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In addition, the food database is based on FNDDS from 2011-2012 (FNDDS 6.0) and FPED from 2011-2012 and will not be updated with future data releases.", + "tags": [ + "Dietary Guidelines", + "Health", + "Nutrition" + ], + "contact": { + "email": "Jackie.Haven@cnpp.usda.gov" + }, + "status": "Archival", + "vcs": "zip", + "downloadURL": "https://inventory.data.gov/dataset/97f9a5cf-61c4-406b-8170-5a6422b68654/resource/c04948d7-4af3-42c7-ae4b-5b805ea7571e/download/supertrackersource2.zip", + "languages": [], + "repositoryURL": "https://inventory.data.gov/dataset/97f9a5cf-61c4-406b-8170-5a6422b68654/resource/c04948d7-4af3-42c7-ae4b-5b805ea7571e/download/supertrackersource2.zip", + "homepageURL": "https://catalog.data.gov/dataset/supertracker-source-code-and-foods-database", + "permissions": { + "licenses": [ + { + "URL": "http://opendefinition.org/licenses/cc-zero/", + "name": "CC0" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "created": "2018-10-12", + "lastModified": "2019-05-02", + "metadataLastUpdated": "2019-09-22" + } + }, + { + "organization": "ARS", + "name": "Fast and robust curve skeletonization for real-world elongated objects", + "description": "A curve skeletonization method for elongated objects that may be noisy.", + "tags": [ + "curve skeletonization" + ], + "contact": { + "email": "amy.tabb@ars.usda.gov" + }, + "status": "Production", + "vcs": "git", + "downloadURL": "https://github.com/amy-tabb/CurveSkel-Tabb-Medeiros.git", + "languages": [ + "C++" + ], + "repositoryURL": "https://github.com/amy-tabb/CurveSkel-Tabb-Medeiros", + "homepageURL": "https://github.com/amy-tabb/CurveSkel-Tabb-Medeiros", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/amy-tabb/CurveSkel-Tabb-Medeiros/blob/master/LICENSE", + "name": "GPL 3.0" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "created": "2017-10-11", + "lastModified": "2018-08-16", + "metadataLastUpdated": "2019-09-22" + } + }, + { + "organization": "ARS", + "name": "Automated Water Supply Model (AWSM)", + "description": "Automated Water Supply Model (AWSM) was developed at the USDA Agricultural Research Service (ARS) in Boise, ID. AWSM was designed to streamline the work flow used by the ARS to forecast the water supply of multiple water basins. AWSM standardizes the steps needed to distribute weather station data with SMRF, run an energy and mass balance with iSnobal, and process the results, while maintaining the flexibility of each program.", + "tags": [ + "Northwest Watershed Research Center", + "watershed", + "hydrology", + "awsm", + "forecast", + "modeling", + "water", + "snow", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/awsm.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/awsm", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/awsm/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2017-01-18", + "lastModified": "2020-03-24", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Spatial Modeling for Resources Framework (SMRF)", + "description": "Spatial Modeling for Resources Framework (SMRF) was developed by Dr. Scott Havens at the USDA Agricultural Research Service (ARS) in Boise, ID. SMRF was designed to increase the flexibility of taking measured weather data and distributing the point measurements across a watershed. SMRF was developed to be used as an operational or research framework, where ease of use, efficiency, and ability to run in near real time are high priorities.", + "tags": [ + "Northwest Watershed Research Center", + "smrf", + "watershed", + "hydrology", + "modeling", + "interpolation", + "water", + "snow", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python", + "c", + "fortran" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/smrf.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/smrf", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/smrf/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2015-12-28", + "lastModified": "2020-04-30", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Weather Database", + "description": "The Weather Database project creates a MySQL database to ingest and manage weather station data from multiple sources. Included in the repository are the schema model and everything needed to generate a weather station database. The wxdb package is able to interact with the database and grab metadata and station data from multiple sources. ", + "tags": [ + "Northwest Watershed Research Center", + "weather-database", + "database", + "docker", + "python", + "snow", + "modeling", + "mesowest" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python", + "PLSQL", + "PLpgSQL" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/weather_database.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/weather_database", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/weather_database/blob/master/LICENSE", + "name": "GPL3.0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2015-12-29", + "lastModified": "2019-06-04", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Weather forecast retrieval", + "description": "Weather forecast retrieval gathers relevant gridded weather forecasts to ingest into physically based models for water supply forecasts", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python", + "docker" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/weather_forecast_retrieval.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/weather_forecast_retrieval", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/weather_forecast_retrieval/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2017-11-15", + "lastModified": "2020-03-27", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Python Snobal", + "description": "Python implementation of the Snobal model applied at either a point or over and image (iSnobal). This package conatains the C libraries of Snobal in a python wrapper for more flexibility and ease of interaction.", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "c++", + "c", + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/pysnobal.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/pysnobal", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/pysnobal/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2016-01-09", + "lastModified": "2020-05-01", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Snow and water model analysis and visualization (snowav)", + "description": "Snow and water model analysis and visualization (snowav) processes the spatial inputs from smrf and spatial outputs from awsm into summary database values, and generates figures and reports for dissemination.", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "snow", + "water", + "model", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/snowav.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/snowav", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/snowav/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2017-12-13", + "lastModified": "2020-04-28", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Image Processing Workbench (IPW)", + "description": "Image Processing Workbench (IPW) is a collection of utilities to process digital images. IPW contains the energy-balance snowmelt models Snobal and iSnobal.", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "snow", + "water", + "model", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "C", + "Roff", + "Fortran" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/ipw.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/ipw", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/snowav/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2015-03-05", + "lastModified": "2020-03-22", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "inicheck", + "description": "inicheck is an advanced configuration file checker/manager enabling developers high end control over their users configuration files. inicheck is specifcially aimed at files that adhere to the .ini format.", + "tags": [ + "Northwest Watershed Research Center", + "ini file" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/inicheck.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/inicheck", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/inicheck/blob/master/LICENSE", + "name": "GPL 3.0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2018-01-05", + "lastModified": "2020-02-26", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Basin setup tool", + "description": "The basin setup tool is a python script designed to create the required inputs for running SMRF and AWSM simulations. The tool outputs a single netcdf file containing the necessary spatial information for a water basin This includes basin mask, DEM, veg type and height (from Landfire), veg tau, and veg K.", + "tags": [ + "Northwest Watershed Research Center" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/basin_setup.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/basin_setup", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/inicheck/blob/master/LICENSE", + "name": "GPL 3.0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2017-12-05", + "lastModified": "2020-04-29", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "swiflow", + "description": "A python package for modeling streamflow from modeled surface water input.", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "snow", + "water", + "model", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/swiflow.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/swiflow", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/swiflow/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2019-05-23", + "lastModified": "2020-04-02", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "topocalc", + "description": "The topocalc package is a collection of functions to calculate various metrics on a digital elevation model (DEM). The calculations follow the equations laid out in Dozier and Frew, 1990 for the gradient, horizon and sky view factor. ", + "tags": [ + "Northwest Watershed Research Center", + "model", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "Jupyter Notebook" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/topocalc.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/topocalc", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/topocalc/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2020-04-07", + "lastModified": "2020-04-23", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Goldmeister", + "description": "Goldmeister is a Python package designed to manage/examine changes to a gold file.", + "tags": [ + "Northwest Watershed Research Center", + "dataset" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/goldmeister.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/goldmeister", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/goldmeister/blob/master/LICENSE", + "name": "MIT" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2020-04-08", + "lastModified": "2020-04-22", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "spatialnc", + "description": "Python library for managing spatial data in netcdfs with a lot of functionality specifically for AWSM/SMRF.", + "tags": [ + "Northwest Watershed Research Center", + "spatial" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/spatialnc.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/spatialnc", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/spatialnc/blob/master/LICENSE", + "name": "MIT" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2019-01-31", + "lastModified": "2020-04-16", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Tablizer", + "description": "Tablizer makes simple statistical summaries of DataFrames and arrays, and places them on SQL or sqlite database.", + "tags": [ + "Northwest Watershed Research Center", + "statistical summaries" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/tablizer.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/tablizer", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/tablizer/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2019-08-20", + "lastModified": "2019-10-08", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Katana", + "description": "A project for bringing WindNinja Data into the AWSM system.", + "tags": [ + "Northwest Watershed Research Center", + "WindNinja" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/katana.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/katana", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/katana/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2018-08-27", + "lastModified": "2020-04-07", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "AWSM Run Manager", + "description": "AWSM run manager is designed to facilitate AWSM simulations from the command line with more complicated simulations involving multiple Docker images. Currently, awsm_run_manager only supports runs that use atmospheric model's as inputs, like the High Resolution Rapid Refresh, because the Wind is downscaled using Katana.", + "tags": [ + "Northwest Watershed Research Center", + "Docker", + "Katana" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/awsm_run_manager.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/awsm_run_manager", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/awsm_run_manager/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2020-01-02", + "lastModified": "2020-02-06", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Repeat Array Quality Check (RAQC)", + "description": "Utility to 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The goal of Amesos is to make AX=S as easy as it sounds, at least for direct methods. Amesos provides interfaces to a number of third party sparse direct solvers, including SuperLU, SuperLU MPI, DSCPACK, UMFPACK and KLU. Amesos provides a common object oriented interface to the best sparse direct solvers in the world. A sparse direct solver solves for x in Ax = b. where A is a matrix and x and b are vectors (or multi-vectors). A sparse direct solver flrst factors A into trinagular matrices L and U such that A = LU via gaussian elimination and then solves LU x = b. Switching amongst solvers in Amesos roquires a change to a single parameter. Yet, no solver needs to be linked it, unless it is used. All conversions between the matrices provided by the user and the format required by the underlying solver is performed by Amesos. As new sparse direct solvers are created, they will be incorporated into Amesos, allowing the user to simpty link with the new solver, change a single parameter in the calling sequence, and use the new solver. Amesos allows users to specify whether the matrix has changed. Amesos can be used anywhere that any sparse direct solver is needed.", + "laborHours": 8344830.4, + "languages": [], + "name": "Amesos Solver Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The MRSH project is a collection of the following programs: MRSH, MRCP, MRLOGIN, MRSHD, MRLOGIND. These programs are modifications of the programs RSH, RCP, RLOGIN, RSHD, and RLOGIND. They have been modified to provide authentication via munge, an intra-cluster authentication service. Henceforth, \"MRSH\" implies the collective set of programs MRSH, MRCP, MRLOGIN, MRSHD, and MRLOGIND. Similarly RSH will refer to its collective set of programs.", + "laborHours": 24213.6, + "name": "MRSH Version V2.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/mrsh", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Lustre Administrative Tools (LAT) is a set of programs and utilities designed to facilitate management of the Lustre File System by System Administrators.", + "laborHours": 5639.2, + "name": "Lustre Administrative Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cea-hpc/shine", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "WHATSUP determines which nodes in a cluster are up and which nodes are down.", + "laborHours": 58793.6, + "name": "WHATSUP Version1.3", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/whatsup", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Nux is an open-source Java XML toolset geared towards embed:,ed use in high-throughput XML messaging middleware such as large- scale Peer-to-Peer infrastructures, message queues, publish- subscribe and matchmaking systems for Blogs/newsfeeds, text chat, data acquisition and distribution systems, application level routers firewalls, classifiers, etc. It is not an XML database, and does not attempt to be one. Features include: archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Seamless W3C XQuery and XPath support for XOM. archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Full-text search (fuzzy similarity queries) for on-the-fly matchmaking in realtime streaming applications combining structured and unstructured queries. archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Efficient and flexible pools and factories for documents, XQueries, XSL Transforms, as well as document Builders that validate against various schema languages, including W3C XML Schemas, DTDs, RELAX NG, Schematron, etc. archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Optional serialization and deserialization of XOM XML documents to and from an efficient and compact custom binary XML data format (bnux format), without loss or change of any information.", + "laborHours": 997621.6, + "name": "Nux, V.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/er1c/nux/blob/master/doc/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/er1c/nux", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "An MPI-based test for benchmarking parallel I/O beowulf-style clusters.", + "laborHours": 2416.8, + "name": "MIB, the MPI I/O Benchmark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mib", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-12" + }, + "description": "The Galeri package defines a collection of serial and distributed linear algebra objects to be used for software verification and validation. Galeri is used in several of the examples of the Amesos, IFPACK and ML packages, and in the Trilinos tutorial, Didasko. Galeri can be used for the generation of linear system with known propeties and data distribution for convergence analysis of interative solvers of Krylov type and domain decomposition and multigrid preconditioners.", + "laborHours": 8344830.4, + "languages": [], + "name": "Galeri Matrix Generation Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Moertel supplies capabilities for nonconforming mesh tying and contact formulations in 2 and 3 dimensions using Mortar methods. Motar methods are a type of Lagrange Multiplier constraints that can be used in contact formulations and in non-conforming or conforming mesh typing as well as in domain decomposition techniques. Suitable conditions at interfaces are formulated as weak continuity conditions in dual variables introducing Lagrange multiplers on the interface. By an appropriate choice of the function space of the Lagrange multipliers on an interface it is possible to locally condense Lagrange multipliers such that a sparse and definite system of equations can be formed which is equalivalent to the saddle point system resulting from the Lagrange multiplier formulation.", + "laborHours": 16020.8, + "languages": [ + "C++" + ], + "name": "Moertel Fe Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Moertel", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "WebTrilinos is a scientific portal, a web-based environment to use several Trilinos packages through the web. If you are a teaching sparse linear algebra, you can use WebTrilinos to present code snippets and simple scripts, and let the students execute them from their browsers. If you want to test linear algebra solvers, you can use the MatrixPortal module, and you just have to select problems and options, then plot the results in nice graphs.", + "laborHours": 2705.6, + "languages": [], + "name": "Trilinos Web Interface Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/WebTrilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Stratimikos is a small package of C++ wrappers for linear solver and preconditioning functionality exposed through Thyra interfaces. This package makes is possible to aggregate all of the general linear solver capability from the packages Amesos, AztecOO, Belos, lfpack, ML and others into a simple to use, parameter-list driven, interface to linear solvers. This initial version of Stratimikos contains just one utility class for building linear solvrs and preconditioners out of Epetra-based linear operators.", + "laborHours": 8344830.4, + "name": "Stratimikos Wrapper Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Aprepro is an algebraic preprocessor that reads a file containing both general text and algebraic, string, or conditional expressions. It interprets the expressions and outputs them to the output file along with the general text. Aprepro contains several mathematical functions, string functions, and flow control constructs. In addition, functions are included that, with some additional files, implement a units conversion system and a material database lookup system.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "Aprepro - Algebraic Preprocessor", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MRNet is a software tree-based overlay network developed at the University of Wisconsin, Madison that provides a scalable communication mechanism for parallel tools. MRNet, uses a tree topology of networked processes between a user tool and distributed tool daemons. This tree topology allows scalable multicast communication from the tool to the daemons. The internal nodes of the tree can be used to distribute computation and alalysis on data sent from the tool daemons to the tool. This release covers minor implementation to port this software to the BlueGene/L architecuture and for use with a new implementation of the Dynamic Probe Class Library.", + "laborHours": 68460.8, + "name": "Multicast Reduction Network Source Code", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dyninst/mrnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "Tramonto is a code for performing molecular theory calculations using a matrix-based Newton's method approach for 1D, 2D, and 3D geometries. More specifically the code solves the integral equations of a particular class of liquid state theory namely density functional theories (DFT) of inhomogeneous fluids in order to predict the structure and thermodynamic properties of fluids near surfaces, in porous media, or near macromolecules. It can also be used to study self-assembling systems such as lamellae forming diblock copolymers or lipid bilayers. The types of fluids currently treated by the code include atomistic fluids (hard spheres, Lennard-Jones, ions, etc), freely-jointed polymers, and small molecules with bond constraints. The system of equations solved by this code are integral equations of finite range. They lead to sparse matrices for large physical systems, but rather dense matrices when the physical systems are small. The systems of equations are solved using a real space matrix based Newton's method. Standard freely available parallel iterative solvers many be used to solve the problem (see Aztecoo from Sandia's Trilinos project). Alternatively, specialized Schur complement based solvers developed for more efficient solution of these semi-dense matrices may be used.", + "laborHours": 46876.8, + "languages": [ + "C++", + "C", + "CMake", + "Python" + ], + "name": "Tramonto", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tramonto", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Aristos is a Trilinos package for nonlinear continuous optimization, based on full-space sequential quadratic programming (SQP) methods. Aristos is specifically designed for the solution of large-scale constrained optimization problems in which the linearized constraint equations require iterative (i.e. inexact) linear solver techniques. Aristos' unique feature is an efficient handling of inexactness in linear system solves. Aristos currently supports the solution of equality-constrained convex and nonconvex optimization problems. It has been used successfully in the area of PDE-constrained optimization, for the solution of nonlinear optimal control, optimal design, and inverse problems.", + "laborHours": 8344830.4, + "name": "Aristos Optimization Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Sacado is an automatic differentiation package for C++ codes using operator overloading and C++ templating. Sacado provide forward, reverse, and Taylor polynomial automatic differentiation classes and utilities for incorporating these classes into C++ codes. Users can compute derivatives of computations arising in engineering and scientific applications, including nonlinear equation solving, time integration, sensitivity analysis, stability analysis, optimization and uncertainity quantification.", + "laborHours": 8344830.4, + "name": "Automatic Differentiation Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "HPCCG is a simple PDE application and preconditioned conjugate gradient solver that solves a linear system on a beam-shaped domain. Although it does not address many performance issues present in real engineering applications, such as load imbalance and preconditioner scalability, it can serve as a first \"sanity test\" of new processor design choices, inter-connect network design choices and the scalability of a new computer system. Because it is self-contained, easy to compile and easily scaled to 100s or 1000s of porcessors, it can be an attractive study code for computer system designers.", + "laborHours": 775.2, + "languages": [ + "C++", + "Makefile" + ], + "name": "HPCCG Solver Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HPCCG", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MRNet is a software tree-based overlay network developed at the University of Wisconsin, Madison that provides a scalable communication mechanism for parallel tools. MRNet uses a tree topology of networked processes between a user tool and distributed tool daemons. This tree topology allows scalable multicast communication from the tool to the daemons. The internal nodes of the tree can be used to distribute computation and analysis on data sent from the tool daemons to the tool. This release covers modifications that we have made to the Wisconsin implementation to port this software to the BlueGene/L architecture. It also covers some additional files that were created for this port.", + "laborHours": 68460.8, + "name": "BlueGene/L Specific Modification to MRNet: Multicast/Reduction Network", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dyninst/mrnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GraphLib is a support library used by other tools to create, manipulate, store, and export graphs. It provides a simple interface to specifS' arbitrary directed and undirected graphs by adding nodes and edges. Each node and edge can be associated with a set of attributes describing size, color, and shape. Once created, graphs can be manipulated using a set of graph analysis algorithms, including merge, prune, and path coloring operations. 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This effort was funded by US Department of Energy's Atmospheric Radiation Measurement program (www.arm.gov). As an alternative for Campbell Scientific's Loggernet software, this is ideal for deploying with rugged field PCs that have limited processing resources and do not require a full-blown GUI module. The software is designed so that it can be extended to implement a new data storage mechanism, a customized post-processing module and/or integrated with web-services for sophisticated monitoring or reporting.", + "laborHours": 2553.6, + "name": "PbCdlComm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sutanay/PbCdlComm/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sutanay/PbCdlComm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "LaunchMON is a tool infrastructure that allows a HPC tool to deploy tool daemons into the right remote nodes. It makes use of a target resource manager (RM)'s Automatic Process Acquisition Interface (APAI) to identify the remote nodes and processes of a parallel program, and also exploits the same RM's efficient MPI job launching capability on co-locating daemons with the job. To support a wide range of HPC tools that are inherently distributed software, LaunchMON provides the tool with distributed application programming interface sets: the front end (FE) API, the back end (BE) API and the middleware (MW) API. They each support a tool's front end, back end daemons and middleware communication daemons, respectively. Using those API sets, the tool can launch and initialize their remote daemons scalably.", + "laborHours": 17449.6, + "name": "LaunchMON: An Infrastructue for Large Scale Tool Daemon Launching", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/launchmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "SUPES is a collection of subprograms that perform frequently used non-numerical services for the engineering applications programmer. The three functional categories of SUPES are: (1) input command parsing, (2) dynamic memory management, and (3) system dependent utilities. The subprograms in categories one and two are written in standard FORTRAN-77, while the subprograms in category three are written provide a standardized FORTRAN interface to several system dependent features.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "SUPESv.4.1.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "4.1.2" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The qthread library provides a software mechanism for programs to execute a large number of run-to-completion threads at low cost. It provides the ability to perform lightweight synchronization on memory locations. Finally, modules within the library (\"futurelib\", \"qloop\", and \"qutil\") provide the optional ability to manage the number of threads created in C and C++ by providing parallel loop constructs.", + "laborHours": 47393.6, + "languages": [ + "C++", + "C", + "HMTL", + "Makefile", + "Assembly", + "M4" + ], + "name": "Qthreads", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/qthreads?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/qthreads", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-03-20" + }, + "description": "MAPVAR-KD is designed to transfer solution results from one finite element mesh to another. MAPVAR-KD draws heavily from the structure and coding of MERLIN II, but it employs a new finite element data base, EXODUS II, and offers enhanced speed and new capabilities not available in MERLIN II. In keeping with the MERLIN II documentation, the computational algorithms used in MAPVAR-KD are described. User instructions are presented. Example problems are included to demonstrate the operation of the code and the effects of various input options. MAPVAR-KD is a modification of MAPVAR in which the search algorithm was replaced by a kd-tree-based search for better performance on large problems.", + "laborHours": 2002235.2, + "languages": [], + "name": "Finite Element Analysis Code - MAPVAR-KD", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gsjaardema/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-03-20" + }, + "description": "CONEX is a code for joining sequentially in time multiple exodusll database files which all represent the same base mesh topology and geometry. It is used to create a single results or restart file from multiple results or restart files which typically arise as the result of multiple restarted analyses. CONEX is used to postprocess the results from a series of finite element analyses. It can join sequentially the data from multiple results databases into a single database which makes it easier to postprocess the results data.", + "laborHours": 2002235.2, + "languages": [], + "name": "Finite Element Analysis Code - CONEX", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gsjaardema/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-15" + }, + "description": "GJOIN is a two- or three-dimensional mesh combination program. GJOIN combines two or more meshes written in the GENESIS mesh database format into a single GENESIS mesh. Selected nodes in the two meshes that are closer than a specified distance can be combined. The geometry of the mesh databases can be modified by scaling, offsetting, revolving, nd mirroring. The combined meshes can be further modified by deleting, renaming, or combining material blocks, sideset identifications, or nodeset identifications.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "GJOIN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Phalanx is a software library to provide flexible dependency management for complex nonlinear partial differential equation operators. It breaks a complex set of equations into a manageable set of fields and evaluation routines. Users can flexibly swap evaluators to change the underlying dependency graph of the fields automatically. By constructing the dependency list, sensitivities can be calculated either analytically or by using embedded automatic differentiation software.", + "laborHours": 8344830.4, + "name": "Phalanx V1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/phalanx/copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "BECCA is a learning and control method based on the function of the human brain. The goal behind its creation is to learn to control robots in unfamiliar environments in a way that is very robust, similar to the way that an infant learns to interact with her environment by trial and error. As of this release, this software contains two simulations of BECCA controlling robots: one is a one degree-of-freedom spinner robot and the other is a 7 degree-of-freedom serial link arm with a terminal gripper. In addition, the software contains code that identifies synonyms in a untagged corpus of ASCII words. This last is a demonstration of BECCA's ability to generate abstract concepts from concrete experience. The BECCA simulation is coded so as to make it extensible to new applications. It is modular, object-oriented code in which the portions of the code that are specific to one simulation are easily separable from those portions that are the constant between implementations. BECCA makes very few assumptions about the robot and environment it is learning, and so is applicable to a wide range of learning and control problems.", + "laborHours": 927.2, + "languages": [ + "Python" + ], + "name": "Brain-Emulating Cognition and Control Architecture (BECCA) V1.0 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/becca", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ParFlow is a parallel, variabley saturated groundwater flow code that is especially suitable for large scale problem. ParFlow simulates the three-dimensional saturated and variably saturated subsurface flow in heterogeneous porous media in three spatial dimensions. ParFlow's developemt and appkication has been on-ging for more than 10 uear. ParFlow has recently been extended to coupled surface-subsurface flow to enabel the simulation of hillslope runoff and channel routing in a truly integrated fashion. ParFlow simulates the three-dimensional varably saturated subsurface flow in strongly heterogeneous porous media in three spatial dimension.", + "laborHours": 138532.8, + "name": "Simulation of water flow in terrestrial systems", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/parflow/parflow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SLURM is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small computer clusters. As a cluster resource manager, SLURM has three key functions. First, it allocates exclusive and/or non exclusive access to resources (compute nodes) to users for some duration of time so they can perform work. Second, it provides a framework for starting, executing, and monitoring work (normally a parallel job) on the set of allciated nodes. Finally, it arbitrates conflicting requests for resouces by managing a queue of pending work.", + "laborHours": 405900.8, + "name": "Simple Linux Utility for Resource Management", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/schedmd/slurm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "The Scalable Checkpoint/Restart (SCR) library provides an interface that codes may use to worite our and read in application-level checkpoints in a scalable fashion. In the current implementation, checkpoint files are cached in local storage (hard disk or RAM disk) on the compute nodes. This technique provides scalable aggregate bandwidth and uses storage resources that are fully dedicated to the job. This approach addresses the two common drawbacks of checkpointing a large-scale application to a shared parallel file system, namely, limited bandwidth and file system contention. In fact, on current platforms, SCR scales linearly with the number of compute nodes. It has been benchmarked as high as 720GB/s on 1094 nodes of Atlas, which is nearly two orders of magnitude faster thanthe parallel file system.", + "laborHours": 24198.4, + "languages": [], + "name": "The Scalable Checkpoint/Restart Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/scr/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/scr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The PMGR_COLLECTIVE library provides an interface that MPI implemenataions may call to initialize ranks in a scalable way. It was developed to reduce the startup time MPI appkications, however, other tools such as debugger infrastructures have also found use cases for it. When first developed, it reduced the startup time from 15 minutes to 10 seconds on as 8192-node cluster.", + "laborHours": 3283.2, + "name": "The Process Manager Collective Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/pmgr_collective/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pmgr_collective", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A power system simulation that runs on all major platforms, provides open access to all functionality, and supports extended modeling of non-traditional components of the electric power system, such as buildings, distributed resources, and markets. GridLAB-D solution engine can determine the simultaneous state of millions of independent devices, each of which is described by multiple differential equations solved only locally for both state and time. The advantages of this algorithm over traditional finite difference-based simulators are: (1) it is much more accurate; (2) it can handle widely disparate time scales, ranging from sub-seconds to many years; and 3) it is easy to integrate with new modules and third-party systems. The advantage over traditional differential-based solvers is that it is not necessary to integrate all the device's behaviors into a single set of equations that must be solved.", + "laborHours": 252776.0, + "name": "GridLab-D version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/gridlab-d/gridlab-d/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gridlab-d/gridlab-d", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A package of classes for constructing and using distributed sparse and dense matries, vectors and graphs. Templated o the scalar and ordinal types so that any valid floating-point type, as well as any valid integer type can be used with these classes. Other non-standard types, such as 3-by-3 matrices for the scalar type and mod-based integers for ordinal can also be used.", + "laborHours": 8344830.4, + "name": "Tpetra Next-Generation Templated Petra V1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/tpetra/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "ex1ex2v2 is a translator program which will convert a database in exodus1 format to exodusII format. The exodus 1 format is a defined series of Fortran unformatted writes/reads; the exodusII format is defined by the ExodusII API.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "ex1ex2v2 Version 2.10", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.10" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Nem_spread reads it's input command file (default name nem_spread.inp), takes the named ExodusII geometry definition and spreads out the geometry (and optionally results) contained in that file out to a parallel disk system. The decomposition is taken from a scalar Nemesis load balance file generated by the companion utility nem_slice.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "nem_spread Ver. 5.10", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "5.10" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Nem_slice reads in a finite element model description of the geometry of a problem from an ExodusII file and generates either a nodal or elemental graph of the problem. It then calls Chaco to load balance the graph and then outputs a NemesisI load-balance file.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "nem_slice ver. 3.34", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.34" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "BLOT is a graphic program for post-processing finite element analyses output in the EXODUS II database format. It is command driven with free-format input and can drive graphics devices supported by the Sandia Virtual Device Interface. BLOT produces mesh plots of the analysis output variables including deformed mesh plots, line contours, filled (painted) contours, vector plots of two/three variables (velocity vectors), and symbol plots of scalar variables (discrete cracks). Features include pathlines of analysis variables drawn on the mesh, element selection by material, element birth and death, multiple views combining several displays on each plot, symmetry mirroring, and node and element numbering. X-Y plots of the analysis variables include time vs. variable plots or variable vs. variable plots, and distance vs. variable plots at selected time steps where distance is the accumulated distance between pairs of nodes or element centers. BLOT is written in as portable a form as possible. Fortran code is written in ANSI Standard FORTRAN-77. Machine-specific routines are limited in number and are grouped together to minimize the time required to adapt them to a new system. SEACAS codes have been ported to several Unix systems", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "BLOT Ver. 1.65", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.65" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "SVDI is the Sandia Virtual Device Interface library which is an internal library used by SEAMS codes (blot and fastq) to provide graphics to multiple device types; primarily X11R6 clients.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "SVDI Ver. 1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The software is a set of technologies developed by the SciDAC Institute for Ultrascale Visualization in order to address the visualization needs for petascale computing and beyond. These technologies include improved I/O performance, simulation co-processing, advanced rendering capabilities, and specialized visualization techniques developed for SciDAC applications.", + "laborHours": 82095.2, + "languages": [ + "C++", + "C" + ], + "name": "Ultrascale visualization capabilities for the ParaView/VTK framework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/paraview/catalyst", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Simple parallel MD code that serves as a microapplication in the Mantevo suite. Study of computer system design and implementation, benchmarking of new and existing computer systems.", + "laborHours": 11096.0, + "languages": [ + "C++", + "Shell", + "C", + "Makefile" + ], + "name": "miniMD v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniMD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GROPE is a program that examines the input to a finite element analysis (which is in the GENESIS database format) or the output from an analysis (in the EXODUS database format). GROPE allows the user to examine any value in the database. The display can be directed to the user's terminal or to a print file.", + "laborHours": 3063438.4, + "languages": [ + "CSS", + "HTML", + "TeX", + "Makefile", + "JavaScript", + "PostScript" + ], + "name": "Grope Ver. 1.38", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas-docs", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.38" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pamgen creates, in parallel, hexahedral or quadrilateral (in 2D) finite element meshes of cubes, cylinders, and portions of cylinders. For some analysis applications it can obviate the normally serial analysis preparation steps of mesh generation and decomposition. Bypassing these serial steps allows construction of large element count (over a billion) meshes. When linked to an application as a library, it allows each process of a parallel simulation to generate its own finite element domain representation at execution time. As a stand-alone application it can produce the representation of the mesh for processor n of k possible processors. The Pamgen library and application are serial as the mesh generation proceeds without reliance on inter-processor communication.", + "laborHours": 8344830.4, + "name": "Pamgen", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-08-23" + }, + "description": "The TAO project focuses on the development of software for large scale optimization problems. TAO uses an object-oriented design to create a flexible toolkit with strong emphasis on the reuse of external tools where appropriate. Our design enables bi-directional connection to lower level linear algebra support (for example, parallel sparse matrix data structures) as well as higher level application frameworks. The Toolkist for Advanced Optimization (TAO) is aimed at teh solution of large-scale optimization problems on high-performance architectures. Our main goals are portability, performance, scalable parallelism, and an interface independent of the architecture. TAO is suitable for both single-processor and massively-parallel architectures. The current version of TAO has algorithms for unconstrained and bound-constrained optimization.", + "laborHours": 738613.6, + "languages": [], + "name": "TOOLKIT FOR ADVANCED OPTIMIZATION", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/petsc/petsc", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Libra is a tool for scalable analysis of load balance data from all processes in a parallel application. Libra contains an instrumentation module that collects model data from parallel applications and a parallel compression mechanism that uses distributed wavelet transforms to gather load balance model data in a scalable fashion. Data is output to files, and these files can be viewed in a GUI tool by Libra users. The GUI tool associates particular load balance data with regions for code, emabling users to view the load balance properties of distributed \"slices\" of their application code.", + "laborHours": 36723.2, + "name": "Libra: Scalable Load Balance Analysis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/tgamblin/libra/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tgamblin/libra", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The code to be released is a new addition to the LAMMPS molecular dynamics code. LAMMPS is developed and maintained by Sandia, is publicly available, and is used widely by both natioanl laboratories and academics. The new addition to be released enables LAMMPS to perform molecular dynamics simulations of shock waves using the Multi-scale Shock Simulation Technique (MSST) which we have developed and has been previously published. This technique enables molecular dynamics simulations of shock waves in materials for orders of magnitude longer timescales than the direct, commonly employed approach.", + "laborHours": 1281025.6, + "name": "Multi-scale Shock Technique", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lammps/lammps", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A Trilinos package for applying stochastic Galerkin uncertainty quantification methods to large-scale C++ application codes, primarily stochastic partial differential equations. Stokhos is intended for use in estimating uncertainties for general scientific computations and is based on published algorithms. It provides no capability for implementing those computations itself. Estimating uncertainties and errors from solution algorithms or simulations, primarily simulations of partial differential equations, arising from uncertainties or errors in solution algorithm or simulation input data, including statistical moments, probabilities, and coefficients of variation.", + "laborHours": 8344830.4, + "name": "Stokhos v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The SST provides a parallel framework to perform system simulation of computer architectures to determine their performance and power consumption. Additionally, the SST contains basic models of a computer processor, and interconnect and can connect to an external memory simulator (DRAMSim II). The SST framework provides a simple interface by which other computer simulation models can be combined under a common parallel discrete event-based simulation environment. This allows design exploration of future architectures, analysis of how current computer programs will function on future architectures. The SST provides a parallel discrete event simulation framework, including partitioning and object distribution over MPI. It also provides a mechanism by which components can report their power consumption for analysis.", + "laborHours": 25384.0, + "name": "Structural Simluation Toolkit (SST) V 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sstsimulator/sst-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "Poblano is a Matlab toolbox of large-scale algorithms for nonlinear optimization. The algorithms in Poblano require only first-order derivative information (e.g., gradients for scalar-valued objective functions), and therefore can scale to very large problems [6].Poblano is a set of general purpose methods for solving unconstrained nonlinear optimization methods. It has been applied to standard test problems covering a range of application areas. The driving application for Poblano development has been tensor decompositions in data analysis applications (bibliometric analysis, social network analysis, chemometrics, etc.) [1].", + "laborHours": 1474.4, + "languages": [ + "MATLAB", + "M" + ], + "name": "Poblano v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/poblano_toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A package for computing and applying algebraic preconditioners in the context of preconditioned iterative methods. It is related to the existing Ifpack package in Trilinos but provides support for template scalar and ordinal types and explicitly relies on Tpetra and Kokkos instead of Epetra. Algebraic preconditioners are used by iterative solvers as solution method in engineering and scientific applications, including nonlinear equation solving, time integration, sensitivity analysis, stability analysis, optimization, and uncertainty quantification.", + "laborHours": 8344830.4, + "name": "Tifpack v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Climate Data Analysis Tools (CDAT) is a software infrastructure that uses an object-oriented scripting language to link together separate software subsystems and packages thus forming an integrated environment for solving model diagnosis problems, The power of the system comes from Python and its ability to seamlissly interconnect software. Python provides a general purpose and full-featured scripting language with a variety of user interfaces including command-line interaction, stand-alone scripts (applications) and fraphical user interfaces (GUI). The CDAT subsystems, implemented as modules, provide access to and management of gridded data (Climate Data Management Systems or CDMS); large-array numerical operations (Numerical Python); and visualization (Visualization and Control System or VCS).", + "laborHours": 78644.8, + "name": "Climate Data Analysis Tools", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/UV-CDAT/uvcdat/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/UV-CDAT/uvcdat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "PyUtilib is a collection of Python utilities that are used by Python packages developed at Sandia National Laboratories, including the Coopr and FAST Python packages. PyUtilib includes facilities for managing factories, subprocess management, interfacing with Excel, and applying numerical techniques.", + "laborHours": 14972.0, + "languages": [ + "Shell", + "Python" + ], + "name": "PyUtilib: A Pythos Utility Library v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyutilib", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SNL Coopr Forum is a set of Python routines that provide extensions to the Coopr optimization software. This software augments the open-source Coopr project to provide a more comprehensive capability for formulating and solving optimization applications.Optimization is a common analysis tool used in engineering design and scientific discovery. The SNL Coopr Forum software augments the Coopr Forum open source project to provide extensions of the Coopr optimization framework. Specifically, Coopr Forum provides plugin tools that allow Coopr to apply different optimization solvers, manage optimization solvers in a distributed manner, and to process input and output files. Thus, Coopr Forum is comprised of a variety of distinct software components, each of which provides a different capability that can be used within Coopr.", + "laborHours": 314837.6, + "name": "Coopr Forum v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pyomo/pyomo", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "Implements previously developed methodology to calculate total disutility to an organization caused by impacts imposed upon the physical system in question (electric power transmission system, water system, etc).Critical infrastructure utility personnel will use this as a planning tool to determine where system weaknesses are and where improvements should be made such that the consequence of some impact is no longer higher than acceptable.", + "laborHours": 5745.6, + "languages": [ + "Java", + "CSS" + ], + "name": "Critical Infrastructure Consequence Modeler v 0.5.0 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cicm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.5.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "diod is an I/O forwarding daemon used to improve scalability of file systems on large Linux clusters.", + "laborHours": 28576.0, + "name": "diod - distributed I/O daemon", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/diod", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The SIERRA Toolkit is a collection of libraries to facilitate the development of parallel engineering analysis applications. These libraries supply basic core services that an engineering analysis application may need such as a parallel distributed and dynamic mesh database (for unstructured meshes), mechanics algorithm support (parallel infrastructure only), interfaces to parallel solvers, parallel mesh and data I/O, and various utilities (timers, diagnostic tools, etc.).The toolkit is intended to reduce the effort required to develop an engineering analysis application by removing the need to develop core capabilities that most every application would require.", + "laborHours": 8344830.4, + "name": "SIERRA Toolkit v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/stk/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-09" + }, + "description": "The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes (computational models) and iterative analysis methods. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and analysis of computational models on high performance computers.A user provides a set of DAKOTA commands in an input file and launches DAKOTA. DAKOTA invokes instances of the computational models, collects their results, and performs systems analyses. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, polynomial chaos, stochastic collocation, and epistemic methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as hybrid optimization, surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. Services for parallel computing, simulation interfacing, approximation modeling, fault tolerance, restart, and graphics are also included.", + "homepageURL": "https://dakota.sandia.gov/sites/default/files/docs/6.0/html-dev/files.html", + "laborHours": 3812676.8, + "languages": [], + "name": "DAKOTA Design Analysis Kit for Optimization and Terascale", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/sites/default/files/docs/6.0/html-dev/files.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "ForTrilinos stands for interfaces to Trilinos. It effectively replaces common practices for interfacing Fortran codes with Trilinos C++ packages. Common practices include writing user-specific drivers and exploiting the name-mangling schemes of specific compilers. ForTrilinos improves portability and robustness by exploiting the C interoperability constructs of Fortran 2003. These constructs facilitate binding Fortran interface bodies to their equivalent C function prototypes, providing for name resolution independent of the compiler™s underlying mangling scheme and guaranteeing compatible type bit representations. Furthermore, ForTrilinos maintains the overall design philosophy and architecture of Trilinos by creating a derived type structure in Fortran similar to the class hierarchy in the underlying C++.ForTrilinos can be applied wherever the underlying Trilinos packages can be applied.", + "laborHours": 165087.2, + "languages": [ + "Dockerfile", + "C++", + "Shell", + "SWIG", + "CMake", + "Fortran", + "Python" + ], + "name": "ForTrilinos v 10.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/ForTrilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "10.1" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The BOUT++ is a C++ framework for developing plasma fluid simulation codes, and has been developed by the University of York/UK and the LLNL Fusion Energy Program from the original 3D boundary turbulence 2-fluid edge simulation code BOUT. The aim of BOUT++ is to automate the common tasks needed for simulation codes, and to separate the complicated details such as differential geometry, parallel communication, and file input/output from the user-specified equations to be solved. The BOUT++ consists of BOUT++ library and physics modules. BOUT++ modules contains the coding for the specific set of physics equations and boundary conditions for particular physics problems using defined functions in BOUT++ library to perform standard differential operators.", + "laborHours": 77748.0, + "name": "BOUT++", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/boutproject/BOUT-2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GlobiPack contains a small collection of optimization globalization algorithms. These algorithms are used by optimization and various nonlinear equation solver algorithms.Used as the line-search procedure with Newton and Quasi-Newton optimization and nonlinear equation solver methods. These are standard published 1-D line search algorithms such as are described in the book Nocedal and Wright Numerical Optimization: 2nd edition, 2006. One set of algorithms were copied and refactored from the existing open-source Trilinos package MOOCHO where the linear search code is used to globalize SQP methods. This software is generic to any mathematical optimization problem where smooth derivatives exist. There is no specific connection or mention whatsoever to any specific application, period. You cannot find more general mathematical software.", + "laborHours": 8344830.4, + "name": "GlobiPack v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/globipack/copyright_header.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Used to solve basic unconstrained optimization problems that can produce smooth accurate gradients. These are standard published unconstrained optimization such as are described in the book Nocedal and Wright Numerical Optimization: 2nd edition, 2006. This software is generic to any mathematical optimization problem where smooth derivatives exist. There is no specific connection or mention whatsoever to any specific application, period. You cannot find more general mathematical software.OptiPack contains some simple optimization algorithms built on Thyra. Currently, only a few different nonlinear conjugate gradient methods are implemented.", + "laborHours": 8344830.4, + "name": "Optipack", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/optipack/copyright_header.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CTrilinos provides a C language interface to a subset of Trilinos. The interface hides the object-oriented nature of Trilinos by allowing these objects to be acted upon using a set of three integers that uniquely identify the object. No pointers to the underlying objects are made available for direct manipulation, protecting against segmentation faults. CTrilinos serves as a base layer over which the ForTrilinos linking layer operates, facilitating the use Trilinos from object-oriented Fortran.CTrilinos can be applied wherever the supported underlying Trilinos packages can be applied.", + "laborHours": 18164.0, + "name": "CTrilinos v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/CTrilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Geryon is intended to be a simple library for managing the CUDA Runtime, CUDA Driver, and OpenCL APIs with a consistent interface archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Change from one API to another by simply changing the namespace archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Use multiple APIs in the same code archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Lightweight (only include files no build required) archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Manage device query and selection archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple vector and matrix containers archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple routines for data copy and type casting archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple routines for data I/O archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple classes for managing device timing archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple classes for managing kernel compilation and execution The primary application is to facilitate writing a single code that can be compiled using the CUDA Runtime API, the CUDA Driver API, or OpenCL.", + "laborHours": 7569.6, + "languages": [ + "C++", + "C" + ], + "name": "geryon v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/geryon?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/geryon", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "SNL cxxtest is a set of Python routines that support software testing for C++ codes. This software augments the open-source cxxtest project to provide a more comprehensive capability for software testing.", + "laborHours": 11552.0, + "languages": [ + "Smarty", + "C++", + "Shell", + "C", + "CMake", + "Python" + ], + "name": "SNL cxxtest v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cxxtest", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Memory size has long limited large-scale applications on high-performance computing (HPC) systems. Increasing core counts per chip and power density constraints, which limit the number of DIMMs per node, have exacerbated this problem. Mechanisms to manage memory usage - preferably transparently - more efficiently could increase effective DRAM capacity and, thus, the benefit of multicore similarity. These data regions occupy multiple physical locations within a multicore node and thus offer a potential savings in memory capacity. These data, primarily residing in heap, are quite dynamic, which makes them difficult to manage statically. SBLLmalloc is a memory allocation library that automatically identifies the replicated memory blocks and merges them into a single copy. SBLLmalloc does not require application or OS changes since we implement it as a user-level library that can be linked at runtime. SBLLmalloc provides the capability to run larger problems using the same hardware configuration in multicore nodes. SBLLmalloc has been implemented for Linux clusters.", + "laborHours": 4681.6, + "name": "SBLLmalloc V1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SBLLmalloc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Muster is a framework for scalable cluster analysis. It includes implementations of classic K-Medoids partitioning algorithms, as well as infrastructure for making these algorithms run scalably on very large systems. In particular, Muster contains algorithms such as CAPEK (described in reference 1) that are capable of clustering highly distributed data sets in-place on a hundred thousand or more processes.", + "laborHours": 2052.0, + "name": "Muster: Massively Scalable Clustering", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/muster/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/muster", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SAMRAI is an object-oriented support library for structured adaptice mesh refinement (SAMR) simulation of computational science problems, modeled by systems of partial differential equations (PDEs). SAMRAI is developed and maintained in the Center for Applied Scientific Computing (CASC) under ASCI ITS and PSE support. SAMRAI is used in a variety of application research efforts at LLNL and in academia. These applications are developed in collaboration with SAMRAI development team members.", + "laborHours": 279938.4, + "name": "Structured Adaptive Mesh Refinement Application Infrastructure", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SAMRAI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-01-22" + }, + "description": "GLVis is an OpenGL tool for visualization of finite element meshes and functions. When started without any options, GLVis starts a server, which waits for a socket connections and visualizes any recieved data. This way the results of simulations on a remote (parallel) machine can be visualized on the lical user desktop. GLVis can also be used to visualize a mesh with or without a finite element function (solution). It can run a batch sequence of commands (GLVis scripts), or display previously saved socket streams. For more information, see the project website: http://glvis.org/.", + "laborHours": 17343.2, + "languages": [], + "name": "GLVis: OpenGL Finite Element Visualization Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/glvis/glvis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Teko is a C++ library for implementation of blocked and segregated preconditioners in the context of iterative solvers for linear systems. Capabilities for decomposing larger matrices into user defined sub blocks are also provided. Additional functionality for creating approximate inverse operators utilizing solver and preconditioning packages in the Trilinos framework has also been implemented. Teko's primary application is in multiphysics simulation environment where a decomposition of the linear system in to physically meaningful blocks can be utilized to enhance performance of an iterative solver. However, applicability may extend to other problem domains where matrices can be decomposed into meaningful blocks.", + "laborHours": 8344830.4, + "name": "Teko v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "Conjoin is a code for joining sequentially in time multiple exodusII database files. It is used to create a single results or restart file from multiple results or restart files which typically arise as the result of multiple restarted analyses. The resulting output file will be the union of the input files with a status variable indicating the status of each element at the various time planes.Combining multiple exodusII files arising from a restarted analysis or combining multiple exodusII files arising from a finite element analysis with dynamic topology changes.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "Conjoin", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "ejoin is a three-dimensional mesh combination program. ejoin combines two or more meshes written in the exodusII mesh database format into a single exodusII mesh. Selected nodes in the wo meshes that are closer than a specified distance can be combined The geometry of the mesh databases an be modified by offsetting. Any results data on one or more of the input mesh files will be copied to the appropriate nodes/elements/nodesets/sidesets on the output file.Preparation of input mesh files for finite element analysis programs using the exodusII format.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "Ejoin", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "This application can determine the performance and chemical behavior of batteries in 1D when they are cycled. With CanTrilBat, we are developing predictive phenomenological models for battery systems to predict operating performance and rate limiting steps in the performance of battery models. Particular attention is paid to primary and secondary chemistry mechanisms, such as the thermal runaway mechanisms experienced in secondary lithium ion batteries or self-discharge reaction mechanism that all batteries experience to one extent or another. The first application of this model has been for modeling the performance of thermal batteries. However, an implementation for secondary ion batteries is next. CanTrilBat applications solves transient problems involving batteries. It is a 1-D application that represents 3-D physical systems that can be reduced using the porous flow approximation for the anode, cathode, and separator. A control volume formulation is used to track conserved quantities. An operator-split approach is used to calculate the chemistry, diffusion and electronic transport that occurs within cathode and anode particles, allowing for the reduction in code complexity.", + "laborHours": 6177492.8, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "M4", + "Fortran" + ], + "name": "CanTrilBat", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cantrilbat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This program can be used to read a LC-MS/MS data file from either a Finnigan ion trap mass spectrometer (.Raw file) or an Agilent Ion Trap mass spectrometer (.MGF and .CDF files) and create a selected ion chromatogram (SIC) for each of the parent ion masses chosen for fragmentation. The largest peak in each SIC is also identified, with reported statistics including peak elution time, height, area, and signal to noise ratio. It creates several output files, including a base peak intensity (BPI) chromatogram for the survey scan, a BPI for the fragmentation scans, an XML file containing the SIC data for each parent ion, and a \"flat file\" (ready for import into a database) containing summaries of the SIC data statistics.", + "laborHours": 118225.6, + "name": "MS/MS Automated Selected Ion Chromatograms", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MASIC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pagoda is a set of parallel tools as well as an application programmer interface for parallel data analysis of high-resolution climate data. Pagoda implements data parallel versions of some of the commonly used tools from the NetCDF Operators. These tools support data processing operations including subsetting, record and ensemble averages, binary operations, and interpolation. Pagoda also provides an application programmer interface for developing custom data analysis programs.", + "laborHours": 61392.8, + "name": "Pagoda", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jeffdaily/pagoda/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeffdaily/pagoda", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "nodediag is an extensible framework for packaging system diagnostics for Linux clusters.", + "laborHours": 592.8, + "name": "nodediag", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/nodediag", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MixDown is a meta-build tool that orchestrates and manages the building of multiple 3rd party libraries. It can manage the downloading, uncompressing, unpacking, patching, configuration, build, and installation of 3rd party libraries using a variety of configuration and build tools. As a meta-build tool, it relies on 3rd party tools such as GNU Autotools, make, Cmake, scons, etc. to actually confugure and build libraries. MixDown includes an extensive database of settings to be used for general machines and specific leadership class computing resources.", + "laborHours": 6536.0, + "name": "MixDown", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tepperly/MixDown", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "lustre-tools-llnl is a small set of commands that are helpful for using and administering a lustre file system.", + "laborHours": 1033.6, + "name": "lustre-tools-llnl", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/lustre-tools-llnl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This program is used to compute the predicted normalized elution time (NET) for a list of peptide sequences. It includes the Kangas/Petritis neural network trained model, the Krokhin hydrophobicity model, and the Mant hydrophobicity model. In addition, it can compute the predicted strong cation exchange (SCX) fraction (on a 0 to 1 scale) in which a given peptide will appear.", + "laborHours": 7296.0, + "name": "Normalized Elution Time Prediction Utility", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Protein-Digestion-Simulator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OVIS is a tool for intelligent, real-time monitoring of computational clusters. While current monitoring tools treat the cluster as singleton nodes, OVIS considers the cluster as comprised of comparative ensembles. OVIS provides a visual display of deterministic information about state variables and their aggregate statistics. Comparison to statistical quantities can be used for the automatic identification of abnormalities. OVIS collects and processes active data. OVIS can also process historical data files or database files.", + "laborHours": 98252.8, + "name": "OVIS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ovis-hpc/ovis", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Albany code is a general purpose finite element code for solving partial differential equations (PDEs). Albany is a research code that demonstrates how a PDE code can be built by interfacing many of the open-source software libraries that are released under Sandia's Trilinos project. Part of the mission of Albany is to be a testbed for new Trilinos libraries, to refine their methods, usability, and interfaces. Albany also serves as a demonstration code on how to build an application code against an installed Trilinos project. Because of this, Albany is a desirable starting point for new code development efforts that wish to make heavy use of Trilinos. The physics solved in Albany are currently only very academic problems, such as heat transfer, linear elasticity, and nonlinear elasticity. Albany includes hooks to optimization and uncertainty quantification algorithms, including those in the Dakota toolkit.", + "laborHours": 364222.4, + "name": "Albany v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gahansen/Albany", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-10-08" + }, + "description": "PECOS is a computational library for creating and manipulating realizations of stochastic quantities, including scalar uncertain variables, random fields, and stochastic processes. It offers a unified interface to univariate and multivariate polynomial approximations using either orthogonal or interpolation polynomials; numerical integration drivers for Latin hypercube sampling, quadrature, cubature, and sparse grids; and fast Fourier transforms using third party libraries. The PECOS core also offers statistical utilities and transformations between various representations of stochastic uncertainty. PECOS provides a C++ API through which users can generate and transform realizations of stochastic quantities. It is currently used by Sandia's DAKOTA, Stokhos, and Encore software packages for uncertainty quantification and verification. PECOS generates random sample sets and multi-dimensional integration grids, typically used in forward propagation of scalar uncertainty in computational models (uncertainty quantification (UQ)). PECOS also generates samples of random fields (RFs) and stochastic processes (SPs) from a set of user-defined power spectral densities (PSDs). The RF/SP may be either Gaussian or non-Gaussian and either stationary or nonstationary, and the resulting sample is intended for run-time query by parallel finite element simulation codes. Finally, PECOS supports nonlinear transformations of random variables via the Nataf transformation and extensions.", + "homepageURL": "https://dakota.sandia.gov/content/packages?q=content/pecos", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Environment for the Creation of Stochastics 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/content/packages?q=content/pecos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-07-25" + }, + "description": "HiPerSBTK consists of software which integrates equation solving, optimization and graphical interface functions to perform large-scale systems biology modeling.\n\nsee: https://www.nrel.gov/docs/fy11osti/51558.pdf", + "laborHours": 3149576.8, + "languages": [], + "name": "HiPerSBTK [SWR-08-64]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "Amesos2 is a templated direct sparse solver package. Amesos2 provides interfaces to direct sparse solvers, rather than providing native solver capabilities. Amesos2 is a derivative work of the Trilinos package Amesos.", + "laborHours": 8344830.4, + "languages": [], + "name": "Amesos2 Templated Direct Sparse Solver Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The Image Composition Engine for Tiles (lceT) is a high-performance sort-last parallel rendering library. It is designed to be used in parallel applications requiring rendering. The primary purpose of IceT is to be integrated into parallel visualization applications such as ParaView to provide parallel rendering capabilities. The Image Composition Engine for Tiles (lceT) is a high-performance sort-last parallel rendering library. IceT uses a \"sort-Iasf' approach to rendering. Each process in a parallel application independently renders a local piece of geometry. The resulting images are given to IceT, and IceT combines the images together to form a single cohesive image. Ice T is also capable of driving tiled displays, largeformat displays comprising an array of smaller displays. To this end IceT can collect the smaller tile images and organize them such that the entire tiled display can be driven. Ice T takes advantage of spatial coherence in geometry by identifying empty regions of the display and reducing the overall required work.", + "laborHours": 8709.6, + "languages": [ + "C" + ], + "name": "Image Composition Engine for Tiles", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IceT", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "LibVMI is an introspection library focused on reading and writing memory from virtual machines (VMs). For convenience, LibVMI also provides functions for accessing CPU registers, pausing and unpausing a VM, printing binary data, and more. LibVMI is designed to work across multiple virtualization platforms. LibVMI currently supports VMs running in either Xen or KVM. LibVMI also supports reading physical memory snapshots when saved as a file.", + "laborHours": 59097.6, + "languages": [ + "Yacc", + "C++", + "C", + "CMake", + "M4", + "Python" + ], + "name": "LibVMI", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/libvmi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.6" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "miniXyce uses a modified nodal analysis to approximate the governing differential algebraic equations (DAEs) for electronic devices and their coupling via a network and Kirchoff's conservation laws. The resulting nonlinear problem is solved iteratively using a fully coupled Newton method,which in turn results in a linear system that is solved using an iterative method.", + "laborHours": 1748.0, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "Perl", + "MATLAB", + "Python" + ], + "name": "miniXyce", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniXyce", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Peridigm is a multiphysics simulation code for peridynamic models. It provides the capability to simulate nonlocal models of solids undergoing large deformations and failure. It provides basic linear elastic and perfectly plastic peridynamic material models, and well as the capability to apply simply initial, boundary and loading conditions.", + "laborHours": 53534.4, + "languages": [ + "C++", + "Jupyter Notebook", + "CMake", + "Python" + ], + "name": "Peridigm", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/peridigm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-19" + }, + "description": "TriUtils is a package of utilities for other Trilinos packages. TriUtils contains utilities to perform common operations such as command line parsing, and input file reading.", + "laborHours": 8344830.4, + "languages": [], + "name": "TriUtils Trilinos Utilities Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "The Trilinos I/O support (Trios) software provides general I/O support for applications using Trilinos libraries. In particular, this software will include parallel I/O support to read and write selected Trilinos data structures to commonly-used file formats such as netCDF, hdf5, and Exodus.", + "laborHours": 39231.2, + "languages": [ + "C++", + "Shell", + "C", + "RPC", + "CMake", + "Makefile", + "Fortran" + ], + "name": "Trios", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/trios", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Epetra provides the fundamental construction routines and service functions that are required for serial and paraliellinear algebra libraries using double precision scalar values and int ordinal values.", + "laborHours": 8344830.4, + "languages": [], + "name": "Epetra Linear Algebra Services Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "EpetraExt is a set of extensions to Epetra. To allow Epetra to remain focused on its primary functionality as a Linear Algebra object support, EpetraExt was created to maintain additional support for such capabilities as transformations (permutations, subblock views, etc.), coloring support, partitioning (Zoltan), and I/O.", + "laborHours": 8344830.4, + "languages": [], + "name": "EpetraExt (Epetra Extended) - Linear Algebra Services", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Panzer is a finite element assembly engine used for research on solving partial differential equations (PDEs). Panzer takes a physics model implemented by a user and creates and populates the linear algrbra objects, such as residuals and Jacobians, for use in implicit finite element methods. Panzer can be considered \"glue code\" that pulls together the capabilities of a number of open-source Trilinos packages (Epetra, Intrepid, Sacado, FEI, and Phalanx). This code provides a generic framework for describing a set of partial differential equations. Panzer provides a simple example driver that solves the undergraduate textbook partial differential equation of heat transfer in a solid (see for example, \"Transport Phenomena\" by Bird Stewart, and Lightfoot 1960). Panzer is intended as a tool to simplify the use of the discretization tools in Trilinos (Intrepid and Phalanx) and is meant to aid in fundamental research on discretizations. Panzer will be released open-source as a package in Trilinos under a BSD license.", + "laborHours": 8344830.4, + "languages": [], + "name": "Panzer", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SEACAS Trilinos is the packaging of the SEACAS applications inside the Trilinos software package in a manner such that the Trilinos build and configurationprocess can be used to build and configure the SEACAS applications.", + "laborHours": 8344830.4, + "languages": [], + "name": "SEACAS Trilinos", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "IRIS is a search tool plug-in that is used to implement latent topic feedback for enhancing text navigation. It accepts a list of returned documents from an information retrieval wywtem that is generated from keyword search queries. Data is pulled directly from a topic information database and processed by IRIS to determine the most prominent and relevant topics, along with topic-ngrams, associated with the list of returned documents. User selected topics are then used to expand the query and presumabley refine the search results.", + "laborHours": 592.8, + "name": "Search tool plug-in: imploements latent topic feedback", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/iris", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "SmartImport.py is a Python source-code file that implements a replacement for the standard Python module importer. The code is derived from knee.py, a file in the standard Python diestribution , and adds functionality to improve the performance of Python module imports in massively parallel contexts.", + "laborHours": 243.2, + "name": "Python import replacement", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/langton/MPI_Import", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/langton/mpi_import", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MeshKit is an open-source library of mesh generation functionality. MeshKit has general mesh manipulation and generation functions such as Copoy, Move, Rotate and Extrude mesh. In addition, new quad mesh and embedded boundary Cartesian mesh algorithm (EB Mesh) are included. Interfaces to several public domain meshing algorithms (TetGen, netgen, triangle, Gmsh, camal) are also offered. This library interacts with mesh data mostly through iMesh including accessing the mesh in parallel. It also can interact with iGeom interface to provide geometry functionality such as importing solid model based geometries. iGeom and IMesh are implemented in the CGM and MOAB packages, respectively. For some non-existing function in iMesh such as tree-construction and ray-tracing, MeshKit also interacts with MOAB functions directly.", + "laborHours": 128637.6, + "name": "MeshKit", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/fathomteam/meshkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Service-Poke is a system which manages running services ensuring only one copy is running and potentially up to one more copy is marked for future execution.", + "laborHours": 562.4, + "name": "Service-Poke", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/service-poke", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-12-11" + }, + "description": "Co-PylotDB, written completely in Python, provides a user interface (UI) with which to select user and data file(s), directories, and file content, and provide or capture various other information for sending data collected from running any computer program to a pre-formatted database table for persistent storage. The interface allows the user to select input, output, make, source, executable, and qsub files. It also provides fields for specifying the machine name on which the software was run, capturing compile and execution lines, and listing relevant user comments. Data automatically captured by Co-PylotDB and sent to the database are user, current directory, local hostname, current date, and time of send. The UI provides fields for logging into a local or remote database server, specifying a database and a table, and sending the information to the selected database table. If a server is not available, the UI provides for saving the command that would have saved the information to a database table for either later submission or for sending via email to a collaborator who has access to the desired database.", + "laborHours": 64448.0, + "languages": [ + "Python" + ], + "name": "Co-PylotDB - A Python-Based Single-Window User Interface for Transmitting Information to a Database", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PYLOTDB", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "EXOMATLAB extracts the global transient variable data from an exodus file and writes it to a text-based file readable by the Matlab program.", + "laborHours": 692284.0, + "languages": [ + "MATLAB" + ], + "name": "exomatlab", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.9.2" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Domain Name System Security Extensions (DNSSEC) add authentication to the DNS. However, analyzing and troubleshooting a DNSSEC deployment is difficult in part because of the protocol complexity and in part because authentication involves retrieving dependent components from a number of different Internet locations. DNSViz was written to bring all these DNSSEC components together into a single graph, so they can be represented visually, and nuances can be highlighted for easy identification. DNSViz includes functionality for both analyzing a domain name using active probing and visual representation of the domain name, available currently through a Web interface.", + "laborHours": 11445.6, + "name": "DNSViz", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dnsviz/dnsviz", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "eCo-PylotDB, written completely in Python, provides a script that parses incoming emails and prepares extracted data for submission to a database table. The script extracts the database server, the database table, the server password, and the server username all from the email address to which the email is sent. The database table is specified on the Subject line. Any text in the body of the email is extracted as user comments for the database table. Attached files are extracted as data files with each file submitted to a specified table field but in separate rows of the targeted database table. Other information such as sender, date, time, and machine from which the email was sent is extracted and submitted to the database table as well. An email is sent back to the user specifying whether the data from the initial email was accepted or rejected by the database server. If rejected, the return email includes details as to why.", + "laborHours": 64448.0, + "languages": [], + "name": "eCo-Pylot - A Python-Based Script for Sending Parsed Email Data to a Database", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PYLOTDB", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GEN3D is a three-dimensional mesh generation program. The three-dimensional mesh is generated by mapping a two-dimensional mesh into three-dimensions according to one of four types of transformations: translating, rotating, mapping onto a spherical surface, and mapping onto a cylindrical surface. The generated three-dimensional mesh can then be reoriented by offsetting, reflecting about an axis, and revolving about an axis. GEN3D can be used to mesh geometries that are axisymmetric or planar, but, due to three-dimensional loading or boundary conditions, require a three-dimensional finite element mesh and analysis. More importantly, it can be used to mesh complex three-dimensional geometries composed of several sections when the sections can be defined in terms of transformations of two dimensional geometries. The code GJOIN is then used to join the separate sections into a single body. GEN3D reads and writes two-dimensional and three-dimensional mesh databases in the GENESIS database format; therefore, it is compatible with the preprocessing, postprocessing, and analysis codes used by the Engineering Analysis Department at Sandia National Laboratories, Albuquerque, NM.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "GEN3D Ver. 1.37", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.37" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GENSHELL is a three-dimensional shell mesh generation program. The threedimensional shell mesh is generated by mapping a two-dimensional quadrilateral mesh into three dimensions according to one of several types of transformations: translation, mapping onto a spherical, ellipsoidal, or cylindrical surface, and mapping onto a user-defined spline surface. The generated three-dimensional mesh can then be reoriented by offsetting, reflecting about an axis, revolving about an axis, and scaling the coordinates. GENSHELL can be used to mesh complex three-dimensional geometries composed of several sections when the sections can be defined in terms of transformations of two-dimensional geometries. The code GJOIN is then used to join the separate sections into a single body. GENSHELL updates the EXODUS quality assurance and information records to help track the codes and files used to generate the mesh. GENSHELL reads and writes two-dimensional and three-dimensional mesh databases in the GENESIS database format; there, it is compatible with the preprocessing, postprocessing, and analysis codes in the Sandia National Laboratories Engineering Analysis Code Access System (SEACAS).", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "genshell", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.15" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GREPOS is a mesh utility program that repositions or modifies the configuration of a two- dimensional or three-dimensional mesh. GREPOS can be used to change the orientation and size of a two- dimensional or three-dimensional mesh; change the material block, nodeset, and sideset IDs; or \"explode\" the mesh to facilitate viewing of the various parts of the model, and several other mesh modification utilities.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "GREPOS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.61" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "KLU2 is a direct sparse solver for solving unsymmetric linear systems. It is related to the existing KLU solver, (in Amesos package and also as a stand-alone package from University of Florida) but provides template support for scalar and ordinal types. It uses a left looking LU factorization method.", + "laborHours": 8344830.4, + "languages": [], + "name": "KLU2 Direct Linear Solver Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "PylotDB, written completely in Python, provides a user interface (UI) with which to interact with, analyze, graph data from, and manage open source databases such as MySQL. The UI mitigates the user having to know in-depth knowledge of the database application programming interface (API). PylotDB allows the user to generate various kinds of plots from user-selected data; generate statistical information on text as well as numerical fields; backup and restore databases; compare database tables across different databases as well as across different servers; extract information from any field to create new fields; generate, edit, and delete databases, tables, and fields; generate or read into a table CSV data; and similar operations. Since much of the database information is brought under control of the Python computer language, PylotDB is not intended for huge databases for which MySQL and Oracle, for example, are better suited. PylotDB is better suited for smaller databases that might be typically needed in a small research group situation. PylotDB can also be used as a learning tool for database applications in general.", + "laborHours": 64448.0, + "languages": [ + "Python" + ], + "name": "PylotDB - A Database Management, Graphing, and Analysis Tool Written in Python", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PYLOTDB", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "This software consists of code modifications to the open-source OpenSceneGraph software package to enable the creation of TlFF images containing 16 bit unsigned data. They also allow the user to disable compression and set the DPI tags in the resulting TIFF Images. Some image analysis programs require uncompressed, 16 bit unsigned input data. These code modifications allow programs based on OpenSceneGraph to write out such images, improving connectivity between applications.", + "laborHours": 367292.8, + "languages": [ + "Objective-C", + "C++", + "HTML", + "C", + "CMake", + "Objective-C++" + ], + "name": "TIFF Image Writer patch for OpenSceneGraph", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/OpenSceneGraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The functionality of heRXD includes the following: distance and angular calibration and viewing flat-panel detector images used for X-ray diffraction; image (polar) rebinning or \"caking\"; line position fitting in powder diffraction images; image segmentation or \"blob finding\"; crystal orentation indesing; and lattice vector refinement. These functionalities encompass a critical set analyzing teh data for high-energy diffraction measurements that are currently performed at synchrotron sources such as the Advanced Photon Source (APS). The software design modular and open source under LGPL. The intent is to provide a common framework and graphical user interface that has the ability to utillize internal as well as external subroutines to provide various optins for performing the fuctionalities listed above. The software will initially be deployed at several national user facilities--including APS, ALS, and CHESS--and then made available for download using a hosting service such as sourceforge.", + "laborHours": 33865.6, + "name": "High-Energy X-Ray Diffraction Analysis Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/praxes/hexrd", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MountPointAttributes is a software component that provides client code with a technique to raise the local namespace of a file to a global namespace. Its abstractions and mechanisms allow the client code to gather global properties of a file and to use them in devising an effective storage access strategy on this file.", + "laborHours": 2872.8, + "name": "MountPointAttributes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/mountpointattributes", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Forthon generates links between Fortran and Python. Python is a high level, object oriented, interactive and scripting language that allows a flexible and versatile interface to computational tools. The Forthon package generates the necessary wrapping code which allows access to the Fortran database and to the Fortran subroutines and functions. This provides a development package where the computationally intensive parts of a code can be written in efficient Fortran, and the high level controlling code can be written in the much more versatile Python language.", + "laborHours": 3906.4, + "name": "Python interface generator for Fortran based codes (a code development aid)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/dpgrote/Forthon/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dpgrote/Forthon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ECCE provides a sophisticated graphical user interface, scientific visualization tools, and the underlying data management framework enabling scientists to efficiently set up calculations and store, retrieve, and analyze the rapidly growing volumes of data produced by computational chemistry studies. ECCE was conceived as part of the Environmental Molecular Sciences Laboratory construction to solve the problem of researchers being able to effectively utilize complex computational chemistry codes and massively parallel high performance compute resources. Bringing the power of these codes and resources to the desktops of researcher and thus enabling world class research without users needing a detailed understanding of the inner workings of either the theoretical codes or the supercomputers needed to run them was a grand challenge problem in the original version of the EMSL. ECCE allows collaboration among researchers using a web-based data repository where the inputs and results for all calculations done within ECCE are organized. ECCE is a first of kind end-to-end problem solving environment for all phases of computational chemistry research: setting up calculations with sophisticated GUI and direct manipulation visualization tools, submitting and monitoring calculations on remote high performance supercomputers without having to be familiar with the details of using these compute resources, and performing results visualization and analysis including creating publication quality images. ECCE is a suite of tightly integrated applications that are employed as the user moves through the modeling process.", + "laborHours": 450421.6, + "name": "Extensible Computational Chemistry Environment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mattbernst/ECCE/blob/master/ecce-v7.0/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mattbernst/ECCE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Amalgam is a system that allows you to generate collections of files that work with conventional tools but take up minimal extra space on storage. If you already are archiving files in a file system and don't want to make multiple copies of whole files in order to ship the data somewhere then this system is for you. Amalgam consists of tools that allow you to create and get information about '.amalgam' files which contain just the metadata associated with a set of files. It also contains a fuse file system that, using amalgam files, will dynamically create traditional tar files. With this setup, you can see multiple orders of magnitude reduction in storage requirements for temporary data collections.", + "laborHours": 638.4, + "name": "Amalgam", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/amalgam", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-16" + }, + "description": "This software package implements the algorithm from a paper by Bayati, Kim, and Saberi (first reference below) to generate a uniformly random sample of a graph with a prescribed degree distribution.", + "laborHours": 1094.4, + "languages": [ + "MATLAB", + "C++", + "C" + ], + "name": "Bayati Kim Saberi random graph sampler", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/bisquik", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "While an organized source of reference information on PV performance modeling is certainly valuable, there is nothing to match the availability of actual examples of modeling algorithms being used in practice. To meet this need, Sandia has developed a PV performance modeling toolbox (PV_LIB) for Matlab. It contains a set of well-documented, open source functions and example scripts showing the functions being used in practical examples. This toolbox is meant to help make the multi-step process of modeling a PV system more transparent and provide the means for model users to validate and understand the models they use and or develop. It is fully integrated into Matlab's help and documentation utilities. The PV_LIB Toolbox provides more than 30 functions that are sorted into four categories", + "laborHours": 532.0, + "name": "PV_LIB Toolbox", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cwhanse/PVLIB_Python", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Xpetra provides a single interface that allows the use of either Epetra or Tpetra linear algebra libraries from the same source code. Library developers need only learn and use the syntax of Xpetra; the resulting libraries can use either Epetra or Tpetra.", + "laborHours": 8344830.4, + "languages": [ + "C++", + "C", + "Roff", + "MATLAB", + "Fortran", + "Python" + ], + "name": "Xpetra Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "MueLu is intended for the research and development of multigrid algorithms used in the solution of sparse linear systems arising from systems of partial differential equations. The software provides multigrid source code, test programs, and short example programs to demonstrate the various interfaces for creating, accessing, and applying the solvers. MueLu currently provides an implementation of smoothed aggregation algebraic multigrid method and interfaces to many commonly used smoothers. However, the software is intended to be extensible, and new methods can be incorporated easily. MueLu also allows for advanced usage, such as combining multiple methods and segregated solves. The library supports point and block access to matrix data. All algorithms and methods in MueLu have been or will be published in the open scientific literature.", + "laborHours": 8344830.4, + "languages": [], + "name": "MueLu Multigrid Preconditioning Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MiniGhost is a miniapp in the Mantevo project. Using a finite difference method, it mimics the inter-process communication requirements commonly found in applications of this sort. Random values are inserts into the grid, and therefore no \"real problem\" is solved.", + "laborHours": 5016.0, + "name": "miniGhost Mantevo miniapp", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Mantevo/miniGhost", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-19" + }, + "description": "ShyLU is numerical software to solve sparse linear systems of equations. ShyLU uses a hybrid direct-iterative Schur complement method, and may be used either as a preconditioner or as a solver. ShyLU is parallel and optimized for a single compute Solver node. ShyLU will be a package in the Trilinos software framework.", + "laborHours": 8344830.4, + "languages": [], + "name": "jShyLU Scalable Hybrid Preconditioner and Solver", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "pair_bop is a module for performing energy calculations using the Bond Order Potential (BOP) for use in the parallel molecular dynamics code LAMMPS. The bop pair style computes BOP based upon quantum mechanical incorporating both sigma and pi bondings. By analytically deriving the BOP pair bop from quantum mechanical theory its transferability to different phases can approach that of quantum mechanical methods. This potential is extremely effective at modeling 111-V and II-VI compounds such as GaAs and CdTe. This potential is similar to the original BOP developed by Pettifor and later updated by Murdock et al. and Ward et al.", + "laborHours": 1281025.6, + "name": "Bond order potential module for LAMMPS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lammps/lammps", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "MAT2EXO is a program which translates mesh data from Matlab mat-file format to Exodus II format. This tool is the inverse of the commonly used tool exo2mat which translates Exodus II data to the Matlab mat-file format. These tools provide a means for preprocessing an Exodus II model file or postprocessing an Exodus II results file using Matlab", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "Mat2exo", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.6" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The Dax Toolkit enables the fine-grained concurrency for data analysis and visualization required to drive multi-core processors, many-core GPU accelerators, and emerging architectures for exascale computing. Dax simplifies the design of finely threaded algorithms by characterizing them in per element operations, which we call worklets. Worklets simplify design because they can behave as serial processes without the complications of memory clashes or other race conditions. Yet worklets can be scheduled on a practically unlimited number of threads, thereby making effective utilization of many processing cores. Operations coordinated across elements are encapsulated in a few versatile communicative operations that are adapted to the specifics of computing devices.", + "laborHours": 24396.0, + "languages": [ + "C++", + "C", + "CMake", + "Cuda" + ], + "name": "Dax v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DaxToolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The software is a modular framework for controlling data acquisition systems (DAQs) for radiation detectors. Its capabilities include hardware configuration and control as well as data readout and storage. In addition to a generalized extensible framework for building DAQs, the package also includes specific implementations for a number of commercially available hardware devices commonly used in nuclear instrumentation (digitizers, high voltage controllers, etc.).", + "laborHours": 9667.2, + "languages": [ + "Lua" + ], + "name": "SLMod", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DCS-Slmod", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Kokkos Array library implements shared-memory array data structures and parallel task dispatch interfaces for data-parallel computational kernels that are performance-portable to multicore-CPU and manycore-accelerator (e.g., GPGPU) devices.", + "laborHours": 8344830.4, + "name": "Kokkos Array", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "nSIGHTS (n-dimensional Statistical Inverse Graphical Hydraulic Test Simulator) is a comprehensive well test analysis software package. It provides a user-interface, a well test analysis model and many tools to analyze both field and simulated data. The well test analysis model simulates a single-phase, one-dimensional, radial/non-radial flow regime, with a borehole at the center of the modeled flow system. nSIGHTS solves the radially symmetric n-dimensional forward flow problem using a solver based on a graph-theoretic approach. The results of the forward simulation are pressure, and flow rate, given all the input parameters. The parameter estimation portion of nSIGHTS uses a perturbation-based approach to interpret the best-fit well and reservoir parameters, given an observed dataset of pressure and flow rate.", + "laborHours": 269587.2, + "languages": [ + "Objective-C", + "C++", + "HTML", + "C", + "CMake", + "Makefile" + ], + "name": "n-dimensional Statistical Inverse Graphical Hydraulic Test Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/nSIGHTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The ap command traveres all symlinks in a given file, directory, or executable name to identify the final absolute path. It can print just the final path, each intermediate link along with the symlink chan, and the permissions and ownership of each directory component in the final path. It has functionality similar to \"which\", except that it shows the final path instead of the first path. It is also similar to \"pwd\", but it can provide the absolute path to a relative directory from the current working directory.", + "laborHours": 76.0, + "name": "The absolute path command", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/ap/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Datatype Compare (DTCMP) library provides routines that sort, search, merge, partition, rank, and select items using operations that compare MPI datatypes. Such routines are needed im MPI applications dealing with large distributed latasets, where the amount of data is too large to gather to a single process.", + "laborHours": 10047.2, + "name": "The Datatype Compare Library v.1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/dtcmp/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/dtcmp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The mpileaks tool is to be used by MPI application developers to track and report leaked MPI objects, such as requests, groups, and datatypes. This debugging tool is useful as a quality assurance check for MPI applications, or it can be used to identify leaks fatal to long-running MPI applications. It provides an efficient method to report bugs that are otherwise fifficult to identify.", + "laborHours": 22450.4, + "name": "mpileaks - an MPI opject leak debugging library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/mpileaks/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mpileaks", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DI-MMAP is a simulator for modeling the performance of next generation non-volatile random access memory technologies (NVRAM) and a high-perfromance memory-map runtime for the Linux operating system. It is implemented as a device driver for the Linux operating system. It will be used by algorithm designers to unserstand the impact of future NVRAM on their algorithms and will be used by application developers for high-performance access to NVRAM storage.", + "laborHours": 4894.4, + "name": "Data-Intensive Memory-Map simulator and runtime", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/vanessen/di-mmap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "We are seeking a code review of patches against DyninstAPI 8.0. DyninstAPI is an open source binary instrumentation library from the University of Wisconsin and University of Maryland. Our patches port DyninstAPI to the BlueGene/P and BlueGene/Q systems, as well as fix DyninstAPI bugs and implement minor new features in DyninstAPI.", + "laborHours": 290867.2, + "languages": [], + "name": "DyninstAPI Patches", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dyninst/dyninst", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Script to create operating system images in a directory from RPMs using the commands rpm or YUM.", + "laborHours": 136.8, + "name": "Kona", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trentdhooge/kona.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Light-Weight Group (LWGRP) bibrary provides data structures and collective routines to define and operate on groups of MPI processes. Groups can be created and freed efficiently in O(log N) time space requiring less overhead that constructing full MPI communicators. This facilitates faster development of applications and libraries that need to rapidly create, use, and destroy process groups.", + "laborHours": 24289.6, + "name": "The Light-Weight Group Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/lwgrp/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lwgrp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Rubik is a tool that simplifies the process of creating task mappings for structured applications. Rubik allows an application developer to specify communicating groups of processes in a virtual application topology succinctly and map them onto groups of processors in a physical network topology. Both the application topology and the network topology must be Cartesian, but the dimensionality of either is arbitrary. This allows users to easily map low-dimensional structures such as planes to higher-dimensional structures like cubes to increase the number of links used for routing.", + "laborHours": 896.8, + "name": "Rubik", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/rubik/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/rubik", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Give and Take are set of companion utilities that allow a secure transfer of files from one user to another without exposing the files to third parties. The named files are copied to a spool area. The reciever can retrieve the files by running the \"take\" program. Ownership of the files remains with the giver until they are taken. Certain users may be limited to take files only from specific givers. For these users, files may only be taken from givers who are members of the gt-uid-group where uid is the UNIX id of the limited user.", + "laborHours": 26934.4, + "name": "Give/Take", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/give", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Interatomic force and energy calculation subroutine to be used with the molecular dynamics simulation code LAMMPS (Ref a.). The code evaluated the total energy and atomic forces (energy gradient) according to a cubic spline-based variant (Ref b.) of the Modified Embedded Atom Method (MEAM) with a additional Stillinger-Weber (SW) contribution.", + "laborHours": 1281025.6, + "name": "Modified Embedded Atom Method", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lammps/lammps", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Boxfish is a tool for visualizing performance data. It allows users to quickly project performance data gathered from parallel applications onto intuitive domains. It also includes a projection mechanism that automatically finds relations in performance data so the the data can easily be mapped onto non-obviously related domains. For this release, Boxfish allows performance data to be projected onto the nodes and links of a computer network, as well as onto grids or patch-structured applications. This allows a user of the visualization tool to quickly see correlations between performance data and network structure, application data, or communication patterns.", + "laborHours": 225005.6, + "name": "Boxfish", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/boxfish/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/boxfish", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SystemBurn is a tool for creating a synthetic computational load for the purpose of measuring how much power a computer will draw under that type of load. The loads include fundamental library function calls like matrix multiply, memory copies, fourier transforms, bit manipulation, I/O, network packet transfers, and some code contrived to cause the processor to dray more or less power. The code produces some diagnostic and progress output, but the actual measurements would be recorded from the power panels within the computer room.", + "laborHours": 17510.4, + "name": "SystemBurn", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jlothian/systemburn", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SystemConfidence is a benchmark developed at ORNL which can measure statistical variation in which the user can plot. The portions of the code which manage the collection of the histograms and computing statistics on the histograms were designed with the intent that we could use these functions in other codes.", + "laborHours": 1216.0, + "name": "SystemConfidence", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jlothian/sysconfidence", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Log files are typically semi-or un-structured. To be useable, they need to be parsed into a standard, structured format. Regex-Stream facilitates parsing text files into structured data (JSON) in streams of data.", + "laborHours": 34488.8, + "name": "Regex-Stream", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/regex-stream", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"Synchrotron Radiation Workshop\" (SRW) is a physical optics computer code for calculation of detailed characteristics of Synchrotron Radiation (SR) generated by relativistic electrons in magnetic fields of arbitrary configuration and for simulation of the radiation wavefront propagation through optical systems of beamlines. Frequency-domain near-field methods are used for the SR calculation, and the Fourier-optics based approach is generally used for the wavefront propagation simulation. The code enables both fully- and partially-coherent radiation propagation simulations in steady-state and in frequency-/time-dependent regimes. With these features, the code has already proven its utility for a large number of applications in infrared, UV, soft and hard X-ray spectral range, in such important areas as analysis of spectral performances of new synchrotron radiation sources, optimization of user beamlines, development of new optical elements, source and beamline diagnostics, and even complete simulation of SR based experiments. Besides the SR applications, the code can be efficiently used for various simulations involving conventional lasers and other sources. SRW versions interfaced to Python and to IGOR Pro (WaveMetrics), as well as cross-platform library with C API, are available.", + "laborHours": 131008.8, + "name": "Synchrotron Radiation Workshop (SRW)", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ochubar/SRW/blob/master/COPYRIGHT.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ochubar/SRW", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "NV is a visualization tool for exploring vulnerabilities within a network. The data is created with a vulnerability assessment tool, such as Nessus (http://www.tenable.com/products/nessus).", + "laborHours": 270879.2, + "name": "Nessus Visualization", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/nv", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ASPA is an implementation of an adaptive sampling algorithm [1-3], which is used to reduce the computational expense of computer simulations that couple disparate physical scales. The purpose of ASPA is to encapsulate the algorithms required for adaptive sampling independently from any specific application, so that alternative algorithms and programming models for exascale computers can be investigated more easily.", + "laborHours": 19167.2, + "name": "Adaptive Sampling Proxy Application", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exmatex/aspa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ProxyVPFFT computes the micromechanical reaponse of polycriystalline samples directly from images of their microstructures, usually captured using SEM. [2] ProxyVPFFT is proxy application, or a somplified version of existing software by Ricardo Lebensohn (VPFFT).", + "laborHours": 1900.0, + "name": "Prozy Visco-plasticity, Fast Fourier Transform", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/exmatex/VPFFT/blob/master/README-license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exmatex/vpfft", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "LRIOT is a test bench framework that is designed to generate sophisticated I/O rates that can stress high-performance memory and storage systems, such as non-volatile random access memories (NVRAM)and storage class memory. Furthermore, LRIOT provides the capabilities to mix multiple types of concurrency, namely threading and task parallelism, as well as distributed execution using Message Passing Interface (MPI) libraries. It will be used by algorithm designers to generate access patterns that mimic their application's behavior, and by system designers to test high-performance NVRAM storage.", + "laborHours": 760.0, + "name": "Livermore Random I/O Testbench", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/vanessen/lriot/src/594efbf7484ed377e0b9e55e6f1bf564b6556546/lriot_license_header_stub.c", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/vanessen/lriot", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Qball is a modified version of the open source Qbox first-principles molecular dynamics code which was originally developed at LLNL by Francois Gygi.", + "laborHours": 3030135.2, + "name": "Qbox First-principles Molecular Dynamics (Qball branch, svn release 081", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/qball", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Sponge provides a web interface to Pulp (http://pulpproject.org/) that implements a particular workflow as described in the paper \"Staging Package Deployment via Repository Management\" (http://www.usenix.org/events/lisa11/tech/full_papers/Pierre.pdf). Namely, it implements a process for intensive management of software repositories to apply more deterministic updates to clients of those repositories.", + "laborHours": 2021.6, + "name": "Sponge", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stpierre/sponge", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The MPS++ computer code simulates models of strongly correlated quantum lattice systems. The algorithm used is the density-matrix renormalization method formulated in the matrix product states language. These models and methods are used to obtain ground state, dynamic, finite temperature and time evolution properties of the underlying materials that are simulated. These materials are usually one- and quasi-one dimensional strongly correlated electronic systems, such as high temperature superconductors, manganites, and other transition metal oxides. This code is (mostly) an implementation of the paper \"The density-matrix renormalization group in the age of matrix product states\" by U. Schollwoeck, and references therein, found at http://arxiv.org/abs/1008.3477v2 , and that was also published in Annals of Physics 326,96 (2011).", + "laborHours": 1656.8, + "name": "MPS++", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/g1257/mpspp", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.", + "laborHours": 60830.4, + "name": "Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bdsullivan/INDDGO", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "For testing and demonstration purposes, it is often necessary to replay saved network and log data. This library facilitates replaying these saved data streams. This module will take in a stream of JSON strings, read their specified timestamp field, and output according to the given criteria. This can include restricting output to a certain time range, and/or outputting the items with some delay based on their timestamp.", + "laborHours": 40736.0, + "name": "Replay-Stream", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/replay-stream", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Many new, high-performance nuclear energy modeling and simulation tools are under development in the United States and many more existing projects are moving to high-performance computing. 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For that matter, most remote jobs are launched on \"the machine in the other room,\" but that certainly will not work for larger problems that require Leadership Class computing resources found only at U.S. National Laboratories or similar facilities. Overcoming the challenges of launching on these machines and even on public or private \"clouds\" are left as a challenge to the user.", + "laborHours": 92902.4, + "name": "The NEAMS Integrated Computational Environment (NiCE)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/eclipse/ice/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eclipse/ice", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Enables applications to emit debug log information into an output file and provides developers with a way to visually structure the output to make it easier for them to navigate it to understand the sources of application errors.", + "laborHours": 192477.6, + "name": "dbglog", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bronevet/dbglog", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CRUISE implements a user-space file system that stores data in main memory and transparently spills over to other storage, like local flash memory or the parallel file system, as needed. CRUISE also exposes file contents fo remote direct memory access, allowing external tools to copy files to the parallel file system in the background with reduced CPU interruption.", + "laborHours": 4772.8, + "name": "Checkpoint-Restart in User Space", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/cruise/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/cruise", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This client-side web app tracks the amount of time spent on arbitrary tasks. It allosw the creation of an unlimited number of arbitrarily named tasks ans via simple interactions, tracks the amount of time spent working on the drfined tasks.", + "laborHours": 3602.4, + "name": "Task Time Tracker", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Task-Time-Tracker", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SW4 is a program for simulating seismic wave propagation on parallel computers. SW4 colves the seismic wave equations in Cartesian corrdinates. It is therefore appropriate for regional simulations, where the curvature of the earth can be neglected. SW4 implements a free surface boundary condition on a realistic topography, absorbing super-grid conditions on the far-field boundaries, and a kinematic source model consisting of point force and/or point moment tensor source terms. SW4 supports a fully 3-D heterogeneous material model that can be specified in several formats. SW4 can output synthetic seismograms in an ASCII test format, or in the SAC finary format. It can also present simulation information as GMT scripts, whixh can be used to create annotated maps. Furthermore, SW4 can output the solution as well as the material model along 2-D grid planes.", + "laborHours": 75817.6, + "name": "Seismic Waves, 4th order accurate", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/geodynamics/sw4", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ngrm-proto is a package of proff-of-concept utilities intended to demonstrate concepts that will be developed full in the FLUX resource manager.", + "laborHours": 0.0, + "name": "Next Generation Resource Manager Protoryping Environment", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/ngrm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HAVOQGT is a C++ framework that can be used to create highly parallel graph traversal algorithms. The framework stores the graph and algorithmic data structures on external memory that is typically mapped to high performance locally attached NAND FLASH arrays. The framework supports a vertex-centered visitor programming model. The frameworkd has been used to implement breadth first search, connected components, and single source shortest path.", + "laborHours": 15139.2, + "name": "Highly Asynchronous VisitOr Queue Graph Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/PerMA/havoqgt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "An API and implementation to install debug probes into a parallel application", + "laborHours": 5517.6, + "name": "Dynamic Scalable Event Chain Tracing API", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/dysectapi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-01-14" + }, + "description": "LDMS is a framework for collection and transport of system monitoring data from computational clusters. It utilizes existing data sources on the cluster (e.g., temperature sensors, network traffic counters). The collection and transport mechanisms of LDMS are lightweight and do not significantly adversely impact the performance of concurrently running applications.", + "laborHours": 98252.8, + "languages": [ + "Perl", + "C", + "Python" + ], + "name": "Lightweight Distributed Metric Service (LDMS) v. 4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ovis-hpc/ovis", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 4.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-04-18" + }, + "description": "Slycat™ is a web-based system for analysis of large, high-dimensional data such as that produced by High Performance Computing (HPC) platforms. The Slycat™ server integrates data ingestion, scalable analysis, data management, and visualization with commodity web clients using a multi-tiered hierarchy of data and model storage. Analysis inputs are pushed or pulled into Slycat™, where models are generated and analysis artifacts are stored in a project database. These artifacts are the basis for visualizations that are delivered to users’ desktops through ordinary web browsers, eliminating the need to build and deploy platform-specific client applications. Slycat™ currently provides four types of analysis: canonical correlation analysis (CCA) to model relationships between inputs and output metrics, time series analysis featuring clustering and comparative visualization of waveforms, parameter space visualization including remote retrieval of images and movies from HPC disks, and VideoSwarm for modeling video similarities over time.", + "laborHours": 66758.4, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Slycat v 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/slycat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The purpose of the Project Grandmaster Application is to allow individuals to opt-in and give the application access to data sources about their activities on social media sites. The application will cross-reference these data sources to build up a picture of each individual activities they discuss, either at present or in the past, and place this picture in reference to groups of all participants. The goal is to allow an individual to place themselves in the collective and to understand how their behavior patterns fit with the group and potentially find changes to make, such as activities they weren't already aware of or different groups of interest they might want to follow.", + "laborHours": 3967.2, + "name": "Project Grandmaster", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/grandmaster", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-11-01" + }, + "description": "The Xyce Parallel Electronic Simulator simulates electronic circuit behavior in DC, AC, HB, MPDE and transient mode using standard analog (DAE) and/or device (PDE) device models including several age and radiation aware devices. It supports a variety of computing platforms (both serial and parallel) computers. Lastly, it uses a variety of modern solution algorithms dynamic parallel load-balancing and iterative solvers.! ! Xyce is primarily used to simulate the voltage and current behavior of a circuit network (a network of electronic devices connected via a conductive network). As a tool, it is mainly used for the design and analysis of electronic circuits.! ! Kirchoff's conservation laws are enforced over a network using modified nodal analysis. This results in a set of differential algebraic equations (DAEs). The resulting nonlinear problem is solved iteratively using a fully coupled Newton method, which in turn results in a linear system that is solved by either a standard sparse-direct solver or iteratively using Trilinos linear solver packages, also developed at Sandia National Laboratories.", + "laborHours": 491233.6, + "languages": [], + "name": "Xyce(™) Parallel Electronic Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Xycedev/Xyce", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Not Specified", + "laborHours": 222254.4, + "name": "GOMA Ver. 6.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/goma/goma", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Minimega is a simple emulytics platform for creating testbeds of networked devices. The platform consists of easily deployable tools to facilitate bringing up large networks of virtual machines including Windows, Linux, and Android. Minimega attempts to allow experiments to be brought up quickly with nearly no configuration. Minimega also includes tools for simple cluster management, as well as tools for creating Linux based virtual machine images.", + "laborHours": 399334.4, + "name": "minimega", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandia-minimega/minimega", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "New to version 2.0 of Albany is the development of equations sets for specific application areas. These are independent research and development efforts that have chosen to use Albany as their software deployment vehicle. Because of synergies between the projects, they remain in the same code repository and are all releasing together as the Albany software.", + "laborHours": 364222.4, + "name": "Albany 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gahansen/Albany", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "TriBITS is a configuration, build, test, and reporting system that uses the Kitware open-source CMake/CTest/CDash system. TriBITS contains a number of custom CMake/CTest scripts and python scripts that extend the functionality of the out-of-the-box CMake/CTest/CDash system.", + "laborHours": 8344830.4, + "name": "TriBITS (Tribal Build, Integrate, and Test System)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "exodus.py is a Python wrapper of the open source Exodusll API intended for efficient pre-and post-processing finite element model data stored in the Exodusll file format.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "exodus.py", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "A framework for modeling and simulating biological neural systems", + "laborHours": 111902.4, + "languages": [ + "Java", + "C++", + "C", + "Python" + ], + "name": "Neurons to Algorithms", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/n2a", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "High Performance Computing (HPC) systems generate millions of inter-related event log lines per day from thousands of computers, providing feedback on both successful and unsuccessful operations within the system. Thorough analysis of these logs is often required for root cause analysis of problems and tuning for greatest performance. This \"app\" for the \"Gnawts\" log analysis software (http://www.gnawts.com) facilitates faster and deeper insights into HPC system logs.", + "laborHours": 4301.6, + "languages": [ + "CSS", + "Perl", + "HTML", + "Korn shell", + "JavaScript", + "Python" + ], + "name": "Gnawts", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gnawts", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "In the drive to make exascale computing a reality, significant effort is being invested in efficiently implementing and improving current numerical algorithms on various vendors' newest testbeds acquired by DOE's Advanced Simulation and Computing program. Porting large-scale applications to these testbeds is prohibitive in labor and time. Instead, it is more advantageous to run small-scale programs that capture the essence of the large-scale application and that can be more easily modified, improved, and distributed to other collaborators focused on hardware/software co-design. These small-scale applications are called miniapps are are being developed under the aegis of the Mantevo project.", + "laborHours": 6490.4, + "languages": [ + "C", + "Fortran", + "Python" + ], + "name": "miniSMAC2D", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniSMAC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This particular consortium implementation of the software integration infrastructure will, in large part, refactor portions of the Rocstar multiphysics infrastructure. Development of this infrastructure originated at the University of Illinois DOE ASCI Center for Simulation of Advanced Rockets (CSAR) to support the center's massively parallel multiphysics simulation application, Rocstar, and has continued at IllinoisRocstar, a small company formed near the end of the University-based program. IllinoisRocstar is now licensing these new developments as free, open source, in hopes to help improve their own and others' access to infrastructure which can be readily utilized in developing coupled or composite software systems; with particular attention to more rapid production and utilization of multiphysics applications in the HPC environment. There are two major pieces to the consortium implementation, the Application Component Toolkit (ACT), and the Multiphysics Application Coupling Toolkit (MPACT). The current development focus is the ACT, which is (will be) the substrate for MPACT. The ACT itself is built up from the components described in the technical approach. In particular, the ACT has the following major components: 1.The Component Object Manager (COM): The COM package provides encapsulation of user applications, and their data. COM also provides the inter-component function call mechanism. 2.The System Integration Manager (SIM): The SIM package provides constructs and mechanisms for orchestrating composite systems of multiply integrated pieces.", + "laborHours": 113452.8, + "name": "Multiphysics Application Coupling Toolkit", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IllinoisRocstar/IMPACT", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Framework for Network Co-Simulation (FNCS) uses a federated approach to integrate simulations which may have differing time scales. Special consideration is given to integration with a communication network simulation such that inter-simulation messages may be optionally routed through and delayed by such a simulation. In addition, FNCS uses novel time synchronization algorithms to accelerate co-simulation including the application of speculative multithreading. FNCS accomplishes all of these improvements with minimal end user intervention. Simulations can be integrated using FNCS while maintaining their original model input files simply by linking with the FNCS library and making appropriate calls into the FNCS API.", + "laborHours": 38592.8, + "name": "Framework for Network Co-Simulation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/FNCS/fncs/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FNCS/fncs", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This library is an implementation of the Sparse Approximate Matrix Multiplication (SpAMM) algorithm introduced. It provides a matrix data type, and an approximate matrix product, which exhibits linear scaling computational complexity for matrices with decay. The product error and the performance of the multiply can be tuned by choosing an appropriate tolerance. The library can be compiled for serial execution or parallel execution on shared memory systems with an OpenMP capable compiler", + "laborHours": 588726.4, + "name": "spammpack, Version 2013-06-18", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FreeON/spammpack", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The Multiphysics Object Oriented Simulation Environment (MOOSE) software library developed at Idaho National Laboratory is a tool. MOOSE, like other tools, doesn't actually complete a task. Instead, MOOSE seeks to reduce the effort required to create engineering simulation applications. MOOSE itself is a software library: a blank canvas upon which you write equations and then MOOSE can help you solve them. MOOSE is comparable to a spreadsheet application. A spreadsheet, by itself, doesn't do anything. Only once equations are entered into it will a spreadsheet application compute anything. Such is the same for MOOSE. An engineer or scientist can utilize the equation solvers within MOOSE to solve equations related to their area of study. For instance, a geomechanical scientist can input equations related to water flow in underground reservoirs and MOOSE can solve those equations to give the scientist an idea of how water could move over time. An engineer might input equations related to the forces in steel beams in order to understand the load bearing capacity of a bridge. Because MOOSE is a blank canvas it can be useful in many scientific and engineering pursuits.", + "laborHours": 1085021.6, + "languages": [], + "name": "Multiphysics Object Oriented Simulation Environment", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/moose", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GridOPTICS Software System (GOSS) is a middleware that facilitates creation of new, modular and flexible operational and planning platforms that can meet the challenges of the next generation power grid. GOSS enables Department of Energy, power system utilities, and vendors to build better tools faster. GOSS makes it possible to integrate Future Power Grid Initiative software products/prototypes into existing power grid software systems, including the PNNL PowerNet and EIOC environments. GOSS is designed to allow power grid applications developed for different underlying software platforms installed in different utilities to communicate with ease. This can be done in compliance with existing security and data sharing policies between the utilities. GOSS not only supports one-to-one data transfer between applications, but also publisher/subscriber scheme. To support interoperability requirements of future EMS, GOSS is designed for CIM compliance. In addition to this, it supports authentication and authorization capabilities to protect the system from cyber threats. In summary, the contributions of the GOSS middleware are as follows: A platform to support future EMS development. A middleware that promotes interoperability between power grid applications. A distributed architecture that separates data sources from power grid applications. Support for data exchange with either one-to-one or publisher/subscriber interfaces. An authentication and authorization scheme for limiting the access to data between utilities.", + "laborHours": 27724.8, + "name": "GridOPTICS Software System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/craig8/GOSS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Support Vector Machines (SVM) is a popular machine learning technique, which has been applied to a wide range of domains such as science, finance, and social networks for supervised learning. MaTEx undertakes the challenge of designing a scalable parallel SVM training algorithm for large scale systems, which includes commodity multi-core machines, tightly connected supercomputers and cloud computing systems. Several techniques are proposed for improved speed and memory space usage including adaptive and aggressive elimination of samples for faster convergence , and sparse format representation of data samples. Several heuristics for earliest possible to lazy elimination of non-contributing samples are considered in MaTEx. In many cases, where an early sample elimination might result in a false positive, low overhead mechanisms for reconstruction of key data structures are proposed. The proposed algorithm and heuristics are implemented and evaluated on various publicly available datasets", + "laborHours": 647474.4, + "name": "Machine Learning Toolkit for Extreme Scale", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/matex-org/matex/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/matex-org/matex", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Modern processors offer a wide range of control and measurement features. While those are traditionally accessed through libraries like PAPI, some newer features no longer follow the traditional model of counters that can be used to only read the state of the processor. For example, Precise Event Based Sampling (PEBS) can generate records that requires a kernel memory for storage. Additionally, new features like power capping and thermal control require similar new access methods. All of these features are ultimately controlled through Model Specific Registers (MSRs). We therefore need new mechanisms to make such features available to tools and ultimately to the user. libMSR provides a convenient interface to access MSRs and to allow tools to utilize their full functionality.", + "laborHours": 6232.0, + "name": "libMSR library and msr-safe kernel module", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/libmsr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This package inplements a Lua interface to linux containers system calls, such as unshare(2) and chroot(2)", + "laborHours": 0.0, + "name": "Lua modules for linux containers", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/grondo/lua-containers", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This package implements a Lua interface to the LLNL hostlist routines, and includes a hostlist command oine utility based on the lua hostlist library.", + "laborHours": 1930.4, + "name": "Luna Hostlist Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/grondo/lua-hostlist", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "AutomaDeD is a tool that automatically diagnoses performance and correctness faults in MPI applications. It creates time and control-flow models of processes in an MPI program, and when a failure occus, these models are analyzed probabilistically to find the origin of the failure. The output of the tool is MPI processes ranked by the abnormality degree and regions of code where faults are first manifested. The granularity of code region is an MPI call or a computation region between two MPI calls.", + "laborHours": 6308.0, + "name": "Automata-based Debugging for Dissimilar Parallel Tasks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/automaDeD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The \"Callpath Library\" is a software abstraction layer over a number of stack tracing utilities. It allows tool develoopers to conveniently represent and mNipulate call paths gathered fro U. Wisconsin's Stackwalker API and GNU Backtrace.", + "laborHours": 699.2, + "name": "Callpath Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/callpath", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "perf-dump is a library for dumping performance data in much the same way physics simulations dump checkpoints. It records per-process, per-timestep, per-phase, and per-thread performance counter data and dumps this large data periodically into an HDF5 data file.", + "laborHours": 334.4, + "name": "perf-dump", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/perf-dump", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-02-09" + }, + "description": "The HPC software ecosystem is growing larger and more complex, but software distribution mechanisms have not kept up with this trend. Tools, Libraries, and applications need to run on multiple platforms and build with multiple compliers. Increasingly, packages leverage common software components, and building any one component requires building all of its dependencies. In HPC environments, ABI-incompatible interfaces (likeMPI), binary-incompatible compilers, and cross-compiled environments converge to make the build process a combinatoric nightmare. This obstacle deters many users from adopting useful tools, and others waste countless hours building and rebuilding tools. Many package managers exist to solve these problems for typical desktop environments, but none suits the unique needs of supercomputing facilities or users. To address these problems, we have Spack, a package manager that eases the task of managing software for end-users, across multiple platforms, package versions, compilers, and ABI incompatibilities.", + "laborHours": 169312.8, + "languages": [], + "name": "Spack: the Supercomputing Package Manager", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spack/spack", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Fast Global File Status (FGFS) is a system software package that implimints a scalable mechanism to retrieve file information, such as its degree of distribution or replication and consistency.", + "laborHours": 6186.4, + "name": "Fast Global File Status", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/fastglobalfilestatus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MPI_T is an interface for tools introduced in the 3.0 version of MPI. The interface provides mechanisms for tools to access and set performance and control variables that are exposed by an MPI implementation. We have developed an MPI_T tool suite to provide a first set of tools exploiting the new interface and to get tool writers started on the path to more sophisticated support.", + "laborHours": 1033.6, + "name": "The LLNL MPI_Tool Suite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/mpi-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-07-23" + }, + "description": "UPC++ is a Partitioned Global Address Space (PGAS) extension for C++, with three main objectives: 1) to provide an object-oriented PGAS programming model in the context of the popular C++ language; 2) to add useful parallel programming idioms unavailable in UPC, such as asynchronous remote function invocation and multidimensional arrays, to support complex scientific applications; 3) to offer an easy on-ramp to PGAS programming through interoperability with other existing parallel programming systems (e.g., MPI, OpenMP, CUDA). UPC++ includes two main features beyond UPC: 1) One of the major limitations of UPC in the context of DOE application is the relatively weak notion of multidimensional arrays, which it inherited from C. To remedy this problem in UPC++, we included a multidimensional domain and array library based on that of Titanium. Titanium's library is similar to Chapel's dense and strided domains, as both were inspired by the dense and strided regions and arrays in ZPL. 2) Another feature provided by UPC++ but not by UPC is remote function invocation, which is inspired by Phalanx, X10, Habanero-C, and C++11. The user may start an asynchronous remote function invocation with the following syntax: \"async(place)(function, args...);\". UPC++ provides two programming constructs for specifying dynamic dependencies among tasks: 1) event-driven execution as in Phalanx and Habanero-C; 2) finish-async as in X10. We implemented UPC++ with a \"compiler-free\" approach using C++ templates and runtime libraries. The UPC++ front-end consists of a set of C++ header files that enables the C++ compiler to \"translate\" UPC++ features in a user program to runtime library calls. In particular, we use templates and operator overloading to customize the behavior of UPC++ types.\n\nThis software package has been replaced with UPCC++ V 1.0", + "laborHours": 20702.4, + "languages": [], + "name": "UPC++", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/berkeleylab/upcxx/src/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upcxx.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The SEED platform is expected to be a building energy performance data management tool that provides federal, state and local governments, building owners and operators with an easy, flexible and cost-effective method to collect information about groups of buildings, oversee compliance with energy disclosure laws and demonstrate the economic and environmental benefits of energy efficiency. It will allow users to leverage a local application to manage data disclosure and large data sets without the IT investment of developing custom applications. The first users of SEED will be agencies that need to collect, store, and report/share large data sets generated by benchmarking, energy auditing, retro-commissioning or retrofitting of many buildings. Similarly, building owners and operators will use SEED to manage their own energy data in a common format and centralized location. SEED users will also control the disclosure of their information for compliance requirements, recognition programs such as ENERGY STAR, or data sharing with the Buildings Performance Database and/or other third parties at their discretion.", + "laborHours": 81031.2, + "name": "Standard Energy Efficiency Data Platform", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/SEED-platform/seed/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SEED-platform/seed", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Hone sensors are packet-process correlation engines that log the relationships between applications and the communications they are responsible for. Hone sensors are available for a variety of platforms including Linux, Windows, and MacOSX. Hone sensors are designed to help analysts understand the meaning of communications on a deeper level by associating the origin or destination process to the communication. They do this by tracing communications on a per-packet basis, through the kernel of the operating system to determine their ultimate source/destination on the monitored machine.", + "laborHours": 3252.8, + "name": "The Open Host Network Packet Process Correlator for Windows", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/HoneProject/Windows-Sensor/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HoneProject/Windows-Sensor", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The ADARA software is a collection of programs which gather neutron scattering data from multiple detector banks, multiplex the data into a single stream and distribute that stream to analysis, reduction and translation utilities in real-time.", + "laborHours": 26280.8, + "name": "ADARA", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ADARA-Neutrons/adara", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Set of scripts (Python and Bash) to help users configure, run, and benchmark Hadoop clusters on ORNL computing infrastructure.", + "laborHours": 304.0, + "name": "Spot-Hadoop", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jhorey/SpotHadoop", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Data reduction software for the Oak Ridge National Laboratory Spallation Neutron Source's Magnetism Reflectometer beam line 4A, used to extract reflectivity, off-specular and GISANS scattering from raw data in NeXus file format. The package consists of a Python library for the extraction and a Qt4 based graphical user interface to work with the data.", + "laborHours": 31631.2, + "name": "QuickNXS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aglavic/quicknxs", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Chisel is a new open-source hardware construction language developed at UC Berkeley that supports advanced hardware design using highly parameterized generators and layered domain-specific hardware languages. Chisel is embedded in the Scala programming language, which raises the level of hardware design abstraction by providing concepts including object orientation, functional programming, parameterized types, and type inference. From the same source, Chisel can generate a high-speed C++-based cycle-accurate software simulator, or low-level Verilog designed to pass on to standard ASIC or FPGA tools for synthesis and place and route.", + "laborHours": 16233.6, + "name": "Constructing Hardware in a Scale Embedded Language", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ucb-bar/chisel/blob/master/src/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ucb-bar/chisel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Recent advancements in technology scaling have shown a trend towards greater integration with large-scale chips containing thousands of processors connected to memories and other I/O devices using non-trivial network topologies. Software simulation proves insufficient to study the tradeoffs in such complex systems due to slow execution time, whereas hardware RTL development is too time-consuming. We present OpenSoC Fabric, an on-chip network generation infrastructure which aims to provide a parameterizable and powerful on-chip network generator for evaluating future high performance computing architectures based on SoC technology. OpenSoC Fabric leverages a new hardware DSL, Chisel, which contains powerful abstractions provided by its base language, Scala, and generates both software (C++) and hardware (Verilog) models from a single code base. The OpenSoC Fabric2 infrastructure is modeled after existing state-of-the-art simulators, offers large and powerful collections of configuration options, and follows object-oriented design and functional programming to make functionality extension as easy as possible.", + "laborHours": 2888.0, + "name": "OpenSoC Fabric", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LBL-CoDEx/OpenSoCFabric/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-CoDEx/OpenSoCFabric", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kindrew@jlab.org" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This library provides a library containing highly optimized Wilson-Dslash, Wilson Clover operator and Krylov subspace solvers for Lattice QCD simulations. The library is targeted at Intel(R) Xeon Phi(tm), and Intel(R) Xeon(tm) processors.", + "laborHours": 70041.6, + "name": "QCD For Intel(R) Xeon Phi(tm) and Xeon(tm) processors", + "organization": "Thomas Jefferson National Accelerator Facility (TJNAF)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/JeffersonLab/qphix/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JeffersonLab/qphix.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Thomas Jefferson National Accelerator Facility (TJNAF)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A series of software programs that enables students to progress from completely unsecured control of devices to control that protects network commands with authentication, integrity and confidentiality. The working example provided is for turning LED lights on and off on a Raspberry Pi computer.", + "laborHours": 304.0, + "name": "CyPhyTown", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNLgov/cyPhyTown/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNLgov/cyPhyTown", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"The soft costs of solar — costs not associated with hardware — remain stubbornly high. Among the biggest soft costs are those associated with inefficiencies in local permitting and inspection. A study by the National Renewable Energy Laboratory and Lawrence Berkeley National Laboratory estimates that these costs add an average of $0.22/W per residential installation. This project helps reduce non-hardware/balance of system (BOS) costs by creating and maintaining a free and available site of permitting requirements and solar system verification software that installers can use to reduce time, capital, and resource investments in tracking permitting requirements. Software tools to identify best permitting practices can enable government stakeholders to optimize their permitting process and remove superfluous costs and requirements. Like \"\"a Wikipedia for solar permitting\"\", users can add, edit, delete, and update information for a given jurisdiction. We incentivize this crowdsourcing approach by recognizing users for their contributions in the form of SEO benefits to their company or organization by linking back to users' websites.\"", + "laborHours": 113817.6, + "name": "The National Solar Permitting Database", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/solarpermit/solarpermit", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "procmon performs large-scale monitoring, data collection, and analysis of user processes running on Linux systems. It is intended to be used to aid in performing an automated workload analysis of very large scale systems, but may also be useful for live monitoring of the running processes on large scale systems.", + "laborHours": 17358.4, + "name": "procmon", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/berkeleylab/nersc-procmon/src/c6e67d63e7c9c24f85a46b6d8965b8c615097edc/LICENSE?at=master&fileviewer=file-view-default", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/nersc-procmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "F3D is written in OpenCL, so it achieve[sic] platform-portable parallelism on modern mutli-core CPUs and many-core GPUs. The interface and mechanims to access F3D core are written in Java as a plugin for Fiji/ImageJ to deliver several key image-processing algorithms necessary to remove artifacts from micro-tomography data. The algorithms consist of data parallel aware filters that can efficiently utilizes[sic] resources and can work on out of core datasets and scale efficiently across multiple accelerators. Optimizing for data parallel filters, streaming out of core datasets, and efficient resource and memory and data managements over complex execution sequence of filters greatly expedites any scientific workflow with image processing requirements. F3D performs several different types of 3D image processing operations, such as non-linear filtering using bilateral filtering and/or median filtering and/or morphological operators (MM). F3D gray-level MM operators are one-pass constant time methods that can perform morphological transformations with a line-structuring element oriented in discrete directions. Additionally, MM operators can be applied to gray-scale images, and consist of two parts: (a) a reference shape or structuring element, which is translated over the image, and (b) a mechanism, or operation, that defines the comparisons to be performed between the image and the structuring element. This tool provides a critical component within many complex pipelines such as those for performing automated segmentation of image stacks. F3D is also called a \"descendent\" of Quant-CT, another software we developed in the past. These two modules are to be integrated in a next version. Further details were reported in: D.M. Ushizima, T. Perciano, H. Krishnan, B. Loring, H. Bale, D. Parkinson, and J. Sethian. Structure recognition from high-resolution images of ceramic composites. IEEE International Conference on Big Data, October 2014.", + "laborHours": 1869.6, + "name": "F3D Image Processing and Analysis for Many - and Multi-core Platforms", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/CameraIA/F3D/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CameraIA/F3D", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This Drupal metadata and documents capture and management system is a repository, used for maintenance of metadata which describe resources contributed to the AASG State Geothermal Data System. The repository also provides an archive for files that are not hosted by the agency contributing the resource. Data from all 50 state geological surveys is represented here, and is contributed in turn to the National Geothermal Data System.", + "laborHours": 6444.8, + "name": "AASG State Geothermal Data Repository for the National Geothermal Data System.", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/metadata-repository", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is an adaptation of the pre-existing Scimark benchmark code to a variety of Python and Lua implementations. It also measures performance of the Fparser expression parser and C and C++ code on a variety of simple scientific expressions.", + "laborHours": 5654.4, + "name": "Python/Lua Benchmarks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/lebusby/splb/src/e1b801db07cbb8fd0eab2a50fdb3b1f25906fbef/Copyright", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/lebusby/splb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GRAPE is a tool for managing software project workflows for the Git version control system. It provides a suite of tools to simplify and configure branch based development, integration with a project's testing suite, and integration with the Atlassian Stash repository hosting tool.", + "laborHours": 15139.2, + "name": "Git Replacement for the", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/GRAPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Hardware advancements such as Intel's PEBS and AMD's IBS, as well as software developments such as the perf_event API in Linux have made available the acquisition of memory access samples with performance information. MemAxes is a visualization and analysis tool for memory access sample data. By mapping the samples to their associated code, variables, node topology, and application dataset, MemAxes provides intuitive views of the data.", + "laborHours": 5198.4, + "name": "MemAxes Visualization Software", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/scalability-llnl/MemAxes", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "ZFP is a library for lossy compression of single- and double-precision floating-point data. One of the unique features of ZFP is its support for fixed-rate compression, which enables random read and write access at the granularity of small blocks of values. Using a C++ interface, this allows declaring compressed arrays (1D, 2D, and 3D arrays are supported) that through operator overloading can be treated just like conventional, uncompressed arrays, but which allow the user to specify the exact number of bits to allocate to the array. ZFP also has variable-rate fixed-precision and fixed-accuracy modes, which allow the user to specify a tolerance on the relative or absolute error.", + "laborHours": 9272.0, + "languages": [], + "name": "Fixed-rate compressed floating-point arrays", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/zfp/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ZFP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Large-scale systems like Sequoia allow running small numbers of very large (1M+ process) jobs, but their resource managers and schedulers do not allow large numbers of small (4, 8, 16, etc.) process jobs to run efficiently. Cram is a tool that allows users to launch many small MPI jobs within one large partition, and to overcome the limitations of current resource management software for large ensembles of jobs.", + "laborHours": 1824.0, + "name": "Cram", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/scalability-llnl/cram", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OpenSHMEM is a community effort to unifyt and standardize the SHMEM programming model. MPI (Message Passing Interface) is a well-known community standard for parallel programming using distributed memory. The most recen t release of MPI, version 3.0, was designed in part to support programming models like SHMEM.OSHMPI is an implementation of the OpenSHMEM standard using MPI-3 for the Linux operating system. It is the first implementation of SHMEM over MPI one-sided communication and has the potential to be widely adopted due to the portability and widely availability of Linux and MPI-3. OSHMPI has been tested on a variety of systems and implementations of MPI-3, includingInfiniBand clusters using MVAPICH2 and SGI shared-memory supercomputers using MPICH. Current support is limited to Linux but may be extended to Apple OSX if there is sufficient interest. The code is opensource via https://github.com/jeffhammond/oshmpi", + "laborHours": 15291.2, + "name": "OpenSHMEM over MPI-3", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeffhammond/oshmpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This program is a graphical user interface for measuring and performing inter-active analysis of physical unclonable functions (PUFs). It is intended for demonstration and education purposes. See license.txt for license details. The program features a PUF visualization that demonstrates how signatures differ between PUFs and how they exhibit noise over repeated measurements. A similarity scoreboard shows the user how close the current measurement is to the closest chip signatures in the database. Other metrics such as average noise and inter-chip Hamming distances are presented to the user. Randomness tests published in NIST SP 800-22 can be computed and displayed. Noise and inter-chip histograms for the sample of PUFs and repeated PUF measurements can be drawn.", + "laborHours": 2082.4, + "name": "Sandia PUF Analysis Tool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Domi (Greek for \"structure\") is a Trilinos package that provides support for multi-dimensional data arrays distributed over multiple processors of a high performance computing system. The software supports data arrays of arbitrary number of dimensions mapped to a multi-dimensional grid of processors. Domi provides local access to the data, as well as the ability to compute global quantities such as norms, maxima and minima. Data arrays can be constructed with boundary and communication padding, necessary for finite difference algorithms, and provides high-level methods for communicating data between processors to update these buffers. The distributed maps and vectors in Domi can be converted to the equivalent data structures in Epetra and Tpetra (both of which assume unstructured data), using view semantics when appropriate, for use with other Trilinos solvers.", + "laborHours": 10336.0, + "languages": [ + "CMake", + "C++" + ], + "name": "Domi", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Domi/blob/main/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Domi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software serves two purposes. The first purpose of the software is to prototype the Sandia High Performance Computing Power Application Programming Interface Specification effort. The specification can be found at http://powerapi.sandia.gov . Prototypes of the specification were developed in parallel with the development of the specification. Release of the prototype will be instructive to anyone who intends to implement the specification. More specifically, our vendor collaborators will benefit from the availability of the prototype. The second is in direct support of the PowerInsight power measurement device, which was co-developed with Penguin Computing. The software provides a cluster wide measurement capability enabled by the PowerInsight device. The software can be used by anyone who purchases a PowerInsight device. The software will allow the user to easily collect power and energy information of a node that is instrumented with PowerInsight. The software can also be used as an example prototype implementation of the High Performance Computing Power Application Programming Interface Specification.", + "laborHours": 40462.4, + "languages": [ + "C++", + "Shell", + "C", + "SWIG", + "Makefile", + "M4", + "Roff" + ], + "name": "Power API Prototype", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/power-api", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "The Percept software package is a collection of libraries and executables that provide tools for verifying computer simulations of engineering components and systems. Percept is useful for simulations using the finite element or finite volume methods on unstructured meshes. Percept includes API's for adaptive mesh refinement, geometry representation, the method of manufactured solutions, analysis of convergence including the convergence of vibrational eigenmodes, and metrics for analyzing the difference between fields represented on two different overlapping unstructured grids.", + "laborHours": 99560.0, + "languages": [ + "Mathematica", + "C++", + "Shell", + "C", + "CMake", + "Python" + ], + "name": "Percept", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/percept", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "WEC-Sim (Wave Energy Converter SIMulator) is a code developed by Sandia National Laboratories and the National Renewable Energy Laboratory to model wave energy converters (WECs) when they are subject to operational waves. The code is a time-domain modeling tool developed in MATLAB/Simulink using the multi-body dynamics solver SimMechanics. In WEC-Sim, WECs are modeled by connecting rigid bodies to one another with joint or constraint blocks from the WEC-Sim library. WEC-Sim is a publicly available, open-source code to model WECs.", + "laborHours": 3131.2, + "name": "WEC-Sim (Wave Energy Converter - SIMulator)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WEC-Sim/WEC-Sim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This software provides implementations of fast matrix multiplication algorithms. These algorithms perform fewer floating point operations than the classical cubic algorithm. The software uses code generation to automatically implement the fast algorithms based on high-level descriptions. The code serves two general purposes. The first is to demonstrate that these fast algorithms can out-perform vendor matrix multiplication algorithms for modest problem sizes on a single machine. The second is to rapidly prototype many variations of fast matrix multiplication algorithms to encourage future research in this area. The implementations target sequential and shared memory parallel execution.", + "laborHours": 79724.0, + "languages": [ + "Objective-C", + "C++", + "Shell", + "Roff", + "MATLAB", + "Python" + ], + "name": "fast-matmul", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fast-matmul", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SCOT cyber security team enhancement tool that coordinates activities, captures knowledge, and serves as a platform to automate time-consuming tasks that a cyber security team needs to perform in its daily operations.", + "laborHours": 370393.6, + "name": "Sandia Cyber Omni Tracker", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/scot/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/scot", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Oxide is a modular framework for feature extraction and analysis of executable files. Oxide is useful in a variety of reverse engineering and categorization tasks relating to executable content.", + "laborHours": 10244.8, + "languages": [ + "Python" + ], + "name": "Oxide", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Oxide", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Doubly Distributed Transactions (D2T) offers a technique for managing operations from a set of parallel clients with a collection of distributed services. It detects and manages faults. 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The targeted usage of this module is for non-NW applications that support work-for-others in the multiphysics energy sector.", + "laborHours": 50388.0, + "name": "Nalu", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/spdomin/Nalu/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spdomin/Nalu", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is a Python API for interacting with USGIN Content Models.", + "laborHours": 243.2, + "name": "USGIN content models API", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/usginmodels/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/usginmodels", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is a Python API for interacting with USGIN Content Models.", + "laborHours": 4636.0, + "name": "Content Model Validator", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/ContentModelCMS/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/ContentModelCMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This site allows state data contributors to standardize their data in a USIGN content model, ensure that it meets all specifications, reprojects spatial data, and creates a geodatabase that is ready for web services deployment for tier 3 data.", + "laborHours": 5608.8, + "name": "Excel to NGDS Services Tool", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/ExcelToNGDSServiceTool", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Django application providing a user-interface for building a file and metadata management system. 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Also provides batch and real-time controllers which step the model and 1/0 through the time domain (or other discrete domain), and sample 1/0 drivers. This is a Framework library framework, and does not, itself, solve any problems or execute any modelling. The SeMe framework aids in development of models which operate on sequential information, such as time-series, where evaluation is based on prior results combined with new data for this iteration. Ha) applications in quality monitoring, and was developed as part of the CANARY-EDS software, where real-time water quality data is being analyzed", + "laborHours": 4772.8, + "languages": [ + "Java", + "Perl", + "HTML", + "TeX" + ], + "name": "Sequentially Executed Model Evaluation Framework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seme-framework", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SVF is a full featured OpenGL 3d framework that allows for rapid creation of complex visualizations. 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Some simple shapes (actors) are already created for you such as text, bordered text, radial text, text area, complex paths, NURBS paths, cube, disk, grid, plane, geometric shapes, and volumetric area. It also comes with various camera types for viewing that can be dragged, zoomed, and rotated. Picking or selecting items in the scene can be accomplished in various ways depending on your needs (raycasting or color picking.) The framework currently has functionality for tooltips, animation, actor pools, color gradients, 2d physics, text, 1d/2d/3d textures, children, blending, clipping planes, view frustum culling, custom shaders, and custom actor states", + "laborHours": 41602.4, + "name": "Sci-Vis Framework", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/svf/blob/master/svf-core/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/svf", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The FireHose Streaming Benchmarks are a suite of stream-processing benchmarks defined to enable comparison of streaming software and hardware, both quantitatively vis-a-vis the rate at which they can process data, and qualitatively by judging the effort involved to implement and run the benchmarks. Each benchmark has two parts. The first is a generator which produces and outputs datums at a high rate in a specific format. The second is an analytic which reads the stream of datums and is required to perform a well-defined calculation on the collection of datums, typically to find anomalous datums that have been created in the stream by the generator. The FireHose suite provides code for the generators, sample code for the analytics (which users are free to re-implement in their own custom frameworks), and a precise definition of each benchmark calculation.", + "laborHours": 2964.0, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "Python" + ], + "name": "FireHose Streaming Benchmarks", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/firehose", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "miniAMR is a \"miniapp\" which will be added to the Mantevo project. It provides a platform to experiment with different aspects of Adaptive Mesh Refinement (AMR). The calculations are performed on random data and the refinement is driven by simple objects moving through the mesh, so no real problem is solved. By having a small code that runs quickly, we can use to study different aspects of AMR and easily port the code to new testbed machines", + "laborHours": 10989.6, + "languages": [ + "Makefile", + "C" + ], + "name": "miniAMR", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniAMR", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.9" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "PathFinder is a graph search program, traversing a directed cyclic graph to find pathways between labeled nodes. Searches for paths through ordered sequences of labels are termed signatures. Determining the presence of signatures within one or more graphs is the primary function of Path Finder. Path Finder can work in either batch mode or interactively with an analyst. Results are limited to Path Finder whether or not a given signature is present in the graph(s).", + "laborHours": 7630.4, + "languages": [ + "Standard ML", + "ABC", + "Python" + ], + "name": "Path Finder", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PathFinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-05-14" + }, + "description": "This is an implementation of a VTK class that can read data from an ADIOS file. Specifically, it interprets a schema embedded in the attributes of the ADIOS metadata to determine the structure of the data.", + "laborHours": 767204.8, + "languages": [], + "name": "ADIOS Schema reader for VTK", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/paraview/paraview", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SpawnNet provides a networking interface similar to Linux sockets that runs natively on High-performance network interfaces. It is intended to be used to bootstrap parallel jobs and communication libraries like MPI.", + "laborHours": 8436.0, + "name": "SpawnNet", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/spawnnet/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/spawnnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CombAlign is a new Python code that generates a gapped, one-to-many, multiple structure-based sequence alignment(MSSA) given a set of pairwise structure-based alignments. In order to better define regions of similarity among related protein structures, it is useful to detect the residue-residue correspondences among a set of pairwise structure alignments. Few codes exist for constructing a one-to-many, multiple sequence alignment derived from a set of structure alignments, and we perceived a need for creating a new tool for combing pairwise structure alignments that would allow for insertion of gaps in the reference structure.", + "laborHours": 243.2, + "name": "Combining Multiple Pairwise Structure-based Alignments", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/Protein", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "IBTopo is a set of perl modules and scripts that enable one to determine the network topology of an Infiniband network.", + "laborHours": 304.0, + "name": "IBTopo", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/ibtopo/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/ibtopo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ParFELAG is a parallel distributed memory C++ library for numerical upscaling of finite element discretizations. It provides optimal complesity algorithms ro build multilevel hierarchies and solvers that can be used for solving a wide class of partial differential equations (elliptic, hyperbolic, saddle point problems) on general unstructured mesh (under the assumption that the topology of the agglomerated entities is correct). Additionally, a novel multilevel solver for saddle point problems with divergence constraint is implemented.", + "laborHours": 31600.8, + "name": "Parallel Element Agglomeration Algebraic Multigrid and Upscaling Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/parelag", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Compare Gene Profiles (CGP) performs pairwise gene content comparisons among a relatively large set of related bacterial genomes. CGP performs pairwise BLAST among gene calls from a set of input genome and associated annotation files, and combines the results to generate lists of common genes, unique genes, homologs, and genes from each genome that differ substantially in length from corresponding genes in the other genomes. CGP is implemented in Python and runs in a Linux environment in serial or parallel mode.", + "laborHours": 1763.2, + "name": "Compare Gene Profiles", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/Genome", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Qspp is an agent-based stochastic simulation model of the Poliovirus Sabin-to-Mahoney transition. This code simulates a cell-to-cell model of Poliovirus replication. The model tracks genotypes (virus genomes) as they are replicated in cells, and as the cells burst and release particles into the medium of a culture dish. An inoculum is then taken from the pool of virions and is used to inoculate cells on a new dish. This process repeats. The Sabin genotype comprises the initial inoculum. Nucleotide positions that match the Sabin1 (vaccine strain) and Mahoney (wild type) genotypes, as well as the neurovirulent phenotype (from the literature) are enumerated as constants.", + "laborHours": 1915.2, + "name": "Sabin-to-Mahoney Transition Model of Quasispecies Replication", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/Virus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "ROL provides interfaces to and implementations of algorithms for gradient-based unconstrained and constrained optimization. ROL can be used to optimize the response of any client simulation code that evaluates scalar-valued response functions. If the client code can provide gradient information for the response function, ROL will take advantage of it, resulting in faster runtimes. ROL's interfaces are matrix-free, in other words ROL only uses evaluations of scalar-valued and vector-valued functions. ROL can be used to solve optimal design problems and inverse problems based on a variety of simulation software.", + "laborHours": 8344830.4, + "languages": [], + "name": "Rapid Optimization Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Python-ARM Radar Toolkit (Py-ART) is a collection of radar quality control and retrieval codes which all work on two unifying Python objects: the PyRadar and PyGrid objects. By building ingests to several popular radar formats and then abstracting the interface Py-ART greatly simplifies data processing over several other available utilities. In addition Py-ART makes use of Numpy arrays as its primary storage mechanism enabling use of existing and extensive community software tools.", + "laborHours": 159980.0, + "name": "Python-ARM Radar Toolkit", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/pyart", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2022-03-28" + }, + "description": "This is a general purpose math library implementing basic tensor algebra operations on NVidia GPU accelerators. This software is a tensor algebra library that can perform basic tensor algebra operations, including tensor contractions, tensor products, tensor additions, etc., on NVidia GPU accelerators, asynchronously with respect to the CPU host. It supports a simultaneous use of multiple NVidia GPUs. Each asynchronous API function returns a handle which can later be used for querying the completion of the corresponding tensor algebra operation on a specific GPU. The tensors participating in a particular tensor operation are assumed to be stored in local RAM of a node or GPU RAM. The main research area where this library can be utilized is the quantum many-body theory (e.g., in electronic structure theory).", + "laborHours": 19258.4, + "languages": [], + "name": "Tensor Algebra Library for NVidia Graphics Processing Units", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DmitryLyakh/TAL_SH", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SHOMS is a micro benchmark designed to test vendor implementations of the OpenSHMEM 1.1 spec. It seeks to test both bandwidth and latencies for small and large messages.", + "laborHours": 1276.8, + "name": "SHOMS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MattBBaker/shoms", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "STONIX is a program for configuring UNIX and Linux computer operating systems. It applies configurations based on the guidance from publicly accessible resources such as: NSA Guides, DISA STIGs, the Center for Internet Security (CIS), USGCB and vendor security documentation. STONIX is written in the Python programming language using the QT4 and PyQT4 libraries to provide a GUI. The code is designed to be easily extensible and customizable.", + "laborHours": 56878.4, + "name": "Stonix, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CSD-Public/stonix", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "brulilo is a Python package for building and evolving thermonuclear reaction networks, such as those used in astrophysical explosion calculations. It is very much a current work in progress, and much of the intended functionality is still under development. The main goal of brulilo is an easy-to-use code for quick calculations or post-processing, as well as a learning tool to test various implementations of solvers on both CPUs and GPUs. Currently, brulilo parses an input text file that specifies the reactions to be included in the network. The notation of the inputs are in the typical astrophysical notation; i.e. hydrogen burning to deuterium in the sun, \"p + p + e --> d + neutrino\", is given as \"p(p,)d.\" Each reaction is added to a list comprising the reaction network, and once completed, the network contains a list of all isotopes and reactions involved. brulilo then parses publicly available nuclear data (binding energy, spin, partition function data, etc.) for each isotope from the WebNucleo group's data at nucleo.ces.clemson.edu. Fits to reaction rate data for each reaction are obtained from the publicly available data provided by the Joint Institute for Nuclear Astrophysics' Reaclib database. Reverse reactions are calculated from detailed balance. The reaction network then consists of a sparse system of mathematically stiff ordinary differential equations (ODEs). Physically, \"stiffness\" here means that there are some reaction rates that are occurring much faster than others; the ratio of the fast to slow often being greater than 10^15 in astrophysics. Numerical integration of such systems typically involves implicit integration schemes, which brulilo will leverage from the scientific computing Python package, Numpy, as well as implement its own. There has recently been work from researchers at Oak Ridge National Lab who have found good results from applying quasi-equilibrium and quasi-asymptotic conditions to the stiff system of ODEs, which effectively remove some of the stiffness and allow for efficient explicit integration techniques to be used. The original intent of brulilo was to implement these stiffness-alleviating techniques with explicit integrators and compare the performance to traditional implicit integrations of the full stiff system. This is still underway, as the code is very much in an alpha-release state. Furthermore, explicit integrators are often much easier to parallelize than their implicit counterparts. brulilo will implement parallelization of these techniques, leveraging both the Python implementation of MPI, mpi4py, as well as highly parallelized versions targeted at GPUs with PyOpenCL and/or PyCUDA.", + "laborHours": 1743379.2, + "name": "brulilo, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cmsquared/brulilo/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmsquared/brulilo", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The intent of the software is eventually to become a middleware library to provide a cross platform interface for creating and managing a ramdisk. Eventually it will cover many platforms (*nix, Windows, Mac), and have the library written in several languages. At this point, the library is a functional python library for managing a Mac ramdisk. Some code is also included in how to use the library. Initial intended uses for the library: archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Provide a throw-away filesystem for unit testing filesystem related functionality. archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Improve compile time when building software.", + "laborHours": 3754.4, + "name": "ramdisk, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csd-dev-tools/ramdisk", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MATK provides basic functionality to facilitate model analysis within the Python computational environment. Model analysis setup within MATK includes: - define parameters - define observations - define model (python function) - define samplesets (sets of parameter combinations) Currently supported functionality includes: - forward model runs - Latin-Hypercube sampling of parameters - multi-dimensional parameter studies - parallel execution of parameter samples - model calibration using internal Levenberg-Marquardt algorithm - model calibration using lmfit package - model calibration using levmar package - Markov Chain Monte Carlo using pymc package MATK facilitates model analysis using: - scipy - calibration (scipy.optimize) - rpy2 - Python interface to R", + "laborHours": 54856.8, + "name": "Model Analysis ToolKit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dharp/MATK", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Streaming Canvas is an interactive data visualization tool for high dimensional data such as text documents. It allows the user to interactively analyze documents.", + "laborHours": 104226.4, + "name": "Streaming Canvas", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/aim-science-of-interaction/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/aim-science-of-interaction", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Vector extensions, such as SSE, have been part of the x86 CPU since the 1990s, with applications in graphics, signal processing, and scientific applications. Although many algorithms and applications can naturally benefit from automatic vectorization techniques, there are still many that are difficult to vectorize due to their dependence on irregular data structures, dense branch operations, or data dependencies. Sequence alignment, one of the most widely used operations in bioinformatics workflows, has a computational footprint that features complex data dependencies. The trend of widening vector registers adversely affects the state-of-the-art sequence alignment algorithm based on striped data layouts. Therefore, a novel SIMD implementation of a parallel scan-based sequence alignment algorithm that can better exploit wider SIMD units was implemented as part of the Parallel Sequence Alignment Library (parasail). Parasail features: Reference implementations of all known vectorized sequence alignment approaches. Implementations of Smith Waterman (SW), semi-global (SG), and Needleman Wunsch (NW) sequence alignment algorithms. Implementations across all modern CPU instruction sets including AVX2 and KNC. Language interfaces for C/C++ and Python.", + "laborHours": 589045.6, + "name": "Pairwise Sequence Alignment Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jeffdaily/parasail/blob/master/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeffdaily/parasail", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Shifter enables application virtualization or containerization in large-scale HPC environments. This technology decreases the effort to port applications to or between HPC sites while increasing reproducibility and scientific productivity. Shifter works by converting application/container images to a common format, and then leverages basic Linux functionality to make that image available to batch jobs run in the HPC environment.", + "laborHours": 13756.0, + "name": "shifter", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NERSC/shifter/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/shifter", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Tomopy is a Python toolbox to perform x-ray data processing, image reconstruction and data exchange tasks at synchrotron facilities. The dependencies of the software are currently as follows: -Python related python standard library (http://docs.python.org/2/library/) numpy (http://www.numpy.org/) scipy (http://scipy.org/) matplotlib (http://matplotlip.org/) sphinx (http://sphinx-doc.org) pil (http://www.pythonware.com/products/pil/) pyhdf (http://pysclint.sourceforge.net/pyhdf/) h5py (http://www.h5py.org) pywt (http://www.pybytes.com/pywavelets/) file.py (https://pyspec.svn.sourceforge.net/svnroot/pyspec/trunk/pyspec/ccd/files.py) -C/C++ related: gridec (anonymous?? C-code written back in 1997 that uses standard C library) fftw (http://www.fftw.org/) tomoRecon (multi-threaded C++ verion of gridrec. Author: Mark Rivers from APS. http://cars9.uchicago.edu/software/epics/tomoRecon.html) epics (http://www.aps.anl.gov/epics/)", + "laborHours": 9986.4, + "name": "Tomopy: A Python toolbox to perform X-Ray data proessing and image reconstruction.", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/tomopy/tomopy/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tomopy/tomopy", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The OpenSM Monitoring System includes a collection of diagnostic and monitoring tools for use on Infiniband networks. The information this system gathers is obtained from a service, which in turn is obtained directly from the OpenSM subnet manager.", + "laborHours": 34899.2, + "name": "OpenSM Monitoring System", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/meier/opensm-smt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Not Specified", + "laborHours": 39793.6, + "name": "Framework for Network Co-simulation v. 2.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GridOPTICS/FNCS/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GridOPTICS/FNCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Flume-plugins are plugins for Apache Flume, which are used for managing data transferred through Apache Flume.", + "laborHours": 592.8, + "name": "flume-plugins Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/flume-plugins/blob/master/DISCLAIMER", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chu11/flume-plugins", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "FileUtils provides a suite of tools to manage large datasets typically created by large parallel MPI applications. They are written in C and use standard POSIX I/Ocalls. The current suite consists of tools to copy, compare, remove, and list. The tools provide dramatic speedup over existing Linux tools, which often run as a single process.", + "laborHours": 18194.4, + "languages": [], + "name": "Distributed File System Utilities to Manage Large DatasetsVersion 0.5", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/hpc/mpifileutils/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/fileutils", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "FALCON has been developed to enable simulation of the tightly coupled fluid-rock behavior in hydrothermal and engineered geothermal system (EGS) reservoirs, targeting the dynamics of fracture stimulation, fluid flow, rock deformation, and heat transport in a single integrated code, with the ultimate goal of providing a tool that can be used to test the viability of EGS in the United States and worldwide. Reliable reservoir performance predictions of EGS systems require accurate and robust modeling for the coupled thermal­hydrological­mechanical processes.", + "laborHours": 23043.2, + "languages": [], + "name": "Fracturing And Liquid CONvection", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/falcon", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A general particle library designed to run on next-generation hardware such as MICs and GPUs.", + "laborHours": 31342.4, + "name": "Libparty, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/libparty", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kindrew@jlab.org" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A simple code-generator to generate the low level code kernels used by the QPhiX Library for Lattice QCD. Generates Kernels for Wilson-Dslash, and Wilson-Clover kernels. Can be reused to write other optimized kernels for Intel Xeon Phi(tm), Intel Xeon(tm) and potentially other architectures.", + "laborHours": 5897.6, + "name": "QPhiX Code Generator", + "organization": "Thomas Jefferson National Accelerator Facility (TJNAF)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/JeffersonLab/qphix-codegen/blob/master/codegen/LICENSE.markdown", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JeffersonLab/qphix-codegen", + "status": "Production", + "tags": [ + "DOE CODE", + "Thomas Jefferson National Accelerator Facility (TJNAF)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MACSio is a Multi-purpose, Application-Centric, Scalable I/O proxy application. It is designed to support a number of goals with respect to parallel I/O performance testing and benchmarking including the ability to test and compare various I/O libraries and I/O paradigms, to predict scalable performance of real applications and to help identify where improvements in I/O performance can be made within the HPC I/O software stack.", + "laborHours": 36814.4, + "name": "Multi-Purpose, Application-Centric, Scalable I/O Proxy Application", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MACSio", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"MetaGenomic Assembly by Merging\" (MeGAMerge)Is a novel method of merging of multiple genomic assembly or long read data sources for assembly by use of internal trimming/filtering of data, followed by use of two 3rd party tools to merge data by overlap based assembly.", + "laborHours": 288.8, + "name": "MetaGenomic Assembly by Merging (MeGAMerge)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/MeGAMerge/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MeGAMerge", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Edge Bioinformatics is a developmental bioinformatics and data management platform which seeks to supply laboratories with bioinformatics pipelines for analyzing data associated with common samples case goals. Edge Bioinformatics enables sequencing as a solution and forward-deployed situations where human-resources, space, bandwidth, and time are limited. The Edge bioinformatics pipeline was designed based on following USE CASES and specific to illumina sequencing reads. 1. Assay performance adjudication (PCR): Analysis of an existing PCR assay in a genomic context, and automated design of a new assay to resolve conflicting results; 2. Clinical presentation with extreme symptoms: Characterization of a known pathogen or co-infection with a. Novel emerging disease outbreak or b. Environmental surveillance", + "laborHours": 155587.2, + "name": "Edge Bioinformatics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/edge", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "One major challenge in the field of shotgun metagenomics is the accurate identification of the organisms present within the community, based on classification of short sequence reads. Though microbial community profiling methods have emerged to attempt to rapidly classify the millions of reads output from contemporary sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling tool with significantly smaller FDR, which is also capable of classifying never-before seen genomes into the appropriate parent taxa.The algorithm is based upon three primary computational phases: (I) genomic decomposition into bit vectors, (II) bit vector intersections to identify shared regions, and (III) bit vector subtractions to remove shared regions and reveal unique, signature regions. In the Decomposition phase, genomic data is first masked to highlight only the valid (non-ambiguous) regions and then decomposed into overlapping 24-mers. The k-mers are sorted along with their start positions, de-replicated, and then prefixed, to minimize data duplication. The prefixes are indexed and an identical data structure is created for the start positions to mimic that of the k-mer data structure. During the Intersection phase -- which is the most computationally intensive phase -- as an all-vs-all comparison is made, the number of comparisons is first reduced by four methods: (a) Prefix restriction, (b) Overlap detection, (c) Overlap restriction, and (d) Result recording. In Prefix restriction, only k-mers of the same prefix are compared. Within that group, potential overlap of k-mer suffixes that would result in a non-empty set intersection are screened for. If such an overlap exists, the region which intersects is first reduced by performing a binary search of the boundary suffixes of the smaller set into the larger set, which defines the limits of the zipper-based intersection process. Rather than recording the actual k-mers of the intersection, another data structure of identical \"shape\" is created which consists of only bit vectors so that only a 1 or 0 will be stored in the location of the k-mer suffix that was found in the intersection. This reduces the amount of data generated and stored considerably. During the Subtraction phase, relevant intersection bitmasks are first unionized together to form a single bitmask which is then applied over the original genome to reveal only those regions of the genome that are unique. These regions are then exported to disk in FASTA format and used in the application of determining the constituents of an unknown metagenomic community.", + "laborHours": 5168.0, + "name": "GOTTCHA, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/GOTTCHA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "One major challenge in the field of shotgun metagenomics is the accurate identification of the organisms present within the community, based on classification of short sequence reads. Though microbial community profiling methods have emerged to attempt to rapidly classify the millions of reads output from contemporary sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling tool with significantly smaller FDR, which is also capable of classifying never-before seen genomes into the appropriate parent taxa.The algorithm is based upon three primary computational phases: (I) genomic decomposition into bit vectors, (II) bit vector intersections to identify shared regions, and (III) bit vector subtractions to remove shared regions and reveal unique, signature regions.In the Decomposition phase, genomic data is first masked to highlight only the valid (non-ambiguous) regions and then decomposed into overlapping 24-mers. The k-mers are sorted along with their start positions, de-replicated, and then prefixed, to minimize data duplication. The prefixes are indexed and an identical data structure is created for the start positions to mimic that of the k-mer data structure.During the Intersection phase -- which is the most computationally intensive phase -- as an all-vs-all comparison is made, the number of comparisons is first reduced by four methods: (a) Prefix restriction, (b) Overlap detection, (c) Overlap restriction, and (d) Result recording. In Prefix restriction, only k-mers of the same prefix are compared. Within that group, potential overlap of k-mer suffixes that would result in a non-empty set intersection are screened for. If such an overlap exists, the region which intersects is first reduced by performing a binary search of the boundary suffixes of the smaller set into the larger set, which defines the limits of the zipper-based intersection process. Rather than recording the actual k-mers of the intersection, another data structure of identical \"shape\" is created which consists of only bit vectors so that only a 1 or 0 will be stored in the location of the k-mer suffix that was found in the intersection. This reduces the amount of data generated and stored considerably.During the Subtraction phase, relevant intersection bitmasks are first unionized together to form a single bitmask which is then applied over the original genome to reveal only those regions of the genome that are unique. These regions are then exported to disk in FASTA format and used in the application of determining the constituents of an unknown metagenomic community.The DATABASE provided is the result of the algorithm described.", + "laborHours": 5168.0, + "name": "GOTTCHA Database, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/GOTTCHA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CASL's modeling and simulation technology, the Virtual Environment for Reactor Applications (VERA), incorporates coupled physics and science-based models, state-of-the-art numerical methods, modern computational science, integrated uncertainty quantification (UQ) and validation against data from operating pressurized water reactors (PWRs), single-effect experiments, and integral tests. The computational simulation component of VERA is the VERA Core Simulator (VERA-CS). The core simulator is the specific collection of multi-physics computer codes used to model and deplete a LWR core over multiple cycles. The core simulator has a single common input file that drives all of the different physics codes. The parser code, VERAIn, converts VERA Input into an XML file that is used as input to different VERA codes.", + "laborHours": 13786.4, + "name": "VERAIn", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/CASL/VERAin/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CASL/VERAin", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Cloud droplet number concentration is an important factor in understanding aerosol-cloud interactions. As aerosol concentration increases, it is expected that droplet number concentration (Nd) will increase and droplet size will decrease, for a given liquid water path. This will greatly affect cloud albedo as smaller droplets reflect more shortwave radiation; however, the magnitude and variability of these processes under different environmental conditions is still uncertain.McComiskey et al. (2009) have implemented a method, based onBoers and Mitchell (1994), for calculating Nd from ground-based remote sensing measurements of optical depth and liquid water path. They show that the magnitude of the aerosol-cloud interactions (ACI) varies with a range of factors, including the relative value of the cloud liquid water path (LWP), the aerosol size distribution, and the cloud updraft velocity. Estimates of Nd under a range of cloud types and conditions and at a variety of sites are needed to further quantify the impacts of aerosol cloud interactions. In order to provide data sets for studying aerosol-cloud interactions, the McComiskey et al. (2009) method was implemented as the Droplet Number Concentration (NDROP) value-added product (VAP).", + "laborHours": 532.0, + "name": "Droplet Number Concentration Value Added Product", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ARM-DOE/adi-vap-ndrop", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/adi-vap-ndrop", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "joiner@ameslab.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ParFit is a flexible and extendable framework and library of classes for fitting force-field parameters to data from high-level ab-initio calculations on the basis of deterministic and stochastic algorithms. Currently, the code is fitting MM3 and Merck force-field parameters but could easily extend to other force-field types.", + "laborHours": 31874.4, + "name": "Force-Field Parameter Fitter", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fzahari/ParFit", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The four-dimensional scattering function S(Q,w) obtained by inelastic neutron scattering measurements provides unique \"dynamical fingerprints\" of the spin state and interactions present in complex magnetic materials. Extracting this information however is currently a slow and complex process that may take an expert -depending on the complexity of the system- up to several weeks of painstaking work to complete. Spin Wave Genie was created to abstract and automate this process. It strives to both reduce the time to complete this analysis and make these calculations more accessible to a broader group of scientists and engineers.", + "laborHours": 11658.4, + "name": "Spin Wave Genie", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SpinWaveGenie/SpinWaveGenie", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DESTINY is a comprehensive tool for modeling 3D and 2D cache designs using SRAM,embedded DRAM (eDRAM), spin transfer torque RAM (STT-RAM), resistive RAM (ReRAM), and phase change RAM (PCN). In its purpose, it is similar to CACTI, CACTI-3DD or NVSim. DESTINY is very useful for performing design-space exploration across several dimensions, such as optimizing for a target (e.g. latency, area or energy-delay product) for agiven memory technology, choosing the suitable memory technology or fabrication method (i.e. 2D v/s 3D) for a given optimization target, etc. DESTINY has been validated against several cache prototypes. DESTINY is expected to boost studies of next-generation memory architectures used in systems ranging from mobile devices to extreme-scale supercomputers.", + "laborHours": 6292.8, + "name": "DESTINY", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/3d_cache_modeling_tool/destiny/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/3d_cache_modeling_tool/destiny", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "To address a pressing need to better understand the behavior and complex interaction of ice sheets within the global Earth system, significant development of continental-scale, dynamical ice-sheet models is underway. The associated verification and validation process of these models is being coordinated through a new, robust, python-based extensible software package, the Land Ice Verification and Validation toolkit (LIVV). This release provides robust and automated verification and a performance evaluation on LCF platforms. The performance V&V involves a comprehensive comparison of model performance relative to expected behavior on a given computing platform. LIVV operates on a set of benchmark and test data, and provides comparisons for a suite of community prioritized tests, including configuration and parameter variations, bit-4-bit evaluation, and plots of tests where differences occur.", + "laborHours": 4772.8, + "name": "Land Ice Verification and Validation Kit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LIVVkit/LIVVkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Autotune software code uses an island-based evolutionary algorithm to solve multi-objective optimization problems. For the code provided, this has been applied to the whole-building simulation engine EnergyPlus to allow a software description of a building to be calibrated to measured data.", + "laborHours": 7068.0, + "name": "Autotune", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-BTRIC/Autotune/blob/master/LICENCE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-BTRIC/Autotune", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A collection of functions for statistical computing and data manipulation. These include routines for rapidly aggregating heterogeneous matrices, manipulating file names, loading R objects, sourcing multiple R files, formatting datetimes, multi-core parallel computing, stream editing, specialized plotting, etc. Smisc-package A collection of miscellaneous functions allMissing Identifies missing rows or columns in a data frame or matrix as.numericSilent Silent wrapper for coercing a vector to numeric comboList Produces all possible combinations of a set of linear model predictors cumMax Computes the maximum of the vector up to the current index cumsumNA Computes the cummulative sum of a vector without propogating NAs d2binom Probability functions for the sum of two independent binomials dataIn A flexible way to import data into R. dbb The Beta-Binomial Distribution df2list Row-wise conversion of a data frame to a list dfplapply Parallelized single row processing of a data frame dframeEquiv Examines the equivalence of two dataframes or matrices dkbinom Probability functions for the sum of k independent binomials factor2character Converts all factor variables in a dataframe to character variables findDepMat Identify linearly dependent rows or columns in a matrix formatDT Converts date or datetime strings into alternate formats getExtension Filename manipulations: remove the extension or path, extract the extension or path getPath Filename manipulations: remove the extension or path, extract the extension or path grabLast Filename manipulations: remove the extension or path, extract the extension or path ifelse1 Non-vectorized version of ifelse integ Simple numerical integration routine interactionPlot Two-way Interaction Plot with Error Bar linearMap Linear mapping of a numerical vector or scalar list2df Convert a list to a data frame loadObject Loads and returns the object(s) in an \".Rdata\" file more Display the contents of a file to the R terminal movAvg2 Calculate the moving average using a 2-sided window openDevice Opens a graphics device based on the filename extension p2binom Probability functions for the sum of two independent binomials padZero Pad a vector of numbers with zeros parseJob Parses a collection of elements into (almost) equal sized groups pbb The Beta-Binomial Distribution pcbinom A continuous version of the binomial cdf pkbinom Probability functions for the sum of k independent binomials plapply Simple parallelization of lapply plotFun Plot one or more functions on a single plot PowerData An example of power data pvar Prints the name and value of one or more objects qbb The Beta-Binomial Distribution rbb And numerous others (space limits reporting).", + "laborHours": 2568.8, + "name": "Smisc - A collection of miscellaneous functions", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/Smisc/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Smisc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-01-25" + }, + "description": "The core of the modeling platform is an extensible block library for the MATLAB/Simulink software suite. The platform enables true co-simulation (interaction at each simulation time step) with NREL's state-of-the-art modeling tools and other energy modeling software.", + "laborHours": 3024.8, + "languages": [], + "name": "Campus Energy Model for Control and Performance Validation [SWR-15-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CampusEnergyModeling", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-05-22" + }, + "description": "Small pieces of software that wraps the FAST model so that FAST can be integrated to WISDEM. NOTE: THIS REPOSITORY IS DEPRECATED AND WAS ARCHIVED (READ-ONLY) IN NOVEMBER 2019. NREL's WISDEM® software has moved to a single, integrated repository at https://github.com/wisdem/wisdem", + "laborHours": 11536.8, + "languages": [ + "Python" + ], + "name": "Aeroelastic Systems Engineering Module [SWR 14-26]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/aeroelasticse", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "FESTR is a modeling tool for calculating spectroscopic-quality synthetic outputs (e.g., spectra and images) based on (in general) the time evolutions of 3-D spatial distributions of materials characterized by their chemical composition, temperature, and density conditions. FESTR performs raytracing across unstructured meshes, builds intrinsic optical properties of mixed materials by performing equation-of-state lookups in external data, and then solves the radiation-transport equation along rays to obtain emergent time and space resolved synthetic spectra. These results can be further processed into time and/or space integrated spectra, as well as into spectral-band-integrated synthetic images, radiated power histories, and total radiated energy values. FESTR is also applicable to spatial reconstructions of material properties via the analysis of experimental data.", + "laborHours": 70376.0, + "name": "FESTR, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LANLhakel/FESTR/blob/d5a8941f2e74fb0adc8b12a90180b299b95dc93e/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANLhakel/FESTR", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This package contains statistical routines for extracting features from multivariate time-series data which can then be used for subsequent multivariate statistical analysis to identify patterns and anomalous behavior. It calculates local linear or quadratic regression model fits to moving windows for each series and then summarizes the model coefficients across user-defined time intervals for each series. These methods are domain agnostic-but they have been successfully applied to a variety of domains, including commercial aviation and electric power grid data.", + "laborHours": 988.0, + "name": "qFeature", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/qFeature/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL/qFeature", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Enables applications to emit log information into an output file and produced a structured visual summary of the log data, as well as various statistical analyses of it. This makes it easier for developers to understand the behavior of their applications.", + "laborHours": 170893.6, + "name": "Sight Version 0.1", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bronevet/sight", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "joiner@ameslab.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "As the rate, sophistication, and potential damage of cyber attacks continue to grow, the latency of human-speed analysis and response is becoming increasingly costly. Intelligent response to detected attacks and other malicious activity requires both knowledge of the characteristics of the attack as well as how resources involved in the attack related to the mission of the organization. Cydime fills this need by estimating a key component of intrusion detection and response automation: the relationship type and strength between the target organization and the potential attacker.", + "laborHours": 15762.4, + "name": "Cyber Dynamic Impact Modeling Engine", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Ames-Laboratory-Cyber-Group/Cydime", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-08-16" + }, + "description": "DICe is an open source digital image correlation (DIC) tool intended for use as a module in an external application or as a standalone analysis code. It's primary capability is computing full-field displacements and strains from sequences of digital These images are typically of a material sample undergoing a materials characterization experiment, but DICe is also useful for other applications (for example, trajectory tracking). DICe is machine portable (Windows, Linux and Mac) and can be effectively deployed on a high performance computing platform. Capabilities from DICe can be invoked through a library interface, via source code integration of DICe classes or through a graphical user interface.", + "laborHours": 45128.8, + "languages": [], + "name": "Digital Image Correlation Engine v.3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dicengine/dice", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Many simulation software produce data in the form of a set of field values or of a set of particle positions. (one such example is that of particle-in-cell codes, which produce data on the electromagnetic fields that they simulate.) However, each particular software uses its own particular format and layout, for the output data. This makes it difficult to compare the results of different simulation software, or to have a common visualization tool for these results. However, a standardized layout for fields and particles has recently been developed: the openPMD format ( HYPERLINK \"http://www.openpmd.org/\"www.openpmd.org) This format is open- source, and specifies a standard way in which field data and particle data should be written. The openPMD format is already implemented in the particle-in-cell code Warp (developed at LBL) and in PIConGPU (developed at HZDR, Germany). In this context, the proposed software (openPMD-viewer) is a Python package, which allows to access and visualize any data which has been formatted according to the openPMD standard. This package contains two main components: - a Python API, which allows to read and extract the data from a openPMD file, so as to be able to work with it within the Python environment. (e.g. plot the data and reprocess it with particular Python functions) - a graphical interface, which works with the ipython notebook, and allows to quickly visualize the data and browse through a set of openPMD files. The proposed software will be typically used when analyzing the results of numerical simulations. It will be useful to quickly extract scientific meaning from a set of numerical data.", + "laborHours": 1246.4, + "name": "openPMD-viewer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/openPMD/openPMD-viewer/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openPMD/openPMD-viewer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-11-06" + }, + "description": "VOLTTRON™ is an agent execution platform providing services to its agents that allow them to easily communicate with physical devices and other resources. VOLTTRON™ delivers an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls. It enables mobile and stationary software agents to perform information gathering, processing, and control actions. VOLTTRON™ can independently manage a wide range of applications, such as HVAC systems, electric vehicles, distributed energy or entire building loads, leading to improved operational efficiency.", + "laborHours": 0.0, + "languages": [], + "name": "VOLTTRON Version 3.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/VOLTTRON/volttron/blob/3.x/TERMS.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron/releases/tag/3.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"XTL Converter\" is a short Python script for electron microscopy simulation. The program takes an input crystal file in the VESTA *.XTL format and converts it to a text format readable by the multislice simulation program ìSTEM. The process of converting a crystal *.XTL file to the format used by the ìSTEM simulation program is quite tedious; it generally requires the user to select dozens or hundreds of atoms, rearranging and reformatting their position. Header information must also be reformatted to a specific style to be read by ìSTEM. \"XTL Converter\" simplifies this process, saving the user time and allowing for easy batch processing of crystals.", + "laborHours": 136.8, + "name": "XTL Converter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/stevenspurgeon/xtl-converter/blob/master/License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stevenspurgeon/xtl-converter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Cantera is a suite of object-oriented software tools for problems involving chemical kinetics, thermodynamics, and/or transport processes. It is a multi-organizational effort to create and formulate high quality 0D and 1D constitutive modeling tools for reactive transport codes.Institutions involved with the effort include Sandia, MIT, Colorado School of Mines, U. Texas, NASA, and Oak Ridge National Labs. Specific to Sandia's contributions, the Cantera Electrolyte Thermo Objects (CETO) packages is comprised of add-on routines for Cantera that handle electrolyte thermochemistry and reactions within the overall Cantera package. Cantera is a C++ Cal Tech code that handles gas phase species transport, reaction, and thermodynamics. With this addition, Cantera can be extended to handle problems involving liquid phase reactions and transport in electrolyte systems, and phase equilibrium problemsinvolving concentrated electrolytes and gas/solid phases. A full treatment of molten salt thermodynamics and transport has also been implemented in CETO. The routines themselves consist of .cpp and .h files containing C++ objects that are derived from parent Cantera objects representing thermodynamic functions. They are linked unto the main Cantera libraries when requested by the user. As an addendum to the main thermodynamics objects, several utility applications are provided. The first is multiphase Gibbs free energy minimizer based on the vcs algorithm, called vcs_cantera. This code allows for the calculation of thermodynamic equilibrium in multiple phases at constant temperature and pressure. Note, a similar code capability exists already in Cantera. This version follows the same algorithm, but gas a different code-base starting point, and is used as a research tool for algorithm development. The second program, cttables, prints out tables of thermodynamic and kinetic information for thermodynamic and kinetic objects within Cantera. This program serves as a \"Get the numbers out\" utility for Cantera, and as such it is very useful as a verification tool. These add-on utilities are encapsulated into a directory structure named cantera_apps, whose installation uses autoconf and also utilizes Cantera's application environment (i.e., they utilize Cantera as a library).", + "laborHours": 97432.0, + "name": "Cantera and Cantera Electrolyte Thermodynamics Objects", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Cantera/cantera", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-09" + }, + "description": "Sandia's Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to: (1) enhance understanding of risk, (2) improve products, and (3) assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a computational model. However, Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. The algorithms implemented in Dakota aim to address challenges in performing these analyses with complex science and engineering models from desktop to high performance computers.", + "homepageURL": "https://dakota.sandia.gov/sites/default/files/docs/6.0/html-dev/files.html", + "laborHours": 3812676.8, + "languages": [], + "name": "Design Analysis Kit for Optimization and Terascale Applications 6.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/sites/default/files/docs/6.0/html-dev/files.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-01" + }, + "description": "The Kokkos library implements thread-parallel execution policies and shared-memory multidimensional array data structures that enable applications and domain libraries to develop computational kernels that are performance portable across multicore-CPU and manycore-accelerator (e.g. GPU) computing architectures.", + "laborHours": 119700.0, + "languages": [], + "name": "Kokkos Version 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/kokkos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Sandia National Laboratories has modified Simulating WAves Nearshore (SWAN), the Delft University of Technology code,, to include functionality to better model wave energy converters (WECs). The code modified by SNL has been named SNL-SWAN. SNL-SWAN includes a frequency dependent WEC Module that builds upon the traditional obstacle module in SWAN. In SNL-SWAN, a frequency dependent transmission coefficient is calculated to model power absorbed by WEC devices. The power transmission coefficients are calculated based on the WEC's power performance, which is defined by the user in the input text files. Two methods of defining WEC power performance have been implemented: a user-specified power matrix, and a user-specified relative capture width. These methods allow the user to define the WEC's frequency dependent energy absorption as a function of period and/or wave height. SWAN test cases were run to verify the compiled code's functionality, and verification of the frequency dependent WEC Module in SNL-SWAN has also been performed. SNL-SWAN code is will be released as open source code and will be made publicly available.", + "laborHours": 23985.6, + "languages": [ + "Fortran" + ], + "name": "SNL-SWAN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SNL-SWAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "UseLATEX.cmake is a collection of script functions and examples for building LaTeX documents. It simplifies the process of building LaTeX documents, which requires the execution of multiple programs and the management of several input files. UseLATEX.cmake also provides several options to customize the LaTeX build process.", + "laborHours": 1520.0, + "languages": [ + "CMake", + "Shell", + "TeX" + ], + "name": "UseLATEX.cmake", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/UseLATEX", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-01" + }, + "description": "VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures. VTK-m supports the fine-grained concurrency for data analysis and visualization algorithms required to drive extreme scale computing by providing abstract models for data and execution that can be applied to a variety of algorithms across many different processor architectures.", + "laborHours": 204652.8, + "languages": [], + "name": "VTK-m", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk-m", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Some moment methods for kinetic equations are complicated and take time to develop. Over the course of a couple years, this software was developed to test different closures on standard test problems in the literature. With this software, researchers in the field of moment closures will be able to rapidly test new methods.", + "laborHours": 22298.4, + "name": "Moment Closures on Two-Dimensional Cartesian Grids", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ckrisgarrett/closures-2d", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ckrisgarrett/closures-2d", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "An automated drift time extraction and computed associated collision cross section software tool for small molecule analysis with ion mobility spectrometry-mass spectrometry (IMS-MS). The software automatically extracts drift times and computes associated collision cross sections for small molecules analyzed using ion mobility spectrometry-mass spectrometry (IMS-MS) based on a target list of expected ions provided by the user.", + "laborHours": 83235.2, + "name": "IMS - MS Data Extractor", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/PIXIE/blob/master/PNNL%20OSS%20License_citation.doc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PIXIE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "nHHD is a C++ library to decompose a flow field into three components exhibiting specific types of behaviors. These components allow more targeted analysis of flow behavior and can be applied to a variety of application areas.", + "laborHours": 10396.8, + "name": "The Natural Helmholtz-Hodge Decomposition", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bhatiaharsh/naturalHHD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "To understand the performance of parallel programs, developers need to be able to relate performance measurement data with context information, such as the call path / line numbers or iteration numbers where measurements were taken. Caliper provides a generic way to specify and collect multi-dimensional context information across the software stack, and provide ti to third-party measurement tools or write it into a file or database in the form of context streams.", + "laborHours": 35096.8, + "languages": [], + "name": "Caliper Context Annotation Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/Caliper/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Caliper", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "LCMSnet communicates with, controls and orchestrates devices for high pressure liquid chromatography. In developing cutting edge chromatographic methods it was apparent that components from different manufacturers were required. Autosamplers, valves, and pumps all had to be controlled and configured to run unattended and in the highest throughput possible. The power of LCMSnet is the ability so build methods in a simple step by step fashion and then the software uses a scheduling algorithm to run the devices as efficiently as possible without crashing critical functions. This latest iteration of the software allows for modeling of the valves and incorporates logic that will report if a fluid path is undesirable. LCMSnet has reduced method development time from days to minutes and allows the ability to check configurations before any valves or pumps are connected.", + "laborHours": 70239.2, + "name": "LCMSNet v. 3.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/LCMSNet", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LCMSNet", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "BGQNCL is a library to monitor and record network performance counters on the 5D torus interconnection network of IBM's Blue Gene/Q platform.", + "laborHours": 152.0, + "name": "Blue Gene/Q Network Performance Counters Monitoring Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/bgqncl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Dragonview is an interactive visual analytics tool to visualize the nodes and links of a supercomputer that uses the dragonfly topology for its interconnection network. It can be used to map different data such as number of packets or bytes or stalls on the network links and job IDs or other on-node metrics on the router or node.", + "laborHours": 3085.6, + "name": "Dragonview", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DragonView", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Graphator is a collection of relatively simple sequential programs that generate communication graphs/matrices for commonly occurring patterns in parallel programs. Currently, there is support for five communication patterns: two-dimensional 4-point stencil, four-dimensional 8-point stencil, all-to-alls over sub-communicators, random near-neighbor communication, and near-neighbor communication.", + "laborHours": 91.2, + "name": "Communication Graph Generator for Parallel Programs", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/graphator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "AriesNCL is a library to monitor and record network router tile performance counters on the Aries router of Cray's Cascade/XC30 platform.", + "laborHours": 152.0, + "name": "Aries Network Performance Counters Monitoring Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ariesncl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Damselfly is a model-based parallel network simulator. It can simulate communication patterns of High Performance Computing applications on different network topologies. It outputs steady-state network traffic for a communication pattern, which can help in studying network congestion and its impact on performance.", + "laborHours": 2401.6, + "name": "Damselfly Network Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/damselfly", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Most of the software related to file system are written for conventional local file system, they are serialized and can't take advantage of the benefit of a large scale parallel file system. \"pcircle\" software builds on top of ubiquitous MPI in cluster computing environment and \"work-stealing\" pattern to provide a scalable, high-performance suite of file system tools. In particular - it implemented parallel data copy and parallel data checksumming, with advanced features such as async progress report, checkpoint and restart, as well as integrity checking.", + "laborHours": 3085.6, + "name": "pcircle - A Suite of Scalable Parallel File System Tools", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-TechInt/pcircle", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The visualization enables the simulation analyst to see changes in the frequency through time and space. With this technology, the analyst has a bird's eye view of the frequency at loads and generators as the simulated power system responds to the loss of a generator, spikes in load, and other contingencies. The significance of a contingency to the operation of an electrical power system depends critically on how the resulting tansients evolve in time and space. Consequently, these dynamic events can only be understood when seen in their proper geographic context. this understanding is indispensable to engineers working on the next generation of distributed sensing and control systems for the smart grid. By making possible a natural and intuitive presentation of dynamic behavior, our new visualization technology is a situational-awareness tool for power-system engineers.", + "laborHours": 773132.8, + "name": "Geographic Visualization of Power-Grid Dynamics", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ssrangan/VizPower/blob/master/Open%20Source%20Software%20License%20(Permissive).pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ssrangan/VizPower", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SSCA1-K1 is a parallel implementation of kernel 1 of the SSCA1 benchmark suite released by the DARPA HPCS program. This kernel is able to run in parallel on a distributed shared memory system at extreme scales using OpenSHMEM.", + "laborHours": 775.2, + "name": "SSCA1-K1", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/MattBBaker/ssca1", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Intrepid is a library of interoperable tools for compatible discretizations of Partial Differential Equations (PDEs).Current version is intended primarily for application developers who want to reuse large parts of their existing code frameworks such as I/O, data structures, assembly routines, etc. while gaining access to advanced discretization capabilities provided by Intrepid. Intrepid2 is a performance portable version of Intrepid, that requires all input data types be Kokkos (performance-portability library from Trillions) multidimentional arrays. this restriction is needed for providing performance portability in Intrepid2 and break backward-compatibility of Intrepid.", + "laborHours": 8344830.4, + "name": "INteroperable Tools for Rapid dEveloPment of compatible Discretizations", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/intrepid/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This code implements the GloVe algorithm for learning word vectors from a text corpus. It uses a modern C++ approach. This algorithm is described in the open literature in the referenced paper by Pennington, Jeffrey, Richard Socher, and Christopher D. Manning.", + "laborHours": 486.4, + "languages": [ + "C++", + "Makefile" + ], + "name": "GloVe C++ v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GloveCpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "ryan.morrone@netl.doe.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "RVA is a plugin developed for the 64-bit Windows version of the ParaView 3.14 visualization package. RVA is designed to provide support in the visualization and analysis of complex reservoirs being managed using multi-fluid EOR techniques. RVA, for Reservoir Visualization and Analysis, was developed at the University of Illinois at Urbana-Champaign, with contributions from the Illinois State Geological Survey, Department of Computer Science and National Center for Supercomputing Applications. RVA was designed to utilize and enhance the state-of-the-art visualization capabilities within ParaView, readily allowing joint visualization of geologic framework and reservoir fluid simulation model results. Particular emphasis was placed on enabling visualization and analysis of simulation results highlighting multiple fluid phases, multiple properties for each fluid phase (including flow lines), multiple geologic models and multiple time steps. Additional advanced functionality was provided through the development of custom code to implement data mining capabilities. The built-in functionality of ParaView provides the capacity to process and visualize data sets ranging from small models on local desktop systems to extremely large models created and stored on remote supercomputers. The RVA plugin that we developed and the associated User Manual provide improved functionality through new software tools, and instruction in the use of ParaView-RVA, targeted to petroleum engineers and geologists in industry and research. The RVA web site (http://rva.cs.illinois.edu) provides an overview of functions, and the development web site (https://github.com/shaffer1/RVA) provides ready access to the source code, compiled binaries, user manual, and a suite of demonstration data sets. Key functionality has been included to support a range of reservoirs visualization and analysis needs, including: sophisticated connectivity analysis, cross sections through simulation results between selected wells, simplified volumetric calculations, global vertical exaggeration adjustments, ingestion of UTChem simulation results, ingestion of Isatis geostatistical framework models, interrogation of joint geologic and reservoir modeling results, joint visualization and analysis of well history files, location-targeted visualization, advanced correlation analysis, visualization of flow paths, and creation of static images and animations highlighting targeted reservoir features.", + "laborHours": 7220.0, + "name": "RVA: A Plugin for ParaView 3.14", + "organization": "National Energy Technology Laboratory (NETL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/shaffer1/RVA/blob/master/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/shaffer1/RVA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Energy Technology Laboratory (NETL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-12" + }, + "description": "PyTrilinos is a Python interface to selected Trilinos packages. This makes Trilinos linear algebra classes, linear solvers, preconditioners, nonlinear solvers, eigensolvers, and tools available to Python programmers. This broadens the user base of Trilinos, and facilitates rapid prototyping of scientific codes and interactive manipulation of large, distributed data sets.", + "laborHours": 8344830.4, + "languages": [], + "name": "PyTrilinos", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The DOE has funded Sandia National Labs (SNL) to develop an open-source modeling tool to guide the design and layout of marine hydrokinetic (MHK) arrays to maximize power production while minimizing environmental effects. This modeling framework simulates flows through and around MHK arrays while quantifying environmental responses. As an augmented version of US EPA's Environmental Fluid Dynamics Code (EFDC), SNL-EFDC includes: (1) a new module that simulates energy conversion (momentum withdrawal) by MHK devices with commensurate changes in the turbulent kinetic energy and its dissipation rate, (2) new, advanced sediment dynamics routines, and (3) augmented water quality modules.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Sandia National Laboratories Environmental Fluid Dynamics Code V. 1 0.0 (Beta)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/EFDC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "10.0" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The basic matrix library (bml) is a collection of various matrix data formats (in dense and sparse) and their associated algorithms for basic matrix operations.", + "laborHours": 38319.2, + "name": "Basic Matrix Library (bml), Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/bml/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qmmd/bml", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code is a set of global sums to support the paper \"Computational Reproducibility for Production Physics Applications\" submitted to the Numerical Reproducibility at Exascale (NRE 2015) workshop at the 2015 Supercomputing conference, Nov. 20, 2015", + "laborHours": 851.2, + "name": "GlobalSums, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/GlobalSums", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PV_LIB comprises a library of Matlab? code for modeling photovoltaic (PV) systems. Included are functions to compute solar position and to estimate irradiance in the PV system's plane of array, cell temperature, PV module electrical output, and conversion from DC to AC power. Also included are functions that aid in determining parameters for module performance models from module characterization testing. PV_LIB is open source code primarily intended for research and academic purposes. All algorithms are documented in openly available literature with the appropriate references included in comments within the code.", + "laborHours": 3359.2, + "name": "PV_LIB Toolbox v. 1.3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SandiaTestAccount/PVLIB_Matlab", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The Water Network Tool for Resilience (WNTR) is an open source Python package designed to simulate and analyze resilience of water distribution networks. The United States Environmental Protection Agency, in partnership with Sandia National Laboratories, developed WNTR to integrate critical aspects of resilience modeling for water distribution networks into a single software framework.\nThe software includes capability to:\n•\tGenerate water network models\n•\tModify network structure and operations\n•\tAssign fragility and survival curves to network components\n•\tModel disruptive events such as power outages, earthquakes, fires, pipe breaks, and contamination incidents\n•\tModel response and repair strategies\n•\tSimulate hydraulics and water quality\n•\tEvaluate resilience using a wide range of metrics\n•\tIntegrate dependency with other critical infrastructure and supply chains\n•\tAnalyze results and generate graphics\nSAND2019-450 M", + "laborHours": 147561.6, + "languages": [ + "C++", + "C", + "Python" + ], + "name": "Water Network Tool for Resilience (WNTR)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/WNTR", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Single-Sided Messaging (SSM) is a portable, multitransport networking library that enables applications to leverage potential one-sided capabilities of underlying network transports. It also provides desirable semantics that services for highperformance, massively parallel computers can leverage, such as an explicit cancel operation for pending transmissions, as well as enhanced matching semantics favoring large numbers of buffers attached to a single match entry. This release supports TCP/IP, shared memory, and Infiniband.", + "laborHours": 37741.6, + "languages": [], + "name": "Single Sided Messaging v. 0.6.6", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/single-sided-messaging", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.6.6" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Mobile digital signage software optimized for giving tours and trade shows.", + "laborHours": 2690.4, + "name": "DiTour OSS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ditour/ditour/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ditour/ditour", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "VTK is a software library used for scientific visualization tasks. My specific contribution is a new class that improves the I/O performance when reading certain input files.", + "laborHours": 3149576.8, + "name": "vtkPNetCDFPOPReader: a new C++ class for Visualization Toolkit (VTK)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.vtk.org/licensing", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Sirocco is a parallel storage system under development, designed for write-intensive workloads on large-scale HPC platforms. It implements a keyvalue object store on top of a set of loosely federated storage servers that cooperate to ensure data integrity and performance. It includes support for a range of different types of storage transactions. This software release constitutes a conformant storage server, along with the client-side libraries to access the storage over a network.", + "laborHours": 42848.8, + "languages": [ + "Shell", + "C++", + "C", + "RPC", + "Makefile" + ], + "name": "Sirocco Storage Server v. pre-alpha 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/sirocco-release?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sirocco-release", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "minimega is an emulytics platform for creating testbeds of networked devices. The platoform consists of easily deployable tools to facilitate bringing up large networks of virtual machines including Windows, Linux, and Android. minimega allows experiments to be brought up quickly with almost no configuration. minimega also includes tools for simple cluster, management, as well as tools for creating Linux-based virtual machines. This release of minimega includes new emulated sensors for Android devices to improve the fidelity of testbeds that include mobile devices. Emulated sensors include GPS and", + "laborHours": 399334.4, + "name": "minimega v. 3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandia-minimega/minimega", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GridDyn is a part of power grid simulation toolkit. The code is designed using modern object oriented C++ methods utilizing C++11 and recent Boost libraries to ensure compatibility with multiple operating systems and environments.", + "laborHours": 493620.0, + "name": "Dynamic Power Grid Simulation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/GridDyn/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GridDyn", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Stride Search provides a flexible tool for detecting storms or other extreme climate events in high-resolution climate data sets saved on uniform latitude-longitude grids in standard NetCDF format. Users provide the software a quantitative description of a meteorological event they are interested in; the software searches a data set for locations in space and time that meet the user’s description. In its first stage, Stride Search performs a spatial search of the data set at each timestep by dividing a search domain into circular sectors of constant geodesic radius. Data from a netCDF file is read into memory for each circular search sector. If the data meet or exceed a set of storm identification criteria (defined by the user), a storm is recorded to a linked list. Finally, the linked list is examined and duplicate detections of the same storm are removed and the results are written to an output file. The first stage’s output file is read by a second program that builds storm. Additional identification criteria may be applied at this stage to further classify storms. Storm tracks are the software’s ultimate output and routines are provided for formatting that output for various external software libraries for plotting and tabulating data.", + "laborHours": 8116.8, + "languages": [ + "C++", + "CMake", + "Fortran", + "Python" + ], + "name": "Stride Search v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/StrideSearch", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "In the cyber security operations of a typical organization, data from multiple sources are monitored, and when certain conditions in the data are met, an alert is generated in an alert management system. Analysts inspect these alerts to decide if any deserve promotion to an event requiring further scrutiny. This triage process is manual, time-consuming, and detracts from the in-depth investigation of events. We have created a software system that uses supervised machine learning to automatically prioritize these alerts. In particular we utilize active learning to make efficient use of the pool of unlabeled alerts, thereby improving the performance of our ranking models over passive learning. We have demonstrated the effectiveness of our system on a large, real-world dataset of cyber security alerts.", + "laborHours": 2508.0, + "name": "Alert Triage v 0.1 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/alert-triage", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This application can determine the performance and chemical behavior of batteries in 1D when they are cycled. With CanTrilBat, we are developing predictive phenomenological models for battery systems to predict operating performance and rate limiting steps in the performance of battery models. Particular attention is paid to primary and secondary chemistry mechanisms, such as the thermal runaway mechanisms experienced in secondary lithium ion batteries or self-discharge reaction mechanism that all batteries experience to one extent or another. The first application of this model has been for modeling the performance of thermal batteries. However, an implementation for secondary ion batteries is next. CanTrilBat applications solves transient problems involving batteries. It is a 1-D application that represents 3-D physical systems that can be reduced using the porous flow approximation for the anode, cathode, and separator. A control volume formulation is used to track conserved quantities. An operator-split approach is used to calculate the chemistry, diffusion and electronic transport that occurs within cathode and anode particles, allowing for the reduction in code complexity. All jacobian operations in CanTrilBat utilize numerical jacobians. A home grown predictor corrector scheme is used for time step control, and a home grown newton solver is used to relax the equations at each time step. Trilinos is used to solve for the resulting linear systems equation A block text input format is used to initialize options for the CanTriBat program. Within this block are the names of several XML input files, which specify the chemistry mechanism. These XML input files are read by low level Cantera routines, and serve to initialize the electrode and electrolyte chemistry mechanisms and transport properties. A GUI implementation has been contracted out to a university professor, but has not been implemented yet. It?s expected that CanTriBat will have the capability to do adaptive grid refinement in later versions. Grids will be halved based on an complicated set of heuristic criteria, based on how well the mesh captures changes to the first and second derivatives of selected solution components. Primary emphasis is given towards converged profiles for IV performance.", + "laborHours": 6177492.8, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "M4", + "Fortran" + ], + "name": "CanTrilBat and Cantera_apps v1.0 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cantrilbat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "TraceR is a trace reply tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performances and understanding network behavior by simulating messaging in High Performance Computing applications on interconnection networks.", + "laborHours": 4727.2, + "name": "Trace Replay and Network Simulation Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/tracer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The Albany code is a general-purpose finite element code for solving partial differential equations (PDEs). Albany is a research code that demonstrates how a PDE code can be built by interfacing many of the open-source software libraries that are released under Sandia's Trilinos project. Part of the mission of Albany is to be a testbed for new Trilinos libraries, to refine their methods, usability, and interfaces. Albany includes hooks to optimization and uncertainty quantification algorithms, including those in Trilinos as well as those in the Dakota toolkit. Because of this, Albany is a desirable starting point for new code development efforts that wish to make heavy use of Trilinos. Albany is both a framework and the host for specific finite element applications. These applications have project names, and can be controlled by configuration option when the code is compiled, but are all developed and released as part of the single Albany code base, These include LCM, QCAD, FELIX, Aeras, and ATO applications.", + "laborHours": 195228.8, + "languages": [ + "Shell", + "C", + "CMake", + "MATLAB", + "Python", + "GLSL" + ], + "name": "Albany v. 3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Albany", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PyGSTi is an implementation of Gate Set Tomography in the python programming language. Gate Set Tomography (GST) is a theory and protocol for simultaneously estimating the state preparation, gate operations, and measurement effects of a physical system of one or many quantum bits (qubits). These estimates are based entirely on the statistics of experimental measurements, and their interpretation and analysis can provide a detailed understanding of the types of errors/imperfections in the physical system. In this way, GST provides not only a means of certifying the \"goodness\" of qubits but also a means of debugging (i.e. improving) them.", + "laborHours": 95425.6, + "name": "Python GST Implementation v. 0.9 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pyGSTio/pyGSTi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This software extends the Cray Chapel runtime to use directly Sandia's Qthreads lightweight threading library and Sandia's Portals4 lightweight communication reference library.", + "laborHours": 4298453.6, + "name": "Lightweight Threading and Communication Shims for Chapel v. 1.0 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/chapel-lang/chapel/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chapel-lang/chapel", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A processor emulator and a suite of benchmark applications have been developed to assist in characterizing the performance of data-centric workloads on current and future computer architectures. Some of the applications have been collected from other open source projects. For more details on the emulator and an example of its usage, see reference [1].", + "laborHours": 21872.8, + "name": "Processor Emulator with Benchmark Applications", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/PerMA/emulator_st/src/2969fa5dab7e1b0ffe425869bd27158242c2ee27/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/perma/emulator_st", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code is a data parse for preparing output from the Qspp agent-based stochastic simulation model for plotting in Excel. This code is specific to a set of simulations that were run for the purpose of preparing data for a publication. It is necessary to make this code open-source in order to publish the model code (Qspp), which has already been released. There is a necessity of assuring that results from using Qspp for a publication", + "laborHours": 1915.2, + "name": "Parser for Sabin-to-Mahoney Transition Model of Quasispecies Replication", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.github.com/carolzhou/virus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OLCF's ATlas 1 & 2 filesystems use disk drive controllers from a company named Data Direct Networks. The vendor-provided monitoring software is sufficient for a small number of controllers, but is ill-suited for simultaneous monitoring of all the controllers used by OLCF. This tool provides a means of gathering performance data from multiple controllers, collating it and storing it in a database for querying by other tools.", + "laborHours": 577.6, + "name": "DDNTool", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-TechInt/DDNTool_v2/blob/master/License.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-TechInt/DDNTool_v2", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Simple Ontology Format (SOFT) library and file format specification provides a set of simple tools for developing and maintaining ontologies. The library, implemented as a perl module, supports parsing and verification of the files in SOFt format, operations with ontologies (adding, removing, or filtering of entities), and converting of ontologies into other formats. SOFT allows users to quickly create ontologies using only a basic text editor, verify it, and portray it in a graph layout system using customized styles.", + "laborHours": 684.0, + "name": "Simple Ontology Format (SOFT)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sorokine/SOFT/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sorokine/SOFT", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Atom Trajectory Viewer is a visualization tool developed to enable interactive exploration of atomic trajectories and corresponding statistics in molecular dynamics.", + "laborHours": 12996.0, + "name": "Atom Trajectory Viewer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bhatiaharsh/TrajectoryExplorer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software is the interface between LCIO (lcio.desy.de) and Julia (julialang.org), such that event records in the LCIO format can be analyzed with Julia and its libraries.", + "laborHours": 243.2, + "name": "LCIO Julia Bindings", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jstrube/LCIO.jl/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jstrube/LCIO.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CoMD-Em is a software implementation suite of the CoMD [4] proxy app using different emerging programming models. It is intended to analyze the features and capabilities of novel programming models that could help ensure code and performance portability and scalability across heterogeneous platforms while improving programmer productivity. Another goal is to provide the authors and venders with some meaningful feedback regarding the capabilities and limitations of their models. The actual application is a classical molecular dynamics (MD) simulation using either the Lennard-Jones method (LJ) or the embedded atom method (EAM) for primary particle interaction. The code can be extended to support alternate interaction models. The code is expected ro run on a wide class of heterogeneous hardware configurations like shard/distributed/hybrid memory, GPU's and any other platform supported by the underlying programming model.", + "laborHours": 1337.6, + "name": "CoMD Implementation Suite in Emerging Programming Models", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/CoMD-Chapel/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CoMD-Chapel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software provides a web interface means to upload, generate, analyze, manage and store DNA fragment length polymorphism data. This tool can easily be configured to accommodate other bio data.", + "laborHours": 380.0, + "name": "ReteBiome", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/ReteBiome/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ReteBiome", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures. VTK-m supports the fine-grained concurrency for data analysis and visualization algorithms required to drive extreme scale computing by providing abstract models for data and execution that can be applied to a variety of algorithms across many different processor architectures.", + "laborHours": 204652.8, + "name": "VTK-m v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk-m", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pecos is a python package designed to perform quality control analysis on time series data for system operations. The software loads time indexed databases, performs a series of quality control tests defined by the user, and creates automated reports which include summary statistics, tables, and graphics.", + "laborHours": 2295.2, + "name": "Pecos v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/pecos/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pecos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Sandia's Lightweight Distributed Metric Service (LDMS) is a data collection and transport system used at Livermore Computing to gather performance data across the center. While Sandia has a set of plugins available, they do not include all the data we need to capture. 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Multiple collision operator options are provided, from Krook to fully nonlinear Fokker-Planck.", + "laborHours": 1019479.2, + "name": "Continuum Gyrokinetic Edge New Technology", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/COGENT/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/cogent", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Virtual Flow Simulator (VFS) is a state-of-the-art computational fluid mechanics (CFD) package that is capable of simulating multi-physics/multi-phase flows with the most advanced turbulence models (RANS, LES) over complex terrains. The flow solver is based on the Curvilinear Immersed Boundary (CURVIB) method to handle geometrically complex and moving domains. Different modules of the VFS package can provide different simulation capabilities for specific applications ranging from the fluid-structure interaction (FSI) of solid and deformable bodies, the two-phase free surface flow solver based on the level set method for ocean waves, sediment transport models in rivers and the large-scale models of wind farms based on actuator lines and surfaces. All numerical features of VFS package have been validated with known analytical and experimental data as reported in the related journal articles. VFS package is suitable for a broad range of engineering applications within different industries. VFS has been used in different projects with applications in wind and hydrokinetic energy, offshore and near-shore ocean studies, cardiovascular and biological flows, and natural streams and river morphodynamics. Over the last decade, the development of VFS has been supported and assisted with the help of various United States companies and federal agencies that are listed in the sponsor lists. In this version, VFS-Wind contains all the necessary modeling tools for wind energy applications, including land-based and offshore wind farms. VFS is highly scalable to run on either desktop computers or high performance clusters (up to 16,000 CPUs). This released version comes with a detailed user’s manual and a set of case studies designed to facilitate the learning of the various aspects of the code in a comprehensive manner. The included documentation and support material has been elaborated in a collaboration effort with Sandia National Labs under the contract DE-EE0005482. The VFS-Wind source code is distributed under the GNU General Public License (GPL 2.0), offering to the community the flexibility to use and expand the capabilities of the package. We note that future publications including academic journals that result from the use of VFS must be cited appropriately under the GPL v.2 license agreement.", + "laborHours": 31053.6, + "name": "Virtual Flow Simulator", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SAFL-CFD-Lab/VFS-Wind", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Draco is an object-oriented component library geared towards numerically intensive, radiation (particle) transport applications built for parallel computing hardware. It consists of semi-independent packages and a robust build system. The packages in Draco provide a set of components that can be used by multiple clients to build transport codes. The build system can also be extracted for use in clients. Software includes smart pointers, Design-by-Contract assertions, unit test framework, wrapped MPI functions, a file parser, unstructured mesh data structures, a random number generator, root finders and an angular quadrature component.", + "laborHours": 67214.4, + "name": "Draco,Version 6.x.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/Draco/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/Draco", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-06" + }, + "description": "The Simulation Toolkit for Renewable Energy and Advanced Materials Modeling (STREAMM) is a python package that generates structures and input files for quantum chemical and molecular dynamics codes. STREAMM does not directly conduct simulations rather it is meant to drive quantum chemical and molecular dynamics codes to allow for high-throughput computational analysis of materials. The STREAMM package is written for python2.7 (https://www.python.org/download/releases/2.7/) and incorporates some of the core modules from the pymatgen (http://pymatgen.org/) code.", + "laborHours": 12205.6, + "languages": [ + "Python" + ], + "name": "STREAMM-tools (Simulation Toolkit for Renewable Energy Advanced Materials Modeling) [SWR-15-29]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/streamm-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-03-04" + }, + "description": "Overview of the OpenStudio® Fault Models Gem: Creating a comprehensive library of OpenStudio® fault models.\nFeatures:\n - Physics-based fault impact simulation within the capability of EnergyPlus®/OpenStudio®\n- Fault intensity implementation simulating how severe faults are (e.g., how much portion is fouled in the condenser heat exchanger) and estimating the impact of a fault in different fault intensities. \n- Fault evolution implementation simulating evolving/increasing fault intensity through certain period of time. \nFuture goals:\n- what are common/typical faults in different sample spaces (e.g., HVAC system type, building operation type, building location etc.)? \n- how often (e.g., incidence and prevalence) faults occur in different sample spaces (e.g., HVAC system type, building operation type, building location etc.)?", + "laborHours": 0.0, + "languages": [ + "Ruby", + "HTML" + ], + "name": "OpenStudio® Fault Models Gem [SWR-15-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-fault-measure-gem/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-fault-measure-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This is a Python package to translate between gdx (GAMS data) and pandas. \n\nThere are two main ways to use gdxpds. 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Starting with the Version 1.0.0 rewrite, there is now a second style of use which involves interfacing with GDX files and symbols via the `gdxpds.gdx.GdxFile` and `gdxpds.gdx.GdxSymbol` classes.\n\nPlease visit https://nrel.github.io/gdx-pandas for the latest documentation.", + "laborHours": 972.8, + "languages": [ + "Python" + ], + "name": "GDX-pandas [SWR 15-21]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/gdx-pandas", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.3.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-03-11" + }, + "description": "Bus.py is a transmission bus emulator with functionality for communicating with the distribution simulation software GridLAB-D.", + "laborHours": 1535.2, + "languages": [ + "Python" + ], + "name": "bus.py [SWR-15-14]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/buspy", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "A cost model for operational expenditures for land-based wind plants.", + "laborHours": 6733.6, + "languages": [], + "name": "LandOpExSE (Land-Based Operational Expenditures SE) [SWR-14-31]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/Plant_CostsSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This repository has been archived by the owner on Mar 6, 2024. It is now read-only.\n\nHome Energy Score is a simulation-based rating method for existing homes. Home Performance XML (HPXML) is a data transfer standard for home energy audit and retrofit data used throughout the industry. This software receives an HPXML document and translates the building characteristics into HEScore inputs compliant with their API.", + "laborHours": 23119.2, + "languages": [ + "Python" + ], + "name": "HPXML to Home Energy Score Translator (hescore-hpxml) [SWR-14-30]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hescore-hpxml", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v2023.05.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "The software consists of a CKAN extension to an existing REEGLE Tagging API.", + "laborHours": 106.4, + "languages": [], + "name": "Reegle Tagging API (CKAN Extension) [SWR-14-28]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/REEEP/ckanext-climate-tagger/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/REEEP/ckanext-climate-tagger", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Framework for Unified Systems Engineering and Design of Wind Plants ( FUSED-Wind) is an open-source framework for multi-disciplinary optimisation and analysis (MDAO) of wind energy systems, developed jointly by DTU and NREL. The framework is designed as an extension to the NASA developed OpenMDAO, and defines key I/O elements and methods necessary for wiring together different simulation codes in order to achieve a system level analysis capability of wind turbine plants with multiple levels of fidelity. NREL and DTU have developed independent interfaces to their respective simulation codes and cost models (e.g. FAST/CCBlade, HAWC2/BECAS) with the aim of offering an environment where these codes can be used interchangeably. The open source nature of the framework enables third parties to develop interfaces to their own tools, either replacing or extending those offered by DTU and NREL.", + "laborHours": 12935.2, + "languages": [ + "Python" + ], + "name": "Framework for Unified Systems Engineering and Design of Wind Plants (FUSED-Wind) cost models and case analyzer [SWR-14-25]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FUSED-Wind/fusedwind", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "THIS REPOSITORY IS DEPRECATED AND WAS ARCHIVED (READ-ONLY) on June 19, 2020.\n\nWISDEM has moved to a single, integrated repository at https://github.com/wisdem/wisdem\n\nJacketSE is a systems engineering model for 3 and 4-legged lattice structures (jackets) supporting tubular steel towers for offshore wind turbines. A module for static hydrodynamic, aerodynamic, and structural design and analysis of wind turbine jacket and towers within the Systems Engineering toolbox.", + "laborHours": 27861.6, + "languages": [ + "Fortran", + "Python" + ], + "name": "JacketSE [SWR-14-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/JacketSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "A module that allows Frame3DD to interact with codes developed at NREL within the Systems Engineering WIDEM toolbox.", + "laborHours": 7448.0, + "languages": [ + "C", + "Python" + ], + "name": "PyFrame3DD [SWR-14-22]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/pyFrame3DD", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-08-07" + }, + "description": "*** PUBLIC ARCHIVE*** THIS IS A READ-ONLY VERSION OF THE DEPRECATED VERSION. FOR THE CURRENT VERSION OF THE FLORIS SOFTWARE, SEE WWW.GITHUB.COM/NREL/FLORIS\n\nFLORIS is an engineering model of wind turbine wake interactions which accounts for the effects of turbines on the flow through the creation of wakes an accounting for both velocity deficit and wake redirection through yaw", + "laborHours": 1003.2, + "languages": [ + "OpenEdge ABL", + "Python" + ], + "name": "FLORIS [SWR-14-20]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/FLORISSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-16" + }, + "description": "rplexos is a R (statistical software framework; more? details below) package that processes and facilitates analysis of solution from PLEXOS. PLEXOS is a production cost model that is utilize to simulate the behavior of the power.systems and is developed and commercialized by Energy Exomplar. The intention is to make rptexos open-source so other PLEXOS users can utilize it.", + "laborHours": 2173.6, + "languages": [ + "C++", + "R" + ], + "name": "rplexos [SWR-14-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/rplexos/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rplexos", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.1.2" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-11-26" + }, + "description": "This package is the R implementation of the Renewable Energy Probabilistic Resource Assessment (REPRA) tool, developed at the National Renewable Energy Laboratory (NREL). REPRA is a statistical tool that models the effect of variable generation in the calculation of resource adequacy metrics. It is built as a research tool to explore different methodologies and technologies.", + "laborHours": 319.2, + "languages": [ + "C++", + "R" + ], + "name": "REPRA (Renewable Energy Probabilistic Resource Assessment) [SWR-14-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/REPRA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.3" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Cost model for Land-Based BOS for wind turbines.", + "laborHours": 1884.8, + "languages": [], + "name": "LandBOSSE (Land-Based Balance Of System) [SWR-18-43]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/WISDEM/LandBOSSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/LandBOSSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "A modular tool for simulating wind plant aerodynamics with computational fluid dynamics and turbine structural and control response to the incoming flow.", + "laborHours": 16963.2, + "languages": [ + "C++", + "C", + "Roff", + "shell", + "Fortran" + ], + "name": "Simulator for Wind Farm Applications (SOWFA) [SWR-14-12]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/SOWFA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "NREL_WISDEM is an integrated model for wind turbines and plants developed In python based on the open source software OpenMDAO. NREL_WISDEM is a set of wrappers for various wind turbine and models that integrate pre-existing models together into OpenMDAO. It is organized into groups each with their own repositories including Plant_CostSE. Plant_EnergySE, Turbine_CostSE and TurbineSE. The wrappers are designed for licensed and non-licensed models though in both cases, one has to have access to and install the individual models themselves before using them in the overall software platform.", + "laborHours": 229778.4, + "name": "NREL Wind Integrated System Design and Engineering Model", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/WISDEM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This repository has been archived by the owner on Jun 19, 2020. It is now read-only. \n\nTurbine_CostsSE is a set of models for assessing the costs of a wind turbine. The first model is a new version of NREL's turbine Cost and Scaling Model that uses 2015 survey data to compute component mass properties from key turbine parameters such as rotor diameter, rated power and hub height. A second model is a new mass-to-cost model which takes the individual component masses as inputs to estimate each component costs with additional cost factors for assembly, overhead, and profits.", + "laborHours": 2340.8, + "languages": [ + "Python" + ], + "name": "Turbine_CostSE (Turbine Cost Systems Engineering Model) DEPRECATED [SWR-13-30]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/turbine_costsse", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "nacelleSE and hubSE are a set of models that size wind turbine hub system and drivetrain components based on key turbine design parameters and load inputs from a rotor model.", + "laborHours": 3070.4, + "name": "Nacelle Systems Engineering Model and Hub Systems Engineering Model", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/drivese", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A module for static aerodynamic and structural analysis of wind turbine towers", + "laborHours": 2219.2, + "name": "TowerSE", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/towerse", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A module for static aerodynamic and structural analysis of wind turbine rotors", + "laborHours": 15960.0, + "name": "RotorSE", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/rotorse", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-12-14" + }, + "description": "pBEAM (Polynomial Beam Element Analysis Module) is a finite element method for beam-like structures.", + "laborHours": 75118.4, + "languages": [ + "C++", + "C", + "Fortran", + "Python" + ], + "name": "pBEAM (Polynomial Beam Element Analysis Module) [SWR-13-20]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/pbeam", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-10-25" + }, + "description": "A blade element momentum method for analyzing wind turbine aerodynamic performance that is robust (guaranteed convergence), fast (superlinear convergence rate), and smooth (continuously differentiable). Analytic gradients are also (optionally) provided for the distributed loads, thrust, torque, and power with respect to design variables of interest.", + "laborHours": 3587.2, + "languages": [ + "Meson", + "Fortran", + "Python" + ], + "name": "CCBlade (WISDEM®) [SWR-13-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/ccblade", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.3" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-10-25" + }, + "description": "A Python module for preprocessing and evaluating aerodynamic ainoil data---primarily for wind turbine applications.", + "laborHours": 1884.8, + "languages": [ + "Python" + ], + "name": "AirfoilPrep.py (WISDEM®) [SWR 13-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/airfoilpreppy", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2022-09-19" + }, + "description": "NREL_CSM is a set of models that provide an overall cost of energy analysis for the wind plant.", + "laborHours": 2295.2, + "languages": [], + "name": "NREL Wind Energy Cost and Scaling Model", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/nrel_csm", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DrivePy is physics-based drivetrain model that sizes drivetrain components based on aerodynamic and operational loads for use in a systems engineering model. It also calculates costs based on empirical data collected by NREL's National Wind Technology Center.", + "laborHours": 3070.4, + "name": "DrivePy", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/DriveSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-08-17" + }, + "description": "The National Renewable Energy Laboratory (NREL) has developed a new system dynamics global LUC model intended to examine LUC attributed to biofuel production. The BioLUC model represents major global, stocks, flows and produces results under different food and biofuel demand assumptions, with flexible regional divisions. This model is not intended to generate precise numerical estimates, but instead to provide insights into the drivers and dynamic interactions of LUC, population, dietary choices, and biofuel policy.", + "laborHours": 15.2, + "languages": [], + "name": "BioLUC (Bioenergy and Land Use Change) [SWR 13-08]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://creativecommons.org/licenses/by-sa/3.0/legalcode", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bioluc", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.0.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-11" + }, + "description": "pyDAKOTA is an interface to Sandia Laboratory's Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) analysis suite.\n\nAllows for users to construct DAKOTA input, feed the input to DAKOTA, and for DAKOTA to call a python object with a \"dakota_callback\" function for function evaluations.\n\nThis allows for a light-weight custom python interface to DAKOTA.\n\nThis is intended to be used with the OpenMDAO dakota driver\n\nAuthor: NREL WISDEM Team", + "laborHours": 699.2, + "languages": [ + "C++", + "Shell", + "CMake", + "Python" + ], + "name": "pyDAKOTA (Dakota Driver) [SWR-13-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/pyDAKOTA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This software is a learning model excerpted from the BSM that can be used to examine effects of different learning rates and different techno-economics on industry evolution.", + "laborHours": 15.2, + "name": "Learning in Emerging Energy Industries", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/bsm-learning/blob/master/ReadMe.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bsm-learning", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-06-12" + }, + "description": "The BACnet Client is designed to gather data from building control systems through the BACnet protocol and send to various destinations for data logging and collection.", + "laborHours": 15625.6, + "languages": [ + "Java" + ], + "name": "BACnet Client [SWR-13-26]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BACnet", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.3" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The Portals reference implementation is based on the Portals 4.X API, published by Sandia National Laboratories as a freely available public document. It is designed to be an implementation of the Portals Networking Application Programming Interface and is used by several other upper layer protocols like SHMEM, GASNet and MPI. It is implemented over existing networks, specifically Ethernet and InfiniBand networks. This implementation provides Portals networks functionality and serves as a software emulation of Portals compliant networking hardware. It can be used to develop software using the Portals API prior to the debut of Portals networking hardware, such as Bull’s BXI interconnect, as well as a substitute for portals hardware on development platforms that do not have Portals compliant hardware. The reference implementation provides new capabilities beyond that of a typical network, namely the ability to have messages matched in hardware in a way compatible with upper layer software such as MPI or SHMEM. It also offers methods of offloading network operations via triggered operations, which can be used to create offloaded collective operations. Specific details on the Portals API can be found at http://portals4.org.", + "laborHours": 65496.8, + "languages": [ + "Makefile", + "C", + "M4" + ], + "name": "Portals Reference Implementation v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/portals4?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/portals4", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Response Surface Modeling (RSM) Tool Suite is a collection of three codes used to generate an empirical interpolation function for a collection of drag coefficient calculations computed with Test Particle Monte Carlo (TPMC) simulations. The first code, \"Automated RSM\", automates the generation of a drag coefficient RSM for a particular object to a single command. \"Automated RSM\" first creates a Latin Hypercube Sample (LHS) of 1,000 ensemble members to explore the global parameter space. For each ensemble member, a TPMC simulation is performed and the object drag coefficient is computed. In the next step of the \"Automated RSM\" code, a Gaussian process is used to fit the TPMC simulations. In the final step, Markov Chain Monte Carlo (MCMC) is used to evaluate the non-analytic probability distribution function from the Gaussian process. The second code, \"RSM Area\", creates a look-up table for the projected area of the object based on input limits on the minimum and maximum allowed pitch and yaw angles and pitch and yaw angle intervals. The projected area from the look-up table is used to compute the ballistic coefficient of the object based on its pitch and yaw angle. An accurate ballistic coefficient is crucial in accurately computing the drag on an object. The third code, \"RSM Cd\", uses the RSM generated by the \"Automated RSM\" code and the projected area look-up table generated by the \"RSM Area\" code to accurately compute the drag coefficient and ballistic coefficient of the object. The user can modify the object velocity, object surface temperature, the translational temperature of the gas, the species concentrations of the gas, and the pitch and yaw angles of the object. Together, these codes allow for the accurate derivation of an object's drag coefficient and ballistic coefficient under any conditions with only knowledge of the object's geometry and mass.", + "laborHours": 3708.8, + "name": "Response Surface Modeling Tool Suite, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AndrewCWalker/rsm_tool_suite", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "LBANN is a toolkit that is designed to train artificial neural networks efficiently on high performance computing architectures. It is optimized to take advantages of key High Performance Computing features to accelerate neural network training. Specifically it is optimized for low-latency, high bandwidth interconnects, node-local NVRAM, node-local GPU accelerators, and high bandwidth parallel file systems. It is built on top of the open source Elemental distributed-memory dense and spars-direct linear algebra and optimization library that is released under the BSD license. The algorithms contained within LBANN are drawn from the academic literature and implemented to work within a distributed-memory framework.", + "laborHours": 64919.2, + "name": "Livermore Big Artificial Neural Network Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LBANN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Kokkos Clang compiler is a version of the Clang C++ compiler that has been modified to perform targeted code generation for Kokkos constructs in the goal of generating highly optimized code and to provide semantic (domain) awareness throughout the compilation toolchain of these constructs such as parallel for and parallel reduce. This approach is taken to explore the possibilities of exposing the developer’s intentions to the underlying compiler infrastructure (e.g. optimization and analysis passes within the middle stages of the compiler) instead of relying solely on the restricted capabilities of C++ template metaprogramming. To date our current activities have focused on correct GPU code generation and thus we have not yet focused on improving overall performance. The compiler is implemented by recognizing specific (syntactic) Kokkos constructs in order to bypass normal template expansion mechanisms and instead use the semantic knowledge of Kokkos to directly generate code in the compiler’s intermediate representation (IR); which is then translated into an NVIDIA-centric GPU program and supporting runtime calls. In addition, by capturing and maintaining the higher-level semantics of Kokkos directly within the lower levels of the compiler has the potential for significantly improving the ability of the compiler to communicate with the developer in the terms of their original programming model/semantics.", + "laborHours": 2076198.4, + "name": "Kokkos GPU Compiler", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/kokkos-clang/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/kokkos-clang", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "FQCDB builds up existing open source software, FastQC, implementing a modern web interface for across parsed output of FastQC. In addition, FQCDB is extensible as a web service to include additional plots of type line, boxplot, or heatmap, across data formatted according to guidelines. The interface is also configurable via more readable JSON format, enabling customization by non-web programmers.", + "laborHours": 56376.8, + "name": "FASTQ quality control dashboard", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/brwnj/fqc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"rsed\" is an R package that contains tools for stream editing: manipulating text files by making insertions, replacements, deletions, substitutions, or commenting. It hails from the powerful Unix command, \"sed\". While the \"rsed\" package is not nearly as powerful as \"see\", it is much simpler to use. R programmers often write scripts that may require simple manipulation of text files. \"rsed\" addresses that need.", + "laborHours": 136.8, + "name": "rsed", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/rsed/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/rsed", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ROSSTEP is a system for sequentially running roslaunch, rosnode, and bash scripts automatically, for use in Robot Operating System (ROS) applications. The system consists of YAML files which define actions and conditions. A python file parses the code and runs actions sequentially using the sys and subprocess python modules. Between actions, it uses various ROS-based code to check conditions required to proceed, and only moves on to the next action when all the necessary conditions have been met. Included is rosstep-creator, a QT application designed to create the YAML files required for ROSSTEP. It has a nearly one-to-one mapping from interface elements to YAML output, and serves as a convenient GUI for working with the ROSSTEP system.", + "laborHours": 714.4, + "name": "ROSSTEP v1.3", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/Kukanani/rosstep/blob/8747daaa86110b2456711906177073ba7d511f92/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Kukanani/ROSSTEP", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-01-29" + }, + "description": "Nuflood Version 1.x is a surface-water hydrodynamic package designed for the simulation of overland flow of fluids. It consists of various routines to address a wide range of applications (e.g., rainfall-runoff, tsunami, storm surge) and real time, interactive visualization tools. Nuflood has been designed for general-purpose computers and workstations containing multi-core processors and/or graphics processing units. The software is easy to use and extensible, constructed in mind for instructors, students, and practicing engineers. Nuflood is intended to assist the water resource community in planning against water-related natural disasters.", + "laborHours": 2325.6, + "languages": [], + "name": "Nuflood, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/nuflood/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/nuflood", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The contact control code is a generalized force control scheme meant to interface with a robotic arm being controlled using the Robot Operating System (ROS). The code allows the user to specify a control scheme for each control dimension in a way that many different control task controllers could be built from the same generalized controller. The input to the code includes maximum velocity, maximum force, maximum displacement, and a control law assigned to each direction and the output is a 6 degree of freedom velocity command that is sent to the robot controller.", + "laborHours": 7174.4, + "name": "Contact Control, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/UTNuclearRoboticsPublic/contact_control/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/UTNuclearRoboticsPublic/contact_control", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The spark-hdf5 package is an extension to the Apache Spark program to allow native access to HDF5 files. 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Each processor uses CUDA to set up the grid's buffer on the GPU, and that buffer is fed to other GPU languages to apply the rules of the game of life. Only the halo is copied off the buffer and exchanged using MPI. This code looks at the interoperability of GPU languages among current platforms.", + "laborHours": 1185.6, + "name": "GPULife", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnkelly/GPULife", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SANDAL is a particle-mesh simulation mini-app. The simple simulated physics propagates a set of particles in a constant, 2D wind field with Gaussian turbulence. SANDAL demonstrates the feasibility of formulating a computational physics problem using an alternative, modern design. Specifically, it is implemented using relational tables and queries, rather than array-based data model. It also is implemented with functional language design and cloud deployment, Scala and Apache Spark, rather than Fortran and MPI+X.", + "laborHours": 456.0, + "name": "Simple rANDom wALk simulation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/Sandal/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/Sandal", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-01-31" + }, + "description": "OpenStudio® is a cross-platform (Windows, Mac, and Linux) collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance. 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Users can leverage the Ruby interface to create OpenStudio Measures that can be easily shared and applied to OpenStudio Models.\n\nOPENSTUDIO® IS A REGISTERED TRADEMARK OF ALLIANCE FOR SUSTAINABLE ENERGY, LLC, THE MANAGER AND OPERATOR OF THE NATIONAL RENEWABLE ENERGY LABORATORY.", + "laborHours": 4456883.2, + "languages": [ + "Ruby", + "C++" + ], + "name": "OPENSTUDIO® [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "3.3.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-07-07" + }, + "description": "This translator takes fields from the HPXML and translates them into RESO’s Data Dictionary, which is used in MLS systems for real estate transactions across the country. The purpose is to get energy efficiency data into the real estate transaction.", + "laborHours": 167.2, + "languages": [], + "name": "HPXML2RESO (Home Performance XML to Real Estate Standards Organization Data Dictionary Translator)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hpxml2reso", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Operating software for MET-2 Vaultbot project. Pan-tilt camera control, autonomous task planning, inventory integration functions.", + "laborHours": 1048.8, + "name": "Vaultbot ROS Package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/UTNuclearRoboticsPublic/task_planning", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "NREL's Developer Network, developer.nrel.gov, provides data that users can access to provide data to their own analyses, mobile and web applications. Developers can retrieve the data through a Web services API (application programming interface). The Developer Network handles overhead of serving up web services such as key management, authentication, analytics, reporting, documentation standards, and throttling in a common architecture, while allowing web services and APIs to be maintained and managed independently.", + "laborHours": 64736.8, + "name": "Developer Network", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/developer.nrel.gov/blob/master/source/terms.html.erb", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/developer.nrel.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software is designed for efficiently integrating large-size of multi-scale environmental data using the Bayesian framework. Suppose we need to estimate the spatial distribution of variable X with high spatial resolution. The available data include (1) direct measurements Z of the unknowns with high resolution in a subset of the spatial domain (small spatial coverage), (2) measurements C of the unknowns at the median scale, and (3) measurements A of the unknowns at the coarsest scale but with large spatial coverage. The goal is to estimate the unknowns at the fine grids by conditioning to all the available data. We first consider all the unknowns as random variables and estimate conditional probability distribution of those variables by conditioning to the limited high-resolution observations (Z). We then treat the estimated probability distribution as the prior distribution. Within the Bayesian framework, we combine the median and large-scale measurements (C and A) through likelihood functions. Since we assume that all the relevant multivariate distributions are Gaussian, the resulting posterior distribution is a multivariate Gaussian distribution. The developed software provides numerical solutions of the posterior probability distribution. The software can be extended in several different ways to solve more general multi-scale data integration problems.", + "laborHours": 684.0, + "name": "Bayesian Integration of multiscale environmental data", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jschen83/Multiscale-Bayesian-Integration/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jschen83/Multiscale-Bayesian-Integration", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OpenSHMEM is an effort to create a specification for a standardized API for parallel programming in the Partitioned Global Address Space. Along with the specification the project is also creating a reference implementation of the API. This implementation attempts to be portable, to allow it to be deployed in multiple environments, and to be a starting point for implementations targeted to particular hardware platforms. It will also serve as a springboard for future development of the API.", + "laborHours": 9469.6, + "name": "Open SHMEM Reference Implementation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/openshmem-org/openshmem/blob/master/ACKNOWLEDGEMENT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openshmem-org/openshmem", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Suite of Python Libraries that implement structure data format processing, multivariate analysis, and interactive visualization of microscopy data and other spectral imaging modalities, including scanning probe microscopy, electron microscopy, Bragg diffraction microscopy, and chemical imaging.", + "laborHours": 12783.2, + "name": "pyCroscopy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pycroscopy/pycroscopy", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The purpose of this software is to interpret and analyze data taken using the NI PXIe-5171R digitizer based data acquisition system for the UCNB and Nab experiments. The detection and data acquisition systems are identical for the 2 experiments, with some differences in analysis requirements. The software converts raw binary files produced by the NI DAQ into ROOT TTree format, performs waveform analysis using trapezoidal filter algorithms, pulse fitting, and noise analysis routines, and applies variable criteria to identify valid events in the data stream. The software will be used to perform analysis of the events for multi-channel coincidences, timing and energy studies, and event rates under different experimental conditions.", + "laborHours": 5456.8, + "name": "UCNB_Analyzer", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/UCNB_Analyzer", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "GraphBench is a benchmark suite for graph pattern mining and graph analysis systems. The benchmark suite is a significant addition to conducting apples-apples comparison of graph analysis software (databases, in-memory tools, triple stores, etc.)", + "laborHours": 19121.6, + "name": "GraphBench", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ssrangan/GraphBench/blob/master/Open%20Source%20Software%20License%20(Permissive%20May%202015)%20for%20GM-SPARQL.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ssrangan/GraphBench", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Availability of accessing the World Bank Data API through the R language was limited to one existing package, which is limited in its ability. The software provides access to all of the features in World Bank API in one software package for the R language and provides functions for searching and downloading data from the World Bank API.", + "laborHours": 729.6, + "name": "wbstats", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GIST-ORNL/wbstats/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GIST-ORNL/wbstats", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Mcqueuer is a simple tool that allows anyone from researchers to experienced developers to create multi-node/multi-core jobs by simply creating a file with a list of commands. Users simply combine tasks, which would otherwise each be their own job on the cluster, into a single file that is given to Mcqueuer. Mcqueuer then does the heavy lifting required to process the tasks in parallel in a single multi-node job. In addition, Mcqueuer provides load-balancing, which frees the user from having to worry about complex memory and CPU considerations, and instead focus on the processing itself.", + "laborHours": 198785.6, + "name": "Mcqueuer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/aaronrphillips/mcqr/blob/master/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aaronrphillips/mcqr", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "AE3D solves for the shear Alfven eigenmodes and eigenfrequencies in a torodal magnetic fusion confinement device. The configuration can be either 2D (e.g. tokamak, reversed field pinch) or 3D (e.g. stellarator, helical reversed field pinch, tokamak with ripple). The equations solved are based on a reduced MHD model and sound wave coupling effects are not currently included.", + "laborHours": 1428.8, + "name": "AE3D", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-Fusion/AE3D", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Stellgap calculates the shear Alfven gap structure for 3D configurations (stellarators, RFPs, 3D tokamaks). These codes are used to calculate shear Alfven continua for 3D configurations, both with and without sound wave coupling effects.", + "laborHours": 2462.4, + "name": "Stellgap", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-Fusion/Stellgap", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-19" + }, + "description": "GeoPlace software solves several problems related to efficient sensor placement for remote sensing. It consists of several components. “GeoFoot” finds efficient locations for centering a set of camera images, in order to ensure that the collection of images contains an entire region. It is built on a modified version of “Simple MPS”. GeoSubFoot selects non-overlapping rectangular subregions of a single camera image, in order to devote more resources for higher-fidelity sub-images of those regions. The goal is for the rectangular subregions to contain many user-specified pixels of interest. Simple MPS is a generic program that produces point-sample distributions with blue noise characteristics over arbitrary-dimensional squares. GeoFoot includes an extension of it to sampling from polygons in 2d, including both the inside of the polygon and slightly outside it.", + "laborHours": 2280.0, + "languages": [ + "C++", + "Shell", + "Makefile", + "Python" + ], + "name": "GeoPlace v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/GeoPlace?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cgvalic/GeoPlace", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DFNWorks is a suite of software for generating and solving flow and transport physics on a Discrete Fracture Network (DFN). The suite is composed of three components: DFNGen: Stochastic fracture generation, mesh generation, model setup; DFNFlow: Flow solution using PFLOTRAN or FEHM control volume formulation solver; DFNTrans: Particle tracking transport; DFNGen Algorithm Description: This is a workflow that uses Mathematica software, Python scripts written by the authors and the LaGriT software to generate; DFNFlow; The solution of flow in porous media is accomplished by coupling DFNGen output with the existing software packages FEHM and PFLOTRAN. The DFNWorks workflow involves modules and scripts that translate DFNGen output to formats compatible with FEHM and PFLOTRAN input. FEHM LA-CC-2012-083 PFLOTRAN LA-CC-09-047 LaGriT LA-CC-07-38 DFNTrans Stand alone particle tracking algorithm that takes FEHM/PFLOTRAN flow solution as output and computes velocity field and advects particles.", + "laborHours": 10700.8, + "name": "dfnWorks, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/dfnWorks/dfnWorks-Version1.0/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dfnWorks/dfnWorks-Version1.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code is a toy (short) version of CODE-2016-83. From a general perspective, the code represents an unsupervised adaptive machine learning algorithm that allows efficient and high performance de-mixing and feature extraction of a multitude of non-negative signals mixed and recorded by a network of uncorrelated sensor arrays. The code identifies the number of the mixed original signals and their locations. Further, the code also allows deciphering of signals that have been delayed in regards to the mixing process in each sensor. This code is high customizable and it can be efficiently used for a fast macro-analyses of data. The code is applicable to a plethora of distinct problems: chemical decomposition, pressure transient decomposition, unknown sources/signal allocation, EM signal decomposition. An additional procedure for allocation of the unknown sources is incorporated in the code.", + "laborHours": 1960.8, + "name": "shiftNMFk 1.1: Robust Nonnegative matrix factorization with kmeans clustering and signal shift, for allocation of unknown physical sources, toy version for open sourcing with publications", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/rNMF/ShiftNMFk.jl/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rNMF/ShiftNMFk.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "A Splunk App designed to parse and tabulate PathScan data.", + "laborHours": 15.2, + "name": "PathScan for Splunk", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jwernicke/pathscan-splunk", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jwernicke/pathscan-splunk", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Mads.jl (Model analysis and decision support in Julia) is a code that streamlines the process of using data and models for analysis and decision support. It is based on another open-source code developed at LANL and written in C/C++ (MADS; http://mads.lanl.gov; LA-CC-11- 035). Mads.jl can work with external models of arbitrary complexity as well as built-in models of flow and transport in porous media. It enables a number of data- and model-based analyses including model calibration, sensitivity analysis, uncertainty quantification, and decision analysis. The code also can use a series of alternative adaptive computational techniques for Bayesian sampling, Monte Carlo, and Bayesian Information-Gap Decision Theory. The code is implemented in the Julia programming language, and has high-performance (parallel) and memory management capabilities. The code uses a series of third party modules developed by others. The code development will also include contributions to the existing third party modules written in Julia; this contributions will be important for the efficient implementation of the algorithm used by Mads.jl. The code also uses a series of LANL developed modules that are developed by Dan O'Malley; these modules will be also a part of the Mads.jl release. Mads.jl will be released under GPL V3 license. The code will be distributed as a Git repo at gitlab.com and github.com. Mads.jl manual and documentation will be posted at madsjulia.lanl.gov.", + "laborHours": 150434.4, + "name": "Mads.jl", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/madsjulia/Mads.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HPSim is a GPU-accelerated online multi-particle beam dynamics simulation tool for ion linacs. It was originally developed for use on the Los Alamos 800-MeV proton linac. It is a “z-code” that contains typical linac beam transport elements. The linac RF-gap transformation utilizes transit-time-factors to calculate the beam acceleration therein. The space-charge effects are computed using the 2D SCHEFF (Space CHarge EFFect) algorithm, which calculates the radial and longitudinal space charge forces for cylindrically symmetric beam distributions. Other space- charge routines to be incorporated include the 3D PICNIC and a 3D Poisson solver. HPSim can simulate beam dynamics in drift tube linacs (DTLs) and coupled cavity linacs (CCLs). Elliptical superconducting cavity (SC) structures will also be incorporated into the code. The computational core of the code is written in C++ and accelerated using the NVIDIA CUDA technology. Users access the core code, which is wrapped in Python/C APIs, via Pythons scripts that enable ease-of-use and automation of the simulations. The overall linac description including the EPICS PV machine control parameters is kept in an SQLite database that also contains calibration and conversion factors required to transform the machine set points into model values used in the simulation.", + "laborHours": 31661.6, + "name": "HPSim, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/apphys/hpsim/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/apphys/hpsim", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The SIERRA Toolkit is a collection of libraries to facilitate the development of parallel engineering analysis applications. These libraries supply basic core services that an engineering application may need such as a parallel distributed and dynamic mesh database (for unstructured meshes), mechanics algorithm support (parallel infrastructure only), interfaces to parallel solvers, parallel mesh and data I/O, and various utilities (timers, diagnostic tools, etc.)", + "laborHours": 8344830.4, + "languages": [ + "C++" + ], + "name": "SIERRA Toolkit v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "The IonControl software is a set of python scripts and Field-Programmable-Gate-Array (FPGA) code designed to control a trapped ion research experiment. It enables one to generate the pulses (time resolution: 20ns) necessary to control the quantum states of trapped ions and allows one to collect and analyze measurement results from trapped ion systems.", + "laborHours": 228410.4, + "languages": [ + "CSS", + "HTML", + "TeX", + "JavaScript", + "PostScript", + "Python" + ], + "name": "IonControl v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IonControl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-11-06" + }, + "description": "VOLTTRON™ is an agent execution platform providing services to its agents that allow them to easily communicate with physical devices and other resources. VOLTTRON™ delivers an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls. It enables mobile and stationary software agents to perform information gathering, processing, and control actions. VOLTTRON™ can independently manage a wide range of applications, such as HVAC systems, electric vehicles, distributed energy or entire building loads, leading to improved operational efficiency.", + "laborHours": 0.0, + "languages": [], + "name": "VOLTTRON Version 4", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron/releases/tag/4.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "4.0" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Electrostatics software under development since 1999. Soee http://www.poissonboltzmann.org/ for more detail.", + "laborHours": 262975.2, + "name": "APBS (Adaptive Poisson-Boltzmann Solver) and PDB2PQR", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electrostatics/apbs-pdb2pqr", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PyGeoTess is a Python interface module to the GeoTess gridding and earth model library from Sandia National Laboratories. It provides simplified access to a subset of the GeoTess C++ library, and takes advantage of Python's interactive interpreter and inline documentation system.", + "laborHours": 8299.2, + "name": "PyGeoTess 0.2.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LANL-Seismoacoustics/PyGeoTess/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-seismoacoustics/pygeotess", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Whole community shotgun sequencing of total DNA (i.e. metagenomics) and total RNA (i.e. metatranscriptomics) has provided a wealth of information in the microbial community structure, predicted functions, metabolic networks, and is even able to reconstruct complete genomes directly. Here we present ATLAS (Automatic Tool for Local Assembly Structures) a comprehensive pipeline for assembly, annotation, genomic binning of metagenomic and metatranscriptomic data with an integrated framework for Multi-Omics. This will provide an open source tool for the Multi-Omic community at large.", + "laborHours": 4438.4, + "name": "Automatic Tool for Local Assembly Structures", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/atlas", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The MC3 code is used to perform Monte Carlo simulations in the isothermal-isobaric ensemble (constant number of particles, temperature, and pressure) on molecular crystals. The molecules within the periodic simulation cell are treated as rigid bodies, alleviating the requirement for a complex interatomic potential. Intermolecular interactions are described using generic, atom-centered pair potentials whose parameterization is taken from the literature [D. E. Williams, J. Comput. Chem., 22, 1154 (2001)] and electrostatic interactions arising from atom-centered, fixed, point partial charges. The primary uses of the MC3 code are the computation of i) the temperature and pressure dependence of lattice parameters and thermal expansion coefficients, ii) tensors of elastic constants and compliances via the Parrinello and Rahman’s fluctuation formula [M. Parrinello and A. Rahman, J. Chem. Phys., 76, 2662 (1982)], and iii) the investigation of polymorphic phase transformations. The MC3 code is written in Fortran90 and requires LAPACK and BLAS linear algebra libraries to be linked during compilation. Computationally expensive loops are accelerated using OpenMP.", + "laborHours": 0.0, + "name": "MC3, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cawkwell/MC3", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Software library for parallel rapid order N and graph-based recursive electronic structure solvers with applications to material science, chemistry, and molecular biology.", + "laborHours": 425.6, + "name": "Progress Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/progress/progress.github.io", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The code would be used in analyses of data from the LHC, to improve the sensitivity of their experiments to new exotic particles. The software minimizes a certain function, as defined in the above reference, for some input provided by the user. The output to the user is the global minimum of that function. The code finds the global minimum using the Nelder-Mead algorithm. All the codes for the minimization including the Nelder-Mead algorithm, is written by the author. The software is written in c++.", + "laborHours": 0.0, + "name": "Topness, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/michaelgraesser/topness/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/michaelgraesser/topness", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-03-28" + }, + "description": "Sirepo is an open source framework for cloud computing. The graphical user interface (GUI) for Sirepo, also known as the client, executes in any HTML5 compliant web browser on any computing platform, including tablets. The client is built in JavaScript, making use of the following open source libraries: Bootstrap, which is fundamental for cross-platform web applications; AngularJS, which provides a model–view–controller (MVC) architecture and GUI components; and D3.js, which provides interactive plots and data-driven transformations. The Sirepo server is built on the following Python technologies: Flask, which is a lightweight framework for web development; Jinja, which is a secure and widely used templating language; and Werkzeug, a utility library that is compliant with the WSGI standard. We use Nginx as the HTTP server and proxy, which provides a scalable event-driven architecture. The physics codes supported by Sirepo execute inside a Docker container. One of the codes supported by Sirepo is the Synchrotron Radiation Workshop (SRW). SRW computes synchrotron radiation from relativistic electrons in arbitrary magnetic fields and propagates the radiation wavefronts through optical beamlines. SRW is open source and is primarily supported by Dr. Oleg Chubar of NSLS-II at Brookhaven National Laboratory.", + "laborHours": 158824.8, + "name": "Sirepo for Synchrotron Radiation Workshop", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/radiasoft/sirepo", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Sirepo is an open source framework for cloud computing. The graphical user interface (GUI) for Sirepo, also known as the client, executes in any HTML5 compliant web browser on any computing platform, including tablets. The client is built in JavaScript, making use of the following open source libraries: Bootstrap, which is fundamental for cross-platform web applications; AngularJS, which provides a model–view–controller (MVC) architecture and GUI components; and D3.js, which provides interactive plots and data-driven transformations. The Sirepo server is built on the following Python technologies: Flask, which is a lightweight framework for web development; Jin-ja, which is a secure and widely used templating language; and Werkzeug, a utility library that is compliant with the WSGI standard. We use Nginx as the HTTP server and proxy, which provides a scalable event-driven architecture. The physics codes supported by Sirepo execute inside a Docker container. One of the codes supported by Sirepo is Warp. Warp is a particle-in-cell (PIC) code de-signed to simulate high-intensity charged particle beams and plasmas in both the electrostatic and electromagnetic regimes, with a wide variety of integrated physics models and diagnostics. At pre-sent, Sirepo supports a small subset of Warp’s capabilities. Warp is open source and is part of the Berkeley Lab Accelerator Simulation Toolkit.", + "laborHours": 158824.8, + "name": "Sirepo - Warp", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/radiasoft/sirepo", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OSCARS is a general purpose code for computation of radiation from charged particles in motion.", + "laborHours": 18559.2, + "name": "Open Source Code for Advanced Radiation Simulation", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/dhidas/OSCARS/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dhidas/OSCARS", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Nanoindentation is a tool that allows the mechanical response of a variety of materials at the nano to micron length scale to be measured. Recent advances in spherical nanoindentation techniques have allowed for a more reliable and meaningful characterization of the mechanical response from nanoindentation experiments in the form on an indentation stress-strain curve. This code base, Spin, is written in MATLAB (The Mathworks, Inc.) and based on the analysis protocols developed by S.R. Kalidindi and S. Pathak [1, 2]. The inputs include the displacement, load, harmonic contact stiffness, harmonic displacement, and harmonic load from spherical nanoindentation tests in the form of an Excel (Microsoft) spreadsheet. The outputs include indentation stress-strain curves and indentation properties as well their variance due to the uncertainty of the zero-point correction in the form of MATLAB data (.mat) and figures (.png). [1] S. Pathak, S.R. Kalidindi. Spherical nanoindentation stress–strain curves, Mater. Sci. Eng R-Rep 91 (2015). [2] S.R. Kalidindi, S. Pathak. Determination of the effective zero-point and the extraction of spherical nanoindentation stress-strain curves, Acta Materialia 56 (2008) 3523-3532.", + "laborHours": 440.8, + "name": "Spherical nanoindentation stress-strain analysis, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jsweaver/Spin", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-03-21" + }, + "description": "Arion is a library and tool set that enables researchers to holistically define test system models. To define a complex system for testing an algorithm or control requires expertise across multiple domains. Simulating a complex system requires the integration of multiple simulators and test hardware, each with their own specification languages and concepts. This requires extensive set of knowledge and capabilities. Arion was developed to alleviate this challenge. Arion is a library of Java libraries that abstracts the concepts from supported simulators into a cohesive model language that allows someone to build models to their needed level of fidelity and expertise. Arion is also a software tool that translates the users model back into the specification languages of the simulators and test hardware needed for execution.", + "laborHours": 10016.8, + "languages": [], + "name": "Arion", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/arion/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/arion", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A system for processing network packet capture streams, extracting metadata and generating flow records (via Argus). The system can be used by network security operators and analysts to enable forensic investigations for network security events.", + "laborHours": 1094.4, + "name": "Retro-Future", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cardi/timefind", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MADSpython (Model analysis and decision support tools in Python) is a code in Python that streamlines the process of using data and models for analysis and decision support using the code MADS. MADS is open-source code developed at LANL and written in C/C++ (MADS; http://mads.lanl.gov; LA-CC-11-035). MADS can work with external models of arbitrary complexity as well as built-in models of flow and transport in porous media. The Python scripts in MADSpython facilitate the generation of input and output file needed by MADS as wells as the external simulators which include FEHM and PFLOTRAN. MADSpython enables a number of data- and model-based analyses including model calibration, sensitivity analysis, uncertainty quantification, and decision analysis. MADSpython will be released under GPL V3 license. MADSpython will be distributed as a Git repo at gitlab.com and github.com. MADSpython manual and documentation will be posted at http://madspy.lanl.gov.", + "laborHours": 182.4, + "name": "MADSpython 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/madspython", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-11-26" + }, + "description": "MICOT is a tool for optimizing and controlling infrastructure systems. In includes modules for optimizing the operations of an infrastructure structure (for example optimal dispatch), designing infrastructure systems, restoring infrastructures systems, resiliency, preparing for natural disasters, interdicting networks, state estimation, sensor placement, and simulation of infrastructure systems. It implements algorithms developed at LANL that have been published in the academic community. This is a release of the of resilient design module of the MICOT.", + "laborHours": 12281858.4, + "languages": [], + "name": "Multi Infrastructure Control and Optimization Toolkit, Resilient Design Module (MICOT-RDT), version 2.X", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl-ansi/micot-rdt/blob/master/LICENCE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/micot", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-10" + }, + "description": "RmultiProcess software is designed to work with multiple correlated sensors. The characteristic that allows data to be filled in or the support to be changed is correlation, the interdependence between observations.", + "laborHours": 167.2, + "languages": [], + "name": "Multivariate Gaussian Process Model for Correlated Time Series in R", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/multivariate-gaussian-process-model-for-correlated-time-series-in-r", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Returns bitwise identical sums regardless of the order of the summands. Uses no branches and mostly integer operations. Designed to be vectorizeable.", + "laborHours": 60.8, + "name": "Branchless Reproducible Floating Point Summation With Integers, Version 1.x.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/peterahrens/BranchlessReproducibleFloatingPointWithIntegers/blob/master/brfpwi.c", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/peterahrens/BranchlessReproducibleFloatingPointWithIntegers", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DView is a time series data visualization tool that provides several different ways to plot time series datasets. It is particularly well suited for browsing the results of energy systems simulation programs such as BeOpt, SAM, and PVWatts.", + "laborHours": 205640.8, + "name": "DVIEW", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/wex", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This software presents a user-provided multivariate dataset as an interactive three dimensional visualization so that the user can explore the correlation between variables in the observations and the distribution of observations among the variables.", + "laborHours": 896.8, + "name": "Parallel Planes Information Visualization", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/infovis-parallel", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Clog is a library of charged particle stopping powers and related Coulomb logarithm processes in a plasma. The stopping power is a particularly useful quantity for plasma physics, as it measures the energy loss of per unit length of charged particle as it traverses a plasma. Clog's primary stopping power is the BPS (Brown-Preston-Singleton) theory.", + "laborHours": 5532.8, + "name": "Coulomb Logarithm, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/clog/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/clog", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "NJOY2016 is used to convert evaluations in the Evaluated Nuclear Data Files (ENDF) format into forms useful for practical applications such as fission and fusion reactor analysis, criticality safety, radiation shielding, nuclear waste management, nuclear medicine procedures, and more. It begins with the generation of pointwise libraries, including reaction and resonance reconstruction, Doppler broadening, radiation heating and damage, thermal scattering data, unresolved resonance data, and gas production. It reviews the production of libraries for the continuous-energy Monte Carlo code MCNP, multigroup neutron, photon, and particle cross sections and matrices, and photon interaction data. Uncertainty information for ENDF data is processed, including the capability for calculating covariances of resonance data, angular distributions, energy distributions, and radioactive nuclide production. NJOY can prepare and process thermal scattering data evaluations into application libraries. It can also plot cross sections, angular distributions and secondary emission spectra.", + "laborHours": 1945.6, + "name": "NJOY2016", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/njoy/NJOY21/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/njoy/NJOY21.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Tusas is a general / flexible software framework for solving coupled systems of onlinear partial differential equations. Tusas was originally developed for phase-field simulation of solidification. In order for Tusas to be effective, the PDEs must be compatible with structured or unstructured Lagrange (nodal) finite element discretizations and explicit (Euler) or implicit (Euler, Trapezoid, BDF2) temporal discretizations.", + "laborHours": 10442.4, + "name": "Tusas, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chrisknewman/tusas", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code implements the non-homogeneous poisson process model for estimating the rate of fast radio bursts. It includes modeling terms for the distribution of events in the Universe and the detection sensitivity of the radio telescopes and arrays used in observation. The model is described in LA-UR-16-26261.", + "laborHours": 121.6, + "name": "NHPP for FRBs, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/NHPP-for-FRBs/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/NHPP-for-FRBs", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "TBM3 is an open source package for computational simulations of quantum materials at multiple scales in length and time. The project originated to investigate the multiferroic behavior in transition-metal oxide heterostructures. The framework has also been designed to study emergent phemona in other quantum materials like 2-dimensional transition-metal dichalcogenides, graphene, topological insulators, and skyrmion in materials, etc. In the long term, we will enable the package for transport and time-resolved phenomena. TBM3 is currently a C++ based numerical tool package and framework for the design and construction of any kind of lattice structures with multi-orbital and spin degrees of freedom. The fortran based portion of the package will be added in the near future. The design of TBM3 is in a highly flexible and reusable framework and the tight-binding parameters can be modeled or informed by DFT calculations. It is currently GPU enabled and feature of CPU enabled MPI will be added in the future.", + "laborHours": 4286.4, + "name": "Tight-binding model for materials at mesoscale", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/TDIV/TBM3/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/TDIV/TBM3", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "An example of reading the Galacticus HDF5 file in R and a demonstration of some of the features of the data.", + "laborHours": 15.2, + "name": "Galacticus HDF5 Example, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/Galacticus-HDF5-Example/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/Galacticus-HDF5-Example", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PcapDB is a packet capture system designed to optimize the captured data for fast search in the typical (network incident response) use case. The technology involved in this software has been submitted via the IDEAS system and has been filed as a provisional patent. It includes the following primary components: capture: The capture component utilizes existing capture libraries to retrieve packets from network interfaces. Once retrieved the packets are passed to additional threads for sorting into flows and indexing. The sorted flows and indexes are passed to other threads so that they can be written to disk. These components are written in the C programming language. search: The search components provide a means to find relevant flows and the associated packets. A search query is parsed and represented as a search tree. Various search commands, written in C, are then used resolve this tree into a set of search results. The tree generation and search execution management components are written in python. interface: The PcapDB web interface is written in Python on the Django framework. It provides a series of pages, API's, and asynchronous tasks that allow the user to manage the capture system, perform searches, and retrieve results. Web page components are written in HTML,CSS and Javascript.", + "laborHours": 194301.6, + "name": "PcapDB: Search Optimized Packet Capture, Version 0.1.0.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dirtbags/pcapdb", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The JMP Add-In TopN-PFS provides an automated tool for finding layered Pareto front to identify the top N solutions from an enumerated list of candidates subject to optimizing multiple criteria. The approach constructs the N layers of Pareto fronts, and then provides a suite of graphical tools to explore the alternatives based on different prioritizations of the criteria. The tool is designed to provide a set of alternatives from which the decision-maker can select the best option for their study goals.", + "laborHours": 0.0, + "name": "TopN-Pareto Front Search", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/candcook/TopN-PFS/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/candcook/TopN-PFS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Code Analysis and Refactoring with Clang Tools is a small set of example code that demonstrates techniques for applying tools distributed with the open source Clang compiler. Examples include analyzing where variables are used and replacing old data structures with standard structures.", + "laborHours": 2675.2, + "name": "Code Analysis and Refactoring with Clang Tools, Version 0.1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/CoARCT", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A common operation in scientific visualization is to compute and render a contour of a data set. Given a function of the form f : R^d -> R, a level set is defined as an inverse image f^-1(h) for an isovalue h, and a contour is a single connected component of a level set. The Reeb graph can then be defined to be the result of contracting each contour to a single point, and is well defined for Euclidean spaces or for general manifolds. For simple domains, the graph is guaranteed to be a tree, and is called the contour tree. Analysis can then be performed on the contour tree in order to identify isovalues of particular interest, based on various metrics, and render the corresponding contours, without having to know such isovalues a priori. This code is intended to be the first data-parallel algorithm for computing contour trees. Our implementation will use the portable data-parallel primitives provided by Nvidia’s Thrust library, allowing us to compile our same code for both GPUs and multi-core CPUs. Native OpenMP and purely serial versions of the code will likely also be included. It will also be extended to provide a hybrid data-parallel / distributed algorithm, allowing scaling beyond a single GPU or CPU.", + "laborHours": 204652.8, + "name": "Hybrid Parallel Contour Trees, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.kitware.com/vtk/vtk-m/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk-m", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The ParSplice code implements the Parallel Trajectory Splicing algorithm described in [1]. This method is part of the Accelerated Molecular Dynamics family of techniques developed in Los Alamos National Laboratory over the last 16 years. These methods aim at generating high-quality trajectories of ensembles of atoms in materials. ParSplice uses multiple independent replicas of the system in order to parallelize the generation of such trajectories in the time domain, enabling simulations of systems of modest size over very long timescales. ParSplice includes capabilities to store configurations of the system, to generate and distribute tasks across a large number of processors, and to harvest the results of these tasks to generate long trajectories. ParSplice is a management layer that orchestrate large number of calculations, but it does not perform the actual molecular dynamics itself; this is done by external molecular dynamics engines. [1] Danny Perez, Ekin D Cubuk, Amos Waterland, Efthimios Kaxiras, Arthur F Voter, Long-time dynamics through parallel trajectory splicing, Journal of chemical theory and computation 12, 18 (2015)", + "laborHours": 1398.4, + "name": "ParSplice, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/dannyperez/parsplice/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/dannyperez/parsplice", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "TRPS code was developed for the project \"Time Resolved Phonon Spectroscopy\". Routines contained in this piece of software were specially created to model phonon generation and tracking within materials that interact with ionizing radiation, particularly applicable to the modeling of cryogenic radiation detectors for dark matter and neutrino research. These routines were created to link seamlessly with the open source Geant4 framework for the modeling of radiation transport in matter, with the explicit intent of open sourcing them for eventual integration into that code base.", + "laborHours": 1124.8, + "name": "Time Resolved Phonon Spectroscopy, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/goett/TRPS/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/goett/TRPS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "It can be challenging to interface National Instruments LabVIEW (http://www.ni.com/labview/) with EPICS (http://www.aps.anl.gov/epics/). Such interface is required when an instrument control program was developed in LabVIEW but it also has to be part of global control system. This is frequently useful in big accelerator facilities. The Channel Access Server is written in LabVIEW, so it works on any hardware/software platform where LabVIEW is available. It provides full server functionality, so any EPICS client can communicate with it.", + "laborHours": 243.2, + "name": "EPICS Channel Access Server for LabVIEW", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/az9/LVCA/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/az9/LVCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Fortran language does not provide a standard library that implements generic containers, like linked lists, trees, dictionaries, etc. The GFC software provides an implementation of generic Fortran containers natively written in Fortran 2003/2008 language. The following containers are either already implemented or planned: Stack (done), Linked list (done), Tree (done), Dictionary (done), Queue (planned), Priority queue (planned).", + "laborHours": 8268.8, + "name": "Generic Fortran Containers (GFC)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/DmitryLyakh/GFC", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Flexible visible exploration of long, high-resolution time series from multiple sensor streams is a challenge in several domains. Falcon is a visual analytics approach that helps researchers acquire a deep understanding of patterns in log and imagery data. Falcon allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations with multiple levels of detail. These capabilities are applicable to the analysis of any quantitative time series.", + "laborHours": 0.0, + "name": "Falcon: A Temporal Visual Analysis System", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csteed/falcon", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DFNWorks is a suite of software for generating and solving flow and transport physics on a Discrete Fracture Network (DFN). The suite is composed of three components: DFNGen: Stochastic fracture generation, mesh generation, model setup; DFNFlow: Flow solution using PFLOTRAN or FEHM control volume formulation solver; DFNTrans: Particle tracking transport; DFNGen Algorithm Description: This is a workflow that uses C++ software version for fracture generation, Python scripts written by the authors and the LaGriT software to generate computational mesh. DFNFlow The solution of flow in porous media is accomplished by coupling DFNGen output with the existing software packages FEHM and PFLOTRAN. The DFNWorks workflow involves modules and scripts that translate DFNGen output to formats compatible with FEHM and PFLOTRAN input. FEHM LA-CC-2012-083 PFLOTRAN LA-CC-09-047 LaGriT LA-CC-07-38 DFNTrans Stand-alone particle tracking algorithm that takes FEHM/PFLOTRAN flow solution as output and computes velocity field and advects particles.", + "laborHours": 0.0, + "name": "dfnWorks, Version 2.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dfnWorks/dfnWorks-Version2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code is made to model the effect of muons in a future double beta decay array with the Geant4 software framework.", + "laborHours": 471.2, + "name": "Muon GUORE - Geant4 MACRO for nextGEN 0vBB", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/massarczyk/Muon_GUORE/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/massarczyk/Muon_GUORE", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Securely transferring timing information in the electrical grid is a critical component of securing the nation's infrastructure from cyber attacks. One solution to this problem is to use quantum information to securely transfer the timing information across sites. This software provides such an infrastructure using a standard Java webserver that pulls the quantum information from associated hardware.", + "laborHours": 699.2, + "name": "TASQC Quantum Key Transfer Program", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/TASQC/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/TASQC", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Finding Godsil-McKay switching sets in graphs is one way to demonstrate that a specific graph is not determined by its spectrum--the eigenvalues of its adjacency matrix. An important area of active research in pure mathematics is determining which graphs are determined by their spectra, i.e. when the spectrum of the adjacency matrix uniquely determines the underlying graph. We are interested in exploring the spectra of graphs in the Johnson scheme and specifically seek to determine which of these graphs are determined by their spectra. Given a graph G, a Godsil-McKay switching set is an induced subgraph H on 2k vertices with the following properties: I) H is regular, ii) every vertex in G/H is adjacent to either 0, k, or 2k vertices of H, and iii) at least one vertex in G/H is adjacent to k vertices in H. The software package examines each subset of a user specified size to determine whether or not it satisfies those 3 conditions. The software makes use of the massive parallel processing power of CUDA enabled GPUs. It also exploits the vertex transitivity of graphs in the Johnson scheme by reasoning that if G has a Godsil-McKay switching set, then it has a switching set which includes vertex 1. While the code (in its current state) is tuned to this specific problem, the method of examining each induced subgraph of G can be easily re-written to check for any user specified conditions on the subgraphs and can therefore be used much more broadly.", + "laborHours": 106.4, + "name": "CUDA Enabled Graph Subset Examiner", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jtjohnston/computational_combinatorics/blob/master/GM-switching/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jtjohnston/computational_combinatorics", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Hybrid programming models for beyond-CMOS technologies will prove critical for integrating new computing technologies alongside our existing infrastructure. Unfortunately the software infrastructure required to enable this is lacking or not available. XACC is a programming framework for extreme-scale, post-exascale accelerator architectures that integrates alongside existing conventional applications. It is a pluggable framework for programming languages developed for next-gen computing hardware architectures like quantum and neuromorphic computing. It lets computational scientists efficiently off-load classically intractable work to attached accelerators through user-friendly Kernel definitions. XACC makes post-exascale hybrid programming approachable for domain computational scientists.", + "laborHours": 454860.0, + "name": "XACC - eXtreme-scale Accelerator Programming Framework", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/xacc", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "There is a lack of state-of-the-art HPC simulation tools for simulating general quantum computing. Furthermore, there are no real software tools that integrate current quantum computers into existing classical HPC workflows. This product, the Quantum Virtual Machine (QVM), solves this problem by providing an extensible framework for pluggable virtual, or physical, quantum processing units (QPUs). It enables the execution of low level quantum assembly codes and returns the results of such executions.", + "laborHours": 15.2, + "name": "Quantum Virtual Machine (QVM)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-QCI/qvm", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/qvm", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "There is a lack of state-of-the-art quantum computing simulation software that scales on heterogeneous systems like Titan. Tensor Network Quantum Virtual Machine (TNQVM) provides a quantum simulator that leverages a distributed network of GPUs to simulate quantum circuits in a manner that leverages recent results from tensor network theory.", + "laborHours": 23332.0, + "name": "Tensor Network Quantum Virtual Machine (TNQVM)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-QCI/tnqvm/blob/master/examples/CMakeLists.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/tnqvm", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "There are many common software patterns and utilities for the ORNL Quantum Computing Institute that can and should be shared across projects. Otherwise we find duplication of code which adds unwanted complexity. This is a software product seeks to alleviate this by providing common utilities such as object factories, graph data structures, parameter input mechanisms, etc., for other software products within the ORNL Quantum Computing Institute. This work enables pure basic research, has no export controlled utilities, and has no real commercial value.", + "laborHours": 334.4, + "name": "QCI Common", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/common", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "In this era of data-driven decisions and discovery where Big Data is producing Bigger Data, data scientists at the Oak Ridge National Laboratory are leveraging unique leadership infrastructure (e.g., Urika XA and Urika GD appliances) to develop scalable algorithms for semantic, logical and statistical reasoning with Big Data (i.e., data stored in databases as well as unstructured data in documents). ORiGAMI is a next-generation knowledge-discovery framework that is: (a) knowledge nurturing (i.e., evolves seamlessly with newer knowledge and data), (b) smart and curious (i.e. using information-foraging and reasoning algorithms to digest content) and (c) synergistic (i.e., interfaces computers with what they do best to help subject-matter-experts do their best. ORiGAMI has been demonstrated using the National Library of Medicine's SEMANTIC MEDLINE (archive of medical knowledge since 1994).", + "laborHours": 136.8, + "name": "Oak Ridge Graph Analytics for Medical Innovation (ORiGAMI)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ssrangan/origami/blob/master/Open%20Source%20Software%20License.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ssrangan/origami", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Portage is a software library system for physics remapping (mapping physics variables from one computational mesh to another) either within a single simulation code or between two disparate simulation codes. Portage is designed to utilize advanced-architecture compute platforms and to be easily extensible by third parties.", + "laborHours": 73157.6, + "name": "Portage, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/laristra/portage/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laristra/portage", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "In order to support engineering analysis of Virtual Environment for Reactor Analysis (VERA) model results, the Consortium for Advanced Simulation of Light Water Reactors (CASL) needs a tool that provides visualizations of HDF5 files that adhere to the VERAOUT specification. VERAView provides an interactive graphical interface for the visualization and engineering analyses of output data from VERA. The Python-based software provides instantaneous 2D and 3D images, 1D plots, and alphanumeric data from VERA multi-physics simulations.", + "laborHours": 21675.2, + "name": "VERAView", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CASL/VERAview", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The iESM is a simulation code that represents the physical and biological aspects of Earth's climate system, and also includes the macro-economic and demographic properties of human societies. The human aspect of the simulation code is focused in particular on the effects of human activities on land use and land cover change, but also includes aspects such as energy economies. The time frame for predictions with iESM is approximately 1970 through 2100.", + "laborHours": 6406374.4, + "name": "Integrated Earth System Model (iESM)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ACME-Climate/iESM/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ACME-Climate/iESM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MultiMatTest is a demonstration code to support a talk and paper titled A Comparative Study of Multi-material Data Structures for Computational Physics Applications. The application times basic operations for different representations of multi-material data structures.", + "laborHours": 1155.2, + "name": "MultiMatTest, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/MultiMatTest/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL/MultiMatTest", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Ring current Atmosphere interactions Model with Self-Consistent magnetic field (B) is a unique code that combines a kinetic model of ring current plasma with a three dimensional force-balanced model of the terrestrial magnetic field. The kinetic portion, RAM, solves the kinetic equation to yield the bounce-averaged distribution function as a function of azimuth, radial distance, energy and pitch angle for three ion species (H+, He+, and O+) and, optionally, electrons. The domain is a circle in the Solar-Magnetic (SM) equatorial plane with a radial span of 2 to 6.5 RE. It has an energy range of approximately 100 eV to 500 KeV. The 3-D force balanced magnetic field model, SCB, balances the JxB force with the divergence of the general pressure tensor to calculate the magnetic field configuration within its domain. The domain ranges from near the Earth’s surface, where the field is assumed dipolar, to the shell created by field lines passing through the SM equatorial plane at a radial distance of 6.5 RE. The two codes work in tandem, with RAM providing anisotropic pressure to SCB and SCB returning the self-consistent magnetic field through which RAM plasma is advected.", + "laborHours": 81259.2, + "name": "Ring current Atmosphere interactions Model with Self-Consistent Magnetic field", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/RAM-SCB/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/RAM-SCB", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Mercat is a highly scalable property software package for robust of analysis of features in next-generation sequencing data and observed unique peptides from metaproteomic data. Mercat is offered in python 3.5/anaconda3, is multiparellel and is easily installed using bioconda/conda recipes. Mercat inputs include assembled contigs, raw sequence reads from any platform, and unique peptide files obtained from proteomics with feature abundance counts tables. Mercat is the only software available that allows for direct analysis of data properties without a data-dependent search tools such as BLAST or diamond for compositional analysis of whole community shotgun sequencing (e.g. metagenomes and/or metatranscriptomes) or metaproteomic data.", + "laborHours": 380.0, + "name": "Mercat", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/mercat/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mercat", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pinyon is a tool that stores steps involved in creating a model derived from a collection of data. The main function of Pinyon is to store descriptions of calculations used to analyze or visualize the data in a database, and allow users to view the results of these calculations via a web interface. Additionally, users may also use the web interface to make adjustments to the calculations and rerun the entire collection of analysis steps automatically.", + "laborHours": 6505.6, + "name": "Pinyon, Version 0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/pinyon/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pinyon", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "System for converting DESIRE (Direct Executing Simulation in Real Time) simulation models to executable code models (C# / C++). These converted models are used as the basis for 2 products, one of which is the focus of this review: an engineering design interface for Fissile Solution Systems. ModelConverter.exe (C#) converts DESIRE model inputs to a C++ plug-in subclass. SimApp.exe (C# / C++) has a C++ dll that is a numerical integration engine that the Converted models plug into. The engineering design interface is a C# GUI that calls on the C++ dll to execute a particular converted model. The GUI allows the user to specify the length of a simulation, run the simulation, view data plots and data tables. Stability plots may also be produced and manipulated. The engineering design interface will be released as source code and executable; the model converter source is also intended for release.", + "laborHours": 13710.4, + "name": "SimApp 1.8.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/determan/SimApp1.8x/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/determan/SimApp1.8x.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Grappa is a latency tolerant runtime system for mass market computer systems comprised of multiple nodes having x86 multicore processors and infiniband interconnect. Grappa is designed to enable in-memory irregular applications written in the C++ programming language to scale up on multiprocessor systems. Grappa addresses the load balance, communication, and synchronization challenges posed by running applications that do not partition evenly across large systems. Two mechanisms are essential to its success: fast task switching and message aggregation. Fast task switching enables processors to tolerate communication and synchronization delays; aggregation sustains high bandwidth on low injection rate networks.", + "laborHours": 120764.0, + "name": "A Latency Tolerant Runtime System for Mass Market Computer Systems", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/uwsampa/grappa", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The GIBS software program is a Grand Canonical Monte Carlo (GCMC) simulation program (written in C++) that can be used for 1) computing the excess chemical potential of ions and the mean activity coefficients of salts in homogeneous electrolyte solutions; and, 2) for computing the distribution of ions around fixed macromolecules such as, nucleic acids and proteins. The solvent can be represented as neutral hard spheres or as a dielectric continuum. The ions are represented as charged hard spheres that can interact via Coulomb, hard-sphere, or Lennard-Jones potentials. In addition to hard-sphere repulsions, the ions can also be made to interact with the solvent hard spheres via short-ranged attractive square-well potentials.", + "laborHours": 3906.4, + "name": "A Grand Canonical Monte Carlo simulation program for computing ion distributions around biomolecules in hard sphere solvents", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/30876-615-os", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electrostatics/GIBS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Futility package contains the following: 1) Definition of the size of integers and real numbers; 2) A generic Unit test harness; 3) Definitions for some basic extensions to the Fortran language: arbitrary length strings, a parameter list construct, exception handlers, command line processor, timers; 4) Geometry definitions: point, line, plane, box, cylinder, polyhedron; 5) File wrapper functions: standard Fortran input/output files, Fortran binary files, HDF5 files; 6) Parallel wrapper functions: MPI, and Open MP abstraction layers, partitioning algorithms; 7) Math utilities: BLAS, Matrix and Vector definitions, Linear Solver methods and wrappers for other TPLs (PETSC, MKL, etc), preconditioner classes; 8) Misc: random number generator, water saturation properties, sorting algorithms.", + "laborHours": 99727.2, + "name": "Futility", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CASL/Futility", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software provides a real-time processing system for sonar to detect and track animals, and to extract water column biomass statistics in order to facilitate continuous monitoring of an underwater environment. The Nekton Interaction Monitoring System (NIMS) extracts and archives tracking and backscatter statistics data from a real-time stream of data from a sonar device. NIMS also sends real-time tracking messages over the network that can be used by other systems to generate other metrics or to trigger instruments such as an optical video camera. A web-based user interface provides remote monitoring and control. NIMS currently supports three popular sonar devices: M3 multi-beam sonar (Kongsberg), EK60 split-beam echo-sounder (Simrad) and BlueView acoustic camera (Teledyne).", + "laborHours": 164707.2, + "name": "Nekton Interaction Monitoring System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/nims/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/nims", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2022-11-18" + }, + "description": "Transactive Energy Simulation Platform (TESP) combines existing domain simulators in the electric power grid, buildings, and communication systems, with new transactive agents, growth models and evaluation scripts. The existing domain simulators include GridLAB-D for the distribution grid and single-family residential buildings, MATPOWER for transmission and bulk generation, EnergyPlus for large buildings and ns-3 for communication systems. More are planned for subsequent versions of TESP. The new elements are: TEAgents - simulate market participants and transactive systems for market clearing. Some of this functionality was extracted from GridLAB-D and implemented in Python for customization by PNNL and others. Growth Model - a means for simulating system changes over a multiyear period, including both normal load growth and specific investment decisions. Customizable in Python code. Evaluation Script - a means of evaluating different transactive systems through customizable post-processing in Python code. TESP will run on Linux, Windows and Mac OS X.", + "laborHours": 46892.0, + "languages": [], + "name": "Transactive Energy Simulation Platform", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/tesp", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Haystack is a software agent platform for user emulation. We are leveraging python and the SPADE software packages to develop an architecture and platform where software agents can be sent actuation behaviors, configured with different behavior profiles (time based, event based, probability based, etc.), and controlled/monitored from a central control unit. The haystack agent platform provides the ability to model and simulate user behavior in cyber systems. This eliminates the need to fund real users to provide this interaction, provides control such that researchers can randomize, hold-steady, or model whatever behavior that want to study without running afoul of IRB requirements, and provides a documented truth that enables understanding what happened in and experiment and provides for repeatability.", + "laborHours": 364.8, + "name": "Haystack", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/haystack", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code solves the gray thermal radiative transfer (TRT) equations in parallel using simple opacities and Cartesian meshes. Although Branson solves the TRT equations it is not designed to model radiation transport: Branson contains simple physics and does not have a multigroup treatment, nor can it use physical material data. The opacities have are simple polynomials in temperature there is a limited ability to specify complex geometries and sources. Branson was designed only to capture the computational demands of production IMC codes, especially in large parallel runs. It was also intended to foster collaboration with vendors, universities and other DOE partners. Branson is similar in character to the neutron transport proxy-app Quicksilver from LLNL, which was recently open-sourced.", + "laborHours": 33987.2, + "name": "Branson: A Mini-App for Studying Parallel IMC, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/branson/blob/develop/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/branson", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "WARP, which can stand for ``Weaving All the Random Particles,'' is a three-dimensional (3D) continuous energy Monte Carlo neutron transport code developed at UC Berkeley to efficiently execute on NVIDIA graphics processing unit (GPU) platforms. WARP accelerates Monte Carlo simulations while preserving the benefits of using the Monte Carlo method, namely, that very few physical and geometrical simplifications are applied. WARP is able to calculate multiplication factors, neutron flux distributions (in both space and energy), and fission source distributions for time-independent neutron transport problems. It can run in both criticality or fixed source modes, but fixed source mode is currently not robust, optimized, or maintained in the newest version. WARP can transport neutrons in unrestricted arrangements of parallelepipeds, hexagonal prisms, cylinders, and spheres. The goal of developing WARP is to investigate algorithms that can grow into a full-featured, continuous energy, Monte Carlo neutron transport code that is accelerated by running on GPUs. The crux of the effort is to make Monte Carlo calculations faster while producing accurate results. Modern supercomputers are commonly being built with GPU coprocessor cards in their nodes to increase their computational efficiency and performance. GPUs execute efficiently on data-parallel problems, but most CPU codes, including those for Monte Carlo neutral particle transport, are predominantly task-parallel. WARP uses a data-parallel neutron transport algorithm to take advantage of the computing power GPUs offer.", + "laborHours": 7083.2, + "name": "WARP", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sellitforcache/warp/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sellitforcache/warp", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Memory systems are expected to get evermore complicated in the coming years, and it isn't clear exactly what form that complexity will take. On the software side, a simple, flexible way of identifying and working with memory pools is needed. Additionally, most developers seek code portability and do not want to learn the intricacies of complex memory. Hence, we believe that a library for interacting with complex memory systems should expose two kinds of abstraction: First, a low-level, mechanism-based interface designed for the runtime or advanced user that wants complete control, with its focus on simplified representation but with all decisions left to the caller. Second, a high-level, policy-based interface designed for ease of use for the application developer, in which we aim for best-practice decisions based on application intent. We have developed such a library, called SICM: Simplified Interface to Complex Memory.", + "laborHours": 17829.6, + "name": "Simplified Interface to Complex Memory Hierarchies 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SICM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CHROTRAN is a fork of the widely-used PFLOTRAN flow and reactive transport numerical simulation code. It implements custom physics and chemistry appropriate to the design of in-situ reduction of heavy metals such as Cr(VI) in groundwater. CHROTRAN includes full dynamics for five species: the metal to be remediated, an electron donor, biofilm, a nontoxic conservative bio-inhibitor, and a biocide. Direct abiotic reduction by donor-metal interaction as well as donor-driven biomass growth and bio-reduction are modeled, along with crucial processes such as donor sorption, and biofilm inactivation. The software implementation handles heterogeneous flow fields, arbitrarily many chemical species and amendment injection points, and features full coupling between flow and reactive transport, allowing for assessment of the effect of bio-fouling.", + "laborHours": 173325.6, + "name": "CHROTRAN, 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/scottkalevhansen/CHROTRAN-release", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MASS1 simulates open channel hydrodynamics and transport in branched channel networks, using cross-section averaged forms of the continuity, momentum, and convection diffusion equations. Thermal energy transport (temperature), including meteorological influences is supported. The thermodynamics of total dissolved gas (TDG) can be directly simulated. MASS1 has been developed over the last 20 years. It is currently being used on DOE projects that require MASS1 to beopen source. Hence, the authors would like to distribute MASS1 in source form.", + "laborHours": 9910.4, + "name": "Modular Aquatic Simulation System 1D", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/mass1/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mass1", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Synthetic Proxy Infrastructure for Task Evaluation is a proxy application designed to support application developers in gauging the performance of various task granularities when determining how best to utilize task based programming models.The infrastructure is designed to provide examples of common communication patterns with a synthetic workload intended to provide performance data to evaluate programming model and platform overheads for the purpose of determining task granularity for task decomposition purposes. This is presented as a reference implementation of a proxy application with run-time configurable input and output task dependencies ranging from an embarrassingly parallel scenario to patterns with stencil-like dependencies upon their nearest neighbors. Once all, if any, inputs are satisfied each task will execute a synthetic workload (a simple DGEMM of in this case) of varying size and output all, if any, outputs to the next tasks.The intent is for this reference implementation to be implemented as a proxy app in different programming models so as to provide the same infrastructure and to allow for application developers to simulate their own communication needs to assist in task decomposition under various models on a given platform.", + "laborHours": 106.4, + "name": "Synthetic Proxy Infrastructure for Task Evaluation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/spite/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/spite", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The CosmicEmu implements a Gaussian process emulation scheme to predict the dark matter and dark matter + neutrino power spectra over a range of physical parameters that describe the composition and evolution of the Universe. The procedure can produce thousands of spectra per second, much faster than the complex n-body simulations used to produce the training set, which can take weeks per simulation. The training simulations, their design, and the general scheme is described in Lawrence et al. (2010), Heitmann et al. (2014), Heitmann et al. (2016), and an upcoming paper.", + "laborHours": 159311.2, + "name": "CosmicEmu, Version 2.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/CosmicEmu/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/CosmicEmu", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HELICS is designed to support very-large-scale (100,000+ federates) cosimulations with off-the-shelf power-system, communication, market, and end-use tools. Other key features include cross platform operating system support, the integration of both event driven (e.g., packetized communication) and time-series (e.g., power flow) simulations, and the ability to co-iterate among federates to ensure physical model convergence at each time step.", + "laborHours": 265848.0, + "name": "Hierarchical Engine for Large-scale Infrastructure Co-Simulation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GMLC-TDC/HELICS-src/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GMLC-TDC/HELICS-src", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ECoG ClusterFlow is a novel multi-scale visual analysis system for the detailed exploration of dynamic functional connectivity graphs obtained through electrocorticography.", + "laborHours": 576718.4, + "name": "ECoG Cluster Flow v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sugeerth/ECoG-ClusterFlow/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sugeerth/ECoG-ClusterFlow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Small Python package to compute tomographic reconstructions using a reconstruction method published in: Pelt, D.M., & De Andrade, V. (2017). Improved tomographic reconstruction of large-scale real-world data by filter optimization. Advanced Structural and Chemical Imaging 2: 17; and Pelt, D. M., & Batenburg, K. J. (2015). Accurately approximating algebraic tomographic reconstruction by filtered backprojection. In Proceedings of The 13th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (pp. 158-161).", + "laborHours": 395.2, + "name": "SIRT-FILTER v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/dmpelt/sirtfilter/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/dmpelt/sirtfilter", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "New contributions to the existing open source project called 'progressbars2.\" Improvements were created for use in JBEI software, but are generally useful to the open source software community.", + "laborHours": 2188.8, + "name": "progressbar2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WoLpH/python-progressbar", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Equilibrium thermodynamics underpins many of the technologies used throughout theoretical physics, yet verification of the various theoretical models in the open literature remains challenging. EOSlib provides a single, consistent, verifiable implementation of these models, in a single, easy-to-use software package. It consists of three parts: a software library implementing various published equation-of-state (EOS) models; a database of fitting parameters for various materials for these models; and a number of useful utility functions for simplifying thermodynamic calculations such as computing Hugoniot curves or Riemann problem solutions. Ready availability of this library will enable reliable code-to- code testing of equation-of-state implementations, as well as a starting point for more rigorous verification work. EOSlib also provides a single, consistent API for its analytic and tabular EOS models, which simplifies the process of comparing models for a particular application.", + "laborHours": 55753.6, + "name": "EOSlib, Version 3", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/EOSlib/blob/github/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EOSlib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Virtual Machine Builder is a graphical user interface for use and modification of virtual machine templates using Hashi Corp packer to perform virtual machine creation.", + "laborHours": 6566.4, + "name": "Virtual Machine Builder", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csd-dev-tools/VmBuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Jali is a parallel unstructured mesh infrastructure library designed for use by multi-physics simulations. It supports 2D and 3D arbitrary polyhedral meshes distributed over hundreds to thousands of nodes. Jali can read write Exodus II meshes along with fields and sets on the mesh and support for other formats is partially implemented or is (https://github.com/MeshToolkit/MSTK), an open source general purpose unstructured mesh infrastructure library from Los Alamos National Laboratory. While it has been made to work with other mesh frameworks such as MOAB and STKmesh in the past, support for maintaining the interface to these frameworks has been suspended for now. Jali supports distributed as well as on-node parallelism. Support of on-node parallelism is through direct use of the the mesh in multi-threaded constructs or through the use of \"tiles\" which are submeshes or sub-partitions of a partition destined for a compute node.", + "laborHours": 16841.6, + "name": "Jali - Unstructured Mesh Infrastructure for Multi-Physics Applications", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/jali", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "At exascale, the challenge becomes to develop applications that run at scale and use exascale platforms reliably, efficiently, and flexibly. Workflows become much more complex because they must seamlessly integrate simulation and data analytics. They must include down-sampling, post-processing, feature extraction, and visualization. Power and data transfer limitations require these analysis tasks to be run in-situ or in-transit. We expect successful workflows will comprise multiple linked simulations along with tens of analysis routines. Users will have limited development time at scale and, therefore, must have rich tools to develop, debug, test, and deploy applications. At this scale, successful workflows will compose linked computations from an assortment of reliable, well-defined computation elements, ones that can come and go as required, based on the needs of the workflow over time. We propose a novel framework that utilizes both virtual machines (VMs) and software containers to create a workflow system that establishes a uniform build and execution environment (BEE) beyond the capabilities of current systems. In this environment, applications will run reliably and repeatably across heterogeneous hardware and software. Containers, both commercial (Docker and Rocket) and open-source (LXC and LXD), define a runtime that isolates all software dependencies from the machine operating system. Workflows may contain multiple containers that run different operating systems, different software, and even different versions of the same software. We will run containers in open-source virtual machines (KVM) and emulators (QEMU) so that workflows run on any machine entirely in user-space. On this platform of containers and virtual machines, we will deliver workflow software that provides services, including repeatable execution, provenance, checkpointing, and future proofing. We will capture provenance about how containers were launched and how they interact to annotate workflows for repeatable and partial re-execution. We will coordinate the physical snapshots of virtual machines with parallel programming constructs, such as barriers, to automate checkpoint and restart. We will also integrate with HPC-specific container runtimes to gain access to accelerators and other specialized hardware to preserve native performance. Containers will link development to continuous integration. When application developers check code in, it will automatically be tested on a suite of different software and hardware architectures.", + "laborHours": 2629.6, + "name": "Build and Execute Environment", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/BEE/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/BEE", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Our Python module, colormap_module, presented here can be used to analyze and manipulate colormaps and has two main aims: (i) compare existing and new custom colormaps quantitatively by comparing their values in a color space, called CAM02-UCS, that directly shows how a human perceives their hue, saturation, and lightness values and (ii) create isoluminant colormaps from existing or custom colormaps and (iii) mix isoluminant colormap data with a 4th dimension of data by manipulating lightness values across the image and present the new image. Our module was designed to be a tool for the community to use as a whole, allowing scientists to present, analyze, and manipulate colormaps they have created and/or decided to use for a particular type of data. By being able to do this, the scientific community as a whole will think more about the colormaps they choose, see why particular colormaps are bad to use for certain types of data, and move toward using colormaps our eyes can interpret much more efficiently.", + "laborHours": 304.0, + "name": "colormap_util", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jamienunez/cmaputil/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jamienunez/cmaputil", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Route Sanitizer is ORNL's connected vehicle moving object database de-identification tool and a graphical user interface to ORNL's connected vehicle de-identification algorithm. It uses the Google Chrome (soon to be Electron) platform so it will run on different computing platforms. The basic de-identification strategy is record redaction: portions of a vehicle trajectory (e.g. sequences of precise temporal spatial records) are removed. It does not alter retained records. The algorithm uses custom techniques to find areas within trajectories that may be considered private, then it suppresses those in addition to enough of the trajectory surrounding those locations to protect against \"inference attacks\" in a mathematically sound way. Map data is integrated into the process to make this possible.", + "laborHours": 0.0, + "name": "Route Sanitizer: Connected Vehicle Trajectory De-Identification Tool", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmcarter9t/route-sanitizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "EDGE bioinformatics was developed to help biologists process Next Generation Sequencing data (in the form of raw FASTQ files), even if they have little to no bioinformatics expertise. EDGE is a highly integrated and interactive web-based platform that is capable of running many of the standard analyses that biologists require for viral, bacterial/archaeal, and metagenomic samples. EDGE provides the following analytical workflows: quality trimming and host removal, assembly and annotation, comparisons against known references, taxonomy classification of reads and contigs, whole genome SNP-based phylogenetic analysis, and PCR analysis. EDGE provides an intuitive web-based interface for user input, allows users to visualize and interact with selected results (e.g. JBrowse genome browser), and generates a final detailed PDF report. Results in the form of tables, text files, graphic files, and PDFs can be downloaded. A user management system allows tracking of an individual’s EDGE runs, along with the ability to share, post publicly, delete, or archive their results.", + "laborHours": 155587.2, + "name": "Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform, Version 1.5 and 1.x.", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Bioinformatics/EDGE.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "A Git server (GitHub, GitLab, BitBucket) sends event notifications to the Civet server. These are either a \" Pull Request\" or a \"Push\" notification. Civet then checks the database to determine what tests need to be run and marks them as ready to run. Civet clients, running on dedicated machines, query the server for available jobs that are ready to run. When a client gets a job it executes the scripts attached to the job and report back to the server the output and exit status. When the client updates the server, the server will also update the Git server with the result of the job, as well as updating the main web page.", + "laborHours": 26615.2, + "languages": [], + "name": "CIVET: Continuous Integration, Verification, Enhancement, and Testing", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/civet", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Xanthos is a Python package designed to quantify and analyze global water availability in history and in future at 0.5° × 0.5° spatial resolution and a monthly time step under a changing climate. Its performance was also tested through real applications. It is open-source, extendable and convenient to researchers who work on long-term climate data for studies of global water supply, and Global Change Assessment Model (GCAM). This package integrates inherent global gridded data maps, I/O modules, Water-Balance Model modules and diagnostics modules by user-defined configuration.", + "laborHours": 1656.8, + "name": "Xanthos", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/xanthos", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-01-22" + }, + "description": "WindSE is a tool for modeling atmospheric fluid flow within a wind plant and performing optimization of the turbine positions or operating settings. WindSE is a python package that uses a FEniCS backend to perform wind farm simulations and optimization.", + "laborHours": 3146.4, + "languages": [ + "Python" + ], + "name": "WindSE: Wind Systems Engineering [SWR-17-03]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WindSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-10-01" + }, + "description": "The Functionally-Assembled Terrestrial Ecosystem Simulator (FATES) is a vegetation model for use in Earth system models (ESMs). The model includes a size- and age-structured representation of tree dynamics, competition between functionally diverse plant functional types, and the biophysics underpinning plant growth, competition, mortality, as well as the carbon, water, and energy exchange with the atmosphere. The FATES model is designed as a modular vegetation model that can be integrated within a host land model for inclusion in ESMs. The model is designed for use in global change studies to understand and project the responses and feedbacks between terrestrial ecosystems and the Earth system under changing climate and other forcings.", + "homepageURL": "https://zenodo.org/record/3825474", + "laborHours": 0.0, + "languages": [], + "name": "The Functionally-Assembled Terrestrial Ecosystem Simulator Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NGEET/fates-release/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://zenodo.org/record/3825474", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Charliecloud is a set of scripts to let users run a virtual cluster of virtual machines (VMs) on a desktop or supercomputer. Key functions include: 1. Creating (typically by installing an operating system from vendor media) and updating VM images; 2. Running a single VM; 3. Running multiple VMs in a virtual cluster. The virtual machines can talk to one another over the network and (in some cases) the outside world. This is accomplished by calling external programs such as QEMU and the Virtual Distributed Ethernet (VDE) suite. The goal is to let users have a virtual cluster containing nodes where they have privileged access, while isolating that privilege within the virtual cluster so it cannot affect the physical compute resources. Host configuration enforces security; this is not included in Charliecloud, though security guidelines are included in its documentation and Charliecloud is designed to facilitate such configuration. Charliecloud manages passing information from host computers into and out of the virtual machines, such as parameters of the virtual cluster, input data specified by the user, output data from virtual compute jobs, VM console display, and network connections (e.g., SSH or X11). Parameters for the virtual cluster (number of VMs, RAM and disk per VM, etc.) are specified by the user or gathered from the environment (e.g., SLURM environment variables). Example job scripts are included. These include computation examples (such as a \"hello world\" MPI job) as well as performance tests. They also include a security test script to verify that the virtual cluster is appropriately sandboxed. Tests include: 1. Pinging hosts inside and outside the virtual cluster to explore connectivity; 2. Port scans (again inside and outside) to see what services are available; 3. Sniffing tests to see what traffic is visible to running VMs; 4. IP address spoofing to test network functionality in this case; 5. File access tests to make sure host access permissions are enforced. This test script is not a comprehensive scanner and does not test for specific vulnerabilities. Importantly, no information about physical hosts or network topology is included in this script (or any of Charliecloud); while part of a sensible test, such information is specified by the user when the test is run. That is, one cannot learn anything about the LANL network or computing infrastructure by examining Charliecloud code.", + "laborHours": 4879.2, + "name": "Charliecloud", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/charliecloud", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Los Alamos sea ice model (CICE) is the result of an effort to develop a computationally efficient sea ice component for a fully coupled atmosphere–land–ocean–ice global climate model. It was originally designed to be compatible with the Parallel Ocean Program (POP), an ocean circulation model developed at Los Alamos National Laboratory for use on massively parallel computers. CICE has several interacting components: a vertical thermodynamic model that computes local growth rates of snow and ice due to vertical conductive, radiative and turbulent fluxes, along with snowfall; an elastic-viscous-plastic model of ice dynamics, which predicts the velocity field of the ice pack based on a model of the material strength of the ice; an incremental remapping transport model that describes horizontal advection of the areal concentration, ice and snow volume and other state variables; and a ridging parameterization that transfers ice among thickness categories based on energetic balances and rates of strain. It also includes a biogeochemical model that describes evolution of the ice ecosystem. The CICE sea ice model is used for climate research as one component of complex global earth system models that include atmosphere, land, ocean and biogeochemistry components. It is also used for operational sea ice forecasting in the polar regions and in numerical weather prediction models.", + "laborHours": 51938.4, + "name": "CICE, The Los Alamos Sea Ice Model", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/CICE-Consortium/CICE/blob/master/LICENSE.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CICE-Consortium/CICE", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2025-03-26" + }, + "description": "URBANopt is a user interface for creating and running district and city scale building energy simulations. The framework is built around the OpenStudio Urban Measures which are part of the OpenStudio project. Building footprints, building height, building type, and other data can be imported from public records or other sources. Footprints and locations for new buildings and district systems can also be specified. OpenStudio Measures are used to create starting point energy models and to model energy design features and efficiency measures for each building. URBANopt allows a user to pose several scenarios such as “what if 30% of the commercial retail buildings added roof top solar” or “what if all elementary schools converted to ground source heat pumps” and then visualize the impacts at a district or city scale. URBANopt is capable of modeling existing buildings, new construction, and district energy systems. URBANopt can be used to explore options for achieving Zero Energy across a collection of buildings (e.g., Zero Energy Districts).", + "homepageURL": "https://www.nrel.gov/buildings/urbanopt.html", + "laborHours": 635147.2, + "languages": [], + "name": "URBANopt (Urban Renewable Building And Neighborhood Optimization) [SWR-16-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/buildings/urbanopt.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "FleCSPH is a multi-physics compact application that exercises FleCSI parallel data structures for tree-based particle methods. In particular, FleCSPH implements a smoothed-particle hydrodynamics (SPH) solver for the solution of Lagrangian problems in astrophysics and cosmology. FleCSPH includes support for gravitational forces using the fast multipole method (FMM).", + "laborHours": 10001.6, + "name": "FleCSPH - a parallel and distributed SPH implementation based on the FleCSI framework", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laristra/flecsph", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "In most Home Energy Management Systems (HEMS) available in the market, different devices running different communication protocols cannot interact with each other and exchange information. As a result of this integration, the information about different devices running different communication protocol can be accessible by other agents and devices running on VOLTTRON platform. The integration process can be used by any HEMS available in the market regardless of the programming language they use. If the existing HEMS provides an Application Programming Interface (API) based on the RESTFul architecture, that API can be used for integration. Our candidate HEMS in this project is home-assistant (Hass). An agent is implemented which can communicate with the Hass API and receives information about the devices loaded on the API. The agent publishes the information it receives on the VOLTTRON message bus so other agents can have access to this information. On the other side, for each type of devices, an agent is implemented such as Climate Agent, Lock Agent, Switch Agent, Light Agent, etc. Each of these agents is subscribed to the messages published on the message bus about their associated devices. These agents can also change the status of the devices by sending appropriate service calls to the API. Other agents and services on the platform can also access this information and coordinate their decision-making process based on this information.", + "laborHours": 109880.8, + "name": "Home Energy Management System - VOLTTRON Integration", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/VOLTTRON/volttron-applications/blob/master/ornl/HomeAssistant-VOLTTRON-Integration-Agents/License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron-applications", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The VisIT Java Client (JVC) library is a lightweight thin client that is designed and written purely in the native language of Java (the Python & JavaScript versions of the library use the same concept) and communicates with any new unmodified standalone version of VisIT, a high performance computing parallel visualization toolkit, over traditional or web sockets and dynamically determines capabilities of the running VisIT instance whether local or remote.", + "laborHours": 1383.2, + "name": "Visualization Software for VisIT Java Client", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/visit-vis/visit_java_client/blob/master/gov.lbnl.visit.swt/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/visit-vis/visit_java_client", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Knowledge graphs represent information as entities and relationships between them. For tasks such as natural language question answering or automated analysis of text, a knowledge graph provides valuable context to establish the specific type of entities being discussed. It allow us to derive better context about newly arriving information and leads to intelligent reasoning capabilities. We address two primary needs: A) Automated construction of knowledge graphs is a technically challenging, expensive process; and B) The ability to synthesize new information by monitoring newly emerging knowledge is a transformational capability that does not exist in state of the art systems.", + "laborHours": 19136.8, + "name": "NOUS: A Knowledge Graph Management System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/streaming-graphs/NOUS", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/streaming-graphs/NOUS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Pececillo is a proxy-app for the open source Truchas metal processing code (LA-CC-15-097). It implements many of the physics models used in Truchas: free-surface, incompressible Navier-Stokes fluid dynamics (e.g., water waves); heat transport, material phase change, view factor thermal radiation; species advection-diffusion; quasi-static, elastic/plastic solid mechanics with contact; electomagnetics (Maxwell's equations). The models are simplified versions that retain the fundamental computational complexity of the Truchas models while omitting many non-essential features and modeling capabilities. The purpose is to expose Truchas algorithms in a greatly simplified context where computer science problems related to parallel performance on advanced architectures can be more easily investigated. While Pececillo is capable of performing simulations representative of typical Truchas metal casting, welding, and additive manufacturing simulations, it lacks many of the modeling capabilites needed for real applications.", + "laborHours": 21705.6, + "name": "Pececillo", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/truchas/pececillo/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/truchas/pececillo", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Graphical user interface for use and modification of virtual machine templates using Hashi Corp packer to perform virtual machine creation.", + "laborHours": 6566.4, + "name": "ClockworkVMs", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csd-dev-tools/VmBuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The open source Project Haystack initiative defines meta data and communication standards related to data from buildings and intelligent devices. The Project Haystack REST API defines standard formats and operations for exchanging Haystack tagged data over HTTP. The HaystackRuby gem wraps calls to this REST API to enable Ruby application to easily integrate data hosted on a Project Haystack compliant server. The HaystackRuby gem was developed at the National Renewable Energy Lab to support applications related to campus energy. We hope that this tool may be useful to others.", + "laborHours": 425.6, + "name": "Haystack-Ruby", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/haystack_ruby", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-10-13" + }, + "description": "High-Throughput software platform to create/launch/analyze physics-related calculations. The front-end is a python API which allows the user to create any conceivable first-principles physics calculation. Is is coupled to an ipython interface to launch and retrieve large number of calculations. It was successfully used in high-throughput calculations of point defect formation enthalpies, compound formation enthalpies, and a genetic algorithm search of direct-gap silicon/germanium structures.", + "laborHours": 49506.4, + "languages": [ + "C++", + "Python" + ], + "name": "LaDa™", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://pylada.github.io/pylada", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mdavezac/LaDa", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The MAGMA software package is a package created in the R scripting language that reads a SQL database and outputs tables and figures of important data. The SQL database is created by another R package called “rplexos” and uses the .zip solution file output by PLEXOS, which is commercially available production cost modeling software.", + "laborHours": 3435.2, + "name": "Multi-area Grid Metrics Analyzer", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/MAGMA", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MAGMA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Knife-ovirt is code building on the chef, knife-cloud, fog, rbovirt projects that allows deployment of virtual machines on an ovirt cluster, and immediately bootstrap them into a chef managed infrastructure. (similar to knife-openstack project).", + "laborHours": 258.4, + "name": "Knife-ovirt", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/knife-ovirt", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software is intended to be part of an open source effort regarding soils data. The software provides customized data ingestion scripts for soil carbon related data sets and scripts for output databases that conform to common templates.", + "laborHours": 714.4, + "name": "Soil Carbon Data: long tail recovery", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ktoddbrown/soils-long-tail-recovery", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-07-19" + }, + "description": "The software was produced to reproduce biologically relevant results and present them using clear and elegant graphs.", + "laborHours": 3632.8, + "languages": [], + "name": "Supplemental Material for Bernstein-2017-founders-species", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/bernstein-2017-founders-species", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/brislawn-2018-founders-species", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SimulatorToFMU is a software package written in Python which allows users to export a memoryless Python-driven simulation program or script as a Functional Mock-up Unit (FMU) for model exchange or co-simulation.In CyDER (Cyber Physical Co-simulation Platform for Distributed Energy Resources in Smart Grids), SimulatorToFMU will allow exporting OPAL-RT as an FMU. This will enable OPAL-RT to be linked to CYMDIST and GridDyn FMUs through a standardized open source interface.", + "laborHours": 4332.0, + "name": "SimulatorToFMU v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LBNL-ETA/SimulatorToFMU/blob/master/simulatortofmu/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/SimulatorToFMU", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "YADAS is a software system for statistical analysis using Markov chain Monte Carlo (MCMC). As such, it performs Monte Carlo integration of probability distributions and generates estimates of unknown quantities based on data and expert opinion if available. Its architecture makes it extensible enough to be helpful in the analysis of any statistical model, so it is particularly useful for statistic researchers. YADAS features a versatile scheme for defining models, and another versatile scheme for defining sampling algorithms that includes a default starting place for most analyses.", + "laborHours": 3222.4, + "name": "YADAS, Version 0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/gertvv/yadas/blob/master/COPYING.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gertvv/yadas", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-01-31" + }, + "description": "RdTools™ provides a set of tools for quantifying the degradation of photovoltaic systems and modules.", + "laborHours": 1003.2, + "languages": [ + "Python" + ], + "name": "RdTools™ [SWR-17-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rdtools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.2.0-beta.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2022-07-21" + }, + "description": "PeleC is an adaptive-mesh compressible hydrodynamics code for reacting flows. It solves the compressible Navier-Stokes with multispecies transport in a block structured framework. The resulting algorithm is well suited for flows with localized resolution requirements and robust to discontinuities. User controllable refinement crieteria has the potential to result in extremely small numerical dissipation and dispersion, making this code appropriate for both research and applied usage. The code is built on the AMReX library which facilitates hierarchical parallelism and manages distributed memory parallism. PeleC algorithms are implemented to express shared memory parallelism.", + "laborHours": 0.0, + "languages": [], + "name": "PELEC", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/AMReX-Combustion/PeleC/blob/development/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Combustion/PeleC", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-04-24" + }, + "description": "PelePhysics is a suite of physics packages that provides functionality of use to reacting hydrodynamics CFD codes. The initial release includes an interface to reaction rate mechanism evaluation, transport coefficient evaluation, and a generalized equation of state (EOS) facility. 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The LK language is used by NREL’s System Advisor Model (SAM), the SAM Software Development Kit (SDK), and SolTrace products. LK is easy extensible and adaptable to new software due to its small footprint and is designed to be statically linked into other software. It is written in standard C++, is cross-platform (Windows, Linux, and OSX), and includes optional portions that enable direct integration with graphical user interfaces written in the open source C++ wxWidgets Version 3.0+ toolkit.", + "laborHours": 111248.8, + "name": "LK Scripting Language", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/lk/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/lk", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Quantized State Systems (QSS) Solver with Functional Mock-Up Units (FMU) Support", + "laborHours": 23560.0, + "name": "Quantized State Systems (QSS) Solver with Functional Mock-Up Units (FMU) Support", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/SOEP-QSS/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SOEP-QSS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "BSF is a highly efficient pairwise similarity algorithm enabling extensive data mining.", + "laborHours": 91.2, + "name": "Blazing Signature Filter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/bsf-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The PLEXOS Input Data Generator (PIDG) is a tool that enables PLEXOS users to better version their data, automate data processing, collaborate in developing inputs, and transfer data between different production cost modeling and other power systems analysis software. PIDG can process data that is in a generalized format from multiple input sources, including CSV files, PostgreSQL databases, and PSS/E .raw files and write it to an Excel file that can be imported into PLEXOS with only limited manual intervention.", + "laborHours": 1687.2, + "name": "PLEXOS Input Data Generator", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/PIDG/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PIDG", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "LEAF Version 2.0 is a framework comprising of three models RUSLE2, WEPS, and AGNPS. The framework can predict row crop, crop residue, and energy crop yields at a sub-field resolutions for various combinations of soil, climate and crop management and residue harvesting practices. It estimates the loss of soil, carbon, and nutrients to the atmosphere, to the groundwater, and to runoff. It also models the overland flow of water and washed-off sediments, nutrients and other chemicals to provide estimates of sediment, nutrient, and chemical loadings to water bodies within a watershed. AGNPS model and wash-off calculations are the new additions to this version of LEAF. Development of LEAF software is supported by DOE's BETO program.", + "laborHours": 0.0, + "languages": [], + "name": "Landscape Environmental Assessment Framework", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/LEAF", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "SIEVAS provides an immersive visualization framework for connecting multiple systems in real time for data science. SIEVAS provides the ability to connect multiple COTS and GOTS products in a seamless fashion for data fusion, data analysis, and viewing. It provides this capability by using a combination of micro services, real time messaging, and web service compliant back-end system.", + "laborHours": 15929.6, + "languages": [], + "name": "Scientific & Intelligence Exascale Visualization Analysis System", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/SIEVAS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "LUNUS software for generating 3D maps of diffuse scattering from macromolecular X-ray crystallography diffraction images. A set of tools needed for advanced refinement of crystal structures and crystallographic charge density models. Includes tools for processing X--ray diffraction images, charge density maps, and structure factors for analysis of diffuse X-ray scattering and charge density variations in crystallography. Specific methods include: elementary algebraic operations on images and 3D lattices; fourier transform of images and 3D lattices; image processing to measure diffuse intensity; crystallographic refinement; and 3D integration of diffuse intensity.", + "laborHours": 25353.6, + "name": "LUNUS, Version 0.1a", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mewall/lunus/blob/master/00LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mewall/lunus", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software implements a heterogeneous multiscale method (HMM), which involves solving a classical molecular dynamics (MD) problem and then computes the entropy production in order to compute the relaxation times towards equilibrium for use in a Bhatnagar-Gross-Krook (BGK) solver.", + "laborHours": 1900.0, + "name": "BGK-MD, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/gilshohet/plasma-bgkmd/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gilshohet/plasma-bgkmd", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Building on the existing Multiplicative Attribute Graph (MAG) model, the software relaxes the assumptions of the MAG model allowing dataset expansion while replicating statistical properties.", + "laborHours": 349.6, + "name": "Realistic Simulation of Property Graphs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/propgraph/pgm/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/propgraph/pgm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Nmrfit reads the output from a nuclear magnetic resonance (NMR) experiment and, through a number of intuitive API calls, produces a least-squares fit of Voigt-function approximations via particle swarm optimization.", + "laborHours": 380.0, + "name": "nmrfit", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/nmrfit/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/nmrfit", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "PolyPole is a numerical algorithm for the calculation of intra-granular fission gas release. In particular, the algorithm solves the gas diffusion problem in a fuel grain in time-varying conditions. The program has been extensively tested. PolyPole combines a high accuracy with a high computational efficiency and is ideally suited for application in fuel performance codes.", + "laborHours": 0.0, + "languages": [], + "name": "Polypole Program For The Calculation Of Intra-granular Fission Gas Release", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/PolyPole", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The Idaho National Laboratory (INL) has teamed with University of Idaho and Boise State University to make the use of ADs more attractive by implementing a two-stage AD and coupling additional processes to the system. The addition of a polyhydroxyalkanoate (PHA) reactor, algae cultivation system, and a biomass treatment system such as fast-pyrolysis or hydrothermal liquefaction (HTL) would further sequester carbon and nutrients, as well as add valuable products that can be sold or used on-site to mitigate costs. The Decision-support for Digester-Algae IntegRation for Improved Environmental and Economic Sustainability (DAIRIEES) technoeconomic model will play a key role in evaluating the effectiveness and viability of this system to achieve economic and environmental sustainability by the dairy industry.", + "laborHours": 0.0, + "languages": [], + "name": "Decision Support For Digester Algae Integration For Improved Environmental And Economic Sustainability", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/DAIRIEES", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The Water-Energy Simulation Toolset (WEST) is an interactive simulation model that helps visualize impacts of different stakeholders on water quantity and quality of a watershed. The case study is applied for the Snake River Basin with the fictional name Cutthroat River Basin. There are four groups of stakeholders of interest: hydropower, agriculture, flood control, and environmental protection. Currently, the quality component depicts nitrogen-nitrate contaminant. Users can easily interact with the model by changing certain inputs (climate change, fertilizer inputs, etc.) to observe the change over the entire system. Users can also change certain parameters to test their management policy.", + "laborHours": 0.0, + "languages": [], + "name": "Water Energy Simulation Toolset", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/WEST", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "This program has been designed to assist with the tracking of a sample from one analytical instrument to another such as SEM, microscopes, micro x-ray diffraction and other instruments where particular positions/locations on the sample are examined, photographed, etc. The software is designed to easily enter the position of fiducials and locations of interest such that in a future session in the same of different instrument the positions of interest can be re-found through using the known location fiducials in the current and reference session to transform the point into the current sessions coordinate system. The software is dialog box driven guiding the user through the necessary data entry and program choices. Information is stored in a series of text based extensible markup language (XML) files.", + "laborHours": 0.0, + "languages": [], + "name": "Cross-instrument Analysis Correlation Software", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/CIACS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "AMG is a parallel algebraic multigrid solver for linear systems arising from problems on unstructured grids. It has been derived directly from the BoomerAMG solver in the hypre library, a large linear solvers library that is being developed in the Center for Applied Scientific Computing (CASC) at LLNL and is very similar to the AMG2013 benchmark with additional optimizations. The driver provided in the benchmark can build various test problems. The default problem is a Laplace type problem with a 27-point stencil, which can be scaled up and is designed to solve a very large problem. A second problem simulates a time dependent problem, in which successively various smnllcr systems are solved.", + "laborHours": 44414.4, + "name": "Algebraic Multigrid Benchmark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AMG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The ProvEn Software is designed to analyze and monitor distributed scientific workflow application behavior in the context of its environment.", + "laborHours": 349.6, + "name": "Provenance Environment Services Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ProvenanceEnvironment", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is the repository for Building Energy Management Open Source Software (BEMOSS), which is an open source operating system that is engineered to improve sensing and control of equipment in small- and medium-sized commercial buildings. BEMOSS offers the following key features: (1) Open source, open architecture – BEMOSS is an open source operating system that is built upon VOLTTRON – a distributed agent platform developed by Pacific Northwest National Laboratory (PNNL). BEMOSS was designed to make it easy for hardware manufacturers to seamlessly interface their devices with BEMOSS. Software developers can also contribute to adding additional BEMOSS functionalities and applications. (2) Plug & play – BEMOSS was designed to automatically discover supported load controllers (including smart thermostats, VAV/RTUs, lighting load controllers and plug load controllers) in commercial buildings. (3) Interoperability – BEMOSS was designed to work with load control devices form different manufacturers that operate on different communication technologies and data exchange protocols. (4) Cost effectiveness – Implementation of BEMOSS deemed to be cost-effective as it was built upon a robust open source platform that can operate on a low-cost single-board computer, such as Odroid. This feature could contribute to its rapid deployment in small- or medium-sized commercial buildings. (5) Scalability and ease of deployment – With its multi-node architecture, BEMOSS provides a distributed architecture where load controllers in a multi-floor and high occupancy building could be monitored and controlled by multiple single-board computers hosting BEMOSS. This makes it possible for a building engineer to deploy BEMOSS in one zone of a building, be comfortable with its operation, and later on expand the deployment to the entire building to make it more energy efficient. (6) Ability to provide local and remote monitoring – BEMOSS provides both local and remote monitoring ability with role-based access control. (7) Security – In addition to built-in security features provided by VOLTTRON, BEMOSS provides enhanced security features, including BEMOSS discovery approval process, encrypted core-to-node communication, thermostat anti-tampering feature and many more. (8) Support from the Advisory Committee – BEMOSS was developed in consultation with an advisory committee from the beginning of the project. BEMOSS advisory committee comprises representatives from 22 organizations from government and industry.", + "laborHours": 153185.6, + "name": "Building Energy Management Open Source Software", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bemoss/BEMOSS3.5", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software is an application for Oelta3D, QT and OpenSceneGraph, all of which are extemal open source software.", + "laborHours": 2447.2, + "name": "Open Facility Viewer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Open-Facility-Viewer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OpenEIS was created to provide standard methods for authoring, sharing, testing, using, and improving algorithms for operational building energy efficiency with building managers and building owners. OpenEIS is designed as a no-cost/low-cost solution that will propagate the fault detection and diagnostic (FDD) solutions into the marketplace by providing state- of- the-art analytical and diagnostic algorithms. As OpenEIS penetrates the market, demand by control system manufacturers and integrators serving small and medium commercial customers will help push these types of commercial software tool offerings into the broader marketplace.", + "laborHours": 1036123.2, + "name": "Open Energy Information System version 2.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/VOLTTRON/openeis/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/openeis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The paramutate software package Is a tool to calculate the genotyplc and phenotyplc propagation of a gene drive that can be silenced with a homologuus trans-Inactivating panmutatlon, ln dlptera or other species with a slmUar-acttng pl RNA system/Plwi pathway. Method of SolaUon: paramutate uses rults of Mendelian, gene drive (I.e.. stimulated conversion), and maternal Inheritance to compute the propaptlon of a notional gene drive construct and Its trans-lnactlvat1n1 paramutatlon, throu1b a panmlctlc, fixed-size population reproducing In synchronous generations.", + "laborHours": 12813.6, + "name": "Reversible Gene Drive Mechanism Utilizing Trana Inactivating Paramutatlons In Insects (paramutale 0.9)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/RAJAPerf/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RAJAPerf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The Hybrid Toolkit facilitates moving research algorithms into a production environment by creating useful abstractions that separate analytics developers from the intricacies of the production data formats, data flows, and result representations. The toolkit also assists developers with activities such as creating analysis feature vectors, converting between data structures, and creating data pipelines.", + "laborHours": 13087.2, + "name": "The Hybrid Toolkit", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/The-Hybrid-Toolkit/tree/master/docs", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/The-Hybrid-Toolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Demeter-W, an open-access software written in Python, consists of extensible module packages. It is developed with statistical downscaling algorithms, to spatially and temporally downscale water demand data into finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. For better understanding of the driving forces and patterns for global water withdrawal, the researchers is able to utilize Demeter-W to reconstruct the data sets to examine the issues related to water withdrawals at fine spatial and temporal scales.", + "laborHours": 1124.8, + "name": "Demeter-W", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/demeter-w", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "EnergyPlus(TM) is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption - for heating, cooling, ventilation, lighting and plus and process loads - and water use in buildings.", + "laborHours": 2335920.8, + "name": "EnergyPlus", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/EnergyPlus/blob/develop/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlus", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-03-28" + }, + "description": "A Modelica based library for modeling thermal hydraulic energy systems and other multi-physics systems. \n\nExisting development tools for early stage design and scoping of energy systems are often time consuming to use, proprietary, and do not contain the necessary function to model complete systems (i.e., controls, primary, and secondary systems) in a common platform. The Modelica programming language based TRANSFORM tool (1) provides a standardized, common simulation environment for early design of energy systems (i.e., power plants), (2) provides a library of baseline component modules to be assembled into full plant models using available geometry, design, and thermal-hydraulic data, (3) defines modeling conventions for interconnecting component models, and (4) establishes user interfaces and support tools to facilitate simulation development (i.e., configuration and parameterization), execution, and results display and capture.", + "laborHours": 1732.8, + "languages": [], + "name": "TRANSFORM - TRANsient Simulation Framework of Reconfigurable Models", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-Modelica/TRANSFORM-Library/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-Modelica/TRANSFORM-Library", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The gr-uaslink software is an out of tree (OOT) module for GNU Radio. It provides a wrapper around pymavlink to allow MAVlink messages to be sent with GNU Radio.", + "laborHours": 7372.0, + "name": "gr-uaslink", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/deptofdefense/gr-uaslink", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HELICS ls a new open-source, cyber-physlcal-energy co-simulation framework for electric power systems. HELICS Is designed to support very-large-scale (100,000+ federates) co­simulations with off-the-shelf power-system, communication, market, and end-use tools. Other key features Include cross platform operating system support, the integration of both eventdrlven (e.g., packetlzed communication) and time-series (e.g.,power flow) simulations, and the ability to co-Iterate among federates to ensure physical model convergence at each time step.", + "laborHours": 265848.0, + "name": "Hiearchical Engine for Large Scale Infrastructure Simulation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GMLC-TDC/HELICS-src/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GMLC-Tdc/HELICS-src", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-11-06" + }, + "description": "VOLTTRON is an agent execution platform providing services to its agents that allow them to easily communicate with physical devices and other resources. VOLTTRON delivers an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls. It enables mobile and stationary software agents to perform information gathering, processing, and control actions. VOLTTRON can independently manage a wide range of applications, such as HVAC systems, electric vehicles, distributed energy or entire building loads, leading to improved operational efficiency.", + "laborHours": 0.0, + "languages": [], + "name": "VOLTTRON Version 5.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/VOLTTRON/volttron/blob/master/TERMS.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron/releases/tag/5.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "5.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-02-27" + }, + "description": "Originally developed in 1999, an updated version 8.8.0 with bug fixes was released on September 30th, 2017. EnergyPlus™ is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption—for heating, cooling, ventilation, lighting and plug and process loads—and water use in buildings. EnergyPlus is a console-based program that reads input and writes output to text files. It ships with a number of utilities including IDF-Editor for creating input files using a simple spreadsheet-like interface, EP-Launch for managing input and output files and performing batch simulations, and EP-Compare for graphically comparing the results of two or more simulations. Several comprehensive graphical interfaces for EnergyPlus are also available. DOE does most of its work with EnergyPlus using the OpenStudio® software development kit and suite of applications. DOE releases major updates to EnergyPlus twice annually.", + "laborHours": 2335920.8, + "languages": [], + "name": "EnergyPlus™ (SWR-17-23)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/EnergyPlus/blob/develop/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlus", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "ExaMPM is a mini-application for the Material Point Method (MPM) for studying the application of MPM to future exascale computing systems. MPM is a general method for computational mechanics and fluids and is used in a wide variety of science and engineering disciplines to study problems with large deformations, phase change, fracture, and other phenomena. ExaMPM provides a reference implementation of MPM as described in the 1994 work of Sulsky et.al. (Sulsky, Deborah, Zhen Chen, and Howard L. Schreyer. \"A particle method for history-dependent materials.\" Computer methods in applied mechanics and engineering 118.1-2 (1994): 179-196.). The software can solve basic MPM problems in solid mechanics using the original algorithm of Sulsky with explicit time integration, basic geometries, and free-slip and no-slip boundary conditions as described in the reference. ExaMPM is intended to be used as a starting point to design new parallel algorithms for the next generation of DOE supercomputers.", + "laborHours": 33911.2, + "name": "ExaMPM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ECP-copa/ExaMPM", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-copa/ExaMPM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ProRad is a computer program that is used to generate synthetic images of proton (or other charged particles) radiographs. The proton radiographs arc images that arc obtained by sending energetic protons (or electrons or positrons, for example) through 11 plasma where electric and/or magnetic fields alter the particles trajectory, Dnd the variations me imaged on RC film, image plate, or equivalent", + "laborHours": 988.0, + "name": "Proton Radiography Imager:Generates Synthetic Proton Radiographs", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/prorad/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/prorad", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-12-03" + }, + "description": "The Sandia Engineering Analysis Code Access System (SEACAS) is a suite of preprocessing, post processing, translation, visualization, and utility applications supporting finite element analysis software using the Exodus database file format.", + "laborHours": 692284.0, + "languages": [ + "MATLAB" + ], + "name": "Sandia Engineering Analysis Code Access System v. 2.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Python script for querying a list of web sites and their details from Splunk and dynamically creating tests for monitoring uptime. The data generated from this script is then sent back to Splunk for creating reports and alerts.", + "laborHours": 212.8, + "name": "Synthetic Transaction Test Generator for Websites", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/justinatpnnl/splunk_web_transactions_generator", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/justinatpnnl/splunk_web_transactions_generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Password management solutions exist, but few are designed for enterprise systems administrators sharing oncall rotations. Due to the Multi-Factor Level of Assurance 4 effort, DOE is now distributing PIV cards with cryptographically signed certificate and private key pairs to administrators and other security-significant users. We utilize this public key infrastructure (PKI) to encrypt passwords for other recipients in a secure way. This is cross platform (works on OSX and Linux systems), and has already been adopted internally by the NCCS systems administration staff to replace their old password book system.", + "laborHours": 1626.4, + "name": "PKPass", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/olcf/pkpass", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/pkpass", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A pipeline for scanning domains to measure things like speed, accessibility, and HTTPS.", + "laborHours": 2781.6, + "name": "domain-scan", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/18F/domain-scan/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/18F/domain-scan", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "libristra is a mathematical and computational utility and support library for codes. It includes utilities such as input parsing, commonly used mathematical routines, scientific units, etc.", + "laborHours": 18012.0, + "name": "libristra", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laristra/libristra", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Canary is an extensible water-quality change-detection tool for algorithm development. It has been developed in MATLAB and was developed as part of an IAG with the US EPA NHSRC.", + "homepageURL": "https://software.sandia.gov/trac/canary", + "laborHours": 0.0, + "name": "CANARYV1.5", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://software.sandia.gov/trac/canary", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "YADAS is a software system for statistical analysis, using Markov chain Monte carlo (MCMC). As such, it performs Monte Carlo integration of probability distributions and generates estimates of unknown quantities based on data and expert opinion if available. Its architecture makes it extensible enought to be helpful in the analysis of any statistical model, so it is particularly useful for statistic researchers. YADAS features a versatile scheme for defining models, and another versatile scheme for defining sampling algorithms that includes a default starting place for most analyses. Models are specified using bonds, which relate unknown parameters using a probability density function through functions that convert the parameters into arguments of the probability density. This structure appears to be versatile enough to be useful for virtually all statistical models. The updating algorighms emphasize componentwise random walk Metropolis algorighm updates, but YADAS also contains a framework for updating correlated parameters together. Reversible jump updates are also supported.", + "homepageURL": "http://yadas.lanl.gov/index.html", + "laborHours": 0.0, + "name": "YADAS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://yadas.lanl.gov/node34.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://yadas.lanl.gov/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "This software, a library, contains FORTRAN77 subroutines to calculate first and second derivatives up to 8th order, interpolations (1D and 2D) up to 10th order and filters up to 14th order. Only even orders are addressed and finite-difference stencils are implemented on a vertex-centered mesh. The primary aim of this library is to be used in block-structured adaptive mesh simulations where high order is desired. The interpolants in this library are essentially designed to do prolongations and restrictions between levels of rfinement - however, they assume that the refinement ratio is 2. The filters are provided to remove high wavenumber content from solutions in case Runge phenomenon occurs - a common occurrence in case of marginal resolution of the solution. Details of the derivation and use are to be found in \"Using high-order methods on adaptively refined block-structured meshes - discretizations, interpolations and filters\", by J. Ray, C.A. Kennedy, S. Lefantzi and H.N. Najm, Sandia Technical Report, SAND2005-7981. The software comes with a User's Guide and examples how to use it.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "HODIF: High-Order Discretizations, Interpolations and Filters for AMR", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HODIF", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Our work is aimed at providing a data store for system-level events and presenting a flexible query interface to those events. The work extends the functinality provided by the open source Request Tracker (RT) (http://www.bestpractical.com/rt) project witht the Asset Tracker (AT) addon (http://atwiki.chaka.net). We have developed an Event Tracker add-on to RT and an interface for gathering, dispatching, and inserting system events into Event Tracker. Data sources include data from all components of the system. Data is initially sent to a defined set of data filters. The data filters are capable of discarding specified data, throttling input, handling context-sensitive input, passing data through an external shell pipe command, and compressing multiple data enteries into a single event. The filters then pass the data on to an event dispatch engine. The dispatcher can print events to the screen as they happen, track them in the database, forward them on, or pass them on to an external command. By collecting all of the data into a single database, we are able to leverage the Query Builder interface supplied by RT to create, save, and restore almost any kind of query imaginable.", + "homepageURL": "https://sourceforge.net/projects/rasilience", + "laborHours": 0.0, + "name": "Reliability Availability Serviceability", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/rasilience", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "P-STET assists in the security technology decision making process from a costlbeneflt perspective. It aids in addressing such questions as whether to acquire and deploy new security technology, to re-configure an existing product or system, or to maintain status quo. P-STET offers both a qualitative and quantitative option. P-STET is most efficient when tailored to an organization's security cost/benefit environment. It then serves as both a guide to show what types of security questions should be addressed and as a means to analyze the data gathered from the questions to make an informed decision. The quantitative option provides a straightforward way to express costs/benefits in terms of dollars. It relies on the organization to quantify benefits or cost avoidances, and, therefore, best serves as a guide to ensure various cost and benefit angles are evaluated. The qualitative option allows the organization to assess costs by levels with respect to security and PCS budgets, operational impacts, and opportunity costs. Benefits are represented in terms of improvements to the organization's operations and are also assessed by levels with respect to some benchmark such as compliance with best practices. Results are displayed graphically using radar charts, allowing the user to make a more intuitive decision. The shaded area of each chart represents the overall cost and benefit of the security investment. A good investment is denoted when the ratio of benefit shaded area to cost shaded area is large.", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "PCS Security Technology Evaluation Tool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/P-STET", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "IBSimu(Ion Beam Simulator) is a computer program for making two and three dimensional ion optical simulations. The program can solve electrostatic field in a rectangular mesh using Poisson equation using Finite Difference method (FDM). The mesh can consist of a coarse and a fine part so that the calculation accuracy can be increased in critical areas of the geometry, while most of the calculation is done quickly using the coarse mesh. IBSimu can launch ion beam trajectories into the simulation from an injection surface or fomo plasma. Ion beam space charge of time independent simulations can be taken in account using Viasov iteration. Plasma is calculated by compensating space charge with electrons having Boltzmann energy distribution. The simulation software can also be used to calculate time dependent cases if the space charge is not calculated. Software includes diagnostic tools for plotting the geometry, electric field, space charge map, ion beam trajectories, emittance data and beam profiles.", + "homepageURL": "https://sourceforge.net/projects/ibsimu", + "laborHours": 0.0, + "name": "Ion Beam Simulator", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/ibsimu", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MpiGraph consists of an MPI application called mpiGraph written in C to measure message bandwidth and an associated crunch_mpiGraph script written in Perl to process the application output into an HTMO report. The mpiGraph application is designed to inspect the health and scalability of a high-performance interconnect while under heavy load. This is useful to detect hardware and software problems in a system, such as slow nodes, links, switches, or contention in switch routing. It is also useful to characterize how interconnect performance changes with different settings or how one interconnect type compares to another.", + "homepageURL": "https://sourceforge.net/projects/mpigraph", + "laborHours": 0.0, + "name": "mpiGraph", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/mpigraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "EPANET-BAM 1.0 is an augmented version of EPANET 2.00.10, open-source software distributed by the US Environmental Protection Agency that models flow and contaminant transport through water distribution pipe networks. EPANET-BAM uses a new Bulk advective Mixing (BAM) model to predict concentrations of an aqueous solute at the outlets of cross junctions in a water quality simulation.", + "laborHours": 0.0, + "languages": [], + "name": "EPANET-BAM", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/EPANET-BAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Provides the shell of a plugin based application environment that builds on MVC Framework to allow one to rapidly construct an application by using a collection of plugins. The MVC Shell is implemented in C# as a .NET 2.0 application that can then be used as a shell for building a plugin based application. The infrastructure allows for dynamically processing a specified collection of plugins in order to determine the functionality of the application, where all plugins operate within the context of the underlying MVC Framework environment.", + "homepageURL": "http://www.codeplex.com/mvcshell", + "laborHours": 0.0, + "name": "MVC Shell", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.codeplex.com/mvcshell", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The TEVA-SPOT Toolkit (SPOT) supports the design of contaminant warning systems (CWSs) that use real-time sensors to detect contaminants in municipal water distribution networks. Specifically, SPOT provides the capability to select the locations for installing sensors in order to maximize the utility and effectiveness of the CWS. SPOT models the sensor placement process as an optimization problem, and the user can specify a wide range of performance objectives for contaminant warning system design, including population health effects, time to detection, extent of contamination, volume consumed and number of failed detections. For example, a SPOT user can integrate expert knowledge during the design process by specigying required sensor placements or designating network locations as forbidden. Further, cost considerations can be integrated by limiting the design with user-specified installation costs at each location.", + "laborHours": 30.4, + "languages": [ + "C++", + "C", + "Python" + ], + "name": "TEVA-SPOT Toolkit 1.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TEVA-SPOT-Toolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-02-07" + }, + "description": "PSUADE is an software system that is used to study the relationships between the inputs and outputs of general simulation models for the purpose of performing uncertainty and sensitivity analyses on simulation models.", + "laborHours": 0.0, + "languages": [], + "name": "Problem Solving Environment for Uncertainty Analysis and Design Exploration", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "TaqSim simulates various types of PRC reactions, including multiplex reactions. Given a set of primers and dearch databases, TaqSim identifies amplicons that match user defined criteria and can generate output files in a number of formats allowing it to serve as a front-end or back-end for other software.", + "homepageURL": "http://staff.vbi.vt.edu/dyermd/publications/taqsim.html", + "laborHours": 0.0, + "name": "TaqMan PCR Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://staff.vbi.vt.edu/dyermd/publications/taqsim.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "STRIDE is a suite of benchmarks, 8 in total, which access a computers low level caches and memory in a variety of patterns. The resulting performance of the kernels provides significant insight into the performance that a real application may incur and dictate how certain algorithmic choices should be made.", + "homepageURL": "https://asc.llnl.gov/sequoia/benchmarks", + "laborHours": 0.0, + "name": "Stride Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://asc.llnl.gov/sequoia/benchmarks", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "iScore measures the interestingness of news article in a limited user environment. it is an online learning algorithm that combines a large set of disparate features to classify documents.", + "homepageURL": "https://sourceforge.net/projects/iscore", + "laborHours": 0.0, + "name": "iScore: news filtering software", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/iscore", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "VisIt is an interactive parallel visualization and graphical analysis tool for viewing scientific date on UNIX and PC platforms. Users can quickly generate visualizations from their data, animate them through time, manipulate them, and save the resulting images for presentations. VisIt contains a rich set of visualization features so that you can view your data in a variety of ways. It can be used to visualize scalar and vector fields defined on two- and three- dimensional (2D and 3D) structured and unstructured meshes. VisIt was designed to handle very large data set sizes in the terascale range and yet can also handle small data sets in the kilobyte range.", + "homepageURL": "https://visit.llnl.gov", + "laborHours": 1937164.0, + "languages": [], + "name": "A Distributed, Parallel Visualization and Analysis Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://wci.llnl.gov/simulation/computer-codes/visit/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://visit.llnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pianola is a software benchmark for measuring the performance of input/output (I/O) hardware and software. It works by monitoring the I/O activity of an existing application and storing the sequence of events, along with their timing, in a script. After some additional processing, a separate piece of software in this package can replay these I/) events and replicate their timing without reference to the original application. Therefore, Pianola allows users to create standalone I/O benchmarks that mimic the behavior of applications that either cannot be released or that are difficult for nonspecialists to configure, build or run.", + "homepageURL": "https://computation.llnl.gov/software-catalog", + "laborHours": 0.0, + "name": "Pianola Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://computation.llnl.gov/software-catalog", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The MDEF package contains capabilities ofr modeling the deformation of materials at the crystal scale. Primary code capabilities are: xoth \"strength\" and \"equation of state\" aspects of material response, post-processing utilities, utilities for comparing results with data from diffraction experiments.", + "homepageURL": "https://anisotropy.mae.cornell.edu/dplab/mdef", + "laborHours": 0.0, + "name": "Multi-scale and Multi-phase deformation of crystalline materials", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://anisotropy.mae.cornell.edu/dplab/mdef", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-03-27" + }, + "description": "Embody (Environment Modules Build) is a software build tool with integrated support for the environment-modules package. The tool eases and automates the task of building and installing software packages from source or binary distributions, as well as the management of associated module files. An administrator or software pool maintainer has to write a brief script for the installation process. These steps are usually described for manual execution, in a package's README or INSTALL file. It would be up to the site administrator to work out a procedure to capture the steps taken. This tool: streamlines and codifies the installation tasks in a common framework; it provides a self-documenting and unified way for maintaining package installations; uses bash shell variables and functions for portability; keeps log files of the proceedings. It is similar in intent and function to other existing tools, such as RPM, but has several novel features tailored for High Performance Computing (HPC) software deployments. The design goal is simplicity and decoupling from RPM's dependencies and its database, which enables coexistence of several builds. Useful on HPC systems, new builds can be deployed centrally to shared file systems and without affecting running jobs.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "EMBODY(Environmental Modules Build System Software)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MeDICi is an evolving middleware platform for building complex, high performance analytical applications. These applications typically comprise a pipeline of software components, each of which performs some analysis on incoming data and passes on its results to the next step in the pipeline.", + "homepageURL": "http://medici.pnl.gov/download_mif", + "laborHours": 0.0, + "name": "Middleware for Data Intensive Computing", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://medici.pnl.gov/standard_pnnl_oss_liscense", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://medici.pnl.gov/download_mif", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The MapReduce MPI library is a software tool for performing MapReduce operations on a distributed memory parallel computer via message passing (MPI). These are data-processing or computational operations which achieve parallelism by breaking a large task into two stages, a map and a reduce . Each of these are formulated as simple on-processor functions which the user can easily write. The library assigns independent tasks to processors and performs the parallel data movement and transformations behind the scenes.", + "laborHours": 13315.2, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "HTML", + "Python", + "Odin" + ], + "name": "MapReduce MPI library (MR-MPI) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mapreduce", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The FAST software package contains a variety of Python packages for applying and managing software tests. In version 2.0, FAST includes (1) the EXACT package, which supports the definition and execution of computational experiments, (2) the FAST package, which manages the distributed execution of software builds, and (3) general tools related to the PyUnit testing framework.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "FAST - A Framework for Agile Software Testing v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://software.sandia.gov/trac/fast/wiki/Licensing", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fast", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "SOLERGY simulates the operation and power output of a user-defined solar central receiver power plant for a time period of up to one year. SOLERGY utilizes recorded or simulated weather data and plant component performance models to calculate the power flowing through each part of the solar plant. A plant control subroutine monitors these powers and determines when to operate the various plant subsystems. The original version of the code was released in May 1987, within SAND86-8060 and was widely distributed. The Beta Version 1 to be released in 2009, includes some relatively small modifications to the original code.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Solergy (Beta Version 1)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/solergy", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Dimensionality Reduction Library is a C++ library for dimensionality reduction. In the context of this library, dimensionality reduction is considered to consist of 1)estimation of the intrinsic dimensionality using sampled data, 2) Finding maps that reduce the dimensionality of data (forward map) or increase the dimensionality of data (reverse map) and 3) mapping arbitray coordinates to high and low dimensionalities. The library is intended to provide a consistent interface to multiple dimensionality reduction algorithms with an efficient C++ interface that runs efficiently on multicore architectures. A few routines have been optimized with an option for GPU acceleration or distributed computation. Currently the library offers intrinsic dimensionality estimation using point-PCA reconstruction error and/ residual variance. The following dimensionality reduction methods have been implemented: Principal Component Analysis Multidimensional Scaling Locally Linear Embedding IsoMap Autoencoder Neutral Networks An executable is also supplied that can be built to allow for command-line access to the library routines. A description for an application of the library for molecular structure analysis has been published.", + "laborHours": 6976.8, + "languages": [ + "JavaScript" + ], + "name": "Dimensionality Reduction Library v 0.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/dimensionality-reduction-library", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "DELSOL calculates collector field performance and layout and optimal system design for solar thermal central receiver plants. The code consists of a detailed model of the optical performance, a simpler model of the non-optical performance, an algorithm for field layout, and a searching algorithm to find the best system design based on energy cost. The latter two features are coupled to a cost model of central receiver components and an economic model for calculating energy costs. The program optimizes the tower height, receiver size, field layout, heliostat spacings, and tower position at user specified power levels.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "DELSOL v. 3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/delsol", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The RSTT software computes predictions of the travel time of seismic energy traveling from a source to a receiver through 2.5D models of the seismic velocity distribution within the Earth. The two primary applications for the RSTT library are tomographic inversion studies and seismic event location calculations. In tomographic inversions studies, a seismologist begins with number of source-receiver travel time observations and an initial starting model of the velocity distribution within the Earth. A forward travel time calculator, such as the RSTT library, is used to compute predictions of each observed travel time and all of the residuals (observed minus predicted travel time) are calculated. The Earth model is then modified in some systematic way with the goal of minimizing the residuals. The Earth model obtained in this way is assumed to be a better model than the starting model if it has lower residuals. The other major application for the RSTT library is seismic event location. Given an Earth model, an initial estimate of the location of a seismic event, and some number of observations of seismic travel time thought to have originated from that event, location codes systematically modify the estimate of the location of the event with the goal of minimizing the difference between the observed and predicted travel times. The second application, seismic event location, is routinely implemented by the military as part of its effort to monitor the Earth for nuclear tests conducted by foreign countries.", + "laborHours": 0.0, + "languages": [ + "Python", + "Java", + "C++", + "C" + ], + "name": "Code for Calculating Regional Seismic Travel Time", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/rstt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "A library of utility classes for computer vision. Contains implementations of various well-known image processing techniques, such as interest point operators and region descriptors. Includes interfaces to various libraries for image and video I/O, as well as an interface to LAPACK/BLAS. FL was developed at the University of Illinois, Urbana-Champaign (UIUC) and released under an open source license. Version 1.2 was a maintenance release provided by SNL under the LGPL license. Version 1.3 is a maintenance release, containing the following changes: - Improved image format handling. Now handles strided and planar memory layouts and a wider range of pixel formats. - Improved image file I/O, including better support for metadata, a wider range of stored pixel types, and a couple of new file formats. - Improvements to DOG and SIFT, and efficiency improvements in low-level convolution. - Improvements to networking, including a generic TCP listener. - Various improvements to numerical processing. 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HOPSPACK ships with the Generating Set Search (GSS) algorithm, developed at Sandia as part of the APPSPACK open source software project.", + "laborHours": 0.0, + "languages": [], + "name": "Hybrid Optimization Parallel Search PACKage", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hopspack", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "This OpenFabrics Alliance (OFA) OpenSM routing engine module provides credit-loop-free routing while supporting two quality of service (QoS) levels for an InfiniBand fabric with a 3D torus topology. 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By providing the capability to route traffic around failed fabric components, it enables repair of failed components without impacting jobs running on the computer system.", + "homepageURL": "http://downloads.openfabrics.org/OFED", + "laborHours": 0.0, + "name": "3D Torus Routing Engine Module for OFA OpenSM v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://downloads.openfabrics.org/OFED/README.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://downloads.openfabrics.org/OFED", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The MEGRAPHS software package provides a front-end to graphs and vectors residing on special-purpose computing resources. 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These computations are transparently executed on the Cray XMT compute nodes.", + "laborHours": 0.0, + "languages": [], + "name": "Modular Environment for Graph Research and Analysis with a Persistent", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/megraphs", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The MultiThreaded Graph Library (MTGL) is a set of header files that implement graph algorithm in such a way that they can run on massively multithreaded architectures. 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It has gained relevance due to its ability to map serial operations onto parallel distributed architectures, significantly improving developer/analyst productivity. The MapReduceXMT implements the key aspects of MapReduce for the Cray XMT, a massively threaded system that is inherently difficult to program. MapReduceXMT allows users to utilize the machine effectively and efficiently without extensive training in multi-threaded programming. The MapReduceXMT library ports the MapReduce framework onto the Cray XMT. MapReduce is a programming paradigm and an approach to data management for unstructured problems. It has gained relevance due to its ability to map serial operations onto parallel distributed architectures, significantly improving developer/analyst productivity. The MapReduceXMT implements the key aspects of MapReduce for the Cray XMT, a massively threaded system that is inherently difficult to program. MapReduceXMT allows users to utilize the machine effectively and efficiently without extensive training in multi-threaded programming.", + "laborHours": 0.0, + "languages": [], + "name": "MapReduceXMT v. Beta 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/map-reduce-xmt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This revision corrects some errors in SPRNG 1. Users of newer SPRNG versions can obtain the corrected files and build their version with it. This version also improves the scalability of some of the application-based tests in the SPRNG test suite. It also includes an interface to a parallel Mersenne Twister, so that if users install the Mersenne Twister, then they can test this generator with the SPRNG test suite and also use some SPRNG features with that generator.", + "homepageURL": "http://www.sprng.org", + "laborHours": 0.0, + "name": "SPRNG Scalable Parallel Random Number Generator LIbrary", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://creativecommons.org/licenses/by-nc-sa/4.0", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.sprng.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-15" + }, + "description": "Extensions to the AMPL/solver interface library (http://netlib.sandia.gov/ampl/solvers) to compute bounds on algebraic expressions, plus a test program. use in uncertainty quantification and global optimization algorithms. This software is not primarily for military applications.", + "homepageURL": "https://netlib.sandia.gov/ampl/solvers", + "laborHours": 0.0, + "languages": [], + "name": "Slope Extensions to ASL Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://netlib.sandia.gov/ampl/solvers/README", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://netlib.sandia.gov/ampl/solvers", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-18" + }, + "description": "Partially completed extensions for stochastic programming to the AMPL/solver interface library (ASL).modeling and experimenting with stochastic recourse problems. This software is not primarily for military applications.", + "homepageURL": "https://www.netlib.org/ampl/solvers", + "laborHours": 0.0, + "languages": [], + "name": "Partial ASL extensions for stochastic programming", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://netlib.sandia.gov/ampl/solvers/README", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.netlib.org/ampl/solvers", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Foobug is an application to assist a group of developers in keeping track of issues relevant to their shared interests. These are sometimes called \"bug-tracking\" or \"ticket-tracking\" systems.", + "homepageURL": "http://sourceforge.net/projects/foobug", + "laborHours": 0.0, + "name": "Foobug", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://sourceforge.net/projects/foobug", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Inline_System replaces a small subset of file query and manipulation commands, on computing platforms that do not offer a complete standard POSIX environment.", + "homepageURL": "https://sourceforge.net/projects/inlinesystem", + "laborHours": 0.0, + "name": "Inline_System", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/inlinesystem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "A C++ utility library that provides abstractions for common data types with debugging features, support for I/O redirection and support for portability.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "C++ Utility Library V4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/snl-dakota/dakota-packages", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "4.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Acro provides a software infrastructure that integrates a variety of optimization software libraries, as well as general-purpose libraries like UTILIB that support the development of parallel optimizers.", + "homepageURL": "https://software.sandia.gov/trac/acro", + "laborHours": 0.0, + "name": "Acro (A Common Repository for Optimizers) v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://software.sandia.gov/trac/acro", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The Cognitive Foundry is a unified collection of tools designed for research and applications that use cognitive modeling, machine learning, or pattern recognition. The software library contains design patterns, interface definitions, and default implementations of reusable software components and algorithms designed to support a wide variety of research and development needs. The library contains three main software packages: the Common package that contains basic utilities and linear algebraic methods, the Cognitive Framework package that contains tools to assist in implementing and analyzing theories of cognition, and the Machine Learning package that provides general algorithms and methods for populating Cognitive Framework components from domain-relevant data.", + "laborHours": 189939.2, + "languages": [ + "Java" + ], + "name": "Cognitive Foundry v. 3.0 (OSS)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/algorithmfoundry/Foundry", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-02-07" + }, + "description": "PSUADE is an software system that is used to study the relationships between the inputs and outputs of general simulation models for the purpose of performing uncertainty and sensitivity analyses on simulation models.", + "laborHours": 0.0, + "languages": [ + "C(80%), C++(20%)" + ], + "name": "Problem Solving Environment for Uncertainty Analysis and Design Exploration", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.3" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "This code consists of Matlab routines which enable the user to perform non-manifold surface reconstruction via triangulation from high dimensional point cloud data. The code was based on an algorithm originally developed in [Freedman (2007), An Incremental Algorithm for Reconstruction of Surfaces of Arbitrary Codimension Computational Geometry: Theory and Applications, 36(2):106-116]. This algorithm has been modified to accommodate non-manifold surface according to the work described in [S. Martin and J.-P. Watson (2009), Non-Manifold Surface Reconstruction from High Dimensional Point Cloud DataSAND #5272610].The motivation for developing the code was a point cloud describing the molecular conformation space of cyclooctane (C8H16). Cyclooctane conformation space was represented using points in 72 dimensions (3 coordinates for each molecule). The code was used to triangulate the point cloud and thereby study the geometry and topology of cyclooctane. Futures applications are envisioned for peptides and proteins.", + "laborHours": 0.0, + "languages": [], + "name": "NMTRI v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/NMTRI", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/NMTRI", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "BUHFS is a fuse-based POSIX compliant filesystem interface for HPSS. BUHFS was written to provide users with a stable, POSIX compliant interface to EMSL new HPSS based Scientific Data Archive, Aurora.", + "homepageURL": "https://svn.pnl.gov/esp/wiki/ReleasePage", + "laborHours": 0.0, + "name": "Better Userspace HPSS File System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://svn.pnl.gov/esp/wiki/ReleasePage", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.pnl.gov/esp/wiki/ReleasePage", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PriMux is used to compute sets of compatible Polymerase Chain Reaction (PCR)signatures that can be used for detecting the presence of biological species in a small sample of material. Before use, the computed signatures must be empirically tested in a wet lab.", + "homepageURL": "https://sourceforge.net/projects/primux", + "laborHours": 0.0, + "name": "PriMux", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/primux", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Provides python rountines to convert ENDF-6 formatted nuclear data (4) into the new GND structure. Includes sample published ENDF-6 formatted data as well as published ENSL (5) and HDF5 file.", + "homepageURL": "https://ndclx4.bnl.gov/gf/project/gnd/frs/?action=FrsReleaseBrowse&frs_package_id=26", + "laborHours": 0.0, + "name": "General Nuclear Date", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ndclx4.bnl.gov/gf/project/gnd/frs/?action=FrsReleaseBrowse&frs_package_id=26", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The Source Water Quality Modeling software (SWQM) simulates the water quality conditions that reflect properties of water generated by water treatment facilities. SWQM consists of a set of Matlab scripts that model the statistical variation that is expected in a water treatment facility's water, such as pH and chlorine levels.", + "homepageURL": "https://software.sandia.gov/trac/canary/downloader/download/category/10", + "laborHours": 0.0, + "name": "SWQM: Source Water Quality Modeling Software", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://software.sandia.gov/trac/canary/downloader/download/category/10", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://software.sandia.gov/trac/canary/downloader/download/category/10", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "G4beamline is a single-particle-tracking simulation code based on the Geant4 toolkit. It is specifically optimized for the realistic evaluation of beam lines. It is especially useful for evaluating future muon facilities.", + "homepageURL": "http://g4beamline.muonsinc.com", + "laborHours": 0.0, + "name": "G4beamline", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://g4beamline.muonsinc.com", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ] + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "THYME is an object oriented library for building models of wide area control and communications in electric power systems. This software is designed as a module to be used with existing open source simulators for discrete event systems in general and communication systems in particular. THYME consists of a typical model for simulating electro-mechanical transients (e.g., as are used in dynamic stability studies), data handling objects to work with CDF and PTI formatted power flow data, and sample models of discrete sensors and controllers.", + "homepageURL": "http://www.ornl.gov/~1qn/thyme/docs", + "laborHours": 0.0, + "name": "THYME: Toolkit for Hybrid Modeling of Electric Power Systems", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://web.ornl.gov/~nutarojj/thyme/docs/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.ornl.gov/~1qn/thyme/docs", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Bayesloc is a statistical model of the multiple seismic location system, including event hypocenters, corrections to model-based travel time predictions, assessments precision for measurement phase arrival times, and phase lavels which indicate phase ray path.", + "homepageURL": "https://www-gs.llnl.gov/nuclear-threat-reduction/nuclear-explosion-monitoring/bayesloc", + "laborHours": 0.0, + "name": "Bayesian Mulitple-Event Location", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www-gs.llnl.gov/nuclear-threat-reduction/nuclear-explosion-monitoring/bayesloc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CANARY -EDS provides probabilistic event detection based on analysis of time-series data from water quality or other sensors. CANARY also can compare patterns against a library of previously seen data to indicate that a certain pattern has reoccurred, suppressing what would otherwise be considered an event. CANARY can be configured to analyze previously recorded data from files or databases, or it can be configured to run in real-time mode directory from a database, or through the US EPA EDDIES software.", + "homepageURL": "https://software.sandia.gov/trac/canary", + "laborHours": 0.0, + "name": "Characterization and Analysis of Networked Array of Sensors for Event Detection (CANARY-EDS)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://software.sandia.gov/trac/canary", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The TChem toolkit is a software library that enables numerical simulations using complex chemistry and facilitates the analysis of detailed kinetic models. The toolkit provide capabilities for thermodynamic properties based on NASA polynomials and species production and consumption rates. It incorporates methods that can selectively modify reaction parameters for sensitivity analysis and uncertainty quantification. The library also contains several functions that provide analytically computed Jacobian matrices necessary for the efficient time advancement and analysis of detailed kinetic models.", + "homepageURL": "http://www.sandia.gov/tchem", + "laborHours": 0.0, + "name": "TChem", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.sandia.gov/tchem", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "LIME 0.5 is an initial version of a Lightweight Integrating Multi-physics Environment for coupling codes. LIME by itself is not a code for doing multiphysics simulations. Instead, LIME provides the key high-level software, a flexible but defined approach, and interface requirements for a collection of (potentially disparate) physics codes to be combined with strong coupling (when needed) though non-linear solution methods (e.g. JFNK, fixed point), thus creating a new multi-physics simulation capability customized for a particular need. The approach taken is designed to; preserve and leverage any important specialized algorithms and/or functionality an existing application may provide; minimize the requirements barrier for an application to participate; and work within advanced solver frameworks (e.g. as extensions to the Trilinos/NOX nonlinear solver libraries, PETSc, . . .). Of note is that components/physics codes that can be coupled within LIME are NOT limited to: components written in one particular language; a particular numerical discretization approach ( e.g. Finite Element); or physical models expressed as PDE's.", + "laborHours": 7326.4, + "languages": [ + "CMake", + "C++", + "Fortran" + ], + "name": "LIME 0.5", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/limeext", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-02-07" + }, + "description": "PSUADE is an software system that is used to study the releationships between the inputs and outputs of gerneral simulation models for the purpose of performing uncertainty and sensitivity analyses on simulation models.", + "laborHours": 0.0, + "languages": [], + "name": "Problem Solving Environment for Uncertainty Analysis and Design Exploration", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.4" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The All People's Simulator is a software package which can simulate a large number of people wandering randomly through a real city. It utilizes freely-available map data from the OpenStreetMaps project to create a map of city streets, then simulates people wandering through those streets. APS was designed to integrate with other work being done in the \"Megadroid\" LDRD, but is capable of functioning and providing value completely on its own.", + "laborHours": 547.2, + "languages": [ + "Go", + "Makefile" + ], + "name": "All People's Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/gosim?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gosim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Interatomic force and energy calculation subroutine tobe used with the molecular dynamics simulation code LAMMPS (Ref a.). The code evaluates the total energy and atomic forces (energy gradient) according to cubic spine-based variant (Ref b.) of the Modified Embedded Atom Method (MEAM).", + "homepageURL": "http://lammps.sandia.gov/download.html", + "laborHours": 0.0, + "name": "MEAM interatomic force calculation subroutine for LAMMPS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://lammps.sandia.gov/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The Water Security Toolkit (WST) provides software for modeling and analyzing water distribution systems to minimize the potential impact of contamination incidents. WST wraps capabilities for contaminant transport, impact assessment, and sensor network design with response action plans, including source identification, rerouting, and decontamination, to provide a range of water security planning and real-time applications.", + "laborHours": 695460.8, + "languages": [ + "C++", + "HTML", + "C", + "JavaScript", + "M4", + "Python" + ], + "name": "Water Security Toolkit", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/Water-Security-Toolkit?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Water-Security-Toolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "PHISH is a lightweight framework which a set of independent processes can use to exchange data as they run on the same desktop machine, on processors of a parallel machine, or on different machines across a network. This enables them to work in a coordinated parallel fashion to perform computations on either streaming, archived, or self-generated data. The PHISH distribution includes a simple, portable library for performing data exchanges in useful patterns either via MPI message-passing or ZMQ sockets. PHISH input scripts are used to describe a data-processing algorithm, and additional tools provided in the PHISH distribution convert the script into a form that can be launched as a parallel job.", + "laborHours": 6733.6, + "languages": [ + "C++", + "C", + "CMake", + "Makefile", + "Ring", + "Edge", + "Python" + ], + "name": "Parallel Harness for Informatic Stream Hashing", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/phish", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "This application simulates microstructural and compositional evolution in two-phase, two-component systems. It is designed to run within the SPPARKS solver and combines the kMC with solution to the Cahn-Hilliard Eq. for phase field.", + "laborHours": 165102.4, + "languages": [ + "C++", + "C" + ], + "name": "app_hybridPotts-phasefield.cpp", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spparks", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This application simulates simple solid state sintering by incorporating all the active mechanisms, namely, curvature-driven gain growth, pore shaping and migration by surface diffusion, and creation, diffusion and annihilation of vacancies. It is an application developed for SPPARKS and has to be run within this framework.", + "homepageURL": "http://spparks.sandia.gov", + "laborHours": 0.0, + "name": "app_sintering.cpp", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://spparks.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The plpdfa software is a product of an LDRD project at LLNL entitked \"Adaptive Sampling for Very High Throughput Data Streams\" (tracking number 11-ERD-035). This software was developed by a graduate student summer intern, Chris Challis, who worked under project PI Dan Merl furing the summer of 2011. The software the source code is implementing is a statistical analysis technique for clustering and classification of text-valued data. The method had been previously published by the PI in the open literature.", + "homepageURL": "http://cran.r-project.org", + "laborHours": 0.0, + "name": "Particle learning for probabilistic deterministic finite automata", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://cran.r-project.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DAQMAN is a flexible configurable interface that allows the user to build and operate a VME-based data acquisition system on a Linux workstation. It consists of two parts: a Java-based Graphical User Interface to configure the system, and a C-based utility that reads out the data and creates the output ASCII data file, with two levels of diagnostic tools. The data acquisition system requires a CAEN CONET-VME Bridge to communicate between the hardware in the VME crate and the Linux workstation. Data acquisition modules, such as ADCs, TDC, Scalers, can be loaded into the system, or removed easily. The GUI allows users to activate modules, and channels within modules by clicking on icons. Running configurations are stored; data are collected and can be viewed either as raw numbers, or by charts and histograms that update as the data are accumulated. Data files are written to disk in ASCII format, with a date and time stamp.", + "homepageURL": "https://www.bnl.gov/nsrl/userguide/data-aquisition.php", + "laborHours": 0.0, + "name": "DAQMAN - A flexible configurable data acquisition system", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.bnl.gov/nsrl/userguide/data-aquisition.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.bnl.gov/nsrl/userguide/data-aquisition.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HFBRHO is a physics computer code that is used to model the structure of the nucleus. It is an implementation of the nuclear energy Density Functional Theory (DFT), where the energy of the nucleus is obtained by integration over space of some phenomenological energy density, which is itself a functional of the neutron and proton densities. In HFBTHO, the energy density derives from the Skyrme effective two-body interaction between nucleons, nuclear superfluidity is treated at the Hartree-Fock-Bogoliubov (HFB) approximation, and axial-symmetry of the nuclear shape is assumed This version is the 2nd release of the program; the previous version has been published in Computer Physics Communications (1). It is the first version that has been partly developed at Lawrence Livermore National Laboratory.", + "homepageURL": "http://cpc.cs.qub.ac.uk/summaries/ADUI_v2_0.html", + "laborHours": 0.0, + "name": "HFBTHO", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://cpc.cs.qub.ac.uk/summaries/ADUI_v2_0.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "LMAT is designed to take as input a collection of raw metagenomic sequencer reads, and search each read against a reference genome database and assign a taxonomic label and confidence value to each read and report a summary of the predicted taxonomic contents of the metagenomic sample.", + "homepageURL": "https://sourceforge.net/projects/lmat", + "laborHours": 0.0, + "name": "Livermore Metagenomics Analysis Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/lmat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PERM is a C library for persistent heap management and is intended for use with a dynamic-memory allocator (e.g. malloc, free). The PERM memory allocator replaces the standard C dynamic memory allocation functions with compatible versions that provide persistent memory to application programs. Memory allocated with the PERM allocatory will persist between program invocations after a call to a checkpoint function. This function essentially saves the state of the heap and registered global variables to a file which may reside in flash memory or other node local storage. A few other functions are also provided by the library to manage checkpoint files. Global variables in an application can be marked persistent and be included in a checkpoint by using a compiler attribute defined as PERM. The PERM checkpoint methof is not dependent on the programming model ans works with distributed memory or shared memory programs.", + "homepageURL": "https://computation.llnl.gov/projects/memory-centric-architectures/download/perm-je-0.9.7.tgz", + "laborHours": 0.0, + "name": "Persistent heap Management library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://computation.llnl.gov/projects/memory-centric-architectures/download/perm-je-0.9.7.tgz", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MMA is a stand-alone memory management system for MPI clusters. It implements a shared Partitioned Global Address Space, where multiple MPI processes request objects from the allocator and the latter provides them with system-wide unique memory addresses for each object. It provides applications with an intuitive way of managing the memory system in a unified way, thus enabling easier writing of irregular application code.", + "homepageURL": "http://myrmics.com/download.php", + "laborHours": 0.0, + "name": "Myrmics Memory Allocator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://myrmics.com/downloads/mma_license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://myrmics.com/download.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GeoTess facilitates access to a multi-level triangular tessellation of a unit sphere, including find the index of the triangle in which an arbitrary position on the sphere resides and computing the interpolation coefficients that should be applied to data stored on the nodes of the tessellation that defines the triangle. It is very common for Earth scientists to store values of various Earth properties on a grid that spans the globe. For convenience, they almost always choose a grid which is evenly spaced in both latitude and longitude over the surface of the globe. While these grids are evenly spaced in latitude-longitude coordinates, they are in reality very unevenly spaced when cell size is evaluated in square km since lines of longitude converge at the poles. Tessellations consisting of a set of approximately equal area triangles that span the globe are much more efficient way to impose a grid onto the surface of a sphere. The GeoTess software facilitates interacting with a triangular tessellation of a sphere and could significantly increase the efficiency of Earth science software codes. The code can construct variable resolution triangular tessellations. It can also load a previously constructed tessellation from an input file and implements a \"walking triangle\" search algorithm to find the index of the triangle on the tessellation that contains a user specified point of interest. It also computes the interpolation coefficients that should be applied to data stored on the nodes of the containing triangle", + "laborHours": 135918.4, + "languages": [ + "Java", + "HTML" + ], + "name": "GeoTess v. 2.6.8", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GeoTessJava", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.6.8" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-19" + }, + "description": "SHOE is research code for characterizing and visualizing higher-order finite elements; it contains a framework for defining classes of interpolation techniques and element shapes; methods for interpolating triangular, quadrilateral, tetrahedral, and hexahedral cells using Lagrange and Legendre polynomial bases of arbitrary order; methods to decompose each element into domains of constant gradient flow (using a polynomial solver to identify critical points); and an isocontouring technique that uses this decomposition to guarantee topological correctness. Please note that this is an alpha release of research software and that some time has passed since it was actively developed; build- and run-time issues likely exist.", + "laborHours": 13360.8, + "languages": [ + "C++", + "C", + "CMake", + "Python" + ], + "name": "Sandia Higher Order Elements (SHOE) v 0.5 alpha", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/shoe", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "The Uncertainty Quantification (UQ) Toolkit is a software library for the characterizaton and propagation of uncertainties in computational models. For the characterization of uncertainties, Bayesian inference tools are provided to infer uncertain model parameters, as well as Bayesian compressive sensing methods for discovering sparse representations of high-dimensional input-output response surfaces, and also Karhunen-Loève expansions for representing stochastic processes. Uncertain parameters are treated as random variables and represented with Polynomial Chaos expansions (PCEs). The library implements several spectral basis function types (e.g. Hermite basis functions in terms of Gaussian random variables or Legendre basis functions in terms of uniform random variables) that can be used to represent random variables with PCEs. For propagation of uncertainty, tools are provided to propagate PCEs that describe the input uncertainty through the computational model using either intrusive methods (Galerkin projection of equations onto basis functions) or non-intrusive methods (perform deterministic operation at sampled values of the random values and project the obtained results onto basis functions).", + "laborHours": 217101.6, + "languages": [ + "C++", + "C", + "Fortran" + ], + "name": "UQ Toolkit v 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/UQTk", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "CACTUS is a code that calculates the performance and aero/hydrodynamic loads of a wind or water turbine. The turbine may be either a vertical-axis or a horizontal-axis machine, and may consist of one or more blade curved or straight blades. The performance model is based on a lifting-line free wake formulation that calculates rotor power and blade loads in the time domain. The rotor is treated as a rotating rigid body, such that structural dynamical motions are not modeled. The turbine is assumed to operate within a steady, but possibly sheared, wind or current velocity. For marine hydrokinetic energy applications, the presence of a river/tidal channel bed and water surface boundaries may be modeled.", + "laborHours": 3587.2, + "languages": [ + "CMake", + "MATLAB", + "Fortran", + "GLSL", + "Python" + ], + "name": "Code for Axial and Crossflow Turbine Simulation", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CACTUS", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Our application, the Omics Metadata Management Software (OMMS), answers both needs, empowering experimentalists to generate intuitive, consistent metadata, and to perform bioinformatics analyses and information management tasks via a simple and intuitive web-based interface. Several use cases with short-read sequence datasets are provided to showcase the full functionality of the OMMS, from metadata curation tasks, to bioinformatics analyses and results management and downloading. The OMMS can be implemented as a stand alone-package for individual laboratories, or can be configured for web-based deployment supporting geographically dispersed research teams. Our software was developed with open-source bundles, is flexible, extensible and easily installed and run by operators with general system administration and scripting language literacy.", + "homepageURL": "http://omms.sandia.gov", + "laborHours": 0.0, + "name": "Omics Metadata Management Software v. 1 (OMMS)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://omms.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The RAPTOR computational pipeline identifies microbial nucleic acid sequences present in sequence data from clinical samples. It takes as input raw short-read genomic sequence data (in particular, the type generated by the Illumina sequencing platforms) and outputs taxonomic evaluation of detected microbes in various human-readable formats. This software was designed to assist in the diagnosis or characterization of infectious disease, by detecting pathogen sequences in nucleic acid sequence data from clinical samples. It has also been applied in the detection of algal pathogens, when algal biofuel ponds became unproductive. RAPTOR first trims and filters genomic sequence reads based on quality and related considerations, then performs a quick alignment to the human (or other host) genome to filter out host sequences, then performs a deeper search against microbial genomes. Alignment to a protein sequence database is optional. Alignment results are summarized and placed in a taxonomic framework using the Lowest Common Ancestor algorithm.", + "homepageURL": "http://bioinformatics.sandia.gov/software", + "laborHours": 0.0, + "name": "Rapid Threat Organism Recognition Pipeline", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://bioinformatics.sandia.gov/software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://bioinformatics.sandia.gov/software", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "NuMAD helps to enable efficient creation and use of high fidelity wind turbine blade models for structural and aerodynamic analysis. NuMAD is a GUI-based tool used to manage the specific geometry and materials inputs required to fully describe a wind turbine blade.", + "laborHours": 34321.6, + "languages": [ + "MATLAB", + "HTML" + ], + "name": "Numerical Manufacturing And Design tool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/NuMAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "graphMC consists of an implementation of a set of statistical tests that ensure that a Markov chain in the space of graphs has converged to its stationary distribution. The tests are applicable when the graphs have labelled nodes. The tests are applied to the binary time-series traced out by an edge between two selected nodes. The software fits models of a first-order Markov process and an independent draws from a binary distribution to the time-series and selects one based on the BIC scores of the two models. The package consists of (1) an implementation of a Markov chain driving a graph rewiring process that preserves the joint degree distribution of the graph, (2) implementation of the statistical test mentioned above and (3) two examples that show how the Markov chain infrastructure and the statistical tests can be used.", + "laborHours": 0.0, + "languages": [], + "name": "graphMC: A package for testing the independence of graphs", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/graphMC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "NetMOD is a tool to model the performance of global ground-based explosion monitoring systems. The initial version of the software supports the simulation of seismic detection capability. The tool provides a user interface to execute simulations based upon a hypothetical definition of the monitoring system configuration, geophysical properties of the Earth, and detection analysis criteria.", + "laborHours": 15.2, + "languages": [ + "Java" + ], + "name": "NetMOD", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/netmod", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software implements the generative graph algorithm described in the following reference: T. G. Kolda, A. Pinar, T. Plantenga and C. Seshadhri. A Scalable Generative Graph Model with Community Structure, arXiv:1302.6636, March 2013, http:l/arxiv.org/abs/1302.6636. The software also implements the clustering coefficient algorithms described in C. Seshadhri, A. Pinar and T. G. Kolda. Triadic Measures on Graphs: The Power of Wedge Sampling, in Proc. 2013 SIAM International Conference on Data Mining {SDM), May 2013.", + "laborHours": 0.0, + "languages": [], + "name": "FEASTPACK v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/feastpack", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Software to manipulate and describe crystal and molecular structures and set up structural refinements from multiple experimental inputs. Calculation and simulation of structure derived physical quantities. Library for creating customized refinements of atomic structures from available experimental and theoretical inputs.", + "homepageURL": "http://www.diffpy.org", + "laborHours": 0.0, + "name": "DiffPy-CMI-Python libraries for Complex Modeling Initiative", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.diffpy.org/products/diffpycmi/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.diffpy.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Polytope is a library that wraps several algorithms for generating the Voronoi diagram in both serial and distributed parallel.", + "homepageURL": "https://bitbucket.org/jjphatt/polytope", + "laborHours": 0.0, + "name": "Polytope", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/jjphatt/polytope/src/ef2ecd61b60b31a4b7ba95e88f893f2fd7382a80/LICENSE?at=default&fileviewer=file-view-default", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/jjphatt/polytope", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SolidSpheral is an extension of the Spheral open source meshless hydrodynamics method. SolidSpheral adds the capability to model solid materials using analytic equations of state, and a simple damage model to allow for the modeled materials to undergo dynamic damage evolution. SolidSpheral is a distributed parallel code employing MPI for the parallel framework.", + "homepageURL": "https://sourceforge.net/projects/spheral", + "laborHours": 0.0, + "name": "SolidShperal", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/spheral", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-01" + }, + "description": "The Toolkit for Adaptive Stochastic Modeling and Non-Intrusive ApproximatioN is a collection of robust libraries for high dimensional integration and interpolation as well as parameter calibration. The code consists of several modules that can be used individually or conjointly.", + "laborHours": 24624.0, + "languages": [], + "name": "Tasmanian", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/Tasmanian", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Code to support, enable, and expand monitoring of network devices, servers, and network services.", + "homepageURL": "http://mathias-kettner.de/checkmk.html", + "laborHours": 0.0, + "name": "check_mkcheck_mk (ORNL expansions)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://mathias-kettner.de/checkmk.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This package implements an optimal-scaling multigrid solver for the (non) linear systems that arise from the discretization of problems with evolutionary behavior. Typically, solution algorithms for evolution equations are based on a time-marching approach, solving sequentially for one time step after the other. Parallelism in these traditional time-integrarion techniques is limited to spatial parallelism. However, current trends in computer architectures are leading twards system with more, but not faster. processors. Therefore, faster compute speeds must come from greater parallelism. One approach to achieve parallelism in time is with multigrid, but extending classical multigrid methods for elliptic poerators to this setting is a significant achievement. In this software, we implement a non-intrusive, optimal-scaling time-parallel method based on multigrid reduction techniques. The examples in the package demonstrate optimality of our multigrid-reduction-in-time algorithm (MGRIT) for solving a variety of parabolic equations in two and three sparial dimensions. These examples can also be used to show that MGRIT can achieve significant speedup in comparison to sequential time marching on modern architectures.", + "homepageURL": "https://computation.llnl.gov/projects/parallel-time-integration-multigrid/software", + "laborHours": 0.0, + "name": "Parallel time integration software", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://computation.llnl.gov/projects/parallel-time-integration-multigrid/software", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "joiner@ameslab.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ThermoPhonon is a stand-alone code, which can be integrated into other software packages. Typically, it is used together with a density functional theory (DFT) code (such as VASP, Wien2k, AbInit, SIESTA) and a phonon code (such as Phonopy or Phon). The workflow is the following. Molecular dynamics (MD) in a supercell at a given temperature T is performed using another code. After sufficient equilibration, the output in the form of atomic positions and forces for a large number of selected MD steps is recorded into a file. If needed, one can modify this file by applying additional constraints, such as enforced crystal symmetry or subtracted motion of the center of mass. ThermoPhonon reads the file with atomic positions and forces and writes a new file with the force constants. Force constants can be used by another code (such as Phonopy or Phon) to produce phonon spectrum for plotting, in the assumption of known equilibrium atomic positions provided in a separate file.", + "homepageURL": "http://lib.dr.iastate.edu/ameslab_software/2", + "laborHours": 0.0, + "name": "ThermoPhonon", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://lib.dr.iastate.edu/ameslab_software/2", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "ForQint is a Fortran software library to adaptively integrate multivariable functions versus well known probability distributions (e.g. normal, lognormal, etc.) using quadrature rules. Such integration is known to be more efficient and accurate especially when the function evaluation is expensive. The library also FQint enables the creation of both full and sparse anisotropic multi-dimensional quadrature rules. These latter encompass different such as Gauss-Hermite, Gauss-Legendre, etc. The functions Maher Salloum, Bert Debusschere, Kenny Chowdhary and subroutines rely on the C++ Stokhos package of Trilinos (trilinos.sandia.gov) where the appropriate classes were wrapped into Fortran.", + "laborHours": 699.2, + "languages": [ + "Makefile", + "Fortran" + ], + "name": "ForQint", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ForQint", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The software is used to fit models of emission fields (e.g., fossil-fuel CO2 emissions) to sparse measurements of gaseous concentrations. Its primary aim is to provide an implementation and a demonstration for the algorithms and models developed in J. Ray, V. Yadav, A. M. Michalak, B. van Bloemen Waanders and S. A. McKenna, \"A multiresolution spatial parameterization for the estimation of fossil-fuel carbon dioxide emissions via atmospheric inversions\", accepted, Geoscientific Model Development, 2014. The software can be used to estimate emissions of non-reactive gases such as fossil-fuel CO2, methane etc. The software uses a proxy of the emission field being estimated (e.g., for fossil-fuel CO2, a population density map is a good proxy) to construct a wavelet model for the emission field. It then uses a shrinkage regression algorithm called Stagewise Orthogonal Matching Pursuit (StOMP) to fit the wavelet model to concentration measurements, using an atmospheric transport model to relate emission and concentration fields. Algorithmic novelties described in the paper above (1) ensure that the estimated emission fields are non-negative, (2) allow the use of guesses for emission fields to accelerate the estimation processes and (3) ensure that under/overestimates in the guesses do not skew the estimation.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "sparse-msrf:A package for sparse modeling and estimation of fossil-fuel CO2 emission fields", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sparse-msrf", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-19" + }, + "description": "Genomic islands are key mobile DNA elements in bacterial evolution, that can distinguish pathogenic strains from each other, or distinguish pathogenic strains from non-pathogenic strains. Their detection in genomes is a challenging problem. We present 3 main software components that attack the island detection problem on two different bases: 1) the preference of islands to insert in chromosomal tRNA or tmRNA genes (islander.pl), and 2) islands' sporadic occurrence among closely related strains. The latter principle is employed in both an algorithm (learnedPhyloblocks.pl) and a visualization method (panGenome.pl). Component islander.pl finds islands based on their preference for a particular target gene type. We annotate each tRNA and tmRNA gene, find fragments of each such gene as candidates for the distal ends of islands, and filter candidates to remove false positives. Component learnedPhyloblocks.pl uses islands found by islander.pl and other methods as a training set to find new islands. Reference genomes are aligned using mugsy, then the \"phylotypes\" or patterns of occurrence in the reference set are determined for each position in the target genome, and those phylotypes most enriched in the training set of islands are followed to detect yet more islands. Component panGenome.pl produces a big-data visualization of the chromosomally-ordered \"pan-genome\", that includes every gene of every reference genome (x-axis, pan-genome order; y-axis, reference genomes; color-coding, gene presence/absence etc.), islands appearing as dark patches.", + "laborHours": 18027.2, + "languages": [ + "Perl", + "C", + "Python" + ], + "name": "Genomic Island Identification Software v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TIGER", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "Matlab Toolbox for simulating the impact of solar energy on the distribution grid. The majority of the functions are useful for interfacing OpenDSS and MATLAB, and they are of generic use for commanding OpenDSS from MATLAB and retrieving GridPV Toolbox information from simulations. A set of functions is also included for modeling PV plant output and setting up the PV plant in the OpenDSS simulation. The toolbox contains functions for modeling the OpenDSS distribution feeder on satellite images with GPS coordinates. Finally, example simulations functions are included to show potential uses of the toolbox functions.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "OpenDSS" + ], + "name": "GridPV Toolbox", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gridpv", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The SPARTA package is software for simulating low-density fluids via the Direct Simulation Monte Carlo (DSMC) method, which is a particle-based method for tracking particle trajectories and collisions as a model of a multi-species gas. The main component of SPARTA is a simulation code which allows the user to specify a simulation domain, populate it with particles, embed triangulated surfaces as boundary conditions for the flow, overlay a grid for finding pairs of collision partners, and evolve the system in time via explicit timestepping. The package also includes various pre- and post-processing tools, useful for setting up simulations and analyzing the results. The simulation code runs either in serial on a single processor or desktop machine, or can be run in parallel using the MPI message-passing library, to enable faster performance on large problems.", + "laborHours": 267930.4, + "languages": [ + "C++", + "Shell", + "C", + "Roff", + "CMake", + "Python" + ], + "name": "Stochastic PArallel Rarefied-gas Time-accurate Analyzer", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sparta/sparta", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Performs a cross-correlation calculation to align images. This is particularly useful for aligning frames of a movie so that an object of interest does not spatially drift. For in situ microscopy experiments. Movies are collected where an object changes with time. At the same time, the object usually drifts too. This shifts the movie frames so that the object is aligned from frame to frame. Then it is easy to see the object changes without the added complication of it moving too.", + "homepageURL": "http://freesourcecode.net/matlabprojects/57416/drifty-shifty-deluxe-in-matlab#.Wczt52hyKUk", + "laborHours": 0.0, + "name": "Drifty shifty deluxe.m", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://freesourcecode.net/matlabprojects/57416/drifty-shifty-deluxe-in-matlab#.Wczt52hyKUk", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MGPT is an unclassified source code for the fast evaluation and application of quantum-based MGPT interatomic potentials for mrtals. The present version of MGPT has been developed entirely at LLNL, but is specifically designed for implementation in the open-source molecular0dynamics code LAMMPS maintained by Sandia National Laboratories. Using MGPT in LAMMPS, with separate input potential data, one can perform large-scale atomistic simulations of the structural, thermodynamic, defeat and mechanical properties of transition metals with quantum-mechanical realism.", + "homepageURL": "http://lammps.sandia.gov/download.html", + "laborHours": 0.0, + "name": "Fast Model Generalized Pseudopotential Theory Interatomic Potential Routine", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://lammps.sandia.gov/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "joiner@ameslab.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HostDesigner is a computer-aided molecular design code that enables the general application of de novo structure-based methods to problems in chemistry and material science. Its purpose is to identify organic molecules with 3D structures that match user-input specifications. To accomplish this, the code connects chemical fragments to build millions of potential molecules, evaluates the resulting structures based on geometric constraints, and outputs a rank-ordered list of candidates. Example applications include the design of metal ion sequestering agents for use in separations processes, molecules that form self-assembled nanoscale containers, and molecular building blocks for metal-organic frameworks.", + "homepageURL": "http://sourceforge.net/projects/hostdesigner-v3-0", + "laborHours": 0.0, + "name": "HostDesigner, Version 3", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://sourceforge.net/projects/hostdesigner-v3-0", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "This software generates environmental contours of extreme sea states using buoy observations of significant wave height and energy period or peak period. The code transforms these observations using principal component analysis (PCA) to create an uncorrelated representation of the data. The subsequent components are modeled using probability distributions and parameter fitting functions. The inverse first-order reliability method (I-FORM) is then applied to these models in order to generate an extreme event contour based on a given return period (i.e., 100 years).The subsequent contour is then transformed back into the original input space defined by the variables of interest in order to create an environmental contour of extreme sea states.", + "laborHours": 197.6, + "languages": [ + "MATLAB" + ], + "name": "Extreme_SeaState_Contour_v1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SNL-ESSC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "creinke@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-01-18" + }, + "description": "LuaCLRBridge is a library which provides an interface for hosting Lua within .NET applications and facilitating interoperability between the two runtimes.", + "homepageURL": "https://bitbucket.org/luaclrbridge/luaclrbridge/src", + "laborHours": 20748.0, + "languages": [ + "C#", + "C++/CLI" + ], + "name": "Lua-CLR Bridge", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/luaclrbridge/luaclrbridge/src", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Geospatial Toolkit is an NREL-developed map-based software application that integrates resource data and other geographic information systems (GIS) data for integrated resource assessment. The non-resource, country-specific data for each toolkit comes from a variety of agencies within each country as well as from global datasets. Originally developed in 2005, the Geospatial Toolkit was completely redesigned and re-released in November 2010 to provide a more modern, easier-to-use interface with considerably faster analytical querying capabilities. The revised version of the Geospatial Toolkit has been released for all original toolkit countries/regions and each software package is made available on NREL's website,", + "homepageURL": "http://www.nrel.gov/international/geospatial_toolkits.html", + "laborHours": 281245.6, + "name": "Geospatial Toolkit", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.nrel.gov/international/geospatial_toolkits.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This software contains a set of python modules – input, search, cluster, analysis; these modules read input files containing spatial coordinates and associated attributes which can be used to perform nearest neighbor search (spatial indexing via kdtree), cluster analysis/identification, and calculation of spatial statistics for analysis.", + "homepageURL": "http://spparks.sandia.gov", + "laborHours": 0.0, + "name": "cluster trials v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://spparks.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "Sandia SPT is designed as software to accompany a book chapter being published a methods chapter which provides an introduction on how to label and track individual proteins. The Sandia Simple Particle Tracking code uses techniques common to the image processing community, where its value is that it facilitates implementing the methods described in the book chapter by providing the necessary open-source code. The code performs single particle spot detection (or segmentation and localization) followed by tracking (or connecting the detected particles into trajectories). The book chapter, which along with the headers in each file, constitutes the documentation for the code is: Anthony, S.M.; Carroll-Portillo, A.; Timlon, J.A., Dynamics and Interactions of Individual Proteins in the Membrane of Living Cells. In Anup K. Singh (Ed.) Single Cell Protein Analysis Methods in Molecular Biology. Springer", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Sandia Simple Particle Tracking (Sandia SPT) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The SDET Tool is used to create open-access power grid data sets and facilitate updates of these data sets by the community. Pacific Northwest National Laboratory (PNNL) and its power industry and software vendor partners are developing an innovative sustainable data evolution technology (SDET) to create open-access power grid datasets and facilitate updates to these datasets by the power grid community. The objective is to make this a sustained effort within and beyond the ARPA-E GRID DATA program so that the datasets can evolve over time and meet the current and future needs for power grid optimization and potentially other applications in power grid operation and planning.", + "homepageURL": "https://egriddata.org/dataset/sdet-tool", + "laborHours": 0.0, + "name": "Sustainable Data Evolution Technology for Power Grid Optimization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://egriddata.org/dataset/sdet-tool", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://egriddata.org/dataset/sdet-tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "Socorro can be used to compute the ground-state electron density for a periodically repeated simulation cell in which the external potential is obtained from norm-conserving pseudopotentials or projector-augmented-wave functions. The ground-state electron density is computed by summation over one-electron orbitals which are obtained using the Kohn-Sham formulation of density-functional theory and which are expanded in a plane-wave basis. Various quantities can be computed from the ground-state solution, including atomic forces which can be used to optimize atom positions in the simulation cell and to perform molecular dynamics simulations.", + "laborHours": 0.0, + "languages": [ + "C", + "Fortran" + ], + "name": "Socorro Electronic Structure Software", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/socorro", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A set of programs and utilities for generating and manipulating data files in TSV (tab-separated value) or JSON format.", + "laborHours": 8755.2, + "name": "db, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl-chash/db/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-chash/db", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Computing a Voronoi or Delaunay tessellation from a set of points is a core part of the analysis of many simulated and measured datasets. As the scale of simulations and observations surpasses billions of particles, a distributed-memory scalable parallel algorithm is the only feasible approach. The primary contribution of this software is a distributed-memory parallel Delaunay and Voronoi tessellation algorithm based on existing serial computational geometry libraries that automatically determines which neighbor points need to be exchanged among the subdomains of a spatial decomposition. Other contributions include the addition of periodic and wall boundary conditions.", + "laborHours": 5502.4, + "name": "TESS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/diatomic/tess2", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Ravel is a tool for analyzing and visualizing parallel execution traces. It deduces a logical structure of parallel program events from the trace records and calculates comparative metrics. It displays the results of this analysis using multiple views at varying levels of detail to allow interactive exploration of the trace.", + "laborHours": 12555.2, + "name": "Ravel", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/scalability-llnl/Ravel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-07" + }, + "description": "PIKA is a MOOSE-based application for modeling micro-structure evolution of seasonal snow. The model will be useful for environmental, atmospheric, and climate scientists. Possible applications include application to energy balance models, ice sheet modeling, and avalanche forecasting. The model implements physics from published, peer-reviewed articles. The main purpose is to foster university and laboratory collaboration to build a larger multi-scale snow model using MOOSE. The main feature of the code is that it is implemented using the MOOSE framework, thus making features such as multiphysics coupling, adaptive mesh refinement, and parallel scalability native to the application. PIKA implements three equations: the phase-field equation for tracking the evolution of the ice-air interface within seasonal snow at the grain-scale; the heat equation for computing the temperature of both the ice and air within the snow; and the mass transport equation for monitoring the diffusion of water vapor in the pore space of the snow.", + "laborHours": 6840.0, + "languages": [], + "name": "Snow Micro-Structure Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/pika", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Lestre performs a high-speed scan of the Lustre metadata target, and provides a listing of files that match a user-specified criteria, such as modification time, inode number, or if its data resides on specific OSTs. The output format is configurable, as is the parameters it uses to perform IO.", + "laborHours": 2492.8, + "name": "Lester, the Lustre Lister", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-TechInt/lester", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This site allows state data contributors to validate their WFS services against a specified schema for tier 3 data. The application uses the USGIN models API at https://github.com/usgin/usginmodels.", + "laborHours": 4636.0, + "name": "Web Feature Service Validator", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/ContentModelCMS/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/ContentModelCMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Django site used to manage the approved information exchanges (content models) after creation and public comment at https://github.com/usgin-models.", + "laborHours": 14394.4, + "name": "Information Exchange management site", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/modelmanager", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "THE NGDS IS A USER-FRIENDLY, WEB-BASED APPLICATION TO SUPPORT FINDING, VISUALIZING, MAPPING, AND ACQUISITION OF DATA BY END-USERS. THIS APPLICATION ALLOWS USERS TO DISCOVER AND ACCESS RESOURCES MADE AVAILABLE ACROSS ALL NGDS NODES, AND TO SEARCH FOR DATA ACROSS THE SYSTEM BASED ON TOPIC, LOCATION, AND OR OTHER CRITERIA. STANDARDIZED METADATA DESCRIBING EACH DATASET PROVIDES THE USER WITH THE INFORMATION NECESSARY TO DETERMINE THE UTILITY OF THAT DATASET FOR THEIR PURPOSES. GEOGRAPHIC DATASETS CAN BE VISUALIZED THROUGH A MAP INTERFACE THAT ALLOWS USERS TO INSPECT THE DETAILS OF INDIVIDUAL DATA POINTS (E.G. WELLS, TEMPERATURE MEASUREMENTS, ETC.) FROM PROPERLY FORMATTED DATASETS. IN ADDITION TO VISUALIZATION WITHIN THE APPLICATION, THE INTERFACE PROVIDES THE INFORMATION NECESSARY FOR USERS TO ACCESS THE DATA FROM OTHER APPLICATIONS.", + "laborHours": 8816.0, + "name": "National Geothermal Database", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ngds/documents", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Django app for converting CSV records to XML metadata documents. This transformation from the metadata content model to parsed ISO XML documents allows for metadata integration into NGDS.", + "laborHours": 45.6, + "name": "CSV to ISO XML metadata transformation tool", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/usgincsv/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/usgincsv", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Not Specified", + "laborHours": 87278.4, + "name": "CASTRO", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/AMReX-Astro/Castro/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Astro/Castro", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-07-13" + }, + "description": "KINSOL is part of a software family called SUNDIALS: SUite of Nonlinear and Differential/Algebraic equation Solvers [1]. KINSOL is a general-purpose nonlinear system solver based on Newton-Krylov and fixed-point solver technologies [2].", + "laborHours": 213088.8, + "languages": [], + "name": "General purpose nonlinear system solver based on Newton-Krylov method", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Avalaunch implements a tree-based process launcher. It first bootstraps itself on to a set of compute nodes by launching children processes, which immediately connect back to the parent process to acquire info needed t launch their own children. Once the tree is established, user processes are started by broadcasting commands and application binaries through the tree. All communication flows over high-performance network protocols via spawnnet. The goal is to start MPI jobs having hundreds of thousands of processes within seconds.", + "laborHours": 21371.2, + "name": "Avalaunch", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/avalaunch/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/avalaunch", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The av_sys_image_mgr utility provides an interface for the creation, manipulation, and analysis of system boot images for computer systems. It is primarily intended to provide a convenient method for managing the introduction of changes to boot images for long-lived production HPC systems.", + "laborHours": 60.8, + "name": "Auto-Versioning Systems Image Manager", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NERSC/avs_image_mgr/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/avs_image_mgr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Enables UNIX and Mac OS X command line users to put (individually or batch mode) local ascii files into Google Documents, where the ascii is converted to Google Document format using formatting the user can specify.", + "laborHours": 425.6, + "name": "ascii2gdocs", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/stefanlasiewski/ascii2gdocs/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stefanlasiewski/ascii2gdocs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Atmospheric Radiation Measurement (ARM) Data Integrator (ADI) streamlines the development of scientific algorithms and analysis of time-series NetCDF data, and improves the content and consistency of the output data products produced by these algorithms. The framework automates the process of retrieving and preparing data for analysis, and allows users to design output data products through a graphical interface. It also provides a modular, flexible software development architecture that scientists can use to generate C, Python, and IDL source code templates that embed the pre and post processing logic allowing the scientist to focus on only their science. The input data, preprocessing, and output data specifications of algorithms are defined through a graphical interface and stored in a database. ADI implements workflow for data integration and supports user access to data through a library of software modules. Data preprocess capabilities supported include automated retrieval of data from input files, merging the retrieved data into appropriately sized chunks, and transformation of the data onto a common coordinate system grid. Through the graphical interface, users can view the details of both their data products and those in the ARM catalog and allows developers to use existing data product to build new data products. Views of the output data products include an overlay of how the design meets ARM archive's data standards providing the user with a visual cue indicating where their output violates an archive standard. The ADI libraries access the information provided through the GUI via a Postgres database. The ADI framework and its supporting components can significantly decrease the time and cost of implementing scientific algorithms while improving the ability of scientists to disseminate their results.", + "laborHours": 76.0, + "name": "ARM Data Integrator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ARM-DOE/ADI/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/ADI", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Physical device safety is typically implemented locally using embedded controllers, while operations safety is primarily performed in control centers. Safe operations can be enhanced by correct design of device-level control algorithms, and protocols, procedures and operator training at the control-room level, but all can fail. Moreover, these elements exchange data and issue commands via vulnerable communication layers. In order to secure these gaps and enhance operational safety, we believe monitoring of command sequences must be combined with an awareness of physical device limitations and automata models that capture safety mechanisms. One way of doing this is by leveraging specification-based intrusion detection to monitor for physical constraint violations. The method can also verify that physical infrastructure state is consistent with monitoring information and control commands exchanged between field devices and control centers. This additional security layer enhances protection from both outsider attacks and insider mistakes. We implemented specification-based SCADA command analyzers using physical constraint algorithms directly in the Bro framework and Broccoli APIs for three separate scenarios: a water heater, an automated distribution system, and an over-current protection scheme. To accomplish this, we added low-level analyzers capable of examining control system-specific protocol packets for both Modbus TCP and DNP3, and also higher-level analyzers able to interpret device command and data streams within the context of each device's physical capabilities and present operational state. Thus the software that we are making available includes the Bro/Broccoli scripts for these three scenarios, as well as simulators, written in C, of those scenarios that generate sample traffic that is monitored by the Bro/Broccoli scripts. In addition, we have also implemented systems to directly pull cyber-physical information from the OSIsoft PI historian system. We have included the Python scripts used to perform that monitoring.", + "laborHours": 43487.2, + "name": "HC-NIDS: signatures and simulations for detecting cyber-attacks aiming to cause damage against cyber-physical energy systems", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lbnl-cybersecurity/LBNL_Physics_Based_IDS/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/LBNL_Physics_Based_IDS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "IceNine is a MPI-parallel orientation reconstruction and microstructure analysis code. It's primary purpose is to reconstruct a spatially resolved orientation map given a set of diffraction images from a high energy x-ray diffraction microscopy (HEDM) experiment (1). In particular, IceNine implements the adaptive version of the forward modeling method (2, 3). Part of IceNine is a library used to for conbined analysis of the microstructure with the experimentally measured diffraction signal. The libraries is also designed for tapid prototyping of new reconstruction and analysis algorithms. IceNine is also built with a simulator of diffraction images with an input microstructure.", + "laborHours": 20778.4, + "name": "Adaptive Forward Modeling Method for Analysis and Reconstructions of Orientation Image Map", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/FrankieLi/IceNine/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FrankieLi/IceNine", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Coopr integrates Python packages for defining optimizers, modeling optimization applications, and managing computational experiments. A major driver for Coopr development is the Pyomo package that can be used to define abstract problems, create concrete problem instances, and solve these instances with standard solvers. Other Coopr packages include EXACT, a framework for managing computational experiments, SUCASA, a tool for customizing integer programming solvers, and OPT, a generic optimization interface.", + "laborHours": 314837.6, + "name": "COOPR: A COmmon Optimization Python Repository v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pyomo/pyomo", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "BECCA is a learning and control method based on the function of the human brain. The goal behind its creation is to learn to control robots in unfamiliar environments in a way that is very robust, similar to the way that an infant learns to interact with her environment by trial and error. As of this release, this software contains an application for controlling robot hardware through a socket. The code was created so as to make it extensible to new applications. It is modular, object-oriented code in which the portions of the code that are specific to one robot are easily separable from those portions that are the constant between implementations. BECCA makes very few assumptions about the robot and environment it is learning, and so is applicable to a wide range of learning and control problems.", + "laborHours": 927.2, + "languages": [ + "Python" + ], + "name": "Brain-Emulating Cognition and Control Architecture (BECCA) v. 0.2 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/becca", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2" + }, + { + "contact": { + "email": "westm@osti.gov" + }, + "date": { + "created": "2017-10-31", + "metadataLastUpdated": "2019-08-09" + }, + "description": "Main repo for managing the new DOE CODE site from the DOE Office of Scientific and Technical Information (OSTI).", + "laborHours": 2219.2, + "languages": [], + "name": "DOE CODE", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/doecode/doecode", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-11-08", + "metadataLastUpdated": "2023-08-14" + }, + "description": "bifacial_radiance contains a series of Python wrapper functions to make working with RADIANCE easier, particularly for the PV researcher interested in bifacial PV performance. Users can configure site details such as latitude / longitude, and ground albedo. A bifacial PV system is created with a number of PV modules in rows. The user can specify ground clearance height, row spacing, tilt and azimuth angle, etc. The scene is created, and annual or hourly irradiance profiles are applied to identify the rear irradiance fraction for a given condition.", + "laborHours": 13528.0, + "languages": [ + "Python" + ], + "name": "Bifacial_Radiance [SWR-18-03]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bifacial_radiance", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "billingsjj@ornl.gov" + }, + "date": { + "created": "2017-11-15", + "metadataLastUpdated": "2017-11-15" + }, + "description": "Ice Project Main repo", + "laborHours": 92902.4, + "name": "eclipse/ice", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eclipse/ice", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "billingsjj@ornl.gov" + }, + "date": { + "created": "2017-11-15", + "metadataLastUpdated": "2017-12-19" + }, + "description": "Eclipse advanced visualization project", + "laborHours": 40052.0, + "name": "eclipse/eavp", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eclipse/eavp", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "watsongr@ornl.gov" + }, + "date": { + "created": "2017-11-15", + "metadataLastUpdated": "2020-08-12" + }, + "description": "The PTP project provides an integrated development environment to support the development of parallel applications written in C, C++, and Fortran. This include support for the MPI, OpenMP and UPC programming models, as well as OpenSHMEM and OpenACC, support for a wide range of batch systems and runtime systems, including PBS/Torque, LoadLeveler, GridEngine, Parallel Environment, Open MPI, and MPICH2. A scalable parallel debugger and support for the integration of a wide range of parallel tools is also included.", + "homepageURL": "https://git.eclipse.org/c/ptp/org.eclipse.ptp.git", + "laborHours": 548841.6, + "languages": [], + "name": "Eclipse Parallel Tools Platform", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.eclipse.org/c/ptp/org.eclipse.ptp.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-11-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software is a plugin/installer for existing software. Composer (https://getcomposer.org) is a dependency manager for\nPHP. Installer plugins can be created through Composer's plugin API (https://getcomposer.org/doc/articles/custominstallers.\nmd) allowing certain types of packages to be automatically installed to specific paths. Plugins like this exist for\nseveral different frameworks: https://packagist.org/search/?q=installer&type=composer-plugin\nThis software is a plugin to install Drupal modules (https://www.drupal.org/). Drupal has begun supporting Composer as a means of installing and maintaining modules, but requires specific paths for it's various components. These paths can be\nmanually specified in the \"composer.json\" file, or can be automatically determined with a plugin. Currently an installer\nplugin does not exist for Drupal.", + "laborHours": 273.6, + "languages": [], + "name": "Drupal Installer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/drupal-installer", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-11-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A collection of R packages for statistical computing and analysis", + "laborHours": 7645.6, + "languages": [], + "name": "lhsego/sUtils", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lhsego/sUtils", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-11-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Asset Score Preview API Test Harness is PHP code that will be made publicly accessible to software developers\nsupporting the DOE commercial energy scoring efforts. Asset Score is a DOE funded web-based application that enables cities to interactively describe commercial buildings, identify assets that would affect the energy footprint of the building, and use the Asset Score models (FEDS, Open Studio) to determine the approximate energy score.", + "homepageURL": "https://buildingenergyscore.energy.gov", + "laborHours": 0.0, + "languages": [], + "name": "Asset Score API", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://buildingenergyscore.energy.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-11-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The ISDDD software program simulates a mathematical model, named ISD3 (\"ISDDD\"), developed for describing the time-, concentration- and particle size- dependent dissolution of particles, their delivery to cells, and the delivery and uptake of ions to cells in in vitro liquid test systems. The model is based on a specific formulation of the Population Balance Equation, derived for soluble particles. ISD3 solves for the size and spatial distribution of particle numbers, represented together as a particle number density (that is a function of particle location and diameter). From the number density, all other quantities, such as mass, concentration, size distribution and surface areas are derived. The model can be applied for any initial particle size distribution data by representing the data in terms of the number density. As a result, time dependent solutions can be obtained for all size ranges in a single run of the ISD3 simulation for a given particle type and\nmedia conditions. In the current implementation, particles are treated as spherical in shape and can be modeled as primary particles, agglomerates, or as primary particles coated with proteins. Ions are modeled as a lumped system with a uniform concentration in the liquid media. Particle transport is assumed to occur down the liquid column via diffusion and sedimentation (no fluid convection), and no aggregation/agglomeration, coagulation and break-up of the particles occur during transport. Cellular uptake kinetics of ions and particle dissolution kinetics are currently implemented using empirical models that were developed and calibrated for silver nanoparticles and ions. The ISD3 code is modular, allowing use of the existing equations for the dissolution model and ion uptake, but can be modified to include alternate models developed by the user. Application of ISD3 to another particle system would involve inputting parameters appropriate for the particles and model system. For particle uptake by cells, users have the option to use a no-flux or a perfectly absorbing ‘sticky’ boundary condition. For reactive boundary conditions, the user needs to modify a few lines of the code to express the desired form of the boundary condition (e.g., Robin type of boundary condition).", + "homepageURL": "http://nanodose.pnnl.gov/ModelDownload.aspx", + "laborHours": 0.0, + "languages": [], + "name": "ISDDD", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://nanodose.pnnl.gov/ModelDownload.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2017-12-11", + "metadataLastUpdated": "2018-01-10" + }, + "description": "As supercomputing resources increase, cosmological scientists are able to run more detailed and larger simulations generating massive amounts of data. Analyzing these simulations with an available open-source toolkit is important for collaborative Department of Energy scientific discovery across labs, universities, and other partners. Developed software as a part of this collection include: comparing data with other existing simulations, verifying and validating results with observation databases, new halo finder algorithms, and using analytical tools to get insights into the physics of the\ncosmological universe. The goal of this software project is to provide a set of open-source libraries, tools, and packages for large-scale cosmology that allows scientists to visualize, analyze, and compare large-scale simulation and observational\ndata sets. Developed software will provide a variety of methods for processing, visualization, and analysis of astronomical observation and cosmological simulation data. These tools are intended for deployment on multiple scientific computing\nplatforms, including but not limited to personal computers, cloud computing, experimental sites (telescopes) and high performance supercomputers.", + "laborHours": 101308.0, + "name": "Framework for Analysis and Visualization of Simulation Data (VizAly)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/VizAly", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-12-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "VOLTTRON Application tree (moved from volttron/applications)\nAutomated Identification of Re-tuning Measures", + "laborHours": 109880.8, + "languages": [], + "name": "VOLTTRON/volttron-applications", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron-applications", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-12-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Some of the most pressing machine learning applications such as cyber security and object recognition lack enough ground-truth training data to build a classifier. We solve this problem by using unsupervised deep learning techniques to determine when data were anomalous or deviated from the norm. Traditional methods require either specific context dependent expertise to construct models, or prior examples of events and large amounts of well-labeled data to perform machine learning. Some cutting-edge deep learning approaches have been used to characterize complex events, but these have not been applied to the streaming environment and require a great deal of data. We demonstrated the use of an autoencoder and relevant featurization techniques to both learn a feature space and then identify anomalous portions without the aid of labeled data or domain knowledge. In this way, we demonstrated the detection of anomalous features without domain knowledge or tagged examples, and delivered these features to users.", + "laborHours": 40371.2, + "languages": [], + "name": "pnnl/safekit", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/safekit", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-12-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ModME is a generalization and benchmark framework for the notion of semantic importance. It is primarily used in a stream reasoning context, where hidden information can be extracted out of the data streams.", + "laborHours": 18331.2, + "languages": [], + "name": "ModME", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/modme", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2017-12-13", + "metadataLastUpdated": "2018-05-02" + }, + "description": "CodeVision (formerly MassAV) is a malware analysis workflow system and repository. It began as a simple tool for analyzing a large malware corpus using multiple COTS antivirus engines in parallel. It has since evolved into a unified interface for collecting, storing and analyzing malicious executable code using a variety of COTS and GOTS backends. Not only can CodeVision receive samples from users via its command-line and web interfaces, but it can also operate on continuous network data feeds (e.g., perimeter e-mail attachments, HTTP downloads). The modular analysis framework and simple API give developers the ability to integrate custom and off-the-shelf analysis tools with ease. The system manages scheduling and dependencies, allowing modules to be chained together into analysis-driven workflows. The system is designed as a distributed, load-balanced web service, an architecture that allows it to scale horizontally by adding additional nodes.", + "homepageURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 7676.0, + "name": "Codevision 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-12-19", + "metadataLastUpdated": "2018-01-19" + }, + "description": "ScaLAPACK is a library of high-performance linear algebra routines for parallel distributed memory machines. 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REDUCE performs automated static code analysis and identifies similarities between malware samples in order to support knowledge sharing about related pieces of malware. By integrating with well-established reverse engineering tools, REDUCE speeds up both deep-dive reverse engineering efforts and custom signature generation.", + "homepageURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "name": "REDUCE: Statistically-Guided Reverse Engineering Toolkit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-01-15", + "metadataLastUpdated": "2018-01-16" + }, + "description": "The converter extracts all the required feeder data information from “Opendss format” files also known as “.dss” files to construct the feeder data spreadsheets to be interfaced with the “ePHASORSIM” simulator.", + "laborHours": 8664.0, + "name": "DSS2ePHASOR (\"OpenDSS\" files to \"ePHASORSIM\" interface files converter)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/DSS2ePHASOR/blob/master/README.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DSS2ePHASOR", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2018-01-23", + "metadataLastUpdated": "2019-07-30" + }, + "description": "PIVAuth provides a key based OpenSSH authentication method for use with SmartCards, HSPD-12, PIV, CAC, and similar credentials that support PKCS11. PIVAuth validates the x509 client certificate chain of trust and revocation status on each authenticiation attempt before converting he certificate into a format that Open SSH can make use of. PIVAuth makes use of Bash shell code andi ndustry standard utilities like OpenSSL and OpenLDAP/ It aims to be audit friendly, and easily understood by any Linux administrator.", + "laborHours": 167.2, + "languages": [], + "name": "PIVAuth", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bensallen/pivauth", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jbbrown@lbl.gov" + }, + "date": { + "created": "2018-01-23", + "metadataLastUpdated": "2018-01-24" + }, + "description": "pbdR-enabled HPC-compatible implementation of iRF. Tested on Titan.", + "laborHours": 5122.4, + "name": "Jromero1208/PBDRiRF", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Jromero1208/PBDRiRF", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-01-25", + "metadataLastUpdated": "2018-01-26" + }, + "description": "Swiftbat is a set of Python library routines and command-line utilities that have been developed for the purpose of retrieving, analyzing, and displaying data from NASA's Swift spacecraft, especially the data from the Swift Burst Alert Telescope (BAT).", + "laborHours": 744.8, + "name": "Swiftbat Python Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/swiftbat_python", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-01-26", + "metadataLastUpdated": "2018-01-26" + }, + "description": "We developed a grid reference system-based Unique Building Identifier (UBID). The method converts a building footprint on a map to a unique code. Unlike geographic coordinates (latitude and longitude), which require high precision and can only locate points on the earth, the UBID code records two-dimensional information about a building footprint in a concise and practical manner. The UBID itself is neither a database nor a data schema. Rather, it acts as an external common key between databases to facilitate data mapping. The developed ruleset ensures that individual implementers can reach the same conclusion utilizing publicly available digital maps. It can also automatically resolve discrepancies, caused by physical space or structure changes over time, during data exchange. The method is also flexible and scalable to identify a portion of a building or a group of buildings.", + "laborHours": 440.8, + "name": "Unique Building Identifier Generator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-01-29", + "metadataLastUpdated": "2018-01-29" + }, + "description": "The Fast Equilibration of Ocean Tracers Software (FEOTS) is a set of Fortran modules and programs for post-processing output from LANL's Parallel Ocean Program (POP). However, it is written so that it can be extended for use with other General Circulation Models. Tools are provided for aiding in the diagnosis of sparse matrices that capture advection and diffusion operators that are consistent with General Circulation Model discretizations. FEOTS additionally offers tools to make use of the diagnosed operators to run offline tracer models in forward or equilibration modes.", + "laborHours": 4119.2, + "name": "Fast Equilibration of Ocean Tracers Software", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/FEOTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-01-29", + "metadataLastUpdated": "2018-01-29" + }, + "description": "Software programs Red Pitaya to sweep frequency and records the in phase and quadrature response.", + "laborHours": 1489.6, + "name": "Resonant Ultrasound Spectroscopy Software", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ffb-LANL/resonant-ultrasound", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-01-29", + "metadataLastUpdated": "2018-01-29" + }, + "description": "RuleBuilder is a tool for drawing graphs represented by the BioNetGen rule-based modeling language (BNGL), a domain-specific language used to formulate mathematical models of biochemical interaction networks. This framework provides an intuitive plain-text representation of such networks using a graph-based formalism. The interactions between the model's components are graph-rewriting rules that denote the minimum context needed for the interaction to occur. In some cases the context required for reactions to occur can grow quite large, and the lengthy textual description of the interaction can be difficult to interpret or debug. RuleBuilder is designed to make this process simpler through visualization of individual rule or pattern strings. The software assists in the reading of existing models by converting the BNGL strings of interest into a graph-based representation composed of nodes and edges. RuleBuilder also enables the user to build the visual representation directly from its interface, composing the BNGL string as components and operators are added to the graphical object.", + "laborHours": 1368.0, + "name": "RuleBuilder", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/RuleWorld/RuleBuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "darve@stanford.edu" + }, + "date": { + "created": "2018-01-31", + "metadataLastUpdated": "2018-01-31" + }, + "description": "The regular weighted ensemble method simulation Python code was originally developed by H. Lee, Stanford. The bash \nscript for multiple simultaneous simulations was originally developed by S. Ahn, Stanford. The resampling method \nimplemented in the code is from E. Darve and J. Izaguirre (Chapter 7 in Schlick's \"Innovations in Biomolecular Modeling \nand Simulations.\"). The Concurrent Adaptive Sampling (CAS) algorithm Python code was developed on top of the regular \nweighted ensemble method code by S. Ahn, Stanford. Improvements on the parameter input file had been made by J. \nBirgmeier, Stanford.\n\nThere are two folders provided in this Github repository: **2D_Toy_Model_Code** and **MD_Code**. Each folder provides \nall of the needed code with input files for a particular example, e.g., toymodel1, toymodel2, and penta-alanine. In the \n2D_Toy_Model_Code, **Code_With_Proper_Files** will make a separate folder with many output files for each walker and\n**Code_Without_Proper_Files** will only output minimum number of files like flux.txt, total_weight_on_each_ball.txt, \ntotal_weight.txt, time_record.txt, etc.", + "laborHours": 2523.2, + "name": "CAS_Code", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/shirleyahn/CAS_Code", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "radercd@ornl.gov" + }, + "date": { + "created": "2018-02-01", + "metadataLastUpdated": "2020-09-24" + }, + "description": "Thermochimica is a software library that determines a unique combination of phases and their compositions at thermochemical equilibrium. Thermochimica can be used for stand-alone calculations or it can be directly coupled to other codes. This release of the software does not have a graphical user interface (GUI) and it can be executed from the command line or from an Application Programming Interface (API). Also, it is not intended for thermodynamic model development or for constructing phase diagrams. The main purpose of the software is to be directly coupled with a multi-physics code to provide material properties and boundary conditions for various physical phenomena. Significant research efforts have been dedicated to enhance computational performance through advanced algorithm development, such as improved estimation techniques and non-linear solvers. Various useful parameters can be provided as output from Thermochimica, such as: determination of which phases are stable at equilibrium, the mass of solution species and phases at equilibrium, mole fractions of solution phase constituents, thermochemical activities (which are related to partial pressures for gaseous species), chemical potentials of solution species and phases, and integral Gibbs energy (referenced relative to standard state). The overall goal is to provide an open source computational tool to enhance the predictive capability of multi-physics codes without significantly impeding computational performance.", + "laborHours": 5654.4, + "languages": [], + "name": "Thermochimica", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-CEES/thermochimica", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Capacity Expansion Regional Feasibility (CERF) model", + "laborHours": 2538.4, + "languages": [], + "name": "IMMM-SFA/cerf", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/immm-sfa/cerf", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "junghans@lanl.gov" + }, + "date": { + "created": "2018-02-08", + "metadataLastUpdated": "2020-12-15" + }, + "description": "set of computational science infrastructure tools designed to aid in the implementation of multi-physics application development", + "laborHours": 38668.8, + "languages": [], + "name": "flecsi", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laristra/flecsi", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wehart@sandia.gov" + }, + "date": { + "created": "2018-02-08", + "metadataLastUpdated": "2020-09-01" + }, + "description": "The main repository for the Pyomo optimization modeling software.", + "laborHours": 314837.6, + "languages": [], + "name": "Pyomo", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pyomo/pyomo", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "edwards@jlab.org" + }, + "date": { + "created": "2018-02-08", + "metadataLastUpdated": "2018-02-11" + }, + "description": "The Chroma package supports data-parallel programming constructs for lattice field theory and in particular lattice QCD. It uses the SciDAC QDP++ data-parallel programming (in C++) that presents a single high-level code image to the user, but can generate highly optimized code for many architectural systems including single node workstations, multi and many-core nodes, clusters of nodes via QMP, and classic vector computers.", + "laborHours": 672037.6, + "name": "Chroma", + "organization": "Thomas Jefferson National Accelerator Facility (TJNAF)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JeffersonLab/chroma", + "status": "Production", + "tags": [ + "DOE CODE", + "Thomas Jefferson National Accelerator Facility (TJNAF)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Controls automation module for the hard x-ray split and delay instrument.", + "laborHours": 3161.6, + "name": "Hard X-Ray Split and Delay Automated Controls System", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/HXRSnD/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/HXRSnD", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Common repository for streaming kernel drivers (PGP, AxiStream, ExoTem).", + "laborHours": 5168.0, + "name": "aes-stream-drivers", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + 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"contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "SLAC Ultimate RTL Framework", + "laborHours": 195016.0, + "name": "surf", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/surf/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/surf", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "ZeroRM SQL Composition library", + "laborHours": 1596.0, + "name": "ZeroRM", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/zerorm/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/zerorm", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-02-16", + "metadataLastUpdated": "2018-02-16" + }, + "description": "KIVA-hpFE is a computer software for solving the physics of multi-species turbulent reactive flow in complex geometries having immersed moving parts. The code is written in Fortran 90/95 and can be used on any computer platform with any popular complier. The code is in 2 versions, a serial version and a parallel version utilizing MPICH2 type Message Passing Interface (MPI or Intel MPI) for solving distributed domains.", + "homepageURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/portfolio-software.php", + "laborHours": 0.0, + "name": "KIVA-hpFE version 1.0.1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/portfolio-software.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/portfolio-software.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SDK for controlling the Adaptable Multiple Power Supplies (AMPS boxes)", + "laborHours": 9013.6, + "languages": [], + "name": "AmpsSDK", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/AmpsSDK", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Ion mobility mass spectrometry data viewer and extractor, targeted toward PNNL's UIMF files", + "laborHours": 49065.6, + "languages": [], + "name": "Atreyu", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Atreyu", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Here, we present the implementation of a Bayesian model (BP-Quant) that uses statistically derived peptides signatures to identify peptides that are outside the dominant pattern, or the existence of multiple over-expressed patterns to improve relative protein abundance estimates. It is a research-driven approach that utilizes the objectives of the experiment, defined in the context of a standard statistical hypothesis, to identify a set of peptides exhibiting similar statistical behavior relating to a protein. This approach infers that changes in relative protein abundance can be used as a surrogate for changes in function, without necessarily taking into account the effect of differential post-translational modifications, processing, or splicing in altering protein function. BP-Quant is available as MatLab ® and R packages here.", + "laborHours": 182.4, + "languages": [], + "name": "BP-Quant", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/BP-Quant", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "All the data and materials for the publication about the Blazing Signature Filter", + "laborHours": 516.8, + "languages": [], + "name": "BSF_publication", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/BSF_publication", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "BioPython scripts for conversion of GBK files or DNA-based FASTA files to protein FASTA files", + "laborHours": 121.6, + "languages": [], + "name": "BioPython Scripts", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/BioPython_Scripts", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Library for reading data files acquired on Bruker mass spectrometers.", + "laborHours": 729.6, + "languages": [], + "name": "Bruker Data Reader", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/BrukerDataReader", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Utility for manually and automatically adding datasets to DMS", + "laborHours": 10032.0, + "languages": [], + "name": "Buzzard", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Buzzard", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Allows for reading Agilent Chemstation .D folders using Dot.NET. The ChemstationMSFileReader provides C# or VB.NET access to reading Agilent Chemstation .D dataset folders, for example, from an Agilent single quadrupole GC-MS instrument.", + "laborHours": 942.4, + "languages": [], + "name": "ChemstationMSFileReader", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/ChemstationMSFileReader", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Given a list of proteins, finds all cross-linked peptides in the given Ion Mobility MS dataset. This application attempts to find all cross-linked peptides in the given Ion Mobility MS dataset. First, the FASTA file is read in and possible peptides are generated by digesting the protein(s) and assuming 1 max missed cleavage. The possible peptides are searched for in the given features by matching up the monoisotopic mass of the feature to the mass of the peptides. The mass ppm tolerance is an input parameter of the application. All possible cross-links of the unmodified peptides are then calculated and searched for in the Isotopic Peak data. A detailed csv results file is created at the end.", + "laborHours": 684.0, + "languages": [], + "name": "Crosslinking IMS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/CrossLinkingIMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Exports Sql Server database objects as schema files. Exported objects include tables, views, stored procedures, and functions,plus also database properties including database roles and logins. The program can also export table data to create SQL files with an Insert Into statement for each row.", + "laborHours": 4620.8, + "languages": [], + "name": "DB Schema Export Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DB-Schema-Export-Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PRISM Data Management System database schema. This is a collection of DDL files that define the database schema used by the Data Management System (DMS) component of the Pan-Omics Research Information Storage and Management system (PRISM) at the Pacific Northwest National Laboratory (PNNL). PRISM incorporates a diverse set of analysis tools and allows a wide range of operations to be incorporated, leveraing a state machine that is accessible to independent, distributed computational nodes. The system has scaled well as data volume has increased since 2002, while allowing adaptability for incorporating new and improved data analysis tools for more effective proteomics research.", + "laborHours": 462475.2, + "languages": [], + "name": "DBSchema_DMS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DBSchema_DMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a collection of DDL files that define the database schema used by the Mass and Time Tag System (MTS) component of the Pan-Omics Research Information Storage and Management system (PRISM) at the Pacific Northwest National Laboratory (PNNL). MTS is used to track and quantify peptides and proteins identified in proteomics and related samples.", + "laborHours": 116112.8, + "languages": [], + "name": "DBSchema_MTS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DBSchema_MTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Analysis Tool Manager is a part of PRISM, the Proteomics Research Information and Management System. The analysis manager performs automated processing of available job steps, tracked by the in the DMS_Pipeline database. Plugin DLLs implement the processing details for each analysis tool.", + "laborHours": 188297.6, + "languages": [], + "name": "DMS Analysis Tool Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Analysis-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Capture Task Manager is a part of PRISM, the Proteomics Research Information and Management System. The capture manager processes instrument data files, copying them from the instrument to storage servers, validating the data, creating QC graphics, and pushing the data into MyEMSL. Plugin DLLs implement the processing details for each tool.", + "laborHours": 110990.4, + "languages": [], + "name": "DMS Capture Task Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Capture-Task-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Email Manager obtains data from a SQL Server database using queries defined in a settings file, e-mailing the results of the queries to one or more people. Reports can be e-mailed daily or only on certain days. It also supports calling a stored procedure or querying WMI.", + "laborHours": 2143.2, + "languages": [], + "name": "DMS EMail Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-EMail-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This program examines the source folder on instrument computers to find files and folders. It creates a tab-delimited text file for each instrument, listing the names of the files and folders found. The text files for the instruments are stored in a central location, and are made made visible via the DMS website to allow instrument operators to see the instrument data files on the instrument computer.", + "laborHours": 760.0, + "languages": [], + "name": "DMS Instrument Directory Scanner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Instrument-Directory-Scanner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Organism Database (FASTA file) programs, including PRISMSeq Uploader and the FastaFileMaker console application. This repository includes several software utilities for working with Protein Collections stored in PRISM, the Proteomics Research Information and Management System.", + "laborHours": 10883.2, + "languages": [], + "name": "DMS Organism Database Handler", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Organism-Database-Handler", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Program Runner (MultiProgRunner) is a Windows Service that can be configured to start specific programs on a regular interval. In the Proteomics Research Information and Management System (PRISM) the DMS Program runner Service is used to run manager programs at regular intervals.", + "laborHours": 957.6, + "languages": [], + "name": "DMS Program Runner Service", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Program-Runner-Service", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Space Manager is a part of PRISM, the Proteomics Research Information and Management System. The space manager monitors the free space on Proto-x storage servers, purging old dataset files to free up space if the available space drops below a threshold.", + "laborHours": 1656.8, + "languages": [], + "name": "DMS Space Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Space-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Update Manager is used to keep automated processing manager software up-to-date. Although it is part of PRISM (the Proteomics Research Information and Management System), it is a standalone program and does not contact any databases. The program compares the files on a central distribution share to files on the local computer, updating any files that are out of date. It supports rolling back local files to an older version and auto-deleting extra files.", + "laborHours": 2006.4, + "languages": [], + "name": "DMS Update Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Update-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PNNL Data Management System (DMS) is composed of a SQL Server backend and website front end to allow PNNL staff to track biomaterial, samples, instrument data, and result files from automated software analyses. This repository tracks the files behind the DMS website.", + "laborHours": 108132.8, + "languages": [], + "name": "DMS Website", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Website", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Data Import Manager is a part of PRISM, the Proteomics Research Information and Management System. The Data Import Manager monitors a central folder for new dataset trigger files, which are XML files that specify metadata for new datasets to import into the Data Management System (DMS). The Data Import Manager validates the metadata in the XML trigger file, notifying the instrument operator by e-mail if invalid metadata is encountered. After processing each XML trigger file, the file is moved into either a success or failure folder.", + "laborHours": 1641.6, + "languages": [], + "name": "Data Import Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Data-Import-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Data Package Archive Manager is a part of PRISM, the Proteomics Research Information and Management System. The software scans data package folders and files, pushing new or changed files into MyEMSL.", + "laborHours": 760.0, + "languages": [], + "name": "Data Package Archive Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DataPackage-Archive-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DeconEngine includes routines for deconvoluting (deisotoping) observed isotopic signatures in mass spectrometry data to detect features.", + "laborHours": 91017.6, + "languages": [], + "name": "DeconEngineV2", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DeconEngineV2", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "DeconMSn converts mass spectrometry instrument data to text files, including determining the charge state for each parent ion.", + "laborHours": 74692.8, + "languages": [], + "name": "DeconMSn", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DeconMSn", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "DeconTools is a software package used for detecting features in MS data by using the isotopic signatures of expected components. The tool uses different algorithms for different parts of the deconvolution process: noise reduction, peak detection, prediction of theoretical isotopic envelope and scoring functions that quantitate the quality of signature observed in the data.", + "laborHours": 306447.2, + "languages": [], + "name": "DeconTools", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DeconTools", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The FASTA File Splitter program can be used to split apart a protein FASTA file into a number of sections. Although the splitting is random, each section will have a nearly identical number of residues.", + "laborHours": 440.8, + "languages": [], + "name": "Fasta File Splitter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Fasta-File-Splitter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Reads a protein FASTA file and filters the proteins by either organism name or protein name to create a new, filtered file.", + "laborHours": 501.6, + "languages": [], + "name": "Fasta Organism Filter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Fasta-Organism-Filter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The file Comparison Sampler console application compares two or more files (typically in separate folders) to check whether the start of the files match, the end of the files match, and selected sections inside the files also match. It is useful for comparing large files without reading the entire file. Alternatively, you can provide two folder paths and the program will compare all of the files in the first folder to the identically named files in the second folder.", + "laborHours": 532.0, + "languages": [], + "name": "File Comparison Sampler", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/File-Comparison-Sampler", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This program sorts a text file alphabetically (forward or reverse). It supports both in-memory sorts for smaller files and use of temporary swap files for large files. It can alternatively sort on a column in a tab-delimited or comma-separated file. The column sort mode also supports numeric sorting.", + "laborHours": 1763.2, + "languages": [], + "name": "Flexible File Sort Utility", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/FlexibleFileSortUtility", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "GlyQ-IQ is a program that performs a targeted, chromatographic centric search of mass spectral data for glycans. It is designed for high resolution LC-MS datasets. The software uses a list of glycan targets to search for expected features in MS1 spectra. Features are characterized by monoisotopic mass, elution time, and isotopic fit score. Features are annotated by glycan family relationships and optionally by in-source fragmentation patterns.", + "laborHours": 321601.6, + "languages": [], + "name": "GlyQ-IQ", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/GlyQ-IQ", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This program processes IMS data in a UIMF file to align all frames to a base frame, adjusting the observed drift times of each frame to align with the base frame.", + "laborHours": 775.2, + "languages": [], + "name": "IMS Drift Time Aligner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/IMS-Drift-Time-Aligner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ImsInformed is a .NET class library that provides target identification workflows for peptides and metabolites alike in IMS experiment runs.", + "laborHours": 127345.6, + "languages": [], + "name": "ImsInformed Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/IMS-Informed-Library", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/IMS-Informed-Library", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "InfernoRDN can perform various downstream analyses on large scale datasets from proteomics and microarrays.", + "laborHours": 63353.6, + "languages": [], + "name": "InfernoRDN", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/InfernoRDN", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Informed Proteomics project includes algorithms for proteomic mass spectrometry data analysis. Although the back-end data access and some of the scoring routines are general purpose, this repository is currently maintained for top down MS/MS datasets.", + "laborHours": 335874.4, + "languages": [], + "name": "Informed Proteomics", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Informed-Proteomics", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The LC-IMS-MS Feature Finder finds LC-IMS-MS features and conformers using deisotoped features from DeconTools. ", + "laborHours": 2021.6, + "languages": [], + "name": "LC-IMS-MS Feature Finder", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LC-IMS-MS-Feature-Finder", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "LCMS raw data and MSGF+ results viewer. LcmsSpectator is a standalone Windows graphical user interface tool for viewing LC-MS data and identifications.", + "laborHours": 114304.0, + "languages": [], + "name": "LCMS-Spectator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/LCMS-Spectator/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LCMS-Spectator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "LIQUID is a software tool for identifying lipids in LC-MS/MS-based lipidomics data. It is described in publication LIQUID: an-open source software for identifying lipids in LC-MS/MS-based lipidomics data (doi: 10.1093/bioinformatics/btx046). LIQUID provides users with the capability to process high throughput data and contains a customizable target library and scoring model per project needs. The graphical user interface provides visualization of multiple lines of spectral evidence for each lipid identification, allowing rapid examination of data for making confident identifications of lipid molecular species.", + "laborHours": 76015.2, + "languages": [], + "name": "LIQUID", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LIQUID", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python scripts of SVM model training and testing used in a publication entitled 'A generalizable method for false-discovery rate estimation in mass spectrometry-based lipidomics'.", + "laborHours": 121.6, + "languages": [], + "name": "LipidFDR", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LipidFDR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Utility to show the shared folders on the local computer, or on a remote computer", + "laborHours": 212.8, + "languages": [], + "name": "ListWindowsShares", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/List-Windows-Shares", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A VB.NET DLL that can read mass spectrometry data from four file formats: mzXML, mzData, concatenated .dta files (_dta.txt), and Mascot Generic Format files (.mgf)", + "laborHours": 4225.6, + "languages": [], + "name": "MsDataFileReader", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MS-Data-File-Reader", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The MS File Info Scanner can be used to scan a series of MS data files (or data folders) and extract the acquisition start and end times, number of spectra, and the total size of the data. In addition, it can create 2D-plot graphics of the m/z values vs. time for QA purposes.", + "laborHours": 47348.0, + "languages": [], + "name": "MS File Info Scanner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MS-File-Info-Scanner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "DataProcessing toolbox for running MSGF+ and MASIC, then merging the results. Uses Windows batch files to automate the process for a folder of Thermo .Raw files", + "laborHours": 4575.2, + "languages": [], + "name": "MSGFPlus_MASIC_Toolbox", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MSGFPlus_MASIC_Toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Used to generate an Accurate Mass and Time tag database from local MS/MS search engine results (from SEQUEST, X!Tandem, or MSGF+)", + "laborHours": 36571.2, + "languages": [], + "name": "MTDB-Creator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MTDB-Creator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Mage suite of tools provide access to DMS files and metadata.", + "laborHours": 25262.4, + "languages": [], + "name": "Mage", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Mage", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a the code and data for a website created to display collision cross section data for metabolites and small molecules. This repository hosts two things. First is the source code (js) for a website created to display collision cross section data for metabolites and other small molecules. The second is the underlying CCS dataset. The growing interest in metabolomic and exposomic studies is also inciting a need for new techniques to analyze these diverse molecules. Mass spectrometry-based studies are often preferred for the confident identification of small molecules. Ion mobility spectrometry (IMS) is capable of separating molecules that have the same m/z but different conformational arrangements, which is very useful in metabolomic and exposomic analyses. As the desire for IMS measurements of metabolites continues to grow, so does the need for high quality collision cross section (CCS) values.", + "laborHours": 57425.6, + "languages": [], + "name": "Metabolomics Collision Cross Section Database and Server", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MetabolomicsCCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This program can calculate the molecular weight and percent composition of chemical formulas and amino acids, providing a graphical user interface to edit the formulas and parsing options. It recognizes user-definable abbreviations, custom elemental isotopes, and can display up to 20 compounds simultaneously. It also includes a Mole/Mass Converter, Formula Finder, Capillary Flow Modeller, Amino Acid Notation Converter, Peptide Sequence Fragmentation Modeler, Isotopic Distribution Calculator, and built-in calculator. Full program documentation is available by pressing F1 during program operation.", + "laborHours": 30962.4, + "languages": [], + "name": "Molecular Weight Calculator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Molecular-Weight-Calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MwtWinDLL contains utility functions for calculating the molecular weight and percent composition of chemical formulas and amino acids. It recognizes user-definable abbreviations and custom elemental isotopes. It also includes a Mole/Mass Converter, Formula Finder, Capillary Flow Modeller, Amino Acid Notation Converter, Isotopic Distribution Calculator, and Peptide Sequence Fragmentation Modeller. To use, simply include the DLL in a .NET project.", + "laborHours": 6596.8, + "languages": [], + "name": "Molecular Weight Calculator Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Molecular-Weight-Calculator-DLL", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Aligns multiple LC-MS datasets to one another after which LC-MS features can be matched to a database of peptides (typically an AMT tag database)", + "laborHours": 132179.2, + "languages": [], + "name": "MultiAlign", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MultiAlign", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Finds 3D XIC features across LC, m/z, and drift time dimensions", + "laborHours": 5472.0, + "languages": [], + "name": "Multidimensional Peak Finding", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Multidimensional-Peak-Finding", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MTS manager for retrieving files from MyEMSL; The MyEMSL MTS File Cache Manager is a part of PRISM, the Proteomics Research Information and Management System. The software processes the MyEMSL Download Queue in the Mass and Time Tag System (MTS) to download files required for processing.", + "laborHours": 456.0, + "languages": [], + "name": "MyEMSL MTS File Cache Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MyEMSL-MTS-File-Cache-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The MyEMSL Reader is a library used by manager programs in PRISM, the Proteomics Research Information and Management System. The library allows the managers to push files into MyEMSL and later search for and retrieve the files.", + "laborHours": 3024.8, + "languages": [], + "name": "MyEMSL Reader", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MyEMSL-Reader", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Converts an mzIdentML created by MS-GF+ to a tab-delimited text file.", + "laborHours": 334.4, + "languages": [], + "name": "MzidToTsvConverter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Mzid-To-Tsv-Converter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The OBO Data Converter reads an Ontology file in the OBO format and converts the data to a tab-delimited text file.", + "laborHours": 395.2, + "languages": [], + "name": "OBO-Data-Converter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/OBO-Data-Converter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The OxyDataPlotter library includes a WinForms control with a customizable instance of OxyPlot.", + "laborHours": 8284.0, + "languages": [], + "name": "OxyDataPlotter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/OxyDataPlotter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Peptide Hit Results Processor (PHRP) can be used to convert an X!Tandem results file (XML format), MSGF+ .tsv search result file, Sequest Synopsis/First Hits file, or Inspect search result into a series of tab-delimited text files summarizing the results. It will insert modification symbols into the peptide sequences for modified peptides. Parallel files are created containing sequence information, modification details, and protein information. The user can optionally provide a modification definition file that specifies the symbol to use for each modification mass.", + "laborHours": 514444.0, + "languages": [], + "name": "Peptide Hit Results Processor", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PHRP", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PNNL Biodiversity Plugin is a software tool for Skyline and is designed to allow pathway-centric browsing of peptides previously identified by LC-MS/MS. The plugin is designed to assist in SRM assay design or DIA data analysis. Users select an organism and biological pathway of interest, then the plugin shows information about the associated peptides.", + "laborHours": 282218.4, + "languages": [], + "name": "PNNL Biodiversity Library Plugin", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PNNL-Biodiversity-Library-Plugin", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PNNL Omics Library (PNNLOmics.dll) is a collection of data analysis, file I/O, and visualization routines used by several of the omics-related software developed at PNNL.", + "laborHours": 19516.8, + "languages": [], + "name": "PNNL OMICS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PNNL-Omics", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PRISM Class Library (PRISM.dll) is a collection of routines used by many of the software tools that support the Proteomics Research Information and Management System (PRISM) at PNNL. Although written for use by PRISM tools, the methods in the PRISM class library are general utility methods, and are not dependent on any PNNL resources.", + "laborHours": 15549.6, + "languages": [], + "name": "PRISM Class Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PRISM-Class-Library", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "C# reader/writer for mzIdentML files (.mzID). Also supports reading mzML files.", + "laborHours": 29609.6, + "languages": [], + "name": "PSI_Interface", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PSI-Interface", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PepAligner program can read a file containing peptides and align them to a file of protein sequences (.Fasta or delimited text) using Smith-Waterman alignment.", + "laborHours": 1550.4, + "languages": [], + "name": "PepAligner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PepAligner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Peptide Fragmentation Modeller is a command-line utility reads that reads in a text file of peptide sequences and generates the theoretical fragmentation pattern for each, outputting the results in a single concatenated DTA file, or in separate .Dta files. The ion intensity values are not predicted values; instead, b, c, y, and z ions are assigned an intensity of 100; while a ions and neutral loss ions receive an intensity of 20.", + "laborHours": 1717.6, + "languages": [], + "name": "Peptide Fragmentation Modeller", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Peptide-Fragmentation-Modeller", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PeptideListToXML application reads a tab-delimited text file created by the Peptide Hit Results Processor (PHRP) and creates a PepXML with the appropriate information. The various _SeqInfo files created by PHRP must be present in the same folder as the text file. If the MASIC Scan Stats file is also present, then elution time information will be extracted and included in the PepXML file. You should ideally also include the name of the parameter file used for the MS/MS search engine.", + "laborHours": 4104.0, + "languages": [], + "name": "PeptideListToXML", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PeptideListToXML", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Population Variation plug-in for the Skyline software program that can assist researchers in determining whether their target peptides have known mutations in the general human population.", + "laborHours": 5304.8, + "languages": [], + "name": "Population Variation Plug-In", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PopulationVariationPlugin", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Protein Digestion Simulator is a utility for processing FASTA files including converting to/from tab delimited text. It also supports FASTA file validation.", + "laborHours": 7296.0, + "languages": [], + "name": "Protein Digestion Simulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Protein-Digestion-Simulator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The ProteowizardWrapper is a series of C# classes that can be used to interface with the ProteoWizard libraries.", + "laborHours": 44277.6, + "languages": [], + "name": "ProteowizardWrapper", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Proteowizard-Wrapper", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SMAQC computes quality metrics for a LC-MS/MS dataset. The quality metrics are based on the metrics proposed by Rudnick and Stein, as described in \"Performance metrics for liquid chromatography-tandem mass spectrometry systems in proteomics analyses.\", Mol Cell Proteomics. 2010 Feb;9(2):225-41. SMAQC requires that the dataset first be processed with MASIC, then processed with MSGF+ or X!Tandem. The MSGF+ or X!Tandem results must be post-processed with the PeptideHitResultsProcessor (PHRP).", + "laborHours": 5548.0, + "languages": [], + "name": "SMAQC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/SMAQC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "CodeIgniter based website for browsing QC Metrics stored in DMS", + "laborHours": 51725.6, + "languages": [], + "name": "SMAQC_Website", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/SMAQC_Website", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SIPPER can be used to automatically detect and quantify partially labeled C13 peptides in a single dataset. It includes a GUI for manual visualization and annotation of detected LC-MS features. It also includes a Simple MS Viewer for exploring mass spectral data. Supports Thermo .Raw files, plus also mzXML, mzML, and mz5.", + "laborHours": 22906.4, + "languages": [], + "name": "Sipper", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Sipper", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SpectrumLook can be used to visually inspect the peptide sequence matches (PSMs) against fragmentation spectra in an LC-MS/MS dataset.", + "laborHours": 11430.4, + "languages": [], + "name": "SpectrumLook", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/SpectrumLook", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Thermo Raw File Reader is a .NET DLL wrapper for Thermo's MS File Reader, which is accessible by creating an account at https://thermo.flexnetoperations.com/control/thmo/login then logging in and choosing \"Utility Software\". 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We utilized a Lasso logistic regression classifier (LLRC) which simultaneously restricts the size of model coefficients and the number of quality metrics included the model. Importantly the model does not treat false-negatives and false-positives as equally deleterious events.", + "laborHours": 364.8, + "languages": [], + "name": "glmnetGLR", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/glmnetGLR/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/glmnetGLR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a simple C# console program to validate and update the data from MetabolomicsCCS", + "laborHours": 988.0, + "languages": [], + "name": "MetaboliteValidation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/metaboliteValidation", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Protein Coverage Summarizer can be used to determine the percent of the residues in each protein sequence that have been identified, based on a list of identified peptides. A graphical user interface (GUI) is provided to allow the user to select the input files, set the options, and browse the coverage results.", + "laborHours": 7569.6, + "languages": [], + "name": "Protein Coverage Summarizer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/protein-coverage-summarizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The RMD_RUNS function will log10 transform peptide peak intensity, that is, peptide abundance data and determine if any LC-MS analyses (ie,runs) in a N x P peptide data set are statistical outliers. 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Generic instructions for compiling the source code is shown below as a UNIX/Linux command line, with f90 representing the user's Fortran 90 compiler.", + "laborHours": 73735.2, + "languages": [], + "name": "STOMP-W", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/STOMP-W", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ThermalTracker tracks birds and bats in thermal video. It will process video in any standard format that was recorded with a thermal video camera. The output is images of the flight tracks of birds and bats in PNG format, and a comma-separated value (CSV) file listing the details of the extracted flight tracks.", + "laborHours": 2796.8, + "languages": [], + "name": "ThermalTracker", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/ThermalTracker/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ThermalTracker", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This repository contains sample code written in PHP that allows you to access the Asset Score API. The Department of Energy Building Energy Asset Score (Asset Score) is a national standardized tool for evaluating the physical and structural energy efficiency of commercial and multifamily residential buildings. The scoring tool will store user-provided data and generate an asset score and system evaluation for your building envelope and mechanical and electrical systems. The tool will also identify cost-effective upgrade opportunities and help you gain insight into the energy efficiency potential of your building.", + "laborHours": 2705.6, + "languages": [], + "name": "asset-score-api-test-harness", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/asset-score-api-test-harness/blob/master/Readme.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/asset-score-api-test-harness", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Trade-offs between microbiome diversity and productivity in a stratified microbial mat", + "laborHours": 456.0, + "languages": [], + "name": "bernstein-2016-productivity-and-diversity", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/bernstein-2016-productivity-and-diversity/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/bernstein-2016-productivity-and-diversity", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Primary and heterotrophic productivity relate to multi-kingdom diversity in a hypersaline mat", + "laborHours": 1292.0, + "languages": [], + "name": "bernstein-2017-productivity-and-diversity-2", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/bernstein-2017-productivity-and-diversity-2", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "BuildingSync® is a common schema for energy audit data that can be utilized by different software and databases involved in the energy audit process. It allows data to be more easily aggregated, compared and exchanged between different databases and software tools. This streamlines the energy audit process, improving the value of the data and facilitating achievement of greater energy efficiency.", + "laborHours": 134793.6, + "languages": [], + "name": "BuildingSync", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/BuildingSync/schema/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BuildingSync/schema", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This repository contains the tutorial and package reference for the Smisc package.", + "laborHours": 4043.2, + "languages": [], + "name": "docs-Smisc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/docs-Smisc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This repository contains the tutorial and package reference for the rsed package.", + "laborHours": 1200.8, + "languages": [], + "name": "docs-rsed", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/docs-rsed", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "eSTOMP-WR (exascale Subsurface Transport Over Multiple Phases) is a highly scalable (parallel), general-purpose tool for simulating subsurface flow and reactive transport in variably saturated geologic media. 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FQC is designed to better group FastQC result data across groups where each group is comprised of FASTQs related to an experiment or sequencing batch. 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This project 'bernstein-2017-founders-species', explores community succession using a lake biofilm as a model. The code here was used to process and analyze environmental metadata and genetic sequencing data. Statistical tests and data visualization are included.\nThis code makes use of commodity software that is freely available and commonly used in this field. No new methods or techniques are introduced in this code.", + "laborHours": 167.2, + "languages": [], + "name": "jansson_snijders_collaborative_cross", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/jansson_snijders_collaborative_cross/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/jansson_snijders_collaborative_cross", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The JAT (Just Add Tests) Box is a preconfigured Behat Vagrant virtual machine.", + "laborHours": 152.0, + "languages": [], + "name": "JAT-Box", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/jatbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This code can be used to generate a damage map based on the presence of rubble. Rubble is often detectable in images with submeter resolution, and can indicate damage to structures from high winds or earthquakes. The process_images.py script outputs a mask indicating the pixels in the original image where rubble was detected. The mask can be used in a geospatial software application like ArcMap to generate a damage map based on the rubble density. The rubble detection mask will contain some false positives which are usually more isolated than true rubble, so a density map will provide a more accurate indication of affected areas than the indivdidual rubble detections will.", + "laborHours": 91.2, + "languages": [], + "name": "rubblepy", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/rubblepy/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/rubblepy", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This provides several Fortran for consistent handling of time series data. These are used by PNNL's MASS1 and MASS2 codes.", + "laborHours": 2994.4, + "languages": [], + "name": "Time Series Fortran 90 Modules", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/time_series/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/time_series", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Uncertainty quantification code from PNNL", + "laborHours": 5882.4, + "languages": [], + "name": "uq", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/uq", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "nijhuis2@llnl.gov" + }, + "date": { + "created": "2018-02-23", + "metadataLastUpdated": "2018-07-19" + }, + "description": "A sequence-based annotation pipeline for phage", + "laborHours": 3830.4, + "languages": [], + "name": "PhATE (Phage Annotation Tool and Evaluator)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/phate", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An API library that allows communication with oVirt using the Go language.", + "laborHours": 1033.6, + "languages": [], + "name": "Go oVirt API", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/ovirtapi", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This code creates a new \"provider\" plugin to the terraform utility that allows it control virtual machines running in oVirt.", + "laborHours": 228.0, + "languages": [], + "name": "Terraform oVirt Provider", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/terraform-provider-ovirt", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-03-01", + "metadataLastUpdated": "2024-09-17" + }, + "description": "BioCompoundML is a software tool for rapidly screening chemicals by chemical properties, using machine learning.", + "laborHours": 8876.8, + "languages": [ + "Python" + ], + "name": "sandialabs/BioCompoundML", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/BioCompoundML", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "daibane@sandia.gov" + }, + "date": { + "created": "2018-03-01", + "metadataLastUpdated": "2020-09-01" + }, + "description": "Omega_h is a C++11 library that implements tetrahedron and triangle mesh adaptativity, with a focus on scalable HPC performance using (optionally) MPI, OpenMP, or CUDA. It is intended to provided adaptive functionality to existing simulation codes. Mesh adaptivity allows one to minimize both discretization error and number of degrees of freedom live during the simulation, as well as enabling moving object and evolving geometry simulations. Omega_h will do this for you in a way that is fast, memory-efficient, and portable across many different architectures, including NVIDIA GPUs.", + "laborHours": 35826.4, + "languages": [], + "name": "Omega_h", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SNLComputation/omega_h", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "barno1@llnl.gov" + }, + "date": { + "created": "2018-03-06", + "metadataLastUpdated": "2018-03-06" + }, + "description": "Tool for calibrating 1D coda seismic models", + "laborHours": 47712.8, + "name": "LLNL/coda-calibration-tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/coda-calibration-tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-06", + "metadataLastUpdated": "2020-03-03" + }, + "description": "The purpose of this code is to enable collaborative research in simulation of large deformation structural mechanics.\n\nParticularly, it will be used to investigate abstract physics coupling methods and algorithms for implicit solves on emerging computing hardware.", + "laborHours": 24836.8, + "languages": [], + "name": "SERAC", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/serac", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-03-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Executables for working with EnergyPlus Input Files (IDF) This project aims to provide a suite of executables for working with EnergyPlus Input Files (IDF). The project is developed using the Haskell programming language (c.f., https://www.haskell.org/).\nThe current release (version 0.1.0.0) includes a utility that \"pretty prints\" the input file (i.e., that decodes and then, immediately, re-encodes and displays the input file, viz., that sanitizes the input) and a utility that converts the input file into\na labeled graph in the DOT language (c.f., https://www.graphviz.org/doc/info/lang.html) for subsequent rendering using\nGraphviz Visualization Software (c.f., https://www.graphviz.org/).\n\nAn example workflow is to pipe the input file into the pretty printer, to pipe the result into the labeled graph converter, and then to pipe the result into Graphviz, yielding an image file that depicts the hierarchical and referential relationships between EnergyPlus Data Dictionary (IDD) classes that are detected within the input file.", + "laborHours": 152.0, + "languages": [], + "name": "pnnl/Haskell-IDF-Executable", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Haskell-IDF-Executable", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-03-06", + "metadataLastUpdated": "2018-03-15" + }, + "description": "Resonance Inspection encompasses a suite of techniques for the purpose of materials characterization and nondestructive evaluation. These techniques utilize the mechanical resonances of the sample(s) to determine and monitor material properties (e.g., elastic moduli, phase changes), sort mechanically defective parts, determine the presence/level of mechanical damage (micro-cracking, delaminations, disbonding, etc.) and monitor mass/density fluctuations to name a few applications. The Resonance Inspection Techniques & Analyses (RITA) system has been developed to facilitate these and other applications in a user friendly and cost effective package.", + "homepageURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "name": "Resonance Inspection Techniques & Analysis (RITA)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-07", + "metadataLastUpdated": "2018-03-20" + }, + "description": "ConveyorLC is a high throughput virtual screening pipeline for in-silico screening of virtual compound databases using high performance computing. The pipeline mainly includes four modules: receptor/target preparation, ligand preparation, VinaLC docking calculation, and molecular mechanics/generalized Born surface area rescoring.", + "laborHours": 68932.0, + "name": "Conveyor LC", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/XiaohuaZhangLLNL/conveyorlc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-03-15", + "metadataLastUpdated": "2018-03-15" + }, + "description": "XMOF2D is a library implementing the X-MOF (eXtended Moments of Fluid) interface reconstruction method on unstructured polygonal meshes with convex cells. Given a computational mesh with multi-material cells, for which volume fractions and centroids of contained materials are provided, piecewise linear material interfaces are constructed inside such cells using the Moment-of-Fluid (MOF) method. Additionally, a hierarchical mesh is created, where every multi-material cell of the computational mesh contains a local mesh with fully established local topology, as well as the parentage information to relate mesh entities from the local and the computational \nmeshes.", + "laborHours": 2082.4, + "name": "XMOF2D", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laristra/XMOF2D", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-03-15", + "metadataLastUpdated": "2018-03-15" + }, + "description": "PetaVision is an open source, object oriented neural simulation toolbox optimized for high-performance multi-core, multi-node computer architectures. PetaVision is intended for computational neuroscientists who seek to apply neuromorphic models to hard signal processing problems; both to improve on the performance of existing algorithms and/or to gain insight into the computational mechanisms underlying biological neural processing. \n\nPlease note that this assertion and ESTSC deposit are only for the portions of PetaVision which have been funded and written by LANL developers.", + "laborHours": 69342.4, + "name": "PetaVision version 2.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PetaVision/OpenPV", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-03-16", + "metadataLastUpdated": "2018-03-16" + }, + "description": "Plugin API for the LANL Mama (Morphological Analysis of Materials) application.", + "laborHours": 136.8, + "name": "MAMA Plugin API", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/mama-plugin-api", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-20", + "metadataLastUpdated": "2018-03-21" + }, + "description": "AMPE is a phase-field code. It evolves in time the Allen-Cahn equations associated with a phase­field model, coupled with the time-evolution of a composition field (in an alloy) and a temperature field which are described by diffusion equations. It can also solve the elasticity equations assuming mechanical equilibrium at every time-step. Grain orientations are described by normalized quaternions which also evolve in time according to Allen-Cahn type equations. ", + "laborHours": 58976.0, + "name": "AMPE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AMPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-20", + "metadataLastUpdated": "2018-03-20" + }, + "description": "VinaLC is based on a very popular PC-based molecular docking program, AutoDock Vina. The original Vina docking program was modified and parallelized, using an MPI and multithreading hybrid scheme, and potentially can be used in the future on exascale machines, without sacrificing accuracy.", + "laborHours": 4727.2, + "name": "VinaLC: Parallel Molecular Docking Program", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/XiaohuaZhangLLNL/VinaLC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2018-03-21", + "metadataLastUpdated": "2018-03-21" + }, + "description": "Image processing tools for computed tomography. This is an non-functioning, incomplete, and abandoned project.", + "laborHours": 3891.2, + "name": "pyRafters", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BrookhavenNationalLaboratory/pyRafters", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-03-26", + "metadataLastUpdated": "2019-04-17" + }, + "description": "Simsee is a program for generating artificial seeing data for simulations of astronomical surveys. It includes a jupyter notebook for deriving model parameters from Dual Image Motion Monitor (DIMM) data, and a program that reads these model parameters and creates a data file suitable for use by survey strategy simulation code (which is outside the scope of this package). It is specifically designed to provide input data for LSST’s opsim4 survey simulator, but may be adapted for use with different simulators as well. The code is verified to work on a Linux workstation with an Intel Xeon E5-6980 CPU and 256GB or memory, but should work fine on systems with far more limited resources.", + "laborHours": 12479.2, + "languages": [], + "name": "simsee", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LSSTDESC/ObsStrat", + "status": "Production", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-03-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The goal of Computational Simulation of Online Social Behavior (SocialSim) is to develop innovative technologies for highfidelity computational simulation of online social behavior. SocialSim will focus specifically on information spread and evolution. Current computational approaches to social and behavioral simulation are limited in this regard. Top-down simulation approaches focus on the dynamics of a population as a whole, and model behavioral phenomena by assuming uniform or mostly-uniform behavior across that population. Such methods can easily scale to simulate massive populations, but can be inaccurate if there are specific, distinct variations in the characteristics of the population. In contrast, bottom-up simulation approaches treat population dynamics as an emergent property of the activities and interactions taking place within a diverse population. While such approaches can enable more accurate simulation of information spread, they do not readily scale to represent large populations. SocialSim aims to develop novel approaches to address these challenges.", + "laborHours": 8086.4, + "languages": [], + "name": "pnnl/socialsim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/socialsim", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-28", + "metadataLastUpdated": "2018-03-28" + }, + "description": "The program is a set of python scripts which extends the open source\nprogram Caffc lo allow it to learn to train a neuml network using self -supervised training. 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In addition to these standard methods, an option to use FE for flow is available, as well as a simple Finite Difference scheme.", + "laborHours": 1601304.8, + "name": "FEHM V3.0 - V3.X", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/FEHM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jodi@ecolibrium3.org" + }, + "date": { + "created": "2018-03-30", + "metadataLastUpdated": "2018-05-15" + }, + "description": "The Duluth Shines! application is an online solar map developed in partnership with the University of Minnesota-Duluth to allow the public to compute solar resources available on the rooftops of properties within the Duluth City Limits. The map links to a Minnesota DNR solar cost calculator.", + "homepageURL": "http://umd-cla-gis04.d.umn.edu/duluthshines", + "laborHours": 1945.6, + "languages": [], + "name": "Duluth Shines! Solar Map Application", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://solar.maps.umn.edu/products.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://umd-cla-gis04.d.umn.edu/duluthshines", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Scalable High-performance Algorithms and Data-structures.\nScalable High-performance Algorithms and Data-structures (SHAD) is an application programming interface based on a generic software library. It has a modular design that enables reuse of modules. 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It is designed to accommodate significant amount of data which can be accessed in massively parallel environments, and used as building blocks for SHAD extensions, i.e. higher level software libraries.", + "laborHours": 13573.6, + "languages": [], + "name": "pnnl/SHAD", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SHAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL Cost-Performance Tool (DOE-OE sponsored) for Estimation of Capital Costs for Redox Flow Batteries. Battelle IPID 30401. 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The supply chain from the liquefaction plant to the station can be modeled using real gas equations of state from REFPROP and heat transfer models. ", + "laborHours": 532.0, + "name": "LH2 Transfer Simulation ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/NASA-1.3", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LH2Transfer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-04-10", + "metadataLastUpdated": "2018-04-11" + }, + "description": "PyFEHM is an open-source Python library that provides classes and methods to support a scripting environment for the subsurface heat and mass transfer, and geomechanics code FEHM. It is inspired by a similar library, PyTOUGH, available for use with the TOUGH2 family of codes. ", + "laborHours": 34382.4, + "name": "pyFEHM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PyFEHM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-04-10", + "metadataLastUpdated": "2018-04-10" + }, + "description": "This piece of software aims at providing an implementation of methods to perform efficient optimization, probabilistic inference and model selection and learning for various type of networked systems. The software contains a suite of methods and functions that: 1) perform probabilistic inference and random sampling on networked models 2) select or learn networked models from data 3) solve optimization tasks with a networked structure Network models that are supported by these features include, but are not limited to, factor graphs and Markov random fields such as Ising models, Potts models, p-spins models, Gaussian random fields and restricted Boltzmann machine.", + "laborHours": 440.8, + "name": "Optimization, Inference and Learning for Advanced Networks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/GraphicalModelLearning.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-04-11", + "metadataLastUpdated": "2018-04-11" + }, + "description": "This code package solves the multi-species 1D-3V BGK kinetic model of Haack, Hauck, and Murillo [J. 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It can be run in 0D-3V and 1D-3V modes.", + "laborHours": 3070.4, + "name": "Multi-BGK", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Multi-BGK", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-04-12", + "metadataLastUpdated": "2020-11-02" + }, + "description": "ExaMiniMD is a proxy application for Molecular Dynamics (MD) codes such as LAMMPS. Its intend is to facilitate research and development on MD algorithms in particular in the context of CoDesign efforts with hardware vendors. Currently, ExaMiniMD implements a basic Lennard Jones two body potential as well as the SNAP many body potential, both of which are available in LAMMPS. It also includes basic neighbor list builds as well as constant energy integration as found in LAMMPS and other MD codes. A feature not generally available in other MD codes is a set of statistical correctness checks which will help other developers judge whether changes to the code still give correct answers. ExaMiniMD is using the Kokkos programming model to achieve performance portability and is able to run across all major HPC platforms (GPUs, ManyCore, CPUs).", + "laborHours": 3389.6, + "languages": [], + "name": "ECP-copa/ExaMiniMD", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ecp-copa/examinimd", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-04-12", + "metadataLastUpdated": "2021-08-16" + }, + "description": "FAODEL is a collection of libraries for implementing data management services on high-performance computing (HPC) platforms. 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FAODEL is different than other communication libraries in that it supports both intra- and inter-job communication, features event-driven mechanisms, and provides high-level primitives for developers to reason about a platform’s distributed resources.", + "laborHours": 108558.4, + "languages": [], + "name": "FAODEL", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/faodel/faodel", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2108.1" + }, + { + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-04-12", + "metadataLastUpdated": "2018-04-12" + }, + "description": "The MCMD 1.0 model is used to quantify mass and heat transfer for both direct contact and air gap membrane distillation technologies. The code is designed to be able to be extended to include many different membrane distillation configurations of which air-gap and direct contact are two examples that have already been implemented. ", + "laborHours": 6642.4, + "name": "Multi-Configuration Membrane Distillation Model 1.0 ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dlvilla/mcmd1", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ostrouchovg@ornl.gov" + }, + "date": { + "created": "2018-04-13", + "metadataLastUpdated": "2018-06-28" + }, + "description": "pbdR: This release script for pbdR 1.0 combines several repositories on GitHub and on CRAN with an installer script. We list authors of the subject repositories who are active maintainers.\n\nPackages are released under a variety of licenses noted in the release script.", + "laborHours": 136.8, + "languages": [ + "R" + ], + "name": "RBigData/release", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + }, + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + }, + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + }, + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/RBigData/release", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2018-04-13", + "metadataLastUpdated": "2021-11-08" + }, + "description": "MCT is a set of open-source software tools for creating coupled models. MCT is fully parallel and can be used to couple message-passing parallel models to create a parallel coupled model. MCT is available as a small library and a set of Fortran90 modules. Interoperability is through a simple API. Two models that declare and use MCT datatypes can be coupled with a minimum of effort.", + "laborHours": 34184.8, + "languages": [], + "name": "Model Coupling Toolkit v2.10", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MCSclimate/MCT", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v2.10" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2018-04-17", + "metadataLastUpdated": "2020-06-01" + }, + "description": "PETSc is a suite of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations. It supports MPI, and GPUs through CUDA or OpenCL, as well as hybrid MPI-GPU parallelism. PETSc (sometimes called PETSc/Tao) also contains the Tao optimization software library.", + "laborHours": 723352.8, + "languages": [], + "name": "PETSc", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/petsc/petsc/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/petsc/petsc", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Modbus XML Schema Definition and utility software\n", + "laborHours": 577.6, + "name": "ModbusXMLSchema", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-BTRIC/ModbusXMLSchema", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "OpenStudio is a cross-platform collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance. http://openstudio.nrel.gov/\n", + "laborHours": 1326808.0, + "name": "OpenStudio", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-BTRIC/OpenStudio/blob/develop/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-BTRIC/OpenStudio", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "A library for modeling energy storage devices. http://cap.readthedocs.org\n", + "laborHours": 6232.0, + "name": "Cap", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-CEES/Cap", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "DTKData contains large files for DataTransferKit testing and 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The end result of running the software is a piece of code called an emulator, a statistical approximation which predicts the output of complex computer simulation, but at a much faster speed. The emulator is built using a training set of inputs and outputs from the simulations. The input-output pairs are used in a Bayesian scheme to estimate the parameters of a Gaussian process based regression model that learns the input-output relationship. The estimated parameters are combined with a generic C skeleton to produce a compile-able instantiation of the emulator.", + "laborHours": 1854.4, + "name": "Emulator Generation Gadget", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EGG", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-19", + "metadataLastUpdated": "2023-08-16" + }, + "description": "bifacialvf is a self-contained view factor (or configuration factor) model which replicates a 5-row PV system of infinite extent perpendicular to the module rows. Single-axis tracking is supported, and hourly output files based on TMY inputs are saved. Spatial nonuniformity is reported, with multiple rear-facing irradiances collected on the back of each module row.\n\nBilinear interpolation code add-on to bifacialvf (description below) to pre-generate IV arrays and bifacial coefficients, and to examine the energy production with back side irradiance mismatch for either a portrait or landscape module.\nIncluded are IV curves and bifacial info for a Yingli (standard) module.\n\nBased on the publication: \"A Practical Irradiance Model for Bifacial PV Modules\" B. Marion, S. MacAlpine, C. Deline, A. Asgharzadeh, F. Toor, D. Riley, J. Stein, C. Hansen 2017 IEEE Photovoltaic Specialists Conference, Washington DC, 2017 URL: https://www.nrel.gov/docs/fy17osti/67847.pdf\n", + "laborHours": 1018.4, + "languages": [], + "name": "bifacialVF - Bifacial PV View Factor model [SWR 17-58]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bifacialvf", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-19", + "metadataLastUpdated": "2018-04-19" + }, + "description": "The HTEM DB is a public database and web application containing measurements of thin film materials collected using \"high throughput\" (combinatorial) synthesis and measurement processes. This software provides examples of utilizing the HTEM-DB API to access, plot and analyze the data contained therein.", + "laborHours": 364.8, + "name": "HTEM-DB API Examples", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/htem-api-examples", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-19", + "metadataLastUpdated": "2025-03-03" + }, + "description": "The WIND Toolkit Highly Scalable Data Service (HSDS) API examples provide example python software notebooks (software) and a javascript visualization that demonstrate use of the HDF Group's HSDS API utilizing data for NREL's WIND Toolkit.", + "laborHours": 699.2, + "languages": [ + "Jupyter Notebook" + ], + "name": "WIND Toolkit Highly Scalable Data Service (HSDS) API Examples [SWR-18-05]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/hsds-examples", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "fattebertj@ornl.gov" + }, + "date": { + "created": "2018-04-20", + "metadataLastUpdated": "2018-04-20" + }, + "description": "MGmol is a scalable O(N) First-Principles Molecular Dynamics code that is capable of performing large-scale electronics structure calculations and molecular dynamics simulations of atomistic systems.", + "laborHours": 62760.8, + "name": "LLNL/mgmol", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mgmol", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MOSART-WM - a large scale water management model", + "laborHours": 1322.4, + "languages": [], + "name": "IMMM-SFA/wm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/wm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-23", + "metadataLastUpdated": "2023-08-16" + }, + "description": "BRICR is software for translating NREL's BuildingSync™ XML (BSXML) to OpenStudio® Workflow (OSW) files for simulation. Each BSXML contains information about a building as well as multiple possible energy efficiency upgrade options. An OSW file is created and run for each possible efficiency upgrade, the results of all simulations are stored in BSXML format.\n\nBRICR was jointly developed by NREL and LBNL for the San Francisco BayREN: Integrated Commercial Retrofits (BRICR) project funded under the DOE solicitation \"Solutions to Improve the Energy Efficiency of U.S. Small and Medium Commercial Buildings (DE-FOA-0001385)\":\n\nhttps://www.energy.gov/eere/buildings/downloads/san-francisco-bayren-integrated-commercial-retrofits", + "laborHours": 0.0, + "languages": [], + "name": "BRICR v0.2.0 (BayREN Integrated Commercial Retrofits) [SWR 18-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bricr/releases/tag/v0.2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.2.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-23", + "metadataLastUpdated": "2023-01-20" + }, + "description": "A python library used to estimate soiling losses from PV energy production data.", + "laborHours": 744.8, + "languages": [ + "Python" + ], + "name": "PV Soiling Detection [SWR-18-02]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pv_soiling", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.2.2" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-04-24", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The ns-3 topology generator provides a quick and easy way to create a network topology, and generate C++ simulation code for ns-3.", + "laborHours": 3116.0, + "languages": [], + "name": "Topology_Generator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Topology_Generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-04-24", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The ns-3 code generator provides a way to automatically generate C++ simulation code for ns-3 from a high level network topology description.", + "laborHours": 1854.4, + "languages": [], + "name": "idaholab/Code_Generator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Code_Generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-04-24", + "metadataLastUpdated": "2023-03-15" + }, + "description": "HPC job tracker is a wrapper script which will allow some of the resources a HPC application consumes to be tracked for the duration of the job.", + "laborHours": 456.0, + "languages": [], + "name": "HPC_Job_Tracker", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HPC_Job_Tracker", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-04-24", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Mesoscale Atomistic Glue Program for Integrated Execution", + "laborHours": 14333.6, + "languages": [], + "name": "magpie", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/magpie", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Interactive machine learning interface\nOur invention allows the user to interact with individual instances, see recommendations for similar items, and make\nadjustments. The scalable nature of our solution allows it to perform instantaneously from the user's perspective, even for\n100K+ data items.", + "laborHours": 13421.6, + "languages": [], + "name": "pnnl/chissl", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/chissl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Simulation software for biochemical systems that use mass action kinetics based on maximum entropy production.", + "laborHours": 47560.8, + "languages": [], + "name": "Simulations of State for Biology", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/Boltzmann", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-05-01", + "metadataLastUpdated": "2018-05-01" + }, + "description": "Phase Field Dislocation Dynamics (PFDD) is a phase field approach for tracking the motion and interactions of individual dislocations in materials, mostly face-centered cubic (fcc) metals. The phase field approach relies on scalar order parameters or phase field variables to track a quantity of interest. In PFDD, these phase field variables represent the passage of perfect dislocations across each active slip system, with one order parameter defined in each slip system. Partial dislocations are represented with linear combinations of the order parameters. The system is evolved through minimization of the total system energy, which is directly dependent on the phase field variables. All of the physics is described by the total energy functional that is derived from a thermodynamic basis, and the system kinetics are evolved using a Ginzburg-Landau (GL) equation.", + "laborHours": 3024.8, + "name": "Phase Field Dislocation Dynamics (PFDD)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Phase-Field-Dislocation-Dynamics-PFDD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-05-02", + "metadataLastUpdated": "2018-05-02" + }, + "description": "The software is an analyzer for automated sandbox analysis of malware on the OS X operating system. It runs inside an OS X virtual machine to collect data about what happens when a given file opened or run. As of August 2014, there was no sandbox software for Mac OS X malware, as it requires different methods from those used on the Windows OS (which most sandboxes are written for). This software adds OS X analysis capabilities to an existing open-source sandbox, Cuckoo Sandbox (https://cuckoosandbox.org/), which previously only worked for Windows. \n\nThe analyzer itself can take many different types of files as input: the traditional Mach-O and FAT executables, .app files, zip files, Python scripts, Java archives, and web pages, as well as PDFs and other documents. While the file is running, the analyzer also simulates rudimentary human interaction with clicks and mouse movements in order to bypass the tests some malware use to see if they are being analyzed. The analyzer outputs several different kinds of data: functions call traces, network captures, screenshots, and all created and modified files. This work also includes a static analysis Cuckoo module for Mach-O binary files. It extracts file structures, code library imports and exports, and signatures. This data can be used along with the analyzer results to create signatures for malware. ", + "laborHours": 1276.8, + "name": "sandialabs/mac-sandbox", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mac-sandbox", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-05-02", + "metadataLastUpdated": "2018-05-02" + }, + "description": "LAPART is an artificial neural network algorithm written in the Python programming language. The algorithm can learn patterns using multi-dimensional hyper boxes. It can also perfrom regression and classification calculations based on learned associations.", + "laborHours": 258.4, + "name": "sandialabs/lapart-python", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/lapart-python", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-05-02", + "metadataLastUpdated": "2018-05-02" + }, + "description": "The standard scenarios match (sssmatch) tool accepts limited information about an existing transmission system model and computes a new generation mix based on a.) matching a particular NREL Standard Scenario generation mix and b.) minimizing the distance between the system’s original mix and the final one. The distance metric is computed on a nodal basis.", + "laborHours": 562.4, + "name": "sssmatch (Standard ScenarioS Match)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Smart-DS/sssmatch", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bjoo@jlab.org" + }, + "date": { + "created": "2018-05-08", + "metadataLastUpdated": "2018-05-08" + }, + "description": "QMP Message Passing Library. A simple wrapper for MPI to implement the QMP Interface.", + "laborHours": 8557.6, + "name": "QMP", + "organization": "Thomas Jefferson National Accelerator Facility (TJNAF)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://raw.githubusercontent.com/usqcd-software/qmp/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usqcd-software/qmp", + "status": "Production", + "tags": [ + "DOE CODE", + "Thomas Jefferson National Accelerator Facility (TJNAF)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bjoo@jlab.org" + }, + "date": { + "created": "2018-05-08", + "metadataLastUpdated": "2018-05-08" + }, + "description": "A library to read LIME files. LIME is a record oriented file format allowing binary and textual records to be kept in the same file. It is based on a proposed Internet standard by Microsoft called DIME which is now part of the .NET framework.", + "laborHours": 1869.6, + "name": "c-lime", + "organization": "Thomas Jefferson National Accelerator Facility (TJNAF)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://raw.githubusercontent.com/usqcd-software/c-lime/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usqcd-software/c-lime", + "status": "Development", + "tags": [ + "DOE CODE", + "Thomas Jefferson National Accelerator Facility (TJNAF)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-05-09", + "metadataLastUpdated": "2018-05-09" + }, + "description": "The RMA-MT benchmarks are a suite of performance tests for multi-threaded Message Passing Interface (MPI) Remote Memory Access (RMA) implementations. The suite includes tests for bandwidth and latency with any number of threads. This suite was originally developed and release by Sandia National Laboratory. LANL modifications to the suite include a complete re-write of much of the source code, bi-directional bandwidth, and message rate tests.", + "laborHours": 1155.2, + "name": "RMA-MT Benchmarks ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/rma-mt", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-05-09", + "metadataLastUpdated": "2018-05-09" + }, + "description": "The forms and workflow developed were designed to collect additional statistical information not normally available in out of- the-box implementations of the Remedy Action Request System designed by BMC Software. This workflow is used to collect additional information about users accessing the Remedy application, such as operating system and browser type. This information along with frequency of user logins, number of emails sent and received, and overall license usage help provide Remedy Administrators a better overview of the application they support. These custom forms and workflow work heavily with existing out-of-the-box forms in Remedy, and display the collected data to users through the product BMC’s companion product Smart Reporting. ", + "laborHours": 60420.0, + "name": "Remedy Application Statistics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Remedy-Application-Statistics", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-05-10", + "metadataLastUpdated": "2018-05-22" + }, + "description": "Pyranda Is fortran 90 code which solves compact finite difference equations on a three dimensional fortran arrays, domain decomposed using the Message Passing Interface (MPI). The fortran source solves the linear system of equations which forms a pentadtagona1 matrix. Derivatives are used to construct hyperbolic partlal differential equation (PDE) operators, namely gradient, divergence, Laplacian, and curl operators. \n5. Solution Method:\nThe library provides a python Interface which facilitates problem setup and description. However, the core solver Is written in the fortran 90 language. The solver couples MPI communication and linear solves together so that a direct (non-iterative) solution to the linear system of equations can be computed with minimal communication. Domain decomposition is limited to a uniform data size but provides perfect load balancing. \n6. Computer for which the code Is written:", + "laborHours": 9849.6, + "languages": [], + "name": "PYRANDA", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pyranda", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-05-10", + "metadataLastUpdated": "2020-05-27" + }, + "description": "STAT is a light weight debugging tool that gathers and merges stack traces from all of the processes in a parallel application. STAT uses the MRNet tree based overlay network to broadcast commands from the tool front-end to the STAT daemons and for the front-end to gather the traces from the STAT daemons. As the traces propagate through the MRNet network tree, they are merged across all tasks to fonn a single call prefix tree. The call prefix tree can be examined to identify tuks with similar function call patterns and to delineate a small set of equivalence classes. A representative task from each of these classes can then be fed into a full feature debugger like TotalView for root cause analysis. ", + "laborHours": 27755.2, + "languages": [], + "name": "Stack Trace Analysis Tool (STAT)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/STAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-05-15", + "metadataLastUpdated": "2018-05-15" + }, + "description": "Mota is a library that provides several heuristics for mapping tasks to compute ranks (processes) on a networked computer cluster or supercomputer. It was originally designed for task placement of adaptive mesh refinement codes (AMR). It is multi-objective in the sense that it simultaneously balances (potentially multiple types of) computational load on each rank as well as the communication traffic between the boxes. The heuristics used for mapping include algorithms such as greedy list assignment and space-filling curves, as well as algorithms from graph analysis such as adjacency matrix bandwidth reduction, recursive bisection, and greedy graph placement.", + "laborHours": 1930.4, + "languages": [], + "name": "Mota Mapper: A Multi-Objective Topology-Aware Mapper Library", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-CoDEx/mota", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-05-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Global Memory and Threading runtime system", + "laborHours": 5228.8, + "languages": [], + "name": "pnnl/gmt", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/gmt", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-05-18", + "metadataLastUpdated": "2018-05-18" + }, + "description": "OpenStudio is a cross-platform collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance.\n\nThis disclosure includes two OpenStudio measures: (1) data center prototype models, and (2) occupant schedule generator. 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Users of MaDaTS can execute a workflow by either specifying the workflow stages in a YAML description file, or use the API to manage the workflow through a Virtual Data Space (VDS) abstraction.", + "laborHours": 4484.0, + "languages": [], + "name": "\tManaging Data on Tiered Storage for Scientific Workflows (MaDaTS) v1.1.2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dghoshal-lbl/madats", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-05-22", + "metadataLastUpdated": "2025-03-26" + }, + "description": "The software was developed for the purpose of Microgrid Controller Procurement where multiple Microgrid Controller vendors were competing to prove the best performance. Each microgrid controller was connected to Real-Time Simulator (Opal-RT) where the Real-Time model of microgrid was simulated. Microgrid controllers were able to control most of the assets in the model. To be able to fairly compare controller's performance each controller was evaluated using exactly the same model, with the same initial conditions and exactly the same test sequence.\n\nThe microgrid evaluation test sequence lasted 100 minutes and consist of various grid disturbances to which a microgrid controller must respond. The microgrid and power system will experience multiple types of disturbances while performing dispatch functions. Many functions are tested in grid-connected and islanded modes such as unexpended failures of generators, energy storage trip events, and large load fluctuations. The test sequence focuses on fault scenarios that cause the highest short-circuit fault current contribution; force a swing bus or generator capable of being a swing bus offline; cause the most reconfigurations; and cause conflicting objectives for the microgrid controller. \n\nDuring the test sequence execution multiple datapoints are being recorded and stored. During data postprocessing key performance parameters are extracted allowing quantitative comparison of performance on multiple aspects including: resiliency, fuel utilization, grid interconnection, ancillary services and power quality and eventually after summing all key performance parameters by comparing the overall result.\n\nTo be able to perform such testing multiple tools had to be developed included in this repository including:\n- Real time model of microgrid (Urban-Banshee, Remote-smaller model)\n- Test sequence configuration tools\n- Test execution real-time scripts\n- Post processing scripts\n- Human Machine Interface software", + "homepageURL": "https://github.com/PowerSystemsHIL/EPHCC/tree/NREL_merge", + "laborHours": 242196.8, + "languages": [], + "name": "GHOST (Grid Hardware Open Source Testbed) [SWR-18-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PowerSystemsHIL/EPHCC/tree/NREL_merge", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-05-22", + "metadataLastUpdated": "2018-05-22" + }, + "description": "SolarPILOT™advances the analytical flux image Hermite series approximation used in DELSOL3 by applying it to individual heliostat images rather than \"zones\", allowing characterization of a wide variety of heliostat field layouts. SolarPILOT also integrates the SolTrace Monte-Carlo ray tracing engine, providing improved receiver optical modeling capability, a user-friendly front end for geometry definition, and side-by-side validation of the analytical algorithms. The tool and source code are publicly available and are designed for third-party modification and extendability. The software is intended as a replacement for the more antiquated DELSOL3 algorithm originally developed at Sandia National Laboratory. The software will be used at NREL for power tower component design analysis and may be used at other laboratories, in academia, or as a third-party validation tool by some industry groups.", + "laborHours": 28743.2, + "languages": [], + "name": "SolarPILOT™", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SolarPILOT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-05-23", + "metadataLastUpdated": "2018-05-23" + }, + "description": "ParELAGMC is a parallel distributed memory C++ library for multilevel Monte Carlo (MLMC) simulations with algebraically constructed coarse spaces for estimating statistical moments of a quantity of interest involving solutions of partial differential equations with uncertain coefficients. A primary focus of the library is the scalable generation of Gaussian random fields using a novel stochastic PDE (SPDE) sampling technique for large-scale simulations. A key feature in the SPDE sampling technique is a novel non-matching mesh embedding technique to mitigate artificial boundary artifacts that are inherent in the method. Example applications to uncertainty quantification of subsurface flow simulations in the mixed finite element setting are provided as well.", + "laborHours": 17905.6, + "languages": [], + "name": "Parallel Element Agglomeration Multilevel Monte Carlo Library (ParELAGMC)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/parelagmc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-05-23", + "metadataLastUpdated": "2018-05-23" + }, + "description": "Lightweight Python package for assembling, sharing, and running workflows, especially those associated with modifying, running, and analyzing simulation models.", + "laborHours": 699.2, + "languages": [], + "name": "layerstack", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Smart-DS/layerstack", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "A python client that talks to the PCDS logbook using the logbook webservice.\n", + "laborHours": 1352.8, + "languages": [], + "name": "LogBookClient", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": 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Description Markup Language (GDML) version 3.1.2 (deprecated but used by SLIC).\n", + "laborHours": 19167.2, + "languages": [], + "name": "Geometry Description Markup Language (GDML)", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/gdml/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/gdml", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "Investigate hdf5 1.10 features like SWMR and virtual dataset for LCLS II\n", + "laborHours": 6080.0, + "languages": [], + "name": "lc2-hdf5-110", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + 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application.\n", + "laborHours": 4104.0, + "languages": [], + "name": "SLIC", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/slic/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/slic", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "Work to cross validate on mutli GPU host.\n", + "laborHours": 516.8, + "languages": [], + "name": "xvalid", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], 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"contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2018-05-30" + }, + "description": "Parameter Manager for PCDS IMS Motors.\n", + "laborHours": 4803.2, + "languages": [], + "name": "pmgr", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pmgr/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pmgr", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2018-05-30" + }, + "description": "Timescan control for cxi.\n", + "laborHours": 364.8, + "languages": [], + "name": "timescans", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/timescans", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2018-05-30" + }, + "description": "This repository contains instructions on the setup and building the DTM firmware for Proto-DUNE.\n", + "laborHours": 121356.8, + "languages": [], + "name": "Proto-DUNE", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/proto-dune/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": 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"metadataLastUpdated": "2018-05-30" + }, + "description": "Python module for control of LCLS beamlines-By abstracting individual devices into larger collections of paths, operators can quickly guide beam to experimental end stations. Instead of dealing with the individual interfaces for each device, devices are summarized in states. This allows operators to quickly view and manipulate large sections of the beamline when the goal is to simply handle beam delivery.\n", + "laborHours": 1915.2, + "languages": [], + "name": "LCLS Lightpath", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pcdshub/lightpath/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/lightpath", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2018-05-30" + }, + "description": "Automated calculation of beryllium lens focusing optics for MFX Transfocator.\n", + "laborHours": 805.6, + "languages": [], + "name": "transfocate", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pcdshub/transfocate/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/transfocate", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2023-03-15" + }, + "description": "SPPARKS is a kinetic Monte Carlo (KMC) code designed to run efficiently on parallel computers using both KMC and Metropolis Monte Carlo algorithms.", + "laborHours": 25703.2, + "languages": [], + "name": "SPPARKS", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/SPPARKS", + "status": "Development", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2023-03-15" + }, + "description": "A script package for an advanced cubit interface. Provides a lot of functionality, that is not included in the official python interface.", + "laborHours": 547.2, + "languages": [], + "name": "advcubit", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/advcubit", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2023-03-07" + }, + "description": "Example recipes and scripts for use with CIVET (Continuous Integration, Verification, Enhancement, and Testing).", + "laborHours": 136.8, + "languages": [], + "name": "Example CIVET recipes", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/civet_example_recipes", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Test repository used for CIVET demonstration purposes.", + "laborHours": 121.6, + "languages": [], + "name": "labrat", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/labrat", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Three dimensional binary collision Monte Carlo library for sampling ion collision cascades in materials.", + "laborHours": 2568.8, + "languages": [], + "name": "MyTRIM", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/mytrim", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2023-03-15" + }, + "description": "RAVEN (Risk Analysis Virtual Environment) is a flexible and multi-purpose probabilistic risk analysis, uncertainty quantification, parameter optimization and data knowledge-discovering framework. https://raven.inl.gov/", + "laborHours": 770108.0, + "languages": [], + "name": "Raven", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/raven", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2023-03-07" + }, + "description": "Create schematics of thermal-hydraulic systems.", + "laborHours": 1520.0, + "languages": [], + "name": "Schematics", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/schematics", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-06-05", + "metadataLastUpdated": "2018-06-05" + }, + "description": "This module performs abstractions for the CXI detector stands in order to manipulate them as rigid bodies. By first manipulating pairs of motors as joints, and then the stand as a collection of three unieque joints, higher level functions such as translate and rotate are created to help the operator quickly adjust the stand.\n", + "laborHours": 820.8, + "languages": [], + "name": "detrot", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/detrot/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/detrot", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-06-05", + "metadataLastUpdated": "2018-06-05" + }, + "description": "This is the repository for hxdhome developed at SLAC National Accelerator Laboratory.", + "laborHours": 836.0, + "languages": [], + "name": "hxdhome", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/hxdhome/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/hxdhome", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-06-05", + "metadataLastUpdated": "2018-06-05" + }, + "description": "A general repository of useful information for programming across the lab. This repository is oriented around tools, education, best practices, and general knowledge around programming and software development across the lab. We hope it will empower anyone who writes softare at the lab, whether it's analysis scripts in python, firmware for daq systems, web apps for communications, or just simple bash scripts.\n", + "laborHours": 60.8, + "languages": [], + "name": "Programming at SLAC", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/programming/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/programming", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-06-08", + "metadataLastUpdated": "2018-06-14" + }, + "description": "TaskAMR is a Cartesian Block Adaptive Mesh Refinement (AMR) code, written using the Regent/Legion parallel programming system, that solves Finite Volume calculations. We provide implementations for linear advection and gas dynamics.", + "laborHours": 380.0, + "languages": [], + "name": "TaskAMR", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/TaskAMR", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "spotluri@nvidia.com" + }, + "date": { + "created": "2018-06-12", + "metadataLastUpdated": "2020-09-08" + }, + "description": "Prototype of OpenSHMEM for NVIDIA GPUs, developed as part of DoE Design Forward project.", + "laborHours": 744.8, + "languages": [ + "C" + ], + "name": "NVIDIA/df-nvshmem-prototype", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NVIDIA/df-nvshmem-prototype", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-13", + "metadataLastUpdated": "2022-09-14" + }, + "description": "COBRA-SFS (Spent Fuel Storage) is a code for thermal-hydraulic analysis of multi-assembly spent fuel storage and transportation systems. It uses a lumped parameter finite difference approach to predict flow and temperature distributions in spent fuel storage systems and fuel assemblies, under forced and natural convection heat transfer conditions. Derived from the COBRA family of codes, which have been extensively evaluated against in-pile and out-of-pile data, COBRA-SFS retains all the important features of the COBRA codes for single phase fluid analysis, and extends the range application to include problems with two-dimensional radiative and three-dimensional conductive heat transfer. COBRA-SFS has been used to analyze various single- and multi-assembly spent fuel storage systems containing unconsolidated and consolidated fuel rods, with a variety of fill media, including air, helium and vacuum. Cycle 0 of COBRA-SFS was released in 1986. Subsequent applications of the code led to development of additional capabilities, which resulted in the release of Cycle 1 in February 1989. Since then, the code has undergone an independent technical review as part of a submittal to the Nuclear Regulatory Commission for a generic license to apply the code to spent fuel storage system analysis. Modifications and improvements to the code have been combined to form Cycle 2. Cycle 3., the newest version of COBRA-SFS, has been validated and verified for transient applications, such as a storage cask thermal response to a pool fire.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Thermal Hydraulic Analysis of Spent Fuel Casks", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-13", + "metadataLastUpdated": "2022-09-14" + }, + "description": "Integrated system to compute long-term public health risks as the result of the release of hazardous and/or radioactive materials to air, groundwater, surface water, and overland transport pathways.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Multimedia Environmental Pollutant Assessment System", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "phuck@lbl.gov" + }, + "date": { + "created": "2018-06-14", + "metadataLastUpdated": "2019-06-26" + }, + "description": "Python Materials Genomics (pymatgen) is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project.", + "laborHours": 1902280.0, + "languages": [ + "Python" + ], + "name": "pymatgen", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/materialsproject/pymatgen", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "phuck@lbl.gov" + }, + "date": { + "created": "2018-06-14", + "metadataLastUpdated": "2018-06-14" + }, + "description": "FireWorks is a free, open-source code for defining, managing, and executing workflows. Complex workflows can be defined using Python, JSON, or YAML, are stored using MongoDB, and can be monitored through a built-in web interface. Workflow execution can be automated over arbitrary computing resources, including those that have a queueing system. FireWorks has been used to run millions of workflows encompassing tens of millions of CPU-hours across diverse application areas and in long-term production projects over the span of multiple years.", + "laborHours": 55799.2, + "languages": [ + "Python" + ], + "name": "fireworks", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/materialsproject/fireworks", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "phuck@lbl.gov" + }, + "date": { + "created": "2018-06-14", + "metadataLastUpdated": "2018-06-14" + }, + "description": "Since its start in 2011, Materials Project (MP, https://materialsproject.org/) has grown into a world-wide resource for a materials sciences community of more than 27,000 users who rely on the portal as a trusted source to accelerate their research. As a result, they wish to help with MP's efforts by contributing back, but also ask for support in sharing their experimental and computational datasets alongside MP's curated results. This provides the opportunity for researchers in both domains to validate calculations or measurements almost instantaneously and use the disseminated data for integrated materials studies.\n\nWith the public announcement of our general contribution framework, MPContribs, we present a sustainable solution for well-curated data management, organization and dissemination in the context of MP. The framework serves the purpose of collectively maintaining contributions to local and MP community databases as annotations to existing MP materials. It subsequently disseminates them through a generic interactive gateway powered by Jupyter notebooks or through custom project web apps enabled by the webtzite app kit.", + "laborHours": 7949.6, + "languages": [ + "JavaScript", + "Python" + ], + "name": "MPContribs", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/materialsproject/MPContribs", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-06-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python Remote Sensing", + "laborHours": 15.2, + "languages": [], + "name": "pnnl/pysensing", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pysensing", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-06-15", + "metadataLastUpdated": "2018-06-18" + }, + "description": "GeoMatTool support the estimation of parameter values for certain models of use in geomechanics modeling and simulation. The tool itself is a Java language script that functions principally as a database manager for data from certain geomechanical tests. The tool as a database manager allows the user to access, review and modify in limited ways the data. The tool then serves as an interface to plotting and statistical software packages to facilitate the evaluation of the data and parameter estimation.", + "homepageURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [], + "name": "GeoMatTool, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2018-06-19" + }, + "description": "ROVER Is an application for distributed-memory volume rendering and simulated radiography focused on many-core architectures (e.g., GPU, CPU, and MIC). Volume rendering, also known as volume visualization, is a commonly used scientific visualization algorithm that enables users to visualize an entire scalar field at once by mapping scalar values to colors and transparency. Simulated radiography Is a generalization of the volume rendering algorithm from four color channels (I.e., red, green, blue, and transparency) to an arbitrary number of channels representing material opacities in discrete energy groups, measured In electron volts.", + "laborHours": 81943.2, + "languages": [ + "C++" + ], + "name": "ROVER", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/rover", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2022-11-10" + }, + "description": "COSTSAFR3.0 generates a set of compliance forms which will be attached to housing Requests for Proposals (RFPs) issued by Departments or Agencies of the Federal Government. The compliance forms provide a uniform method for estimating the total yearly energy cost for each proposal. COSTSAFR3.0 analyzes specific housing projects at a given site, using alternative fuel types, and considering alternative housing types. The program is designed around the concept of minimizing overall costs through energy conservation design, including first cost and future utility costs, and estabilishes a standard design to which proposed housing designs are compared. It provides a point table for each housing type that can be used to determine whether a proposed design meets the standard and how a design can be modified to meet the standard.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Yearly Energy Costs for Buildings", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2022-11-10" + }, + "description": "UNSAT-H Version 2.0 is a one-dimensional model that simulates the dynamic processes of infiltration, drainage, redistribution, surface evaporation, and the uptake of water from soil by plants. The model was developed for assessing the water dynamics of arid sites used or proposed for near-surface waste disposal. In particular, the model is used for simulating the water balance of cover systems over buried waste and for estimating the recharge rate (i.e., the drainage rate beneath the plant root zone when a sizable vadose zone is present). The mathematical base of the model are Richards'' equation for water flow, Ficks'' law for vapor diffusion, and Fouriers law for heat flow. The simulated profile can be homogeneous or layered. The boundary conditions can be controlled as either constant (potential or temperature) or flux conditions to reflect actual conditions at a given site.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Water and Heat Balance Model for Predicting Drainage Below the Plant Root Zone", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2018-06-19" + }, + "description": "Kappa and BioNetGen (BNGL) are prominent rule-based modeling languages for representing complex biochemical reaction networks. Each language is distributed with a distinct software suite and modelers may wish to take advantage of both toolsets. This application, TRuML, translates models written in either Kappa or BNGL into the other language. While similar in many respects, key differences between the two languages makes translation sufficiently complex that automation becomes a useful tool. TRuML accommodates the languages' complexities and produces a semantically equivalent model in the alternate language of the input model when possible, and an approximate model in certain other cases.", + "laborHours": 1565.6, + "languages": [], + "name": "TRuML", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/TRuML", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2022-11-10" + }, + "description": "REOPT has been developed by Pacific Northwest Laboratory to provide information about remedial action technologies, including application and regulatory information for over 700 contaminants. 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REOPT contains data for approximately 90 remedial action technologies, divided into categories according to the portion of a remedial action (i.e., containment, treatment, disposal, etc.) that they relate to or perform. Technologies are also classified according to the contaminants to which they may be applied. Contaminants may be selected from a list of approximately 700 in ten organic and four inorganic categories. The information for each technology is organized into the broad categories of descriptive information, application information, and additional information sources; these are then subdivided to allow the user to access more specific information about the technology.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "An Electronic Encyclopedia of Remedial Options", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2018-06-19" + }, + "description": "PyDislocDyn is a suite of python programs designed to perform various calculations for basic research in dislocation dynamics in metals with simple crystal symmetries in the continuum limit. 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TAP-LOOP was developed to perform scoping and conceptual design analyses for closed test loops in the Fast Flux Test Facility (FFTF), but it can handle a variety of problems which can be described in terms of potentials, sources, sinks, and storage including, in addition to heat transfer problems, studies of potential fluid flow, electrical networks, and stress analysis.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Thermal Analysis of Closed Systems", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-06-21", + "metadataLastUpdated": "2018-06-21" + }, + "description": "Securely and quickly copy data from source to target. bbcp is a point-to-point network file copy application. It is capable of transferring files at approaching line speeds in the WAN.\n", + "laborHours": 7919.2, + "languages": [], + "name": "bbcp", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.slac.stanford.edu/~abh/bbcp/#_Toc392015168", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/bbcp", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-21", + "metadataLastUpdated": "2022-11-28" + }, + "description": "NRADA1.1 is a supplement to NRADA1.0. This version eliminates several bugs, and includes a few new features. The diskettes consist of a distributed subset of information representative of the extensive NRA databases and database access software maintained at the Pacific Northwest Laboratory which provide an introduction to the scope and style of the NRA Information Systems. Information in the NRA Summary, Inventory, and Bibliographic database is available upon request. Printed reports have been provided in the past. The completion of the NRADA1.1 is the realization of a long standing goal of the staff and advisory committee. Information may be easily distributed to the user in an electronic form which preserves the relationships between the various databases.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Nation Radiobiology Archives Distributed Access", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-22", + "metadataLastUpdated": "2022-12-07" + }, + "description": "SYSPLAN evaluates capital investment in customer side of the meter load leveling battery systems. Such systems reduce the customer's monthly electrical demand charge by reducing the maximum power load supplied by the utility during the customer's peak demand. System equipment consists of a large array of batteries, a current converter, and balance of plant equipment and facilities required to support the battery and converter system. The system is installed on the customer's side of the meter and controlled and operated by the customer. Its economic feasibility depends largely on the customer's load profile. Load shape requirements, utility rate structures, and battery equipment cost and performance data serve as bases for determining whether a load leveling battery system is economically feasible for a particular installation. Life-cycle costs for system hardware include all costs associated with the purchase, installation, and operation of battery, converter, and balance of plant facilities and equipment. The SYSPLAN spreadsheet software is specifically designed to evaluate these costs and the reduced demand charge benefits; it completes a 20 year period life cycle cost analysis based on the battery system description and cost data. A built-in sensitivity analysis routine is also included for key battery cost parameters. The life cycle cost analysis spreadsheet is augmented by a system sizing routine to help users identify load leveling system size requirements for their facilities. The optional XSIZE system sizing spreadsheet which is included can be used to identify a range of battery system sizes that might be economically attractive. XSIZE output consisting of system operating requirements can then be passed by the temporary file SIZE to the main SYSPLAN spreadsheet.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Load Leveling Battery System Costs", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-06-26", + "metadataLastUpdated": "2018-06-26" + }, + "description": "The Software is a toolbox for Dynamic Programming and Adaptive Dynamic Programming (ADP) that enables stochastic, multi-period decision optimization for arbitrary \"black box\" models. It’s modular framework is designed to serve as a wrapper for other simulation tools. This enables forward-looking optimization under uncertainty to aid decision making by a variety of stakeholders when facing an increasingly uncertain future. ", + "laborHours": 5122.4, + "languages": [], + "name": "dynamo", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dynamo", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "czhu@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2018-06-27" + }, + "description": "FOCUS uses 3D curves to represent coils in fusion devices, mainly for toroidal devices including stellarators and tokamaks. For a given configuration, FOCUS can find optimal coils, which can produced the required magnetic field for confining the plasma meeting the user-specified physics and engineering constraints.", + "homepageURL": "https://princetonuniversity.github.io/FOCUS", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Flexible Optimized Coils Using Space curves (FOCUS)", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://princetonuniversity.github.io/FOCUS", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "version": "0.3.1" + }, + { + "contact": { + "email": "fpoli@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2022-01-02" + }, + "description": "TRANSP is a 1.5D equilibrium and transport solver for interpretation and prediction of tokamak discharges.", + "homepageURL": "https://transp.pppl.gov", + "laborHours": 1936723.2, + "languages": [], + "name": "TRANSP", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://transp.pppl.gov/license.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://transp.pppl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] + }, + { + "contact": { + "email": "czhu@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2018-06-27" + }, + "description": "Building on the theoretical foundations of Bruno & Laurence, that three-dimensional, (3D) magnetohydrodynamic (MHD) equilibria with “stepped”-pressure profiles are well-defined and guaranteed to exist, whereas 3D equilibria with integrable magnetic-fields and smooth pressure (or with non-integrable fields and continuous-but-fractal pressure) are pathological. Dr. S.R. Hudson wrote the “Stepped Pressure Equilibrium Code”, (SPEC). SPEC finds minimal-plasma-energy states, subject to the constraints of conserved helicity and fluxes in a collection of nested sub-volumes by extremizing the multi-region, relaxed-MHD (MRxMHD), energy functional, introduced by Dr. M.J. Hole, Dr. S.R. Hudson & Prof. R.L. Dewar.", + "homepageURL": "https://princetonuniversity.github.io/SPEC", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Stepped-Pressure Equilibrium Code (SPEC)", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://princetonuniversity.github.io/SPEC", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] + }, + { + "contact": { + "email": "czhu@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2020-05-07" + }, + "description": "The STELLOPT code is designed to optimize 3D MHD equilibria to a set of target physics parameters encompassing stellarator design and 3D equilibrium reconstructions.", + "laborHours": 173812.0, + "languages": [ + "Fortran" + ], + "name": "STELLOPT", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PrincetonUniversity/STELLOPT", + "status": "Production", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "vcs": "git", + "version": "2.7.5" + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2023-01-17" + }, + "description": "GEOCITY is a large-scale simulation model which combines both engineering and economic submodels to systematically calculate the cost of geothermal district heating systems for space heating, hot-water heating, and process heating based upon hydrothermal geothermal resources. The GEOCITY program simulates the entire production, distribution, and waste disposal process for geothermal district heating systems, but does not include the cost of radiators, convectors, or other in-house heating systems. GEOCITY calculates the cost of district heating based on the climate, population, and heat demand of the district; characteristics of the geothermal resource and distance from the distribution center; well-drilling costs; design of the distribution system; tax rates; and financial conditions.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Geothermal District Heating Economics", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "ethier@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2018-07-26" + }, + "description": "Global, gyrokinetic PIC code in full general geometry used for studying core microturbulent transport in experimental tokamaks.", + "homepageURL": "https://theory.pppl.gov/research/research.php?rid=10#h47", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Gyrokinetic Tokamak Simulation code (GTS)", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://theorycodes.pppl.wikispaces.net/file/detail/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://theory.pppl.gov/research/research.php?rid=10#h47", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] + }, + { + "contact": { + "email": "sku@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2021-04-13" + }, + "description": "XGC (X-point included gyrokinetic code), Version 3 Primary Author: Seunghoe Ku (PPPL, sku@pppl.gov), Robert Hager (PPPL, rhager@pppl.gov) 31 July 2017 XGC is a gyrokinetic particle-in-cell code, which is sepeciallized in tokamak edge simulatin. The simulation domain can include the magnetic separatrix, magnetic axis and the biased material wall. XGC can run in full-f, total-delta-f, and conventional delta-f mode. The ion is kinetic always except ETG simulation. The electron can be adiabatic, fluid, drift kinetic, or gyrokinetic (for ETG). XGC is written in Fortran 90 and is designed for HPCs utilizing MPI, OpenMP, CUDA (GPU), OpenACC (GPU), and vectorization (Intel MIC-KNL). The weak scaling is roughly linear to the maximal nodes of leading HPCs in US. There several versions of XGCs for different purpose: XGC0 is earlist version of XGC0 which is designed for neoclassical transport in the tokamak edge. It uses full-f method, and 00-mode electrostatic field is solved only. RMP and current response can be calculated with coupling with M3D. XGC1 is for turbulence simulation with low parallel wavenumber. Piecewise field following coordinates are used to handle low k-parallel perturbation with small (~64) number of toroidal resolution. In total-delta-f method, it utilizes phase space grid in addition to particles, to handel non-maxwellian distribution in the tokamak edge. XGCa is axisymmetric version of XGC1 to simulate neoclassical transport. References: [1] S. Ku et al., Nuclear Fusion 49, 115021 (2009) [2] S. Ku, R. Hager, C.S. Chang et al., J. Comp. Physics, 315, 467 (2016) https://doi.org/10.1016/j.jcp.2016.03.062 [2] R. Hager. E.S. Yoon. S.Ku et al., J. Comp. Physics, 315, 644 (2016) https://doi.org/10.1016/j.jcp.2016.03.064 [3] R. Hager, J. Lang et al., Phys. Plasmas 24,054508 (2017) http://dx.doi.org/10.1063/1.4983320", + "homepageURL": "https://xgc.pppl.gov", + "laborHours": 0.0, + "languages": [ + "Fortran", + "C++" + ], + "name": "XGC", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://theory.pppl.gov/research/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://xgc.pppl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] + }, + { + "contact": { + "email": "nferraro@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2018-07-02" + }, + "description": "M3D-C1 is a code for simulating magnetized plasmas using an extended-MHD model", + "homepageURL": "https://w3.pppl.gov/~nferraro/m3dc1.html", + "laborHours": 0.0, + "languages": [ + "C++", + "Fortran", + "IDL" + ], + "name": "M3D-C1", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://w3.pppl.gov/~nferraro/m3dc1.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-28", + "metadataLastUpdated": "2023-01-17" + }, + "description": "MMEDE is a software tool designed by Battelle, PNL to support the maintenance of an environmental risk computation database.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Multimedia-Modeling Environmental Database Editor", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-28", + "metadataLastUpdated": "2023-01-17" + }, + "description": "RAAS1.1 is a software-based system designed to assist remediation professionals at each stage of the environmental analysis process. RAAS1.1 provides a template for environmental restoration analysis, and provides the user with key results at each step in the analysis. RAAS1.1 assists the user to develop a coherent and consistent site description, estimate baseline and residual risk to public health from the contaminated site, identify applicable environmental restoration technologies, and formulate feasible remedial response alternatives. In addition, the RAAS1.1 methodology allows the user to then assess and compare those remedial response alternatives across EPA criteria, including: compliance with objectives; short-term and long-term effectiveness; extent of treatment; and implementability of the technologies. The analytic methodology is segmented and presented in a standardized, concise, easy-to-use format that can be viewed on the personal computer screen, saved and further manipulated, or printed for later use. Each screen and analytic step is accessed via a user-friendly personal computer graphical interface. Intuitively-designed buttons, menus, and lists help the user focus in on the particular information and analysis component of interest; the corresponding results are presented in a format that facilitates their use in decision-making.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Remedial Action Assessment System", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-02", + "metadataLastUpdated": "2018-07-02" + }, + "description": "Active Harmony provides software architecture that supports distributed execution of computational objects, and allows applications to be tuned with minimal changes to the application and library source code. It can be used to improve the performance of an application during execution taking into account observed performance. ", + "laborHours": 13619.2, + "languages": [], + "name": "Active Harmony", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ActiveHarmony/harmony", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-02", + "metadataLastUpdated": "2018-07-02" + }, + "description": "ADIC is a tool for the automatic differentiation (AD) of programs written in ANSI C. 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", + "laborHours": 213088.8, + "languages": [], + "name": "SUNDIALS/CVODE", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "CVODES solves ordinary differential equation (ODE) systems and includes sensitivity analysis capabilities (forward and adjoint). Part of the SUNDIALS SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. ", + "laborHours": 213088.8, + "languages": [], + "name": "SUNDIALS/CVODES", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "IDA solves initial value problems for differential-algebraic equation (DAE) systems. Part of the SUNDIALS SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. ", + "laborHours": 213088.8, + "languages": [], + "name": "SUNDIALS/IDA", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2022-02-01" + }, + "description": "SuperLU is a general purpose library for the direct solution of large, sparse, nonsymmetric systems of linear equations on high performance machines.", + "laborHours": 119426.4, + "languages": [], + "name": "SuperLU", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/xiaoyeli/superlu/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xiaoyeli/superlu", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "High-accuracy water level data are needed to resolve the temporal and spatial hydraulic response to pumping in aquifers. However, the water-level data are typically affected by physical process unrelated to the aquifer pumping such as barometric pressure changes, tides, earthquakes, {\\etc}. We have developed a computational framework to correct for barometric and Earth tide effects using linear regression deconvolution, as an initial guess for a nonlinear residual minimization to account for pumping effects. The pumping effects are predicted using the Theis equation with initialization by Jacob's method. After minimizing the residuals between the observed data and Theis predicted pumping effects, the algorithm estimates storativity and transmissivity of the aquifer. The algorithm also provides information about the measurement accuracy of the collected water-level data. The computational framework CHiPBETA is developed in Python and demonstrated to analyze synthetic and real data.", + "laborHours": 4605.6, + "languages": [ + "Python" + ], + "name": "CHiPBETA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/zem/chipbeta", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-12" + }, + "description": "Anasazi is an extensible and interoperable framework for large-scale eigenvalue algorithms. Abstract interface supports Epetra and other linear algebra objects. To access the Anasazi package, please refer to the packages directory within the main Trilinos GitHub repository. \n\n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/Anasazi", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-12" + }, + "description": "AztecOO provides an object-oriented interface the the well-known Aztec Krylov-space iterative solver library. Uses the Epetra linear algebra services to define vector and operator objects. To access the AztecOO package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/AztecOO", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/tree/master/packages/aztecoo", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2019-04-17" + }, + "description": "kcron is a new package for Fermilab’s Scientific Linux 7, which functions as a utility for getting Kerberos credentials in scheduled jobs. The code is written in BASH and C, and depends on Kerberos, POSIX syslog, and POSIX permissions. ", + "laborHours": 425.6, + "languages": [ + "Bash", + "C" + ], + "name": "kcron", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/scientificlinux/kcron", + "status": "Production", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-07-11", + "metadataLastUpdated": "2019-04-17" + }, + "description": "BigData Express is a high-performance data transfer service for big data. It has several salient features:\n•\tBigData Express WebPortal is a distributed web application designed to support BigData Express services and functions. All BDE web portals use a common single-point sign-on service – Cilogon service – to obtain X.509 user certificates for secure access to BDE sites.\n•\tBigData Express scheduler co-schedules Data Transfer Node(s), network, and storage resources for data transfer to achieve optimum performance.\n•\tBigData Express AmoebaNet is a SDN-enabled network service that provide “Application-aware” network. It allows application to program network at run-time for optimum performance. \n", + "homepageURL": "https://bigdataexpress.fnal.gov", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Java", + "JavaScript", + "Python" + ], + "name": "BigData Express", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bigdataexpress.fnal.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-11", + "metadataLastUpdated": "2018-07-11" + }, + "description": "This is a Fortran 95/2003 implementation of the Parallel Full Approximation Scheme in Space and Time (PFASST), which is a method for the time parallelization of ordinary and partial differential equations.", + "laborHours": 16476.8, + "languages": [], + "name": "libpfasst v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/libpfasst/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "IFPACK provides a suite of object-oriented algebraic preconditioners for the solution of preconditioned iterative solvers. To access the IFPACK package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/IFPACK", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/ifpack/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "Isorropia performs combinatorial scientific computing, with focus on partitioning and load balancing, but also supports coloring and ordering of sparse matrices. Isorropia provides an object-oriented interface to Zoltan using the Epetra linear algebra services. To access the Isorropia package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/Isorropia", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://trilinos.org/download/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "LOCA is the Library of Continuation Algorithms, whose objective is to compute families of solutions to the parameterized nonlinear equation F(x,p) = 0 and their bifurcations. To access the LOCA package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/LOCA", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/nox/Copyright_LOCA.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "ML is the Trilinos multigrid preconditioning package designed to solve large sparse linear systems of equations arising primarily from elliptic PDE discretizations. To access the ML package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/ML", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/ml/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "NOX is the Nonlinear Object-Oriented Solutions package of Trilinos, which enables the robust and efficient solution of the nonlinear equations of the form F(x) = 0. To access the NOX package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/NOX", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/nox/Copyright_NOX.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "Zoltan provides dynamic load balancing for parallel computing with a procedural C interface, with a variety of redistribution algorithms available. To access the Zoltan package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/Zoltan", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/zoltan/COPYRIGHT_AND_LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2020-06-01" + }, + "description": "The Trilinos Project is an effort to develop algorithms and enabling technologies within an object-oriented software framework for the solution of large-scale, complex multi-physics engineering and scientific problems. 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Nuclear data is typically processed and made available to simulation codes at various temperatures applicable to the general class of problems that the simulation code is designed to model. These libraries are historically pre-processed and made available to the world. The libraries are based on fundamental physical data and are used by scientists and researchers.", + "laborHours": 820.8, + "languages": [ + "C++", + "Fortran", + "Python", + "C++", + "LaTex", + "Python" + ], + "name": "Nuclear Data Specifications, Utilities, and Libraries", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NuclearData/ACEFormat", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-13", + "metadataLastUpdated": "2018-07-13" + }, + "description": "VisTrails is an open-source scientific workflow and provenance management system developed at the University of Utah that provides support for data exploration and visualization.", + "laborHours": 376960.0, + "languages": [], + "name": "VisTrails", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VisTrails/VisTrails", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-13", + "metadataLastUpdated": "2018-07-13" + }, + "description": "ZeptoOS is a research project that focuses on operating systems for petascale architectures. It provides a complete software stack for Blue Gene/P, covering both compute and I/O nodes. ", + "laborHours": 448415.2, + "languages": [], + "name": "ZeptoOS", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://wiki.mcs.anl.gov/zeptoos/index.php/Licensing", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.mcs.anl.gov/repos/ZeptoOS/trunk", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-13", + "metadataLastUpdated": "2021-11-23" + }, + "description": "Globus is a platform for research data management. The Globus service, operated by the University of Chicago, enables secure, reliable file transfer, sharing and data automation. The service is integrated into data portals, science gateways, and other web applications that manage data distribution from instruments and provide access to reference datasets.", + "homepageURL": "https://globus.org", + "laborHours": 0.0, + "languages": [], + "name": "Globus", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.globus.org/legal", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://globus.org", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-13", + "metadataLastUpdated": "2020-06-01" + }, + "description": "ParaView is an open-source, multi-platform data analysis and visualization application that allows users to quickly build visualizations to analyze their data using qualitative and quantitative techniques. 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", + "homepageURL": "http://www.mcs.anl.gov/research/projects/tao", + "laborHours": 0.0, + "languages": [], + "name": "PETSc/TAO", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.mcs.anl.gov/research/projects/tao", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-13", + "metadataLastUpdated": "2020-06-01" + }, + "description": "ROSE is a compiler infrastructure that builds source-to-source program transformation for a variety of programming languages. These transformations can be used for static analysis, program optimization, performance analysis, and cyber-security purposes. ", + "laborHours": 5605912.0, + "languages": [], + "name": "ROSE", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/rose-compiler/rose/blob/master/LicenseInformation/ROSE_BSD_License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rose-compiler/rose", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This is Nami, a library for parallel wavelet compression. \n", + "laborHours": 1976.0, + "languages": [], + "name": "Nami", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/nami", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "The DiagnosticsViewer is a Django web application for uploading, sharing, and distributing any kind of structured output. The output_viewer project provides a convenient set of scripts for interacting with the app (it builds a JSON, uploads the relevant files, and manages account information on the client).\n", + "laborHours": 1079.2, + "languages": [], + "name": "DiagnosticsViewer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/DiagnosticsViewer", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This is the repository for apache-frontend, Earth System Grid Federation (ESGF) developed at Lawrence Livermore National 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"languages": [], + "name": "ESGF Openid Relying Party (ORP)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esg-orp", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This repository contains a basic description and layout of the ESFG Publisher, with the latest version including the following updates: Support for CMIP6, integration of PrePARE, PID creation via RabbitMQ, cdf2cim included, and handler for non-netCDF and skip variable scan for multiple cases. http://esgf.github.io/esg-publisher/\n", + "laborHours": 24806.4, + "languages": [], + "name": "ESGF Publisher", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esg-publisher", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This module contains the next generation search functionality for the Earth System Grid Federation, built upon the Apache Solr search engine. The package contains functionality for: - Publishing and unpublishing search metadata records into and from a Solr server. Metadata records are generated by harvesting a remote metadata source (a hierarchy of THREDDS catalogs, a OAI repository, a CAS metadata catalog). - Searching the Solr engine content via a free text or faceted search.\n", + "laborHours": 12828.8, + "languages": [], + "name": "ESGF Search Component", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esg-search", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "Maven Repo Of ESGF Project Artifacts\n", + "laborHours": 3268.0, + "languages": [], + "name": "esgf-artifacts", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-artifacts", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "Scripts for building ESGF releases, creating repo mirrors and pushing binaries. https://esgf.github.io/esgf-build/\n", + "laborHours": 197.6, + "languages": [], + "name": "esgf-build", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-build", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2021-07-06" + }, + "description": "New synthetic biology capabilities hold the promise of dramatically improving our ability to engineer biological systems. However, a fundamental hurdle in realizing this potential is our inability to accurately predict biological behavior after modifying the corresponding genotype. Kinetic models have traditionally been used to predict pathway dynamics in bioengineered systems, but they take significant time to develop, and rely heavily on domain expertise. This software implements a method to effectively predict pathway dynamics in an automated fashion using a combination of machine learning and abundant multiomics data (proteomics and metabolomics). The new method outperforms a classical kinetic model, and produces qualitative and quantitative predictions that can be used to productively guide bioengineering efforts. This method systematically leverages arbitrary amounts of new data to improve predictions, and does not assume any particular interactions, but rather implicitly chooses the most predictive ones.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Kinetic Learning vo.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "The Earth System Grid Federation (ESGF), uses three internal Certification Authorities (Cas), to issue CA and identify certificates for the systems in ESGF. The ESGF CA infrastrucutre supports grid and e-science activities in the ESGF.\n", + "laborHours": 212.8, + "languages": [], + "name": "esgf-ca", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-ca", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "The ESGF Compute end-user API provides an object-oriented climatology package to access large scale computational resources through the Web Processing Service interface standard.\n", + "laborHours": 1307.2, + "languages": [], + "name": "ESGF Compute end-user API", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-compute-api", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "ESGF Compute is a Django application capable of providing compute resources to the ESGF data stack. It leverages the 1.0.0 version of the Web Processing Service (WPS) standard to process compute requests.\n", + "laborHours": 21325.6, + "languages": [], + "name": "ESGF Compute WPS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-compute-wps", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This is the repository for the ESFG Dashboard developed at Lawrence Livermore National Laboratory. \n", + "laborHours": 51269.6, + "languages": [], + "name": "ESGF Dashboard", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-dashboard", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "New Dashboard front-end for ESGF.\n", + "laborHours": 52029.6, + "languages": [], + "name": "esgf-dashboard-ui", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-dashboard-ui", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "Repository containing ESGF distributions.\n", + "laborHours": 0.0, + "languages": [], + "name": "esgf-dist", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-dist", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "ESGF software stack as Docker images.\n", + "laborHours": 10822.4, + "languages": [], + "name": "esgf-docker", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-docker", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This is a Python library for processing the 5th Climate Model Intercomparison Project [CMIP5]_ Data Reference Syntax [DRS]_. http://esgf.org/esgf-drslib/\n", + "laborHours": 4818.4, + "languages": [], + "name": "esgf-drslib", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-drslib", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "ESGF Fetcher - Keeps fetched files sync'ed http://esgf.org/esgf-fetcher/\n", + "laborHours": 380.0, + "languages": [], + "name": "ESGF Fetcher", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-fetcher", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This branch of esgf-getcert explores use MyProxyLogon of http://grid.ncsa.illinois.edu/myproxy/MyProxyLogon/ instead of MyProxy and implements a own implementation to convert private key PKCS#8 in PKCS#1. So it can avoid the bug with openJDK versions (https://github.com/ESGF/esgf-getcert/issues/2). Also, this new implementation allows generate a getcert.jar smaller than MyProxy version getcert.jar.\n", + "laborHours": 1033.6, + "languages": [], + "name": "esgf-getcert", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-getcert", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-17" + }, + "description": "The Yadis discovery service is a simple web application that returns XML documents containing URLs for user services. It has no significant library dependencies. The Openid Server functionality is based on the openid4java library, currently the version modified by ESGF to support attribute providers. It uses Spring for managing the application configuration through dependency injection, but it does not use any Spring Security (except for enforcing HTTPS connections), since Spring Security does not support the server-side functionality of the openid exchange. The Openid Client package is a small application provided as a facility to test the Openid Server. It relies on Spring Security support for the client-side openid, which is in turn based on the openid4java library also.\n", + "laborHours": 2188.8, + "languages": [], + "name": "ESGF IDP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-idp", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "ESGF Ingestion Software developed at Lawrence Livermore National Laboratory. \n", + "laborHours": 0.0, + "languages": [], + "name": "esgf-ingestion", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-ingestion", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "The ESGF Installer is a command line tool for installing the ESGF Software Stack. The software stack is comprised of: Tomcat, Thredds, CDAT & CDMS, PostgreSQL, MyProxy, and several ESGF.org custom software applications running on a LINUX (RedHat/CentOS) operating system.\n", + "laborHours": 6748.8, + "languages": [], + "name": "ESGF Installer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-installer", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-17" + }, + "description": "The ESGF Node Manager is transitioning. We are repurposing this repo to contain the material essential for installing the new node manager while keeping the original parts of the previous version. 1) java source needed for access logging filter only - future work is to migrate this to another module within ESGF. 2) python sources: for database table creation, for node manager request and worker daemon and django REST service API 3) bash control scripts\n", + "laborHours": 7828.0, + "languages": [], + "name": "ESGF Node Manager", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-node-manager", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "ESGF Next Generation Publishing Resource files; Repository of project schema and resource files needed for \"next generation\" publishing.\n", + "laborHours": 1535.2, + "languages": [], + "name": "esgf-publisher-resources", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-publisher-resources", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This package contains API code for calling the ESGF Search API within client code. The initial implementation is in Python.\n", + "laborHours": 1033.6, + "languages": [], + "name": "esgf-pyclient", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-pyclient", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This project contains a web application that can be used to deploy an ESG Attribute Service and/or an ESG Authorization service. 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MacPatch offers features and functionality that provide Mac OS X administrators with best possible patching solution to meet the challenges of supporting Mac OS X in a Workgroup or Enterprise.\n", + "laborHours": 97052.0, + "languages": [], + "name": "MacPatch", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MacPatch", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This processor adds the ability to upload AutoPkg packages to a MacPatch server.\n", + "laborHours": 288.8, + "languages": [], + "name": "MacPatchImporter for AutoPkg", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MacPatch-AutoPKG", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "MemAxes is a tool for visualizing memory access samples acquired by load/store sampling mechanisms like Intel PEBS or AMD IBS. It allows a user to view the data projected into various domains; specifically, the layout of the hardware resources, the code/variables, the dataset domain, and parallel coordinates.\n", + "laborHours": 5198.4, + "languages": [], + "name": "MemAxes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MemAxes", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "Mitos is a library and a tool for collecting sampled memory performance data to view with MemAxes.\n", + "laborHours": 684.0, + "languages": [], + "name": "Mitos", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Mitos", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "Symbolic Regression (SR) is a genetic programming algorithm for finding mathematical functions that match a given set of data. It works by evolving an approximation function from a set of primitives. This makes it able to discover the form of the function, in addition to it's coefficients. It has even been shown to be able to discover natural physical laws from experimental data. Given that SR is one of the biggest success stories in genetic programming, it's surprising that there doesn't seem to be an easy-to-use, open-source SR program available. SoRa attempts to fill that gap. With SoRa any user should easily be able to provide experimental data and write a simple configuration file such that SoRa can find a set of good mathematical functions to match the data.\n", + "laborHours": 1550.4, + "languages": [], + "name": "SoRa: Symbolic Regression in Python", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SoRa", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This repository contains companion code and data for the SAE paper \"A Framework for Quantifying Measurement Uncertainties and Uncertainty Propagation in HCCI/LTGC Engine Experiments\", G. Petitpas, M. J. McNenly, R. A. Whitesides.\n", + "laborHours": 410.4, + "languages": [], + "name": "UQ_combustion", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/UQ_combustion", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "The software runs using the Priithon image analysis platform (https://github.com/sebhaase/priithon), which is part of this release. The version of this mac distribution is: Priithon_27_mac-20151127, which expands to a folder named Priithon_27_mac. The paper is the reference source for the wavelet algorithm in this distribution; \"A novel 3D wavelet-based filter for visualizing features in noisy biological data,\" J. Microsc. 219, 43-49 (2005). This distribution has been tested on Mac OS 10.9.5, 10.10.3, and 10.11.1\n", + "laborHours": 1069350.4, + "languages": [], + "name": "WVL", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/WVL", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2019-04-22" + }, + "description": "This software package is the Graphic User Interface (GUI) software component for the Sensor Suitcase Retro-Commissioning project, which is a sensor and analysis system to support monitoring-based retro-commissioning of small commercial buildings, performed by non-experts. \n\nSmall commercial buildings typically do not have the budgets or business economics to allow investing in energy efficiency enhancements the building retro-commissioning provides. In addition, they do not have in-house staff with expertise in building systems who can perform building retro-commissioning or identify energy efficiency improvement opportunities. \n\nThe solution to this problem is to develop a turn-key hardware/software solution (the RCx Sensor Suitcase) that can be used by non-experts to automatically generate low and no-cost energy efficiency rec commendations that will improve building operating costs, occupant comfort and building energy performance. \n\nThis is a joint project between Lawrence Berkeley National Laboratory, leading the development of the software and analysis elements, and Pacific Northwest National Laboratory (PNNL), leading the development of the hardware and sensor elements with an associated table-based configuration support tool. The project is funded by the U.S. Department of Energy. \n\nThis software package was developed as a proof-of-concept prototype for the sensor suitcase software component. The software component was developed with a Microsoft Excel spreadsheet which reads the sensor data and calls a MATLAB DLL to analyze the sensor data.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Retro-Commissioning Sensor Suitcase", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "This is the repository for annie-rose developed at Oak Ridge National Laboratory. 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Backstroke implements a technique for incremental state saving (also called incremental check-pointing). Backstroke supports the simulator ROSS for parallel discrete event simulation (PDES) and can establish automatically the reversibility of ROSS models.\n", + "laborHours": 5031.2, + "languages": [], + "name": "backstroke", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/backstroke", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Blockbuster is a movie player designed for playing movies in the \"Streaming Movie\" format on large power walls. It includes a Sidecar component for controlling the movie player from a remote workstation, and for executing \"movie cues\" to facilitate one-click execution of a planned series of movie transitions, window placements, and other actions that might occur during a presentation.\n", + "laborHours": 137377.6, + "languages": [], + "name": "blockbuster", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/blockbuster", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "A streamlined CMake build system foundation for developing HPC software.\n", + "laborHours": 83767.2, + "languages": [], + "name": "BLT", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/blt", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "A Distributed Burst Buffer File System.\n", + "laborHours": 21371.2, + "languages": [], + "name": "BurstFS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], 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{ + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "This is a script to merge IBM BlueGene lightweight core files into STAT prefix trees.\n", + "laborHours": 3997.6, + "languages": [], + "name": "core_stack_merge", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/core_stack_merge", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2020-10-29" + }, + "description": "Cars Overhead With Context related scripts described in Mundhenk et al. 2016 ECCV. http://gdo152.ucllnl.org/cowc/\n", + "laborHours": 380.0, + "languages": [ + "Python" + ], + "name": "cowc", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/cowc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Tool to run many small MPI jobs inside of one large MPI job.\n", + "laborHours": 1824.0, + "languages": [], + "name": "Cram", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": 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OpenMP is a popular parallel programming model for multi-threaded applications.\n", + "laborHours": 4164.8, + "languages": [], + "name": "DataRaceBench", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/dataracebench", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Datatype Compare (DTCMP) Library for sorting and ranking distributed data using MPI.", + "laborHours": 10047.2, + "languages": [], + "name": "DTCMP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/dtcmp", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Recursive generator of directory trees.\n", + "laborHours": 121.6, + "languages": [], + "name": "fdtree", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/fdtree", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "A small collection of Flume Plugins and scripts.\n", + "laborHours": 592.8, + "languages": [], + "name": "flume-plugins", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/flume-plugins", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2019-07-11" + }, + "description": "Mirror of GLVis - a lightweight OpenGL tool for accurate and flexible finite element visualization. GLVis is an OpenGL tool for visualization of finite element meshes and functions.\n", + "homepageURL": "https://glvis.org", + "laborHours": 0.0, + "languages": [], + "name": "GLVis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://glvis.org", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Repository containing vagrant configurations for how to properly install and harden common web servers, as well as configuration for meeting requirements for (e.g.) HTTPS and HSTS, as laid out in OMB M-15-13 / The HTTPS-Only Standard.\n", + "laborHours": 30.4, + "languages": [], + "name": "HTTPS Servers Cheat Sheet", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/hscs", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "The IBTopo package contains a set of perl modules and a script that uses the modules to process network connectivity information.\n", + "laborHours": 304.0, + "languages": [], + "name": "IBTopo", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ibtopo", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Parallel filesystem I/O benchmark.\n", + "laborHours": 3845.6, + "languages": [], + "name": "IOR", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ior", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2022-10-27" + }, + "description": "A tool for filling C/C++ or Fortran data structures from Lua input tables. 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The purpose of this software portal is to serve as a hub for open source software that is produced by Lawrence Livermore National Laboratory.\n", + "laborHours": 198892.0, + "languages": [], + "name": "LLNL Software Catalog", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/llnl.github.io", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2019-04-22" + }, + "description": "A web-based residential energy calculator with APIs that run two LBNL websites: http://hes.lbl.gov and http://hespro.lbl.gov. Provide customized estimates of residential energy use, energy bills, and CO2 emissions, based on building description information provided by the user. Energy use is estimated by end-use and device, using engineering models developed at LBNL. Space heating and cooling use is based on the DOE-2.1 E building simulation model. Other end-uses (water heating, appliances, lighting, and miscellaneous equipment) are based on engineering models developed by LBNL. Users can estimate their household carbon footprint and compare it to average values for their neighborhood and other regions, displayed using the Google Maps API. Energy bills can be calculated using either average energy price data or actual utility tariffs. The HES software also includes extensive default input for required user inputs. Hardware req.: Multi-platform; Type of files: Source code, installation instructions other; programmer documentation; user manual; electronic format.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 181138.4, + "languages": [], + "name": "Home Energy Saver v3 (website) and APIs", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2019-04-22" + }, + "description": "The software is a research tool for improving the reproducibility of simulations. It does this by keeping a log file of the input file and the input parameters; it also helps with running the same simulations on different computers such as desktops and clusters. It's should be useful for anyone who runs many simulations with input files that are kept in a git repository.", + "laborHours": 395.2, + "languages": [], + "name": "berkeleylab/reproducible", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/reproducible", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-19" + }, + "description": "smwflow imports and exports Cray system management configurations to and from git repositories. smwflow implements both the mechanism for this and, in combination with git, implements a systems engineering workflow that can be used to manage multiple systems, enable rational implementation of features, and add traceability to systems management activities.", + "laborHours": 836.0, + "languages": [ + "SMW 8.0 / CLE 6.0" + ], + "name": "smwflow.v2018.05.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/smwflow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-07-19", + "metadataLastUpdated": "2024-05-07" + }, + "description": "SERA is a simulation environment for planning three-dimensional neutron capture therapy. SERA can allows creating models of the geometry of the tumor and surrounding tissue from CT or MRI data, and then planning and simulating the treatment of the tumor with Boron Neutron Capture Therapy. Boron Neutron Capture Therapy uses the combination of a boron containing drug and a neutron source to treat a tumor.", + "laborHours": 0.0, + "languages": [ + "C", + "Fortran" + ], + "name": "Simulation Environment For Radiotherapy Applications", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/SERA", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-07-19", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The program employs a novel approach to assess the correctness of arbitrary iteration reordering transformations on an affine program, including non-affine transformations.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/PolyCheck", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/PolyCheck", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-07-20", + "metadataLastUpdated": "2018-07-20" + }, + "description": "AXL provides a common C interface to many vendor-specific NVM technologies. In addition, AXL provides a synchronous transfer method. We expect this component to be reused by the VeloC and SCR software packages. ", + "laborHours": 1276.8, + "languages": [], + "name": "Asynchronous Transfer Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-VeloC/AXL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-20", + "metadataLastUpdated": "2018-07-20" + }, + "description": "The Utility Stock Analysis Tool is a pro-forma spreadsheet tool used to model changes in utility cost of equity and return on equity.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Utility Stock Analysis Tool (USAT)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-07-20", + "metadataLastUpdated": "2018-07-20" + }, + "description": "VeloC: Very Low Overhead Transparent Multilevel Checkpoint/Restart. The VeloC software suite will be a multilevel checkpoint/restart interface and implementation for exascale applications. VeloC will have three major impacts. It will: (1) optimize checkpoint/restart perfonnance for applications and workflows (2) increase programmer productivity by dramatically reducing the difficulty of handling varied and complex storage architectures and the need for\nperformance/reliability optimizations. (3) benefit a wide community.\nVeloC is a collaboration between LLNL and ANL as part of the Exascale Computing Project. ", + "laborHours": 1276.8, + "languages": [], + "name": "Very Low Overhead Transparent Multilevel ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-VeloC/AXL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-07-20", + "metadataLastUpdated": "2018-07-20" + }, + "description": "Rst2slldes Is a python extension package for the standard docuti!s documentation generation system. Docutlls translates a simple text markup language called reStructuredText Into a variety of formals, Including HTML and PDF. The reveal.Js presentation framework is a popular syslem klr displaying a specially prepared HTML file as a slldeshow. Because reStructuredText is far simpler to compose end read than HTML, rst2slldes is a useful tool for creating and maintaining technical presentations, which can be delivered to the audience using any web browser. Most of the functionality of rst2slldes, Including lhe ability to display equations written In LaTeX and to embed Images, Is Inherited from docutlls. Besides slightly modifying Ule HTML output to work with reveal.js, the features added by rst2slldes are the ability to embed video, and to set reveal.js configuration options.", + "laborHours": 456.0, + "languages": [], + "name": "Generate reveal.js slfdeshow from reStructuredText", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/rst2slides", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-07-20", + "metadataLastUpdated": "2018-07-20" + }, + "description": "Generally, for encrypted communication to occur, a root trust must be established (usually In the form of a certificate authority) and used to sign communlcatln1 component's certificates that are used to perform encryption. This process ls rather Involved In a number of manual steps with arcane command syntax. Certlpy wraps the standard Python PyOpenSSL library to simplify the calls to create the above mentioned PKI (public key infrastructure) with both a command line and programming Interface. Certlpy was orlglnally created to automate and manage PKI within the open source JupyterHub project so that It could be deployed safely In Uvennore Computing. JupyterHub Is a collection of software components enabling Interactive python notebooks and reproducible science. To ensure secure communication throuahout, Certlpy signs and Issues certs to each component: enabling encryption and authentication (SSL). ", + "laborHours": 380.0, + "languages": [], + "name": "Simple utility for creat1n1 and signing SSL certificates.", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/certipy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-07-23", + "metadataLastUpdated": "2023-03-02" + }, + "description": "The software package provides several utilities written in LabView. These utilities don't form independent programs, but rather can be used as a library or controls in other labview programs. The utilities include several new controls (xcontrols), VIs for input and output routines, as well as other 'helper'-functions not provided in the standard LabView environment.", + "laborHours": 0.0, + "languages": [], + "name": "Labview utilities", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/atap-ibt-labview-utilities", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-23", + "metadataLastUpdated": "2018-08-13" + }, + "description": "The PIACE software is an approach to the parallel integration and chromosomal expansion (PIACE) of metabolic pathways, which extends the Chemical-Induced Chromosomal Expansion (CIChE) method. The software has little to no application outside the specific use case of a specific approach to isopentanol production and analysis of specific related data.", + "laborHours": 273.6, + "languages": [], + "name": "PIACE Project v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/PIACE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-07-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A lightweight Python package to simulate model interactions", + "laborHours": 1079.2, + "languages": [], + "name": "IMMM-SFA/proxymod", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/proxymod", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-23", + "metadataLastUpdated": "2018-08-13" + }, + "description": "This software performs multi-label segmentation of 2D/3D images. It is highly accurate, results rely on use of an Markov random field (MRF) formulation. It runs in both shared and distributed memory parallel modes. MRF algorithms are powerful tools in image analysis to explore contextual information of data.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Markov Random Fields for Image Segmentation (PMRF-IS) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tperciano/PMRF-IS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-07-24", + "metadataLastUpdated": "2018-07-24" + }, + "description": "OJINN Is an easy-to-use deep neural network model that requires fewer user-specified hyper-parameters than traditional neural networks. The algorithm leverages decision trees trained on the data to determine an appropriate deep neural network architectures and weight Initializations. Optional functions also select the learning rate, batch size. and number of training Iterations necessary to create an accurate model.", + "laborHours": 562.4, + "languages": [], + "name": "Deep Jointly-Informed neural networks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DJINN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-07-25", + "metadataLastUpdated": "2018-07-25" + }, + "description": "Owsim is a tool for generating minor modifications to the reference results so some types of minor changes in strategy may be evaluated using the same tool (MAF) without the need to produce complete opsim simulations. The specific modification included in the initial version of owsim is for triggered follow-up of transient events, but the tool is general enough to support different kinds of modifications as well.", + "laborHours": 12479.2, + "languages": [ + "Python" + ], + "name": "owsim", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LSSTDESC/ObsStrat", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-07-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The IGCAPT allows electric utility personnel to perform a static analysis of their communications network supporting smart grid architectures from a network utilization and performance standpoint. IGCAPT is meant to be a \"first order\" planning tool - the tool will accommodate estimates and best available data alongside default settings, which the user can then improve over time.", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "IGCAPT", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/IGCAPT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-25", + "metadataLastUpdated": "2018-07-27" + }, + "description": "This creation is used for standard energy performance tests of household and commercial refrigerators and other refrigeration equipment. It automates the door opening at a preset duration and velocity specified by the test procedure.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Universal Automated Refrigerator Door Opener", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ahakim@pppl.gov" + }, + "date": { + "created": "2018-07-26", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Gkeyll v2.0 (also known as Gkyl, or G2) is a computational plasma physics code mostly written in LuaJIT, with time-critical parts written in C++. Gkyl contains solvers for gyrokinetic equations, Vlasov-Maxwell equations, and multi-fluid equations. Gkeyll contains ab-initio and novel implementations of a number of algorithms, and perhaps is unique in using a JIT compiled typeless dynamic language for its implementation.\n\nOne of the main innovations in Gkeyll is the blurring of boundaries between user written code (i.e. input files) and backend solver code. In fact, there is no difference: the front-end and back-end are written in the same programming language, opening up a very powerful way of composing simulations. All solver objects (grids, data-structures, updaters) can be queried, modified and controlled by the user, allowing complete control over the full simulation cycle. The use of the highly optimized Just-in-Time (JIT) compiled LuaJIT as the main programming language ensures that user written code remains highly efficient. Of course, core kernels can always be written in C/C++ and hooked in via LuaJIT’s powerful FFI facilities.", + "homepageURL": "https://theory.pppl.gov/research/research.php?rid=10#h44", + "laborHours": 0.0, + "languages": [ + "C++", + "C++", + "Lua" + ], + "name": "Gkeyll 2.0", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://theory.pppl.gov/research/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://theory.pppl.gov/research/research.php?rid=10#h44", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "version": "2.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-26", + "metadataLastUpdated": "2018-07-27" + }, + "description": "The software, titled Cryomodule-On-Chip (CMOC), simulates a cryomodule used for low-level RF acceleration in superconducting cavities. The model includes a state-space model of the accelerating fields inside the cavity, the mechanical resonances inside a cryomodule, and their interactions.", + "laborHours": 21690.4, + "languages": [], + "name": "CryoModule On Chip (CMOC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/CMOC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-07-26", + "metadataLastUpdated": "2018-08-03" + }, + "description": "MPAS-Analysis is a software package designed to process and analyze output data of the Model for Prediction Across Scales (MPAS) Ocean, Sea-Ice and Land-Ice model components. It is built primarily on the python language, with remapping of model unstructured-grid fields onto regular grids performed through the ESMF package, and with the computation of climatologies performed through the NCO package. The main purpose of MPAS-Analysis is to analyze the MPAS simulations in terms of ocean and ice metrics, in comparison with available observations, and therefore provide an accurate model evaluation and simulation assessment.", + "laborHours": 20489.6, + "languages": [], + "name": "MPAS-Analysis", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MPAS-Dev/MPAS-Analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ngorelen@pppl.gov" + }, + "date": { + "created": "2018-07-27", + "metadataLastUpdated": "2018-07-27" + }, + "description": "NOVA is a suite of codes including the linear ideal eigenmode solver to find the solutions of ideal magnetohydrodynamic (MHD) system of equations, including such effects as plasma compressibility and realistic tokamak geometry. The kinetic post-processor of the suite, NOVA-K, analyses those solutions to find their stability properties. NOVA-K evaluates the wave particle interaction of the eigenmodes such as Toroidal Alfvén Eigenmodes (TAEs) or Reversed Shear Alfvén Eigenmodes (RSAEs) by employing the quadratic form with the perturbed distribution function coming from the drift kinetic equations. In computations of the hot ion contribution to the growth rate NOVA-K makes use of the constant of motion to represent the hot particle drift orbits. \nNOVA is routinely used for AE structure computations and comparisons with the experimentally observed instabilities [M. A. Van Zeeland et al., Phys. Rev. Lett. 97, 135001 (2006), G. J. Kramer, Phys. Plasmas 13, 056104 (2006)]. The main limitations of NOVA code are caused by neglecting thermal ion finite Larmor radius (FLR), toroidal rotation, and drift effects for the eigenmode computations. Therefore it can not describe accurately radiative damping for example. Finite element methods are used in radial direction and Fourier harmonics are used in poloidal and toroidal directions.\n\nNOVA-K is able to predict various kinetic growth and damping rates perturbatively, such as the phase space gradient drive from energetic particles, continuum damping, radiative damping, ion/electron Landau damping and trapped electron collisional damping. ", + "homepageURL": "https://theory.pppl.gov/research/research.php?rid=10#h45", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "NOVA/NOVA-K", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://theory.pppl.gov/research/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://theory.pppl.gov/research/research.php?rid=10#h45", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "LMT is a distributed system that provides a \"top\"-like display of the activity levels of the server-side (MDS, OSSes, and LNET routers) nodes of one or more Lustre-based filesystems. It is possible to watch server metrics in real time, and to graph past behavior. The clients provide this capability, but it is also possible to directly mine the MySQL database, e.g. with SQL scripts and GNU plot.\n", + "laborHours": 8253.6, + "languages": [], + "name": "LMT (Lustre Monitoring Tool)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lmt", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "This repository contains LLNL's branches of Lustre.\n", + "laborHours": 450832.0, + "languages": [], + "name": "lustre", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lustre", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Some lustre-related scripts and utilities in use at LLNL.\n", + "laborHours": 1033.6, + "languages": [], + "name": "lustre-tools-llnl", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lustre-tools-llnl", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2020-02-05" + }, + "description": "Magpie contains a number of scripts for running Big Data software in HPC environments, including Hadoop and Spark. There is support for Lustre, Slurm, Moab, Torque. and LSF.\n", + "laborHours": 52607.2, + "languages": [], + "name": "Magpie", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/magpie", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Used for testing the metadata performance of a file system.\n", + "laborHours": 1565.6, + "languages": [], + "name": "mdtest", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mdtest", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Melodee (Modular Expression Language for Ordinary Differential Equation Editing) is a new language for ODE modeling and development. It has been designed to make it easy for domain experts to write modular equation systems. Using a familiar Matlab-like syntax, modelers can describe their systems of interests and combine them in new and novel ways at run time. Existing models can easily be converted to MELODEE because of its familiar semantics and syntax.\n", + "laborHours": 2325.6, + "languages": [], + "name": "Melodee ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/melodee", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2019-07-11" + }, + "description": "Mirror of MFEM - a lightweight, general, scalable C++ library for finite element methods. MFEM is a modular parallel C++ library for finite element methods. Its goal is to enable the research and development of scalable finite element discretization and solver algorithms through general finite element abstractions, accurate and flexible visualization, and tight integration with the hypre library.\n", + "homepageURL": "https://mfem.org", + "laborHours": 0.0, + "languages": [], + "name": "MFEM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://mfem.org", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "A light-weight MPI profiler. http://llnl.github.io/mpiP\n", + "laborHours": 13558.4, + "languages": [], + "name": "mpiP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mpiP", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Allows safer access to model specific registers (MSRs).", + "laborHours": 2614.4, + "languages": [], + "name": "msr-safe", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/msr-safe", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Pynamic is a benchmark designed to test a system's ability to handle the Dynamic Linking and Loading requirements of Python-based scientific applications. This benchmark is developed to add a workload to our testing environment, workload that represents a newly emerging class of DLL behaviors. Pynamic builds on pyMPI, an MPI extension to Python. Our augmentation includes a code generator that automatically generates Python C-extension dummy codes and a glue layer that facilitates linking and loading of the generated dynamic modules into the resulting pyMPI. Pynamic is configurable, enabling modeling the static properties of a specific code. It does not, however, model any significant computations of the target and hence it is not subjected to the same level of control as the target code. In fact, HPC computer vendors and tool developers will be encouraged to add it to their testing suite once the code release is completed. An ability to produce and run this benchmark is an effective test for validating the capability of a compiler and a linker/loader as well as an OS kernel and other runtime systems of HPC computer vendors. In addition, the benchmark is designed as a stress test case for code development tools. Though Python has recently gained popularity in the HPC community, its heavy DLL operations have hindered certain HPC code development tools, notably parallel debuggers, from performing optimally.\n", + "laborHours": 14029.6, + "languages": [], + "name": "Pynamic", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pynamic", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Python library for interacting with LLNL's Lorenz REST API.\n", + "laborHours": 273.6, + "languages": [], + "name": "python-lora", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/python-lora", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Ravel is a trace visualization tool for MPI with recent experimental support for Charm++. 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This effort has begun the conversion of these TSG calculations into a Java application format from the original Excel spreadsheets. The original set of Excel spreadsheet calculation aids do not provide the same level of integration, usability, intuitiveness, and speed as a well-designed Java-based application. Achieving the best combination of these characteristics is highly important in an emergency response tool to mitigate a high stress situation and allow a faster, more robust response. Integration in a Java-based application allows for data to be better organized and communicated during the incident.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Technical Support Guidelines Calculator Tool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2018-10-23" + }, + "description": "HALucinator enables execution of firmware on a generic system emulation through interception of hardware abstraction library functions. This enables it to intercept the execution of functions that would interact with external hardware and to model the external hardware at a high-level of abstraction while maintaining correct firmware behavior. ", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HALucinator v. 0.1 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2024-08-07" + }, + "description": "QuESt is an open source, Python-based application suite for energy storage simulation and analysis. The initial release will include an application for energy storage valuation, an analysis where the maximum revenue of a hypothetical energy storage device is estimated using historical energy market data. This is done by determining the sequence of state of charge management actions that optimize revenue generation, assuming perfect foresight of the historical data. The initial release will also include a utility to obtain historical data directly from supported market operating entities for use in analysis. More applications will be added as they are developed. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python", + "CSS", + "HTML", + "Batchfile", + "kvlang", + "JavaScript" + ], + "name": "QuEST v. 1.6", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/snl-quest", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.6" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2018-09-07" + }, + "description": "The goal of this track is to develop blockchain-based ledgering solutions to log and query the user activities of accessing genomic datasets (e.g., GTEx) across multiple sites.", + "laborHours": 121.6, + "languages": [ + "Python" + ], + "name": "iDASH 2018: Task 1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.github.com/sandialabs/idash2018task1", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2018-08-27", + "metadataLastUpdated": "2018-08-27" + }, + "description": "A software suite for applying hierarchical matrices, specifically the \"hierarchically off-diagonal low rank\" (HODLR) format, to Gaussian process computing", + "laborHours": 1717.6, + "languages": [], + "name": "KernelMatrices.jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/cgeoga/kernelmatrices.jl", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-08-27", + "metadataLastUpdated": "2018-08-28" + }, + "description": "High Performance Computing clusters and supercomputers are expensive and complex systems to manage. The software tools to manage these systems are also aging to the point where they are no longer actively developed and their methodology is antiquated. There has been a surge of new methodologies and software tools developed by the cloud providers to maximize availability of services and scalability of server deployment. The authors would like to utilize these new software tools to distribute our proof of concept, named Kraken, that will be responsible for booting and managing LANL's HPC systems in the future", + "laborHours": 91.2, + "languages": [], + "name": "System Administration Tools", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/fast-image-creation", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2018-10-23" + }, + "description": "The Scribetabletop recorder allows usersto visually record and play backscenariosdeveloped during atabletop exercise. It offers a set of tools to visualize,organize, record data, and make decisions while usersdevelop scenarios.Datacan be viewed in both 2D and 3D and played backin real-time or at various speeds", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "SCRIBE 3D-Tabletop Recorder v. 1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Collection of Linux scripts and libraries to aid in common administration tasks and automation. Scripts are for LDAP, nagios, ansible, automatic emailing, license managers, and supporting functions", + "laborHours": 0.0, + "languages": [], + "name": "LinuxSA", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholabUnsupported/LinuxSA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2023-03-15" + }, + "description": "When developing Asp.Net Core applications for deployment in Linux or Docker environments, applications are no longer able to be configured to use Windows Authentication. Many organizations have an ADFS implementation that applications can authenticate off of, but during development there are issues with ADFS. This is a small set of applications that represent a dummy ADFS implementation that removes restrictions while developing locally.", + "laborHours": 0.0, + "languages": [], + "name": "FakeADFS", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/FakeADFS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2023-03-15" + }, + "description": "BlackBear is a MOOSE-based code for simulating degradation processes in concrete and other structural materials.", + "laborHours": 6110.4, + "languages": [], + "name": "Blackbear", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/blackbear", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2024-07-19" + }, + "description": "ACES is a modified version of LLVM for ARMv7-M micro controllers that enables automatic application of compartments to bare-metal system code. It breaks the single monolithic binary of these systems into multiple execution domains using a developer selected policy. This increases the difficulty of compromising the entire system, as the data, code, and peripherals accessible at any given point in execution limited to the subset identified by the policy.", + "laborHours": 1070247.2, + "languages": [ + "C++", + "Shell", + "HTML", + "C", + "Assembly", + "Rich Text Format" + ], + "name": "Automatic Compartments for Embedded Systems", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/ACES?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ACES", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-08-29", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The HPC Software stack testing framework", + "laborHours": 42240.8, + "languages": [], + "name": "hpcswtest", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/hpcswtest", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2020-09-01" + }, + "description": "ImagingSIMS is an open-source project for loading, analyzing, and visualizing secondary ion mass spectrometry (SIMS) data.", + "laborHours": 111887.2, + "languages": [], + "name": "ImagingSIMS/ImagingSIMS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ImagingSIMS/ImagingSIMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a JavaScript library for a storyline layout\nalgorithm. Storylines are adept at communicating\ncomplex change by encoding time on the x-axis and\nusing the proximity of lines in the y direction to\nrepresent interaction between entities. The library in\nthis disclosure takes as input a list of objects\ncontaining an id, time, and state. The output is a\ndata structure that can be used to conveniently\nrender a storyline visualization. Most importantly, the\nlibrary computes the y-coordinate of the entities over\ntime that decreases layout artifacts including\ncrossings, wiggles, and whitespace. This is\naccomplished through multi-objective, multi-stage\noptimization problem, where the output of one stage\nproduces input and constraints for the next stage.", + "laborHours": 15671.2, + "languages": [], + "name": "pnnl/sven", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/sven", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2018-08-30" + }, + "description": "The SDET Tool is used to create open-access power\ngrid data sets and facilitate updates of these data\nsets by the community. Pacific Northwest National\nLaboratory (PNNL) and its power industry and\nsoftware vendor partners are developing an\ninnovative sustainable data evolution technology\n(SDET) to create open-access power grid datasets\nand facilitate updates to these datasets by the power\ngrid community. The objective is to make this a\nsustained effort within and beyond the ARPA-E\nGRID DATA program so that the datasets can evolve\nover time and meet the current and future needs for\npower grid optimization and potentially other\napplications in power grid operation and planning.", + "homepageURL": "https://egriddata.org/dataset/sdet-tool", + "laborHours": 152.0, + "languages": [], + "name": "sdet-tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://egriddata.org/dataset/sdet-tool", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Multi-Speak - Secure Protocol Enterprise Access Kit", + "laborHours": 159189.6, + "languages": [], + "name": "pnnl/ms-speak", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ms-speak", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2018-08-31" + }, + "description": "BELLA is a long-read overlapper and read-to-read aligner that exploits novel approaches for selecting reliable k-mer seeds for filtering and for detecting overlapping read pairs to reconstruct the whole genome. BELLA uses a sparse matrix-matrix multiplication for high-performance overlap detection and then performs pairwise alignment on the overlapping read pairs. BELLA can be built with different pre-existing aligners to use on each read pair, so precision rates are determined by those aligners. Our evaluations include real and synthetic datasets with varying size and complexity and include recall, precision, and running time. BELLA's overlap detection retains nearly all true alignments, with recall rates that exceed other aligners, yet it filters enough read pairs that the running time, including pairwise alignments, is closer to tools that only perform overlapping and is significantly faster than tools that also perform alignment", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper (BELLA) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/aydozz/longreads", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-08-31", + "metadataLastUpdated": "2018-09-04" + }, + "description": "This software comprises a portable, open-source implementation of a runtime library to support applications written in the Unified Parallel C (UPC) language. This library implements the UPC-specific functionality, including shared-memory allocation and distributed locks. The network-dependent functionality is implemented as a thin wrapper around the separate GASNet (Global-Address Space Networking) library, which is required for operation. This software implements the \"Berkeley UPC Runtime Specification\", which is targeted by at least four separate UPC compiler front-ends. The implementation is highly portable and runs over hardware ranging from laptops to custom supercomputers. An external library is required for certain local memory allocation operations; a well-defined interface allows for multiple implementations of this library, but at present the \"umalloc\" library from LBNL is the only compatible implementation.", + "laborHours": 91230.4, + "languages": [], + "name": "Berkeley Unified Parallel C (UPC) runtime library", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upc-runtime", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-04" + }, + "description": "This high-performance ray tracing library provides very fast rendering, compact code, type flexibility via C++ 'generic programming' techniques, and ease of use through an application programming interface (API) that functions independently of any GUI, on-screen display, or other enclosing application. Kip supports constructive solid geometry models based on any of several built-in shapes and operators and allows for new, user-defined shapes and operators. Additional features include basic texturing, input/output of models using a simple human-readable file format with full error checking and detailed diagnostics, and support for shared data parallelism. Kip is written in pure, ANSI Standard C++, is entirely platform independent, and is very easy to use, as it requires no build system, configuration or installation scripts, wizards, special preprocessing, makefiles, or external libraries.", + "laborHours": 10001.6, + "languages": [], + "name": "Kip, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/staleyLANL/kip", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-04" + }, + "description": "Metamesh is a general-purpose C++ language library for creating data structures that represent meshes. An important difference between Metamesh and other \"mesh\" libraries is that Metamesh does not provide a specific mesh format, in the usual sense, or tools or a GUI by which users build specific meshes. Rather, it provides a mechanism by which mesh formats themselves can be built, based on their constituent parts and the relationships between them.Consider that a mesh in up to three space dimensions can, in principle, contain nodes (0d entities, or points), edges (1d entities), faces (2d entities), and cells (3d, or volumetric, entities). A node might be defined in terms of (x), (x,y), or (x,y,z) in Cartesian coordinates; or perhaps something else, in a different coordinate system. An edge is typically defined from two nodes; say, \"edge E goes from node A=(ax,ay) to node B=(bx,by).\" Faces can reasonably be defined in terms of nodes or edges, and cells in terms of nodes, edges, or faces. Note also that someone might wish to support general faces or cells, or only specific variants - say, triangular faces and tetrahedral cells, or quadrilateral faces and hexahedral cells. Or, perhaps, both triangular and quadrilateral faces (but no others), with prisms for each cell. Consider also that a mesh can have the same or a lesser dimension than that of its enclosing space. In 3d, for example, one could have a full 3d mesh, a 2d \"sheet\" mesh with no cells, a 1d \"parametrized curve\" with neither faces nor cells, or even a 1d \"point cloud.\" And, in addition to defining a mesh scheme, a user might wish to place additional data onto one or more mesh entities. Imagine, for example, a velocity at each node, a flux across each edge or face, and a mass or average density per cell. Metamesh supports all of this, through the use of C++ class and function templates, and template metaprogramming techniques. Programmers begin with constructs that Metamesh provides (or, users can define their own), and assemble them in particular ways in order to create particular mesh formats. Metamesh then provides functionality automatically to meshes that are constructed in this manner. Finally, Metamesh provides very general functions for spinning, extruding, visualizing, and performing input/output of whatever meshes a user builds with it.", + "laborHours": 7052.8, + "languages": [], + "name": "Metamesh, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/staleyLANL/metamesh", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2020-06-01" + }, + "description": "There is a sea (mar is Spanish for sea) of data out there that needs to be handled efficiently. Object Stores are filling the hole of managing large amounts of data efficiently. However, in many cases, and our HPC case in particular, we need a traditional file (POSIX) interface to this data as HPC I/O models have not moved to object interfaces, such as Amazon S3, CDMI, etc.Eventually Object Store providers may deliver file interfaces to their object stores, but at this point those interfaces are not ready to do the job that we need done. MarFS will glue together two existing scalable components: a file system's scalable metadata component that provides the file interface; and existing scalable object stores (from one or more providers). There will be utilities to do work that is not critical to be done in real-time so that MarFS can manage the space used by objects and allocated to individual users.", + "laborHours": 10244.8, + "languages": [], + "name": "MarFS, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mar-file-system/marfs", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-05" + }, + "description": "This program is a portable, open-source, compiler for the UPC language. It is based on the Open64 framework and has extensive support for optimizations. This compiler operates by translating UPC into ANSI/ISO C for compilation by a native compiler and linking with the UPC Runtime Library. This design eases portability to both shared- and distributed-memory parallel architectures. For proper operation it requires the \"Berkeley Unified Parallel C (UPC) Runtime Library\" and its dependencies. \n", + "laborHours": 2197342.4, + "languages": [], + "name": "Berkeley Unified Parallel C (BUPC) Compiler", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upc-translator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-04" + }, + "description": "The Performance Prediction Toolkit (PPT), is a scalable co-design tool that contains the hardware and middle-ware models, which accept proxy applications as input in runtime prediction. PPT relies on Simian, a parallel discrete event simulation engine in Python or Lua, that uses the process concept, where each computing unit (host, node, core) is a Simian entity. Processes perform their task through message exchanges to remain active, sleep, wake-up, begin and end. ", + "laborHours": 45478.4, + "languages": [], + "name": "Performance Prediction Toolkit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PPT", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-04" + }, + "description": "Quinoa is a set of computational tools that enables research and numerical analysis in fluid dynamics. At this time it remains a test-bed to experiment with various algorithms using fully asynchronous runtime systems. Currently, Quinoa consists of the following tools: (1) Walker, a numerical integrator for systems of stochastic differential equations in time. It is a mathematical tool to analyze and design the behavior of stochastic differential equations. It allows the estimation of arbitrary coupled statistics and probability density functions and is currently used for the design of statistical moment approximations for multiple mixing materials in variable-density turbulence. (2) Inciter, an overdecomposition-aware finite element field solver for partial differential equations using 3D unstructured grids. Inciter is used to research asynchronous mesh-based algorithms and to experiment with coupling asynchronous to bulk-synchronous parallel code. Two planned new features of Inciter, compared to the previous release (LA-CC-16-015), to be implemented in 2017, are (a) a simple Navier-Stokes solver for ideal single-material compressible gases, and (b) solution-adaptive mesh refinement (AMR), which enables dynamically concentrating compute resources to regions with interesting physics. Using the NS-AMR problem we plan to explore how to scale such high-load-imbalance simulations, representative of large production multiphysics codes, to very large problems on very large computers using an asynchronous runtime system. (3) RNGTest, a test harness to subject random number generators to stringent statistical tests enabling quantitative ranking with respect to their quality and computational cost. (4) UnitTest, a unit test harness, running hundreds of tests per second, capable of testing serial, synchronous, and asynchronous functions. (5) MeshConv, a mesh file converter that can be used to convert 3D tetrahedron meshes from and to either of the following formats: Gmsh, http://www.geuz.org/gmsh, Netgen, http://sourceforge.net/apps/mediawiki/netgen-mesher, ExodusII, http://sourceforge.net/projects/exodusii, HyperMesh, http://www.altairhyperworks.com/product/HyperMesh.", + "laborHours": 130020.8, + "languages": [], + "name": "Quinoa, Version 0.2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/quinoacomputing/quinoa", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2020-09-01" + }, + "description": "This package provides a basic toolkit for model validation and forecast verification, implemented in Python. The code is designed to aid model validation tasks for users of the standard scientific python stack. Functions and classes are provided to calculate a broad range of metrics for continuous and categorical predictions.", + "laborHours": 866.4, + "languages": [], + "name": "PyForecastTools", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/drsteve/PyForecastTools", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2018-09-07" + }, + "description": "MELCOR is a severe accident code developed at Sandia National Laboratories for the US Nuclear Regulatory Commission. It is an integral code with models describing the important physics that come into play during a severe accident. Such physics includes, but is not limited to, the heat-up of reactor core components, thermal hydraulics, oxidation of materials, core degradation, release of fission products from components and the transport of those fission products and other important aerosols through a reactor system, molten core/concrete interactions, and modeling of reactor safety systems. MELCOR modeling is general and flexible, using a “control volume” approach to describe the plant system which has also allowed it to successfully model spent fuel pools.", + "homepageURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "MELCOR", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrc.gov/about-nrc/regulatory/research/obtainingcodes.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "2" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2018-09-07" + }, + "description": "MACCS is the NRC code used to estimate the offsite radiological consequences of potential severe accidents at nuclear power plants (NPPs). The code is used to perform probabilistic health and economic consequence assessment of hypothetical releases of radioactive material. Atmospheric dispersion and transport, wet and dry deposition, probabilistic treatment of meteorology, environmental transfer, countermeasure strategies, dosimetry, health effects, site specific characteristics, evacuation/sheltering activities, and economic impacts are addressed in the code.", + "homepageURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "WinMACCS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrc.gov/about-nrc/regulatory/research/obtainingcodes.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2018-09-07" + }, + "description": "MelMACCS is the interface tool that allows MELCOR plot files to be post processed to create MACCS source term data that can be imported directly into WinMACCS", + "homepageURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "laborHours": 0.0, + "languages": [ + "Visual Basic" + ], + "name": "MelMACCS ver. 2.0.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrc.gov/about-nrc/regulatory/research/obtainingcodes.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Archive Walker Software to read and examine PMU data to detect events and conditions for further analysis.", + "laborHours": 219837.6, + "languages": [], + "name": "pnnl/archive_walker", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/archive_walker", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2020-10-29" + }, + "description": "GridAPPS-D provides a method for developers to run their new applications on a real-time simulator with extensive modeling and tool support. GridAPPS-D is built around standard data models like the CIM. It readily interfaces to existing software products, which may also 1) use components of GridAPPS-D and 2) supplement or replace the built-in distribution simulator, facilitating the deployment of new ADMS applications to existing software products.", + "laborHours": 70862.4, + "languages": [], + "name": "GRIDAPPSD/GOSS-GridAPPS-D", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GRIDAPPSD/GOSS-GridAPPS-D", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2018-09-05" + }, + "description": "GASNet is a language-independent, networking middleware layer that provides network-independent, high-performance communication primitives including Remote Memory Access (RMA) and Active Messages (AM). It has been used to implement parallel programming models and libraries such as UPC, Co-Array Fortran, Titanium, Legion, Chapel, and many others. The interface is primarily intended as a compilation target and for use by runtime library writers (as opposed to end users), and the primary goals are high performance, interface portability, and expressiveness. GASNet stands for \"Global-Address Space Networking\". \n\n", + "laborHours": 93632.0, + "languages": [], + "name": "Global-Address Networking (GASNet-1) Library", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/gasnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The XFEMClipPartialElements tool is a plugin for the open-source Paraview visualization software to correctly visualize results with discontinuities represented using the extended finite element method (XFEM) in MOOSE-based codes.", + "laborHours": 182.4, + "languages": [], + "name": "XFEMParaviewPlugin", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/XFEMParaviewPlugin", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2018-09-07" + }, + "description": "This software provides mechanical/structural explanations for machine learning in chemistry.", + "laborHours": 2097.6, + "languages": [ + "Python" + ], + "name": "FeatureCreature", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/FeatureCreature", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The Sandia Strehl Calculator is designed to calculate the Gibson and Lanni point spread function (PSF), Strehl ratio, and ensquared energy, allowing non-design immersion, coverslip, and sample layers. It also uses Abbe number calculations to determine the refractive index at specific wavelengths when given the refractive index at a different wavelength and the dispersion. The theory behind the code is all fully developed in standard optics references. The novelty of the code is packaging it in a format that is accessible to general microscope users, not limited to individuals with expertise in both optics and computer programming.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Sandia Strehl Calculator Version", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Strehl", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Arcus is a library developed and used within an internally developed network configuration tool. Arcus is being open sourced not the configuration tool.", + "laborHours": 4301.6, + "languages": [ + "C#", + "Powershell" + ], + "name": "Arcus v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/arcus", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2024-07-19" + }, + "description": "This Python package provides high-performance implementations of the functions and examples presented in \"BiEntropy - The Approximate Entropy of a Finite Binary String\" by Grenville J. Croll, presented at ANPA 34 in 2013. https://arxiv.org/abs/1305.0954\n\nAccording to the paper, BiEntropy is \"a simple algorithm which computes the approximate entropy of a finite binary string of arbitrary length\" using \"a weighted average of the Shannon Entropies of the string and all but the last binary derivative of the string.\"", + "laborHours": 2021.6, + "languages": [ + "C", + "Python", + "Makefile" + ], + "name": "BiEntropy for Python v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/bientropy", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2019-07-30" + }, + "description": "This software adds a data handling module to the GNU Radio (GR) software defined radio (SDR) framework as well as some general-purpose function blocks (filters, metadata control, etc). This software is useful for processing bursty RF transmissions with GR, and serves as a base for applying SDR signal processing techniques to a whole burst of data at a time, as opposed to streaming data which GR.", + "laborHours": 11536.8, + "languages": [ + "C++", + "Python" + ], + "name": "GNU Radio Sandia Utilities v. 1.6", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gr-pdu_utils", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.6" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2024-09-18" + }, + "description": "R code that performs the analysis of a data set presented in the paper ‘Leveraging Multiple Statistical Methods for Inverse Prediction in Nuclear Forensics Applications’ by Lewis, J., Zhang, A., Anderson-Cook, C. It provides functions for doing inverse predictions in this setting using several different statistical methods. The data set is a publicly available data set from a historical Plutonium production experiment.", + "laborHours": 349.6, + "languages": [ + "R" + ], + "name": "Analysis Code - Data Analysis in 'Leveraging Multiple Statistical Methods for Inverse Prediction in Nuclear Forensics Applications' (LMSMIPNFA) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/LMSMIPNFA", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2018-09-06" + }, + "description": "Loop-Less Coe Generator for small even size matrices multiplication for AMD processor systems. Matrices are stored in double precision row-wise. Defining the sizes of double precision matrices required. Output is an assembly listing file. Stored as a text file. ", + "laborHours": 0.0, + "languages": [], + "name": "LOOP-LESS CODE GENERATOR FOR WELL-DEFINED COMPUTATIONAL TASKS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jesseYhWang/LLCGX", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2020-06-01" + }, + "description": "GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of Partitioned Global Address Space (PGAS) runtime systems and other alternative models in future exascale machines. The library is an evolution of the popular GASNet communication system, building upon over 15 years of lessons learned. \n\nGASNet is a language-independent, networking middleware layer that provides network-independent, high-performance communication primitives including Remote Memory Access (RMA) and Active Messages (AM). It has been used to implement parallel programming models and libraries such as UPC, Co-Array Fortran, Titanium, Legion, Chapel, and many others. The interface is primarily intended as a compilation target and for use by runtime library writers (as opposed to end users), and the primary goals are high performance, interface portability, and expressiveness. GASNet stands for \"Global-Address Space Networking\". \n", + "homepageURL": "http://gasnet.lbl.gov", + "laborHours": 235858.4, + "languages": [], + "name": "Global-Address Space Networking for Exascale", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://gasnet.lbl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-07", + "metadataLastUpdated": "2020-06-01" + }, + "description": "UPC++ is a C++11 library providing classes and functions that support Partitioned \nGlobal Address Space (PGAS) programming. We are revising the library under the auspices of the DOE's Exascale Computing Project, to meet the needs of applications requiring PGAS support. UPC++ is intended for implementing elaborate distributed data structures where communication is irregular or fine-grained. The UPC++ interfaces for moving non-contiguous data and handling memories with different optimal access methods are composable and similar to those used in conventional C++. The UPC++ programmer can expect communication to run at close to hardware speeds. \n\nThe key facilities in UPC++ are global pointers, that enable the programmer to express \nownership information for improving locality, one-sided communication, both put/get and RPC, futures and continuations. Futures capture data readiness state, which is useful in making scheduling decisions, and continuations provide for completion handling via callbacks. Together, these enable the programmer to chain together a DAG of operations to execute asynchronously as high-latency dependencies become satisfied.\n", + "laborHours": 20702.4, + "languages": [], + "name": "UPC++ V1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upcxx/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-10", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The DOE has funded Sandia National Labs (SNL) to develop an open-source modeling tool to guide the design and layout of marine hydrokinetic (MHK) arrays to maximize power production while minimizing environmental effects. This modeling framework simulates flows through and around a MHK arrays while quantifying environmental responses. As an augmented version of the Dutch company, Deltares’s, environmental hydrodynamics code, Delft3D, SNL-Delft3D-CEC-FM includes a new module that simulates energy conversion (momentum withdrawal) by MHK current energy conversion devices with commensurate changes in the turbulent kinetic energy and its dissipation rate. SNL-Delft3D-CEC-FM modified the Delft3D flexible mesh flow solver, DFlowFM. The Following is a description of Deltares’s open-source code Delft3D from which Delft3D-CEC is built upon. “Delft3D is a world leading 3D modeling suite to investigate hydrodynamics, sediment transport and morphology and water quality for fluvial, estuarine and coastal environments. As per 1 January 2011, the Delft3D flow (FLOW), morphology (MOR) and waves (WAVE) modules are available in open source. The software is used and has proven his capabilities on many places around the world, like the Netherlands, USA, Hong Kong, Singapore, Australia, Venice, etc. The software is continuously improved and developed with innovating advanced modelling techniques as consequence of the research work of our institute and to stay world leading. The FLOW module is the heart of Delft3D and is a multi-dimensional (2D or 3D) hydrodynamic (and transport) simulation program which calculates non-steady flow and transport phenomena resulting from tidal and meteorological forcing on a curvilinear, boundary fitted grid or spherical coordinates. In 3D simulations, the vertical grid is defined following the so-called sigma coordinate approach or Z-layer approach. The MOR module computes sediment transport (both suspended and bed total load) and morphological changes for an arbitrary number of cohesive and non-cohesive fractions. Both currents and waves act as driving forces and a wide variety of transport formulae have been incorporated. For the suspended load this module connects to the 2D or 3D advection-diffusion solver of the FLOW module; density effects may be taken into account. An essential feature of the MOR module is the dynamic feedback with the FLOW and WAVE modules, which allow the flows and waves to adjust themselves to the local bathymetry and allows for simulations on any time scale from days (storm impact) to centuries (system dynamics). It can keep track of the bed composition to build up a stratigraphic record. The MOR module may be extended to include extensive features to simulate dredging and dumping scenarios. For over 30 years Deltares has been in the forefront of these types of combined morphological simulation techniques.”", + "laborHours": 1149545.6, + "languages": [ + "Fortran", + "C++", + "Shell", + "C", + "MATLAB", + "Makefile" + ], + "name": "Sandia's Current Energy Conversion module for Flexible-Mesh Delft3D flow solver v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SNL-Delft3D-FM-CEC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-10", + "metadataLastUpdated": "2018-09-13" + }, + "description": "Software is an online self-service portal for testing M&V methods/tools using buildings' interval meter data. After registering as a user in the portal, that user can download test data files, run those test data files through their own M&V software, and then upload software modeling results to the online portal as a csv file. After the user has uploaded their modeling results the portal will develop statistical accuracy metrics for that M&V tool. The online portal will summarize test results for some or all of the submitted tests. This online portal has been developed by LBNL, and we have been collaborating with the Efficiency Valuation Organization (EVO) with the objective of EVO managing the portal as an ongoing service. Portal is currently posted at http://mvportal.evo-world.org/", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 3237.6, + "languages": [], + "name": "M&V Tool Testing Portal v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-10", + "metadataLastUpdated": "2020-09-08" + }, + "description": "System assessments typically yield large quantities of data from disparate sources for an analyst to scrutinize for issues. Netmeld is used to parse input from different file formats, store the data in a common format, allow users to easily query it, and enable analysts to tie different analysis tools together using a common back-end. ", + "laborHours": 10868.0, + "languages": [ + "C++", + "Python", + "SQL" + ], + "name": "Netmelt v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/netmeld/netmeld", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-10", + "metadataLastUpdated": "2021-08-30" + }, + "description": "The Dakota GUI is an interactive graphical analysis environment for creating, running, and interpreting Dakota optimization and uncertainty quantification studies. It includes problem (Dakota study) set-up, option specification, simulation interfacing, analysis execution, and results visualization. Through the use of wizards, templates, and views, Dakota GUI helps uses navigate Dakota’s complex capability landscape.", + "homepageURL": "https://dakota.sandia.gov", + "laborHours": 3988282.4, + "languages": [ + "Java" + ], + "name": "Dakota Graphical User Interface", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v.6.12" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "CHGL is a hypergraph computation library for Chapel. It's primary contributions are data structures for hypergraphs and the algorithms to operate on these data structures.", + "laborHours": 6414.4, + "languages": [], + "name": "pnnl/chgl", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/chgl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This application works with the Building Agent BACnet library to provide stateful and modular control of device discovery, device OID lookup, and device polling/data scraping. Discovered devices and oids are persisted to a Mongo database, decoupling discovery from the polling process.", + "laborHours": 836.0, + "languages": [], + "name": "Stateful BACnet Scraper [SWR-13-26]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BACnet-state", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This directory tree contains the materials for the initial version of an openMDAO \"Driver\" object that wraps Sandia Lab's \"DAKOTA\" optimization and analysis code.", + "laborHours": 1048.8, + "languages": [ + "Python" + ], + "name": "DAKOTA_plugin, dakota_driver (pydakdriver) [SWR-13-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DAKOTA_plugin", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2018-09-12" + }, + "description": "HARP_Opt (Horizontal Axis Rotor Performance Optimization) utilizes MATLAB's optimization algorithms and the National Renewable Energy Laboratory's (NREL) WT-Perf blade element momentum (BEM) code to design axial-flow wind and water (i.e. hydrokinetic) turbine rotors. The code optimizes a rotor's performance for steady and uniform flows (no sheared or yawed flows). A variety of rotor control configurations can be designed using HARP_Opt, including fixed or variable rotor speed and fixed or variable blade pitch configuration. Blades with circular or non-circular roots are also supported.\n", + "laborHours": 5396.0, + "languages": [], + "name": "HARP_Opt: Horizontal Axis Rotor Performance Optimization", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HARP_Opt", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2018-09-12" + }, + "description": "The Parametric Analysis Tool (PAT) is part of the OpenStudio collection of software tools. It is included in the OpenStudio installer.\n", + "laborHours": 1055837.6, + "languages": [], + "name": "Parametric Analysis Tool (PAT)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-PAT/blob/develop/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-PAT", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "The OpenStudio® Analysis Gem is used to communicate files to the OpenStudio Distributed Analysis. The purpose of this gem is to generate the analysis.json file, analysis.zip, and communicate with the server to upload the simulations. This gem does not create the cluster. To manage cloud resources use the OpenStudio Analysis Framework Helm Charts.", + "laborHours": 7767.2, + "languages": [ + "Ruby" + ], + "name": "OpenStudio® Analysis Gem [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-analysis-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.3.5" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "OpenStudio® AWS uses the OpenStudio AWS ruby class to launch a server and multiple workers for doing OpenStudio®/EnergyPlus® Analyses using Amazon AWS/EC2.", + "laborHours": 1261.6, + "languages": [ + "shell", + "Ruby" + ], + "name": "OpenStudio® AWS Gem [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-aws-gem/blob/develop/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-aws-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.8" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "This repository includes a suite of simulation tests that can be used to validate new OpenStudio® model objects as well as ensure that objects continue to work after they are added. Each new OpenStudio Model object should ideally have two simulation tests associated with it: - a Ruby one which verifies the Ruby API and, - an OSM one that verifies the OSM file can be loaded with future versions of OpenStudio. Both tests should result in a simulation-ready OpenStudio Model that can be simulated using EnergyPlus®. Both of these tests are located in the /model/simulationtests directory, the easiest way to add a new test is to find a related existing test and modify it. When new tests are added they must be added to the model_tests.rb file.", + "laborHours": 1593948.0, + "languages": [ + "Ruby", + "html", + "jupyter notebook" + ], + "name": "OpenStudio® Resources [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-resources/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-resources", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "OpenStudio® Server is a web application and distributed computing tool, which is the backbone of the OpenStudio Analysis Framework (OSAF). It is intended to make parametric analysis of building energy models accessible to architects, engineers, and designers via the OpenStudio PAT GUI or the OpenStudio Analysis Gem. OpenStudio Server analyses are defined by PAT projects or OSA's. Each analysis may include many OpenStudio simulations, as determined by project configuration.", + "laborHours": 42803.2, + "languages": [ + "R", + "Shell", + "HTML", + "Ruby", + "SCSS", + "JavaScript" + ], + "name": "OpenStudio® Server [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-server/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-server", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "3.7.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "This branch is the development branch for the OpenStudio® workflow gem.", + "laborHours": 216645.6, + "languages": [ + "Ruby", + "HTML" + ], + "name": "OpenStudio® Workflow Gem [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-workflow-gem/blob/develop/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-workflow-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.3.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2018-09-12" + }, + "description": "OpenWARP is an open source boundary element simulation tool based on the NEMOH code. OpenWARP and NEMOH provide the ability to determine the frequency dependent added mass, radiation damping, and excitation coefficients that describe the behavior of a floating or submerged body in a wave field. These coefficients are widely used in conjunction with the Cummins equation to model the behavior of wave energy conversion devices, ships, offshore platforms, and other floating structures.\n", + "laborHours": 54872.0, + "languages": [], + "name": "OpenWARP", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenWARP", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2023-05-31" + }, + "description": "API Umbrella is an open source API management platform for exposing web service APIs. The basic goal of API Umbrella is to make life easier for both API creators and API consumers. Binary packages are available for download. Follow the quick setup instructions on the download page to begin running API Umbrella.", + "laborHours": 61088.8, + "languages": [ + "Lua", + "Ruby", + "JavaScript" + ], + "name": "API Umbrella [SWR-12-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/api-umbrella", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.15.1 / 2019-05-14" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2023-06-06" + }, + "description": "This is the repository for api-umbrella-cookbook developed at National Renewable Energy Laboratory. This repository has been archived by the owner, as it is no longer used. The files are now available as read-only.", + "laborHours": 136.8, + "languages": [ + "Ruby" + ], + "name": "api-umbrella-cookbook [SWR-12-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/api-umbrella-cookbook", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ADTKM Disruption Tolerant Key Management", + "laborHours": 2158.4, + "languages": [], + "name": "pnnl/ADTKM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ADTKM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-17", + "metadataLastUpdated": "2018-09-17" + }, + "description": "The Gas Reliability Analysis Integrated Library (GRAIL) is a prototype computational tool for solving a class of intra-day model-predictive control problems for a simplified network model of midstream natural gas pipeline systems. The model accurately resolves dynamic gas flows through long pipes using a non-ideal gas equation of state. It can be used to provide optimal intra-day flow schedules as well as spatiotemporal economic values of natural gas while ensuring that pipeline hydraulic limitations, compressor station constraints, operational factors, and pre-existing shipping contracts are satisfied. The inputs to the code are a model of the pipeline system as well as time-series data that specify boundary conditions on the network and time-dependent constraints on the optimal control problem. The outputs are time-series data that provide an approximately optimal solution of flows, pressures, compressor settings, and sensitivities to the objective function.", + "laborHours": 1976.0, + "languages": [], + "name": "Gas Reliability Analysis Integrated Library (GRAIL)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/grail", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-18", + "metadataLastUpdated": "2019-09-24" + }, + "description": "iTOUGH2 (inverse TOUGH2) provides inverse modeling capabilities for TOUGH2, a simulator for multi-dimensional, multi-phase, multi-component, non-isothermal flow and transport in fractured porous media. \n\niTOUGH2 performs sensitivity analyses, data-worth analyses, parameter estimation, and uncertainty propagation analyses in geosciences and reservoir engineering and other application areas. \n\niTOUGH2 supports a number of different combinations of fluids and components (equation-of-state (EOS) modules). In addition, the optimization routines implemented in iTOUGH2 can also be used for sensitivity analysis, automatic model calibration, and uncertainty quantification of any external code that uses text-based input and output files using the PEST protocol. \n\niTOUGH2 solves the inverse problem by minimizing a non-linear objective function of the weighted differences between model output and the corresponding observations. Multiple minimization algorithms (derivative-free, gradient-based, and second-order; local and global) are available. iTOUGH2 also performs Latin Hypercube Monte Carlo simulations for uncertainty propagation analyses. A detailed residual and error analysis is provided. \n\nThis upgrade includes (a) global sensitivity analysis methods, (b) dynamic memory allocation (c) additional input features and output analyses, (d) increased forward simulation capabilities, (e) parallel execution on multicore PCs and Linux clusters, and (f) bug fixes. \n", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 74130.4, + "languages": [], + "name": "iTOUGH2 v7.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-09-19", + "metadataLastUpdated": "2018-09-19" + }, + "description": "Chatterbug is a suite of proxy applications that represent the communication patterns commonly occurring in high performance computing codes.", + "laborHours": 684.0, + "languages": [], + "name": "Chatterbug", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/chatterbug", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-09-19", + "metadataLastUpdated": "2018-10-23" + }, + "description": "The Energy Market Price Response (EMPR) service is provided by the device, which shifts demand from high price periods in the day to low price periods. The device would consume energy when prices are low and release energy (or defer consumption) when prices are high. This load shifting benefits the individual consumers and society in general by shifting consumption to periods when production resources are available at lower costs. The service could be driven by price forecasts of the day-ahead market or shorter time periods. The service could be facilitated by demand response aggregators, utilities, or other load serving entities.", + "laborHours": 76.0, + "languages": [], + "name": "Dispatch Table", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/TomEdmunds/DispatchTable", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-09-19", + "metadataLastUpdated": "2018-09-19" + }, + "description": "CAMP provides a portable optimized implementation of template meta-programming primitives. All capabilities found within are available in other open source \nprojects, including metal and mpl among others, but no other library we know of supports all compilers required by LLNL codes. CAMP serves as an efficient facility for writing portable compile-time operations in C++ codes. It was \ndeveloped as part of the RAJA project to facilitate more complex compile-time introspection and better error message delivery to users, but has since proven useful in Umpire, CHAI and other pre-release LLNL software projects and is thus being re-factored to stand alone. \n\nThe CAMP library uses portable C++ template mechanisms almost exclusively, with the exception of intrinsics provided for performance by some compilers such as clang and gee. There are no private or protected interfaces and no proprietary information included in the source.\n\nAny and all future versions will limit themselves to implementing commonly available and well known primitives for compile-time manipulation of types.\n \nA new public github repository will be created to host the code independent of its current location in the raja repository, likely at github.com/llnl/camp. \n \n", + "laborHours": 22708.8, + "languages": [], + "name": "Concepts and Meta-Programming Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/raja", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-19", + "metadataLastUpdated": "2018-09-20" + }, + "description": "T2Well/ECO2N is a coupled wellbore and reservoir model for simulating the dynamics of CO2 injection and leakage through wellbores. It can be seen as an extension to standard TOUGH/ECO2N V2.0, and can be applied to situations relevant to geologic CO2 storage involving upward flow (e.g., leakage) and downward flow (injection). The new simulator integrates a wellbore-reservoir system by assigning the wellbore and reservoir to two different sub-domains in which flow is controlled by appropriate physical laws. In the reservoir, we model flow using a standard multiphase Darcy flow approach. In the wellbores, we use the Drift-Flux Model and related conservation equations for describing transient two-phase non-isothermal wellbore flow of CO2-water mixtures. The mass and thermal energy balance equations are solved numerically by a finite difference scheme with wellbore heat transmission to the surrounding rock handled either semi-analytically or numerically. The momentum balance equation for the flow in the wellbore is solved numerically with a semi-explicit scheme.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 7904.0, + "languages": [], + "name": "T2Well/ECO2N Version 1.0: Multiphase and Non-Isothermal Model for Coupled Wellbore-Reservoir Flow of Carbon Dioxide and Variable Salinity Water", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-09-21", + "metadataLastUpdated": "2018-09-21" + }, + "description": "This nonlinear program was developed from a nonlinear solver (called OASIS). During Phase I work, it was applied on a number of nonlinear-solver benchmarking problems and a few SLAC accelerator problems. By searching over only two optimization-control parameters, this Phase I work has enabled the development of a systematic procedure to facilitate the finding of a \"best-guessed\" global minimum solution for various types of problems with different size and complexity. This set of rules has been codified and has led to a versatile nonlinear program IMIGO.", + "homepageURL": "http://www.slac.stanford.edu/doecode/IMIGO_2011", + "laborHours": 167.2, + "languages": [], + "name": "IMIGO Software for Lattice Element Error Modeling in Accelerators", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.slac.stanford.edu/doecode/IMIGO_2011", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.slac.stanford.edu/doecode/IMIGO_2011", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The tool is designed to read, process, analyze, and report on data produced by phasor measurement units (PMUs). It has\nthree main functions:\nData ingestion and processing\nForced oscillation detection\nEvent tracking\nResult writing\nAmbient oscillation baselining\nSpectral analysis and event detection\nDominant mode identification\nResult writing\nData ingestion involves reading PMU data from CSV files, concatenating it, and applying standard signal processing\ntechniques to prepare the data for analysis.\nThe forced oscillation detection portion of the tool examines the data for evidence of a particular dynamic phenomenon in\npower systems known as forced oscillations. It is implemented with a periodogram-based method that was developed at\nPNNL. Forced oscillation events are tracked across time. Results are written to CSV files.\nThe ambient oscillation baselining portion of the tool is based on the Robust Modified Daniell-Welch (RMDW) spectral\nestimator, which was developed at PNNL. It produces estimates of the signal's ambient spectrum while detecting large\npower system events. The ambient spectrum is analyzed to identify the most observable (dominant) mode frequency. At\nthe end of each day, the tool applies the k-means clustering algorithm to distinguish between dominant system modes.\nResults are written to CSV files.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "Eastern Interconnection Situational Awareness Monitoring System (ESAMS) Oscillation Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software reads PMU (phasor measurement unit) data and creates features from the data that are used in analyses. It\nthen takes the past features from previous days of data and builds a baseline to understand the typical behavior of the\npower grid. This baseline is used by employing multivariate statistical algorithms like PCA (Principal Component Analysis),\nclustering (unsupervised learning), and classification (supervised learning). This baseline is then applied to new data to\ndetermine the state of the power grid, whether the behavior is typical or atypical, compared to what has been seen\npreviously. At the end of the day, the baseline is updated and the new baseline is used on the next day. When a time period\nis determined to be atypical, then drill down analyses are performed to help the user understand why the time period is\natypical. Plots and tables are used to show atypicality, including a performance envelope plot. This plot shows the typical\nbehavior of the variable or feature of interest, by plotting in the background the values of the variable from past days using\ncontour shading over time and then the new data over time. This allows the user to see how the new data differs from past\ndata at the same time.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "ESAMS Anomaly Detection Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The US / DOE Office of Nuclear Smuggling Detection and Deterrence (NSDD) Knowledge Management Mobile App will\nprovide password-protected direct access to non-sensitive information regarding the operations, maintenance, and\nsustainability of deployed radiation detection systems. This Mobile App will serve content managed on the NSDD\nKnowledge Management Website to users in a more user-friendly manner. The Mobile App will be cross-platform,\nfunctioning for both iOS and Android devices. The Mobile App will operate both with and without a network connection,\nprovide access to KMW content based on the users' interests, and strengthen analysis of NSDD's training effectiveness.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "NSDD Knowledge Management Mobile App", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "crop model yield change emulation", + "laborHours": 1748.0, + "languages": [], + "name": "JGCRI/persephone", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/persephone", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-25", + "metadataLastUpdated": "2019-09-23" + }, + "description": "\tBecquerel is a Python package for analyzing nuclear spectroscopic measurements. The core functionalities are reading and writing different spectrum file types, fitting spectral features, performing detector calibrations, and interpreting measurement results. It will include tools for plotting radiation spectra and fits of different spectral features, as well as convenient access to tabulated nuclear data. It relies heavily on the standard scientific Python stack of numpy, scipy, matplotlib, and pandas. It is intended to be general-purpose enough that it can be useful to anyone from an undergraduate taking a laboratory course to the advanced researcher.", + "laborHours": 4757.6, + "languages": [], + "name": "Becquerel (Bq) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-anp/becquerel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ZebrafishBMD: A software tool to perform benchmark dose calculations using toxicity screening data of high-throughput zebrafish assays.\nHigh-content imaging of larval zebrafish behavior can be used as a screening approach to rapidly evaluate the relative potential for chemicals to cause toxicity. However, most statistical methods applied to these data transform movement values to incidence-based “hits” and calculate lowest effect levels (LELs), which loses individual fish resolution of behavior and defies hazard ranking due to reliance on applied dose levels. We developed a parallelizable workflow to calculate benchmark dose (BMD) values from dynamic, high-content zebrafish behavior data that scales for high throughput chemical screening. To capture the zebrafish movement response from light to dark stimulus, we summarized time-dependent data using both area under the curve and the immediate change at the transition point into two novel metrics that characterized abnormal behavior as a function of chemical concentration. The BMD workflow was applied to calculate BMD10 values of 1,060 ToxCast chemicals for 24 zebrafish endpoints, including behavior, mortality and morphology.\nZebrafishBMD implements the BMD workflow and provides Matlab scripts to read the data (stored in a specific structure) from a .mat file, to calculate the behavioral endpoint values from movement versus time data, to construct concentrationresponse\ncurves, to perform curve-fitting, and to calculate BMD10 values.", + "laborHours": 15.2, + "languages": [], + "name": "pnnl/ZebrafishBMD", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ZebrafishBMD", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-25", + "metadataLastUpdated": "2018-09-27" + }, + "description": "TOUGH2 is a numerical simulator for nonisothermal flows of multicomponent, multiphase fluids in one-, two-, and three-dimensional porous and fracture media. The chief applications for which TOUGH2 is designed are in geothermal reservoir engineering, nuclear waste disposal, environmental assessment and remediation, geologic carbon sequestration, and unsaturated and saturated zone hydrology. \n\nThe TOUGH2 V2.1 package is an upgrade of TOUGH2 V2.0 (CR-1574) and includes the following improvements and enhancements relative to TOUGH2 V2.0: \n\n- Includes all known bug fixes \n\n- The module TMVOC (CR-1820) is fully integrated \n\n- The module ECO2N (CR-2202) is fully integrated \n\n- A fluid property module ECO2M has been added, that can seamlessly model CO2 storage and leakage scenarios, including transitions between super- and sub-critical fluids, and phase changes between liquid and gaseous CO2. \n\nThe TOUGH2 V2.1 package also supports all legacy fluid property modules, i.e., those packaged into TOUGH2 V2.0 (CR-1574), which includes T2VOC (CR-1254).", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 5715.2, + "languages": [], + "name": "TOUGH2 V2.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-26", + "metadataLastUpdated": "2019-09-24" + }, + "description": "EOS7C is an equation of state module for the TOUGH2 program for CO2 or N2 in Methane (CH4) Reservoirs. In the present work, additions have been made to the EOS7C Version 1.0 module to include the Enhanced Coal Bed Methane (ECBM) modifications developed by Webb (2003). In addition, the Dusty Gas Model for gas-phase diffusion (Webb 2001) has been included. The ECBM modification to the EOS7C equation of state incorporate the extended Langmuir isothem for sorbing gases, including the change in porosity associated with the sorbed gas mass. Comparison to hand calculations for pure gas and binary mixture shows very good agreement. Application to a CO2 well injection problem by Law et al. (2002). The Dusty Model modification add options to calculate gas diffusion using the Dusty-Gas Model including separate and coupled approaches. Comparison to low-permeability pure gas diffusion data shows excellent agreement. The results from the DGM are compared to the Fick's Law behavior for diffusion across a capillary fringe. The differences between the models are small due to the relatively high permeability (10-11 m2) of the problem.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "EOS7C-ECBM Version 1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-27", + "metadataLastUpdated": "2019-09-24" + }, + "description": "EOS7C allows the user to model CO2 injection into natural gas reservoirs that contain methane. There are numerous natural gas modeling codes that can be easily modified to handle CO2, but the developer is not aware of any direct competitors. The current use of the code would be research on carbon sequestration or enhanced natural gas recovery (something the industry is not yet motivated to do). The code development was fully funded by DOE, contains no third party code as the developer has removed MA 28 from the manual, and fully written by LBNL employees. \n\nThe code will be distributed via the TOUGH website and requires the use of TOUGH 2 v2, with which it will be bundled. ", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 7159.2, + "languages": [], + "name": "EOS7C Version 1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "VOLTTRON Distributed Control System Platform", + "laborHours": 196657.6, + "languages": [], + "name": "VOLTTRON/volttron", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-27", + "metadataLastUpdated": "2019-09-24" + }, + "description": "This is a significant upgrade on the TOUGH2 code, which is only distributed via ESTSC. The executable version contains two pieces of third party code. The developer is in the process of obtaining permission to release an executable version with these third party libraries. At this point we will only release source code.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TOUGH2-MP Ver 2.0, the parallel version of TOUGH2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-27", + "metadataLastUpdated": "2019-09-24" + }, + "description": "ECO2N V2.0 is a fluid property module for the TOUGH2 simulator (Version 2.1) that was designed for applications to geologic sequestration of CO2 in saline aquifers and enhanced geothermal reservoirs. ECO2N V2.0 is an enhanced version of the previous ECO2N V1.0 module (Pruess, 2005). It expands the temperature range up to about 300oC whereas V1.0 can only be used for temperatures below about 110oC. V2.0 includes a comprehensive description of the thermodynamic and thermophysical properties of H2O - NaCl - CO2 mixtures, that reproduces fluid properties largely within experimental error for the temperature, pressure and salinity conditions 10 °C < T < 300 °C, P < 600 bar, and salinity up to halite saturation. This includes density, viscosity, and specific enthalpy of fluid phases as functions of temperature, pressure, and composition, as well as partitioning of mass components H2O, NaCl and CO2 among the different phases. In particular, V2.0 accounts for the effects of water on the thermophysical properties of the CO2-rich phase, which was ignored in V1.0, using a model consistent with the solubility models developed by Spycher and Pruess (2005, 2010). In terms of solubility models, V2.0 uses the same model for partitioning of mass components among the different phases (Spycher and Pruess, 2005) as V1.0 for the low temperature range (<99oC) but uses a new model (Spycher and Pruess, 2010) for the high temperature range (>109oC). In the transition range (99-109oC), a smooth interpolation is applied to estimate the partitioning as a function of the temperature. Flow processes can be modeled isothermally or non-isothermally, and phase conditions represented may include a single (aqueous or CO2-rich) phase, as well as two-phase (brine-CO2) mixtures. Fluid phases may appear or disappear in the course of a simulation, and solid salt may precipitate or dissolve. Note that the model cannot be applied to subcritical conditions that involves both liquid and gaseous CO2 unless thermol process is ignored (i.e.,isothermal run). For those cases, a user may use the fluid property module ECO2M (Pruess, 2011) instead.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "\tECO2N V2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-09-28", + "metadataLastUpdated": "2019-03-22" + }, + "description": "The framework stores HEP event data into a database and provides fast and scalable access to the data for distributed Python- and numpy-based analysis.", + "homepageURL": "http://cdcvs.fnal.gov/projects/nosql-ldrd", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "NoSQL BigData Project", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://cdcvs.fnal.gov/projects/nosql-ldrd", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "With Exascale performance and its challenges in\nmind, one ubiquitous concern among architects is energy efficiency.\nPetascale systems projected to Exascale systems are\nunsustainable at current power consumption rates. One major\ncontributor to system-wide power consumption is the number of\nmemory operations leading to data movement and management\ntechniques applied by the runtime system. To address this\nproblem, we present the concept of the Architected Composite\nData Types (ACDT) framework. The framework is made aware of\ndata composites, assigning them a specific layout, transformations\nand operators. Data manipulation overhead is amortized over a\nlarger number of elements and program performance and power\nefficiency can be significantly improved.", + "homepageURL": "http://hpc.pnl.gov/projects/POCR", + "laborHours": 0.0, + "languages": [], + "name": "POSCArchitected Composite Data Type Framework", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://hpc.pnl.gov/projects/POCR", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-28", + "metadataLastUpdated": "2018-10-01" + }, + "description": "EOS7CA is a TOUGH2 module for mixtures of a non-condensible gas (NCG) and air (with or without a gas tracer), an aqueous phase, and water vapor. The user can select the NCG as being CO2, N2, or CH4. EOS7CA uses a cubic equation of state with a multiphase version of Darcy's Law to model flow and transport of gas and aqueous phase mixtures over a range of pressures and temperatures appropriate to shallow subsurface porous media systems. The limitation to shallow systems arises from the use of Henry's Law for gas solubility which is appropriate for low pressures but begins to over-predict solubility starting at pressures greater than approximately 1 MPa (10 bar). The components modeled in EOS7CA are water, brine, NCG, gas tracer, air, and optional heat.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 7706.4, + "languages": [], + "name": "EOS7CA Version 1.0: TOUGH2 Module for Gas Migration in Shallow Subsurface Porous Media Systems", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-01", + "metadataLastUpdated": "2018-10-02" + }, + "description": "VTE is a library that allows fast and simple generation of C++ testers for modules written in Chisel and build an efficient interface to existing C++ based simulators. It contains Scala-based interface and C++ testbench class. Scala interface interacts with Firtl Interpreter and generates a basic set of C++ testbench files. These files contain the list of the Device Under Test (DUT) input-output ports as well as their parameters. C++ testbench provides functionalities similar to the Chisel PeekPokeTester, such as poke, expect, step functions. As a backend it uses Verilator.\n", + "laborHours": 562.4, + "languages": [], + "name": "Verilator Testbench Environment (VTE) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnlcomputerarch/vte", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-10-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Generate random global temperature fields with spatial and temporal correlation derived from an ESM", + "laborHours": 988.0, + "languages": [], + "name": "JGCRI/fldgen", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/fldgen", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-03", + "metadataLastUpdated": "2019-09-23" + }, + "description": "PICviewer is an easy-to-use graphical user interface for data analysis and visualization of Particle-In-Cell (PIC) simulations.", + "laborHours": 2781.6, + "languages": [], + "name": "Picviewer v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/ecp_warpx/picviewer/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-10-04", + "metadataLastUpdated": "2018-10-09" + }, + "description": "This code processes the images collected during high throughput tensile tests to measure the area of each specimen. First, the code identifies the reference images and primary sample images from list of images collected. Then, the size of the reference in the reference images is used to determine a scale (um/pixel) value which can be used to determine the size of each sample in an image. The subsequent sample images are processed to automatically detect the sample present and then identify the size in pixels. The measurements from two different views of the sample are then combined to determine the sample area (um2). ", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 228.0, + "languages": [ + "MATLAB" + ], + "name": "Area Values from Image Dimensions (AVID) v. 3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 3" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-04", + "metadataLastUpdated": "2022-02-16" + }, + "description": "Lidar (light detection and ranging) instruments are often used in wind energy studies in place of meteorological towers, as they can collect measurements at higher heights than met towers and are more easily moved to different parts of a site. While lidars can accurately measure mean wind speeds, they frequently measure different values of turbulence intensity (TI) than would be measured by a cup anemometer on a tower. Discrepancies in TI values are caused by several factors, including instrument noise and volume averaging. The inability of lidars to accurately measure turbulence is a significant barrier to replacing met towers with lidars in the future. There is currently no accepted standard process for quantifying and removing these errors in lidar TI measurements. The Software is an error reduction algorithm for lidar-measured turbulence. The algorithm is trained using co-located lidar and meteorological tower data. Lidar-measured parameters, such as wind speed, shear, and TI, will be used to predict the difference between the lidar- and tower-measured TI. The algorithm will be disseminated as a set of computer code that can be used by lidar users and manufacturers to correct lidar TI data in real time or in post-processing.", + "laborHours": 684.0, + "languages": [ + "Python" + ], + "name": "L-TERRA", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/L-TERRA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2024-09-19" + }, + "description": "BuildingSync® is a standardized language for commercial building energy audit data that software developers can use to exchange data between audit tools. Taking the form of an XML schema, BuildingSync can be required by building owners and audit program managers to allow data analysis and aggregation across multiple buildings in order to evaluate program performance and analyze trends. BuildingSync was developed using the standard energy data terminology defined in the Building Energy Data Exchange Specification (BEDES). BuildingSync is one of the first implementations of BEDES Version 1.0, and it was developed in close collaboration with the BEDES working groups. BuildingSync standardizes the format of the energy audit data itself. It is not intended to standardize the calculations performed on these data by engineers, analysts, software packages, or other audit tools. For more, see: https://buildingsync.net/", + "laborHours": 134793.6, + "languages": [ + "R", + "HTML", + "Ruby", + "Python" + ], + "name": "BuildingSync® [SWR-18-28]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/BuildingSync/schema/blob/develop-v2/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BuildingSync/schema", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2023-06-12" + }, + "description": "This repository contains all the methods to build, test, and release the gem available as rake tasks via bundler/gem_tasks.\n", + "laborHours": 11126.4, + "languages": [], + "name": "BCL Gem [SWR 21-64]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bcl-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This is the repository for capistrano_nrel_ext developed at National Renewable Energy Laboratory.", + "laborHours": 1003.2, + "languages": [ + "Ruby" + ], + "name": "capistrano_nrel_ext [no known SWR]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/capistrano_nrel_ext", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "This gem is an API client for DEnCity.org.", + "laborHours": 425.6, + "languages": [], + "name": "Dencity Gem", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/dencity-gem/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dencity-gem", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "This is the repository for dencity-scripts developed at National Renewable Energy Laboratory. ", + "laborHours": 273.6, + "languages": [], + "name": "dencity-scripts", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dencity-scripts", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "This is the repository for dencity-web developed at National Renewable Energy Laboratory.\n", + "laborHours": 17206.4, + "languages": [], + "name": "dencity-web", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dencity-web", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "Drupal VM is a VM for Drupal, built with Ansible. Drupal VM makes building Drupal development environments quick and easy, and introduces developers to the wonderful world of Drupal development on virtual machines or Docker containers.", + "laborHours": 9576.0, + "languages": [], + "name": "Drupal VM", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/drupal-vm", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "This repository can be used to set up a Composer-Managed Drupal 8 site on Pantheon.", + "laborHours": 288.8, + "languages": [], + "name": "Example Drops 8 Composer", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/example-drops-8-composer", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2021-03-16" + }, + "description": "Python scripting of GridLAB-D input files (.glm) derived from the Open Modeling Framework (OMF).", + "laborHours": 4666.4, + "languages": [], + "name": "glmgen", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/glmgen", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "4.1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2023-08-10" + }, + "description": "kaleidoscope is an R package developed to visualize PLEXOS scenarios as packaged by the rplexos R package. The package provides three types of visualizations intended to be used as coordinated views: a geographic diagram, a chord diagram, and dispatch charts. The geographic diagram provides a qualitative view of the study domain representing individual generator output and interregional transmission flows. The chord diagrams provide a more quantitative view of the net interchange between each of the regions. The dispatch charts are stacked and grouped bar charts providing an instantaneous snapshot of the generation mix by ISO and scenario.\n", + "laborHours": 425.6, + "languages": [ + "R" + ], + "name": "kaleidoscope", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/kaleidoscope/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/kaleidoscope", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2024-02-09" + }, + "description": "The Legacy OpenStudio® SketchUp Plug-in makes it easy to create and edit the building geometry in EnergyPlus® input files. This free plug-in also allows you to launch EnergyPlus simulations and view the results without leaving the SketchUp 3D drawing program.\n\nNote that active OpenStudio development has moved from the Legacy OpenStudio Plug-in to the more comprehensive OpenStudio suite of tools and libraries found here: https://github.com/NREL/OpenStudio. More information can be found at http://openstudio.net.\n\nThe OpenStudio Legacy Plug-in has been relaunched as Euclid by Big Ladder Software, the project's new homepage is http://bigladdersoftware.com/projects/euclid/.\n\nThe Legacy OpenStudio Plug-in was created by the National Renewable Energy Laboratory for the U.S. Department of Energy as an interface to the EnergyPlus simulation engine. Refer to the EnergyPlus webpage at energyplus.gov for an overview of the concept and features.\n\nUser support is available via the community moderated question and answer resource unmethours.com.", + "laborHours": 17571.2, + "languages": [ + "Ruby", + "HTML", + "JavaScript" + ], + "name": "Legacy OpenStudio® SketchUp Plug-in [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/legacy-openstudio", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.14" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "A widget for creating 2d geometry for building energy models.\n", + "laborHours": 19167.2, + "languages": [], + "name": "FloorspaceJS", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/openstudio-geometry-editor/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/openstudio-geometry-editor", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2024-02-09" + }, + "description": "OpenStudio® Standards is a Ruby Gem library that extends the OpenStudio SDK. It has four main use-cases:\n\nProvide higher level methods to help BEM users and developers to create OpenStudio models from existing geometry, or programmatically generated geometry\nCreate typical building models in OpenStudio format\nCreate a code baseline model from a proposed model\nCheck a model against a code/standard\nopenstudio-standards previously supported making the DOE/PNNL prototype buildings in OpenStudio format. This has since been deprecated, as the DOE/PNNL prototypes are intended for specific code comparisons under the Energy Policy Act and are not intended to accurately represent typical existing or new buildings. While openstudio-standards still creates typical buildings, these are not the same as the DOE/PNNL prototypes.", + "laborHours": 16303611.2, + "languages": [ + "Ruby" + ], + "name": "OpenStudio® Standards [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/openstudio-standards", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-11-26" + }, + "description": "The SEED Platform is a web-based application that helps organizations easily manage data on the energy performance of large groups of buildings. Users can combine data from multiple sources, clean and validate it, and share the information with others. The software application provides an easy, flexible, and cost-effective method to improve the quality and availability of data to help demonstrate the economic and environmental benefits of energy efficiency, to implement programs, and to target investment activity.", + "laborHours": 81031.2, + "languages": [], + "name": "Standard Energy Efficiency Data (SEED) Platform", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/seed/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SEED-platform/seed", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "Testing suite for the STREAMM-tools source code. 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The model accounts for heat and up to four mass components, i.e., water, CH4, hydrate, and water-soluble inhibitors such as salts or alcohols. These are partitioned among four possible phases (gas phase, liquid phase, ice phase and hydrate phase). Hydrate dissociation or formation, phase changes and the corresponding thermal effects are fully described, as are the effects of inhibitors. The model can describe all possible hydrate dissociation mechanisms, i.e., depressurization, thermal stimulation, salting-out effects and inhibitor-induced effects.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 9408.8, + "languages": [], + "name": "HYDRATE v1.5 OPTION OF TOUGH+ v1.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-10-11", + "metadataLastUpdated": "2019-03-22" + }, + "description": "SolCalc is a software suite that computes and displays magnetic fields generated by a three dimensional (3D) solenoid system. 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The capabilities of the code include coupled flow and thermal effects, real gas behavior, Darcy and non-Darcy flow, several isotherm options of gas sorption onto the grains of the porous media, complex fracture descriptions, gas solubility into water, and geomechanical effects on flow properties. RealGasBrine v1.0 allows the study of flow and transport of fluids and heat over a wide range of time frames and spatial scales not only in gas reservoirs, but also in any problem involving the flow of gases in geologic media, including the geologic storage of greenhouse gas mixtures, the behavior of geothermal reservoirs with multi-component condensable (H2O and CO2) and non-condensable gas mixtures, the transport of water and released H2 in nuclear waste storage applications, etc.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 6414.4, + "languages": [], + "name": "RealGasBrine v1.0 option of TOUGH+ v1.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-11", + "metadataLastUpdated": "2024-10-25" + }, + "description": "OpenMDAO driver for DAKOTA (Design Analysis Kit for Optimization and Terascale Applications). 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These are now available in a “pluggable” way to any openMDAO based workflow.", + "laborHours": 684.0, + "languages": [ + "Python" + ], + "name": "DAKOTA Driver (WISDEM®) [SWR-13-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/dakota_driver", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-10-11", + "metadataLastUpdated": "2024-09-18" + }, + "description": "PECOS is Python package that provides a framework for studying, developing, and evaluating quantum error-correcting codes. 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It provides a description of the underlying physics and thermodynamics of non-isothermal flow, of the mathematical and numerical approaches, as well as a detailed explanation of the general (common to all applications) input requirements, options, capabilities and output specifications. The core code cannot run by itself: it needs to be coupled with the code for the specific TOUGH+ application option that describes a particular type of problem. The additional input requirements specific to a particular TOUGH+ application options and related illustrative examples can be found in the corresponding User's Manual.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 8876.8, + "languages": [], + "name": "TOUGH+ v1.5 Core Code", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-12", + "metadataLastUpdated": "2019-09-24" + }, + "description": "\tThe BubbleCluster algorithm was developed to help address the limitations of traditional genetic mapping tools when presented with large amounts of data. The BubbleCluster software is a tool for the initial stage in the genetic mapping pipeline -- clustering genetic markers into linkage groups. BubbleCluster was designed to tackle large genetic marker data sets, and has been tested on input of up to 1.6M markers. Input format is identical to that of the popular MSTMap package, aiding useability.", + "laborHours": 395.2, + "languages": [], + "name": "BubbleCluster v4", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/vstrnadova/BubbleCluster", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-15", + "metadataLastUpdated": "2018-10-17" + }, + "description": "This software is designed for the sole purpose of analyzing numerical lattice QCD results computed for one of the developers' research projects related to neutrinoless double beta decay, and will be distributed with their research publication. This software is provided to maximize the dissemination of the research results, to enable other scientists and the general public to easily check the results of their analysis, and also to be in compliance with the public availability of \"digital data\" as required by the DOE.", + "laborHours": 957.6, + "languages": [], + "name": "project_0vbb v1.0-beta", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/callat-qcd/project_0vbb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-16", + "metadataLastUpdated": "2018-10-17" + }, + "description": "fcompare is a software package that applies for comparing two curves generated from datasets in csv format. 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In addition, it can be used for Modelica library developer to do the unit test that verifies new model developments.", + "laborHours": 1018.4, + "languages": [], + "name": "funnel v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-srg/funnel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-16", + "metadataLastUpdated": "2018-10-17" + }, + "description": "The Distributed Energy Resources Customer Adoption Model (DER-CAM) is a powerful and comprehensive decision support tool that primarily serves the purpose of finding optimal distributed energy resource (DER) investments in the context of either buildings or multi-energy microgrids. \n\nVersion 5.9 introduces significant advancements to DER-CAM, including support for wholesale market integration (ancillary services), storage aging effects, improved solar thermal collector modeling, improved part-load efficiency modeling for conventional generators, added support for hydro generation, among others.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 5335.2, + "languages": [], + "name": "Distributed Energy Resources Customer Adoption Model (DER-CAM) v5.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-10-17", + "metadataLastUpdated": "2019-03-19" + }, + "description": "COMMON is a tool for collecting, storing, and displaying critical information to facilitate analysis on Microsoft Windows based IT systems. 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A unique feature is the creation of daily output files (JSON) from the data collected for off site evaluation by subject matter experts.", + "laborHours": 43988.8, + "languages": [ + "C#", + "JavaScript", + "TypeScript" + ], + "name": "COMMON – Communications System Monitor v. 1.5", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/common", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.5" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-23", + "metadataLastUpdated": "2023-05-05" + }, + "description": "This library provides a framework for working with large timeseries data from wind plants, such as SCADA. 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Persistence vectors are a type of vector, based on multidimensional persistent homology theory, which have magnitudes and directions that reflect dominant trends in the multi-component data. The software is a collection of MATLAB scripts, and thus MATLAB runs the scripts. The master script that calls other scripts is called Snorri. The purpose is thus analysis of time-series data to extract dominant trends or events and to classify the type of event. The software produces characteristic vectors (an average of the persistence vectors), which can have directions that reflect the overall dominant trend in a time-series data set. The MATLAB scripts have been partially converted to the PYTHON language and no do not have the full functionality of the MATLAB and are not fully tested; the python scripts are to be covered under this copyright assertion. Two versions of the PYTHON scripts are included, called: mph25.py and mph38.py, each with their own main.py file.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 1444.0, + "languages": [ + "MATLAB" + ], + "name": "Snorri Version 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-30", + "metadataLastUpdated": "2019-09-23" + }, + "description": "This software is an extension to OTM (Open Traffic Models), which is an open-source traffic simulator maintained at the Institute of Transportation Studies at U.C. Berkeley. OTM-MPI provides functionality for running OTM simulations in distributed computing environments. Its functionality includes min-cut division of traffic networks (using METIS), deployment of sub-networks on multiple compute nodes, and inter-node MPI communications.", + "laborHours": 1155.2, + "languages": [], + "name": "OTM-MPI (Open Traffic Models - MPI)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ggomes/otm-mpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-30", + "metadataLastUpdated": "2019-09-23" + }, + "description": "TA_solver is a modular software framework for solving user equilibrium traffic assignment problems, both static and dynamic, utilizing the OTM (Open Traffic Models) API to encode traffic scenarios. The design is based on the formulation of the problem as a variational inequality. Unlike most existing traffic assignment software which focus on specific traffic models, TA_solver accommodates various traffic models, but also enables using parallel computation in high performance computing environments to speed up large-scale equilibrium calculations.", + "laborHours": 39033.6, + "languages": [], + "name": "TA_solver -- Traffic Assignment solver package", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ugirumurera/TA_solver", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-30", + "metadataLastUpdated": "2019-09-23" + }, + "description": "WarpX is a fully electromagnetic Particle-In-Cell code for the modeling of plasma-based particle accelerators. The code includes unique features such as mesh refinement and arbitrary-order analytical pseudo-spectral Maxwell solvers.", + "laborHours": 23712.0, + "languages": [], + "name": "WarpX v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-WarpX/WarpX", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-30", + "metadataLastUpdated": "2019-09-24" + }, + "description": "IDAES PSE capabilities support the design and optimization of innovative new advanced Process Systems Engineering (PSE) capabilities to improve the efficiency and reliability of the existing fleet of coal-fired power plants while accelerating the development of a broad range of advanced fossil energy systems.", + "laborHours": 99788.0, + "languages": [], + "name": "Institute for the Design of Advanced Energy Systems Process Systems Engineering Framework (IDAES PSE Framework) ", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/IDAES/idaes-pse/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaes/idaes-pse", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-31", + "metadataLastUpdated": "2019-09-23" + }, + "description": "The Dac-Man framework identifies, captures and manages change in large scientific datasets, and enables plug-in of domain-specific change analysis with minimal user effort.", + "laborHours": 4316.8, + "languages": [], + "name": "Data Change Management for Scientific Datasets on HPC systems", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dghoshal-lbl/dac-man", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-10-31", + "metadataLastUpdated": "2018-11-01" + }, + "description": "Velo is the domain independent collaboration environment originally created as the basis of the Geological Sequestration Software Suite (GS3) under the Carbon Sequestration Initiative (CSI) LDRD program at PNNL. The enviroment supports teams in performing scientific research including setting up computational models, running simulations, and\nanalyzing/visualizing simulation output.", + "laborHours": 461517.6, + "languages": [], + "name": "pnnl/velo", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/velo", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-11-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software tool, written in R, performs manipulations necessary to translate Human-Earth system model regional/sector emission outputs, such as those from PNNL's Global Change Assessment Model (GCAM), to gridded form needed by Earth System Models, such as DOEs E3SM (Energy Exascale Earth System Model) model. The tool takes as its primary input emissions in a standard community format, and produces CF-compliant netCDF gridded emission as its primary output. As intermediate output the tool produces downscaled emissions at the country level.", + "laborHours": 2508.0, + "languages": [ + "R" + ], + "name": "iiasa/emissions_downscaling", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/iiasa/emissions_downscaling", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-05", + "metadataLastUpdated": "2018-11-05" + }, + "description": "PV TOMCAT predicts the outdoor operating temperature and output power of a PV module based on measured physical properties and outdoor conditions. It includes a ray tracing model of a PV module, which runs in the commercial SunSolve ray tracer. Output from this model is combined with meteorological time series data to produce a combined input file for a finite-element model of heat conduction and radiation. Finally, this finite-element model is run in the commercial COMSOL Multiphysics software, producing time series outputs of temperature and power.", + "laborHours": 349.6, + "languages": [ + "Python" + ], + "name": "PV TOMCAT", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pv_tomcat", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-06", + "metadataLastUpdated": "2021-04-27" + }, + "description": "Gear-SCouP is an analytical model for the rating analysis of articulated spline coupling designs. Articulated splines are commonly used in the planetary stage of wind turbine gearboxes as the means of transmitting the driving torque while also improving load sharing. Direct measurement of spline loads and performance is extremely challenging because of limited accessibility and spline design standards are limited. For a given torque and shaft misalignment, Gear-SCouP quickly yields physical insights into relationships between the spline design parameters and resulting loads, bending, contact, and shear stresses, and safety factors considering various heat treatment methods. Results of this analytical model are compared well against several computational approaches under moderate misalignment. The computational time of Gear-SCouP is significantly less than other FE-based tools.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Gear-SCouP", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GEAR-SCouP", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "sfiligoii@fusion.gat.com" + }, + "date": { + "created": "2018-11-06", + "metadataLastUpdated": "2018-11-09" + }, + "description": "CGYRO is a multi-species spectral gyrokinetic solver with sonic rotation capability. It is an Eulerian GK solver specifically designed and optimized for collisional, electromagnetic, multiscale simulation. A key algorithmic aspect of CGYRO is the radially spectral formulation used to reduce the complicated integral gyroaveraging kernel into a multiplication in wavenumber space, but retaining the ability to treat profile variation important for edge plasmas. This makes it suitable for\nnext-generation computational systems that require high levels of parallel concurrency.\n", + "homepageURL": "http://gafusion.github.io/doc/download.html", + "laborHours": 160496.8, + "languages": [ + "Fortran" + ], + "name": "CGYRO", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://gafusion.github.io/doc/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://gafusion.github.io/doc/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "version": "16.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-07", + "metadataLastUpdated": "2018-11-07" + }, + "description": "The miniGraphics package provides a collection of reference implementations for parallel rendering. In particular, miniGraphics is focused on sort-last parallel rendering, which is the rendering algorithm of choice for HPC rendering. The miniGraphics package provides a collection of simple serial rendering systems and a collection of parallel image compositing methods, which can be combined to test the behavior of parallel rendering under different conditions.", + "laborHours": 42423.2, + "languages": [ + "C++" + ], + "name": "miniGraphics v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniGraphics", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-12", + "metadataLastUpdated": "2019-09-23" + }, + "description": "This is top-level lattice QCD code developed by employees at LBNL and LLNL. It currently compiles on top of the USQCD Chroma software stack. This code contains high-performance routines that are used in our research, and we intend to release this code publicly to ensure reproducibility and to meet our obligations for complying with the DOE Digital Data rules.", + "laborHours": 10822.4, + "languages": [], + "name": "lalibe v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/callat-qcd/lalibe", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-12", + "metadataLastUpdated": "2019-05-28" + }, + "description": "Suite of tools designed to simply data collection, extraction, reduction, and plotting for resonant soft x-ray scattering experiments performed at ALS beamline 4.0.2; speeds up the process of converting data into meaningful information for users to publish experimental results. \n\n* Python software routines for processing CCD images, including reciprocal space maps, diffraction peak alignment, resonant spectral profiles, line-cut comparisons, coordinate transforms, etc. \n* Scan file generator, optimized for typical uses cases, reduces burden on users by handling complex operations behind the scenes of a simplified user interface \n* Deployed at beamline endstation computers; packaged and deployable as standardized PyPI package \n* Under version control (git) and hosted on LBL-sponsored repository (bitbucket)", + "laborHours": 1991.2, + "languages": [], + "name": "ALS/Milo: BL402 RSXD data analysis", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/als.milo/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-11-13", + "metadataLastUpdated": "2018-11-13" + }, + "description": "This software is a C to Verilog converter. However it doesn't just generate any Verilog code, it is intended to generate Verilog code compatible with execution over quantum based D-Wave systems. ", + "laborHours": 410.4, + "languages": [], + "name": "Dwave compatible C to Verilog converter ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/c2verilog", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-13", + "metadataLastUpdated": "2018-11-16" + }, + "description": "TOUGHREACT is a numerical simulation program for chemically reactive non-isothermal flows of multiphase fluids in porous and fractured media. The program is written in Fortran 77 and was developed by introducing reactive chemistry into the multiphase flow code TOUGH2 V2. Interactions between mineral assemblages and fluids can occur under local equilibrium or kinetic rates. The gas phase can be chemically active. Precipitation and dissolution reactions can change formation porosity and permeability, and can also modify the unsaturated flow properties of the rock.\nThe code is distributed with a comprehensive user's guide that includes sample problems addressing geothermal reservoirs and hydrothermal systems, nuclear waste isolation, groundwater quality, sequestration of carbon dioxide in saline aquifers, and supergene copper enrichment. The TOUGHREACT-Pitzer V1.21 package supports the following fluid property modules packaged into TOUGH2 V2.0 (CR-1574): EOS1, EOS2, EOS3, EOS4, EOS7, EOS9, and ECO2N. This version incorporates a Pitzer ion interaction model for application to saline solutions. It is NOT compatible with the most recent TOUGHREACT V2 and relies on the previous TOUGHREACT V1.21.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TOUGHREACT-Pitzer V1.21", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-19", + "metadataLastUpdated": "2019-09-24" + }, + "description": "The TOUGHREACT Pitzer ion-interaction model version was developed based on the previous versions of TOUGHREACT. The main extensions include the Pitzer ion-interaction model for ionic activity calculation of solutions over a broad range of concentrations and the coupling of the vapor-pressure-lowering effect of salinity to phase partitioning.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TOUGHREACT Pitzer Ion-Interaction Model", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-20", + "metadataLastUpdated": "2018-11-20" + }, + "description": "Solves the electromagnetic forward problem for a plane wave or magnetic dipole fields impingent on a set of spherical shells in a whole space of uniform resistivity, relative permeability , and relative permitivity for electric fields and magnetic fields of internal origin at nrcv receivers and nf frequencies. For receivers outside the largest sphere these are standard secondary fields. Results are given in either time or frequency domain. Time domain results allow modelling turn-on or turn-off step function transmitter wave forms, or square pulse and half sine pulse wave funcitons with arbitrary pulse length and repetition rate. Pulses may be either uni-modal or bi-modal (alternating sign each half period).", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 4848.8, + "languages": [], + "name": "timesphere6.f software", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-20", + "metadataLastUpdated": "2020-11-03" + }, + "description": "SCEPTRE solves the linear Boltzmann transport equation for general one-, two- and three-dimensional unstructured-mesh Cartesian geometries. SCEPTRE can handle any particle type for which multigroup-Legendre cross sections are available. However, the code is designed primarily to model the transport of photons, electrons, and positrons through matter. SCEPTRE 2.0 includes several auxiliary packages for pre- and post-processing, regression testing, stochastic radiation transport, thermal radiation transport, and charged-particle transport in the presence of electromagnetic fields. SCEPTRE 2.0 includes sophisticated transport-synthetic acceleration and ray-effects mitigation capabilities.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "SCEPTRE v. 2.0 (Sandia Computational Engine for Particle Transport for Radiat", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 2.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-20", + "metadataLastUpdated": "2019-09-23" + }, + "description": "Software to provide fluid properties, including thermodynamic relationships, transport properties and reaction kinetics, for computational fluid dynamics packages.", + "laborHours": 2114760.8, + "languages": [], + "name": "PelePhysics v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Combustion/PelePhysics", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-21", + "metadataLastUpdated": "2019-09-23" + }, + "description": "The software, PICMI and AMI, establish conventions for the naming and structuring of input files for Particle-In-Cell and particle accelerator simulations.", + "laborHours": 501.6, + "languages": [], + "name": "Particle-In-Cell/Accelerator Modeling Interface", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/atap-ami", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-26", + "metadataLastUpdated": "2018-12-04" + }, + "description": "The md_viscoplastic software is a numerical implementation of the Munson-Dawson material model for rock salt. One inputs a deformation increment, a temperature increment, and the current stress state to md_viscoplastic. It returns the new stress state by numerically integrating ordinary differential equations. ", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "md_viscoplastic v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-11-26", + "metadataLastUpdated": "2018-11-27" + }, + "description": "Systems biology models written in the BioNetGen language often contain parameters that must be fit based on experimental data. PyBioNetFit is a software tool designed to fit parameters of BioNetGen models. The user is expected to provide a BioNetGen model that contains unknown parameters, along with one or more text files containing experimental data. PyBioNetFit will perform a series of calls to the BioNetGen simulator using different parameter sets, to identify the parameter set that best fits the data. The parameter search is dictated by the user's choice of one of several metaheuristic optimization algorithms, including differential evolution, particle swarm optimization, scatter search, and simulated annealing. The software supports parallelized computing on multi-core computers and on computing clusters. We expect this software to be a useful tool for researchers designing BioNetGen models in collaboration with experimentalists.", + "laborHours": 24715.2, + "languages": [], + "name": "PyBioNetFit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PyBNF", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-28", + "metadataLastUpdated": "2021-09-07" + }, + "description": "Radiographic Image Acquisition & Processing Software for Security Markets", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C#", + "WPF" + ], + "name": "X-Ray Toolkit (XTK) v. 3.1.x", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 3.1.x" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-12-18" + }, + "description": "Affect is a module written in the Python language that provides functions for post-processing data that are the result of computer simulations—usually the result of the finite element method—for engineering and physics systems and environments.", + "laborHours": 86275.2, + "languages": [ + "C", + "C++", + "Python", + "Cython" + ], + "name": "Affect v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kevincopps/affect", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2019-01-23" + }, + "description": "This software is a Python package designed to act as an interface between FEniCS and PETSc to facilitate the construction and application of parallel block solvers/preconditioners. The original intent of this software was to help enable Battery and Wind Farm simulations for use on high performance computing systems. The code is written in Python and uses the petsc4py module to access the more advance features of the PETSc Krylov Solver. In essence, pFibs is an interface to make accessing these features more streamlined. Additionally, pFibs also provides a template for building custom Python based preconditioning algorithms. ", + "laborHours": 1276.8, + "languages": [ + "Python" + ], + "name": "Parallel Fenics Implementation of Block Solvers (pFibs)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pfibs", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "This is View3D, version 3.2, a C program for the computation of geometric view factors. This version of View3D is included as part of the EnergyPlus installer package. The program utilizes a number of integration techniques to compute view factors between planar triangles or quadrilaterals in three dimensions.", + "laborHours": 3252.8, + "languages": [ + "C" + ], + "name": "View3D", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/View3D-3.2", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "3.2" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "The Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS) is a co-simulation platform that is currently under development as part of a GMLC project. The High Level Architecture (HLA) is a co-simulation standard, various implementations of which have been widely used for co-simulations for several years, particularly in the defense community. The objective of developing the HELICS-HLA interface is to provide the ability of making software connected with HLA implementations to work with software connected with HELICS. Since each HLA federation is dependent on the RTI being used, the HELICS-HLA interface developed here uses an implementation of the HLA, the Universal CPS Environment for Federation (UCEF), to create this interface. Both HELICS and UCEF are open source software. UCEF-gateway that enables the integration of HELICS and UCEF is also an open source software.", + "laborHours": 1109.6, + "languages": [], + "name": "HELICS-HLA", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GMLC-TDC/HELICS-HLA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "This software is an interface in Python for interacting with EPRI DBus software.", + "laborHours": 182.4, + "languages": [ + "Python" + ], + "name": "PyDBus", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pydbus", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2019-07-10" + }, + "description": "The Distribution Transformation Tool (DiTTo) provides a framework for converting between and modifying several different types of distribution model formats . These include commercial formats such as CYME, Synergi, DEW, ePHASORSIM as well as open source formats such as OpenDSS and GridLAB-D. DiTTo consists of an API which represents electrical equipment, configurations, settings and timeseries data. This API acts as an intermediary between different distribution model formats. Several modules for reading and writing the models connect to this API to facilitate easy conversion between formats. Once feeder models are converted into the intermediate API, analysis can be done on the feeder using a network module. The modification module allows changes to be made to the model in the intermediate API. This allows a clear workflow that supports reading a model from one format, performing analysis, making modifications and writing the model to a different format.", + "laborHours": 62639.2, + "languages": [ + "Python", + "Python" + ], + "name": "DiTTo (Distribution Transformation Tool)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ditto", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2023-08-15" + }, + "description": "Building Energy Simulation Test (BESTEST) is an NREL-developed method to validate the qualitative performance of different whole building simulations engines relative to each other. \nhttps://www.nrel.gov/docs/legosti/old/6231.pdf\n\nFor EnergyPlus® and OpenStudio®, generation of test cases, simulation, and reporting has been a manual or partially automated process that typically took a number of months after a new version of EnergyPlus came out. Building Energy Simulation Test - Generation Simulation and Reporting (BESTEST-GSR) was developed to fully automate this process so it is less error-prone, less time-consuming, and can be quickly run on request for any development branch of EnergyPlus and OpenStudio.\n\nThe initial use case is to directly support OpenStudio and EnergyPlus development, but the software is configured to support use by external software developers that build tools on top of EnergyPlus and/or OpenStudio. Tools built on top of OpenStudio can leverage the test generation, simulation, and reporting, while tools built on EnergyPlus can leverage the test simulation and reporting.\n\nThe model generation is accomplished by running OpenStudio measures for envelope, heating, or cooling test cases. At this stage the specified weather file required for a specific test case is assigned to the model. Simulation is enabled using the OpenStudio Command Line Interface (CLI) to run a series of OpenStudio and Reporting measures to a specified seed model. The specified workflow is defined with an OpenStudio OSW file. The first measure generates the test case model, while the second measure is a reporting measure that runs after the simulation to collect necessary simulation results from the EnergyPlus SQL file. The Reporting stage gathers data from individual OpenStudio OSW files and populates a series of BESTEST Microsoft Excel spreadsheets. BESTEST-GSR also gathers zip files from individual simulations for diagnostic purposes.", + "laborHours": 68339.2, + "languages": [], + "name": "BESTEST-GSR (Building Energy Simulation Test - Generation Simulation and Reporting) [SWR 18-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BESTEST-GSR", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2019-09-24" + }, + "description": "Parallel TOUGH + Hydrate, and other Parallel modules, takes TOUGH code to the next level by enabling parallel processing. TOUGH+ codes can be used for the solution of problems of fluid flow and heat transport in complex geologic media.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Parallel TOUGH+HYDRATE ", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "This tool can be used to enumerate the subdomains associated with a company by aggregating the results of multiple OSINT (Open Source Intelligence) tools.", + "laborHours": 1459.2, + "languages": [ + "Bash", + "Perl", + "Python", + "Ruby" + ], + "name": "Domain Reconniassance Robot (DR. ROBOT) Beta 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/dr_robot", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "Beta 0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "psychrometricsExt is a SkySpark extension that provides a set of psychrometric functions using equations from the ASHRAE Fundamentals handbook.", + "laborHours": 30.4, + "languages": [], + "name": "SkySpark psychrometricsExt ", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/psychrometricsExt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2024-03-11" + }, + "description": "Data structures in Julia to enable power systems analysis. Also, PowerSimulations.jl is a Julia package for power system modeling and simulation found at https://github.com/NREL/PowerSimulations.jl. The objectives of the package are: Provide a flexible modeling framework that can accommodate problems of different complexity and at different time-scales. Streamline the construction of large scale optimization problems to avoid repetition of work when adding/modifying model details. Exploit Julia's capabilities to improve computational performance of large scale power system simulations. The flexible modeling framework is enabled through a modular set of capabilities that enable scalable power system analysis and exploration of new analysis methods. The modularity of PowerSimulations results from the structure of the simulations enabled by the package: Simulations define a set of problems that can be solved using numerical techniques. Problems are generated by expressing model formulations against system data For example, an annual production cost modeling simulation can be created by formulating a unit commitment model against system data to assemble a set of 365 daily time-coupled scheduling problems.", + "laborHours": 8466.4, + "languages": [ + "Julia" + ], + "name": "PowerSystems.jl and PowerSimulations.jl [SWR-18-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PowerSystems.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.15.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-30" + }, + "description": "Solves the Poisson equation on three-dimensional network of line segments, each of uniform material properties, subject to boundary condition forcing.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 121.6, + "languages": [], + "name": "FLUXNET v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-12-03" + }, + "description": "The purpose of the ADAPT code is to generate Dynamic Event Trees (DET) using a user specified set of simulators. ADAPT can utilize any simulation tool which meets a minimal set of requirements. ADAPT is based on the concept of DET which uses explicit modeling of the deterministic dynamic processes that take place during a nuclear reactor plant system (or other complex system) evolution along with stochastic modeling. When DET are used to model different aspects of Probabilistic Risk Assessment (PRA), all accident progression scenarios starting from an initiating event are considered simultaneously. The DET branching occurs at user specified times and/or when an action is required by the system and/or the operator. These outcomes then decide how the dynamic system variables will evolve in time for each DET branch. Since two different outcomes at a DET branching may lead to completely different paths for system evolution, the next branching for these paths may occur not only at different times, but can be based on different branching criteria. The computational infrastructure allows for flexibility in ADAPT to link with different system simulation codes, parallel processing of the scenarios under consideration, on-line scenario management (initiation as well as termination), analysis of results, and user friendly graphical capabilities. The ADAPT system is designed for a distributed computing environment; the scheduler can track multiple concurrent branches simultaneously. The scheduler is modularized so that the DET branching strategy can be modified (e.g. biasing towards the worst case scenario/event). Independent database systems store data from the simulation tasks and the DET structure so that the event tree can be constructed and analyzed later. ADAPT is provided with a user-friendly client which can easily sort through and display the results of an experiment, precluding the need for the user to manually inspect individual simulator runs.", + "homepageURL": "http://www.sandia.gov/adapt", + "laborHours": 0.0, + "languages": [ + "Python 2", + "MySQL" + ], + "name": "ADAPT (Analysis of Dynamic Accident Progression Trees) Revision 5710", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.sandia.gov/adapt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "Revision 5710" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-11-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Unique Building Identification (UBID) for JavaScript\nThis is a line-for-line translation from the Python programming language to the JavaScript programming language of the UBID application programming interface (API): the \"encode\", \"decode\" and \"isValid\" UBID functions. No new functionality is introduced.", + "laborHours": 76.0, + "languages": [ + "Java" + ], + "name": "pnnl/buildingid-js", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid-js", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-11-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Unique Building Identification (UBID) for Ruby\nAn implementation of the Unique Building Identification (UBID) concept for the Ruby programming language. This work is a line-for-line port of the original implementation for the Python programming language (IPID: 31437-E). No new functionality is added.", + "laborHours": 76.0, + "languages": [ + "Ruby" + ], + "name": "pnnl/buildingid-rb", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid-rb", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-12-03", + "metadataLastUpdated": "2018-12-03" + }, + "description": "Code #1 solves the one-dimensional Poisson equation and outputs the band bending poteatial near a metal-semiconductor interface.\nCode #2 uses the output of code #1 and calculates the contact resistivity of the interface.\n", + "homepageURL": "http://www.sandia.gov/nanocarb/research.php", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Band Bending/Contact Resistivity Codes v. 1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.sandia.gov/nanocarb/research.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v1" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-12-03", + "metadataLastUpdated": "2018-12-04" + }, + "description": "pyperc is a Python package for invasion percolation which models multiphase fluid migration in porous \nmedia. The model accounts for capillary pressure, buoyancy, and gravity. Regular and unstructured grids can be used. A tuning parameter can be set to adjust the stochastic nature of the process. Graphics depict fluid migration according to the invasion pressure.\n", + "laborHours": 410.4, + "languages": [ + "Python" + ], + "name": "pyperc v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyperc", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-12-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PostgreSQL histograms for ActiveRecord relations.\nA plugin for the Ruby on Rails (RoR) web application development framework web application development framework that leverages the \"Active Relation\" relational algebra component to automatically formulate SQL statements for the construction of histograms.", + "laborHours": 76.0, + "languages": [ + "Ruby" + ], + "name": "pnnl/pg-histogram", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pg-histogram", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-05", + "metadataLastUpdated": "2018-12-05" + }, + "description": "The software is a flexible architecture used to integrate motors, analog data, digital signals, and instruments together to control scientific experiments and collect data during an experiment. The architecture supports features needed by scientists to quickly add new hardware to an experiment and to take and view data in a meaningful way. It does not perform analysis of the data, but provides basic visualization needed to evaluate the quality of the data as well as the calibration of the system.\n", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 60.8, + "languages": [], + "name": "BCS (Beamline Control System) v2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-12-05", + "metadataLastUpdated": "2023-05-30" + }, + "description": "Alfalfa is a web based software service that implements a virtual building control system using the EnergyPlus simulation as a backend. Conventional building energy simulation is non interactive, meaning that a simulation is started and run to completion without any user input during the simulation. Alfalfa allows a client to start a building simulation, then interactively read sensor locations and dynamically command actuators in realtime. The Alfalfa web service conforms to the Project Haystack standard, which is a specification adopted by many building control system vendors. The service enables Haystack compliant control system vendors to test their control modules and algorithms without the need for a physical building or modifying their hardware and software, enabling faster and cheaper development cycles. Alfalfa has use cases beyond control system testing. One example is building fault detection, where physical building performance can be compared to simulated values in realtime, indicating where there may be a problem in the building. Another use case is informing predictive control systems, where near future events are simulated to premptively guide control decisions in the real building. This software is web based and designed to be self service. Users of Alfalfa can upload an OpenStudio building model and begin communicating with the simulated building without any advanced setup or configuration, as if they were communicating a real building control system. Behind the scenes, Alfalfa makes extensive use of Amazon Web Services, in order to scale from a very small number of users and buildings, to extremely large numbers in a cost effective way.", + "laborHours": 31479.2, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Alfalfa [SWR 18-17]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/alfalfa", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.5.1" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-12-05", + "metadataLastUpdated": "2018-12-06" + }, + "description": "PLUMECALC is a post processor to random walk particle tracking simulations of subsurface solute transport. PLUMECALC takes results of a single particle tracking run without retention processes and incorporates the effects of matrix diffusion or other retention processes for a user-specified solute source.", + "laborHours": 3511.2, + "languages": [], + "name": "PLUMECALC, Version 2.3.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PLUMECALC", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-12-07", + "metadataLastUpdated": "2018-12-10" + }, + "description": "StCUDA is a software package for VisualWorks Smalltalk that contains classes and methods that interfaces Smalltalk to CUDA API's.\nSupporting class StCUDA contains the low level calls to the CUDA API's", + "laborHours": 440.8, + "languages": [], + "name": "StCUDA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/StCUDA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-11", + "metadataLastUpdated": "2019-09-24" + }, + "description": "This code is a set of modules designed to detect certain classes of cyber attacks against equipment in power distribution grid substations, including attacks against transformer tap changers and capacitor bank switches, as well as \"reconnaissance\" attacks against equipment in power grid substations.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1413.6, + "languages": [], + "name": "Analytics for Stream-Processing Architecture for Real-time Cyber-physical Security (Analytic-SPARCS) v0.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-12-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The first step toward the design of good error detection/correction techniques involves an understanding of an application’s vulnerability to soft errors.\nTo study the behavior of iterative methods in the presence of soft errors, we inject errors during the execution of these methods. In particular, we study the impact of one error (single- or multi-bit) on the execution of iterative methods. We use real life datasets from the SuiteSparse Matrix Collection (https://sparse.tamu.edu) and widely used iterative solver library (Iterative Methods Library, IML++ v1.2a). We instrument the iterative solver implementations so that our error injection methodology can control the iteration, vector, position, number of bits and position of the bits of the error injection. We employed 6 solvers and 28 datasets, performed a total of 1,744,800 error injection runs and collected more than 2.5TB data.", + "laborHours": 60.8, + "languages": [], + "name": "pnnl/IMIC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/IMIC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-13", + "metadataLastUpdated": "2019-09-23" + }, + "description": "ButterflyPACK is a mathematical software for rapidly solving large-scale dense linear systems that exhibit off-diagonal rank-deficiency properties. These targeted systems are either matrices arising from discretized boundary integral equations, or frontal matrices in multi-frontal solvers for differential equations. ButterflyPACK relies on low-rank and butterfly formats under Hierarchical matrix, HODLR or HSS frameworks to compress, factor/precondition and solve the linear system in quasi-linear time. ButterflyPACK is particularly useful for large-scale ill-conditioned matrices arising from high-frequency wave equations involving multiple right-hand-sides. \n\nButterflyPACK is based on Fortran 2003, it also has interface written in C++. In addition, ButterflyPACK can be readily invoked from the software STRUMPACK. \n\nButterflyPACK supports hybrid MPI/OpenMP programming models.", + "laborHours": 25931.2, + "languages": [], + "name": "ButterflyPACK", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/liuyangzhuan/ButterflyPACK", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-13", + "metadataLastUpdated": "2020-12-28" + }, + "description": "Neural network was trained on the amino acid sequences of known two-component systems (2CS) pairs. The recommender algorithm uses learned model to select the most likely 2CS pair from an arbitrary set of protein pairs whose amino acid sequences are known.", + "laborHours": 1717.6, + "languages": [], + "name": "Predicting 2CS protein pairs with Deep Learning", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.code.sf.net/p/kinaseorakle/code", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2019-09-23" + }, + "description": "This software implements a new algorithm and its shared-memory parallelization for computing maximum cardinality matchings in bipartite graphs. The algorithm searches for augmenting paths via specialized breadth-first searches (BFS) from multiple source vertices, hence creating more parallelism than single source algorithms.", + "laborHours": 1003.2, + "languages": [], + "name": "Parallel Maximum Cardinality Matchings via Tree-Grafting", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/azadcse/ms-bfs-graft/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2019-09-23" + }, + "description": "Data Elavator allows extensive optimizations, such as overlapping read and write operations, choosing I/O modes, and aligning buffer boundaries. Is as much as 4.2X faster than Cray DataWarp, the start-of-art software for burst buffer, and 4X faster than directly writing to PFS.", + "laborHours": 53473.6, + "languages": [], + "name": "Data Elevator", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/sbyna/dataelevator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "Aluminum is an optimized GPU-aware communication library. It provides a generic Interface to high-performance allreduce algorithms, with support for additional collective operations in progress. Blocking and non-blocking algorithms and GPU-aware algorithms are supported. Aluminum contains custom Implementations and Interfaces to existing optimized communication libraries, exposed through a generic API. ", + "laborHours": 5578.4, + "languages": [], + "name": "Aluminum GPU-aware Communication Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Aluminum", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "Comb is a communication performance benchmarking tool. It is used to determine performance tradeoffs in implementing communication patterns on high performance computing (HPC) platforms. At its core comb runs combinations of communication patterns with execution patterns, and memory spaces. The current set of capabilities Comb provides includes:\no\tConfigurable structured mesh halo exchange communication.\no\tA variety of communication patterns based on grouping messages.\no\tA variety of execution patterns including serial, openmp threading, cuda, cuda batched kernels, and cuda persistent kernels.\no\tA variety of memory spaces including default system allocated memory, pinned host memory, cuda device memory, and cuda managed memory with different cuda memory advice.", + "laborHours": 8071.2, + "languages": [], + "name": "Comb", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Comb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "UEDGE is an interactive suite of physics packages using the Python or BASIS scripting systems. The original (circa 2007) Python version has been supplanted by a version developed under the FACETS SciDAC project [Cary 2008, Mccourt 2012]. The plasma is described by time-dependent 2D plasma fluid equations that include equations for density, velocity, ion temperature, electron temperature, electrostatic potential, and gas density in the edge region of a magnetic fusion energy confinement device. Slab, cylindrical, and toroidal geometries are allowed, and closed Wld open magnetic field-line regions are included. Classical transport is assumed along magnetic field lines, and anomalous transport is assumed across field lines. Multi-charge state impurities can be included with the corresponding line-radiation energy loss. ", + "laborHours": 71576.8, + "languages": [], + "name": "Unified EDGE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/UEDGE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "This project is intended to take a graph and build a smaller (upscaled) graph that is representative of the original in some way. We represent the graph Laplacian in a mixed form, solve some local eigenvalue problems to uncover near-nullspace modes, and use those modes as coarse degrees of freedom.", + "laborHours": 7584.8, + "languages": [], + "name": "GAUSS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gelever/GAUSS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "CKAN plugin for computing and displaying the phase diagram and defect formation energy diagram of a solar cell compound, when given the formation energies and defect formation energies.", + "laborHours": 9408.8, + "languages": [], + "name": "Solar Cell Phase and Defect Formation Energy Diagram", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SC-PD-FED", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "py-hostlist processes slurm-style hostlist strings and can return those strings in manipulated fashion.", + "laborHours": 653.6, + "languages": [], + "name": "py-hostlist", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/py-hostlist", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "SNLS (small non-linear solver) is a C++ library for solving non-linear systems. The emphasis is on small systems on equations for which direct factorization of the Jacobian is appropriate. The systems of equations may be numerically ill-conditioned. Implementation is amenable to GPU usage, with the idea that class instantiate would occur within device functions.", + "laborHours": 699.2, + "languages": [], + "name": "Small Non-Linear Solver", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SNLS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-18" + }, + "description": "SimUtil contains various small utility functions used in multiple HPC simulation codes here at LLNL, such as: simulation parameter input parsing, parallel file-IO, memory allocation, unit parsing, and helper functions for using MPI.", + "laborHours": 3024.8, + "languages": [], + "name": "Simulation Utility Library for HPC codes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/simutil", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-18" + }, + "description": "VPIC I/O Utilities provide scalable input and output code for writing and reading HDF5 data by the Vector Particle-in-cell (VPIC) simulation codes. The I/O utility writes particle, field, and hydro data from VPIC to HDF5 files. The filed and hydro codes also write XDMF files, which can be used by visualization tools such as ParaView to read and visualize the HDF5 data written.", + "laborHours": 744.8, + "languages": [], + "name": "VPIC IO utilities", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/dbin_sdm/viou/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-18" + }, + "description": "Cardioid is a cardiac multiscale simulation suite spanning from subcellular mechanisms up to simulations of organ-level clinical phenomena. The suite contains tools for simulating cardiac electrophysiology, cardiac mechanics, torso-ECGs, cardiac meshing and fiber generation tools.", + "laborHours": 161834.4, + "languages": [], + "name": "Cardioid", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/cardioid", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-18" + }, + "description": "MemSurfer is a software tool to compute bilayer membrane surfaces. These surfaces are found in the biophysical simulations, and generally analyzed using a set of python packages. MemSurfer offers new robust functionalities to compute the undulations in the surfaces, and relevant properties of the lipids *along* the surface, rather than along the projections, as done in many existing tools.", + "laborHours": 4088.8, + "languages": [], + "name": "MemSurfer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MemSurfer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Paracousti simulates 3-D acoustic wave propagation in fixed (non-moving) complex media. It solves the linear acoustic equations of motion using the velocity-pressure system of first order linear differential equations on a finite-difference Cartesian grid using Newton’s law of motion and mass continuity equations. It also has the ability to incorporate acoustic attenuation to simulate non-recoverable energy losses via the velocity-memory-pressure system of linear differential equations. We assume stationary, non-heat conducting, adiabatic media (fluid) where the background sound speed and material density are fixed in time. Capabilities include massively parallel design, optimization for high contrast media interfaces, inclusion of arbitrary pressure and force sources defined by the user, inclusion of arbitrary pressure and velocity receivers defined by the user, acoustic wavefield snapshots in time for visualization, and convolutional perfectly matched layers to minimize artificial grid boundary reflections. Paracousti was built upon the foundational framework of TDAAPS (Time-Domain Atmospheric Acoustic Propagation Suite) by Neill Symons, Dave Aldridge, and Leiph Preston.", + "laborHours": 29488.0, + "languages": [ + "C++", + "C", + "MATLAB", + "Makefile", + "JavaScript" + ], + "name": "Paracousti v. 2.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Paracousti", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 2.0.0" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2019-04-17" + }, + "description": "The QuarkNet Data Acquisition (DAQ) circuit board is provided in a kit that includes a power supply, GPS capability with temperature sensor and cabling, and a USB link to the user’s computer. The DAQ circuit board has 4 analog discriminator inputs and produces trigger time and pulse edge time data for 1- to 4-fold coincidence levels. The DAQ then checks for user-defined trigger multiplicity across the four inputs. If the pulses satisfy the trigger requirement, the DAQ encodes time information for each input. Timing on the DAQ is done with a local clock synchronized to GPS time (via local module) once per second. This gives local times of nearly one nanosecond precision recorded with the accuracy inherent in GPS time. The DAQ kit is equipped to measure ambient temperature and atmospheric pressure; it also can determine its latitude and longitude from the GPS unit. A laptop or desktop computer connects to the DAQ via USB for control and collection of formatted raw data. ", + "homepageURL": "http://quarknet.fnal.gov/toolkits/ati/fnaldet.html", + "laborHours": 0.0, + "languages": [ + "C", + "VHDL" + ], + "name": "QuarkNet DAQ Kit", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://partnerships.fnal.gov/licensing", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://quarknet.fnal.gov/toolkits/ati/fnaldet.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2020-05-27" + }, + "description": "The Umpire library consists of a collection of software components that provide memory and resource management capabilities that can be used by diverse high performance computing (HPC) applications. The current set of capabilities that Umpire provides Includes: \n•\tFlexible allocators to provision memory In the range of available memory resources on a target system.\n•\tAn extensible allocation strategy model, allowing custom algorithms to be used to allocate memory resources in a scalable and high­performance fashion.\n•\tMemory-location aware operations that can be used to migrate and modify memory using specialized functions dependent on source and target data locations\n•\tA set of Introspection capabilities to allow the user to query the state of the different allocators and memory allocations.", + "laborHours": 30096.0, + "languages": [], + "name": "Umpire", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Umpire", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-20" + }, + "description": "4.Brief Description:\nThis is a LAMMPS extension (LAMMPS \"fix\") to capture electron-ion interaction. We use this extension mechanism to generalize the two­\ntemperature model to include electron-phonon coupling. The extension is flexible enough to represent cascades, laser heating and equilibration and study energy transport with realistic electron-phonon coupling. ", + "laborHours": 1444.0, + "languages": [], + "name": "Electron-phonon dynamics for LAMMPS ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/USER-EPH", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2019-06-26" + }, + "description": "The non-routine event (NRE) detection and adjustment module provides algorithms to detect and to adjust changes in energy use that are not attributable to installed efficiency measures, and not accounted for in the baseline model's independent variables. The detection algorithm is based on statistical change point algorithm and the adjustment uses a data driven approach to quantify the changes in the energy use that are induced by the NRE.", + "laborHours": 653.6, + "languages": [], + "name": "Non-Routine Event Detection and Adjustment (NRE) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/nre", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-19" + }, + "description": "The Replicative Assessment of Spectroscopic Equipment (RASE) methodology is a semi-empirical approach to generating synthetic gamma-ray spectra for injection into a radionuclide identification algorithm of a vendor-provided detection system. RASE facilitates studies of the spectroscopic device performance and a quantitative assessment of its capabilities to correctly distinguish and identify isotopes of interest in realistic scenarios.", + "laborHours": 4088.8, + "languages": [], + "name": "RASE OSS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RASE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-20" + }, + "description": "CryoH2Vehicle enables to simulate the variations of the thermodynamic states of H2 inside nn onboard vessel, that undergoes n given duty cycle (park/drive/fill). Typical states of charge and boil-off losses can thus be estimated. ", + "laborHours": 380.0, + "languages": [], + "name": "Cryogenic H2 vehicle simulation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/cryoH2vehicle", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-19" + }, + "description": "The software Is an application for Oelta3D, QT and OpenSceneGraph, all of which are external open source software.", + "laborHours": 2447.2, + "languages": [], + "name": "Open Facility Viewer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Open-Facility-Viewer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-19" + }, + "description": "Using machine learning to score potential drug candidates may offer an advantage over traditional imprecise scoring functions because the parameters and model structure can be learned from the data. However, models may lack interpretability, are often overfit to the data, and are not generalizable to drug targets and chemotypes not in the training data. Benchmark datasets are prone to artificial enrichment and analogue bias due to the overrepresentation of certain scaffolds in experimentally determined active sets. Datasets can be evaluated using spatial statistics to quantify the dataset topology and better understand potential biases. Dataset clumping comprises a combination of self-similarity of actives and separation from decoys in chemical space and is associated with overoptimistic virtual screening results. This code explores methods of quantifying potential biases and examines some common benchmark datasets.", + "laborHours": 304.0, + "languages": [], + "name": "Small Molecule Evaluator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SmallMolEval", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-19" + }, + "description": "An agent-based simulation of the innate immune response to bacterial infection.", + "laborHours": 1124.8, + "languages": [], + "name": "Innate Immune Response Agent-based Model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/iirabm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-20" + }, + "description": "ADaPT Is a software library that Is used for mixed preclsk>n ftoatln1 point analysis.", + "laborHours": 456.0, + "languages": [], + "name": "Algorithmic Differentlation Applied to Floating-Point Precision Tuning", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/adapt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-20" + }, + "description": "NLPVis is a visualization system that, through a tight yet flexible integration between visualization elements and the underlying model, allows a user to interrogate the modal by perturbing the input, internal state, and prediction while observing changes. ", + "laborHours": 6551.2, + "languages": [], + "name": "NLPVis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/shusenl/nlpvis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-20" + }, + "description": "Sequedex is computer software to rapidly assign phylogeny and function to short sequences of nucleic acid or protein. In addition, Sequedex comprises functions required to generate underlying data modules as well as tools for analyzing assignments in a variety of contexts.", + "laborHours": 8724.8, + "languages": [], + "name": "Sequedex V2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/sequedex-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-12-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL grid related applications\nObject oriented design intended to facilitate reuse and extensibility of system features. The template enforces that needed structure and behaviors are available. Users may inherit and adapt these structures and behaviors to meet their specific requirements. Recognizes separation of the transactive system calculations into (1) scheduling of assets, (2) balancing of\nsupply and demand, and (3) coordination among independent agents. This separation facilitates useful computation boundaries in which computations can be completed without requiring end-to-end communication for each update. The code provides fundamental market solutions for balancing. The code provides mechanisms for inter-agent coordination. Allows event-driven agent interactions; not limited to prescribed time intervals. Aggregates value and electricity at nodes and conveys opportunities up and down through the network.", + "laborHours": 8952.8, + "languages": [], + "name": "VOLTTRON/volttron-GS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron-GS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-02", + "metadataLastUpdated": "2025-03-26" + }, + "description": "The software is a simplified method for modeling the impact of arbitrary partial shading conditions on PV array performance.\nThe software implements a simple method for modeling shade loss: a database of shade impact results (loss percentages), generated using a validated, detailed simulation tool and encompassing a wide variety of shading scenarios. The database is intended to predict shading losses in crystalline silicon PV arrays and is accessed using basic inputs generally available in any PV simulation tool. Performance predictions using the database are within 1-2% of measured data for several partially shaded PV systems, and within 1% of those predicted by the full, detailed simulation tool on an annual basis. The shade loss database shows potential to considerably improve performance prediction for partially shaded PV systems.", + "homepageURL": "https://github.com/NREL/ssc/blob/develop/shared/lib_pv_shade_loss_mpp.cpp", + "laborHours": 2204.0, + "languages": [ + "C++" + ], + "name": "PV Shading Database [SWR-16-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ssc/blob/develop/shared/lib_pv_shade_loss_mpp.cpp", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-01-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "HyperNetX is a Python library of classes, algorithms, and generators for working with multi-way and nested relational data. Given a network of nodes and relationships, the base class HyperNetX.Entity is used to instantiate individual data elements along with their relationships to other elements of the network. By exploiting Python's dictionary data structure we capture both multi-way and nested data structures with constant time lookup. The base class HyperNetX.Hypergraph instantiates a network of this data into a hypergraph structure. Many of the common metrics and features of graphs, such as diameter, connectedness, and clustering coefficient, have analogous definitions with respect to hypergraphs, which are computed using algorithms in the HyperNetX library.", + "laborHours": 14789.6, + "languages": [ + "Python" + ], + "name": "pnnl/HyperNetX", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/HyperNetX", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-04", + "metadataLastUpdated": "2023-11-02" + }, + "description": "Keras layers for end-to-end learning on molecular structure. Based on Keras, Tensorflow, and RDKit. Source code used in the study Message-passing neural networks for high-throughput polymer screening. SEE ALSO https://github.com/NREL/alfabet", + "laborHours": 866.4, + "languages": [ + "Python" + ], + "name": "ALFABET™ and nfp (Neural Fingerprint) [SWR-19-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/nfp", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-07", + "metadataLastUpdated": "2019-01-08" + }, + "description": "The Anno log annotation system provides tools for creating and querying annotations to supercomputing log data.", + "laborHours": 1109.6, + "languages": [], + "name": "Anno v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/agreiner/anno", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-08", + "metadataLastUpdated": "2019-09-23" + }, + "description": "Implementation of a flexible Grazing Incidence Small-Angle Scattering (GISAXS). Simulation code based on the Distorted Wave Born Approximation (DWBA) theory that effectively utilizes the parallel processing power provided by graphic processors and multicore processors. This constitutes a handy tool for experimentalists facing a massive flux of data, allowing them to accurately simulate the GISAXS process and analyze the produced data. The software computes the diffraction image for any given super position of custom shapes or morphologies in a user-defined region of the reciprocal space for all possible grazing incidence angles and in-plane sample rotations. This flexibility then allows to easily tackle a wide range of possible sample structures such as nanoparticles o top of or embedded in a substrate or a multilayered structure. In cases where the sample displays regions of significant refractive index contrast, an algorithm has been implemented to perform a slicing of the sample along the vertical direction and compute the averaging refractive index profile to be used as the reference geometry of the unpertubed system. Preliminary tests show good agreement with experimental data for a variety of commonly encountered nanostructures.", + "laborHours": 20033.6, + "languages": [], + "name": "HipGISAXS", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/hipgisaxs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-08", + "metadataLastUpdated": "2021-08-05" + }, + "description": "This is an open-source, empirical data-driven, virtual building energy analysis and retrofit targeting tool. The open-source tool will provide a fully-automated, \"no-cost/no-touch\" approach to screen large volumes of buildings for operational improvement and equipment upgrade opportunities and quantify associated potential energy and cost savings.", + "laborHours": 1292.0, + "languages": [], + "name": "Building Efficiency Targeting Tool for Energy Retrofits (BETTER) Analytical Engine", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-JCI-ICF/BETTER", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-09", + "metadataLastUpdated": "2019-06-26" + }, + "description": "Research Network Transfer Performance Predictor (netperf-predict) v 0.9", + "laborHours": 152.0, + "languages": [], + "name": "Research Network Transfer Performance Predictor (netperf-predict) v 0.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/tstat-dtn-analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "0.9" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-01-09", + "metadataLastUpdated": "2019-03-25" + }, + "description": "AIMFAST is a software code used to align facets on a dish or heliostat solar concentrator to a specific aimpoint strategy to minimize peak fluxes and maximize system optical performance. AIMFAST uses a large monitor or projection screen to display fringe patterns, and a machine vision camera to image the reflection of these patterns in the subject dish mirrors. From these images, a detailed map of surface normals can be generated and compared to design or fitted mirror shapes. This fitted comparison is then used to develop a single vector representing the orientation of the facets relative to the design orientation and provide near-real-time adjustment information to a communicating computer. The communicating computer can display adjustments or directly interface with adjustment tools. ", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 4879.2, + "languages": [ + "MATLAB" + ], + "name": "Alignment Implementation for Manufacturing using Fringe Analysis Slope Technique (AIMFAST) 2018.11.20", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "2018.11.20" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-09", + "metadataLastUpdated": "2019-01-15" + }, + "description": "The CBES API provides Application Programming Interface to a suite of functions to improve energy efficiency of buildings, including building energy benchmarking, preliminary retrofit analysis using a pre-simulation database DEEP, and detailed retrofit analysis using energy modeling with the EnergyPlus simulation engine. New capabilities in version 2.0 include renewable technologies (PV, storage), advanced HVAC systems, demand response measures, TDV (Time Dependent Valuation energy) metrics, as well as shading from adjacent buildings, trees or roof obstructions. The CBES API is used to power the LBNL CBES Web App. It can be used by third party developers and vendors.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1501972.8, + "languages": [], + "name": "Commercial Building Energy Saver, API (CBES API) v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-01-09", + "metadataLastUpdated": "2019-03-25" + }, + "description": "SOFAST is used to characterize the surface slope of reflective mirrors for solar applications. SOFAST uses a large monitor or projection screen to display fringe patterns, and a machine vision camera to image the reflection of these patterns in the subject mirror. From these images, a detailed map of surface normals can be generated and compared to design or fitted mirror shapes. SOFAST uses standard Fringe Reflection (Deflectometry) approaches to measure the mirror surface normals. SOFAST uses an extrinsic analysis of key points on the facet to locate the camera and monitor relative to the facet coordinate system. It then refines this position based on the measured surface slope and integrated shape of the mirror facet. The facet is placed into a reference frame such that key points on the facet match the design facet in orientation and position. This is key to evaluating a facet as suitable for a specific solar application. SOFAST reports the measurements of the facet as detailed surface normal location in a format suitable for ray tracing optical analysis codes. SOFAST also reports summary information as to the facet fitted shape (monomial) and error parameters. Useful plots of the error distribution are also presented.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 10822.4, + "languages": [], + "name": "Sandia Optical Fringe Analysis Slope Tool (SOFAST) v. 2018.11.20", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 2018.11.20" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-11", + "metadataLastUpdated": "2019-01-15" + }, + "description": "The CBES App is a web-based toolkit for use by small businesses and building owners and operators of small and medium size commercial buildings to perform energy benchmarking and retrofit analysis for buildings. 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The model efficiently describes Li diffusion dynamics in active material and electrolyte phases, charge transfer kinetics, charge balance, and electron transport processes. The model requires a separate pre-processing step to identify SVM parameters.\n", + "homepageURL": "https://www.nrel.gov/workingwithus/licensing.html", + "laborHours": 0.0, + "languages": [ + "C", + "MATLAB" + ], + "name": "State-variable model of porous electrode batteries 1-D electrochemical/thermal behavior", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrel.gov/workingwithus/licensing.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrel.gov/workingwithus/licensing.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-23", + "metadataLastUpdated": "2019-01-25" + }, + "description": "This computer software is a MATLAB standalone code for implementation of the Lumped Particle Domain model. 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Physico-chemical states of batteries are also evaluated by the model.", + "homepageURL": "https://www.nrel.gov/workingwithus/licensing.html", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "ED-LPD, MATLAB standalone", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrel.gov/workingwithus/licensing.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrel.gov/workingwithus/licensing.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2019-01-23", + "metadataLastUpdated": "2023-03-07" + }, + "description": "The code extrapolates the nearest neighbor particle spacing and sizing from collected X-ray images. The profiles are directly interpretable for non-destructive imaging of large imaging datasets that span the micron to millimeter size scale.", + "laborHours": 0.0, + "languages": [], + "name": "COMPACT", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/idaholabresearch-compact", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-23", + "metadataLastUpdated": "2023-12-13" + }, + "description": "The REopt® techno-economic decision support platform is used by NREL researchers to optimize energy systems for buildings, campuses, communities, microgrids, and more. 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The model is now also used to optimize the size and operating strategy of microgrids, storage, and energy/water systems.", + "homepageURL": "https://reopt.nrel.gov", + "laborHours": 130932.8, + "languages": [], + "name": "REopt® [SWR-12-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://reopt.nrel.gov/contacts.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://reopt.nrel.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-01-24", + "metadataLastUpdated": "2024-07-26" + }, + "description": "https://www.osti.gov/doecMatMCNP is a code for generating material cards for the MCNP radiation transport code. The program allows for material specification as either atomic or weight percent (fractions). MatMCNP also permits the specification of enriched lithium, boron, and/or uranium. In addition to producing the material cards for MCNP, the code calculates the atomic (or number) density in atoms/barn-cm as well as the multiplier that should be used to convert neutron and gamma fluences into dose in the material specified.", + "laborHours": 4544.8, + "languages": [ + "Fortran", + "Python" + ], + "name": "MatMCNP v. 4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MatMCNP", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 4.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-24", + "metadataLastUpdated": "2019-01-24" + }, + "description": "An algorithm that infers the reaction SMARTS pattern for a biochemical reaction, given an atom-atom mapped reaction input. The algorithm can create patterns of variable specificity, depending on user needs. The SMARTS patterns can be used to computationally assess hypothetical biochemical reactions that would generate hypothetical or novel compounds. If all known compounds are run through all known SMARTS, a theoretical biochemical reaction network could be formed for biological discovery purposes.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 866.4, + "languages": [], + "name": "Automated Biochemical Reaction Coder (Reactionizer) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-01-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Generate random global temperature fields with spatial and temporal correlation derived from an ESM\nAs of version 2.0, fldgen allows to emulate any climate variable, not just ones that are approximately normally distributed, and it allows us to emulate climate variables in combinations, such as temperature and precipitation. These new capabilities can be used for risk modeling in areas such as drought and it agricultural impacts, where both temperature and moisture play a role.", + "laborHours": 988.0, + "languages": [], + "name": "JGCRI/fldgen", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/fldgen", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-25", + "metadataLastUpdated": "2019-01-31" + }, + "description": "The software is for detecting and identifying anomalies within gamma-ray spectra. The design enables quick implementation, testing, comparison, and deployment of different anomaly and identification algorithms. The software currently contains implementations of four algorithms, two of which are common place within the field, and two that novel research products from this effort.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 3815.2, + "languages": [], + "name": "Berkeley Anomaly Detection (BAD) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-28", + "metadataLastUpdated": "2019-01-29" + }, + "description": "PhyCA allows interpretation of a PhyloChip assay. 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The software depends on other software to be installed on the same machine as PhyCA.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1352.8, + "languages": [], + "name": "PhyCA-PhyloChip Analysis", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-28", + "metadataLastUpdated": "2019-01-29" + }, + "description": "The National Renewable Energy Laboratory, NREL and Argonne National Laboratory, ANL are creating an open-source situational awareness and decision support platform called WindView that provides grid operators with knowledge on the state and performance of wind power on their system. 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Once complete, it will be publicly available for industry and academic researchers.", + "laborHours": 9971.2, + "languages": [ + "JavaScript", + "css", + "html" + ], + "name": "WindView", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/windview/client", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-30", + "metadataLastUpdated": "2019-02-01" + }, + "description": "TOUGHREACT V3.32 is a 3-D reactive transport code that handles to non-isothermal, multiphase/multicomponent fluid flow, heat transport, aqueous and gaseous species advection-diffusion, and equilibrium/kinetic water-gas-rock-biological reactions. 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This request is to re-license the flux framework in full to LGPLv3 to better support vendor collaboration and allow use of external apache2 and similarly licensed libraries.\nflux is a framework for writing resource managers as well as a resource manager for HPC systems. It allows for hierarchical nesting and providing a portable interface for job scheduling across systems.", + "laborHours": 118028.0, + "languages": [], + "name": "Flux Resource Manager Framework", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/flux-framework/flux-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-01-31", + "metadataLastUpdated": "2019-02-01" + }, + "description": "Sonar contains software for managing a HPC performance-monitoring software stack. This includes streaming data into a distributed Kafka message queue, storing/querying from a distributed Cassandra database, and front-end tools for secure access, visualization, and analytics of facility-wide performance data.", + "laborHours": 790.4, + "languages": [], + "name": "Sonar", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sonar-driver", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-01", + "metadataLastUpdated": "2019-02-01" + }, + "description": "The invention simulates multi-dimensional, multi-phase, multi-component, non-isothermal flow and transport in fractured porous media, with applications in geosciences and reservoir engineering among others. The invention supports a number of different combinations of fluids and components from previous software versions.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TOUGH3 v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-02-04", + "metadataLastUpdated": "2019-02-05" + }, + "description": "The Hydrogen Dispenser Test Apparatus (HDTA) is used to validate hydrogen fueling station performance. This software takes the data generated from HDTA and compares it to fueling standards CSA HGV4.3 and SAE J2601. The software generates plots and metrics for pressure, temperature and IR communications from the HDTA.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "HDTADA", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HDTADA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "nlogan@pppl.gov" + }, + "date": { + "created": "2019-02-07", + "metadataLastUpdated": "2019-02-12" + }, + "description": "The Generalized Perturbed Equilibrium Code (GPEC) package contains a suite of non-axisymmetric stability and perturbed equilibrium force balance codes including DCON/RDCON/STRIDE (stability), GPEC (driven plasma response), and PENTRC (NTV torque). The perturbation calculations can optionally use ideal MHD throughout, kinetic MHD throughout, or a mix of ideal MHD outer layer and resistive MHD inner layer physics at the rational surfaces. \n\nEarlier versions of this software contained only the ideal MHD model, and results were published under the name of the Ideal Perturbed Equilibrium Code (IPEC).\n\nPrimary journal citations can be found on the landing page.", + "homepageURL": "http://princetonuniversity.github.io/GPEC", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Generalized Perturbed Equilibrium Code", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://princetonuniversity.github.io/GPEC", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://princetonuniversity.github.io/GPEC", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "version": "1.2" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-02-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A tool for inferring and analyzing forecast-guided dam and reservoir operations", + "laborHours": 410.4, + "languages": [], + "name": "IMMM-SFA/horizon", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/horizon", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-02-08", + "metadataLastUpdated": "2019-03-22" + }, + "description": "Resonance Control GUI for LCLS-II ResCtl System is a Qt5-based, python GUI used for interacting with an LCLS-II resonance control system for an 8-cavity cryomodule. The code is written in Python, and can use auxiliary software Qt5, pyqtgraph, numpy, and scipy. The code is operating system-agnostic, has no specific hardware requirements, and has no embedded source code.", + "homepageURL": "http://pip2.fnal.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Resonance Control GUI for LCLS-II ResCtl System", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://pip2.fnal.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-08", + "metadataLastUpdated": "2019-04-29" + }, + "description": "(based on Erbilgin et al., BMC Bioinformatics, 2017, 18:57). Mixed cultures of microbial species are increasingly used to carry out a specific task in lieu of engineering a single microbe to do the same task. However, knowing how different species' metabolisms will integrate to reach a desired outcome is a difficult problem that has been studied in great detail--but only using steady-state models. Mixed cultures used for biotechnology processes, as well as microbial communities that exist in nature and crop agriculture, are metabolically dynamic systems. Studying the temporal substrate utilization by individuals is individuals in mixed cultures is an important first step in developing approaches to better model these biochemical processes and microbial communities found in nature. \n\nThe 2017-004 software is comprised of four custom iPython notebooks that were used for all computational tasks in the experimental work described in \"Dynamic substrate preferences predict metabolic properties of a simple microbial consortium\" (Erbilgin et al., BMC Bioinformatics, 2017). The results indicate that a significant portion of a model community's overall metabolism can be predicted based on the metabolism of the individuals. The results further suggest that, when the mixed culture's substrate depletion significantly deviates from such a prediction, this may highlight potential metabolic pathways affected by species-species microbial interactions, leading to hypotheses about how a particular microbial community's structure and function may be modulated to perform a particular biotechnological goal.", + "laborHours": 501.6, + "languages": [], + "name": "Predicting Coculture Substrate Depletion (PCSD) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biorack/bmc_bioinf_2016_erbilgin", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-08", + "metadataLastUpdated": "2019-02-19" + }, + "description": "\tWith the benefit of hindsight, it is easy to see that the readout of the human genome, spectacular milestone that it was, represents only the beginning of the \"omics\" information explosion. The technical side of the 'omics explosion--enabling researchers to efficiently readout terabytes of information spelling out whole genomes, transcriptomes, proteomes and metabolomes, does not per se provide a clear picture of how life works. Nor does it show us how we can engineer biology to solve the grand challenges of the 21st century: feeding 10 billion people with declining per capita supplies of arable land and clean water, sustaining biological diversity and slowing the increase in greenhouse gas formation, primarily carbon dioxide and methane. \n\nThe 2017-063 invention--Metabolites and Genes Integration Technology--proposes an integrated approach to correcting and connecting the dots of the 'omics explosion: linking genes to proteins, proteins to pathways, pathways to biochemical reactions and metabolites. The '063 invention is potentially transformational in that it can generate testable hypotheses across thousands of genes to predict their chemical and metabolic products. It can also do the reverse; i.e., starting from chemical and metabolic products it can generate testable hypotheses about which genes and pathways those molecules are linked to. Since we know that genomic, transcriptomic, proteomic and metabolomic databases are chock full or erroneous information, MAGI also has the unique benefit of correcting these errors through its own independent pathway of bidirectional hypothesis generation (genes=>proteins=>metabolites + metabolites=>proteins=>genes). Perfectly amenable to high-throughput hypothesis generation and experimentation, MAGI can transform our understanding of human, animal, plant and microbial biology over several decades, laying the essential knowledge foundation to addressing the grand scientific challenges of the 21st century.", + "laborHours": 1352.8, + "languages": [], + "name": "Metabolites Annotations and Genes Integrated (MAGI) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biorack/magi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-08", + "metadataLastUpdated": "2019-04-29" + }, + "description": "AERCalc is a software tool for evaluating the energy performance of window attachments (e.g., shading systems, attached window panels, etc.). All the annual energy modeling is performed by the EnergyPlus OS engine. The program incorporates a user-friendly GUI.", + "laborHours": 67564.0, + "languages": [], + "name": "AERCalc v1.2.10", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/AERCalc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "1.2.10" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-02-11", + "metadataLastUpdated": "2019-02-11" + }, + "description": "OpenDSSDirect.jl is a cross-platform Julia package implements a \"direct\" library interface to OpenDSS using dss_capi. OpenDSS is an open-source distribution system simulator. See OpenDSSDirect.py for a similar package in Julia.\n\nThis package is now available for Windows, Mac, and Linux.", + "laborHours": 7022.4, + "languages": [ + "Julia" + ], + "name": "OpenDSSDirect.jl", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dss-extensions/OpenDSSDirect.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-02-12", + "metadataLastUpdated": "2019-03-22" + }, + "description": "Skybright is a utility to estimate the sky brightness in images of the sky taken by optical astronomical telescopes. It uses a simple three component model, including airglow, scattered moonlight, and twilight. The code is derived from an extraction of the sky estimation code in obstac, the telescope scheduling code used by the Dark Energy Survey (written by the same author).", + "laborHours": 395.2, + "languages": [ + "Python" + ], + "name": "skybright", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ehneilsen/skybright", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-02-12", + "metadataLastUpdated": "2019-02-13" + }, + "description": "Enable developers to run the Granta MI Scripting Toolkit (MSTK) within a docker container. Developers who work with the MSTK can use this tool to test their code on various operating systems, as well as load custom Python libraries as desired. This can help to replicate an environment as close to production as possible. The MSTK does not officially support macOS, as such this docker project allows macOS users to quickly spin up an environment to develop with the toolkit without the need to use a dedicated VM.", + "laborHours": 106.4, + "languages": [], + "name": "mstk-docker", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mstk-docker", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-02-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "In order to support different hardware configurations, an extensible and modular software architecture was developed that could adapt to new requirements in an agile manner. This led to the design of an application programming interface or software development kit that would allow for the rapid integration of new hardware plugins, including AMPS, MIPS, and National Instruments, along with support for digitizers from vendors such as Acqiris. The use of ZeroMQ and a simple communication protocol allows for real time data display and analysis. This is achieved via a separate application simply called the AgMD1 Console. This application allows for low level foreign function interface (FFI) calls to the AGMD1 libraries to operate the U1084A analog-to-digital converter.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Falkor Data Station", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/business/default.aspx?topic=Licensing_Guidelines", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-02-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The acquisition of analog signal from a time of flight mass spectrometer requires robust, efficient, and fast software. Writing multi-threaded applications is inherently more challenging due to the potential for livelocks, deadlocks, and race conditions. Rust was identified as a \"safe\" language that has a compiler that statically checks the code for these potential problems and prevents compilation entirely if detected. Rust is a systems level language, on par with C / C++. However, it supports a thriving package management system similar to npm or NuGet and has other modern features which make it accessible for rapid prototyping and simplifies compilation procedures.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Falkor 'Rust' Acquisition Module", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/business/default.aspx?topic=Licensing_Guidelines", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-02-19", + "metadataLastUpdated": "2019-02-20" + }, + "description": "nSnare™ analyses and categorizes log messages generated by various and customizable third party software packages using a custom multi-tiered rules engine. Each log message is either determined to be a false positive, or it is assigned a score based on the severity of the potential attack and confidence that the activity described by the log message is not a false positive. Log messages are then assigned to an event, which is a collection of log messages related to a single potential attack. Meta-analysis rules run on the collection of all logs within an event to correlate multiple related logs into a single known attack signature. When the sum of the scores of all logs within an event exceeds a pre-defined threshold, the event is labelled as an attack and an automated response is generated to block the attacker from connecting to any protected resources, called quarantining within the application, for a variable length of time. The length of time that the quarantine lasts for is based on the severity and frequency of the attack, along with historical information on the attacker and any third party provided threat intelligence data that the system has gathered. An additional random length of time is added to each quarantine so the algorithm cannot easily be learned and bypassed by a persistent attacker. A confidence score is generated based on a proprietary algorithm that determines the likelihood that the data which lead to the attacker getting quarantined was a false positive. A threat intelligence record is created for each detected attack, with details on the attacker, a summary of what triggered the quarantine, the severity of the attack and the confidence the system has that the attack is not the result of false data, which can then be shared with external entities so that they can also protect themselves from a related attack.\n\nThe software also includes a web based front end for analyzing the current quarantined attacks, removing a quarantine in the case of a false positive, viewing previously quarantined attacks, and tracking suspicious activity that the system is currently evaluating. The web interface also allows the creation and modification of rules used by the rules engine, and the maintenance of a whitelist of known good systems that should never be automatically quarantined.\n", + "homepageURL": "https://www.labpartnering.org/lab-technologies/09425b12-3332-4a90-892d-44dbb8e1be34", + "laborHours": 0.0, + "languages": [], + "name": "nSnare™", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.labpartnering.org/lab-technologies/09425b12-3332-4a90-892d-44dbb8e1be34", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.labpartnering.org/lab-technologies/09425b12-3332-4a90-892d-44dbb8e1be34", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-25", + "metadataLastUpdated": "2019-05-31" + }, + "description": "WINGRIDDER V3.0 is a Windows-based software for designing and generating numerical grids for numerical simulators that are based on the \"integral finite difference\" or the \"control volume\" numerical scheme (e.g., TOUGH2, Pruess et al., 1996). The user can design and generate grid that properly represents the stratigraphic features, inclined faults, and repository. WINGRIDDER V3.0 is an upgrade from WINGRIDDER V2.0. This revision includes testable requirements as listed in the Requirements Document (RD), 10024-RD-3.0-00, Section 2. With new features, WINGRIDDER V3.0 adds the ability to generate a multiple-interactive-continuum (MINC) grid.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "WinGridder-A graphic grid generator for TOUGH2 simulators (WinGridder) v3.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-02-26", + "metadataLastUpdated": "2019-03-22" + }, + "description": "TRACE is a debugging and logging utility written in C/C++, perl, and shell", + "homepageURL": "https://cdcvs.fnal.gov/redmine/projects/trace", + "laborHours": 0.0, + "languages": [ + "C", + "C++" + ], + "name": "TRACE", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cdcvs.fnal.gov/redmine/projects/trace", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-02-27", + "metadataLastUpdated": "2019-02-27" + }, + "description": "PYB11Generator is a code generator to simplify using the open-source pybind11 package for interoperability between C++ and Python. PYB11Generator parses a description of the C++ code to be exposed to Python written in pure Python syntax, and generates the pybind11 C++ coding which can be compiled into a shared library allowing the C++ code to be used from Python. The purpose of PYB11Generator is to simplify this process of binding together C++ and Python, removing much of the redundant code needed by pybind11 such as trampoline classes for providing virtual function overrides in Python.", + "laborHours": 1231.2, + "languages": [], + "name": "PYB11Generator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmikeowen/pyb11generator", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-02-28", + "metadataLastUpdated": "2024-02-09" + }, + "description": "The OpenStudio®-ERI project allows calculating an Energy Rating Index (ERI) using the Department of Energy's open-source OpenStudio®/EnergyPlus® simulation platform. The building description is provided in an HPXML file format. The project supports: - ANSI/RESNET/ICC 301© Standard for the Calculation and Labeling of the Energy Performance of Dwelling and Sleeping Units using an Energy Rating Index - ENERGY STAR Certification System for Homes and Apartments Using an ERI Compliance Path - IECC ERI Compliance Alternative (Section R406) - DOE ZERH Certification Using an ERI Compliance Path For more information on running simulations, generating HPXML files, etc., please visit the documentation at https://openstudio-eri.readthedocs.io/en/latest/", + "laborHours": 249295.2, + "languages": [ + "Ruby" + ], + "name": "OpenStudio® Energy Rating Index (ERI) Workflow (SWR-18-72)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-ERI", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.5.2" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-06", + "metadataLastUpdated": "2019-03-06" + }, + "description": "Ladybug Tools IN2 Measures is a collection of OpenStudio® measures, file formats, scripts, and related tools for integrating Ladybug Tools with energy modeling via OpenStudio. ", + "laborHours": 0.0, + "languages": [], + "name": "Ladybug Tools IN2 Measures", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ladybug-tools-in2/standards-measure", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-11", + "metadataLastUpdated": "2019-03-12" + }, + "description": "Coramin is a package that provides tools for developing tailored algorithms for mixed-integer nonlinear programming problems. This software includes the ability to:\n- Generate convex or piecewise relaxations of nonlinear optimization problems, addressing bilinear, quadratic, and convex/concave univariate functions\n- Perform optimization-based bounds tightening on all or subsets of the problem variables\n- Generate polyhedral envelopes for multi-linear functions", + "laborHours": 2006.4, + "languages": [ + "Python" + ], + "name": "Coramin v. 0.1 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Coramin/Coramin", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.1" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-11", + "metadataLastUpdated": "2019-03-12" + }, + "description": "Egret is a package that provides tools for building electric grid optimization models. This software includes objects and functions for parsing, storing, and managing electric grid data. Egret also includes the following electric grid models:\n- ACOPF (alternating current optimal power flow)\n- DCOPF – a linearized transmission model\n- ACOPF relaxations\n- Unit commitment\n- Economic dispatch", + "laborHours": 7174.4, + "languages": [ + "Python" + ], + "name": "Egret v. 0.1 (beta)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/grid-parity-exchange/Egret", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.1 (beta)" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2019-03-13" + }, + "description": "This software uses averaged weighted estimators to classify instances and then explicate the individual decision process in classification. The software has state of the art performance in accuracy, while maintaining full explainability. It does this by calculating hierarchically averaged probabilities for a large class of feature combinations and updating them ‘on-the-fly’. On the fly updating also allows the model to be accurate, relative to the total dataset, maintaining accuracy in real-time, without a need to retrain the classifier. ", + "laborHours": 31768.0, + "languages": [ + "C++", + "Python" + ], + "name": "AWE-ML: Averaged Weights for Explainable Machine Learning v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/aweml", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2019-03-13" + }, + "description": "Stitch is a new IO library focused around supporting simulations where only a small portion of the simulation space changes at each timestep. It improves storage efficiency by only storing the changed data and constructs on request a view of an arbitrary region at a given time by stitching together parts of various outputs. This enables scaling from a single process to 100s of nodes.", + "laborHours": 113270.4, + "languages": [ + "C", + "Python" + ], + "name": "Stitch v. 1.0 IO Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gflofst/stitch-io", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2019-03-12" + }, + "description": "The MPRM is a simulation code that is used to statistically quantify the performance and reliability of a microgrid operating in islanded mode. Performance can be expressed in terms of fuel efficiency, renewable penetration, and other operational characteristics of the grid. Reliability can be expressed in terms of frequency and magnitude of load loss on a tier-by-tier, bus-by-bus basis or on an", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 30612.8, + "languages": [], + "name": "The Microgrid Performance Reliability Model (MPRM) v. 1.50 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.50 Beta" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2019-03-12" + }, + "description": "The software generates and analyzes nuclear magnetic resonance spin diffusion simulations for the purpose of measuring domain sizes or spin diffusion constants in a heterogenous sample. Its primary capabilities are:\n1.\tIt solves the spin magnetization diffusion equation to simulate the results of a spin diffusion experiment using any structural input geometry, including structure models generated by molecular dynamics or other computational or experimental methods.\n2.\tIt compares the results of simulations on an input structure to experimental data, providing a data fitting algorithm to extract physical information from the experimental data via the simulation.\n3.\tIt can provide statistical measures to compare correlations between structural models, to determine domain clustering and connectedness, and to provide goodness-of-fit measures including chord length distributions, chi-squared values, Pearson coefficients and pair correlation functions.\n4.\tIt provides output reports, data files, and movies to visualize simulation results.\n", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 410.4, + "languages": [ + "MATLAB" + ], + "name": "NMR_DIFFSIM v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2019-03-12" + }, + "description": "Evaluating the effectiveness of data visualizations is a challenging undertaking and often relies on one-off human subject studies that test a visualization in the context of one specific task. Researchers across the fields of data science, visualization, and human-computer interaction are calling for foundational tools and principles that could be applied to assessing the effectiveness of data visualizations in a more rapid and generalizable manner. The visual saliency model for data visualizations described here addresses this need for evaluation tools. Visual saliency models assess the visual features (e.g. color, contrast, edges) of an image to predict which areas of that image will draw a viewer’s attention. Providing predictions of where viewers will look in a visualization based on the saliency of the various regions and elements in that image could help designers to assess whether or not their design will draw the viewer’s attention as intended. The Data Visualization Saliency model, a saliency model for data visualizations, consists of two parts: a text saliency map and a modified version of the Itti, Koch and Niebur model [1]. The final saliency map is a linear combination of the two. The text saliency map is created from an algorithm that computes the likelihood of belonging to a text region for each pixel of an input visualization image. The modified Itti model transforms the original input image to a representation in CIE LAB color space, which provides an accurate representation of perceptual color opponency.\n\nFor a given input data visualization image, the Data Visualization Saliency model computes and returns the visualization saliency map highlighting areas of the data visualization that will draw a viewer’s attention. It also returns the lower level saliency maps for text and the modified Itti model.\n\n", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 1869.6, + "languages": [ + "MATLAB" + ], + "name": "Data Visualization Saliency v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2022-06-27" + }, + "description": "SolTrace is a software tool developed at the National Renewable Energy Laboratory (NREL) to model concentrating solar power (CSP) systems and analyze their optical performance.\n\nAlthough ideally suited for solar applications, the code can also be used to model and characterize many general optical systems. The creation of the code evolved out of a need to model more complex solar optical systems than could be modeled with existing tools.\n\nSolTrace can be installed either using the official NREL packaged distribution or from source code at the SolTrace open source project website. NREL welcomes contributions from programmers to the simulation engine or to the interface and encourages interested persons to get involved. More information on contributing, compiling the source code, and license requirements is available on the project website.(https://www.nrel.gov/csp/soltrace.html). For details on integration with SAM, see the SAM website. (https://sam.nrel.gov/)", + "laborHours": 10381.6, + "languages": [ + "C++", + "css", + "html", + "Tex", + "JavaScript", + "Python" + ], + "name": "SolTrace (Optical Analysis Software)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SolTrace", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.0.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-13", + "metadataLastUpdated": "2019-10-23" + }, + "description": "The Connected and Automated Vehicles Scenario Generation (CSG) model is a system dynamics model. It was built by NREL and funded by the U.S. Department of Energy under the Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility initiative. The purpose of the model is to simulate the “transitions from predominantly individual ownership of non-CAVs to various future scenarios of high connectivity/automation”(Bush, Vimmerstedt, and Gonder 2019).", + "laborHours": 30.4, + "languages": [ + " STELLA Professional 1.9.1. " + ], + "name": "CSG-public", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CSG-public", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-13", + "metadataLastUpdated": "2023-05-30" + }, + "description": "The Alternative Fueling Station Locator app helps you find fueling stations that offer electricity, natural gas, biodiesel, ethanol (E85), propane, and hydrogen.\n\nUse your current location or enter a custom location to find the 20 closest stations within a 30-mile radius. View the stations on a map or see a list of stations ordered by distance from your location. Select your alternative fuel of choice and adjust the custom filters to fit your needs.\n\nSelect a station from the map or list to view contact info and other details:\n- address, phone number, and hours of operation\n- payment types accepted\n- public or private access\n- special services\n- compression (natural gas)\n- vehicle size access (natural gas)\n- number and types of chargers (electric)\n- blends available (biodiesel)\n- blender pumps (ethanol)\n\nThe free app draws information from the U.S. Department of Energy's Alternative Fuels Data Center, which houses the most comprehensive, up-to-date database of alternative fueling stations in the United States. The database contains location information for more than 25,000 alternative fueling stations throughout the country.", + "homepageURL": "https://afdc.energy.gov/stations#/find/nearest", + "laborHours": 29518.4, + "languages": [ + "JavaScript", + "HTML", + "CSS" + ], + "name": "Alternative Fueling Station Locator - ANDROID [SWR 17-07]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrel.gov/disclaimer.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://afdc.energy.gov/stations#/find/nearest", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "1.0.2 (as of 3/13/2019)" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-13", + "metadataLastUpdated": "2023-05-30" + }, + "description": "The free Alternative Fueling Station Locator app helps you find fueling stations that offer electricity, natural gas, biodiesel, E85, propane, or hydrogen.\n\nUse your current location or enter a custom location to find the 20 closest stations within a 30-mile radius. View the stations on a map or see a list of stations ordered by distance from your location. Select your alternative fuel of choice and adjust the custom filters to fit your needs.\n\nSelect a station from the map or list to view contact info and other details:\n- address, phone number, and hours of operation\n- payment types accepted\n- public or private access\n- special services\n- compression (natural gas)\n- vehicle size access (natural gas)\n- number and types of chargers (electric)\n- blends available (biodiesel)\n- blender pumps (ethanol)\n\nThe app draws information from the U.S. Department of Energy's Alternative Fuels Data Center, which houses the most comprehensive, up-to-date database of alternative fueling stations in the United States. The database contains location information for more than 15,000 alternative fueling stations throughout the country.", + "homepageURL": "https://afdc.energy.gov/stations#/find/nearest", + "laborHours": 29518.4, + "languages": [ + "Objective-C" + ], + "name": "Alternative Fueling Station Locator - APPLE [SWR 17-06]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrel.gov/disclaimer.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://afdc.energy.gov/stations#/find/nearest", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "1.1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-03-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Collection of measurements and metrics to be used on social network data. The task was to develop a set of measurements and metrics that can be used to measure the effectiveness of various social network simulations. Provides a collection of measurements and metrics. This takes a variety of metrics and measurements and packages them into a consistent framework.", + "laborHours": 23134.4, + "languages": [], + "name": "pnnl/socialsim_package", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/socialsim_package", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-14", + "metadataLastUpdated": "2019-03-18" + }, + "description": "As systems and devices become virtualized and deployed in the cloud, the hypervisor becomes an increasingly appropriate place to collect performance data, system state, system landscape, function calls, transaction traces, and other characteristics. We developed a method by which an introspection application may be coupled with a hypervisor to “reach into” the VM with minimal intrusiveness to collect data critical to the reconstruction of events, files, and operations. Such a capability is required to take advantage of the hypervisor as an instrumentation platform and to integrate that data with more traditional collection mechanisms. The concept of a VM serviced by a lightweight hypervisor is a relatively new paradigm for forensic practitioners. Traditional forensic techniques, based on assumptions that the filesystem was directly interacting with the hardware through an abstraction, afforded the forensic practitioner the assumption that there was nothing controlling the application below the filesystem. This is not the case when using virtualized technologies. Hypervisors can covertly monitor, introspect and interact with the guest in a transparent fashion. The problems of storage and collection of actionable data are exhausting. The current challenge is most hypervisors do not expose a useful application programming interface (API) at a sufficient level to do transparent, fine-grained and customizable introspection. Scalable VM instrumentation and introspection at an in-depth level requires fast handling of events, as well as direct access to VM state. Furthermore, deep introspection benefits greatly from the ability to gather data from the hardware during the VM’s exit to the hypervisor. All of this requires identical access to the system as the hypervisor itself; improper use of this ability could easily cause system instability. It is for this reason we believe that the hypervisor developers have been hesitant to grant this much control through their APIs. However, our approach leverages other means to collect and monitor the guests in a targeted fashion. Virtual machine introspection (VMI) is a technique used to monitor the runtime state of a system-level virtual machine. The runtime state can be may include processor registers, memory, disk, network, and any other hardware-level events\nA review of research literature and current VMI technologies exposed several limitations and tradeoffs in VMI approaches, including: the use of in-guest agents; kernel to user space transitions (dramatically slowing down processing); VMI tool pre-configuration requirements; hypervisor version lock-in or source code patching; reliance on operating system symbols; limited processor features due to hypervisor (even if the hardware could do more).\nTo address these constraints, a VMI tool was envisioned to provide the cloud forensic capabilities while having as few of these limitations as possible. The Kernel-based Virtual Machine Introspection (KVMi) tool was developed for hypervisors on Intel’s x86-64 architecture. To meet performance, scoping and use-case demands, the follow criteria were applied to KVMi to support live, forensic data collection:\n•\tShall not require in-guest agents.\n•\tShall work with any recent version of modern hypervisors.\n•\tShall introspect upon any guest (VM) running modern versions of Windows, Linux and OS X.\n•\tShall have the ability to find and track operating system artifacts\n•\tShall not require operating system symbol files.\n•\tShall be able to fully handle VM-exits, bypassing execution of the hypervisor if necessary, to facilitate new features the hypervisor may not support.\n•\tShall be compilable/loadable on a running system with standard build tools.\n", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 38273.6, + "languages": [ + "C" + ], + "name": "Sandia Cloud Forensics and Incident Response Platform v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-03-19", + "metadataLastUpdated": "2019-03-22" + }, + "description": "Synoptic is a system for graphical representation of real-time data in the Fermilab Accelerator Control System. It offers a means for domain experts to create, in a short time, coherent displays representing a machine or a process, along with actual readings from the control system indicating its current state. The displays can run either within a Java application, or in a conventional web browser as SVG images updated on the fly. Synoptic also optionally supports setting data back to the control system. The end users do not have to be familiar with programming, because displays are composed in a high-level graphical editor from preexisting building blocks: gauges, alarm indicators, static shapes, and such. Similarly, the runtime environment takes care of all internal “plumbing and wiring” between components and hides the complexity of the actual data acquisition protocols.\n\nThe open-source Java Synoptic Toolkit includes a core of Synoptic, free of dependencies from the proprietary infrastructure. It can be used with any data acquisition system, providing that an appropriate data access interface is developed. The product can be customized in a variety of ways, for instance, by developing specialized components for rendering data.\n", + "homepageURL": "http://synoptic.fnal.gov/opensource.html", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Java Synoptic Toolkit", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://synoptic.fnal.gov/opensource.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-03-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Dynamic, unsupervised quality control methodology for mass spectrometry", + "laborHours": 167.2, + "languages": [], + "name": "stanfill/QC-ART", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stanfill/QC-ART", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-28", + "metadataLastUpdated": "2019-03-28" + }, + "description": "This program calculates performance characteristics for a split flow recompression closed Brayton cycle. The user defines for the cycle; minimum temperature, minimum pressure, maximum temperature, maximum pressure, pinch temperature at the cold ends of the low temperature and high temperature recuperators, component fractional pressure drop, and efficiencies for each of the two turbines and each of the two compressors. All of these parameters except component fractional pressure drop and turbomachinery efficiencies are varies in separate do loops. In this way, minimum and maximum values for each of these parameters can be set. Results from each iteration are saved to a .csv file. Following completion of the program run, the .csv file can be read into a plotting package and the results can be plotted.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 121.6, + "languages": [], + "name": "CATS v. 2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 2" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-04-02", + "metadataLastUpdated": "2019-04-02" + }, + "description": "PTFREAD is an Excel Add-In used to post-process MELCOR plotfile data for plotting and animation of MELCOR results. ", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 21888.0, + "languages": [], + "name": "PTFREAD v. 188r", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 188r" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-03", + "metadataLastUpdated": "2019-04-03" + }, + "description": "Brief Description for Public Release:\nA collection of general code samples demonstrating issues encountered with using OpenMP4.5 (and some CUDA) during efforts to port codes to a GPU platform using IBM XL. These independent examples include both C++ and FORTRAN language usage, along with attempts to use OpenMP and CUDA in an interoperable manner. This suite of code samples is meant to supplement the examples provided by openmp.org at https://github.com/OpenMP/Examples, especially in regards to FORTRAN language support and OpenMP/CUDA interoperability.", + "laborHours": 2158.4, + "languages": [], + "name": "OpenMP 4.5 and CUDA C++ and FORTRAN code samples", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FGPU", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-04-03", + "metadataLastUpdated": "2019-04-03" + }, + "description": "Flexible Energy Scheduling Tool for Integrating Variable generation (FESTIV) is a tool that simulates the realistic representation of steady-state power system operations and scheduling performed by an independent system operator, regional transmission organization, or a vertically integrated regulated utility. The tool integrates security-constrained unit commitment (SCUC), security-constrained economic dispatch (SCED), and automatic generation control (AGC) into one model. These are the three modes of power system scheduling that are used to meet the changing net demand. Each of these submodels have different time characteristics and are used to meet the changing demand at different time resolutions and horizons. This allows multiple timescales to be studied where FESTIV accounts for intertemporal coupling between each submodel and the submodels themselves. It does this while having different objectives between the submodels; commitment of resources, dispatch and reserve commitment, and finally control.", + "laborHours": 10488.0, + "languages": [], + "name": "FESTIV (Flexible Energy Scheduling Tool for Integrating Variable generation)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/FESTIV_MODEL", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-08", + "metadataLastUpdated": "2019-04-08" + }, + "description": "ScrubJay allows users to query large collections of heterogeneous numerical dawets. Scrubjay v 1.0 a general and scalable framework for analyzing big he1erogeneous HPC performance data. ScrubJay decouples the task of specifying data relationships from the task of analyzing d111a 11nd automates performance 1111alysis. ScrubJay makes large-scale analysis tractable, reproducible, and provides insights into HPC facilities.", + "laborHours": 1626.4, + "languages": [], + "name": "ScrubJay", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ScrubJay", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-08", + "metadataLastUpdated": "2019-04-08" + }, + "description": "Cygnus is a C++ code which is used to analyze Coulomb excitation experiments. In these experiments, the structure of nuclei is probed at low energy, so that only the electromagnetic interaction is involved. The excitation can then be solved semi-classically. Cygnus fits calculated yields to experimental data, allowing the extraction of transition matrix elements, which are important probes of nuclear structure.", + "laborHours": 49172.0, + "languages": [], + "name": "Cygnus", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jhenderson88/Cygnus", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-08", + "metadataLastUpdated": "2019-04-08" + }, + "description": "H2OI95 is a stand-alone Fortran code for evaluating the IAPWS-95 equation-of-state model (Wagner and Pruss, 2002) for the thermodynamic properties of water. It further evaluates the corresponding thermochemical properties of water consistent with the CODATA recommendations (Cox et al., 1989). The IAPWS-95 model is based on a model equation for the dimensionless Helmholtz energy for which the primary variables are the inverse reduced temperature and reduced density. Here is the absolute temperature (K), is density (kg/m3), and the subscript refers to the critical point of water (647.096 K and 22.064 MPa pressure in this model, for which is 322 kg/m3). The code solves four basic types of problems, distinguished by the specified inputs: \n1, Temperature (K) and density (kg/m3) or reduced density\n2. Temperature (K) and pressure (MPa). \n3. Temperature (K) on the saturation (liquid-vapor equilibrium) curve \n4. Pressure (MPa) on the saturation curve\nEach type of problem is run using a corresponding input (text) file. All but the first type of problem require iteration. For example, to solve for desired temperature and pressure, the reduced density must be adjusted to give the desired pressure. Iteration is accomplished using the Newton-Raphson method, though the secant method is also used in solving the fourth type of problem. H2OI95 has been used to conduct numerical studies of convergence and the problem of multiple numerical solutions, only some of which correspond to valid results. Obtaining valid results depends mainly on appropriate choice of starting values. The default values in H2OI95 appear to consistently lead to generally desired results. With modification (not addressed here), H2OI95 can be used to support SUPCRT92 (Johnson et al., 1992) and similar codes that compute chemical thermodynamic properties of species and reactions over a wide range of temperature and pressure (273.16-1273K and 0-1000 MPa).\n", + "laborHours": 15.2, + "languages": [], + "name": "H2OI95: A Stand-Alone Fortran Code for Evaluating the IAPWS-95 Equation-of-State Model for Water", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/H2OI95", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-08", + "metadataLastUpdated": "2019-04-08" + }, + "description": "libROM is a collection of C++ classes that compute reduced order models and hyperreduced order models for systems of ordinary differential equations. libROM includes parallel, adaptive methods for proper orthogonal decomposition, and parallel, non-adaptive methods for hyperreduction using the discrete empirical interpolation method.", + "laborHours": 16887.2, + "languages": [], + "name": "libROM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/libROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-08", + "metadataLastUpdated": "2019-04-08" + }, + "description": "CUDA is the programming model used to program NVIDIA GPUs, which are widely used in DOE supercomputers. FPChecker allows programmers to detect and fix hidden exceptions in the floating-point computations that CUDA executes. When a floating-point exception occurs (e.g., division by zero), GPUs cannot catch these errors. FPChecker intercepts each floating-point operations (addition, subtraction, multiplication and division) and reports to users where exceptions occur (file and line of code).", + "laborHours": 2280.0, + "languages": [], + "name": "FPChecker", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FPChecker", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-10", + "metadataLastUpdated": "2019-04-10" + }, + "description": "Metall provides simplified memory allocation interfaces for out-of-core applications that use block-addressable persistent memory devices to extend the capacity of main memory and to persistently store data on such devices. Using Metall, users can dynamically allocate memory in persistent memory devices just as in main-memory. In order to store data persistently and reload the data easily, Metall also provides a key-value store like interface. Metall offers APIs to allocate contiguous memory regions like malloc(3) does and to construct C++ objects, including STL-like containers. Metall has a similar APIs to\nBoost.Interprocess (BIP).", + "laborHours": 5943.2, + "languages": [], + "name": "Meta Allocator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/metall", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-10", + "metadataLastUpdated": "2019-04-10" + }, + "description": "The OpenRES is an open-source library of intermittent energy resources developed in the JModelica.org platform, and provides capability for performing long-term power grid dynamic simulation with renewable ancillary services (e.g., load ramp, frequency and voltage regulation).", + "laborHours": 45.6, + "languages": [], + "name": "OpenRES", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/OpenRES", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-10", + "metadataLastUpdated": "2019-04-11" + }, + "description": "MPI Usage is a python program that gathers statistics of MPI usage in MPI programs. It reports the MPI routines used in the program among other statistics, such as, the number of lines and languages used in the program (e.g., C, C++, Fortran, CUDA and OpenMP).", + "laborHours": 6900.8, + "languages": [], + "name": "MPI Usage", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MPI-Usage", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-04-11", + "metadataLastUpdated": "2021-08-30" + }, + "description": "The Compadre Toolkit solves a minimization problem, that once solved allows a user to reconstruct a function from sample data collected from a cloud of data sites. The solution to this minimization can also be used to assemble a linear system that can be solved numerically using some other software. The minimization problem the toolkit solves is to find the optimal finite polynomial in a user specified finite dimensional space with regards to minimizing an objective function which measures a linear sampling functional applied to the polynomial, compared to the same sampling functional applied to the source function, weighted by a positive kernel that has compact support.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python" + ], + "name": "Compadre Toolkit ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/compadre", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-04-11", + "metadataLastUpdated": "2019-04-12" + }, + "description": "COMPOSE is scientific software to help to solve tracer transport equations, which are partial differential equations that model how chemical species move when carried by a fluid. It will be used in a future version of the open-source DOE Energy Exascale Earth System Model (E3SM) to help model the movement of chemical species in Earth’s atmosphere as part of simulating the climate. In particular, COMPOSE help to implement semi-Lagrangian tracer transport and, more generally, property preserving remap of tracer fields. Logical components include Communication-Efficient Constrained Density Reconstructors (COMPOSE-CEDR) and Spherical Polygon Intersection and Quadrature with Kokkos (COMPOSE-SIQK).", + "laborHours": 3374.4, + "languages": [ + "C++" + ], + "name": "COMPOSE Version. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/COMPOSE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-04-11", + "metadataLastUpdated": "2019-04-12" + }, + "description": "Sella is a tool for locating and optimizing first order saddle points of arbitrary functions, with an emphasis on the potential energy surfaces of molecules. Sella uses ASE to interface with a variety of electronic structure theory packages. Sella can also be used to minimize functions, or find higher-order saddle points.", + "laborHours": 1869.6, + "languages": [], + "name": "Sella Beta Version 0.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zadorlab/sella", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "Beta Version 0.0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "HATS allows partner countries to collect data on all of their handheld radiation detectors. The DataViewer then allows them to get summaries of how all the devices are performing over time, pick outliers in performance so they can be fixed, trend how individual devices perform over time, and provide reports on the state of health of devices they service. The application is intended to be for maintenance providers and partner countries involved in the NSDD program. It is not clear if other entities use multiple detectors or require trending of a single detector type.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "Handheld Assessment Tool - Data Viewers (HATS)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Biocellion is a software platform to accelerate modeling and simulation of multicellular biological systems. Biocellion integrates simulations of individual cell behaviors, short-distance intercellular biomechanics, and extracellular molecular transport to understand and predict multicellular biological system behaviors in their entirety. This software release (Biocellion 3.1) updates previous Biocellion 2.0. The main updates include support for ellipsoid based cell biomechanics modeling and layer based initialization of multi-layered multicellular biological systems in addition to performance improvements and various API updates. Through Biocellion SPC (https://biocellion.com), these updates have been used to investigate skin biomechanics under different conditions (e.g. humidity) for Procter and Gamble. This is the only discrete agent based solution to allow seamless integration of individual cell level knowledge and measurements to a whole skin model to the best of our knowledge.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "Biocellion 3.1", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Wind and solar generation is increasing rapidly in the USA and around the world and has the potential to replace carbon emitting generation. However, at high penetration, intermittent generation can present significant challenges because of increasing system variability and uncertainty. To manage these challenges, operation and planning procedures should incorporate additional analysis tools and methodologies. Particularly, tools are needed to help plan and operate the power system for maintaining intra‐day and intra‐hour balance between generation and load in power system’s balancing authorities. This tool addresses this problem by providing a way to plan for adequate amounts of balancing reserves for future years or seasons for expected wind and solar generation. This is a user friendly tool to calculate ahead monthly required balancing reserves and the flexibility of scheduled\ngeneration to meet such requirements. This tool calculates reserves requirements of various types, such as day‐ahead, load following and regulation, as well as estimates the capacity of the generation fleet to provide the required reserves. The estimations are based on utilities’ operational practices (such as forecasting, timeframe of reserve deployment), and it incorporates detailed synchronized variable and uncertain data from renewable generation and load. This tool uses a methodology that has been previously tested and applied to several systems: California Independent System Operator Corp., Columbia Grid, Northwest Power Pool, the Western Interconnection of the United States, and internationally in Honduras, Guatemala, El Salvador, Nicaragua, Costa Rica, and Panama.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "GRAF-Plan", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Network Collapse is a STEM education VR game for grade 6-12 students to interactively learn about how information is transmitted and protected on networks. Players assume the role of a router and must transfer incoming data packets to the correct outgoing pathway without losing too many. Eventually the player must also recognize a cyber-attack and turn on the best tool to protect their network. Six levels introduce core basic ideas with increasing complexity in game play to maintain engagement while learning new ideas. The game is designed to run on the standalone VR headset, Oculus Go.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "Network Collapse", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is collection of methods to control weld power and temperature with unprecedented accuracy, precision and process robustness. These control techniques are implemented on the spindle axis only and run independently from weld path and forge axis motion.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "Robust Temperature Control for Friction Stir Welding", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-04-29", + "metadataLastUpdated": "2019-04-30" + }, + "description": "Mass spectrometry (MS) is an analytical technique that enables all chemical species within a complex mixture to be resolved and identified based on their mass:charge ratio. MS is an increasingly important tool in life science research and development because it can resolve or separate small molecules, peptides, lipids, proteins, biopolymers and fragments of all of these structures. Unfortunately, the use of MS has been limited for lack of software tools to visualize, manipulate, store and transfer MS data. Ben Bowen, Oliver Ruebel and colleagues made a huge advance on the resolution of these limitations with the invention of \"OpenMSI\" (#2013-004), a computational method that makes the handling of these very large files (up to 50 Tb) much easier, especially for scientists with limited background in bioinformatics or sophisticated software applications of the type needed to handle such data files. \n\nWith the OpenMSI Arrayed Analysis Tool (OMAAT, #2016-188) invention, the authors take MS data analysis one step further by providing tolls for automatic sample position optimization and ion selection. Even though sample deposition technologies have improved greatly, there is always the chance of encountering outliers in a predefined roster, especially in very large sample sets. Manual curation of the data would be extremely time consuming, so the inventors have included an algorithm that automatically finds the outliers. OMAAT is written in Python with accompanying Jupyter (formerly iPython) notebook and is fully integrated with OpenMSI.", + "laborHours": 623.2, + "languages": [], + "name": "OpenMSI Arrayed Analysis Tools (OMAAT) v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/biorack/omaat/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biorack/omaat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Multidimensional Stoichiometric Compound Classification\nThis R code provides a quick access to the Multidimensional Stoichiometric Compound Classification (MSCC) constraints as published in Rivas-Ubach et al., 2018 Analytical Chemistry (DOI: 10.1021/acs.analchem.8b00529).", + "laborHours": 91.2, + "languages": [], + "name": "PNNL-Comp-Mass-Spec/MSCC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MSCC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The OMICS group at PNNL has developed a wide range of software utilities over the last 15+ years. These tools are used to manage data files, transform data, visualize data, and automate data processing. The software is distributed on GitHub as open source, typically under the Apache 2.0 license agreement. See https://github.com/PNNL-Comp-Mass-Spec Lipid analysis tool developed by PNNL", + "laborHours": 76015.2, + "languages": [], + "name": "PNNL-Comp-Mass-Spec/LIQUID", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LIQUID", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Abstract RunTime System (ARTS) aims to provide different levels of abstraction that trade-off performance and programmability and helps to connect upper layers of the software stack with the different computational substrates.", + "laborHours": 10108.0, + "languages": [], + "name": "pnnl/ARTS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ARTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2019-10-04" + }, + "description": "The Building Informatics Environment is a modeling environment based on the Modelica language. The environment allows users to create a computer model of a building and its energy systems with various time scales and physical resolutions. The environment can be used for rapid development of e.g. demand controls algorithms new HVAC system solutions and new operational strategies. Models for building energy and control systems are made available in the environment. The models can be used as provided or they can be changed or linked with each other in order to model the effects that a particular user is interested in.", + "laborHours": 100122.4, + "languages": [], + "name": "Modelica Buildings Library", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-srg/modelica-buildings", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2019-10-04" + }, + "description": "BuildingsPy is a Python package that can be used to run Modelica simulations and to process Modelica output files. It can also be used to run unit tests as part of the development of LBNL's Modelica Buildings library. The package provides functions to extract data series from the output file for further use in the python packages matplotlib for plotting and SciPy for scientific computing.", + "laborHours": 3936.8, + "languages": [], + "name": "BuildingsPy", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-srg/BuildingsPy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2021-05-11" + }, + "description": "The Software consists of a spreadsheet written in Microsoft Excel which provides an hourly simulation of a solar hot water heating system (including solar geometry, solar collector efficiency as a function of temperature, energy balance on storage tank and lifecycle cost analysis).", + "homepageURL": "https://www.labpartnering.org/lab-technologies/abbc8ccf-3984-416e-b276-4c9d8d192a9f", + "laborHours": 0.0, + "languages": [ + "excel" + ], + "name": "Solar Hot Water Hourly Simulation", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.labpartnering.org/lab-technologies/abbc8ccf-3984-416e-b276-4c9d8d192a9f", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.labpartnering.org/lab-technologies/abbc8ccf-3984-416e-b276-4c9d8d192a9f", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-05-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The hydrological emulator (HE) was built to mimic complex global hydrological models (GHMs) at a range of spatial scales. The HE was written in MATLAB and utilizes a genetic algorithm to calibrate the a, b, c, d, m parameters from the ABCD runoff algorithm to observed runoff from GHMs when forced by the same climate data. The HE employs two methods to choose from when processing basin data: lumped (by basin) and distributed (gridded). Both methods can be evaluated using the built-in Kling-Gupta efficiency as a measure of model performance when compared to the outputs from the more complex GHM. Testing shows that the HE is 7 orders of magnitude faster then the widely used Variable Infiltration Capacity (VIC) GHM.", + "laborHours": 2067.2, + "languages": [], + "name": "JGCRI/hydro-emulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/hydro-emulator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kalb@bnl.gov" + }, + "date": { + "created": "2019-05-02", + "metadataLastUpdated": "2019-05-02" + }, + "description": "BNL NowCasting software is used in conjunction with multiple ground-based, upward looking, high definition imagers to predict available solar resources in the zero - 30 minutes time frame. It takes HD images of the sky as input and conducts image pre-processing to correct image geometry, correct deformation caused by fish-eye lenses and remove extraneous parts of the image. It calculates the location of the sun and removes it to reduce distortion. A cloud detection/tracking algorithm was developed using both spectral and spatial information for discriminating clouds and clear sky based on their shape, size, and color. The software repeats the process with updated images generated every 30 seconds (or less) and then tracks the clouds as they move through the region of interest. Cloud motion determination is based on finding the maximal normalized cross-correlation between sequential images. The resolution of multiple imager views of clouds in the sky allows the system to estimate cloud height and categorize them into low or high cloud regimes that move at different rates. Additional input data on solar irradiance from pyranometers is ingested. The algorithm then determines the transmissivity of light and uses machine-learning techniques to predict the amount of available global horizontal irradiance (GHI) that will be available on the ground. Images from individual sets of cameras are stitched together to form regional forecasts that cover both generating facilities and distributed solar resources. The size of the nowcasting network is dependent on the number and location of imagers that are installed but has been demonstrated in an area up to 50 sq km", + "laborHours": 3693.6, + "languages": [ + "Python" + ], + "name": "BNL-NowCasting/SolarForecasting", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BNL-NowCasting/SolarForecasting", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-02", + "metadataLastUpdated": "2019-05-03" + }, + "description": "Supplementary Folder 1\" is documentation with embedded code. It is a supplement to a manuscript communicating results for a collaborative research project on the evolutionary mechanisms of fruit fly mating.", + "laborHours": 6049.6, + "languages": [], + "name": "Evolution of mechanisms that control mating in Drosophila males - \"Supplemental Folder 1\"", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aavilaherrera/flymating", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-02", + "metadataLastUpdated": "2019-05-02" + }, + "description": "Extends the JupyterHub LocalProcessSpawner to instead launch notebooks on a remote host (e.g. a login node).", + "laborHours": 243.2, + "languages": [], + "name": "SSHSpawner", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SSHSpawner", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "sprice@lanl.gov" + }, + "date": { + "created": "2019-05-02", + "metadataLastUpdated": "2019-05-06" + }, + "description": "The Model for Prediction Across Scales (MPAS) is a collaborative project for developing atmosphere, ocean, and other earth-system simulation components for use in climate, regional climate, and weather studies. The primary development partners are the climate modeling group at Los Alamos National Laboratory (COSIM) and the National Center for Atmospheric Research. Both primary partners are responsible for the MPAS framework, operators, and tools common to the applications; LANL has primary responsibility for the ocean, sea ice, and land ice models, and NCAR has primary responsibility for the atmospheric model.", + "laborHours": 244279.2, + "languages": [ + "C++", + "Fortran" + ], + "name": "MPAS-Dev/MPAS-Model", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MPAS-Dev/MPAS-Model", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "6.2" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-03", + "metadataLastUpdated": "2019-05-06" + }, + "description": "Collection of tools and code for evaluation testing of HPC orchestration solutions by HPCCEA summer students. These scripts and configuration files were written by HPCCEA summer students as part of their summer internship where they explore alternative solutions to our current HPC cluster management software. These scripts/configuration files range from using configuration management tools (Puppet, Chef, Ansible, Fabric, etc.) to scripting languages (Phython, BASH, Perl, etc.). Each year, new students will be added to the project and expand on previous years work.", + "laborHours": 1474.4, + "languages": [], + "name": "High Performance Computing Cluster Engineering Academy", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/HPCCEA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-03", + "metadataLastUpdated": "2019-05-06" + }, + "description": "We provide a self-contained package to load, process, and test the ICF JAG dataset. In particular, we include a Neural Network designed to act as a surrogate for the JAG 1D Simulator. The neural network is implemented in Tensorflow.\nWe include a Jupyter notebook which allows a user to load the dataset, load the neural network and train it such that given just the 5 input parameters, it predicts the scalars and images accurately. This can be done directly in the notebook, without any additional modifications. During training, intermediate predictions are also saved to disk (as specified by the user). We hope this serves as a starting point to build, test and play with the ICF-JAG simulation dataset.", + "laborHours": 532.0, + "languages": [], + "name": "Cycle Consistent Surrogate for Inertial Confinement Fusion", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rushilanirudh/icf-jag-cycleGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-03", + "metadataLastUpdated": "2019-05-06" + }, + "description": "While deep learning technologies for computer vision have developed rapidly since 2012, modeling of remote sensing systems has remained focused around human vision. In particular, remote sensing systems are usually constructed to optimize sensing cost-quality trade-offs with respect to human image interpretability. While some recent studies have explored remote sensing system design as a function of simple computer vision algorithm performance, there has been little work relating this design to the state-of-the-art in computer vision: deep learning with convolutional neural networks. We develop experimental systems to conduct this analysis, showing results with modern deep learning algorithms and recent overhead image data. Our results are compared to standard image quality measurements based on human visual perception, and we conclude not only that machine and human interpretability differ significantly, but that computer vision performance is largely self-consistent across a range of disparate conditions.\nThis repository contains all the code required to replicate the results of our research paper, and the corresponding docker environment in which that code can be executed. All code is written in Python3 and utilizes the PyTorch library (v1.0) for neural network model training and evaluation. Jupyter notebooks are used to visualize images transformed with our code, in addition to plotting experimental results. We also include the specific parameter files used to execute our experiments, with the intent that these experiments can be replicated.", + "laborHours": 2340.8, + "languages": [], + "name": "Remote Sensor Design for Visual Recognition with Convolutional Neural Networks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sepsense", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-06", + "metadataLastUpdated": "2019-05-13" + }, + "description": "The Design, Analysis, and Operations Toolkit (DAO-Tk) is a software package that allows users to explore design optimization, operations decision, and performance characterization of concentrating solar power tower plants. Users interface with the tool through a scripting language, and results are reported in time series tables, plots, runtime logs, and design outputs. Users choose from a list of variables such as tower height, solar multiple, design-point irradiance, thermal storage size, etc., and specify information about the system using a list of parameters. The software can then optimize the specified variables to reduce the cost of energy produced by the system while meeting certain production requirements, accounting for uncertain weather and electricity price forecasts, and correcting for equipment failures or repair time. The DAO-Tk software is the first comprehensive design tool of it's kind to incorporate all of these aspects while being deployed as open source. ", + "laborHours": 106536.8, + "languages": [], + "name": "Design, Analysis, and Operations Toolkit (DAO-Tk)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dao-tk", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-06", + "metadataLastUpdated": "2019-10-04" + }, + "description": "FERIS is an agent-based model that simulates the activity of a fleet of electric taxis in a metropolitan area. Agent activities include serving trips, rebalancing to anticipate future demand, and relocating to charge. The modeling framework allows researchers to study the impact of different routing algorithms, battery range, and charging infrastructure on fleet performance, energy consumption, environmental impact, and cost of service.", + "laborHours": 912.0, + "languages": [], + "name": "Routing and Infrastructure simulation for Shared Electric vehicles (RISE)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gb4uer/RISE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-06", + "metadataLastUpdated": "2019-10-04" + }, + "description": "This package is a set of tools in the Python language for preprocessing GPS trajectory data gathered from consumer devices, to detect and flag potentially erroneous data.", + "laborHours": 1048.8, + "languages": [], + "name": "TraVerSE: Trajectory Veracity for Simple Errors", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/bgerke/traverse", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-07", + "metadataLastUpdated": "2019-06-26" + }, + "description": "The Modelica IBPSA library is a free open-source library with basic models that codify best practices for the implementation of models for building and community energy and control systems. \n\nThe development of the IBPSA library is organized through the IBPSA Project 1 (https://ibpsa.github.io/project1) of the International Building Performance Simulation Association (IBPSA). \n\nThis library is typically not used directly by end-users. Rather, it is integrated by developers of other Modelica libraries for building and community energy systems, who then distribute it to end-users as part of their respective library.", + "laborHours": 36328.0, + "languages": [], + "name": "Modelica IBPSA Library v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ibpsa/modelica-ibpsa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-05-10", + "metadataLastUpdated": "2019-05-13" + }, + "description": "This is a follow on to a subset of SCR#2291.0, and represents a set of FPGA and Linux driver software that serves to enhance the Epiq Solutions Sidekiq line of products with very standard and well defined digital signal processing capabilities that are found on other such software defined radio hardware. This includes timed command support, sub-band tuners, and other generic DSP capabilities.\nSAND2019-3719 M", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "Sidekiq DSP v. 0.4", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 0.4" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-13", + "metadataLastUpdated": "2019-05-13" + }, + "description": "SLAPI is a command line tool that communicates with Spectra Logic tape libraries using their XML command reference. This provides a simple way to administer and monitor Spectra Logic tape libraries in large data centers.", + "laborHours": 2264.8, + "languages": [], + "name": "SLAPI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/slapi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-13", + "metadataLastUpdated": "2019-05-13" + }, + "description": "Polycubes are arrangements of unit cubes connected by their faces. This code generates all possible polycubes with a specified number of unit cubes that are unique under 3D rotation (the family of polycubes of size N) and also finds a globally and locally valid edge unfolding for either a single polycube or a specified family of polycubes.", + "laborHours": 608.0, + "languages": [], + "name": "Polycube Edge Unfolder", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/polycube", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-13", + "metadataLastUpdated": "2019-05-13" + }, + "description": "skyline is a header-only C++ library for the direct solution of linear algebraic equations that are stored in skyline format. It is intended for medium-sized sparse problems with moderate bandwidth. This solution approach has historically been used for pressure network solvers and in some finite element codes. 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By utilizing COMBIgor software package the burden of data management in combinatorial materials science experiments can be significantly reduced.", + "laborHours": 13588.8, + "languages": [], + "name": "COMBIgor (A data assistant for combinatorial scientists in Igor Pro) [SWR-19-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CombIgor", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2019-05-13", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Structured Threat Intelligence Graph", + "laborHours": 6064.8, + "languages": [], + "name": "STIG", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLab/STIG", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2019-05-13", + "metadataLastUpdated": "2019-05-15" + }, + "description": "Cybersecurity Evaluation Tool", + "laborHours": 1186223.2, + "languages": [], + "name": "cisagov/cset", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cisagov/cset", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-14", + "metadataLastUpdated": "2022-02-16" + }, + "description": "PyDSS is a high level python interface for OpenDSS and provides the following functionalities 1] Object oriented programming 2] Dynamic visualization 3] Custom controls 4] Simulation parallelization 5] Exporting results 6] Improved Error logging 7] Communication interface", + "laborHours": 5304.8, + "languages": [ + "Python" + ], + "name": "PyDSS", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PyDSS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2019-05-14", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Woody Biomass Companion Markets Model", + "laborHours": 15.2, + "languages": [], + "name": "WOODCOM", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/WOODCOM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-05-14", + "metadataLastUpdated": "2019-05-14" + }, + "description": "The State of Stress Assessment Tool (SOSAT) is a set of routines that take in information about a geologic carbon storage reservoir and generates a probability distribution for the state of stress in the reservoir before and during injection. As part of this, the tool reports the estimated probability of a critically-oriented fault becoming activated as a result of the injection. The tool also allows a storage site operator to evaluate the likely value of different types of characterization on the knowledge of the geomechanical conditions and probability of induced seismicity. ", + "homepageURL": "https://edx.netl.doe.gov/dataset/state-of-stress-analysis-tool", + "laborHours": 334.4, + "languages": [], + "name": "State of Stress Analysis Tool (SOSAT)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://edx.netl.doe.gov/dataset/state-of-stress-analysis-tool", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-15" + }, + "description": "A unit library was needed to be able to represent units of a wide range of disciplines and be able to separate them from the numerical values for use in calculations. 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The libary also has its origin in power systems so support for per-unit operations was also lacking in the alternatives.", + "laborHours": 42985.6, + "languages": [], + "name": "units", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/units", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-15" + }, + "description": "Machine learning for predicting physics variables in Sedov blast simulation.", + "laborHours": 668.8, + "languages": [], + "name": "Machine Learning for Sedov Blast", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Sedov-ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-15" + }, + "description": "The Application Reporting and Termination Utility for Windows (terminate.exe) is a simple diagnostics and recovery tool designed to help LANDesk system administrators manage hung client applications on Windows systems. Terminate can either report on (tag) or stop (kill) a specified process on computers on which it is run. If KILL is specified, all processes that match the specified name and have a start time older than the specified minutes will be force stopped. If TAG is specified, all processes that match the name and have a start time older than the specified minutes will be reported to LANDesk inventory via the miniscan LANDesk client component.", + "laborHours": 364.8, + "languages": [], + "name": "Application Reporting and Termination Utility for Windows", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/david-frye/Terminate", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2025-03-26" + }, + "description": "These models are based on the 2015 Design Report of Dutta et al. found here: https://www.nrel.gov/docs/fy15osti/62455.pdf The models are distributed under the GNU General Public License. You will need a separate license to use the Aspen Plus and Microsoft Excel software packages in order to run the models. These models relate to an Aspen Plus process model for in situ and ex situ upgrading of fast pyrolysis vapors for the conversion of biomass to hydrocarbon fuels. It is based on conceptual designs that allow projections of future commercial implementations of the technologies based on a combination of research and existing commercial technologies. Results from the model are documented in a detailed design report NREL/TP-5100-62455 (available at http://www.nrel.gov/docs/fy15osti/62455.pdf). The model consists of the following key operations: (a) fast pyrolysis and vapor upgrading, (b) vapor condensation and recovery of an organic liquid and an aqueous phase, (c) hydroprocessing of the liquid organic phase to produce a fuel blendstock, (d) hydrogen production from off gases, (e) electricity production from excess heat, (f) other utilities such as cooling water, (g) wastewater utilization and treatment.", + "homepageURL": "https://www.nrel.gov/extranet/biorefinery/aspen-models", + "laborHours": 0.0, + "languages": [], + "name": "Ex Situ and In Situ Catalytic Fast Pyrolysis Models (ASPEN PLUS MODELS) [SWR-16-12]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/extranet/biorefinery/aspen-models", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-15" + }, + "description": "WUFI - Oak Ridge National Laboratory (ORNL)/Fraunhofer IBP is a menu-driven PC program which allows realistic calculation of the transient coupled one-dimensional heat and moisture transport in multi-layer building components exposed to natural weather. It is based on the newest findings regarding vapor diffusion and liquid transport in building materials and has been validated by detailed comparison with measurements obtained in the laboratory and on outdoor testing fields. Together with Oak Ridge National Laboratory (ORNL) Fraunhofer IBP has developed a special version of WUFI ® for North America. WUFI® ORNL is a functionally limited free version of WUFI® Pro for non-commercial purposes. It contains climate data for 62 cities in the USA and Canada which are all available in the free version.", + "homepageURL": "https://web.ornl.gov/sci/buildings/tools/wufi", + "laborHours": 0.0, + "languages": [], + "name": "WUFI (Wärme and Feuchte Instationär)-Oak Ridge National Laboratory (ORNL)/Fraunhofer IBP", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://web.ornl.gov/sci/buildings/tools/wufi", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://web.ornl.gov/sci/buildings/tools/wufi", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-16" + }, + "description": "The purpose of the ROSE Complier Framework Is to automate source code porting, source and binary code analysis, and source code translations such as platform optimization, binary code analysis, Identification of source code and binary code vulnerablllttes.", + "laborHours": 5605912.0, + "languages": [], + "name": "ROSE Compiler Framework ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rose-compiler/rose", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-16" + }, + "description": "Archer is a data race detector for OpenMP programs.\nArcher combines static and dynamic techniques to identify data races in large OpenMP applications, leading to low runtime and memory overheads, while still offering high accuracy and precision. It builds on open-source tools infrastructure such as LLVM, ThreadSanitizer, and OMPT to provide portability.", + "laborHours": 2903.2, + "languages": [], + "name": "Archer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PRUNERS/archer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-16", + "metadataLastUpdated": "2024-07-01" + }, + "description": "Daft is a Haskell library that implements the key constructs of relational algebra via static structural typing. Its DataCube typeclass supports selection, projection, aggregation, disaggregation, natural joins, semijoins, and antijoins. Instances of DataCube include both map- and function-based representations. An additional abstract data type provides Vinyl-style, keyed relational tables for which an embedded domain-specific language compactly represents relational operations. Utility types and functions support serialization to tab-separated-value data files, JSON arrays, MongoDB documents, and PostgreSQL tables, including automatic detection and verification of the schema for the input data.", + "laborHours": 1094.4, + "languages": [ + "Haskell" + ], + "name": "daft [SWR-17-53]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/daft", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-05-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Per sequence functional classification and Functional annotation in addition to linking those functions to taxonomic groups presents a challenge due to many established tools performing one task and not the other creating disparate downstream data. PerSeq aims to address these challenges by performing local alignments against a reference database annotated for both aspects, function and taxonomy, to annotate sequences individually. Downstream results are merged into count tables facilitating complex analyses based on observed function or functional potential in addition to being able to separate out function by taxonomic level to determine metabolic contributions by present organisms.", + "laborHours": 775.2, + "languages": [], + "name": "PNNL-CompBio/perseq", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/perseq", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dstotler@pppl.gov" + }, + "date": { + "created": "2019-05-22", + "metadataLastUpdated": "2019-05-22" + }, + "description": "DEGAS 2 [1], like its predecessor, DEGAS [2], uses the Monte Carlo approach to integrating the Boltzmann equation, allowing the treatment of complex geometries, atomic physics, and wall interactions. DEGAS 2 is written in a \"macro-enhanced'' version of FORTRAN via the FWEB library, providing an object oriented capability and simplifying tedious tasks, such as dynamic memory allocation and the reading and written of self-describing binary files. As a result, the code is extremely flexible and can be readily adapted to problems seemingly far removed from tokamak divertor physics, e.g., its use in simulating the diffusive evaporation of lithium in NSTX [3] and LTX [4]. DEGAS 2 has been extensively verified, as is documented in its User's Manual [5]. Experimental validation has been largely centered on the Gas Puff Imaging (GPI) technique for visualizing plasma turbulence in the tokamak edge. The validation against deuterium gas puff data from NSTX is described in the paper by B. Cao et al. [6] Analogous work with both deuterium and helium has been carried out on Alcator C-Mod. A related application of DEGAS 2 is in the interpretation of data from the Edge Neutral Density Diagnostic on NSTX [7] and NSTX-U. DEGAS 2 has been applied to many other devices, including JT-60U [8], ADITYA [9], and FRC experiments at Tri-Alpha Energy [10]. Neutral transport codes are frequently coupled to plasma simulation codes to allow a self-consistent plasma-neutral solution to be computed. Initially, DEGAS 2 was coupled to UEDGE [11]. More recently, DEGAS 2 has been coupled to the drift-kinetic XGC0 [12], and has been used in the development and testing of the simplified built-in neutral transport module in XGC1 [13]. A related project is a DEGAS 2-based synthetic GPI diagnostic for XGC1 [14].\n\n[1] D. P. Stotler & C. F. F. Karney, Contrib. Plasma Phys. 34, 392 (1994)\n[2] D. Heifetz, D. Post et al., J. Comp. Phys. 46, 309 (1982)\n[3] D. P. Stotler et al., J. Nucl. Mater. 415, S1058 (2011)\n[4] J. C. Schmitt et al., J. Nucl. Mater. 438, S1096 (2013)\n[5] DEGAS 2 Home Page\n[6] B. Cao et al., Fusion Sci. Tech. 64, 29 (2013)\n[7] D. P. Stotler et al., Phys. Plasmas 22, 082506 (2015)\n[8] H. Takenaga et al., Nucl. Fusion 41, 1777 (2001)\n[9] R. Dey et al., Nucl. Fusion 57, 086003 (2017)\n[10] E. M. Granstedt et al., Presented at 60th Annual Meeting of the APS Division of Plasma Physics\n[11] D. P. Stotler et al., Contrib. Plasma Phys. 40, 221 (2000)[\n[12] D. P. Stotler et al., Comput. Sci. Disc. 6, 015006 (2013)\n[13] D. P. Stotler et al., Nucl. Fusion 57, 086028 (2017)\n[14] D. P. Stotler et al., Nucl. Mater. Energy 19, 113 (2019)\n\n", + "homepageURL": "https://theory.pppl.gov/research/research.php?rid=10#h52", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "DEGAS 2", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://theory.pppl.gov/research/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://theory.pppl.gov/research/research.php?rid=10#h52", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-05-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Shiny interface for the Lipid Mining and Ontology (Lipid Mini-On) tool, which uses the Rodin R package\nThe software allows users to mine and perform enrichment of lipid based on their molecular characteristics, classification at multiple levels.", + "laborHours": 4985.6, + "languages": [], + "name": "PNNL-Comp-Mass-Spec/LipidMiniOn", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LipidMiniOn", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-22", + "metadataLastUpdated": "2019-05-28" + }, + "description": "Calculation of thermal and optical properties of glass, windows, and shades. Calculational code only, no GUI.\n\nThe software hosted at this repository is one out of five repositories that make up this entire project. The others can be found at the following DOIs: 10.11578/dc.20190522.2, 10.11578/dc.20190522.4, 10.11578/dc.20190522.5, and 10.11578/dc.20190524.1.\n", + "laborHours": 35552.8, + "languages": [], + "name": "Berkeley Lab WINDOW Calc Engine (CalcEngine) v2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/Windows-CalcEngine", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-22", + "metadataLastUpdated": "2019-05-28" + }, + "description": "Calculation of thermal and optical properties of glass, windows, and shades. Calculational code only, no GUI.\n\nThe software hosted at this repository is one out of five repositories that make up this entire project. The others can be found at the following DOIs: 10.11578/dc.20190522.1, 10.11578/dc.20190522.4, 10.11578/dc.20190522.5, and 10.11578/dc.20190524.1.", + "laborHours": 1626.4, + "languages": [], + "name": "Berkeley Lab WINDOW Calc Engine (CalcEngine) v2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/WinCalc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-22", + "metadataLastUpdated": "2019-05-22" + }, + "description": "Clean energy systems including the future power grid are enabled via the development, analysis and application of advanced simulation of complex systems based on large datasets. The ability to handle and enable the simulation of complex systems allows researchers and analysts to address significant problems with greater confidence and greater levels of integrity. Parallel execution of complex systems is paramount to addressing increasing complexity. Programmatic interfaces for software configuration and parallel execution enable handling greater complexity and improving simulation integrity. The Class Object Attribute Data (COAD) software is written as a programmatic interface to the PLEXOS dataset that enables the decomposition of the dataset in time and execution in parallel without loss of integrity. COAD also enable the recomposition of solution datasets that are the output of distributed parallel execution of the core simulator. ", + "laborHours": 4836533.6, + "languages": [], + "name": "plexos-coad (Plexos Class-Object-Attribute Data manipulation tool)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Computational-Energy/plexos-coad", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-22", + "metadataLastUpdated": "2019-05-28" + }, + "description": "Calculation of thermal and optical properties of glass, windows, and shades. Calculational code only, no GUI. \n\nThe software hosted at this repository is one out of five repositories that make up this entire project. The others can be found at the following DOIs: 10.11578/dc.20190522.1, 10.11578/dc.20190522.2, 10.11578/dc.20190522.5, and 10.11578/dc.20190524.1.", + "laborHours": 152.0, + "languages": [], + "name": "Berkeley Lab WINDOW Calc Engine (CalcEngine) v2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/pyWinCalc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-22", + "metadataLastUpdated": "2019-05-28" + }, + "description": "Calculation of thermal and optical properties of glass, windows, and shades. Calculational code only, no GUI. \n\nThe software hosted at this repository is one out of five repositories that make up this entire project. The others can be found at the following DOIs: 10.11578/dc.20190522.1, 10.11578/dc.20190522.2, 10.11578/dc.20190522.4, and 10.11578/dc.20190524.1.", + "laborHours": 562.4, + "languages": [], + "name": "Berkeley Lab WINDOW Calc Engine (CalcEngine) v2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/OpticalMeasurementParser", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-22", + "metadataLastUpdated": "2019-05-28" + }, + "description": "Calculation of thermal and optical properties of glass, windows, and shades. Calculational code only, no GUI.\n\nThe software hosted at this repository is one out of five repositories that make up this entire project. The others can be found at the following DOIs: 10.11578/dc.20190522.1, 10.11578/dc.20190522.2, 10.11578/dc.20190522.4 and 10.11578/dc.20190522.5.", + "laborHours": 714.4, + "languages": [], + "name": "Berkeley Lab WINDOW Calc Engine (CalcEngine) v2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/Windows-CalcStandards", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-23", + "metadataLastUpdated": "2019-05-23" + }, + "description": "ldlms_plugins_llnl contains LLNL-developed plugins for LDMS (Lightweight Distributed Metric Service), which is software for low overhead monitoring, transport and storage of cluster metric data. These plugins add to LDMS the capability to monitor Lustre file system clients, metadata servers, and object storage servers.", + "laborHours": 1216.0, + "languages": [], + "name": "ldlms_plugins_llnl", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ldms-plugins-llnl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-24", + "metadataLastUpdated": "2019-05-31" + }, + "description": "The main purpose of the software is to model energy use for individual and community scale solar water heating projects in California. \n\nUsage \n\nThe user provides a climate zone for a project, an occupancy for each household and whether any of the occupants stay at home during the day. The software can then load a set of example California specific hourly domestic hot water end-use load profiles from a database, size and locate the systems. The user can now simulate the hourly system performance over a period of one representative year, visualize and explore the simulation results using time-series plots for temperature profiles, heat and power rates, or look at annual summaries. Similarly the user can model individual household solar water heating projects and base case conventional gas tank water heater systems, such that the results can be compared between the individual, community and base case systems. \n\nThis functionality is readily available through a Jupyter notebook and a Django web framework, depending on what level of detail the user would like to access. \n\nFeatures \n\n- Python module to calculate solar irradiation on a tilted surface \n\n- Python module with simplified component models for Converter (solar collectors, electric resistance heater, gas burner, photovoltaic panels, heat pump), Storage (solar thermal tank, heat pump thermal tank, conventional gas tank water heater), and Distribution (distribution and solar pump, piping losses) components \n\n- Python module with preconfigured system simulation models for: base case gas tank water heaters, solar thermal water heaters (solar collector feeding a storage tank, with a tankeless gas water heater backup in a new installation cases and a base case gas tank water heater in a retrofit case) and solar electric water heaters (heat pump storage tank with an electric resistance backup) \n\n- Database with component performance parameters, California specific weather data and domestic hot water end-use load profiles \n\n- Django web framework to configure project, parametrize components and run simulation from a web browser \n\nThe package contains functional and unit tests and it is structured so that it can be extended with further technologies, applications and locations.", + "laborHours": 18285.6, + "languages": [], + "name": "Multiscale Solar Water Heating (MSWH) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/MSWH", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-05-24", + "metadataLastUpdated": "2024-07-24" + }, + "description": "This code replicates the analysis completed in the published article (see reference below) for the 2D-DIC Challenge (https://sem.org/dic-challenge/), conducted under the auspices of the Society for Experimental Mechanics (SEM). The purpose of the DIC Challenge is to provide a set of vetted and standard images, which all users and developers of Digital Image Correlation (DIC) software can use -DIC Challenge results from Sample 14 and Sample 15 of the DIC-Challenge images, and computes various statistics on the data, such as the noise, bias, and spatial resolution. \n\nP.L. Reu, E. Toussaint, E. Jones, H.A. Bruck, M. Iadicola, R. Balcaen, D.Z. Turner, T. Siebert, P. Lava, M. Simonsen (2018) Exp. Mech. 58(7):1067-1099, https://doi.org/10.1007/s11340-017-0349-0.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "2D-DIC Challenge MATLAB Analysis Code v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/2-D-DIC-Challenge", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-28", + "metadataLastUpdated": "2024-01-03" + }, + "description": "The Regional Energy Deployment System (ReEDS™) is a free, open-access tool that empowers users to explore least-cost pathways for large-scale power sector transformation. NREL’s flagship energy capacity planning model for the North American electricity system allows users to examine the interactions between policy, technology, economics, and the environment when integrating renewables onto the grid from now through 2050.", + "homepageURL": "https://www.nrel.gov/analysis/reeds", + "laborHours": 0.0, + "languages": [ + "GAMS", + "R", + "Python" + ], + "name": "ReEDS™ (Regional Energy Deployment System) [SWR-20-36 and SWR-09-14]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/analysis/reeds/request-access.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/analysis/reeds", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-05-28", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This tool helps red teamers and penetration testers to conduct post exploitation activities through various Configuration Management tools such as Puppet, Chef, Ansible, and Salt.", + "laborHours": 1109.6, + "languages": [], + "name": "Master of Servers (MOSE) v. 1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mose", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-06-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Code and data for the SIEVE-Ub prediction algorithm for prediction of E3 ubiquitin ligase mimics\nThe SIEVEUb approach is a novel approach to determination of sequence similarity that retains flexibility in sequence via a reduced amino acid alphabet and does not require sequence alignment, a prohibitive step for many applications.", + "laborHours": 1094.4, + "languages": [], + "name": "biodataganache/SIEVE-Ub", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biodataganache/SIEVE-Ub", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-06-03", + "metadataLastUpdated": "2024-08-07" + }, + "description": "EGSim contains tools aimed at simulating static load flow solutions for power grids. It implements models for loads, generators, and transmission lines. The static load flow solution is computed via gradient descent. \n\nSAND20019-4672 M", + "laborHours": 13968.8, + "languages": [ + "C++", + "Fortran" + ], + "name": "EGSim v1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/EGSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" + }, + { + "contact": { + "email": "doakpw@ornl.gov" + }, + "date": { + "created": "2019-06-03", + "metadataLastUpdated": "2020-09-25" + }, + "description": "With the DCA++ project, we aim to gain insight into the fascinating physics of strongly correlated electron systems by employing modern quantum cluster methods. The DCA++ code provides a state of the art implementation of the dynamical cluster approximation (DCA) and its DCA+ extension. High scalability and portable performance allow to exploit today's leadership computing systems.", + "laborHours": 113255.2, + "languages": [ + "C++" + ], + "name": "DCA++", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CompFUSE/DCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.1" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-06-03", + "metadataLastUpdated": "2019-06-04" + }, + "description": " IX uses whole building analysis, and solar power cost algorithms to evaluate tradeoffs associated with alternative large-scale, long term facilities energy conservation strategies. It is designed to use existing energy simulation tools such as doe2.2 and SAMS to produce detailed results which are then processed at a higher level. ", + "laborHours": 425.6, + "languages": [], + "name": "Institutional Transformation v. 2.6", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IX2.6", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 2.6" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-06-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Structural Temporal Modeling\nGenerating a synthetic graph that is similar to a given real- world graph is a critical requirement for privacy preservation and benchmarking purposes. This software presents a temporal-motif based approach to generate synthetic temporal graph datasets.", + "laborHours": 8755.2, + "languages": [], + "name": "temporal-graphs/STM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/temporal-graphs/STM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "radercd@ornl.gov" + }, + "date": { + "created": "2019-06-12", + "metadataLastUpdated": "2020-09-09" + }, + "description": "The code was developed to produce figures for an associated Journal of Materials and Design publication.", + "laborHours": 334.4, + "languages": [ + "Python" + ], + "name": "Supplemental Information to 'Data visualization heuristics for the physical sceinces'", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/nmp/data_visualization_paper", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0,0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-06-12", + "metadataLastUpdated": "2025-04-14" + }, + "description": "SRS is a web-based and mobile toolkit for information visualization and collaboration. It includes server-side components in the form of web services that provide analytical functions such as data clustering and temporal analysis. The SRS client is accessed via a web browser and uses asynchronous javascript and XML (AJAX) to interact with and visualize the results of these web services. Users of SRS can query data sources that are connected to the SRS backend, and query results are presented in the form of coordinated visual displays in a web browser that depict temporal, topical, and spatial relationships in the results. SRS also includes an early stage graphical reasoning diagram interface that helps analysts express and test hypotheses. \nThis software was developed with funding from the Science and Technology Directorate of the U.S. Department of Homeland Security.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 35112.0, + "languages": [], + "name": "Scalable Reasoning System (SRS)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "2.x" + }, + { + "contact": { + "email": "kentpr@ornl.gov" + }, + "date": { + "created": "2019-06-13", + "metadataLastUpdated": "2020-09-09" + }, + "description": "QMCPACK is an open source C++ code that runs across multiple high performance computing architectures including accelerators. It's main function is to implement several Quantum Monte Carlo method for solving the many-body Schrodinger equation.", + "laborHours": 1334484.0, + "languages": [ + "C++14" + ], + "name": "QMCPACK", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qmcpack/qmcpack", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "3.6.0" + }, + { + "contact": { + "email": "radercd@ornl.gov" + }, + "date": { + "created": "2019-06-13", + "metadataLastUpdated": "2020-09-09" + }, + "description": "Generating a CTF (thermal-hydraulics subchannel code) model can be time consuming and error prone because of the rigid formatting of the input file and the amount of input requirements. Because of the structured input format, making small changes to a model can require large scale changes to the input file. Furthermore, a user typically has to perform calculations to develop CTF input parameters from actual model geometry. Changing model geometry requires re-calculating input parameters and copying them from wherever the calculation was performed, be it a script, spreadsheet, or piece of paper. This process complicates the quality assurance process for that model and makes changing the model more difficult. CtfDeckBuilder is an object-oriented Python interface to CTF that allows the user to build a CTF model in Python. The user no longer needs to interface with the CTF input file when using the CtfDeckBuilder. The interface reduces the information required of the user by offering defaults for most modeling options provided by CTF. The user can perform calculations directly in Python when building the model so that calculations stay with the model itself. ", + "laborHours": 461852.0, + "languages": [ + "Python 2.7.13" + ], + "name": "SubKit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/CTF/SubKit", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0.1" + }, + { + "contact": { + "email": "radercd@ornl.gov" + }, + "date": { + "created": "2019-06-13", + "metadataLastUpdated": "2020-09-09" + }, + "description": "There is a need for a way to simulate the heat transfer conditions for the entire layer of a build (both temperature and solidification gradient and velocity). CFD models could do this but those may take months to finish a simulation. The solution is an adaptive integration scheme for a analytic, conduction-only approach for a volumetric Gaussian heat source. Because this is analytic, it also allows increased functionality as well. 3DThesis can simulate heat transfer conditions for a volumetric Gaussian heat source moving in an arbitrary path at a point in time. This allows for the calculation of discrete snapshots of the temperature field or even the final solidification gradients and velocities.", + "laborHours": 1611.2, + "languages": [ + "C++(11)", + "GCC", + "Visual C++", + "Intel" + ], + "name": "3DThesis (3D THErmal Simulation Software)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/JamieStumpORNL/3DThesis", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-13", + "metadataLastUpdated": "2019-06-17" + }, + "description": "Geo T automates into a stand-alone computer program the multicomponent chemical geothermometry method previously developed by Reed and Spycher (1984). Geo T allows for simultaneous regression of multiple water chemical analyses, automatic reconstitution of deep fluids, and estimation of reservoir temperature from statistical evaluation of computed mineral saturation indices. The temperature estimation includes a \"best\" estimated temperature with its range of uncertainity. The computer program also outputs temperatures predicted using classical geothermometers. Input parameters include water composition and optionally, gas composition, dilution/evaporation factor (in case of boiling or mixing with dilute waters), and end-member water composition (in case of mixing with other non-dilute waters). This program was designed for geothermal applications but is also useful as a tool to quickly speciate a large number of water analyses.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "GeoT V1.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2019-06-18", + "metadataLastUpdated": "2019-06-19" + }, + "description": "LATTE is a code used for computing the energy of, and forces acting on atoms in molecular materials using an implementation of the self-consistent charge tranfer tight-binding approximation. 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+ "metadataLastUpdated": "2019-07-03" + }, + "description": "This service provides means to stream data from data collection interface to analysis, while logging data into metadataStore.", + "laborHours": 106.4, + "languages": [], + "name": "brokerStreamServer", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/brokerStreamServer", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-03", + "metadataLastUpdated": "2019-07-03" + }, + "description": "A framework for easily creating beautiful presentations using HTML. reveal.js comes with a broad range of features including nested slides, Markdown contents, PDF export, speaker notes and a JavaScript API. There's also a fully featured visual editor and platform for sharing reveal.js presentations at slides.com.", + "laborHours": 10564.0, + "languages": [], + "name": "reveal.js", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/caproto-lightning-slides", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2019-07-03", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Malcolm is a powerful, easily deployable network traffic analysis tool suite for full packet capture artifacts (PCAP files) and Zeek logs.", + "laborHours": 44885.6, + "languages": [], + "name": "Malcolm", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Malcolm", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-07-03", + "metadataLastUpdated": "2019-07-03" + }, + "description": "The general topology-aware task assignment problem is an NP-complete graph isomorphism problem. Existing task scheduling approaches are either heuristic or based on physical optimization algorithms, providing different speed and solution quality trade-offs. Physical Ising machines such as quantum and digital annealers have recently become available offering an alternative hardware solution to solve certain types of optimization problems. We propose an algorithm that allows expressing the problem in the compatible format. We present a domain specific partition strategy that enables to execute larger scale problems. TIGER - topology-aware task assignment mapper tool - implements the proposed algorithm and automatically integrates task- communication graph and an architecture graph into the quantum software environment.", + "laborHours": 380.0, + "languages": [], + "name": "Topology-aware task-assIGnment mappER (TIGER) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnlcomputerarch/tiger", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-03", + "metadataLastUpdated": "2019-07-03" + }, + "description": "This package predicts the minimum inhibitory concentration of a genome using a trained XGBoost model. A set of data files are stored in the data_files directory for use with the Klebsiella genus. A pkl model is also provided for testing purposes as well as a fasta file.", + "laborHours": 136.8, + "languages": [], + "name": "Software for Predicting Bacterial Minimum Inhibitory Concentrations From Genome Sequence Data", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PATRIC3/mic_prediction", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "This is the repository for arista-tapagg-ansible, developed by the Energy Sciences Network (ESnet). ", + "laborHours": 15.2, + "languages": [], + "name": "arista-tapagg-ansible", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/arista-tapagg-ansible", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "This is the repository for the client for the BHR site. 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The implementations include: client library implementation using gnmi.proto, CLI for interacting with gNMI service, and caching collector that connects to multiple gNMI targets and makes the data available over a single gNMI Subscribe RPC to clients.", + "laborHours": 12996.0, + "languages": [], + "name": "gNMI - gRPC Network Management Interface", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/gnmi", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "JA3 is a method for creating SSL/TLS client fingerprints that are easy to produce and can be easily shared for threat intelligence.", + "laborHours": 304.0, + "languages": [], + "name": "JA3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/ja3", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "Python tools for gNMI.", + "laborHours": 106.4, + "languages": [], + "name": "pygnmi", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/pygnmi", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "React ART is a JavaScript library for drawing vector graphics using React. It provides declarative and reactive bindings to the ART library. Using the same declarative API you can render the output to either Canvas, SVG or VML (IE8). The examples directory contains a simple example of using React ART; you can also test out the art branch of the react-page project.", + "laborHours": 501.6, + "languages": [], + "name": "React ART", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/react-art", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "Seccubus automates regular vulnerability scans with various tools and aids security people in the fast analysis of its output, both on the first scan and on repeated scans. On repeated scan delta reporting ensures that findings only need to be judged when they first appear in the scan results or when their output changes.", + "laborHours": 128333.6, + "languages": [], + "name": "Seccubus V2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/Seccubus_v2", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "Graphite consists of two major components: the frontend Django webapp that runs under Apache/mod_wsgi and the the backend carbon-cache.py daemon.", + "laborHours": 42833.6, + "languages": [], + "name": "graphite-web", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/graphite-web", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-08", + "metadataLastUpdated": "2023-06-13" + }, + "description": "The BEopt™ (Building Energy Optimization Tool) software provides capabilities to evaluate residential building designs and identify cost-optimal efficiency packages at various levels of whole-house energy savings along the path to zero net energy. BEopt can be used to analyze both new construction and existing home retrofits, as well as single-family detached and multi-family buildings, through evaluation of single building designs, parametric sweeps, and cost-based optimizations. BEopt provides detailed simulation-based analysis based on specific house characteristics, such as size, architecture, occupancy, vintage, location, and utility rates. Discrete envelope and equipment options, reflecting realistic construction materials and practices, are evaluated. BEopt uses EnergyPlus, the Department of Energy's flagship simulation engine. Simulation assumptions are based on the Building America Housing Simulation Protocols. The sequential search optimization technique used by BEopt: Finds minimum-cost building designs at different target energy-savings levels, Identifies multiple near-optimal designs along the path, allowing for equivalent solutions based on builder or contractor preference. BEopt has been developed by the National Renewable Energy Laboratory in support of the U. S. Department of Energy Building America program goal to develop market-ready energy solutions for new and existing homes.", + "homepageURL": "https://beopt.nrel.gov/home", + "laborHours": 657962.4, + "languages": [], + "name": "BEopt™ (Building Energy Optimization Tool) [SWR-05-41]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://beopt.nrel.gov/BEopt_setup_2.8.0.0", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://beopt.nrel.gov/home", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "2.8.0.0" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-07-08", + "metadataLastUpdated": "2019-07-09" + }, + "description": "Service for publishing user code tarballs in cvmfs repositories", + "laborHours": 288.8, + "languages": [ + "Python" + ], + "name": "cvmfs-contrib/cvmfs-user-pub", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cvmfs-contrib/cvmfs-user-pub", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-10", + "metadataLastUpdated": "2019-07-10" + }, + "description": "Power system modeler-friendly tool for downloading wind and solar power and forecast data.", + "laborHours": 790.4, + "languages": [ + "Python" + ], + "name": "Renewable Resource and Power Data tool (R2PD)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Smart-DS/R2PD", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-10", + "metadataLastUpdated": "2023-05-26" + }, + "description": "The AirflowNetwork software provides the ability to simulate air movement and the resulting transport of contaminants and other materials within a building. The performance of air distribution systems, including supply and return leaks, and multizone airflows driven by outdoor wind and forced air during HVAC system operation are simulated using a nodal network representation of the building. The pressure network model implemented here is based on George Walton's AIRNET and was modified for inclusion in the EnergyPlus building energy modeling software. The algorithm were then extracted from EnergyPlus into a stand-alone package to facility use without the building energy model and more extensive testing and validation of the underlying operations.", + "laborHours": 192158.4, + "languages": [ + "C++" + ], + "name": "AirflowNetwork [SWR 19-45]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/AirflowNetwork", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-11", + "metadataLastUpdated": "2019-07-11" + }, + "description": "This program a new physical insight regarding efforts to evaluate electrochemical catalysts being developed for electrochemical energy conversion and storage. In particular, we ask: The methodology described here offers a solution to the problem of how to conduct Tafel analysis, which is used in determining electrocatalyst performance, in a quantitative manner, rather than through the qualitative guesswork it currently requires. This enables the measurement of electrocatalyst Tafel slopes and their associated parameters in a way that avoids the introduction of researcher bias, a problem to which current methods of Tafel fitting are prone. This procedure should significantly improve the ability of researchers working in the field of electrochemical energy conversion to rate and compare the catalyst materials being developed, advancing the characterization toolkit available to experimental electrochemists. \n\nThis work is born out of our general hypothesis that it should be possible to determine the proper regions for unambiguously fitting Tafel data by applying some set of physical constraints that link aspects of a Tafel plot to its corresponding J-V polarization curve. This algorithm applies such constraints and achieves the extraction of Tafel slopes in a wholly quantifiable and reliable fashion. Verification of this approach is achieved by pairing the theory with experiment, as the algorithm was tested using experimentally acquired data of three distinct, electrochemical reactions: platinum hydrogen evolution, iridium-catalyzed oxygen evolution, and platinum-catalyzed dioxygen reduction. For each of these cases, the algorithm predicts the same Tafel slope as those reported in long-established bodies of electrochemical literature, results suggesting the general applicability of this method for determining electrocatalyst Tafel slopes.", + "laborHours": 0.0, + "languages": [], + "name": "Tafel Fitter v1.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MEG-LBNL/Tafel_Fitter", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-11", + "metadataLastUpdated": "2019-07-12" + }, + "description": "A database, web API and portal will be developed that stores data from synchotron experiments. The data stored will be: \n- metadata about the experiment (who ran it, when it was conducted, what proposal and ESAF were covered) \n- references to raw data (e.g. images taken at the beamline) \n- references to derived data \n\nBeamline users and Beamline staff will have private access to view experiment data and assign web-friendly visualizations to it. They will also be use the portal to download some of the data taken at the beamline. They we will be able to create and approve experiment pages that can be viewed publicly. \n\nThe software created for this project will include replication and fail over technologies to maintain a high level of uptime. \n\nSoftware developed in this project will be: \n- database schema \n- web middleware to create a web API \n- web-based user interface code", + "laborHours": 4833.6, + "languages": [], + "name": "Splash v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/als-computing/splash", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2020-07-09" + }, + "description": "hypre is a library of high performance preconditioners and solvers featuring multigrid methods for the solution of large, sparse linear systems of equations on massively parallel computers.\n", + "laborHours": 0.0, + "languages": [], + "name": "hypre", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hypre-space/hypre/releases/tag/v2.17.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "V2.17.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-10-04" + }, + "description": "This software provides a basic Generative Adversarial Network (GAN) template for modeling 2D slices of N-body dark matter simulations, as part of the Exalearn project. The underlying design is a standard deep convolutional GAN, but we augment it with a technique we are calling multi-channel rescaling. This technique adds a second image channel to the output of the GAN, which represents the data in a different normalization in order to improve the quality of the results.", + "laborHours": 349.6, + "languages": [], + "name": "ExaGAN v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pzharrington/ExaGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-15" + }, + "description": "FUDGEFudge provides (Python based) tools to:\n• Store and modify nuclear data.\n• Convert ENDF-6 formatted nuclear data [1] into Generalized Nuclear\nData (GND) structure [2].\n• Convert LLNL’s ENDL formatted nuclear data [3] into GND.\n• Plot data from GND files.\n• Check for physics problems in GND files.\n• Process nuclear data for use by Monte Carlo and/or deterministic\ncodes. Fudge contains hooks for the future addition of nuclear data\nprocessing routines.\nThe Fudge release includes samples of published ENDF-6 formatted data that\ncan be converted to the new GND format.\nThis software is the next release in a series of releases that began with GND\nversion 0.1 [2].", + "laborHours": 84664.0, + "languages": [], + "name": "fudge", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/paulromano/fudge", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "GIDIplus contains libraries for reading and using GNDS-formatted nuclear data.\n\nIt includes sub-packages\nGIDI, MCGIDI, PoPs, numerical Functions and status Message Reporting along with scripts for building and installing the entire library.", + "laborHours": 60359.2, + "languages": [], + "name": "Generalized Interaction Data Interface and associated packages", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "The Bridge Kernel is a Jupyter Kernel for connecting to compute backends that implement the bridge kernel (bk) protocol. The bk protocol is a client-server protocol that emphasizes minimal dependencies, easy embedding with MPI, secure connections + authentication, and non-local backends with automatic\ntunneling.", + "laborHours": 562.4, + "languages": [], + "name": "Bridge Kernel", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/bridge-kernel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "Implementation of the Progressive Hedging algorithm written in Julia utilizing JuMP. This is used to solve multistage optimization problems (e.g. Stochastic programs or capacity expansion models). The user uses the StructJuMP extension of JuMP to create the model and build up the scenario tree.", + "laborHours": 820.8, + "languages": [], + "name": "ProgressiveHedging.jl", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ProgressiveHedging.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "A comprehensive package to study lattice dynamics from first-principles. The interatomic force constants were fitted using the compressive sensing algorithm.", + "laborHours": 11734.4, + "languages": [], + "name": "Compressive sensing lattice dynamics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/csld", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "The General Interaction Data Interface (GIDI) is a C++ API that reads and writes nuclear reaction data stored in the General Nuclear Data Structure (GNDS). GNDS is a new \"format\" for storing nuclear reaction data developed by the Working Party on Evaluation Co-operation (OECD/NEA/WPEC) Subgroup 38. \n\nGNDS can store evaluated nuclear data as well as nuclear data processed for deterministic (multi-group) and Monte Carlo transport. GIDI handles and provides accesses to all forms of the GNDS nuclear data.\n\nFor multi-group data, GIDI provides functions to sum the data over all reactions. It also has functions for collapsing multi-group data to a small subset of groups and can transport correct multi-group data using the Pendlebury/Underhill formalism.\n\nThe GNDS definition supports data for a PROjectile hitting a TARget for a given Evaluation. In GIDI this is called a PROTARE. For example, a neutron hitting O-16 from the ENDF/B-VIII.0 evaluation.\n\nTo support a collection of protares, GIDI adds a Map class. The map class reads in a \"map\" file which specifies a list of projectile/target/evalaution's and their associated protare files. \n\nWith a map instance, a user can request a specific projectile/target/evaluation and the map instance will return the requested protare.", + "laborHours": 60359.2, + "languages": [ + "C++" + ], + "name": "General Interaction Data Interface", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.17" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-11-26" + }, + "description": "Software suite with multitask learning models. The pipeline includes functionality to process data, train, evaluate models, and generate reports.", + "laborHours": 1444.0, + "languages": [], + "name": "Multi-Task Learning Software Suite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MTL-suite", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "A new format for storing particle information (i.e., mass, spin, parity) has been developed. \n\nThe format is a subset of the Generalized Nuclear Data Structure (GNDS) developed for storing nuclear reaction data. \n\nA C++ library dubbed \"Property of Particles\" (PoPs) has been developed to read particle data in the GNDS\nformat. \n\nThe PoPs library provides functions for reading in a GNDS particle database as well as for accessing a particle and its properties.", + "laborHours": 60359.2, + "languages": [ + "C++" + ], + "name": "PoPsCpp", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "Sina is a tool set for modern scientific data management that provides flexible, light-weight support of non-bulk data capture for retention in and queries against SQL and noSQL data stores. HPC simulations traditionally maintain their data in files. Extracting data of interest for subsequent analysis then requires the time-consuming process of traversing directories and scraping data from files in a variety of formats. Sina facilitates capturing relevant data during execution or post-processing of simulation runs for retention in and queries from a modern data store. The tools are sufficiently general to allow for the inclusion of new fields as scientists learn more about their data. Libraries, currently in C++ and Python, and a command line interface (CLI) are provided.\nSina's flexibility starts with a general schema, in JSON, for the collection of non-bulk simulation data. JSON provides a flexible, human-readable representation of the data that of interest. Sina currently has a C++ library for simulations to write data to and read from a schema-compliant file for subsequent ingestion into one of the supported data stores. However, applications are free to write their data directly into a schema-compliant file. Python packages provide data ingestion, management, query, and export capabilities. A command line interface (CLI) provides simplified access to these features. A common application programming interface (API) is used to maintain and query data in any of the supported data stores, which are currently limited to SQL and Apache Cassandra (a column store). Tutorials, demonstrations, and examples illustrate aspects of the process using scripts and Jupyter notebooks.", + "laborHours": 5487.2, + "languages": [], + "name": "Simulation INsight and Analysis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Sina", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "The numericalFunction C library is designed to handle point-wise interpolative data representing a mathematical function. The library currently handles 1-d functions (i.e., functions of the format f(x)). \n\nThe main object is the ptwXYPoints C struct that holds list of x,y pairs sorted by ascending x-values with an interpolation rule. That is, it contains the 1-d function f(x) = y(x). \n\nFunctions are included that support common unitary and binary operations (e.g., negation, addition, multiplication). \n\nAs example, if f(x) and g(x) are two ptwXYPoints instances, then routines to calculate f(x) + g(x) and f(x) * g(x) are included.\n\nThe library support storage of data with lin-lin, lin-log, log-lin, log-log and flat (or histogram) interpolation.\n\nFunctions to convert any of the supported interpolation to lin-lin are included. However, many of the binary functions only support lin-lin interpolation.\n\nThe library also contains a C struct for storing a Legendre series representation of a 1-d function, and functions to convert Legendre series to and from a ptwXYPoints instance.\n\nA python interface to the library is included, with the ptwXYPoints C struct treated as a class. This class has many of the standard python math methods (e.g., __add__, __mul__).", + "laborHours": 60359.2, + "languages": [ + "Python" + ], + "name": "numericalFunctions", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-16" + }, + "description": "A Browser-based visualization of morphology, material, and chemical data extracted from chemical papers. This UI is focused for specifically nanomaterial synthesis papers. The visual analytic environment allows the user to explore a large number of papers quickly, through an interactive, intuitive, and visual way that helps see possible trends in the data. This exploration-oriented systems allows domain experts who may not have an extensive background in writing analysis code or database queries to easily express their idea to experiment on the data and view the results.\nThe visualization software requires the data in JSON format. The data packaged with the software is the result of 35k nanomaterial synthesis papers queried from Elsevier, created through a separate software pipeline. The data contains information such as the title, authors, chemicals, and created material and morphology.", + "laborHours": 2773893.6, + "languages": [], + "name": "Materials Informatics ChemVis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MI-ChemVis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-16" + }, + "description": "goTLS is an automated TLS certificate issuance and management tool for Windows, Mac, and Linux. \n\nIt can generate keys, CSRs, and optionally obtain the certificate with an internal Active Directory Certificate Services (ADCS) endpoint.", + "laborHours": 243.2, + "languages": [], + "name": "goTLS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gotls", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-16" + }, + "description": "Zero-order Reaction Kinetics (Zero-RK) is a software package that simulates chemically reacting systems in a computationally efficient manner. The fundamental advance embodied in Zero-RK is the numerical approach, which results in orders-of-magnitude reduction in simulation time while maintaining the accuracy of the results.", + "laborHours": 13497.6, + "languages": [], + "name": "Zero-Order Reaction Kinetics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/zero-rk", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-16" + }, + "description": "Unlike computer languages like C++ which has throw/catch, Python which has try/except and other newer computer languages, C has no built-in mechanism for handling exceptions (e.g., memory allocate failure or a divide by zero exceptions).\n\nWhile simple exception handling in the form of an integer parameter (e.g, errno) or an enum are often implemented in C programs, the richer types of exception reporting possible with newer computer languages are rarely implemented in C. \n\nThe statusMessageReporting package was created to facilitate rich exception reporting by C functions to their calling functions.\n\nThe statusMessageReporting (smr) package allows a function, called the generator, to communicate an exception to its calling function using a statusMessageReporting report. \n\nThe main parts of a report are:\n\n1)the level of the report called the status (valid levels are smr_status_Ok, smr_status_Info, smr_statusWarning and smr_status_Error)\n\n2) a string called the report's message and 3) two integer values, one representing the generator's ID, called the libraryID, and the other is the library's specific integer, called the code, that represents the type of exception the generator is reporting.\n\nThe code is similar to the errno for the C standard library. Since libraries are often developed independent of one another, they often use the same code values to represent different exceptions (e.g., one library may define the code 3 to be an error opening a file while another library may define the code 3 to be a divide-by-zero error) which is why the libraryID is needed. \n\nThat is, the equivalent of errno is the combination libraryID:code. To insure that each library's libraryID is unique, libraryIDs must be obtained from the function smr_registerLibrary.\n", + "laborHours": 60359.2, + "languages": [ + "Python" + ], + "name": "statusMessageReporting", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-16" + }, + "description": "SPIFY is a C++ library for parsing input files to be used in scientific computing applications.\n\nThe library allows an application developer to define a full set of required and optional input variable of different types\nand handles all of the parsing and validation.", + "laborHours": 912.0, + "languages": [ + "C++" + ], + "name": "Spify Parser of Input Files with YAML syntax", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/spify", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-17" + }, + "description": "WaterSystems.jl is a Julia package for defining water delivery infrastructure system data and problem definitions. The WaterSystems.jl package enables parsing from the EPANET *.inp file format and the expression of data for WaterSimulations.jl models. WaterSystems.jl defines a data schema for water infrastructure networks. ", + "laborHours": 167.2, + "languages": [ + "julia" + ], + "name": "WaterSystems.jl", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WaterSystems.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-17" + }, + "description": "This Matlab script implements a simple topology optimization algorithm that minimizes the compliance of a structure within a 3D prismatic design domain. \n\nIt uses a simple linear elastic finite element solver to solve the equilibrium equations, and the optimality criterion (00) method to update the design iteratively.\n\nThis functionality is identical to, or the simplest possible extension from 2D to 3D of, a 99-line Matlab code released in 2001 in a journal article by Sigmund. \n\nWhat is new in this code is our implementation of simple surrogate models for several truss micro-architectures, which converts this code to a multiscale design tool, whereas the original code is single-scale. \n\nThe development of these surrogate models and their implementation is described in a journal article we intend to submit. \n\nWe plan to include the full source code in an Appendix in this paper. \n\nThe code’s primary function is as a pedagogical tool rather than as a finished software product. \n\nSigmund’s 2001 paper describes the implementation line-by-line.\n\nWe are including this updated version of the code to allow the reader to understand exactly what changes must be made to a “standard” topology optimization code to implement the surrogate models and thus multiscale design optimization.", + "laborHours": 91.2, + "languages": [ + "MATLAB" + ], + "name": "Matlab Code for Multiscale Topology Optimization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MultiscaleTopOpt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-19", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Tools to construct a model for sources of radioactive backgrounds in a low radioactivity dertector system\nBackground explorer simplifies or automates many of the tedious and error-prone tasks involved in creating a detailed radioactivity budget for a low background detector system. The tool also provides a rich web interface allowing even nontechnical users to easily modify the model assumptions and drill-down into the model and result details.\nBackend: https://github.com/bloer/bgmodelbuilder Web application: https://github.com/bloer/bgexplorer \nDemo/user template: https://github.com/bloer/bgexplorer-demo", + "laborHours": 2325.6, + "languages": [], + "name": "Background Explorer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bloer/bgmodelbuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2024-07-23" + }, + "description": "PyGSTi is a Python package for modeling and characterizing noise (errors) in small quantum information processors. In addition to being a basic framework for describing quantum circuits and noise models, it implements mainstream quantum characterization, verification, and validation (QCVV) protocols such as Gate Set Tomography (GST), Randomized Benchmarking (RB), Robust Phase Estimation, and Idle Tomography. It also implements prototype protocols used for timeseries analysis and crosstalk detection, all of which have the goal of better understanding the noise found in existing as-built experimental devices. The central protocol of pyGSTi (from where it derives its name) is Gate Set Tomography. GST is a theory and protocol for simultaneously estimating the state preparation, gate operations, and measurement effects of a physical system of one or many quantum bits (qubits). These estimates are based entirely on the statistics of experimental measurements, and their interpretation and analysis can provide a detailed understanding of the types of errors/imperfections in the physical system. In this way, GST provides not only a means of certifying the “goodness” of qubits but also a means of debugging (i.e.\nimproving) them. The other protocols follow this similar pattern in that they use statistical inference and analysis of experimental data to estimate one or more properties of the noise in a\ndevice.", + "laborHours": 317619.2, + "languages": [ + "C++", + "CSS", + "HTML", + "Jupyter Notebook", + "Cython", + "Python" + ], + "name": "Python GST Implementation (PyGSTi) v. 0.9", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyGSTi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.9.12" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2020-06-15" + }, + "description": "HyRAM is a software toolkit for conducting quantitative risk assessment (QRA) and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM contains validated, simplified hydrogen behavior models, a standardized QRA approach, and engineering models and generic data relevant to hydrogen installations. HyRAM 1.0 was developed by Sandia National Laboratories for the U. S. Department of Energy.\nSAND2019-5270 M", + "laborHours": 21508.0, + "languages": [], + "name": "HyRAM (Hydrogen Risk Assessment Models) v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hyram", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 2.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2019-07-22" + }, + "description": "Scripts that enable emulating firmware by intercepting low-level hardware abstraction function calls and replacing their execution with abstractions of the hardware the intercepted functions are intended to interact with.", + "laborHours": 4316.8, + "languages": [], + "name": "HALucinator v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/embedded-sec/halucinator", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A JIRA Add-on that adds custom workflows and automation hooks for provisioning services within other Atlassian tools like Confluence, Bitbucket, and Crucible/Fisheye based on project keys", + "laborHours": 4727.2, + "languages": [], + "name": "pnnl/jira-aperture", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/jira-aperture", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2025-01-08" + }, + "description": "In silico chemical library engine for high-accuracy chemical property prediction", + "laborHours": 3815.2, + "languages": [], + "name": "pnnl/isicle", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/isicle", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Plan and visualize staff labor allocation. This package produces outputs in spreadsheet form that are easily navigable and informative. Outputs include staff-level individual summaries detailing project commitment monthly, project-level summaries highlighting the number of staff and hours per project within an organization, a staff overview summary containing funding probability considerations and visualization, all staff rundown of monthly commitments tied to visual indicators for over- and under-commitment, and overall summary charts and data for all staff and all project and their interrelation. labor_planner was designed for extension and reuse and the authors encourage continued community development.", + "laborHours": 668.8, + "languages": [], + "name": "Labor_Planner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/crvernon/labor_planner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-23", + "metadataLastUpdated": "2019-07-25" + }, + "description": "A critical component of designing solar energy projects that will have long-term profitability is the availability and access to accurate “bankable data”, methodologies and tools to understand the uncertainties in the data. The current solar energy performance and economic models used to convert solar resource data to power generation do not factor in or provide adequate information regarding the uncertainty in the solar resource information. The Solar resource uncertainty (SOLARUN) application assists stakeholders to quantify solar resource measurement uncertainty from radiometers which ultimately support in the decision-making process, speeds up the acceptance and deployment of projects and reduces risk to the financiers and developers.", + "laborHours": 319.2, + "languages": [], + "name": "SOLARUN (SolarResourceTools)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SolarResourceTools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-25", + "metadataLastUpdated": "2019-07-25" + }, + "description": "AnisWave2D is a 2D finite-difference code for simulating seismic wave propagation in fully anisotropic materials. The code is implemented to run in parallel over multiple processors and is fully portable. A mesh refinement algorithm has been utilized to allow the grid-spacing to be tailored to the velocity model, avoiding the over-sampling of high-velocity materials that usually occurs in fixed-grid schemes.", + "laborHours": 0.0, + "languages": [], + "name": "AnisWave2D", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sainslie1966/AnisWave2D", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL is developing an automated procedure to perform the system-level model validation for the Central America power grid, which includes six countries and one power system equivalent model for Mexico representation is also considered. The specific features for this invention are given as follows: 1) Automated case integration of Mexico equivalent model and Central America grid model; 2) Automated power system event replay based on system-level dynamic simulations; 3) Automated extraction and comparison of power flow conditions/measurements/quantities between SCADA/PMU data and simulated data for pre-event, during event and post-event stages; 4) One procedure to identify potential mismatch in power flow conditions and erroneous model parameters in power system dynamic models.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Automated System-Level Model Validation for Central America", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Rapid Analytics for Disaster Response (RADR) is a disaster response and situational awareness system that provides actionable insights using image analytics derived from optical and radar-based remotely-sensed imagery (optical and radar satellite, airborne, UAS). Geospatial analysis can also interface with the image analytic results to understand potential impacts to critical infrastructure assets. The rapid response is driven by a lifecycle workflow that spans event monitoring and action, image acquisition and retrieval, image pre-processing, image analytics algorithm deployment, analytics packaging, and analytics delivery.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Rapid Analytics for Disaster Response (RADR)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Industrial Radiography Mobile Source Transit Security (IR-MSTS) Software and Firmware Applications and Components described here are part of a system developed under NNSA funding to track mobile radioactive sources used in the industrial radiography service industry. The individual software applications and libraries, and firmware executables work together and in conjunction with the electronic hardware components to provide situational awareness of the radioactive sources as they are transported from the home base of operations to a job site and back again. Industrial radiography devices are equipped with IR-MSTS components to provide near real time source location information. A Global Positioning System (GPS) is used to track the geographic location of the transport vehicle. Various sensors are used to detect and report tamper of the IR-MSTS components. Base Station application software, IR Dashboard, allows qualified personnel to track alarms, device information and locations and provides contact info of individuals that need to be notified should anomalous conditions be detected. Firmware for Industrial Radiography 31602 IR Cloud Services for Industrial Radiography 31600 PM-Mat Firmware for Industrial Radiography 31599 IR Dashboard for Industrial Radiography 31598 PM-Box Firmware for Industrial Radiography 31597 PM-Tag Firmware for Industrial Radiography 31596 VCU Firmware for Industrial Radiography 31595", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Industrial Radiography Mobile Source Transit Security Software and Firmware", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Well Logging Mobile Source Transit Security (WL-MSTS) system was developed under funding from the National Nuclear Security Administration (NNSA) Office of Radiological Security (ORS). The objective of the system is to track mobile radioactive sources used in the well-logging service industry in support of oil and gas exploration. The individual software applications and libraries, and firmware executables work together and in conjunction with the electronic hardware components to provide situational awareness of the radioactive sources as they are transported from the home base of operations to a job site and back again. Information flows in near real time from the transport vehicle carrying the sources to the end user's central monitoring center using both cellular and satellite communications. A combination of active radio-frequency (RF) tags (attached to source shields) and radiation sensing is used to monitor the proximity of the radioactive sources to the transport vehicle. A Global Positioning System (GPS) is used to track the geographic location of the transport vehicle. Various sensors are used to detect and report tamper of the WL-MSTS components. An in-Cab Unit (iCU) is used to provide local status of the monitoring system to the driver of the transport vehicle. A browser based application allows authorized engineers to interact with the monitoring system to configure it and check status. Base Station application software allows qualified personnel to track alarms, source information and source locations and provides contact info of individuals that need to be notified should anomalous conditions be detected.\nWell Logging Master Control Unit (MCU)\t31390\nWell Logging MSTS rTag firmware\t31433\nWell Logging - In Cab Unit firmware\t31432\nBLE Beacon Electronic Tag (eTag) Firmware\t31480\nHome Base Security Solution (HBSS) Vault Extender Scanner\t31566\nHome Base Security Solution (HBSS) Master Scanner Firmware\t31567\nWell Logging MSTS Message Parser Library\t31568\nWell Logging MSTS GSOC Viewer\t31569\nWell Logging MSTS Admin Tool\t31570\nWell Logging HBSS Bunker Automated Data Service (BADS)\t31571\nWell Logging HBSS Bunker Inventory Graphical System (BIGS)\t31572\nWell Logging Master Control Unit Overpack (WL-MCU-OP) Firmware\t31583", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "The Well Logging Mobile Source Transit Security (WL-MSTS) system", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2019-07-29" + }, + "description": "The scientific community performs a lot of redundant work when working with data. Researches tend to write their own code to perform basic functions for reading, visualizing, and analyzing the data. This strategy is unnecessarily time consuming, and potentially costly, for the individual researcher (as well as for programs). Open-source software disrupts that process and moves the development effort toward capabilities that can be used by the broader scientific community. The broader scientific community can then, in turn, contribute to and collaborate on efforts to improve the process for the individual researcher and program. Researchers will be able to do more science with fewer resources without the burden of developing code from the ground up. For any software to be adopted by a community, it needs to have a solid framework that will be easy to use and provide clear benefit worthy of the investment in participating. In support of this goal, our Atmospheric Data Community Toolkit will leverage the knowledge gained from the successful adoption of the Python Atmospheric Radiation Measurement User Facility Radar Toolkit (Py-ART) to build that framework. The framework will provide the environment to enable collaboration in the research community. This environment will allow the development of tools for funded programs, as well as provide researchers in the scientific community with code for advancing their work. Research programs will also be able to adopt code provided by the scientific community without having to develop it from scratch. The final goal of this proposed effort is to have a framework on GitHub that has the basic features that the atmospheric research community needs to begin working with and adopting, including, but not limited to, reading and visualization. We expect future effort will be needed for Argonne scientists to demonstrate their specific capabilities within this framework. This project will provide an avenue for other proposed research to be demonstrated, such as the Global Oceans/Argonne proposed Atmospheric Instrumentation Suite; edge computing National Science Foundation proposed effort; and the Computing, Environment, and Life Sciences Directorate's strategic effort on the Southern Great Plains climate observation site relating to water across the surface interface. ", + "laborHours": 3784.8, + "languages": [], + "name": "ATMOSPHERIC DATA COMMUNITY TOOLKIT (ACT)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-DIGR/ACT", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "A C++ implementation of a web_view interface being proposed for standardization by the C++ standards committee.", + "laborHours": 319.2, + "languages": [], + "name": "web_view", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hfinkel/web_view", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "GRChombo is a new numerical relativity code written to take full advantage of modern parallel computing techniques. GRChombo's features include full adaptive mesh refinement (AMR) with block structured Berger-Rigoutsos grid generation which supports non-trivial \"many-boxes-in-many-boxes\" meshing hierarchies, and massive parallelism through the Message Passing Interface (MPI). GRChombo evolves the Einstein equation with the standard BSSN formalism, with an option to turn on CCZ4 constraint damping if required. It can stably and accurately evolve vacuum black hole spacetimes such as binary black hole mergers, and non-vacuum spacetimes such as scalar collapses into black holes. ", + "laborHours": 6551.2, + "languages": [], + "name": "GRChombo", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GRChombo/GRChombo", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-31" + }, + "description": "PyARC is a wrapper script developed to integrate the Argonne Reactor Computation suite of neutronic codes into the NEAMS Workbench user interface. It contains the Workbench \"common input\" definition, handles some pre-processing, writes the native codes inputs, handles the runtime environment, and performs some post-processing. It was developed to facilitate access and utilization of the ARC codes, and facilitate transition to higher fidelity NEAMS codes.", + "laborHours": 21356.0, + "languages": [], + "name": "PyARC", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/neams-workbench/PyARC", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "OpenADR 2.0 a/b Virtual End Node (VEN) node for Node-Red.", + "laborHours": 1930.4, + "languages": [], + "name": "node-red-contrib-oadr-ven", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/node-red-contrib-oadr-ven", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "Calibrate high-pressure using Au or Ag powder diffraction. Designed to be used with spec files from the 4-ID-D beamline, Advanced Photon Source, Argonne National Laboratory. ", + "laborHours": 851.2, + "languages": [], + "name": "pypressxrd", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gfabbris/pypressxrd", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "To the author's knowledge, VALENCE is the only implementation of the variational subspace valence bond (VSVB) method. At Argonne, VSVB was developed from the ground up with extreme scalability and high performance on emerging hardware paradigms in mind. Thus, VSVB is the only quantum chemistry method that promises high accuracy with cross-cutting applicability at the exascale. VSVB also offers unique opportunities for machine learning and stands to revolutionize many fields across materials science, chemistry, and biology. The existence of an open-source software implementation of VSVB is an essential step in its development and support for the benefit of the community. ", + "laborHours": 4924.8, + "languages": [], + "name": "VALENCE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gdfletcher/VALENCE", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "This software is a package for assimilating data from multiple radars and models together to create a 3D wind retrieval over a region. The framework is based off of the minimization of a cost function related to the varying sensors, mass continuity, and model. Since it is open source the community is able to contribute and expand the package to use data from their own desired model or sensor. ", + "laborHours": 2675.2, + "languages": [], + "name": "PyDDA (Pythonic Direct Data Assimilation)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openradar/PyDDA", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dching@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2023-02-02" + }, + "description": "Tike is a library for reconstructing a 3D object from its diffraction measurements.", + "laborHours": 0.0, + "languages": [ + "CUDA", + "Python" + ], + "name": "Tike", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdvancedPhotonSource/tike.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "This is python software couples UrbanSim, a free software package to the Argonne Isomodel building energy model and provides a few analysis tools.", + "laborHours": 0.0, + "languages": [], + "name": "Urbansim to Isomodel", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/urbansim-isomodel", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-30" + }, + "description": "X-ray ptychography imaging at synchrotron facilities like the Advanced Photon Source (APS) involves controlling instrument hardwares to collect a set of diffraction patterns from overlapping coherent illumination spots on extended samples, managing data storage, reconstructing ptychographic images from acquired diffraction patterns, and providing the visualization of results and feedback. This brings up the need to develop a flexible, robust and user friendly processing pipeline for ptychographic data analysis. Here we present a software framework including visualization and ptychographic data reconstruction for streaming data analysis and reconstruction. ", + "laborHours": 4666.4, + "languages": [], + "name": "ptychopy", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kyuepublic/ptychopy", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "This IDL based GUI interface is for complete phase retrieval based on transport of intensity formalism. It provides routines for alignment of images, alignment of unflipped and flippped image stacks and finally various options for phase retrieval algorithm. ", + "laborHours": 1140.0, + "languages": [], + "name": "Full TIE Reconstruction", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cphatak/full_tie", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2020-06-01" + }, + "description": "Library for managing ensemble-like collections of computations", + "laborHours": 7311.2, + "languages": [], + "name": "LibEnsemble", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Libensemble/libensemble", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2024-08-07" + }, + "description": "SWinzip is a Matlab and C++ library for scientific lossy data compression and reconstruction using compressed sensing and tree-wavelets transforms. These methods are known for their large compression and usefulness in data analytics such as features extraction. Compressed sensing and wavelets methods rely heavily on sparse and dense linear algebra operations implemented through the Boost codes in our library. SWinzip accommodates data represented on both regular grids (e.g. image data) and point-clouds (e.g. unstructured meshes).\n\nIn SWinzip v2.0, there is more focus on wavelet compression and the following\nfeatures are added:\n\n- The matrix-free (direct) wavelet transform is implemented in both C++ and Matlab. A threshold-based compression can now be used. Examples for distributed compression are also added.\n- Python implementation of Alpert wavelet transforms\n- Field data comparison using wavelets in Matlab with global and local metrics", + "laborHours": 13740.8, + "languages": [ + "C++", + "C", + "MATLAB", + "Makefile", + "Python" + ], + "name": "SWinzip v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SWinzip", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 2.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "X-ray grating interferometry has been employed for a wide range of imaging applications by using the Talbot self-images of a grating. At synchrotron facilities, it has also been exploited to characterize the coherence and wavefront of the x-ray beam. The method is relatively straightforward, easy to implement, and provides accurate quantitative data. However, to exploit its full potential, it requires highly specialized, robust data analysis. If this works, we have set the framework for the development and dissemination of a robust open-source code called wavepy that is tailored to the data analysis for imaging and beam characterization using grating interferometry. Wavepy consists of a Python library for data analysis of x-ray grating interferometry. The library takes advantage of the python programming language capabilities and flexibility, and aims to be easy to collaborate, distribute, and integrate with other imaging packages. The main reason for using Python is twofold: to take advantage of a widely used language in the scientific community, and also to make extensive use of the existing Python libraries for numerical calculation and plotting, namely numpy, scipy and matplotlib. Installation is facilitated by using conda to solve dependencies. The development makes use of git for version control and collaborative development. The code is hosted in the GitHub repository https://github.com/APS-XSD-OPT-Group/wavepy. One of the reasons for using Python is to be able to integrate wavey with other projects, mainly DXchange to seamlessly load images of different formats, and TomoPy for tomography. The main code is a collection of functions that can be used in different ways, for instance, inside a development environment (DE) or by creating a graphical interface that uses wavepy underneath. ", + "laborHours": 3040.0, + "languages": [], + "name": "wavepy", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/APS-XSD-OPT-Group/wavepy", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "Supervised Learning Approach for Dynamic Sampling using Deep Neural Networks.", + "laborHours": 608.0, + "languages": [], + "name": "SLADS-Net", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cphatak/SLADS-Net", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "DeepHyper is a Python package and infrastructure that targets experimental research in DL search methods, scalability, and portability across high performance computing (HPC) systems. It comprises three modules: benchmarks, a collection of extensible and diverse DL hyperparameter search problems; search, a set of search algorithms for DL hyperparameter search; and evaluators, a common interface for evaluating hyperparameter configurations on HPC platforms. ", + "laborHours": 12388.0, + "languages": [], + "name": "DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/deephyper/deephyper", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "Decaf is a dataflow system for the parallel communication of coupled tasks in an HPC workflow and allows the user to allocate resources and execute custom code in the dataflow. The runtime for calling tasks is entirely message-driven. Such a message-driven runtime allows cyclic task dependencies in the workflow graph, for example, to enact computational steering based on the result of downstream tasks. Decaf can stand alone as a complete workflow system, or Decaf can also be used as the dataflow layer by one or more other workflow systems to form a heterogeneous task-based computing environment.", + "laborHours": 45372.0, + "languages": [], + "name": "Decaf", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tpeterka/decaf", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-31", + "metadataLastUpdated": "2019-07-31" + }, + "description": "Derivatives are required in many contexts: optimization, sensitivity analysis, uncertainty analysis, and parameter estimation. The radolc package is an interface to ADOL-C == a C++ library that facilitates the computation of first and higher derivatives of vector functions that are defined by computer programs. ADOL-C can compute gradients, the Jacobian matrix, the Hessian matrix, Jacobian vector products and Hessian vector products.", + "laborHours": 24852.0, + "languages": [], + "name": "radolc", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sriharikrishna/radolc", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-31", + "metadataLastUpdated": "2019-07-31" + }, + "description": "ENRICO is a code to automate the workflow for iteratively solving neutral particle transport via the OpenMC code and fluid dynamics via the Nek5000 code. It establishes a mapping between the geometry representation of a model in OpenMC and the spectral element mesh used by Nek5000 so that the output of each code can be used as the input of the other. Heat generation rates as solved by OpenMC are used as heat sources in a Nek5000 simulation, and the temperature/density fields from Nek5000 are used as inputs for the OpenMC model. Both OpenMC and Nek5000 are open-source, community-developed, simulation codes. ", + "laborHours": 34245.6, + "languages": [], + "name": "ENRICO: Exascale Nuclear Reactor Investigative Code ", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/enrico-dev/enrico", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-31", + "metadataLastUpdated": "2019-07-31" + }, + "description": "A source-to-source translation tool for assisting software developers in migrating from OpenACC to OpenMP 4.5", + "laborHours": 91.2, + "languages": [], + "name": "ACC2OMP", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/naromero77/ACC2OMP", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "velliquettet@ornl.gov" + }, + "date": { + "created": "2019-07-31", + "metadataLastUpdated": "2019-09-19" + }, + "description": "The Advanced Terrestrial Simulator (formerly sometimes known as the Arctic Terrestrial Simulator) is a code for solving ecosystem-based, integrated, distributed hydrology. Capabilities are largely based on solving various forms of Richards equation coupled to a surface flow equation, along with the needed sources and sinks for ecosystem and climate models. This can (but need not) include thermal processes (especially ice for frozen soils), evapo-transpiration, albedo-driven surface energy balances, snow, biogeochemistry, plant dynamics, deformation, transport, and much more.\n\nPreferred citation (including correct author order):\nEthan Coon, Markus Berndt, Ahmad Jan, Daniil Svyatsky, Adam Atchley, Eugene Kikinzon, Dylan Harp, Gianmarco Manzini, Eitan Shelef, Konstantin Lipnikov, Rao Garimella, Chonggang Xu, David Moulton, Satish Karra, Scott Painter, Elchin Jafarov, and Sergi Molins. 2019. Advanced Terrestrial Simulator. Next Generation Ecosystem Experiments Arctic Data Collection, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, USA. Version [xxx]. DOI link: https://doi.org/10.11578/dc.20190911.1", + "laborHours": 58231.2, + "languages": [], + "name": "Advanced Terrestrial Simulator", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/amanzi/ats", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-01", + "metadataLastUpdated": "2019-08-01" + }, + "description": "This software couples commercial and existing transmission system simulation software PSSE and distribution system simulation software OpenDSS to enable transmission and distribution (T&D) co-simulation. This tool is capable of both steady-state and dynamic T&D co-simulation. It is written in Python. It also integrates dynamic distributed energy resource (DER) models (Python-based standalone models developed under an EERE project) into OpenDSS to involve dynamics of DER. This tool allows transmission system entities to understand the full spectrum impact of DER on the bulk electric system (BES) and assists in ensuring secure and reliable grid planning and operations. ", + "laborHours": 4848.8, + "languages": [], + "name": "TDcosim - Transmission and Distribution System Co-simulation Tool", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tdcosim/TDcoSim", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-08-01", + "metadataLastUpdated": "2019-10-24" + }, + "description": "ML4Chem is a free, and open-source machine learning package for chemistry and materials sciences written in Python. It allows scientists to focus on applying the most commonly used machine learning models in chemistry and materials sciences with minimum effort.", + "laborHours": 2675.2, + "languages": [], + "name": "ML4Chem: Machine Learning for Chemistry and Materials v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/muammar/ml4chem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-02", + "metadataLastUpdated": "2019-08-02" + }, + "description": "This software allows the user to run simulations of a solar PV-Distributed energy resource connected to a stiff voltage source. It allows modifying DER parameters, introducing external disturbance events, and visualizing the simulation results. It models the PV-DER (inverter) using dynamic phasor concept. ", + "laborHours": 2401.6, + "languages": [], + "name": "Photovoltaic Distributed Energy Resource (PV-DER) Simulation Utility", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sibyjackgrove/SolarPV-DER-simulation-utility", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Sub-Regional Nexus Modeling\nMetis provides a framework allowing analysis of dynamics across multiple sectors including energy, water, land and socioeconomics at variable spatial and temporal scales. It is designed to be a flexible tool which can take inputs from both global integrated assessment models (IAMs) which capture global dynamics as well as more detailed models which capture specific sub-regional and sectoral details at finer resolutions. Metis integrates across tools by sharing data in standardized formats.", + "laborHours": 14348.8, + "languages": [], + "name": "JGCRI/metis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/metis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-08-05", + "metadataLastUpdated": "2019-10-03" + }, + "description": "BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets) uses a data brokering approach to synthesize diverse earth science data from a variety of remote sources in real-time without the need for additional storage. BASIN-3D is an extendable Django web framework application using a generalized data synthesis model that makes the synthesized data available via REpresentational State Transfer (REST) Application Programming Interface (API). We have currently implemented our data synthesis model to represent sensor-based time series earth science observations across a hierarchy of spatial locations. Supporting our data synthesis model is a plugin framework that allows developers to map data sources of interest to the BASIN-3D synthesis model\n", + "laborHours": 2143.2, + "languages": [], + "name": "Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets v1.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Watershed-Function-SFA/BASIN-3D", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-08-07", + "metadataLastUpdated": "2020-09-08" + }, + "description": "GPTune is an autotuning framework for exascale applications. Given an application with a set of parameters controlling its performance (e.g. runtime, memory and/or energy consumption, numerical accuracy, ...), GPTune aims at finding a combination of the parameters that yields the best possible performance. Although general enough, GPTune specializes in the tunning of expensive-to-run applications, where the cost of running the application is very expensive (in terms of computing power requirement and/or runtime).", + "laborHours": 38471.2, + "languages": [], + "name": "GPTune v.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gptune/GPTune", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-08-08", + "metadataLastUpdated": "2023-04-24" + }, + "description": "Researchers at NREL have developed a novel real-time control architecture to optimize the operation of DERs at residential, commercial, and industrial levels. The real-time system enables (portions of) feeders to emulate virtual power plants providing services to the rest of the grid, while ensuring satisfaction of electrical limits and maximizing customers’ benefits. This system can be integrated with legacy hardware and/or new advanced systems to optimally manage both individually-controlled DERs and aggregations of DERs. By virtue of the proposed engineering approach, the DERs collectively regulate the powers at an electrical point to respond to grid dispatch signals such as an automatic generation control, a ramping signal, or a 5-minute dispatch. Overall, this architecture allows end customers to minimize their payments and partake in grid operations while guaranteeing power quality in the distribution network.", + "homepageURL": "https://www.labpartnering.org/p/lab-technologies/ce8d218e-4826-497d-aa9b-af23282648ec", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Real-Time Optimization of Distribution-level Energy Resources [SWR-18-27]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.federallabs.org/technology/real-time-optimization-of-distribution-level-energy-resources", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.labpartnering.org/p/lab-technologies/ce8d218e-4826-497d-aa9b-af23282648ec", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a database and associated data treatment that enables software for real-time Raman spectral analysis of sample streams in traditional flow and static solution cells and microfluidic devices. It will enable a chemometric approach to identify and quantify species of interest, including UO22+, nitric acid, and total nitrate. \nLicensed with right to sublicense.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Database and training set enabling real-time, on-line process monitoring", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-08-09", + "metadataLastUpdated": "2019-08-12" + }, + "description": "ExaCMech is a GPU-friendly library of constitutive models. Crystal-mechanics-based and porositymechanics-\nbased models are a principal focus.", + "laborHours": 1900.0, + "languages": [], + "name": "LLNL/ExaCMech", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/exacmech", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-08-09", + "metadataLastUpdated": "2019-10-11" + }, + "description": "When wind blows over snow, it self-organizes. This forms surface features, such as ripples and dunes, that alter the reflectivity and thermal conductivity of the snow.\n\nThese features have just begun to be studied by the snow and climate science communities (see 1, 2, 3 for recent work).\n\nWe created rescal-snow to provide a highly capable snow dune modelling toolkit, to enable snow scientists to study snow features in controlled numerical experiments, and produce high-quality quantitative output. \n\nWe hope that this model will be useful to researchers in snow science, geomorphology, and polar climate.", + "laborHours": 81836.8, + "languages": [], + "name": "LLNL/Rescal-snow", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Rescal-snow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "gord.stephen@nrel.gov" + }, + "date": { + "created": "2019-08-13", + "metadataLastUpdated": "2019-08-16" + }, + "description": "The Probabilistic Resource Adequacy Suite (PRAS) provides an open-source, research-oriented collection of tools for analysing the resource adequacy of a bulk power system. The simulation methods offered support everything from classical convolution-based analytical techniques through to high-performance sequential Monte Carlo methods supporting multi-region composite reliability assessment, including simulation of energy-limited resources such as storage.", + "laborHours": 76.0, + "languages": [ + "Julia" + ], + "name": "Probabilistic Resource Adequacy Suite (PRAS)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PRAS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-08-13", + "metadataLastUpdated": "2019-08-14" + }, + "description": "A small library that supports multilevel graph partitioning and graph embedding.", + "laborHours": 1763.2, + "languages": [], + "name": "Multilevel Graph Partitioning and Embedding", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/graph-embed", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-08-14", + "metadataLastUpdated": "2019-08-15" + }, + "description": "A Python library and GUI for doing comparisons of EnergyPlus® builds. EPRT is almost exclusively a developer tool for members of the EnergyPlus® development team to ensure that code changes are not impacting the test suite.", + "laborHours": 16856.8, + "languages": [ + "Python" + ], + "name": "EnergyPlus® Regression Tool (EPRT)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlusRegressionTool", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-08-15", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This is software developed in the course of my dissertation work, which was funded by Sandia. The software includes a library (the Streaming Analytics Machine or SAM) for expressing machine learning and subgraph matching over streaming data sources. It also includes a utility that will convert from a high-level language, the Streaming Analytics Language (SAL) to SAM.\n\nSAND2019-4322 M", + "laborHours": 13604.0, + "languages": [ + "C++", + "Jupyter Notebook", + "Scala", + "Python" + ], + "name": "Streaming Analytics Machine (SAM) v. 0.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.0.1" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-16", + "metadataLastUpdated": "2019-08-16" + }, + "description": "High performance parallel power flow solver that can be run in desktops as well as in high performance computing cluster. ", + "laborHours": 6216.8, + "languages": [], + "name": "PFLOW", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pflow-team/PFLOW", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-16", + "metadataLastUpdated": "2019-08-16" + }, + "description": "MAPSToTomoPy provides a graphical user interface (GUI) to control a work flow between MAPS and TomoPy, with tools for visualizing the sinograms of projection image sequences from particular elements and to use these to help correct misalignments of the rotation axis. The program also provides an integrated output of the 3D distribution of the detected elements for subsequent 3D visualization packages.", + "laborHours": 1535.2, + "languages": [], + "name": "MAPSToTomoPy", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdvancedPhotonSource/MAPSToTomoPy", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-16", + "metadataLastUpdated": "2019-08-19" + }, + "description": "ADUPROP is a scalable implementation for uncertainty propagation using the method of moments. The Taylor coefficients for the moments first (mean) and second moment (Covariance matrix) require the efficient computation of derivatives. ADUPROP leverages the technique of Automatic Differentiation (AD) to generate the implementation of derivative computations. ADUPROP solves a differential equation x' = f(x), where f(x) is a nonlinear function and the flow phi(x) of the differential equation is obtained using the usual discretization techniques: x_k+1 = phi(x_k). The user has only to provide f(x) and its Jacobian. For a given input mean and covariance matrix ADUPROP propagates this uncertainty information according to the method of moments. ", + "laborHours": 4940.0, + "languages": [], + "name": "ADUPROP", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/aduprop/aduprop", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-19", + "metadataLastUpdated": "2020-04-20" + }, + "description": "As a part of the annual Argonne Cyber Defense Competition, we develop 3 general categories of software: 1. Mock infrastructure components including ICS systems, web properties, etc.; 2. Visualization, monitoring, and network administration software; 3. Software to assist in the development of puzzles and challenges. We would like to use this disclosure to notify of the existence of this code and allow us to open source portions of the code that would be useful to our community building and education efforts associated with the Cyber Defense Competition. Software will only be released after each year's competition when it won't give a competitive advantage to future competitors. ", + "laborHours": 17084.8, + "languages": [], + "name": "Cyber Defense Competition Code ", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/cyber-defense-competition", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Metagenomic analysis is a computationally intensive task, this problem is compounded when many hundreds of samples need to be analyzed. We needed a program that would process the metagenomic sequencing data, manage computing resources, and combine the results into a unified output. We developed a script that prepares raw metagenomic sequencing data for analysis, configures analysis parameters, launches analysis jobs, keeps track of analysis progress, and combines analysis output. The analysis itself itself is done by the functionality provided by mothur (https://www.mothur.org/).", + "laborHours": 76.0, + "languages": [], + "name": "pnnl/metagenomic_analysis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/metagenomic_analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software tool implements a version of the N-SCRAD anomaly detection algorithm. This algorithm classifies a gamma-ray energy spectrum as either consistent or inconsistent with previously measured background and a set of predefined nuisance sources. N-SCRAD was originally developed for DOE/NNSA/NA-22 and has since been utilized in a variety of applications for various clients. The present software tool is intended to demonstrate the capabilities of N-SCRAD. The tool accepts input data as either text files or GADRAS binary files, and saves the output alarm metric as a text file. A separate parameter file allows advanced users to configure algorithm settings.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "N-SCRAD", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Use GrumPHP to ensure your files conform to the standards setup in your projects .editorconfig file. This plugin allows your Git pre-commit hooks to check your files for the proper file standards and reject a commit if any of your files don't conform.", + "laborHours": 136.8, + "languages": [], + "name": "GrumPHP Editor Config", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/editorconfig", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software takes JSON and YAML files, and after running them through a linter, sorts the keys of objects alphabetically. This helps prevent the following problems when checking these data/config files into repositories:\nProblems where the entire file looks like it was removed and added due to\nIndentation changes Key sorting differences\nMerging issues when 2 or more people add data to the same or similar locations", + "laborHours": 0.0, + "languages": [], + "name": "Pretty Linter GrumPhP", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pretty_lint", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-08-26", + "metadataLastUpdated": "2021-05-19" + }, + "description": "PathParser is a python-based computational tool for the thermodynamics and robustness analysis of native and designed metabolic pathways. The following functionalities are provided: 1 Max-min driving force (MDF) optimization. The Gibbs free energy change of the least favorable reaction will be maximized to evaluate thermodynamic feasibility of the entire pathway. 2 Protein cost estimation. The smallest enzyme investment will be assessed by calculating the minimal total enzyme cost supporting a given pathway flux. 3 Robustness analysis. Specifically, an ensemble of models is generated to simulate the system response to enzyme perturbation based on bifurcation theory and a continuation method. Probability of system failure and flux fold change against enzyme perturbation are estimated as well as a flux control index.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PathParser", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PathParser", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-08-26", + "metadataLastUpdated": "2019-08-27" + }, + "description": "Finds LASSO fit coefficient values of hyperspectral data for a Gaussian sigmoid basis function collection using LARS (least angle regression) methodology on a provided vector of sensor wavelength bins.", + "laborHours": 212.8, + "languages": [], + "name": "Hyperspectral Data Approximation by Gaussian Sigmoids", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/hydags", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The system allows for multiple people to \"crowdsource\" feature generation and also enables the system to use these features to suggest alternative features to the user. The user interacts with a \"canvas\", where they position icons representing pieces of data. A unique feature is that the data can be heterogeneous -- some of the icons can represent images, while others could be text, audio, etc. After the user positions items on the screen to their satisfaction, they press a button to commit the X/Y coordinates of each icon to a central database, where these positions are added as a latent feature to each item. The user also has the option to request new, untouched data be added to the canvas, and the system positions each new item according the pattern it has learned from the original data. Another unique feature is that the user can ask the system to refine their initial rough work. The system uses information theoretic measures to determine which features in the database best explain how the user positioned the icons on the screen. It then attempts to *incrementally* optimize the positions on the screen to best explain those features it isolated. The user can then adjust the positions to correct the system, or the user can request additional refinement to further optimize the positions. In this way, by incorporating user feedback and crowdsourced features, the system reduces the time required for a user to develop a rich classification scheme for large amounts of data.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "An Interactive System for Crowdsourcing Features Generation and Building Classifiers for Machine Learning (\"Sharkzor\")", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Unicorn Face provides novel \"n-shot learning\" capabilities, which enables conducting machine learning with small amounts of data in real time. 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The code base is intended to serve as a support library for HDL designs.", + "laborHours": 35689.6, + "languages": [], + "name": "Bedrock v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/Bedrock", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-01", + "metadataLastUpdated": "2019-10-02" + }, + "description": "The BEDES Manager is a web-based application for archiving, searching, and editing BEDES terms and mapping them to terms in user applications. BEDES is a standard data dictionary for building energy related terms.\nThe BEDES Manager can be used in the following ways:\n- Search for BEDES terms, including composite terms.\n- Create new composite terms for use in application mappings.\n- Create, manage and export application mappings.", + "laborHours": 62335.2, + "languages": [], + "name": "BEDES Mapping Manager v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/BEDES-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-02", + "metadataLastUpdated": "2019-10-02" + }, + "description": "eZeeKonfigurator is a web application and supporting tools for configuring Zeek (formerly Bro) systems.\n\nZeek is an open-source tool developed at LBNL that's used to secure computer networks. A recent version of Zeek introduced the configuration framework, where changes can be made while the system is running. However, the provided method is difficult to operationalize, as it requires a set of text files to be deployed and updated across all the Zeek systems.\n\neZeeKonfigurator provides an easy-to-use web interface to this. Users can view and modify options in a web application, and then those changes are deployed to the desired Zeek systems. Additionally, users benefit from additional features, such as:\n\n* Logging and auditing, to determine who made what change and when\n* Automated expiration of changes (e.g. an exception is added for 2 weeks, after which time it will be removed)\n* Validation of changes and verification that the change has been applied\n* Fine-grained role-based access", + "laborHours": 1991.2, + "languages": [], + "name": "eZeeKonfigurator v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/eZeeKonfigurator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-02", + "metadataLastUpdated": "2019-10-02" + }, + "description": "The Moirai Land Data System (Moirai LDS) is designed to produce recent historical land data inputs for the AgLU module of GCAM data system , but the Moirai LDS outputs could also be used by other models/applications. The Moirai are the Greek Fates, and this software is named Moirai to represent the fundamental influence of land data inputs on model outcomes. The primary function of the Moirai LDS is to combine spatially explicit input data (e.g., raster images) with tabular input data (e.g., crop price table) to generate tabular output data for a suite of variables. Some of these outputs replace the data provide by the Global Trade Analysis Project (GTAP), and other data replace and augment the original GCAM GIS processing. The Moirai LDS output data are aggregated by Geographic Land Unit (GLU) within each country. The GLU coverage is an input to the Moirai LDS (as a thematic raster image and an associated CSV file that maps the thematic integers to names), and the GLU boundaries can be determined arbitrarily. Previous versions of GCAM (and Moirai LDS) used only bioclimatic Agro-Ecological Zones (AEZs) and corresponding data that were provided by GTAP, as the GLUs. As a result, some AEZ terminology still exists in the code, but this terminology now refers more generally to GLUs. The Moirai LDS now enables any set of boundaries to be used as GLUs (including AEZs), allowing for more flexible generation of land use region boundaries (defined as the intersection of GLUs with geopolitical regions). The current default set of GLUs is the same set of 235 global watersheds as used by the GCAM water module. The GCAM 5.1 geopolitical regions (32 or 14) are included and used as inputs to Moirai to generate a mapping file between the Moirai outputs, which are at the level of the intersection between the GLUs and the country boundaries, and the geopolitical regions. The diagnostics scripts use this geopolitical region mapping in some cases. Moirai can also recalibrate three of the outputs (crop production, harvested area, and land rent) to a specified year that is the center of a five-year averaging window. No recalibration retains the circa 2000, 7-year average of the source data. The cucrrency-year for land rent can also be specified, and the default is 2001 to match the GTAP data.", + "laborHours": 7752.0, + "languages": [], + "name": "Moirai Land Data System (Moirai) v3.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/moirai", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-10-07", + "metadataLastUpdated": "2019-10-08" + }, + "description": "Software infrastructure for using a custom (user-written) scheduler with the SISPI control system of DECam, and an example template for such a scheduler. This version of the obstac code is only infrastructure for supporting writing a scheduler, not a functional scheduler in itself: earlier versions of obstac that include the DES scheduler are part of SISPI, and not included as part of this package.", + "laborHours": 623.2, + "languages": [ + "Python" + ], + "name": "obstac10", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ehneilsen/obstac10", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-10-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The current scripts utilize a well-known cluster analysis algorithm, called ordering points to identify the clustering structures (OPTICS), and an automatic cluster extraction algorithm for clustering analysis of 3D spatial data, specifically for the Atom Probe Tomography data. A hierarchical clustering scheme, together with density-based clustering, were implemented.", + "laborHours": 1778.4, + "languages": [], + "name": "pnnl/apt", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/apt", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-10-08", + "metadataLastUpdated": "2022-01-05" + }, + "description": "SKYSTRATA is a software as a service framework for managing and orchestrating containers across cloud systems.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "SKYSTRATA", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-10-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Work space for in development Economic Dispatch Application.\nMulti-purpose open-source control algorithms that will ensure real-time optimal operation, increase electric grid reliability, and lead to the goal of clean, efficient, reliable and affordable next generation building-integrated combine cooling, heating and power (CHP) system.The CHP system could include conventional heating, ventilation, air conditioning (HVAC) systems, distributed generation (DG), local storage (both thermal and electric) and local solar photovoltaic (PV) systems.", + "laborHours": 1459.2, + "languages": [], + "name": "VOLTTRON/econ-dispatch", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/volttron/econ-dispatch", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-10-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Unique Building Identifier (UBID)\nThis \"invention\" is an enhanced version of the UBID library and command-line executable that, in addition to encoding, decoding and validating UBIDs, also calculates UBID-based statistics and generates figures.", + "laborHours": 440.8, + "languages": [], + "name": "pnnl/buildingid", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-10-10", + "metadataLastUpdated": "2019-10-11" + }, + "description": "IMPLEMENTS PARALLEL GENETIC ALGORITHMS AND PHASE RETRIVAL METHOS FOR BRASS CDI TECHNIQUES. THE SOFTWARE HAS GOOD PERFORMANCE, IS EASY TO MAINTAIN AND INCLUDES MULTIPLE FEATURES TO GUIDE THE RECONSTRUCTION PROCESS.", + "laborHours": 3511.2, + "languages": [], + "name": "CDI RECONSTRUCTION (RECCDI)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdvancedPhotonSource/cdi", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kelleherme@ornl.gov" + }, + "date": { + "created": "2019-10-10", + "metadataLastUpdated": "2019-11-06" + }, + "description": "This software provides a framework for comparing different methods of finding the subtropical jet.\n\nIncluded in these is a new method for locating the subtropical jet. The tropopause gradient method uses the peak gradient in potential temperature along the dynamic tropopause to locate the subtropical jet.", + "laborHours": 2736.0, + "languages": [ + "Python" + ], + "name": "STJ_PV: Subtropical Jet Finding Framework", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mkstratos/stj_pv", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-11", + "metadataLastUpdated": "2024-04-26" + }, + "description": "The ResStock™ analysis tool is helping states, municipalities, utilities, and manufacturers identify which home improvements save the most energy and money.With support from the U.S. Department of Energy (DOE), researchers at NREL developed ResStock. It's a versatile tool that takes a new approach to large-scale residential energy analysis by combining:\n\n- Large public and private data sources\n- Statistical sampling\n- Detailed subhourly building simulations\n- High-performance computing.\n- This combination achieves unprecedented granularity and most importantly—accuracy—in modeling the diversity of the single-family housing stock.", + "laborHours": 4008133.6, + "languages": [], + "name": "ResStock™ [SWR-19-15 and SWR-20-07]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-BuildStock/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-BuildStock", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-10-11", + "metadataLastUpdated": "2019-10-11" + }, + "description": "This suite of code learns neural network models to emulate the dynamics of time series data. \n\nTo do so, it learns a set of \"neural shape functions\" that provide a common vocabulary for expressing the various dynamics operators. \n\nThe code is implemented in Python and TensorFlow.", + "laborHours": 152.0, + "languages": [ + "Python" + ], + "name": "Modeling Time Series Data with Ordinary Differential Equations and Neural Networks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tadesautels/PSINN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-10-14", + "metadataLastUpdated": "2019-10-14" + }, + "description": "A command line tool that converts a protocol specification into a target language.", + "homepageURL": "https://cdcvs.fnal.gov/redmine/projects/protocol-compiler/repository", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Protocol Compiler", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cdcvs.fnal.gov/redmine/projects/protocol-compiler/repository", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-14", + "metadataLastUpdated": "2019-10-15" + }, + "description": "This module mostly wraps the XIA C-library to control and readout the XIA-pixie16 module. It also includes some functions to analyze the data and to make control of the pixie16 more convienent in python.", + "laborHours": 2401.6, + "languages": [], + "name": "Pixie16 Python Interface (Pixie16) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/pypixie16/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-15", + "metadataLastUpdated": "2019-10-15" + }, + "description": "Code to perform operation count minimization for the evaluation of a large number of tensor contractions. A possible application is the efficient evaluation of correlation functions in lattice QCD calculations, where a reduction of computational complexity by an order of magnitude is achieved", + "laborHours": 364.8, + "languages": [], + "name": "Contraction Optimizer v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laphnn/contraction_optimizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-15", + "metadataLastUpdated": "2019-10-15" + }, + "description": "This is a controller for distributed energy resources (i.e. photovoltaics, storage,..) based on model predictive control. It is written in Python.", + "laborHours": 4453.6, + "languages": [], + "name": "Distributed Optimal and Predictive Energy Resources (DOPER) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/DOPER", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-15", + "metadataLastUpdated": "2019-10-15" + }, + "description": "GraphDot is a scikit-learn compatible library that implements GPU-accelerated graph kernels for similarity comparison between graphs.", + "laborHours": 1126912.8, + "languages": [], + "name": "GraphDot v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/yhtang/graphdot", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-16", + "metadataLastUpdated": "2019-10-16" + }, + "description": "SHEBO (surrogate optimization of problems with hidden constraints and expensive black-box objectives) is an efficient optimization algorithm that employs surrogate models to solve computationally expensive black-box simulation optimization problems that have hidden constraints. Hidden constraints are encountered when the objective function evaluation does not return a value for a parameter vector. These constraints are often encountered in optimization problems in which the objective function is computed by a black-box simulation code. SHEBO uses a combination of local and global search strategies together with an evaluability prediction function and a dynamically adjusted evaluability threshold to iteratively select new sample points.", + "laborHours": 319.2, + "languages": [], + "name": "Surrogate Optimization of Computationally Expensive Black-Box Problems with Hidden Constraints (SHEBO) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/julianem/shebo-hidden-constraint-optimization/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-16", + "metadataLastUpdated": "2019-10-17" + }, + "description": "FPEAM is a modeling framework that integrates agricultural and forestry production, supply data, and equipment budgets for those activities with methodologies for estimating air pollutant emissions.", + "laborHours": 4408.0, + "languages": [ + "Python" + ], + "name": "FPEAM (Feedstock Production to Air Emissions Model)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/fpeam", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-17", + "metadataLastUpdated": "2019-12-02" + }, + "description": "The webtool displays the following types of data:\n\nWastewater treatment plants (WWTP) with anaerobic digestion\nFacilities with anaerobic digestion onsite other than WWTP\nCombustion plants.\nManure locations.\nManure (non points)\nMunicipal solid waste locations\nCrop locations\nProcessor residue (non points)\nDistrict energy systems\nMixed use developments (non points)\nProcess heating and cooling locations\nBasic Usage\nUsers can interact with the map in the following ways:\n\nSelect the year of the analysis from a drop-down menu.\nSet the background layer as biomass availability or thermal consumption density from a drop-down menu.\nSelect whether the facility of interest is an Anaerobic Digestion or a Therochemical facility from a drop-down menu. This filters the biomass data by moisture and only shows the relevant portions based on the facility selection.\nSelect from a drop-down menu whether the biomass amounts will be shown as gross amounts or technical amounts.\nSet the radius for the search buffer in which the analysis will be performed.\nClick on any point data on the map to get more information.\nClick on the map, to given the signal of the query point location, from where the algorithmic process is going to initiate. This will show the available biomass locations and amounts that fall within the predefined buffer zone.\nDownload the data in a csv format for the entire county or the selected biomass that is inside the predefined buffer.\nReport whether there are errors in the data to us and we will work to the best of our abilities to confirm and fix any issues.\nThe outputs of the algorithmic process are going to appear on the screen after the computation is done. The outputs consist of the locations of all available biomass that are within the buffer zone from the clicked location. By clicking on any point the user can get more information on the nature and amounts of the biomass.", + "homepageURL": "https://biositing.jbei.org", + "laborHours": 11324.0, + "languages": [], + "name": "Biositing Webtool, v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://lead.jbei.org", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://biositing.jbei.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-21", + "metadataLastUpdated": "2019-10-21" + }, + "description": "This is a software utility for calculating pooling volumes and graphing quality control data of next generation sequencing libraries amplified with fluorescent intercalating agents and monitored by real-time quantitative PCR (qPCR). The tool is used to calculate pooling volumes of individual next generation sequencing libraries based on experimentally determined fluorescence values. To do this, fluorescent values are used as a proxy for relative concentration to determine the ratio of transfer volumes. The output is a \"transfer file\" that specifies the transfer volume and destination well of a given library. The tool can also be used to assess the quality of individual next generation sequencing libraries by melting curve analysis. The output are small-multiples graphs of the melting curves of individual sequencing libraries according to the specified plate layout.", + "laborHours": 152.0, + "languages": [], + "name": "Fluorescent Amplification of Next Generation Sequencing Libraries Tools (FA-NGS tools) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AgileBioFoundry/FA-NGS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2019-10-23" + }, + "description": "The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) has established a set of standardized high performance sequences of operation for Heating, Ventilation and Air Conditioning (HVAC) systems in buildings through their \"Guideline 36\". In order to achieve the intended performance, these sequences must be translated and programmed accurately in the Building Automation System (BAS) controllers. Standardizing these sequences will allow for a more efficient product delivery mechanism where the sequences are programmed and tested centrally by each manufacturer, and then distributed to their dealers/engineering contractors. This approach would minimize the need for each installer to re-interpret and program the sequences, reduces risk of errors, and reduces the time required for commissioning in the field.\n\nTo achieve this goal, a performance validation method is needed to provide independent confirmation that each manufacturer has programmed the Guideline 36 sequences accurately. A standardized method of test would also avoid the need for manual interpretation (and the associated human variability) that is required with typical functional testing approaches by automating the inputs and the range of expected responses. This software \"guideline36_conformance_test\" has been developed to conduct standardized, repeatable and manufacturer independent tests to validate that a BAS controller has been programmed in conformance with Guideline 36. Manufacturers would provide the controller (or the control program) and the software would run a suite of tests by setting a set of inputs to the controller and verifying the output signals from the controller matches the expected output as set by Guideline 36.\n\n", + "laborHours": 197.6, + "languages": [], + "name": "guideline36_conformance_test 0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/guideline36_conformance_test", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2019-10-23" + }, + "description": "The Behavior, Energy, Autonomy, and Mobility (BEAM) model is an integrated, agent-based travel demand simulation framework. Individual agents express preferences through a utility-maximizing evolutionary algorithm that minimizes each individual's cost and time spent traveling via diverse modal options, including the competition for scarce supply resources such as parking spaces and charging infrastructure. BEAM simulates the essential elements that compose a dynamic transportation system. From the road network, parking and charging infrastructure, to the transit system and a synthetic population with plans and preferences, the virtual system is an amalgamation of multiple spatially resolved layers that together represent an integrated transportation system. BEAM is an extension to the MATSim (Multi-Agent Transportation Simulation) model, where agents employ reinforcement learning across successive simulated days to maximize their personal utility through plan mutation (exploration) and selecting between previously executed plans (exploitation). The BEAM model shifts some of the behavioral emphasis in MATSim from across-day planning to within-day planning, where agents dynamically respond to the state of the system during the mobility simulation. In BEAM, agents can plan across all major modes of travel including driving, walking, biking, transit, and demand-responsive ride hailing.", + "laborHours": 58200.8, + "languages": [], + "name": "Behavior, Energy, Autonomy, Mobility Modeling Framework", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-UCB-STI/beam", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2021-02-22" + }, + "description": "MDBEngine is a class library that provides Microsoft Access (.mdb) database functionality to applications that require complex data entry. Example functionality supports undo/redo, data verification and warnings, referential integrity checks, change history tracking, and other capabilities to simplify the task of using a database in an application. SAND2019-9689 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Visual Basic .NET" + ], + "name": "MDBEngine v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2024-08-07" + }, + "description": "Software that employs an algorithm that rapidly and rigorously solves nonnegative least squares problems with many right hand sides. This is the latest internal version of MATLAB pseudocode that was described in a published in M. H. Van Benthem and M. R. Keenan, \"Fast algorithm for the solution of largescale non-negativity-constrained least squares problems,\" J. Chemom. 18(10), 441-450 (2004). Example code of this algorithm was included in the publication. This algorithm was also patented in M. H. Van Benthem and M. R. Keenan, \"Fast combinatorial algorithm for the solution of linearly constrained least squares problems,\"USPTO, Ed., Sandia Corporation, USA (2008). SAND2019-10098 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 45.6, + "languages": [ + "MATLAB" + ], + "name": "Fast Combinatorial Nonnegative Least Squares v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fcnnls", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2019-10-29" + }, + "description": "Software package for R and Python for analysis of extremes in climate data. Functions for fitting GEV and POT (via point process fitting) models for extremes in climate data, providing return values, return probabilities, and return periods for stationary and nonstationary models. Also provides differences in return values and differences in log return probabilities for contrasts of covariate values. Functions for estimating risk ratios for event attribution analyses, including uncertainty. Under the hood, many of the functions use functions from 'extRemes', including for fitting the statistical models.", + "laborHours": 8679.2, + "languages": [], + "name": "climextremes v0.2.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/lbl-cascade/climextremes-dev", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "burnsrl1@nv.doe.gov" + }, + "date": { + "created": "2019-10-24", + "metadataLastUpdated": "2019-11-19" + }, + "description": "QuickView PRO (QVPRO) is similar to QuickView but designed to focus on analysis. QuickView was designed for visualization only, adding analysis capabilities later. This made QuickView complicated when using it as an analysis tool. QVPRO uses the same analysis algorithms in a more streamlined workflow and has a user friendly GUI. QVPRO provides the unique capability of analyzing Photonic Doppler Velocimetry (PDV) data records from different PDV systems and still allows for processing hundreds of PDV data records in a practical manner.", + "homepageURL": "http://gitlab.osti.gov/doecode/dc-31683", + "laborHours": 881.6, + "languages": [], + "name": "QuickView PRO, QVPRO", + "organization": "Nevada National Security Site/Mission Support and Test Services LLC (MSTS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://gitlab.osti.gov/doecode/dc-31683", + "status": "Production", + "tags": [ + "DOE CODE", + "Nevada National Security Site/Mission Support and Test Services LLC (MSTS)" + ] + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-10-24", + "metadataLastUpdated": "2019-10-24" + }, + "description": "The principal purpose of this code is to determine bulk constitutive properties and response of polycrystalline materials. \n\nThis is a nonlinear quasi-static, implicit solid mechanics code built on the MFEM library based on an updated Lagrangian formulation (velocity based).\n\nWithin this context, there is flexibility in the type of constitutive model employed, with the code allowing for various UMATs to be interfaced within the code framework or for the use of the ExaCMech library.\n\nUsing crystal-mechanics-based constitutive models, the code can be used, for example, to compute homogenized response behavior over a polycrystal.\n", + "laborHours": 4180.0, + "languages": [], + "name": "ExaConstit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ExaConstit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.2.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-25", + "metadataLastUpdated": "2023-06-16" + }, + "description": "CatCost™ is a state-of-the-art cost estimation tool designed to reduce the cost uncertainty associated with pre-commercial catalyst materials. The tool combines industry-standard cost estimation methods and resources into an intuitive suite of tools to bring actionable cost insight to every step of catalyst research and development. CatCost™ allows the rapid development of comprehensive catalyst cost estimates. It incorporates detailed insight into manufacturing methods, especially for pre-commercial catalysts, without requiring any process design experience.\n\nThe tool has been designed from the ground up with a number of user-selectable estimation methods, pricing libraries, and ease-of-use features to tailor an estimate to a user's skill level and need for customization, empowering researchers of all skill-levels to make better R&D decisions throughout the catalyst development cycle. Our costing methods are fully transparent and enable power-users the ability to adjust any estimate to the economic realities of their operation.\n\nThe tool has been designed from the ground up with a number of user-selectable estimation methods, pricing libraries, and ease-of-use features to tailor an estimate to a user's skill level and need for customization, empowering researchers of all skill-levels to make better R&D decisions throughout the catalyst development cycle. Our costing methods are fully transparent and enable power-users the ability to adjust any estimate to the economic realities of their operation.\n\nFeatures include:\nRaw materials pricing: Libraries of common chemicals, cost scaling indices, guidance for obtaining bulk quotes, and methods for extrapolating laboratory-scale prices to bulk.\nSimplified step method for synthesis by a contract manufacturer: All-in hourly cost for process equipment using methods and data from tollers. (Excel-only in v1.0)", + "homepageURL": "https://catcost.chemcatbio.org", + "laborHours": 0.0, + "languages": [], + "name": "CatCost™ (Catalyst Cost Estimation Tool) [SWR-18-74]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://catcost.chemcatbio.org/disclaimer", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://catcost.chemcatbio.org", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-10-25", + "metadataLastUpdated": "2019-10-25" + }, + "description": "Adiak is a computer science data management interface tool for collecting metadata about an application's runs and disseminating it to tools that subscribe to this data. Examples of this metadata could be what user is running an application, what systems it runs on, or application provided name/value pairs. \n\nAdiak's capabilities include automated reading of system-level metadata, and a generic type system for applications to register their own name/value metadata. \n\nAdiak is currently designed to provide a standard interface that can be integrated with MPI-based applications that run on high performance computing systems.\n\nExample tools that use Adiak metadata include performance analysis tools and workflow tools. By allowing the application to specify metadata to Adiak, which then disseminates it to tools, application developers do not have to write to tool-specific interfaces.\n\n", + "laborHours": 1170.4, + "languages": [], + "name": "Adiak", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/adiak", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-10-25", + "metadataLastUpdated": "2019-10-25" + }, + "description": "Web-based Interface for the N-Dimensional Data Analysis and Visualization System.", + "laborHours": 10913.6, + "languages": [ + "Python" + ], + "name": "NDDAV", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/NDDAV", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-29", + "metadataLastUpdated": "2019-10-29" + }, + "description": "Hardware simulation is an indispensable tool for designing chips as well as researching future architectures. Unfortunately, the slow rate of simulation can often bottleneck the design process, as designers must wait to see the results of a simulation before changing the design and starting a new simulation. The Essential Signal Simulation Enabled by Netlist Transforms (ESSENT) is a tool designed to accelerate hardware simulations. ESSENT takes in a design, uses graph algorithms to identify opportunities for conditional execution, and generates a simulator that leverages these opportunities. The generated simulator produces the exact same simulation results that would be returned by an unoptimized simulator, but in substantially less time. For input, ESSENT takes in designs formatted in FIRRTL (an open format).", + "laborHours": 1717.6, + "languages": [], + "name": "Essential Signal Simulation Enabled by Netlist Transforms (ESSENT) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ucsc-vama/essent", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-29", + "metadataLastUpdated": "2019-10-29" + }, + "description": "This package is developed as a backend for multi-layer and multi-time domain controller. One example are controller based on [Model Predictive Control] (MPC) where different modules with different time constants have to be coordinated to allow optimal control. In a simple example, the Weather Forecast must be acquired and processed, the MPC is computed, and finally the control is applied. All these modules typically run on the same time step (Time step: 5 minutes), but are different instances within the framework. The framework allows parallelization using the `multiprocessing` module. However, another real-time controller (Time step: 1 second) must be applied to react on instant system disturbances beyond the MPC time step. Last, a supervisory MPC controller (Time step: 1 hour) might be added to ensure global optimality.", + "laborHours": 501.6, + "languages": [], + "name": "Framework for Multi Layer Control in Python (FMLC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/FMLC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ellisjc@ornl.gov" + }, + "date": { + "created": "2019-10-30", + "metadataLastUpdated": "2019-10-30" + }, + "description": "P Finder is a GUI software application for the fast identification of the rnpB gene in prokaryote genomes", + "laborHours": 0.0, + "languages": [], + "name": "JChristopherEllis/P-Finder", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JChristopherEllis/P-Finder", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-30", + "metadataLastUpdated": "2019-10-30" + }, + "description": "Pairwise sequence alignment is one of the most compute-intense challenges for the analysis of genomics data and it can account for more than 90% of the runtime depending on the application. Despite the effort to reduce the computational cost introducing heuristics such as banded and x-drop alignment, the performance of state-of-the-art software is often unsatisfactory for long sequences. Recent advances in single-molecule sequencing technologies keep increasing the length of the sequences to align at the cost of higher error rates b ranging from 5% to 15% b, emphasizing the need for fast and accurate software.\n\nOur long-read alignment software, named Xavier, computes high-performance x-drop adaptive banded pairwise alignment exploiting instruction-level parallelism via Single-Instruction-Multiple-Data (SIMD) operations. Xavier uses a narrow bandwidth that appreciably improves performance reducing the search space for the optimal alignment. In our experiment, the adaptive mechanism enables Xavier to find the optimal alignment between related sequences even when the error rate is as high as 50%. Xavier achieves speed-up up to 5X over competitor software when enabling the x-drop termination and up to 415X when disabling it, with negligible accuracy loss.", + "laborHours": 456.0, + "languages": [], + "name": "Xavier: High-Performance X-Drop Adaptive Banded Pairwise Alignment (Xavier) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/giuliaguidi/xavier", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-30", + "metadataLastUpdated": "2019-10-30" + }, + "description": "This is a library of 27 abnormal (electrical) grid events recorded at LBNL campus. Each event lasts for about 1 second. The library is published for other researchers to develop control algorithms.", + "laborHours": 45.6, + "languages": [], + "name": "PMU event library v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/pmu_event_library", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-30", + "metadataLastUpdated": "2019-10-30" + }, + "description": "This package includes a variety of simulation models for distributed energy resources (i.e. photovoltacis, storage, inverter, controls, grid) in the language Modelica.", + "laborHours": 15.2, + "languages": [], + "name": "Smart Control of Distributed Energy Resources (SCooDER) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/SCooDER", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2019-10-31" + }, + "description": "This software implements the first base caller for nanopore data that calls bases directly from raw data. The basecRAWller algorithm has two major advantages over current nanopore base calling software: (1) streaming base calling and (2) base calling from information rich raw signal. The ability to perform truly streaming base calling as signal is received from the sequencer can be very powerful as this is one of the major advantages of this technology as compared to other sequencing technologies. As such enabling as much streaming potential as possible will be incredibly important as this technology continues to become more widely applied in biosciences. All other base callers currently employ the Viterbi algorithm which requires the whole sequence to employ the complete base calling procedure and thus precludes a natural streaming base calling procedure. The other major advantage of the basecRAWller algorithm is the prediction of bases from raw signal which contains much richer information than the segmented chunks that current algorithms employ. This leads to the potential for much more accurate base calls which would make this technology much more valuable to all of the growing user base for this technology.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1976.0, + "languages": [], + "name": "basecRAWller v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2020-01-20" + }, + "description": "Chordly is a JavaScript library that lets you detect and act upon user keyboard input. This is accomplished by wiring Chordly up to listen for key sequences, known as chords, entered by a user.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2019-11084 M\n", + "laborHours": 1185.6, + "languages": [ + "JavaScript" + ], + "name": "Chordly", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Chordly", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2024-06-18" + }, + "description": "DefectSegNet for semantic segmentation of defects in Steels\nThe first and most important step of automating defect analysis is perceptual defect identification. In terms of digital image processing, semantic segmentation best emulates human recognition of defect features – it identifies the crystallographic defects and where they are located in a TEM micrograph. We solved this problem by developing DefectSegNet, a novel hybrid CNN algorithm for robust and automated semantic segmentation of three crystallographic defects, including line dislocations, precipitates and voids, that are commonly observed in structural metals and alloys.", + "laborHours": 1033.6, + "languages": [], + "name": "DefectSegNet", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ZEMG-UCONN/DefectSegNet", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2023-05-08" + }, + "description": "This is a package for easy application of multiple machine learning models to a single problem, and comparison via various metrics. For a pretty detailed description of the models that are available in the tool, and a quite detailed description of the metrics that it pumps out, see the paper, \"A Machine Learning Decision Support Tool for Travel Demand Modeling\". Accessible at: https://github.com/NREL/TEAM-TDM/blob/master/paper/team_tdm.pdf\n", + "laborHours": 4119.2, + "languages": [ + "Perl", + "Jupyter Notebook", + "Tex", + "Python" + ], + "name": "TEAM-TDM: A Tool for Evaluating an Array of Machine Learning Travel Demand Models [SWR-18-64]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/TEAM-TDM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2019-11-04" + }, + "description": "The Industry Energy Tool (IET) is an open-source calculator tool designed for projecting energy and emissions impacts of industrial sector energy efficiency, material efficiency, and fuel switching. Projections are available at the county and Census Region levels. The IET is based on a detailed county-level energy data set for agriculture, mining, construction, and manufacturing industries. End use energy disaggregation is provided for manufacturing industries, and some agriculture and mining industries. Process temperature disaggregation is provided for most manufacturing industries.", + "laborHours": 2416.8, + "languages": [], + "name": "Industry Energy Tool", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Industry-Energy-Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-11-06", + "metadataLastUpdated": "2019-11-06" + }, + "description": "Dockerfiles for quantum simulators", + "laborHours": 152.0, + "languages": [ + "make", + "dockerfile" + ], + "name": "fermilab-qc/docker-quantum", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fermilab-qc/docker-quantum", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-07", + "metadataLastUpdated": "2020-11-06" + }, + "description": "VOLTTRON™ Distributed Control System Platform\nVersion 7.0\nVOLTTRON™ is an agent execution platform providing services to its agents that allow them to easily communicate with physical devices and other resources.\nVOLTTRON™ delivers an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls. It enables mobile and stationary software agents to perform information gathering, processing, and control actions. VOLTTRON™ can independently manage a wide range of applications, such as HVAC systems, electric vehicles, distributed energy or entire building loads, leading to improved operational efficiency.", + "laborHours": 0.0, + "languages": [], + "name": "VOLTTRON Version 7.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron/releases/tag/7.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "7.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-11-11", + "metadataLastUpdated": "2019-11-11" + }, + "description": "This project simplifies the registration and authentication of a Gitlab runner. \n\nThis allows administrators to create a set of static configuration files from which this script will build the appropriate, host-specific config needed to communicate with and accept jobs from Gitlab.", + "laborHours": 182.4, + "languages": [], + "name": "Gitlab Runner Auth", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/gitlab-runner-auth", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-11-12", + "metadataLastUpdated": "2019-11-12" + }, + "description": "User-defined elements in ANSYS enable programming of the finite element method to simulate the unique behavior of superconducting magnets. A set of electromagnetic and thermal user elements incorporate both quench and interfilament coupling current (IFCC) effects in a consistent manner, allowing for simulation of strongly coupled, multiphysics behavior typical of superconducting devices.", + "laborHours": 6870.4, + "languages": [], + "name": "SCPACK vR1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lnbrouwer/ANSYS_UEL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-11-13", + "metadataLastUpdated": "2019-11-13" + }, + "description": "Pairwise sequence alignment is one of the most computationally intensive kernels in genomic data analysis, accounting for more than 90% of the run time for key bioinformatics applications. This method is particularly expensive for third-generation sequences due to the high computational expense of analyzing these long read lengths (1Kb-1Mb). Given the quadratic overhead of exact pairwise algorithms such as Smith-Waterman, for long alignments, the community primarily relies on approximate algorithms that search only for high-quality alignments and stop early when one is not found. In this work, we present the first GPU optimization of the popular X-drop alignment algorithm, named LOGAN. Results show that our high-performance multi-GPU LOGAN implementation achieves up to 181.6 GCUPS and speed-ups up to 6.6x and 30.7x using 1 and 6 NVIDIA Tesla V100, respectively, over the state-of-the-art software running on two IBM Power9 processors using 168 threads, with equivalent accuracy. We also demonstrate a 2.3x LOGAN speed-up versus ksw2, a state-of-art vectorized algorithm for sequence alignment implemented in minimap2. To highlight the impact of our work on a real-world application, we couple the LOGAN aligner with a many-to-many long-read alignment software called BELLA, and demonstrate that our implementation improves the overall BELLA runtime by up to 10.6x. Finally, we adapt the Roofline model for our optimized kernel and demonstrate that our implementation is near-optimal on the NVIDIA Tesla V100s.", + "laborHours": 133851.2, + "languages": [], + "name": "LOGAN: High-Performance X-Drop Pairwise Alignment on GPU (LOGAN) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/albertozeni/LOGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-11-13", + "metadataLastUpdated": "2019-11-13" + }, + "description": "Radiance matrix algebraic methods enable efficient annual daylight simulation while preserving accuracy. The five sub-methods, 2 to 6 phase methods, enable scene components parameterization and separation of direct and diffuse flux transfer based on the user's need. However, the burden is on the user to figure out the which method, matrix basis, matrix resolution, simulation parameters to use to achieve the desired efficiency and accuracy to the end application. Several utility programs and an executive program (in-progress) were created to lower the entry barrier and to reduce human error when executing the simulation. This suite of programs should also reduce the burden of adopting Radiance matrix methods for third party software.", + "laborHours": 729.6, + "languages": [], + "name": "Framework for Radiance Simulation Control (Frads) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/frads", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-11-13", + "metadataLastUpdated": "2019-11-13" + }, + "description": "A plugin for the Grafana monitoring/dashboarding web application that provides \nan interface to data provided by GraphQL APIs, such as the \"Lens\" API service\nthat SCD maintains for batch job monitoring data.", + "laborHours": 1520.0, + "languages": [ + "JavaScript", + "TypeScript" + ], + "name": "fifemon-graphql-datasource", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fifemon/graphql-datasource", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Transparent Asynchronous Zero-copy Remote I/O (TAZeR) is a framework built to facilitate grid computing by easing the memory movement and management across geographically separated computing resources. TAZeR employs a multiclient/\nmulti-server paradigm where data is stored at on a remote server. Users preload an interposing library which upon application start-up, stands up an ephemeral lightweight client. The client captures POSIX I/O calls to TAZeR meta-files which contains the IP address/port of the remote server, the location of the file on remote server, and additional meta-data.\nThe client connects to the server using this information and begins downloading the file in parts optionally compressing the data.", + "laborHours": 8648.8, + "languages": [], + "name": "Transparent Asynchronous Zero-copy Remote I/O (TAZeR)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/tazer", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is an improved system for detecting a nuclear criticality event at RPL (325) building, named the Mark III Nuclear Criticality Detector (NCD), replacing the 40 year old Mark II. The materials are primarily schematic diagrams and other technical information that is of interest to a commercial manufacturer of similar equipment.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Nuclear Criticality Detector Mark-III", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-11-14", + "metadataLastUpdated": "2019-11-14" + }, + "description": "The software SAFIRE implements a fault injection tool to evaluate the impact of soft errors on parallel, multi-threaded applications.\n\nIt implements instruction-level fault models that emulate soft errors by flipping bits in the register operands of executed machine instructions.\n\nSAFIRE is based on the LLVM compiler and utilizes novel techniques to optimize instruction instrumentation and fault injection. \n\nBy detailed measurements, SAFIRE is multiple times faster than other state-of-the-art fault injection techniques, while having the same accuracy.", + "laborHours": 1362148.0, + "languages": [], + "name": "SAFIRE : Scalable and Accurate Fault Injection for Parallel Multi-threaded Applications", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/safire", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "v1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Software for detecting matching subgraphs within a temporal network dataset, such that the chronology ordering of the edges is identical to the query graph. This can be used to find patterns of behavior in temporal graph data that may be of interest for a particular use case. The resulting matching nodes, edges and subgraphs are then output for the user, including the number of times a particular node was found to be associated with a temporal subgraph match. The number of times a node is associated with a match may indicate that node is more noteworthy for the given use case.", + "laborHours": 2249.6, + "languages": [], + "name": "Temporal Subgraph Isomorphism Detector", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/temporal_subgraph_isomorphism", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "julia.dark@cfdrc.com" + }, + "date": { + "created": "2019-11-18", + "metadataLastUpdated": "2019-11-18" + }, + "description": "Peridot is a mesh free state-based peridynamics simulation developed using the Kokkos library for parallel execution. ", + "homepageURL": "https://www.cfd-research.com/products/peridot", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Peridot", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.cfd-research.com/products/peridot", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "version": "0.1.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python package to be used when working with the DDAO method of visualizing phosphatase activity in the rhizosphere. Includes a module with functions that generate figures for analysis of phosphatase levels in images of soil and root based on pixel intensity. These functions can be used on images with a single root or multiple roots. Figures include distance maps to show how phosphatase levels change as you move away from the root and along the roots themselves, line plots to show average phosphatase levels moving down the root and the soil surrounding the root, 2D histograms to show how phosphatase levels change moving away from the root, and 1D histograms to show overall differences in phosphatase distribution depending on whether a root was grown next to a phosphorus source or not.", + "laborHours": 273.6, + "languages": [], + "name": "pnnl/rhizo_phosph", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/rhizo_phosph", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-11-19", + "metadataLastUpdated": "2019-11-19" + }, + "description": "This software is to implement real-time energy dispatch for distributed energy resources such as distributed PV, using distributed control algorithm that NREL has developed. The software is developed using Python and is available as open-source. ", + "laborHours": 957.6, + "languages": [ + "Python" + ], + "name": "Real-Time Distributed Energy Resource Energy Dispatch Using Distributed Control", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DER-Dispatch", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-11-20", + "metadataLastUpdated": "2019-11-20" + }, + "description": "There are numerous options for renewable energy systems development. Location, size, type of system, and a number of other criteria need to be considered. The objective of this program is to determine the optimal size (capacity, Kilowatt (kW)) of a renewable energy generator, based on minimizing life cycle cost (LCC). The reason for developing such a program is driven by three major issues. First, the need to evaluate a very large number (tens of thousands) of project opportunity sites. Next, the need for data transfer efficiency and computational efficiency in on-line and mobile applications. And lastly, to increase the accuracy of screening studies, which are the earliest indicators of project opportunities. Many existing programs require the user to enter the size (kW) of the renewable energy system in order to start calculations. \n \nHowever, there are many factors that affect what the size should be including: renewable energy resources, utility rates, initial and maintenance costs, and economic parameters. NREL scientists have developed an algorithm that addresses the previous three major issues. Lifecycle cost is calculated based on: the sum of initial cost, plus the present value of operations and maintenance costs, costs involved with purchasing power from the utility company, and revenue involved with the sale of excess electricity back to the utility.\n\nThe algorithm computes the derivative of an equation for LCC as a function of the size of the renewable energy generator (P), then sets the derivative equal to zero (dLCC/dP=0), and solves for the value of (P) that minimizes life cycle cost. Once the size (P) has been determined, other project details may be calculated. This algorithm develops a closed-form solution for the optimal size of a renewable energy generator. Having a closed-form solution avoids problems of scale and speed that can be encountered with optimization algorithms. Incentives that affect initial cost or provide a payment for energy production are also represented.\n\nBecause the algorithm was built in terms of analytics (calculus) and not numeric methods, it can be easily implemented in any platform such as spreadsheets or mobile computing applications. The program is very accurate as long as the simplifying assumptions in the derivation apply: constant load (during daylight hours for PV, all hours for wind); a single rate for all power purchased from the utility; and a single rate for all power sold back to the utility. The program calculates energy saved on-site and energy sold back to the utility using a duration curve based on capacity factor. Data for the calculation is available on-line at www.nrel.gov/gis.", + "homepageURL": "https://www.labpartnering.org/p/lab-technologies/4d681f46-9778-4024-877c-6633a9617a0b", + "laborHours": 0.0, + "languages": [], + "name": "dlCC Optimization", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.labpartnering.org/p/lab-technologies/4d681f46-9778-4024-877c-6633a9617a0b", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.labpartnering.org/p/lab-technologies/4d681f46-9778-4024-877c-6633a9617a0b", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-11-25", + "metadataLastUpdated": "2019-11-25" + }, + "description": "The Modelica IBPSA MPC Library is a free open-source library with basic models that codify best practices for the implementation of models to be used in Nonlinear Model Predictive Control of building and community energy systems.\n\nThe development of the Modelica IBPSA MPC Library is organized through the IBPSA Project 1 (https://ibpsa.github.io/project1) of the International Building Performance Simulation Association (IBPSA).", + "laborHours": 15.2, + "languages": [], + "name": "Modelica IBPSA MPC Library v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ibpsa/modelica-ibpsa-mpc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Flow routing using a hexagonal grid.", + "laborHours": 2158.4, + "languages": [], + "name": "pnnl/hexwatershed", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/hexwatershed", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-12-02", + "metadataLastUpdated": "2021-09-07" + }, + "description": "HYbrid Battery Robust Energy Design (HYBRED) Tool is formulated as a mixed integer linear programming (MILP) model where discrete decisions are taken as of size of battery per type, choice of service each battery type can provide at a specific time (grid or dynamic regulatory service), and times of charging and discharging each battery. The potential charging sources are grid and renewables while the end users are commercial and industrial building loads, and electrical vehicles. The objective of the model is to maximize the batteries profit or in other words, to minimize the total battery cost. Major inputs to the model are solar irradiation profiles, time of use tariffs, buildings loads, dynamic regulatory service signal, various battery parameters, etc. Major outputs of the tool include battery sizes, costs and revenues, temporal profiles, and duration curves.", + "homepageURL": "https://www.labpartnering.org/p/lab-technologies/02761bf5-e886-43b9-b506-5be4b0416b99", + "laborHours": 0.0, + "languages": [], + "name": "HYBRED (HYbrid Battery Robust Energy Design Tool)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.labpartnering.org/p/lab-technologies/02761bf5-e886-43b9-b506-5be4b0416b99", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.labpartnering.org/p/lab-technologies/02761bf5-e886-43b9-b506-5be4b0416b99", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-02", + "metadataLastUpdated": "2019-12-02" + }, + "description": "A re-implementation of Quantile Kriging.\n\nQuantile Kriging was described by Matthew Plumlee & Rui Tuo in their 2014 paper \"Building Accurate Emulators for Stochastic Simulations via Quantile Kriging.\" \n\nWith computational savings when dealing with replication from the recent paper \"Practical heteroskedastic Gaussian process modeling for large simulation experiments”, it is now possible to apply Quantile Kriging to a wider class of problems. \n\nIn addition to fitting the model, other useful tools are provided such as the ability to automatically perform leave-one-out cross validation.", + "laborHours": 288.8, + "languages": [], + "name": "Quantile Kriging R Package", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/quantkriging", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-02", + "metadataLastUpdated": "2019-12-02" + }, + "description": "Simplexdesign is a small collection of tools for the design of statistical experiments on Agent \nBased Models.\n\nIt includes a coordinate exchange algorithm for homogeneous agents, and more generally any simplex. \n\nThere is also an optimization algorithm for the case with multiple classes of homogeneous agents.", + "laborHours": 136.8, + "languages": [], + "name": "Simplex Design for Stochastic Simulations and Agent Based Models", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/simplexdesign", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-02", + "metadataLastUpdated": "2019-12-02" + }, + "description": "Python package for a systems approach to blur estimation and reduction", + "laborHours": 440.8, + "languages": [], + "name": "Systems Approach to Blur Estimation and Removal", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sabersw/pysaber", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-04", + "metadataLastUpdated": "2019-12-04" + }, + "description": "The National Energy Research Scientific Computing Center (NERSC) is the primary scientific computing facility for the Office of Science in the U.S. Department of Energy. NERSC houses top-ranked Cray supercomputers, and our staff works very closely with on-site Cray engineers, submitting 75 Cray cases per month on average. Until recently, submitting a Cray case was only possible by phone or email, and all subsequent updates were delivered manually. This process led to delays, errors during manual data entry, and greatly increased incident processing and resolution time. In 2018, NERSC deployed an API-based bidirectional integration that allowed to submit and update Cray cases directly from our Incident Management platform, thus streamlining our 24x7 operations and enhancing communication between our engineering teams. This solution is applicable to any Incident Management platform.", + "laborHours": 5532.8, + "languages": [], + "name": "ServiceNow/CrayPort Integration v2.1.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/crayport/crayport-app-code.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "oleg@dynamite.ai" + }, + "date": { + "created": "2019-12-04", + "metadataLastUpdated": "2021-12-02" + }, + "description": "DynamiteNSM is a free Network Security Monitor (NSM), built on top of several leading, enterprise-grade technologies. The tool provides network and cybersecurity operators with holistic insights into their networks while giving them the ability to deep-dive into lower-level activities. The solution presents powerful dashboards, giving comprehensive view into performance and threat-based metrics. Dynamite-NSM can be easily deployed in different environments including high-speed data centers, small-to-large enterprises, IoT & industrial networks, and even at home.\n\nDynamite-NSM handles massive volumes of network traffic through scalable ingestion and optimized network sensors. The solution includes two key components: the agent and the monitor. The agent analyzes and forwards network events, while the monitor processes incoming events and displays analytic information. The monitor component builds upon the OpenSearch stack and is coupled with network packet inspection by Zeek and Suricata. \n\nDynamite-NSM is designed to be deployed very quickly with minimal configuration. Unlike many other tools, it can be installed and managed with a standalone command-line utility. The system is inherently passive without disruption to the network. There is no need to install agents on every computer, perform network scans, or directly interact with network assets.", + "laborHours": 4620.8, + "languages": [], + "name": "DynamiteNSM", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DynamiteAI/dynamite-nsm", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-05", + "metadataLastUpdated": "2020-02-05" + }, + "description": "A central goal in experimental science is to explore and understand the composition-processing-structure-property relations of materials in their associated multi-dimensional parameter spaces, These parameter spaces can be thought of as the set of all conceivable combinations of the parameters affecting an experiment, including synthesis and processing conditions, material composition, and environmental conditions during the experiment. gpCAM analyzes data to steer the experiment. The software tool creates a surrogate model and associated uncertainties by performing a Gaussian process regression. Mathematical function optimization is then used to find measurements of maximum value.", + "laborHours": 1869.6, + "languages": [], + "name": "gpCAM v3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/MarcusMichaelNoack/gpcamv3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-05", + "metadataLastUpdated": "2019-12-05" + }, + "description": "The Localization and Mapping Platform (LAMP) software fuses radiation and contextual data to produce 3-D maps that locate and identify gamma-ray emitting sources in complex environments. It enables data collection, fusion, and processing onboard the LAMP system in handheld configurations, and enables near-real-time 3-D mapping from onboard an unmanned aerial system (UAS). This software enables a real-time 3-D gamma-ray mapping capability that is not available commercially. This software disclosure is for a new simultaneous gamma-ray and neutron mapping software update to the original LAMP software.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1124.8, + "languages": [], + "name": "Neutron Gamma LAMP Software version 1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-06", + "metadataLastUpdated": "2019-12-06" + }, + "description": "pyPicFusion is a standalone fusion reaction code that takes arbitrarily weighted macro-particles representing fusion reactants and generates fusion products. \n\nThe code takes into account the fusion cross-section and kinematics of the reaction to produce weighted fusion products with given velocities/energies in the laboratory frame.", + "laborHours": 364.8, + "languages": [ + "Python" + ], + "name": "pyPICfusion", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pyPICfusion", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-11", + "metadataLastUpdated": "2019-12-11" + }, + "description": "This repository contains code for the computational framework to build ML models for drug discovery\npurposes. \n\nOur end-to-end pipeline extracts features from model-ready datasets and trains and saves the model to our model zoo or to disk.\n\nOur pipeline generates a variety of molecular features and both shallow and deep ML models.\n\nThe HPC-specific module we have developed conducts efficient parallelized search of the model hyperparameter space and reports the best-performing hyperparameters for each of these feature/model combinations.", + "laborHours": 34656.0, + "languages": [], + "name": "Atom Modeling PipeLine", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ATOMconsortium/AMPL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-11", + "metadataLastUpdated": "2019-12-11" + }, + "description": "ompparser is a standalone and unified OpenMP parser, which is motivated by the facts that:\n\n1) The differences in terms of syntax and semantics of OpenMP constructs between C/C++ and Fortran\nare minor.\n\n2) Current OpenMP compilers often develop their own parsers, which represent redundant work.\n\nThe features of ompparser include:\n\n1) ompparser can be used standalone for static source code analysis, e.g. tools for semantics checking or similarity analysis between C/C++ and Fortran programs\n\n2) omppaser can be integrated into an OpenMP compiler implementation can reduce the development efforts, and there is no need to create and maintain two separate parsers for C/C++ and Fortran.\n\n3) ompparser provides a complete reference OpenMP grammar in the Backus-Naur Form that formally describes all the latest OpenMP language constructs.\n\nThis will help users understand the rules and restriction of the OpenMP standard, which no longer contains a reference grammar in its recent versions.\n", + "laborHours": 3769.6, + "languages": [], + "name": "Ompparser", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/passlab/ompparser", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-12-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Locating Luna is a STEM Education virtual reality game for grade 6-12 students. Users search for a lost dog in a dark swamp, calling out to the dog and lighting torches as they search. The app collects data on all user actions which are saved in a file for download. Teachers then have students use various tools to represent and analyze their data. This provides a common interactive experience for teachers to use in addressing computer science learning standards. Locations of key points of interest in the app (such as the dog) are randomly generated when the game is restarted; however, replay without a restart of the game allows users to try the same scenario again with a different search strategy. This allows users to compare strategies using data. A teacher's guide supports use by teachers in the classroom.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Locating Luna", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-12-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Analysis and reporting for water and irrigation usage\nPNNL developed the Water Balance Tool, which provides a method to determine potable water consumption, by end-use, of a campus. A water balance compares the total water supply to the volume of water consumed by water-using equipment and applications. The output of the tool provides the estimated potable water consumption by major end-use and compares the sum of the end-uses to the total potable water supplied to the campus.", + "laborHours": 6824.8, + "languages": [], + "name": "pnnl/femp-water-balance", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/femp-water-balance", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lyon@fnal.gov" + }, + "date": { + "created": "2019-12-13", + "metadataLastUpdated": "2019-12-13" + }, + "description": "Linux style development, like what we do for particle physics experiments at Fermilab, is becoming more difficult on the Mac. Apple is moving to its own style of development that is often incompatible. For example,\n\n* System Integrity Protection (SIP) prevents using DYLD_LIBRARY_PATH, breaking the mechanism used by our development environment system, ups.\n\n* Mac headers and system libraries are not always compatible with those on Linux, necessitating platform dependent code.\n\n* XCode is more focused on Swift, Objective-C, and Mac or iOS-style development. XCode does not understand CMake builds natively.\n\nThe differences that Mac and XCode introduce are difficult to manage and many experiments have stopped making Mac builds. Despite these problems, Mac laptops remain powerful machines and the MacOS environment is advantageous in many other areas. Therefore, mitigating the problems with Linux style development is motivated.\n\nThis package contains a configuration for docker containers along with instructions for integrating with the Mac that make for an effective and efficient development platform for Linux style development of physics code. Instructions for using CLion for C++ development in this environment are given in the documentation for running CLion within the linux container or from the Mac host.\n\nNote that the containers and techniques here may also work on Windows. You will have to adapt the instructions for that platform.", + "laborHours": 410.4, + "languages": [ + "Bash", + "docker" + ], + "name": "devenv", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lyon-fnal/devenv", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-16", + "metadataLastUpdated": "2019-12-16" + }, + "description": "The software developed is a library for the Modelica language. The library includes different extremum seeking control algorithms and examples of possible usecases. It is also intended to export the models as so called Functional Mock-up Units, which are models supported by any kind of software which supports the Functional Mock-up Interface standard.", + "laborHours": 15.2, + "languages": [], + "name": "Extremum Seeking Library (ESL) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/ESL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2023-05-08" + }, + "description": "Persistent model serves as the baseline in the intra-hour forecasting of solar radiation due to the extensive computing efforts from the numerical weather prediction (NWP) models and the lack of surface observations in cloud as well as other atmospheric properties. The smart persistent model actively updates the extraterrestrial solar radiation with time and is an important improvement from the persistent model while the cloud conditions are assumed unchanged by giving constant clear-sky indexes. We developed a Physics-based Smart Persistent model for Intra-hour solar forecasting (PSPI) to further improve the accuracy of the smart persistent model. We used a cloud retrieval technique developed by Xie and Liu (2013) to estimate cloudy fraction and cloud albedo using surface-based observations of solar radiation. The solar radiation in future time steps is accurately given by actively computing individual cloud albedo related to the future solar position. Our evaluation studies indicated that the PSPI model significantly increased the accuracy in the short-term forecast of solar radiation, especially in thin cloud conditions or those covered by broken clouds.", + "laborHours": 410.4, + "languages": [ + "Python", + "Dockerfile" + ], + "name": "Solar-Forecast GridAPPS-D Application [SWR-18-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Solar-Forecasting", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2024-09-17" + }, + "description": "The PyEPANET package is a set of commands for the Python programming language that are built to wrap the EPANET toolkit library commands, without requiring the end user to program using the ctypes package. This package does not contain the \nEPANET code, nor does it implement the functions within the EPANET software, and it requires the separately downloaded or compiled EPANET2 toolkit dynamic library (epanet.dll, libepanet.so, or epanet.dylib) and/or the EPANET-MSX dynamic library in order to function. \n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 147744.0, + "languages": [ + "Python", + "C++", + "C" + ], + "name": "PyEPANET v. 0.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PyEPANET", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2024-06-11" + }, + "description": "Program uses linear, nodal finite elements to solve the space-fractional Helmholtz equation over segments of an arbitrary 3D graph.SAND2019-11082 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 1124.8, + "languages": [ + "Fortran" + ], + "name": "FRACHELM v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-04" + }, + "description": "PyApprox provides flexible and efficient tools for high-dimensional approximation and uncertainty quantification. PyApprox implements methods addressing various issues surrounding high-dimensional parameter spaces and limited evaluations of expensive simulation models with the goal of facilitating simulation-aided knowledge discovery, prediction and design. Tools are provided for: (i) building surrogates using polynomial chaos expansions using least squares, compressive sensing and interpolation; (ii) sparse grid interpolation and quadrature; (iii) low-rank tensor-decompositions; (iv) multi-fidelity approximation and sampling; (v) large-scale Bayesian inference; (vi) numerical solvers for canonical ordinary and partial differential equations useful for demonstration purposes; compressive sensing solvers (vii) and (viii) visualization. The code is intended to as a python toolbox but provides c++ code with Python interfaces to computationally expensive algorithms to increase performance. SANDS2019-5458 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. \n", + "laborHours": 48807.2, + "languages": [ + "C++", + "Python" + ], + "name": "Python Approximation Toolbox (PyApprox) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/pyapprox/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyapprox", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-05" + }, + "description": "This software examines raw Illumina sequence data files for cas genes and CRISPR arrays, either to be used as evidence of genome editing or for basic analysis of bacterial genomes. It translates sequencing reads into peptide sequences, and runs these against sensitive hidden Markov models for numerous Cas protein families. The set of hit read seeds is then expanded leftward and rightward by sequence matching to remaining reads, and after multiple cycles, this small fraction of the original reads is assembled to produce Cas operons. A separate mode using known CRISPR repeat sequences for a genus are used to identify CRISPR arrays that may be in genomic locations that are isolated from Cas genes.SAND2019-11770 M\n\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.\n", + "laborHours": 410.4, + "languages": [ + "Perl", + "Python" + ], + "name": "CasCollect: Detecting cas genes and CRISPR arrays in raw sequence data v1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CasCollect", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2024-08-07" + }, + "description": "A clear way to increase current capabilities for seismic nuclear explosion monitoring is to supplement the global International Monitoring System (IMS) network with openly available stations. The quality of openly available data is typically much lower than that of the IMS, given the wide variety of experimental goals and deployment conditions. Incorporating additional stations without properly identifying and mitigating data quality problems can actually degrade overall monitoring capabilities. Towards that objective, Pycheron, a python-based library for seismic data quality control (QC) was developed. Pycheron began as a translation of the Incorporated Research Institutions for Seismology (IRIS) Modular Utility for STAtistical kNowledge Gathering (MUSTANG) package (written in R) into Python, but has grown into a stand-alone package that includes significant additional functionality. Pycheron is intended to be implemented at the beginning of the data processing pipeline. The objectives of the library are to: automatically assess data quality and instrumentation health; maintain the highest quality of data possible; identify specific and key problems; alert downstream processing algorithms to any degradation in quality; improve our ability to process orders of magnitudes more data; and, serve as a basic service that all data processing within our program builds upon. Pycheron calculates metrics characterizing quality over time as well as creating QC masks to identify each interval with a QC problem. SAND2019-11607 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 34124.0, + "languages": [ + "Python", + "CSS", + "Fortran" + ], + "name": "Pycheron", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pycheron", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2019-12-19" + }, + "description": "A library of utility classes for computer vision. Contains implementations of various well-known image processing techniques, such as interest point operators and region descriptors. Includes interfaces to various libraries for image and video I/O, as well as an interface to LAPACK/BLAS. FL was developed at the University of Illinois, Urbana-Champaign (UIUC) and released under an open source license. Version 1.2 was a maintenance release provided by SNL under the LGPL license. Version 1.3 is a maintenance release, containing the following changes: - Improved image format handling. Now handles strided and planar memory layouts and a wider range of pixel formats. - Improved image file I/O, including better support for metadata, a wider range of stored pixel types, and a couple of new file formats. - Improvements to DOG and SIFT, and efficiency improvements in low-level convolution. - Improvements to networking, including a generic TCP listener. - Various improvements to numerical processing. The HISTORY file included in the distribution contains a more detailed description of the changes.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "FL V1.4", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.4" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-04" + }, + "description": "Deep learning has been applied with great success to the segmentation of 3D X-Ray Computed Tomography (CT) scans. Establishing the credibility of these segmentations requires uncertainty quantification (UQ) to identify problem areas. Bayesian neural networks (BNNs), which use variational inference to learn the posterior distribution of the neural network weights, have been proposed to incorporate UQ into deep learning models. This software is an implementation of a novel 3D Bayesian convolutional neural network (BCNN) that provides accurate binary segmentations and uncertainty maps for 3D volumes. In particular, the uncertainty maps generated by this BCNN capture continuity and visual gradients, making them interpretable as confidence intervals for segmentation usable in numerical simulations. SAND2019-12927 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 516.8, + "languages": [ + "Python" + ], + "name": "Bayesian Segmentation (BCNN) v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/bcnn", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-05" + }, + "description": "An entry to the IDASH PRIVACY & SECURITY WORKSHOP 2019 - secure genome analysis competition, Track I: Distributed Gene-Drug Interaction Data Sharing based on Blockchain and Smart Contracts. The entire codebase is comprised of a single solidity file, GeneDrugRepo.sol. Solidity is a smart contract language for the Ethereum blockchain platform. SAND2019-13419 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 106.4, + "languages": [ + "Solidity" + ], + "name": "GeneDrugRepo.sol", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/iDASH2019GeneDrug", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-05" + }, + "description": "Nalu-Wind is derived from Nalu-CFD (for which Sandia has an existing copyright assertion). Nalu-Wind is specific to the wind energy simulation space. SAND2019-10379 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 134398.4, + "languages": [], + "name": "Nalu-Wind v.1.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exawind/nalu-wind", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-01-20" + }, + "description": "PAO supports the formulation and analysis of mathematical models for complex optimization applications. This capability is commonly associated with algebraic modeling languages (AMLs), which support the description and analysis of mathematical models with a high-level language. PAO is derived from the Pyomo subpackage pyomo.bilevel, which has been deprecated. PAO supports the formulation and solution of optimization models that explicitly represent adversarial behavior. This includes variances of bilevel programming, including methods that represent challenging problems with discrete decisions and uncertain model parameters. SAND2019-14490 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PAO", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2019-12-19" + }, + "description": "fpzip is a C/C++ library for lossless and lossy compression of 1D, 2D, and 3D single- and double-precision floating-point arrays. \n\nAlthough designed for lossless compression, the user may optionally request lossy compression by specifying how many bits of precision per floating-point value to retain.\n\nFpzip supports streaming compression and decompression with either a memory buffer or a file as source or destination. \n\nIn addition to a simple C interface, fpzip comes with an executable for (de)compressing binary files.", + "laborHours": 1322.4, + "languages": [], + "name": "FPZIP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/fpzip", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.2.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-07-30" + }, + "description": "MPI library that supports serializing (and check-pointing) its MPI Stages is a communication library that allows nodes and programs in a computer cluster to communicate via the Message-Passing Interface (MPI).\n\nThe internal data objects of the library are serializable, i.e., the user can convert the MPI state or objects, such as groups or communicators, into byte streams and save them into a checkpoint file. \n\nLater users can load the checkpoint file and de-serialize previous objects into the library. \n\nSerialization/de-serialization is useful in MPI applications to recover from node failures.", + "laborHours": 9636.8, + "languages": [], + "name": "MPI Stages : A Serializable MPI Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/mpi-stages", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-12-23", + "metadataLastUpdated": "2024-10-25" + }, + "description": "Offshore Renewables Balance of System and Installation Tool (ORBIT) simulates balance of system and installation processes for offshore wind plants. It is intended to be used to study the effects of weather delays on offshore vessel logistics and for medium fidelity trade-off studies for offshore technologies.", + "laborHours": 10776.8, + "languages": [ + "Python" + ], + "name": "ORBIT (Offshore Renewables Balance of System and Installation Tool) WISDEM® [SWR-20-11]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/ORBIT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.8" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-23", + "metadataLastUpdated": "2021-07-22" + }, + "description": "GPU-BSW is a version of Smith-Waterman alignment algorithm which has been optimized to perform large number of sequence alignments on GPUs.", + "laborHours": 851.2, + "languages": [], + "name": "A Domain indEpendent sequence alignment strategy for gPu archiTectures (ADEPT) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/m-gul/GPU-BSW", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-01-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Biological Performance Assessment (BioPA) version 3, uses computational fluid dynamics (CFD) and particle trajectory simulations of the hydro-turbine to quantify the exposure of passing fish to a set of known injury mechanisms. By appropriate sampling of the fluid domain, the BioPA assigns exposure probabilities to each mechanism. The exposure probabilities are combined with dose- response data from laboratory stress studies of fish to produce a set of biological BioPA Scores. These metrics provide an objective measure that can be used to compare competing turbines or to refine a new design.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Biological Performance Assessment (BioPA) Toolset version 3", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "3" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-06", + "metadataLastUpdated": "2020-01-06" + }, + "description": "DiHydrogen is the second version of the Hydrogen fork of the well-known distributed linear algebra library, Elemental. \n\nDiHydrogen is a GPU-accelerated distributed multilinear algebra interface with a particular emphasis on the needs of the scalable distributed deep learning training and inference. \n\nDiHydrogen is part of the Livermore Big Artificial Neural Network (LBANN) software stack.", + "laborHours": 38456.0, + "languages": [], + "name": "DiHydrogen", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/dihydrogen", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-01-07", + "metadataLastUpdated": "2020-01-07" + }, + "description": "This software simulates and compares the losses in AC and DC buildings. It uses formatted load profile data from EnergyPlus, PV generation data from PVWatts, realistic converter efficiency curves based on product data, a battery controller based on excess PV, and a realistic wire model. The software includes Modelica code, which is an extension of the Buildings Library Electrical models. It also includes Python code, which manages the Modelica parametric simulations and plots results.", + "laborHours": 36571.2, + "languages": [], + "name": "Modelica Buildings Library Extension for AC and DC Building Comparison (Modelica DC Buildings) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dgerb/DCBuildingSimModelica", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-01-09", + "metadataLastUpdated": "2020-07-27" + }, + "description": "Brief Description for Public Release:\nVarity is a framework to identify variations in floating-point programs through randomized differential testing. Varity generates random tests that include floating-point operations and compile these tests with different compilers in a system. It also generates random floating-point inputs for the tests. When tests are executed, the results are compared to identify variations in the results. Varity helps users of a system to identify the compilers that produce the most similar results in the system.", + "laborHours": 15732.0, + "languages": [], + "name": "Varity", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Varity", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-01-09", + "metadataLastUpdated": "2020-01-09" + }, + "description": "This code is a simply python module that allows the user to read in the solar system value from a\nprovided database. It simply reads in the database, and calculates ratios with various values. Currently,\nthe solar system values from Lodders et al. (2009) are solely included. The tool is designed to assist a\nastrophysics / cosmochemist user in their daily life of calculating those ratios for programs and was\nwritten by the author to simplify his own life. A setup.py routine has been written as well. Release is\nanticipated via github as well as in the form of a pypi package.", + "laborHours": 121.6, + "languages": [], + "name": "Solar System Initial Abundnace Reader", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/iniabu", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The testbed “PRIME” is implemented as a typical end-to-end SCADA hierarchy, from the substation to the control center,\nusing a combination of a well-known power system simulator, power system control, hardware-in-the-loop (HIL) and\nindustry grade EMS software. Other cyber-physical testbeds have similar modularity. However, they lack flexibility in\nswapping out the software used for EMS, FEP, and the hardware used for RTU and relays as the computational\nsubsystems and the input/output (I/O) subsystems are tightly coupled and integrated. They tend to be tied to a single\nvendor. In our approach, the power system simulator and the hardware driver (analog output subsystems to drive HIL) are\ndecoupled and are interconnected through communication protocols as an interface. This provides an additional level of\nmodularity to the architecture creating an interoperable environment where power system simulators and hardware could\nbe interchanged as long as they support streaming of measurements/commands.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "PRIME", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A joint inverse module was developed by imposing structural similarities between different physical parameters and\nincorporated into the E4D geophysical simulator, a parallel multi-physics modeling and inversion code with unstructured\ntetrahedral mesh. The inversion capability of E4D can accommodate joint inversions of data from two or more geophysical\nmethods that are available in E4D and is suitable for large scale three-dimensional subsurface characterization or\nmonitoring. The joint inversion capability were tested using synthetic data from borehole electrical resistivity tomography\nand seismic survey.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "E4D Simulator with Joint Inversion Capability", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "chitra.sivaraman@pnnl.gov" + }, + "date": { + "created": "2020-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The MHKiT Code Hub is a collection of open-source marine renewable energy (MRE) software. The MHKiT code, developed in Python and MATLAB, includes modules for ingesting, quality controlling, processing, visualizing, and managing data. MHKiT-Python and MHKiT-MATLAB provide robust and verified functions in both Python and MATLAB that are needed by the MRE community to standardize data processing. Calculations and visualizations adhere to IEC technical specifications and other guidelines. Current functionality includes power performance, power quality, mechanical loads, resource tools, and data quality control for wave, tidal, and river applications.", + "laborHours": 579864.8, + "languages": [ + "MATLAB" + ], + "name": "MHKiT (Marine and Hydrokinetic Toolkit) - MATLAB", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MHKiT-Software/MHKiT-MATLAB", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "chitra.sivaraman@pnnl.gov" + }, + "date": { + "created": "2020-01-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The MHKiT Code Hub is a collection of open-source marine renewable energy (MRE) software. The MHKiT code, developed in Python and MATLAB, includes modules for ingesting, quality controlling, processing, visualizing, and managing data. MHKiT-Python and MHKiT-MATLAB provide robust and verified functions in both Python and MATLAB that are needed by the MRE community to standardize data processing. Calculations and visualizations adhere to IEC technical specifications and other guidelines. Current functionality includes power performance, power quality, mechanical loads, resource tools, and data quality control for wave, tidal, and river applications.", + "laborHours": 593985.6, + "languages": [ + "Python" + ], + "name": "MHKiT (Marine and Hydrokinetic Toolkit) - Python", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MHKiT-Software/MHKiT-Python", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2020-01-16", + "metadataLastUpdated": "2020-01-16" + }, + "description": "cubacpp provides a C++ binding for the excellent CUBA library, and to a lesser extent, to the GSL integration library GSL. cubacpp provides no new integration facilities. It merely provides a more convenient syntax for use of the CUBA (and GSL) integration routines, made possible by the features of the C++ programming language.", + "laborHours": 7995.2, + "languages": [], + "name": "cubacpp", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/mpaterno/cubacpp", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "gwright@pppl.gov" + }, + "date": { + "created": "2020-01-16", + "metadataLastUpdated": "2020-02-25" + }, + "description": "CUDA C Orbit Model\n\nNumerical guiding center code for toroidally confined plasma.", + "laborHours": 2812.0, + "languages": [ + "C", + "C", + "CUDA" + ], + "name": "cuOrbit", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PrincetonUniversity/cuOrbit", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "vcs": "git", + "version": "validation-alpha-rc1" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-24", + "metadataLastUpdated": "2020-01-24" + }, + "description": "Code takes a data file of input features of a set of digitized pulses and converts the file to three vectors describing a two-component Gaussian mixture model of the input pulses. \n\nThese three vectors can then be applied mathematically to a set of input feature data of digitized pulses to \ngenerate soft-scores describing the likelihood of each pulse's membership in each of the two Gaussian modeled components. \n\nThe operation of the code also displays graphics to the user for \ninterpreting the output vectors and\ndistribution of the soft-scores of the input data.", + "laborHours": 182.4, + "languages": [], + "name": "PSD GMM Trainer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/trainGMM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-27", + "metadataLastUpdated": "2020-01-27" + }, + "description": "AutoParBench is a benchmark framework to evaluate compilers and tools designed to automatically insert\nOpenMP directives. \n\nThe goal is to generate actional information (bug reports and feature requests) for compiler and tool developers.\n\nWe also want to drive the research for automatic parallelization using OpenMP and make OpenMP more declarative to reduce the burdens on OpenMP users.", + "laborHours": 209866.4, + "languages": [], + "name": "AutoParBench", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/autoparbench", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "Python class for handling encrypted elements in a config file. Extension of ConfigParser. This class overides the 'get' method of ConfigParser replacing it with Fernet symmetric encryption so that you can safely store encrypted passwords in an ini file.", + "laborHours": 152.0, + "languages": [ + "Python" + ], + "name": "CryptoConfig (ITS Data Management)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CryptoConfig", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "Identification of cell state based on objective metrics is a fundamental problem in developmental biology. With the advent of fluorescent activated cell sorting (FACS), transcriptomics, and (more recently) single-cell RNA sequencing, it has become possible to profile mRNA abundance of all genes in individual cells or cell types. This transcriptomic information for cell types is often characteristic, and can be used to classify cell types for cells with unknown identity. Previously, an algorithm was developed using a Bayesian method to derive specificity scores for all genes across all known cell types, and then to use these scores to assign the most likely cell type for a new transcriptomic profile. ICITools implements this Index of Cell Identity algorithm as an R package, making the method more easily distributed. In addition, this package implements slight improvements on the previous implementation by adding parallelization, small enhancements in speed, and the ability to customize some aspects of the specificity score computation method. The package does not alter the underlying algorithm, nor the overall functionality of the original methods.", + "laborHours": 380.0, + "languages": [], + "name": "ICITools v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/b-coli/ICITools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "The Remote Mirror Security project is a git hook used to evaluate a remote repository from which changes are mirrored and enforce a security policy before accepting changes.", + "laborHours": 866.4, + "languages": [], + "name": "Remote Mirror Security", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/remote-mirror-security", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "This software implements an active learning framework for Natural Language Processing (NLP) systems.\n\nIt is intended to be applied on scenarios where limited amount of labeled data is available to train a machine learning-based NLP classification system, but a large set of unlabeled documents exist. \n\nThis software will point, from the set of unlabeled documents, which ones we should label next so that the overall performance of the classifier is improved.", + "laborHours": 1064.0, + "languages": [], + "name": "Active Learning for NLP Systems", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AL_NLP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "The Detection Framework Testbed and Toolkit \n(DFTT) is a signal detection system that uses\nautomatically generated subspace and correlation detectors. \n\nDFTT is intended to facilitate the development and testing of algorithms for operating suites of such detectors. \n\nThe software is a generalization of the system described in Harris and Dodge (2011) and has been applied in contexts ranging from local borehole induced seismicity to large-scale teleseismic observations. \n\nThe software includes interactive applications for creating detection configurations, inspecting and \nediting templates, viewing detection statistics, viewing detected signals, classifying detectors and more.", + "laborHours": 102448.0, + "languages": [], + "name": "Detection Framework Testbed and Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DFTT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-31", + "metadataLastUpdated": "2020-01-31" + }, + "description": "Evaluate Copson's solution for the free expansion of an ideal gas into vacuum. \n\nThe solution for streamlines and characteristics are given along with a way to evaluate the solution for any (x,t) location.", + "laborHours": 334.4, + "languages": [], + "name": "Copson Expansion Solution", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/copson_expansion_solution", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "BuildingSyncRails is a library for the Ruby on Rails [1] web application development framework that leverages the Isomorphic library for the Ruby programming language (IPID Submission #11610) in order to provide BuildingSync [2] XML capabilities to Ruby on Rails applications. BuildingSyncRails provides the following capabilities:\nCapability to download the most recent version of the BuildingSync XML schema document from GitHub and to automatically convert said document into Ruby code.\nToolkit for constructing and manipulating Ruby objects that represent BuildingSync XML elements.\nBuildingSyncRails builds upon the capabilities of the Isomorphic library for the Ruby programming language; specializing the generic capabilities of the Isomorphic library for BuildingSync specifically, e.g., by providing a library of BuildingSyncfriendly methods to simplify the construction of BuildingSync XML documents.", + "laborHours": 304.0, + "languages": [], + "name": "pnnl/building_sync_rails", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/building_sync_rails", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Isomorphic is a Ruby library for specifying isomorphisms between Ruby objects.\nThe inventive features of the new Ruby library are as follows:\nDomain-specific language (DSL) for declaration of isomorphisms between Ruby objects.\nFunctional references (viz., \"lenses\") for getter/setter operations.\nTo our knowledge, this is the first library of its kind for the Ruby programming language. Moreover, to our knowledge, this is the first implementation of the \"functional references\" concept within the Ruby programming language.", + "laborHours": 714.4, + "languages": [], + "name": "pnnl/isomorphic", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/isomorphic", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "GridPACK is a software framework consisting of a set of modules designed to simplify the development of programs that model the power grid and run on parallel, high performance computing platforms. It also contains several fully developed applications, including powerflow, dynamic simulation, state estimation, Kalman filter analysis (dynamic state estimation), contingency analysis and real time path rating. These applications can be used either standalone or as components in more complicated workflows that combine several different types of application together. The framework modules are available as a combination of libraries and software templates and consist of components for setting up and distributing power grid networks, support for modeling the behavior of individual buses and branches in the network, converting the network models to the corresponding algebraic equations, and parallel routines for manipulating and solving large algebraic systems. The framework also contains a module for distributing tasks evenly amongst computing resources, even if individual tasks vary widely in their execution times. Additional modules support input and output, basic statistical analysis of contingency based calculations, distributed data structures, as well as basic profiling and error management.", + "laborHours": 217861.6, + "languages": [], + "name": "GridOPTICS/GridPACK", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GridOPTICS/GridPACK", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-07", + "metadataLastUpdated": "2020-02-07" + }, + "description": "MHYSA is a conservative finite-difference code to solve the 1D, 2D, and 3D multispecies Navier-Stokes equations for hypersonic flow applications. \n\nIt supports Cartesian grids only and has the option of including immersed boundaries.\n- Solves 1D Euler and 2D and 3D Navier-Stokes equations.\n- Solves the PDEs over Cartesian grids.\n- Written entirely in C and uses the MPICH library. It also uses OpenMP threads but this is a work-inprogress.\n- Can be compiled with PETSc (http://www.mcs.anl.gov/petsc/), if available, where it can use PETSc's time integration module TS (http://www.mcs.anl.gov/petsc/petsc-current/src/ts/).\n- For 3-dimensional simulations, the immersed boundaries can be used to solve over non-Cartesian geometries.\n\nMHYSA has been developed to be scalable, and apart from the usual functionalities to solve a system of PDEs on distributed architectures, it provides scalable file I/O functions.\n", + "laborHours": 16704.8, + "languages": [], + "name": "Multispecies Hypersonic Flow Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/mhysa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-07", + "metadataLastUpdated": "2020-02-07" + }, + "description": "Bindee is a clang tool that outputs a simple pybind11 template given a C++ file for efficient generation of C++-Python bindings. \n\nBindee is intended to be a helper tool for minimizing initial user effort and\nsafeguarding against common runtime errors.\n\nBindee relies on two open-source software to produce bindings.\n\nClang's LibTooling enables bindee to traverse a C++ file's AST to pick out bindable variables and functions, or \"bindees.\"\n\nPyBind11 is templated, header-only library for generating C++-Python bindings for variables and functions.\n\nOperating purely in C++, bindee does not require learning any new API for accomplishing its task.\n\nAdditionally, picking the correct pybind11 API for a given bindable element is handled without interaction from the user. Any user input is denoted by '@TEXT@' string substitution.\n\nBindee is capable of generating modular bindings for public class methods, public class variables, enumerations, and free functions and variables. \n\nBindings for templates are also supported. \n\nFor those familiar with pybind11, bindee does not handle trampolines, C++ extensions through lambdas, or custom type casters.\n", + "laborHours": 1915.2, + "languages": [], + "name": "Bindee", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/bindee", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-02-10", + "metadataLastUpdated": "2020-02-10" + }, + "description": "This mini app is to measure performance of a kernel for computing the correlation energy of GAMESS (General Atomic and Molecular Electronic Structure System) application on multiple processor architectures.", + "laborHours": 760.0, + "languages": [], + "name": "GAMESS RI-MP2 MiniApp", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/NCSA", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jkwack/GAMESS_RI-MP2_MiniApp", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-12", + "metadataLastUpdated": "2020-02-12" + }, + "description": "Reinforcement learning (RL) aims to learn optimal strategies for control problems with complex, stochastic dynamics. \n\nStandard RL formulations assume that transition dynamics are the same across episodes. \n\nHowever, this is not the case for many real-world environments, e.g. a disease process in which each patient is unique. \n\nTransfer learning in RL aims to solve this problem; however, existing methods allow for multiple trials on a test episode.\n\nWe consider the \"single episode transfer\" setting in which a policy is evaluated on one and only one test episode; thus, any adaptation must occur during that episode. \n\nSingle episode policy transfer (SEPT) is a framework for finding optimal control policies in this setting. \n\nIn SEPT, a \"probe policy\" initially probes the environment to gain information about how that episode is unique. \n\nThen, the information gained from the probe becomes an additional input to the \"universal policy\" that controls the remainder of the episode. \n\nSEPT is a general algorithm and can be used with any existing RL algorithm, including in batch learning mode.\n", + "laborHours": 4058.4, + "languages": [], + "name": "Single Episode Policy Transfer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/011235813/sept", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-02-12", + "metadataLastUpdated": "2020-02-17" + }, + "description": "GEOPHIRES v2.0 is a geothermal techno-economic simulation tool upgraded from GEOPHIRES v1.2. The name stands for \"GEOthermal energy for Production of Heat and electricity (“IR”) Economically Simulated\". GEOPHIRES combines reservoir, wellbore, and surface plant technical models with cost correlations and levelized cost models to estimate the capital and operation and maintenance costs, instantaneous and lifetime energy production, and overall levelized cost of energy of a geothermal plant. In addition to electricity generation, direct-use heat applications and combined heat and power or cogeneration can be modeled. Various upgrades have been implemented to develop GEOPHIRES v2.0, including: updating the built-in cost correlations, coupling to the external reservoir simulator TOUGH2, enhancing the built-in wellbore simulator, converting the programming language to Python, and making the code open-source. Users are encouraged to build upon the tool, e.g. by implementing their own correlations or coupling to other simulators. ", + "laborHours": 1140.0, + "languages": [ + "Python" + ], + "name": "GEOPHIRES v2.0", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GEOPHIRES-v2", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-13", + "metadataLastUpdated": "2021-10-05" + }, + "description": "Holotomography is a non-destructive x-ray imaging technique which allows to visualize the interior morphology of object without damaging them. It is similar to x-ray computed tomography (CT), but unlike conventional CT, which is based on the attenuation of x-rays passing through the object, holotomography exploits the phase shift caused by the sample. This phase-contrast imaging allows to increase image contrast by recovering refractive index of materials and is proven to be more sensitive to density variations than conventional absorption-based X-ray imaging when applied to low-Z materials. In holotomography, the phase is retrieved by measuring the variations in intensity of the object at different sample to detector distances. Several algorithms exist to perform this task such as, contrast transfer function (CTF), transport of intensity equation (TIE), and a mixed approach which combine both TIE and CTF.", + "laborHours": 349.6, + "languages": [], + "name": "Holotomography Phase-Retrieval", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jbforien/phaseCT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-02-13", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Analytical Data Reduction Excel Macro", + "laborHours": 0.0, + "languages": [], + "name": "ADREM", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/ADREM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gwright@pppl.gov" + }, + "date": { + "created": "2020-02-14", + "metadataLastUpdated": "2020-02-19" + }, + "description": "The CQL family are Relativistic Collisional/QuasiLinear Fokker-Planck codes.\n\ncql3d_f90 is a derived work of the CompX CQL3D Fortran IV/77 GNU code. This F90 version uses derived types, modules, fixes several bugs, is distributed with a Centos7 (Docker) container, and includes automated CI tests.", + "homepageURL": "https://princetonuniversity.github.io/cql3d_f90", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "cql3d_f90", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://princetonuniversity.github.io/cql3d_f90", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Virtual reality for biomolecular electrostatics UnityMol-APBS (NIH iEdison No. 0685901-19-0009, Grant No. GM069702)\nVisualization of molecular electrostatics on a two-dimensional screen greatly diminishes the associated depth component.\nUsing a virtual world to explore molecular electrostatics allows researchers to be immersed within their data.", + "laborHours": 15.2, + "languages": [], + "name": "UnityMol-APBS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electrostatics/VR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Prototype software for virtual reality based instruction manual for transmission electron microscopy (TEM).", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "TEM Instruction", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "nsu@lifeeusa.com" + }, + "date": { + "created": "2020-02-18", + "metadataLastUpdated": "2020-09-09" + }, + "description": "Deep neural network-based force field enables researchers to study materials systems of large size and/or time scale efficiently with comparable accuracy to DFT-based methods. However, such force fields, if improperly trained or mistakenly selected, could result in ill-conditioned results. This SBIR Phase I project has explored the possibility to characterize and index force fields in Deep potential theme by quantizing local atomic environments of atoms in a simulation system. This project has also demonstrated the feasibility of building a public accessible web infrastructure providing high quality machine learning algorithm-based force field for next generation materials modeling and simulation to accelerate the study and discovery of new energy-related materials.", + "laborHours": 638.4, + "languages": [ + "Python" + ], + "name": "LEMD", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mogudaxia/LEMD.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-20", + "metadataLastUpdated": "2020-02-20" + }, + "description": "Symbolic regression is the task of finding tractable mathematical expressions that best fit an input\ndataset. \n\nDeep symbolic regression (DSR) searches the space of tractable mathematical expressions by using a recurrent neural network that generates mathematical expressions. \n\nThe network is trained using reinforcement learning.", + "laborHours": 4985.6, + "languages": [], + "name": "Deep Symbolic Regression", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/brendenpetersen/deep-symbolic-regression", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The SMDS detects RTU performance degradation and select operational faults and provides estimates of the accrued energy and cost impacts weekly after detection of a performance issue. It uses only two sensors per each RTU, outdoor-air temperature and total power demand, both collected at one-minute intervals. Software code based on the methodology and algorithms developed by PNNL in a collaborative develop effort with NorthWrite Inc. and Universal Devices implement the detection processes and estimation of energy and cost impacts. The methodology, algorithms and original prototype software were developed exclusively by PNNL. Two versions of the SMDS, the Hardware SMDS and the Cloud SMDS, have been prototyped and tested on buildings in the field and/or on data from buildings. Both versions use the same methodologies for detection of performance degradation and for detection of specific faults.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Smart Monitoring and Diagnostic System (SMDS)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Ion Mobility control software designed to work specifically with Thermo Fisher Scientific ion trap (specifically the Exactive / Q Exactive)", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Ion mobility control software (Ion Trap coupled)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "rgrandy@bnl.gov" + }, + "date": { + "created": "2020-03-02", + "metadataLastUpdated": "2020-03-02" + }, + "description": "An open-source package for 2D X-ray near-edge spectroscopy analysis", + "laborHours": 10761.6, + "languages": [ + "Python" + ], + "name": "PyXAS", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gmysage/pyxas", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-03-03", + "metadataLastUpdated": "2020-03-03" + }, + "description": "These are miscellaneous utility functions that I've developed and found useful in working with sequencing counts.\n\nPurpose: To collect often reused procedures in one open source location that can be shared and worked on publicly, and perhaps contributed back to other open source projects.\n\nFunction: Adds, divides, filters, summarizes tables of counts.\n\nCapabilities: Currently, the main capability is to reformat count tables for use with the ALDEx2 package.", + "laborHours": 34428.0, + "languages": [], + "name": "Microbial Ecology Toy Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/meco", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.9000" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-03-03", + "metadataLastUpdated": "2022-07-28" + }, + "description": "MTtime is a software tool developed for time domain inversion of complete seismic waveform data to obtain the seismic moment tensor. It supports both deviatoric and full moment tensor inversions as well as 1-D and 3-D basis Green's functions.", + "laborHours": 0.0, + "languages": [], + "name": "Time Domain Moment Tensor Inversion in Python", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mttime", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-03-03", + "metadataLastUpdated": "2020-03-03" + }, + "description": "This tool traces all memory accesses to stack (static allocation) and heap (dynamic allocation) on a trace run in a particular hardware and then estimates execution time on given arbitrary hardware configurations for hardware design space exploration.\n\nIt can also compute memory access statistics, such as reuse distance.", + "laborHours": 6353.6, + "languages": [], + "name": "Memory Analysis Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-03-03", + "metadataLastUpdated": "2020-05-27" + }, + "description": "MFEM is a free, lightweight, scalable C++ library for finite element methods. \n\nThe goal of MFEM is to enable research and development of scalable finite element discretization and solver algorithms through general finite element abstractions, accurate and flexible visualization, and tight integration with the hypre\nlibrary.\n\nConceptually, MFEM can be viewed as a finite element toolbox that provides the building blocks for developing finite element algorithms in a manner similar to that of MATLAB for linear algebra methods.", + "laborHours": 0.0, + "languages": [], + "name": "Modular Finite Element Methods", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfem/mfem/releases/tag/v4.1", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "4.1" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-03-04", + "metadataLastUpdated": "2023-05-31" + }, + "description": "reVX is a complementary toolset that enables the extraction, translation, and loading (ETL) of reV results into formats required by downstream models, such as RPM, ReEDS, and PLEXOS.\n\nSEE ALSO: https://github.com/NREL/revruns", + "laborHours": 12737.6, + "languages": [ + "Python" + ], + "name": "reVX (The Renewable Energy Potential Exchange Tool) [SWR-20-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/reVX", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-03-04", + "metadataLastUpdated": "2023-08-25" + }, + "description": "The Renewable Energy Potential (reV) model is a platform for the detailed assessment of renewable energy resources and their geospatial intersection with grid infrastructure and land use characteristics. The reV model currently supports photovoltaic (PV), concentrating solar power (CSP), and land-based wind turbine technologies. Modules in the reV framework function at different spatial and temporal resolutions, allowing for the assessment of resource potential, technical potential, and supply curves at varying levels of detail. The platform runs on the National Renewable Energy Laboratory’s (NREL’s) high-performance computing system, providing scalable and efficient performance from a single location up to a continent, for a single year or decades of time-series resource data. Coupled with NREL’s System Advisor Model (SAM), reV supports resource assessments from 5-minute to hourly temporal resolutions and supports the analysis of long-term (i.e., year-on-year) variability of renewable generation (e.g., interannual variability and exceedance probabilities).", + "laborHours": 250526.4, + "languages": [ + "Python" + ], + "name": "reV (The Renewable Energy Potential Model - Open Source) [SWR-21-59, SWR-20-20 and SWR-17-34]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/reV", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2020-03-12", + "metadataLastUpdated": "2020-03-12" + }, + "description": "GlideinMonitor is a Web application that allows to view GlideinWMS’s Glidein log files: it provides a user interface, tools to do quick searches and to decode the log content; it provides an efficient managed archive of the log files and a framework to add log processing, e.g. log sanitation.\nhttps://docs.google.com/document/d/1PqmQ_-_JtqK472DT-Y0D08yU1m-lPeFvrp8n4x9f5QE/edit?usp=sharing", + "homepageURL": "https://cdcvs.fnal.gov/redmine/projects/glideinwms/repository/glideinmonitor", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "GlideinMonitor", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cdcvs.fnal.gov/redmine/projects/glideinwms/repository/glideinmonitor", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "dzander@sandia.gov" + }, + "date": { + "created": "2020-03-12", + "metadataLastUpdated": "2021-03-05" + }, + "description": "Shadow is a PyTorch based library for semi-supervised machine learning via consistency regularization.", + "laborHours": 820.8, + "languages": [ + "Python" + ], + "name": "shadow-ssml", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/shadow", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bethany@lbl.gov" + }, + "date": { + "created": "2020-03-14", + "metadataLastUpdated": "2020-03-14" + }, + "description": "A supervised machine learning pipeline, MIMOSAS (Multisource Input Model Output Security Analysis Suite), has been developed for classification of multimodal data to inform nuclear security and proliferation detection scenarios. MIMOSAS provides an end-to-end data processing workflow, from data ingestion and pre-processing to model training and test set classification. The pipeline is specified via an input deck, making workflow customization effortless, and the framework is modular allowing for the easy addition of new learning algorithms. In the current build, the user selects from decision tree, random forest, and feed-forward neural network classifiers to train customizable models with built-in cross validation methods for hyperparameter optimization. Trained model outputs are stored with the associated metadata for rapid deployment. These can be applied in supervised classification to assess previously unseen data or for further training as new observations are added to the existing data set. MIMOSAS provides the capability to fuse a wide range of data sources (e.g., radiation, environmental, acoustic, seismic, imagery, etc.) to make, confirm, and correlate machine learning predictions for nuclear security applications.", + "laborHours": 5198.4, + "languages": [ + "Python" + ], + "name": "MIMOSAS", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://complexity.berkeley.edu/wp-content/uploads/2019/09/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nonproliferation/mimosas", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-03-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This development was conceived to help solve the problem of the large number of chemical structures that result from a large number of atoms. This includes large surface models, functionalized surfaces, or supported clusters, relevant to many chemical problems in Separations and Catalysis. The program was developed to address these issues, and also solve the problem associated with the need to know the large number of structures that are energetically close. Knowing\nhow many structures are similar allows us to develop better starting models for large scale simulations.", + "homepageURL": "https://store.pnnl.gov/content/north-west-potential-energy-surface-search-engine-nwpesse", + "laborHours": 0.0, + "languages": [], + "name": "NWPEsSE (North West Potential Energy Surface Search Engine)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/north-west-potential-energy-surface-search-engine-nwpesse", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2020-03-17", + "metadataLastUpdated": "2020-03-17" + }, + "description": "nubhlight is a code for simulating disks of materials around black holes formed after the in-spiral and merger of two-black holes. It is based on the open-source code bhlight. nubhlight models all relevant physics required to solve the post-merger disk problem. This includes: general relativity in a static spacetime, neutrino and weak physics, relativistic magnetohydrodynamics, and the ability to use open-sourced tabulated equations of state provided by stellarcollapse.org.\n", + "laborHours": 27344.8, + "languages": [], + "name": "lanl/nubhlight", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/nubhlight", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-03-18", + "metadataLastUpdated": "2020-04-03" + }, + "description": "The Multi-Area Frequency Response Integration Tool (MAFRIT) is the only software tool of its kind that integrates primary frequency response (turbine governor control) with secondary frequency response (automatic generation control). It simulates the power system dynamic response in full time spectrum with variable time steps from millisecond to minutes to hours and days. Capable of simulating both normal and event conditions, this tool can represent real power system operations and thus evaluate the primary and secondary reserves adequacy. This unique interaction of a turbine governor model and a novel automatic generation control model places special emphasis on electric power systems with high penetrations of renewable generation.", + "laborHours": 3967.2, + "languages": [ + "MATLAB" + ], + "name": "MAFRIT (Multi-Area Frequency Response Integration Tool)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MAFRIT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-03-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This package includes the implementation for four sparse linear algebra kernels: Sparse-Matrix-Vector-Multiplication (SpMV), Sparse-Triangular-Solve (SpTRSV), Sparse-Matrix-Transposition (SpTrans) and Sparse-Matrix-Matrix-Multiplication (SpMM) for Single-node Multi-GPU (scale-up) platforms such as NVIDIA DGX-1 and DGX-2.", + "laborHours": 5715.2, + "languages": [], + "name": "s-blas", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/s-blas", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-03-24", + "metadataLastUpdated": "2021-08-17" + }, + "description": "This open-source tool implements Circular Economy metrics for photovoltaic (PV) materials. It can be used to quantify and assign a value framework to efforts on re-design, reduction, replacement, reuse, recycling, and lifetime and reliability increases in the PV value chain.\n\nThe PV_ICE is leveraging published data from different sources on PV manufacturing and predicted technological changes. Input data is being compiled here\n\nThis tool will help implement circularity metrics, quantify and assign a value framework to efforts on re-design, reduction, replacement, reusage, recycling, and lifetime and reliability increases on PV.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PV_ICE: PV in the Circular Economy, Dynamic Energy and Materials Tool (PV ICE)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PV_ICE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v. 2" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-03-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Project Schedule Comparison and Visualization allows project schedules to be compared across time scales. It also allows for visualization of schedules in the form of a network graph. This compliments Gantt chart view in major project risk management software. The software mimics complex networks and makes it easy to visualize tasks and links. It produces a list with differences between snapshots. Selecting these differences renders a view focused on these changes in the network.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Project Schedule Comparison and Visualization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "rgrandy@bnl.gov" + }, + "date": { + "created": "2020-03-30", + "metadataLastUpdated": "2020-03-30" + }, + "description": "PyMDA allows for processing individual microcrystal data sets as progressive wedges to address radiation damage and allows for robust extraction of diffraction signals including weak anomalous signals through the implementation of unit-cell-based classification and an iterative outlier rejection strategy. PyMDA may be used routinely to process microcrystal data sets to produce one or more assembled data sets for structural analysis.", + "laborHours": 395.2, + "languages": [ + "Python" + ], + "name": "PyMDA", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qun-liu/PyMDA", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-04-02", + "metadataLastUpdated": "2023-08-16" + }, + "description": "Simple examples of bokeh streaming data. The plots are intended to be generic and able to infer some of the plot data from the structure of the data sent. The receiver accepts zlib compressed pickled python dictionaries.", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "bokeh streaming [SWR 19-08]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bokeh-streaming", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-04-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Software that runs a model of a physical process either generated from extrapolative machine learning or from canned physics simulators to generate realistic data for feeding deceptive controller decoys for defense.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Process model simulator for deception", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-04-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A creation of packages of metadata, data, and communication networks services that are designed to highly accurately mimic the behavior of specific models of control system devices such as relays, PLCs, RTUs, etc. The inventive nature is the packaging of these features together such that they mimic specific models of equipment where existing approaches\nfocus on generalized control devices.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "High fidelity OT Decoy Profiles/Services", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-04-08", + "metadataLastUpdated": "2020-04-09" + }, + "description": "Modelica is a modeling and simulation language similar to Matlab/Simulink. Modelica has many advantages, which will not be discussed here, over conventional software. The software project implements a parser of the Modelica language allowing for easy-to-implement transformations of Modelica files.\n", + "laborHours": 4985.6, + "languages": [ + "Modelica" + ], + "name": "Modelica Builder (ModBuild)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/urbanopt/modelica-builder", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-04-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Rechargeable lithium metal batteries are being intensively studied in recent years because of their high energy density which potentially could double the cell energy of state-of-art Li-ion batteries. However, cell design of realistic high-energy Li metal batteries is quite different with Li-ion batteries, not mentioning prediction of cycle life. A powerful software using machine learning will greatly accelerate academic research and industry battery manufacturing process.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Application of Machine Learning for Rechargeable Lithium Metal Battery Design and performance prediction", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "savaraa@ornl.gov" + }, + "date": { + "created": "2020-04-13", + "metadataLastUpdated": "2020-09-25" + }, + "description": "UnitTesterSG is a unit testing framework that is designed for nested and/or scientific/engineering data structures. It is designed primarily for testing the outputs if a single function or simulation run by storing the expected results file such that comparisons to the stored output can be made with unit tests after the function or software has been edited.\n\nThis module is designed to be able to unit test arrays, strings, as well as nested and deeply nested objects (including arrays with tuples inside, arrays with strings inside, etc.). The module is compatable with nested objects, and thus has a dependency on the nestedObjectsFunctions module within. The module takes *calculated* results and then compares them to *expected* results. If no expected results are available (or they do not match the calculated results) the module then offers to store the calculated results as expected results for next time.", + "laborHours": 319.2, + "languages": [ + "Python" + ], + "name": "UnitTesterSG", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdityaSavara/UnitTesterSG", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "5.0" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-04-17", + "metadataLastUpdated": "2020-04-20" + }, + "description": "The Resource Extraction Tool (rex) includes tools developed for reV and reVX related to the efficient access of, extraction from, and computation on NREL's renewable resource datasets (NSRDB and WTK).", + "laborHours": 8040.8, + "languages": [ + "Python" + ], + "name": "Resource Extraction Tool (rex)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/rex", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-05-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Automated Raabe table generationPyRaabe is a Python package to automate Raabe table -- a graph representation of airway geometry -- generation from a triangulated surface of an airway geometry. With a single command, it extracts a centerline from an input 3D surface mesh and subsequently computes the relevant attributes for the Raabe table, including length, diameter, bifurcation angle, and gravity angle. These can be used to inform downstream models, such as the Multiple-Path Particle Dosimetry (MPPD) model.", + "laborHours": 91.2, + "languages": [], + "name": "pnnl/pyraabe", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pyraabe", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-05-01", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The data of a nuclear utility or plant are stored in various isolated forms in different systems. These data have different structures and tools and are, therefore, used independently. The integration of data sources is often needed and is performed manually and on an as-needed basis. The integration of the data would enable creating a data warehouse for a single nuclear power plant (NPP) or multiple plants. A data model contains objects that make up a given domain along with their attributes and relationships and could be used as a standard for exchange between applications for simple integration and data aggregation. After a survey of existing models, it was determined that a new model was required to meet the scope of this problem. DIAMOND has been developed in the form of an ontology to meet these needs. An ontology is simply a data model that also acts as a taxonomy for the domain, organizing the objects in a hierarchy with the most general objects at the top.", + "laborHours": 30.4, + "languages": [], + "name": "Data Integration Aggregated Model For Nuclear Deployment", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DIAMOND", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-08", + "metadataLastUpdated": "2020-05-08" + }, + "description": "MFEM is a modular parallel C++ library for finite element methods. Its goal is to enable high-performance scalable finite element discretization research and application development on a wide variety of platforms, ranging from laptops to supercomputers.", + "laborHours": 125658.4, + "languages": [], + "name": "Modular Finite Element Methods (MFEM)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfem/mfem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-08", + "metadataLastUpdated": "2020-05-08" + }, + "description": "Typeforge is a tool for type refactoring in C/C++ programs. It enables users to transform the type of any\nvariables or operations. It guarantees the syntactic and semantic correctness of the generated code -- it\nwill always compile!\nIs", + "laborHours": 9697.6, + "languages": [], + "name": "Typeforge", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/typeforge", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-08", + "metadataLastUpdated": "2020-05-08" + }, + "description": "Benchmark Algorithm for Radio-Nuclide Identification (BARNI) is an automatic radionuclide identification\ntool for use with gamma-ray spectra. BARNI is designed to serve as a comparative tool for commercial\nvendor algorithms, such as those found in RadioIsotope Identification Devices (RIID). The tool\nincorporates an automated training routine allowing BARNI's classifier to be trained for a variety of\ndetectors. The identification algorithm uses a peak search, the results of which are used to build features\nthat are subsequently used for training a classifier. The user provided spectral templates allow BARNI to\nbe trained for any detector of the user's choice.\nIs", + "laborHours": 1641.6, + "languages": [], + "name": "Benchmark Algorithm for RadioNuclide Identification v1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/barni", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-08", + "metadataLastUpdated": "2020-05-08" + }, + "description": "The Direct-FUSE framework supports multiple FUSE file systems as well as other, custom user-level file\nsystems in user space without the need to cross the user/kernel boundary into the FUSE kernel module.\nAll layers of Direct-FUSE are in user space, and applications can directly use pre-defined unified file\nsystem calls to interact with different user-defined file systems. Our performance results show that Direct-\nFUSE can outperform some native FUSE file systems by 11.9% on average and does not add significant\noverhead over backend file systems.\n", + "laborHours": 13588.8, + "languages": [], + "name": "Direct-FUSE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/direct-fuse", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2025-04-14" + }, + "description": "The \"Secure Design and Development Cyber Security Capability Maturity Model\" (SD2-CM2) allows electrical system managers to assess the maturity of their cybersecurity systems, including designs reflecting internet of things devices (IOT). The content provides best practices in the field and users can assess the level of their designs. Modules are \"Content\" and \"Infrastructure\"", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 3986352.0, + "languages": [], + "name": "Secure Design and Development Cyber Security Capability Maturity Model” (SD2-CM2)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2020-05-11" + }, + "description": "C++ template library to represent quantities in scientific computing. It enables a strong, compile-time,\ntyping of physical quantities. This typing includes information about:\n- representation: float, double, ...\n- unit: [ mass, length, time, angle ]\n- scale: kilo, milli, micro, ...\nIs", + "laborHours": 3040.0, + "languages": [], + "name": "Quantities need Representation, Unit and Scale", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/QRUS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2020-05-11" + }, + "description": "Narrows solves the discrete ordinates neutron transport equation using a neural network.", + "laborHours": 942.4, + "languages": [], + "name": "Narrows", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/narrows", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2020-05-11" + }, + "description": "Scanning Electron Microscopy (SEM) images provide a variety of structural and morphological\ninformation for the characterization of the nanomaterials. This code offers automatic recognition and\nquantitative analysis of SEM images in a high-throughput manner using computer vision and machine\nlearning techniques. The main function of this application is to extract particle size and morphology\ninformation of overlapping nanoparticles and core-shell nanostructures in a user friendly interface. The\ncode is written in C++ with QT environment, and has been tested on MacOSX.", + "laborHours": 3192.0, + "languages": [], + "name": "LIvermore SEM image Tools", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LIST", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2020-05-27" + }, + "description": "This is a program to convert a directory of Redvox JSON packets to a single HDF5 file.", + "laborHours": 228.0, + "languages": [], + "name": "PackageRedvoxToHdf5", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stevenmz/package-redvox-to-hdf5", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-12", + "metadataLastUpdated": "2020-05-12" + }, + "description": "QnD is a pure Python package for working with binary files. It has built-in support for HDF5, NetCDF3,\nand PDB formats. It provides a Pythonic, dict-like interface, and allows easy movement among time-like\n\"records\". Both reading and writing are enabled. The HDF and NetCDF capabilities rely on external\nlibraries, while the PDB support is part of QnD itself and entirely in Python. QnD works under Python 2\nand 3. For interactive use, much less typing is involved than for some other packages.", + "laborHours": 2310.4, + "languages": [], + "name": "Quick n Dirty", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/qnd", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-12", + "metadataLastUpdated": "2020-05-12" + }, + "description": "A whole cell model (WCM) is a comprehensive multi-scale computational model representing all the\nknown biochemical processes in a cell. It relies on a variety of intracellular pathway models and omics\ndata.\nThis computational framework enables seamless integration of diverse simulation methods used in WCM\nsuch as stochastic simulation algorithm (SSA), ordinary differential equations (ODE), flux balance\nanalysis (FBA), and logic-based approaches. These methods run simultaneously, not only for whole\npathways but also for subsets of reactions. Furthermore, we aim to enable dynamic switching between\nthe methods when beneficial.\nIs", + "laborHours": 12084.0, + "languages": [], + "name": "Whole cell simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/wcs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.4.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2020-05-13" + }, + "description": "Prediction of ligand-protein binding affinity from 3D atomic structures", + "laborHours": 2538.4, + "languages": [], + "name": "Fusion models for Atomic and molecular STructures", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FAST", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2020-05-13" + }, + "description": "This software is an implementation which is described in: \"Efficient Saliency Maps for Explainable AI\"\n(https://openreview.net/forum?id=ryxf9CEKDr). The toolkit is located in:\nhttps://mybitbucket.llnl.gov/projects/SAL/repos/smoe_lovi/browse. It is a set of of PyTorch related python\nscripts for extracting the what parts of an image are most salient to a deep neural network in an efficient\nmanner. This source will allow one to replicate the results in the paper referenced above.\nIs there", + "laborHours": 1170.4, + "languages": [], + "name": "Efficent XAI Information Saliency Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/fastcam", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2020-09-11" + }, + "description": "Modern processors offer a wide range of control and measurement features, such as performance\ncounters, power capping, and thermal control. These features are ultimately controlled through Model\nSpecific Registers (MSRs), which require elevated privileges for access. While this is often no problem on\nindividual workstations, it is a significant security risk on multi-user systems and large-scale compute\nclusters. The msr-safe kernel module provides controlled user-level access to MSRs through a\nwhitelisting mechanism.\nIs", + "laborHours": 2614.4, + "languages": [], + "name": "msr-safe", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/msr-safe", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.4.0" + }, + { + "contact": { + "email": "parkerpg@ornl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2023-04-13" + }, + "description": "ONCat is used to store information about neutron experiment data at SNS / HFIR. ONCat consists of an API with which various software clients can communicate to gain access to that information, as well as a web site (see landing page) which offers a way for experiment teams and instrument staff to easily view the metadata relating to experiments using just a web browser. The code is currently private and closed-source. Please contact oncat-support@ornl.gov for more information.", + "homepageURL": "https://oncat.ornl.gov", + "laborHours": 0.0, + "languages": [ + "Python", + "TypeScript" + ], + "name": "ONCat (ORNL Neutron Catalog)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://oncat.ornl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://oncat.ornl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2020-05-13" + }, + "description": "As power becomes an important resource to provision for modern HPC systems it becomes crucial to\nobtain deeper insights into application's power and thermal characteristics and to correlate application\ncontext with important system-level measurements. Existing profiling tools to monitor power and thermal\nmeasurements either operate at a granularity that is not fine enough to correlate with application-level\nevents that describe application context or are not equipped to sample application-level events\ntransparently. We introduce LibPowerMon, a lightweight, vendor-neutral user-level profiling framework to\nsimultaneously sample user-specified application events and system-level metrics at up to 1 kHz\nsampling intervals. At the application level, LibPowerMon provides a source-level phase markup interface\nto capture application context. At runtime level, LibPowerMon records MPI and OpenMP events and can\nbe extended to include other runtimes. At the system level, LibPowerMon samples power, thermal and\nrelevant metrics, and provides an extensible interface to system's control capabilities. In this release,\nLibPowerMon supports monitoring and control functionalities on the Intel, IBM Power9 and Nvidia Volta architectures.\n", + "laborHours": 0.0, + "languages": [], + "name": "LibPowerMon: A vendor-neutral system monitoring library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LibPowerMon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "Gecko is a C++ library for solving graph linear arrangement problems. Gecko orders the nodes of a\ngraph, representing data elements, that are connected by edges, representing affinity relations, with the\ngoal of minimizing a chosen functional of edge length. Gecko was primarily designed to minimize the\nproduct of edge lengths but can also be used to reduce bandwidth (maximum edge length) and 1-sum\n(sum of edge lengths), among others. Minimum-edge-product orderings generalize space-filling curve\norderings to geometryless graphs and find applications in data locality optimization, graph partitioning,\nand dimensionality reduction.\n", + "laborHours": 1216.0, + "languages": [], + "name": "gecko", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gecko", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "INQ is an engine for electronic structure calculations. INQ is implemented as a C++ library of components\ndesigned to build a parallel, portable code for electronic structure calculations, including ground state and\nexcited states. INQ is based on density functional theory (DFT). It can calculate ground state properties in\nDFT, and also excited states using time-dependent DFT (TDDFT) in real-time and linear-response. It\nimplements different approximations for the exchange and correlation part: semi-local functionals like\nLDAs, GGAs and metaGGAs, and hybrid functionals that are implemented through the ACE approach for\nfast execution.", + "laborHours": 92644.0, + "languages": [], + "name": "Electronic Structure Engine", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/inq", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-09-01" + }, + "description": "Linear Algebra Kernels and Graph Kernels are foundational technologies for scientific simulations. These foundational kernels need to run on several computer platforms that are popular for scientific simulations. KokkosKernels provides an implementation of different kernels that is portable to different architectures.", + "laborHours": 187370.4, + "languages": [], + "name": "Kokkos Kernels v. 0.9", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/kokkos-kernels", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2022-07-28" + }, + "description": "The most up-to-date location for Spack packages for Kokkos and Kokkos Kernels.", + "laborHours": 0.0, + "languages": [], + "name": "Kokkos Spack", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/kokkos-spack", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "Production-quality reference implementation of mdspan.", + "laborHours": 12068.8, + "languages": [], + "name": "Production-quality mdspan implementation", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/mdspan", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "Kokkos C++ Performance Portability Programming EcoSystem: Profiling and Debugging Tools. 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EzGET (pronounced\neasy-get) is specifically designed to access climate data and climate model output. You can specify how the data should be structured and whether it should undergo a grid transformation before you receive it, even when you know little about the structure of the stored data (i.e., its dimension order, grid, and domain).", + "laborHours": 9484.8, + "languages": [], + "name": "EzGet", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/EzGet", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "This is the repository for legacy lats library code developed at Lawrence Livermore National Laboratory (LLNL). 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Next we are going to provide a high level description of the APIs provided by Vcs.js including session management, data introspection and subsetting and plotting.\n", + "laborHours": 17176.0, + "languages": [], + "name": "vcs.js", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/vcs-js", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "This is the repository for distarray developed at Lawrence Livermore National Laboratory (LLNL). 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It has support for GitHub statuses and uses GitHub wiki for commit test logs.", + "laborHours": 304.0, + "languages": [], + "name": "Continous Improvement testbot (CI-bot)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/ci-bots", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "Metrics aka diagnostics for comparing models with observations or each other.", + "laborHours": 42286.4, + "languages": [], + "name": "uvcmetrics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + 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Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "This project provides a few components that combine together to provide a command-line utility for viewing the difference between two images.", + "laborHours": 106.4, + "languages": [], + "name": "image-compare: A Simple Package for Comparing Images", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/image-compare", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "This is the repository for CDAT/unidata developed at Lawrence Livermore National Laboratory (LLNL). \n", + "laborHours": 2006.4, + "languages": [], + "name": "CDAT/unidata", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/unidata", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "Scripts for visualizing our analytics data.", + "laborHours": 212.8, + "languages": [], + "name": "CDAT/analytics_scripts", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/analytics_scripts", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "Tools to view pre-generated pictures.", + "laborHours": 45.6, + "languages": [], + "name": "staticView", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/staticView", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "Software for Linear Algebra Targeting Exascale (SLATE) will deliver fundamental dense linear algebra capabilities for current and upcoming distributed-memory systems, including GPU-accelerated systems as well as more traditional multi core-only systems.", + "homepageURL": "https://bitbucket.org/icl/slate/src/default", + "laborHours": 52713.6, + "languages": [], + "name": "SLATE", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/icl/slate/src/default/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/icl/slate/src/default", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "The MAGMA (Matrix Algebra on GPU and Multicore Architectures) project aims to develop a dense linear algebra library similar to LAPACK but for heterogeneous/hybrid architectures, starting with current \"Multicore+GPU\" systems.", + "homepageURL": "https://bitbucket.org/icl/magma/src/default", + "laborHours": 303969.6, + "languages": [], + "name": "MAGMA", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/icl/magma/src/default/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/icl/magma/src/default", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "CHAI and RAJA provide an excellent base on which to build portable codes. CARE expands that\nfunctionality, adding new features such as loop fusion capability and a portable interface for many\nnumerical algorithms. It provides all the basics for anyone wanting to write portable code.", + "laborHours": 9956.0, + "languages": [], + "name": "CHAI and RAJA Extensions", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CARE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.10" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "With function preserving projection (FPP), we aim to address high-dimensional data exploration\nchallenges common in many scientific applications. Instead of preserving the global or local geometric\nstructure of a dataset like traditional dimensionality reduction methods (e.g., principal component\nanalysis, t-stochastic neighborhood embedding), the proposed approach finds a linear projection that\nreveal interpretable (yet potentially nonlinear) pattern of the properties of interests defined on a highdimensional\ndomain (e.g., simulation yield defined on the input parameter space).\nThe key insight driving FPP is the fact that while non-linear embeddings are difficult to interpret, humans\nare highly skilled in understanding complex visual patterns. FPP lets users select the complexity of a\npattern they consider interpretable, allows to find a joint projection that explains multiple functions, and\nprovides a confidence statistic (akin to a p-value) indicating how salient the resulting pattern is. We\ndemonstrate the efficacy of the proposed method on several synthetic and scientific datasets for both\ncontinuous (regression) and discrete (classification) problems of interests and illustrate the scalability of\nFPP by finding an optimal projection for close to 40 gigabytes in around 10 minutes.\n", + "laborHours": 182.4, + "languages": [], + "name": "Function Preserving Projection", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/fpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "Devil Ray is a ray tracing library for high-order elements", + "laborHours": 38258.4, + "languages": [], + "name": "Devil Ray", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/devil_ray", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "C version of mpibind, an algorithm to map MPI tasks, threads, and GPU kernels to the hardware.", + "laborHours": 4468.8, + "languages": [], + "name": "C version of mpibind", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ac-mpibind", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "Hatchet is a Python-based library to analyze performance data that has a tree hierarchy (calling context\ntrees, call graphs, callpath traces, nested regions' timers, etc.).", + "laborHours": 29062.4, + "languages": [], + "name": "Hatchet", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/hatchet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-06-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A low-level OpenQASM benchmark suite for NISQ evaluation and simulation. Please see our paper for details.\nn this repository you will find a low-level and light-weighted benchmark suite based on IBM OpenQASM language (see spec). It collects commonly seen quantum algorithms and routines from various domains including chemistry, simulation, linear algebra, searching, optimization, arithmetic, machine learning, fault tolerance, cryptography, etc. QASMBench trades-off between generality and usability, covering the number of qubits ranging from 2 to 60K, and the circuit depth from 4 to 12M", + "laborHours": 4666.4, + "languages": [], + "name": "pnnl/QASMBench", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/QASMBench", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-06-05", + "metadataLastUpdated": "2023-04-27" + }, + "description": "(DG)2 is an impact analysis tool for electrical utilities to perform spatio-temporal analysis with solar and battery energy storage systems. The purpose of the tool is to help distribution utilities with identifying impacts and costs associated with locating a MW-scale solar farm and energy storage system at a certain location over other choices. 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AMES existed in a non-version controlled and inconsistent form. PNNL added price-sensitive loads for transactive systems, with various other bug fixes and features.", + "laborHours": 2644.8, + "languages": [], + "name": "ames-market/psst", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ames-market/psst", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-06-10", + "metadataLastUpdated": "2020-06-10" + }, + "description": "RiskCat is designed to calculate probabilistic seismic hazard and risk at specified locations on the Earth's surface. 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The software also allows for embedding sensors for smart structures. The software relates to Battelle patents.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Ultrasonic Welding Bond Characterization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-06-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An easy to use tool for identifying energy saving retrofits for buildings.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "FEDS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "8" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-24", + "metadataLastUpdated": "2020-06-24" + }, + "description": "FRESCOX is a flexible, science-oriented, and general-purpose computer code that models direct\nreactions during the interaction of two atomic nuclei. FRESCOX is a coupled-channels program that can\nhave finite-range transfer interactions among any number of mass partitions, and any number of nuclear\nexcitations in each partition.", + "laborHours": 43532.8, + "languages": [], + "name": "Frescox", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Frescox", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-24", + "metadataLastUpdated": "2020-06-24" + }, + "description": "A flexible package manager that supports multiple versions, configurations, platforms, and compilers.", + "laborHours": 169312.8, + "languages": [], + "name": "Spack", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spack/spack", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-06-26", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Power Distribution Designing for Resilience Application (PowDDeR) is a software application to succinctly capture the capabilities of a power system to respond to disturbances, including natural or human (malicious or errors) caused disturbances. The software provides a measure of resilience for power systems.", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Power Distribution Designing For Resilience Application (powdder)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/PowDDeR", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-06-26", + "metadataLastUpdated": "2023-03-07" + }, + "description": "STOTS (Structured Threat Observation Tool Set) is a collection of tools that allow users in a test environment to create STIX v2 observable objects.", + "laborHours": 1140.0, + "languages": [ + "Python" + ], + "name": "Stots (structured Threat Observation Tool Set)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/STOTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-06-29", + "metadataLastUpdated": "2023-05-31" + }, + "description": "AMR-Wind is a massively parallel, block-structured adaptive-mesh, incompressible flow solver for wind turbine and wind farm simulations. The solver is built on top of the AMReX library. AMReX is developed at LBNL , NREL , and ANL as part of the Block-Structured AMR Co-Design Center in DOE's Exascale Computing Project. AMReX library provides the mesh data structures, mesh adaptivity, as well as the linear solvers used for solving the governing equations. The primary applications for AMR-Wind are: performing large-eddy simulations (LES) of atmospheric boundary layer (ABL) flows, simulating wind farm turbine-wake interactions using actuator disk or actuator line models for turbines, and as a background solver when coupled with a near-body solver with overset methodology to perform blade-resolved simulations of multiple wind turbines within a wind farm.", + "laborHours": 57182.4, + "languages": [ + "CMake", + "C++", + "Python" + ], + "name": "AMR-Wind [SWR-20-85]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exawind/amr-wind", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-07-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "New bit capability for GPUs, bit-tensor-core.", + "laborHours": 4894.4, + "languages": [], + "name": "pnnl/TCBNN", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/TCBNN", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-07-01", + "metadataLastUpdated": "2024-06-05" + }, + "description": "This open-source tool functions for calculating degradation of photovoltaic modules. For example, functions to calculate front and rear relative Humidity, as well as Acceleration Factors. A degradation calculation function is also being developed, considering humidity and spectral irradiances models.", + "laborHours": 3617.6, + "languages": [ + "Python" + ], + "name": "PV Degradation Tools [SWR-20-71]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PVDegradationTools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.3.3" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-07-02", + "metadataLastUpdated": "2024-03-11" + }, + "description": "This simulation-based parameter optimization framework is proposed to tune parameters of different types of communication networks using ns-3 to achieve the optimal network performance. It consists of three main components: an ns-3 packet reporting module; a sampler running simulations with all possible parameter sets for the input parameter variables by using a parallel executor at each generation; and a hybrid optimization algorithm for tuning configurable parameters of hybrid designs and application parameter variables. The proposed hybrid metaheuristic optimization algorithm combines an evolutionary algorithm with a gradient descent function to quickly achieve an approximate globally optimum solution.\n\nThis software is designed to be used in a multi-core processing Linux environment and run over a long duration of time. The execution time varies depending mainly upon the nature of the ns-3 configuration being simulated. This software includes a custom ns-3 QoS measurement application which must be included with the ns-3 source code during installation of the software.", + "laborHours": 1048.8, + "languages": [ + "C++", + "Python", + "C++" + ], + "name": "Parameter Optimization Toolbox for NS-3 network optimization, NS-3 Parameter Optimization Framework [SWR-18-60]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/ParaOptimizationNS3", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ParaOptimizationNS3", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-07-02", + "metadataLastUpdated": "2023-12-18" + }, + "description": "MATBOX is a MATLAB application for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization, result three-dimensional visualization and result correlation, and microstructure meshing. MATBOX was originally developed to analyze electrode microstructures for lithium ion batteries; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphic-User Interface.", + "laborHours": 28059.2, + "languages": [ + "MATLAB" + ], + "name": "MATBOX (Microstructure Analysis Toolbox) [SWR-20-76]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/MATBOX_Microstructure_analysis_toolbox", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MATBOX_Microstructure_analysis_toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "Matbox2021c" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-07-06", + "metadataLastUpdated": "2020-07-06" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. 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It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model ® (2019 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2019" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-07-06", + "metadataLastUpdated": "2020-07-06" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. 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These are not likely to change very often, and the generation process to get the whole batch is not straightforward in all cases, so they've been included here. The clients are updated in src/kbase-clients by replacing the appropriate client file with the updated one from the home project. Before being used they must be prepared and placed into the dist directory under kb/service.", + "laborHours": 24365.6, + "languages": [], + "name": "KBase API clients", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-service-clients-js", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "savaraa@ornl.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-09-08" + }, + "description": "Parameter estimation for complex physical problems often suffers from finding 'solutions' that are not physically realistic. The CheKiPEUQ software provides tools for finding physically realistic parameter estimates.and CheKiPEUQ provide tools for making graphs of the parameter positions within parameter space as well as plots of the final simulation results.\n\nThe primary purpose of the CheKiPEUQ software is to enable more physically realistic parameter estimation from comparing simulations to experiments. Specifically, when prior knowledge is available about the region of parameter space which is physically realistic and when the level of uncertainty from experiment can be estimated. The software is intentionally general and can be used for almost any type of simulation. The software is made in a user friendly manner so that users can simply enter the required data and then run the program, following guidelines provided by the authors along with some trial and error. Examples are provided. Users do not need to understand the methodology that will be namedi in the following sentences. While CheKiPEUQ can be used for conventional parameter estimation and other uses, the primary uses for CheKiPEUQ are: 1) Bayesian Parameter Estimation, 2) Bayesian Model Discrimination, 3) Bayesian Design of Experiments. For more information see the project website, documentation, examples, and related publications.", + "laborHours": 109455.2, + "languages": [ + "Python" + ], + "name": "CheKiPEUQ", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdityaSavara/CheKiPEUQ", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is the repository for \"kbase-ui-plugin-dataview\" developed by KBase. ", + "laborHours": 49719.2, + "languages": [], + "name": "kbase-ui-plugin-dataview", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-dataview", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This repo contains a data search plugin for the KBase UI.", + "laborHours": 13892.8, + "languages": [], + "name": "KBase UI Plugin - Data Search", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-data-search", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "A kbase ui plugin for searching JGI JAMO data and copying it to a user's KBase staging area.", + "laborHours": 12296.8, + "languages": [], + "name": "JGI Search Plugin", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-jgi-search", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "A kbase-ui plugin which provides a view of a user's notification feeds.", + "laborHours": 7934.4, + "languages": [], + "name": "KBase UI Feeds Plugin", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-feeds", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This kbase-ui plugin is responsible for displaying a user profile - either the current user's profile if the path is #people or #user, or a given user profile if the path is #people/USERNAME or #user/USERNAME.", + "laborHours": 107737.6, + "languages": [], + "name": "User Profile Plugin", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-user-profile", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This repository contains code for gathering and uploading KBase system metrics from Condor API such as memory, disk and cpu usage, as well as job and queue information. 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Within the queue resources file the 'get_job_info' function is main.", + "laborHours": 334.4, + "languages": [], + "name": "KBase System Metrics", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/SystemMetrics", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-27" + }, + "description": "Compiler optimizations can alter significantly the numerical results of scientific computing applications.\nWhen numerical results differ significantly between compilers, optimization levels, and floating-point\nhardware, these numerical inconsistencies can impact programming productivity. pLiner is a framework\nthat helps programmers identify locations in the source code that are highly affected by compiler\noptimizations. pLiner uses a novel approach to identify such code locations by enhancing the floatingpoint\nprecision of variables and expressions. Using a guided search to locate the most significant code\nregions, pLiner can report to users such locations at different granularities, file, function, and line of code.", + "laborHours": 18194.4, + "languages": [], + "name": "pLiner", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pLiner", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-27" + }, + "description": "mpibind is a memory-driven algorithm to map parallel hybrid applications to the underlying hardware\nresources transparently, efficiently, and portably. There are two fundamental aspects of this algorithm.\nFirst, unlike existing mappings, its primary design point is the memory system. Compute elements are\nselected based on the identified memory components and not vice versa. Second, it embodies a global\nawareness of hybrid programming abstractions as well as heterogeneous devices.", + "laborHours": 23590.4, + "languages": [], + "name": "A memory-driven mapping algorithm for heterogeneous systems", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mpibind", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-27" + }, + "description": "ZFP is a floating-point compression format gaining traction in high-performance computing applications. A\nsoftware implementation has demonstrated the ability to reduce data movement across communication\nchannels and to reduce the footprint of floating-point arrays in memory. Nevertheless, any benefit in\nperformance is limited to the spare compute cycles available before reaching bandwidth limitations. A\nhardware implementation of ZFP has the potential to substantially improve HPC application performance.\nHardware compression speedup over software alone on a single CPU core ranges from 15x for 1-D\narrays to over 200x for 3-D arrays.\nThe implementation of ZFP is sourced in SystemC to facilitate its evaluation in various architectures. The\nencode pipeline consists of several modules. Uncompressed blocks of floating-point numbers in IEEE\nformat flow into the pipeline in a stream and a compressed bitstream flows out from the pipeline. The\ndecode pipeline is the inverse of the encode pipeline. A modular design enables formats other than IEEE\n(such as posits) to be considered with minor adaptations. Best performance will be realized from the\nhardware ZFP unit when batches of blocks are processed at a time. The implementation supports 1-D, 2-\nD and 3-D blocks of floating-point numbers.\nThe hardware implementation of ZFP has been validated with the software implementation of ZFP. C++\ntemplate parameters are used to specify the bit width of floating-point numbers and the array dimension\nof the encoder. A test bench program has been created with several test cases, some with continuous\ndata that is ideal for ZFP, and others with extreme cases containing numbers near or at the maximum or\nminimum values supported by the number format.", + "laborHours": 2766.4, + "languages": [], + "name": "ZFP Hardware Implementation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/zhw.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.5" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-30" + }, + "description": "This Python package is developed for converting GROMACS files to ddcMD inputs. The code makes it\neasier for ddcMD users to convert GROMACS MD simulations into ddcMD. It is used in the MuMMI\nframework for multiscale MD simulations.", + "laborHours": 7812.8, + "languages": [], + "name": "ddcMD converter", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ddcMDconverter", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.3" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-27" + }, + "description": "ddcMD is a general purpose molecular dynamics (MD) code that supports MPI parallelism. MD codes are\nused for simulation of particles systems and capture all the many-body effects of the underlying particle\npotential that defines the physical system. Though MD can be used to model systems from the\nsubatomic to astrological length scales ddcMD is mainly focused on the atomic scale length scale, In\nthis release of ddcMD the support will be mainly for systems using the coarse-grain Martini potential, a\nparticle potential for biological systems.", + "laborHours": 38197.6, + "languages": [], + "name": "ddcMD.os", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ddcMD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-28", + "metadataLastUpdated": "2020-07-28" + }, + "description": "Logic in Memory Emulator (LiME) is a hardware/software tool specially designed for memory system evaluation and experiment. Emerging memories display a wide range of bandwidths, latencies, and capacities, making it challenging for the computer architect to navigate the design space of potential memory configurations, and for the application developer to assess performance implications of using such memories. With the LiME framework, architectural ideas can be prototyped in great detail yet with sufficient performance to support realistic evaluation on long running applications. LiME consists of two fundamental components: 1) the hardware and OS infrastructure for the emulator, and 2) a suite of benchmark applications to assist in characterizing the performance of current and future computer architectures. Some of the applications have been collected from other open source projects.\nUses:\nLogging, replay and analysis of an application's memory behavior Evaluate impact of emerging memory technology on application performance. Emulate complex memory interactions in whole applications orders of magnitude faster than software\nsimulation. Emulate acceleration hardware co-located with the memory subsystem.\nFeatures:\nCapture and log external memory accesses to a separate off-chip memory device without affecting application execution.\nMemory traces include the address, length, timestamp, and optionally the data for each transaction. Captured trace data can be saved to an SD card for off-line analysis.\nConfigure a wide range of memory latencies in sub-nanosecond increments that encompass highbandwidth and storage class memories.\nSpecify regions of interest (ROI) in applications to reduce the amount of trace data captured for analysis. Currently supports execution on Xilinx Zynq SoC which integrates an ARM processor with FPGA logic on a single device.\nApplications can be run under Linux or in bare metal mode on the ARM cores.", + "laborHours": 32041.6, + "languages": [], + "name": "Logic in Memory Emulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lime.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.2" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is a plugin for kbase-ui, which allows a KBase user to browse, view, and manage Organizations.", + "laborHours": 27785.6, + "languages": [], + "name": "KBase UI Plugin: Organizations", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-organizations", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "The job runner is started by the batch/resource manager system and is the component that actually executes the SDK module. It also provides the callback handler and pushes logs to the execution engine logging system.", + "laborHours": 2036.8, + "languages": [], + "name": "JobRunner", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/JobRunner", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "A port of some of the commonly used modules, at least those that are dependencies of the new auth2 APIs, from the KBase Common JS collection.", + "laborHours": 5912.8, + "languages": [], + "name": "KBase Common Typescript", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-common-ts", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "In this project, we create unit test modules in-situ with the module they are providing tests for which makes for self-documenting tests. ", + "laborHours": 2948.8, + "languages": [], + "name": "KBase UI ES6 Library", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-common-es6", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is an API for taxonomy data (updated from taxon_api) that queries the relation engine. 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These imports are performed on a periodic basis as new features developed on the SEED side are required in the KBase codebase. This deploys both client and service libraries.", + "laborHours": 276077.6, + "languages": [], + "name": "kb_seed", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kb_seed", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "A kbase-ui plugin to allow a KBase user to view their Narrative jobs; and for job admins to manage all jobs. This plugin provides a single top level component designed to serve both regular users and administrators. It's primary purpose is to allow the user to view their current and past jobs. Administrative users can use it to inspect jobs for all users.", + "laborHours": 8056.0, + "languages": [], + "name": "kbase-ui-plugin-job-browser2", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-job-browser2", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "Narrative method specs repo for use in the -ci (or other nonproduction) environments.", + "laborHours": 592.8, + "languages": [], + "name": "narrative_method_specs_ci ", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/narrative_method_specs_ci", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is the repository for \"NarrativeViewers\" developed by KBase. 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This repository is configured to use TravisCI.", + "laborHours": 157867.2, + "languages": [], + "name": "kbase/data_api", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/data_api", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-25", + "metadataLastUpdated": "2020-08-25" + }, + "description": "A service that provides import, upload, and download capabilities as well as tools for validating and converting between data types, both internal and external to KBase.", + "laborHours": 16492.0, + "languages": [], + "name": "KBase Transform v0.1", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/transform", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-25", + "metadataLastUpdated": "2020-08-25" + }, + "description": "Codes for aggregating public reference data from remote sources.", + "laborHours": 395.2, + "languages": [], + "name": "reference_data", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/reference_data", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2020-08-25", + "metadataLastUpdated": "2020-08-25" + }, + "description": "First release of E3SM v1.1\n\nThis release includes scientifically-validated tunings of the E3SM Land Model (ELM) and E3SM Atmosphere Model (EAM) for coupled simulations with active land, ocean, and sea ice biogeochemistry, for ELM configurations using the CTC approach to representing nutrient competition.\n\nAdditional diagnostic variables have been made available as history variables from the ELM,\nand from the MPAS-Ocean and MPAS-Seaice biogeochemistry modules, in order to improve consistency with the output variable requests of the Coupled Climate Carbon Cycle Model Intercomparison\nProject (C4MIP), and to support improved analysis of the land, ocean, and sea ice carbon cycles.\n\nThe atmosphere models prognostic CO2 code has been updated to enable regridding of anthropogenic\nCO2 emission files to the E3SMs native spectral element grid. Note that (1) the prognostic CO2\nconfiguration of E3SM has not been scientifically validated, and (2) the regridding of emission\nfiles as currently implemented is not mass-conserving and is intended as a temporary workaround.\nWe do not advise using E3SMv1.1 for fully-coupled carbon cycle simulations where mass conservation\nis critical, but it is suitable for enabling use of the 3D CO2 tracer for diagnostic and testing purposes.\n\nSeveral bugs found after v1.0 have been fixed in this tag and changes made to default settings, including:\n EAM: adding limiters to avoid bad extrapolation in RRTMG, fixing an error in the calculation of NIR\n reflectance that affects cloud fields derived from MODIS simulator.\n ELM: fixing surface water and lakes, increasing the land field name size, fixing a memory leak in\n ELM CNStateType, fixing a snow compaction bug that was resulting in sporadic unphysical snow depths,\n adding a water budget in the land model (and fixing a water conservation error)\n MPAS-O: preventing thermo energy conservation errors by lowering the permitted surface flux error\n in the mushy layer picard iteration to 0.9*ferrmax, fixing a small bug in marine BGC,\n MPAS-SeaIce: Turning off mpas-seaice history files by default\n MOSART: Replacing the low-res (half-degree) MOSART file\n\nIn addition, the budget output has been turned on by default for any fully coupled case, and CIME was\nmodified to remove a bad term from E3SM water budgets. The CCSM_CO2_PPMV is now set correctly in BGC cases. A bugfix for the IEFLX output is included and the timestep for the EC60to30 mesh has been\nupdated. Finally, a number of minor bugfixes and technical improvements have been introduced in the\nEAM, ELM and MPAS-Ocean models.\n\nMachine updates for cascade, edison, eos, cori are included.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v1.1", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v1.1.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v1.1.0" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2020-08-25", + "metadataLastUpdated": "2020-08-25" + }, + "description": "Second release of E3SM v1.1\n\nThis update to v1.1.0 includes additional output variables and small changes to the\nECA configurations. 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It is developed to simulate microstructural evolution in materials during irradiation. KSOME is developed from ground up with priority given to the flexibility, ease of upgradability, and computation efficiency, in that order. With previously developed simulation codes, various processes (more precisely, the diffusion-reaction processes) that can occur in a system were hardwired into the code. Hence, to perform higher fidelity simulations, a significant coding effort was required every time to incorporate either a more accurate description of existing processes or new processes. With KSOME, the necessity for frequent code upgrades whenever there is a need to perform higher fidelity simulations is either eliminated or reduced significantly. In KSOME, the categories of various diffusion-reaction processes and the data-management system are hardwired, while the execution of the diffusion-reaction processes specific to a system is specified via input files. In the present version of KSOME, the analytical expression required to calculate defect interaction radii are inputted via a text file. However, the ability to parse mathematical expressions from a text file can be extended to input the analytical expression to calculate other defect properties; including the expressions to calculate the change in the migration barriers of mobile defects due to long-range interaction with extended defects ", + "laborHours": 8968.0, + "languages": [ + "C++" + ], + "name": "Kinetic Simulations of Microstructural Evolution (KSOME)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/giridharnandipati/ksome", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2024-03-11" + }, + "description": "Realistic data-driven renewable energy scenarios for stochastic grid operation problems", + "laborHours": 39200.8, + "languages": [ + "MATLAB", + "Python", + "Jupyter Notebook", + "Tex" + ], + "name": "powerscenarios [SWR-20-50]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/powerscenarios", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "The JavaScript Data API is, like the Python API, custom wrapper code on top of the JavaScript library generated by Thrift. The source code for these wrappers is in src/js/.", + "laborHours": 769028.8, + "languages": [], + "name": "JavaScript API Wrappers for the Data API", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-data-api-client-js", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "This repo contains the various client libraries generated from the Data API Thrift specifications. Upon changes to the Data API Thrift specs, new client libraries are generated and copied into this repo. A new semver tag is generated, and the repo is merged into the canonical repo (KBase). This workflow ensures that downstream projects can pick up the correct or latest library version.", + "laborHours": 108923.2, + "languages": [], + "name": "KBase Data Thrift Clients", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-data-thrift-clients", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "This is the repository for \"kbase/narrative_job_service\" developed by KBase.", + "laborHours": 866.4, + "languages": [], + "name": "kbase/narrative_job_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/narrative_job_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "Callable service that provides access to a homolog database that covers prokaryotes, eukaryotes and metagenomes. It can be used for navigation between sequences as well as for computation on protein families defined on the homologs.", + "laborHours": 1064.0, + "languages": [], + "name": "homology_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/homology_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "The purpose of the Probabilistic Annotation service is to provide users with alternative annotations for genes, each attached to a likelihood score, and to translate these likelihood scores into likelihood scores for the existence of reactions in metabolic models.", + "laborHours": 3009.6, + "languages": [], + "name": "Probabilistic Annotation", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/probabilistic_annotation", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "This provides an emulation of the Globus Nexus API that can be used to support authentication back ends other than Globus Nexus.", + "laborHours": 334.4, + "languages": [], + "name": "nexus_emulation", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/nexus_emulation", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "An implementation of binary transports and protocols for JavaScript Thrift library, as well as some modifications to generated Thrift code to create a better modern JavaScript API using the bluebird Promises library.", + "laborHours": 2021.6, + "languages": [], + "name": "Javascript clients for Apache Thrift", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-data-thrift-js", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "The Gene Families service finds domains (from public protein domain libraries such as COGs and Pfam) in proteins in a user-supplied genome.", + "laborHours": 4301.6, + "languages": [], + "name": "gene_families", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/gene_families", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "The mgrast_pipeline repository provides KBase release engineering tools for the deployment of the MG-RAST pipeline. The MG-RAST pipeline repository is included as a submodule in the mgrast_pipeline repository and is maintained at http://github.com/MG-RAST/pipeline.", + "laborHours": 15.2, + "languages": [], + "name": "mgrast_pipeline", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/mgrast_pipeline", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "This repository was created for the purpose of bundling the communities API code. ", + "laborHours": 3480.8, + "languages": [], + "name": "communities_api", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/communities_api", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "This is the repository for \"communities_qc\" developed by KBase.", + "laborHours": 3024.8, + "languages": [], + "name": "communities_qc", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/communities_qc", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "The main functionality of ontology service is to allow the retrieval of ontology term distribution for a given a set of genes and additionally, identifies statistically overrepresented GO terms within given gene sets. 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The distance has a value with a minimum of 0 meaning the communities are the same and a maximum of 1 meaning the communities are completely different.", + "laborHours": 729.6, + "languages": [], + "name": "Compression-Based Distance", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/cbd", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"Central Store Quality Control\" developed by KBase. 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The Inferelator algorithm infers regulatory networks from gene expression data, and takes as input cMonkey biclusters, a list of regulators, and expression data.", + "laborHours": 13148.0, + "languages": [], + "name": "Module Inferelator Version 1.0", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/inferelator", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This service wraps the ERDB software and allows querying the CDS via the ERDB using typecompiler generated clients rather than direct Perl imports of the ERDB code.", + "laborHours": 136.8, + "languages": [], + "name": "EDRB Service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/erdb_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "A module for sequence similarity service.", + "laborHours": 197.6, + "languages": [], + "name": "sim_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/sim_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "KBase service code for RDP. A classifier of rRNA amplicon data contributed by the RDB Project. Deploys both client and service.", + "laborHours": 608.0, + "languages": [], + "name": "RDPTools Services", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/rdptools", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "The KBase Data Importer allows users to upload data for use in KBase.", + "laborHours": 6064.8, + "languages": [], + "name": "KBase DataImporter v1.0", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/uploader", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This service has methods for finding Protein Structure Databank (PDB) entries with sequences similar to a KBase protein sequence, specified by either a MD5 id or a feature or coding sequence id. There are two functions, one for searching by MD5, and the other searching by feature ID (FID). ", + "laborHours": 1140.0, + "languages": [], + "name": "protein_structure_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/protein_structure_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "Simple wrappers around fba tools.", + "laborHours": 258.4, + "languages": [], + "name": "simple_fba", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/simple_fba", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "The code found in this repository contains the client and server code for the jnomics-manager. 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In this case we have used medical reports and medical coder's structured labels as our training data. 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The DPCL API is machine independent; hence DPCL-based tools built on one platform will work on another platform", + "homepageURL": "https://sourceforge.net/projects/dpcl/files", + "laborHours": 83296.0, + "languages": [ + "C, C++" + ], + "name": "MRNet-based Dynamic Probe Class Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/IPL-1.0", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/dpcl/files", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-09-22", + "metadataLastUpdated": "2022-08-31" + }, + "description": "The software is Python-based code that takes monomers, represented as SMILES, and \"reacts\" them together to form long polymer chains, represented as SMILES, based on known polymer chemistries. 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The user is able to specify different monomer pairings and degree of polymerization for different polymer chains.", + "laborHours": 1216.0, + "languages": [ + "Python", + "Python" + ], + "name": "m2p (Monomers to Polymers)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/m2p", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-09-24", + "metadataLastUpdated": "2020-09-24" + }, + "description": "This python toolkit has been developed to automate 3D segmentation of X-ray Computed Tomography (CT) data using convolutional neural networks - an AI methodology. 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The 2D architecture offers\nlower GPU memory requirement while maintaining accuracy, which has been characterized on high-resolution CT scans\nof fuel injector nozzles. 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It can also be used to develop new Monte Carlo models that hook to the existing solver and parallel infrastructure provided by the code.", + "laborHours": 165102.4, + "languages": [ + "C++", + "C" + ], + "name": "Stochastic Parallel PARticle Kinetic Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spparks", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-09-25", + "metadataLastUpdated": "2025-02-10" + }, + "description": "This software provides a collection of algorithms, an API, and a functional Web UI for the Distributed Wind’s WindWatts project. 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The computational framework and the back-end API are powering the easy to use front-end services available at: https://windwatts.nrel.gov.\n\nhttps://github.com/NREL/dw-tap-api; https://github.com/NREL/dw-tap; https://github.com/NREL/windwatts-data\n\nFor reference, this software was previously known as DW TAP Computational Framework.", + "laborHours": 9895.2, + "languages": [ + "JavaScript", + "Python" + ], + "name": "WindWatts Computational Framework and Web UI [SWR-20-100]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dw-tap-api", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-25", + "metadataLastUpdated": "2020-09-25" + }, + "description": "ATS is a Python-language program for automating test suites for software programs that do not interact with thier users, such as scripted scientific simulations. ATS features a decentralized approach especially suited to larger projects. In its multinode mode it can utilize many nodes of a cluster in order to do many test in parallel. It has features for submitting longer-running tests to a batch system and would have to be customized for use elsewhere.", + "homepageURL": "https://sourceforge.net/projects/ats-automatedtestingsystem", + "laborHours": 4544.8, + "languages": [ + "None" + ], + "name": "Automated Testing System", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/ats-automatedtestingsystem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "gord.stephen@nrel.gov" + }, + "date": { + "created": "2020-09-28", + "metadataLastUpdated": "2023-04-24" + }, + "description": "The Electricity Markets Investment Suite - Competitive Equilibrium (EMIS-CE) model is an optimization-based power system investment model developed at NREL. It attempts to approximate a market-driven investment equilibrium outcome under the assumption of idealized or perfect competition (e.g. no participants are able to exert market power or leverage exclusive cost advantages) and uncertain future conditions.", + "laborHours": 1079.2, + "languages": [ + "Julia" + ], + "name": "EMIS-CompetitiveEquilibrium.jl [SWR-19-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMIS-CompetitiveEquilibrium.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The construction of megaprojects has consistently demonstrated challenges for project managers in regard to meeting cost, schedule, and performance requirements. Megaproject construction challenges are common place within megaprojects with many active projects in the United States failing to meet cost and schedule efforts by significant margins. Currently, engineering teams operate in siloed tools and disparate teams where connections across design, procurement, and construction systems are translated manually or over brittle point-to-point integrations. The manual nature of data exchange increases the risk of silent errors in the reactor design, with each silent error cascading across the design. These cascading errors lead to uncontrollable risk during construction, resulting in significant delays and cost overruns. Deep Lynx allows for an integrated platform during design and operations of mega projects.", + "laborHours": 119244.0, + "languages": [ + "JavaScript" + ], + "name": "Deep Lynx: Digital Engineering Integration Hub", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2024-06-04" + }, + "description": "HERON is a modeling toolset and plugin for RAVEN to accelerate stochastic technoeconomic assessment of the economic viability of various grid-energy system configurations, especially with application to electrical grids and integrated energy systems (IES). The frameworks enabling this toolset are INL's RAVEN and its TEAL plugin. The toolset includes automated RAVEN workflow generation tools for performing stochastic analysis and optimization driven by technoeconomic factors. The workflows generated employ RAVEN for parametric or optimizing study of grid component characteristics, and again for stochastic sampling of regulated and deregulated markets, load, and weather histories. The toolset further provides methods for economically-optimal dispatch of system components given the stochastic samples of market, load, and weather histories. The toolset allows assembling of existing and new models through the RAVEN interface to the Modelica process modeling language.", + "laborHours": 14272.8, + "languages": [ + "Python" + ], + "name": "HERON", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HERON", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-13" + }, + "description": "TEAL is a financial performance calculator plugin for the RAVEN code, framework, resolving around the computation of Net Present Value and associated financial metrics. TEAL can make use of inflation rates, taxation, escalation factors, capital expenditure economy of scale scaling factors. The unique feature of TEAL is the capability to be linked with RAVEN external models and build corresponding cash flows using the variables computed by those external models. In addition to be able to use the capability to generate cash flows derived from complex physical models generated by RAVEN, another distinctive feature of TEAL is the capability to provide financial risk/probabilistic metrics that can empower RAVEN to perform optimization/analysis driven by financial risk augmentations. Optimization, robust optimization, parametric studies, large parallel simulations, sensitivity analysis, data mining, etc. are just some of the capabilities that can be leveraged.", + "laborHours": 4788.0, + "languages": [ + "Python" + ], + "name": "TEAL", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/TEAL", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Field Landscape Decision Support (FieLDS) is a decision support tool that assists agricultural producers and farm managers in selecting parts of the field that can be converted to bioenergy plants, like perennial grasses, from the conventional use, like corn or soybean growth. That conversion of parts of the field is done based on the specific landscape properties and the agricultural producer’s priorities. The decision support tool generates a map of the field layout and spatially marks where to place each plant based on the spatial input from the user. Also, the user selects which priorities (sustainability indicators) are most relevant to them in their decision-making. By allowing the user to set the weights among the priorities, the tool empowers the user to generate field designs specific to their needs instead of imposing the developer’s set of priorities, and increases the transparency of the decision process.", + "laborHours": 152.0, + "languages": [ + "Python" + ], + "name": "FieLDS", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/FieLDS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-13" + }, + "description": "WiiBin is a framework to determine architecture of an unknown binary and locate opcode sections within the same binary via supervised machine learning.", + "laborHours": 486.4, + "languages": [ + "Python" + ], + "name": "WiiBin", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/WiiBin", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-13" + }, + "description": "Structured Threat Automated Response (STAR) is a script that creates a python run-time for automated response action included in the Structure Threat Information Expression (STIX) Course of Action object. This script can parse a valid STIX json file and execute the included Course of Action.", + "laborHours": 76.0, + "languages": [ + "Python" + ], + "name": "STAR", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/STAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "yunl68@illinois.edu" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2020-09-29" + }, + "description": "BioCro is a model that predicts plant growth over time given crop-specific parameters and environmental data as input.\n\nIt uses models of key physiological and biophysical processes underlying plant growth (Humphries and Long, 1995), and has previously been used for predicting biomass yield and leaf area index of switchgrass, miscanthus, sugarcane and willow (Miguez et al., 2009; Jaiswal et al. 2017).\n\nThe latest version has been redesigned to closely represent a dynamical system, which makes it easier to implement new crops and provides more accurate simulations. Parameters to model energy sorghum have also been added.", + "laborHours": 10913.6, + "languages": [], + "name": "BioCro", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ebimodeling/biocro/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ebimodeling/biocro", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-11-05" + }, + "description": "JEGA is a software package that implements a multi-objective genetic algorithm (MOGA) for solution to multi-objective optimization problems (MOPS) and a single objective genetic algorithm (SOGA) for solution to single objective optimization problems (SOPS). JEGA is highly configurable and provides a rich set of algorithmic components for tailored optimization. It has been used successfully on many problems by users both internal and external to Sandia. By employing object-oriented design to implement abstractions of the key components making up the algorithms, JEGA provides a flexible and extensible problem-solving environment for design and performance analysis of computational models.", + "homepageURL": "https://dakota.sandia.gov", + "laborHours": 3988282.4, + "languages": [ + "C++ compiler" + ], + "name": "JEGA V 2.3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://dakota.sandia.gov/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-10-08" + }, + "description": "Silo is a library for reading and writing a wide variety of scientific data to binary, disk files. The files Silo produces and the data within them can be easily shared and exchanged between wholly independently developed applications running on disparate computing platforms. Consequently, Silo facilitates the development of general purpose tools for processing scientific data. One of the more popular tools that process Silo data files is the VisIt visualization tool.", + "homepageURL": "https://wci.llnl.gov/simulation/computer-codes/silo", + "laborHours": 110929.6, + "languages": [], + "name": "Silo", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://wci.llnl.gov/simulation/computer-codes/silo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-09-30" + }, + "description": "LULESH v1.0 is a 3D unstructured Lagrange hydrodynamics simulation written specifically to solve a standard analytical test problem, known as the Sedov problem. In this problem, a quantum of energy is deposited into a gas and propagates through the gas over time.", + "laborHours": 2933.6, + "languages": [ + "None" + ], + "name": "Livermore Unstructured Lagrange Explicit Shock Hydrodynamics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/lulesh", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-10-08" + }, + "description": "BRAID is a rewriting system for translating abstract intermediate descriptions into light-weight, \"pay only for what you need\" middleware wrappers. Initial capabilities will focus on language interoperability, remote method invocation (RMI), and interface contract enforcement wrappers from Scientific Interface Definition Language (SIDL) specifications. Language interoperability will be provided for software written in C, C++, Fortran, Java, and Python, as was done with Babel, but also a subset of PGAS/HPCS languages, such as Chapel, UPC, and X10. Interface contract enforcement wrappers will initially be supported in a subset of those languages.", + "homepageURL": "https://sourceforge.net/projects/compose-hpc", + "laborHours": 154523.2, + "languages": [], + "name": "BRAID", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/compose-hpc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-09-30" + }, + "description": "Establishes the input/output dependencies between individual application tasks, schedules and executes them on available computing resources in order of their dependencies. Uses statistical modeling algorithms to summarize the properties of the tasks to present to users a compact view of the surrent state of the overall application tasks and the effectiveness of various runtime optimizations on such tasks to improve utility of scheduling. Finally, uses statistical models to predict availability of computing resources", + "homepageURL": "https://sourceforge.net/projects/sched-minions", + "laborHours": 76121.6, + "languages": [ + "None" + ], + "name": "Minions Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/sched-minions", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-10-08" + }, + "description": "LRIOT is a test bench framework that is designed to generate sophisticated I/O rates that can stress high-performance memory and storage systems, such as non-volatile random access memories (NVRAM)and storage class memory. Furthermore, LRIOT provides the capabilities to mix multiple types of concurrency, namely threading and task parallelism, as well as distributed execution using Message Passing Interface (MPI) libraries. It will be used by algorithm designers to generate access patterns that mimic their application's behavior, and by system designers to test high-performance NVRAM storage.", + "laborHours": 760.0, + "languages": [ + "None" + ], + "name": "Livermore Random I/O Testbench", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/vanessen/lriot/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-09-30" + }, + "description": "Assessing primer specificity and predicting both desired and off-target amplification products is an essential step for robust PCR assay design. Code is described to predict potential polymerase chain reaction (PCR) amplicons in a large sequence database such as NCBI nt from either singleplex or a large multiplexed set of primers, allowing degenerate primer and probe bases, with target mismatch annotates amplicons with gene information automatically downloaded from NCBI, and optionally it can predict whether there are also TaqMan/Luminex probe matches within predicted amplicons.", + "homepageURL": "https://sourceforge.net/projects/simulatepcr", + "laborHours": 243.2, + "languages": [ + "PERL" + ], + "name": "PCR Amplicon Prediction from Multiplex Degenerate Primer and Probe Sets", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/simulatepcr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-10-08" + }, + "description": "ARKode is part of a software family called SUNDIALS: SUite of Nonlinear and Differential/ALgebraic equation Solvers [1]. The ARKode solver library provides an adaptive-step time integration package for stiff, nonstiff and multi-rate systems of ordinary differential equations (ODEs) using Runge Kutta methods [2].", + "homepageURL": "https://computation.llnl.gov/projects/sundials", + "laborHours": 103025.6, + "languages": [], + "name": "ARKode, v1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://computation.llnl.gov/projects/sundials", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-01-22" + }, + "description": "Spawn is a next generation building simulation engine designed to build on the strengths of NREL's venerable EnergyPlus engine, and add new advanced HVAC and controls modeling capability by incorporating the Modelica equation based modeling language. In effect, Spawn is a hybrid of the existing EnergyPlus and Modelica software products, with some new software to provide glue between the components in order to provide a seamless end user experience.", + "laborHours": 0.0, + "languages": [ + "C++", + "C" + ], + "name": "Spawn [SWR-SWR-20-10]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Spawn", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2023-05-16" + }, + "description": "The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.", + "laborHours": 0.0, + "languages": [ + "GAMS", + "Batchfile", + "MATLAB", + "Python", + "Python" + ], + "name": "RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/RODeO", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This Drupal Module extend the functionality of Drupal by modifying the output of dates to comply to the format of AP Style guide.", + "homepageURL": "https://www.drupal.org/project/date_ap_style", + "laborHours": 380.0, + "languages": [ + "PHP (99%)", + "JavaScript (1%)" + ], + "name": "Drupal Contributed Modules Date AP Style", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.drupal.org/project/date_ap_style", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "FRENSIE (the Framework for Research in Nuclear Science and Engineering) is a Monte Carlo code for solving linear particle transport problems with neutron, photon, and electron particles.", + "laborHours": 228927.2, + "languages": [ + "C++" + ], + "name": "Framework for Research in Nuclear Science and Engineering v. 0.3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lkersting/SCR-2123", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Phoenix is a Java Virtual Machine (JVM) based library for performing mathematical and astrodynamics calculations. It consists of two primary sub-modules, phoenix-math and phoenix-astrodynamics. The mathematics package has a variety of mathematical classes for performing 3D transformations, geometric reasoning, and numerical analysis. The astrodynamics package has various classes and methods for computing locations, attitudes, accesses, and other values useful for general satellite modeling and simulation. Methods for computing celestial locations, such as the location of the Sun and Moon, are also included. Phoenix is meant to be used as a library within the context of a larger application. For example, it could be used for a web service, desktop client, or to compute simple values in a scripting environment.", + "laborHours": 7721.6, + "languages": [ + "Scala/scalac/2.11" + ], + "name": "Phoenix v. 1.0-SNAPSHOT", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/phoenix/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/phoenix", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-26" + }, + "description": "SMASH is a collection of MATLAB programs, packages, and class definitions for analyzing experimental data.", + "laborHours": 330980.0, + "languages": [ + "MATLAB", + "HTML" + ], + "name": "Sandia Matlab AnalysiS Hierarchy toolbox v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SMASHtoolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The Sandia hyperspectral upper-bound spectrum algorithm (hyper-UBS) is a cosmic ray despiking algorithm for hyperspectral data sets. When naturally-occurring, high-energy (gigaelectronvolt) cosmic rays impact the earth’s atmosphere, they create an avalanche of secondary particles which will register as a large, positive spike on any spectroscopic detector they hit. Cosmic ray spikes are therefore an unavoidable spectroscopic contaminant which can interfere with subsequent analysis. A variety of cosmic ray despiking algorithms already exist and can potentially be applied to hyperspectral data matrices, most notably the upper-bound spectrum data matrices (UBS-DM) algorithm by Dongmao Zhang and Dor Ben-Amotz which served as the basis for the hyper-UBS algorithm. However, the existing algorithms either cannot be applied to hyperspectral data, require information that is not always available, introduce undesired spectral bias, or have otherwise limited effectiveness for some experimentally relevant conditions. Hyper-UBS is more effective at removing a wider variety of cosmic ray spikes from hyperspectral data without introducing undesired spectral bias. In addition to the core algorithm the Sandia hyper-UBS software package includes additional source code useful in evaluating the effectiveness of the hyper-UBS algorithm. The accompanying source code includes code to generate simulated hyperspectral data contaminated by cosmic ray spikes, several existing despiking algorithms, and code to evaluate the performance of the despiking algorithms on simulated data.", + "laborHours": 0.0, + "languages": [ + "Mathworks Matlab R2015b" + ], + "name": "Sandia Hyperspectral Upper-Bound Spectrum Version 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Hyper-UBS", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "As parallel computing trends towards the exascale, scientific data produced by high-fidelity simulations are growing increasingly massive. For instance, a simulation on a three-dimensional spatial grid with 512 points per dimension that tracks 64 variables per grid point for 128 time steps yields 8 TB of data. By viewing the data as a dense five-way tensor, we can compute a Tucker decomposition to find inherent low-dimensional multilinear structure, achieving compression ratios of up to 10000 on real-world data sets with negligible loss in accuracy. So that we can operate on such massive data, we present the first-ever distributed-memory parallel implementation for the Tucker decomposition, whose key computations correspond to parallel linear algebra operations, albeit with nonstandard data layouts. Our approach specifies a data distribution for tensors that avoids any tensor data redistribution, either locally or in parallel. This software provides a method for compressing large-scale multiway data.", + "laborHours": 19364.8, + "languages": [ + "C++", + "Shell", + "CMake", + "MATLAB", + "Makefile", + "Python" + ], + "name": "TuckerCompressMPI v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TuckerMPI", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Fenix provides APIs to allow the users to add fault tolerance capability to MPI-based parallel programs in a transparent manner. Fenix-enabled programs can run through process failures during program execution using a pool of spare processes accommodated by Fenix.", + "laborHours": 3070.4, + "languages": [ + "CMake", + "C" + ], + "name": "Fenix, A Fault Tolerant Programming Framework for MPI Applications", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/epizon-project/Fenix", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "HyperHeadTail is a streaming algorithm for estimating the degree distribution of a graph from a stream of edges using very small storage space. Our algorithm builds upon the HeadTail algorithm of Simpson, Comandur, and McGregor [14], but extends it to handle repeat edges and variable-length sliding time windows, making it suitable for application to real-world streams such as those generated by network traffic or other communication networks.", + "laborHours": 684.0, + "languages": [ + "C++, Python" + ], + "name": "HyperHeadTail v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/HyperHeadTail?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HyperHeadTail", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This software uses a database of existing biological pathways to determine efficient routes for genetic engineering.", + "laborHours": 1413296.0, + "languages": [ + "Python" + ], + "name": "RetSynth v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/RetSynth", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "PV-RPM is intended to address more “real world” situations by coupling a photovoltaic system performance model with a reliability model so that inverters, modules, combiner boxes, etc. can experience failures and be repaired (or left unrepaired). The model can also include other effects, such as module output degradation over time or disruptions such as electrical grid outages. In addition, PV-RPM is a dynamic probabilistic model that can be used to run many realizations (i.e., possible future outcomes) of a system’s performance using probability distributions to represent uncertain parameter inputs.", + "homepageURL": "https://sam.nrel.gov/photovoltaic/pvrpm.html", + "laborHours": 0.0, + "languages": [ + "For existing proof-of-concept, it was written in Goldsim in an object oriented format. The next vers" + ], + "name": "Photovoltaic Reliability Performance Model v 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sam.nrel.gov/photovoltaic/pvrpm.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sam.nrel.gov/photovoltaic/pvrpm.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Algebra, calculus, manipulation and optimization for small vectors and tensors.", + "laborHours": 8344830.4, + "languages": [], + "name": "MiniTensor v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This software collects sequence reads from Illumina next-generation sequencing to identify the counts of reads that support the mobilization of DNA.", + "laborHours": 1337.6, + "languages": [ + "Perl" + ], + "name": "Juxtaposer v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Juxtaposer", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Exomerge is a lightweight Python interface for manipulating ExodusII files.", + "laborHours": 4377.6, + "languages": [ + "Shell", + "Python" + ], + "name": "Exomerge v. 8.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/exomerge", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "8.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-26" + }, + "description": "PuLP/XtraPulp is software for partitioning graphs from several real-world problems. Graphs occur in several places in real world from road networks, social networks and scientific simulations. For efficient parallel processing these graphs have to be partitioned (split) with respect to metrics such as computation and communication costs. Our software allows such partitioning for massive graphs.", + "laborHours": 11795.2, + "languages": [ + "C++", + "C" + ], + "name": "PuLP/XtraPuLP : Partitioning Tools for Extreme-Scale Graphs", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PuLP", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Graphs occur in several places in real world from road networks, social networks and scientific simulations. Connectivity is a graph analysis software to graph connectivity in modern architectures like multicore CPUs, Xeon Phi and GPUs.", + "laborHours": 2796.8, + "languages": [ + "C++" + ], + "name": "Connectivity: Performance Portable Algorithms for graph connectivity v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Connectivity", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Graphs occur in several places in real world from road networks, social networks and scientific simulations. HPC Graph is a graph analysis software to analyze the properties such as connectivity, communities etc in extreme scale graphs.", + "laborHours": 2295.2, + "languages": [ + "C++", + "Makefile", + "C" + ], + "name": "HPCGraph v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HPCGraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Prove-It is a tool for proving and organizing general theorems using Python.", + "laborHours": 70953.6, + "languages": [ + "Python", + "Smarty", + "CSS", + "HTML", + "Jupyter Notebook", + "TeX" + ], + "name": "Prove-It v. 0.3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Prove-It", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.3" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "LabVIEW Task Manager is a debugging tool for use during code development in the National Instruments (NI) LabVIEW® IDE. While providing a dynamic & big-picture view of running code, an expandable/collapsible tree diagram displays detailed information (both static and dynamic) on all VIs in memory, belonging to a selected project/target. It allows for interacting with single or multiple selected VIs at a time, providing significant benefits while troubleshooting, and has the following features: Look & Feel similar to Windows® Task Manager; Selection of project/target; Lists all VIs in memory, grouped by class/library; Searches for and enumerates clones in memory; DropIn VI for including dynamically referenced clones (Clone Beacon); 'Refresh Now' (F5) re-reads all VIs in memory and adds new ones to the tree; Displays VI name, owning class/library, state, path, data size & code size; Displays VI FP Behavior, Reentrant?, Reentrancy Type, Paused? & Highlight?; Sort by any column, including by library name; Filter by item types vi, ctl, and vit/ctt; Filter out vi.lib and global VIs; Tracking of, and ability to toggle, execution highlighting on multiple selected VIs; Tracking of paused VIs with ability to Pause/Resume/TogglePause multiple selected VIs; DropIn VI for pausing on a condition; If a clone initiates a pause, a different pause symbol is used for all clones of that same reentrant original VI; Select multiple VIs and open or close their FPs or BDs; Double Click a VI from the tree to bring the BD (first choice) or FP to front, if already open; and Select multiple top-level VIs and Abort them.", + "laborHours": 1596.0, + "languages": [ + "National Instruments (NI) LabVIEW®, versions 2010 through 2016", + "LABVIEW", + "HTML" + ], + "name": "LabVIEW Task Manager v. 1.10.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/lavag/labview-task-manager/src/master/Documentation/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/LVTM", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.10" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Communities of uncultivated microbes are critical to ecosystem function and microorganism health, and a key objective of metagenomic studies is to analyze organism-specific metabolic pathways and reconstruct community interaction networks. This requires accurate assignment of genes to genomes, yet existing binning methods often fail to predict a reasonable number of genomes and report many bins of low quality and completeness. Furthermore, the performance of existing algorithms varies between samples and biotypes. Here, we present a dereplication, aggregation and scoring strategy, DAS Tool, that combines the strengths of a flexible set of established binning algorithms. DAS Tools applied to a constructed community generated more accurate bins than any automated method. Further, when applied to samples of different complexity, including soil, natural oil seeps, and the human gut, DAS Tool recovered substantially more near-complete genomes than any single binning method alone. Included were three genomes from a novel lineage . The ability to reconstruct many near-complete genomes from metagenomics data will greatly advance genome-centric analyses of ecosystems.", + "laborHours": 3344.0, + "languages": [ + "NA" + ], + "name": "Dereplication, Aggregation and Scoring Tool (DAS Tool) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cmks/DAS_Tool/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmks/DAS_Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Tempus is a software framework for the time integration of ordinary differential equations (ODEs), partial differential equations (PDEs), and differential-algebraic equations (DAEs). Examples of time-integration methods available are Forward Euler, Backward Euler, Explicit Runge-Kutta and Implicit Runge-Kutta methods. Tempus can be used from small systems of equations (e.g., single ODEs for the time evolution of plasticity models) to large-scale transient simulations requiring exascale computing (e.g., flow fields around reentry vehicles and magneto-hydrodynamics). Tempus will be released as part of Trilinos under a BSD open source license.", + "laborHours": 8344830.4, + "languages": [], + "name": "Tempus v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "A library for performing numerical computation with low-rank functions. The (C3) library enables performing continuous linear and multilinear algebra with multidimensional functions. Common tasks include taking \"matrix\" decompositions of vector- or matrix-valued functions, approximating multidimensional functions in low-rank format, adding or multiplying functions together, integrating multidimensional functions.", + "laborHours": 1999271.2, + "languages": [ + "C", + "HTML", + "SWIG", + "CMake", + "Tex", + "Python" + ], + "name": "Compressed Continuous Computation v. 12/20/2016", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/compressed-continuous-computation?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/compressed-continuous-computation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The purpose of this software is to function as a generalized ferroelectric material model. The material model is designed to work with existing finite element packages by providing updated information on material properties that are nonlinear and dependent on loading history. The two major nonlinear phenomena this model captures are domain-switching and phase transformation. The software itself does not contain potentially sensitive material information and instead provides a framework for different physical phenomena observed within ferroelectric materials. The model is calibrated to a specific ferroelectric material through input parameters provided by the user.", + "laborHours": 1079.2, + "languages": [ + "C++", + "C" + ], + "name": "General Nonlinear Ferroelectric Model v. Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/gnom3-fe?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gnom3-fe", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "ISPH code is developed to solve multi-physics meso-scale flow problems using implicit SPH method. In particular, the code can provides solutions for incompressible, multi phase flow and electro-kinetic flows.", + "laborHours": 19425.6, + "languages": [ + "C++", + "MATLAB" + ], + "name": "Implicit SPH v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/implicit-sph", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-25" + }, + "description": "Tensors (also known as multidimensional arrays or N-way arrays) are used in a variety of applications ranging from chemometrics to network analysis. The Tensor Toolbox provides classes for manipulating dense, sparse, and structured tensors using MATLAB's object-oriented features. It also provides algorithms for tensor decomposition and factorization, algorithms for computing tensor eigenvalues, and methods for visualization of results.", + "laborHours": 21386.4, + "languages": [ + "MATLAB", + "XSLT", + "C" + ], + "name": "Tensor Toolbox for MATLAB v. 3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tensor_toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "This software package can be used to build, train, and test a neural network machine learning model. The neural network architecture is specifically designed to embed tensor invariance properties by enforcing that the model predictions sit on an invariant tensor basis. This neural network architecture can be used in developing constitutive models for applications such as turbulence modeling, materials science, and electromagnetism.", + "laborHours": 380.0, + "languages": [ + "Python 2.7" + ], + "name": "Tensor Basis Neural Network v. 1.0 (beta)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tbnn", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "CIME is the software infrastructure for configuring, building, running, and testing an Earth system model. It can be developed and tested as stand-alone software, but its main role is to be integrating into the CESM and ACME Earth system models.", + "laborHours": 59827.2, + "languages": [ + "Python" + ], + "name": "CIME, Common Infrastructure for Modeling the Earth v. 5.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ESMCI/cime/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESMCI/cime", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "A simulation of a research processor-in-memory class computer architecture running the accumulation function of sparse matrix-matrix multiply.", + "laborHours": 1352.8, + "languages": [ + "C++" + ], + "name": "Superstrider simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.debenedictis.org/SuperStrider.cpp", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/superstrider", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The Fourier-Bessel Particle-In-Cell code is a scientific simulation software for relativistic plasma physics. It is a Particle-In-Cell code whose distinctive feature is to use a spectral decomposition in cylindrical geometry.\r\n\r\nThis decomposition allows to combine the advantages of spectral 3D Cartesian PIC codes (high accuracy and stability) and those of finite-difference cylindrical PIC codes with azimuthal decomposition (orders-of-magnitude speedup when compared to 3D simulations).\r\n\r\nThe code is built on Python and can run both on CPU and GPU (the GPU runs being typically 1 or 2 orders of magnitude faster than the corresponding CPU runs.)\r\n\r\nThe code has the exact same output format as the open-source PIC codes Warp and PIConGPU (openPMD format: openpmd.org) and has a very similar input format as Warp (Python script with many similarities). There is therefore tight interoperability between Warp and FBPIC, and this interoperability will increase even more in the future.", + "laborHours": 16233.6, + "languages": [ + "None" + ], + "name": "Fourier-Bessel Particle-In-Cell (FBPIC) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fbpic/fbpic", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Pyomo supports the formulation and analysis of mathematical models for complex optimization applications. This capability is commonly associated with algebraic modeling languages (AMLs), which support the description and analysis of mathematical models with a high-level language. Although most AMLs are implemented in custom modeling languages, Pyomo's modeling objects are embedded within Python, a full- featured high-level programming language that contains a rich set of supporting libraries.", + "laborHours": 0.0, + "languages": [ + "Python 2.6, 2.7, 3.4, 3.5" + ], + "name": "Pyomo v5.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pyomo/pyomo/releases/tag/5.0.1", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "LinkShop is a software tool for applying the method of Linkography to the analysis time-sequence data. LinkShop provides command line, web, and application programming interfaces (API) for input and processing of time-sequence data, abstraction models, and ontologies. The software creates graph representations of the abstraction model, ontology, and derived linkograph. Finally, the tool allows the user to perform statistical measurements of the linkograph and refine the ontology through direct manipulation of the linkograph.", + "laborHours": 10503.2, + "languages": [ + "Python 3, Javascript, C++" + ], + "name": "LinkShop v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/linkshop", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The statistical code, STEPWISE, evaluates variable importance by developing regression models between the observed response and input variables using either a forward, backward, or stepwise regression procedure on the raw or ranked data. The software will be used for performing sensitivity analysis on probabilistic results. Stepwise creates linear (or monotonic) regression of the output of interest using a set of input data in a stepwise fashion (i.e., adding one variable at a time). The program estimates parameters such as regression and standardized regressions coefficients for each selected input variables as well as the coefficient of determination of the resulting model", + "laborHours": 0.0, + "languages": [ + "FORTRAN" + ], + "name": "Stepwise v. 2.21", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/stepwise", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.21" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The CEED Software suite is a collection of generally applicable software tools focusing on the following computational motives: PDE discretizations on unstructured meshes, high-order finite element and spectral element methods and unstructured adaptive mesh refinement. All of this software is being developed as part of CEED, a co-design Center for Efficient Exascale Discretizations, within DOE's Exascale Computing Project (ECP) program.", + "homepageURL": "http://ceed.exascaleproject.org", + "laborHours": 0.0, + "languages": [ + "C++, C, Fortran, Shell, Python" + ], + "name": "Center for Efficient Exascale Discretizations Software Suite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ceed.exascaleproject.org/software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://ceed.exascaleproject.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Tensors, or multidimensional arrays, are a powerful mathematical means of describing multiway data. This software provides computational means for decomposing or approximating a given tensor in terms of smaller tensors of lower dimension, focusing on decomposition of large, sparse tensors. These techniques have applications in many scientific areas, including signal processing, linear algebra, computer vision, numerical analysis, data mining, graph analysis, neuroscience and more. The software is designed to take advantage of parallelism present emerging computer architectures such has multi-core CPUs, many-core accelerators such as the Intel Xeon Phi, and computation-oriented GPUs to enable efficient processing of large tensors.", + "laborHours": 606784.0, + "languages": [ + "C++", + "Shell", + "C", + "CMake", + "Makefile", + "Python" + ], + "name": "Genten: Software for Generalized Tensor Decompositions v. 1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/GenTen?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GenTen", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "SmartBlock offers reusable components that can provide data manipulation and transformation operations on different data streams without requiring recompilation for the new data types.", + "laborHours": 1292.0, + "languages": [ + "C++, C" + ], + "name": "SmartBlock v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gflofst/SmartBlock", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The RAJA Performance Suite is designed to evaluate performance of the RAJA performance portability library on a wide variety of important high performance computing (HPC) algorithmic lulmels. These kernels assess compiler optimizations and various parallel programming model backends accessible through RAJA, such as OpenMP, CUDA, etc. The Initial version of the suite contains 25 computational kernels, each of which appears in 6 variants: Baseline SequcntiaJ, RAJA SequentiaJ, Baseline OpenMP, RAJA OpenMP, Baseline CUDA, RAJA CUDA. All variants of each kernel perform essentially the same mathematical operations and the loop body code for each kernel is identical across all variants. There are a few kernels, such as those that contain reduction operations, that require CUDA-specific coding for their CUDA variants. ActuaJ computer instructions executed and how they run in parallel differs depending on the parallel programming model backend used and which optimizations are perfonned by the compiler used to build the Perfonnance Suite executable. The Suite will be used primarily by RAJA developers to perform regular assessments of RAJA performance across a range of hardware platforms and compilers as RAJA features are being developed. It will also be used by LLNL hardware and software vendor panners for new defining requirements for future computing platform procurements and acceptance testing. In particular, the RAJA Performance Suite will be used for compiler acceptance testing of the upcoming CORAUSierra machine {initial LLNL delivery expected in late-2017/early 2018) and the CORAL-2 procurement. The Suite will aJso be used to generate concise source code reproducers of compiler and runtime issues we uncover so that we may provide them to relevant vendors to be fixed.", + "laborHours": 12813.6, + "languages": [ + "CC++ I I standard required" + ], + "name": "RAJA Performance Suite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RAJAPerf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "In this software, we implement an adaptive, multivariate partitioning algorithm for solving mixed-integer nonlinear programs (MINLP) to global optimality. The algorithm combines ideas that exploit the structure of convex relaxations to MINLPs and bound tightening procedures", + "laborHours": 16279.2, + "languages": [ + "Julia, C++" + ], + "name": "A Polyhedral Outer-approximation, Dynamic-discretization optimization solver, 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl-ansi/Alpine.jl/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/Alpine.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "ExaSP2 is a reference implementation of typical linear algebra algorithms and workloads for a quantum molecular dynamics (QMD) electronic structure code. The algorithm is based on a recursive second-order Fermi-Operator expansion method (SP2) and is tailored for density functional based tight-binding calculations of material systems.", + "laborHours": 1048.8, + "languages": [ + "C" + ], + "name": "ExaSP2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ECP-copa/ExaSP2/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-copa/ExaSP2", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "TraceR Is a trace replay tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performance and understanding network behavior by simulating messaging In High Performance Computing applications on interconnection networks.", + "laborHours": 4803.2, + "languages": [ + "C++" + ], + "name": "Trace Replay and Network Simulation Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpcgroup/TraceR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "\"TopoMS\" is a visualization and analysis tool developed to enable interactive exploration of molecular systems, allowing the users perform Bader analysis as well as detailed analysis of molecular graph in complex systems.", + "laborHours": 23286.4, + "languages": [ + "C++" + ], + "name": "TopoMS-UI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TopoMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Collection of applications and cloud templates. Project currently based on www.packer.io for automation, www.github.com/boxcutter templates and the www.github.com/csd-dev-tools/ClockworkVMs application for wrapping both of the above for easy creation of virtual systems. Will in future also contain cloud templates tuned for various services, applications and purposes.", + "laborHours": 714.4, + "languages": [ + "Python, PyQt, JSON, GO" + ], + "name": "CloudStackProjectsNContributions", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csd-dev-tools/CloudStackProjectsNContributions", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The SpecTAD software represents a refactoring of the Temperature Accelerated Dynamics (TAD2) code authored by Arthur F. Voter and Blas P. Uberuaga (LA-CC-02-05). SpecTAD extends the capabilities of TAD2, by providing algorithms for both temporal and spatial parallelism. The novel algorithms for temporal parallelism include both speculation and replication based techniques. SpecTAD also offers the optional capability to dynamically link to the open-source LAMMPS package.", + "laborHours": 29032.0, + "languages": [ + "Fortran" + ], + "name": "SpecTAD", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/spectad", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-12-09" + }, + "description": "DEBS advances the resistive MHD equations via a combination of the explicit leapfrop method and the semi-implicit method. In this way the time step is limited by the CFL condition v*kmax*dt < 1, where v is the local flow velocity, NOT the wave propagation (sound plus Alfven) velocity. The code is thus able to take timesteps that are much larger than allowed by purely explicit codes. For the spatial discretization, DEBS uses a finite difference approximation for the radial variation and a Fourier representation for the variation of the fields in the poloidal and axial directions, i.e it assumes a doubly-periodic geometry. It advances the vector potential in lieu of the magnetic field and uses the Weyl gauge which assumes the electrostatic potential is zero", + "homepageURL": "http://www.tibbartech.com", + "laborHours": 7128.8, + "languages": [ + "fortran 77" + ], + "name": "DEBS MHD Code", + "organization": "USDOE Advanced Research Projects Agency – Energy (ARPA-E) (United States) (ARPA-E)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.tibbartech.com/contact", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.tibbartech.com", + "status": "Production", + "tags": [ + "DOE CODE", + "USDOE Advanced Research Projects Agency – Energy (ARPA-E) (United States) (ARPA-E)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "CallFlow Is a visualization tool to view and analyze Calling Context Tree (CCT) data provided by HPCToolkit.", + "laborHours": 25870.4, + "languages": [ + "D3, JavaScript" + ], + "name": "CallFlow", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/LLNL/CallFlow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The ShiftNMFk1.2 code, or as we call it, GreenNMFk, represents a hybrid algorithm combining unsupervised adaptive machine learning and Green's function inverse method. GreenNMFk allows an efficient and high performance de-mixing and feature extraction of a multitude of nonnegative signals that change their shape propagating through the medium. The signals are mixed and recorded by a network of uncorrelated sensors. The code couples Non-negative Matrix Factorization (NMF) and inverse-analysis Green's functions method. GreenNMF synergistically performs decomposition of the recorded mixtures, finds the number of the unknown sources and uses the Green's function of the governing partial differential equation to identify the unknown sources and their charecteristics. GreenNMF can be applied directly to any problem controlled by a known partial-differential parabolic equation where mixtures of an unknown number of sources are measured at multiple locations. Full GreenNMFk method is a subject LANL U.S. Patent application S133364.000 August, 2017. The ShiftNMFk 1.2 version here is a toy version of this method that can work with a limited number of unknown sources (4 or less).", + "laborHours": 760.0, + "languages": [ + "Matlab" + ], + "name": "ShiftNMFk 1.2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/rNMF/HNMF/blob/master/License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rNMF/HNMF", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "HIOP is a HPC solver for solving certain optimization problems arising in mathematical optimization of systems described by partial-differential equations (POEs).", + "laborHours": 51573.6, + "languages": [ + "C++ (95%), CMake (5%)" + ], + "name": "High-performance optimization solver", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/hiop/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/hiop", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "BIGSTICK Is a flexible configuration-Interaction open-source shell-model code for the many-fermion problem In a shell model (occupation representation) framework. BIGSTICK can generate energy spectra, static and transition one-body densities, and expectation values of scalar operators. Using the built-in Lanczos algorithm one can compute transition probabflity distributions and decompose wave functions into components defined by group theory.", + "laborHours": 40690.4, + "languages": [ + "Fortran 90" + ], + "name": "Flexible configuration-interaction shell-model many-body solver", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cwjsdsu/BigstickPublick", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "TreeScope Is a visualization tool to view and analyze network traffic on fat-tree networks, e.g., on cab.", + "laborHours": 2219.2, + "languages": [ + "D3, JavaScript" + ], + "name": "TreeScope Visualization Tool for Fat-tree Networks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TreeScope", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "MGmol ls a First-Principles Molecular Dynamics code. It relies on the Born-Oppenheimer approximation and models the electronic structure using Density Functional Theory, either LDA or PBE. Norm-conserving pseudopotentials are used to model atomic cores.", + "laborHours": 62760.8, + "languages": [ + "C++, parallellsm based on MPI" + ], + "name": "Multigrid based First-Principles Molecular Dynamics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mgmol", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The purpose of this model was to facilitate the design of a control system that uses fine grained control of residential and small commercial HVAC loads to counterbalance voltage swings caused by intermittent solar power sources (e.g., rooftop panels) installed in that distribution circuit. Included is the source code and pre-compiled 64 bit dll for adding building HVAC loads to an OpenDSS distribution circuit. As written, the Makefile assumes you are using the Microsoft C++ development tools.", + "homepageURL": "https://sourceforge.net/projects/sunlamp", + "laborHours": 1246.4, + "languages": [ + "Visual Studio 2015" + ], + "name": "Sunlamp", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sourceforge.net/p/sunlamp/code/ci/master/tree/copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/sunlamp", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Residential Simulation Tool was developed to understand the impact of residential load consumption on utilities including the role of demand response. This is complicated as many different residential loads exist and are utilized for different purposes. The tool models human behavior and contributes this to load utilization, which contributes to the electrical consumption prediction by the tool. The tool integrates a number of different databases from Department of Energy and other Government websites to support the load consumption prediction.", + "laborHours": 8694.4, + "languages": [ + "Matlab" + ], + "name": "Residential Simulation Tool", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/starkemr/Residential-Simulation-Tool/blob/master/LICENSE.md/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/starkemr/Residential-Simulation-Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "A cosmic ray Muon Flexible Framework for Spectral GENeration for Monte Carlo Applications (MUFFSgenMC) has been developed to support state-of-the-art cosmic ray muon tomographic applications. The flexible framework allows for easy and fast creation of source terms for popular Monte Carlo applications like GEANT4 and MCNP. This code framework simplifies the process of simulations used for cosmic ray muon tomography.", + "homepageURL": "https://www.mathworks.com/matlabcentral/fileexchange/65585-muffsgenmc", + "laborHours": 167.2, + "languages": [ + "Matlab R2017" + ], + "name": "MUFFSgenMC: An Open Source MUon Flexible Framework for Spectral GENeration for Monte Carlo Applications", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.mathworks.com/matlabcentral/fileexchange/65585-muffsgenmc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.mathworks.com/matlabcentral/fileexchange/65585-muffsgenmc", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "In developing visualizations for different data sets, the end solution often become dependent on the data being visualized. This causes engineers to have to re-develop many common components multiple times. The vis-react components library was designed to help enable creating visualizations that are independent of the underlying data. This library utilizes the React.js pattern of instantiating components that may be re-used. The library exposes an example application that allows other developers to understand how to use the components in the library.", + "laborHours": 691539.2, + "languages": [ + "Javascript" + ], + "name": "vis-react-components", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/vis-react-components", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "OddMon reads statistics information from multiple Lustre OSS's, forwards it to a central aggregator and then processes the data into a form suitable to inserting into a Splunk data store.", + "laborHours": 836.0, + "languages": [ + "Python 2.6" + ], + "name": "OddMon", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-TechInt/oddmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This program takes the users' Input data and fits a linear regression to it using the prescription presented by Mahon (1996). Compared to the commonly used York fit, this method has the correct prescription for measurement error \r\npropagation. This software should facilitate the proper fitting of measurements with a simple Interface.", + "laborHours": 304.0, + "languages": [ + "Python 2.7 (100%)" + ], + "name": "Fitting program for linear regressions according to Mahon (1996)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MahonFitting", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "smoothG is a collection of parallel C++ classes/functions that algebraically constructs reduced models of different resolutions from a given high-fidelity graph model. In addition, smoothG also provides efficient linear solvers for the reduced models. Other than pure graph problem, the software finds its application in subsurface flow and power grid simulations in which graph Laplacians are found", + "laborHours": 9986.4, + "languages": [ + "C++ (100%)" + ], + "name": "smoothG", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/LLNL/smoothG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "TopoMS Is an analysis tool for molecular and condensed-matter systems. It can be used for Bader analysis, study of charge transfer, bond detection, and computation of complete molecular graph.", + "laborHours": 23286.4, + "languages": [ + "C++" + ], + "name": "TopoMS, Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/TopoMS/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TopoMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-24" + }, + "description": "This software enables the user to produce Google Earth visualizations of turbine wake effects for wind farms. The visualizations are based on computations of statistical quantities that vary with wind direction and help quantify the effects on power production of upwind turbines on turbines in their wakes. The results of the software are plot images and kml files that can be loaded into Google Earth. The statistics computed are described in greater detail in the paper: S. Martin, C. H. Westergaard, and J. White (2016), Visualizing Wind Farm Wakes Using SCADA Data, in Wither Turbulence and Big Data in the 21st Century? Eds. A. Pollard, L. Castillo, L. Danaila, and M. Glauser. Springer, pgs. 231-254.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Wind Wake Watcher v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Wind-Wake-Watcher", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "loupe is a PMPl-based library to profile MPI routines in a parallel application.", + "laborHours": 304.0, + "languages": [ + "C++, Python" + ], + "name": "MPI Profiler", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/loupe", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "KVTree is a hierarchical, tree-structured, key-value data structure library that can be used and re-used by other tools.", + "laborHours": 3131.2, + "languages": [ + "C" + ], + "name": "KVTree", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/KVTree", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "MathWorks' MATLAB is widely used in academia and industry for prototyping, data analysis, data processing, etc. Many users compile their programs using the MATLAB Compiler to run on workstations/computing clusters via the free MATLAB Compiler Runtime (MCR). The MCR facilitates the execution of code calling Application Programming Interfaces (API) functions from both base MATLAB and MATLAB toolboxes. In a Linux environment, a sizable number of third-party runtime dependencies (i.e. shared libraries) are necessary. Unfortunately, to the MTLAB community's knowledge, these dependencies are not documented, leaving system administrators and/or end-users to find/install the necessary libraries either as runtime errors resulting from them missing or by inspecting the header information of Executable and Linkable Format (ELF) libraries of the MCR to determine which ones are missing from the system. To address various shortcomings, Docker Images based on Community Enterprise Operating System (CentOS) 7, a derivative of Redhat Enterprise Linux (RHEL) 7, containing recent (2015-2017) MCR releases and their dependencies were created. These images, along with a provided sample Docker Compose YAML Script, can be used to create a simulated computing cluster where MATLAB Compiler created binaries can be executed using a sample Slurm Workload Manager script.", + "laborHours": 45.6, + "languages": [ + "Bash 4.x, Docker 17.09" + ], + "name": "MCR Container Tools", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/mcr-container-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "OpenMP, a directive-based programming API, introduce directives for accelerator devices that programmers are starting to use more frequently in production codes. To make sure OpenMP directives work correctly across architectures, it is critical to have a mechanism that tests for an implementation's conformance to the OpenMP standard. This testing process can uncover ambiguities in the OpenMP specification, which helps compiler developers and users make a better use of the standard. We fill this gap through our validation and verification test suite that focuses on the offload directives available in OpenMP 4.5.", + "laborHours": 12479.2, + "languages": [ + "C/C++/Fortran" + ], + "name": "OpenMP 4.5 Validation and Verification Suite", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/crpl_cisc/sollve_vv", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "A computational method to automatically detect solar panels on rooftops to aid policy and financial assessment of solar distributed generation. The code automatically classifies parcels containing solar panels in the U.S. as residential or commercial. The code allows the user to specify an input dataset containing parcels and detected solar panels, and then uses information about the parcels and solar panels to automatically classify the rooftops as residential or commercial using machine learning techniques. The zip file containing the code includes sample input and output datasets for the Boston and DC areas.", + "laborHours": 197.6, + "languages": [ + "R/NA/3.4.0" + ], + "name": "Automatic Residential/Commercial Classification of Parcels with Solar Panel Detections", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/nset-ornl/ornlsolar/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nset-ornl/ornlsolar", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Boiler tubes in steam power plants experience exfoliation of oxide grown on the inner side of the tubes. In extreme cases, the exfoliation cause significant tube blockages that lead to forced power plant outages. It is thus desired to predict through modeling the propensity of exfoliation events in order to inform power plant operators of possible tube blockages. SpallMap solves for the stress-strain equations in an axisymmetric geometry, tracking the stress/strain evolution during boiler operation including outages at one-location along a boiler tube and compares it with scale damage criteria represented by Armitt diagram. The SPALLMAP code contains modules developed for oxide growth, stress analysis, and classical fracture mechanics correlations by taking into account the following phenomena and features, (a) Non-uniform thermal expansion coefficient of oxides and metal substrates, (b) Plant operation schedule with periodic alternate full-load and partial-load regimes, (c) axisymmetric formulation for cylindrical tubes, (d) Multiple oxide layers, (e) oxide-growth induced stresses, and (f) damage criteria from classical fracture mechanics. The computer program is written in FORTRAN90. Its modular structure was sought for allowing the best flexibility in updating the program by implementing new constitutive equations due to availability of new material property data and/or new physical phenomena.", + "laborHours": 0.0, + "languages": [ + "Fortran90" + ], + "name": "SPALLMAP", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/adisoft17/spallmap/blob/master/License_SpallMap_OpenSourceSoftware_ORNL.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/adisoft17/spallmap", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Samlab provides a workflow and data storage for machine learning experiment inputs and outputs using mongodb, and a web service to manage, search, visualize, and analyze the results.", + "laborHours": 7296.0, + "languages": [ + "Python" + ], + "name": "Sandia Machine Learning Laboratory", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/samlab/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/samlab", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2021-08-25" + }, + "description": "Charon is used to solve the drift-diffusion PDE Equations associated with semi-conductor physics. it is used to stimulate the operation of semi-conductor devices such as transistors and diodes. Additionally, the ode includes the functionality, but no the restricted data, to model these devices under the effects of neutron radiation.", + "homepageURL": "https://charon.sandia.gov", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Charon v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://charon.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The CSlib is a small, portable library which enables two (or more) independent simulation codes to be coupled, by exchanging messages with each other. Both codes link to the library when they are built, and can them communicate with each other as they run. The messages contain data or instructions that the two codes send back-and-forth to each other. The messaging can take place via files, sockets, or MPI. The latter is a standard distributed-memory message-passing library.", + "laborHours": 4240.8, + "languages": [ + "The CSlib can be used from programs written in C++, C, Fortran, or Python. The library itself is wr", + "Shell", + "Makefile" + ], + "name": "CSlib, a library to couple codes via Client/Server messaging", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://cslib.sandia.gov/open_source.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cslib", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The fftMPI library enables two and three dimensional Fast Fourier Transforms (FFTs) to be\r\nperformed efficiently in parallel on a variety of platforms from desktop machines to supercomputers. It allows for flexibility in the initial distribution of the FFT grid across processors, as well as the final output. It handles the data communication and reordering necessary to perform multi-dimensional FFTs in parallel. It relies on open-source or vendor-provided libraries to perform one dimensional FFTs on a single processor. It uses MPI for inter-processor communication, which is a standard distributed memory message-passing library.", + "laborHours": 8907.2, + "languages": [ + "The CSlib can be used from programs written in C++, C, Fortran, or Python.", + "Shell", + "Makefile" + ], + "name": "fftMPI, a library for performing 2d and 3d FFTs in parallel", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/fftmpi?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fftmpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "It compares the performance of several different algorithms for electronic structure simulation.", + "laborHours": 2188.8, + "languages": [ + "Shell", + "C", + "Python" + ], + "name": "Companion Software to \"Assessment of localized and randomized algorithms for electronic structure\"", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/linear-scaling-test", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "HOMMEXX is a global atmosphere dynamics and transport solver that uses a spectral element method, and is now written to be performance portable to many new computer architectures.", + "laborHours": 93723.2, + "languages": [ + "C++" + ], + "name": "HOMMEXX", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/E3SM-Project/HOMMEXX/blob/master/src/share/cxx/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/HOMMEXX", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "ShareAnalytics is a lightweight extensible platform for collaborative data analytics and facility characterization via Non-intrusive Load Monitoring (NILM). It consists of three core components: a full stack web application, a dashboard tool for analyzing streaming data and a High Performance Computing (HPC) cluster leveraging slurm for resource management to perform real time analysis. The entire framework is implemented in Docker for ease of deployment and to allow the user to test the platform before making a significant investment in hardware if they require additional computing resources. While many other platforms for analyzing streaming data exists, ShareAnalytics is unique in that HPC capabilities and facility characterization via scored analytics are fully integrated into the platform.", + "laborHours": 8755.2, + "languages": [ + "JavaScript / Bash" + ], + "name": "ShareAnalytics", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/ShareAnalytics", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Lab experiments involving digital signal processing tend to capture heterogeneous data that is binned into individual files. The structure of the whole experiment tends to get lost in this process, generating a \"mess\" of data that is difficult to summarize, and even more difficult to analyze in a consistent way. DataXray is a set of python routines that wraps publicly available open-source codes to create a consistent workflow for data and experiments, involving imaging, spectral and hyperspectral data. Routines are provided for data translation, slicing, visualization, multivariate statistics, integral transforms, feature extraction and reporting in the form of publication-grade figures.", + "laborHours": 2173.6, + "languages": [ + "Python 3.5" + ], + "name": "DataXray", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/glacio/data-xray/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This program implements a novel algorithm to obtain the density of state of a physical system, expanded in a chosen basis set. Unlike existing algorithms that return the density of states as a numerical array, this algorithm avoids binning of a continuous variable and is able to express the density of states in an analytical form. It is thus suitable for the study of the statistical mechanics and thermodynamic properties of physical systems where the density of a continuous state variable is of interest. The new algorithm presented here is a special reweighting method in classical Monte Carlo approaches. In particular, it can be regarded as a descendant and a hybrid method closely related to the multicanonical method and Wang--Landau sampling.", + "laborHours": 106.4, + "languages": [ + "Python3" + ], + "name": "HistogramFreeMUCA", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yingwaili/HistogramFreeMUCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Physics simulations that use particles in their algorithms are ubiquitous on modern high performance computers. Cabana is a C++ library for developing particle-based simulations on heterogeneous high performance computing platforms. Cabana provides general data structures and algorithms for common particle operations in a way that is both performant and portable on HPC systems. This includes particle data structure allocatable and configurable on GPU and CPU architectures, and threaded and distributed algorithms for sorting particles, halo exchanges, neighbor list generation, and other basic particle operations.", + "laborHours": 32528.0, + "languages": [ + "C++/clang,GCC,Intel,NVCC" + ], + "name": "Cabana", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-copa/Cabana", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Existing tools for computational anatomy and image registration are not aimed at HPC environments. As such they are not easily adapted to multimode platforms and contain inefficient batch processing modes. Lagomorph addresses this by providing an easy to install and use pure python implementation of very efficient image registration and atlas building which is aimed at extreme-scale anatomical studies using modern HPC and GPU resources.", + "laborHours": 3192.0, + "languages": [ + "Python 3.6" + ], + "name": "Lagomorph", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jacobhinkle/lagomorph/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jacobhinkle/lagomorph", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Kelvin is a multiphysics sintering simulation software that uses the material point method to simulate the thermomechanical behavior of metal parts.", + "laborHours": 2264.8, + "languages": [ + "C++, gcc 8.x" + ], + "name": "Kelvin", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/kelvin/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/kelvin", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "VeraRun provides users a command-line utility that determines the sequence of VERA codes and utilities to be executed, calculates and determines PBS directives and job parameters, creates a job script, and submits the script on behalf of the user. While hiding all the details, the script allows the user to set PBS parameters explicitly. VeraRun is implemented as a Python package with host-specific configurations and job script templates. Host configurations are stored in JavaScript Object Notation (JSON) files and specify machine characteristics (e.g., number of nodes, number of processors per node, memory available per node, location of VERA installations). Job templates are Bash scripts with parameters substituting for host-specific PBS directives and controls. These files are named by the hostname, thus making VeraRun extensible to other systems and environments. VeraRun reads the VERA input file to determine code and execution environment requirements, creating and optionally submitting a job script.", + "laborHours": 21675.2, + "languages": [ + "Python 2 or 3" + ], + "name": "VeraRun", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/casl/VeraView", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Information extraction and coding of free-text pathology reports is an important activity for cancer registries to support national cancer surveillance. Cancer registrars must process high volumes of pathology reports on an annual basis. We investigated an automated approach using a convolutional neural networks (CNNs) for extracting the primary site, laterality, histology, behavior, and histological grade from unstructured cancer pathology text reports. Our multi-task learning (MTL) with hard parameter sharing approach is used to train a multi-task MT-CNN model for all the tasks. The performance of our proposed approach was compared against a state of-the-art CNN and the commonly used SVM classifier. We observed that the proposed model consistently outperformed the baseline models, especially for the less prevalent classes. Also, the results demonstrate the potential of the proposed method for handling class imbalance within each task.", + "laborHours": 273.6, + "languages": [ + "Python" + ], + "name": "Multi-Task Convolutional Neural Networks for Natural Text Classification", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CBIIT/pilot3_MT-CNN_ORNL", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The code is a set of first-principles based thermodynamic properties calculations for materials properties at finite temperature. It provides a collection of commonly used Monte Carlo algorithms, interfaced with a few external codes that carry out density functional theory calculations, such as Quantum Espresso and Local Self-consistent Multiple Scattering. The code provides high accuracy thermodynamic calculations that are comparable to real-world materials properties.", + "laborHours": 4453.6, + "languages": [ + "C++11" + ], + "name": "Oak Ridge Wang-Landau (OWL)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/owl-suite/OWL", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Many universities have published highly accurate open source face recognition algorithms, but configuring and using those algorithms can be very difficult due to poor documentation and challenges with installing the right software and libraries. Comparing research results is also a problem due to uncontrolled research methods. Provide baseline face recognition implementations that can be used for evaluating algorithm accuracy. The software provides a consistent web service interface to face recognition algorithms that can be used to support research in biometrics. The software uses protobuf and grpc services to publish standardized interfaces to the algorithms. The software also provides Docker container support which allows services to be easily started and configured on new machines. Reproducible baseline configurations are provided to serve as bench marks for publications in this area.", + "laborHours": 35613.6, + "languages": [ + "Python 3" + ], + "name": "Face Recognition from Oak Ridge (FaRO)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/faro", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "A challenging scientific problem that will benefit from exascale computing is predictive simulation of two- and three-dimensional quantum many-body Hamiltonians in condensed matter physics, together with the related strong entanglement problems in quantum chemistry and quantum computing. Efficient numerical simulations will require new insights into wavefunction compression algorithms that scale on extremely heterogeneous HPC architectures. To address this need, we propose to develop a scalable math library of parallel multi-linear algebraic numerical primitives for hierarchical tensor compression. Our library will subsequently be used for building an efficient, performance-portable HPC framework for simulating strongly correlated quantum systems. In particular, our will will be the first to deliver a massively parallel implementation of the multiscale entanglement renormalization ansatz (MERA), a hierarchical tensor decomposition quantum scheme capable of expressing local expectation values of strongly entangled higher-dimensional quantum systems efficiently. To address the extreme complexity and high computational cost of such schemes, we will automate their parallel implementation by delivering an integrated software framework, ExaTN (Exascale Tensor Networks), that will process hierarchical tensor representations on exascale HPC systems via an asymchronous task-based programming model. As a specific application, our framework will provide scientists with a capability of simulating strongly entangled quantum systems, thus positioning ORNL as a strategic leader in modeling of strongly correlated materials.", + "laborHours": 173097.6, + "languages": [ + "C++ using clang and/or gcc versions compliant with C++11" + ], + "name": "ExaTN", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-qci/exatn", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The QCOR compiler provides a mechanism for the expression and compilation of quantum code alongside standard, modern C++. It does so through integration with Clang and its robust abstract syntax tree analysis tools, as well as integration with the XACC infrastructure.", + "laborHours": 62228.8, + "languages": [ + "C++, Clang/GCC with C++11 support" + ], + "name": "QCOR", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-qci/qcor", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "ExaTENSOR is a software math library for performing basic numerical tensor algebra operations on distributed heterogeneous HPC platforms. The library provides the following basic numerical tensor algebra primitives: tensor contraction, tensor product, tensor addition, tensor scaling by a scalar, etc. ExaTENSOR supports dense, block-sparse and hierarchical block-sparse tensors stored and processed across many heterogeneous HPC nodes (node equipped with NVIDIA GPU and Intel Xeon Phi have been considered so far). The architecture of ExaTENSOR is based on the concept of domain-specific virtual processor (DSVP), that is, an intermediate software layer capable of processing domain-specific instructions, in this case, numerical tensor algebra instructions. In this way, a separation of the domain-specific algorithm expression and hardware-agnostic algorithm execution is achieved, thus ensuring portability of the applications which use ExaTENSOR as a numerical backend.", + "laborHours": 85591.2, + "languages": [ + "Fortran 2003", + "C/C++", + "gcc-8.1", + "intel-1.8", + "xl-16.1.1" + ], + "name": "ExaTENSOR", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/ExaTENSOR", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Iterative Random Forest (iRF) is an improvement upon the classic Random Forest, using weighted iterations to distill the forests. Ranger is a C++ implementation of random forest or recursive partitioning, particularly suited for high dimensional data. Ranger-Based iRF uses Ranger as a base Random Forest codebase upon which iterative and scalability aspects have been added.", + "laborHours": 6976.8, + "languages": [ + "C++/gnu-cmake" + ], + "name": "Ranger-based Iterative Random Forest", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Jromero1208/RangerBasediRF", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Current software uses a least squares statistical method. For each model parameter, current software yields a point estimate and estimated standard error for each point estimate. In contrast, we have employed a Bayesian approach with sampling algorithm to provide a full posterior probability density function on each model parameter. This yields a different type of solution (probabilistic) with better fidelity. The Quantitative Uncertainty Analysis for Diffraction (QUAD) package returns a matrix of affect model parameters as a function of iteration through the MCMC analysis. QUAD is a Python code that allows for analysis of X-ray and neutron diffraction data to infer the structure of materials with quantifiable certainty. The code uses Bayesian statistics and Markov chain sampling algorithms to create posterior probability distributions on all material structure parameters that are modeled by a researcher. The statistical packages use the open source GSASII project as a library to calculate model diffraction patterns.", + "laborHours": 653.6, + "languages": [ + "Python" + ], + "name": "Quantitative Uncertainty Analysis for Diffraction", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/rabroughton/QUAD/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rabroughton/QUAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "TRITON is a 2D hydraulic, digital elevation model (DEM)-based model that accepts a variety of flow inputs including point-based inflow hydrographs, external boundary conditions, and runoff (i.e., excess rainfall). It provides information of flood maps and temporal evolution of water depth at each grid cell point at user-specified output time. Its unique feature is that TRITON can run on single or multiple CPUs and GPUs, proving to be very flexible in terms of system architecture.", + "laborHours": 5168.0, + "languages": [ + "C++, CUDA" + ], + "name": "TRITON", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/hydro/triton/-/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/hydro/triton", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The code \"STEMDL\" provides highly-optimized multi-gpu implementations of DL models of applicability in electron microscopy via the use of mixed-precision arithmetic, native graph construction and evaluation in Tensorflow, and adaptive scaling of learning parameters to avoid numerical instabilities due to reduced precision. STEMDL also uses low-level methods from the Horovod library for gradient communication and reduction and adds an additional optimization by allowing the user to scheduling the gradient reduction operations based on their position within the layers of a neural net. STEMDL provides optimized I/O routines for data staging and data reading/writing in both Tensorflow and Pytorch using multi-processing and asynchronous transfer between host and device.\r\n.", + "laborHours": 147014.4, + "languages": [ + "Python 2.7/3.x" + ], + "name": "STEMDL", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/disMultiABM/stemdl", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "RDF triplestores are great tools for online graph analytic processing (i.e., graph pattern query processing), but they do not provide graph mining capabilities (e.g., PageRank, connected-component analysis, node eccentricity, etc.). The software title “TripleGraph” is a graph analysis toolkit, which uses an RDF triplestore as its backend for creating, manipulating, mining, and programming with large scale property graphs. It allows users to run various graph mining algorithms easily. User can import edgelist-formatted (homogeneous graph) or JSON-formatted graph (property graph) into the RDF triplestore using the provided tool and perform various analysis such as (1) Node/edge retrieval and manipulation, (2) Pathfinding between two given nodes, (3) Running graph mining algorithms (PageRank/Personalized PageRank, Single Source Shortest Path/Multi-Source Shortest Path, Connected Component, Node Eccentricity, Peer Pressure Clustering). It supports standard graph data format and works with a standard SPARQL endpoint like Jena Fuseki. It allows users to perform online graph analytic processing and graph mining on the same platform (a triplestore).", + "laborHours": 380.0, + "languages": [ + "Python 2.7" + ], + "name": "TripleGraph", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/liza183/TripleGraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The code “miniWeather” solves the 2-D Euler equations with a Finite-Volume method on a regular Cartesian grid with Runge-Kutta time stepping, 4th-order hypervisocisty, and 4th-order spatial accuracy. The code is primarily a parallel programming training mini application in Fortran, C, and C++ with MPI, OpenMP, OpenMP offload, OpenACC, and C++ portability approaches. It can also serve as a mini application for acceptance testing for new machines and compilers for both functionality and performance.", + "laborHours": 7828.0, + "languages": [ + "C++11, any C++11 compiler can be used" + ], + "name": "miniWeather", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mrnorman/miniWeather", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The software \"eeyore\" solves the problem of running Markov chain Monte Carlo (MCMC) algorithms on Bayesian neural networks. There is software for MCMC algorithms and software for neural network (such as PyTorch and TensorFlow), but there are limited solutions for combining the two. The main idea is to create a subclass of the 'torch.nn.Module' for defining Bayesian neural networks with the desired functionality required by MCMC taking the form of additional methods in that sub-class. This way, neural network functionality of PyTorch is exposed to the developer and user, allowing to develop MCMC methods on top of it through a simple API. The code implements Langevin Monte Carlo algorithms and population MCMC algorithms, as well as combinations of these, for Bayesian neural networks. This kind of functionality is not available elsewhere, to the best of the authors' knowledge. Moreover, a simple API is available that allows to implement new MCMC algorithms in the future.", + "laborHours": 2614.4, + "languages": [ + "Python (v3.6 onwards)" + ], + "name": "eeyore", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/papamarkou/eeyore", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "In NAMSA, we introduce two main solutions to address the limitations of MSA-type algorithms for simulation of electron scattering/microscopy data: just-in-time compilation and work partitioning via MPI and GPU-to-GPU communication. First, the just-in-time (JIT) compilation strategy produces optimally tuned CUDA C++ kernels due to the data layout being perfectly known at runtime and compiled via calls from the Python interpreter. NAMSA automatically optimizes the 2-D FFT planning, and CUDA multi-streams scheduling/launching of probe simulations. With NAMSA, we can simulate electron scattering/microscopy on hundreds to thousands of GPUs, while removing the major limitations of memory and bandwidth from MSA.", + "laborHours": 2766.4, + "languages": [ + "Python (2.7/3.X), CUDA C++ /NVCC/10.01" + ], + "name": "NAMSA", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/disMultiABM/namsa", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "P Finder is written in C# and has been tested in multiple 64-bit Windows environments (Windows 7/8/Vista). It has a user-friendly graphical user interface (GUI) that allows for intuitive RNase P RNA identification and/or annotation. The user can select from four search criteria including the use multiple threads. In addition, the user can determine what display data they wish to incorporate in the output such as: bitscore, E-value, percent ID, start location, end location, the strand in which the sequence is located, and of course the sequence itself. P Finder is the only available algorithm that is capable of not only identifying the RNase P RNA for annotation but also differentiating among the five different RNase P RNA structural types (A, B, C, M, and T) with the option to select these data types for display in the final output.", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "P Finder", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JChristopherEllis/P-Finder", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "CoMet is an application for finding epistatic and pleiotropic relationships from large quantities of genomic data. 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CoMet was developed at the Oak Ridge Leadership Computing Facility in collaboration with the Computational Biology and Bioinformatics Group at Oak Ridge National Laboratory.", + "laborHours": 18361.6, + "languages": [ + "GNU C++, NVIDIA NVCC" + ], + "name": "CoMet", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wdj/comet", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The code titled “eBPF Community ID Calculation” allows easy correlation of monitoring logs with existing network forensics logs on high-performance computing (HPC) systems. This code implements the Community ID Flow Hashing standard to calculate community ID Flow identifiers. These identifiers will be used to correlate host forensics logs with network forensics logs. The correlation provides valuable insight and the ability to easily pivot between disparate data sources. The computer code removes the libpcap dependency from the code base.", + "laborHours": 167.2, + "languages": [ + "Golang. 1.13" + ], + "name": "eBPF Community ID Calculation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stefanmaerz/eBPF_communityID", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2022-05-06" + }, + "description": "“The code “Certificate Validation Libraries” provides the ability to validate x509 certificates in python using a simple library. These libraries validate certificates in 3 ways: 1) validation that certificate has not expired. 2) validation that certificate has not been revoked and 3) validation of certificate's digital signature. The benefits of this code is that one can properly validate x509 certificates, thus strengthening the security of systems using these libraries.”", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "Certification Validation Libraries", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/certification-validation-libraries", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "In the era of machine learning, we often need to run the same code/script many times with little or no variations (e.g., performance evaluation, data preprocessing, data generation, hyperparameter tuning, etc.). It is not a problem when you just need to do that a few times, but when the number of repetitions becomes very large, it can be a daunting task. The code “Serial2Parallel” provides an easy way for users to be able to run many numbers of any serial code/scripts in a parallel manner across multiple nodes in an message passing interface (MPI) cluster. The code includes the server program that deals with task pool management and client program that processes task. The server gets the tasks ready and waits for clients' connections. The client code pulls tasks from the server and processes them. The client code will run in parallel.", + "laborHours": 136.8, + "languages": [ + "Python 3" + ], + "name": "Serial2Parallel", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/liza183/Serial2Parallel", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/liza183/Serial2Parallel", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The software “MEUMAPPS” is a h high-performance computing code used to simulate microstructure evolution associated with diffusional solid-state transformations in structural alloys. Understanding microstructure evolution during thermo-mechanical processing of structural alloys is the first step towards designing and processing alloys for specific applications by meeting property requirements demanded by the application. In this instance, the code is an important component in predicting processing-structure linkages during additive manufacturing of structural alloys as a function of processing parameters and alloy composition used in an additive manufacturing process. The code provides a detailed three-dimensional distribution of different types of phases / constituents and their morphologies, as well as the compositions of these phases that make up the microstructure. The microstructure is simulated by solving the governing partial differential equations using a Fourier Spectral Method.", + "laborHours": 851.2, + "languages": [ + "Fortran/PGI/19.9" + ], + "name": "MEUMAPPS (Microstructure Evolution Using Massively Parallel Phase-field Simulations)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/meumapps_ss", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-05", + "metadataLastUpdated": "2024-07-19" + }, + "description": "KARMA4 is a C++ library for autoregressive moving average (ARMA) modeling and forecasting of time-series data while incorporating both process and observation error. KARMA4 is designed for fitting and forecasting of time-series data for predictive purposes.", + "laborHours": 471.2, + "languages": [ + "C++", + "MATLAB", + "Makefile" + ], + "name": "KARMA4", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/KARMA4", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-10-05", + "metadataLastUpdated": "2020-10-05" + }, + "description": "The invention improves accuracy of metabolite identification by combining direct infusion ESI-MS with one-dimensional 1H-NMR spectroscopy. First, we apply a standard 1H-NMR metabolite identification protocol by matching the chemical shift, J-coupling and intensity information of experimental NMR signals against the NMR signals of standard metabolites in a metabolomics reference libraries. This generates a list of candidate metabolites. The list contains both false positive and ambiguous identifications. The software tool (the invention) takes the list of candidate metabolites, generated from NMRbased metabolite identification, and then calculates, for each of the candidate metabolites, the monoisotopic mass-tocharge (m/z) ratios for each commonly observed ion, fragment and adduct feature. These are then used to assign m/z ratios in experimental ESI-MS spectra of the same sample. Detection of the signals of a given metabolite in both NMR and MS spectra resolves the ambiguities, and therefore, significantly improves the confidence of the identification.", + "laborHours": 15.2, + "languages": [ + "Software is compiled and interpreted for the Java Virtual Machine (JVM) version 6 or higher." + ], + "name": "Unambiguous Metabolite Identification in High-Throughput Metabolomics by Hybrid 1H-NMR/ESI-MS1 Approach", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/unambiguous-metabolite-identification-hybrid-1d-1h-nmresi-ms1-approach", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-NMR-EPR/MATLAB-1D_1H_NMR_ESI_MS1-WebApp", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-10-05", + "metadataLastUpdated": "2020-10-05" + }, + "description": "Algorithms and software code to detect and diagnose faulty operations with economizer operations.", + "laborHours": 109880.8, + "languages": [ + "Linux" + ], + "name": "Active and Passive Economizer Diagnostics for Rooftop and Air-Handling Units", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron-applications", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-10-05", + "metadataLastUpdated": "2020-10-05" + }, + "description": "The ILC algorithm prioritizes available loads for curtailment in large and small/medium size commercial buildings.", + "laborHours": 109880.8, + "languages": [ + "Python" + ], + "name": "Intelligent Load Control", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron-applications", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-10-07", + "metadataLastUpdated": "2023-05-08" + }, + "description": "Open Energy Data Initiative (OpenEDI): Advancing Analytics and Research Innovation through Improved Data Access. The Open Energy Data Initiative (OEDI) aims to improve and automate access of high-value energy data sets across the U.S. Department of Energy’s (DOE’s) programs, offices, and national laboratories. Sponsored by the DOE, this platform is being implemented by the National Renewable Energy Laboratory (NREL) to make data actionable and discoverable by researchers and industry to accelerate analysis and advance innovation. Partners at other national laboratories will help utilize the platform for analysis, can be directly involved in determining requirements, and will be resources for providing new datasets that can be shared with the public to expand innovation.", + "laborHours": 20322.4, + "languages": [ + "Python", + "Dockerfile" + ], + "name": "Open Energy Data Initiative (OpenEDI) - Open Data Access Tools (OEDI-ODAT) [SWR 20-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openEDI/open-data-access-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.2.1" + }, + { + "contact": { + "email": "gaoz@ornl.gov" + }, + "date": { + "created": "2020-10-08", + "metadataLastUpdated": "2021-03-05" + }, + "description": "Membrane-based dehumidification is currently being considered as a promising solution for the building application due to its low cost and very limited energy consumption. Developing a simple and efficient open-source code simulation tool is important for boosting the optimization and evaluation of such device in HVAC community. This paper reports a first-order physics based model which accounts for the fundamental heat and mass transfer of humid-air vapor at feed side to flow stream at permeate side. The current model comprises two membrane mass transfer submodels (i.e. microstructure model and performance map model); and it adopts a segment-by-segment methodology for discretizing heat and mass transfer governing equations. The model is capable of simulating both dehumidifiers and energy recovery ventilators with parallel-flow cross-flow, and counter-flow configurations. The model was validated with the measurements at appropriate device. The practices in dehumidification and energy recovery exchangers are also discussed. The model and open-source codes are expected to become a solid fundament for developing a more comprehensive and accurate membrane-based dehumidification in the future. ", + "laborHours": 1200.8, + "languages": [ + "C++" + ], + "name": "MBMS1.0: An Open-Source Code for Modeling and Simulation of Membrane-Based Dehumidification and Energy Recovery", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MBMS/C-CODE_FOR_MEMBRANE_BASED_MODEL", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "MBMS. 1.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-10-13", + "metadataLastUpdated": "2020-10-19" + }, + "description": "ExaPF is a HPC package in Julia for solving power flow (PF) on a GPU. It currently solves PF using the Newton-Raphson algorithm on NVIDA GPUs.", + "laborHours": 6080.0, + "languages": [], + "name": "ExaPF", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exanauts/EXaPF.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-10-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Automated NGFC system design tool set to develop optimized, next-generation solid oxide fuel cell (SOFC)\nbased natural gas fuel cell (NGFC) system designs with >70% fuel efficiency and <30 g/kWh CO2 emissions", + "laborHours": 39261.6, + "languages": [], + "name": "NGFC-Lib/NGFC-Lib", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NGFC-Lib/NGFC-Lib", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-10-19", + "metadataLastUpdated": "2020-10-19" + }, + "description": "RELOG is a supply chain optimization package focusing on reverse logistics and reverse manufacturing. For example,the package can be used to determine where to build recycling plants, what sizes should they have and which customers should be served by which plants. The package supports customized reverse logistics pipelines, with multiple types of\nplants, multiple types of product and multiple time periods.\n", + "laborHours": 24411.2, + "languages": [], + "name": "RELOG", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-CEEESA/RELOG", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "fattebertj@ornl.gov" + }, + "date": { + "created": "2020-10-20", + "metadataLastUpdated": "2020-10-20" + }, + "description": "Loewdin orthonormalization of distributed tall-skinny matrix using Schulz iteration", + "laborHours": 1869.6, + "languages": [ + "C++" + ], + "name": "ORNL/ParrLO", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/ParrLO", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-10-21", + "metadataLastUpdated": "2020-10-21" + }, + "description": "JPype is a Python module to provide full access to Java from within Python. It allows Python to make use of Java only libraries, exploring and visualization of Java structures, development and testing of Java libraries, scientific computing, and much more. By gaining the best of both worlds using Python for rapid prototyping and Java for strong typed production code, JPype provides a powerful environment for engineering and code development. This is achieved not through re-implementing Python, as Jython has done, but rather through interfacing at the native level in both virtual machines. This shared memory based approach achieves decent computing performance, while providing the access to the entirety of CPython and Java libraries.", + "laborHours": 34656.0, + "languages": [], + "name": "JPype", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Thrameos/jpype", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-10-21", + "metadataLastUpdated": "2020-10-21" + }, + "description": "Compilers transform program source code to machine executable code. During this transformation, they perform a number of compiler optimizations to improve the performance of the generated executable\ncode. Importantly, applying those optimizations depends on the source code structure, such as the parallel programming model used to\nparallelize an algorithm. Often, implementations of the same algorithm with different programming models have vastly different performance because the compiler optimized them differently. We create FAROS, a framework to structure and automate the analysis of compiler optimizations on programs. FAROS automates the building process, execution profiling, and analysis of compiler optimization of programs, through a configuration interface. It outputs compiler optimization reports to show which\noptimizations applied to which line of source code, leveraging compilation remarks output by the compiler. Also, FAROS supports\nbenchmarking performance of different program versions by collecting execution time results. In this first release of FAROS, we provide a configuration file to analyze compiler optimization differences for sequential vs OpenMP compilation, including 38 programs consisting of HPC proxy/mini/large applications, and NAS and Rodina kernels for analysis. ", + "laborHours": 1976.0, + "languages": [], + "name": "A Framework for the Analysis of Compiler Optimizations", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FAROS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-10-26", + "metadataLastUpdated": "2023-04-24" + }, + "description": "The Electricity Markets Investment Suite Approximate Equilibrium (EMIS-AE) package is developed at NREL and provides a solution capability to solve generation expansion equilibrium problems in the electricity markets. EMIS-AE is designed to capture the evolution of the electricity generation portfolio resulting from the interactions of heterogeneous investors under different policy and market designs. The investment problem for each generation company (GENCO) is a bi-level problem with the investment decision made in the upper level and market clearing condition in the lower level, which traditionally is represented as a Mathematical Program with Equilibrium Constraint (MPEC). EMIS-AE provides a predictive model to be trained for estimating the system-wide revenues for each technology type across energy, ancillary services and capacity markets given the amount of installed capacity on the grid. The profit maximization investment problem for each GENCO is solved using a global search algorithm, which uses the predictive model to evaluate the objective function. To solve for the strategic equilibrium, each GENCO’s problem is plugged into a diagonalization algorithm that is generally used in multi-leader, single-follower bi-level problems.", + "laborHours": 1520.0, + "languages": [ + "Julia", + "Python" + ], + "name": "EMISApproximateEquilibrium.jl [SWR-19-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMISApproximateEquilibrium.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-10-26", + "metadataLastUpdated": "2023-04-24" + }, + "description": "In support of the Electricity Markets and Investment Suite, this repository hold data set used in the following julia packages EMISApproximateEquilibrium.jl, EMISCompetitiveEquilibrium.jl, and EMISAgentSimulation.jl.", + "laborHours": 137073.6, + "languages": [ + "HTML" + ], + "name": "EMIS-Data [SWR-19-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMIS-Data", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-10-26", + "metadataLastUpdated": "2023-04-24" + }, + "description": "The Electricity Markets Investment Suite Agent-based Simulation (EMIS-AS) model is an agent-based model developed at NREL for simulating annual investment and retirement decisions of heterogeneous investors in the electricity sector. EMIS-AS is designed to capture the evolution of the electricity generation portfolio resulting from the interactions of heterogeneous investors under different policy and market designs. 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SAND2019-15220 M\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 7995.2, + "languages": [ + "C#" + ], + "name": "Peak Map", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/Peak-Map/blob/master/PeakMap/LICENSE.rtf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Peak-Map", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-07-29" + }, + "description": "This is software in Python that simulates the quantum approximate optimization algorithm (QAOA) as described in https://arxiv.org/abs/1411.4028. The software has customization that speeds up simulation and provides interface to the Rapid Optimization Library (ROL) developed at Sandia. SAND2019-8935 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 820.8, + "languages": [ + "Python" + ], + "name": "Quantum Approximate Optimization Algorithm in Python", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyQAOA", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-08-07" + }, + "description": "ARG is a computational simulation tool. It generates user-configurable reports, including graphs and images, from user data in various formats.SAND2019-9525 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 10366.4, + "languages": [ + "TeX", + "Perl", + "Python" + ], + "name": "Automatic Report Generator (ARG)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/arg", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-07-30" + }, + "description": "TestSNAP is a stand-alone prototype of the SNAP force kernel used in the LAMMPS molecular dynamics code. It contains synthetic input data (neighbor atom positions) and reference output data (forces on atoms) for several different SNAP models. The prototype performs the force calculation repeatedly, checking the results against the reference data. At the end it reports the grind time [msec/atomstep] and RMS force error [eV/A]. This allows performance experts to quickly test new hardware and software strategies, obtain a realistic performance estimate and verify that the computation was performed correctly. SAND2019-12243 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 181153.6, + "languages": [ + "C" + ], + "name": "TestSNAP", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TestSNAP", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-08-07" + }, + "description": "COEK (C++ Optimization Expression Kernel) is a C++ library that supports the expression and manipulation of algebraic expressions commonly used in optimization applications. COEK. Supports several mechanisms for defining and managing expressions and performing automatic differentiation. COEK also includes low-level interfaces for defining optimization models and interfacing with optimization solvers.SAND2019-14491 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 98070.4, + "languages": [ + "C++", + "Cmake", + "C", + "AMPL", + "NMODL", + "Python" + ], + "name": "COEK", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/coek", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-09-20" + }, + "description": "PAO supports the formulation and analysis of mathematical models for complex optimization applications. This capability is commonly associated with algebraic modeling languages (AMLs), which support the description and analysis of mathematical models with a high-level language. PAO is derived from the Pyomo subpackage pyomo.bilevel, which has been deprecated. PAO supports the formulation and solution of optimization models that explicitly represent adversarial behavior. This includes variances of bilevel programming, including methods that represent challenging problems with discrete decisions and uncertain model parameters.", + "laborHours": 12357.6, + "languages": [ + "Python" + ], + "name": "PAO", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pao", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-09-18" + }, + "description": "Diventi provides a write optimized index of network logs such as netflow or zeek. The program will ingest various network traffic logs (zeek connection logs or NetflowV5, v9 or IPFix logs) and index each IP address and time of its activity. This database can then be queried for timely tracking of network activity. It currently uses the ft-index library from Percona but is adaptable to any key-value store that supports the Berkeley DB api.SAND2019-15037 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 6642.4, + "languages": [ + "C++", + "Makefile", + "Python" + ], + "name": "Diventi", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/opendiventi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2021-03-05" + }, + "description": "Semi-supervised machine learning via consistency regularization", + "laborHours": 820.8, + "languages": [], + "name": "Shadow", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/shadow", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/shadow", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-08-07" + }, + "description": "POEK (Python Optimization Expression Kernel) is a Python library that supports the expression and manipulation of algebraic expressions commonly used in optimization applications. POEK interfaces with the COEK library to support fast methods for defining and managing expressions and performing automatic differentiation. POEK also interfaces with COEK to directly interface with optimization solvers (i.e. without relying on file I/O). SAND2019-14492 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 98070.4, + "languages": [ + "C++", + "C", + "CMake", + "AMPL", + "NMODL", + "Python" + ], + "name": "POEK", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/coek", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "savaraa@ornl.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2020-10-30" + }, + "description": "There is a need to provide a way for dev-users (Scientists, Engineers, and other Software Developers) to get credit (citations) when they contribute to an important software package - particularly a large package that is already established. Various solutions (including cross package) solutions do exist, but a simple standard format that can work between multiple packages and multiple languages in a modular way is not widely available. \n\nCiteSoft_py is a python implementation of CiteSoft. CiteSoft is a plain text standard consisting of a format and a protocol that exports the citations for the end-users for whichever softwares they have used. CiteSoft has been designed so that software dev-users can rely upon it regardless of coding language or platform, and even for cases where multiple codes are working in a coupled manner. The CiteSoft_py implementation includes python decorators to make wrappers for facile use.\n\nThe purpose is that when dev-users (scientists, engineers and professional programmers) contribute to a collaborative software project, that the appropriate citations (e.g., journal article, conference proceeding) are provided to the end-user. The end-user does not need to know how to use a command line interface, API, etc. ", + "laborHours": 258.4, + "languages": [ + "Python" + ], + "name": "CiteSoft_Py", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdityaSavara/CiteSoft_py", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Spitfire is a Python and C++ code for solving canonical flame structure problems to build tabulated chemistry models for the simulation of large-scale fires. Spitfire is a modular software with performance critical code written in C++, abstract numerical methods provided in Python, and chemistry tabulation techniques made convenient for high-level use by non-expert users. It facilitates both high-level usage and novel research in tabulated chemistry approaches. SAND2019-11791 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 60739.2, + "languages": [ + "C++", + "Cython", + "Python" + ], + "name": "Spitfire", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Spitfire", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2020-11-05" + }, + "description": "Tools for extracting and viewing information from zip archives. Simply extracts and displays zip file metadata in a format convenient for analysts.SAND2020-0168 M\n", + "laborHours": 364.8, + "languages": [ + "Python" + ], + "name": "sandialabs/xyz", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/xyz", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.20181129" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2024-07-29" + }, + "description": "miniGAN is a python-based machine learning proxy application for generative adversarial networks, developed through the Exascale Computing Project's (ECP) ExaLearn project. It will be included in the main ECP proxy application and the machine learning proxy application suite. It is a proxy for ECP cosmological(CosmoFlow, ExaGAN) and wind energy(ExaWind) applications. miniGAN will be distributed to ECP hardware vendors as part of hardware codesign. miniGAN uses the Numpy/PyTorch/TensorFlow/Keras/Horovod frameworks and libraries. It also relies on the Kokkos and Kokkos-Kernels packages developed here at Sandia Labs. SAND2020-2038 M\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 516.8, + "languages": [ + "Shell", + "Python" + ], + "name": "miniGAN: a proxy application for generative adversarial networks", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2024-07-29" + }, + "description": "The Java Software Extensibility Library provides tools that help Java software developers produce flexible and extensible Java applications. The major components include a Plugin Library and a Polymorphic Map data structure. The Plugin Library provides developers with a Plugin Registry and a standard pattern for designing, versioning, registering, retrieving, and annotating plugins. It also enables advanced capabilities such as loading plugins at runtime, and creating/loading encrypted plugin packages. The Polymorphic Map data structure facilitates the storage and retrieval of objects of varying types within a single data structure; while maintaining type safety. The library also provides a standard design pattern for producing application-specific \"Domain Maps\" and \"Closed Domain Maps\".SAND2020-3816 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 5715.2, + "languages": [ + "Java" + ], + "name": "Java Software Extensibility Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/jsel", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.9.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2024-08-07" + }, + "description": "Robust Phase Estimation (RPE) is a quantum algorithm to determine the relative phases of eigenstates of a unitary operator. This code implements the classical portion of the RPE algorithm, useful both in simulation (e.g., Sandia's pyGSTi or IBM's Qiskit simulators) and on actual quantum hardware (e.g., IBM's Qiskit Quantum Experience). It additionally implements improvements in these dependent software packages, for both required core function of the RPE and improved usability. SAND2020-12547 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 91.2, + "languages": [ + "Python" + ], + "name": "Python Robust Phase Estimation (PyRPE)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyRPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2024-09-18" + }, + "description": "A set of subroutines that interact with an existing computer program, Quantum Espresso (QE), that takes a set of electronic orbitals from QE and propagates them forward in time in response to a number of perturbations. These perturbations include the motion of ions and a wide spectrum of applied electromagnetic fields (e.g., static magnetic fields, slowly-varying electric fields, x-rays, etc.). From the time evolution of the electronic orbitals comes time-varying values of physical observables like the electronic charge and current densities and atomic forces. These are further post-processed to yield properties of interest like stopping powers, conductivities, and the dynamic structure factor. The electronic orbitals are described in a plane wave basis and the equations of motion are carried out using a unitary or approximately unitary time propagation algorithm. Related work will include subroutines for interfacing this capability, as well as others that already exist within QE, with a fork of QE that is more extensible and modular.SAND2019-12611 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1519589.6, + "languages": [ + "Shell", + "HTML", + "C", + "Roff", + "Fortran", + "PostScript" + ], + "name": "Real-time time-dependent density functional theory in Quantum Espresso and related codes", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/qe-rt-tddft", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "mohror1@llnl.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-01" + }, + "description": "Workflow I/O Emulation Framework", + "laborHours": 4529.6, + "languages": [ + "C", + "C++", + "Perl", + "C", + "python" + ], + "name": "LLNL/Wemul", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/wemul", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2025-02-13" + }, + "description": "GentenMPI is software to compute low-rank approximations of sparse data tensors. These methods are often used for unsupervised machine learning to find significant properties of sparse, unstructured data sets. GentenMPI uses the same algorithms that are available in Sandia's open-source codes TensorToolbox and Genten, but GentenMPI provides distributed memory implementations of these algorithms using infrastructure from Sandia's open-source Trilinos framework. GentenMPI includes an implementation CP-ALS (canonical polyadic decomposition via alternating least squares optimization, first published in 1970 by Carroll & Chang and Harshman); its distributed memory implementation uses Trilinos' Map-based distribution of data to processors and Trilinos' communication operations designed for sparse matrix-vector multiplication. Its performance is comparable to other open-source CP-ALS implementations (e.g., the SPLATT tool of Smith and Karypis). GentenMPI also include a distributed memory implementation of GCP-SGD (generalized canonical polyadic decomposition via stochastic gradient descent, first published in 2019 by Hong, Kolda and Deursch); the implementation closely follows that in TensorToolbox, and exploits a block-based data distribution to perform sampling in parallel. GentenMPI is written in C++ and relies on the MPI (Message Passing Interface) library available on most distributed memory computers. SAND2020-12648 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 12448.8, + "languages": [ + "C++", + "Cmake" + ], + "name": "GentenMPI", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GentenMPI", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-04" + }, + "description": "This is a small but pretty quiz application written in Python for Flask that is meant to be easy to understand for new users of Flask, but not necessarily optimized for performance or security.SAND2020-12216 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 501.6, + "languages": [], + "name": "flasquiz", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/flasquiz", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-12" + }, + "description": "The SEMS Pipeline Framework Infrastructure (SPiFI) library is a collection of utilities that simplify the development of Continuous Integration (CI) / Continuous Delivery (CD) pipelines within the Jenkins testing application.\nThe goal of SPiFI is to provide a layer of convenience functions for common tasks a pipeline developer will need to implement, such as timeouts, automatic retries, dry-run testing, concurrent test launching, results aggregation, and email notifications to accelerate pipeline development. SPiFI enables the DevOPs engineer to focus more on what their pipeline should do rather than how to implement certain details within the restricted programming environment provided by the Jenkins application.SAND2020-12550 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 8664.0, + "languages": [ + "Groovy" + ], + "name": "SEMS Pipeline Framework Infrastructure", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SPiFI", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-13" + }, + "description": "Set of Matlab scripts to investigate properties of IMEX time stepping methods. Scripts include discretization of a system of linearized equations. One script plots numerical dispersion against analytical dispersion of the system. Another set of scripts uses the system to break it into stiff and non stiff part to investigate stability of Implicit-Explicit Runge-Kutta methods. \n\nScripts are based on \nThuburn, J. and Woollings, T. J., Vertical Discretizations for Compressible Euler Equation Atmospheric Models Giving Optimal Representation of Normal Modes , 2005 and\nLock, S.-J. and Wood, N. and Weller, H., Numerical analyses of Runge-Kutta implicit-explicit schemes for horizontally explicit, vertically implicit solutions of atmospheric models, 2014\nexpanding ideas from these two papers.\n\nScripts are used to develop IMEX schemes. SAND2020-12594 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 668.8, + "languages": [ + "MATLAB" + ], + "name": "sta-imex (scripts to investigate stability of IMEX methods)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/sta-imex", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.01" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-03" + }, + "description": "This is software lets one explore the data released as part of the COVID-19 Open Research Dataset Challenge. It downloads and analyzes the natural language text of the data set and then creates a 2D visualization that can be used to explore it. SAND2020-12185 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 152.0, + "languages": [], + "name": "Galen View", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/galen-view/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/galen-view", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2021-03-30" + }, + "description": "WeightedAFL (WAFL) is an improvement to open source fuzzer, American Fuzzy Lop (AFL). Fuzzers modify input to target programs in order to produce crashes and other unintended output in those target programs. WAFL integrates directly with AFL to determine offsets within a buffer that will improve performance metrics. WAFL uses various machine learning techniques to learn these offsets. WAFL also provides a novel software engineering solution to integrate with AFL and allows contributors to quickly write and test algorithms in python. SAND2020-12546 O\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [], + "name": "WeightedAFL", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/sandialabs/wafl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This MATLAB pseudocode perform multivariate curve resolution (MCR) using PCA scores & loadings of data as inputs. It employs rigorous least squares equality and inequality constraints for all elements in the solution factor matrices. It also can be used to perform nonnegative matrix factorization.\nSAND2020-12650 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 91.2, + "languages": [ + "MATLAB" + ], + "name": "Multivariate Curve Resolution (MCR) using Principal Components Inputs and Rigorous Equality and Inequality Constraints", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mcr", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-08-07" + }, + "description": "This is a method of performing trilinear analysis on large data sets using a modification of the PARAFAC-ALS algorithm. It iteratively decomposes the data matrix into a core matrix and three loading matrices based on the Tucker1 model. The algorithm is particularly useful for data sets that are too large to upload into a computer?s main memory. While the performance advantage in utilizing our algorithm is dependent on the number of data elements and dimensions of the data array, we have seen a significant performance improvement over operating PARAFAC-ALS on the full data set.\nSAND2020-12649 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 60.8, + "languages": [ + "MATLAB" + ], + "name": "PARAFAC_T1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PARAFAC_T1", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-07-29" + }, + "description": "Code developed in conjunction with a research paper. This code demonstrates how to identify static graph snapshots from a stream of communication events. A second, related code generates simulated communication events with known split moments for accuracy testing.SAND2020-12245 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 653.6, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "EASEE: Edge Advertisements into Snapshots using Evolving Expectations", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Easee", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-01" + }, + "description": "Prescient is a software package for simulating electricity grid (power systems) operations, under both nominal and extreme event conditions. Core functionality includes discrete event simulation, commitment and dispatch optimization, probabilistic scenario construction, and reporting/visualization. SAND2020-0169 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 18620.0, + "languages": [], + "name": "Prescient", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/grid-parity-exchange/Prescient", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Experiment scripts and analysis tools created for the QUE LDRD. SAND2020-12250 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 866.4, + "languages": [ + "Shell", + "Python" + ], + "name": "QUE LDRD Tools", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/que-ldrd-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-09-18" + }, + "description": "Sandia's ns-3 contributions are modifications to the open source ns-3 network simulator that enable simulation speedup. One improvement, for example, removes the need for simulating the transmission and receipt of packets between nodes that are too distant to actually be able to communicate. In large-scale simulations this optimization has shown significant gains in performance. Additional contributions will pave the way for parallel discrete simulation (PDES) in ns-3. SAND2020-12456 O\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 891936.0, + "languages": [ + "C++", + "Python", + "Click", + "C", + "MATLAB", + "Makefile" + ], + "name": "Robust Event Simulation Variants Endowed to Ns-3 for General Exploration", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/kmsim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-07-23" + }, + "description": "fbWecCntrl is set of MATLAB functions and scripts demonstrating a causal impedance matching approach to wave energy converter (WEC) control design. SAND2020-12219 M\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1246.4, + "languages": [ + "MATLAB", + "Python" + ], + "name": "fbWecCntrl", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fbWecCntrl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-05" + }, + "description": "This pair style will enable molecular dynamics simulations of hydrogen interaction with Fe-C steels. No such simulations are possible without such a pair style. This is significant because Fe-C steels are the most commonly used steels and improving their resistance to hydrogen embrittlement has attracted wide interests. SAND2020-12230 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1281025.6, + "languages": [ + "C++" + ], + "name": "New pair style for molecular dynamics package LAMMPS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lammps/lammps", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-09" + }, + "description": "This will be a fork of the LLVM project which will contain enhancements to help Kokkos users. It will also wrap in contributions from LANL and Argonne, that we might also give our users access to that work. We will eventually try to upstream (give back to LLVM) any changes we make, if possible. SAND2020-12447 O\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 12563271.2, + "languages": [ + "C++" + ], + "name": "Kokkos Clang", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/llvm-project", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "9.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-04" + }, + "description": "Torchbraid is a python package designed for interaction with the PyTorch library. It enables training of neural networks in a layer-parallel fashion.SAND2020-12228 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 972.8, + "languages": [ + "Python" + ], + "name": "TorchBraid", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The project that developed this is unclassified, with the mandate to produce open source code. This code computes the hitting time moments of a graph using a linear algebra configuration. The goal of this work is to explore the performance capabilities of the Chapel programming language. Toward that end, we generate random adjacency matrices which represent a random graph. The code can also read in an adjacency matrix from a file. The main computation is the Conjugate Gradient method.SAND2020-12651 M.\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [], + "name": "Computation of graph hitting time moments; Chapel code implementation.", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/htm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2021-01-13" + }, + "description": "Supervised machine learning is the process of using past experience to predict the future. \"Ensembles\" are a machine-learning meta-method that can be applied to most machine learning algorithms. Ensembles generally greatly improve accuracy, reduce or remove most of the design issues presented by machine learning, and are admirably suited to parallel and distributed computation. The Avatar Tools codes are an implementation of ensembles specifically for decision trees. Some features that distinguish Avatar Tools from other \"ensembles for decision trees\" codes are: (1) Does the bookkeeping necessary for out of bag (OOB) validation. (2) Can use OOB validation to automatically determine optimal ensemble size. (3) Provides an MPI-based parallel implementation, for distributed operation. (4) Provides convenient tools for cross-validation, to assess the accuracy provided by a training set. SAND2020-3858 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C", + "Python" + ], + "name": "Avatar Tools", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/avatar", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-03" + }, + "description": "PFLOTRAN is a GNU LGPL licensed code that simulates single phase water and multiphase (air, co2, water) flow, energy transport, geochemical reaction and biological reaction in the earth's subsurface environment. The problem may be discretized on structured and unstructured grids. The code is designed to run in parallel on supercomputers and leverages the open source PETSc library for solvers and data structures and open source HDF5 for binary file I/O. See www.pflotran.org and/or doc-dev.pflotran.org for further information. SAND2020-12161 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 281686.4, + "languages": [ + "Fortran", + "Python" + ], + "name": "PFLOTRAN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "3.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This is a wrapper around the LANL NJOY-2016 code that interfaces with extended code capabilities and minor modification of the LANL NJOY-2016 code that supports modeling radiation damage to materials. The NJOY Nuclear Data Processing System is a modular computer code designed to read evaluated data in ENDF format, transform the data in various ways, and output the results as libraries designed to be used in various applications. The wrapper provided here permits Sandia-specific control parameters to be used in the input data file. The modifications incorporated here enhance the ability of NJOY to address material damage response functions for many materials, e.g. to include the NRT and arc-dpa forms of the damage energy in addition to the default NJOY-2016 implementation of the sharp-threshold Kinchin-Pease threshold energy treatment. All of the modifications provided here are being made available to the GitHub-based NJOY-2016 code. As useful enhancements found here are incorporated into the baseline NJOY-2016 code, they will be eliminated from this version so as to maintain our compatibility with the baseline NJOY-2016 code. SAND2020-13060 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA00035", + "laborHours": 79344.0, + "languages": [ + "Fortran", + "Postscript", + "LSL", + "CMake", + "Makefile", + "Python" + ], + "name": "SNL-NJOY-2016", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/NJOY2016", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-07-29" + }, + "description": "Jaqal-pup (Jaqal Programming Utilities Project) is a high-level Python metaprogramming interface for Jaqal, a quantum programming language for near-term quantum hardware (see https://arxiv.org/abs/2003.09382 for a description of Jaqal). In addition to parsing and writing out Jaqal programs, it includes the ability to read in and write out quantum programs in other languages and frameworks, e.g. Qiskit (IBM), Quil (Rigetti), Cirq (Google), Q# (Microsoft), ProjectQ (ETH Zurich), and tket (Cambridge Quantum Computing). It implements a gate scheduler, an emulator of a small-scale quantum computer programmed using Jaqal, and tie-ins for other simulation back-ends. SAND2020-12710 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 5548.0, + "languages": [ + "Python", + "Shell" + ], + "name": "JaqalPaq v.1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/JaqalPaq", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-09-18" + }, + "description": "Sphynx is a software library for parallel graph partitioning and load balancing. It partitions a set of vertices in a graph such that the vertex parts are balanced, and the edge cut is approximately minimized. The primary use case is to partition a computational graph into smaller tasks that can be assigned to processors (cores) for efficient parallel computing. Sphynx is based on the Trilinos scientific computing toolkit so can run on both multi-CPU and multi-GPU systems. SAND2020-12183 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 8344830.4, + "languages": [], + "name": "Sphynx", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-09-18" + }, + "description": "The Advanced Tri-lab Software Environment (ATSE) is an effort to build an open, modular, extensible, community-engaged, and vendor-adaptable software ecosystem that enables the prototyping of new technologies for improving the ASC computing environment. The initial target for ATSE is to accelerate the maturity of the Arm ecosystem for supporting ASC computing and the high-performance computing community more broadly. ATSE provides an integrated and optimized software stack that includes: 1) Application development environment and libraries including compilers, math libraries, tools, MPI, and OpenMP, 2) Low-level system software including optimized Linux, network stack, file systems, containers, and virtual machines, 3) Job scheduling and management including workload manager, application launcher, and user tools, and 4) System administration and management tools supporting booting, monitoring, and operating system image management. SAND2020-12377 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1748.0, + "languages": [ + "C++", + "Dockerfile", + "Shell", + "Roff", + "BitBake", + "Python" + ], + "name": "Advanced Tri-lab Software Environment (ATSE)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/atse", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2.5" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-02", + "metadataLastUpdated": "2020-11-04" + }, + "description": "The Sandia Injury Biomechanics Laboratory (SIBL) Library is a collection of scripts and tools used to preprocess, process, and postprocess data for analysis of injury biomechanics data. SAND2020-3663 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 54081.6, + "languages": [ + "Python", + "Python" + ], + "name": "Sandia Injury Biomechanics Laboratory Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sibl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "vossjm@ornl.gov" + }, + "date": { + "created": "2020-11-03", + "metadataLastUpdated": "2020-11-03" + }, + "description": "Extensible diskless booting dracut module", + "laborHours": 1672.0, + "languages": [ + "Bash" + ], + "name": "Anchor", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/anchor", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "velliquettet@ornl.gov" + }, + "date": { + "created": "2020-11-03", + "metadataLastUpdated": "2021-02-08" + }, + "description": "The File-level Metadata (FLMD) parser is a lightweight python script that can produce a summary of fields based on column headers within a Comma-separated Values (CSV) file. The script enables a way to extract certain metadata fields from CSV data files. An optional configuration file can be used to select specific column headers to extract a smaller subset of values. The script can be used on a single file, or it can be given a directory to process groups of files in bulk. The FLMD parser outputs the metadata as a JSON and can be configured to updated the source file or produce an external companion file.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ESS-DIVE File Level Metadata Extractor", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/ngee-arctic/ess-dive-meta", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/ngee-arctic/ess-dive-meta", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-04", + "metadataLastUpdated": "2024-09-18" + }, + "description": "This code solves a steady state heat equation problem on a wire with random walks implemented using a spiking neural algorithm. SAND2020-12194 M", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "Heat Equation Neural Simulation", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HeatEquationNeuralSimulation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "rusu1@llnl.gov" + }, + "date": { + "created": "2020-11-04", + "metadataLastUpdated": "2020-11-04" + }, + "description": "Agent Based Modeling and Reinforcement Learning", + "laborHours": 10138.4, + "languages": [ + "Python" + ], + "name": "LLNL/Admiral", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Admiral", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-11-05", + "metadataLastUpdated": "2020-11-06" + }, + "description": "VOLTTRON Distributed Control System Platform VOLTTRON™ delivers an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls.", + "laborHours": 0.0, + "languages": [], + "name": "VOLTTRON Version 8", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron/releases/tag/8.0rc1", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "8" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-11-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Cybersecurity Framework Tool is a web-based tool that provides five (5) concurrent and continuous functions to identify, detect, protect, respond and recover from cyber security threats to critical infrastructure.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Cybersecurity Framework Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-09", + "metadataLastUpdated": "2020-11-09" + }, + "description": "A repository of code that transforms packets into a vectorized representation to be used for classification of malicious/benign packets. SAND2019-13500 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1246.4, + "languages": [ + "C++" + ], + "name": "Packet2Vec", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/packet2vec", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-09", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Parapint is a Python package for parallel solution of dynamic optimization problems. SAND2020-12446 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 3359.2, + "languages": [ + "Python" + ], + "name": "Parapint", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/parapint", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-09", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The code that was developed is called SAMM (Semi-Analytic MagLIF Model). In 2015, McBride and Slutz published all of the equations that are solved by the code in the original SAMM paper: R. D. McBride and S. A. Slutz, ?A semi-analytic model of magnetized liner inertial fusion?, Phys. Plasmas 22, 052708 (2015); http://doi.org/10.1063/1.4918953. The SAMM code is now implemented in both the MATLAB and Python programming languages. Students from multiple universities have requested copies of the code so that they can become more familiar with the MagLIF concept. We would like to seek an open-source solution. There is no market value to this code, as there are plenty of more sophisticated simulation codes already available; SAMM is merely a simplified model that is purely for educational purposes. In fact, at least one graduate student (from the University of California, San Diego) has already implemented and published his own modified version of the model: J. Narkis, H. U. Rahman, J. C. Valenzuela, F. Conti, R. D. McBride, D. Venosa, and F. N. Beg, ?A semi-analytic model of gas-puff liner-on-target magneto-inertial fusion?, Phys. Plasmas 26, 032708 (2019); https://doi.org/10.1063/1.5086056. SAND2020-12244 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 4438.4, + "languages": [ + "Python" + ], + "name": "Semi-analytic model of magnetized liner inertial fusion", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pysamm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-11-09", + "metadataLastUpdated": "2022-01-05" + }, + "description": "QTensor is a quantum circuit simulator designed to run efficiently in parallel mode on large supercomputers. It is based on the tensor network representation of quantum circuits. The simulator is flexible and agnostic to both the connectivity map of the quantum device and the types of gates used in the circuit.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "QTENSOR", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-11-09", + "metadataLastUpdated": "2022-01-05" + }, + "description": "A methodology and tool for computing the benefits and costs of Advanced Distribution Management Systems (DMS) for Grid Modernization. It suggests an approach for monetizing the \"functional\" benefits, expressed in non-monetary terms, such as System Average Interruption Duration Index/System Average Interruption Frequency Index (SAIDI/SAIFI) reduction and improved efficiency, using commonly available technical and financial parameters. It offers a model for individual utilities to determine the estimated costs and benefits using their own specific data. Where actual utility-specific data is not available, industry default values are offered. The model uses discounted cash flow (DCF) analysis to evaluate the economic justification for an investment in DMS.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "DVCalc", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Reduced-order Models (ROMs). ROMs are \"compressed\" approximations of high-fidelity computational models. Implementing ROM methods in production codes is typically intrusive, i.e. the native codes must be adapted and modified, with individual ROM methods reimplemented in every application code. This clearly constitutes an obstacle to users who want to use ROMs. To address this, we have developed Pressio, which is a C++ header-only ROM library that can be used by an application code in a non-intrusive fashion. The main objectives behind the design of Pressio are: (a) support for general computational models (data structures, PDE types); (b) heterogeneous hardware (CPU, GPU); (c) performance; and (d) extensibility. Using metaprogramming techniques, Pressio detects and leverages the application?s native linear algebra data structures (e.g. vector and matrix) to run the ROM methods. The application only needs to expose the velocity vector and Jacobian matrix via an adapter class. Pressio checks at compile time that the target application meets the correct API. The library is structured in several modular packages including (a) non-linear least-square solvers (e.g. Gauss-Newton with and without line-search); (b) singular value decomposition (for the computation of the ROM generalized coordinates) and (c) algebraic hyper-reduction.SAND2019-5878 M", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 49354.4, + "languages": [ + "C++" + ], + "name": "Pressio", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2021-10-01" + }, + "description": "This code is comprised of example problems to show implementation details of our SCITECH 2021 paper :Open-Source, Object-Oriented, Multi-Phase Pseudospectral Optimization Using Pyomo.\" Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2020-13973", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Pyomo Optimization Example Problems v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyomo_optimization_example_problems", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2022-04-13" + }, + "description": "SAND2020-13696 M BigDNA takes a user input fast DNA sequence and outputs overlapping long PCR primers for Gibson Assembly. The software can design primers that remove gene products, insert new gene products, or completely circularize long DNAs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Perl", + "Python" + ], + "name": "BigDNA", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/bigdna", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2024-08-07" + }, + "description": "IIA is a solver for optimizing integer matrix problems Ax=b. It was developed to decide the number of mesh edges on model curves (intervals) for quad and hex meshing. Meshing schemes impose constraints ranging from the mild requirement (i.e. that any quad mesh must have an even number of edges on its boundary) to structured mapped patches where opposite sides of a rectangle must have exactly equal numbers of edges. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.\nSAND2020-13618 M", + "laborHours": 2004074.4, + "languages": [ + "C++" + ], + "name": "IIA Incremental Interval Assignment", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IntervalAssignment", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2020-11-10" + }, + "description": "Software application: Sandia RPM Lane Simulator.\nSimulates Rapiscan radiation portal monitors and network cameras that are in use in the NNSA Nuclear Smuggling Detection and Deterrence (NSDD) program. SAND2019-3741 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 28728.0, + "languages": [], + "name": "Sandia RPM Lane Simulator ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SRLS", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2020-11-18" + }, + "description": "Submission-beluga is an open-source optimal control software that uses publicly available indirect methods to model inequality constraints at boundaries. This release of beluga introduces a method known as UTM, modified handling of constraints to support the UTM method, and includes bug fixes and related requirements changes.SAND2020-12847 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 20337.6, + "languages": [], + "name": "beluga", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2024-09-12" + }, + "description": "The Verdict code verifies the correctness of a finite element mesh stored in the Exodus II fine format. Verdict calculates multiple quality metrics for each individual element, verifies local and global connectivity, analyzes interfaces between element blocks, predicts the probability topology of the mesh, and prints out any problems discovered. SAND2019-7026 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 10138.4, + "languages": [ + "C++", + "CMake" + ], + "name": "Verdict", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/verdict", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2024-08-07" + }, + "description": "This work presents a method of performing PARAFAC2 factorization of a three-way data using a compact representation of the data. The data are decomposed into a core matrix and sets of orthogonal loading matrices. The algorithm is particularly useful for very large data sets and essentially permits imposition of nonnegativity in all three modes. SAND2019-10097 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 91.2, + "languages": [ + "MATLAB" + ], + "name": "CANDELINC2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CANDELINC2", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2024-08-07" + }, + "description": "The Chemical Asset Tracker, CAT, is a web-based (browser) application for tracking chemical inventories. The application records information about stored chemicals from user input (via the keyboard, barcode readers, or mobile device) and stores that information into a database. A tiered user login controls access to functions in the application. A user interface is provided that allows users to search the database and update data in the database. SAND2019-7525 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 194772.8, + "languages": [ + "C#", + "Python" + ], + "name": "Chemical Asset Tracker (CAT)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ChemicalAssetTracker", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2021-02-09" + }, + "description": "This software is extended from HPX, open source software (the copyright belongs to Louisiana State University). SAND2019-5457 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.\n", + "laborHours": 696965.6, + "languages": [], + "name": "HPXr, HPX with Resilience Extension", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/STEllAR-GROUP/hpx/blob/master/LICENSE_1_0.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/STEllAR-GROUP/hpx", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2024-08-07" + }, + "description": "Principal component analysis (PCA) is arguably the most popular tool in multivariate exploratory data analysis. We consider the question of how to handle heterogeneous variables that include continuous, binary, and ordinal. In the probabilistic interpretation of low-rank PCA, the data has a normal multivariate distribution and, therefore, normal marginal distributions for each column. If some marginals are continuous but not normal, the semiparametric copula-based principal component analysis (COCA) method is an alternative to PCA that combines a Gaussian copula with nonparametric marginals. If some marginals are discrete or semi-continuous, we present a new extended PCA (XPCA) method that also uses a Gaussian copula and nonparametric marginals and accounts for discrete variables in the likelihood calculation by integrating over appropriate intervals. Like PCA, the factors produced by XPCA can be used to find latent structure in data, build predictive models, and perform dimensionality reduction. We implement the new model, XPCA, and its ancestors PCA and COCA in both R and Python. This software provides implementations of XPCA, COCA, and probabilistic PCA in both R and Python. XPCA is written in arXiv report https://arxiv.org/abs/1808.07510. SAND2019-10591 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 425.6, + "languages": [ + "Python" + ], + "name": "XPCA -Python Implementation", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/xpca", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2020-11-11" + }, + "description": "Gulliver is a C# utility package and library engineered for the manipulation of arbitrary sized byte arrays accounting for appropriate endianness and jagged byte length. Functionality includes the as previously unsupported standard set of boolean algebraic operations, bitwise shifting, and unsigned endian aware mathematical addition, subtraction, and comparison. Gulliver exists to free developers from managing byte ordering and operations and the low level as was previously required by the standard C# language distributions.SAND2019-8990 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.\n", + "laborHours": 3724.0, + "languages": [ + "C++" + ], + "name": "Gulliver", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Gulliver", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "facklerpw@ornl.gov" + }, + "date": { + "created": "2020-11-17", + "metadataLastUpdated": "2020-11-17" + }, + "description": "Custom spatial subdivision of N-dimensional lattice region in GPU memory. An extension of the method of a hyper-octree is used to allow for arbitrary subdivision ratios in each dimension. In addition, the decision to refine (or select) a given sub-region is based on a user-provided callback, allowing for arbitrary refinement domains to be expressed either geometrically or programmatically.", + "laborHours": 2432.0, + "languages": [ + "C++" + ], + "name": "Parallel Lattice Subpaving Map (plsm)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-Fusion/plsm", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-11-18", + "metadataLastUpdated": "2020-11-20" + }, + "description": "SEEDling is intended to simplify the merging of multiple data sources prior to importing into the SEED platform. Geographic information about buildings and taxlots is often obtained from various data sources, and the process of synthesizing this information for many buildings across a city can be burdensome for city data managers. SEEDling uses GIS tools to automate and simplify this process, as well as apply criteria for SEED inclusion (ex: sqft > 50k) and assign UBIDs, to create records that can be easily imported into the SEED platform.", + "laborHours": 87628.0, + "languages": [], + "name": "SEEDling", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SEED-platform/seedling", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-20", + "metadataLastUpdated": "2020-11-30" + }, + "description": "A-PRIME, is a collection of scripts designed to provide Accelerated Climate Model for Energy (ACME) model developers and analysts with a variety of analysis of the model needed to determine if the model is producing the desired results, depending on the goals of the simulation. The software is csh scripts based at the top level to enable scientist to provide the input parameters. Within the scripts, the csh scripts calls code to perform the postprocessing of the raw data analysis and create plots for visual assessment.", + "laborHours": 5107.2, + "languages": [ + "Csh; python/2.7.3; bash; ncl/6.3.0; nco/4.6.4" + ], + "name": "ACME Priority Metrics (A-PRIME)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/a-prime", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "Simulations and analyses of data from hexagonally pixelated detectors require conversions from a Cartesian coordinate system to and from a hexagonal pixel index. This software builds and indexes the detector geometry, calculates neighbors and coordinate system conversions, and provides a framework for plotting analysis results.", + "laborHours": 440.8, + "languages": [ + "C++;gcc;4.8.4" + ], + "name": "HexFinder", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/leahbroussard/HexFinder/-/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/leahbroussard/HexFinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The Workbench Analysis Sequence Processor (WASP) was developed to streamline lexing, parsing, access, validation, and analysis of ascii text files.", + "laborHours": 81426.4, + "languages": [], + "name": "Workbench Analysis Sequence Processor", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/neams-workbench/wasp/-/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/neams-workbench/wasp", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The J-integral vs. crack growth resistance curve (J-R curve) is a useful tool for evaluating material fracture toughness in the ductile condition. A widely accepted practice for conducting tests to obtain J-R curves is ASTM standard E1820, in which the normalization method was introduced as an alternative method for determining the J-R curve. The normalization method requires solely force-displacement data, together with initial and final crack size measurements from a specimen to derive the J-R curve. Because of the elimination of the compliance measurement, the normalization method significantly simplifies testing requirements to obtain J-R curve. Despite these advantages, the analysis procedures of the normalization method are quite complicated to follow, which may limit the wide application of this method. To address this, we have developed a software with user-friendly graphic interface to perform automated normalization analysis. Any users, even without detailed knowledge of the normalization analysis, can use this software to derive J-R curves based on the ASTM E1820 normalization method.", + "laborHours": 4301.6, + "languages": [ + "MATLAB" + ], + "name": "Automated J-R Curve Analysis Based on the ASTM E1820 Normalization Method", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/xc8/ANJR", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/xc8/ANJR", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "Developers at ORNL explored how a deep learning (DL) approach based on hierarchical attention networks (HANs) can improve model performance for multiple information extraction tasks from unstructured cancer pathology reports compared to conventional methods that do not sufficiently capture syntactic and semantic contexts from free-text documents. The HAN was implemented for 2 information extraction tasks: (1) primary site, matched to 12 International Classification of Diseases for Oncology topography codes (7 breast, 5 lung primary sites), and (2) histological grade classification, matched to G1–G4. Our results demonstrate that for both information tasks, HAN performed significantly better compared to the conventional ML and DL techniques.", + "laborHours": 501.6, + "languages": [ + "Python 2.7" + ], + "name": "PathRepHAN: Hierarchical attention networks for pathology report classification", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/v33/PathRepHAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "Machine learning (ML) models often contain numerous hyperparameters, free parameters that must be set before the models can be trained. As the number of model hyperparameters increases, their optimization becomes significantly more challenging as we face a combinatorial increase in potential model configurations. Similarly, there is an increased chance that our models’ hyperparameters interact in complex ways. HyperSpace allows a user to optimize complex machine learning algorithms based on their hyperparameters. HyperSpace works by parallelizing parameter search spaces, running Bayesian model based optimization (SMBO) over each of these spaces in parallel. It was designed to be as minimally invasive as possible such that very little change to existing code will be needed to get a user started.", + "laborHours": 1717.6, + "languages": [ + "Python 3" + ], + "name": "HyperSpace", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yngtodd/hyperspace", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2024-08-23" + }, + "description": "This code solves the Vlasov-Poisson equations in 6-dimensions without approximation. It uses sparse grid discretization to solve the high-dimensional PDEs. The code functions as a discontinuous Galerkin finite element solver. Advantages/benefits include no approximations, supports high-dimensionality, leadership-scale capability, and implicit time advance.", + "laborHours": 33029.6, + "languages": [ + "C++17" + ], + "name": "Adaptive Sparse Grid Discretization (ASGarD)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/project-asgard/asgard/releases/tag/v0.5.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v0.5.0" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "A collection of MATLAB scripts forming a toolbox for video (frame by frame) detection and tracking of beads imaged with fluorescence microscope for estimating bead flow and location tracks. Scripts accept tiff image stacks of video frames and provide bead locations and tracked positions over frames in stack. Various utility functions are also provided to assist in data I/O. A custom solution for specific data source - specifically, the software works well for noisy/out of focus florescence microscopy images.", + "laborHours": 7645.6, + "languages": [ + "MATLAB/2018a" + ], + "name": "Bead-Tracking Toolbox for MATLAB", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dnbornl/beadtracking", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "Data science capabilities are becoming important more and more. Even though there exist many data science and machine learning tools, they are not intuitive for many traditional scientists who are not familiar with programming. ASCENDS provides easy and intuitive interfaces (command-line interface, graphical user interface) to users so they can use data science capabilities without having to understand programming language. ASCENDS performs data visualization, machine learning model training, storing and prediction (regression problem), automatic hyperparameter tuning, and supports various machine learning models including random forest, kernel ridge, nearest neighbor, neural network, etc. Users can use standard CSV (comma separated values) format data set and investigate the feature columns that are highly correlated to a target column; further, they can learn ML models, then store and use them for predictions. The tool is supposed to be generically applicable so that it can be used for many different applications.", + "laborHours": 101414.4, + "languages": [ + "Python 3.7" + ], + "name": "ASCENDS: Advanced Data SCiENce Toolkit for Non-Data Scientists", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornlpmcp/ASCENDS", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The PySCL (Python Standard Composition Library) is a library that provides a standard and consistent method of specifying the material mixtures for a given problem. The library enables software to use standard nuclide names and convenient naturally occurring composition and elemental abundances.", + "laborHours": 22055.2, + "languages": [ + "Python" + ], + "name": "PySCL", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/neams-workbench/PySCL", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "There is a need to easily and uniformly capture, access, enrich, organize, search, and collaborate on working scientific data sets across geographically distributed experiment, computation, and data analytics facilities. DataFed provides a set of services and applications enabling simple and uniform cross-facility scientific data management with federated (distributed) data repositories. This solution greatly reduces effort required by scientist to organize and/or move data between facilities/institutes, Reduces likelihood of misidentification and subsequent misuse of data, and improves scientific reproducibility through deep, domain-specific context and provenance capture.", + "laborHours": 83797.6, + "languages": [ + "C++11 GCC 5.x or grerater; Python 3" + ], + "name": "DataFed", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/DataFed", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The software titled \"nccd\" is used for running residual neural networks (ResNets) on images of nuclear canisters. The software provides only the code for the implementation (based on the fastai library), but it does not share the image data. The compute code allows the use of residual nets (and more generally of other deep learning models) for classifying images from nuclear canisters as corroded. or intact. An image is considered to be corroded if it contains pitting or stress corrosion cracks. The code trains ResNets on image tiles extracted from original images from nuclear canisters, and then implements a classification rule, which can be applied to a validation set to decide if each original image is corroded or intact. The software automates the process of using images taken from nuclear canisters to detect corrosion. It provides also scope for future research directions on the basis of the existing research and code.", + "laborHours": 486.4, + "languages": [ + "Python (v3.6 onwards)" + ], + "name": "Nuclear Canister Corrosion Detection", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/papamarkou/nccd", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2021-03-05" + }, + "description": "Air dehumidification processes are important and significantly impact both the performance of building ventilation and air conditioning systems, and the health of occupants. In a membrane-based dehumidifier, a permselective membrane is adopted to separate the two flow streams at feed and permeate sides. The feed side is continuously supplied with humid air at atmospheric pressure, while the permeate side is connected to a vacuum pump to produce vacuum or a low permeate vapor pressure as a driving force for water vapor permeation. The software MBMS 1.0 enables modeling and simulation of the design and configuration optimization of a membrane-based air-to-air (A2A) or air-to-vapor (A2V) device. A first-order physical-constant model was developed to reasonably account for the fundamental heat and mass transfer processes involved.", + "laborHours": 1200.8, + "languages": [ + "C", + "C++" + ], + "name": "MBMS1.0: An Open-Source Code for Modeling and Simulation of Membrane-Based Dehumidification and Energy Recovery", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MBMS/C-CODE_FOR_MEMBRANE_BASED_MODEL", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "MBMS. 1.0" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The existing methodologies for gathering and computing zonal statistics from the combination of a raster image and a shapefile either require advanced programming knowledge in at least one language or the use of proprietary software such as ArcGIS. The software “Choppy Lite” offers several solutions for acquiring zonal statistics that can be used without proprietary software or programming knowledge. This software provides a Docker-based ecosystem, allowing users of any experience level to simply run a single line command in a terminal prompt independent of the operating system. Intermediate to advanced users can import the class provided by the software package into their own Python scripts.", + "laborHours": 425.6, + "languages": [ + "Python 3.8" + ], + "name": "Choppy Lite", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nset-ornl/choppy", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The software code titled “Scripts for Running Multiple Lunes of Evidence Analysis” enables high throughput network analysis; efficient analysis of large multi-omic networks in order to rank genes by connectivity. This code creates a set of scripts that take omic networks as input as well as list of known genes and calculates scores for all other genes in genome based on connectivity to those genes and does so accurately and efficiently. In addition, it aids the user in performing a validation check of observed data to random. The code outputs a table of all genes in the genome with LOE scores and scores observed data versus random.", + "laborHours": 76.0, + "languages": [ + "Python 3.6" + ], + "name": "Scripts for Running Multiple Lines of Evidence Analysis", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/afurches/Cell_Wall_LOE", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2022-02-15" + }, + "description": "SLiDE (Scalable Linked Dynamic Equilibrium) replicates the blueNOTE (National Open source Tools for general Equilibrium analysis) datastream from the Wisconsin National Data Consortium. From there, it produces a recursive dynamic computable general equilibrium model of the US states and eventually the global/national economies. The datastream operations have been set up to allow for scalability of both regions and sectors represented. The model has the capability to flexibly define functional forms similar to other general equilibrium model construction software.", + "laborHours": 3724.0, + "languages": [ + "Julia" + ], + "name": "Scalable Linked Dynamic Equilibrium (SLiDE)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/slide", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The Panel-Segmentation package is a computer vision (CV) framework for automated metadata extraction for solar PV arrays using satellite imagery. With Panel-Segmentation, a user inputs a set of latitude-longitude coordinates to automatically generate a satellite image using the Google Maps API, and runs the image through a deep learning framework to get a pixel-by-pixel representation of the solar panel(s) in an image. If a solar array is located, the user can then perform spectral clustering to cluster individual solar arrays in an image (if applicable), and run each cluster through an azimuth estimation algorithm. This package framework is versatile, allowing for future CV techniques to be added and/or modified. ", + "laborHours": 2158.4, + "languages": [ + "Python" + ], + "name": "Panel-Segmentation", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Panel-Segmentation", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-12-03", + "metadataLastUpdated": "2023-10-11" + }, + "description": "CatCost™ enables catalyst researchers to develop comprehensive estimates of the cost to produce pre-commercial catalysts early in the catalyst development process. It includes both web browser and Excel-based tools, each with distinct strengths. The web tool includes powerful visualization capabilities, while the Excel tool allows for high degrees of control and customization by power users. The CatCost™ Python Data Tools are designed to facilitate the transfer of data from the Excel tool to the web tool, so that users can take advantage of both the powerful visualization in the web tool and the higher degree of customization available in the excel tool. Rather than painstakingly copying entries from estimates, the materials, equipment, and spent catalyst libraries from Excel to a JSON format for the web tool, the CatCost™ Data Tools provide an intuitive applet which allows them to simply choose which library or estimate they wish to transfer, and then returns files that integrate smoothly with the web version of the tool.", + "laborHours": 1824.0, + "languages": [ + "Python" + ], + "name": "CatCost™ Data Tools [SWR-20-59]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/catcost-data-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MEEDS is a cybersecurity solution that empowers under resourced owners and operators of critical energy infrastructure to rapidly identify and detect the publicly exposed and vulnerable operational technology (OT) and other critical Industrial Control and Energy Delivery Systems.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Mitigation of External Exposure of Energy Delivery System (MEEDS).", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Thermoelectric Capacity at Risk Analysis Tool for ERCOT. capratTX is a unique R package, featuring algorithms for simulating water storages that provide cooling water for thermoelectric power plants. The tool may be used to compute long-term \"capacity at risk\" under a range of future climate\nprojections.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/capratTX", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/capratTX", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-12-09", + "metadataLastUpdated": "2020-12-09" + }, + "description": "coreFPU is a simple test code designed to detect bac CPU's.", + "laborHours": 0.0, + "languages": [], + "name": "coreFPUtest Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/coreFPUtest/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/coreFPUtest", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-12-11", + "metadataLastUpdated": "2024-01-04" + }, + "description": "The Distributed Generation Market Demand (dGen™) model is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The National Renewable Energy Laboratory (NREL) developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States within a single modeling platform. The dGen model builds on, extends, and provides significant advances over NREL’s SolarDS model (Denholm et al. 2009), which is now deprecated.", + "laborHours": 17540.8, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "dGen™ (Distributed Generation Market Demand Model) [SWR-17-09]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dgen", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-14", + "metadataLastUpdated": "2020-12-14" + }, + "description": "Palm/FastFootprints implements two method for rapid memory footprint access diagnostics. The two methods are whole program and precise. Current footprint analyses can cause 200× or more slowdown with realistic inputs and are therefore impractical. The whole-program method reduces the overhead to 10% by computing upper bounds, but still yields interprocedural insight through a call path profile. Our precise method uses additional static analysis and profiling to refine the upper bounds for intra-procedural loop nests.", + "laborHours": 0.0, + "languages": [], + "name": "Palm/FastFootprint", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab-hub/palm/palm-memory", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-14", + "metadataLastUpdated": "2020-12-14" + }, + "description": "BigFlowSim is a workflow I/O simulator that captures key implementation choices for remote I/O, including intensity, reuse, locality, access pattern, and data movement. With BigFlowSim, it is possible to generate synthetic benchmarks, and then perform sensitivity analyses to quantify the effects of the various I/O parameters. In addition to generating synthetic workflows, BigFlowSim is also able to replay traces (of I/O access) captured from execution of actual distributed scientific workflows.", + "laborHours": 0.0, + "languages": [], + "name": "BigFlowSim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab-hub/tazer/tazer-bigflow-sim", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-14", + "metadataLastUpdated": "2020-12-14" + }, + "description": "MIAMI was designed for Pin 2. Unfortunately, Pin 2 is deprecated and no longer runs on modern versions of Linux. For example, it does not work on RHEL 7.x. In particular, Pin 2 requires a C++ ABI <= GCC 4.4.", + "laborHours": 0.0, + "languages": [], + "name": "MIAMI-NW", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab-hub/palm/miami-nw", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "OpenCGRA is an open-source framework for modeling, testing, and evaluating CGRAs. The first open-source integrated framework able to support the full top-to-bottom design flow for specializing and implementing CGRAs: modeling at different abstraction levels (functional level, cycle level, register-transfer level) with compiler support, verification at different granularities (unit testing, integration testing, property-based testing), simulation, generation of synthesizable Verilog, and characterization (area, power, and timing).", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/OpenCGRA", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/OpenCGRA", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "Dynamic Importance (DynIm) Sampling is a new approach for importance sampling in high-dimensional space. DynIm has two key characteristics. (1) Importance sampling: The notion of importance of candidate samples is used to guide the sampling, where importance is defined based on the (dis)similarity from previously selected samples (via Euclidean distance metric). (2) Dynamic sampling: The sampling can be performed dynamically, as new candidates are generated and new samples must be selected.\nDynIm was developed as part of a machine learning based coupling of scales in large multiscale simulations and can be used for a variety of applications.", + "laborHours": 0.0, + "languages": [], + "name": "Dynamic Importance Sampling", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/dynim", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "Archspec aims at providing a standard set of human-understandable labels for various aspects of a system architecture like CPU, network fabrics, etc. and APIs to detect, query and compare them. This project grew out of Spack and is currently under active development. At present it supports APIs to detect and model compatibility relationships among different CPU microarchitectures.", + "laborHours": 0.0, + "languages": [], + "name": "archspec", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/archspec/archspec", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "Software including a Bayesian multitask learning model. The pipeline includes functionality to process data, train, evaluate models, and generate reports.", + "laborHours": 0.0, + "languages": [], + "name": "Bayesian Multitask with Structure Learning", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/bmsl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "CRADL captures performance metrics of machine learning algorithms operating on mesh data from multiphysics\ncodes This proxy application is a tool to explore scalability of inference on HPC platforms, and also gather performance metrics for inference on new machine learning specific hardware. CRADL is designed to give users as fine a control as possible over an inference simulation. Users may\nselect the number of cycles, amount of data, and batch size to pass to the accelerator of choice. Additionally the user may select a number of performance optimization libraries and flags. CRADL comes packaged with a repository of anonymized multi-physics simulation data, as well as a\npretrained model for inference. The code allows a user to load their own pre-trained model and data if they wish. The code can operate in multiple parallelization schemes, with performance enhancing options such as half-precision libraries, PyTorch benchmarking, and pinned memory with non-blocking data transfers.\n", + "laborHours": 0.0, + "languages": [], + "name": "Concurrent Relaxation through Accelerated Deep Learning", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CRADL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "HavoqGT (Highly Asynchronous Visitor Queue Graph Toolkit) is a framework for expressing\nasynchronous vertex-centric graph algorithms, and executing them on High Performance Computing (HPC) systems. It provides a vertex 'visitor' interface, where actions are defined at an individual vertex level, and contains a suite of classic graph algorithms. HavoqGT is capable of processing large graphs stored in NVRAM (SSDs) using a memory mapped interface.\n", + "laborHours": 15139.2, + "languages": [], + "name": "Highly Asynchronous Visitor Queue Graph Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/havoqgt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.2" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "Very early stages of a simple tool able to create multiple automated requests of different Independent System Operators (ISOs) data, and download it in comma separated value (.csv) files.\n", + "laborHours": 0.0, + "languages": [], + "name": "ISO Data Automated Request Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ISO-DART", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "MPIDiff is a C++ library for pairing a correct version of an executable with a version that may have bugs\nor race conditions in it. The correct version checks that the data communicated from the other program\nmatches its own and reports any differences.", + "laborHours": 0.0, + "languages": [], + "name": "MPIDiff", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MPIDiff", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-12-18", + "metadataLastUpdated": "2020-12-21" + }, + "description": "This library includes in-progress code for the optimization of materials and molecules using reinforcement learning. This project seeks to develop a generalized machine learning approach for optimizing targeted, and often complex, functional properties over the space of possible material structures, allowing faster identification of promising candidates. Electronic and transport properties of materials are determined by their molecular structure (for molecules) or their crystal structure (for in-organic crystalline materials). The atomic composition, bonding, and 3-D-spatial arrangement in these systems therefore represent a vast, discontinuous search space for optimal candidates. This library implements AlphaZero style reinforcement learning applied to two worked examples: the optimization of stable organic radicals for redox flow batteries, and the determination of stable electrolyte species for solid state batteries. The current code contains proof-of-concept results run on the Eagle HPC system, while the completed package will be a flexible tool for material optimization across of number of energy-relevant fields, which leverages cloud compute resources for the majority of the computational heavy lifting.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "rlmolecule: A library for general-purpose material and molecular optimization using AlphaZero-style reinforcement learning", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rlmolecule", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-12-23", + "metadataLastUpdated": "2023-06-09" + }, + "description": "Modern high-performance buildings exhibit an increasing number of building loads that use direct current (DC) electricity internally, rather than alternating current (AC), due to the advent of low-cost computing and advanced power electronics. Powering DC devices from the AC grid requires AC/DC power conversion, which introduces energy losses and reduces efficiency. As DC loads proliferate, the cumulative wasted energy associated with hundreds of millions of AC/DC converters has become one of the broadest energy savings opportunities in buildings.\n\nDC power distribution systems have been proposed as an elegant and transformative solution to the problem of DC devices. In a DC distribution system, the building's wires carry DC electricity, rather than AC; and a few centralized, highly efficient AC/DC converters replace the many smaller, less efficient converters that serve individual DC loads. Unfortunately, the trade-offs associated with DC distribution systems are not well understood. Reported energy savings associated with DC power distribution differ widely and have not been well validated.\n\nThe Building Electrical Efficiency Analysis Model (BEEAM) is a Modelica library that simulates the efficiency of building electrical distribution systems using harmonic power flow. BEEAM can model a wide variety of building distribution topologies, including three-phase AC, single-phase AC, unipolar DC, bipolar DC, and hybrid networks under both balanced and unbalanced load conditions. BEEAM accurately models power electronic converter losses, provides granular estimates of losses throughout the distribution system, and properly models efficiency at part load conditions. Users can package BEEAM within a functional mockup unit (FMU), enabling co-simulation with other modeling platform, such as EnergyPlus. In summary, BEEAM provides a tool suite for fair and accurate comparison of the efficiency of building electrical distribution systems, including AC, DC, and hybrid systems.", + "laborHours": 0.0, + "languages": [ + "Modelica", + "MATLAB", + "Ruby", + "Jupyter ", + "Python" + ], + "name": "BEEAM (Building Electrical Efficiency Analysis Model) [SWR-20-107]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BEEAM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "obriense@ornl.gov" + }, + "date": { + "created": "2020-12-29", + "metadataLastUpdated": "2020-12-29" + }, + "description": "Neutron multiplicity analysis is a widely used technique in international safeguards and is most commonly applied to the assay of product and scrap materials in the production of mixed oxide fuel. The typical neutron multiplicity analysis applies only a crude, almost cursory, uncertainty\nanalysis limited to propagation of statistical errors in the derived singles, doubles, and triples count rates through the point source model. An assay result without a properly assigned uncertainty has little value, and an assay result with a significantly understated uncertainty can lead to\nboth unsafe facility operations and an increased misclassification rate for the item of interest. We have developed a complete and robust total measurement uncertainty treatment for multiplicity analysis that incorporates instrumental, environmental and nuclear data error contributions.", + "laborHours": 0.0, + "languages": [ + "Visual Basic .NET" + ], + "name": "Multiplicity TMU Estimator", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/multTMU/multTMU", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Deep learning approaches which incorporate geophysical data and readings from multiple remote sensing platforms for predictive mapping of vegetation over very large, ecologically diverse regions.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/fieryfuture", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/fieryfuture", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Framework that can produce visually compelling articles for project research. The design of our framework is centered around simplifying content creation so that researchers unfamiliar with the underlying technology stack can still produce informative, beautiful research documents with interactive and visual features.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Deep-Learning-Control-with-Embedded-Physical-Structure", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Deep-Learning-Control-with-Embedded-Physical-Structure", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Open source release of Python Systems Library which contains benchmark datasets, system emulators, and data loading codes.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/slim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/slim", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "software library of structured linear maps that can be used as drop in replacements for Pytorch linear layers.\nThese maps can be used to enforce physically realistic outcomes to data-driven machine learning scientific modeling problems.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/psl", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/psl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2021-01-12" + }, + "description": "The (wind) turbine-models GitHub repo hosts an archive/database of turbine models already in the public domain. This includes mainly tabular power and thrust (when available) curve data in .csv files, other technical data, as well as documentation and references built with Sphinx/GitHub Pages. There is a script called \"curve_parser.py\" to assist with the parsing of power and thrust curves, but this repo is mostly a central location for turbine model data.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "turbine-models", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/turbine-models", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-12", + "metadataLastUpdated": "2024-02-27" + }, + "description": "Industrial Control Systems protocol parsers plugins for the Zeek network security monitoring framework. Currently we have four fully developed protocol parsers but we plan on adding more in the future. The protocol parsers we currently have developed are for BACnet, DNP3, Ethernet/IP, and Modbus.", + "laborHours": 0.0, + "languages": [], + "name": "Industrial Control Systems Network Protocol Parsers", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/cisagov/ICSNPP", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2023-03-08" + }, + "description": "LIGGGHTS-INL is a capability-extended version of LIGGGHTS. LIGGGHTS is an Open Source Discrete Element Method Particle Simulation Software (https://www.cfdem.com/media/DEM/docu/Manual.html). LIGGGHTS stands for LAMMPS improved for general granular and granular heat transfer simulations. LAMMPS is a classical molecular dynamics simulator. It is widely used in the field of Molecular Dynamics (https://lammps.sandia.gov/doc/Manual.html). Thanks to physical and algorithmic analogies, LAMMPS is a very good platform for DEM simulations. LAMMPS offers a GRANULAR package to perform these kinds of simulations. LIGGGHTS aims to improve those capability with the goal to apply it to industrial applications.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Granular Flow", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/LIGGGHTS-INL", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2023-03-15" + }, + "description": "This software produces general location descriptions from time-series location data collected from mobile devices that record global positioning system (GPS) coordinates over time. The purpose of this software is to convert detailed location history data, which is considered personally identifiable information (PII), into non-traceable, anonymized, generic information that is useful to researchers but does not contain PII. The software is specifically designed for use with trigger-based data that describe the parked locations and dwell times of automobiles.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Location Generalizer", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Location-Generalizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Hierarchical Parallel Tensor Infrastructure (HiParTI), is to support fast essential sparse tensor operations and tensor decompositions on multicore CPU and GPU architectures. It consists of sparse tensor decompositions, CANDECOMP/PARAFAC (CP) and Tucker decompositions, fundamental tensor operations, and tensor transformations", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/HiParTI", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/HiParTI", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2023-05-26" + }, + "description": "By 2050, there could be as many as 10 million photovoltaic (PV) modules that have reached their end of life. The circular economy (CE) proposes to tackle waste issues by maximizing value retention in the economy but transitioning to a CE implies certain stakeholder behaviors. In this context, we propose an agent-based model (ABM) to account for social factors in CE strategies assessment of end-of-life PV modules. Four different types of agents are represented and five possible end-of-life pathways are modeled. A machine-learning metamodel is used to explore the parameter space of the ABM. Results show that excluding social factors underestimates the effect that lower recycling prices have on material circularity by 100% and highlight the limitation of the reuse strategy as, even in an ideal case, used modules only provide a third of demand in the United States. The ABM could be developed to compute the environmental impacts of end-of-life pathways.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "ABSiCE (Agent-Based Simulations of the Circular Economy) [SWR 20-113]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ABSiCE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2021-01-14" + }, + "description": "Implementation of the SISSO regression algorithm in MATLAB. The SISSO regression algorithm iteratively selects model features from candidates, converging even when the number of possible features is much greater than the number of available data points.\n\nIncludes a test script that validates the algorithm by replicating the results using data and procedure from https://analytics-toolkit.nomad-coe.eu/hub/user-redirect/notebooks/tutorials/compressed_sensing.ipynb.\n\nPython code from the SISSO regressor in 'sisso.py', from the link above, was used as the basis for developing the MATLAB implementation. The SISSO regression algorithm is detailed by the original authors in R. Ouyang, S. Curtarolo, E. Ahmetcik et al., Phys. Rev. Mater. 2, 083802 (2018), R. Ouyang, E. Ahmetcik, C. Carbogno, M. Scheffler, and L. M. Ghiringhelli, J. Phys.: Mater. 2, 024002 (2019).", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "SISSO (Sure-independence-screening sparsifying-operator regressor)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SISSORegressor_MATLAB", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-19", + "metadataLastUpdated": "2023-03-13" + }, + "description": "SR2ML is a software package which contains a set of safety and reliability models designed to be interfaced with the INL developed RAVEN code. These models can be employed to perform both static and dynamic system risk analysis and determine risk importance of specific elements of the considered system. Two classes of reliability models have been developed; the first class includes all classical reliability models (Fault-Trees, Event-Trees, Markov models and Reliability Block Diagrams) which have been extended to deal not only with Boolean logic values but also time dependent values. The second class includes several components aging models. Models of these two classes are designed to be included in a RAVEN ensemble model to perform time dependent system reliability analysis (dynamic analysis). Similarly, these models can be interfaced with system analysis codes to determine failure time of systems and evaluate accident progression (static analysis).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Safety Risk Reliability Model Library", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/SR2ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-19", + "metadataLastUpdated": "2023-03-08" + }, + "description": "LOGOS is a software package which contains a set of discrete optimization models that can be employed for capital budgeting optimization problems. More specifically, provided a set of items (characterized by cost and reward values) and constraints, these models select the best combination of items which maximizes overall reward and satisfies the provided constraints. The developed models are based on different versions of the knapsack optimization algorithms. Two main classes of optimization models have been initially developed: deterministic and stochastic. Stochastic optimization models evolve deterministic models by explicitly considering data uncertainties (associated to constraints or item cost and reward). These models can be employed as stand-alone models or interfaced with the INL developed RAVEN code to propagate data uncertainties and analyze the generated data (i.e., sensitivity analysis).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "LOGOS", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/LOGOS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-19", + "metadataLastUpdated": "2023-03-15" + }, + "description": "CMIP model explores various charging infrastructure network designs to serve a free-floating car-sharing fleet and determine the charging downtime experienced by the fleet for each design. Development of the CMIP model had two major steps: (1) describing modeling assumptions and (2) developing an integer program (IP) that jointly optimizes decisions about locations to install DC fast chargers and EV-to-charger assignments. The CMIP model integrates an EV charging model, EV energy consumption model, and heterogeneous, real-world vehicle use data with an integer programming optimization model to identify optimal location of new charging stations and calculate vehicle downtime for charging. The CMIP model can be applied to understand: (a) the reduction of EV fleet downtime if an additional fast-charging station is added to the current infrastructure and (b) to what extent total vehicle downtime would be sensitive to additional charging infrastructure.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Charging-management And Infrastructure-planning (cmip) Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/CMIP", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-01-22", + "metadataLastUpdated": "2021-01-22" + }, + "description": "Tracktable is a toolkit for analysis and visualization of the trajectories of moving objects. Its main focus is on air and sea traffic. It can also work with more abstract trajectories such as eye tracking data. We supply a set of core data structures, input/output routines, math and machine learning algorithms that operate on those data structures, and visualization algorithms to produce movies and still images of the results.\n", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Tracktable ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/tracktable", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tracktable", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1 (Alpha)" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-01-22", + "metadataLastUpdated": "2024-09-23" + }, + "description": "Laika BOSS (Binary Object Scanning System), often written as \"Laikaboss\", is an object scanner and intrusion detection system that strives to be scalable, flexible, and verbose. Its goal is to take arbitrary file input and extract all relevant subfiles and metadata for use in helping analysts determine the function and maliciousness of a file at a glance. This is an extension to the original code developed by Lockheed Martin.", + "laborHours": 11901.6, + "languages": [ + "Dockerfile", + "Shell", + "YARA", + "JavaScript", + "Vue", + "Python" + ], + "name": "Laika BOSS (Binary Object Scanning System)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/laikaboss", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.00+2821.g2403134" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-25", + "metadataLastUpdated": "2021-01-26" + }, + "description": "ModuleOT is an open hardware security platform which provides all features necessary for securing remote energy resources. The platform consists of a physical bump in-the wire device which runs a custom-built application built with Go and Python and leverages AES-NI Instruction set available on modern hardware for cryptographic acceleration. By combining these features, ModuleOT acts as an all-in-one low-cost solution to enable cryptographically secured communications to any critical remote servers or devices. Because the software application has been built using Golang, this source can be easily compiled for different hardware platforms. The module is designed to provide the following core features: (1) encrypted communications across an untrusted network, (2) certificate-based authentication with secure storage, (3) hardware cryptographic acceleration, (4) IP-based whitelisting, (5) local firewall management, and (6) legacy (RS485) device support.\n", + "laborHours": 0.0, + "languages": [], + "name": "ModuleOT", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ModuleOT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Processing temperature is decisive to the properties and performance of the product in friction extrusion. However, the constantly varying thermal boundary conditions result in an unstable processing temperature even fixed die rotational speed and feed rate were implemented, which extensively disturb the stability of the process and the quality of the\nproduct. It is key to maintain the process temperature to ensure the properties of the product is uniform. What's more, a controlled processing temperature enables the properties of the product to be manipulatable between parts and between\ndifferent locations of one part", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Temperature controlled friction extrusion process", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-27", + "metadataLastUpdated": "2024-03-04" + }, + "description": "DES_HVAC is a repository of a Parametric Analysis Tool (PAT) project and for scripts related to modeling of different HVAC systems for buildings in a district served by a district thermal energy system.\n\nThe Measures directory contains the new measures developed to extract data from the simulations. Update these measures and not the measures in the Test Suite measures directory. PAT should be used to update the measures in the Test Suite project.\n\nThe Test directory contains a PAT project for testing the functionality of the measures. The PAT project is named HVAC_Test and can be opened in PAT > 3.x.", + "laborHours": 0.0, + "languages": [], + "name": "URBANopt™ District Energy Systems HVAC Measures (DES_HVAC) [SWR-21-30]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/urbanopt/DES_HVAC", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stewartsl@ornl.gov" + }, + "date": { + "created": "2021-01-29", + "metadataLastUpdated": "2022-02-08" + }, + "description": "The Transformer eXplainability and eXploration library is intended to aid in the explorability and explainability of transformer classification networks, or transformer language models with sequence classification heads. The basic function of this library is to take a trained transformer and test/train dataset and produce an ipywidget dashboard which can be displayed in a jupyter notebook or in jupyter lab.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Transformer eXplainability and eXploration", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/tx2", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "johnsonsr@ornl.gov" + }, + "date": { + "created": "2021-01-31", + "metadataLastUpdated": "2021-02-01" + }, + "description": "Flibcpp is a library for use by application developers that provides native Fortran interfaces to existing high-quality algorithms and containers implemented in C++ and available on all modern computer systems.", + "laborHours": 0.0, + "languages": [ + "C++", + "Fortran", + "SWIG" + ], + "name": "Flibcpp", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/swig-fortran/flibcpp", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-02-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PaKman: A Scalable Algorithm for Generating Genomic Contigs on Distributed Memory Machines. PaKman presents a fully distributed method that tackles assembly of large genomes through the combinationof a novel data-structure (PaK-Graph) and algorithmic strategies to simplify communication and I/O footprint during the\nassembly process.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/pakman", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pakman", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-03", + "metadataLastUpdated": "2021-03-04" + }, + "description": "Python implementation of the Method of Moving Asymptotes optimization algorithm described in[Svanberg, K., The method of moving asymptotes- a new method for structural optimization. International journal for numerical methods in engineering, 1987. 24(2): p.359 (https://onlinelibrary.wiley.com/doi/abs/10.1002/nme.1620240207). Originally implemented in[GetDP](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=717799) [project](https://gitlab.onelab.info/getdp/getdp), although it has been deleted in their repository.", + "laborHours": 0.0, + "languages": [], + "name": "Method of Moving Asymptotes Optimization Algorithm in Python", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pyMMAopt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-03", + "metadataLastUpdated": "2021-02-03" + }, + "description": "We perform a comparison study of two topology optimizations methods applied to the design of a two fluids heat exchanger modeled with a coupled thermal-flow problem. The flow follows an isothermal and\nincompressible Stokes-Brinkman equation and the heat transfer is governed by a convection-diffusion\nequation without internal generation and high Peclet number. To keep the two fluid phases separated, we solve two Stokes-Brinkman equations, where the Brinkman term models the other phase as a solid. These two velocity fields are then fed to the heat transfer equation. Our goal is to maximize the enthalpy at the cold outlet while constraining the pressure drop. We first solve the design modeling the solid and fluid phases with a volume fraction variable. A SIMP-like penalization in the Brinkman term drives the optimization to a discrete design. The cost and constraint function\nderivatives are calculated with the library pyadjoint and the optimization is performed by IPOPT. We present optimized designs in two dimensions and discuss the influence of the parameters.\n", + "laborHours": 0.0, + "languages": [], + "name": "Two dimensional topology optimization of heat exchangers with the volume fraction method", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/2DHEVF", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-03", + "metadataLastUpdated": "2021-02-04" + }, + "description": "B.MPI3 is a C++ library wrapper for standard MPI-3. B.MPI3 is designed following the principles of Boost\nand the STL. B.MPI3 is unrelated to the official, now deprecated, MPI-C++ interface. It provides an iterator-based interface and MPI-3 features (RMA and Shared memory). B.MPI3 is written from scratch in C++14.\n", + "laborHours": 0.0, + "languages": [], + "name": "B.MPI3", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/b-mpi3/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/b-mpi3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-03", + "metadataLastUpdated": "2021-03-11" + }, + "description": "The Chebyshev Interaction Model for Efficient Simulation (ChIMES) is a machine-learned interatomic potential targeting chemistry in condensed phase systems. ChIMES models are able to approach\nquantum-accuracy through a systematically improvable explicitly many-bodied basis comprised of linear combinations of Chebyshev polynomials. Though originally developed as to enable description of organic molecular materials, ChIMES has successfully been applied to systems spanning ambient water to molten carbon, and leveraged as correction for density functional based tight binding simulations. The\nChIMES calculator comprises a flexible toolset for evaluating ChIMES interactions (e.g. in simulations, single point calculations, etc). Users have the option of directly imbedding the ChIMES calculator within their codes, or evaluating interactions through the beginner-friendly serial interface, each of which have\nPython, C++, C, and Fortran API's.", + "laborHours": 0.0, + "languages": [], + "name": "chimes_calculator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rk-lindsey/chimes_calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-02-05", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The NRIC Digital Engineering Ecosystem is a software suite designed to eliminate procedural failures in the engineering lifecycle of complex projects. It focuses on improving the flow of scheduling data, safety information, engineering requirements, and CAD files among stakeholders of complex engineering projects. The project comprises software adapters that move engineering data from disparate software tools in and out of a central database. The ecosystem is designed to efficiently incorporate data sources from many different engineering toolsets, making it software agnostic, and adaptable to many different engineering applications.", + "laborHours": 0.0, + "languages": [ + "JavaScript" + ], + "name": "NRIC Digital Engineering Ecosystem", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/IDEAS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-02-05", + "metadataLastUpdated": "2023-03-13" + }, + "description": "TMAP8 is a MOOSE application for solving 0-1D scalar diffusion-reactive transport. It contains unique custom syntax for 0D or 1D geometric/algebraic entities that make it more usable for 0-1D transport than standard MOOSE syntax.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "TMAP8", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/TMAP8", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-08", + "metadataLastUpdated": "2021-02-08" + }, + "description": "The Fat Crayon Toolkit (FCT) provides python modules for assisting in the design and visualization of\nboreholes and tunnels and their relationship with natural features such as fractures. Distances of closest\napproach among the boreholes can be calculated, along with other key design metrics. Additionally, the shear propensity of natural fractures (either deterministic or stochastic) can be visualized in either 3D (as\nVTK files) or in 2D (stereonets). The example provided demonstrates a test bed developed for the\nEnhanced Geothermal Systems (EGS) Collab project. This material is based upon work supported by the\nGeothermal Office of the Department of Energy and the Sanford Underground Research Facility and was\nprepared by LLNL under Contract DE-AC52-07NA27344.", + "laborHours": 0.0, + "languages": [], + "name": "Fat Crayon Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/joepmorris/FatCrayonToolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2021-02-17" + }, + "description": "SAND2021-1508 O\nThe Pynta code is designed to automatically characterize chemical reactions relevant to heterogeneous catalysis in which gas-phase molecules interact with crystal facets of a solid. It organizes multiple quantum chemistry calculations to carry out this task. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python 3", + "bash script" + ], + "name": "Pynta v. 1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zadorlab/pynta", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2021-1654 O\nThe Python Material Tensor code (PyMTensor) applies crystal symmetries to arbitrary material tensors. It uses symbolic algebra to exactly determine the zero tensor components and the relationships between the nonzero components for all crystallographic point groups. It is capable of computing components of higher-order material tensors needed when treating nonlinear effects. It has a simple and flexible interface for inputting tensor rank information and any known symmetries between tensor indices.Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 562.4, + "languages": [ + "Python", + "Sage" + ], + "name": "PyMTensor 1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pymtensor", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2021-1511 O. The code takes a description of a system comprised of two leads that are sources and sinks of electrons, a set of abstract sites that those electrons can occupy, and their connectivity. It then predicts the current passing between the two leads through the set of abstract sites. There are numerical parameters that define the rate at which electrons tunnel between sites and another parameter that determines the energy of having two electrons on the same site. When the ratio of these energies and biases are set just right, they can be used to predict the existence of Coulomb blockade in which no current flows because the energetic penalty would be too high. That is, the code predicts a current and the absence of a current which is predictive of Coulomb blockade. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 182.4, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "Fermi-Hubbard Transport Solver v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/FermiHubbardTransport", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2021-05-18" + }, + "description": "SAND2021-0624 O Watchr is a Jenkins plugin for tracking the performance of subroutines over many individual builds. It reads build-generated performance reports and displays the data contained in these performance reports as a series of graphs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Java", + "JavaScript", + "Java", + "Java" + ], + "name": "Watchr 3.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/watchr-jenkins/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/watchr-jenkins", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2021-02-17" + }, + "description": "SAND2021-1505 O. TINES is an open source software providing math infrastructure for solving many stiff time ordinary differential equations (ODEs) and/or differential algebraic equations (DAEs) using a batch hierarchical parallelism. The code is written using a parallel programming model (i.e., Kokkos) to future-proof the next generation parallel computing platforms such as GPU accelerators. This code is developed to support Exascale Catalytic Chemistry (ECC) Project. The code provides fundamental math helpers that can aid other research projects. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "TINES - Time Integration, Newton and Eigen Solver v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Tines", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "slatterysr@ornl.gov" + }, + "date": { + "created": "2021-02-17", + "metadataLastUpdated": "2021-02-17" + }, + "description": "Picasso is a C++ template library for the development of exascale-class particle-in-cell methods. 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When needed, users can define their own parameters to create their own station or vehicle components.\n\nDownload H2FillS in Two Steps\nRead the terms of the end user software license agreement.\nRegister to download the software.\nThere are two versions of the model:\n\nA full-station model starts the simulation at high-pressure ground storage, runs through a dispenser, and ends at a vehicle storage system.\nA partial-station model starts at the dispenser breakaway and consists solely of the dispenser components and the vehicle storage system.\nH2FillS will automatically output fill performance data from the vehicle by tracking pressure and temperature throughout the fill. Users can input their own fill profiles into the model to run a variety of simulations.", + "homepageURL": "https://www.nrel.gov/hydrogen/h2fills.html", + "laborHours": 0.0, + "languages": [], + "name": "H2Fills™", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrel.gov/hydrogen/h2fills-agreement-registration.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrel.gov/hydrogen/h2fills.html", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-02-24", + "metadataLastUpdated": "2021-03-05" + }, + "description": "With this COUNT software, we can run a simple query on a campus's Wireless Local Area Network controller (WLAN controller) to obtain the number of connected devices per access point across the whole campus and this can be used as a proxy for the actual number of occupants in the campus. 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The outputs include: time dependent shuttle energy level, time dependent charging station usage, time dependent number of passengers on each bus, time dependent number of passengers at each bus stop, history of number of passengers left at each bus stop, route history of fleet shuttle buses and on-demand buses, and time dependent bus distance traveled.", + "laborHours": 0.0, + "languages": [], + "name": "Athena - Shuttle Bus Optimization and Event Driven Simulator [SWR 20-105]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/athena-bus", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-02-25", + "metadataLastUpdated": "2023-06-01" + }, + "description": "The software provides database access and analysis code for project ATHENA data. 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The examples provided are a representation of the DFW airport for curbside dropoff and and pickup.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "Athena - Digital Twin and Infrastructure Model [SWR 20-106]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/athena-forecast", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-02-25", + "metadataLastUpdated": "2021-02-25" + }, + "description": "Science Capsule captures the processing and data life cycle across machines, organizations, people, and science domains. 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These matrices are more commonly used to represent monetary inputs and outputs by sector. In contrast, the developers have constructed a model that uses a customized matrix consisting of key products and services (in place of sectors) that are directly and/or indirectly relevant to bioenergy systems (and energy systems more broadly). Their matrix tracks inputs and outputs based on physical units and uses prices only to complete the required calculations before converting total requirements back to physical units of interest.", + "laborHours": 0.0, + "languages": [], + "name": "Agile Cradle-to-Grave (Agile C2G) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/olgakavvada/biofuels_lca_tool/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "version": "v1" + }, + { + "contact": { + "email": "sanderb@slac.stanford.edu" + }, + "date": { + "created": "2021-03-08", + "metadataLastUpdated": "2021-03-09" + }, + "description": "This software package is used for the acute shortage ventilator developed to battle against the Covid crisis on a global scale. 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Juqbox.jl is written in the Julia programming language which, among many other features, provides a convenient interface to the Ipopt library.", + "laborHours": 0.0, + "languages": [], + "name": "Juqbox.jl", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Juqbox.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2021-03-11" + }, + "description": "MT-xGEMM is a simple driver for benchmarking xGEMM Level 3 BLAS functions. 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It implements the method as well as related data analysis functions.", + "laborHours": 0.0, + "languages": [], + "name": "Dynamical Components Analysis (DCA) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BouchardLab/DynamicalComponentsAnalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2021-03-12" + }, + "description": "Dynamical Components Analysis is a Python implementation of the method described in \"Unsupervised discovery of temporal structure in noisy data with dynamical components analysis\". It implements the method as well as related data analysis functions.", + "laborHours": 0.0, + "languages": [], + "name": "Dynamical Components Analysis (DCA) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BouchardLab/DynamicalComponentsAnalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2021-03-11" + }, + "description": "This is a software utility used to maximize next-generation sequencing data output without compromising quality values. The DNA Sequencing Optimizer is used to determine the optimal amount of library to load. To do this a supervised machine learning model predicts cluster density, a measure of how much DNA is bound to the sequence, from the concentration of DNA loaded. The output is a plot that is used by experimentalists to determine the best DNA library concentration to load onto the sequencer.", + "laborHours": 0.0, + "languages": [], + "name": "DNA Sequencing Optimizer v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/library_loading_concentration_prediction", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2021-03-12" + }, + "description": "FlexDRL is a framework that can be used as a benchmarking tool to evaluate different Deep Reinforcement Learning algorithms in a building energy management setting. OpenAI Gym was used as wrapper to the co-simulation environment (EnergyPlus for envelope and HVAC and Modelica for battery and PV) to interface with DRL algorithms, which are developed in PyTorch. In order to facilitate the usage of FlexDRL, all the required dependencies have been packaged into a Docker container.", + "laborHours": 0.0, + "languages": [], + "name": "FlexDRL v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/FlexDRL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2023-03-15" + }, + "description": "TAPsolver is a python package, which automates TAP simulation and analysis routines. TAPsolver is built around the python packages FEniCS and Dolfin-Adjoint, which help take advantage of model adjoints to provide automatic derivatives. TAPsolver is flexible, with reaction mechanisms and rate constants that can be set through input files that allow users to take advantage of the different functionalities, which include sensitivity analyses, parameter optimization and uncertainty quantification.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Tapsolver: A Python Package For The Simulation And Analysis Of Tap Reactor Experiments", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/medford-group/TAPsolver", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "prokopenkoav@ornl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2025-04-17" + }, + "description": "ArborX library tackles a problem of efficiently finding geometric objects that are close in space. Variations of this problem, such as finding the nearest neighbors of a point, or finding all objects within a certain distance, are inherent components of applications in many fields. The data may be large so that solving the problem efficiently may require significant computational resources, such as multiple processors or accelerators such as general purpose GPUs.\n\nArborX' main advantage in its ability to solve large problems efficiently utilizing a combination of distributed and on-node parallelism. ArborX can be run efficiently on a wide variety of hardware, including GPUs from different vendors, which distinguishes it from other available libraries which typically choose only few of these. The other advantage is that it supports both types of user problems: spatial problems (useful for intersections and finding objects within certain distance), and nearest neighbor problems. ArborX also supports flexible interface in its interaction with a user. Particularly, it allows a user to call user's own function on a positive match, a functionality not rarely available in other libraries.\n\nArborX implements construction and traversal algorithms using efficient tree structures, such as bounding volume hierarchy (BVH). At its core, it uses linear BVH for its low construction cost and sufficient quality. ArborX is written using C++, and is parallelized using the message passing interface (MPI) for the distributed communication, and the Kokkos library for on-node parallelism. This approach allows ArborX to be run on a wide variety of hardware, from common laptops and desktops to supercomputers while using the same codebase. ArborX also implements several advanced algorithms using geometric search, such as density-based clustering algorithm DBSCAN.", + "laborHours": 16492.0, + "languages": [ + "C++" + ], + "name": "ArborX", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/arborx/ArborX", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-03-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a trained machine learning model written in Pytorch for automated control of the FlexyAir\n(https://ocl.sk/hardware/flexyair/) dynamical system control educational device. This software is to be released to support our demonstration of our deepMPC methods on embedded hardware to control a real (albeit tutorial) physical system with control actuators.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/FlexyAirDeepMPC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/FlexyAirDeepMPC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "lukensjm@ornl.gov" + }, + "date": { + "created": "2021-03-12", + "metadataLastUpdated": "2021-03-12" + }, + "description": "This code provides examples of a new, self-contained approach for Bayesian quantum state estimation which offers improved computational efficiency compared to previous approaches. Leveraging advances in machine learning and statistics, our formulation relies on highly efficient preconditioned Crank-Nicolson sampling and a pseudo-likelihood. Details of the theory behind it can be found in our paper https://doi.org/10.1088/1367-2630/ab8efa", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "BayesQuanTom", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmlukens/BayesQuanTom", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-15", + "metadataLastUpdated": "2021-03-15" + }, + "description": "The software is a general optimizer, simliar to scipy.minimize, but using advanced methods and it is HPC ready.", + "laborHours": 0.0, + "languages": [], + "name": "HGDL v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/hgdl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "version": "v1" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-03-15", + "metadataLastUpdated": "2021-03-15" + }, + "description": "Flexible API for combinating and generating parsers given a JSON schema.", + "laborHours": 0.0, + "languages": [], + "name": "Generalized Nuclear Data - Mim", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GeneralizedNuclearData/Mim/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GeneralizedNuclearData/Mim", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-03-15", + "metadataLastUpdated": "2021-03-15" + }, + "description": "Schemas defining the GNDS format. Hosting the schemas in a public place allows anyone to refer to them and a common place to store them.", + "laborHours": 0.0, + "languages": [], + "name": "Generalized Nuclear Data - schemas ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GeneralizedNuclearData/schemas/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GeneralizedNuclearData/schemas", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-03-15", + "metadataLastUpdated": "2021-03-15" + }, + "description": "This repository describes the goals and governance of WPEC Subgroup 43 (SG43). 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The resulting application, DiBELLA, is the first distributed memory overlapper and aligner specifically designed for long reads and parallel scalability.", + "homepageURL": "https://sourceforge.net/projects/dibella", + "laborHours": 0.0, + "languages": [], + "name": "Distributed Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper (DiBELLA) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/dibella", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-16", + "metadataLastUpdated": "2021-03-16" + }, + "description": "This is a OpenStudio measure that calculates and reports the system-level key performance indicators (KPIs) for evaluating building energy performance at the system level. 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Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 972.8, + "languages": [ + "Python", + "SWIG", + "Assembly" + ], + "name": "PyNetUQ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PyNetUQ", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-03-19", + "metadataLastUpdated": "2021-03-19" + }, + "description": "Open SHMEM is an increasingly popular standard of the SHMEM programing model. 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MIQS achieved up to 99% time reduction in index construction and up to 172,000X search performance improvement with up to 75% reduction in memory footprint.", + "laborHours": 0.0, + "languages": [], + "name": "MIQS v0.6", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/miqs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-23", + "metadataLastUpdated": "2021-03-23" + }, + "description": "In this research, we propose a novel Metadata Indexing and Querying for Self-describing formats (MIQS), which removes the external DBMS and utilizes in-memory index to achieve efficient metadata searching. 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MIQS achieved up to 99% time reduction in index construction and up to 172,000X search performance improvement with up to 75% reduction in memory footprint.", + "laborHours": 0.0, + "languages": [], + "name": "MIQS v0.6", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/miqs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-25", + "metadataLastUpdated": "2021-03-25" + }, + "description": "As extreme-scale era software, we are developing novel object- based data abstractions and storage mechanisms that take advantage of the deep storage hierarchy and enable proactive automated performance tuning. In order to achieve these goals, we have developed a fundamental new data abstraction, called Proactive Data Containers (PDC). 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The code includes a back end module that interfaces with third party open source software (ArangoDB), and a front end user interface (UI) that allows user interaction with the software through a web interface.", + "laborHours": 0.0, + "languages": [], + "name": "CORAL Prototype Implementation (CORAL) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmchandonia/CORAL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-25", + "metadataLastUpdated": "2021-03-31" + }, + "description": "Repository and website for tutorials on 3d Euclidean equivariant neural networks.", + "laborHours": 0.0, + "languages": [], + "name": "e3nn tutorial v0.2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/blondegeek/e3nn_tutorial", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "0.2" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-25", + "metadataLastUpdated": "2021-03-25" + }, + "description": "This toolkit is composed of several modules for extracting buildings geometrical and thermal characteristics from RGB and thermal imagery captured using a drone.\n- Building 3D reconstruction module: leverage a photogrammetry software to construct a 3D point cloud from RGB drone imagery, which is then used in conjunction with image processing and geometric methods to extract building footprint and building height (i.e., 3D model of the building).\n- Windows to wall ratio estimation module: leverage deep learning semantic segmentation modeling to detect windows on 2D drone RGB images. The detected windows are then projected onto the extracted building 3D model (using building 3D reconstruction module) and their area is computed to obtain window to wall ratio estimation.\n- Thermal anomalies detection module: leverage image processing and machine learning algorithm to detect on 2D drone thermal images potential thermal anomalies within building's facades and roofs.", + "laborHours": 0.0, + "languages": [], + "name": "Aerial 3D Building Reconstruction from Drone Imagery (A3DBR) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/a3dbr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v1" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-25", + "metadataLastUpdated": "2021-03-31" + }, + "description": "Emu is a particle-in-cell code for solving the neutrino quantum kinetic equations in 1, 2, or 3 spatial dimensions with arbitrary angular resolution in order to simulate neutrino flavor transformation in neutron star merger and core collapse supernova environments. Emu represents the neutrino distribution function as a set of particles, each of which represent a collection of neutrinos and antineutrinos with unique position and momentum. Each particle carries two density matrices to define the flavor state of the neutrinos and antineutrinos it represents. Emu includes the vacuum, matter, and neutrino self-interaction potentials. Emu calculates the self-interaction potential using PIC deposition and interpolation algorithms that efficiently compute the local number density and flux at particle locations. Emu is implemented in C++ and is based on the AMReX library for high-performance, block-structured adaptive mesh refinement. 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This includes one-way communication for most applications and two-way loose coupling for customizable applications Providing the sequence and timing of events that lead to the specified outcomes when calculating results Traditional aspects of components with basic events, fault trees, and event trees are all captured in a dynamic framework of state diagrams, which are displayed.", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Event-modeled Risk Assessment Using Linked Diagrams", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/EMRALD", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Combining planning models with operational details allows the industry to proactively investigate future resource and load scenarios, rather than react to their implementation in real time. 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The approach allows tracking in near real time and automatically identifies moving objects based on features from the motion track and object size.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "ThermalTracker 3D", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-07", + "metadataLastUpdated": "2021-04-07" + }, + "description": "A library for multi-threaded computation of persistence diagrams. 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Once it is so configured, a reliable Hydra network of ASICs remains that can be reconfigured later to respond to damage or malfunction of one or more of the constituent ASICs.", + "homepageURL": "https://sites.google.com/lbl.gov/hydra2020-132/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Hydra Network Automatic Configuration (Hydra Autoconfig) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/hydra2020-132/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-08", + "metadataLastUpdated": "2021-04-08" + }, + "description": "The Building Performance Database (BPD) is the largest publicly-available source of measured energy performance data for buildings in the United States. 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While the common use cases for VPIC employ low-order particles on rectilinear meshes, a framework exists to treat higher-order particles and curvilinear meshes, as well as more advanced field solvers.", + "laborHours": 0.0, + "languages": [ + "C++", + "C" + ], + "name": "VPIC v.1.2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vpic", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "1.2" + }, + { + "contact": { + "email": "ajnonaka@lbl.gov" + }, + "date": { + "created": "2021-04-15", + "metadataLastUpdated": "2021-04-15" + }, + "description": "MAESTROeX is a massively parallel, finite-volume C++/F90 solver for low Mach number astrophysical flows. 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The BDRM supports requests to get multiple files in a single call, manages a queue of the requested files, brings in as many files as the space quota permits, and continues to reuse the space when files are released to stream files to the client until the entire request is satisfied. Similarly, the B-DRM supports requests to put multiple files into its space, streaming files into the allocated space and reusing the space if necessary.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "gcc 2.9x" + ], + "name": "Berkeley Disk Resource Manager", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This software is a library for C and C++ programmers to use for fast and efficient parsing and processing of symbolic expressions, or s-expressions. An s-expression is a text-representation of a tree data structure, and is the basis for the syntax of the LISP and Scheme programming languages. Multiple similar libraries exist, but this one was designed from the ground up for speed, efficiency, and simplicity.", + "laborHours": 0.0, + "languages": [ + "Any ANSI-C compiler" + ], + "name": "Small, Fast S-Expression Library, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mjsottile/sfsexp/blob/master/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mjsottile/sfsexp", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "Ipmiconsole is a tool and library that allows a user to establish a console session with a remote machine using the IPMI Serial over LAN (SOL) protocol", + "homepageURL": "https://www.gnu.org/software/freeipmi/index.html", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "ipmiconsole", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "WebLogo is a web based application designed to make the generation of sequence logos as easy and painless as possible. 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In general, a sequence logo provides a richer and more precise description of, for example, a binding site, than would a consensus sequence.", + "homepageURL": "http://weblogo.berkeley.edu", + "laborHours": 0.0, + "languages": [], + "name": "WebLogo", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://weblogo.berkeley.edu", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Toba is an extensible personal information retrieval system. It supports various plugins which the user uses to create and store bits of information. It comes configured to store meeting notes, task items, issue, and business development opportunities. Plugins could be written to support almost any kind of digital information. So with the right plugins, Toba could become a full fledged contact manager, project management application, programmer's toolkit, or almost any other type of data storage/search/retrieval application imaginable. Toba comes with a built in command line interface and via a plugin it has a fully scripting language (jython). The information stored can be searched by keyword or through SQL queries.", + "laborHours": 0.0, + "languages": [], + "name": "TOBA", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/toba", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This package implements system-level checkpointing of scientific applications running on Linux clusters in a manner suitable for implementing preemption, migration and fault recovery by a batch scheduler The design includes documented interfaces for a cooperating application or library to implement extensions to the checkpoint system, such as consistent checkpointing of distributed MPI applications Using this package with an appropriate MPI implementation, the vast majority of scientific applications which use MPI for communication are checkpointable without any modifications to the application source code. Extending VMAdump code used in the bproc system, the BLCR kernel modules provide three additional features necessary for useful system-level checkpointing of scientific applications(installation of bproc is not required to use BLCR) First, this package provides the bookkeeping and coordination required for checkpointing and restoring multi-threaded and multi-process applications running on a single node Secondly, this package provides a system call interface allowing checkpoints to be requested by any authorized process, such as a batch scheduler. Thirdly, this package provides a system call interface allowing applications and/or application libraries to extend the checkpoint capabilities in user space, for instance to provide coordination of checkpoints of distributed MPI applications. The \"Iibcr\" library in this package implements a wrapper around the system call interface exported by the kernel modules, and maintains bookkeeping to allow registration of callbacks by runtime libraries This library also provides the necessary thread-safety and signal-safety mechanisms Thus, this library provides the means for applications and run-time libraries, such as MPI, to register callback functions to be run when a checkpoint is taken or when restarting from one. This library may also be used as a LD_PRELOAD to enable checkpointing of applications with development releases of BLCR (which cannot preempt unmodified applications otherwise). This package also includes simple command line utilities to request a checkpoint or restart of a process. These provide the means for a user, system administrator, or batch scheduler to use BLCR.", + "homepageURL": "https://crd.lbl.gov/departments/computer-science/class/research/past-projects/BLCR", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Lab Checkpoint/Restart for Linux", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://crd.lbl.gov/departments/computer-science/class/research/past-projects/BLCR", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://crd.lbl.gov/departments/computer-science/class/research/past-projects/BLCR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This library implements a memory allocator/manager which ask its host program or library for memory refions to manage rather than requesting them from the operating system. 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This package is a modified version of the LGPL-licensed \"mmalloc\" allocator from release 5.2 of the \"gdb\" debugger's source code.", + "laborHours": 0.0, + "languages": [ + "Any ANSI C compiler." + ], + "name": "The Unobtrusive Memory Allocator", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upc-runtime/src/master/umalloc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This package permits a scientist to perform computations using an arbitrarily high level of numeric precision (the equivalent of hundreds or even thousands of digits), by making only minor changes to conventional C++ or Fortran-90 soruce code. This software takes advantage of certain properties of IEEE floating-point arithmetic, together with advanced numeric algorithms, custom data types and operator overloading. Also included in this package is the \"Experimental Mathematician's Toolkit\", which incorporates many of these facilities into an easy-to-use interactive program.", + "homepageURL": "https://www.davidhbailey.com/dhbsoftware", + "laborHours": 0.0, + "languages": [ + "C++ and F90 compilers" + ], + "name": "An Arbitrary Precision Computation Package", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.davidhbailey.com/dhbsoftware", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.davidhbailey.com/dhbsoftware", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "Akenti is an authorization service for distributed resources. The authorization policy is kept in distributed certificates signed by one or more stakeholders for the resources. The package consists of the following components: Java GUI tools to create and sign the policy certificates C++ libraries to do make access decisions based on the policy certificates A standalone authorization server that make access decisions C interfaces to the libraries and server", + "homepageURL": "https://dst.lbl.gov/ACSSoftware/Akenti", + "laborHours": 0.0, + "languages": [ + "gcc 2.95.3, jdk 1.3" + ], + "name": "Akenti Authorization System", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://dst.lbl.gov/ACSSoftware/Akenti/download.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dst.lbl.gov/ACSSoftware/Akenti", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This package permits a scientist to perform computations using a precision level of either 32 or 64 decimal digits, by making only minor changes to conventional C++ or Fortran-90 source code. This software takes advantage of certain properties of IEEE floating-point arithmetic, together with advanced numeric algorithms, custom datatypes and operator overloading.", + "homepageURL": "https://www.davidhbailey.com/dhbsoftware", + "laborHours": 0.0, + "languages": [], + "name": "QD: A Double-Double/Quad-Double Package", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.davidhbailey.com/dhbsoftware", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.davidhbailey.com/dhbsoftware", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "AMELIA is an application with focus on particle physics processes in ATLAS. This will allow students and other users to decode the collision events that unfold after the head-on collisions of protons at the Large hadron Collider. AMELIA uses the Irrlicht engine for the 3D graphics and wxWidgets for the interface. It uses the best aspects of technical animation and allows users to control 3D representations of collision events and to manipulate 3D models of the detector and see how particles are detected as they pass through. It allows the user to rotate, zoom and select virtual pieces of the ATLAS detector and events. The characteristics of the events (momentum etc.) can also be read, and one can select tracks for analysis, activate context-oriented media, etc. This framework intends to integrate different types of media into a single product. This way, videos, animations, sound, interactive visualization and data analysis will be bound together in the same package.-", + "homepageURL": "https://sourceforge.net/projects/amelia", + "laborHours": 0.0, + "languages": [], + "name": "Atlas Multimedia Educational Lab for Interactive Analysis", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/amelia", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "DRQAT (Demand Response Quick Assessment Tool) is the tool for assessing demand response saving potentials for large commercial buildings. This tool is based on EnergyPlus simulations of prototypical buildings and HVAC equipment. The opportunities for demand reduction and cost savings with building demand responsive controls vary tremendously with building type and location. The assessment tools will predict the energy and demand savings, the economic savings, and the thermal comfort impact for various demand responsive strategies. Users of the tools will be asked to enter the basic building information such as types, square footage, building envelope, orientation, utility schedule, etc. The assessment tools will then use the prototypical simulation models to calculate the energy and demand reduction potential under certain demand responsive strategies, such as precooling, zonal temperature set up, and chilled water loop and air loop set points adjustment.", + "homepageURL": "https://buildings.lbl.gov/demand-response-quick-assessment-tool-drqat", + "laborHours": 0.0, + "languages": [], + "name": "Demand Response Quick Assessment Tool", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://buildings.lbl.gov/demand-response-quick-assessment-tool-drqat", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://buildings.lbl.gov/demand-response-quick-assessment-tool-drqat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Ipmi-fru retrieves field replacement unit (FRU) information, such as product name, manufacturer, and serial numbers, from a motherboard. It retrieves this information using the IPMI protocol.", + "homepageURL": "https://www.gnu.org/software/freeipmi/index.html", + "laborHours": 0.0, + "languages": [], + "name": "ipmi-fru", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The GAM/GAMV GUI provides a graphic user interface to public domain FORTRAN codes (gam, version 2.0 and gamv, version 2.0) that were developed at Stanford University in 1998 (see Deutsch and Journel, 1998). The gam and gamv codes allow for calculation of different measures of spatial variability and spatial correction from a set of available data. The GAM/GAMV GUI accesses the executable versions of the gam and gamv software, initiates the calculations by the executables and manages the outputs of the executables in a user friendly graphical manner. Additionally, the GAM/GAMV GUI code then provides the user with both automatic and interactive tools in a graphical interface to fit models to the calculations of the spatial variation/correlation of the data. The GAM/GAMV GUI software allows the user to get various parameters for the gam and gamv executables that do the actual calculations by using dialog boxes, it provides some error checking as these parameters are set and then allows the user to run the calculation by calling the executable compiled from the previously developed FORTRAN software. The resulting output of the gam or gamv codes can be visualized in the GAM/GAMV GUI interface. The visualization portion of GAM/GAMV allows for both automatic and manual fitting of the model of spatial variation/correlation. GAM/GAMV GUI can be run in batch mode from the command line without invoking the graphical interface.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "GAM/GAMV GUI", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/GAM-GAMV-GUI-AND-K3TD?tab=readme-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GAM-GAMV-GUI-AND-K3TD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The KT3D GUI provides a graphic user interface to a public domain FORTRAN code (kt3d) that was developed at Stanford University in 1998 (see Deutsch and Journel, 1998). The kt3d software contains the implementation of several kriging algorithms that complete spatial estimation onto a grid or a set of points from a set of available data and using a variogram model to describe the spatial variation of the data. The variogram model is calculated and modeled using the GAM/GAMV GUI software described separately. The KT3D GUI software allows the user to set various parameters for the FORTRAN code by using dialog boxes, it provides some error checking as these parameters are set and then allows the user to run the calculation by calling the executable compiled from the previously developed FORTRAN software. The resulting output of the kt3d code can be visualized in the KT3D GUI in several ways. If a gridded estimation problem is selected, color maps of the estimated values and the kriging variance are displayed in side by side images. If either jackknifing or cross-validation options are selected, then a series of user-defined X-Y plots can be created.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "KT3D GUI", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/GAM-GAMV-GUI-AND-K3TD?tab=readme-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GAM-GAMV-GUI-AND-K3TD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Dr. L provides two-dimensional visualizations of very large abstract graph structures. it can be used for data mining applications including biology, scientific literature, and social network analysis. Dr. L is a graph layout program that uses a multilevel force-directed algorithm. A graph is input and drawn using a force-directed algorithm based on simulated annealing. The resulting layout is clustered using a single link algorithm. This clustering is used to produce a coarsened graph (fewer nodes) which is then re-drawn. this process is repeated until a sufficiently small graph is produced. The smallest graph is drawn and then used as a basis for drawing the original graph by refining the series of coarsened graphs that were produced. The layout engine can be run in serial or in parallel.", + "homepageURL": "https://www.sandia.gov/smartin/software.html", + "laborHours": 0.0, + "languages": [ + "g++ and bash" + ], + "name": "Dr.L: Distributed Recursive (Graph) Layout", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.sandia.gov/smartin/software.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Provides a basic collection of utility plugins for use in the MVC Shell or MVC Framework environment. The MVC PluginLib is implemented in C# as a collection of.NET 2.0 frameworks that implement MVC Framework and MVC Shell compatible plugins. Three plugins are provided at this time, with more to be added over time: ApplicationInfoPlugin - provides basic information about the running application IronPythonPlugin - provides an IronPython based interactive shell environment ProgressBarPlugin - provides a basic progress bar implementation.", + "homepageURL": "https://archive.codeplex.com/?p=mvcpluginlib", + "laborHours": 0.0, + "languages": [], + "name": "MVC Plugin Lib", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://archive.codeplex.com/?p=mvcpluginlib", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Provides a reusable model-view-controller application programming interface (API) for use in the rapid development of graphical user interface applications in the .NET 2.0 framework. This includes a mechanism for adding new data stores, data sources, data analyses, and visualizations in the form of plugins.] The MVC Framework is implemented in C# as a .NET 2.0 framework that can then be built against when developing applications. The infrastructure allows for presenting application specific views (visualizations) to the user to interact with. Based on the interactions the user makes with a view, requests are generated which in turn are handled by the central controller facility. The controller handles the request in an application specific manner by routing the request to appropriate data stores, data accessors or data analyzers. Retrieved or processed data is published to subscribed components for further processing or for presentation to the user.", + "homepageURL": "http://www.codeplex.com/mvcframework", + "laborHours": 0.0, + "languages": [ + ".NET Framework 2.0" + ], + "name": "MVC Framework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.codeplex.com/mvcframework", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-22" + }, + "description": "This software is a set of utility libraries and tools developed in support of multiple scientific simulation projects. These libraries provide many general-purpose capabilities, such as a compact, extensible, machine-independent binary file format for various forms of scientific data, a Fortran-callable command parser that supports symbolic variables, looping, and conditional constructs, a Fortran-callable interface to ITT Corporation's callable IDL graphics and data analysis, a multi-block, 2D electrostatic solver, a machine-independent Fortran interface to standard system services, and various Fortran-callable dynamic memory services. In some cases, C interfaces are also provided. In addition, some tools that use these various libraries are available. A brief description of each library/tool follows: PFF library - PFF is a compact, extensible, machine-independent binary file format for various forms of scientific data. Two libraries are provided: one designed to be called from Fortran 77, and the other designed to be called from C or C++. Dataset types for several varieties of scientific data are built into the library, and new dataset types can be added. The libraries provide support for reading/writing these datasets from/to PFF files, as well as functionality for interactive processing of PFF files and the data they contain. Tools for manipulating, converting, and comparing PFF data are also available.", + "laborHours": 42043.2, + "languages": [ + "C++", + "C", + "Fortran", + "Python" + ], + "name": "Hermes Utility Libraries and Tools", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hermes-util", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The Transport version 3 (T3) system uses the Network News Transfer Protocol (NNTP) to move data from sources to a Data Repository (DR). Interested recipients subscribe to newsgroups to retrieve data. Data in transport is protected by AES-256 and RSA cryptographic services provided by the external OpenSSL cryptographic libraries.", + "homepageURL": "https://svn.pnl.gov/transport", + "laborHours": 0.0, + "languages": [ + "Python and Perl" + ], + "name": "Transport Version 3", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://svn.pnl.gov/transport", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.pnl.gov/transport", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The software calculates the interior eigenstates of a nanosystem with a given Hamiltonian. This is used for nonselfconsistent calculations of electron and hole states for large (a few thousands to hundreds of thousands of atoms) nanostructures. The electron wave function is represented by a planewave basis set. FFT is used to transform the wavefunction from reciprocal space to real space to be applied to the potential. Nonlocal pseudopotentlals are used in the Hamiltonian and spin-orbit interactions are included. One primary approach to calculate the interior eigenstates in the code is to use the folded spectrum method. Several numerical algorithms are implemented in this package, including the conjugated gradient method, the Jacobi-Davidson method, and the LOPCG method. The user can select different algorithms based on their particular problem and number of wavefunctions needed to be solved.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Fortran 90 and C" + ], + "name": "Pescan", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "GenOpt is a generic optimization program for nonlinear, constrained optimization. For evaluating the objective function, any simulation program that communicates over text files can be coupled to GenOpt without code modification. No analytic properties of the objective function are used by GenOpt. Optimization algorithms and numerical methods can be implemented in a library and shared among users. GenOpt offers an interlace between the optimization algorithm and its kernel to make the implementation of new algorithms fast and easy. Different algorithms of constrained and unconstrained minimization can be added to a library. Algorithms for approximation derivatives and performing line-search will be implemented. The objective function is evaluated as a black-box function by an external simulation program. The kernel of GenOpt deals with the data I/O, result storage and report, interlace to the external simulation program, and error handling. An abstract optimization class offers methods to interface the GenOpt kernel and the optimization algorithm library.", + "homepageURL": "http://simulationresearch.lbl.gov/GO", + "laborHours": 0.0, + "languages": [], + "name": "Generic Optimization Program", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://simulationresearch.lbl.gov/GO/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://simulationresearch.lbl.gov/GO", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The Building Controls Virtual Test Bed (BCVTB) is a modular software environment that is based on the Ptolemy II software environment. The BCVTB can be used for design and analysis of heterogenous systems, such as building energy and controls systems. Our additions to Ptolemy II allow users to Couple to Ptolemy II simulation software such as EnergyPlus, MATLAB/Simulink or Dymola for data exchange during run-time. Future versions of the BCVTS will also contain an interface to BACnet which is a communication protocol for building Control systems, and interfaces to digital/analog converters that allow communication with controls hardware. Through Ptolemy II, the BCVTB provides a graphical model building environment, synchronizes the exchanged data and visualizes the system evolution during run- time.", + "homepageURL": "https://simulationresearch.lbl.gov/bcvtb", + "laborHours": 0.0, + "languages": [], + "name": "Building Controls Virtual Test Bed", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://simulationresearch.lbl.gov/bcvtb/License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://simulationresearch.lbl.gov/bcvtb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Voro++ is a software library for the Computation of 3D Voronoi cells. It is primarily designed for applications in physics and materials science, where Voronoi cells can be a useful tool in the analysis of densely-packed particle systems. For a set of points in a space, the Voronoi cell of each particle is defined as the region which is closer to that particle than any other. Originally defined by Georgy Voronci [1], it has become a powerful tool in many scientific fields, whenever region of space must be divided between constituent points or particles [2]. Over the past twenty years, the algorithms for computing Voronoi cells have been well-studied, and several high-quality software packages are available. However, some (such as Triangle [3] are designed for the 2D case. Others, such as QHull [4], make use of algorithms for computing complete tessellations. This can offer limited flexibility, such as for handling complex boundary conditions, where direct cell-by-cell manipulation is beneficial. Voro++ is a library of C++ classes for direct computation of 3D Voronoi cells. The author believes this the first general purpose library that takes full advantage of the C++ class structure, making it simple to use, modify, and incorporate into other programs. The author has received considerable interest from other academic institutions about making use of the code. Features include: -- Rapid computation times, two to three times faster than Qhull in some typical cases -- Support for floating point inaccuracies and degenerate cases -- Support for curved and planar walls; periodic and non-periodic boundary conditions -- Support for radical Voronoi tessellations and neighbor list computations --Straightforward generalization to a parallel/ multicore architecture.", + "homepageURL": "http://math.lbl.gov/voro++", + "laborHours": 0.0, + "languages": [], + "name": "VORO++", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://math.lbl.gov/voro++/download", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://math.lbl.gov/voro++", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Nek5000 is high-order spectral element code used for the simulation of incompressible fluid flow, MHD, and heat transfer in general three-dimensional domains that has been specifically developed for deployment on large-scale distributed memory parallel architectures. The code features state of the art matrix free multilevel iterative solvers coupled with stable second and third order operator-split stepping schemes. Scalable performance has been established onup to 32,000 processors and the overall quality of the algorithmic approach, implementation, and performance were recognized with the award of the Gordon Bell Prize in 1999.", + "laborHours": 0.0, + "languages": [ + "f77/C" + ], + "name": "Nek5000", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/Nek5000/Nek5000/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Nek5000/Nek5000", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Ipmi-dcmi supports motherboards compliant to the Data Center Management Interface (DCMI) specification, DCMI features include asset management and power limit management.", + "homepageURL": "https://www.gnu.org/software/freeipmi/index.html", + "laborHours": 0.0, + "languages": [], + "name": "ipmi-dcmi", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "This is a Matlab toolbox for investigating the application of cluster ensembles to data classification, with the objective of improving the accuracy and/or speed of clustering. The toolbox divides the cluster ensemble problem into four areas, providing functionality for each. These include, (1) synthetic data generation, (2) clustering to generate individual data partitions and similarity matrices, (3) consensus function generation and final clustering to generate ensemble data partitioning, and (4) implementation of accuracy metrics. With regard to data generation, Gaussian data of arbitrary dimension can be generated. The kcenters algorithm can then be used to generate individual data partitions by either, (a) subsampling the data and clustering each subsample, or by (b) randomly initializing the algorithm and generating a clustering for each initialization. In either case an overall similarity matrix can be computed using a consensus function operating on the individual similarity matrices. A final clustering can be performed and performance metrics are provided for evaluation purposes.", + "homepageURL": "https://www.mathworks.com/matlabcentral/fileexchange/23941-matlab-cluster-ensemble-toolbox", + "laborHours": 0.0, + "languages": [], + "name": "Matlab Cluster Ensemble Toolbox", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.mathworks.com/matlabcentral/fileexchange/23941-matlab-cluster-ensemble-toolbox", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.mathworks.com/matlabcentral/fileexchange/23941-matlab-cluster-ensemble-toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Zonetool is a utility for managing signed DNS zones and managing DNSSEC keys. It maintains the state of managed DNS zones and uses the BIND utilities to actually perform key generation, zone signing, and validation. DNS administrators will use Zonetool to initially deploy and further maintain a signed DNS zone.", + "laborHours": 0.0, + "languages": [], + "name": "Zonetool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/zonetool", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "PACT is a set of tools to help software developers create applications that will run on any platform and data that can be written/read on any platform.", + "homepageURL": "https://code.google.com/p/pactnew", + "laborHours": 0.0, + "languages": [], + "name": "Portable Application Code Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.google.com/p/pactnew", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Provides a tool with which create and characterize a very large set of matrix-based visual analogy problems that have properties that are similar to Raven's Progressive Matrices (RPMs)™. The software uses the same underlying patterns found in RPMs to generate large numbers of unique matrix problems using parameters chosen by the researcher. Specifically, the software is designed so that researchers can choose the type, direction, and number of relations in a problem and then create any number of unique matrices that share the same underlying structure (e.g. changes in numerosity in a diagonal pattern) but have different surface features (e.g. shapes, colors).Raven's Progressive Matrices (RPMs) ™ are a widely-used test for assessing intelligence and reasoning ability. Since the test is non-verbal, it can be applied to many different populations and has been used all over the world. However, there are relatively few matrices in the sets developed by Raven, which limits their use in experiments requiring large numbers of stimuli. This tool creates a matrix set in a systematic way that allows researchers to have a great deal of control over the underlying structure, surface features, and difficulty of the matrix problems while providing a large set of novel matrices with which to conduct experiments.", + "laborHours": 0.0, + "languages": [], + "name": "Sandia Generated Matrix Tool (SGMT) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Matrices", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The ESnet On-Demand Secure Circuits and Advance Reservation System (OSCARS) is a prototype service enabling advance reservation of guaranteed bandwidth secure virtual circuits. OSCARS operates within the Energy Sciences Network (ESnet), and has provisions for interoperation with other network domains. OSCARS utilizes the Web services model and standards to implement communication with the system and between domains, and for authentication, authorization, and auditing (AAA). The management and operation of end-to-end virtual circuits within the network is done at the layer 3 network level. Multi-Protocol Label Switching (MPLS) and the Resource Reservation Protocol (RSVP) are used to create the virtual circuits or Label Switched Paths (LSP's). Quality of Service (QoS) is used to provide bandwidth guarantees.", + "homepageURL": "https://www.es.net/engineering-services/oscars", + "laborHours": 0.0, + "languages": [ + "None" + ], + "name": "Oscars", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.es.net/engineering-services/oscars", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The national Water, Energy and Carbon Sequestration Simulation Model (WECSsim) is an analysis tool that can be used at the local, regional and national scale to address a potentially combined system using a coal or natural gas-fired power plant, a geologic carbon sequestration system in saline formations, and water extraction and treatment. With this combined system for geologic storage of CO2 in saline formations, the treated saline formation water could be used as cooling water in the power plant. The key areas addressed in this tool include applying a data reduction process to existing NatCarb saline formation data to select the most viable formations for CO2 injection, water withdrawal and treatment metrics, and developing a national model to address the multiple combinations of power plants and saline formations. This model can be utilized by decision makers to understand the economic benefits and tradeoffs of this combined system. WECSsim allows for sensitivity analyses for capital costs, variables costs, CO2 sequestration and water treatment systems' costs. The main goal of the WECSsim model is to allow interested individuals or groups the ability to run custom power plant, CO2 sequestration and water use scenarios for different regions of the country and understand the associated economics, longevity and potential of the CO2 sequestration and water extraction systems.", + "laborHours": 0.0, + "languages": [ + "PowerSim Studio 7" + ], + "name": "Water, Energy and Carbon Sequestration Model (WECSsim) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/WECSSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Zoltan2 is a refactoring of the open-source Zoltan library that enables Zoltan users to take better advantage of current and emerging high performance computing architectures and software tools. Like Zoltan, Zoltan2 is a toolkit of combinatorial scientific computing algorithms that enable better performance of scientific codes via improved data locality and parallel scalability. Specifically Zoltan2 partitions data, colors graphs, and orders matrices. Zoltan2 is a software library written in template C++; it supports a wider range of data types and problem sizes than Zoltan. It will be available as part of Sandia's Trilinos framework of scientific computing packages.", + "laborHours": 8344830.4, + "languages": [], + "name": "Zoltan2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Impiseld stores IPMI based hardware events into normal system logs.", + "homepageURL": "https://www.gnu.org/software/freeipmi/index.html", + "laborHours": 0.0, + "languages": [], + "name": "ipmiseld", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Warp is a multidimensional discrete-particle beam simulation program designed to be applicable where the beam space-charge is non-negligible or dominant. It is being developed in a collaboration among LLNL, LBNL and the University of Maryland. It was originally designed and optimized for heave ion fusion accelerator physics studies, but has received use in a broader range of applications, including for example laser wakefield accelerators, e-cloud studies in high enery accelerators, particle traps and other areas. At present it incorporates 3-D, axisymmetric (r,z) planar (x-z) and transverse slice (x,y) descriptions, with both electrostatic and electro-magnetic fields, and a beam envelope model. The code is guilt atop the Python interpreter language.", + "laborHours": 0.0, + "languages": [], + "name": "Particle-in-cell/accelerator code for space-charge dominated beam simulation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/warp/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "We study the detection of mutations, sequencing errors, and homologous horizontal gene transfers (HGT) in a set of closely related microbial genomes. We base the model on single nucleotide polymorphisms (SNP's) and break the genomes into blocks to handle the rearrangement problem. Then we apply a synamic programming algorithm to model whether changes within each block are likely a result of mutations, sequencing errors, or HGT.", + "homepageURL": "https://sourceforge.net/projects/hgtfinder", + "laborHours": 0.0, + "languages": [], + "name": "Detection of homologous horizontal gene transfer in SNP data", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sourceforge.net/projects/hgtfinder/files", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/hgtfinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The function of the World Oil Market Model (WOMM) is to calculate a world oil price. SEDS will set start and end dates for the forecast period, and a time increment (assumed to be 1 year in the initial version). The WOMM will then randomly select an Annual Energy Outlook (AEO) oil price case and calibrate itself to that case. As it steps through each year, the WOMM will generate a stochastic supply shock to OPEC output and accept a new estimate of U.S. petroleum demand from SEDS. The WOMM will then calculate a new oil market equilibrium for the current year. The world oil price at the new equilibrium will be sent back to SEDS. When the end year is reached, the process will begin again with the selection of a new AEO forecast. Iterations over forecasts will continue until SEDS has completed all its simulation runs.", + "homepageURL": "https://www.nrel.gov/analysis/seds/oil-market-module.html", + "laborHours": 0.0, + "languages": [ + "Lumina Decision System's Analytica version 4.3" + ], + "name": "Stochastic Energy Deployment System (SEDS) World Oil Model (WOM)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/analysis/seds/download-model.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/analysis/seds/oil-market-module.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The EDEN toolkit facilitates exploratory data analysis and visualization of global climate model simulation datasets. EDEN provides an interactive graphical user interface (GUI) that helps the user visually construct dynamic queries of the characteristically large climate datasets using temporal ranges, variable selections, and geographic areas of interest. EDEN reads the selected data into a multivariate visualization panel which features an extended implementation of parallel coordinates plots as well as interactive scatterplots. The user can query data in the visualization panel using mouse gestures to analyze different ranges of data. The visualization panel provides coordinated multiple views whereby selections made in one plot are propagated to the other plots.", + "laborHours": 0.0, + "languages": [ + "Java 1.6 or higher" + ], + "name": "Ensemble Data Analysis ENvironment (EDEN)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/csteed/eden/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csteed/eden", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "FREYA is a computer code that generates complete fission events. The output includes the energy and momentum of these final state particles: fission products, prompt neutrons and prompt photons. The version of FREYA that is to be released is a module for MCNP6.", + "homepageURL": "http://nuclear.llnl.gov/simulations", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Event-by-event fission simulation code, generates complete fission events", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://nuclear.llnl.gov/simulations", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://nuclear.llnl.gov/simulations", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2022-11-16" + }, + "description": "EQ3/6 is a software package for modeling geochemical interactions between aqueous solution, solids, and gases, following principles of chemical thermodynamics and chemical kinetics. It is useful for interpreting aqueous solution chemical compositions and for calculating the consequences of reaction of such solutions with minerals, other solids, and gases. It is designed to run in a command line environment. EQPT is a thermodynamic data file preprocessor. EQ3NR is a speciation-solubility code. EQ6 is a reaction path code.", + "laborHours": 0.0, + "languages": [], + "name": "EQ3/6 A Software Package for Geochemical Modeling", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/eq3_6", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "CorAL is a software Library designed to aid in the analysis of femtoscipic data. Femtoscopic data are a class of measured quantities used in heavy-ion collisions to characterize particle emitting source sizes. The most common type of this data is two-particle correleations induced by the Hanbury-Brown/Twiss (HBT) Effect, but can also include correlations induced by final-state interactions between pairs of emitted particles in a heavy-ion collision. Because heavy-ion collisions are complex many particle systems, modeling hydrodynamical models or hybrid techniques. Using the CRAB module, CorAL can turn the output from these models into something that can be directley compared to experimental data. CorAL can also take the raw experimentally measured correlation functions and image them by inverting the Koonin-Pratt equation to extract the space-time emission profile of the particle emitting source. This source function can be further analyzed or directly compared to theoretical calculations.", + "homepageURL": "https://asc.llnl.gov/CORAL-benchmarks", + "laborHours": 0.0, + "languages": [ + "C++, Python" + ], + "name": "Correlation Algorithm Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://asc.llnl.gov/CORAL-benchmarks", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://asc.llnl.gov/CORAL-benchmarks", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Community detection has become a fundamental operation in numerous graph-theoretic applications. It is used to reveal natural divisions that exist within real world networks without imposing prior size or cardinality constraints on the set of communities. Despite its potential for application, there is only limited support for community detection on large-scale parallel computers, largely owing to the irregular and inherently sequential nature of the underlying heuristics. In this paper, we present parallelization heuristics for fast community detection using the Louvain method as the serial template. The Louvain method is an iterative heuristic for modularity optimization. Originally developed by Blondel et al. in 2008, the method has become increasingly popular owing to its ability to detect high modularity community partitions in a fast and memory-efficient manner. However, the method is also inherently sequential, thereby limiting its scalability. Here, we observe certain key properties of this method that present challenges for its parallelization, and consequently propose heuristics that are designed to break the sequential barrier. For evaluation purposes, we implemented our heuristics using OpenMP multithreading, and tested them over real world graphs derived from multiple application domains (e.g., internet, citation, biological). Compared to the serial Louvain implementation, our parallel implementation is able to produce community outputs with a higher modularity for most of the inputs tested, in comparable number of iterations, while providing real speedups of up to 8x using 32 threads. In addition, our parallel implementation was able to exhibit weak scaling properties on up to 32 threads.", + "laborHours": 0.0, + "languages": [], + "name": "Grappolo", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exa-Graph/grappolo", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The PNNL Prony Ringdown graphical user interface is one analysis tool included in the Dynamic System Identification toolbox (DSI Toolbox). The Dynamic System Identification toolbox is a MATLAB-based collection of tools for parsing and analyzing phasor measurement unit data, especially in regards to small signal stability. It includes tools to read the data, preprocess it, and perform small signal analysis. 5. Method of Solution: The Dynamic System Identification Toolbox (DSI Toolbox) is designed to provide a research environment for examining phasor measurement unit data and performing small signal stability analysis. The software uses a series of text-driven menus to help guide users and organize the toolbox features. Methods for reading in populate phasor measurement unit data are provided, with appropriate preprocessing options for small-signal-stability analysis. The toolbox includes the Prony Ringdown GUI and basic algorithms to estimate information on oscillatory modes of the system, such as modal frequency and damping ratio.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Prony Ringdown GUI (CERTS Prony Ringdown, part of the DSI Tool Box)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ftuffner/DSIToolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "FABLE is a Fortran to C++ source-to-source conversion tool. This enables the continued development of new methods even while switching programming languages. FABLE is available under a nonrestrictive open source license. In FABLE the analysis of the Fortran source is separated from the generation of the C++ source. Therefore parts of FABLE could be reused for other target languages. Hardware req.: Multi-platform; types of files: source code, sample problem Input data, sample problem output, installation instructions, user guide.", + "laborHours": 0.0, + "languages": [ + "fortran" + ], + "name": "FABLE - automatic Fortran to C++ conversion", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cctbx/cctbx_project/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cctbx/cctbx_project", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-09-08" + }, + "description": "Alquimia provides a generic interface between flow and transport simulators (drivers) and biogeochemical reaction capabilities (engines). Alquimia consists of two parts: an application programming interface, API, and a wrapper library. The API describes in detail how information is exchanged between the driver and the engine. This includes the function call signatures and data structures required for implementing alquimia in a mixed language (C/C++/Fortran) programming environment. The library is an implementation of the documented API, providing an interface into the biogeochemistry routines supplied by other codes: Alquimia does not do any geochemical calculations. Version 1.0 provides interfaces to the open source codes (BSD) CrunchFlow/CrunchTope and (LGPL) PFLOTRAN. Version 1.0 meets the policies set forth by (and is part of) the Extreme-scale Scientific Software Development Kit, xSDK version 0.6.0.", + "laborHours": 0.0, + "languages": [ + "C++", + "Fortran" + ], + "name": "Alquimia", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LBL-EESA/alquimia-dev/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-EESA/alquimia-dev", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Warewulf is a scalable systems management suite originally developed to manage large high-performance Linux clusters. Focused on general scalable systems management, it includes a framework for system configuration, management, provisioning/installation, monitoring, event notification, and more via a modular plugin architecture. Install the components and features you need or leverage the existing system configuration stored within Warewulf to create custom solutions to meet your performance needs. One of the goals of the project is to grow the project by allowing other organizations and developers to contribute back to the project under an open source BSD license. We have been successful with gaining support within the open source community already and have contributors and support in not only the government and academic space but also the commercial sector (e.g. Intel). Being both open source and vendor neutral puts Warewulf in a unique position to be supported and utilized as an open standard in High Performance Computing (HPC). Warewulf is an active member of various HPC initiatives and groups and is considered one of the most utilized, extensible and scalable clustering toolkits available.", + "laborHours": 0.0, + "languages": [], + "name": "Warewulf 3.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://warewulf.lbl.gov/trac/browser/trunk/common/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/warewulf/warewulf3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "COMFEN supports the systematic evaluation of alternative fenestration systems for project-specific commercial building applications. COMFEN provides simplified Excel-based user interface that focuses attention on key variables in fenestration design. Under the hood in EnergyPlus, a sophisticated analysis engine that dynamically simulate the effects of these key fenestration variables on energy consumption, peak energy demand, and thermal and visual comfort. The results from the EnergyPlus simulation are presented in graphical and tabular format within the simplified user interface for up to four comparative fenestration design cases to help users move toward optimal fenestration design choices for their project.", + "homepageURL": "https://windows.lbl.gov/software/comfen", + "laborHours": 0.0, + "languages": [], + "name": "COMFEN", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://windows.lbl.gov/software/comfen", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://windows.lbl.gov/software/comfen", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Bulk Data Mover (BDM) is a high-level data transfer management tool. BDM handles the issue of large variance in file sizes and a big portion of small files by managing the file transfers with optimized transfer queue and concurrency management algorithms. For example, climate simulation data sets are characterized by large volume of files with extreme variance in file sizes. The BDN achieves high performance using a variety of techniques, including multi-threaded concurrent transfer connections, data channel caching, load balancing over multiple transfer servers, and storage i/o pre-fetching. Logging information from the BDM is collected and analyzed to study the effectiveness of the transfer management algorithms. The BDM can accept a request composed of multiple files or an entire directory. The request also contains the target site and directory where the replicated files will reside. If a directory is provided at the source, then the BDM will replicate the structure of the source directory at the target site. The BDM is capable of transferring multiple files concurrently as well as using parallel TCP streams. The optimal level of concurrency or parallel streams depends on the bandwidth capacity of the storage systems at both ends of the transfer as well as achievable bandwidth of the wide-area network. Hardware req.-PC, MAC, Multi-platform & Workstation; Software req.: Compile/version-Java 1.50_x or above; Type of files: source code, executable modules, installation instructions other, user guide; URL: http://sdm.lbl.gov/bdm/", + "homepageURL": "https://sdm.lbl.gov/bdm", + "laborHours": 0.0, + "languages": [ + "java 1.50{sub minus}x or above" + ], + "name": "Bulk Data Mover", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sdm.lbl.gov/bdm/License.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sdm.lbl.gov/bdm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "DataMover-Lite (DML) is a client program whose purpose is to automatically manage multi-file transfers to clients. It expects as its input a transfer-instruction file, and a local target directory where the files will be moved to. The input file contains the Logical File Names (LFNs) and the transfer URLs (TURLs) of files that need to be transferred. The TURLs can have various protocols depending on the server that manages the files, including gridftp, ftp, https, and srm. Given a multi-file request for a large number of files, the DML can issue concurrently a number of transfers in order to get the files. The number of transfers it can issue is set as a parameter and is usually less than 10. For example, if the multi-file is for 100 files, the DML may keep active only 5 transfers at any one time. When any of the 5 transfers completes it will initiate another transfer. It is not necessary for a single request to contain files whose TURLs have same protocol. If the request to the DML contains TURLs with various protocols, the DML will contact the various servers on different threads according to each TURL's protocol. The DMK take care if scheduling the transfers, monitoring their progress, releasing the files, and getting the authorization for each file to be transferred.", + "homepageURL": "https://sdm.lbl.gov/dml", + "laborHours": 0.0, + "languages": [ + "java 1.5.0{sub minus}x or above" + ], + "name": "DataMover-Lite", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sdm.lbl.gov/dml/DMLLicense.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sdm.lbl.gov/dml", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "minomond is a simple software package built to unobtrrusively collect large amounts of trending data on computer systems, and send that data to one or more external trending data aggregation services. The goal is to enable ongoing recording of many metrics from many nodes in order to identify historical patterns and provide historical visibility into systems problems. minimond is intended to replace large collections of ad hoc scripts that are commonly used for this purpose. minomond is built with an emphasis on simplicity and extensibility, and is intended to supplement, not replace, other availability and trending data monitoring systems.", + "laborHours": 0.0, + "languages": [], + "name": "Minimond", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NERSC/minimond/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/minimond", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "BEST-Cities is designed to provide city authorities with strategies they can follow to reduce city-wide carbon dioxide (CO2) and methane (CH4) emissions. The tool quickly assesses local energy use and energy-related CO2 emissions across nine sectors (i.e., industry, public and commercial buildings, residential buildings, transportation, power and heat, street lighting, water & wastewater, solid waste, and urban green space), giving officials a comprehensive perspective on their local carbon performance. Cities can also use the tool to benchmark their energy and emissions performance to other cities inside and outside China, and identify those sectors with the greatest energy saving and emissions reduction potential.", + "homepageURL": "https://china.lbl.gov/best-cities", + "laborHours": 0.0, + "languages": [], + "name": "Benchmarking and Energy Saving Tool for Low Carbon Cities (BEST Cities)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://china.lbl.gov/best-cities", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://china.lbl.gov/best-cities", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "bobby.kitchens@srnl.doe.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Mesh2d is a Fortran90 program designed to generate two-dimensional structured grids of the form [x(i),y(i,j)] where [x,y] are grid coordinates identified by indices (i,j). The x(i) coordinates alone can be used to specify a one-dimensional grid. Because the x-coordinates vary only with the i index, a two-dimensional grid is composed in part of straight vertical lines. However, the nominally horizontal y(i,j0) coordinates along index i are permitted to undulate or otherwise vary. Mesh2d also assigns an integer material type to each grid cell, mtyp(i,j), in a user-specified manner. The complete grid is specified through three separate input files defining the x(i), y(i,j), and mtyp(i,j) variations.", + "homepageURL": "http://srnl.doe.gov/downloads/Mesh2d_distribution.zip", + "laborHours": 0.0, + "languages": [ + "Fortran90 compiler / N/A" + ], + "name": "Mesh2d", + "organization": "Savannah River Site (SRS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://srnl.doe.gov/downloads/Mesh2d_distribution.zip", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://srnl.doe.gov/downloads/Mesh2d_distribution.zip", + "status": "Production", + "tags": [ + "DOE CODE", + "Savannah River Site (SRS)" + ] + }, + { + "contact": { + "email": "bobby.kitchens@srnl.doe.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "DLLExternalCode is the a general dynamic-link library (DLL) interface for linking GoldSim (www.goldsim.com) with external codes. The overall concept is to use GoldSim as top level modeling software with interfaces to external codes for specific calculations. The DLLExternalCode DLL that performs the linking function is designed to take a list of code inputs from GoldSim, create an input file for the external application, run the external code, and return a list of outputs, read from files created by the external application, back to GoldSim. Instructions for creating the input file, running the external code, and reading the output are contained in an instructions file that is read and interpreted by the DLL.", + "homepageURL": "http://srnl.doe.gov/downloads/DllExternalCode_distribution.zip", + "laborHours": 0.0, + "languages": [ + "Fortran90 compiler" + ], + "name": "DLLExternalCode", + "organization": "Savannah River Site (SRS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://srnl.doe.gov/downloads/DllExternalCode_distribution.zip", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://srnl.doe.gov/downloads/DllExternalCode_distribution.zip", + "status": "Production", + "tags": [ + "DOE CODE", + "Savannah River Site (SRS)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Analytical application performance models are critical for diagnosing performance-limiting resources, optimizing systems, and designing machines. Creating models, however, is difficult. Furthermore, models are frequently expressed in forms that are hard to distribute and validate. The Performance and Architecture Lab Modeling tool, or Palm, is a modeling tool designed to make application modeling easier. Palm provides a source code modeling annotation language. Not only does the modeling language divide the modeling task into sub problems, it formally links an application's source code with its model. This link is important because a model's purpose is to capture application behavior. Furthermore, this link makes it possible to define rules for generating models according to source code organization. Palm generates hierarchical models according to well-defined rules. Given an application, a set of annotations, and a representative execution environment, Palm will generate the same model. A generated model is a an executable program whose constituent parts directly correspond to the modeled application. Palm generates models by combining top-down (human-provided) semantic insight with bottom-up static and dynamic analysis. A model's hierarchy is defined by static and dynamic source code structure. Because Palm coordinates models and source code, Palm's models are 'first-class' and reproducible. Palm automates common modeling tasks. For instance, Palm incorporates measurements to focus attention, represent constant behavior, and validate models. Palm's workflow is as follows. The workflow's input is source code annotated with Palm modeling annotations. The most important annotation models an instance of a block of code. Given annotated source code, the Palm Compiler produces executables and the Palm Monitor collects a representative performance profile. The Palm Generator synthesizes a model based on the static and dynamic mapping of annotations to program behavior. The model -- an executable program -- is a hierarchical composition of annotation functions, synthesized functions, statistics for runtime values, and performance measurements.", + "laborHours": 0.0, + "languages": [ + "C/C++ Language compiler" + ], + "name": "Performance and Architecture Lab Modeling Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.pnnl.gov/perf-lab-hub/palm/palm/-/blob/master/README-license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab-hub/palm/palm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Morph is a framework and domain-specific language (DSL) that helps parse and transform structured documents. It currently supports several file formats including XML, JSON, and CSV, and custom formats are usable as well.", + "laborHours": 0.0, + "languages": [ + "Scala 2.10x/. JVM 1.7+" + ], + "name": "morph", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stucco-archive/morph", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Building energy efficient retrofit energy savings and cost-effectiveness analysis.", + "homepageURL": "https://china.lbl.gov/combat", + "laborHours": 0.0, + "languages": [], + "name": "Commercial Building Analysis Tool for Building Energy Efficient Retrofit - COMBAT", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://china.lbl.gov/combat", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://china.lbl.gov/combat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Tracktable is designed for analysis and rendering of the trajectories of moving objects such as planes, trains, automobiles and ships. Its purpose is to operate on large sets of trajectories (millions) to help a user detect, analyze and display patterns. It will also be used to disseminate trajectory research results from Sandia's PANTHER Grand Challenge LDRD.", + "laborHours": 0.0, + "languages": [ + "C++", + "Shell", + "C", + "Jupyter Notebook", + "CMake", + "Python" + ], + "name": "TrackTable Trajectory Analysis", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tracktable", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "WINDOW features include: - Microsoft Windows TM interface - algorithms for the calculation of total fenestration product U-values and Solar Heat Gain Coefficient consistent with ASHRAE SPC 142, ISO 15099, and the National Fenestration Rating Council - a Condensation Resistance Index in accordance with the NFRC 500 Standard - and integrated database of properties - imports data from other LBNL window analysis software: - Import THERM file into the Frame Library - Import records from IGDB and OPtics5 into the Glass Library for the optical properties of coated and uncoated glazings, laminates, and applied films. Program Capabilities WINDOW 7.2 offers the following features: The ability to analyze products made from any combination of glazing layers, gas layers, frames, spacers, and dividers under any environmental conditions and at any tilt; The ability to model complex glazing systems such as venetian blinds and roller shades. Directly accessible libraries of window system components, (glazing systems, glazing layers, gas fills, frame and divider elements), and environmental conditions; The choice of working in English (IP), or Systeme International (SI) units; The ability to specify the dimensions and thermal properties of each frame element (header, sills, jamb, mullion) in a window; A multi-band (wavelength-by-wavelength) spectral model; A Glass Library which can access spectral data files for many common glazing materials from the Optics5database; A night-sky radiative model; A link with the DOE-2.1E and Energy Plus building energy analysis program. Performance Indices and Other Results For a user-defined fenestration system and user-defined environmental conditions, WINDOW calculates: The U-value, solar heat gain coefficient, shading coefficient, and visible transmittance for the complete window system; The U-value, solar heat gain coefficient, shading coefficient, and visible transmittance for the glazing system (center-of-glass values); The U-values of the frame and divider elements and corresponding edge-of-glass areas (based on generic correlations); The total solar and visible transmittance and reflectances of the glazing system. Color properties, i.e. L*, a*, and b* color coordinates, dominant wavelength, and purity for transmitted and reflected (outdoor) solar radiation; The damage-weighted transmittance of the glazing system between 0.3 an 0.38 microns; The angular dependence of the solar and visible transmittances, solar and visible reflectances, solar absorptance, and solar heat gain coefficient of the glazing system; The percent relative humidity of the inside and outside air for which condensation will occur on the interior and exterior glazing surfaces respectively; The center-of-glass temperature distribution.", + "homepageURL": "https://windows.lbl.gov/software/window", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Lab WINDOW", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://windows.lbl.gov/window-license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://windows.lbl.gov/software/window", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Octopus is a scientific program aimed at the ab initio virtual experimentation on a hopefully ever-increasing range of system types. Electrons are described quantum-mechanically within density-functional theory (DFT), in its time-dependent form (TDDFT) when doing simulations in time. Nuclei are described classically as point particles. Electron-nucleus interaction is described within the pseudopotential approximation.", + "laborHours": 3054820.0, + "languages": [], + "name": "Octopus", + "organization": "USDOE Advanced Research Projects Agency – Energy (ARPA-E) (United States) (ARPA-E)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/octopus-code/octopus/blob/develop/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/octopus-code/octopus", + "status": "Production", + "tags": [ + "DOE CODE", + "USDOE Advanced Research Projects Agency – Energy (ARPA-E) (United States) (ARPA-E)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "This software package provides tools for astrophysical experiments which record data in the form of individual time streams from discrete detectors. TOAST provides tools from meta-data manipulation and job set up, I/O operation, telescope pointing reconstruction, and map-making. It also provides tools for constructing simulated observations.", + "laborHours": 0.0, + "languages": [ + "Any Standard C++ complier which supports the BOOST software package" + ], + "name": "Time Ordered Astrophysics Scalable Tools", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/tskisner/toast/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tskisner/TOAST", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Cambio opens data files from common gamma radiation detectors, displays a visual representation of it, and allows the user to edit the meta-data, as well as convert the data to a different file format.", + "laborHours": 0.0, + "languages": [ + "Requires C++03 compliant compiler" + ], + "name": "Cambio", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cambio", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bobby.kitchens@srnl.doe.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Gnuforplot Graphics is a Fortran90 program designed to generate two and three dimensional plots of data on a personal computer. The program uses calls to the open source code Gnuplot to generate the plots. Two Fortran90 programs have been written to use the Gnuplot graphics capabilities. The first program, named Plotsetup.f90 reads data from output files created by either the Stadium or LeachXS/Orchestra modeling codes and saves the data in arrays for plotting. This program then calls Gnuforplot which takes the data array along with user specified parameters to set plot specifications and issues Gnuplot commands that generate the screen plots. The user can view the plots and optionally save copies in jpeg format.", + "homepageURL": "http://sti.srs.gov/fulltext/Software/gnuforplot_rev_11-4-15.zip", + "laborHours": 0.0, + "languages": [ + "Fortran90" + ], + "name": "GnuForPlot Graphics", + "organization": "Savannah River Site (SRS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://sti.srs.gov/fulltext/Software/gnuforplot_rev_11-4-15.zip", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://sti.srs.gov/fulltext/Software/gnuforplot_rev_11-4-15.zip", + "status": "Production", + "tags": [ + "DOE CODE", + "Savannah River Site (SRS)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2022-06-15" + }, + "description": "The MapRE (Multi-criteria Analysis for Planning Renewable Energy) GIS (Geographic Information Systems) Tools are a set of ArcGIS tools to a) conduct site suitability analysis for wind and solar resources using inclusion and exclusion criteria, and create resource maps, b) create project opportunity areas and compute various attributes such as cost, distances to existing and planned infrastructure. and environmental impact factors; and c) calculate and update various attributes for already processed renewable energy zones. In addition, MapRE data sets are geospatial data of renewable energy project opportunity areas and zones with pre-calculated attributes for several countries. These tools and data are available at mapre.lbl.gov.", + "homepageURL": "http://mapre.lbl.gov", + "laborHours": 0.0, + "languages": [], + "name": "MapRE GIS Tools & Data (MapRE)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://mapre.lbl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Time-lapse ERT imaging for monitoring both natural and engineered subsurface processes has advanced rapidly over the past 15-20 years. However, imaging results generally required a significant amount of manual and computational effort, and therefore were not available while the process was occurring. Although the value of real-time imaging was recognized, several obstacles prevented it's implementation. E4D_RT addresses these obstacles by 1) providing specialized algorithms that negate the need for user intervention, thereby automating the time-lapse data processing steps, 2) linking field data collection systems with parallel supercomputing systems via wireless data transfer link, and 3) addressing the computational burdens by utilizing distributed memory supercomputing resources, thereby enabling rapid data processing and imaging results.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "E4D_RT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/E4D/blob/master/E4D_LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/E4D", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Singularity is a container solution designed to facilitate mobility of compute across systems and HPC infrastructures. It does this by creating minimal containers that are defined by a specfile and files from the host system are used to build the container. The resulting container can then be launched by any Linux computer with Singularity installed regardless if the programs inside the container are present on the target system, or if they are a different version, or even incompatible versions. Singularity achieves extreme portability without sacrificing usability thus solving the need of mobility of compute. Singularity containers can be executed within a normal/standard command line process flow.", + "laborHours": 0.0, + "languages": [ + "ANY C COMPLIER" + ], + "name": "Singularity v1.x", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpcng/singularity", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "These Drupal Modules extend the functionality of Drupal by including specific styles for dates and tabs, publishing options for scheduled and immediate publication of content modes, field visibility in content forms, keyword block filters (taxonomy based), adding content nodes to a specified queue for display in views, and status display of workflow settings.", + "laborHours": 0.0, + "languages": [ + "PHP (99%)", + "JavaScript (1%)" + ], + "name": "Drupal Contributed Modules", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.drupalcode.org/project/field_visibility", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Analysis scripts for data from the NDCX-II experiment.", + "laborHours": 0.0, + "languages": [], + "name": "NDCX-II Python Module", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/berkeleylab/atap-ndcxii-python/src/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/atap-ndcxii-python", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "WARNO is a software system designed to monitor the radars in the ARM Radar Network. 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It provides a web portal on the front end to interact with users, a REST API webpoint for interactions with third party systems, and an internal distributed architecture to allow it to be deployed at multiple sites.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Watchdog for ARM Radar Network Operations", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ARM-DOE/warno/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/warno", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "GRIDDER is a simple interactive grid generation tool for creating orthogonal, 2D quadrilateral or 3D hexahedral grids. Grid spacing can be even, logarithmic, or geometric. Gridder creates orthogonal one-dimensional, two-dimensional, or three- dimensional grids. Each dimension can have multiple regions, each with different nodal spacing. This spacing can be equal spacing, geometric spacing, or logarithmic spacing. The resulting grid can be output in AVS (Advanced Visualization Systems) format, Tracer 30, Vectors, or FEHM format. Coordinate and connectivity data are output for AVS, but only coordinate data is output for Tracer30. As it runs, Gridder prompts the user for input such as number of dimensions, number of regions in each dimension, coordinates of region borders, number of divisions in each region, spacing specifications of each region, and output format. The Gridder can also accept the necessary information from a file, bypassing the interactive interface. Every time the interactive interface is used, the input parameters are saved to a file so that the same grid can be regenerated from that file.", + "laborHours": 0.0, + "languages": [ + "c", + "gcc version 4.8.2" + ], + "name": "Gridder, Version 3", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/gridder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "SEDS is an economy-wide energy model of the U.S. The model captures dynamics between supply, demand, and pricing of the major energy types consumed and produced within the U.S. These dynamics are captured by including: the effects of macroeconomics; the resources and costs of primary energy types such as oil, natural gas, coal, and biomass; the conversion of primary fuels into energy products like petroleum products, electricity, biofuels, and hydrogen; and lastly the end- use consumption attributable to residential and commercial buildings, light and heavy transportation, and industry. Projections from SEDS extend to the year 2050 by one-year time steps and are generally projected at the national level. SEDS differs from other economy-wide energy models in that it explicitly accounts for uncertainty in technology, markets, and policy. SEDS has been specifically developed to avoid the computational burden, and sometimes fruitless labor, that comes from modeling significantly low-level details. Instead, SEDS focuses on the major drivers within the energy economy and evaluates the impact of uncertainty around those drivers.", + "homepageURL": "https://www.nrel.gov/analysis/seds", + "laborHours": 0.0, + "languages": [ + "Ruby" + ], + "name": "Stochastic Energy Deployment System", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/analysis/seds/download-model.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/analysis/seds", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Generates data for the associated paper and its supplementary data table, which are sets of residues and poles that define rational functions to approximate the Fermi-Dirac distribution.", + "laborHours": 440.8, + "languages": [ + "C" + ], + "name": "Companion software to: Minimax Rational Approximation of the Fermi-Dirac Distribution v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fermi-rational-approximation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "This algorithm processes high-rate 3-phase signals to identify the start time of each signal and estimate its envelope as data features. The start time and magnitude of each signal during the steady state is also extracted. The features can be used to detect abnormal signals. This algorithm is developed to analyze Exxeno's 3-phase voltage and current data recorded from refrigeration systems to detect device failure or degradation.", + "homepageURL": "https://store.pnnl.gov/content/data-feature-extraction-high-rate-3-phase-data", + "laborHours": 0.0, + "languages": [ + "Algorithm" + ], + "name": "Data Feature Extraction for High-Rate 3-Phase Data", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/data-feature-extraction-high-rate-3-phase-data", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "A trans-active energy micro-grid controller is implemented in the VOLTTRON distributed control platform. The system uses the price of electricity as the mechanism for conducting transactions that are used to manage energy use and to balance supply and demand. In order to allow testing and analysis of the control system, the implementation is designed to run completely as a software simulation, while allowing the inclusion of selected hardware that physically manages power. Equipment to be integrated with the micro-grid controller must have an IP (Internet Protocol)-based network connection and a software \"driver\" must exist to translate data communications between the device and the controller.", + "laborHours": 0.0, + "languages": [ + "NA" + ], + "name": "Price Based Local Power Distribution Management System (Local Power Distribution Manager) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LBNL-ETA/LPDM/blob/CBERD/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/LPDM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The PeakWorks software is designed to assist in the quantitative analysis of atom probe tomography (APT) generated mass spectra. Specifically, through an interactive user interface, mass peaks can be identified automatically (defined by a threshold) and/or identified manually. The software then provides a means to assign specific elemental isotopes (including more than one) to each peak. The software also provides a means for the user to choose background subtraction of each peak based on background fitting functions, the choice of which is left to the users discretion. Peak ranging (the mass range over which peaks are integrated) is also automated allowing the user to chose a quantitative range (e.g. full-widthhalf- maximum). The software then integrates all identified peaks, providing a background-subtracted composition, which also includes the deconvolution of peaks (i.e. those peaks that happen to have overlapping isotopic masses). The software is also able to output a 'range file' that can be used in other software packages, such as within IVAS. A range file lists the peak identities, the mass range of each identified peak, and a color code for the peak. The software is also able to generate 'dummy' peak ranges within an outputted range file that can be used within IVAS to provide a means for background subtracted proximity histogram analysis.", + "homepageURL": "https://store.pnnl.gov/content/peakworks", + "laborHours": 0.0, + "languages": [ + "MatLab" + ], + "name": "PeakWorks", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/peakworks", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "FermiLib is an open source software package designed to facilitate the development and testing of algorithms for simulations of fermionic systems on quantum computers. Fermionic simulations represent an important application of early quantum devices with a lot of potential high value targets, such as quantum chemistry for the development of new catalysts. This software strives to provide a link between the required domain expertise in specific fermionic applications and quantum computing to enable more users to directly interface with, and develop for, these applications. It is an extensible Python library designed to interface with the high performance quantum simulator, ProjectQ, as well as application specific software such as PSI4 from the domain of quantum chemistry. Such software is key to enabling effective user facilities in quantum computation research.", + "laborHours": 0.0, + "languages": [ + "PYTHON 2.7" + ], + "name": "FermiLib v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ProjectQ-Framework/FermiLib", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Screamer is a special purpose circuit code developed for the design of Pulsed Power systems. It models electrical circuits which have a restricted topology in order to provide a fast-running tool while still allowing configurations general enough for most Pulsed Power system designs", + "laborHours": 0.0, + "languages": [ + "Fortran and C++" + ], + "name": "Screamer version 4.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/screamer", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "4.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "A parallelization of the k-means++ seed selection algorithm on three distinct hardware platforms: GPU, multicore CPU, and multithreaded architecture. K-means++ was developed by David Arthur and Sergei Vassilvitskii in 2007 as an extension of the k-means data clustering technique. These algorithms allow people to cluster multidimensional data, by attempting to minimize the mean distance of data points within a cluster. K-means++ improved upon traditional k-means by using a more intelligent approach to selecting the initial seeds for the clustering process. While k-means++ has become a popular alternative to traditional k-means clustering, little work has been done to parallelize this technique. We have developed original C++ code for parallelizing the algorithm on three unique hardware architectures: GPU using NVidia's CUDA/Thrust framework, multicore CPU using OpenMP, and the Cray XMT multithreaded architecture. By parallelizing the process for these platforms, we are able to perform k-means++ clustering much more quickly than it could be done before.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel k-means++", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/patrickmackey/parallel_kpp/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/patrickmackey/parallel_kpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "A software library for parsing and manipulating frequency-domain data files that have been processed using the Bruker TopSpin NMR software package. 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The data can include building energy consumption, sensor data, environmental data and any data that may affect the building's energy consumption. The algorithm is a modified nonlinear Bayesian support vector machine, which examines daily energy consumption profile, detect the days with abnormal events, and diagnose the cause of the events.", + "homepageURL": "https://store.pnnl.gov/content/bayesian-support-vector-machine-bsvm", + "laborHours": 0.0, + "languages": [ + "Matlab R2014a" + ], + "name": "Bayesian Support Vector Machine (BSVM)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/bayesian-support-vector-machine-bsvm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The BSEPACK contains a set of subroutines for solving the Bethe-Salpeter Eigenvalue (BSE) problem. This type of problem arises in this study of optical excitation of nanoscale materials. The BSE problem is a structured non-Hermitian eigenvalue problem. The BSEPACK software can be used to compute all or subset of eigenpairs of a BSE Hamiltonian. It can also be used to compute the optical absorption spectrum without computing BSE eigenvalues and eigenvectors explicitly. The package makes use of the ScaLAPACK, LAPACK and BLAS.", + "homepageURL": "https://sites.google.com/a/lbl.gov/bsepack", + "laborHours": 0.0, + "languages": [ + "FORTRAN" + ], + "name": "Bethe-Salpeter Eigenvalue Solver Package (BSEPACK) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sites.google.com/a/lbl.gov/bsepack/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sites.google.com/a/lbl.gov/bsepack", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Sparx, a new environment for Cryo-EM image processing; Cryo-EM, Single particle reconstruction, principal component analysis; Hardware Req.: PC, MAC, Supercomputer, Mainframe, Multiplatform, Workstation. Software Req.: operating system is Unix; Compiler C++; type of files: source code, object library, executable modules, compilation instructions; sample problem input data. Location/transmission: http://sparx-em.org; User manual & paper: http://sparx-em.org;", + "homepageURL": "http://sparx-em.org", + "laborHours": 0.0, + "languages": [], + "name": "Sparx PCA Module", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://sparx-em.org/sparxwiki/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://sparx-em.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Tigres provides a programming library to compose and execute large-scale data-intensive scientific workflows from desktops to supercomputers. DOE User Facilities and large science collaborations are increasingly generating large enough data sets that it is no longer practical to download them to a desktop to operate on them. They are instead stored at centralized compute and storage resources such as high performance computing (HPC) centers. Analysis of this data requires an ability to run on these facilities, but with current technologies, scaling an analysis to an HPC center and to a large data set is difficult even for experts. Tigres is addressing the challenge of enabling collaborative analysis of DOE Science data through a new concept of reusable \"templates\" that enable scientists to easily compose, run and manage collaborative computational tasks. These templates define common computation patterns used in analyzing a data set.", + "homepageURL": "http://tigres.lbl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Template Interfaces for Agile Parallel Data-Intensive Science", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://dst.lbl.gov/ACSSoftware/tigres/docs/tigres-0.2.0/license_agreement.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://tigres.lbl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Demeter is a fully extensible, community-based land use land cover (LULC) downscaling and change detection model that allows for customization and/or additions from its user base.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Demeter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/demeter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2023-03-15" + }, + "description": "MASTODON has the capability to model stochastic nonlinear soil-structure interaction (NLSSI) in a dynamic probabilistic risk assessment framework. The NLSSI simulations include structural dynamics, time integration, dynamic porous media flow, nonlinear hysteretic soil constitutive models, geometric nonlinearities (gapping, sliding, and uplift). MASTODON is also the MOOSE based master application for dynamic PRA of external hazards.", + "laborHours": 28287.2, + "languages": [ + "C++" + ], + "name": "Mastodon", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/mastodon", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "Revision 1.0" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Problem Solved: A novel technique for regression and sensitivity analysis of C1 function f problematic input dimension given observations (x_i, f(x_i), f'(x_i)). Solution Provided by the Code: Active Manifolds reduces the problem to analysis/regression of a 1 dimensional analogue by exploiting geometric properties of the function.", + "laborHours": 0.0, + "languages": [ + "Python 2.7" + ], + "name": "Active Manifolds ICML 2019 Paper Results Code", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/bridgesra/active-manifold-icml2019-code", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bridgesra/active-manifold-icml2019-code", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-04-17", + "metadataLastUpdated": "2021-06-15" + }, + "description": "The FasTensor implements the native array data programming mode namely SLOPE for modern data analysis tasks. It is designed to work in parallel on supercomputer and can handle terabyte data analysis tasks. It is thousand times faster than other data analysis systems such as Apache Spark and 38% faster than TensorFlow in dealing with large scale scientific data analysis. It has wide applications in image data analysis and mesh data analysis tasks in physical simulations and other fields.", + "laborHours": 0.0, + "languages": [], + "name": "FasTensor (FT) v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/fastensor/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-04-18", + "metadataLastUpdated": "2024-07-01" + }, + "description": "The Records API (application program interface) for Advanced Energy System Design (AESD) enables software that serves multidimensional record-oriented data to interoperate with software than uses such data. In the context of the Records API, multidimensional data records are simply tuples of real numbers, integers, and character strings, where each data value is tagged by a variable name, according to a pre-defined schema, and each record is assigned a unique integer identifier. Conceptually, these records are isomorphic to rows in a relational database, JSON objects, or key-value maps. Records servers might supply static datasets, sensor measurements that periodically update as new telemetry become available, or the results of simulations as the simulations generate new output. Records client software might display or analyze the data, but in the case of simulations the client request the creation of new ensembles for specified input parameters. It is also possible to chain records clients and servers together so that a client consuming data from a server might transform that data and serve it to additional clients. This minimalist API avoids imposing burdensome metadata, structural, or implementation requirements on developers by relying on open-source technologies that are readily available for common programming languages. In particular, the API has been designed to place the least possible burden on services that provide data. This document defines the message format for the Records API, a transport mechanism for communicating the data, and the semantics for interpreting it. The message format is specified as Google Protocol Buffers and the transport mechanism uses WebSockets. We discuss three major use cases for serving and consuming records data: (i) static data, (ii) dynamically augmented data, (iii) on-demand simulations, (iv) with filters, and (v) with bookmarks. Separate implementations of the API exist in C++, Haskell, JavaScript, Python, and R.", + "laborHours": 0.0, + "languages": [], + "name": "AESD (Advanced Energy System Design) Records API [SWRs-17-50, 17-51, 17-52]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/AESD/blob/master/libs/Haskell/records/LICENSE", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/AESD", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-04-18", + "metadataLastUpdated": "2021-04-18" + }, + "description": "The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an open-source tool for visualizing variable renewable resource forecasts and ramp alerts for significant up/down ramps in renewable resource and the consequent net-load. The modular dashboard of RAVIS contains configurable panes for viewing- probabilistic time series forecasts, ramp event alerts on the look-ahead timeline, spatially resolved resource sites and forecasts, and system simulation and market clearing data such as transmission lines utilization, nodal prices and available generation flexibility.", + "laborHours": 0.0, + "languages": [ + "JavaScript" + ], + "name": "Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ravis-nrel/ravis", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-04-19", + "metadataLastUpdated": "2024-07-01" + }, + "description": "The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "Fast All-sky Radiation Model for Solar applications (FARMS) [SWR-16-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/farms", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "charles.tripp@nrel.gov" + }, + "date": { + "created": "2021-04-20", + "metadataLastUpdated": "2021-04-26" + }, + "description": "KRoad is a 2-dimensional, lightweight, vehicle driver simulator that uses 3-dimensional vehicle driving model considerations, i.e. state-of-the-art friction models, and enables the driver to make control decisions with less computation time and programmer effort required than is with full-fidelity 3d simulators. KRoad is fully compatible with OpenAI gym, and contains a factored gym framework for composing gyms from various components (process, reward function, observation function, termination conditions, etc.). KRoad is additionally compatible with the RLlib distributed reinforcement learning environment, running under the Ray distributed python framework.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "K_Road (KRoad)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/K_Road", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-21", + "metadataLastUpdated": "2021-04-21" + }, + "description": "ArQTiC is a domain-specific full-stack software package built for the dynamic simulations of materials on quantum computers. Its main contributions include providing a software library for high-level programming of such simulations on quantum computers, and providing post-processing capabilities that allow users to more efficiently analyze results from the quantum computer. Paired with the power to optimize and execute quantum circuits, ArQTiC opens the field of dynamic materials simulations on quantum computers to a broader community of scientists from a wider range of domain sciences, paving the way for accelerated progress towards physical quantum supremacy.", + "laborHours": 0.0, + "languages": [], + "name": "Architecture for Quantum Time-dependent Circuits (ArQTIC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lebassman/ArQTiC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-21", + "metadataLastUpdated": "2021-04-21" + }, + "description": "H5bench benchmark suite contains a list of applications that are used to measure the HDF5 I/O performance from various aspects.", + "laborHours": 0.0, + "languages": [], + "name": "H5bench: a benchmark suite for parallel HDF5 (H5bench) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/h5bench", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-21", + "metadataLastUpdated": "2021-04-21" + }, + "description": "the Xilinx tools relay on a component on the board (FTDI chip) to have a small memory from a particular manufacturer (Digilent) to serve as a bridge to the FPGA. What the software we're requesting to release simply does is to run between the Xilinx tools (one of them is called Vivado but there are others) and our boards so that we don't need that memory on our boards. The protocol the software uses to communicate with the Xilinx tools is called XVC (Xilinx Virtual Cable). This server code runs on the computer that is physically connected to the FPGA board, but the Xilinx tools that communicate with it can run either on that computer or some other computer connected to it over the network, this is where the network component comes into play.", + "laborHours": 0.0, + "languages": [], + "name": "XVC FTDI JTAG v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/XVC-FTDI-JTAG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Ruleset Checking Tool (RCT) will be a tool 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However, dynamic ab initio simulations come with high computational cost. Deep learning techniques offer a method to obtain both high accuracy and low cost predictions of dynamics. 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The user selects single-port or two-port subnetworks for reduction, and the software reduces the subnetwork as described in the paper \"Power System Network Reduction for Power Hardware-in-the-Loop Simulation\" (submitted).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PSSE Network Reduction", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PSSE_Network_Reduction", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-12", + "metadataLastUpdated": "2024-08-07" + }, + "description": "A suite of software tools used to interface with power electronic equipment for laboratory testing and device certification. 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SAND2021-1185 O", + "laborHours": 18665.6, + "languages": [ + "Python 2.7", + "Scilab" + ], + "name": "System Validation Platform Working Directories", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/svp_energy_lab", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-05-12", + "metadataLastUpdated": "2021-05-12" + }, + "description": "Lestofire is an academic software for the automated design of engineering components. It finds the optimal geometry of a system to minimize a given cost function while constrained by a given set of physics equations. 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TOGA uses an approach based on the Peng-Robinson equation of state (PR-EOS) to calculate the thermophysical properties of the gas and oil phases including the gas/oil components dissolved in the aqueous phase, and uses a mixing model to estimate the thermophysical properties of the aqueous phase.", + "homepageURL": "https://tough.lbl.gov/licensing-download/tough-related-codes-licensing-download", + "laborHours": 0.0, + "languages": [], + "name": "TOGA: A TOUGH code for modeling three-phase, multi-component, and non-isothermal processes involved in CO2-based Enhanced Oil Recovery (TOGA) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://marketplace.lbl.gov/search?q=toga", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://tough.lbl.gov/licensing-download/tough-related-codes-licensing-download", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-13", + "metadataLastUpdated": "2021-06-28" + }, + "description": "The MAPIT - Material Accountancy Performance Indicator Toolkit includes statistical tests and calculations based on open literature that calculate safeguards metrics. 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The modular toolsets combine aspects of radiation transport, navigation, graph theory, optimization, and visualization to allow the complete end-to-end simulation of large scale, highly-distributed sensor networks.", + "homepageURL": "https://sites.google.com/lbl.gov/udm/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Urban Deployment Model (UDM) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://marketplace.lbl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/udm/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-17", + "metadataLastUpdated": "2021-05-17" + }, + "description": "QCLAB is an object-oriented MATLAB package for creating and representing quantum circuits. 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Plasma acceleration is a priority in the ATAP division, and such problems represent a wide range of parameters. Hipace++ is an HPC (high-performance computing) code running on supercomputers and it provides the first efficient implementation of the quasi-static PIC method on Graphic Processing Units (GPU), showing 10x speedup and using much less resources than CPU implementations for production simulations. It currently runs on Nvidia GPUs and will ultimately be portable to more accelerated HPC platforms. The porting strategy is novel, and can be adapted to other flavors of quasi-static PIC. Besides, Hipace++ aims at using mesh refinement for higher efficiency, thus enabling simulations unfeasible today. 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The Monte-Carlo model of electron-neutral collisions and the Langevin model of Coulomb collisions for electrons are also implemented.", + "laborHours": 0.0, + "languages": [ + "C", + "Fortran" + ], + "name": "1D EDIPIC", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PrincetonUniversity/EDIPIC", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "apritch@pppl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-21" + }, + "description": "EDIPIC codes were developed for simulation of kinetic effects in low-temperature plasmas. 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Currently the Nettest framework incorporates lperf-vl.2, a simple ping type test, and a tuned TCP test that uses a given required throughput and ping results to determine the round trip time to set a buffer size (based on the delay bandwidth product) and then performs an iperf TCP throughput test. Additional network test tools can be integrated into the Nettest framework in the future.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Net Test", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "This software provides a framework for building application layter overlay networks. It includes example overlays that can be used without modification. 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Our information-sharing tool uses group communication, in particular the InterGroup protocols, to reliably deliver each query to all of the current participants in a scalable manner, without having to discover all of their identities. We will use the Secure Group Layer (SGL) and Akenti to provide security to the participants of our environment, SGL will provide confidentiality, integrity, authenticity, and authorization enforcement for the InterGroup protocols and Akenti will provide access control to other resources.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Java 1.4 or higher" + ], + "name": "Secure Information Sharing", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "This toolkit supports component-level model-based fault detection methods in commercial building HVAC systems. The toolbox consists of five basic modules: a parameter estimator for model calibration, a preprocessor, an AHU model simulator, a steady-state detector, and a comparator. Each of these modules and the fuzzy logic rules for fault diagnosis are described in detail. The toolbox is written in C++ and also invokes the SPARK simulation program.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "HVAC Fault Detection and Diagnosis Toolkit", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "The Beowulf Distributed process Space (Bproc) software stack is comprised of UNIX/Linux kernel modifications and a support library by which a cluster of machines, each running their own private kernel, can present itself as a unified process space to the user. 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See http://www.clustermatic.org, http://bproc.sourceforge.net, and http://www.perl.org", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "gcc or equivalent ANSI C compiler." + ], + "name": "Perl Extension to the Bproc Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "Bag is a miniature pcap filter which takes pcap input (or input off the wire) using a bpf filter, if specified, and then writes the output to stdout or a file (in pcap format). It depends for some aspects of its functionality on a libpcap library which uses a shared memory packet capture ring bugger. There are two build in modules: chcksum and session. the build in chcksum modules is used to anonymize the ip addresses and repair any checksums in the stream. % bag -r /tmp/*.pcap -Cchucksum, 128.1 65: 10.10 The session module generates sessions which are defined as a series of packets that have two things in common. the first is a unique five-tuple composed oi an IP protocol, IP source address, IP source port, IP destination address, and IP destination port. The second is that if the originating packet is associated with a bi-directional service such as ftpltcp, characteristics and data will be kept for both flows involved with the service. The only protocols evaluated beyond the IP header are ICMP, TCP and UDP. A session can last for as long as bag is running. However, under normal conditions, sessions are generated every time they appear to have closed down. There is a man page included with the distribution which goes into more detail.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [], + "name": "BAG (Continuous Round Robin Packet Capture)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "GROK is web based Internet Protocol (IP) search tool designed to help the user find and analyze network sessions in close to real time (5 minute). It relies on the output generated by a packet capture and session summary tool called BAG. The bag program runs on a linux system, and continuously generates 5 minute full packet capture ILIBPCAP files, Internet session summary files, and interface statistic files, round-robin, over a period limited to the amount of disc storage available to the system. In the LANL case, an 8 terabyte file system accommodates seven days of data (most of the time). Summary information, such as top 20 outgoing and incoming network services (such as www/tcp or 161/udp) along with network interface statistics which indicate the health of the capture system are plotted every 5 minutes for display by the GROK web server. The grok home page presents the analyst with a set of search criteria used to query the information being collected by the bag program. Since the information ultimately resides in \"pcap\" files, other pcap aware programs such as bro ethereal, nosehair, smacqq, snort, and tcpdump have been incorporated into groks web interface. Clickable documentation is available for each search criteria.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [], + "name": "GROK", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "INET's was developed in the 80's when the Internet was in it's infancy and various vendors were attempting to get into the ball game with half baked code that indicated a lack of understanding about basic IP standards in the area of IP and ICMP. Various test applications were written to test conformance to the early Internet RFC's especially ICMP. The INET program allows the user to exercise various minor internet services provided by a specified service host. See the DDN Protocol Handbook, Volume Two, Section 8 for a detailed description of various minor applications which one might attempt to exercise. The unix network daemon \"inetd\" was the inspiration for the name \"inet\". A simple C library generated at the time was recently used to build a program called 'dp' shich GROK uses to transfer BAG session information to some backend data collector such as DISARM (LA-CC number 05-D47)", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "gcc 3.2.3 through gcc 4.0.3" + ], + "name": "inet", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "PMI is a XML framework for formulating tests of software and software environments which operate in a relatively push button manner, i.e., can be automated, and that provide results that are readily consumable/publishable via RSS. Insofar as possible the tests are carried out in manner congruent with real usage. PMI drives shell scripts via a perl program which is charge of timing, validating each test, and controlling the flow through sets of tests. Testing in PMI is built up hierarchically. A suite of tests may start by testing basic functionalities (file system is writable, compiler is found and functions, shell environment behaves as expected, etc.) and work up to large more complicated activities (execution of parallel code, file transfers, etc.) At each step in this hierarchy a failure leads to generation of a text message or RSS that can be tagged as to who should be notified of the failure. There are two functionalities that PMI has been directed at. 1) regular and automated testing of multi user environments and 2) version-wise testing of new software releases prior to their deployment in a production mode.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "C, Fortran" + ], + "name": "Production Maintenance Infrastructure", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-24" + }, + "description": "ChISELS is used for the theoretical modeling of detailed surface chemistry and consomitant surface evolutions occurring during microsystem fabrication processes conducted at low pressures. Examples include physical vapor deposition (PVD), low pressure chemical vapor deposition (PECVD), and plasma etching. Evolving interfaces are represented using the level-set method and the evolution equations time integrated using a Semi-Lagrangian approach. A Ballistic transport model is employed to solve for the fluxes incident on each of the surface elements. Surface chemistry leading to etching or deposition is computed by either coupling to Surface Chemkin (a commercially available code) or by providing user defined subroutines. The computational meshes used are quad-trees (2-D) and oct-trees (3-D), constructed such that grid refinement is localized to regions near the surface interfaces. As the interface evolves, the mesh is dynamically reconstructed as needed for the grid to remain fine only around the interface. For parallel computation, a domain decomposition scheme with dynamic load balancing is used to distribute the computational work across processors.", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Chemically Induced Surface Evolutions with Level Sets", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/chisels", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The Terascale Simulation Tools and Technologies (TSTT) center is a collaboration between several universities and DOE laboratories, and is funded by the DOE Scientific Discovery for Advanced Computing (SciDAC) program. The primary objective of the (TSTT) center is to develop technologies that enable application scientists to easily use multiple mesh and discretization strageties within a single simulation on terascale computers. This is accomplished through the development of common functional interfaces to geometry, mesh, and other simulation data. This package is Sandia's implementation of these interfaces.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Terascale Simulation Tolls and Technologies", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The purpose of the Aggregate Remote Memory Copy (ARMCI) library is to provide a general- purpose, efficient, and Widely portable remote memory access (RMA) operations (one-sided communication) optimized for Contiguous and noncontiguous (strided, scatter/gather, I/O vector) data transfers. In addition, ARMCI includes a set of atomic and mutual exclusion operations. The development ARMCI is driven by the need to support the global-address space communication model in context of distributed regular or irregular distributed data structures, communication libraries, and compilers. ARMCI is a standalone system that could be used to support user-level libraries and applications that use MPI or PVM.", + "homepageURL": "https://hpc.pnl.gov/armci", + "laborHours": 0.0, + "languages": [], + "name": "Aggregate Remote Memory Copy Interface", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://hpc.pnl.gov/armci", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://hpc.pnl.gov/armci", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "Self-Configuring Network Monitor (SCNM) is a passive monitoring that can collect packet headers from any point in a network path. SCNM uses special activation packets to automatically activate monitors deployed at the layer three ingress and egress routers of the wide-area network, and at critical points within the site networks. Monitoring output data is sent back to the application data source or destination host. No modifications are required to the application or network routing infrastructure in order to activate monitoring of traffic for an application. This ensures that the monitoring operation does not add a burden to the networks administrator.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Self-Configuring Network Monitor", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "Visapult is software pipeline of two components, a backend and viewer, used to perform pipelined and distributed memory parallel, Image Based Rendering assisted volume rendering of 3D scalar data on structured rectilinear grids. Visapult implements a two-stage volume rendering pipeline using two software components called the \"backend\" and the \"viewer.\" The backend reads 3D scientific data from some source in a domain-decomposed fashion, and performs software volume rendering on each block of data. Results, which consist of six images per block (representing the six primary view axes) are transmitted over parallel sockets to the viewer. The viewer receives each block's worth of data, constructs an internal scene graph, and presents the resulting rendering to the human viewer. The human user can interactively transform the 3D model to obtain a view from any angle. Whereas full-resolution volume rendering is extremely computer and bandwidth intensive, the Visapult architecture is designed to perform the most demanding part of volume rendering on a parallel computer. Yet, the viewer maintains interactive rendering rates independent of the size of the original volume, and independent of network bandwidth.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "C and C++" + ], + "name": "VISAPULT", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "This program tests distributed filesystems using small files for lock and metadata contention. It is useful for debugging.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Distributed File System Test Using Small FilesV1.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "Procdn is a collection of software that provides support in the Linux kernel for Globus distinguished name (DNs). The primary component is a Linux kernel module that creates data structures in the kernel for associating DNs with user processes. The other components included with the software help initiate this mapping in the kernel, including patches for the Flobus toolkit and a sample implementation for various batch scheduler systems. In addition, the software includes some utilities for listing current mappings in the kernel.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "PROCDN", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The NetLogger Toolkit is designed to monitor, under actual operating conditions, the behavior of all the elements of the application-to-application communication path in order to determine exactly where time is spent within a complex system. Using NetLogger, distributed application components are modified to produce timestamped logs of \"interesting\" events at all the critical points of the distributed system. Events from each component are correlated, which allows one to characterize the performance of all aspects of the system and network in detail. The NetLogger Toolkit itself consists of four components an API and library of functions to simplify the generation of application-level event logs, a set of tools for collecting and sorting log files, an event archive system, and a tool for visualization and analysis of the log files. In order to instrument an application to produce event logs, the application developer inserts calls to the NetLogger API at all the critical points in the code, then links the application with the NetLogger library. All the tools in the NetLogger Toolkit share a common log format, and assume the existence of accurate and synchronized system clocks. NetLogger messages can be logged using an easy-to-read text based format based on the lETF-proposed ULM format, or a binary format that can still be used through the same API but that is several times faster and smaller, with performance comparable or better than binary message formats such as MPI, XDR, SDDF-Binary, and PBIO. The NetLogger binary format is both highly efficient and self-describing, thus optimized for the dynamic message construction and parsing of application instrumentation. NetLogger includes an \"activation\" API that allows NetLogger logging to be turned on, off, or modified by changing an external file This IS useful for activating logging in daemons/services (e g GndFTP server). The NetLogger reliability API provides the ability to specify backup logging locations and periodically try to reconnect broken TCP pipe. A typical use for this is to store data on local disk while net is down. An event archiver can log one or more incoming NetLogger streams to a local disk file (netlogd) or to a mySQL database (netarchd). We have found exploratory, visual analysis of the log event data to be the most useful means of determining the causes of performance anomalies The NetLogger Visualization tool, niv, has been developed to provide a flexible and interactive graphical representation of system-level and application-level events.", + "homepageURL": "http://netlogger.lbl.gov", + "laborHours": 0.0, + "languages": [], + "name": "The NetLogger Toolkit V2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://netlogger.lbl.gov/software/netlogger-license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://netlogger.lbl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The IRCD is an IRC server that was originally distributed by the IRCD Hybrid developer team for use as a server in IRC message over the public Internet. By supporting the IRC protocol defined in the IRC RFC, IRCD allows the users to create and join channels for group or one-to-one text-based instant messaging. It stores information about channels (e.g., whether it is public, secret, or invite-only, the topic set, membership) and users (who is online and what channels they are members of). It receives messages for a specific user or channel and forwards these messages to the targeted destination. Since server-to-server communication is also supported, these targeted destinations may be connected to different IRC servers. Messages are exchanged over TCP connections that remain open between the client and the server. The IRCD is being used within the Pervasive Computing Collaboration Environment (PCCE) as the 'chat server' for message exchange over public and private channels. After an LBNLSecureMessaging(PCCE chat) client has been authenticated, the client connects to IRCD with its assigned nickname or 'nick.' The client can then create or join channels for group discussions or one-to-one conversations. These channels can have an initial mode of public or invite-only and the mode may be changed after creation. If a channel is public, any one online can join the discussion; if a channel is invite-only, users can only join if existing members of the channel explicitly invite them. Users can be invited to any type of channel and users may be members of multiple channels simultaneously. For use with the PCCE environment, the IRCD application (which was written in C) was ported to Linux and has been tested and installed under Linux Redhat 7.2. The source code was also modified with SSL so that all messages exchanged over the network are encrypted. This modified IRC server also verifies with an authentication server that the client is who he or she claims to be and that this user is authorized to ain access to the IRCD.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Secure IRC Server", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The LBNLSecureMessaging application enables collaboration among colocated or geograhically dispersed users by supporting secure synchronous and asynchronous communication. This application is the graphical user interface client that is meant to be used in conjunction with servers (LBNL's PCCEServer and a customized IRC server) to allow group and one-to-one conversations via text-based instant messaging. Conversations may be private (by invitation only) or public (open to any member of a collaboratory group_ and they may be permanent and on-going or temporary and ad hoc. Users may leave notes for other people who are online or offline. By providing presence and awareness information, collaborators can easily locate each other and rendezvous. Written in Java/Swing, this application is cross-platform. To gain access to functionality, users have to be registered with an authorization server (PCCEServer) that maintains an access control list. Thus a collaboration group is comprised of a set of PCCE-registered users. Registered users can log in via either X.509 certificate or a username and password combination. PKI and SSL are used to authenticate servers and clients and to encrypt messages sent over the network. The LBNLSecureMessaging application offers instant messaging capabilities in a secure environment that provides data integrity, privacy authorization, and authentication.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "LBNL SecureMessaging", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The PCCEServer application is a server that should be used in conjunction with the LBNLSecureMessaging user interface to enable secure synchronous and asynchronous messaging. It provides authentication and authorization services for members of a collaboration group via PKI/SSL and maintains an access control list. Members of collaboration groups using the LBNLSecureMessaging client must register identifying information. including username and password and an optional X.509 certificate, with the PCCEServer. This registration not only restricts access to instant messaging, but augments the LBNLSecureMessaging's IRC-based chat facility with persistence. Users register permanent unique user ids by which they are known to other users in the system and create permanent venues intended for group conversations on a tong-term or continuous basis. In addition, the PCCEServer enhances instant messaging with presence and awareness information such as user availability, and it allows users to leave notes asynchronously for other users who are online or offline. Written in Java, it is a standalone application that can run on any platform that supports a Java Virtual Machine.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Java Version 1.4 or higher (including JSSE)" + ], + "name": "PCCEServer", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "pyGlobus provides a high-level object-oriented interface to the Globus Toolkit(r). It offers similar performance to the underlying toolkit, while allowing for easier programming.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "pyGlobus", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "Existing reliable ordered group communication protocols have been developed for local-area networks and do not in general scale well to a large number of nodes and wide-area networks. The InterGroup suite of protocols is a scalable group communication system that introduces an unusual approach to handling group membership, and supports a receiver-oriented selection of service. The protocols are intended for a wide-area network, with a large number of nodes, that has highly variable delays and a high message loss rate, such as the Internet. 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CORE contains implementation of two remapping algorithms: a new, efficient \"swept region\" algorithm, and a more traditional algorithm basedon the computation of cell intersections. Grids may be Cartesian or cylindrical, and cells may have three or more vertices, with no upper limit. CORE can run in serial and in parallel, but in order to achieve wide applicability, CORE used no particular parallel communication library. Instead it achieves parallel communication through strategically placed, user defined callbacks. Users can also provide callbacks to redefine different parts or subcomponents of the remapping process. CORE allows the use of different data types, e.g. single-, double-, and quadruple- precision floating-point numbers, through the use of C++ templates. Using CORE is simple, and requires no configuration scripts or makefiles.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "Any ANSI-compliant C++ compiler" + ], + "name": "Conservative Remapper", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The ThreatView project is based on our prior work with the existing ParaView open-source scientific visualization application. Where ParaView provides a grapical client optimized scientific visualization over the VTK parallel client server architecture, ThreatView provides a client optimized for more generic visual analytics over the same architecture. Because ThreatView is based on the VTK parallel client-server architecture, data sources can reside on remote hosts, and processing and rendering can be performed in parallel. As seen in Fig. 1, ThreatView provides four main methods for visualizing data: Landscape View, which displays a graph using a landscape metaphor where clusters of graph nodes produce \"hills\" in the landscape; Graph View, which displays a graph using a traditional \"ball-and-stick\" style; Table View, which displays tabular data in a standard spreadsheet; and Attribute View, which displays a tabular \"histogram\" of input data - for a selected table column, the Attribute View displays each unique value within the column, and the number of times that value appears in the data. There are two supplemental view types: Text View, which displays tabular data one-record-at-a-time; and the Statistics View, which displays input metadata, such as the number of vertices and edges in a graph, the number of rows in a table, etc.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "ThreatView", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The \"Fuel Cycle Services Needs Estimator\", Version 2.0 allows users to estimate the amount of uranium enrichment services needed and amount of spent nuclear fuel produced by a given fleet of nuclear power reactors through 2050 based on user-determined information about the size of a reactor fleet and average characteristics of reactors in that fleet. The program helps users evaluate the current and future supply of nuclear fuel cycle services. The program also allows users to compare the enrichment needs and spent fuel production of more up to seven defined nuclear power reactor fleets and to aggregate estimated needs. Version 2.0 of the program has an additions of new graphs to show results of calculations (calculation capabilities and other graphing tools included in version 1.o), maps showing flows of material based on calculation results, and additional calculation capabilities that allow the user to compare supply to demand (demand calculations included in version 1.0). Default values for seven selected nuclear energy programs in East Asia are included for reference and comparison. The program was designed using the dynamic simulation software, Powersim.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "Fuel Cycle Services Needs Estimator v.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "TIIA is designed to perform ecological and human risk assessments for environmental contaminants in air, water, soil, and sediment. 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Specifically, the main class of problems targeted by HEMLOCK is the problem of multiple-class classification (also called labeling or categorization) of data with continuous or discrete features. HEMLOCK consists of various data readers, machine learning algorithms, model combination and comparison routines, evaluation methods for model performance testing, and interfaces to external, state-of-the-art machine learning software libraries.", + "laborHours": 2720.8, + "languages": [ + "Java" + ], + "name": "HEMLOCK", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/HEMLOCK?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HEMLOCK", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "These are patches to Sun Microsystems open source OpenSSO project to fix various bugs and incorporate changes for Sandia and NNSA to use the product including fixes to improve OpenSSO's authentication and authorization abilities. These fixes will then by incorporated by Sun into their Sun Access Manager product, which is used by various DOE/NNSA plants and labs. Having Sun maintain these changes will relieve SNL and DOE from the cost of maintaining the changes themselves.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "OpenSSO Project Patches", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-25" + }, + "description": "NIDR (New Input Deck Reader) is a facility for processing block-structured input to large programs. NIDR was written to simplify maintenance of DAKOTA (a program for uncertainty quantification and optimization), to provide better error checking of input and to allow use of aliases in the input. While written to support DAKOTA input conventions, NIDR itself is independent of DAKOTA and can be used in many kinds of programs. The initial version of NIDR was copyrighted in 2008. We have since extended NIDR to support a graphical user interface called Jaguar for DAKOTA. In the Review and Approval process for an updated paper on NIDR, the Classification Approver states that a new copyright assertion should be performed.processing input to programs. NIDR is not primarily for military applications.", + "laborHours": 0.0, + "languages": [ + "C++/C" + ], + "name": "NIDR (New Input Deck Reader) V2.0 2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/nidr", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.02" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "libdinterpose is a Linux, C convenience library to assist you in writing interposer libraries to help you debug programs.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "lib debug interpose", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Master stores information about each node in a computer cluster, similar to an asset tracking program. Records changes and events happening on the system. 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GIO uses a combination of configuration files and API calls to define the mapping of internal model data to output variables in standard climate data formats. The mapping from model data to model output includes method of data slicing, aggregation, and linearization using a morton ordering approach. The data is then persisted through a standard interface that can be implemented using several different high level parallel libraries. Both Parallel NetCDF and NetCDF4 interfaces are provided. GIO is designed to run on supercomputing systems or multi-processor clusters with parallel file systems.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Geodesic IO Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The SWTools code is an infrastructure to facilitate the management of third-party software installations. 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Inventory and user documentation will be kept up to date dynamically; that is, the same documentation that the installer writes for local users of the system will be made available online, and all web based inventory information will be dynamically updated.", + "homepageURL": "https://www.olcf.ornl.gov/center-projects/swtools", + "laborHours": 0.0, + "languages": [ + "Python 2.5 or Korn shell script" + ], + "name": "SWTools", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.olcf.ornl.gov/center-projects/swtools", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.olcf.ornl.gov/center-projects/swtools", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "An important rate-limiting step in the resonance assignment process is accurate identification of resonance peaks in MNR spectra. NMR spectra are noisy. Hence, automatic peak-picking programs must navigate between the Scylla of reliable but incomplete picking, and the Charybdis of noisy but complete picking. Each of these extremes complicates the assignment process: incomplete peak-picking results in the loss of essential connectivities, while noisy picking conceals the true connectivities under a combinatiorial explosion of false positives. Intermediate processing can simplify the assignment process by preferentially removing false peaks from noisy peak lists. This is accomplished by requiring consensus between multiple NMR experiments, exploiting a priori information about NMR spectra, and drawing on empirical statistical distributions of chemical shift extracted from the BioMagResBank. Experienced NMR practitioners currently apply many of these techniques \"by hand\", which is tedious, and may appear arbitrary to the novice. To increase efficiency, we have created a systematic and automated approach to this process, known as APART. Automated pre-processing has three main advantages: reduced tedium, standardization, and pedagogy. In the hands of experienced spectroscopists, the main advantage is reduced tedium (a rapid increase in the ratio of true peaks to false peaks with minimal effort). When a project is passed from hand to hand, the main advantage is standardization. APART automatically documents the peak filtering process by archiving its original recommendations, the accompanying justifications, and whether a user accepted or overrode a given filtering recommendation. In the hands of a novice, this tool can reduce the stumbling block of learning to differentiate between real peaks and noise, by providing real-time examples of how such decisions are made.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [], + "name": "Automated Pre-processing for NMR Assignments with Reduced Tedium", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The security group at NERSC recently undertook a project to gain access to this information from user ssh logins. Our solution was to modify the SSH daemon to export information about user names, authentication, keystrokes, file transfers, remote command execution and a variety of SSH related metadata in as agnostic a way as possible. In addition to improved system auditing, we added the Pittsburgh Supercomputing Performance improvement patches as well.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Instrumented OpenSSH", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Software tool based on a structured methodology for conducting laboratory biosafety risk assessments by biosafety experts. Software is based upon an MCDA scheme and uses peer reviewed criteria and weights. The software was developed upon Microsoft's .net framework. The methodology defines likelihood and consequence of a laboratory exposure for thirteen unique scenarios and provides numerical relative risks for each of the relevant thirteen. The software produces 2-d graphs reflecting the relative risk and a sensitivity analysis which highlights the overall importance of each factor. The software works as a set of questions with absolute scales and uses a weighted additive model to calculate the likelihood and consequence.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Windows.NET" + ], + "name": "Biosafety Risk Assessment Model", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-22" + }, + "description": "HNQ is a low level benchmark code used to characterize storage hardware performance.", + "laborHours": 334.4, + "languages": [ + "C" + ], + "name": "HNQ Version 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hnq", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Drekar is a code written for solving the low-mach incompressible Navier-Stokes and magnetohydrodynamics equations. It implements a stabilized Galerkin finite element discretization of the incompressible Navier-Stokes equations and a variational multiscale stabilized formulation for magnetohydrodynamics published by Codina. Drekar contains the front end physics description of the problem and then leverages 30 open source Trilinos packages to solve the problem. It relies on Trilinos for all parallel capabilities. The code will be released open source under the LGPL license. The code will be used by the partners of the Consortium for Advanced Simulation of Light Water Reactors (CASL), an Energy Innovation Hub funded by DOE to simulate fluid flow and heat transfer inside nuclear reactors. Additionally the code will be used for fundamental research collaborations in magnetohydrodynamics and computational fluid dynamics.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++ / various compilers" + ], + "name": "Drekar", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The software provides a simple web api to allow users to request a time window where a file will not be removed from cache. HPSS provides the concept of a \"purge lock\". When a purge lock is set on a file, the file will not be removed from disk, entering tape only state. A lot of network file protocols assume a file is on disk so it is good to purge lock a file before transferring using one of those protocols. HPSS's purge lock system is very coarse grained though. A file is either purge locked or not. Nothing enforces quotas, timely unlocking of purge locks, or managing the races inherent with multiple users wanting to lock/unlock the same file. The Purge Lock Server lets you, through a simple REST API, specify a list of files to purge lock and an expire time, and the system will ensure things happen properly.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C", + "PHP" + ], + "name": "Purge Lock Server", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "MyEMSL provides the following features: user-assisted upload of data from scientific instruments to an archive, tracking data though the upload process, providing metadata for recovery of uploaded data, providing users with access to the data. These features are supplied by a mixture of open source software and internally developed software. MyESML also provides a notification system that allows the system to communicate with users and other parts of the MyEMSL system. This allows the system to support automated workflows and user interaction. Reprocessing of already ingested data is also supported.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C, Python, PHP, Go, C#, Javascript" + ], + "name": "MyEMSL", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The software package, processMC, is a python script that allows for the rapid modeling of small , noisy quantum systems and the computation of the averaged quantum evolution map.", + "laborHours": 228.0, + "languages": [ + "Python 2.6" + ], + "name": "Quantum Process Matrix Computation by Monte Carlo", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/processMC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "COYOTE is designed for the analysis of steady and transient, multi-dimensional, nonlinear heat conduction problems. The spatial discretization technique is based on the Galerkin finite element method. The code contains a library of linear and quadratic elements and incudes bars and shells. COYOTE Implicit and explicit time integration methods, with adaptive time step control, are available for transient problems and fixed-point methods are used for Conjugate gradient iterative methods are used for the matrix solution. Coupled enclosure radiation with efficient view factor computation is included. Simulation capabilities include material motion, dynamic radiation enclosures, contact boundary conditions, multipoint constraints, material (element) addition, and deletion, bulk nodes, chemically reactive materials, and coupling with other mechanics codes. The code is designed for single or multi-processor computing", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "COYOTE", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The STAYSL PNNL Suite of software provides a set of tools for working with neutron activation rates measured in a nuclear fission reactor, an accelerator-based neutron source, or any neutron field to determine the neutron flux spectrum through a generalized least-squares approach. This process is referred to as neutron spectral adjustment since the preferred approach is to use measured data to adjust neutron spectra provided by neutron physics calculations. The input data consist of the reaction rates based on measured activities, an initial estimate of the neutron flux spectrum, neutron activation cross sections and their associated uncertainties (covariances), and relevant correction factors. The output consists of the adjusted neutron flux spectrum and associated covariance matrix, which is useful for neutron dosimetry and radiation damage calculations. The software suite consists of the STAYSL PNNL, SHIELD, BCF, and NJpp Fortran codes and the SigPhi Calculator spreadsheet tool. In addition, the development of this software suite and associated data libraries used the third-party NJOY99 Fortran code (http://t2.lanl.gov/nis/codes/njoy99/). The NJOY99 and NJpp codes are used to assemble cross section and covariance input data libraries (for both SHIELD and STAYSL PNNL) from the International Reactor Dosimetry File of 2002 (IRDF-2002; http://www-nds.iaea.org/irdf2002/) developed by the Nuclear Data Section of the International Atomic Energy Agency (Vienna, Austria). The BCF, SigPhi Calculator, and SHIELD software tools are used to calculate corrected activation rates and neutron self-shielding correction factors, which are inputs to the STAYSL PNNL code.", + "homepageURL": "https://www.pnnl.gov/projects/staysl-pnnl-software-suite-reactor-dosimetry", + "laborHours": 0.0, + "languages": [], + "name": "STAYSL PNNL Suite", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/projects/staysl-pnnl-software-suite-reactor-dosimetry", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/projects/staysl-pnnl-software-suite-reactor-dosimetry", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The LMDT software automates the process of the load composite model data preparation in the format supported by the major power system software vendors (GE and Siemens). Proper representation of the load composite model in power system dynamic analysis is very important. Software tools for power system simulation like GE PSLF and Siemens PSSE already include algorithms for the load composite modeling. However, these tools require that the input information on composite load to be provided in custom formats. Preparation of this data is time consuming and requires multiple manual operations. The LMDT software enables to automate this process. Software is designed to generate composite load model data. It uses the default load composition data, motor information, and bus information as an input. Software processes the input information and produces load composition model. Generated model can be stored in .dyd format supported by GE PSLF package or .dyr format supported by Siemens PSSE package.", + "homepageURL": "https://svn.pnl.gov/LoadTool", + "laborHours": 0.0, + "languages": [], + "name": "Load Model Data Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://svn.pnl.gov/LoadTool#License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.pnl.gov/LoadTool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "This software is used to combine output files US EPA CAp88-PC software (http://www.epa.gov/radiation/assessment/CAP88/aboutcap88.html) and estimate input parameters for CAP88-PC. Also includes features for tabular and graphical review of results.", + "homepageURL": "http://rneshaps.r-forge.r-project.org", + "laborHours": 0.0, + "languages": [], + "name": "Rneshaps", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://rneshaps.r-forge.r-project.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The software interpolates tabular data, such as for equations of state, provided on an unstructured triangular grid. In particular, interpolation occurs in a two dimensional space by looking up the triangle in which the desired evaluation point resides and then performing a linear interpolation over the n-tuples associated with the nodes of the chosen triangle. The interface to the interpolation routines allows for automated conversion of units from those tabulated to the desired output units. when multiple tables are included in a data file, new tables may be generated by on-the-fly mixing of the provided tables", + "laborHours": 1656.8, + "languages": [ + "C", + "Fortran" + ], + "name": "Sandia Unstructured Triangle Tabular Interpolation Package v 0.1 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/UTri", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software generates data tables for thermodynamic and transport properties of materials as described by a set of input models. For each input model parameterization, an associated table is created on an unstructured triangular grid. These grids all conform to the same topology. A statistical accuracy guarantee is provided for the tabular representation of the model. Details of the model and table specification are given in a XML input deck.", + "laborHours": 69798.4, + "languages": [ + "lc/C++/FORTRAN" + ], + "name": "Sandia Unstructured Triangle Table Generator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/SUTTG?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SUTTG", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SOS is software that stores data values in a set of structured flat files. The data is organized in the files based upon functions specified by the user in order to enable fast insertion and retrieval of data.", + "laborHours": 54036.0, + "languages": [ + "C", + "Roff", + "RPC", + "Cython", + "M4", + "Python" + ], + "name": "Scalable Object Store v. 1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ovis-hpc/sos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This package assists in genome assembly. extendFromReads takes as input a set of Illumina (eg, MiSeq) DNA sequencing reads, a query seed sequence and a direction to extend the seed. The algorithm collects all seed-- ]matching reads (flipping reverse-- ]orientation hits), trims off the seed and additional sequence in the other direction, sorts the remaining sequences alphabetically, and prints them aligned without gaps from the point of seed trimming. This produces a visual display distinguishing the flanks of multi- ]copy seeds. A companion script hitMates.pl collects the mates of seed-- ]hi]ng reads, whose alignment reveals longer extensions from the seed. The collect/trim/sort strategy was made iterative and scaled up in the script denovo.pl, for de novo contig assembly. An index is pre-- ]built using indexReads.pl that for each unique 21-- ]mer found in all the reads, records its gfate h of extension (whether extendable, blocked by low coverage, or blocked by branching after a duplicated sequence) and other characteristics. Importantly, denovo.pl records all branchings that follow a branching contig endpoint, providing contig- ]extension information", + "laborHours": 30.4, + "languages": [ + "perl" + ], + "name": "extendFromReads", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/extendFromReads", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-24" + }, + "description": "JAGUAR is a Java software tool for automatically rendering a graphical user interface (GUI) from a structured input specification. It is designed as a plug-in to the Eclipse workbench to enable users to create, edit, and externally execute analysis application input decks and then view the results. JAGUAR serves as a GUI for Sandia's DAKOTA software toolkit for optimization and uncertainty quantification. It will include problem (input deck)set-up, option specification, analysis execution, and results visualization. Through the use of wizards, templates, and views, JAGUAR helps uses navigate the complexity of DAKOTA's complete input specification. JAGUAR is implemented in Java, leveraging Eclipse extension points and Eclipse user interface. JAGUAR parses a DAKOTA NIDR input specification and presents the user with linked graphical and plain text representations of problem set-up and option specification for DAKOTA studies. After the data has been input by the user, JAGUAR generates one or more input files for DAKOTA, executes DAKOTA, and captures and interprets the results", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "JAva GUi for Applied Research (JAGUAR) v 3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/jaguar", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "This piece of software is a new feature implemented inside an existing open-source library. Specifically, it is a new implementation of a density functional (HSE, short for Heyd-Scuseria-Ernzerhof) for a repository of density functionals, the libxc library. It fixes some numerical problems with existing implementations, as outlined in a scientific paper recently submitted for publication. Density functionals are components of electronic structure simulations, which model properties of electrons inside molecules and crystals.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C, any up-to-date compiler should suffice" + ], + "name": "HSE12 implementation in libxc", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The Megatux platform enables the emulation of large scale (multi-million node) distributed systems. In particular, it allows for the emulation of large-scale networks interconnecting a very large number of emulated computer systems. It does this by leveraging virtualization and associated technologies to allow hundreds of virtual computers to be hosted on a single moderately sized server or workstation. Virtualization technology provided by modern processors allows for multiple guest OSs to run at the same time, sharing the hardware resources. The Megatux platform can be deployed on a single PC, a small cluster of a few boxes or a large cluster of computers. With a modest cluster, the Megatux platform can emulate complex organizational networks. By using virtualization, we emulate the hardware, but run actual software enabling large scale without sacrificing fidelity.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C/Python" + ], + "name": "Megatux", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software provides a general interface for querying thermodynamic states of material models along with implementation of both general and specific equation of state models. In particular, models are provided for the IAPWS-IF97 and IAPWS95 water standards as well as the associated water standards for viscosity, thermal conductivity, and surface tension. The interface supports implementation of models in a variety of independent variable spaces. Also, model support routines are included that allow for coupling of models and determination and representation of phase boundaries.", + "laborHours": 3009.6, + "languages": [ + "CMake", + "C++", + "C" + ], + "name": "Sandia Equation of State Model Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/SESML?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SESML", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Rnnotator is an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads.", + "homepageURL": "https://sites.google.com/a/lbl.gov/rnnotator/home", + "laborHours": 0.0, + "languages": [], + "name": "Rnnotator 3.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sites.google.com/a/lbl.gov/rnnotator/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sites.google.com/a/lbl.gov/rnnotator/home", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "CLaMS-\"Classifer for Metagenonic Sequences\" is a Java application for binning assembled metagenomes wings user-specified training sequence sets and other user-specified initial parameters. Since ClAmS analyzes and matches sequence composition-based genomic signatures, it is much faster than binning tools that rely on alignments to homologs; CLaMS can bin ~20,000 sequences in 3 minutes on a laptop with a 2.4 Ghz. Intel Core 2 Duo processor and 2 GB Ram. CLaMS is meant to be desktop application for biologist and can be run on any machine under any operating system on which the Java Runtime Environment is enabled. CLaMS is freely available in both GVI-based and command-line based forms.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "JRE" + ], + "name": "CLaMS: Classifier for Metagenomic Sequences", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Application that uses the Python low-level socket interface to pass network traffic between devices on the local side of a NAT router and the WAN side of the NAT router. This application is designed to generate traffic that complies with the Energy Star Small Network Equipment Test Method.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Python 2.7" + ], + "name": "Network Traffic Generator for Low-rate Small Network Equipment Software", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "StruMF is an algebraic structured preconditioner for the interative solution of large sparse linear systems. The preconditioner corresponds to a multifrontal variant of sparse LU factorization in which some dense blocks of the factors are approximated with low-rank matrices. It is algebraic in that it only requires the linear system itself, and the approximation threshold that determines the accuracy of individual low-rank approximations. Favourable rank properties are obtained using a block partitioning which is a refinement of the partitioning induced by nested dissection ordering.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "C compilers" + ], + "name": "Structured Multifrontal Sparse Solver", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The raw computational power GPU Accelerators enables fast denoising of 3D MR images using bilateral filtering, anisotropic diffusion, and non-local means. This software addresses two facets of this promising application: what tuning is necessary to achieve optimal performance on a modern GPU? And what parameters yield the best denoising results in practice? To answer the first question, the software performs an autotuning step to empirically determine optimal memory blocking on the GPU. To answer the second, it performs a sweep of algorithm parameters to determine the combination that best reduces the mean squared error relative to a noiseless reference image.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "GPU-Accelerated Denoising in 3D (GD3D)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The Single Cell Data Decontamination Pipeline is a fully-automated software tool which classifies unscreened contigs from single cell datasets through a combination of homology and feature-based methodologies using the organism's nucleotide sequences and known NCBI taxonomony. The software is freely available to download and install, and can be run on any system.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "ProDeGe: A Computational Protocol for fully Automated Decontamination of Genomic Data", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "TabVar: A Python library for manipulating datasets in the form of tabulated variables. Tables in tabvar contain many columns representing independent variables, but exactly one distinguished column for the dependent variable. Having a single distinguished column allows a natural lifting of arithmetic operators to tables, much (and in fact fully generalizing) multidimensional array arithmetic. The convenient syntax of whole-table arithmetic, along with the usual operations of filtering and aggregation, and all in the setting of python's interactive REPL allows for rapid exploration of datasets.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TabVar: Tabulated Variables", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "batchacct provides convenient library and command-line access to batch system accounting data for GridEngine and SLURM schedulers. It can be used to perform queries useful for data analysis of the accounting data alone or for integrative analysis in the context of a larger query.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "gcc/4.8 or higher" + ], + "name": "QQACCT", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Mini-PIC is an electrostatic particle-in-cell (PIC} testbed application for development of MPl+X applications on next generation platforms.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++98" + ], + "name": "Mini-PIC", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Mingus provides hybrid coupled local/non-local mechanics analysis capabilities that extend several traditional methods to applications with inherent discontinuities. Its primary features include adaptations of solid mechanics, fluid dynamics and digital image correlation that naturally accommodate dijointed data or irregular solution fields by assimilating a variety of discretizations (such as control volume finite elements, peridynamics and meshless control point clouds). The goal of this software is to provide an analysis framework form multiphysics engineering problems with an integrated image correlation capability that can be used for experimental validation and model", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++, CNU or Clang" + ], + "name": "Mingus Discontinuous Multiphysics", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "In the field of mathematical finance, a \"backtest\" is the usage of historical market data to assess the performance of a proposed trading strategy. It is a relatively simple matter for a present-day computer system to explore thousands, millions or even billions of variations of a proposed strategy, and pick the best performing variant as the \"optimal\" strategy \"in sample\" (i.e., on the input dataset). Unfortunately, such an \"optimal\" strategy often performs very poorly \"out of sample\" (i.e. on another dataset), because the parameters of the invest strategy have been oversit to the in-sample data, a situation known as \"backtest overfitting\". While the mathematics of backtest overfitting has been examined in several recent theoretical studies, here we pursue a more tangible analysis of this problem, in the form of an online simulator tool. Given a input random walk time series, the tool develops an \"optimal\" variant of a simple strategy by exhaustively exploring all integer parameter values among a handful of parameters. That \"optimal\" strategy is overfit, since by definition a random walk is unpredictable. Then the tool tests the resulting \"optimal\" strategy on a second random walk time series. In most runs using our online tool, the \"optimal\" strategy derived from the first time series performs poorly on the second time series, demonstrating how hard it is not to overfit a backtest. We offer this online tool, \"Simple Example of Backtest Overfitting (SEBO)\", to facilitate further research in this area.", + "homepageURL": "http://datagrid.lbl.gov/backtest", + "laborHours": 0.0, + "languages": [ + "Phython 2.7" + ], + "name": "Simple Example of Backtest Overfitting (SEBO)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://datagrid.lbl.gov/backtest", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://datagrid.lbl.gov/backtest", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "VAWTGen is a mesh generator for creating a finite element beam mesh of arbitrary vertical-axis wind turbines (VAWT). The software accepts input files specifying tower and blade structural and aerodynamic descriptions and constructs a VAWT using a minimal set of inputs. VAWTs with an arbitrary number of blades can be constructed with or without a central tower. Strut connections between the tower and blades can be specified in an arbitrary manner. The software also facilitates specifying arbitrary joints between structural components and concentrated structural tenns (mass and stiffness). The output files which describe the VAWT configuration are intended to be used with the Offshore Wind ENergy Simulation (OWENS) Toolkit software for structural dynamics analysis of VAWTs. Furthermore, VAWTGen is useful for visualizing output from the OWENS analysis software.", + "laborHours": 912.0, + "languages": [ + "MATLAB" + ], + "name": "Vertical-Axis Wind Turbine Mesh Generator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/VAWTGen?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/VAWTGen", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "This software allows a student/user at some point during the flow of content on a web page to input comments and rate the content with things such as: 1) True false 2) Text Comments 3) Ratings 1-5 4) etc. This information is stored anonymously in the database and can be retrieved and reported on.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + ".NET 4.5x" + ], + "name": "Survey Administration Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This software package provides a common \"front end\" for various math operations that are relevant to astrophysical data processing. This includes special function evaluation, fast Fourier transforms, streamed random number generation and spherical geometry projections. Computer-vendor specific libraries and internal algorithms can be selected on different systems in order to achieve the best possible performance on all systems. This software is still in an early state of development. ", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Any Standard C++ compiler which supports the BOOST software package" + ], + "name": "Machine Optimized Analysis Tools", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The Open Smart Energy Gateway (OpenSEG) aims to provide near-real time smart meter data to consumers without the delays or latencies associated with it being transported to the utility data center and then back to the consumer's application. To do this, the gateway queries the local Smart Meter to which it is bound to get energy consumption information at pre-defined intervals (minimum interval is 4 seconds). OpenSEG then stores the resulting data internally for retrieval by an external application.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Open Smart Energy Gateway (OpenSEG)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Phisherman is an online software tool that was created to help experimenters study phishing. It can potentially be re-purposed to run other human studies. Phisherman enables studies to be run online, so that users can participate from their own computers. This means that experimenters can get data from subjects in their natural settings. Alternatively, an experimenter can also run the app online in a lab-based setting, if that is desired. The software enables the online deployment of a study that is comprised of three main parts: (1) a consent page, (2) a survey, and (3) an identification task, with instruction/transition screens between each part, allowing the experimenter to provide the user with instructions and messages. Upon logging in, the subject is taken to the permission page, where they agree to or do not agree to take part in the study. If the subject agrees to participate, then the software randomly chooses between doing the survey first (and identification task second) or the identification task first (and survey second). This is to balance possible order effects in the data. Procedurally, in the identification task, the software shows the stimuli to the subject, and asks if she thinks it is a phish (yes/no) and how confident she is about her answer. The subject is given 5 levels of certainty to select from, labeled \"low\" (1), to \"medium\" (3), to \"high\" (5), with the option of picking a level between low and medium (2), and between medium and high (4). After selecting his/her confidence level, then the \"Next\" button activates, allowing a user to move to the next email. The software saves a given subject's progress in the identification task, so that she may log in and out of the site. The consent page is a space for the experimenter to provide the subject with human studies board /internal review board information, and to formally consent to participate in the study. The survey is a space for the experimenter to provide questions and spaces for the users to input answers (allowing both multiple-choice and free-answer options). Phisherman includes administrative pages for managing the stimuli and users. This includes a tool for the experimenter to create, preview, edit, delete (if desired), and manage stimuli (emails). The stimuli may include pictures (uploaded to an appropriate folder) and links, for realism. The software includes a safety feature that prevents the user from going to any link location or opening a file/image. Instead of re-directing the subject's browser, the software provides a pop-up box with the URL location of where the user would have gone. Another administrative page may be used to create fake subject accounts for testing the software prior to deployment, as well as to delete subject accounts when necessary. Data from the experiment can be downloaded from another administrative page.", + "laborHours": 3800.0, + "languages": [ + "Groovy", + "CSS", + "JavaScript" + ], + "name": "Phisherman v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/phisherman", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Computational Fluid Dynamics is an important area in scientific computing where, despite the use of multi-threading, obtaining good performance at each core is still extremely challenging. The challenges are primarily due to memory bandwidth limitations and difficulties in using short SIMD engines effectively. One strategy to improve in-core performance involves using a hierarchical data layout made of small cubical structures of the problem states that can fit well in the cache hierarchy. Even for such a hierarchical data layout, finite-differencing equations can be easily expressed but at the expense of some inefficiency. The transformations to overcome the inefficiencies are highly tedious and error-prone. Therefore, we built a source-to-source translator called CFDbuilder to automate the transformations using directives. We see up to 6.92x performance improvement with one of our advection codes using such an approach. We believe such an approach could enable library and application writers to build efficient CFD libraries.", + "laborHours": 8831.2, + "languages": [ + "Java", + "Makefile", + "GAP" + ], + "name": "CFDbuilder", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/CFDbuilder?tab=License-1-ov-file", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CFDbuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Suite of programs for evaluating endothelial function, including protocol execution, data acquisition, and analysis", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "GCC 4.x" + ], + "name": "Software Suite for Endothelial Function Assessment", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Flexibility from distributed energy resources presents an enormous potential to provide various services to the smart grid. In this paper, we propose a unified hierarchical framework for aggregation and coordination of various flexible loads, such as commercial building Heating, Ventilation, and Air-Conditioning (HVAC) systems, Thermostatically Controlled Loads (TCLs), Distributed Energy Storages (DESs), residential Pool Pumps (PPs), and Electric Vehicles (EVs). Moreover, a multistage Nash-bargaining-based control strategy is proposed to coordinate different aggregations of flexible loads for demand response. Case studies are provided to demonstrate the efficacy of our proposed framework and coordination strategy in managing peak power demand in a community.", + "homepageURL": "https://store.pnnl.gov/content/multi-period-nash-bargaining-coordination-distributed-energy-resources", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Multi-period Nash bargaining for Coordination of Distributed Energy Resources", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/multi-period-nash-bargaining-coordination-distributed-energy-resources", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/multi-period-nash-bargaining-coordination-distributed-energy-resources", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The approach is based on classical Density Functional Theory (cDFT) coupled with the Poisson-Nernst-Planck (PNP) transport kinetics model and quantum mechanical description of short-range interaction and elementary transport processes. The model we proposed and implemented is fully atomistic, taking into account pairwise short-range and manybody long-range interactions. But in contrast to standard molecular dynamics (MD) simulations, where long-range manybody interactions are evaluated as a sum of pair-wise atom-atom contributions, we include them analytically based on well-established theories of electrostatic and excluded volume interactions in multicomponent systems. This feature of the PNP/cDFT approach allows us to reach well beyond the length-scales accessible to MD simulations, while retaining the essential physics of interatomic interactions from first principles and in a parameter-free fashion.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "FORTRAN" + ], + "name": "cDF Theory Software for mesoscopic modeling of equilibrium and transport phenomena", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The Designs for Risk Evaluation and Management (DREAM) tool was developed as part of the effort to quantify the risk of geologic storage of carbon dioxide (CO2) under the U.S. Department of Energy's National Risk Assessment Partnership (NRAP). DREAM is an optimization tool created to identify optimal monitoring schemes that minimize the time to first detection of CO2 leakage from a subsurface storage formation. DREAM acts as a post-processer on user-provided output from subsurface leakage simulations. While DREAM was developed for CO2 leakage scenarios, it is applicable to any subsurface leakage simulation of the same output format. The DREAM tool is comprised of three main components: (1) a Java wizard used to configure and execute the simulations, (2) a visualization tool to view the domain space and optimization results, and (3) a plotting tool used to analyze the results. A secondary Java application is provided to aid users in converting common American Standard Code for Information Interchange (ASCII) output data to the standard DREAM hierarchical data format (HDF5). DREAM employs a simulated annealing approach that searches the solution space by iteratively mutating potential monitoring schemes built of various configurations of monitoring locations and leak detection parameters. This approach has proven to be orders of magnitude faster than an exhaustive search of the entire solution space. The user's manual illustrates the program graphical user interface (GUI), describes the tool inputs, and includes an example application.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Designs for Risk Evaluation and Management", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The OpenSHMEM Analyzer is a compiler-based tool that can help users detect errors and provide useful analyses about their OpenSHMEM applications. The tool is built on top of the OpenUH compiler (a branch of Open64 compiler) and presents OpenSHMEM information as feedback to the user. Some of the analyses it provides include checks for correct usage of symmetric variables in OpenSHMEM calls, out-of-bounds checks for symmetric data, checks for the correct initialization of pointers to symmetric data, and symmetric data alias information.", + "homepageURL": "http://www.openshmem.org/site/OSA", + "laborHours": 0.0, + "languages": [ + "C, C++ / GCC / 4.3.4" + ], + "name": "The OpenSHMEM Analyzer", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.openshmem.org/site/node/58", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.openshmem.org/site/OSA", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "GFS is a simulation engine that is used for the characterization of Accelerator performance parameters based on the machine layout, configuration and noise sources. It combines extensively tested Feedback models with a longitudinal phase space tracking simulator along with the interaction between the two via beam-based feedback using a computationally efficient simulation engine. The models include beam instrumentation, considerations on loop delays for in both the R and beam-based feedback loops, as well as the ability to inject noise (both correlated and uncorrelated) at different points of the machine including a full characterization of the electron gun performance parameters.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Global Feedback Simulator", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The Dynamic Contingency Analysis Tool (DCAT) is an open-platform and publicly available methodology to help develop applications that aim to improve the capabilities of power system planning engineers to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. Outputs from the DCAT will help find mitigation solutions to reduce the risk of cascading outages in technically sound and effective ways. The current prototype DCAT implementation has been developed as a Python code that accesses the simulation functions of the Siemens PSS/E planning tool (PSS/E). It has the following features: It uses a hybrid dynamic and steady-state approach to simulating the cascading outage sequences that includes fast dynamic and slower steady-state events. It integrates dynamic models with protection scheme models for generation, transmission, and load. It models special protection systems (SPSs)/remedial action schemes (RASs) and automatic and manual corrective actions. Overall, the DCAT attempts to bridge multiple gaps in cascading-outage analysis in a single, unique prototype tool capable of automatically simulating and analyzing cascading sequences in real systems using multiprocessor computers. While the DCAT has been implemented using PSS/E in Phase I of the study, other commercial software packages with similar capabilities can be used within the DCAT framework.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Dynamic Contingency Analysis Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software generates predicted results of differential scanning calorimetry experiments for samples of palladium in a perforated capsule in an atmosphere containing a mixture of hydrogen isotopologues and helium. 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The purpose of the code is to demonstrate both the time it takes to solve the problem as well as the accuracy of the approximate approach. 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We have designed SEAK, a new benchmark suite, (a) to capture these bottlenecks in a way that encourages creative solutions to these bottlenecks? and (b) to facilitate rigorous, objective, end-user evaluation for their solutions. To avoid biasing solutions toward existing algorithms, SEAK benchmarks use a mission-centric (abstracted from a particular algorithm) and goal-oriented (functional) specification. To encourage solutions that are any combination of software or hardware, we use an end-user blackbox evaluation that can capture tradeoffs between performance, power, accuracy, size, and weight. The tradeoffs are especially informative for procurement decisions. We call our benchmarks future proof because each mission-centric interface and evaluation remains useful despite shifting algorithmic preferences. It is challenging to create both concise and precise goal-oriented specifications for mission-centric problems. This paper describes the SEAK benchmark suite and presents an evaluation of sample solutions that highlights power and performance tradeoffs.", + "homepageURL": "https://hpc.pnl.gov/SEAK", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "The Suite for Embedded Applications and Kernels", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://hpc.pnl.gov/SEAK", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://hpc.pnl.gov/SEAK", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Arrows is a software package that combines NWChem, SQL and NOSQL databases, email, and social networks (e.g. Twitter, Tumblr) that simplifies molecular and materials modeling and makes these modeling capabilities accessible to all scientists and engineers. EMSL Arrows is very simple to use. The user just emails chemical reactions to arrows@emsl.pnnl.gov and then an email is sent back with thermodynamic, reaction pathway (kinetic), spectroscopy, and other results. EMSL Arrows parses the email and then searches the database for the compounds in the reactions. If a compound isn't there, an NWChem calculation is setup and submitted to calculate it. Once the calculation is finished the results are entered into the database and then results are emailed back.", + "homepageURL": "https://store.pnnl.gov/content/emsl-arrows", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Environmental and Molecular Science Laboratory Arrow", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/emsl-arrows", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/emsl-arrows", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "INT is a toolkit for computing radiative heat exchange between particles. The algorithm is based on the the 'Photon Monte Carlo\" approach described by Wang and Modest and implemented as a library that can be interfaced with a variety of CFD codes to analyze radiative heat transfer in particle laden flows.", + "homepageURL": "https://www.nrel.gov/workingwithus/licensing.html", + "laborHours": 0.0, + "languages": [ + "FORTRAN" + ], + "name": "IHT: Tools for Computing Insolation Absorption by Particle Laden Flows", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/workingwithus/licensing.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/workingwithus/licensing.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "FAST is a simulation tool (computer software) for modeling tlie dynamic response of horizontal-axis wind turbines. FAST employs a combined modal and multibody structural-dynamics formulation in the time domain.", + "laborHours": 0.0, + "languages": [ + "Fortran", + "C", + "MATLAB (for Simulink interface)" + ], + "name": "FAST Simulation Tool Containing Methods for Predicting the Dynamic Response of Wind Turbines", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/OpenFAST/openfast", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This software package collects various open source and freely available codes and algorithms to compute and archive the categorical data for certain semisimple braided monoidal categories. In particular, it computes the data for of group theoretical categories for academic research.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "GAP / Python" + ], + "name": "Software for Computing, Archiving, and Querying Semisimple Braided Monoidal Category Data", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Xi-CAM aims to provide a community driven platform for multimodal analysis in synchrotron science. The platform core provides a robust plugin infrastructure for extensibility, allowing continuing development to simply add further functionality. Current modules include tools for characterization with (GI)SAXS, Tomography, and XAS. This will continue to serve as a development base as algorithms for multimodal analysis develop. Seamless remote data access, visualization and analysis are key elements of Xi-CAM, and will become critical to synchrotron data infrastructure as expectations for future data volume and acquisition rates rise with continuously increasing throughputs. The highly interactive design elements of Xi-cam will similarly support a generation of users which depend on immediate data quality feedback during high-throughput or burst acquisition modes.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Xi-CAM v1.2.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "A Powersim Studio implementation of the system dynamics’ ‘Molecules of Structure’. The original implementation was in Ventana’s Vensim language by James Hines. The molecules are fundamental constructs of the system dynamics simulation methodology.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Powersim Studio 7, Feature Pack 3, Service Release 9" + ], + "name": "Molecules in Studio v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This method employs the concept of federation, which is defined as the use of existing models that represent aspects of a system in specific domains (such as physical and cyber security domains) and building interfaces to link all of domain models. Federation seeks to build on existing bodies of work. Some examples include the Common Information Models (CIM) maintained by the International Electrotechnical Commission Technical Committee 57 (IEC TC 57) for the electric power industry. Another relevant model is the CIM maintained by the Distributed Management Task Force (DMTF)? this CIM defines a representation of the managed elements in an Information Technology (IT) environment. The power system is an example of a cyber-physical system, where the cyber systems, consisting of computing infrastructure such as networks and devices, play a critical role in the operation of the underlying physical electricity delivery system. Measurements from remote field devices are relayed to control centers through computer networks, and the data is processed to determine suitable control actions. Control decisions are then relayed back to field devices. It has been observed that threat actors may be able to successfully compromise this cyber layer in order to impact power system operation. Therefore, future control center applications must be wary of potentially compromised measurements coming from field devices. In order to ensure the integrity of the field measurements, these applications could make use of compromise indicators from alternate sources of information such as cyber security. Thus, modern control applications may require access to data from sources that are not defined in the local information model. In such cases, software application interfaces will require integration of data objects from cross-domain data models. When incorporating or federating different domains, it is important to have subject matter experts work together, recognizing that not everyone has the same knowledge, responsibilities, focus, or skill set.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Federation of UML models for cyber physical use cases", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This code is a highly modular framework for developing smoothed particle hydrodynamic (SPH) simulations running on parallel platforms. The compartmentalization of the code allows for rapid development of new SPH applications and modifications of existing algorithms. The compartmentalization also allows changes in one part of the code used by many applications to instantly be made available to all applications.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Linux" + ], + "name": "Smoothed Particle Hydrodynamic Simulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "P-Mart was designed specifically to allow cancer researchers to perform robust statistical processing of publicly available cancer proteomic datasets. To date an online statistical processing suite for proteomics does not exist. The P-Mart software is designed to allow statistical programmers to utilize these algorithms through packages in the R programming language as well as offering a web-based interface using the Azure cloud technology. The Azure cloud technology also allows the release of the software via Docker containers.", + "homepageURL": "https://pmart.labworks.org/index.html", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "P-Mart", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://pmart.labworks.org/index.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://pmart.labworks.org/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Typically environmental management problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly integration into a series of models with different complexity for various types of model analyses where the data are applied as soft and hard model constraints. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions). To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian- Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org). The ZEM framework is open-source and can be applied to any environmental management site. The framework will be open-source and released under GPL V3 license.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "Advanced Computational Framework for Environmental Management ZEM, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Akuna is a user environment that enables geoscientists to create conceptual models for subsurface investigations. These conceptual models can be augmented to create numerical models for specific subsurface simulators, and Akuna enables these simulations to be executed on supercomputers, and the results analyzed and visualized. Akuna is designed to easily support multiple subsurface simulators by using a novel, declarative approach that describes the specific features (input file formats, execution modes, output formats) of a simulator in an external data file, based on this data file, Akuna user interfaces are dynamically generated by Akuna, greatly reducing the effort and cost required to support a new simulator.", + "homepageURL": "https://store.pnnl.gov/content/akuna", + "laborHours": 0.0, + "languages": [ + "HPC languages" + ], + "name": "Akuna", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/akuna", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/akuna", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "An application that provides users with ex post information on foregone travel conclusions to induce travel behavioral change.", + "homepageURL": "https://www.nrel.gov/workingwithus/licensing.html", + "laborHours": 0.0, + "languages": [ + "Python 2.7, Javascript, Ruby" + ], + "name": "Retrospective Mobility Analysis", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/workingwithus/licensing.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/workingwithus/licensing.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "LibIsopach is a toolkit for high performance distributed immersive visualization, leveraging modern OpenGL. It features a multi-process scenegraph, explicit instance rendering, mesh generation, and three-dimensional user interaction event processing.", + "homepageURL": "https://www.nrel.gov/workingwithus/licensing.html", + "laborHours": 11126.4, + "languages": [ + "C++14" + ], + "name": "LibIsopach", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/workingwithus/licensing.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/workingwithus/licensing.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The software allows users of the OpenDSS grid modeling software to access their load flow models using a GUI interface developed in MATLAB. The circuit definitions are entered into a Microsoft Excel spreadsheet which makes circuit creation and editing a much simpler process than the basic text-based editors used in the native OpenDSS interface. Plot tools have been developed which can be accessed through a MATLAB GUI once the desired parameters have been simulated.", + "homepageURL": "https://sourceforge.net/projects/electricdss", + "laborHours": 0.0, + "languages": [ + "MATLAB, Delphi (http://www.embarcadero.com), currently version Delphi XE2, Free Pascal" + ], + "name": "Matlab-Excel Interface for OpenDSS", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sourceforge.net/p/electricdss/code/HEAD/tree/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/electricdss", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "PNNL developed a new tool for oscillation analysis and baselining. This tool has been developed under a new DOE Grid Modernization Laboratory Consortium (GMLC) Project (GM0072 - “Suite of open-source applications and models for advanced synchrophasor analysis”) and it is based on the open platform for PMU analysis. The Oscillation Baselining and Analysis Tool (OBAT) performs the oscillation analysis and identifies modes of oscillations (frequency, damping, energy, and shape). The tool also does oscillation event baselining (fining correlation between oscillations characteristics and system operating conditions).", + "homepageURL": "https://svn.pnl.gov/OBAT", + "laborHours": 0.0, + "languages": [ + "VB.NET (MS Visual Studio 2012)" + ], + "name": "Oscillation Baselining and Analysis Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://svn.pnl.gov/OBAT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.pnl.gov/OBAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Gap Resolution is a software package that was developed to improve Newbler genome assemblies by automating the closure of sequence gaps caused by repetitive regions in the DNA. This is done by performing the follow steps:1) Identify and distribute the data for each gap in sub-projects. 2) Assemble the data associated with each sub-project using a secondary assembler, such as Newbler or PGA. 3) Determine if any gaps are closed after reassembly, and either design fakes (consensus of closed gap) for those that closed or lab experiments for those that require additional data. The software requires as input a genome assembly produce by the Newbler assembler provided by Roche and 454 data containing paired-end reads.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Gap Resolution", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Data management tool designed for the Advanced Simulation Capability for Environmental Management (ASCEM) framework. Distinguishing features of this gateway include: (1) handling of complex geometry data, (2) advance selection mechanism, (3) state of art rendering of spatiotemporal data records, and (4) seamless integration with a distributed workflow engine.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "ASCEM Data Brower (ASCEMDB) v0.8", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The software contains a MATLAB implementation of the Generalized Preconditioned Locally Harmonic Residual (GPLHR) method for solving standard and generalized non-Hermitian eigenproblems. 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Standard and generalized eigenproblems are handled in a unified framework.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Generalized Preconditioned Locally Harmonic Residual Eigensolver (GPLHR) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Energy Operation Model (EOM) simulates the operation of the electric grid at the zonal scale, including inter-zonal transmission constraints. 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What is missing is a hydro power dispatch.", + "homepageURL": "https://store.pnnl.gov/content/energy-operation-model-eom", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Energy Operation Model", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/energy-operation-model-eom", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/energy-operation-model-eom", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "High performance parallel computation of sparse inverse covariance matrix estimation.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "MPI C++ COMPLIER WITH OPENmp SUPPORT" + ], + "name": "HP-CONCORD v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This software (Asset Scoring Tool) is designed to help building owners and managers to gain insight into the as-built efficiency of their buildings. 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An API is also under development to allow the third-party applications to exchange data with the web service of the scoring tool.", + "homepageURL": "https://buildingenergyscore.energy.gov", + "laborHours": 0.0, + "languages": [ + "Ruby, C# Javascript" + ], + "name": "Commercial Building Energy Asset Score", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://buildingenergyscore.energy.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://buildingenergyscore.energy.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2025-02-12" + }, + "description": "Two dimension, depth-averaged hydrodynamic and transport model.", + "laborHours": 46284.0, + "languages": [ + "Fortran 90" + ], + "name": "pnnl/mass2", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mass2", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The tool is intended to facilitate hydropower development and water resource planning by improving synthesis and interpretation of disparate spatial datasets that are considered in development actions (e.g., hydrological characteristics, environmentally and culturally sensitive areas, existing or proposed water power resources, climate-informed forecasts). The tool enables this capability by providing a unique framework for assimilating, relating, summarizing, and visualizing disparate spatial data through the use of spatial aggregation techniques, relational geodatabase platforms, and an interactive web-based Geographic Information Systems (GIS). Data are aggregated and related based on shared intersections with a common spatial unit; in this case, industry-standard hydrologic drainage areas for the U.S. (National Hydrography Dataset) are used as the spatial unit to associate planning data. This process is performed using all available scalar delineations of drainage areas (i.e., region, sub-region, basin, sub-basin, watershed, sub-watershed, catchment) to create spatially hierarchical relationships among planning data and drainages. These entity-relationships are stored in a relational geodatabase that provides back-end structure to the web GIS and its widgets. The full technology stack was built using all open-source software in modern programming languages. Interactive widgets that function within the viewport are also compatible with all modern browsers.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Basin Assessment Spatial Planning Platform", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "NIMROD uses a combination of semi-implicit and implicit time-stepping algorithms to advance the equations of extended magnetohydrodynamics. 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For example, the BLAS and derived standards such as cuBLAS do not accept overloads and a different functions have to be called for each input type, thus it is very challenging to write a single template that handles multiple precision modes and works well with different C++ containers. HALA offers a series of templates that wrap around the BLAS/cuBLAS and other similar methods, automatically infer the relevant types and call the appropriate back-end. The templates work out-of-the-box with all C++ standard vector-like containers and can be easily extended (with template specializations) to handle user-provided containers. The HALA API is also overloaded to handle both GPU and CPU cases with a single \"engine\" class, thus a single high-level algorithms can utilize both CPU or GPU backends, i.e., the HALA API is unified and handles the variations between cuBLAS and BLAS. In addition to BLAS and cuBLAS, wrapper templates are provided for subset of LAPACK, cuSparse, and Cholmod methods. Work is in progress to complete as many of these standards as possible. HALA also includes a module for low-level extended register vectorization for complex number arithmetic and several simple solvers that build on the basic linear algebra capabilities. A single unified C++ API will benefit fast prototyping and easily writing code that is portable across GPU/CPU platforms as well as precision types and user containers. Note that HALA does not provide any accelerated algorithms, it simply serves as a \"handy\" front-end to other standards.", + "laborHours": 0.0, + "languages": [ + "C++ (gcc6 and 7 or clang 5 and 6)" + ], + "name": "HALA: Handy Accelerated Linear Algebra", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LIBHALA/hala", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-24", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The aDORe repository architecture, designed and implemented for ingesting, storing, and accessing a vast collection of Digital Objects. aDORe was originally created for use at the Research Library of the Los Alamos National Laboratory. 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Failure to maintain frequency can disrupt the operation of equipment and initiate disconnection of power plant equipment to prevent it from being damaged, which could lead to wide-spread blackouts.\" Frequency Response Tool automates the power system frequency response analysis process. The tool performs initial estimation of the system frequency parameters (initial frequency, minimum frequency, settling point). User can visually inspect and adjust these parameters. The tool also calculates the frequency response performance metrics of the system, archives the historic events and baselines the system performance. Frequency response performance characteristics of the system are calculated using phasor measurement unit (PMU) information. Methodology of the frequency response performance assessment implemented in the tool complies with the NERC Frequency response standard.", + "homepageURL": "https://svn.pnl.gov/FRTool", + "laborHours": 0.0, + "languages": [ + "VB.NET" + ], + "name": "Frequency Response Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://svn.pnl.gov/FRTool#License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.pnl.gov/FRTool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-24", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The Demand Response (DR) Dispatch Tool uses price profiles to dispatch demand response resources and create load modifying profiles. These annual profiles are used as inputs to production cost models and regional planning tools (e.g., PROMOD). The tool has been effectively implemented in transmission planning studies conducted by the Western Electricity Coordinating Council via its Transmission Expansion Planning and Policy Committee. The DR Dispatch Tool can properly model the dispatch of DR resources for both reliability and economic conditions.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Demand Response Dispatch Tool", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-24", + "metadataLastUpdated": "2021-06-10" + }, + "description": "BioStudio is a library of algorithms for the design of large synthetic DNA, with an emphasis on the chromosome scale.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "perl 5.10" + ], + "name": "BioStudio", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-24", + "metadataLastUpdated": "2024-09-11" + }, + "description": "The Battery Lifecycle (BLC) Framework is an open-source platform that provides tools to visualize and share battery data from material characterization, cell testing, manufacturing, and field testing through the technology development cycle. BLC has three components: data importers, a front-end for querying the data and creating visualizations, and an application programming interface to provide access to the data from Python. BLC has been deployed for tracking the development of a battery from the lab to a manufacturing line and systems installed in the field and for comparing studies of multiple cells of the same battery chemistry and configuration. The code was developed around Redash, a robust open-source extract-transform-load engine. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-4546 O", + "laborHours": 380.0, + "languages": [ + "Python", + "Jupyter Notebook", + "Shell" + ], + "name": "Battery Lifecycle Framework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/battery-archive-sandbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-25", + "metadataLastUpdated": "2021-05-25" + }, + "description": "C20129 CoSyR is a unique particle beam dynamics simulation code developed using MPI + Kokkos on multi-GPU platforms. This new simulation code tackles a fundamental problem of the nonlinear dynamics of a particle beam from its complete self-fields, particularly the radiation fields, which underpins many accelerator design issues in high brightness beam applications as well as those arising in the development of advanced accelerators.", + "laborHours": 0.0, + "languages": [], + "name": "CoSyR ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/cosyr.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-05-26", + "metadataLastUpdated": "2021-09-13" + }, + "description": "This tool helps utilities evaluate potential time of use price-plans and find effective hours for price plan on peak periods and the potential price-elastic demand response. An optimization model can be used to find tiered prices for the time of use tariffs and analyze the impact on load profiles, energy consumption, utility, and customer savings. The tool is equipped with an optimization model to determine the energy consumption of electric appliances that can leverage survey data containing information on the number of appliances owned by customers. Lastly, a statistical model can be used to predict system-level load based on exogenous parameters such as weather, time of day, month, type of day, and year. The tool is scripted in Python and uses the Pyomo python optimization language.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "EFFORT (EFFectiveness Of Rate sTructure for enabling demand response)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EFFORT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2021-05-27" + }, + "description": "PSL is a software framework for localizing radiation point sources in a 3D environment using a freely moving radiation detector system. The framework assumes a single point source of radiation is in the environment and uses known detector positions and orientations along with their radiation measurements to find the most likely location of the point source. This approach to the problem enables analyses that improve upon the capability of a standard Maximum Likelihood Expectation Maximization (MLEM) approach, such as setting a source detection threshold, finding a likelihood interval for the position of the source, finding a likelihood interval for the activity (intensity) of the source, determining whether more than one point source may be present, and generating a map of Minimum Detectable Activity (MDA) for a given source type. Applications include radiological and nuclear security, consequence management, decontamination and decommissioning of nuclear facilities, and radiological emergency response.", + "homepageURL": "https://gitlab.com/lbl-anp/ipo/psl", + "laborHours": 0.0, + "languages": [], + "name": "Point Source Likelihood Framework (psl) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://gitlab.com/lbl-anp/ipo/psl", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://gitlab.com/lbl-anp/ipo/psl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "gabor.karsai@vanderbilt.edu" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2021-05-27" + }, + "description": "Python implementation of the RIAPS component model", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "RIAPS/riaps-pycom", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/RIAPS/riaps-pycom", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git", + "version": "1.1.18" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2021-05-27" + }, + "description": "The Localization and Mapping Platform (LAMP) software fuses radiation and contextual data to produce 3-D maps that locate and identify gamma-ray emitting sources in complex environments. It enables data collection, fusion, and processing onboard the LAMP system in handheld configurations, and enables near-real-time 3-D mapping from onboard an unmanned aerial system (UAS). This software enables a real-time 3-D gamma-ray mapping capability that is not available commercially.", + "homepageURL": "https://gitlab.com/lbl-anp/ipo/lamp", + "laborHours": 0.0, + "languages": [], + "name": "Localization and Mapping Platform Software (LAMP) v3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://gitlab.com/lbl-anp/ipo/lamp", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://gitlab.com/lbl-anp/ipo/lamp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2021-09-07" + }, + "description": "The software is used to control an Associated Particle Imaging (API) imaging system that can measure the 3d carbon distribution in soil. Furthermore, the software is used to analyze the data from the instrument.", + "homepageURL": "https://ibt.lbl.gov/projects/software", + "laborHours": 0.0, + "languages": [], + "name": "Associated Particle Imaging for Carbon (APIC) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ibt.lbl.gov/projects/software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ibt.lbl.gov/projects/software", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2021-05-27" + }, + "description": "PARADISE will enable the research community to rapidly evaluate the impact of emerging technologies at the architectural level, and thus provide the means to select among available technologies to facilitate continued digital computing performance scaling.", + "homepageURL": "https://sites.google.com/lbl.gov/paradise/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "PARADISE: PostMoore Architecture and Accelerator Design Space Exploration using Device Level Experiments", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/paradise/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/paradise/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2021-05-27" + }, + "description": "The Functional Mock-up Interface - Machine Learning Center is a tool to interface the Python-Tensorflow library with building simulation models, to develop and train machine learning-based controls. In particular, this framework allows the use of reinforcement learning through the standardized Functional Mock-up Interface, an open industry standard for co-simulation. First application was the development of a controller for dynamic façade and heating ventilation and air conditioning (HVAC) systems.", + "laborHours": 0.0, + "languages": [], + "name": "Functional Mock-up Interface - Machine Learning Center (FMI-MLC) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/FMI-MLC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2021-05-27" + }, + "description": "QCLAB++ is a high-level C++ library of template headers for quantum gates and quantum circuits.", + "laborHours": 0.0, + "languages": [], + "name": "QCLAB++ v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QuantumComputingLab/qclabpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2022-06-13" + }, + "description": "WaterTAP is a new open source library of water-specific models built on the IDAES Integrated Platform to support the design and optimization of integrated water treatment systems, improve existing systems and enable the analysis of new designs incorporating emerging technologies. WaterTAP enables advanced modeling and optimization for: conceptual and multiscale design, dynamics and model predictive control of water systems and networks.", + "laborHours": 0.0, + "languages": [], + "name": "WaterTAP v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/watertap-org/watertap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-05-28", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This code describes the process to estimate material properties using elemental properties and machine learning.", + "laborHours": 0.0, + "languages": [ + "R" + ], + "name": "High Entropy Analysis Code", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HEA_Code", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-05-28", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The Stochastic Techno-Economic Model or STEM is an analytical tool that estimates the logistics cost of different biomass feedstocks by incorporating uncertainty into the modeling framework. The scope of the model covers multiple stages of the biomass life cycle spanning feedstock harvest, collection, transportation and handling, preprocessing, and storage. The model determines the total logistics cost per dry metric ton ($/DM ton) for biomass and breaks down the costs for important cost categories including ownership related costs such as interest and depreciation, insurance, housing, and taxes as well as operating costs like repairs and maintenance, labor costs, and fuel and lube costs.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Stochastic Techno Economic Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/STEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "smith84@llnl.gov" + }, + "date": { + "created": "2021-06-02", + "metadataLastUpdated": "2021-06-29" + }, + "description": "ParFlow is an open-source, modular, parallel watershed flow model. It includes fully-integrated overland flow, the ability to simulate complex topography, geology and heterogeneity and coupled land-surface processes including the land-energy budget, biogeochemistry and snow (via CLM). It is multi-platform and runs with a common I/O structure from laptop to supercomputer. ParFlow is the result of a long, multi-institutional development history and is now a collaborative effort between CSM, LLNL, UniBonn and UCB. ParFlow has been coupled to the mesoscale, meteorological code ARPS and the NCAR code WRF.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Python", + "Tcl" + ], + "name": "ParFlow", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/parflow/parflow/releases/tag/v3.8.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.8.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-06-03", + "metadataLastUpdated": "2021-06-04" + }, + "description": "Five computationally expensive stencil evaluation routines from SW4(https://github.com/geodynamics/sw4 GPL license) have been extracted and packaged with a driver to create a mini-app for evaluating compiler and GPU performance. The kernels can executed on AMD and Nvidia GPUs with and without RAJA. The kernel driver generates synthetic inputs, checks for correctness and measures kernel run times. ", + "laborHours": 0.0, + "languages": [], + "name": "SW4 Curvilinear Kernels", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SW4CK", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-03", + "metadataLastUpdated": "2021-06-03" + }, + "description": "The Berkeley Quantum Synthesis Toolkit (BQSKit) is an optimizing quantum compiler and research vehicle that combines ideas from several projects at LBNL into one easily accessible and quickly extensible software package. The ideas in the QFAST, QSearch, LEAP, and QFactor software tools (all licensed through ipo.lbl.gov) all build upon one another. By combining these into one package, we create symbiotic interactions between the tools. This means better results, better throughput, less to maintain, and greater surface area to the public. Additionally, the BQSKit tool will create a research platform for future work here at LBNL.", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Quantum Synthesis Toolkit (BQSKit) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BQSKit/bqskit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "Dendro-GRCA is a parallel and distributed partial differential equation solver to perform large scale simulations in general relativistic computational astrophysics problems such as merging black holes and neutron stars and also many other problems in computational astrophysics. This toolkit, the Dendro library is a large scale distributed memory adaptive octree framework. Dendro consists of efficient parallel data structures and algorithms to perform finite element methods and finite difference methods on 2:1 balanced arbitrary adaptive octrees. ", + "laborHours": 0.0, + "languages": [], + "name": "Dendro-GRCA ver. 2.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Dendro-GRCA", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The holistic analysis and understanding of the latent (that is, not-directly observable) variables and patterns buried in large datasets is crucial for data-driven science, decision making and emergency response. Such exploratory analyses require devising unsupervised learning methods for data mining and extraction of the latent features, and non-negative matrix factorization (NMF) is one of the prominent such methods. % to extract interpretable latent features, with dimensionality reduction for data mining and blind source separation. NMF is based on compute-intense non-convex constrained minimization, which, for large datasets requires fast and distributed algorithms. However, current parallel implementations of NMF fail to estimate the number of latent features. In practice, identifying these features is both difficult and significant for pattern recognition and latent feature analysis, especially for large dense matrices. In this paper, we introduce a distributed NMF algorithm coupled with distributed custom clustering followed by a stability analysis on dense data, which we call DnMFk, to determine the number of latent variables. The results on synthetic data and the classical Swimmer data set demonstrate the accuracy of model determination while scaling nearly linearly across multiple processors for large data. Further, we employ DnMFk to determine the number of hidden features from a tera byte (TB) matrix.", + "laborHours": 0.0, + "languages": [], + "name": "DnMFk ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/DnMFkCPP", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "Identifying nucleic acid sequences of interest in complex metagenomic samples is often likened to “finding a needle in haystack”. While the polymerase chain reaction (PCR) can provide unparalleled, selective enrichment of known sequences from complex metagenomic samples, traditional (endpoint and real-time) PCR assays only provide “yes” or “no” results and, more significantly, can be prone to database “overfitting”. Overfitting occurs during the computational PCR primer design process, which typically uses all of the available target and near-neighbor sequences to predict highly specific PCR primers. Even though the number of known sequences continues to grow exponentially, we have still only sequenced a small fraction of the sequence diversity that occurs in nature. As a result, PCR primers that appear to offer “perfect” target discrimination (i.e. no false positives or negatives) fail when experimentally tested against unsequenced targets and/or near-neighbors. These assay failures can also become apparent when PCR primers are computationally screened against sequences that were not included in the original design process. As a result, PCR assays are said to suffer from “signature erosion”. A useful strategy to overcome signature erosion is to not rely on single, or even a handful, of target-specific PCR primers, but instead use hundreds or thousands of different primer pairs in a single “multiplexed” (or even megaplex) PCR. In much the same way that financial index funds can outperform hand-picked individual stocks, an ensemble of primer pairs can tolerate the failure of many individual pairs and still provide robust target enrichment. Next generation sequencing enables a digital readout of all of the sequences (or “amplicons”) that are amplified during a successful PCR. This amplicon sequence information can be used by bioinformatics analysis programs to identify the most likely organisms, reject closely-related near-neighbors and uncover phenotypic (e.g. antibiotic resistance) and forensic (e.g. informative SNP) markers.\n\nHowever, it is still challenging to design a large set of primer pairs for multiplex PCR. These challenges include selecting individual primers that do not form hairpins, homo-dimers or hetero-dimers, as these unwanted reactions reduce the assay sensitivity by reducing the effective concentration of the effected primers. Primers must bind to their intended target sequences with similar affinities and produce similar length amplicons to ensure uniform amplicon enrichment. Amplicons that form stable secondary structures should be avoided to prevent any “stalling” of the DNA polymerase that could reduce the enrichment level. In addition, unintended PCR amplification, caused by primers that happen to bind in close proximity and in the correct orientation to non-target sequences, must be avoided to maintain a sufficient signal to noise level for target enrichment and detection. Finally, it is essential to experimentally test a multiplex PCR design strategy. Experiments can uncover software bugs and design flaws that would otherwise reduce the level of target enrichment. In particular, experimentally measuring assay performance on both known (sequenced) and unknown (unsequenced) targets and backgrounds will help bound the expected target enrichment levels for deployed assays.", + "laborHours": 0.0, + "languages": [], + "name": "PCRamp", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Bioinformatics/PCRamp", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The developed software is an HPC cluster model and collaboration tool which provides the\nfollowing features:\n- Construction of HPC cluster nodes\n- Complex interaction and dependency between HPC cluster nodes\n- Construction of fully software stacks (OS, data base, scheduler, libraries) internal to the\ncluster environment\n- Cluster nodes may be implemented via arbitrary providers (virtual machines, containers)\n- Complex interaction and dependency between HPC node’s software stacks\n- Verification test framework between nodes and their software stacks\nThis is being used for active projects. This is intended to be used to provide consistent, coordinated scenario measurements,\nconfiguration and collaboration among the DoE TriLabs and other USG HPC sites in the\nforeseeable future, to accomplish DoE HPC CCE goals.", + "laborHours": 0.0, + "languages": [], + "name": "HPC Cluster Modeler and CoLaboration Platform", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/hpc-collab", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The capacity for big data manipulation and analysis has greatly evolved in the modern digital world due to varying sources such as social networks, medical scans, surveillance and monitoring systems, etc. Data mining and deep learning techniques are currently being utilized to understand the latent representation of the data using unsupervised approaches and also are known for their fast processing time. Even though these frameworks exhibit superior performance in supervised learning applications, however they are restricted in their algorithmic complexity and prove ineffective in computing the optimal latent representations for unsupervised applications. Non-Negative Matrix Factorization (NMF) techniques have proven effective in finding the most complex latent representations applied to a wide field of applications involving dimension reduction techniques applied to the fields of topic modeling, text mining, background separation in image/video datasets, anomaly detections and cancer detection. However NMF needs apriori information about the latent dimensionality. PyDnNMFk has NMF coupled with custom clustering that enables the recognition of the unknown latent dimensionality of the data along with the ability for an accurate reconstruction of the Factors. As the data size grows, the bottleneck due to the hardware computing/memory abilities grows too. Even though shared-memory based multiprocessing NMF frameworks perform faster compared to single core implementations, still the latency gives rise to the long wait times which might be an issue for time constraint applications. This raises the need for an optimal high performance implementation of NMF where the distributed memory and inter-process communication across massively parallel cores across multiple nodes tends to address the challenge. Hence we also provide Distributed implementation of NMFk, which can effectively factorize with identifying the latent dimensionality on exa-scale data. The implementations include a shared-memory multiprocessing based k estimation( pynNMFk), distributed memory inter-processor implementation(pyDnNMFk) and GPU factorization based implementation(pyGnNMFk) . The factor updates are based on Forbenius norm/KL divergence minimization criteria. ", + "laborHours": 0.0, + "languages": [], + "name": "pyDnMFk (Python Distributed Non Negative Matrix Factorization with determination of hidden features)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyDNMFk", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "PIDOTS is a software application for studying an alternative iterative and parallel solution technique for linear, deterministic neutral-particle radiation transport. The code solves a very generic, simplified—i.e., dumb—form of the system of relevant system of equations. PIDOTS is less capable than the open source proxy application SNAP. Given limitations introduced by the equations as well as limitations in data and meshing, PIDOTS is incapable of performing real physics simulations or addressing actual physics questions for transport. Instead of using transport mesh sweeps that we see in many production codes (and SNAP), PIDOTS uses a Jacobi or Jacobi-like iterative scheme that updates the flux information between adjacent, decoupled subdomains. By completely decoupling subdomains, PIDOTS permits massively large-scale decomposition (i.e., tens of thousands of processes or more) of the spatial mesh, making it an interesting alternative to mesh sweeps, worth continued studying and development. ", + "laborHours": 0.0, + "languages": [], + "name": "PIDOTS: Parallel Integral Discrete Ordinates Transport Solver v1.xx", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pidots", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "This code contains an implementation of Micromorphic continuum mechanics in the style of Eringen and Suhubi [1] developed during Nathan Miller's PhD thesis under the supervision of Richard Regueiro. The code is written in a finite deformation framework and contains micromoprhic constitutive models which can be used to simulate various solid mechanics problems. Interfaces to Abaqus and the Idaho National Laboratory code MOOSE are included as a part of the functionality with the possibility of extending to additional codes in the future.\n\n[1] A.Cemal Eringen, E.S. Suhubi, \"Nonlinear theory of simple micro-elastic solids—I\", International Journal of Engineering Science, Volume 2, Issue 2, 1964, Pages 189-20", + "laborHours": 0.0, + "languages": [], + "name": "Tardigrade", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/tardigrade", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The Programming Repository for In Situ Modeling (PRISM) is a set of tools for fitting statistics and machine learning models to simulation data inside the simulations as they are running. By fitting models inside running simulations, PRISM can be used to analyze simulation data that is otherwise inaccessible because of I/O and storage bottlenecks associated with exascale and other future high performance computing architectures. The tools are designed to implement a wide variety of data analyses with an emphasis on spatiotemporal hierarchical Bayesian models. PRISM is efficient, scalable, and streaming with estimation based on variational inference, advanced Monte Carlo techniques, and fast optimization methods. The core modeling components aid this goal by imposing sparsity and approximate inference wherever possible. These components are written in Julia, a high-level programming language designed for high performance. PRISM also contains tools for interfacing with large-scale scientific simulations written in Fortran and C/C++. This layer of abstraction allows the data scientist to construct analysis models in Julia without concern for the implementation details of the simulation capability. With these components, PRISM can be used to unlock the full scientific potential of next-generation HPC simulations.", + "laborHours": 0.0, + "languages": [], + "name": "Programming Repository for In Situ Modeling", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PRISM", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The multimat_1drdg code is a one-dimensional code which is used to prototype the numerical method published in “Pandare, A. K., Waltz, J., & Bakosi, J. (2019). A Reconstructed Discontinuous Galerkin method for Multi-Material Hydrodynamics with Sharp-Interfaces. International Journal for Numerical Methods in Fluids.” It solves the multi-fluid dynamics equations (arbitrary number of fluids) using the third-order Reconstructed Discontinuous Galerkin (rDG) method. A few academic test problems from previous published literature are included as initial setup options.", + "laborHours": 0.0, + "languages": [], + "name": "multimat_1drdg", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/multimat_1drdg", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The Automated Testing System (ATS) is an open-source, Python-based tool for automating the running of tests of an application across a broad range of high performance computers.", + "laborHours": 0.0, + "languages": [], + "name": "Automated Testing System", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ATS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "Dante is a probabilistic flu forecasting model. The methodology was developed to produce real-time flu forecasts in the U.S. The software to execute Dante is a collection of R scripts and JAGS files. It takes publicly available data from the US Centers for Disease Control and Prevention (CDC) as input. It runs R scrips and JAGS code to produce model output. ", + "laborHours": 0.0, + "languages": [], + "name": "Dante", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Dante", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2022-09-15" + }, + "description": "FIDUCIA: Filtered Diode Unfolder (using) Cubic-spline Algorithm Fiducia is a DANTE signal deconvolver based on the cubic splines method. Given time-resolved DANTE data across a number of K-edge filtered channels, this code can produce time-resolved x-ray spectra with coarse spectral resolution, as well as time-resolved x-ray flux and radiation temperature for a given source. The main application for this code is for diagnosing and constraining hohlraum drives on high energy density plasma physics experiments at the OMEGA Laser Facility and the National Ignition Facility. Spectral unfolds are created by assuming each DANTE channel provides information on the x-ray intensity in a particular photon energy band defined by its K-edge filter. The combination of multiple DANTE channels sensitive to different photon energies then provides coarse spectral information. The overall x-ray spectrum is approximated as a series of cubic splines corresponding to each energy band, which reduces the process of unfolding x-ray spectra from time-resolved DANTE channel data to a series of matrix operations folded with the DANTE response functions. By reducing the spectral deconvolution to a series of matrix operations, DANTE analysis is accelerated to the point where it could be feasibly used for on-the-fly characterization of hohlraum drives during experiments, with no additional assumptions about the shape of the x-ray spectrum.", + "laborHours": 0.0, + "languages": [], + "name": "Fiducia", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/fiducia", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-07" + }, + "description": "As high-performance computing reaches exascale, data analysis and visualization will need to shift from a predominantly post hoc approach to an in situ paradigm – running while the simulation is running. Memory and I/O bandwidth growth is expected to lag behind concurrency growth by orders of magnitude. This will require new in situ algorithms and tools that can leverage emerging accelerator technology to sufficiently decrease the volume of data moved on the machine and amount saved to persistent storage. As part of the Department of Energy’s Exascale Computing Project (ECP), the ALPINE and team at Los Alamos National Laboratory (LANL) is collaboratively developing open source solutions with DOE leadership laboratories, universities, and industry partners to address these challenges. The ECP ALPINE project is developing filters and algorithms to support the in situ analysis and visualization goals of ECP application codes. Prototypes of the filters and algorithms are written in C++ and Python while production versions are written in VTK or VTK-m. These filters and algorithms will be available in commonly used visualization tools and infrastructures such as ParaView, VisIt, and Ascent and will be deployed on exascale machines at the DOE Leadership Computing Facilities. The primary users of these projects will be both at Los Alamos National Laboratory and will include application codes at institutions across the Exascale Computing Project (https://www.exascaleproject.org/).", + "laborHours": 0.0, + "languages": [], + "name": "ECP Collaborative Software Development for In Situ Data Analysis and Visualization", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/alpine-lanl", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2022-01-11" + }, + "description": "Python-based Sampling Toolkit (PySTK) is a set of python functions developed for efficient data reduction via sampling for large-scale time-varying complex scientific datasets. PySTK provides a range of capabilities: starting from naive random sampling of data to a more sophisticated data-drives feature-preserving sampling for regular grid datasets. PySTK further includes the option of visualization the samples using open-source library Visualization ToolKit (VTK), reconstruction from the samples, and fast sample-based query mechanism for scientific datasets. PySTK is designed to be efficient yet extendable, as it strives to handle large datasets using primarily the Numpy-based operations. This toolkit uses the python-based multi-threading for effective use of available resources. Not only the big supercomputers, modern day laptops and desktops are used for data analysis purposes by the domain experts and data analysts. PySTK seamlessly enables the use of such hardware to handle big data sets. PySTK can be used to explore large datasets generated by HPC simulations with intelligent sampling algorithms and exploit the existing hardware for efficient data analysis. Aside from the sampling code, PySTK will further contain the related documentation, test/demo cases, details of its build system, unit test harness, and a scholarly bibliography.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "PySTK: Python-Based Sampling Toolkit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-06-07", + "metadataLastUpdated": "2024-10-25" + }, + "description": "The windfarm operations and maintenance cost-benefit analysis tool (WOMBAT) is software to simulate the operations and maintenance phase of either onshore or offshore windfarms. WOMBAT is a medium-fidelity tool that is designed to model turbine, cable, and substation failures at the subassembly level, but is flexible enough that individual component or asset-level modeling can also be performed. WOMBAT enables users to model technological improvements, the use of a wide range of service equipment from drone repairs and remote resets to heavy lift vessels and crawler cranes, to analyze cost trends with varying trade-offs in conjunction with energy production, availability and a growing range of metrics. \n\nThis library provides a tool to simulate the operation and maintenance phase (O&M) of distributed, land-based, and offshore windfarms using a discrete event simulation framework.\n\nWOMBAT is written around the SimPy discrete event simulation framework. Additionally, this is supported using a flexible and modular object-oriented code base, which enables the modeling of arbitrarily large (or small) windfarms with as many or as few failure and maintenance tasks that can be encoded.\n\nPlease note that this is still heavily under development, so you may find some functionality to be incomplete at the current moment, but rest assured the functionality is expanding. With that said, it would be greatly appreciated for issues or PRs to be submitted for any improvements at all, from fixing typos (guaranteed to be a few) to features to testing.\n\nAlso available at: https://pypi.org/project/wombat/", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "WOMBAT (Windfarm Operations and Maintenance cost-Benefit Analysis Tool) WISDEM® [SWR-21-68]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/WOMBAT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "V0.9.3" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-06-07", + "metadataLastUpdated": "2022-09-13" + }, + "description": "KiteFAST is a simulator for airborne wind energy systems based on NREL's OpenFAST whole turbine simulator. KiteFAST is a multi-physics engineering tool for modeling the coupled aero-servo-elastic dynamics of airborne wind energy systems i.e. a wind-energy kite. The engineering model is like NREL's OpenFAST tool for land-based or offshore horizontal-axis wind turbines atop towers, in that KiteFAST models the important physical phenomena and system couplings, including the wind/aerodynamic excitation and full-system dynamics response (fuselage, wings, tail, stabilizers, pylons, nacelles, rotors, tether, ground station, control surfaces, and controller) under both normal (for fatigue) and extreme (for ultimate) loading conditions. The configuration of the wind-energy kite is assumed to have one fuselage; two wings (starboard, port) attached to the fuselage; one vertical stabilizer attached the fuselage; two horizontal stabilizers (starboard, port) attached to the vertical stabilizer; one or more pylons per wing, each with two rotors (top, bottom); one ground-station-fixed tether with a bridal connection to the wings, and nominal circular motion of the energy kite in the port (left) direction. The general configuration of the control surfaces assumes one or more flaps per wing, two rudders on the vertical stabilizer, two elevators per horizontal stabilizer, and rotors with variable speed and rotor-collective blade pitch. KiteFAST was developed from (1) the existing MBDyn open-source multi-body dynamics code; (2) the existing/modified OpenFAST modules NWTC Subroutine Library, AirfoilInfo, InflowWind, MoorDyn, and TurbSim; and (3) new source code for a) generating MBDyn models of the energy kite (KiteMBDyn Preprocessor), b) computing quasi-steady energy-kite aerodynamics (KiteAeroDyn, KiteAeroDyn Driver, KiteVSM, ActuatorDisk), c) interfacing an energy-kite controller, and d) coupling the various KiteFAST modules together (KiteFASTMBD).", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Fortran", + "Python", + "Jupyter Notebook", + "Roff", + "C", + "C++" + ], + "name": "KiteFAST", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/OpenFAST/KiteFAST", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-10", + "metadataLastUpdated": "2021-06-11" + }, + "description": "This software package contains a simple calculator that can be used to estimate savings from implementing a retrofit of HVAC controls to ASHRAE Guideline 36 in a multi-zone office building. Implemented in Excel, the calculator has a user-interface front-end to configure parameters of the case study, such as location, building size, and existing control strategies, and a back-end containing results from a large number of pre-run annual energy simulations. The software package also contains the simulation models and associated pre- and post-processing scripts to generate these results.", + "laborHours": 0.0, + "languages": [], + "name": "Guideline 36 Savings Calculator v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/G36SavingsCalculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-10", + "metadataLastUpdated": "2021-06-11" + }, + "description": "We have developed a series of compact RF mixing boards by integrating I/Q quadrature mixing, IF(intermediate frequency)/LO(local oscillator)/RF power level adjustments, and DC (direct current) bias fine tuning on a 40 mm × 80 mm 4-layer PCB (printed circuit board) board with EMI (electromagnetic interference) shielding.", + "laborHours": 0.0, + "languages": [], + "name": "RF mixing modules for superconducting qubit room temperature control systems v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/LBL-QubiC/rfmixingmodules", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-10", + "metadataLastUpdated": "2021-06-11" + }, + "description": "In short, the GENESPACE pipeline conducts analysis of orthology networks, constrained within syntenic regions. Since analyses are limited to local tests conducted within syntenic blocks, GENESPACE is agnostic to ploidy, duplicated regions, inversions or other whole-genome chromosomal complexities that are common across many evolutionary lineages. This advantage allows for evolutionary tests in polyploids (e.g. switchgrass, manuscript in review), species with ancient, but retained whole-genome duplications (e.g. pecan, manuscript in prep), high levels of tandem array proliferation (e.g. eukalypts, manuscript in review) and many other factors that can confound comparative genomic analyses. The major advances of GENESPACE are three-fold: First, this is the first R package to integrate visualization and analysis of large-scale comparative genomics. R, which offers a high-level environment for graphical and statistical exploration of data, is often speed- and memory-limited and not used for computationally intensive tasks such as comparative genomics. The highly efficient C++ scripts used in GENESPACE (via data.table) permit a much faster and computationally lightweight implementation of comparative genomics than is currently available. Second, the pipeline itself is novel. To the best of our knowledge, no other program accomplishes synteny-constrained and ploidy-agnostic comparative genomics. Since nearly all plants and many animals have a history of whole-genome duplications, this is a major and necessary advance to the field. Third, GENESPACE offers high-level and intuitive multi-genome graphical outputs. The dotplots and 'riparian' plots produced herein, which are produced entirely through original R code, are publication-ready and easily customizable.", + "laborHours": 0.0, + "languages": [], + "name": "GENESPACE R Package (GENESPACE) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/plant/genespace-r", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-15", + "metadataLastUpdated": "2021-06-16" + }, + "description": "Heliostat Aimpoint and Layout Optimization Software (HALOS) is an open-source software package that allows users to explore solar field layout optimization, aimpoint strategy optimization, and performance characterization of concentrating solar power tower plants. Users interface with the tool through python, and results are reported in time series tables, plots, runtime logs, and flat-file outputs. Users choose from a list of variables such as tower height, receiver capacity, flux limits, design-point irradiance, etc., and specify information about the system using a small collection of flat files. The software can then optimize the specified variables (e.g., aimpoints for each heliostat) to maximize the thermal energy delivered to the receiver while adhering to flux limits. HALOS is implemented to be flexible with respect to flux characterization methods, but includes a direct connection to NREL's SolarPILOT™ software via its python API so that users can utilize high-fidelity flux simulation methods that have already been developed.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HALOS (Heliostat Aimpoint and Layout Optimization Software)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HALOS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-16", + "metadataLastUpdated": "2021-06-17" + }, + "description": "OSIF is a tool that allows the user to easily fit electrochemical impedance spectra of proton exchange membrane fuel cells to a commonly accepted equivalent circuit model. The fitted parameters provide insight into the physical properties of the cell which allow the user to support experimental hypotheses.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "OSIF (Open Source Impedance Fitter)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OSIF", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This model links global demand and supply of three intertwined materials cobalt (Co), copper (Cu) and nickel (Ni) in a simulation market model with explicit consideration of electric vehicle (EV) and battery scenarios. By incorporating feedback between supply, demand, prices and capacity expansion, we quantify realistic production scenarios for both primary (mining) and secondary sources (recycling). Furthermore, to understand the magnitude of material (battery) demand from the in-use EV stock, we also consider demand to replace end-of-life (EOL) batteries. We seek to answer the following questions: 1) How will production from both primary and secondary sources react to various EV deployment scenarios and battery-chemistry combinations? 2) How much supply might promising/potential new (mining) projects contribute to supply? 3) What is the impact of reducing battery lifetime? 4) If recycling rates are increased for all 3 materials, what are the implications for Co production?", + "laborHours": 0.0, + "languages": [], + "name": "Cobalt-copper-nickel Supply Chains Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/CoCuNi", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "The finite difference optimizer (FIDO), is a tool for optimizing finite difference discretization stencils for stability. It supports uniform Cartesian meshes as well as cut-cell meshes. FIDO is a driver program with a configurable objective function that is meant to be coupled with a solver.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "FIDO", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "SEPIA (Simulation-Enabled Prediction, Inference, and Analysis) is a Python port, with user interface enhancements, of GPMSA software. GPMSA is released as LACC-06-079. \nThe software performs analysis and uncertainty quantification, by comparing experimental observations to ensembles of computer simulations. \nThis software is based on the methodology of Higdon et.al 2008, https://doi.org/10.1198/016214507000000888 .", + "laborHours": 0.0, + "languages": [], + "name": "SEPIA (Simulation-Enabled Prediction, Inference, and Analysis)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SEPIA", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "Software for converting data to DNA. The purpose of the software is to convert binary data file(s) into a collection of DNA oligo descriptions that can be synthesized and provide long-term data storage. The software is designed to target the unique properties of DNA synthesis and sequencing and include error correction codes that can recover the data despite the high error rates of the current DNA state of the art techniques.", + "laborHours": 0.0, + "languages": [], + "name": "ACOMA (Formerly LADNAC)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/adscodex", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-28" + }, + "description": "Electric grid transformation with the proliferation of distributed energy resources (DER), such as solar photovoltaic (PV), wind, advanced energy storage technologies, and electric vehicles, and the growing use of communication technologies in both transmission and distribution systems are increasing the need to capture the interactions among these systems. Advanced modeling, control, and simulation tools that can perform co-simulation of electric power systems with other domains become indispensable to accurately model these interactions. To address this need, we have developed a codebase that integrates an electric power distribution system simulator, DER models, and DER controls. The codebase is based on OpenDSS, a distribution system simulator, and an existing open source co-simulation framework called HELICS. The contribution and uniqueness of the proposed codebase is that it tailors the generic HELICS framework specifically for distribution grid-related applications. The codebase includes an OpenDSS wrapper that controls the simulation, implements advanced DER controls, and extracts power flows, voltages, and other power system element information from the the distribution network modeled in OpenDSS. Sample HELICS federates, including a federate for OpenDSS, are provided that can communicate messages through the HELICS interface. Sample federates can be modified and additional HELICS federates can be added by the user depending on their use case requirements. SEE ALSO: https://github.com/NREL/dss-cosim", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "OpenDSS-wrapper (Distribution System Co-simulator with Distributed Energy Resource Controls)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenDSS-wrapper", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "VPIC is a general-purpose Particle-In-Cell (PIC) simulation code for modeling multi-species kinetic plasmas in one, two, or three spatial dimensions. VPIC can solve equations of motion for different plasma species using kinetic or fluid descriptions. To solve for the kinetic species, VPIC employs a variety of explicit and implicit time-stepping schemes to update charged particle positions and velocities. In contrast, the fluid species is advanced in time by solving a number of fluid moment equations on a spatial grid using finite-difference methods. The electromagnetic fields are also solved on a spatial grid using either the full Maxwell equations, or a low frequency quasi-neutral approximation that uses an Ohm's law for the electric field. To couple the kinetic particle quantities with the grid-based field and fluid-moment descriptions requires that electromagnetic fields are interpolated from spatial grid points to the particle positions, and current densities are collected from the particles onto the spatial grid points. The VPIC code has been optimized for modern computing architectures and uses Message Passing Interface (MPI) calls for multi-node execution, in addition to exploiting node-level data-parallelism. The current feature set for VPIC includes a flexible input deck format capable of treating a wide variety of problems. These include: the ability to treat electromagnetic materials (scalar and tensor dielectric, conductivity, and diamagnetic material properties); multiple emission models, including user-configurable models; arbitrary, user-configurable boundary conditions for particles and fields; user-definable simulation units; a suite of \"standard\" diagnostics, as well as user-configurable diagnostics; a Monte-Carlo treatment of collisional processes capable of treating binary and unary collisions and secondary particle generation; and, flexible checkpoint-restart semantics enabling VPIC checkpoint files to be read as input for subsequent simulations. While the common use cases for VPIC employ low-order particles on rectilinear meshes, a framework exists to treat higher-order particles and curvilinear meshes, as well as more advanced field solvers.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "VPIC", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "Singular value decomposition (SVD) is a matrix factorization widely used for dimensionality reduction, data analytics, information retrieval and unsupervised learning. In the SVD's applications for big-data, usually, only the singular values are calculated. However, new methods, such as the tensor network factorization, require an accurate retrieval of a substantial number of singular vectors for truncated SVD. Also, many real-world datasets are too big to fit directly into the memory, which mandates the development of out-of-memory algorithms that work with data that is primarily on the disk. Here, building upon a previous work, we present a method for computation of the singular vectors of matrices that cannot fit into the memory. We also describe ways for reducing the communication during the computation of the left and right reflectors, needed to compute the singular vectors, and introduce a method for reducing the block-sizes, needed to hide communication on parallel file systems.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Out-of-memory SVD", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "This disclosure is related to code contributions to the LLVM compiler infrastructure (see http://llvm.org). This includes all the projects encompassed in LLVM as well as a new addition that supports the Fortran programming language. In quick summary, the LLVM Project is a collection of modular and reusable compiler and toolchain technologies. This includes C/C++, Go, runtime systems for OpenMP, and various other supporting pieces such as a debugger and linker. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "LLVM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "This disclosure covers LANL's contributions of source code to the already open source Legion Programming System. This covers example codes, contributions to the system's base source code, new features, bug fixes, associated documentation, and benchmarks. \n\nLegion is a data-centric parallel programming system for writing portable high performance programs targeted at distributed heterogeneous architectures. Legion presents abstractions which allow programmers to describe properties of program data (e.g. independence, locality). By making the Legion programming system aware of the structure of program data, it can automate many of the tedious tasks programmers currently face, including correctly extracting task- and data-level parallelism and moving data around complex memory hierarchies. A novel mapping interface provides explicit programmer controlled placement of data in the memory hierarchy and assignment of tasks to processors in a way that is orthogonal to correctness, thereby enabling easy porting and tuning of Legion applications to new architectures. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "The Legion Programming System", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "The Stable, High-Order, Cut-Cell Solver (SHOCCS), solves a variety of partial differential equations (PDE's) involving complicated bodies on a simple Cartesian mesh through the use of a novel cut-cell approach.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "SHOCCS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "This is a one-temperature diffusion code designed to model supernova explosions.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Simple Supernova Light-Curve Code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "lvPortDriver and the lvPortDriver virtual library are functions that enable LabVIEW code to run an EPICS (Experimental Physics and\nIndustrial Control System) IOC (Input/Output Controller), and communicate with it.\nThe EPICS records interface just as they would with any other asynPortDriver device.\nlvPortDriver is an asynPortDriver class (asynPortDriver is written by Mark Rivers, University of Chicago) that stores parameters in the parameter library (inherits from the base class). Arrays functions have been overridden to store data in LabVIEW's (LabVIEW is developed by National Instruments) native format.\nC wrappers permit LabVIEW to call the C++ code necessary to read and write parameters, and to be notified of changes in parameters by asyn. This notification is achieved though a user event that provides LabVIEW with the new value and status.\nA LabVIEW virtual library includes VIs that call these wrapper functions. The LabVIEW code is responsible for initializing the driver, and creating all the parameters that will be used. Parameter names are stored as variant properties, so their indicies can be looked-up via an O(log(N)) mechanism.\nThe example code included consists of a queue-driven state machine that does a simulated diagnostic measurement (does a specified number of waits for a specified time, and records the actual time between steps). A caQtDM screen is used to control the example measurement and plot the results by interfacing via an EPICS IOC with the included database.", + "laborHours": 0.0, + "languages": [], + "name": "lvPortDriver 1.X", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/lvPortDriver", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "ELEMENTS is a C++ library of mathematical functions and computer routines to support a broad range of numerical methods on diverse element types including: a) serendipity linear, quadratic, and cubic elements; b) arbitrary order tensor-product space elements b) high-order spectral elements; and d) a linear space-time element. The ELEMENTS library can be used for research and development of both continuous and discontinuous finite element methods for solving a diverse range of partial differential equations. The library has functions for calculating quantities that are commonly used in continuous and discontinuous finite element methods such as the gradient of a basis function, the Jacobi matrix, the inverse Jacobi matrix, the determinant of the Jacobi matrix, and a physical position inside the element, to name a few examples. The library supports both Gauss–Legendre and Gauss–Lobatto quadrature rules up to 8 quadrature points in each coordinate direction. The library has a mesh class designed for unstructured meshes and supports sub-cell decomposition that is used with advanced discontinuous numerical methods. Novel routines exist in the mesh class for connectivity across various mesh entities including: nodes, vertices, quadrature points, surfaces, elements, subcells, subcell-corners, and subcell-faces. These routines have simple interfaces and are cleverly designed for computational performance. The mesh class is designed to minimize memory usage.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "ELEMENTS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "We have developed a mechanistic model of leaf utilization of nitrogen for assimilation (LUNA V1.0) to predict the photosynthetic capacity at the global scale under different environmental conditions. We adopt an optimality hypothesis to nitrogen allocation among light capture, electron transport, carboxylation, and respiration. The LUNA model is able to reasonably capture the measured spatial and temporal patterns of the photosynthetic capacity as it explains ~55% of the global variation in the observed values of maximum carboxylation rate (Vc,max25) and ~65% of the variation in the observed values of maximum electron transport rate (Jmax25).", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "LUNA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "The Scalable Unusual Message Detector (SUD) is a scalable software program for finding anomalous log messages on a single machine or cluster in near real time. This program is able to detect unusual messages by turning the text into sets of ngrams, which are multiple sets of tokens/words per message, and comparing incoming messages with the saved ngrams. A set of rules are used for determining if the saved ngrams match an incoming message based on the size of the incoming message. This tools is intended to final unusual/anomalous messages to find critical events that system administrators are not expecting. Currently the algorithms/methods are being used on HPC’s scalalble log analysis machine. Work is being done to port the algorithms/methods to a standalone tool.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Scalable Unusual Syslog Message Detector", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "The Joint Genome Institute (JGI) has developed JGI Analysis Workflow Service (JAWS) as a framework to run computational workflows. The purpose of JAWS is to improve the reusability and robustness of bioinformatic (or any) workflows in evolving and/or diverse high-performance computing (HPC), large cluster, and cloud environments. JAWS moves data and code to user-specified compute resources, executes computation, and returns results. JAWS implements Cromwell, developed at the Broad Institute, to make use of Workflow Description Language (WDL). Additionally, JAWS implements containers (compatible with Docker, Shifter, and Singularity) to ensure use of well-defined compute environments and workflow task codebases. To run the compute tasks, JAWS provides the JGI Task Manager (JTM), a compute task farming tool that manages workers on compute nodes and executes tasks on them.", + "laborHours": 0.0, + "languages": [], + "name": "Joint Genome Institute Analysis Workflow Service (JAWS) v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGI-Bioinformatics/jaws.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "The Catch2 library is an open-source unit-testing framework available on GitHub (https://github.com/catchorg/Catch2). The Catch2 unit-testing framework currently lacks support for handling C-style assertions via the \"assert\" macro. The source code being disclosed adds the ability to verify that C-style assertions are caught when expected and registered with the Catch2 framework by making direct additions to the Catch2 software. This source code will be contributed back to the Catch2 project on Github and copyright will need to cover any alterations required by the project owners on Github including alterations to source code, documentation, testing, etc. Ideally, the changes made herein will be released under the Boost Software License Version 1.0.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Catch2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/catchorg/Catch2/blob/devel/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-12" + }, + "description": "Truchas-PBF is a specialization of LANL's open source Truchas software (LA-CC-15-097) that is designed to simulate the powder bed fusion (PBF) additive manufacturing process for metal materials. The software uses physics-based continuum models of heat conduction, phase change, fluid flow, and solid mechanics to simulate the detailed dynamics of the traveling liquid melt pool to predict the extent of the fusion zone, solidification microstructure, and resulting residual stress in the fused material.", + "laborHours": 0.0, + "languages": [], + "name": "Truchas-PBF", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/truchas-pbf/truchas-pbf", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "The software creates the Hangul Fonts data set.The Hangul Fonts Datasets consists of all possible blocks for each font along with a set of labels and features for each block which are common across all fonts. We provide scripts to render each block and font into an image and store them together in an HDF5 file for each font and fontsize specified. Each font has 11,172 possible blocks and we have curated 35 fonts for a total of 391,020 possible images. The spoken consonants and vowel correspond to a set of \"initial\", \"medial\", and \"final\" labels for each block with 19, 21, and 28 classes respectively. In addition, each block can also be assigned a hierarchy label based on the block geometry. Finally, the individual glyphs (atoms) are composed across the initial, medial, and final locations along with potential scalings, translations, or rotations. These features of the data set make it uniquely positioned in the deep representation learning field because of its compositionally and hierarchical organization, while retaining diverse types of variation in the realizations.", + "laborHours": 0.0, + "languages": [], + "name": "HangulFonts v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BouchardLab/HangulFontsDatasetGenerator.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This license is for a computer-science focused subset of the XCP-3 developed shared component libraries (SHACL), referred to as SHACL Utilities. The SHACL Utilities product is a collection of repositories developed to help XCP-3 developers quickly write maintainable and efficient computational physics software. This collection of libraries provides software abstractions, algorithms, and tools based on modern software practices and design idioms, while supporting interfaces to other programming languages when required by production codes. The libraries are semi-independent repositories and are developed with an emphasis on performance and sharing code between applications.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Shared Component Library - Utilities", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "As HPC physics simulations grow ever larger in size, accessing the data generated by them becomes an increasingly difficult challenge. Searching for individual pieces of data or ranges of data in storage takes significant amounts of time that could be better spent elsewhere. In order to reduce the cost of pulling data from storage, we have developed the Hexadimensional Hashing Indexing Middleware (HXHIM). HXHIM is a distributed key-value store library written in C++ with a C api with networking performed by MPI and Thallium, and with LevelDB as the storage backend. Data is stored as Subject-Predicate-Object triples that can be searched for in any combination and can return ranges of data instead of just a single data point, allowing for fast, parallel extraction of large amounts of data from storage in significantly less time than existing methods are able to obtain the same data.", + "laborHours": 0.0, + "languages": [], + "name": "HXHIM: The Hexa-dimensional Hashing Indexing Middleware", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/hxhim", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "This software is an open-source Python library that provides a collection of advanced algorithms to address computational imaging and inverse problems arising in the analysis of scientific data. The main goal is to deliver a unified mathematical formulation that applies state-of-the art methods developed within the computational imaging community to inversion problems. This includes computational algorithms that are able to reconstruct the quantities of interest given specific collections of experimental data and enable the inversion even for cases where there are not enough measurements to uniquely specify the solution (ill-posed problems). The core of the library consists of optimization algorithms with the flexibility to incorporate explicit analytical priors, explicit regularization constraints, as well as implicit regularization models which can be learned offline via machine learning methods. The library will interface with well-known Python packages providing support for forward models relevant to tomographic imaging and coherent diffraction imaging, as well as Python libraries for machine learning. Supporting visualization and analysis of results will also be provided. The software will include thorough documentation and extensive application examples.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Scientific Computational Imaging COde (SCICO)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Los Alamos National Laboratory has played key roles in the development of ParaView and the Visualization Toolkit (VTK). James Ahrens (Director, ISTI & Senior Staff Scientist, Data Science at Scale, CCS-7) is the founder and design lead of ParaView. With over a million downloads, ParaView is one of the leading data analysis and visualization applications and is widely used by scientific users within the Department of Energy Office of Science (SC) and the DOE National Nuclear Security Agency (NNSA). VTK is an open-source software visualization library based on C++ and includes interface layers for Python and Java. ParaView extensively uses the VTK libraries for its graphics and analysis. First open-sourced under LA_CC Number 99_44, this work has been continuously funded over the years under Department of Energy contracts. The goal of this software project is to continue the collaborative development of open-source general use case contributions to ParaView and VTK by LANL researchers. The developed software will provide open-source computer science algorithms, interfaces, filters, visualization approaches, and data analysis modules that will be merged into ParaView and VTK for general use by ParaView and VTK users. The primary users of these projects will include institutional users at Los Alamos National Laboratory, institutional users across the DOE complex and scientific users of VTK and ParaView as open-source tools for data analysis and visualization.", + "laborHours": 0.0, + "languages": [], + "name": "ParaView-VTK Collaborative Software Development for Data Analysis and Visualization", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/dav-pv-vtk", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "Software is used to apply digital signatures to pdf drawings. The signatures applied must be consistent in role, size and placement on the pdf drawings. The software provides the ability to process these signatures in a batch mode, signing multiple pdf drawings, selectable by either folder and/or file selections.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Sign Drawings (Electronic Signatures)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Ethon is a research code that implements well-known hydrodynamics methods (finite-volume and Discontinuous Galerkin) to solve the compressible Euler equations with a simple ideal gas equation of state and no additional physics using a block-based adaptive mesh refinement (AMR) infrastructure. Ethon uses the publicly available Kokkos library for performance portability between CPUs and GPUs. The purpose of Ethon is to evaluate the hydrodynamics methods using block-based AMR on different computing infrastructures.", + "laborHours": 0.0, + "languages": [], + "name": "Ethon", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ethon", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-13" + }, + "description": "High Magnetic Field Science Toolset is designed to acquire and analyze experimental data at high magnetic fields. The software toolset is developed at Los Alamos National Laboratory for the National High Magnetic Field Laboratory user program within the scope of the High Magnetic Field Science Designated Unclassified Subject Area.", + "homepageURL": "https://github.com/ffb-LANL/High-Magnetic-Field-Science-Toolset", + "laborHours": 0.0, + "languages": [], + "name": "High Magnetic Field Science Toolset", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ffb-LANL/High-Magnetic-Field-Science-Toolset", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "v1.5" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-02" + }, + "description": "We develop a lightweight, easy-to-use plotting package based on Python and matplotlib for scalar data visualization. The package contains eight plotting functions that can efficiently and conveniently render one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) regular-grid scalar data into publication-quality figures of various formats. These plotting functions include plotting 1D scalar data as a curve or a set of colored scatter points, showing 2D regular-grid scalar data as an image, wiggles, or contours, and displaying 3D regular-grid scalar data as a volume or three orthogonal slices in the image or contour form. We develop this package to facilitate quick rendering of 1D, 2D and 3D scalar data into visually decent forms with simple commands and options. The package is also capable of rendering various fonts, subscripts, superscripts, and mathematical symbols on plots in a consistent manner. Example plots demonstrate the efficiency, convenience, and versatility of our plotting package in generating high-quality plots. We make our plotting package open-source at GitHub, a United States-based global company that provides hosting for software development version control.", + "laborHours": 0.0, + "languages": [], + "name": "Pymplot: An open-source, lightweight plotting package based on Python and matplotlib", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pymplot", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-28" + }, + "description": "fuelcell is a Python package designed to standardize and streamline the analysis of electrochemical data. This package includes modules for data processing and data visualization, as well as a graphical user interface (GUI) for interactive use.", + "laborHours": 0.0, + "languages": [], + "name": "fuelcell: A Python package and graphical user interface for electrochemical data analysis (fuelcell) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/samaygarg/fuelcell.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-21" + }, + "description": "NREL's RTS Data Vis App contains the following sub-projects: (1) Conditioner: A tool to resample high-rate data from the relay for low-rate visualization and (2) Chart: A tool to plot the data from the relay, including a specialized copy of the Conditioner. The Conditioner is a command-line tool for reading ADMS data from ZMQ, resampling, and exporting over a websocket. The Chart is an example of a charting tool for ADMS applications, using a ZMQ message bus.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Real Time Streaming Data visualization tooling (RTS Data Vis App)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rts-vis-app", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "From a single data description file, this package generates a simple but complete RESTful web interface to a relational database, in the form of containers that run in a Docker environment. This initial version produces containers that are intended for use on the NERSC Spin platform. It was developed as a foundation for the smart catalog created for LDRD FY20 ACTS: Accelerating COVID-19 Testing with Screening.", + "laborHours": 0.0, + "languages": [], + "name": "REST Interface Generator (RESTInG) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dani-lbnl/resting.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vchendrix@lbl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets) uses a data brokering approach to synthesize diverse earth science data from a variety of remote sources in real-time without the need for additional storage. BASIN-3D is an extendable Django web framework application using a generalized data synthesis model that makes the synthesized data available via Application Programming Interface (API). This extends the basin3d Python framework for data synthesis (http://github.com/BASIN-3D/basin3d).We have currently implemented our data synthesis model to represent sensor-based time series earth science observations across a hierarchy of spatial locations. Supporting our data synthesis model is a plugin framework that allows developers to map data sources of interest to the BASIN-3D synthesis model.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets (django-basin3d)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BASIN-3D/django-basin3d", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2021-06-24" + }, + "description": "The Distributed Energy Resource Cybersecurity Framework (DERCF) provides U.S. federal government sites with a tool to assess the cybersecurity posture—or health—of their distributed energy resource (DER) systems.", + "homepageURL": "https://dercf.nrel.gov", + "laborHours": 0.0, + "languages": [], + "name": "DERCF (Distributed Energy Resource Cybersecurity Framework)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://dercf.nrel.gov/auth/#/register", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://dercf.nrel.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2024-07-01" + }, + "description": "cloud-fs (Cloud File System Utilities) is a generalized file-system handler that will dynamically determine if files are local or on the cloud (currently AWS) and perform basic file-system operations.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "cloud_fs (Cloud File System Utilities) [SWR-21-83]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/cloud_fs", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2021-06-24" + }, + "description": "KSSOLV is a MATLAB toolbox for solving Kohn-Sham density functional theory based electronic structure eigenvalue problems. It uses an object oriented features of MATLAB to represent atom, molecules, wavefunctions and Hamiltonians and their operations. It is designed to make it easier for users to prototype and test new algorithms for solving the Kohn-Sham problem. KSSOLV2.0 contains significant improvement over the original KSSOLV described in a paper published in ACM Transaction on Mathematical Software (attached). In addition to performing ground state calculation for small molecules, it can also perform geometry optimization for both molecules and solids. It uses standard pseudopotentials and implements local density approximation, generalized gradient approximation and hybrid functionals. Future releases will also include time-dependent DFT and post DFT calculations such as the GW quasi-particle energy calculation and Bethe-Salpeter equation solver for optical absorption.", + "laborHours": 0.0, + "languages": [], + "name": "Kohn-Sham Solver (KSSOLV) v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/kssolv2.0/src/release", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2021-06-24" + }, + "description": "The DIVA software interfaces a process in which researchers design their DNA with a web-based graphical user interface (DeviceEditor), submit their designs to a central queue, and a few weeks later receive their sequence-verified clonal constructs. Each researcher independently designs the DNA to be constructed with a web-based BioCAD tool, and presses a button to submit their designs to a central queue. Researchers have web-based access to their DNA design queues, and can track the progress of their submitted designs as they progress from \"evaluation\", to \"waiting for reagents\", to \"in progress\", to \"complete\". Researchers access their completed constructs through the central DNA repository. Along the way, all DNA construction success/failure rates are captured in a central database. his success/failure rate data can be leveraged to refine the DNA assembly design process.", + "homepageURL": "https://agilebiofoundry.org/capabilities/diva-biocad", + "laborHours": 0.0, + "languages": [], + "name": "DIVA/DeviceEditor (DIVA) v5.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://agilebiofoundry.org/capabilities/diva-biocad", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://agilebiofoundry.org/capabilities/diva-biocad", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2021-06-24" + }, + "description": "H5bench benchmark suite contains a list of applications that are used to measure the HDF5 I/O performance from various aspects.", + "laborHours": 0.0, + "languages": [], + "name": "H5bench: a benchmark suite for parallel HDF5 (H5bench) v0.6", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/h5bench", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lioukaihsin@utexas.edu" + }, + "date": { + "created": "2021-06-27", + "metadataLastUpdated": "2021-06-27" + }, + "description": "PARSEC is a computer code that solves the Kohn-Sham equations by expressing electron wave-functions directly in real space, without the use of explicit basis sets. It uses norm-conserving pseudopotentials (Troullier-Martins and other varieties). It is designed for ab initio quantum-mechanical calculations of the electronic structure of matter, within density-functional theory.\nPARSEC is optimized for massively parallel computing environment, but it is also compatible with serial machines. A finite-difference approach is used for the calculation of spatial derivatives. Owing to the sparsity of the Hamiltonian matrix, the Kohn-Sham equations are solved by direct diagonalization, with the use of extremely efficient sparse-matrix eigensolvers. Some of its features are: Choice of boundary conditions: periodic (on all three directions), or confined. Structural relaxation. Simulated annealing. Langevin molecular dynamics. Polarizability calculations (confined-system boundary conditions only). Spin-orbit coupling. Non-collinear magnetism.", + "laborHours": 0.0, + "languages": [ + "Fortran", + "Python" + ], + "name": "Pseudopotential Algorithm for Real-Space Electronic Structure Calculations", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/real-space/parsec", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "version": "1.4" + }, + { + "contact": { + "email": "lioukaihsin@utexas.edu" + }, + "date": { + "created": "2021-06-27", + "metadataLastUpdated": "2021-06-27" + }, + "description": "NanoGW can perform the following calculations:\n\n1. Linear-response time-dependent density functional theory (by solving Casida equation)\n2. Full-frequency GW calculation with or without LDA vertex function (does not support spin-orbit coupling)\n3. Construct and solve Bethe-Salpeter equation\n\nNanoGW has been tested thoroughly and optimized for molecules and nanoclusters. It runs particularly efficient for small-size (less than 30 atoms) molecules or clusters. This package can also deal with crystalline systems. However, its functionality for dealing crystals has not been thoroughly tested yet.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "NanoGW", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/real-space/nanogw", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-06-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python library for analyzing the internal structure of deep neural networks.", + "laborHours": 22374.4, + "languages": [ + "Python" + ], + "name": "pnnl/DeepDataProfiler", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/deepdataprofiler", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-28", + "metadataLastUpdated": "2021-06-28" + }, + "description": "Hybrid Power Plants (HPPs) have the potential to increase the value of renewable energy systems and decrease their costs through shared development (e.g., permitting) and infrastructure (e.g., collection system). Prior work has identified potential cost savings and technical and economic performance improvements for solar plus storage plants. However, additional research is needed to understand cost drivers that are specific to hybrid wind plants. Here we analyze the potential for shared infrastructure cost savings at one type of hybrid plant: wind plus solar photovoltaic (PV). To perform this analysis, we developed a new open-source, Python-based cost modeling tool: the Hybrid Balance-of-System (BOS) Systems Engineering model (HybridBOSSE). HybridBOSSE is an extension of NREL's LandBOSSE tool.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HybridBOSSE (Hybrid Balance-of-System (BOS) Systems Engineering Model)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HybridBOSSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-06-29", + "metadataLastUpdated": "2022-10-17" + }, + "description": "SAND2021-8720 O PyRIID is a Python package that provides methods for generating gamma spectra synthetically and offers models that can input a gamma spectrum and predict what radioisotope is present in it. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525", + "laborHours": 0.0, + "languages": [ + "Python 3.5 +" + ], + "name": "PyRIID v.2.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyriid", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0.0" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-06-29", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This software is a python package that interacts with the Application Programming Interface (API) suite provided by Deep Lynx. 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This can be replaced with any other fully convolutional deep learning architecture with relative ease.", + "laborHours": 0.0, + "languages": [], + "name": "Graphene U-Net v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnlcomputerarch/graphene-u-net", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-01", + "metadataLastUpdated": "2021-07-01" + }, + "description": "The Web of Registries Search (WoRs) is a web based software application that enables users to search for publicly available biological parts using keywords or sequence fragments. 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Included in the indexed information is the source of the information.", + "laborHours": 0.0, + "languages": [], + "name": "Web of Registries Search (WoRS) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/wors", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-01", + "metadataLastUpdated": "2021-07-01" + }, + "description": "Enhances accessibility of the Automated Recommendation Tool (ART), by adding on a graphical user interface, user authentication, and by exposing a REST API. Enables authenticated remote users and applications to interface with ART and to leverage remote computing resources to perform runs.", + "homepageURL": "https://sites.google.com/lbl.gov/art/home", + "laborHours": 0.0, + "languages": [], + "name": "ART Front End v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/art/licensing-code", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/art/home", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-01", + "metadataLastUpdated": "2021-07-08" + }, + "description": "Multi-modal Free-moving Data Fusion (MFDF) is a python package that implements low and high-level functionality for performing qualitative and quantitative gamma-ray imaging analyses. Such analyses enable the use of gamma-ray spectrometers and/or imagers to estimate the distribution and quantity of radiological materials in an environment. Free-moving 3D imaging requires additional information about the 3D trajectory and orientation of the system, however all of these methods can be applied to 2D static gamma-ray imaging as well. The package includes methods (MLEM and MAP) for distributed source reconstruction, methods (PSL) for point source reconstruction, the ability to ingest and utilize quantitative detector response functions (for absolute analyses), and the ability to perform 3D estimation of dose-rates from quantitative reconstructions.", + "homepageURL": "https://ipo.lbl.gov/multimodal-free-moving-data-fusion-for-gamma-ray-imaging-analysis", + "laborHours": 0.0, + "languages": [], + "name": "Multi-modal Free-moving Data Fusion (MFDF) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/multimodal-free-moving-data-fusion-for-gamma-ray-imaging-analysis", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/multimodal-free-moving-data-fusion-for-gamma-ray-imaging-analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Here we have developed a pipeline for the fast evaluation of viral emerging risks (FEVER) that generates primer and probe sets for genetically diverse viruses. The goal of probe design is to produce a short nucleotide sequence (called a K-mer, as it is of length K) that reacts with SARS-CoV-2 without also reacting to background material that may be present in the sample that is being tested. Other desirable properties of the probe, making it more effective in the experimental setup, include maintaining a high G/C content and reducing the \"hairpin propensity\" (ie, the tendency of the probe string to fold over on itself) by ensuring that any self-complementary pairs of sub-strings in the probe are sufficiently short. The mathematical formalization of the problem is expressed in terms of a constrained optimization, with G/C content and length of self-complementary sub-strings taken as constraints, while maximizing coverage of the probe. A probe is said to \"cover\" a SARS-CoV-2 sequence if the probe's K-mer appears as a sub-sequence of that sequence. Thus, coverage is defined as the number of sequences in the database that are covered by the probe. \"Exact\" coverage corresponds to an exact match of probe and sub-sequence; \"off-by-m\" coverage corresponds to an approximate match in which all but m nucleotides agree. Given a database of SARS-CoV-2 sequences, the single probe design problem is to find a string of length K, subject to the constraints of G/C content and hairpin aversion, which covers as many SARS-CoV-2 sequences as possible. For the multi-probe design problem, we seek P probes instead of just one, and a P-probe design is said to cover a SARS-CoV-2 sequence if any one of the probes cover it. Selection of K=31 was used because it was short enough that a single probe can cover a large fraction of the sequences in the SARS-CoV-2 database, but long enough that it won't accidentally cover potential background sequences. ", + "laborHours": 0.0, + "languages": [], + "name": "FEVER Probe Design Algorithm", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jt-lanl/fever-probes", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The software in development is a model of convection to be added to a public domain 1-dimensional supernova code. The supernova code models the collapse and explosion of stars. Without a convection module, the 1-dimensional code does not include the effects of convection under an entropy gradient. The modules that will be integrated into this code will calculate this convection.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Core-Collapse Supernova Code with New Convection Algorithms", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Two quantum graph algorithms (as python scripts) that run on the D-Wave Quantum Annealer are included for copyright. The Quantum Graph Partitioning software takes a graph as input and the number of partitions of equal size desired. This is transformed into a quadratic unconstrained binary optimization (QUBO) that is run as a quantum-classical algorithm using D-Wave/qbsolv. The Quantum Community Detection software takes a graph and the maximum number of communities/clusters desired. This is transformed into a quadratic unconstrained binary optimization (QUBO) that is run as a quantum-classical algorithm using D-Wave/qbsolv.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Quantum Graph Algorithms", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "ACD is a collection of python routines for detecting anomalous changes in pairs of images. The images can be panchromatic or multispectral (even hyperspectral), and for most of the algorithms in the collection, the two images need not have the same number of spectral bands. The general idea is to distinguish anomalous changes, which are assumed to be rare, from pervasive differences, which are assumed to occur throughout large portions of the image. The anomalous changes are candidates for actual, possibly interesting, changes on the ground, while the pervasive differences might for instance be due to different illumination or calibration during the acquisition of the two images.", + "laborHours": 0.0, + "languages": [], + "name": "ACD - Anomalous Change Detection software in python", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jt-lanl/acd", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The Geppetto application, developed in collaboration between Los Alamos National Laboratory and the DARPA MediFor program, provides an analysis platform for deepfake video detection. Geppetto provides a web interface and backend software that orchestrates the upload and analysis processes for a set of videos. This disclosure covers the user interface for Geppetto. ", + "laborHours": 0.0, + "languages": [], + "name": "Geppetto User Interface (UI)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/geppetto-ui", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "FlexFlow is a deep learning framework and engine, built using the Legion Programming System, that accelerates distributed deep neural network training by automatically discovering fast parallelization strategies. This is achieved by using a guided randomized search to find a fast parallelization strategy for a specific parallel machine architecture. To accelerate this search, FlexFlow introduces a novel execution simulator that can accurately predict a parallelization strategy’s performance and is three orders of magnitude faster than prior approaches that execute each strategy. FlexFlow currently out-performs common industry software frameworks like Google's TensorFlow/Keras and Facebook's PyTorch by factors ranging from 3 to 15 times.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "FlexFlow ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-06" + }, + "description": "Versatile Object-oriented Toolkit for Coarse-graining Applications (VOTCA) is a Coarse-grained modeling package, which focuses on the analysis of molecular dynamics data, the development of systematic coarse-graining techniques as well as methods used for simulating microscopic charge (and exciton) transport in disordered semiconductors. It was originally developed at the Max Planck Institute for Polymer Research. VOTCA has 2 major parts, the Coarse-graining toolkit (VOTCA-CSG) and the Excitation Transport Toolkit (VOTCA-XTP). All of them are based on the VOTCA Tools library, which implements shared procedures. Coarse-graining toolkit (VOTCA-CSG) VOTCA-CSG supports a variety of different coarse-graining methods, incl. (iterative) Boltzmann Inversion, Inverse Monte Carlo, Force Matching (also known as the multiscale coarse-graining method) and the Relative entropy method and hybrid combinations of those as well as optimization-driven approaches, like simplex and CMA. To gather statistics VOTCA-CSG can use multiple molecular dynamics package incl. GROMACS, DL_POLY, ESPResSo, ESPResSo++, LAMMPS and HOOMD-blue for sampling. Excitation Transport toolkit (VOTCA-XTP) VOTCA-XTP allows to simulate excitation transport and properties. Therefore, it provides its own implementation of GW-BSE and a basic DFT implementation, employing localized basis sets. Polarized QM/MM calculations for excited states are provided in the Thole framework. It features interfaces to more external Quantum Chemistry packages (Gaussian, NWChem and ORCA) for large scale production runs.", + "laborHours": 0.0, + "languages": [], + "name": "Contribute to VOTCA package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/votca/votca", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The program “EMCCD Calibration” is software to provide accurate calibration of the gain and analogue-to-digital conversation factor for a variety of scientific imaging devices, such as electron-multiplying charge-coupled device (EMCCD) cameras, complementary metal-oxide semiconductor (sCMOS), and intensified charge coupled device (ICCD) cameras. The software implements new calibration methods that are described in a manuscript intended for publication under the title “From Noise to Harmony: Calibration Methods for Electron Multiplying CCD Cameras”. The software provides ready-to-use tools for researchers using EMCCD, sCMOS, or ICCD cameras.", + "laborHours": 0.0, + "languages": [], + "name": "EMCCD Calibration", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ryand-LANL/EMCCD-calibration", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "MF-LBM is a high-performance lattice Boltzmann code for direct numerical simulation of three-dimensional multiphase flow in porous media. The main features of the code include: 1) implemented with advanced multiphase and wetting models that enable simulation of supercritical CO2 (scCO2) and brine displacement in real rock geometries; 2) extensively optimized for modern SIMD/SIMT processors/co-processors, such as GPU; 3) based on MPI-OpenACC/OpenMP hybrid programing model that enables high portability; 4) overlapped communication and computation that enables high scalability; 5) designed for flow simulations on digital rock images or complex microfluidic devices.", + "laborHours": 0.0, + "languages": [], + "name": "MF-LBM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MF-LBM", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "ARMO is a software tool for solving Alignment and Registration problems via Mathematical Optimization.\nGiven different 3D point clouds of overlapping areas, the tool can fix alignment issues by finding the optimal rotation and translation operations.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "ARMO", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Analysis scripts associated with “Hydraulically-vulnerable trees survive on deep-water access in a tropical forest community”\n\nThis dataset contains R scripts for all the analyses to reproduce the manuscript, “Chitra-Tarak, Rutuja, Chonggang Xu, Kristina Anderson-Teixeira, Jeff Chambers, Matteo Detto, Boris Faybishenko, Rosie Fisher, Ryan Knox, Charlie Koven, Lara Kueppers, Nobert Kunert, Stefan J. Kupers, Nathan G. McDowell, Brent Newman, Steve Paton, Laurent Ruiz, Lawren Sack, Jeffrey Warren, Brett Wolfe, Cynthia Wright, S. Joseph Wright, Joseph Zailaa, Sean M. McMahon. Hydraulically-vulnerable trees survive on deep-water access in a tropical forest community. To be submitted”. These scripts are divided into two parts: the first set of scripts prepare files for running and processing simulations from the model, Energy Exascale Earth System Land Model-Functionally Assembled Advanced Terrestrial simulator (ELM-FATES) to obtain soil water availability by depth at BCI, Panama, and the second set of scripts are associated with all the analyses related to the inverse modeling for tree rooting depths at BCI. ", + "laborHours": 0.0, + "languages": [], + "name": "Analysis scripts associated with manuscript, “Hydraulically-vulnerable trees survive on deep-water access during droughts in a tropical forest”", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/bci.elm.fates.hydrology", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-09-20" + }, + "description": "Los Alamos National Laboratory is embarking on a project to set a new standard in genome mapping through development of unique 4D genomics capabilities. We will develop and deploy open source software tools to discover fundamental cellular functions that are hijacked by viruses to cause disease. Given LANL’s breadth of expertise in genomics, high performance computing, and advanced visualization, we are uniquely positioned to build the nascent 4D genomics field to help determine the 4D spatial-temporal architecture and dynamic reconfiguration of the human genome for any application. The goal of this software project is to create a web-based interactive application, with a complete web software stack, that provides a way to browse, visualization, query and annotate curated sets of related genomic data. The software will provide an intuitive interface to this complex data, utilizing a set of custom and off-the-shelf components integrated into specific configurations of coordinated data views. To achieve this, the project will provide components, algorithms and integrated applications and will be available as an open source project that can be used by others to view related sets of data. The primary users of this platform will include institutional users at Los Alamos National Laboratory, scientists and researchers from collaborative institutions, and others interested in exploring multi-modal genomic databases.", + "laborHours": 0.0, + "languages": [], + "name": "4D Genome Browser", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/4DGB", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The Nuclear Data Access Tool Kit (NDATK) is a C++ API that provides continuous energy neutron and photon libraries corresponding to multigroup neutron libraries. It uses libraries named to match Nuclear Data Interface (NDI) libraries and tells the host code where the continuous energy data is. Like NDI, it includes multi-temperature data.", + "laborHours": 0.0, + "languages": [], + "name": "Nuclear Data Access Tool Kit NDATK", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/NDATK", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The SHIELDS Particle Tracing Model (PTM) is a large-scale particle tracing code, primarily intended for magnetospheric applications. It provides a fast, parallel computing-friendly, and versatile framework for tracing charged particles in arbitrary electric and magnetic fields. To support a broad range of test particle applications, full Lorentz motion can be modeled as well as guiding center motion. Switching strategies allow accurate and efficient test particle tracing across regions where the guiding center approximation may not be maintained. PTM supports tracing of particle motion both forwards and backwards in time. For backwards tracing, PTM can launch particles from a specified location and trace until stopping criteria are met. These stopping criteria can include crossing a surface in space, or a time limit. For forwards tracing particles can be launched from specified points or spatial regions. The code is designed to allow many applications without requiring recompilation, instead providing a rich, user-configurable interface that allows use of different modes at runtime. Model results are stored in user-selected format for post-processing including Liouville mapping of particle fluxes from source to target location. PTM includes pre-processing for field configurations, tools for setting up runs, and post-processing capabilities to enable scientific use. Sample applications include specifying the geosynchronous particle boundary for inner magnetosphere modeling, and determining access of solar energetic protons.", + "laborHours": 0.0, + "languages": [], + "name": "SHIELDS-PTM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SHIELDS-PTM", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Anaerobic Digestion Model No 1 (ADM1) is a mathematical model used by researchers to simulate the anaerobic digestion process that converts organic matter into biogas. The reduction of biosolids during anaerobic digestion reduces the solids handling cost while the biogas produced can be used to generate heat and electricity to offset the cost of heat and electricity at water resource recovery facilities. The original version of the ADM1 developed by the International Water Associations Task Group for Mathematical Modelling of Anaerobic Digestion Processes was created to describe the kinetics and stoichiometry of the primary biochemical processes in anaerobic digestion. The EES-16 team modified the ADM1 by adding mathematical terms which separate the solids retention time from hydraulic retention time to simulate novel AD technologies, integrating the model into one package in C++ language, introducing sophisticated implicit solvers by linking it to the PETSc package which allows fast and scalable (parallel) solution for the system of differential equations in the ADM1. Also, we created an easy-to-navigate interface with tutorial examples documented in the ipython notebook allowing customization of the operating conditions and reactor configurations for the simulation of the model.", + "laborHours": 0.0, + "languages": [], + "name": "Anaerobic Digestion Model", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ADM1F", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "I am submitting an umbrella/blanket disclosure because I am working on several inter-related projects in a fast-moving research area. The general theme is statistical analysis and visualization of SARS-CoV-2 viral genetic sequence data in order to learn about epidemiology. Examples of research questions are: How do viral genetic relationships relate to contact tracing links? How does viral genetics reflect signatures of transmission from one person to another? Do some genetic variants have a consistent transmission advantage?", + "laborHours": 0.0, + "languages": [], + "name": "Blanket Phylogenetic and genetic analyses of SARS-CoV-2 epidemiology", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eeg-lanl/sarscov2-selection", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Alignment of replicate time series can be useful for identifying shared but time-warps behavior in time series data such as monitoring temperature or network communication patterns for cyberphysical systems. This learning of common behavior is a first step for identifying abnormal behavior such as intrusion or anomalies. We developed the alignts R package to provide an R implementation of Listgarten (2004) with advancements described in Grosskopf (submitted 2021). The package is programmed in R and Fortran 95 with OpenMP support. The package includes functions for aligning a collection of nominally replicate time series, making forecast predictions of future states conditioned on the current data, and carrying out particle filtering for estimating uncertainty in the state of the system in an on-line data collection environment. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "alignts", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "singularity-eos is a library that provides a unified interface and performance portable implementations of equations of state (EOS). The library includes a set of simple analytic models that are all published in the open literature and generic tabulated EOS capabilities that build on a generic table interpolation library that is being released under a separate disclosure. However, absolutely no tabulated data for material EOS is included in singularity-eos. Instead, users of singularity-eos need to provide the tabulated data.", + "laborHours": 0.0, + "languages": [], + "name": "singularity-eos", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/singularity-eos", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "tkonstant@bnl.gov" + }, + "date": { + "created": "2021-07-04", + "metadataLastUpdated": "2021-07-05" + }, + "description": "Code and data for training CNN-Encoder-Decoder model described in the publication 'Noise reduction in X-ray photon correlation spectroscopy with convolutional neural networks encoder-decoder models.'", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "CNN-Encoder-Decoder Model", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bnl/CNN-Encoder-Decoder", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-06", + "metadataLastUpdated": "2021-07-06" + }, + "description": "Watchr is a Java library that processes time-series data and generates HTML graphs. It is primarily used to track the performance of subroutines over time. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.\nSAND2021-7299 O", + "laborHours": 0.0, + "languages": [ + "Java", + "Java" + ], + "name": "watchr-core", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/watchr-core", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-07", + "metadataLastUpdated": "2021-07-07" + }, + "description": "The CENS code translates Evaluated Nuclear Structure Data File, ENSDF, into application-specific formats, such as\nReference Input Parameter Library, RIPL, as well as into a generic XML format. Although ENSDF contains the most updated\nnuclear structure information, its complex format and philosophy of purely experimental basis often prevent direct use in\npractical applications in fundamental and applied science. CENS reads the adopted discrete levels, their spin and parity,\nand gamma-ray branching ratios etc. compiled in ENSDF, and estimates some missing information as needed by\nconsidering the statistical properties of nuclear structure, then prints out the nuclear structure data in more readable\nformats. CENS is written in C++, about 5,000 lines in total. A user's manual is also provided in HTML in the same package.\n[LAUR 21-22523]", + "laborHours": 0.0, + "languages": [], + "name": "CENS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/toshihikokawano/CENS", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-07", + "metadataLastUpdated": "2021-07-07" + }, + "description": "GoFigure is a code repository for a set of tools for the analysis and retrieval of technical images, or figures, such as drawings and plots. The goal of these tools is to automate the understanding of technical content contained in scientific images. Computer vision algorithms are automating the analysis of content in images and these tools will extend these innovations for images of scientific content. GoFigure includes tools for analyzing the context, topology and shape information in images, as well as graph-based matching algorithms for fast retrieval of similar images. These components are written in Python, a high-level programming language that takes advantage of the Python eco-system of high-quality open-source packages for computer vision, graph algorithms and machine learning.", + "laborHours": 0.0, + "languages": [], + "name": "GoFigure", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GoFigure-LANL/GoFigure", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-07-08", + "metadataLastUpdated": "2021-10-01" + }, + "description": "The Water Technoeconomic Assessment Pipe-Parity Platform (WaterTAP3) was developed under the National Alliance for Water Innovation (NAWI) to facilitate consistent technoeconomic assessments of desalination treatment trains. The WaterTAP3 is an analytically robust modeling tool that can be used to evaluate water technology cost, energy, environmental, and resiliency tradeoffs across different water sources, sectors, and scales. The model simulates steady-state water treatment train performance and costs including flow and constituent mass balance across unit processes, based on source water conditions, configurations of treatment technologies, and system-level techno-economic assumptions. Users can build a new treatment train by connecting any number of unit processes, specific for their context and system, or selecting a train from the treatment train library. The model contains various technical and cost parameter options for a range of treatment processes and a library of influent water quality characteristics for a variety of source waters and case studies. Users can customize water quality parameters to evaluate the technology performance in their context. The model can be set up for different assessment needs including simulation, optimization, and uncertainty and sensitivity analyses. The results from WaterTAP3 can help identify trade-offs among the different system performance metrics, with insight on how particular technologies or systems promote pipe-parity. The flexibility and comprehensive scope of the tool makes it a promising solution to industry-wide water technoeconomic evaluations, leading to more informed water investment decisions and technologies. As a user-friendly, open-source platform, WaterTAP3 can be used by industry, academia, policymakers, planners, and those with or without extensive analytical experience.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "WaterTAP3 (The Water Technoeconomic Assessment Pipe-Parity Platform)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WaterTAP3", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-12", + "metadataLastUpdated": "2021-07-12" + }, + "description": "NchooseK represents a suite of software tools that seeks to unify and facilitate the exploitation of circuit-model quantum computers and quantum annealers. Numerous types of software will be included in this suite including compilers, preprocessors, optimizers, translators, run-time systems, support tools and scripts, and technology demonstrations.", + "laborHours": 0.0, + "languages": [], + "name": "NchooseK", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/NchooseK", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-07-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Verification and Validation Assuring Reliability and Security (VARS) project team has developed the proof-of-concept VARS framework which will be implemented in the form of a software tool called Risk-Informed Verification and Validation Recommendation (RIVVR). The framework will provide Energy Delivery System (EDS) stakeholders with cybersecurity focused verification and validation (V&V) approach which includes list of potentially relevant vulnerabilities to test or address, pre-procurement guidance, and separate lists of relevant standards, tools, and techniques (ST2) to be considered by utilities and vendors", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "VARS Framework", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-12", + "metadataLastUpdated": "2021-07-12" + }, + "description": "Distributed energy resource management systems (DERMS) are being deployed in feeders with high distributed energy resource (DER) penetration to provide visibility of DERs and enable DER control strategies for grid operators. DERMS can support centralized grid controls by aggregating individual DER information into a single virtual DER model. This codebase creates algorithms for a DERMS platform that are able to aggregate a set of DERs that can be modeled as batteries, create a virtual battery model for centralized grid controls, and dispatch power setpoints to the individual DERs based on a desired virtual power setpoint received from the centralized grid control. It integrates with existing co-simulation frameworks and models for buildings, DERs, and distribution systems. While the DERMS is designed to work with batteries, it can be used with any DER that can be defined by a generalized battery model.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Virtual Battery Aggregator (Virtual Battery Aggregator for Distributed Energy Resource Management Systems)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/virtual-battery-aggregator", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ahearin@anl.gov" + }, + "date": { + "created": "2021-07-13", + "metadataLastUpdated": "2021-07-13" + }, + "description": "Halotools is a specialized python package for building simulation-based models of cosmological structure formation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "halotools", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/astropy/halotools", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "0.7" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-07-14", + "metadataLastUpdated": "2023-08-14" + }, + "description": "This is a basic package for creating Bewley Lattice Diagrams in Python. https://nrel.github.io/bewley", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "Bewley Lattice Diagram [SWR-19-17]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bewley", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-14", + "metadataLastUpdated": "2021-07-14" + }, + "description": "Intuitive GUI for manipulating microscope stages, allowing to align crystallographic data with stages, allowing to align crystallographic data with stage coordinates and microscope images. Simulates kinematic diffraction patterns and Kikuchi line patterns. Simulated patterns can be displayed as overlay to actually measured data, allowing manual fingerprinting and angular alignment. Crystallographic data is fed to the program in form of CIF (crystallographic information file) files, which are available from many databases and cover virtually all crystal structure ever reported in any journal. Actual goniometer scales can be linearized by lookup tables, program can be used with any microscope goniometer, double tilt and tilt-rotation type. Software requirements: Win32 platform (XP); Compiler/Version: Borland C++ Builder 5; Type of files: Executable modules; Hardware requirement: PC", + "laborHours": 0.0, + "languages": [], + "name": "KSpaceNavigator (KSN)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/kspacenavigator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-14", + "metadataLastUpdated": "2021-07-14" + }, + "description": "Lightweight C++11 multithreading tasking system featuring thread-pool, task-groups, and lock-free task queue.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Tasking Library (PTL) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jrmadsen/PTL.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-07-15", + "metadataLastUpdated": "2021-07-15" + }, + "description": "Frontend for the Software Defined Accelerators from Machine Learning Tools Environment (SODALITE) and the Software Defined Architectures for Data Analytics (SO(DA)^2) projects. This frontend takes in input json files from trained neural networks from the most common machine learning tools (PyTorch, TensorFlow, MxNet, etc.) and the related h5 files with weights, and generate the related MLIR (multilevel intermediate representation) linear algebra dialect. This allows the neural networks to be ingested by the rest of the SODA toolchain.", + "laborHours": 0.0, + "languages": [], + "name": "SODA frontend", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/sodalite/soda-frontend", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2021-07-15", + "metadataLastUpdated": "2021-07-15" + }, + "description": "Configure a Hashicorp Vault server for use with htgettoken", + "laborHours": 0.0, + "languages": [ + "Bash", + "Python" + ], + "name": "fermitools/htvault-config", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fermitools/htvault-config", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-07-19", + "metadataLastUpdated": "2021-07-19" + }, + "description": "This script converts files from the XML format to the CLI format.", + "laborHours": 0.0, + "languages": [], + "name": "AMXML to CLI converter", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CLDruzgalski/AM_fileConverters", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "allus@ornl.gov" + }, + "date": { + "created": "2021-07-20", + "metadataLastUpdated": "2021-09-28" + }, + "description": "Parallel computer code for the simulator for dynamics of power systems which has the capability to initiate the system and create different faults for the dynamic analysis. The code is based on time-parallel method (Parareal) with Adaptive Method Reduction (AMR). The coarse solvers for the Parareal algorithm include several Semi Analytical Solution methods. Also, Integrated simulation of coupled transmission and distribution systems can be studied.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "RAPID", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/PowerSystems/rapid", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-07-21", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This model was developed to assess the viability of US Lithium supply from geothermal brine and the potential supply chain impact of extracting Lithium from this source. This model links global demand and supply of lithium (Li) considering different electric vehicle (EV) demand scenarios. We seek to answer the following questions: • What is the economic potential of Li extraction from US geothermal sources? • Is geothermal Li extraction technology a viable investment in the US? • What is the potential supply chain impact of Li supply from US geothermal sources?", + "laborHours": 0.0, + "languages": [], + "name": "Lithium Supply Analysis Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/LISA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-22", + "metadataLastUpdated": "2021-07-22" + }, + "description": "The Decision-support and Emissions Prediction Interactive Cities Tool (DEPICT) aims at predicting the cross-sectoral (building construction, operation and vehicles) energy consumption and greenhouse gases emissions at campus and urban scale. It leverages capabilities of multiple modeling tools: EnergyPlus for building operation, CalEEMod for building construction and gas vehicle, BEAM for electric vehicles and SAM for building–integrated photovoltaics. It distinguishes from other cross-sectoral model such as CalEEMod or BEST in that it uses physical models, rather than empirical models, for all sectors, which allows for a more accurate and customizable quantification. It is relevant for short-term multi-sectoral decision making by developers and city planners and long-term policy making by municipal and state officials. Information about all the developers", + "homepageURL": "https://buildings.lbl.gov/impel/people/lit/lit5", + "laborHours": 0.0, + "languages": [], + "name": "Decision-support and Emissions Prediction Interactive Cities Tool", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://buildings.lbl.gov/impel/people/lit/lit5", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://buildings.lbl.gov/impel/people/lit/lit5", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-22", + "metadataLastUpdated": "2021-07-22" + }, + "description": "Software toolchain to program the MMC on Marble boards", + "laborHours": 0.0, + "languages": [], + "name": "Marble MMC v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/Marble-MMC.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-22", + "metadataLastUpdated": "2021-07-22" + }, + "description": "Some different SYCL implementations of the reduction operation. The parallel reduction kernel aggregates vector elements into a single result. It consists of four ways to implement the reduction operation using two different data management strategies, which we could not find elsewhere as a single package.", + "laborHours": 0.0, + "languages": [], + "name": "sycl-reduction benchmark v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/nersc-proxies/sycl-reduction.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2021-07-23", + "metadataLastUpdated": "2021-07-23" + }, + "description": "We propose a stable, distributed approach to perform AA that accelerates the convergence rate of stochastic first-order optimizers to train neural networks.\nDifferently from previous works, we do not alter neither the scheme to perform AA nor the loss function minimized during the training. \nTo improve robustness against stagnation, we customize general guidelines that suggest to relax the frequency of AA corrections by performing AA only at the end of an entire training epoch. \nTo improve robustness of AA against the stochastic oscillations of first-order optimizers, we average the gradients computed on consecutive stochastic optimization updates. The improved regularity of the converging sequence and the reduced amplitude of stochastic oscillations across consecutive optimization steps allows AA to efficiently extrapolate an improved converging sequence, thereby overcoming limitations of existing approaches to perform AA on stochastic optimization.\n \n", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AADL: Anderson Accelerated Deep Learning", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/AADL.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2021-07-26" + }, + "description": "The Multi-scenario Extreme Weather Simulator (MEWS) takes existing historical weather data and inserts trends and extreme events such as heat waves, hurricanes, extreme precipitation, or winter storms. The code includes functionality for projecting increasing frequency and duration of such events over a large range of statistically sampled realizations of the future. These weather files can then be used in building energy simulations through the Energy Plus software created by DOE. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-8658 O", + "laborHours": 0.0, + "languages": [ + "Python", + "cython" + ], + "name": "Multi-Scenario Extreme Weather Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MEWS", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2023-08-14" + }, + "description": "This wind turbine digital twin software (wtDigiTwin) provides a digital twin solution for wind turbine applications. The focus of wtDigiTwin is to estimate loads, motions and environmental conditions for an operating wind turbine. The program uses supervisory control and data acquisition (SCADA) measurements as inputs, together with a wind turbine model. The wind industry is currently challenged by the high cost of operation and maintenance. These costs could be mitigated if component failures are predicted, but such predictions are difficult unless the turbines are equipped with expensive measuring devices. The alternative is to use a digital twin such as wtDigiTwin to estimate the necessary signals. wtDigiTwin can perform online prediction of signals that are otherwise not measured, using a limited set of reliable measurements and a physics-based model. The predicted signals can be used in applications that have direct cost benefits: 1) real-time estimation of the fatigue consumption of key components of the wind turbine; 2) root cause analyses and failure detections ; 3) lifetime reassessments ; 4) improvements to follow-on designs. The current version provides examples to estimate wind speed, thrust, torque, tower-top position, and tower loads on an onshore wind turbine using the following measurements tower top acceleration, generator torque, pitch, and rotational speed. The model combines a linear state-space model, a wind speed estimator, and a Kalman filter algorithm that integrates measurements with the state model to perform state estimations. The state space model is obtained either using OpenFAST linearizations, or using the yams package provided with the software.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python" + ], + "name": "wtDigiTwin (Wind Turbine Digital Twin) [SWR-21-15]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/wtDigiTwin", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2021-07-26" + }, + "description": "MoorPy is a quasi-static mooring model and a suite of associated functions for mooring system analysis. The core model supports quasi-static analysis of moored floating systems including any arrangement of mooring lines and floating platforms. It solves the distributed position and tension of each mooring line segment using standard catenary equations. Floating platforms can be represented with linear hydrostatic characteristics. MoorPy automatically computes a floating system's equilibrium state and can be queried to identify a mooring system's nonlinear force-displacement relationships. Linearized stiffness matrices are efficiently computed using semi-analytic Jacobians. MoorPy also includes plotting functions and a library of mooring component property and cost coefficients. MoorPy can be used directly from Python scripts to perform mooring design and analysis tasks, or it can be coupled with other tools to compute quasi-static mooring reactions as part of a larger simulation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "MoorPy (Quasi-Static Mooring Analysis in Python)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MoorPy", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2024-09-19" + }, + "description": "The Role-Based Access Control (RBAC) for Distributed Energy Resources (DER) software is an automated and transparent stack for RBAC administrators to interact with RBAC policy. The package includes demonstrations of centralized and decentralized RBAC implementation. Both include simulated DER entities that are stored automatically in a centralized Lightweight Directory Access Protocol (LDAP) server. It also includes a REST-API to serve the HTTP requests of the RBAC administrators. A complete front-end is included to serve the users' needs. This software may be used by industry (DER vendors/utilities) as well as the research community to determine if a centralized or decentralized solution fits better the needs of an RBAC model in a DER environment. Additionally, parts of this software may be useful for developing implementations for specific needs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8292 O", + "laborHours": 87582.4, + "languages": [ + "JavaScript", + "Vue", + "CSS", + "Python", + "Makerfile", + "SCSS" + ], + "name": "Role-Based Access Control for Distributed Energy Resources v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/RBAC_Centralized", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2021-08-16" + }, + "description": "The Sudoku Online Testing Framework provides a configurable basis for testing user interactions to solve visualization-related problems with sudoku puzzles and games. It consists of a server, a client, and test code. The python server implements sudoku puzzle logic and board selection functions. The JavaScript client implements a graphical user interface (GUI) front-end to display the puzzles and facilitate interactions with users. Within the GUI, logical rules may be selected. Cells may be selected to “pivot” on to make a board for each possible value in the cell. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-6409 O", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Sudoku Online Testing Framework v.0.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sudoku-online", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-27", + "metadataLastUpdated": "2023-05-16" + }, + "description": "Risk Informed Timelines (RIT) is a more modern and holistic method for understanding how access delay timelines are developed and utilized in physical security system evaluations. The software utilizes Bayesian methods to combine subject matter expert judgement and small performance test datasets in a consistent and defensible way. It allows a more holistic view of delay performance that provides distributions of task times and task success probabilities to account for tasks that, if failed, would result in failure of the attack. The RIT methodology is meant to enable security risk managers to begin the transition into more comprehensive delay timeline analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8294 O", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C#", + "C++", + "C#" + ], + "name": "Risk Informed Timelines (RIT) v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-27", + "metadataLastUpdated": "2021-08-30" + }, + "description": "X-Ray Toolkit Mobile (Android) is a software application for acquiring and processing digital images. The application runs on mobile devices running Android operating systems. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-1981 O", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Java", + "Java" + ], + "name": "X-Ray Toolkit Mobile (Android)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.X.X. - Android" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-28", + "metadataLastUpdated": "2021-09-13" + }, + "description": "This is the companion repository to NREL's Interactive Mobility Landscape App (SEE: DOE Code ID 61291. NREL SWR-21-10). \n\nThe Interactive Mobility Data Landscape is a project intended as a map through the previously uncharted, growing mobility data science field. This attempts to categorize most of the data sources, specifications, and tools in the field of mobility. It has been built by the National Renewable Energy Laboratory's (NREL) Mobility, Behavior, and Advanced Powertrains (MBAP) research group.\n\nThe software for the interactive landscape is located at https://github.com/NREL/mobility_landscapeapp\nThis repo includes all of the data and images specific to the Interactive Mobility \nData Landscape.", + "laborHours": 0.0, + "languages": [], + "name": "Interactive Mobility Data Landscape", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mobility_landscape", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-28", + "metadataLastUpdated": "2021-09-13" + }, + "description": "This is the companion repository to NREL's Interactive Mobility Data Landscape (SEE: DOE Code ID 61284. 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The BETTER V.1.0 web application, developed with the Django web-framework and the Model-View-Controller (MVC) architecture being disclosed here, provides a graphical user interface (GUI) for any user to view the software tutorials, download and upload a data entry template, configure and run the BETTER analyses, and view the final analytical reports.", + "homepageURL": "https://sites.google.com/lbl.gov/2021-127/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Building Efficiency Targeting Tool for Energy Retrofits (BETTER) Web Application (BETTER Web App) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2021-127/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-127/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-29", + "metadataLastUpdated": "2021-07-29" + }, + "description": "The BETTER API allows advanced users and developers to access BETTER's analytical functionalities via HTTP requests from their own software platform without using the BETTER web-interface. API users prepare the input data and analysis configurations in a JSON format and send it to the web application via an HTTP request. The web application runs the analytical workflow on the back end and returns an HTTP response in JSON format. The user can then decide to render the results or further process it.", + "homepageURL": "https://sites.google.com/lbl.gov/2021-128/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Building Efficiency Targeting Tool for Energy Retrofits (BETTER) Application Programing Interface (API) (BETTER API) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2021-128/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-128/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "Phoebus is a performance portable code for simulating relativistic astrophysical phenomena. 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Capabilities for these physical ingredients are developed atop the open source Parthenon framework for performance portable, block-structured adaptive mesh refinement.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Phoebus", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "An R programmatic interface for querying, handling, and summarizing AmeriFlux (https://ameriflux.lbl.gov/) data and metadata. 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The tentative features include 1) listing the sites with basic site general info, 2) querying how much data & metadata are available, 3) subsetting a target site list for download, 4) parsing data & metadata, 5) cleaning & summarizing data, 6) data visualization and 7) listing target sites' contacts & DOI.", + "laborHours": 0.0, + "languages": [], + "name": "amerifluxr v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chuhousen/amerifluxr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "singularity-opac is a library for providing a unified interface for opacities, emissivities, and scattering cross-sections for materials and use in simulation codes. It is designed to be performance portable and run on CPU and GPU.", + "laborHours": 0.0, + "languages": [], + "name": "singularity-opac", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/singularity-opac", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "SHIVER (SARS CoV-2 Historically Identified Variants in Epitope Regions) analyzes and summarizes the historical record of amino acid sequences for the Spike protein of the SARS Cov-2 virus. The analysis is focused on the N-terminal domain (NTD) and Receptor Binding domain (RBD) epitope regions, and aims to choose a set of variant forms that collectively cover a large fraction of the sequences in the alignment as a whole (globally) but also that cover large fractions of sequences collected on the different continents. The software provides a set of Spike protein sequences in a standard (fasta) sequence format.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "SHIVER", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "The CELL Adaptive mesh Refinement (CELLAR) application provides cell-based adaptive mesh refinement data structures and execution for parallel computing architectures. This application also includes example tests that exercise iteration patterns over the mesh entities (cells, edges, faces). The application is written in C++ and Fortran.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "CELLAR", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "We develop algorithms and software that uses the D-Wave 2000Q quantum annealer to solve several types of Boolean tensor factorization problems. Boolean tensor factorization refers to the problem of representing a high-dimensional tensor filled with Boolean values as a product of smaller Boolean core tensors and Boolean matrices. We consider different tensor factorization models, including Boolean Tensor Train, Boolean Tucker, and Boolean Hierarchical Tucker. As an exact decomposition of a given type may not exist in the general case, the objective is to minimize the difference between the input high-dimensional tensor and the product of the lower-dimensional tensors of the proposed factorization, using a specified tensor norm. In our approach, we reduce the Boolean tensor factorization problem to a sequence of quadratic unconstrained binary optimization problems suitable for the D-Wave 2000Q quantum annealer. Although current quantum technology is still fairly restricted in the problems it can tackle, we show that complex tensor factorization problems as the ones addressed by us can be solved efficiently and accurately.", + "laborHours": 0.0, + "languages": [], + "name": "QBTNs - Quantum Boolean Tensor Networks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyQBTNs", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "pyCP_APR is a tensor decomposition and anomaly detection Python library that is designed for the fast analysis of large datasets by accelerating computation speed using GPUs. pyCP_APR uses the CANDECOMP/PARAFAC Alternating Poisson Regression (CP-APR) tensor factorization algorithm utilizing both Numpy and PyTorch backend. While the Numpy backend can be used for the analysis of both sparse and dense tensors, the PyTorch backend provides a faster decomposition of large and sparse tensors on the GPU. pyCP_APR's Scikit-learn like API allows comfortable interaction with the library, and includes the methods for statistical anomaly detection via the p-values obtained from the CP-APR factorization.", + "laborHours": 0.0, + "languages": [], + "name": "pyCP_APR", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyCP_APR", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "R code to fit generalized Bayesian Adaptive Smoothing Spline (GBASS) models for nonlinear regression. The approach is similar to the Bayesian MARS approach of Francom & Sanso (2020), but allows for non-Gaussian likelihoods. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "GBASS SOFTWARE", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-08-19" + }, + "description": "The Zotero Robust Links extension automatically creates an archival copy (memento) of the URI of an item ingested into a Zotero library. The extension can also manually be triggered to create mementos. The software also contains a \"translator\" that enables the export of \"robustified\" items with Robust Links-enhanced HTML code.", + "laborHours": 0.0, + "languages": [], + "name": "Zotero Robust Links Extension", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Zotero-Robust-Links-Extension", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "Clustering methods are heavily dependent on the algorithm of choice, as well as the chosen hyperparameters of the algorithm and their sensitivity to data scales is largely unknown. In our software, we introduce a tensor clustering that relays on discrete wavelet transform to analyze the effects of course-graining on clustering of high-dimensional tensor data. Our method CGC allows us to understand how the different scales affect clustering. The scale of data is an important feature with regards to clustering. CGC calculates the normalized mutual information drop off at different length scales which illustrates certain resolutions are producing novel clusters. Consequently, in addition to running several clustering algorithms, it is also important to include several coarse-grain clusterings into a cluster ensemble.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "CGC", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-08-03" + }, + "description": "FIERRO is a modern C++ code intended to simulate quasi-static solid mechanics problems and transient, compressible material dynamic problems with Lagrangian methods, which have meshes with constant mass elements that move with the material. FIERRO is designed to aid a) material model research that has historically been done using commercial implicit and explicit finite element codes, b) numerical methods research, and c) computer science research. FIERRO supports user developed material models that adhere to several industry standard formats by using a C++ to Fortran interface to couple the model to the numerical solvers. FIERRO is built on the ELEMENTS library that supports a diverse suite of element types, including high-order elements, and quadrature rules. The mesh class within the ELEMENTS library is designed for efficient calculations on unstructured meshes and to minimize memory usage. FIERRO is designed to readily accommodate a range of numerical methods including continuous finite element, finite volume, and discontinuous Galerkin methods. FIERRO is designed to support explicit and implicit time integration methods. FIERRO only supports a single material in an element. No physical data exists within the code.", + "laborHours": 0.0, + "languages": [], + "name": "FIERRO V.X", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Fierro", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "This software converts XML files created by the Netfabb software to the XML format used by the Intelligent Feed Forward (IFF) tools developed at LLNL.", + "laborHours": 0.0, + "languages": [], + "name": "Netfabb to IFF XML converter", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CLDruzgalski/AM_fileConverters", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2022-06-16" + }, + "description": "The Ubiquitous Traffic Volume Estimation System uses Machine Learning (ML) algorithms to provide accurate estimates of number vehicles on the roadway (ubiquitous traffic volume) based on inputs such as commercial probe traffic data that includes average vehicle speed and probe counts, roadway characteristics, weather, time of day, and day of week, and reference volume counts from a limited number of automatic traffic recorder stations. The Ubiquitous Traffic Volume Estimation System estimates traffic volumes 24 hours a day, 7 days a week, and 365 days a year on all major corridors and freeways in Denver metropolitan area and is being expanded to the whole state of Colorado. The methodology and code developed in this effort can be easily customized to other states and cities where similar data is available.", + "laborHours": 0.0, + "languages": [ + "R", + "Jupyter Notebook" + ], + "name": "Ubiquitous Traffic Volume Estimation System", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/TrafficVolumeEstimation", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-05" + }, + "description": "GPos is a software that was created to determine the properties of positron beams resulting from the interaction of the LBNL BELLA center PetaWatt laser-driven plasma-capillary accelerated electron beam and the atoms of a thin solid target. GPos is written in C++, easily compiled with cmake and the spack package manager, which allows for multi-thread and MPI parallel computing. Its functions expand on the Geant4 toolkit library and allow for propagation of the modelled particles through vacuum drift distances with a focusing element (thin lens approximation). Users can change beam-foil-drift-lens parameters - to adapt GPos to other particle sources and infrastructures - in a simple input file. The code particle data output format, openPMD, which is compatible, for example, with the input of the ECP WarpX project code used to explore the physics of particle acceleration in plasmas. Using GPos in conjunction to WarpX allowed us to test various configurations for designing a high-quality and high-energy positron source at BELLA -required for us to address positron acceleration challenges in the development of future linear colliders. GPos can also be advantageous when tackling the physics of muon sources for future muon colliders as well as for the investigation of positron sources in lower energy regimes for applications like annihilation spectroscopy and astrophysical gamma-ray-bursts.", + "laborHours": 0.0, + "languages": [], + "name": "Geant4 based positron beam source (GPos) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LDAmorim/GPos", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-05" + }, + "description": "eProject Builder (ePB) is a secure, web-based system that enables agencies and ESCOs to securely: (1) preserve, track, and access energy project information for the life of the contract (2) quickly generate data and reports for their portfolio of projects (3) develop project scenarios using standardized amortization calculations (4) benchmark new projects against historical project data", + "homepageURL": "https://sites.google.com/lbl.gov/2021-124/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "eProject Builder (ePB) v3.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2021-124/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-124/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-05" + }, + "description": "A Machine Learning Platform that connects beamline scientists and machine learning (ML) researchers so that the ML researchers can quickly distribute their ML models to beamline scientists, and beamline scientists can give feedback to help ML researchers improve their models.", + "laborHours": 0.0, + "languages": [], + "name": "MLExchange v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mlexchange/mlex", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-06" + }, + "description": "Fast Free Fermion Compiler (F3C) is an application-specific quantum circuit compiler for time-evolution circuits of spin Hamiltonian systems that can be mapped to free fermions.", + "laborHours": 0.0, + "languages": [], + "name": "F3C++ v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QuantumComputingLab/f3cpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-06" + }, + "description": "Fast Free Fermion Compiler (F3C) is an application-specific quantum circuit compiler for time-evolution circuits of spin Hamiltonian systems that can be mapped to free fermions. F3C is the Matlab software version and the related F3C++ is the C++ software version.", + "laborHours": 0.0, + "languages": [], + "name": "F3C v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QuantumComputingLab/f3c", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-11" + }, + "description": "The District EnErgy Planner - DEEP is an Mixed Integer Linear Programming (MILP) optimization software tool to solve district energy system, technology configuration, operation strategies, and energy retail business schemes. DEEP takes user input energy demand on heating, cooling and electricity demand. Energy loss through pipeline is calculated for heating and cooling from central plants. The optimal system configuration to minimize the district energy system life cycle cost or minimize CO2 emission is calculated based on energy balance equations and various constraints. The recent update on DEEP include a feature of waste heat utilization energy balance based optimization to take into accounts of different temperature bands of heat into account to maximize system efficiency. Another feature is to optimize district energy retail by provide optimal pricing scheme for heating, cooling and electricity to end users to incorporate district to grid demand response.", + "laborHours": 0.0, + "languages": [], + "name": "District EnErgy Planner (DEEP) v2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/deep_ceg_lbl/deep_ceg_lbl/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-06", + "metadataLastUpdated": "2021-09-21" + }, + "description": "The Exploration Toolkit (ExTK) is a reusable Extended Reality (XR) system developed for incorporating and exploring 3-Dimensional (3-D) computer aided design (CAD) models in XR, with a primary focus on Augmented Reality (AR). The ExTK consists of a Developer Mode and a User Mode. In Developer Mode, ExTK provides developers with the ability to easily import 3-D CAD models and activate desired exploration functionality and layout. Multiple models can be added to a single instantiation of the ExTK using Unity's Scene capability. Exploration functions include scaling, rotating, explode/contract, animations, hiding parts, submodules, and measurement functions. In User Mode, ExTK provides a menu system that allows users to select models and initiate exploration functions. ExTK is architected for reusability and developers can customize the ExTK layout and functions according to application needs. ExTK is designed to be hardware agnostic, although initial development focused on the Microsoft HoloLens as the primary deployment platform. The ExTK is developed using the Unity Game Engine Development Platform. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. 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CoMTE outperforms state-of-the-art explainability methods on several different machine learning frameworks and data sets in comprehensibility and robustness. CoMTE can be used to debug machine learning frameworks and gain a better understanding of the underlying multivariate time series data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1686 O", + "laborHours": 471.2, + "languages": [ + "Jupyter Notebook", + "Rust", + "Python" + ], + "name": "CoMTE: Counterfactual Explanations for Supervised Machine Learning Frameworks on Multivariate Time Series Data", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CoMTE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-08-06", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This repository contains data ingestion, feature extraction, and analysis code used in NREL Technical report \"Clustering Analysis of Commercial Vehicles Using Automatically Extracted Features from Time Series Data.\" The code is written in Python. The ETL and feature extraction code must be run in a Spark context. The analysis code can be run without Spark, provided you have pre-computed features in a CSV file. Analysis code related to the NREL Technical Report NREL/TP-2C00-74212. Includes PySpark functions to perform trip segmentation and feature extraction over big time series data in Apache Spark. Includes \"domain specific\" features such as Aerodynamic Speed (ft/s), Characteristic Acceleration (ft/s2), Percent Below 55 (%), Percent Zero (%), Stops Per Mile, Average Speed (mph), Maximum Speed (mph), and Speed Standard Deviation (mph). Includes Pyspark UDF to compute \"domain agnostic\" features using the TSFresh library. This software record also includes the analysis notebooks and code to generate the results in the previously mentioned technical report.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Code Artifact for: Clustering Analysis of Commercial Vehicles Using Automatically Extracted Features from Time Series Data [SWR-21-96]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/clustering-analysis-domain-agnostic-features-2018", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-06", + "metadataLastUpdated": "2023-03-15" + }, + "description": "This tool can be used to determine a least-cost feedstock mix from crop residue, energy crop and MSW to meet conversion specifications, while also identifying appropriate depot locations and size, given that depot can be co-located with the biorefinery or can be located in any counties in the biofinery’s supply shed.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Multi-feedstock Supply Chain Optimization Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/MFSCO", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "sarat@ornl.gov" + }, + "date": { + "created": "2021-08-06", + "metadataLastUpdated": "2021-08-06" + }, + "description": "Climate kernels for Co-design These kernels originate from the Energy Exascale Earth System Model (E3SM). They are intended for sharing with interested parties for co-design purposes.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "E3SM Co-design Kernels", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/codesign-kernels", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-09", + "metadataLastUpdated": "2024-07-23" + }, + "description": "EUForia is a general-purpose model checker that solves reachability problems in dynamical systems. It implements an abstraction-refinement process in which the system is iteratively approximated until it can prove or disprove that a system state is reachable. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-3020 O", + "laborHours": 23499.2, + "languages": [ + "C++", + "Shell", + "Nix", + "CMake", + "Makefile", + "Python" + ], + "name": "EUForia", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/euforia", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "devarakondar@ornl.gov" + }, + "date": { + "created": "2021-08-11", + "metadataLastUpdated": "2021-08-11" + }, + "description": "The AGU/AMS Abstract Search and Display Software is a standalone web application which enables the searching, storing, and displaying of abstracts featured at the annual American Geophysical Union (AGU) and American Meteorological Society (AMS) meetings. This application is designed for those who wish to host a standalone web application and feature a select subset of posters and talks scheduled for the AGU/AMS meetings. Please read the entirety of this README.md file before attempting to download and use the application. There are three views available via the UI: Lookup - enables searching and submitting posters for displaying on the summary view Manual Submission - allows individual manual submission of posters given a poster ID Summary - displays all posters submitted by users from the lookup view", + "laborHours": 0.0, + "languages": [], + "name": "AGU/AMS Abstract Search and Display Software", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/arm-data-science-integration/poster-api-wrapper", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-08-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The EXPERT toolkit contains next-gen AI capabilities to detect, anticipate, and reason about proliferation expertise evolution from unstructured dynamic multilingual real-world data.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/EXPERT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/EXPERT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-11", + "metadataLastUpdated": "2021-08-11" + }, + "description": "EScp is a high speed transfer tool with a similar command line syntax to scp. Unlike SCP it is designed to transfer files at high speed, thus far we have been able to show 100gbit/s transfers, although I expect that the throughput should scale in proportion to the network interface, i.e. I expect 400gbit/s performance on our 400gbit/s test bed. EScp achieves good performance through an innovative design (multithreaded, zero copy transfers), along with pluggable filters and I/O engines. As an example, you can switch from POSIX i/O to UIO by checking a different engine. It also natively supports encryption, and cheksums for file verification and transport security. AAA is through standard SSH (same as SCP). By taking advantage of filters, EScp supports transferring unstructured data and/or I/O to non-posix data sources. Examples include streaming data (i.e. from equipment), transferring data to the cloud, and/or supporting non-posix file systems (like HPSS).", + "laborHours": 0.0, + "languages": [], + "name": "ESnet Secure Copy (EScp) v0.6", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/EScp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-11", + "metadataLastUpdated": "2021-08-13" + }, + "description": "1. Segmentation We provide scripts for the model definition of the U-net architecture adapted from: https://github.com/jvanvugt/pytorch-unet/blob/master/unet.py We developed scripts for preparing the lung segmentation data set. We developed scripts for training the U-Net architecture. We developed scripts for applying the trained U-Net model to perform the ROI Hide and Seek protocol on the classification dataset to create the modified dataset. 2. Classification We provide scripts for the training of the COVID-Net models provided by Linda Wang, this code is adapted from her github repository: https://github.com/lindawangg/COVID-Net/tree/d7b36831d854f57de5bc7557217f5439e86e016f. These scripts were modified to save training log information as well as to load the provided models in their github repo. We developed scripts for training standard Neural Network Models (resnet 50, vgg 11, Alexnet) on the COVID datsets along with the ROI Hide and Seek altered datasets.", + "laborHours": 0.0, + "languages": [], + "name": "ROI Hide and Seek Protocol v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electro1111/COVID_19_CXR_CLASSIFICATION", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "We developed an analysis framework for quantitatively interpreting results from multi-color fluorescence microscopy data. When the emission signal from fluorescent probes (i.e. from biological microscopy or in single-particle microscopy) is spectrally separated before detection, the resulting signals contain information about the strengths of each probe. We built a model to deconvolve the raw data into quantitative descriptions of either of the wavelength of a single probe or the relative strengths among multiple probes. This approach requires only spectrally separating the image data into two or more channels, as opposed to fully resolving the spectral profile, thus allowing other microscopy techniques to be used simultaneously. Our analysis framework incorporates the response features of the optical and imaging elements used to produce the spectral separation, yielding highly quantitative interpretations of the underlying behaviors that give rise to the data.", + "laborHours": 0.0, + "languages": [], + "name": "Quantitative analysis method for multi-color microscopy", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ryand-LANL/DualColorAnalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "MF-LBM-nanopore is a high-performance lattice Boltzmann code for direct numerical simulation of flow in nano-porous media with confinement effects. The main features of the code include: 1) implemented with adsorption and slip modules that enable simulation of flow in nano-porous media with confinement effects; 2) extensively optimized for modern SIMD/SIMT processors/co-processors, such as GPU; 3) based on MPI-OpenACC/OpenMP hybrid programing model that enables high portability. The main application of the code is in modeling shale gas flow.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "MF-LBM-nanopore", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "The era of exascale computing opens new venues for innovations and discoveries in many scientific, engineering, and commercial fields. However, with the exa flops also come the extra-large high-dimensional data generated by high performance computing. High-dimensional data is presented as multidimensional arrays, aka tensors. The presence of latent (not directly observable) structures in the tensor allows a unique representation and compression of the data by classical tensor factorization techniques. However, the classical tensor methods are not always stable or they can be exponential in their memory requirements, which makes them not suitable for high-dimensional tensors. Tensor train (TT) is a state-of-the-art tensor network introduced for factorization of high-dimensional tensors. TT transforms the initial high-dimensional tensor in a network of three-dimensional tensors that requires only a linear storage. Many real-world data, such as, density, temperature, population, probability, etc., are non-negative and for an easy interpretation, the algorithms preserving non-negativity are preferred. Here, we introduce a distributed non-negative tensor-train and demonstrate its scalability and the compression on synthetic and real world big datasets.", + "laborHours": 0.0, + "languages": [], + "name": "DNTTD (Distributed Non-Negative Tensor Train Decomposition)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyDNTNK", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "A python class has been developed to help streamline the creation of customizable Github applications Python Class for Github Application Development (Py-CGAD). Py-CGAD contains an interface for interacting with Github’s RESTful API by automatically handling authentication and providing common functionality through simple methods. These methods include uploading files to a repository, posting and getting statuses among others. Py-CGAD is generic and can be used as a template for quickly building a variety of different application of interest to the mission of the lab and the public in general.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Python Class for Github Application Development (Py-CGAD)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "XSPIKE (eXplore the SPIKE protein) identifies sites of high variability (high entropy) in amino acid sequences of the Spike protein of the SARS CoV-2 virus. Among these sites, it further identifies correlations between pairs of them, and provides both graphical and tabular display of that information. It also provides a table of occurrences of co-occurring patterns found among natural sequences, featuring associations within those most highly variable sites to emphasize common covariation patterns; this table includes information about the number of sequences in which those patterns are seen, broken out by continent, and provides as context a list of mutations for each pattern that corresponds to the differences between the reference sequence (usually the Wuhan form) and the most common full sequence that exhibits that pattern.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "xSpike", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-27" + }, + "description": "The copyrightable material is a set of software whose goal is to explore the use of Monte Carlo methods at extreme processor counts. This will include application software, libraries, middleware, various system software, and possibly compilers and translators", + "laborHours": 0.0, + "languages": [], + "name": "Billion-Core Monte Carlo", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/c2nova", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-19" + }, + "description": "BdNMC is a Monte Carlo that simulates the creation, propagation and detection of dark sector particles in particle physics experiments. Dark sector particles are defined as any particles which are weakly coupled to matter and are expected to travel large distances in matter without interaction. The code takes input from some initial distribution or list of Standard Model particles and generates a list of dark sector particles. The generated dark sector particles are propagated to a defined detector volume, where they are then checked for their probability to interact with the detector through either decay or scattering. The code outputs an expected number of interaction events to the user, and may optionally produce an additional output file of all of the particles simulated by the code for each interaction event. This contribution makes corrections and updates to several of the physics formulas and functions implemented in the BdNMC simulation code related to Coherent Captain Mills experiment's physics analyses.", + "laborHours": 0.0, + "languages": [], + "name": "Contribution to Open Source Software BdNMC", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/BdNMC_LANL", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "PANACEA provides a means for generating unique configurations. The primary motivation for its development stems from the need to generate unique configurations for the purpose of training machine learned interatomic potentials. PANCEA is a C++ library with python and linux scripts. The C++ library is the engine which provides can be installed and used to measure the disorder/order of a system via the information entropy. The python and linux scripts provide useful helper functionality such as visualization of files that can be output from the library.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Portable Approach for Novel Arrangements using a Cross Entropy Algorithm (PANACEA)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "Amanzi provides a flexible and extensible multiphase, multicomponent, flow and reactive transport simulation capability for environmental applications. It also includes thermal and geomechanical processes in the subsurface. It includes toolsets for meshing infrastructure, discretizations, and solvers for the resulting nonlinear systems of equations. The framework Arcos (LA-CC-14-053), provides the internal data management, process and coupling interfaces, and runtime configuration through a directed acyclic graph [1]. The code is parallel and makes use of open-source parallel frameworks such as Trilinos [2] developed at Sandia National Laboratory and PETSc (the Portable Extensible Toolkit for Scientific Computing) [3] developed at Argonne National Laboratory. Rudimentary geochemistry capabilities are included in Amanzi, while a state-of-the-art geochemistry support is provided through the Alquimia interface library, which can use well established open-source geochemistry engines (e.g., PFLOTRAN or CrunchFlow). In addition, support for GPUs is being developed through the Kokkos [4] performance portability library. Amanzi is used to model contaminant migration at various DOE waste sites (e.g., Hanford, and Savannah River), and is generally applicable to contaminant migration in groundwater under partially saturated nonisothermal conditions and its interaction with surface water. Development of Amanzi is funded by the DOE Office of Science, primarily through programs in the DOE Office of Biological and Environmental Research (BER) and internally through LDRD. [1] Coon, E. T., J. D. Moulton, and S. L. Painter, Managing complexity in simulations of land surface and near-surface processes, Environmental Modelling & Software, 78, pp. 134-149, 2016. http://dx.doi.org/10.1016/j.envsoft.2015.12.017 [2] Trilinos, https://trilinos.github.io/ [3] Portable, Extensible Toolkit for Scientific Computation, https://www.mcs.anl.gov/petsc/ [4] Kokkos C++ Performance Portability Programming EcoSystem, https://github.com/kokkos", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Amanzi 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "The Advanced Terrestrial Simulator (ATS) is a code for solving multiscale ecosystem-based, integrated, distributed hydrology. It builds on the multi-physics framework and toolsets (mesh infrastructure, discretizations, solvers) provided by Amanzi (original release LA-CC-10-069, new release pending in FCI) and is a key driver of development of the flexible multiphysics framework Acros (LA-CC-14-053). Capabilities are largely based on solving various forms of variably saturated subsurface flow (e.g., Richards equation) coupled to a surface flow equation, along with the needed sources and sinks for ecosystem and climate models. This can (but need not) include thermal processes (especially ice for frozen soils), evapo-transpiration, albedo-driven surface energy balances, snow, biogeochemistry, plant dynamics, deformation, solute and contaminant transport, erosion and sediment transport, and much more. It is unique in its thermal integrated hydrology capabilities, which include thermal energy with freeze/thaw processes in both the surface and subsurface water, and its reactive transport capabilities, which are also coupled in both surface and subsurface water. Like Amanzi, the ATS uses the Alquimia interface library to couple its transport capabilities with biogeochemical reaction engines (e.g., PFLOTRAN and CrunchFlow). The ATS has been used to explore how a wide range of ecosystems function under a variety of environmental drivers, including the evolution of polygonal permafrost in the warming arctic [1,2], the impact of forest fires on the water quality of streams in the Jaramillo watershed, and the impact of seawater intrusion on vegetation in salt water marshes on the Delaware. \n\n[1] Painter, S. L., E. T. Coon, A. L. Atchley, M. Berndt, R. Garimella, J. D. Moulton,D. Svyatskiy, and C. J. Wilson, Integrated surface/subsurface permafrost thermal hydrology: Model formulation and proof-of-concept simulations,Water Resour. Res.,52,6062–6077, 2016. https://doi.org/10.1002/2015WR018427\n[2] Jafarov, E. E., E. T. Coon, D. R. Harp, C. J. Wilson, S. L. Painter, A. L. Atchley, V. E. Romanovsky, Modeling the role of preferential snow accumulation in through talik development and hillslope groundwater flow in a transitional permafrost landscape, Environmental Research Letters, 13(10):105006, 2018. https://doi.org/10.1088/1748-9326/aadd30", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Advanced Terrestral Simulator (ATS) 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-08-16", + "metadataLastUpdated": "2021-08-16" + }, + "description": "The pySMARTS module contains functions for calling SMARTS: Simple Model of the Atmospheric Radiative Transfer of Sunshine, from NREL, developed by Dr. Christian Gueymard. SMARTS software can be obtained from: https://www.nrel.gov/grid/solar-resource/smarts.html Users will be responsible to obtain a copy of SMARTS from NREL, honor it's license, and download the SMART files into their PVLib folder. This wrapper is shared under a BSD-3-Clause License, and was originally coded in Matlab by Juan Russo (2001), updated and ported to python by Silvana Ayala (2019-2020).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "pySMARTS: SMARTS Python Wrapper (Simple Model of the Atmospheric Radiative Transfer of Sunshine)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pySMARTS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "Version: 0.18" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-16", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The Intermode Communication Protocol Wrapper, or Icypaw, structures and facilitates communication between endpoints in a network. It is used to connect various independent software and hardware components into one loosely organized system controllable from one or more locations. The code uses the MQTT protocol to communicate and enhances it with a useful framework. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8293 O", + "laborHours": 4909.6, + "languages": [ + "Python" + ], + "name": "Icypaw", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IcyPaw", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-17", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Reduced-order Models (ROMs). ROMs are \"compressed\" approximations of high-fidelity computational models. Implementing ROM methods in production codes is typically intrusive, i.e. the native codes must be adapted and modified, with individual ROM methods reimplemented in every application code. This clearly constitutes an obstacle to users who want to use ROMs. To address this, we have developed Pressio, which is a C++ header-only ROM library that can be used by an application code in a non-intrusive fashion. The main objectives behind the design of Pressio are: (a) support for general computational models (data structures, PDE types); (b) heterogeneous hardware (CPU, GPU); (c) performance; and (d) extensibility. Using metaprogramming techniques, Pressio detects and leverages the application?s native linear algebra data structures (e.g. vector and matrix) to run the ROM methods. The application only needs to expose the velocity vector and Jacobian matrix via an adapter class. Pressio checks at compile time that the target application meets the correct API. The library is structured in several modular packages including (a) non-linear least-square solvers (e.g. Gauss-Newton with and without line-search); (b) singular value decomposition (for the computation of the ROM generalized coordinates) and (c) algebraic hyper-reduction.SAND2019-5878 M", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Pressio v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pressio", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "parishcm@ornl.gov" + }, + "date": { + "created": "2021-08-17", + "metadataLastUpdated": "2021-08-17" + }, + "description": "Applies machine learning to analyze individual or sets of X-ray energy dispersive spectroscopy spectrum images acquired in the electron microscope.", + "laborHours": 0.0, + "languages": [], + "name": "EDS Montage", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/nmp/eds_montage", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This software improves upon the Clifford gate+T gate magic state strong simulation algorithm by Brayvi and Gosset. It provides a better stabilizer state decomposition that scales as 2^{0.463t}, an improvement over 2^{0.468t}, for t T gate magic states. This code enables simulations of universal quantum computing with that asymptotic scaling cost. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525 SAND2020-14293 O", + "laborHours": 0.0, + "languages": [], + "name": "Stabilizer Rank Strong Simulation v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Stabilizer-Rank-Strong-Simulation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2024-09-19" + }, + "description": "Universal quantum circuits can be formulated in the Pauli measurement-based formalism as input T gate magic states, Clifford gates, and then multi-Pauli measurements. This code simulates single-Pauli measurements to show some theoretical bounds on the cost of full multi-Pauli measurements. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2020-14080 O", + "laborHours": 0.0, + "languages": [], + "name": "Gauss Sum Strong Simulation v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Gauss-Sum-Strong-Simulation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-18" + }, + "description": "The SPARSIFY algorithm implemented by the code allows for classical simulation of universal quantum computer sample outcomes. The code sparsifies the stabilizer decomposition of a qubit t-tensored T gate magic state to some additive error. This is accomplished by either independent L1 sampling or with correlated L1 sampling to supplement an independent subset, which offers a more efficient decomposition: for a given t, a sparser decomposition is sufficient with correlated L1 sampling to satisfy a given additive error. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8296 O", + "homepageURL": "https://s3miclassical.com/gitweb", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Weak Simulation v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://s3miclassical.com/gitweb", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-18" + }, + "description": "Pilgrim is a profiling tool for MPI applications. It tracks the communication activities in an MPI application and records them as logs for further analysis. It allows users to have a better insight into the execution of their application and identify potential performance bottlenecks.", + "laborHours": 0.0, + "languages": [], + "name": "PILGRIM", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/pilgrim", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2023-07-21" + }, + "description": "As the size of turbulent flow simulations continues to grow, in situ data compression is becoming increasingly important for visualization, analysis, and restart checkpointing. For these applications, single-pass compression techniques with low computational and communication overhead are crucial. In this paper we present a deep-learning approach to in situ compression using an autoencoder architecture that is customized for three-dimensional turbulent flows and is well suited for contemporary heterogeneous computing resources. The autoencoder is compared against a recently introduced randomized single-pass singular value decomposition (SVD) for three different canonical turbulent flows: decaying homogeneous isotropic turbulence, a Taylor-Green vortex, and turbulent channel flow. Our proposed fully convolutional autoencoder architecture compresses turbulent flow snapshots by a factor of 64 with a single pass, allows for arbitrarily sized input fields, is cheaper to compute than the randomized single-pass SVD for typical simulation sizes, performs well on unseen flow configurations, and has been made publicly available. The results reported here show that the autoencoder dramatically outperforms a randomized single-pass SVD with similar compression ratio and yields comparable performance to a higher-rank decomposition with an order of magnitude less compression in regard to preserving a number of important statistical quantities such as turbulent kinetic energy, enstrophy, and Reynolds stresses.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AEflow (Autoencoder fluid flow compression network) [SWR-22-29]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/AEflow", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This package is a set of extensions to MOOSE (https://moose.inl.gov) adding anisotropic graphite material models for irradiation creep and swelling. The goal of the package is to provide a framework to model graphite components for use in future high temperature nuclear reactors.", + "laborHours": 0.0, + "languages": [], + "name": "GOOSE (GRAPHITE OBJECT-ORIENTED SIMULATION ENVIRONMENT)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/goose", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-18" + }, + "description": "A digital twin for synchrotron-based tomography for generating synthetic datasets from ground-truth phantoms. The code outputs greyscale projection images / tomographic volumes with realistic artifacts such as noise and phase-contrast and emulates their dependence on the acquisition parameters defining the beam and detector configuration. Some ground-truth phantoms are included with the code.", + "laborHours": 0.0, + "languages": [], + "name": "TomoTwin: A simple digital twin for synchrotron tomography", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aniketkt/TomoTwin", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-18" + }, + "description": "Real-time steering of time-resolved or in-situ X-ray tomography requires capturing changes in morphological descriptors in a sample (e.g., porosity, particle size, and crack width) during continuous data acquisition. 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As a faster and unsupervised alternative, a feature-extraction approach using a convolutional autoencoders was developed, where the latent space of the encoder responds to relative changes in morphology with-out prior knowledge of the morphological descriptors.", + "laborHours": 0.0, + "languages": [], + "name": "TomoEncoders: 3D Autoencoders for feature extraction in X-ray tomography", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aniketkt/TomoEncoders", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-19", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This code is designed to reconstruct magnetic field deflections, and thus the path-integrated magnetic field, from sets of proton images at two distinct proton probe energies. A differential evolution (DE) algorithm is used to iteratively update a population of solution candidates of the magnetic deflections of the protons for reconstructing the input images, selecting improved candidates as they are discovered. 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Data analysis is both challenging and time consuming. Novices often rely on the assistance of an expert, such as the instrument scientist who supported them at the facility where the experiment was performed, to analyze their data. The high flux provided by modern facilities makes it possible to study dozens of samples or sample conditions during a single trip. Ultimately, the high throughput of modern instruments limits access to instrument scientists. A bottleneck in the research effort results that reduces facility productivity. Sas-temper seeks to address this problem, as well as the intrinsic difficulties of being confident in non-linear least squared fitting of data, by providing tools that automate much of the manual process of initial data fitting and refinement, as well as by providing tools for characterizing the nature of the parameter space that fits the measured data. The tools provided by sas-temper help small-angle scattering practitioners transition data into results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "sas-temper", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/wt3/sas_temper", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-19", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This software package contains utilities for ingesting battery cycling data from various equipment and converting it to a common file format including metadata. 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The model is implemented using Tensorflow and the training dataset is generated using physics-based atomistic simulations. Custom codes are written to handle the resampling of diffraction images to oversampling ratios appropriate for the neural network model.", + "laborHours": 0.0, + "languages": [], + "name": "NEURAL NETWORK FOR COHERENT DIFFRACTION IMAGE INVERSION", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hyiprc/3D-CDI-NN", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-19", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This package estimates future potential for utility customers to provide various forms of demand response (DR) based on granular forecasts of energy demand by customer type and a database of DR-enabling technologies.", + "homepageURL": "https://buildings.lbl.gov/download-phase-3-dr-potential-study", + "laborHours": 0.0, + "languages": [], + "name": "DR-Path", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://buildings.lbl.gov/download-phase-3-dr-potential-study", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2021-08-20" + }, + "description": "This study develops a neural network-based approach for emulating high-resolution modeled precipitation data with comparable statistical properties but at greatly reduced computational cost. The key idea is to use combination of low-and high- resolution simulations to train a neural network to map from the former to the latter. Specifically, we define two types of CNNs, one that stacks variables directly and one that encodes each variable before stacking, and we train each CNN type both with a conventional loss function, such as mean square error (MSE), and with a conditional generative adversarial network (CGAN), for a total of four CNN variants. We compare the four new CNN-derived high-resolution precipitation results with precipitation generated from original high resolution simulations, a bilinear interpolater and the state-of-the-art CNN-based super-resolution (SR) technique. Results show that the SR technique produces results similar to those of the bilinear interpolator with smoother spatial and temporal distributions and smaller data variabilities and extremes than the original high resolution simulations. While the new CNNs trained by MSE generate better results over some regions than the interpolator and SR technique do, their predictions are still not as close as the original high resolution simulations. The CNNs trained by CGAN generate more realistic and physically reasonable results, better capturing not only data variability in time and space but also extremes such as intense and long-lasting storms. The new proposed CNN-based downscaling approach can downscale precipitation from 50~km to 12~km in 14~min for 30~years", + "laborHours": 0.0, + "languages": [], + "name": "DSGAN", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lzhengchun/DSGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2021-08-20" + }, + "description": "Massively Parallel, Portable, and Reproducible Tractography (MaPPeRTrac) is a brain tractography workflow for high performance computing. It incorporates novel technologies to simplify and accelerate neuroimaging research.", + "laborHours": 0.0, + "languages": [], + "name": "MaPPeRTrac", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MaPPeRTrac", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The application is being developed with the goal of preventing the entropy of all the different single purpose applications. This application utilizes a framework that enables different file formats to be read and understood through plugins dynamically loaded to the main application containing the framework. The main application provides interoperability to all the different plugins, this allows each file format to convert to every other file format that has been read. There is no theoretical limit to the number of plugins that can be used by the application. Even though the plugins may be individually written and serve a purpose like single use scripts, the plugins can only be used with the main application, this forces the application and plugins to be linked. In theory this will force better data management, or at least the bundling of the main application with the plugins.", + "laborHours": 0.0, + "languages": [ + "C++", + "JavaScript" + ], + "name": "Vulcan Digital Engineering Application", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/VDEA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The number of power outages have been on the rise as extreme weather patterns have been occurring more frequently due to climate change. These outages have an economic impact in the billions of dollar. The modernization of the power grid and adoption of high penetration of distributed generation such as wind and solar have the potential to reduce the number and length of time of these power outages. However, planners and operators need a way to value the resilience the distributed assets provide to the grid. PowDDeR is a tool that allows them to evaluate the resilience each asset provides as well as how they provide resilience over the connected network.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Power Distribution Designing For Resilience Application", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/PowDDeR-Python", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2023-03-13" + }, + "description": "PyEmission is a Python library for estimation of vehicular emissions and fuel consumption. This tool covers a wide range of light duty motor vehicles including passenger car, SUV, passenger truck, and light commercial truck. The tool only takes second-by-second driving cycle and vehicle characteristics data as inputs and generate results of vehicular emissions (CO2, CO, NOx, and HC) and fuel consumption.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Python Library For Vehicular Emission Estimation", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/PyEmission", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2023-03-13" + }, + "description": "This is a simple wrapper script that will be used to enable the use of a two-factor authentication mechanism for downloading NCRC controlled codes through the popular \"Conda\" distribution mechanism.", + "laborHours": 0.0, + "languages": [], + "name": "Ncrc-client", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/ncrc-client", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-23", + "metadataLastUpdated": "2021-08-23" + }, + "description": "The Ducted Assembly Steady State Heat transfer software (DASSH) performs full core, steady state, subchannel temperature calculations for hexagonal, ducted assemblies. DASSH is targeted for use in the early stages of the reactor design process when assembly characteristics may not be defined or are undergoing considerable changes. DASSH provides a relatively rapid assessment of the temperature and flow distribution to inform reactor design updates and analysis.", + "laborHours": 0.0, + "languages": [], + "name": "DUCTED ASSEMBLY STEADY STATE HEAT TRANSFER SOFTWARE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dassh-dev/dassh", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-23", + "metadataLastUpdated": "2021-08-24" + }, + "description": "This software uses AI tools for enhanced functional imaging using Lorentz transmission electron microscopy by retrieving phase shift at higher spatial resolution, and under noisy conditions. This is a companion code for a publication that is currently being submitted (APT # 164160).", + "laborHours": 0.0, + "languages": [], + "name": "AD_LTEM", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/danielzt12/AD_LTEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-24", + "metadataLastUpdated": "2021-08-24" + }, + "description": "cuSZ is a CUDA implementation of the world-widely used SZ lossy compressor. It is the first error-bounded lossy compressor on GPUs for scientific data, which significantly improves SZ's throughput in GPU-based heterogeneous HPC systems.", + "laborHours": 0.0, + "languages": [], + "name": "cuSZ:CUDA-based Error-Bounded Lossy Compressor for Scientific Data Scientific Data", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/szcompressor/cuSZ", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-24", + "metadataLastUpdated": "2021-08-24" + }, + "description": "kSZ is a Kokkos-based implementation of the world-widely used SZ lossy compressor. We use Kokkos because it provides abstractions for both parallel execution of code and data management, which can be used to support portable implementation across different accelerator technologies. Kokkos can support OpenMP/OpenMPTarget, oneAPI, Pthreads, and CUDA as backend programming models.", + "laborHours": 0.0, + "languages": [], + "name": "kokkosSZ (kSZ) A Portable Cellerator Implementation of SZ using Kokkos Programming Model", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/szcompressor/kokkosSZ", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-24", + "metadataLastUpdated": "2021-08-24" + }, + "description": "x-ray fluorescence (XRF) imaging typically involves the creation and analysis of 3D data sets, where at each scan position a full energy dispersive x-ray spectrum is recorded. This allows one to later process the data in a variety of different approaches, e.g., by spectral region of interest (ROI) summation with or without background subtraction, principal component analysis, or fitting. XRF-Maps is a C++ open source software package that implements these functions to provide a tool set for the analysis of XRF data sets.", + "laborHours": 0.0, + "languages": [], + "name": "XRF-MAPS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdvancedPhotonSource/XRF-Maps", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-24", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The Deep Lynx MOOSE Adapter connects the Deep Lynx data warehouse with any MOOSE executable. The Adapter can receive events from Deep Lynx and will take incoming data to format a template input file for the MOOSE executable. Returns from the MOOSE run are sent back to Deep Lynx for use by other applications.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deep Lynx MOOSE Adapter", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-MOOSE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "obriense@ornl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "Determine uranium and plutonium concentrations of solutions using K-edge densitometry. Returns estimates, including the uncertainty, for the mass densities of U, Pu, Np, Am, Bi, and the matrix. GUI that allows users to select high resolution gamma spectrum files of measurements of vials of solutions containing U/Pu. These spectra are fit to find to find k-edge and x-ray fluorescence peaks. The user can adjust and set fit variables, such as vial size, spectrum parameters, detector specifications, and attenuation coefficients. Technique is an accurate and rapid assay technique commonly used in nuclear fuel reprocessing facilities. The measurement is a typical international safeguards tool for accountancy of U and Pu for dissolved product solutions.", + "laborHours": 0.0, + "languages": [ + "Fortran", + "Visual Basic" + ], + "name": "MEKED Fit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/meked/HybridKedge/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/meked/HybridKedge", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "QuanSimBench is a software program that performs a gate-by-gate simulation of a quantum computer with a full state vector formulation. It simulates a simplified version of Shor's algorithm with increasing number of qubits until resources are exhausted. The score (states/s) is how fast the Approximate Quantum Fourier Transform can be computed (the modular exponentiation is not timed). The goal is to quantify the ability of a computer to simulate ideal quantum circuits.", + "laborHours": 0.0, + "languages": [], + "name": "QuanSimBench", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/datavortex/QuanSimBench", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "The tool inputs cryo electron microscopy (cryo-EM) 3-D reconstructions and an accompanying 3-D atomistic model of a molecular complex. It uses molecular simulation to guide the atomistic model into the 3-D reconstruction, making the atomistic model more consistent with the 3-D reconstruction. This will not be distributed by LANL. This was designed with the intention of being open to the public.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Cryo electron microscopy fitting ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "The number of nucleic acid sequences in GenBank has been growing exponentially for almost 40 years. With the rapid adoption of high throughput, relatively inexpensive sequencing devices, the amount of available “raw”, unassembled sequence in the Sequence Read Archive (SRA) is significantly greater than the traditional GenBank “complete” and “WGS” sequence categories combined. The SRA is an invaluable data trove that contains sequence reads that reflect the enormous diversity of modern genomic science from “A” (aardvark gut metagenome) to “Z” (zebra finch auditory lobule RNA-seq). \n\nHowever, as a result of the explosive growth of the SRA traditional methods for querying sequence databases (e.g. BLAST) can no longer keep up. Instead of finding the list of best matching database sequences for a given search query (usually accompanied by pairwise sequence alignments), new search algorithms have been developed to identify the “samples” (i.e. collections of short, sequenced reads from a single biological sample) that are most “similar” to the query sequence. These search algorithms represent collections of sequences (both the query and the database entries) as mathematical sets of short, fixed-length sequences (“k-mers”) and then rank potential matches between the query set and each of the database sets using the fraction of k-mers that are shared between each pair of sets (e.g. the Jaccard distance).\n\nDue to the large amount of sequence data stored in the SRA, a naïve, “brute-force” approach that attempts to enumerate and store the k-mers associated with each biological sample in the SRA will quickly exhaust the available storage of most high-performance computing centers. Instead, the primary innovation of the new search algorithms is the application Bloom filters (and related computer science data structures) to the massive sequence search problem. A Bloom filter provides a pragmatic trade-off between “set size” and “match certainty”. By using one or more hash functions to map k-mers to a smaller set of numbers, the size of k-mers used to represent a collection of sequence reads can be dramatically reduced. This brings the added benefit that smaller set sizes can be computationally compared more quickly. However, there is no bioinformatic “free-lunch” – the similarity between two Bloom filters now only approximates the similarity between the underlying k-mer sets. Thanks to the properties of the hash functions used to build the Bloom filters, the approximation is “one-sided” – the Bloom filter-based similarity can be greater, but never less, than the true k-mer set similarity. This leads to a non-zero probability of false discovery, where a predicted database match to a query sequence is not actually similar to the query. Thankfully, the probability of a false negative (i.e. failing to report a database match that is actually similar to the query) is zero. In addition, there is practical statistics-based guidance that enables implementing a Bloom filter with a known, user-specified false discovery rate.", + "laborHours": 0.0, + "languages": [], + "name": "KWAGE (FORMERLY BIGSI++)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Bioinformatics/KWAGE", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": " The Block-Structured Adaptive Mesh Refinement (BAMR++) application provides block-structured adaptive mesh refinement data structures and an execution model for parallel computing architectures. This application also includes example tests that exercise iteration patterns over the mesh entities (cells, edges, faces). The application is written in C++.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "BAMR++", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-09-24" + }, + "description": "PYSEQM is a package for performing semi-empirical quantum mechanical (SEQM) simulations on molecular systems utilizing PyTorch. SEQM simulations determine molecular properties (energy, electron density, dipole moment, ect.) by solving an approximate Schrödinger equation for the motions of electrons in a molecule. The use of PyTorch provides three specific advantages. First, it allows the calculations to be offloaded to GPU accelerators, giving an order of magnitude increase in speed. Second, back propagation is used to get atomic forces (derivative of the total energy with respect to atomic position) at the same computational cost as the energy calculation itself. Finally, the use of PyTorch makes for a natural interface to modern machine learning methods, which can be used to adjust the semi-empirical parameters build into SEQM methods. Additionally, PYSEQM implements various other optimizations for performing quantum mechanics based molecular dynamics, including SP2 for rapid GPU based solution of the self-consistent field algorithm, and the extended Lagrangian method for rapid QM-MD.", + "laborHours": 0.0, + "languages": [], + "name": "PYSEQM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PYSEQM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "This software simulates drawdown in an underground reservoir or aquifer using superposition of the Theis solution. Examples in the repository perform physics-informed machine learning in order to train a neural network to manage reservoir or aquifer pressures.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "MultiTheisDP", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "The River and Basin Profiler (RaBPro) represents a set of python tools that help characterize and analyze rivers and watersheds from a digital elevation model (DEM). RaBPro contains three primary functions: First, RaBPro will delineate watersheds for any given points within a DEM. Second, RaBPro will extract the elevation and slope profiles for flowlines (rivers) within the DEM. Finally, RaBPro provides convenient zonal statistics functionality for characterizing watersheds using auxiliary data the the user provides.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "River and Basin Profiler", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "Two Python files, entSpectroscopy.py and simulateCircuitsScript.py, containing the necessary code to reproduce the experiments for our recent work \"Qubit-efficient entanglement spectroscopy using qubit resets\" LA-UR-20-25416 (https://arxiv.org/abs/2010.03080). This paper described new quantum algorithms, also known as circuits, and described experiments testing these algorithms both on real quantum hardware and in simulators. The file entSpectroscopy.py contains functions which take parameters describing the input (e.g. input size) and output descriptions of quantum circuits by implementing the algorithms described in our paper. These circuit descriptions are created as `QuantumCircuit` objects using the Python library qiskit, and our simulation experiments use simulators provided by qiskit. The file also contains helper functions for processing the results of these circuits and for calculating the statistical uncertainty in the results, both according to formulas given in our paper. Finally, entSpectroscopy.py includes helper functions for easily preparing the qiskit simulator according to given noise parameters. The file simulateCircuitsScript.py demonstrates how we performed our experiments by calling functions in entSpectroscopy.py. This script takes as input parameters from the command line and hardcoded data, uses functions in entSpectroscopy.py to get circuit descriptions, simulates those circuits using qiskit, and outputs and plots the results.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Qubit-efficient entanglement spectroscopy", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "maldonadopbp@ornl.gov" + }, + "date": { + "created": "2021-08-29", + "metadataLastUpdated": "2021-08-29" + }, + "description": "In this simulation study, cycle-to-cycle fuel control was used to reduce CCV by injecting additional fuel in operating conditions with sporadic misfires and partial burns. An optimal control policy was proposed that utilizes 1) a physics-based model that tracks in-cylinder gas composition and 2) a one-step-ahead prediction of the combustion efficiency based on a kernel density estimator. The optimal solution, however, presents a tradeoff between the reduction in combustion CCV and the increase in fuel injection quantity required to stabilize the charge. Such a tradeoff can be ad- just by a single parameter embedded in the cost function.", + "homepageURL": "https://codeocean.com/capsule/8130780/tree", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Next-Cycle Optimal Fuel Control for Cycle-to-Cycle Variability Reduction in EGR-Diluted Combustion", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://codeocean.com/capsule/8130780/tree", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2021-08-30" + }, + "description": "Dakota GUI is a graphical analysis environment for Sandia’s Dakota software for optimization and uncertainty quantification. This version of the Dakota GUI includes new functionality such as plotting capabilities, Eclipse-based resource management, and integration with the SAW-IF Next Gen Workflow editor. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10629 O", + "homepageURL": "https://dakota.sandia.gov/download.html", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Dakota Graphical User Interface v.6.14", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v.6.14" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2021-08-30" + }, + "description": "Sandia's Dakota software supports science and engineering transformation through advanced exploration of simulations. Specifically, Dakota manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to: (1) enhance understanding of risk, (2) improve products, and (3) assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a computational model. Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. The algorithms implemented in Dakota aim to address challenges in performing these analyses with complex science and engineering models from desktop to high performance computers. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-10468 O", + "homepageURL": "https://dakota.sandia.gov/download.html", + "laborHours": 0.0, + "languages": [ + "C++", + "C++" + ], + "name": "DAKOTA (Design Analysis Kit for Optimization and Terascale) v.6.14", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "6.14" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2021-08-30" + }, + "description": "It is an unsupervised representation algorithm used to learn morphometric properties from cellular objects. Many similar/identical open source implementations are widely available in tensorflow, pytorch, etc. And ours is implemented in matlab.", + "homepageURL": "https://bbds.lbl.gov/project/lgg-cms", + "laborHours": 0.0, + "languages": [], + "name": "stacked predictive sparse decomposition (SPSD) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bbds.lbl.gov/project/lgg-cms", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2021-08-30" + }, + "description": "Calibr8 provides an application to rapidly prototype and perform material model calibration for complex plasticity models using advanced adjoint or forward sensitivity analyses for execution on massively parallel machines. These techniques can be orders of magnitude faster than traditional finite difference approaches for material model calibration. The underlying technology used in Calibr8 is automatic differentiation, which allows for the rapid implementation and testing of new plasticity models within its framework. Additionally, Calibr8 can perform adjoint-based error estimation to approximate discretization errors for user-implemented plasticity models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10630 O", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Calibr8 v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/calibr8", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2024-04-26" + }, + "description": "ComStock™ is an analytic methodology for modeling the energy usage of the commercial building stock within the United States of America. The commercial building stock is represented through a sampling of complex probabilistic distributions of various features of interest for modeling energy usage within commercial buildings. Each sample from these distributions is converted into a building energy model based on the features of that specific sample. Each building energy model can be simulated as is, but additional changes can be made to the model through addition of energy conservation measures, component faults, or other desired alterations. The results of the simulations are then processed to provide insights for various stakeholders, including but not limited to policy makers, engineers, and marketers.", + "laborHours": 0.0, + "languages": [ + "Ruby" + ], + "name": "ComStock™ [SWR-19-33 and SWR-20-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ComStock", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-08-31", + "metadataLastUpdated": "2024-06-18" + }, + "description": "HIPPO software is a Python implementation of the HIPPO technology. The HIPPO technology provides the computational and modeling capabilities for managing electricity market operations and for designing and prototyping future markets. The current software can solve the day-ahead unit commitment problem and perform simultaneous feasibility test. It can be used to handle industry scale electricity market.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "HIPPO Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-08-31", + "metadataLastUpdated": "2025-03-26" + }, + "description": "The International Jobs and Economic Development Impacts (I-JEDI) model is a free, online tool for analyzing the economic impacts of renewable energy development. The tool estimates the potential gross economic impacts of wind, solar, biomass and geothermal energy projects for a specific country.\n\nI-JEDI estimates the employment, earnings, gross domestic product, and output from the construction and operation of renewable energy projects and across the domestic supply chain. The model results include total economic impacts as well as impacts by industry (e.g., construction, manufacturing, banking services, etc.). This information helps align renewable energy action with key economic development goals. I-JEDI was developed through the USAID-NREL Partnership to support informed renewable energy decisions.", + "homepageURL": "https://www.i-jedi.org/scenario/start", + "laborHours": 0.0, + "languages": [], + "name": "I-JEDI (International Jobs and Economic Development Impacts) [SWR-19-20]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/disclaimer.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.i-jedi.org/scenario/start", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "v.10" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-09-01", + "metadataLastUpdated": "2021-09-21" + }, + "description": "Sequential Training ToolKit, or STTK, is a software toolkit plugin for the Unity development platform that enables software developers to easily develop structured Sequential Training applications for gaming and extended reality (XR) environments. STTK is architected to easily import the toolkit as a plugin for the Unity platform and then interact with the graphical user interface (GUI) for drag-and-drop functionality. STTK also includes easy add-on plugins for Prefabs and auto-builds a State Machine. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-3059 O", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Sequential Training ToolKit - STTK", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/STTK", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-09-01", + "metadataLastUpdated": "2021-09-21" + }, + "description": "The Menu Framework is a reusable Extended Reality multi-level menu system for the Unity Development Platform. The menu structure is architected for reusability to suit whatever need the developer may have for a multi-level, reusable menu framework. Menu Framework's architecture, GUI, and functionality are based on the paper \"Extended Reality for Enhanced Training and Knowledge Capture\" (SAND2020-2361C). This tool uses the Microsoft Mixed Reality ToolKit (MRTK) built in functionality to provide a suite of functionalities including bounding box, follow me, minimize, maximize, settings, and help commands. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1507 O", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "MenuFramework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MenuFramework", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2021-09-01", + "metadataLastUpdated": "2021-10-16" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). 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Using the tool again will integrate these label and color coding into the existing analysis table to aid in conducting an evaluation of the network traffic.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Network Architecture Verification & Validation Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/NAVV", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "3" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2021-09-02", + "metadataLastUpdated": "2021-10-16" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2021 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2021 (v1.3.0.13857)" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-02", + "metadataLastUpdated": "2021-09-02" + }, + "description": "GALATIC is a CUDA template library for performing Sparse Matrix - Sparse Matrix multiplication (SpGEMM) over arbitrary semirings on the GPU. 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The GSM additionally provides its clients with sub-model libraries to allow them to model desired physics within their own physical models.", + "laborHours": 0.0, + "languages": [], + "name": "The Generalized Spallation Model", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/generalized-spallation-model", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2021-09-24" + }, + "description": "dbprocessing is a python framework for automating data processing pipelines. 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While the framework is written in python, it can run software in any language but may require a “wrapper” to translate the dbprocessing command line arguments to the form expected by the software.", + "laborHours": 0.0, + "languages": [], + "name": "dbprocessing", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/dbprocessing", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2022-01-11" + }, + "description": "These codes and scripts will perform analyses related to genetic, evolutionary and epidemiological investigations of pathogen spread. 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Our research under which these codes are developed is supported by the NIH, which requires us to share codes with other researchers.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Code for pathogen evolution and epidemiology", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2021-09-10" + }, + "description": "A collection of python scripts to load in data from supernovae simulations and use that data to model chemistry and astrophysical dust formation.", + "laborHours": 0.0, + "languages": [], + "name": "sndust", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/sndust", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2021-09-10" + }, + "description": "Understanding flow and transport in fractured rock is an important national priority, which includes environmental protection, resource development, infrastructure development, and seismic risk. In energy resources formations, such as tight sandstone formations, shale formations and coal beds with very low permeability, as well as nuclear waste repository sites, networks of fractures are typically the principal pathways for fluid and gas flow and contaminant transport. A Discrete Fracture Network (DFN) approach is an advanced method to mimic discrete pathways for fluid flow through a fractured rock mass. DFN models represent deterministically and stochastically defined fractures observed at subsurface media and to predict flow and transport for individual sites. In order to achieve accurate flow and transport predictions, a high-quality computational mesh is required. The geometric features (fractures, fracture intersections, spaces between fracture intersections, etc.) that must be resolved in a generated DFN typically span a wide range of spatial scales and make the efficient automated generation of high-quality meshes a challenge. To deal with these challenges, many approaches deform the DFN to align its features with a mesh. The proposed nudging technique allows for the production of a high-quality conforming Delaunay triangulation of a DFN without significant modification of fractures location, size, orientation, and topology. The nudging technique is based on the feature rejection algorithm for meshing (FRAM). Using FRAM, the DFN mesh is constructed so that all the features in the network, e.g., length of intersections between fractures and distance between lines of intersection of a fracture are equal to or larger than a user-defined minimum length scale, h. FRAM performs well in the case of stochastically defined networks, where fractures size, positions, orientation, etc., are sampled from given probabilistic distributions. However, reproducing a DFN with deterministically defined fractures where fractures position, orientation and size are rigidly defined, is not possible using the standard version of FRAM. This nudging technique is developed to accompany FRAM and produce high quality mesh on a DFN with both stochastic and deterministic fractures. The essence of the nudging technique is in the fracture perturbation in fracture location and fracture orientation in the way that keeps the fracture within a distance h of their original position and do not create any features smaller than h. If needed, the nudging approach applies multiple times until the desired requirements on distance are met with no significant fracture network deformation and no original connectivity modification. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Nudging Technique for Robust Meshing of Intersecting Polygons in Discrete Fracture Networks v1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "State of Stress Analysis Tool (for carbon sequestration). The SOSAT tool provides value during GCS site screening and characterization phases to target collection of specific additional data to constrain uncertainties in geomechanical risk and to help operators to make informed decisions during the operational phase (Appriou et al., 2019). The capability represented in SOSAT, therefore, helps build stakeholder confidence that geomechanical risks are understood and manageable", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/SOSAT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SOSAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Codebase for analyzing large atomistic simulation results using graph analytics. Analysis of large molecular simulations is difficult due to size and memory constrains in commonly used analysis software. This code was developed to analyze an ~8 million atom polycrystalline Al system under shear, with a particular emphasis on identifying defect structures. This code applies graph theory to reduce the system to components of interest and applies associated algorithms to characterize these components.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/galas", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/galas", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The concept of the software is for a user to input the desired decay period and initial isotopic distribution and radioactivity, and RA-Decay will return the new isotopic distribution and radioactivity including the progeny ingrowth.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "RA Decay", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-09-15", + "metadataLastUpdated": "2023-05-26" + }, + "description": "Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by NREL. This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript \"Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning\", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nrel.gov for any questions.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "AI-BATT-OS (Autonomous Identification of Battery Life Models – Open Source) [SWR 21-17 and SWR 21-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/AI-Batt-OS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-09-15", + "metadataLastUpdated": "2021-09-15" + }, + "description": "Predictive modeling of patient tumor growth response to drug treatment is severely limited by a lack of experimental data for training. Combining experimental data from several studies is an attractive approach, but presents two problems: batch effects and limited data for individual drugs and cell lines. Batch effects are caused by systematic procedural differences among studies, which causes systematic experimental outcome differences. Directly using these experimental results as features for machine learning commonly causes problems when training on one study and testing on another. This severely limits a model's ability to perform well on new experiments. Even after combining studies, predicting outcomes on new patient tumors remains an open challenge. We propose a semi-supervised, autoencoder-based, machine learning procedure, which learns a smaller set of gene expression features that are robust to batch effects using background information on a cell line or tissue's tumor type. We implemented this reduced feature representation and show that the new feature space clusters strongly according to tumor type. This experiment is carried out across multiple studies: CCLE, CTRP, gCSI, GDSC, NCI60, and patient derived tumors. We hypothesize that using a batch effect resistant feature set across studies will improve prediction performance. Genome Data Commons (GDC) gene expression profiles for publicly available human tissues and cell lines from NCI60 and CCLE were processed using the semi-supervised learning procedure. Our autoencoder repurposes the 'center loss' (CL) cost function of Wen et. al. to learn a more generalized set of features using the cell line or tissue's tumor type. ", + "laborHours": 0.0, + "languages": [], + "name": "RNA-seq latent featurizer using center loss cost function", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CBIIT/NCI-DOE-Collab-Pilot1-Semi-Supervised-Feature-Learning-with-Center-Loss", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-09-15", + "metadataLastUpdated": "2021-09-15" + }, + "description": "Axom is an open-source library of \"building block\" software components that provide core infrastructure capabilities for HPC applications. Such capabilities include: input file parsing and verification for various file formats, format specification for material shape input to multi-material simulations and tools for placing those shapes on meshes, parallel distributed coordination of diagnostic messages, geometric primitives, spatial queries and spatial search acceleration data structures, in memory key-value data store for managing simulation data and parallel file I/O. Axom components are used widely across LLNL Advanced Simulation and Computing program applications. It is also part of the LLNL institutionally-supported RADIUSS project, which promotes and funds its adoption by projects across LLNL.", + "laborHours": 229945.6, + "languages": [], + "name": "Axom", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/axom", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.6.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-09-16", + "metadataLastUpdated": "2021-09-16" + }, + "description": "Fast ion transport along the electrode thickness is required for Lithium ion battery (LIB) to sustain continuous high-rate discharge or charge currents, which is a desired feature for the fast charging of electric vehicle batteries. Advance in LIB electrode manufacturing allows to control, to a certain extent, the electrode microstructure architecture in order to improve the macroscopic performances of these devices. For instance, several groups have experimentally tested architectures tailored specifically to increase the through plane ionic diffusion in regards for fast charge application by adding channels or groove-like large pores oriented along the electrode thickness. These voids do not replace the existing pores of the electrode microstructure but consist in a second, coarser, pore network, called the secondary pore network (SPN). The model quantifies the impact of SPN on ionic diffusion with a composite electrode through a simple analytical approach, considering various pore channel geometries and comparing to standard electrodes with identical gravimetric and identical volumetric specific theoretical capacity. The goal is to find optimal SPN design parameters according to three optimization objectives aiming to balance the improved overall through-plane, thanks to the coarse aligned channels, and the degraded in-plane diffusion, due to the porous matrix densification required to maintain gravimetric and volumetric specific theoretical capacity. The analytical model must be considered as a pre-screening tool to quickly investigate large design space, that can be refined later with more complex electrochemical CPU-expensive numerical models.", + "laborHours": 0.0, + "languages": [], + "name": "Secondary Pore Network Design Optimization Analytical Diffusion Model for Lithium Ion Battery", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Secondary_pore_network", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2023-03-13" + }, + "description": "Temporal analysis of products statistical analysis package (tapsap) is a package for reading, cleaning, analyzing and making inference of temporal analysis of products (TAP) information. This package is designed with the intent for collaboration within the TAP community for advancing TAP analysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Temporal Analysis Of Products Statistical Analysis Processing", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/tapsap", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Procedure for reverse engineering binary files and storing the result in a graph database structure for later analysis. This is achieved through the use of Python, angr, and OrientDB Community Edition.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DISCOverflow", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/idaholab/DISCOverflow/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DISCOverflow", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "3.6 and up" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-17" + }, + "description": "The Devastator runtime is a modern C++ implementation of optimistic parallel discrete event simulation methods. Devastator allows simulation application code to productively specify their component and event functionality with C++14 constructs. It utilizes GASNet-EX for distributed memory communication and includes parallel performance optimizations such as light-weight thread message queues and asynchronous GVT. Furthermore, it supports efficient event broadcasts and pause-rewind-resume functionality to support periodic load balancing and outer loop optimization algorithms.", + "laborHours": 0.0, + "languages": [], + "name": "Devastator Parallel Discrete Event Simulation Runtime (Devastator) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cychan-lbnl/devastator.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-17" + }, + "description": "LW3D is code for modeling beam dynamics in particle accelerators including Lienard-Wiechert self-fields. It is similar to codes like IMPACT-T except that the Poisson solver is replaced by a Lienard-Wiechert solver. Along with space-charge effects, the code can model effects like coherent synchrotron radiation.", + "laborHours": 0.0, + "languages": [], + "name": "LW3D v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LienardWiechert/LW3D", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-20" + }, + "description": "DASSA (Parallel DAS Data Storage and Analysis) provides a data storage engine and analysis engine for data from distributed acoustic sensing and other methods. It supports various data analysis operations, from FFT , signal filter, cross-correlation, compression, stacking etc.", + "laborHours": 0.0, + "languages": [], + "name": "DASSA v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/dbin_sdm/dassa/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-21" + }, + "description": "A suite of non-proprietary C-like procedures (code) that compile and run within the commercial Igor Pro data analysis program (wavemetrics.com) have been developed for the data file loading, plotting and analysis of Angle-Resolved Photoemission Spectroscopy (ARPES) data. The data file loading procedures are more specific to ARPES data acquisition and file formats at Advanced Light Source (ALS) beamlines, while plotting and analysis procedures are more generic to processing of 1D, 2D and higher dimensional dataset arrays with some specific tools tailored to the ARPES technique.", + "homepageURL": "https://sites.google.com/lbl.gov/2021-158/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Igor Pro procedures for ARPES analysis (ARPES Igor procedures) v21.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-158/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-17" + }, + "description": "H5TurboPFor is a wrapper for the TurboPFor-Integer-Compression for HDF5 library. Basically, it enables the HDF5 library to compress integer data using the TurboPFor.", + "laborHours": 0.0, + "languages": [], + "name": "H5TurboPFor v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/berkeleysdm/H5TurboPFor.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-21", + "metadataLastUpdated": "2021-09-21" + }, + "description": "The Localization and Mapping Platform (LAMP) software fuses radiation and contextual data to produce 3-D maps that locate and identify gamma-ray emitting sources in complex environments. It enables data collection, fusion, and processing in near-real-time and on-board in several configurations, including handheld and unmanned aerial system (UAS) form factors.", + "homepageURL": "https://sites.google.com/lbl.gov/2018-041/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Localization and Mapping Platform Software (LAMP Software) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2018-041/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2018-041/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-21", + "metadataLastUpdated": "2021-09-21" + }, + "description": "Occupant schedules at room level are crucial information to building energy modeling which quantifies occupant-related energy efficiency technologies and controls for new building design as well as existing building retrofits to reduce energy use and GHG emissions in buildings. The Occupancy Simulator Solver is an executable software component that simulates the stochastic behavior of occupant presence and movement in a building using the Markov-chain model. Occupancy Simulator Solver is the calculation engine of the web App Occupancy Simulator, which takes high level input on occupants, spaces and events, then calls the Solver to simulate occupant movement and generate occupant schedules for each space. The generated schedules capture diversity and stochastic nature of occupant activities (e.g., in office, meetings, breaks, lunch). These schedules are stored in CSV files and can be downloaded from the App and used for building performance simulation.", + "homepageURL": "https://sites.google.com/lbl.gov/2019-163/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Occupancy Simulator Solver v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2019-163/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2019-163/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-21", + "metadataLastUpdated": "2021-09-21" + }, + "description": "The Radiological Anomaly Detection and Identification (RADAI) software package is a python library for implementing, training, and storing algorithms that detect and identify anomalies in gamma-ray spectra. The library defines a general framework for implementing detection (binary) and identification (classification) algorithms, objects to encapsulate the results of analyses, a variety of temporal filtering tools that can be used in constructing algorithms, and conceptual design that allows easy reading and writing of algorithms (and their time dependent state). In addition to this framework, the library includes implementations of a variety of algorithms from the scientific literature including: gross-counts k-sigma, SPRT, N-SCRAD, Region of Interest, and Censored Energy Window. The implementation of these algorithms within the RADAI package was done to facilitate user-initiated training and configuration to by applied to different gamma-ray detector types. Finally, benchmarked and synthetic datasets will be made available for standardized algorithm characterization with corresponding utilities in the RADAI package for data access and processing.", + "laborHours": 0.0, + "languages": [], + "name": "Radiological Anomaly Detection And Identification (RADAI) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/lbl-anp/radai/radai", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A data annotation tool that integrates with the python Jupyter notebook environment.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/diet-parselantro", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/diet-parselantro", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "DM-Sim: Quantum Simulator on GPU Cluster using Density Matrix: a new simulation approach that significantly reduces communication overhead.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/DM-Sim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/DM-Sim", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2021-09-22" + }, + "description": "A library for solving large scale power system stochastic multi-period security-constrained optimization problems on next generation exascale architectures", + "laborHours": 0.0, + "languages": [], + "name": "ExaGo", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/exasgd/frameworks/exago", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Dynamics-based deep learning methods to modernize current scientific computing methods. Neuromancer is currently capable of solving inverse problems for a system of ordinary differential equations. The functionality includes system identification and constrained optimal control of unknown or partially known ODEs.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/neuromancer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/neuromancer", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A data-driven performance verification framework, which conducts automated output-based verification of building performance (especially control requirements which be only verified via time-series output)", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/ANIMATE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ANIMATE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2021-09-22" + }, + "description": "FunFact is a Python package for functional factorization of matrices and higher-order tensors", + "laborHours": 0.0, + "languages": [], + "name": "FunFact v0.6", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yhtang/FunFact.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2021-09-22" + }, + "description": "Simcov is an agent-based model of the spread of viral infections and the immune response in human lung at the cellular level. It is designed to scale well on HPC systems. No other software like it currently exists.", + "laborHours": 0.0, + "languages": [], + "name": "simcov v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdaptiveComputationLab/simcov.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "oeschts@ornl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2021-09-23" + }, + "description": "To reduce hand/wrist pain from frequent computer use I decided to create a program that will convert voice to common keyboard/mouse actions in order to reduce clicks/keypresses. It is not intended to replace the keyboard and mouse, but rather to reduce their use, hence the name Sidekick. Sidekick handles transcription, mouse movement/click/wheel, and common commands.\n", + "laborHours": 0.0, + "languages": [], + "name": "Sidekick", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/oeschsec/Sidekick---voice-controlled-keyboard-and-mouse", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A software for a multi-challenge power-flow grid optimization competition was developed. The platform brings together high performance computing clusters, webservers, databases, competition datasets, schedulers, evaluation codes, and a multitude of language compilers and optimization solvers to host the competition. The original video announcing the competition, from former Secretary Perry, at: https://www.youtube.com/watch?v=hZwX3P9vS8M", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Grid Optimization (GO) Competition Platform", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ConverterBlocks uses the output of detailed electromagnetic transient (EMT) simulations to produce generalized block diagram models of power electronic systems. The process uses deep learning with customized block architectures. The outputs are reduced-order models that meet specified accuracy requirements, while providing important advantages over the original EMT models: ConverterBlock models have fewer nodes and can take longer time steps, resulting in shorter simulation times ConverterBlock models are continuously differentiable, making them compatible with control design methodsGeneralized block diagram modeling of power electronic converters for grid solar and storage applications.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/pecblocks", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pecblocks", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Distributed photovoltaics protection software toolkit The code package includes several important functions for design and analysis of new grid protection schemes, for scenarios of distributed photovoltaic (DPV) generation approaching 100% of the peak feeder load, i.e., high-penetration DPV. Convert distribution feeder models, used by planning engineers, to electromagnetic transient (EMT) models that produce waveforms for advanced relay algorithms. Visualize the results of protection scheme operation. Tools to determine distance relay settings on distribution systems. Tools to predict the performance of time-domain, incremental distance relay algorithms", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/DPVPROT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/DPVPROT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "NWQSim is a quantum circuit simulation environment developed at PNNL. It currently includes two major components: a state-vector simulator (SV-Sim) and a density matrix simulator (DM-Sim) and we may add more components, such as a Clifford simulator, in the future effort. NWQSim has two language interface: C/C++ and Python. It supports Q#/QDK frontend through QIR and QIR-runtime. It supports Qiskit and Cirq frontends through OpenQASM. NWQSim runs on several backends: Intel-CPU, Intel-Xeon-Phi, AMD-CPU, AMD-GPU, NVIDIA-GPU, and IBM-CPU. It supports three modes: (1) single processor, such as a single CPU (with and without AVX2 and AVX512 acceleration), a single NVIDIA GPU or a single AMD GPU; (2) single-node-multi-processors, such as multi-CPUs/Xeon-Phis, multi-NVIDA/AMD GPUs; (3) multi-nodes, such as a CPU cluster, a Xeon-Phi cluster (e.g., ANL Theta, NERSC Cori), an NVIDIA cluster (e.g., ORNL Summit, NERSC Perlmutter).", + "laborHours": 0.0, + "languages": [], + "name": "NWQ-sim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/sv-sim", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Subgraph Based Learning of Contextual Embedding\na framework bridging static representation learning methods using global information from the entire graph with localized attention driven mechanisms to learn contextual node representations.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/SLiCE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SLiCE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Two datadriven predictive approaches, namely, {\\em Koopman Operator Theoretic (KOT)-based} model and {\\em Graph Neural Network (GNN)-based model}, to enable effective power system state predictions. The KOT-based approaches (Robust\nDMD, deepDMD) capture the power system evolution as a linear dynamical system on an abstract space. The GNNs model the spatio-temporal correlations using graph convolutional network and are called Spatio-Temporal Graph Convolutional\nNetwork (STGCN). These predictive models are trained, tested and compared rigorously based on their predictions of frequencies in the IEEE 68 bus system when subjected to a disturbance. GridSTAGE framework developed at Pacific Northwest National Laboratory is leveraged to generate multiple datasets (in the form of PMU measurements) for training and testing by strategically creating load changes across the spatial locations of the network", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/grid_prediction", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/grid_prediction", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "Codes developed by ASC supported personnel for generating semi-analytic solutions to traditional verification test problems. \n\nConcrete example is a script written to do a numerical integral of an analytic function that serves as a known solution to a complex differential equation. This is very useful when checking if your general purpose physics code can produce the solution you expect when it starts from a set of known initial conditions. If the form of the integral is complex, the only way to evaluate the integral is to write a code that performs the integration numerically.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "ASC Blanket Disclosure 5", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "Software developed by ASC personnel and that includes physics which aims to understand astrophysics-only applications. \n\nThis provides a list of concrete code types allowed within this Blanket, but here I offer more detail about what each of those types entail.\n- Galactic Chemical Evolution: Uses prescriptions to define the synthesis of heavy elements from various astrophysical objects (stars, supernovae, novae, big bang), and then represents the rate at which these astrophysical objects occur within our galaxy. The convolution of the rate of incidence with the material released by each instance gives a prediction for the chemical evolution of the galaxy.\n- Stellar Population Synthesis: Uses prescriptions for the rate of occurrence of various properties or events in the life of a star (its initial mass, whether it has a binary companion, its binary distance separation, etc) to model what happens to the stars as they evolve. Gives a sense of what a population of stars should look like statistically speaking. Useful for predicting, for example, how many binary stars will merge in our galaxy in the next 1 million years, or how many supernovae do we expect to see with current telescopes.\n- Hydrostatic equilibrium, time-implicit, stellar evolution codes: Uses equilibrium equations to show how the structure of a star must change throughout its life. Assumes that gravity is equally balanced by stellar pressure at all times. Includes nucleosynthesis network for calculating energy generation from nuclear burning in the star. This energy generation holds the star up against the gravitational forces trying to collapse the star. Hydrodynamic timescales are not resolved, only hydrostatic is considered. \n- Astrophysical nuclear / astrophysical chemical network codes: Solves a system of rate equations that describe the network of elements involved in nuclear or chemical evolution for astrophysical events (e.g. supernovae, stars, big bang, protostars, interstellar medium). These codes are designed for use in post-process, which means that the density and temperature conditions in a fluid element are defined versus time and fed into these codes. Then, these codes report back how the nuclear or chemical makeup of the fluid element would evolve based on those conditions. There is no feedback from the energy released by that evolution on the fluid element’s conditions.\n-Astrophysical orbital dynamics codes: Calculates the orbits of a set of point masses according to the laws of gravity (e.g. planetary systems, solar system asteroids, extra-solar planet orbits…).", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "ASC Blanket Disclosure 4", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2022-01-06" + }, + "description": "Modern data scientists are tasked to analyze ever-growing data sets with increasingly complex relationships. Tensor decompositions have come to play a central role in identifying underlying latent structures in higher-order data. The problem of fitting tensor models to different distributions is complicated by the combinations of size, dimensionality, and sparsity present in real world data. The situation demands efficient algorithms designed for shared-memory and distributed systems. This work will present new research that tackles these challenges on several different fronts, leveraging optimizations in numerical algorithms and sparse tensor representations in heterogeneous high performance computing environments.", + "laborHours": 0.0, + "languages": [], + "name": "pyDRESCALk", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyDRESCALk", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "Code used in the generation, application, and execution of model and methods related to work in theoretical and computational biology specifically surrounding the evolution, ecology, and epidemiology of infectious disease. This code included the implementation of models used for data analysis, code to generate figures, code to process and manipulate data for said purposes, and code to execute published analyses. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Blanket software for theoretical and computational biology applications", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "PALM-LANL is a model system for conducting large-eddy simulations, that is, simulations of turbulence that only resolve the largest turbulent eddies and rely on a turbulence closure scheme to represent the smallest turbulent eddies. PALM-LANL is based on PALM version 5.0 but it contains numerous modifications by LANL authors to add research capabilities. PALM is written for atmosphere and ocean turbulence; PALM-LANL includes modifications and additions to the ocean turbulence components, analysis, and data output capabilities. ", + "laborHours": 0.0, + "languages": [], + "name": "LANL Contributions to Parallelized large-Eddy Simulation Model Formerly PALM-LANL", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/palm_lanl", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "The \"Wrapper for the optimization of cross-section generation in OpenMC\" is Python-based software that runs the open-source Monte Carlo code OpenMC (https://docs.openmc.org/en/stable/ ) to generate cross-sections for any reactor geometry. The wrapper then optimizes those cross sections. The optimization aims to choose an energy group structure and a scattering representation that maximize accuracy with respect to continuous-energy results while avoiding significant computational expense. It then outputs these cross-sections in an ISOXML format readable by the Idaho National Lab code suite MOOSE (Olin William Calvin, Mark D DeHart, “Architecture for the Performance of Nuclear Fuel Depletion Calculations”, Idaho National Laboratory report, November 2019). The expected use-cases of this software include: -finding the best group structure and scattering representation for a specific reactor -testing the appropriateness of energy group structures for different reactor types -comparing energy group structures and scattering representations to each other -generating cross sections for use in deterministic codes, including ones found in the MOOSE suite The example reactor geometry included in this release is a generic reactor design, not based on any reactor in existence or in development. It was fabricated for the sole purpose of being a “testbed-geometry” upon which to develop this tool. Since the tool is designed to be generic, the nature of the test geometry is not very important, however, it is valuable to include as an example for users who are unfamiliar with developing reactor geometries for OpenMC.", + "laborHours": 0.0, + "languages": [], + "name": "Wrapper for the optimization of cross-section generation in OpenMC", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/TOGA.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "The Sequence Read Archive (SRA) is a cloud-based repository of biological sequence data provided by the National Center for Biotechnology Information. The SRA is a database of “raw” sequencing data – typically short (100 bp – 1000 bp) nucleotide sequences generated by modern, next-generation sequencing instruments and submitted by researchers around the world. Data in the SRA is stored in a highly-compressed binary format that can be directly read by most bioinformatics analysis tools. Existing tools to convert this binary data into standard nucleic acid sequence formats (like FASTA and FASTQ) are slow and error prone (due to a computationally demanding reordering step to place the sequenced reads in their originally submitted order). The “sracat” tool provides a fast, reliable conversion utility for use-cases that do not require ordered reads.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "sracat", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "This version used only for additional G-cases in the v1 Cryosphere campaign. MPAS-Ocean: Update MPAS-source to GM varying, add namelist options for 3D varying GM bolus Kappa Flags are added to enable the 3D varying GM bolus Kappa, it is enabled by default and is on whenever the GM parameterization is on. Output of kappaGM3D and the phase speed are added to monthly history as well Differences from v1.2 simulations include above and all of those listed in the v1.3.0-beta tag.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v1.3", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v1.3.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v1.3.0" + }, + { + "contact": { + "email": "bernholdtde@ornl.gov" + }, + "date": { + "created": "2021-09-26", + "metadataLastUpdated": "2021-09-28" + }, + "description": "IPS is an environment to orchestrate complex coupled simulation workflows on parallel computers. 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The biogeochemical calculations using CE-QUAL-ICM kinetics are conducted over the same finite-volume mesh and in the FVCOM framework.", + "laborHours": 0.0, + "languages": [], + "name": "FVCOM-ICM4.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ssmc/fvcom-icm4.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2021-09-27", + "metadataLastUpdated": "2022-11-18" + }, + "description": "First release of version 2 of the Energy Exascale Earth System Model. The atmosphere component remains EAM. Major changes since version 1 include: all column-physics parameterizations are computed on a separate grid that has approximately half the number of points of the dynamics grid, a new nonhydrostatic dynamical core (running in hydrostatic mode) with semi-Lagrangian tracer transport, CLUBB updated from v1 to v2, a new convective trigger (dCAPE/ULL) based on the dynamic Convective Available Potential Energy (CAPE) (dCAPE) and the Unrestricted Launch Level (ULL) concepts is used in ZM. minimum cloud droplet number changed, gravity wave drag energy conservation fixed and new tunings used, dust emission size distribution changed to emit more coarse dust particles The land component is still ELM. Major changes since version 1 include: using SNICAR-AD for radiation in snow to match the sea-ice model and fixing bugs in snow compaction and water state calculation. The ocean component remains MPAS-ocean. Major change since version 1 include: Redi isopycnal mixing has been updated, tested, and tuned in combination with the Gent-McWilliams parameterization, a sign error was fixed in the 3rd-order flux routines, the mesh used in low-resolution coupled cases was modified and the time steps adjusted, new regionally refined meshes were created, one focused on North America and another on the Southern Ocean, including ice shelf cavities. The sea-ice component remains MPAS-seaice. Major changes since version 1 include: A new heat- and freshwater-conserving coupling of frazil ice, turning off of SSH filtering, addition of SNICAR-AD and snow grain aging. The land-ice component remains MPAS-Albany-landIce (MALI) and is a static ice sheet. There is more out-of-the-box support for cryosphere configurations including the new regionally refined configuration around Antarctica with ice shelf cavities. The river model is MOSART. The half-degree river mesh was redone so it no longer treats Black and Caspian seas as ocean. The coupler remains cpl7/MCT. Major changes since version 1 include handling of ice shelf melt fluxes (heat / freshwater exchange with the ocean), and data icebergs. All components allow regional refinement of their meshes and two separate example of refinement, one in and around North America and one around Antarctica and the Southern Ocean, are provided.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v2.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v2.0.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v2.0.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "OpenMC is an open source, community-developed framework for performing Monte Carlo particle transport calculations.It is capable of simulating neutron and photon transport below ~50 MeV and also includes a model for bremsstrahlung\nproduction of photons by electrons/positrons. Fixed source, k-eigenvalue, and subcritical multiplication problems can be\nsolved. Problem geometries can be modeled either using constructive solid geometry or a CAD representation. A flexible and efficient tally system enables a wide variety of physical quantities to be tallied and analyzed. OpenMC can run in\nparallel using a hybrid MPI and OpenMP programming model and has been extensively tested on leadership class supercomputers. A built-in Bateman equation solver enables the modeling of material composition changes due to\nirradiation. One of the unique features of OpenMC is its rich, extensible Python and C/C++ programming interfaces that enable programming pre- and post-processing, multigroup cross section generation, workflow automation, multiphysics\ncoupling, and the visualization of geometry and tally results. In addition to the core Monte Carlo transport solver and associated APIs, OpenMC includes a Python-based nuclear data interface that enables power users to inspect, modify,and perform various types of nuclear data processing on ENDF, ACE, and OpenMC¿s native HDF5 files", + "laborHours": 0.0, + "languages": [], + "name": "OpenMC", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openmc-dev/openmc", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The Infrastructure Expression: Discovery Tools is a toolset that allows for the automated collection of various network, hardware, and software vulnerabilities and details to be collected from systems on a given network. These details are then converted into a STIX 2.1 format, allowing for easy viewing in existing applications as well as sharing and interfacing with tools that already use the STIX 2.1 format.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Infrastructure Expression: Discovery Tools", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/IX-DiscoveryTools", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "3" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "The MIRA project comprises of a set of Python drivers that enable rigorous intercomparison of remapping algorithms by providing the infrastructure for computing the numerical metrics of interest for ESM. 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Enthalpy and density of the non-conventional materials were defined using non-conventional material properties.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Aspenplus Model For Msw Sorting Process", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/AspenPlus", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "MPI-distributed expert-focused C++-based modeling system that is designed for use on large computing clusters and supercomputers.", + "laborHours": 0.0, + "languages": [], + "name": "Repast for High-Performance Computing )Repast HPC", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Repast/repast.hpc", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "ChiSIM is a framework for implementing agent-based models that simulate the mixing of a synthetic population. 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For example, an agent may expose other agents to a disease in an epidemiological model.", + "laborHours": 0.0, + "languages": [], + "name": "The Chicago Social Interaction Model (ChiSIM)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Repast/chiSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-30" + }, + "description": "PIRT is a tomography inversion code that incorporates center of rotation correction written with the goal of being scalable on HPC systems. 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It does this by defining relations between a set of client nodes that share data via a set of server nodes. The primary focus of UUDEX is to facilitate communications between control centers, operations centers, and other trusted organization.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/UUDEX", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/UUDEX", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "Symbolic regression software that formulates a symbolic regression problem as a mixed-integer nonlinear optimization problem, and solves it using a sequential tree construction heuristic", + "laborHours": 0.0, + "languages": [], + "name": "STreCH", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jongeunkim/STreCH", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-30" + }, + "description": "Models the generation asset investment decisions of individual utility \"agents\" in a user-specified electricity market. Agents employ limited local resources and information to evaluate projections of future market events, and determine when and how quickly they should construct new generation assets to respond to market trends and the retirement of existing system assets. ABCE is implemented in Python and Julia, and can be connected to the ANL A-LEAF electricity system optimization code; the contribution from A-LEAF is completely compartmentalized in the code's execution and will not be released as open-source at this time.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "ABCE (Agent Based Capacity Expansion)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-30" + }, + "description": "The software develops a framework for training intelligent agent to conduct automatic service restoration in power distribution systems. The framework is based on imitation learning paradigm with a mixed-integer programming based expert and environment. The software also provides access to reinforcement learning baseline comparison.", + "laborHours": 0.0, + "languages": [], + "name": "IntelliHealer: Imitation Learning Online Service Restoration", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/whoiszyc/IntelliHealer", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "This repository consists of various code examples demonstrating common patterns used in High-Performance Computing (HPC). 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SAND2021-2714 O", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "ParseGen v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/parsegen-cpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-10-04", + "metadataLastUpdated": "2024-01-03" + }, + "description": "The U.S. Department of Energy's Bioenergy Technologies Office and the National Renewable Energy Laboratory (NREL) developed the BSM (Bioenergy Scenario Model) to explore the development of a U.S. biofuels industry. The BSM is a system dynamics model built on the STELLA software platform. 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Instead, it is best used to (1) analyze and evaluate alternate policies; (2) generate scenarios; (3) identify high-impact levers and bottlenecks to system evolution; and (4) seed focused discussion among policymakers, analysts, and stakeholders.", + "laborHours": 0.0, + "languages": [ + "STELLA" + ], + "name": "BSM (Bioenergy Scenario Model) FKA: Biomass Scenario Model [SWR-09-09]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bsm-public", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-10-04", + "metadataLastUpdated": "2024-01-25" + }, + "description": "The Caltalyst Layer Crack Detector, or CLCD (\"clicked\") is a program that takes in optical micrographs of catalyst coatings for PEM fuel cells or electrolyzers and calculates the percent area that consist of cracks. 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Despite anticipated overall benefits to society, the transition to a circular economy is likely to create regional differences in impacts. Current tools are unable to fully evaluate these potential externalities, which will be important for informing research prioritization and regional decision making. The Circular Economy Lifecycle Assessment and VIsualization (CELAVI) framework allows stakeholders to quantify and visualize potential regional and sectoral transfers of impacts that could result from transitioning to a circular economy, with particular focus on energy materials. The framework uses system dynamics to model material flows for multiple circular economy pathways and decisions are based on learning-by-doing and are implemented via cost and strategic value of different circular economy pathways. It uses network theory to track the spatial and sectoral flow of functional units across a graph and discrete event simulation to to step through time and evaluate lifecycle assessment data at each time step. The framework is designed to be flexible and scalable to accommodate multiple energy materials and multiple energy technologies. 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", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "EtherNet IP Client Library", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-epics/etherip", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-10-13", + "metadataLastUpdated": "2024-07-23" + }, + "description": "MC3 is a model checking solver that provides a more efficient tool for a widely studied class of problems currently solved by other open-source software tools. 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SAND2020-10230 M", + "laborHours": 109728.8, + "languages": [ + "Java", + "Java" + ], + "name": "Credibility Framework (CF) v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/cf?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cf", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-14", + "metadataLastUpdated": "2021-10-14" + }, + "description": "This software provides an implementation of the physics-informed neural network setup for different differential equations. It provides a way to solve differential equations using machine learning, via a physical constraint term in the loss function. 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The model developed in Simulink has been designed and tuned to match the governor-turbine response for a real-world hydropower unit owned by Idaho Falls Power (IFP). The Simulink and RSCAD models enable real-time testing in a hardware-in-the-loop (HIL) implementation using OPAL-RT and RTDS digital real-time simulators, respectively. An automatic initialization for dynamic simulation has also been integrated to each model in both Simulink and RSCAD. The RSCAD initialization involves a novel python-based interfacing for automatic modification of the initial conditions in the model. The parameters of these models can be tuned to match other hydropower plants in this class.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python", + "Simulink" + ], + "name": "Bulb-style Kaplan Turbine - Run-of-the-river (ror) Hydro Governor And Turbine Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Hydropower_Unit_Models", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kimj@ornl.gov" + }, + "date": { + "created": "2021-10-20", + "metadataLastUpdated": "2021-10-27" + }, + "description": "A unified framework across multiple programming platforms", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Fortran", + "Python" + ], + "name": "IRIS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/iris", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-21", + "metadataLastUpdated": "2021-10-21" + }, + "description": "ScalES is a high performance software package for performing large scale electronic structure calculations on high performance supercomputers.", + "laborHours": 0.0, + "languages": [], + "name": "Scalable Electronic Structure (ScalES) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/scales/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-21", + "metadataLastUpdated": "2021-10-21" + }, + "description": "MFDn kernels is a collection of small subroutines designed to capture essential characteristics of the Many-Fermion Dynamics---nuclear (MFDn) application (DOI: 10.1016/j.procs.2010.04.012). 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The package includes a Simulink S-Function that allows communication to the data broker via inter process communication; a data broker, which orchestrates communication between the emulated control system network and the simulation; an endpoint, which facilitates communication between the data broker and PLC's on the control network using ModBus/TCP; and an example PLC structured text files that work with OpenPLC, an open source emulated PLC. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-11479 O", + "laborHours": 0.0, + "languages": [ + "Python", + "Simulink", + "S Function", + "C Code", + "Python" + ], + "name": "OT Emulation Data Broker", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SMARTT", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-11-03", + "metadataLastUpdated": "2024-07-30" + }, + "description": "OptML is an open-source Python package that provides modeling and solution capabilities for optimization problems with embedded machine learning models. OptML is a collaborative open-source project that includes advanced algorithms from the academic community for efficient solution of these problems. Sandia contributions to this package include the development of interfaces between these algorithms and Pyomo. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10861 O", + "laborHours": 1155.2, + "languages": [ + "Python" + ], + "name": "OptML", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/OptML", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-11-03", + "metadataLastUpdated": "2021-11-03" + }, + "description": "HyRAM+ is a software toolkit for conducting quantitative risk assessment (QRA) and consequence modeling for hydrogen and other alternative fuels infrastructure and transportation systems. HyRAM+ contains validated, simplified release behavior models, a standardized QRA approach, and engineering models and generic data relevant to hydrogen installations. HyRAM (hydrogen-only) versions 1.0 to 3.1 were developed by Sandia for the U.S. Department of Energy (DOE) Hydrogen and Fuel Cell Technologies Office (HFTO). The U.S. DOE Vehicle Technologies Office (VTO) and U.S. Department of Transportation (DOT) Pipeline and Hazardous Material Safety Administration (PHMSA) contributed to the development of HyRAM+ version 4.0 regarding the addition of methane (natural gas) and propane models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10862 O", + "laborHours": 21508.0, + "languages": [], + "name": "HyRAM+ (Hydrogen Plus Other Alternative Fuels Risk Assessment Models) v.4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hyram", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 4.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A successful architecture that depicts the relationship between the energy market engineering requirements and blockchain requirements\n(shown as enablers). Software includes sequential and relational architectures supported by the UML flow diagrams. For a successful blockchain agnostic implementation of energy markets, the proposed architecture/blueprint supported by prototype implementation is very efficient. The proposed invention also depicts various means of the use of\nblockchain technology for energy market systems.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Blockchain smart contracts for energy markets", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "We present PyOECP, a Python-based flexible open-source software for estimating and modeling the complex permittivity obtained from the open-ended coaxial probe (OECP) technique. The transformation of the measured reflection coefficient to complex permittivity is performed based on two different models, including the capacitance model and the antenna model. The software library contains dielectric spectra of common reference liquids, which can be used to transform the reflection coefficient into the dielectric spectra. Several Python routines that are commonly employed (e.g., SciPy and NumPy) are only required so that the users can alter the software structure depending on their needs. The modeling algorithm exploits the Markov chain Monte Carlo method for the data regression. The discrete relaxation models can be built by a proper combination of well-known relaxation models. In addition to these models, the electrode polarization, which is a common measurement artifact for interpreting the dielectric spectra, can be incorporated in the modeling algorithm. A continuous relaxation model, which solves the Fredholm integral equation of the first kind (a mathematically ill-posed problem) is also included.", + "laborHours": 0.0, + "languages": [], + "name": "PyOECP: A flexible open-source software for the measurement and modeling of the dielectric spectrum from the reflection coefficient", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tyoon124/PyOECP", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "This is software that will be used to do data analytics in experimental workflows for x-ray mesoscale science. This tool set will provide a mechanism for supporting experiments in many ways, from collecting calibration information and raw data, to managing and viewing data to extracting crystallographic and physical parameters. It will eventually include development of a fully automated workflow that will include statistical information and prediction capabilities to support the scientists in decision-making and replanning their experiments when necessary.", + "laborHours": 0.0, + "languages": [], + "name": "Mesoscale Science Data Analytics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/fiteos", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": " When faced with biological threats, our ability to provide early warning, situational awareness, and decision support will depend on whether we can rapidly and accurately detect threat pathogens in clinical and environmental samples. While next generation sequencing technology and advanced analytic methods provide the means to identify the organisms present in metagenomic samples from clinical and environmental sources, proper identification of pathogens in these samples requires a comprehensive resource providing in-depth knowledge of known pathogens. Because there are myriad species, including rare and uncommon taxa, in metagenomic samples, it is not always possible to recognize pathogens by name. As time will most likely be a critical factor in outbreak situations, it may not be possible to consult with subject matter experts for pathogen identification. \n To effectively safeguard the security and safety of people, animals and plants, we must have detailed knowledge of the biological agents (pathogens), infectious diseases, and food-borne illnesses that could potentially cause harm. Prior to any mass event, relevant information must be identified, gathered together and integrated in ways that will make it most useful to the biosurveillence analysts in real-time during an actual event. This type of knowledge falls within the realm of a disease ontology, which integrates the various types of data associated with disease states. Having a comprehensive, curated, globally applicable disease ontology is critical to determine the severity of disease outbreaks, which in turn can inform predictive epidemiological models. For a disease ontology to be useful in biosurveillance applications, detailed information about the organisms that cause particular diseases (pathogens), as well as vectors that transmit the disease-causing pathogens, must be included in the ontology. \n While various websites and publications provide lists of pathogens and a few relevant features that may be useful, there is currently no single resource that provides a comprehensive curated list of all known human, animal and agriculturally relevant pathogens. To remedy this deficiency, we are developing a comprehensive pathogen knowledgebase, encompassing all known pathogens of humans, animals and plants. Having pathogen information already integrated into a usable knowledgebase will enable real-time analyses during an actual event, will facilitate the analysis of post-event data on pathogen-mediated disease outbreaks, and may contribute to improved predictive epidemiological models. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Pathogen Knowledge Base", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "DevOps cloud on the fly provides automated virtual machine creation on demand. This is accomplished using two very powerful software tools: Packer and Vagrant.", + "laborHours": 0.0, + "languages": [], + "name": "DevOps Cloud on the fly", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/devOpsCloudOnTheFly", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "System benchmarking provides a means to compare or assess the performance of hardware or software against a point of reference. Because of the multitude of factors that ultimately influence a benchmark’s results, reproducibility is challenging. To aid in this, we present a software framework named bueno that provides mechanisms to automate many arduous, error-prone benchmarking tasks: environmental setup; program compilation/execution; data storage and analysis.", + "laborHours": 0.0, + "languages": [], + "name": "bueno", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/bueno", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Blockchain Applicability and Cybersecurity Frameworks is the implementation of an earlier invention disclosure and Provisional Patent Application: S-146,805, Battelle IPID 31608-E. —BAF walks a user (or an interested party) through ~100 controls to determine various factors, including:\n1. Does the application need a blockchain?\n2. If the application needs a blockchain, does it need a private blockchain or permissionless/public blockchain?\n3. What kind of consensus is most suitable for the application? The current version of BAF evaluates between four consensus mechanisms: proof-of-work, proof-of-stake, proof-of-burn, and proof-of-authority.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Blockchain Applicability and Cybersecurity Frameworks (BAF)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "Rossi Alpha View (RAV) is a teaching aid for explaining what a Rossi-alpha distribution is and how it is generated. The software provides graphical user interface (GUI) in which a pulse train is shown from which a Rossi-alpha distribution is generated as pulses appear. The source strength, correlated fraction, and speed of the pulse train can be adjusted as well as the die-away time and efficiency of the hypothetical detector from which the pulses would be generated. Additionally, neutron coincidence counting principles are illustrated through the software by showing a reals plus accidentals (R+A) gate and an accidentals (A) gate with an adjustable pre-delay, gate width, and long delay.", + "laborHours": 0.0, + "languages": [], + "name": "Rossi Alpha View", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/RossiAlphaView", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "The micron level generalized defect dynamics code is a numerical tool predicting the overall mechanical response and microstructure evolutions of metals deforming by dislocation glide, cross slip and climb and point defect diffusion and clustering. The tool relies on the use of a Fast Fourier Transform mechanical solver allowing for the computation of mechanical fields resulting from the presence of dislocations, grain boundaries and second phases. The code leverages both field defect mechanics and cluster dynamics modeling framework.\n\n\tThe primary intent of this tool is to validate and calibrate mathematical constitutive models used to describe the mechanical response and microstructure evolutions of metals. This is achieved by tracking the evolution of an ensemble of dislocations and of points defects subjected to mechanical loading. The code can simulate complex microstructures and physical phenomena associated with plasticity. As such, it can be applied to metals with any crystal symmetry (face centered cubic, body centered cubic, hexagonal closed packed). Further, the model can be applied to single crystalline and to polycrystalline aggregates. Simulation volumes can be subjected to mixed boundary conditions (i.e. stress and strain) and the effect of free surfaces can also be accounted for such as to mimic plasticity in thin films and in micropillars.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Generalized defect dynamics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "The TAIl Particle Solver (TaiPS) described in this abstract evaluates the fast ion and electron distribution for inertial confinement fusion applications (ICF). The code was developed under a Laboratory Directed Research and Development (LDRD) project. The code falls under the Los Alamos Plasma Simulation (LAPS) framework, though it operates as a stand alone code. We would like to make it open source in order to enable its use by the broader ICF community. TaiPS solves the non-relativistic Fokker-Planck equation in 1D-2V geometry for a fast particle tail. Up to four ion species are evolved along with the electron population. A suite of approximate collision operators is present: (i) a test particle collision operator, (ii) a linearized Fokker-Planck collision operator, and (iii) and a nonlinear Fokker-Planck collision operator. The tail solution is matched to a bulk distribution function, whose form is evaluated from a Braginskii closure [S. Braginskii, Reviews of plasma physics]. The code utilizes a Chang-Cooper discretization in energy [J. Chang and G. Cooper, Journal of Computational Physics 6, 1 (1970)], a Legendre expansion in the pitch coordinate, and finite different in configuration space. The code has mostly been used to evaluate steady state solutions, though time stepping can be done utilizing PETSc's suite of explicit and implicit schemes. The primary applications of the code are to take the fast ion or electron tail distribution and use them to evaluate the fusion reactivity or various diagnostic signals such as Bremsstrahlung radiation. A separate code has been written to evaluate the fusion reactivity, whereas Bremsstrahlung radiation is evaluated by codes developed by Grisha Kagan's collaborators. Publications that have utilized this code are contained in Refs. [X.-Z. Tang, H. Berk, Z. Guo, and C. McDevitt, Physics of Plasmas 21, 032707 (2014), X.-Z. Tang, C. McDevitt, Z. Guo, and H. Berk, EPL (Europhysics Letters) 105, 32001 (2014), X.-Z. Tang, C. McDevitt, Z. Guo, and H. Berk, Physics of Plasmas 21, 032706 (2014), C. McDevitt, X.-Z. Tang, Z. Guo, and H. Berk, Physics of Plasmas 21, 032708 (2014), C. J. McDevitt, X.-Z. Tang, and Z. Guo, Physics of Plasmas 24, 112702 (2017), C. J. McDevitt, X.-Z. Tang, and Z. Guo, Plasma Physics and Controlled Fusion 61, 025005 (2018), C. McDevitt, X.-Z. Tang, Z. Guo, and H. Berk, Physics of Plasmas 21, 102705 (2014)].", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "TaiPS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "rkmlviewer is an application designed to read and display data encoded in the Keyhole Markup Language.\nThe application provides a graphical window with a first person style camera to view KML files in 3d.\nThe application is built to display \"large scale\" data (not suitable for resolution > 100km)\nrkmlviewer is written in Go, uses OpenGL 3.3 for rendering, and GLFW for cross platform windowing support.\nrkmlviewer contains a command line (ncurses style) gui to select application options at runtime.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "rkmlviewer", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "Matlab Resistive Wake Calculator \nThis is a Matlab code that calculates the resistive wake from an undulator beam pipe. The code is based on a published paper by Bane and Stupakov [1]. The code can calculate the wake for a round or a flat beam pipe, and can calculate the wake for different types of metal (for example, Aluminum or Copper). The code can be used to simply calculate the wake (“GenericACWakeForGen”), or it can be used to append a wake calculation to an input file for the free electron laser code Genesis [2] (“ReadFullBeam”). The code can also be used to simply plot out the impedances or wakes of a round or flat beam (“CalcZbarFlat” and “ZbarAC”). The top level code, “ReadFullBeam” is designed to read an output from the beam code Elegant [3] that has been converted to Genesis format using the command “Elegant2Genesis.” \n\n\nReferences:\n[1] K. Bane and G. Stupakov, “Resistive Wall Wakefield in the LCLS Undulator,” Proc. Of 2005 Part. Accel. Conf., Knoxville, TN, p. 3390 – 3392.\n[2] S. Reiche, “GENESIS 1.3: a fully 3D time-dependent FEL simulation code,” Nucl. Inst. Methods in Phys. A, 429 (1999) 243-248.\n[3] M. Borland, “elegant: A Flexible SDDS-Compliant Code for Accelerator Simulation,” Advanced Photon Source LS-287, September 2000.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "QuinnsWakeCalculator", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2021-11-08", + "metadataLastUpdated": "2021-11-08" + }, + "description": "Model Coupling Tookit", + "laborHours": 34184.8, + "languages": [], + "name": "Model Coupling Toolkit v2.11", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MCSclimate/MCT", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "2.11" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-11-08", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This collection of python scripts is the co-optimizer, or the co-optima scenario analysis tool. This release (V0.2) is intended primarily to analysis such as done to support co-optima project planning and identification of potentially fruitful research directions rather than specify particular fuel blends. The intention of this release is to add concreteness to the co-optimization concepts, and facilitate discussion between the teams and stakeholders as the tool evolves. The user interface is currently non-existant from a productions standpoint. Questions, comments, and rants can be directed to Ray.Grout@nrel.gov", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "Co-Optima Co-Optimizer (Co-optimization of fuels and engines Co-optimizer) [SWR-18-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/cooptima-co-optimizer", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "V0.2" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-11-10", + "metadataLastUpdated": "2024-03-11" + }, + "description": "NREL's PowerGridworld provides a modular simulation environment for training heterogenous, grid-aware, multi-agent reinforcement learning (RL) policies at scale. The package enables the user to create component gym environments that can be composed into more complex agents. For example, a grid interactive building environment can be created by composing together component environments each encapsulating the building, PV, and battery physics. These multi-component environments can then be combined into multi-agent simulation where each agent's power consumption/injection becomes an input for solving the optimal power flow on a distribution feeder modeled in OpenDSS. Information from OpenDSS, such as bus voltages and line flows, can be included in the agents' observation spaces to enable grid-aware rewards. The default API for the PowerGridworld simulator conforms to RLLib's MultiAgent API and thus enables distributed training using HPC and cloud resources.", + "laborHours": 0.0, + "languages": [], + "name": "PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems [SWR-22-07]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PowerGridworld", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-11-10", + "metadataLastUpdated": "2022-01-28" + }, + "description": "PS-Samp is a software that reduces a given dataset by pruning data. Data is downselected such that it uniformly spans the phase-space, thereby ensuring that the full dataset is correctly represented. The algorithm relies on estimating the probability map of the data and using it to construct an acceptance probability. The software is designed to handle very large data sets.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PS-Samp (Phase-Space Sampling)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Phase-space-sampling", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "buonassisi@mit.edu" + }, + "date": { + "created": "2021-11-10", + "metadataLastUpdated": "2021-11-10" + }, + "description": "This is a code and data repository to conduct Bayesian Optimization with knowledge constraints for manufacturing process of perovskite solar cells ", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PV-Lab/SL-PerovskiteOpt", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PV-Lab/SL-PerovskiteOpt", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-11-12", + "metadataLastUpdated": "2023-05-25" + }, + "description": "Hydropower is one of the most mature forms of renewable energy generation. The United States (US) has almost 103 GW of installed, with 80 GW of conventional generation and 23 GW of pumped hydropower [1]. Moreover, the potential for future development on Non-Powered Dams is up to 10 GW. With the US setting its goals to become carbon neutral [2], more renewable energy in the form of hydropower needs to be integrated with the grid. Currently, there are no publicly available tool that can estimate the hydropower potential for existing hydropower dams or other non-powered dams. The HydroGenerate is an open-source python library that has the capability of estimating hydropower generation based on flow rate either provided by the user or received from United States Geological Survey (USGS) water data services. The tool calculates the efficiency as a function of flow based on the turbine type either selected by the user or estimated based on the “head” provided by the user.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Hydrogenerate: Open Source Python Tool To Estimate Hydropower Generation Time-series", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HydroGenerate", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "3.6 or newer" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-11-15", + "metadataLastUpdated": "2021-11-16" + }, + "description": "Archparse is a Python package that holds the purpose and capability of converting the contents of a text file to a functioning neural network based on the Tensorflow 2.X framework. This is able to be done with minimal written Python code and next to no knowledge of how to build models with Tensorflow directly. More specifically Archparse parses a text file with extension \".arch\" which contains neural network architecture information that corresponds to either the Tensorflow 2.X API or custom code written with the Tensorflow 2.X API. Included in the initial version is the capacity to easily produce sequential autoencoders and sequential neural networks.", + "laborHours": 0.0, + "languages": [], + "name": "Archparse", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EnderWiggin14/ARCHPARSE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-11-15", + "metadataLastUpdated": "2021-11-16" + }, + "description": "Optvis is a web application to visualize control flow graphs, call graphs, disassembly code from a binary or executable. The main use case is visualizing the compiler optimizations in binary code.", + "laborHours": 0.0, + "languages": [], + "name": "Optvis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CcNav", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-11-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "We show how to model discrete ordinary differential equations (ODE) with algebraic nonlinearities as deep neural networks with varying degrees of prior knowledge.\nWe derive the stability guarantees of the network layers based on the implicit constraints imposed on the weight's eigenvalues. Moreover, we show how to use barrier methods to generically handle additional inequality constraints.\nWe demonstrate the prediction accuracy of learned neural ODEs evaluated on open-loop simulations compared to ground truth dynamics with bi-linear terms.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/neural_ODE_ICLR2020", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/neural_ODE_ICLR2020", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-11-16", + "metadataLastUpdated": "2021-11-16" + }, + "description": "Genealogical importance splitting marches towards a rare event by iteratively selecting and replicating realizations that are headed towards a rare event. The replication step is made difficult when applied to deterministic systems as the initial conditions of the offspring realizations need to be adjusted. Typically, a random perturbation is applied to the offspring. For some cases, this cloning technique may not be adequate and prevent variance reduction in the probability estimate. A GAN-based replication process is proposed to address this limitation. The perturbations applied to the clones are physically consistent instead of being randomly chosen. The proposed method allows reducing the variance in the probability estimation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "GANISP (GAN-assisted Importance SPlitting)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GANISP", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jgoodall@ornl.gov" + }, + "date": { + "created": "2021-11-17", + "metadataLastUpdated": "2021-11-17" + }, + "description": "Capture packet data from a computer's network interface in a scalable manner and making it available to search and filter across the most commonly used fields", + "laborHours": 0.0, + "languages": [ + "Go" + ], + "name": "jgoodall/mercury", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jgoodall/mercury", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v1.0.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-19", + "metadataLastUpdated": "2021-11-19" + }, + "description": "The presented python code provides wrapper functions for two decomposition algorithms: One algorithm to decompose Maximum Clique problems and one to decompose Minimum Vertex Cover problems. The functions take as input a networkx graph object, and decompose either problem on the input graph recursively into subproblems such that the optimal solution can be constructed from the optimal solutions of both subproblems. The recursion ends as soon as the subproblems reach a pre-specified size limit by the user, and they can be solved using any method provided in advance by the user as external function. This includes exact solvers or an adiabatic quantum annealer.", + "laborHours": 0.0, + "languages": [], + "name": "Decomposition Algorithms for Scalable Quantum Annealing", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Decomposition-Algorithms-for-Scalable-Quantum-Annealing", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-19", + "metadataLastUpdated": "2021-11-19" + }, + "description": "HSNMon is a robust high speed network monitoring daemon that provides insight into network availability, hardware failure, and network performance for switches and network cards. HSNMon collects counters, forwarding tables, and error information at high resolution using publicly available Omni-Path Management APIs. The collected data can be forwarded into multiple logging infrastructures including syslog and message queuing systems. HSNMon is only the infrastructure for collecting the network data. It does not include any collected data or proprietary LANL information", + "laborHours": 0.0, + "languages": [], + "name": "HSNMon: High-Speed Monitoring Software for Omni-Path", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/hsnmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-19", + "metadataLastUpdated": "2021-11-19" + }, + "description": "materialsCloudCompute (mCC) is a software package for running easily parallelizable materials science theoretical computations on Amazon Web Services (AWS) infrastructure. mCC provides tools to partition out computational problem into smaller subproblems which can be run in parallel, and ensure that each of those subproblems completes successfully. It utilizes the following AWS services: EC2, S3, and RDS. It operates by launch a managing EC2 instance, which can launch worker instances that perform the calculations. The Managing instance tracks the subproblems and ensures that the Worker instances continue to operation, killing and relaunching them if they fail.", + "laborHours": 0.0, + "languages": [], + "name": "materialsCloudCompute", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/materialsCloudCompute", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-19", + "metadataLastUpdated": "2021-11-19" + }, + "description": "This computer code uses the concept of the parallax to compute the x, y and z coordinates of points found using transmission electron microscopy (TEM), or any transmission imaging technique, using two images, each taken at a different perspective of the region containing the points. Points correspond, but are not limited, to the center of cavities or precipitates, positions of irradiation black dot damage, positions along a dislocation line, or positions along where an interface meets a free surface. Features can include dislocations, interfaces, cavities, precipitates, inclusions etc. The x, y and z coordinates of the points are output in a text file. The code also allows the user to visualize the features containing the points in three dimensions.", + "laborHours": 0.0, + "languages": [], + "name": "Obtain3D_open", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Obtain3D_open", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ostrouchovg@ornl.gov" + }, + "date": { + "created": "2021-11-20", + "metadataLastUpdated": "2021-11-23" + }, + "description": "Clusters medical trajectories (unequally spaced and unequal length time series) aligned by an intervention time. Performs k-means clustering, where each mean is a thin plate spline fit to all points in a cluster. Distance is MSE across trajectory points to cluster spline. Provides silhouette plots and Adjusted Rand Index evaluations of the number of clusters. Scales well to large data with multicore parallelism available to speed computation.", + "homepageURL": "https://cran.r-project.org/package=clustra", + "laborHours": 0.0, + "languages": [ + "R" + ], + "name": "clustra", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cran.r-project.org/package=clustra", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0.1.5" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-22", + "metadataLastUpdated": "2021-11-22" + }, + "description": "The low-tilt tomographic reconstruction (LoTToR) method is a post-processing method to correct the missing-wedge artifact, which contains a model-free iteration process under a set of constraints in real and reciprocal spaces. A proof of concept is conducted by using the LoTToR on a phantom, i.e., a simulated 3D reconstruction from a low-tilt series of images, including that within a tilt range of ±15°. The method is validated by using both negative-staining (NS) and cryo-electron tomography (cryo-ET) experimental data. A significantly reduced missing-wedge artifact verifies the capability of LoTToR, suggesting a new tool to support the future study of macromolecular dynamics, fluctuation and chemical activity from the viewpoint of single-molecule 3D structure determination. Moreover, the software can be used for hospital computer tomography (CT) to reduce the radiation damage to patients without reducing the CT image quality.", + "homepageURL": "https://rengroup.lbl.gov/page6/page6-LoTToR-download.html", + "laborHours": 0.0, + "languages": [], + "name": "LoTToR: An Algorithm for Missing-Wedge Correction of the Low-Tilt Tomographic 3D Reconstruction of a Single-Molecule Structure (LoTToR) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://rengroup.lbl.gov/page6/page6-LoTToR-download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-11-22", + "metadataLastUpdated": "2023-03-08" + }, + "description": "A graphical user interface (GUI) that helps analyze data from coincidence Doppler broadening positron annihilation spectroscopy. It is a quick tool to rapidly reduce large data and conveniently analyze multiple datasets.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Coincidence Doppler Broadening Analysis Program", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/CDB_Analysis_Program", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-12-20" + }, + "description": "Millstone is a mechanics solver for geological processes, focusing on coupling to reservoir simulators. It solves the linear balance of momentum with incremental poroelastic stress rate formulations under quasistatic assumptions.", + "homepageURL": "https://link.springer.com/article/10.1007/s11242-019-01254-6", + "laborHours": 0.0, + "languages": [], + "name": "Millstone", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2018-140/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://link.springer.com/article/10.1007/s11242-019-01254-6", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "SoDa is an irradiance-based synthetic Solar Data generation tool to generate realistic sub-minute solar photovoltaic (PV) power time series, that emulate the weather pattern for a certain geographical location. Our tool relies on the National Solar Radiation Database (NSRDB) to obtain irradiance and weather data patterns for the site. Irradiance is mapped onto a PV model estimate of a solar plant's 30-min power output, based on the configuration of the panel. We use a stochastic model with a switching behavior due to different weather regimes as provided by the cloud type label in the NSRDB, with parameters for the cloudy states trained on the high-resolution solar power measurements from a Phasor Measurement Unit (PMU).", + "laborHours": 0.0, + "languages": [], + "name": "SoDa: An Irradiance-Based Synthetic Solar Data Generation Tool (SoDa) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Ignacio-Losada/SoDa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "Floorspace.js is a 2D geometry editor. Users can define an explicit floor plan for each story of a building. A story-by-story interface makes it easy to develop space geometry and assign properties. Referencing satellite imagery or floor plan images, when available, speeds up geometry entry. Conversion of 2D to 3D geometry is currently out of scope for Floorspace.js, a reference implementation is available in the OpenStudio® SDK. Explicit floor plans allow more building-specific information than parameterized shoe-boxes but less information than a full 3D BIM model. Sloped walls, complex roofs, detailed shading structures, and other complex 3D structures are out of FloorspaceJS's scope. In general, if users have a 3D BIM model in a tool that can export a useful BEM representation then it is better to use that export than to recreate a new model using FloorspaceJS. Re-usability and minimal dependencies were key design considerations for software developers. Web technologies can be used in both online and desktop applications. The editor was written in pure JavaScript for maximum portability and re-usability. A custom JavaScript Object Notation (JSON) file format was developed to ease integration with other applications. Custom JSON schema design was a key part of FloorspaceJS development.", + "laborHours": 0.0, + "languages": [ + "C++", + "JavaScript", + "Vue" + ], + "name": "Floorspace.js", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/floorspace.js", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "V0.8.0" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "Background: Codon2Vec is an embedding neural network that predicts 'high' or 'low' gene expression directly from the protein-coding sequences. Embedding neural networks are commonly used for natural language processing (NLP) applications. Analogous to how an English sentence is a string of words, a gene can be thought of as a string of codons. Similar to how NLP neural networks model English sentences as a non-random sequence of words, we considered a coding sequence as a non-random non-overlapping array of codons (k-mers of length = 3). Value Proposition: - Codon2Vec achieved a high median AUC-ROC score of 83.8% when trained and applied to transcriptomic data from 300 fungal species - Unlike Codo2Vec, conventional methods predicting for expression based on codon usage rely on a priori knowledge of optimal codons or a set of reference genes. - Unlike Codon2vec, these methods do not account for the effect of codon order on gene expression. - Codon2Vec neural network bypasses the need for artisanal feature selection step that is necessary for traditional machine learning models.", + "laborHours": 0.0, + "languages": [], + "name": "Codon2Vec v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rhondene/Codon2Vec", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "HYPPO is a hyperparameter optimization (HPO) software that uses surrogate modeling and uncertainty quantification to provide reliable neural network architectures. Similar state-of-the-art HPO technologies do not use such features and mostly perform random searches to explore the parameter space, which can easily become computationally expensive. Using HYPPO, the user is able to reduce by an order of magnitude the number of evaluations necessary to identify the most optimal region in the hyperparameter space. Finally, using asynchronous nested parallelism, we are able to decrease by two orders of magnitude the amount of time required to complete the HPO process.", + "laborHours": 0.0, + "languages": [], + "name": "HYPPO v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/hpo-uq/hyppo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "This software can be used to tune the HPC operations of a Cray system running Slurm workload manager software. This includes many of the customizations that NERSC has made over the past three years. In particular these customizations allow for complex site-local policies to be implemented and managed in a scalable way, or add unique capabilities to slurm via our plugins, including: * performance software integration and compute node staging * temporary directory/dynamic user content management automation * software defined networking integration", + "laborHours": 0.0, + "languages": [], + "name": "NERSC Slurm Software Configurations and Plugins", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/nersc-slurm-contrib", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "turcksinbr@ornl.gov" + }, + "date": { + "created": "2021-11-29", + "metadataLastUpdated": "2021-11-29" + }, + "description": "Thermal field simulation of the additive manufacturing process enhanced using data assimilation.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "adamantine-sim/adamantine", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/adamantine-sim/adamantine", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-11-29", + "metadataLastUpdated": "2021-11-29" + }, + "description": "Symmetric Positive Definite (SPD) enforcement layers for PyTorch. Regardless of the input, the output of these layers will always be a SPD tensor! The `Cholesky` layer uses a cholesky factorization to enforce SPD, and the `Eigen` layer uses an eigendecomposition to enforce SPD. Both layers take in some tensor of shape `[batch_size, input_shape]` and output a SPD tensor of shape`[batch_size, output_shape, output_shape]`. The relationship between input and output is defined by the following. ```python input_shape = sum([i for i in range(output_shape + 1)]) ``` The layers have no learnable parameters, and merely serve to transform a vector space to a SPD matrix space.", + "laborHours": 0.0, + "languages": [], + "name": "spdlayers", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/spdlayers", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-11-29", + "metadataLastUpdated": "2021-11-30" + }, + "description": "A package containing utility components for running processes and managing tasks.", + "laborHours": 0.0, + "languages": [], + "name": "pyaestro", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FrankD412/pyaestro", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2021-12-02" + }, + "description": "SAND2021-0565 O PRIME is a modeling framework designed for the real-time characterization and forecasting of partially observed epidemics. The method is designed to help guide medical resource allocation in the early epoch of the outbreak. Characterization is the estimation of infection spread parameters using daily counts of symptomatic patients. The estimation problem is posed as one of Bayesian inference and solved using a Markov Chain Monte Carlo technique. The framework can accommodate multiple epidemic waves and can help identify different disease dynamics at the regional, state, and country levels. Examples are provided using publicly available COVID-19 data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PRIME", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PRIME", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "fattebertj@ornl.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2021-12-02" + }, + "description": "Library to compute equilibrium compositions and equal chemical potential compositions in binary and ternary alloys.\nThis library supports thermodynamic data formulated according to CALPHAD (Computer Coupling of Phase Diagrams and Thermochemistry) models, as well as dilute binary alloys.\nOne major aim is to solve the Kim-Kim-Suzuki (KKS) equations to obtain local compositions given a local mixture of two phases.\nThese quantities are then used to evaluate the phase-field model driving force (right handside of time-evolution equation), as well as the energy\ndensity", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "ORNL/Thermo4PFM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/Thermo4PFM", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2021-12-02" + }, + "description": "SAND2021-4723 O CausalFS is a Python package that evaluates causal relationships between dataset features and the metric to be predicted. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "CausalFS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CausalFS", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2024-07-26" + }, + "description": "SAND2021-4823 O InterSpec decodes and displays gamma radiation data from a variety of handheld, laboratory, and fixed installation detector types. Once loaded, InterSpec provides a means to interactively analyze the data via a peak-based methodology. InterSpec assists with isotope identification and determines the source strength and shielding characteristics of the measured item. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "HTML", + "C++", + "Shell", + "Makefile", + "C" + ], + "name": "InterSpec v. 1.0.8", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/InterSpec", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.8" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2021-12-02" + }, + "description": "SAND2021-6830 O Capp is a minimal package manager that supports the dependencies of one application. Its value in comparison to other package managers is its high portability across operating systems and its simplicity and usability for High Performance Computing (HPC) programmers. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "CMAKE" + ], + "name": "CApp v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/capp", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "weberb@ornl.gov" + }, + "date": { + "created": "2021-12-03", + "metadataLastUpdated": "2024-01-18" + }, + "description": "A python VNC client written from scratch using python's socket library", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "pyvnc_client", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/pyvnc_client", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-12-07", + "metadataLastUpdated": "2023-03-28" + }, + "description": "Performs Multi-Tiered Iterative Phasing for Single Particle Imaging. The Spinifel code uses distributed computing (using MPI and Legion) to spread work across many compute nodes. On-node computation is accelerated using GPGPUs (using CuPy, and CUDA).", + "laborHours": 0.0, + "languages": [], + "name": "MTIP Single Particle Imaging (Spinifel) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/mtip/spinifel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-12-07", + "metadataLastUpdated": "2021-12-20" + }, + "description": "In order to support the California state goals to reduce the carbon and pollution emissions (AB2127), The goal of this project (HEVI-Pro) is to project the charging infrastructure needs by future medium- and heavy- duty electric vehicles, and assess optimal deployment the infrastructure in California and provide grid impacts analysis. The MHDV projections will also consider transportation system and electric system interaction with light duty vehicles. The project consists of 2 approaches in general: top-down approach that takes aggregated MHDV adoptions as the inputs and provide the county-level projections of charging load profile and infrastructure need, and the bottom-up approach that that incorporates more granular (temporal, spatial and duty-cycle-specific) behaviors of a variety of MHDVs into activity simulations/optimizations for further analysis.", + "homepageURL": "https://sites.google.com/lbl.gov/2020-157/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Medium and Heavy-Duty Electric Vehicle Infrastructure - Load Operations and Deployment (HEVI-LOAD) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2020-157/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2020-157/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-21" + }, + "description": "The ability to embed molecules in a numeric space is essential in order to build mathematical and machine-learning models describing molecular properties or other processes affected by molecules. MACAW is a cheminformatic tool that allows embedding small molecules into a multidimensional numeric space. In the embedding, each molecule is assigned a numeric vector that captures information of the molecule in relation to other molecules, and that vector can be used as input to mathematical models. Molecules that are more similar to each other are embedded closer in this numeric space, whereas molecules that are more different are embedded further away. One advantage of the MACAW embedding technology compared to established alterantives is that it is fast and does not require extensive computational resources or expertise. In particular, MACAW embeddings can be used as input to mathematical models without the need for variable cleaning or feature selection, saving time and simplifying their use. On the other hand, MACAW also contains methods to generate new molecules and to recommend new molecules satisfying a desired molecular property. The generation of new molecules can be biased based on an input set of molecules, effectively generating molecular diversity around it. In its turn, MACAW's molecular recommendation tool is a novel method for evolving molecules in silico towards a desired molecular specification. In this method, the biased molecular generator tool is applied iteratively in combination with a molecular selection step. As a result, in each iteration the molecules selected by the software are increasingly closer to the desired specification. Both the molecular generation and the molecular recommendation tools are very fast, efficient, and intuitive to use.", + "homepageURL": "https://sites.google.com/lbl.gov/2021-187/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "MACAW v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2021-187/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-187/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2024-05-02" + }, + "description": "The Wind-Plant Integrated System Design and Engineering Model (WISDEM®) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM® is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM® turbine design capability. Please install all of the pre-requisites prior to installing WISDEM® by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM® development, please visit the official NREL systems engineering for wind energy website. https://www.nrel.gov/wind/systems-engineering.html", + "laborHours": 229778.4, + "languages": [ + "C", + "Fortran", + "Python" + ], + "name": "WISDEM® (Wind-Plant Integrated System Design and Engineering Model) [SWR-14-05]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/WISDEM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.4.1" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-20" + }, + "description": "The package contains algorithms for the estimation of sprout/plant density and the corresponding enhanced plant vigor from remotely sensed (RS) images. These algorithms aim to improve the plant characterization and monitoring in the early season when the soil component is significant compared to the plant spatial coverage. In such a scenario, the identification of sprouts (or plants) and the estimation of plant vegetation indexes can be performed only using UAV-acquired images. Additionally, because of the extremely high resolution, gridding becomes necessary to improve visualization and provide more informative maps. However, to capture the real range of values of the VIs, it is important to avoid the inclusion of those pixels belonging to the soil component. The sprout/plant density estimation algorithm takes in input a classification map and uses the vegetation class to estimates the plant density within a user-defined grid using a floating window. Similarly, the enhanced plant vigor algorithm takes in input the vegetation index and the classification map. The enhanced vegetation index is computed for each pixel as the average value among those pixels that belong to the vegetation class within a floating window. The software is developed for the MATLAB environment.", + "homepageURL": "https://ipo.lbl.gov/plant-density-and-enhanced-plant-vigor-estimation-algorithms-for-high-resolution-images-2019-179", + "laborHours": 0.0, + "languages": [], + "name": "Plant density and enhanced plant vigor estimation for high-resolution images v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/plant-density-and-enhanced-plant-vigor-estimation-algorithms-for-high-resolution-images-2019-179", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/plant-density-and-enhanced-plant-vigor-estimation-algorithms-for-high-resolution-images-2019-179", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "UMT is a Sn deterministic thermal radiative transport Fortran proxy application. Its primary purpose is to research how data layout, programming paradigms and architectures effect the implementation and performance of Sn transport in Fortran on unstructured meshes. 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Augments the Deep Fluids (Kim et al., 2019) approach as described in our paper \"Latent Space Simulation for Carbon Capture Design Optimization\" (Bartoldson et al., 2021).", + "laborHours": 0.0, + "languages": [], + "name": "Deeper Fluids", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CCSI-Toolset/DeeperFluids", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "YGM provides a simplified distributed memory communication framework based on a mailbox abstraction for HPC applications. YGM is designed for irregular data-driven applications that communicate small message payloads in an all-to-all fashion. YGM aggregates and routes messages into larger payloads to gain greater bandwidth utilization on modern HPC interconnects. YGM has been demonstrated up to 131k cores of IBM BG/P Sequoia and 96k cores of Catalyst at LLNL, and contains a set of graph-inspired benchmarks.", + "laborHours": 0.0, + "languages": [], + "name": "YGM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ygm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-10" + }, + "description": "Zero-RK is a software package that simulates chemically reacting systems using sparse, preconditioned, adaptive matrix methods to achieve orders-of-magnitude reduction in simulation time while maintaining accurate results.", + "laborHours": 13497.6, + "languages": [], + "name": "Zero-Order Reaction Kinetics v3.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/zero-rk", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "Background: Machine learning (ML) based risk stratification models of Electronic Health records (EHR) data may help to optimize treatment of COVID-19 patients, but are often limited by their lack of clinical interpretability and cost of laboratory tests. We develop a ML based tool for predicting adverse outcomes based on EHR data to optimize clinical utility under a given cost structure. This cohort study was performed using deidentified EHR data from COVID-19 patients from ProMedica Healthcare in northwest Ohio and southeastern Michigan. Methods: We tested performance of various ML approaches for predicting either increasing ventilatory support or mortality and the set of model features under a budget constraint was optimized via exhaustive search across all combinations of features. Results: The optimal sets of features for predicting ventilation under any budget constraint included demographics and comorbidities (DCM), basic metabolic panel (BMP), D-dimer, lactate dehydrogenase (LDH), erythrocyte sedimentation rate (ESR), CRP, brain natriuretic peptide (BNP), and procalcitonin and for mortality included DCM, BMP, complete blood count, D-dimer, LDH, CRP, BNP, procalcitonin and ferritin. Conclusions: This study presents a quick, accurate and cost-effective method to evaluate risk of deterioration for patients with SARS-CoV-2 infection at the time of clinical evaluation.", + "laborHours": 0.0, + "languages": [], + "name": "Budget Constrained Machine Learning for Early Prediction of Adverse Outcomes for COVID-19 Patients", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/BCML-COVID19", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "This code repository contains the implementation of the \"High-Performance Approximate Computing\" (HPAC) toolkit. The toolkit allows you to approximate your own C/C++. The developer uses \"pragma's\" to annotate code regions as approximate. The compiler extensions lower these pragmas to either compiletime approximate techniques or runtime approximation techniques. At execution time, the implemented runtime system decides which annotated regions it should approximate. HPAC also provides a set of script utilities. The utilities perform a grid search within approximation parameters and performance. The user can analyze the raw data to identify optimal approximation techniques for the application.", + "laborHours": 0.0, + "languages": [], + "name": "High Performance Approximate Computing", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/HPAC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2023-09-11" + }, + "description": "OCHRE™: Object-Oriented Controllable High-Resolution Residential Energy Model\n\nA high-fidelity, high-resolution residential building model with behind-the-meter DERs and flexible load models that integrates with controllers and distribution models in building-to-grid co-simulation platforms.\n\nThe full documentation for OCHRE can be found at https://ochre-docs-final.readthedocs.io/en/latest/", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "OCHRE™ (Object-Oriented Controllable High-Resolution Residential Energy Model) [SWR-19-71]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OCHRE", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.8.3-beta" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "Code framework to perform simulations of nuclear reactions with incident particles including gammas, protons, neutrons, deuterons, tritons, helium-3, and alphas to develop nuclear data libraries and study nuclear reaction phenomona. The code can model nuclear reactions or initial populations specified by the user. The decays principally follow the compound-nucleus hypothesis and the statistical decay of Hauser and Feshbach. The code models nuclear decays with a Monte Carlo process that tracks the decay of each state. Data libraries are produced that can be translated into GNDS (generalized Nuclear Data Structure). YAHFC can also be used as an event generator, with individual decays written to disk for offline analysis. Both serial and MPI versions are provided. YAHFC does NOT perform transport of nuclear reactions through materials, only the primary reaction with a target material.", + "laborHours": 0.0, + "languages": [], + "name": "Yet Another Hauser-Feshbach Code", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Yet-Another-Hauser-Feshbach-Code", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "MuMMI Core is the central component of the Multiscale Machine-Learned Modeling Infrastructure (MuMMI), a scalable and generalizable framework that couples pairs of models using machine learning and in situ feedback across three scales of resolution.", + "laborHours": 0.0, + "languages": [], + "name": "Multiscale Machine-Learned Modeling Infrastructure Core", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mummi-framework/mummi-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "MuMMI RAS is the application component of the Multiscale Machine-Learned Modeling Infrastructure (MuMMI). It simulates RAS protein interactions at three scales of resolution coupled with ML-based selection and in-situ feedback. MuMMI RAS is particularly configured for massive scale, running thousands of simultaneous jobs with several terabytes of data on Lassen and Summit.", + "laborHours": 0.0, + "languages": [], + "name": "Multiscale Machine-Learned Modeling Infrastructure RAS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mummi-framework/mummi-ras", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "The code performs image intensity normalization. A new intensity normalization method is presented, which works well with images whose pixel intensity distribution follow a Gamma Probability Distribution. Some examples are provided to show the normalization effect. This new intensity normalization method is also compared to some other well-established intensity normalization methods.", + "laborHours": 0.0, + "languages": [], + "name": "cdf_normalize", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xiaotingzhong/image_intensity_gamma_normalization", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "Converts XML file formats to CLI format for 3D printing; combines equivalent polyline segments (laser power, velocity, focus/spot-size) into a single polyline for a given path. Also plots CLI file format with respect to power for a single specified layer, or the entire file, for 3D printed applications.", + "laborHours": 0.0, + "languages": [], + "name": "AMXML to CLI multi-segment polyline converter and plotter", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CLDruzgalski/AM_fileConverters", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "weberb@ornl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "ORNL conducted an experiment to test COTS (commercial off the shelf) SOAR tools. Vendors interested in entering their tool into the experiment were asked to submit information videos about their tool for phase 1 to down-select which tools should make it through to the testing phase. SOC operators were assigned to watch a subset of the videos such that each video was assigned to the same number of operators. After watching all the videos, operators completed surveys which asked them to grade basic aspects about the tool as best as they could based on the provided video, and asked them to rank the order of their interest in the vendors they were assigned to watch videos on. The problem solved was how do we aggregate the results of the surveys and each of the operator's ranked lists into an overall ranking of all the tools. In addition, it was desirable to be able to work on this code before final results were collected from operators, so code to generate fake data was developed to output in the same output as the survey results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Soar Survey Scoring", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/soar_survey_scoring", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "C-PACE Market Assessment Tool This tool was developed for the U.S. Department of Energy’s Commercial Property Assessed Clean Energy (C-PACE) Working Group to support state and local governments creating, joining, and implementing C-PACE programs. This tool allows users to input a jurisdiction (city, county, or state) and automate a report with building characteristics, energy use, and energy efficiency savings opportunities for commercial buildings in that jurisdiction. The report generated by the tool identifies jurisdiction-specific energy end uses, building use types, and building technologies that a local C-PACE program should consider focusing on to more effectively allocate limited resources and maximize energy savings and investment.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/CPACE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/CPACE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "GLVis is a lightweight tool for accurate and flexible finite element visualization. GLVis uses OpenGL with interactive refinement to accurately represent curved high-order meshes and a wide variety of finite element grid functions defined on them.", + "laborHours": 17343.2, + "languages": [], + "name": "GL Visualization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/glvis/glvis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "4.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "Quandary numerically simulates and optimizes the time-evolution of open quantum systems. The underlying dynamics are modelled by Lindblad's master equation, a linear ordinary differential equation (ODE) describing quantum systems interacting with the environment. Quandary solves this ODE numerically by applying a time-stepping integration scheme, and utilizes a gradient-based optimization approach to determine optimal control pulses that drive the quantum system to a desired target state. Two optimization objectives are considered: (a) Unitary gate optimization that finds controls to realize a unitary gate transformation, and (b) optimal reset that aims to drive the quantum system to the ground states. Gradient-based optimization schemes utilizing Petsc's Tao optimization package are applied to generate control pulses that minimize the respective measure. To evaluate the gradient of the objective function, the discrete adjoint method is used while leveraging techniques from Algorithmic Differentiation to produce exact and consistent gradients. To mitigate excessive execution run times, the software can be build together with the XBraid software library which provides a parallelization strategy to distribute the time-evolution of the underlying dynamics onto multiple processor.", + "laborHours": 0.0, + "languages": [], + "name": "Quandary", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/quandary", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "Clippy (CLI + PYthon) is a Python language interface to HPC resources. Precompiled binaries that execute on HPC systems are exposed as methods to a dynamically-created Clippy Python object, where they present a familiar interface to researchers, data scientists, and others. Clippy allows these users to interact with HPC resources in an easy, straightforward environment - at the REPL, for example, or within a notebook - without the need to learn complex HPC behavior and arcane job submission commands.", + "laborHours": 0.0, + "languages": [], + "name": "Clippy", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/clippy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-14" + }, + "description": "Summary: To address the need for improved tools for annotation and comparative genomics of bacteriophage genomes, we developed multiPhATE2. As an extension of the multiPhATE code, multiPhATE2 includes comparative genomics codes for gene matching among sets of input bacteriophage genomes, and scales well to large input data sets due to incorporation of multiprocessing in the functional annotation and comparative genomics subsystems. Furthermore, additional search algorithms and databases have been added to the functional annotation subsystem. MultiPhATE2 was implemented in Python 3.7, and runs as a command-line code under Linux or MAC-OS.", + "laborHours": 0.0, + "languages": [], + "name": "Multi-genome Phage Annotation Toolkit and Evaluator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/multiPhATE2", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "Lighter version of the Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE)", + "laborHours": 0.0, + "languages": [], + "name": "psuade-lite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade-lite", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.8" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "The code for regularized adversarial domain adaption is provided here. The RADA methodology is developed for correcting climate model biases using an adversarial learning strategy. The code here covers the data processing, the algorithm, the baseline models, and the evaluation.", + "laborHours": 0.0, + "languages": [], + "name": "RADA", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/panbaoxiang/RADA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "swadling1@llnl.gov" + }, + "date": { + "created": "2021-12-13", + "metadataLastUpdated": "2021-12-20" + }, + "description": "MATLAB Functions for calculating the Thomson scattering cross-section", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "LLNL/Thomson-Scattering-Cross-Section-Calculator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Thomson-Scattering-Cross-Section-Calculator", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-14", + "metadataLastUpdated": "2021-12-14" + }, + "description": "Code to calculate Thomson scattering cross sections.", + "laborHours": 0.0, + "languages": [], + "name": "Thomson scattering Cross section Calculator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Thomson-Scattering-Cross-Section-Calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-14", + "metadataLastUpdated": "2021-12-14" + }, + "description": "The Replicative Assessment of Spectrometric Equipment (RASE) is a software for evaluating the performance of radiation detectors and isotope identification algorithms. It uses a semi-empirical approach to rapidly generate synthetic spectra and inject into detector's software to obtain nuclide identification response. RASE facilitates studies of spectroscopic device performance and a quantitative assessment of its capabilities to correctly distinguish and identify isotopes of interest in realistic scenarios.", + "laborHours": 4088.8, + "languages": [], + "name": "Replicative Assessment of Spectroscopic Equipment", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RASE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-14", + "metadataLastUpdated": "2021-12-14" + }, + "description": "This code has been previous released as open source under LLNL-CODE-529294. The HEXRD program comprises a library of X-ray diffraction analysis tools and a stand-alone GUI application. While there are many software packages that provide similar capabilities, HEXRD was designed to provide an extremely flexible and extensible basis for describing a broad array of X-ray diffraction instruments; this includes both mono- and poly-chromatic modalities as well as poly- and single-crystal samples. The high-level objects include Material: an abstraction for defining crystalline materials, including unit cell parameters and anisotropic elastic moduli Imageseries: an interface for series of diffraction images containing one or more frames, including provisions for metadata. Instrument: an abstraction of an X-ray diffraction instrument including support for the definition of multiple detector elements as well as powder, Laue, and mono-chromatic single/multi-grain diffraction analysis modalities (including attendant calibration routines). The hexrdgui package is a standalone PySide2/Qt5 GUI built on top of hexrd. The 0.8.1 release includes various bug fixes as well as some new functionality in the GUI, including: o Enhancements to the import tools for LLNL diffraction instruemtns (PXRDIP and TARDIS) o The ability to save 1-d LeBail fits of integrated diffraction spectra.", + "laborHours": 0.0, + "languages": [], + "name": "Highly Extensible X-ray Diffraction Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HEXRD/hexrd", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.8.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-14", + "metadataLastUpdated": "2021-12-16" + }, + "description": "Massively Parallel and Portable Genomic Sequence Analysis (mappgene) is a sequencing analysis workflow for high performance computing. It incorporates novel technologies to simplify and accelerate genetics research.", + "laborHours": 0.0, + "languages": [], + "name": "Massively Parallel and Portable Genomic Sequence Analysis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mappgene", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2024-07-01" + }, + "description": "Reducing greenhouse gas emissions remains a critical challenge for the transportation and chemical sectors. The electrochemical reduction of carbon dioxide is a potential pathway for production of fuels and chemicals that uses atmospheric carbon dioxide as a feedstock. Here we present an analysis of the potential for carbon dioxide captured from point sources and via direct air capture to be utilized in electrochemical reduction under different market scenarios. Using a numerical optimization framework and national data sets, scenarios for nationwide production of ethylene, formate, and carbon monoxide are evaluated at scales comparable to current production of these molecules in the United States. We show that developing a network for production of these products at scale requires capture and utilization of significant portions of the carbon dioxide that is currently emitted from large stationary point sources. Because carbon dioxide point sources are spatially and compositionally variable, their use for carbon dioxide reduction depends on electricity prices, capture cost, and location. If the power sector in the United States is decarbonized, carbon dioxide supply decreases significantly, increasing the importance of utilizing other carbon dioxide streams, and increasing the likelihood that direct air capture plays a role in supplying carbon dioxide feedstocks. These findings provide a first insight into the feedstock and energy constraints for carbon dioxide reduction.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "CO2ROpt (Feedstock Allocation Optimization Model) [SWR-22-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CO2ROpt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "Danish is a forward modeling package for curvature wavefront sensing in the geometric limit.", + "laborHours": 0.0, + "languages": [], + "name": "danish", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmeyers314/danish", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "CUDAMicroBench is a collection of fourteen microbenchmarks that demonstrate performance challenges in CUDA programming and techniques to optimize the CUDA programs to address these challenges. It also includes examples and techniques for using advanced CUDA features such as data shuffling between threads, dynamic parallelism, etc that can help users optimize the CUDA program for performance.", + "laborHours": 0.0, + "languages": [], + "name": "CUDAMicroBench", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CUDAMicroBench", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "This repo demonstrates how to use the LLNL developed Gaussian process hyperparameter estimation method, MuyGPS, for image classification using Zwicky Transient Facility (ZTF) data.", + "laborHours": 0.0, + "languages": [], + "name": "ZTF_image_classification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Kerianne28/ZTF_image_classification", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-23" + }, + "description": "MuyGPs is a GP estimation method that affords fast hyperparameter optimization by way of performing leave-one-out cross-validation. MuyGPs achieves best-in-class speed and scalability by limiting inference to the information contained in k nearest neighborhoods for prediction locations for both hyperparameter optimization and tuning. This feature affords the optimization of hyperparameters by way of leave-one-out cross-validation, as opposed to the more expensive loglikelihood evaluations requires by similar sparse methods", + "laborHours": 0.0, + "languages": [], + "name": "MuyGPyS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MuyGPyS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "These scripts document the code used to analyze the Death Valley Regional Flow System (DVRFS) microbial community for a manuscript titled \"Subsurface Planktonic Microbial Communities Reflect Regional-Scale Groundwater Hydraulic Connectivity\".", + "laborHours": 0.0, + "languages": [], + "name": "DVRFS Microbiome 2021 Manuscript Code", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/2021_DVRFS_microbiome", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "Source code for Brain Attend and Decode paper. Functional magnetic resonance imaging (fMRI) is a neuroimaging modality that captures the blood oxygen level in a subject's brain while the subject either rests or performs a variety of functional tasks under different conditions. Given fMRI data, the problem of inferring the task, known as task state decoding, is challenging due to the high dimensionality (hundreds of million sampling points per datum) and complex spatio-temporal blood flow patterns inherent in the data. In this work, we propose to tackle the fMRI task state decoding problem by casting it as a 4D spatiotemporal classification problem. We present a novel architecture called Brain Attend and Decode (BAnD), that uses residual convolutional neural networks for spatial feature extraction and self-attention mechanisms for temporal modeling. We achieve significant performance gain compared to previous works on a 7-task benchmark from the large-scale Human Connectome Project-Young Adult (HCP-YA) dataset. We also investigate the transferability of BAnD's extracted features on unseen HCP tasks, either by freezing the spatial feature extraction layers and retraining the temporal model, or finetuning the entire model. The pre-trained features from BAnD are useful on similar tasks while finetuning them yields competitive results on unseen tasks/conditions.", + "laborHours": 0.0, + "languages": [], + "name": "Attend and Decode: 4D fMRI Task State Decoding Using Attention Models", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/BAnD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1." + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2023-03-13" + }, + "description": "This code allows for a geologic cross-sectional profile to be obtained from a user-drawn profile line within a web map application.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Interactive Web Mapping Tools And Custom Subsurface Cross-sections For Interdisciplinary Geologic Investigation", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/SFWDSubsurface", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "This model is a cellular automata-based algorithm used to predict grain-scale microstructure development. Nucleation and growth of existing grains are considered in an initially liquid domain, where the temperature field evolution is either driven through heat transport simulation data or a frozen temperature approximation (i.e., a constant cooling rate and a fixed thermal gradient). The growth of grains is based on the decentered octahedron algorithm published by Gandin and Rappaz (https://doi.org/10.1016/S1359-6454(96)00303-5), where the grain envelopes are tracked as approximations of the evolving dendritic growth front. The input heat transport data, which can come from simulation of an arbitrary processing technique, consists of coordinates and times at which said coordinates fall below the liquidus and solidus temperatures for the final time. As a result, only the final solidification of a given region is modeled (no remelting). The code is designed to be compatible with pre-Exascale architectures, and uses MPI and the Kokkos library to decompose the computational domain and offload solidification calculations to GPUs.", + "laborHours": 0.0, + "languages": [], + "name": "Exascale-capable cellular automaton for nucleation and grain growth", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ExaCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2022-03-17" + }, + "description": "krowkee is a toolkit for scalably and efficiently summarizing many data streams in distributed memory. krowkee is intended for applications where one needs to summarize huge loosely structured data, such as matrices or graphs, where individual components such rows/columns or vertex adjacency information are impractical to store and directly inspect. krowkee ingests these objects as data streams - unstructured, arbitrarily ordered lists of updates - and accumulates summaries thereof in the form of data sketches.", + "laborHours": 0.0, + "languages": [], + "name": "krowkee", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/krowkee", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "XPlacer Machine Learning Guided Data Placement uses machine learning model to assist programmers to select the data placement advises for application running on HPC system with Nvidia GPUs. XPlacer Machine Learning Guided Data Placement consists three components: (1) 4 revised benchmarks from Rodinia benchmarks; (2) compiler script and execution script to generate variants, and collect training data for the machine learning model; (3) the scripts to post-process the collected data and generate the machine leaning model.", + "laborHours": 0.0, + "languages": [], + "name": "XPlacer Machine Learning Guided Data Placement", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/peihunglin/XPlacer-ML-DataPlacement", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "The topology optimization community has regularly employed optimization algorithms from the operations research community. However, these algorithms are implemented in the sequence space l2 instead of the\nproper function space where the design variable resides. In this software, we benchmark the mesh independent implementation of pyMMAopt with three common problems in topology optimization. We show how the volume fraction variable discretization on non-uniform meshes affects the convergence of\nl2 based optimization algorithms and how pyMMAopt successfully achieves mesh independent convergence.", + "homepageURL": "https://zenodo.org/record/5526481#.YU36FMZOmL8", + "laborHours": 0.0, + "languages": [], + "name": "Mesh independency in topology optimization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://zenodo.org/record/5526481#.YU36FMZOmL8", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "0.0.1" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-12-30", + "metadataLastUpdated": "2021-12-30" + }, + "description": "JOBS EV estimates economic impact associated with deploying electric vehicle supply equipment. It is a derivative of the other JOBS models available at the ES website.", + "homepageURL": "https://jobsfc.es.anl.gov", + "laborHours": 0.0, + "languages": [], + "name": "JOBS EV", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://jobsfc.es.anl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-12-30", + "metadataLastUpdated": "2022-01-03" + }, + "description": "PowerSAS.m is a robust, efficient and scalable power grid analysis framework based on semi-analytical solutions (SAS) technology for MATLAB/Octave users. It provides various functionalities for power grid analysis including steady-state analysis, dynamic analysis and hybrid extended-term analysis. It features high numerical robustness, enhanced computational performance and highly customizable and extensible user interfaces.", + "laborHours": 0.0, + "languages": [], + "name": "POWERSAS.m ( A POWER GRID ANALYSIS TOOKBOX BASED ON SEMI-ANALYTICAL SOLUTION APPROACH)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ANL-CEEESA/powersas.m/blob/release/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-CEEESA/powersas.m", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-03" + }, + "description": "This code performs fast interpolation for volume datasets, specifically, Laplace and Matern interpolation where missing data are on a grid of arbitrary dimension.", + "laborHours": 0.0, + "languages": [], + "name": "LaplaceInterpolation.jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/vishwas1984/LaplaceInterpolation.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-03" + }, + "description": "Slepians.jl is a package that solves the concentration problem of Slepian, Landau and Pollak, numerically. Loosely speaking, we find a function that is both finite in extent and has a Fourier transform which lies in a certain domain. In a single dimension, with discrete sampling, the discrete prolate spheroidal sequences solve this optimization problem.", + "laborHours": 0.0, + "languages": [], + "name": "Slepians.jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lootie/Slepians.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-04" + }, + "description": "The code is a python implementation of the optimization algorithm that is proposed in \"Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints\" (Apt# 163042). The code is not a general purpose optimization software but is designed to solve the specific class of optimization problems in the aforementioned article. To allow reproducibility it is implemented close to the theoretical framework that has been developed in the aforementioned article. It will be published without any third-party dependencies except for python and some popular and widespread python libraries.", + "laborHours": 0.0, + "languages": [], + "name": "TRUST REGION METHOD FOR BOUND-CONSTRAINED MPCCS WITH NONLINEAR OBJECTIVE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/paulmanns/slpcc", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-05" + }, + "description": "AutoPhaseNN is a deep learning (DL) based approach for solving the phase problem. By combining the 3D convolutional neural network (CNN) with the physics of the imaging technique, AutoPhaseNN is trained to learn the inversion from the measured intensity to the amplitude and phase images without labeled data. Once trained, AutoPhaseNN is ~100X faster than conventional iterative phase retrieval methods,", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "AUTOPHASENN: UNSUPERVISED PHYSICS-AWARE DEEP LEARNING FOR PHASE RETRIEVAL", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-05" + }, + "description": "The software being disclosed is the Reference Governor plug-in for Risk Analysis Virtual Environment (RAVEN) developed in Idaho National Laboratory. This software is used as a part of the supervisory control system for integrated energy system project, which can receive the original control variable issued by the upstream control system, then adjust the control variable based on the system states and performance projection of the downstream power-generating systems, in order to keep the response of the downstream systems within all the thermal mechanical constraints.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "REFERENCE GOVERNOR PLUG-IN FOR RAVEN", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-01-05", + "metadataLastUpdated": "2022-01-05" + }, + "description": "Converts XML format files to VTK format files for visualization of 3D printing.", + "laborHours": 0.0, + "languages": [], + "name": "Convert XML to VTK", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CLDruzgalski/AM_fileConverters", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "000" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "This is a set of utilities for reading and manipulating PIO files written in python and C++. These files are intended to be building blocks for other scripts / programs that will use them to do great things. The PIO format itself is described in LA-UR-05-7425 at page 102 and embodied in code LA-CC-05-052. In addition to reading the raw PIO files, the bundled utilities will expand variable that use a compressed sparse row notation", + "laborHours": 0.0, + "languages": [], + "name": "PIO Tools", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/piotools", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "One complication to infectious disease forecasting efforts is delay in reporting of cases, where real-time data often under-report the true disease burden. This pair of R scripts (1) provides example code demonstrating several strategies to account for the reporting delay and improve disease forecasts and (2) applies these methods using publicly-available data on dengue fever case reporting in Puerto Rico from 1990 to 2009.", + "laborHours": 0.0, + "languages": [], + "name": "Correcting for reporting delay: an example using dengue fever data", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbeesleyBIOSTAT/Reporting_Delay_Example_Code", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "As data volume increases in HPC centers, storing data in reasonable amounts of space and time while maintaining data integrity and recoverability becomes ever more difficult. ZFS is a filesystem that provides these features, among many others, that make it attractive for usage in HPC environments. It has the ability to compress data, compute checksums, and compute redundancy codes within the same runtime, rather than compute each separately, without knowledge of the underlying structure of the filesystem. However, measurements have shown that compression on CPUs can be incredibly inefficient and significantly reduce the performance of ZFS. The ZFS Interface for Accelerators (Z.I.A.) was developed to provide an interface to route data to accelerators while being processed by ZFS, so that the ZFS infrastructure and features are maintained, while allowing for ZFS administrators to provide faster implementations of compression, or other features, to their instance of ZFS.", + "laborHours": 0.0, + "languages": [], + "name": "ZFS Interface For Accelerators", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/zfs", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-24" + }, + "description": "The Data Processing Services Module (DPUSM) provides the ability to perform pluggable compression, erasure coding, checksuming and other important file system operations within the Linux kernel. The pluggable provider interface allows for the use of hardware acceleration of those services. In-kernel file systems are then able to use these functions to use these accelerators to perform operations that are normally run on the processor, resulting in improved file system performance. Third parties will register \"providers\" with the DPUSM to communicate with their respective accelerators. Providers will implement functions with DPUSM API signatures so that the DPUSM can translate the data inputted by users of the DPUSM into data that providers recognize.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Data Processing Unit Services Module", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "HPXML is a consensus data transfer standard for residential buildings. Over several years, multiple versions of the standard have been released. This tool accepts an HPXML file in an older version and translates it to a newer version.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HPXML Version Translator", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hpxml_version_translator", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "PsDNS is a Python package which makes it easy to solve partial differential equation using a pseudo-spectral method. The code uses Python classes and Numpy-like arrays to provide a simple interface with which users can construct equations, integrators, and diagnostics. It also includes implementation for common problems, in particular, the incompressible Navier-Stokes equation in a periodic domain, which is commonly used as a benchmark problem for turbulence research. PsDNS uses MPI to allow massively parallel computation for large problems.", + "laborHours": 0.0, + "languages": [], + "name": "PsDNS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PsDNS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "The Memento Protocol Validator software provides a suite of tools to validate compliance with the Memento protocol. The Memento protocol is an interoperability solution for accessing web archiving information with the DateTime dimension.", + "laborHours": 0.0, + "languages": [], + "name": "Memento Protocol Validator Software", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/memento-validator", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "To support and accelerate the development of simulation protocols in atomistic modelling, we introduce an integrated development environment (IDE) for computational materials science called pyiron (http://pyiron.org). The pyiron IDE combines a web based source code editor, a job management system for build automation, and a hierarchical data management solution. The core components of the pyiron IDE are pyiron objects based on an abstract class, which links application structures such as atomistic structures, projects, jobs, simulation protocols and computing resources with persistent storage and an interactive user environment. The simulation protocols within the pyiron IDE are constructed using the Python programming language. To highlight key concepts of this tool as well as to demonstrate its ability to simplify the implementation and testing of simulation protocols we discuss two applications. In these examples we show how pyiron supports the whole life cycle of a typical simulation, seamlessly combines ab initio with empirical potential calculations, and how complex feedback loops can be implemented. While originally developed with focus on ab initio thermodynamics simulations, the concepts and implementation of pyiron are general thus allowing to employ it for a wide range of simulation topics.", + "laborHours": 0.0, + "languages": [], + "name": "LANL Contributions to pyiron: An integrated development environment for computational materials science", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pyiron/pyiron_contrib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chaic@ornl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "This package (SUrface-wave Grader with ARtificial intelligence or SUGAR) automatically assigns a quality score to surface-wave seismograms (SAC format) using a trained artificial neural network model (included). Specifically, the python script 01_apply_ann.py calculates probability scores for a list of SAC files. You may consider seismograms with probability scores larger than 0.5 as acceptable data. Note no scores will be given to seismograms that do not pass an initial check (e.g., insufficient number of data points). See https://doi.org/10.1002/essoar.10507941.3 for more details.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ccp137/SUGAR", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ccp137/SUGAR", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "Link Parser Library is a Python library for parsing HTTP Link header format. Link Parser extracts information about relationships to other resources from Link Header and translates it into an easy to use Json structure.", + "laborHours": 0.0, + "languages": [], + "name": "Link Parser Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/link-parse", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "fanchercm@ornl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "pyRS is a python software package that was designed to meet the data reduction and analysis needs of the neutron residual stress mapping user community at Oak Ridge National Laboratory (ORNL). pyRS incorporates separate modules that provide a streamlined workflow for reducing raw neutron events into 1D intensity vs. scattering angle and subsequent analysis to extract the interatomic spacing and intensity for residual stress and texture analysis. Users can access the modules through either a graphical or command-line interface. pyRS saves data into a single HDF5 file, in which the metadata, reduced diffraction data, and peak analysis results are passed between different modules.", + "laborHours": 0.0, + "languages": [], + "name": "Python Residual Stress Analysis (pyRS)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/neutrons/PyRS.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "DistGANs is a Python package to perform distributed training of conditional generative adversarial neural networks for multi-class labeled image data.\nDistGANs partitionins the training data according to data labels, and enhances scalability by performing a parallel training where multiple generators are concurrently trained, each one of them focusing on a single data label.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DistGANS- Distributed Generative Adversarial Neural Networks", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/DistGANs", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0" + }, + { + "contact": { + "email": "craigca@ornl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-01-07" + }, + "description": "A tool to quickly perform recon in the init process of a given firmware.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "initAnalysis", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Codeman655/initAnalysis", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-01-07" + }, + "description": "XPlacer/Tracer is a dynamic analysis tool that finds bad memory access patterns in heterogeneous codes. XPlacer/Tracer consists of two components. (1) A configurable ROSE plugin for source code instrumentation of heterogeneous code written in the C/C++ and CUDA programming languages. (2) A sample configuration that instruments memory accesses to dynamic memory in CPU and GPU codes, and a runtime library that tracks these memory accesses at runtime. The collected information is reported in form of a textual summary or as memory map that can be converted to images.", + "laborHours": 0.0, + "languages": [], + "name": "XPlacer/Tracer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/XPL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.5" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-01-07" + }, + "description": "This routine is to be used with the open source package for seismic wave propagation\nSPECFEM3D_Globe version v7.0.2-111-gf469578\n(https://geodynamics.org/cig/software/specfem3d_globe/) to implement the LLNL S-, P-, Rayleigh, Love wave model (SPiRaL). It handles 3D radial isotropic crustal and mantle properties, as well as 410-660 topography.", + "laborHours": 0.0, + "languages": [], + "name": "LLNL S-, P-, Rayleigh, Love wave model implementation into SPECFEM3D_Globe", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/geodynamics/specfem3d_globe.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "accawigk@ornl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-03-22" + }, + "description": "MEASUR your energy savings with the free DOE MEASUR software The Department of Energy (DOE), with Oak Ridge National Laboratory (ORNL), released version 1.0 of their energy efficiency software tool MEASUR (Manufacturing Energy Assessment Software for Utility Reduction). MEASUR has been available for several years as a beta version, being tested by industry experts and real users, and will continue to be updated and improved in the coming years. It is an integrated suite of tools to aid manufacturers in improving the efficiency of energy systems and equipment within a plant, including motors, pumps, fans, process heating, steam, and compressed air. Additionally, there are modules for wastewater energy analysis and to help perform energy treasure hunts. Several calculators are also included, allowing users to independently perform smaller calculations and analyses (such as estimating pump head, performing a fan traverse analysis, estimating waste heat recovery potential, and cataloging compressed air leaks). The MEASUR modules are based on previous DOE software tools that have been used by industry since the early 2000s (such as MotorMaster, AirMaster+, PSAT, PHAST, and FSAT). The original tools only ran on Windows operating systems, and by Windows 10, most of them were inoperable. DOE started their energy efficiency software tool revitalization effort in 2016, first with PSAT (for pumps), then began to integrate the other tools and expand their functionality and utility. The new MEASUR suite provides an extensively more user-friendly, modern, and versatile set of tools. All the assessment modules and most of the calculators have several visual components and graphs and detailed help text for every user input. To help reach international users, the tool utilizes Google translate and users can easily change unit systems, even converting existing user inputs if desired. The assessment files can be organized within the internal file system and easily shared to other users, regardless of their operating system. The entire suite is free, open-source, and can be downloaded on Windows, Mac, or Linux operating systems.", + "laborHours": 0.0, + "languages": [ + "TypeScript", + "CSS", + "HTML", + "Node.js", + "Angular8", + "Electron" + ], + "name": "MEASUR - Manufacturing Energy Assessment Software for Utility Reduction", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-AMO/AMO-Tools-Desktop/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-AMO/AMO-Tools-Desktop", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-01-07" + }, + "description": "Zero-RK is a software package that simulates chemically reacting systems using sparse, preconditioned, adaptive matrix methods to achieve orders-of-magnitude reduction in simulation time while maintaining accurate results", + "laborHours": 13497.6, + "languages": [], + "name": "Zero-Order Reaction Kinetics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Zero-RK", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "borreguerojm@ornl.gov" + }, + "date": { + "created": "2022-01-09", + "metadataLastUpdated": "2022-01-11" + }, + "description": "drtsans is highly modular, allowing users to customize collected data as well as test hypothetical or simulated neutron events data. Instrument scientists can use the advance features of drtsans to calibrate their instruments and reduced large quantities of datasets in a streamlined mode. Users can correct the collected data with dark current subtraction and normalization by neutron flux, detector sensitivity, solid angle subtended by the detectors, and scaling to absolute units. Conversion from time-of-flight and/or wavelength to 1D or 2D momentum transfer renders the final scattering quantities amenable to analysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "drtsans", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/sns-hfir-scse/sans/sans-backend", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.2.0" + }, + { + "contact": { + "email": "bassbc@ornl.gov" + }, + "date": { + "created": "2022-01-10", + "metadataLastUpdated": "2022-01-10" + }, + "description": "Automatic Building Energy Modeling (AutoBEM, https://bit.ly/AutoBEM) has been used to create an OpenStudio and EnergyPlus building energy model of 122.9 million U.S. buildings (https://bit.ly/ModelAmerica). Simulating and analyzing a model of every building for large areas (e.g. cities) is often not feasible. This dynamic archetyping capability uses a representative building and calculates a floor-space multiplier that allows millions of buildings to be represented by less than 100 buildings. This script (WRF_Archetypes_Parallel.py) calculates these building archetypes for each of the grid cells from a Weather Research and Forecasting (WRF) model in a parallel fashion. The script works by looping through each of the grid cells in the shapefile in parallel, spatially joining the building metadata table to each grid cell, aggregating relevant archetypes and calculating necessary statistics related to area and number of buildings in each cell. The output is a table (.csv) in which each row is an archetype building with properties about that building as well as statistics that relate that building to the total cell (such as an area multiplier). The following inputs are required: WRF zone shapefile (.shp) (wrf-grids-origin_Vegas_Select_100.geojson) The projection of the shapefile (\"EPSG:XXXX\") Input table containing building metadata for area corresponding to shapefile (.csv) (https://zenodo.org/record/4552901#.YZQEotDMJPY - ClarkCounty2.csv) The number of cores that will be parallelized (integer) The output file name for the archetype table (.csv) Sample command line inputs: python3 ~/WRF_Archetypes_Parallel.py -i ~/wrf-grids-origin_Vegas_Select_100.geojson -c ~/ClarkCounty2.csv -o ~/OutputArchetypes.csv -j 72 -e EPSG:4326 Using Geopandas Version 0.9.0", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AutoBEM-DynamicArchetypes", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-BTRIC/AutoBEM-DynamicArchetypes", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "39s@ornl.gov" + }, + "date": { + "created": "2022-01-10", + "metadataLastUpdated": "2022-01-10" + }, + "description": "Software attempts to detect, estimate the composition, and segment phases from Energy Dispersive Spectroscopy datasets. ", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Autodidactic VB-GMM for Multispectral Microscopy Data", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esrah-ap-niht/Microscopy-VB-GMM", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "gureckywl@ornl.gov" + }, + "date": { + "created": "2022-01-10", + "metadataLastUpdated": "2024-01-24" + }, + "description": "The computer code uses a parallel simulated annealing framework with embedded machine learning components to solve multi-constrained optimization problems. The software automatically balances the execution of low and high fidelity physics models within the optimization procedure. The low fidelity model is used to rapidly explore the design space while the high fidelity physics model is executed sparingly to account for complex design constraints that are not resolved by the quickly executing low fidelity model.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ML-PSA", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/ml-psa/ml-psa", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2022-01-11", + "metadataLastUpdated": "2022-01-11" + }, + "description": "This package provides a secure transport layer connecting mini-applications run as components of a server infrastructure. The guiding principle is that mini-apps should be \"actors\" -- able to expose a set of API calls to the network and to have a shared trust model for knowing who is calling which API function and who takes\nresponsibility for the result.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Actor API", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/99R/actor_api", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0.0" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-01-12", + "metadataLastUpdated": "2023-03-08" + }, + "description": "There is a rising need for the measurement and understanding of hydrogen transport properties in materials for the energy and transportation industries. The Hydrogen Permeation Analysis Tool (HyPAT) provides a user friendly interface for batch analysis of dynamic hydrogen permeation data to calculate the transport properties permeability, solubility, and diffusivity. A built in literature database provides an easy comparison to known values. A common method for measuring these hydrogen transport properties is dynamic pressure rise permeation experiments, for example, those done in the Static Gas Absorption and Permeation (SGAP) experiment at INL. Most laboratories develop individual, in-house codes for data analysis. HyPAT provides a platform that can be adopted by other user groups for such experimental analysis and significantly reduce personnel time spent performing data analysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Hydrogen Permeation Analysis Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HyPAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "moriano@ornl.gov" + }, + "date": { + "created": "2022-01-12", + "metadataLastUpdated": "2022-01-12" + }, + "description": "Modern vehicles are complex cyber-physical systems made of hundreds of electronic control units (ECUs) that communicate over controller area networks (CANs). This inherited complexity has expanded the CAN attack surface which is vulnerable to message injection attacks. These injections change the overall timing characteristics of messages on the bus, and thus, to detect these malicious messages, time-based intrusion detection systems (IDSs) have been proposed. However, time-based IDSs are usually trained and tested on low-fidelity datasets with unrealistic, labeled attacks. This makes difficult the task of evaluating, comparing, and validating IDSs. Here we detail and benchmark four time-based IDSs against the newly published ROAD dataset, the first open CAN IDS dataset with real (non-simulated) stealthy attacks with physically verified effects. We found that methods that perform hypothesis testing by explicitly estimating message timing distributions have lower performance than methods that seek anomalies in a distribution related statistic. In particular, these “distribution-agnostic” based methods outperform “distribution-based” methods by at least 55% in area under the precision-recall curve (AUC-PR). Our results expand the body of knowledge of CAN time-based IDSs by providing details of these methods and reporting their results when tested on datasets with real advanced attacks. Finally, we develop an after-market plug-in detector using lightweight hardware, which can be used to deploy the best performing IDS method on nearly any vehicle.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Time-Based CAN IDS Paper Results Code", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmoriano/can-time-based-ids-benchmark", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-01-12", + "metadataLastUpdated": "2022-01-12" + }, + "description": "Data processing routines and moment tensor inversion of PNE data", + "laborHours": 0.0, + "languages": [], + "name": "PNE moment tensor inversions", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/PNE_MTINV", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dewittsj@ornl.gov" + }, + "date": { + "created": "2022-01-13", + "metadataLastUpdated": "2022-01-14" + }, + "description": "Many materials, metal alloys in particular, have features on the on micrometer or nanometer scale that have a large impact on the properties of the material. These features are known as the microstructure of the material. Understanding why and how the microstructure forms in a material is of fundamental scientific interest as well as of significant technological interest. The capability to predict microstructure evolution in a material allows the intentional design of microstructures and hence the intentional design of material properties. The phase-field method is one of the leading methods for predicting microstructure evolution. One of the most significant problems for phase-field models is their computational expense. Even limited phase-field simulations can easily require thousands of CPU core-hours to complete, which significantly limits their use. This code provides both a general framework for creating scalable, GPU-accelerated phase-field model applications as well as several applications themselves. The code is capable of using hundreds of GPUs efficiently, which greatly reduces the time required to perform simulations. The code is written with an emphasis on performance portability, that is the ability for the code to run efficiently on a number of different computing architectures without modification of the source code. The performance portability of this code is primarily enabled through the use of two libraries, Kokkos (performance portable data structures and execution patterns) and heFFTe (performance portable distributed 3D fast Fourier transforms). The code consists of a core library, applications, and tests. The core library includes shared functionality between applications. This includes interfaces with fast Fourier transform (FFT) libraries such as heFFTe, data structures based on Kokkos, file input and output capabilities, and a solver for infinitesimal strain mechanical equilibrium problems. Five applications are included in the code. The flagship application is the MEUMAPPS-SS application, which implements the Kim-Kim-Suzuki phase-field model for precipitation for an arbitrary number of phases and components in a metal alloy. Five simpler applications are also included that solve the Eshelby inclusion problem, Allen-Cahn equation, the coupled Allen-Cahn and diffusion equations, and the Cahn-Hilliard equation. The code includes two applications to solve the Cahn-Hilliard equation, one with constant-step-size first-order time integration and the second with adaptive high-order time integration.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "MEUMAPPS (C++ Version)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/meumapps/meumapps/-/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/meumapps/meumapps", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-01-13", + "metadataLastUpdated": "2023-03-08" + }, + "description": "ISOPOD (InverSe OPtimizatiOn and Design) will be a MOOSE (Multiphysics Object Oriented Simulation Environment)-based framework which will iteratively estimate the parameters by minimizing the difference between simulated and experimental observables. While inverse optimization has long been used for parameter estimation, the unique feature of ISOPOD is rapid solution of new inverse problems, leading to accelerated Research, Development and Demonstration (RD&D) for complex parameter estimation problems. This will be achieved by extending the software structure of MOOSE to inverse optimization, as well as building on the unique automatic differentiation feature of MOOSE.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Isopod (inverse Optimization And Design): Moose-based Application For Performing Inverse Optimization On Multiphysics Modeling And Simulation", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/isopod", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-01-13", + "metadataLastUpdated": "2022-01-13" + }, + "description": "Lighter version of the Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE)", + "laborHours": 0.0, + "languages": [], + "name": "psuade-lite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade-lite", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.9.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-01-14", + "metadataLastUpdated": "2022-01-14" + }, + "description": "To date, quantitative prediction on CPUs has been limited to laborious `white-box' methods; and learning has been limited to special cases such as best-case (throughput) performance. We present Qualm, a method for learning quantitative performance of optimized latency", + "laborHours": 0.0, + "languages": [], + "name": "Qualm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab/qualm/qualm", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-14", + "metadataLastUpdated": "2022-01-14" + }, + "description": "A scalable software framework for reinforcement learning environments and agents/policies used for the Design and Control applications", + "laborHours": 0.0, + "languages": [], + "name": "EXARL-Easily eXtendable Architecture for Reinforcement Learning", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exalearn/exarl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "tkonstant@bnl.gov" + }, + "date": { + "created": "2022-01-18", + "metadataLastUpdated": "2022-01-19" + }, + "description": "Code used for generating results in the publication: \"Machine learning enabling high-throughput and remote operations at large-scale user facilities\"", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Machine learning enabling high-throughput and remote operations at large-scale user facilities", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bnl/pub-ML_examples", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-01-19", + "metadataLastUpdated": "2022-01-19" + }, + "description": "The Gravitation and Mesh Adaptation (GaMA) toolbox consists of a set of Matlab classes for modeling the environment around asteroids and comets. A variety of gravitational models and supporting algorithms from are consolidated alongside a custom meshing utility tailored for the application. This allows the user to work within a single streamlined environment to import and manipulate surface definitions, probe the dynamical environment, integrate trajectories, and post-process results. For other applications, modified surface meshes can be exported. Gravity Models: 1) Werner's analytic polyhedron model 2) Mascon model 3) Gottlieb's spherical harmonic model 4) Approximate polyhedron models 5) Curvilinear surface models 6) Custom composite models Meshing Features: 1) Array-based half-edge data structure 2) Supports curvilinear surface definitions up to degree 4 3) Ray-tracing 4) Coarsening 5) Feature-based refinement 6) Projection 7) Smoothing 8) Mesh quality validity tests 9) Mesh repair Additional Features: 1) Solar radiation pressure model 2) Distant 3rd body model 3) Collision detection 4) Trajectory integration and post-processing 5) Visualization of surface fields", + "laborHours": 0.0, + "languages": [], + "name": "Gravitation and Mesh Adaption", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmpearl/GaMA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "diazab@nv.doe.gov" + }, + "date": { + "created": "2022-01-20", + "metadataLastUpdated": "2022-01-20" + }, + "description": "QuickView PRO (QVPRO) is similar to QuickView but designed to focus on analysis. QuickView was designed for visualization only, adding analysis capabilities later. This made QuickView complicated when using it as an analysis tool. QVPRO uses the same analysis algorithms in a more streamlined workflow and has a user friendly GUI. QVPRO provides the unique capability of analyzing Photonic Doppler Velocimetry (PDV) data records from different PDV systems and still allows for processing hundreds of PDV data records in a practical manner.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "QVPRO", + "organization": "Nevada National Security Site/Mission Support and Test Services LLC (MSTS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://gitlab.osti.gov/doecode/dc-31683", + "status": "Development", + "tags": [ + "DOE CODE", + "Nevada National Security Site/Mission Support and Test Services LLC (MSTS)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-01-21", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The Deep Lynx UNC is a small utility written in Python that uses only basic Python libraries and the Deep Lynx Python Software Development Kit (SDK). It queries Deep Lynx for tasks that indicate some data to be run in the UNC's environment. Once a task is acquired, the UNC retrieves the associated data and provides it to some other application for processing, waits for output, and sends the output from the other application to Deep Lynx. As data flows only from the UNC to Deep Lynx, this software solves the problem of connecting Deep Lynx with applications and resources that exist in a network where the network can reach Deep Lynx, but Deep Lynx cannot reach that network (unidirectional network).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deep Lynx Unidirectional Network Connector", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-UNC", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-01-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL contributions to project site managed by federal agency. Schema Grapher is an application that takes in CSV datasets and converts them to RDF for loading into a graph database. Schema Grapher is responsible for the extract and transform part of an ETL (i.e., extract, transform, load) pipeline.", + "laborHours": 0.0, + "languages": [], + "name": "Schema Grapher", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/schema-grapher", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-01-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL contribution to project managed by federal agency. SignalGen is a software application that generates synthetic RDF graphs that satisfy the constraints specified in a search template. The purpose of this tool is most to aid in the development of the graph search engine and ensure it is able to find known graph patterns.", + "laborHours": 0.0, + "languages": [], + "name": "SignalGen", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/signalgen", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "Remote Key/Value storage service for Mochi.", + "laborHours": 0.0, + "languages": [], + "name": "Yokan", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-yokan/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-yokan", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "Bedrock is Mochi's service bootstrapping mechanism.", + "laborHours": 0.0, + "languages": [], + "name": "Bedrock", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-bedrock/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-bedrock", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "mochi-quintain is a microservice (i.e., a Mochi provider) that responds to parameterized RPCs to generate synthetic concurrent server load.", + "laborHours": 0.0, + "languages": [], + "name": "mochi-quintain", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-quintain/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-quintain", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "Margo provides Argobots-aware bindings to the Mercury RPC library. Margo combines Mercury and Argobots to simplify development of distributed services. Mercury operations are presented as conventional blocking operations, and RPC handlers are presented as sequential threads. This configuration enables high degree of concurrency while hiding the complexity associated with asynchronous communication progress and callback management.", + "laborHours": 0.0, + "languages": [], + "name": "mochi-hpc/mochi-margo", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-margo/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-margo", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "Py-Bedrock providers Python utilities to configure and deploy Mochi-based services using Python.", + "laborHours": 0.0, + "languages": [], + "name": "Py-Bedrock", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/py-mochi-bedrock/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/py-mochi-bedrock", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "SSG is a group membership microservice based on the Mercury RPC system. 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However, traffic signal controllers used in North America widely use National Electrical Manufacturers Association (NEMA) phase definition. A NEMA phase is defined by a certain flow movement at an intersection. At one time, more than one NEMA phase could happen together as long as they do not conflict with each other. We can visualize the NEMA phases and timings in Ring-and-Barrier structured NEMA diagrams. For one controller, only one phase from a ring can be activated at a time. Phases from different rings could be activated together as long as they are not from the different sides of a barrier. When a controller is operated in fixed-time control mode, we can model the NEMA phase timing as a corresponding stage-based control timing without any issues. When introducing actuation into the signal control, a Ring-and-Barrier structured traffic signal controller can be more flexible than stage-based controller by allowing different possible phase combinations. We made two efforts in modeling Ring-and-Barrier structured controllers in SUMO. One is to translate a NEMA phases timing into SUMO-readable phases and timings as an additional file for SUMO. This translation worked well for fixed-time control. To model actuated control and coordinated actuated control, we augmented the SUMO source code by adding a Ring-and-Barrier structured controller module. This module could implement traffic signal timing from controllers using NEMA phases. We also augmented TraCI to be able to set new NEMA phase timings during simulations. We examined the Ring-and-Barrier structured traffic signal controller module by both visually observing the simulation animations and the simulation records. The developed control module can model the generalized Ring-and-Barrier structured traffic signal timing that is used in North America. 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The primary purpose of op is to simplify the process of integrating different optimization solvers (serial or parallel) with scalable parallel physics engines. By design it has several features that help make this a reality. The core abstraction interface was developed to encompass a large class of optimization problems in an optimizer-agnostic way. This enables us to describe the optimization problem once and then use a variety of supported \"op\" optimizers with ideally no code-changes. The abstraction interface is made up of lightweight wrappers that make it easy to integrate with existing simulation codes. This makes integration less intrusive and should minimize changes to existing physics codes. The \"op\" interface includes an assortment of utility methods that help specify parallel communication patterns as well as methods to convert from optimization-specific interfaces to the more general \"op\" interface. Lastly a dynamic library linking interface is provided to allow for use of proprietary optimization engines without explicit reference in the source code, along with standard shared library interfaces for opensource engines.", + "laborHours": 0.0, + "languages": [], + "name": "Optimization Plugin Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/op", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Software that orchestrate data processing and management for mass spectrometry workflows and data products. Stack presented contains a web application, data processing job scheduling, and data processing workers for data processing and management.", + "laborHours": 0.0, + "languages": [], + "name": "EMSL-Computing/CoreMS-Portal", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-Computing/CoreMS-Portal", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "zimmercj@ornl.gov" + }, + "date": { + "created": "2022-03-02", + "metadataLastUpdated": "2022-03-02" + }, + "description": "Spectral is a portable and transparent middleware library to enable use of the node-local burst buffers for accelerated application output on Summit and Frontier. It is used to enable large scientific applications to leverage the performance benefit of the in-node NVMe storage for periodic checkpoints without having to modify the application code. Spectral acheives this by intercepting write only file creates, redirecting the output, and then transfering the file to the original destination when the file is closed. Spectrals migration agent runs on the isolated core of each reserved node, so it does not occupy resources and based on some parameters the user could define which folder to be copied to the GPFS.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Spectral", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/cz7/spectral-io/-/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/cz7/spectral-io", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2022-03-03", + "metadataLastUpdated": "2022-03-03" + }, + "description": "Data Driven Anderson Acceleration for Physics Informed Neural Networks to solve high dimensional partial differential equations", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "DD-AADL", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/DD-AADL", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-03", + "metadataLastUpdated": "2022-03-03" + }, + "description": "Code for the paper Learning Interpretable Models Through Multi-Objective Neural Architecture Search by Zachariah Carmichael, Tim Moon, and Sam Ade Jacobs. Monumental advances in deep learning have led to unprecedented achievements across a multitude of domains. While the performance of deep neural networks is indubitable, the architectural design and interpretability of such models are nontrivial. Research has been introduced to automate the design of neural network architectures through neural architecture search (NAS). Recent progress has made these methods more pragmatic by exploiting distributed computation and novel optimization algorithms. However, there is little work in optimizing architectures for interpretability. To this end, we propose a multiobjective distributed NAS framework that optimizes for both task performance and introspection. We leverage the non-dominated sorting genetic algorithm (NSGA-II) and explainable AI (XAI) techniques to reward architectures that can be better comprehended by humans. The framework is evaluated on several image classification datasets. We demonstrate that jointly optimizing for introspection ability and task error leads to more disentangled architectures that perform within tolerable error.", + "laborHours": 0.0, + "languages": [], + "name": "Explainable Neural Architecture Search (XNAS)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/XNAS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0" + }, + { + "contact": { + "email": "obriense@ornl.gov" + }, + "date": { + "created": "2022-03-04", + "metadataLastUpdated": "2022-03-04" + }, + "description": "Uses spectral fitting of X-Ray fluorescence to obtain the density (g/L) of transuranics.", + "laborHours": 0.0, + "languages": [ + "Visual Basic" + ], + "name": "MEXRF", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/multTMU/MEXRF", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Minos Computing Library (MCL) is a task-based programming language and runtime for extremely heterogeneous systems. MCL facilitates writing program for heterogeneous devices and porting applications across different systems and devices. MCL supports asynchronous execution of computing tasks on all available heterogeneous devices, including GPUs, FGPAs, fixed-point accelerators, and AI accelerators. MCL provides a high-level programming interface and automatically and autonomously performs resource management, load balancing, and locality-aware scheduling.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/mcl-runtime", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mcl-runtime", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Amalgamate existing climate data to create monthly climate variable fields. The STITCHES python library provides a user-friendly interface to top-down climate emulation.", + "laborHours": 0.0, + "languages": [], + "name": "JGCRI/stitches", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jgcri/stitches", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Prepare and format the inputs for Hector. 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Toward these goals, Reaction Rover is designed to be modular, allowing the optimization algorithm, analyzer, and reactor components to be changed for any given process using easily integrated plugins. The Reaction Rover platform is a key development that enables the testing, use, and automation of machine learning (ML) and non-ML optimizers in a variety of laboratory situations.", + "laborHours": 0.0, + "languages": [ + "LabVIEW", + "Python" + ], + "name": "Reaction Rover", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/RxnRover/RxnRover/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/RxnRover/RxnRover", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-03-10", + "metadataLastUpdated": "2024-01-04" + }, + "description": "DISCO is a suite of software for configuring and parallelizing large numbers of distribution power flow simulations and analyzing the results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DISCO (Distribution Integration Solution Cost Options) [SWR-20-02]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/disco", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.2.1" + }, + { + "contact": { + "email": "landryne@ornl.gov" + }, + "date": { + "created": "2022-03-10", + "metadataLastUpdated": "2022-03-10" + }, + "description": "This code is used to determine the different types of pleiotropy among genes and multiple phenotypes", + "laborHours": 0.0, + "languages": [], + "name": "Multi-Phenotype Association (MPA) Decomposition", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/daweighill/MPA_decomp", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "The stochastic and hybrid representation electronic structure by density functional theory (SHRED) calculates microscopic material properties using time-dependent, nonadiabatic, and ground-state density functional theory (DFT) with a periodic basis. It can utilize deterministic, stochastic, and hybrid representations of the electronic orbitals. This provides a capability for highly parallelized computation of DFT for larger systems and/or higher temperatures. Thus, the code is particularly suited for calculation of material properties in the warm and hot dense matter regimes.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "SHRED: Stochastic and Hybrid Representation Electronic structure by Density functional theory", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This is a software package to predict electromagnetic counterpart production associated with gravitational-wave observations from binary neutron star and neutron star - black hole mergers. This reads in posterior distributions of signal parameters produced by parameter estimation pipelines analyzing gravitational-wave data and predicts whether an electromagnetic transient will be produced and observable in the sky. The code relies on open-source, easy-to-use software tools.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "PyKilonova", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "The goal of the isrhostinfo project is to enumerate security-significant Red Hat host application configuration data and send that data via syslog to an enterprise log server for analysis and monitoring. The project includes binaries for the RHEL7 and RHEL8 distros, python3 source code for RHEL6 support, bash helper scripts and the .yml configurations to enable another individual or organization to modify the source code and build organization-specific rpms through Gitlab and open-source CentOS Docker images.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "rhelhostinfo", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "The Generic Learning User Enablement Code (GLUE Code) is a modular framework designed to couple different scientific\napplications to support use cases including multiscale methods and various forms of machine learning. The workflow was\ninitially designed around supporting active learning as an alternative to coupled applications to support multiscale\nmethods but has been written in a sufficiently modular way that different machine learning methods can be utilized.\nApplication programming interfaces (API) are available for C, C++, Fortran, and Python with support for various storage\nformats including SQL databases and HDF5. The code also provides direct coupling with high performance computing job\nschedulers such as Slurm and Flux. The associated open source repository will include source code, build infrastructure,\ndocumentations, and examples demonstrating how to use the GLUE Code with oopen source ICF and Porous Media\napplications", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Generic Learning User Enablement Code (GLUE Code)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This software is a package of MATLAB functions which analyzes optical flow data to perform analysis on the motion contained in microscopy videos taken of beating heart cells. The resulting information is used to quantify key features of the motion such as frequency, magnitude, and correlation. This software can be applied to analyze different types of movement such as heart and muscle cell contractions frequency, beat strength, and overall beat synchronization.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "CardioFlow", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This project calculates the absolute detection efficiency, defined as the ratio of particles emitted by a source to particles detected using the Geant4 and MCNP radiation transport codes.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Absolute efficiency calculations in Geant4 and MCNP6 for a simple geometry", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "thavappiragm@ornl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "A molecular docking mini-app, GPU-accelerated particle-grid based protein ligand docking programs that can be used for virtual drug discovery compound screens based on a molecular recognition model, that analysis a three-dimensional model of an interaction between a protein and a small molecule (ligand). The miniMDock is developed using multiple programming models/APIs and can be used to evaluate performance portability of molecular docking applications over different heterogeneous systems.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "C", + "C++", + "Cuda", + "Hip" + ], + "name": "miniMDock", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + }, + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-PE/miniMDock", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "Unified Reaction Structures for Astrophysics (URSA) defines a format for nuclear inputs used in the simulation of astrophysical nucleosynthesis. Data of this type is currently stored, transferred, and implemented using a disparate patchwork of data formats and supporting codes. URSA intends to unify these disparate data sources/formats into a single data structure that accommodates the fullest possible range of different reaction types arising in astrophysical environments (e.g., transfer, pickup, or capture reactions; radioactive decay; or delayed particle emission, among many other possibilities). Furthermore, URSA provides a modern and efficient C++ library that existing and/or future astrophysics simulation codes may link against to directly implement nuclear data libraries constructed within the URSA format. In this approach, URSA will ensure that nuclear data inferred from measurements and generated by new facilities such as the Facility for Rare Isotope Beams (FRIB) is appropriately and consistently used in astrophysical applications.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Unified Reaction Structures for Astrophysics (URSA)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "Advanced high-fidelity modelling capabilities are available to evaluate hydraulic fracture growth, fluid flow in fracture networks, fluid-rock heat and mass transfer, geomechanical coupling, geochemical coupling, and electrical power production. While all these components must be considered to design geothermal wells and well fields, as of yet, no models couple all these processes efficiently enough for timely making during ongoing projects. Here we present a new modelling tool to inform rapid decision making for well design, drilling, and operation in fracture-dominated geothermal systems. This new tool, which we call the Geothermal Design Tool (GeoDT), evaluates 3D well placement, natural and hydraulic fracture stimulation by fluid injection, induced seismicity risk, long term flow behavior, heat transfer to flowing fluid over time, and transient electrical power production. Instead of using only first-principles and the common simplifying assumptions that are typical of high-fidelity models, this model is based more on experiment derived scaling relations that, by their nature, include the effect of multi-scale complex effects. This approach helps to avoid misleading simplifications while, at the same time, including small-scale complexities that are often too cumbersome or ill-defined to directly include in higher-fidelity models. The final product is a tool that can model 20 years of dynamic geothermal fluid production from a stimulated fracture dominated systems in seconds using a desktop computer.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Geothermal Design Tool (GeoDT)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "To solve an optimization problem using a commercial quantum annealer, one has to represent the problem of interest as an Ising or a quadratic unconstrained binary optimization (QUBO) problem and submit its coefficients to the annealer, which then returns a user-specified number of low-energy solutions. It would be useful to know what happens in the quantum processor during the anneal process so that one could design better algorithms or suggest improvements to the hardware. However, existing quantum annealers are not able to directly extract such information from the processor. Hence, in this work we develop methods to use advanced features of D-Wave 2000Q to indirectly infer information about the dynamics of the state evolution during the anneal process. Specifically, D-Wave 2000Q allows the user to customize the anneal schedule, that is, the schedule with which the anneal fraction is changed from the start to the end of the anneal. Using this feature, we design a set of modified anneal schedules whose outputs can be used to generate information about the states of the system at user-defined time points during a standard anneal. With this process, called slicing, we obtain approximate distributions of lowest-energy anneal solutions as the anneal time evolves. We use our technique to obtain a variety of insights into the annealer, such as the state evolution during annealing, when individual bits in an evolving solution flip during the anneal process and when they stabilize, and we introduce a technique to estimate the freeze-out point of both the system as well as of individual qubits. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Slicing D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "Quantum annealers offer an efficient way to compute high quality solutions of NP-hard problems when expressed in a QUBO (quadratic unconstrained binary optimization) or an Ising form. This is done by mapping a problem onto the physical qubits and couplers of the quantum chip, from which a solution is read after a process called quantum annealing. However, this process is subject to multiple sources of biases, including poor calibration, leakage between adjacent qubits, control biases, etc., which might negatively influence the quality of the annealing results. In this software, we aim at mitigating the effect of such biases for solving constrained optimization problems, by offering a two-step method, and apply it to Graph Partitioning. In the first step, we measure and reduce any biases that result from implementing the constraints of the problem. In the second, we add the objective function to the resulting bias-corrected implementation of the constraints, and send the problem to the quantum annealer. We apply this concept to Graph Partitioning, an important NP-hard problem, which asks to find a partition of the vertices of a graph that is balanced (the constraint) and minimizes the cut size (the objective). We develop methods for an iterative method to correct any such biases. We demonstrate that, after adding the objective, solving the resulting bias-corrected Ising problem on the quantum annealer results in a higher solution accuracy.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Graph Partitioning Bias Reduction for D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2023-01-17" + }, + "description": "The D-Wave quantum annealers make it possible to obtain high quality solutions of NP-hard problems by mapping a problem in a QUBO (quadratic unconstrained binary optimization) or Ising form to the physical qubit connectivity structure on the D-Wave chip. However, the latter is restricted in that only a fraction of all pairwise couplers between physical qubits exists. Modeling the connectivity structure of a given problem instance thus necessitates the computation of a minor embedding of the variables in the problem specification onto the logical qubits, which consist of several physical qubits \"chained\" together to act as a logical one. After annealing, it is however not guaranteed that all chained qubits get the same value (-1 or +1 for an Ising model, and 0 or 1 for a QUBO), and several approaches exist to assign a final value to each logical qubit (a process called \"unembedding\"). In this software, we develop tailored unembedding techniques for four important NP-hard problems: the Maximum Clique, Maximum Cut, Minimum Vertex Cover, and Graph Partitioning problems. Our techniques are simple and yet make use of structural properties of the problem being solved. Using Erd\\H{o}s-R\\'enyi random graphs as inputs, we compare our unembedding techniques to three popular ones (majority vote, random weighting, and minimize energy). We demonstrate that our proposed algorithms outperform the currently available ones in that they yield solutions of better quality, while being computationally equally efficient.", + "laborHours": 0.0, + "languages": [], + "name": "Advanced Unembedding Algorithms for D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/custom-unembedding-algorithms-QA", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "We developed software which finds HGain schedules that can be used to encode initial solutions into a quantum annealer in a similar manner to the reveres annealing feature on the D-Wave 2000Q. With the newer generations of the D-Wave annealer, more advanced features are available which allow the user to have greater control of the anneal process. We study how such features can help in improving the quality of the solutions returned by the annealer. Specifically, we focus on two of these features: reverse annealing and h-gain. Reverse annealing (RA) was designed to allow refining a known solution by backward annealing from a classical state representing the solution to a mid-anneal point where a transverse field is present, followed by an ordinary forward anneal, which is hoped to improve on the previous solution.The h-gain (HG) feature stands for time-dependent gain in Hamiltonian linear ($h$) biases and was originally developed to help study freezeout times and phase transitions in spin glasses. Here we apply HG to bias the quantum state in the beginning of the annealing process towards the known solution as in the RA case, but using a different apparatus. We also investigate a hybrid reverse annealing/h-gain schedule, which has a backward phase resembling an RA step and whose forward phase uses the HG idea. To optimize the parameters of the schedules, we employ a Bayesian optimization framework. We test all techniques on a variety of input problems including the weighted Maximum Cut problem and the weighted Maximum Clique problem. Our results show that each technique may dominate the others depending on the input instance, and that the HG technique is a viable alternative to RA for some problems.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Encoding Initial Solutions using the HGain feature on D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This code package computes the multi-species BGK kinetic model of Haack, Hauck, and Murillo [J. Stat. Phys., 168, 2017]. It uses a block adaptive mesh refinement (AMR) framework derived from the open-source, Parthenon performance portable AMR framework to provide refinement in the (up to) six dimensional phase space. It includes an atomic ionization model, accurate collision physics across coupling regimes, self-consistent electric fields, and allows for degeneracy in the electronic screening. This kinetic model greatly extends the temperature regime and the spatiotemporal scales for modeling moderately coupled plasmas.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Zapp", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "We developed software which optimizes the selection of spin reversal's on the D-Wave 2000Q for individual problems. Commercial quantum annealers from D-Wave Systems make it possible to obtain approximate solutions of high quality for certain NP-hard problems in nearly constant time. Before solving a problem on D-Wave, several pre-processing methods can be applied, one of them being the so-called spin reversal or gauge transform. The spin reversal transform flips the sign of selected variables and coefficients of the Ising or QUBO (quadratic unconstrained binary optimization) representation of the problem that D-Wave minimizes. The spin reversal transform leaves the ground state of the Ising model invariant, but can average out the biases induced through analog and systematic errors on the device, thus improving the quality of the solution that D-Wave returns. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Genetic Algorithms for Optimizing Spin Reversals on D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "The work done on the open source MPI.jl package was done in order to allow it to work with a streaming, in-situ Gaussian process. The addition was to add the capability for the Julia package to use the MPI non-blocking Barrier, Ibarrier. 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The code is written in Fortran and includes Python wrappers.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Data Assimilation Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This software consists of LANL contributions to the pFUnit unit testing framework, developed and copyrighted by NASA/Goddard Space Flight Center.\n\npFUnit is a unit testing framework enabling JUnit-like testing of serial and MPI-parallel software written in Fortran. 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The models and features currently included in the VE library include a models/simulations for pretreatment, enzymatic hydrolysis, and aerobic bioreaction.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Fortran", + "Python", + "Tex", + "shell" + ], + "name": "Virtual Engineering (VE) (vebio)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/VirtualEngineering", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-03-21", + "metadataLastUpdated": "2023-09-11" + }, + "description": "The Photovoltaic Dynamic Material Flow Assessment (PV DMFA) model (also referred to here as “The model”) is a computational framework written in Python based on utility-scale PV electricity generation to quantify time-series stocks and flows of PV materials primarily in crystalline silicon PV technologies. The model evaluates cradle-to-cradle life cycle of utility-scale solar PV systems in the United States in the period 2000-2100. PV DMFA serves as a sustainability analysis tool to assess the impacts of different material circularity practices (i.e., reduce, reuse/refurbish, remanufacture, and recycle), PV module design shifts and sensitivity of material processing and technology related parameters to material installations, waste creation and raw material depletion in PV material supply chains. This tool enables advanced planning for future material needs and informs sustainable pathways for PV material management in the circular economy. This tool could be helpful to a wide range of stakeholders; Particularly, researchers and manufacturers looking for technoeconomic and/or environmental life cycle analysis (LCA) feedback for renewable energy (RE) systems.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "PV DMFA [SWR-21-105]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PV-DMFA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-21", + "metadataLastUpdated": "2022-04-08" + }, + "description": "This code is for the topology optimization of porous electrodes. It was used to produce the results in Roy, T., Salazar de Troya, M.A., Worsley, M.A. and Beck, V.A., 2021. Topology optimization for the design of porous electrodes. arXiv preprint arXiv:2111.12059.", + "laborHours": 0.0, + "languages": [], + "name": "Topology Optimization for Porous Electrodes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TOPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "kyager@bnl.gov" + }, + "date": { + "created": "2022-03-22", + "metadataLastUpdated": "2022-03-22" + }, + "description": "Collection of tools (Python scripts) for scientific experiments: SciAnalysis (analyze image-like data), SciControl (instrument control), and SciVis (visualize data).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "kevinyager/SciTools", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kevinyager/SciTools", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "We have developed a deep learning based method to decode the protein-ligand interactions and predict their probability of binding. We use 3-Dimensional structure of proteins and ligand molecules with the ligand docked to the receptor and use the information at the interaction region to assess the binding of the protein-ligand complex.", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-CompBio/pf-gnn_pli", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/pf-gnn_pli", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The terrestrial dycores will solve tightly coupled conservation of water and energy equations. While the land dycore will simulate processes for a three-dimensional subsurface coupled to a one-dimensional plant’s vascular system, the river dycore will simulate two-dimensional processes in the river.", + "laborHours": 0.0, + "languages": [], + "name": "TDycores-Project/TDycore", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/TDycores-Project/Tdycore", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "TEMWizard is used to visualize results from Atomap, an open-source software tool for determining the position and other features of atomic columns in transmission electron microscopy images.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Temwizard", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Temwizard", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2023-07-07" + }, + "description": "This is a repository with the tools developed for predicting energy produced at Open-Source Reservoir (OSR). It includes both simulation data for OSR, as well as Jupyter notebooks for training and evaluating prediction models. OSR was constructed based on the data from Brady Hot Springs reservoir (Nevada, USA) but has a number of sufficiently modified characteristics and does not disclose any sensitive data.", + "laborHours": 0.0, + "languages": [ + "JUPYTER NOTEBOOK" + ], + "name": "geothermal_osr (Energy Predictor for Geothermal Open Source Reservoir) [SWR-22-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/geothermal_osr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2023-07-11" + }, + "description": "PVwindow simulates photovoltaic window properties by allowing the user build stacks of thin film materials that compose the window layers. The only needed inputs are the complex refractive indices and thicknesses of the materials. The software will simulate the optical transmission, front reflection, and back reflection of the stack using the transfer matrix method. Properties specific to PV window optics such as visible transmittance and color are also calculated. The optics code extracts the number of absorbed photons in the PV absorber layer and solves the single diode equation to yield theoretical photovoltaic metrics such as power conversion efficiency, fill factor, open circuit voltage, and short circuit current of the PV window when illuminated at an arbitrary angle or from either side of the stack. The software tool ultimately allows researchers to design photovoltaic windows and simulate their properties. The software also exports files that can be read into LBL Window software or into the EnergyPlus and Open Studio building energy modeling software to determine larger scale energy impacts of PV window integration.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PVwindow (Photovoltaic Window Simulator) [SWR-22-01]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PVwindow", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2022-03-24" + }, + "description": "The Delaunay density diagnostic helps detect and assess geometric scales within unstructured numerical data sets. The algorithm was first introduced in the paper \"Data-driven geometric scale detection via Delaunay interpolation\" by Andrew Gillette and Eugene Kur, 2022. More details can be found in that paper, as well as the included README file.", + "laborHours": 0.0, + "languages": [], + "name": "Delaunay density diagnostic", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ddd", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2022-03-24" + }, + "description": "In the context of a larger effort for in situ data analytics, there is a need to calculate basic statistics metrics (e.g., count, mean, median) online as new data points become available. 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To use the Streaming Statistics library, the user chooses a statistic, constructs an object for it, and then \"adds\" values to it, which means the statistic is augmented.", + "laborHours": 0.0, + "languages": [], + "name": "Streaming Statistics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/STREAMSTAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Python package for organizing and calculating cross-sectoral interdependency flow values. The interflow package collects known resource flow values (e.g., water demand) between sectors provided by the user and calculates new sector flows for a secondary resource type (e.g., energy demand) based on provided resource intensity estimates, source sector fractions, and downstream sector discharge fractions.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/interflow", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/interflow", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The FEMP Cyber Security Arsenal is a family of cyber security tools for the federal facility owners and operators. Using these tools, facility owners can evaluate their overall cybersecurity posture. These tools are web-based front-end tools. This is an upgrade of the tools available from the earlier version in DOE CODE ID: #41457", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "FEMP Cyber Security Arsenal", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "2" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The software implements the methodology of cybersecurity training architecture and is leveraged to build a turn-key based simulated cyberattack game in which the player assumes the facility manager's role and must defend the OT network from adaptive cyberattacks by directly configuring the physical network environment and implementing security policies.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Network Defense Workforce Development System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "pillairr@ornl.gov" + }, + "date": { + "created": "2022-03-28", + "metadataLastUpdated": "2022-03-28" + }, + "description": "The modeling tool developed in the current project provides lifetime assessment of three candidate materials 740H, 282 and 625 for sCO2/molten salts heat exchanger. The tool incorporated physics-based models that accounted for all relevant underlying degradation mechanisms (creep and corrosion). Reduced-order models enabled rapid simulations of realistic component lifetimes (~100kh) while still retaining the fidelity of the complex models.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "rishipillai/CSP-CorrCreep_ORNL", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rishipillai/CSP-CorrCreep_ORNL", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "qians@ornl.gov" + }, + "date": { + "created": "2022-03-28", + "metadataLastUpdated": "2022-03-29" + }, + "description": "It takes multiple data sets from small-angle neutron scattering experiment at different contrast conditions to synthetically use DENSS algorithm (https://www.nature.com/articles/nmeth.4581) to combine all the information from each data set. As the multiple data set contains more information than a single data, all information in the multiple data set are collectively contribute to the final single synthetic structure that represents a molecular particle structure.", + "laborHours": 0.0, + "languages": [], + "name": "DENSS-Multiple", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/q3n/denss-multiple", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-04-01" + }, + "description": "The ROI-finder software is being developed for use by several Microscopy Group beamlines at Argonne National Laboratory, including 2-ID microprobes and 9-ID-B Bionanoprobe which use multi-scale scanning fluorescence microscopy to acquire elemental maps (multi-modal image data). Microscopy experiments require scan of samples at a coarse resolution followed by ROI identification using feature detection based on domain expertise. Finer resolution scans are then conducted based on identified ROI. The decision-making process based on domain expertise will be difficult to perform for faster data rates and much larger sampling volumes anticipated after APS-U necessitating the need for the ROI-finder software. The ROI- finder detects regions of interest through a continuous learning process, starting with a unsupervised representation learning and improving its recommendations through supervised learning and an interactive tool for user annotation. The scope of ongoing development efforts includes the integration of image registration module to correlate optical and X-ray images, extraction of feature morphology as well as elemental signatures in the image space and incorporation of beamtime streaming data by the scanning probe via EPICS.", + "laborHours": 0.0, + "languages": [], + "name": "XRF-ROI Finder: Machine Learning to Guide Region-of-Interest Scanning for X-ray Fluorescence Microscopy", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/arshadzahangirchowdhury/ROI-Finder", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "The TargetID pipeline enables rapid identification and characterization of binding sites in SARS-CoV-2 proteins as well as the core chemical components with which these sites interact.", + "laborHours": 0.0, + "languages": [], + "name": "Drug Target and Chemotype Identification Pipeline", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TargetID", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2023-07-27" + }, + "description": "pyvisco is a Python library that supports the identification of Prony series parameters for linear viscoelastic materials described by a Generalized Maxwell model. The necessary material model parameters are identified by fitting a Prony series to the experimental measurement data. pyvisco allows for the identification of Prony series parameters from experimental data measured in either the frequency-domain (via Dynamic Mechanical Thermal Analysis) or time-domain (via relaxation measurements). The experimental data can be provided as raw measurement sets at different temperatures or as pre-processed master curves. An optional minimization routine is included to reduce the number of Prony elements. This routine is helpful in Finite Element simulations where reducing the computational complexity of the linear viscoelastic material models can shorten the simulation time.\n\nSee also, https://pypi.org/project/pyvisco/", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "pyvisco [SWR-22-30]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pyvisco", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2023-07-27" + }, + "description": "Model predictive control (MPC) is a system or process control technique for making decisions under uncertainty via rolling look-ahead optimizations at each control step where only the current step decisions are applied, and the rest are discarded. In this work, we developed an MPC for a critical load restoration (CLR) in power distribution systems to recover system service (electricity delivery) following an extreme event-triggered substation outage. The method considers the problem of controlling distributed energy resources (DERs) of the distribution system with the objective of achieving maximum load pick up while satisfying distribution network flow and voltage constraints. A linearized optimal power flow (OPF) model is employed to represent the physics of the network. The problem formulation is augmented with a ramping (up) reserve product for the DERs to ensure improved and upward monotonic load restoration as time evolves. Simulation analysis and performance tests are performed using a modified IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage battery. The software is developed using various software packages in Julia and Python. The MPC model is implemented using the JuMP optimization language in Julia while the data analytics including renewable generation and load demand forecasts, running the MPC simulation and visualizations is performed in Python.", + "laborHours": 0.0, + "languages": [ + "Julia", + "Python" + ], + "name": "MPC4CLR (Model-Predictive-Control-for-Critical-Load-Restoration-in-Power-Distribution-Systems) [SWR-22-24]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mpc4clr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "SAND2022-3576 O tenzing provides techniques for improving the performance of key applications and libraries. The program is specified as a directed acyclic graph of operations. It uses Monte-Carlo tree search to explore the design space of possible implementations and applies machine learning to the observed empirical performance to deliver design guidance to users. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++", + "C++", + "CUDA", + "Python 3" + ], + "name": "tenzing", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tenzing", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SAND2022-3548 O This code contains scripts that allow users to generate molecular electron densities, train a machine learning model to predict electron densities, and analyze the accuracy of machine learned electron densities. It accompanies a publication titled \"Cracking the Quantum Scaling Limit with Machine Learned Electron Densities.” Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1565.6, + "languages": [ + "Python", + "Jupyter notebook" + ], + "name": "equivariant_electron_density", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/equivariant_electron_density", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-09-19" + }, + "description": "Hybrid-RL-MPC4CLR was developed as a hybrid controller for active distribution grid critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. The RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while the MPC models grid operations incorporating the RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. The developers formulated the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The software is developed using various software packages in Python. The MPC's optimal power flow (OPF) model is implemented using the Pyomo package, the RL simulation environment is implemented using the MPC simulation with various scenarios of renewable energy and load demand profiles and power outage beginning times, based on the OpenAI Gym framework. The RL agent training is performed using the RLlib Ray package. The RL algorithm is trained offline using historical forecasts of renewable generation and load demand profiles. Simulation analysis and performance tests are conducted using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "python" + ], + "name": "Hybrid-RL-MPC4CLR (Hybird-Reinforcement-Learning-Model-Predictive-Control-for-Reserve-Policy-Assisted-Critical-Load-Restoration-in-Distribution-Grids)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hybrid-rl-mpc4clr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-09-19" + }, + "description": "RLC4CLR demonstrates using a reinforcement learning controller (RLC) to solve a critical load restoration (CLR) problem, which improves the grid resilience after a substation outage event. RLC4CLR consists of two parts. (1) RL environment: This environment encapsulates the CLR problem to be solved and provides interfacing functions to follow the standard OpenAI Gym format. A power system simulator, i.e., OpenDSS, is included to provide the power flow solution. Controller inputs and outputs (RL state and action) as well as the reward are defined in this environment as well. In summary, the RL environment is the problem formulation from which the RL agent can learn. (2) RL training script: The training script enables the RL agent to learn its control policy by interacting with the RL environment. For RL training, an open-sourced RL library, i.e., RLlib, is leveraged which is based on a distributed computing framework (Ray). The training script is designed to be able to be run on both local machine or the NREL HPC system. Other components of RLC4CLR include input data, e.g., grid model (standard IEEE test feeders), and other files used for results analysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "RLC4CLR (Reinforcement Learning Controller for Critical Load Restoration Problems)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rlc4clr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "SAND2021-15055 O Limbo provides a programmatic interface for accessing computer vision training data. It is organized in the Limbo format. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://limbo-ml.readthedocs.io/en/latest", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "Limbo", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://limbo-ml.readthedocs.io/en/latest", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "SAND2021-15054 O PyNucleus is a finite element code for nonlocal equations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python", + "C++" + ], + "name": "PyNucleus", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PyNucleus", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "SAND2021-15053 O ManiPIO is a Python-based tool used to test Programmable Logic Controllers (PLCs), Industrial Control Systems (ICS), and ICS networks. It reads an input script to construct complex Events on ICS networks and uses the ModBus communication standard to communicate. Users can use ManiPIO to construct complex timelines of ICS communication events to simulate any number of network-based scenarios. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ManiPIO - Manipulate Process I/O", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SMARTT", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "gillette7@llnl.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-30" + }, + "description": "This code implements algorithms described in: \"Data-driven geometric scale detection via Delaunay interpolation\" Andrew Gillette and Eugene Kur, 2022 https://arxiv.org/abs/2203.05685", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "LLNL/ddd", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ddd", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "albertop@iastate.edu" + }, + "date": { + "created": "2022-03-30", + "metadataLastUpdated": "2022-03-31" + }, + "description": "Implementation of homogeneous models (PFR and PaSR for applications to biomass pyrolysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Homogeneous models for biomass pyrolysis", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Biomass-Autothermal-Pyrolysis/HomogeneousModels", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "colettima@ornl.gov" + }, + "date": { + "created": "2022-03-31", + "metadataLastUpdated": "2022-03-31" + }, + "description": "Gremlin is an evolutionary algorithm that discovers weaknesses in machine learning models.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Gremlin", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/markcoletti/gremlin", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v0.3" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-03-31", + "metadataLastUpdated": "2022-03-31" + }, + "description": "densegranFoam is a dense granular material flow solver developed using the OpenFoam Computational Fluid Dynamics (CFD) tool. It is developed using Euler-Euler framework. The transport model is implemented using the shear rate dependant constitutive model. The primary focus of the solver is to simulate shear rate dependency on the dense granular flow bulk behavior.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Python" + ], + "name": "densegranFoam", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/densegranFoam", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "albertop@iastate.edu" + }, + "date": { + "created": "2022-03-31", + "metadataLastUpdated": "2022-03-31" + }, + "description": "Eulerian-Eulerian CFD models with bidisperse kinetic theory of the granular flow, and kinetics for biomass pyrolysis. The models were implemented in customized versions of OpenFOAM.", + "laborHours": 0.0, + "languages": [ + "C", + "C++" + ], + "name": "CFD codes for biomass pyrolysis", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Biomass-Autothermal-Pyrolysis/CFDCodes", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "albertop@iastate.edu" + }, + "date": { + "created": "2022-03-31", + "metadataLastUpdated": "2022-03-31" + }, + "description": "Reduced-order model that takes the biomass biochemical composition as input and returns the primary pyrolysis products in a dictionary. ", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Reduced-order model for biomass pyrolysis", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Biomass-Autothermal-Pyrolysis/ReducedOrderModel", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-04-01", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The purpose of Scramble is to provide a cross validation method to ensure machine learning model accuracy in cases where model classes have heterogeneous N values.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Scramble", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Scramble", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-04-05", + "metadataLastUpdated": "2022-07-26" + }, + "description": "JADE provides a simple, flexible interface to submit jobs to an HPC. JADE is an HPC workflow management system that enables researchers to run simulations efficiently. It provides a simple, flexible interface to define jobs, as well as dependencies between jobs, and then dispatch them to an HPC with maximized parallelization. It also provides detailed error reporting and resource utilization statistics to aid in debugging problems.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "JADE", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/jade", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "smith84@llnl.gov" + }, + "date": { + "created": "2022-04-05", + "metadataLastUpdated": "2022-04-05" + }, + "description": "ParFlow is an open-source, modular, parallel watershed flow model. It includes fully-integrated overland flow, the ability to simulate complex topography, geology and heterogeneity and coupled land-surface processes including the land-energy budget, biogeochemistry and snow (via CLM). It is multi-platform and runs with a common I/O structure from laptop to supercomputer. ParFlow is the result of a long, multi-institutional development history and is now a collaborative effort between CSM, LLNL, UniBonn and UCB. ParFlow has been coupled to the mesoscale, meteorological code ARPS and the NCAR code WRF.", + "laborHours": 138532.8, + "languages": [ + "C", + "C++", + "Python", + "Tcl" + ], + "name": "ParFlow", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/parflow/parflow", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.10.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-05", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SAND2021-14370 O Tesuract (tensor surrogate approximation and computation) provides Python tools to build machine learning regressors that include polynomial chaos expansions. The software also offers methods for creation regressors for tensor outputs such as spatially varying fields and using a reduced order modeling methodology. The library is built on and compatible with the scikit-learn API, which allows integration with one of the most ubiquitous machine learning Python libraries out there. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 24639.2, + "languages": [ + "Python" + ], + "name": "tesuract v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tesuract", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-08", + "metadataLastUpdated": "2022-04-08" + }, + "description": "Due to recent improvements in image resolution and acquisition speed, materials microscopy is experiencing an explosion of published imaging data. The standard publication format, while sufficient for traditional data ingestion scenarios where a select number of images can be critically examined and curated manually, is not conducive tolarge-scale data aggregation or analysis, hindering data sharing and reuse. Most images in publications are presented as components of a larger figure with their explicit context buried in the main body or caption text, so even if aggregated, collections of images with weak or no digitized contextual labels have limited value. To solve the problem of curating labeled microscopy data from literature, we introduce the EXSCLAIM! Python toolkit for the automatic EXtraction, Separation, and Caption-based natural Language Annotation of IMages from scientific literature. The software is implemented through a three part pipeline: the JournalScraper, which searches the web and downloads figures and captions based on a user provided query, the CaptionDistributor, which separates caption text based on the subfigure each portion of the caption refers to, and the FigueSeparator, which separates figures into component subfigures and extracts other visual information. Also included is a Django user interface for exploring the resulting dataset.", + "laborHours": 0.0, + "languages": [], + "name": "EXSCLAIM!", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MaterialEyes/exsclaim", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2022-04-11", + "metadataLastUpdated": "2022-04-11" + }, + "description": "METS-R ADDSEVS simulator is a high fidelity, parallel, agent-based evacuation simulator for multi-modal energy-optimal trip scheduling in real-time (METS-R) at transportation hubs. It consists of two modules. The first one is the traffic simulator module; the second one is the high-performance computing (HPC) module. More details can be found at https://umnilab.github.io/METS-R_doc/.", + "homepageURL": "https://umnilab.github.io/METS-R_doc", + "laborHours": 0.0, + "languages": [], + "name": "An agent-based deployment decision-support system for electric vehicle services", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://umnilab.github.io/METS-R_doc", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2022-04-11", + "metadataLastUpdated": "2022-04-11" + }, + "description": "R3IT is a free and open-source web application that allows utilities to automate the processing of solar interconnection requests. It handles request submission, request review workflows, payment collection, signature collection, email notifications for any status changes, and optionally an automated engineering screening and approval process.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "R3IT: Rapid, Rural, Resilient Interconnection Toolkit", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dpinney/r3it", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-04-12", + "metadataLastUpdated": "2023-08-17" + }, + "description": "A surprisingly non-trivial technical challenge is to associate points in space (e.g., GPS data) with specific segments of a road network or map. The software package ( allows users to match GPS point data to a road network (commonly known as \"map matching\"). The software is designed such that a user could match a set of GPS points to a variety of different road network representations using a variety of map matching algorithms. There are currently several \"built-in\" road networks and map matching algorithms but the software has been designed to enable new ones to be added with minimal overhead.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Mappymatch FKA: YAMM (Yet Another Map-Matcher) [SWR 22-38] ", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/yamm", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-04-12", + "metadataLastUpdated": "2022-04-12" + }, + "description": "BinFPE is a tool that detects floating-point exceptions (NaN, infinity, and subnormal quantities) in NVIDIA GPU applications using binary instrumentation. It requires no re-compilation of the application and can analyze libraries. The tool extends NVBit (https://github.com/NVlabs/NVBit), which is provided by NVIDIA Labs to analyze binaries. When the tool detects a floating-point exception it reports to the user the location of the exception (file and line number).", + "laborHours": 0.0, + "languages": [], + "name": "BinFPE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/BinFPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-04-13", + "metadataLastUpdated": "2022-04-13" + }, + "description": "This code performs an optimization over the structure of a porous electrode formed from a lattice of unit cells. This is a steepest descent version of the code used in: V. A. Beck, J. J. Wong, C. F. Jekel, D. A. Tortorelli, S. E. Baker, E. B. Duoss and M. A. Worsley, Computational design of microarchitected porous electrodes for redox flow batteries, J. Power Sources, 2021, 512, 230453.", + "laborHours": 0.0, + "languages": [], + "name": "Lattice Optimization for Porous Electrode", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LOPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software contains a routine for active sampling of a DFT-generated dataset for training a neural network potential (SchNet). Major updates to the base SchNet code are also included to accommodate large systems (100s of atoms). We also provide code to apply the neural network potential in dynamic shear simulations.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Active-Sampling-for-Atomistic-Potentials", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Active-Sampling-for-Atomistic-Potentials", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "Provides an easy to use high-level interface to Web100. 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Towards this goal we are developing a Pervasive Collaborative Computing Environment (PCCE) within which participants can rendezvous and interact with each other. The PCCE aims to support continuous or ad hoc collaboration, target daily tasks and base connectivity, be easy to use and install across multiple platforms, leverage off of existing components when possible, use standards-based components, and leverage off of Grid services (e.g., security and directory services). A key concept for this work is \"incremental trust\", which allows the system's \"trust\" of a given user to change dynamically. PCCE Jabber client software: This leverages Jabber. an open Instant Messaging (IM) protocol and the related Internet Engineering Task Force (IETF) standards \"XMPP\" and \"XMPP-IM\" to allow collaborating parties to chat either one-on-one or in \"chat rooms\". Standard Jabber clients will work within this framework, but the software will also include extensions to a (multi-platform) GUI client (Gaim) for X.509-based security, search, and incremental trust. This software also includes Web interfaces for managing user registration to a Jabber server. PCCE Jabber server software: Extensions to the code, database, and configuration files for the dominant open-source Jabber server, \"jabberd\". Extensions for search, X.509 security, and incremental trust. Note that the jabberd software is not included as part of this software.", + "homepageURL": "https://dst.lbl.gov/ACSSoftware/pccejt/Home", + "laborHours": 0.0, + "languages": [], + "name": "Pervasive Collaboratorive Computing Environment Jabber Toolkit", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://dst.lbl.gov/ACSSoftware/pccejt/Home/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dst.lbl.gov/ACSSoftware/pccejt/Home", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "Non-encrypted, TCP-streams, host-to-host file copy utility intended to enable greater transfer rates, while having the basic user-interface concept of BSD rcp. The underlying design provides the opportunity to maximize performance by allocating supplemental IP sockets as dedicated and optimizable data-channels, in a mode similar to FTP. Additionally, a parallel I/O scheme, based on the HPSS paradigm, is also employed, offering potentials for multiple-sockets over a single network connection (which, in many circumstances, especially those in involving heterogeneous host platforms, or large latency situations, can capture more bandwidth), and also the distribution of the sockets across a manifold of parallel IP network connections.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "MPSCP", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "The L3 system is a computational steering environment for image processing and scientific computing. It consists of an interactive graphical language and interface. Its purpose is to help advanced users in controlling their computational software and assist in the management of data accumulated during numerical experiments. L3 provides a combination of features not found in other environments; these are: - textual and graphical construction of programs - persistence of programs and associated data - direct mapping between the scripts, the parameters, and the produced data - implicit hierarchial data organization - full programmability, including conditionals and functions - incremental execution of programs The software includes the l3 language and the graphical environment. The language is a single-assignment functional language; the implementation consists of lexer, parser, interpreter, storage handler, and editing support, The graphical environment is an event-driven nested list viewer/editor providing graphical elements corresponding to the language. These elements are both the representation of a users program and active interfaces to the values computed by that program.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "L3 Interactive Data Language", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "ProteinShop is a graphical environment that facilitates a solution to the protein prediction problem through a combination of unique features and capabilities. These include: 1. Helping researchers automatically generate 3D protein structures from scratch by using the sequence of amino acids and secondary structure specifications as input. 2. Enabling users to apply their accumulated biochemical knowledge and intuition during the interactive manipulation of structures. 3. Facilitating interactive comparison and analysis of alternative structures through visualization of free energy computed during modeling. 4. Accelerating discovery of low-energy configurations by applying local optimizations plug-in to user-selected protein structures. ProteinShop v.2.0 includes the following new features: - Visualizes multiple-domain structures - Automatically creates a user-specified number of beta-sheet configurations - Provides the interface and the libraries for energy visualization and local minimization of protein structures - Reads standard POB files without previous editing.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "A Tool for Interactive Protein Manipulation", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "This software was developed by Lawrence Berkeley National Laboratory.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Hierarchical Resource Manager", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "ROMPIO is a software-based test designed to measure MPI collective, independent, asynchronous, and POSIX file I/O performance, synthesizing how applications utilize file systems in the LANL ASC computing environment. File layouts include N processors to N files and N processors to 1 file. Write access patterns include non-strided and strided. Pure network performance measure can also be obtained for relevant MPI collective calls.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [], + "name": "ROMPIO v 1.0.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "MPI-FTW is a scalable MPI based software application that navigates a directory tree by dynamically allocating processes to navigate sub-directories found. Upon completion, MPI-FTW provides statistics on the number of directories found, files found, and time to complete. In addition, commands can be executed at each directory level.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "mpicc compiler" + ], + "name": "MPI File Tree Walk", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "The Berkeley Quantitative Genome Browser provides graphical browsing functionality for genomic data organized, at a minimum, by sequence and position. 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This was in connection with Incoming License Agreement Number 04-I00039 between Sandia National Labs and AMPL Optimization LLC. Addition of support for random variables as described in SAND2006-4717C to the AMPL language processor; See http://www.ampl.com. This was in connection with Incoming License Agreement Number 04-I00039 between Sandia National Labs and AMPL Optimization LLC.", + "homepageURL": "https://ampl.com/products/solvers/open-source", + "laborHours": 0.0, + "languages": [ + "the subet of C++ recognized by cfront" + ], + "name": "AMPL extensions for stochastic programming", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ampl.com/products/solvers/open-source", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ampl.com/products/solvers/open-source", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "EMPaSE is a hierarchical, extensible, modular modeling environment for developing and running hybrid simulations of sequential-modular, systems dynamics, discrete-event, and agent-based paradigms. 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As with the simulation engine, the GUI is constructed on top of an extensible architecture that supports rapid customization of the user experience through external plug-in libraries.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "gcc>=3.4.2 or Microsfot Visual Studio 2005" + ], + "name": "EMPaSE: an Extensible Multi-Paradigm Simulation Environment", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "JBlulce (Java Beam Line Universal Integrated Configuration Environment is a data acquisition software for macromolecular crystallography conforming user interface of the SSRL Blulce that has become a de-factor standard in the field. 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Finally, the graphic interface is implemented in Java making full use of rich Java libraries and Jave IDE for debugging. to compare, Blulce user interface is implemented with aging Tcl/tk language providing very restricted capabilities. JBlulce makes full use of the industrial power and wide drivers selection of EPICS in controlling hardware; all hardware communication is routed via multiple EPICS servers residing on local area network. JBlulce also includes several EPICS State Notation servers aimed at making hardware communication more robust. Besides using EPICS for controlling hardware, JBlulce extensively uses EPICS databases for efficient communications between multiple instances of JBlulce clients and JBlulce plugins that can run in parallel on different computers. All of the above makes JBlulce one of the biggest and most sophisticated EPICS client projects to date. JBlulce configuration is stored in my SQL database which provides flexibility in tuning the system. 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From the users perspective JBlulce provides all standard features of data acquisition software for macromolecular crystallography plus such unique capabilities as one click beamline energy change that may involve switching undulator harmonics, mirrors lanes and beam realignment, automated diffraction rtastering for finding small crystals and sweet spots on poorly diffracting crystals with automated scoring of raster cells by the number of reflections; data collection along a vector; automated on-the-fly fluorescent tastering, a faster and lower-irradiation compliment to the diffraction raster; fully automated fluorescence measurements for MAD that include signal optimization, fast on the fly energy scanning and automated adapting of scan range to chemical shifts; fly-scan minibeam realignment; automated loop and crystal centering, controls for sample automounter, automated screening, data collection auditing, remote access and a lot more.", + "homepageURL": "https://www.gmca.aps.anl.gov/jbluice-epics", + "laborHours": 0.0, + "languages": [ + "SUN JDK 1.6, Perl 5, EPICS 3.14, SNL 2.0" + ], + "name": "JBlulce Data Acquisition Software for Macromolecular Crystallography", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.gmca.aps.anl.gov/jbluice-epics/jbluice-license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gmca.aps.anl.gov/jbluice-epics", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The Relational Blackboard (RBB) is an extension of the H2 Relational Database to support discrete events and timeseries data. 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Free add-ons and other third party software products are available for use with EnergyPlus.", + "laborHours": 0.0, + "languages": [ + "Intel Fortran V11" + ], + "name": "EnergyPlus Version 7", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://energyplus.net/licensing", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlusRelease/releases/tag/7.0.0.036", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "7.0.0.036" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "meraculous2 is a whole genome shotgun assembler for short-reads that is capable of assembling large, polymorphic genomes with modest computational requirements. Meraculous relies on an efficient and conservative traversal of the subgraph of the k-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. Additional features include (1) handling of allelic variation using \"bubble\" structures within the deBruijn graph, (2) gap closing of repetitive and low quality regions using localized assemblies, and (3) an improved scaffolding algorithm that produces more complete assemblies without compromising on scaffolding accuracy", + "homepageURL": "https://sourceforge.net/projects/meraculous20", + "laborHours": 0.0, + "languages": [ + "GCC g++>=4.63" + ], + "name": "Meraculous2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/meraculous20", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "The MRPA++ computer code simulates neutron scattering and superconductivity in correlated electron systems. It uses a random-phase approximation (RPA) / Bardeen-Cooper-Schrieffer (BCS) theory to predict the neutron scattering cross section of realistic multi-orbital tight-binding models with Hubbard-like electron-electron interactions for the normal and superconducting states. It can also be used to calculate the pairing interaction in these models using an RPA approximation and to predict the superconducting gap structure.", + "laborHours": 0.0, + "languages": [ + "C++/Gnu g++ (GCC)/4.1.2" + ], + "name": "MRPA++", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/maierta/MRPAPP/blob/master/Open%20Source%20Software%20License%20MRPAPP.doc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maierta/MRPAPP", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "This web site provides a single online system for AASG State Geothermal Data participants to integrate their data into the NGDS, discovering how to digitize at-risk, legacy, geothermal-relevant data and combine it with existing digital data to create a publicly accessible system.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "State Geothermal Data data delivery tools", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "This program simulates the beam propagation of weather radar pulses under particular and realistic atmospheric conditions (without using the assumption of standard refraction conditions). It consists of two modules: radiosondings_refract_index_many.pro (MAIN MODULE) beam_propagation_function.pro(EXTERNAL FUNCTION) FOR THE MAIN MODULE, THE CODE DOES OUTPUT--INTO A FILE--THE BEAM HEIGHT AS A FUNCTION OF RANGE. THE RADIOSONDE INPUT FILES SHOULD BE ALREADY AVAILABLE BY THE USER. FOR EXAMPLE, RADIOSONDE OBSERVATION FILES CAN BE OBTAINED AT: RADIOSONDE OBSERVATIONS DOWNLOADED AT \"http://weather.uwyo.edu/upperair/soounding.html\" OR \"http://jervis.pyr.ec.gc.ca\" THE EXTERNAL FUNCTION DOES THE ACTUAL COMPUTATION OF BEAM PROPAGATION. IT INCLUDES CONDITIONS OF ANOMALOUS PROPAGATION AND NEGATIVE ELEVATION ANGLES. THE EQUATIONS USED HERE WERE DERIVED BY EDWIN CAMPOS, BASED ON THE SNELL-DESCARTES LAW OF REFRACTION, CONSIDERING THE EARTH CURVATURE. THE PROGRAM REQUIRES A COMPILER FOR THE INTERACTIVE DATA LANGUAGE (IDL). DESCRIPTION AND VALIDATION DETAILS HAVE BEEN PUBLISHED IN THE PEER-REVIEWED SCIENTIFIC LITERATURE, AS FOLLOWS: Campos E. 2012. Estimating weather radar coverage over complex terrain, pp.26-32, peer reviewed, in Weather Radar and Hydrology, edited by Moore RJ, Cole SJ and Illingworth AJ. International Association of Hydrological Sciences (IAHS) Press, IAHS Publ. 351. ISBN 978-1-907161-26-1.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [ + "Interactive Data Language" + ], + "name": "Beam Propagator for Weather Radars, Modules 1 and 2", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "The Biogeochemical Transport and Reaction Model (BeTR) is a F90 code that enables reactive transport modeling in land modules of earth system models (e.g. CESM, ACME). The code adopts the Objective-Oriented-Design, and allows users to plug in their own biogeochemical (BGC) formulations/codes, and compare them to other existing BGC codes in those ESMs. The code takes information of soil physics variables, such as variables, such as temperature, moisture, soil density profile; water flow, etc., from a land model to track the movement of different chemicals in presence of biogeochemical reactions.", + "laborHours": 0.0, + "languages": [ + "N/A" + ], + "name": "Biogeochemical Transport and Reaction Model (BeTR) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/BeTR-biogeochemistry-modeling/sbetr/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BeTR-biogeochemistry-modeling/sbetr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "A closed-loop proportional-integral (PI) control software is provided for fully mechanically controlled automated electron microscopic tomography. The software is developed based on Gatan DigitalMicrograph, and is compatible with Zeiss LIBRA 120 transmission electron microscope. However, it can be expanded to other TEM instrument with modification. The software consists of a graphical user interface, a digital PI controller, an image analyzing unit, and other drive units (i.e.: image acquire unit and goniometer drive unit). During a tomography data collection process, the image analyzing unit analyzes both the accumulated shift and defocus value of the latest acquired image, and provides the results to the digital PI controller. The digital PI control compares the results with the preset values and determines the optimum adjustments of the goniometer. The goniometer drive unit adjusts the spatial position of the specimen according to the instructions given by the digital PI controller for the next tilt angle and image acquisition. The goniometer drive unit achieves high precision positioning by using a backlash elimination method. The major benefits of the software are: 1) the goniometer drive unit keeps pre-aligned/optimized beam conditions unchanged and achieves position tracking solely through mechanical control; 2) the image analyzing unit relies on only historical data and therefore does not require additional images/exposures; 3) the PI controller enables the system to dynamically track the imaging target with extremely low system error.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "A Closed-Loop Proportional-Integral (PI) Control Software for Fully Mechanically Controlled Automated Electron Microscopic Tomography", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "Beam Instrumentation Development System (BIDS) is a collection of common support libraries and modules developed during a series of Low-Level Radio Frequency (LLRF) control and timing/synchronization projects. BIDS includes a collection of Hardware Description Language (HDL) libraries and software libraries. The BIDS can be used for the development of any FPGA-based system, such as LLRF controllers. HDL code in this library is generic and supports common Digital Signal Processing (DSP) functions, FPGA-specific drivers (high-speed serial link wrappers, clock generation, etc.), ADC/DAC drivers, Ethernet MAC implementation, etc.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "G++, ISE" + ], + "name": "Beam Instrument Development System", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-23" + }, + "description": "miniTri is a miniapplication developed as part of the Mantevo project. Given a graph, miniTri enumerates all triangles in this graph and computes a metric for each triangle based on the triangle edge and vertex degree. The output of miniTri is a summary of this metric. miniTri mimics the computational requirements of an important set of data science applications. Several approaches to this problem are included in the miniTri software.", + "laborHours": 5791.2, + "languages": [ + "C, C++", + "Makefile" + ], + "name": "miniTri Mantevo miniapp v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/miniTri?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniTri", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "GEECS (Generalized Equipment and Experiment Control System) monitors and controls equipment distributed across a network, performs experiments by scanning input variables, and collects and stores various types of data synchronously from devices. Examples of devices include cameras, motors and pressure gauges. GEEKS is based upon LabView graphical object oriented programming (GOOP), allowing for a modular and scalable framework. Data is published for subscription of an arbitrary number of variables over TCP. A secondary framework allows easy development of graphical user interfaces for a combined control of any available devices on the control system without the need of programming knowledge. This allows for rapid integration of GEECS into a wide variety of systems. A database interface provides for devise and process configuration while allowing the user to save large quantities of data to local or network drives.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "LABVIEW 2011 OR LATER" + ], + "name": "GEECS (Generalized Equipment and Experiment Control System)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient distributed algorithms to solve the problem for big data sets. We propose a high-performance distributed-memory parallel algorithm that computes the factorization by iteratively solving alternating non-negative least squares (NLS) subproblems for $\\WW$ and $\\HH$. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). As opposed to previous implementation, our algorithm is also flexible: It performs well for both dense and sparse matrices, and allows the user to choose any one of the multiple algorithms for solving the updates to low rank factors $\\WW$ and $\\HH$ within the alternating iterations.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "HPC-NMF: A High-Performance Parallel Algorithm for Nonnegative Matrix Factorization", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ramkikannan/planc/blob/master/license.dat", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ramkikannan/planc", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-29" + }, + "description": "The purpose of the DYNAMIC software system is to perform simulations to validate a new research concept called “Chaotic Logic” which we recently published. The problem to be solved is to simulate certain networks of nonlinearly-interacting dynamical variables, and collect statistics on their behavior, to show that they can reliably perform useful computations. The dynamical trajectories for such networks are computed by time integration of their Hamilton’s equations.", + "laborHours": 2827.2, + "languages": [ + "Python 3.5.2" + ], + "name": "DYNAMIC - The Nonlinear Dynamical Network Simulator v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/dynamic", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "The ExaSAT framework automates the extraction of parameterized performance models directly from source code using compiler analysis. Its parameterized analytic model enables quantitative evaluation of a broad range of hardware design trade-offs and software optimizations on a variety of different performance metrics, with a primary focus on data movement as a metric. ExaSAT analysis provides insights in the hardware and software tradeoffs and lays the groundwork for exploring a more targeted set of design points using cycle-accurate architectural simulators and emulators.", + "laborHours": 0.0, + "languages": [ + "NA" + ], + "name": "ExaSat: An Exascale Static Analysis Tool (ExaSat) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LBL-CoDEx/exasat/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-CoDEx/exasat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "Modern cosmology and plasma physics codes are now capable of simulating trillions of particles on petascale systems. Each timestep output from such simulations is on the order of 10s of TBs. Summarizing and visualizing raw particle data is challenging, and scientists often focus on density structures, whether in the real 3D space, or a high-dimensional phase space. In this work, code was developed for reading 10s of terabytes of data and for writing the resultant cluster IDs for each particle. This code will be part of a highly scalable version of the clustering algorithm DBSCAN, and apply it to the largest datasets produced by state-of-the-art codes. The overall function of BD-CATS (Big Data Clustering at Trillion Particles Scale) is to perform end-to-end analysis: loading the data, dynamic partitioning, computing kdtrees, performing clustering analysis, and storing the results. BD-CATS-IO provides the functionality of loading the data and storing the results.", + "laborHours": 0.0, + "languages": [], + "name": "BD-CATS-IO", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/hpc-io/BD-CATS-IO/blob/main/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/BD-CATS-IO", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "Camellia offers a framework for development of solvers for the discontinuous Petrov-Galerkin methodology of Demkowicz and Gopalakrishnan as well as other finite element methodologies. Spatially 1D-3D meshes are supported, and space-time elements are supported for all spatial topologies. Both h and p adaptivity are supported. A general interface for direct and iterative solvers is provided; a geometric multigrid preconditioner is also provided. 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Plasmas 14 072706 (2007).", + "laborHours": 0.0, + "languages": [], + "name": "Linear Grains", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LIGR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-04-18", + "metadataLastUpdated": "2024-03-11" + }, + "description": "OPFLearn.jl is a Julia package for creating datasets for machine learning approaches to solving AC optimal power flow (AC OPF). 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To use OPFLearn.jl a PowerModels network data dictionary is required (can be loaded from Matpower \".m\" files) to define the network the dataset is being created for.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "OPFLearn.jl [SWR-21-109]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OPFLearn.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.1.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-04-19", + "metadataLastUpdated": "2022-04-19" + }, + "description": "This software implements a one-dimensional model of a supercapacitor and calibrates it to experimental data. 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Specific tools include:\n- principal geodesic analysis over normal coordinate neighborhoods of matrix manifolds;\n- a variety of data-regularized deformations to nominal 2D airfoil shapes;\n- Riemannian interpolation connecting a sequence of airfoil cross-sections to build 3D blades from 2D data;\n- consistent perturbations over the span of interpolated 3D blades based on dominant modes from the data-driven analysis.", + "laborHours": 0.0, + "languages": [ + "HTML", + "Python" + ], + "name": "G2Aero (Separable shape tensors for aerodynamic design) [SWR-22-44]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/G2Aero", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.0.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-04-22", + "metadataLastUpdated": "2022-06-22" + }, + "description": "The Graph-Env library provides a framework for adapting graph search problems into OpenAI Gym environments for reinforcement learning. 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The entire process is free of human interference. It is usually encountered in practice that, even with a DC power flow solution, acquiring the solved AC power flow solution, if exists, sometimes could be a challenging task, especially during the planning stage. It is also difficult to distinguish the unsolvable cases from diverging iterations. Manual adjustments to approach the desired power flow condition has been largely relied on in the past using lots of engineering heuristics. This tool provides a systematic way to first achieve a solvable AC power flow case by modifying the power flow condition, and then try to track the AC power flow solution while gradually removing the adopted changes. If all adopted changes can be completely removed, then the original AC power flow solution is obtained. Otherwise, insights for actionable controls are derived to help operation and planning. Currently, this tool has been implemented in Python using SIEMENS PTI PSS/E as power flow solver, where only adjusting generator terminal voltage set point is considered as an available means to try to turn an unsolved power flow to a solved one. 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FLASC also largely relies on the energy ratio to, among others, quantify wake losses in synthetic and historical data, to perform turbine northing calibrations, and for model parameter estimation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "FLASC (FLORIS-based Analysis for SCADA data)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/flasc", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-05-05", + "metadataLastUpdated": "2022-05-05" + }, + "description": "lvnm Is a library for fitting latent variable network models within the R programming language. The code focuses on the Stochastic Block Model, Weighted Stochastic Block Model, and Dynamic Stochastic Block Model. Features include simulation methods, estimation methods, diagnostic plots and anomaly detection routines for network data.", + "laborHours": 0.0, + "languages": [ + "R (55%), C++ (40%), Rmarkdown (5%)" + ], + "name": "Latent Variable Network Modeling", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bdabbs13/lvnm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-05-06", + "metadataLastUpdated": "2023-10-25" + }, + "description": "WPGNN is the graph neural network machine learning based surrogate model and software that provides a streamlined approximation of wind plant wake models. 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The PLayGen_demo.ipynb notebook provides a demonstration of how to use the generator tool.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "WPGNN and PLayGen (Wind Plant Graph Neural Network and Plant Layout Generator) [SWR-21-90]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WPGNN", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jewellbc@ornl.gov" + }, + "date": { + "created": "2022-05-09", + "metadataLastUpdated": "2022-05-09" + }, + "description": "Project for overlaying attacks onto existing PCAP data. 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VPIC features very powerful input decks, allowing insertion of arbitrary C++ code for custom diagnostics, boundary conditions, and additional physics models.", + "laborHours": 0.0, + "languages": [], + "name": "VPIC-Kokkos", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vpic-kokkos", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-05-09", + "metadataLastUpdated": "2022-05-09" + }, + "description": "This software consists of a set of codes designed to learn flux limiters from direct numerical simulation data.", + "laborHours": 0.0, + "languages": [], + "name": "Software for Machine Learning a Flux Limiter", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/fluxlimiter", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-05-09", + "metadataLastUpdated": "2022-05-10" + }, + "description": "Web application that interacts with the Amazon AWS S3 REST API to allow users to manage files and buckets without having to use the aws command line application.", + "laborHours": 0.0, + "languages": [], + "name": "s3-browser", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/s3-browser", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-05-09", + "metadataLastUpdated": "2022-05-10" + }, + "description": "rhelhostinfo v1.x adds some functionality to the existing approved C21099 rhelhostinfo by identifying host configuration changes over time. 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The software implements the neural circuit itself and a demonstration application where the MNIST dataset (a standard test problem) is used to train a neural network.", + "laborHours": 0.0, + "languages": [], + "name": "Neuromorphic Backpropagation Algorithm Software", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/spikingBackprop", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-05-09", + "metadataLastUpdated": "2022-05-09" + }, + "description": "The catemis python package includes the analysis methods used in paper \"DARHT Axis-II Dispenser-Cathode Emissivity and Temperature\", which was presented at the 2021 Weapons Engineering Symposium and Journal (WESJ) hosted by Los Alamos National Laboratory. The paper (LA-UR-21-25647) and presentation (LA-UR-21-28231) report on a temperature and emissivity model that has been developed and applied to data from diagnostics used to measure the surface temperature of the DARHT Axis-II hot dispenser cathode over more than a decade of operation. The catemis package provides all the methods used in reporting these results along with the data files used to create the plots and tables in the paper. This includes methods for loading and processing FAR spectral pyrometer data along with methods for temperature calibration of cathode images.", + "laborHours": 0.0, + "languages": [], + "name": "Python catemis package for DARHT Axis-II Dispenser-Cathode Emissivity and Temperature Analysis", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/koglin-LANL/catemis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-05-09", + "metadataLastUpdated": "2022-05-09" + }, + "description": "The disclosure is about the numerical simulations and visualization implemented in general-purpose language Python and C++. 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The Python APIs are provided using Pybind11", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/NWHypergraph", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/NWHypergraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-06-01", + "metadataLastUpdated": "2022-06-01" + }, + "description": "Garbled Autonomous Bots Leveraging Ethereum (GABLE) uses simple but effective algorithms to permit secure private execution of garbled state machines and garbled circuits on public computing resources. 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SAND2022-7215 O", + "laborHours": 0.0, + "languages": [ + "Solidity" + ], + "name": "GABLE contract source code", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gable", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "kainerd@ornl.gov" + }, + "date": { + "created": "2022-06-07", + "metadataLastUpdated": "2022-06-23" + }, + "description": "a set of command-line and R tools for performing Random-walk with Restart analyses on multiplex networks in any species", + "laborHours": 0.0, + "languages": [ + "R" + ], + "name": "dkainer/RWRtoolkit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/dkainer/rwrtoolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lees4@ornl.gov" + }, + "date": { + "created": "2022-06-09", + "metadataLastUpdated": "2022-06-23" + }, + "description": "Brick (https://brickschema.org/) is a unified metadata schema to address the problem of building data standardization. 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The package is designed to smoothly work standalone or be used with the numpyro probabilistic programming language.", + "laborHours": 0.0, + "languages": [], + "name": "dfdjaxGP", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/dfdjaxGP", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2022-07-15" + }, + "description": "SplitML (Signal Processing Library for Interference rejecTion by Machine Learning) is a code repository for a set of tools for interference rejection in complex time-domain signals. The goal of the tools is to provide machine learning modeling capabilities for rejecting interference. Recent related machine learning algorithms for signal processing have focused mostly on speech enhancement or multi-speaker speech separation; the tools in SplitML will extend these innovations to generic time-domain signals of interest. SplitML includes tools for generating synthetic noisy signals, code for customized machine learning models applicable to interference rejection, and tools for evaluating such algorithms against standard signal processing techniques. These components are written in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning and signal processing.", + "laborHours": 0.0, + "languages": [], + "name": "SplitML", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SplitML", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Ray tracing and ray casting have been extensively studied by the graphics and visualization community to create images. Many different algorithms as well as optimizations techniques have been developed to help speed up these two techniques and make best use of different hardware. However, ray tracing and ray casting can also be used for scientific purposes. While graphics applications focus on photon interactions, scientific application will also monitor the interaction of photons, electrons, neutrons, alpha particles, and other particles. For example, ray casting can be used in cosmology to study the re-ionization of the early universe where ultraviolet photons broke atoms apart and ray tracing of ions can be used to study mass spectography. For this project, the aim is to investigate how techniques, frameworks, algorithms, optimizations, ... developed by the graphics community could be modified and applied to solve scientific problems requiring the tracing of different particles.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Agnostic Particle Tracing", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2022-07-15" + }, + "description": "Test suite of quantum algorithms for Noisy Intermediate Scale Quantum (NISQ) computers. The test suite includes benchmark-style code for quantum volume circuits (QV), fairness sampling circuits, quantum telecloning circuits, and other NISQ benchmark style algorithms on small problems (i.e., up to 100 qubits), such as Variational Quantum Eigensolver (VQE), Hamiltonian Simulation, and Grover unstructured search example circuits. These benchmark-style applications are implemented in quantum software packages, mostly IBM's QISKIT, but may include vendor-specific frameworks, such as PyQuil (for Rigetti) or Q\\# for Microsoft, or CirQ (for Google) as the test suite grows with the vendor sample. The test suite also includes numerical simulation code for Quantum Alternating Operator Ansatz (QAOA) algorithms, VQE, Hamiltonian Simulation and search examples. Numerical simulation code simulates quantum computers on classical computers, which is only possible for small problem instances; the implementation framework of choice is typically within Python, using the numpy/scipy libraries as well as extensions to the Julia language.", + "laborHours": 0.0, + "languages": [], + "name": "NISQ Benchmarking", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Quantum-Volume-in-Practice", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2022-07-15" + }, + "description": "The Sunny package is an existing open source software to support the simulation of magnetic spin systems. It is available online under the MIT license here: https://github.com/SunnySuite/Sunny.jl The package aims to include the following features: - Analysis for symmetry-allowed interactions - Monte Carlo algorithms for simulating equilibrium configurations. - Schemes for integrating spin dynamics. - Inference of model Hamiltonians - Support for generalized SU(N) spins - Tools for interpreting experimental data, such as diffraction data, magnetization curves, and heat capacity data", + "laborHours": 0.0, + "languages": [], + "name": "Contributing to Sunny open source code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SunnySuite/Sunny.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PUFFIn software package is a graphical user interface that allows for photon and electron beam calculations using the\nPENELOPE computer code. It prepares the required input files and displays the resulting output data. It can be used by\nanyone interested in the interaction of photon or electron beams with matter", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "PUFFIn", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SOCRATES is a Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites. It provides tools to retrieve, filter,\nselect, and view Hanford data and to perform multiple types of data analyses. SOCRATES currently includes four data\nanalytics modules", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "SOCRATES", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Chernobyl Bibliographic Search System (Chernolit TM) provides bibliographic data in a usable format for research studies relating to the Chernobyl nuclear accident that occurred in the former Ukrainian Republic of the USSR in 1986. Chernolit TM is a portable and easy to use product. The bibliographic data is provided under the control of a graphical user interface so that the user may quickly and easily retrieve pertinent information from the large database. The user may search the database for occurrences of words, names, or phrases; view bibliographic references on screen; and obtain reports of selected references. Reports may be viewed on the screen, printed, or accumulated in a folder that is written to a disk file when the user exits the software. Chernolit TM provides a cost-effective alternative to multiple, independent literature searches. Forty-five hundred references concerning the accident, including abstracts, are distributed with Chernolit TM. The data contained in the database were obtained from electronic literature searches and from requested donations from individuals and organizations. These literature searches interrogated the Energy Science and Technology database (formerly DOE ENERGY) of the DIALOG Information Retrieval Service. Energy Science and Technology, provided by the U.S. DOE, Washington, D.C., is a multi-disciplinary database containing references to the world's scientific and technical literature on energy. All unclassified information processed at the Office of Scientific and Technical Information (OSTI) of the U.S. DOE is included in the database. In addition, information on many documents has been manually added to Chernolit TM. Most of this information was obtained in response to requests for data sent to people and/or organizations throughout the world.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Chernobyl Bibliographic Search System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "SID characterizes natural language based documents so that they may be related and retrieved based on content similarity. This technology processes textual documents, autonomously identifies the major topics of the document set, and constructs an interpretable, high dimensional representation of each document. SID also provides the ability to interactively re-weight representations based on user needs, so that users may analyze the data set from multiple points of view. The particular advantages SID offers are speed, data compression, flexibility in representation, and incremental processing.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "System for Information Discovery", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "SID characterizes natural language based documents so that they may be related and retrieved based on content similarity. This technology processes textual documents, autonomously identifies the major topics of the document set, and constructs an interpretable, high dimensional representation of each document. SID also provides the ability to interactively reweight representations based on user need, so users may analyze the dataset from multiple points of view. The particular advantages SID offers are speed, data compression, flexibility in representation, and incremental processing. SPIRE consists of software for visual analysis of text-based information sources. This technology enables users to make discoveries about the content of very large sets of textual documents without requiring the user to read or presort the documents. It employs algorithms for text and word proximity analysis to identify the key themes within the documents. The results of this analysis are projected onto a visual spatial proximity display (Galaxies or Themescape) where document proximity represents the degree of relatedness of theme.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "System for Information Discovery - SPIRE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Acoustic Inspection Device (AID) is an instrument used to interrogate materials with ultrasonic acoustic waves. The AID application software program runs under the Microsoft Windows 98 or Windows 2000 operating system. Is serves as the instrument controller and provides the user interface for the instrument known as the Acoustic Inspection Device (AID). The program requests, acquires, and analyzes acoustic waveforms from the AID hardware (pulser/receiver module, digitizer, and communications link). Graphical user displays of the AID application program include the real-time display of ultrasonic acoustic waveforms and analytical results including acoustic time-of-flight, velocity, and material identification. This program utilizes a novel algorithm, developed at PNNL, that automatically extracts the time-of-flight and amplitude data from the raw waveform and compares the extracted data to a material database.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Acoustic Inspection Device V1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The D3P system is designed to provide a very fast imaging system in order to search for weapons on persons in an airport environment. The complete vision of the D3P system is to have two array systems facing each other. Version 2.3 of the software is designed to control and process data from a single panel. A second panel is expected to be added at a future date and the software will be modified at that time to integrate the images from two panels at one time. The D3P software can be segmented into three specific tasks. The first task is data acquisition and scanner control. At the operator's request, this task commands the scanner to move and the radar transceiver-array to send data to the computer system in a known and well-ordered manner. The array is moved over the complete aperture in 1 to 2 seconds. At the completion of the array movement the second software task reconstructs the high-resolution image from the radar data utilizing the integrated DSP board. The third task displays the result to the computer screen for user review and analysis.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Dual Panal Planar Portal", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The CS system is designed to provide a very fast imaging system in order to search for weapons on persons in an airport environment. The Cylindrical Scanner moves a vertical transceiver array rapidly around a person standing stationary. The software can be segmented in to three specific tasks. The first task is data acquisition and scanner control. At the operator's request, this task commands the scanner to move and the radar transceiver array to send data to the computer system in a known and well-ordered manner. The array is moved over the complete aperture in 10 to 12 seconds. At the completion of the array movement the second software task automatically reconstructs the high-resolution image from the radar data utilizing the integrated DSP boards. The third task displays the resulting images, as they become available, to the computer screen for user review and analysis.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Cylindrical Scanner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "TRA was developed as a computer tool for the DOE Office of River Protection (ORP) that will provides the capability to visualize and rapidly understand information about the risks associated with the River protection Project (RPP). Previously, technical and programmatic risk management within ORP had relied heavily on risk lists and other techniques that presented risk information but did not place it in perspective of the overall project. This made it difficult for ORP senior management to understand the risk information presented, prioritize their activities, and provide direction to ORP staff and contractors about how to manage specific risk events. The TRA visualization tool, provides the appropriate context and perspective that allows senior management to effectively manage risks. Basically, the TRA overlays information about risks associated with specific activities and their magnitudes on top of the project baseline schedule. this provides senior management with information about the magnitudes of specific risk events as well as their timing, and allows them to focus their attention and resources on the risks that merit attention and possible further action. The TRA tool can also be used to display other types of information associated with scheduled activities, such as cost to date, technical performance, schedule performance, etc. Additionally, the base of the 3-dimensional representation can be changed to other types of graphics, such as maps, process flow diagrams, etc., which allows the display of other types of information, such as hazards, health and safety risks, and system availability.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Topographical Risk Assessment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Code for Internal Dosimetry Software Package (CINDY1.4) was developed to assist in the interpretation of bioassay data, provide bioassay projections, and evaluate committed and calendar-year doses from intake or bioassay measurement data. CINDY1.4 addresses the U.S. Department of Energy's (DOE) Order 5480.11 and the U.S. Nuclear Regulatory Commission's (NRC) 10 CFR 20 by providing the capabilities to calculate organ dose equivalents and effective dose equivalents using the International Commission on radiological Protection (ICRP) 30 approach. Biokinetic models, which allow user-modified parameter values, are used to estimate intakes based on bioassay data using weighted and unweighted least-squares regression between measured and expected bioassay values, to estimate organ burdens as well as urinary and fecal excretion rates from a given intake, and to determine organ doses for annual, 50-year, calendar year, or any other time point. Intakes to be considered may be either acute or chronic, and may consist of many combinations of intake routes, radionuclides, and physical and chemical forms. A four-compartment input model (with user defined parameters) is used for wounds and absorption. Direct injection can be simulated as direct absorption. Appropriate metabolic models for each radionuclide are selected by the user from menus. Metabolic models available in CINDY1.4 are the ICRP 30 lung model, ICRP 30 gastrointestinal model, ICRP 30 general systematic model, Johnson and Dunford tritium model, ICRP 30 tritium model, including the Johnson HT lung model, Johnson alkaline earth model, ICRP 54 iodine model, tellurium-iodine model, Jones excretion model, Durbin excretion model, ICRP 54 excretion models, Wrenn-Lipsztein uranium model, Fisher Modified Wrenn-Lipsztein uranium model, and the ICRP 30 carbon model. For Windows 95 or Windows NT an alternate CD is required.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Code for INternal DosimetrY", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Ipmiping is a collection of two programs, impiping and rmcpping. Both ipmiping and rmcpping are similar to the Unix/Linux ping utility, except they use a different network protocol. Ipmiping uses Intelligent Platform Management Interface (IPMI) messages to discover if a remote destination supports IPMI. Rmcpping uses remote management control protocol (RMCP) messages to discover if a remote destination supports RMCP.", + "homepageURL": "https://www.gnu.org/software/freeipmi", + "laborHours": 0.0, + "languages": [], + "name": "Ipmiping V1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The XML Engineering Environment is a reconfigurable software system that allows users to translate, enhance and route data from sources to sinks.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "XML Engineering Environment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Web Operational Status Boards (WebOSB)is a web-based application designed to acquire, display, and update highly dynamic status information between multiple users and jurisdictions. WebOSB is able to disseminate real-time status information support the timely sharing of information with constant, dynamic updates via personal computers and the Internet between emergency operations centers (EOCs), incident command centers, and to users outside the EOC who need to know the information (hospitals, shelters, schools). The WebOSB application far exceeds outdated information-sharing methods used by emergency workers: whiteboards, Word and Excel documents, or even locality-specific Web sites. WebOSB's capabilities include the following elements: - Secure access. Multiple users can access information on WebOSB from any personal computer with Internet access and a secure ID. Privileges are use to control access and distribution of status information and to identify users who are authorized to add or edit information. - Simultaneous update. WebOSB provides options for users to add, display, and update dynamic information simultaneously at all locations involved in the emergency management effort, A single status board can be updated from multiple locations enabling shelters and hospitals to post bed availability or list decontamination capability. - On-the-fly modification. Allowing the definition of an existing status board to be modified on-the-fly can be an asset during an emergency, where information requirements can change quickly. The status board designer feature allows an administrator to quickly define, modi,, add to, and implement new status boards in minutes without needing the help of Web designers and computer programmers. - Publisher/subscriber notification. As a subscriber, each user automatically receives notification of any new information relating to specific status boards. The publisher/subscriber feature automatically notified each user of any new information relating to specific status boards. WebOSB can be installed to fit the specific needs of an emergency management community. 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This version is intended to be implemented as a world wide web application and made accessible to end users by use of a Web browser and an Internet connection, but the web interface is not provided as part of the software - a web service provider must provide the web-based graphical user interface.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Whole Building Energy Diagnostician, version 3.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "DCAF is a software library containing analytic functions for encoding, mapping, structuring, and providing access to relations among a collection of entities and deriving attribute and structural features for the purposes of providing an interpretable representation of the information within a collection.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Deep Center Analytical Foundations v. 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "GreenArrow is a visualization program for displaying directed graphs that can use text in place of lines to represent the edges between nodes. 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When faults are detected, the software provides alarm codes corresponding to the detected problem(s). These alarms map into explanations of the faults, possible causes for them, and suggested actions to remedy the faults. For air handling, the software also estimates energy and cost impacts of faults. The software is intended for implementation on a hardware systems that includes sensors, sensor signal processing, micro-processor unit for running this software, and communication to a web server. Results are made available to users via the world wide web using a computer with Web browser and Internet connection for access. 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The CORE Technology Program includes a suite of tools and user-centered staff that can facilitate rapid delivery of a deployable integrated information to users. Integration of Air Force data streams, summarizing the information and providing team members with the information they need to rapidly understand and respond.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Common Operating and Response Environment - U.S. Air Force", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "CORE is an architecture to bridge the gaps between disparate data integration and delivery of disparate information visualization. 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The interaction with the system is independent of time and location, so that input of information and conversations can occur more naturally as they currently do with email.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Situational Awareness for Strategic Leadership (part of CORE system)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Resource management and workflow capability applied to engineering design situational awareness, providing the ability to make assignments and track progress through the construction and maintenance life cycle of an engineered structure.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Resource Tracking and Workflow System - part of the CORE system", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "A data integration system to support the US Customs and Border Protection Officers to supervise and make decisions for container inspections. CORE is designed to act as a framework to bridge the gaps between disparate data integration and delivery of disparate information visualization.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Container Security - part of the CORE system", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "EMTA is a stand-alone computer program that has been developed for the computation of elastic properties and thermal expansion coefficients (thermoelastic properties) of discontinuous fiber composites. EMTA stands for the Eshelby-Mori-Tanaka approach. It implements the standard and modified Mori-Tanaka models that use the Eshelby's equivalent inclusion method. EMTA carries out the Eshelby-Mori-Tanaka homogenization procedure accounting for the constituents (fiber and matrix) properties such as the elastic properties and thermal expansion coefficients (CTEs) of the fibers and of the matrix. It also accounts for the constituents features such as fiber length and orientation distributions, fiber curvature, and imperfect fiber/matrix interfaces. The outputs of an EMTA execution are the elastic properties (engineering constants) and CTEs of the as-formed composite in the defined material coordinate system. These results can readily be used in engineering applications and designs that require these properties.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Eshelby-Mori-Tanaka Approach", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "EMTA-NLA is a computer program for analyzing the nonlinear stiffness, strength, and thermo-elastic properties of discontinuous fiber composite materials. Discontinuous fiber composites are chopped-fiber reinforced polymer materials that are formed by injection molding or compression molding techniques. The fibers tend to align during forming as the composite flows and fills the mold. EMTA-NLA can read the fiber orientation data from the molding software, Autodesk Moldflow Plastics Insight, and calculate the local material properties for accurately analyzing the warpage, stiffness, and strength of the as-formed composite part using the commercial NLA software. Therefore, EMTA-NLA is a unique assembly of mathematical algorithms that provide a one-of-a-kind composites constitutive model that links these two powerful commercial software packages.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "EMTA-NLA", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The ESG-CET system consist of two major components: 1) Gateways that support portal services, which serve as interfaces to end-users who can search, discover, and request data and data products, and 2) Data Nodes where the data actually resides. The Data is \"published\" to the Data Node, which makes the data visible to a Gateway and enables its delivery to end-users. It is expected that Gateways will only be installed by a small number of centers devoted to serving data (e.g., LLNL/PCMDI, NCAR, GFDL, DADC, DKRZ, ANU, JAMSTEC), whereas it is hoped that most climate modeling centers will install the Data Node software through which they can serve their model output.", + "laborHours": 0.0, + "languages": [], + "name": "Earth System Grid (ESG) Data Node Software Stack", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/earth-system-grid-esg-data-node-software-stack", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Fit event counting histograms.", + "laborHours": 0.0, + "languages": [], + "name": "Levenberg-Marquardt Minimization for Poisson Distributed Data", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/levenberg-marquardt-minimization-for-poisson-distributed-data", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Pacific Northwest National Laboratory (PNNL) has developed a prototype stream extraction algorithm that semi-automatically extracts and characterizes streams using a variety of multisensor imagery and digital terrain elevation data. The system is currently optimized for three types of single-band imagery: radar, visible, and thermal. Method of Solution: DRAGON: (1) classifies pixels into clumps of water objects based on the classification of water pixels by spectral signatures and neighborhood relationships, (2) uses the morphology operations (erosion and dilation) to separate out large lakes (or embayment), isolated lakes, ponds, wide rivers and narrow rivers, and (3) translates the river objects into vector objects. In detail, the process can be broken down into the following steps. A. Water pixels are initially identified using on the extend range and slope values (if an optional DEM file is available). B. Erode to the distance that defines a large water body and then dilate back. The resulting mask can be used to identify large lake and embayment objects that are then removed from the image. Since this operation be time consuming it is only performed if a simple test (i.e. a large box can be found somewhere in the image that contains only water pixels) that indicates a large water body is present. C. All water pixels are clumped (in Imagine terminology clumping is when pixels of a common classification that touch are connected) and clumps which do not contain pure water pixels (e.g. dark cloud shadows) are removed D. The resulting true water pixels are clumped and water objects which are too small (e.g. ponds) or isolated lakes (i.e. isolated objects with a small compactness ratio) are removed. Note that at this point lakes have been identified has a byproduct of the filtering process and can be output has vector layers if needed. E. At this point only river pixels are left in the image. To separate out wide rivers all objects in the image are eroded by the half width of narrow rivers. This causes all narrow rivers to be removed and leaves only the core of wide rivers. This core is dilated out by the same distance to create a mask that is used with the original river image to separate out rivers into two separate images of narrow rivers and wide rivers F. If in the image that contains wide rivers there are small isolated short (less than 300 meters if NGA criteria is used) segments these segments are transferred to the narrow river file in order to be treated has parts of single line rivers G. The narrow river file is optionally dilated and eroded. This closing has the effect of removing small islands, filling small gaps, and smoothing the outline. H. The user also has the option of closing objects in the wide river file. However, this depends on the degree to which the user wants to remove small islands in the large rivers. I. To make the translation from raster to single vector easier the objects in the narrow river image are reduced to a single center line (i.e. thinned) with binary morphology operations.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Drainage Algorithm for Geospatial Knowledge", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The RAD3D software solves the critical heat transfer mechanisms that occur in production glass furnaces. The code includes state-of-the-art solution algorithms for efficient radiant interaction of the heating elements, furnace walls and internal furnace components. The code specifically solves the coupled radiative and conductive heating of semi-transparent materials such as glass to calculate the temperature distribution in the glass during processing.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Radiation Heat Transfer in 3 Dimensions for Semi-Transparent Materials....", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Polisher is a software package designed to facilitate the error correction of an assembled genome using Illumia read data. The software addresses substandard regions by automatically correcting consensus errors and/or suggesting primer walking reactions to improve the quality of the bases.", + "laborHours": 0.0, + "languages": [ + "Perl" + ], + "name": "Polisher", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/polisher", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "MANGO software is to provide a solution for improving small signal stability of power systems through adjusting operator-controllable variables using PMU measurement. System oscillation problems are one of the major threats to the grid stability and reliability in California and the Western Interconnection. These problems result in power fluctuations, lower grid operation efficiency, and may even lead to large-scale grid breakup and outages. This MANGO software aims to solve this problem by automatically generating recommended operation procedures termed Modal Analysis for Grid Operation (MANGO) to improve damping of inter-area oscillation modes. The MANGO procedure includes three steps: recognizing small signal stability problems, implementing operating point adjustment using modal sensitivity, and evaluating the effectiveness of the adjustment. The MANGO software package is designed to help implement the MANGO procedure.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab, Python script, batch script, PSAT Python script" + ], + "name": "Modal Analysis for Grid Operation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "FLOWER was written as a refactoring/reimplementation of the existing Flo software used by the Cooperative Protection Program (CPP) to provide network flow summaries for analysis by the Operational Analysis Center (OAC) and other US Department of Energy cyber security elements. FLOWER is designed and tested to operate at 10 gigabits/second, nearly 10 times faster than competing solutions. FLOWER output is optimized for importation into SQL databases for categorization and analysis. FLOWER is written in C++ using current best software engineering practices.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "FLOWER IPv4/IPv6 Network Flow Summarization software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Liquid Chromatography-Ion Mobility-time of Flight Instrument Control and Data Visualization software is designed to control instrument voltages for the Ion Mobility drift tube. It collects and stores information collected from the Agilent TOF instrument and analyses/displays the ion intensity information acquired. The software interface can be split into 3 categories -- Instrument Settings/Controls, Data Acquisition, and Viewer. The Instrument Settings/Controls prepares the instrument for Data Acquisition. The Viewer contains common objects that are used by Instrument Settings/Controls and Data Acquisition. Intensity information is collected in 1 nanosec bins and separated by TOF pulses called scans. A collection of scans are stored side by side making up an accumulation. In order for the computer to keep up with the stream of data, 30-50 accumulations are commonly summed into a single frame. A collection of frames makes up an experiment. The Viewer software then takes the experiment and presents the data in several possible ways, each frame can be viewed in TOF bins or m/z (mass to charge ratio). The experiment can be viewed frame by frame, merging several frames, or by viewing the peak chromatogram. The user can zoom into the data, export data, and/or animate frames. Additional features include calibration of the data and even post-processing multiplexed data.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C#, C++" + ], + "name": "LC-IM-TOF Instrument Control & Data Visualization Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Wrapper Induction is a software package that allows for unsupervised, semi-supervised, and manual extraction of social media data independent of language or site architecture. A large range of blog formats is available to individuals as means of publishing data to the internet. Blogs are a source of rich information for analysts. With a growing volume of information and blog engines, there is an increased need for automatic or semi-automatic extraction of that data for processing to help deliver results to analysts. Wrapper Induction is designed to automatically or semi-automatically create a template that can be used to harvest blog data from websites. Blogs are in a variety of formats and languages. Wrapper Induction creates a template and extracts blog data in a way that is independent of a specified blog format or language.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java, Javascript" + ], + "name": "Wrapper Induction Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "GridLAB-D is a new power system simulation tool that provides valuable information to users who design and operate electric power transmission and distribution systems, and to utilities that wish to take advantage of the latest smart grid technology. This special release of GridLAB-D was developed to study the proposed Smart Grid technology that is used by Battelle Memorial Institute in the AEP gridSMART demonstration project in Northeast Columbus, Ohio.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C, C++, Java" + ], + "name": "GridLAB-D/SG", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "A hybrid demand response simulator is developed to test different control algorithms for centralized and distributed demand response (DR) programs in a small distribution power grid. The HDRS is designed to model a wide variety of DR services such as peak having, load shifting, arbitrage, spinning reserves, load following, regulation, emergency load shedding, etc. The HDRS does not model the dynamic behaviors of the loads, rather, it simulates the load scheduling and dispatch process. The load models include TCAs (water heaters, air conditioners, refrigerators, freezers, etc) and non-TCAs (lighting, washer, dishwasher, etc.) The ambient temperature changes, thermal resistance, capacitance, and the unit control logics can be modeled for TCA loads. The use patterns of the non-TCA can be modeled by probability of use and probabilistic durations. Some of the communication network characteristics, such as delays and errors, can also be modeled. Most importantly, because the simulator is modular and greatly simplified the thermal models for TCA loads, it is very easy and fast to be used to test and validate different control algorithms in a simulated environment.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab/Simlink" + ], + "name": "A Hybrid Demand Response Simulator Version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "DSOM (Decision Support for Operations and Maintenance) is an expert operations and maintenance system that integrates plant operations, fuel management, and maintenance processes. The DSOM package provides operators with the information they need for cost-effective operating decisions creating savings in fuel, personnel, maintenance, and plant life extension. DSOM provides operators real-time system performance information to allow them to determine if the plant is malfunctioning or running below expectations. By catching potential problems, DSOM enables plants to operate safely at peak efficiency, while providing a higher level of reliability and safety.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++", + "Java", + "PHP" + ], + "name": "Decision Support for Operations and Maintenance IV", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Tool Gear Version 2 is an expanded collection of programs and software libraries that form the infrastructure on which software tools may be built. The software tools help application developers understand the performance of the programs or help them find programming errors. Tool Gear includes components for gathering data from target programs, either through direct instrumentations or by parsing the output of third-party tools, transmitting the data to a database, organizing and storing the data, presenting it through a variety of graphical interfaces. Tool Gear is designed to be an extensible system, so users can manage a variety of data and create new ways to present it. Tool Gear is designed to work with both sequential and parallel programs on multiple computer platforms", + "laborHours": 0.0, + "languages": [], + "name": "Tool Gear Version 2.3", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/tool-gear-version-2.3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The CLOMP_TM benchmark was developed to measure the overheads of various mechanisms used to guarantee the generation of correct results in threaded code even when multiple threads might be accessing and/or updating the same memory location at the same time. This includes widely supported mechanisms like OpenMP Atomic and Open MP Critical as well as new mechanisms like Transactional Memory (TM) and Speculative Execution (SE) of threads. The CLOMP_TM benchmark is highly configurable to allow a variety of problem sizes, atomic update region sizes, and potential race condition opportunities to be studied. A wide variety of checks are done on the results to verify the expected answer was actually generated. Thus CLOMP_TM can be used both to measure the overhead for various mechanisms and to check the correctness of their implementation.", + "laborHours": 0.0, + "languages": [], + "name": "CLOMP_TM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/clomp-tm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "ASSA is a software application that processes binary data into summarized index tables that can be used to organize features contained within the data. ASSA's index tables can also be used to search for user specified features. ASSA is designed to organize and search for patterns in unstructured binary data streams or archives, such as video, images, audio, and network traffic. ASSA is basically a very general search engine used to search for any pattern in any binary data stream. It has uses in video analytics, image analysis, audio analysis, searching hard-drives, monitoring network traffic, etc.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++, C, Fortran, Python, PHP, Javascript, HTML" + ], + "name": "All Source Sensor Analysis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "MSI QuickView is a software designed to provide a graphical user interface (GUI) for greatly speeding up experimental feedback (visualization and analysis) of mass spectrometry imaging (MSI or IMS) data during data acquisition. Often different software loads the entire data set, i.e., all lines of data into computer memory (RAM). This causes out of memory errors for larger datasets. We solved this in MSI QuickView by reading in the data one line at a time. Only the required information (e.g. the final pixel values for that line of heat map) is maintained in RAM. Interim analysis options include the mean intensity vs. m/z spectrum, intensity vs. time spectrums for up to 6 different m/z values or ranges chosen by the user and heat maps for each line. This assists in validating the usefulness of the particular experiment after scanning the first few lines. In addition, the tool facilitates further processing and analysis of the massive datasets. The user can manually pick different m/z values, time ranges, scroll through the spectra for any line in the data without having to load it in manually, save multiple images, change aspect ratios for the heat maps, and process the heat maps in multiple ways including overlaying images at different m/z values, displaying up to 9 different heat maps, alignment of scans along each line etc. There is no manipulation of the data required by the user to visualize the data.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "MATLAB, Java" + ], + "name": "Mass Spectrometry Imaging Quick View", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "LC-IMS-MS Feature Finder is a command line software application which searches for possible molecular ion signatures in multidimensional liquid chromatography, ion mobility spectrometry, and mass spectrometry data by clustering deisotoped peaks with similar monoisotopic mass values, charge states, elution times, and drift times. The software application includes an algorithm for detecting multiple conformations and co-eluting species in the ion mobility dimension. LC-IMS-MS Feature Finder is designed to create an output file with detected features that includes associated information about the detected features.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "LC-IMS-MS Feature Finder", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The BioPA provides turbine designers with a set of tools that can be used to assess biological risks of turbines during the design phase, before expensive construction begins. The toolset can also be used to assess existing installations under a variety of operating conditions, supplementing data obtained through expensive field testing. The BioPA uses computational fluid dynamics (CFD) simulations of a turbine design to quantify the exposure of passing fish to a set of known injury mechanisms. By appropriate sampling of the fluid domain, the BioPA assigns exposure probabilities to each mechanism. The exposure probabilities are combined with dose-response data from laboratory stress studies of fish to produce a set of biological BioPA Scores. These metrics provide an objective measure that can be used to compare competing turbines or to refine a new design. The BioPA process can be performed during the turbine design phase and is considerably less expensive than prototype-scale field testing.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Tecplot Macro, Python, Visual Basic" + ], + "name": "Biological Performance Assessment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Spindle is software infrastructure that solves file system scalability problems associated with starting dynamically linked applications in HPC environments. When an HPC applications starts up thousands of processes at once, and those processes simultaneously access a shared file system to look for shared libraries, it can cause significant performance problems for both the application and other users. Spindle scalably coordinates the distribution of shared libraries to an application to avoid hammering the shared file system.", + "laborHours": 0.0, + "languages": [], + "name": "Spindle", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/hpc/Spindle/blob/devel/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/spindle", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "SOFC-MP is a simulation tool developed at PNNL to evaluate the tightly coupled multi-physical phenomena in SOFCs. The purpose of the tool is to allow SOFC manufacturers to numerically test changes in planar stack design to meet DOE technical targets. The SOFC-MP 2D module is designed for computational efficiency to enable rapid engineering evaluations for operation of tall symmetric stacks. It can quickly compute distributions for the current density, voltage, temperature, and species composition in tall stacks with co-flow or counter-flow orientations. The 3D module computes distributions in entire 3D domain and handles all planner configurations: co-flow, counter-flow, and cross-flow. The detailed data from 3D simulation can be used as input for structural analysis. SOFC-MP GUI integrates both 2D and 3D modules, and it provides user friendly pre-processing and post-processing capabilities.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++, FORTRAN, C#" + ], + "name": "Solid Oxide Fuel Cell - Multi-Physics and GUI", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "BMA-NIS is a package/library designed to be called by a script (e.g. Perl or Python). The software itself is written in the language of R. The software assists electric power delivery systems in planning resource availability and demand, based on historical data and current data variables. Net Interchange Schedule (NIS) is the algebraic sum of all energy scheduled to flow into or out of a balancing area during any interval. Accurate forecasts for NIS are important so that the Area Control Error (ACE) stays within an acceptable limit. To date, there are many approaches for forecasting NIS but all none of these are based on single models that can be sensitive to time of day and day of week effects.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "R" + ], + "name": "System for NIS Forecasting Based on Ensembles Analysis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "RUT software is designed for use by the Balancing Authorities to predict and display additional requirements caused by the variability and uncertainty in load and generation. The prediction is made for the next operating hours as well as for the next day. The tool predicts possible deficiencies in generation capability and ramping capability. This deficiency of balancing resources can cause serious risks to power system stability and also impact real-time market energy prices. The tool dynamically and adaptively correlates changing system conditions with the additional balancing needs triggered by the interplay between forecasted and actual load and output of variable resources. The assessment is performed using a specially developed probabilistic algorithm incorporating multiple sources of uncertainty including wind, solar and load forecast errors. The tool evaluates required generation for a worst case scenario, with a user-specified confidence level.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "VB.NET" + ], + "name": "Ramping and Uncertainty Prediction Tool - Analysis and Visualization of Wind Generation Impact on Electrical Grid", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "ESIOS is a software program developed at Pacific Northwest National Laboratory (PNNL) that performs intra-hour dispatch and automatic generation control (AGC) simulations for electric power system frequency regulation and load/variable generation following. The program dispatches generation resources at minute interval to meet control performance requirements, while incorporating stochastic models of forecast errors and variability with generation, load, interchange and market behaviors. The simulator also contains an operator model that mimics manual actions to adjust resource dispatch and maintain system reserves. Besides simulating generation fleet intra-hour dispatch, ESIOS can also be used as a test platform for the design and verification of energy storage, demand response, and other technologies helping to accommodate variable generation.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Python, Java" + ], + "name": "Electric System Intra-hour Operation Simulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Profile Interface Generator (PIG) is a tool for loosely coupling applications and performance tools. It enables applications to write code that looks like standard C and Fortran functions calls, without requiring that applications link to specific implementations of those function calls. Performance tools can register with PIG in order to listen to only the calls that give information they care about. This interface reduces the build and configuration burden on application developers and allows semantic instrumentation to live in production codes without interfering with production runs.", + "laborHours": 0.0, + "languages": [], + "name": "Profile Interface Generator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/profile-interface-generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "DAMPI is a dynamic testing/verification tool that scalably covers non-deterministic interactions of MPI (e.g., sildcard-receives).", + "laborHours": 0.0, + "languages": [], + "name": "The Dynamic Analyzer for MPI: the first dynamic analyzer of MPI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/the-dynamic-analyzer-for-mpi-the-first-dynamic-analyzer-of-mpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "LIQUID (Lipid Informed Quantitation and Identification) is a software program that has been developed to enable users to conduct both informed and high-throughput global liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based lipidomics analysis. This newly designed desktop application can quickly identify and quantify lipids from LC-MS/MS datasets while providing a friendly graphical user interface for users to fully explore the data. Informed data analysis simply involves the user specifying an electrospray ionization mode, lipid common name (i.e. PE(16:0/18:2)), and associated charge carrier. A stemplot of the isotopic profile and a line plot of the extracted ion chromatogram are also provided to show the MS-level evidence of the identified lipid. In addition to plots, other information such as intensity, mass measurement error, and elution time are also provided. Typically, a global analysis for 15,000 lipid targets.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Lipid Informed Quantitation and Identification", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Electrical resistivity tomography ERT is a method of imaging the electrical conductivity of the subsurface. Electrical conductivity is a useful metric for understanding the subsurface because it is governed by geomechanical and geochemical properties that drive subsurface systems. ERT works by injecting current into the subsurface across a pair of electrodes, and measuring the corresponding electrical potential response across another pair of electrodes. Many such measurements are strategically taken across an array of electrodes to produce an ERT data set. These data are then processed through a computationally demanding process known as inversion to produce an image of the subsurface conductivity structure that gave rise to the measurements. Data can be inverted to provide 2D images, 3D images, or in the case of time-lapse 3D imaging, 4D images. ERT is generally not well suited for environments with buried electrically conductive infrastructure such as pipes, tanks, or well casings, because these features tend to dominate and degrade ERT images. This reduces or eliminates the utility of ERT imaging where it would otherwise be highly useful for, for example, imaging fluid migration from leaking pipes, imaging soil contamination beneath leaking subsurface tanks, and monitoring contaminant migration in locations with dense network of metal cased monitoring wells. The location and dimension of buried metallic infrastructure is often known. If so, then the effects of the infrastructure can be explicitly modeled within the ERT imaging algorithm, and thereby removed from the corresponding ERT image. However, there are a number of obstacles limiting this application. 1) Metallic infrastructure cannot be accurately modeled with standard codes because of the large contrast in conductivity between the metal and host material. 2) Modeling infrastructure in true dimension requires the computational mesh to be highly refined near the metal inclusions, which increases computational demands. 3) The ERT imaging algorithm requires specialized modifications to accommodate high conductivity inclusions within the computational mesh. The solution to each of these challenges was implemented within E4D (formerly FERM3D), which is a parallel ERT imaging code developed at PNNL (IPID #30249). The infrastructure modeling module implement in E4D uses a method of decoupling the model at the metallic interface(s) boundaries, into several well posed sub-problems (one for each distinct metallic inclusion) that are subsequently solved and recombined to form the global solution. The approach is based on the immersed interface method, with has been applied for similar problems in other fields (e.g. semiconductor industry). Comparisons to analytic solutions have shown the results to be very accurate, addressing item 1 above. The solution is implemented about an unstructured mesh, which enables arbitrary shapes to be efficiently modelled, thereby addressing item 2 above. In addition, the algorithm is written in parallel and shows excellent scalability, which also addresses equation 2 above. Finally, because only the boundaries of metallic inclusions are modeled, there are no high conductivity cells within the modeling mesh, and the problem described by item 3 above is no longer applicable.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "gfortran/intel" + ], + "name": "Parallel Infrastructure Modeling and Inversion Module for E4D", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "This software code is designed to track generator state variables in real time using the Ensemble Kalman Filter method with the aid of PMU measurements. This code can also be used to calibrate dynamic model parameters by augmenting parameters in the state variable vector.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab" + ], + "name": "Grid State Estimation Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Designed for building energy managers, utilities and firms providing energy services, FEDS provides a comprehensive and user-friendly method for users to quickly and accurately identifying energy conversion and end-use technology improvements that offer maximum savings in energy usage and cost. FEDS enables the user to assess energy efficiency and consumption, identify retrofit opportunities, select minimum life cycle costs, determine payback, and prioritize investments in energy efficiency retrofit projects for multiple or single buildings across a particular site. As part of the life-cycle cost optimization it also considers several options for partial or complete abandonment of central energy plants including: individual technologies dropping off a thermal loop, a loop and all technologies dropping off a central plant, and all technologies and loops dropping off a central plant resulting in its complete abandonment. Improvements in release 7.0 include: FEDS 7.0 is now a full hourly simulation model (runs every hour of the year as opposed to the previous simplified hourly approach which ran 9 24-hour periods to represent each month). Enhanced building operation and occupancy modeling; New HVAC technology options (VAV, Economizers, Demand Controlled Ventilation, Terminal Reheat, Subcool Dehumidification); Additional chiller types; New lighting technologies (LED, Halogen, Induction, additional fluorescent options); Completely updated retrofit cost and performance data; Regional cost data tied to zip code (previously applied state level averages); Updated and enhanced reporting capabilities; and New pier floor model", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++, Microsoft Visual Studio" + ], + "name": "Facility Energy Decision System (FEDS) version 7.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "This work extends Biocellion 1.0 to solve advection-reaction-diffusion and incompressible Navier-Stokes partial differential equations to model water/blood flow. Biocellion is a software framework to simulate a large number of cells using high-performance parallel computers. The version 1.0 allows software users to describe biological system behaviors as a set of rules describing how individual cells behave and how cells locally interact with neighboring cells or the surrounding micro-environment. However, the version 1.0 does not support users to incorporate water/blood flow into the model, which is important to properly capture long distance communications between distant cells. This extension (version 2.0) integrates two partial differential equation solvers to the Biocellion framework to solve this limitation. Navier-Stokes equation solvers (for incompressible flow) are added to compute flow rate, and advection-reaction-diffusion equation solvers are added to update molecular concentrations considering both advection (due to flow) and local diffusion.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Biocellion Version 2.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "FELIX is a physics computer code used to model fission fragment mass distributions in a fully quantum-mechanical, microscopic framework that only relies on our current knowledge of nuclear forces. It is an implementation of the time-dependent generator coordinate method (TDGCM), which simulates the dynamics of a collective quantum wave-packet assuming the motion is adiabatic. In typical applications of the TDGCM, the nuclear collective wavepacket is obtained as a superposition of wavefunctions obtained by solving the Hartree-Fock-Bogoliubov equations of nuclear density functional theory (DFT). The program calculates at each time step the coefficients of that superposition.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Finite Element Solver for Fission Dynamics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/finite-element-solver-for-fission-dynamics", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Developed to solve specific problem: Assist transmission planning for regional transfers in interconnected power systems. This work was originated in a study for the U.S. Department of State, to recommend transmission reinforcements for the Central American regional system that interconnects 6 countries. Transmission planning analysis is currently performed by engineers with domain-specific and system-specific knowledge without a unique methodology. The software codes of this disclosure assists engineers by defining systematic analysis procedures to help identify weak points and make decisions on transmission planning of regional interconnected power systems. Transmission Planning Analysis Tool groups PSS/E results of multiple AC contingency analysis and voltage stability analysis and QV analysis of many scenarios of study and arrange them in a systematic way to aid power system planning engineers or transmission operators in effective decision-making process or in the offline study environment.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab/ 7.11.0" + ], + "name": "Transmission Planning Analysis Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "SWIFT is a computer code that is designed to do research level signal analysis on seismic waveforms, including visualization, filtering and measurement. LLNL is using this code, amplitude and global tomography efforts.", + "laborHours": 0.0, + "languages": [ + "JAVA 100%" + ], + "name": "Seismic waveform viewer, processor and calculator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/seismic-waveform-viewer-processor-and-calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The battery storage sizing tool developed at Pacific Northwest National Laboratory can be used to evaluate economic performance and determine the optimal size of battery storage in different use cases considering multiple power system applications. The considered use cases include i) utility owned battery storage, and ii) battery storage behind customer meter. The power system applications from energy storage include energy arbitrage, balancing services, T&D deferral, outage mitigation, demand charge reduction etc. Most of existing solutions consider only one or two grid services simultaneously, such as balancing service and energy arbitrage. ES-select developed by Sandia and KEMA is able to consider multiple grid services but it stacks the grid services based on priorities instead of co-optimization. This tool is the first one that provides a co-optimization for systematic and local grid services.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Optimal Sizing Tool for Battery Storage in Grid Applications", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2025-04-14" + }, + "description": "ABCD is a four-level hierarchy with human supervisors at the top, a top-level agent called a Sergeant controlling each enclave, Sentinel agents located at each monitored host, and mobile Sensor agents that swarm through the enclaves to detect cyber malice and misconfigurations. The code comprises four parts: (1) the core agent framework, (2) the user interface and visualization, (3) test-range software to create a network of virtual machines including a simulated Internet and user and host activity emulation scripts, and (4) a test harness to allow the safe running of adversarial code within the framework of monitored virtual machines.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 371898.4, + "languages": [ + "Python 2.6 or later" + ], + "name": "Ant-Based Cyber Defense", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Contingency analysis based approach for quantifying and examining the resiliency of a cyber system in respect to confidentiality, integrity and availability. A graph representing an organization's cyber system and related resources is used for the availability contingency analysis. The mission critical paths associated with an organization are used to determine the consequences of a potential contingency. A node (or combination of nodes) are removed from the graph to analyze a particular contingency. The value of all mission critical paths that are disrupted by that contingency are used to quantify its severity. A total severity score can be calculated based on the complete list of all these contingencies. A simple n1 analysis can be done in which only one node is removed at a time for the analysis. We can also compute nk analysis, where k is the number of nodes to simultaneously remove for analysis. A contingency risk score can also be computed, which takes the probability of the contingencies into account. In addition to availability, we can also quantify confidentiality and integrity scores for the system. These treat user accounts as potential contingencies. The amount (and type) of files that an account can read to is used to compute the confidentiality score. The amount (and type) of files that an account can write to is used to compute the integrity score. As with availability analysis, we can use this information to compute total severity scores in regards to confidentiality and integrity. We can also take probability into account to compute associated risk scores.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++11 QtCreator 5.3" + ], + "name": "Cyber Contingency Analysis version 1.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The battery storage evaluation tool developed at Pacific Northwest National Laboratory is used to run a one-year simulation to evaluate the benefits of battery storage for multiple grid applications, including energy arbitrage, balancing service, capacity value, distribution system equipment deferral, and outage mitigation. This tool is based on the optimal control strategies to capture multiple services from a single energy storage device. In this control strategy, at each hour, a lookahead optimization is first formulated and solved to determine the battery base operating point. The minute-by-minute simulation is then performed to simulate the actual battery operation.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab MCR" + ], + "name": "Battery Storage Evaluation Tool, version 1.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Look-ahead dynamic simulation software system incorporates the high performance parallel computing technologies, significantly reduces the solution time for each transient simulation case, and brings the dynamic simulation analysis into on-line applications to enable more transparency for better reliability and asset utilization. It takes the snapshot of the current power grid status, functions in parallel computing the system dynamic simulation, and outputs the transient response of the power system in real time.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Linux" + ], + "name": "Look-ahead Dynamic Simulation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Methodology that interpolates low time-resolution data (e.g., hourly) to high time-resolution (e.g., minutely) with variability patterns extracted from historical records. Magnitude of the variability inserted into the low time resolution data can be adjusted according to the installed capacity represented by the low time-resolution data compared to that by historical records. This approach enables detailed analysis of the impacts from wind and solar on power system intra-hour operations and balancing reserve requirements even with only hourly data. It also allows convenient creation of high resolution wind or solar generation data with various degree of variability to investigate their operational impacts. The methodology comprises of the following steps: 1. Smooth the historical data (set A) with an appropriate window length l to get its trend (set B); l can be a fraction of an hour (e.g., 15 minutes) or longer than an hour, of which the length of the variability patterns will be; 2. Extract the variable component (set C) of historical data by subtracting the smooth trend from it, i.e. set C = set A - set B 3. For each window length l of the variable component data set, find the average value x (will call it base component) of the corresponding window of the historical data set; 4. Define a series of segments (set D) that the values of data will be grouped into, e.g. (0, 0.1), (0.1, 0.2), ..., (0.9, 1.0) after normalization; Link each variability pattern to a data segment based on its corresponding base component x; after this step, each data segment should be linked to multiple variability patterns after this step; 5. Use spline function to interpolate the low time-resolution forecast data (set E) to become a high time-resolution smooth curve (set F); 6. Based on the window length l , calculate the average value y in each window length of set F; find the data segment that y belongs to; then randomly select one of the variability patterns linked to this data segment; 7. Add the selected variability pattern in each window to set F to get the high time-resolution data (set G) with variability observed from historical data set A; a coefficient k can be multiplied to the selected variability pattern to reflect the potential difference in variability between forecast set E and historical data set A caused by installation capacity and other factors. 8. After set G is constructed, variability statistics can be checked for set A and set G for comparison. Adjust the coefficient k if necessary to achieve desired variability in the reconstructed data.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Interpolating Low Time-Resolution Forecast Data", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Power system operation requires maintaining a continuous balance between system demand and generation within certain constraints. Traditionally, the balancing processes are based on deterministic models, which do not consider possible random deviations of system generation and load from their predicted values. With the increasing penetration of the renewable generation, unexpected balancing problems can happen due to the deviations. This can result in serious risks to system reliability and efficiency. When the available balancing reserve is not enough to cover the predicted net load range with uncertainty, deficiency of balancing needs occurs. In this case, it is necessary to commit or de-commit additional conventional generators to achieve the desired confidence level for the balancing needs. The framework is built for solving this problem. The ramping tool engine is used to predict additional balancing requirements caused by the variability and uncertainty of the renewable energy, under the constraints of the generation ramping capability and interchange schedule. The web browser- based GUI is used to visualize the data in web-environment, which provides flexibility to allow user to see the ramping outputs in any platform. The GOSS structure provides strong support to allow easy communication between ramping engine, and system inputs, as well as the GUI.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java 8.x" + ], + "name": "A Framework to Support Generator Ramping Uncertainty Analysis and Visualization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The STOMP simulator is a suite of numerical simulators developed by Pacific Northwest National Laboratory for addressing problems involving coupled multifluid hydrologic, thermal, geochemical, and geomechanical processes in the subsurface. The simulator has been applied to problems concerning environmental remediation, environmental stewardship, carbon sequestration, conventional petroleum production, and the production of unconventional hydrocarbon fuels. The simulator is copyrighted by Battelle Memorial Institute, and is available outside of PNNL via use agreements. To promote the open exchange of scientific ideas the simulator is provided as source code. A demonstration version of the simulator has been developed, which will provide potential new users with an executable (not source code) implementation of the software royalty free. Demonstration versions will be offered via the STOMP website for all currently available operational modes of the simulator. The demonstration versions of the simulator will be configured with the direct banded linear system solver and have a limit of 1,000 active grid cells. This will provide potential new users with an opportunity to apply the code to simple problems, including many of the STOMP short course problems, without having to pay a license fee. Users will be required to register on the STOMP website prior to receiving an executable.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Fortran 90" + ], + "name": "Subsurface Transport Over Multiple Phases Demonstration Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The software was created in the process of developing a system known as the Smart Monitoring and Diagnostic System (SMDS) for packaged air conditioners and heat pumps used on commercial buildings (known as RTUs). The SMDS provides automated remote monitoring and detection of performance degradation and faults in these RTUs and could increase the awareness by building owners and maintenance providers of the condition of the equipment, the cost of operating it in degraded condition, and the quality of maintenance and repair service when it is performed. The SMDS provides these capabilities and would enable conditioned-based maintenance rather than the reactive and schedule-based preventive maintenance commonly used today, when maintenance of RTUs is done at all. Improved maintenance would help ensure persistent peak operating efficiencies, reducing energy consumption by an estimated 10% to 30%.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C#, C++, PHP, JavaScript, MSSQL query, .NET" + ], + "name": "Methodology for Automated Detection of Degradation and Faults in Packaged Air Conditioners and Heat Pumps Using Only Two Sensors", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The PPMV is used to validate generator model using disturbance recordings. The PPMV tool contains a collection of power plant models and model validation studies, as well as disturbance recordings from a number of historic grid events. The user can import data from a new disturbance into the database, which converts PMU and SCADA data into GE PSLF format, and then run the tool to validate (or invalidate) the model for a specific power plant against its actual performance. The PNNL PPMV tool enables the automation of the process of power plant model validation using disturbance recordings. The tool uses PMU and SCADA measurements as input information. The tool automatically adjusts all required EPCL scripts and interacts with GE PSLF in the batch mode. The main tool features includes: The tool interacts with GE PSLF; The tool uses GE PSLF Play-In Function for generator model validation; Database of projects (model validation studies); Database of the historic events; Database of the power plant; The tool has advanced visualization capabilities; and the tool automatically generates reports.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "EPCL" + ], + "name": "Power Plant Model Validation Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "MultiSpeaker is a software application that parses wsdl and xsd files that define the MultiSpeak protocol. The MultiSpeak protocol (www.multispeak.org) is a SOA-based integration architecture that defines the complex communications between various endpoints of a utility company. MultiSpeaker parses the files and presents an easy to read and understand representation of the underlying protocol. The user may then use visual clues to know what message elements are required, descriptions for the elements along with valid entries. The user may then edit or modify the payload of the actual messages. MultiSpeaker also provides a mechanism for scheduling multiple modified protocol messages.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Qt" + ], + "name": "Multispeaker", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Fishes and marine mammals may suffer a range of potential effects from exposure to intense underwater sound generated by anthropogenic activities such as pile driving, shipping, sonars, and underwater blasting. Several underwater sound recording (USR) devices have been built to acquire samples of the underwater sound generated by anthropogenic activities. Software becomes indispensable for processing and analyzing the audio files recorded by these USRs. The new Aquatic Acoustic Metrics Interface Utility Software (AAMI) is specifically designed for analysis of underwater sound recordings to provide data in metrics that facilitate evaluation of the potential impacts of the sound on aquatic animals. In addition to the basic functions, such as loading and editing audio files recorded by USRs and batch processing of sound files, the software utilizes recording system calibration data to compute important parameters in physical units. The software also facilitates comparison of the noise sound sample metrics with biological measures such as audiograms of the sensitivity of aquatic animals to the sound, integrating various components into a single analytical frame.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab" + ], + "name": "Aquatic Acoustic Metrics Interface", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "SADE is a software package for rapidly assembling analytic pipelines to manipulate data. The packages consists of the engine that manages the data and coordinates the movement of data between the tasks performing a function, a set of core libraries consisting of plugins that perform common tasks, and a framework to extend the system supporting the development of new plugins. Currently through configuration files, a pipeline can be defined that maps the routing of data through a series of plugins. Pipelines can be run in a batch mode or can process streaming data; they can be executed from the command line or run through a Windows background service. There currently exists over a hundred plugins, over fifty pipeline configurations, and the software is now being used by about a half-dozen projects.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Windows.Net framework 4.5, C#" + ], + "name": "Streaming Analytics and Data Engineering", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "T.Rex is used to explore tabular data sets containing up to ten million records to help rapidly understand a previously unknown data set. Analysis can quickly identify patterns of interest and the records and fields that capture those patterns. T.Rex contains a growing set of deep analytical tools and supports robust export capabilities that selected data can be incorporated into to other specialized tools for further analysis. T.Rex is flexible in ingesting different types and formats of data, allowing the user to interactively experiment and perform trial and error guesses on the structure of the data; and also has a variety of linked visual analytic tools that enable exploration of the data to find relevant content, relationships among content, trends within the content, and capture knowledge about the content. Finally, T.Rex has a rich export capability, to extract relevant subsets of a larger data source, to further analyze their data in other analytic tools.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "T.Rex", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "CB-EMS is the latest implementation of DSOM (Decision Support for Operations and Maintenance), which was previously patented by PNNL. CB-EMS WAS specifically designed for contingency bases for the US Army. It is a software package that is designed to monitor energy consumption at an Army contingency base to alert the camp manager when the systems are wasting energy. It's main feature that separates it from DSOM is it's ability to add systems using a plug and play menu system.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Contingency Base Energy Management System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The Sensor Fish collects information that can be used to evaluate conditions encountered by juvenile salmonids and other fish as they pass through hydroelectric dams on their way to the ocean. Sensor Fish are deployed in turbines, spillways, and sluiceways and measure changes in pressure, angular rate of change, and linear acceleration during passage. The software is need to make Sensor Fish fully functional and easy to use. Sensor Fish Communicator (SFC) links to Sensor Fish, allowing users to control data collection settings and download data. It may also be used to convert native raw data (.raw2) files into Comma Separated Variable (.csv) files and plot the results. The multiple capabilities of the SFC allow hardware communication, data conversion, and data plotting with one application.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "c++" + ], + "name": "Sensor Fish Communicator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The algorithm develops a single health score for office computers, today just Windows, but we plan to extend this to Apple computers. The score is derived from various parameters, including: CPU Utilization; Memory Utilization; Various Error logs; Disk Problems; and Disk write queue length. It then uses a weighting scheme to balance these parameters and provide an overall health score. By using these parameters, we are not just assessing the theoretical performance of the components of the computer, rather we are using actual performance metrics that are selected to be a more realistic representation of the experience of the person using the computer. This includes compensating for the nature of their use. If there are two identical computers and the user of one places heavy demands on their computer compared with the user of the second computer, the former will have a lower health score. This allows us to provide a 'fit for purpose' score tailored to the assigned user. This is very helpful data to inform the mangers when individual computers need to be replaced. Additionally it provides specific information that can facilitate the fixing of the computer, to extend it's useful lifetime. This presents direct financial savings, time savings for users transferring from one computer to the next, and better environmental stewardship.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Multiple" + ], + "name": "Computer Health Score", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The embodiment of this work is a table top game to explore cyber security and network defense concepts and cost. The game structure is such that it provides players an immersive environment to play a given role in cyber security to investigate the result of infrastructure and response decisions.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "The Defender's Role in Cyber Security", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The Xenon International Automated Control software monitors, displays status, and allows for manual operator control as well as fully automatic control of multiple commercial and PNNL designed hardware components to generate and transmit atmospheric radioxenon concentration measurements every six hours.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "gcc-c++" + ], + "name": "Xenon International Automated Control", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Representation learning is a deep-learning based technique for extracting features from data for the purpose of machine learning. This requires a large amount of data, on order tens of thousands to millions of samples, to properly teach the deep neural network. This a system for continuous representation learning, where the system may be improved with a small number of additional samples (order 10-100). The unique characteristics of this invention include a human-computer feedback component, where assess the quality of the current representation and then provides a better representation to the system. The system then mixes the new data with old training examples to avoid overfitting and improve overall performance of the system. The model can be exported and shared with other users, and it may be applied to additional images the system hasn't seen before.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "multi" + ], + "name": "Continous Representation Learning via User Feedback", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The ECE application forecasts annual costs of preventive and corrective maintenance for budgeting purposes. Features within the application enable the user to change the specifications of the model to customize your forecast to best fit their needs and support “what if” analysis. Based on the user's selections, the ECE model forecasts annual maintenance costs. Preventive maintenance costs include the cost of labor to perform preventive maintenance activities at the specific frequency and labor rate. Corrective maintenance costs include the cost of labor and the cost of replacement parts. The application presents forecasted maintenance costs for the next five years in two tables: costs by year and costs by site.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++, other" + ], + "name": "Equipment Cost Estimator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "A robust three-dimensional solver was needed to accurately and efficiently estimate the time sequence of locations of fish tagged with acoustic transmitters and vocalizing marine mammals to describe in sufficient detail the information needed to assess the function of dam-passage design alternatives and support Marine Renewable Energy. An approximate maximum likelihood solver was developed using measurements of time difference of arrival from all hydrophones in receiving arrays on which a transmission was detected. Field experiments demonstrated that the developed solver performed significantly better in tracking efficiency and accuracy than other solvers described in the literature.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "A 3D approximate maximum likelihood localization solver", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "If transmission path ratings are determined in real time and optimized control methods can be implemented, congestion problems can be more effectively managed using the existing transmission assets, reducing congestion costs, avoiding capital expenditures for new physical assets, increasing revenues from the existing system, and maintaining reliability. In just one illustrative case, a BPA study has shown that a 1000-MW rating increase for a transmission path generates $15M in annual revenue, even if only 25% of the increased margin can be tapped for just 25% of the year.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "multi" + ], + "name": "A real-time path rating calculation tool powered by HPC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The Retrocommissioning Sensor Suitcase is targeted for use in small commercial buildings of less than 50,000 square feet of floor space that regularly receive basic services such as maintenance and repair, but don't have in-house energy management staff or buildings experts. The Suitcase is designed to be easy-to-use by building maintenance staff, or other professionals such as telecom and alarm technicians. The software in the hand-held is designed to guide the staff to input the building and system information, deploy the sensors in proper location, configure the sensor hardware, and start the data collection.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "MS" + ], + "name": "Sensor Suitcase Tablet Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "This software is a set of analytical tools to evaluate the physical and biological performance of existing, refurbished, or newly installed conventional hydro-turbines nationwide where fish passage is a regulatory concern. The current version is based on information collected by the Sensor Fish. Future version will include other technologies. The tool set includes data acquisition, data processing, and biological response tools with applications to various turbine designs and other passage alternatives. The associated database is centralized, and can be accessed remotely. We have demonstrated its use for various applications including both turbines and spillways.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "MS" + ], + "name": "Hydropower Biological Evaluation Tools", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Incorporation of real-time component information using equipment condition assessment (ECA) through the development of enhanced risk monitors (ERM) for active components in advanced reactor (AR) and advanced small modular reactor (SMR) designs. We incorporate time-dependent failure probabilities from prognostic health management (PHM) systems to dynamically update the risk metric of interest. This information is used to augment data used for supervisory control and plant-wide coordination of multiple modules by providing the incremental risk incurred due to aging and demands placed on components that support mission requirements.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "MS" + ], + "name": "Methodology for Risk-informed O&M decision making in power plants", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Developed for the Midcontinent Independent System Operator, Inc. (MISO), HIPPO-Unit Commitment Version 1 is for solving security constrained unit commitment problem. The model was developed to solve MISO's cases. This version of codes includes I/O module to read in MISO's csv files, modules to create a state-based mixed integer programming formulation for solving MIP, and modules to test basic procedures to solve MIP via HPC.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Python 2.7.7" + ], + "name": "HIPPO Unit Commitment Version 1", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "CyPSA seeks to organize and gain insight into the diverse sets of data that a critical infrastructure provider must manage. Specifically CyPSA inventories, manages, and analyzes assets and relations among those assets. A variety of interfaces are provided. CyPSA inventories assets (both cyber and physical). This may include the cataloging of assets through a common interface. Data sources used to generate a catalogue of assets include PowerWorld, NPView, NMap Scans, and device configurations. Depending upon the role of the person using the tool the types of assets accessed as well as the data sources through which asset information is accessed may vary. CyPSA allows practitioners to catalogue relations among assets and these may either be manually or programmatically generated. For example, some common relations among assets include the following: Topological Network Data: Which devices and assets are connected and how? Data sources for this kind of information include NMap scans, NPView topologies (via Firewall rule analysis). Security Metrics Outputs: The output of various security metrics such as overall exposure. Configure Assets:CyPSA may eventually include the ability to configure assets including relays and switches. For example, a system administrator would be able to configure and alter the state of a relay via the CyPSA interface. Annotate Assets: CyPSA also allows practitioners to manually and programmatically annotate assets. Sources of information with which to annotate assets include provenance metadata regarding the data source from which the asset was loaded, vulnerability information from vulnerability databases, configuration information, and the output of an analysis in general.", + "laborHours": 0.0, + "languages": [ + "Java, Python" + ], + "name": "Cyber-Physical Security Assessment (CyPSA) Toolset", + "organization": "USDOE Advanced Research Projects Agency – Energy (ARPA-E) (United States) (ARPA-E)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/bigezy/Armadillo/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bigezy/Armadillo", + "status": "Production", + "tags": [ + "DOE CODE", + "USDOE Advanced Research Projects Agency – Energy (ARPA-E) (United States) (ARPA-E)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Software that runs on smartphones and desktop web browsers and notifies border officials of radiation alarms. It displays images and data associated with an alarm and provides a variety of reports. DOE had a need for discrete notification. PAS replaces the lights and sounds of a Radiation Portal Monitor.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Personal Alarm System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "MOFA-COBRA is a software code for Matlab that performs Multi-Objective Flux Analysis (MOFA), a solving of linear programming problems. The leading software package for conducting different types of analyses using constrain-based models is the COBRA Toolbox for Matlab. MOFA-COBRA is an added tool for COBRA that solves multi-objective problems using a novel algorithm.", + "laborHours": 0.0, + "languages": [ + "Matlab (100%)" + ], + "name": "MOFA Software for the COBRA Toolbox", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/mofa-software-for-the-cobra-toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2024-07-19" + }, + "description": "EPOXY is a LLVM base compiler that applies security protections to bare-metal programs on ARM Cortex-M series micro-controllers. This includes privilege overlaying, wherein operations requiring privileged execution are identified and only these operations execute in privileged mode. It also applies code integrity, control-flow hijacking defenses, stack protections, and fine-grained randomization schemes. All of its protections work within the constraints of bare-metal systems.", + "laborHours": 263081.6, + "languages": [ + "C++", + "HTML", + "C", + "Makefile", + "Assembly", + "Rich Text Format" + ], + "name": "EPOXY", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/EPOXY?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/EPOXY", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2025-04-14" + }, + "description": "Few works exist that attempt to build predictive models for tweet deletion. Zhou et al. (2015) focus on a subset of deleted tweets – regrettable tweets. These are tweets that the authors believe to contain inappropriate content. Inappropriate can range from vulgar language to sharing private content such as a personal email address. The presence of inappropriate content doesn’t guarantee that a tweet will be deleted, however intuition dictates it can be in an important factor in the tweet being deleted. In their work, the authors create a predictive model for identifying regrettable tweets. It is important to note the authors focus on predicting regrettable tweets that are distinctly not spam and only written in English. Through manual investigation, the authors identify ten major topics including negative sentiment, cursing, and relationships that are prevalent in regrettable tweets. The authors then exploit WordNet and UrbanDictionary to create keyword lists related to the ten topics. Finally, using a combination of existing lexica and the topic keywords as features, the authors build classifiers to test the accuracy of their model. The authors complement 700 manually labeled regrettable tweets with 700 normal tweets to create their evaluation dataset. 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Rucio has been originally developed to meet the requirements of the high-energy physics experiment ATLAS, and is continuously extended to support LHC experiments and other diverse scientific communities.", + "laborHours": 0.0, + "languages": [], + "name": "Rucio - Scientific Data Management", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/rucio", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "UC Santa Cruz Head and Neck.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/ucsc-hn", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/ucsc-hn/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ucsc-hn", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "This Ansible role allows you to install chrony and manage its configuration.", + "laborHours": 0.0, + "languages": [], + "name": "Ansible Role: chrony", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ansible-role-chrony", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "Gafaelfawr is a FastAPI application for the authorization and management of tokens, including their issuance and revocation.", + "laborHours": 0.0, + "languages": [], + "name": "Gafaelfawr", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/gafaelfawr", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This invention is a Ruby \"gem\" (library) that provides clients for ENERGY STAR Portfolio Manager (ESPM) Web Services,\nInventive features:\n100% coverage of version 18.0 of the ESPM API.\nAutomated mapping between ESPM XML schemas and Ruby objects.\nClients for both the \"live\" and \"test\" ESPM API environments.\nDebugging mode with HTTP request/response logging.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/portfoliomanager-rb", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/portfoliomanager-rb", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Simple Building Calculator is a web application that estimates annual energy\nuse using regression models that have been fit to simulation results for the DOE\nCommercial Prototype Building Models. The tool is a single-page application that\nwill allow a user to rapidly analyze the impact of energy efficiency measures and\ndesign options on building performance. As it uses linear regression models rather\nthan more complicated machine learning models or physics based simulation, the\ntool can deploy easily and run client-side.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/simple-building-calculator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/simple-building-calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Performance curve generator for building energy simulation. Copper is a tool in the form of Python package that can be used to generate metric specific performance curves for\nbuilding energy simulations.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/copper", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/copper", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "This is a standalone Fortran code (mie_scat) that calculates the mie scattering cross sections, absorption cross sections, and efficiency coefficients of dust grains. It includes a separate file (miegrn) that functions as a wrapper function between PHOENIX (a proprietary radiative transfer code to model stellar atmospheres) and the mie scattering calculations. Miegrn works to determine the input parameters for mie_scat and then feeds the resultant data back into PHOENIX.", + "laborHours": 0.0, + "languages": [], + "name": "mie_scat", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/mie_scat", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "Computes the atomic positions in cleaved crystal lattices. The current version of the code allows to cleave the lattices with different planes that are readily available. The cleavages can be performed on any type of lattices. The code constructs a slab that can be used to study surface properties.", + "laborHours": 0.0, + "languages": [], + "name": "LANL Crystal Cut (LCC)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/LCC", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "Protective vaccines and reliable diagnostics are essential tools for controlling viral diseases. However, the efficacy of these tools can be diminished by mutations in viral genomes. The delay between the emergence of new viral strains and the redesign of vaccines and diagnostics allows for continued viral transmission. Is it possible to address this challenge by computationally predicting viral genome sequence evolution? Can we “future-proof” vaccines and diagnostics by targeting both current and anticipated future sequence variants? While predicting viral evolution is still an unsolved, “grand challenge” problem in biology, the large, and rapidly growing, number of SARS-CoV-2 genome sequences provide an opportunity to quantify the ability of machine learning to predict viral genome sequence evolution. Towards this end, we have developed a simple computational model for predicting viral evolution at the level of individual nucleotides. The key metric for quantifying the per-base, prediction accuracy for viral evolution is the Mann-Whitney U statistic (or, equivalently, the area under the receiver operator curve). Since the Mann-Whitney U statistic is not a differentiable function, existing deep leaning packages (like Pytorch and Keras/TensorFlow) are not useful, as they require that the accuracy metric/objective function be analytically differentiable with respect to the model parameters. To overcome this challenge, we have implemented custom software, “FutureTense”, that can train a machine learning model by maximizing the non-differentiable Mann-Whitney U statistic. This software trains a machine learning model by exploring along the direction of the discrete gradient of the Mann-Whitney U statistic in the model parameter space. Parallel computing and genome sequence-specific optimizations are used to accelerate model training. The resulting machine learning model learns the observed high C->U mutation rates in the SARS-CoV-2 genome (which are potentially induced by host defenses) and provides prediction accuracies that are significantly better than one would expect from random chance. While predicting viral evolution is still quite far from a solved problem, the surprising performance of this simple model gives hope that the accuracy of predicting viral genome evolution can be further increased by more sophisticated approaches.", + "laborHours": 0.0, + "languages": [], + "name": "FutureTense", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/FutureTense", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "Carbon fluxes in terrestrial ecosystems and their response to environmental change are a major source of uncertainty in the modern carbon cycle. The National Ecological Observatory Network (NEON) presents the opportunity to merge eddy covariance (EC)-derived fluxes with CO2 isotope ratio measurements to gain insights into carbon cycle processes. Collected continuously and consistently across >40 sites, NEON EC and isotope data facilitate novel integrative analyses. However, currently provisioned atmospheric isotope data are uncalibrated, greatly limiting ability to perform cross-site analyses. Here, we present two approaches to calibrating NEON CO2 isotope ratios, along with an R package to calibrate NEON data. We find that calibrating CO2 isotopologues independently yields a lower d13C bias (<0.05‰) and higher precision (<0.40‰) than directly correcting d13C with linear regression (bias: <0.11‰, precision: 0.42‰), but with slightly higher error and lower precision in calibrated CO2 mole fraction. The magnitude of the corrections to d13C and CO2 mole fractions vary substantially by site, underscoring the need for users to apply a consistent calibration framework to data in the NEON archive. Post-calibration data sets show that site mean annual d13C correlates negatively with precipitation, temperature, and aridity, but positively with elevation. Forested and agricultural ecosystems exhibit larger gradients in CO2 and d13C than other sites, particularly during the summer and at night. The overview and analysis tools developed here will facilitate cross-site analysis using NEON data, provide a model for other continental-scale observational networks, and enable new advances leveraging the isotope ratios of specific carbon fluxes.", + "laborHours": 0.0, + "languages": [], + "name": "NEONiso R Package, versions greater than 0.5.2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/NEONiso", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "WORM (Write One, Run Many) is an easy to use, cross platform, embedded and extensible, functional programming language designed to facilitate the creation of input-decks for computer codes that use standard ASCII text files for input. WORM makes it easy to create generic (yet, complex and powerful) reusable models. Additionally its nature allows for complex calculations and routines to be coded once and easily reused, further simplifying the creation of input decks. WORM (Write One, Run Many) is a powerful and versatile tool designed to improve the efficiency of today’s criticality safety analyst by allowing: + input decks for parametric studies to be created quickly and easily, + calculations and variables to be imbedded into any input deck, thus allowing for meaningful parameter specifications, + problems to be specified using any combination of units, and + complex mathematically defined models to be created. A very simple syntax is employed, and therefore the WORM is easy to learn. A WORM model is essentially a standard input deck with some of its numerical values replaced by WORM code. WORM code may include and evaluate the following mathematical operators and functions: addition, subtraction, multiplication, division, exponentiation, modulus, sine, cosine, tangent, arcsine, arccosine, arctangent, the natural logarithm, logarithm base 10, integer truncation, absolute value, and random number. Several common constants, e.g., pi, e, and Avogadros’s Number (both as 6.022e23 and 0.6022), are predefined in WORM. Additionally, many unit conversion factors are also predefined: millimeters, meters, inches, feet, yards, and mils to centimeters; kilograms, pounds, and ounces to grams; liters, milliliters, gallons, and fluid ounces to cubic centimeters; and angular degrees to radians. For parametric studies, WORM supports various shorthand list specifications: the explicit step size, linear interpolation, and logarithmic interpolation. The list notation sequentially assigns multiple values to a name. WORM creates an input deck for each value of the name. If multiple lists are used, WORM steps through each list individually, i.e., WORM creates input decks corresponding to each and every permutation of the list values. Additionally, a library of standard material definitions and Perl subroutines are included. Any one of these files can be incorporated into the subject model with a simple WORM read command. WORM is completely written in Perl, the Practical Extraction and Reporting Language. Perl is one of the most portable programming languages available today. As such, the WORM works on practically any computer platform.", + "laborHours": 0.0, + "languages": [], + "name": "WORM (Write One, Read Many)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rsartor-lanl/worm-1.7.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "The Department of Energy and the National Cancer Institute have developed new software for conducting multi-scale simulations of complex systems. This software, called the Multiscale Machine-Learned Modeling Infrastructure (MuMMI), couples simulations on three spatial scales to study slow, large-scale reorganizations of biomolecular systems with the speed of continuum and coarse-grained models while revealing selected interactions at full atomic precision. In these simulations, coarse-to-fine model conversions are used to spawn relevant fine-scale simulations along chosen order parameters, and fine-to-coarse feedback is used to iteratively improve the accuracy and multi-scale consistency of coarse-scale and continuum simulations. The complete MuMMI framework will be reviewed and released as open-source software by Lawrence Livermore National Laboratory. This review covers a subset of the MuMMI components that were developed exclusively at the Los Alamos National Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "components for the MuMMI software release", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cneale-LANL/MuMMI-C21095", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "New diagnostics to obtain high-temporal resolution observation of surface velocity provide a rich collection of data from high-explosive (HE) experiments. Using this data to estimate the temporal evolution of an imploding, HE-driven surface is of great interest for validating simulation of the physical system and for design of future experiments. This is the code for a paper in which we propose a method for using a Gaussian process to estimate the surface position over time and provide uncertainty estimates on that reconstruction accounting for measurement error, uncertainty to sparse spatial sampling velocity data, and robustness to outlying observations. In the paper, the code is applied on data from a hemispherical HE implosion experiment. This code is for release with the paper for peer-review, replicating the results and making the figures from the paper.", + "laborHours": 0.0, + "languages": [], + "name": "Code for paper \"Reconstructing an Implosion with Space-Time Smoothing of Velocimetry Traces\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PDV_Reconstruction", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "The BPP package contains R code to perform Bayesian projection pursuit regression under various regression settings. Bayesian projection pursuit regression learns the functional relationship between inputs and outputs by considering a sum of functions of one dimensional projections of the inputs. This is useful as a general machine learning software.", + "laborHours": 0.0, + "languages": [], + "name": "BPP R package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gqcollins/BayesPPR", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dixitmb@ornl.gov" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2022-08-02" + }, + "description": "SolidPAC: Solid-State Battery Performance Analyzer and Calculator SolidPAC is an interactive experimental toolkit developed at Oak Ridge National Laboratory to enable the design of a solid-state battery for user-specified application requirements. The toolkit is flexible enough to assist the battery community in quantifying the impact of materials chemistry and fractions, electrode thicknesses and loadings, and electron flows on cell energy density and cost, and to be able to utilize inverse engineering concepts to correlate cell energy density output to materials and cell design inputs. The toolkit allows users to assess and extrapolate the impact of battery design and choice of cell components on cell-level energy density of a solid-state battery. SolidPAC brings practicality to the design of solid-state batteries.", + "homepageURL": "https://www.ornl.gov/content/solidpac", + "laborHours": 0.0, + "languages": [ + "LabVIEW" + ], + "name": "SolidPAC", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.ornl.gov/content/solidpac", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SAND2020-14229 O This software builds on an open source Kinetic Monte Carlo library to evaluate the incorporation rate of semiconductor dopant atoms in an Atomic Precision Advanced Manufacturing (APAM) process. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525", + "laborHours": 6779.2, + "languages": [ + "Python" + ], + "name": "Kinetic Monte Carlo for semiconductor surface science v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/apam-kmc", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2022-08-02" + }, + "description": "Source control and documentation for epix-hr-2M-10k.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/epix-hr-2M-10k", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/epix-hr-2M-10k/blob/main/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/epix-hr-2M-10k", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2022-08-02" + }, + "description": "SAND2020-14119 O A Tensorflow and Keras-backed framework for learned segmentation methods of 3D CT scan volumes. Supported functionality includes training models, running inference and quantifying uncertainty. The main underlying model architecture is V-Net. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Keras CT Segmentation v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mcdn-3d-seg", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": ".1" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2022-08-02" + }, + "description": "This is a supermodule to build, test, bundle and deploy all Java/Maven modules of the EPICS Core Libraries. 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For details on the approach please see our paper, and when referencing this code please cite our paper: Bridges, Robert A., Sean Oesch, Miki E. Verma, Michael D. Iannacone, Kelly MT Huffer, Brian Jewell, Jeff A. Nichols et al. \"Beyond the Hype: A Real-World Evaluation of the Impact and Cost of Machine Learning-Based Malware Detection.\" arXiv preprint arXiv:2012.09214 (2022). @misc{bridges2022beyond, doi = {10.48550/ARXIV.2012.09214}, url = {https://arxiv.org/abs/2012.09214}, author = {Bridges, Robert A. and Oesch, Sean and Verma, Miki E. and Iannacone, Michael D. and Huffer, Kelly M. T. and Jewell, Brian and Nichols, Jeff A. and Weber, Brian and Beaver, Justin M. and Smith, Jared M. and Scofield, Daniel and Miles, Craig and Plummer, Thomas and Daniell, Mark and Tall, Anne M.}, title = {Beyond the Hype: A Real-World Evaluation of the Impact and Cost of Machine Learning-Based Malware Detection}, publisher = {arXiv}, year = {2022}, } Repository contents: readme.md fake-data-table.csv This is a table of simulated data from two malware detectors, with randomly generated results suitable for running the cost model code as an example. config.py - provides global variables with input parameters needed for the cost model. model.py - provides the functions needed to run the cost model with examples on the fake data and three simulated detectors. Includes the complementary cost model--computes savings/costs of adding a network detector to a host detector. make_plots.py - shows example plots varying parameters. plots/ # contents populated by ./code/make_plots.py", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Beyond The Hype paper code", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bridgesra/beyond-the-hype-paper-code/releases/tag/tag", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "pi" + }, + { + "contact": { + "email": "bridgesra@ornl.gov" + }, + "date": { + "created": "2022-08-22", + "metadataLastUpdated": "2022-08-23" + }, + "description": "Contains anonymized and obfuscated data from the SOAR (AI ATAC 3) user study and code to produce correlation plots. The experiment, data, and our results are found in our paper https://arxiv.org/abs/2208.06075. Please cite our paper when using this data or code. @article{bridges2022testing, title={Testing SOAR Tools in Use}, author={Bridges, Robert A and Rice, Ashley E and Oesch, Sean and Nichols, Jeff A and Watson, Cory and Spakes, Kevin and Norem, Savannah and Huettel, Mike and Jewell, Brian and Weber, Brian and others}, journal={arXiv preprint arXiv:2208.06075}, year={2022} } file: anonymized_obfuscated_data.csv The data in this table is not the \"raw\" data. It has been user- and SOAR-tool anonymized; SOAR tool names have been removed, as have participant user ids. Probabilistic techniques to obfuscate the data by adding noise while retaining its characteristics have been performed. To ensure utility of the anonymized data, we provide code to reproduce the Subcategory Average Correlation heatmap, found in the publication. While the SOAR tool names have been removed, a binary indicator for if the test data per row is from a SOAR tool or from a baseline environment (full SOC tool suite but no SOAR tool). The likert columns correspond to questions posed to the users (participants) during and after working investigations with a SOAR tool or in a baseline environment (full SOC tool stack but with no SOAR tool). Sentiment columns correspond to answers given by analysts to free response questions. Transcriptions of their responses are quantified with sentiment analysis. The ticket columns report quality and completion of tickets from the test investigations based on percent of correctness according to a gold standard (rubric). The window swapping and time columns report the number of times the participant changed windows in an investigation (quantifying context switching), and the duration of the investigation (quantifying efficiency), respectively. User identification information has been removed. There are four columns of user/participant demographics documenting their familiarity with SOAR tools, job role (SOC analyst or other), number of years working in their security-related job role, and the number of different security operation centers (SOCs) they have supported. These have all been converted to binary variables. 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This software can be applied to non-reacting solids dominant flows in silos, hoppers and screw conveyors as well as in high temperature reacting systems such as screw kilns and auger reactors.", + "laborHours": 0.0, + "languages": [ + "C++", + "C", + "Python" + ], + "name": "BDEM (Discrete-element-simulator for high-solids granular flows) [SWR-22-72]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BDEM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-08-24", + "metadataLastUpdated": "2023-04-24" + }, + "description": "The well-known Fresnel equations solve for the reflection and transmission of light for precise incident angles. 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Ocelot is written in Python. 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PyTREES is designed to input LIBS data in the format provided by the ChemCam team [1]. PyTREES then applies appropriate pre-processing to this data [2], and implements several regression methods for predicting oxides from spectra. The regression methods include: ensemble methods (random forest, extra trees, and gradient boosting regression) and blended submodels using the “double blending” technique. PyTREES additionally implements methods for quantifying the importance of features in regression model: (1) mean decrease in impurity (MDI) and (2) permutation importance to investigate the wavelengths used by the regression methods. [1] Gasda et al. (2021). Spectrochim Acta B, 181, 106223. [2] Clegg et al. (2017). Spectrochim Acta B , 129, 64–85.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "PyTREES", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-09-15", + "metadataLastUpdated": "2022-09-19" + }, + "description": "VelocityGAN is a software to solve subsurface imaging problems. 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It implements an efficient data processing conveyor allowing to overlap all data transfers with computations. First, independent Python threads are started for reading data chunks from the hard disk into a Python data queue and for writing reconstructed chunks from the Python queue to the hard disk. 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The software utilizes machine learning and includes a graphical user interface to enable rapid prototyping and to accelerate energy storage research, development, and manufacturing. The Cylindrical battery design V1.0 comprises of three types of cylindrical batteries, Microbattery (Primary), Microbattery (Secondary) and 18650/21700/xxxxx Cylindrical battery. The software was developed in MATLAB. The software has the capability to output the cell design with the capacity ranges from several mAh to several million Ah.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Cylindrical battery design app", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-10-06" + }, + "description": "A model structure to support representation of power system dispatching for optimal power flow that includes bid-in demands for load. Used to support the ARPA-E GO-3 competition.", + "laborHours": 0.0, + "languages": [ + "Python", + "TeX" + ], + "name": "Bid-DS-data-model (Demand Side Bidding Data Model) [SWR-22-80]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Smart-DS/Bid-DS-data-model", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.0.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "The consolidated code is deployed in an embedded GPU System (Jetson AGX Xavier Developer Kit), performs inference on the pVA stream sent from the X-ray detector. The inferred output is sent back to the local detector machine as a PVA stream and can be viewed in an ImageJ viewer.", + "laborHours": 0.0, + "languages": [], + "name": "REAL-TIME EDGE INFERENCE FOR PTYCHOGRAPHIC NANOSCALE XRAY IMAGING", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/vbanakha/edgePtychoNN", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "Argonne National Laboratory has worked on electrochemical energy storage for several decades. The focus on lithium-ion chemistries started in the early 1990s, developing new materials, synthesis methods, and performance characterizations. Sponsored by the U.S. Department of Energy, Energy Efficiency and Renewable Energy, Vehicle Technologies Office (DOE-EERE-VTO), Argonne has led with many advances. The experimental activities were complemented with multi-scale modeling that ranged from the atomic to the system (manufacturing processes and automobiles) level. The Battery Performance and Cost (BatPaC) model is a calculation method based on Microsoft¿ Office Excel spreadsheets that have been developed at Argonne for estimating the performance and manufacturing cost of lithium-ion batteries for electric-drive vehicles including hybrid-electrics (HEV), plug-in hybrids (PHEV) and pure electrics. The effort is being funded by the Vehicle Technology Office (VTO), which is part of the Energy Efficiency and Renewable Energy (EERE) office of the U.S. Department of Energy (USDOE). BatPaC was first developed in 2007, was subsequently peer-reviewed, and it has served Argonne researchers and the greater battery community in studying the impact of material properties on performance at the pack level. With further developments, the model now allows the design of cells and battery packs for automotive applications, to meet performance requirements (power, energy, recharge time), and estimates the cost of manufacturing the designed batteries. Since the cost depends on the materials he design, and the manufacturing process, this bottom-up model/tool enables the user to study their effects. Designed or the lithium-ion cell and battery researcher, BatPaC helps answer many questions by being 1.Transparent in the assumptions made and the method of calculation 2.Capable of designing a battery specifically for the requirements of an application 3.Constrained by the physical limitations that govern battery performance 4. A bottom-up calculation approach to account for every cost factors. BatPaC predicts the impact of promising materials (and their properties) on the performance metrics relevant for the different applications. Researchers can use the specific capacities and the half-cell voltages of a particular set of electrode materials to calculate the mass and volume of a cell to develop a model incorporating the properties of all the other materials in the cell and the design of the cell enclosure. These calculations not only reveal the impact of an improved material but also enable researchers to calculate the material properties that would be needed to meet the performance criteria of a full battery pack. With this information, researchers can provide he battery industry with realistic expectations that will help it more successfully advance novel battery technologies an Applications.", + "homepageURL": "https://www.anl.gov/cse/batpac-model-software", + "laborHours": 0.0, + "languages": [], + "name": "BATPAC--VERSION 5.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/cse/batpac-model-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2023-03-15" + }, + "description": "A-LEAF is an electricity market simulation framework. It includes models for short-term market operations and long-term investment planning of generation, storage, and transmission. Model formulations include least cost and two-stage market equilibrium. Simulations can be flexibly structured over one or more years, including options for periodic samples or jumping to a single future year. Years can be simulated as 365 consecutive days at hourly or 5-minute sample rates, or they can be subsampled using a representative day group selection algorithm.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "A-LEAF", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "pycreep is a Python software package for modeling and correlating time-dependent material data like the results of creep rupture and creep deformation tests. The package provides a means to generate models for these test data which can be used to determine design material properties, like those used in the ASME Boiler and Pressure Vessel Code.", + "laborHours": 0.0, + "languages": [], + "name": "PYCREEP", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/pycreep", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "The \"X-RAY DETECTOR GAIN MAP CALCULATION\" was developed by Argonne National Laboratory.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "X-RAY DETECTOR GAIN MAP CALCULATION", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "This software organizes the collection of information necessary to evaluate heat stress and compare it to the exposure limits of the American Conference of Industrial Hygienists.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "HEAT STRESS TIME WEIGHTED AVERAGE CALCULATOR", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-23" + }, + "description": "BatchScan provides an interactive graphical user interface (GUI) that allows visualization of X-ray microscopic data,\nselection of scan coordinates, and execution of desired scan coordinates in a single software package. In addition to the\nthree primary functionalities, BatchScan also maintains an active list of scans that users inserted and updates lifetime\nfeedback on scan status.\n", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "BATCHSCAN", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-23" + }, + "description": "A suite of tools for efficient maximum likelihood optimization of parametric Gaussian process models", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "gpmaxlik.jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "This is a prototype framework initially developed as part of an international consortium (aica-iwg.org/) for NATO ACT in 2021 under an LGPL license (Blakely/ANL did 100% of the coding). It is intended to serve as a reference model and collaborative project for researchers interested in working on self-defending software agents. It consists of a set of Docker containers that allow simulation of a network environment, including a manager agent that has capabilities for observing network activities, using automated decision making to select appropriate defensive/proactive actions, and putting those actions into practice. It is currently at an \"MVP\" level but we are continuing to add to this and have submitted a DHS S&T CAP proposal to build an open source community around it.", + "laborHours": 0.0, + "languages": [], + "name": "AUTONOMOUS INTELLIGENCE CYBERDEFENSE AGENT (AICA)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aica-iwg/aica-agent", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2023-03-16" + }, + "description": "A generic simulation tool for power grid and general dynamic systems based on semi-analytical solutions (SAS) technology.", + "laborHours": 0.0, + "languages": [], + "name": "Generic Semi-Analytical Simulation Tool (GenSAS)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-CEEESA/gensas", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2023-03-14" + }, + "description": "ParMOO is a Python library for solving multiobjective simulation optimization problems, while exploiting problem structure. ParMOO stands for \"parallel multiobjective optimization\".", + "laborHours": 0.0, + "languages": [], + "name": "PARMOO", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/parmoo/parmoo", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "This program was developed to calculate rovibrational levels by solving n-dimensional potentials. The program is capable of generating the necessary grid and, once the potential energy for those coordinates has been calculated, solving it for the given dimensionality. The potential is solved using the universal Discrete Variable Representation (DVR) originally developed by Colbert and Miller [Colbert1992]. While the implementation can entertain both aperiodic and periodic potentials, the intrinsic target are soft and large-amplitude motions of non-rigid molecules. For the present purpose, non-rigid molecules are defined as those with at least one internal coordinate that undergoes a large amplitude motion [Bunker1998]. The potentials of these vibrational motions are poorly approximated with harmonic oscillators. The current implementation is in practice limited to solving 1 and 2 dimensional potentials due to the strongly scaling cost of these methods with increased dimensionality. [Colbert1992] Colbert, D. T.; Miller, W. H. A Novel Discrete Variable Representation for Quantum-Mechanical Reactive Scattering via the S-Matrix Kohn Method. J. Chem. Phys. 1992, 96, 1982¿1991. http://doi.org/10.1063/1.462100 [Bunker1998] Bunker, P. R.; Jensen P. Molecular Symmetry and Spectroscopy, 2nd ed.; NRC Research Press: Ottawa 1998. .. [Colbert1992] Colbert, D. T.; Miller, W. H. A Novel Discrete Variable Representation for Quantum-Mechanical Reactive Scattering via the S-Matrix Kohn Method. J. Chem. Phys. 1992, 96, 1982¿1991. http://doi.org/10.1063/1.462100 .. [Bunker] Bunker, P. R.; Jensen P. 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A reference scenario is developed using Energy Information Administration (EIA AEO) projection of economic activities for 2020-2050, GHG emissions data from Environmental Protection Agency's (EPA) inventory of GHG sources and sinks for 2019, and emission factors from Argonne's Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model (GREET®) tool. We consider several carbon reduction approaches including replacement and scale-up of electricity generation with renewables, partial electrification of the transportation sector complimented with biofuels, improvements in building energy efficiency, replacement of natural gas with renewable hydrogen, mitigation of methane emissions from waste and natural gas, agricultural decarbonization, and carbon dioxide removal pathways. 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Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "python 3.7+" + ], + "name": "CFTrack v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CFTrack", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2022-10-06" + }, + "description": "SAND2021-13992 O EMPRESSA is a descriptive metadata management service for large-scale HPC applications that use any mesh type. 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It can accomplish this either by independent L1 sampling like in the popular SPARSIFY algorithm or with correlated L1 sampling, which offers a more efficient decomposition. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://s3miclassical.com/gitweb", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Weak Simulation v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://s3miclassical.com/gitweb", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-16", + "metadataLastUpdated": "2022-10-16" + }, + "description": "SAND2021-4823 O InterSpec decodes and displays gamma radiation data from a variety of handheld, laboratory, and fixed installation detector types. Once loaded, InterSpec provides a means to interactively analyze the data via a peak-based methodology. InterSpec assists with isotope identification and determines the source strength and shielding characteristics of the measured item. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++", + "JavaScript", + "C++", + "HTML" + ], + "name": "InterSpec v. 1.0.9", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/InterSpec", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.9" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-16", + "metadataLastUpdated": "2022-10-16" + }, + "description": "SAND2021-11479 O The OT Emulation Data Broker system allows Simulink models to be connected to an emulated control system network. The package includes a Simulink S-Function that allows communication to the data broker via inter process communication; a data broker, which orchestrates communication between the emulated control system network and the simulation; an endpoint, which facilitates communication between the data broker and PLC's on the control network using ModBus/TCP; and an example PLC structured text files that work with OpenPLC, an open source emulated PLC. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C", + "Python", + "Simulink", + "S Function" + ], + "name": "OT Emulation Data Broker v.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SMARTT", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-10-17", + "metadataLastUpdated": "2022-10-17" + }, + "description": "This software is used to disentangle the forced-versus-unforced components of tropospheric temperature change over the satellite era (after 1979) using maps of surface temperature change as a predictor. 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The software relies on scikit-learn ridge regression, PLS regression, and neural network algorithms.", + "laborHours": 0.0, + "languages": [], + "name": "MSU Disentanglement Analysis Software", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MDAS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2022-10-17", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural Networks (DNNs), Neural ODEs, and Symplectic Neural Networks (SympNets) used with state-of-the-art sampling schemes like Hamiltonian Monte Carlo (HMC) and the No-U-Turn-Sampler (NUTS).", + "laborHours": 0.0, + "languages": [], + "name": "BIhNNs", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/BIhNNs", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2022-10-17", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The purpose of this code is to automatically create random C programs that are guaranteed to have bugs of a particular \"interestingness\". We are using this to train learning machines to fuzz programs better. Other people might want to use it for training humans to examine software.", + "laborHours": 0.0, + "languages": [ + "python 3" + ], + "name": "Buggy-Program-Program", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Buggy-Program-Program", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2022-10-18", + "metadataLastUpdated": "2023-03-13" + }, + "description": "Scoring Threat Objects Analysis Tool", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "python3" + ], + "name": "cisagov/STOAT", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cisagov/STOAT/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cisagov/STOAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-10-18", + "metadataLastUpdated": "2023-02-07" + }, + "description": "ERAD is a software product for computing resiliency and equity metrics in power distribution system. It uses graph database technology to store, query and compute metrics making it highly scalable and available. Metrics can be computed for various resiliency scenarios such as fire, flooding, earthquake.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "ERAD (Equitable Resiliency Analysis tool for Distribution System) [SWR-22-75]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/erad", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "39s@ornl.gov" + }, + "date": { + "created": "2022-10-20", + "metadataLastUpdated": "2022-10-20" + }, + "description": "Reads proprietary electron microscope vendor files and exports them in a standardized open source HDF5 format.", + "laborHours": 0.0, + "languages": [], + "name": "Microscopy Parser", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esrah-ap-niht/Microscopy-VB-GMM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2022-10-26", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The optimization tool denoted as the “Hydropower Flexibility Valuation Tool” aims to maximize the revenue from market participation after satisfying flow requirements, considering a range of power market price signals and water availability scenarios.", + "laborHours": 0.0, + "languages": [], + "name": "HFVT", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HFVT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-10-27", + "metadataLastUpdated": "2022-10-27" + }, + "description": "TEE-ACM2 is a library that computes matrix chain multiplication efficiently on GPUs, using a blocking strategy to load data. The library will provide an energy efficient algorithm for chain Matrix Multiplication, by minimizing both computations and off chip data transfers on the GPUs.", + "laborHours": 0.0, + "languages": [], + "name": "TEE-ACM2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/TEE-ACM2", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-10-27", + "metadataLastUpdated": "2022-10-27" + }, + "description": "This R code consists of three scripts, described below.\n1. ILI_LHC_sample.R The first script generate 10,000 samples from the total\nparameter space formed by the ranges of the following five parameters inputted\ninto the ILI model: transmission rate (beta), per capita rate of progress from\nexposed to infectious state (gamma_1), per capita rate of progress through initial\ninfectious state (gamma_2), per capita rate of progress through hospitalized state\n(gamma_3), and per capita rate of progress through non-hospitalized infectious\nstate (gamma_4). The output is LHS_samples.csv, for input into the global\nsensitivity script, ILI_SEIR.\n2. ILI_SEIR.R The second script solves a standard Susceptible-Exposed-Infected-\nRecovered (SEIR) model (a system of Ordinary Differential Equations (ODEs)),\nruns global sensitivity analyses, and generates plots showing the impact of the\ninput variables on the response variables for each virus.\n3. virus_sims.R The third script solves a standard Susceptible-Exposed-Infected-\nRecovered (SEIR) model (a system of Ordinary Differential Equations (ODEs)),\naimed at modeling outbreaks for five common upper respiratory viruses within a\ncontained population. The output of this code is an epidemic curve to show\ntiming and magnitude of the epidemic peak for each virus.\nNote: for all three scripts, the parameter values must be hard-coded by the user or the\noutput will not be accurate.", + "laborHours": 0.0, + "languages": [], + "name": "ILI Code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ILI", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-10-27", + "metadataLastUpdated": "2022-10-27" + }, + "description": "A collection of iterators built on NVIDIA's thrust library driven by a small domain specific language", + "laborHours": 0.0, + "languages": [], + "name": "thrust iterators", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/thrust-iterators", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-11-03", + "metadataLastUpdated": "2023-04-11" + }, + "description": "Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The code has gone through five rounds of development with images used to train the models. This advancement allows for automated real-time data collection, identification, and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. We will discuss the two open source and publicly available machine learning models developed within this scope of this work: 1) a binary model with a 97.5% accuracy in identifying the difference between an object and an empty scene, including wind turbine and clouds; and 2) a multiple classification model with the capability of identifying the type of object detected: bats (90% accuracy), birds (83% accuracy), insects (69% accuracy) and non-biological (99% accuracy).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "BFSVBF (BatFinder Smart Video BioFilter) [SWR-22-87] and Multi-class BatFinder Smart Video BioFilter Keras", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BatFinder_Smart_Video_BioFilter", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-11-03", + "metadataLastUpdated": "2023-05-05" + }, + "description": "Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source 3D computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The machine learning has been trained on 3D data and allows for automated real-time data collection, identification and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. This machine learning model is an added feature to the previous BatFinder Smart Video BioFilter and increases the accuracy of that systems classification by increasing the accuracy of identifying bats (90% accuracy) and insects (69% accuracy) to a 97% accuracy. There are two object classifier machine learning models, Binary and multi-classification. Binary object classifier labeled BatFinder_Smart_Video_BioFilter.h5 distinguishes between biological objects and non-biological objects. The main goal of this object classifier is to ignore the turbine blades while detecting biological object flying withing the rotor swept area of the turbine. Non-biological objects have a probability of 0 and biological objects have a probability of 1. Multi-classifier labeled Multiclass_BatFinder_Smart_Video_BioFilter.h5 distinguishes between bats, birds, insects and non-biological.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "3DBFSVBF (3D BatFinder Smart Video BioFilter and Multi-class BatFinder Smart Video BioFilter) [SWR-22-88]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BatFinder_Smart_Video_BioFilter", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Code to run the experiments of the Neurips 2022 paper [On the Symmetries of Deep Learning Models and their Internal Representations](https://arxiv.org/abs/2205.14258).", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/modelsym", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/modelsym", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "salkork@ornl.gov" + }, + "date": { + "created": "2022-11-08", + "metadataLastUpdated": "2022-11-08" + }, + "description": "SalineMoose is a MOOSE wrapper for the open-source Saline code, which is an interface for fluid property databsae files. This code is meant to provide access to Saline, which can easily be integrated into MOOSE-based codes that need access to the fluid thermophysical properties that Saline can provide. Wrapping Saline in SalineMoose allows MOOSE codes to use the native MOOSE build system for linking Saline to their MOOSE application.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "SalineMoose", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/neams/saline_moose/-/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/neams/saline_moose", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "vogl2@llnl.gov" + }, + "date": { + "created": "2022-11-09", + "metadataLastUpdated": "2022-11-15" + }, + "description": "A platform for building collaborative autonomy-focused applications.", + "laborHours": 0.0, + "languages": [], + "name": "Skywing", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Skywing/releases/tag/v0.1", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-11-10", + "metadataLastUpdated": "2022-11-10" + }, + "description": "LOKI is a simulation code that models weakly-coupled plasma evolution using Eulerian kinetic models in four phase space dimensions. The code is useful to understand basic plasma nonlinear plasma physics phenomena - in particular, wave-particle and wave-wave resonances that occur in laser plasma interactions. LOKI can simulate fundamental physical process in low-density plasmas on a scale of hundreds of light wavelengths. It does so by solving the relativistic Vlasov and Valsov-Fokker-Planck differential transport equations describing the collision less and low-collisionality evolution of charged particles in electromagnetic fields in two configuration space and two velocity space dimensions. 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Challenges to large-scale adoption of this additive manufacturing method include identifying light dosage parameters and monitoring during fabrication. A research team from LLNL, Iowa State University, and Georgia Tech is applying machine learning models to tackle these challenges-i.e., accelerate the process of identifying optimal light dosage parameters and automate the detection of part quality. Funded by LLNL's Laboratory Directed Research and Development Program, the project team has curated a video dataset of TPL processes for parameters such as light dosages, photo-curable resins, and structures. Both raw and labeled versions of the datasets are available on the links in the Open Data Initiative page. The code uses the labeled dataset. Notebook compiled by Nisha Mulakken (mulakken1@llnl.gov) for LLNL Open Data Initiative, Summer 2022. Original code provided by research team. Publications: X.Y. Lee, S.K. Saha, S. Sarkar, B. Giera. \"Automated detection of part quality during two-photon lithography via deep learning.\" Additive Manufacturing 36, December 2020: doi.org/10.1016/j.addma.2020.101444 X.Y. Lee, S.K. Saha, S. Sarkar, B. Giera. \"wo Photon lithography additive manufacturing: Video dataset of parameter sweep of light dosages, photo-curable resins, and structures.\" Data in Brief 32, October 2020. doi.org/10.1016/j.dib.2020.106119.", + "laborHours": 0.0, + "languages": [], + "name": "ODI notebook additive_manufacturing_video_2022", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnlopendata/additive_manufacturing_video_2022", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2022-11-16", + "metadataLastUpdated": "2022-11-16" + }, + "description": "First patch release of v2.0.0 Changes since v2.0.0 [Important change] Fix ocean threading bug seen in debug cases on Chrysalis with Intel 20.0.4. Was introduced around time of v2.0.0 tag. Does not change v2.0.0 answers on Chrysalis because those didn't use threading or debugging. [EAM] Add semi-lagrangian tracer transport for theta-l (F90 and C++), add new algorithm for finding tropopause, add DSCREAM to allow v2 and SCREAM settings in same code such as adjust_ps [EAM-MMF] 60L default, allow C++ back end of RRTMGP (EAM too). [EAMxx] add nu-top functionality, fix forcing functor, add ttype9 and dcmip2012 tests 2.1, 2.2, and 3 HOMME: remove obsolete remap algs, option to specify dynamics alg indep of tracer, new sponge layer, add imex tests [ELM] Add topography-based subgrid (topounits), add FATES-ELM Nitro., Phos. and CH4 coupling, add land-use ts for NARRM, add lulc for SSP3 RCP7, Fix nutrient fertilization exp test and carbon isotope flux, Fix xactive lnd dry deposition, add lake water storage option, fix plant hydraulics 2d params, fix carbon budget calc, fix soil nutrient conc. bug, fix mosart dam bug, add test for new ELM, MOSART features, fix bug in O3 dry dep stomatal resistances, fix plant hydraulics restart BFB error, update mkmapdata. [MOSART] fix bug for reading the latitude from an unstructured input file, fix oversat in bubble test. [MPAS-ocean] Add CFC11, CFC12 tracers, add 2D spherical transport tests, fix del4 tracer mixing, add MARBL ocean tracer mixing, modify harmonic analysis options, add GPU port of vmix routines, fix calc of ML-averaged BV freq. [MPAS-seaice] Change extents of initial polar disks for oRRS18to6v3 grid, fix ice BGC with MARBL, update spherical test cases, fix DON coupling, Remove Cf from sea ice constants. [MPAS-landice] add CRYO1850-4xCO2 compset [CIME] add GCP, ANL GCE, Spock, Perlmutter, deprecate config_compilers.xml, fix and clean-up cmake macros, fix slurm bindings, refactor CIME internal testing, cleanup SCORPIO perf data, allow position independent compset naming, [also] update v2 benchmarking suite, extend e3sm_prod with throughput and memory checks", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v2.0.1", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v2.0.1", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v2.0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Web server and RESTful backend services for APBS and PDB2PQR\nThis software was developed to deploy APBS (https://github.com/Electrostatics/apbs) and PDB2PQR\n(https://github.com/Electrostatics/pdb2pqr) on Azure to address a gap left by the closing of the previous hosting service at\nUCSD", + "laborHours": 0.0, + "languages": [], + "name": "Electrostatics/apbs-rest", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://creativecommons.org/publicdomain/zero/1.0", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electrostatics/apbs-rest", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SSASSE software is responsible for validating, and verifying innovative safe scanning methodologies, models, architectures, and prototypes to safely assess operational technology (OT) installed in critical energy infrastructure.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/ssass-e", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ssass-e", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Mapping software with pre-loaded global and local maps", + "laborHours": 0.0, + "languages": [], + "name": "JGCRI/rmap", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/rmap", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "FENATE: Fast Evaluation of Network Architecture -- Toolchain and Environment. Our framework is comprised of scalable\ntools to both skeletonize and simulate MPI communication patterns providing a functional view of the network under\ninvestigation (trading off accuracy for speed)", + "laborHours": 0.0, + "languages": [], + "name": "FENATE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/FENATE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Transfer Learning From Existing Diseases Via Hierarchical Multi-Modal BERT Models", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/TransMED", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/TransMED", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Python package that provides an interface to raw MS data in the MZA format.", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-m-q/mzapy", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-m-q/mzapy", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Designs for Risk Evaluation and Management (DREAM) tool was developed as part of the effort to quantify the risk of\ngeologic storage of carbon dioxide (CO2) under the U.S. Department of Energy’s National Risk Assessment Partnership\n(NRAP). DREAM is an optimization tool created to identify optimal monitoring schemes that minimize the time to first\ndetection of CO2 leakage from a subsurface storage formation. DREAM acts as a post-processer on user-provided output\nfrom subsurface leakage simulations. While DREAM was developed for CO2 leakage scenarios, it is applicable to any\nsubsurface leakage simulation of the same output format", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/dream_v3", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/dream_v3", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Archive Sprinter tool is designed to efficiently process synchrophasor measurements from electric power grids and\nexport data signatures that summarize the grid's behavior. Parallel processing will allow data to be processed quickly to\nenable practical analyses of archives spanning years. The grid's behavior will be summarized using a wide-array of\nsignatures calculated from the input data.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/archive-sprinter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/archive-sprinter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "zulissi@andrew.cmu.edu" + }, + "date": { + "created": "2022-11-18", + "metadataLastUpdated": "2022-11-18" + }, + "description": "CatGym is a deep reinforcement learning (DRL) environment for predicting the thermal surface reconstruction pathways and their associated kinetic barriers in crystalline solids under reaction conditions. The DRL agent iteratively changes the positions of atoms in the near-surface region to generate kinetic pathways to accessible local minima involving changes in the surface compositions.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "catgym", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ulissigroup/catgym", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-11-18", + "metadataLastUpdated": "2022-11-18" + }, + "description": "The autodataman tool is intended to be a very lightweight climate data database and data distribution engine.", + "laborHours": 0.0, + "languages": [], + "name": "Autodataman", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmecmetrics/autodataman", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2022-11-18", + "metadataLastUpdated": "2022-12-23" + }, + "description": "Second patch release of v2.0.0 Changes since v2.0.1 [Important change] Add and update SSP370 and SSP585 cases, add tests, fix use-case files, Change ocean and sea-ice IC for ARRM60to10. [EAM] allow thetaxx as a CAM_TARGET, enable northamericax4v1pg2_WC14to60E2r3 for AMIP, fix ndrop initialization, allow up to 15 history files. [EAMxx] allow use of readnl [EAM-MMF] allow transient SST case for C++ MMF, remove specific task/thread count for ESMT test, modify the variance transport diagnostic, reorg tests, [HOMME] Allow optional sponge layer. [ELM] add 2 land-atm compsets, update FATES to API 17.0.0, allow FATES sp mode, allow ELM harvest to drive FATES harvest, fix memleaks, reduce test build times, modified parameters for miscanthus and switchgrass based on calibration [MPAS-Ocean] turn on ocean BGC in BGC cases, fix interface locations for 60L PHC grid, add mode spec to conservation check streams, allow oRRS18to6v3 grid to run with JRA, update ocean and sea ice ICs for ARRM60to10 (needed for v2), GPU port of thickness tendency, add CMPASO-JRA1p4, [MPAS framework] Add new reproducible global sum module for MPAS components, Add mostRecentAccessTime attribute to streams [MPAS-landice] Update MALI version and Greenland mesh [MPAS-seaice] add single-cell test case, fix BGC restart, Adds omp critical directives for ice warnings seen on cori. [CIME] Fix component namelist creation bugs when NINST>1, add OpenACC, OpenMP and CXX GPU tests, fix nonBFB tests, stop using config_compilers, reduce ELM test build times with shared executable, update OpenMPI on Chrysalis. fix baseline handling, provenance handling with update to cime6.0.33, also use component-specific config_pes files and add the ones from master [Machine updates] cori modules after maint, Chrysalis to OpenMPI-4.1.3 [run_e3sm] replace default case name and group. [Externals] update SCORPIO to 1.3.2", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v2.0.2", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v2.0.2", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v2.0.2" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "We investigate substituting a parallel, half-approximation for maximum weight matching instead of an exact computation. Our experiments show that the resulting difference in solution quality is negligible. 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The MFC modulates the flexible GEB in the lower level with guaranteed thermal comfort of end users in response to the optimal pricing and power signals determined in the upper layer using a Stackelberg game integrated with aggregate virtual battery constraints. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable even on small, embedded devices. This software code enables the use of residential and small-size commercial buildings to offer a potentially substantial source of ancillary grid services that are currently underutilized. A hierarchical, model-free transactive building control provides a smooth interface between the grid service requests of utilities and the reliable control required by participating buildings. Model-free control, which supports distributed control architecture, will be a more scalable solution that can be deployed in neighborhood-size systems as well as individual buildings. The proposed approach contributes to the body of knowledge on two main aspects. First, it couples the MFC with the game-theoretic control and proposes a scalable model-free transactive control approach. MFC does not require any modeling effort or model training for the various building loads. This is very beneficial since deriving an accurate model for every single unit participating in DR programs and obtaining all the parameters about the units (e.g., thermal coefficients, standby losses) are infeasible. Also, MFC is computationally efficient, easily deployable even on small, embedded devices, and can be implemented in real time. Second, it integrates the concept of virtual battery into DR via the Stackelberg game. 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Additionally, the scripts implement analysis methods to evaluate and explore the results of the method. 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In TriPoll, users define their own callback functions that get executed on the metadata of each triangle within a\ngraph as triangles are identified. This functionality makes it possible for users to perform advanced analyses and gather statistics about specific classes of triangles of interest.", + "laborHours": 0.0, + "languages": [], + "name": "TriPoll", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/tripoll", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "qinwu@bnl.gov" + }, + "date": { + "created": "2022-12-23", + "metadataLastUpdated": "2022-12-23" + }, + "description": "Kinetics of a reaction network that follows mass-action rate laws can be described with a system of ordinary differential equations (ODEs) with polynomial right-hand side. 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Importantly, we have implemented various measures to apply physical constraints and chemical knowledge in the training to regularize the solution space.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PolyODENet", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ICKMod/PolyODENet/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ICKMod/PolyODENet", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-01-03", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This application allows parallel development of simulator screens for the Human System Simulation Laboratory and connection of the backend simulators for various power plants", + "laborHours": 0.0, + "languages": [], + "name": "General-Simulator-Intermediary", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/General-Simulator-Intermediary", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-01-03", + "metadataLastUpdated": "2023-05-17" + }, + "description": "Caldera ICM is part of Caldera software platform, a suite of collective, open-source tools that was developed to improve the state of the art in modeling the impacts of Electric Vehicle (EV) charging on the grid. The foundation of Caldera ICM is it’s first-of-its-kind library of high-fidelity charging models for a wide variety of vehicles, validated by test data under a range of operating conditions. The charging models are used to accurately model the EV charging on an electric vehicle supply equipment (EVSE) – also known as a charger. ICM uses as inputs, the EV characteristics such as battery size, battery chemistry (i.e. NMC, LTO), watt hour per mile, inverter efficiency and max charge rate; as well as EVSE characteristics such as max current and supply equipment type (i.e. L2 vs XFC). Using these inputs Caldera ICM creates an uncontrolled charging profile curve for each compatible EV-EVSE pair. These charge profiles can be used stand alone to estimate charge duration given start State Of Charge (SOC) and end SOC or charge energy size given start SOC and charge duration. In Caldera Grid, another tool in the Caldera software platform, these charge profiles are used to represent EV charging as a load on the grid using charge event data such as EV type, SE type, start SOC, final SOC, park start time and park end time. ICM currently supports energy shifting Smart Charge Management (SCM) strategies such as \"Time Of Use (TOU) immediate”, “TOU random” and “random start” by delaying the charge to start at a preferable time with respect to the strategy and, one voltage support SCM strategy named autonomous voltage control strategy by providing reactive power back to the electric grid.", + "laborHours": 0.0, + "languages": [], + "name": "Caldera Infrastructure Charge Module (ICM)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Caldera_ICM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-01-03", + "metadataLastUpdated": "2023-05-17" + }, + "description": "Caldera Grid is part of Caldera software platform, a suite of collective, open-source tools that was developed to improve the state of the art in modeling the impacts of Electric Vehicle (EV) charging on the grid. Caldera Grid is a co-simulation framework implemented using Hierarchical Engine for Large scale Infrastructure Co-Simulation (HELICS). The framework facilitates the co-simulation of EV charging and Smart Charge Management (SCM) strategies in Caldera Infrastructure Charge Model (ICM) with distribution level grid models in OpenDSS. Vehicle energy needs and charge session requirements generated using Caldera Charge Decision Module (CDM) are fed in as input to Caldera Grid. The EV charging models in Caldera ICM simulates both the uncontrolled charging loads as well as loads modified by the SCM strategies to develop distributed load profiles for each grid node hosting an Electric Vehicle Supply Equipment (EVSE) – also known as chargers. These loads were simulated in OpenDSS alongside existing distribution feeder loads. Each of these models are co-simulated in a HELICS federate. The HELICS co-simulation framework facilitates communication and synchronization between the federates. By co-simulating EV loads and distribution feeder loads, Caldera Grid can assess the potential grid impacts of EV charging on distribution feeders under various grid conditions. A control strategy federate is implemented with an interface where control strategies based on feedback from EV charging status and grid conditions can be developed and implemented. The platform can also support multiple control strategies in a single co-simulation.", + "laborHours": 0.0, + "languages": [], + "name": "Caldera_Grid", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Caldera_Grid", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-04", + "metadataLastUpdated": "2023-01-04" + }, + "description": "This software contains the code for a data-driven model to produce high-resolution (< 1 km2) estimates of temperature, salinity, and turbidity over decadal time scales as required by next-generation Earth Systems Models. Our model fits daily MODIS Aqua reflectance data to surface observations (< 1 m depth) from 2000-2021 in Chesapeake Bay, USA.", + "laborHours": 0.0, + "languages": [], + "name": "Geographically aware estimates of remotely sensed water properties for Chesapeake Bay", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DOE-ICoM/geowq-chesapeake", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-04", + "metadataLastUpdated": "2023-01-04" + }, + "description": "Ring Pull Strain Analysis (RPSA) is a framework for analysis of Digital Image Correlation (DIC) data of gaugeless ring pull testing. It is meant for analysis of rings cut from tube cross sections and pulled in a displacement-controlled tensile test. This code takes load frame data, images take during testing, and csv files from the DIC analysis of those images and allows the user to analyze and plot data from the test. Some important features of the software include getting the strain values as a function of radial distance and angle, plotting of the strain around the ring, and stress-strain analysis of the load frame data.", + "laborHours": 0.0, + "languages": [], + "name": "Ring Pull Strain Analysis", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/RingPullStrainAnalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-04", + "metadataLastUpdated": "2023-01-04" + }, + "description": "Architector is a 3D chemical structure generation software package designed to take minimal 2D information about ligands and metal centers and generates chemically sensible 3D conformers and stereochemistry of the organometallic compounds. Architector is capable of high-throughput in-silico construction of s-, p-, d-, and f-block organometallic complexes. Architector represents a transformative step towards cross-periodic table computational design of metal complex chemistry.", + "laborHours": 0.0, + "languages": [], + "name": "Architector", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Architector", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-04", + "metadataLastUpdated": "2023-01-04" + }, + "description": "The Orthogonal Diffusion Discretizations (ODD) library is a collection of low order (Diffusion, P1, Ray Tracing, and Variable Eddington Factor (VEF)) thermal radiation solvers for orthogonal structured grids driven by an application programing interface (API).", + "laborHours": 0.0, + "languages": [], + "name": "ODD (Version 0.X)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ODD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-04", + "metadataLastUpdated": "2023-01-04" + }, + "description": "EAP Patterns: Memory access and iteration patterns from the EAP code base with the physics removed. This is intended to be a serial app representing memory access patterns. We will populate the data structures from EAP output files to provide representative patterns of face and cell loops within the EAP code base The arguments to the program are the EAP output file and the number of MPI processors to emulate. Currently there is no MPI in the application and the number of processors represents a means of emulating the halo (clone) cells around the domain of the given processor. An optional argument `processor_ID` can be provided to specify the processor to emulate. In the future we plan to include the ability to run multiple MPI ranks to more accurately represent the on-node demands on memory bandwidth.", + "laborHours": 0.0, + "languages": [], + "name": "EAP Patterns", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/eap-patterns", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-15185 O Differentially Private DBSCAN is a differential private clustering algorithm used for running experiments and conducting data analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 76.0, + "languages": [ + "Python3" + ], + "name": "Differentially Private DBSCAN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DP_DBSCAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2023-06-22" + }, + "description": "SAND2022-14744 O The Deep Learning Denoiser uses a trained deep convolutional neural network (CNN) model to decompose an input waveform into a signal and noise waveform. In the approach, the CNN provides a signal mask and a noise mask for an input signal. The Short-Time Fourier Transform (STFT) of the estimated signal is obtained by multiplying the signal mask with the STFT of the input signal. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deep Learning Denoiser", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Deep-Learning-Denoiser", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2023-01-12" + }, + "description": "SAND2022-14694 O CrystalVR is a CAD2VR plugin which enables the import of crystallographic information files (CIF) into a virtual reality (VR) environment for visualization and interaction. Crystallographic data is incredibly complex and difficult to navigate and visualize on a two-dimensional or 2D screen. CrystalVR empowers users to step inside their crystals, allowing them to intuitively grow, shrink, and scale the crystal structure. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "CrystalVR", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "2022.0.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2023-05-16" + }, + "description": "The HOMP software module is contained within NREL's Hybrid Optimization and Performance Platform (HOPP) at this URL: https://github.com/NREL/HOPP/tree/feature/HOMP. HOMP is a python-based software module which can be used concurrently with the Hybrid Optimization and Performance Platform (HOPP) to model, simulate, and optimize degradation, reliability, and operations and maintenance of hybrid power plant components. The program currently models lithium ion battery, PEM electrolyzer, wind turbine, and solar PV array components, which enables users to understand the design and operation tradeoffs of hybrid power plants. For instance, HOMP enables users to answer questions like: how large does a battery bank need to be to achieve optimal charge/discharge rates for performance and reliability? How does plant design change for different objectives (e.g., profit versus resilience)? Under what conditions is it better to produce electricity versus hydrogen? How do we optimally control hybrid power plants to reduce downtime and increase performance?", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "PowerBuilder", + "Python" + ], + "name": "HOMP (Hybrid Operation and Maintenance Platform) [SWR-22-81]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HOPP", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-14659 O The Wind Energy Intrusion Detection System uses a human-machine interface (HMI) to parse results and analyze for anomalies. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "Wind Energy Intrusion Detection System", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/wind_hids", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Protein-DNA Interaction Workflow (PDI Workflow), a pipeline that focuses on generating\nhigh-quality docking and molecular dynamics simulations for Protein-DNA complexes. This allows us to take DNA\nsequences with unknown tertiary structures, accurately predict their structure, dock them with the desired target protein,\nand then simulate their interactions using molecular dynamics simulations", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Auto_PDI", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "3D-MolGNNRL, couples reinforcement learning (RL) to a deep\ngenerative model based on 3D-Scaffold to generate target candidates specific to a protein pocket building up atom by\natom from the core scaffold. 3D-MolGNNRL provides an efficient way to optimize key features within a protein pocket using\na parallel graph neural network model. The agent learns to build molecules in 3D space while optimizing the binding\naffinity, potency, and synthetic accessibility of the candidates generated for the SARS-CoV-2 Main protease", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "3D_MolGNN_RL", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "control software for an automated liquid chromatography sample injection and\nseparation system. It is related to a PNNL invention report 31630-E, Method for direct delivering trace samples from smallsize\nwells to liquid chromatography and mass spectrometry. The main purpose of the control software is to enable\nautomated sample injection from a nanowell device.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Autosampler software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A method for prediction of cell regulation to maximize cell growth rate while maintaining the solvent capacity\nof the cell. Prediction is formulated as an optimization problem using a thermodynamic framework that can leverage\nexperimental data. We develop a formulation and variable initialization procedure that allows for computing solutions of\nthe optimization with an interior point method", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Pathway_Controlled_Optimization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Pathway_Controlled_Optimization", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2023-01-12" + }, + "description": "First release of version 2.1 of the Energy Exascale Earth System Model. [ATM] The atmosphere component remains EAM. There are no major changes in the default configuration since 2.0. New features include: A semi-lagrangian tracer transport for theta-l dycore, a new algorithm for finding the tropopause, new RRM mesh configurations. Add and update SSP370 and SSP585 cases. Restore the FIDEAL case. [LAND] The land component is ELM. There are no major changes in the default configuration since 2.0. Several option features have been added including: implementation of topography-based subgrid structure (topounits) and accompanying parameterizations and atmospheric forcing downscaling methods; a new plant hydraulics scheme; two-way land-river hydrological coupling through the infiltration of floodplain water; an implementation of perennial crops; updates to the SNICAR-AD snow radiative transfer model; and implementation of soil erosion and sediment yield in ELM-Erosion. Each of these new changes is modular in design and can be turned on or off as the user specifies; they are currently being tested in different “BGC” configurations. [OCEAN] The ocean component remains MPAS-Ocean. Major change since version 2.0 include the addition of the Fox-Kemper et al. 2011 parameterization for submesocale eddies, a correction for barotropic thickness consistency that reduces divergence noise, and the addition of an ocean carbon conservation analysis member. [SEAICE] The sea-ice component remains MPAS-Seaice. Major changes since version 2.0 include: A correction to how shortwave parameters are interpolated in the snicar-ad 5-band radiation scheme, the addition of a sea ice carbon conservation analysis member, updates to the default sea ice biogeochemistry namelist parameters to be consistent with version 2.0 improvements to nitrogen cycling and a correction in the ice-ocean dissolved organic nitrogen coupling. [LAND ICE] The land-ice component remains MPAS-Albany-landIce (MALI). Major changes since 2.0 include an update to the MALI version and the Greenland mesh.[RIVER] The river model is MOSART. There are no major changes in the default configuration since 2.0. A major new optional feature is two-way river-ocean hydrological coupling between MOSART and MPAS-O. This change can be turned on or off as the user specifies, and is being tested in different configurations. [COUPLER] The coupler remains cpl7/MCT. Major changes since version 2.0 include: Carbon budget calculated when heat/water budgets active. Fix a bug in land-atm fluxes for tri-grid configurations. [OTHER] a small bug in the zenith angle calculation was fixed in the data models.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v2.1.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v2.1.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v2.1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-01-11", + "metadataLastUpdated": "2023-03-29" + }, + "description": "The Beam Characterization System (BCS) is an image-processing tool for estimating heliostat tracking errors. A large mirror, or heliostat, reflects the sun onto a distant target. A carefully calibrated camera then takes an image of this target to capture the shape of the reflected beam. The software kit hosts a series of scripts to identify key features and run analysis on the captured images.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "BCS (CSP Beam Characterization System) [SWR-23-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NREL-Beam-Characterization", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The molecular graphics program, PyMol, was employed to produce all images in the training/validation/testing datasets. A\nPyMol script identified the clusters of interest from a list of all proteins containing 1) Fe (III) and Fe (II) ion and 2) FeS,\nrespectively. A PyMol script and a Python webscraper were also used to classify [2Fe-2S] cofactors into three classes:\nstandard, Rieske, and other and to identify iron atoms with four cysteine residues. We also used the pyMol script to rotate\namino acids for training", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/mlprotein", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mlprotein", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "mcarbone@bnl.gov" + }, + "date": { + "created": "2023-01-15", + "metadataLastUpdated": "2023-01-15" + }, + "description": "Neural network ensembles for X-ray absorption spectroscopy of molecules and materials. Companion code for preprint https://arxiv.org/abs/2210.00336.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AI-multimodal/XAS-NNE", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AI-multimodal/XAS-NNE", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git", + "version": "v0.1.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-17", + "metadataLastUpdated": "2023-01-17" + }, + "description": "This software builds on PHAME developed at LANL to generate phylogenetic trees of bacterial whole genome sequences. Where PHAME uses whole genome alignments to generate informative sites to base tress on, PHAME-OuS annotates bacterial genes, identifies orthologous sequences, aligns related proteins, uses those alignments to inform transcript alignments, then builds trees with several methods. The first is a conventional gene concatenation and ML tree estemation method. The second attempts to reconcile gene tree with a unified species tree using quartets (ASTRAL). Both methods allow filtering of gene lists on number of species represented, length, and gappiness in order to tune noise-to-signal for tree estimation", + "laborHours": 0.0, + "languages": [], + "name": "OrthoPhylo", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/OrthoPhylo", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2023-01-17", + "metadataLastUpdated": "2023-08-24" + }, + "description": "This open-source tool aims to provide a powerful and flexible platform for simulating electromagnetic transients (EMT) of large-scale inverter-based resource (IBR)-dominated power systems. The purpose of making it open source is to foster a community of EMT simulation and assist in exploring new EMT algorithms and applying advanced computational techniques to EMT simulation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ParaEMT (NREL's EMT Simulator: An Open Source, and HPC-Compatible Large-Scale Power System Electro-Magnetic Transient (EMT) Simulator) [SWR-22-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ParaEMT_public", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ghawalyjm@ornl.gov" + }, + "date": { + "created": "2023-01-18", + "metadataLastUpdated": "2023-01-18" + }, + "description": "Code accompanying the \"Introduction to Machine Learning\" short course for the 2022 IEEE NSS MIC RTSD conference.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "IEEE Short Course 4: Introduction to Machine Learning", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jghawaly/IEEE_Intro2ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "nutarojj@ornl.gov" + }, + "date": { + "created": "2023-01-19", + "metadataLastUpdated": "2023-01-19" + }, + "description": "Convert Collada 3D model files to a voxel model.", + "laborHours": 0.0, + "languages": [], + "name": "tovox", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/1qn/tovox", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "vincent@sacksteder.com" + }, + "date": { + "created": "2023-01-24", + "metadataLastUpdated": "2023-02-21" + }, + "description": "ComDMFT is an ab initio code for simulating correlated quantum materials with crystalline symmetry. It combines DFT or qsGW calculations with impurity problems describing strong on-atom correlations. The impurity problem is set up using Wannier90 and cRPA, and can be solved with DMFT and CTQMC.", + "laborHours": 0.0, + "languages": [], + "name": "ComDMFT", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/comscope/ComDMFT", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-01-24", + "metadataLastUpdated": "2023-04-05" + }, + "description": "These datasets describe multiple facets of the temporal complementarity of co-located hybrid renewable energy systems throughout the United States. Several metrics characterizing the complementarity of generation profiles are provided on an annual and monthly basis (for both hourly and daily aggregations). These generation profiles are underpinned by hourly resource data (e.g., the WIND Toolkit and National Solar Radiation Database (NSRDB)) spanning the multi-year period 2007-2013. The data include complementarity results for greater than 1.76 million individual locations within the continental United States (CONUS). The data are intended to accompany two publications on the topic of temporal complementarity: 1) Harrison-Atlas, Dylan, Caitlin Murphy, Anna Schleifer, and Nicholas Grue. \"Temporal complementarity and value of wind-PV hybrid systems across the United States.\" Renewable Energy 201 (2022): 111-123, doi:10.1016/j.renene.2022.10.060; and 2) Murphy, Caitlin, Harrison-Atlas, Dylan, Nicholas Grue, Vahan Gevorgian, Juan Gallego-Calderon, Shiloh Elliot and Thomas Mosier. “A Resource Assessment for FlexPower”. NREL Technical Report.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "Data on temporal complementarity of hybrid renewable energy systems [SWR-23-09]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Renewable-Complementarity", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-01-25", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Bayesian Model Calibration (BayCal) toolkit is a software plugin for Risk Analysis Virtual Environment (RAVEN) framework, arming at inversely quantifying the uncertainties associated with simulation model parameters based on available experiment data. BayCal seeks statistical inference of the uncertain input parameters that are consistent with the available measurement data or observed data. The unique feature of BayCal is the capability to be linked with RAVEN to build corresponding calibration workflows for complex multi-physics simulations. In addition to be able to use the machine learning capability of RAVEN to significantly reduce the computational cost of expensive simulation models, another distinctive feature of BayCal is the capability to deal with high-dimensional correlated model outputs, such as time series observations at multiple locations, via principal component analysis (PCA) technique.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Baycal", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/BayCal", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-01-25", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This code provides annotation and an interface to 10+ hours of video activities in a high performance datacenter with 20+ different types of anomalous activities. The purpose is to enable machine learning for video surveillance systems in high performance computing centers. This is the first code of this type addressing the space of high performance computing datacenters.", + "laborHours": 0.0, + "languages": [], + "name": "Anomalous And Normal High Performance Computing Datacenter Activities", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HPCACT-2022", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-01-27", + "metadataLastUpdated": "2023-01-27" + }, + "description": "Cardinal is a code that automates the workflow for iteratively solving neutral particle transport via the OpenMC code and computational fluid dynamics via the NekRS code within the Multiphysics Object Oriented Simulation Environment (MOOSE), a finite element framework for solving general partial differential equations. Cardinal establishes a mapping between the Monte Carlo geometry representation used in OpenMC and the spectral element mesh used in NekRS to other physics applications built upon the MOOSE framework, allowing high-resolution particle transport and fluid dynamics physics feedback to the MOOSE application ecosystem. Heat generation rates as solved by OpenMC are used as heat sources in MOOSE, while the temperature and density fields from NekRS are used as conjugate heat transfer boundary conditions and/or source fields in MOOSE. OpenMC, Nek5000, and MOOSE are open source, community-developed simulation codes.", + "laborHours": 0.0, + "languages": [], + "name": "CARDINAL", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/neams-th-coe/cardinal", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Building Re-tuning Simulator (BRS) is a Re-tuning focused modeling and building automation system simulation environment.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Building Re-tuning Simulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-02-01", + "metadataLastUpdated": "2023-02-06" + }, + "description": "OEDI-SI (formerly known as GADAL (Grid Algorithms and Data Analytics Library)) provides a library for connecting Algorithms and Datasets in a co-simulation framework can be found at the following URLS: https://github.com/openEDI/GADAL; https://github.com/openEDI/sgidal-example; https://github.com/openEDI/gadal-ieee123", + "laborHours": 0.0, + "languages": [], + "name": "Open Energy Data Initiative – Systems Integration (OEDI-SI) f/k/a GADAL (Grid Algorithms and Data Analytics Library) [SWR-22-86]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openEDI/gadal-ieee123", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-02", + "metadataLastUpdated": "2023-02-07" + }, + "description": "PSUADE (Problem Solving testbed for Uncertainty Analysis and Design Exploration) is a mathematical software useful for performing uncertainty quantification and sensitivity analysis.", + "laborHours": 0.0, + "languages": [], + "name": "PSUADE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.1" + }, + { + "contact": { + "email": "passarellals@ornl.gov" + }, + "date": { + "created": "2023-02-06", + "metadataLastUpdated": "2023-02-06" + }, + "description": "This model uses an unsupervised sentence encoder proposed by Liu et al. (2021) to create better sentence representations for the SPECTER transformer model.", + "laborHours": 0.0, + "languages": [], + "name": "mirror-SPECTER", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://huggingface.co/Linseypass/mirror-SPECTER", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "jcreed2@ncsu.edu" + }, + "date": { + "created": "2023-02-07", + "metadataLastUpdated": "2023-02-08" + }, + "description": "This project is a code base for a tethered energy-harvesting kite system, that is able to operate in both a water or wind environment. The project is broken into: Classes - containing classes for things such as the kite, the environment, the flight controller, the tethers, ect. Compositions - contains simulink block diagrams for using instances of the classes, for things such as the kite, the environment, the flight controller, the tethers, ect. Units - basically Simulink library files used in many places to perform fundamental operations Master Simulink model - where all the compositions are run together Test scripts - scripts to run the master Simulink model under various conditions The key components of the model are the kite vehicle, the tethers, the ground station, the environment, the flight controller, and high level controllers.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Simulink" + ], + "name": "Ocean Kite Project", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NCSUCORE/DoEOceanKiteProject/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NCSUCORE/DoEOceanKiteProject.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kallander2@llnl.gov" + }, + "date": { + "created": "2023-02-07", + "metadataLastUpdated": "2023-02-17" + }, + "description": "Trestles is a modified H.264 decoder that allows access to the uncompressed transformed residual pixel and motion vector values that are contained (in compressed form) in the H.264 NAL units (a.k.a. video bitstream).", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Trestles", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/trestles", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "kentpr@ornl.gov" + }, + "date": { + "created": "2023-02-08", + "metadataLastUpdated": "2023-02-08" + }, + "description": "QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support.", + "laborHours": 0.0, + "languages": [ + "C++17" + ], + "name": "QMCPACK v3.16.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/NCSA", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QMCPACK/qmcpack/releases/tag/v3.16.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v3.16.0" + }, + { + "contact": { + "email": "spannausat@ornl.gov" + }, + "date": { + "created": "2023-02-08", + "metadataLastUpdated": "2023-08-22" + }, + "description": "The National Cancer Institute (NCI) monitors population level cancer trends as part of its Surveillance, Epidemiology, and End Results (SEER) program. This program consists of state or regional level cancer registries which collect, analyze, and annotate cancer pathology reports. From these annotated pathology reports, each individual registry aggregates cancer phenotype information and summary statistics about cancer prevalence to facilitate population level monitoring of cancer incidence. Extracting cancer phenotype from these reports is a labor intensive task, requiring specialized knowledge about the reports and cancer. Automating this information extraction process from cancer pathology reports has the potential to improve not only the quality of the data by extracting information in a consistent manner across registries, but to improve the quality of patient outcomes by reducing the time to assimilate new data and enabling time-sensitive applications such as precision medicine. Here we present FrESCO: Framework for Exploring Scalable Computational Oncology, a modular deep-learning natural language processing (NLP) library for extracting pathology information from clinical text documents.", + "laborHours": 0.0, + "languages": [], + "name": "FrESCO", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DOE-NCI-MOSSAIC/FrESCO", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v0.2.3" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-02-09", + "metadataLastUpdated": "2023-03-08" + }, + "description": "To more effectively and completely convert STIX1 data to STIX2.", + "laborHours": 0.0, + "languages": [], + "name": "Enhanced_STIX_Elevator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/idaholab/Enhanced_STIX_Elevator/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Enhanced_STIX_Elevator", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-02-09", + "metadataLastUpdated": "2023-03-13" + }, + "description": "Resilience of Microgrids with Adaptive capacity and Inertia calculates the maximum size of a disturbance a microgrid could withstand before frequency limits are violated. The results are based on power generation assets in the microgrid and its inertia.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Resilience Of Microgrids With Adaptive Capacity And Inertia", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/ReMAIn", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wanh@ornl.gov" + }, + "date": { + "created": "2023-02-13", + "metadataLastUpdated": "2023-02-13" + }, + "description": "ASHRAE Standard 205 - Heat Pump Design Model supply; This package helps OEMs to convert HPDM output files to STD 205 format; it also provides some RS sample tables.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HPDM-STD205", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/HPDM-STD205", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-15", + "metadataLastUpdated": "2023-02-15" + }, + "description": "Hermes-3 is a plasma simulation model built on BOUT++, developed as part of research studies of the edge and divertor regions of magnetically confined fusion plasmas such as tokamaks. The main purpose of this model is multi-species simulation of plasmas containing a mixture of deuterium, tritium, helium and other plasma and neutral gas species.", + "laborHours": 0.0, + "languages": [], + "name": "Hermes-3", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bendudson/hermes-3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-02-16", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Stitch is a new IO library focused around supporting simulations where only a small portion of the simulation space changes at each timestep. It improves storage efficiency by only storing the changed data and constructs on request a view of an arbitrary region at a given time by stitching together parts of various outputs. This enables scaling from a single process to 100s of nodes. The earlier version performance of the library as the data size scaled was too slow. Changes were made to improve the performance by a factor of about 30x in the production applications. 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We find that although a surprising degree of transfer is possible between certain do- mains, it is not so successful between others. 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This collection of tools has been built into an R package for easy use at LANL and in the probabilistic numerics community.", + "laborHours": 0.0, + "languages": [], + "name": "gpde", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/gpde", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-02-24", + "metadataLastUpdated": "2023-02-24" + }, + "description": "This software contains the code for Bayesian uncertainty analysis of global lake area. Computed uncertainties are compared against more conventional estimation using lake size-abundance distributions. 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This project includes a template WAVES modsim repository which is used for the tutorials and for integration and regression testing of the WAVES extensions to SCons.", + "laborHours": 0.0, + "languages": [], + "name": "WAVES: WAVES Analysis for Verified Engineering Simulatio", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/waves", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "mazeauej@ornl.gov" + }, + "date": { + "created": "2023-02-27", + "metadataLastUpdated": "2023-02-27" + }, + "description": "[Atomic Simulation Environment](https://wiki.fysik.dtu.dk/ase/): A Python library for working with atoms", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ase", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ase/ase", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-28", + "metadataLastUpdated": "2023-02-28" + }, + "description": "DeltaUQ is a PyTorch library for uncertainty quantification with deep neural networks. 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Is there", + "laborHours": 0.0, + "languages": [], + "name": "nvidia dataframe library patch to support parquet indexing", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rapidsai/cudf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-28", + "metadataLastUpdated": "2023-02-28" + }, + "description": "MetallData is an HPC platform for interactive data science applications at HPC-scales. 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Wintap can support a wide variety of applications across production operations, cyber security operations, and cyber security research.", + "laborHours": 0.0, + "languages": [], + "name": "Wintap", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Wintap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "6.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-01", + "metadataLastUpdated": "2023-03-01" + }, + "description": "This code provides fast Gaussian process prediction algorithms based on the MuyGPs scalable hyperparameter optimization algorithm. 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Such an effort that brings in more developers to use and contribute to lab software can further improve the quality of the software, and developer experience at the lab. 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This work was not funded by, nor was any work performed under any DOE contract.", + "laborHours": 0.0, + "languages": [ + "Bash", + "C", + "Python" + ], + "name": "Klippy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Laikulo/klippy-tooling", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.11.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-07", + "metadataLastUpdated": "2023-03-07" + }, + "description": "LaSDI is a data-driven physical simulation software that forms a latent space for a given high-fidelity model and discovers a set of ordinary differential equations for the latent space dynamics. 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A concept of local dynamics identification procedure is introduced to enable a parametric model, which enhances the accuracy level over a given parameter space.", + "laborHours": 0.0, + "languages": [], + "name": "Latent Space Dynamics Identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LaSDI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-07", + "metadataLastUpdated": "2023-06-23" + }, + "description": "GENTANGLE is a high performance containerized pipeline for the computational design of two overlapping genes translated in different reading frames of the genome that can be used to design and test gene entanglements for new microbial engineering projects using arbitrary sets of user specified gene pairs.", + "laborHours": 0.0, + "languages": [], + "name": "Gene Tuples ArraNGed in overLapping Elements", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BiosecSFA/gentangle", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-07", + "metadataLastUpdated": "2023-10-20" + }, + "description": "Operational Forecasting of Induced Seismicity (ORION) is an open-source toolkit developed as part of the US Department of Energy SMART and NRAP programs. ORION is designed to help both expert and non-expert users understand the seismic hazard at a site. This tool analyzes how the seismic hazard evolves during injection of fluid, and can be used to identify potential mitigation strategies for observed or forecasted seismic activity. ORION is built using Python, and has an optional GUI where users can easily configure model parameters, evaluate temporal and spatial forecasts, and inspect key data (seismicity, fluid injection, pressure models, etc.).", + "laborHours": 0.0, + "languages": [], + "name": "Operational Forecasting of Induced Seismicity", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NRAP/orion", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "0.5" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-03-08", + "metadataLastUpdated": "2023-09-18" + }, + "description": "Thermal tank model that accounts for phase change of the tank medium.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "pytank (Python Thermal Tank Model) [SWR-22-76]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ThermalTank", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-03-10", + "metadataLastUpdated": "2024-01-29" + }, + "description": "The demand-side grid model harnesses decades of sector-specific energy modeling expertise to understand current and future U.S. electricity load for power systems analyses. The API provides tools for submitting datasets to dsgrid projects, validating individual datasets and project data as a whole, querying, analysis, and visualization.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook", + "Shell" + ], + "name": "dsgrid (Demand-Side Grid Toolkit) [SWR-21-52]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dsgrid/dsgrid", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-13", + "metadataLastUpdated": "2023-03-13" + }, + "description": "SF-23-005 PyOED is a highly extensible scientific package that enables developing and testing model-constrained optimal experimental design (OED) for inverse problems. Specifically, PyOED aims to be a comprehensive Python toolkit for model-constrained OED. The package targets scientists and researchers interested in understanding the details of OED formulations and approaches. It is also meant to enable researchers to experiment with standard and innovative OED technologies with a wide range of test problems (e.g., simulation models). OED, inverse problems (e.g., Bayesian inversion), and data assimilation (DA) are closely related research fields, and their formulations overlap significantly. Thus, PyOED is continuously being expanded with a plethora of Bayesian inversion, DA, and OED methods as well as new scientific simulation models, observation error models, and observation operators. These pieces are added such that they can be permuted to enable testing OED methods in various settings of varying complexities. The PyOED core is completely written in Python and utilizes the inherent object-oriented capabilities; however, PyOED is meant to be extensible rather than scalable. Specifically, PyOED is developed to ``enable rapid development and benchmarking of OED methods with minimal coding effort and to maximize code reutilization.'' PyOED will be continuously expanded with a plethora of Bayesian inversion, DA, and OED methods as well as new scientific simulation models, observation error models, and observation operators.", + "laborHours": 0.0, + "languages": [], + "name": "PYOED: AN ETENSIBLE SUITE FOR DATA ASSIMILATION AND MODEL-CONSTRAINED OPTIMAL DESIGN OF EXPERIMENTS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ahmedattia/pyoed", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-13", + "metadataLastUpdated": "2023-03-14" + }, + "description": "SF-22-160 Elastemp is a software to obtain the quasi-harmonic temperature dependent elastic constants of material. Elastemp integrates with VASP quantum-mechanical simulation package and with Phonopy package to perform dynamic calculations. Elastemp is capable of creating symmetry dependent deformations, run static and dynamic calculations to obtain the helmholtz energies from which quasi-harmonic temperature dependent elastic constants are obtained.", + "laborHours": 0.0, + "languages": [], + "name": "ELASTEMP", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Karthik-Balas/elastemp", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-13", + "metadataLastUpdated": "2023-03-14" + }, + "description": "SF-22-156 Machine learning (ML) models and applications in materials design and discovery typically involve the use of feature representations or descriptors followed by a learning algorithm that maps them to user desired properties of interest. Most popular mathematical formulation-based descriptors are not unique across atomic environments and suffer from transferability issues across different application domains and/or material classes. The CEGANN code provides a unified interface to facilitate material characterization across materials across multiple scales (from atomic to mesoscale) and diverse classes of materials ranging from metals oxides, non-metals, and even hierarchical materials such as zeolites and semi ordered materials such as mesophases. CEGANN implements a Graph Attention Network (GAT) type convolution architecture. The details of network architecture can be found in the paper https://doi.org/10.48550/arXiv.2207.10168. The software comes with pretrained examples and dataset for the classification of the following representative systems: (1) Structure-level representation such as space group (2) Structural dimensionality (e.g., bulk, 2D, clusters etc.) (3) Grain boundary identification (4) Nucleation and growth of a zeolite polymorph (5) Characterization of binary mesophases and their phase transitions (6) Growth of ice. The code is written in python programming language.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "CEGANN: CRYSTAL EDGE GRAPH ATTENTION NEURAL NETWORK", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sbanik2/CEGANN", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-03-13", + "metadataLastUpdated": "2023-03-13" + }, + "description": "MALAMUTE combines MOOSE module functionality with realistic materials and geometries for arbitrary-Eulerian-Lagrangian (ALE) and level-set based laser melting and welding applications and electric-field assisted sintering (EFAS) applications.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "idaholab/malamute", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/malamute", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2023-03-14" + }, + "description": "SF-22-157 NEML2 is an extension of an earlier open source code developed at ANL (SF-xxxx) called NEML. These libraries provide tools for constructing and using models of engineering materials, with a focus on high temperature materials for nuclear reactor applications. The software include tools for setting up material models, calibrating models, storing models for later use in other simulations, and running simple \"material point\" simulations of the material behavior. The main difference between NEML and NEML2 is the new software has been complete restructured to run on GPUs and other accelerators in order to improve the performance of methods used to train constitutive models against data and to improve the performance of the final models in production environments, like finite element software. While over time we expect NEML2 to become more-or-less feature complete with NEML we are filing a new software disclosure because (1) the library has been complete restructured and (2) we want to host NEML2 in a separate repository.", + "laborHours": 0.0, + "languages": [], + "name": "NEML2 - THE NEW ENGINEERING MATERIAL MODEL LIBRARY, VERSION 2", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/reverendbedford/neml2", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2023-03-14" + }, + "description": "GSAS-II is a comprehensive data analysis and simulation software package for determining atomistic structures from single-crystal and powder diffraction data. X-ray, neutron and electron data may be used. Constant-wavelength, time-of-flight and pink-beam sources may be employed and analyses may combine different types of data. The package is oriented towards materials characterization problems, but protein crystallography, pair-distribution function analysis, small-angle scattering and reflectometry analysis are all included. GSAS-II provides tools for indexing and solving structures from powder diffraction data, in addition to structure, data and results visualization tools", + "laborHours": 0.0, + "languages": [], + "name": "GSAS-II (GENERAL STRUCTURE AND ALAYSIS SYSTEM-II)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://subversion.xray.aps.anl.gov/pyGSAS/trunk", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2023-03-14" + }, + "description": "SF-22-136 Deep learning has been shown as a successful method for various tasks, and its popularity results in numerous open-source deep learning software tools. Deep learning has been applied to a broad spectrum of scientific domains such as cosmology, particle physics, computer vision, fusion, and astrophysics. Scientists have performed a great deal of work to optimize the computational performance of deep learning frameworks. However, the same cannot be said for I/O performance. As deep learning algorithms rely on big-data volume and variety to effectively train neural networks accurately, I/O is a significant bottleneck on large-scale distributed deep learning training. DLIO, is a novel representative benchmark suite built based on the I/O profiling of the selected workloads. DLIO can be utilized to accurately emulate the I/O behavior of modern deep learning applications. Using DLIO, application developers and system software solution architects can identify potential I/O bottlenecks in their applications and guide optimizations to boost the I/O performance leading to lower training times. The storage vendor can also use DLIO as a guide for designing and optimize the storage and filesystem targeting at deep learning application.", + "laborHours": 0.0, + "languages": [], + "name": "DLIO: A DATA-CENTRIC BENCHMARK FOR DEEP LEARNING APPLICATIONS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/argonne-lcf/dlio_benchmark", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A topology-based anomaly detection tool for temporal varying data. The input is json or CSV formatted data with a timestamp field identified. The algorithm computes vectorizations (using a vectorization config file) of time windows of data and computes a topological measure of anomalousness. The output is a sequence of anomaly scores for each time window", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/PHANTOM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/PHANTOM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Interconnection Innovation e-Xchange (i2x) Test Systems allows for scripted customizations of social behavior, recovery operations, investment decisions, and metrics in a simplified Python module. Public test systems allow for replication of results by other stakeholders", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/i2x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/i2x", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2023-03-14" + }, + "description": "SF-22-121 Graph convolutional neural networks (GCNN) are powerful machine learning models that apply a message-passing algorithm on adjacent nodes in a graph. Due to the natural representation of molecules via discrete graphs (where nodes encode atoms and edges encode bonds), GCNNs are an intuitive machine learning model chemical space informatics, including the prediction of polymer properties. Here, molecules are represented in feature and adjacency matrices where they are directly used as inputs to a GCNN.", + "laborHours": 0.0, + "languages": [], + "name": "GRAPH CONVOLUTIONAL NEURAL NETWORK (GCNN)FOR POLYMER PROPERTY PREDICTION", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AI4Plastics/AI4Plastics", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "luh1@ornl.gov" + }, + "date": { + "created": "2023-03-15", + "metadataLastUpdated": "2023-03-15" + }, + "description": "This is an opensource library for benchmarking the system's GPU mixed precision capabilities. The software calculates solution of the system of linear equation in 64bit accuracy using mixed precision techniques and iterative refinement. Original benchmark designed is done by ICL, and it is name HPL-MxP (HPL-AI)", + "laborHours": 0.0, + "languages": [ + "C++", + "C" + ], + "name": "OpenMxP-Opensource Mixed Precision Computing", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/at-aaims/openMxP", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-03-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Locally Competitive Algorithm (LCA) is a dynamical sparse solver that uses only local computations, allowing for massively parallel implementations on compatible neuromorphic architectures such as Intel's Loihi research chip. In this invention, we show how unsupervised dictionary learning with spiking LCA can be implemented on GPUs and Intel's Loihi research chip.", + "laborHours": 0.0, + "languages": [], + "name": "LCA", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/LCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-17", + "metadataLastUpdated": "2023-03-17" + }, + "description": "SF-22-099 Pressure-film Open Source Scanning and Mapping (POSSM) is software that analyses images of pressure-film (scans or photographs). POSSM collects data from that analysis in order to produce a number of visual aides, including pressure maps, histograms, and 3d surface plots. POSSM is designed to be able to analyze an entire folder full of images, exporting numeric data as .csv files and visual graphics as .png files.", + "laborHours": 0.0, + "languages": [], + "name": "PRESSURE-FILM OPEN SOURCE SCANNING AND MAPPING", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PatrickGrider/POSSM", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lagergrenjh@ornl.gov" + }, + "date": { + "created": "2023-03-20", + "metadataLastUpdated": "2023-03-21" + }, + "description": "In this work, we use few-shot learning to segment the body and vein architecture of Populus trichocarpa leaves from high-resolution scans obtained in the UC Davis common garden. Leaf and vein segmentation are formulated as separate tasks, in which convolutional neural networks (CNNs) are used to iteratively expand partial segmentations until reaching stopping criteria. Our leaf and vein segmentation approaches use just 50 and 8 manually traced images for training, respectively, and are applied to a set of 2,634 top and bottom leaf scans. We show that both methods achieve high segmentation accuracy, in some cases exceeding even human-level segmentation. The leaf and vein segmentations are subsequently used to extract 68 morphological traits using traditional open-source image processing tools, which are validated using real-world physical measurements. For a biological perspective, we perform a genome-wide association study using the \"vein density\" trait to discover novel genetic architectures associated with multiple physiological processes relating to leaf development and function. In addition to sharing all of the few-shot learning code, we are releasing all images, manual segmentations, model predictions, 68 extracted leaf phenotypes, and a new set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Few-shot leaf segmentation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jlager/few-shot-leaf-segmentation", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-03-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Home of PoolDilutionR, a package for easily calculating gross rates from isotope pool dilution data.", + "laborHours": 0.0, + "languages": [ + "R" + ], + "name": "COMPASS-DOE/PoolDilutionR", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/COMPASS-DOE/PoolDilutionR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-21", + "metadataLastUpdated": "2023-03-21" + }, + "description": "This is a variant of LaSDI where it minimizes both reconstruction loss terms of auto encoder and dynamics regression loss terms simultaneously. Plus, an active learning framework is adopted so that a physics-informed greedy sampling point can be added to enhance the performance of gLaSDI. It is written in python and several examples are included in this software.", + "laborHours": 0.0, + "languages": [], + "name": "Greedy Latent Space Dynamics Identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gLaSDI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "datepa@ornl.gov" + }, + "date": { + "created": "2023-03-22", + "metadataLastUpdated": "2023-03-28" + }, + "description": "A matrix-based simulator for neuromorphic computing.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ORNL/superneuro-mat", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/superneuromat", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "gunaratnecs@ornl.gov" + }, + "date": { + "created": "2023-03-22", + "metadataLastUpdated": "2023-03-28" + }, + "description": "A GPU-based multi-agent simulation framework for neuromorphic computing", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SuperNeuroABM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/superneuroabm", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-27", + "metadataLastUpdated": "2023-03-27" + }, + "description": "Productivity Frameworks for HPC will include container recipes, build recipes, continuous integration scripts, and other software aimed at testing the portability of containerized HPC software across platforms and interconnects. In particular, it tests the utility of bind-mounting at the MPI layer (rather than the underlying fabric layer) to leverage a standardized protocol and avoid various technical debt and vendor lock-in. Since MPIs are often ABI-incompatible, trampolines such as the open-source Wi4MPI will be tested when such cases arise.", + "laborHours": 0.0, + "languages": [], + "name": "Productivity frameworks for HPC", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/productivity-frameworks", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-03-28", + "metadataLastUpdated": "2023-03-29" + }, + "description": "The UEDGE Toolbox supplies an object-based interface and a wide array of tools used for running and analyzing UEDGE simulations. The toolbox provides routines for setting up UEDGE cases using YAML input files, shorthand commands for restoring converged solutions, as well as plotting profiles and surface plots of any of the parameters in UEDGE. Furthermore, the toolbox provides the necessary objects for compiling and analyzing parameter scans consisiting of several UEDGE simulations.", + "laborHours": 0.0, + "languages": [], + "name": "UEDGE toolbox", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/UETOOLS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-29", + "metadataLastUpdated": "2023-03-29" + }, + "description": "Linux kernel driver for the Cray ClusterStor E1000 NVMe slot LEDs. This driver allows us to set the 'fault' and 'locate' LEDs on a CrayE1000 slot to indicate which drive has failed. Is there", + "laborHours": 0.0, + "languages": [], + "name": "Linux kernel driver for Cray ClusterStor E1000 NVMe slot LEDs", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tonyhutter/e1000_nvme_led", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-03-30", + "metadataLastUpdated": "2023-05-08" + }, + "description": "Recently, numerous data-driven approaches to control an electric grid using machine learning techniques have been investigated. With the advancement of reinforcement learning (RL) based techniques, gradually the conventional optimization based solvers are being replaced with RL approach where there is uncertainty in the environment such as renewable generation or cyber system emulation. However, to train an agent efficiently, it requires numerous interactions with an environment to learn the best policies. There are numerous RL environments for the power systems based on some well-known simulators, similarly there are environment for communication domains. While majority of the cyber emulators are based in an UNIX environment, the power simulators are based in the Windows-based operating system, the generation of cyber-physical mixed domain RL environment has been challenging. Existing co-simulation methods are efficient but resource and time intensive to generate large scale data set for training RL agents. Hence, this software focuses on development and validation of a mixed domain RL environment using Open DSS for the physical side and leverages a discrete event simulator python package, SimPy, for cyber-side emulation which is Operating Systems agnostic. Further utilizing this software co-simulation and training RL agents for re-routing based resilient control for network reconfiguration and volt-var control in power distribution feeder are performed.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DSS-SimPy-RL (Open-DSS and SimPy based Cyber-Physical RL environment) [SWR-23-29]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DSS-SimPy-RL", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-03-30", + "metadataLastUpdated": "2023-04-06" + }, + "description": "Accurate energy forecasting is becoming critical due to many reasons: i ) optimal distributed energy resources operations and dispatch, ii) fault detection and diagnostics, and iii) meeting operational energy efficiency targets. Wattile uses deep learning (DL) for the building's short-term load forecasting application. Two specific types of neural networks called, Long Short Term Memory (LSTM) and Sequence-to-Sequence (S2S) models are used to make predictions. Forecasting models are trained using online historical weather and occupancy indicator data streams from the Intelligent Campus Program's data acquisition systems at the National Renewable Energy Laboratory (NREL) for main meters and sub-meters of multiple building types. These models use probabilistic methods to provide quantile-based forecasts in addition to nominal conditional median predictions of electricity consumption.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "Wattile: Probabilistic Deep Learning-based Forecasting of Building Energy Consumption [SWR-20-94]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Wattile", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-03-31", + "metadataLastUpdated": "2023-03-31" + }, + "description": "xCDAT is an extension of xarray for climate data analysis on structured grids. It serves as a modern successor to the Community Data Analysis Tools (CDAT) library. Xarray is an \"open source project and Python package that introduces labels in the form of dimensions, coordinates, and attributes on top of raw NumPy-like arrays, which allows for more intuitive, more concise, and less error-prone user experience. Xarray includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures\" (source: https://xarray.dev/). The goal of xCDAT is to provide generalizable features and utilities for simple and robust analysis of climate data. xCDAT's design philosophy is focused on reducing the overhead required to accomplish certain tasks in xarray. Some key xCDAT features are inspired by or ported from the core CDAT library, while others leverage powerful libraries in the xarray ecosystem (e.g., xESMF and cf_xarray) to deliver robust APIs.", + "laborHours": 0.0, + "languages": [], + "name": "Xarray Climate Data Analysis Tools", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xCDAT/xcdat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.5.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-04-04", + "metadataLastUpdated": "2023-04-04" + }, + "description": "The ezAlign is aimed at clustering coarse grain simulation to find common or uncommon occurrences and convert coarse (CG) grained coordinate and topology files to atomistic formats. We use a PointNet based approach to map individual frames of simulation to points in a latent space. These points are then clustered using a variety of clustering methods. Clusters are analyzed to associate them with states in the simulation. Frames can be chosen from these clusters based on proximity to cluster centers. ezAlign takes CG coordinate and topology files and converts and outputs their corresponding atomistic formats using an alignment and relaxation procedure. ezAlign is designed to convert complex, solvated biological systems including lipid membranes with drug-like molecules using GROMACS. A GROMACS checkpoint (.cpt) file is also outputted to enable continuation simulations that retain the equilibrated atomic velocities. Independent atomistic coordinates and topologies for every molecule must already be included in ezAlign/files. A number of commonly simulated biological molecules are currently provided.", + "laborHours": 0.0, + "languages": [], + "name": "ezAlign", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ezAlign", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "morelandkd@ornl.gov" + }, + "date": { + "created": "2023-04-04", + "metadataLastUpdated": "2023-04-05" + }, + "description": "VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures. VTK-m supports the fine-grained concurrency for data analysis and visualization algorithms required to drive extreme scale computing by providing abstract models for data and execution that can be applied to a variety of algorithms across many different processor architectures.", + "laborHours": 204652.8, + "languages": [ + "C++" + ], + "name": "VTK-m v. 2.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk-m", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "2.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-04-05", + "metadataLastUpdated": "2023-11-27" + }, + "description": "EMF Biomass Data Interpreter was developed for the transportation team of the Energy Modeling Forum (EMF) 37: Deep Decarbonization and High Electrification Scenarios for North America project. It parses results from different modeling groups to show how biomass might be employed under electrification.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "EMF Biomass Data Interpreter [SWR-23-06]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMF_Data_Interpreter", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-04-06", + "metadataLastUpdated": "2023-04-06" + }, + "description": "GHEDesigner is a Python package for designing ground heat exchangers (GHE) used with ground source heat pump (GSHP) systems.", + "laborHours": 0.0, + "languages": [ + "PYTHON" + ], + "name": "GHEDesigner [SWR-23-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BETSRG/GHEDesigner", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-04-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "NetViz is an app built to visualize communication and power networks. Developed under the CINDER project at PNNL.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Netviz", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Netviz", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-04-13", + "metadataLastUpdated": "2023-04-13" + }, + "description": "The AMG2023 benchmark solves two diffusion problems with a linear solver preconditioned with algebraic multigrid. The code only contains a driver, a Makefile, and a documentation file. It requires an installation of the open source software library hypre that needs to be downloaded elsewhere and is not included here. Its purpose is to benchmark linear solver performance on high performance computers.", + "laborHours": 0.0, + "languages": [], + "name": "AMG2023", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AMG2023", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-04-13", + "metadataLastUpdated": "2023-04-13" + }, + "description": "This code along with the included data allows users to train machine learning models on network packet data.", + "laborHours": 0.0, + "languages": [], + "name": "IdahoLabResearch/INLIDD", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/INLIDD", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-04-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This research code base includes functions to compute statistics of image distributions in (spatial DFT) frequency space, train deep learning image classifiers on these distributions with variable depth and weight decay, and finally measure the sensitivity of the trained models to perturbations along (spatial DFT) frequency components.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/frequency_sensitivity", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/frequency_sensitivity", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-04-14", + "metadataLastUpdated": "2023-11-01" + }, + "description": "The Xyce Parallel Electronic Simulator simulates electronic circuit behavior in DC, AC, HB, MPDE and transient mode using standard analog (DAE) and/or device (PDE) device models including several age and radiation aware devices. It supports a variety of computing platforms (both serial and parallel) computers. Lastly, it uses a variety of modern solution algorithms dynamic parallel load-balancing and iterative solvers.! ! Xyce is primarily used to simulate the voltage and current behavior of a circuit network (a network of electronic devices connected via a conductive network). As a tool, it is mainly used for the design and analysis of electronic circuits.! ! Kirchoff's conservation laws are enforced over a network using modified nodal analysis. This results in a set of differential algebraic equations (DAEs). The resulting nonlinear problem is solved iteratively using a fully coupled Newton method, which in turn results in a linear system that is solved by either a standard sparse-direct solver or iteratively using Trilinos linear solver packages, also developed at Sandia National Laboratories.", + "laborHours": 0.0, + "languages": [ + "C++", + "Perl", + "Python" + ], + "name": "Xyce(™) Parallel Electronic Simulator v.7.6", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Xyce/Xyce", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "7.6" + }, + { + "contact": { + "email": "kerteszv@ornl.gov" + }, + "date": { + "created": "2023-04-19", + "metadataLastUpdated": "2023-04-19" + }, + "description": "Support for the following electrochemical techniques: · cyclic voltammogram (CV) · linear sweep voltammogram (LSV) · differential pulse voltammogram (DPV) · chronoamperometry (CA) Specific application: low-cost DIY potentiostat, demonstrating electrochemistry in the educational sector", + "homepageURL": "https://u.pcloud.link/publink/show?code=XZyeQqVZWfpzv3qm0HJ40WFUBDEmzhUcJfP7", + "laborHours": 0.0, + "languages": [ + "Delphi/Object Pascal" + ], + "name": "HunStat v4.10", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://u.pcloud.link/publink/show?code=XZyeQqVZWfpzv3qm0HJ40WFUBDEmzhUcJfP7", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "4.10" + }, + { + "contact": { + "email": "radercd@ornl.gov" + }, + "date": { + "created": "2023-04-24", + "metadataLastUpdated": "2023-04-24" + }, + "description": "Boiler tubes in steam power plants experience tube blockages due to exfoliation of oxide grown on the inner side of the tubes. In extreme cases, significant tube blockages can lead to forced power plant outages. It is thus desired to predict through modeling the amount of tube blockage in order to inform power plant operators of possible forced outages. SpalLoop solves for the stress-strain equations in an axisymmetric geometry, tracking the stress/strain evolution during boiler operation including outages for the entire boiler tube length. At each operational outage, i.e., temperature excursions down to room temperature, the amount of exfoliated area for the entire tube loop is estimated the amount of tube blockage is predicted based assumed blockage geometry and site. The SpaLLoop code contains modules developed for oxide growth, stress analysis, tube loop geometry, blockage area by taking into account the following phenomena and features, (a) Plant operation schedule with periodic alternate full-load and partial-load regimes and shut-downs, i.e., temperature excursions from high-load to room temperature, (b) axisymmetric formulation for cylindrical tubes, (c) oxide growth in a temperature gradient with multiple oxide layers, (d) geometry of a boiler tube with a single tube loop or two tube loops, (e) temperature variation along the tube length based on hot gas temperature distribution outside the tube and inlet steam temperature, (f) non-uniform oxide growth along the tube length according to the local steam tube temperature, (g) exfoliated area module: at each operational outage considered, the amount of exfoliated area and exfoliated volume along the tube is estimated, (h) blockage module: at each operational outage considered, the exfoliated volume/mass for each tube loop is estimated from which the amount of tube blockage is predicted based on given blockage geometry (length, location, and geometry). The computer program is written in FORTRAN90. Its modular structure was sought for allowing the best flexibility in updating the program by implementing new constitutive equations due to availability of new material property data and/or new physical phenomena.", + "laborHours": 0.0, + "languages": [ + "Fortran90" + ], + "name": "SPALLOOP", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/adisoft17/spallop/blob/master/License_Spalloop_OpenSourceSoftware_ORNL.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/adisoft17/spallop", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-04-24", + "metadataLastUpdated": "2023-04-24" + }, + "description": "CMEC driver is a command line tool that runs earth system evaluation modules.", + "laborHours": 0.0, + "languages": [], + "name": "CMEC driver", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmecmetrics/cmec-driver", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.1.9" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "Geospatial Analysis Pipelines (GAPs) is a framework designed to scale single-location geospatial models to a High-Performance Computing (HPC) environment.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "GAPs (Geospatial Analysis Pipelines)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/gaps", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-05-03" + }, + "description": "Multiverse is a code repository for a set of tools for Bayesian model selection for neural networks. The goal of the tools is to provide capabilities for selecting among prior and model specifications for Bayesian neural networks. Multiverse will include tools for creating Bayesian neural networks, evaluating the Bayesian model evidence, and performing inference in Bayesian neural networks. These components are written in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning and signal processing.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Multiverse: Bayesian model selection for neural networks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "The software is code for analyzing, debugging, and solving optimization models. The code implements several algorithms and provides convenient APIs to apply these algorithms to optimization models. The algorithms are primarily based on graph theory. They compute well-known partitions of graphs, and use these partitions to provide the user information about their optimization model, including diagnosing certain types of structural modeling errors. Some algorithms may be used as a subroutine to solve an optimization problem, and may call an optimization solver to facilitate this. Well-known linear algebra routines are called to provide further diagnostics. The software contains no data and no models other than toy models used for testing.", + "laborHours": 0.0, + "languages": [], + "name": "Tools for analysis of optimization models", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/JuMPIn.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "DEPDOSE is an open-source computer application which combines the KDEP respiratory tract deposition software with committed equivalent dose coefficient tables from the DC_PAK internal dosimetry package. DEPDOSE allows the user to rapidly produce tables of dose coefficients to workers and members of the public inhaling a precisely defined, user-specified aerosols using the ICRP 60 series methodology. Combined with a plume dispersion modeling system such as QUIC, this makes it possible to predict radiation doses downstream from an accidental or intentional release of radioactive materials. For this work, a radioactive plume was calculated to members of the public downstream from a plausible release of radionuclides into the atmosphere.", + "laborHours": 0.0, + "languages": [], + "name": "DEPDOSE", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/DEPDOSE", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "shasta wrapper was written as an interface with which to manage clusters running CSM (Cray System Management) with the purpose being: * Showcase the shortcomings of the provided Cray System Management software to the vendor * Provide practical and easy to use tool to manage a clsuter running Cray System Management", + "laborHours": 0.0, + "languages": [], + "name": "Shasta Wrapper", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/shasta_wrapper", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-05-03" + }, + "description": "FIERRO is a parallel C++ code designed to simulate fluid mechanics, heat transfer, and solid mechanics in two- and three-dimensional space. 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The micromechanical solvers can also help research efforts create continuum-scale constitutive models for solids, as a function of the microstructure, in situ in a calculation or in a stand-alone manner. No physical data exists within the code.", + "laborHours": 0.0, + "languages": [], + "name": "Fierro Version 2.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Fierro", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "2.x" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "MATAR is a C++ software library to allow developers to easily create and use dense and sparse data representations that are also portable across disparate architectures using Kokkos.", + "laborHours": 0.0, + "languages": [], + "name": "Matrix and Array (MATAR) Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MATAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stewartsl@ornl.gov" + }, + "date": { + "created": "2023-04-27", + "metadataLastUpdated": "2023-04-27" + }, + "description": "The Interactive Corpus Analysis Tool (ICAT) is an interactive machine learning dashboard for unlabeled text/natural language processing datasets that allows a user to iteratively and visually define features, explore and label instances of their dataset, and simultaneously train a logistic regression model. ICAT was created to allow subject matter experts in a specific domain to directly train their own models for unlabeled datasets visually, without needing to be a machine learning expert or needing to know how to code the models themselves. This approach allows users to directly leverage the power of machine learning, but critically, also involves the user in the development of the machine learning model.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Interactive Corpus Analysis Tool", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/icat", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "brownjm@ornl.gov" + }, + "date": { + "created": "2023-04-27", + "metadataLastUpdated": "2023-04-27" + }, + "description": "Julia language version of the SAMMY R-matrix code", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "Jammy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/brownjm1968/Jammy", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-04-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Python tool for determination of lipid double bond locations from OzID data", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-m-q/lipidoz", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-m-q/lipidoz", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "xuanji.yu@case.edu" + }, + "date": { + "created": "2023-04-29", + "metadataLastUpdated": "2023-04-29" + }, + "description": "PV Performance Loss Rate Estimation using Spatio-temporal Graph Neural Networks\n\nPVplr-stGNN is a Python 3 package developed by the SDLE Research Center at Case Western Reserve University in Cleveland OH. This repository contains the full source PVplr-stGNN package. The package contains the PV-stGAE for missingness data detection and imputation and PV-DynGNN for PLR estimation.", + "homepageURL": "https://pypi.org/project/PVplr-stGNN", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PVplr-stGNN 0.1.10", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://pypi.org/project/PVplr-stGNN", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "version": "0.1.10" + }, + { + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2023-05-01", + "metadataLastUpdated": "2023-05-01" + }, + "description": "HydraGNN is an Oak Ridge National Laboratory (ORNL)-branded implementation of distributed multi-tasking graph neural networks that supports several scientific applications within the ORNL portfolio to support the US-DOE mission.\n\nNew or improved capabilities included in v2.0.0 release are as follows:\n\n1) Enhancement in message passing layers through class inheritance\n2) Adding transformation to ensure translation and rotation invariance\n3) Supporting various optimizers\n4) Atomic descriptors\n5) Integration with continuous CI test\n6) Distributed printouts and timers\n7) Profiling\n8) Support of ADIOS2 for scalable data loading\n9) Large-scale system support, including Summit (ORNL) and Perlmutter (NERSC)", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HydraGNN 2.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/HydraGNN/releases/tag/v2.0.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v2.0.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-02", + "metadataLastUpdated": "2023-05-02" + }, + "description": "The Coda Envelope Ratio Tool (CERT) allows for calculating seismic envelopes from waveforms and measuring the amplitude ratios for multiple events against each other to invert for seismic source information. The methodology is based on Walter, W. R., Yoo, S.-H., Mayeda, K., and Gök, R. (2017), Earthquake stress via event ratio levels: Application to the 2011 and 2016 Oklahoma seismic sequences, Geophys. Res. Lett., 3147- 3155, 44, doi:10.1002/2016GL072348.", + "laborHours": 47712.8, + "languages": [], + "name": "Coda Envelope Ratio Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/coda-calibration-tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.19" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-02", + "metadataLastUpdated": "2023-05-02" + }, + "description": "mkite is a distributed computing platform for materials simulation. mkite is built with the server-client pattern, decoupling production databases from client runners. When used in combination with message brokers, mkite enables any available client to perform calculations without prior hardware specification on the server side. Furthermore, the software enables the creation of complex workflows with multiple inputs and branches, facilitating the exploration of combinatorial chemical spaces. The mkite suite provides recipes and tools to interact with package such as VASP, but is extensible to any other simulation package. Finally, mkite helps keeping the provenance of calculations in a SQL database. A complete description of the software is available at https://arxiv.org/abs/2301.08841.", + "laborHours": 0.0, + "languages": [], + "name": "mkite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mkite-group/mkite_db", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "set of data collection forms implemented as a web app to be used for quality assurance purposes by residential efficiency contractors during the installation process. There are data collection forms for several efficiency measures including heat pump, heat pump water heater, attic weatherization, and basement weatherization.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Remote-QA-Web-App", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Remote-QA-Web-App", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-05-04", + "metadataLastUpdated": "2023-05-30" + }, + "description": "A python library to aid in modeling and understanding light- and elevated temperature-induced degradation (LETID) and boron-oxygen light-induced degradation (B-O LID) in silicon solar cells and wafers\n\nhttps://github.com/NREL/PVDegradationTools/blob/main/pvdeg/letid.py\nhttps://github.com/NREL/PVDegradationTools/blob/main/pvdeg/collection.py", + "laborHours": 3617.6, + "languages": [ + "PYTHON" + ], + "name": "pyletid [SWR 23-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PVDegradationTools", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-05-04", + "metadataLastUpdated": "2023-05-05" + }, + "description": "PVAnalytics inputs long term (multiple years) photovoltaic (PV) outdoor sensor data and completes autonomous quality assurance (QA) analysis on the data. Time series data from individual sensors such as electric meters, inverter outputs, irradiance, and temperature sensors are compared to physically expected outputs of these sensors under clear sky conditions based on the latitude, longitude, and orientation of the PV system. PVAnalytics outputs as QA pass or fail for each sensor, reasons determined for failure, time series flags identifying QA thresholds have been exceeded, flags for sunny days, the time zone found for the given sensor, sensor drift, time periods for passing data, and results of orientation checks.", + "laborHours": 0.0, + "languages": [ + "python" + ], + "name": "PVAnalytics [SWR-20-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pvlib/pvanalytics", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.3" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "BoltzmannMFX is a biological simulation code that solves chemical reaction networks using maximum entropy methods. It uses modules from MFiX-Exa and is based on the AMReX framework for massively parallel block-structured adaptive mesh applications.", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-CompBio/BoltzmannMFX", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/BoltzmannMFX", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The QC-GN2OMS2 neural network was designed to predict mass spectra better than currently available approaches. Fundamentally the neural net is designed to input the structure of a molecule and collision energy value then output a spectra datafile for the end user. This software is able to make predictions orders of magnitude faster (milliseconds) than QC methods and with 50-60% greater accuracy than rules approaches.", + "laborHours": 0.0, + "languages": [], + "name": "QC-GN2OMS2", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-m-q/qcgnoms", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2023-05-08" + }, + "description": "Compiler optimizations can alter the numerical results of scientific computing applications. When numerical results differ significantly between compilers, optimization levels, and floating-point hardware, these numerical inconsistencies can impact programming productivity. Ciel is a framework that helps programmers identify locations in the source code that are affected by compiler optimizations in CPU and GPU code. Ciel uses a floating-point precision enhancement strategy, guided by a recursive bisection search algorithm with increasing search granularity, to identify the program expressions that induce numerical inconsistencies due to compiler optimizations.", + "laborHours": 0.0, + "languages": [], + "name": "Ciel", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Ciel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2023-05-09" + }, + "description": "PhaseTorch is a python package that implements algorithms for forward and inverse problem solutions in X-ray phase contrast tomography (XPCT). XPCT is useful to reconstruct the 3D distribution of the refractive index decrement and absorption index of an imaged object. PhaseTorch implements algorithms for simulation, reconstruction, and analysis of XPCT data. PhaseTorch provides algorithms for simulation of XPCT data of an object with known refractive and absorption indices. It contains algorithms for reconstructing the projections of the absorption index and refractive index decrement. ", + "laborHours": 0.0, + "languages": [], + "name": "Algorithms for Forward and Inverse Problem Solutions in Phase Contrast Tomography", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/phasetorch/phasetorch", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2023-05-08" + }, + "description": "\tThe CRT Command Line Interface is a software tool released as public domain software in 2007 by Charles Bland and can be downloaded under http://www.room220.com/crt/.\n\nThe last CRT-CLI release update was in 2008 and bumped up its version number to 1.2.\n\nWe used the CRT-CLI tool in our IMG Annotation Pipeline and over the years modified the original code based on suggestions made by our in-house experts to add more functionality, e.g. being able to detect truncated repeats at the edge of sequences or repeats containing Ns, additional output file options, and additional identity and similarity control parameters.", + "laborHours": 0.0, + "languages": [], + "name": "\tCRISPR Recognition Tool (CRT) - Command Line Interface (IMGAP Version) (CRT-CLI) v1.8.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/img/img-pipelines/crt-cli-imgap-version", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "sarat@ornl.gov" + }, + "date": { + "created": "2023-05-09", + "metadataLastUpdated": "2023-05-09" + }, + "description": "Performance Analytics for Computational Experiments (PACE) is an end-to-end performance monitoring infrastructure to summarize performance data collected from Department of Energy’s (DOE) climate model experiments to derive insights and present them through a web portal. PACE automatically captures provenance/timing data from simulations run on DOE supercomputers.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "PACE", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/pace", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-05-11", + "metadataLastUpdated": "2023-05-22" + }, + "description": "The Hydrogen Financial Analysis Scenario Tool, H2FAST, provides a quick and convenient in-depth financial analysis for hydrogen and nonhydrogen systems and services.\n\nH2FAST is available as a downloadable Excel spreadsheet. The model uses a generally accepted accounting principles analysis framework and provides annual projections of income statements, cash flow statements, and balance sheets. H2FAST allows users to generate a side-by-side scenario analysis, where a base system can be tested by varying key operating or financing parameters. Detailed capital structure, taxation, and incentives are included. The model has built-in risk analysis allowing impact assessment of parameters bearing user-specified uncertainty ranges. Financial articulation is presented in graphical and tabular format for the user-specified analysis period. The model is self-documented, with embedded help functions and annotation of input parameters.\n\nNote: The model is also flexible for providing analysis for International Financial Reporting Standards by adjusting inputs for compliance with their rules.\n\nThe H2FAST framework has been used for analysis of a variety of systems, e.g., retail hydrogen refueling stations with incentives analysis, ammonia production, methane pyrolysis, seasonal energy storage, hydrogen fleet operations, electric vehicle charging with time of use rate structures, combined heat and power systems, hydrogen production pathways, and hydrogen transmission and distribution. The example cases available for download are intended to demonstrate model functionality and should be populated with user-specific analysis values such as CapEx, OpEx, and capital structure.", + "homepageURL": "https://www.nrel.gov/hydrogen/h2fast.html", + "laborHours": 0.0, + "languages": [ + "Excel" + ], + "name": "H2FAST: Hydrogen Financial Analysis Scenario Tool [SWR 15-06]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/hydrogen/assets/pdfs/h2fast_spreadsheet_user_manual.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/hydrogen/h2fast.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-05-17", + "metadataLastUpdated": "2023-05-22" + }, + "description": "Provides an XSD framework within the Common Information Model – IEC 61970 Part 7 – for the integration of dynamic line ratings within the utility software systems. 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The variables are read and the desired values are taken and added to an array in the correct format. This array is then converted into a python array for future use. The code also utilizes MATPOWER's ability to construct different power flow scenarios and repeat them a chosen number of times. Each iteration will add a new line to the formatted array so that the final output is a matrix has a height equal to the number of repetition used.", + "laborHours": 0.0, + "languages": [ + "Matlab Programming Language" + ], + "name": "Training Data Regarding Optimal Power Flow For Efficient Machine Learning", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/TROPFE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2023-05-19", + "metadataLastUpdated": "2023-05-19" + }, + "description": "A framework for developing modular software.", + "laborHours": 0.0, + "languages": [], + "name": "NWChemEx-Project/PluginPlay", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NWChemEx-Project/PluginPlay", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Confidence Estimation for Mass Spectrometry Proteomics. Crema is an open-source Python tool that estimates the false discovery rate (FDR) of a set of peptide-spectrum matches\nthat result from proteomics data analysis. Crema implements standard FDR estimation methods that are widely used within\nthe field. This package is meant to be simple, easy to use, stand-along, and easy to maintain.", + "laborHours": 0.0, + "languages": [], + "name": "Noble-Lab/crema", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Noble-Lab/crema", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Evaluates the reserve requirements for power system balancing areas based on variability and uncertainty of load as well as wind and solar generation scenarios. The tool uses minute‐by‐minute site‐specific generation and load information, as well as information from generation and load forecasting algorithms used in the balancing areas. The Balancing‐Plan Tool can be used directly by utility planners and operators to aid in the integration of intermittent renewable resources. The tool provides reserve requirements of various kinds, such as day‐ahead, load following and regulation, as well as estimates the capacity of the generation fleet to provide the require reserves.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "GRAF-Plan for Vietnam", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The invention is a set of algorithms and calculations for a performance-based\nmodel to translate wildfire burn potential to actual transmission line outages\nin real-time in an interactive application that uses geospatial data sets on the\nwildfire burn potential as well as detailed grid topographical datasets.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Wildfires Risk Evaluation of the System (WiRES) Framework Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-25", + "metadataLastUpdated": "2023-05-25" + }, + "description": "THE DATA SCIENCE INSTITUTE WILL BE INVITING STUDENTS FROM UC MERCED AND UC\nRIVERSIDE TO PARTICIPATE IN A DATA SCIENCE CHALLENGE AT LLNL. IN THE CHALLENGE,\nTHE STUDENTS WILL EXPLORE A DATA-DRIVEN APPROACH TO RECONSTRUCTING ELECTROANATOMICAL\nMAPS OF THE HEART AT CLINICALLY RELEVANT RESOLUTIONS, COMBINING\nINPUT FROM THE STANDARD 12-LEAD ECG WITH ADVANCED MACHINE LEARNING\nTECHNIQUES. THE DATA THE STUDENTS WILL HAVE ACCESS TO HAS BEEN IM REVIEWED FOR\nEXTERNAL RELEASE. (LLNL-MI-835833) THESE NOTEBOOKS WILL PROVIDE THE STUDENTS\nWITH INSTRUCTIONS OF HOW TO LOAD THE DATA AND WORK WITH THE DATA, ALONG WITH\nTUTORIALS TO DO BASIC MACHINE LEARNING TASKS LIKE LOGISTIC REGRESSION AND IMAGE\nCLASSIFICATION.", + "laborHours": 0.0, + "languages": [], + "name": "2023 Data Science Challenge Notebooks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/landajuela/cardiac_challenge", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-31", + "metadataLastUpdated": "2023-05-31" + }, + "description": "DFTF converts Redfish events to messages on a Kafka bus. DFTF subscribes to events in Redfish,\nspecifically Alerts and CrayTelemetry. It listens for HTTP POST requests containing event data, reduces\nthe data, serializes the reduced data using Avro, and publishes the data to topics in Kafka.", + "laborHours": 0.0, + "languages": [], + "name": "Drink From The Firehose", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/dftf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-05-31", + "metadataLastUpdated": "2023-06-07" + }, + "description": "SAND2021-6722 O\nThis is a fitness tracking mobile application and server created to train college-level students to build full stack software. The front end is written using an open-source framework called Flutter. The API server is written using an open-source python framework called Flask. The app functions as a workout tracker and is intentionally partially functional for the purpose of training students during the live workshops hosted by Sandia's HR recruiting teams. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Dart", + "Python" + ], + "name": "NSU Hack-a-Thon Workshop v.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ohon3/sandia-hackathon-fall2021", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-06-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software was developed to solve the problem of curating and validating individual metabolic models and combining\nthem into different consortia.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl-predictive-phenomics/concerto", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/concerto", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-09-18" + }, + "description": "This software supports the paper, \"Exploring the scaling limitations of the variational quantum eigensolver with the bond dissociation of hydride diatomic molecules,\" published in the International Journal of Quantum Chemistry, whose abstract is as follows: Materials simulations involving strongly correlated electrons pose fundamental challenges to state-of-the-art electronic structure methods but are hypothesized to be the ideal use case for quantum computing. To date, no quantum computer has simulated a molecule of a size and complexity relevant to real-world applications, despite the fact that the variational quantum eigensolver (VQE) algorithm can predict chemically accurate total energies. Nevertheless, because of the many applications of moderately-sized, strongly correlated systems, such as molecular catalysts, the successful use of the VQE stands as an important waypoint in the advancement toward useful chemical modeling on near-term quantum processors. In this paper, we take a significant step in this direction. We lay out the steps, write, and run parallel code for an (emulated) quantum computer to compute the bond dissociation curves of the TiH, LiH, NaH, and KH diatomic hydride molecules using VQE. TiH was chosen as a relatively simple chemical system that incorporates d orbitals and strong electron correlation. Because current VQE implementations on existing quantum hardware are limited by qubit error rates, the number of qubits available, and the allowable gate depth, recent studies have focused on chemical systems involving s and p block elements. Through VQE + UCCSD calculations of TiH, we evaluate the near-term feasibility of modeling a molecule with d-orbitals on real quantum hardware. We demonstrate that the inclusion of d-orbitals and the use of the UCCSD ansatz, which are both necessary to capture the correct TiH physics, dramatically increase the cost of this problem. We estimate the approximate error rates necessary to model TiH on current quantum computing hardware using VQE+UCCSD and show them to likely be prohibitive until significant improvements in hardware and error correction algorithms are available.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "tih_vqe [SWR-23-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/tih-vqe", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2024-07-01" + }, + "description": "OCHRE™ Gymnasium is a Python framework for conducting reinforcement learning research on residential building energy management problems. It is a lightweight wrapper around OCHRE, a Python-based thermal-electric residential building simulator developed in-house at NREL. OCHRE Gymnasium adheres to the standard OpenAI Gym API for a reinforcement learning environment. Detailed Sphinx documentation will be auto-generated and accompany this codebase. This documentation will detail the API, provide examples of how to use the code, etc.", + "laborHours": 29928.8, + "languages": [ + "Python" + ], + "name": "OCHRE™ Gymnasium (ochre_gym) [SWR-23-47]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ochre_gym", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2024-06-05" + }, + "description": "A Python package for directed evolution on a protein sequence with gradient-based discrete Markov chain monte carlo (MCMC). Users are able to compose custom models that map sequence to function with pretrained models, including protein language models (PLMs), to guide and constrain search. Our package natively integrates with the HuggingFace platform and supports PLMs from transformers.\n\nOur MCMC sampler identifies promising amino acids to mutate via model gradients taken with respect to the input (i.e., sensitivity analysis). We allow users to compose their own custom target function for MCMC by leveraging the Product of Experts MCMC paradigm. Each model is an \"expert\" that contributes its own knowledge about the protein's fitness landscape to the overall target function. The sampler is designed to be more efficient and effective than brute force and random search while maintaining most of the generality and flexibility.\n\nAdditional information can be found in the related publication: https://iopscience.iop.org/article/10.1088/2632-2153/accacd", + "laborHours": 820.8, + "languages": [ + "PYTHON", + "Jupyter Notebook" + ], + "name": "EvoProtGrad (Directed Evolution for Proteins with Gradients) [SWR-23-48]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EvoProtGrad", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-08-28" + }, + "description": "The residential and commercial building stock in the United States is responsible for a significant percentage of energy consumption and greenhouse gas emissions. Electrification of end-uses, as well as decarbonizing the electrical grid through renewable energy sources such as solar and wind, constitutes the pathway to zero-emission buildings. Forecasting day-ahead building energy consumption is an integral part of this solution. Currently, specialized forecasting models are hand-made for each individual building, which is time-consuming, expensive, and leads to duplicated efforts. BuildingsBench is a Python software framework for training and comparing generalized machine learning models for universal building load forecasting. This challenge tasks a single foundational model to generalize its forecasts for a wide variety of buildings, across geographic regions, building types, weather patterns, and more. This software provide code for pre-training such models and subsequently evaluating their performance on a suite of hundreds of diverse real and synthetic buildings.\n\nBuildingsBench is a platform for:\n\n- Large-scale pretraining with the synthetic Buildings-900K dataset for short-term load forecasting (STLF). Buildings-900K is statistically representative of the entire U.S. building stock and is extracted from the NREL End-Use Load Profiles database.\n\n- Benchmarking on two tasks evaluating generalization: zero-shot STLF and transfer learning for STLF.\n\nWe provide an index-based PyTorch Dataset for large-scale pretraining, easy data loading for multiple real building energy consumption datasets as PyTorch Tensors or Pandas DataFrames, simple (persistence) to advanced (transformer) baselines, metrics management, and more.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "BuildingsBench: A Benchmark for Universal Building Load Forecasting [SWR-23-51]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BuildingsBench", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "A new version of the verification tool ExactPack, 1.7.0, includes three new solvers: A Radshocks solver, Riemann solver and an Elastic-Plastic Piston problem solver. The code has been refactored to work with Python 3. All Fortran code has been removed and solvers implemented in Fortran have been re-implemented in Python where necessary. All unit tests have been converted to use the Pytest format and all the GUI, CLI and verification analysis code has been removed.", + "laborHours": 0.0, + "languages": [], + "name": "ExactPack", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ExactPack", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "Understanding how inaccuracies in visualizations affect users’ perception and understanding of scientific data is hard. Inaccuracies in visualizations are quite common and could arise from a range of sources such as errors in the original dataset arising from compression artifacts, errors in the capturing device, noise during transmission of the data, effects due to the algorithm being used to convert data to visualization images, images generated from neural networks, and sources we have yet to discover. Many image quality assessment metrics have been developed to quantify image errors. However, these are usually focused on “natural images” rather than visualizations of scientific data. Common image quality assessment metrics (IQAs) include MSE, PSNR, perceptual metrics such SSIM, FSIM as well as perceptual metrics using deep learning approaches. However, a critical part of understanding how errors are perceived by humans, and subsequently developing more accurate quality assessment metrics, is through user evaluation studies.\n\nThe goal of this software is to develop a visualization quality assessment (VQA) process that will enable the generation of VQAs that can be used to quantify errors in scientific data visualizations. The VQA development process will include software to support user evaluation experimental design, analysis of visualization differences against standard quality metrics, and the ability to develop additional VQA metrics specific to scientific visualization images. ", + "laborHours": 0.0, + "languages": [], + "name": "Visualization Quality Assessment", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vizStudy", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-06" + }, + "description": "Light-matter interactions play an important role in many branches of physics, chemistry, energy, and materials science. In the strong coupling regime, light-matter interactions are able to tune the materials properties via the formation of new quasiparticles, such as plasmons and polaritons. However, theoretical and numerical modeling of the light-matter interaction-mediated processes remain a big challenge because light-matter interactions are fundamentally multiscale and multiphysics problems involving multiple interactions between electrons, nuclei, and photons at different time/length scales. In the current community, light-matter interactions were treated at different levels of theoretical complexity in quantum chemistry and quantum optics. In quantum optics or quantum photonics, the matter is usually simplified as a few-level system, and the light is treated quantum-mechanically. On the other hand, quantum chemistry explores first-principles methods, including both single-particle and many-body-based techniques, to describe the electronic properties of matter in detail. However, light is usually prescribed as a classical electromagnetic field, and the light-matter interaction is taken into account as an external potential via classical approximations. This software is designed to fill current modeling shortcomings by delivering a first-ever scalable multiscale platform for simulating light-matter interactions in realistic electromagnetic environments. The software solves Maxwell and Schrodinger equations self-consistent on the heterogeneous platforms. It implements HF/DFT, TDDFT, and coupled-cluster counterparts for light-matter interactions and adopts modular programming to offload massively parallel algorithms on a large number of CPU/GPUs.", + "laborHours": 0.0, + "languages": [], + "name": "Multiscale Ecosystem for solving Maxwell-Schrodinger equations of open quantum systems (OpenMS) ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/OpenMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "Dimension reduction techniques have long been an important topic in statistics, and active subspaces (AS) have received much attention this past decade in the computer experiments literature. The most common approach towards estimating the AS is to use Monte Carlo with numerical gradient evaluation. This software takes a new approach towards estimating the active subspace, in which Multivariate Adaptive Regression Splines (MARS) is used as a surrogate model, and relevant calculation are obtained analytically. Using a MARS surrogate has many advantages including improved scaling, better estimation of active subspaces in high dimensions and the ability to handle a large number of prior distributions in closed form. This software is also capable of conducting a so-called \"concordance analysis\", using a generalization of ASs which we refer to as \"Co-Active\" subspaces. ", + "laborHours": 0.0, + "languages": [], + "name": "Concordance", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/knrumsey-lanl/concordance", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "Ume is an open-source collection of data structures for unstructured computational meshes and some simple algorithms that operate on them. These algorithms mimic the memory access patterns of a common class of operations found in several of the computational physics simulation codes developed at Los Alamos National Laboratory. The intent is that Ume can be used by hardware vendors to understand the memory traffic created by complex codes in a simplified environment, and to explore new means of optimization for that traffic. Ume is provided as a source-code C++ library and includes several applications that demonstrate the use of that library.", + "laborHours": 0.0, + "languages": [], + "name": "Ume: Unstructured Mesh Explorations", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/UME", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "LANL science workflows generate complex data sets and ensembles of data requiring significant compute and storage resources. 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The abstraction layer API allows the user to query a range of data types: raw output, processed data, configuration data, machine learning models, performance data, etc. In addition to the abstraction backend API, the DSI project is developing client-driven query APIs and UIs to support specific user workflows.", + "laborHours": 0.0, + "languages": [], + "name": "Data Science Infrastructure SOFTWARE", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/dsi", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-07" + }, + "description": "The ratio of heavy-to-light stable isotope abundance in water vapor is a tracer of atmospheric processes including evapotranspiration, condensation, mixing, and transport. Measurements of these isotope ratios at the surface, in the atmospheric column, or from satellites provide insights into atmospheric processes that cannot be gained from measurements of water vapor mixing ratios alone. A number of theoretical models for how water vapor isotope ratios should vary in response to atmospheric processes have been developed, and LANL contributions to the isoWater R package provides a simplified interface for calculating expected vapor isotope ratios based on these models and adding them to plots of water vapor isotope ratios.", + "laborHours": 0.0, + "languages": [], + "name": "LANL contributions to isoWater R package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/isoWater", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-05" + }, + "description": "The purpose of the current request is to enable LANL employees to contribute computer source code to the existing public repository of the MoDELib software package. This software implements discrete dislocation dynamics (DDD) and finite element (FEM) methods and is currently a vital component of an ongoing DR project at LANL, in collaboration with its original author and maintainer Giacomo Po. Contributions from LANL employees would aim to enhance the reliability, accuracy, and performance of MoDELib simulations using LANL's high performance computing platforms through bug fixes, algorithmic refinements, and parallelization.", + "laborHours": 0.0, + "languages": [], + "name": "Contributions to MoDELib SOFTWARE", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nickjulian-LANL/MoDELib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "Harmony is a finite element ALE code for solving the equations of fluid dynamics for single-material flows with arbitrary mesh motion in three dimensional geometry. ", + "laborHours": 0.0, + "languages": [], + "name": "Harmony code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Harmony", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-05" + }, + "description": "The scientific and public health communities responded to the COVID-19 pandemic with\nsample acquisition and genome sequencing on a scale that eclipsed all prior sequencing\nefforts. While this can only be characterized as a resounding success story that has\ncemented the use of genomics for epidemiological investigations for any future infectious\ndisease outbreak, several retrospective studies are cataloging an array of lessons learned\nand issues that have yet to be addressed in order to realize the full potential of genomics as\na routine biosurveillance tool. We have been both developing methods to accurately assess\nSARS-CoV-2 genomes from complex samples, and analyzing the large volumes of\ninternational data, both at the consensus level and the raw sequencing data. During the\ncourse of our investigations and similar to other groups, we have examined COVID-19\nsamples with signatures from multiple lineages of SARS-CoV-2 and will describe some of\nour findings during the development of a novel workflow that incorporates detection and\nreporting of potential co-infection within samples and also highlights any evidence of\nwithin-host recombination.", + "laborHours": 0.0, + "languages": [], + "name": "Recombinant And Mix-Infection Finder for SARS-CoV-2 sample", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ramifi", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-05", + "metadataLastUpdated": "2023-07-31" + }, + "description": "This tool provides interfaces for ingesting real-time unit commitment data (e.g., from a grid operator's control room energy management system) and calculating system inertia estimates based on the H-constant method, before relaying those estimates to customizable visualization or logging outputs.", + "laborHours": 0.0, + "languages": [ + "Go", + "CSS", + "HTML", + "JavaScript" + ], + "name": "G-PST Inertia Monitoring Tool [SWR-23-54]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/G-PST/inertia", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-06-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "3D printing design documents for a bearing-less centrifugal water pump comprised of an impeller rotor enclosing a permanent magnet which is\ndriven by a second permanent magnet rotated by an electric motor.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Bearing-less Centrifugal Pump (non-levitated, non-electromagnetic)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-06-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "3D design documents for 3D printing. The holes in the electrode cage are designed to condense hydrogen into progressively larger\nbubbles, and to direct the flow of hydrogen from the cathode up and out of the bioreactor so it is kept away from the anode\nand collected as nearly pure hydrogen.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Electrode Cage for Hydrogen Production", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-06-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "3D printable reactor base provides all of the mixing innovations needed to make excellent mixing reactors at any scale", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Hybrid Bioreactor for Enhanced Mixing Efficiency", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-06-06", + "metadataLastUpdated": "2023-06-16" + }, + "description": "Zero-RK is a software package that simulates chemically reacting systems using sparse, preconditioned,\nadaptive matrix methods to achieve orders-of-magnitude reduction in simulation time while maintaining\naccurate results.", + "laborHours": 13497.6, + "languages": [], + "name": "Zero-Order Reaction Kinetics v. 3.4.hip", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/zero-rk", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.4.hip" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-07", + "metadataLastUpdated": "2023-06-07" + }, + "description": "AIIO uses Artificial Intelligence for Job-Level and Automatic I/O Performance Bottleneck Diagnosis.", + "laborHours": 0.0, + "languages": [], + "name": "AIIO v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/aiio", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-07", + "metadataLastUpdated": "2023-06-07" + }, + "description": "The AmeriFlux BASE Flux/Met Data QA/QC and Processing (AMF-BASE-QAQC) code provides tools to review and prepare continuous flux/met data submitted to the AmeriFlux Management Project for publication as the AmeriFlux BASE data product. The code provides 3 core functionalities: Format QA/QC assesses submitted data files for compliance with the required submission format; Data QA/QC assesses the data quality; BASE Publish prepares the data for publication.", + "laborHours": 0.0, + "languages": [], + "name": "AmeriFlux BASE Flux/Met Data QA/QC and Processing (AMF-BASE-QAQC) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMF-FLX/AMF-BASE-QAQC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-07", + "metadataLastUpdated": "2023-06-12" + }, + "description": "This software generates QED fields in which the photon has a finite mass, and also the 0-mode subtracted scheme. They are intended to be used with lattice QCD calculations to understand the QED corrections to nuclear physics processes that are being computed with lattice QCD. To the best of my knowledge, this will be the only publicly available software that generates background QED configurations with massive photons. ", + "laborHours": 0.0, + "languages": [], + "name": "noncompact_u1 (qed_m) v1.0.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/callat-qcd/qed_m", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "colemanjs@ornl.gov" + }, + "date": { + "created": "2023-06-13", + "metadataLastUpdated": "2024-05-07" + }, + "description": "AdditiveFOAM is a continuum heat transfer and fluid flow code for metal additive manufacturing developed on the OpenFOAM CFD Framework. The main components of AdditiveFOAM include: a dynamic heat source model representing heat input from independently moving beams; a robust and efficient thermodynamic solver for solid-liquid phase change in metal alloys; a library to export thermal data to ExaCA— a cellular automata (CA) code used for predicting solidification grain growth. By integrating these capabilities, AdditiveFOAM offers valuable insights into the process-structure relationships of metal additive manufacturing components.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "AdditiveFOAM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/AdditiveFOAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-15", + "metadataLastUpdated": "2023-06-15" + }, + "description": "MetaBAT-LR is an extension to the metaBAT program, which adds functionalities to leverage various datasets (long-reads, Hi-C) to improve the completeness of metagenome binning while keeping contamination levels low. It trains a random forest model using the self-supervised training paradigm to predict linkage information among metagenome scaffolds, then uses this information to recruit unbinned scaffolds and merge incomplete bins that are from the same species.", + "laborHours": 0.0, + "languages": [], + "name": "MetaBAT-LR v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/project-metabat/metabat-lr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-06-19", + "metadataLastUpdated": "2023-06-19" + }, + "description": "This software is intended to facilitate the sending of data from DeepLynx to some human machine interface (HMI). The HMI would read the data generated by this software and potentially make a physical change on a process which the HMI controls. This software enables a digital twin using DeepLynx to talk to an HMI, thereby making autonomous updates to the physical asset which is being twinned.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deeplynx Supervisory Control Adapter", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-Supervisory-Control", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-06-20", + "metadataLastUpdated": "2023-06-20" + }, + "description": "AutoCog is a framework to design programming models (PM) for language models (LM). 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These tools were used in the manuscript entitled \"Continuous-Time Probabilistic Models for\nLongitudinal Electronic Health Records.\"", + "laborHours": 0.0, + "languages": [], + "name": "Continuous-Time Models for Longitudinal Data", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/alankaplan/CTMLD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-21", + "metadataLastUpdated": "2023-08-28" + }, + "description": "A2E2G is a platform that integrates 1) forecasting tools to account for weather uncertainty, with 2) aerodynamic wind plant models to account for wake dynamics and wind plant operation, and 3) economic models to advise on operation for a wind power plant that offers grid services in addition to energy. 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The code is assembled into a Python package and can be easily downloaded and installed from the A2E2g repository (https://github.com/NREL/a2e2g).", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "A2E2G (Atmosphere to Electrons to the Grid platform) [SWR-23-22]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/a2e2g", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-21", + "metadataLastUpdated": "2023-06-21" + }, + "description": "Stacker is a library and command-line tool for interacting with components of the Elastic Stack remotely\nusing their APIs. 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This package can be used with both CPU and GPU with CUDA.", + "laborHours": 0.0, + "languages": [], + "name": "LivermorE Al Projector for Computed Tomography Tasks ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/leap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-23", + "metadataLastUpdated": "2023-06-30" + }, + "description": "This toolset generates heterogeneous spatial layouts, aimed at representing forest fuels applicable to wildland fire modeling. 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More broadly, Tribol supports the research, development, and\nimplementation of numerical methods for interface physics.\n", + "laborHours": 0.0, + "languages": [], + "name": "Tribol Interface Physics Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Tribol", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-27", + "metadataLastUpdated": "2023-06-27" + }, + "description": "This software offers methods and functions for training calibrated out-of-distribution detectors for medical\nimage classification tasks. It includes functionalities for training, synthesizing data augmentations,\ncalibration, and out-of-distribution detection. Developed using PyTorch, this software is compatible with\nstandard neural network architectures used for imaging data. Additionally, it provides capabilities to compute evaluation metrics for assessing the performance and quality of the detectors.", + "laborHours": 0.0, + "languages": [], + "name": "Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/OODmedic", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-06-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Open Source Exascale Computational Chemistry Software", + "laborHours": 0.0, + "languages": [], + "name": "ExaChem/exachem", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ExaChem/exachem", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-28", + "metadataLastUpdated": "2023-06-28" + }, + "description": "PyTorch code for cardiac electrical imaging using the 12-lead ECG. This code is associated with the\npaper from CINC 2022. If you use this code, please cite:\nPaper : https://cinc.org/2022/Program/accepted/26_Preprint.pdf\nDataset : https://library.ucsd.edu/dc/object/bb29449106\nThe code support two tasks:\nTask 1: Activation Map Reconstruction from ECG\nTask 2: Transmembrane potential Reconstruction from ECG", + "laborHours": 0.0, + "languages": [], + "name": "Machine Learning for Cardiac Electrical Imaging", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/landajuela/cardiac_ml", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0." + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-28", + "metadataLastUpdated": "2023-06-30" + }, + "description": "This is a script and the associated test input/output that will accompany a new manuscript (soon to be submitted for publication). 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This script is released as documentation for the manuscript, but there is no specific invention, and most bioinformaticians would be able to recreate a comparable script in a matter of days (if not hours) based on the description in the manuscript.", + "laborHours": 0.0, + "languages": [], + "name": "Custom script used in 'Updated virophage taxonomy and distinction from polinton-like viruses' (Virophage_Scripts) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/simroux/ICTV_VirophageSG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-28", + "metadataLastUpdated": "2023-06-28" + }, + "description": "\tHaxall-based Fault Correction is a set of fault auto-correction algorithms implemented using the Axon language. These algorithms can automatically fix equipment and control problems as they arise and improve the operation of building Heating, Ventilation, and Air Conditioning (HVAC) systems. The coded auto-correction algorithms include mitigation of rogue zones, ASHRAE Guideline 36 static pressure and supply air reset, resolution of control hunting due to improper settings in a proportional-integral-derivative controller, correction of biased temperature sensors, etc. FDD tools with enhanced auto-correction capability can resolve control problems as they are detected, increasing energy savings and emissions reductions while freeing up operational staff expertise for the hardest facility problems.", + "laborHours": 0.0, + "languages": [], + "name": "Haxall-based (Axon) fault auto-correction package for building HVAC system (Haxall-based Fault Correction) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/haxall-based-fault-correction", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gureckywl@ornl.gov" + }, + "date": { + "created": "2023-06-29", + "metadataLastUpdated": "2023-06-29" + }, + "description": "The software solves the time dependent, one dimensional (1D) coupled mass and momentum balance equations governing the elastic flow of water through the penstock, turbine and draft tube in a hydroelectric facility using a high order finite volume based method. The numerical method is based on the Kurganov-Tadmor central method paired with the Monotonic Upstream-centered Scheme for Conservation Laws (MUSCL). This solution method accurately resolves the fast transient behavior of the flow, including water hammer. Additionally, the software estimates the full 3D flow field within the turbine chamber in real time, a feat that is made possible by leveraging pre-computed CFD results by utilizing a reduced order modeling method based on an efficient randomized singular value decomposition (SVD) driven proper orthogonal decomposition (POD) with POD-mode weight regression. The reduced order model of the 3D flow is directly coupled to the 1D elastic flow model so the entire flow field through the penstock and turbine system is resolved quickly and with high fidelity.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DT-HYDRO", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/dt-hydro/dt-hydro-cfd", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0.0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-30", + "metadataLastUpdated": "2023-06-30" + }, + "description": "edit-initramfs.sh is a simple script to extract, edit, and rebuild an initramfs image. This makes it easy to quickly make edits to the contents of an initramfs.\n", + "laborHours": 0.0, + "languages": [], + "name": "edit-initramfs.sh", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tonyhutter/edit-initramfs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-07-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PTM-Psi is a Python 3 package that combines several capabilities to streamline the workflow to interrogate the impact of\nPTMs on proteins using well-established software packages. The workflow of the PTM-Psi software package includes\ninput files and launch instances from standard packages such as AlphaFold, NWChem, GROMACS, and the Autodock\nSuite", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/PTMPSI", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ptmpsi", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-07-03", + "metadataLastUpdated": "2023-07-03" + }, + "description": "Provides a central location for viewing and comparing different methods for downscaling coarse resolution\nclimate model output.", + "laborHours": 0.0, + "languages": [], + "name": "Downscaled Climate Data Dashboard", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Downscaled-Climate-Data-Dashboard", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-07-06", + "metadataLastUpdated": "2024-10-16" + }, + "description": "Battery life modeling often involves a lot of manual parameter fitting and is not easy for users to adopt the model and use it. To reduce the difficulties for users to adopt battery lifetime models, an automatic battery lifetime modeling analysis and simulation tool suite, Auto-BLAST, has been developed. Auto-BLAST includes a lithium-loss-base life model, a battery electric model, and an algorithm which automatically fits all key parameters in the electric and life models using user provided data. The models and algorithm are packaged into two user-friendly GUIs, Auto-LifeMod, for easy battery life prognostic model fitting and Auto-LifeSim, for easy battery lifetime simulation. The lithium-loss-based life model adopts a similar model framework that models degradations using aging rate models, using battery cycling data to predict battery degradation and expected lifetime. The electric model is an equivalent circuit model which simulates battery voltage responses based on current/power demand profiles. The auto-fitting algorithm uses the user-input data to generate custom battery life model(s). Two GUIs, wrapping around the life model and the auto-fitting algorithm, provide friendly interfaces for users to generate a life model and use it for case study. One GUI requires summary data from accelerated battery life degradation tests as an input and produces battery life models predicting (a) capacity degradation, and (b) resistance growth of the battery. The GUI displays the electrical model response and the input experimental data against the life model predictions with fitted model parameters and fitting error. The GUI also generates an output file to save the fitted model parameters. The second GUI uses the life model from the first GUI and a user-defined battery cycling profile to predict battery lifetime degradation and expected lifetime. Predicted capacity and resistance vs. time are plotted in the GUI and saved to output file. There is a user guide for both GUIs", + "homepageURL": "https://labpartnering.org/technologies/a298da24-0625-42a8-9693-a81d839529d7", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Auto-BLAST (AutoBLAST) [SWR-20-93]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://labpartnering.org/technologies/a298da24-0625-42a8-9693-a81d839529d7", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://labpartnering.org/technologies/a298da24-0625-42a8-9693-a81d839529d7", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-06", + "metadataLastUpdated": "2023-07-06" + }, + "description": "\tQuantitative Universal Option Prioritizer (QUOP) is a three-layer analytical hierarchy process (AHP) based multi-criteria decision-making option evaluation and prioritization tool. Decision-making often entails evaluation of options. Such competing options can either be mutual substitutes or cumulative means to achieve an objective. The options themselves can be methods, tools, technologies, processes, etc. Stakeholders involved in achieving the objective may view each option characteristic differently, depending on their needs and preferences. The QUOP tool enables a streamlined quantitative collaborative process of weighing the opinion of each stakeholder in evaluating the options. The evaluation may also be performed under different scenarios, for instance, various option potential estimates, prices, or end-user demand projections. The QUOP tool can find application in both public and private sectors, as well as on an individual level. The major advantage of using the QUOP decision-making tool is in documenting the quantified stakeholder opinion, therefore the background to each decision made, while simultaneously maintaining high transparency and stakeholder involvement. The tool is particularly suitable for decisions involving a high number of options and option characteristics, that is, aspects of each option that matter to the stakeholders", + "laborHours": 0.0, + "languages": [], + "name": "Quantitative Universal Option Prioritizer (QUOP) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/QUOP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-06", + "metadataLastUpdated": "2023-07-06" + }, + "description": "The High Speed Digitizer firmware is an FPGA gateware and embedded firmware that run on evaluation kits (either Xilinx ZCU111 or Xilinx ZCU208 ) that digitizes signals up to 4GSPS and 4GHz analog bandwidth, which can be synchronized to the accelerator timing system, providing synchronous sampling frequency/phase digitization. In addition to these capabilities, a proof of concept for a beam position monitor is also present, providing an envelope detection algorithm capable of determining the transverse beam position for an electron circular accelerator, such as ALS/ALS-U.", + "laborHours": 0.0, + "languages": [], + "name": "High Speed Digitizer Firmware (HSD) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/LBNL-Digitizers", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for \"Faster Parallel Exact Density Peaks Clustering\" paper.\n\nHuang, Yihao, Shangdi Yu, and Julian Shun. \"Faster Parallel Exact Density Peaks Clustering.\" SIAM Conference on Applied and Computational Discrete Algorithms (ACDA23). Society for Industrial and Applied Mathematics, 2023.\n", + "laborHours": 0.0, + "languages": [], + "name": "Faster Parallel Exact Density Peaks Clustering", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/michaelyhuang23/ParCluster", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper: \n\nZhi Wei Gan, Grace Cai, Noble Harasha, Nancy Lynch, and Julian Shun.\nParSwarm: A C++ Framework for Evaluating Distributed Algorithms for Robot Swarms.\nProceedings of the Workshop on Advanced Tools, Programming Languages, and Platforms for Implementing and Evaluating Algorithms for Distributed Systems (ApPLIED), Article No. 14, pp. 1-5, 2023.\n", + "laborHours": 0.0, + "languages": [], + "name": "ParSwarm: A C++ Framework for Evaluating Distributed Algorithms for Robot Swarms", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zhiweigan/geo-swarm-framework", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper:\n\nShangdi Yu and Julian Shun.\nParallel Filtered Graphs for Hierarchical Clustering.\nProceedings of the IEEE International Conference on Data Engineering (ICDE), 2023.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Filtered Graphs for Hierarchical Clustering", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yushangdi/par-filtered-graph-clustering", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper:\n\nYihao Huang, Claire Wang, Jessica Shi, and Julian Shun.\nEfficient Algorithms for Parallel Bi-core Decomposition.\nProceedings of the SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS), pp. 17-32, 2023.", + "laborHours": 0.0, + "languages": [], + "name": "Efficient Algorithms for Parallel Bi-core Decomposition", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/clairebookworm/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper:\n\nJessica Shi, Louisa Huang, and Julian Shun.\nParallel Five-Cycle Counting Algorithms.\nACM Journal of Experimental Algorithmics (JEA), Vol. 27, Article No. 4:1, pp.1-23, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Five-Cycle Counting Algorithms", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper:\n\nYiqiu Wang, Rahul Yesantharao, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun.\nParGeo: A Library for Parallel Computational Geometry.\nProceedings of the European Symposium on Algorithms (ESA), pp. 88:1-88:19, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "ParGeo: A Library for Parallel Computational Geometry", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/ParGeo", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nJessica Shi and Julian Shun.\nParallel Algorithms for Butterfly Computations.\nMassive Graph Analytics, pp. 287-330, 2022. (Earlier version appears in APOCS 2020.)", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Algorithms for Butterfly Computations", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeshi96/parbutterfly", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nQuanquan Liu, Jessica Shi, Shangdi Yu, Laxman Dhulipala, and Julian Shun.\nParallel Batch-Dynamic Algorithms for k-Core Decomposition and Related Graph Problems.\nProceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), pp. 191-204, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Batch-Dynamic Algorithms for k-Core Decomposition and Related Graph Problems", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qqliu/batch-dynamic-kcore-decomposition", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nJessica Shi, Laxman Dhulipala, and Julian Shun.\nTheoretically and Practically Efficient Parallel Nucleus Decomposition.\nProceedings of the VLDB Endowment, 15(3), pp. 583-596, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "Theoretically and Practically Efficient Parallel Nucleus Decomposition", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeshi96/arb-nucleus-decomp", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nShangdi Yu, Yiqiu Wang, Yan Gu, Laxman Dhulipala, and Julian Shun.\nParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain.\nProceedings of the VLDB Endowment, 15(2), pp. 285-298, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yushangdi/parChain", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nYiqiu Wang, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun.\nGeoGraph: A Framework for Graph Processing on Geometric Data.\nACM SIGOPS Operating Systems Review, Vol. 55 Issue 1, pp. 38-46, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "GeoGraph: A Framework for Graph Processing on Geometric Data", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/GeoGraph", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper (https://github.com/ParAlg/gbbs/tree/master/benchmarks/CliqueCounting):\n\nJessica Shi, Laxman Dhulipala, and Julian Shun.\nParallel Clique Counting and Peeling Algorithms.\nProceedings of the SIAM Conference on Applied and Computational Discrete Algorithms (ACDA), pp. 135-146, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Clique Counting and Peeling Algorithms", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nYiqiu Wang, Shangdi Yu, Yan Gu, and Julian Shun.\nA Parallel Batch-Dynamic Data Structure for the Closest Pair Problem.\nProceedings of the International Symposium on Computational Geometry (SoCG), pp. 60:1-60:16, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "A Parallel Batch-Dynamic Data Structure for the Closest Pair Problem", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wangyiqiu/closest-pair", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nYiqiu Wang, Shangdi Yu, Yan Gu, and Julian Shun.\nFast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering.\nProceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pp. 1982-1995, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wangyiqiu/hdbscan", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper (https://github.com/ParAlg/gbbs/tree/master/benchmarks/SCAN/IndexBased):\n\nTom Tseng, Laxman Dhulipala, and Julian Shun.\nParallel Index-Based Structural Graph Clustering and Its Approximation.\nProceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pp. 1851-1864, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Index-Based Structural Graph Clustering and Its Approximation", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-11" + }, + "description": "Source code for paper (https://github.com/ParAlg/gbbs/tree/tri_merge/benchmarks/TriangleCounting/DhulipalaLiuShunYu20):\n\nLaxman Dhulipala, Quanquan Liu, Julian Shun, and Shangdi Yu.\nParallel Batch-Dynamic k-Clique Counting.\nProceedings of the SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS), pp. 129-143, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Batch-Dynamic k-Clique Counting", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nChangwan Hong, Laxman Dhulipala, and Julian Shun.\nExploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs.\nProceedings of International Conference on Parallel Architectures and Compilation Techniques (PACT), pp. 55-69, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "Exploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hochawa/gconn", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nLaxman Dhulipala, Changwan Hong, and Julian Shun.\nConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms.\nProceedings of the VLDB Endowment, 14(4), pp. 653-667, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "ConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-11" + }, + "description": "Source code for paper (https://github.com/ParAlg/gbbs/tree/semi_asymmetric): \n\nLaxman Dhulipala, Charles McGuffey, Hongbo Kang, Yan Gu, Guy Blelloch, Phillip Gibbons, and Julian Shun.\nSage: Parallel Semi-Asymmetric Graph Algorithms for NVRAMs.\nProceedings of the VLDB Endowment, 13(9), pp. 1598-1613, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "Sage: Parallel Semi-Asymmetric Graph Algorithms for NVRAMs", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\n\nYiqiu Wang, Yan Gu, and Julian Shun.\nTheoretically-Efficient and Practical Parallel DBSCAN.\nProceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pp. 2555-2571, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "Theoretically-Efficient and Practical Parallel DBSCAN", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wangyiqiu/dbscan", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nLaxman Dhulipala, Jessica Shi, Tom Tseng, Guy Blelloch, and Julian Shun.\nThe Graph Based Benchmark Suite (GBBS).\nProceedings of the Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA), pp. 1-8, 2020.\n\nWebsite: https://paralg.github.io/gbbs/", + "laborHours": 0.0, + "languages": [], + "name": "The Graph Based Benchmark Suite (GBBS)", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nJulian Shun.\nPractical Parallel Hypergraph Algorithms.\nProceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), pp. 232-249, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "Practical Parallel Hypergraph Algorithms", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jshun/ligra", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for GraphIt DSL. See https://graphit-lang.org/ for more info.", + "laborHours": 0.0, + "languages": [], + "name": "GraphIt: A high-performance graph domain specific language", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GraphIt-DSL/graphit", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nLaxman Dhulipala, Guy Blelloch, and Julian Shun.\nLow-Latency Graph Streaming Using Compressed Purely-Functional Trees.\nProceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), pp. 918-934, 2019.", + "laborHours": 0.0, + "languages": [], + "name": "Low-Latency Graph Streaming Using Compressed Purely-Functional Trees", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ldhulipala/aspen", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nOmar Obeya, Endrias Kahssay, Edward Fan, and Julian Shun.\nTheoretically-Efficient and Practical Parallel In-Place Radix Sorting.\nProceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), pp. 213-224, 2019.", + "laborHours": 0.0, + "languages": [], + "name": "Theoretically-Efficient and Practical Parallel In-Place Radix Sorting", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/omarobeya/parallel-inplace-radixsort", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nYu Xia, Xiangyao Yu, William Moses, Julian Shun, and Srini Devadas.\nLiTM: A Lightweight Deterministic Software Transactional Memory System.\nProceedings of the International Workshop on Programming Models and Applications for Multicores and Manycores (PMAM), pp. 1-10, 2019.", + "laborHours": 0.0, + "languages": [], + "name": "LiTM: A Lightweight Deterministic Software Transactional Memory System", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yuxiamit/LiTM", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-07-12", + "metadataLastUpdated": "2023-07-12" + }, + "description": "The Deep Lynx MATLAB Adapter is a Python application that connects the Deep Lynx data warehouse with any MATLAB simulation.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python" + ], + "name": "Deep Lynx Matlab Adapter", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-MATLAB", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-07-12", + "metadataLastUpdated": "2023-07-12" + }, + "description": "This code provides natural language annotation and labels for multiple activities in high performance. The purpose is to enable machine learning for natural language processing algorithms with high performance computing systems. ", + "laborHours": 0.0, + "languages": [ + "python3", + "yml" + ], + "name": "Hpc Natural Language Understanding (nlu) Dataset", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HPC_Natural_Language_Understanding_-NLU-_Dataset", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-18" + }, + "description": "This software is a Rust package that interacts with the Application Programming Interface (API) suite provided by DeepLynx. A Rust codebase may import this package in order to have access to these methods for communicating with a DeepLynx instance.", + "laborHours": 0.0, + "languages": [ + "Rust" + ], + "name": "Deeplynx Rust Sdk", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-Rust_SDK", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "CmdWebCtrl is a utility that runs a given command and provides a simple web interface for viewing\nanything it outputs to the console, along with providing some simple controls for restarting it.", + "laborHours": 0.0, + "languages": [], + "name": "CmdWebCtrl", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GMLC-TDC/CmdWebCtrl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "ctrl-flow is a software that assists users in selecting a building control sequence from a library of control sequences that are implemented in the Modelica Buildings Library. The software allows selecting, configuring and editing the control sequences. It also allows exporting the sequence for use in building project design documents in Modelica-based simulations. The export will be in a json intermediate format, in the Modelica Language, in the Control Description Language and in English language format, such as in a Word document. The software functions as a web based application that includes a graphical user interface.", + "laborHours": 0.0, + "languages": [], + "name": "ctrl-flow v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-srg/ctrl-flow-dev.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "ERF is a next-generation regional atmospheric modeling code for simulation mesoscale atmospheric flows. Its capabilities include the ability to model advection, diffusion, turbulence, terrain and moisture physics.", + "laborHours": 0.0, + "languages": [], + "name": "Energy Research and Forecasting (ERF) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/erf-model/ERF", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "GPU-FPX is a tool based on NVBit that detects and analyzes floating-point exceptions on NVIDIA GPUs through binary instrumentation. Its purpose is to detect and report the occurrences of floating-point exceptions during numerical computations, offering efficient location detections and exception flow. GPUFPX achieves exceptional performance, being 16x faster than comparable prior tools, such as BinFPE.", + "laborHours": 0.0, + "languages": [], + "name": "GPU-FPX", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GPU-FPX", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "Given a pre-trained neural network, Inference-Engine performs maps network inputs to outputs by executing the forward pass through the provided network. Although the predominant programming language for machine-learning is Python, most high-performance computing (HPC) applications are written in Fortran, C, or C++. Inference-Engine aims to support HPC programs and is written in Fortran, a language with a large feature set supporting interoperability with C. This software exposes concurrency in a portable way by using standard language features that some modern Fortran compilers can exploit with various optimizations, including offloading computation to a Graphics Processing Unit (GPU). In particular, this software makes extensive use of Fortran's \"do concurrent\" parallel loop construct, implicitly parallel array statements, and pure procedures that can be invoked inside \"do concurrent\" blocks. Inference-Engine also supports dynamic choice of inference methods at runtime. Two current options include one method that uses Fortran's \"dot_product\" intrinsic function inside \"do concurrent\" blocks and another method that instead uses Fortran' \"matmul\" array intrinsic function. We plan to investigate automatic compiler offloading of \"do concurrent\" calculations to GPUs and compile-time substitution of optimized libraries such as the Basic Linear Algebra Library (BLAS) for \"matmul\" invocations. We also envision the potential for the choice of which method to use could happen at program launch based on in situ performance measurements on any given platform.", + "laborHours": 0.0, + "languages": [], + "name": "Inference-Engine v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/Inference-Engine", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "Direct-Sampling Beam Position Monitor is an FPGA gateware and embedded firmware that run on evaluation kits (either Xilinx ZCU111 or Xilinx ZCU208 ) that digitizes signals up to 4GSPS and 4GHz analog bandwidth, which can be synchronized to the accelerator timing system, providing synchronous sampling frequency/phase digitization. In addition to these capabilities, a proof of concept for a beam position monitor is also present, providing an envelope detection algorithm capable of determining the transverse beam position for an electron circular accelerator, such as ALS/ALS-U.", + "laborHours": 0.0, + "languages": [], + "name": "Direct-Sampling Beam Position Monitor (dsbpm) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/LBNL-DSBPM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "Software networking library to allow an FPGA ethernet core (such as Badger: https://gitlab.lbl.gov/hdl-libraries/bedrock/-/tree/master/badger) to be used in a soft-core processor or microcontroller.", + "laborHours": 0.0, + "languages": [], + "name": "Bantamweight Badger UDP support (BWUDP) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/BWUDP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "The dual event generator is a event-based timing system implementation capable of synchronizing (with respect to clock, events and triggers) hundreds of downstreams devices. This has been in use by ALS for many years and this is a similar implementation, but with a synchronized dual-master frequency , as opposed to just one in a more conventional approach.", + "laborHours": 0.0, + "languages": [], + "name": "Dual Event Generator (dual-evg) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/LBNL-Dual-EVG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-14" + }, + "description": "The Electricity Bill Calculator Library is a generic tool for manipulating the tariffs of electricity, with an emphasis on commercial Time-Of-Use (TOU) rates in the U.S. and residential Net Energy Metering tariffs in CA. Typical uses of the package are price signal generation and bill computation. To generate price signals from a specific tariff and given a time window, the tool creates a pandas dataframes containing the various components of the electricity charges, at each time step. This is particularly useful for Demand Response (DR) applications, such as price-based optimization of energy in buildings. The tool also computes bills given a building's power consumption and a specific tariff and returning the corresponding cost of electricity, as well as a breakdown per type of rate.", + "laborHours": 0.0, + "languages": [], + "name": "Electricity Bill Calculator (elecprice) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/elecprice", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "A software program for experimenting with holographic teleportation protocol on quantum computers. The code implements the protocol that was proposed in https://arxiv.org/abs/1911.06314.\n\nThe code is an end-to-end software solution that facilitates conducting the holographic teleportation experiments on state-of-the-art and emergent generations of QPUs supported by the Qiskit and tket SDKs. The code bundles all stages of an experiment as a single configurable workflow allowing faster development and experimentation cycles.\n\nFeatures:\n1. Easy switching between Qiskit and tket quantum compilers.\n2. Semi-automatic facilities for finding optimal compilation solutions beyond what Qiskit and tket provide by default.\n3. Experiment resolution scaling (based on automatic jobs' batching).\n4. Automatic experiment scaling over qubits.\n5. Automatic readout error mitigation.\n6. Automatic reproducibility analysis.\n7. Standalone error-mitigation tools (randomized compiling, mitigation with estimation circuits, zero-noise extrapolation)", + "laborHours": 0.0, + "languages": [], + "name": "QGLab v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ishapova/qglab", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "FABLE is a s light-weight software package for easy generation of quantum circuits that block encode arbitrary matrices.", + "laborHours": 0.0, + "languages": [], + "name": "FABLE v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QuantumComputingLab/fable", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "\tFusionML_RF consists of multiple codes and trained machine learning (ML) models that perform low-cost output modeling from the Genray-CQL3D. Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. For example, completing a single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time. On the other hand, these ML models achieve ~ms of inference time with high accuracy across the input parameter space. This software collection consists of multiple components. (1) codes that use ML methods and precomputed Genray-CQL3D simulation output to build regression models that enable approximate computations of Genray-CLQ3D outputs from arbitrary but physically meaningful input parameters (surrogate modeling); (2) three trained models created by the team, using a database of 16,000+ GENRAY/CQL3D simulations, to study the performance of ML models for surrogate modeling; (3) codes that load the trained models and simulation data, and then compute mean squared error between the models' predictions and the ground truth of simulation output data. This collection is being made available in conjunction with a scientific publication about the work to promote reusability and provide an artifact of the scientific work.", + "laborHours": 0.0, + "languages": [], + "name": "Fusion RF Modeling Machine Learning (FusionML_RF) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FusionRFModelingMachineLearning/genray-cql3d-ml", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-07-14", + "metadataLastUpdated": "2023-07-14" + }, + "description": "Surfactant is a tool to generate an SBOM for the files in a directory/system based on information contained in various file format, including but not limited to PE, ELF, Mach-O, Java classes, .NET\nassemblies, and various source code files/scripts. Gathered information can be output in a variety of different SBOM formats, and functionality is provided to manipulate and analyze SBOMs (merging, manual additions, querying info, etc). Users are able to add new features via a plugin system.", + "laborHours": 0.0, + "languages": [], + "name": "Surfactant", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Surfactant", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-07-17", + "metadataLastUpdated": "2023-07-17" + }, + "description": "'deeplynx-timeseries-loader' is a library designed to make it as easy as possible for users to download and access timeseries or tabular data from DeepLynx.", + "laborHours": 0.0, + "languages": [ + "Rust" + ], + "name": "Deeplynx-loader", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-Timeseries-Loader", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-07-18", + "metadataLastUpdated": "2024-01-19" + }, + "description": "Symmetry-protected subspaces in quantum systems are subspaces demarcated by a conserved quantity of that quantum system. We introduce two classical algorithms, which efficiently compute and elucidate features of these subspaces. The first algorithm explores the entire symmetry-protected subspace of an initial state in time complexity linear to the size of the subspace by closing local basis state-to-basis state transitions. The second algorithm determines, with bounded error, if a given measurement outcome of a dynamically-generated state is within the symmetry-protected subspace of the state in which the dynamical system is initialized. This software is paired with the paper of the same name at https://arxiv.org/pdf/2302.08586.pdf.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "ADoSPSiQS (Automated Detection of Symmetry-Protected Subspaces in Quantum Simulations ) [SWR-23-55]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SymmetryDetectionForQuantumSim", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-07-18", + "metadataLastUpdated": "2023-07-18" + }, + "description": "A Python script that parsers Saleae Logic 2 output files into useful data sets.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Saleae Logic 2 Output File Parser", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Saleae_Output_Parser", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-07-20", + "metadataLastUpdated": "2023-07-20" + }, + "description": "The Resilience Development for Electric Energy Delivery Systems (ResDEEDS) tool walks users through the process of evaluating electric energy delivery systems (EEDS) for resiliency. It implements the steps of the INL Resilience Framework for EEDS and provides automated tracking of resilience planning and suggestions for mitigating hazards.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Resilience Development For Electric Energy Delivery Systems", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/ResDEEDS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-07-21", + "metadataLastUpdated": "2023-07-25" + }, + "description": "AMSLib provides infrastructure to tightly couple multi-scale physics simulation code with ML surrogate\nmodel inference. It provides a wholistic runtime execution paradigm to supports uncertainty quantification,\nsurrogate model inference, persistent data storing throughout the execution of a simulation.", + "laborHours": 0.0, + "languages": [], + "name": "Autonomous MultiScale Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.0.alpha" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-07-24", + "metadataLastUpdated": "2024-10-16" + }, + "description": "Battery Lifetime Analysis and Simulation Toolsuite (BLAST) provides a library of battery lifetime and degradation models for various commercial lithium-ion batteries from recent years. Degradation models are identified from publicly available lab-based aging data using NREL's battery life model identification toolkit. The battery life models predicted the expected lifetime of batteries used in mobile or stationary applications as functions of their temperature and use (state-of-charge, depth-of-discharge, and charge/discharge rates). Model implementation is in both Python and MATLAB programming languages. The MATLAB code also provides example applications (stationary storage and EV), climate data, and simple thermal management options. For more information on battery health diagnostics, prediction, and optimization, see NREL's Battery Lifespan webpage.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python", + "Jupyter Notebook" + ], + "name": "BLAST-Lite (Battery Lifetime Analysis and Simulation Tool - Lite) [SWR-22-69] Related to: BLAST aka: BLAST-Py", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BLAST-Lite", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-07-25", + "metadataLastUpdated": "2023-11-13" + }, + "description": "The Wind Farm Wake Comparison Framework (Wcomp) is a software tool to facilitate the comparison of a specific collection of wind farm wake modeling tools: Python-based, steady-state, analytical wake modeling utilities. Wcomp integrates another software project, windIO, to create a consistent method for describing a wind farm flow control problem. Additionally, a data structure is included to represent the outputs a wind farm flow control simulation. Well-described interfaces allow existing wake modeling tools to plug into this framework.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Wcomp (Wind Farm Wake Comparison Framework) [SWR-23-72]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/wcomp", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-07-25", + "metadataLastUpdated": "2023-07-25" + }, + "description": "See the SAM™ website to build a desktop version of the National Renewable Energy Laboratory's (NREL's) System Advisor Model™ (SAM). https://sam.nrel.gov/\n\nThe System Advisor Model™ (SAM™) is a free techno-economic software model that facilitates decision-making for people in the renewable energy industry:\n\n-Project managers and engineers\n-Policy analysts\n-Technology developers\n-Researchers\nSAM can model many types of renewable energy systems:\n\n-Photovoltaic systems, from small residential rooftop to large utility-scale systems\n-Battery storage with Lithium ion, lead acid, or flow batteries for front-of-meter or behind-the-meter applications\n-Concentrating Solar Power systems for electric power generation, including parabolic trough, power tower, and linear Fresnel\n-Industrial process heat from parabolic trough and linear Fresnel systems\n-Wind power, from individual turbines to large wind farms\n-Marine energy wave and tidal systems\n-Solar water heating\n-Fuel cells\n-Geothermal power generation\n-Biomass combustion for power generation\n-High concentration photovoltaic systems\n\nSAM's financial models are for the following types of projects:\n\n-Residential and commercial projects where the renewable energy system is on the customer side of the electric utility meter (behind the meter), and power from the system is used to reduce the customer's electricity bill.\n\n-Power purchase agreement (PPA) projects where the system is connected to the grid at an interconnection point, and the project earns revenue through power sales. The project may be owned and operated by a single owner or by a partnership involving a flip or leaseback arrangement.\n\n-Third party ownership where the system is installed on the customer's (host) property and owned by a separate entity (developer), and the host is compensated for power generated by the system through either a PPA or lease agreement.\n\nFor a more detailed description of SAM, see Blair et al. (2018), System Advisor Model (SAM) General Description (Version 2017.9.5), NREL/TP-6A20-70414. \n\nhttps://www.nrel.gov/docs/fy18osti/70414.pdf\n", + "laborHours": 552915.2, + "languages": [ + "C++", + "LK script" + ], + "name": "SAM™ (System Advisor Model™) [SWR-16-02, SWR-10-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SAM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2020.2.29" + }, + { + "contact": { + "email": "haunab@ornl.gov" + }, + "date": { + "created": "2023-07-25", + "metadataLastUpdated": "2023-08-02" + }, + "description": "Tools for building containers to ease building Klipper and CanBoot for multiple targets.\n\nNote: This is being submitted to DOECODE as per instructions received after providing notification of creation of IP outside of work as part of a site-specific IP assignment agreement. This work was not funded by, nor was any work performed under any DOE contract.", + "laborHours": 0.0, + "languages": [ + "Bash", + "C", + "Z shell" + ], + "name": "Klipper Firmware Tools", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laikulo/Klipper-firmware.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "realsimxil@gmail.com" + }, + "date": { + "created": "2023-07-27", + "metadataLastUpdated": "2023-07-28" + }, + "description": "Real-Sim is a multi-resolution X-in-the-loop simulation framework to support inclusive testing and evaluation of CAVs before actual implementation in the real world. Real-Sim framework connects different simulation components and integrates various traffic and vehicle simulation tools, virtual environments, and XIL systems through a Flexible Interface for XIL Simulation (FIXS). Connections among different tools are transparent to users and handled by the interface behind the scenes. Co-simulation of various vehicle and traffic simulation tools with different XIL systems can be easily achieved and become a transparent \"plug-and-play\" process to users.", + "laborHours": 0.0, + "languages": [], + "name": "Real-Sim Flexible Interface for X-in-the-loop Simulation (FIXS)", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Real-Sim-XIL/FIXS", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "Metabolic Context Species Interaction Networks (MetConSIN) generates microbe-metabolte and metabolite-metabolite interaction networks using constraint based metabolic modeling. To do this, MetConSIN simulates with the dynamic FBA system and saves the sequence of interaction networks implied by that system, as well as the time-average network.", + "laborHours": 0.0, + "languages": [], + "name": "MetConSIN", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/metconsin", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "This code enables fitting a model of an infectious disease outbreak, customized for when available data is a combination of case counts and symptom survey responses. This is just a small bit of code being used only for a publication; we need to release it to fulfill a journal's requirement that our work be reproducible.", + "laborHours": 0.0, + "languages": [], + "name": "Outbreak analysis from case count and survey data", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eeg-lanl/cov2-china2022", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "HopPyBar is a python program to import, analyze, and export split-Hopkinson pressure bar (SHPB, also known as Kolsky bar) data. Traditional analysis offers a black box approach, where input data is converted to analyzed output by performing a series of calculations without user involvement. This program serves as a developmental platform to \"white box\" the data analysis process. Data streams can be captured (in-situ) to enable advanced or unconventional analyses, statistics, and comparisons. Additionally, the program is geared towards the standardized forms of input and output used at LANL to streamline analysis, but the open nature of the program makes additional input/output schemes straightforward to add. General workflow will import SHPB data in one of a number of formats, identify relevant portions of data signals, and convert to stress-strain-strain rate to show material behavior as a function of dynamic testing.", + "laborHours": 0.0, + "languages": [], + "name": "HopPyBar", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/HopPyBar", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "LCA-PyTorch is a code repository which contains PyTorch implementations of the Locally Competitive Algorithm (LCA), which is a biologically-plausible sparse coding model. LCA-PyTorch allows for the training, testing, and analysis of single layer LCA networks, multi-layer LCA networks, and hybrid LCA-based deep neural network models on a wide variety of applications and data types. LCA-PyTorch was developed in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning. LCA-PyTorch interfaces heavily with the open-source PyTorch Python package. ", + "laborHours": 0.0, + "languages": [], + "name": "LCA-PyTorch", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/lca-pytorch", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "We would like to disclose two scripts, written in Jupyter notebook, in which we implement the \"Blackout Diffusion Process\" described in the manuscript \"Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces\" (LA-UR-23-20509), to be submitted to the International Conference of Machine Learning (ICML). The abstract of the manuscript is append below. \n\n==\nTypical generative diffusion models rely on a Gaussian diffusion process for training the backward transformations, which can then be used generate samples from Gaussian noise. However, real world data often takes place in discrete-state spaces, which occur in many scientific applications. Here, we develop a theoretical formulation for arbitrary discrete-state Markov processes in the forward diffusion process. We relate the theory to the existing continuous-state Gaussian diffusion and identify the corresponding reverse-time stochastic process and score function in the continuous-time setting, and the reverse-time mapping in the discrete-time setting. As an example of this framework, we introduce \"Blackout Diffusion\", which learns to produce samples from an empty image instead of from noise. Numerical experiments on the CIFAR-10 dataset confirm the feasibility of generative diffusion modeling in a discrete space. Generalizing from specific (Gaussian) forward processes to a more general framework also sheds light on how to interpret generative diffusion models and their mathematical structure, which we comment on.", + "laborHours": 0.0, + "languages": [], + "name": "Code for the manuscript titled \"Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Blackout-Diffusion", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "\"Bluehat\" is a collection of python routines to facilitate the analysis of spectral (multispectral and hyperspectral) remote sensing\nimagery, with an emphasis on various kind of target detection. The package provides collections of utilities that developers can use in producing algorithms for specific target detection scenarios.\n\nAlthough \"bluehat\" is mostly expected to be used for remote sensing imagery (which often comes from satellite sensors), and although early versions of \"bluehat\" were used to design algorithms that were then rewritten for onboard processing; \"bluehat\" itself is not not specially designed for space and/or satellite application.", + "laborHours": 0.0, + "languages": [], + "name": "BlueHat", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jt-lanl/bluehat", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "reevest@ornl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "Phase-field framework built on the Cabana particle library", + "laborHours": 0.0, + "languages": [], + "name": "CabanaPF", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/CabanaPF", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "luszczek@icl.utk.edu" + }, + "date": { + "created": "2023-07-30", + "metadataLastUpdated": "2023-07-30" + }, + "description": "SLIP (Surrogate Launching and Integration Platform) is a software ecosystem for downloading and running ML/AI benchmarks.\nSLIP automatically downloads and sets up the code and data running a benchmark. The large data sets and model code are cached locally with a specific ID within a designated cache directory.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SLIP (Surrogate Launching and Integration Platform)", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/icl-utk-edu/slip.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "luszczek@icl.utk.edu" + }, + "date": { + "created": "2023-07-30", + "metadataLastUpdated": "2023-07-30" + }, + "description": "SABATH provides benchmarking infrastructure for evaluating scientific ML/AI models. It contains support for scientific machine learning surrogates from external repositories. The software dependences are explicitly exposed in the surrogate model definition, which allows the use of advanced optimization, communication, and hardware features.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SABATH: Surrogate AI Benchmarking Applications' Testing Harness", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/icl-utk-edu/sabath.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-07-31", + "metadataLastUpdated": "2023-07-31" + }, + "description": "GPLaSDI is a software that introduces GPLaSDI, a novel LaSDI-based framework that relies on Gaussian\nprocess (GP) for latent space ODE interpolations. Using GPs offers two significant advantages. First, it\nenables the quantification of uncertainty over the reduced order model (ROM) predictions. Second,\nleveraging this prediction uncertainty allows for efficient adaptive training through a greedy selection of\nadditional training data points. This approach does not require prior knowledge of the underlying PDEs.\nConsequently, GPLaSDI is inherently non-intrusive and can be applied to problems without a known PDE\nor its residual. We demonstrate the effectiveness of our approach on the Burgers equation, Vlasov\nequation for plasma physics, and a rising thermal bubble problem. Our proposed method achieves\nbetween 200 and 100,000 times speed-up, with up to 7% relative error.", + "laborHours": 0.0, + "languages": [], + "name": "GPLaSDI: Gaussian Process Latent Space Dynamics Identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GPLaSDI", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2024-09-09" + }, + "description": "SAND2022-3463 O\nThis code is intended to accompany the journal manuscript, “Sub-resolution modeling of the apparent mass loss in quantitative broadband X-ray radiography.\" The manuscript covers in detail how to improve the quantitative mass distribution measurements made for optical diagnostics of multiphase flows. The code contains four separate script files in MATLAB format to support the objective of improving mass measurements.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 349.6, + "languages": [ + "MATLAB" + ], + "name": "Codes for sub-resolution modeling of the apparent mass loss in quantitative broadband X-ray radiography", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/X-ray-Imaging-Apparent-Mass-Loss-Error", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2024-09-09" + }, + "description": "SAND2022-7288 O\nThe exodus_helper Python package is a set of tools that allows a user to query and create datasets in the Exodus II format for use in finite element analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 2280.0, + "languages": [ + "Python" + ], + "name": "exodus_helper", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/exodus_helper", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-02" + }, + "description": "SAND2022-7062 O\nThe Analytical Tool to Evaluate Heterogeneous Neuromorphic Architectures (ATHENA) quickly evaluates performance metrics like energy, area, and latency for an AI/ML network. It currently supports the evaluation of analog neural networks. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 203832.0, + "languages": [ + "C++", + "Python" + ], + "name": "Analytical Tool to evaluate Heterogeneous Neuromorphic Architectures (ATHENA)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "We introduce the Binned Large Interval Network Kernel approach for scoring fragmentation mass spectra similarity which takes advantage of sparse matrix multiplication. This enables BLINK to perform 100 million comparisons while maintaining 98% accuracy in 2.2 seconds making it over 1,000 times faster than the current implementations.", + "laborHours": 0.0, + "languages": [], + "name": "BLINK v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biorack/blink", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "\tAutodiDAQt automates and simplifies writing data acquisition software for spectroscopy and microscopy. After defining only how to communicate with instruments and hardware, autodiDAQt generates user interfaces for long running acquisition applications, handlings data collation and retention, and provides remote communication to analysis computers. This reduces the time to get experiments running from months to hours and increases reliability for scientific experiments.\n\nAutodiDAQt metaprograms from instrument drivers directly, where possible.", + "laborHours": 0.0, + "languages": [], + "name": "AutodiDAQt v1.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chstan/autodiDAQt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "Caffeine is the CoArray Fortran Framework of Efficient Interfaces to Network Environments. Caffeine aims to produce a parallel runtime library that will support Fortran compilers with a programming-model-agnostic application binary interface (ABI) to various lower-level communication libraries. The current version of Caffeine uses the GASNet-EX networking middleware, also developed at Berkeley Lab. On many combinations of applications and platforms, GASNet-EX outperforms the widely used Message Passing Interface (MPI). Through GASNet-EX's support for communicating between graphics processing units (GPU), GASNet-EX has features that specifically target the emerging, leading-edge exascale computing platforms.", + "laborHours": 0.0, + "languages": [], + "name": "Caffeine v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/berkeleylab/caffeine", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "HAMR is a library defining an accelerator technology agnostic memory model that bridges between accelerator technologies (CUDA, HIP, ROCm, OpenMP, Sycl, OpenCL, Kokos, etc) and traditional CPUs in heterogeneous computing environments. HAMR is light weight and implemented in modern C++. HAMR can be used to manage memory with in a single code or as a data model for coupling codes in a technologically agnostic way. HAMR provides a Python module for coupling C++ and Python codes which implements zero-copy data transfers to and from Python using the Numpy array interface and Numba CUDA array interface protocols.", + "laborHours": 0.0, + "languages": [], + "name": "HAMR - Heterogeneous Accelerator Memory Resource (HAMR) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-EESA/HAMR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "PDCVOL is an extension software originated from the Proactive Data Containers (PDC) software (LBNL Track Code 2017-098), it is an HDF5 VOL connector that allows HDF5 applications to store and access data with the PDC system without the need to modify their code. The application can take advantage of the PDC optimization features and achieve better I/O performance.", + "laborHours": 0.0, + "languages": [], + "name": "PDC VOL Connector (PDCVOL) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/vol-pdc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "This is a data analysis package designed for analyzing correlation functions generated with lattice QCD calculations. The purpose is to make a centralized software suite for use by all members of my collaboration, so that various members can spend less time developing their own analysis codes, and more time extracting the interesting physics from our calculations. There are also 3 independent collaborations that have expressed interest in using this code, so there is some expectation it will be used in the broader international lattice QCD community.", + "laborHours": 0.0, + "languages": [], + "name": "Collaboration 51 Correlation Function Analysis Suite (c51_corr_analysis) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/callat-qcd/c51_corr_analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "This is a web service that allows users to request an identifier for a sequence in a specific database, given another identifier for the same sequence with respect to another given database. This process is called ID mapping. It's a minimalist service (fast, no database server) that will be significantly easier to use in a container environment.", + "laborHours": 0.0, + "languages": [], + "name": "Sequence ID Map (SeqIDMap) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/jgi-kbase/seqidmap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "The code consists of two scripts that assign functional domains to RNA virus proteins. They achieve this by aggregating the outputs of multiple freely available tools and clustering the domains into high hierarchy clusters.", + "laborHours": 0.0, + "languages": [], + "name": "RNA virus annotation pipeline (RVAP) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/rvmt-jgi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "ImpactX is the next generation of the IMPACT-Z code. It is a s-based simulation code for modeling intense beams in particle accelerators using symplectic tracking methods and includes collective effects. It is multi-node parallel and supports modern compute hardware such as GPUs, modern algorithms such as mesh-refinement and realistic geometries (embedded boundaries).", + "laborHours": 0.0, + "languages": [], + "name": "ImpactX v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-WarpX/impactx", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "\tThe Feedstock to Function (F2F) tool was designed to help scientists and companies explore viable biofuels and bioproducts early in the R&D cycle to support more productive experimentation, while reducing early-stage exploration from months/years to days/weeks (feedstock-to-function.lbl.gov). The tool focuses on using machine learning to predict biomass-derived molecule properties, while evaluating the cost, benefits, and risks of promising molecules for sustainable aviation fuels. The tool successfully predicts (within 15% of experimental values) high-throughput aviation properties for over 10,000 molecules while enabling users to explore new possibilities and opportunities rapidly and effortlessly. It also links to lightweight life-cycle analysis and techno-economic tools for cost and emissions analyses. Predicted molecule properties include melting point, boiling point, flash point, yield sooting index, and heat of combustion.\n\nTo date, F2F is more expansive and outperforms several other molecule property prediction models while enabling users (scientists, companies, and policy makers) to explore new possibilities and opportunities rapidly and effortlessly. F2F provides the foundation for developing an adaptive computational tool that predicts properties, cost, benefits, and risk of promising new and uncertified alternative jet fuel pathways and their blending effects.", + "laborHours": 0.0, + "languages": [], + "name": "Feedstock to Function (F2F) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tylerhuntington/feedstock-to-function", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "smol is a Python implementation of the Cluster Expansion Method and extensions of this methodology; which is used to fit applied lattice models from first principle calculations for subsequent use in Monte Carlo simulations for computing thermodynamic and statistical properties of atomic configuration. smol has a several notable advantages over other similar software packages. The first being its Python implementation which makes it easy to use even for users with little software and coding skills. Despite being implemented in Python, essential Monte Carlo routines are implemented in Cython such that performance is not compromised and is competitive even to similar software implemented in C/C++. Furthermore, the package has specific functionality for handling complex ionic materials (such as cathodes and electrolytes) that is not readily available in other packages. Lastly, the software has a flexible and modular design with the intention of making it fast and efficient to develop and extend the methodology.", + "laborHours": 0.0, + "languages": [], + "name": "Statistical Mechanics on Lattices (smol) v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CederGroupHub/smol", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "deep-taxon is a package for training neural networks for classifying genomic sequence data. deep-taxon provides tools for converting genomic sequence data into high performance computing file formats capable of training neural networks at scale.", + "laborHours": 0.0, + "languages": [], + "name": "deep-taxon v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exabiome/deep-taxon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "villezk@ornl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-11-21" + }, + "description": "BOOTS is a package for optimal selection of candidate operating points in large-scale manufacturing applications. It is designed to optimally select operating points to maximize predicted values of product quality and resource efficiency according to a data-driven model. The package is based on the use of a multi-input multi-output (MIMO) Gaussian process model to describe the relationships between inputs (operating points) and outputs (product quality and resource efficiency). This package does not provide any site- or process-specific information.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "BOOTS: Bayesian Optimization for Optimal Test Selection", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/krisvillez/boots", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "v1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Model for HVAC system optimization in multi-family housing market.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Model Based Real Time HVAC Systems Optimization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Optimization of HVAC systems in multi-family housing market.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "System Architecture for Real-time HVAC optimization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "SAND2022-12898 O\nDGTile is a lightweight C++17 adaptive mesh library meant to support explicit discontinuous Galerkin applications on high performance computing machines. DGTile uses a block-based adaptive mesh refinement approach, where the underlying mesh data structure is an octree in three dimensions, where each leaf node of the tree represents a Cartesian grid. Over each grid, DGTile provides modal discontinuous Galerkin basis functions to facilitate simulations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++17" + ], + "name": "DGTile", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DGTile", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-03", + "metadataLastUpdated": "2023-08-08" + }, + "description": "This Git repository contains codes for the 'Graph Learning in Physical-informed Mesh-reduced Space for Real-world Dynamic Systems' paper that will be published in 2023 SIGKDD. This work uses physical-informed prior (PiP) information to learn and predict fluid dynamics in a reduced mesh space. We propose a two-stage graph-based model for fluid velocity field reconstruction and prediction. In the first stage, we learn a subgraph autoencoder to summarize the information in a mesh-reduced space using physical-informed priors. In the second stage, we learn a dynamics predictor to predict subgraph evolution. We demonstrate the effectiveness of our model on two fluid flow datasets: lid-driven cavity flow data and cylinder flow data. This code is also applicable for any other dynamic systems with corresponding data.", + "laborHours": 0.0, + "languages": [], + "name": "Graph Learning in Physical-informed Mesh-reduced Space for Real-world Dynamic Systems", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Yeping-Hu/MeshGraph-RealDynSys", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2024-01-05" + }, + "description": "FLORIS is a controls-focused wind farm simulation software incorporating steady-state engineering wake models into a performance-focused Python framework. It has been in active development at NREL since 2013 and the latest release is FLORIS v3.5.Online documentation is available at https://nrel.github.io/floris.\n\nThe software is in active development and engagement with the development team is highly encouraged. If you are interested in using FLORIS to conduct studies of a wind farm or extending FLORIS to include your own wake model, please join the conversation in GitHub Discussions!\n\nhttps://www.nrel.gov/wind/floris.html", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "FLORIS v3.5 Wake Modeling and Wind Farm Controls Software [SWR-17-43 and SWR-14-20]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/floris", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.5" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2023-08-07" + }, + "description": "SAND2023-11957O\nSDynPy software can be used in digital signal processing, modal analysis, and geometry algorithms that are available in open literature, specifically the Synthesize Modes and Correlate and polynomial-based multiple reference modal fitters. This software can be used to perform structural dynamic testing and analysis. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SDynPy: A Structural Dynamics Python Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sdynpy", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": " v.0.6.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2023-08-07" + }, + "description": "SAND2023-12116O\nWiretap is an offensive security software package meant for penetration testers and red teams. Unlike a traditional VPN, Wiretap transparently proxies networking traffic without requiring administrator privileges. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Golang", + "Go" + ], + "name": "Wiretap", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/wiretap", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.5" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-15186 O\nYoDawg CI Runner builds a container that hosts a Gitlab runner as a service. It provides the ability to run Podman in a nested fashion as part of a CI workflow (i.e., \"Podman-in-Podman”). This allows CI jobs to be run on HPC resources by standard users through an on-demand batch scheduler. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 45.6, + "languages": [ + "Dockerfile", + "Shell" + ], + "name": "YoDawg CI Runner", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/yodawg-ci-runner", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2023-08-08" + }, + "description": "SAND2022-14468 O\nThe Python ISMAGS subgraph isomorphism algorithm is a translation of a java-based algorithm. It used for finding unique occurrences of a motif subgraph within a larger network graph. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Python ISMAGS subgraph isomorphism algorithm", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ISMAGS-in-Python", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-08", + "metadataLastUpdated": "2023-08-08" + }, + "description": "SAND2023-11967O\nGeneric Data Display (GD2) is a real-time data visualization application that can display user-defined input data. The open-source software is comprised of a back end system written in Python, and a front end user interface written in JavaScript. The back end system collects data from a variety of input sources, such as message queue, HTTP, XML, JSON, and others. The front end displays data in an Open MCT web interface, and users can configure the system by providing JSON formatted configuration files. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "python" + ], + "name": "Generic Data Display (GD2)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/generic-data-display", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-08-08", + "metadataLastUpdated": "2023-09-19" + }, + "description": "SDOM is designed to accurately represent the operation of energy storage across different timescales, including long-duration and seasonal applications, and the spatiotemporal diversity and complementarity among VRE sources. SDOM uses an hourly temporal resolution, a fine spatial resolution for VRE sources, and a 1-year optimization window. SDOM assumes that all builds of VRE are accompanied by sufficient additional transmission capacity to allow full utilization of these additional resources. Nuclear, hydropower, and other renewable generation (e.g., biomass and geothermal energy sources) are fixed based on operational data (time series) for a given year; thus, SDOM minimizes total system cost using conventional generators as balancing units and using VRE and storage technologies to achieve a user-defined carbon-free or renewable energy target. The total system cost includes capital costs, fixed operation-and-maintenance (FO&M) costs, variable operation-and-maintenance (VO&M) costs, and fuel cost for power generation and storage technologies.", + "laborHours": 0.0, + "languages": [ + "GAMS", + "Python" + ], + "name": "SDOM (Storage Deployment Optimization Model) [SWR-21-73]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SDOM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-08", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-11904O\nThis collection of original scripts is made up of Python, Makefile, and Vim. Each script performs a single commonly used function in an encapsulated manner that can easily integrate into larger application-specific software. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1641.6, + "languages": [ + "C", + "Python", + "Vim Script" + ], + "name": "Useful python scripts", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/penney-scripts", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-08", + "metadataLastUpdated": "2024-07-29" + }, + "description": "SAND2023-05829O\nROMNet is a toolbox built on the Tensorflow library for training reduced-order, neural operator surrogate models. The software is used for training reduced order neural operator surrogate models for dynamical systems applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 16446.4, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "ROMNet: Neural-Network-Based Surrogates for Reduced-Order Model Dynamics", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/romnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A tool for developing parametric inputs for other software.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/gparm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/gparm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2023-08-09" + }, + "description": "pylibROM introduces python binder for libROM through pybind11. Through python interface, users who are familiar with python can take advantage of capabilities available in libROM that is fully parallelized C++ library for reduced order modeling. libROM itself is an open source code developed at LLNL. libROM is available at https://github.com/LLNL/libROM .", + "laborHours": 0.0, + "languages": [], + "name": "python binder for libROM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pylibROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2023-08-10" + }, + "description": "SAND2023-05661O\nThe proactive intrusion detection and mitigation system (PIDMS) provides grid-edge situational awareness for cybersecurity defense by capturing real-time distributed energy resource (DER) network traffic and performance data with a novel approach that improves the detection and prevention of cyber-physical attacks. \nThe PIDMS addresses the grid-edge security gap with real-time analysis of both network traffic and photovoltaic performance data to deliver a novel, cyber-physical intrusion detection system (IDS) approach that increases the accuracy and effectiveness of detection and mitigation. \nThis hybrid IDS analysis enables dual monitoring that increases the workload of the adversary; both cyber and physical data would have to be simultaneously spoofed to evade detection. Furthermore, monitoring and analyzing cyber data are insufficient in some cases. For example, in an insider threat aimed at disrupting inverter grid-support functions where proper credentials and authentication are achieved, only the altered PV performance would indicate abnormal behavior. All in all, the PIDMS provides novel capabilities for:\n•\tDistributed, real-time cyber-physical detection and mitigation analysis\n•\tCybersecurity defense for grid-edge systems\n•\tAnalysis framework that can provide situational awareness across the transmission, distribution, and DER systems\nThe PIDMS sensor is designed to collect cyber-physical data, process the data using machine-learning algorithms, detect abnormal events, and deploy mitigations. \nWith these goals, the main functional PIDMS objectives are: \n•\tCapability to collect cyber-physical data\n•\tOnboard storage of cyber-physical data\n•\tPeer-to-peer communication\n•\tComputationally efficient machine-learning algorithms\n•\tOnline cyber-physical data analysis\n•\tAlerting/visualization capabilities\n•\tMitigation deployment capability with bump-in-the-wire (BITW) implementation \nEach of these functional objectives enable PIDMS to perform effective cyber-physical intrusion detection and mitigation.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Bash Scripts", + "Python" + ], + "name": "Proactive Intrusion Detection and Mitigation System", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2023-08-10" + }, + "description": "+++ This repository was archived by the owner on May 4, 2020. It is now read-only. +++\n\nAn offshore balance of station (BOS) model for estimating the costs in assembly, installation, financing, and decommissioning of offshore wind plants.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python", + "makefile" + ], + "name": "OffshoreBOS (Offshore Wind Balance-of-Station (BOS) Model) \"S\" was originally \"System\" [SWR-16-27]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/OffshoreBOS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Public release of a version of the cross-reference capability of the UBID software that is\nfeature-limited to cross-reference via Jaccard similarity coefficient (viz., intersection-over-union or \"IoU\") [2] over a\nquadtree-based spatial index only.", + "laborHours": 440.8, + "languages": [], + "name": "Unique Building Identifier (UBID) cross-reference using intersection-over-union (IoU) over quadtreebased spatial index", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2024-07-30" + }, + "description": "SAND2023-05682O\nThe Energy Storage Sizing, Placement, and Valuation for Distribution software allows a user to simulate sizing, placement, and operation of one or more storage assets on a distribution grid. Among its features are measuring differences to determine the best combinations, and options for configuring and comparing results. This new simulation capability leverages the Open Distribution System Simulator and the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS).\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 6840.0, + "languages": [ + "Python", + "kvlang" + ], + "name": "Energy Storage Sizing, Placement and Valuation for Distribution Networks", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/quest-ssim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2023-08-09" + }, + "description": "NREL's advanced hosting capacity analysis and System Analysis Reports can help utilities, policymakers, and solar developers better understand the impact of adding new distributed photovoltaic (DPV) systems to the electrical distribution system.\nAdvanced hosting capacity analysis considers the thresholds at which new DPV systems will trigger upgrades or changes to the electrical distribution system and evaluates the cost of different options for expanding the hosting capacity.\n\nIt is one part of NREL's work to help stakeholders better understand the distribution system costs associated with integrating new DPV systems at different penetration levels.\n\nNREL's analysis uses a bottom-up methodology that involves simulating distribution systems. The analysis considers sequential increases in hosting capacity and corresponding upgrade costs from a baseline scenario with no DPV up to penetration levels greater than 100% of peak load.", + "laborHours": 0.0, + "languages": [], + "name": "DERHCAT (Distributed Energy Resource Hosting Capacity Analysis Tool) [SWR-16-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SystemsAnalysisReports", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-07249O\nThe 2-D Surface Temperature Simulation Data and Matlab software can estimate 2D temperature fields from electrical measurements along the edge of the 2D domain.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 91.2, + "languages": [ + "Matlab" + ], + "name": "2-D Surface Temperature Simulation Data and Matlab Scripts", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/2-D-Surface-Temperature-Simulation-Data", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-06591O\nThrough National Alliance for Water Innovation funding, Sandia will be contributing to the Water treatment Technoeconomic Assessment Platform (WaterTAP) project. WaterTAP is an open-source, Python-based software package that supports the technoeconomic assessment of full water treatment trains. WaterTAP includes a modular water treatment model library spanning a broad set of water treatment processes composed of unit, property, and costing models.", + "laborHours": 1656.8, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "Sandia Contributions to WaterTAP", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/watertap-org/watertap-renrtl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2023-08-10" + }, + "description": "SAND2023-06672O\nThe Protection Settings Optimizer (PSO) uses system and fault data as inputs to formulate the problem of calculating relay settings as a mixed integer, nonlinear optimization problem (MINLP). The MINLP is solved using a genetic algorithm-based optimizer that attempts to find settings to reduce the relay operating times. \n\nThe PSO protects the power system by using the steady-state fault voltages and currents, which then calculates the optimal device setting to protect the power system.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Protection settings optimizer", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Protection-settings-optimizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2023-08-14" + }, + "description": "SAND2023-06720O\nHod Carrier is a simple proof-of-concept library for moving data from host to NVIDIA BlueField device memory using remote direct memory access. The Hod Carrier software also facilitates research activities related to the potential uses of NVIDIA BlueField data processing unit devices. Using well-established technologies (e.g., RDMA over Infiniband), it will move data from the host to the data processing unit’s memory. This software is a middleware utility for moving data without regard to its semantic meaning. Its operation is fundamentally unaffected by storage allocation. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python", + "bash shell scripts" + ], + "name": "Hod Carrier ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hod-carrier", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2023-08-10" + }, + "description": "SAND2023-05377O\nThe Modal Aerosol Model with 4 fixed modes (MAM4xx) is a performance-portable, C++ implementation for modeling the chemical reactions of aerosols in the atmosphere. MAM4xx is part of the Energy Exascale Earth System Model (E3SM). The E3SM project is an ongoing Earth system modeling, simulation, and prediction project that optimizes the use of DOE laboratory resources to meet the science needs of the nation and the mission needs of DOE. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "MAM4xx", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eagles-project/mam4xx", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Commercial Parking Application is a web-based application that alerts delivery drivers in real time to available parking\nspaces near their destinations. Parking availability can be viewed on a map in real-time, using sensor data supplied by\nexternal services. The app can be viewed with a web browser on a mobile device or PC. Currently the app supports\nconnections to real time sensors from Lacuna, Fybr, Cleverciti, and Automotus", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/parking", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/parking", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2023-08-10" + }, + "description": "SAND2023-05107O\nJuliaOceanWaves is a collection of packages and functions for modeling wave energy converters. The open-source software is designed to be used by the wave energy community to model new concepts, perform design optimization, and more.\nCapabilities include: \n•\tA representation of ocean wave spectra and input/output (e.g. read from National Oceanic and Atmospheric Administration buoys) and post-processing functionalities; \n•\tA solver for the linear potential flow radiation and diffraction equations for wave forcing on floating structures. \n•\tSolving the floating body linear dynamics in the frequency domain. \nFuture additions to the software will include solving non-linear floating body dynamics in the time-domain through time-marching Ordinary Differential Equation solvers and the pseudo-spectral optimization method.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "JuliaOceanWaves", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmichelenstrofer/JuliaOceanWaves", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2023-08-10" + }, + "description": "SAND2023-05455O\nReposcanner provides a highly modular, extensible framework for defining routines for mining data from software repositories and performing analyses on that data to yield valuable insights on team behaviors. Reposcanner features seamless support for different version control platforms like GitHub, Gitlab, and Bitbucket; smart parsing of URLs; intelligent credential management capabilities; and a comprehensive test suite. Reposcanner is connected to the Exascale Computing Project and is intended for research purposes.", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "Reposcanner ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bssw-psip/bssw-psip.github.io", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-13", + "metadataLastUpdated": "2023-08-13" + }, + "description": "SAND2023-05484O\nQuantification of Uncertainties in Neural Networks (QUiNN) is a python library centered around various probabilistic wrappers over PyTorch modules in order to provide uncertainty estimation in neural network (NN) predictions. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "QUiNN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/quinn", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-13", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-05551O\nIgor, an open-source software, manages large clusters of users in a high-performance computing community. The systems allows users to choose an operating system and reserve and request hosts. The administrative side sets up and executes requests from users while simultaneously giving them tools to manage and enforce reservation policies and user access to the hosts.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 20930.4, + "languages": [ + "Go", + "Shell", + "JavaScript", + "Vue" + ], + "name": "Igor", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/igor", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-13", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-05510O\nGNATFinder is a software tool for extracting graphical neural activity threads (GNATs) from spiking neural networks. GNATFinder efficiently extracts GNATs from spiking neural network data. A GNAT is a graph that represents the causal relationships between individual spikes in a spiking network using a combination of the network connectivity structure and the timing of individual spikes. The software allows for identifying similar, repeating threads that often reappear in a dataset. Using quadtree data structures to recursively subdivide the time interval over which spikes were produced by the spiking network, GNATFinder allows for efficient pairwise comparisons of spike times to determine the degree of causal relatedness among all pairs of spikes in a dataset. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 440.8, + "languages": [ + "C", + "C++" + ], + "name": "GNATFinder", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GNATFinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-13", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-06608O\nThe EAM-X Potential Generator code establishes parameters that describe interactions between atoms in pure metals and alloys. The open-source software allows for the understanding of the relationship between general properties of atoms and macroscopic properties of metals. The code reads in values for the parameters of the model and outputs a table that describes the interactions. This code will be published by Acta Materialia along with two papers describing the method. The output of this code is meant for use by the LAMMPS simulation code created by Sandia. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [], + "name": "EAM-X Potential Generator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/EAM-X-Potential-Generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-15" + }, + "description": "CyQuanDyn is a collection of codes developed for modelling the phonon-induced carrier pumping in ZrTe5 system. Codes in the collection include 1) TLS: time-dependent two-orbital spinless fermion Bogoliubov-de Gennes Hamiltonian simulation, 2) TDSE: ab initio time-dependent Schrödinger equation simulation of the ZrTe5 system under the periodic modulation of A1g Raman mode. Associated publication is T. Jiang, P. P. Orth, L. Luo, L.-L. Wang, F. Zhang, C.-Z. Wang, J. Zhao, K.-M. Ho, J. Wang, and Y.-X. Yao, Ab-Initio Simulations of Coherent Phonon-Induced Pumping of Carriers in ZrTe5. [arXiv:2304.08449 (2023).](https://arxiv.org/abs/2304.08449)", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "cyquandyn", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/lmqc/cyquandyn", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "version": "3.8" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Simulation tool for electrical grid security. It is possible to select from pre-loaded power system topologies, enable different grid controls\n(like AGC, power system stabilizer), add faults, tweak different parameters, add pre-modeled attack scenarios, and run\nbatch simulations to generate data needed for research.", + "laborHours": 0.0, + "languages": [], + "name": "GridSTAGE (aka PowerDrone)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/GridSTAGE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Identifying single molecules from fluorescence images obtained by a camera and obtain their location and intensity has\nmany applications. We have developed an efficient mathematical algorithm for this task and translate it into computer\nsoftware. Our algorithm are fast, stable and accurate comparing other programs to do the similar task. We have used our\nsoftware in several scientific research areas, such as tracking receptors in live cells, super resolution fluorescence\nmicroscopy, and counting mRNA copies in cells.", + "laborHours": 0.0, + "languages": [], + "name": "flifish", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hudehong/flifish", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-15" + }, + "description": "Mappymatch is a pure-python package developed and open sourced by the National Renewable Energy Laboratory. It contains a collection of \"Matchers\" that enable matching a GPS trace (series of GPS coordinates) to a map.\n\nAs of 8/14/2023, The current matchers are:\n\nLCSSMatcher: A matcher that implements the LCSS algorithm described in this paper. Works best with high resolution GPS traces.\n\nOsrmMatcher: A light matcher that pings an OSRM server to request map matching results. See the official documentation for more info.\n\nValhallaMatcher: A matcher to ping a Valhalla server for map matching results.\nCurrently supported map formats are:\n\nOpen Street Maps\n\nNOTE: This software was formerly known as YAMM (Yet Another Map-Matcher)", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Mappymatch [SWR 22-38]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mappymatch", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.4.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A transpiler that incorporates several key features. It includes a mapping and routing method, a\nprocess for decomposing gates into basis gates compatible with IBM machines, and a remapping method designed to\nenhance simulation performance. Compared to the state-of-art transpiler qiskit, we have dramatically speed up in various\nbenchmarks.", + "laborHours": 0.0, + "languages": [], + "name": "QASMTrans", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/qasmtrans", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-14" + }, + "description": "The BEopt™ (Building Energy Optimization Tool) software provides capabilities to evaluate residential building designs and identify cost-optimal efficiency packages at various levels of whole-house energy savings along the path to zero net energy.\n\nThe BEopt software can be used to analyze both new construction and existing home retrofits, as well as single-family detached and multi-family buildings, through evaluation of single building designs, parametric sweeps, and cost-based optimizations.\n\nThe BEopt software provides detailed simulation-based analysis based on specific house characteristics, such as size, architecture, occupancy, vintage, location, and utility rates. Discrete envelope and equipment options, reflecting realistic construction materials and practices, are evaluated.\n\nThe BEopt software uses EnergyPlus®, the Department of Energy's flagship simulation engine. Simulation assumptions are based on ANSI/RESNET/ICC Standards and the Building America Housing Simulation Protocols.\n\nThe sequential search optimization technique used by the BEopt software:\n\nFinds minimum-cost building designs at different target energy-savings levels\nIdentifies multiple near-optimal designs along the path, allowing for equivalent solutions based on builder or contractor preference.\n\nDownload\n\nA BEopt™ Version 3.0.1 Beta release (Mar. 16, 2023) is now available. Download the BEopt 3.0.1 Beta setup file.", + "homepageURL": "https://www.nrel.gov/buildings/beopt.html?utm_medium=print&utm_source=buildings&utm_campaign=beopt", + "laborHours": 0.0, + "languages": [], + "name": "BEopt™ (Building Energy Optimization Tool) version 3.0.1 3/16/2023 [SWR-05-41]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://beopt.nrel.gov/BEopt_setup_2.8.0.0", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrel.gov/buildings/beopt.html?utm_medium=print&utm_source=buildings&utm_campaign=beopt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "3.0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-17" + }, + "description": "Building Energy Simulation Test (BESTEST) is an NREL-developed method to validate the qualitative performance of different whole building simulations engines relative to each other. \nhttps://www.nrel.gov/docs/legosti/old/6231.pdf\n\nThe purpose of this repository is to generate BESTEST test case models, run simulations, and populate data for ASHRAE Standard 140 reporting spreadsheets for EnergyPlus® based whole building simulation tools. It was originally setup for 2014 version of Standard 140. In May of 2022 it was updated to the 2020 version of Standard 140. This update included updates and additions to existing test suites, the bulk of which was in Section 5.2 (Building Thermal Envelope and Fabric Load Tests). We did not add Section 5.5 Airside HVAC Equipment Performance, but we hope to add that later in 2022. At some point we also hope to add Section 5.2.4 ground modeling, which is currently excluded.\n\nSupported Tools\nThe default IDF generation is based on the OpenStudio® CLI, but the workflow supports a 'Bring your own IDF' use case. Additionally, for non-EnergyPlus® based tools the post processing scripts can be used if simulation results are provided as a CSV file.The scripts on this repository should work on Mac, Windows, and Linux.\n\nDependencies\nInstall OpenStudio® 3.4.0\nmake sure command line can recognize the 'openstudio' command\nThis includes EnergyPlus® 22.1\nInstall Ruby on your system if it isn't already setup.\n2.7 is used for development but other versions may work\nSince OpenStudio has its own embedded Ruby, which is used for running measures, you don't necessarily have to use a version of Ruby supported by OpenStudio.\nInstall RubyXL Ruby gem\nThis is used to modify Microsoft Excel spreadsheets\nInstall Parallel Ruby gem\nThis allows the CLI to run simulations in parallel", + "laborHours": 68339.2, + "languages": [ + "Ruby", + "HTML" + ], + "name": "BESTEST-GSR (Building Energy Simulation Test - Generation Simulation and Reporting) 2023 [SWR 18-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BESTEST-GSR", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "OpenStudio 3.4.0 EnergyPlus 22.1 Std 140 ver 2020" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-14" + }, + "description": "The bifacial_radiance software contains a series of Python wrapper functions to make working with RADIANCE easier, particularly for the PV researcher interested in bifacial PV performance. For more information, check out our documentation, Tutorials in the form of Jupyter Notebooks, or refer to our Wiki and Issues page.\n\nInstallation\nhttps://youtu.be/4A9GocfHKyM This video shows how to install the bifacial_radiance software and all associated software needed. More info on the Wiki. Instructions are also shown below.\n\nFor detailed instructions of how to install bifacial_radiance, you can also refer to the installation guide.\n\nA GUI has been added in version 3.0. The GUI reads/writes all input parameters necessary to run a simulation, and runs the specified simulation by calling the correct functions with the specified parameters. So no need to use a journal or a script! But you still need to install following the procedure below.", + "laborHours": 13528.0, + "languages": [ + "C++", + "Python", + "Tex" + ], + "name": "Bifacial_Radiance v0.4.2 [SWR-18-03]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bifacial_radiance", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.2" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-14" + }, + "description": "bifacialvf is a self-contained view factor (or configuration factor) model which replicates a 5-row PV system of infinite extent perpendicular to the module rows. \nSingle-axis tracking is supported, and hourly output files based on TMY inputs are saved. Spatial nonuniformity is reported, with multiple rear-facing irradiances collected on the back of each module row.\n\nBilinear interpolation code add-on to bifacialvf (description below) to pre-generate IV arrays and bifacial coefficients, and to examine the energy production with back side irradiance mismatch for either a portrait or landscape module.\nIncluded are IV curves and bifacial info for a Yingli (standard) module.\n\nBased on the publication: \"A Practical Irradiance Model for Bifacial PV Modules\" B. Marion, S. MacAlpine, C. Deline, A. Asgharzadeh, F. Toor, D. Riley, J. Stein, C. Hansen 2017 IEEE Photovoltaic Specialists Conference, Washington DC, 2017 URL: https://www.nrel.gov/docs/fy17osti/67847.pdf\n", + "laborHours": 1018.4, + "languages": [ + "Python" + ], + "name": "bifacialVF - Bifacial PV View Factor model 2022 [SWR 17-58]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bifacialvf", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.8.1" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-08-15", + "metadataLastUpdated": "2023-08-15" + }, + "description": "ORCA is a modeling toolset to accelerate real-time control and optimization of digital twins, including virtual models of facilities, physical facilities, and interconnections to allow optimal control of physical facilities using virtual models. ORCA is enabled by INL's RAVEN and DeepLynx software codes.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Optimization Of Real-time Capacity Allocation", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/ORCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-08-15", + "metadataLastUpdated": "2023-09-11" + }, + "description": "NMACFoam is a computational fluid dynamics tool for simulating flow and solids transport in membrane-spacer channels pertaining to reverse osmosis or nanofiltration applications. It is developed on the OpenFOAM framework and allows for simulating spacers with complex geometries. It includes porous wall boundary conditions for membranes and can accurately capture concentration polarization effects. One can perform large calculations at module-scale domain sizes using high performance computing resources with NMACFoam, which scales to 1000s of processors for problems with 1-10 million cells.", + "laborHours": 0.0, + "languages": [ + "C++", + "python", + "C" + ], + "name": "NMACFoam (Numerical-model for Membrane-spacer Assemblies and Configurations in OpenFOAM) [SWR-23-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NMACFoam", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-08-15", + "metadataLastUpdated": "2023-09-14" + }, + "description": "This software is a suite of Python files and Jupyter notebooks supporting the calculation of cost and financial parameters for the Annual Technology Baseline (ATB) electricity data, including capital expenditures, levelized cost of energy, and debt fractions using the ATB input data.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "ATB-calc (Annual Technology Baseline Calculators) [SWR-23-60]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ATB-calc", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-15", + "metadataLastUpdated": "2023-08-15" + }, + "description": "This is the code for the paper [Multi-Agent Reinforcement Learning for Adaptive Mesh\nRefinement](https://arxiv.org/abs/2211.00801), published at AAMAS 2023. 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VDGN is the first\nlearning algorithm to display anticipatory refinement behavior in AMR, and it outperforms local error\nthreshold-based heuristic strategies.", + "laborHours": 0.0, + "languages": [], + "name": "Code for Value Decomposition Graph Network and environment for AMR on linear advection", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/011235813/marl-amr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Correlate packets to the responsible processes in Linux systems. 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Hone sensors are available for a variety of platforms including Linux, Windows, and MacOSX", + "laborHours": 0.0, + "languages": [], + "name": "HONE Sensor Wireshark Shim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HoneProject/Wireshark-Shim", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-16", + "metadataLastUpdated": "2024-01-03" + }, + "description": "The U.S. Department of Energy's (DOE's) Bioenergy Technologies Office and the National Renewable Energy Laboratory (NREL) developed the BSM (Bioenergy Scenario model) to explore the development of a U.S. biofuels industry. 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Instead, it is best used to (1) analyze and evaluate alternate policies; (2) generate scenarios; (3) identify high-impact levers and bottlenecks to system evolution; and (4) seed focused discussion among policymakers, analysts, and stakeholders.", + "laborHours": 0.0, + "languages": [ + "STELLA" + ], + "name": "BSM (Bioenergy Scenario Model) 2023 FKA: Biomass Scenario Model [SWR-09-09]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bsm-public", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2023 release" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-16", + "metadataLastUpdated": "2023-08-16" + }, + "description": "BRICR is software for translating NREL's BuildingSync™ XML (BSXML) to OpenStudio® Workflow (OSW) files for simulation. 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An OSW file is created and run for each possible efficiency upgrade, the results of all simulations are stored in BSXML format.\n\nBRICR was jointly developed by NREL and LBNL for the San Francisco BayREN: Integrated Commercial Retrofits (BRICR) project funded under the DOE solicitation \"Solutions to Improve the Energy Efficiency of U.S. Small and Medium Commercial Buildings (DE-FOA-0001385)\":\n\nhttps://www.energy.gov/eere/buildings/downloads/san-francisco-bayren-integrated-commercial-retrofits", + "laborHours": 127847.2, + "languages": [ + "Ruby" + ], + "name": "BRICR [SWR 18-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bricr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.2.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-23" + }, + "description": "FE-DWBA is a software package that computes the x-ray scattering patterns of objects that locate on \na surface or buried next to a surface, such as the nano-circuits and nano-patterns of the mask used \nin the extreme ultraviolet lithography. It can incorporate the dynamical scattering effect (photons \nscattered multiple times), which is predominant in surface scattering and yield high-fidelity \nscattering patterns. The application includes surface imaging using x-rays, and critical dimension \ndetermination for semiconductor manufacturing.\n\n", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "FINITE-ELEMENT DISTORED WAVE BORN APPROXIMATION FOR SURFACE SCATTERING", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-17" + }, + "description": "SONICC computes density and velocity transfer functions for use in the initial conditions of \nmassive neutrino\ncosmological simulations. The transfer functions are backscaled using a scale-dependent growth \nfunction that produces self-consistent evolution for all three matter species (cold dark matter, \nbaryons, massive neutrinos) in the Newtonian forward model of cosmological simulations.\n\n", + "laborHours": 0.0, + "languages": [], + "name": "sf-23-021 SONICC (SCALE-DEPENDENT OMEGA FOR NEUTRINO INITIAL CONDITION CODES)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.cels.anl.gov/hacc/sonicc", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-18" + }, + "description": "SF-23-006 FAST (FAST AUTONOMOUS SCANNING TOOLKIT)The software is deployed on an edge computing device at the beamline computer attached to a \nscanning microscope. It iteratively analyzes the data collected, then identifies new scan positions \nto scan next and directs the positioners that move the sample (or probe beam) to these positions. \nOverall, it identifies a sparse set of scan positions that are sufficient to image the full sample. \nThis can reduce the scan time by >60%.\n\n", + "laborHours": 0.0, + "languages": [], + "name": "FAST (FAST AUTONOMOUS SCANNING TOOLKIT)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/saugatkandel/fast_smart_scanning", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-17" + }, + "description": "SF-23-008 This project is a Julia implementation of the Gradient Optimization of Analytic conTrols (GOAT) \noptimal control\nmethodology. It integrates with other packages in Julia's ecosystem to provide memory-efficient, \nparallelized solutions to quantum optimal control tasks. A prototype implementation of some of these algorithms was initially developed and funded by the \nASCR Early Career Research Award program under PI Travis Humble at Oak Ridge National Laboratory. \nThe current version was funded under the ASCR AIDE-QC Program under PI Paul Hovland. The current \npackage to be released has a novel implementation, syntax, and structure making it substantially \ndifferent than the original prototype (which was not released under copyright to the best of my \nknowledge).\n", + "laborHours": 0.0, + "languages": [], + "name": "GOAT. jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MCS-Quantum/GOAT.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-23" + }, + "description": "SF-23-061 A Python package that provides a streamlined interface to Griffin along with support for integration with PyARC and Workbench.\n", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "PYGRIFFIN", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-18" + }, + "description": "SF-23-026 This software computes effective transport properties of composite materials involving fibers and nanoparticles using a\nrandom-walk algorithm that efficiently scales to an arbitrary number of processes and cores. Effective transport\nproperties (thermal, electrical) are key to bridge the microstructure of complex materials with its macroscopic behavior.\nTraditional approaches either use effective medium approximations (closed mathematical expressions that are\napproximation for certain conditions) or continuum simulation models such as finite element or finite volume, which\nrequire the generation of a mesh for each configuration explored. cowalker leverages the equivalence between laplacian\nor heat equation-based models and random walks to compute the asymptotic transport properties from an ensemble of\nfirst sojourn times of a random walker moving through the composite material. This allows us to directly define a\ncomposite material as a collection of particles and use algorithms developed for molecular dynamics to quickly compute\nthe intersection of the walker with the different interfaces in the material. cowalker is developed in C++, and it relies on\nthe GNU Scientific Library for random generation. cowalker is currently delivered as source code, so the GSL library is\nnot included in cowalker's distribution. A more userfriendly version, cowalker.jl is currently in development and will be\nreleased as part of cowalker.\n", + "laborHours": 0.0, + "languages": [], + "name": "COWALKER:EFFECTIVE TRANSPORT PROPERTIES OF COMPOSITE MATERIALS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spikingnn/spikingtorch", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-23" + }, + "description": "FireCat performs multiscale simulations by coupling ab initio microkinetic simulations from CatMAP with two-dimensional continuum transport simulations from EchemFEM (Firedrake). This coupling is performed in an iterative fashion. The examples provided here are specific to electrochemical CO2 reduction to CO on Au electrodes.\n", + "laborHours": 0.0, + "languages": [], + "name": "FireCat", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/firecat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.01" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-21" + }, + "description": "SF-23-071\nJobrunner is a command line tool to manage and deploy computing jobs, organize complex workloads, and enforce a\ndirectory based hierarchy to enable reuse of files and bash scripts within a project. Organization details of a directory\ntree are encoded in Jobfiles which serve as an index of files/scripts, and indicate their purpose when deploying or\nsetting up a job. It is a flexible tool that allows users to design 16 their own directory structure, perserve their design,\nand maintain 17 consistency with increase in complexity of the project.\n", + "laborHours": 0.0, + "languages": [], + "name": "JOBRUNNER", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/akashdhruv/Jobrunner", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "georgea@ornl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-18" + }, + "description": "PoliMOR is a scalable, automated, and customizable policy engine framework for multi-tiered parallel file systems. 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The agents in PoliMOR can be customized to integrate any utilities/tools that perform tasks like metadata scanning and data placement management.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python" + ], + "name": "PoliMOR", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/olcf/polimor/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/polimor", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-24" + }, + "description": "SF-23-067\nBoxKit is a library that provides building blocks to parallelize and scale data science, high performance computing, and\nmachine learning applications for block-structured datasets. Spatial data from simulations and experiments can be\naccessed and managed using tools available in this library when working with more data analysis oriented packages like\nSciKit (https://github.com/scikit-learn/scikit-learn) and FlowNet (https://github.com/NVIDIA/flownet2-pytorch)", + "laborHours": 0.0, + "languages": [], + "name": "BOXKIT", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/akashdhruv/BoxKit", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-21", + "metadataLastUpdated": "2023-08-21" + }, + "description": "SF-23-084\nThis software provides enhanced authorization and access control support to be used in tandem with the open source\nTerminal Access Controller Access Control System (TACACS+) software tac_plus; providing Authentication,\nAuthorization and Auditing (AAA) capabilities for networking devices.\n", + "laborHours": 0.0, + "languages": [], + "name": "TACPLUS-DO-AUTH", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/argonne-lcf/tacplus-do-auth", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Cylindrical Fast Backprojection (CFBP) is a novel image reconstruction algorithm developed at PNNL that radically\nincreases the efficiency of normal backprojection techniques and is ideally suited to microwave and millimeter-wave\nimaging systems based on scanned linear arrays such as current and next-generation cylindrical body scanners in\ncommon use for aviation security screening. T", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Cylindrical Fast Backprojection", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Fayda application developed as a part of the Reaction Roulette m/q LDRD project (76006) primarily exists as a data\nvisualization, analysis and predictive platform for data collected using atomic tandem inductively coupled plasma mass\nspectrometry (ICP-MS/MS)", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Fayda", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Rhizogrid guided molecular root imaging workflow enables investigating root rhizosphere interactions in a near native\nenvironment. Non-invasive root images are captured, and three-dimensional root images are reconstructed using x-ray\ncomputed tomography technique. Root and rhizosphere samples are then harvested and processed for root-rhizosphere\nmetabolite and microbial profiling.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Rhizogrids and 3D molecular root imaging workflow", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "lees4@ornl.gov" + }, + "date": { + "created": "2023-08-23", + "metadataLastUpdated": "2023-08-28" + }, + "description": "Atomistic simulation with artificial intelligence (AI) is an emerging tool for understanding materials' properties and behaviors and predicting novel materials with optimized/targeted properties. Neural network potentials (NNPs) are outstanding in this field as they have shown a comparable accuracy to ab initio electronic structure calculations for reproducing potential energy surfaces while being several orders of magnitude faster. However, such NNPs can perform poorly outside of their training domain and typically fail catastrophically in the prediction of rare events in molecular dynamics (MD) simulations. For effective AL loops to distinguish the informative data from enhanced sampled configurations, we developed a decision engine by configurational similarity and uncertainty quantification (UQ) with data augmentation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AL-ASMR: Active Learning of Atomistic Surrogate Models for Rare Events", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/al-asmr/blob/master/license.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/al-asmr", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-23", + "metadataLastUpdated": "2023-08-23" + }, + "description": "ParaDiS, or Parallel Dislocation Simulator, is a simulation tool that performs direct numerical simulation of\ndislocation ensembles, the carriers of plasticity, to predict the strength in crystalline materials from the\nfundamental physics of defect motion, evolution, and interaction.\nThe code has been successfully deployed on high performance computing architectures and used to\nstudy the origins of strength and strain hardening for cubic crystals, the strength of micro-pillars, and\nirradiated materials at LLNL. The ParaDiS code has been successfully deployed on more than one\nhundred thousand CPU's with over ten million active degrees of freedom.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Dislocation Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ParaDiS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "4.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "We would like to disclose a code based on Python/Pytorch, in which we implement the data-driven physics-informed machine learning of Lagrangian large eddy simulation that is described in the manuscript \"Lagrangian Large Eddy Simulations via Physics-Informed Machine Learning \". High-Reynolds number Homogeneous Isotropic Turbulence is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as Large Eddy Simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about the effects of sub-grid scales on the resolved scales. Here, we take an alternative approach and design novel LES heuristics stated in terms of Lagrangian particles moving with the flow. Our \\emph{Lagrangian LES}, thus L-LES, is described by equations generalizing the weakly compressible Smoothed Particle Hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from Direct Numerical Simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The sub-grid scale contributions are modeled separately with physical constraints to account for the effects from un-resolved scales. We build the resulting model under the Differentiable Programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our Lagrangian LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.", + "laborHours": 0.0, + "languages": [], + "name": "Code for the manuscript \"Lagrangian Large Eddy Simulations vis Physics-informed Machine Learning\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Lagrangian-LES", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "FriendlyNets provides a method for assessing the promotion/inhibition effect on a microbe of a microbial community using a network of community interactions. At its core, FriendlyNets judges how much a network promotes or inhibits one of its nodes. It does this by assuming a set of dynamical systems represented by the network and using the resulting dynamics. FriendlyNets is also packaged with functions for generating a network from a set of genome-scale metabolic models (commonly called GSMs or GEMs) by simulating pairwise growth.", + "laborHours": 0.0, + "languages": [], + "name": "FriendlyNets", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/friendlyNets", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "The duqling R package is a tool for facilitating reproducible research in UQ and ML by providing easy-to-use and consistent access to a wide variety of popular (public) test functions", + "laborHours": 0.0, + "languages": [], + "name": "duqling", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/knrumsey/duqling", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "This software is being developed to support data analysis and simulation for the growing field of outer heliosphere physics. In particular, this software will allow data analysis, inference, and simulation of physical mechanisms describing how energetic neutral atoms behave that originate from the solar system's boundary with the interstellar medium. ", + "laborHours": 0.0, + "languages": [], + "name": "Program Repository for Tools for Heliophysics Science (Theseus)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Theseus", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "The Renewable Energy Potential (reV) model is a first-of-its-kind detailed spatio-temporal modeling assessment tool that empowers users to calculate renewable energy capacity, generation, and cost based on geospatial intersection with grid infrastructure and land-use characteristics.\n\nThe National Renewable Energy Laboratory (NREL) developed the reV model to help utility planners, regional and national agencies, project and land developers, and researchers assess renewable energy resource potential. Available as open source since February 2020, the reV model currently supports photovoltaic, concentrating solar power, and wind turbine technologies. The tool can model a single site up to an entire continent at temporal resolutions ranging from five minutes to hourly, spanning a single year or multiple decades.\n\nBy automating access to resource data at unprecedented scale, fidelity, and flexibility, the reV model integrates formerly disparate analysis frameworks in the fields of resource modeling, technical potential, and renewable energy cost supply curves.\n\nThe reV model currently provides broad coverage across North America, South and Central Asia, the Middle East, South America, and South Africa to inform national- and international-scale analyses as well as regional infrastructure and deployment planning.", + "laborHours": 250526.4, + "languages": [ + "Python", + "PowerBuilder" + ], + "name": "reV (The Renewable Energy Potential Model - Open Source) [SWR-21-59, SWR-20-20 and SWR-17-34]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/reV", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.8.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-28", + "metadataLastUpdated": "2023-08-28" + }, + "description": "This package evaluates an analytic formula for the change in velocity imparted to an asteroid by a 1 or 2\nkeV black body source given the radius of the asteroid, the standoff distance, the x-ray yield, the density\nof the asteroid, and the fit coefficients for the 1 or 2 keV black body source (provided in the module).\nThree variations of the formula are given; the \"original\" form, the \"modified\" form that accounts for the\nangle of incidence in calculating the melt depth, and a form based on an \"impulse\" model.\nEach formula is fit to simulations of spherical asteroids of uniform composition illuminated by black body\nx-rays.", + "laborHours": 0.0, + "languages": [], + "name": "Analytic_Deflection_of_Asteroids_by_NEDs", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Analytic_Deflection_of_Asteroids_by_NEDs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-28", + "metadataLastUpdated": "2023-08-28" + }, + "description": "In the event of a potentially catastrophic asteroid impact, with sufficient warning time, deploying a nuclear\ndevice remains a powerful option for planetary defense if a kinetic impactor proves insufficient. Predicting\nthe effectiveness of a potential nuclear deflection or disruption mission depends on accurate multiphysics\nsimulations of the device's x-ray energy deposition into the asteroid and the resulting material ablation.\nThese simulations span many orders of magnitude, require a variety of different complex physics\npackages, and are computationally expensive. Having an efficient and accurate way of modeling this\nsystem is necessary for exploring a mission's sensitivity to the asteroid's range of physical properties. To\nexpedite future simulations, we present a completed x-ray energy deposition model developed using the\nradiation-hydrodynamics code Kull which can be used to initiate a nuclear mitigation mission hydrocode.\nThe model spans a wide variety of possible mission initial conditions: four different asteroid-like materials\n(Silicon Dioxide, Forsterite, Iron, and Ice), two different source spectra (1 and 2 keV blackbodies), and\nthen a broad range of radiation fluences (0.0001 to 1 kt per square meter), source durations (10 to 100\nns), and asteroid porosities (0 to 80 percent). Using blowoff momentum as the primary metric, the modelinitiated\nsimulation results match the full radiation-hydrodynamics results to within 10 percent. Please\nreference the journal article: Burkey et al., X-Ray Energy Deposition Model for Simulating Asteroid\nResponse to a Nuclear Planetary Defense Mitigation Mission, Planetary Science Journal, (2023) for more\ninformation.", + "laborHours": 0.0, + "languages": [], + "name": "NED_Asteroid_Energy_Deposition", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/NED_Asteroid_Energy_Deposition", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-28", + "metadataLastUpdated": "2023-08-28" + }, + "description": "The Regional Energy Deployment System (ReEDS™) Model 2.0 is a free, open-access tool that empowers users to explore least-cost pathways for large-scale power sector transformation. NREL's flagship energy capacity planning model for the North American electricity system allows users to examine the interactions between policy, technology, economics, and the environment when integrating renewables onto the grid from now through 2050.\n\nThis GitHub repository contains the source code for NREL's ReEDS™ 2.0model. Users of this source code agree to the ReEDS licensing agreement: https://nrel.gov/analysis/reeds/request-access.html.\n\n The ReEDS 2.0 model source code is available at no cost from the National Renewable Energy Laboratory (NREL). The ReEDS 2.0 model can be downloaded or cloned from https://github.com/NREL/ReEDS_OpenAccess. New users must request access to the ReEDS repository through https://nrel.gov/analysis/reeds/request-access.html.\n\nA ReEDS training video (recorded in July 2020 and based on the 2019 version of ReEDS) is available on the NREL YouTube channel at https://youtu.be/Cdo27F18AZA. In addition, the Open-Access ReEDS Webinar from October 2019 gives an overview of the 2019 ReEDS model and how it works (https://www.youtube.com/watch?v=QpRtvs_0kkA).", + "laborHours": 0.0, + "languages": [ + "Python", + "R", + "GAMS", + "Jupyter Notebook" + ], + "name": "ReEDS™ 2.0 (Regional Energy Deployment System Model) Version 2.0 [SWR-20-36 and SWR-09-14]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ReEDS-2.0", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "Version 2.0" + }, + { + "contact": { + "email": "georgea@ornl.gov" + }, + "date": { + "created": "2023-08-29", + "metadataLastUpdated": "2023-08-30" + }, + "description": "Performance of file systems shift during their life cycles. Evaluating this performance change over time is not trivial. Complexity arises in the interplay between external (i.e. application I/O workloads) and internal (i.e. the filesystem state) factors. Many benchmarks can test how a filesystem performs at the current snapshot state, but to observe the change over time necessitates that the filesystem state mutate (age) between benchmark runs. For a large-scale HPC parallel filesystem, the sheer scale and amount of interacting components during I/O operations magnify these challenges. LCIO addresses the question - how will the filesystem perform at different stages of its life cycle? LCIO is a synthetic benchmark, which provides the file system aging process to increase the amount of information that existing benchmarks like IOR and MDTest yield, as well as provide additional points of data that will be useful to system architects and engineers.", + "laborHours": 0.0, + "languages": [ + "C", + "Python" + ], + "name": "LCIO", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/olcf/lcio/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/lcio", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-09-13" + }, + "description": "MemLeap is a GPU Memory Profiler built atop Nvbit (NVidia Binary Instrumentation Tool) framework. It\nanalyzes memory accesses to memory objects in GPU memory, including Unified Memory, to optimize\nmemory usage and reveal performance bottlenecks.", + "laborHours": 0.0, + "languages": [], + "name": "MemLeap GPU Memory Profiler", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IBPeng/memleap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-08-30" + }, + "description": "This software is used to compute numerous properties for the liquid and vapor phases of sodium.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Sodium Fluid Properties", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/sodium", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-08-30" + }, + "description": "This software is used to compute numerous properties for the liquid and vapor phases of potassium.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Potassium Fluid Properties", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/potassium", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-08-30" + }, + "description": "This software is used to compute numerous properties for helium.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Helium Fluid Properties", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/helium", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-08-30" + }, + "description": "This software is used to compute numerous properties for the liquid and vapor phases of carbon dioxide.", + "laborHours": 0.0, + "languages": [], + "name": "Carbon Dioxide Fluid Properties", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/carbon_dioxide", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-08-30" + }, + "description": "This software is used to compute numerous properties for air.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Air Fluid Properties", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/air", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-08-30" + }, + "description": "This software is used to compute numerous properties for nitrogen.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Nitrogen Fluid Properties", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/nitrogen", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-09-29" + }, + "description": "FAST.Farm is a multi-physics engineering tool for predicting the performance and loads of wind turbines within a wind farm. FAST.Farm uses FAST to solve the aero-hydro-servo-elastic dynamics of an individual turbine, but adds additional physics for wind farm-wide ambient wind in the atmospheric boundary layer; a wind-farm super controller; and wake deficits, advection, deflection, meandering, and merging. FAST.Farm is based on the principles of the Dynamic Wake Meandering (DWM) model—including passive tracer modeling of wake meandering—but addresses many of the limitations of previous DWM limitations. FAST.Farm maintains a low computational cost to the often highly iterative and probabilistic design process. Applications of FAST.Farm include reducing wind farm underperformance and loads uncertainty, developing wind farm controls to enhance operation, optimizing wind farm siting and topology, and innovating the design of wind turbines for the wind-farm environment.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "FAST.Farm [SWR-17-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/farms", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-09-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Converts netCDF to other formats", + "laborHours": 0.0, + "languages": [], + "name": "tsdat/ncconvert", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tsdat/ncconvert", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "emlawsky@unr.edu" + }, + "date": { + "created": "2023-09-06", + "metadataLastUpdated": "2023-09-06" + }, + "description": "Git archive containing Python modules and resources used to generate machine-learning models used in the \"Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada\" project. This software is licensed as free to use, modify, and distribute with attribution. Full license details are included within the archive. 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It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2023 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2023" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2023-09-07", + "metadataLastUpdated": "2023-09-15" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. 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The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2023 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2023 (v1.3.0.14xxx)" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-09-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Predicting Interactions of Aerosol and Clouds in Large Eddy Simulation (PINACLES) is a high-performance, massively\nparallel, anelastic atmospheric model written in Python", + "laborHours": 0.0, + "languages": [], + "name": "pinacles", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pinacles", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-09-11", + "metadataLastUpdated": "2023-09-11" + }, + "description": "Exawind-driver is a C++ code that is part of the ExaWind software stack. It was designed to couple and drive hybrid-solver computational fluid dynamics (CFD) simulations where NREL's AMR-Wind (SWR-20-85) software and NREL's Nalu-Wind (SWR-20-27) CFD codes are run simultaneously and are two-way coupled via overset meshes and the TIOGA overset-mesh library.", + "laborHours": 0.0, + "languages": [ + "C++", + "CMake" + ], + "name": "exawind-driver [SWR-23-10]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exawind/exawind-driver", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-09-11", + "metadataLastUpdated": "2023-09-26" + }, + "description": "Rust 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}, + "description": "Template for development of TMO related code at LCLS(-II)", + "laborHours": 0.0, + "languages": [], + "name": "SLAC TMO Template for GIT/DOECODE", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slac-lcls-tmo/tmo-template", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-09-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The software allows rapid development of simulations using the fermionic swap method on Microsoft's Quantum\nDevelopment Kit (QDK) framework. Gate, circuit, etc. costs can be estimated using Microsoft's resource estimator", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/FermionicSwap", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/FermionicSwap", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "greenquistit@ornl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-11-03" + }, + "description": "This code is a wrapper for Python code so that it can be accessed by MOOSE and the two can pass variables back and forth.\n\nSince this code was developed by ORNL, it must be independently approved before being added to the MOOSE repository.", + "laborHours": 1085021.6, + "languages": [ + "C++" + ], + "name": "MOOSE-Python Binder", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/moose", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "This library builds a framework for defending ML models against adversarial attacks. The library will be developed at various stages leading to publication and software release at each stage. We employ tensor decomposition strategies as preprocessing stages for the first stage to provide robustness against the prominent adversarial noise. In the second stage, we develop a latent noise generator capable of generating novel adversarial noise that threatens the existing state-of-the-art defense strategy. In the third stage, we develop a UNSUP-GAN model, where the generator is trained to denoise against latent noise and most adversarial noises. This generator can provide a robust adversarial attack against any unseen attack.", + "laborHours": 0.0, + "languages": [], + "name": "AdversarialTensors", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/AdversarialTensors", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "This software describes computational tasks for quantum computers that are derived from LANL basic science research applications such as the modeling of materials, chemicals and compounds at atomic scales. The computations focus on quantum simulation tasks, such as quantum dynamics, thermal state preparation and ground state estimation. The primary function of the software is to develop estimates of the requirements for large-scale fault-tolerant quantum computers to solve these scientific computations. The secondary focus of the software are codes for assessing the limitations of conducting quantum computations on classical computers.", + "laborHours": 0.0, + "languages": [], + "name": "Quantum Application Specifications and Benchmarks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/qc-applications", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-10-17" + }, + "description": "UQ4ML is a code repository for a set of tools for the development of robust machine learning methods, uncertainty quantification and explainability of machine learning methods. The goal of these tools is to develop more robust and statistically rigorous machine learning methods for scientific applications. These tools are developed in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Robust Machine Learning", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "LEAD is a suite of scripts to enable rapid estimation of model parameters for damage models for ductile materials using machine learning. In its current version, the only supported damage model is TEPLA, though others are planned. The data we train on are comprised of free surface velocity data as well as porosity data. Some details about our method can be found in the preprint LA-UR-23-20468 (arxiv.org/abs/2301.07790)", + "laborHours": 0.0, + "languages": [], + "name": "LEAD - LEArning Damage", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dblaschke-LANL/LEAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "Seismic interpretation aims to extract quantitative and interpretable attributes from a seismic image produced using some migration method to inform characteristics of a subsurface reservoir or target of interest. Current paradigms for computing seismic attributes mostly rely on single-task algorithms. We develop an iterative, multi-task machine learning method to learn and infer multiple attributes from a seismic image. This method is composed of two stages: a multi-task inference stage and a multi-modal, multi-task refinement stage. The basic mechanism of this method is that we train a multi-task inference neural network (NN) to estimate a set of attributes, including a relative geological time (RGT), a denoised higher-resolution (DHR) seismic image, and multiple fault attributes (including probability, dip, and strike), from a low-resolution, noisy seismic image; then we input the inferred attributes to a multi-task refinement NN to enhance the raw inference results iteratively. The two multi-task NNs are trained separately based on synthetic seismic images and associated attributes generated by a geological modeling algorithm. The software we intend to release is a PyTorch implementation of this multi-task learning method for both 2D and 3D cases along with scripts to run the training/validation. The algorithm and software can be a useful tool for automatic seismic interpretation.", + "laborHours": 0.0, + "languages": [], + "name": "Iterative multi-task learning and inference from seismic images", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/mtl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "NuDustc++ is a nucleating and sputtering dust code. It takes in the temperature-density profiles, abundance data, and chemistry network. It creates a binned size distribution from user input data to track certain grain sizes. NuDustc++ loads the data and calculates where and when a shock is detected in the input data. Using a runge-Kutta DoPri 5 integrator, it calculates nucleation and growth of grains by solving a system of coupled non-linear ODEs. It calculates sputtering based on the presence or lack of a shock by either integrating over energy or summing up the sputtering yield contributions per gas species. It is used to determine and track dust grain nucleation, growth, and erosion (sputtering) in gaseous systems to determine characteristics of the produced grain distribution.", + "laborHours": 0.0, + "languages": [], + "name": "NuDustC++", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/nuDustC", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2024-08-27" + }, + "description": "This repository contains a python package of neural network interpretability techniques (interpretability) and a keras callback to easily compute and capture data related to these techniques (values metrics) during training. It was developed to be used with NREL's BUTTER Deep Learning Experimental Framework, but does not depend on this framework and may be useful to projects outside of this framework.\n\nThe vision for this codebase is to collect algorithms for explainable artificial intelligence (XAI) in a single framework that is easy to use, easy to read, and can be expand upon. Here, we package XAI algorithms into a module called \"metrics\", which are implemented as python functions. The return type of a metric is typically a dictionary holding data of multiple data types, such as real values and numpy matrices. Callbacks and any other connector code is provided as necessary in a separate module to make these metrics more easily usable. This project depends on Tensorflow's Keras API, although it would be nice to try and support multiple backends one day.\n\nRelated to: https://github.com/NREL/BUTTER-Empirical-Deep-Learning-Experimental-Framework", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "BUTTER-Clarifier [SWR-23-61]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BUTTER-Clarifier", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pcicilio@alaska.edu" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-28" + }, + "description": "This R script takes reads the csv file of stream-wise velocity data and generates a new time series of with comparable but distinct noise using the Langevin method and library. It simulates a time series measured at 1/10 the sampling rate by calculating a moving average of 10, though other sampling rates can be calculated by adjusting the moving average window.\n\nA stationary signal is calculated by taking the difference of the original signal and the moving average, then normalizing by the standard deviation of the moving average. The stationary signal is used to calculate drift and diffusion coefficients. Those coefficients are used to generate a new stationary signal.\n\nThe new stationary signal is un-normalized and added to the moving average (or new equivalent signal) to create a new up-sampled velocity time-series.", + "laborHours": 0.0, + "languages": [], + "name": "ADCP Upsample", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/acep-uaf/ADCP_Upsample", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pcicilio@alaska.edu" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "MiGRIDS is a software that models islanded microgrid power systems with different controls and components. For example, using load and resource data from a microgrid, you could model it with additional wind turbines, battery etc. You could also try out different dispatch schemes to see which one worked best.\n\nMiGRIDS is designed to help optimize the size and dispatch of grid components in a microgrid. While a grid connect feature is expected to be added in the future, islanded operation is the focus. Note that this is a basic implementation and more features and functionality (such as a GUI) are coming!\n\nMiGRIDS runs time-step energy balance simulations for different grid components and controls. In smaller microgrid environments, dispatch decisions are being made on the order of seconds. In order to fully capture their effect, this tool lets you run simulations on the order of seconds. The end result is a more realistic representation of what can be achieved by integrating different components and control strategies in a grid.", + "laborHours": 0.0, + "languages": [], + "name": "MiGRIDS", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/acep-uaf/MiGRIDS_DOE_MarineMicrogrids", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-09-25", + "metadataLastUpdated": "2023-09-28" + }, + "description": "Finite-difference methods are widely used to simulate infrasound propagation in the atmosphere.\nFlexibility of finite-difference scheme allows implementation of highly heterogeneous media for sound\npropagation as well as complex source models for sound generation. While full 3-D finite-difference\nmethods have been utilized for local infrasound propagation with pronounced topography, 2-D modeling\napproach has been preferred for regional and global propagation as full 3-D methods generally require\nenormous computational resources. Infrasound propagation is often simulated with a second-order finite difference\nscheme. This lowest-order finite-difference scheme is robust and straightforward to implement\ncomplex boundary conditions, but the solution includes large error with numerical dispersion and\ndissipation. This large numerical error may make the second-order finite-difference not optimal for long range\ninfrasound propagation modeling as the numerical dispersion degrades the accuracy of the solution\nunacceptably. Here, we developed a high-order finite-difference solver for long-range infrasound\nsimulation. The high-order scheme is particularly popular for linear wave modeling in aeroacoustics\nowing to its low-dispersive and low-dissipative behavior. We develop and evaluate a high-order finite difference\nscheme in 2-D axisymmetric coordinates. The axisymmetry allows to approximate 3-D\nspherical sound propagation and amplitude attenuation by a 2-D method. AC2Dr is developed to simulate\ninfrasound propagation in realistic atmosphere, but can be used for linear acoustic waves in general\nmaterials with background flow. AC2Dr in an axisymmetric coordinates allows for spherical radiation of\nacoustic waves from compact sources.", + "laborHours": 0.0, + "languages": [], + "name": "Acoustic Codes in 2D Spherical Coordinate", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AC2Dr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "pcicilio@alaska.edu" + }, + "date": { + "created": "2023-09-27", + "metadataLastUpdated": "2023-09-27" + }, + "description": "WEC-GRID is an open-source Python library crafted to simulate the integration of Wave Energy Converters (WECs) and Current Energy Converters (CECs) into renowned power grid simulators like PSS®E & PyPSA.", + "laborHours": 0.0, + "languages": [], + "name": "WEC-GRID", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/acep-uaf/WEC-GRID", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-09-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DEIMoS Graphical User Interface was created as an interface for DEIMoS: Data Extraction for Integrated\nMultidimensional Spectrometry. DEIMoS is a Python package to process data from mass spectrometry instrument\ndeveloped at PNNL.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/deimos_gui", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/deimos_gui", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-09-28", + "metadataLastUpdated": "2023-09-28" + }, + "description": "SSGUI is a web-based application that integrates the integrative genomics browser (IGV) with upstream alignment pipelines enabling rapid analysis of a batch of next-generation sequencing (NGS) samples. The input to SSGUI is an NGS file system directory that is organized by experiment and reference sequence. The output is an online dashboard containing various sequencing statistics for each sample and an integrated IGV plugin enabling rapid analysis of aligned NGS reads.", + "laborHours": 0.0, + "languages": [], + "name": "SSGUI v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/ssgui", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-09-28", + "metadataLastUpdated": "2023-09-28" + }, + "description": "MVP stands for Multi-choice Viromics Pipeline. It is a pipeline that utilizes a suite of state-of-art tools:\n\ngeNomad to identify viruses, proviruses, and plasmids in sequencing data,\n\nCheckV to assess the quality, and completeness of identified viral genomes, including identification of host contamination for integrated proviruses,\nA custom code for a rapid genome clustering based on pairwise ANI,\n\nBowtie2, Samtools, and CoverM to calculate coverage of individual viral genomes by read mapping,\nA custom code to create a vOTU table of abundance,\n\nMMseqs2 to compare viral proteins to multiple databases.\n\nIt provides a quick, and intuitive pipeline to get viral sequences and corresponding properties that can be used for downstream analyses.", + "laborHours": 0.0, + "languages": [], + "name": "Multi-choice Viromics Pipeline (MVP) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ccoclet/mvp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-09-28", + "metadataLastUpdated": "2023-09-28" + }, + "description": "This software is used to process the raw data from the GridSweep instrument, a device developed under subcontract by McEachern Laboroatories for a DOE GMLC project. The software scrubbs, demodulates, and transforms point on wave voltage timeseries data into frequency/voltage amplitude/time data. It also has a GUI that allows for user selection of processed experimental data and graphing in heatmaps or 3-D plots. It was created alongside the GridSweep instrument as a part of the same project and is required to be open-source.", + "laborHours": 0.0, + "languages": [], + "name": "GridSweep Processing and Graphing Software v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/jsmacdonald/gridsweep-processing/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "khutto30@gatech.edu" + }, + "date": { + "created": "2023-09-29", + "metadataLastUpdated": "2023-09-29" + }, + "description": "Hardware/software co-designed systems are increasingly prevalent due to trends such as the adoption of hardware accelerators and the availability of heterogeneous system-on-chip (SoC) architectures. A potential security concern arising from hardware/software interaction in heterogeneous computing architectures is the possibility of software-based attacks on reconfigurable hardware, and vice versa. This is especially important when considering remote updates of the software, hardware, or both combined. In this work, we have created a remote update scheme that relies on a physical unclonable function (PUF) and multiple updating parties to deliver hardware/software updates in a secure fashion. The scheme, GridTrust, provides a high level of assurance that the system only accepts updates from approved entities while also preventing common remote attacks from compromising the security of the update process. As shown above, an attacker has multiple opportunities to attack. GridTrust’s protection features help to prevent any single attack from the locations shown in Figure 1 from succeeding.\n\nThe GridTrust scheme follows a few key tenets; (1) the usage of auditable open-source software, (2) software update authorization via two distinct entities, (3) and device authentication via a hardware fingerprinting technique known as a PUF. Used together, these techniques harden cybersecurity defenses in the electric grid supply chain against both a third-party actor and a malicious lone-wolf insider.", + "laborHours": 0.0, + "languages": [ + "Rust" + ], + "name": "GridTrust", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/huttokd/GridTrust", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2023-09-29", + "metadataLastUpdated": "2023-09-29" + }, + "description": "A novel Hybrid CUCKOO SEARCH determines combinatorial global optimum SCRAPs for specified point and pair correlations in high-entropy alloys having proper distributions.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python" + ], + "name": "Super-Cell Random APproximates(SCRAPs): A Multicomponent Alloy Structure Design Tool", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DuaneDJohnson/Hybrid-Cuckoo-Search", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2023-09-29", + "metadataLastUpdated": "2023-09-29" + }, + "description": "CMakePPLang is an object-oriented extension to the CMake language written entirely using the original CMake language, with the goal of making projects built on CMake easier to create and maintain.", + "laborHours": 0.0, + "languages": [ + "CMake" + ], + "name": "CMakePP/CMakePPLang", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CMakePP/CMakePPLang", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-09-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Deep Learning models for multi- and hyper-spectral imaging data", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/gumby-spectral-imaging", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/gumby-spectral-imaging", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "mcarbone@bnl.gov" + }, + "date": { + "created": "2023-10-01", + "metadataLastUpdated": "2023-10-01" + }, + "description": "A greatly abstracted machine learning suite built for ease of use, powered by Hydra + Lightning", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Crescendo", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://GitHub.com/matthewcarbone/crescendo", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "version": "0.0.1" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-10-02", + "metadataLastUpdated": "2023-10-05" + }, + "description": "DFLEXLIBS is a library/repository of HVAC-based demand flexibility control applications developed using Python. The library is based on portable control applications that exclusively contain control logic and are abstract to building details, such as point names and communication protocols. The library leverages semantic models and control platform-oriented interfaces to configure and run the controls in specific buildings. To date, the library contains two applications and two interfaces (for BOPTEST and VOLTTRON) and has been demonstrated in five heterogeneous buildings.", + "laborHours": 0.0, + "languages": [], + "name": "Demand Flexibility Controls Library using Semantics (DFLEXLIBS) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/DFLEXLIBS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-10-03", + "metadataLastUpdated": "2023-10-03" + }, + "description": "The Python binding for AMReX, pyAMReX, bridges the worlds of block-structured codes and data science: it provides zero-copy application GPU data access for AI/ML, in situ analysis, application coupling and enables rapid, massively parallel prototyping.", + "laborHours": 0.0, + "languages": [], + "name": "pyAMReX v23.08", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Codes/pyamrex", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-10-03", + "metadataLastUpdated": "2023-10-03" + }, + "description": "The Justice 40 tool provides a quantitative framework to support decision-making around equitable energy interventions at the community level. The tool calculates the optimal portfolio of policy interventions that explicitly mitigates energy insecurity of an eligible population, by reducing its disproportionate energy burden. The place-based analysis assumes a spatial census tract-level resolution and distinguishes different sociodemographic groups within each tract.\n\nInstead of focusing on a specific technology, the underlying J40 model captures the combined effect of a set of policy interventions, currently including weatherization, rooftop solar, community solar and community wind. For each tract, the model chooses the optimal (least cost) combination of interventions to address the disproportionate burden, considering the specific population demographics and techno-economic potentials of technologies. Mathematically, this problem is formalized as an optimization model and formulated as a linear program.", + "laborHours": 0.0, + "languages": [], + "name": "Justice 40 Tool (J40 Tool) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNLgrid/j40model", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-10-04", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Light sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as\nthe entire mouse brain. We fine-tuned an existing model, TrailMap, using expert labeled data from axonal structures in neocortex. Without\nchanging the network architecture, we implemented nnU-Net framework modifications in data augmentation, data\nforeground sampling, window learning rate, and the inference overlap method. The resulting model from these combined\napproaches yielded an improved F1 score", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/brain_ohsu", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/brain_ohsu", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-09", + "metadataLastUpdated": "2023-10-30" + }, + "description": "RouteE-Powertrain is a tool for predicting energy usage over a set of road links.\n\nRouteE-Powertrain is a Python package that allows users to work with a set of pre-trained mesoscopic vehicle energy prediction models for a varity of vehicle types. Additionally, users can train their own models if \"ground truth\" energy consumption and driving data are available. RouteE-Powertrain models predict vehicle energy consumption over links in a road network, so the features considered for prediction often include traffic speeds, road grade, turns, etc.\n\nThe typical user will utilize RouteE's catalog of pre-trained models. Currently, the catalog consists of light-duty vehicle models, including conventional gasoline, diesel, hybrid electric (HEV), and battery electric (BEV). These models can be applied to link-level driving data (in the form of pandas dataframes) to output energy consumption predictions.\n\nUsers that wish to train new RouteE models can do so. The model training function of RouteE enables users to use their own drive-cycle data, powertrain modeling system, and road network data to train custom models.\n\nhttps://pypi.org/project/nrel.routee.powertrain/\npip install nrel.routee.powertrain", + "laborHours": 0.0, + "languages": [ + "Shell", + "Rust", + "Python" + ], + "name": "RouteE-Powertrain [SWR-19-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/routee-powertrain", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-10-09", + "metadataLastUpdated": "2023-10-09" + }, + "description": "Limited-Angle Computed Tomography (LACT) is a non-destructive evaluation technique used in a variety\nof applications ranging from security to medicine. The limited angle coverage in LACT is often a dominant\nsource of severe artifacts in the reconstructed images, making it a challenging inverse problem. We\npresent DOLCE, a new deep model-based framework for LACT that uses a conditional diffusion model as\nan image prior. Diffusion models are a recent class of deep generative models that are relatively easy to\ntrain due to their implementation as image denoisers. DOLCE can form high-quality images from severely\nunder-sampled data by integrating data-consistency updates with the sampling updates of a diffusion\nmodel, which is conditioned on the transformed limited-angle data. We show through extensive\nexperimentation on several challenging real LACT datasets that, the same pre-trained DOLCE model\nachieves the SOTA performance on drastically different types of images. Additionally, we show that,\nunlike standard LACT reconstruction methods, DOLCE naturally enables the quantification of the\nreconstruction uncertainty by generating multiple samples consistent with the measured data.", + "laborHours": 0.0, + "languages": [], + "name": "DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wustl-cig/DOLCE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-09", + "metadataLastUpdated": "2024-01-17" + }, + "description": "RouteE Compass is an energy-aware routing engine for the NREL-developed RouteE ecosystem of software tools with the following key features:\n\n- Dynamic and extensible search objectives that allow customized blends of distance, time, cost, and energy (via RouteE Powertrain) at query-time\n\n- Core engine written in Rust for improved runtimes, parallel query execution, and the ability to load nation-sized road networks into memory\n\n-Rust, HTTP, and Python APIs for integration into different research pipelines and other software\n\nRouteE Compass is a part of the RouteE family of mobility tools created at the National Renewable Energy Laboratory (NREL).", + "laborHours": 0.0, + "languages": [ + "Rust", + "Python" + ], + "name": "RouteE-Compass [SWR-23-95]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/routee-compass", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.6.1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-09", + "metadataLastUpdated": "2023-10-09" + }, + "description": "MARBLES (Multi-scale Adaptively Refined Boltzmann LatticE Solver) is an open-source computational fluid dynamics package powered by the lattice Boltzmann equations and built on AMReX. In the lattice Boltzmann method, local collisions between meso-scale fictitious particles drive the governing equations which enables MARBLES to easily simulate flow around complex and/or moving geometry without the generation of a body-conforming mesh. Using AMReX data structures and operations ensures a high level of computational performance and parallel scaling on heterogenous architectures while also naturally supporting locally enhanced grid resolution and fidelity through automatic mesh refinement. New domains and problem definitions are easily specified through an input file with examples and guidance on all options and variables provided in the MARBLES documentation.", + "laborHours": 0.0, + "languages": [ + "C++", + "CMake" + ], + "name": "MARBLES (Multi-scale Adaptively Refined Boltzmann LatticE Solver) [SWR-23-37]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/marbles", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-10-11", + "metadataLastUpdated": "2023-10-11" + }, + "description": "MaCaw is a MOOSE-based application that enables domain-decomposed neutral particle transport calculations in MOOSE. It leverages the ray tracing MOOSE module for unstructured mesh tracking and OpenMC for collision physics, handling material definitions, and tallying quantities.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Macaw", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/macaw", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-10-11", + "metadataLastUpdated": "2023-10-11" + }, + "description": "This software gathers irrigation data as well as evapotranspiration rates to understand the on field water balances and track water usage.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Irrigation Monitor", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/irrmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-11", + "metadataLastUpdated": "2023-10-17" + }, + "description": "The Energy Language Model (ELM) software provides interfaces to apply Large Language Models (LLMs) like ChatGPT and GPT-4 to energy research.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ELM (Energy Language Model) [SWR-23-94]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/elm", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "peless@ornl.gov" + }, + "date": { + "created": "2023-10-13", + "metadataLastUpdated": "2023-10-17" + }, + "description": "Library of GPU-resident linear solvers", + "laborHours": 0.0, + "languages": [ + "C++", + "CUDA", + "HIP" + ], + "name": "ReSolve", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/ReSolve", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-10-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software includes the Jupyter notebooks, model pretraining and evaluation code for the EXPERT 2.0 Human-AI\nReasoning Engine V0.1. It supports pre-training a Human-AI model for reasoning over multi-layer network representations.\nIt includes prompt-based evaluation framework in a Jupyter notebook for AI reasoning and Jupyter widgets with AI-based\ntechniques for evidence generation and uncertainty quantification to support human-AI reasoning.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/EXPERT2", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/EXPERT2", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-10-19", + "metadataLastUpdated": "2023-10-19" + }, + "description": "In post-crash situations, passengers, bystanders, and first responders are exposed to the immediate safety risks of stranded energy in electric vehicle (EV) batteries. A potentially damaged battery with an unknown state of safety might go into a thermal runaway without proper handling, leading to potential loss of life and property damage. Therefore, it is imperative to develop methods, guidelines and tools to handle the post-crash EVs appropriately and minimize safety risks from immediately after an EV accident to final disposal or re-entry to the road. \nThis software tool:\n(1) provides quick access to EV specification, \n(2) estimate stranded energy left in an EV after a crash specific to EVs in a user-friendly way, \n(3) inform EV structure/disconnect for appropriate quick post-crash handling,\n(4) perform the calculation for the first responder to decide on onsite or offsite discharge, and\n(5) feature appropriate battery disposal and education/lessons learned.\nThis software tool will directly help the emergency responders to handle EV post-crash situations effectively and safely.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python", + "SQL" + ], + "name": "Ev Info And Incident Response Solutions", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/EVIRS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-10-20", + "metadataLastUpdated": "2023-10-20" + }, + "description": "This is a toy problem intended as an example on which to test V/UQ tools for multi-physics problems (coupled sub-models). It has grown from the solution to a graduate-school homework problem that has been posted on open-source (https://github.com/PhilipSmith-Canada/EthyleneOxideHomeWork).", + "laborHours": 0.0, + "languages": [], + "name": "ToyProblem-EthyleneOx", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/smith-LANL/ToyProblem-EthyleneOx", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-10-20", + "metadataLastUpdated": "2023-10-20" + }, + "description": "This software is being developed to support data analysis, modeling, and simulation for the growing field of heliosphere physics. In particular, this software will implement data analysis, modeling, inference, and simulation of physical mechanisms describing how energetic neutral atoms behave within the Earth’s heliosphere and in the interstellar medium beyond.", + "laborHours": 0.0, + "languages": [], + "name": "Software for Heliospheric Science", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/IBEX_RibbonSeparation", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-10-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Interactive user-interface application for deep probabilistic day-ahead net-load forecasting. This application allows a utility\noperator and/or other end-user to access through an easy interface the powers of advanced deep AI/ML algorithms for\ngenerating day-ahead probabilistic forecast of net-load. Also known as \"VRN3P\"", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Forte", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Forte", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-10-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PFLOTRAN leverages massively parallel, high performance computing to simulate large-scale non-isothermal multiphase\nflow, multicomponent reactive transport and electrical resistivity tomography (ERT) problems in the subsurface\nenvironment. Researchers have employed PFLOTRAN to simulate these Earth system processes on leadership class\nsupercomputers for over two decades. The code is designed to predict the future estate of environmental systems and\nbetter inform stakeholders in the regulatory decision making process (e.g., fate of contaminants, long-term stewardship for\nnuclear waste, impact of climate change, etc.). A diverse team of scientists oversees PFLOTRAN development and\nmaintenance under an open-source licensing agreement and manages contributions from an international community of\nresearchers.", + "laborHours": 0.0, + "languages": [], + "name": "PFLOTRAN 5", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/pflotran/pflotran/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "5" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-10-25", + "metadataLastUpdated": "2023-11-08" + }, + "description": "The purpose of this code is to provide a high-fidelity model of Type-5 wind turbine drivetrain for grid integration and transient stability studies. The increasing integration of renewable energy resources in evolving bulk power system (BPS) is impacting the system’s inertia. Type-5 wind turbine generation has the potential to behave like a traditional synchronous generator and can help mitigate the aforementioned impact. A hydraulic torque converter (TC) and gearbox with torque limiting feature are integral parts of a Type-5 wind turbine unit. A generic and high-fidelity model of a Type-5 wind turbine drivetrain is not openly and widely available for grid integration and transient stability studies. This hinders appropriate assessment of Type-5 wind power plant's contribution to the BPS resilience. This work develops and validates a TC model based on those generally used in automobile's transmission system.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Open Source High Fidelity Modeling Of A Type-5 Wind Turbine Drivetrain", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Type_5_Wind_Turbine_Drivetrain", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-26", + "metadataLastUpdated": "2023-12-08" + }, + "description": "PV Aerodynamic Design Engineering (PVade) is an open-source fluid-structure interaction (FSI) solver which can accurately simulate wind loads and aerodynamic stability in solar-tracking PV arrays. PVade’s pressure profiles and inertial load time series can be used as inputs into mechanical module models to study degradation mechanisms including cracking of cells, weathering of cracked cells, and glass breakage. This software enables PV plant owners to predict optimal high-wind stow strategies under a variety of weather and site conditions.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PVade (PV Aerodynamic Design Engineering) [SWR-23-49]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PVade", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-10-26", + "metadataLastUpdated": "2023-11-08" + }, + "description": "The purpose of this software is to pull data from the Oracle Primavera P6 scheduling tool and bring it into the DeepLynx data warehouse.", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "P6 Deeplynx Adapter", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/p6-deeplynx-adapter", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-10-30", + "metadataLastUpdated": "2023-10-30" + }, + "description": "The LLNL Automized Surface Titration Model (L-ASTM) is a community data-driven surface complexation\nmodeling workflow for simulating potentiometric titration of mineral surfaces. The model accepts raw\nexperimental potentiometric titration data formatted in a findable, accessible, interoperable, and reusable\n(FAIR) structure. The workflow was coded in Python and coupled to PHREEQC for surface complexation\nmodeling and PEST for data fitting and parameter estimation.", + "laborHours": 0.0, + "languages": [], + "name": "LLNL Automized Surface Titration Model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LLNL-ASTM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-30", + "metadataLastUpdated": "2024-04-05" + }, + "description": "NREL conducted comprehensive field measurements of the atmospheric turbulent wind conditions and the resulting structural wind loads on parabolic troughs at the Nevada Solar One plant from October 2021 to June, 2023. The measurement set-up included meteorological masts and structural load sensors on four trough rows. Additionally, NREL commissioned a lidar scanning the horizontal plane over the trough field. The high-resolution data set, characterizing the complex flow field and resulting structural loads, is available at https://data.openei.org/submissions/5938. The processing routines published here were used to create the data from the instruments' raw data.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "NSO Processing Scripts (NSO wind loading data set processing scripts) [SWR-23-86]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NSO_processing_scripts", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-10-30", + "metadataLastUpdated": "2023-10-30" + }, + "description": "JSAC is a Java implementation of the Seismic Analysis Code (SAC2000,\nhttps://github.com/LLNL/SAC2000). It is intended to bring the most commonly used features of SAC2000\nup to date with modern standards, support parallelized computation where possible, and implement\nimprovements in algorithms and numerics.", + "laborHours": 0.0, + "languages": [], + "name": "JSAC", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/JSAC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-10-30", + "metadataLastUpdated": "2023-10-30" + }, + "description": "The seismic response processing module is a Java based library that provides support for removing\ninstrument response signals from seismic recordings. The response module provides support for\nEvalResp, PZF, PAZ, FAP, PAZFIR, PAZFAP, FIRFAP, and CSS response types and parallel processing\nsupport for transfer operations. Additionally, the response module uses the JSR-363 units of\nmeasurement specification to allow for transfer to and from a wide range of units types to represent the\ntime-series.", + "laborHours": 0.0, + "languages": [], + "name": "Seismic Response Processing Module", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/response", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-31", + "metadataLastUpdated": "2023-11-06" + }, + "description": "Energy systems models typically take the form of complex partial differential equations which make multiple forward calculations prohibitively expensive. Fast and data-efficient construction of surrogate models is of utmost importance for applications that require parameter exploration such as design optimization and Bayesian calibration. In presence of a large number of parameters, surrogate models that capture correct dependencies may be difficult to construct with traditional techniques. The issue is addressed here with the formulation of the surrogate model constructed via Physics-Informed Neural Networks (PINN) which capture the dependence with respect to the parameters to estimate, while using a limited amount of data. Since forward evaluations of the surrogate model are cheap, parameter exploration is made inexpensive, even when considering a large number of parameters.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PINNSTRIPES (Physics-Informed Neural Network SurrogaTe for Rapidly Identifying Parameters in Energy Systems) [SWR-22-12]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PINNSTRIPES", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "martins@ornl.gov" + }, + "date": { + "created": "2023-11-01", + "metadataLastUpdated": "2024-01-30" + }, + "description": "A kubernetes based pipeline for analyzing hyperspectral data", + "laborHours": 0.0, + "languages": [], + "name": "HyperKube", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/StantonMartin/hyperkube", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-11-02", + "metadataLastUpdated": "2023-11-02" + }, + "description": "MSR-Genie is a vendor-neutral tool for fast and efficient queries about model-specific registers (MSRs).\nThe tool allows end users to query bi-directionally across MSR lists as well as processor families and\nmodels, and provides them with guidance on appropriate bitmasks. The msr-genie tool is open-source\nand easily extensible, and currently supports 30 Intel processor models and two-thousand unique MSRs.", + "laborHours": 0.0, + "languages": [], + "name": "msr-genie", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/msr-genie", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-03" + }, + "description": "LANL developed a benchmark of software code for radiation testing of microprocessors several years ago, and it was published under an open-source license on GitHub. Publishing the software is necessary for other researchers to adopt and implement this benchmark for radiation testing of other microprocessors to standardize test practices so that test data can be compared across different microprocessors. The original codes have been used several times by other organizations to test a wide range of microcontrollers and microprocessors. \nAfter several years of research, LANL is ready to update the benchmark. Changes include:\n1.\tAddition of new codes that allow common software codes to be tested,\n2.\tAddition of new codes that instrument more microprocessor circuitry, \n3.\tAddition of input patterns that allow for a more compressive understanding of how the memory layout affects the sensitivity to radiation-induced faults and better use of automated test pattern generation standards, and\n4.\tModification of current codes for faster and more resilient detection, reporting and correction of radiation-induced faults.\nThese codes have been tested by LANL researchers over the last few years, which has been published in the open literature. As the code base for the new benchmarks are stable, it is time to release the update to the GitHub repository, where the original codes were released.", + "laborHours": 0.0, + "languages": [], + "name": "Update to the Microcontroller Benchmark for Radiation Testing", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/benchmark_codes", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-03" + }, + "description": "The software provides machine learning analysis and visualization to detect patterns in microbiome data, including topic modeling, probabilistic graphical modeling, conventional machine learning methods, and deep learning. The software is written in python and R, it uses some python and R libraries as well as big open-source libraries like sklearn, networkX, pytorch (python), pgmpy (python), and bnlearn (R). It also has a script to use for MALLET and DTM (open-source packages for topic modeling, written in Java).", + "laborHours": 0.0, + "languages": [], + "name": "ML for microbiomes", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ML-for-microbiomes", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-03" + }, + "description": "The unambiguous identification of compounds from their electron ionization mass (EI-MS) spectra remains a significant unsolved problem in the field of metabolomics and analytical chemistry as a whole. Typically EI-MS spectra are compared using various mathematical operations that convert the spectral similarity or differences into a distance-like metric that roughly approximates the similarity of any two spectra. A commonly used metric for this is the cosine similarity metric which has values close to one for very similar spectra and a value of zero for very dissimilar spectra; however, no metric is perfect. Due to the prevalence of structurally-similar compounds such as isomers and the prevalence of certain fragmentation patterns across structurally-dissimilar compounds, the unambiguous assignment of EI-MS spectra compounds remains difficult. Frequently, querying an observed EI-MS spectrum against a large database such as the NIST17 library yields multiple possible assignments requiring the end user to distinguish between multiple high scoring hits, or multiple low scoring hits while keeping in mind that the correct hit may not be in the database at all. Although techniques such as orthogonal information from techniques such as chromatography can greatly aid in unambiguous assignment, this also requires more complicated experimental designs and access to more complicated analytical instrumentation.\nSubstructures can be trivially detected and represented as strings using a previously published technique called node coloring from a known chemical structure. However, for experimentally-derived EI-MS spectra this information must be derived from the spectra itself (i.e., because we do not know what compound it represents). To achieve this, the software uses techniques from the field of machine learning and a large training dataset of EI-MS spectra corresponding to known structures annotated with substructure strings, to build models that can predict the presence of a given chemical substructure from an EI-MS spectrum directly.If these predictions are of high-quality (i.e., are unlikely to be false positives), the presence of one or more predicted substructures can be used to constrain the number of possible hits for a query spectrum. Mathematically, this restriction could be expressed in many forms, but the most straight-forward implementation is to weight the cosine similarity of a query spectrum and a plausible database match with a Tanimoto-like coefficient based on the ratio of the number of substructures predicted to the number of substructures present in the potential database hit.\nDetermining which combination of models best reduces assignment ambiguity will be achieved using a combination of manual curation and optimization techniques such as genetic algorithms. This software will perform all the steps necessary to construct said models from a training dataset and evaluate them using a holdout dataset. Various statistical analyses can be performed to determine if this approach does decrease assignment ambiguity. For example, if this approach works, on average, the rank-order of the correct assignment for the holdout set of EI-MS spectra should decrease and the weighted cosine similarities for most of the possible matches in the database should be better than the unweighted cosine similarities. Furthermore, this same pipeline can be used on real experimental data to generate less ambiguous assignments.", + "laborHours": 0.0, + "languages": [], + "name": "EI_MS_ML", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EI_MS_ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-03" + }, + "description": "Machine learning (ML) of interatomic potentials show great promise to accelerate scientific simulation, e.g., by emulating expensive computations at a high accuracy but much reduced computational cost. Training datasets are calculated from computationally expensive ab initio quantum mechanics methods, density functional theory (DFT). Trained on this data, an ML model can be very successful in predicting energy and forces for new atomic configurations. A critical factor is the quality and diversity of the training dataset. Thus, a highly automated approach to dataset construction based on active learning framework is designed suitable for material physics.\n\nThe active learning scheme begins with fully randomized atomic configurations. Then, many Molecular Dynamics (MD) trajectories are simulated using current ML potentials, where each MD trajectory is initialized to a random disordered configuration. The temperature is varied in order to diversify the sampled configuration during these simulations. The variance of predictions for eight neural networks within an ensemble is analyzed to determine whether the model is operating as expected. This helps in determining whether collecting more data would be helpful to the model by checking the ensemble variance is greater than the threshold. In this case, the MD trajectory is terminated and the final atomic configuration is placed on a queue (SQL database) for DFT calculations and added to training dataset. Periodically, ML model is retrained to the updated training model. This Active Learning loop is iterated until the cost of MD simulations becomes prohibitively expensive. The MD simulations will hopefully be sufficiently robust to support nucleation after many active learning iterations. In this sense, active learning scheme must automatically discover the important low energy and nonequilibrium physics.", + "laborHours": 0.0, + "languages": [], + "name": "Active Learning Framework", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/alf", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-08" + }, + "description": "VPSC is a mean-field polycrystal plasticity code for the prediction of the mechanical response and microstructure evolution\nof polycrystalline aggregates. The VPSC code is the computational realization of the visco-plastic self-consistent theory of polycrystal deformation. Both the theory and details of its numerical implementation were originally reported by R.A.\nLebensohn and C.N. Tomé: \"A self-consistent approach for the simulation of plastic deformation and texture development\nof polycrystals: application to Zirconium alloys\", Acta Metallurgica et Materialia 41, 2611 (1993). Since then, the VPSC code\nhas experienced several improvements and extensions and it is nowadays extensively used to simulate plastic deformation\nof polycrystalline aggregates and to interpret experimental evidence on metals, minerals and polymers.", + "laborHours": 0.0, + "languages": [], + "name": "Viscoplastic selfconsistent (VPSC) code (version 8, open source)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vpsc_code", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-11-08", + "metadataLastUpdated": "2023-11-08" + }, + "description": "The purpose of the software is to provide initial machine learning results to an unknown data set.", + "laborHours": 0.0, + "languages": [ + "Python", + "R" + ], + "name": "Digital Twin Analytics Search", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Digital-Twin-Analytics-SEARCH", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wilsonbe@ornl.gov" + }, + "date": { + "created": "2023-11-08", + "metadataLastUpdated": "2023-11-08" + }, + "description": "Earthdata Pub is a toolset that provides forms and workflows so that a data producer can request archival of their NASA-funded data, NASA can determine which (if any) DAAC is appropriate to that data, and the selected DAAC can work with the data producer to get the data and metadata necessary for publication.", + "laborHours": 0.0, + "languages": [], + "name": "Earthdata Pub", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eosdis-nasa/earthdata-pub", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-11-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Low precision-based nearest neighboring particle searching algorithm.This work introduces a computationally efficient Nearest Neighbor Particles Searching (NNPS) algorithm tailored for the\nmeshfree Smoothed Particle Hydrodynamics (SPH) method in large-deformation problems simulations. The innovation lies\nin the strategic use of low-precision float-point 16 (FP16) in NNPS for efficiency purpose.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/lpNNPS4SPH", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/lpNNPS4SPH", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-11-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a repository for work conducted in our research paper we would like to make open source. The main features are\nthat we forked another open source library and added functionality that enabled us to compute neural-kernel objects using\nrandom vector projection software for both computer vision and large language text models. The new features are\nspecifically code that enables the calculation of objects we define and refer to as the projection pseudo neural tangent\nkernel and the projection trace neural tangent kernel; both of which are approximations of the empirical neural tangent\nkernel. The software that computes the projections themselves are not part of the invention, but are necessarily tied to our\nsoftware and licensed via MIT license, and BSD 2 license.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/projection_ntk", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/projection_ntk", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-11-14", + "metadataLastUpdated": "2023-11-16" + }, + "description": "ThermalNetwork is software to size distributed ground heat exchangers for district-connected ground-source heat pump systems. The intended audience includes Ground Source Heat Pump Designers.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "ThermalNetwork [SWR-23-101]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/thermalNetwork", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-11-14", + "metadataLastUpdated": "2023-11-14" + }, + "description": "Official code for the NeurIPS 2023 paper \"Neural Image Compression: Generalization, Robustness, and\nSpectral Biases\". This code can be used to:\n- Computing spectral distortion errors of images compressed with traditional codes or neural image\ncompression models (as proposed in the aformentioned paper)\n- Visualize power spectral densities and fourier heatmaps (as proposed in the aformentioned paper)\n- Train and test a variety of neural image compression models", + "laborHours": 0.0, + "languages": [], + "name": "Out of distribution evaluation for neural image compression", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/klieberman/ood_nic", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-11-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Model-based Deep Reinforcement Learning for Real-time Grid Emergency Voltage Control. A model-based Deep Reinforcement Learning (DRL) framework where a deep neural network (DNN)-based\nsurrogate model is utilized within the control policy learning framework, making the learning process faster and more\nsample efficient", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/MBDRL", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/MBDRL", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-11-15", + "metadataLastUpdated": "2023-11-15" + }, + "description": "Open OnDemand is a software tool that is used to access HPC resources. It provides a framework for organizations to create apps and other additional functionality that may be useful to the organization. This code expands upon the pre-existing INL applications, including the NEAMS Workbench application, MOOSE Herd applications, and others. These changes significantly expand upon the functionality originally provided. Due to the extensive functionality that we added, these changes would not be added to the original application but would function as a standalone application that other organizations would be able to utilize on their own systems.", + "laborHours": 0.0, + "languages": [ + "Bash", + "JavaScript", + "Ruby", + "HTML", + "CSS", + "yml" + ], + "name": "Inl Open Ondemand Applications", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HPC_OOD", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-17", + "metadataLastUpdated": "2023-11-17" + }, + "description": "This software is an open-source Python library that provides tools for processing hyperspectral neutron time-of-flight radiography data. This type of data allows material decomposed reconstructions to be generated with the use of material characteristic spectral responses and the algorithms provided in this code library. The software library will contain tools for pre-processing the neutron measurement data, estimating measurement system parameters, reconstructing material decomposed radiographs, and computing material decomposed computed tomography (CT). Furthermore, it will have capability to generate and process simulated neutron time-of-flight data with the goal of benchmarking and demonstrating the tools that are provided. The software will include thorough documentation and application examples.", + "laborHours": 0.0, + "languages": [], + "name": "TRINIDI (Time-of-Flight Resonance Imaging with Neutrons for Isotopic Density Inference)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/trinidi", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-17", + "metadataLastUpdated": "2023-11-17" + }, + "description": "The Trees program is a pre-processing tool used to virtually build forest fuel arrays to be read into FIRETEC, QUIC-Fire, or similar wildland fire related tool which requires the conversion of raw collected forest data to a digitalized voxelization of the fuels.", + "laborHours": 0.0, + "languages": [], + "name": "Trees", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Trees", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-17", + "metadataLastUpdated": "2023-11-21" + }, + "description": "Automatically summarizing a collection of documents requires analyzing their features using various operations. Hypercane is a framework for building algorithms for sampling files from a collection. Sampling is a vital part of automatic summarization. Hypercane ties together many existing third-party libraries. These libraries include those for processing web resources, natural language processing for analyzing text and filtering documents, and machine learning for clustering summarization candidates. A user can run up to more than 70 operations on a corpus in the order of their choosing. Through these operations, they can create custom automatic summarization algorithms to help them process the corpus of their choice. Details of the algorithms possible with Hypercane are available in Jones 2021. Details of running Hypercane are available in Jones et al.; 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Hypercane", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/hypercane", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-17", + "metadataLastUpdated": "2023-11-21" + }, + "description": "This disclosure is for version 2.x of a mesoscale model called Phase Field Dislocation Dynamics (PFDD). PFDD is used for investigating deformation in nanoscale (grain sizes of ~300 nm and less) materials, such as metals and alloys. This approach models the motion and interaction of individual defects, namely dislocations, in the material using scalar-valued phase field variables, also called order parameters. The system is evolved through energy minimization thus the model calculates the total energy density in terms of the phase field variables. The energy minimization is completed using the Ginzburg-Landau equation, and is implemented with explicit time integration. The total system energy can be comprised of several terms, including the strain energy (which describes dislocation-dislocation interactions), the energy due to an applied stress (dislocation interactions with the applied stress), and a core/lattice (perfect dislocations) or generalized stacking fault (partial dislocations) energy (described the dislocation core structure). The latter term in particular may vary based on the crystal structure being modeled and is typically informed using lower length scale (e.g., atomistic) approaches, although no such (atomistic) calculations are completed within the PFDD algorithm. This basic formulation was previously reviewed by Los Alamos National Laboratory and released under license number C17113. This previously reviewed version we will henceforth refer to as PFDD v1.0. \n\nPFDD v1.0 consisted of 2 codes (one parallel and one serial) plus input files, all written in the C language. This new disclosure is addressing the next versions of the PFDD, versions 2.x. There have been several enhancements of PFDD v1.0, which are described here and included in the attached code, which we will refer to as PFDD v2.0. There are also several new features described here that are either planned or already in process and are expected to be subsequent releases, i.e., v2.1, v2.2, ...v2.x.", + "laborHours": 0.0, + "languages": [], + "name": "Phase Field Dislocation Dynamics (PFDD) version 2.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Phase-Field-Dislocation-Dynamics-PFDD-2.x", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-11-27", + "metadataLastUpdated": "2023-12-20" + }, + "description": "The Wind Asset Value Estimation System (WAVES) model is a coupling framework for core NREL techno economic analysis software models to estimate capital expenditures (ORBIT), operational expenditures (WOMBAT), and energy production (FLORIS) for offshore wind power plants. Existing workflows to couple the three models for lifecycle performance and cost estimation require a large amount of manual and error-prone setup to combine both shared inputs and dependent outputs, as such WAVES's primary functionality is to wrap the core logic for running standard modeling workflows to ensure shared settings and entangled results are correctly and efficiently combined every time. SEE ALSO: https://pypi.org/project/WAVES/", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "WAVES (Wind Asset Value Estimation System) [SWR-23-81]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WAVES", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.5" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-11-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Similarity learning of two mass spectrometry runs solely using MS1 data", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/deep_scoreMS1", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/deep_scoreMS1", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-11-28", + "metadataLastUpdated": "2023-11-30" + }, + "description": "The Advanced Locomotive Technology and Rail Infrastructure Optimization System (ALTRIOS) is a unique, fully integrated, open-source software tool to evaluate strategies for deploying advanced locomotive technologies and associated infrastructure for cost-effective decarbonization. ALTRIOS simulates freight-demand driven train scheduling, mainline meet-pass planning, locomotive dynamics, train dynamics, energy conversion efficiencies, and energy storage dynamics of line-haul train operations. Because new locomotives represent a significant long-term capital investment and new technologies must be thoroughly demonstrated before deployment, this tool provides guidance on the risk/reward tradeoffs of different technology rollout strategies. An open, integrated simulation tool is invaluable for identifying future research needs and making decisions on technology development, routes, and train selection. ALTRIOS was developed as part of a collaborative effort by a team comprising the National Renewable Energy Laboratory (NREL), University of Illinois Urbana-Champaign (UIUC), Southwest Research Institute (SwRI), and BNSF Railway.\n\nPython Package: https://pypi.org/project/altrios/\nRust Crate: https://crates.io/crates/altrios-core", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ALTRIOS (Advanced Locomotive Technology and Rail Infrastructure Optimization System) [SWR-22-54]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ALTRIOS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "V0.1.3" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-12-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Database of building energy standards data for building energy simulation.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/building-energy-standards-data", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/building-energy-standards-data", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-12-05", + "metadataLastUpdated": "2023-12-05" + }, + "description": "We present an open-source Python-based framework that can be used for objective evaluation of\nAtmospheric Rivers (ARs) in climate models. With a comprehensive pool of pre-defined metrics, this\npackage is useful for systematic AR evaluation across a range of model simulations, such as the MIPs in\nCMIP5/6 models and large ensemble experiments.", + "laborHours": 0.0, + "languages": [], + "name": "PCMDI PMP Interactive Visualization Web Page, Atmospheric River Metrics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kristinchang3/peak_season_cmec", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-12-05", + "metadataLastUpdated": "2023-12-05" + }, + "description": "scaleupROM is a scalable, physics-constrained reduced order model (ROM). It aims to provide robust,\naccelerated physics predictions at extrapolated scales, based on the small, component-level data. This is\nimplemented by combining projection-based ROM with discontinuous Galerkin domain decomposition, in\nthe framework of MFEM and libROM. It currently supports the Poisson equation and Stokes flow\nequation, and more work is in progress toward general, nonlinear physics systems.", + "laborHours": 0.0, + "languages": [], + "name": "Scalable Reduced Order Model with Discontinuous Galerkin Domain Decomposition", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/scaleupROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-12-07", + "metadataLastUpdated": "2024-11-01" + }, + "description": "UWLi is a user interface for modifying Universal Workflow Language (UWL) files. UWL is a data format used to represent high fidelity scientific procedures in a generalized, field agnostic workflow format.\n\nSee related publication: https://arxiv.org/pdf/2409.05899", + "laborHours": 3040.0, + "languages": [ + "Smarty", + "Python" + ], + "name": "UWLi (Universal Workflow Language Interface) [SWR-24-12]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Universal-Workflow-Language-Interface", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-12-11", + "metadataLastUpdated": "2024-02-09" + }, + "description": "The Production Financial Analysis Scenario Tool (ProFAST) provides a quick and convenient in-depth financial analysis for production facilities. The model uses a generally accepted accounting principles analysis framework and provides annual projections of income statements, cash flow statements, and balance sheets. ProFAST allows users to calculate the levelized cost of the produced commodity by providing an expected financial performance, or on the other hand, calculate the financial performance based on an input price. Model inputs generally capital expenditures, operating expenditures, and financing structure. The programmatic approach of ProFAST allows users to easily perform large sensitivity analyses and integrates easily with other python tools.", + "homepageURL": "https://github.com/NREL/ProFAST", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ProFAST (Production Financial Analysis Scenario Tool) [SWR-23-88]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://github.com/NREL/ProFAST/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://github.com/NREL/ProFAST", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-12-13", + "metadataLastUpdated": "2023-12-18" + }, + "description": "BuildStockQuery is a python library designed to simplify and streamline the process of querying massive, terabyte-scale datasets generated by ResStock(TM). ResStock (SWR-19-15) is a U.S. DOE-supported, NREL-built, national residential building energy stock model that enables a new approach to large-scale residential energy analysis across the U.S. by combining large public and private data sources, statistical sampling, detailed sub-hourly building simulations, and high-performance computing. \n\nBuildStockQuery offers an intuitive Object-Oriented Programming (OOP) interface to the ResStock output dataset allowing users to easily perform common queries and receive results in familiar pandas DataFrame format, abstracting away the need for complex SQL query. By initializing a query object with the pertinent Athena database and table names, users can easily query for various kinds of insights, for example, timeseries electricity for an end use for a given state grouped by building types.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "BuildStockQuery [SWR-23-58]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/buildstock-query", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-12-13", + "metadataLastUpdated": "2023-12-13" + }, + "description": "To achieve the desired particle size of biomass feedstocks during preprocessing for trouble-free handling and conversion to produce biofuels and bioproducts, the raw materials must undergo a crucial milling process. The particle size of biomass plays a critical role in subsequent biofuel manufacturing, where a larger area-to-volume ratio facilitates efficient synthesis while balancing the impact of moisture on biomass storage. To optimize biofuel production efficiency and overcome these challenges, it is imperative to accurately predict the particle size distribution (PSD) of the biomass in the design of efficient preprocessing systems. The population balance model (PBM), upon empirical calibration and validation, can provide rapid prediction of post-milling PSD of granular biomass. However, PSD has limitations related to mass conservation and the absence of moisture considerations. To overcome these drawbacks, a deep learning model called the enhanced deep neural operator (DNO+) is implemented in the code. This model not only retains the capabilities of the PBM in handling complex mapping functions but also incorporates additional factors influencing the system. By considering various experimental conditions such as sieve size and moisture content, the trained DNO+ model can effectively predict the PSD after milling for any given feed PSD. To further reduce the reliance on experimental data, the PBM is integrated into the DNO+ model, resulting in a physics-informed DNO+ (PIDNO+). The PIDNO+ model addresses the non-conservation of quality exhibited by the PBM while inheriting the advantages of the DNO+ model in considering multiple influencing factors. Moreover, the PIDNO+ model significantly reduces the amount of data required for model training. Both deep learning models, i.e., DNO+ and PIDNO+, are excellent in predictive performance, offering swift and accurate machine learning-based predictions. The use of this code that contains these models will assist in guiding the proper milling equipment selection and operational conditions to achieve the desired biomass particle sizes, ensuring the efficiency of subsequent biofuel and bioproduct production processes.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Smart Preprocessing & Robust Integration Emulator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/SPRITE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-12-15", + "metadataLastUpdated": "2024-04-19" + }, + "description": "Ryujin (https://github.com/conservation-laws/ryujin) is a high-performance finite-element software for solving mathematical partial differential equations (PDEs) with dominant hyperbolic structures. The author of this request, Eric Tovar, is using Ryujin as a high-performance tool for his Mark Kac postdoctoral fellowship research at LANL. Eric would like to contribute openly to the ryujin software without changing its core functionality. This includes: (i) bug fixes; (ii) re-organization of code for performance and syntactic updates including documentation; (iii) implementation of new PDE numerical methods that align with the core solver; (iv) implementation of new initial state configurations for target applications.", + "laborHours": 0.0, + "languages": [], + "name": "LANL contribution to ryujin, an open source finite element solver", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EricTovar-LANL/ryujin-contribution.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-12-15", + "metadataLastUpdated": "2023-12-15" + }, + "description": "Software tools for quantifying atmospheric variability and uncertainty for use in uncertainty quantification of acoustic/infrasound propagation simulations.", + "laborHours": 0.0, + "languages": [], + "name": "stochprop", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Seismoacoustics/stochprop", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-12-15", + "metadataLastUpdated": "2023-12-15" + }, + "description": "This is code associated with the publication “Nonparametric Multi-shape Modeling with Uncertainty Quantification,” authored by Hengrui Luo (Lawrence Berkeley National Laboratory) and Justin Strait (Los Alamos National Laboratory). The code is used to fit multiple-output Gaussian process (GP) models of planar closed curves to collections of ordered point sets, allowing for flexible nonlinear prediction of the underlying curve under dense or sparse point set samplings and with or without noise, as well as tractable uncertainty quantification. To do this, we employ use of a periodic kernel to account for the nonlinear input space of closed curves, and combine with coregionalization models to account for dependence both (i) between curve coordinates, and (ii) between pairs of curves. Functions in the code are capable of fitting these models, as well as performing additional tasks with the fitted curves such as (a) shape registration and alignment, (b) shape averaging, and (c) fitting for curve sub-populations / clusters.", + "laborHours": 0.0, + "languages": [], + "name": "Code for multi-shape Gaussian process (GP) fitting with uncertainty quantification (UQ)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/multishapeGP", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-12-15", + "metadataLastUpdated": "2023-12-15" + }, + "description": "Class and supporting functions to utilize an object oriented approach to F-ANOVA", + "laborHours": 0.0, + "languages": [], + "name": "F-ANOVA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/F-ANOVA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-12-20", + "metadataLastUpdated": "2023-12-20" + }, + "description": "PECAN2, Pose Classification with 3D Atomic Network 2, presents an innovative approach to pose\nclassification in computational modeling, particularly in the context of molecular docking. Traditional\nmethods like docking, which rely on physics-based calculations, are prone to inaccuracies in predicting\nbinding poses during experimental testing. While machine learning (ML) approaches, such as ML-driven\npose classification, have been introduced to address these issues, they often depend on the availability of\ncrystal structure data.\nIn contrast, PECAN2 introduces a novel pose classification method that operates independently of crystal\nstructures. Instead, it utilizes a 3D atomic neural network with Point Cloud Network (PCN) to establish\ncorrelations between docking scores and experimental data. This approach marks a departure from\nprevious studies that heavily relied on crystal structures for labeling.\nThe key innovation lies in the ability of PECAN2 to enhance the performance of molecular docking by\nfiltering out false positives and false negatives through the correlation between docking scores and\nexperimental data.", + "laborHours": 0.0, + "languages": [], + "name": "PECAN2", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/PECAN2", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-12-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A multi-task neural network for the simultaneous identification of multiple compounds from XRD data obtained in a synchrotron-based hydrothermal fluid system. To enhance the alignment between the training and test datasets, random noise is introduced into the synthetic training dataset, and minor labeled experimental data is incorporated. Additionally, we employ a weighted cross-entropy loss function to address data imbalances and ensure smoother model training.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/mlxrd", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mlxrd", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wehart@sandia.gov" + }, + "date": { + "created": "2024-01-02", + "metadataLastUpdated": "2024-01-02" + }, + "description": "Pypm supports the analysis of time series data to identify patterns that reflect the execution of a known process. Pypm uses a process model to identify patterns, where the execution of a process is decomposed into a sequence of related activities. A process model describes the activities used in the process, dependencies between activities that constrain their execution, resources needed to execute each activity and information about the activities that are observable.\n\nPypm implements process matching algorithms that infer a schedule of the activities in a process model to maximize the alignement of the process with observational data. Pypm uses numerical optimization to search for a maximal match score. When data is labeled and associated with the resources in the process model, then integer programming methods are used to find an optimal match. For unlabeled data, tabu search methods are used to predict data labels, which can then be used by integer programming methods.\n\nPypm solvers address a variety of complicating concerns, including variable-duration process activities, gaps in activity execution, preferences for compact matches, and tailored methods that depend on data characteristics.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "pypm", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pypm", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-02", + "metadataLastUpdated": "2024-01-09" + }, + "description": "This repository contains all of the methods for the NSRDB data processing pipeline. The NSRDB is a serially complete collection of hourly and half-hourly values of meteorological data and the three most common measurements of solar radiation: global horizontal, direct normal and diffuse horizontal irradiance.", + "laborHours": 0.0, + "languages": [ + "HTML", + "C", + "Jupyter Notebook", + "Python" + ], + "name": "NSRDB (National Solar Radiation Database Software) [SWR-23-77]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/nsrdb", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "4.0.1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-03", + "metadataLastUpdated": "2024-03-11" + }, + "description": "PowerSimulations.jl is a Julia-based BSD- licensed power system operations simulation tool developed as a flexible and open source software for quasi-static power systems simulations including Production Cost Models. PowerSimulations.jl tackles the issues of developing a simulation model in a modular way providing tools for the formulation of decision models and emulation models that can be solved independently or in an interconnected fashion. \n\nFor further information regarding the Sienna modeling framework at NREL, see: https://www.nrel.gov/analysis/sienna.html", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "PSI (PowerSimulations.jl) [SWR-23-104]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-Sienna/PowerSimulations.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.27.5" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-01-04", + "metadataLastUpdated": "2024-01-04" + }, + "description": "DISCO is a suite of software for configuring and parallelizing large numbers of distribution power flow simulations and analyzing the results.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook", + "Mustache" + ], + "name": "DISCO (Distribution Integration Solution Cost Options) v0.5.0 [SWR-20-02]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/disco", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.5.0" + }, + { + "contact": { + "email": "burtscher@txstate.edu" + }, + "date": { + "created": "2024-01-08", + "metadataLastUpdated": "2024-01-08" + }, + "description": "LICO is a fast lossless image compressor. It takes BMP files (in 24-bit BMP3 format) as input.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "burtscher/LICO", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/burtscher/LICO", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-08", + "metadataLastUpdated": "2024-04-16" + }, + "description": "BlendPATH provides case-by-case techno-economic analysis for potential projects where hydrogen is blended into a natural gas transmission pipeline. BlendPATH estimates 1) the transmission pipeline modifications and operating conditions necessary to blend hydrogen to a user specified volume faction of hydrogen in pipeline gas and 2) the incremental capital and operating expenses to prepare said transmission pipeline for hydrogen blending. BlendPATH is developed in Python and requires SAInt, a underlying commercial natural gas pipeline network modeling software, to run. Pipeline modification and operation condition estimation is guided by ASME B31.12. The intent of this software is to target application for projects in the initial project assessment stage and provide the user with the capability of assess promising opportunities before the use proceeds with further detailed pipeline evaluation based on a probable economic outcome.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "BlendPATH (Blending Pipeline Analysis Tool for Hydrogen) [SWR-24-10]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BlendPATH", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-01-08", + "metadataLastUpdated": "2024-01-08" + }, + "description": "This project provides a tool to compute LCOM metrics for important Ada abstraction mechanisms (e.g.,\npackages, protected objects). It analyzes data accesses and routine calls to compute an abstract\nrepresentation of an Ada package (or some other abstraction). Different LCOM metrics (1-5) are\ncomputed from the abstract representation. The project also provides support for representing the\nabstraction graphically (via graphviz). The LCOM tool requires an existing ROSE installation configured\nwith the GNAT 2019 compiler.", + "laborHours": 0.0, + "languages": [], + "name": "ROSE LCOM Tools", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ROSE-LCOM-Tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.5" + }, + { + "contact": { + "email": "zhangc@ornl.gov" + }, + "date": { + "created": "2024-01-08", + "metadataLastUpdated": "2024-01-09" + }, + "description": "Tutorial on graph neural network (GNN) for the digital twin (DT) team at ORNL.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Graph neural network tutorial for digital twin application", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/KedoKudo/DT_GNN_Tutorial", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "zhangc@ornl.gov" + }, + "date": { + "created": "2024-01-08", + "metadataLastUpdated": "2024-01-08" + }, + "description": "Contains software that is used to process the raw tpx3 data into hit and events.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "ornlneutronimaging/mcpevent2hist", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornlneutronimaging/mcpevent2hist", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "2.2.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-10", + "metadataLastUpdated": "2024-03-11" + }, + "description": "PowerSystems.jl is a package to organize and manipulate data for the study of energy systems with diverse modeling requirements. This software serves two main purposes: to reduce the burden of large power system data set development, and to promote reproducible research and simulation. PowerSystems.jl implements an abstract hierarchy to represent and customize power systems data and includes data containers for quasi-static and dynamic simulation applications. Key features include efficient management of large quantities of time series data, optimized serialization, and comprehensive validation capabilities.\n\nFor further information regarding the Sienna modeling framework at NREL, see: https://www.nrel.gov/analysis/sienna.html", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "PSY (PowerSystems.jl) [SWR-23-105]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-Sienna/PowerSystems.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.2.2" + }, + { + "contact": { + "email": "dewittsj@ornl.gov" + }, + "date": { + "created": "2024-01-10", + "metadataLastUpdated": "2024-01-10" + }, + "description": "This repository contains example implementations of phase-field codes primarily for educational purposes. These codes demonstrate how a simple phase-field models can be implemented as an introduction for researchers new to the area (students, new staff, collaborators from different domains, etc.). \n\nThe computer code includes highly documented Jupyter notebooks that implement phase-field models and analyze the results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Phase-Field Method Tutorial Codes", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/pf_tutorial_codes", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "mazeauej@ornl.gov" + }, + "date": { + "created": "2024-01-11", + "metadataLastUpdated": "2024-01-11" + }, + "description": "C++ Project Euler files", + "laborHours": 0.0, + "languages": [], + "name": "mazeau/project-euler", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mazeau/project-euler", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stewartsl@ornl.gov" + }, + "date": { + "created": "2024-01-12", + "metadataLastUpdated": "2024-01-12" + }, + "description": "Dimensionally aligned signal projection (DASP) algorithms are used to analyze fast Fourier transforms (FFTs) and generate visualizations that help focus on the harmonics for specific signals. At a high level, these algorithms extract the FFT segments around each harmonic frequency center, and then align them in equally sized arrays ordered by increasing distance from the base frequency. This allows for a focused view of the harmonic frequencies, which, among other use cases, can enable machine learning algorithms to more easily identify salient patterns. \n \nThe DASP library is implemented in Python and contains four types of algorithms for implementing these feature engineering techniques: fixed harmonically aligned signal projection (HASP), decimating HASP, interpolating HASP, and frequency aligned signal projection (FASP). Each algorithm returns a numerical array, which can be visualized as an image. For consistency FASP, which is the terminology used for the short-time Fourier transform, has been implemented as part of the library to provide a similar interface to the STFT of the raw signal. Additionally, the library contains an algorithm to generate artificial signals with basic customizations such as the base frequency, sample rate, duration, number of harmonics, noise, and number of signals.\n \nFinally, the library provides multiple interactive visualizations, each implemented using IPyWidgets and work in a Jupyter environment. A dashboard-style visualization is provided, which contains some common signal-processing visual components (signal, FFT, spectrogram) updating in unison with the HASP functions (see Figure 1 below). Separate from the dashboard, an independent visualization is provided for each of the DASP algorithms as well as the artificial signal generator. These visualizations are included in the library to aid in developing an intuitive understanding how the algorithms are affected by different input signals and parameter selections.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Dimensionally Aligned Signal Processing Algorithms", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/dasp-stacker", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "sabaua@ornl.gov" + }, + "date": { + "created": "2024-01-12", + "metadataLastUpdated": "2024-01-30" + }, + "description": "Code for modeling solidification microstructure based on the Cellular Automata method for binary/pseudo-binary alloys.\n\nThis code is derived from the open-source software uMatIC developed at the Imperial College London https://www.imperial.ac.uk/engineering-alloys/research/software", + "laborHours": 0.0, + "languages": [ + "C", + "cmake" + ], + "name": "muMatScale", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lang-yuan/muMatScale", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-12", + "metadataLastUpdated": "2024-01-22" + }, + "description": "We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE)7. We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.\n\nScientific publication available here: https://pubs.acs.org/doi/full/10.1021/acs.est.2c04246", + "laborHours": 0.0, + "languages": [ + "Python", + "Shell" + ], + "name": "LiAISON (Life-cycle Assessment Integration into Scalable Open-source Numerical models) [SWR-24-01]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/LiAISON", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.0.1" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2024-01-15", + "metadataLastUpdated": "2024-01-25" + }, + "description": "Montepy is an object-oriented Python interface for MCNP input files. It excels at reading, editing, creating, and writing MCNP input files. The Monte Carlo N Particle (MCNP) code is a Monte Carlo transport solver for simulating many different types of radiation problems and is developed by Los Alamos National Laboratory. Montepy creates an object-oriented interface for the MCNP input file to allow for efficient automated modifications to large, complex simulations.", + "laborHours": 0.0, + "languages": [ + "python3.8" + ], + "name": "Montepy", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/MontePy", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2024-01-15", + "metadataLastUpdated": "2024-01-15" + }, + "description": "AcCCS is a collection of scripts that leverage open-source code, off-the-shelf hardware, and published protocol specifications to create a flexible and inexpensive test and evaluation device for the Electric Vehicle industry. AcCCS is capable of emulating either an Electric Vehicle (EV) or Electric Vehicle Supply Equipment (EVSE). It provides a flexible set of Python scripts to test and evaluate the various communication protocols between the Electric Vehicle Communication Controller (EVCC) and Supply Equipment Communication Controller (SECC). This capability is useful for cybersecurity researchers, automotive OEMs, and EVSE manufactures.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Access Capabilities Through Ccs Communications Protocol (acccs)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/AcCCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2024-01-15", + "metadataLastUpdated": "2024-02-06" + }, + "description": "This project brings together a multidisciplinary team to develop tools and analysis that will help U.S. industry accelerate deployment of floating PV on reservoirs and estuaries through producing:\n•\tA tool to assess potential environmental interactions of FPV on reservoirs and estuaries and thresholds for corresponding impacts.\n•\tA tailored FPV-specific techno-economic tool to guide users on financial performance and corresponding design considerations.\n•\tA synthesized tool, AquaPV, that combines the environmental and economic tools.\n•\tA set of case studies on an open-loop reservoir with a traditional hydropower plant (i.e., connected to a natural waterbody), closed-loop reservoir with a proposed pumped storage hydropower plant (i.e., manmade and disconnected from a natural waterbody), and a marine estuary (i.e., where a river meets the ocean), with an FPV system designed and modeled for each site.\n•\tA review of regulatory, environmental, and stakeholder opportunities and challenges to identify clear regulatory and environmental pathways to siting FPV on U.S. reservoirs.\n•\tA novel, high-fidelity geospatial resource assessment to estimate FPV technical potential on reservoirs in the United States.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Aquapv", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/AquaPV", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-17", + "metadataLastUpdated": "2024-01-31" + }, + "description": "VSP selects the appropriate number and location of environmental samples to ensure that the results of statistical tests performed to provide input to risk decisions have the required confidence and performance. VSP Version 5.0 provides sample-size equations or algorithms needed by specific statistical tests appropriate for specific environmental sampling objectives. It also provides data quality assessment and statistical analysis functions to support evaluation of the data and determine whether the data support decisions regarding sites suspected of contamination. The easy-to-use program is highly visual and graphic. VSP runs on personal computers with Microsoft Windows operating systems (98, NT, 2000, Millennium Edition, CE, and XP) Designed primarily for project managers and users without expertise in statistics, VSP is applicable to two- and three-dimensional populations to be sampled (e.g., rooms and buildings, surface soil, a defined layer of subsurface soil, water bodies, and other similar applications) for studies of environmental quality. VSP is also applicable for designing sampling plans for assessing chem./rad/bio threat and hazard identification within rooms and buildings, and for designing geophysical surveys for UXO identification.", + "homepageURL": "https://www.pnnl.gov/projects/visual-sample-plan", + "laborHours": 0.0, + "languages": [], + "name": "Visual Sample Plan", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/projects/visual-sample-plan", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/projects/visual-sample-plan", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-17", + "metadataLastUpdated": "2024-01-31" + }, + "description": "ProMAT is a software tool for statistically analyzing data from enzyme-linked immunosorbent assay microarray experiments. The software estimates standard curves, sample protein concentrations and their uncertainties for multiple assays. ProMAT generates a set of comprehensive figures for assessing results and diagnosing process quality. The tool is available for Windows or Mac, and is distributed as open-source Java and R code.", + "homepageURL": "https://www.pnnl.gov/statistics/ProMAT", + "laborHours": 0.0, + "languages": [], + "name": "ProMat", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/statistics/ProMAT", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/statistics/ProMAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-17", + "metadataLastUpdated": "2024-01-31" + }, + "description": "The Bayesian Estimator of Protein-Protein Association Probabilities (BEPro3) is a software tool for estimating probabilities of protein-protein association between bait and prey protein pairs using data from multiple-bait, multiple-replicate, protein LC-MS/MS affinity isolation experiments. BEPro3 is public domain software, has been tested on Windows XP and version 10.4 or newer of the Mac OS 10.4, and is freely available. A user guide, example dataset with analysis and additional documentation are included with the BEPro3 download.", + "homepageURL": "http://www.pnl.gov/statistics/BEPro3", + "laborHours": 0.0, + "languages": [ + "R, JAVA" + ], + "name": "Bayesian Estimator of Protein-Protein Association Probabilities", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.pnl.gov/statistics/BEPro3", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.pnl.gov/statistics/BEPro3", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-01-17", + "metadataLastUpdated": "2024-01-31" + }, + "description": "Passively maps IP networks using data generated by other network monitoring tools as well as using network device configuration files. Organizes network data, such as names, device types, device addresses, traffic data, etc. in a database for analysis and extraction into a network visualization tool.", + "laborHours": 0.0, + "languages": [], + "name": "ANTFARM", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ccss-sandia/antfarm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-19", + "metadataLastUpdated": "2024-01-19" + }, + "description": "DATING (Determining Allowable Temperatures in Inert and Nitrogen Gases) calculates allowable initial temperatures for dry storage of light-water-reactor spent fuel and the cumulative damage fraction of Zircaloy cladding for specified initial storage temperature and stress and cooling histories. It is made available to ensure compliance with NUREG 10CFR Part 72, Licensing Requirements for the Storage of Spent Fuel in an Independent Spent Fuel Storage Installation (ISFSI). Although the program's principal purpose is to calculate estimates of allowable temperature limits, estimates for creep strain, annealing fraction, and life fraction as a function of storage time are also provided. Equations for the temperature of spent fuel in inert and nitrogen gas storage are included explicitly in the code; in addition, an option is included for a user-specified cooling history in tabular form, and tables of the temperature and stress dependencies of creep-strain rate and creep-rupture time for Zircaloy at constant temperature and constant stress or constant ratio of stress/modulus can be created. DATING includes the GEAR package for the numerical solution of the rate equations and DPLOT for plotting the time-dependence of the calculated cumulative damage-fraction, creep strain, radiation damage recovery, and temperature decay.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "None" + ], + "name": "Temperature for Spent Fuel Dry Storage (DATING-A)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-19", + "metadataLastUpdated": "2024-01-19" + }, + "description": "DATING (Determining Allowable Temperatures in Inert and Nitrogen Gases) calculates allowable initial temperatures for dry storage of light-water-reactor spent fuel and the cumulative damage fraction of Zircaloy cladding for specified initial storage temperature and stress and cooling histories. It is made available to ensure compliance with NUREG 10CFR Part 72, Licensing Requirements for the Storage of Spent Fuel in an Independent Spent Fuel Storage Installation (ISFSI). Although the program's principal purpose is to calculate estimates of allowable temperature limits, estimates for creep strain, annealing fraction, and life fraction as a function of storage time are also provided. Equations for the temperature of spent fuel in inert and nitrogen gas storage are included explicitly in the code; in addition, an option is included for a user-specified cooling history in tabular form, and tables of the temperature and stress dependencies of creep-strain rate and creep-rupture time for Zircaloy at constant temperature and constant stress or constant ratio of stress/modulus can be created. DATING includes the GEAR package for the numerical solution of the rate equations and DPLOT for plotting the time-dependence of the calculated cumulative damage-fraction, creep strain, radiation damage recovery, and temperature decay.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "None" + ], + "name": "Temperature for Spent Fuel Dry Storage (DATING-M)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-19", + "metadataLastUpdated": "2025-01-31" + }, + "description": "CMS provides an inventory of all chemicals on order or being held in the laboratory, to provide a specific location for all chemical containers, to ensure that health and safety regulatory codes are being upheld, and to provide PNNL staff with hazardous chemical information to better manage their inventories. CMS is comprised of five major modules: 1) chemical purchasing, 2) chemical inventory, 3) chemical names, properties, and hazard groups, 4) reporting, and 5) system administration.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "None" + ], + "name": "Chemical Management System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-01-22", + "metadataLastUpdated": "2024-01-22" + }, + "description": "Spawn is a software package for performing co-simulations involving NREL's EnergyPlus™ tool and Modelica. This package bundles the following items in one self-contained package.\n\n1. A method for connecting EnergyPlus models to Modelica\n2. A Modelica compiler toolchain for compiling and running Modelica models\n3. Modelica libraries and content, including the Modelica Buildings Library (MBL) and the Modelica Standard Library.\n\nThe Spawn installation package is fully self-contained, and there are no external third-party dependencies. Together the capabilities in this package provide a single integrated environment for performing hybrid Modelica and EnergyPlus simulations. The primary entry point is the Spawn command line interface.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "CMake" + ], + "name": "Spawn v.0.5.0 Released 12.15.2023 [SWR-SWR-20-10]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Spawn", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.5.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-01-22", + "metadataLastUpdated": "2024-01-22" + }, + "description": "WindSE is a python package that uses a FEniCS backend to perform wind farm simulations and optimization. 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Additionally, three distinct tools have been developed:\nPV Hosting Capacity: This tool allows users to determine the additional amount of photovoltaic (PV) generation that can be\nintegrated into the system without breaching operational constraints.\nEV Hosting Capacity: This tool focuses on identifying the capacity for incorporating extra electric vehicle (EV) load into the\nsystem without surpassing operational limitations.\nProject Impact Analysis Tool: This tool is designed to assess and report all potential grid violations associated with a\nspecific project, providing valuable insights into its impact on the distribution grid.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Grid Modeling and Hosting Capacity Analysis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "gureckywl@ornl.gov" + }, + "date": { + "created": "2024-01-24", + "metadataLastUpdated": "2024-01-24" + }, + "description": "This software package performs time series forecasting for engineering systems using neural controlled differential equations. Neural controlled differential equations are continuous time analogues to recurrent neural networks. AIRES-NODE is particularly well suited for dynamic systems which are subject to external forcing terms and time-dependent boundary conditions. AIRES-NODE provides an encoder-decoder architecture which allows for variable-length forecasts to be made and is not limited to a fixed time step size when forecasting. Additionally, by utilizing a novel combination of a variational autoencoder and neural controlled differential equations, the AIRES-NODE package is capable of producing probabilistic future forecasts.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AIRES-NODE", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/AIRES/aires-node", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0.0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-01-25", + "metadataLastUpdated": "2024-01-25" + }, + "description": "NREL's Campus Energy Modeling project provides a suite of simulation tools for integrated, data driven energy modeling of commercial buildings and campuses using Simulink. The tools enable development of fully interconnected models for commercial campus energy infrastructure, including electrical distribution systems, district heating and cooling, onsite generation (both conventional and renewable), building loads, energy storage, and control systems.", + "laborHours": 3024.8, + "languages": [ + "Java", + "MATLAB", + "HTML" + ], + "name": "Campus Energy Modeling (2015) [SWR-15-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CampusEnergyModeling", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.2.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-01-25", + "metadataLastUpdated": "2024-01-29" + }, + "description": "This software is an advanced TCO calculator that takes into account various scenarios of vehicle and component costs, battery and fuel price forecasts, drive patterns, battery wear, charging infrastructure costs, purchase incentives, financing, ownership, and other criteria. The vehicle economics considered include vehicle and related infrastructure purchases, financing, fuel (gasoline and electricity) costs, non-fuel operating and maintenance costs, battery replacement, salvage value, and any costs passed on by a third party such as a service provider to account for the installation, use, and availability of infrastructure. Battery degradation, charging strategies, and drive patterns play an important role in each of these elements.", + "homepageURL": "https://labpartnering.org/technologies/55f86d47-38e0-41b5-aa8c-bc4020564b1b", + "laborHours": 0.0, + "languages": [], + "name": "Complete Battery Ownership Model And Cost Calculator (BOM) [SWR-20-28]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://labpartnering.org/technologies/55f86d47-38e0-41b5-aa8c-bc4020564b1b", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://labpartnering.org/technologies/55f86d47-38e0-41b5-aa8c-bc4020564b1b", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-02-06" + }, + "description": "HydroPowerSimulations is an extension to NREL's PowerSimulations.jl software that enables the modeling and analysis of hydropower systems.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "HPS (HydroPowerSimulations.jl) [SWR-23-110]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-Sienna/HydroPowerSimulations.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.8.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-29" + }, + "description": "We seek to release SuperNu, Version 4.x, as a continuation of development for the open source SuperNu software. The SuperNu, Version 3.x Monte Carlo radiative transfer code for astrophysical transients was released with GPLv3 copyright, asserted by LANL in 2015. For the next release we have features planned for development , including: opacity implementation (including non-local thermodynamic equilibrium effects), generalized source implementation (e.g. for emulating shock heating in Type II supernovae), 3T (electron, ion, radiation) internal energy update, special relativity corrections through O(v^2/c^2), light polarization (e.g. for comparison to spectroplarimetry observations of supernovae and kilonovae), and infrastructure features (checkpoint and restart of simulations, and tools including setup and Slurm batch scripts and simulation post-processing/analysis scripts). These features are intended to improve the fidelity and/or better understand uncertainty in supernova and kilonova light curve calculations.", + "laborHours": 0.0, + "languages": [], + "name": "SuperNu Version 4.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SuperNu", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "Materials Analysis Using Diffraction (MAUD) is an open source Rietveld refinement program which fits diffraction models to\ndiffraction spectra allowing quantitative diffraction analysis. The scripting interface developed here using python facilitates the\nchoice of parameters to refine during the Rietveld fitting process and provides a simple MPI framework for running MAUD\ninstances in parallel. The scripting language facilitates batch, custom, and reproducible Rietveld refinements of large datasets.", + "laborHours": 0.0, + "languages": [], + "name": "MAUD Interface Tool Kit (MILK)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MILK", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-02-29" + }, + "description": "Development of a prototype, code-based life cycle assessment framework, the Harmonized Impacts across Products, Scenarios, and Technologies for Environmental and Resource metrics (HIPSTER), to coherently assess outputs of prospective NREL models across environmental and resource use metrics. Eventually, HIPSTER is aimed to also cover socioeconomic and justice metrics. At present, NREL model scenario impact assessments are performed incoherently, as they as based on varying assumptions and inputs, specifically life cycle inventories, and cover different system boundaries. HIPSTER was created to align the assumptions and boundaries with those of cradle-to-grave life cycle assessment. In FY22, HIPSTER was successfully applied using scenarios from the ReEDS™ model, NREL's flagship capacity expansion model resulting in cradle-to-grace time-series life cycle impacts across LCA midpoints and resource use metrics.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HIPSTER (Harmonized Impacts across Products, Scenarios, and Technologies for Environmental and Resource metrics) [SWR-24-17]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HIPSTER", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.0.1 beta" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-11-15" + }, + "description": "Quinoa is a set of computational tools that enables research and numerical analysis in fluid and solid dynamics.", + "laborHours": 130020.8, + "languages": [], + "name": "Quinoa, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/quinoacomputing/quinoa", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-30" + }, + "description": "This script illustrates the advantages of loychikSD_NP, e.g. acts as a demonstration of the higher-order spectral density.", + "laborHours": 0.0, + "languages": [], + "name": "Modeling Script", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SpectralDensities", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "This is the script to calculate higher-order spectral densities.", + "laborHours": 0.0, + "languages": [], + "name": "Extract Bandwidth Statistical Properties", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SpectralDensities", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "The feature interpretability code is a python module that interprets and analyzes neural networks trained on hydrodynamic simulation output in the form of numpy arrays. The code takes trained neural networks and extracts internal model states in the form of images. Additionally, tools for covariance analysis of network weights and predictions are provided. This code is built on the TensorFlow and PyTorch python libraries, and includes trained networks and example input data for demonstration purposes.", + "laborHours": 0.0, + "languages": [], + "name": "Feature Interpretability", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/feature_interpretability", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "SurFE-XD is a mesoscale finite element framework to model surface diffusion under mutliphysics environments. The code uses legacy C++ library dolphin wrapped with python in a FEniCS driven unified form language and just-in-time (JIT) compilation setting. The purpose of the release is to attract wide-ranging usage of the code along with publication supplementation to support reproducibility of scientific data. SurFE-XD has been originally conceived under the LDRD-DR funding for “High-Gradient (C-BAND) Breakdown tolerant accelerator materials project. Currently SrFE-XD support electrostatics and Thermo-elasticity driven surface diffusion kernels. Releasing the code will also enable to include contributions from other physical regimes e.g., plasticity and electrodynamics etc as well portability to GPU-based platforms.", + "laborHours": 0.0, + "languages": [], + "name": "SurFE-XD (Surface curvature-driven Finite Elements model for Diffusion under eXtreme conditions)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sbagchi-LANL/SurFE-XD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-02-22" + }, + "description": "Tardigrade is a collection of functions, libraries, and stand-alone code which enables the simulation of materials using the higher-order micromorphic framework. The tools present are the interface to INL's MOOSE code which is used as the underlying FEA solver, several constitutive equations (linear elasticity, a pressure-sensitive elasto-plastic model, crystal plasticity, and additional models for geo-materials) useful for demonstration purposes and the simulation of some materials, the micromorphic filter which converts DNS information to micromorphic stress-deformation quantities, and the overlap coupling framework which enables multi-scale simulations of a coupled higher-order macroscale and a classically defined microscale.", + "laborHours": 0.0, + "languages": [], + "name": "Tardigrade, Version 1.1x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/tardigrade", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "1.1x" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "Historically, codes for simulating supernovae (such as Arepo, FLASH or LEAFS) have been at the forefront of scientific high-performance computing to the immense computational resources required for full 3D simulations. However, given the shift towards heterogenous HPC architectures, many current-generation codes are at the risk of losing their competitiveness as they are only designed to run on homogeneous CPU-only systems. There exist several efforts to enable these codes for GPU’s, however, these efforts only consider specific architectures or vendors (e.g., implement only CUDA or HIP), limiting themselves to a small range of exascale computing systems.\nFrameworks such as Kokkos aim to provide a framework which is agnostic of the targeted architecture, enabling the development of performant and portable code.\nIn the Ares code, we develop a performance portable tool to simulate supernovae based on the Parthenon Framework, which in turn uses Kokkos in the background. Here, the Parthenon Framework provides an interface to the underlying mesh-refinement routines, which form the backbone of our code. In addition, we incorporate the already existing Singularity-EOS toolkit to provide us with various equations of state, primarily the Helmholtz equation of state. We also include the JINA Reaclib as a basis for our nuclear network solver. Finally, we implement a gravity solver to complete the required physics.\nThis setup will provide us with a minimal code base to simulate supernova in a similar style to the tried-and-tested Arepo code, but in a futureproof performance portable framework.", + "laborHours": 0.0, + "languages": [], + "name": "ARES v1.x - Performance Portable Tool to Simulate Supernovae based on Parthenon Framework", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/AresPK", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-29" + }, + "description": "DeBoinR (Density Boxplots in R) takes in a set of Probability Density Functions (PDFs), calculates outliers based on several notions of distance, and visualizes these outliers via functional boxplots. This code is written as a stand-along R package with the hopes of eventually submitting it to CRAN. The package is written in generality; it would be useful to any researching looking to analyze a general ensemble of PDFs.", + "laborHours": 0.0, + "languages": [], + "name": "DeBoinR: Density Boxplots in R", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/deboinr", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2024-01-31", + "metadataLastUpdated": "2024-01-31" + }, + "description": "New or improved capabilities included in v3.0 release are as follows:\n\n1. Enhancement in message passing layers through generalization of the class inheritance to enable the inclusion of a broader set of message passing policies\nInclusion of equivariant message passing layers from the original implementations of:\nSchNet (https://pubs.aip.org/aip/jcp/article/148/24/241722/962591/SchNet-A-deep-learning-architecture-for-molecules); DimeNet++ (https://arxiv.org/abs/2011.14115); EGNN models (https://arxiv.org/pdf/2102.09844.pdf)\n2. Restructuring of class inheritance for data management\n3. Support of DDStore https://github.com/ORNL/DDStore capabilities for improved distributed data parallelism on large volumes of data that cannot fit on intra-node memory capacities\n4. Large-scale system support for OLCF-Crusher and OLCF-Frontier", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HydraGNN v3.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/HydraGNN/releases/tag/v3.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v3.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-02-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Tool for water system owners to estimate the cost of system interruption or loss. Publicly available for download (.zip file) at https://www.pnnl.gov/media/24681", + "homepageURL": "https://www.pnnl.gov/media/24681", + "laborHours": 0.0, + "languages": [], + "name": "Drinking Water System Energy Resilience Value Estimator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://creativecommons.org/publicdomain/zero/1.0/legalcode", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/media/24681", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "leblondtr@ornl.gov" + }, + "date": { + "created": "2024-02-01", + "metadataLastUpdated": "2024-02-01" + }, + "description": "We introduce the Trapped-Ion Surface Code Compiler (TISCC), a software tool that generates circuits for a universal set of surface code patch operations in terms of a native trapped-ion gate set. To accomplish this, TISCC manages an internal representation of a trapped-ion system where a repeating pattern of trapping zones and junctions is arranged in an arbitrarily large rectangular grid. Surface code operations are compiled by instantiating surface code patches on the grid and using methods to generate transversal operations over data qubits, rounds of error correction over stabilizer plaquettes, and/or lattice surgery operations between neighboring patches. Beyond the implementation of a basic surface code instruction set, TISCC contains corner movement functionality and a patch translation that is implemented using ion movement alone. Except in the latter case, all TISCC functionality is extensible to alternative grid-like hardware architectures. TISCC output has been verified using the Oak Ridge Quasi-Clifford Simulator (ORQCS).", + "laborHours": 0.0, + "languages": [], + "name": "ORNL-QCI/TISCC", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-QCI/TISCC/blob/v1.0.0/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/TISCC", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-02-08", + "metadataLastUpdated": "2024-02-20" + }, + "description": "This notebook makes seismic phase travel time predictions using machine learning. There are 3 different\nmachine learning models corresponding to the three regimes: local, regional, and teleseismic. After\nreading in the test data and splitting into the 3 regimes, we use precomputed scalers to scale the input\nfeatures used to make the travel time predictions. We then load the machine learning models and use\nthem to predict travel times for test data.", + "homepageURL": "https://gdo-maltte.llnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Machine Learning Travel Time emulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gdo-maltte.llnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "choij@ornl.gov" + }, + "date": { + "created": "2024-02-09", + "metadataLastUpdated": "2024-02-12" + }, + "description": "DDStore is designed to addresses random, read-oriented, global shuffle operations for data-intensive deep learning applications. By preserving global shuffling, DDStore ensures that deep learning model maintains high accuracy and generalizability when it is trained with large volume of data using HPC facilities.", + "laborHours": 0.0, + "languages": [], + "name": "DDStore", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/DDStore", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-02-09", + "metadataLastUpdated": "2024-03-04" + }, + "description": "The OpenStudio®-ERI project allows calculating an Energy Rating Index (ERI) using the Department of Energy's open-source OpenStudio®/EnergyPlus® simulation platform. The building description is provided in an HPXML file format. \nThe project supports: \n- ANSI/RESNET/ICC 301© Standard for the Calculation and Labeling of the Energy Performance of Dwelling and Sleeping Units using an Energy Rating Index \n- ENERGY STAR Certification System for Homes and Apartments Using an ERI Compliance Path \n- IECC ERI Compliance Alternative (Section R406) \n- DOE ZERH Certification Using an ERI Compliance Path For more information on running simulations, generating HPXML files, etc., please visit the documentation at https://openstudio-eri.readthedocs.io/en/latest/", + "laborHours": 249295.2, + "languages": [ + "Ruby" + ], + "name": "OpenStudio®-ERI (Energy Rating Index (ERI) Workflow) [SWR-18-72] 1.7.0 Released 12/14/2023", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-ERI", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.7.0" + }, + { + "contact": { + "email": "wieselquiswa@ornl.gov" + }, + "date": { + "created": "2024-02-12", + "metadataLastUpdated": "2024-02-15" + }, + "description": "OLM focuses on managing the ORIGEN reactor library, which is a special collection of data that enables rapid spent fuel calculations with SCALE/ORIGAMI.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ORIGEN Library Manager", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/scale/code/olm", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-02-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "a new release of the software tool that includes newly developed algorithms housed along\npreviously released ones within a single user interface.\nThe new functionalities are:\nCCS raw data converter (iEdison No. 0685901-23-0100), IPID 32762-E.\nIM-MS-DDA converter and data format (iEdison No. 0685901-23-0099), IPID 32761-E.\nThe previously developed functionalities are:\nPNNL-PreProcessor, IPID 31727-E.\n2DLC-MS to LC-IM-MS data file converter, IPID 32136-E.\nIMS data file transformations, IPID 32137-E.\nRemarks about the PNNL-PreProcessor:\nDirectly reads Agilent MassHunter (.d) data files and generates new Agilent MassHunter (.d) data files with\nenhanced raw signal quality and/or transformed data. Can also process UIMF files.\nHas both command-line and graphical user interfaces.\nPNNL provides the software executable, freely available for download (https://pnnl-comp-massspec.github.io/PNNL-PreProcessor) and it can be utilized by Agilent customers for non-commercial use.\nThe source code is not publicly available, an internal source code repository is maintained at PNNL", + "homepageURL": "https://pnnl-comp-mass-spec.github.io/PNNL-PreProcessor", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-PreProcessor v5.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://pnnl-comp-mass-spec.github.io/PNNL-PreProcessor", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://pnnl-comp-mass-spec.github.io/PNNL-PreProcessor", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "5" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-02-14", + "metadataLastUpdated": "2024-04-30" + }, + "description": "The Holistic Electricity Model (HEM) is a computational framework for analyzing electricity systems in their entirety, from the points of view of all key stakeholders.\n\nRelated publication: https://ieeexplore.ieee.org/document/10128887", + "laborHours": 7159.2, + "languages": [ + "Julia" + ], + "name": "HEM (HolisticElectricityModel.jl) [SWR-21-62]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel-hem/HolisticElectricityModel.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maiterthm@ornl.gov" + }, + "date": { + "created": "2024-02-14", + "metadataLastUpdated": "2024-06-21" + }, + "description": "This project provides the AR/VR interface to ORNL's exascale digital twin.\nThe main functionality is implemented using Unreal Engine 5.1 for Desktop or\nMicrosoft Hololens2 based visualization and interation with the system.\nThe digital twin provides data ingestion from telemetry, as well as triggering\nand interacting with simulations developed for the wider ExaDigiT project at\nORNL, as well as for the LUMI system at CSC and other CrayEX Supercomputers.\nFor the overarching project, see ExaDigiT at https://exadigit.github.io,\nwith the code repositories at https://code.ornl.gov/exadigit.", + "laborHours": 25262.4, + "languages": [], + "name": "exadigitUE5", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/exadigit/exadigitue5.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "yakubovs@ornl.gov" + }, + "date": { + "created": "2024-02-15", + "metadataLastUpdated": "2024-02-15" + }, + "description": "This project enables user authentication on servers using OpenID Connect tokens. It includes a PAM module for SSH login via an OIDC token and a utility for executing commands and copying files on behalf of a user, also utilizing an OIDC token for authentication.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "OIDC Utils", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PaNGalaxy/oidc-utils", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-02-15", + "metadataLastUpdated": "2024-02-21" + }, + "description": "The National Renewable Energy Laboratory (NREL) and the U.S. Department of Energy's (DOE) Weatherization Assistance Program (WAP) are collaborating with the home energy retrofit industry to support the development of skilled workers. The Installer Badges Toolkit provides a flexible, customizable, and voluntary approach to training and skills recognition for WAP implementers, utility programs, private-sector workers, and contractors.\n\nIn Fiscal Year 2018, DOE, along with the Crew Leader scheme committee, determined the Retrofit Installer Technician (RIT) Job Task Analysis (JTA) could be eliminated and its tasks inserted in the Crew Leader JTA. The RIT tasks became the basis of the Installer Badges.\n\nThe Badges Toolkit was updated in 2020 to add licensing and copyright agreements. Users must cite the copyright information when using or distributing copies of the Badges Toolkit in any way. The technical content has remained unchanged from previous versions of the Badges Toolkit.\n\nThe Toolkit for home retrofits consists of 25 Badges, each representing different energy efficiency tasks that an installer could perform on a home. Each Badge defines the desired outcome, criteria to verify, applicable material requirements, and references to Standard Work Specifications (SWS) or other relevant standards.\n\nThe Badges provide a consistent approach to training by ensuring that installers in different regions are learning the same skills nationwide. Organizations can also customize the Toolkit by choosing only those Badges that are relevant to their program.\n\nThe Badges Toolkit includes five pieces:\n\n\"How to Use the Badges Toolkit\" provides a brief overview of how a Grantee, Subgrantee, or training provider may approach using the toolkit.\nThe \"Badges Toolkit: Worksheet\" includes what to consider when determining whether and how to best incorporate the Badges into a weatherization assistance program.\nThe \"Crew Leader Job Task Analysis Spreadsheet\" indicates how the Badges align with specific areas of the JTA.\nThe \"Installer Badges Passport\" features separate pages for each Badge, which include places for the installer and the supervisor/trainer to record the number of times a task has been successfully completed.\nThe \"Installer Badges Verification Criteria\" includes sample inspection checklists for each Badge. These can be modified as needed based on approved variance requests or more stringent requirements. They also provide a basis for consistent inspections and awarding of Badges.\n \n\nNote: All elements of the Badges Toolkit are designed for use by potential program implementers. They are not off-the-shelf products intended for immediate deployment. Program implementers must review and modify as needed, revise verification criteria to match local requirements, complete worksheets, and otherwise define the parameters of their own badging program.", + "homepageURL": "https://sws.nrel.gov/installerbadges", + "laborHours": 0.0, + "languages": [], + "name": "GHEP WIBT (Guidelines for Home Energy Professionals Weatherization Installer Badges Toolkit) [SWR-20-69]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://creativecommons.org/licenses/by-nc/4.0/deed.en", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sws.nrel.gov/installerbadges", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-02-16", + "metadataLastUpdated": "2024-02-16" + }, + "description": "The Single-Family and Manufactured Interactive 3D houses can be used as a self-guided learning tool by anyone interested in learning more about retrofit strategies of common weatherization measures. Alternatively, the tool can be used by training organizations for a more structured learning experience when paired with a learning activity or trainer-led demonstration.", + "homepageURL": "https://www.energy.gov/scep/wap/weatherization-installer-job-aids-and-single-family-interactive-3d-house", + "laborHours": 0.0, + "languages": [], + "name": "3D House (3DH) [SWR-22-83]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.energy.gov/sites/default/files/2023-09/License-and-Agreement-3D-house_9.22.23.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.energy.gov/scep/wap/weatherization-installer-job-aids-and-single-family-interactive-3d-house", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-02-22", + "metadataLastUpdated": "2024-04-01" + }, + "description": "Data-based closure models are increasingly being used to replace physic-based closure models because of their flexibility and the growing availability of data. However, closure models are subject to uncertainty because of lack of data in parts of the input space (epistemic uncertainty) or because of noise in the data (aleatoric uncertainty). This software contains a toolbox for training bayesian neural nets that can estimate both uncertainties. A specific treatment is provided to ensure accuracy outside of the data distribution. A set of tools are provided to reduce the dimensionality of the uncertain parameter space, thereby enabling fast uncertainty propagation.", + "laborHours": 3328.8, + "languages": [ + "PureBasic", + "Jupyter", + "Python", + "Shell" + ], + "name": "MLUQ (Uncertainty quantification for ML closure models) [SWR-24-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mluq-prop", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "reevest@ornl.gov" + }, + "date": { + "created": "2024-02-23", + "metadataLastUpdated": "2024-02-23" + }, + "description": "Finite difference heat transfer using Cabana for additive manufacturing", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Finch", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-MDF/Finch", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-02-26", + "metadataLastUpdated": "2024-05-08" + }, + "description": "Co-optimized Machine-Learned Manifolds (CMLM) is a data-driven approach for developing reduced-order manifold models for high-dimensional chemically reacting systems. It involves a specially designed neural network, the training of which simultaneously optimizes linear combinations of species that define the manifold, nonlinear mapping to outputs of interest such as reaction rates, and (optionally) subfilter closure for large eddy simulation. This software package provides an implementation of the CMLM approach in Python using the PyTorch machine learning library. A few example cases are included, showing how the tool can be applied to different types of data from 0D and 1D reacting simulations performed using Cantera. The neural networks can be saved in a format that is readable by the Pele suite of combustion solvers for use in reacting computational fluid dynamics simulations.\n\nThis software repository contains several python scripts to perform various tasks associated with the Co-optimized Machine Learned Manifolds (CMLM) model, which is described in Perry, Henry de Frahan, and Yellapantula, CNF, 2022 (https://doi.org/10.1016/j.combustflame.2022.112286). This includes not only the code that defines the CMLM model, but also scripts to generate suitable training data, scripts to pre-process the data, scripts to train the CMLM model, and scripts to plot the output, as well as various other helper files. The scripts depend on several commonly used python libraries for data analysis and chemical reaction computations. The trained models that result from this tool are designed to work with the an interface being implemented in the Pele suite of reacting flow solvers (https://github.com/AMReX-Combustion).", + "laborHours": 1778.4, + "languages": [ + "Python" + ], + "name": "CMLM (Co-Optimized Machine-Learned Manifolds) [SWR-23-41]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/cmlm", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-02-27", + "metadataLastUpdated": "2024-02-27" + }, + "description": "INL engineers developed a special purpose software framework designed to establish real-time connections between multiple running Unity instances.\n\nThe framework is developed in Unity, a game engine development platform. \n\nThis framework programmatically attaches functions to engineering models, enabling users to interact with, observe, and make changes to virtual models. These interactions are broadcasted through websocket connections, and received by other engineers in real-time.", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Multiplayer Engineering", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Multiplayer_Engineering", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "brownjm@ornl.gov" + }, + "date": { + "created": "2024-02-27", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This is a collection of public data produced by AMPX or curated from quality sources that the SCALE code system relies on for user problem input.", + "laborHours": 15.2, + "languages": [], + "name": "SCALE/DB-Public", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/scale/code/db-public/-/blob/main/LICENSE", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/scale/data/db-public", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-02-27", + "metadataLastUpdated": "2024-06-05" + }, + "description": "EnergyPlus™ is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption and water use in buildings.\n\nThis is the EnergyPlus Development Repository.\n\nThe Department of Energy maintains a public website for EnergyPlus where you can find much more information about the program. https://energyplus.net/\n\nFor detailed developer information, consult the wiki. https://github.com/NREL/EnergyPlus/wiki\n\nMany users (and developers) of EnergyPlus are active on Unmet Hours, so that's a great place to start if you have a question about EnergyPlus or building simulation. https://unmethours.com/questions/\n\nFor more in-depth, developer-driven support, please utilize the EnergyPlus Helpdesk. https://energyplushelp.freshdesk.com/support/home", + "laborHours": 2335920.8, + "languages": [ + "C++", + "Fortran", + "Python", + "Jupyter Notebook", + "Visual Basic 6.0", + "CMake" + ], + "name": "EnergyPlus™ v.23.2.0 2023 [SWR-17-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/EnergyPlus?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlus", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "23.2.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-02-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Efficient Graph Neural Network for Predicting Molecular Properties software can compare the prediction quality with ab initio DFT results reported by the high-performance state-of-theart NWChem quantum chemistry package [1] through Mean Absolute Error (MAE) obtained by the fitting between DFT and\nmodel predictions i.e, MPNN [2]. We also demonstrated the performance benefits by grouping large molecules by atom\nsizes, and executing GNN models on different types of resources. Since the training times depend on the number of\natoms, we demonstrate the impact of distributing the workloads on two GPUs with varying capabilities (e.g., NVIDIA A100\nvs. GeForce RTX 2080 Ti) to optimize the efficiency. We are at the precipice of broad adoption of GNNs for molecular\nproperty prediction tasks; hence, our work is timely by comparing model prediction against classical approaches with the\nintent of providing initial screening for specific classes of molecules.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/emp-gnn", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/emp-gnn", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Fair Bagging Boosting Models is a software implementation of a framework for building, measuring bias and correcting bias in 3 popular forest machine learning models: gradient boosted trees (GBT), random forest (RF), and XGBoost models, using the XGBoost library. The framework takes advantage of the flexibility in XGBoost library to represent gradient boosted tree and random forest models, as well as the ability to use custom loss function.", + "laborHours": 1216.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "Fair Bagging Boosting Models [SWR-24-38]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Fair_Bagging_Boosting_Models", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2024-03-01", + "metadataLastUpdated": "2024-03-04" + }, + "description": "First release of version 3.0 of the Energy Exascale Earth System Model. \nThe fully coupled cases now run by default in a “tri-grid” configuration where the land and river model share a higher-resolution (0.5 degree) lat-lon grid while the atmosphere and ocean are on their own grids. [ATM] component is EAM. Vertical res. has been increased from 72 to 80 layers; horizontal res. remains ne30pg2. Atmospheric physics have had significant additions and changes since version 2. Added: interactive gas chemistry in stratosphere and troposphere; size mode for prognostic treatment of stratospheric sulfate aerosol; explicit representation of secondary organic aerosols (SOA) sources; a new dust emission scheme; Predicted Particle Properties (P3) for stratiform clouds; cloud microphysics for convective clouds; MCSP to represent the effects of organized mesoscale convective systems; rougher topography. Improved: aerosol wet removal processes to reduce the overestimation of aerosols and thus aerosol forcing; numerical coupling of aerosol emission, vertical mixing and dry deposition; cloud base mass flux adjustment in ZM; lower stratospheric vertical grid and surrogate-accelerated parameter optimization. Re-tuned: Dimethyl sulfide (DMS) emission, number of monolayers for black carbon (BC) aging, and hygroscopicity of particulate organic matter (kPOM). [LAND] component is ELM. The default configuration for ELM has been switched from vegetation leaf area specified as a static monthly time series based on satellite data to a dynamic vegetation growth model. This implementation uses prognostic coupled carbon, nitrogen, and phosphorus cycles (C-N-P) for vegetation and soil biogeochemistry; the relative demand (RD) approach to resolve competition between plants and soil microbes for available nutrients; the converging trophic cascade (CTC) model for organization of plant litter and soil organic matter pools. The model also includes: A computationally efficient radiative transfer parameterization (TOP), which is based on the Monte Carlo simulations, accounts for subgrid topographic effects on solar radiation; Changed the order of sublimation and dew on snow depth calculation to ensure that snow depth is not accidentally set to a negative value. [RIVER] model is still MOSART. [OCEAN] component remains MPAS-Ocean. Major change since version 2.1 include: Using a new Icosahedral 30 km mesh with Ice Shelf Cavities (IcoswISC30E3r5) for low-resolution coupled simulations. Switched coupled surface pressure to pressure at mean sea level which reduces errors in gradient term for sea ice. Improvements to the Redi isopycnal mixing scheme; Improved computational efficiency of the ocean component by changing the baroclinic time stepping method. [SEA-ICE] component is MPAS-Seaice and has had many improvements since 2.1; Added Icepack as the default sea ice column physics; Switched to high-frequency sea ice coupling as the default surface stress flux option for all meshes; Reduced the maximum number of sea ice atmospheric turbulent flux iterations; Decreased the dynamics minimum concentration sea ice and the ice mass per unit area cutoff; Reduced standard monthly sea ice output by removing sea ice age, first year ice tracers, and level ice volume and area; Added or updated checks on configuration settings. [LAND-ICE] component remains MPAS-Albany-landIce (MALI). The version of MALI has been updated to include higher-order advection and time integration. The land-ice component is not yet supported in production configurations with v3. [COUPLER] remains cpl7/MCT. A new property-preserving map procedure enables high-order flux maps between components for selected fields. In v3 LR cases, applied to all atmosphere-to-surface fluxes except precip. Calculation of gustiness between atmosphere, ocean and land was rationalized. Default processor layouts for the low-resolution configuration are available on Perlmutter and other DOE platforms.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v3.0.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v3.0.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v3.0.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-03-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Atmospheric Radiation Measurement Program developed a value added product that could run autonomously to\ndetermine planetary boundary height using radiosondes. This product has produced data for 117 unique sites and\nfacilities for more than 10 years. The initial software was released around 2013 and data has been produced since 2001 for\nsome sites.", + "laborHours": 0.0, + "languages": [], + "name": "ARM-DOE/adi-vap-pblhtsonde", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/adi-vap-pblhtsonde", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "liny@ornl.gov" + }, + "date": { + "created": "2024-03-04", + "metadataLastUpdated": "2024-03-04" + }, + "description": "IRAD (Ion Irradiation and Radiation Damage) is an open-source GUI for SRIM-like vacancy production and implanted ion profile calculations. Using updated databases, IRAD is accessible at https://code.ornl.gov/liny/irad for Windows systems. It performs energy-corrected Iradina calculations, automatically determining dpa and implanted ion concentration, considering total ion fluence. Additional results like ion trajectories, final positions, stopping power distribution, etc., are available. Advanced settings permit customization of parameters such as stopping power database, incident ion angle, and 3D target simulations.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "IRAD", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/liny/irad", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-05", + "metadataLastUpdated": "2024-03-14" + }, + "description": "The interplay between energy, climate, and weather is becoming more complex as our changing climate continues to affect the weather we experience which in turn drives changes in the ever increasing share of renewable energy generation and energy demand. Energy system analyses commonly rely on meteorological inputs to estimate renewable energy generation and energy demand; however, these inputs rarely represent the estimated impacts of future climate change. Climate models and publicly available climate change datasets can be used for this purpose, but the selection of inputs from the myriad of available models and datasets is a nuanced and often subjective process. There is no single perfect climate model or dataset for all applications. In this repository, we include software and the corresponding assessments of various global climate models (GCMs) from the Coupled Model Intercomparison Project (CMIP6), evaluating their skills with respect to the historical climate and comparing of their future projections of climate change. We focus on variables that directly affect the energy system including the representation of extreme values that can drive grid resilience events. The objective of this repository is not to recommend the best climate model and dataset for a given analysis, but instead to provide a reference to facilitate the selection of climate models and datasets in subsequent work.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "gcm_eval (NREL Global Climate Model Evaluation) [SWR-24-37]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/gcm_eval", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-05", + "metadataLastUpdated": "2024-03-07" + }, + "description": "Numerical simulations can accelerate scale up and optimization of bioreactors. This project provides a toolbox to facilitate such numerical simulations in OpenFOAM. The tool box contains 1) mesh generations tools for several typical bio reactor types in OpenFOAM 2) Inverse modeling tools to calibrate models using available experimental data 3) post processing tools that accelerate and streamline the analysis of the numerical simulations.", + "laborHours": 0.0, + "languages": [ + "C++", + "Liquid" + ], + "name": "BiRD (BioReactorDesign) [SWR-24-35]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BioReactorDesign", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "foleymk@ornl.gov" + }, + "date": { + "created": "2024-03-07", + "metadataLastUpdated": "2024-03-12" + }, + "description": "The Hydropower Fleet Intelligence application can integrate hydropower facilities data sources to perform analyses on asset age, reliability and costs, as well as produce visualizations that combine time series data collected by mechanical component sensors with event history.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python", + "TypeScript" + ], + "name": "Hydropower Fleet Intelligence", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/HydroFleetIntel/blob/main/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/HydroFleetIntel", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "datepa@ornl.gov" + }, + "date": { + "created": "2024-03-07", + "metadataLastUpdated": "2024-03-07" + }, + "description": "Machine Learning on Adiabatic Quantum Computers (MAQ) is a library of algorithms used to train machine learning models on adiabatic quantum computers.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "MAQ: Machine Learning on Adiabatic Quantum Computers", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/prasannadate/maq", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-07", + "metadataLastUpdated": "2024-04-16" + }, + "description": "GRAVI (GRid Analysis and Visualization Interface) is a web application for viewing and analyzing nodal Production Cost Model (PCM) and Capacity Expansion Model (CEM) simulations. The web application provides the ability to animate geospatially coupled timeseries data in an agnostic way regardless of the underlying simulation tool used to generate the data. GRAVI also provides capabilities to animate non-geospatial data relevant to a PCM or CEM model. Furthermore, this web application can be tailored as an real-time operational tool to better understand a live grid.", + "laborHours": 1535.2, + "languages": [ + "TypeScript", + "CSS", + "JavaScript", + "Python" + ], + "name": "GRid Analysis and Visualization Interface (GRAVI) [SWR-24-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GRAVI", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-03-07", + "metadataLastUpdated": "2024-10-28" + }, + "description": "T3CO (Transportation Technology Total Cost of Ownership), is open source software for modeling total cost of ownership for commercial vehicles with advanced powertrains.\n\nT3CO is a modeling framework for determining geospatially and temporally optimized total cost of ownership (TCO) for vehicle powertrain technologies. T3CO runs NREL's FASTSim™ software for a representative set of operating conditions to minimize TCO based on vehicle parameters that affect purchase and operating costs (e.g., fuel/electricity consumption, asset depreciation, opportunity costs associated with charging time) while simultaneously ensuring that firm performance constraints (e.g. zero-to-sixty time, gradeability) are satisfied. T3CO will enable the user to control which powertrain parameters are used in optimizing TCO, and these parameters will be modified by a multi-objective optimization (MOO) algorithm to identify a Pareto-optimal solution set. The optimization algorithm will be modular so that users can choose from many different MOO options or insert their own user-defined optimization tool.\n\nNREL T3CO Homepage: https://www.nrel.gov/transportation/t3co.html\nPyPI package: https://pypi.org/project/t3co/", + "laborHours": 5289.6, + "languages": [ + "Python" + ], + "name": "T3CO (Transportation Technology Total Cost of Ownership) Open Source [SWR-21-54]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/T3CO", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-03-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An R package to prepare, process, and synthesize FAOSTAT data for global agroeconomic and multisector dynamic modeling", + "laborHours": 0.0, + "languages": [], + "name": "JGCRI/gcamfaostat", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/gcamfaostat", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-08", + "metadataLastUpdated": "2025-04-03" + }, + "description": "Test-grid-buildouts is a set of notebooks for creating buildouts of synthetic transmission grids with various levels of renewable energy. Workflows can be used to augment various test grid with varying levels of wind/solar generation. Aggregated renewable energy time series (actuals and scenarios) at grid buses can then be used for various transmission grid operation problems. Highly customizable workflow consists of parsing of synthetic grid files, setting up SAM & reV simulations, application of exclusion masks, creating of custom renewable generators on the grid, aggregating of power time series, and writing of modified grid description files.", + "laborHours": 6824.8, + "languages": [ + "Jupyter Notebook" + ], + "name": "test-grid-buildouts [SWR-23-112]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/test-grid-buildouts", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-09", + "metadataLastUpdated": "2024-03-20" + }, + "description": "This software implements a data-driven framework to uncover mechanistic models of dynamics directly from time-resolved coherent X-ray scattering measurements. It employs neural differential equations to parameterize unknown real-space dynamics and incorporates a computational scattering forward model to relate real-space predictions to reciprocal-space observations.", + "laborHours": 0.0, + "languages": [], + "name": "DATA-DRIVEN DISCOVERY OF DYNAMICS FROM TIME-RESOLVED COHERENT SCATTERING", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ninarina12/dynamiCXS", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-09", + "metadataLastUpdated": "2024-03-13" + }, + "description": "This is a graphical user interface (GUI) that can be deployed in a Node-RED environment and be configured to provide monitoring and control of an ISO 15118 EV Charger (DC or AC).", + "laborHours": 0.0, + "languages": [], + "name": "ISO 15118 Node-Red Dashboard", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/node-red/node-red", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-09", + "metadataLastUpdated": "2024-03-26" + }, + "description": "RMEM - a prototyping platform to explore the usage of RMA-based strategies in GPU-to-GPU communication.\nThe implementation relies on libfabric (BSD-2 or GNUv2) to explore different synchronization approach and their associated performance. It is compatible with different network technologies such as InfiniBand, SlingShot-11, and TCP. It provides to the user host-to-host and device-to-device communication. The latter can be initiated either from the host, or from the device.", + "laborHours": 0.0, + "languages": [], + "name": "RMEM-REMOTE MEMORY", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/rmem", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-03-11", + "metadataLastUpdated": "2024-03-11" + }, + "description": "This model provides a cost estimate for transporting CO2 via truck or rail in the United States using\ncommercially available equipment and technologies. The model includes an analysis of direct and indirect\nCO2 emissions to determine costs per net tonne of CO2 transported. Publicly available data and methods\npublished in the peer-reviewed literature are used to the extent possible; references are available at the\nbottom of the \"Calculations\" sheet. Upstream (i.e., liquefaction, buffer storage) and downstream (i.e.,\nbuffer storage, reconditioning) activities are included in the model of emissions and costs. All capital and\noperating expenditures are estimated in the \"Calculations\" sheet. The cost of financing the project is\ndetermined in the \"FINEX\" sheet. All user inputs are done via drop down menus in on the \"User Interface\"\nsheet. Summary results are also provided on the \"User Interface\" sheet.", + "laborHours": 0.0, + "languages": [], + "name": "Multimodal CO2 Transportation Cost Model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/myers79/MuMo-CoCo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-03-11", + "metadataLastUpdated": "2024-03-11" + }, + "description": "This patch will implement the new size statistics standard in the Rust implementation of Apache Arrow\nand Parquet (https://github.com/apache/arrow-rs/). This allows an uncompressed and unencoded size to\nbe known prior to uncompressing and unencoding data stored in parquet files.", + "laborHours": 0.0, + "languages": [], + "name": "Implement the size statistics Parquet standard in the Rust implementation of Arrow and Parquet.", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/apache/arrow-rs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-03-11", + "metadataLastUpdated": "2024-03-11" + }, + "description": "OPFLearn.jl is a Julia package for creating datasets for machine learning approaches to solving AC optimal power flow (AC OPF). It was developed to provide researchers with a standardized way to efficiently create AC OPF datasets that are representative of more of the AC OPF feasible load space compared to typical dataset creation methods. The OPFLearn dataset creation method uses a relaxed AC OPF formulation to reduce the volume of the unclassified input space throughout the dataset creation process. Over time this input space tightens around the relaxed AC OPF feasible region to increase the percentage of feasible load profiles found while uniformly sampling the input space. Load samples are processed using AC OPF formulations from PowerModels.jl. More information on the dataset creation method can be found in our publication, \"OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets\". To use OPFLearn.jl a PowerModels network data dictionary is required (can be loaded from Matpower \".m\" files) to define the network the dataset is being created for.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "OPFLearn.jl v0.1.2 5/18/2023 [SWR-21-109]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OPFLearn.jl", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.1.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-03-11", + "metadataLastUpdated": "2024-03-11" + }, + "description": "A circular economy emphasizes the efficient use of all resources (e.g., materials, land, water). Despite anticipated overall benefits to society, the transition to a circular economy is likely to create regional differences in impacts. Current tools are unable to fully evaluate these potential externalities, which will be important for informing research prioritization and regional decision making. The Circular Economy Lifecycle Assessment and VIsualization (CELAVI) framework allows stakeholders to quantify and visualize potential regional and sectoral transfers of impacts that could result from transitioning to a circular economy, with particular focus on energy materials. The framework uses system dynamics to model material flows for multiple circular economy pathways and decisions are based on learning-by-doing and are implemented via cost and strategic value of different circular economy pathways. It uses network theory to track the spatial and sectoral flow of functional units across a graph and discrete event simulation to to step through time and evaluate lifecycle assessment data at each time step. The framework is designed to be flexible and scalable to accommodate multiple energy materials and multiple energy technologies. The primary goal of CELAVI is to help answer questions about how material flows and environmental and economic impacts of energy systems might change if the circularity of energy systems increases.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "CELAVI (Circular Economy Lifecycle Assessment and VIsualization) v.1.3.1 9/30/2022 [SWR-20-87]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/celavi", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v.1.3.1" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-12", + "metadataLastUpdated": "2024-03-19" + }, + "description": "This program provides a fixed-grid quadrature algorithm to compute integrals in the self-energy of the quark propagator within the Maris-Tandy model. The quark propagator both on t he spacelike real axis and at complex-valued momenta is determined from its Schwinger-Dyson equation (SDE). We first apply an iterative solver to find the quark propagator on the spacelike real axis. The propagator at complex-valued momenta is then computed from its self-energy based on this solution, where \ndemanding integrals are encountered. In order to compute of these integrals, we apply customized variable transformations for the radial integral after subtracting the asymptotics. We subsequently apply an optional compound of quadrature rules for the angular integral.", + "laborHours": 0.0, + "languages": [], + "name": "SDE_quark", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/shaoyangjia/SDE_quark", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-12", + "metadataLastUpdated": "2024-03-19" + }, + "description": "This is a small kernel that was used to collect data for an upcoming paper. We would like to have the code be open source so that the reviewers (and then readers) of the paper can see the whole code, and can reproduce/verify our results. This is not a fully featured application, it cannot produce any useful simulation results, it just executes a small abstracted kernel using synthetic data. The purpose of the kernel is to understand the basic performance characteristics of an HPC kernel on novel AI accelerator architectures. The main kernel is written in the CSL coding language for use with the Cerebras WSE-2 AI accelerator. The kernel represented is the Monte Carlo cross section lookup kernel, which is a small kernel used by the Monte Carlo neutral particle transport algorithm. There is also a baseline kernel written in CUDA that we will include in the repository to form a basis for comparing the WSE-2 to GPU.", + "laborHours": 0.0, + "languages": [], + "name": "MONTE CARLO CROSS SECTION LOOKUP KERNEL FOR THE CEREBRAS WSE-2 IN CSL", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-science/mc_on_accelerators", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kwons@ornl.gov" + }, + "date": { + "created": "2024-03-12", + "metadataLastUpdated": "2024-03-13" + }, + "description": "There is high demand for high-throughput calculations of phase equilibria based on the CALPHAD method (CALculation of PHAse Diagram). High-throughput calculations are possible through HPC, currently by a commercial program called Thermo-Calc. However, the number of nodes/processors are limited to the number of purchased license (16 processors per license). This program provides a toolkit for high-throughput calculations of phase equilibria by the CALPHAD method. The program is prepared for Python environment, so that it can be easily installed and used together with other open-source programs. The program can be run in supercomputer.", + "laborHours": 0.0, + "languages": [ + "Fortran", + "Python" + ], + "name": "Equilipy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/Equilipy", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2024-02120O\nThis program enumerates and classifies all possible functional elements in several different categories within the Ballistic Asynchronous Reversible Computing (barc) model of computation. barc software is a research tool that is being used to help document the possible digital behaviors of primitive functional elements in the ABRC a.k.a. BARC model of computation. \n\nThe method of operation of this software leverages elementary concepts and methods from discrete mathematics: combinatorics (permutations), partitions and equivalence classes, symmetry transformations, and the theory of finite groups. Implementation is in Python programming language. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 562.4, + "languages": [ + "Python" + ], + "name": "BARC Element Classifier (barc)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/barcs", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-15" + }, + "description": "SAND2024-02099O\nThe software is designed to allow researchers to perform kinetic Monte Carlo (KMC) simulations of catalytic reactions on a 2D lattice. The code is written efficiently to run on a variety of shared memory computing architectures (e.g. GPU, multi-core) and to natively express the full complexity of lateral interactions on reaction rates. The software allows researchers to perform KMC simulations of catalytic reactions on a 2D lattice. It uses parallel shared-memory computing architectures to reduce run-times and allows for simultaneous simulation of multiple independent runs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python", + "C++" + ], + "name": "KinCat v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/KinCat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-15" + }, + "description": "SAND2024-01982O\nThe Searchlight Source Code is software for creating, managing, and dismantling experiments. It also is a simple web server that mimics an online training module with scripts to automate a client. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python", + "html", + "CSS", + "PHP" + ], + "name": "Searchlight Source Code", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "kentpr@ornl.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-19" + }, + "description": "QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support.", + "laborHours": 0.0, + "languages": [ + "C++17" + ], + "name": "QMCPACK v3.17.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/QMCPACK/qmcpack?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QMCPACK/qmcpack/releases/tag/v3.17.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v3.17.0" + }, + { + "contact": { + "email": "kentpr@ornl.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-19" + }, + "description": "QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support.", + "laborHours": 0.0, + "languages": [ + "C++17" + ], + "name": "QMCPACK v3.17.1", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/QMCPACK/qmcpack?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QMCPACK/qmcpack/releases/tag/v3.17.1", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v3.17.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-15" + }, + "description": "SAND2024-01823O\nThe HawaiiCoast_GT dataset validates anomaly detection algorithms on marine vessel tracks. The software also curates the dataset by extracting, filtering, cleaning, correlating, and computing. The codebase demonstrates the overarching methodology for deriving datasets like HawaiiCoast_GT. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HawaiiCoast_GT Code Generation", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HawaiiCoast_GT_Code_Generation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-18" + }, + "description": "SAND2024-01664O\nThis software demonstrates the usage of the Variational Kalman Filtering with Hinf-Based Correction software, which can be used to calculate the mean and covariance of the estimate of a high-dimensional parameter. The software performs this task faster than the traditional Kalman filtering technique. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Variational Kalman Filtering with Hinf-Based Correction v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/VKF-with-Hinf-Based-Correction-for-Robust-Bayesian-Learning", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2024-01501O\nLogical Activation Functions software is a PyTorch implementation from the paper, \"Logical Activation Functions for Training Arbitrary Probabilistic Boolean Logic.\" The activation functions approximate logit-space marginalization of probabilistic truth tables from probabilistic interpretations of inputs. They also provide a general methodology to approximate logical relationships between abstract antecedents and consequents for machine learning architectures. They do not target any specific application or use-case. By training probabilistic truth tables, these activation functions can capture more expressive relationships in a neural network than typical elementwise activation functions. \n\nThis code is only designed for a single compute node with a GPU and is limited to machine learning architectures than can fit within the memory of a single GPU. \n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 608.0, + "languages": [ + "C++", + "Python", + "Cuda", + "Shell" + ], + "name": "Logical Activation Functions v.1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/logic-act", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "mdelben@lbl.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-20" + }, + "description": "BerkeleyGW is a versatile, massively parallel, GPU-enabled, modular software package for quantum many-body perturbation theory applied to study the excited state properties of electrons in materials. It employs the ab-initio GW and GW plus Bethe-Salpeter equation (GW-BSE) methods and beyond. It can be used to investigate a wide range of materials from bulk crystals to clusters and 2D/1D materials, adapting to insulating, metallic, and semi-metallic systems alike. Journal article: https://doi.org/10.1016/j.cpc.2011.12.006", + "homepageURL": "https://berkeleygw.org/download", + "laborHours": 0.0, + "languages": [], + "name": "BerkeleyGW", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://berkeleygw.org/download", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "haunab@ornl.gov" + }, + "date": { + "created": "2024-03-18", + "metadataLastUpdated": "2024-03-18" + }, + "description": "A tool to compile firmware and flash same to Klipper MCUs\n\nNote: This is a personal project being submitted to DOE CODE as per instruction from ORNL's TTS office.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Klipper Quick Flash", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laikulo/klipper-quickflash.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-19" + }, + "description": "SAND2024-02969O\nThe NetCDFFile provides a generic interface to NetCDF and/or PnetCDF library calls, allowing the user to write generic code to read and write from NetCDF files. The NetCDFFile library requires a C++20 compliant compiler as well as NetCDF and PnetCDF libraries installed on the machine. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "NetCDFFile v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-19" + }, + "description": "SAND2024-02520O\nTensor SQL Database performs certain relational database management system/structured query language (RDBMS/SQL) queries faster than is possible using existing state-of-the-art databases. Tensor SQL is optimized for sparse linear algebra problems and other whole-table queries. Currently, the database is being used only for research and program development. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "TenSQL v.2023.01.20", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TenSQL", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2023.01.20" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-19" + }, + "description": "SAND2024-02435O\nThe software coloring allows applications written in the C++ language to generate publication-quality 2D plots. Its functionality is similar to Microsoft Excel's chart functionality or the Python language's matplotlib package. The value of coloring is that it is written purely in C++ and thus can be compiled on systems where Python is not available and linked into high performance computing software. \n\nFor drawing shapes onto an image, coloring uses the mathematical definition of quadratic Bezier splines and uses Newton's method to search for the closest point on a spline to a given query point. This is then used to do accurate sub-pixel sampling to get clean, non-pixelated images. For working with the actual plot data, coloring has basic statistical methods such as finding maxima and minima as well as axis scaling such as logarithms. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++17 version" + ], + "name": "coloring v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/coloring", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-19" + }, + "description": "SAND2024-01427O\nMesoscale Multiphysics Phase Field Simulator (MEMPHIS) is used for solving interfacial problems and can be applied to many evolutionary problems. Some examples are solidification dynamics, viscous fingering, fracture mechanics, hydrogen embrittlement, vesicle dynamics, electro-mechanical degradation of batteries, aging of microstructures, and segregation. MEMPHIS is written in Fortran 90 in a modular fashion, where model and numerical solvers are decoupled from one another. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "fortran 90" + ], + "name": "MEMPHIS (Mesoscle Multiphysics Phase Field Simulator v.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-20" + }, + "description": "SAND2024-01365O\nThe Graph Neural Networks and Applied Linear Algebra is companion software for the educational article with the same title. The software provides illustrative examples of graph neural networks in Matlab and Python. These stand-alone algorithms are for educational purposes. \n\nThe software also includes graph neural network-based algorithms for a trainable Jacobi iteration as well as diffusion coefficient estimation. The software provides human-interpretable implementations of Graph Neural Networks in Matlab and Python. These implementations are not optimized for performance and instead emphasize readability. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python" + ], + "name": "Graph Neural Networks and Applied Linear Algebra v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gnn-applied-linear-algebra", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-04-22" + }, + "description": "This software introduces a high-level interface designed to simplify solving linear systems using hypre, a\nrenowned library for such computational challenges. It is crafted to be accessible and user-friendly,\nmaking the powerful capabilities of hypre available to a broader audience without requiring in-depth\ntechnical knowledge. The interface is characterized by its use of YAML for input, a format celebrated for\nits structured yet straightforward readability. This choice ensures that users can easily configure the\nsoftware to meet their specific needs. Additionally, the software boasts an intuitive API that encapsulates\nhypre's functionalities, making it easier for users to interact with the process of solving linear systems. It is\nparticularly beneficial for prototyping, offering a quick and efficient means to test various solver and\npreconditioner configurations. Furthermore, the software allows for the creation of an offline testing\nframework in which predefined linear systems are read from files and benchmarked with user-defined\nsolution strategies. This makes it an invaluable tool for developers and researchers exploring and\nvalidating their computational models. Overall, the software serves as a bridge, bringing the advanced\ncomputational capabilities of hypre closer to users who may need more specialized technical expertise,\nthereby facilitating innovation and exploration in the field of numerical linear algebra.", + "laborHours": 3845.6, + "languages": [], + "name": "hypredrive: high-level interface for solving linear systems with hypre", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hypre-space/hypredrive", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-20" + }, + "description": "EB_Profiler, v2.2 is a LabVIEW program which uses computed tomography to determine the power\ndistribution in the beams of electron beam welders. It requires that the National Instruments LabVIEW\nRun-Time Engine be installed. The program takes in beam profile data from a data acquisition device or\nfrom a data file. Beam parameters necessary for calculations are entered by the user or automatically\nextracted from header information in the data file. The result is a two-dimensional reconstruction of the\npower distribution in the beam.", + "homepageURL": "https://softwarelicensing.llnl.gov/product/ebprofiler-v22", + "laborHours": 0.0, + "languages": [], + "name": "EB_Profiler", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://softwarelicensing.llnl.gov/product/ebprofiler-v22", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "2.2" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-21" + }, + "description": "SAND2024-01324O\nMrHyDE, which stands for Multi-resolution Hybridized Differential Equations, is a general-purpose C++ package for the solution of coupled multiphysics and multiscale systems on massively parallel computing systems. \n\nMrHyDE is designed to enable moving beyond forward simulation for multiscale applications which includes optimization, control, uncertainty quantification, and stochastic inversion. The framework provides interfaces to several packages within the Trilinos framework and leverages automatic differentiation to enable adjoint capabilities for large-scale, gradient-based optimization. MrHyDE provides automated multiscale capabilities through a subgrid model interface and multiscale Dirichlet-to-Neumann maps. \n\nFor extreme-scale applications, MrHyDE provides in situ data-compression algorithms to reduce memory requirements while maintaining performance. MrHyDE is a general-purpose, computational framework for the solution of multiscale and multiphysics applications. It uses a combination of structure-preserving, physics-compatible discretizations, fully implicit methods, multi-resolution schemes, or fully explicit methods. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python" + ], + "name": "MrHyDE v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MrHyDE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2024-01302O\nNeuralRW-Loihi: Spiking Discrete Time Markov Chain Simulator for Intel Loihi is a neuromorphic script that generates a random walk simulation of a discrete-time Markov Chain for the Loihi neuromorphic hardware. The code was used to produce the paper \"Neuromorphic scaling advantages for energy-efficient random walk computations\" by Smith et al., 2021. It was published in Nature Electronics. \n\nThe software provides code for implementing the discrete time Markov chain random walks on Intel's Loihi Neuromorphic platform. In addition, it provides an example problem through a mini app.", + "laborHours": 1352.8, + "languages": [ + "Python" + ], + "name": "NeuralRW-Loihi: Spiking Discrete Time Markov Chain Simulator for Intel Loihi v", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Neural-Random-Walker", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-26" + }, + "description": "SAND2024-01293O\nThe Code for BALDR Study 07.05 software reproduces results from the BALDR study concerning \"A Semi-Supervised Learning Method to Produce Explainable Radioisotope Proportion Estimates for NaI-based Synthetic and Measured Gamma Spectra.\" \n\nThe code for BALDR Study 07.05 can reproduce a scientific study following the step numbers within the file names. Using synthetic and measured data to find the best model for the radioisotope proportion estimation task of interest, the study generated results for inclusion in a paper. The high-level methods involved are neural networks, semi-supervised learning, and out-of-distribution detection. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python 3.8 - 3.10" + ], + "name": "Code for BALDR Study 07.05 v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/BALDR-Study-07.05", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-20" + }, + "description": "SAND2024-01234O\nTICC is a clustering algorithm that labels a sequence of data points according to numerical properties. This library is a Python implementation of the algorithm described in \"Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data\" (Hallac et al. 2017). It includes documentation, performance improvements, examples, and test coverage. \n\nThis library allows users to automatically segment a series of multivariate data points according to their covariance—that is, the way the values at each data point are changing in relation to one another. This is useful for identifying periods in which a system is behaving. For example, if a sensor is measuring a car's velocity, steering wheel angle, braking and acceleration, TICC can determine when the car was stopped, beginning/exiting a turn, slowing or accelerating at an intersection, or driving on straight or curved roads. TICC can be applied to measure multiple quantities at known times.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "TICC Clustering Library v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fast_ticc", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-20" + }, + "description": "SAND2024-01061O\nThe HiFiPDV-2 software is similar to other photonic Doppler velocimetry (PDV) analysis codes in that it converts signals from intensity-time space to frequency-time space using a short-time Fourier transform (STFT). It then analyzes peaks of the resulting power spectral density information to extract the velocity-time history. \n\nThe unique aspects of HiFiPDV and HiFiPDV-2 are that this reduction process is repeated for an array of reasonable STFT input variables. The resulting population distribution of output velocity-time histories is evaluated to determine the most likely velocity history and its associated uncertainty. This uncertainty is defined as the systematic uncertainty of the PDV signal as it is a function of input values to the reduction process. The HiFiPDV-2 program brings new functionality and efficiency to these calculations—most notably significant reductions in memory usage and calculation times, the ability to evaluate frequency-shifted signals, and the ability to filter out baseline signals. \n\nDevelopers recommend that users have at least 2 GB of RAM per CPU core in their system. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "HiFiPDV2 v. 2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HiFiPDV2", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Behind-the-meter Infrastructure Costs for Electrification Progression (BICEP) model quantifies the behind-the-meter (BTM) electrical upgrades required for decarbonization through electrification by comparing the expected change in capacity requirements from the electrification technologies to the existing capacity in distributed energy resources (DER) stock (including buildings).", + "laborHours": 0.0, + "languages": [], + "name": "Behind-the-meter Infrastructure Costs for Electrification Progression (BICEP) Model", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/BICEP", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-26" + }, + "description": "The codes reproduce the figures of the manuscript entitled \"Shallow Soil Response to a Buried Chemical Explosion with Geophones and Distributed Acoustic Sensing\" submitted to Journal of Geophysical Research - Solid Earth. Geophone data and Distributed acoustic sensing (DAS) data recorded during the Phase II of the The Source Physics Experiment (SPE) along a fiber-optic cable offshore were processed to understand the response of the shallow subsurface to an explosion. This Ground-based Nuclear Detonation Detection (GNDD), Low Yield Nuclear Monitoring (LYNM), and Source Physics Experiment (SPE) research was funded by the National Nuclear Security Administration, Defense Nuclear Nonproliferation Research and Development (NNSA DNN R&D).", + "laborHours": 0.0, + "languages": [], + "name": "Codes for \"Shallow Soil Response to a Buried Chemical Explosion with Geophones and Distributed Acoustic Sensing\" DAG - 01101646", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lviens-LANL/2024_DAG", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "MATLAB code that executes a numerical simulation in the open-source software, SPINACH, which is written for MATLAB. The simulation was used as data in our published paper (https://doi.org/10.1016/j.jmr.2023.107540).", + "laborHours": 0.0, + "languages": [], + "name": "Earth's Field NMR SPINACH Simulation Code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EFNMR_LANL", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "This code analyzes openly available, downscaled climate model output and counts days in a year that are available to conduct prescribed fire based on meteorological prescription data obtained from US land management agencies.", + "laborHours": 0.0, + "languages": [], + "name": "Analysis of prescribed fire days in climate model output", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ajonko/RxFire", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "Following the Open Research requirements for AGU journals, we must release the code used to perform the experiment described in our recent publication, posted at (https://arxiv.org/abs/2312.04722). This code fits a joint emulator to data from a Discrete Fracture Network (DFN) simulation, performed using the open-source software DFNworks (https://dfnworks.lanl.gov/). All code to be released implements existing methods; there are no novel algorithms nor any major innovations to existing software.", + "laborHours": 0.0, + "languages": [], + "name": "Code for Experiment in Publication “Sensitivity Analysis in the Presence of Intrinsic Stochasticity for Discrete Fracture Network Simulations”", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/sa_for_dfns", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "The Notify Validator software represents a web service that supports implementers of the COAR Notify protocol.", + "laborHours": 0.0, + "languages": [], + "name": "Notify Validator", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jepowell-LANL/coar-notify-validator-inbox", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "COSUBS (COrrelated Sampling Using Batch Statistics) reads MCNP6 output files and propagates the statistical uncertainties of various combinations of tallies using batch statistics, accounting for correlations.", + "laborHours": 0.0, + "languages": [], + "name": "COSUBS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/COSUBS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "Exploratory implementations of possible algorithms for simulating small quantum mechanical systems on a classical computer.", + "laborHours": 0.0, + "languages": [], + "name": "Machine learning methods for quantum mechanics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MLQM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "The Vistransformers Explained library is a collection of python notebooks that demonstrate the internal mechanics and uses of visual-transformer (ViT) machine learning models. The code implements, with mild modifications, ViT models that have been made publicly available through publication and GitHub code. The value added by this code is in-depth explanations of the mathematics behind the sub-modules of the ViT models, including original figures. Additionally, the library contains the code necessary to implement and train the ViT models. The library does not include example training data for the models; instead, it would rely on users generating their own datasets. The code is based on the PyTorch python library. It does not include any files other than python scripts, modules, or notebooks.", + "laborHours": 0.0, + "languages": [], + "name": "Vistransformers Explained", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vision_transformers_explained", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This script is used to read the infinitely growing data files created by a Campbell Data Logger to extract hourly data and\nwrite the content to hourly output files.", + "laborHours": 0.0, + "languages": [], + "name": "MRE-Code-Hub/extract_loggernet", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MRE-Code-Hub/extract_loggernet", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2024-03-26", + "metadataLastUpdated": "2024-03-26" + }, + "description": "This repository provide capabilities to generate multiple process groups within the PyTorch distributed environment. \n\nThe partitions of processes into groups allows to generate multiple independent version of distributed data parallelism (DDP) in order to perform scalable ensemble learning (EL) and hyperparameter optimization (HPO).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "MultiDistTorch: Generation of multiple processes groups within PyTorch distributed environments for hierarchical parallelization", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/MultiDistTorch", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "gunaratnecs@ornl.gov" + }, + "date": { + "created": "2024-03-27", + "metadataLastUpdated": "2024-03-27" + }, + "description": "SAGESim: Scalable Agent-based GPU-Enabled Simulator is a distributed GPU agent-based modeling framework in Python. SAGESim enables researchers to study complex adaptive systems at large scales on high-performance computing systems", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SAGESim", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl/sagesim", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-28", + "metadataLastUpdated": "2024-03-28" + }, + "description": "SAND2024-01040O\nPyRoCS software synthesizes mathematical equations from several domains—including information theory, ecology, and engineering sciences—to support resilience analysis for complex systems. Resilience is the ability of the complex system being analyzed to withstand, operate through, and recover from a disruption. The complex system can be a physical system such as an electric grid, an organization such as a company, or even a subfunction of an organization. \n\nExisting mathematical equations for resilience analysis are found within multiple domains including information theory, biological sciences, and complex systems. This package synthesizes and refactors equations from these various domains to make them more generalizable for application across different types of complex systems relevant for resilience analysis. Users will be able to apply these equations to characterize different components of complex systems based on available data. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "A python package for analyzing Resilience of Complex Systems (pyRoCS) v.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyrocs", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0" + }, + { + "contact": { + "email": "krawczukpn@ornl.gov" + }, + "date": { + "created": "2024-03-28", + "metadataLastUpdated": "2024-03-28" + }, + "description": "BARDI: Batch-processing Abstraction for Raw Data Integration", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "BARDI", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DOE-NCI-MOSSAIC/bardi", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.3.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-01", + "metadataLastUpdated": "2024-04-11" + }, + "description": "This repository contains python scripts and numerical data accompanying the paper:\n\"Leveraging Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning,\" Tyler Chang, Andrew Gillette, Romit Maulik, 2024. The following subdirectories are included:\n- \"interpolants\" contains our interpolation scripts used for all studies\n- \"experiments\" contains scripts demonstrating our experiments with synthetic data\n- \"airfoil\" contains scripts demonstrating our experiments with the publicly available UIUC airfoil dataset. Further instructions are provided in READMEs within the sub-directories.", + "laborHours": 0.0, + "languages": [], + "name": "Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/interpML", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-01", + "metadataLastUpdated": "2024-04-01" + }, + "description": "This code performs estimation of a mixture model involving heterogeneous data types. The resulting\nmodel can be used to calculate likelihoods of underlying model components.", + "laborHours": 273.6, + "languages": [], + "name": "Heterogeneous Data Type Mixture Model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/alankaplan/HDTMM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-01", + "metadataLastUpdated": "2024-06-28" + }, + "description": "The Differential Equation System Solver (DESS) is a Rust crate implementing fixed-step and adaptive-step solvers and designed especially for modeling physical systems. Seven explicit ordinary differential equation (ODE) solver methods have been added so far: Euler’s, Heun’s, Midpoint, Ralston’s, Classic Runge-Kutta, Bogacki-Shampine, and Cash-Karp. These comprise five fixed-step methods and two adaptive-step methods. Few solver packages are implemented in the Rust ecosystem and none are intended specifically for physical system modeling, so the goal of DESS is to create a Rust ODE solver crate designed to easily specify and model physical systems with modular, configurable solver options. In addition to allowing users to directly input equations to solve, DESS allows users to optionally specify and define relationships between nodes in their system, which the package then translates into a system of equations via the Rust macro system, leading to simpler and more intuitive code.", + "laborHours": 5791.2, + "languages": [ + "Rust", + "Python" + ], + "name": "DESS (Differential Equation System Solver) [SWR-24-48]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/de-system-solver", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "OpenEDI - System Integration (OEDI-SI) - PNNL Distributed Optimal Power Flow (DOPF)", + "laborHours": 3404.8, + "languages": [], + "name": "pnnl/oedisi_dopf", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/oedisi_dopf", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software implements an algorithm for finding triplets of hyperedges with specified size relations. Specifically, this is an\nimplementation of the pseudo-code in Algorithm 2 of our preprint manuscript \"Size-aware hypergraph motifs\", see:\nhttps://arxiv.org/pdf/2311.07783.pdf", + "laborHours": 7113.6, + "languages": [], + "name": "pnnl/hyperedge-triplets", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/hyperedge-triplets", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "georgea@ornl.gov" + }, + "date": { + "created": "2024-04-03", + "metadataLastUpdated": "2024-04-18" + }, + "description": "We present MLEC-Sim, a sophisticated simulator for Multi-Level Erasure Coding (MLEC), developed in approximately 13 KLOC. The simulator is engineered to analyze the impact of various system configurations and erasure coding policies on system durability and network overhead. It supports a comprehensive range of parameters including disk capacity, disk I/O bandwidth, failure rates, network bandwidth, and system scale, accommodating various erasure coding approaches such as Single-Level Erasure Coding (SLEC), Multi-Level Erasure Coding (MLEC), and Local Reconstruction Codes (LRC).\n\nMLEC-Sim provides support for multiple chunk placement policies, including clustered parity and declustered parity, and encompasses a variety of repair methods like Repair-ALL, Repair-FCO, Repair-HYB, and Repair-MIN. It is capable of simulating disk failures through a variety of means, including distribution-based or trace-based mechanisms, and can handle complex multi-level (de)clustered placements and repair processes.\n\nA key feature of MLEC-Sim is its adoption of the splitting simulation method for evaluating system durabilities at extremely high levels, which are challenging to assess with traditional simulation approaches. This feature allows for a detailed evaluation of system resilience under a range of conditions, aiding in the selection of appropriate erasure coding solutions for enhancing system durability.\n\nMLEC-Sim contributes to the field of data storage and reliability by providing a tool for the detailed evaluation of the durability and efficiency of erasure coding configurations, intended for use by researchers and practitioners in the design and optimization of storage systems.", + "laborHours": 15078.4, + "languages": [ + "Python" + ], + "name": "MLEC-Sim: A Simulator for Evaluating Multi-Level Erasure Coding", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ucare-uchicago/mlec-sim/blob/main/LICENSE.rtf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ucare-uchicago/mlec-sim", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-04", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The invention was developed to solve the problem of representing all systems biology knowledge about an organism in one database.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl-predictive-phenomics/concerto v2.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/Concerto", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-04", + "metadataLastUpdated": "2024-04-16" + }, + "description": "REST2 is the high-performance solar radiation model for cloudless-sky irradiance, illuminance, and photosynthetically active radiation.", + "laborHours": 288.8, + "languages": [ + "Python" + ], + "name": "REST2 [SWR-23-96]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rest2", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-04", + "metadataLastUpdated": "2024-04-04" + }, + "description": "The National Renewable Energy Laboratory (NREL) has developed a data acquisition system to support laboratory (component) and in-water validation and testing of Marine Renewable Energy (MRE) technologies. The Modular Ocean Data AcQuisition System (MODAQ) is a robust system built on industrial grade hardware that can acquire high-quality and summary data from many sensor and instrument types. MODAQ includes modules to perform real-time QC screening, system health monitoring, and send alerts. MODAQ is also part of a larger data management, processing, visualization, and archiving system.", + "laborHours": 16917.6, + "languages": [ + "HTML", + "LabVIEW", + "SaltStack", + "JavaScript" + ], + "name": "MODAQ (Modular Offshore Data Acquisition System) [SWR-24-58]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MODAQ", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "HNS Rigid Body Simulatoris a tool for performing rigid-body dynamics simulations of nanoscale systems (e.g., macromolecular\nassemblies) in Python.", + "laborHours": 988.0, + "languages": [], + "name": "pnnl/HNSRigidBodySimulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/HNSRigidBodySimulator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The software manages a database of historical hydrology and power systems operations data and based on some newly developed algorithms helps generate and\ntranslate historical hydrology data into estimations of steady-state and dynamic model parameters based on user inputs of hydro conditions which can be imported to\nexisting power system simulators.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Hydropower Modeling Gap Tools", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-04-25" + }, + "description": "This package implements a data store for components and time series in support of Python-based modeling packages. While it is designed to support teams modeling transmission and distribution systems for electrical grids, it can be used by any package that needs to store components (e.g., generators and buses) that have quantities (e.g., power and voltage) which may vary over time.\n\nThe package was inspired by InfrastructureSystems.jl (https://github.com/NREL-Sienna/InfrastructureSystems.jl).", + "laborHours": 2021.6, + "languages": [ + "Python" + ], + "name": "InfraSys (Infrastructure Systems) [SWR-24-42]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/infrasys", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.0.3" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-04-25" + }, + "description": "Grid Data Models (GDM) is a collection of pydantic data models for power distribution and transmission system components. These data models can be easily serialized and deserialized. GDM provides a standard interface for accessing power system component data with built in validation.\n\nSee also: https://pypi.org/project/grid-data-models/", + "laborHours": 1976.0, + "languages": [ + "Python" + ], + "name": "GDM (Grid Data Models) [SWR-24-31]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-Distribution-Suites/grid-data-models", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.1.2" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-07-19" + }, + "description": "This is a vehicular networking simulator designed to enable synchronized network simulation with vehicle traffic simulation software. The communications model is based on the 3GPP LTE-V2X Mode 4 protocol, but includes several other wireless network protocol models as well. This simulator includes both a V2X network simulation implemented in ns-3 as well as an interface to automatically configure, run, and interact with a set of ns-3 instances based on network size and available hardware. This software has been tested with Aimsun NEXT 2.0 simulator (with V2X SDK), but uses a generic interface for compatibility with any comparable vehicle traffic simulator across the HELICS co-simulation framework. This software is intended as a generalized extension to vehicle traffic simulation, and does not model any vehicle traffic on its own.", + "laborHours": 755713.6, + "languages": [ + "C++", + "Python" + ], + "name": "N-S3 Cellular Vehicle-to-Everything (C-V2X) Cosimulation Framework [SWR-24-54]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NS3-C-V2X-Cosimulation-Framework", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-04-10", + "metadataLastUpdated": "2024-04-10" + }, + "description": "Context-Aware Language Model for Science (CALMS) is designed to assist scientists with instrument operations and complex experimentation. CALMS consists of a large-language model (LLM) augmented with context and tool use abilities. With the ability to retrieve relevant information from facility documentation, CALMS can answer simple questions on scientific capabilities and other operational procedures. With the ability to interface with software tools and experimental hardware, CALMS can operate scientific instruments in a conversational manner.", + "laborHours": 67427.2, + "languages": [], + "name": "CALMS: CONTEXT-AWARE LANGUAGE MODEL FOR SCIENCE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mcherukara/CALMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-11", + "metadataLastUpdated": "2024-04-11" + }, + "description": "A workflow is a series of dependent computations which are executed to\nyield an experimental result, much like sheet music describes a musical\nperformance. Dynamic workflows are like improvisational jazz, in which\nthe musicians create unique, situation-driven, collaborative variations\non themes. Dynamic workflows can potentially yield better results, save\ncomputation, and/or save human decision-making effort versus pre-specified\nor manual workflows, as they need not run the exhaustive set of studies\nwhich might be required in a pre-specified set, and they make their own\nexperimental design decisions at run time. If you have an existing\nMaestro study where you would like to save computation and/or human time,\nImprov is for you.\nImprov provides core capabilities for creating a simple, hierarchical structure over Maestro studies,\nallowing you to connect ``experimental'' Maestro strudies with decision-making code to select parameters\nand run corresponding studies.", + "laborHours": 2492.8, + "languages": [], + "name": "Improv Dynamic Workflows", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/improvwf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-11", + "metadataLastUpdated": "2024-04-11" + }, + "description": "Train and use machine learning models; select protein sequences for simulation and laboratory testing.\nCode implements key decision steps in this process. Provided for review purposes and public release.", + "laborHours": 2736.0, + "languages": [], + "name": "Review materials for Computationally Restoring the Potency of a Clinical Antibody", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CRPCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "v2" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-15", + "metadataLastUpdated": "2024-04-15" + }, + "description": "A python package that helps with working with MSI Windows installers, by providing a library and utilities\nto read information from the file, extract embedded files, and update/write MSI files. Functionality is\nsimilar to https://wiki.gnome.org/msitools and https://github.com/mdsteele/rust-msi but written in pure\nPython so that it can easily be installed and used on a wider variety of systems.", + "laborHours": 288.8, + "languages": [], + "name": "PyMSI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nightlark/pymsi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.0" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-04-15", + "metadataLastUpdated": "2024-04-15" + }, + "description": "This tool, the Non-Powered Dam Hydropower Development and Ranking Opportunity Tool (NPD HYDRO), allows users to prioritize or rank NPD sites for future development based on user-defined priorities. Benefits can be evaluated in several categories: the grid, community, industry, and environment (represented by the GCIE impact scores in the tool. In addition, the tool provides the user with a qualitative measure for the feasibility of adding energy storage during NPD conversion, specifically battery, hydrogen electrolysis, and pumped-storage hydropower (PSH). By taking a holistic approach to the potential range of benefits provided by NPD conversions with results tailored to the user’s priorities, NPD HYDRO provides the opportunity for national-level screening and enables users to focus on the sites that are most closely aligned with their interests.", + "laborHours": 4696.8, + "languages": [ + "Python" + ], + "name": "NPD Hydro", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/NPD_Hydro", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stipekcw@ornl.gov" + }, + "date": { + "created": "2024-04-16", + "metadataLastUpdated": "2024-04-16" + }, + "description": "This project's goal is to ingest morphology features (2D) and infer height (3D) for individual buildings:\n\nThe following breaks the vivald process into the respective steps\nIdentify 2D buildings from AOI\nGenerate morphology features using the Gauntlet feature morphology process\nPlease see Clinton Stipek for availability of Gauntlet features\nRun a recursive feature eliminator to streamline modelling process\nHyper-tune parameters via bayesian optimization\nInfer building heights at a building-by-building level leveraging a XGBoost algorithm", + "laborHours": 136.8, + "languages": [ + "Python" + ], + "name": "vivaldi", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/stipekcw/vivaldi/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stipekcw/vivaldi", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v0.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-17", + "metadataLastUpdated": "2024-04-17" + }, + "description": "SSAPy is a python package allowing for fast and precise orbital modeling. SSAPy is designed with speed\nand accuracy in mind and offers the following capabilities:\n- A variety of integrators, including Runge-Kutta, SciPy, SGP4, etc.\n- Customizable force propagation models, including a variety of Earth gravity models, lunar gravity,\nradiation pressure, etc.\n- Multiple-hypothesis tracking (MHT) UCT linker\n- Vectorized computations\n- Short arc probabilistic orbit determination\n- Conjunction probability estimation\n- Uncertainty quantification\n- Monte Carlo data fusion\n- Support for multiple coordinate frames (with coordinate frame conversions)", + "laborHours": 6976.8, + "languages": [], + "name": "Space Situational Awareness for Python", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SSAPy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-05-03" + }, + "description": "Ring Pull Strain Analysis (RPSA) is a framework for analysis of Digital Image Correlation (DIC) data of gaugeless ring pull testing. It is meant for analysis of rings cut from tube cross sections and pulled in a displacement-controlled tensile test. This code takes load frame data, images take during testing, and csv files from the DIC analysis of those images and allows the user to analyze and plot data from the test. Some important features of the software include getting the strain values as a function of radial distance and angle, plotting of the strain around the ring, and stress-strain analysis of the load frame\ndata. Additional capability is included with Ring Pull Coating Analysis (RPCA, also part of the software). Additional images are taken of samples with an outer coating and are used to correlate failure of the coating with strain values measured with DIC.", + "laborHours": 0.0, + "languages": [], + "name": "Ring Pull Strain Analysis", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/RingPullStrainAnalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-22" + }, + "description": "The Memento Proxy software transforms Invenio systems on the web into repositories that are compliant with the Memento protocol.", + "laborHours": 425.6, + "languages": [], + "name": "InvenioRDM Memento Proxy", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/invenio-memento-proxy", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "NRAP-Open-IAM is an open-source software product that enables quantification of containment effectiveness and leakage risk at storage sites in the context of system uncertainties and variability.", + "laborHours": 114197.6, + "languages": [], + "name": "LANL Contribution to NRAP-Open-IAM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NRAP/OpenIAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "The ThunderBoltz application programming interface (API) code is written in Python and is comprised of a set of tools to facilitate compilation of the ThunderBoltz code, as well as fast assembly and formatting of input files for the ThunderBoltz code, post-processing tools of ThunderBoltz results, plotting tools, and runs/schedules the ThunderBoltz code executable for calculations. The ThunderBoltz API code is utilized for importing and manipulating input cross section sets, input conditions, and any other simulation settings made available within the ThunderBoltz input deck via user-defined settings or via automatic generation. The API comes with a set of plotting capabilities of input cross sections, results from ThunderBoltz, and post-processed results carried out with the API.", + "laborHours": 5502.4, + "languages": [], + "name": "ThunderBoltz API", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ThunderBoltz", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "Supports characterization of explosive events by providing estimates of device parameters such as yield, height of burst/depth of burial, geolocation, and event time with uncertainty quantification.", + "laborHours": 16932.8, + "languages": [], + "name": "MultiPEM Toolbox", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MultiPEM_Toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "Minervachem is a tool for cheminformatics and machine learning in chemistry. It includes both algorithms from existing literature and algorithms which we have developed. Its features center around two main themes: molecular representations and algorithms, both for molecular machine learning. It provides a scikit-learn transformer interface for molecular featurization and an estimator interface for machine learning algorithms. It also provides visualization tools for explaining machine learning predictions. We aim to continue developing this software to improve its performance and usability and expand its capabilities within the realm of molecular machine learning, cheminformatics, and visualization.", + "laborHours": 1398.4, + "languages": [], + "name": "minervachem", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/minervachem", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "HERMES - High-speed Event Retrieval and Management for Enhanced Spectral imaging code. \nThis code is meant to unpack and process neutron imaging data from the TPX3Cam made by Amsterdam Scientific Instruments. The TPX3Cam utilizes the Timepix3 chip in a single photon counting mode of image acquisition. The photon counting data streaming off the TPX3Cam needs to be process and analyzed in order to create final images. Therefore we are developing both python and cpp codes to allow for users of the TPX3Cam to efficiently analyze data and create images.", + "laborHours": 1261.6, + "languages": [], + "name": "HERMES", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/hermes", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-22", + "metadataLastUpdated": "2024-04-22" + }, + "description": "ExaDiS, or Exascale Dislocation Simulator, is a set of software modules written to enable numerical\nsimulations of large groups of moving and interacting dislocations, line defects in crystals responsible for\ncrystal plasticity. By tracking time evolution of sufficiently large dislocation ensembles, ExaDiS predicts\nplasticity response and plastic strength of crystalline materials. ExaDiS is built around a library of core\nfunctions for Discrete Dislocation Dynamics method specifically written to perform efficient computations\non GPUs.", + "laborHours": 8040.8, + "languages": [], + "name": "Exascale Dislocation Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/exadis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-24", + "metadataLastUpdated": "2024-04-25" + }, + "description": "The National Solar Radiation Database (NSRDB) is NREL’s flagship solar data resource. With over 20 years of high-resolution surface irradiance data covering most of the western hemisphere, the NSRDB is a crucial public data asset. A fundamental input to accurate surface irradiance in the NSRDB is high quality cloud property data. Cloud properties are used in radiative transfer calculations and are sourced from satellite imagery. Improving the accuracy of cloud property inputs is a tractable method for improving the accuracy of the irradiance data in the NSRDB. For example, in July of 2018, an average location in the Continental United States is missing cloud property data for nearly one quarter of all daylight cloudy timesteps. This project aims to improve the cloud data inputs to the NSRDB by using machine learning techniques to exploit the NSRDB’s massive data resources. More accurate cloud property input data will yield more accurate surface irradiance data in the NSRDB, providing direct benefit to researchers at NREL and to public data users everywhere.", + "laborHours": 1626.4, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "MLClouds [SWR-24-24]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mlclouds", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "huettelmr@ornl.gov" + }, + "date": { + "created": "2024-04-26", + "metadataLastUpdated": "2024-04-26" + }, + "description": "Systemd Snapshot is a static analysis tool for Linux systems that use systemd. It aims to enumerate, aggregate, and investigate systemd services without requiring an operational system. The tool produces a set of JSON files that consolidates not only systemd information, but additional forensic information associated with systemd artifacts. A graph is also produced based on the relationships and ordering defined in systemd unit files and the binaries they specify.", + "laborHours": 0.0, + "languages": [], + "name": "Systemd Snapshot", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/Systemd_Snapshot", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-26", + "metadataLastUpdated": "2024-04-26" + }, + "description": "This software provides a data-driven approach for efficiently identifying high impedance faults (HIFs) in distribution systems. To tackle the nonlinearity of the voltage current trajectory of HIFs, we first formulate linear least squares problems to approximate the trajectory with piecewise functions. Then we collect the function features of all segments as inputs and use the support vector machine approach to efficiently identify HIFs at different locations.", + "laborHours": 60.8, + "languages": [ + "Python" + ], + "name": "A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems [SWR-24-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openEDI/oedisi-hif-identification", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-04-26", + "metadataLastUpdated": "2024-04-26" + }, + "description": "ComStock™ is an NREL model of the U.S. commercial building stock. The model takes some building characteristics from the U.S. Department of Energy's (DOE's) Commercial Prototype Building Models and Commercial Reference Building. However, unlike many other building stock models, ComStock also combines these with a variety of additional public- and private-sector data sets. Collectively, this information provides high-fidelity building stock representation with a realistic diversity of building characteristics.\n\nThis repository contains the source code used to build and execute ComStock models, including upgrade scenarios. In addition, the sampling of buildings characteristics used for the initial ComStock (V1.0) release is provided. The ComStock model is under active calibration and development, which is publicly visible on this repository.\n\nExecution of the ComStock workflow is managed through the buildstockbatch repository, a shared asset of ResStock™ and ComStock™ , specifically developed to scale to execution of tens of millions of simulations through multiple infrastructure providers.\n\nThe dataset output from the initial ComStock (V1.0) release can be found at the accompanying ComStock data viewer website and additional information about ComStock found on the NREL Buildings Website. For more details about ongoing model development please consult the End Use Load Profiles website.\n\nComStock is a direct result of the NREL residential stock modeling tool ResStock™ (recipient of a R&D100 award) and was inspired by the high-fidelity solar & storage adoption model dGen™. Additionally, this tool would not be possible without the decades of work undertaken by the OpenStudio® and EnergyPlus® visionaries and contributors, significant funding, feedback and support from the Los Angeles Department of Water and Power, and the Department of Energy's Building Technology Office ongoing support of and investment in building energy modeling software.\n\n is an analytic methodology for modeling the energy usage of the commercial building stock within the United States of America. The commercial building stock is represented through a sampling of complex probabilistic distributions of various features of interest for modeling energy usage within commercial buildings. Each sample from these distributions is converted into a building energy model based on the features of that specific sample. Each building energy model can be simulated as is, but additional changes can be made to the model through addition of energy conservation measures, component faults, or other desired alterations. The results of the simulations are then processed to provide insights for various stakeholders, including but not limited to policy makers, engineers, and marketers.", + "laborHours": 0.0, + "languages": [ + "Python", + "Ruby" + ], + "name": "ComStock™ 2024 Release 1 [SWR-19-33 and SWR-20-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ComStock", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2024 Release 1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-04-26", + "metadataLastUpdated": "2024-04-26" + }, + "description": "The ResStock™ analysis tool was built on NREL's OpenStudio® platform, and is a project geared at modeling existing residential building stocks at national, regional, or local scales with a high-degree of granularity (e.g., one physics-based simulation model for every 200 dwelling units), using the EnergyPlus® simulation engine. Information about ComStock™, a sister tool for modeling the commercial building stock, can be found here: https://www.nrel.gov/buildings/comstock.html\nThis repository contains:\nHousing characteristics of the U.S. residential building stock, in the form of conditional probability distributions stored as tab-separated value (.tsv) files. Comments at the bottom of each file document data sources and assumptions for each.\nA library of housing characteristic \"options\" that translate high-level characteristic parameters into arguments for OpenStudio measures, and which are referenced by the housing characteristic .tsv files and building energy upgrades defined in project definition files\nProject definition files:\nv2.3.0 and later: buildstockbatch YML files openable in any text editor\nv2.2.5 and prior: Project folder openable in PAT\nUnit-level OpenStudio Measures for automatically constructing OpenStudio Models of each representative dwelling unit model:\nv3.0.0 and later: OpenStudio-HPXML Measures\nv2.5.0 and prior: OpenStudio Measures\nHigher-level OpenStudio Measures for controlling simulation inputs and outputs\nThis repository does not contain software for running ResStock simulations, which can be found as follows:\n\nVersions 2.3.0 and later only support the use of buildstockbatch for deploying simulations on high-performance or cloud computing. Version 2.3.0 also removed separate projects for single-family detached and multifamily buildings, in lieu of a combined project_national representing the U.S. residential building stock. See the changelog for more details.\nVersions 2.2.5 and prior support the use of the publicly available OpenStudio-PAT software as an interface for deploying simulations on cloud computing. Read the documentation for v2.2.5.", + "laborHours": 2638370.4, + "languages": [ + "Python", + "Ruby" + ], + "name": "ResStock™ v3.2.0 [SWR-19-15 and SWR-20-07]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/resstock/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/resstock", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.2.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-29", + "metadataLastUpdated": "2024-04-29" + }, + "description": "This code solves for the one-dimensional concentration and temperature distribution within a carbon\ncapture column using a homogenized absorber model. These solutions are compared to experimental\ndata.", + "laborHours": 927.2, + "languages": [], + "name": "DynamicSimCCS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DynamicSimCCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.01" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-04-30", + "metadataLastUpdated": "2024-04-30" + }, + "description": "Parsnip has three parts. The first part is the front-end user experience. The front end will be a graphical representation of the intermediate language. Once a user is satisfied with the information on the front end, Parsnip translates the data from the visual application into the second part of Parsnip - the intermediate language. More advanced users may skip the front end and generate their own intermediate language files. The final part is the backend which takes the intermediate language files and generates Zeek and Spicy code.\nParsnip will not completely replace parser developers. Many protocols have unique challenges requiring manual effort; however, the goal of Parsnip is to automate at least 90% of the development that largely consists of repetitive tasks. Parsnip output will compile a functioning parser but may not include all PDU types or parse all data.", + "laborHours": 5973.6, + "languages": [ + "JavaScript", + "Python", + "Jinja2" + ], + "name": "Parsnip Parser Creation Application", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cisagov/parsnip", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Identification and zonal classification of the faults is a decisive factor in the relay’s decision to trip or not. Different types of\nfault like three-phase, line-to-line-to-ground and single-line-to-ground can occur at various locations in the feeder. These\nfaults are seen as the variation in the instantaneous values of three-phase voltages and currents, i.e., waveforms, that are\nmeasured at the relay location. The objective of this work is to develop a machine learning model that can\nidentify a fault and classify it to various protection zones based on measured waveforms. In this work, a data-driven relay\nbased on Convolutional Neural Network (CNN) is proposed for fault identification in distribution feeders with high\npenetration solar PV. The proposed CNN model takes local current and voltage waveforms as input and classify it into\nfault, no-fault or a capacitor switching. Further, the CNN also attempts to identify fault zones based on the images of\nwaveforms. The overall testing accuracy of the trained model exceeds 95%.", + "laborHours": 60.8, + "languages": [], + "name": "Convolution Neural Network for Fault Identification in Distribution Feeder with High Penetration Solar PV", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/DPVCNN", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-05-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a dashboard for exploring the results of machine learning models for predicting molecular properties from\nmolecular structure. It includes tools for:\n1. Modifying molecules to observe the change in predicted properties\n2. Exploring the relationship between molecular structure and predicted properties\n3. Recommending structurally similar molecules with improved properties\n4. Exploring the impact of data subsampling on model performance metrics", + "laborHours": 532.0, + "languages": [], + "name": "Dashboard for Visualizing Molecular Property Prediction Machine Learning Results", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mol-ml-dashboard", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-05-02", + "metadataLastUpdated": "2024-05-02" + }, + "description": "The Wind-Plant Integrated System Design and Engineering Model (WISDEM®) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM® is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM® turbine design capability. Please install all of the pre-requisites prior to installing WISDEM® by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM® development, please visit the official NREL systems engineering for wind energy website. https://www.nrel.gov/wind/systems-engineering.html", + "laborHours": 229778.4, + "languages": [ + "C", + "Fortran", + "Python" + ], + "name": "WISDEM® v3.15.2 2024 (Wind-Plant Integrated System Design and Engineering Model) [SWR-14-05]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/WISDEM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.15.2" + }, + { + "contact": { + "email": "degrawjw@ornl.gov" + }, + "date": { + "created": "2024-05-06", + "metadataLastUpdated": "2024-10-01" + }, + "description": "hippogryph is a Python package for the generation of multiblock structured grids with the grid locations determined by a mapping. A structured grid is a grid for which there is a relationship between the physical space coordinates x, y, and z and three indices i, j, and k and a multiblock grid is constructed from a set of subgrids (\"blocks\"). A \"mapped\" grid is a grid for which there is a transformation f such that the nodal locations are determined by applying this mapping to the indices: (x, y, z) = f(i, j, k). While it is possible to represent most structured grids in this form, the focus here is on mappings that are known beforehand and not computed using the numerical calculations that are commonly used within the field of numerical grid generation. The grid is first constructed in index space using primitive shapes, and then the physical space grid is constructed from the mapping, usually a tensor-product type mapping where x=f(i), y=f(j), and z=f(k), though more mappings may be added in the future. hippogryph can read and write grids in the structured Plot3D format as well as the unstructured Exodus II format.", + "laborHours": 5274.4, + "languages": [ + "Python" + ], + "name": "hippogryph", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jasondegraw/hippogryph", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-05-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "CIMantic Graphs (aka CIM-Graph) is a new python library developed by PNNL to reduce the burden of working with the\nCommon Information Model. CIMantic Graphs takes a novel approach of building in-memory labeled property graphs for\ncreating, parsing, and editing CIM power system models.", + "laborHours": 38729.6, + "languages": [], + "name": "CIMantic Graphs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CIM-Tools/CIM-Graph", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2024-05-09", + "metadataLastUpdated": "2024-05-09" + }, + "description": "This software is for an application, designed for phones and/or tablets, to assist microbiome researchers collecting samples in the field to also collect metadata in a standardized and systematic way. The type of samples covered would be e.g. soil sample from a forest, sediment sample from a lake, or water sample in the ocean. The app allows users to collect sample information and metadata in an easy and intuitive way, and connects to the NMDC submission portal (https://data.microbiomedata.org/submission/home) a website from where users can review the samples they collected and add more information if necessary.", + "laborHours": 19076.0, + "languages": [], + "name": "NMDC Field Notes Phone Application (NMDC Field Notes) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/microbiomedata/nmdc-field-notes", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2024-05-09", + "metadataLastUpdated": "2024-05-15" + }, + "description": "EOS7MG is a new TOUGH3 module for modeling water, brine, and multiple gas mixtures in the subsurface multiphase flow system. The module allows mixture of as more as three gas components selecting from a list of predefined gases (CH4, C2H6, C3H8, H2S, CO2, N2, NO2, H2, and AIR). EOS7MG was developed based on EOS7C and inherited the general modeling capabilities of the TOUGH3 platform. It uses cubic equation of states for gas density, viscosity, and enthalpy calculation. The module provides the selection options for Peng-Robinson, Redlich-Kwong, or Soave-Redlich-Kwong equations of state. The subsurface flow and transport of gas and aqueous phase mixtures over a wide range of pressures and temperatures is modeled with a multiphase Darcy's Law and an accurate chemical equilibrium approach as originally implemented in EOS7C is used for calculation of the solubilities of different mass components. EOS7MG was designed to allow flexible number of components based on the number of gases included in the model. The potential application of this module may include subsurface gas storage, energy storage, CCS, enhanced gas recovery, and more.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 36039.2, + "languages": [], + "name": "TOUGH3/EOS7MG (EOS7MG) v1.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://marketplace.lbl.gov/tough", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-05-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A multi-modal few-shot learning approach is used to identify similarities between particles obtained from environmental samples. The inferred similarities are then used in a similarity graph to identify groupings and outliers in the sample", + "laborHours": 668.8, + "languages": [], + "name": "FLAMINGo: Few shot Learning Analysis of Multi-modal Inference Network Graphs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/particlefsl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "femtotime is a library for time tracking which uses 128 bit integers\nto allow tracking time with femtosecond resolution.\n\nThe API takes the form of a C++ class GPStime, which allows setting,\ngetting, manipulation, and conversion of time. The conversion to and\nfrom UTC tracks leapseconds.", + "laborHours": 1033.6, + "languages": [], + "name": "femtotime", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/femtotime", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "Tensor ELF is a user-friendly parallel tensor decomposition Python toolbox that includes a suite of machine learning algorithms for CPU and GPU architectures for the analysis of sparse and dense data including utility tools for pre-processing and post-processing.", + "laborHours": 32756.0, + "languages": [], + "name": "Tensor Extraction of Latent Features (TELF)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/T-ELF", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "ASAUM is a C++ library for representing distributed, multi-block structed and unstructured meshes. The library is meant to provide users with the ability to read/write, partition, and query the large distributed meshes that are commonly used in scientific computing.", + "laborHours": 14926.4, + "languages": [], + "name": "ASAUM--Adaptive Structured and Unstructured Mesh", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ASAUM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "Allows the user to fit a classical event categorization matrix (ECM) model, and a novel Bayesian event categorization matrix model, both of which are used for nuclear detonation detection.", + "laborHours": 1276.8, + "languages": [], + "name": "ezECM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/skoermer-LANL/ezECM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "Code for my PhD thesis that creates meshes using gmsh and code I wrote to create high-order hybrid meshes to use for testing a hybrid method between spectral element method and generalized finite differences. It also uses a tetrahedral mesh improvement method called \"stellar\" to improve mesh quality near a curved boundary.", + "laborHours": 1900.0, + "languages": [], + "name": "mgsflib", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Jacobj-LANL/mgsflib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "The software is a set of test problems for nonlinear optimization algorithms, including subroutines such as linear algebra routines and automatic differentiation algorithms. The test problems come from chemical engineering open literature, and describe optimization tasks related to the design and operation of processes such as carbon capture, Hydrogen production, heat exchange, and distillation.", + "laborHours": 167.2, + "languages": [], + "name": "A set of test problems for nonlinear optimization", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Robbybp/pselib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "It is a machine learning code written in python. The code is an inherent part of a paper (#LA-UR-24-22420). The code is required to be available on github as a part of paper submission process in the journal.", + "laborHours": 1079.2, + "languages": [], + "name": "Conditional latent autoregressive recurrent model (CLARM)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/clarm", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "Hop-Decorate is a python code developed as part of the LDRD funded project: 20220063DR: Accelerated Dynamics Across Computational and Physical Scales with the aim of using molecular dynamics and statics techniques to generate atomistic databases of defect transport in chemically complex materials using automated energy barrier calculations.", + "laborHours": 1109.6, + "languages": [], + "name": "Hop Decorate", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Hop-Decorate", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "RIDDL is a suite of software tools that enable AI/ML analysis of infrasound data. Methods and capabilities include construction, evaluation, and application of models for infrasound signal analysis, construction of synthetic data useful for construction and evaluation, as well as various other advanced data science tools enabling infrasound signal detection and categorization as well as downstream analysis methods such as localization and characterization of detected sources.", + "laborHours": 760.0, + "languages": [], + "name": "Robust Infrasound Detection via Deep Learning (RIDDL)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Seismoacoustics/riddl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "HPSim is a GPU-accelerated online multi-particle beam dynamics simulation tool for ion linacs. It was originally developed for use on the Los Alamos 800-MeV proton linac with the goal of providing a fast and accurate tool for realistic beam simulations of the actual operating linac. It runs on a GPU equipped workstation. The simulation parameters mirror those of the actual accelerator and can be manipulated through Python scripts in an offline mode or track them\nwhen connected via EPICS in an online mode.", + "laborHours": 33272.8, + "languages": [], + "name": "High Performance Simulator (HPSim", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/enchuanhuang/hpsim", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-22" + }, + "description": "DiscoFluxM is software for modeling the deformation behavior of crystalline materials within the third-party finite-element based software, MOOSE. The software enables full-field crystal plasticity finite element simulations of deformation processes of metals and other crystalline materials. DiscoFluxM is an implementation of the DiscoFlux theoretical and algorithmic framework for coupling single-crystal plasticity with dislocation transport. The \ncontinuum mesoscale modeling framework is founded upon a nonlocal dislocation-density based crystal plasticity theory. The nonlocal theory couples continuum dislocation transport with an otherwise spatially-local single-crystal model employing nonlinear thermoelasticity and crystallographic plasticity. Dislocation transport is modeled by enforcing dislocation conservation at a slip-system level through the solution of advection-diffusion equations. The configuration of geometrically necessary dislocation density gives rise to a back-stress that inhibits or accentuates the flow of dislocations.", + "laborHours": 1778.4, + "languages": [], + "name": "DiscoFluxM version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/subhendu-LANL/DiscoFluxM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "The Pipeline Hydrogen Decarbonization and Repurposing Analyzers (P-HyDRAs) are a set of prototype computational tools for simulating and optimizing midstream natural gas pipeline system operations subject to location and time-dependent hydrogen blending. The models can accurately resolve dynamic gas flows through large-scale pipeline networks using non-ideal gas equations of state. The codes can be used as decision support for planning and design decisions involving intra-day energy flow schedules as well as spatiotemporal economic values of natural gas, hydrogen, and net energy delivered to consumers while ensuring that pipeline hydraulic limitations, gas compressor station constraints, operational factors, and pre-existing shipping contracts are satisfied. The inputs to the codes are a model of the pipeline system as well as time-series data that specify boundary conditions on the network. For optimization, the code module requires price and quantity offers for natural gas and hydrogen and price and quantity bids for energy, which are used as time-dependent constraints in an optimal control problem. The outputs are time-series data that provide a predictive simulation of gas flows, mass fractions, and pressures, or with additional degrees of freedom give an approximately optimal solution for gas injections/withdrawals, compressor settings, and sensitivities to the objective function that provide locational values of energy.", + "laborHours": 5198.4, + "languages": [], + "name": "Pipeline Hydrogen Decarbonization and Repurposing Analyzers (P-HyDRAs)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/phydras", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gureckywl@ornl.gov" + }, + "date": { + "created": "2024-05-21", + "metadataLastUpdated": "2024-05-21" + }, + "description": "The CORRLA-RS package provides a suite of statistical methods for sampling multidimensional distributions and to conduct sensitivity and correlation analysis of large scale data in the Rust programming language. The software provides a unique solution to multidimensional constrained sampling problems utilizing a combination of parallelized Markov Chain Monte Carlo methods and traditional rejection sampling. The sensitivity and correlation analysis methods are backed by a high performance randomized singular value decomposition implementation which enables datasets larger than the random access memory (RAM) size to be analyzed. 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Code applied to data from the Groundwater\nAmbient Monitoring and Assessment (GAMA) program in California, including well location and\nconstruction information, chemical constituents and isotopic tracers, and land use metrics.", + "laborHours": 577.6, + "languages": [], + "name": "Ground Water Age Predictor", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GWAP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-05-28", + "metadataLastUpdated": "2024-05-28" + }, + "description": "A user friendly, graphical, open-source implementation of the multiple benefits framework to non-energy-benefits incorporating additional aspects to make the tool effective for use in the United States. 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Along with the actual fitting script, this repository contains several support scripts for data analysis and recall of prior fit results.", + "laborHours": 532.0, + "languages": [ + "Python" + ], + "name": "In-situ FTIR Spectral Deconvolution [SWR-24-60]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/In-Situ-FTIR-SpectralDeconvolution", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "martindalena@ornl.gov" + }, + "date": { + "created": "2024-05-30", + "metadataLastUpdated": "2024-05-30" + }, + "description": "IPyOverlay is a Python library that provides several IPyWidget components for use within the Jupyter software ecosystem. 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This capability enables adding click-and-draggable overlay windows containing other widgets, right-click context menus, and more complex tooltip functionality.", + "laborHours": 820.8, + "languages": [ + "Python" + ], + "name": "IPyOverlay", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl/ipyoverlay", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "allenmr@ornl.gov" + }, + "date": { + "created": "2024-05-31", + "metadataLastUpdated": "2024-06-05" + }, + "description": "This new version of NATURF, Version 1.0, builds on Version 0 by streamlining the code, decreasing its runtime and combining multiple modules into one convenient pip-installable package.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Neighborhood Adaptive Tissues for Urban Resilience Futures (NATURF) V1.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/naturf", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-06-01", + "metadataLastUpdated": "2024-06-06" + }, + "description": "The main function of ACCERT (The Algorithm for the Capital Cost Estimation of Reactor Technologies) is to provide an item-by-item estimate of the cost of a facility, at present a nuclear reactor complex, primarily nuclear power stations. The core of ACCERT is the large number of algorithms that have been developed and will continue to be developed. ACCERT is also a general methodology \nfor identifying and organizing the individual items that are estimated using the ACCERT algorithms. \nACCERT also summarize status and results; to save results and pull information from previous analyses; and to provide an interactive dynamic graphical user interface for a wide range of functions and visualizations.", + "laborHours": 16340.0, + "languages": [], + "name": "ACCERT", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/accert-dev/ACCERT", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-06-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An unsupervised segmentation method for structural analysis of Scanning Transmission\nElectron Microscopy (STEM) images", + "laborHours": 212.8, + "languages": [], + "name": "GraphEM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/GraphEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-06-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "CACTUS is an innovative LLM‐based agent that combines the cognitive capabilities of large language models with domain‐specific tools. By integrating\ncheminformatics tools, CACTUS assists researchers in tasks such as molecular property prediction, similarity searching, and drug‐likeness assessment.", + "laborHours": 729.6, + "languages": [], + "name": "CACTUS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/cactus", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "brewerwh@ornl.gov" + }, + "date": { + "created": "2024-06-04", + "metadataLastUpdated": "2024-06-28" + }, + "description": "ExaDigiT is a framework for developing comprehensive digital twins of liquid-cooled supercomputers, which has three main modules: (1) a python-based Resource Allocator and Power Simulator (RAPS), (2) a Modelica-based Thermo-Fluidic cooling model, and (3) a C++-based augmented reality model built on Unreal Engine 5. RAPS either simulates workloads or replays historical workloads from system telemetry, and is able to predict dynamic energy consumption, as well as interact with the cooling model to predict cooling system behavior. Such a tool can be used together with reinforcement learning algorithms to provide an end-to-end optimization tool for data centers.", + "laborHours": 775.2, + "languages": [ + "Python" + ], + "name": "ExaDigiT/RAPS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/exadigit/raps", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "hahnse@ornl.gov" + }, + "date": { + "created": "2024-06-04", + "metadataLastUpdated": "2024-06-05" + }, + "description": "AGILE GETRS provides an optimized implementation of DETRS that is faster than vendor optimized libraries for small (< 4000) problem sizes. 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For parameters defined by an equation (e.g. a polynomial function) or a list of tabulated values, Mist can evaluate parameter values at requested conditions. Mist also provides an API for direct usage of the Mist data structures in calculations, if supported.", + "laborHours": 410.4, + "languages": [ + "Python" + ], + "name": "Mist", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-MDF/mist", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "dewittsj@ornl.gov" + }, + "date": { + "created": "2024-06-04", + "metadataLastUpdated": "2024-06-04" + }, + "description": "Many computationally unintensive models for material process-structure-property connections exist in the literature (e.g. journal articles and textbooks). However, to our knowledge there is no existing compilation of these models in one package. Many industrially and research relevant workflows involve combinations of many of these models and if the models have inconsistent interfaces, building these workflows can be challenging.\n\nRamen provides a collection of computationally unintensive models for calculating material process-structure-property relationships from the literature, as well as related tools (e.g. for plotting results). These models use a consistent interface structure and all leverage material data files and data structures from the Mist library (also developed at ORNL).\n\nRamen provides a structured package for combining many standard models in one place, with a standardized interface. This approach makes combining models in long/complex chains easy and straightforward.", + "laborHours": 228.0, + "languages": [ + "Python" + ], + "name": "Ramen", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-MDF/ramen", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-05", + "metadataLastUpdated": "2024-06-05" + }, + "description": "SAND2024-04584O\nR package for applying the VEESA pipeline method is a technique used for explainable machine learning with functional data. The VEESA pipeline makes use of the elastic-shape analysis framework for functional data. It also implements functional principal component analysis and permutation feature importance. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 486.4, + "languages": [ + "R" + ], + "name": "VEESA R package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/veesa", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-06", + "metadataLastUpdated": "2024-06-06" + }, + "description": "SAND2024-01003O\nZPAL is a Python software development kit designed for use by network automation engineers. It is an application programming interface (API) wrapper that is compatible with ZPE System's Nodegrid API. ZPE produces networking equipment. ZPAL simplifies connections to the ZPE Nodegrid API and makes configuration changes on the associated networking equipment.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 896.8, + "languages": [ + "Python" + ], + "name": "ZPAL v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ZPAL", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-06", + "metadataLastUpdated": "2024-06-11" + }, + "description": "SAND2024-00946O\nPython codes used in \"Trade-offs in the latent representation of microstructure evolution,\" a manuscript accepted for publication in Acta Materialia, are part of a repository. The code was developed to perform analysis of microstructure evolution. \n\nThe repository consists of two main directories: models, which train and test models such as autoencoders and diffusion maps, and analysis, which analyzes microstructures. Source code is used to perform dimensionality reduction of microstructure data for analysis of its evolution in time. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Python codes for the paper - \"Trade-offs in the latent representation of microstructure evolution\"", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-06", + "metadataLastUpdated": "2024-06-06" + }, + "description": "SAND2024-00922O\nThis software uses electroluminescence images to predict power loss due to cell cracks in photovoltaic modules. The software will incorporate trained variational autoencoder(s) to parameterize cell cracks detected in electroluminescence images of photovoltaic modules and relate cracks to electrical properties; reduced-order models of finite element simulations of electrical behavior of photovoltaic modules under thermomechanical stresses; reduced-order models of stress distributions; inside photovoltaic modules resulting from x-ray topography experiments; and image segmentation and splining methods to analyze x-ray topography measurements of cracked photovoltaic cells. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "pvcracks", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pvcracks", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-06", + "metadataLastUpdated": "2024-06-06" + }, + "description": "SAND2024-00905O\nConstitutive Models via Automatic Differentiation (CMAD) provides a software framework for solving constitutive or material model calibration problems. It relies on JAX's automatic differentiation capabilities to compute the derivatives needed for both forward and adjoint sensitivity analyses. The software can be used to implement constitutive models and calibrate the parameters from experimental data. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1550.4, + "languages": [ + "Python" + ], + "name": "Constitutive Models via Automatic Differentiation v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cmad", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-07", + "metadataLastUpdated": "2024-06-13" + }, + "description": "SAND2023-07883O\nKokkos software implements C++ performance portability programming models, tools and math libraries, which enables science and engineering software developers to use single-source codes for a wide range of computer architectures. Kokkos also provides implementations of existing and proposed C++ standard features that support programming model and math libraries that are used for implementing performance-portable scientific and engineering applications. The Kokkos libraries provide algorithms, data structures, and tools to enable high-performance computing developers to write performance-portable code. Capabilities fall into three broad categories: Kokkos Core, Kokkos Kernels, and Kokkos Tools.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 119700.0, + "languages": [ + "C++" + ], + "name": "Kokkos v.4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/kokkos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "4.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-07", + "metadataLastUpdated": "2024-06-07" + }, + "description": "SAND2023-07864O\nScribe Network API is an add-on tool for Scribe3D software. Scribe Network API documents tabletop exercises in trainings and plays back simulated videos of the scenarios and responses. Users can apply the software to compiled projects, or to a simple visual studio project solution package. The software runs a web application that relays information between computers using Scribe3D through a web application, or web app. The web app involves a representational state transfer (REST) application programming interface that handles sending and receiving Scribe save files and an SQL server that stores the save files. This follow-on package allows users to facilitate a networked tabletop exercise. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 11764.8, + "languages": [ + "C#", + "SQL" + ], + "name": "Scribe Network API v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/scribe3d-api", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-07", + "metadataLastUpdated": "2024-06-07" + }, + "description": "Wetlands have often been described as the “Earth’s kidneys” because wetlands have the ability filter pollutants and purify water. Based upon wetland storage capacity, average daily flow, and inflow nutrient loading this model estimates potential load reductions of nitrate and orthophosphate) from a constructed surface flow wetland (CW). The model relies upon equations, coefficients, and models provided by Cheng et al. 2020 and Cheng & Basu 2017.\nNitrogen (N) and phosphorus are important nutrients to ecosystems, but high concentrations can lead to water quality issues. Major sources of these nutrients come from agricultural areas where fertilizer is applied in large quantitates and/or animal waste is present. Excess nitrate and phosphorus may result in overgrowth of algae, which can decrease the dissolved oxygen in water, thereby harming and killing fish and other aquatic species. This model evaluates water purification results and estimates cost to install a surface flow constructed wetlands.", + "laborHours": 197.6, + "languages": [ + "Python" + ], + "name": "Wetlands Geoprocessor (v 1.0)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/Wetlands_Geoprocessor", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-07", + "metadataLastUpdated": "2024-06-07" + }, + "description": "The proposed code, named FROG (Fusion neutron Generator) is built upon the open-source particle transport Monte Carlo toolkit Geant4. Geant4 provides C++ classes that can be leveraged to build application-specific codes dealing with the transport of particles through matter. Geant4-based codes are applied in high-energy particle physics experiments, medical applications, shielding, and space applications for example.\n\nThe FROG code allows the user to define the geometry of a neutron converter device shaped as a hollow cylinder, where a neutron breeding material such as lithium deuteride (LiD) is cladded by two concentric cylinders. Such neutron converter is then placed inside a regular nuclear fission reactor, where thermal neutrons will react with the neutron breeder material (typically, Lithium 6), and through a series of reactions, will generate high-energy neutrons – neutrons whose kinetic energy are around 14 MeV. The hollowed central portion can hold a specimen that will be bombarded by high-energy neutrons created inside the neutron breeding material. Figuratively speaking, this type of device transforms neutrons from thermal (~0.625 eV) to fusion (~14 MeV) energies and is sometimes termed “fusion-to-thermal neutron converters” in the literature. \n\nThe code consists of C++ source file compiled and linked to generate an executable. The user can select the dimensions of the converter (radius, length, and thickness of the breeder material), the breeder material type, the cladding material, and the specimen material that will be activated or irradiated. As input, the neutron flux for a specific location inside a reactor, for instance, positions in ATR, is required. As output, the code predicts the number of high-energy neutrons produced, the total neutron flux and fluence as well as its detailed spectrum. \n\nThe physics involved in such device is very complex, as it requires modeling neutron transport, light-ion (tritons) transport, as well as fusion reactions. The Geant4 toolkit provides the required physical models.", + "laborHours": 1489.6, + "languages": [ + "C++" + ], + "name": "Fusion Neutron Generator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/thermal_to_fusion_converter", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bridgesra@ornl.gov" + }, + "date": { + "created": "2024-06-11", + "metadataLastUpdated": "2024-06-11" + }, + "description": "This code allows reproduction of results in the paper\n\n\"Are Normalizing Flows the Key to Unlocking the Exponential Mechanism? \" https://arxiv.org/abs/2311.09200\n\nThe code here provides implementation of our experiments where we test if we can training models with ExpM+NF alongside and in comparison with DPSGD and non-private training.", + "laborHours": 21994.4, + "languages": [], + "name": "ExpM+NF MIMIC III experiments", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bridgesra/expm_nf_mimic3_results_code", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2024-06-11", + "metadataLastUpdated": "2024-06-17" + }, + "description": "AMES-Fit is a program used to automatically fit the multi-field solid-state NMR spectra of half-integer quadrupolar nuclei. Due to the high dimensional space, gradient algorithms have failed to address the fitting of such data, which is at present done manually. AMES-Fit diverges from these approaches by using an adaptive step size random search algorithm to fit the NMR spectra to consistently find the global best fit parameters.", + "laborHours": 1140.0, + "languages": [ + "C++" + ], + "name": "Automatic Multiple Experiment Simulation and Fitting (Ames-Fit)", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fperras/AMES-Fit", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2024-06-12", + "metadataLastUpdated": "2024-06-12" + }, + "description": "Axolotl is a Python library for scalable distributed genome and metagenome data analysis. Existing tools and systems that we rely on are struggling to keep up with the rapid explosion of genomic data. Compounding this issue, developing scalable solutions require a steep learning curve in parallel programming, which presents a barrier to academic researchers. While we do have scalable solutions for specific tasks, we lack comprehensive, end-to-end solutions. It's this gap in our toolkit that we aim to address with Axolotl. The Axolotl library is built for easy parallel processing, efficiently handling multiple tasks or large datasets simultaneously, and scaling up to meet the demands of extensive genomic data analysis.", + "laborHours": 2158.4, + "languages": [], + "name": "Axolotl: a scalable genomics library based on Apache Spark (Axolotl) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGI-Bioinformatics/axolotl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-12", + "metadataLastUpdated": "2024-06-12" + }, + "description": "RhizoNet is designed for the semantic segmentation of plant root scans, utilizing a sophisticated deep learning network known as Residual Unet. It specializes in processing color images of plants cultivated in a hydroponic EcoFAB system, captured using an Epson scanner. The core of the algorithm is based on Residual U-nets, which significantly improve prediction accuracy. This is achieved through the implementation of a convex hull operation, which effectively delineates the primary root component by leveraging spatio-temporal image data. This enables researchers to accurately assess predicted biomass and monitor plant growth over time.", + "laborHours": 608.0, + "languages": [], + "name": "RhizoNet: semantic segmentation of plant roots using CNN (RhizoNet) v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/rhizonet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "semalek@lbl.gov" + }, + "date": { + "created": "2024-06-12", + "metadataLastUpdated": "2024-06-17" + }, + "description": "The proposed system is written in the hardware description language (HDL) verilog targeting an FPGA board. It is intended as a testbed to explore architecture tradeoffs in multi-tiled heterogeneous architectures. Although we target FPGAs, the system can be implemented as a monolithic SoC or a package comprised of many chiplets that are interconnected in the same package using a NoC. The proposed NoC is lightweight and follows an axi-lite interface. The endpoints of the NoC are a heterogeneous mix of \"tiles\" as endpoints that are general purpose processors, fixed function accelerators, and programmable accelerators. We assume that the network interfaces for the NoC endpoints are all addressable in a global name-space in that they represent an address range (for memory addresses) or a range of unique identifiers that are associated with each individual tile. This makes the functionality abstract from the standpoint of the NoC design details. Message queues offer a direct inter-processor interface between peer general purpose cores and diverse accelerators that comprise an SoC. Although they share the same NoC infrastructure for inter-tile communication within an SoC or SiP, the hardware message queues bypass the memory hierarchy and thus do not pollute the memory state or invoke the cache coherence mechanism.", + "laborHours": 39656.8, + "languages": [], + "name": "P38 heterogeneous multi-tiled system with support for message queues (MoSAIC) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnlcomputerarch/MoSAIC-P38", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-12", + "metadataLastUpdated": "2024-06-12" + }, + "description": "This software allows to analyze XRF maps, XFS spectra and XAS spectra collected at the Advanced Light Source's Beamline 10.3.2.\n\nFeatures include:\n1) XRF maps:\n- process XRF maps, all elemental maps are saved as bmp automatically and labeled with the incident energy used, the scale bar is also labeled and can be controlled.\n- XRF elemental correlation plots, save the correlation plots automatically\n- Extract single or multiple transects in XRF maps on one or several regions of interest, each transect profile is numbered and saved in a corresponding folder, along with the corresponding maps showing transect location.\n\n2) XFS spectra\n- save in log10 scale the XFS spectra, either a single or multiple files all at once. The files are saved as .bmp.\n- XFS spectra are labeled according to tabulated fluorescence emission lines.\n\n3) XAS spectra\n- allows to plot individual scalers in the raw data.\n- allows calibration of the spectra using an Io internal glitch present in all spectra and performing 1st derivative.\n- Least-square linear combination fitting of XANES or extended XANES spectra using a database of standards using 1, 2 or 3 components maximum. It also provides the 5 top combinations and provide the user for the possibility of saving the 2nd, 3rd, 4th and 5th best combinations in addition to the best one. The processed spectra (pre-edge background substracted, post-edge normalized), the fits and residuals are automatically saved.\nA table of the component, with fit% and SSN is provided and saved automatically as well.", + "laborHours": 16400.8, + "languages": [], + "name": "XRF-XFS-XAS-Auto v1.0 - Beta release", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/als-computing/bl1032", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-13", + "metadataLastUpdated": "2024-06-13" + }, + "description": "DTX Explorer is a tool to generate interactive data visualizations of Darshan I/O traces collected from HPC applications. Its goal is to provide an easy and interactive way for researchers and developers to explore their application's I/O behavior and detect possible I/O bottlenecks that are impacting performance.", + "laborHours": 0.0, + "languages": [], + "name": "DXT Explorer v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/dxt-explorer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-13", + "metadataLastUpdated": "2024-06-17" + }, + "description": "PILATES allows for flexibly and at-scale coupling of multiple models to allow for multi-scale and multi-resolution simulation of regional-scale transport networks. In particular, it couples the MATSim-derived transportation modeling framework for Behavior, Energy, Autonomy and Mobility (BEAM) with other models operating at different time scales. Rather than tightly coupling supply and demand models using shared agents and memory within the same software process, PILATES orchestrates different model runs in a containerized framework. This structure requires passing information from the demand models to BEAM in the format of a synthetic population and agent plans, and from BEAM to the demand models in terms or origin/destination tables (also known as \"skims\"). This allows it to take advantage of the behavioral sophistication of existing activity-based models as well as the reinforcement learning structure of MATSim replanning and adopted by BEAM, in a way that requires minimal changes to existing models. It also takes advantage of the computational performance of BEAM, which allows for simulations with millions of agents to complete in reasonable time as well as allowing for detailed mechanistic simulation of the operation of on-demand modes.", + "laborHours": 4894.4, + "languages": [], + "name": "Platform for Integrated Land use And Transportation Experiments and Simulation (PILATES) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-UCB-STI/PILATES", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "edoardo.apra@pnnl.gov" + }, + "date": { + "created": "2024-06-13", + "metadataLastUpdated": "2024-06-17" + }, + "description": "NWChem is a computational chemistry software package which includes quantum chemical and molecular dynamics functionality. It aims to be scalable both in its ability to treat large problems efficiently, and in its usage of available parallel computing resources.", + "laborHours": 5977217.6, + "languages": [ + "C", + "Fortran", + "Python" + ], + "name": "NWChem", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/nwchemgit/nwchem/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nwchemgit/nwchem", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "7.2.2" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-06-13", + "metadataLastUpdated": "2024-06-13" + }, + "description": "This package includes three parts, (1) gov.llnl.math, (2)gov.llnl.utility and (3)gov.llnl.rtk, which are utilized\nin the development of Radiation Detector Simulator (RadSim) project. RadSim is being developed to\nprovide the capability to: (1) simulate radiation source emissions, (2) interpolate results from radiation\ntransport tools into a common format to prepare incident flux, and (3) model radiation detector response\nto rapidly produce synthetic radiation measurement templates. RadSim is targeted for open-source\nrelease, which will enable researchers and industry partners to model gamma-ray detectors response to\nsimulated flux from the transport tool of their choice. The techniques and implementation will be entirely\ntransparent, which will allow for improvements and boutique modifications by future researchers beyond\nthe lifespan of this specific project.\nThe first tool of the package, gov.llnl.math, includes classes and functions to define and perform basic\nmath operations. Some of the example features available in the package include defining statistical\ndistributions and performing algebra and matrix operations, all of which are already accessible on publicly\navailable software packages such as MATLAB and ROOT. The second package gov.llnl.utility includes\ntools commonly used to enable optimization and readability of various data structures such as Java lists\nand external xml files. Lastly, the gov.llnl.rtk package includes classes and functions to implement\nmethods commonly used in radiation physics, such as data structures to represent and characterize\nphoton spectra and tools to apply well-defined and published methods to calibrate a given spectra.", + "laborHours": 93373.6, + "languages": [], + "name": "RadSim: Math, Utility & RTK", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RadSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2025-03-26" + }, + "description": "The WETO Stack software is a collection of data, data analysis scripts, and website content produced through the Holistic Modeling Project’s Portfolio Coordination task. The purpose of the software is to characterize the collection of wind energy software projects supported by the U.S. Department of Energy’s Wind Energy Technologies Office. The included data contains characteristics of the actively funded software projects, and the data analysis scripts provide insights into the breadth, depth, and maturity of the collection of software projects. The website content presents the results of the analyses as well as reports from workshops and other events. It can be viewed at https://nrel.github.io/WETOStack/index.html.", + "homepageURL": "https://github.com/NREL/WETOStack", + "laborHours": 5076.8, + "languages": [ + "Python", + "TeX", + "Makefile" + ], + "name": "WETO Stack [SWR-24-81]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://creativecommons.org/licenses/by-nc-nd/4.0/?ref=chooser-v1", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://github.com/NREL/WETOStack", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2024-09-16" + }, + "description": "The NREL Wattile extension, nrelWattileExt, provides an interface between SkySpark, an energy management and analytics software, and Wattile, an NREL-developed Python package for probabilistic prediction of building energy consumption. Wattile models predict discrete quantiles of the probability distribution of a target quantity (typically energy consumption) using the historical time series data from one or more predictors (typically weather data). Within SkySpark, predictions from Wattile models can be used for measurement & verification of building performance, detection of energy anomalies, and fault detection.\n\nRelated to: https://github.com/NREL/Wattile", + "laborHours": 182.4, + "languages": [ + "Dockerfile", + "Fantom" + ], + "name": "nrelWattileExt (SkySpark Wattile Extension) [SWR-24-73]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/nrelWattileExt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The software framework, AMReX, supports the development of block-structured adaptive mesh refinement (AMR) algorithms for solving systems of partial differential equations. 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AMReX uses a lightweight abstraction layer that effectively hides the details of the architecture from the application. The framework currently supports CUDA, HIP and SYCL for GPU acceleration and OpenMP for multi-core CPU architectures.", + "laborHours": 0.0, + "languages": [], + "name": "AMReX v2024", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Codes/amrex", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2024-06-14" + }, + "description": "This software provides functions to perform visual predicate estimation by leveraging the pre-trained\nvision-language model CLIP. In addition to training the prediction estimator with a labeled dataset, it also\nperforms performance evaluation and visualization of results.", + "laborHours": 927.2, + "languages": [], + "name": "CLIP Representation Enhanced Predicate Estimation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CREPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2024-06-14" + }, + "description": "These codes estimate effective diffusivity for species transport in materials and simultaneously fit multiple temperatures of measured isotherm and effective diffusivities for sorption transport of species through materials. Assumes triple-mode type sorption thermodynamics with mobile and immobile species in quasi-equilibrium.", + "laborHours": 349.6, + "languages": [], + "name": "FitIsoAndDeff and DeffCalculator Matlab Codes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/foley352/polymer-diffusion", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "01" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ATLAS is a comprehensive vehicle transaction and technology adoption microsimulator. ATLAS evolves the fleet mix of individual households by simulating the transaction (vehicle addition, disposal, and replacement) and choice (vehicle type, vintage, powertrain, and tenure) decisions in response to the co-evolving demographics, land use, and vehicle technology simulations. Different from the existing vehicle models that are either static or aggregated (e.g. stock model), ATLAS is fully disaggregated and dynamic following a sequential and circumstantial decision-making trajectory. This fine-grained approach not only enhances the realism of the simulation but also provides a nuanced understanding of the dynamics inherent in vehicle fleet evolution. ATLAS outputs are fully compatible with subsequent agent-based transportation modeling system and can enable distributional effect analysis regarding the fleet turnover among heterogeneous populations. ATLAS expands the typical new sale focused vehicle choice modeling to including used vehicle transactions that are of increasing interests to understanding the vehicle adoption behavior among lower income households.", + "laborHours": 2173.6, + "languages": [], + "name": "Automobile and Technology Lifecycle-Based Assignment (ATLAS) v2.0.12", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-science-it/atlas-release", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2024-06-19", + "metadataLastUpdated": "2024-06-19" + }, + "description": "We introduce HTESP (High-Throughput Electronic Structure Package), an automated tool designed for high-throughput ab initio calculations. HTESP simplifies the entire workflow, including data extraction, input files generation, calculation submission, result collection, and plotting. The package is implemented in Python and Bash languages. In this paper, we provide detailed information about the package, its installation process and some illustrative examples to demonstrate its usage. Additionally, the package includes comprehensive online documentation on input parameters and tutorials to assist users.", + "laborHours": 14060.0, + "languages": [ + "Bash", + "Python" + ], + "name": "High-throughput electronic structure package", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Neraaz/HTESP", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "Polyglot utilizes a combination of custom and open source tools and libraries to provide developers with a consistent environment for building tools, etc. for a wide variety of targets with minimal changes to the code being built. It supports a variety of architectures and operating systems/firmware in as target-agnostic way as possible. This allows for developers to minimize the amount of time/effort required to port tools—in particular, forensic tools—to a wide variety of targets.\nThe project is comprised of two main components: a frontend toolchain that understands how to utilize other tools in order to build code for a specific target, and a minimalistic C library specific to Polyglot. These collectively provide the method to build code for a specific target, and the capability for code to interact with the underlying operating system when run on the target. Both components are written in a way to minimize the amount of target-specific knowledge required to both develop and utilize the project.", + "laborHours": 4347.2, + "languages": [ + "C", + "C++", + "Python" + ], + "name": "Polyglot Framework", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/polyglot", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "The C library component of Polyglot.\nPolyglot utilizes a combination of custom and open source tools and libraries to provide developers with a consistent environment for building tools, etc. for a wide variety of targets with minimal changes to the code being built. It supports a variety of architectures and operating systems/firmware in as target-agnostic way as possible. This allows for developers to minimize the amount of time/effort required to port tools-in particular, forensic tools-to a wide variety of targets.\nThe project is comprised of two main components: a frontend toolchain that understands how to utilize other tools in order to build code for a specific target, and a minimalistic C library specific to Polyglot. These collectively provide the method to build code for a specific target, and the capability for code to interact with the underlying operating system when run on the target. Both components are written in a way to minimize the amount of target-specific knowledge required to both develop and utilize the project.", + "laborHours": 31129.6, + "languages": [ + "C" + ], + "name": "Polyglot C Library", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/polyglot-libc", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "This code is a web-based front-end only (HTML, CSS, JS) chatbot interface for any OpenAI compatible text completion API.", + "laborHours": 638.4, + "languages": [ + "JavaScript", + "HTML", + "CSS" + ], + "name": "Front-end Only Chatbot Interface", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HPC_OOD_Chat", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-26" + }, + "description": "Complex engineering systems such as nuclear power plants (NPPs) generate and collect large amounts of equipment reliability (ER) data elements that contain information on the status of components, assets, and systems. Some of this information is textual in form and can be found in documents such as incident reports (IRs) and work orders (WOs). Analyses of textual data in current NPPs-using natural language processing (NLP) methods-have been expanded over the last decade, and it is only recently that the true potential of such analyses has emerged. So far, applications of NLP methods have mostly been limited to classification and prediction, the goal being to identify the nature of the textual element (e.g., safety or non-safety related). Here, we target a more complex problem: automatically extracting knowledge from a textual element in order to assist system engineers in conducting system health assessments. Knowledge extraction is a very broad concept, and its definition may vary depending on the application context. Our methods are a blend of both rule-based and machine learning (ML) algorithms. For our purposes, knowledge extraction means identifying the systems or assets mentioned in a given textual element, as well as the type of event described (e.g., component failure or maintenance activity). In addition, we want to capture details such as measured quantities and the temporal/cause-effect relations between events. In this tool, we also demonstrate how textual data elements are preprocessed in order to handle typos, acronyms, and abbreviations. One main feature of these methods is that they are not based solely on data, but are in fact model-based. In other words, they also rely on MBSE models that are designed to capture-from a functional point of view-the architecture of the systems/assets under consideration. The main purpose of such models is to digitally emulate system engineers' knowledge of system and asset architecture and to identify dependencies among systems, assets, and components. Provided these models, analyses of textual and numeric ER data can be performed by first identifying the OPM model elements to which the ER data elements are referring. The relationships between ER data elements are then identified by checking for any temporal or logical dependencies.", + "laborHours": 7265.6, + "languages": [ + "Python" + ], + "name": "Digital Analytics, Causal Knowledge Acquisition and Reasoning for Technical Language Processing", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DACKAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "The Many-Body Adaptive Configuration Interaction Suite (MACIS) is a modern C++ software infrastructure for the development of selected-configuration interaction (sCI) methods for the fermionic many-body problem in quantum chemistry and materials science. MACIS provides a high-performance, parallel implementation of the Adaptive Sampling Configuration Interaction (ASCI) method as related solvers such as self-consistent orbital optimization and the evaluation of excited states and spectral functions. Unlike existing sCI software, MACIS is developed as a modular software infrastructure which allows it to exist both as a standalone sCI solver and as a library to integrate into existing many-body codes. This modularity allows MACIS to be quickly extensible, including its integration with other sCI methods and high-performance solvers.", + "laborHours": 18696.0, + "languages": [], + "name": "Many-Body Adaptive Configuration Interaction Suite (MACIS) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wavefunction91/MACIS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "Scripts for analyzing microbial community taxonomy and function, running statistical tests, and making complex graphics.", + "laborHours": 14440.0, + "languages": [], + "name": "SF_Microbe_Methane (SFMM) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cliffbueno/SF_microbe_methane", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-25" + }, + "description": "Geant-4 based detector simulations in c++ which combines simulation and analysis into a single framework to precisely model detector components and analyze experimental data. Ratpac allows the user to easily build new detector geometries and configurations through both the source library and through configurable text files at runtime.", + "laborHours": 48883.2, + "languages": [], + "name": "Ratpac-Two v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rat-pac/ratpac-two", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "REMORA (previously known as ROMS-X) is a GPU-enabled regional ocean modeling code with the same core capabilities as the Regional Ocean Modeling System (ROMS) code.", + "laborHours": 11187.2, + "languages": [], + "name": "REMORA v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/seahorce-scidac/REMORA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "This repository contains data and code for statistically comparing soil microbial communities across four different wetland sites and making publication quality figures. It is similar to other microbiome analysis but is specific for this project.", + "laborHours": 834145.6, + "languages": [], + "name": "EastCoast v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cliffbueno/EastCoast", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-26" + }, + "description": "Open source Node-Red \"nodes\" to support the Open Charge Point Protocol (OCPP) 2.0.1 protocol.", + "laborHours": 15899.2, + "languages": [], + "name": "node-red-contrib-ocpp2", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/node-red-contrib-ocpp2", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "SynthFirm is a large-scale agent-based freight demand model which generates a complete synthetic population of firms in the U.S. and the business-to-business commodity flows between them. Using publicly available data sources as inputs, SynthFirm simulates detailed firm and fleet characteristics, commodity production and consumption, formation of supply chains, and selection of shipping modes, all of which are essential drivers of commodity flow at a disaggregate level.", + "laborHours": 19456.0, + "languages": [], + "name": "Firm Synthesizer and Supply-chain Simulator (SynthFirm) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-UCB-STI/SynthFirm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-26" + }, + "description": "The Inventory of Composable Elements (ICE) is an open source registry software platform for managing information about biological parts. It is capable of recording information about plasmids, microbial host strains and seeds, as well as DNA parts. Includes features such as DNA sequence visualization, editing and annotation, auto-aligning sequencing trace files against reference templates, SBOL XML/RDF support, and web-of-registries functionality. The web of registries functionality provides strong support for distributed interconnected use and enables sharing and transfer of biological parts across various independent ICE instances. ICE adopts modern software development principles, leveraging component-base frameworks, offering a REST API for convenient third-party integration and emphasizing scalability, security, and service integrations for dynamic content availability. The source code is hosted at https://github.com/JBEI/ice. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects.", + "laborHours": 45037.6, + "languages": [], + "name": "Inventory of Composable Elements (ICE) v6.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/ice", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "Fusion Transfer Learning (FTL) model provides a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. The knowledge transfer process leverages a pre-trained neural encoder-decoder network, initially trained on linear simulations, to effectively capture nonlinear dynamics. The low-dimensional embeddings extract the coherent structures of interest, while preserving the inherent dynamics of the complex system. Experimental results highlight FTL's capacity to capture transitional behaviors and dynamical features in plasma dynamics -- a task often challenging for conventional methods. The model developed in this study is generalizable and can be extended broadly through transfer learning to address various magnetohydrodynamics (MHD) modes.", + "laborHours": 91.2, + "languages": [], + "name": "FTL: Transfer Learning Nonlinear Plasma Dynamic Transitions in Low Dimensional Embeddings (FTL) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zhbai/FTL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-27" + }, + "description": "For the development of magnets for particle accellerators, the tool ROXIE from CERN has become a de facto standard. This script interprets the output files of ROXIE and translates them into a VTK file that can be read in ParaView for visualization.", + "laborHours": 273.6, + "languages": [], + "name": "rox2vtk v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmesse/rox2vtk.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "The software program, referred to as BELFEM, is a specialized finite element code designed for the magnetodynamic modeling of high-temperature superconducting (HTS) tapes. It incorporates novel mixed finite element formulations, particularly the h-ϕ-formulation with thin-shell simplification, to efficiently simulate larger geometries. This methodology is extremely promising for predicting the electrodynamic performance of HTS tapes used in superconducting cables and magnets, offering the benefit of reduced computational cost. Compared to similar technologies like COMSOL Multiphysics and GetDP, BELFEM's performance benchmarking indicates superior efficiency in its thin-shell implementation. In the future, it will also support features like thermal coupling and inter-tape current sharing, enhancing its utility in research and development, particularly in nuclear fusion applications. The intent is to develop BELFEM as a robust and efficient tool for the HTS community, contributing to the analysis and design of superconducting cables and magnets.", + "laborHours": 97416.8, + "languages": [], + "name": "Berkeley Lab Finite Element Framework (BELFEM) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmesse/belfem.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Active learning algorithms based on surrogate models to solve black-box optimization problems and other scientific applications.", + "laborHours": 4332.0, + "languages": [ + "Jupyter Notebook", + "R", + "Python" + ], + "name": "BBOpt (Black-Box Opt) [SWR-24-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bbopt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "This package includes three parts, (1) gov.bnl.nndc.ensdf, (2) gov.nist.xray and (3) gov.nist.physics.n42, which are utilized in the development of Radiation Detector Simulator (RadSim) project. RadSim is being developed to provide the capability to: (1) simulate radiation source emissions, (2) interpolate results from radiation transport tools into a common format to prepare incident flux, and (3) model radiation detector response to rapidly produce synthetic radiation measurement templates. RadSim is targeted for open-source release, which will enable researchers and industry partners to model gamma-ray detectors response to simulated flux from the transport tool of their choice. The first tool of the package, gov.bnl.nndc.ensdf, includes functionality to parse and split publicly available decay records in ENSDF format, and pull the relevant information from ENSDF libraries. The second tool, gov.nist.xray, provides Xray information using the public NIST database. Lastly, gov.nist.physics.n42, is a tool used to convert an N42 xml file into a Java object that can be interfaced within a Java program.", + "laborHours": 93373.6, + "languages": [], + "name": "RadSim: ENSDF, Xray and N42", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RadSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "Modelling and solution library for security-constrained AC optimal power flow problems that uses nonlinear programming methods (interior-point methods) and solvers (Ipopt, HiOp). The code is written in C++ and provides parallel computing capabilities in the form of task parallelism (solving contingency problems in parallel). Code can run on a variety of commodity high-performance computing.", + "laborHours": 11886.4, + "languages": [], + "name": "Grid Optimization Lawrence Livermore Nonlinear Programming", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gollnlp/gollnlp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-24", + "metadataLastUpdated": "2024-06-27" + }, + "description": "The software package in question is a collection of simulation models in the Modelica language, representing a variety of mechanical system designs and envelope conditions related to LBL's FLEXLAB facility. The collection of models also features multiple controls sequences that can be simulated with the FLEXLAB model to simulate different demand flexibility scenarios. Additionally, this package will feature datasets from 3 experimental tests, used for calibration, validation and comparison against the Modelica models, this includes weather data that can be used to replicate different scenarios in simulation across the same weather conditions experienced in real experiments. Given FLEXLAB high level of instrumentation and available data, the models are calibrated across multiple measurement points, and thus results from the extension of this model to other climate zones or control sequences, would provide high level of confidence.", + "laborHours": 0.0, + "languages": [], + "name": "Hardware In the Loop for Demand Flexibility (HIL4DF) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/HIL4DF", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-24", + "metadataLastUpdated": "2024-06-24" + }, + "description": "This is a parallel variable population multi-objective optimizer with an adaptive unified differential evolution algorithm or a genetic algorithm.\nIt can also be used for single objective optimization.\nSome features of this code include:\n1) The population size varies from generation to generation to save the total # of objective function evaluations.\n2) The population is uniformly distributed to a number of parallel processors for simultaneous objective function evaluation.\n3) The objective function evaluation can be attained from an external simulation program with control variables in its input file and objectives calculated from its output files.\n4) The optimizer includes an adaptive unified differential evolution algorithm and a real value genetic algorithm. The parameters in the unified differential evolution algorithm can be chosen to attain any mutation schemes in the published literature.", + "laborHours": 836.0, + "languages": [], + "name": "Parallel Variable Population Multi-Objective Optimizer (pvpmoo) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qianglbl/PVPmoo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-25", + "metadataLastUpdated": "2024-07-03" + }, + "description": "This program is used to subset metagenomic functional profiles to a list of desired taxa.", + "laborHours": 15.2, + "languages": [], + "name": "KO_by_taxa v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cliffbueno/KO_by_taxa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-25", + "metadataLastUpdated": "2024-06-25" + }, + "description": "It is a serial/parallel code for fast electron beam longitudinal\nforward or backward tracking through an electron linear accelerator.\n\nThis codes includes longitudinal space-charge effect, structure\nand resistive wall wakefields, and longitudinal coherent synchrotron radiation effect.\n\nTo use it as a parallel code, please comment out the \"use mpistub\" in BeamBunch.f90, rename mpif.h as mpif.hh,\nand use the Makefile_parallel as Makefile.", + "laborHours": 942.4, + "languages": [], + "name": "Electron Beam Longitudinal Tracking (EBLT) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qianglbl/EBLT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-25", + "metadataLastUpdated": "2024-06-25" + }, + "description": "This software was designed as a sequence validation tool for the assembly of synthetic constructs. It analyzes FASTQ files against a list of reference sequences, combining the results from eight sequencing libraries to generate a summary, and the files needed to view the results in the Integrative Genomics Viewer (IGV) application for manual verification. This was developed for FASTQ files generated by PacBio sequencing, but could be used on any FASTQ files that do not have paired end reads. It can be used to analyze one - eight libraries at a time, and assumes that each construct sequence in the reference will be in each pool, however, this is not a requirement. This is used to identify which libraries of pooled sequences contains a perfect match, or fixable match to the reference file.\n\nThis pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up, as well as the user friendly html summary that is generated.", + "laborHours": 9363.2, + "languages": [], + "name": "Synthetic Biology PacBio/JAWS QC Analysis (PBJ) v3.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/jgi-synbio-public/synbioqc-pbj", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-27", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This software was designed as a sequence validation tool for the assembly of synthetic constructs, where the constructs have a high degree of similarity and thus are barcoded prior to the sequencing library prep. It demultiplexes each FASTQ file for each barcode, then analyzes the resulting FASTQ files against a list of reference sequences for that barcode/library, combining the results from eight sequencing libraries to generate a summary, and the files needed to view the results in the Integrative Genomics Viewer (IGV) application for manual verification. This was developed for FASTQ files generated by PacBio sequencing, but could be used on any FASTQ files that do not have paired end reads. It can be used to analyze one - eight libraries at a time. Each construct is independently analyzed with only the sequences with the same barcode, in the same pooled library. Then the results are combined into a user friendly summary. This is used to identify which libraries of pooled sequences contains a perfect match, or fixable match to the reference file. This pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up, as well as the user friendly html summary that is generated.", + "laborHours": 3800.0, + "languages": [], + "name": "SynBio QC Dual Barcode QC (DBC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/jgi-synbio-public/synbioqc-dual_barcode", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-27", + "metadataLastUpdated": "2024-06-27" + }, + "description": "ICDFO is python and matlab/octave code for a set of for interpolation-based optimization methods for composite derivative-free optimization. These methods are applicable when a user wishes to maximize or minimize a function that depends on some blackbox component/simulation for which derivatives with respect to the decision variables are not available. The methods include pounders and goombah.", + "laborHours": 3040.0, + "languages": [], + "name": "Interpolation-Based Composite Derivative-Free Optimization (IBCDFO) v0.01", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/POptUS/IBCDFO", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-27", + "metadataLastUpdated": "2024-06-27" + }, + "description": "The Scientific sofTware Research for User experience, Design, Engagement, and Learning project (STRUDEL) will create, using user research methodologies, a planning framework and design system for scientific software that will guide and support the development of highly functional and usable user interfaces.", + "laborHours": 323243.2, + "languages": [], + "name": "Scientific sofTware Research for User experience, Design, Engagement, and Learning (STRUDEL) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/strudel-science/strudel-kit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-28", + "metadataLastUpdated": "2024-06-28" + }, + "description": "Increases in sequencing capacity, combined with rapid accumulation of publications and associated data resources, have increased the complexity of maintaining associations between literature and genomic data. As the volume of literature and data have exceeded the capacity of manual curation, automated approaches to maintaining and confirming associations among these resources have become necessary. Here we present the Data Citation Explorer (DCE), which discovers literature incorporating genomic data whether or not provenance was clearly indicated. This service provides advantages over manual curation methods including consistent resource coverage, metadata enrichment, documentation of new use cases, and identification of conflicting metadata. The service reduces labor costs associated with manual review, improves the quality of genome metadata maintained by the U.S. Department of Energy Joint Genome Institute (JGI), and increases the number of known publications that incorporate its data products. The DCE facilitates an understanding of JGI impact, improves credit attribution for data generators, and can encourage data sharing by allowing scientists to see how reuse amplifies the impact of their original studies.", + "laborHours": 16036.0, + "languages": [ + "ABAP" + ], + "name": "Data Citation Explorer (DCE) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/data-citation-explorer/data-citation-explorer-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-06-28", + "metadataLastUpdated": "2024-07-15" + }, + "description": "EVI-OnDemand is a simulation platform which estimates fast-charging infrastructure requirements necessary to support ride-hailing electrification. The tool belongs to the broader EVI-X family, a consortium of infrastructure modeling tools created by researchers at the National Renewable Energy Laboratory (NREL).", + "laborHours": 228.0, + "languages": [ + "Python" + ], + "name": "EVI-OnDemand [SWR-21-115]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EVI-OnDemand", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kumarv@ornl.gov" + }, + "date": { + "created": "2024-06-28", + "metadataLastUpdated": "2025-03-31" + }, + "description": "ExaDigiT is a framework for developing comprehensive digital twins of liquid-cooled supercomputers, which has three main modules: (1) a python-based Resource Allocator and Power Simulator (RAPS), (2) a Modelica-based Thermo-Fluidic cooling model, and (3) a C++-based augmented reality model built on Unreal Engine 5. The Modelica-based cooling model is primarily built-on the open-source Transient Simulation Framework\nof Reconfigurable Models (TRANSFORM) library and the open-source autocsm library.\nThe library follows the templating architecture developed in the TRANSFORM and the autocsm libraries. This tool can be easily extended to model other Frontier-like liquid cooled supercomputers.", + "laborHours": 395.2, + "languages": [], + "name": "datacenterCoolingModel", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/exadigit/datacenterCoolingModel", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-07-01", + "metadataLastUpdated": "2024-07-01" + }, + "description": "Artifact Description of the Cerebras TriLabs SC'24 conference paper. Include details and procedures for how to reproduce timing computations.", + "laborHours": 45.6, + "languages": [], + "name": "Cerebras TriLabs SC'24 paper Artifact Description", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CerebrasTrilabs-SC24AD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-07-01", + "metadataLastUpdated": "2024-07-01" + }, + "description": "The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.", + "laborHours": 0.0, + "languages": [ + "Python", + "Shell" + ], + "name": "Fast All-sky Radiation Model for Solar applications (FARMS) 2023 [SWR-16-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/farms", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.5" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-07-01", + "metadataLastUpdated": "2024-07-01" + }, + "description": "cloud-fs (Cloud File System Utilities) is a generalized file-system handler that will dynamically determine if files are local or on the cloud (currently AWS) and perform basic file-system operations.", + "laborHours": 0.0, + "languages": [ + "Python", + "Shell" + ], + "name": "cloud_fs (Cloud File System Utilities) 10.6.2021 [SWR-21-83]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/cloud_fs", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.0.8" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SAND2024-01036O\nThe updated Sandia Solution Mining Code (SANSMIC) modeling software models the dissolution of underground salt cavern walls due to raw-water injection (leaching), assuming an oil blanket. A previous version of this software modeled the impacts of leaching at the Strategic Petroleum Reserve and has been used in research for several decades, but the source code was not available. The new version will enhance current research as additional subsurface storage of energy in solution-mined caverns increases. It will also allow research reproducibility by making the software available to the wider research community. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 2021.6, + "languages": [ + "C++", + "Python" + ], + "name": "SANSMIC v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sansmic", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-03", + "metadataLastUpdated": "2024-07-03" + }, + "description": "SAND2024-08373O\nTwinMe4AD is a Python-based software tool designed for anomaly detection using digital twins that closely mimic real, wearable healthcare datasets. The tool is invaluable for scenarios where collecting data is either expensive or impractical, serving as a privacy-preserving solution. Sensitive information is protected by training deep learning models on synthetic data derived from real datasets. One of TwinMe4AD's key features is its anomaly detection capability, which is based on fourth-order moments of parameters. This versatile approach can be applied across a range of datasets, from univariate to multivariate, making it compatible with various types of data. It also generates synthetic twins using Wasserstein Generative Adversarial Networks (WGANs), allowing users to create a small cohort of a population similar to that of a village population. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1550.4, + "languages": [ + "Python 3.6" + ], + "name": "TwinMe4AD: WGAN-based Digital Twins for Anomaly Detection", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TwinMe4AD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-08", + "metadataLastUpdated": "2024-07-16" + }, + "description": "SAND2021-6741 O\nphenix is Sandia's orchestration tool that allows users to quickly deploy, un-deploy, and interact with SCEPTRE ICS environments. phenix is an orchestration tool used for managing the creation, configuration, and deployment of modeling and simulation environments. As an abstraction layer on top of an underlying virtual machine manager called minimega, phenix organizes the network, application, and scenario information for a given deployment. It allows users to create, configure, and deploy experiments in a repeatable and rapid fashion. An application framework provides the flexibility to manipulate an experiment to suit various needs and requirements. phenix also includes a web-based graphical user interface (GUI) where experiments can be created, configured, and interacted with.", + "laborHours": 131145.6, + "languages": [ + "Go", + "Javascript", + "Vue" + ], + "name": "phenix v. 7.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sceptre-phenix", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "7.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-07-09", + "metadataLastUpdated": "2024-07-09" + }, + "description": "Python software package for PCA analysis of ToF-SIMS spectra data", + "laborHours": 805.6, + "languages": [], + "name": "Automated ToF-SIMS PCA Analysis Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pca-analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-07-10", + "metadataLastUpdated": "2024-07-10" + }, + "description": "This is the official code for the ICML 2024 paper \"Adversarial Robustness Limits via Scaling-Law and\nHuman-Alignment Studies\". 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It will include general scripts for user management, scripts for helping users interact with\nLC resource management software (e.g. SLURM and Flux), and scripts to automate common user\ncommand-line tasks on LC and other HPC machines. These scripts are intended to be made available to\nall LC users. Hosting them on GitHub will allow LC staff, users, and collaborators to work on them\ntogether.", + "laborHours": 60.8, + "languages": [], + "name": "Livermore Computing User and System Scripts", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LCUSS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-11", + "metadataLastUpdated": "2024-07-11" + }, + "description": "REFA is designed to help transmission planners better understand the financial, environmental and economic benefits of reconductoring upgrades, using traditional or advanced conductors. More specifically, the tool enables grid planners and utilities to demonstrate the entire lifetime value of reconductoring projects, providing potential justifications for projects with higher Capex - the purchase of long-term physical or fixed assets used in a business's operations. Existing tools are designed to compare technical aspects of different conductor applications. They typically do not allow a cost-benefit analysis over the lifetime of the conductor's operations.", + "homepageURL": "https://gridintegration.lbl.gov/refa", + "laborHours": 98800.0, + "languages": [], + "name": "Reconductoring Economic and Financial Analysis Tool (REFA) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://gridintegration.lbl.gov/refa", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://gridintegration.lbl.gov/refa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-11", + "metadataLastUpdated": "2024-07-11" + }, + "description": "A Python package that provides differentially private queries optimized for energy systems' data. It may be used to publish queries such as clustering, averaging, metadata inference, etc. that are useful for a variety of grid-related analytics, including cyberattack detection.", + "laborHours": 410.4, + "languages": [], + "name": "CEDS Differential Privacy (CEDSDP) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/CEDSKMeans", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This Python package implements a high-level interface to access the data published by the Particle Data Group (PDG) in the Review of Particle Physics (the \"Review\").\n\nThe Particle Data Group is an international collaboration led by the PDG group at LBNL. The PDG summarizes the established knowledge in the field of particle physics in a single publication, the Review of Particle Physics. The Review is published and updated online (see https://pdg.lbl.gov) each year, and published in a scientific journal every other year. It is currently licensed under a CC BY-NC 4.0 license. In 2021 PDG was designated by the Office of Science as a SC PuRe Data Resource. The Review is one of the most highly cited publications in the field of particle physics.\n\nThe PDG Python API is part of PDG's efforts to make all data provided in the Review available in machine-readable format. This data includes the PDG world averages (or best limits) on particle masses, widths or lifetimes, branching fractions, magnetic moments, form factors, coupling constant ratios, and searches, as well as particle quantum numbers. It also includes detailed information on how PDG arrived at its averages, such as e.g. tables of published measurements with comments and footnotes, information on the consistency of published measurements, and detailed fit information.", + "laborHours": 988.0, + "languages": [], + "name": "Python package for machine-readable access to PDG data (PDG Python API) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/particledatagroup/api", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "The Advanced Fenestration Controller is the result of 5+ years of R&D to develop an advanced control system for Dynamic Facades (e.g., automated shades, blinds, etc.), electric lighting, and HVAC system in buildings. It can dynamically control those technologies to reduce electricity cost while increasing comfort. The work in FY22 focused on open-sourcing our development, per agreement with DOE.", + "laborHours": 2523.2, + "languages": [], + "name": "Advanced Fenestration Controller (AFC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/AFC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2025-01-30" + }, + "description": "Tardigrade-examples is a repository of computational workflows that exercise the Tardigrade software package. The Tardigrade software package is an implementation of Eringen’s micromorphic continuum theory with capabilities to support multiscale material modeling. These capabilities include homogenization through the Micromorphic Filter, calibration of micromorphic material models, and macroscale simulation in Tardigrade-MOOSE. This repository investigates continuum upscaling of various direct numerical simulations (DNS) conducted in Abaqus finite element (FE), Ratel FE, and GEOS material point method (MPM) software. Verification of the upscaling workflow is first investigated by considering DNS of trivial stress states for homogeneous materials, results of which indicate that classical continuum behavior is recovered as expected. DNS of heterogeneous materials are then considered.", + "laborHours": 10579.2, + "languages": [], + "name": "Tardigrade-examples V0.1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Tardigrade-examples", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This library is a collection of python modules that define, train, and analyze vision-transformer (ViT) machine learning models. The code implements, with mild modifications, ViT models that have been made publicly available through publication and GitHub code. The training data for these models is hydrodynamic simulation output in the form of numpy arrays. This library contains code to train these ViT models on the hydrodynamic simulation output with a variety of hyperparameters, and to compare the results of such models. Furthermore, the library contains definitions of simple convolutional neural network (CNN) machine learning architectures which can be trained on the same hydrodynamic simulation output. These are included as a reference point to compare the ViT models to. Additionally, the library includes trained ViT and CNN models and example input data for demonstration purposes. The code is based on the PyTorch python library.", + "laborHours": 2006.4, + "languages": [], + "name": "Hyperparameter Studies for Vision Transformers Trained on High-Fidelity Simulations", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/CNN-T2TViT-comparison", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This code compares the runtimes between the Dirichlet Dempster-Shafer Model (DSM) against the competition method, the Simplex DSM. Besides the code used to implement the Dirichlet DSM, all code to be released implements existing methods that are not novel algorithms nor any major innovations to existing software.", + "laborHours": 547.2, + "languages": [], + "name": "Code for Experiment in Publication “A New Method for Multinomial Inference using Dempster-Shafer Theory”", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/dempster-shafer-multinomial", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "Software for performing calculations of physical systems, both equilibrium and dynamical, using convex constraints.", + "laborHours": 425.6, + "languages": [], + "name": "Convex methods for physics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/concave", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "PLEIADES: Python Libraries Extensions for Isotopic Analysis via Detailed Extraction of SAMMY. \n\nThis is a Python package that configures and executes the code SAMMY, which is an open sourced R-Matrix fitting code from ORNL. Additionally, PLEIADES includes python packages to analyze SAMMY results and process them into isotopic images.", + "laborHours": 1504.8, + "languages": [], + "name": "LANL contributions to PLEIADES", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PLEIADES", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This framework aids in Transcription factor binding site prediction given DNA sequence information and DNA biophysical characteristics computed by pyDNA-EPBD. This framework utilizes a large language model for binding site prediction.", + "laborHours": 10564.0, + "languages": [], + "name": "EPBD-BERT", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EPBD-BERT", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "DISSIDE uses novel unsupervised learning to select samples that best represent the strongest a\npriori discrete pattern in a given data set. It further removes major outliers and \"noisy\" samples\nthat do not fit discrete patterns well or represent outliers in groups below a defined n value. It\nthen estimates the fit and strength of the a priori discrete pattern using both unconstrained and\nconstrained methods for raw and cleaned data", + "laborHours": 744.8, + "languages": [], + "name": "DISSIDE: Dynamic In Silico Sample Identification for Discrete Evaluation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lebrun-LANL/DISSIDE-Dynamic-In-Silico-Sample-Identification-for-Discrete-Evaluation", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "pySimFrac is a python library for generating 3D synthetic fracture realizations, integrating with fluid simulators, and performing analysis.", + "laborHours": 1398.4, + "languages": [], + "name": "pySimFrac", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pySimFrac", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "We would like to create an open source repository in LANL's github on code written in Julia, in which we implement and extend the data-driven Mori-Zwanzig method for extracting large-scale spatio-temporal structures from data, which we call MZMD. This method is an extension of Dynamic Mode Decomposition (DMD) in which Mori-Zwanzig memory kernels are included into the associated companion matrix. In the code we would like to release, we apply MZMD to a flow over a cylinder with Reynolds number 100 rather than the much larger data set used in the associated manuscript. DMD is used extensively in the fluid dynamics community mainly for extracting large scale spatio-temporal structures (patters) from flow data. This is useful for understanding the key mechanisms that generate certain complex dynamical process relevant in engineering design. In MZMD, we improve upon DMD by adding the Mori-Zwanzig memory kernels, and show this improvement is especially important in strongly nonlinear regions of the flow.", + "laborHours": 304.0, + "languages": [], + "name": "Code for the manuscript \"Mori-Zwanzig Modal Decomposition\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MoriZwanzigModalDecomposition.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This Fortran code consists of multiple modules with a focus on simplifying array operations, image processing, and numerical computation especially for computational geophysics applications. We intend to use this code to demonstrate the application and usefulness of Fortran interface and templates for generic programming, especially for computational geophysics and seismology applications. The code has several notable features. Firstly, it is based on a modularized structure, where each module contains multiple functions but with a focus of functionality. Secondly, it heavily uses interfaces and templates for improving the genericness and convenience of the resulting code, where a same function interface can enclose a group of functions that perform the same functionality but with inputs/output variables of different data types. Thirdly, it includes a variety of generic functions with an emphasis on array operations, such as rotation, flipping, cropping, padding, fast Fourier transform, Gaussian blurring, interpolation, and so on. We name this package FLIP – a generic Fortran Library based on Interfaces and Templates.", + "laborHours": 33105.6, + "languages": [], + "name": "FLIT: A Generic Fortran Library based on Interfaces and Templates", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/flit", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "weberb@ornl.gov" + }, + "date": { + "created": "2024-07-15", + "metadataLastUpdated": "2024-07-15" + }, + "description": "Cyberwheel is a high fidelity training environment for autonomous cyber defense agents that includes both simulation and emulation capabilities. Cyberwheel simplifies customization of the training network and easily allows redefining the agent’s reward function, observation space, and action space to support rapid experimentation of novel approaches to agent design. It also provides visibility into agent behaviors necessary for agent evaluation and sufficient documentation and examples to lower the barrier to entry.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Cyberwheel", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl/cyberwheel", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-07-15", + "metadataLastUpdated": "2024-08-26" + }, + "description": "A 3D microstructure resolving electrochemical transport and interfacial chemistry solver. \n\nElectrode microstructure plays an important role in determining the performance of an electrochemical system, e.g. lithium ion battery. EchemAMR is a microstructure scale model that solves the governing equations for ion transport, electrical current continuity, interfacial chemistry and structural mechanics. Complex microstructure geometries from imaging can be directly imported into EchemAMR. A volume fraction based description of the geometry on Cartesian grid with an immersed interface formulation enables simplified meshing and large-scale simulations with millions of degrees of freedom. EchemAMR has been tested against systems with analytic solutions for numerical convergence and highly resolved lithium ion battery microstructures. EchemAMR demonstrates excellent mass conversation and efficient scaling on heterogenous High-Performance Computing (HPC) with central and graphics processing units.", + "laborHours": 8253.6, + "languages": [ + "C++", + "HTML", + "C", + "Jupyter Notebook", + "MATLAB", + "Python" + ], + "name": "EchemAMR (electro-chemical microsctructure scale models with adaptive meshing) [SWR-23-111]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/echemAMR", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "LowFive is a new data transport layer based on the HDF5 data model, for in situ workflows. Executables using LowFive can communicate in situ (using in-memory data and MPI message passing), reading and writing traditional HDF5 files to physical storage, and combining the two modes. Minimal and often no source-code modification is needed for programs that already use HDF5. LowFive maintains deep copies or shallow references of datasets, configurable by the user. More than one task can produce (write) data, and more than one task can consume (read) data, accommodating fan-in and fan-out in the workflow task graph. LowFive supports data redistribution from n producer processes to m consumer processes.", + "laborHours": 212161.6, + "languages": [], + "name": "LowFive v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/diatomic/LowFive", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The event fanout-receiver is an event-based timing system implementation capable of synchronizing (with respect to clock, events and triggers) to an upstream event generator. This can be used in 2 modes: fanout or receiver. the first one receives 1 upstream timing streams and fanouts it to 36. The second one receives and decodes the stream. This has been in use by ALS for many years and this is a similar implementation, but providing a more flexible configuration", + "laborHours": 8618.4, + "languages": [], + "name": "Event Fanout/Receiver (evfr) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/LBNL-EVFR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The IMG Annotation Pipeline is a collection of Bash and Python scripts to control a workflow for structural and functional annotation of prokaryotic genomes, metagenomes, and metatranscriptomes. The bash scripts in general control the overall workflow and are wrappers around 3rd party executables (not included in repo) that predict features or functions. Whereas the Python scripts do post-processing of raw output in terms of filtering or format transformation and in some cases contain some logic for picking the correct predictions or resolving overlaps. The pipeline is tailored to produce results required by IMG (https://img.jgi.doe.gov/) and is executed on every dataset submitted to IMG via https://img.jgi.doe.gov/submit. These consist of internal genomes, metagenomes and metatranscriptomes sequenced and assembled at the JGI, as well as datasets submitted by external users (non-lab/JGI affiliates).", + "laborHours": 3556.8, + "languages": [], + "name": "IMG Annotation Pipeline (IMGAP) v5.1.13", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/img/img-pipelines/img-annotation-pipeline", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "This software helps the user mathematically determine the losses in a boost converter they are designing. They can enter the component parasitic values from their component datasheets, and the software will calculate exactly where the losses are coming from. This can help the designer target and reduce specific sources of loss. It also helps system engineers compare the losses between AC and DC versions of the boost converter. Finally, it establishes a set of mathematical equations to help academics study loss theoretically.", + "laborHours": 562.4, + "languages": [], + "name": "Boost Converter Loss Analysis v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dgerb/Boost-Converter-Loss-Analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "We created a cloud-based application for running AlphaFold2 and related structural programs called Foldy. Foldy is built on Helm / Kubernetes, which enables a facile production deployment and a scalable backend. Once set up by an institution, Foldy requires no software expertise from its users. It can be used to predict the structure of large proteins (up to 3000 amino acids), to visualize Pfam and antiSMASH annotations, and to perform ligand docking with Autodock Vina.", + "laborHours": 32224.0, + "languages": [], + "name": "Foldy v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/foldy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "nexport is a lightweight python 3 package which enables neural network developers to export the weights and biases of trained networks to useful file types. It provides I/O support for applications which require specific data types for instantiating neural networks in various inference environments. It was initially developed to support exporting to the data structure used by 'inference-engine', a Fortran inference package.", + "laborHours": 471.2, + "languages": [], + "name": "Neural Network Export Package (nexport) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/nexport", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Lasy is a Python library that facilitates numerical simulations of the interaction of complex laser pulses with plasmas.\n\nMore specifically, lasy offers many ways to define complex laser pulses (e.g. from commonly-known analytical formulas, from experimental measurements, etc.) and then computes and saves the corresponding laser field in a standardized file. This file can then be read by external plasma simulation codes, that will then simulate the interaction between the complex laser pulse and a plasma.\n\nLasy is useful for instance for numerical simulations of plasma-based particle accelerators, plasma-based laser amplification, etc. Lasy avoids having to duplicate the code that defines complex laser pulses in each plasma simulation codes, and instead provides a trusted, centralized implementation.", + "laborHours": 1763.2, + "languages": [], + "name": "lasy v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LASY-org/lasy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "This algorithm will identify the genesis and track the lifecycle of atmospheric rivers. It can be applied in different global atmospheric river detection algorithms. It is one of the earliest atmospheric river lifecycle tracking algorithms.", + "laborHours": 60.8, + "languages": [], + "name": "Depth-First Atmospheric River lifecycle Tracking (DART) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-EESA/DART", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Jupyter notebooks to reconstruct and visualize microCT data from ALS beamline 8.3.2. Relies on standard tomography and image processing tools (astra, tomopy, itk, scikit-image) and ipywidgets (sliders, drop down menus, etc) to make parameter selection and data visualization easy for users.", + "laborHours": 1854.4, + "languages": [], + "name": "als microct recon (microct) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/als-computing/microct", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Tsuchinoko is a Qt application for adaptive experiment execution and tuning. Live visualizations show details of measurements, and provide feedback on the adaptive engine's decision-making process. The parameters of the adaptive engine can also be tuned live to explore and optimize the search procedure.\n\nWhile Tsuchinoko is designed to allow custom adaptive engines to drive experiments, the gpCAM engine is a featured inclusion. This tool is based on a flexible and powerful Gaussian process regression at the core.\n\nA Tsuchinoko system includes 4 distinct components: the GUI client, an adaptive engine, and execution engine, and a core service. These components are separable to allow flexibility with a variety of distributed designs.", + "laborHours": 3967.2, + "languages": [], + "name": "Tsuchinoko v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/tsuchinoko", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-11-06" + }, + "description": "This software is a pipeline used to identify the distribution of user-specified sequences in oligo pools that have been sequenced on the MiSeq platform for quality control purposes. The software counts instances of user-specified sequences (inserts or spacers) identified in sequencing data, returning the distribution of sequences in each pool and the length distribution of all the sequences. Among other types similar types of projects, this can be used to assess the quality of a guideRNA library once it has been inserted into the vector of choice to ensure that there is an even distribution of all the individual protospacers in the pool.\n\nThis pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up.", + "laborHours": 1960.8, + "languages": [], + "name": "SynBio QC-Library QC (LibQC) v2.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.jgi.doe.gov/jgi-synbio-public/synbioqc-libqc/-/blob/main/LICENSE?ref_type=heads", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/jgi-synbio-public/synbioqc-libqc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-09-30" + }, + "description": "This software library serves as a Python wrapper for Geotab's Altitude API. It streamlines querying of the API, converts loosely structured API outputs into a standardized tabular data format, and enables analysis of the resulting data tables. It also includes example notebooks showing how to use the library.", + "laborHours": 668.8, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "Python wrapper library and analysis functions for Geotab Altitude API [SWR-24-77]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Geotab_Altitude_Wrapper", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "We have developed some scripts and tools that compliment an existing open-source product (Podman, https://podman.io/). This enables podman to function as a high-performance container solution. This capability is similar to Shifter and Singularity (both developed at LBNL). The advantage of leveraging Podman is it has greater support in the broader community outside of HPC and has capabilities missing from many of the HPC-only solutions.\n\nThe specific enhancements we wish to share our how to enable Podman to scale to very large HPC jobs and our integrations we have done to utilize high-performance interconnects and GPUs.", + "laborHours": 1140.0, + "languages": [], + "name": "Podman-hpc v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/podman-hpc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The ESnet SmartNIC is a collection of Verilog based FPGA design software, as well as drivers to interact with the FPGA. It provides an infrastructure framework for FPGA based hardware acceleration of network packet use cases. Different research and production applications can be easily written for the SmartNIC. Its advantage is that it reduces the development time for new applications by providing a pre-existing shell library for common functions.", + "laborHours": 15838.4, + "languages": [], + "name": "ESnet SmartNIC v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/esnet-smartnic-hw", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Build Optimization Software Tools (BOOST) accelerate the design of DNA, RNA and protein sequences for their synthesis and assembly in an automated and scalable fashion.\n\nThe BOOST Juggler automates the following two design tasks:\n- Reverse-Translation of protein sequences into DNA sequences\n- Codon Juggling of DNA sequences\n\nThe BOOST Polisher provides the following design tasks:\n- The Verification of DNA sequences against DNA synthesis constraints\n- The Modification of DNA sequences in case they violate any DNA synthesis constraint\nIn addition, the BOOST Polisher can be instructed to verify and modify DNA sequences against sequence patterns, such as restriction sites.\n\nThe BOOST Partitioner supports both Gibson/chewback and Yeast assembly (also known as Transformation-Associated Recombination, or TAR) methods when performing the decomposition of large sequences that exceed the maximum length of DNA synthesis into synthesizable building blocks. The Partitioner can be instructed to find building blocks with appropriate overlap sequences, making their assembly into the complete construct more efficient.\n\nBOOST Workflows enable, in a customized fashion, the execution of the Juggler, Polisher, and Partitioner tools on a batch of sequences.", + "homepageURL": "https://marketplace.lbl.gov/biosciences/computational-biology/BOOST", + "laborHours": 0.0, + "languages": [], + "name": "Build Optimization Software Tools (BOOST) v2.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/license-agreements-marketplace-licenses", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://marketplace.lbl.gov/biosciences/computational-biology/BOOST", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The program is expected to be a useful tool during operation of a range of solar-driven electrochemical devices, such as PV-electrolyzers and photoelectrochemical (PEC) devices. It makes use of current-voltage data collected during operation, operation parameters that are easily accessible for many devices of interest. The program captures the time-dependence of loss mechanisms at play during PEC device operation and opens the door for real-time optimizations of operational parameters like the feed humidity to minimize performance losses. Currently, the program is useful for applications where the current-voltage polarization response of the photoabsorber and electrolyzer are pre-recorded, and changes over time can be estimated based on the pre-recorded current-voltage scans. More complicated scenarios that involve permanent degradation of the PV component or complex calculations of the electrolyzer current-voltage characteristics may be included in future versions of this software. Aside from the possibility of deconvoluting loss mechanisms, this software can also reveal possible performance benefits by convective PV cooling when the photoabsorber is integrated into the electrolysis cell. The latter can highlight why certain device architectures may be beneficial over others. No similar technologies are known to the developer.", + "laborHours": 927.2, + "languages": [], + "name": "Current-Voltage Analysis Tool for Solar Fuel Production (CATS) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MEG-LBNL/Current-Voltage-Analysis-Tool-for-Solar-Fuel-Production-CATS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "With the falling costs of solar arrays and battery storage and reduced reliability of the grid due to natural disasters, small-scale local generation and storage resources are beginning to proliferate. However, very few software options exist for integrated control of building loads, batteries and other distributed energy resources. The available software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice, and are often incapable of operating independently of the grid during blackouts. In this software package, we present the \"Solar+ Optimizer\" (SPO), a control platform that provides demand flexibility, resiliency and reduced utility bills, built using open-source software. SPO employs Model Predictive Control (MPC) to produce real time optimal control strategies for the building loads and the distributed energy resources on site. SPO is designed to be vendor-agnostic, protocol-independent and resilient to loss of wide-area network connectivity. The software was evaluated in a real convenience store in northern California with on-site solar generation, battery storage and control of HVAC and commercial refrigeration loads. Preliminary tests showed price responsiveness of the building and cost savings of more than 10% in energy costs alone.", + "laborHours": 20200.8, + "languages": [], + "name": "SolarPlus-Optimizer v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/SolarPlus-Optimizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-18" + }, + "description": "Drishti is a command-line tool to guide end-users in optimizing I/O in their applications by detecting typical I/O performance pitfalls and providing a set of recommendations.", + "laborHours": 1170.4, + "languages": [], + "name": "Drishti v0.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/drishti", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-18" + }, + "description": "Markov chain Monte Carlo sampler useful for a variety of problems for optimization, numerical integration, and generating draws from a probability distribution. They are often used in physical and mathematical problems, especially when it is difficult or impossible to use other approaches.\n\nThis disclosure is for new bug fixes and enhancements to an existing open source library that is already in the public domain under the MIT license.\nhttps://github.com/jellis18/PTMCMCSampler", + "laborHours": 1246.4, + "languages": [], + "name": "Bug fixes / enhancements to Parallel tempering Markov chain Monte Carlo sampler (PTMCMCSampler) v3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nanograv/PTMCMCSampler", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-17" + }, + "description": "The program extends the analysis capabilities of existing profilers through additional analysis to provide insights about communication computation overlap, communication modeling, and broad performance summaries of CPU, GPU and memory. This allows users to understand how their applications are spending time and where performance bottlenecks are.", + "laborHours": 410.4, + "languages": [], + "name": "NEthing v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/nething", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-17" + }, + "description": "This is a security automation tool heavily influenced by the tool written at NCSA https://github.com/ncsa/bhr-site.\n\nThe tool is a web interface that aims to centralize information on blocking malicious traffic. There is a list of currently blocked traffic, a place for other tools to automatically add traffic they deem malicious, as well as for human users to input blocks.\n\n* Logging and auditing, to determine who made what change and when\n* Automated expiration of changes (e.g. an exception is added for 2 weeks, after which time it will be removed)\n* Validation of changes and verification that the change has been applied\n* Fine-grained role-based access", + "laborHours": 2888.0, + "languages": [], + "name": "Security Catch and Release Automation Manager (SCRAM) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet-security/scram", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-17" + }, + "description": "This is an announcement service for JupyterHub that JupyterHub admins can manage through a JupyterHub-styled UI. JupyterHub administrators can use it to communicate with their hub's users about status, upcoming outages, or share news. It allows admins to post a current announcement, and show previous announcements in reverse chronological order. It provides a REST API hook that admins can use to post the latest announcement on JupyterHub itself (with custom templates).", + "laborHours": 440.8, + "languages": [], + "name": "jupyterhub-announcement v0.8", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rcthomas/jupyterhub-announcement", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-17" + }, + "description": "This repository will host the software, data models and documentation developed as part of the California Energy Commission (CEC) funded California Load Flexibility Research and Development Hub (CalFlexHub) project. The main objectives of CalFlexHub are:\n- Identify, develop, evaluate, demonstrate and deploy cost-effective, scalable, building load-flexible (LF) technologies that are consistent with building energy efficiency, appliance, and load management standards.\n- Create a portfolio of LF RDD&D technology projects across various building types and sizes including single-family-residential, multi-family, commercial buildings and integrated campuses.\n- Deploy LF technologies to demonstrate the ability for 99% of the state's customers to receive the load management standards price and marginal GHG signals.", + "laborHours": 60.8, + "languages": [], + "name": "California Load Flexibility Research and Development Hub (CalFlexhub) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/CalFlexHub", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-07-18", + "metadataLastUpdated": "2024-07-18" + }, + "description": "The software contains\n(a) the source codes to generate Point-on-Wave (PoW) transient data for any feeder model in Alternative Transient Program\n(ATP) format. Codes provide options to change different steady state settings, including the loading condition and PV\ncapacity and transient state setting like faults type, location and initiation time\n(b) data post-processing source code to converted data from native format to COMTRADE, csv, HDF5\n(c) Docker container to train CNN to classify fault locations by protective zone. The container takes dataset and other\ntraining parameters (sampling rate, training epochs, batch size etc) as input to train CNN. The container writes back the\ntrained CNN model, training and testing metrics and plots to the local workstation", + "laborHours": 501.6, + "languages": [], + "name": "Data-Driven Protection Software to classify fault locations by protective zone in distribution systems with high PV penetration", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/oedisi_transients", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-18", + "metadataLastUpdated": "2024-07-18" + }, + "description": "Despite advances in microscopy, imaging techniques only capture a very small spatial and temporal fraction of T cell activity within a tissue. For this reason, we have pursued the development of a virtual T cell model. Matcha's objective is to design virtual T cells that move like biological T cells. The virtual T cells will match the speed and turning angle distributions of biological cells. In addition, Matcha will also attempt to match the volume patrolled by the biological cells and the dependence on speed and turning angle on the previous speed.", + "laborHours": 790.4, + "languages": [], + "name": "Motility Analysis of T-Cell Histories in Activation (Matcha) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/matcha", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-18", + "metadataLastUpdated": "2024-07-18" + }, + "description": "As demand flexibility becomes more common, the mix and frequency of a range of demand flexibility strategies will introduce potential biases into baselines, i.e., the time period immediately prior to a LS event may include other LS or DF events. Baseline degradation assessment provides an approach to quantify how these biases begin to compromise predictive accuracy. Heatmaps, based on each month of the year provides a granular view of a given model's predictive capability. However, for comparing multiple algorithms, separately for weekdays and weekends, aggregating results to seasons provides a simpler means of comparison while still allowing for review of variations by time of day and time of year", + "laborHours": 1398.4, + "languages": [], + "name": "Grid Services Load Shift Baseline Degradation Analysis Methodology v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sgfernandes/Loadshift", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-07-22", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The DeepLynx Airflow Provider Package is a python package used to interact with the data warehouse DeepLynx when using the workflow orchestration tool Apache Airflow. This python package is packaged together using the airflow package standard so that it can be easily installed and used in any Apache Airflow environment. This package is meant to encapsulate the DeepLynx API for use in Airflow so that any interactions with DeepLynx that a user may want to use in their Airflow workflow can be easily accomplished using this provider package. This allows us to develop, implement, and test our DeepLynx-Airflow interactions in one provider package repository, and then easily install and use this package in any airflow instance. This DeepLynx Airflow Provider Package will be used extensively by the DeepLynx DAG repository.", + "laborHours": 1079.2, + "languages": [ + "Python" + ], + "name": "Deeplynx Airflow Provider Package", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/airflow-provider-deeplynx", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-07-23", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Code allows users to easily pull publications from PubMed, OSTI, and SCOPUS; identify biological terms and extract\ntheir contexts from these papers; and determine which terms are related to other terms using one of the eleven wrapped\nalgorithms", + "laborHours": 501.6, + "languages": [], + "name": "Natural Language Processing for Biological Relationship Extraction", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/biological_relationship_extraction", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-23", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This is a repository for scripts and documents to help reproduce the results in \"A Global Phylogenomic Analysis of the Shiitake Genus Lentinula\".", + "laborHours": 516.8, + "languages": [], + "name": "Scripts for \"A Global Phylogenomic Analysis of the Shiitake Genus Lentinula\" v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/jgi-lentinula/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-23", + "metadataLastUpdated": "2024-07-26" + }, + "description": "iPHoP is a bioinformatic tools that uses a set of approaches to predict the potential host of novel bacteriophages (viruses infecting bacteria) that are only known by their genome sequence, and not cultivated in the laboratory. Existing technologies typically rely on a single method, and the main advantage of iPHoP is its ability to integrate the results from multiple methods into a single prediction. This is of interest for microbial ecology researchers, as they often analyze novel bacteriophage genomes that they were able to assemble from metagenomes, but they don't know which bacteria these phages infect.", + "laborHours": 3116.0, + "languages": [], + "name": "Integrated Phage-Host Prediction tool (iPHoP) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/srouxjgi/iphop", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-23", + "metadataLastUpdated": "2024-07-23" + }, + "description": "BioParts is a web based search portal for biological parts available in the public domain. It combines the ease and convenience of modern web search engines with the capabilities of bioinformatics search tools such as BLAST. This portal, available at bioparts.org, allows anyone to search for publicly accessible biological part information (e.g., NCBI, iGEM, SynBioHub, Addgene), including parts publicly accessible through ICE Registries. Additionally, the portal offers a REST API that enables third-party applications and tools to access the portal's functionality programmatically. While there are several standalone biological part repositories, there doesn't exist an application that indexes these publicly available parts and enables features such as keyword and BLAST searches along with automatic sequence annotation.", + "laborHours": 27694.4, + "languages": [], + "name": "Biological Parts Search Portal (BioParts) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/BioParts", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-24", + "metadataLastUpdated": "2024-07-24" + }, + "description": "This software library presents efficient and multithreaded implementations of matrix low rank approximation via column selection in C++17 code. The algorithms are described in Fornace, Mark, and Michael Lindsey. \"Column and row subset selection using nuclear scores: algorithms and theory for Nystro m approximation, CUR decomposition, and graph Laplacian reduction.\" arXiv preprint arXiv:2407.01698 (2024). The presented methods are by-and-large ver novel, have provable approximation guarantees, multiple use-cases, and exhibit higher quality approximations on a variety of studied examples.", + "laborHours": 927.2, + "languages": [], + "name": "nuclear-score-maximization v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfornace/nuclear-score-maximization", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-24", + "metadataLastUpdated": "2024-07-31" + }, + "description": "The software has two main features: (1) identify data movement trends in HPC data centers that use network flow monitoring (2) analyze the performance of individual data flows under the existing data movement management strategy and identify performance bottlenecks that impede timely data availability for science workflows. Its main advantage is that it is tailored for HPC network traffic by considering HPC data movement management intricacies.", + "laborHours": 349.6, + "languages": [], + "name": "Network performance analysis for HPC datacenters (net_perf) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/annna-gian/nersc_net_perf.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-07-26", + "metadataLastUpdated": "2024-07-26" + }, + "description": "system2atoms is a suite of models that can simulate the performance of hydrogen\ninfrastructure across multiple scales. Examples of the different scale levels include:\n1. System Scale - techno-economic analysis for hydrogen applications,\nintegration of hydrogen infrastructure with the electrical grid,\nand supply and demand constraints across applications\n2. Component Scale - continuous-flow catalyst beds, electrochemical conversion\nunits, gas-phase separators, pumps, compressors, storage tanks, evaporators,\nheaters, and coolers\n3. Material Scale - surface reactions, degradation mechanisms, and catalyst\npoisoning", + "laborHours": 20079.2, + "languages": [], + "name": "system2atoms", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/systems2atoms", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-27", + "metadataLastUpdated": "2024-07-27" + }, + "description": "SAND2021-14236 O\nPMatch is a function matching plugin for Ghidra. PMatch uses hashing and p-code to create function databases and complete function matching on other binary files. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 349.6, + "languages": [ + "Python" + ], + "name": "PMatch v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/halucinator_PMatch", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-27", + "metadataLastUpdated": "2024-07-27" + }, + "description": "SAND2022-4247 O\nLocOO3d is used to estimate the location of seismic events by comparing estimates of the arrival time for seismic waves from hypothesized locations to observed arrival times. LocOO3d also computes errors in estimated locations through the computation of an “error ellipsoid” around the optimal event location.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 291095.2, + "languages": [], + "name": "LocOO3d v.1.1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Salsa3DSoftware", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-27", + "metadataLastUpdated": "2024-07-27" + }, + "description": "SAND2022-4256 O\nOnline version control platforms offer insight into traffic and engagement with source code repositories, but only in limited ways and over short windows of time. Scientific software teams at Sandia National Laboratories and elsewhere want to collect and store engagement data to help tell their story and the impact their work has on the community. Repometer aims to supplement existing capabilities by collecting timely and insightful data from GitHub and GitLab repositories and passing it to a database for longer-term storage.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1793.6, + "languages": [ + "Python" + ], + "name": "Repometer v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Repometer", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-27", + "metadataLastUpdated": "2024-09-12" + }, + "description": "SAND2022-13232 O\nThe sbovqaopt package provides a surrogate-based optimizer for variational quantum algorithms as introduced in the journal publication of the same title. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "sbovqaopt: Surrogate-based optimizer for variational quantum algorithms v.0.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sbovqaopt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-07-29", + "metadataLastUpdated": "2024-07-29" + }, + "description": "Lack of harmonic rich datasets limits the ability to have fine grained load models at grid edge. We aim to develop\nmathematical models for power electronic based load combinations at grid edge to help replicate current and future\nevolving load conditions", + "laborHours": 30.4, + "languages": [], + "name": "Continual Load Modelling", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Continual-Load-Modelling-HELM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "klaskyhb@ornl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "The program summarizer.py is the product of the 'Automating Data Collection with Large Language Models (LLMs): Summarization and CSV Generation' project. This project aims to automate data collection from Internet content using LLMs. This project integrates zero-shot learning concepts, as the agents were not previously trained on the particular subjects of the inputted sources, and Retrieval Augmented Generation (RAG).\nThis summarizer program summarizes characteristics of the URL sources which are specified by the user. As written, the program identifies six characteristics of the inputs: source_name, source_creator, source_url, source_overview, source_data, and number_of_datapoints. However, this program is designed to be highly generalizable, so throughout the code, docstrings specify what parameters and variables should be changed for the user to utilize this program on their own inputs and characteristics. This repository contains example outputs for two datasets: one on the health effects of air pollutions and one on congenital heart defects.", + "laborHours": 258.4, + "languages": [ + "Python" + ], + "name": "Automating Data Collection with Large Language Models: Summarization and CSV Generation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/summer_2024/summarization", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "Summer 2024" + }, + { + "contact": { + "email": "klaskyhb@ornl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "Given the text files of LLM outputs for specific variables about numerous databases and the reference Excel sheets to compare the LLM outputs to, this program will generate Excel sheets and CSV files of evaluations to describe the LLMs' performances. When the program is executed, these files can be located in ./evals. All folders within ./evals are named by the time which the program finished.\nThe main focus of this pipeline is to evaluate the database descriptions using BERTScore, SacreBLEU, and MoverScore. However, multiple different types of metadata aside from descriptions.", + "laborHours": 410.4, + "languages": [ + "Python" + ], + "name": "Large Language Model Output Evaluator", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/summer_2024/llm_output_evaluation", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "Summer 2024" + }, + { + "contact": { + "email": "klaskyhb@ornl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "This project evaluates a set of prompts to test their performance on specific tasks for large language models (LLMs), in order to find the optimal prompt to enhance task performance.", + "laborHours": 1018.4, + "languages": [ + "Python" + ], + "name": "Complete Prompt Permutation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/summer_2024/prompt_engineering/complete-prompt-permutation", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "Summer 2024" + }, + { + "contact": { + "email": "klaskyhb@ornl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "This project evaluates a set of prompts to test their performance on specific summarization tasks for large language models (LLMs), in order to find the optimal prompt to enhance task performance. This is a slightly more generalized version of the complete-prompt-permutation project, with different strengths.", + "laborHours": 304.0, + "languages": [ + "Python" + ], + "name": "Template Prompt Permutation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/summer_2024/prompt_engineering/template-prompt-permutation", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "Summer 2024" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "This is a C ++ acquisition API for neurophysiological data in the NeurodataWithoutBorders (NWB) data standard.", + "laborHours": 1869.6, + "languages": [], + "name": "AqNWB v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NeurodataWithoutBorders/aqnwb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "Code to organize, prepare, and segment multi-scan, larger-than-memory, volumetric dataset. Deep learning segmentation uses pytorch-lightning for code organization, logging and metrics, and multi-GPU parallelization of training and prediction. Also uses moani for volumetric data augmentation and model implementation (currently U-Net++). Training can be done slice-by-slice with 2D models trained on 2D patches either aligned with or perpendicular to the electrode plane, or with 3D models on 3D patches. Sparse labels can be used to minimize required hand-labeling -- less than 0.1% of the entire dataset was labeled. Also includes code for data preparation (alignment/cropping/patching).", + "laborHours": 714.4, + "languages": [], + "name": "batteryNET v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/batteryNET", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-31", + "metadataLastUpdated": "2024-07-31" + }, + "description": "SAND2024-08428O\nThe IDB Loader is a database designed to hold gamma spectra. IDB is a web-accessible database of reference gamma spectra for measuring uranium (U) and plutonium (Pu) isotopic composition. The database, developed by the International Atomic Energy Agency (IAEA), provides access to well-characterized groups of gamma spectra curated by international experts in gamma spectroscopy. It was created to promote sustainability and maintenance of software used to determine the isotopic abundances of U and Pu. The IDB Loader works by uploading one set of spectral data into an existing IDB. The Data Loader package includes documentation describing the IDB's table, the format of the spectral data, and a description of the loader program. The IDB is currently hosted by the IAEA at: https://nds.iaea.org/idb \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 4104.0, + "languages": [ + "Java" + ], + "name": "IDB Loader", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IDB_Loader", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-08-01", + "metadataLastUpdated": "2024-09-12" + }, + "description": "Publicly available collections of drug-like molecules have grown to comprise tens of billions of compounds\ndue to advances in combinatorial chemistry. Traditional methods for identifying \"hit\" molecules from a\nlarge collection of potential drug-like candidates have relied on biophysical theory to compute\napproximations to the Gibbs free energy of the binding interaction between the drug and its protein target.\nThese approaches have the major drawback that they require exceptional computing capabilities for\neven relatively small collections of molecules.\nHyperdimensional Computing (HDC) is a recently-proposed learning paradigm that represents data with\nhigh-dimension binary vectors; this allows the use of low-precision binary vector arithmetic to create\nmodels of the data that can be learned without the need for the gradient-based optimization required in\nmany conventional machine learning and deep learning methods. This algorithmic simplicity allows for\nacceleration in hardware that has been previously demonstrated in a range of application areas. We\nconsider existing HDC approaches for molecular property classification and introduce two novel\nencodings of a commonly-used molecular representation, the extended connectivity fingerprint (ECFP).\nWe show that HDC-based inference methods are as much as 91 times more efficient than traditional\nmachine learning methods, and achieve an acceleration of nearly nine orders of magnitude compared to\nmolecular docking. Our results show that HDC accelerated methods retain competitive accuracy on a\nnumber of well-studied tasks such as molecular property predictions using the MoleculeNet dataset, and\nbind/no-bind activity classification using the DUD-E and LIT-PCBA datasets.\nOur work thus motivates further investigation into molecular representation learning to develop ultraefficient\npre-screening tools.", + "laborHours": 6064.8, + "languages": [], + "name": "HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/hdbind", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-02", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Pore2Chip is a Python module designed to streamline the process of analyzing X-ray computed tomography (XCT) images\nof soil and creating 2D micromodel designs based on that analysis.", + "laborHours": 11962.4, + "languages": [], + "name": "Pore2Chip", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-Computing/Pore2Chip", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-05", + "metadataLastUpdated": "2024-08-05" + }, + "description": "An R package built to match proteoform isotoping distributions to mass spectrum, quantitatively select\nmatches of high quality, and visualize those matches in a trelliscope display.", + "laborHours": 3085.6, + "languages": [], + "name": "IsoMatchMS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-HubMAP-Proteoform-Suite/IsoMatchMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-05", + "metadataLastUpdated": "2024-08-05" + }, + "description": "Benchmark dataset that harmonizes drug\nresponse data across thousands of patient samples and cancer model systems enabling the training and benchmarking of\nAI/ML algorithms at scale.", + "laborHours": 112662.4, + "languages": [], + "name": "CoderData", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/coderdata", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-08-05", + "metadataLastUpdated": "2024-08-05" + }, + "description": "The present work details the creation of a high-fidelity Monte Carlo methodology for analyzing the run-in and subsequent approach to equilibrium for PBRs. The methodology entails a Python module wrapped around Serpent so as to perform neutronics calculations, move pebbles, refuel the core, and discharge pebbles, thereby modeling the explicit behavior of the PBR run-in. The code kugelpy is within the GitHub repository `pyrates`.", + "laborHours": 3116.0, + "languages": [ + "Python" + ], + "name": "Framework For Performing Time-dependent Pebble Bed Reactor Simulations", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/kugelpy", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-08-05", + "metadataLastUpdated": "2024-08-05" + }, + "description": "The code here provides the training/testing of using Fourier Neural Operator for geological carbon storage applications", + "laborHours": 456.0, + "languages": [], + "name": "3D FNO model for geological carbon storage", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qingkaikong/3DFNO_GCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-06", + "metadataLastUpdated": "2024-09-12" + }, + "description": "The Fortran programming language standard defines a broad feature set supporting the interoperability of Fortran programs with program written according to the C programming language standard. Among Fortran's C-interoperability features is a a C header file \"ISO_Fortran_binding.h\" This header file defines the interface to various C data structures and functions that C programs may use to access Fortran data entities. The ISO_Fortran_binding_m software defines a native Fortran module that presents an interface to these same data structures and functions. ISO_Fortran_bind_m thus enables Fortran programs to access and manipulate Fortran entities in ways that precisely mirror what C programs can do using ISO_Fortran_binding.h. ISO_Fortran_binding_m facilitates writing portable standard-conforming Fortran programs that emulate non-interoperable features, e.g., dynamic polymorphism, in a standard-conforming interoperable way similar but broader than what is demonstrated in Berkeley Lab's Caffeine software [1]. ISO_Fortran_binding_m also enables a Fortran programmer to extend Fortran's capabilities to emulate certain C functionality such as memory address arithmetic or computing C's \"sizeof\" function.\n\n[1] https://github.com/BerkeleyLab/caffeine/blob/213e3df1c319f0663306354414f352acda42a24f/src/caffeine/collective_subroutines/co_reduce_s.f90#L88\n[2] https://github.com/BerkeleyLab/ISO_Fortran_binding_m/blob/0c585362bb4f2c72cf9049c800a7115b529ec533/src/iso_fortran_binding_m.F90#L196", + "laborHours": 167.2, + "languages": [], + "name": "ISO_Fortran_binding_m v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/ISO_Fortran_binding_m", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-06", + "metadataLastUpdated": "2024-08-06" + }, + "description": "Julienne is a compiler-portable unit-testing framework for Fortran software projects, including those that use the parallel/accelerator-programming features of Fortran 2023. Julienne achieves portability across compilers through minimalism and isolation. The minimal design ensures that Julienne uses only features supported by the majority of Fortran compilers. The isolation through zero dependencies ensures that no other projects block Julienne from building with a particular compiler.\n\nJulienne also contains with additional services that support its unit-testing code. These include functions for manipulating strings, command lines and input/output format strings; and a user-defined collective subroutine for verifying that all processes pass a test in parallel testing.\n\nJulienne's name derives from the term for vegetables sliced into thin strings: julienne vegetables. Julienne captures the authors' most frequently used thin slice of the Veggies and Sourcery software repositories while avoiding certain compiler limitations of the those two packages.", + "laborHours": 972.8, + "languages": [], + "name": "Julienne v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/julienne", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-06", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The Mbin software, is a software toolkit that implements the IMG metagenome binning pipeline. The software allows the user to process input metagenome contigs, and produces metagenome assembled genomes (metagenome bins) and valuation metrics per bin including completion and contamination estimates, quality assignment, predicted lineage and eukaryotic potential. It is currently packed as a portable docker container and provides the advantage of running the process of binning and analysis of the bins generated, using a suite of tools run sequentially with controls in place to capture errors and optional arguments to run a modified version depending on individual needs and capabilities.", + "laborHours": 0.0, + "languages": [], + "name": "Mbin v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/metagenome-science-program/mbin-docker", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-06", + "metadataLastUpdated": "2024-08-07" + }, + "description": "The levelized cost of avoided CO2 (LCAC) tool facilitates techno-economic calculations for various decarbonization technologies. It comprises two components to accomplish this: an input workbook based on MS Excel and a web-based output tool. The workbook acts as the input sheet, using the user-provided decarbonization measures and their impacts on lifetime energy consumption, energy costs, and CO2 emissions to compute LCAC (expressed in $/metric ton of avoided CO2). The workbook is uploaded to a web-based tool to generate an LCAC curve. This graphical representation illustrates the economic comparison of all decarbonization measures for purposes such as implementation prioritization. We are unaware of any publicly available tools with similar capabilities.", + "laborHours": 881.6, + "languages": [], + "name": "Levelized Cost of Avoided CO2 tool (LCAC tool) v0.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IACDecarb/IAC-Decarb-Tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-06", + "metadataLastUpdated": "2024-08-13" + }, + "description": "Facility CO2 Flow Tool assists facilities and entities to visualize their CO2 flows for accounting and decarbonization purposes. To do so, the suite offers two components – an MS Excel-based input workbook and a web-based visualization tool. The workbook serves as the input sheet, utilizing the user-provided process and equipment-level energy consumption data to calculate the corresponding CO2 emissions. The web-based tool utilizes the data from this workbook to generate a Sankey diagram. This diagram visually represents the CO2 flow originating from the fuel and electricity consumption within the facility/entity boundary.", + "laborHours": 881.6, + "languages": [], + "name": "Facility CO2 Flow Tool (FCFT) v0.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IACDecarb/IAC-Decarb-Tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-08-07", + "metadataLastUpdated": "2024-12-11" + }, + "description": "Via-wind is an open-source tool for conducting visual impact assessments for wind turbines.\n\nIt combines geographic information system (GIS) and 3D simulation methods to account for the key factors driving the visual impact of installed wind turbines, including distance, viewing angle, turbine orientation, visual exposure, and the cumulative effects of multiple turbines.\n\nThis software is optimized for use in high-performance computing environments to enable large scale (e.g., country-wide) analysis, but can also be run on a single server or personal computer.\n\nFor more information, please see the related journal article: https://www.sciencedirect.com/science/article/pii/S0306261924021846", + "laborHours": 1900.0, + "languages": [ + "Python" + ], + "name": "via-wind (A Visual Impact Assessment Tool for Wind Turbines) [SWR-24-87]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/via-wind", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.12" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-08-08", + "metadataLastUpdated": "2024-08-26" + }, + "description": "The Django Query Logger (DQL) is a tool that allows developers of Django web applications to stream the raw database queries that are being executed in real-time from any Django application for review, profiling, filtering, formatting, and analysis.\n\nReference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or Alliance for Sustainable Energy, LLC. The views and opinions of authors expressed in the available or referenced documents do not necessarily state or reflect those of the United States Government or Alliance.", + "laborHours": 562.4, + "languages": [ + "TypeScript", + "SCSS", + "HTML" + ], + "name": "DQL (Django Query Logger) [SWR-24-96]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/django-query-logger", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-08", + "metadataLastUpdated": "2024-09-12" + }, + "description": "LTAU (Loss Trajectory Analysis for Uncertainty) is a technique for estimating the uncertainty in a model's\npredictions for any regression task by approximating the cumulative distribution function (CDF) of the\nmodel's errors over the course of training. The approximated CDF, combined with a similarity search\nalgorithm in the model's descriptor space, can then be used to estimate the likelihood that the model's\npredictions on any given test point will fall below a chosen threshold. LTAU-FF (LTAU in atomistic Force\nFields) is the application of LTAU specifically for use with atomistic force fields.", + "laborHours": 896.8, + "languages": [], + "name": "LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ltau-ff", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-08", + "metadataLastUpdated": "2024-08-08" + }, + "description": "Global Pathway Selection (GPS) is an algorithm to effectively generates reduced (skeletal) chemistry\nmechanisms, which speeds up simulations and can be used as a systematic analytics tool to extract\ninsights from complex reacting system. This release is an extension of the original code to run in parallel\nand to use LLNL's Zero-RK solver for fast solution of chemical problems.", + "laborHours": 10351.2, + "languages": [], + "name": "Global Pathway Selection with Zero-RK", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GPS-Z", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.4" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-08", + "metadataLastUpdated": "2024-09-12" + }, + "description": "QUESTS provides a strategy to quantify the uncertainty and the information content (entropy) of datasets\nof atomistic simulations. The code implements the calculation of a descriptor, compares information\ncontents of datasets, verifies whether given structures are contained in specific datasets, and more. This\ncode base enables better design of training sets for machine learning force fields as well as\nunderstanding some thermodynamic properties of materials.", + "laborHours": 714.4, + "languages": [], + "name": "QUESTS: Quick Uncertainty and Entropy from STructural Similarity", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dskoda/quests", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2025-02-24" + }, + "description": "This algorithm can process small or large (>1000 curves) batches of data and output arrays with the reduction peak start,\nend, halfway point, and area in each curve in a file of the user's choice", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 532.0, + "languages": [], + "name": "Automated Quantification of Cyclic Voltammetry Reactions", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This software contains the code for a machine learning-based pipeline for creating persistent waterbody databases used in hydrologic routing. It consists of three components, 1) a PyTorch library (TorchWBType) for classifying/labeling arbitrary waterbodies into lakes and non-lakes, 2) a batch processing orchestrator (wbextractor) for delineating waterbodies from remote sensing imagery, and 3) graphing/analysis scripts for reproducing the plots in an associated journal article (LA-UR-24-22590).", + "laborHours": 1140.0, + "languages": [], + "name": "High resolution hydrologic routing with machine learning assisted waterbody classification", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VeinsOfTheEarth/waterbody_classification_ms", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "Algorithms for phylogenetic tree inference.", + "laborHours": 456.0, + "languages": [], + "name": "Inferring trees from limited data", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/distphylo", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "The code provides machine learning, data collection, and computer science tools used to detect undocumented orphaned wells in United States from aerial imagery.", + "laborHours": 258.4, + "languages": [], + "name": "UOWDetection", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/uow", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "AdvEP is a code repository which contains PyTorch implementations of various adversarial attacks on a deep neural network trained with Equilibrium Propagation (EP), which is a neuromorphic learning framework. AdvEP allows for the training, testing, and conducting white/black-box attacks of EP models on a wide variety of applications and datasets. AdvEP is based on the open-source code https://github.com/Laborieux-Axel/Equilibrium-Propagation which was developed to train energy models. AdvEP was created by modifying the original code to perform and test against adversarial attacks. AdvEP was developed in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning. AdvEP interfaces heavily with the open-source PyTorch Python package as well as the open-source Adversarial Robustness Toolbox (ART) package.", + "laborHours": 4058.4, + "languages": [], + "name": "AdvEP", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/AdvEP", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "Much strain-specific sequence data exists in research conducted before the deployment of large sequencing repositories, making it challenging to identify and validate the identity of strains used in these studies through bioinformatics and phenotyping. The American Type Culture Collection (ATCC) is an organization that sells a wide variety of microbes with strain-level taxonomy classification and associated sequenced reference genomes. Currently, ATCC does not provide a method for searching for sequence similarity between a query sequence and their database of reference genomes. Here I propose the software ATCCfinder, which utilizes ATCC application interface software (API) to generate query-able databases from ATCC Genome resources.", + "laborHours": 349.6, + "languages": [], + "name": "ATCCfinder - Download and Search the ATCC Genome Portal", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ATCCfinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This software enables the calculation of the pressure field based on experimental velocity measurements utilizing the matrix-based omnidirectional pressure integration algorithm developed by Dr. John Charonko and Dr. Fernando Zigunov, which is several orders of magnitude faster than the current state of the art.", + "laborHours": 2401.6, + "languages": [], + "name": "Matrix-based Omnidirectional Pressure Integratio", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pressure-osmosis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This code is a collection of python code that defines, trains, and tests Log-Additive Convolutional Neural Networks. The model components and training routine are based on the PyTorch python library. The code implements the Log-Additive Convolutional Neural Networks as described in Pagendam et al. 2023. In addition to the Log-Additive Convolutional Neural Networks, this library also defines the Log-Normal Density loss function as described in Pagendam et al. 2023. Code from this paper is not publicly available, so the Pytorch implementation of this type of model is unique to this library.", + "laborHours": 744.8, + "languages": [], + "name": "PyTorch Implementation of Log-Additive Convolutional Neural Networks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pagendam-callis-groundwaterML", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "We plan to release the code used to perform the experiment described in our recent publication, entitled “Determining the dominant factors for carbon-1 mineralization in three-dimensional fracture networks.” This code fits a joint emulator to data from several Discrete Fracture Network (DFN) simulations, performed using the open-source software DFNworks (https://dfnworks.lanl.gov/). All code to be released implements existing methods; there are no novel algorithms nor any major innovations to existing software.", + "laborHours": 4043.2, + "languages": [], + "name": "Code for Experiment in Publication “Determining the dominant factors for carbon-1 mineralization in three-dimensional fracture networks”", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/mineralization_dfnworks", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "The software provides machine learning analysis and visualization to detect patterns in epigenetic data, including conventional machine learning and statistical methods, and open-source packages like pyBigWig (https://github.com/deeptools/pyBigWig) for data processing. The software is written in python, it uses some python libraries.", + "laborHours": 1200.8, + "languages": [], + "name": "Machine learning tools for epigenetics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/epigen", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This Fortran code is to accompany a manuscript to be submitted to Computers & Geosciences, a high-impact, peer-reviewed journal in computer methods for geosciences research. \n\nThis Fortran code focuses on generation of synthetic geological models using a multi-randomization strategy. Generating high-fidelity synthetic geological models, including realistic seismic reflector migration images, faults, salt bodies, and relative geological time images, is the key for many supervised machine learning methods that aim to delineate faults and other geological properties of interest from seismic migration images. Our package contains two major functionalities: generating 2D synthetic random geological models and generating 3D synthetic random geological models. In each step of the generation process, we set random values for key properties of a geological model to improve the fidelity of the resulting geological model. The package also includes example codes on how to use the random geological model generation subroutines. We name this package RGM – Random Geological Model generation package.", + "laborHours": 2280.0, + "languages": [], + "name": "RGM: Random Geological Model Generation Package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/rgm", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This Fortran code focuses on traveltime computation and tomography based on eikonal equation. Specifically, the package provides three major functionalities: (1) forward modeling of traveltime from single-point or ensemble source based on factorized eikonal equation, (2) adjoint-state first-arrival traveltime tomography based on picked first arrival traveltime using steepest descent, conjugate gradient, or limited-memory BFGS inversion scheme, and (3) adjoint-state joint transmission-reflection tomography based on picked first-arrival and reflection traveltimes. The package applies to forward modeling and tomography based on traveltime in 2D and 3D isotropic regular-grid models. We name this package LATTE – Los Alamos TravelTime package based on Eikonal equation. \n\n* The code is for accompanying a journal paper under preparation. The paper will be submitted via LA-UR separately later.", + "laborHours": 7949.6, + "languages": [], + "name": "LATTE: Los Alamos TravelTime package based on Eikonal equation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/latte_traveltime", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This software is being developed to link infectious disease sequence data to epidemiological models to support forecasting efforts for public health impact. More specifically, this software will allow data analysis, feature extraction, data synthesis, inference, and forecasting of sequence data for infectious diseases (e.g., COVID, flu, dengue) and forecasting of public health outcomes (e.g., cases, hospitalizations, deaths).", + "laborHours": 638.4, + "languages": [], + "name": "Program Repository for Tools for Analyzing Infectious Disease Sequence Data and Forecasting Public Health Outcomes", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/precog", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This software is developed for researchers to evaluate the energy performance of of dynamic windows in the world-wide climate, and this first version focuses on thermochromic windows. We bring new indicators (necessity level and recommendation index) to the evaluation system for thermochromic windows. We estimate the majority users of this software tool will be non-commercial academic researchers. But commercial companies can also use it to optimize their products and estimate where their product has the most promising market.", + "laborHours": 258.4, + "languages": [], + "name": "PyDynamicWindow v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/PyDynamicWindow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "myoon@ornl.gov" + }, + "date": { + "created": "2024-08-13", + "metadataLastUpdated": "2024-09-17" + }, + "description": "In the field of first-principles calculations, the creation and modification of input geometry files is a fundamental step. These files are essential for defining the atomic structures used in simulations and come in a variety of formats such as CIF, POSCAR, and XYZ. Traditionally, editing these files for specific requirements has been done manually or through GUI-based tools such as VESTA.\n\nHowever, manual and GUI-based methods fall short in high-throughput scenarios, especially when running on high-performance computing (HPC) systems. There, the need for fast and automated batch processing of geometry files becomes apparent - a need that is not adequately addressed by existing methods.\n\nThe Atomic Simulation Environment (ASE) Python library provides a robust solution with its array of geometry modification functions and support for multiple file types. However, this robustness comes at the cost of complexity: effective use of ASE requires knowledge of Python programming, which can be a hurdle for users who are not well versed in programming.\n\nTo address this gap, we developed a utility that encapsulates the functionality of ASE in a more accessible interface. This tool solves the problem of requiring extensive programming knowledge to manipulate geometry files in high-throughput computations. It provides a command-line solution that allows batch processing without the need for direct code intervention.\n\nIn addition, our tool enhances customization through user-generated plug-in files. This allows for customized modifications that can evolve as users' needs change. By simplifying the process of converting and modifying geometry files, our utility significantly reduces the effort required to prepare simulations for HPC environments.", + "laborHours": 1079.2, + "languages": [], + "name": "CompMatORNL - aseconv", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CompMatORNL/aseconv", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-14", + "metadataLastUpdated": "2024-08-14" + }, + "description": "BiG-SLiCE was originally an open source Python-based command line bioinformatics software that offers a highly scalable clustering analysis on biosynthetic gene clusters (BGC) data. It allows a simultaneous analysis of millions of BGCs, exceeding the capability of other existing tools (around one hundred thousands). As a tradeoff, the clustering accuracy is relatively lower and sometimes fall short in corner cases and specific BGC classes such as the RiPPs (Ribosomally-translated, Post-translationally modified Peptides).\n\nIn BiG-SLiCE V2 (developed in LBNL), the clustering algorithm has been significantly improved to deliver a much accurate result even for RiPPs and other previous corner case classes. Moreover, the speed of the overall pipeline has been improved by 50-100%. Finally, additional features were implemented to support downstream analyses of BiG-SLiCE results, such as customized tabular (TSV/CSV) and columnar (Parquet) outputs.", + "laborHours": 29837.6, + "languages": [], + "name": "BiG-SLiCE 2 v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/SAKautsar/bigslice_v2", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-14", + "metadataLastUpdated": "2024-08-14" + }, + "description": "A library of Axon code and Trio files in active use at LBNL to analyze and display data related to the operation of buildings in the Haxall or SkySpark environment.", + "laborHours": 15.2, + "languages": [], + "name": "Haxall and Haystack Data Analysis for Building Operations (Data Analysis for Operations) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ralphou/data-analysis-operations", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "Psychart is a graphical program developed for NERSC for accurately monitoring air conditions for the air cooled HPC equipment. Psychart will live directly in the OMNI system as a Grafana plugin. It employs the use of Psychrolib and the Grafana Starter Panel to create a front-end program that plots the state of the environmental air on a psychrometric chart. It is highly customizable, allowing the user to modify graph bounds, optionally show ASHRAE data center comfort regions, change the series point color, and more. What sets Psychart apart from other existing psychrometric charts is its ability to plot in real-time. Other psychrometric charts that can be found online require manual input of data and do not seamlessly integrate with Grafana.", + "laborHours": 12676.8, + "languages": [], + "name": "Psychrometric Chart v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nicfv/Psychart", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "GTNet is a neural network capable of identifying the species from which a genomic sequence was derived. Its main use will be in processing metagenomic sequences generated in microbiome research.", + "laborHours": 714.4, + "languages": [], + "name": "The Genome Taxonomy Network (GTNet) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exabiome/gtnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "PPO and Friends (PPOAF) is a pytorch implementation of proximal policy optimization for single- and\nmulti-agent reinforcement learning (the PPO), along with several optimizations and add-ons (the Friends)\nto enable efficient MPI-parallelized model training on HPC clusters.", + "laborHours": 6536.0, + "languages": [], + "name": "PPO And Friends", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ppo_and_friends", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "Kinetics05 uses a variety of linear and nonlinear regression methods, depending on the model to be fitted.\nIsoconversional methods use linear regression, supplemented by empirical correlations between model\nparameters and reaction profile characteristics. Distributed activation energy and nucleation-growth\nmodels use nonlinear regression, with the exception of the discrete distribution model, which uses a\nnested constrained linear-nonlinear regression method.", + "homepageURL": "https://softwarelicensing.llnl.gov/product/kinetics05oss", + "laborHours": 6688.0, + "languages": [], + "name": "Kinetics05_OSS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://softwarelicensing.llnl.gov/product/kinetics05oss", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "0" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "We introduce a new encoder-decoder system that overcomes adaptability and scalability issues. We adapt multiple CNNs as encoders, allowing for the definition of multiple function parameter arguments to structure the models according to the targeted datasets and scientific problem.\n\nWe leverage the flexibility of the U-Net architecture to act as a scalable decoder. The CRF-RNN layer is integrated into the decoder as an optional final layer, keeping the entire system fully compatible with back-propagation.", + "laborHours": 1474.4, + "languages": [], + "name": "U-Net Decoder CRF v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mavaylon1/UNet_Decoder_CRF", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-09-16" + }, + "description": "The software \"BaseBuddy\" (basebuddy.lbl.gov) is a user-friendly web app designed for codon optimization of heterologous genes. Codon optimization is a widely used technique to enhance the expression levels of non-native genes. Our app is built on the DNA Chisel Python library (Zulkower and Rosser, 2020), which offers highly customizable and transparent gene optimization. Unlike DNA Chisel, which is a command-line interface software with numerous optional functions, our web app simplifies the process for users. Additionally, while DNA Chisel relies on the outdated Kazusa codon usage database, our app introduces the option to utilize the most recent version of the CoCoPUTs database (Athey et al., 2017). By incorporating CoCoPUTs, we also expand the range of target organisms and maintain up-to-date sequencing data for more accurate codon optimization results.", + "laborHours": 167.2, + "languages": [], + "name": "BaseBuddy v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jbei/basebuddy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-18", + "metadataLastUpdated": "2024-08-20" + }, + "description": "The repo that provides data archive for DOE PoSeiDon project. It also contains scripts and instructions to parse the data.", + "laborHours": 349.6, + "languages": [], + "name": "FlowBench Raw Data Archive", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/FlowBench-Raw-Workflow-Data", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-18", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Flow-Bench is a benchmark dataset for anomaly detection techniques in computational workflows. Flow-Bench contains workflow execution traces, executed on distributed infrastructure, that include systematically injected anomalies (labeled), and offers both the raw execution logs and a more compact parsed version. In this GitHub repository, apart from the logs and traces, you will find sample code to load and process the parsed data using pytorch, as well as, the code used to parse the raw logs and events.", + "laborHours": 14272.8, + "languages": [], + "name": "Flow-Bench: A Dataset for Computational Workflow Anomaly Detection", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/FlowBench", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Repo for running Large Language Models for Anomaly Detection in Computational Workflows. Include datasets for 1000Genome, Montage, and Predict Future Sales workflows.", + "laborHours": 3617.6, + "languages": [], + "name": "Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context Learning", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/LLM_AD", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-20" + }, + "description": "This repository provides a set of scripts and tools for conducting network research, including performance analysis, buffer status inspection, and RTT probing. It is designed to streamline network data collection and post-processing, primarily leveraging iperf and other network utilities. The primary goal of the RADT dataset is to provide researchers with detailed insights into the interactions between TCP Congestion Control Algorithms (CCAs) and Active Queue Management (AQM) algorithms under different network conditions, enabling the development of more advanced, AI-driven CCAs.", + "laborHours": 1368.0, + "languages": [], + "name": "RADT Scripts for Network Research", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/RADT_scripts_for_network_research", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Clang Unified Parallel C 2 C (Clang UPC2C) translator compiles programs written in the UPC (Unified Parallel C) language to ISO C99, with calls to the Berkeley UPC runtime system. The Clang UPC2C compiler extends the capabilities of the Clang LLVM C frontend to comply with the UPC Language Specification version 1.3. The compiler generates programs that run on a wide variety of systems ranging from workstations to leadership-class supercomputers, in conjunction with the Berkeley UPC runtime and GASNet communication system. In addition to the standard UPC libraries, Clang UPC2C also provides access to Berkeley UPC library extensions.", + "laborHours": 1682077.6, + "languages": [], + "name": "Clang UPC2C Translator (Clang UPC2C) v9.0.1-1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/clangupc/clang-upc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-20" + }, + "description": "Clang Unified Parallel C (Clang UPC) provides a compilation and execution environment for programs written in the UPC (Unified Parallel C) language. The Clang UPC compiler extends the capabilities of the Clang LLVM C compiler to comply with the UPC Language Specification version 1.3. It includes support for UPC collectives and a configurable pointer-to-shared representation. The compiler generates programs that run on a wide variety of systems ranging from workstations to leadership-class supercomputers, in conjunction with the Berkeley UPC runtime and GASNet communication system. This compiler generates assembly code / object code directly for Intel processors and IBM PowerPC.", + "laborHours": 1155.2, + "languages": [], + "name": "Clang UPC Compiler (Clang UPC) v3.9.1-1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://clangupc.github.io/clang-upc2c", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/clangupc/upc2c", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This work applies thermography (Thermal infrared imaging) on building images to identify defects inside of them. The objective is to segment the defect area from the non-defect area automatically without human intervention—a machine vision approach.", + "laborHours": 471.2, + "languages": [], + "name": "Thermal anomaly and rooftop unit (RTU) detection in buildings through machine learning (TAR) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/TAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-19" + }, + "description": "The Land-based Balance-of-System Systems Engineering (LandBOSSE) model is a systems engineering tool that estimates the balance-of-system (BOS) costs associated with installing utility scale wind plants (10, 1.5 MW turbines or larger). It can execute on macOS and Windows. At this time, for both platforms, it is a command line tool that needs to be accessed from the command line.\n\nThe methods used to develop this model (specifically, LandBOSSE Version 2.1.0) are described in greater detail the following report:\n\nEberle, Annika, Owen Roberts, Alicia Key, Parangat Bhaskar, and Katherine Dykes. 2019. NREL’s Balance-of-System Cost Model for Land-Based Wind. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-72201. https://www.nrel.gov/docs/fy19osti/72201.pdf.", + "laborHours": 1884.8, + "languages": [ + "Python" + ], + "name": "LandBOSSE (Land-Based Balance Of System) 2023 [SWR-18-43]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/LandBOSSE", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.5.0" + }, + { + "contact": { + "email": "olattjv@ornl.gov" + }, + "date": { + "created": "2024-08-20", + "metadataLastUpdated": "2024-08-20" + }, + "description": "The J1939 Decoder package is a set of scripts that will allow one to decode J1939 messages.", + "laborHours": 15.2, + "languages": [], + "name": "J1939 Decoder", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/joornl/J1939-Decoder", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "knappgl@ornl.gov" + }, + "date": { + "created": "2024-08-20", + "metadataLastUpdated": "2024-08-20" + }, + "description": "The additive manufacturing (AM) community has been developing digital factory tools over the past decade to better leverage the multi-modal process data coming out of the advanced manufacturing process. As a result, numerous databases of additive manufacturing process data exist in the literature and in the archival storage of disparate research groups. While some efforts have been made to create a standard ontology for storing and sharing AM data, in practice a variety of data structures are used to store AM build data, even within a single institution. This causes many problems for maintainability and extensibility when attempting to integrate computational modeling tools with experimental data to either validate models or to provide further insight into results and trends.\n\nMyna is a Python-based framework that aims to decrease the effort needed to connect individual computational models to the variety of AM process data that exist in different research groups and institutions. This type of software is sometimes referred to as \"middleware\" or “glueware,” in that it connects disparate databases and applications into a single computational ecosystem. Instead of maintaining unique interfaces between each application and each database, developers can create a single interface from each application to Myna and thereby gain access to the implemented database connections. Similarly, developing a database connection in Myna provides access to the developed simulation applications. This framework greatly simplifies the maintainability of model applications that rely on experimental data. Using external simulation tools, users will also be able to run pre-configured workflows using the built-in workflow manager. Several examples of input files are provided with Myna for different workflows, including melt pool geometry predictions and detailed melt pool and solidification microstructure predictions.", + "laborHours": 4043.2, + "languages": [ + "Python" + ], + "name": "Myna", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-MDF/Myna", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-20", + "metadataLastUpdated": "2024-08-21" + }, + "description": "The MicroEleX code package contains a variety of models and algorithms for physical modeling of microelectronic circuitry, including electrostatics, electrodynamics, superconducting physics, micromagnetics, multi-ferroic systems, and quantum transport. MicroEleX leverages the AMReX software framework to provide scalability on GPU-based supercomputing architectures. The code is open source and designed to be algorithmically flexible so developers can incorporate enhanced or customized physics.", + "laborHours": 81669.6, + "languages": [], + "name": "Exascale-Enabled Models and Algorithms for Microelectronics Applications (MicroEleX) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Microelectronics/artemis.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-20", + "metadataLastUpdated": "2024-08-20" + }, + "description": "Repo that contains code and example data for workflow anomaly detection with graph neural networks", + "laborHours": 13832.0, + "languages": [], + "name": "Graph Neural Network for Anomaly Detection and Classification in Scientific Workflows", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/FlowGAD", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-22", + "metadataLastUpdated": "2024-09-16" + }, + "description": "MSD-LIVE, the MultiSector Dynamics – Living, Intuitive, Value-adding, Environment, is a flexible and scalable data and code\nmanagement system combined with a distributed computational platform that will enable MSD researchers to document\nand archive their data, run their models and analysis tools, and share their data, software, and multi-model workflows\nwithin a robust Community of Practice. MSD-LIVE will facilitate a new open, collaborative, resource-rich, technology-facilitated,\ncommunity-driven way of doing MSD research.", + "laborHours": 0.0, + "languages": [], + "name": "msdlive-cli-distro", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MSD-LIVE/msdlive-cli-distro", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-23", + "metadataLastUpdated": "2024-08-23" + }, + "description": "Genetic Algorithms meets Deep RL for Hyperparameters Hyperparameter optimization and architecture search can easily become cumbersome and finding the right hyperparameters can seriously impact the robustness of the deep RL application being developed.\n\nWe use genetic algorithms to evolve optimum deep RL architectures in a scalable manner.\n\nHPS-RL is designed to work with multiple gym enviornments, allow users to test their own optimization functions and tune multi-objective parameters in multiple deep RL algorithms. HPS-RL uses multi-threading and is being extended with mpipy for distributed processing on HPC.\n\nhttps://arxiv.org/abs/2201.11182", + "laborHours": 1915.2, + "languages": [], + "name": "HPS-RL: Hyperparameter tuning for deep RL applications (HPS-RL) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SelfDrivingNetworkLab/hps-rl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "moriano@ornl.gov" + }, + "date": { + "created": "2024-08-23", + "metadataLastUpdated": "2024-08-23" + }, + "description": "Source code to replicate the results of the paper: Benchmarking Unsupervised Online IDS for Masquerade Attacks in CAN (arXiv:2406.13778 [cs.CR])", + "laborHours": 1246.4, + "languages": [], + "name": "pmoriano/benchmarking-unsupervised-online-IDS-masquerade-attacks", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmoriano/benchmarking-unsupervised-online-IDS-masquerade-attacks", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-09052O\nQuasi-Newton Variational Bayes (QNVB) is a training algorithm that performs high-dimensional variational inference on machine learning models. It provides mechanisms to calibrate and control model uncertainty during training. The PyTorch implementation of projective integral updates for Gaussian mean-fields supports the manuscript, \"Projective Integral Updates for High-Dimensional Variational Inference.\"\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 243.2, + "languages": [ + "Python", + "PyTorch" + ], + "name": "Quasi-Newton Variational Bayes v.3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/qnvb", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08987O\nOpenCSP analyzes and improves the performance of optical mirrors that reflect sunlight and concentrate it onto a receiver. The algorithms in this library analyze the flow of light from an original source—such as the sun—reflecting off one or more mirrors, and onto a receiver, optical screen, or camera. OpenCSP also analyzes optical systems using other techniques, such as shape or slope comparison. The software calculates aggregate properties of the optical system, such as its efficiency, manufacturing error, pointing control error, expected performance, and other useful parameters. \n\nOpenCSP also includes high-level tools, such as Open SOFAST, a program that obtains high-resolution measurement of CSP mirrors, full heliostats, and other CSP collectors. OpenCSP supports producing meaningful output data to help CSP designers and field operators improve the performance of their systems. OpenCSP also includes classes and functions that support these calculations, including input utilities, analysis output libraries, geometric constraint analysis for drone flight planning, and more. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 40188.8, + "languages": [ + "Python" + ], + "name": "OpenCSP v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/OpenCSP", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08793O\nQuESt Equity cross-references several public databases for power plant pollution and demographics to assess energy equity and environmental justice for energy storage projects. It also calculates the impacts of power plant pollution in disadvantaged communities. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 387828.0, + "languages": [ + "Python" + ], + "name": "QuESt Equity v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/snl-quest-equity", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "This is an Excel-based time-independent discount cash flow calculator for LWR-HTSE systems. The tool incorporates (1) discounted cash flow and levelized cost of hydrogen (LCOH) analysis, (2) sensitivity analysis with respect to select financial performance metrics with output ‘tornado’ charts, (3) profitability analysis represented by heat maps using the two most sensitive parameters, (4) electricity versus hydrogen production preference analysis by comparing change in net present value (?NPV) between NPP-HTSE and business-as-usual electricity production for the grid, and (5) competitiveness analysis by comparing the calculated LCOH for NPP-HTSE with that of steam methane reforming, which is the conventional process to produce hydrogen.", + "laborHours": 0.0, + "languages": [ + "Visual Basic" + ], + "name": "Nuclear Integrated Hydrogen Production Analysis Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/NIHPA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "The platform of optimal experiment management, POEM, powered with automated machine learning to accelerate the discovery of optimal solutions, and automatically guide the design of experiments to be evaluated. POEM currently supports 1) random model explorations for experiment design, 2) sparse grid model explorations with Gaussian Polynomial Chaos surrogate model to accelerate experiment design ,3) time-dependent model sensitivity and uncertainty analysis to identify the importance features for experiment design, 4) model calibrations via Bayesian inference to integrate experiments to improve model performance, and 5) Bayesian optimization for optimal experimental design. In addition, POEM aims to simplify the process of experimental design for users, enabling them to analyze the data with minimal human intervention, and improving the technological output from research activities.", + "laborHours": 2933.6, + "languages": [ + "Python" + ], + "name": "Platform Of Optimal Experiment Management", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/POEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08641O\nExoToComsol models capability-sharing. For example, the software can develop a multiphysics modeling chain using physics modeling capabilities from different research institutions using either SIERRA or COMSOL. The converter program allows exporting user-defined, region-of-interest from a large FE model, which results in a finer mesh of the submodel that can be used for subsequent analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 152.0, + "languages": [ + "python" + ], + "name": "ExoToComsol v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ExoToComsol", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08619O\nThe DISCO GUI software, written in MATLAB, allows for data calibration for X-ray diffraction work at Sandia National Labs’ Z Machine. The program manually identifies and manipulates images from seven fiber bundles based on a calibration reticle. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 212.8, + "languages": [ + "MATLAB" + ], + "name": "DISCO GUI v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DISCO_GUI", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08606O\nThe pyNuMAD software is used for managing wind turbine blade model data. pyNuMAD specializes in defining the geometry, materials, and boundary conditions for structural analysis of wind turbine blades. This includes loading in data files and providing an interface for users to make updates to the model. The software also features meshing functionality, which takes the blade model and creates a shell or brick mesh for use in finite element analysis. A typical user workflow might be: load in blade information from a yaml file, make adjustments to the blade properties, update the blade based on the adjustments, create a mesh of the blade, export this blade to another software for structural analysis.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 12646.4, + "languages": [ + "Python" + ], + "name": "pyNuMAD v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyNuMAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-30" + }, + "description": "SAND2024-08598O\nThe Quantum Instrumentation Control Kit Defect Arbitrary Waveform Generator (QICKDAWG) characterizes nitrogen-vacancy centers in diamond and other defects. It does this by using a radio frequency system-on-a-chip (RFSoC) field programmable gate array (FPGA). QICKDAWG synthesizes microwave pulses from the RFSoC to change the spin state of the defects. The software also allows for laser control using the RFSoC, which optically pumps defects. Ultimately, QICKDAWG supports the implementation of RFSoC FPGAs in defect characterization. This replaces the slow, expensive, traditional hardware, thus lowering the cost and time for defect characterization. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 144278.4, + "languages": [ + "Python" + ], + "name": "Quantum Instrumentation Control Kit Defect Arbitrary Waveform Generator (QICKDAWG) v.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/qick-dawg", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "This tool provides codes to prune and quantize vision transformers (ViTs). The tool will allow developers and researchers to speed up inference of ViTs and deploy them on CPUs.", + "laborHours": 425.6, + "languages": [], + "name": "prune_quant_vit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kshitij11/PQV-Mobile", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-27", + "metadataLastUpdated": "2024-08-27" + }, + "description": "CIGEN is a tool that finds input ranges that cause high compiler-induced numerical inconsistencies in\nnumerical programs written in a compiled language. Numerical program behavior may diverge when they\nare compiled and ran differently. Many factors, such as different hardware architectures (for example, the\nx87 FPU with its 80-bit registers), different compilers, or different optimization flags may cause the results\nof floating-point computations to become inconsistent. This kind of inconsistencies are known as\ncompiler-induced numerical inconsistencies. Given a program with floating-point inputs and an output,", + "laborHours": 3739.2, + "languages": [], + "name": "CIGEN", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CIGEN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-27", + "metadataLastUpdated": "2024-08-27" + }, + "description": "This software combines nonlinear-manifold reduced order models (NM-ROMs) with domain\ndecomposition (DD) techniques. NM-ROMs, which utilize a shallow, sparse autoencoder trained with full\norder model (FOM) snapshot data, approximate the FOM state on a nonlinear manifold. These models\noffer advantages over linear-subspace ROMs (LS-ROMs) particularly in scenarios with slowly decaying\nKolmogorov n-width. However, the training of NM-ROMs involves a number of parameters that scale with\nthe size of the FOM, and storing high-dimensional FOM snapshots can significantly increase the cost of\nROM training for extreme-scale problems.\nTo mitigate these costs, the software employs DD to partition the FOM into smaller subdomains,\ncomputes NM-ROMs for each, and then integrates these to form a global NM-ROM. This strategy offers\nmultiple benefits: it enables parallel training of subdomain NM-ROMs, reduces the number of parameters\nneeded, decreases the dimensional requirements of subdomain FOM training data, and allows for\ncustomization to the unique characteristics of each FOM subdomain. The use of a shallow, sparse\nautoencoder architecture in each subdomain NM-ROM facilitates the application of hyper-reduction (HR),\nsimplifying the nonlinear complexities and enhancing computational speed.\nThis software marks the inaugural application of NM-ROM combined with HR to a DD problem. It features\nan algebraic DD reformulation of the FOM, training of NM-ROMs with HR for each subdomain, and\nemploys a sequential quadratic programming (SQP) solver for the evaluation of the coupled global NMROM.\nThe effectiveness of the DD NM-ROM with HR is numerically demonstrated on the 2D steady-state\nBurgers' equation, showing an order of magnitude improvement in accuracy over the DD LS-ROM with\nHR.", + "laborHours": 3055.2, + "languages": [], + "name": "Domain-decomposition nonlinear manifold reduced order model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DD-NM-ROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-08-27", + "metadataLastUpdated": "2024-09-10" + }, + "description": "FRISM simulates day-to-day freight activities including end-consumer shopping, distribution channel, and carrier operation with e-commerce dynamics between passenger and freight travel. It outputs an assignment of different shipments to carriers and tour plans of the carriers' vehicles to transport shipments from their origins to their destinations.", + "laborHours": 6171.2, + "languages": [ + "Python", + "Shell" + ], + "name": "FRISM (FReight Integrated Simulation Model) [SWR-24-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/FRISM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-08-28", + "metadataLastUpdated": "2024-08-28" + }, + "description": "(SF-24-031) Software PolyLaue, having ANL OPEN SOURCE LICENSE, will be extended by KITWARE, INC. New functionality, including file manager, visualizer and mapping routine will substantially improve the procedure to identify single-crystals across compression with Laue diffraction technique.", + "laborHours": 1565.6, + "languages": [], + "name": "EXTENDED VERSION OF SOFTWARE POLYLAUE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PolyLaue/PolyLaue", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-28", + "metadataLastUpdated": "2024-08-28" + }, + "description": "Hydropower simulation model that allows for changes to inflow scenarios.", + "laborHours": 988.0, + "languages": [], + "name": "9505-PNNL/wmpy_power", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/9505-PNNL/wmpy_power", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-28", + "metadataLastUpdated": "2024-08-29" + }, + "description": "Volt-VAR and Volt-Watt functionality in photovoltaic (PV) smart inverters provide mechanisms to ensure system voltage magnitudes and power factors remain within acceptable limits. However, these control functions can become unstable, introducing oscillations in system voltages when not appropriately configured or maliciously altered during a cyberattack. In the event that Volt-VAR and Volt-Watt control functions in a portion of PV smart inverters in a distribution grid are unstable, the proposed adaptation scheme utilizes the remaining and stably-behaving PV smart inverters and other Distributed Energy Resources to mitigate the effect of the instability in real-time. The adaptation mechanism is entirely decentralized, model-free, communication-free, and requires virtually no external configuration. This repository provides code to simulate the algorithm in experiments on the IEEE 37 node test feeder.", + "laborHours": 1626.4, + "languages": [], + "name": "Adaptive Control Algorithm to Adjust Settings in Photovoltaic Inverters for Electric Grid Cybersecurity (DERAC) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/smart-inverter-adaptive-control", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-29", + "metadataLastUpdated": "2024-08-30" + }, + "description": "T2DM adds two-dimensional hydrodynamic dispersion to TOUGH2/EOS7C. T2DM can be used when modeling flow and transport of brine in porous media to account for hydrodynamic dispersion.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 775.2, + "languages": [], + "name": "T2DM v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-09-16" + }, + "description": "PyCIGAR is a python software package that merges off-the-shelf reinforcement learning libraries (RLLib and Ray) with electric power distribution system simulation tools (OpenDSS and a custom power flow solver built by LBL). PyCIGAR enables the training of neural networks to optimize the behavior of different components in the electric distribution grid, such as control systems in photovoltaic rooftop solar inverters and electric battery storage systems. The software package has been used to train neural networks to update settings in photovoltaic rooftop solar inverter control systems to mitigate cyber attacks on other solar photovoltaic rooftop devices.", + "laborHours": 13391.2, + "languages": [], + "name": "Reinforcement Learning for Distribution Grid Optimization (PyCIGAR) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/ceds-cigar", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "TOUGHREACT V4.12 is a 3-D reactive transport code that handles to non-isothermal, multiphase/multicomponent fluid flow, heat transport, aqueous and gaseous species advection-diffusion, and equilibrium/kinetic water-gas-rock-biological reactions.\n\nTOUGHREACT V4.12 is based on TOUGHREACT V3.3, with several new features including: an option to compute activity coefficients using the Pitzer ion interaction model; implementation of ECO2N V2.0 for temperatures up to 300 C; options to simulate forward and reverse osmosis, including 2D Poiseuille flow; addition of EOS8 and revisions for EOS5 and EWASG with H2(g); addition of gas species decay, various new output formats and time step control options; many bug fixes.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 39428.8, + "languages": [], + "name": "TOUGHREACT V4.12", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "This software contains a set of components that allow us to measure and analyze the use and performance of computer networks using existing off the shelf Open Source components organized into a scalable and extensible system. The components were developed for and used within ESnet's Stardust Measurement Environment. The components are used to collect, process and display network measurement data in an architecture that employs a combination of Elasticsearch, Logstash and Grafana. The advantage of this approach is we can tailor system behavior to our analytical needs and expand its capability with new types of network measurement without waiting for a commercial vendor to support our fairly niche use cases. Additionally we have existing collaborations within our community that came about from prior research efforts that will benefit from the release of this software so that others can also contribute features.", + "laborHours": 16340.0, + "languages": [], + "name": "Stardust Network Measurement Components (esnet-stardust-components) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/stardust-snmp-pipeline", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "This jupyter notebook calculates basic statistics (e.g., mean, standard deviation, coefficient of variation) and simple graphs (e.g., bar graphs, line plots) for data from the Experiment Data Depot (EDD) to provide rapid and reproducible assessment of data quality to aid research efforts across the JBEI and ABF projects. It rapidly and reproducibly calculates basic statistical values for data stored in the EDD which aids researchers and strengthens comparisons across different experiments and projects.", + "laborHours": 288.8, + "languages": [], + "name": "EDD Basic Stats and Graphs Notebook analysis (EDD BSG Notebook) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/Omics-Data-QA-QC-tool", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "City Buildings, Energy, and Sustainability (CityBES) is a web-based data and computing platform, focusing on energy modeling and analysis of a city's building stock to support district or city-scale building energy efficiency programs. CityBES uses an international open data standard, CityGML, to represent and exchange 3D city models. CityBES employs EnergyPlus to simulate building energy use and savings from energy efficient retrofits. Other CityBES features include energy benchmarking, district heating and cooling system modeling, rooftop PV analysis, building performance visualization, heat resilience modeling, as well as urban scale mapping of microclimate and heat vulnerability at census tract level. Different from other tools, CityBES uses integrated open and standard 3D city building data and models each individual building using EnergyPlus. CityBES can be used by urban planners, city energy managers, building owners, utilities, energy consultants and researchers.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 170468.0, + "languages": [], + "name": "CityBES v2021", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-11-07" + }, + "description": "The IRViz package provides easy to use graphical user interface for the analysis of IR data.", + "laborHours": 3222.4, + "languages": [], + "name": "IRViz v0.0.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/irviz", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "The software contains only one perl script that take advantage of a module published 8 years ago from the public domain (https://github.com/dongyingwu/TreeOTU) . It take a phylogenetic tree, and select a give number (user defined) of taxa that represent the maximize phylogenetic diversity from the tree.", + "laborHours": 577.6, + "languages": [], + "name": "maximize phylogenetic diversity taxa selection script (maxPD.pl) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/maxpd/src/master", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "This software uses machine learning models to perform inference on X-ray diffraction powder patterns, output from a diffractometer, to estimate all 6 unit cell parameters of crystalline lattices. Novel aspects of this software originated from the incorporation of concepts from crystallography to an ML-based approach; The resulting method achieves new performance capabilities without significant loss of accuracy and with less computationally intensive models.", + "laborHours": 258.4, + "languages": [], + "name": "Machine Learning Based System for Automated Estimation of Crystal Unit Cell Parameters from X-ray Diffraction Powder Patterns (MLCell) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cctbx-xfel/MLCell", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "This package contains the code for the paper Evaluating Physics Informed Neural Network Performance\nfor Seismic Discrimination Between Earthquake published at Seismological Research Letters. There are\none Jupyter notebook and demo data so that the audience can run build a machine learning model with\nthe P/S ratios as a physics loss in addition to the data driven loss.t", + "laborHours": 106.4, + "languages": [], + "name": "Evaluating Physics Informed Neural Network Performance for Seismic Discrimination Between Earthquake", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qingkaikong/PhysicsML-PINN-EmpiricalRelationship", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "(SF-24-012) Stopping power describes the rate that a material slows radiation particles passing through it and is useful in designing many technologies. Few organizations can perform new measurements, which require significant resources and rare equipment, and all others rely on coarse approximations \nrendered from pre-existing data. Methods for computing stopping power in new materials, such as time-dependent density functional theory (TD-DFT), have only recently (circa-2015) become available but are too computationally costly to use frequently enough to have a pronounced impact. We have created a method that opens a pathway to computing stopping power without any need for experimental \ndata by combining electronic structure computations and machine learning.", + "laborHours": 2979.2, + "languages": [], + "name": "Machine learning and TDDFT software for stopping power computation", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/globus-labs/stopping-power-ml", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Spinbox is a piece of software that facilitates quantum mechanical calculations relevant to Monte Carlo simulation of atomic nuclei. At the front lines of research on the nuclear many-body problem are a large number of supercomputer-scale simulation codes. These codes produce valuable results but can be hard to understand, especially for those without intimate knowledge of the relevant theoretical methods.\nThus, tools that fill pedagogical roles are extremely valuable. Spinbox makes it easy for one to replicate and analyze the computational processes relevant to a Quantum Monte Carlo (QMC) simulation that may be difficult to\nunderstand/debug/analyze due to the scale of the corresponding simulation software.\nSpinbox is written in Python using other state-of-the-art Python modules for numerical calculations. While a number of Python libraries exist that are suited to general quantum many-body calculations, the motivation of Spinbox is quite particular.\nIn Diffusion Monte Carlo methods (DMC, GFMC, AFDMC), the central calculation is the imaginary-time propagation of individual samples of the many-body wavefunction.\nAlthough quantum wavefunctions generally must be described by a probability distribution over a basis, DMC imbues particles (within one sample) with classical spatial coordinates. This method is unusual, so other Python packages are typically not set up to do this easily. Furthermore, the software has built-in options for nuclear systems assuming isospin symmetry, which can be set up with other libraries but is a nontrivial process to do so. Features:\n- numerical representation of samples of the many-body wavefunctions, including tensor-product states (used in AFDMC)\n- numerical representation of many-body operators, including tensor-product operators: general, spin, imaginary-time propagation, etc.\n- the correct associated arithmetic and algebra, implemented as class methods\n- classes for representing realistic nuclear two- and three-body Hamiltonians (e.g. Argonne V18, Illinois NNN)\n- large-scale parallel integration over random variables, crucial for the AFDMC method\nMy goal is to make this package open source so that anyone may use it and contribute to it, particularly other researchers doing AFDMC calculations", + "laborHours": 7022.4, + "languages": [], + "name": "Spinbox: tools for many-body quantum systems in a Monte Carlo context", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmrfox/spinbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SF-24-077 Our software generates a circuit that prepares a specified target quantum state. It generates circuits with CNOT counts of O(mn), where m is the number of nonzero amplitudes of the state and n is the number of qubits. The method does not require ancillas. It is designed for sparse states, but works for any quantum state. Our method is based on the new perspective of dynamic continuous time quantum walks for quantum state preparation. This is an intuitive perspective where a graph is \nfirst constructed to traverse the basis states. The method works by 1.) construct a graph of the basis states, 2.) transform the graph into quantum walks, and 3.) construct the final gate based \ncircuit optimized with our control reduction method.", + "laborHours": 243.2, + "languages": [], + "name": "Arbitrary State Preparation via Quantum Walks Software", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GaidaiIgor/quantum_walks", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SF-24-051 PBS_Utils is a collection of tools and libraries for administrating a PBSPro/OpenPBS system.", + "laborHours": 3860.8, + "languages": [], + "name": "PBS_UTILS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.cels.anl.gov/aig-public/pbs_utils", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SF-24-054 Octeres is a collection of tools and libraries for processing large amounts of\nsupercomputer data.", + "laborHours": 11688.8, + "languages": [], + "name": "Octeres", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.cels.anl.gov/aig-public/octeres", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-09-03", + "metadataLastUpdated": "2024-09-03" + }, + "description": "Use of media compiler and ART to perform media optimization for titer maximization in flaviolin producing P. putida", + "laborHours": 3754.4, + "languages": [], + "name": "Flaviolin_Media_Optimization_C2 v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/Flaviolin_media_opt_C2", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-09-03", + "metadataLastUpdated": "2024-09-03" + }, + "description": "Use of media compiler and ART to perform media optimization", + "laborHours": 153976.0, + "languages": [], + "name": "Flaviolin_Media_Optimization_C1 v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/Flaviolin_media_opt_C1", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-09-03", + "metadataLastUpdated": "2024-09-19" + }, + "description": "This software is used in a media optimization pipeline. It is used to calculate stock concentrations, volumes and instructions for the liquid handler used in ESE (Biomek NX-S8).", + "laborHours": 341969.6, + "languages": [], + "name": "Media Compiler v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/media_compiler", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-09-04", + "metadataLastUpdated": "2024-09-06" + }, + "description": "This software is an API for create and modify XML that are used for Plexos.\n\nDISCLAIMER: PLEXOS is a registered trademark of Energy Exemplar Pty Ltd (\"Owner\"). Owner has no affiliation to or participation in this software. Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or Alliance for Sustainable Energy, LLC (\"Alliance\"). The views and opinions of authors expressed in the available or referenced documents do not necessarily state or reflect those of the United States Government or Alliance.", + "laborHours": 1246.4, + "languages": [ + "Python" + ], + "name": "Database Manager for use with PLEXOS XML files [SWR-24-90]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/plexosdb", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.0.2" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-04", + "metadataLastUpdated": "2024-09-04" + }, + "description": "This software showcases the enhanced capabilities of the Latent Space Dynamics Identification (LaSDI)\nalgorithm through the application of the weak form, resulting in WLaSDI. WLaSDI first compresses the\ndata, then projects it onto test functions, and subsequently learns the local latent space models. Notably,\nWLaSDI demonstrates significantly improved robustness to noise. Using weak-form equation learning\ntechniques, WLaSDI achieves local latent space modeling. Compared to the standard sparse\nidentification of nonlinear dynamics (SINDy) used in LaSDI, the variance reduction of the weak form\nensures robust and precise latent space recovery, enabling fast, robust, and accurate simulations.\nWe demonstrate the efficacy of WLaSDI against LaSDI using several common benchmark examples,\nincluding viscid and inviscid Burgers', radial advection, and heat conduction. For instance, in 1D inviscid\nBurgers' simulations with up to 100% Gaussian white noise, WLaSDI maintains relative errors\nconsistently below 6%, whereas LaSDI errors can exceed 10,000%. Similarly, in radial advection\nsimulations, WLaSDI keeps relative errors below 16%, compared to potential errors of up to 10,000% with\nLaSDI. Additionally, WLaSDI achieves significant speedups, such as a 140X speedup in 1D Burgers'\nsimulations compared to the corresponding full order model.", + "laborHours": 2690.4, + "languages": [], + "name": "Weak-Form Latent Space Dynamics Identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MathBioCU/PyWLaSDI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-04", + "metadataLastUpdated": "2024-09-19" + }, + "description": "Traditional linear subspace reduced order models (LS-ROMs) are able to accelerate physical simulations\nin which the intrinsic solution space falls into a subspace with a small dimension, i.e., the solution space\nhas a small Kolmogorov n-width. However, for physical phenomena not of this type, e.g., any advection-dominated\nflow phenomena such as in traffic flow, atmospheric flows, and air flow over vehicles, a lowdimensional\nlinear subspace poorly approximates the solution. To address cases such as these, we have\ndeveloped a fast and accurate physics-informed neural network ROM, namely nonlinear manifold ROM\n(NM-ROM), which can better approximate high-fidelity model solutions with a smaller latent space\ndimension than the LS-ROMs. Our software takes advantage of the existing numerical methods that are\nused to solve the corresponding full order models. The efficiency is achieved by developing a hyper-reduction\ntechnique in the context of the NM-ROM. Numerical results show that neural networks can learn\na more efficient latent space representation on advection-dominated data from 1D and 2D Burgers'\nequations. A speedup of up to 2.6 for 1D Burgers' and a speedup of 11.7 for 2D Burgers' equations are\nachieved with an appropriate treatment of the nonlinear terms through a hyper-reduction technique.", + "laborHours": 20170.4, + "languages": [], + "name": "Nonlinear manifold reduced order model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/NM-ROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-05", + "metadataLastUpdated": "2024-09-19" + }, + "description": "This software showcases a latent space dynamics identification method, namely tLaSDI, that embeds the\nfirst and second principles of thermodynamics. The latent variables are learned through an autoencoder\nas a nonlinear dimension reduction model. The latent dynamics are constructed by a neural network-based\nmodel that precisely preserves certain structures for the thermodynamic laws through the\nGENERIC formalism. An abstract error estimate is established, which provides a new loss formulation\ninvolving the Jacobian computation of autoencoder. The autoencoder and the latent dynamics are\nsimultaneously trained to minimize the new loss. Computational examples demonstrate the effectiveness\nof tLaSDI, which exhibits robust generalization ability, even in extrapolation. In addition, an intriguing\ncorrelation is empirically observed between a quantity from tLaSDI in the latent space and the behaviors\nof the full-state solution.", + "laborHours": 2188.8, + "languages": [], + "name": "Thermodynamics-informed latent space dynamics identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pjss1223/tLaSDI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "greenwoodms@ornl.gov" + }, + "date": { + "created": "2024-09-05", + "metadataLastUpdated": "2024-09-05" + }, + "description": "A template system-of-systems modeling approach for\nautomating the development, deployment, and integration of cooling system models (CSMs) for supercomputing facilities within the ExaDigiT framework.\n\nAutoCSM is a Python-based framework to assist in CSM developers in accelerating the creation and deployment of system-level thermal-hydraulic CSMs. The intention is for this tool specifically to help standardize digital twin workflows for ExaDigiT. However, this tool can be used independent of ExaDigiT (and even other systems besides CSMs).", + "laborHours": 532.0, + "languages": [ + "Python", + "Modelica" + ], + "name": "AutoCSM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/exadigit/AutoCSM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2024-09-05", + "metadataLastUpdated": "2024-09-05" + }, + "description": "This project uses the NanoMsg next-generation library to receive data, temporarily store in an in-memory buffer, and then send it out. The buffer handles a high-bandwidth stream from multiple producers (sources) to multiple consumers (sinks).", + "laborHours": 456.0, + "languages": [ + "Python" + ], + "name": "nng_stream", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/frobnitzem/nng_stream", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0.6" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-09", + "metadataLastUpdated": "2024-09-09" + }, + "description": "The AiiDA-INQ plugin will allow the INQ code developed at the lab to utilize the AiiDA workflow manager\nwhich enables high-throughput workflows. This includes provenance tracking, restart capabilities, job\ncalculators, and other capabilities", + "laborHours": 1246.4, + "languages": [], + "name": "AiiDA-INQ plugin", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/aiida-inq", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-09", + "metadataLastUpdated": "2024-09-19" + }, + "description": "The Common Electric Power Transmission System Model (CTM) is an intuitive, extensible, language-agnostic,\nand error-resistant specification of electric power network components parameter names and\nunits, and relation between components, intended for use by the research community developing new\ncomputational methods for power systems operations and simulation. Power system datasets following\nthe CTM specification can be read as dictionaries and manipulated in that form in most programming\nlanguages (e.g., Python, Julia, C++). This standard data structure in CTM makes it easy to work in\nmultiple power systems domains (e.g., economic operation, reliability assessment, electricity markets,\nstability assessment, etc.) without requiring conversions between use-case-specific file formats with\ninformation loss in the process. This repository specifies CTM as a JSON Schema, provides\ndocumentation, derivate (code-generated) implementations of CTM, and example data and usage of the\nschema for important use cases.", + "laborHours": 1081616.8, + "languages": [], + "name": "Common Electric Power Transmission System Model JSON Schema Specification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ctm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "v0.1-alpha" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-09", + "metadataLastUpdated": "2024-09-19" + }, + "description": "This program will generate random points for electrons within the dimensions given by a parameter input\nfile. Based on these randomly generated electron positions and the nuclear positions given by a position\ninput file it will generate a value for the total electronic energy of an isolated system. This total electronic\nenergy is calculated using the electronic Hamiltonian for a monoatomic system with atoms having the\nsame number of protons and neutrons. The size of the system is defined by the parameter input file. The\nprogram will do this many times to generate a distribution of theoretically possible electronic total energies\nof the system. A user can then compare the total electronic energy given by their electronic structure\nmethod to make sure it falls within the distribution of theoretically possible values.", + "laborHours": 243.2, + "languages": [], + "name": "Uncertainty Quantification for Electronic Hamiltonian", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/linyang-121/UQEH-p", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-09-10", + "metadataLastUpdated": "2025-02-24" + }, + "description": "The proposed framework derives a set of\nquality metrics to provide critical insights into and tracking of grid operations, sensor performance, sensor longevity, and\nevent statistics. Power grid engineers can utilize this information to identify problems with existing sensor locations and\nproblematic power grid assets including generators, transmission lines, load centers, and substations. This information\ncan also be used to identify unexpected/abnormal behavior of power grid components, improve power grid observability,\nand operational monitoring, and thus enhance real-time decision-making support system. Power grid planners can utilize\nthis information to augment existing sensing architecture with new sensors and improve the observability of the network.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Sensor Data Analytics and Data Quality Assessment Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-11", + "metadataLastUpdated": "2024-09-18" + }, + "description": "SAND2021-0503 O\n\nThe epi_inference software supports the prediction of disease transmission parameters from data.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 7637437.6, + "languages": [ + "Python" + ], + "name": "epi_inference v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/epi_inference", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-09-11", + "metadataLastUpdated": "2024-10-25" + }, + "description": "MemFriend was developed to focus on providing a comprehensive view of access patterns by analysing spatial-temporal\nlocality between pairs of memory locations. It is intended to aid in data layout optimizations, and data placement decisions.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/MemFriend", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/memgaze", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-09-12" + }, + "description": "The software suite uses a microservice architecture using Docker and `docker-compose`. The microservices are as follows:\n1. User interface. This interface is written in JavaScript using the Svelte framework. It exposes form elements and a 3D visualizer to prompt the user through the definition of microstructure parameters, and setting parameters for mesh generation and refinement.\n2. Mesh generator. This is a container running the Python package for DREAM3D to generate a voxelized mesh that represents a microstructure defined by the user in the interface.\n3. Cubit runner. This is a secure shell protocol tool that makes the submitting the DREAM mesh to an HPC instance and starts to run Cubit shell commands to smooth the grain boundaries with its `sculpt` library, applies user-defined boundary node sets, and bundles and returns the simulation-ready meshes and input files as a zipped directory.", + "laborHours": 10001.6, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Mesh Computing Remote Automatic Workflow", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/MURMUR", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-09-12" + }, + "description": "This is the repository for all code related to the AGN-201 Nuclear Reactor Digital Twin at Idaho State University. The goal of this code repository is to consolidate all pieces required to run the AGN-201 Digital Twin in the [DeepLynx](https://github.com/idaholab/Deep-Lynx) ecosystem. This is the first successfully launched digital twin of a fissile nuclear reactor that we are aware of. While the code is not complex, the problems of networking, policy, and initial groundwork were significant to overcome.", + "laborHours": 54461.6, + "languages": [ + "Python", + "Rust" + ], + "name": "Agn-201 Digital Twin", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/agn201_Digital_Twin", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "martins@ornl.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-09-19" + }, + "description": "Field Expedition Routing and Navigation (FERN) is an IOS app funded by the Center for Bioenergy Innovation (CBI). It allows an end user to make trips to collect novel data points. It allows user to return to previously surveyed points to collect more data. It calculates the optimal route to use to sample points needed for return trips. A companion php/database application is required for full functionality. Links to this open source project are in the README. FERN can use the default GPS on an Iphone but it also optimized for Arrow Gold GPS. Other external GPS could be supported by modifying this code and adding the proper routines.", + "laborHours": 2097.6, + "languages": [ + "Swift" + ], + "name": "exnehilo7/fielddata-lite-iOS-app", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exnehilo7/fielddata-lite-iOS-app", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-09-12" + }, + "description": "BuildingSync® is a building data exchange schema to better enable integration between software tools and building data workflows. The schema's original use case was focused on commercial building energy audits; however, several additional use cases have been realized including building energy modeling and more high-level generic building data exchange.\n\nBuildingSync helps streamline the data exchange process, improving the value of the data, minimizing duplication of effort for subsequent building data collection efforts (including audits), and facilitating the achievement of greater energy efficiency. This in done in part by standardizing on (a) reporting audits in an electronic format, (b) tracking proposed, implemented, and discarded energy conservation measures, and (c) storing building characteristics (at multiple levels) for audits, benchmarking, and building energy analysis.\n\nBuildingSync has several documents and tools available to help users understand how to best leverage BuildingSync. The list below are only a subset of the resources available. If new resources are discovered, then feel free to create a new pull request with the additions.\n\nGeneric BuildingSync information is available on the DOE website and the project website.\n\nBuildingSync Examples - These examples are kept up to date and show a wide range of implementations. Any new update to BuildingSync is required to pass validation on these example files.\n\nBuildingSync Use Case Validator allows for users to determine if their instance complies with a specific use case for BuildingSync by checking if the required elements are implemented in an uploaded instance. An API is also provided for automated integration into other tools. Also, the website contains an easy way to view the entirety of the schema and how elements relate to the Building Exchange Data Exchange Specification. The Validator is open sourced here\nUse Case TestSuite provides a Python package for easier generation of BuildingSync use cases. BuildingSync use cases depend on the generation of schematron documents, which is time-consuming and difficult to implement well. The TestSuite allows users to define a use case using a more palatable CSV template, which it then turns into a Schematron document. The source code is available here.\n\nBuildingSync to OpenStudio/EnergyPlus. The translator is open sourced here. This project will translate a Level 1 (and partial Level 2) ASHRAE Energy Audit to a fully defined OpenStudio and EnergyPlus model. This project is in early Beta testing and any feedback is welcome!", + "laborHours": 134793.6, + "languages": [ + "Python", + "Ruby" + ], + "name": "BuildingSync® v.2.5.0 2024 [SWR-18-28]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BuildingSync/schema", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.5.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Chemical Webscraper uses the chrome web browser to search for and collect cost data for chemicals from specified distribution websites.", + "laborHours": 304.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "Chemical Webscraper [SWR-24-105]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ChemicalWebScraper", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-17", + "metadataLastUpdated": "2024-10-17" + }, + "description": "A suite of beamline controls software based on the Bluesky framework. SF-23-122", + "laborHours": 58854.4, + "languages": [], + "name": "Haven beamline control software", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spc-group/haven", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-17", + "metadataLastUpdated": "2025-01-09" + }, + "description": "This is the implementation of the framework for the planning of the technological makeup of the industrial sector.\nMotivated by the efforts to achieve carbon neutrality, the model of this framework modifies the portfolio of technologies over time for the sector of interest such that,\n- Net Present Value (NPV) is minimized\n- Constraint on Greenhouse Emissions (GHG), e.g. carbon dioxide, is satisfied\n- Demand of the underlying commodity is satisfied\n- The current implementation reflects a case study for the electric power sector.\nThe for a given initial set of capacities of different vintages, the space of decisions include,\n- Retirement of the existing capacities.\n- Retrofitting the existing capacities to alternative characteristics.\n- Creation of new capacities from a technology portfolio.\nAll the associated quantities with the deployments, e.g. CO2, heat requirement, etc.", + "laborHours": 2690.4, + "languages": [], + "name": "STREAM: Strategic Technology Roadmapping and Energy, Environmental, and Economic Analysis Model", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-CEEESA/dre4m", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-17", + "metadataLastUpdated": "2024-09-17" + }, + "description": "popclass is a lightweight python package that allows fast, probabilistic classification of the lens of a\nmicrolensing event given the event's posterior distribution and a model of the Galaxy. popclass provides\nthe bridge between Galactic simulation and lens classification, an interface to common Bayesian\ninference libraries, and the ability for users to flexibly specify their own Galactic model and classification\nparameters.", + "laborHours": 775.2, + "languages": [], + "name": "popclass", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/popclass", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "lensor@illinois.edu" + }, + "date": { + "created": "2024-09-18", + "metadataLastUpdated": "2024-09-19" + }, + "description": "CROPSR is a python tool designed for genome-wide gRNA design and evaluation for CRISPR experiments, with special focus on complex genomes such as those found in energy-producing crops. CROPSR is a product of the DOE Center for Advanced Bioenergy and Bioproducts Innovation (CABBI).", + "laborHours": 486.4, + "languages": [], + "name": "CROPSR: An Automated Platform for Complex Genome-Wide CRISPR gRNA Design and Validation", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/H2muller/CROPSR", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-09-18", + "metadataLastUpdated": "2024-09-18" + }, + "description": "R2X is a tool that allows modeler to convert input/output models to other input/out models (e.g., ReEDS™ to Plexos). This is tools is built as a parser of inputs that uses infrasys to create a network representation that then is used to create custom files as input for other models.", + "laborHours": 6672.8, + "languages": [ + "Python" + ], + "name": "R2X (ReEDS™ to X) [SWR-24-91]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/R2X", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-18", + "metadataLastUpdated": "2024-09-18" + }, + "description": "Python scripts for physics informed machine learning for time-dependent problems. The code implements\nhard constrained sequential physics-informed neural networks (HCSPINNs) using JAX library. The details\nof the method and implementation can be found in the following paper:\nRoy, P., & Castonguay, S. (2024). Exact Enforcement of Temporal Continuity in Sequential Physics-\nInformed Neural Networks. arXiv preprint arXiv:2403.03223. (https://arxiv.org/abs/2403.03223)", + "laborHours": 1444.0, + "languages": [], + "name": "PhyML", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/PhyML", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-09-20", + "metadataLastUpdated": "2024-09-20" + }, + "description": "The MTINV toolkit (2002-present) is a collection of computer codes and applications written to invert for\nthe moment tensor of a seismic source given the three components of ground motion recorded at regional\nseismic stations (e.g., Ichinose et al., 2003). The computer codes and workflow are organized to\ngenerate moment tensor solutions for a range of source depths and origin times because of the trade-off\nbetween these two quantities. The metric used is the variance reduction and variance reduction\nmodulated by the percent double-couple to determine the best-fit moment-tensor solution. We can solve\nfor a deviatoric moment tensor with a constraint added for no isotropic component although this constraint\ncan be lifted for estimating the full moment tensor like mining collapses or explosion sources.", + "laborHours": 40325.6, + "languages": [], + "name": "Moment Tensor Inversion Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mtinv", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "4.0.2" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-23", + "metadataLastUpdated": "2024-09-23" + }, + "description": "SF-24-041 aldsim is a Python module that provides a set of ALD models that allow the user to explore the \nbehavior of self-limited chemistries inside common reactor configurations.", + "laborHours": 106.4, + "languages": [], + "name": "aldsim", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aldsim/aldsim", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-09-24", + "metadataLastUpdated": "2024-09-24" + }, + "description": "The Spectral Efficiency and Tandem Performance Calculators allow users to test material types for use in tandem photovoltaic devices to better understand if a given material could work well. The Spectral Efficiency (SE) calculator takes a set of current vs voltage (I-V) and quantum efficiency (QE) data along with a spectrum input and plots the spectral efficiency of the cells represented by the datasets for the spectrum provided. The Tandem Performance calculator uses the calculated spectral efficiency of top and bottom cells and the transmission data of the top cell to calculate performance metrics for a tandem device in either a two or four terminal architecture. The SE and Tandem Performance calculators are based on the following publication: Yu, Z., Leilaeioun, M. & Holman, Z. Selecting tandem partners for silicon solar cells. Nat Energy 1, 16137 (2016).", + "laborHours": 957.6, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "Spectral Efficiency and Tandem Performance Calculators [SWR-24-92]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SE-and-Tandems", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "spongda@ornl.gov" + }, + "date": { + "created": "2024-09-24", + "metadataLastUpdated": "2024-10-18" + }, + "description": "The FAR3d model calculates the linear and nonlinear stability properties of energetic particle driven Alfven instabilities for both\ntokamak and stellarator plasma confinement devices using gyro-landau closure methods. 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Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 603090.4, + "languages": [ + "Python", + "R" + ], + "name": "Bayesian calibration of stochastic agent based model via random forest", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Bayesian-calibration-of-stochastic-agent-based-model-via-random-forest", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "A data ontology defined using the W3C Web Ontology Language (OWL) format. 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The goal is to accurately capture the dispatching behavior of a complex energy system given varying time-dependent signals for demand and commodity pricing.", + "laborHours": 1535.2, + "languages": [ + "Python" + ], + "name": "Dispatch Optimization Variable Engine", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DOVE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "SAND2024-11300O\nTChem-atm is a software library that was developed to solve complex kinetic models for atmospheric chemistry applications. 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Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 34519.2, + "languages": [ + "C++" + ], + "name": "TChem-atm v1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TChem-atm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "SAND2024-11256O\nThe Code for BALDR Study 07.04 software reproduces results from the BALDR study concerning \"Multilabel Proportion Prediction and Out-of-Distribution Detection on Gamma Spectra of Short-Lived Fission Products.\" This code can reproduce a scientific study following the step numbers present in the file names. The scientific study uses synthetic and measured data to find the best model for the radioisotope proportion estimation task of interest and generates results. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1577790.4, + "languages": [ + "Python 3.8" + ], + "name": "Code for BALDR Study 07.04", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/BALDR-Study-07.04", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "The Cyber-Informed Engineering Microgrid Analysis Tool (CIEMAT) leverages the Department of Energy’s Cyber-Informed Engineering to prompt engineering designers and operators through an analysis of the critical functions to be supported by a microgrid installations, the criticality of those functions, the impacts of denial, disruption or misuse of those functions on the microgrid and dependent functions, and the mitigations which could best prevent impacts to those functions resulting from cyber attack. Through use of this tool, microgrid designers and operators can quickly identify appropriate engineering mitigations to limit impacts from cyber attack and functions where engineering and operational staff can prioritize and guide the application of cybersecurity protections to best support the resiliency of the system.", + "laborHours": 0.0, + "languages": [], + "name": "Cyber-informed Engineering Microgrid Analysis Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/CIEMAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pearce8@llnl.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "Thicket is a python-based toolkit for Exploratory Data Analysis (EDA) of parallel performance data that enables performance optimization and understanding of applications’ performance on supercomputers. It bridges the performance tool gap between being able to consider only a single instance of a simulation run (e.g., single platform, single measurement tool, or single scale) and finding actionable insights in multi-dimensional, multi-scale, multi-architecture, and multi-tool performance datasets.", + "laborHours": 18452.8, + "languages": [ + "Python" + ], + "name": "LLNL/thicket", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/thicket", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pearce8@llnl.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "An open collaborative repository for reproducible specifications of HPC benchmarks and cross site benchmarking environments", + "laborHours": 7280.8, + "languages": [ + "Python" + ], + "name": "LLNL/benchpark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/benchpark", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-09-26", + "metadataLastUpdated": "2024-09-26" + }, + "description": "Automatically label regions of histology images.", + "laborHours": 684.0, + "languages": [], + "name": "PNNL-HubMAP-Proteoform-Suite/UnsupervisedSegmentation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-HubMAP-Proteoform-Suite/UnsupervisedSegmentation", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-09-26", + "metadataLastUpdated": "2024-09-26" + }, + "description": "Differentiable land surface model reimplementing an existing simulator, CANOAK, in JAX—a Google-developed Python package for high-performance machine learning research using automatic differentiation. The model's\npurpose is to perform hybrid land surface modeling that seamlessly couples process-based components with deep neural\nnetworks", + "laborHours": 18118.4, + "languages": [], + "name": "pnnl/JAX-CanVeg", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/JAX-CanVeg", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "mcdonnellmt@ornl.gov" + }, + "date": { + "created": "2024-09-27", + "metadataLastUpdated": "2024-10-15" + }, + "description": "Interconnected Science Ecosystem - Software Development Kit (INTERSECT-SDK)", + "laborHours": 6064.8, + "languages": [ + "Python" + ], + "name": "INTERSECT-SDK (Python)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/INTERSECT-SDK/python-sdk", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "delchinimg@ornl.gov" + }, + "date": { + "created": "2024-09-30", + "metadataLastUpdated": "2024-10-01" + }, + "description": "VERTEX-CFD is primary used for safety analysis and design optimization of fusion blankets. VERTEX-CFD has a highly flexible code structure that facilitates the addition of new features such as equations, boundary conditions, and source terms. VERTEX-CFD is designed to run on CPU- and GPU-enabled high-performance computing (HPC) platforms by relying on Kokkos. The code architecture supports a plug-and-play approach allowing equations to be coupled by selecting the correct set of input parameters in the XML format input file. A set of verification and validation problems were run to test VERTEX-CFD solver. VERTEX-CFD implements the incompressible Navier-Stokes equations coupled to a temperature equation and magneto-hydrodynamic equations. This code is being developed for fusion applications.", + "laborHours": 34792.8, + "languages": [ + "C++", + "Python", + "CUDA" + ], + "name": "VERTEX-CFD", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/delcmo/Vertex-CFD", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "Version 1.0" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2024-09-30", + "metadataLastUpdated": "2024-10-02" + }, + "description": "E3SM v3.0.1. First patch release of v3.0. The main purpose of this release is to introduce additional compsets used in v3 simulations and also fix some bugs found in compsets released with 3.0.0. [BUG FIXES] WCYCL20TR and F20TR have an updated landuse timeseries file. Those compsets and F2010 also have corrected nitrogen deposition and population density files for years after 1990. Except for those compsets, the simulated climate is identical for compsets released in v3.0.0. [NEW COMPSETS] New fully coupled compsets, including WCYCLSSP245, WCYCLSSP370, and WCYCLSSP585, which simulate future climate scenarios based on different socio-economic pathways. New single-forcing compsets like WCYCL20TR-GHG (greenhouse gases), and WCYCL20TR-aer (aerosols), allow simulations focusing on specific climate drivers. Two fully coupled compsets with dynamic ice sheets are also available. [GENERAL] Documentation for all components has been created at https://docs.e3sm.org/E3SM/ . All components have new optional features but the defaults have not changed for v3.0.0 supported compsets. The supported resolution is still a \"tri-grid\" as described in v3.0.0. [ATM] Add ability to calculate zonal mean quantities for QBO. Add new diagnostic to output CCN fields per mass of air. Add four new joint histograms to the MODIS simulator. Add alternative data stream control for SO2 species. Fix diagnostic output of in-cloud qc, nc, qi, and ni in P3. Created new User and Technical guide for EAM. Restore ability to output variable along ship/flight tracks Major update to PAM in EAM-MMF: Add adaptive subcycling in driver and enable variance transport by default. Add compsets to facilitate the E3SM-MMF (and E3SM) contributions to phase 1 & 2 of the radiative-convective equilibrium model inter-comparison project (RCEMIP). [LAND] Several fixes to C,N, P balance checks. Optionally modify the ELM snowcapping routing scheme along with the snow and firn compaction schemes to include changes made by Schneider et al. (2022); optionally implement the new snow thermal conductivity calculation method introduced in Fourteau et al. (2021); introduce a new optional format for PFT physiology files (paramfile) that allows user to specify a flexible number of PFTs. Add a LULC file for 1850-2015 at r025; allow output of land fraction used in dust mobilization. [OCEAN] Modify SSS restoring to include under sea ice by default. Fix GOTM interface for vertical mixing. Assign alkalinity equals DIC in sea ice melt, switch ice-shelf melt fluxes to Paolo 2023. Add frazil to ice-shelf melt rates, add distinct passive tracer background vert diffusivity, add parametrized tidal mixing effects to ice shelf basal melt, and add subglacial discharge at grounding line. Improve checks for ocean conservation. [LAND-ICE] Add support for dynamic Greenland Ice sheet and Antarctic Ice Sheet meshes for MALI. Add MALI thermal solver bug fix and improved iceberg handling. Activate MALI thermal solver and update configuration to be relevant to both AIS and GIS grids. [SEA-ICE] Merged vertically resolved biogeochemistry and aerosols from the standard MPAS-Seaice column package into the Icepack library, enabling the option to use Icepack for active biogeochemistry and aerosol simulations. Added a namelist option to use a spatial field for dust-iron solubility rather than a constant. Added capability to read atmospheric dust fluxes and dust-iron solubility maps from an input file. \n[COUPLER] Add ability to robustly recover from failures during restart-file writing, and cryo fields to coupler budget accounting. [Included libraries] update SCORPIO to v1.6.5, Kokkos to 4.2, CIME to 6.1.18. SCORPIO 1.6.5 includes improved support for Perlmutter and Frontier. A new rearranger, PIO_REARR_ANY, was added that lets the library choose the appropriate data rearranger to use.The default I/O NetCDF format (for reading and writing) is changed from \"64-bit offset\" (NetCDF CDF2) to \"64bit-data\" (NetCDF CDF5).", + "laborHours": 1762470.4, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v3.0.1", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v3.0.1", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v3.0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-01", + "metadataLastUpdated": "2024-10-02" + }, + "description": "To maintain/improve the\ndistribution system fault-tolerance for a grid with high penetration of distributed energy resources requires improvement,\nBlockchain can add value to improve fault-tolerant grid operations. That can be achieved using blockchain's core features\nof distributed consensus-based decision-making process and immutability.", + "laborHours": 20672.0, + "languages": [], + "name": "Blockchain-based fault tolerant grid operations system", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/dltDFLISR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2024-10-02", + "metadataLastUpdated": "2024-10-02" + }, + "description": "The missing certificate infrastructure for web APIs.", + "laborHours": 1383.2, + "languages": [ + "Python" + ], + "name": "certified", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/certified.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bostelmannf@ornl.gov" + }, + "date": { + "created": "2024-10-03", + "metadataLastUpdated": "2024-10-03" + }, + "description": "For most of their lifetime, pebble-bed reactors (PBRs) operate at an equilibrium state in which the core is filled with fuel pebbles at various levels of burnup. A fuel pebble travels multiple times in so-called passes through the reactor before it reaches its target discharge burnup and is replaced with a fresh fuel pebble. Given the stochastic nature of the fuel pebble travel paths and consequently the individual fuel pebble histories, it is not possible with standard methods developed for traditional reactor concepts to calculate the fuel inventory in the reactor core. \nAn iterative approach, the SCALE Leap-In method for Cores at Equilibrium (SLICE), was developed to generate region-average fuel inventory for a PBR. The SLICE code enables automatic generation of input files for the SCALE code system (https://www.ornl.gov/scale), management of the SCALE result files, and analysis of results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SLICE", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/scale/code/slice", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-10-03", + "metadataLastUpdated": "2024-10-03" + }, + "description": "This replication package is a case study on automated deductive verification for Rust for practical\nprograms. It is a companion artifact to a corresponding usability study on verification titled \"Union-Find\nand Usability: A Case Study and Analysis of Rust Formal Verifiers\". It seeks to answer the question \"Can\nRust developers today use Rust verifiers to verify their code?\". To answer this question, the study\ncontrasts the verification experience of two mature Rust verifiers, Creusot and Prusti, by using the tools to\ndevelop a verified implementation of union-find in Rust. The union-find implementation is based on real-world code as used in the popular egg E-graph library. The artifact consists of two different verified\nlibraries, one using Creusot and one using Prusti. The libraries have similar Rust interfaces and high-level\nproofs but differ in their details: Creusot and Prusti have different annotation languages and support\ndifferent proof styles. Each implementation can be verified with its respective tool and compiles as a\ntraditional Rust development.", + "homepageURL": "https://zenodo.org/records/13887654", + "laborHours": 456.0, + "languages": [], + "name": "Replication Package for \"Union-Find and Usability: A Case Study and Analysis of Rust Formal Verifier", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://zenodo.org/records/13887654", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-04", + "metadataLastUpdated": "2024-10-04" + }, + "description": "Cell performance optimization is important for improving the system efficiency of a redox flow battery. To gain better insights into key controlling factors Of system efficiency, this work first proposed a theoretical model for a unit cell by extending a two-dimensional analytic model to a full cell. The model is then used for cell performance optimization after validating it with experimental and numerical modeling data.", + "laborHours": 1808.8, + "languages": [], + "name": "pnnl/EZBattery", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/EZBattery", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-10-04", + "metadataLastUpdated": "2024-10-04" + }, + "description": "EWSMod-2D: A Fortran Code for 2D Elastic-Wave Sensitivity Modeling", + "laborHours": 547.2, + "languages": [], + "name": "lanl/ews", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ews", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-10-04", + "metadataLastUpdated": "2024-10-04" + }, + "description": "The python routines are outlined in detail to perform the methods and results in the manuscript under review in the journal Geophysical Research Letters titled “Seismic features predict ground motions during repeating caldera collapse sequence” with LA-UR-23-33345. All routines are written in open source python and were applied to publicly available data sets. The codes formats the data into the appropriate structure required to train a boosted tree regression model. Other codes produce figure results.", + "laborHours": 486.4, + "languages": [], + "name": "cjohnson-LANL/GRL_Kilauea", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cjohnson-LANL/GRL_Kilauea", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2025-02-24" + }, + "description": "Sonar image classification with Convolution\nNeural Network (CNN)", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 42073.6, + "languages": [], + "name": "Deep Learning for Automated Fish Detection from Sonar Images", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2024-10-07" + }, + "description": "The Fields to Farms methodology illustrates the generation of farm parcels from the Crop Data Layer (CDL), a raster dataset containing 133 categories representing various crop types and land uses. This methodology involves two primary steps: Field Delineation and Farm Aggregation. The code specifically addresses the aggregation of pre-delineated fields within a county to form farms, adhering to predefined criteria for farm size categories. It is assumed that the field delineation process, which involves creating vector polygons from CDL raster, has been completed beforehand, possibly through external tools or methods. Upon initialization, the script processes county-level fields, preparing them for farm aggregation. In the Farm Aggregation phase, the code iteratively combines delineated fields into farms based on specified criteria, continuing until the aggregated farm size meets predefined thresholds derived from data from the 2017 National Agricultural Statistics Service (NASS) census. Throughout this iterative process, the script dynamically adjusts the aggregation to ensure alignment with the desired distribution reported by NASS. The resulting output of the script is a GeoDataFrame containing classified farms, which are subsequently saved as GeoPackage files. These files enable further analysis and visualization, facilitating comprehensive exploration of the farm landscape generated through the methodology.", + "laborHours": 76.0, + "languages": [ + "Python" + ], + "name": "Field To Farm Aggregation For Agricultural Systems", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Field2Farm", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2024-10-07" + }, + "description": "The DeepLynx DAG repository will contain several Airflow DAGs (Directed Acyclic Graphs) which will be used in the context of DeepLynx's deployed Apache Airflow instance. These DAGs will be used for multiple data management tasks for DeepLynx data, including but not limited to:\n- bringing data from various sources and tools into DeepLynx\n- managing sequential data workflows, such as running Python scripts on data to perform analysis and returning the results to DeepLynx\n- performing any necessary transformation or pre-processing on data coming into DeepLynx from external sources or out of DeepLynx to go to external applications", + "laborHours": 258.4, + "languages": [ + "Python" + ], + "name": "Deeplynx Dag Repository", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DLDAGS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2024-10-07" + }, + "description": "Siting Lab contains a collection of user-friendly tutorials and guides for working with the Siting Lab (https://data.openei.org/siting_lab) data within the context of the reV model. The python code examples demonstrate the creation and transformation of Siting Lab data into reV compliant format as well as working with the reV model inputs and outputs.\n\nSpecifically, Siting Lab provides a collection of Jupyter Notebooks that serve as guides for working with data from NREL's spatial analysis portfolio. These notebooks teach users how to create and interact with reV data in order to facilitate external use of the model. The guides in this repository reference NREL's Supply Curve data as well as Siting Lab spatial data available on OEDI.", + "laborHours": 532.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "Siting Lab [SWR-24-95]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SitingLab", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2024-10-07" + }, + "description": "This software accompanies an NREL-designed machine for observing changes in optical density of 16 biological samples growing in Hungate tubes. It involves hardware & app for Multi-Tube OD Reader.\n\nOur Multi-Tube-OD-Reader device is based on the TubeOD reader (linked below), but with a housing to maximize throughput.\n\nThis repository contains the schematics for 3D printing an enclosure, a parts list for constructing, and the code for controlling the 16-tube, in-line optical density monitoring device. This device and software are particularly useful for researchers studying microbes that grow well in Hungate tubes, but are not amenable to growth in microplate readers.\n\nRelated publication: https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2021.790576/full", + "laborHours": 623.2, + "languages": [ + "Python" + ], + "name": "Multi-tube-OD-reader [SWR-24-126]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Multi-Tube-OD-Reader", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-09", + "metadataLastUpdated": "2024-10-09" + }, + "description": "SAND2021-2751 O\nThe Offshore Wind ENergy Simulation Toolkit (OWENS) is a collection of aerodynamic, structural, hydrodynamic, drivetrain, controls, composite structure and mesh preprocessing, and data postprocessing. OWENS is primarily an ontology, or glue code, pulling together many open-source and Sandia-developed libraries to model the aero-servo-hydro-elastic physics of wind and marine energy turbines. The toolkit’s intended use is for arbitrary aeroelastic rotor configurations analysis including vertical-axis wind turbines, horizontal-axis wind turbines, and analogous marine energy applications for fixed-bottom and floating configurations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525", + "laborHours": 11962.4, + "languages": [ + "Julia", + "Fortran" + ], + "name": "Offshore Wind ENergy Simulation Toolkit (OWENS)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/OWENS.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.00" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-09", + "metadataLastUpdated": "2024-10-09" + }, + "description": "SAND2024-13027O\nThe CHMMPP: A c++ Library for Constrained Hidden Markov Models (HMM) software supports the analysis of multivariate time series data to detect patterns using HMM. Many applications involve the detection and characterization of hidden or latent states in a complex system using observable states and variables. This software supports inference of latent states integrating both an HMM and application-specific constraints that reflect known relationships in hidden states. The CHMMPP software supports application-specific and generic methods for constrained inference. This includes a framework for customized Viterbi methods, constrained inference of hidden states with A* and integer programming methods, and various constraint-informed methods for learning HMM model parameters. CHMMPP focuses on supporting generic methods that enable the agile expression of complex sets of constraints that naturally arise in many real-world applications.", + "laborHours": 4028.0, + "languages": [ + "C++" + ], + "name": "CHMMPP: A c++ library for constrained Hidden Markov Models", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/chmmpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-10-10", + "metadataLastUpdated": "2024-10-10" + }, + "description": "This software provides dislocation-type defect identification and segmentation using a standard open source computer vision model, YOLOv8, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of expert annotated micrographs for training. This model demonstrates the ability to segment both dislocation lines and loops concurrently in micrographs with high pixel noise levels and on multiple alloys. It includes multiple layers of frozen layers used for transfer learning from multidisciplinary data and is extensible to alloys that are not included in the training dataset.", + "laborHours": 136.8, + "languages": [ + "Python" + ], + "name": "Post Irradiation Examination Dislocation Defect Detection Software", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/PANDA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-14", + "metadataLastUpdated": "2024-10-14" + }, + "description": "APT Clustering Visualizer", + "laborHours": 197.6, + "languages": [], + "name": "pnnl/APTVIZ", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/APTVIZ", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-14", + "metadataLastUpdated": "2024-10-14" + }, + "description": "Vidyut3d is a massively-parallel plasma-fluid solver for low-temperature plasmas (LTPs) that supports both local field (LFA) and local mean energy (LMEA) approximations, as well as complex gas and surface-phase chemistry. The solver supports 2D and 3D domains, and uses AMReX's adaptive mesh refinement capabilities to increase the grid resolution around complex structures (e.g. streamer heads and sheaths) while maintaining a tractable problem size. Vidyut specializes in simulating various types of gas-phase discharges, as well as plasma/surface interactions and surface chemistry (e.g. for plasma-mediated catalysis applications). The solver also supports hybrid CPU/GPU parallelization strategies, and has demonstrated excellent scaling on various HPC architectures for problem sizes consisting of O(100 M) control volumes.", + "laborHours": 21173.6, + "languages": [ + "C++", + "Python" + ], + "name": "Vidyut3d: A Non-Equilibrium Plasma Modeling Tool [SWR-24-101]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/vidyut3d", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-15", + "metadataLastUpdated": "2024-10-15" + }, + "description": "SAND2024-11125O\nThe Maximum Switching Throughput Density Estimator software performs a simple analysis that estimates the maximum logic switching throughput density that’s achieved in various CMOS technology nodes on the International Roadmap for Devices and Systems. This software utilizes simple device models and optimization techniques, performing a simple sweep over a range of possible logic supply voltages, and analytically calculating the maximum switching frequency for the given logic voltage that meets the power density constraint. It does this by using simple models of power dissipation in conventional and fully adiabatic switching. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 167.2, + "languages": [ + "MATLAB" + ], + "name": "Maximum Switching Throughput Density Estimator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/max-cmos-throughput", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v.0.15w (beta) script version" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-15", + "metadataLastUpdated": "2024-10-15" + }, + "description": "SAND2024-10158O\nPython HITMIX is a software package for computing hitting time moments of vertices in a graph. Hitting time moments can be used to rank the strengths of relationships between vertices in a graph. Examples are provided for computing and using hitting time moments on generic graphs and similarity graphs arising from the analysis of text documents in information retrieval applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 243.2, + "languages": [ + "python" + ], + "name": "Python HITMIX", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hitmix", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-10-16", + "metadataLastUpdated": "2024-10-16" + }, + "description": "This package consists of simulations of control algorithms being proposed for upcoming adaptive optics\nprojects for exoplanet direct imaging, in which one wavefront affector (deformable mirror) is controlled by\ntwo wavefront sensors. Simulations include time-domain behavior under various assumed conditions,\nparameter optimization routines for the controllers, and stability analysis.", + "laborHours": 2295.2, + "languages": [], + "name": "Control Algorithms for Multi-Wavefront Sensor Adaptive Optics for Astronomical Exoplanet Imaging", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/multiwfs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-17", + "metadataLastUpdated": "2024-10-17" + }, + "description": "SAND2024-08692O\nThe Gaussian Integral Inner Products (GIIP) calculates the integral of squared difference of atomic density functions minimized over the orthogonal group. It uses the hyper-spherical coverings library to sample orthogonal group.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 17069.6, + "languages": [ + "Python 3" + ], + "name": "GIIP (Gaussian Integral Inner Products)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/giip", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-17", + "metadataLastUpdated": "2024-11-04" + }, + "description": "SAND2024-08577O\nCanonical and Noncanonical Hamiltonian Operator Inference is research code that applies old and new model reduction algorithms to well-known and publicly available \"toy\" problems. It applies operator inference (OpInf) methods for model reduction to several benchmark hyperbolic partial differential equations: linear wave, Korteweg-de Vries, Benjamin-Bona-Mahoney, and linear elasticity.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 576171.2, + "languages": [ + "Python 3.8" + ], + "name": "Canonical and Noncanonical Hamiltonian Operator Inference", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HamiltonianOpInf", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-10-18", + "metadataLastUpdated": "2024-10-18" + }, + "description": "FTTN is a test suite to evaluate the numerical behaviors of matrix accelerators of GPUs (NVIDIA Tensor\nCores and AMD Matrix Cores) in a quick and simple setting. Matrix accelerators are heavily used in\ntoday's computationally intense applications to speed up matrix multiplications. This test suite provides a\ncomprehensive study on the numerical behaviors of these accelerators, including support for subnormals,\nrounding modes, extra precision bits and FMA features.\nIs there", + "laborHours": 1474.4, + "languages": [], + "name": "FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FTTN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "hespelersc@ornl.gov" + }, + "date": { + "created": "2024-10-22", + "metadataLastUpdated": "2024-10-22" + }, + "description": "Fault detection in Controller Area Network (CAN) systems is crucial for ensuring the reliability and safety of automotive and industrial applications. This study investigates and compares the effectiveness of time series classification models for supervised fault detection in CAN data. This repository contains the code and data for our benchmarking experiment aimed at detecting intermittent faults in automotive Controller Area Network (CAN) data. The goal of this project is to compare various machine learning (ML) and deep learning (DL) models using different Time Series Cross-Validation (TSCV) techniques to evaluate their effectiveness in a streaming environment for fault detection.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Multivariate Time Series Intermittent Fault Detectionin Controller Area Network CAN", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/TovNephesh/Multivariate-Time-Series-Intermittent-Fault-Detection-in-Controller-Area-Network-CAN-", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08551O\nThe Spatial Environmental Assessment Tool (SEAT) evaluates potential environmental risk associated with marine energy device deployment by coupling modeled impacts with risk severity maps. As a graphical user interface-based software, it interacts with marine energy stressor and receptor data to evaluate the risk of changes to marine environment. SEAT, which relies on spatial and temporal data, is a plug-in for geospatial software QGIS. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 4286.4, + "languages": [ + "python" + ], + "name": "Spatial Environmental Assessment Tool (SEAT)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seat-qgis-plugin", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08549O\nPyTorch Circuit-Aware Bit-Cell Modeling, a Python library, demonstrates circuit-aware training for analog machine learning accelerators. Built upon PyTorch, this software provides hardware-aware versions of common neural network layers to mitigate non-ideal behavior from novel hardware. The software provides accurate forward and backward pass estimates for hardware-mapped neural networks that are implemented in crossbars (arrays) that contain a non-linear transistor selector device. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 3784.8, + "languages": [ + "python" + ], + "name": "PyTorch Circuit-Aware Bit-Cell Modeling", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08546O\nThe underground hydrogen gas salt cavern (uh2sc) simulator software will be used to understand how hydrogen gas injection and extraction rates affect energy efficiency of weekly to monthly H2 storage. Salt cavern dynamics include: Heat transfer to the surrounding walls, gas dynamics, dissolution into brine at the bottom of caverns, multi-species gas mixtures of H2 and natural gas or other cushion gasses, and structural creep of the salt cavern or closure due to under-pressure in the cavern. The model is designed to interface with surface hydrogen system dynamics models via co-simulation. This is so it can be used as an individual tool to understand injection and extraction of H2, common faults in caverns (i.e. a leak vs. creep closure or other issues), model predictive control, and other applications. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 15.2, + "languages": [ + "Python" + ], + "name": "uh2sc simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/uh2sc", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08545O\nAlpheus is the code implementation of an advanced data structure addressing the technical challenge of analyzing a continuous data stream that is too big to fit in a computer's memory. Alpheus reports when explicitly-defined conditions on the data in the stream are met. Though the software doesn’t have a specific application domain, it was built to address challenges in cybersecurity. The software includes a representative cybersecurity data set, as well as simulated attack and benign activity.\n\nThe software’s capabilities are critical to real-world application. For example, it can operate with unlimited-sized data streams while maintaining the same theoretical performance and reporting guarantees. The code’s authors also improved execution performance by leveraging persistent memory. \n\nThe code is designed for use by the technical reviewers for the Algorithm Engineering and Experiments conference run by the Society for Industrial and Applied Mathematics.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "python", + "Bash" + ], + "name": "Alpheus", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08541O\nSTTPHAWKES software solution is a Bayesian estimation approach to a Hawkes process model that treats missing data as a latent variable in the estimation. The open-source software will be released to the R CRAN repository and Sandia National Labs’ Github.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 3526.4, + "languages": [ + "R", + "C++" + ], + "name": "STPPHAWKES", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/stpphawkes", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-11-05" + }, + "description": "SAND2024-08539O\nThe High Performance GMRES Mixed-Precision (HPG-MxP) is a benchmark for ranking high-performance supercomputers, allowing use of mixed-precision. Similar to HPCG benchmark, it is designed to profile the computers' capabilities to perform the computational and communication tasks that are commonly found in important classes of real-world applications. At the same time, like HPL-MxP benchmark, it allows the use of mixed-precision arithmetic, while ensuring the double-precision accuracy of the computed solution.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 2888.0, + "languages": [ + "C++" + ], + "name": "High-Performance GMRES Mixed-Precision (HPG-MxP) Benchmark", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/iyamazaki/hpcg", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08511O\nThe Hydrogen Extremely Low Probability of Rupture (HELPR) software toolkit provides probabilistic fracture assessments of natural gas infrastructure for transporting hydrogen. Using probabilistic sampling and sensitivity analysis—along with engineering fatigue and fracture mechanics— the software develops models that can predict structural integrity measures for natural gas pipelines under stress. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 7630.4, + "languages": [ + "Python", + "QML" + ], + "name": "Hydrogen Extremely Low Probability of Rupture Version 1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/helpr", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08478O\nThe spot_bt_ros tool allows users to easily construct complex autonomous behaviors for Boston Dynamic's Spot robot without having to overly rely on the Spot software development kit (SDK). This package specifically allows a user to run the Robot Operating System 2 alongside the SDK. Using a form-of-state machine called a \"behavior tree,” the software develops different \"leaves\" or actions that the robot undergoes. Attaching multiple actions in sequence creates a \"branch\" and several of these make up the \"tree.\"\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1687.2, + "languages": [ + "python 3.10", + "ROS Humble" + ], + "name": "spot_bt_ros v.0.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spot_bt_ros", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08430O\nspot_bt allows users to easily construct complex, autonomous behaviors without having to overly rely on Boston Dynamic’s Spot robot software development kit. Using a form-of-state machine called a \"behavior tree,\" the software develops and applies different \"leaves\" or actions to the robot. Attaching multiple actions in sequence creates a \"branch,\" and a series of these make up the \"tree.\" The software works on any x86 or aarch64 hardware but must run on a Linux OS. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525", + "laborHours": 1550.4, + "languages": [ + "Python 3.10" + ], + "name": "spot_bt v.0.1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spot_bt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-24", + "metadataLastUpdated": "2024-10-24" + }, + "description": "The Renewable Energy and Storage Cybersecurity Research (RESCue) project is a collaborative effort aimed at securing the rapidly growing deployment of transmission-connected hybrid renewable energy systems, consisting of a combination of wind, solar, and/or energy storage equipment, against escalating cyber threats. This project brings together major original equipment manufacturers (OEMs) of wind, solar, and energy storage, along with major asset owners and DOE National Laboratories, to collectively identify cyber threats, assess risks, and develop robust cybersecurity strategies and solutions. The development of hybrid reference architectures has provided comprehensive blueprints for the secure design and integration of hybrid renewable energy systems, accounting for their unique characteristics and interdependencies. Additionally, NREL has created a cyber-resilient design framework that integrates cybersecurity considerations from the start of the system lifecycle, ensuring security is \"baked in\" from the initial design phase.\n\nThe research thrusts for the project included (i) development of hybrid reference architectures and (ii) a cyber-resilient design framework for hybrid energy systems. The reference architectures has provided comprehensive blueprints for the secure design and integration of hybrid renewable energy systems, accounting for their unique characteristics and interdependencies. Additionally, NREL has created a cyber-resilient design framework that integrates cybersecurity considerations from the start of the system lifecycle, ensuring security is \"baked in\" from the initial design phase. A demonstration experiment was developed for one of the architectures using NREL's Cyber Range resources. This experiment configuration, deployable using open-source tools, is provided here in this repository. Additional models were developed for the wind and solar architectures as well, however the configurations for only the Energy Storage scenario are provided here: https://www.nrel.gov/docs/fy24osti/89921.pdf", + "laborHours": 2173.6, + "languages": [ + "Python", + "Shell" + ], + "name": "RESCue Model (RESCue Experiment and Model) [SWR-24-84]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/RESCue", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-24", + "metadataLastUpdated": "2025-01-08" + }, + "description": "Acoustic tomography seeks the best-fit fluctuating velocity and temperature fields that explain a collection of signal travel times in a region of interest. This codebase defines an end-to-end framework for executing turbulent field retrievals from acoustic signals, acoustic signal design and processing tools for the physical array, and analysis tool that leverage virtual acoustic tomography arrays based on large-eddy simulations of the atmospheric boundary layer.", + "laborHours": 22739.2, + "languages": [ + "CSS", + "HTML", + "TeX", + "JavaScript", + "Python" + ], + "name": "ATom (Acoustic Tomography Processing Suite) [SWR-24-120]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ATom", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2024-10-24", + "metadataLastUpdated": "2024-10-24" + }, + "description": "The Behavior, Energy, Autonomy, and Mobility (BEAM) model is an integrated, agent-based travel demand simulation framework. Individual agents express preferences through a utility- maximizing evolutionary algorithm that minimizes each individual’s cost and time spent traveling via diverse modal options, including the competition for scarce supply resources such as parking spaces and charging infrastructure. BEAM simulates the essential elements that compose a dynamic transportation system. From the road network, parking and charging infrastructure, to the transit system and a synthetic population with plans and preferences, the virtual system is an amalgamation of multiple spatially resolved layers that together represent an integrated transportation system. \n\nBEAM is an extension to the MATSim (Multi-Agent Transportation Simulation) model, where agents employ reinforcement learning across successive simulated days to maximize their personal utility through plan mutation (exploration) and selecting between previously executed plans (exploitation). The BEAM model shifts some of the behavioral emphasis in MATSim from across-day planning to within- day planning, where agents dynamically respond to the state of the system during the mobility simulation. In BEAM, agents can plan across all major modes of travel including driving, walking, biking, transit, and demand-responsive ride hailing. It is designed to integrate with other open source transportation models, such as ActivitySim.", + "laborHours": 58200.8, + "languages": [], + "name": "Behavior, Energy, Autonomy, Mobility Modeling Framework (BEAM) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-UCB-STI/beam", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lensor@illinois.edu" + }, + "date": { + "created": "2024-10-29", + "metadataLastUpdated": "2024-10-29" + }, + "description": "The robust nature of the non-conventional yeast Issatchenkia orientalis allows it to grow under highly acidic conditions and therefore, has gained increasing interest in producing organic acids using a variety of carbon sources. Recently, the development of a genetic toolbox for I. orientalis, including an episomal plasmid, characterization of multiple promoters and terminators, and CRISPR-Cas9 tools, has eased the metabolic engineering efforts in I. orientalis. However, multiplex engineering is still hampered by the lack of efficient multicopy integration tools. To facilitate the construction of large, complex metabolic pathways by multiplex CRISPR-Cas9-mediated genome editing, we developed a bioinformatics pipeline to identify and prioritize genome-wide intergenic loci and characterized 47 gRNAs located in 21 intergenic regions. These loci are screened for guide RNA cutting efficiency, integration efficiency of a gene cassette, the resulting cellular fitness, and GFP expression level. We further developed a landing pad system using components from these well-characterized loci, which can aid in the integration of multiple genes using single guide RNA and multiple repair templates of the user’s choice. We have demonstrated the use of the landing pad for simultaneous integrations of 2, 3, 4, or 5 genes to the target loci with efficiencies greater than 80%. As a proof of concept, we showed how the production of 5-aminolevulinic acid can be improved by integrating five copies of genes at multiple sites in one step. We have further demonstrated the efficiency of this tool by constructing a metabolic pathway for succinic acid production by integrating five gene expression cassettes using a single guide RNA along with five different repair templates, leading to the production of 9 g/L of succinic acid in batch fermentations. This study demonstrates the effectiveness of a single gRNA-mediated CRISPR platform to build complex metabolic pathways in a non-conventional yeast. This landing pad system will be a valuable tool for the metabolic engineering of I. orientalis.", + "laborHours": 197.6, + "languages": [], + "name": "A Landing Pad System for Multicopy Gene Integration in Issatchenkia orientalis", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Zhao-Group/Landing-pad-model", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-29", + "metadataLastUpdated": "2024-10-29" + }, + "description": "PLUMES2.0 is a revived version of the Visual Plumes model that was developed by Dr. Walter Frick at USEPA. PLUMES2.0\nand Visual Plumes are codes that compute initial and far-field dilution of buoyant discharges into receiving fresh or marine\nenvironments.", + "laborHours": 15.2, + "languages": [ + "Fortran" + ], + "name": "PLUMES 2.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ssmc-uw/PLUMES2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-10-30", + "metadataLastUpdated": "2024-10-30" + }, + "description": "Biofuels policies induce land use changes (LUC), including cropland expansion and crop switching, and this in turn alters water and soil management practices. Policies differ in the extent and type of land use changes they induce and therefore in their impact on water resources. We quantify and compare the spatially varying water impacts of biofuel crops stemming from LUC induced by two different biofuels policies by coupling a biophysical model with an economic model to simulate the economically viable mix of crops, land uses, and crop management choices under alternative policy scenarios. We assess the outputs of an economic model with a high-resolution crop-water model for major agricultural crops and potential cellulosic feedstocks in the US to analyze the impacts of three alternative policy scenarios on water balances: a counterfactual ‘no-biofuels policy’ (BAU) scenario, a volumetric mandate (Mandate) scenario, and a clean fuel-intensity standard (CFS) scenario incentivizing fuels based on their carbon intensities. While both biofuel policies incentivize more biofuels than in the counterfactual, they differ in the mix of corn ethanol and advanced biofuels from miscanthus and switchgrass (more corn ethanol in Mandate and more cellulosic biofuels in CFS). The two policies differ in their impact on irrigated acreage, irrigation demand, groundwater use and runoff. Net irrigation requirements increase 0.7% in Mandate and decrease 3.8% in CFS, but in both scenarios increases are concentrated in regions of Kansas and Nebraska that rely upon the Ogallala aquifer for irrigation water. Our study illustrates the importance of accounting for the overall LUC and shifts in agricultural production and management practices in response to policies when assessing the water impacts of biofuels.", + "laborHours": 1185.6, + "languages": [], + "name": "jacobteter/CropWatR", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jacobteter/CropWatR", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-10-31", + "metadataLastUpdated": "2024-10-31" + }, + "description": "Untargeted metabolomics can detect more than 10 000 peaks in a single LC–MS run. The correspondence between these peaks and metabolites, however, remains unclear. Here, we introduce a Peak Annotation and Verification Engine (PAVE) for annotating untargeted microbial metabolomics data. The workflow involves growing cells in 13C and 15N isotope-labeled media to identify peaks from biological compounds and their carbon and nitrogen atom counts. Improved deisotoping and deadducting are enabled by algorithms that integrate positive mode, negative mode, and labeling data. To distinguish metabolites and their fragments, PAVE experimentally measures the response of each peak to weak in-source collision induced dissociation, which increases the peak intensity for fragments while decreasing it for their parent ions. The molecular formulas of the putative metabolites are then assigned based on database searching using both m/z and C/N atom counts. Application of this procedure to Saccharomyces cerevisiae and Escherichia coli revealed that more than 80% of peaks do not label, i.e., are environmental contaminants. More than 70% of the biological peaks are isotopic variants, adducts, fragments, or mass spectrometry artifacts yielding ∼2000 apparent metabolites across the two organisms. About 650 match to a known metabolite formula based on m/z and C/N atom counts, with 220 assigned structures based on MS/MS and/or retention time to match to authenticated standards. Thus, PAVE enables systematic annotation of LC–MS metabolomics data with only ∼4% of peaks annotated as apparent metabolites.", + "laborHours": 562.4, + "languages": [], + "name": "xxing9703/PAVE", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xxing9703/PAVE", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Plasmids harbor transferable genes that contribute to the functional repertoire of microbial communities, yet their contributions to metagenomes are often overlooked. Environmental plasmids have the potential to spread antibiotic resistance to clinical microbial strains. In soils, high microbiome diversity and high variability in plasmid characteristics present a challenge for studying plasmids. To improve the understanding of soil plasmids, we present RefSoil+, a database containing plasmid sequences from 922 soil microorganisms. Soil plasmids were larger than other described plasmids, which is a trait associated with plasmid mobility. There was a weak relationship between chromosome size and plasmid size and no relationship between chromosome size and plasmid number, suggesting that these genomic traits are independent in soil. We used RefSoil+ to inform the distributions of antibiotic resistance genes among soil microorganisms compared to those among nonsoil microorganisms. Soil-associated plasmids, but not chromosomes, had fewer antibiotic resistance genes than other microorganisms. These data suggest that soils may offer limited opportunity for plasmid-mediated transfer of described antibiotic resistance genes. RefSoil+ can serve as a reference for the diversity, composition, and host associations of plasmid-borne functional genes in soil, a utility that will be enhanced as the database expands. Our study improves the understanding of soil plasmids and provides a resource for assessing the dynamics of the genes that they carry, especially genes conferring antibiotic resistances.", + "laborHours": 304.0, + "languages": [], + "name": "ShadeLab/RefSoil_plasmids", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ShadeLab/RefSoil_plasmids", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-12-10" + }, + "description": "An R implementation of a modified version of the sparse Bayesian polynomial chaos expansion algorithm of Shao et al., (2017).", + "laborHours": 501.6, + "languages": [], + "name": "khaos", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/knrumsey/khaos", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2025-04-24" + }, + "description": "Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. We train a random forest machine learning model to predict snow depth from variability in ground surface temperature. To our knowledge, this is the first time that small ground surface temperature sensors have been used to estimate snow depth. The model performs well at sites where the model was trained and at pan-arctic evaluation sites (RMSE <= 0.15 m). Small temperature sensors are cheap and easy-to-deploy, so this technique enables spatially distributed and temporally continuous snowpack monitoring to an extent previously infeasible. The model is flexible and can be applied to datasets retroactively to retrieve snow depth estimates at additional sites. This code package includes a *.joblib file of the trained random forest model and a *.ipynb file showing how to clean input data, train the random forest model, and apply the model.", + "laborHours": 45.6, + "languages": [], + "name": "Code Description for \"Brief Communication: Monitoring snow depth using small, cheap, and easy-to-deploy ground surface temperature sensors\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cbachand-LANL/iButton-SnowDepth-ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "This package contains R&D python codes that can nowcast >2 MeV electron distributions in the Earth's outer radiation belt, using LANL's GPS electron data (publicly available) as the primary driver. Functions of this PreMevE-MEO model has been described with details in a manuscript titled \"PreMevE-MEO: Predicting Ultra-relativistic Electrons Using Observations from GPS Satellites\" (LA-UR-24-23843), which has been submitted to Space Weather Journal.", + "laborHours": 2568.8, + "languages": [], + "name": "cheny-lanl/PreMevE-MEO-2024", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cheny-lanl/PreMevE-MEO-2024", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Python library for the calculation of benchmark dose response curves", + "laborHours": 1337.6, + "languages": [ + "Python" + ], + "name": "PNNL-CompBio/bmdrc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/bmdrc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "A collection of solid body modeling tools for 2D sketched, 2D axisymmetric, and 3D revolved models. It also contains general purpose meshing and image generation utilities appropriate for any model, not just those created with this package. Implemented for Abaqus and Cubit as backend modeling and meshing software. Orginal implementation targeted Abaqus so most options and descriptions use Abaqus modeling concepts and language.\n\nTurbo-Turtle makes a best effort to maintain common behaviors and features across each third-party software’s modeling concepts. As much as possible, the work for each subcommand is performed in Python 3 to minimize solution approach duplication in third-party tools. The third-party scripting interface is only accessed when creating the final tool specific objects and output. The tools contained in this project can be expanded to drive other meshing utilities in the future, as needed by the user community.\n\nThis project derives its name from the origins as a sphere partitioning utility following the turtle shell (or soccer ball) pattern.s.", + "laborHours": 5000.8, + "languages": [], + "name": "Turbo-Turtle v0.12.1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-aea/turbo-turtle", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Rayleigh is a 3-D convection code designed for the study of dynamo behavior in spherical geometry. It evolves the incompressible and anelastic MHD equations in spherical geometry using a pseudo-spectral approach.", + "laborHours": 34169.6, + "languages": [], + "name": "LANL contributions to Rayleigh", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/geodynamics/Rayleigh", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Multiplexed proteomics has emerged as a powerful tool to measure relative protein expression levels across multiple conditions. The relative protein abundances are inferred by comparing the signals generated by isobaric tags, which encode the samples’ origins. Intuitively, the trust associated with a protein measurement depends on the similarity of ratios from the protein’s peptides and the signal-strength of these measurements. However, typically the average peptide ratio is reported as the estimate of relative protein abundance, which is only the most likely ratio with a very naive model. Moreover, there is no sense on the confidence in these measurements. Here, we present a mathematically rigorous approach that integrates peptide signal strengths and peptide-measurement agreement into an estimation of the true protein ratio and the associated confidence (BACIQ).\n\nThe main advantages of BACIQ are:\n\nIt removes the need to threshold reported peptide signal based on an arbitrary cut-off, thereby reporting more measurements from a given experiment;\nConfidence can be assigned without replicates;\nFor repeated experiments BACIQ provides confidence intervals for the union, not the intersection, of quantified proteins; and\nFor repeated experiments, BACIQ confidence intervals are more predictive than confidence intervals based on protein measurement agreement.\nTo demonstrate the power of BACIQ, we reanalyzed previously published data on subcellular protein movement upon treatment with an Exportin-1 inhibiting drug. We detect ~2x more highly significant movers, down to subcellular localization changes of ~1% . Thus, our method drastically increases the value obtainable from quantitative proteomics experiments helping researchers to interpret their data and prioritize resources. To make our approach easily accessible we distribute it via a Python/Stan package.", + "laborHours": 364.8, + "languages": [], + "name": "wuhrlab/BACIQ", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/wuhrlab/BACIQ/?tab=GPL-3.0-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wuhrlab/BACIQ", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2025-02-24" + }, + "description": "Code built on Archive Walker. The Generator Scorecard analyzes power grid measurements to automate the process of evaluating the performance of generators. The tool includes three aspects: frequency response, voltage response, and voltage schedule tracking.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 201217.6, + "languages": [], + "name": "Generator Scorecard", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Crowd-sourcing incorporates common citizens as rich sources of data and is promising for environmental monitoring. In this paper, we propose and test the idea of incorporating incentives to crowd-sourcing management for rainfall monitoring. Specifically, we modeled the allocation of incentives (quantitatively measurable and limited rewards) among crowd-sourcing participants for a theoretical rainfall monitoring case. For this purpose, we developed an integrated model comprising a reward allocation component to represent the decision‐making process of a central manager, an agent‐based model to simulate the interactions between the manager and participants, and a rainfall simulation model to evaluate the effectiveness of various reward allocation policies. We simulated six reward allocation policies of varying levels of administrative cost, and consideration of participant and rainfall spatial heterogeneities. The results suggest the performance of each policy to improve with the reward budget and their spatial uniformity. Among the six policies tested, we found that the participant density weighted maximum participation policy yields the most accurate estimation of rainfall intensity due to its more explicit consideration of the spatial distribution of participants; however, this policy associates with a high administrative cost. This highlights the trade‐off between performance and cost in designing effective reward allocation policies. This paper provides a physical and behavior simulation modeling tool to study the feasibility and complexity of reward‐based participant management for crowd-sourcing rainfall monitoring. The proposed crowd-sourcing method is beneficial for a wide range of applications that require rainfall data with fine resolution, such as stormwater management and water availability and biomass assessment for food and energy crops.", + "laborHours": 319.2, + "languages": [], + "name": "Pan-YANG/RA-ABM", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pan-YANG/RA-ABM", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "This script is intended to provide a starting point for users to implement the equivalent soil mass (ESM) approach for calculating soil organic carbon (SOC) stocks and SOC mass percentages (commonly called “SOC concentration”). The user should read this readme file and understand how the script works before using it. The script contains some basic error checking algorithms, but it cannot catch all data entry mistakes. It is possible to misuse the script and produce invalid results. The script was designed to work on individual soil cores that have been divided into three or more contiguous segments, as the cubic spline function contains four coefficients. The script has not been tested on soil cores containing fewer than three contiguous segments. If only one segment is present, interpolation will necessarily be linear rather than cubic, which is expected to result in higher predictive error (Wendt & Hauser, 2013). Considering the wide range of potential applications, the script should not be expected to function correctly in all situations. The user is encouraged to modify or rewrite the script to meet their specific needs.", + "laborHours": 76.0, + "languages": [], + "name": "cabbi-bio/ESM-R-script", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cabbi-bio/ESM-R-script/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cabbi-bio/ESM-R-script", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-11-03", + "metadataLastUpdated": "2024-11-03" + }, + "description": "A python library to enable readout of data from commercial H3D gamma-ray detectors. This software perform readout of data and system status, as well as starting and stopping measurements, with either WebREST (HTTP), XML (N42.42), or Binary (FlatBuffers) interfaces.", + "laborHours": 1550.4, + "languages": [], + "name": "H3D Data Acquisition Software (H3DDAQ) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/lbl-anp/h3d_tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-04", + "metadataLastUpdated": "2024-11-19" + }, + "description": "Scikit-SUNDAE provides Python bindings to SUNDIALS integrators. The implicit differential algebraic (IDA) solver and C-based variable-coefficient ordinary differential equations (CVODE) solver are both included.\n\nThe name SUNDAE combines (SUN)DIALS and DAE, which stands for differential algebraic equations. Solvers specific to DAE problems are not frequently available in Python. An ordinary differential equation (ODE) solver is also included for completeness. ODEs can be categorized as a subset of DAEs (i.e., DAEs with no algebraic constraints).\n\nhttps://pypi.org/project/scikit-sundae", + "laborHours": 8375.2, + "languages": [ + "Makefile", + "C", + "Python", + "Cython" + ], + "name": "scikit-SUNDAE ((SUN)DIALS Differential Algebraic Equations) [SWR-24-137]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/scikit-sundae", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-04", + "metadataLastUpdated": "2024-11-04" + }, + "description": "CoNSEPT is a tool to predict gene expression in various cis and trans contexts. Inputs to CoNSEPT are enhancer sequence, transcription factor levels in one or many trans conditions, TF motifs (PWMs), and any prior knowledge of TF-TF interactions.", + "laborHours": 90166.4, + "languages": [], + "name": "PayamDiba/Manuscript_tools", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PayamDiba/Manuscript_tools", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-04", + "metadataLastUpdated": "2024-11-04" + }, + "description": "A dynamic systems model of C4 photosynthesis was developed based on the previous NADP-ME metabolic model for maize (Wang et al., 2014 ab). The NADP-ME metabolic model is an ordinary differential equation model including all individual steps in C4 photosynthetic carbon metabolism. Here, the model is extended to include posttranslational regulation and temperature response of enzyme activities, dynamic stomata conductance, and leaf energy balance. This model is written in Matlab (R2019a)\n\nSteady-state and dynamic gas exchange data for maize (B73), sugarcane (CP88-1762) and sorghum (Tx430) were measured in a greenhouse in Urbana, IL from July 25, 2019 through August 8, 2019. Data include:\n\nCO2 response curves\nLight response curves\nPhotosynthetic induction curves measured in the transition from darkness to high light (1800 μmol m-2 s-1), data logged every 1 min.\nPhotosynthetic induction in the transition from darkness to high light (1800 μmol m-2 s-1) to determine the kinetics of rubisco activation in these C4 crops (τ_Rubisco), data logged every 10 s.\nGas exchange under fluctuating light. After dark adaptation, the leaves undergo three light change steps, light intensity was set as 1800 µmol m-2 s-1, 200 µmol m-2 s-1 and 1800 µmol m-2 s-1 for each 1800 s step.", + "laborHours": 1261.6, + "languages": [], + "name": "yuwangcn/C4_dynamic_model", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yuwangcn/C4_dynamic_model", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-11-04", + "metadataLastUpdated": "2024-11-04" + }, + "description": "A simple tool allowing recording the execution of a GPU (CUDA) kernel and replaying that kernel as an\nindependent executable.\nThe tool operates in 3 phases. During compile time the user needs to apply a provided LLVM pass to\ninstrument the code. The pass detects all device global variables\nand device functions and stores this information with the respective LLVM-IR in the global device\nmemory. The compilation generates a record-able executable.\nThe second phase involves running the application executable with a desired input and using\nLD_PRELOAD to enable recording. When recording before invoking a device kernel\nthe pre-loaded library stores device memory in persistent storage and associates the memory with the\ndevice kernel and an LLVM IR file. At the end of the recorded execution\nthe pre-load library generates a database in the form of a JSON file containing information regarding the\nLLVM-IR files and the snapshots of device memory.\nDuring the third and last phase the user can replay the execution of an kernel as a separate independent\nexecutable. Besides executing it the user can modify the LLVM IR file and\nauto-tune parameters such as kernel launch-bounds or kernel runtime execution parameters (e.g. Kernel\nBlock and Grid Dimensions).\nIs", + "laborHours": 1687.2, + "languages": [], + "name": "Mneme", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Olympus-HPC/Mneme", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.0.alpha" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2024-11-05", + "metadataLastUpdated": "2024-11-05" + }, + "description": "Based on the well-established GREET model mainly for the United States (U.S.), Argonne National Laboratory (ANL), with the support of the U.S. Department of Energy (DOE), has collaborated with the International Energy Agency (IEA) to develop a global version of the R&D GREET model, referred to as GREET+. GREET+ is a consistent and comparable life cycle analysis (LCA) modeling platform to evaluate life-cycle energy use and greenhouse gas (GHG) emissions of vehicle/fuel systems and technologies. It examines the energy and GHG impacts of technological advancements in different world regions through 2050.\n\nThe GREET+ model builds upon the Excel platform of the R&D GREET® 2022 rev1 model and ANL’s previous efforts on two regionalized GREET versions, i.e., China-GREET for China and MENA-GREET for Middle East and North Africa (MENA). GREET+ covers 16 regions and countries, including Canada, the USA, Mexico, Brazil, Central and South America region A, Central and South America region B, the European Union, China, India, Japan, South Korea, Southeast Asia and Oceania, MENA, Central and South Africa, the UK, and Norway. The current version of GREET+ focuses on the background data of the fuel cycle (or well-to-wheels, WTW), enabling the generation of region-specific WTW results for fuels and vehicles technologies of interest.", + "homepageURL": "https://greet.anl.gov/greet_plus", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "GREET+ Model 2024", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.anl.gov/greet_plus", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "2024" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-05", + "metadataLastUpdated": "2024-12-04" + }, + "description": "Microbial lipid metabolism is an attractive route for producing oleochemicals. The predominant strategy centers on heterologous thioesterases to synthesize desired chain-length fatty acids. To convert acids to oleochemicals (e.g., fatty alcohols, ketones), the narrowed fatty acid pool needs to be reactivated as coenzyme A thioesters at cost of one ATP per reactivation – an expense that could be saved if the acyl-chain was directly transferred from ACP- to CoA-thioester. Here, we demonstrate such an alternative acyl-transferase strategy by heterologous expression of PhaG, an enzyme first identified in Pseudomonads, that transfers 3-hydroxy acyl-chains between acyl-carrier protein and coenzyme A thioester forms for creating polyhydroxyalkanoate monomers. We use it to create a pool of acyl-CoA’s that can be redirected to oleochemical products. Through bioprospecting, mutagenesis, and metabolic engineering, we develop three strains of Escherichia coli capable of producing over 1 g/L of medium-chain free fatty acids, fatty alcohols, and methyl ketones.", + "laborHours": 157304.8, + "languages": [], + "name": "Pfleger-Lab/Metabolic-Modeling---Yield-Analysis-of-PhaG", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pfleger-Lab/Metabolic-Modeling---Yield-Analysis-of-PhaG", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-05", + "metadataLastUpdated": "2024-11-05" + }, + "description": "Genes belonging to the same functional group may include numerous and variable gene sequences, making characterizing and quantifying difficult. Therefore, high-throughput design tools are needed to simultaneously create primers for improved quantification of target genes. We developed MetaFunPrimer, a bioinformatic pipeline, to design primers for numerous genes of interest. This tool also enables gene target prioritization based on ranking the presence of genes in user-defined references, such as environment-specific metagenomes. Given inputs of protein and nucleotide sequences for gene targets of interest and an accompanying set of reference metagenomes or genomes, MetaFunPrimer generates primers for ranked genes of interest. To demonstrate the usage and benefits of MetaFunPrimer, a total of 78 primer pairs were designed to target observed ammonia monooxygenase subunit A (amoA) genes of ammonia-oxidizing bacteria (AOB) in 1,550 publicly available soil metagenomes. We demonstrate computationally that these amoA-AOB primers can cover 94% of the amoA-AOB genes observed in the 1,550 soil metagenomes compared with a 49% estimated coverage by previously published primers. Finally, we verified the utility of these primer sets in incubation experiments that used long-term nitrogen fertilized or unfertilized soils. High-throughput quantitative PCR (qPCR) results and statistical analyses showed significant differences in relative quantification patterns between the two soils, and subsequent absolute quantifications also confirmed that target genes enumerated by six selected primer pairs were significantly more abundant in the nitrogen-fertilized soils. This new tool gives microbial ecologists a new approach to assess functional gene abundance and related microbial community dynamics quickly and affordably.", + "laborHours": 136.8, + "languages": [], + "name": "jialiu232/MetaFunPrimer_paper_info", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jialiu232/MetaFunPrimer_paper_info", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-05", + "metadataLastUpdated": "2024-11-05" + }, + "description": "In the repository are example scripts that perform uncertainty injection and propagation to flux balance analysis with outputs for a small sample size (for demonstration purpose only). For proper analysis, user should download the scripts and run for a large sample size (e.g., 10,000 samples).\n\nIf you use the scripts, please cite the following Metabolic Engineering article: “Quantifying the propagation of parametric uncertainty on flux balance analysis” (https://doi.org/10.1016/j.ymben.2021.10.012)\n\nThere are two subdirectories:\n\n/uncFBA/uncBiom: injection of normally distributed noise to biomass precursor coeffcients and ATP maintenance (growth-associated ATP maintenance (GAM) and non-growth associated ATP maintenance (NGAM))\n/uncFBA/uncRHS: departure from steady-state by adding noise drawn from normal distribution to the RHS terms of mass balance constraints", + "laborHours": 108452.0, + "languages": [], + "name": "maranasgroup/uncFBA", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/uncFBA", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-11-06", + "metadataLastUpdated": "2024-11-06" + }, + "description": "CH4ESE is an EXI conversion tool developed in Python3 that utilizes the open-source EXIficient implementation of the W3C EXI format specification. CH4ESE can be used to translate to and from EXI format using the command line with input data or using the web server for live-translation.", + "laborHours": 1580.8, + "languages": [ + "Python" + ], + "name": "Conversion Helper 4 Easy Serialization Of Exi (ch4ese)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/CH4ESE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-06", + "metadataLastUpdated": "2024-11-06" + }, + "description": "The emergence of the cellulosic bioeconomy requires not only adequate technological, economic, and policy advances, but also effective communication and coordination among the multiple stakeholders in the bioeconomy community. Aiming to facilitate stakeholder communication and collaboration for cellulosic bioeconomy growth, an agent-based model is developed as a community communication tool in this study. The tool simulates the behaviors and interactions of key stakeholders, as well as the responses and interactions between the stakeholders and biophysical, socioeconomic, and environmental conditions. The agent behavior rules are developed and validated based on behavior and economic theories and information attained from a stakeholder focus group study and a land use survey.", + "laborHours": 3891.2, + "languages": [], + "name": "cabbi-bio/BECT-ABM", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cabbi-bio/BECT-ABM", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-08", + "metadataLastUpdated": "2024-11-08" + }, + "description": "The code takes expert-labeled segmented images of irradiated and unirradiated pellets and trains DeepConvolutional\nNeural Networks to segment these images into defects, backgrounds, and boundaries. The code calculated qualitative\nmicrostructural information from these segmented images to facilitate the comparison of unirradiated and irradiated\npellets", + "laborHours": 3404.8, + "languages": [], + "name": "pnnl/defect_detection", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/defect_detection", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-08", + "metadataLastUpdated": "2024-11-08" + }, + "description": "Triacetic acid lactone (TAL) can be microbially produced and further chemically upgraded to several high-value chemicals. In this work, several acidic and basic ion-exchange resins and activated charcoal were evaluated for their ability to adsorb microbially produced TAL. Activated charcoal and a weak base resin, Dowex 66, showed similar TAL adsorption capacity of 0.18 ± 0.002 g/g. At 15% w/v activated charcoal, about 98% of TAL present in fermentation broth could be adsorbed. Further, ethanol washing allowed recovery of 72% of adsorbed TAL. A biorefinery producing TAL from sucrose was designed, simulated, and evaluated (through technoeconomic analysis) under uncertainty, for an estimated TAL minimum product selling price (MPSP) of $4.27/kg [$3.71−4.94/kg; 5th-95th percentiles] for the current state of technology and $2.83/kg [$2.46–3.29/kg] following potential near-term improvements to fermentation. Thus, this work provides an adsorptive process to recover microbially produced TAL that can be chemically upgraded to several industrial products.", + "laborHours": 121159.2, + "languages": [], + "name": "BioSTEAMDevelopmentGroup/Bioindustrial-Park/TAL", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BioSTEAMDevelopmentGroup/Bioindustrial-Park", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-08", + "metadataLastUpdated": "2024-11-08" + }, + "description": "Efforts to manage soils for carbon (C) sequestration remain limited by our understanding of how differences in plant traits and microbial traits mechanistically drive soil organic C (SOC) storage. Addressing this uncertainty is particularly critical in bioenergy agriculture, due to its potential to enhance soil C and provide a C neutral fuel. As such, we examined differences between two contrasting feedstocks, Zea mays (corn) and Miscanthus x giganteus (miscanthus), in the ability of their litter to form new chemically resistant particulate SOC vs. physically protected mineral associated SOC and used this data to improve the parameterization of a microbial SOC model. We tested a hypothesized conceptual model whereby easy to decompose corn litters drive greater microbial carbon use efficiency (CUE) and the formation of more mineral associated SOC over particulate SOC than more complex miscanthus litters. To do this, we performed a soil microcosm experiment where we added 13C enriched aboveground and belowground litters to soils and traced the fate of the 13C into microbial respiration and SOC pools. We found that corn litters promoted higher microbial CUE (0.37) than miscanthus litters (0.24). In turn, corn litter formed approximately 50% more mineral associated SOC than miscanthus litters. Similarly, structurally complex root litters promoted a lower CUE and formed less mineral associated SOC than leaf and shoot litters for both crops. When we used our data to parameterize the SOC model, we found that modeling microbial trait differences uniquely allowed the model to capture the fate of litter C in SOC. Collectively, we found a robust link between litter quality, microbial efficiency, and the formation of SOC. This link bridges the empirical uncertainty in how different crops can form new soil C and provides an empirical basis for modeling SOC transformations.", + "laborHours": 121.6, + "languages": [], + "name": "BrzostekEcologyLab/CORPSE-soil-jars", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BrzostekEcologyLab/CORPSE-soil-jars", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-08", + "metadataLastUpdated": "2024-11-08" + }, + "description": "Saccharomyces cerevisiae is an important model organism and a workhorse in bioproduction. Here, we reconstructed a compact and tractable genome-scale resource balance analysis (RBA) model (i.e., named scRBA) to analyze metabolic fluxes and proteome allocation in a computationally efficient manner. Resource capacity models such as scRBA provide the quantitative means to identify bottlenecks in biosynthetic pathways due to enzyme, compartment size, and/or ribosome availability limitations. ATP maintenance rate and in vivo apparent turnover numbers (kapp) were regressed from metabolic flux and protein concentration data to capture observed physiological growth yield and proteome efficiency and allocation, respectively. Estimated parameter values were found to vary with oxygen and nutrient availability. Overall, this work (i) provides condition-specific model parameters to recapitulate phenotypes corresponding to different extracellular environments, (ii) alludes to the enhancing effect of substrate channeling and post-translational activation on in vivo enzyme efficiency in glycolysis and electron transport chain, and (iii) reveals that the Crabtree effect is underpinned by specific limitations in mitochondrial proteome capacity and secondarily ribosome availability rather than overall proteome capacity.", + "laborHours": 1134406.4, + "languages": [], + "name": "maranasgroup/scRBA", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/scRBA", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "A software framework to study, from the performance and energy perspective, the efficacy of GPU-resident\nparallel Conjugate Gradient (CG) linear solver with different preconditioner options, including Gauss-Seidel, Jacobi, and\nincomplete Cholesky. We also propose a novel GPU-based preconditioner, in which the triangular solves are approximated\nby an iterative process", + "laborHours": 3556.8, + "languages": [], + "name": "pnnl/LAP", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/LAP", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "LAP v 2" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "NeuralMie was developed to improve the representation of aerosol optical properties in E3SM, the DOE's Earth system\nmodel. NeuralMie is able to closely emulate numerical solutions to the problem at a fraction of the computational cost.\nTAMie was written to generate training data for NeuralMie.", + "laborHours": 182.4, + "languages": [], + "name": "pnnl/NEURALMIE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/NEURALMIE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "Hybridization brings together chromosome sets from two or more distinct progenitor species. Genome duplication associated with hybridization, or allopolyploidy, allows these chromosome sets to persist as distinct subgenomes during subsequent meioses. Here, we present a general method for identifying the subgenomes of a polyploid based on shared ancestry as revealed by the genomic distribution of repetitive elements that were active in the progenitors. This subgenome-enriched transposable element signal is intrinsic to the polyploid, allowing broader applicability than other approaches that depend on the availability of sequenced diploid relatives. We develop the statistical basis of the method, demonstrate its applicability in the well-studied cases of tobacco, cotton, and Brassica napus, and apply it to several cases: allotetraploid cyprinids, allohexaploid false flax, and allooctoploid strawberry. These analyses provide insight into the origins of these polyploids, revise the subgenome identities of strawberry, and provide perspective on subgenome dominance in higher polyploids.", + "laborHours": 91.2, + "languages": [], + "name": "amsession/Kmer-based-Subgenome-Mapping", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/amsession/Kmer-based-Subgenome-Mapping", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.", + "laborHours": 592.8, + "languages": [], + "name": "maslov-group/FUN-PROSE", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maslov-group/FUN-PROSE", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "Repository for Kinetic Estimation Tool Capturing Heterogeneous Datasets Using Pyomo (KETCHUP), a flexible parameter estimation tool that leverages a primal-dual interior-point algorithm to solve a nonlinear programming (NLP) problem that identifies a set of parameters capable of recapitulating the steady-state fluxes and concentrations in wild-type and perturbed metabolic networks.", + "laborHours": 76577.6, + "languages": [], + "name": "maranasgroup/KETCHUP", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/KETCHUP", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "Supplemental sequence processing and R statistical analysis for publication which compares the microbiome of 27 Zea cultivars: 12 Inbred maize genotypes, 9 hybrids, and 6 wild teosinte. The project contains amplicon data for various genes: 16S rRNA, ITS, bacterial amoA, Archeal amoA, nirS, nirK, and nosZ. In addition to functional potential assay data, and N2O flux.", + "laborHours": 927.2, + "languages": [], + "name": "favela3/Maize.N-cycle.Function", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/favela3/Maize.N-cycle.Function", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "BioSTEAM is a fast and flexible package for the design, simulation, and techno-economic analysis of biorefineries under uncertainty. BioSTEAM’s framework is built to streamline and automate early-stage technology evaluations and to enable rigorous sensitivity and uncertainty analyses. Complete biorefinery configurations are available at the Bioindustrial-Park GitHub repository, BioSTEAM’s premier repository for biorefinery models and results. The long-term growth and maintenance of BioSTEAM is supported through both community-led development and the research institutions invested in BioSTEAM. Through the open-source and community-lead platform, BioSTEAM aims to foster communication and transparency within the biorefinery research community for an integrated effort to expedite the evaluation of candidate biofuels and bioproducts.\n\nAdditionally, an agile life cycle assessment (LCA) platform has been designed to interface with BioSTEAM, BioSTEAM-LCA. This open-source, installable package allows users to perform streamlined LCAs of biorefineries. The focus of BioSTEAM-LCA is to streamline and automate early-stage environmental impact analyses of processes and technologies, and to enable rigorous sensitivity and uncertainty analyses linking process design, performance, economics, and environmental impacts.", + "laborHours": 23924.8, + "languages": [], + "name": "BioSTEAMDevelopmentGroup/biosteam", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/BioSTEAMDevelopmentGroup/biosteam?tab=License-1-ov-file#readme", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BioSTEAMDevelopmentGroup/biosteam", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and underlying mechanisms; however, there has been no systematic comparison of these models characterizing their relative strengths and shortcomings. Here, we interrogated a rich data set of neuroectodermal enhancers in Drosophila, representing cis- and trans- sources of expression variation, with a suite of biophysical and machine learning models. We performed rigorous comparisons of thermodynamics-based models implementing different mechanisms of activation, repression and cooperativity. Moreover, we developed a convolutional neural network (CNN) model, called CoNSEPT, that learns enhancer ‘grammar’ in an unbiased manner. CoNSEPT is the first general-purpose CNN tool for predicting enhancer function in varying conditions, such as different cell types and experimental conditions, and we show that such complex models can suggest interpretable mechanisms. We found model-based evidence for mechanisms previously established for the studied system, including cooperative activation and short-range repression. The data also favored one hypothesized activation mechanism over another and suggested an intriguing role for a direct, distance-independent repression mechanism. Our modeling shows that while fundamentally different models can yield similar fits to data, they vary in their utility for mechanistic inference.", + "laborHours": 349.6, + "languages": [], + "name": "PayamDiba/CoNSEPT", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PayamDiba/CoNSEPT", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.", + "laborHours": 24441.6, + "languages": [], + "name": "maranasgroup/yeastsMFA", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/yeastsMFA", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.", + "laborHours": 1246.4, + "languages": [], + "name": "maranasgroup/k-sacce306", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/k-sacce306", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "Metabolic efficiency profoundly influences organismal fitness. Heterotrophs, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. While respiration is more energy-efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (i.e. faster). Through quantitative flux analysis and proteomics, we find however that mitochondrial respiration is actually more proteome-efficient than aerobic glycolysis. This is shown across yeasts, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which is valuable for hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth, but outgrow respiratory cells in oxygen limitation. Thus, aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.", + "laborHours": 1535.2, + "languages": [], + "name": "yihuishen/metabolic_flux_regulation", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yihuishen/metabolic_flux_regulation", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "Metabolic efficiency profoundly influences organismal fitness. Heterotrophs, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. While respiration is more energy-efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (i.e. faster). Through quantitative flux analysis and proteomics, we find however that mitochondrial respiration is actually more proteome-efficient than aerobic glycolysis. This is shown across yeasts, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which is valuable for hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth, but outgrow respiratory cells in oxygen limitation. Thus, aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.", + "laborHours": 11415.2, + "languages": [], + "name": "yihuishen/T_cell_MFA", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yihuishen/T_cell_MFA", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "Hydrodynamics And Radiative Diffusion Solver based on FleCSI framework", + "laborHours": 6475.2, + "languages": [], + "name": "HARD", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/HARD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "The code is a transformer model to forecast SARS-CoV-2 lineage frequencies in the future.", + "laborHours": 11445.6, + "languages": [], + "name": "CoVTransformer", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ruianke/CoVTransformer", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "SOURCES is a code for computing neutron source rates and spectra from spontaneous fission (including delayed neutrons) and (alpha,n) reactions in homogeneous materials and (alpha,n) reactions in single-interface and two-interface geometries. SOURCES is a Los Alamos National Laboratory (LANL) code that is written in FORTRAN and distributed through the Radiation Safety Information Computation Center (RSICC). LANL’s last release of SOURCES to RSICC was SOURCES4C in 2002. This disclosure covers the latest version of SOURCES, SOURCES4D. This version adds sensitivity capabilities for (alpha,n) sources in homogeneous materials. Specifically, SOURCES4D writes new output that can be used to calculate, in post-processing, first and second derivatives of the (alpha,n) source rate density and spectrum with respect to nuclide densities in a homogeneous material and first derivatives of the (alpha,n) source rate density and spectrum with respect to nuclide stopping powers and (alpha,n) cross sections (nuclear data). These derivatives are useful for uncertainty quantification, predictive modeling, and other applications in neutron transport problems.", + "laborHours": 2310.4, + "languages": [], + "name": "SOURCES4D", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SOURCES4D", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "hFlux is open source, lightweight, easy-to-use toolkit for simulation code developers working with magnetic fields to seamlessly check their intermediate results throughout the development of simulation codes.", + "laborHours": 76.0, + "languages": [], + "name": "hFlux", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/obeznosov-LANL/hFlux", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "CoH3 (CoH ver.3) is an optical model, exciton pre-equilibrium, and Hauser-Feshbach statistical model code, which calculates nuclear reaction cross sections for medium to heavy targets in the keV to MeV energy region. This program is written in standard C++, divided into approximately 200 source and header files. CoH solves the Schroedinger equation for optical potentials defined in the code, and calculates differential elastic scattering, reaction, and total cross sections, for neutron, proton, deuteron, triton, 3He, and alpha-particle. Deformed optical potentials are solved with the coupled-channels method, in which the ground state rotational band members, or vibrational phonon states are coupled. The optical model gives particle transmission coefficients that are fed into the statistical model calculations. CoH includes the pre-equilibrium model (exciton model), the direct/semidirect capture model, and the multi-stage Hauser-Feshbach statistical decay with width fluctuation correction based on the Gaussian orthogonal ensemble. For weakly coupled levels, the DWBA (distorted wave Born approximation) method is used to calculate the direct inelastic scattering process to the excited states.", + "laborHours": 31251.2, + "languages": [], + "name": "coh3", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/toshihikokawano/coh3", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "The tools used are the modified, enhanced and extended versions of the open source BatSim and BatSched suite, including visualization tools (Evalys) derived from those toolstacks.", + "laborHours": 562.4, + "languages": [], + "name": "LANL-contributed enhancements to BatSim toolstack, including VizUtil, derivative of and enhancement of Evalys", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/BatsimGantt-LANL", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2025-01-08" + }, + "description": "Ensuring accurate detection and attribution of abnormal releases of radioactive material is critical for protecting human health and safety. Most commonly, such detection is accomplished via active monitoring approaches involving the collection of physical samples. This is labor intensive and limits the temporal and spatial resolution of any detected events to a relatively coarse level. As an alternative first step towards passive monitoring, we developed an approach using eddy flux tower data records to identify signals from a known abnormal release and quantify the extent to which that signal also occurs at other times in the data record. Through two case-studies, one of which targeted the Fukushima nuclear disaster and the other targeting an abnormal release event at a radioisotope production facility in Fleurus Belgium, we tested our approach and identified several potential heretofore unidentified abnormal releases that were consistent with atmospheric circulation patterns and/or wind direction from known release sites. Because our approach is relatively simple and is resistant to systematic errors in the observational record, it has broad applicability beyond specific constituents and ecosystem types to identify a wide variety of limited-duration anomalies in flux tower data to ensure human health and industrial safety.", + "laborHours": 2872.8, + "languages": [], + "name": "Eddy covariance towers as sentinels of abnormal radioactive material releases", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/fluxnet-sentinels", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-11-18", + "metadataLastUpdated": "2024-11-18" + }, + "description": "Faraday is a high-temperature electrolysis data visualization tool, which reveals the performance of various button cells under test conditions. These tests and the resulting analytics on their data constitute a state of the industry as the US Department of Energy pushes for the production of hydrogen.\n\nFaraday leverages the Idaho National Laboratory's DeepLynx data warehouse to standardize and query button cell data. Faraday programmatically accesses this data in DeepLynx by traversing the schema, represented by a custom ontology.\n\nThe user interface queries DeepLynx for timeseries data associated with specific button cells in the warehouse, and renders them using JavaScript charts. Additional charting and data analysis techniques are made possible by an auxiliary Python server.", + "laborHours": 4712.0, + "languages": [ + "Python", + "TypeScript" + ], + "name": "Faraday: A High-temperature Electrolysis Data Explorer", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholabresearch/faraday", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-18", + "metadataLastUpdated": "2024-11-18" + }, + "description": "You've found the official code repository for the paper \"SysCaps: Language Interfaces for Simulation Surrogates of Complex Systems,\" presented at the Foundation Models for Science: Progress, Opportunities, and Challenges workshop at NeurIPS 2024. Our paper conjectures that interfaces (both text templates as well as conversational) makes interacting with simulation surrogate models for complex systems more intuitive and accessible for both non-experts and experts. \"System captions\", or SysCaps, are text-based descriptions of systems based on information contained in simulation metadata. Our paper's goal is to train multimodal regression models that take text inputs (SysCaps) and timeseries inputs (exogenous system conditions such as hourly weather) and regress timeseries simulation outputs (e.g. hourly building energy consumption). The experiments in our paper with building and wind farm simulators, which can be reproduced using this codebase, aim to help us understand whether a) accurate regression in this setting is possible and b) if so, how well can we do it.\n\nPaper: https://arxiv.org/abs/2405.19653", + "laborHours": 4651.2, + "languages": [ + "Python", + "Jupyter Notebook", + "Shell" + ], + "name": "SysCaps (Language Interfaces for Simulation Surrogates of Complex Systems) [SWR-24-97]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SysCaps", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-19", + "metadataLastUpdated": "2024-11-19" + }, + "description": "This software is a simple, light-weight python package to generate pytorch compatible machine learning graph dataset representing electric power distribution system. User is able to use these graph datasets to test their graph generation artificial intelligence (AI) models, link prediction AI models, graph classification AI models and so much more. This package uses grid-data-models (https://github.com/NREL-Distribution-Suites/grid-data-models) as input data format for power distribution system. NREL-Ditto (https://github.com/NREL-Distribution-Suites/ditto) tool can be leveraged to transform popular distribution system file formats such as opendss, cyme and synergi to grid-data-models.", + "laborHours": 187963.2, + "languages": [ + "Python" + ], + "name": "Distribution System Dataset Generator for AI Applications [SWR-24-75]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-Distribution-Suites/gridai", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-19", + "metadataLastUpdated": "2024-12-12" + }, + "description": "The WEBAT (Wind Energy with Bat AI-based Tracker) is a Python-based bat tracking software, integrating machine learning and computer vision with infrared thermal sensors to enhance the monitoring and protection of bats in proximity to wind turbines.", + "laborHours": 440.8, + "languages": [ + "Python", + "Shell" + ], + "name": "WEBAT (Wind Energy with Bat AI-based Tracker) [SWR-24-121]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WEBAT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-19", + "metadataLastUpdated": "2024-11-19" + }, + "description": "Extracting Attributes in a Simple DictionarY of CIM (EASY-CIM) is a python library to reduce the\ntime and burden of model queries using simplified data representations of CIM power system models.", + "laborHours": 2128.0, + "languages": [], + "name": "PNNL-CIM-Tools/EASY-CIM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CIM-Tools/EASY-CIM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-20", + "metadataLastUpdated": "2024-11-20" + }, + "description": "We apply semantic\nboosting to the Segment Anything Model (SAM) to obtain microstructure segmentation for transmission electron\nmicroscopy. Our booster, SAM-I-Am, extracts geometric and textural features of various intermediate masks to perform\nmask removal and mask merging operations", + "laborHours": 1155.2, + "languages": [], + "name": "pnnl/SAMIAm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SAMIAm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-20", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Our SuperSAM approach transforms the\nSegment Anything Model (SAM) into an `elastic' supernetwork, enabling the derivation of subnetworks with\nvarying architectures tailored to a wide range of resource constraints.", + "laborHours": 3663.2, + "languages": [], + "name": "pnnl/SuperSAM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SuperSAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "mukherjeed@ornl.gov" + }, + "date": { + "created": "2024-11-24", + "metadataLastUpdated": "2024-11-24" + }, + "description": "Ptychography through Differentiable Programming\nThe aim of this project is to write the forward problem: aka writing the microscope data generation, both for electron and optical microscopes in JAX so that it's end to end differentiable and using this differentiability to run modern optimizers such as Adam and Adagrad to solve for the inverse problem - which is ptychography in our case.", + "laborHours": 577.6, + "languages": [ + "Python" + ], + "name": "ptyrodactyl", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/intersect-em/pterodactyl", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "2024.08.26" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-11-25", + "metadataLastUpdated": "2024-11-25" + }, + "description": "The Dependency Analysis Project creates datasets from package management ecosystems to determine\nwhat package a file was likely installed by, and provides tools to recognize implicit dependencies when\nsource code is available for a variety of language ecosystems. The overarching goal is to help answer the\nquestion: what software does a system use?", + "laborHours": 182.4, + "languages": [], + "name": "Dependency Analysis Project", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/dapper", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-25", + "metadataLastUpdated": "2024-11-25" + }, + "description": "This package is a wrapper for the well-known Thevenin equivalent circuit model for simulating battery behavior with a focus on ease of use. The model is comprised of a single series resistor followed by any number of parallel RC pairs. \n\nThe package includes an intuitive \"experiment\" interface, which simplifies the programming of constant or dynamic current, voltage, and/or power-driven loads, making it ideal for a wide range of applications, from basic tests to complex simulations. It also supports state-of-charge (SOC) and temperature-dependent properties, allowing the model to be more easily calibrated against real cells.", + "laborHours": 2036.8, + "languages": [ + "Python" + ], + "name": "thevenin: An Equivalent Circuit Modeling Package [SWR-24-132]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/thevenin", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-25", + "metadataLastUpdated": "2024-11-25" + }, + "description": "Aerosol process analysis in model-native Spectral Element (SE) grid. Aerosol Diagnostics on Model Native Grid is a Python-based tool designed for diagnosing aerosol processes in E3SM. It is\nparticularly designed to analyze simulation data on the model-native spectral element (SE) grid, soit is also known as\nAerosol SE Diagnostics or “asediag”", + "laborHours": 1884.8, + "languages": [], + "name": "eagles-project/asediag", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eagles-project/asediag", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-25", + "metadataLastUpdated": "2024-11-25" + }, + "description": "OpenStudio-HPXML allows running residential EnergyPlus™ simulations using an HPXML file for the building description. It is intended to be used by user interfaces or other automated software workflows that automatically produce the HPXML file.\n\nOpenStudio-HPXML can accommodate a wide range of different building technologies and geometries. End-to-end simulations typically run in 3-10 seconds, depending on complexity, computer platform and speed, etc.\n\nFor more information on running simulations, generating HPXML files with the appropriate inputs to run EnergyPlus, etc., please visit the documentation linked below.\n\nhttps://openstudio-hpxml.readthedocs.io/en/latest", + "laborHours": 418608.0, + "languages": [ + "Python", + "Ruby" + ], + "name": "OpenStudio® HPXML workflow [SWR-25-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-HPXML", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.9.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-26", + "metadataLastUpdated": "2024-12-11" + }, + "description": "The ninterp crate provides multivariate interpolation over a regular, sorted, nonrepeating grid of any dimensionality. A variety of interpolation strategies are implemented, however more are likely to be added. Extrapolation beyond the range of the supplied coordinates is supported for 1-D linear interpolators, using the slope of the nearby points.\n\nThere are hard-coded interpolators for lower dimensionalities (up to N = 3) for better runtime performance.\n\nAll interpolation is handled through instances of the Interpolator enum, with the selected tuple variant containing relevant data. Interpolation is executed by calling Interpolator::interpolate.", + "laborHours": 820.8, + "languages": [ + "Rust" + ], + "name": "ninterp: N-dimensional interpolation Rust crate [SWR-25-25]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ninterp", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "john.brewer@netl.doe.gov" + }, + "date": { + "created": "2024-11-26", + "metadataLastUpdated": "2024-11-26" + }, + "description": "Reuse of Existing Pipelines for Adapted Carbon Transport (REPACT) is an Excel-based screening tool. This tool enables the user to determine whether a pipeline originally deployed for natural gas transport, can be reused for CO2 transport. The tool along with its associated user's manual walk through an intended usage statement, setup instructions, a list of inputs and outputs in the tool, and frequently used protocols. Please note that this is a first-pass screening tool. The approach presented within this tool is valid for high-level evaluation only and should not be used to make engineering, financial, and/or regulatory decisions. See the User Manual at this link: https://www.netl.doe.gov/energy-analysis/details?id=126f2dad-6d53-423e-8aaa-70954e0a2a9c.", + "homepageURL": "https://netl.doe.gov/energy-analysis/details?id=c699a604-ded1-45cd-b1c0-247b1405aeeb", + "laborHours": 0.0, + "languages": [], + "name": "REPACT Tool", + "organization": "National Energy Technology Laboratory (NETL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://netl.doe.gov/energy-analysis/details?id=c699a604-ded1-45cd-b1c0-247b1405aeeb", + "status": "Development", + "tags": [ + "DOE CODE", + "National Energy Technology Laboratory (NETL)" + ], + "version": "0" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2024-12-03", + "metadataLastUpdated": "2024-12-04" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2024 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2024" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2024-12-03", + "metadataLastUpdated": "2024-12-04" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2024 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2024 (v1.3.0.14xxx)" + }, + { + "contact": { + "email": "sundararajaa@ornl.gov" + }, + "date": { + "created": "2024-12-04", + "metadataLastUpdated": "2025-01-06" + }, + "description": "Existing frameworks to forecast time-series photovoltaic (PV) output power and consumer load for microgrid operations and controls assume a near-continuous availability of real-time input features from the field assets such as PV inverters, energy meters, and weather station. These incoming data points are used to periodically retrain models and update forecast snapshots over a moving horizon window, be it one hour-ahead, one-day ahead, or one-week ahead. However, such frameworks are not resilient to disruptions in data availability caused by losses in communications between the field sensors and data loggers. Hence, there is a need for programs that assume no availability of real-time microgrid asset data and still make reliable forecasts that can be used for decision-making. Such programs would be apt to function in extreme weather events such as hurricanes and would use lightweight recursive time-series models to independently forecast solar irradiance and ambient temperature, then compute PV power from those forecasts, as well as independently forecast consumer load.\n\n\tThe codebase performs forecasting for the scenario of when the microgrid does not have a reliable access to forecasts or real-time observations of solar irradiance (I) and ambient temperature (AT) and load (Load) to be able to adequately forecast, in real-time, the PV power production or a business' load. In this case, using historical values of PV power and load, a univariate forecasting of generation and consumption are respectively made. The use-case in particular has two sub-scenarios: one, a normal 7-day ahead forecast where the unavailability of real-time data is assumed due to infrastructure issues such as loss of communication or sensor maintenance or service downtimes. Whereas a hurricane-caused unavailability of real-time data requires a second model trained specifically on historical hurricane days to be able to capture the extreme day behavior of generation in particular, and load if applicable.\n\nA gradient boosted regression tree comprises an ensemble of additive models that map between the input of historical values (be it irradiance, temperature, or load) and their corresponding output forecasts of a given horizon such that the individual learner predictions are summed up over the total number of such learners in the ensemble to produce an aggregate forecast. A weighting mechanism is applied to the training data in each iteration, where actual and forecast values are compared to penalize incorrect forecasts by increasing the weight and reducing it to reward correct forecasts.\n\nThe code's benefits are that it: (a) accounts for a contingency where communication loss renders newly measured real-time data unavailable for model tuning and snapshot updates; (b) presents blind forecasting that recursively determines the next time-step value in a horizon using the forecast of the same attribute from a prior step; and (c) employs lightweight models that, once trained, can reliably generalize for different horizons, which make them suitable for enhancing the resilience of field microgrids prone to extreme events that encounter disruptions to data availability.", + "homepageURL": "https://code.ornl.gov/6a6/pv-and-load-forecasting-use-case-3.git", + "laborHours": 182.4, + "languages": [ + "Python" + ], + "name": "PV Generation and Load Forecasting for Adjuntas PR Community Microgrids", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/6a6/pv-and-load-forecasting-use-case-3.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "bilheuxjm@ornl.gov" + }, + "date": { + "created": "2024-12-09", + "metadataLastUpdated": "2024-12-09" + }, + "description": "The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) provides pulsed neutrons with energies varying from epithermal to cold. In preparation for VENUS, the neutron imaging beamline to be located at beam port 10, we have performed a series of experiments focused on wavelength-dependent radiography and computed tomography for a broad range of applications, from materials science to biological tissues.One of the time-of-flight (TOF) techniques that is of interest to the scientific community is the 2-dimensional mapping of phases and average crystalline plane orientation in samples both ex-situ and during applied stresses such as tensile loading and heating. This technique is known as Bragg edgeimaging and relies on the identification of changes of transmission values, fitting of the edge to measure its displacement, and thus identify the shift in lattice parameter due to stresses. One of the challenges of TOF imaging measurements is the amount of data and the inability to observe Bragg edge shifts in real time during an experiment. Thus, we have been focusing on creating a Python-based interface that allows fast data processing and instantaneous mapping and fitting of the Bragg edges, and their evolution through time. Python libraries and Jupyter notebooks have been implemented to facilitate decision making during an experiment. The advantage of the notebooks is the possibility to guide an experiment as they can quickly process and display Bragg edge data. These notebooks can be used independently, or can be combined in a Python Graphical User Interface (GUI) tool called iBeatles. This interface permits visualization and fitting of the Bragg edges, and ultimately back-projects the fitting results onto the radiographs to display a strain map. Assuming data collection has sufficient statistics, the strain mapping analysis can be performed on a pixel-by-pixel basis. This development is a step forward toward a better user experience at the future VENUS beamline in terms of live feedback and productivity. Analysis that used to take days of switching between different applications can now be done in minutes within the", + "laborHours": 36449.6, + "languages": [ + "Python" + ], + "name": "Imaging Bragg Edge Analysis TooLs for Engineering Structures (iBeatles)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornlneutronimaging/iBeatles", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-12-09", + "metadataLastUpdated": "2024-12-09" + }, + "description": "pyzag is a library for efficiently training generic models defined with a recursive nonlinear function. We developed it primarily to provide an efficient means to train NEML2 models\n it can be used to train other, more general types of models.", + "laborHours": 1079.2, + "languages": [], + "name": "sf-24-103", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/applied-material-modeling/pyzag", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-10", + "metadataLastUpdated": "2025-02-24" + }, + "description": "We will employ a machine learning approach with intelligent data mining and\ndatabase construction to analyze enormous data repositories for identifying and\nextracting geographic-dependent cell design specifications from publicly accessible\ngrid-scale energy storage usage databases in an automated way at scale.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 53169.6, + "languages": [], + "name": "LIB Design Module for Grid Energy System Application", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-10", + "metadataLastUpdated": "2025-02-24" + }, + "description": "This software was developed to aid in the automation of electron microscopy. 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The application extends the framework to handle structural problems with a consistent large deformation\nframework as well as adding miscellaneous utility routines we have found useful in our work on high temperature\nstructural design.\n(Provide additional information if necessary in Supplemental section below.)\nYear code", + "laborHours": 10503.2, + "languages": [], + "name": "SF-19-055 deer", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/deer", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-12-19", + "metadataLastUpdated": "2024-12-19" + }, + "description": "Solar receiver structural life estimation tool. This software estimates the life of a tubular concentrating solar power\nreceiver given user input describing the working fluid pressures and temperatures. sf-20-068", + "laborHours": 9241.6, + "languages": [], + "name": "srlife", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/applied-material-modeling/srlife", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-20", + "metadataLastUpdated": "2024-12-23" + }, + "description": "A novel method for pairwise graph comparison that includes both the graph structure and\napplicable metadata. The resulting visual component allows a greater and more interpretable understanding of the\ncomparison than current methods", + "laborHours": 957.6, + "languages": [], + "name": "pnnl/graph_merge", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/graph_merge", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-23", + "metadataLastUpdated": "2024-12-23" + }, + "description": "Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Bacillus\nThese repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model\n(GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of\nmetabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate\nupdates to the GEM, ensuring that model modifications improve or maintain the model's integrity.", + "laborHours": 159676.0, + "languages": [], + "name": "pnnl-predictive-phenomics/csc052-gem", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc052-GEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-23", + "metadataLastUpdated": "2024-12-23" + }, + "description": "Genome-Scale Metabolic Model of CarbStor Community member Microbacterium (csc031) Continuous Validation with\nMemote\nThese repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model\n(GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of\nmetabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate\nupdates to the GEM, ensuring that model modifications improve or maintain the model's integrity", + "laborHours": 169647.2, + "languages": [], + "name": "pnnl-predictive-phenomics/csc031-gem", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc031-GEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-23", + "metadataLastUpdated": "2024-12-23" + }, + "description": "Genome-Scale Metabolic Model of CarbStore Community member Curtobacterium (csc009) Continuous Validation with\nMemote\nThese repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model\n(GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of\nmetabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate\nupdates to the GEM, ensuring that model modifications improve or maintain the model's integrity", + "laborHours": 140280.8, + "languages": [], + "name": "pnnl-predictive-phenomics/csc009-gem", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc009-GEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-23", + "metadataLastUpdated": "2024-12-23" + }, + "description": "Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Rhodococcus\nThese repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model\n(GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of\nmetabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate\nupdates to the GEM, ensuring that model modifications improve or maintain the model's integrity.", + "laborHours": 193952.0, + "languages": [], + "name": "pnnl-predictive-phenomics/csc040-gem", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc040-GEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-23", + "metadataLastUpdated": "2024-12-23" + }, + "description": "Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Paenibacillus\nThese repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model\n(GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of\nmetabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate\nupdates to the GEM, ensuring that model modifications improve or maintain the model's integrity.", + "laborHours": 138289.6, + "languages": [], + "name": "pnnl-predictive-phenomics/csc043-gem", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc043-GEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-12-23", + "metadataLastUpdated": "2024-12-23" + }, + "description": "EyeON: Eye on Operational technology\nSoftware Supply Chain attacks have risen drastically over the past few years, none more well-known and\nimpactful than the SolarWinds compromise. Criminal organizations inserted an attack vector into a\nspecific version of the source code, giving themselves an air of credibility. Once news broke on\nSolarWinds, identifying compromised sites was very difficult, even knowing the culprit update.\nSoftware Bills of Materials (SBOM) have been touted as the solution to reclaiming control of your software\nsupply chain. Deployment of SBOMs has been slow, however, due to conflicting standards, opaque\nstorage requirements, and vendor adoption. Additionally, the path from obtaining an SBOM and securing\nyour supply chain is unclear; how can an SBOM library be leveraged to provide insight to your attack\nsurface? The EyeON tool, sponsored by Department of Energy Cybersecurity, Energy Security, and\nEmergency Response (DoE CESER), aims to address these gaps by providing an encapsulated solution\nto tracking which updates have been installed in an enterprise, and alerting system administrators to\nvulnerabilities as they become known.\nSimilar to a virus scanner, EyeON is a command line tool to parse either a single file, nested directory\nstructure, or filesystem. It collects data such as signature (hashes), version information, VirusTotal tags,\ncompiler, compilation date, and code signing information. Users will anonymously submit scan data\nperiodically to DoE CESER, who will then compile a database of known software products employed by\nCritical Infrastructure and broadcast alerts based on discovered flaws as they arise.", + "laborHours": 1580.8, + "languages": [], + "name": "EyeON", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pEyeON", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-01-02", + "metadataLastUpdated": "2025-01-02" + }, + "description": "Swift is a fast Fourier transform based spectral solver based on the MOOSE framework. It supports GPU accelerated semi-implicit solves of partial differential equations, such as those used for phase field mesoscale microstructure evolution.", + "laborHours": 140736.8, + "languages": [ + "C++" + ], + "name": "Swift", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/swift", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-01-08", + "metadataLastUpdated": "2025-01-08" + }, + "description": "A wind farm optimization suite for wind energy that is built for modular, gradient-enabled multi-disciplinary and multi-fidelity optimizations.\n\nDig into wind farm design.\n\nAn ard is a type of simple and lightweight plow, used through the single-digit centuries to prepare a farm for planting. The intent of Ard is to be a modular, full-stack multi-disciplinary optimization tool for wind farms.\n\nThe problem with wind farms is that they are complicated, multi-disciplinary objects. They are aerodynamic machines, with complicated control systems, power electronic devices, social and political objects, and the core value (and cost) of complicated financial instruments. Moreover, the design of one of these aspects affects all the rest!\n\nArd seeks to make plant-level design choices that can incorporate these different aspects and their interactions to make wind energy projects more successful.", + "laborHours": 1504.8, + "languages": [ + "Python", + "Jupyter Notebook", + "Shell" + ], + "name": "Ard [SWR-25-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/Ard", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-01-08", + "metadataLastUpdated": "2025-01-08" + }, + "description": "Powering the Blue Economy Hardware-in-the-Loop models (PBE-HIL) is a repository of Power Hardware-in-the-loop models developed for typical Powering the Blue Economy market loads and power requirements. The HIL models were developed to be as generic and functional as possible, meaning that the user can easily configure these models to represent their unique PBE design. These PBE load and power requirement HIL models can then be used to inform marine energy converter (MEC) and power electronics design, as well as be used in laboratory testing using HIL equipment, leading to improved understanding of MEC performance and lower risk prior to open-water MEC deployment.", + "laborHours": 52318.4, + "languages": [ + "C", + "Python", + "HTML" + ], + "name": "PBE-HIL (Powering the Blue Economy Hardware-in-the-Loop models) [SWR-25-37]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PBE-HIL", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "moorea@osti.gov" + }, + "date": { + "created": "2025-01-10", + "metadataLastUpdated": "2025-01-10" + }, + "description": "The Replicative Assessment of Spectrometric Equipment (RASE) is a software for evaluating the\nperformance of radiation detectors and isotope identification algorithms. It uses a semi-empirical\napproach to rapidly generate synthetic spectra and inject into detector's software to obtain nuclide\nidentification response. RASE facilitates studies of spectroscopic device performance and a quantitative\nassessment of its capabilities to correctly distinguish and identify isotopes of interest in realistic scenarios", + "laborHours": 4088.8, + "languages": [], + "name": "Replicative Assessment of Spectroscopic Equipment v3.0", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RASE", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "wongey@ornl.gov" + }, + "date": { + "created": "2025-01-14", + "metadataLastUpdated": "2025-01-14" + }, + "description": "The QIR Execution Engine library provides interfaces for easily processing Quantum Intermediate Representation code using the LLVM execution engine.", + "laborHours": 3435.2, + "languages": [], + "name": "QIR-EE", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/qiree", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-01-15", + "metadataLastUpdated": "2025-01-15" + }, + "description": "Tool for building CIM models \"from scratch\"", + "laborHours": 48518.4, + "languages": [], + "name": "PNNL-CIM-Tools/CIM-Builder", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CIM-Tools/CIM-Builder", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kotevskao@ornl.gov" + }, + "date": { + "created": "2025-01-16", + "metadataLastUpdated": "2025-04-15" + }, + "description": "This is a repository for PETINA: Privacy prEservaTIoN Algorithms.", + "laborHours": 106.4, + "languages": [ + "Python" + ], + "name": "OKotevska/petina", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/OKotevska/petina", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.11" + }, + { + "contact": { + "email": "alexanderwg@ornl.gov" + }, + "date": { + "created": "2025-01-17", + "metadataLastUpdated": "2025-01-23" + }, + "description": "Here, we develop MIJAMP (MIJAMP Is Just A MethylBED Parser), a software package that was developed to discover methylated motifs from the output of ONT’s Modkit or other data in the methylBED format. MIJAMP employs a human-driven refinement strategy that empirically validates all motifs against genome-wide methylation data, thus eliminating false, under-, or overexplained motifs. MIJAMP can also report methylation data on a specific, user-defined motif.", + "laborHours": 334.4, + "languages": [ + "Python" + ], + "name": "MIJAMP", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/alexander-public/mijamp", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-01-17", + "metadataLastUpdated": "2025-01-17" + }, + "description": "Funded by the DOE's Bioenergy Technology Office through the Feedstock-Conversion Interface Consortium, INL researchers developed this code to model biomass freestock flow in various handling equipment, such as hoppers and augers. Built on top of an existing open-source code DualSPHysics (https://dual.sphysics.org/) , the enrichment includes modification of the mass conservation equation that switching tracking density to void ratio, adding a hypoplastic constitutive law to better capture the flow physics of this type of material and implementing a novel boundary condition that can handle the dynamic contact between material and equipment. All implementation were realized via Nvidia CUDA, so GPU accelaration can be leveraged to signifiantly speed up the computational process.", + "laborHours": 44338.4, + "languages": [ + "C++" + ], + "name": "DualSPHysics-INL", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/DualSPHysics-INL", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-01-17", + "metadataLastUpdated": "2025-01-17" + }, + "description": "This code is a python based application that queries the National Vulnerability Database (NVD) API search term and CPE endpoints. It then sifts through the API response and uses the STIX2 python package to create STIX SDOs, SROs, and SCOs from the applicable data. If there are CWEs associated with the bundle, it queries the OpenCVE API for information on the weakness, then translates that data to STIX as well. It then combines all the data into a STIX bundle and outputs it to a JSON file.", + "laborHours": 91.2, + "languages": [ + "Python" + ], + "name": "Nvd Search To Stix", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/NSTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-01-17", + "metadataLastUpdated": "2025-01-17" + }, + "description": "The Cyber-Informed Engineering Battery Analysis Tool (CIEBAT) leverages the Department of Energy’s Cyber-Informed Engineering to prompt engineering designers and operators through an analysis of the critical functions to be supported by a BESS installation, the criticality of those functions, the impacts of denial, disruption or misuse of those functions within the BESS system, and the mitigations which could best prevent impacts to those functions resulting from cyber attack. Through use of this tool, BESS designers and operators can quickly identify appropriate engineering mitigation opportunities to limit impacts from cyber attack and functions where engineering and operational staff can prioritize and guide the application of cybersecurity protections to best support the resiliency of the system.", + "laborHours": 0.0, + "languages": [], + "name": "Cyber-informed Engineering Battery Analysis Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/CIEBAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-01-22", + "metadataLastUpdated": "2025-01-22" + }, + "description": "The Tracer Analysis Toolbox (TAT) is a stand-alone executable software package that focuses on reservoir monitoring, using changes in concentration of thermally degrading tracers between and injection well and a production well to reflect the temperature-time histories along flow paths through the reservoir. By conducting such tests periodically, the thermal evolution of the flow paths connecting injection wells to production wells can be monitored. Because this approach is sensitive to temperature along the whole path, it can detect changes well before they occur at the distal end of the path (i.e., the production well). 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The FeatherWing is powered through the vehicle's auxiliary power (from cigarette lighter) socket via a micro USB cable. 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Agents in the power system capture components of power generation, transportation, distribution and use (electricity demands, sources, etc.).", + "laborHours": 744.8, + "languages": [ + "Python" + ], + "name": "Interdependent Water And Power Infrastructure Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Integrated_Water_Power_System", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-04", + "metadataLastUpdated": "2025-02-04" + }, + "description": "This codebase was designed to tackle the problem of how to directly utilize experimental omics measurements with a\ngenome scale metabolic model of the organism of the study. 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Our approach is also more\nspecific than those used in Rosetta where we calculate parameters specific for each NCAA rather than assuming\ntransferability.", + "homepageURL": "https://github.com/pnnl/ncap", + "laborHours": 1626.4, + "languages": [], + "name": "NCAP - Non-Canonical Amino Acid Parameterization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://github.com/pnnl/ncap", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://github.com/pnnl/ncap", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2025-02-05", + "metadataLastUpdated": "2025-02-05" + }, + "description": "A plug and play techno-economic analysis (TEA) and lifecycle assessment (LCA) tool was built that could incorporate new projects into the California ARCHES LLC Hydrogen hub, and generate results for the project, as well as the overall hub on an annual basis. The model was first constructed in Microsoft Excel and ArcGIS, but required labor intensive updating and manual decision making regarding the matching of hydrogen supplier and offtaker and estimation of transportation distances and utility sources. The project team converted the Excel model used for the ARCHES LLC hub conceptualization into a highly flexible and nearly completely automated R code. The R code runs the TEA and LCA, as well as provides mapping capabilities that automatically link projects by latitude and longitude to nearby utilities.", + "laborHours": 4484.0, + "languages": [], + "name": "Hydrogen Hub Systems Analysis and Mapping Tool (ParaCraft) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/calgem/Paracraft", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-05", + "metadataLastUpdated": "2025-02-24" + }, + "description": "This technology was developed to address the need for monitoring bird and bat activity at offshore locations for wind\nenergy", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 12844.0, + "languages": [], + "name": "ThermalTracker", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-06", + "metadataLastUpdated": "2025-02-06" + }, + "description": "SAND2025-01123O\nE3SMFC is a software tool that integrates a feedback controller algorithm into the E3SM climate model to regulate sulfur dioxide injection, aiming to achieve specific climate outcomes. The program uses proportional-integral-derivative feedback control to adjusts sulfur dioxide levels in both spatial and temporal dimensions. It will only operate on computers that can run the DOE climate model E3SM. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1769751.2, + "languages": [ + "Fortran", + "Python" + ], + "name": "E3SMFC", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/E3SMFC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-07", + "metadataLastUpdated": "2025-02-07" + }, + "description": "IdPP is a Python package that provides a framework for the curation and analysis of molecular properties from\nmultidimensional mass spectrometry (MS) measurements. The main components of the package are organized around a\nmolecular property database and identification probability analysis", + "laborHours": 349.6, + "languages": [], + "name": "pnnl/idpp_rtp", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/idpp_rtp", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kentpr@ornl.gov" + }, + "date": { + "created": "2025-02-09", + "metadataLastUpdated": "2025-02-10" + }, + "description": "QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support.", + "laborHours": 1334484.0, + "languages": [ + "C++17" + ], + "name": "QMCPACK v4.0.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/license/uoi-ncsa-php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QMCPACK/qmcpack", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v4.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-10", + "metadataLastUpdated": "2025-02-10" + }, + "description": "SAND2025-01223O\n\"Exploring the Transferability of Machine-Learning Models\" is a software tool that trains and tests machine-learning models using simulated data. It includes Python scripts and a Jupyter Notebook to train models to predict material properties from X-ray diffraction profiles. The software provides a template for developing predictive models without requiring proprietary data. It streamlines the model training process and validates model transferability across different datasets. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Code for \"Exploring the Transferability of Machine-Learning Models\"", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2025-02-10", + "metadataLastUpdated": "2025-02-10" + }, + "description": "This work develops the NSBC (non-stationary bias correction) methodology to correct temperature\nprojection bias from E3SM.\nThe NSBC deep learning framework consists of a three-part architecture: an auto-encoder for\ncompressing the spatial information, an LSTM for predicting annual temperature mean, and a U-Net for\ncapturing the residual bias in temperature. The non-stationary bias correction (NSBC) framework can\ncorrect the non-stationarity of the biases of the climate models, which significantly improves the accuracy\nof future temperature prediction and improves the overestimation of extreme high temperatures that many\nexisting bias correction methods suffer from.\nGetting started\n1. Obtain the historical climate simulation and observation data.\nThe E3SM simulation data are available through https://aims2.llnl.gov/search/cmip6/.\nThe pseudo observations, the Geophysical Fluid Dynamics Laboratory (GFDL)-ESM4 model (Krasting et\nal., 2018) are available through https://aims2.llnl.gov/search/cmip6/.\nThe spatial resolution of E3SM and pseudo observation datasets are both regridded to a common 1°\nresolution grid using conservative interpolation. The regridded E3SM and pseudo observation with 1°\nresolution can be found throught ./data/.\n2. Train the Auto-encoder model.\nPython 0-autoencoder.py\n3. Train the LSTM\nPython 1-LSTM.py\n4. Generate the annual mean temperature based on trained LSTM\nPython 2-generate_annual_mean_LSTM.py\n5. Train the U-Net.\nPython 3-unet.py\n6. Evaluation and compared with the baseline\nPython 4_evaluation.py\nIs there a deadline approaching that requires the release of yo", + "laborHours": 684.0, + "languages": [], + "name": "Deep Learning-based Non-Stationary Bias Correction (NSBC)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/NSBC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2025-02-11", + "metadataLastUpdated": "2025-02-11" + }, + "description": "Multi-Level Monte Carlo Methods in Chemical Applications with Lennard-Jones Potentials and other Landscapes with Isolated Singularities", + "laborHours": 1854.4, + "languages": [ + "Python" + ], + "name": "ORNL/MLMC", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/MLMC", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "martins@ornl.gov" + }, + "date": { + "created": "2025-02-13", + "metadataLastUpdated": "2025-02-27" + }, + "description": "The bioenergy.org website is the end product of the Data Sharing Shared Research objective for the Bioenergy Centers. The objective is to Enhance BRC data legacy through the development and use of shared software tools to make previously published datasets more findable and accessible through the Inter-BRC Data Products Portal, and to explore the use of generative AI to assist in the exploration of published datasets. The software repository is released per the license information below.", + "laborHours": 1839.2, + "languages": [ + "JavaScript" + ], + "name": "Bioenergy Research Centers Data Sharing Portal", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/bioenergy-research-centers/bioenergy.org?tab=License-1-ov-file", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bioenergy-research-centers/bioenergy.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-14", + "metadataLastUpdated": "2025-02-24" + }, + "description": "The Aviation Security Screening Optimizer for Risk and Throughput (ASSORT) is designed to assess risk-based\napproaches for passenger screening and checkpoint operations. Additionally, ASSORT is exploring various traveler\ncategories — general, trusted, and trusted-plus — along with different checkpoint screening Concept of Operations\ntailored to each traveler type", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 1200.8, + "languages": [], + "name": "Aviation Security Screening Optimizer for Risk and ThroughputASSORT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "dewittsj@ornl.gov" + }, + "date": { + "created": "2025-02-14", + "metadataLastUpdated": "2025-02-14" + }, + "description": "A key step in almost all scientific endeavors is answering the question: Given this data I already collected, what new data do I expect will yield the most useful information toward my scientific objective? The area of (sequential) experimental design has long been investigating answers to this question, but in recent years techniques from the machine learning subfield of active learning are increasingly applied. Researchers need a simple software tool for active learning applied to experimental design that can easily integrate into their existing workflows.\n\nThis computer code, Dial, provides a microservice in ORNL's INTERSECT ecosystem for active learning applied to experimental design. By being part of the INTERSECT ecosystem, Dial is simple to integrate into any INTERSECT-based workflow. Dial provides multiple backend options, where a backend is an implementation of a specific active learning method. Users can select the backend that performs best for their application. Developers can also add new backends as needed.\n\nAt its core, Dial receives a set of pre-existing measurements and input parameter bounds and then recommends one or more new sets of parameters to measure. Dial also includes interfaces to other microservices in the INTERSECT ecosystem so that it can be incorporated into INTERSECT campaigns.\n\nDial provides a simple, yet powerful interface to convert automated INTERSECT workflows into autonomous workflows that adapt based on the results that are obtained. A shared microservice for active learning prevents duplicated effort by each application team implementing its own adaptive design of experiments tool.", + "laborHours": 668.8, + "languages": [ + "Python" + ], + "name": "Dial", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/INTERSECT-DIAL/dial", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "A River dynamical core for E3SM", + "laborHours": 11400.0, + "languages": [], + "name": "RDycore/RDycore", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rdycore/rdycore", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00929O\nVessel Integrated Turbine Assessment for LCOE (VITAL) is a user-friendly software tool that optimizes the design and control of hydrokinetic turbines deployed from floating vessels. It uses data about rotor blade performance, vessel parameters, tidal data, and cost models. This data is used to determine the best turbine design and control strategies to minimize the levelized cost of energy (LCOE). This application can enhance the efficiency and cost-effectiveness of tidal energy projects. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 653.6, + "languages": [ + "Python" + ], + "name": "Vessel Integrated Turbine Assessment for LCOE (VITAL) v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00927O\nCORRA is a software tool that helps evaluate the costs and benefits of inspecting and repairing wind turbine blades. It combines probabilistic analysis of blade damage with economic analysis to calculate the overall cost of energy production. CORRA can compare different maintenance strategies and their impact on energy costs, which aids in the optimization of wind turbine operations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Cost Optimized Risk and Reliability Assessment Tool v.0.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00898O\nFork of Reflow is a software tool that extends the functionality of NASA Reflow to support relevant projects. It provides automated reasoning support for floating-point roundoff error in numerical computer programs. The tool integrates with Frama-C and the PVS theorem prover to specify and verify program properties, ensuring compliance with specifications through weakest-precondition style analysis. This fork enhances automated reasoning features and enables direct analysis of C code, making it suitable for applications involving small programs with floating-point computations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Haskell", + "PVS", + "C" + ], + "name": "Fork of Reflow v.1.0.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0.2" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00852O\nDecLib is a software library that aids in the study and application of discrete exterior calculus (DEC) in physical systems. It offers a range of models in fluid and solid mechanics that help users understand complex dynamics like shallow water and compressible Euler equations. DecLib preserves the inherent structures of these systems to ensure accurate and reliable simulations. It is a user-friendly application for exploring geometric mechanics and enhancing the study of physical phenomena. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DecLib v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00777O\nHy2.0-eos-lasso is a software tool that derives an equation of state (EOS) using the compound energy formalism (CEF) with LASSO-based parameter fitting. It uses experimental and density functional theory (DFT) data to derive accurate EOS parameters. This tool is designed for users familiar with CEF and aims to facilitate reproducibility in academic research by meeting open-sourcing requirements. Hy2.0-eos-lasso addresses fundamental materials modeling challenges by providing a robust method for EOS parameter fitting. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Hy2.0-eos-lasso v.0.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00731O\nNorma is a software tool that simplifies the testing of algorithms and concepts for coupling and multiphysics, with a focus on solid mechanics and heat conduction. It uses the Finite Element Method to allow researchers to explore and validate new approaches in these domains. Norma provides a flexible and efficient platform for computational experimentation and development. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 8876.8, + "languages": [ + "Julia" + ], + "name": "Norma v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Norma.jl", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "a new urban scale building energy simulation framework", + "laborHours": 28636.8, + "languages": [], + "name": "pnnl/UrbanBEM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/UrbanBEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "GeoCLUSTER is a Python-based web application that provides a collection of interactive methods for streamlining the visualization of the technical and economic modeling of closed-loop geothermal systems.", + "laborHours": 4240.8, + "languages": [], + "name": "pnnl/GeoCLUSTER", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/GeoCLUSTER", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-02-18", + "metadataLastUpdated": "2025-02-18" + }, + "description": "This product includes software developed by Members of the Geant4 Collaboration (http://cern.ch/geant4). The basic principle of ALFRED consists of a k-eigenvalue module in which all generated particles are tracked and all deposited energy is accounted for. An eigenvalue module updates the neutron source after each run based on the neutrons emitted at each fission in the previous run. As a result, the source distribution converges to the fundamental mode of the steady-state eigenvalue problem of the associated critical reactor. 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Additionally, the simulator can trip lines and subsequently update and dispatch AGC signals, running power flow analysis after each tripping event.", + "laborHours": 197.6, + "languages": [ + "Python" + ], + "name": "Electric Grid Simulator For Human Factor Research", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/PSSE_for_Human_factor_research", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-18", + "metadataLastUpdated": "2025-02-18" + }, + "description": "The Lagrangian Droplet cloud microphysics scheme uses high-resolution data of air velocity, temperature, and water\nvapor mixing ratio to drive particle-based simulations of cloud microphysics. The model was first implemented using a\nhigh-resolution Large Eddy Simulation of the Pi Chamber at Michigan Tech, which is small-scale convection chamber the\ngenerates clouds in a laboratory setting", + "laborHours": 820.8, + "languages": [], + "name": "pnnl/Lagrangian-Droplets", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Lagrangian-Droplets", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-18", + "metadataLastUpdated": "2025-02-18" + }, + "description": "Network Optimization and Causal Analysis of Perturb-seq (NOCAP) is a software package for causal inference of gene\nregulation networks using data from perturb-seq.", + "laborHours": 1003.2, + "languages": [], + "name": "CRISPR-CARB/nocap", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/crispr-carb/nocap", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-19", + "metadataLastUpdated": "2025-02-20" + }, + "description": "VOLTTRON Distributed Control System Platform", + "laborHours": 196657.6, + "languages": [], + "name": "VOLTTRON/volttron Version 9", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "VOLTTRON v. 9" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-02-20", + "metadataLastUpdated": "2025-02-20" + }, + "description": "NodeMan is a command line tool to manage nodes in an HPC cluster. At it's core, it is an extensible framework composed of bash scripting and GNU parallel. HPC System Administrator will find it useful in that it encapsulates desired functions and allows them to be assembled in a way familiar to administrators - through pipes. In fact, NodeMan functions can work with common command line tools as long as they use stdin/stdout. System Administrators can construct moderately complex logic and filtering on a compact command line that would normally require a substantial shell script. In the spirit of clush and pdsh, it is able to run commands remotely on nodes. Additionally, NodeMan is more flexible. For example, it can interact with IPMI and naturally processes node lists for orchestrating different tools. The library of useful pre-built functions is growing. System administrators can easily create new functions and make it their own.", + "laborHours": 440.8, + "languages": [], + "name": "Nodeman: A Node Management Tool For Hpc Clusters", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/nodeman", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-20", + "metadataLastUpdated": "2025-02-20" + }, + "description": "An automated workflow and introduces new approaches to curate existing cybersecurity\nknowledge from multiple sources. It also proposes AI/ML-based methods to infer knowledge alignments across different\nrepositories.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 608.0, + "languages": [], + "name": "Cyber Knowledge Alignment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-20", + "metadataLastUpdated": "2025-02-20" + }, + "description": "We propose a generalized framework which performs an optimal partitioning of a limited budget into various\norganizational sectors in order to improve the cybersecurity of a smart device or component in the Cyber Physical Energy\nSystem (CPS). The framework identifies the adversarial threats and possible attack sequences which can be performed to\nexploit cyber vulnerabilities of the component. Thereafter, we formulate an Mixed Integer Linear Programming (MILP)\noptimization problem which aims to evaluate the optimal budget partitions in order to minimize the number of highly likely\nattack sequences. Though we provide results for using the framework in CPES, the proposed methodology can be\nextended for multiple domains with a set of known adversarial and mitigation actions.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 3526.4, + "languages": [], + "name": "Optimal Mitigation Planning For Adversarial Scenarios", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-20", + "metadataLastUpdated": "2025-02-20" + }, + "description": "Underwater video analysis software.", + "laborHours": 13771.2, + "languages": [], + "name": "pnnl/EyeSea", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/EyeSea", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-20", + "metadataLastUpdated": "2025-02-20" + }, + "description": "This repository contains the code necessary to process any new data for the Superfund Research Program Analytics Portal.", + "laborHours": 2447.2, + "languages": [], + "name": "PNNL-CompBio/srpAnalytics", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/srpAnalytics", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "sullivanhe@ornl.gov" + }, + "date": { + "created": "2025-02-21", + "metadataLastUpdated": "2025-02-21" + }, + "description": "This is the official implementation of ResSR [1]. ResSR is a computationally efficient MSI-SR method that achieves high-quality reconstructions by using a closed-form spectral decomposition along with a spatial residual correction. ResSR applies singular value decomposition to identify correlations across spectral bands, uses pixel-wise computation to upsample the MSI, and then applies a residual correction process to correct the high-spatial frequency components of the upsampled bands. While ResSR is formulated as the solution to a spatially-coupled optimization problem, we use pixel-wise regularization and derive an approximate closed-form solution, resulting in a pixel-wise algorithm with a dramatic reduction in computation that achieves state-of-the-art reconstructions.\n\n[1] Duba-Sullivan, H., Reid, E. J., Voisin, S., Bouman, C. A., & Buzzard, G. T. (2024). ResSR: A Computationally Efficient Residual Approach to Super-Resolving Multispectral Images. arXiv preprint arXiv:2408.13225.", + "laborHours": 532.0, + "languages": [ + "Python" + ], + "name": "hdsullivan/ResSR", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hdsullivan/ResSR", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2025-02-23", + "metadataLastUpdated": "2025-02-23" + }, + "description": "SF-25-008 This software optimizes quantum circuits using a two-step process. The first step, Clifford Extraction, moves the Clifford gates to the end of the circuit and includes circuit\noptimizations. The second step, Clifford Absorption, then addresses these extracted gates on a classical computer. By reducing the number of gates that need to run on the quantum device, the software achieves a significantly lower gate count.", + "laborHours": 66956.0, + "languages": [], + "name": "QuCLEAR", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/revilooliver/QuCLEAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-24", + "metadataLastUpdated": "2025-02-24" + }, + "description": "BioPAC is the Biological and other Particles in Aerosols Classifier. It is a software to assist in the accurate measurement\nand identification of primary biological aerosol particles, which play a pivotal role in mediating the reciprocal relationships\nbetween biological systems and atmospheric conditions.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 334.4, + "languages": [], + "name": "BioPac", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-02-24", + "metadataLastUpdated": "2025-03-11" + }, + "description": "GeoGridFusion facilitates the usage and storage of gridded geospatial satellite data by users outside of the National Renewable Lab (NREL), particularly those without access to high-performance computing (HPC) resources. This tool builds on work done by the PVDegradationTools project for DuraMAT, with the goal of making our advancements from this project widely accessible.\n\nThis repo contains utilities to allow for the storage of user downloaded geospatial weather data by providing a local datastore for storage and spatial queries, supporting large-scale analyses without the need for HPC resources.", + "laborHours": 9393.6, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "GeoGridFusion (Open-Source Geospatial Toolkit for Solar Data Integration​) [SWR-25-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GeoGridFusion", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-25", + "metadataLastUpdated": "2025-02-25" + }, + "description": "The FEMP Cyber Security Arsenal is a family of cyber security tools for the federal facility owners and operators. Using these tools, facility owners can evaluate their overall cybersecurity posture. These tools are web-based front-end tools. The tools are meant to help federal owners and operators to evaluate their overall cybersecurity posture. These tools are developed based on the NIST Cybersecurity framework, risk management framework, and DOE C2M2 architectures. Version 3 provides significant updates and features in ten areas", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 126038.4, + "languages": [], + "name": "FEMP Cybersecurity Arsenal", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "3" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-25", + "metadataLastUpdated": "2025-02-25" + }, + "description": "A content repository for the life cycle inventory (LCI) rooftop unit (RTU) data collection template, a data collection template for the linked openLCA model Life Cycle Assessment (LCA) for automated Environmental Product Declaration (EPD) results generation.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Rooftop-Unit-LCI-Template", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Rooftop-Unit-LCI-Template", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "coellopereea@ornl.gov" + }, + "date": { + "created": "2025-02-25", + "metadataLastUpdated": "2025-02-25" + }, + "description": "An utility to benchmark the quality of an HPC and Quantum Computers integration. The benchmark allows the definition of a set of users for which a set of configurable quantum applications will be randomly selected. Example of currently supported quantum applications: VQE, PyMatching, RB. Users can create custom applications and use them together with the core applications. QStone generates different portable files (.tar.gz), each supporting a different user and a different scheduler (currently supporting: slurm, lsf, bare_metal). During execution of the benchmark, QStone gathers information on each steps of the applications, allowing investigations on bottlenecks and/or resource constraints at the interface between Quantum and HPC.", + "laborHours": 1611.2, + "languages": [ + "Python" + ], + "name": "QStone", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/riverlane/QStone", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.2.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-27", + "metadataLastUpdated": "2025-03-04" + }, + "description": "SAND2025-00659O\nMAPLE is a software tool that uses epigenomic data to predict gene expression. MAPLE uses a set of epigenomic modifications to determine the effect on gene expression in a specific subset of species. The algorithm can be trained on additional species and epigenomic modifications, enhancing its predictive capabilities. EAGLE employs a hybrid neural network architecture, featuring a convolutional front-end and a multi-head attention layer, to process pre-processed signal data as input. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 243.2, + "languages": [ + "Python" + ], + "name": "MAPLE v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MAPLE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2025-02-27", + "metadataLastUpdated": "2025-02-27" + }, + "description": "Simple Julia scrips for solving AC power flow, AC optimal power flow, and security-constrained AC\noptimal power flow.\nThese scripts are intended for experimentation with different (possibly, new) methods, formulations, and\nsettings for solving these power system problem. Their implementation, therefore, intentionally avoids\nexcessive encapsulation, which makes other packages difficult to modify by non-developers.", + "laborHours": 1307.2, + "languages": [], + "name": "Exascale Julia Grid Optimization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/exajugo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-03-05", + "metadataLastUpdated": "2025-03-05" + }, + "description": "HydroBoost is the most realistic revenue optimization tool for the hybridization of hydropower and battery energy storage systems to date. The innovative representation of how operators actually schedule hydropower in practice results in more realistic predictions of revenue and operations. Unlike other optimization tools, HydroBoost generates forecast energy prices with uncertainty to use in the optimization. This allows HydroBoost to give users a range of potential revenue with an upper bound using the perfect foresight pricing and a lower bound using a naive persistence forecast model. Additional forecast can be generated and used in the optimization, such as additive models, random forest, and neural networks to give further insight into potential revenue. \n\nHydroBoost has been designed to be applicable for both run-of-river and reservoir storage sites. The primary focus is on the day-ahead market and requires year-long data with an hour time-step. All time-series input and constraints are contained in an Excel worksheet for convince. The user will run the forecasting generation first with a Python script to give the optimization model the necessary requirements. Next the optimization is ran using Julia and results are generated and stored into a directory as csv files.\n\nHydroBoost includes an additional module to generate figures based on the results of the optimization simulation. The results help analyze the results and users to draw insights into how the hydro and battery systems are operated and the revenue each is producing. Additionally, the difference between the perfect foresight model and models that include forecast can easily be inspected.", + "laborHours": 1322.4, + "languages": [ + "Julia", + "Python" + ], + "name": "Hydroboost", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HydroBoost", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-03-05", + "metadataLastUpdated": "2025-03-05" + }, + "description": "This was written in React, using Typescript, Vite, and Material UI", + "laborHours": 10336.0, + "languages": [ + "JavaScript", + "TypeScript" + ], + "name": "Lbl/bctc Ldrd Graphical User Interface", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Solvent_Extraction_Experiment_GUI", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "khana@ornl.gov" + }, + "date": { + "created": "2025-03-06", + "metadataLastUpdated": "2025-03-07" + }, + "description": "HVAC is a high-performance caching system designed for large-scale AI training workloads.", + "laborHours": 684.0, + "languages": [ + "C++", + "C" + ], + "name": "High Velocity AI Cache (HVAC)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/akhanaornl/hvac.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "The Graph-based Learning of Aerosol Dynamics (GLAD) package implements a Graph Network-based Simulator (GNS), a machine learning framework that has been used to simulate particle-based fluid dynamics models", + "laborHours": 1079.2, + "languages": [], + "name": "pnnl/glad", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/glad", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Natural products have provided a rich reservoir of beneficial compounds in public health including antibiotics, therapeutics, and immunosuppressants. These natural products are synthesized by enzymes encoded by Biosynthetic Gene Clusters (BGCs), clusters of co-localized biosynthetic genes. Computational detection of BGCs has become a crucial step in natural product discovery. While this process has been facilitated in bacterial and fungal organisms thanks to the currently available tools (e.g., antiSMASH), a large spectrum of eukaryotic organisms have been neglected by these existing tools due to the scarcity and incompleteness of genome annotation resources. Here, we introduce Biosynthetic Gene cluster Extensive Search Tool (BiGEST) to provide an extensive annotation-free search for BGCs in diverse eukaryotic organisms. As a result, BiGEST uncovers eukaryotic BGCs that could be undetected by other BGC detection tools.", + "laborHours": 5639.2, + "languages": [], + "name": "BiGEST", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/BiGEST", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "The software being developed for this project has two mains aims. First, a Bayesian Model Calibration (BMC) procedure is being developed to calibrate a spallation model that simulates protons hitting a spacecraft orbiting earth to real data. The procedure will be developed for general data (there is no data release requested as part of this code release). Second, an inverse physics modeling task is being undertaken to map the number of resulting neutrons observed from this process to the expected number of protons that hit the model. This second task is of statistical interest; to publish on it, the code will need to be open source.", + "laborHours": 197.6, + "languages": [], + "name": "Code Release for “Unlocking Extreme Space Weather through Advanced Modeling of Legacy Vela Spacecraft” ER", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vela_sep", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Libra is a Python package that extends support of its parent package, SQLAlchemy. Libra’s primary functionality supports the dynamic creation of object-oriented analogs of SQL tables from a variety of user-defined, text-based schema definition formats and provides quality control and analysis tools and methods", + "laborHours": 501.6, + "languages": [], + "name": "Libra", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Seismoacoustics/libra", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Latent Feature Attacks on Non-negative Matrix Factorization", + "laborHours": 1003.2, + "languages": [], + "name": "LaFA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/LaFA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Analyze virus genetic sequences to identify lineages that are spreading especially rapidly.", + "laborHours": 121.6, + "languages": [], + "name": "Graph theory approach to estimate the rate of SARS-CoV-2 lineage spread from early genetic sequence data", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ruianke/CoV2-GenomicGraphTheory-PCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-12" + }, + "description": "Software, Documentation, Tutorials, Testing data, Example data for processing, analysis, filtering, querying, visualization and otherwise transforming genomic data for scientific analysis and discovery.", + "laborHours": 45.6, + "languages": [], + "name": "epicsuite(EAS)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/epicsuite/epicsuite-readthedocs", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-12" + }, + "description": "Seismic amplitudes offer vital information about explosion source characteristics, including discrimination and yield estimation. To take advantage of this, we developed an interactive Python package to measure, control data quality, generate broad area propagation models and perform discrimination and estimate yield. Propagation models are essential in support of transportable yield and broad area discrimination. The key benefit of this package will be its ability to continuously integrate data and new techniques. The AmpSuite framework will provide standardized, repeatable, and accurate model generation and characterization routines. The capability is crucial for monitoring agencies tasked with rapid and high-quality seismic event characterization.\nThe AmpSuite software includes a series of independent modules to perform:\n• Direct Phase Amplitude Measurement and Storage\n• Coda Envelope Measurement and Storage\n• Data Quality Control\n• New Propagation Model Developments\n• Seismic Discrimination and Analysis\n• Yield Estimation\nand supporting utility software. The AmpSuite software provides comprehensive solutions for monitoring agencies seeking to optimize model generation and event analysis within a contemporary Python framework. Stakeholders (AFTAC) have begun to move towards the Python language for scientific analysis as a new workforce emerges.", + "laborHours": 440.8, + "languages": [], + "name": "AmpSuite", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/AmpSuite", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "We developed the atomistic-coarse-grained multiscale MD simulation method in the OpenMM simulation package by iterating between the all-atom (AA) and coarse-grained (CG) MD simulations to enhance the sampling of biomolecular conformations. As the free energy surfaces are flattened during CG MD simulations, we can accelerate the transitions between different low-energy conformations. The AA-CG-AA cycles are repeated, facilitating the accelerated sampling of biomolecular conformations at a CG level, while the finer atomistic interactions are refined with AA simulators.", + "laborHours": 304.0, + "languages": [], + "name": "Multiscale Molecular Dynamics Simulations: Accelerating Conformational Sampling of Biomolecular Systems by Iterating All-Atom and Coarse-Grained Simulations", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/iMMD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Repository of the codes developed for the paper titled \"Liouville Flow Importance Sampler\"", + "laborHours": 775.2, + "languages": [], + "name": "LFIS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/LFIS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "VerifyIO is a tool designed for verifying I/O consistency semantics in High-Performance Computing (HPC)\napplications. It addresses the challenges of ensuring correctness and portability across different I/O\nconsistency models, such as POSIX, Commit, Session, and MPI-IO. By analyzing execution traces,\ndetecting conflicts, and verifying synchronization adherence, VerifyIO provides actionable insights for both\napplication developers and I/O library designers.", + "laborHours": 760.0, + "languages": [], + "name": "VerifyIO: Verifying Adherence to Parallel I/O Consistency Semantics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wangvsa/VerifyIO", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "peless@ornl.gov" + }, + "date": { + "created": "2025-03-10", + "metadataLastUpdated": "2025-03-10" + }, + "description": "Modeling framework for power systems simulations and analysis.", + "laborHours": 10320.8, + "languages": [ + "C++" + ], + "name": "GridKit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/GridKit", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-12", + "metadataLastUpdated": "2025-03-12" + }, + "description": "P. putida KT2440 and related engineered strains.", + "laborHours": 232043.2, + "languages": [], + "name": "CRISPR-CARB/Pseudomonas_putida_KT2440_GEM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CRISPR-CARB/Pseudomonas_putida_KT2440_GEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "mtatonett@bnl.gov" + }, + "date": { + "created": "2025-03-13", + "metadataLastUpdated": "2025-03-13" + }, + "description": "It is a pre-trained model for processing blurred and noisy tomographic reconstruction taken from a fast fly-scan.", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "ultra_fast_tomo", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gmysage/ultra_fast_tomo", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-03-13", + "metadataLastUpdated": "2025-03-13" + }, + "description": "Ampworks is a collection of tools designed to process experimental battery data with a focus on model-relevant analyses. It currently provides functions for incremental capacity analysis and GITT data processing, helping extract key properties for life and physics-based models (e.g., SPM and P2D). Some tools, like the incremental capacity analysis module, also include graphical user interfaces for ease of use.\n\nhttps://github.com/NREL/ampworks/\nhttps://pypi.org/project/ampworks/", + "laborHours": 2082.4, + "languages": [ + "Python" + ], + "name": "ampworks: Battery analysis tools in Python [SWR-25-39]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ampworks", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-14", + "metadataLastUpdated": "2025-03-14" + }, + "description": "genome-scale model of Rhodobacter sphaeroides and flux analysis", + "laborHours": 265772.0, + "languages": [], + "name": "CRISPR-CARB/Rhodobacter_sphaeroides_GEMs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CRISPR-CARB/Rhodobacter_sphaeroides_GEMs", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "burtscher@txstate.edu" + }, + "date": { + "created": "2025-03-14", + "metadataLastUpdated": "2025-03-14" + }, + "description": "This repository contains the code and related scripts for 4 high-performance lossless compression algorithms for single- and double-precision floating-point data. They are named SPratio, SPspeed, DPratio, and DPspeed. The compressors work on CPUs and GPUs and deliver state-of-the-art throughputs and compression ratios.", + "laborHours": 4453.6, + "languages": [], + "name": "FPcompress", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/burtscher/FPcompress", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "burtscher@txstate.edu" + }, + "date": { + "created": "2025-03-14", + "metadataLastUpdated": "2025-03-14" + }, + "description": "This repository holds the PFPL code. PFPL is a guaranteed-error-bound lossy compressor/decompressor that produces bit-for-bit identical files on CPUs and GPUs. It supports absolute (ABS), relative (REL), and normalized-absolute (NOA) point-wise error bounds for single- and double-precision inputs in IEEE 754 binary format. It yields good compression ratios at high throughputs.", + "laborHours": 4316.8, + "languages": [], + "name": "PFPL", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/burtscher/PFPL", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-03-17", + "metadataLastUpdated": "2025-03-17" + }, + "description": "FuelLib is a library that utilizes the group contribution method (GCM) for calculating thermodynamic properties of hydro-carbon jet fuels.\n\nFuelLib utilizes the tables and functions of the GCM as proposed by Constantinou and Gani (1994) and Constantinou, Gani and O'Connel (1995), with additional physical properties discussed in Govindaraju & Ihme (2016). The code is based on Pavan B. Govindaraju's Matlab implementation of the GCM, and has been expanded to include additional thermodynamic properties and mixture properties. The fuel library contains gas chromatography (GC x GC) data for a variety of fuels ranging from simple single component fuels to complex jet fuels. The GC x GC data for POSF jet fuels comes from Edwards (2020).", + "laborHours": 532.0, + "languages": [ + "Python" + ], + "name": "FuelLib (Fuel Library) [SWR-25-26]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/FuelLib", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "congg@ornl.gov" + }, + "date": { + "created": "2025-03-17", + "metadataLastUpdated": "2025-03-17" + }, + "description": "We propose TransPlatformer for translating toxicogenomics from one platform to another. Transcriptomic profiling has evolved through multiple generations of technology, from microarrays (e.g., Affymetrix, CodeLink) to more recent high-throughput sequencing and targeted panels such as S1500+. Microarrays, which dominated gene expression studies in the early 2000s, provided affordable and high-throughput transcript quantification but suffered from cross-hybridization issues and limited dynamic range . RNA-Seq, introduced in the late 2000s, revolutionized transcriptomics by enabling unbiased and comprehensive gene expression analysis, albeit at higher costs and computational demands .\n\nDespite advances, many studies rely on historical microarray data, necessitating the translation of legacy data into modern platforms to ensure continuity and comparability. This translation is complicated by factors such as platform-specific probe design, differences in transcript coverage, and batch effects . Existing methods for cross-platform mapping include statistical normalization, machine learning models, and biological anchoring approaches.\n\nThe ability to translate transcriptomic data between platforms has broad implications, including enhanced meta-analyses, improved toxicological modeling, and better integration of historical datasets with contemporary research. TransPlatformer seeks to contribute to this effort by evaluating translation methodologies and proposing novel strategies to improve cross-platform gene expression harmonization.\n\nIn this repository there are code examples for TransPlatformer implementation", + "laborHours": 592.8, + "languages": [ + "Python" + ], + "name": "TransPlatformer", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/goooopy/TransPlatformer", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2025-03-17", + "metadataLastUpdated": "2025-03-17" + }, + "description": "Sigma is a header-only C++ library for uncertainty propagation throughout mathematical operations on floating point values.", + "laborHours": 1231.2, + "languages": [ + "C++", + "GCC 12-14", + "Clang 14", + "MSVC" + ], + "name": "QCUncertainty/sigma", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QCUncertainty/sigma", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-19", + "metadataLastUpdated": "2025-03-19" + }, + "description": "MUPPET is a tool for OpenMP programs that identifies program modifications, called mutations, aimed at\nimproving program performance. Existing performance optimization techniques, including profiling-based\nand auto-tuning techniques, fail to indicate program modifications at the source level thus preventing their\nportability across compilers. MUPPET aims to help HPC developers reason about performance defects\nand missed opportunities to improve performance at the source code level.", + "laborHours": 12570.4, + "languages": [], + "name": "MUPPET: An automated OpenMP mutation testing framework for performance optimization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MUPPET", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "gonzalesjj@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "Mind the Gap is an algorithm for detecting areas of missing data in building footprints.", + "laborHours": 440.8, + "languages": [ + "Python" + ], + "name": "ORNL/mind_the_gap", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/mind_the_gap/blob/main/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/mind_the_gap", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "This package is part of the Likeness Python toolkit, which generates high-fidelity synthetic populations for human dynamics modeling. The LiveLike package provides a high-level wrapper for generating synthetic populations via Census APIs based on the American Community Survey (ACS) 5-Year Estimates. Synthetic populations are virtual representations of people and households produced for small census areas (block groups, tracts) and can be attributed by a variety of demographic, economic, social, worker, student, mobility, housing, health, and communication characteristics found in the ACS.", + "laborHours": 4636.0, + "languages": [ + "Python" + ], + "name": "LiveLike", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/livelike/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/livelike", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.4.7" + }, + { + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "The PyMEDM package is a Python-native port of Penalized-Maximum Entropy Dasymetric Modeling (P-MEDM) method. While the original implementation of P-MEDM consists of an R interface over a model written in C++, PyMEDM combines both capabilities in a common language that interfaces with other utilities in the Likeness stack. PyMEDM is also GPU-enabled via JAX , which supports High-Performance Computing (HPC) applications.", + "laborHours": 1580.8, + "languages": [ + "Python" + ], + "name": "PyMEDM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/pymedm/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/pymedm", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "2.2.3" + }, + { + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "This package is part of the Likeness Python toolkit, which generates high-fidelity synthetic populations for human dynamics modeling. The PMEDM-Legacy package provides a Python interface for using the original implementation of Penalized-Maximum Entropy Dasymetric Modeling (P-MEDM) method, written in R/C++, for statistically matching population survey data from the American Community Survey's Public-Use Microdata Sample (PUMS) to sub-county spatial scales. To achieve this, it interfaces with a companion R package in the Likeness stack, PMEDMrcppPal, via the rpy2 Python-R bridge.", + "laborHours": 486.4, + "languages": [ + "Python" + ], + "name": "PMEDM-Legacy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/pmedm-legacy/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/pmedm-legacy", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.5" + }, + { + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "This package is part of the Likeness Python toolkit, which generates high-fidelity synthetic populations for human dynamics modeling. It primarily supports the PMEDM-Legacy package, which provides a Python interface for using the original implementation of Penalized-Maximum Entropy Dasymetric Modeling (P-MEDM) method, written in R/C++, for statistically matching population survey data from the American Community Survey's Public-Use Microdata Sample (PUMS) to sub-county spatial scales. Model inputs specified in the Python environment are converted to R variables and passed to the PMEDMrcpp model with PMEDMrcppPal.", + "laborHours": 91.2, + "languages": [ + "R" + ], + "name": "PMEDMrcpp-Pal", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/pmedmrcpp-pal/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/pmedmrcpp-pal", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "This package is part of the Likeness Python toolkit, which generates high-fidelity synthetic populations for human dynamics modeling.", + "laborHours": 577.6, + "languages": [ + "Python" + ], + "name": "Likeness-Vitals", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/likeness-vitals/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/likeness-vitals", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.4.3" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-21", + "metadataLastUpdated": "2025-03-21" + }, + "description": "This is a tool for long term prognosis of redox flow battery parameter degradation which uses Transformer-based deep\nlearning models for time series forecasting which was developed as part of the ROVI project.", + "laborHours": 19592.8, + "languages": [], + "name": "pnnl/battery-degradation-prognosis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/battery-degradation-prognosis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-21", + "metadataLastUpdated": "2025-03-21" + }, + "description": "repligit will be a python library which implements the git transfer protocol allowing git repositories to be\nmirrored between two locations without storing state locally.", + "laborHours": 152.0, + "languages": [], + "name": "repligit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/repligit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-24", + "metadataLastUpdated": "2025-03-24" + }, + "description": "Using the genome annotation as input, Pathway-tools generates a database containing all the information that can be\ninferred from the genome. The Pathway/Genome database (PGDB) can subsequently be curated manually\nLicensed under the CC-BY-4.0 license", + "laborHours": 106.4, + "languages": [], + "name": "pnnl-predictive-phenomics/csc052cyc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl-predictive-phenomics/csc052cyc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc052cyc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-24", + "metadataLastUpdated": "2025-03-24" + }, + "description": "Using the genome annotation as input, Pathway-tools generates a database containing all the information that can be\ninferred from the genome. The Pathway/Genome database (PGDB) can subsequently be curated manually", + "laborHours": 136.8, + "languages": [], + "name": "pnnl-predictive-phenomics/csc040cyc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl-predictive-phenomics/csc040cyc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc040cyc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-24", + "metadataLastUpdated": "2025-03-24" + }, + "description": "Organism-specific Pathway/Genome databases enable the analysis, visualization and interrogation of metabolism,\nregulation, and genetics.\nLicensed under the CC-BY-4.0 license", + "laborHours": 212.8, + "languages": [], + "name": "pnnl-predictive-phenomics/csc031cyc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl-predictive-phenomics/csc031cyc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc031cyc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-24", + "metadataLastUpdated": "2025-03-24" + }, + "description": "Using the genome annotation as input, Pathway-tools generates a database containing all the information that can be\ninferred from the genome. The Pathway/Genome database (PGDB) can subsequently be curated manually.\nLicensed under the CC-BY-4.0 license", + "laborHours": 76.0, + "languages": [], + "name": "pnnl-predictive-phenomics/csc009cyc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl-predictive-phenomics/csc009cyc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc009cyc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-24", + "metadataLastUpdated": "2025-03-24" + }, + "description": "Organism-specific Pathway/Genome databases enable the analysis, visualization and interrogation of metabolism,\nregulation, and genetics.\nLicensed under the CC-BY-4.0 license", + "laborHours": 121.6, + "languages": [], + "name": "pnnl-predictive-phenomics/csc043cyc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl-predictive-phenomics/csc043cyc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc043cyc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "haunab@ornl.gov" + }, + "date": { + "created": "2025-03-25", + "metadataLastUpdated": "2025-04-22" + }, + "description": "A CLI for interacting with Klipper components.", + "laborHours": 45.6, + "languages": [ + "Python" + ], + "name": "klipperctl", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Laikulo/klipperctl.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-25", + "metadataLastUpdated": "2025-03-25" + }, + "description": "In this work, we detail two uncertainty quantification (UQ) methods that provide complementary information. Readout\nensembling, by finetuning only the readout layers of an ensemble of foundation models, provides information about model\nuncertainty. Amending the final readout layer to predict upper and lower quantiles replaces point predictions with\ndistributional predictions, which provide information about uncertainty within the underlying training data. We\ndemonstrate our approach with the MACE-MP-0 model, applying UQ to both the foundation model and a series of finetuned\nmodels. The uncertainties produced by the ensemble and quantile methods are demonstrated to be distinct measures by\nwhich the quality of the NNP output can be judged.", + "laborHours": 33485.6, + "languages": [], + "name": "pnnl/SNAP", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/snap", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gautama@ornl.gov" + }, + "date": { + "created": "2025-03-26", + "metadataLastUpdated": "2025-03-26" + }, + "description": "NeuroCoreX is an open-source codebase that enables the implementation of brain-inspired, energy-efficient neuromorphic computing models on FPGA hardware. Designed to support real-time learning, all-to-all neural connectivity, and flexible network architectures, NeuroCoreX offers a hands-on, accessible platform for exploring biologically inspired models of neural computation. It empowers researchers, students, and developers to implement and experiment with adaptive systems—bringing the power of neuromorphic computing to a broader community through a low-cost, scalable, and reconfigurable framework.", + "laborHours": 0.0, + "languages": [ + "VHDL" + ], + "name": "NeuroCoreX: Brain-Inspired Computing from Code to Circuit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/NeuroCoreX", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-03-26", + "metadataLastUpdated": "2025-03-26" + }, + "description": "Urban heat is a growing concern, particularly in dense metropolitan areas where high temperatures increase the risk of heat-related illness and drive energy expenses for cooling. Estimating the effects of urban heat remains a challenge due to limitations in describing the built environment, computational constraints, and the need for high-resolution data. This software presents open-source, computationally efficient machine learning methods that enhance the accuracy of urban temperature estimates compared to historical reanalysis data. Models trained using this software have been applied to urban microclimates in Los Angeles and Seattle showing greater accuracy and less bias when compared to low-resolution reanalysis datasets like ERA5 and even when compared to high-resolution mesoscale numerical weather models like WRF with an urban canopy model. Initial findings highlight how machine learning can support urban heat resilience planning by enabling improved assessments of local heat islands, mitigation strategies, and their energy implications.\n\nThis software is an extension of (sup3r).\n\nThis software supports the following publication:\n\nBuster, Grant, et al. Tackling Extreme Urban Heat: A Machine Learning Approach to Assess the Impacts of Climate Change and the Efficacy of Climate Adaptation Strategies in Urban Microclimates. arXiv:2411.05952, arXiv, 8 Nov. 2024. arXiv.org, https://doi.org/10.48550/arXiv.2411.05952.\n\nAnd has related public data records available at:\n\nBuster, Grant, Cox, Jordan, Benton, Brandon, and King, Ryan. Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI). United States: N.p., 16 Oct, 2024. Web. https://data.openei.org/submissions/6220.", + "laborHours": 775.2, + "languages": [ + "Python" + ], + "name": "sup3ruhi (Super Resolution for Renewable Resource Data and Urban Heat Islands) [SWR-25-05]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/sup3ruhi", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dietzdt@ornl.gov" + }, + "date": { + "created": "2025-03-27", + "metadataLastUpdated": "2025-03-28" + }, + "description": "Acceptance and regression testing of a High Performance Computing (HPC) system requires an automated and reproducible framework and tool for running and logging results. Manually running tests across a system is labor intensive and prone to reproducibility errors. The OLCF Test Harness (OTH) provides a framework in which to document required tests for a HPC system. The OTH then provides tools to execute and log results of these tests in an automated fashion.", + "laborHours": 22496.0, + "languages": [ + "Python" + ], + "name": "OLCF Test Harness", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/olcf/olcf-test-harness/blob/devel/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/olcf-test-harness", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-31", + "metadataLastUpdated": "2025-03-31" + }, + "description": "This software provides methods and functions for training deep image classification models based on the\nprinciple of anchoring. It features a user-friendly PyTorch wrapper that facilitates the easy conversion of\nany model into an anchored model. The software supports various standard datasets and includes scripts\nfor conducting evaluations. Developed with PyTorch, it is compatible with common neural network\narchitectures used for image data. Additionally, it offers tools for computing evaluation metrics to assess\nmodel performance.", + "laborHours": 2872.8, + "languages": [], + "name": "Anchoring", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/anchoring", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-31", + "metadataLastUpdated": "2025-03-31" + }, + "description": "The Program for Climate Model Diagnosis & Intercomparison (PCMDI) Metrics Package (PMP) is used to\nprovide \"quick-look\" objective comparisons of Earth System Models (ESMs) with one another and\navailable observations. The PMP provides a diverse suite of analysis utilities each of which produce\nsummary statistics that gauge the consistency between climate model simulations and available\nobservations. The primary application of the PMP is to evaluate simulations from the Coupled Model\nIntercomparison Project (CMIP). It can also be used to provide objective performance summaries during\nthe model development process as well as selected research purposes.", + "laborHours": 173112.8, + "languages": [], + "name": "PCMDI Metrics Package", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PCMDI/pcmdi_metrics", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.8.2" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-31", + "metadataLastUpdated": "2025-03-31" + }, + "description": "This code is used to conduct topology optimization of a general full cell energy storage device. The anode\nand cathode designs are optimized simultaneously, allowing possibility for interdigitation. The charging\nmechanism can consist of both electric double layer charging (EDLC) typically observed in capacitors and\nredox reaction typically observed in batteries.", + "laborHours": 942.4, + "languages": [], + "name": "Topology Optimization for Full-Cell Electrochemical Energy Storage Device", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TOPEFC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-02", + "metadataLastUpdated": "2025-04-15" + }, + "description": "This repository contains code and data for performing a siting analysis of long-duration energy storage (LDES) in the 5-bus and RTS systems using the Sienna suite developed by the National Renewable Energy Laboratory for production cost modeling (PCM). 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By clustering similar documents together, this Windows-based software unveils common themes and reveals hidden relationships within the collection. IN-SPIRE™ allows analysts to spend more time exploring the information they find most relevant and less time sifting through the masses of irrelevant documents.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 3747666.4, + "languages": [], + "name": "IN-SPIRE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "5" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-15", + "metadataLastUpdated": "2025-04-15" + }, + "description": "INFRA-COMPASS is an innovative software tool that harnesses the power of Large Language Models (LLMs) to automate the compilation and continued maintenance of an inventory of state and local codes and ordinances pertaining to energy infrastructure.", + "laborHours": 5274.4, + "languages": [ + "Python", + "Rust" + ], + "name": "INFRA-COMPASS (Infrastructure Continuous Ordinance Mapping for Planning and Siting Systems) [SWR-25-62]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/COMPASS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v.0.3.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-15", + "metadataLastUpdated": "2025-04-15" + }, + "description": "A domain-aware generative framework that takes 3D coordinates of the molecule and scaffold as an input\nand generates 3D coordinates of novel therapeutic candidates as an output while preserving the desired scaffolds. 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This code can be used to produce vision\nlanguage models (VLMs), like LLaVA, with enhanced robustness to adversarial attacks (e.g. jailbreaks).", + "laborHours": 225188.0, + "languages": [], + "name": "Double Visual Defense", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zw615/Double_Visual_Defense", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "prokopenkoav@ornl.gov" + }, + "date": { + "created": "2025-04-16", + "metadataLastUpdated": "2025-04-17" + }, + "description": "ArborX library tackles a problem of efficiently finding geometric objects that are close in space. 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This automation includes incorporation of a\nMachine Learning component that will provide feedback analysis and experiment modification in a fully hands-free\nmanner. 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BatteryOSv1 was the first Python implementation; BatteryOSv2 was the first C++ implementation; BatteryOSv3 is the final, cleaned-up C++ implementation.", + "laborHours": 12859.2, + "languages": [], + "name": "BatteryOS", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Stanford-New-Energy-Systems/BatteryOS", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + } + ], + "Department of Health and Human Services": [ + { + "name": "pillbox_docs", + "description": "Pillbox at the National Library of Medicine", + "status": "Development", + "permissions": { + "usageType": "openSource", + "licenses": null + }, + "organization": "Department of Health and Human Services", + "homepageURL": "https://github.com/HHS/pillbox_docs", + "downloadURL": 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open-source DMS (data management system) for powering data hubs and data portals. CKAN makes it easy to publish, share and use data. It powers the http://thedatahub.org/ and http://data.gov.uk/ among many other sites.", + "status": "Development", + "permissions": { + "usageType": "openSource", + "licenses": null + }, + "organization": "Department of Health and Human Services", + "homepageURL": "https://github.com/HHS/ckan", + "downloadURL": "https://api.github.com/repos/HHS/ckan/downloads", + "repositoryURL": "https://github.com/HHS/ckan.git", + "vcs": "git", + "laborHours": 0.0, + "languages": [ + "Python", + "CSS", + "JavaScript", + "Shell" + ], + "date": { + "created": "2012-08-26", + "lastModified": "2021-04-15", + "metadataLastUpdated": "2022-03-22" + }, + "tags": [ + "CKAN", + "open", + "source", + "DMS", + "management", + "powering", + "hubs", + "portals", + "makes", + "easy", + "publish", + "share", + "use", + "powers", + "http:", + "thedatahub", + "org", + "uk", + "sites" + ], + "contact": { + "email": "HHS_GitHub_Service_Desk@hhs.gov", + "name": "U.S. Department of Health & Human Services" + } + }, + { + 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The data received from CMS will include Title II beneficiaries who reside in nursing homes, are enrolled in HMOs, or have private health insurance.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Medicare" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Medicare - IRMAA", + "repositoryURL": "", + "description": "Imposes higher Medicare Part B and Part D premium rates on high-income earners as defined by statute, adjusts those additional amounts on the basis of beneficiary allegations, and verifies the accuracy of those allegations.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "medicare" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Military Service Reimbursement", + "repositoryURL": "", + "description": "The Military Service Reimbursement System (MSRS) was developed to replace the process within the Title II AERO system that calculates Primary Insurance Amounts (PIA) for the Office of the Chief Actuary (OCACT).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reimbursement", + "Military" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Legal Automated Workflow System", + "repositoryURL": "", + "description": "A new system replacing the Program Litigation functions in the National Docketing Management Information System (NDMIS). LAWS electronically receives information contained in the Certified Administrative Record (CAR), interacts with Electronic Folder, allows OGC users access to historical data, accurately captures workloads, and enables users to produce and communicate management information.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workflow" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Cost Analysis System", + "repositoryURL": "", + "description": "The Cost Analysis System gathers workload counts and costs.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Cost Analysis" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Federal Assistance Award Data System", + "repositoryURL": "", + "description": "A central collection of selected, computer-based domestic financial assistance programs data for the Federal Government mandated by the Federal Funding Accountability and Transparency Act and is compiled quarterly.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Federal Assistance" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Quality Performance Management System / DARES", + "repositoryURL": "", + "description": "Performance management data extracted from multiple sources is consolidated into the QPMS data warehouse, providing a \"one-stop\" source for generating quality performance measures. The Disability Adjudication Review Evaluation System (DARES) provides a dashboard display of necessary management/decision support and risk information to Office of Disability Adjudication and Review (ODAR) officials, allowing them to effectively monitor and control the hearings backlog reduction initiatives and to determine the health of the overall hearings backlog reduction program at SSA. DARES also serves as the front-end starting point for QPMS DARES, which offers web-based, parameter-driven reports that are based on the breakdown of ODAR workloads within the context of how they relate to key hearing backlog initiatives. ", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Review", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Case Processing Management System", + "repositoryURL": "", + "description": "An intranet application used by the Office of Disability Adjudication and Review's (ODAR) hearing offices to process cases and manage office workloads.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Management", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Work Reporting Front End", + "repositoryURL": "", + "description": "A Web-based application used by all SSA technicians (TSC, FO, PC, and OCO), which fully automates the initiation, development, adjudication, and effectuation of Title II Work CDRs.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Work Reporting", + "Title II" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Consent Based Social Security Number Verification", + "repositoryURL": "", + "description": "A fee-based SSN verification service that permits private businesses, as well as Federal, State and Local governments, to use the Internet or a Web Service to verify an individual's SSN once a valid signed consent form is obtained from the SSN holder.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Number Verification", + "repositoryURL": "", + "description": "An application within Business Services Online (BSO). SSNVS allows registered users to verify names and SSNs of their employees against SSA's master files via the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Internet", + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "National Instant Criminal Background Check System", + "repositoryURL": "", + "description": "The purpose of the National Instant Criminal Background Check System (NICS) is to process potential NICS candidates for inclusion to the FBI, prohibiting firearm ownership.\nThis is an Intranet application for CRs to gather information from potential candidates who are identified by EDCS. CRs will then process the candidates who are legally incompetent and provide notification of NICS determinations to the appropriate parties, such as legal guardians, appointed representatives, and representative payees. All candidates found eligible will have identifying information submitted to the FBI.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Criminal", + "Background Check" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Internet Ticket Operations Provider Support System", + "repositoryURL": "", + "description": "An automated system that allows users to award contracts, provide ticket assignment/unassignment, and payments for Employment Networks (EN). 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The system allows field office personnel to quickly process payments and eliminates the need to bundle and send payment requests to the Office of Finance at headquarters.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Fee Collection" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Returned Check Action", + "repositoryURL": "", + "description": "The program generates an electronic alert file to the servicing Processing Center (PC) when Title II benefit payments are returned, indicating the beneficiary is deceased. It will automatically send a call-in letter to each beneficiary indicating the stop payment and the reason why.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Death", + "Title II", + "Processing Center" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Fugitive Felon Matching Agreements", + "repositoryURL": "", + "description": "APPLICATION TO COLLECT INFORMATION ON SSA EFFORTS TO NEGOTIATE MATCHING AGREEMENTS WITH LAW ENFORCEMENT AGENCIES TO IDENTIFY FUGITIVE FELONS AND PAROLE AND PROBATION VIOLATORS", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Felon" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "National Docketing Management Information System", + "repositoryURL": "", + "description": "Centralized system for tracking and managing legal matters as a system-of-record for all OGC regions and at OGC headquarters. 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Enables transactions that allow: Messages and alerts to be sent to case processing systems; Electronic cases to be transferred between processing locations and closed when processing is complete; and Case processing systems to electronically send data to the CEF when case processing actions are complete.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Access for Cross-Platform Intranet Services", + "repositoryURL": "", + "description": "Access to Cross-Platform Intranet Services (AXIS), a Web Service environment, is a part of Core Services for security logon. It allows ColdFusion applications to leverage the security infrastructure in order to access mainframe resources on z/OS.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Security", + "Web Services" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Work History Assistant Tool", + "repositoryURL": "", + "description": "A web-based application, available on a need-to-know basis, that retrieves Detail Earnings Query (DEQY) data and makes it easier to interpret.wh", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Employment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Employee Office Sampler", + "repositoryURL": "", + "description": "Capture/store/manage end-user work activities at designated times as needed for DOWS sampling", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Field Office" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Medical Evidence Gathering & Analysis Health Information Technology", + "repositoryURL": "", + "description": "An application called through Health IT that requests, receives, and analyzes electronic medical records in a fully automated manner. Upon transfer of a claim to a disability case processing unit, MEGAHIT automatically identifies a health IT participating source and gathers electronic medical records.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Medical Records" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Document Generation System", + "repositoryURL": "", + "description": "DGS is a Windows-based application used to create Office of Hearings and Appeals (OHA) Distributed Online Correspondence System (DOCS) and notices.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Notices", + "Document Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Access Control Utility", + "repositoryURL": "", + "description": "Access Control Utility (ACU) provides access only to applications that employ Knowledge Based Authentication (KBA).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Authentication", + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Access - (RIR)", + "repositoryURL": "", + "description": "ID Proofing and Authentication system for SSA online applications.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Security", + "Authentication" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "EMR-Framework", + "repositoryURL": "", + "description": "The Enterprise Metadata Repository Framework is built on an open architecture using relational databases and provides an infrastructure for retrieving data to load to the EMR, as well as controlling the load process.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Framework", + "Data", + "Metadata Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "EMR-UI/API", + "repositoryURL": "", + "description": "Provides front-end and API access to the Enterprise Metadata Repository, which stores metadata about SSA's applications and databases. The Enterprise Metadata Repository (EMR) is a data management tool used to coordinate enterprise-wide information. It ties physical and logical metadata which may be used in data administration and application development efforts. The EMR is built on an open architecture using relational databases. It serves as a central location for documentation of SSA's data infrastructure.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Front End", + "Data", + "Metadata Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Health informationTechnology management information", + "repositoryURL": "", + "description": "Health IT Management Information (HIT MI) is part of the WebFocus Business Intelligence Dashboard. It provides data analysis to monitor work loads and trend analysis and information on a variety of variables such as time and location, allowing users to make further improvements and enhancements to the disability process.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "HealthIT" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "WMI for IC and Appeals", + "repositoryURL": "", + "description": "Legacy Workload Management Information (WMI) for IC and appeals batch programs and CICS screens.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Appeals", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "VIEWS - Agreement Workflow Tool", + "repositoryURL": "", + "description": "AWT is a workflow tool and repository for the reimbursable agreement documents. The agreement process begins in AWT, which allows related documentation to be circulated electronically for approval and signature.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Agreements", + "Workflow Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MI Central", + "repositoryURL": "", + "description": "Facilitates access to management information and workload control reports by providing centralized access to workload counts, workload control listings, processing time reports, performance measurement reports and managerial cost analysis data/reports.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Management Information" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Detailed Office Organization Resource System", + "repositoryURL": "", + "description": "The Detailed Office/Organization Resource System (DOORS) is SSA's official Agency repository of office information, such as location and phone numbers, for all SSA offices. DOORS has a user and customer base of all SSA employees, hundreds of SSA systems, and members of the public who use SSA.GOV on the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Inventory Management", + "Office", + "Administrative" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Automatic Earnings Reappraisal Operation", + "repositoryURL": "", + "description": "The process that \"automatically\" screens the earning records of Retirement, Survivors, and Disability Insurance (RSDI) beneficiaries for additional earnings and computes necessary changes. The beneficiary does NOT have to initiate this process.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Automated", + "Disability", + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Number Application Process", + "repositoryURL": "", + "description": "An Enumeration software application that will perform a cross-reference check of a new SSN.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Application", + "Enumeration" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Verifications Account Management System", + "repositoryURL": "", + "description": "Verification Account Management System (VAMS) is a centralized location for maintaining Enumeration Verification Systems (EVS) accounts. VAMS allows users to create new accounts, search for existing accounts, update current accounts, and generate MI count reports. DEVO interfaces with VAMS to perform the administrative functions of registration, access control and tracking, and to manage assignment of the functional processes.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Account Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Integrated Client Database System", + "repositoryURL": "", + "description": "The Integrated Client Database (ICDB) System allows data to be shared among SSA's major application systems (e.g., Title II and Title XVI Claims Processing). ICDB is comprised of a set of databases, common screens and access software that collects, maintains, and provides access to common Client data.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Client" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Earnings Use - SEQY", + "repositoryURL": "", + "description": "A Master File online query request screen that adds earnings from up to 10 SSNs to the query response. The system then combines the earnings from the SSNs in the yearly totals on the query response.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Person Information", + "repositoryURL": "", + "description": "The Person Information web application was created to provide a common set of screens to display and collect person data. It is available as an independent application through the Person Information link on iMain. It can also be included in another application's path.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Person" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Folder Interface - Data Access", + "repositoryURL": "", + "description": "Allows shared access via eView to legacy information and documents within a case.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Document", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "AccuWage", + "repositoryURL": "", + "description": "AccuWage is used for testing the Electronic Filing of Wage and Tax Statement (EFW2). The software is downloaded from the SSA Web site by a submitter and used to check the format of a wage report submission file.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Taxes", + "Employment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Comprehensive Integrity Review Process - Mainframe", + "repositoryURL": "", + "description": "Collects and evaluates electronic transactions entered into the programmatic systems. Identifies those transactions that may indicate abuse or fraudulent activity involving SSA employees or the public.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Review", + "Fraud Prevention" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "DCS Budget Tracking System", + "repositoryURL": "", + "description": "Tracks Other Objects budget allocations for the Office of Systems and tracks some Information Technology budgets. Monitors and tracks allocations, expenditures and generates Management Information (MI) reports for planning budget requests and allocations.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Management Information", + "Administrative", + "Budget Tracking" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Internet Special Notices Option", + "repositoryURL": "", + "description": "An Internet/Intranet application designed to collect notice preferences from applicants, beneficiaries, recipients, and representative payees who allege blindness or visual impairment. These individuals can select to receive all notices and written communication from SSA via a Microsoft Word CD or in Braille.", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "SNO", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Performance Assessment and Communication System", + "repositoryURL": "", + "description": "PACS assists supervisors in preparing employee performance plans, documenting expectations and progress reviews and preparing performance appraisals.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Performance Appraisals", + "Human Resources" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Security Administration Reports Application", + "repositoryURL": "", + "description": "SARA is the automated solution to an existing manual review\nprocess, and it will provide the ability to capture trending data to\nassist in management decisions. Yes, The Security Administration Reports\nApplication SARA will allow Information Security Officers ISOs,\nAlternate Information Security Officers ALT ISOs and Management Designee\nMD to access, review and take appropriate action on Security\nAdministration Reports.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reporting", + "Management Information", + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Document Processing System", + "repositoryURL": "", + "description": "The Document Processing System (DPS) is an SSA developed, browser based application that will provide the user with functionality similar to the client server based system, Distributed Online Correspondence System (DOCS).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Document Processing", + "Document Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Personal Enrollment Credential System", + "repositoryURL": "", + "description": "The HSPD-12 Electronic Personal Enrollment Credential System (EPECS) supports the HSPD-12 credentialing process at SSA. It automates the sponsoring, vetting, and issuing of HSPD-12 credentials. It interfaces with other SSA systems for compliance with various directives.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Bench Book", + "repositoryURL": "", + "description": "A web-based application used by the office of Disability Adjudication and Review/ODAR to aid with documentation, analysis, and adjudication of disability cases.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Adjudication", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Visitor Intake Process - Rewrite", + "repositoryURL": "", + "description": "Manages appointments and walk-ins for Field Office (FO) and assigns them to the FO staff in an effective way to minimize the wait time of the users.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Scheduling", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Hires and Losses Tracking System", + "repositoryURL": "", + "description": "This application tracks the hires and losses of employees to the Office of Systems. It provides an automated way of approving hires and tracking both hires and losses in Systems. It also provides many reports from captured data on individuals joining the Office of Systems, leaving the Office of Systems, or moving from one Associate Commissioner's office within Systems to another Associate Commissioner's office within Systems. The data from these reports are used by management to make budget decisions.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Human Resources" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "GSO - Interim Assistance Reimbursement", + "repositoryURL": "", + "description": "An online mechanism for state agencies to report to SSA the amount of state or local assistance the agencies paid to individuals who are now eligible for SSI payments.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Data Exchanges", + "Payments" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Modernized Supplemental Security Income Claims System", + "repositoryURL": "", + "description": "Web-based Intranet pages that collect and document application information about the claimant, provide a modernized data-collection environment for most post-eligibility (PE) events - regardless of whether the action taken is an initial claim or a PE event - and allow online claims initiation for the majority of SSI claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Internet", + "Claim", + "SSI" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Affordable Care Act - Batch Redetermination/Renewal Process", + "repositoryURL": "", + "description": "A batch application exchanges data with CMS related to eligibility Redeterminations and Renewal decisions for Insurance Affordability Programs.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Medical", + "Insurance" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Freedom of Information Act System -Intranet", + "repositoryURL": "", + "description": "An Intranet application used by the Office of Public Disclosure (OPD) and the Division of Earnings Record Operations (DERO) to process the different types of FOIA requests that are received.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Intranet", + "FOIA" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Direct Deposit Fraud Prevention", + "repositoryURL": "", + "description": "An intranet web application developed to collect and processes requests to block direct deposit auto-enrollment changes that are received and processed in the SSA Notification of Change (SANOC) System. The DDFP web application also requires input of the reason for the block - Fraud Alleged or Preventive Measure. Both the adding and removal of the block are updated in real time allowing the application to access the data for display the block request history.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Direct Deposit", + "Fraud Prevention" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "SSI Claims System - Web", + "repositoryURL": "", + "description": "Enables SSI claim submissions via a web-based intranet data collection process. It replaces the previous set of CICS MSSICS screens.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Data Collection", + "Claim", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Access to Financial Institutions", + "repositoryURL": "", + "description": "Electronically verifies depository account balances for Supplemental Security Income (SSI) applicants, recipients, and deemors. It also searches for undisclosed depository accounts and detects unreported excess resources, reducing improper SSI payments.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Direct Deposit", + "Financial" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "electronic Representative Payee System", + "repositoryURL": "", + "description": "The Electronic Representative Payee Accounting (eRPA) system is an intranet-based system that has automated the processing of Representative Payee Accounting forms.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Forms", + "Intranet", + "Representative Payee" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Data Exchange and Verification Online", + "repositoryURL": "", + "description": "DEVO is the back-end application for processing SSN verifications and data exchanges. DEVO uses modern technology for parameter driven processing of both batch and real time requests. DEVO provides the capability for SSA to accurately and rapidly respond to customized requests, legislative mandates, and court orders. Legacy verification and data exchange applications (Enumeration Verification System (EVS), Numident Online Verification Utility (NOVU), State Verification Exchange System (SVES), and State Online Query System (SOLQ)) are methodically being reengineered into DEVO, which will make use of reusable, flexible software. DEVO interfaces with the Verification Account Management System (VAMS) to determine account status, obtain processing parameters, and store transaction counts for Management Information (MI).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Verification", + "Data Exchange" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Core Services", + "repositoryURL": "", + "description": "A suite of Intranet-based utilities designed to simplify central or common routines required by many web based applications. The utilities leverage open, accessible technologies eliminating the drawbacks commonly seen in proprietary coding techniques. They help prevent duplication of effort by reusing what already exists.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Intranet", + "Services" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "StaRZ & Stripes - The Next Generation", + "repositoryURL": "", + "description": "StarRZ and Stripes the Next Generation (SSTNG) provides the full range of detailed workload monitoring, management reports and listings used by Claims Reps, Operation Supervisors and FO Managers to identify, track and successfully complete their annual Redetermination/Limited (RZ/LI) workloads.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MI for Debt Management System", + "repositoryURL": "", + "description": "Provides an summary of the financial Debt Management screens at the regional field offices and the processing center levels", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Processing Center", + "Debt Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Customer Help and Information Program", + "repositoryURL": "", + "description": "CHIP is an Intranet application currently used by National 800 Number (N8NN) Agents to respond to inquiries made by the public. 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"organization": "Federal Election Commission", + "contact": { + "URL": "https://github.com/fecgov/fec/issues", + "email": "opensource@fec.gov" + }, + "date": { + "created": "2016-10-29", + "lastModified": "2020-09-29", + "metadataLastUpdated": "2020-10-06" + }, + "description": "Pattern Library for FEC.gov", + "downloadURL": "https://api.github.com/repos/fecgov/fec-pattern-library/downloads", + "homepageURL": "https://fec-pattern-library.app.cloud.gov/", + "laborHours": 11110.6, + "languages": [ + "HTML", + "JavaScript", + "SCSS", + "Shell" + ], + "name": "fec-pattern-library", + "permissions": { + "usageType": "openSource", + "licenses": [ + { + "URL": "https://github.com/fecgov/fec-pattern-library/blob/master/LICENSE.md", + "name": "CC0" + } + ] + }, + "repositoryURL": "https://github.com/fecgov/fec-pattern-library", + "relatedCode": [ + { + "name": "U.S. Web Design System", + "URL": "https://github.com/uswds/uswds" + } + ], + "status": "Production", + "tags": [ + "FEC", + "github", + "styles", + "design patterns" + ], + "vcs": "git" + }, + { + "organization": "Federal Election Commission", + "contact": { + "URL": "https://github.com/fecgov/fec/issues", + "email": "opensource@fec.gov" + }, + "date": { + "created": "2017-02-11", + "lastModified": "2020-05-31", + "metadataLastUpdated": "2020-10-06" + }, + "description": "Terraform configuration and CircleCI for managing custom FEC infrastructure in AWS.", + "downloadURL": "https://api.github.com/repos/fecgov/fec-infrastructure/downloads", + "homepageURL": "https://github.com/fecgov/fec-infrastructure", + "laborHours": 121.6, + "languages": [ + "HCL" + ], + "name": "fec-infrastructure", + "permissions": { + "usageType": "openSource", + "licenses": [ + { + "URL": "https://github.com/fecgov/fec-infrastructure/blob/master/LICENSE.md", + "name": "CC0" + } + ] + }, + "repositoryURL": "https://github.com/fecgov/fec-infrastructure", + "status": "Production", + "tags": [ + "FEC", + "github", + "ferraform", + "configuration", + "AWS" + ], + "vcs": "git" + } + ] +} \ No newline at end of file diff --git a/scripts/web-scraper.py b/scripts/web-scraper.py new file mode 100644 index 00000000..d73374b0 --- /dev/null +++ b/scripts/web-scraper.py @@ -0,0 +1,62 @@ +import requests +import json + +agencies_links = { + "Department of Agriculture": "https://usda.gov/code.json", + # "Department of Commerce": "https://www.commerce.gov/code.json", + "Department of Defense": "https://www.code.mil/code.json", + # "Department of Education": "https://ed.gov/code.json", + "Department of Energy": "https://www.energy.gov/code.json", + "Department of Health and Human Services": "https://www.hhs.gov/code.json", + # "Department of Housing and Urban Development": "https://www.hud.gov/code.json", + "Department of Homeland Security": "https://www.dhs.gov/code.json", + # "Department of Justice": "https://www.justice.gov/d9/code.json", + # "Department of Labor": "https://www.dol.gov/code.json", + # "Department of Transportation": "https://www.transportation.gov/code.json", + "Department of Treasury": "https://www.treasury.gov/code.json", + "Department of Veterans Affairs": "https://www.va.gov/code.json", + "Environmental Protection Agency": "https://www.epa.gov/code.json", + # "National Aeronautics and Space Administration": "https://code.nasa.gov/code.json", + # "Agency for International Development": "https://www.usaid.gov/code.json", + # "General Services Administration": "https://www.gsa.gov/code.json", + "National Science Foundation": "https://www.nsf.gov/code.json", + # "Office of Personnel Management": "https://www.opm.gov/code.json", + # "Small Business Administration": "https://www.sba.gov/code.json", + "Social Security Administration": "https://www.ssa.gov/code.json", + "Federal Election Commission": "https://www.fec.gov/code.json" +} + +headers = { + 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36', + 'Accept': 'application/json, text/plain, */*', +} + +file_path = "../legacy-codegov.json" +legacy_codegov = {} + +try: + for agency, link in agencies_links.items(): + response = requests.get(link, headers = headers) + + print(agency) + print(f"Status code: {response.status_code}") + + if response.status_code == 200: + print("Data received:", len(response.text)) + data = response.json() + legacy_codegov[agency] = data["releases"] + else: + print("Error message from API:", response.text) + + print("\n") + +except requests.exceptions.RequestException as e: + print(f"Request failed: {e}") + +try: + with open(file_path, 'w', encoding='utf-8') as file: + json.dump(legacy_codegov, file, indent=4, ensure_ascii=False) +except Exception as e: + print(f"Failed to save JSON file: {e}") + +print(legacy_codegov) \ No newline at end of file From ca6bf5384573447dc50ba9742d58cb5e8a719656 Mon Sep 17 00:00:00 2001 From: Isaac Milarsky Date: Wed, 4 Jun 2025 11:30:37 -0500 Subject: [PATCH 02/14] add manifest file Signed-off-by: Isaac Milarsky --- repo-manifest.json | 3762 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 3762 insertions(+) create mode 100644 repo-manifest.json diff --git a/repo-manifest.json b/repo-manifest.json new file mode 100644 index 00000000..d5a8b6a6 --- /dev/null +++ b/repo-manifest.json @@ -0,0 +1,3762 @@ +{ + "GSA" : [ + "https://github.com/GSA/mobile-fu", + "https://github.com/GSA/rails-google-visualization-plugin", + "https://github.com/GSA/apache-log-parser", + "https://github.com/GSA/active_scaffold", + "https://github.com/GSA/fckeditor", + "https://github.com/GSA/aws-s3", + "https://github.com/GSA/capistrano", + "https://github.com/GSA/sunspot", + "https://github.com/GSA/resque-priority", + "https://github.com/GSA/open311-simple-crm", + "https://github.com/GSA/datafiles-wordpress-plugin", + "https://github.com/GSA/federal-open-source-repos-php", + "https://github.com/GSA/federal-open-source-repos", + "https://github.com/GSA/federal-open-source-repos-ruby", + "https://github.com/GSA/gogogon", + "https://github.com/GSA/ckanext-geodatagov", + "https://github.com/GSA/digital-strategy", + "https://github.com/GSA/digital-strategy-report-generator", + "https://github.com/GSA/ruby-cloudfiles", + "https://github.com/GSA/us-digital-registry", + "https://github.com/GSA/digital-strategy-drupal-module", + "https://github.com/GSA/oauth2-provider", + "https://github.com/GSA/Open311-Forms-Engine", + "https://github.com/GSA/uReport", + "https://github.com/GSA/open311-proxy", + "https://github.com/GSA/mygov-mobile-first-foundation", + "https://github.com/GSA/slash-developer-pages", + "https://github.com/GSA/pdf-filler", + "https://github.com/GSA/epa_uv_index", + "https://github.com/GSA/apidocs", + "https://github.com/GSA/omniauth-mygov", + "https://github.com/GSA/mygov-bar", + "https://github.com/GSA/mygov-discovery", + "https://github.com/GSA/mygov-forms", + "https://github.com/GSA/db-to-api", + "https://github.com/GSA/DataBeam", + "https://github.com/GSA/benefits-mockup", + "https://github.com/GSA/recalls_api", + "https://github.com/GSA/jobs_api", + "https://github.com/GSA/mygov-feedback-reporting", + "https://github.com/GSA/mygov-account", + "https://github.com/GSA/us_states", + "https://github.com/GSA/labs-html", + "https://github.com/GSA/mygov-account-php-sdk", + "https://github.com/GSA/usa-faqs", + "https://github.com/GSA/idm", + "https://github.com/GSA/unclaimed_money", + "https://github.com/GSA/omniauth-openid", + "https://github.com/GSA/GSA-APIs", + "https://github.com/GSA/usfedgov_google_analytics", + "https://github.com/GSA/alpha-data-dot-gov", + "https://github.com/GSA/ckanext-saml2", + "https://github.com/GSA/datagov-wptheme", + "https://github.com/GSA/rack-openid", + "https://github.com/GSA/SMR-site-embed", + "https://github.com/GSA/Mobile-Code-Catalog", + "https://github.com/GSA/Mobile-Web-Manual-Testing-Script", + "https://github.com/GSA/myusa-account-demo", + "https://github.com/GSA/federal-apps-gallery-widgets", + "https://github.com/GSA/ckanext-usmetadata", + "https://github.com/GSA/mygov-admin-tasks", + "https://github.com/GSA/myusa-tasks", + "https://github.com/GSA/Crowdsource-Testing-USDA_FSIS", + "https://github.com/GSA/hyabusa", + "https://github.com/GSA/modus-operandi", + "https://github.com/GSA/just_inform", + "https://github.com/GSA/just_inform_web", + "https://github.com/GSA/.Gov-Content-as-an-API", + "https://github.com/GSA/ckanext-datajson", + "https://github.com/GSA/project-open-data-dashboard", + "https://github.com/GSA/embedding-data-catalogs", + "https://github.com/GSA/enterprise-data-inventory", + "https://github.com/GSA/capistrano-resque", + "https://github.com/GSA/Crowdsource-Testing-CIO.gov", + "https://github.com/GSA/gman", + "https://github.com/GSA/helio", + "https://github.com/GSA/govt-urls", + "https://github.com/GSA/logo", + "https://github.com/GSA/datagov-design", + "https://github.com/GSA/twitter-widgets-gallery", + "https://github.com/GSA/Template-Microsite", + "https://github.com/GSA/Open-Data-Collaboration-Sandbox", + "https://github.com/GSA/Very-Simple-API", + "https://github.com/GSA/Developer-Feedback-for-Government-APIs", + "https://github.com/GSA/search.digitalgov.gov", + "https://github.com/GSA/API-Resources", + "https://github.com/GSA/ckan-php-client", + "https://github.com/GSA/ckan-php-manager", + "https://github.com/GSA/wp-open311", + "https://github.com/GSA/data_gov_json_validator", + "https://github.com/GSA/open-data-program-template", + "https://github.com/GSA/pod-schema-variants", + "https://github.com/GSA/PricesPaidAPI", + "https://github.com/GSA/LAMP-CentOS-with-Vagrant", + "https://github.com/GSA/ckan", + "https://github.com/GSA/ckanext-harvest", + "https://github.com/GSA/ckanext-spatial", + "https://github.com/GSA/idp", + "https://github.com/GSA/arcgis-map", + "https://github.com/GSA/custom-contact-forms", + "https://github.com/GSA/custom-post-view-generator", + "https://github.com/GSA/datagov-custom", + "https://github.com/GSA/metric-count", + "https://github.com/GSA/restrict-categories", + "https://github.com/GSA/saml-20-single-sign-on", + "https://github.com/GSA/sticky-posts-in-category", + "https://github.com/GSA/suggested-datasets", + "https://github.com/GSA/twitter-posts-to-blog", + "https://github.com/GSA/twitter-widget-pro", + "https://github.com/GSA/usa-search", + "https://github.com/GSA/wordpress-seo", + "https://github.com/GSA/Open-And-Structured-Content-Models", + "https://github.com/GSA/Crowdsource-Testing-DFAS.mil", + "https://github.com/GSA/ckanext-qa", + "https://github.com/GSA/FedCMS-Slider", + "https://github.com/GSA/ckanext-archiver", + "https://github.com/GSA/Crowdsource-Testing-HHS-ACF.gov", + "https://github.com/GSA/open.gsa.gov", + "https://github.com/GSA/instant-comment-validation", + "https://github.com/GSA/asis", + "https://github.com/GSA/simple-tooltips", + "https://github.com/GSA/ckanext-googleanalyticsbasic", + "https://github.com/GSA/wp-external-links", + "https://github.com/GSA/Crowdsource-Testing-NOAA-CrowdMag", + "https://github.com/GSA/Crowdsource-Testing-ABMC.gov", + "https://github.com/GSA/IAE-Architecture", + "https://github.com/GSA/auctions_api", + "https://github.com/GSA/OWSLib", + "https://github.com/GSA/datagov-presentations", + "https://github.com/GSA/testsite922", + "https://github.com/GSA/Crowdsource-Testing-HHS-MAIN", + "https://github.com/GSA/ckanext-report", + "https://github.com/GSA/data.gov-styleguide", + "https://github.com/GSA/developers", + "https://github.com/GSA/data", + "https://github.com/GSA/data.json-template", + "https://github.com/GSA/sites-digitalgov-search", + "https://github.com/GSA/Very-Simple-API-2", + "https://github.com/GSA/sitelink_generator", + "https://github.com/GSA/punchcard", + "https://github.com/GSA/Crowdsource-Testing-NOAA-CrowdMag--iOS", + "https://github.com/GSA/Crowdsource-Testing-Central-Artifact-Repository", + "https://github.com/GSA/cfpb.github.io", + "https://github.com/GSA/social-media-registry-api", + "https://github.com/GSA/api", + "https://github.com/GSA/labs", + "https://github.com/GSA/fssi-file-processor", + "https://github.com/GSA/https", + "https://github.com/GSA/Crowdsource-Testing-NIH-HCI-1-2015", + "https://github.com/GSA/data-json", + "https://github.com/GSA/eMuseum-API", + "https://github.com/GSA/seo", + "https://github.com/GSA/participation-playbook", + "https://github.com/GSA/Holiday-Utility", + "https://github.com/GSA/Membership-Utility", + "https://github.com/GSA/open311-github", + "https://github.com/GSA/Crowdsource-Testing-Connect.gov_3-2015", + "https://github.com/GSA/USA.gov-API-Integration", + "https://github.com/GSA/GitHub-Administration", + "https://github.com/GSA/i14y", + "https://github.com/GSA/agile_accelerator_admin_guide", + "https://github.com/GSA/wp-rss-multi-importer", + "https://github.com/GSA/structured_content_wordpress", + "https://github.com/GSA/GSA-Digital-Innovation", + 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"https://github.com/GSA/codeinventory-metadata-generator", + "https://github.com/GSA/FM-VITAP-MIGRATED", + "https://github.com/GSA/codeinventory", + "https://github.com/GSA/FEDSIM_root", + "https://github.com/GSA/ec2-broker", + "https://github.com/GSA/elastalert", + "https://github.com/GSA/prototype-city-pairs-api", + "https://github.com/GSA/SF-Event-Monitoring-Log-Retrieval", + "https://github.com/GSA/codeinventory-github", + "https://github.com/GSA/sf-ProjectDashboard", + "https://github.com/GSA/api-standards", + "https://github.com/GSA/sdg-nrp-scripts", + "https://github.com/GSA/ansible-role-repo-webtatic", + "https://github.com/GSA/api-documentation-template", + "https://github.com/GSA/prototype-city-pairs-api-documentation", + "https://github.com/GSA/fedramp", + "https://github.com/GSA/ansible-tomcat", + "https://github.com/GSA/sfdx_pilot", + "https://github.com/GSA/accessibility-for-teams", + "https://github.com/GSA/som", + "https://github.com/GSA/DSSAPIDocumentation", + "https://github.com/GSA/third-party-services", + "https://github.com/GSA/fedramp-tailored", + "https://github.com/GSA/GEAR2-NodeJS", + "https://github.com/GSA/aws-cis-scanner", + "https://github.com/GSA/datagov-infrastructure", + "https://github.com/GSA/DOTGOVDASH-archived", + "https://github.com/GSA/FM-ULO-MIGRATED", + "https://github.com/GSA/FM-PegasysWebPortal", + "https://github.com/GSA/FM-FMISWebPortal", + "https://github.com/GSA/digital.gov", + "https://github.com/GSA/sf_ANTbuildfiles", + "https://github.com/GSA/ITDB-schema", + "https://github.com/GSA/ficam-pacs", + "https://github.com/GSA/digitalgov-wordpress", + "https://github.com/GSA/mysql_to_cloudwatch", + "https://github.com/GSA/laptop-management", + "https://github.com/GSA/AI-Assistant-Pilot", + "https://github.com/GSA/apps-gsa-gov", + "https://github.com/GSA/recruiter", + "https://github.com/GSA/CIO.gov", + "https://github.com/GSA/jenkins-deploy", + "https://github.com/GSA/domain-knowledge", + "https://github.com/GSA/hi", + "https://github.com/GSA/icam-fisma", + "https://github.com/GSA/security-benchmarks", + "https://github.com/GSA/ISE-Security-Benchmark-GPOs", + "https://github.com/GSA/digital-governance-outline", + "https://github.com/GSA/ckanext-security", + "https://github.com/GSA/rvm1-ansible", + "https://github.com/GSA/service-design-analytics", + "https://github.com/GSA/Digital-Council", + "https://github.com/GSA/jekyll-rebuilder", + "https://github.com/GSA/AAS_root", + "https://github.com/GSA/open.usa.gov", + "https://github.com/GSA/ansible-role-jenkins", + "https://github.com/GSA/digital.gov-hugo", + "https://github.com/GSA/ansible-microstrategy", + "https://github.com/GSA/digital.gov-design", + "https://github.com/GSA/PSHC_Applets", + "https://github.com/GSA/OMB-Max-Auth-for-Salesforce", + "https://github.com/GSA/terriajs-server", + "https://github.com/GSA/code-gov-admintool", + "https://github.com/GSA/open-source-policy", + "https://github.com/GSA/GSA-UX-UI-Playbook", + "https://github.com/GSA/ansible-https-proxy", + "https://github.com/GSA/CIW", + "https://github.com/GSA/ficam-scvp-testing", + "https://github.com/GSA/QueryToCSV", + "https://github.com/GSA/Suitability", + "https://github.com/GSA/Adjudications", + "https://github.com/GSA/CHRISUpdate", + "https://github.com/GSA/matter-maker", + "https://github.com/GSA/ansible-os-ubuntu-14", + "https://github.com/GSA/participate-nap4", + "https://github.com/GSA/code-gov-admin-backend", + "https://github.com/GSA/innovation.gov", + "https://github.com/GSA/modernization", + "https://github.com/GSA/digitalgov.gov", + "https://github.com/GSA/front-matter-editor", + "https://github.com/GSA/frntmttr", + "https://github.com/GSA/devsecops-example", + "https://github.com/GSA/training-pathway-data-practitioner", + "https://github.com/GSA/gsa-icam-card-builder", + "https://github.com/GSA/ansible-os-rhel-7", + "https://github.com/GSA/CorpIT-GSAResp", + "https://github.com/GSA/datagov-infrastructure-modules", + "https://github.com/GSA/datagov-infrastructure-live", + "https://github.com/GSA/code-gov-gitsecretpatterns", + "https://github.com/GSA/usagov-api", + "https://github.com/GSA/usagov-hub", + "https://github.com/GSA/plainlanguage.gov", + "https://github.com/GSA/DevSecOps", + "https://github.com/GSA/CorpIT-CloudSandbox", + "https://github.com/GSA/fpkilint", + "https://github.com/GSA/CorpIT-ChildCare", + "https://github.com/GSA/DevSecOps-Mgmt-Tools-Deploy", + "https://github.com/GSA/ice-cream", + "https://github.com/GSA/opp-code-gov-web", + "https://github.com/GSA/robots_tag_parser", + "https://github.com/GSA/ansible-role-kibana", + "https://github.com/GSA/ansible-role-nessus-agent", + "https://github.com/GSA/ansible-os-rhel-6", + "https://github.com/GSA/code-gov-harvester-deprecated", + "https://github.com/GSA/ficam-scripts-public", + "https://github.com/GSA/devsecops-cloud-custodian-rules", + "https://github.com/GSA/jz-example", + "https://github.com/GSA/opp-example", + "https://github.com/GSA/devsecops-ekk-stack", + "https://github.com/GSA/digitalgov-chrome", + "https://github.com/GSA/Canada-USA-Digital-Collaboration", + "https://github.com/GSA/feedback.usa.gov", + "https://github.com/GSA/opp-federalist", + "https://github.com/GSA/go.usa.gov", + "https://github.com/GSA/consumer_complaint_letter", + "https://github.com/GSA/voc_admin", + "https://github.com/GSA/voc_public", + "https://github.com/GSA/emerging-technology-atlas", + "https://github.com/GSA/legacy-fedramp-website", + "https://github.com/GSA/code-gov-data", + "https://github.com/GSA/devsecops-jenkins", + "https://github.com/GSA/public-participation", + "https://github.com/GSA/ansible-os-ubuntu-16", + "https://github.com/GSA/newperformancedotgov1", + "https://github.com/GSA/citizenscience.gov", + "https://github.com/GSA/trustymail", + "https://github.com/GSA/code-central", + "https://github.com/GSA/terraform-role", + "https://github.com/GSA/GEAR-Documentation", + "https://github.com/GSA/terraform-aws-vpc", + "https://github.com/GSA/devsecops-example-prod", + "https://github.com/GSA/streamalert", + "https://github.com/GSA/piv-conformance", + "https://github.com/GSA/methods", + "https://github.com/GSA/terraform-vpc-flow-log", + "https://github.com/GSA/api.data.gov-design", + "https://github.com/GSA/inactive-logout", + "https://github.com/GSA/devsecops-fleet", + "https://github.com/GSA/ansible-role-kolide-fleet", + "https://github.com/GSA/terraform", + "https://github.com/GSA/10x", + "https://github.com/GSA/ansible-osquery", + "https://github.com/GSA/opioids.gov", + "https://github.com/GSA/Performance.gov-Maintenance", + "https://github.com/GSA/ansible-fluentd", + "https://github.com/GSA/packer", + "https://github.com/GSA/opp-ops", + "https://github.com/GSA/redir", + "https://github.com/GSA/InterimPerformance-Dot-Gov-2018", + "https://github.com/GSA/unified-shared-services-management", + "https://github.com/GSA/fedramp-gov", + "https://github.com/GSA/privacy-pages", + "https://github.com/GSA/fedramp-modular-experiment", + "https://github.com/GSA/code-gov", + "https://github.com/GSA/datagov-filestore-landing", + "https://github.com/GSA/back-soon", + "https://github.com/GSA/FM-VITAP-OSS-MIGRATED", + "https://github.com/GSA/devsecops-log-forwarding", + "https://github.com/GSA/ecpic-redir", + "https://github.com/GSA/code-gov-api-client", + "https://github.com/GSA/digitalgov-redir", + "https://github.com/GSA/aws-account-broker", + "https://github.com/GSA/time-estimator", + "https://github.com/GSA/BSP_Mode1_Reporting", + "https://github.com/GSA/code-gov-stats", + "https://github.com/GSA/cio-council", + "https://github.com/GSA/federal-privacy-council", + "https://github.com/GSA/devsecops-subaccount-admin", + "https://github.com/GSA/christopher", + "https://github.com/GSA/code-gov-stats-jupyter-notebook", + "https://github.com/GSA/code-gov-developer-docs", + "https://github.com/GSA/search-gov", + "https://github.com/GSA/dns", + "https://github.com/GSA/howto.gov-redir", + "https://github.com/GSA/code-gov-style", + "https://github.com/GSA/jquery-rails", + "https://github.com/GSA/code-gov-font", + "https://github.com/GSA/RPA-OSS", + "https://github.com/GSA/devsecops-ebs-backup", + "https://github.com/GSA/logger-codeigniter", + "https://github.com/GSA/datagov-deploy-dashboard", + "https://github.com/GSA/devsecops-iam-roles", + "https://github.com/GSA/tbm_ml_discovery", + "https://github.com/GSA/cooking-with-gas", + "https://github.com/GSA/steve", + "https://github.com/GSA/search-gov-agency-collaboration", + "https://github.com/GSA/centers-of-excellence", + "https://github.com/GSA/datagov-deploy-ckan-common", + "https://github.com/GSA/datagov-deploy-ckan-catalog", + "https://github.com/GSA/datagov-deploy-ckan-inventory", + "https://github.com/GSA/datagov-deploy-wordpress", + "https://github.com/GSA/datagov-deploy-crm", + "https://github.com/GSA/datagov-deploy-mysql", + "https://github.com/GSA/datagov-deploy-postgresql", + "https://github.com/GSA/datagov-deploy-redis", + "https://github.com/GSA/datagov-deploy-nginx", + "https://github.com/GSA/datagov-deploy-apache2", + "https://github.com/GSA/datagov-deploy-jetty", + "https://github.com/GSA/datagov-deploy-elasticsearch", + "https://github.com/GSA/datagov-deploy-solr", + "https://github.com/GSA/GSA-RPA-Standard", + "https://github.com/GSA/sf-lightning-components", + "https://github.com/GSA/data-strategy", + "https://github.com/GSA/coe-industry-day", + "https://github.com/GSA/grace-example", + "https://github.com/GSA/CF-Report-Server", + "https://github.com/GSA/app_identifier", + "https://github.com/GSA/sam-cfda-site", + "https://github.com/GSA/code-gov-data-quality-poc", + "https://github.com/GSA/ubuntu-common", + "https://github.com/GSA/cloud", + "https://github.com/GSA/code-clerk", + "https://github.com/GSA/service-tracking", + "https://github.com/GSA/cx.gsa.gov", + "https://github.com/GSA/PIC_dot_gov", + "https://github.com/GSA/FM-SIFT", + "https://github.com/GSA/pdi-etl", + "https://github.com/GSA/Reinvestigation", + "https://github.com/GSA/custom-content-type-manager", + "https://github.com/GSA/code-gov-validator", + "https://github.com/GSA/ASP-.NET-Core-Template", + "https://github.com/GSA/grace-rhel-ami", + "https://github.com/GSA/grace-ubuntu-ami", + "https://github.com/GSA/infrastructure-agent-ansible", + "https://github.com/GSA/FM-FMITwebdesign", + "https://github.com/GSA/FM-WebBill", + "https://github.com/GSA/FM-FedPay-Prototype", + "https://github.com/GSA/FM-CCS", + "https://github.com/GSA/sdg-data-usa", + "https://github.com/GSA/digitalgov-workflow", + "https://github.com/GSA/grace-tf-module-budget", + "https://github.com/GSA/grace-tf-module-member-account", + "https://github.com/GSA/code-gov-integrations", + "https://github.com/GSA/RPA-FASDelinquency", + "https://github.com/GSA/data-strategy-topic-modeling", + "https://github.com/GSA/data-strategy-classification", + "https://github.com/GSA/bigfix", + "https://github.com/GSA/inventory-app", + "https://github.com/GSA/publictrustpki-repository", + "https://github.com/GSA/srt-fbo-scraper", + "https://github.com/GSA/MD-GitHub-Admin", + "https://github.com/GSA/RPA-FASChargeback", + "https://github.com/GSA/BrianRPA", + "https://github.com/GSA/RPA-Sandbox", + "https://github.com/GSA/code-gov-front-end", + "https://github.com/GSA/ansible-elastalert", + "https://github.com/GSA/Tenant-Satisfaction-Survey", + "https://github.com/GSA/Python-Server-Instructions", + "https://github.com/GSA/FM-BillView", + "https://github.com/GSA/FM-NWTB", + "https://github.com/GSA/code-gov-site-map-generator", + "https://github.com/GSA/datagov-dedupe", + "https://github.com/GSA/code-gov-adapters", + "https://github.com/GSA/touchpoints", + "https://github.com/GSA/api-doco-with-uswds", + "https://github.com/GSA/code-gov-coding-languages", + "https://github.com/GSA/FM-Credit-and-Finance", + "https://github.com/GSA/os3_taxonomy_constructor", + "https://github.com/GSA/sdg-theme", + "https://github.com/GSA/FM-FMIT-Portal-MIGRATED", + "https://github.com/GSA/datagov-ckan-multi", + "https://github.com/GSA/cautious", + "https://github.com/GSA/FAS-Chargebacks-Data-Capture-Tool", + "https://github.com/GSA/FM-App-Status-API", + "https://github.com/GSA/contracting-hypotheses", + "https://github.com/GSA/code-gov-fscp-react-component", + "https://github.com/GSA/code-gov-about-page", + "https://github.com/GSA/json-schema-web-component", + "https://github.com/GSA/cf-cron-python", + "https://github.com/GSA/compliance-dashboard-web-component", + "https://github.com/GSA/json-schema-validator-web-component", + "https://github.com/GSA/code-gov-repos-parser", + "https://github.com/GSA/code-gov-converter", + "https://github.com/GSA/code-gov-harvester", + "https://github.com/GSA/jobkit", + "https://github.com/GSA/jck-healthy-strategies-ingest", + "https://github.com/GSA/grace-tftest", + "https://github.com/GSA/miniature-telegram", + "https://github.com/GSA/sam-prototypes", + "https://github.com/GSA/federal-apis", + "https://github.com/GSA/ansible-os-win-2016", + "https://github.com/GSA/qualtrics-to-mssql", + "https://github.com/GSA/us-data-federation-design", + "https://github.com/GSA/sdg-translations", + "https://github.com/GSA/sdg-indicators-archive", + "https://github.com/GSA/sdg-indicators", + "https://github.com/GSA/grace-circleci-builder", + "https://github.com/GSA/chef-cookbook-ruby-ng", + "https://github.com/GSA/grace-tenant-cleanup", + "https://github.com/GSA/code-reporting-tools", + "https://github.com/GSA/cloud-journey", + "https://github.com/GSA/Opportunities-api-docs", + "https://github.com/GSA/ODC-SPID", + "https://github.com/GSA/USSM", + "https://github.com/GSA/WDOL-SPLASH-PAGE", + "https://github.com/GSA/sam-styles", + "https://github.com/GSA/sam-design-system", + "https://github.com/GSA/FM-WebBill-SE", + "https://github.com/GSA/coe-discovery-bpa", + "https://github.com/GSA/grace-app", + "https://github.com/GSA/ansible-role-beats", + "https://github.com/GSA/MG_WB2", + "https://github.com/GSA/grace-citest", + "https://github.com/GSA/sf-field-history", + "https://github.com/GSA/wazuh-ansible", + "https://github.com/GSA/digitalgov-pra", + "https://github.com/GSA/Section508", + "https://github.com/GSA/sdg-translations-demo", + "https://github.com/GSA/geoip-auto-update", + "https://github.com/GSA/cookbook-elasticsearch", + "https://github.com/GSA/nodejs", + "https://github.com/GSA/ckanphpimport", + "https://github.com/GSA/ckanpyimport", + "https://github.com/GSA/wdol", + "https://github.com/GSA/srt-api", + "https://github.com/GSA/srt-ui", + "https://github.com/GSA/si-captcha-for-wordpress", + "https://github.com/GSA/datagov-deploy-python-app", + "https://github.com/GSA/dspg-summit-2018", + "https://github.com/GSA/grace-sqs-poc", + "https://github.com/GSA/travel-project-report", + "https://github.com/GSA/datagov-deploy-jumpbox", + "https://github.com/GSA/datagov-deploy-common", + "https://github.com/GSA/datagov-deploy-php", + "https://github.com/GSA/FM-RECON-NWTB-MIGRATED", + "https://github.com/GSA/datagov-deploy-ci", + "https://github.com/GSA/datagov-deploy-ckan", + "https://github.com/GSA/environment-followerphase-staging", + "https://github.com/GSA/environment-followerphase-production", + "https://github.com/GSA/challenges-and-prizes", + "https://github.com/GSA/dcoi", + "https://github.com/GSA/GEAR-Center-RFI-Responses", + "https://github.com/GSA/frpp-load", + "https://github.com/GSA/learning-data-science", + "https://github.com/GSA/sbchrist.github.io", + "https://github.com/GSA/MD-website-dym", + "https://github.com/GSA/grace-account-lockout", + "https://github.com/GSA/coe-hud-acquisitions", + "https://github.com/GSA/GSA-Acquisition-FAR", + "https://github.com/GSA/GSA-Acquisition-GSAM", + "https://github.com/GSA/coe-hud-acq-faas-erm-ide", + "https://github.com/GSA/coe-hud-acq-hudcentral", + "https://github.com/GSA/coe-hud-acq-agency-wide-cx", + "https://github.com/GSA/coe-hud-acq-ocdo", + "https://github.com/GSA/coe-hud-acq-data-visualization", + "https://github.com/GSA/coe-hud-acq-advanced-analytics", + "https://github.com/GSA/FM-Data-API-MIGRATED", + "https://github.com/GSA/FM-PMP-API-Client-MIGRATED", + "https://github.com/GSA/FM-FedPay-Archiver-MIGRATED", + "https://github.com/GSA/grace-style-guide", + "https://github.com/GSA/hackathon-acquisition-gateway", + "https://github.com/GSA/hackathon-frpp", + "https://github.com/GSA/hackathon-hrlinks", + "https://github.com/GSA/hackathon-gsait-service-desk", + "https://github.com/GSA/RPA-ULO", + "https://github.com/GSA/cio.gov-redo", + "https://github.com/GSA/Payroll-Reporting", + "https://github.com/GSA/Receiving-Reports-for-Recurring-Services---Phase-1", + "https://github.com/GSA/AP-Email-Notifications", + "https://github.com/GSA/INFORM-Pilot", + "https://github.com/GSA/machine-readable-TTS", + "https://github.com/GSA/resources.data.gov", + "https://github.com/GSA/coe-acquisitions", + "https://github.com/GSA/coe-opm-acquisitions", + "https://github.com/GSA/Credit_Card_Logging_Bot", + "https://github.com/GSA/GSA-RPA-Example-Bots-", + "https://github.com/GSA/grace-template", + "https://github.com/GSA/code-gov-github-metrics", + "https://github.com/GSA/coe-opm-mainframe-dr-plan", + "https://github.com/GSA/code-gov-repo-template", + "https://github.com/GSA/code-gov-open-source-toolkit", + "https://github.com/GSA/tbm-scan", + "https://github.com/GSA/srt-ml", + "https://github.com/GSA/FBO-SplashPage", + "https://github.com/GSA/Broadcast-Message", + "https://github.com/GSA/grace-securityhub", + "https://github.com/GSA/CoE-MPT-process", + "https://github.com/GSA/CoE-MPT-template", + "https://github.com/GSA/GSA-FAR-Test", + "https://github.com/GSA/FM-CIR-MIGRATED", + "https://github.com/GSA/grace-logging", + "https://github.com/GSA/tts-solutions-web-council", + "https://github.com/GSA/datagov-deploy-pycsw", + "https://github.com/GSA/GmailForwardingTool", + "https://github.com/GSA/css-logit-regression", + "https://github.com/GSA/cto-sandbox-tools", + "https://github.com/GSA/coe-cpsc-acquisitions", + "https://github.com/GSA/datagov-deploy-jenkins", + "https://github.com/GSA/usagov-50", + "https://github.com/GSA/the-foundation-project", + "https://github.com/GSA/TDE", + "https://github.com/GSA/sds-icons", + "https://github.com/GSA/FM-ARCS", + "https://github.com/GSA/grace-inventory", + "https://github.com/GSA/grace-cloudcustodian", + "https://github.com/GSA/CoE-MPT", + "https://github.com/GSA/coe-jaic-acquisitions", + "https://github.com/GSA/odp-gcp-project-setup", + "https://github.com/GSA/cio-gov-application-rationalization-playbook", + "https://github.com/GSA/odp-tf-google-appengine", + "https://github.com/GSA/cic", + "https://github.com/GSA/digitalgov-usability", + "https://github.com/GSA/odp-terraform-validator-example", + "https://github.com/GSA/tts-a11y-guild", + "https://github.com/GSA/sf-trigger-framework", + "https://github.com/GSA/MD-Automated-Text-Analysis", + "https://github.com/GSA/coe-opm-calculation-service", + "https://github.com/GSA/coe-opm-app-replacement", + "https://github.com/GSA/touchpoints-maintenance-page", + "https://github.com/GSA/sds-docs-content", + "https://github.com/GSA/fedramp-automation", + "https://github.com/GSA/site-scanning-documentation", + "https://github.com/GSA/sds-docs-site", + "https://github.com/GSA/odp-tf-aws-ref-arch-iam", + "https://github.com/GSA/odp-tf-aws-ref-arch-cloudwatch-monitoring", + "https://github.com/GSA/odp-tf-aws-ref-arch-config", + "https://github.com/GSA/grace-doc-gen", + "https://github.com/GSA/coe-opm-dbpa-data-store", + "https://github.com/GSA/grace-fcs-network", + "https://github.com/GSA/FM-RSNAP-MIGRATED", + "https://github.com/GSA/VRM-DONOTUSE", + "https://github.com/GSA/odp-code-repository-commit-rules", + "https://github.com/GSA/ci-phpunit-test", + "https://github.com/GSA/FM-GSA.FM.Utility.Core-MIGRATED", + "https://github.com/GSA/benchmarking-validation-reports", + "https://github.com/GSA/DBMW-Inventory-Repo", + "https://github.com/GSA/serverless-transit-network-orchestrator", + "https://github.com/GSA/webob", + "https://github.com/GSA/DBMW-Tower-Inventory", + "https://github.com/GSA/grace-log-parser", + "https://github.com/GSA/odp-tf-aws-ref-arch-guardduty", + "https://github.com/GSA/grace-alerting", + "https://github.com/GSA/grace-config", + "https://github.com/GSA/Digital-Innovation-Division", + "https://github.com/GSA/coe-gao-acquisitions", + "https://github.com/GSA/coe-dol-acquisitions", + "https://github.com/GSA/grace-config-differ", + "https://github.com/GSA/grace-iam", + "https://github.com/GSA/Challenge_gov", + "https://github.com/GSA/tgw-customer-template", + "https://github.com/GSA/datagov-compliance", + "https://github.com/GSA/cloudgov-demo-postgrest", + "https://github.com/GSA/search-gov-website", + "https://github.com/GSA/ERIS", + "https://github.com/GSA/CFO.gov", + "https://github.com/GSA/TestRepo", + "https://github.com/GSA/SRS", + "https://github.com/GSA/IMD", + "https://github.com/GSA/ckanext-collections", + "https://github.com/GSA/Lightweight-Trigger-Framework", + "https://github.com/GSA/sam-static-content", + "https://github.com/GSA/FM-financeweb-MIGRATED", + "https://github.com/GSA/usagov-lambda", + "https://github.com/GSA/Acquisition-Supplemental-Regulations", + "https://github.com/GSA/grace-paas-network", + "https://github.com/GSA/grace-paas-dns", + "https://github.com/GSA/NewPay", + "https://github.com/GSA/odp-testowner", + "https://github.com/GSA/catalog.data.gov", + "https://github.com/GSA/IMD-ePMR-Dashboard-Reporting-Sub-team", + "https://github.com/GSA/grace-paas-rds", + "https://github.com/GSA/coe-nichd-acquisitions", + "https://github.com/GSA/coe-fda-acquisitions", + "https://github.com/GSA/GEAR3", + "https://github.com/GSA/rocis-eda", + "https://github.com/GSA/sam-design-system-challenge", + "https://github.com/GSA/grace-rotate-accesskeys", + "https://github.com/GSA/odp-jenkins-jte", + "https://github.com/GSA/FRPP-ra-2020", + "https://github.com/GSA/CSS_2020_text_analysis", + "https://github.com/GSA/ai-experience-sharing-platform", + "https://github.com/GSA/ckanext-datagovcatalog", + "https://github.com/GSA/odp-ansible-cylance", + "https://github.com/GSA/grace-ansible-lambda", + "https://github.com/GSA/uswds-sf-lightning-community", + "https://github.com/GSA/PBS-USCourtsWeb", + "https://github.com/GSA/GSA-Acquisition-DFARS", + "https://github.com/GSA/cloud-service-broker", + "https://github.com/GSA/github-copy", + "https://github.com/GSA/datagov-tf-eks-helm", + "https://github.com/GSA/CorpIT-ScreeningTool", + "https://github.com/GSA/oscal-sap-to-word", + "https://github.com/GSA/oscal-sar-to-word", + "https://github.com/GSA/oscal-gen-tool", + "https://github.com/GSA/oscal-ssp-to-word", + "https://github.com/GSA/grace-ansible-template", + "https://github.com/GSA/datagov-deploy-fgdc2iso", + "https://github.com/GSA/ckanext-react_usmetadata", + "https://github.com/GSA/ansible-bigfix", + "https://github.com/GSA/FMIT-VCSS-APP", + "https://github.com/GSA/grace-paas-elb", + "https://github.com/GSA/HRM-Case-Management", + "https://github.com/GSA/PD-Library", + "https://github.com/GSA/cg-fork-test", + "https://github.com/GSA/grace-ansible-batch", + "https://github.com/GSA/Project-360-Executive-Business-Case", + "https://github.com/GSA/datagov-ssb", + "https://github.com/GSA/ckanext-dcat_usmetadata", + "https://github.com/GSA/ansible-bit9", + "https://github.com/GSA/ansible-cylance", + "https://github.com/GSA/ansible-nessus", + "https://github.com/GSA/ansible-fireeye", + "https://github.com/GSA/Controlled-Document-Tracker", + "https://github.com/GSA/odp-ansible-fireeye", + "https://github.com/GSA/cloudwatch-ansible-callback-plugin", + "https://github.com/GSA/hello-world", + "https://github.com/GSA/ansible-cloudwatch", + "https://github.com/GSA/ansible-snare", + "https://github.com/GSA/ansible-vrealize_orchestrator", + "https://github.com/GSA/ansible-firstboot", + "https://github.com/GSA/cdoc", + "https://github.com/GSA/ansible-solarwinds", + "https://github.com/GSA/fpc.gov", + "https://github.com/GSA/grace-secrets-sync-lambda", + "https://github.com/GSA/template-brokerpak", + "https://github.com/GSA/sectools-terraform-jenkins", + "https://github.com/GSA/sectools-ansible-jenkins", + "https://github.com/GSA/ansible-role-docker", + "https://github.com/GSA/odp-ansible-cis-docker", + "https://github.com/GSA/odp-image-build-example", + "https://github.com/GSA/ansible-forescout", + "https://github.com/GSA/grace-paas-backup", + "https://github.com/GSA/odp-eks-sample", + "https://github.com/GSA/odp-ansible-cis-eks-worker", + "https://github.com/GSA/GSA-DITA-OT-ToolKit-Developer", + "https://github.com/GSA/FM-PaymentSearch-MIGRATED", + "https://github.com/GSA/HRIT-LA-URS", + "https://github.com/GSA/fas-styles", + "https://github.com/GSA/ansible-os-win-2019", + "https://github.com/GSA/twitter", + "https://github.com/GSA/HRQSMO", + "https://github.com/GSA/ansible-endgame", + "https://github.com/GSA/grace-ecr", + "https://github.com/GSA/site-scanning-engine", + "https://github.com/GSA/acq-policy-analaysis", + "https://github.com/GSA/odp-sonatype-poc", + "https://github.com/GSA/grace-ansible-notifier", + "https://github.com/GSA/grace-decider", + "https://github.com/GSA/covid-screener-gsa.gov", + "https://github.com/GSA/ansible-rhel-domain", + "https://github.com/GSA/HRIT-LA-URS-3.1", + "https://github.com/GSA/HRIT-QMS-3.1", + "https://github.com/GSA/etc_environment", + "https://github.com/GSA/ficam-playbooks", + "https://github.com/GSA/ansible-os-amazon-linux2-eks", + "https://github.com/GSA/SF-reCAPTCHA-Enterprise", + "https://github.com/GSA/jenkins-shared-library-examples", + "https://github.com/GSA/ise-jenkins-shared-library", + "https://github.com/GSA/FM-FEDPAY-PORTAL-MIGRATED", + "https://github.com/GSA/ise-ansible-nessus-agent", + "https://github.com/GSA/max-gov", + "https://github.com/GSA/ise-hardened-docker-example", + "https://github.com/GSA/datagov-load-testing", + "https://github.com/GSA/CorpIT-CC_Migration_Sandbox", + "https://github.com/GSA/datagov-terraform-ecs-solr", + "https://github.com/GSA/ansible-os-ubuntu18", + "https://github.com/GSA/odp-ansible-common-utils", + "https://github.com/GSA/sectools-deploy-jenkins", + "https://github.com/GSA/geo-vm-inventory", + "https://github.com/GSA/terraform-kubernetes-aws-load-balancer-controller", + "https://github.com/GSA/git-quick-start", + "https://github.com/GSA/PerformanceGov", + "https://github.com/GSA/datagov-iam", + "https://github.com/GSA/odp-container-audit-log-best-practice", + "https://github.com/GSA/odp-aws-secretsmanager-poc", + "https://github.com/GSA/odp-ansible-endgame", + "https://github.com/GSA/dx-pgadmin", + "https://github.com/GSA/odp-cdk-example", + "https://github.com/GSA/searchgov_style", + "https://github.com/GSA/Trump-archives-performance-gov", + "https://github.com/GSA/odp-packer-ubuntu-eks", + "https://github.com/GSA/FM-FEDPAY-Test-Automation-GU", + "https://github.com/GSA/FM-UiPath-ActivityPack", + "https://github.com/GSA/odp-ansible-winlogbeat", + "https://github.com/GSA/site-scanning-query-builder", + "https://github.com/GSA/odp-ansible-windows2019", + "https://github.com/GSA/odp-tf-prisma-deps", + "https://github.com/GSA/ussm2.0", + "https://github.com/GSA/covid19-dashboard", + "https://github.com/GSA/csb-brokerpak-aws", + "https://github.com/GSA/datagov-datapusher", + "https://github.com/GSA/SaferFederalWorkforce.gov", + "https://github.com/GSA/cwa_ng", + "https://github.com/GSA/EDX", + "https://github.com/GSA/commit_hook", + "https://github.com/GSA/slack-norms", + "https://github.com/GSA/cloud-gov-manifests", + "https://github.com/GSA/fss19-cis-contract-service", + "https://github.com/GSA/datagov-logstack", + "https://github.com/GSA/odp-jenkins-hardening-pipeline", + "https://github.com/GSA/pyfpds", + "https://github.com/GSA/AI_Grand_Challenge_For_Resiliency", + "https://github.com/GSA/ai-experience-sharing-upptime", + "https://github.com/GSA/odp-techdoc", + "https://github.com/GSA/ag-api", + "https://github.com/GSA/Section508.gov", + "https://github.com/GSA/datagov-docker", + "https://github.com/GSA/odp-anchore-poc", + "https://github.com/GSA/spba-elastic", + "https://github.com/GSA/ansible-os-rhel8", + "https://github.com/GSA/ogp_platform_terraform", + "https://github.com/GSA/pr-test", + "https://github.com/GSA/odp-artifactory-proxy-poc", + "https://github.com/GSA/swagger-ui", + "https://github.com/GSA/icew-static-sandbox", + "https://github.com/GSA/icew-test", + "https://github.com/GSA/federal-website-index", + "https://github.com/GSA/ogp_plotly_terraform", + "https://github.com/GSA/GSA-Acquisition-DAFFARS", + "https://github.com/GSA/ogp_drupal_terraform", + "https://github.com/GSA/site-scanning", + "https://github.com/GSA/ogp_streamsets_terraform", + "https://github.com/GSA/odp-terraform-eks-bsp-sec", + "https://github.com/GSA/ansible-os-amazon-linux2", + "https://github.com/GSA/ngx-uswds", + "https://github.com/GSA/eoc", + "https://github.com/GSA/ogp_elasticsearch_terraform", + "https://github.com/GSA/pygments", + "https://github.com/GSA/ogp_drupal_db_terraform", + "https://github.com/GSA/itvmo", + "https://github.com/GSA/digital-scorecard", + "https://github.com/GSA/odp-tf-anchore-deps", + "https://github.com/GSA/odp-jenkins-anchore-scan-poc", + "https://github.com/GSA/gsaAdvantage-TestAutomation", + "https://github.com/GSA/usagov-benefits-eligibility-rules", + "https://github.com/GSA/odp-helm-chart-stackrox-sensor", + "https://github.com/GSA/CIS_OLD", + "https://github.com/GSA/ansible-role-tomcat", + "https://github.com/GSA/ngx-uswds-icons", + "https://github.com/GSA/SF-Katalon-VISION", + "https://github.com/GSA/idmanagement.gov", + "https://github.com/GSA/ECASDAS_BASE_CONFIG", + "https://github.com/GSA/ECASDAS_BASE_DRUPAL", + "https://github.com/GSA/ECASDAS_DRUPAL_APP1", + "https://github.com/GSA/ECASDAS_DRUPAL_APP2", + "https://github.com/GSA/ECASDAS_DRUPAL_APP3", + "https://github.com/GSA/odp-artifactory", + "https://github.com/GSA/digitalcorps.gsa.gov", + "https://github.com/GSA/aws-access-key-rotation-lambda", + "https://github.com/GSA/odp-artifactory-anchore", + "https://github.com/GSA/odp-jenkins-container-hardening-pipeline", + "https://github.com/GSA/PPMS-API", + "https://github.com/GSA/mule-easi-system-api", + "https://github.com/GSA/SF-Katalon-RSAP", + "https://github.com/GSA/openacr", + "https://github.com/GSA/cio-aia", + "https://github.com/GSA/G1ToG2Conversion", + "https://github.com/GSA/mule-r7migration-system-api", + "https://github.com/GSA/mule-r3demo-system-api", + "https://github.com/GSA/mule-epm-system-api", + "https://github.com/GSA/openacr-website", + "https://github.com/GSA/SF-Katalon-REDIFORCE", + "https://github.com/GSA/SF-Katalon-RSAP-GREX-Load-Test-Testing", + "https://github.com/GSA/SF-Katalon-CMLS-Sandbox_1INTp", + "https://github.com/GSA/cloud-identity-playbook", + "https://github.com/GSA/wg-web-modernization", + "https://github.com/GSA/oscal-poam-to-excel", + "https://github.com/GSA/devtraining-needit-quebec", + "https://github.com/GSA/GSA-FAI-D9", + "https://github.com/GSA/Testscanpoc-Sunny", + "https://github.com/GSA/ciss-iaas-baseline", + "https://github.com/GSA/AppRatDataDictionary", + "https://github.com/GSA/iaas-ingress-vpc", + "https://github.com/GSA/FM-FEDPAY-Test-Automation-Vendor", + "https://github.com/GSA/gsaEbuy-TestAutomation", + "https://github.com/GSA/iaas-transit-gateway", + "https://github.com/GSA/iaas-iam", + "https://github.com/GSA/mule-rediforce-api", + "https://github.com/GSA/odp-Jenkins-image-scan", + "https://github.com/GSA/ECASDAS_BASE_INFRA", + "https://github.com/GSA/grace-tfvars", + "https://github.com/GSA/ckanext-envvars", + "https://github.com/GSA/ciss-iaas-iam", + "https://github.com/GSA/g-iaas-dns", + "https://github.com/GSA/ciss-iaas-network", + "https://github.com/GSA/aws-terraform-executor", + "https://github.com/GSA/ciss-infra-tenant", + "https://github.com/GSA/tweetstream", + "https://github.com/GSA/iaas-networking", + "https://github.com/GSA/arp-cicd", + "https://github.com/GSA/federalist-uswds-jekyll", + "https://github.com/GSA/mule-r4-migration-system-api", + "https://github.com/GSA/ciss-utils", + "https://github.com/GSA/terraform-aws-alb", + "https://github.com/GSA/afp-progressive-web-app", + "https://github.com/GSA/SF-Katalon-CRM", + "https://github.com/GSA/frpp_d2d_auth", + "https://github.com/GSA/sf-lightning-roadmap", + "https://github.com/GSA/ciss-rotate-circleci-lambda", + "https://github.com/GSA/ciss-iaas-alerting", + "https://github.com/GSA/CISSPortal", + "https://github.com/GSA/ciss-iaas-bootstrap", + "https://github.com/GSA/snyktest", + "https://github.com/GSA/GSA-ECAS-GSAGOV", + "https://github.com/GSA/okta-sign-in-screens", + "https://github.com/GSA/datagov-website", + "https://github.com/GSA/dxcore-pricing-web", + "https://github.com/GSA/dxcore-pricing-calc", + "https://github.com/GSA/sam-maintenance", + "https://github.com/GSA/mule-oabill-system-api", + "https://github.com/GSA/techradar", + "https://github.com/GSA/sam-layouts", + "https://github.com/GSA/HRQMS6", + "https://github.com/GSA/public-benefits-studio", + "https://github.com/GSA/odp-ansible-bigfix", + "https://github.com/GSA/openacr-editor", + "https://github.com/GSA/cybersecurity-readiness-assessment-2021", + "https://github.com/GSA/SF-Katalon-AAAP", + "https://github.com/GSA/developer-handbook", + "https://github.com/GSA/acrIntegration-TestAutomation", + "https://github.com/GSA/cf-backup-manager", + "https://github.com/GSA/eBuy-TestAutomation", + "https://github.com/GSA/live-docs", + "https://github.com/GSA/technology-modernization-fund-v2", + "https://github.com/GSA/datagov-wp-migration", + "https://github.com/GSA/datagov-s3-migrate", + "https://github.com/GSA/InteragencyCollaboration", + "https://github.com/GSA/vcrpm-cli", + "https://github.com/GSA/vcrpm-server", + "https://github.com/GSA/mule-euas-system-api", + "https://github.com/GSA/SF-Katalon-PPRT", + "https://github.com/GSA/made-in-america-forms", + "https://github.com/GSA/GSA-Acquisition-AFARS", + "https://github.com/GSA/GSA-Acquisition-NMCARS", + "https://github.com/GSA/GSA-Acquisition-SOFARS", + "https://github.com/GSA/GSA-Acquisition-DARS", + "https://github.com/GSA/GSA-Acquisition-DLAD", + "https://github.com/GSA/ogp_osdbu", + "https://github.com/GSA/threat-analysis", + "https://github.com/GSA/thingie", + "https://github.com/GSA/odp-jenkins-nessus-scan-pipeline", + "https://github.com/GSA/MD-Website-Monitor", + "https://github.com/GSA/OneHR", + "https://github.com/GSA/made-in-america-django", + "https://github.com/GSA/epa-forms", + "https://github.com/GSA/made-in-america-samkeycheck", + "https://github.com/GSA/fcsm", + "https://github.com/GSA/MD-FPDS-Atom-Feeds", + "https://github.com/GSA/MD-Topics-Analyser", + "https://github.com/GSA/odp-ami-hardening-pipeline-lockdown", + "https://github.com/GSA/datagov-11ty", + "https://github.com/GSA/MD-fleet-asset-level-data-cleanup", + "https://github.com/GSA/VISION-CICD", + "https://github.com/GSA/odp-tf-stackrox-report", + "https://github.com/GSA/odp-tf-prisma", + "https://github.com/GSA/service-delivery", + "https://github.com/GSA/SF-Katalon-LOP-AAAP-BDD", + "https://github.com/GSA/PROJECT-CICD", + "https://github.com/GSA/search-services", + "https://github.com/GSA/odp-jenkins-stackrox-image-publishing-pipeline", + "https://github.com/GSA/odp-jenkins-stackrox-reporting-pipeline", + "https://github.com/GSA/GSA-Acquisition-VAAR", + "https://github.com/GSA/GSA-Acquisition-DIAR", + "https://github.com/GSA/elasticsearch-ruby", + "https://github.com/GSA/MA-per-diem-embedded-map", + "https://github.com/GSA/tts-brokerpak-clouddev", + "https://github.com/GSA/odp-aml2-os-hardening-role", + "https://github.com/GSA/odp-aml2-eks-worker-node-hardening-role", + "https://github.com/GSA/notifications-api", + "https://github.com/GSA/notifications-admin", + "https://github.com/GSA/odp-aml2-eks-ami-hardened-pipeline", + "https://github.com/GSA/GSA-Acquisition-AGAR", + "https://github.com/GSA/GSA-Acquisition-AIDAR", + "https://github.com/GSA/GSA-Acquisition-CAR", + "https://github.com/GSA/GSA-Acquisition-DEAR", + "https://github.com/GSA/GSA-Acquisition-DOLAR", + "https://github.com/GSA/GSA-Acquisition-DOSAR", + "https://github.com/GSA/GSA-Acquisition-DTAR", + "https://github.com/GSA/GSA-Acquisition-EDAR", + "https://github.com/GSA/GSA-Acquisition-EPAAR", + "https://github.com/GSA/GSA-Acquisition-FEHBAR", + "https://github.com/GSA/GSA-Acquisition-HHSAR", + "https://github.com/GSA/GSA-Acquisition-HSAR", + "https://github.com/GSA/GSA-Acquisition-HUDAR", + "https://github.com/GSA/GSA-Acquisition-JAR", + "https://github.com/GSA/GSA-Acquisition-NRCAR", + "https://github.com/GSA/GSA-Acquisition-TAR", + "https://github.com/GSA/GSA-Acquisition-IAAR", + "https://github.com/GSA/GSA-Acquisition-LIFAR", + "https://github.com/GSA/GSA-Acquisition-NFS", + "https://github.com/GSA/GSA-Acquisition-CASBAR", + "https://github.com/GSA/ckanext-saml2auth", + "https://github.com/GSA/gtm-test", + "https://github.com/GSA/gtm", + "https://github.com/GSA/aws-broker", + "https://github.com/GSA/cx-working-group", + "https://github.com/GSA/ProvenOptics", + "https://github.com/GSA/CSOD-EHRI", + "https://github.com/GSA/aws-trustedadvisor-reports", + "https://github.com/GSA/mas-prototype", + "https://github.com/GSA/icsp", + "https://github.com/GSA/assets.FCSM", + "https://github.com/GSA/made-in-america-iac", + "https://github.com/GSA/made-in-america-iac-modules", + "https://github.com/GSA/finearts-mockup", + "https://github.com/GSA/beta.performance.gov", + "https://github.com/GSA/mule-vision-system-api", + "https://github.com/GSA/CorpIT-ESB-Mirror", + "https://github.com/GSA/sd-prototyping-template", + "https://github.com/GSA/sd-11ty-cloud-prototype", + "https://github.com/GSA/US-performance-reporting", + "https://github.com/GSA/HRQMS-2.0", + "https://github.com/GSA/marketplace-fedramp-gov", + "https://github.com/GSA/GCPA-ide-prv-casesactapp-1", + "https://github.com/GSA/made-in-america-forms-service", + "https://github.com/GSA/made-in-america-forms-service-iac", + "https://github.com/GSA/made-in-america-forms-service-iac-modules", + "https://github.com/GSA/GCPA-h1p-oas-cdtapp-1", + "https://github.com/GSA/us-notify-compliance", + "https://github.com/GSA/cfo-redesign", + "https://github.com/GSA/HR-QMS-1.x-RefactoredNotifications", + "https://github.com/GSA/notifications-utils", + "https://github.com/GSA/hbdr2", + "https://github.com/GSA/notify-python-demo", + "https://github.com/GSA/HR-QMS-2.x", + "https://github.com/GSA/pulse-survey-analysis", + "https://github.com/GSA/assets_1.cfo", + "https://github.com/GSA/assets.CFO", + "https://github.com/GSA/pgov-docs", + "https://github.com/GSA/CloudFRPP", + "https://github.com/GSA/assets.cfo.gov", + "https://github.com/GSA/smart_pay_setup", + "https://github.com/GSA/PBS-USCourtsWeb-Workplace2030", + "https://github.com/GSA/ckanext-metrics_dashboard", + "https://github.com/GSA/made-in-america-forms-service-image", + "https://github.com/GSA/ttsnotify-brokerpak-sms", + "https://github.com/GSA/odp-ansible-elp", + "https://github.com/GSA/cpct-tool", + "https://github.com/GSA/futureofwork.gsa.gov", + "https://github.com/GSA/site-scanning-analysis", + "https://github.com/GSA/made-in-america-load-test", + "https://github.com/GSA/ART", + "https://github.com/GSA/889-tool", + "https://github.com/GSA/ODSHRDW", + "https://github.com/GSA/vote-gov-d10", + "https://github.com/GSA/889-vue", + "https://github.com/GSA/afp-pegasys-test", + "https://github.com/GSA/SF-Katalon-NCMT-Project", + "https://github.com/GSA/smartpay-website", + "https://github.com/GSA/edms-update-user-groups", + "https://github.com/GSA/HRIT-QMS-6.x", + "https://github.com/GSA/odp-sectools-stackrox-policies", + "https://github.com/GSA/odp-master", + "https://github.com/GSA/SF-Katalon-NCMT", + "https://github.com/GSA/ansible-os-ubuntu20", + "https://github.com/GSA/site-scanning-snapshots", + "https://github.com/GSA/wp2030-microsite", + "https://github.com/GSA/OneHRv2", + "https://github.com/GSA/FCcore", + "https://github.com/GSA/oes-msg-voting_description", + "https://github.com/GSA/2233-USWDS-Digital-Dashboard", + "https://github.com/GSA/2312-Occupancy-Patterns", + "https://github.com/GSA/made-in-america-static-assets", + "https://github.com/GSA/made-in-america-forms-tools", + "https://github.com/GSA/assets.cio.gov", + "https://github.com/GSA/workplace-microsite", + "https://github.com/GSA/uswds", + "https://github.com/GSA/rmarkdown-discussion", + "https://github.com/GSA/usnotify-ssb", + "https://github.com/GSA/smartpay-training", + "https://github.com/GSA/us-performance-reporting-archive", + "https://github.com/GSA/oesrrr", + "https://github.com/GSA/marketplace-fedramp-gov-data", + "https://github.com/GSA/odp-whispers-poc", + "https://github.com/GSA/datagov-harvester-test-cloudgov", + "https://github.com/GSA/datagov-harvester-test-aws", + "https://github.com/GSA/mdTranslator", + "https://github.com/GSA/odp-whispers-demo", + "https://github.com/GSA/odp-VulnerableWebApp", + "https://github.com/GSA/SmartPay-RFI", + "https://github.com/GSA/cg-cli-tools", + "https://github.com/GSA/fake-data", + "https://github.com/GSA/px-bears-drupal", + "https://github.com/GSA/datagov-harvesting-logic", + "https://github.com/GSA/Sustainable-IT-Procurement-Lexicon", + "https://github.com/GSA/msg_project_template", + "https://github.com/GSA/ansible-os-rhel7", + "https://github.com/GSA/CX-Jupyter-Notebooks", + "https://github.com/GSA/Strategic-Atlas", + "https://github.com/GSA/dms-ansible-inv", + "https://github.com/GSA/FASSRP-ContractsAPI", + "https://github.com/GSA/odp-jenkins-stackrox-policies-deployment-pipeline", + "https://github.com/GSA/robotex", + "https://github.com/GSA/deployer", + "https://github.com/GSA/EDX-test-website", + "https://github.com/GSA/search-gov-indexing", + "https://github.com/GSA/itcollect-data-capture-schemas", + "https://github.com/GSA/HISP-CX-Analysis", + "https://github.com/GSA/research-portal", + "https://github.com/GSA/ChallengeGov_FrontEnd", + "https://github.com/GSA/lighthouse-plugin-edx", + "https://github.com/GSA/FPKI_AR_Submissions", + "https://github.com/GSA/HRIT-QMS-ParTranRetry", + "https://github.com/GSA/EDX-github-action", + "https://github.com/GSA/rer-dms-ansible-inv", + "https://github.com/GSA/odp-ansible-elastic-agent", + "https://github.com/GSA/gtcop-wiki", + "https://github.com/GSA/FME", + "https://github.com/GSA/msg-tribal-acquisition", + "https://github.com/GSA/PerformanceGov-RFI", + "https://github.com/GSA/2332-MSG-USCIS-Votegov-Messages", + "https://github.com/GSA/Dynamo", + "https://github.com/GSA/FASSRP-SalesAPI", + "https://github.com/GSA/FASSRP-PaymentsAPI", + "https://github.com/GSA/SDM_Standards", + "https://github.com/GSA/SmartPay-RFQ", + "https://github.com/GSA/devtraining-needit-sandiego", + "https://github.com/GSA/devtraining-needit-sandiego-1", + "https://github.com/GSA/sdg-data-usa-staging", + "https://github.com/GSA/tutorial-test-repo", + "https://github.com/GSA/odp-k8s-elastic-agent", + "https://github.com/GSA/HISP-CX-Data", + "https://github.com/GSA/open-science-exploratory-workshop", + "https://github.com/GSA/MSG-2315-telework", + "https://github.com/GSA/EDX-chrome-extension", + "https://github.com/GSA/ECD-Ansible", + "https://github.com/GSA/GovCXAnalyzer", + "https://github.com/GSA/oescolorrrs", + "https://github.com/GSA/ux-team", + "https://github.com/GSA/ecd-analytics-session-manager", + "https://github.com/GSA/ansible-os-ubuntu22", + "https://github.com/GSA/VoC-Analysis", + "https://github.com/GSA/px-benefit-finder", + "https://github.com/GSA/oasis-plus", + "https://github.com/GSA/ACR-schema", + "https://github.com/GSA/datagov-harvester-airflow", + "https://github.com/GSA/adv-ebuy-eda-etl", + "https://github.com/GSA/StrategicAtlas", + "https://github.com/GSA/D2D-Kanban-Automation", + "https://github.com/GSA/afp-sandbox", + "https://github.com/GSA/EIS-data-analysis", + "https://github.com/GSA/GovCXAI4VoCLab", + "https://github.com/GSA/FEDSIM_Business_Intelligence_EOYDashboard", + "https://github.com/GSA/oasis-prototype", + "https://github.com/GSA/supplier-portal-rfi", + "https://github.com/GSA/2317-Federal-Coworking-Developmental-Phase-Evaluation", + "https://github.com/GSA/BOD_NCSCData", + "https://github.com/GSA/BOD_FPDSDataToDB", + "https://github.com/GSA/ckanext-googleanalytics", + "https://github.com/GSA/cmo-ad-hoc", + "https://github.com/GSA/cmo-team-ops", + "https://github.com/GSA/.allstar", + "https://github.com/GSA/CIC-Automation", + "https://github.com/GSA/DPA-Automation", + "https://github.com/GSA/TSCPortal-Automation", + "https://github.com/GSA/cmo-community-of-practice", + "https://github.com/GSA/ebuy_api", + "https://github.com/GSA/cmo-google-website", + "https://github.com/GSA/BOD_py_Emailer", + "https://github.com/GSA/ise-diagrams", + "https://github.com/GSA/ociso-site", + "https://github.com/GSA/ADV-Mail", + "https://github.com/GSA/ADV-eLibrary-DownloadContracts", + "https://github.com/GSA/ise-engagements", + "https://github.com/GSA/fedramp-oscal-earlyadopters", + "https://github.com/GSA/TestDemo", + "https://github.com/GSA/FASSRP-EmailerAPI", + "https://github.com/GSA/dev-docs", + "https://github.com/GSA/searchgov-tf", + "https://github.com/GSA/searchgov-ansible", + "https://github.com/GSA/ag-automation", + "https://github.com/GSA/datagov-harvest-transformer", + "https://github.com/GSA/14110s101h", + "https://github.com/GSA/afp-docker-setup", + "https://github.com/GSA/tsc-clamav", + "https://github.com/GSA/srt-user-management", + "https://github.com/GSA/OSCAL", + "https://github.com/GSA/DigitalCXAnalyzer", + "https://github.com/GSA/ansible-os-rhel9", + "https://github.com/GSA/GSA_BIA_PDFOCR", + "https://github.com/GSA/BABS-SQL", + "https://github.com/GSA/datagov-harvest-orchestrator", + "https://github.com/GSA/datagov-harvest-ui", + "https://github.com/GSA/The-AI-Community-of-Practice", + "https://github.com/GSA/us-tech-policy", + "https://github.com/GSA/openacr-editor-stage", + "https://github.com/GSA/KaiPersonal", + "https://github.com/GSA/Flask_harvest_app", + "https://github.com/GSA/afp-catalog-public-svc", + "https://github.com/GSA/ART-API", + "https://github.com/GSA/identity-oscal", + "https://github.com/GSA/odp-ansible-bit9", + "https://github.com/GSA/gsa-displacy-demo", + "https://github.com/GSA/Staffing", + "https://github.com/GSA/ise-arch-review", + "https://github.com/GSA/ansible-os-amazon-linux-2023", + "https://github.com/GSA/multi-tenant-emr-uat-test", + "https://github.com/GSA/searchgov-k8s", + "https://github.com/GSA/odp-prod-ecr", + "https://github.com/GSA/odp-wiki", + "https://github.com/GSA/rmReportTool", + "https://github.com/GSA/searchgov-spider", + "https://github.com/GSA/APG-Pilot-AI-Editor", + "https://github.com/GSA/eOfferMVN-Dependencies", + "https://github.com/GSA/automate.fedramp.gov", + "https://github.com/GSA/gsa-auth-web", + "https://github.com/GSA/uswds-hugo", + "https://github.com/GSA/MSG-2431-Creating-Effective-Messaging", + "https://github.com/GSA/MSG-2411-Core-Days", + "https://github.com/GSA/beta-gsa", + "https://github.com/GSA/gearTestingFramework", + "https://github.com/GSA/MSG-2414-SmallBusinessForecasting", + "https://github.com/GSA/MSG-2415-RetirementForecasting", + "https://github.com/GSA/code-reporting-poc", + "https://github.com/GSA/fedramp-ai", + "https://github.com/GSA/mobile-fu", + "https://github.com/GSA/rails-google-visualization-plugin", + "https://github.com/GSA/apache-log-parser", + "https://github.com/GSA/active_scaffold", + "https://github.com/GSA/fckeditor", + "https://github.com/GSA/aws-s3", + "https://github.com/GSA/capistrano", + "https://github.com/GSA/sunspot", + "https://github.com/GSA/resque-priority", + "https://github.com/GSA/open311-simple-crm", + "https://github.com/GSA/datafiles-wordpress-plugin", + "https://github.com/GSA/federal-open-source-repos-php", + "https://github.com/GSA/federal-open-source-repos", + "https://github.com/GSA/federal-open-source-repos-ruby", + "https://github.com/GSA/gogogon", + "https://github.com/GSA/ckanext-geodatagov", + "https://github.com/GSA/digital-strategy", + "https://github.com/GSA/digital-strategy-report-generator", + "https://github.com/GSA/ruby-cloudfiles", + "https://github.com/GSA/us-digital-registry", + "https://github.com/GSA/digital-strategy-drupal-module", + "https://github.com/GSA/oauth2-provider", + "https://github.com/GSA/Open311-Forms-Engine", + "https://github.com/GSA/uReport", + "https://github.com/GSA/open311-proxy", + "https://github.com/GSA/mygov-mobile-first-foundation", + "https://github.com/GSA/slash-developer-pages", + "https://github.com/GSA/pdf-filler", + "https://github.com/GSA/epa_uv_index", + "https://github.com/GSA/apidocs", + "https://github.com/GSA/omniauth-mygov", + "https://github.com/GSA/mygov-bar", + "https://github.com/GSA/mygov-discovery", + "https://github.com/GSA/mygov-forms", + "https://github.com/GSA/db-to-api", + "https://github.com/GSA/DataBeam", + "https://github.com/GSA/benefits-mockup", + "https://github.com/GSA/recalls_api", + "https://github.com/GSA/jobs_api", + "https://github.com/GSA/mygov-feedback-reporting", + "https://github.com/GSA/mygov-account", + "https://github.com/GSA/us_states", + "https://github.com/GSA/labs-html", + "https://github.com/GSA/mygov-account-php-sdk", + "https://github.com/GSA/usa-faqs", + "https://github.com/GSA/idm", + "https://github.com/GSA/unclaimed_money", + "https://github.com/GSA/omniauth-openid", + "https://github.com/GSA/GSA-APIs", + "https://github.com/GSA/usfedgov_google_analytics", + "https://github.com/GSA/alpha-data-dot-gov", + "https://github.com/GSA/ckanext-saml2", + "https://github.com/GSA/datagov-wptheme", + "https://github.com/GSA/rack-openid", + "https://github.com/GSA/SMR-site-embed", + "https://github.com/GSA/Mobile-Code-Catalog", + "https://github.com/GSA/Mobile-Web-Manual-Testing-Script", + "https://github.com/GSA/myusa-account-demo", + "https://github.com/GSA/federal-apps-gallery-widgets", + "https://github.com/GSA/ckanext-usmetadata", + "https://github.com/GSA/mygov-admin-tasks", + "https://github.com/GSA/myusa-tasks", + "https://github.com/GSA/Crowdsource-Testing-USDA_FSIS", + "https://github.com/GSA/hyabusa", + "https://github.com/GSA/modus-operandi", + "https://github.com/GSA/just_inform", + "https://github.com/GSA/just_inform_web", + "https://github.com/GSA/.Gov-Content-as-an-API", + "https://github.com/GSA/ckanext-datajson", + "https://github.com/GSA/project-open-data-dashboard", + "https://github.com/GSA/embedding-data-catalogs", + "https://github.com/GSA/enterprise-data-inventory", + "https://github.com/GSA/capistrano-resque", + "https://github.com/GSA/Crowdsource-Testing-CIO.gov", + "https://github.com/GSA/gman", + "https://github.com/GSA/helio", + "https://github.com/GSA/govt-urls", + "https://github.com/GSA/logo", + "https://github.com/GSA/datagov-design", + "https://github.com/GSA/twitter-widgets-gallery", + "https://github.com/GSA/Template-Microsite", + "https://github.com/GSA/Open-Data-Collaboration-Sandbox", + "https://github.com/GSA/Very-Simple-API", + "https://github.com/GSA/Developer-Feedback-for-Government-APIs", + "https://github.com/GSA/search.digitalgov.gov", + "https://github.com/GSA/API-Resources", + "https://github.com/GSA/ckan-php-client", + "https://github.com/GSA/ckan-php-manager", + "https://github.com/GSA/wp-open311", + "https://github.com/GSA/data_gov_json_validator", + "https://github.com/GSA/open-data-program-template", + "https://github.com/GSA/pod-schema-variants", + "https://github.com/GSA/PricesPaidAPI", + "https://github.com/GSA/LAMP-CentOS-with-Vagrant", + "https://github.com/GSA/ckan", + "https://github.com/GSA/ckanext-harvest", + "https://github.com/GSA/ckanext-spatial", + "https://github.com/GSA/idp", + "https://github.com/GSA/arcgis-map", + "https://github.com/GSA/custom-contact-forms", + "https://github.com/GSA/custom-post-view-generator", + "https://github.com/GSA/datagov-custom", + "https://github.com/GSA/metric-count", + "https://github.com/GSA/restrict-categories", + "https://github.com/GSA/saml-20-single-sign-on", + "https://github.com/GSA/sticky-posts-in-category", + "https://github.com/GSA/suggested-datasets", + "https://github.com/GSA/twitter-posts-to-blog", + "https://github.com/GSA/twitter-widget-pro", + "https://github.com/GSA/usa-search", + "https://github.com/GSA/wordpress-seo", + "https://github.com/GSA/Open-And-Structured-Content-Models", + "https://github.com/GSA/Crowdsource-Testing-DFAS.mil", + "https://github.com/GSA/ckanext-qa", + "https://github.com/GSA/FedCMS-Slider", + "https://github.com/GSA/ckanext-archiver", + "https://github.com/GSA/Crowdsource-Testing-HHS-ACF.gov", + "https://github.com/GSA/open.gsa.gov", + "https://github.com/GSA/instant-comment-validation", + "https://github.com/GSA/asis", + "https://github.com/GSA/simple-tooltips", + "https://github.com/GSA/ckanext-googleanalyticsbasic", + "https://github.com/GSA/wp-external-links", + "https://github.com/GSA/Crowdsource-Testing-NOAA-CrowdMag", + "https://github.com/GSA/Crowdsource-Testing-ABMC.gov", + "https://github.com/GSA/IAE-Architecture", + "https://github.com/GSA/auctions_api", + "https://github.com/GSA/OWSLib", + "https://github.com/GSA/datagov-presentations", + "https://github.com/GSA/testsite922", + "https://github.com/GSA/Crowdsource-Testing-HHS-MAIN", + "https://github.com/GSA/ckanext-report", + "https://github.com/GSA/data.gov-styleguide", + "https://github.com/GSA/developers", + "https://github.com/GSA/data", + "https://github.com/GSA/data.json-template", + "https://github.com/GSA/sites-digitalgov-search", + "https://github.com/GSA/Very-Simple-API-2", + "https://github.com/GSA/sitelink_generator", + "https://github.com/GSA/punchcard", + "https://github.com/GSA/Crowdsource-Testing-NOAA-CrowdMag--iOS", + "https://github.com/GSA/Crowdsource-Testing-Central-Artifact-Repository", + "https://github.com/GSA/cfpb.github.io", + "https://github.com/GSA/social-media-registry-api", + "https://github.com/GSA/api", + "https://github.com/GSA/labs", + "https://github.com/GSA/fssi-file-processor", + "https://github.com/GSA/https", + "https://github.com/GSA/Crowdsource-Testing-NIH-HCI-1-2015", + "https://github.com/GSA/data-json", + "https://github.com/GSA/eMuseum-API", + "https://github.com/GSA/seo", + "https://github.com/GSA/participation-playbook", + "https://github.com/GSA/Holiday-Utility", + "https://github.com/GSA/Membership-Utility", + "https://github.com/GSA/open311-github", + "https://github.com/GSA/Crowdsource-Testing-Connect.gov_3-2015", + "https://github.com/GSA/USA.gov-API-Integration", + "https://github.com/GSA/GitHub-Administration", + "https://github.com/GSA/i14y", + "https://github.com/GSA/agile_accelerator_admin_guide", + "https://github.com/GSA/wp-rss-multi-importer", + "https://github.com/GSA/structured_content_wordpress", + "https://github.com/GSA/GSA-Digital-Innovation", + "https://github.com/GSA/GSA-team-5", + "https://github.com/GSA/Hackathon-Team-10", + "https://github.com/GSA/gsa-digitial-innovation-hackathon", + "https://github.com/GSA/gsa-hackathon-t4", + "https://github.com/GSA/opensource-framework", + "https://github.com/GSA/ckanext-datagovtheme", + "https://github.com/GSA/custom-permalinks", + "https://github.com/GSA/slate", + "https://github.com/GSA/FederalHierarchy-Crosswalk", + "https://github.com/GSA/github-federal-stats", + "https://github.com/GSA/tsd-agile-cm-manifesto", + "https://github.com/GSA/vocab.data.gov", + "https://github.com/GSA/ckanext-extlink", + "https://github.com/GSA/Salesforce-Communities-Login", + "https://github.com/GSA/scopeid-script", + "https://github.com/GSA/tsd-agile-sdlc", + "https://github.com/GSA/wp-digitalgov-i14y-indexer", + "https://github.com/GSA/fssi-file-processor-gui", + "https://github.com/GSA/Crowdsource-Testing-SBA.gov_7-2015", + "https://github.com/GSA/activerecord-validate_unique_child_attribute", + "https://github.com/GSA/font-awesome-grunticon-rails", + "https://github.com/GSA/tsd-ga-framework", + "https://github.com/GSA/Crowdsource-Testing-Federal-Crowdsourcing-and-Citizen-Science-Toolkit_8-2015", + "https://github.com/GSA/wp-sitemap-page", + "https://github.com/GSA/Crowdsource-Testing-TSA.GOV_9-2015", + "https://github.com/GSA/data.gov", + "https://github.com/GSA/catalog-app", + "https://github.com/GSA/pycsw", + "https://github.com/GSA/DataCenterMashup", + "https://github.com/GSA/gsa-hackathon-2015", + "https://github.com/GSA/GSA-2015-Fall", + "https://github.com/GSA/GSA-Fall-Hackathon-GHG", + "https://github.com/GSA/gsa-hackathon", + "https://github.com/GSA/CGI", + "https://github.com/GSA/general-hackathon-administration", + "https://github.com/GSA/Ventera-GSAHackathon", + "https://github.com/GSA/trip", + "https://github.com/GSA/data-center-tool", + "https://github.com/GSA/Crowdsource-Testing-FTC-IdentityTheft.gov_11-2015", + "https://github.com/GSA/ficam-arch", + "https://github.com/GSA/pysaml2", + "https://github.com/GSA/PyZ3950", + "https://github.com/GSA/q-and-a", + "https://github.com/GSA/wp-no-taxonomy-base", + "https://github.com/GSA/cg-manifests", + "https://github.com/GSA/gsa-doc-digital-signature", + "https://github.com/GSA/cg-pipelines", + "https://github.com/GSA/open.gsa.gov.github.io", + "https://github.com/GSA/fpki-guides", + "https://github.com/GSA/piv-guides", + "https://github.com/GSA/datagov-cf-cron", + "https://github.com/GSA/datagov-bosh", + "https://github.com/GSA/logsearch-boshrelease", + "https://github.com/GSA/Crowdsource-Testing-USCIS.gov_2_2016", + "https://github.com/GSA/oauth2_proxy", + "https://github.com/GSA/cg-deploy-concourse", + "https://github.com/GSA/GSADigitalService", + "https://github.com/GSA/FederalProjectSchema", + "https://github.com/GSA/IASHub", + "https://github.com/GSA/sf-sandbox-post-copy", + "https://github.com/GSA/CAP-Documentation", + "https://github.com/GSA/jkan", + "https://github.com/GSA/community-catalog", + "https://github.com/GSA/catalog-solr", + "https://github.com/GSA/catalog-fgdc2iso", + "https://github.com/GSA/catalog-db", + "https://github.com/GSA/catalog-scheduler", + "https://github.com/GSA/inventory-solr", + "https://github.com/GSA/catalog-pycsw", + "https://github.com/GSA/catalog-nginx", + "https://github.com/GSA/NAP-Stat", + "https://github.com/GSA/bwp-external-links", + "https://github.com/GSA/pbs-sensor", + "https://github.com/GSA/jekyll-centos-deploy", + "https://github.com/GSA/us-data-federation", + "https://github.com/GSA/governmentwide-classifications", + "https://github.com/GSA/cto-website", + "https://github.com/GSA/formk8s", + "https://github.com/GSA/angular-toasty", + "https://github.com/GSA/sdg-indicators-usa", + "https://github.com/GSA/api-documentation-template-old", + "https://github.com/GSA/ficam-federation", + "https://github.com/GSA/ficam-management", + "https://github.com/GSA/datapusher", + "https://github.com/GSA/openstack-ansible-security", + "https://github.com/GSA/sam-design-system-site", + "https://github.com/GSA/sam-ui-elements", + "https://github.com/GSA/compliance-docs", + "https://github.com/GSA/open-gsa-redesign", + "https://github.com/GSA/code-gov-web", + "https://github.com/GSA/datagov-wp-boilerplate", + "https://github.com/GSA/ficam-access", + "https://github.com/GSA/ckanext-s3filestore", + "https://github.com/GSA/ficam-identity", + "https://github.com/GSA/lynis", + "https://github.com/GSA/fail2ban", + "https://github.com/GSA/Crowdsource-Testing-DHS.gov_9_2016", + "https://github.com/GSA/opengovplan", + "https://github.com/GSA/ckanext-ga-report", + "https://github.com/GSA/GSAOpenSourceImplementation", + "https://github.com/GSA/ckanext-fulltext", + "https://github.com/GSA/watchdog-test", + "https://github.com/GSA/code-gov-api", + "https://github.com/GSA/sentry", + "https://github.com/GSA/ckanext-cesiumpreview", + "https://github.com/GSA/CorpIT-EARS", + "https://github.com/GSA/codeinventory-metadata-generator", + "https://github.com/GSA/FM-VITAP-MIGRATED", + "https://github.com/GSA/codeinventory", + "https://github.com/GSA/FEDSIM_root", + "https://github.com/GSA/ec2-broker", + "https://github.com/GSA/elastalert", + "https://github.com/GSA/prototype-city-pairs-api", + "https://github.com/GSA/SF-Event-Monitoring-Log-Retrieval", + "https://github.com/GSA/codeinventory-github", + "https://github.com/GSA/sf-ProjectDashboard", + "https://github.com/GSA/api-standards", + "https://github.com/GSA/sdg-nrp-scripts", + "https://github.com/GSA/ansible-role-repo-webtatic", + "https://github.com/GSA/api-documentation-template", + "https://github.com/GSA/prototype-city-pairs-api-documentation", + "https://github.com/GSA/fedramp", + "https://github.com/GSA/ansible-tomcat", + "https://github.com/GSA/sfdx_pilot", + "https://github.com/GSA/accessibility-for-teams", + "https://github.com/GSA/som", + "https://github.com/GSA/DSSAPIDocumentation", + "https://github.com/GSA/third-party-services", + "https://github.com/GSA/fedramp-tailored", + "https://github.com/GSA/GEAR2-NodeJS", + "https://github.com/GSA/aws-cis-scanner", + "https://github.com/GSA/datagov-infrastructure", + "https://github.com/GSA/DOTGOVDASH-archived", + "https://github.com/GSA/FM-ULO-MIGRATED", + "https://github.com/GSA/FM-PegasysWebPortal", + "https://github.com/GSA/FM-FMISWebPortal", + "https://github.com/GSA/digital.gov", + "https://github.com/GSA/sf_ANTbuildfiles", + "https://github.com/GSA/ITDB-schema", + "https://github.com/GSA/ficam-pacs", + "https://github.com/GSA/digitalgov-wordpress", + "https://github.com/GSA/mysql_to_cloudwatch", + "https://github.com/GSA/laptop-management", + "https://github.com/GSA/AI-Assistant-Pilot", + "https://github.com/GSA/apps-gsa-gov", + "https://github.com/GSA/recruiter", + "https://github.com/GSA/CIO.gov", + "https://github.com/GSA/jenkins-deploy", + "https://github.com/GSA/domain-knowledge", + "https://github.com/GSA/hi", + "https://github.com/GSA/icam-fisma", + "https://github.com/GSA/security-benchmarks", + "https://github.com/GSA/ISE-Security-Benchmark-GPOs", + "https://github.com/GSA/digital-governance-outline", + "https://github.com/GSA/ckanext-security", + "https://github.com/GSA/rvm1-ansible", + "https://github.com/GSA/service-design-analytics", + "https://github.com/GSA/Digital-Council", + "https://github.com/GSA/jekyll-rebuilder", + "https://github.com/GSA/AAS_root", + "https://github.com/GSA/open.usa.gov", + "https://github.com/GSA/ansible-role-jenkins", + "https://github.com/GSA/digital.gov-hugo", + "https://github.com/GSA/ansible-microstrategy", + "https://github.com/GSA/digital.gov-design", + "https://github.com/GSA/PSHC_Applets", + "https://github.com/GSA/OMB-Max-Auth-for-Salesforce", + "https://github.com/GSA/terriajs-server", + "https://github.com/GSA/code-gov-admintool", + "https://github.com/GSA/open-source-policy", + "https://github.com/GSA/GSA-UX-UI-Playbook", + "https://github.com/GSA/ansible-https-proxy", + "https://github.com/GSA/CIW", + "https://github.com/GSA/ficam-scvp-testing", + "https://github.com/GSA/QueryToCSV", + "https://github.com/GSA/Suitability", + "https://github.com/GSA/Adjudications", + "https://github.com/GSA/CHRISUpdate", + "https://github.com/GSA/matter-maker", + "https://github.com/GSA/ansible-os-ubuntu-14", + "https://github.com/GSA/participate-nap4", + "https://github.com/GSA/code-gov-admin-backend", + "https://github.com/GSA/innovation.gov", + "https://github.com/GSA/modernization", + "https://github.com/GSA/digitalgov.gov", + "https://github.com/GSA/front-matter-editor", + "https://github.com/GSA/frntmttr", + "https://github.com/GSA/devsecops-example", + "https://github.com/GSA/training-pathway-data-practitioner", + "https://github.com/GSA/gsa-icam-card-builder", + "https://github.com/GSA/ansible-os-rhel-7", + "https://github.com/GSA/CorpIT-GSAResp", + "https://github.com/GSA/datagov-infrastructure-modules", + "https://github.com/GSA/datagov-infrastructure-live", + "https://github.com/GSA/code-gov-gitsecretpatterns", + "https://github.com/GSA/usagov-api", + "https://github.com/GSA/usagov-hub", + "https://github.com/GSA/plainlanguage.gov", + "https://github.com/GSA/DevSecOps", + "https://github.com/GSA/CorpIT-CloudSandbox", + "https://github.com/GSA/fpkilint", + "https://github.com/GSA/CorpIT-ChildCare", + "https://github.com/GSA/DevSecOps-Mgmt-Tools-Deploy", + "https://github.com/GSA/ice-cream", + "https://github.com/GSA/opp-code-gov-web", + "https://github.com/GSA/robots_tag_parser", + "https://github.com/GSA/ansible-role-kibana", + "https://github.com/GSA/ansible-role-nessus-agent", + "https://github.com/GSA/ansible-os-rhel-6", + "https://github.com/GSA/code-gov-harvester-deprecated", + "https://github.com/GSA/ficam-scripts-public", + "https://github.com/GSA/devsecops-cloud-custodian-rules", + "https://github.com/GSA/jz-example", + "https://github.com/GSA/opp-example", + "https://github.com/GSA/devsecops-ekk-stack", + "https://github.com/GSA/digitalgov-chrome", + "https://github.com/GSA/Canada-USA-Digital-Collaboration", + "https://github.com/GSA/feedback.usa.gov", + "https://github.com/GSA/opp-federalist", + "https://github.com/GSA/go.usa.gov", + "https://github.com/GSA/consumer_complaint_letter", + "https://github.com/GSA/voc_admin", + "https://github.com/GSA/voc_public", + "https://github.com/GSA/emerging-technology-atlas", + "https://github.com/GSA/legacy-fedramp-website", + "https://github.com/GSA/code-gov-data", + "https://github.com/GSA/devsecops-jenkins", + "https://github.com/GSA/public-participation", + "https://github.com/GSA/ansible-os-ubuntu-16", + "https://github.com/GSA/newperformancedotgov1", + "https://github.com/GSA/citizenscience.gov", + "https://github.com/GSA/trustymail", + "https://github.com/GSA/code-central", + "https://github.com/GSA/terraform-role", + "https://github.com/GSA/GEAR-Documentation", + "https://github.com/GSA/terraform-aws-vpc", + "https://github.com/GSA/devsecops-example-prod", + "https://github.com/GSA/streamalert", + "https://github.com/GSA/piv-conformance", + "https://github.com/GSA/methods", + "https://github.com/GSA/terraform-vpc-flow-log", + "https://github.com/GSA/api.data.gov-design", + "https://github.com/GSA/inactive-logout", + "https://github.com/GSA/devsecops-fleet", + "https://github.com/GSA/ansible-role-kolide-fleet", + "https://github.com/GSA/terraform", + "https://github.com/GSA/10x", + "https://github.com/GSA/ansible-osquery", + "https://github.com/GSA/opioids.gov", + "https://github.com/GSA/Performance.gov-Maintenance", + "https://github.com/GSA/ansible-fluentd", + "https://github.com/GSA/packer", + "https://github.com/GSA/opp-ops", + "https://github.com/GSA/redir", + "https://github.com/GSA/InterimPerformance-Dot-Gov-2018", + "https://github.com/GSA/unified-shared-services-management", + "https://github.com/GSA/fedramp-gov", + "https://github.com/GSA/privacy-pages", + "https://github.com/GSA/fedramp-modular-experiment", + "https://github.com/GSA/code-gov", + "https://github.com/GSA/datagov-filestore-landing", + "https://github.com/GSA/back-soon", + "https://github.com/GSA/FM-VITAP-OSS-MIGRATED", + "https://github.com/GSA/devsecops-log-forwarding", + "https://github.com/GSA/ecpic-redir", + "https://github.com/GSA/code-gov-api-client", + "https://github.com/GSA/digitalgov-redir", + "https://github.com/GSA/aws-account-broker", + "https://github.com/GSA/time-estimator", + "https://github.com/GSA/BSP_Mode1_Reporting", + "https://github.com/GSA/code-gov-stats", + "https://github.com/GSA/cio-council", + "https://github.com/GSA/federal-privacy-council", + "https://github.com/GSA/devsecops-subaccount-admin", + "https://github.com/GSA/christopher", + "https://github.com/GSA/code-gov-stats-jupyter-notebook", + "https://github.com/GSA/code-gov-developer-docs", + "https://github.com/GSA/search-gov", + "https://github.com/GSA/dns", + "https://github.com/GSA/howto.gov-redir", + "https://github.com/GSA/code-gov-style", + "https://github.com/GSA/jquery-rails", + "https://github.com/GSA/code-gov-font", + "https://github.com/GSA/RPA-OSS", + "https://github.com/GSA/devsecops-ebs-backup", + "https://github.com/GSA/logger-codeigniter", + "https://github.com/GSA/datagov-deploy-dashboard", + "https://github.com/GSA/devsecops-iam-roles", + "https://github.com/GSA/tbm_ml_discovery", + "https://github.com/GSA/cooking-with-gas", + "https://github.com/GSA/steve", + "https://github.com/GSA/search-gov-agency-collaboration", + "https://github.com/GSA/centers-of-excellence", + "https://github.com/GSA/datagov-deploy-ckan-common", + "https://github.com/GSA/datagov-deploy-ckan-catalog", + "https://github.com/GSA/datagov-deploy-ckan-inventory", + "https://github.com/GSA/datagov-deploy-wordpress", + "https://github.com/GSA/datagov-deploy-crm", + "https://github.com/GSA/datagov-deploy-mysql", + "https://github.com/GSA/datagov-deploy-postgresql", + "https://github.com/GSA/datagov-deploy-redis", + "https://github.com/GSA/datagov-deploy-nginx", + "https://github.com/GSA/datagov-deploy-apache2", + "https://github.com/GSA/datagov-deploy-jetty", + "https://github.com/GSA/datagov-deploy-elasticsearch", + "https://github.com/GSA/datagov-deploy-solr", + "https://github.com/GSA/GSA-RPA-Standard", + "https://github.com/GSA/sf-lightning-components", + "https://github.com/GSA/data-strategy", + "https://github.com/GSA/coe-industry-day", + "https://github.com/GSA/grace-example", + "https://github.com/GSA/CF-Report-Server", + "https://github.com/GSA/app_identifier", + "https://github.com/GSA/sam-cfda-site", + "https://github.com/GSA/code-gov-data-quality-poc", + "https://github.com/GSA/ubuntu-common", + "https://github.com/GSA/cloud", + "https://github.com/GSA/code-clerk", + "https://github.com/GSA/service-tracking", + "https://github.com/GSA/cx.gsa.gov", + "https://github.com/GSA/PIC_dot_gov", + "https://github.com/GSA/FM-SIFT", + "https://github.com/GSA/pdi-etl", + "https://github.com/GSA/Reinvestigation", + "https://github.com/GSA/custom-content-type-manager", + "https://github.com/GSA/code-gov-validator", + "https://github.com/GSA/ASP-.NET-Core-Template", + "https://github.com/GSA/grace-rhel-ami", + "https://github.com/GSA/grace-ubuntu-ami", + "https://github.com/GSA/infrastructure-agent-ansible", + "https://github.com/GSA/FM-FMITwebdesign", + "https://github.com/GSA/FM-WebBill", + "https://github.com/GSA/FM-FedPay-Prototype", + "https://github.com/GSA/FM-CCS", + "https://github.com/GSA/sdg-data-usa", + "https://github.com/GSA/digitalgov-workflow", + "https://github.com/GSA/grace-tf-module-budget", + "https://github.com/GSA/grace-tf-module-member-account", + "https://github.com/GSA/code-gov-integrations", + "https://github.com/GSA/RPA-FASDelinquency", + "https://github.com/GSA/data-strategy-topic-modeling", + "https://github.com/GSA/data-strategy-classification", + "https://github.com/GSA/bigfix", + "https://github.com/GSA/inventory-app", + "https://github.com/GSA/publictrustpki-repository", + "https://github.com/GSA/srt-fbo-scraper", + "https://github.com/GSA/MD-GitHub-Admin", + "https://github.com/GSA/RPA-FASChargeback", + "https://github.com/GSA/BrianRPA", + "https://github.com/GSA/RPA-Sandbox", + "https://github.com/GSA/code-gov-front-end", + "https://github.com/GSA/ansible-elastalert", + "https://github.com/GSA/Tenant-Satisfaction-Survey", + "https://github.com/GSA/Python-Server-Instructions", + "https://github.com/GSA/FM-BillView", + "https://github.com/GSA/FM-NWTB", + "https://github.com/GSA/code-gov-site-map-generator", + "https://github.com/GSA/datagov-dedupe", + "https://github.com/GSA/code-gov-adapters", + "https://github.com/GSA/touchpoints", + "https://github.com/GSA/api-doco-with-uswds", + "https://github.com/GSA/code-gov-coding-languages", + "https://github.com/GSA/FM-Credit-and-Finance", + "https://github.com/GSA/os3_taxonomy_constructor", + "https://github.com/GSA/sdg-theme", + "https://github.com/GSA/FM-FMIT-Portal-MIGRATED", + "https://github.com/GSA/datagov-ckan-multi", + "https://github.com/GSA/cautious", + "https://github.com/GSA/FAS-Chargebacks-Data-Capture-Tool", + "https://github.com/GSA/FM-App-Status-API", + "https://github.com/GSA/contracting-hypotheses", + "https://github.com/GSA/code-gov-fscp-react-component", + "https://github.com/GSA/code-gov-about-page", + "https://github.com/GSA/json-schema-web-component", + "https://github.com/GSA/cf-cron-python", + "https://github.com/GSA/compliance-dashboard-web-component", + "https://github.com/GSA/json-schema-validator-web-component", + "https://github.com/GSA/code-gov-repos-parser", + "https://github.com/GSA/code-gov-converter", + "https://github.com/GSA/code-gov-harvester", + "https://github.com/GSA/jobkit", + "https://github.com/GSA/jck-healthy-strategies-ingest", + "https://github.com/GSA/grace-tftest", + "https://github.com/GSA/miniature-telegram", + "https://github.com/GSA/sam-prototypes", + "https://github.com/GSA/federal-apis", + "https://github.com/GSA/ansible-os-win-2016", + "https://github.com/GSA/qualtrics-to-mssql", + "https://github.com/GSA/us-data-federation-design", + "https://github.com/GSA/sdg-translations", + "https://github.com/GSA/sdg-indicators-archive", + "https://github.com/GSA/sdg-indicators", + "https://github.com/GSA/grace-circleci-builder", + "https://github.com/GSA/chef-cookbook-ruby-ng", + "https://github.com/GSA/grace-tenant-cleanup", + "https://github.com/GSA/code-reporting-tools", + "https://github.com/GSA/cloud-journey", + "https://github.com/GSA/Opportunities-api-docs", + "https://github.com/GSA/ODC-SPID", + "https://github.com/GSA/USSM", + "https://github.com/GSA/WDOL-SPLASH-PAGE", + "https://github.com/GSA/sam-styles", + "https://github.com/GSA/sam-design-system", + "https://github.com/GSA/FM-WebBill-SE", + "https://github.com/GSA/coe-discovery-bpa", + "https://github.com/GSA/grace-app", + "https://github.com/GSA/ansible-role-beats", + "https://github.com/GSA/MG_WB2", + "https://github.com/GSA/grace-citest", + "https://github.com/GSA/sf-field-history", + "https://github.com/GSA/wazuh-ansible", + "https://github.com/GSA/digitalgov-pra", + "https://github.com/GSA/Section508", + "https://github.com/GSA/sdg-translations-demo", + "https://github.com/GSA/geoip-auto-update", + "https://github.com/GSA/cookbook-elasticsearch", + "https://github.com/GSA/nodejs", + "https://github.com/GSA/ckanphpimport", + "https://github.com/GSA/ckanpyimport", + "https://github.com/GSA/wdol", + "https://github.com/GSA/srt-api", + "https://github.com/GSA/srt-ui", + "https://github.com/GSA/si-captcha-for-wordpress", + "https://github.com/GSA/datagov-deploy-python-app", + "https://github.com/GSA/dspg-summit-2018", + "https://github.com/GSA/grace-sqs-poc", + "https://github.com/GSA/travel-project-report", + "https://github.com/GSA/datagov-deploy-jumpbox", + "https://github.com/GSA/datagov-deploy-common", + "https://github.com/GSA/datagov-deploy-php", + "https://github.com/GSA/FM-RECON-NWTB-MIGRATED", + "https://github.com/GSA/datagov-deploy-ci", + "https://github.com/GSA/datagov-deploy-ckan", + "https://github.com/GSA/environment-followerphase-staging", + "https://github.com/GSA/environment-followerphase-production", + "https://github.com/GSA/challenges-and-prizes", + "https://github.com/GSA/dcoi", + "https://github.com/GSA/GEAR-Center-RFI-Responses", + "https://github.com/GSA/frpp-load", + "https://github.com/GSA/learning-data-science", + "https://github.com/GSA/sbchrist.github.io", + "https://github.com/GSA/MD-website-dym", + "https://github.com/GSA/grace-account-lockout", + "https://github.com/GSA/coe-hud-acquisitions", + "https://github.com/GSA/GSA-Acquisition-FAR", + "https://github.com/GSA/GSA-Acquisition-GSAM", + "https://github.com/GSA/coe-hud-acq-faas-erm-ide", + "https://github.com/GSA/coe-hud-acq-hudcentral", + "https://github.com/GSA/coe-hud-acq-agency-wide-cx", + "https://github.com/GSA/coe-hud-acq-ocdo", + "https://github.com/GSA/coe-hud-acq-data-visualization", + "https://github.com/GSA/coe-hud-acq-advanced-analytics", + "https://github.com/GSA/FM-Data-API-MIGRATED", + "https://github.com/GSA/FM-PMP-API-Client-MIGRATED", + "https://github.com/GSA/FM-FedPay-Archiver-MIGRATED", + "https://github.com/GSA/grace-style-guide", + "https://github.com/GSA/hackathon-acquisition-gateway", + "https://github.com/GSA/hackathon-frpp", + "https://github.com/GSA/hackathon-hrlinks", + "https://github.com/GSA/hackathon-gsait-service-desk", + "https://github.com/GSA/RPA-ULO", + "https://github.com/GSA/cio.gov-redo", + "https://github.com/GSA/Payroll-Reporting", + "https://github.com/GSA/Receiving-Reports-for-Recurring-Services---Phase-1", + "https://github.com/GSA/AP-Email-Notifications", + "https://github.com/GSA/INFORM-Pilot", + "https://github.com/GSA/machine-readable-TTS", + "https://github.com/GSA/resources.data.gov", + "https://github.com/GSA/coe-acquisitions", + "https://github.com/GSA/coe-opm-acquisitions", + "https://github.com/GSA/Credit_Card_Logging_Bot", + "https://github.com/GSA/GSA-RPA-Example-Bots-", + "https://github.com/GSA/grace-template", + "https://github.com/GSA/code-gov-github-metrics", + "https://github.com/GSA/coe-opm-mainframe-dr-plan", + "https://github.com/GSA/code-gov-repo-template", + "https://github.com/GSA/code-gov-open-source-toolkit", + "https://github.com/GSA/tbm-scan", + "https://github.com/GSA/srt-ml", + "https://github.com/GSA/FBO-SplashPage", + "https://github.com/GSA/Broadcast-Message", + "https://github.com/GSA/grace-securityhub", + "https://github.com/GSA/CoE-MPT-process", + "https://github.com/GSA/CoE-MPT-template", + "https://github.com/GSA/GSA-FAR-Test", + "https://github.com/GSA/FM-CIR-MIGRATED", + "https://github.com/GSA/grace-logging", + "https://github.com/GSA/tts-solutions-web-council", + "https://github.com/GSA/datagov-deploy-pycsw", + "https://github.com/GSA/GmailForwardingTool", + "https://github.com/GSA/css-logit-regression", + "https://github.com/GSA/cto-sandbox-tools", + "https://github.com/GSA/coe-cpsc-acquisitions", + "https://github.com/GSA/datagov-deploy-jenkins", + "https://github.com/GSA/usagov-50", + "https://github.com/GSA/the-foundation-project", + "https://github.com/GSA/TDE", + "https://github.com/GSA/sds-icons", + "https://github.com/GSA/FM-ARCS", + "https://github.com/GSA/grace-inventory", + "https://github.com/GSA/grace-cloudcustodian", + "https://github.com/GSA/CoE-MPT", + "https://github.com/GSA/coe-jaic-acquisitions", + "https://github.com/GSA/odp-gcp-project-setup", + "https://github.com/GSA/cio-gov-application-rationalization-playbook", + "https://github.com/GSA/odp-tf-google-appengine", + "https://github.com/GSA/cic", + "https://github.com/GSA/digitalgov-usability", + "https://github.com/GSA/odp-terraform-validator-example", + "https://github.com/GSA/tts-a11y-guild", + "https://github.com/GSA/sf-trigger-framework", + "https://github.com/GSA/MD-Automated-Text-Analysis", + "https://github.com/GSA/coe-opm-calculation-service", + "https://github.com/GSA/coe-opm-app-replacement", + "https://github.com/GSA/touchpoints-maintenance-page", + "https://github.com/GSA/sds-docs-content", + "https://github.com/GSA/fedramp-automation", + "https://github.com/GSA/site-scanning-documentation", + "https://github.com/GSA/sds-docs-site", + "https://github.com/GSA/odp-tf-aws-ref-arch-iam", + "https://github.com/GSA/odp-tf-aws-ref-arch-cloudwatch-monitoring", + "https://github.com/GSA/odp-tf-aws-ref-arch-config", + "https://github.com/GSA/grace-doc-gen", + "https://github.com/GSA/coe-opm-dbpa-data-store", + "https://github.com/GSA/grace-fcs-network", + "https://github.com/GSA/FM-RSNAP-MIGRATED", + "https://github.com/GSA/VRM-DONOTUSE", + "https://github.com/GSA/odp-code-repository-commit-rules", + "https://github.com/GSA/ci-phpunit-test", + "https://github.com/GSA/FM-GSA.FM.Utility.Core-MIGRATED", + "https://github.com/GSA/benchmarking-validation-reports", + "https://github.com/GSA/DBMW-Inventory-Repo", + "https://github.com/GSA/serverless-transit-network-orchestrator", + "https://github.com/GSA/webob", + "https://github.com/GSA/DBMW-Tower-Inventory", + "https://github.com/GSA/grace-log-parser", + "https://github.com/GSA/odp-tf-aws-ref-arch-guardduty", + "https://github.com/GSA/grace-alerting", + "https://github.com/GSA/grace-config", + "https://github.com/GSA/Digital-Innovation-Division", + "https://github.com/GSA/coe-gao-acquisitions", + "https://github.com/GSA/coe-dol-acquisitions", + "https://github.com/GSA/grace-config-differ", + "https://github.com/GSA/grace-iam", + "https://github.com/GSA/Challenge_gov", + "https://github.com/GSA/tgw-customer-template", + "https://github.com/GSA/datagov-compliance", + "https://github.com/GSA/cloudgov-demo-postgrest", + "https://github.com/GSA/search-gov-website", + "https://github.com/GSA/ERIS", + "https://github.com/GSA/CFO.gov", + "https://github.com/GSA/TestRepo", + "https://github.com/GSA/SRS", + "https://github.com/GSA/IMD", + "https://github.com/GSA/ckanext-collections", + "https://github.com/GSA/Lightweight-Trigger-Framework", + "https://github.com/GSA/sam-static-content", + "https://github.com/GSA/FM-financeweb-MIGRATED", + "https://github.com/GSA/usagov-lambda", + "https://github.com/GSA/Acquisition-Supplemental-Regulations", + "https://github.com/GSA/grace-paas-network", + "https://github.com/GSA/grace-paas-dns", + "https://github.com/GSA/NewPay", + "https://github.com/GSA/odp-testowner", + "https://github.com/GSA/catalog.data.gov", + "https://github.com/GSA/IMD-ePMR-Dashboard-Reporting-Sub-team", + "https://github.com/GSA/grace-paas-rds", + "https://github.com/GSA/coe-nichd-acquisitions", + "https://github.com/GSA/coe-fda-acquisitions", + "https://github.com/GSA/GEAR3", + "https://github.com/GSA/rocis-eda", + "https://github.com/GSA/sam-design-system-challenge", + "https://github.com/GSA/grace-rotate-accesskeys", + "https://github.com/GSA/odp-jenkins-jte", + "https://github.com/GSA/FRPP-ra-2020", + "https://github.com/GSA/CSS_2020_text_analysis", + "https://github.com/GSA/ai-experience-sharing-platform", + "https://github.com/GSA/ckanext-datagovcatalog", + "https://github.com/GSA/odp-ansible-cylance", + "https://github.com/GSA/grace-ansible-lambda", + "https://github.com/GSA/uswds-sf-lightning-community", + "https://github.com/GSA/PBS-USCourtsWeb", + "https://github.com/GSA/GSA-Acquisition-DFARS", + "https://github.com/GSA/cloud-service-broker", + "https://github.com/GSA/github-copy", + "https://github.com/GSA/datagov-tf-eks-helm", + "https://github.com/GSA/CorpIT-ScreeningTool", + "https://github.com/GSA/oscal-sap-to-word", + "https://github.com/GSA/oscal-sar-to-word", + "https://github.com/GSA/oscal-gen-tool", + "https://github.com/GSA/oscal-ssp-to-word", + "https://github.com/GSA/grace-ansible-template", + "https://github.com/GSA/datagov-deploy-fgdc2iso", + "https://github.com/GSA/ckanext-react_usmetadata", + "https://github.com/GSA/ansible-bigfix", + "https://github.com/GSA/FMIT-VCSS-APP", + "https://github.com/GSA/grace-paas-elb", + "https://github.com/GSA/HRM-Case-Management", + "https://github.com/GSA/PD-Library", + "https://github.com/GSA/cg-fork-test", + "https://github.com/GSA/grace-ansible-batch", + "https://github.com/GSA/Project-360-Executive-Business-Case", + "https://github.com/GSA/datagov-ssb", + "https://github.com/GSA/ckanext-dcat_usmetadata", + "https://github.com/GSA/ansible-bit9", + "https://github.com/GSA/ansible-cylance", + "https://github.com/GSA/ansible-nessus", + "https://github.com/GSA/ansible-fireeye", + "https://github.com/GSA/Controlled-Document-Tracker", + "https://github.com/GSA/odp-ansible-fireeye", + "https://github.com/GSA/cloudwatch-ansible-callback-plugin", + "https://github.com/GSA/hello-world", + "https://github.com/GSA/ansible-cloudwatch", + "https://github.com/GSA/ansible-snare", + "https://github.com/GSA/ansible-vrealize_orchestrator", + "https://github.com/GSA/ansible-firstboot", + "https://github.com/GSA/cdoc", + "https://github.com/GSA/ansible-solarwinds", + "https://github.com/GSA/fpc.gov", + "https://github.com/GSA/grace-secrets-sync-lambda", + "https://github.com/GSA/template-brokerpak", + "https://github.com/GSA/sectools-terraform-jenkins", + "https://github.com/GSA/sectools-ansible-jenkins", + "https://github.com/GSA/ansible-role-docker", + "https://github.com/GSA/odp-ansible-cis-docker", + "https://github.com/GSA/odp-image-build-example", + "https://github.com/GSA/ansible-forescout", + "https://github.com/GSA/grace-paas-backup", + "https://github.com/GSA/odp-eks-sample", + "https://github.com/GSA/odp-ansible-cis-eks-worker", + "https://github.com/GSA/GSA-DITA-OT-ToolKit-Developer", + "https://github.com/GSA/FM-PaymentSearch-MIGRATED", + "https://github.com/GSA/HRIT-LA-URS", + "https://github.com/GSA/fas-styles", + "https://github.com/GSA/ansible-os-win-2019", + "https://github.com/GSA/twitter", + "https://github.com/GSA/HRQSMO", + "https://github.com/GSA/ansible-endgame", + "https://github.com/GSA/grace-ecr", + "https://github.com/GSA/site-scanning-engine", + "https://github.com/GSA/acq-policy-analaysis", + "https://github.com/GSA/odp-sonatype-poc", + "https://github.com/GSA/grace-ansible-notifier", + "https://github.com/GSA/grace-decider", + "https://github.com/GSA/covid-screener-gsa.gov", + "https://github.com/GSA/ansible-rhel-domain", + "https://github.com/GSA/HRIT-LA-URS-3.1", + "https://github.com/GSA/HRIT-QMS-3.1", + "https://github.com/GSA/etc_environment", + "https://github.com/GSA/ficam-playbooks", + "https://github.com/GSA/ansible-os-amazon-linux2-eks", + "https://github.com/GSA/SF-reCAPTCHA-Enterprise", + "https://github.com/GSA/jenkins-shared-library-examples", + "https://github.com/GSA/ise-jenkins-shared-library", + "https://github.com/GSA/FM-FEDPAY-PORTAL-MIGRATED", + "https://github.com/GSA/ise-ansible-nessus-agent", + "https://github.com/GSA/max-gov", + "https://github.com/GSA/ise-hardened-docker-example", + "https://github.com/GSA/datagov-load-testing", + "https://github.com/GSA/CorpIT-CC_Migration_Sandbox", + "https://github.com/GSA/datagov-terraform-ecs-solr", + "https://github.com/GSA/ansible-os-ubuntu18", + "https://github.com/GSA/odp-ansible-common-utils", + "https://github.com/GSA/sectools-deploy-jenkins", + "https://github.com/GSA/geo-vm-inventory", + "https://github.com/GSA/terraform-kubernetes-aws-load-balancer-controller", + "https://github.com/GSA/git-quick-start", + "https://github.com/GSA/PerformanceGov", + "https://github.com/GSA/datagov-iam", + "https://github.com/GSA/odp-container-audit-log-best-practice", + "https://github.com/GSA/odp-aws-secretsmanager-poc", + "https://github.com/GSA/odp-ansible-endgame", + "https://github.com/GSA/dx-pgadmin", + "https://github.com/GSA/odp-cdk-example", + "https://github.com/GSA/searchgov_style", + "https://github.com/GSA/Trump-archives-performance-gov", + "https://github.com/GSA/odp-packer-ubuntu-eks", + "https://github.com/GSA/FM-FEDPAY-Test-Automation-GU", + "https://github.com/GSA/FM-UiPath-ActivityPack", + "https://github.com/GSA/odp-ansible-winlogbeat", + "https://github.com/GSA/site-scanning-query-builder", + "https://github.com/GSA/odp-ansible-windows2019", + "https://github.com/GSA/odp-tf-prisma-deps", + "https://github.com/GSA/ussm2.0", + "https://github.com/GSA/covid19-dashboard", + "https://github.com/GSA/csb-brokerpak-aws", + "https://github.com/GSA/datagov-datapusher", + "https://github.com/GSA/SaferFederalWorkforce.gov", + "https://github.com/GSA/cwa_ng", + "https://github.com/GSA/EDX", + "https://github.com/GSA/commit_hook", + "https://github.com/GSA/slack-norms", + "https://github.com/GSA/cloud-gov-manifests", + "https://github.com/GSA/fss19-cis-contract-service", + "https://github.com/GSA/datagov-logstack", + "https://github.com/GSA/odp-jenkins-hardening-pipeline", + "https://github.com/GSA/pyfpds", + "https://github.com/GSA/AI_Grand_Challenge_For_Resiliency", + "https://github.com/GSA/ai-experience-sharing-upptime", + "https://github.com/GSA/odp-techdoc", + "https://github.com/GSA/ag-api", + "https://github.com/GSA/Section508.gov", + "https://github.com/GSA/datagov-docker", + "https://github.com/GSA/odp-anchore-poc", + "https://github.com/GSA/spba-elastic", + "https://github.com/GSA/ansible-os-rhel8", + "https://github.com/GSA/ogp_platform_terraform", + "https://github.com/GSA/pr-test", + "https://github.com/GSA/odp-artifactory-proxy-poc", + "https://github.com/GSA/swagger-ui", + "https://github.com/GSA/icew-static-sandbox", + "https://github.com/GSA/icew-test", + "https://github.com/GSA/federal-website-index", + "https://github.com/GSA/ogp_plotly_terraform", + "https://github.com/GSA/GSA-Acquisition-DAFFARS", + "https://github.com/GSA/ogp_drupal_terraform", + "https://github.com/GSA/site-scanning", + "https://github.com/GSA/ogp_streamsets_terraform", + "https://github.com/GSA/odp-terraform-eks-bsp-sec", + "https://github.com/GSA/ansible-os-amazon-linux2", + "https://github.com/GSA/ngx-uswds", + "https://github.com/GSA/eoc", + "https://github.com/GSA/ogp_elasticsearch_terraform", + "https://github.com/GSA/pygments", + "https://github.com/GSA/ogp_drupal_db_terraform", + "https://github.com/GSA/itvmo", + "https://github.com/GSA/digital-scorecard", + "https://github.com/GSA/odp-tf-anchore-deps", + "https://github.com/GSA/odp-jenkins-anchore-scan-poc", + "https://github.com/GSA/gsaAdvantage-TestAutomation", + "https://github.com/GSA/usagov-benefits-eligibility-rules", + "https://github.com/GSA/odp-helm-chart-stackrox-sensor", + "https://github.com/GSA/CIS_OLD", + "https://github.com/GSA/ansible-role-tomcat", + "https://github.com/GSA/ngx-uswds-icons", + "https://github.com/GSA/SF-Katalon-VISION", + "https://github.com/GSA/idmanagement.gov", + "https://github.com/GSA/ECASDAS_BASE_CONFIG", + "https://github.com/GSA/ECASDAS_BASE_DRUPAL", + "https://github.com/GSA/ECASDAS_DRUPAL_APP1", + "https://github.com/GSA/ECASDAS_DRUPAL_APP2", + "https://github.com/GSA/ECASDAS_DRUPAL_APP3", + "https://github.com/GSA/odp-artifactory", + "https://github.com/GSA/digitalcorps.gsa.gov", + "https://github.com/GSA/aws-access-key-rotation-lambda", + "https://github.com/GSA/odp-artifactory-anchore", + "https://github.com/GSA/odp-jenkins-container-hardening-pipeline", + "https://github.com/GSA/PPMS-API", + "https://github.com/GSA/mule-easi-system-api", + "https://github.com/GSA/SF-Katalon-RSAP", + "https://github.com/GSA/openacr", + "https://github.com/GSA/cio-aia", + "https://github.com/GSA/G1ToG2Conversion", + "https://github.com/GSA/mule-r7migration-system-api", + "https://github.com/GSA/mule-r3demo-system-api", + "https://github.com/GSA/mule-epm-system-api", + "https://github.com/GSA/openacr-website", + "https://github.com/GSA/SF-Katalon-REDIFORCE", + "https://github.com/GSA/SF-Katalon-RSAP-GREX-Load-Test-Testing", + "https://github.com/GSA/SF-Katalon-CMLS-Sandbox_1INTp", + "https://github.com/GSA/cloud-identity-playbook", + "https://github.com/GSA/wg-web-modernization", + "https://github.com/GSA/oscal-poam-to-excel", + "https://github.com/GSA/devtraining-needit-quebec", + "https://github.com/GSA/GSA-FAI-D9", + "https://github.com/GSA/Testscanpoc-Sunny", + "https://github.com/GSA/ciss-iaas-baseline", + "https://github.com/GSA/AppRatDataDictionary", + "https://github.com/GSA/iaas-ingress-vpc", + "https://github.com/GSA/FM-FEDPAY-Test-Automation-Vendor", + "https://github.com/GSA/gsaEbuy-TestAutomation", + "https://github.com/GSA/iaas-transit-gateway", + "https://github.com/GSA/iaas-iam", + "https://github.com/GSA/mule-rediforce-api", + "https://github.com/GSA/odp-Jenkins-image-scan", + "https://github.com/GSA/ECASDAS_BASE_INFRA", + "https://github.com/GSA/grace-tfvars", + "https://github.com/GSA/ckanext-envvars", + "https://github.com/GSA/ciss-iaas-iam", + "https://github.com/GSA/g-iaas-dns", + "https://github.com/GSA/ciss-iaas-network", + "https://github.com/GSA/aws-terraform-executor", + "https://github.com/GSA/ciss-infra-tenant", + "https://github.com/GSA/tweetstream", + "https://github.com/GSA/iaas-networking", + "https://github.com/GSA/arp-cicd", + "https://github.com/GSA/federalist-uswds-jekyll", + "https://github.com/GSA/mule-r4-migration-system-api", + "https://github.com/GSA/ciss-utils", + "https://github.com/GSA/terraform-aws-alb", + "https://github.com/GSA/afp-progressive-web-app", + "https://github.com/GSA/SF-Katalon-CRM", + "https://github.com/GSA/frpp_d2d_auth", + "https://github.com/GSA/sf-lightning-roadmap", + "https://github.com/GSA/ciss-rotate-circleci-lambda", + "https://github.com/GSA/ciss-iaas-alerting", + "https://github.com/GSA/CISSPortal", + "https://github.com/GSA/ciss-iaas-bootstrap", + "https://github.com/GSA/snyktest", + "https://github.com/GSA/GSA-ECAS-GSAGOV", + "https://github.com/GSA/okta-sign-in-screens", + "https://github.com/GSA/datagov-website", + "https://github.com/GSA/dxcore-pricing-web", + "https://github.com/GSA/dxcore-pricing-calc", + "https://github.com/GSA/sam-maintenance", + "https://github.com/GSA/mule-oabill-system-api", + "https://github.com/GSA/techradar", + "https://github.com/GSA/sam-layouts", + "https://github.com/GSA/HRQMS6", + "https://github.com/GSA/public-benefits-studio", + "https://github.com/GSA/odp-ansible-bigfix", + "https://github.com/GSA/openacr-editor", + "https://github.com/GSA/cybersecurity-readiness-assessment-2021", + "https://github.com/GSA/SF-Katalon-AAAP", + "https://github.com/GSA/developer-handbook", + "https://github.com/GSA/acrIntegration-TestAutomation", + "https://github.com/GSA/cf-backup-manager", + "https://github.com/GSA/eBuy-TestAutomation", + "https://github.com/GSA/live-docs", + "https://github.com/GSA/technology-modernization-fund-v2", + "https://github.com/GSA/datagov-wp-migration", + "https://github.com/GSA/datagov-s3-migrate", + "https://github.com/GSA/InteragencyCollaboration", + "https://github.com/GSA/vcrpm-cli", + "https://github.com/GSA/vcrpm-server", + "https://github.com/GSA/mule-euas-system-api", + "https://github.com/GSA/SF-Katalon-PPRT", + "https://github.com/GSA/made-in-america-forms", + "https://github.com/GSA/GSA-Acquisition-AFARS", + "https://github.com/GSA/GSA-Acquisition-NMCARS", + "https://github.com/GSA/GSA-Acquisition-SOFARS", + "https://github.com/GSA/GSA-Acquisition-DARS", + "https://github.com/GSA/GSA-Acquisition-DLAD", + "https://github.com/GSA/ogp_osdbu", + "https://github.com/GSA/threat-analysis", + "https://github.com/GSA/thingie", + "https://github.com/GSA/odp-jenkins-nessus-scan-pipeline", + "https://github.com/GSA/MD-Website-Monitor", + "https://github.com/GSA/OneHR", + "https://github.com/GSA/made-in-america-django", + "https://github.com/GSA/epa-forms", + "https://github.com/GSA/made-in-america-samkeycheck", + "https://github.com/GSA/fcsm", + "https://github.com/GSA/MD-FPDS-Atom-Feeds", + "https://github.com/GSA/MD-Topics-Analyser", + "https://github.com/GSA/odp-ami-hardening-pipeline-lockdown", + "https://github.com/GSA/datagov-11ty", + "https://github.com/GSA/MD-fleet-asset-level-data-cleanup", + "https://github.com/GSA/VISION-CICD", + "https://github.com/GSA/odp-tf-stackrox-report", + "https://github.com/GSA/odp-tf-prisma", + "https://github.com/GSA/service-delivery", + "https://github.com/GSA/SF-Katalon-LOP-AAAP-BDD", + "https://github.com/GSA/PROJECT-CICD", + "https://github.com/GSA/search-services", + "https://github.com/GSA/odp-jenkins-stackrox-image-publishing-pipeline", + "https://github.com/GSA/odp-jenkins-stackrox-reporting-pipeline", + "https://github.com/GSA/GSA-Acquisition-VAAR", + "https://github.com/GSA/GSA-Acquisition-DIAR", + "https://github.com/GSA/elasticsearch-ruby", + "https://github.com/GSA/MA-per-diem-embedded-map", + "https://github.com/GSA/tts-brokerpak-clouddev", + "https://github.com/GSA/odp-aml2-os-hardening-role", + "https://github.com/GSA/odp-aml2-eks-worker-node-hardening-role", + "https://github.com/GSA/notifications-api", + "https://github.com/GSA/notifications-admin", + "https://github.com/GSA/odp-aml2-eks-ami-hardened-pipeline", + "https://github.com/GSA/GSA-Acquisition-AGAR", + "https://github.com/GSA/GSA-Acquisition-AIDAR", + "https://github.com/GSA/GSA-Acquisition-CAR", + "https://github.com/GSA/GSA-Acquisition-DEAR", + "https://github.com/GSA/GSA-Acquisition-DOLAR", + "https://github.com/GSA/GSA-Acquisition-DOSAR", + "https://github.com/GSA/GSA-Acquisition-DTAR", + "https://github.com/GSA/GSA-Acquisition-EDAR", + "https://github.com/GSA/GSA-Acquisition-EPAAR", + "https://github.com/GSA/GSA-Acquisition-FEHBAR", + "https://github.com/GSA/GSA-Acquisition-HHSAR", + "https://github.com/GSA/GSA-Acquisition-HSAR", + "https://github.com/GSA/GSA-Acquisition-HUDAR", + "https://github.com/GSA/GSA-Acquisition-JAR", + "https://github.com/GSA/GSA-Acquisition-NRCAR", + "https://github.com/GSA/GSA-Acquisition-TAR", + "https://github.com/GSA/GSA-Acquisition-IAAR", + "https://github.com/GSA/GSA-Acquisition-LIFAR", + "https://github.com/GSA/GSA-Acquisition-NFS", + "https://github.com/GSA/GSA-Acquisition-CASBAR", + "https://github.com/GSA/ckanext-saml2auth", + "https://github.com/GSA/gtm-test", + "https://github.com/GSA/gtm", + "https://github.com/GSA/aws-broker", + "https://github.com/GSA/cx-working-group", + "https://github.com/GSA/ProvenOptics", + "https://github.com/GSA/CSOD-EHRI", + "https://github.com/GSA/aws-trustedadvisor-reports", + "https://github.com/GSA/mas-prototype", + "https://github.com/GSA/icsp", + "https://github.com/GSA/assets.FCSM", + "https://github.com/GSA/made-in-america-iac", + "https://github.com/GSA/made-in-america-iac-modules", + "https://github.com/GSA/finearts-mockup", + "https://github.com/GSA/beta.performance.gov", + "https://github.com/GSA/mule-vision-system-api", + "https://github.com/GSA/CorpIT-ESB-Mirror", + "https://github.com/GSA/sd-prototyping-template", + "https://github.com/GSA/sd-11ty-cloud-prototype", + "https://github.com/GSA/US-performance-reporting", + "https://github.com/GSA/HRQMS-2.0", + "https://github.com/GSA/marketplace-fedramp-gov", + "https://github.com/GSA/GCPA-ide-prv-casesactapp-1", + "https://github.com/GSA/made-in-america-forms-service", + "https://github.com/GSA/made-in-america-forms-service-iac", + "https://github.com/GSA/made-in-america-forms-service-iac-modules", + "https://github.com/GSA/GCPA-h1p-oas-cdtapp-1", + "https://github.com/GSA/us-notify-compliance", + "https://github.com/GSA/cfo-redesign", + "https://github.com/GSA/HR-QMS-1.x-RefactoredNotifications", + "https://github.com/GSA/notifications-utils", + "https://github.com/GSA/hbdr2", + "https://github.com/GSA/notify-python-demo", + "https://github.com/GSA/HR-QMS-2.x", + "https://github.com/GSA/pulse-survey-analysis", + "https://github.com/GSA/assets_1.cfo", + "https://github.com/GSA/assets.CFO", + "https://github.com/GSA/pgov-docs", + "https://github.com/GSA/CloudFRPP", + "https://github.com/GSA/assets.cfo.gov", + "https://github.com/GSA/smart_pay_setup", + "https://github.com/GSA/PBS-USCourtsWeb-Workplace2030", + "https://github.com/GSA/ckanext-metrics_dashboard", + "https://github.com/GSA/made-in-america-forms-service-image", + "https://github.com/GSA/ttsnotify-brokerpak-sms", + "https://github.com/GSA/odp-ansible-elp", + "https://github.com/GSA/cpct-tool", + "https://github.com/GSA/futureofwork.gsa.gov", + "https://github.com/GSA/site-scanning-analysis", + "https://github.com/GSA/made-in-america-load-test", + "https://github.com/GSA/ART", + "https://github.com/GSA/889-tool", + "https://github.com/GSA/ODSHRDW", + "https://github.com/GSA/vote-gov-d10", + "https://github.com/GSA/889-vue", + "https://github.com/GSA/afp-pegasys-test", + "https://github.com/GSA/SF-Katalon-NCMT-Project", + "https://github.com/GSA/smartpay-website", + "https://github.com/GSA/edms-update-user-groups", + "https://github.com/GSA/HRIT-QMS-6.x", + "https://github.com/GSA/odp-sectools-stackrox-policies", + "https://github.com/GSA/odp-master", + "https://github.com/GSA/SF-Katalon-NCMT", + "https://github.com/GSA/ansible-os-ubuntu20", + "https://github.com/GSA/site-scanning-snapshots", + "https://github.com/GSA/wp2030-microsite", + "https://github.com/GSA/OneHRv2", + "https://github.com/GSA/FCcore", + "https://github.com/GSA/oes-msg-voting_description", + "https://github.com/GSA/2233-USWDS-Digital-Dashboard", + "https://github.com/GSA/2312-Occupancy-Patterns", + "https://github.com/GSA/made-in-america-static-assets", + "https://github.com/GSA/made-in-america-forms-tools", + "https://github.com/GSA/assets.cio.gov", + "https://github.com/GSA/workplace-microsite", + "https://github.com/GSA/uswds", + "https://github.com/GSA/rmarkdown-discussion", + "https://github.com/GSA/usnotify-ssb", + "https://github.com/GSA/smartpay-training", + "https://github.com/GSA/us-performance-reporting-archive", + "https://github.com/GSA/oesrrr", + "https://github.com/GSA/marketplace-fedramp-gov-data", + "https://github.com/GSA/odp-whispers-poc", + "https://github.com/GSA/datagov-harvester-test-cloudgov", + "https://github.com/GSA/datagov-harvester-test-aws", + "https://github.com/GSA/mdTranslator", + "https://github.com/GSA/odp-whispers-demo", + "https://github.com/GSA/odp-VulnerableWebApp", + "https://github.com/GSA/SmartPay-RFI", + "https://github.com/GSA/cg-cli-tools", + "https://github.com/GSA/fake-data", + "https://github.com/GSA/px-bears-drupal", + "https://github.com/GSA/datagov-harvesting-logic", + "https://github.com/GSA/Sustainable-IT-Procurement-Lexicon", + "https://github.com/GSA/msg_project_template", + "https://github.com/GSA/ansible-os-rhel7", + "https://github.com/GSA/CX-Jupyter-Notebooks", + "https://github.com/GSA/Strategic-Atlas", + "https://github.com/GSA/dms-ansible-inv", + "https://github.com/GSA/FASSRP-ContractsAPI", + "https://github.com/GSA/odp-jenkins-stackrox-policies-deployment-pipeline", + "https://github.com/GSA/robotex", + "https://github.com/GSA/deployer", + "https://github.com/GSA/EDX-test-website", + "https://github.com/GSA/search-gov-indexing", + "https://github.com/GSA/itcollect-data-capture-schemas", + "https://github.com/GSA/HISP-CX-Analysis", + "https://github.com/GSA/research-portal", + "https://github.com/GSA/ChallengeGov_FrontEnd", + "https://github.com/GSA/lighthouse-plugin-edx", + "https://github.com/GSA/FPKI_AR_Submissions", + "https://github.com/GSA/HRIT-QMS-ParTranRetry", + "https://github.com/GSA/EDX-github-action", + "https://github.com/GSA/rer-dms-ansible-inv", + "https://github.com/GSA/odp-ansible-elastic-agent", + "https://github.com/GSA/gtcop-wiki", + "https://github.com/GSA/FME", + "https://github.com/GSA/msg-tribal-acquisition", + "https://github.com/GSA/PerformanceGov-RFI", + "https://github.com/GSA/2332-MSG-USCIS-Votegov-Messages", + "https://github.com/GSA/Dynamo", + "https://github.com/GSA/FASSRP-SalesAPI", + "https://github.com/GSA/FASSRP-PaymentsAPI", + "https://github.com/GSA/SDM_Standards", + "https://github.com/GSA/SmartPay-RFQ", + "https://github.com/GSA/devtraining-needit-sandiego", + "https://github.com/GSA/devtraining-needit-sandiego-1", + "https://github.com/GSA/sdg-data-usa-staging", + "https://github.com/GSA/tutorial-test-repo", + "https://github.com/GSA/odp-k8s-elastic-agent", + "https://github.com/GSA/HISP-CX-Data", + "https://github.com/GSA/open-science-exploratory-workshop", + "https://github.com/GSA/MSG-2315-telework", + "https://github.com/GSA/EDX-chrome-extension", + "https://github.com/GSA/ECD-Ansible", + "https://github.com/GSA/GovCXAnalyzer", + "https://github.com/GSA/oescolorrrs", + "https://github.com/GSA/ux-team", + "https://github.com/GSA/ecd-analytics-session-manager", + "https://github.com/GSA/ansible-os-ubuntu22", + "https://github.com/GSA/VoC-Analysis", + "https://github.com/GSA/px-benefit-finder", + "https://github.com/GSA/oasis-plus", + "https://github.com/GSA/ACR-schema", + "https://github.com/GSA/datagov-harvester-airflow", + "https://github.com/GSA/adv-ebuy-eda-etl", + "https://github.com/GSA/StrategicAtlas", + "https://github.com/GSA/D2D-Kanban-Automation", + "https://github.com/GSA/afp-sandbox", + "https://github.com/GSA/EIS-data-analysis", + "https://github.com/GSA/GovCXAI4VoCLab", + "https://github.com/GSA/FEDSIM_Business_Intelligence_EOYDashboard", + "https://github.com/GSA/oasis-prototype", + "https://github.com/GSA/supplier-portal-rfi", + "https://github.com/GSA/2317-Federal-Coworking-Developmental-Phase-Evaluation", + "https://github.com/GSA/BOD_NCSCData", + "https://github.com/GSA/BOD_FPDSDataToDB", + "https://github.com/GSA/ckanext-googleanalytics", + "https://github.com/GSA/cmo-ad-hoc", + "https://github.com/GSA/cmo-team-ops", + "https://github.com/GSA/.allstar", + "https://github.com/GSA/CIC-Automation", + "https://github.com/GSA/DPA-Automation", + "https://github.com/GSA/TSCPortal-Automation", + "https://github.com/GSA/cmo-community-of-practice", + "https://github.com/GSA/ebuy_api", + "https://github.com/GSA/cmo-google-website", + "https://github.com/GSA/BOD_py_Emailer", + "https://github.com/GSA/ise-diagrams", + "https://github.com/GSA/ociso-site", + "https://github.com/GSA/ADV-Mail", + "https://github.com/GSA/ADV-eLibrary-DownloadContracts", + "https://github.com/GSA/ise-engagements", + "https://github.com/GSA/fedramp-oscal-earlyadopters", + "https://github.com/GSA/TestDemo", + "https://github.com/GSA/FASSRP-EmailerAPI", + "https://github.com/GSA/dev-docs", + "https://github.com/GSA/searchgov-tf", + "https://github.com/GSA/searchgov-ansible", + "https://github.com/GSA/ag-automation", + "https://github.com/GSA/datagov-harvest-transformer", + "https://github.com/GSA/14110s101h", + "https://github.com/GSA/afp-docker-setup", + "https://github.com/GSA/tsc-clamav", + "https://github.com/GSA/srt-user-management", + "https://github.com/GSA/OSCAL", + "https://github.com/GSA/DigitalCXAnalyzer", + "https://github.com/GSA/ansible-os-rhel9", + "https://github.com/GSA/GSA_BIA_PDFOCR", + "https://github.com/GSA/BABS-SQL", + "https://github.com/GSA/datagov-harvest-orchestrator", + "https://github.com/GSA/datagov-harvest-ui", + "https://github.com/GSA/The-AI-Community-of-Practice", + "https://github.com/GSA/us-tech-policy", + "https://github.com/GSA/openacr-editor-stage", + "https://github.com/GSA/KaiPersonal", + "https://github.com/GSA/Flask_harvest_app", + "https://github.com/GSA/afp-catalog-public-svc", + "https://github.com/GSA/ART-API", + "https://github.com/GSA/identity-oscal", + "https://github.com/GSA/odp-ansible-bit9", + "https://github.com/GSA/gsa-displacy-demo", + "https://github.com/GSA/Staffing", + "https://github.com/GSA/ise-arch-review", + "https://github.com/GSA/ansible-os-amazon-linux-2023", + "https://github.com/GSA/multi-tenant-emr-uat-test", + "https://github.com/GSA/searchgov-k8s", + "https://github.com/GSA/odp-prod-ecr", + "https://github.com/GSA/odp-wiki", + "https://github.com/GSA/rmReportTool", + "https://github.com/GSA/searchgov-spider", + "https://github.com/GSA/APG-Pilot-AI-Editor", + "https://github.com/GSA/eOfferMVN-Dependencies", + "https://github.com/GSA/automate.fedramp.gov", + "https://github.com/GSA/gsa-auth-web", + "https://github.com/GSA/uswds-hugo", + "https://github.com/GSA/MSG-2431-Creating-Effective-Messaging", + "https://github.com/GSA/MSG-2411-Core-Days", + "https://github.com/GSA/beta-gsa", + "https://github.com/GSA/gearTestingFramework", + "https://github.com/GSA/MSG-2414-SmallBusinessForecasting", + "https://github.com/GSA/MSG-2415-RetirementForecasting", + "https://github.com/GSA/code-reporting-poc", + "https://github.com/GSA/fedramp-ai", + "https://github.com/18F/api.data.gov", + "https://github.com/18F/omniauth-myusa", + "https://github.com/18F/PriceHistoryAPI", + "https://github.com/18F/MorrisDataDecorator", + "https://github.com/18F/fbopen", + "https://github.com/18F/fbopen-widget", + "https://github.com/18F/xavier", + "https://github.com/18F/PriceHistoryGUI", + "https://github.com/18F/PriceHistoryAuth", + "https://github.com/18F/MicroP3ApiUser", + "https://github.com/18F/pif-interest", + "https://github.com/18F/API-Usability-Testing", + "https://github.com/18F/pif-app", + "https://github.com/18F/ifgovthenthat", + "https://github.com/18F/18f.gsa.gov", + "https://github.com/18F/18f.github.io", + "https://github.com/18F/brutus", + "https://github.com/18F/Mario", + "https://github.com/18F/afsmallbiz", + "https://github.com/18F/API-All-the-X", + 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"https://github.com/presidential-innovation-fellows/midaas-api", + "https://github.com/presidential-innovation-fellows/ceic-partnering", + "https://github.com/presidential-innovation-fellows/static-gen", + "https://github.com/presidential-innovation-fellows/discourse", + "https://github.com/presidential-innovation-fellows/label-explorer", + "https://github.com/presidential-innovation-fellows/dolores-landingham-bot", + "https://github.com/presidential-innovation-fellows/apps-gov-v2", + "https://github.com/presidential-innovation-fellows/slack-fetch-bot", + "https://github.com/presidential-innovation-fellows/dap-guide", + "https://github.com/presidential-innovation-fellows/hack-the-paygap", + "https://github.com/presidential-innovation-fellows/epa-opp-explorer", + "https://github.com/presidential-innovation-fellows/node-fdsh-client", + "https://github.com/presidential-innovation-fellows/node-fdsh-client-lambda", + "https://github.com/presidential-innovation-fellows/benefits-integration-poc", + "https://github.com/presidential-innovation-fellows/angrytock", + "https://github.com/presidential-innovation-fellows/week-of-making", + "https://github.com/presidential-innovation-fellows/consolidated-citizen-services", + "https://github.com/presidential-innovation-fellows/clinical-trials-search", + "https://github.com/presidential-innovation-fellows/top_v2", + "https://github.com/presidential-innovation-fellows/worker-dol-gov", + "https://github.com/presidential-innovation-fellows/school-meals", + "https://github.com/presidential-innovation-fellows/dns", + "https://github.com/presidential-innovation-fellows/code-gov-web", + "https://github.com/presidential-innovation-fellows/code-gov-tools", + "https://github.com/presidential-innovation-fellows/code-gov-policy", + "https://github.com/presidential-innovation-fellows/foster-youth-experience", + "https://github.com/presidential-innovation-fellows/newopportunity", + "https://github.com/presidential-innovation-fellows/opportunity-pm", + "https://github.com/presidential-innovation-fellows/fyem-jekyll", + "https://github.com/presidential-innovation-fellows/child-welfare-product-hub", + "https://github.com/presidential-innovation-fellows/code-gov-api", + "https://github.com/presidential-innovation-fellows/software-inventory-schema-tools", + "https://github.com/presidential-innovation-fellows/heroku-buildpack-apt", + "https://github.com/GSA/mobile-fu", + "https://github.com/GSA/rails-google-visualization-plugin", + "https://github.com/GSA/apache-log-parser", + "https://github.com/GSA/active_scaffold", + "https://github.com/GSA/fckeditor", + "https://github.com/GSA/aws-s3", + "https://github.com/GSA/capistrano", + "https://github.com/GSA/sunspot", + "https://github.com/GSA/resque-priority", + "https://github.com/GSA/open311-simple-crm", + "https://github.com/GSA/datafiles-wordpress-plugin", + "https://github.com/GSA/federal-open-source-repos-php", + "https://github.com/GSA/federal-open-source-repos", + "https://github.com/GSA/federal-open-source-repos-ruby", + "https://github.com/GSA/gogogon", + "https://github.com/GSA/ckanext-geodatagov", + "https://github.com/GSA/digital-strategy", + "https://github.com/GSA/digital-strategy-report-generator", + "https://github.com/GSA/ruby-cloudfiles", + "https://github.com/GSA/us-digital-registry", + "https://github.com/GSA/digital-strategy-drupal-module", + "https://github.com/GSA/oauth2-provider", + "https://github.com/GSA/Open311-Forms-Engine", + "https://github.com/GSA/uReport", + "https://github.com/GSA/open311-proxy", + "https://github.com/GSA/mygov-mobile-first-foundation", + "https://github.com/GSA/slash-developer-pages", + "https://github.com/GSA/pdf-filler", + "https://github.com/GSA/epa_uv_index", + "https://github.com/GSA/apidocs", + "https://github.com/GSA/omniauth-mygov", + "https://github.com/GSA/mygov-bar", + "https://github.com/GSA/mygov-discovery", + "https://github.com/GSA/mygov-forms", + "https://github.com/GSA/db-to-api", + "https://github.com/GSA/DataBeam", + "https://github.com/GSA/benefits-mockup", + "https://github.com/GSA/recalls_api", + "https://github.com/GSA/jobs_api", + "https://github.com/GSA/mygov-feedback-reporting", + "https://github.com/GSA/mygov-account", + "https://github.com/GSA/us_states", + "https://github.com/GSA/labs-html", + "https://github.com/GSA/mygov-account-php-sdk", + "https://github.com/GSA/usa-faqs", + "https://github.com/GSA/idm", + "https://github.com/GSA/unclaimed_money", + "https://github.com/GSA/omniauth-openid", + "https://github.com/GSA/GSA-APIs", + "https://github.com/GSA/usfedgov_google_analytics", + "https://github.com/GSA/alpha-data-dot-gov", + "https://github.com/GSA/ckanext-saml2", + "https://github.com/GSA/data.gov", + "https://github.com/GSA/rack-openid", + "https://github.com/GSA/SMR-site-embed", + "https://github.com/GSA/Mobile-Code-Catalog", + "https://github.com/GSA/Mobile-Web-Manual-Testing-Script", + "https://github.com/GSA/myusa-account-demo", + "https://github.com/GSA/federal-apps-gallery-widgets", + "https://github.com/GSA/USMetadata", + "https://github.com/GSA/mygov-admin-tasks", + "https://github.com/GSA/myusa-tasks", + "https://github.com/GSA/Crowdsource-Testing-USDA_FSIS", + "https://github.com/GSA/hyabusa", + "https://github.com/GSA/modus-operandi", + "https://github.com/GSA/just_inform", + "https://github.com/GSA/just_inform_web", + "https://github.com/GSA/.Gov-Content-as-an-API", + "https://github.com/GSA/ckanext-datajson", + "https://github.com/GSA/embedding-data-catalogs", + "https://github.com/GSA/enterprise-data-inventory", + "https://github.com/GSA/capistrano-resque", + "https://github.com/GSA/Crowdsource-Testing-CIO.gov", + "https://github.com/GSA/oauthd", + "https://github.com/GSA/gman", + "https://github.com/GSA/helio", + "https://github.com/GSA/govt-urls", + "https://github.com/GSA/logo", + "https://github.com/GSA/datagov-design", + "https://github.com/GSA/twitter-widgets-gallery", + "https://github.com/GSA/Template-Microsite", + "https://github.com/GSA/Open-Data-Collaboration-Sandbox", + "https://github.com/GSA/Very-Simple-API", + "https://github.com/GSA/Developer-Feedback-for-Government-APIs", + "https://github.com/GSA/search.digitalgov.gov", + "https://github.com/GSA/API-Resources", + "https://github.com/GSA/ckan-php-client", + "https://github.com/GSA/ckan-php-manager", + "https://github.com/GSA/wp-open311", + "https://github.com/GSA/data_gov_json_validator", + "https://github.com/GSA/open-data-program-template", + "https://github.com/GSA/pod-schema-variants", + "https://github.com/GSA/PricesPaidAPI", + "https://github.com/GSA/LAMP-CentOS-with-Vagrant", + "https://github.com/GSA/ckan", + "https://github.com/GSA/ckanext-harvest", + "https://github.com/GSA/ckanext-spatial", + "https://github.com/GSA/sam_api", + "https://github.com/GSA/datagov-deploy", + "https://github.com/GSA/idp", + "https://github.com/GSA/arcgis-map", + "https://github.com/GSA/custom-contact-forms", + "https://github.com/GSA/custom-post-view-generator", + "https://github.com/GSA/datagov-custom", + "https://github.com/GSA/metric-count", + "https://github.com/GSA/restrict-categories", + "https://github.com/GSA/saml-20-single-sign-on", + "https://github.com/GSA/sticky-posts-in-category", + "https://github.com/GSA/suggested-datasets", + "https://github.com/GSA/twitter-posts-to-blog", + "https://github.com/GSA/twitter-widget-pro", + "https://github.com/GSA/usa-search", + "https://github.com/GSA/wordpress-seo", + "https://github.com/GSA/Open-And-Structured-Content-Models", + "https://github.com/GSA/Crowdsource-Testing-DFAS.mil", + "https://github.com/GSA/ckanext-qa", + "https://github.com/GSA/FedCMS-Slider", + "https://github.com/GSA/ckanext-archiver", + "https://github.com/GSA/Crowdsource-Testing-HHS-ACF.gov", + "https://github.com/GSA/open.gsa.gov", + "https://github.com/GSA/instant-comment-validation", + "https://github.com/GSA/asis", + "https://github.com/GSA/simple-tooltips", + "https://github.com/GSA/ckanext-googleanalyticsbasic", + "https://github.com/GSA/wp-external-links", + "https://github.com/GSA/Crowdsource-Testing-NOAA-CrowdMag", + "https://github.com/GSA/Crowdsource-Testing-ABMC.gov", + "https://github.com/GSA/IAE-Architecture", + "https://github.com/GSA/auctions_api", + "https://github.com/GSA/OWSLib", + "https://github.com/GSA/datagov-presentations", + "https://github.com/GSA/testsite922", + "https://github.com/GSA/Crowdsource-Testing-HHS-MAIN", + "https://github.com/GSA/ckanext-report", + "https://github.com/GSA/data.gov-styleguide", + "https://github.com/GSA/developers", + "https://github.com/GSA/data", + "https://github.com/GSA/data.json-template", + "https://github.com/GSA/sites-digitalgov-search", + "https://github.com/GSA/Very-Simple-API-2", + "https://github.com/GSA/sitelink_generator", + "https://github.com/GSA/openIAE", + "https://github.com/GSA/punchcard", + "https://github.com/GSA/Crowdsource-Testing-NOAA-CrowdMag--iOS", + "https://github.com/GSA/Crowdsource-Testing-Central-Artifact-Repository", + "https://github.com/GSA/cfpb.github.io", + "https://github.com/GSA/social-media-registry-api", + "https://github.com/GSA/api", + "https://github.com/GSA/labs", + "https://github.com/GSA/fssi-file-processor", + "https://github.com/GSA/https", + "https://github.com/GSA/Crowdsource-Testing-NIH-HCI-1-2015", + "https://github.com/GSA/data-json", + "https://github.com/GSA/eMuseum-API", + "https://github.com/GSA/seo", + "https://github.com/GSA/participation-playbook", + "https://github.com/GSA/Holiday-Utility", + "https://github.com/GSA/Membership-Utility", + "https://github.com/GSA/open311-github", + "https://github.com/GSA/Crowdsource-Testing-Connect.gov_3-2015", + "https://github.com/GSA/USA.gov-API-Integration", + "https://github.com/GSA/GitHub-Administration", + "https://github.com/GSA/i14y", + "https://github.com/GSA/agile_accelerator_admin_guide", + "https://github.com/GSA/wp-rss-multi-importer", + "https://github.com/GSA/structured_content_wordpress", + "https://github.com/GSA/GSA-Digital-Innovation", + "https://github.com/GSA/GSA-team-5", + "https://github.com/GSA/Hackathon-Team-10", + "https://github.com/GSA/gsa-digitial-innovation-hackathon", + "https://github.com/GSA/gsa-hackathon-t4", + "https://github.com/GSA/opensource-framework", + "https://github.com/GSA/ckanext-datagovtheme", + "https://github.com/GSA/custom-permalinks", + "https://github.com/GSA/slate", + "https://github.com/GSA/FederalHierarchy-Crosswalk", + "https://github.com/GSA/github-federal-stats", + "https://github.com/GSA/tsd-agile-cm-manifesto", + "https://github.com/GSA/vocab.data.gov", + "https://github.com/GSA/ckanext-extlink", + "https://github.com/GSA/Salesforce-Communities-Login", + "https://github.com/GSA/scopeid-script", + "https://github.com/GSA/tsd-agile-sdlc", + "https://github.com/GSA/wp-digitalgov-i14y-indexer", + "https://github.com/GSA/fssi-file-processor-gui", + "https://github.com/GSA/Crowdsource-Testing-SBA.gov_7-2015", + "https://github.com/GSA/activerecord-validate_unique_child_attribute", + "https://github.com/GSA/font-awesome-grunticon-rails", + "https://github.com/GSA/tsd-ga-framework", + "https://github.com/GSA/Crowdsource-Testing-Federal-Crowdsourcing-and-Citizen-Science-Toolkit_8-2015", + "https://github.com/GSA/wp-sitemap-page", + "https://github.com/GSA/Crowdsource-Testing-TSA.GOV_9-2015", + "https://github.com/GSA/catalog-deploy", + "https://github.com/GSA/catalog-app", + "https://github.com/GSA/pycsw", + "https://github.com/GSA/DataCenterMashup", + "https://github.com/GSA/gsa-hackathon-2015", + "https://github.com/GSA/GSA-2015-Fall", + "https://github.com/GSA/GSA-Fall-Hackathon-GHG", + "https://github.com/GSA/gsa-hackathon", + "https://github.com/GSA/CGI", + "https://github.com/GSA/general-hackathon-administration", + "https://github.com/GSA/Ventera-GSAHackathon", + "https://github.com/GSA/trip", + "https://github.com/GSA/data-center-tool", + "https://github.com/GSA/Crowdsource-Testing-FTC-IdentityTheft.gov_11-2015", + "https://github.com/GSA/ficam-arch", + "https://github.com/GSA/pysaml2", + "https://github.com/GSA/PyZ3950", + "https://github.com/GSA/q-and-a", + "https://github.com/GSA/wp-no-taxonomy-base", + "https://github.com/GSA/cg-manifests", + "https://github.com/GSA/gsa-doc-digital-signature", + "https://github.com/GSA/cg-pipelines", + "https://github.com/GSA/datagovATO", + "https://github.com/GSA/open.gsa.gov.github.io", + "https://github.com/GSA/ficam-guides", + "https://github.com/GSA/fpki-guides", + "https://github.com/GSA/piv-guides", + "https://github.com/GSA/datagov-cf-cron", + "https://github.com/GSA/datagov-bosh", + "https://github.com/GSA/logsearch-boshrelease", + "https://github.com/GSA/Crowdsource-Testing-USCIS.gov_2_2016", + "https://github.com/GSA/oauth2_proxy", + "https://github.com/GSA/cg-deploy-concourse", + "https://github.com/GSA/GSADigitalService", + "https://github.com/GSA/FederalProjectSchema", + "https://github.com/GSA/IASHub", + "https://github.com/GSA/sf-sandbox-post-copy", + "https://github.com/GSA/CAP-Documentation", + "https://github.com/GSA/iae-uikit-php", + "https://github.com/GSA/jkan", + "https://github.com/GSA/community-catalog", + "https://github.com/GSA/catalog-solr", + "https://github.com/GSA/catalog-fgdc2iso", + "https://github.com/GSA/catalog-db", + "https://github.com/GSA/catalog-scheduler", + "https://github.com/GSA/inventory-solr", + "https://github.com/GSA/catalog-pycsw", + "https://github.com/GSA/catalog-nginx", + "https://github.com/GSA/NAP-Stat", + "https://github.com/GSA/bwp-external-links", + "https://github.com/GSA/pbs-sensor", + "https://github.com/GSA/jekyll-centos-deploy", + "https://github.com/GSA/us-data-federation", + "https://github.com/GSA/governmentwide-classifications", + "https://github.com/GSA/cto-website", + "https://github.com/GSA/formk8s", + "https://github.com/GSA/angular-toasty", + "https://github.com/GSA/sdg-indicators", + "https://github.com/GSA/api-documentation-template-old", + "https://github.com/GSA/ficam-federation", + "https://github.com/GSA/ficam-management", + "https://github.com/GSA/datapusher", + "https://github.com/GSA/it-accessibility-playbook", + "https://github.com/GSA/openstack-ansible-security", + "https://github.com/GSA/sam-web-design-standards", + "https://github.com/GSA/compliance-docs", + "https://github.com/GSA/open-gsa-redesign", + "https://github.com/GSA/datagov-wp-boilerplate", + "https://github.com/GSA/ficam-access", + "https://github.com/GSA/ckanext-s3filestore", + "https://github.com/GSA/ficam-identity", + "https://github.com/GSA/lynis", + "https://github.com/GSA/fail2ban", + "https://github.com/GSA/Crowdsource-Testing-DHS.gov_9_2016", + "https://github.com/GSA/opengovplan", + "https://github.com/GSA/ckanext-ga-report", + "https://github.com/GSA/GSAOpenSourcePolicy", + "https://github.com/GSA/ckanext-fulltext", + "https://github.com/GSA/watchdog-test", + "https://github.com/GSA/sentry", + "https://github.com/GSA/ckanext-cesiumpreview", + "https://github.com/GSA/codeinventory-metadata-generator", + "https://github.com/GSA/codeinventory", + "https://github.com/GSA/FEDSIM_root", + "https://github.com/GSA/ec2-broker", + "https://github.com/GSA/elastalert", + "https://github.com/GSA/prototype-city-pairs-api", + "https://github.com/GSA/SF-Event-Monitoring-Log-Retrieval", + "https://github.com/GSA/codeinventory-github", + "https://github.com/GSA/sf-ProjectDashboard", + "https://github.com/GSA/api-standards", + "https://github.com/GSA/sdg-nrp-scripts", + "https://github.com/GSA/ansible-role-repo-webtatic", + "https://github.com/GSA/api-documentation-template", + "https://github.com/GSA/prototype-city-pairs-api-documentation", + "https://github.com/GSA/fedramp", + "https://github.com/GSA/ansible-tomcat", + "https://github.com/GSA/icpa_user_training" + + ], + "HHS" : [ + "https://github.com/DSACMS/automated-codejson-generator", + "https://github.com/CMSgov/beneficiary-fhir-data", + "https://github.com/DSACMS/cms-gource", + "https://github.com/DSACMS/cms-open-source-policy", + "https://github.com/DSACMS/codejson-generator", + "https://github.com/DSACMS/codejson-generator", + "https://github.com/DSACMS/codejson-generator", + "https://github.com/DSACMS/codejson-index-generator", + "https://github.com/DSACMS/decks", + "https://github.com/DSACMS/dedupliFHIR", + "https://github.com/DSACMS/dsacms.github.io", + "https://github.com/DSACMS/form-demo", + "https://github.com/DSACMS/gource-log", + "https://github.com/DSACMS/gov-codejson", + "https://github.com/DSACMS/income-reporting-playbook", + "https://github.com/DSACMS/index-generator-website", + "https://github.com/DSACMS/metrics", + "https://github.com/DSACMS/metrics-dash-backend-tools", + "https://github.com/DSACMS/open", + "https://github.com/DSACMS/opportunities", + "https://github.com/DSACMS/ospo-guide", + "https://github.com/DSACMS/ospo-guide", + "https://github.com/DSACMS/oss-community-runbook", + "https://github.com/DSACMS/repo-scaffolder", + "https://github.com/DSACMS/repodive-tools", + "https://github.com/DSACMS/repolinter-actions", + "https://github.com/DSACMS/repolinter-test-1", + "https://github.com/DSACMS/reverse-scorecard-generation", + "https://github.com/DSACMS/share-it-act-lp", + "https://github.com/DSACMS/mural-ollama" + ] +} \ No newline at end of file From e585896ced4bc28e905e5c7769ff4eccf90ed3b5 Mon Sep 17 00:00:00 2001 From: Isaac Milarsky Date: Wed, 4 Jun 2025 12:05:31 -0500 Subject: [PATCH 03/14] alter parsing to parse by url rather than by org Signed-off-by: Isaac Milarsky --- scripts/pull-public-assets.py | 27 ++++++++++++++++++++++----- 1 file changed, 22 insertions(+), 5 deletions(-) diff --git a/scripts/pull-public-assets.py b/scripts/pull-public-assets.py index ce51013f..c640d613 100644 --- a/scripts/pull-public-assets.py +++ b/scripts/pull-public-assets.py @@ -9,7 +9,7 @@ def main(): - with open('codegov.json','r') as file: + with open('repo-manifest.json','r') as file: codegovDict = json.load(file) github_key = os.getenv("GITHUB_TOKEN") @@ -36,10 +36,27 @@ def main(): except FileExistsError: print(f"File already exists: {agency_subdir}") - orgs = codegovDict[agency]["orgs"] - for org in orgs: - org = org.strip() - indexGen.process_organization(org,add_to_index=True,codeJSONPath=agency_subdir) + #orgs = codegovDict[agency]["orgs"] + #for org in orgs: + # org = org.strip() + # indexGen.process_organization(org,add_to_index=True,codeJSONPath=agency_subdir) + + try: + for id,repo in enumerate(codegovDict[agency],1): + print(f"\nChecking {repo} [{id}/{len(codegovDict[agency])}]") + + repoPath = os.path.join(agency_subdir, (repo + '.json')) + repo_obj = indexGen.github.get_repo(repo.split("github.com/")[1]) + code_json = indexGen.save_code_json(repo_obj) + + if code_json: + print(f"✅ Found code.json in {repo}") + indexGen.update_index(indexGen.index,code_json,repo_obj.organization, repo_obj.name) + else: + print(f"❌ No code.json found in {repo}") + except Exception as e: + print(e) + indexGen.save_index(os.path.join(AGENCY_CODEJSON_DIR, agency + "_index.json")) print(f"\nIndexing complete. Results saved to {AGENCY_CODEJSON_DIR}") From e03cc73eeed9765255152c5d91b2dc4cf6896e17 Mon Sep 17 00:00:00 2001 From: Isaac Milarsky Date: Wed, 4 Jun 2025 15:18:55 -0500 Subject: [PATCH 04/14] update to handle 404 Signed-off-by: Isaac Milarsky --- agency-indexes/GSA_index.json | 50700 +--------------- agency-indexes/HHS/code-gov.json | 59 - agency-indexes/HHS/gov-codejson.json | 4 +- .../HHS/outbound-tools-survey-2.json | 62 - agency-indexes/HHS/un-sdg-form.json | 62 - agency-indexes/HHS_index.json | 924 +- scripts/pull-public-assets.py | 13 +- 7 files changed, 15 insertions(+), 51809 deletions(-) delete mode 100644 agency-indexes/HHS/code-gov.json delete mode 100644 agency-indexes/HHS/outbound-tools-survey-2.json delete mode 100644 agency-indexes/HHS/un-sdg-form.json diff --git a/agency-indexes/GSA_index.json b/agency-indexes/GSA_index.json index 2f924199..0915afc4 100644 --- a/agency-indexes/GSA_index.json +++ b/agency-indexes/GSA_index.json @@ -4,50703 +4,5 @@ "measurementType": { "method": "projects" }, - "releases": [ - { - "organization": "GSA", - "name": "open-gsa-redesign", - "agency": "GSA", - "measurementType": { - "method": "modules" - }, - "version": "2.0.0", - "releases": [ - { - "name": "mobile-fu", - "description": "Automatically detect mobile requests from mobile devices in your Rails application.", - "permissions": { - "licenses": [ - { - "URL": "http://choosealicense.com/licenses/mit/", - "name": "mit" - } - ], - "usageType": "openSource" - }, - "tags": [ - "GSA" - ], - "repositoryURL": "https://github.com/GSA/mobile-fu", - "homepageURL": "http://www.intridea.com/2008/7/21/mobilize-your-rails-application-with-mobile-fu", - "contact": { - "email": "gsa-github.support@gsa.gov" - }, - "languages": [ - "Ruby" - ], - "laborHours": 0, - "vcs": "git", - "organization": "GSA" - }, - { - "name": "rails-google-visualization-plugin", - "description": "A rails plugin that provides simple block helpers to introduce google visualizations (gap minder)", - "permissions": { - "licenses": [ - 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"repositoryURL": "https://github.com/DSACMS/ospo-guide", - "vcs": "git", - "laborHours": 2992, - "platforms": [ - "web" - ], - "categories": [ - "knowledge-management", - "document-management" - ], - "softwareType": "standalone/web", - "languages": [ - "Markdown" - ], - "maintenance": "internal", - "date": { - "created": "2024-04-03T20:47:21Z", - "lastModified": "2025-02-11T17:21:41Z", - "metaDataLastUpdated": "2025-02-11T17:22:34.291Z" - }, - "tags": [ - "OSPO", - "guide", - "documentation" - ], - "contact": { - "email": "opensource@cms.hhs.gov", - "name": "CMS Open Source Team" - }, - "localisation": false, - "repositoryType": "standards", - "userInput": false, - "fismaLevel": "Low", - "group": "CMS/OA/DSAC", - "subsetInHealthcare": [ - "Operational" - ], - "userType": [ - "Government" - ], - "repositoryHost": "github.com/DSACMS", - "maturityModelTier": 2 -} \ No newline at end of file diff --git a/agency-indexes/HHS/gov-codejson.json b/agency-indexes/HHS/gov-codejson.json index 21efed99..54fbaea3 100644 --- a/agency-indexes/HHS/gov-codejson.json +++ b/agency-indexes/HHS/gov-codejson.json @@ -1,7 +1,7 @@ { "name": "gov-codejson", - "description": "CMS code.json: An agency-wide metadata standard for software projects", - "longDescription": "This repository contains documentation on CMS code.json, a metadata standard used to collect information on the agency's software projects in compliance with M-16-21 and the SHARE IT Act.", + "description": "code.json: An agency-wide metadata standard for software projects", + "longDescription": "This repository contains documentation on code.json, a metadata standard used to collect information on the agency's software projects in compliance with M-16-21 and the SHARE IT Act.", "status": "Production", "permissions": { "license": [ diff --git a/agency-indexes/HHS/outbound-tools-survey-2.json b/agency-indexes/HHS/outbound-tools-survey-2.json deleted file mode 100644 index 8d586cbc..00000000 --- a/agency-indexes/HHS/outbound-tools-survey-2.json +++ /dev/null @@ -1,62 +0,0 @@ -{ - "name": "codejson-generator", - "description": "Form to generate a CMS code.json", - "longDescription": "A web form where project teams fill out information about their project and creates a completed code.json for local download to add to repositories.", - "status": "Production", - "permissions": { - "license": [ - { - "name": "CC0 1.0 Universal", - "URL": "https://github.com/DSACMS/codejson-generator/blob/main/LICENSE" - } - ], - "usageType": "openSource", - "exemptionText": "" - }, - "organization": "Centers for Medicare & Medicaid Services", - "repositoryURL": "https://github.com/DSACMS/codejson-generator", - "vcs": "git", - "laborHours": 3347, - "platforms": [ - "web" - ], - "categories": [ - "it-asset-management", - "inventory-management", - "data-collection" - ], - "softwareType": "standalone/web", - "languages": [ - "JavaScript", - "HTML", - "CSS" - ], - "maintenance": "internal", - "date": { - "created": "2024-11-22T16:30:29Z", - "lastModified": "2025-02-13T20:05:39Z", - "metaDataLastUpdated": "2025-02-14T15:06:13.678Z" - }, - "tags": [ - "codejson", - "compliance", - "OSPO" - ], - "contact": { - "email": "opensource@cms.hhs.gov", - "name": "CMS Open Source Team" - }, - "localisation": false, - "repositoryType": "website", - "userInput": false, - "fismaLevel": "Low", - "group": "CMS/OA/DSAC", - "subsetInHealthcare": [ - "Operational" - ], - "userType": [ - "Government" - ], - "repositoryHost": "github.com/DSACMS", - "maturityModelTier": 3 -} \ No newline at end of file diff --git a/agency-indexes/HHS/un-sdg-form.json b/agency-indexes/HHS/un-sdg-form.json deleted file mode 100644 index 8d586cbc..00000000 --- a/agency-indexes/HHS/un-sdg-form.json +++ /dev/null @@ -1,62 +0,0 @@ -{ - "name": "codejson-generator", - "description": "Form to generate a CMS code.json", - "longDescription": "A web form where project teams fill out information about their project and creates a completed code.json for local download to add to repositories.", - "status": "Production", - "permissions": { - "license": [ - { - "name": "CC0 1.0 Universal", - "URL": "https://github.com/DSACMS/codejson-generator/blob/main/LICENSE" - } - ], - "usageType": "openSource", - "exemptionText": "" - }, - "organization": "Centers for Medicare & Medicaid Services", - "repositoryURL": "https://github.com/DSACMS/codejson-generator", - 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"subsetInHealthcare": [ - "Operational" - ], - "userType": [ - "Government" - ], - "repositoryHost": "github.com/DSACMS", - "maturityModelTier": 1 } ] } \ No newline at end of file diff --git a/scripts/pull-public-assets.py b/scripts/pull-public-assets.py index c640d613..4bc97c44 100644 --- a/scripts/pull-public-assets.py +++ b/scripts/pull-public-assets.py @@ -45,9 +45,16 @@ def main(): for id,repo in enumerate(codegovDict[agency],1): print(f"\nChecking {repo} [{id}/{len(codegovDict[agency])}]") - repoPath = os.path.join(agency_subdir, (repo + '.json')) - repo_obj = indexGen.github.get_repo(repo.split("github.com/")[1]) - code_json = indexGen.save_code_json(repo_obj) + print(repo.split("github.com/")[1]) + try: + repo_obj = indexGen.github.get_repo(repo.split("github.com/")[1]) + + except: + print("Could not retrieve Repo with API query") + continue + + repoPath = os.path.join(agency_subdir, (repo_obj.name + '.json')) + code_json = indexGen.save_code_json(repo_obj,repoPath) if code_json: print(f"✅ Found code.json in {repo}") From b3783f724a8182cc9911c6ea9ddf5d2fd38eaf3f Mon Sep 17 00:00:00 2001 From: Sachin Panayil Date: Wed, 4 Jun 2025 17:02:55 -0400 Subject: [PATCH 05/14] added merge logic and pulled all data succesfully Signed-off-by: Sachin Panayil --- agency-indexes/DHS-index.json | 16899 ++ agency-indexes/DHS/.dotfiles.json | 35 + agency-indexes/DHS/.github.json | 36 + agency-indexes/DHS/ACID.json | 34 + agency-indexes/DHS/ATC-Framework.json | 34 + agency-indexes/DHS/BASE.json | 32 + agency-indexes/DHS/CHIRP.json | 40 + agency-indexes/DHS/CISASuite.json | 32 + agency-indexes/DHS/CSAF.json | 27 + agency-indexes/DHS/ConPCA_test.json | 29 + agency-indexes/DHS/DCAT-dhs.json | 32 + agency-indexes/DHS/ESXiArgs-Recover.json | 34 + agency-indexes/DHS/Epsilon.json | 36 + agency-indexes/DHS/Excel2STIX.json | 29 + agency-indexes/DHS/FLAREclient-Java.json | 33 + agency-indexes/DHS/FLAREclient-UI.json | 35 + agency-indexes/DHS/FLAREclient-container.json | 31 + .../DHS/GMU-CYSE-Capstone-2020-21.json | 32 + agency-indexes/DHS/GTAS-IS.json | 29 + agency-indexes/DHS/GTAS-UI.json | 40 + agency-indexes/DHS/GTAS.json | 60 + agency-indexes/DHS/ICSNPP.json | 32 + agency-indexes/DHS/Katalon_API_Project.json | 27 + agency-indexes/DHS/LME.json | 49 + agency-indexes/DHS/Ludus.json | 40 + agency-indexes/DHS/MQ-Bridge.json | 34 + agency-indexes/DHS/Malcolm.json | 58 + agency-indexes/DHS/PNT-Integrity-Toolkit.json | 36 + agency-indexes/DHS/PNT-Integrity.json | 35 + agency-indexes/DHS/Ready-Set-Cyber.json | 36 + agency-indexes/DHS/RedEye.json | 42 + agency-indexes/DHS/STOAT.json | 40 + agency-indexes/DHS/ScubaGear.json | 51 + agency-indexes/DHS/ScubaGoggles.json | 52 + agency-indexes/DHS/Sogu.json | 33 + agency-indexes/DHS/Sparrow.json | 34 + agency-indexes/DHS/XFD.json | 44 + agency-indexes/DHS/action-apb-dashboard.json | 36 + agency-indexes/DHS/action-apb.json | 39 + .../DHS/action-disable-apparmor.json | 37 + agency-indexes/DHS/action-job-preamble.json | 37 + agency-indexes/DHS/action-lineage.json | 36 + agency-indexes/DHS/admiral-docker.json | 38 + agency-indexes/DHS/admiral.json | 39 + .../DHS/ami-build-iam-user-tf-module.json | 35 + .../DHS/ami-launch-permission-tf-module.json | 35 + agency-indexes/DHS/ansible-manage-user.json | 36 + agency-indexes/DHS/ansible-role-admiral.json | 36 + .../DHS/ansible-role-amazon-efs-utils.json | 36 + .../DHS/ansible-role-amazon-ssm-agent.json | 36 + .../DHS/ansible-role-apt-over-https.json | 36 + .../DHS/ansible-role-assessment-tool.json | 36 + .../DHS/ansible-role-assessor-workbench.json | 37 + ...sible-role-automated-security-updates.json | 36 + .../DHS/ansible-role-backports.json | 36 + agency-indexes/DHS/ansible-role-banner.json | 39 + .../DHS/ansible-role-bloodhound.json | 37 + .../DHS/ansible-role-burp-suite-pro.json | 37 + .../DHS/ansible-role-cdm-certificates.json | 38 + .../DHS/ansible-role-cdm-nessus-agent.json | 40 + .../DHS/ansible-role-cdm-tanium-client.json | 39 + .../DHS/ansible-role-chrony-aws.json | 36 + agency-indexes/DHS/ansible-role-clamav.json | 40 + .../DHS/ansible-role-client-cert-update.json | 38 + .../DHS/ansible-role-cloudwatch-agent.json | 37 + .../DHS/ansible-role-cobalt-strike.json | 40 + .../DHS/ansible-role-code-gov-update.json | 37 + .../DHS/ansible-role-crowdstrike.json | 37 + .../DHS/ansible-role-cs2modrewrite.json | 36 + .../DHS/ansible-role-cyhy-archive.json | 40 + .../DHS/ansible-role-cyhy-commander.json | 40 + .../DHS/ansible-role-cyhy-core.json | 40 + .../DHS/ansible-role-cyhy-feeds.json | 39 + .../DHS/ansible-role-cyhy-logrotate.json | 40 + .../DHS/ansible-role-cyhy-mailer.json | 39 + .../DHS/ansible-role-cyhy-reports.json | 40 + .../DHS/ansible-role-cyhy-runner.json | 39 + .../DHS/ansible-role-dev-ssh-access.json | 39 + .../DHS/ansible-role-devops-user.json | 36 + .../DHS/ansible-role-dhs-certificates.json | 36 + .../DHS/ansible-role-disable-numa.json | 38 + agency-indexes/DHS/ansible-role-docker.json | 38 + .../DHS/ansible-role-domain-manager.json | 39 + .../DHS/ansible-role-ena-driver.json | 36 + .../DHS/ansible-role-freeipa-client.json | 38 + .../DHS/ansible-role-freeipa-server.json | 38 + agency-indexes/DHS/ansible-role-geoip2.json | 37 + .../DHS/ansible-role-guacamole.json | 37 + .../DHS/ansible-role-hardening-2.json | 36 + .../DHS/ansible-role-hardening.json | 36 + agency-indexes/DHS/ansible-role-htop.json | 38 + agency-indexes/DHS/ansible-role-httpd.json | 36 + .../DHS/ansible-role-joiner-user.json | 36 + agency-indexes/DHS/ansible-role-kali.json | 38 + .../DHS/ansible-role-libselinux-python.json | 36 + .../DHS/ansible-role-logrotate.json | 39 + .../DHS/ansible-role-manage-thp.json | 36 + .../ansible-role-megazord-composition.json | 36 + .../DHS/ansible-role-metasploit.json | 36 + .../DHS/ansible-role-mongo-logrotate.json | 39 + agency-indexes/DHS/ansible-role-mongo.json | 40 + .../ansible-role-more-ephemeral-ports.json | 38 + .../DHS/ansible-role-ncats-webd.json | 39 + .../DHS/ansible-role-ncats-webui.json | 38 + agency-indexes/DHS/ansible-role-nessus.json | 40 + agency-indexes/DHS/ansible-role-nmap.json | 38 + agency-indexes/DHS/ansible-role-numactl.json | 37 + agency-indexes/DHS/ansible-role-nvme.json | 39 + .../ansible-role-okta-asa-server-agent.json | 36 + agency-indexes/DHS/ansible-role-openjdk.json | 37 + agency-indexes/DHS/ansible-role-openvpn.json | 41 + .../DHS/ansible-role-oracle-java.json | 38 + .../DHS/ansible-role-orchestrator.json | 38 + .../DHS/ansible-role-passwordless-sudo.json | 36 + .../ansible-role-pca-gophish-composition.json | 37 + .../DHS/ansible-role-persist-journald.json | 39 + agency-indexes/DHS/ansible-role-pip.json | 38 + agency-indexes/DHS/ansible-role-python.json | 38 + .../DHS/ansible-role-remove-python2.json | 36 + agency-indexes/DHS/ansible-role-samba.json | 39 + .../DHS/ansible-role-server-setup.json | 37 + .../DHS/ansible-role-sourcepoint.json | 36 + .../DHS/ansible-role-sshd-allow-rsa.json | 40 + .../DHS/ansible-role-systemd-resolved.json | 36 + .../DHS/ansible-role-terraform.json | 36 + agency-indexes/DHS/ansible-role-ufw.json | 38 + agency-indexes/DHS/ansible-role-upgrade.json | 38 + .../ansible-role-user-with-ssh-access.json | 36 + .../DHS/ansible-role-vdp-scanner.json | 36 + .../DHS/ansible-role-vnc-server.json | 38 + .../DHS/ansible-role-xfce-cool.json | 39 + agency-indexes/DHS/ansible-role-xfce.json | 36 + agency-indexes/DHS/ansible-role-xfs.json | 38 + agency-indexes/DHS/apache2-docker.json | 36 + .../DHS/assessment-data-export.json | 35 + .../DHS/assessment-data-import-lambda.json | 36 + .../DHS/assessment-data-import-terraform.json | 35 + .../DHS/assessment-data-import.json | 36 + .../DHS/assessor-workbench-packer.json | 36 + ...bda-with-cloudwatch-trigger-tf-module.json | 35 + agency-indexes/DHS/aws-profile-sync.json | 40 + agency-indexes/DHS/aws_playground.json | 34 + agency-indexes/DHS/awssh.json | 36 + agency-indexes/DHS/bad-practices.json | 35 + agency-indexes/DHS/base-images.json | 31 + .../DHS/bems-theme-react-starter.json | 32 + agency-indexes/DHS/beyond-dev.json | 27 + agency-indexes/DHS/bod-18-01-celery.json | 35 + .../DHS/bod-18-01-cloudwatch-users.json | 39 + agency-indexes/DHS/bod-18-01-terraform.json | 42 + .../DHS/build-debian-buster-ami.json | 32 + agency-indexes/DHS/cbp-ds-for-designers.json | 27 + agency-indexes/DHS/cbp-style-guide.json | 39 + agency-indexes/DHS/cbp-theme.json | 43 + .../DHS/cert-read-role-tf-module.json | 35 + agency-indexes/DHS/certboto-docker.json | 42 + agency-indexes/DHS/check-cve-2019-19781.json | 39 + agency-indexes/DHS/check-your-pulse.json | 34 + agency-indexes/DHS/ci-iam-user-tf-module.json | 35 + agency-indexes/DHS/cisagov.json | 34 + agency-indexes/DHS/clamav-report.json | 39 + agency-indexes/DHS/client-cert-update.json | 37 + agency-indexes/DHS/code-gov-update.json | 38 + agency-indexes/DHS/con-pca-api.json | 40 + agency-indexes/DHS/con-pca-cicd.json | 36 + agency-indexes/DHS/con-pca-gophish.json | 39 + agency-indexes/DHS/con-pca-reports.json | 40 + agency-indexes/DHS/con-pca-tasks-docker.json | 36 + agency-indexes/DHS/con-pca-tasks.json | 36 + agency-indexes/DHS/con-pca-web.json | 42 + .../DHS/cool-accounts-cyhy-tf-root.json | 35 + .../DHS/cool-accounts-domain-manager.json | 35 + agency-indexes/DHS/cool-accounts-pca.json | 35 + .../DHS/cool-accounts-userservices.json | 35 + agency-indexes/DHS/cool-accounts.json | 35 + .../DHS/cool-admin-provisioner-iam.json | 35 + .../cool-assessment-images-manager-iam.json | 35 + .../DHS/cool-assessment-provisioner-iam.json | 35 + .../DHS/cool-assessment-terraform.json | 36 + agency-indexes/DHS/cool-auditor-iam.json | 35 + .../DHS/cool-cdm-cloudtrail-tf-module.json | 35 + .../DHS/cool-certificate-manager-iam.json | 35 + .../DHS/cool-configure-aws-account.json | 35 + .../DHS/cool-dns-57.69.64.in-addr.arpa.json | 35 + agency-indexes/DHS/cool-dns-certboto.json | 35 + .../DHS/cool-dns-cyber.dhs.gov.json | 35 + agency-indexes/DHS/cool-dns-dmarc-import.json | 35 + .../DHS/cool-domain-manager-iam.json | 35 + .../DHS/cool-domain-manager-networking.json | 35 + .../DHS/cool-iam-user-group-manager-iam.json | 35 + .../DHS/cool-images-assessment-images.json | 35 + .../DHS/cool-images-parameterstore.json | 35 + agency-indexes/DHS/cool-images-vmimport.json | 35 + agency-indexes/DHS/cool-pca-iam.json | 35 + .../cool-pca-transitgateway-attachment.json | 35 + .../DHS/cool-root-new-user-alarm.json | 35 + .../DHS/cool-ses-send-email-iam.json | 35 + .../DHS/cool-sharedservices-cdm.json | 38 + .../DHS/cool-sharedservices-freeipa.json | 35 + .../DHS/cool-sharedservices-nessus.json | 35 + .../DHS/cool-sharedservices-networking.json | 35 + .../DHS/cool-sharedservices-openvpn.json | 35 + agency-indexes/DHS/cool-users-non-admin.json | 35 + agency-indexes/DHS/cool-userservices-dns.json | 35 + .../DHS/cool-userservices-networking.json | 35 + .../DHS/cool-userservices-was-db.json | 35 + agency-indexes/DHS/cool-was-db-iam.json | 35 + .../DHS/cool-windows-ami-sharing.json | 35 + agency-indexes/DHS/copy-old-es-database.json | 34 + agency-indexes/DHS/coredns-docker.json | 36 + agency-indexes/DHS/crossfeed-mlb.json | 44 + agency-indexes/DHS/crossfeed.json | 47 + agency-indexes/DHS/cset-analytics-api.json | 38 + agency-indexes/DHS/cset-analytics-cicd.json | 35 + agency-indexes/DHS/cset-analytics-ui.json | 40 + agency-indexes/DHS/cset-analytics.json | 27 + agency-indexes/DHS/cset-bucket-terraform.json | 35 + agency-indexes/DHS/cset-test.json | 29 + agency-indexes/DHS/cset.json | 49 + agency-indexes/DHS/cyber-care-archive.json | 34 + agency-indexes/DHS/cyber.dhs.gov.json | 38 + .../DHS/cybersecurity-performance-goals.json | 35 + agency-indexes/DHS/cyhy-account.json | 35 + agency-indexes/DHS/cyhy-api.json | 36 + agency-indexes/DHS/cyhy-auditor-iam.json | 35 + agency-indexes/DHS/cyhy-commander-docker.json | 39 + agency-indexes/DHS/cyhy-commander.json | 31 + agency-indexes/DHS/cyhy-config.json | 35 + agency-indexes/DHS/cyhy-core.json | 38 + agency-indexes/DHS/cyhy-ct-logs.json | 35 + agency-indexes/DHS/cyhy-cvesync-lambda.json | 39 + agency-indexes/DHS/cyhy-cvesync.json | 35 + agency-indexes/DHS/cyhy-db.json | 35 + agency-indexes/DHS/cyhy-feeds.json | 35 + agency-indexes/DHS/cyhy-hackfest-2022-09.json | 38 + agency-indexes/DHS/cyhy-kevsync-lambda.json | 40 + agency-indexes/DHS/cyhy-kevsync.json | 40 + .../DHS/cyhy-lambda-bucket-terraform.json | 35 + agency-indexes/DHS/cyhy-logging.json | 35 + agency-indexes/DHS/cyhy-mailer.json | 36 + .../DHS/cyhy-nvdsync-lambda-terraform.json | 35 + agency-indexes/DHS/cyhy-nvdsync-lambda.json | 36 + agency-indexes/DHS/cyhy-reports.json | 33 + agency-indexes/DHS/cyhy-runner.json | 35 + agency-indexes/DHS/cyhy-system.json | 34 + agency-indexes/DHS/cyhy-tf-root.json | 35 + agency-indexes/DHS/cyhy-users-non-admin.json | 35 + agency-indexes/DHS/cyhy-web.json | 36 + agency-indexes/DHS/cyhy_amis.json | 42 + agency-indexes/DHS/dcat-tool.json | 32 + agency-indexes/DHS/debian-packer.json | 36 + agency-indexes/DHS/decider.json | 40 + .../DHS/dependabot-automerge-test.json | 34 + agency-indexes/DHS/design-system.json | 39 + agency-indexes/DHS/development-guide.json | 38 + .../disable-inactive-iam-users-lambda.json | 36 + .../disable-inactive-iam-users-tf-module.json | 35 + .../DHS/distributed-subnets-tf-module.json | 35 + agency-indexes/DHS/dmarc-import-lambda.json | 36 + .../DHS/dmarc-import-tf-module.json | 35 + agency-indexes/DHS/dmarc-import.json | 37 + agency-indexes/DHS/dns_audit.json | 34 + .../DHS/docker-debian11-ansible.json | 35 + .../DHS/docker-debian12-ansible.json | 35 + .../DHS/docker-debian13-ansible.json | 35 + .../DHS/docker-fedora33-ansible.json | 34 + agency-indexes/DHS/docker-kali-ansible.json | 35 + agency-indexes/DHS/docker-packer.json | 36 + agency-indexes/DHS/domain-manager-api.json | 39 + agency-indexes/DHS/domain-manager-cicd.json | 35 + agency-indexes/DHS/domain-manager-cli.json | 36 + agency-indexes/DHS/domain-manager-ui.json | 42 + agency-indexes/DHS/domain-manager.json | 27 + agency-indexes/DHS/domain-scan.json | 36 + agency-indexes/DHS/dotgov-data.json | 36 + agency-indexes/DHS/dotgov-home.json | 36 + agency-indexes/DHS/dotgov-rfi.json | 28 + agency-indexes/DHS/egress-assess-packer.json | 36 + agency-indexes/DHS/elastic-ips-terraform.json | 36 + agency-indexes/DHS/email-mq-bridge.json | 34 + agency-indexes/DHS/epplib.json | 34 + .../DHS/fargate-browserless-tf-module.json | 34 + .../DHS/fargate-container-def-tf-module.json | 35 + .../DHS/fargate-service-tf-module.json | 34 + agency-indexes/DHS/fast-ansible.json | 31 + agency-indexes/DHS/fast-terraform.json | 30 + agency-indexes/DHS/findcdn.json | 41 + .../DHS/findings-data-import-lambda.json | 36 + .../DHS/findings-data-import-terraform.json | 35 + .../DHS/findings-data-s3-users.json | 35 + agency-indexes/DHS/flare-misp-service.json | 31 + agency-indexes/DHS/flat-tribal-leaders.json | 29 + agency-indexes/DHS/freeipa-client-packer.json | 38 + .../DHS/freeipa-client-tf-module.json | 35 + .../DHS/freeipa-replica-tf-module.json | 39 + agency-indexes/DHS/freeipa-server-packer.json | 38 + .../DHS/freeipa-server-tf-module.json | 38 + agency-indexes/DHS/gatherer.json | 37 + agency-indexes/DHS/get.gov.json | 36 + agency-indexes/DHS/gh-skeleton.json | 35 + .../DHS/github-actions-playground.json | 34 + .../DHS/github-actions-python-docker.json | 36 + .../DHS/github-actions-workflows.json | 34 + .../DHS/github-projects-burndown-chart.json | 35 + .../DHS/github_org_name_change.json | 34 + agency-indexes/DHS/gophish-docker.json | 36 + agency-indexes/DHS/gophish-tools.json | 36 + agency-indexes/DHS/gophish.json | 37 + agency-indexes/DHS/guacamole-composition.json | 35 + agency-indexes/DHS/guacamole-packer.json | 37 + agency-indexes/DHS/guacscanner-docker.json | 37 + agency-indexes/DHS/guacscanner.json | 36 + 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"vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DHS/PNT-Integrity-Toolkit.json b/agency-indexes/DHS/PNT-Integrity-Toolkit.json new file mode 100644 index 00000000..317483fa --- /dev/null +++ b/agency-indexes/DHS/PNT-Integrity-Toolkit.json @@ -0,0 +1,36 @@ +{ + "contact": { + "URL": "https://github.com/cisagov", + "email": "do_not_email_just_use_github@dhs.gov" + }, + "date": { + "created": "2021-09-23", + "lastModified": "2024-06-21" + }, + "description": "The PNT Integrity DIY Toolkit describes how a perspective end-user of the PNT Integrity Library can assemble a demonstrational toolkit with commercial-off-the-shelf (COTS) hardware.", + "downloadURL": "https://api.github.com/repos/cisagov/PNT-Integrity-Toolkit/downloads", + "homepageURL": "https://github.com/cisagov/PNT-Integrity-Toolkit", + "laborHours": 25632.4, + "languages": [ + "C++", + "CMake", + "HTML", + "TeX", + "C", + "Shell", + "Makefile", + "Python" + ], + "name": "PNT-Integrity-Toolkit", + 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}, + "description": "Sparrow.ps1 was created by CISA's Cloud Forensics team to help detect possible compromised accounts and applications in the Azure/m365 environment.", + "downloadURL": "https://api.github.com/repos/cisagov/Sparrow/downloads", + "homepageURL": "https://github.com/cisagov/Sparrow", + "laborHours": 272.6, + "languages": [ + "PowerShell" + ], + "name": "Sparrow", + "organization": "Cybersecurity and Infrastructure Security Agency", + "permissions": { + "licenses": [ + { + "URL": "https://api.github.com/licenses/cc0-1.0", + "name": "CC0-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cisagov/Sparrow.git", + "status": "Development", + "tags": [ + "github" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DHS/XFD.json b/agency-indexes/DHS/XFD.json new file mode 100644 index 00000000..dbffc07a --- /dev/null +++ b/agency-indexes/DHS/XFD.json @@ -0,0 +1,44 @@ +{ + "contact": { + "URL": 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at end of file diff --git a/agency-indexes/DHS/ansible-role-bloodhound.json b/agency-indexes/DHS/ansible-role-bloodhound.json new file mode 100644 index 00000000..c0a1369f --- /dev/null +++ b/agency-indexes/DHS/ansible-role-bloodhound.json @@ -0,0 +1,37 @@ +{ + "contact": { + "URL": "https://github.com/cisagov", + "email": "do_not_email_just_use_github@dhs.gov" + }, + "date": { + "created": "2019-08-06", + "lastModified": "2024-11-19" + }, + "description": "An Ansible role for installing BloodHound", + "downloadURL": "https://api.github.com/repos/cisagov/ansible-role-bloodhound/downloads", + "homepageURL": "https://github.com/cisagov/ansible-role-bloodhound", + "laborHours": 448.8, + "languages": [ + "Shell", + "Python" + ], + "name": "ansible-role-bloodhound", + "organization": "Cybersecurity and Infrastructure Security Agency", + "permissions": { + "licenses": [ + { + "URL": "https://api.github.com/licenses/cc0-1.0", + "name": "CC0-1.0" + } + ], + "usageType": "openSource" + }, + 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In addition, the food database is based on FNDDS from 2011-2012 (FNDDS 6.0) and FPED from 2011-2012 and will not be updated with future data releases.", + "tags": [ + "Dietary Guidelines", + "Health", + "Nutrition" + ], + "contact": { + "email": "Jackie.Haven@cnpp.usda.gov" + }, + "status": "Archival", + "vcs": "zip", + "downloadURL": "https://inventory.data.gov/dataset/97f9a5cf-61c4-406b-8170-5a6422b68654/resource/c04948d7-4af3-42c7-ae4b-5b805ea7571e/download/supertrackersource2.zip", + "languages": [], + "repositoryURL": "https://inventory.data.gov/dataset/97f9a5cf-61c4-406b-8170-5a6422b68654/resource/c04948d7-4af3-42c7-ae4b-5b805ea7571e/download/supertrackersource2.zip", + "homepageURL": "https://catalog.data.gov/dataset/supertracker-source-code-and-foods-database", + "permissions": { + "licenses": [ + { + "URL": "http://opendefinition.org/licenses/cc-zero/", + "name": "CC0" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "created": "2018-10-12", + "lastModified": "2019-05-02", + "metadataLastUpdated": "2019-09-22" + } + }, + { + "organization": "ARS", + "name": "Fast and robust curve skeletonization for real-world elongated objects", + "description": "A curve skeletonization method for elongated objects that may be noisy.", + "tags": [ + "curve skeletonization" + ], + "contact": { + "email": "amy.tabb@ars.usda.gov" + }, + "status": "Production", + "vcs": "git", + "downloadURL": "https://github.com/amy-tabb/CurveSkel-Tabb-Medeiros.git", + "languages": [ + "C++" + ], + "repositoryURL": "https://github.com/amy-tabb/CurveSkel-Tabb-Medeiros", + "homepageURL": "https://github.com/amy-tabb/CurveSkel-Tabb-Medeiros", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/amy-tabb/CurveSkel-Tabb-Medeiros/blob/master/LICENSE", + "name": "GPL 3.0" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "created": "2017-10-11", + "lastModified": "2018-08-16", + "metadataLastUpdated": "2019-09-22" + } + }, + { + "organization": "ARS", + "name": "Automated Water Supply Model (AWSM)", + "description": "Automated Water Supply Model (AWSM) was developed at the USDA Agricultural Research Service (ARS) in Boise, ID. AWSM was designed to streamline the work flow used by the ARS to forecast the water supply of multiple water basins. AWSM standardizes the steps needed to distribute weather station data with SMRF, run an energy and mass balance with iSnobal, and process the results, while maintaining the flexibility of each program.", + "tags": [ + "Northwest Watershed Research Center", + "watershed", + "hydrology", + "awsm", + "forecast", + "modeling", + "water", + "snow", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/awsm.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/awsm", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/awsm/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2017-01-18", + "lastModified": "2020-03-24", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Spatial Modeling for Resources Framework (SMRF)", + "description": "Spatial Modeling for Resources Framework (SMRF) was developed by Dr. Scott Havens at the USDA Agricultural Research Service (ARS) in Boise, ID. SMRF was designed to increase the flexibility of taking measured weather data and distributing the point measurements across a watershed. SMRF was developed to be used as an operational or research framework, where ease of use, efficiency, and ability to run in near real time are high priorities.", + "tags": [ + "Northwest Watershed Research Center", + "smrf", + "watershed", + "hydrology", + "modeling", + "interpolation", + "water", + "snow", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python", + "c", + "fortran" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/smrf.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/smrf", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/smrf/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2015-12-28", + "lastModified": "2020-04-30", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Weather Database", + "description": "The Weather Database project creates a MySQL database to ingest and manage weather station data from multiple sources. Included in the repository are the schema model and everything needed to generate a weather station database. The wxdb package is able to interact with the database and grab metadata and station data from multiple sources. ", + "tags": [ + "Northwest Watershed Research Center", + "weather-database", + "database", + "docker", + "python", + "snow", + "modeling", + "mesowest" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python", + "PLSQL", + "PLpgSQL" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/weather_database.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/weather_database", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/weather_database/blob/master/LICENSE", + "name": "GPL3.0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2015-12-29", + "lastModified": "2019-06-04", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Weather forecast retrieval", + "description": "Weather forecast retrieval gathers relevant gridded weather forecasts to ingest into physically based models for water supply forecasts", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python", + "docker" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/weather_forecast_retrieval.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/weather_forecast_retrieval", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/weather_forecast_retrieval/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2017-11-15", + "lastModified": "2020-03-27", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Python Snobal", + "description": "Python implementation of the Snobal model applied at either a point or over and image (iSnobal). This package conatains the C libraries of Snobal in a python wrapper for more flexibility and ease of interaction.", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "c++", + "c", + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/pysnobal.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/pysnobal", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/pysnobal/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2016-01-09", + "lastModified": "2020-05-01", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Snow and water model analysis and visualization (snowav)", + "description": "Snow and water model analysis and visualization (snowav) processes the spatial inputs from smrf and spatial outputs from awsm into summary database values, and generates figures and reports for dissemination.", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "snow", + "water", + "model", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/snowav.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/snowav", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/snowav/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2017-12-13", + "lastModified": "2020-04-28", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Image Processing Workbench (IPW)", + "description": "Image Processing Workbench (IPW) is a collection of utilities to process digital images. IPW contains the energy-balance snowmelt models Snobal and iSnobal.", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "snow", + "water", + "model", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "C", + "Roff", + "Fortran" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/ipw.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/ipw", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/snowav/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2015-03-05", + "lastModified": "2020-03-22", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "inicheck", + "description": "inicheck is an advanced configuration file checker/manager enabling developers high end control over their users configuration files. inicheck is specifcially aimed at files that adhere to the .ini format.", + "tags": [ + "Northwest Watershed Research Center", + "ini file" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/inicheck.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/inicheck", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/inicheck/blob/master/LICENSE", + "name": "GPL 3.0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2018-01-05", + "lastModified": "2020-02-26", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Basin setup tool", + "description": "The basin setup tool is a python script designed to create the required inputs for running SMRF and AWSM simulations. The tool outputs a single netcdf file containing the necessary spatial information for a water basin This includes basin mask, DEM, veg type and height (from Landfire), veg tau, and veg K.", + "tags": [ + "Northwest Watershed Research Center" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/basin_setup.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/basin_setup", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/inicheck/blob/master/LICENSE", + "name": "GPL 3.0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2017-12-05", + "lastModified": "2020-04-29", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "swiflow", + "description": "A python package for modeling streamflow from modeled surface water input.", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "snow", + "water", + "model", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/swiflow.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/swiflow", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/swiflow/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2019-05-23", + "lastModified": "2020-04-02", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "topocalc", + "description": "The topocalc package is a collection of functions to calculate various metrics on a digital elevation model (DEM). The calculations follow the equations laid out in Dozier and Frew, 1990 for the gradient, horizon and sky view factor. ", + "tags": [ + "Northwest Watershed Research Center", + "model", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "Jupyter Notebook" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/topocalc.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/topocalc", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/topocalc/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2020-04-07", + "lastModified": "2020-04-23", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Goldmeister", + "description": "Goldmeister is a Python package designed to manage/examine changes to a gold file.", + "tags": [ + "Northwest Watershed Research Center", + "dataset" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/goldmeister.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/goldmeister", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/goldmeister/blob/master/LICENSE", + "name": "MIT" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2020-04-08", + "lastModified": "2020-04-22", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "spatialnc", + "description": "Python library for managing spatial data in netcdfs with a lot of functionality specifically for AWSM/SMRF.", + "tags": [ + "Northwest Watershed Research Center", + "spatial" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/spatialnc.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/spatialnc", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/spatialnc/blob/master/LICENSE", + "name": "MIT" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2019-01-31", + "lastModified": "2020-04-16", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Tablizer", + "description": "Tablizer makes simple statistical summaries of DataFrames and arrays, and places them on SQL or sqlite database.", + "tags": [ + "Northwest Watershed Research Center", + "statistical summaries" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/tablizer.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/tablizer", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/tablizer/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2019-08-20", + "lastModified": "2019-10-08", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Katana", + "description": "A project for bringing WindNinja Data into the AWSM system.", + "tags": [ + "Northwest Watershed Research Center", + "WindNinja" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/katana.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/katana", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/katana/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2018-08-27", + "lastModified": "2020-04-07", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "AWSM Run Manager", + "description": "AWSM run manager is designed to facilitate AWSM simulations from the command line with more complicated simulations involving multiple Docker images. Currently, awsm_run_manager only supports runs that use atmospheric model's as inputs, like the High Resolution Rapid Refresh, because the Wind is downscaled using Katana.", + "tags": [ + "Northwest Watershed Research Center", + "Docker", + "Katana" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/awsm_run_manager.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/awsm_run_manager", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/awsm_run_manager/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2020-01-02", + "lastModified": "2020-02-06", + "metadataLastUpdated": "2020-05-03" + } + }, + { + "organization": "ARS", + "name": "Repeat Array Quality Check (RAQC)", + "description": "Utility to assess change in 3D image data, such as gridded output from models and remote sensing imagery collected repeatedly over the same spatial domain.", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "snow", + "water", + "model", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/raqc.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/raqc", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/raqc/blob/master/LICENSE", + "name": "GPL3" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2019-08-01", + "lastModified": "2019-11-05", + "metadataLastUpdated": "2020-05-03" + } + } + ] +} \ No newline at end of file diff --git a/agency-indexes/DoA/AWSM_Run_Manager.json b/agency-indexes/DoA/AWSM_Run_Manager.json new file mode 100644 index 00000000..d85a362f --- /dev/null +++ b/agency-indexes/DoA/AWSM_Run_Manager.json @@ -0,0 +1,37 @@ +{ + "organization": "ARS", + "name": "AWSM Run Manager", + "description": "AWSM run manager is designed to facilitate AWSM simulations from the command line with more complicated simulations involving multiple Docker images. Currently, awsm_run_manager only supports runs that use atmospheric model's as inputs, like the High Resolution Rapid Refresh, because the Wind is downscaled using Katana.", + "tags": [ + "Northwest Watershed Research Center", + "Docker", + "Katana" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/awsm_run_manager.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/awsm_run_manager", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/awsm_run_manager/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2020-01-02", + "lastModified": "2020-02-06", + "metadataLastUpdated": "2020-05-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Animal_Disease_Spread_Model.json b/agency-indexes/DoA/Animal_Disease_Spread_Model.json new file mode 100644 index 00000000..c43cb806 --- /dev/null +++ b/agency-indexes/DoA/Animal_Disease_Spread_Model.json @@ -0,0 +1,46 @@ +{ + "organization": "APHIS", + "name": "Animal Disease Spread Model", + "description": "A simulation of disease spread in livestock populations. Includes detection and containment simulation.", + "repositoryURL": "https://github.com/NAVADMC/ADSM", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/NAVADMC/ADSM/blob/master/LICENSE", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "laborHours": 2838, + "relatedCode": [ + { + "name": "Animal Disease Spread Model C-Engine", + "URL": "https://github.com/NAVADMC/ADSM-CEngine" + } + ], + "tags": [ + "USDA", + "source code", + "animal", + "disease", + "herds", + "livestock", + "simulation", + "model" + ], + "contact": { + "email": "Melissa.Schoenbaum@usda.gov", + "name": "Missy Schoenbaum" + }, + "status": "Beta", + "vcs": "git", + "languages": [ + "python" + ], + "homepageURL": "https://github.com/NAVADMC/ADSM", + "date": { + "lastModified": "2019-06-06", + "metadataLastUpdated": "2019-11-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Animal_Disease_Spread_Model_C-Engine.json b/agency-indexes/DoA/Animal_Disease_Spread_Model_C-Engine.json new file mode 100644 index 00000000..b3b7a8ba --- /dev/null +++ b/agency-indexes/DoA/Animal_Disease_Spread_Model_C-Engine.json @@ -0,0 +1,46 @@ +{ + "organization": "APHIS", + "name": "Animal Disease Spread Model C-Engine", + "description": "The Simulation Backend for the Animal Disease Spread Model (ADSM) Project.", + "repositoryURL": "https://github.com/NAVADMC/ADSM-CEngine", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/NAVADMC/ADSM-CEngine/blob/master/LICENSE", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "relatedCode": [ + { + "name": "Animal Disease Spread Model (ADSM)", + "URL": "https://github.com/NAVADMC/ADSM" + } + ], + "tags": [ + "USDA", + "source code", + "animal", + "disease", + "herds", + "livestock", + "simulation", + "model" + ], + "contact": { + "email": "Melissa.Schoenbaum@usda.gov", + "name": "Missy Schoenbaum" + }, + "status": "Beta", + "vcs": "git", + "languages": [ + "C" + ], + "homepageURL": "https://github.com/NAVADMC/ADSM-CEngine", + "date": { + "lastModified": "2019-05-22", + "metadataLastUpdated": "2019-11-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Automated_Water_Supply_Model__AWSM_.json b/agency-indexes/DoA/Automated_Water_Supply_Model__AWSM_.json new file mode 100644 index 00000000..51af3252 --- /dev/null +++ b/agency-indexes/DoA/Automated_Water_Supply_Model__AWSM_.json @@ -0,0 +1,43 @@ +{ + "organization": "ARS", + "name": "Automated Water Supply Model (AWSM)", + "description": "Automated Water Supply Model (AWSM) was developed at the USDA Agricultural Research Service (ARS) in Boise, ID. AWSM was designed to streamline the work flow used by the ARS to forecast the water supply of multiple water basins. AWSM standardizes the steps needed to distribute weather station data with SMRF, run an energy and mass balance with iSnobal, and process the results, while maintaining the flexibility of each program.", + "tags": [ + "Northwest Watershed Research Center", + "watershed", + "hydrology", + "awsm", + "forecast", + "modeling", + "water", + "snow", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/awsm.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/awsm", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/awsm/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2017-01-18", + "lastModified": "2020-03-24", + "metadataLastUpdated": "2020-05-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Basin_setup_tool.json b/agency-indexes/DoA/Basin_setup_tool.json new file mode 100644 index 00000000..f349688d --- /dev/null +++ b/agency-indexes/DoA/Basin_setup_tool.json @@ -0,0 +1,35 @@ +{ + "organization": "ARS", + "name": "Basin setup tool", + "description": "The basin setup tool is a python script designed to create the required inputs for running SMRF and AWSM simulations. The tool outputs a single netcdf file containing the necessary spatial information for a water basin This includes basin mask, DEM, veg type and height (from Landfire), veg tau, and veg K.", + "tags": [ + "Northwest Watershed Research Center" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/basin_setup.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/basin_setup", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/inicheck/blob/master/LICENSE", + "name": "GPL 3.0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2017-12-05", + "lastModified": "2020-04-29", + "metadataLastUpdated": "2020-05-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/BovineTFBS.json b/agency-indexes/DoA/BovineTFBS.json new file mode 100644 index 00000000..728e5336 --- /dev/null +++ b/agency-indexes/DoA/BovineTFBS.json @@ -0,0 +1,23 @@ +{ + "organization": "ARS-ARGIL", + "name": "BovineTFBS", + "description": "USDA-ARS Animal Genomics and Improvement Laboratory; CDH Conserved Transcription Factor Binding Sites", + "tags": [], + "contact": { + "email": "source.code@ocio.usda.gov" + }, + "status": "Production", + "vcs": "git", + "downloadURL": "https://github.com/USDA-ARS-AGIL/BovineTFBS/archive/master.zip", + "repositoryURL": "https://github.com/USDA-ARS-AGIL/BovineTFBS", + "homepageURL": "https://github.com/USDA-ARS-AGIL/BovineTFBS", + "permissions": { + "licenses": [], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "lastModified": "2015-06-22", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/DigitalGov_Analytics.json b/agency-indexes/DoA/DigitalGov_Analytics.json new file mode 100644 index 00000000..42dc9f28 --- /dev/null +++ b/agency-indexes/DoA/DigitalGov_Analytics.json @@ -0,0 +1,38 @@ +{ + "organization": "OC", + "name": "DigitalGov Analytics", + "description": "A Drupal Module that implements all features defined within the DAP Implementation Guide by exposing an admin configuration page to edit each resource reference customization.", + "repositoryURL": "https://www.drupal.org/project/gov_analytics", + "permissions": { + "licenses": [ + { + "URL": "http://www.gnu.org/licenses/old-licenses/gpl-2.0.html", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "laborHours": 16, + "tags": [ + "Drupal", + "DigitalGov", + "analytics", + "DAP" + ], + "contact": { + "email": "Source.Code@ocio.usda.gov", + "name": "USDA Source Code" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "Drupal", + "php" + ], + "homepageURL": "https://www.drupal.org/project/gov_analytics", + "date": { + "created": "2015-05-29", + "lastModified": "2015-06-01", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/FSA_Prototype_Kit.json b/agency-indexes/DoA/FSA_Prototype_Kit.json new file mode 100644 index 00000000..8b8b0a44 --- /dev/null +++ b/agency-indexes/DoA/FSA_Prototype_Kit.json @@ -0,0 +1,27 @@ +{ + "organization": "FSA", + "name": "FSA Prototype Kit", + "description": "A baseline project starter that utilizes webpack and FSA Style.", + "languages": [ + "JavaScript" + ], + "tags": [], + "contact": { + "email": "source.code@ocio.usda.gov" + }, + "status": "Production", + "vcs": "git", + "downloadURL": "https://github.com/USDA-FSA/fsa-prototype-kit/archive/master.zip", + "repositoryURL": "https://github.com/USDA-FSA/fsa-prototype-kit", + "homepageURL": "https://github.com/USDA-FSA/fsa-prototype-kit", + "permissions": { + "licenses": [], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "created": "2018-08-01", + "lastModified": "2019-04-24", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Fast_and_robust_curve_skeletonization_for_real-world_elongated_objects.json b/agency-indexes/DoA/Fast_and_robust_curve_skeletonization_for_real-world_elongated_objects.json new file mode 100644 index 00000000..8682ad77 --- /dev/null +++ b/agency-indexes/DoA/Fast_and_robust_curve_skeletonization_for_real-world_elongated_objects.json @@ -0,0 +1,34 @@ +{ + "organization": "ARS", + "name": "Fast and robust curve skeletonization for real-world elongated objects", + "description": "A curve skeletonization method for elongated objects that may be noisy.", + "tags": [ + "curve skeletonization" + ], + "contact": { + "email": "amy.tabb@ars.usda.gov" + }, + "status": "Production", + "vcs": "git", + "downloadURL": "https://github.com/amy-tabb/CurveSkel-Tabb-Medeiros.git", + "languages": [ + "C++" + ], + "repositoryURL": "https://github.com/amy-tabb/CurveSkel-Tabb-Medeiros", + "homepageURL": "https://github.com/amy-tabb/CurveSkel-Tabb-Medeiros", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/amy-tabb/CurveSkel-Tabb-Medeiros/blob/master/LICENSE", + "name": "GPL 3.0" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "created": "2017-10-11", + "lastModified": "2018-08-16", + "metadataLastUpdated": "2019-09-22" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Goldmeister.json b/agency-indexes/DoA/Goldmeister.json new file mode 100644 index 00000000..eb2f67a2 --- /dev/null +++ b/agency-indexes/DoA/Goldmeister.json @@ -0,0 +1,36 @@ +{ + "organization": "ARS", + "name": "Goldmeister", + "description": "Goldmeister is a Python package designed to manage/examine changes to a gold file.", + "tags": [ + "Northwest Watershed Research Center", + "dataset" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/goldmeister.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/goldmeister", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/goldmeister/blob/master/LICENSE", + "name": "MIT" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2020-04-08", + "lastModified": "2020-04-22", + "metadataLastUpdated": "2020-05-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Image_Processing_Workbench__IPW_.json b/agency-indexes/DoA/Image_Processing_Workbench__IPW_.json new file mode 100644 index 00000000..e9239c41 --- /dev/null +++ b/agency-indexes/DoA/Image_Processing_Workbench__IPW_.json @@ -0,0 +1,42 @@ +{ + "organization": "ARS", + "name": "Image Processing Workbench (IPW)", + "description": "Image Processing Workbench (IPW) is a collection of utilities to process digital images. IPW contains the energy-balance snowmelt models Snobal and iSnobal.", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "snow", + "water", + "model", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "C", + "Roff", + "Fortran" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/ipw.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/ipw", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/snowav/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2015-03-05", + "lastModified": "2020-03-22", + "metadataLastUpdated": "2020-05-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Katana.json b/agency-indexes/DoA/Katana.json new file mode 100644 index 00000000..6b2ad0d2 --- /dev/null +++ b/agency-indexes/DoA/Katana.json @@ -0,0 +1,36 @@ +{ + "organization": "ARS", + "name": "Katana", + "description": "A project for bringing WindNinja Data into the AWSM system.", + "tags": [ + "Northwest Watershed Research Center", + "WindNinja" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/katana.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/katana", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/katana/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2018-08-27", + "lastModified": "2020-04-07", + "metadataLastUpdated": "2020-05-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/LAP__LAMP_without_MySQL__on_Docker.json b/agency-indexes/DoA/LAP__LAMP_without_MySQL__on_Docker.json new file mode 100644 index 00000000..9ea18203 --- /dev/null +++ b/agency-indexes/DoA/LAP__LAMP_without_MySQL__on_Docker.json @@ -0,0 +1,37 @@ +{ + "organization": "OC", + "name": "LAP (LAMP without MySQL) on Docker", + "description": "Docker LAP/MySQL for Drupal and PHP", + "repositoryURL": "https://bitbucket.org/usdawcmaas/gov-drupal", + "permissions": { + "licenses": [ + { + "URL": "http://www.gnu.org/licenses/old-licenses/gpl-2.0.html", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "laborHours": 480, + "tags": [ + "Docker", + "Drupal", + "PHP", + "DevOps" + ], + "contact": { + "email": "Source.Code@ocio.usda.gov", + "name": "USDA Source Code" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "salt" + ], + "homepageURL": "https://bitbucket.org/usdawcmaas/gov-drupal", + "date": { + "created": "2015-03-24", + "lastModified": "2019-02-05", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Open_Forest.json b/agency-indexes/DoA/Open_Forest.json new file mode 100644 index 00000000..05ac16c7 --- /dev/null +++ b/agency-indexes/DoA/Open_Forest.json @@ -0,0 +1,34 @@ +{ + "organization": "Forest Service (FS)", + "name": "Open Forest", + "description": "This repo contains documentation describing the United States Forest Service (USFS) Open Forest project.", + "tags": [], + "contact": { + "email": "SM.FS.OpnFrstCsSup@usda.gov" + }, + "status": "Production", + "vcs": "git", + "downloadURL": "https://github.com/USDAForestService/fs-open-forest", + "languages": [ + "javascript", + "jquery", + "html5" + ], + "repositoryURL": "https://github.com/USDAForestService/fs-open-forest", + "homepageURL": "https://github.com/USDAForestService/fs-open-forest", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDAForestService/fs-open-forest/blob/master/license.md", + "name": "CC0" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "created": "2017-04-20", + "lastModified": "2019-09-18", + "metadataLastUpdated": "2019-09-18" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Python_Snobal.json b/agency-indexes/DoA/Python_Snobal.json new file mode 100644 index 00000000..bc497e7d --- /dev/null +++ b/agency-indexes/DoA/Python_Snobal.json @@ -0,0 +1,39 @@ +{ + "organization": "ARS", + "name": "Python Snobal", + "description": "Python implementation of the Snobal model applied at either a point or over and image (iSnobal). This package conatains the C libraries of Snobal in a python wrapper for more flexibility and ease of interaction.", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "c++", + "c", + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/pysnobal.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/pysnobal", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/pysnobal/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2016-01-09", + "lastModified": "2020-05-01", + "metadataLastUpdated": "2020-05-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/RIDB.json b/agency-indexes/DoA/RIDB.json new file mode 100644 index 00000000..de668d6d --- /dev/null +++ b/agency-indexes/DoA/RIDB.json @@ -0,0 +1,27 @@ +{ + "organization": "USDA", + "name": "RIDB", + "description": "Recreation Information Database", + "tags": [ + "USDA", + "source code", + "recreation" + ], + "contact": { + "email": "source.code@ocio.usda.gov" + }, + "status": "Production", + "vcs": "git", + "downloadURL": "https://github.com/USDA/RIDB/archive/master.zip", + "repositoryURL": "https://github.com/USDA/RIDB", + "homepageURL": "https://usda.github.io/RIDB", + "permissions": { + "licenses": [], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "lastModified": "2018-10-13", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Rancher_Git_Deployment_Sidekick_Service.json b/agency-indexes/DoA/Rancher_Git_Deployment_Sidekick_Service.json new file mode 100644 index 00000000..81cea547 --- /dev/null +++ b/agency-indexes/DoA/Rancher_Git_Deployment_Sidekick_Service.json @@ -0,0 +1,35 @@ +{ + "organization": "OC", + "name": "Rancher Git Deployment Sidekick Service", + "description": "Rancher Git Deployment Sidekick Service", + "repositoryURL": "https://bitbucket.org/usdawcmaas/git-deploy", + "permissions": { + "licenses": [ + { + "URL": "http://www.gnu.org/licenses/old-licenses/gpl-2.0.html", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "laborHours": 200, + "tags": [ + "Rancher", + "DevOps" + ], + "contact": { + "email": "Source.Code@ocio.usda.gov", + "name": "USDA Source Code" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "salt" + ], + "homepageURL": "https://bitbucket.org/usdawcmaas/git-deploy/src/master/", + "date": { + "created": "2017-11-21", + "lastModified": "2017-11-21", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Repeat_Array_Quality_Check__RAQC_.json b/agency-indexes/DoA/Repeat_Array_Quality_Check__RAQC_.json new file mode 100644 index 00000000..39235629 --- /dev/null +++ b/agency-indexes/DoA/Repeat_Array_Quality_Check__RAQC_.json @@ -0,0 +1,40 @@ +{ + "organization": "ARS", + "name": "Repeat Array Quality Check (RAQC)", + "description": "Utility to assess change in 3D image data, such as gridded output from models and remote sensing imagery collected repeatedly over the same spatial domain.", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "snow", + "water", + "model", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/raqc.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/raqc", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/raqc/blob/master/LICENSE", + "name": "GPL3" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2019-08-01", + "lastModified": "2019-11-05", + "metadataLastUpdated": "2020-05-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Snow_and_water_model_analysis_and_visualization__snowav_.json b/agency-indexes/DoA/Snow_and_water_model_analysis_and_visualization__snowav_.json new file mode 100644 index 00000000..5e853669 --- /dev/null +++ b/agency-indexes/DoA/Snow_and_water_model_analysis_and_visualization__snowav_.json @@ -0,0 +1,40 @@ +{ + "organization": "ARS", + "name": "Snow and water model analysis and visualization (snowav)", + "description": "Snow and water model analysis and visualization (snowav) processes the spatial inputs from smrf and spatial outputs from awsm into summary database values, and generates figures and reports for dissemination.", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "snow", + "water", + "model", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/snowav.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/snowav", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/snowav/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2017-12-13", + "lastModified": "2020-04-28", + "metadataLastUpdated": "2020-05-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Spatial_Modeling_for_Resources_Framework__SMRF_.json b/agency-indexes/DoA/Spatial_Modeling_for_Resources_Framework__SMRF_.json new file mode 100644 index 00000000..1a7a2766 --- /dev/null +++ b/agency-indexes/DoA/Spatial_Modeling_for_Resources_Framework__SMRF_.json @@ -0,0 +1,45 @@ +{ + "organization": "ARS", + "name": "Spatial Modeling for Resources Framework (SMRF)", + "description": "Spatial Modeling for Resources Framework (SMRF) was developed by Dr. Scott Havens at the USDA Agricultural Research Service (ARS) in Boise, ID. SMRF was designed to increase the flexibility of taking measured weather data and distributing the point measurements across a watershed. SMRF was developed to be used as an operational or research framework, where ease of use, efficiency, and ability to run in near real time are high priorities.", + "tags": [ + "Northwest Watershed Research Center", + "smrf", + "watershed", + "hydrology", + "modeling", + "interpolation", + "water", + "snow", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python", + "c", + "fortran" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/smrf.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/smrf", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/smrf/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2015-12-28", + "lastModified": "2020-04-30", + "metadataLastUpdated": "2020-05-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/SuperTracker.json b/agency-indexes/DoA/SuperTracker.json new file mode 100644 index 00000000..487c1d90 --- /dev/null +++ b/agency-indexes/DoA/SuperTracker.json @@ -0,0 +1,34 @@ +{ + "organization": "Food and Nutrition Service", + "name": "SuperTracker", + "description": "SuperTracker was an online tool offered by USDA (2011-2018) that helped users track diet, physical activity and weight. SuperTracker provided a personalized plan based on the 2015-2020 Dietary Guidelines for Americans for what you should eat and drink and guided users to making better choices. This dataset includes the SuperTracker source code (latest update April 2018), including: front end application, database schema, documentation, deployment scripts and a ReadMe.txt file that provides high level instructions for the source code. Database connection strings and actual data are not included. The full foods database spreadsheet is attached as well; these foods are based on the Food and Nutrient Database for Dietary Studies (FNDDS), and the Food Patterns Equivalents Database (FPED), both from the USDA/ARS Food Surveys Research Group.\r\n\r\nIt is important to note that the code is based on 2015-2020 Dietary Guidelines for Americans and will not be updated to reflect future guidance. In addition, the food database is based on FNDDS from 2011-2012 (FNDDS 6.0) and FPED from 2011-2012 and will not be updated with future data releases.", + "tags": [ + "Dietary Guidelines", + "Health", + "Nutrition" + ], + "contact": { + "email": "Jackie.Haven@cnpp.usda.gov" + }, + "status": "Archival", + "vcs": "zip", + "downloadURL": "https://inventory.data.gov/dataset/97f9a5cf-61c4-406b-8170-5a6422b68654/resource/c04948d7-4af3-42c7-ae4b-5b805ea7571e/download/supertrackersource2.zip", + "languages": [], + "repositoryURL": "https://inventory.data.gov/dataset/97f9a5cf-61c4-406b-8170-5a6422b68654/resource/c04948d7-4af3-42c7-ae4b-5b805ea7571e/download/supertrackersource2.zip", + "homepageURL": "https://catalog.data.gov/dataset/supertracker-source-code-and-foods-database", + "permissions": { + "licenses": [ + { + "URL": "http://opendefinition.org/licenses/cc-zero/", + "name": "CC0" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "created": "2018-10-12", + "lastModified": "2019-05-02", + "metadataLastUpdated": "2019-09-22" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Tablizer.json b/agency-indexes/DoA/Tablizer.json new file mode 100644 index 00000000..a1918823 --- /dev/null +++ b/agency-indexes/DoA/Tablizer.json @@ -0,0 +1,36 @@ +{ + "organization": "ARS", + "name": "Tablizer", + "description": "Tablizer makes simple statistical summaries of DataFrames and arrays, and places them on SQL or sqlite database.", + "tags": [ + "Northwest Watershed Research Center", + "statistical summaries" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/tablizer.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/tablizer", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/tablizer/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2019-08-20", + "lastModified": "2019-10-08", + "metadataLastUpdated": "2020-05-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/USDA_WCMaaS_Rancher_Provisioner.json b/agency-indexes/DoA/USDA_WCMaaS_Rancher_Provisioner.json new file mode 100644 index 00000000..fd67fb5d --- /dev/null +++ b/agency-indexes/DoA/USDA_WCMaaS_Rancher_Provisioner.json @@ -0,0 +1,36 @@ +{ + "organization": "OC", + "name": "USDA WCMaaS Rancher Provisioner", + "description": "Salt script for provisioning Rancher for Docker containers.", + "repositoryURL": "https://bitbucket.org/usdawcmaas/rancher-salt", + "permissions": { + "licenses": [ + { + "URL": "http://www.gnu.org/licenses/old-licenses/gpl-2.0.html", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "laborHours": 240, + "tags": [ + "Docker", + "Rancher", + "DevOps" + ], + "contact": { + "email": "Source.Code@ocio.usda.gov", + "name": "USDA Source Code" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "salt" + ], + "homepageURL": "https://usdawcmaas.atlassian.net/wiki/display/PLATFORM/Platform", + "date": { + "created": "2016-08-30", + "lastModified": "2018-04-20", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/USDA_WCMaaS_Varnish_Cache.json b/agency-indexes/DoA/USDA_WCMaaS_Varnish_Cache.json new file mode 100644 index 00000000..72f513a3 --- /dev/null +++ b/agency-indexes/DoA/USDA_WCMaaS_Varnish_Cache.json @@ -0,0 +1,36 @@ +{ + "organization": "OC", + "name": "USDA WCMaaS Varnish Cache", + "description": "Containerization of the high performance web content cache", + "repositoryURL": "https://bitbucket.org/usdawcmaas/varnish-cache", + "permissions": { + "licenses": [ + { + "URL": "http://www.gnu.org/licenses/old-licenses/gpl-2.0.html", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "laborHours": 20, + "tags": [ + "Varnish", + "Rancher", + "DevOps" + ], + "contact": { + "email": "Source.Code@ocio.usda.gov", + "name": "USDA Source Code" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "salt" + ], + "homepageURL": "https://bitbucket.org/usdawcmaas/varnish-cache", + "date": { + "created": "2017-01-25", + "lastModified": "2017-10-13", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Weather_Database.json b/agency-indexes/DoA/Weather_Database.json new file mode 100644 index 00000000..2d87d301 --- /dev/null +++ b/agency-indexes/DoA/Weather_Database.json @@ -0,0 +1,44 @@ +{ + "organization": "ARS", + "name": "Weather Database", + "description": "The Weather Database project creates a MySQL database to ingest and manage weather station data from multiple sources. Included in the repository are the schema model and everything needed to generate a weather station database. The wxdb package is able to interact with the database and grab metadata and station data from multiple sources. ", + "tags": [ + "Northwest Watershed Research Center", + "weather-database", + "database", + "docker", + "python", + "snow", + "modeling", + "mesowest" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python", + "PLSQL", + "PLpgSQL" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/weather_database.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/weather_database", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/weather_database/blob/master/LICENSE", + "name": "GPL3.0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2015-12-29", + "lastModified": "2019-06-04", + "metadataLastUpdated": "2020-05-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/Weather_forecast_retrieval.json b/agency-indexes/DoA/Weather_forecast_retrieval.json new file mode 100644 index 00000000..c5a1f88b --- /dev/null +++ b/agency-indexes/DoA/Weather_forecast_retrieval.json @@ -0,0 +1,38 @@ +{ + "organization": "ARS", + "name": "Weather forecast retrieval", + "description": "Weather forecast retrieval gathers relevant gridded weather forecasts to ingest into physically based models for water supply forecasts", + "tags": [ + "Northwest Watershed Research Center", + "weather", + "usg-artificial-intelligence" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python", + "docker" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/weather_forecast_retrieval.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/weather_forecast_retrieval", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/weather_forecast_retrieval/blob/master/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2017-11-15", + "lastModified": "2020-03-27", + "metadataLastUpdated": "2020-05-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/cattleCNV.json b/agency-indexes/DoA/cattleCNV.json new file mode 100644 index 00000000..93a95f5c --- /dev/null +++ b/agency-indexes/DoA/cattleCNV.json @@ -0,0 +1,23 @@ +{ + "organization": "ARS-ARGIL", + "name": "cattleCNV", + "description": "USDA-ARS Animal Genomics and Improvement Laboratory; Cattle Copy Number Variation", + "tags": [], + "contact": { + "email": "source.code@ocio.usda.gov" + }, + "status": "Ideation", + "vcs": "git", + "downloadURL": "https://github.com/USDA-ARS-AGIL/cattleCNV/archive/master.zip", + "repositoryURL": "https://github.com/USDA-ARS-AGIL/cattleCNV", + "homepageURL": "https://github.com/USDA-ARS-AGIL/cattleCNV", + "permissions": { + "licenses": [], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "lastModified": "2015-06-22", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/data-apis.json b/agency-indexes/DoA/data-apis.json new file mode 100644 index 00000000..2a6629bc --- /dev/null +++ b/agency-indexes/DoA/data-apis.json @@ -0,0 +1,30 @@ +{ + "organization": "ERS", + "name": "data-apis", + "description": "The Data API provides programmatic access to select data sets.", + "tags": [], + "contact": { + "email": "source.code@ocio.usda.gov" + }, + "status": "Production", + "vcs": "git", + "downloadURL": "https://github.com/USDA-ERS/data-apis/archive/master.zip", + "languages": [ + "C#", + "jQuery", + "python", + "ruby" + ], + "partners": [], + "repositoryURL": "https://github.com/USDA-ERS/data-apis", + "homepageURL": "http://www.ers.usda.gov/developer/data-apis.aspx", + "permissions": { + "licenses": [], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "lastModified": "2013-12-12", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/data-standards.json b/agency-indexes/DoA/data-standards.json new file mode 100644 index 00000000..aaeb97e8 --- /dev/null +++ b/agency-indexes/DoA/data-standards.json @@ -0,0 +1,33 @@ +{ + "organization": "USDA", + "name": "data-standards", + "description": "A collaborative site for official USDA data elements and data standards.", + "tags": [ + "USDA", + "source code", + "data", + "standards" + ], + "contact": { + "email": "source.code@ocio.usda.gov" + }, + "status": "Production", + "vcs": "git", + "downloadURL": "https://github.com/USDA/data-standards/archive/master.zip", + "repositoryURL": "https://github.com/USDA/data-standards", + "homepageURL": "https://usda.github.io/data-standards", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA/data-standards/blob/gh-pages/LICENSE", + "name": "CC0" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "lastModified": "2016-11-08", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/dependency-intelligence.json b/agency-indexes/DoA/dependency-intelligence.json new file mode 100644 index 00000000..91ceec25 --- /dev/null +++ b/agency-indexes/DoA/dependency-intelligence.json @@ -0,0 +1,28 @@ +{ + "organization": "FSA", + "name": "dependency-intelligence", + "description": "dependency-intelligence", + "languages": [ + "JavaScript", + "Node.js" + ], + "tags": [], + "contact": { + "email": "source.code@ocio.usda.gov" + }, + "status": "Production", + "vcs": "git", + "downloadURL": "https://github.com/USDA-FSA/dependency-intelligence/archive/master.zip", + "repositoryURL": "https://github.com/USDA-FSA/dependency-intelligence", + "homepageURL": "https://github.com/USDA-FSA/dependency-intelligence", + "permissions": { + "licenses": [], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "created": "2016-10-18", + "lastModified": "2016-10-20", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/fsa-design-system.json b/agency-indexes/DoA/fsa-design-system.json new file mode 100644 index 00000000..a4e6b313 --- /dev/null +++ b/agency-indexes/DoA/fsa-design-system.json @@ -0,0 +1,37 @@ +{ + "organization": "FSA", + "name": "fsa-design-system", + "description": "Design System site for USDA Farm Service Agency digital products", + "tags": [], + "contact": { + "email": "source.code@ocio.usda.gov" + }, + "status": "Production", + "vcs": "git", + "downloadURL": "https://github.com/USDA-FSA/fsa-design-system/archive/master.zip", + "repositoryURL": "https://github.com/USDA-FSA/fsa-design-system", + "homepageURL": "http://usda-fsa.github.io/fsa-design-system", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-FSA/fsa-design-system/blob/gh-pages/LICENSE.md", + "name": "CC0" + }, + { + "URL": "http://scripts.sil.org/OFL", + "name": "SIL Open Font License" + }, + { + "URL": "https://github.com/scottjehl/Respond/blob/master/LICENSE-MIT", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "lastModified": "2019-05-01", + "metadataLastUpdated": "2019-06-06" + }, + "disclaimerURL": "https://github.com/USDA-FSA/fsa-design-system/blob/gh-pages/CONTRIBUTING.md" +} \ No newline at end of file diff --git a/agency-indexes/DoA/fsa-style.json b/agency-indexes/DoA/fsa-style.json new file mode 100644 index 00000000..e388cbdd --- /dev/null +++ b/agency-indexes/DoA/fsa-style.json @@ -0,0 +1,30 @@ +{ + "organization": "FPAC", + "name": "fsa-style", + "description": "USDA FPAC's Visual Language and HTML/CSS Framework, as documented by the Design System .", + "tags": [], + "contact": { + "email": "source.code@ocio.usda.gov" + }, + "status": "Production", + "vcs": "git", + "downloadURL": "https://github.com/USDA-FSA/fsa-style/archive/master.zip", + "languages": [], + "partners": [], + "repositoryURL": "https://github.com/USDA-FSA/fsa-style", + "homepageURL": "http://usda-fsa.github.io/fsa-style/", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-FSA/fsa-style/blob/master/LICENSE.md", + "name": "CC0" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "lastModified": "2019-06-06", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/geospatial-apis.json b/agency-indexes/DoA/geospatial-apis.json new file mode 100644 index 00000000..3761bbbb --- /dev/null +++ b/agency-indexes/DoA/geospatial-apis.json @@ -0,0 +1,23 @@ +{ + "organization": "ERS", + "name": "geospatial-apis", + "description": "ERS Geospatial APIs", + "tags": [], + "contact": { + "email": "source.code@ocio.usda.gov" + }, + "status": "Production", + "vcs": "git", + "downloadURL": "https://github.com/USDA-ERS/geospatial-apis/archive/master.zip", + "repositoryURL": "https://github.com/USDA-ERS/geospatial-apis", + "homepageURL": "https://github.com/USDA-ERS/geospatial-apis", + "permissions": { + "licenses": [], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "lastModified": "2013-12-12", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/inicheck.json b/agency-indexes/DoA/inicheck.json new file mode 100644 index 00000000..4ecff663 --- /dev/null +++ b/agency-indexes/DoA/inicheck.json @@ -0,0 +1,36 @@ +{ + "organization": "ARS", + "name": "inicheck", + "description": "inicheck is an advanced configuration file checker/manager enabling developers high end control over their users configuration files. inicheck is specifcially aimed at files that adhere to the .ini format.", + "tags": [ + "Northwest Watershed Research Center", + "ini file" + ], + "contact": { + "email": "source.code@ocio.usda.gov", + "name": "" + }, + "status": "Production", + "vcs": "git", + "languages": [ + "python" + ], + "repositoryURL": "https://github.com/USDA-ARS-NWRC/inicheck.git", + "homepageURL": "https://github.com/USDA-ARS-NWRC/inicheck", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/USDA-ARS-NWRC/inicheck/blob/master/LICENSE", + "name": "GPL 3.0" + } + ], + "usageType": "openSource", + "exemptionText": null + }, + "laborHours": 0, + "date": { + "created": "2018-01-05", + "lastModified": "2020-02-26", + "metadataLastUpdated": "2020-05-03" + } +} \ No newline at end of file diff --git a/agency-indexes/DoA/ksnp.json b/agency-indexes/DoA/ksnp.json new file mode 100644 index 00000000..9829b966 --- /dev/null +++ b/agency-indexes/DoA/ksnp.json @@ -0,0 +1,28 @@ +{ + "organization": "VS", + "name": "ksnp", + "description": "kSNP repository to continue development, provide additional documentation and commenting of source files and collaboration.", + "tags": [], + "contact": { + "email": "source.code@ocio.usda.gov" + }, + "status": "Archival", + "vcs": "git", + "downloadURL": 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--- /dev/null +++ b/agency-indexes/DoA/widgets.json @@ -0,0 +1,26 @@ +{ + "organization": "ERS", + "name": "widgets", + "description": "Source code for widgets using ERS APIs.", + "tags": [], + "contact": { + "email": "source.code@ocio.usda.gov" + }, + "status": "Production", + "vcs": "git", + "downloadURL": "https://github.com/USDA-ERS/widgets/archive/master.zip", + "languages": [ + "javascript" + ], + "repositoryURL": "https://github.com/USDA-ERS/widgets", + "homepageURL": "https://github.com/USDA-ERS/widgets", + "permissions": { + "licenses": [], + "usageType": "openSource" + }, + "laborHours": 0, + "date": { + "lastModified": "2013-11-29", + "metadataLastUpdated": "2019-06-06" + } +} \ No newline at end of file diff --git a/agency-indexes/DoD-index.json b/agency-indexes/DoD-index.json new file mode 100644 index 00000000..2d429feb --- /dev/null +++ b/agency-indexes/DoD-index.json @@ -0,0 +1,1732 @@ +{ + "agency": "DOD", + "version": "2.0.0", + "measurementType": { + "method": 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xAPI", + "permissions": { + "licenses": [ + { + "name": "Apache License 2.0", + "URL": "https://www.apache.org/licenses/LICENSE-2.0.html" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "status": "Production", + "vcs": "git", + "tags": [ + "ADL", + "xAPI", + "Profiles", + "Schema", + "SCORM", + "Conformance" + ], + "contact": { + "name": "ADL Initiative", + "email": "support@adlnet.gov", + "URL": "https://adlnet.gov" + }, + "date": { + "created": "2014-09-08", + "lastModified": "2020-02-21", + "metadataLastUpdated": "2020-11-13" + } +} \ No newline at end of file diff --git a/agency-indexes/DoD/xAPI-Spec.json b/agency-indexes/DoD/xAPI-Spec.json new file mode 100644 index 00000000..91e9c583 --- /dev/null +++ b/agency-indexes/DoD/xAPI-Spec.json @@ -0,0 +1,27 @@ +{ + "name": "xAPI-Spec", + "version": "xAPI-1.0.3", + "organization": "Advanced Distributed Learning Initiative", + "repositoryURL": "https://github.com/adlnet/xAPI-Spec", + "description": "The full experience API (xAPI) specification", + "laborHours": 0, + "status": "Release Candidate", + "vcs": "git", + "tags": [ + "ADL", + "cmi5", + "LMS", + "Content", + "Learning" + ], + "contact": { + "name": "ADL Initiative", + "email": "support@adlnet.gov", + "URL": "https://adlnet.gov" + }, + "date": { + "created": "2012-12-19", + "lastModified": "2020-10-20", + "metadataLastUpdated": "2020-11-13" + } +} \ No newline at end of file diff --git a/agency-indexes/DoD/xAPIWrapper.json b/agency-indexes/DoD/xAPIWrapper.json new file mode 100644 index 00000000..ca0a9d64 --- /dev/null +++ b/agency-indexes/DoD/xAPIWrapper.json @@ -0,0 +1,40 @@ +{ + "name": "xAPIWrapper", + "version": "v1.11.0", + "organization": "Advanced Distributed Learning Initiative", + "repositoryURL": "https://github.com/adlnet/xAPIWrapper", + "description": "A simple library to send and receive xAPI statements", + "permissions": { + "licenses": [ + { + "name": "Apache License 2.0", + "URL": "https://www.apache.org/licenses/LICENSE-2.0.html" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "status": "Production", + "vcs": "git", + "languages": [ + "JavaScript", + "HTML", + "CSS" + ], + "tags": [ + "ADL", + "xAPI", + "JavaScript", + "Wrapper" + ], + "contact": { + "name": "ADL Initiative", + "email": "support@adlnet.gov", + "URL": "https://adlnet.gov" + }, + "date": { + "created": "2013-09-05", + "lastModified": "2020-10-21", + "metadataLastUpdated": "2020-11-13" + } +} \ No newline at end of file diff --git a/agency-indexes/DoD/xapi-authored-profiles.json b/agency-indexes/DoD/xapi-authored-profiles.json new file mode 100644 index 00000000..ec993e62 --- /dev/null +++ b/agency-indexes/DoD/xapi-authored-profiles.json @@ -0,0 +1,35 @@ +{ + "name": "xapi-authored-profiles", + "organization": "Advanced Distributed Learning Initiative", + "repositoryURL": "https://github.com/adlnet/xapi-authored-profiles", + "description": "A collection of raw JSON for all of the xAPI profiles hosted on http://xapi.vocab.pub", + "permissions": { + "licenses": [ + { + "name": "Apache License 2.0", + "URL": "https://www.apache.org/licenses/LICENSE-2.0.html" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "status": "Production", + "vcs": "git", + "tags": [ + "ADL", + "xAPI", + "Profiles", + "Schema", + "Conformance" + ], + "contact": { + "name": "ADL Initiative", + "email": "support@adlnet.gov", + "URL": "https://adlnet.gov" + }, + "date": { + "created": "2017-08-21", + "lastModified": "2020-10-12", + "metadataLastUpdated": "2020-11-13" + } +} \ No newline at end of file diff --git a/agency-indexes/DoD/xapi-jqm.json b/agency-indexes/DoD/xapi-jqm.json new file mode 100644 index 00000000..ce1f5032 --- /dev/null +++ b/agency-indexes/DoD/xapi-jqm.json @@ -0,0 +1,41 @@ +{ + "name": "xapi-jqm", + "version": "v1.1", + "organization": "Advanced Distributed Learning Initiative", + "repositoryURL": "https://github.com/adlnet/xapi-jqm", + "description": "A collection of templates that integrate jQuery Mobile and xAPI so that instructional designers and developers can focus on content and HTML rather than writing javascript code, without limiting their abilities to extend their statements and tracking of interactions", + "permissions": { + "licenses": [ + { + "name": "Apache License 2.0", + "URL": "https://www.apache.org/licenses/LICENSE-2.0.html" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "status": "Archival", + "vcs": "git", + "languages": [ + "JavaScript", + "HTML", + "CSS" + ], + "tags": [ + "xAPI", + "jQuery", + "Mobile", + "ADL", + "Templates" + ], + "contact": { + "name": "ADL Initiative", + "email": "support@adlnet.gov", + "URL": "https://adlnet.gov" + }, + "date": { + "created": "2014-05-02", + "lastModified": "2019-01-16", + "metadataLastUpdated": "2020-11-13" + } +} \ No newline at end of file diff --git a/agency-indexes/DoD/xapi-profiles.json b/agency-indexes/DoD/xapi-profiles.json new file mode 100644 index 00000000..1a26422b --- /dev/null +++ b/agency-indexes/DoD/xapi-profiles.json @@ -0,0 +1,40 @@ +{ + "name": "xapi-profiles", + "version": "v1.0", + "organization": "Advanced Distributed Learning Initiative", + "repositoryURL": "https://github.com/adlnet/xapi-profiles", + "description": "The specification for creating xAPI Profiles (A ruleset for xAPI data in a specific project)", + "permissions": { + "licenses": [ + { + "name": "Apache License 2.0", + "URL": "https://www.apache.org/licenses/LICENSE-2.0.html" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "status": "Production", + "vcs": "git", + "languages": [ + "Python" + ], + "tags": [ + "ADL", + "xAPI", + "Profiles", + "Schema", + "Conformance", + "Spec" + ], + "contact": { + "name": "ADL Initiative", + "email": "support@adlnet.gov", + "URL": "https://adlnet.gov" + }, + "date": { + "created": "2017-03-27", + "lastModified": "2020-09-02", + "metadataLastUpdated": "2020-11-13" + } +} \ No newline at end of file diff --git a/agency-indexes/DoD/xapi-statement-viewer.json b/agency-indexes/DoD/xapi-statement-viewer.json new file mode 100644 index 00000000..cf3a3cff --- /dev/null +++ b/agency-indexes/DoD/xapi-statement-viewer.json @@ -0,0 +1,39 @@ +{ + "name": "xapi-statement-viewer", + "organization": "Advanced Distributed Learning Initiative", + "repositoryURL": "https://github.com/adlnet/xapi-statement-viewer", + "description": "Simple UI that allows users to view the statements stored in an LRS. A live online version is available.", + "permissions": { + "licenses": [ + { + "name": "MIT License", + "URL": "http://www.opensource.org/licenses/MIT" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "status": "Archival", + "vcs": "git", + "languages": [ + "JavaScript", + "HTML", + "CSS" + ], + "tags": [ + "xAPI", + "Viewer", + "ADL", + "Statements" + ], + "contact": { + "name": "ADL Initiative", + "email": "support@adlnet.gov", + "URL": "https://adlnet.gov" + }, + "date": { + "created": "2015-02-12", + "lastModified": "2020-09-22", + "metadataLastUpdated": "2020-11-13" + } +} \ No newline at end of file diff --git a/agency-indexes/DoD/xapi-youtube.json b/agency-indexes/DoD/xapi-youtube.json new file mode 100644 index 00000000..e2dc9f19 --- /dev/null +++ b/agency-indexes/DoD/xapi-youtube.json @@ -0,0 +1,40 @@ +{ + "name": "xapi-youtube", + "version": "v1.0", + "organization": "Advanced Distributed Learning Initiative", + "repositoryURL": "https://github.com/adlnet/xapi-youtube", + "description": "A toolset that allows developers to embed YouTube videos, and track interactions with these embedded videos with xAPI statements", + "permissions": { + "licenses": [ + { + "name": "Apache License 2.0", + "URL": "https://www.apache.org/licenses/LICENSE-2.0.html" + } + ], + "usageType": "openSource" + }, + "laborHours": 0, + "status": "Archival", + "vcs": "git", + "languages": [ + "JavaScript", + "HTML" + ], + "tags": [ + "xAPI", + "YouTube", + "Video", + "ADL", + "Example" + ], + "contact": { + "name": "ADL Initiative", + "email": "support@adlnet.gov", + "URL": "https://adlnet.gov" + }, + "date": { + "created": "2015-04-14", + "lastModified": "2020-07-23", + "metadataLastUpdated": "2020-11-13" + } +} \ No newline at end of file diff --git a/agency-indexes/DoE-index.json b/agency-indexes/DoE-index.json new file mode 100644 index 00000000..38fa48d6 --- /dev/null +++ b/agency-indexes/DoE-index.json @@ -0,0 +1,187248 @@ +{ + "agency": "DOE", + "measurementType": { + "ifOther": "", + "method": "other" + }, + "releases": [ + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-16" + }, + "description": "Teuchos is designed to provide portable, object-oriented tools for Trillnos developers and users. This includes templated wrappers to BLAS/LAPACK, a serial dense matrix class, a parameter list, XML parsing utilities, reference counted pointer (smart pointer) utilities, and more. These tools are designed to run on both serial and parallel computers.", + "laborHours": 8344830.4, + "languages": [], + "name": "Teuchos Utility Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "Amesos is the Direct Sparse Solver Package in Trilinos. The goal of Amesos is to make AX=S as easy as it sounds, at least for direct methods. Amesos provides interfaces to a number of third party sparse direct solvers, including SuperLU, SuperLU MPI, DSCPACK, UMFPACK and KLU. Amesos provides a common object oriented interface to the best sparse direct solvers in the world. A sparse direct solver solves for x in Ax = b. where A is a matrix and x and b are vectors (or multi-vectors). A sparse direct solver flrst factors A into trinagular matrices L and U such that A = LU via gaussian elimination and then solves LU x = b. Switching amongst solvers in Amesos roquires a change to a single parameter. Yet, no solver needs to be linked it, unless it is used. All conversions between the matrices provided by the user and the format required by the underlying solver is performed by Amesos. As new sparse direct solvers are created, they will be incorporated into Amesos, allowing the user to simpty link with the new solver, change a single parameter in the calling sequence, and use the new solver. Amesos allows users to specify whether the matrix has changed. Amesos can be used anywhere that any sparse direct solver is needed.", + "laborHours": 8344830.4, + "languages": [], + "name": "Amesos Solver Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The MRSH project is a collection of the following programs: MRSH, MRCP, MRLOGIN, MRSHD, MRLOGIND. These programs are modifications of the programs RSH, RCP, RLOGIN, RSHD, and RLOGIND. They have been modified to provide authentication via munge, an intra-cluster authentication service. Henceforth, \"MRSH\" implies the collective set of programs MRSH, MRCP, MRLOGIN, MRSHD, and MRLOGIND. Similarly RSH will refer to its collective set of programs.", + "laborHours": 24213.6, + "name": "MRSH Version V2.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/mrsh", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Lustre Administrative Tools (LAT) is a set of programs and utilities designed to facilitate management of the Lustre File System by System Administrators.", + "laborHours": 5639.2, + "name": "Lustre Administrative Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cea-hpc/shine", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "WHATSUP determines which nodes in a cluster are up and which nodes are down.", + "laborHours": 58793.6, + "name": "WHATSUP Version1.3", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/whatsup", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Nux is an open-source Java XML toolset geared towards embed:,ed use in high-throughput XML messaging middleware such as large- scale Peer-to-Peer infrastructures, message queues, publish- subscribe and matchmaking systems for Blogs/newsfeeds, text chat, data acquisition and distribution systems, application level routers firewalls, classifiers, etc. It is not an XML database, and does not attempt to be one. Features include: archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Seamless W3C XQuery and XPath support for XOM. archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Full-text search (fuzzy similarity queries) for on-the-fly matchmaking in realtime streaming applications combining structured and unstructured queries. archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Efficient and flexible pools and factories for documents, XQueries, XSL Transforms, as well as document Builders that validate against various schema languages, including W3C XML Schemas, DTDs, RELAX NG, Schematron, etc. archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Optional serialization and deserialization of XOM XML documents to and from an efficient and compact custom binary XML data format (bnux format), without loss or change of any information.", + "laborHours": 997621.6, + "name": "Nux, V.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/er1c/nux/blob/master/doc/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/er1c/nux", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "An MPI-based test for benchmarking parallel I/O beowulf-style clusters.", + "laborHours": 2416.8, + "name": "MIB, the MPI I/O Benchmark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mib", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-12" + }, + "description": "The Galeri package defines a collection of serial and distributed linear algebra objects to be used for software verification and validation. Galeri is used in several of the examples of the Amesos, IFPACK and ML packages, and in the Trilinos tutorial, Didasko. Galeri can be used for the generation of linear system with known propeties and data distribution for convergence analysis of interative solvers of Krylov type and domain decomposition and multigrid preconditioners.", + "laborHours": 8344830.4, + "languages": [], + "name": "Galeri Matrix Generation Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Moertel supplies capabilities for nonconforming mesh tying and contact formulations in 2 and 3 dimensions using Mortar methods. Motar methods are a type of Lagrange Multiplier constraints that can be used in contact formulations and in non-conforming or conforming mesh typing as well as in domain decomposition techniques. Suitable conditions at interfaces are formulated as weak continuity conditions in dual variables introducing Lagrange multiplers on the interface. By an appropriate choice of the function space of the Lagrange multipliers on an interface it is possible to locally condense Lagrange multipliers such that a sparse and definite system of equations can be formed which is equalivalent to the saddle point system resulting from the Lagrange multiplier formulation.", + "laborHours": 16020.8, + "languages": [ + "C++" + ], + "name": "Moertel Fe Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Moertel", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "WebTrilinos is a scientific portal, a web-based environment to use several Trilinos packages through the web. If you are a teaching sparse linear algebra, you can use WebTrilinos to present code snippets and simple scripts, and let the students execute them from their browsers. If you want to test linear algebra solvers, you can use the MatrixPortal module, and you just have to select problems and options, then plot the results in nice graphs.", + "laborHours": 2705.6, + "languages": [], + "name": "Trilinos Web Interface Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/WebTrilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Stratimikos is a small package of C++ wrappers for linear solver and preconditioning functionality exposed through Thyra interfaces. This package makes is possible to aggregate all of the general linear solver capability from the packages Amesos, AztecOO, Belos, lfpack, ML and others into a simple to use, parameter-list driven, interface to linear solvers. This initial version of Stratimikos contains just one utility class for building linear solvrs and preconditioners out of Epetra-based linear operators.", + "laborHours": 8344830.4, + "name": "Stratimikos Wrapper Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Aprepro is an algebraic preprocessor that reads a file containing both general text and algebraic, string, or conditional expressions. It interprets the expressions and outputs them to the output file along with the general text. Aprepro contains several mathematical functions, string functions, and flow control constructs. In addition, functions are included that, with some additional files, implement a units conversion system and a material database lookup system.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "Aprepro - Algebraic Preprocessor", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MRNet is a software tree-based overlay network developed at the University of Wisconsin, Madison that provides a scalable communication mechanism for parallel tools. MRNet, uses a tree topology of networked processes between a user tool and distributed tool daemons. This tree topology allows scalable multicast communication from the tool to the daemons. The internal nodes of the tree can be used to distribute computation and alalysis on data sent from the tool daemons to the tool. This release covers minor implementation to port this software to the BlueGene/L architecuture and for use with a new implementation of the Dynamic Probe Class Library.", + "laborHours": 68460.8, + "name": "Multicast Reduction Network Source Code", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dyninst/mrnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "Tramonto is a code for performing molecular theory calculations using a matrix-based Newton's method approach for 1D, 2D, and 3D geometries. More specifically the code solves the integral equations of a particular class of liquid state theory namely density functional theories (DFT) of inhomogeneous fluids in order to predict the structure and thermodynamic properties of fluids near surfaces, in porous media, or near macromolecules. It can also be used to study self-assembling systems such as lamellae forming diblock copolymers or lipid bilayers. The types of fluids currently treated by the code include atomistic fluids (hard spheres, Lennard-Jones, ions, etc), freely-jointed polymers, and small molecules with bond constraints. The system of equations solved by this code are integral equations of finite range. They lead to sparse matrices for large physical systems, but rather dense matrices when the physical systems are small. The systems of equations are solved using a real space matrix based Newton's method. Standard freely available parallel iterative solvers many be used to solve the problem (see Aztecoo from Sandia's Trilinos project). Alternatively, specialized Schur complement based solvers developed for more efficient solution of these semi-dense matrices may be used.", + "laborHours": 46876.8, + "languages": [ + "C++", + "C", + "CMake", + "Python" + ], + "name": "Tramonto", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tramonto", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Aristos is a Trilinos package for nonlinear continuous optimization, based on full-space sequential quadratic programming (SQP) methods. Aristos is specifically designed for the solution of large-scale constrained optimization problems in which the linearized constraint equations require iterative (i.e. inexact) linear solver techniques. Aristos' unique feature is an efficient handling of inexactness in linear system solves. Aristos currently supports the solution of equality-constrained convex and nonconvex optimization problems. It has been used successfully in the area of PDE-constrained optimization, for the solution of nonlinear optimal control, optimal design, and inverse problems.", + "laborHours": 8344830.4, + "name": "Aristos Optimization Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Sacado is an automatic differentiation package for C++ codes using operator overloading and C++ templating. Sacado provide forward, reverse, and Taylor polynomial automatic differentiation classes and utilities for incorporating these classes into C++ codes. Users can compute derivatives of computations arising in engineering and scientific applications, including nonlinear equation solving, time integration, sensitivity analysis, stability analysis, optimization and uncertainity quantification.", + "laborHours": 8344830.4, + "name": "Automatic Differentiation Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "HPCCG is a simple PDE application and preconditioned conjugate gradient solver that solves a linear system on a beam-shaped domain. Although it does not address many performance issues present in real engineering applications, such as load imbalance and preconditioner scalability, it can serve as a first \"sanity test\" of new processor design choices, inter-connect network design choices and the scalability of a new computer system. Because it is self-contained, easy to compile and easily scaled to 100s or 1000s of porcessors, it can be an attractive study code for computer system designers.", + "laborHours": 775.2, + "languages": [ + "C++", + "Makefile" + ], + "name": "HPCCG Solver Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HPCCG", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MRNet is a software tree-based overlay network developed at the University of Wisconsin, Madison that provides a scalable communication mechanism for parallel tools. MRNet uses a tree topology of networked processes between a user tool and distributed tool daemons. This tree topology allows scalable multicast communication from the tool to the daemons. The internal nodes of the tree can be used to distribute computation and analysis on data sent from the tool daemons to the tool. This release covers modifications that we have made to the Wisconsin implementation to port this software to the BlueGene/L architecture. It also covers some additional files that were created for this port.", + "laborHours": 68460.8, + "name": "BlueGene/L Specific Modification to MRNet: Multicast/Reduction Network", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dyninst/mrnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GraphLib is a support library used by other tools to create, manipulate, store, and export graphs. It provides a simple interface to specifS' arbitrary directed and undirected graphs by adding nodes and edges. Each node and edge can be associated with a set of attributes describing size, color, and shape. Once created, graphs can be manipulated using a set of graph analysis algorithms, including merge, prune, and path coloring operations. GraphLib also has the ability to export graphs into various open formats such as DOT and GML.", + "laborHours": 2340.8, + "name": "Graph Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/graphlib", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The numa-maps program displays information about how memory for processes is laid out on a NUMA (Non-Uniform Memory Architecture) system running Linux.", + "laborHours": 106.4, + "name": "numa-maps", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/grondo/numa-maps", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The package provides additional IB programs and scripts which are usefull in some way or another to the management of IB clusters.", + "laborHours": 18635.2, + "name": "Pragmatic-infiniband-utilities", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/weiny2/pragmatic-infiniband-utilities", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "Mapvar is designed to transfer solution results from one finite element mesh to another. Mapvar draws heavily from the structure and coding of MERLIN II, but it employs a new finite element data base. Exodus II, and offers enhanced speed and new capabilities not available in MERLIN II.", + "laborHours": 692284.0, + "languages": [ + "Fortran" + ], + "name": "MAPVAR V1.9", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Parallel Heterogeneous Dynamic unstructured Mesh (phdMesh) data structure library and integration testing code that performs dynamic load balancing of the data structure and parallel geometric proximity search on a contrived test problem. The phdMesh library is intended to be module within a finite element or finite volume library or code. The integration testing code is intended to provide a compact and highly portable performance evaluation code for parallel computing systems.", + "laborHours": 8344830.4, + "name": "phdMesh", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "Txtexo will convert a file in the structured text output format created by exotxt back to an exodusII database file. The text file must conform to the format written by the exotxt program but it can be modified as long as the data are consistent. Txtexo is used to convert the structured text file created by the exotxt code to a binary exodusII database.", + "laborHours": 692284.0, + "languages": [], + "name": "Txtexov.1.9", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.9" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-18" + }, + "description": "Exotxt is an analysis code that reads finite element results data stored in an exodusII file and generates a file in a structured text format. The text file can be edited or modified via a number of text formatting tools. Exotxt is used by analysis to translate data from the binary exodusII format into a structured text format which can then be edited or modified and then either translated back to exodusII format or to another format.", + "laborHours": 692284.0, + "languages": [], + "name": "Finite Element Analysis Code - Exotxt", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The ALGEBRA program allows the user to manipulate data from a finite element analysis before it is plotted. The finite element output data is in the form of variable values (e.g., stress, strain, and velocity components) in an EXODUS II database. The ALGEBRA program evaluates user-supplied functions of the data and writes the results to an output EXODUS II database that can be read by plot programs.", + "homepageURL": "https://github.com/sandialabs/seacas", + "laborHours": 693758.4, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "ALGEBRA v.1.27", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.27" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-11" + }, + "description": "Exodiff compares the results data from two Exodus II files. By defult, a relative difference is used with a tolerance of 1.-6 (about 6 significant digits). The nodal locations are also compared using an absolute difference with a tolerance of 1.e-6. Time step values are compared using a relative difference with a tolerance of 1.e-6 and a floor of 1.e-15. If a third file [diffile.exo] is given, then it is overwritten with the difference of the two files.", + "laborHours": 692284.0, + "languages": [], + "name": "Exodiff v. 2.09", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "EPU recombines multiple results exodus II database files into a single exodus II database. The multiple databases are the results of parallel finite element analysis runs where each processor writes its own portion of the solution to a single file. EPU will then put the pieces back together in the correct order. It allows sub-setting of the data to reduce the size of the final database.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "EPU v.3.0.08", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0.08" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PDLAMMPS is an add-on module to Sandia's LAMMPS molecular dynamics package that implements a simplified peridynamic model.", + "laborHours": 1281025.6, + "name": "PDLAMMPS 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lammps/lammps", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-01" + }, + "description": "The Kitten Lightweight Kernel is a simplified OS (operating system) kernel that is intended to manage a compute node's hardware resources. It provides a set of mechanisms to user-level applications for utilizing hardware resources (e.g., allocating memory, creating processes, accessing the network). Kitten is much simpler than general-purpose OS kernels, such as Linux or Windows, but includes all of the esssential functionality needed to support HPC (high-performance computing) MPI, PGAS and OpenMP applications. Kitten provides unique capabilities such as physically contiguous application memory, transparent large page support, and noise-free tick-less operation, which enable HPC applications to obtain greater efficiency and scalability than with general purpose OS kernels.", + "laborHours": 409913.6, + "languages": [], + "name": "KITTEN Lightweight Kernel 0.1 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HobbesOSR/kitten", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "BOUT is a parallelized 3D nonlocal electromagnetic turbulence code. The principal calculations are the boundary plasma turbulence in a realistic magnetic geometry. BOUT uses fluid Braginskii equations for plasma vorticity, density, electron and ion temperature and Parallel mementum. With sources added in the core-edge region and sinks in the scrape-off-layer (SOL), BOUT follows the self-consistent profile evolution together with turbulence. BOUT also includes coupling to a magnetohyfrodynamic equlibrium (EFIT package) and a two-dimensional hydrodynamic edge transport model (UEDGE package).", + "laborHours": 3298.4, + "name": "BOUndary Plasma Turbulence", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/boutproject/hermes", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-06-04" + }, + "description": "ZFS is a file system written for the Solaris operating system and released under the open source CDDL license. ZFS on Linux is ZFS modified to run on Linux, utilizing the Solaris Porting Layer (SPL).", + "laborHours": 310733.6, + "languages": [], + "name": "ZFS on Linux", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/zfsonlinux/zfs/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zfsonlinux/zfs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PnMPI is a tool infrastructure for parallel programs implemented using the message passing interface (MPI). It enables users to dynamically assemble multiple tools, both existing and newly developed ones, into a single tool chain and to execute them concurrently. This provides new options for scalable tools designs including (but not concurrently. This provides new options for scalable tool designs including (but not limited to) the transparent virtualization of MPI environments of an application. In addition, PnMPI allows tools to export support routines to other tools. This promotes a separation of tasks between tools which leads to enhanced tool modularity. PnMPI has been implemented for a variety of platforms including Linux and AIX clusters, and a static version of PnMPI is available on Blue Gene/L.", + "laborHours": 8451.2, + "name": "PnMPI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/pnmpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SLURM is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small computer clusters. As a cluster resource manager, SLURM has three key functions. First, it allocates exclusive and/or non-exclusive access to resources (compute nodes) to users for some duration of time so they can perform work. Second, it provides a framework for starting, executing, and monitoring work 9normally a parallel job) on the set of allocated nodes. Finally, it arbitrates conflicting requests for resources by managing a queue of pending work.", + "laborHours": 405900.8, + "name": "Simple Linux Utility for Resource Management", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/schedmd/slurm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-07-13" + }, + "description": "IDAS is a general purpose (serial and parallel) solver for differential equation (ODE) systems with senstivity analysis capabilities. It provides both forward and adjoint sensitivity analysis options.", + "laborHours": 213088.8, + "languages": [], + "name": "Stiff DAE integrator with sensitivity analysis capabilities", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "EPICS is a set of software tools and applications developed initially by the Los Alamos National Laboratories for the control of large accelerators, enhanced by contributions from users worldwide and continuing development for application to other large scientific experimental equipment, such as telescopes and detectors. EPICS consists of EPICS BASE, Extensions, and other unbundled modules. EPICS BASE marks a change in the handling of the distribution of the software starting with the EPICS BASE 3.13.7 AND 3.140beta2 software.", + "laborHours": 138928.0, + "name": "Experimental Physics and Industrial Control System BASE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/epics-base/epics-base/blob/3.16/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/epics-base/epics-base", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The TOX (Tomcat Oracle & XML) web archive is a foundation for development of HTTP-based applications using Tomcat (or some other servlet container) and an Oracle RDBMS. Use of TOX requires coding primarily in PL/SQL, JavaScript, and XSLT, but also in HTML, CSS and potentially Java. Coded in Java and PL/SQL itself, TOX provides the foundation for more complex applications to be built.", + "laborHours": 714.4, + "name": "Tomcat, Oracle & XML Web Archive", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/tox", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software comprises two algorithms designed to perform a 2D layout of a graph structure in time linear with respect to the vertices and edges in the graph, whereas most other layout algorithms have a running time that is quadratic with respect to the number of vertices or greater. Although these layout algorithms run in a fraction of the time as their competitors, they provide competitive results when applied to most real-world graphs. These algorithms also have a low constant running time and small memory footprint, making them useful for small to large graphs.", + "laborHours": 3149576.8, + "name": "Two linear time, low overhead algorithms for graph layout", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Thread Pool Interface (TpI) provides a simple interface for running functions written in C or C++ in a thread-parallel mode. Application or library codes may need to perform operations thread-parallel on machines with multicore processors. the TPI library provides a simple mechanism for managing thread activation, deactivation, and thread-parallel execution of application-provided subprograms.", + "laborHours": 8344830.4, + "name": "Thread Pool Interface (TPI)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "RECONCILE is a noun phrase conference resolution system: it identifies noun phrases in a text document and determines which subsets refer to each real world entity referenced in the text. The heart of the system is a combination of supervised and unsupervised machine learning systems. It uses a machine learning algorithm (chosen from an extensive suite, including Weka) for training noun phrase coreference classifier models and implements a variety of clustering algorithms to coordinate the pairwise classifications. A number of features have been implemented, including all of the features employed in Ng & Cardie [2002].", + "laborHours": 144856.0, + "name": "RECONCILE: a machine-learning coreference resolution system", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/davidbuttler/reconcile", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A power system simulation that runs on all major platforms, provides open access to all functionality, and supports extended modeling of non-traditional components of the electric power system, such as buildings, distributed resources, and markets.", + "laborHours": 252776.0, + "name": "GridLab-D", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/gridlab-d/gridlab-d/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gridlab-d/gridlab-d", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The open-source PBCdlComm software is designed for data acquisition from PakBus-protocol based Campbell Data loggers by the Scientific Data Management team at Pacific Northwest National Laboratory (www.pnl.gov). This effort was funded by US Department of Energy's Atmospheric Radiation Measurement program (www.arm.gov). As an alternative for Campbell Scientific's Loggernet software, this is ideal for deploying with rugged field PCs that have limited processing resources and do not require a full-blown GUI module. The software is designed so that it can be extended to implement a new data storage mechanism, a customized post-processing module and/or integrated with web-services for sophisticated monitoring or reporting.", + "laborHours": 2553.6, + "name": "PbCdlComm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sutanay/PbCdlComm/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sutanay/PbCdlComm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "LaunchMON is a tool infrastructure that allows a HPC tool to deploy tool daemons into the right remote nodes. It makes use of a target resource manager (RM)'s Automatic Process Acquisition Interface (APAI) to identify the remote nodes and processes of a parallel program, and also exploits the same RM's efficient MPI job launching capability on co-locating daemons with the job. To support a wide range of HPC tools that are inherently distributed software, LaunchMON provides the tool with distributed application programming interface sets: the front end (FE) API, the back end (BE) API and the middleware (MW) API. They each support a tool's front end, back end daemons and middleware communication daemons, respectively. Using those API sets, the tool can launch and initialize their remote daemons scalably.", + "laborHours": 17449.6, + "name": "LaunchMON: An Infrastructue for Large Scale Tool Daemon Launching", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/launchmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "SUPES is a collection of subprograms that perform frequently used non-numerical services for the engineering applications programmer. The three functional categories of SUPES are: (1) input command parsing, (2) dynamic memory management, and (3) system dependent utilities. The subprograms in categories one and two are written in standard FORTRAN-77, while the subprograms in category three are written provide a standardized FORTRAN interface to several system dependent features.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "SUPESv.4.1.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "4.1.2" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The qthread library provides a software mechanism for programs to execute a large number of run-to-completion threads at low cost. It provides the ability to perform lightweight synchronization on memory locations. Finally, modules within the library (\"futurelib\", \"qloop\", and \"qutil\") provide the optional ability to manage the number of threads created in C and C++ by providing parallel loop constructs.", + "laborHours": 47393.6, + "languages": [ + "C++", + "C", + "HMTL", + "Makefile", + "Assembly", + "M4" + ], + "name": "Qthreads", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/qthreads?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/qthreads", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-03-20" + }, + "description": "MAPVAR-KD is designed to transfer solution results from one finite element mesh to another. MAPVAR-KD draws heavily from the structure and coding of MERLIN II, but it employs a new finite element data base, EXODUS II, and offers enhanced speed and new capabilities not available in MERLIN II. In keeping with the MERLIN II documentation, the computational algorithms used in MAPVAR-KD are described. User instructions are presented. Example problems are included to demonstrate the operation of the code and the effects of various input options. MAPVAR-KD is a modification of MAPVAR in which the search algorithm was replaced by a kd-tree-based search for better performance on large problems.", + "laborHours": 2002235.2, + "languages": [], + "name": "Finite Element Analysis Code - MAPVAR-KD", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gsjaardema/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-03-20" + }, + "description": "CONEX is a code for joining sequentially in time multiple exodusll database files which all represent the same base mesh topology and geometry. It is used to create a single results or restart file from multiple results or restart files which typically arise as the result of multiple restarted analyses. CONEX is used to postprocess the results from a series of finite element analyses. It can join sequentially the data from multiple results databases into a single database which makes it easier to postprocess the results data.", + "laborHours": 2002235.2, + "languages": [], + "name": "Finite Element Analysis Code - CONEX", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gsjaardema/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-15" + }, + "description": "GJOIN is a two- or three-dimensional mesh combination program. GJOIN combines two or more meshes written in the GENESIS mesh database format into a single GENESIS mesh. Selected nodes in the two meshes that are closer than a specified distance can be combined. The geometry of the mesh databases can be modified by scaling, offsetting, revolving, nd mirroring. The combined meshes can be further modified by deleting, renaming, or combining material blocks, sideset identifications, or nodeset identifications.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "GJOIN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Phalanx is a software library to provide flexible dependency management for complex nonlinear partial differential equation operators. It breaks a complex set of equations into a manageable set of fields and evaluation routines. Users can flexibly swap evaluators to change the underlying dependency graph of the fields automatically. By constructing the dependency list, sensitivities can be calculated either analytically or by using embedded automatic differentiation software.", + "laborHours": 8344830.4, + "name": "Phalanx V1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/phalanx/copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "BECCA is a learning and control method based on the function of the human brain. The goal behind its creation is to learn to control robots in unfamiliar environments in a way that is very robust, similar to the way that an infant learns to interact with her environment by trial and error. As of this release, this software contains two simulations of BECCA controlling robots: one is a one degree-of-freedom spinner robot and the other is a 7 degree-of-freedom serial link arm with a terminal gripper. In addition, the software contains code that identifies synonyms in a untagged corpus of ASCII words. This last is a demonstration of BECCA's ability to generate abstract concepts from concrete experience. The BECCA simulation is coded so as to make it extensible to new applications. It is modular, object-oriented code in which the portions of the code that are specific to one simulation are easily separable from those portions that are the constant between implementations. BECCA makes very few assumptions about the robot and environment it is learning, and so is applicable to a wide range of learning and control problems.", + "laborHours": 927.2, + "languages": [ + "Python" + ], + "name": "Brain-Emulating Cognition and Control Architecture (BECCA) V1.0 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/becca", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ParFlow is a parallel, variabley saturated groundwater flow code that is especially suitable for large scale problem. ParFlow simulates the three-dimensional saturated and variably saturated subsurface flow in heterogeneous porous media in three spatial dimensions. ParFlow's developemt and appkication has been on-ging for more than 10 uear. ParFlow has recently been extended to coupled surface-subsurface flow to enabel the simulation of hillslope runoff and channel routing in a truly integrated fashion. ParFlow simulates the three-dimensional varably saturated subsurface flow in strongly heterogeneous porous media in three spatial dimension.", + "laborHours": 138532.8, + "name": "Simulation of water flow in terrestrial systems", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/parflow/parflow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SLURM is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small computer clusters. As a cluster resource manager, SLURM has three key functions. First, it allocates exclusive and/or non exclusive access to resources (compute nodes) to users for some duration of time so they can perform work. Second, it provides a framework for starting, executing, and monitoring work (normally a parallel job) on the set of allciated nodes. Finally, it arbitrates conflicting requests for resouces by managing a queue of pending work.", + "laborHours": 405900.8, + "name": "Simple Linux Utility for Resource Management", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/schedmd/slurm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "The Scalable Checkpoint/Restart (SCR) library provides an interface that codes may use to worite our and read in application-level checkpoints in a scalable fashion. In the current implementation, checkpoint files are cached in local storage (hard disk or RAM disk) on the compute nodes. This technique provides scalable aggregate bandwidth and uses storage resources that are fully dedicated to the job. This approach addresses the two common drawbacks of checkpointing a large-scale application to a shared parallel file system, namely, limited bandwidth and file system contention. In fact, on current platforms, SCR scales linearly with the number of compute nodes. It has been benchmarked as high as 720GB/s on 1094 nodes of Atlas, which is nearly two orders of magnitude faster thanthe parallel file system.", + "laborHours": 24198.4, + "languages": [], + "name": "The Scalable Checkpoint/Restart Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/scr/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/scr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The PMGR_COLLECTIVE library provides an interface that MPI implemenataions may call to initialize ranks in a scalable way. It was developed to reduce the startup time MPI appkications, however, other tools such as debugger infrastructures have also found use cases for it. When first developed, it reduced the startup time from 15 minutes to 10 seconds on as 8192-node cluster.", + "laborHours": 3283.2, + "name": "The Process Manager Collective Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/pmgr_collective/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pmgr_collective", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A power system simulation that runs on all major platforms, provides open access to all functionality, and supports extended modeling of non-traditional components of the electric power system, such as buildings, distributed resources, and markets. GridLAB-D solution engine can determine the simultaneous state of millions of independent devices, each of which is described by multiple differential equations solved only locally for both state and time. The advantages of this algorithm over traditional finite difference-based simulators are: (1) it is much more accurate; (2) it can handle widely disparate time scales, ranging from sub-seconds to many years; and 3) it is easy to integrate with new modules and third-party systems. The advantage over traditional differential-based solvers is that it is not necessary to integrate all the device's behaviors into a single set of equations that must be solved.", + "laborHours": 252776.0, + "name": "GridLab-D version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/gridlab-d/gridlab-d/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gridlab-d/gridlab-d", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A package of classes for constructing and using distributed sparse and dense matries, vectors and graphs. Templated o the scalar and ordinal types so that any valid floating-point type, as well as any valid integer type can be used with these classes. Other non-standard types, such as 3-by-3 matrices for the scalar type and mod-based integers for ordinal can also be used.", + "laborHours": 8344830.4, + "name": "Tpetra Next-Generation Templated Petra V1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/tpetra/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "ex1ex2v2 is a translator program which will convert a database in exodus1 format to exodusII format. The exodus 1 format is a defined series of Fortran unformatted writes/reads; the exodusII format is defined by the ExodusII API.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "ex1ex2v2 Version 2.10", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.10" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Nem_spread reads it's input command file (default name nem_spread.inp), takes the named ExodusII geometry definition and spreads out the geometry (and optionally results) contained in that file out to a parallel disk system. The decomposition is taken from a scalar Nemesis load balance file generated by the companion utility nem_slice.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "nem_spread Ver. 5.10", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "5.10" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Nem_slice reads in a finite element model description of the geometry of a problem from an ExodusII file and generates either a nodal or elemental graph of the problem. It then calls Chaco to load balance the graph and then outputs a NemesisI load-balance file.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "nem_slice ver. 3.34", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.34" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "BLOT is a graphic program for post-processing finite element analyses output in the EXODUS II database format. It is command driven with free-format input and can drive graphics devices supported by the Sandia Virtual Device Interface. BLOT produces mesh plots of the analysis output variables including deformed mesh plots, line contours, filled (painted) contours, vector plots of two/three variables (velocity vectors), and symbol plots of scalar variables (discrete cracks). Features include pathlines of analysis variables drawn on the mesh, element selection by material, element birth and death, multiple views combining several displays on each plot, symmetry mirroring, and node and element numbering. X-Y plots of the analysis variables include time vs. variable plots or variable vs. variable plots, and distance vs. variable plots at selected time steps where distance is the accumulated distance between pairs of nodes or element centers. BLOT is written in as portable a form as possible. Fortran code is written in ANSI Standard FORTRAN-77. Machine-specific routines are limited in number and are grouped together to minimize the time required to adapt them to a new system. SEACAS codes have been ported to several Unix systems", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "BLOT Ver. 1.65", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.65" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "SVDI is the Sandia Virtual Device Interface library which is an internal library used by SEAMS codes (blot and fastq) to provide graphics to multiple device types; primarily X11R6 clients.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "SVDI Ver. 1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The software is a set of technologies developed by the SciDAC Institute for Ultrascale Visualization in order to address the visualization needs for petascale computing and beyond. These technologies include improved I/O performance, simulation co-processing, advanced rendering capabilities, and specialized visualization techniques developed for SciDAC applications.", + "laborHours": 82095.2, + "languages": [ + "C++", + "C" + ], + "name": "Ultrascale visualization capabilities for the ParaView/VTK framework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/paraview/catalyst", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Simple parallel MD code that serves as a microapplication in the Mantevo suite. Study of computer system design and implementation, benchmarking of new and existing computer systems.", + "laborHours": 11096.0, + "languages": [ + "C++", + "Shell", + "C", + "Makefile" + ], + "name": "miniMD v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniMD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GROPE is a program that examines the input to a finite element analysis (which is in the GENESIS database format) or the output from an analysis (in the EXODUS database format). GROPE allows the user to examine any value in the database. The display can be directed to the user's terminal or to a print file.", + "laborHours": 3063438.4, + "languages": [ + "CSS", + "HTML", + "TeX", + "Makefile", + "JavaScript", + "PostScript" + ], + "name": "Grope Ver. 1.38", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas-docs", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.38" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pamgen creates, in parallel, hexahedral or quadrilateral (in 2D) finite element meshes of cubes, cylinders, and portions of cylinders. For some analysis applications it can obviate the normally serial analysis preparation steps of mesh generation and decomposition. Bypassing these serial steps allows construction of large element count (over a billion) meshes. When linked to an application as a library, it allows each process of a parallel simulation to generate its own finite element domain representation at execution time. As a stand-alone application it can produce the representation of the mesh for processor n of k possible processors. The Pamgen library and application are serial as the mesh generation proceeds without reliance on inter-processor communication.", + "laborHours": 8344830.4, + "name": "Pamgen", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-08-23" + }, + "description": "The TAO project focuses on the development of software for large scale optimization problems. TAO uses an object-oriented design to create a flexible toolkit with strong emphasis on the reuse of external tools where appropriate. Our design enables bi-directional connection to lower level linear algebra support (for example, parallel sparse matrix data structures) as well as higher level application frameworks. The Toolkist for Advanced Optimization (TAO) is aimed at teh solution of large-scale optimization problems on high-performance architectures. Our main goals are portability, performance, scalable parallelism, and an interface independent of the architecture. TAO is suitable for both single-processor and massively-parallel architectures. The current version of TAO has algorithms for unconstrained and bound-constrained optimization.", + "laborHours": 738613.6, + "languages": [], + "name": "TOOLKIT FOR ADVANCED OPTIMIZATION", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/petsc/petsc", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Libra is a tool for scalable analysis of load balance data from all processes in a parallel application. Libra contains an instrumentation module that collects model data from parallel applications and a parallel compression mechanism that uses distributed wavelet transforms to gather load balance model data in a scalable fashion. Data is output to files, and these files can be viewed in a GUI tool by Libra users. The GUI tool associates particular load balance data with regions for code, emabling users to view the load balance properties of distributed \"slices\" of their application code.", + "laborHours": 36723.2, + "name": "Libra: Scalable Load Balance Analysis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/tgamblin/libra/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tgamblin/libra", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The code to be released is a new addition to the LAMMPS molecular dynamics code. LAMMPS is developed and maintained by Sandia, is publicly available, and is used widely by both natioanl laboratories and academics. The new addition to be released enables LAMMPS to perform molecular dynamics simulations of shock waves using the Multi-scale Shock Simulation Technique (MSST) which we have developed and has been previously published. This technique enables molecular dynamics simulations of shock waves in materials for orders of magnitude longer timescales than the direct, commonly employed approach.", + "laborHours": 1281025.6, + "name": "Multi-scale Shock Technique", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lammps/lammps", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A Trilinos package for applying stochastic Galerkin uncertainty quantification methods to large-scale C++ application codes, primarily stochastic partial differential equations. Stokhos is intended for use in estimating uncertainties for general scientific computations and is based on published algorithms. It provides no capability for implementing those computations itself. Estimating uncertainties and errors from solution algorithms or simulations, primarily simulations of partial differential equations, arising from uncertainties or errors in solution algorithm or simulation input data, including statistical moments, probabilities, and coefficients of variation.", + "laborHours": 8344830.4, + "name": "Stokhos v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The SST provides a parallel framework to perform system simulation of computer architectures to determine their performance and power consumption. Additionally, the SST contains basic models of a computer processor, and interconnect and can connect to an external memory simulator (DRAMSim II). The SST framework provides a simple interface by which other computer simulation models can be combined under a common parallel discrete event-based simulation environment. This allows design exploration of future architectures, analysis of how current computer programs will function on future architectures. The SST provides a parallel discrete event simulation framework, including partitioning and object distribution over MPI. It also provides a mechanism by which components can report their power consumption for analysis.", + "laborHours": 25384.0, + "name": "Structural Simluation Toolkit (SST) V 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sstsimulator/sst-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "Poblano is a Matlab toolbox of large-scale algorithms for nonlinear optimization. The algorithms in Poblano require only first-order derivative information (e.g., gradients for scalar-valued objective functions), and therefore can scale to very large problems [6].Poblano is a set of general purpose methods for solving unconstrained nonlinear optimization methods. It has been applied to standard test problems covering a range of application areas. The driving application for Poblano development has been tensor decompositions in data analysis applications (bibliometric analysis, social network analysis, chemometrics, etc.) [1].", + "laborHours": 1474.4, + "languages": [ + "MATLAB", + "M" + ], + "name": "Poblano v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/poblano_toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A package for computing and applying algebraic preconditioners in the context of preconditioned iterative methods. It is related to the existing Ifpack package in Trilinos but provides support for template scalar and ordinal types and explicitly relies on Tpetra and Kokkos instead of Epetra. Algebraic preconditioners are used by iterative solvers as solution method in engineering and scientific applications, including nonlinear equation solving, time integration, sensitivity analysis, stability analysis, optimization, and uncertainty quantification.", + "laborHours": 8344830.4, + "name": "Tifpack v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Climate Data Analysis Tools (CDAT) is a software infrastructure that uses an object-oriented scripting language to link together separate software subsystems and packages thus forming an integrated environment for solving model diagnosis problems, The power of the system comes from Python and its ability to seamlissly interconnect software. Python provides a general purpose and full-featured scripting language with a variety of user interfaces including command-line interaction, stand-alone scripts (applications) and fraphical user interfaces (GUI). The CDAT subsystems, implemented as modules, provide access to and management of gridded data (Climate Data Management Systems or CDMS); large-array numerical operations (Numerical Python); and visualization (Visualization and Control System or VCS).", + "laborHours": 78644.8, + "name": "Climate Data Analysis Tools", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/UV-CDAT/uvcdat/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/UV-CDAT/uvcdat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "PyUtilib is a collection of Python utilities that are used by Python packages developed at Sandia National Laboratories, including the Coopr and FAST Python packages. PyUtilib includes facilities for managing factories, subprocess management, interfacing with Excel, and applying numerical techniques.", + "laborHours": 14972.0, + "languages": [ + "Shell", + "Python" + ], + "name": "PyUtilib: A Pythos Utility Library v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyutilib", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SNL Coopr Forum is a set of Python routines that provide extensions to the Coopr optimization software. This software augments the open-source Coopr project to provide a more comprehensive capability for formulating and solving optimization applications.Optimization is a common analysis tool used in engineering design and scientific discovery. The SNL Coopr Forum software augments the Coopr Forum open source project to provide extensions of the Coopr optimization framework. Specifically, Coopr Forum provides plugin tools that allow Coopr to apply different optimization solvers, manage optimization solvers in a distributed manner, and to process input and output files. Thus, Coopr Forum is comprised of a variety of distinct software components, each of which provides a different capability that can be used within Coopr.", + "laborHours": 314837.6, + "name": "Coopr Forum v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pyomo/pyomo", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "Implements previously developed methodology to calculate total disutility to an organization caused by impacts imposed upon the physical system in question (electric power transmission system, water system, etc).Critical infrastructure utility personnel will use this as a planning tool to determine where system weaknesses are and where improvements should be made such that the consequence of some impact is no longer higher than acceptable.", + "laborHours": 5745.6, + "languages": [ + "Java", + "CSS" + ], + "name": "Critical Infrastructure Consequence Modeler v 0.5.0 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cicm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.5.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "diod is an I/O forwarding daemon used to improve scalability of file systems on large Linux clusters.", + "laborHours": 28576.0, + "name": "diod - distributed I/O daemon", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/diod", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The SIERRA Toolkit is a collection of libraries to facilitate the development of parallel engineering analysis applications. These libraries supply basic core services that an engineering analysis application may need such as a parallel distributed and dynamic mesh database (for unstructured meshes), mechanics algorithm support (parallel infrastructure only), interfaces to parallel solvers, parallel mesh and data I/O, and various utilities (timers, diagnostic tools, etc.).The toolkit is intended to reduce the effort required to develop an engineering analysis application by removing the need to develop core capabilities that most every application would require.", + "laborHours": 8344830.4, + "name": "SIERRA Toolkit v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/stk/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-09" + }, + "description": "The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes (computational models) and iterative analysis methods. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and analysis of computational models on high performance computers.A user provides a set of DAKOTA commands in an input file and launches DAKOTA. DAKOTA invokes instances of the computational models, collects their results, and performs systems analyses. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, polynomial chaos, stochastic collocation, and epistemic methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as hybrid optimization, surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. Services for parallel computing, simulation interfacing, approximation modeling, fault tolerance, restart, and graphics are also included.", + "homepageURL": "https://dakota.sandia.gov/sites/default/files/docs/6.0/html-dev/files.html", + "laborHours": 3812676.8, + "languages": [], + "name": "DAKOTA Design Analysis Kit for Optimization and Terascale", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/sites/default/files/docs/6.0/html-dev/files.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "ForTrilinos stands for interfaces to Trilinos. It effectively replaces common practices for interfacing Fortran codes with Trilinos C++ packages. Common practices include writing user-specific drivers and exploiting the name-mangling schemes of specific compilers. ForTrilinos improves portability and robustness by exploiting the C interoperability constructs of Fortran 2003. These constructs facilitate binding Fortran interface bodies to their equivalent C function prototypes, providing for name resolution independent of the compiler\u2122s underlying mangling scheme and guaranteeing compatible type bit representations. Furthermore, ForTrilinos maintains the overall design philosophy and architecture of Trilinos by creating a derived type structure in Fortran similar to the class hierarchy in the underlying C++.ForTrilinos can be applied wherever the underlying Trilinos packages can be applied.", + "laborHours": 165087.2, + "languages": [ + "Dockerfile", + "C++", + "Shell", + "SWIG", + "CMake", + "Fortran", + "Python" + ], + "name": "ForTrilinos v 10.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/ForTrilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "10.1" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The BOUT++ is a C++ framework for developing plasma fluid simulation codes, and has been developed by the University of York/UK and the LLNL Fusion Energy Program from the original 3D boundary turbulence 2-fluid edge simulation code BOUT. The aim of BOUT++ is to automate the common tasks needed for simulation codes, and to separate the complicated details such as differential geometry, parallel communication, and file input/output from the user-specified equations to be solved. The BOUT++ consists of BOUT++ library and physics modules. BOUT++ modules contains the coding for the specific set of physics equations and boundary conditions for particular physics problems using defined functions in BOUT++ library to perform standard differential operators.", + "laborHours": 77748.0, + "name": "BOUT++", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/boutproject/BOUT-2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GlobiPack contains a small collection of optimization globalization algorithms. These algorithms are used by optimization and various nonlinear equation solver algorithms.Used as the line-search procedure with Newton and Quasi-Newton optimization and nonlinear equation solver methods. These are standard published 1-D line search algorithms such as are described in the book Nocedal and Wright Numerical Optimization: 2nd edition, 2006. One set of algorithms were copied and refactored from the existing open-source Trilinos package MOOCHO where the linear search code is used to globalize SQP methods. This software is generic to any mathematical optimization problem where smooth derivatives exist. There is no specific connection or mention whatsoever to any specific application, period. You cannot find more general mathematical software.", + "laborHours": 8344830.4, + "name": "GlobiPack v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/globipack/copyright_header.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Used to solve basic unconstrained optimization problems that can produce smooth accurate gradients. These are standard published unconstrained optimization such as are described in the book Nocedal and Wright Numerical Optimization: 2nd edition, 2006. This software is generic to any mathematical optimization problem where smooth derivatives exist. There is no specific connection or mention whatsoever to any specific application, period. You cannot find more general mathematical software.OptiPack contains some simple optimization algorithms built on Thyra. Currently, only a few different nonlinear conjugate gradient methods are implemented.", + "laborHours": 8344830.4, + "name": "Optipack", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/optipack/copyright_header.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CTrilinos provides a C language interface to a subset of Trilinos. The interface hides the object-oriented nature of Trilinos by allowing these objects to be acted upon using a set of three integers that uniquely identify the object. No pointers to the underlying objects are made available for direct manipulation, protecting against segmentation faults. CTrilinos serves as a base layer over which the ForTrilinos linking layer operates, facilitating the use Trilinos from object-oriented Fortran.CTrilinos can be applied wherever the supported underlying Trilinos packages can be applied.", + "laborHours": 18164.0, + "name": "CTrilinos v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/CTrilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Geryon is intended to be a simple library for managing the CUDA Runtime, CUDA Driver, and OpenCL APIs with a consistent interface archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Change from one API to another by simply changing the namespace archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Use multiple APIs in the same code archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Lightweight (only include files no build required) archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Manage device query and selection archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple vector and matrix containers archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple routines for data copy and type casting archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple routines for data I/O archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple classes for managing device timing archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple classes for managing kernel compilation and execution The primary application is to facilitate writing a single code that can be compiled using the CUDA Runtime API, the CUDA Driver API, or OpenCL.", + "laborHours": 7569.6, + "languages": [ + "C++", + "C" + ], + "name": "geryon v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/geryon?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/geryon", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "SNL cxxtest is a set of Python routines that support software testing for C++ codes. This software augments the open-source cxxtest project to provide a more comprehensive capability for software testing.", + "laborHours": 11552.0, + "languages": [ + "Smarty", + "C++", + "Shell", + "C", + "CMake", + "Python" + ], + "name": "SNL cxxtest v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cxxtest", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Memory size has long limited large-scale applications on high-performance computing (HPC) systems. Increasing core counts per chip and power density constraints, which limit the number of DIMMs per node, have exacerbated this problem. Mechanisms to manage memory usage - preferably transparently - more efficiently could increase effective DRAM capacity and, thus, the benefit of multicore similarity. These data regions occupy multiple physical locations within a multicore node and thus offer a potential savings in memory capacity. These data, primarily residing in heap, are quite dynamic, which makes them difficult to manage statically. SBLLmalloc is a memory allocation library that automatically identifies the replicated memory blocks and merges them into a single copy. SBLLmalloc does not require application or OS changes since we implement it as a user-level library that can be linked at runtime. SBLLmalloc provides the capability to run larger problems using the same hardware configuration in multicore nodes. SBLLmalloc has been implemented for Linux clusters.", + "laborHours": 4681.6, + "name": "SBLLmalloc V1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SBLLmalloc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Muster is a framework for scalable cluster analysis. It includes implementations of classic K-Medoids partitioning algorithms, as well as infrastructure for making these algorithms run scalably on very large systems. In particular, Muster contains algorithms such as CAPEK (described in reference 1) that are capable of clustering highly distributed data sets in-place on a hundred thousand or more processes.", + "laborHours": 2052.0, + "name": "Muster: Massively Scalable Clustering", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/muster/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/muster", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SAMRAI is an object-oriented support library for structured adaptice mesh refinement (SAMR) simulation of computational science problems, modeled by systems of partial differential equations (PDEs). SAMRAI is developed and maintained in the Center for Applied Scientific Computing (CASC) under ASCI ITS and PSE support. SAMRAI is used in a variety of application research efforts at LLNL and in academia. These applications are developed in collaboration with SAMRAI development team members.", + "laborHours": 279938.4, + "name": "Structured Adaptive Mesh Refinement Application Infrastructure", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SAMRAI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-01-22" + }, + "description": "GLVis is an OpenGL tool for visualization of finite element meshes and functions. When started without any options, GLVis starts a server, which waits for a socket connections and visualizes any recieved data. This way the results of simulations on a remote (parallel) machine can be visualized on the lical user desktop. GLVis can also be used to visualize a mesh with or without a finite element function (solution). It can run a batch sequence of commands (GLVis scripts), or display previously saved socket streams. For more information, see the project website: http://glvis.org/.", + "laborHours": 17343.2, + "languages": [], + "name": "GLVis: OpenGL Finite Element Visualization Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/glvis/glvis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Teko is a C++ library for implementation of blocked and segregated preconditioners in the context of iterative solvers for linear systems. Capabilities for decomposing larger matrices into user defined sub blocks are also provided. Additional functionality for creating approximate inverse operators utilizing solver and preconditioning packages in the Trilinos framework has also been implemented. Teko's primary application is in multiphysics simulation environment where a decomposition of the linear system in to physically meaningful blocks can be utilized to enhance performance of an iterative solver. However, applicability may extend to other problem domains where matrices can be decomposed into meaningful blocks.", + "laborHours": 8344830.4, + "name": "Teko v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "Conjoin is a code for joining sequentially in time multiple exodusII database files. It is used to create a single results or restart file from multiple results or restart files which typically arise as the result of multiple restarted analyses. The resulting output file will be the union of the input files with a status variable indicating the status of each element at the various time planes.Combining multiple exodusII files arising from a restarted analysis or combining multiple exodusII files arising from a finite element analysis with dynamic topology changes.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "Conjoin", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "ejoin is a three-dimensional mesh combination program. ejoin combines two or more meshes written in the exodusII mesh database format into a single exodusII mesh. Selected nodes in the wo meshes that are closer than a specified distance can be combined The geometry of the mesh databases an be modified by offsetting. Any results data on one or more of the input mesh files will be copied to the appropriate nodes/elements/nodesets/sidesets on the output file.Preparation of input mesh files for finite element analysis programs using the exodusII format.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "Ejoin", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "This application can determine the performance and chemical behavior of batteries in 1D when they are cycled. With CanTrilBat, we are developing predictive phenomenological models for battery systems to predict operating performance and rate limiting steps in the performance of battery models. Particular attention is paid to primary and secondary chemistry mechanisms, such as the thermal runaway mechanisms experienced in secondary lithium ion batteries or self-discharge reaction mechanism that all batteries experience to one extent or another. The first application of this model has been for modeling the performance of thermal batteries. However, an implementation for secondary ion batteries is next. CanTrilBat applications solves transient problems involving batteries. It is a 1-D application that represents 3-D physical systems that can be reduced using the porous flow approximation for the anode, cathode, and separator. A control volume formulation is used to track conserved quantities. An operator-split approach is used to calculate the chemistry, diffusion and electronic transport that occurs within cathode and anode particles, allowing for the reduction in code complexity.", + "laborHours": 6177492.8, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "M4", + "Fortran" + ], + "name": "CanTrilBat", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cantrilbat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This program can be used to read a LC-MS/MS data file from either a Finnigan ion trap mass spectrometer (.Raw file) or an Agilent Ion Trap mass spectrometer (.MGF and .CDF files) and create a selected ion chromatogram (SIC) for each of the parent ion masses chosen for fragmentation. The largest peak in each SIC is also identified, with reported statistics including peak elution time, height, area, and signal to noise ratio. It creates several output files, including a base peak intensity (BPI) chromatogram for the survey scan, a BPI for the fragmentation scans, an XML file containing the SIC data for each parent ion, and a \"flat file\" (ready for import into a database) containing summaries of the SIC data statistics.", + "laborHours": 118225.6, + "name": "MS/MS Automated Selected Ion Chromatograms", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MASIC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pagoda is a set of parallel tools as well as an application programmer interface for parallel data analysis of high-resolution climate data. Pagoda implements data parallel versions of some of the commonly used tools from the NetCDF Operators. These tools support data processing operations including subsetting, record and ensemble averages, binary operations, and interpolation. Pagoda also provides an application programmer interface for developing custom data analysis programs.", + "laborHours": 61392.8, + "name": "Pagoda", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jeffdaily/pagoda/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeffdaily/pagoda", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "nodediag is an extensible framework for packaging system diagnostics for Linux clusters.", + "laborHours": 592.8, + "name": "nodediag", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/nodediag", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MixDown is a meta-build tool that orchestrates and manages the building of multiple 3rd party libraries. It can manage the downloading, uncompressing, unpacking, patching, configuration, build, and installation of 3rd party libraries using a variety of configuration and build tools. As a meta-build tool, it relies on 3rd party tools such as GNU Autotools, make, Cmake, scons, etc. to actually confugure and build libraries. MixDown includes an extensive database of settings to be used for general machines and specific leadership class computing resources.", + "laborHours": 6536.0, + "name": "MixDown", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tepperly/MixDown", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "lustre-tools-llnl is a small set of commands that are helpful for using and administering a lustre file system.", + "laborHours": 1033.6, + "name": "lustre-tools-llnl", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/lustre-tools-llnl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This program is used to compute the predicted normalized elution time (NET) for a list of peptide sequences. It includes the Kangas/Petritis neural network trained model, the Krokhin hydrophobicity model, and the Mant hydrophobicity model. In addition, it can compute the predicted strong cation exchange (SCX) fraction (on a 0 to 1 scale) in which a given peptide will appear.", + "laborHours": 7296.0, + "name": "Normalized Elution Time Prediction Utility", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Protein-Digestion-Simulator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OVIS is a tool for intelligent, real-time monitoring of computational clusters. While current monitoring tools treat the cluster as singleton nodes, OVIS considers the cluster as comprised of comparative ensembles. OVIS provides a visual display of deterministic information about state variables and their aggregate statistics. Comparison to statistical quantities can be used for the automatic identification of abnormalities. OVIS collects and processes active data. OVIS can also process historical data files or database files.", + "laborHours": 98252.8, + "name": "OVIS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ovis-hpc/ovis", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Albany code is a general purpose finite element code for solving partial differential equations (PDEs). Albany is a research code that demonstrates how a PDE code can be built by interfacing many of the open-source software libraries that are released under Sandia's Trilinos project. Part of the mission of Albany is to be a testbed for new Trilinos libraries, to refine their methods, usability, and interfaces. Albany also serves as a demonstration code on how to build an application code against an installed Trilinos project. Because of this, Albany is a desirable starting point for new code development efforts that wish to make heavy use of Trilinos. The physics solved in Albany are currently only very academic problems, such as heat transfer, linear elasticity, and nonlinear elasticity. Albany includes hooks to optimization and uncertainty quantification algorithms, including those in the Dakota toolkit.", + "laborHours": 364222.4, + "name": "Albany v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gahansen/Albany", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-10-08" + }, + "description": "PECOS is a computational library for creating and manipulating realizations of stochastic quantities, including scalar uncertain variables, random fields, and stochastic processes. It offers a unified interface to univariate and multivariate polynomial approximations using either orthogonal or interpolation polynomials; numerical integration drivers for Latin hypercube sampling, quadrature, cubature, and sparse grids; and fast Fourier transforms using third party libraries. The PECOS core also offers statistical utilities and transformations between various representations of stochastic uncertainty. PECOS provides a C++ API through which users can generate and transform realizations of stochastic quantities. It is currently used by Sandia's DAKOTA, Stokhos, and Encore software packages for uncertainty quantification and verification. PECOS generates random sample sets and multi-dimensional integration grids, typically used in forward propagation of scalar uncertainty in computational models (uncertainty quantification (UQ)). PECOS also generates samples of random fields (RFs) and stochastic processes (SPs) from a set of user-defined power spectral densities (PSDs). The RF/SP may be either Gaussian or non-Gaussian and either stationary or nonstationary, and the resulting sample is intended for run-time query by parallel finite element simulation codes. Finally, PECOS supports nonlinear transformations of random variables via the Nataf transformation and extensions.", + "homepageURL": "https://dakota.sandia.gov/content/packages?q=content/pecos", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Environment for the Creation of Stochastics 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/content/packages?q=content/pecos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-07-25" + }, + "description": "HiPerSBTK consists of software which integrates equation solving, optimization and graphical interface functions to perform large-scale systems biology modeling.\n\nsee: https://www.nrel.gov/docs/fy11osti/51558.pdf", + "laborHours": 3149576.8, + "languages": [], + "name": "HiPerSBTK [SWR-08-64]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "Amesos2 is a templated direct sparse solver package. Amesos2 provides interfaces to direct sparse solvers, rather than providing native solver capabilities. Amesos2 is a derivative work of the Trilinos package Amesos.", + "laborHours": 8344830.4, + "languages": [], + "name": "Amesos2 Templated Direct Sparse Solver Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The Image Composition Engine for Tiles (lceT) is a high-performance sort-last parallel rendering library. It is designed to be used in parallel applications requiring rendering. The primary purpose of IceT is to be integrated into parallel visualization applications such as ParaView to provide parallel rendering capabilities. The Image Composition Engine for Tiles (lceT) is a high-performance sort-last parallel rendering library. IceT uses a \"sort-Iasf' approach to rendering. Each process in a parallel application independently renders a local piece of geometry. The resulting images are given to IceT, and IceT combines the images together to form a single cohesive image. Ice T is also capable of driving tiled displays, largeformat displays comprising an array of smaller displays. To this end IceT can collect the smaller tile images and organize them such that the entire tiled display can be driven. Ice T takes advantage of spatial coherence in geometry by identifying empty regions of the display and reducing the overall required work.", + "laborHours": 8709.6, + "languages": [ + "C" + ], + "name": "Image Composition Engine for Tiles", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IceT", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "LibVMI is an introspection library focused on reading and writing memory from virtual machines (VMs). For convenience, LibVMI also provides functions for accessing CPU registers, pausing and unpausing a VM, printing binary data, and more. LibVMI is designed to work across multiple virtualization platforms. LibVMI currently supports VMs running in either Xen or KVM. LibVMI also supports reading physical memory snapshots when saved as a file.", + "laborHours": 59097.6, + "languages": [ + "Yacc", + "C++", + "C", + "CMake", + "M4", + "Python" + ], + "name": "LibVMI", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/libvmi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.6" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "miniXyce uses a modified nodal analysis to approximate the governing differential algebraic equations (DAEs) for electronic devices and their coupling via a network and Kirchoff's conservation laws. The resulting nonlinear problem is solved iteratively using a fully coupled Newton method,which in turn results in a linear system that is solved using an iterative method.", + "laborHours": 1748.0, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "Perl", + "MATLAB", + "Python" + ], + "name": "miniXyce", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniXyce", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Peridigm is a multiphysics simulation code for peridynamic models. It provides the capability to simulate nonlocal models of solids undergoing large deformations and failure. It provides basic linear elastic and perfectly plastic peridynamic material models, and well as the capability to apply simply initial, boundary and loading conditions.", + "laborHours": 53534.4, + "languages": [ + "C++", + "Jupyter Notebook", + "CMake", + "Python" + ], + "name": "Peridigm", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/peridigm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-19" + }, + "description": "TriUtils is a package of utilities for other Trilinos packages. TriUtils contains utilities to perform common operations such as command line parsing, and input file reading.", + "laborHours": 8344830.4, + "languages": [], + "name": "TriUtils Trilinos Utilities Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "The Trilinos I/O support (Trios) software provides general I/O support for applications using Trilinos libraries. In particular, this software will include parallel I/O support to read and write selected Trilinos data structures to commonly-used file formats such as netCDF, hdf5, and Exodus.", + "laborHours": 39231.2, + "languages": [ + "C++", + "Shell", + "C", + "RPC", + "CMake", + "Makefile", + "Fortran" + ], + "name": "Trios", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/trios", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Epetra provides the fundamental construction routines and service functions that are required for serial and paraliellinear algebra libraries using double precision scalar values and int ordinal values.", + "laborHours": 8344830.4, + "languages": [], + "name": "Epetra Linear Algebra Services Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "EpetraExt is a set of extensions to Epetra. To allow Epetra to remain focused on its primary functionality as a Linear Algebra object support, EpetraExt was created to maintain additional support for such capabilities as transformations (permutations, subblock views, etc.), coloring support, partitioning (Zoltan), and I/O.", + "laborHours": 8344830.4, + "languages": [], + "name": "EpetraExt (Epetra Extended) - Linear Algebra Services", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Panzer is a finite element assembly engine used for research on solving partial differential equations (PDEs). Panzer takes a physics model implemented by a user and creates and populates the linear algrbra objects, such as residuals and Jacobians, for use in implicit finite element methods. Panzer can be considered \"glue code\" that pulls together the capabilities of a number of open-source Trilinos packages (Epetra, Intrepid, Sacado, FEI, and Phalanx). This code provides a generic framework for describing a set of partial differential equations. Panzer provides a simple example driver that solves the undergraduate textbook partial differential equation of heat transfer in a solid (see for example, \"Transport Phenomena\" by Bird Stewart, and Lightfoot 1960). Panzer is intended as a tool to simplify the use of the discretization tools in Trilinos (Intrepid and Phalanx) and is meant to aid in fundamental research on discretizations. Panzer will be released open-source as a package in Trilinos under a BSD license.", + "laborHours": 8344830.4, + "languages": [], + "name": "Panzer", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SEACAS Trilinos is the packaging of the SEACAS applications inside the Trilinos software package in a manner such that the Trilinos build and configurationprocess can be used to build and configure the SEACAS applications.", + "laborHours": 8344830.4, + "languages": [], + "name": "SEACAS Trilinos", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "IRIS is a search tool plug-in that is used to implement latent topic feedback for enhancing text navigation. It accepts a list of returned documents from an information retrieval wywtem that is generated from keyword search queries. Data is pulled directly from a topic information database and processed by IRIS to determine the most prominent and relevant topics, along with topic-ngrams, associated with the list of returned documents. User selected topics are then used to expand the query and presumabley refine the search results.", + "laborHours": 592.8, + "name": "Search tool plug-in: imploements latent topic feedback", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/iris", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "SmartImport.py is a Python source-code file that implements a replacement for the standard Python module importer. The code is derived from knee.py, a file in the standard Python diestribution , and adds functionality to improve the performance of Python module imports in massively parallel contexts.", + "laborHours": 243.2, + "name": "Python import replacement", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/langton/MPI_Import", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/langton/mpi_import", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MeshKit is an open-source library of mesh generation functionality. MeshKit has general mesh manipulation and generation functions such as Copoy, Move, Rotate and Extrude mesh. In addition, new quad mesh and embedded boundary Cartesian mesh algorithm (EB Mesh) are included. Interfaces to several public domain meshing algorithms (TetGen, netgen, triangle, Gmsh, camal) are also offered. This library interacts with mesh data mostly through iMesh including accessing the mesh in parallel. It also can interact with iGeom interface to provide geometry functionality such as importing solid model based geometries. iGeom and IMesh are implemented in the CGM and MOAB packages, respectively. For some non-existing function in iMesh such as tree-construction and ray-tracing, MeshKit also interacts with MOAB functions directly.", + "laborHours": 128637.6, + "name": "MeshKit", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/fathomteam/meshkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Service-Poke is a system which manages running services ensuring only one copy is running and potentially up to one more copy is marked for future execution.", + "laborHours": 562.4, + "name": "Service-Poke", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/service-poke", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-12-11" + }, + "description": "Co-PylotDB, written completely in Python, provides a user interface (UI) with which to select user and data file(s), directories, and file content, and provide or capture various other information for sending data collected from running any computer program to a pre-formatted database table for persistent storage. The interface allows the user to select input, output, make, source, executable, and qsub files. It also provides fields for specifying the machine name on which the software was run, capturing compile and execution lines, and listing relevant user comments. Data automatically captured by Co-PylotDB and sent to the database are user, current directory, local hostname, current date, and time of send. The UI provides fields for logging into a local or remote database server, specifying a database and a table, and sending the information to the selected database table. If a server is not available, the UI provides for saving the command that would have saved the information to a database table for either later submission or for sending via email to a collaborator who has access to the desired database.", + "laborHours": 64448.0, + "languages": [ + "Python" + ], + "name": "Co-PylotDB - A Python-Based Single-Window User Interface for Transmitting Information to a Database", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PYLOTDB", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "EXOMATLAB extracts the global transient variable data from an exodus file and writes it to a text-based file readable by the Matlab program.", + "laborHours": 692284.0, + "languages": [ + "MATLAB" + ], + "name": "exomatlab", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.9.2" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Domain Name System Security Extensions (DNSSEC) add authentication to the DNS. However, analyzing and troubleshooting a DNSSEC deployment is difficult in part because of the protocol complexity and in part because authentication involves retrieving dependent components from a number of different Internet locations. DNSViz was written to bring all these DNSSEC components together into a single graph, so they can be represented visually, and nuances can be highlighted for easy identification. DNSViz includes functionality for both analyzing a domain name using active probing and visual representation of the domain name, available currently through a Web interface.", + "laborHours": 11445.6, + "name": "DNSViz", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dnsviz/dnsviz", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "eCo-PylotDB, written completely in Python, provides a script that parses incoming emails and prepares extracted data for submission to a database table. The script extracts the database server, the database table, the server password, and the server username all from the email address to which the email is sent. The database table is specified on the Subject line. Any text in the body of the email is extracted as user comments for the database table. Attached files are extracted as data files with each file submitted to a specified table field but in separate rows of the targeted database table. Other information such as sender, date, time, and machine from which the email was sent is extracted and submitted to the database table as well. An email is sent back to the user specifying whether the data from the initial email was accepted or rejected by the database server. If rejected, the return email includes details as to why.", + "laborHours": 64448.0, + "languages": [], + "name": "eCo-Pylot - A Python-Based Script for Sending Parsed Email Data to a Database", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PYLOTDB", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GEN3D is a three-dimensional mesh generation program. The three-dimensional mesh is generated by mapping a two-dimensional mesh into three-dimensions according to one of four types of transformations: translating, rotating, mapping onto a spherical surface, and mapping onto a cylindrical surface. The generated three-dimensional mesh can then be reoriented by offsetting, reflecting about an axis, and revolving about an axis. GEN3D can be used to mesh geometries that are axisymmetric or planar, but, due to three-dimensional loading or boundary conditions, require a three-dimensional finite element mesh and analysis. More importantly, it can be used to mesh complex three-dimensional geometries composed of several sections when the sections can be defined in terms of transformations of two dimensional geometries. The code GJOIN is then used to join the separate sections into a single body. GEN3D reads and writes two-dimensional and three-dimensional mesh databases in the GENESIS database format; therefore, it is compatible with the preprocessing, postprocessing, and analysis codes used by the Engineering Analysis Department at Sandia National Laboratories, Albuquerque, NM.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "GEN3D Ver. 1.37", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.37" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GENSHELL is a three-dimensional shell mesh generation program. The threedimensional shell mesh is generated by mapping a two-dimensional quadrilateral mesh into three dimensions according to one of several types of transformations: translation, mapping onto a spherical, ellipsoidal, or cylindrical surface, and mapping onto a user-defined spline surface. The generated three-dimensional mesh can then be reoriented by offsetting, reflecting about an axis, revolving about an axis, and scaling the coordinates. GENSHELL can be used to mesh complex three-dimensional geometries composed of several sections when the sections can be defined in terms of transformations of two-dimensional geometries. The code GJOIN is then used to join the separate sections into a single body. GENSHELL updates the EXODUS quality assurance and information records to help track the codes and files used to generate the mesh. GENSHELL reads and writes two-dimensional and three-dimensional mesh databases in the GENESIS database format; there, it is compatible with the preprocessing, postprocessing, and analysis codes in the Sandia National Laboratories Engineering Analysis Code Access System (SEACAS).", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "genshell", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.15" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GREPOS is a mesh utility program that repositions or modifies the configuration of a two- dimensional or three-dimensional mesh. GREPOS can be used to change the orientation and size of a two- dimensional or three-dimensional mesh; change the material block, nodeset, and sideset IDs; or \"explode\" the mesh to facilitate viewing of the various parts of the model, and several other mesh modification utilities.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "GREPOS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.61" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "KLU2 is a direct sparse solver for solving unsymmetric linear systems. It is related to the existing KLU solver, (in Amesos package and also as a stand-alone package from University of Florida) but provides template support for scalar and ordinal types. It uses a left looking LU factorization method.", + "laborHours": 8344830.4, + "languages": [], + "name": "KLU2 Direct Linear Solver Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "PylotDB, written completely in Python, provides a user interface (UI) with which to interact with, analyze, graph data from, and manage open source databases such as MySQL. The UI mitigates the user having to know in-depth knowledge of the database application programming interface (API). PylotDB allows the user to generate various kinds of plots from user-selected data; generate statistical information on text as well as numerical fields; backup and restore databases; compare database tables across different databases as well as across different servers; extract information from any field to create new fields; generate, edit, and delete databases, tables, and fields; generate or read into a table CSV data; and similar operations. Since much of the database information is brought under control of the Python computer language, PylotDB is not intended for huge databases for which MySQL and Oracle, for example, are better suited. PylotDB is better suited for smaller databases that might be typically needed in a small research group situation. PylotDB can also be used as a learning tool for database applications in general.", + "laborHours": 64448.0, + "languages": [ + "Python" + ], + "name": "PylotDB - A Database Management, Graphing, and Analysis Tool Written in Python", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PYLOTDB", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "This software consists of code modifications to the open-source OpenSceneGraph software package to enable the creation of TlFF images containing 16 bit unsigned data. They also allow the user to disable compression and set the DPI tags in the resulting TIFF Images. Some image analysis programs require uncompressed, 16 bit unsigned input data. These code modifications allow programs based on OpenSceneGraph to write out such images, improving connectivity between applications.", + "laborHours": 367292.8, + "languages": [ + "Objective-C", + "C++", + "HTML", + "C", + "CMake", + "Objective-C++" + ], + "name": "TIFF Image Writer patch for OpenSceneGraph", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/OpenSceneGraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The functionality of heRXD includes the following: distance and angular calibration and viewing flat-panel detector images used for X-ray diffraction; image (polar) rebinning or \"caking\"; line position fitting in powder diffraction images; image segmentation or \"blob finding\"; crystal orentation indesing; and lattice vector refinement. These functionalities encompass a critical set analyzing teh data for high-energy diffraction measurements that are currently performed at synchrotron sources such as the Advanced Photon Source (APS). The software design modular and open source under LGPL. The intent is to provide a common framework and graphical user interface that has the ability to utillize internal as well as external subroutines to provide various optins for performing the fuctionalities listed above. The software will initially be deployed at several national user facilities--including APS, ALS, and CHESS--and then made available for download using a hosting service such as sourceforge.", + "laborHours": 33865.6, + "name": "High-Energy X-Ray Diffraction Analysis Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/praxes/hexrd", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MountPointAttributes is a software component that provides client code with a technique to raise the local namespace of a file to a global namespace. Its abstractions and mechanisms allow the client code to gather global properties of a file and to use them in devising an effective storage access strategy on this file.", + "laborHours": 2872.8, + "name": "MountPointAttributes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/mountpointattributes", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Forthon generates links between Fortran and Python. Python is a high level, object oriented, interactive and scripting language that allows a flexible and versatile interface to computational tools. The Forthon package generates the necessary wrapping code which allows access to the Fortran database and to the Fortran subroutines and functions. This provides a development package where the computationally intensive parts of a code can be written in efficient Fortran, and the high level controlling code can be written in the much more versatile Python language.", + "laborHours": 3906.4, + "name": "Python interface generator for Fortran based codes (a code development aid)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/dpgrote/Forthon/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dpgrote/Forthon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ECCE provides a sophisticated graphical user interface, scientific visualization tools, and the underlying data management framework enabling scientists to efficiently set up calculations and store, retrieve, and analyze the rapidly growing volumes of data produced by computational chemistry studies. ECCE was conceived as part of the Environmental Molecular Sciences Laboratory construction to solve the problem of researchers being able to effectively utilize complex computational chemistry codes and massively parallel high performance compute resources. Bringing the power of these codes and resources to the desktops of researcher and thus enabling world class research without users needing a detailed understanding of the inner workings of either the theoretical codes or the supercomputers needed to run them was a grand challenge problem in the original version of the EMSL. ECCE allows collaboration among researchers using a web-based data repository where the inputs and results for all calculations done within ECCE are organized. ECCE is a first of kind end-to-end problem solving environment for all phases of computational chemistry research: setting up calculations with sophisticated GUI and direct manipulation visualization tools, submitting and monitoring calculations on remote high performance supercomputers without having to be familiar with the details of using these compute resources, and performing results visualization and analysis including creating publication quality images. ECCE is a suite of tightly integrated applications that are employed as the user moves through the modeling process.", + "laborHours": 450421.6, + "name": "Extensible Computational Chemistry Environment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mattbernst/ECCE/blob/master/ecce-v7.0/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mattbernst/ECCE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Amalgam is a system that allows you to generate collections of files that work with conventional tools but take up minimal extra space on storage. If you already are archiving files in a file system and don't want to make multiple copies of whole files in order to ship the data somewhere then this system is for you. Amalgam consists of tools that allow you to create and get information about '.amalgam' files which contain just the metadata associated with a set of files. It also contains a fuse file system that, using amalgam files, will dynamically create traditional tar files. With this setup, you can see multiple orders of magnitude reduction in storage requirements for temporary data collections.", + "laborHours": 638.4, + "name": "Amalgam", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/amalgam", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-16" + }, + "description": "This software package implements the algorithm from a paper by Bayati, Kim, and Saberi (first reference below) to generate a uniformly random sample of a graph with a prescribed degree distribution.", + "laborHours": 1094.4, + "languages": [ + "MATLAB", + "C++", + "C" + ], + "name": "Bayati Kim Saberi random graph sampler", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/bisquik", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "While an organized source of reference information on PV performance modeling is certainly valuable, there is nothing to match the availability of actual examples of modeling algorithms being used in practice. To meet this need, Sandia has developed a PV performance modeling toolbox (PV_LIB) for Matlab. It contains a set of well-documented, open source functions and example scripts showing the functions being used in practical examples. This toolbox is meant to help make the multi-step process of modeling a PV system more transparent and provide the means for model users to validate and understand the models they use and or develop. It is fully integrated into Matlab's help and documentation utilities. The PV_LIB Toolbox provides more than 30 functions that are sorted into four categories", + "laborHours": 532.0, + "name": "PV_LIB Toolbox", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cwhanse/PVLIB_Python", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Xpetra provides a single interface that allows the use of either Epetra or Tpetra linear algebra libraries from the same source code. 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The software provides multigrid source code, test programs, and short example programs to demonstrate the various interfaces for creating, accessing, and applying the solvers. MueLu currently provides an implementation of smoothed aggregation algebraic multigrid method and interfaces to many commonly used smoothers. However, the software is intended to be extensible, and new methods can be incorporated easily. MueLu also allows for advanced usage, such as combining multiple methods and segregated solves. The library supports point and block access to matrix data. All algorithms and methods in MueLu have been or will be published in the open scientific literature.", + "laborHours": 8344830.4, + "languages": [], + "name": "MueLu Multigrid Preconditioning Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MiniGhost is a miniapp in the Mantevo project. Using a finite difference method, it mimics the inter-process communication requirements commonly found in applications of this sort. Random values are inserts into the grid, and therefore no \"real problem\" is solved.", + "laborHours": 5016.0, + "name": "miniGhost Mantevo miniapp", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Mantevo/miniGhost", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-19" + }, + "description": "ShyLU is numerical software to solve sparse linear systems of equations. ShyLU uses a hybrid direct-iterative Schur complement method, and may be used either as a preconditioner or as a solver. ShyLU is parallel and optimized for a single compute Solver node. ShyLU will be a package in the Trilinos software framework.", + "laborHours": 8344830.4, + "languages": [], + "name": "jShyLU Scalable Hybrid Preconditioner and Solver", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "pair_bop is a module for performing energy calculations using the Bond Order Potential (BOP) for use in the parallel molecular dynamics code LAMMPS. The bop pair style computes BOP based upon quantum mechanical incorporating both sigma and pi bondings. By analytically deriving the BOP pair bop from quantum mechanical theory its transferability to different phases can approach that of quantum mechanical methods. This potential is extremely effective at modeling 111-V and II-VI compounds such as GaAs and CdTe. This potential is similar to the original BOP developed by Pettifor and later updated by Murdock et al. and Ward et al.", + "laborHours": 1281025.6, + "name": "Bond order potential module for LAMMPS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lammps/lammps", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "MAT2EXO is a program which translates mesh data from Matlab mat-file format to Exodus II format. This tool is the inverse of the commonly used tool exo2mat which translates Exodus II data to the Matlab mat-file format. These tools provide a means for preprocessing an Exodus II model file or postprocessing an Exodus II results file using Matlab", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "Mat2exo", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.6" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The Dax Toolkit enables the fine-grained concurrency for data analysis and visualization required to drive multi-core processors, many-core GPU accelerators, and emerging architectures for exascale computing. Dax simplifies the design of finely threaded algorithms by characterizing them in per element operations, which we call worklets. Worklets simplify design because they can behave as serial processes without the complications of memory clashes or other race conditions. Yet worklets can be scheduled on a practically unlimited number of threads, thereby making effective utilization of many processing cores. Operations coordinated across elements are encapsulated in a few versatile communicative operations that are adapted to the specifics of computing devices.", + "laborHours": 24396.0, + "languages": [ + "C++", + "C", + "CMake", + "Cuda" + ], + "name": "Dax v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DaxToolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The software is a modular framework for controlling data acquisition systems (DAQs) for radiation detectors. Its capabilities include hardware configuration and control as well as data readout and storage. In addition to a generalized extensible framework for building DAQs, the package also includes specific implementations for a number of commercially available hardware devices commonly used in nuclear instrumentation (digitizers, high voltage controllers, etc.).", + "laborHours": 9667.2, + "languages": [ + "Lua" + ], + "name": "SLMod", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DCS-Slmod", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Kokkos Array library implements shared-memory array data structures and parallel task dispatch interfaces for data-parallel computational kernels that are performance-portable to multicore-CPU and manycore-accelerator (e.g., GPGPU) devices.", + "laborHours": 8344830.4, + "name": "Kokkos Array", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "nSIGHTS (n-dimensional Statistical Inverse Graphical Hydraulic Test Simulator) is a comprehensive well test analysis software package. It provides a user-interface, a well test analysis model and many tools to analyze both field and simulated data. The well test analysis model simulates a single-phase, one-dimensional, radial/non-radial flow regime, with a borehole at the center of the modeled flow system. nSIGHTS solves the radially symmetric n-dimensional forward flow problem using a solver based on a graph-theoretic approach. The results of the forward simulation are pressure, and flow rate, given all the input parameters. The parameter estimation portion of nSIGHTS uses a perturbation-based approach to interpret the best-fit well and reservoir parameters, given an observed dataset of pressure and flow rate.", + "laborHours": 269587.2, + "languages": [ + "Objective-C", + "C++", + "HTML", + "C", + "CMake", + "Makefile" + ], + "name": "n-dimensional Statistical Inverse Graphical Hydraulic Test Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/nSIGHTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The ap command traveres all symlinks in a given file, directory, or executable name to identify the final absolute path. It can print just the final path, each intermediate link along with the symlink chan, and the permissions and ownership of each directory component in the final path. It has functionality similar to \"which\", except that it shows the final path instead of the first path. It is also similar to \"pwd\", but it can provide the absolute path to a relative directory from the current working directory.", + "laborHours": 76.0, + "name": "The absolute path command", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/ap/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Datatype Compare (DTCMP) library provides routines that sort, search, merge, partition, rank, and select items using operations that compare MPI datatypes. Such routines are needed im MPI applications dealing with large distributed latasets, where the amount of data is too large to gather to a single process.", + "laborHours": 10047.2, + "name": "The Datatype Compare Library v.1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/dtcmp/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/dtcmp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The mpileaks tool is to be used by MPI application developers to track and report leaked MPI objects, such as requests, groups, and datatypes. This debugging tool is useful as a quality assurance check for MPI applications, or it can be used to identify leaks fatal to long-running MPI applications. It provides an efficient method to report bugs that are otherwise fifficult to identify.", + "laborHours": 22450.4, + "name": "mpileaks - an MPI opject leak debugging library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/mpileaks/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mpileaks", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DI-MMAP is a simulator for modeling the performance of next generation non-volatile random access memory technologies (NVRAM) and a high-perfromance memory-map runtime for the Linux operating system. It is implemented as a device driver for the Linux operating system. It will be used by algorithm designers to unserstand the impact of future NVRAM on their algorithms and will be used by application developers for high-performance access to NVRAM storage.", + "laborHours": 4894.4, + "name": "Data-Intensive Memory-Map simulator and runtime", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/vanessen/di-mmap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "We are seeking a code review of patches against DyninstAPI 8.0. DyninstAPI is an open source binary instrumentation library from the University of Wisconsin and University of Maryland. Our patches port DyninstAPI to the BlueGene/P and BlueGene/Q systems, as well as fix DyninstAPI bugs and implement minor new features in DyninstAPI.", + "laborHours": 290867.2, + "languages": [], + "name": "DyninstAPI Patches", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dyninst/dyninst", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Script to create operating system images in a directory from RPMs using the commands rpm or YUM.", + "laborHours": 136.8, + "name": "Kona", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trentdhooge/kona.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Light-Weight Group (LWGRP) bibrary provides data structures and collective routines to define and operate on groups of MPI processes. Groups can be created and freed efficiently in O(log N) time space requiring less overhead that constructing full MPI communicators. This facilitates faster development of applications and libraries that need to rapidly create, use, and destroy process groups.", + "laborHours": 24289.6, + "name": "The Light-Weight Group Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/lwgrp/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lwgrp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Rubik is a tool that simplifies the process of creating task mappings for structured applications. Rubik allows an application developer to specify communicating groups of processes in a virtual application topology succinctly and map them onto groups of processors in a physical network topology. Both the application topology and the network topology must be Cartesian, but the dimensionality of either is arbitrary. This allows users to easily map low-dimensional structures such as planes to higher-dimensional structures like cubes to increase the number of links used for routing.", + "laborHours": 896.8, + "name": "Rubik", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/rubik/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/rubik", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Give and Take are set of companion utilities that allow a secure transfer of files from one user to another without exposing the files to third parties. The named files are copied to a spool area. The reciever can retrieve the files by running the \"take\" program. Ownership of the files remains with the giver until they are taken. Certain users may be limited to take files only from specific givers. For these users, files may only be taken from givers who are members of the gt-uid-group where uid is the UNIX id of the limited user.", + "laborHours": 26934.4, + "name": "Give/Take", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/give", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Interatomic force and energy calculation subroutine to be used with the molecular dynamics simulation code LAMMPS (Ref a.). The code evaluated the total energy and atomic forces (energy gradient) according to a cubic spline-based variant (Ref b.) of the Modified Embedded Atom Method (MEAM) with a additional Stillinger-Weber (SW) contribution.", + "laborHours": 1281025.6, + "name": "Modified Embedded Atom Method", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lammps/lammps", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Boxfish is a tool for visualizing performance data. It allows users to quickly project performance data gathered from parallel applications onto intuitive domains. It also includes a projection mechanism that automatically finds relations in performance data so the the data can easily be mapped onto non-obviously related domains. For this release, Boxfish allows performance data to be projected onto the nodes and links of a computer network, as well as onto grids or patch-structured applications. This allows a user of the visualization tool to quickly see correlations between performance data and network structure, application data, or communication patterns.", + "laborHours": 225005.6, + "name": "Boxfish", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/boxfish/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/boxfish", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SystemBurn is a tool for creating a synthetic computational load for the purpose of measuring how much power a computer will draw under that type of load. The loads include fundamental library function calls like matrix multiply, memory copies, fourier transforms, bit manipulation, I/O, network packet transfers, and some code contrived to cause the processor to dray more or less power. The code produces some diagnostic and progress output, but the actual measurements would be recorded from the power panels within the computer room.", + "laborHours": 17510.4, + "name": "SystemBurn", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jlothian/systemburn", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SystemConfidence is a benchmark developed at ORNL which can measure statistical variation in which the user can plot. The portions of the code which manage the collection of the histograms and computing statistics on the histograms were designed with the intent that we could use these functions in other codes.", + "laborHours": 1216.0, + "name": "SystemConfidence", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jlothian/sysconfidence", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Log files are typically semi-or un-structured. To be useable, they need to be parsed into a standard, structured format. Regex-Stream facilitates parsing text files into structured data (JSON) in streams of data.", + "laborHours": 34488.8, + "name": "Regex-Stream", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/regex-stream", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"Synchrotron Radiation Workshop\" (SRW) is a physical optics computer code for calculation of detailed characteristics of Synchrotron Radiation (SR) generated by relativistic electrons in magnetic fields of arbitrary configuration and for simulation of the radiation wavefront propagation through optical systems of beamlines. Frequency-domain near-field methods are used for the SR calculation, and the Fourier-optics based approach is generally used for the wavefront propagation simulation. The code enables both fully- and partially-coherent radiation propagation simulations in steady-state and in frequency-/time-dependent regimes. With these features, the code has already proven its utility for a large number of applications in infrared, UV, soft and hard X-ray spectral range, in such important areas as analysis of spectral performances of new synchrotron radiation sources, optimization of user beamlines, development of new optical elements, source and beamline diagnostics, and even complete simulation of SR based experiments. Besides the SR applications, the code can be efficiently used for various simulations involving conventional lasers and other sources. SRW versions interfaced to Python and to IGOR Pro (WaveMetrics), as well as cross-platform library with C API, are available.", + "laborHours": 131008.8, + "name": "Synchrotron Radiation Workshop (SRW)", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ochubar/SRW/blob/master/COPYRIGHT.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ochubar/SRW", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "NV is a visualization tool for exploring vulnerabilities within a network. The data is created with a vulnerability assessment tool, such as Nessus (http://www.tenable.com/products/nessus).", + "laborHours": 270879.2, + "name": "Nessus Visualization", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/nv", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ASPA is an implementation of an adaptive sampling algorithm [1-3], which is used to reduce the computational expense of computer simulations that couple disparate physical scales. The purpose of ASPA is to encapsulate the algorithms required for adaptive sampling independently from any specific application, so that alternative algorithms and programming models for exascale computers can be investigated more easily.", + "laborHours": 19167.2, + "name": "Adaptive Sampling Proxy Application", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exmatex/aspa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ProxyVPFFT computes the micromechanical reaponse of polycriystalline samples directly from images of their microstructures, usually captured using SEM. [2] ProxyVPFFT is proxy application, or a somplified version of existing software by Ricardo Lebensohn (VPFFT).", + "laborHours": 1900.0, + "name": "Prozy Visco-plasticity, Fast Fourier Transform", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/exmatex/VPFFT/blob/master/README-license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exmatex/vpfft", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "LRIOT is a test bench framework that is designed to generate sophisticated I/O rates that can stress high-performance memory and storage systems, such as non-volatile random access memories (NVRAM)and storage class memory. Furthermore, LRIOT provides the capabilities to mix multiple types of concurrency, namely threading and task parallelism, as well as distributed execution using Message Passing Interface (MPI) libraries. It will be used by algorithm designers to generate access patterns that mimic their application's behavior, and by system designers to test high-performance NVRAM storage.", + "laborHours": 760.0, + "name": "Livermore Random I/O Testbench", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/vanessen/lriot/src/594efbf7484ed377e0b9e55e6f1bf564b6556546/lriot_license_header_stub.c", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/vanessen/lriot", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Qball is a modified version of the open source Qbox first-principles molecular dynamics code which was originally developed at LLNL by Francois Gygi.", + "laborHours": 3030135.2, + "name": "Qbox First-principles Molecular Dynamics (Qball branch, svn release 081", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/qball", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Sponge provides a web interface to Pulp (http://pulpproject.org/) that implements a particular workflow as described in the paper \"Staging Package Deployment via Repository Management\" (http://www.usenix.org/events/lisa11/tech/full_papers/Pierre.pdf). Namely, it implements a process for intensive management of software repositories to apply more deterministic updates to clients of those repositories.", + "laborHours": 2021.6, + "name": "Sponge", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stpierre/sponge", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The MPS++ computer code simulates models of strongly correlated quantum lattice systems. The algorithm used is the density-matrix renormalization method formulated in the matrix product states language. These models and methods are used to obtain ground state, dynamic, finite temperature and time evolution properties of the underlying materials that are simulated. These materials are usually one- and quasi-one dimensional strongly correlated electronic systems, such as high temperature superconductors, manganites, and other transition metal oxides. This code is (mostly) an implementation of the paper \"The density-matrix renormalization group in the age of matrix product states\" by U. Schollwoeck, and references therein, found at http://arxiv.org/abs/1008.3477v2 , and that was also published in Annals of Physics 326,96 (2011).", + "laborHours": 1656.8, + "name": "MPS++", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/g1257/mpspp", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.", + "laborHours": 60830.4, + "name": "Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bdsullivan/INDDGO", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "For testing and demonstration purposes, it is often necessary to replay saved network and log data. This library facilitates replaying these saved data streams. This module will take in a stream of JSON strings, read their specified timestamp field, and output according to the given criteria. This can include restricting output to a certain time range, and/or outputting the items with some delay based on their timestamp.", + "laborHours": 40736.0, + "name": "Replay-Stream", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/replay-stream", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Many new, high-performance nuclear energy modeling and simulation tools are under development in the United States and many more existing projects are moving to high-performance computing. This shift to state-of-the-art modeling and simulation will not only result in an unprecedented use of computing resources but it will generate extremely large amounts of data in extraordinary detail. Domain scientists will find themselves simultaneously in two positions: managing the complexity of their own problem domain and managing the complexity of a nightmarish scenario of high-performance computational tools. We believe that the computational science community should develop integrated tools for coupling, working with and analyzing data from simulation codes instead of leaving domains scientists and students to fend for themselves and come up with a \"working\" solution. While many projects offer some set of tools to work with their codes, to launch jobs remotely or to setup input files, most of these tools are rarely integrated in a holistic way to provide an easy, common and high-productivity environment for users. For that matter, most remote jobs are launched on \"the machine in the other room,\" but that certainly will not work for larger problems that require Leadership Class computing resources found only at U.S. National Laboratories or similar facilities. Overcoming the challenges of launching on these machines and even on public or private \"clouds\" are left as a challenge to the user.", + "laborHours": 92902.4, + "name": "The NEAMS Integrated Computational Environment (NiCE)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/eclipse/ice/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eclipse/ice", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Enables applications to emit debug log information into an output file and provides developers with a way to visually structure the output to make it easier for them to navigate it to understand the sources of application errors.", + "laborHours": 192477.6, + "name": "dbglog", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bronevet/dbglog", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CRUISE implements a user-space file system that stores data in main memory and transparently spills over to other storage, like local flash memory or the parallel file system, as needed. CRUISE also exposes file contents fo remote direct memory access, allowing external tools to copy files to the parallel file system in the background with reduced CPU interruption.", + "laborHours": 4772.8, + "name": "Checkpoint-Restart in User Space", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/cruise/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/cruise", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This client-side web app tracks the amount of time spent on arbitrary tasks. It allosw the creation of an unlimited number of arbitrarily named tasks ans via simple interactions, tracks the amount of time spent working on the drfined tasks.", + "laborHours": 3602.4, + "name": "Task Time Tracker", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Task-Time-Tracker", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SW4 is a program for simulating seismic wave propagation on parallel computers. SW4 colves the seismic wave equations in Cartesian corrdinates. It is therefore appropriate for regional simulations, where the curvature of the earth can be neglected. SW4 implements a free surface boundary condition on a realistic topography, absorbing super-grid conditions on the far-field boundaries, and a kinematic source model consisting of point force and/or point moment tensor source terms. SW4 supports a fully 3-D heterogeneous material model that can be specified in several formats. SW4 can output synthetic seismograms in an ASCII test format, or in the SAC finary format. It can also present simulation information as GMT scripts, whixh can be used to create annotated maps. Furthermore, SW4 can output the solution as well as the material model along 2-D grid planes.", + "laborHours": 75817.6, + "name": "Seismic Waves, 4th order accurate", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/geodynamics/sw4", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ngrm-proto is a package of proff-of-concept utilities intended to demonstrate concepts that will be developed full in the FLUX resource manager.", + "laborHours": 0.0, + "name": "Next Generation Resource Manager Protoryping Environment", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/ngrm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HAVOQGT is a C++ framework that can be used to create highly parallel graph traversal algorithms. The framework stores the graph and algorithmic data structures on external memory that is typically mapped to high performance locally attached NAND FLASH arrays. The framework supports a vertex-centered visitor programming model. The frameworkd has been used to implement breadth first search, connected components, and single source shortest path.", + "laborHours": 15139.2, + "name": "Highly Asynchronous VisitOr Queue Graph Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/PerMA/havoqgt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "An API and implementation to install debug probes into a parallel application", + "laborHours": 5517.6, + "name": "Dynamic Scalable Event Chain Tracing API", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/dysectapi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-01-14" + }, + "description": "LDMS is a framework for collection and transport of system monitoring data from computational clusters. It utilizes existing data sources on the cluster (e.g., temperature sensors, network traffic counters). The collection and transport mechanisms of LDMS are lightweight and do not significantly adversely impact the performance of concurrently running applications.", + "laborHours": 98252.8, + "languages": [ + "Perl", + "C", + "Python" + ], + "name": "Lightweight Distributed Metric Service (LDMS) v. 4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ovis-hpc/ovis", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 4.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-04-18" + }, + "description": "Slycat\u2122 is a web-based system for analysis of large, high-dimensional data such as that produced by High Performance Computing (HPC) platforms. The Slycat\u2122 server integrates data ingestion, scalable analysis, data management, and visualization with commodity web clients using a multi-tiered hierarchy of data and model storage. Analysis inputs are pushed or pulled into Slycat\u2122, where models are generated and analysis artifacts are stored in a project database. These artifacts are the basis for visualizations that are delivered to users\u2019 desktops through ordinary web browsers, eliminating the need to build and deploy platform-specific client applications. Slycat\u2122 currently provides four types of analysis: canonical correlation analysis (CCA) to model relationships between inputs and output metrics, time series analysis featuring clustering and comparative visualization of waveforms, parameter space visualization including remote retrieval of images and movies from HPC disks, and VideoSwarm for modeling video similarities over time.", + "laborHours": 66758.4, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Slycat v 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/slycat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The purpose of the Project Grandmaster Application is to allow individuals to opt-in and give the application access to data sources about their activities on social media sites. The application will cross-reference these data sources to build up a picture of each individual activities they discuss, either at present or in the past, and place this picture in reference to groups of all participants. The goal is to allow an individual to place themselves in the collective and to understand how their behavior patterns fit with the group and potentially find changes to make, such as activities they weren't already aware of or different groups of interest they might want to follow.", + "laborHours": 3967.2, + "name": "Project Grandmaster", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/grandmaster", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-11-01" + }, + "description": "The Xyce Parallel Electronic Simulator simulates electronic circuit behavior in DC, AC, HB, MPDE and transient mode using standard analog (DAE) and/or device (PDE) device models including several age and radiation aware devices. It supports a variety of computing platforms (both serial and parallel) computers. Lastly, it uses a variety of modern solution algorithms dynamic parallel load-balancing and iterative solvers.! ! Xyce is primarily used to simulate the voltage and current behavior of a circuit network (a network of electronic devices connected via a conductive network). As a tool, it is mainly used for the design and analysis of electronic circuits.! ! Kirchoff's conservation laws are enforced over a network using modified nodal analysis. This results in a set of differential algebraic equations (DAEs). The resulting nonlinear problem is solved iteratively using a fully coupled Newton method, which in turn results in a linear system that is solved by either a standard sparse-direct solver or iteratively using Trilinos linear solver packages, also developed at Sandia National Laboratories.", + "laborHours": 491233.6, + "languages": [], + "name": "Xyce(\u2122) Parallel Electronic Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Xycedev/Xyce", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Not Specified", + "laborHours": 222254.4, + "name": "GOMA Ver. 6.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/goma/goma", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Minimega is a simple emulytics platform for creating testbeds of networked devices. The platform consists of easily deployable tools to facilitate bringing up large networks of virtual machines including Windows, Linux, and Android. Minimega attempts to allow experiments to be brought up quickly with nearly no configuration. Minimega also includes tools for simple cluster management, as well as tools for creating Linux based virtual machine images.", + "laborHours": 399334.4, + "name": "minimega", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandia-minimega/minimega", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "New to version 2.0 of Albany is the development of equations sets for specific application areas. These are independent research and development efforts that have chosen to use Albany as their software deployment vehicle. Because of synergies between the projects, they remain in the same code repository and are all releasing together as the Albany software.", + "laborHours": 364222.4, + "name": "Albany 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gahansen/Albany", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "TriBITS is a configuration, build, test, and reporting system that uses the Kitware open-source CMake/CTest/CDash system. TriBITS contains a number of custom CMake/CTest scripts and python scripts that extend the functionality of the out-of-the-box CMake/CTest/CDash system.", + "laborHours": 8344830.4, + "name": "TriBITS (Tribal Build, Integrate, and Test System)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "exodus.py is a Python wrapper of the open source Exodusll API intended for efficient pre-and post-processing finite element model data stored in the Exodusll file format.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "exodus.py", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "A framework for modeling and simulating biological neural systems", + "laborHours": 111902.4, + "languages": [ + "Java", + "C++", + "C", + "Python" + ], + "name": "Neurons to Algorithms", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/n2a", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "High Performance Computing (HPC) systems generate millions of inter-related event log lines per day from thousands of computers, providing feedback on both successful and unsuccessful operations within the system. Thorough analysis of these logs is often required for root cause analysis of problems and tuning for greatest performance. This \"app\" for the \"Gnawts\" log analysis software (http://www.gnawts.com) facilitates faster and deeper insights into HPC system logs.", + "laborHours": 4301.6, + "languages": [ + "CSS", + "Perl", + "HTML", + "Korn shell", + "JavaScript", + "Python" + ], + "name": "Gnawts", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gnawts", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "In the drive to make exascale computing a reality, significant effort is being invested in efficiently implementing and improving current numerical algorithms on various vendors' newest testbeds acquired by DOE's Advanced Simulation and Computing program. Porting large-scale applications to these testbeds is prohibitive in labor and time. Instead, it is more advantageous to run small-scale programs that capture the essence of the large-scale application and that can be more easily modified, improved, and distributed to other collaborators focused on hardware/software co-design. These small-scale applications are called miniapps are are being developed under the aegis of the Mantevo project.", + "laborHours": 6490.4, + "languages": [ + "C", + "Fortran", + "Python" + ], + "name": "miniSMAC2D", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniSMAC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This particular consortium implementation of the software integration infrastructure will, in large part, refactor portions of the Rocstar multiphysics infrastructure. Development of this infrastructure originated at the University of Illinois DOE ASCI Center for Simulation of Advanced Rockets (CSAR) to support the center's massively parallel multiphysics simulation application, Rocstar, and has continued at IllinoisRocstar, a small company formed near the end of the University-based program. IllinoisRocstar is now licensing these new developments as free, open source, in hopes to help improve their own and others' access to infrastructure which can be readily utilized in developing coupled or composite software systems; with particular attention to more rapid production and utilization of multiphysics applications in the HPC environment. There are two major pieces to the consortium implementation, the Application Component Toolkit (ACT), and the Multiphysics Application Coupling Toolkit (MPACT). The current development focus is the ACT, which is (will be) the substrate for MPACT. The ACT itself is built up from the components described in the technical approach. In particular, the ACT has the following major components: 1.The Component Object Manager (COM): The COM package provides encapsulation of user applications, and their data. COM also provides the inter-component function call mechanism. 2.The System Integration Manager (SIM): The SIM package provides constructs and mechanisms for orchestrating composite systems of multiply integrated pieces.", + "laborHours": 113452.8, + "name": "Multiphysics Application Coupling Toolkit", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IllinoisRocstar/IMPACT", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Framework for Network Co-Simulation (FNCS) uses a federated approach to integrate simulations which may have differing time scales. Special consideration is given to integration with a communication network simulation such that inter-simulation messages may be optionally routed through and delayed by such a simulation. In addition, FNCS uses novel time synchronization algorithms to accelerate co-simulation including the application of speculative multithreading. FNCS accomplishes all of these improvements with minimal end user intervention. Simulations can be integrated using FNCS while maintaining their original model input files simply by linking with the FNCS library and making appropriate calls into the FNCS API.", + "laborHours": 38592.8, + "name": "Framework for Network Co-Simulation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/FNCS/fncs/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FNCS/fncs", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This library is an implementation of the Sparse Approximate Matrix Multiplication (SpAMM) algorithm introduced. It provides a matrix data type, and an approximate matrix product, which exhibits linear scaling computational complexity for matrices with decay. The product error and the performance of the multiply can be tuned by choosing an appropriate tolerance. The library can be compiled for serial execution or parallel execution on shared memory systems with an OpenMP capable compiler", + "laborHours": 588726.4, + "name": "spammpack, Version 2013-06-18", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FreeON/spammpack", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The Multiphysics Object Oriented Simulation Environment (MOOSE) software library developed at Idaho National Laboratory is a tool. MOOSE, like other tools, doesn't actually complete a task. Instead, MOOSE seeks to reduce the effort required to create engineering simulation applications. MOOSE itself is a software library: a blank canvas upon which you write equations and then MOOSE can help you solve them. MOOSE is comparable to a spreadsheet application. A spreadsheet, by itself, doesn't do anything. Only once equations are entered into it will a spreadsheet application compute anything. Such is the same for MOOSE. An engineer or scientist can utilize the equation solvers within MOOSE to solve equations related to their area of study. For instance, a geomechanical scientist can input equations related to water flow in underground reservoirs and MOOSE can solve those equations to give the scientist an idea of how water could move over time. An engineer might input equations related to the forces in steel beams in order to understand the load bearing capacity of a bridge. Because MOOSE is a blank canvas it can be useful in many scientific and engineering pursuits.", + "laborHours": 1085021.6, + "languages": [], + "name": "Multiphysics Object Oriented Simulation Environment", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/moose", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GridOPTICS Software System (GOSS) is a middleware that facilitates creation of new, modular and flexible operational and planning platforms that can meet the challenges of the next generation power grid. GOSS enables Department of Energy, power system utilities, and vendors to build better tools faster. GOSS makes it possible to integrate Future Power Grid Initiative software products/prototypes into existing power grid software systems, including the PNNL PowerNet and EIOC environments. GOSS is designed to allow power grid applications developed for different underlying software platforms installed in different utilities to communicate with ease. This can be done in compliance with existing security and data sharing policies between the utilities. GOSS not only supports one-to-one data transfer between applications, but also publisher/subscriber scheme. To support interoperability requirements of future EMS, GOSS is designed for CIM compliance. In addition to this, it supports authentication and authorization capabilities to protect the system from cyber threats. In summary, the contributions of the GOSS middleware are as follows: A platform to support future EMS development. A middleware that promotes interoperability between power grid applications. A distributed architecture that separates data sources from power grid applications. Support for data exchange with either one-to-one or publisher/subscriber interfaces. An authentication and authorization scheme for limiting the access to data between utilities.", + "laborHours": 27724.8, + "name": "GridOPTICS Software System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/craig8/GOSS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Support Vector Machines (SVM) is a popular machine learning technique, which has been applied to a wide range of domains such as science, finance, and social networks for supervised learning. MaTEx undertakes the challenge of designing a scalable parallel SVM training algorithm for large scale systems, which includes commodity multi-core machines, tightly connected supercomputers and cloud computing systems. Several techniques are proposed for improved speed and memory space usage including adaptive and aggressive elimination of samples for faster convergence , and sparse format representation of data samples. Several heuristics for earliest possible to lazy elimination of non-contributing samples are considered in MaTEx. In many cases, where an early sample elimination might result in a false positive, low overhead mechanisms for reconstruction of key data structures are proposed. The proposed algorithm and heuristics are implemented and evaluated on various publicly available datasets", + "laborHours": 647474.4, + "name": "Machine Learning Toolkit for Extreme Scale", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/matex-org/matex/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/matex-org/matex", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Modern processors offer a wide range of control and measurement features. While those are traditionally accessed through libraries like PAPI, some newer features no longer follow the traditional model of counters that can be used to only read the state of the processor. For example, Precise Event Based Sampling (PEBS) can generate records that requires a kernel memory for storage. Additionally, new features like power capping and thermal control require similar new access methods. All of these features are ultimately controlled through Model Specific Registers (MSRs). We therefore need new mechanisms to make such features available to tools and ultimately to the user. libMSR provides a convenient interface to access MSRs and to allow tools to utilize their full functionality.", + "laborHours": 6232.0, + "name": "libMSR library and msr-safe kernel module", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/libmsr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This package inplements a Lua interface to linux containers system calls, such as unshare(2) and chroot(2)", + "laborHours": 0.0, + "name": "Lua modules for linux containers", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/grondo/lua-containers", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This package implements a Lua interface to the LLNL hostlist routines, and includes a hostlist command oine utility based on the lua hostlist library.", + "laborHours": 1930.4, + "name": "Luna Hostlist Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/grondo/lua-hostlist", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "AutomaDeD is a tool that automatically diagnoses performance and correctness faults in MPI applications. It creates time and control-flow models of processes in an MPI program, and when a failure occus, these models are analyzed probabilistically to find the origin of the failure. The output of the tool is MPI processes ranked by the abnormality degree and regions of code where faults are first manifested. The granularity of code region is an MPI call or a computation region between two MPI calls.", + "laborHours": 6308.0, + "name": "Automata-based Debugging for Dissimilar Parallel Tasks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/automaDeD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The \"Callpath Library\" is a software abstraction layer over a number of stack tracing utilities. It allows tool develoopers to conveniently represent and mNipulate call paths gathered fro U. Wisconsin's Stackwalker API and GNU Backtrace.", + "laborHours": 699.2, + "name": "Callpath Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/callpath", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "perf-dump is a library for dumping performance data in much the same way physics simulations dump checkpoints. It records per-process, per-timestep, per-phase, and per-thread performance counter data and dumps this large data periodically into an HDF5 data file.", + "laborHours": 334.4, + "name": "perf-dump", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/perf-dump", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-02-09" + }, + "description": "The HPC software ecosystem is growing larger and more complex, but software distribution mechanisms have not kept up with this trend. Tools, Libraries, and applications need to run on multiple platforms and build with multiple compliers. Increasingly, packages leverage common software components, and building any one component requires building all of its dependencies. In HPC environments, ABI-incompatible interfaces (likeMPI), binary-incompatible compilers, and cross-compiled environments converge to make the build process a combinatoric nightmare. This obstacle deters many users from adopting useful tools, and others waste countless hours building and rebuilding tools. Many package managers exist to solve these problems for typical desktop environments, but none suits the unique needs of supercomputing facilities or users. To address these problems, we have Spack, a package manager that eases the task of managing software for end-users, across multiple platforms, package versions, compilers, and ABI incompatibilities.", + "laborHours": 169312.8, + "languages": [], + "name": "Spack: the Supercomputing Package Manager", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spack/spack", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Fast Global File Status (FGFS) is a system software package that implimints a scalable mechanism to retrieve file information, such as its degree of distribution or replication and consistency.", + "laborHours": 6186.4, + "name": "Fast Global File Status", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/fastglobalfilestatus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MPI_T is an interface for tools introduced in the 3.0 version of MPI. The interface provides mechanisms for tools to access and set performance and control variables that are exposed by an MPI implementation. We have developed an MPI_T tool suite to provide a first set of tools exploiting the new interface and to get tool writers started on the path to more sophisticated support.", + "laborHours": 1033.6, + "name": "The LLNL MPI_Tool Suite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/mpi-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-07-23" + }, + "description": "UPC++ is a Partitioned Global Address Space (PGAS) extension for C++, with three main objectives: 1) to provide an object-oriented PGAS programming model in the context of the popular C++ language; 2) to add useful parallel programming idioms unavailable in UPC, such as asynchronous remote function invocation and multidimensional arrays, to support complex scientific applications; 3) to offer an easy on-ramp to PGAS programming through interoperability with other existing parallel programming systems (e.g., MPI, OpenMP, CUDA). UPC++ includes two main features beyond UPC: 1) One of the major limitations of UPC in the context of DOE application is the relatively weak notion of multidimensional arrays, which it inherited from C. To remedy this problem in UPC++, we included a multidimensional domain and array library based on that of Titanium. Titanium's library is similar to Chapel's dense and strided domains, as both were inspired by the dense and strided regions and arrays in ZPL. 2) Another feature provided by UPC++ but not by UPC is remote function invocation, which is inspired by Phalanx, X10, Habanero-C, and C++11. The user may start an asynchronous remote function invocation with the following syntax: \"async(place)(function, args...);\". UPC++ provides two programming constructs for specifying dynamic dependencies among tasks: 1) event-driven execution as in Phalanx and Habanero-C; 2) finish-async as in X10. We implemented UPC++ with a \"compiler-free\" approach using C++ templates and runtime libraries. The UPC++ front-end consists of a set of C++ header files that enables the C++ compiler to \"translate\" UPC++ features in a user program to runtime library calls. In particular, we use templates and operator overloading to customize the behavior of UPC++ types.\n\nThis software package has been replaced with UPCC++ V 1.0", + "laborHours": 20702.4, + "languages": [], + "name": "UPC++", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/berkeleylab/upcxx/src/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upcxx.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The SEED platform is expected to be a building energy performance data management tool that provides federal, state and local governments, building owners and operators with an easy, flexible and cost-effective method to collect information about groups of buildings, oversee compliance with energy disclosure laws and demonstrate the economic and environmental benefits of energy efficiency. It will allow users to leverage a local application to manage data disclosure and large data sets without the IT investment of developing custom applications. The first users of SEED will be agencies that need to collect, store, and report/share large data sets generated by benchmarking, energy auditing, retro-commissioning or retrofitting of many buildings. Similarly, building owners and operators will use SEED to manage their own energy data in a common format and centralized location. SEED users will also control the disclosure of their information for compliance requirements, recognition programs such as ENERGY STAR, or data sharing with the Buildings Performance Database and/or other third parties at their discretion.", + "laborHours": 81031.2, + "name": "Standard Energy Efficiency Data Platform", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/SEED-platform/seed/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SEED-platform/seed", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Hone sensors are packet-process correlation engines that log the relationships between applications and the communications they are responsible for. Hone sensors are available for a variety of platforms including Linux, Windows, and MacOSX. Hone sensors are designed to help analysts understand the meaning of communications on a deeper level by associating the origin or destination process to the communication. They do this by tracing communications on a per-packet basis, through the kernel of the operating system to determine their ultimate source/destination on the monitored machine.", + "laborHours": 3252.8, + "name": "The Open Host Network Packet Process Correlator for Windows", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/HoneProject/Windows-Sensor/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HoneProject/Windows-Sensor", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The ADARA software is a collection of programs which gather neutron scattering data from multiple detector banks, multiplex the data into a single stream and distribute that stream to analysis, reduction and translation utilities in real-time.", + "laborHours": 26280.8, + "name": "ADARA", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ADARA-Neutrons/adara", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Set of scripts (Python and Bash) to help users configure, run, and benchmark Hadoop clusters on ORNL computing infrastructure.", + "laborHours": 304.0, + "name": "Spot-Hadoop", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jhorey/SpotHadoop", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Data reduction software for the Oak Ridge National Laboratory Spallation Neutron Source's Magnetism Reflectometer beam line 4A, used to extract reflectivity, off-specular and GISANS scattering from raw data in NeXus file format. The package consists of a Python library for the extraction and a Qt4 based graphical user interface to work with the data.", + "laborHours": 31631.2, + "name": "QuickNXS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aglavic/quicknxs", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Chisel is a new open-source hardware construction language developed at UC Berkeley that supports advanced hardware design using highly parameterized generators and layered domain-specific hardware languages. Chisel is embedded in the Scala programming language, which raises the level of hardware design abstraction by providing concepts including object orientation, functional programming, parameterized types, and type inference. From the same source, Chisel can generate a high-speed C++-based cycle-accurate software simulator, or low-level Verilog designed to pass on to standard ASIC or FPGA tools for synthesis and place and route.", + "laborHours": 16233.6, + "name": "Constructing Hardware in a Scale Embedded Language", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ucb-bar/chisel/blob/master/src/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ucb-bar/chisel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Recent advancements in technology scaling have shown a trend towards greater integration with large-scale chips containing thousands of processors connected to memories and other I/O devices using non-trivial network topologies. Software simulation proves insufficient to study the tradeoffs in such complex systems due to slow execution time, whereas hardware RTL development is too time-consuming. We present OpenSoC Fabric, an on-chip network generation infrastructure which aims to provide a parameterizable and powerful on-chip network generator for evaluating future high performance computing architectures based on SoC technology. OpenSoC Fabric leverages a new hardware DSL, Chisel, which contains powerful abstractions provided by its base language, Scala, and generates both software (C++) and hardware (Verilog) models from a single code base. The OpenSoC Fabric2 infrastructure is modeled after existing state-of-the-art simulators, offers large and powerful collections of configuration options, and follows object-oriented design and functional programming to make functionality extension as easy as possible.", + "laborHours": 2888.0, + "name": "OpenSoC Fabric", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LBL-CoDEx/OpenSoCFabric/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-CoDEx/OpenSoCFabric", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kindrew@jlab.org" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This library provides a library containing highly optimized Wilson-Dslash, Wilson Clover operator and Krylov subspace solvers for Lattice QCD simulations. The library is targeted at Intel(R) Xeon Phi(tm), and Intel(R) Xeon(tm) processors.", + "laborHours": 70041.6, + "name": "QCD For Intel(R) Xeon Phi(tm) and Xeon(tm) processors", + "organization": "Thomas Jefferson National Accelerator Facility (TJNAF)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/JeffersonLab/qphix/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JeffersonLab/qphix.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Thomas Jefferson National Accelerator Facility (TJNAF)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A series of software programs that enables students to progress from completely unsecured control of devices to control that protects network commands with authentication, integrity and confidentiality. The working example provided is for turning LED lights on and off on a Raspberry Pi computer.", + "laborHours": 304.0, + "name": "CyPhyTown", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNLgov/cyPhyTown/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNLgov/cyPhyTown", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"The soft costs of solar \u2014 costs not associated with hardware \u2014 remain stubbornly high. Among the biggest soft costs are those associated with inefficiencies in local permitting and inspection. A study by the National Renewable Energy Laboratory and Lawrence Berkeley National Laboratory estimates that these costs add an average of $0.22/W per residential installation. This project helps reduce non-hardware/balance of system (BOS) costs by creating and maintaining a free and available site of permitting requirements and solar system verification software that installers can use to reduce time, capital, and resource investments in tracking permitting requirements. Software tools to identify best permitting practices can enable government stakeholders to optimize their permitting process and remove superfluous costs and requirements. Like \"\"a Wikipedia for solar permitting\"\", users can add, edit, delete, and update information for a given jurisdiction. We incentivize this crowdsourcing approach by recognizing users for their contributions in the form of SEO benefits to their company or organization by linking back to users' websites.\"", + "laborHours": 113817.6, + "name": "The National Solar Permitting Database", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/solarpermit/solarpermit", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "procmon performs large-scale monitoring, data collection, and analysis of user processes running on Linux systems. It is intended to be used to aid in performing an automated workload analysis of very large scale systems, but may also be useful for live monitoring of the running processes on large scale systems.", + "laborHours": 17358.4, + "name": "procmon", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/berkeleylab/nersc-procmon/src/c6e67d63e7c9c24f85a46b6d8965b8c615097edc/LICENSE?at=master&fileviewer=file-view-default", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/nersc-procmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "F3D is written in OpenCL, so it achieve[sic] platform-portable parallelism on modern mutli-core CPUs and many-core GPUs. The interface and mechanims to access F3D core are written in Java as a plugin for Fiji/ImageJ to deliver several key image-processing algorithms necessary to remove artifacts from micro-tomography data. The algorithms consist of data parallel aware filters that can efficiently utilizes[sic] resources and can work on out of core datasets and scale efficiently across multiple accelerators. Optimizing for data parallel filters, streaming out of core datasets, and efficient resource and memory and data managements over complex execution sequence of filters greatly expedites any scientific workflow with image processing requirements. F3D performs several different types of 3D image processing operations, such as non-linear filtering using bilateral filtering and/or median filtering and/or morphological operators (MM). F3D gray-level MM operators are one-pass constant time methods that can perform morphological transformations with a line-structuring element oriented in discrete directions. Additionally, MM operators can be applied to gray-scale images, and consist of two parts: (a) a reference shape or structuring element, which is translated over the image, and (b) a mechanism, or operation, that defines the comparisons to be performed between the image and the structuring element. This tool provides a critical component within many complex pipelines such as those for performing automated segmentation of image stacks. F3D is also called a \"descendent\" of Quant-CT, another software we developed in the past. These two modules are to be integrated in a next version. Further details were reported in: D.M. Ushizima, T. Perciano, H. Krishnan, B. Loring, H. Bale, D. Parkinson, and J. Sethian. Structure recognition from high-resolution images of ceramic composites. IEEE International Conference on Big Data, October 2014.", + "laborHours": 1869.6, + "name": "F3D Image Processing and Analysis for Many - and Multi-core Platforms", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/CameraIA/F3D/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CameraIA/F3D", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This Drupal metadata and documents capture and management system is a repository, used for maintenance of metadata which describe resources contributed to the AASG State Geothermal Data System. The repository also provides an archive for files that are not hosted by the agency contributing the resource. Data from all 50 state geological surveys is represented here, and is contributed in turn to the National Geothermal Data System.", + "laborHours": 6444.8, + "name": "AASG State Geothermal Data Repository for the National Geothermal Data System.", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/metadata-repository", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is an adaptation of the pre-existing Scimark benchmark code to a variety of Python and Lua implementations. It also measures performance of the Fparser expression parser and C and C++ code on a variety of simple scientific expressions.", + "laborHours": 5654.4, + "name": "Python/Lua Benchmarks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/lebusby/splb/src/e1b801db07cbb8fd0eab2a50fdb3b1f25906fbef/Copyright", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/lebusby/splb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GRAPE is a tool for managing software project workflows for the Git version control system. It provides a suite of tools to simplify and configure branch based development, integration with a project's testing suite, and integration with the Atlassian Stash repository hosting tool.", + "laborHours": 15139.2, + "name": "Git Replacement for the", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/GRAPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Hardware advancements such as Intel's PEBS and AMD's IBS, as well as software developments such as the perf_event API in Linux have made available the acquisition of memory access samples with performance information. MemAxes is a visualization and analysis tool for memory access sample data. By mapping the samples to their associated code, variables, node topology, and application dataset, MemAxes provides intuitive views of the data.", + "laborHours": 5198.4, + "name": "MemAxes Visualization Software", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/scalability-llnl/MemAxes", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "ZFP is a library for lossy compression of single- and double-precision floating-point data. One of the unique features of ZFP is its support for fixed-rate compression, which enables random read and write access at the granularity of small blocks of values. Using a C++ interface, this allows declaring compressed arrays (1D, 2D, and 3D arrays are supported) that through operator overloading can be treated just like conventional, uncompressed arrays, but which allow the user to specify the exact number of bits to allocate to the array. ZFP also has variable-rate fixed-precision and fixed-accuracy modes, which allow the user to specify a tolerance on the relative or absolute error.", + "laborHours": 9272.0, + "languages": [], + "name": "Fixed-rate compressed floating-point arrays", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/zfp/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ZFP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Large-scale systems like Sequoia allow running small numbers of very large (1M+ process) jobs, but their resource managers and schedulers do not allow large numbers of small (4, 8, 16, etc.) process jobs to run efficiently. Cram is a tool that allows users to launch many small MPI jobs within one large partition, and to overcome the limitations of current resource management software for large ensembles of jobs.", + "laborHours": 1824.0, + "name": "Cram", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/scalability-llnl/cram", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OpenSHMEM is a community effort to unifyt and standardize the SHMEM programming model. MPI (Message Passing Interface) is a well-known community standard for parallel programming using distributed memory. The most recen t release of MPI, version 3.0, was designed in part to support programming models like SHMEM.OSHMPI is an implementation of the OpenSHMEM standard using MPI-3 for the Linux operating system. It is the first implementation of SHMEM over MPI one-sided communication and has the potential to be widely adopted due to the portability and widely availability of Linux and MPI-3. OSHMPI has been tested on a variety of systems and implementations of MPI-3, includingInfiniBand clusters using MVAPICH2 and SGI shared-memory supercomputers using MPICH. Current support is limited to Linux but may be extended to Apple OSX if there is sufficient interest. The code is opensource via https://github.com/jeffhammond/oshmpi", + "laborHours": 15291.2, + "name": "OpenSHMEM over MPI-3", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeffhammond/oshmpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This program is a graphical user interface for measuring and performing inter-active analysis of physical unclonable functions (PUFs). It is intended for demonstration and education purposes. See license.txt for license details. The program features a PUF visualization that demonstrates how signatures differ between PUFs and how they exhibit noise over repeated measurements. A similarity scoreboard shows the user how close the current measurement is to the closest chip signatures in the database. Other metrics such as average noise and inter-chip Hamming distances are presented to the user. Randomness tests published in NIST SP 800-22 can be computed and displayed. Noise and inter-chip histograms for the sample of PUFs and repeated PUF measurements can be drawn.", + "laborHours": 2082.4, + "name": "Sandia PUF Analysis Tool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Domi (Greek for \"structure\") is a Trilinos package that provides support for multi-dimensional data arrays distributed over multiple processors of a high performance computing system. The software supports data arrays of arbitrary number of dimensions mapped to a multi-dimensional grid of processors. Domi provides local access to the data, as well as the ability to compute global quantities such as norms, maxima and minima. Data arrays can be constructed with boundary and communication padding, necessary for finite difference algorithms, and provides high-level methods for communicating data between processors to update these buffers. The distributed maps and vectors in Domi can be converted to the equivalent data structures in Epetra and Tpetra (both of which assume unstructured data), using view semantics when appropriate, for use with other Trilinos solvers.", + "laborHours": 10336.0, + "languages": [ + "CMake", + "C++" + ], + "name": "Domi", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Domi/blob/main/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Domi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software serves two purposes. The first purpose of the software is to prototype the Sandia High Performance Computing Power Application Programming Interface Specification effort. The specification can be found at http://powerapi.sandia.gov . Prototypes of the specification were developed in parallel with the development of the specification. Release of the prototype will be instructive to anyone who intends to implement the specification. More specifically, our vendor collaborators will benefit from the availability of the prototype. The second is in direct support of the PowerInsight power measurement device, which was co-developed with Penguin Computing. The software provides a cluster wide measurement capability enabled by the PowerInsight device. The software can be used by anyone who purchases a PowerInsight device. The software will allow the user to easily collect power and energy information of a node that is instrumented with PowerInsight. The software can also be used as an example prototype implementation of the High Performance Computing Power Application Programming Interface Specification.", + "laborHours": 40462.4, + "languages": [ + "C++", + "Shell", + "C", + "SWIG", + "Makefile", + "M4", + "Roff" + ], + "name": "Power API Prototype", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/power-api", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "The Percept software package is a collection of libraries and executables that provide tools for verifying computer simulations of engineering components and systems. Percept is useful for simulations using the finite element or finite volume methods on unstructured meshes. Percept includes API's for adaptive mesh refinement, geometry representation, the method of manufactured solutions, analysis of convergence including the convergence of vibrational eigenmodes, and metrics for analyzing the difference between fields represented on two different overlapping unstructured grids.", + "laborHours": 99560.0, + "languages": [ + "Mathematica", + "C++", + "Shell", + "C", + "CMake", + "Python" + ], + "name": "Percept", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/percept", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "WEC-Sim (Wave Energy Converter SIMulator) is a code developed by Sandia National Laboratories and the National Renewable Energy Laboratory to model wave energy converters (WECs) when they are subject to operational waves. The code is a time-domain modeling tool developed in MATLAB/Simulink using the multi-body dynamics solver SimMechanics. In WEC-Sim, WECs are modeled by connecting rigid bodies to one another with joint or constraint blocks from the WEC-Sim library. WEC-Sim is a publicly available, open-source code to model WECs.", + "laborHours": 3131.2, + "name": "WEC-Sim (Wave Energy Converter - SIMulator)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WEC-Sim/WEC-Sim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This software provides implementations of fast matrix multiplication algorithms. These algorithms perform fewer floating point operations than the classical cubic algorithm. The software uses code generation to automatically implement the fast algorithms based on high-level descriptions. The code serves two general purposes. The first is to demonstrate that these fast algorithms can out-perform vendor matrix multiplication algorithms for modest problem sizes on a single machine. The second is to rapidly prototype many variations of fast matrix multiplication algorithms to encourage future research in this area. The implementations target sequential and shared memory parallel execution.", + "laborHours": 79724.0, + "languages": [ + "Objective-C", + "C++", + "Shell", + "Roff", + "MATLAB", + "Python" + ], + "name": "fast-matmul", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fast-matmul", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SCOT cyber security team enhancement tool that coordinates activities, captures knowledge, and serves as a platform to automate time-consuming tasks that a cyber security team needs to perform in its daily operations.", + "laborHours": 370393.6, + "name": "Sandia Cyber Omni Tracker", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/scot/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/scot", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Oxide is a modular framework for feature extraction and analysis of executable files. Oxide is useful in a variety of reverse engineering and categorization tasks relating to executable content.", + "laborHours": 10244.8, + "languages": [ + "Python" + ], + "name": "Oxide", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Oxide", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Doubly Distributed Transactions (D2T) offers a technique for managing operations from a set of parallel clients with a collection of distributed services. It detects and manages faults. Example code with a test harness is also provided", + "laborHours": 61651.2, + "languages": [ + "C++", + "C" + ], + "name": "Doubly Distributed Transactions", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/d2t", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Toyplot integrates high quality interactive, animated plotting capabilities into web browsers using the Python programming language.", + "laborHours": 15032.8, + "name": "toyplot", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/toyplot", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "Pike is a software library for coupling and solving multiphysics applications. It provides basic interfaces and utilities for performing code-to-code coupling. It provides simple \"black-box\" Picard iteration methods for solving the coupled system of equations including Jacobi and Gauss-Seidel solvers. Pike was developed originally to couple neutronics and thermal fluids codes to simulate a light water nuclear reactor for the Consortium for Simulation of Light-water Reactors (CASL) DOE Energy Innovation Hub. The Pike library contains no physics and just provides interfaces and utilities for coupling codes. It will be released open source under a BSD license as part of the Trilinos solver framework (trilinos.org) which is also BSD. This code provides capabilities similar to other open source multiphysics coupling libraries such as LIME, AMP, and MOOSE.", + "laborHours": 4043.2, + "languages": [ + "CMake", + "C++", + "Shell" + ], + "name": "Physics Integration KErnels (PIKE)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Pike", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Django app for tracking individual state's progress in their contributions to the National Geothermal Data System.", + "laborHours": 561214.4, + "name": "AASG Geothermal Data submissions tracking application and site.", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/aasgtrack/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/aasgtrack", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GitHub repositories for creating and managing information exchanges (content models) for use in the NGDS and larger USGIN systems.", + "laborHours": 243.2, + "name": "Information Exchange development forums", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/usginmodels/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/usginmodels", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This web site provides information related to service profiles and implementation in development for the US Geoscience information network (USGIN). It is meant to be a site where developers can learn about the standard in use, the objectives of the application profiles being developed, software being used or tested for implementation of services, and details about particular implementations. Forums are provided for asking questions about the services, profiles, and implemenation issues.", + "laborHours": 268842.4, + "name": "USGIN Lab site", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/lab-usgin-site", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This wiki page provides the public with all specifications needed to create a new information exchange (content model package).", + "laborHours": 243.2, + "name": "Defining a new information exchange", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/usginmodels/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/usginmodels", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This wiki page provides the public with all specifications needed to create a new spreadsheet (workbook) implementation of an information exchange, so that it conforms and functions properly with NGDS validation tools.", + "laborHours": 4636.0, + "name": "Content Model Guidelines", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/ContentModelCMS/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/ContentModelCMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is an executable python script which offers two different conversions for well log data: 1) Conversion from a BoreholeLASLogData.xls model to a LAS version 2.0 formatted XML file. 2) Conversion from a LAS 2.0 formatted XML file to an entry in the WellLog Content Model. Example templates for BoreholeLASLogData.xls and WellLogsTemplate.xls can be found in the package after download.", + "laborHours": 228.0, + "name": "Well Log ETL tool", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/WellLogDataTools", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is a Node.js command line utility for scraping XML metadata from CSW and WFS, downloading linkage data from CSW and WFS, pinging hosts and returning status codes, pinging data linkages and returning status codes, writing ping status to CSV files, and uploading data to Amazon S3.", + "laborHours": 790.4, + "name": "NGDS Data Archiver", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ngds/data-archiver", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Django application providing a user-interface for building a file and metadata management system. Operates in conjunction with https://github.com/usgin/metadata-server.", + "laborHours": 6444.8, + "name": "Metadata staging tools", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/metadata-repository", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Conduit is a C++ software library that helps software developers with data representation and data exchange in scientific simulations", + "laborHours": 94012.0, + "name": "Conduit - Scientific Data Exchange Library for HPC Simulations", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/conduit/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/conduit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This python script, available from ESRI and modified here, checks a server at specified intervals to ensure that web services remain up and running. If any are found to be off, they are automatically turned back on.", + "laborHours": 45.6, + "name": "Web service performance script", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ngds/CheckRunningArcGISservices/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ngds/CheckRunningArcGISservices", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is a repository for tracking issues with metadata in the National Geothermal Data System. Each page representing a resource in NGDS has a link for the user to report issues with the metadata. NGDS teams also use this issue tracker to indicate problems and manage their resolution.", + "laborHours": 0.0, + "name": "Data Quality Reporting", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ngds/metadata-issues/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ngds/metadata-issues", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OpenLayers application to help search for features in a WFS. 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The targeted usage of this module is for non-NW applications that support work-for-others in the multiphysics energy sector.", + "laborHours": 50388.0, + "name": "Nalu", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/spdomin/Nalu/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spdomin/Nalu", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is a Python API for interacting with USGIN Content Models.", + "laborHours": 243.2, + "name": "USGIN content models API", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/usginmodels/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/usginmodels", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is a Python API for interacting with USGIN Content Models.", + "laborHours": 4636.0, + "name": "Content Model Validator", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/ContentModelCMS/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/ContentModelCMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This site allows state data contributors to standardize their data in a USIGN content model, ensure that it meets all specifications, reprojects spatial data, and creates a geodatabase that is ready for web services deployment for tier 3 data.", + "laborHours": 5608.8, + "name": "Excel to NGDS Services Tool", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/ExcelToNGDSServiceTool", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Django application providing a user-interface for building a file and metadata management system. 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Also provides batch and real-time controllers which step the model and 1/0 through the time domain (or other discrete domain), and sample 1/0 drivers. This is a Framework library framework, and does not, itself, solve any problems or execute any modelling. The SeMe framework aids in development of models which operate on sequential information, such as time-series, where evaluation is based on prior results combined with new data for this iteration. Ha) applications in quality monitoring, and was developed as part of the CANARY-EDS software, where real-time water quality data is being analyzed", + "laborHours": 4772.8, + "languages": [ + "Java", + "Perl", + "HTML", + "TeX" + ], + "name": "Sequentially Executed Model Evaluation Framework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seme-framework", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SVF is a full featured OpenGL 3d framework that allows for rapid creation of complex visualizations. 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Some simple shapes (actors) are already created for you such as text, bordered text, radial text, text area, complex paths, NURBS paths, cube, disk, grid, plane, geometric shapes, and volumetric area. It also comes with various camera types for viewing that can be dragged, zoomed, and rotated. Picking or selecting items in the scene can be accomplished in various ways depending on your needs (raycasting or color picking.) The framework currently has functionality for tooltips, animation, actor pools, color gradients, 2d physics, text, 1d/2d/3d textures, children, blending, clipping planes, view frustum culling, custom shaders, and custom actor states", + "laborHours": 41602.4, + "name": "Sci-Vis Framework", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/svf/blob/master/svf-core/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/svf", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The FireHose Streaming Benchmarks are a suite of stream-processing benchmarks defined to enable comparison of streaming software and hardware, both quantitatively vis-a-vis the rate at which they can process data, and qualitatively by judging the effort involved to implement and run the benchmarks. 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The FireHose suite provides code for the generators, sample code for the analytics (which users are free to re-implement in their own custom frameworks), and a precise definition of each benchmark calculation.", + "laborHours": 2964.0, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "Python" + ], + "name": "FireHose Streaming Benchmarks", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/firehose", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "miniAMR is a \"miniapp\" which will be added to the Mantevo project. It provides a platform to experiment with different aspects of Adaptive Mesh Refinement (AMR). The calculations are performed on random data and the refinement is driven by simple objects moving through the mesh, so no real problem is solved. By having a small code that runs quickly, we can use to study different aspects of AMR and easily port the code to new testbed machines", + "laborHours": 10989.6, + "languages": [ + "Makefile", + "C" + ], + "name": "miniAMR", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniAMR", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.9" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "PathFinder is a graph search program, traversing a directed cyclic graph to find pathways between labeled nodes. Searches for paths through ordered sequences of labels are termed signatures. Determining the presence of signatures within one or more graphs is the primary function of Path Finder. Path Finder can work in either batch mode or interactively with an analyst. Results are limited to Path Finder whether or not a given signature is present in the graph(s).", + "laborHours": 7630.4, + "languages": [ + "Standard ML", + "ABC", + "Python" + ], + "name": "Path Finder", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PathFinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-05-14" + }, + "description": "This is an implementation of a VTK class that can read data from an ADIOS file. 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In order to better define regions of similarity among related protein structures, it is useful to detect the residue-residue correspondences among a set of pairwise structure alignments. Few codes exist for constructing a one-to-many, multiple sequence alignment derived from a set of structure alignments, and we perceived a need for creating a new tool for combing pairwise structure alignments that would allow for insertion of gaps in the reference structure.", + "laborHours": 243.2, + "name": "Combining Multiple Pairwise Structure-based Alignments", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/Protein", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "IBTopo is a set of perl modules and scripts that enable one to determine the network topology of an Infiniband network.", + "laborHours": 304.0, + "name": "IBTopo", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/ibtopo/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/ibtopo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ParFELAG is a parallel distributed memory C++ library for numerical upscaling of finite element discretizations. It provides optimal complesity algorithms ro build multilevel hierarchies and solvers that can be used for solving a wide class of partial differential equations (elliptic, hyperbolic, saddle point problems) on general unstructured mesh (under the assumption that the topology of the agglomerated entities is correct). Additionally, a novel multilevel solver for saddle point problems with divergence constraint is implemented.", + "laborHours": 31600.8, + "name": "Parallel Element Agglomeration Algebraic Multigrid and Upscaling Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/parelag", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Compare Gene Profiles (CGP) performs pairwise gene content comparisons among a relatively large set of related bacterial genomes. CGP performs pairwise BLAST among gene calls from a set of input genome and associated annotation files, and combines the results to generate lists of common genes, unique genes, homologs, and genes from each genome that differ substantially in length from corresponding genes in the other genomes. CGP is implemented in Python and runs in a Linux environment in serial or parallel mode.", + "laborHours": 1763.2, + "name": "Compare Gene Profiles", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/Genome", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Qspp is an agent-based stochastic simulation model of the Poliovirus Sabin-to-Mahoney transition. This code simulates a cell-to-cell model of Poliovirus replication. The model tracks genotypes (virus genomes) as they are replicated in cells, and as the cells burst and release particles into the medium of a culture dish. An inoculum is then taken from the pool of virions and is used to inoculate cells on a new dish. This process repeats. The Sabin genotype comprises the initial inoculum. Nucleotide positions that match the Sabin1 (vaccine strain) and Mahoney (wild type) genotypes, as well as the neurovirulent phenotype (from the literature) are enumerated as constants.", + "laborHours": 1915.2, + "name": "Sabin-to-Mahoney Transition Model of Quasispecies Replication", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/Virus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "ROL provides interfaces to and implementations of algorithms for gradient-based unconstrained and constrained optimization. ROL can be used to optimize the response of any client simulation code that evaluates scalar-valued response functions. If the client code can provide gradient information for the response function, ROL will take advantage of it, resulting in faster runtimes. ROL's interfaces are matrix-free, in other words ROL only uses evaluations of scalar-valued and vector-valued functions. ROL can be used to solve optimal design problems and inverse problems based on a variety of simulation software.", + "laborHours": 8344830.4, + "languages": [], + "name": "Rapid Optimization Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Python-ARM Radar Toolkit (Py-ART) is a collection of radar quality control and retrieval codes which all work on two unifying Python objects: the PyRadar and PyGrid objects. By building ingests to several popular radar formats and then abstracting the interface Py-ART greatly simplifies data processing over several other available utilities. In addition Py-ART makes use of Numpy arrays as its primary storage mechanism enabling use of existing and extensive community software tools.", + "laborHours": 159980.0, + "name": "Python-ARM Radar Toolkit", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/pyart", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2022-03-28" + }, + "description": "This is a general purpose math library implementing basic tensor algebra operations on NVidia GPU accelerators. This software is a tensor algebra library that can perform basic tensor algebra operations, including tensor contractions, tensor products, tensor additions, etc., on NVidia GPU accelerators, asynchronously with respect to the CPU host. It supports a simultaneous use of multiple NVidia GPUs. Each asynchronous API function returns a handle which can later be used for querying the completion of the corresponding tensor algebra operation on a specific GPU. The tensors participating in a particular tensor operation are assumed to be stored in local RAM of a node or GPU RAM. The main research area where this library can be utilized is the quantum many-body theory (e.g., in electronic structure theory).", + "laborHours": 19258.4, + "languages": [], + "name": "Tensor Algebra Library for NVidia Graphics Processing Units", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DmitryLyakh/TAL_SH", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SHOMS is a micro benchmark designed to test vendor implementations of the OpenSHMEM 1.1 spec. It seeks to test both bandwidth and latencies for small and large messages.", + "laborHours": 1276.8, + "name": "SHOMS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MattBBaker/shoms", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "STONIX is a program for configuring UNIX and Linux computer operating systems. It applies configurations based on the guidance from publicly accessible resources such as: NSA Guides, DISA STIGs, the Center for Internet Security (CIS), USGCB and vendor security documentation. STONIX is written in the Python programming language using the QT4 and PyQT4 libraries to provide a GUI. The code is designed to be easily extensible and customizable.", + "laborHours": 56878.4, + "name": "Stonix, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CSD-Public/stonix", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "brulilo is a Python package for building and evolving thermonuclear reaction networks, such as those used in astrophysical explosion calculations. It is very much a current work in progress, and much of the intended functionality is still under development. The main goal of brulilo is an easy-to-use code for quick calculations or post-processing, as well as a learning tool to test various implementations of solvers on both CPUs and GPUs. Currently, brulilo parses an input text file that specifies the reactions to be included in the network. The notation of the inputs are in the typical astrophysical notation; i.e. hydrogen burning to deuterium in the sun, \"p + p + e --> d + neutrino\", is given as \"p(p,)d.\" Each reaction is added to a list comprising the reaction network, and once completed, the network contains a list of all isotopes and reactions involved. brulilo then parses publicly available nuclear data (binding energy, spin, partition function data, etc.) for each isotope from the WebNucleo group's data at nucleo.ces.clemson.edu. Fits to reaction rate data for each reaction are obtained from the publicly available data provided by the Joint Institute for Nuclear Astrophysics' Reaclib database. Reverse reactions are calculated from detailed balance. The reaction network then consists of a sparse system of mathematically stiff ordinary differential equations (ODEs). Physically, \"stiffness\" here means that there are some reaction rates that are occurring much faster than others; the ratio of the fast to slow often being greater than 10^15 in astrophysics. Numerical integration of such systems typically involves implicit integration schemes, which brulilo will leverage from the scientific computing Python package, Numpy, as well as implement its own. There has recently been work from researchers at Oak Ridge National Lab who have found good results from applying quasi-equilibrium and quasi-asymptotic conditions to the stiff system of ODEs, which effectively remove some of the stiffness and allow for efficient explicit integration techniques to be used. The original intent of brulilo was to implement these stiffness-alleviating techniques with explicit integrators and compare the performance to traditional implicit integrations of the full stiff system. This is still underway, as the code is very much in an alpha-release state. Furthermore, explicit integrators are often much easier to parallelize than their implicit counterparts. brulilo will implement parallelization of these techniques, leveraging both the Python implementation of MPI, mpi4py, as well as highly parallelized versions targeted at GPUs with PyOpenCL and/or PyCUDA.", + "laborHours": 1743379.2, + "name": "brulilo, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cmsquared/brulilo/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmsquared/brulilo", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The intent of the software is eventually to become a middleware library to provide a cross platform interface for creating and managing a ramdisk. Eventually it will cover many platforms (*nix, Windows, Mac), and have the library written in several languages. At this point, the library is a functional python library for managing a Mac ramdisk. Some code is also included in how to use the library. Initial intended uses for the library: archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Provide a throw-away filesystem for unit testing filesystem related functionality. archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Improve compile time when building software.", + "laborHours": 3754.4, + "name": "ramdisk, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csd-dev-tools/ramdisk", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MATK provides basic functionality to facilitate model analysis within the Python computational environment. Model analysis setup within MATK includes: - define parameters - define observations - define model (python function) - define samplesets (sets of parameter combinations) Currently supported functionality includes: - forward model runs - Latin-Hypercube sampling of parameters - multi-dimensional parameter studies - parallel execution of parameter samples - model calibration using internal Levenberg-Marquardt algorithm - model calibration using lmfit package - model calibration using levmar package - Markov Chain Monte Carlo using pymc package MATK facilitates model analysis using: - scipy - calibration (scipy.optimize) - rpy2 - Python interface to R", + "laborHours": 54856.8, + "name": "Model Analysis ToolKit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dharp/MATK", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Streaming Canvas is an interactive data visualization tool for high dimensional data such as text documents. It allows the user to interactively analyze documents.", + "laborHours": 104226.4, + "name": "Streaming Canvas", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/aim-science-of-interaction/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/aim-science-of-interaction", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Vector extensions, such as SSE, have been part of the x86 CPU since the 1990s, with applications in graphics, signal processing, and scientific applications. Although many algorithms and applications can naturally benefit from automatic vectorization techniques, there are still many that are difficult to vectorize due to their dependence on irregular data structures, dense branch operations, or data dependencies. Sequence alignment, one of the most widely used operations in bioinformatics workflows, has a computational footprint that features complex data dependencies. The trend of widening vector registers adversely affects the state-of-the-art sequence alignment algorithm based on striped data layouts. Therefore, a novel SIMD implementation of a parallel scan-based sequence alignment algorithm that can better exploit wider SIMD units was implemented as part of the Parallel Sequence Alignment Library (parasail). Parasail features: Reference implementations of all known vectorized sequence alignment approaches. Implementations of Smith Waterman (SW), semi-global (SG), and Needleman Wunsch (NW) sequence alignment algorithms. Implementations across all modern CPU instruction sets including AVX2 and KNC. Language interfaces for C/C++ and Python.", + "laborHours": 589045.6, + "name": "Pairwise Sequence Alignment Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jeffdaily/parasail/blob/master/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeffdaily/parasail", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Shifter enables application virtualization or containerization in large-scale HPC environments. This technology decreases the effort to port applications to or between HPC sites while increasing reproducibility and scientific productivity. Shifter works by converting application/container images to a common format, and then leverages basic Linux functionality to make that image available to batch jobs run in the HPC environment.", + "laborHours": 13756.0, + "name": "shifter", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NERSC/shifter/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/shifter", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Tomopy is a Python toolbox to perform x-ray data processing, image reconstruction and data exchange tasks at synchrotron facilities. The dependencies of the software are currently as follows: -Python related python standard library (http://docs.python.org/2/library/) numpy (http://www.numpy.org/) scipy (http://scipy.org/) matplotlib (http://matplotlip.org/) sphinx (http://sphinx-doc.org) pil (http://www.pythonware.com/products/pil/) pyhdf (http://pysclint.sourceforge.net/pyhdf/) h5py (http://www.h5py.org) pywt (http://www.pybytes.com/pywavelets/) file.py (https://pyspec.svn.sourceforge.net/svnroot/pyspec/trunk/pyspec/ccd/files.py) -C/C++ related: gridec (anonymous?? C-code written back in 1997 that uses standard C library) fftw (http://www.fftw.org/) tomoRecon (multi-threaded C++ verion of gridrec. Author: Mark Rivers from APS. http://cars9.uchicago.edu/software/epics/tomoRecon.html) epics (http://www.aps.anl.gov/epics/)", + "laborHours": 9986.4, + "name": "Tomopy: A Python toolbox to perform X-Ray data proessing and image reconstruction.", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/tomopy/tomopy/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tomopy/tomopy", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The OpenSM Monitoring System includes a collection of diagnostic and monitoring tools for use on Infiniband networks. The information this system gathers is obtained from a service, which in turn is obtained directly from the OpenSM subnet manager.", + "laborHours": 34899.2, + "name": "OpenSM Monitoring System", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/meier/opensm-smt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Not Specified", + "laborHours": 39793.6, + "name": "Framework for Network Co-simulation v. 2.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GridOPTICS/FNCS/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GridOPTICS/FNCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Flume-plugins are plugins for Apache Flume, which are used for managing data transferred through Apache Flume.", + "laborHours": 592.8, + "name": "flume-plugins Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/flume-plugins/blob/master/DISCLAIMER", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chu11/flume-plugins", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "FileUtils provides a suite of tools to manage large datasets typically created by large parallel MPI applications. They are written in C and use standard POSIX I/Ocalls. The current suite consists of tools to copy, compare, remove, and list. The tools provide dramatic speedup over existing Linux tools, which often run as a single process.", + "laborHours": 18194.4, + "languages": [], + "name": "Distributed File System Utilities to Manage Large DatasetsVersion 0.5", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/hpc/mpifileutils/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/fileutils", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "FALCON has been developed to enable simulation of the tightly coupled fluid-rock behavior in hydrothermal and engineered geothermal system (EGS) reservoirs, targeting the dynamics of fracture stimulation, fluid flow, rock deformation, and heat transport in a single integrated code, with the ultimate goal of providing a tool that can be used to test the viability of EGS in the United States and worldwide. Reliable reservoir performance predictions of EGS systems require accurate and robust modeling for the coupled thermal\u00adhydrological\u00admechanical processes.", + "laborHours": 23043.2, + "languages": [], + "name": "Fracturing And Liquid CONvection", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/falcon", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A general particle library designed to run on next-generation hardware such as MICs and GPUs.", + "laborHours": 31342.4, + "name": "Libparty, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/libparty", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kindrew@jlab.org" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A simple code-generator to generate the low level code kernels used by the QPhiX Library for Lattice QCD. Generates Kernels for Wilson-Dslash, and Wilson-Clover kernels. Can be reused to write other optimized kernels for Intel Xeon Phi(tm), Intel Xeon(tm) and potentially other architectures.", + "laborHours": 5897.6, + "name": "QPhiX Code Generator", + "organization": "Thomas Jefferson National Accelerator Facility (TJNAF)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/JeffersonLab/qphix-codegen/blob/master/codegen/LICENSE.markdown", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JeffersonLab/qphix-codegen", + "status": "Production", + "tags": [ + "DOE CODE", + "Thomas Jefferson National Accelerator Facility (TJNAF)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MACSio is a Multi-purpose, Application-Centric, Scalable I/O proxy application. It is designed to support a number of goals with respect to parallel I/O performance testing and benchmarking including the ability to test and compare various I/O libraries and I/O paradigms, to predict scalable performance of real applications and to help identify where improvements in I/O performance can be made within the HPC I/O software stack.", + "laborHours": 36814.4, + "name": "Multi-Purpose, Application-Centric, Scalable I/O Proxy Application", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MACSio", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"MetaGenomic Assembly by Merging\" (MeGAMerge)Is a novel method of merging of multiple genomic assembly or long read data sources for assembly by use of internal trimming/filtering of data, followed by use of two 3rd party tools to merge data by overlap based assembly.", + "laborHours": 288.8, + "name": "MetaGenomic Assembly by Merging (MeGAMerge)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/MeGAMerge/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MeGAMerge", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Edge Bioinformatics is a developmental bioinformatics and data management platform which seeks to supply laboratories with bioinformatics pipelines for analyzing data associated with common samples case goals. Edge Bioinformatics enables sequencing as a solution and forward-deployed situations where human-resources, space, bandwidth, and time are limited. The Edge bioinformatics pipeline was designed based on following USE CASES and specific to illumina sequencing reads. 1. Assay performance adjudication (PCR): Analysis of an existing PCR assay in a genomic context, and automated design of a new assay to resolve conflicting results; 2. Clinical presentation with extreme symptoms: Characterization of a known pathogen or co-infection with a. Novel emerging disease outbreak or b. Environmental surveillance", + "laborHours": 155587.2, + "name": "Edge Bioinformatics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/edge", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "One major challenge in the field of shotgun metagenomics is the accurate identification of the organisms present within the community, based on classification of short sequence reads. Though microbial community profiling methods have emerged to attempt to rapidly classify the millions of reads output from contemporary sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling tool with significantly smaller FDR, which is also capable of classifying never-before seen genomes into the appropriate parent taxa.The algorithm is based upon three primary computational phases: (I) genomic decomposition into bit vectors, (II) bit vector intersections to identify shared regions, and (III) bit vector subtractions to remove shared regions and reveal unique, signature regions. In the Decomposition phase, genomic data is first masked to highlight only the valid (non-ambiguous) regions and then decomposed into overlapping 24-mers. The k-mers are sorted along with their start positions, de-replicated, and then prefixed, to minimize data duplication. The prefixes are indexed and an identical data structure is created for the start positions to mimic that of the k-mer data structure. During the Intersection phase -- which is the most computationally intensive phase -- as an all-vs-all comparison is made, the number of comparisons is first reduced by four methods: (a) Prefix restriction, (b) Overlap detection, (c) Overlap restriction, and (d) Result recording. In Prefix restriction, only k-mers of the same prefix are compared. Within that group, potential overlap of k-mer suffixes that would result in a non-empty set intersection are screened for. If such an overlap exists, the region which intersects is first reduced by performing a binary search of the boundary suffixes of the smaller set into the larger set, which defines the limits of the zipper-based intersection process. Rather than recording the actual k-mers of the intersection, another data structure of identical \"shape\" is created which consists of only bit vectors so that only a 1 or 0 will be stored in the location of the k-mer suffix that was found in the intersection. This reduces the amount of data generated and stored considerably. During the Subtraction phase, relevant intersection bitmasks are first unionized together to form a single bitmask which is then applied over the original genome to reveal only those regions of the genome that are unique. These regions are then exported to disk in FASTA format and used in the application of determining the constituents of an unknown metagenomic community.", + "laborHours": 5168.0, + "name": "GOTTCHA, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/GOTTCHA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "One major challenge in the field of shotgun metagenomics is the accurate identification of the organisms present within the community, based on classification of short sequence reads. Though microbial community profiling methods have emerged to attempt to rapidly classify the millions of reads output from contemporary sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling tool with significantly smaller FDR, which is also capable of classifying never-before seen genomes into the appropriate parent taxa.The algorithm is based upon three primary computational phases: (I) genomic decomposition into bit vectors, (II) bit vector intersections to identify shared regions, and (III) bit vector subtractions to remove shared regions and reveal unique, signature regions.In the Decomposition phase, genomic data is first masked to highlight only the valid (non-ambiguous) regions and then decomposed into overlapping 24-mers. The k-mers are sorted along with their start positions, de-replicated, and then prefixed, to minimize data duplication. The prefixes are indexed and an identical data structure is created for the start positions to mimic that of the k-mer data structure.During the Intersection phase -- which is the most computationally intensive phase -- as an all-vs-all comparison is made, the number of comparisons is first reduced by four methods: (a) Prefix restriction, (b) Overlap detection, (c) Overlap restriction, and (d) Result recording. In Prefix restriction, only k-mers of the same prefix are compared. Within that group, potential overlap of k-mer suffixes that would result in a non-empty set intersection are screened for. If such an overlap exists, the region which intersects is first reduced by performing a binary search of the boundary suffixes of the smaller set into the larger set, which defines the limits of the zipper-based intersection process. Rather than recording the actual k-mers of the intersection, another data structure of identical \"shape\" is created which consists of only bit vectors so that only a 1 or 0 will be stored in the location of the k-mer suffix that was found in the intersection. This reduces the amount of data generated and stored considerably.During the Subtraction phase, relevant intersection bitmasks are first unionized together to form a single bitmask which is then applied over the original genome to reveal only those regions of the genome that are unique. These regions are then exported to disk in FASTA format and used in the application of determining the constituents of an unknown metagenomic community.The DATABASE provided is the result of the algorithm described.", + "laborHours": 5168.0, + "name": "GOTTCHA Database, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/GOTTCHA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CASL's modeling and simulation technology, the Virtual Environment for Reactor Applications (VERA), incorporates coupled physics and science-based models, state-of-the-art numerical methods, modern computational science, integrated uncertainty quantification (UQ) and validation against data from operating pressurized water reactors (PWRs), single-effect experiments, and integral tests. The computational simulation component of VERA is the VERA Core Simulator (VERA-CS). The core simulator is the specific collection of multi-physics computer codes used to model and deplete a LWR core over multiple cycles. The core simulator has a single common input file that drives all of the different physics codes. The parser code, VERAIn, converts VERA Input into an XML file that is used as input to different VERA codes.", + "laborHours": 13786.4, + "name": "VERAIn", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/CASL/VERAin/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CASL/VERAin", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Cloud droplet number concentration is an important factor in understanding aerosol-cloud interactions. As aerosol concentration increases, it is expected that droplet number concentration (Nd) will increase and droplet size will decrease, for a given liquid water path. This will greatly affect cloud albedo as smaller droplets reflect more shortwave radiation; however, the magnitude and variability of these processes under different environmental conditions is still uncertain.McComiskey et al. (2009) have implemented a method, based onBoers and Mitchell (1994), for calculating Nd from ground-based remote sensing measurements of optical depth and liquid water path. They show that the magnitude of the aerosol-cloud interactions (ACI) varies with a range of factors, including the relative value of the cloud liquid water path (LWP), the aerosol size distribution, and the cloud updraft velocity. Estimates of Nd under a range of cloud types and conditions and at a variety of sites are needed to further quantify the impacts of aerosol cloud interactions. In order to provide data sets for studying aerosol-cloud interactions, the McComiskey et al. (2009) method was implemented as the Droplet Number Concentration (NDROP) value-added product (VAP).", + "laborHours": 532.0, + "name": "Droplet Number Concentration Value Added Product", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ARM-DOE/adi-vap-ndrop", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/adi-vap-ndrop", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "joiner@ameslab.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ParFit is a flexible and extendable framework and library of classes for fitting force-field parameters to data from high-level ab-initio calculations on the basis of deterministic and stochastic algorithms. Currently, the code is fitting MM3 and Merck force-field parameters but could easily extend to other force-field types.", + "laborHours": 31874.4, + "name": "Force-Field Parameter Fitter", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fzahari/ParFit", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The four-dimensional scattering function S(Q,w) obtained by inelastic neutron scattering measurements provides unique \"dynamical fingerprints\" of the spin state and interactions present in complex magnetic materials. Extracting this information however is currently a slow and complex process that may take an expert -depending on the complexity of the system- up to several weeks of painstaking work to complete. Spin Wave Genie was created to abstract and automate this process. It strives to both reduce the time to complete this analysis and make these calculations more accessible to a broader group of scientists and engineers.", + "laborHours": 11658.4, + "name": "Spin Wave Genie", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SpinWaveGenie/SpinWaveGenie", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DESTINY is a comprehensive tool for modeling 3D and 2D cache designs using SRAM,embedded DRAM (eDRAM), spin transfer torque RAM (STT-RAM), resistive RAM (ReRAM), and phase change RAM (PCN). In its purpose, it is similar to CACTI, CACTI-3DD or NVSim. DESTINY is very useful for performing design-space exploration across several dimensions, such as optimizing for a target (e.g. latency, area or energy-delay product) for agiven memory technology, choosing the suitable memory technology or fabrication method (i.e. 2D v/s 3D) for a given optimization target, etc. DESTINY has been validated against several cache prototypes. DESTINY is expected to boost studies of next-generation memory architectures used in systems ranging from mobile devices to extreme-scale supercomputers.", + "laborHours": 6292.8, + "name": "DESTINY", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/3d_cache_modeling_tool/destiny/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/3d_cache_modeling_tool/destiny", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "To address a pressing need to better understand the behavior and complex interaction of ice sheets within the global Earth system, significant development of continental-scale, dynamical ice-sheet models is underway. The associated verification and validation process of these models is being coordinated through a new, robust, python-based extensible software package, the Land Ice Verification and Validation toolkit (LIVV). This release provides robust and automated verification and a performance evaluation on LCF platforms. The performance V&V involves a comprehensive comparison of model performance relative to expected behavior on a given computing platform. LIVV operates on a set of benchmark and test data, and provides comparisons for a suite of community prioritized tests, including configuration and parameter variations, bit-4-bit evaluation, and plots of tests where differences occur.", + "laborHours": 4772.8, + "name": "Land Ice Verification and Validation Kit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LIVVkit/LIVVkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Autotune software code uses an island-based evolutionary algorithm to solve multi-objective optimization problems. For the code provided, this has been applied to the whole-building simulation engine EnergyPlus to allow a software description of a building to be calibrated to measured data.", + "laborHours": 7068.0, + "name": "Autotune", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-BTRIC/Autotune/blob/master/LICENCE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-BTRIC/Autotune", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A collection of functions for statistical computing and data manipulation. These include routines for rapidly aggregating heterogeneous matrices, manipulating file names, loading R objects, sourcing multiple R files, formatting datetimes, multi-core parallel computing, stream editing, specialized plotting, etc. Smisc-package A collection of miscellaneous functions allMissing Identifies missing rows or columns in a data frame or matrix as.numericSilent Silent wrapper for coercing a vector to numeric comboList Produces all possible combinations of a set of linear model predictors cumMax Computes the maximum of the vector up to the current index cumsumNA Computes the cummulative sum of a vector without propogating NAs d2binom Probability functions for the sum of two independent binomials dataIn A flexible way to import data into R. dbb The Beta-Binomial Distribution df2list Row-wise conversion of a data frame to a list dfplapply Parallelized single row processing of a data frame dframeEquiv Examines the equivalence of two dataframes or matrices dkbinom Probability functions for the sum of k independent binomials factor2character Converts all factor variables in a dataframe to character variables findDepMat Identify linearly dependent rows or columns in a matrix formatDT Converts date or datetime strings into alternate formats getExtension Filename manipulations: remove the extension or path, extract the extension or path getPath Filename manipulations: remove the extension or path, extract the extension or path grabLast Filename manipulations: remove the extension or path, extract the extension or path ifelse1 Non-vectorized version of ifelse integ Simple numerical integration routine interactionPlot Two-way Interaction Plot with Error Bar linearMap Linear mapping of a numerical vector or scalar list2df Convert a list to a data frame loadObject Loads and returns the object(s) in an \".Rdata\" file more Display the contents of a file to the R terminal movAvg2 Calculate the moving average using a 2-sided window openDevice Opens a graphics device based on the filename extension p2binom Probability functions for the sum of two independent binomials padZero Pad a vector of numbers with zeros parseJob Parses a collection of elements into (almost) equal sized groups pbb The Beta-Binomial Distribution pcbinom A continuous version of the binomial cdf pkbinom Probability functions for the sum of k independent binomials plapply Simple parallelization of lapply plotFun Plot one or more functions on a single plot PowerData An example of power data pvar Prints the name and value of one or more objects qbb The Beta-Binomial Distribution rbb And numerous others (space limits reporting).", + "laborHours": 2568.8, + "name": "Smisc - A collection of miscellaneous functions", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/Smisc/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Smisc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-01-25" + }, + "description": "The core of the modeling platform is an extensible block library for the MATLAB/Simulink software suite. The platform enables true co-simulation (interaction at each simulation time step) with NREL's state-of-the-art modeling tools and other energy modeling software.", + "laborHours": 3024.8, + "languages": [], + "name": "Campus Energy Model for Control and Performance Validation [SWR-15-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CampusEnergyModeling", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-05-22" + }, + "description": "Small pieces of software that wraps the FAST model so that FAST can be integrated to WISDEM. NOTE: THIS REPOSITORY IS DEPRECATED AND WAS ARCHIVED (READ-ONLY) IN NOVEMBER 2019. NREL's WISDEM\u00ae software has moved to a single, integrated repository at https://github.com/wisdem/wisdem", + "laborHours": 11536.8, + "languages": [ + "Python" + ], + "name": "Aeroelastic Systems Engineering Module [SWR 14-26]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/aeroelasticse", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "FESTR is a modeling tool for calculating spectroscopic-quality synthetic outputs (e.g., spectra and images) based on (in general) the time evolutions of 3-D spatial distributions of materials characterized by their chemical composition, temperature, and density conditions. FESTR performs raytracing across unstructured meshes, builds intrinsic optical properties of mixed materials by performing equation-of-state lookups in external data, and then solves the radiation-transport equation along rays to obtain emergent time and space resolved synthetic spectra. These results can be further processed into time and/or space integrated spectra, as well as into spectral-band-integrated synthetic images, radiated power histories, and total radiated energy values. FESTR is also applicable to spatial reconstructions of material properties via the analysis of experimental data.", + "laborHours": 70376.0, + "name": "FESTR, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LANLhakel/FESTR/blob/d5a8941f2e74fb0adc8b12a90180b299b95dc93e/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANLhakel/FESTR", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This package contains statistical routines for extracting features from multivariate time-series data which can then be used for subsequent multivariate statistical analysis to identify patterns and anomalous behavior. It calculates local linear or quadratic regression model fits to moving windows for each series and then summarizes the model coefficients across user-defined time intervals for each series. These methods are domain agnostic-but they have been successfully applied to a variety of domains, including commercial aviation and electric power grid data.", + "laborHours": 988.0, + "name": "qFeature", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/qFeature/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL/qFeature", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Enables applications to emit log information into an output file and produced a structured visual summary of the log data, as well as various statistical analyses of it. This makes it easier for developers to understand the behavior of their applications.", + "laborHours": 170893.6, + "name": "Sight Version 0.1", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bronevet/sight", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "joiner@ameslab.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "As the rate, sophistication, and potential damage of cyber attacks continue to grow, the latency of human-speed analysis and response is becoming increasingly costly. Intelligent response to detected attacks and other malicious activity requires both knowledge of the characteristics of the attack as well as how resources involved in the attack related to the mission of the organization. Cydime fills this need by estimating a key component of intrusion detection and response automation: the relationship type and strength between the target organization and the potential attacker.", + "laborHours": 15762.4, + "name": "Cyber Dynamic Impact Modeling Engine", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Ames-Laboratory-Cyber-Group/Cydime", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-08-16" + }, + "description": "DICe is an open source digital image correlation (DIC) tool intended for use as a module in an external application or as a standalone analysis code. It's primary capability is computing full-field displacements and strains from sequences of digital These images are typically of a material sample undergoing a materials characterization experiment, but DICe is also useful for other applications (for example, trajectory tracking). DICe is machine portable (Windows, Linux and Mac) and can be effectively deployed on a high performance computing platform. Capabilities from DICe can be invoked through a library interface, via source code integration of DICe classes or through a graphical user interface.", + "laborHours": 45128.8, + "languages": [], + "name": "Digital Image Correlation Engine v.3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dicengine/dice", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Many simulation software produce data in the form of a set of field values or of a set of particle positions. (one such example is that of particle-in-cell codes, which produce data on the electromagnetic fields that they simulate.) However, each particular software uses its own particular format and layout, for the output data. This makes it difficult to compare the results of different simulation software, or to have a common visualization tool for these results. However, a standardized layout for fields and particles has recently been developed: the openPMD format ( HYPERLINK \"http://www.openpmd.org/\"www.openpmd.org) This format is open- source, and specifies a standard way in which field data and particle data should be written. The openPMD format is already implemented in the particle-in-cell code Warp (developed at LBL) and in PIConGPU (developed at HZDR, Germany). In this context, the proposed software (openPMD-viewer) is a Python package, which allows to access and visualize any data which has been formatted according to the openPMD standard. This package contains two main components: - a Python API, which allows to read and extract the data from a openPMD file, so as to be able to work with it within the Python environment. (e.g. plot the data and reprocess it with particular Python functions) - a graphical interface, which works with the ipython notebook, and allows to quickly visualize the data and browse through a set of openPMD files. The proposed software will be typically used when analyzing the results of numerical simulations. It will be useful to quickly extract scientific meaning from a set of numerical data.", + "laborHours": 1246.4, + "name": "openPMD-viewer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/openPMD/openPMD-viewer/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openPMD/openPMD-viewer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-11-06" + }, + "description": "VOLTTRON\u2122 is an agent execution platform providing services to its agents that allow them to easily communicate with physical devices and other resources. VOLTTRON\u2122 delivers an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls. It enables mobile and stationary software agents to perform information gathering, processing, and control actions. VOLTTRON\u2122 can independently manage a wide range of applications, such as HVAC systems, electric vehicles, distributed energy or entire building loads, leading to improved operational efficiency.", + "laborHours": 0.0, + "languages": [], + "name": "VOLTTRON Version 3.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/VOLTTRON/volttron/blob/3.x/TERMS.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron/releases/tag/3.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"XTL Converter\" is a short Python script for electron microscopy simulation. The program takes an input crystal file in the VESTA *.XTL format and converts it to a text format readable by the multislice simulation program \u00ecSTEM. The process of converting a crystal *.XTL file to the format used by the \u00ecSTEM simulation program is quite tedious; it generally requires the user to select dozens or hundreds of atoms, rearranging and reformatting their position. Header information must also be reformatted to a specific style to be read by \u00ecSTEM. \"XTL Converter\" simplifies this process, saving the user time and allowing for easy batch processing of crystals.", + "laborHours": 136.8, + "name": "XTL Converter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/stevenspurgeon/xtl-converter/blob/master/License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stevenspurgeon/xtl-converter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Cantera is a suite of object-oriented software tools for problems involving chemical kinetics, thermodynamics, and/or transport processes. It is a multi-organizational effort to create and formulate high quality 0D and 1D constitutive modeling tools for reactive transport codes.Institutions involved with the effort include Sandia, MIT, Colorado School of Mines, U. Texas, NASA, and Oak Ridge National Labs. Specific to Sandia's contributions, the Cantera Electrolyte Thermo Objects (CETO) packages is comprised of add-on routines for Cantera that handle electrolyte thermochemistry and reactions within the overall Cantera package. Cantera is a C++ Cal Tech code that handles gas phase species transport, reaction, and thermodynamics. With this addition, Cantera can be extended to handle problems involving liquid phase reactions and transport in electrolyte systems, and phase equilibrium problemsinvolving concentrated electrolytes and gas/solid phases. A full treatment of molten salt thermodynamics and transport has also been implemented in CETO. The routines themselves consist of .cpp and .h files containing C++ objects that are derived from parent Cantera objects representing thermodynamic functions. They are linked unto the main Cantera libraries when requested by the user. As an addendum to the main thermodynamics objects, several utility applications are provided. The first is multiphase Gibbs free energy minimizer based on the vcs algorithm, called vcs_cantera. This code allows for the calculation of thermodynamic equilibrium in multiple phases at constant temperature and pressure. Note, a similar code capability exists already in Cantera. This version follows the same algorithm, but gas a different code-base starting point, and is used as a research tool for algorithm development. The second program, cttables, prints out tables of thermodynamic and kinetic information for thermodynamic and kinetic objects within Cantera. This program serves as a \"Get the numbers out\" utility for Cantera, and as such it is very useful as a verification tool. These add-on utilities are encapsulated into a directory structure named cantera_apps, whose installation uses autoconf and also utilizes Cantera's application environment (i.e., they utilize Cantera as a library).", + "laborHours": 97432.0, + "name": "Cantera and Cantera Electrolyte Thermodynamics Objects", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Cantera/cantera", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-09" + }, + "description": "Sandia's Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to: (1) enhance understanding of risk, (2) improve products, and (3) assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a computational model. However, Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. The algorithms implemented in Dakota aim to address challenges in performing these analyses with complex science and engineering models from desktop to high performance computers.", + "homepageURL": "https://dakota.sandia.gov/sites/default/files/docs/6.0/html-dev/files.html", + "laborHours": 3812676.8, + "languages": [], + "name": "Design Analysis Kit for Optimization and Terascale Applications 6.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/sites/default/files/docs/6.0/html-dev/files.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-01" + }, + "description": "The Kokkos library implements thread-parallel execution policies and shared-memory multidimensional array data structures that enable applications and domain libraries to develop computational kernels that are performance portable across multicore-CPU and manycore-accelerator (e.g. GPU) computing architectures.", + "laborHours": 119700.0, + "languages": [], + "name": "Kokkos Version 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/kokkos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Sandia National Laboratories has modified Simulating WAves Nearshore (SWAN), the Delft University of Technology code,, to include functionality to better model wave energy converters (WECs). The code modified by SNL has been named SNL-SWAN. SNL-SWAN includes a frequency dependent WEC Module that builds upon the traditional obstacle module in SWAN. In SNL-SWAN, a frequency dependent transmission coefficient is calculated to model power absorbed by WEC devices. The power transmission coefficients are calculated based on the WEC's power performance, which is defined by the user in the input text files. Two methods of defining WEC power performance have been implemented: a user-specified power matrix, and a user-specified relative capture width. These methods allow the user to define the WEC's frequency dependent energy absorption as a function of period and/or wave height. SWAN test cases were run to verify the compiled code's functionality, and verification of the frequency dependent WEC Module in SNL-SWAN has also been performed. SNL-SWAN code is will be released as open source code and will be made publicly available.", + "laborHours": 23985.6, + "languages": [ + "Fortran" + ], + "name": "SNL-SWAN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SNL-SWAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "UseLATEX.cmake is a collection of script functions and examples for building LaTeX documents. It simplifies the process of building LaTeX documents, which requires the execution of multiple programs and the management of several input files. UseLATEX.cmake also provides several options to customize the LaTeX build process.", + "laborHours": 1520.0, + "languages": [ + "CMake", + "Shell", + "TeX" + ], + "name": "UseLATEX.cmake", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/UseLATEX", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-01" + }, + "description": "VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures. VTK-m supports the fine-grained concurrency for data analysis and visualization algorithms required to drive extreme scale computing by providing abstract models for data and execution that can be applied to a variety of algorithms across many different processor architectures.", + "laborHours": 204652.8, + "languages": [], + "name": "VTK-m", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk-m", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Some moment methods for kinetic equations are complicated and take time to develop. Over the course of a couple years, this software was developed to test different closures on standard test problems in the literature. With this software, researchers in the field of moment closures will be able to rapidly test new methods.", + "laborHours": 22298.4, + "name": "Moment Closures on Two-Dimensional Cartesian Grids", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ckrisgarrett/closures-2d", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ckrisgarrett/closures-2d", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "An automated drift time extraction and computed associated collision cross section software tool for small molecule analysis with ion mobility spectrometry-mass spectrometry (IMS-MS). The software automatically extracts drift times and computes associated collision cross sections for small molecules analyzed using ion mobility spectrometry-mass spectrometry (IMS-MS) based on a target list of expected ions provided by the user.", + "laborHours": 83235.2, + "name": "IMS - MS Data Extractor", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/PIXIE/blob/master/PNNL%20OSS%20License_citation.doc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PIXIE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "nHHD is a C++ library to decompose a flow field into three components exhibiting specific types of behaviors. These components allow more targeted analysis of flow behavior and can be applied to a variety of application areas.", + "laborHours": 10396.8, + "name": "The Natural Helmholtz-Hodge Decomposition", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bhatiaharsh/naturalHHD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "To understand the performance of parallel programs, developers need to be able to relate performance measurement data with context information, such as the call path / line numbers or iteration numbers where measurements were taken. Caliper provides a generic way to specify and collect multi-dimensional context information across the software stack, and provide ti to third-party measurement tools or write it into a file or database in the form of context streams.", + "laborHours": 35096.8, + "languages": [], + "name": "Caliper Context Annotation Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/Caliper/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Caliper", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "LCMSnet communicates with, controls and orchestrates devices for high pressure liquid chromatography. In developing cutting edge chromatographic methods it was apparent that components from different manufacturers were required. Autosamplers, valves, and pumps all had to be controlled and configured to run unattended and in the highest throughput possible. The power of LCMSnet is the ability so build methods in a simple step by step fashion and then the software uses a scheduling algorithm to run the devices as efficiently as possible without crashing critical functions. This latest iteration of the software allows for modeling of the valves and incorporates logic that will report if a fluid path is undesirable. LCMSnet has reduced method development time from days to minutes and allows the ability to check configurations before any valves or pumps are connected.", + "laborHours": 70239.2, + "name": "LCMSNet v. 3.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/LCMSNet", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LCMSNet", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "BGQNCL is a library to monitor and record network performance counters on the 5D torus interconnection network of IBM's Blue Gene/Q platform.", + "laborHours": 152.0, + "name": "Blue Gene/Q Network Performance Counters Monitoring Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/bgqncl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Dragonview is an interactive visual analytics tool to visualize the nodes and links of a supercomputer that uses the dragonfly topology for its interconnection network. It can be used to map different data such as number of packets or bytes or stalls on the network links and job IDs or other on-node metrics on the router or node.", + "laborHours": 3085.6, + "name": "Dragonview", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DragonView", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Graphator is a collection of relatively simple sequential programs that generate communication graphs/matrices for commonly occurring patterns in parallel programs. Currently, there is support for five communication patterns: two-dimensional 4-point stencil, four-dimensional 8-point stencil, all-to-alls over sub-communicators, random near-neighbor communication, and near-neighbor communication.", + "laborHours": 91.2, + "name": "Communication Graph Generator for Parallel Programs", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/graphator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "AriesNCL is a library to monitor and record network router tile performance counters on the Aries router of Cray's Cascade/XC30 platform.", + "laborHours": 152.0, + "name": "Aries Network Performance Counters Monitoring Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ariesncl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Damselfly is a model-based parallel network simulator. It can simulate communication patterns of High Performance Computing applications on different network topologies. It outputs steady-state network traffic for a communication pattern, which can help in studying network congestion and its impact on performance.", + "laborHours": 2401.6, + "name": "Damselfly Network Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/damselfly", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Most of the software related to file system are written for conventional local file system, they are serialized and can't take advantage of the benefit of a large scale parallel file system. \"pcircle\" software builds on top of ubiquitous MPI in cluster computing environment and \"work-stealing\" pattern to provide a scalable, high-performance suite of file system tools. In particular - it implemented parallel data copy and parallel data checksumming, with advanced features such as async progress report, checkpoint and restart, as well as integrity checking.", + "laborHours": 3085.6, + "name": "pcircle - A Suite of Scalable Parallel File System Tools", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-TechInt/pcircle", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The visualization enables the simulation analyst to see changes in the frequency through time and space. With this technology, the analyst has a bird's eye view of the frequency at loads and generators as the simulated power system responds to the loss of a generator, spikes in load, and other contingencies. The significance of a contingency to the operation of an electrical power system depends critically on how the resulting tansients evolve in time and space. Consequently, these dynamic events can only be understood when seen in their proper geographic context. this understanding is indispensable to engineers working on the next generation of distributed sensing and control systems for the smart grid. By making possible a natural and intuitive presentation of dynamic behavior, our new visualization technology is a situational-awareness tool for power-system engineers.", + "laborHours": 773132.8, + "name": "Geographic Visualization of Power-Grid Dynamics", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ssrangan/VizPower/blob/master/Open%20Source%20Software%20License%20(Permissive).pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ssrangan/VizPower", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SSCA1-K1 is a parallel implementation of kernel 1 of the SSCA1 benchmark suite released by the DARPA HPCS program. This kernel is able to run in parallel on a distributed shared memory system at extreme scales using OpenSHMEM.", + "laborHours": 775.2, + "name": "SSCA1-K1", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/MattBBaker/ssca1", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Intrepid is a library of interoperable tools for compatible discretizations of Partial Differential Equations (PDEs).Current version is intended primarily for application developers who want to reuse large parts of their existing code frameworks such as I/O, data structures, assembly routines, etc. while gaining access to advanced discretization capabilities provided by Intrepid. Intrepid2 is a performance portable version of Intrepid, that requires all input data types be Kokkos (performance-portability library from Trillions) multidimentional arrays. this restriction is needed for providing performance portability in Intrepid2 and break backward-compatibility of Intrepid.", + "laborHours": 8344830.4, + "name": "INteroperable Tools for Rapid dEveloPment of compatible Discretizations", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/intrepid/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This code implements the GloVe algorithm for learning word vectors from a text corpus. It uses a modern C++ approach. This algorithm is described in the open literature in the referenced paper by Pennington, Jeffrey, Richard Socher, and Christopher D. Manning.", + "laborHours": 486.4, + "languages": [ + "C++", + "Makefile" + ], + "name": "GloVe C++ v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GloveCpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "ryan.morrone@netl.doe.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "RVA is a plugin developed for the 64-bit Windows version of the ParaView 3.14 visualization package. RVA is designed to provide support in the visualization and analysis of complex reservoirs being managed using multi-fluid EOR techniques. RVA, for Reservoir Visualization and Analysis, was developed at the University of Illinois at Urbana-Champaign, with contributions from the Illinois State Geological Survey, Department of Computer Science and National Center for Supercomputing Applications. RVA was designed to utilize and enhance the state-of-the-art visualization capabilities within ParaView, readily allowing joint visualization of geologic framework and reservoir fluid simulation model results. Particular emphasis was placed on enabling visualization and analysis of simulation results highlighting multiple fluid phases, multiple properties for each fluid phase (including flow lines), multiple geologic models and multiple time steps. Additional advanced functionality was provided through the development of custom code to implement data mining capabilities. The built-in functionality of ParaView provides the capacity to process and visualize data sets ranging from small models on local desktop systems to extremely large models created and stored on remote supercomputers. The RVA plugin that we developed and the associated User Manual provide improved functionality through new software tools, and instruction in the use of ParaView-RVA, targeted to petroleum engineers and geologists in industry and research. The RVA web site (http://rva.cs.illinois.edu) provides an overview of functions, and the development web site (https://github.com/shaffer1/RVA) provides ready access to the source code, compiled binaries, user manual, and a suite of demonstration data sets. Key functionality has been included to support a range of reservoirs visualization and analysis needs, including: sophisticated connectivity analysis, cross sections through simulation results between selected wells, simplified volumetric calculations, global vertical exaggeration adjustments, ingestion of UTChem simulation results, ingestion of Isatis geostatistical framework models, interrogation of joint geologic and reservoir modeling results, joint visualization and analysis of well history files, location-targeted visualization, advanced correlation analysis, visualization of flow paths, and creation of static images and animations highlighting targeted reservoir features.", + "laborHours": 7220.0, + "name": "RVA: A Plugin for ParaView 3.14", + "organization": "National Energy Technology Laboratory (NETL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/shaffer1/RVA/blob/master/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/shaffer1/RVA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Energy Technology Laboratory (NETL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-12" + }, + "description": "PyTrilinos is a Python interface to selected Trilinos packages. This makes Trilinos linear algebra classes, linear solvers, preconditioners, nonlinear solvers, eigensolvers, and tools available to Python programmers. This broadens the user base of Trilinos, and facilitates rapid prototyping of scientific codes and interactive manipulation of large, distributed data sets.", + "laborHours": 8344830.4, + "languages": [], + "name": "PyTrilinos", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The DOE has funded Sandia National Labs (SNL) to develop an open-source modeling tool to guide the design and layout of marine hydrokinetic (MHK) arrays to maximize power production while minimizing environmental effects. This modeling framework simulates flows through and around MHK arrays while quantifying environmental responses. As an augmented version of US EPA's Environmental Fluid Dynamics Code (EFDC), SNL-EFDC includes: (1) a new module that simulates energy conversion (momentum withdrawal) by MHK devices with commensurate changes in the turbulent kinetic energy and its dissipation rate, (2) new, advanced sediment dynamics routines, and (3) augmented water quality modules.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Sandia National Laboratories Environmental Fluid Dynamics Code V. 1 0.0 (Beta)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/EFDC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "10.0" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The basic matrix library (bml) is a collection of various matrix data formats (in dense and sparse) and their associated algorithms for basic matrix operations.", + "laborHours": 38319.2, + "name": "Basic Matrix Library (bml), Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/bml/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qmmd/bml", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code is a set of global sums to support the paper \"Computational Reproducibility for Production Physics Applications\" submitted to the Numerical Reproducibility at Exascale (NRE 2015) workshop at the 2015 Supercomputing conference, Nov. 20, 2015", + "laborHours": 851.2, + "name": "GlobalSums, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/GlobalSums", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PV_LIB comprises a library of Matlab? code for modeling photovoltaic (PV) systems. Included are functions to compute solar position and to estimate irradiance in the PV system's plane of array, cell temperature, PV module electrical output, and conversion from DC to AC power. Also included are functions that aid in determining parameters for module performance models from module characterization testing. PV_LIB is open source code primarily intended for research and academic purposes. All algorithms are documented in openly available literature with the appropriate references included in comments within the code.", + "laborHours": 3359.2, + "name": "PV_LIB Toolbox v. 1.3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SandiaTestAccount/PVLIB_Matlab", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The Water Network Tool for Resilience (WNTR) is an open source Python package designed to simulate and analyze resilience of water distribution networks. The United States Environmental Protection Agency, in partnership with Sandia National Laboratories, developed WNTR to integrate critical aspects of resilience modeling for water distribution networks into a single software framework.\nThe software includes capability to:\n\u2022\tGenerate water network models\n\u2022\tModify network structure and operations\n\u2022\tAssign fragility and survival curves to network components\n\u2022\tModel disruptive events such as power outages, earthquakes, fires, pipe breaks, and contamination incidents\n\u2022\tModel response and repair strategies\n\u2022\tSimulate hydraulics and water quality\n\u2022\tEvaluate resilience using a wide range of metrics\n\u2022\tIntegrate dependency with other critical infrastructure and supply chains\n\u2022\tAnalyze results and generate graphics\nSAND2019-450 M", + "laborHours": 147561.6, + "languages": [ + "C++", + "C", + "Python" + ], + "name": "Water Network Tool for Resilience (WNTR)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/WNTR", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Single-Sided Messaging (SSM) is a portable, multitransport networking library that enables applications to leverage potential one-sided capabilities of underlying network transports. It also provides desirable semantics that services for highperformance, massively parallel computers can leverage, such as an explicit cancel operation for pending transmissions, as well as enhanced matching semantics favoring large numbers of buffers attached to a single match entry. This release supports TCP/IP, shared memory, and Infiniband.", + "laborHours": 37741.6, + "languages": [], + "name": "Single Sided Messaging v. 0.6.6", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/single-sided-messaging", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.6.6" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Mobile digital signage software optimized for giving tours and trade shows.", + "laborHours": 2690.4, + "name": "DiTour OSS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ditour/ditour/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ditour/ditour", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "VTK is a software library used for scientific visualization tasks. My specific contribution is a new class that improves the I/O performance when reading certain input files.", + "laborHours": 3149576.8, + "name": "vtkPNetCDFPOPReader: a new C++ class for Visualization Toolkit (VTK)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.vtk.org/licensing", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Sirocco is a parallel storage system under development, designed for write-intensive workloads on large-scale HPC platforms. It implements a keyvalue object store on top of a set of loosely federated storage servers that cooperate to ensure data integrity and performance. It includes support for a range of different types of storage transactions. This software release constitutes a conformant storage server, along with the client-side libraries to access the storage over a network.", + "laborHours": 42848.8, + "languages": [ + "Shell", + "C++", + "C", + "RPC", + "Makefile" + ], + "name": "Sirocco Storage Server v. pre-alpha 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/sirocco-release?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sirocco-release", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "minimega is an emulytics platform for creating testbeds of networked devices. The platoform consists of easily deployable tools to facilitate bringing up large networks of virtual machines including Windows, Linux, and Android. minimega allows experiments to be brought up quickly with almost no configuration. minimega also includes tools for simple cluster, management, as well as tools for creating Linux-based virtual machines. This release of minimega includes new emulated sensors for Android devices to improve the fidelity of testbeds that include mobile devices. Emulated sensors include GPS and", + "laborHours": 399334.4, + "name": "minimega v. 3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandia-minimega/minimega", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GridDyn is a part of power grid simulation toolkit. The code is designed using modern object oriented C++ methods utilizing C++11 and recent Boost libraries to ensure compatibility with multiple operating systems and environments.", + "laborHours": 493620.0, + "name": "Dynamic Power Grid Simulation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/GridDyn/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GridDyn", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Stride Search provides a flexible tool for detecting storms or other extreme climate events in high-resolution climate data sets saved on uniform latitude-longitude grids in standard NetCDF format. Users provide the software a quantitative description of a meteorological event they are interested in; the software searches a data set for locations in space and time that meet the user\u2019s description. In its first stage, Stride Search performs a spatial search of the data set at each timestep by dividing a search domain into circular sectors of constant geodesic radius. Data from a netCDF file is read into memory for each circular search sector. If the data meet or exceed a set of storm identification criteria (defined by the user), a storm is recorded to a linked list. Finally, the linked list is examined and duplicate detections of the same storm are removed and the results are written to an output file. The first stage\u2019s output file is read by a second program that builds storm. Additional identification criteria may be applied at this stage to further classify storms. Storm tracks are the software\u2019s ultimate output and routines are provided for formatting that output for various external software libraries for plotting and tabulating data.", + "laborHours": 8116.8, + "languages": [ + "C++", + "CMake", + "Fortran", + "Python" + ], + "name": "Stride Search v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/StrideSearch", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "In the cyber security operations of a typical organization, data from multiple sources are monitored, and when certain conditions in the data are met, an alert is generated in an alert management system. Analysts inspect these alerts to decide if any deserve promotion to an event requiring further scrutiny. This triage process is manual, time-consuming, and detracts from the in-depth investigation of events. We have created a software system that uses supervised machine learning to automatically prioritize these alerts. In particular we utilize active learning to make efficient use of the pool of unlabeled alerts, thereby improving the performance of our ranking models over passive learning. We have demonstrated the effectiveness of our system on a large, real-world dataset of cyber security alerts.", + "laborHours": 2508.0, + "name": "Alert Triage v 0.1 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/alert-triage", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This application can determine the performance and chemical behavior of batteries in 1D when they are cycled. With CanTrilBat, we are developing predictive phenomenological models for battery systems to predict operating performance and rate limiting steps in the performance of battery models. Particular attention is paid to primary and secondary chemistry mechanisms, such as the thermal runaway mechanisms experienced in secondary lithium ion batteries or self-discharge reaction mechanism that all batteries experience to one extent or another. The first application of this model has been for modeling the performance of thermal batteries. However, an implementation for secondary ion batteries is next. CanTrilBat applications solves transient problems involving batteries. It is a 1-D application that represents 3-D physical systems that can be reduced using the porous flow approximation for the anode, cathode, and separator. A control volume formulation is used to track conserved quantities. An operator-split approach is used to calculate the chemistry, diffusion and electronic transport that occurs within cathode and anode particles, allowing for the reduction in code complexity. All jacobian operations in CanTrilBat utilize numerical jacobians. A home grown predictor corrector scheme is used for time step control, and a home grown newton solver is used to relax the equations at each time step. Trilinos is used to solve for the resulting linear systems equation A block text input format is used to initialize options for the CanTriBat program. Within this block are the names of several XML input files, which specify the chemistry mechanism. These XML input files are read by low level Cantera routines, and serve to initialize the electrode and electrolyte chemistry mechanisms and transport properties. A GUI implementation has been contracted out to a university professor, but has not been implemented yet. It?s expected that CanTriBat will have the capability to do adaptive grid refinement in later versions. Grids will be halved based on an complicated set of heuristic criteria, based on how well the mesh captures changes to the first and second derivatives of selected solution components. Primary emphasis is given towards converged profiles for IV performance.", + "laborHours": 6177492.8, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "M4", + "Fortran" + ], + "name": "CanTrilBat and Cantera_apps v1.0 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cantrilbat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "TraceR is a trace reply tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performances and understanding network behavior by simulating messaging in High Performance Computing applications on interconnection networks.", + "laborHours": 4727.2, + "name": "Trace Replay and Network Simulation Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/tracer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The Albany code is a general-purpose finite element code for solving partial differential equations (PDEs). Albany is a research code that demonstrates how a PDE code can be built by interfacing many of the open-source software libraries that are released under Sandia's Trilinos project. Part of the mission of Albany is to be a testbed for new Trilinos libraries, to refine their methods, usability, and interfaces. Albany includes hooks to optimization and uncertainty quantification algorithms, including those in Trilinos as well as those in the Dakota toolkit. Because of this, Albany is a desirable starting point for new code development efforts that wish to make heavy use of Trilinos. Albany is both a framework and the host for specific finite element applications. These applications have project names, and can be controlled by configuration option when the code is compiled, but are all developed and released as part of the single Albany code base, These include LCM, QCAD, FELIX, Aeras, and ATO applications.", + "laborHours": 195228.8, + "languages": [ + "Shell", + "C", + "CMake", + "MATLAB", + "Python", + "GLSL" + ], + "name": "Albany v. 3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Albany", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PyGSTi is an implementation of Gate Set Tomography in the python programming language. Gate Set Tomography (GST) is a theory and protocol for simultaneously estimating the state preparation, gate operations, and measurement effects of a physical system of one or many quantum bits (qubits). These estimates are based entirely on the statistics of experimental measurements, and their interpretation and analysis can provide a detailed understanding of the types of errors/imperfections in the physical system. In this way, GST provides not only a means of certifying the \"goodness\" of qubits but also a means of debugging (i.e. improving) them.", + "laborHours": 95425.6, + "name": "Python GST Implementation v. 0.9 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pyGSTio/pyGSTi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This software extends the Cray Chapel runtime to use directly Sandia's Qthreads lightweight threading library and Sandia's Portals4 lightweight communication reference library.", + "laborHours": 4298453.6, + "name": "Lightweight Threading and Communication Shims for Chapel v. 1.0 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/chapel-lang/chapel/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chapel-lang/chapel", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A processor emulator and a suite of benchmark applications have been developed to assist in characterizing the performance of data-centric workloads on current and future computer architectures. 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Its purpose is to provide visualization and analysis capabilities for the existing ParaDIS parallel dislocation dynamics simulation code.", + "laborHours": 4347.2, + "name": "ParaDIS_lib", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/paraDIS_lib", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "FleCSI is a compile-time configurable framework designed to support multi-physics application development. As such, FleCSI attempts to provide a very general set of infrastructure design patterns that can be specialized and extended to suit the needs of a broad variety of solver and data requirements. Current support includes multi-dimensional mesh topology, mesh geometry, and mesh adjacency information, n-dimensional hashed-tree data structures, graph partitioning interfaces, and dependency closures. FleCSI also introduces a functional programming model with control, execution, and data abstractions that are consistent with both MPI and state-of-the-art task-based runtimes such as Legion and Charm++. The FleCSI abstraction layer provides the developer with insulation from the underlying runtime, while allowing support for multiple runtime systems, including conventional models like asynchronous MPI. The intent is to give developers a concrete set of user-friendly programming tools that can be used now, while allowing flexibility in choosing runtime implementations and optimizations that can be applied to architectures and runtimes that arise in the future. The control and execution models in FleCSI also provide formal nomenclature for describing poorly understood concepts like kernels and tasks.", + "laborHours": 334.4, + "name": "Flexible Computer Science Infrastructure (FleCSI)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/laristra/flecsi-third-party", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/flecsi-third-party", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Methods for fitting and predicting logistic regression classifiers (LRC) with an arbitrary loss function using elastic net or best subsets. This package adds additional model fitting features to the existing glmnet and bestglm R packages. This package was created to perform the analyses described in Amidan BG, Orton DJ, LaMarche BL, et al. 2014. Signatures for Mass Spectrometry Data Quality. Journal of Proteome Research. 13(4), 2215-2222. It makes the model fitting available in the glmnet and bestglm packages more general by identifying optimal model parameters via cross validation with an customizable loss function. It also identifies the optimal threshold for binary classification.", + "laborHours": 744.8, + "name": "glmnetLRC f/k/a lrc package: Logistic Regression Classification", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/glmnetLRC/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/glmnetLRC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Tycho 2 is a mini-app for testing performance of new algorithms and computational optimizations of neutral particle transport sweeps on 3D tetrahedral, unstructured grids.", + "laborHours": 6110.4, + "name": "Tycho 2, Version 0.1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/tycho2/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/tycho2", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "COGENT is a simulation code that models the plasma evolution in the edge region of a tokamak fusion reactor, from the open field line scrape-off layer, across the separatrix, and into the core. The model is based on the 4D gyrokinetic closure of the kinetic equations for a plasma coupled to an electrostatic potential field. The background magnetic field is prescribed either analytically or generated from experimental data, and the grid is aligned with magnetic flux surfaces. Multiple collision operator options are provided, from Krook to fully nonlinear Fokker-Planck.", + "laborHours": 1019479.2, + "name": "Continuum Gyrokinetic Edge New Technology", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/COGENT/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/cogent", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Virtual Flow Simulator (VFS) is a state-of-the-art computational fluid mechanics (CFD) package that is capable of simulating multi-physics/multi-phase flows with the most advanced turbulence models (RANS, LES) over complex terrains. The flow solver is based on the Curvilinear Immersed Boundary (CURVIB) method to handle geometrically complex and moving domains. Different modules of the VFS package can provide different simulation capabilities for specific applications ranging from the fluid-structure interaction (FSI) of solid and deformable bodies, the two-phase free surface flow solver based on the level set method for ocean waves, sediment transport models in rivers and the large-scale models of wind farms based on actuator lines and surfaces. All numerical features of VFS package have been validated with known analytical and experimental data as reported in the related journal articles. VFS package is suitable for a broad range of engineering applications within different industries. VFS has been used in different projects with applications in wind and hydrokinetic energy, offshore and near-shore ocean studies, cardiovascular and biological flows, and natural streams and river morphodynamics. Over the last decade, the development of VFS has been supported and assisted with the help of various United States companies and federal agencies that are listed in the sponsor lists. In this version, VFS-Wind contains all the necessary modeling tools for wind energy applications, including land-based and offshore wind farms. VFS is highly scalable to run on either desktop computers or high performance clusters (up to 16,000 CPUs). This released version comes with a detailed user\u2019s manual and a set of case studies designed to facilitate the learning of the various aspects of the code in a comprehensive manner. The included documentation and support material has been elaborated in a collaboration effort with Sandia National Labs under the contract DE-EE0005482. The VFS-Wind source code is distributed under the GNU General Public License (GPL 2.0), offering to the community the flexibility to use and expand the capabilities of the package. We note that future publications including academic journals that result from the use of VFS must be cited appropriately under the GPL v.2 license agreement.", + "laborHours": 31053.6, + "name": "Virtual Flow Simulator", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SAFL-CFD-Lab/VFS-Wind", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Draco is an object-oriented component library geared towards numerically intensive, radiation (particle) transport applications built for parallel computing hardware. It consists of semi-independent packages and a robust build system. The packages in Draco provide a set of components that can be used by multiple clients to build transport codes. The build system can also be extracted for use in clients. Software includes smart pointers, Design-by-Contract assertions, unit test framework, wrapped MPI functions, a file parser, unstructured mesh data structures, a random number generator, root finders and an angular quadrature component.", + "laborHours": 67214.4, + "name": "Draco,Version 6.x.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/Draco/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/Draco", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-06" + }, + "description": "The Simulation Toolkit for Renewable Energy and Advanced Materials Modeling (STREAMM) is a python package that generates structures and input files for quantum chemical and molecular dynamics codes. STREAMM does not directly conduct simulations rather it is meant to drive quantum chemical and molecular dynamics codes to allow for high-throughput computational analysis of materials. The STREAMM package is written for python2.7 (https://www.python.org/download/releases/2.7/) and incorporates some of the core modules from the pymatgen (http://pymatgen.org/) code.", + "laborHours": 12205.6, + "languages": [ + "Python" + ], + "name": "STREAMM-tools (Simulation Toolkit for Renewable Energy Advanced Materials Modeling) [SWR-15-29]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/streamm-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-03-04" + }, + "description": "Overview of the OpenStudio\u00ae Fault Models Gem: Creating a comprehensive library of OpenStudio\u00ae fault models.\nFeatures:\n - Physics-based fault impact simulation within the capability of EnergyPlus\u00ae/OpenStudio\u00ae\n- Fault intensity implementation simulating how severe faults are (e.g., how much portion is fouled in the condenser heat exchanger) and estimating the impact of a fault in different fault intensities. \n- Fault evolution implementation simulating evolving/increasing fault intensity through certain period of time. \nFuture goals:\n- what are common/typical faults in different sample spaces (e.g., HVAC system type, building operation type, building location etc.)? \n- how often (e.g., incidence and prevalence) faults occur in different sample spaces (e.g., HVAC system type, building operation type, building location etc.)?", + "laborHours": 0.0, + "languages": [ + "Ruby", + "HTML" + ], + "name": "OpenStudio\u00ae Fault Models Gem [SWR-15-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-fault-measure-gem/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-fault-measure-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This is a Python package to translate between gdx (GAMS data) and pandas. \n\nThere are two main ways to use gdxpds. The first use case is the one that was initially supported: direct conversion between GDX files on disk and pandas DataFrames or a csv version thereof. Starting with the Version 1.0.0 rewrite, there is now a second style of use which involves interfacing with GDX files and symbols via the `gdxpds.gdx.GdxFile` and `gdxpds.gdx.GdxSymbol` classes.\n\nPlease visit https://nrel.github.io/gdx-pandas for the latest documentation.", + "laborHours": 972.8, + "languages": [ + "Python" + ], + "name": "GDX-pandas [SWR 15-21]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/gdx-pandas", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.3.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-03-11" + }, + "description": "Bus.py is a transmission bus emulator with functionality for communicating with the distribution simulation software GridLAB-D.", + "laborHours": 1535.2, + "languages": [ + "Python" + ], + "name": "bus.py [SWR-15-14]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/buspy", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "A cost model for operational expenditures for land-based wind plants.", + "laborHours": 6733.6, + "languages": [], + "name": "LandOpExSE (Land-Based Operational Expenditures SE) [SWR-14-31]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/Plant_CostsSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This repository has been archived by the owner on Mar 6, 2024. It is now read-only.\n\nHome Energy Score is a simulation-based rating method for existing homes. Home Performance XML (HPXML) is a data transfer standard for home energy audit and retrofit data used throughout the industry. This software receives an HPXML document and translates the building characteristics into HEScore inputs compliant with their API.", + "laborHours": 23119.2, + "languages": [ + "Python" + ], + "name": "HPXML to Home Energy Score Translator (hescore-hpxml) [SWR-14-30]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hescore-hpxml", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v2023.05.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "The software consists of a CKAN extension to an existing REEGLE Tagging API.", + "laborHours": 106.4, + "languages": [], + "name": "Reegle Tagging API (CKAN Extension) [SWR-14-28]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/REEEP/ckanext-climate-tagger/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/REEEP/ckanext-climate-tagger", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Framework for Unified Systems Engineering and Design of Wind Plants ( FUSED-Wind) is an open-source framework for multi-disciplinary optimisation and analysis (MDAO) of wind energy systems, developed jointly by DTU and NREL. The framework is designed as an extension to the NASA developed OpenMDAO, and defines key I/O elements and methods necessary for wiring together different simulation codes in order to achieve a system level analysis capability of wind turbine plants with multiple levels of fidelity. NREL and DTU have developed independent interfaces to their respective simulation codes and cost models (e.g. FAST/CCBlade, HAWC2/BECAS) with the aim of offering an environment where these codes can be used interchangeably. The open source nature of the framework enables third parties to develop interfaces to their own tools, either replacing or extending those offered by DTU and NREL.", + "laborHours": 12935.2, + "languages": [ + "Python" + ], + "name": "Framework for Unified Systems Engineering and Design of Wind Plants (FUSED-Wind) cost models and case analyzer [SWR-14-25]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FUSED-Wind/fusedwind", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "THIS REPOSITORY IS DEPRECATED AND WAS ARCHIVED (READ-ONLY) on June 19, 2020.\n\nWISDEM has moved to a single, integrated repository at https://github.com/wisdem/wisdem\n\nJacketSE is a systems engineering model for 3 and 4-legged lattice structures (jackets) supporting tubular steel towers for offshore wind turbines. A module for static hydrodynamic, aerodynamic, and structural design and analysis of wind turbine jacket and towers within the Systems Engineering toolbox.", + "laborHours": 27861.6, + "languages": [ + "Fortran", + "Python" + ], + "name": "JacketSE [SWR-14-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/JacketSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "A module that allows Frame3DD to interact with codes developed at NREL within the Systems Engineering WIDEM toolbox.", + "laborHours": 7448.0, + "languages": [ + "C", + "Python" + ], + "name": "PyFrame3DD [SWR-14-22]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/pyFrame3DD", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-08-07" + }, + "description": "*** PUBLIC ARCHIVE*** THIS IS A READ-ONLY VERSION OF THE DEPRECATED VERSION. FOR THE CURRENT VERSION OF THE FLORIS SOFTWARE, SEE WWW.GITHUB.COM/NREL/FLORIS\n\nFLORIS is an engineering model of wind turbine wake interactions which accounts for the effects of turbines on the flow through the creation of wakes an accounting for both velocity deficit and wake redirection through yaw", + "laborHours": 1003.2, + "languages": [ + "OpenEdge ABL", + "Python" + ], + "name": "FLORIS [SWR-14-20]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/FLORISSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-16" + }, + "description": "rplexos is a R (statistical software framework; more? details below) package that processes and facilitates analysis of solution from PLEXOS. PLEXOS is a production cost model that is utilize to simulate the behavior of the power.systems and is developed and commercialized by Energy Exomplar. The intention is to make rptexos open-source so other PLEXOS users can utilize it.", + "laborHours": 2173.6, + "languages": [ + "C++", + "R" + ], + "name": "rplexos [SWR-14-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/rplexos/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rplexos", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.1.2" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-11-26" + }, + "description": "This package is the R implementation of the Renewable Energy Probabilistic Resource Assessment (REPRA) tool, developed at the National Renewable Energy Laboratory (NREL). REPRA is a statistical tool that models the effect of variable generation in the calculation of resource adequacy metrics. It is built as a research tool to explore different methodologies and technologies.", + "laborHours": 319.2, + "languages": [ + "C++", + "R" + ], + "name": "REPRA (Renewable Energy Probabilistic Resource Assessment) [SWR-14-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/REPRA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.3" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Cost model for Land-Based BOS for wind turbines.", + "laborHours": 1884.8, + "languages": [], + "name": "LandBOSSE (Land-Based Balance Of System) [SWR-18-43]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/WISDEM/LandBOSSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/LandBOSSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "A modular tool for simulating wind plant aerodynamics with computational fluid dynamics and turbine structural and control response to the incoming flow.", + "laborHours": 16963.2, + "languages": [ + "C++", + "C", + "Roff", + "shell", + "Fortran" + ], + "name": "Simulator for Wind Farm Applications (SOWFA) [SWR-14-12]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/SOWFA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "NREL_WISDEM is an integrated model for wind turbines and plants developed In python based on the open source software OpenMDAO. NREL_WISDEM is a set of wrappers for various wind turbine and models that integrate pre-existing models together into OpenMDAO. It is organized into groups each with their own repositories including Plant_CostSE. Plant_EnergySE, Turbine_CostSE and TurbineSE. The wrappers are designed for licensed and non-licensed models though in both cases, one has to have access to and install the individual models themselves before using them in the overall software platform.", + "laborHours": 229778.4, + "name": "NREL Wind Integrated System Design and Engineering Model", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/WISDEM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This repository has been archived by the owner on Jun 19, 2020. It is now read-only. \n\nTurbine_CostsSE is a set of models for assessing the costs of a wind turbine. The first model is a new version of NREL's turbine Cost and Scaling Model that uses 2015 survey data to compute component mass properties from key turbine parameters such as rotor diameter, rated power and hub height. A second model is a new mass-to-cost model which takes the individual component masses as inputs to estimate each component costs with additional cost factors for assembly, overhead, and profits.", + "laborHours": 2340.8, + "languages": [ + "Python" + ], + "name": "Turbine_CostSE (Turbine Cost Systems Engineering Model) DEPRECATED [SWR-13-30]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/turbine_costsse", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "nacelleSE and hubSE are a set of models that size wind turbine hub system and drivetrain components based on key turbine design parameters and load inputs from a rotor model.", + "laborHours": 3070.4, + "name": "Nacelle Systems Engineering Model and Hub Systems Engineering Model", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/drivese", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A module for static aerodynamic and structural analysis of wind turbine towers", + "laborHours": 2219.2, + "name": "TowerSE", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/towerse", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A module for static aerodynamic and structural analysis of wind turbine rotors", + "laborHours": 15960.0, + "name": "RotorSE", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/rotorse", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-12-14" + }, + "description": "pBEAM (Polynomial Beam Element Analysis Module) is a finite element method for beam-like structures.", + "laborHours": 75118.4, + "languages": [ + "C++", + "C", + "Fortran", + "Python" + ], + "name": "pBEAM (Polynomial Beam Element Analysis Module) [SWR-13-20]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/pbeam", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-10-25" + }, + "description": "A blade element momentum method for analyzing wind turbine aerodynamic performance that is robust (guaranteed convergence), fast (superlinear convergence rate), and smooth (continuously differentiable). Analytic gradients are also (optionally) provided for the distributed loads, thrust, torque, and power with respect to design variables of interest.", + "laborHours": 3587.2, + "languages": [ + "Meson", + "Fortran", + "Python" + ], + "name": "CCBlade (WISDEM\u00ae) [SWR-13-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/ccblade", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.3" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-10-25" + }, + "description": "A Python module for preprocessing and evaluating aerodynamic ainoil data---primarily for wind turbine applications.", + "laborHours": 1884.8, + "languages": [ + "Python" + ], + "name": "AirfoilPrep.py (WISDEM\u00ae) [SWR 13-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/airfoilpreppy", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2022-09-19" + }, + "description": "NREL_CSM is a set of models that provide an overall cost of energy analysis for the wind plant.", + "laborHours": 2295.2, + "languages": [], + "name": "NREL Wind Energy Cost and Scaling Model", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/nrel_csm", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DrivePy is physics-based drivetrain model that sizes drivetrain components based on aerodynamic and operational loads for use in a systems engineering model. It also calculates costs based on empirical data collected by NREL's National Wind Technology Center.", + "laborHours": 3070.4, + "name": "DrivePy", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/DriveSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-08-17" + }, + "description": "The National Renewable Energy Laboratory (NREL) has developed a new system dynamics global LUC model intended to examine LUC attributed to biofuel production. The BioLUC model represents major global, stocks, flows and produces results under different food and biofuel demand assumptions, with flexible regional divisions. This model is not intended to generate precise numerical estimates, but instead to provide insights into the drivers and dynamic interactions of LUC, population, dietary choices, and biofuel policy.", + "laborHours": 15.2, + "languages": [], + "name": "BioLUC (Bioenergy and Land Use Change) [SWR 13-08]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://creativecommons.org/licenses/by-sa/3.0/legalcode", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bioluc", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.0.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-11" + }, + "description": "pyDAKOTA is an interface to Sandia Laboratory's Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) analysis suite.\n\nAllows for users to construct DAKOTA input, feed the input to DAKOTA, and for DAKOTA to call a python object with a \"dakota_callback\" function for function evaluations.\n\nThis allows for a light-weight custom python interface to DAKOTA.\n\nThis is intended to be used with the OpenMDAO dakota driver\n\nAuthor: NREL WISDEM Team", + "laborHours": 699.2, + "languages": [ + "C++", + "Shell", + "CMake", + "Python" + ], + "name": "pyDAKOTA (Dakota Driver) [SWR-13-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/pyDAKOTA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This software is a learning model excerpted from the BSM that can be used to examine effects of different learning rates and different techno-economics on industry evolution.", + "laborHours": 15.2, + "name": "Learning in Emerging Energy Industries", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/bsm-learning/blob/master/ReadMe.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bsm-learning", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-06-12" + }, + "description": "The BACnet Client is designed to gather data from building control systems through the BACnet protocol and send to various destinations for data logging and collection.", + "laborHours": 15625.6, + "languages": [ + "Java" + ], + "name": "BACnet Client [SWR-13-26]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BACnet", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.3" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The Portals reference implementation is based on the Portals 4.X API, published by Sandia National Laboratories as a freely available public document. It is designed to be an implementation of the Portals Networking Application Programming Interface and is used by several other upper layer protocols like SHMEM, GASNet and MPI. It is implemented over existing networks, specifically Ethernet and InfiniBand networks. This implementation provides Portals networks functionality and serves as a software emulation of Portals compliant networking hardware. It can be used to develop software using the Portals API prior to the debut of Portals networking hardware, such as Bull\u2019s BXI interconnect, as well as a substitute for portals hardware on development platforms that do not have Portals compliant hardware. The reference implementation provides new capabilities beyond that of a typical network, namely the ability to have messages matched in hardware in a way compatible with upper layer software such as MPI or SHMEM. It also offers methods of offloading network operations via triggered operations, which can be used to create offloaded collective operations. Specific details on the Portals API can be found at http://portals4.org.", + "laborHours": 65496.8, + "languages": [ + "Makefile", + "C", + "M4" + ], + "name": "Portals Reference Implementation v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/portals4?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/portals4", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Response Surface Modeling (RSM) Tool Suite is a collection of three codes used to generate an empirical interpolation function for a collection of drag coefficient calculations computed with Test Particle Monte Carlo (TPMC) simulations. The first code, \"Automated RSM\", automates the generation of a drag coefficient RSM for a particular object to a single command. \"Automated RSM\" first creates a Latin Hypercube Sample (LHS) of 1,000 ensemble members to explore the global parameter space. For each ensemble member, a TPMC simulation is performed and the object drag coefficient is computed. In the next step of the \"Automated RSM\" code, a Gaussian process is used to fit the TPMC simulations. In the final step, Markov Chain Monte Carlo (MCMC) is used to evaluate the non-analytic probability distribution function from the Gaussian process. The second code, \"RSM Area\", creates a look-up table for the projected area of the object based on input limits on the minimum and maximum allowed pitch and yaw angles and pitch and yaw angle intervals. The projected area from the look-up table is used to compute the ballistic coefficient of the object based on its pitch and yaw angle. An accurate ballistic coefficient is crucial in accurately computing the drag on an object. The third code, \"RSM Cd\", uses the RSM generated by the \"Automated RSM\" code and the projected area look-up table generated by the \"RSM Area\" code to accurately compute the drag coefficient and ballistic coefficient of the object. The user can modify the object velocity, object surface temperature, the translational temperature of the gas, the species concentrations of the gas, and the pitch and yaw angles of the object. Together, these codes allow for the accurate derivation of an object's drag coefficient and ballistic coefficient under any conditions with only knowledge of the object's geometry and mass.", + "laborHours": 3708.8, + "name": "Response Surface Modeling Tool Suite, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AndrewCWalker/rsm_tool_suite", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "LBANN is a toolkit that is designed to train artificial neural networks efficiently on high performance computing architectures. It is optimized to take advantages of key High Performance Computing features to accelerate neural network training. Specifically it is optimized for low-latency, high bandwidth interconnects, node-local NVRAM, node-local GPU accelerators, and high bandwidth parallel file systems. It is built on top of the open source Elemental distributed-memory dense and spars-direct linear algebra and optimization library that is released under the BSD license. The algorithms contained within LBANN are drawn from the academic literature and implemented to work within a distributed-memory framework.", + "laborHours": 64919.2, + "name": "Livermore Big Artificial Neural Network Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LBANN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Kokkos Clang compiler is a version of the Clang C++ compiler that has been modified to perform targeted code generation for Kokkos constructs in the goal of generating highly optimized code and to provide semantic (domain) awareness throughout the compilation toolchain of these constructs such as parallel for and parallel reduce. This approach is taken to explore the possibilities of exposing the developer\u2019s intentions to the underlying compiler infrastructure (e.g. optimization and analysis passes within the middle stages of the compiler) instead of relying solely on the restricted capabilities of C++ template metaprogramming. To date our current activities have focused on correct GPU code generation and thus we have not yet focused on improving overall performance. The compiler is implemented by recognizing specific (syntactic) Kokkos constructs in order to bypass normal template expansion mechanisms and instead use the semantic knowledge of Kokkos to directly generate code in the compiler\u2019s intermediate representation (IR); which is then translated into an NVIDIA-centric GPU program and supporting runtime calls. In addition, by capturing and maintaining the higher-level semantics of Kokkos directly within the lower levels of the compiler has the potential for significantly improving the ability of the compiler to communicate with the developer in the terms of their original programming model/semantics.", + "laborHours": 2076198.4, + "name": "Kokkos GPU Compiler", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/kokkos-clang/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/kokkos-clang", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "FQCDB builds up existing open source software, FastQC, implementing a modern web interface for across parsed output of FastQC. In addition, FQCDB is extensible as a web service to include additional plots of type line, boxplot, or heatmap, across data formatted according to guidelines. The interface is also configurable via more readable JSON format, enabling customization by non-web programmers.", + "laborHours": 56376.8, + "name": "FASTQ quality control dashboard", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/brwnj/fqc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"rsed\" is an R package that contains tools for stream editing: manipulating text files by making insertions, replacements, deletions, substitutions, or commenting. It hails from the powerful Unix command, \"sed\". While the \"rsed\" package is not nearly as powerful as \"see\", it is much simpler to use. R programmers often write scripts that may require simple manipulation of text files. \"rsed\" addresses that need.", + "laborHours": 136.8, + "name": "rsed", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/rsed/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/rsed", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ROSSTEP is a system for sequentially running roslaunch, rosnode, and bash scripts automatically, for use in Robot Operating System (ROS) applications. 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It has a nearly one-to-one mapping from interface elements to YAML output, and serves as a convenient GUI for working with the ROSSTEP system.", + "laborHours": 714.4, + "name": "ROSSTEP v1.3", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/Kukanani/rosstep/blob/8747daaa86110b2456711906177073ba7d511f92/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Kukanani/ROSSTEP", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-01-29" + }, + "description": "Nuflood Version 1.x is a surface-water hydrodynamic package designed for the simulation of overland flow of fluids. It consists of various routines to address a wide range of applications (e.g., rainfall-runoff, tsunami, storm surge) and real time, interactive visualization tools. Nuflood has been designed for general-purpose computers and workstations containing multi-core processors and/or graphics processing units. The software is easy to use and extensible, constructed in mind for instructors, students, and practicing engineers. Nuflood is intended to assist the water resource community in planning against water-related natural disasters.", + "laborHours": 2325.6, + "languages": [], + "name": "Nuflood, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/nuflood/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/nuflood", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The contact control code is a generalized force control scheme meant to interface with a robotic arm being controlled using the Robot Operating System (ROS). The code allows the user to specify a control scheme for each control dimension in a way that many different control task controllers could be built from the same generalized controller. The input to the code includes maximum velocity, maximum force, maximum displacement, and a control law assigned to each direction and the output is a 6 degree of freedom velocity command that is sent to the robot controller.", + "laborHours": 7174.4, + "name": "Contact Control, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/UTNuclearRoboticsPublic/contact_control/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/UTNuclearRoboticsPublic/contact_control", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The spark-hdf5 package is an extension to the Apache Spark program to allow native access to HDF5 files. It allows users to query the structured files using SQL-like syntax, and can parallelize large queries across several workers.", + "laborHours": 334.4, + "name": "Spark-hdf5", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/spark-hdf5", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The purpose of this software package is to solve large-scale block-angular mixed-integer (linear) programs specified in SMPS format; the major application of this software package is to solving large-scale stochastic mixed-integer programs, which are block-angular.", + "laborHours": 3298.4, + "name": "Parallel Interior Point Solver - Simple Branch & Bound", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/PIPS-SBB", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The code runs the Game of Life among several processors. Each processor uses CUDA to set up the grid's buffer on the GPU, and that buffer is fed to other GPU languages to apply the rules of the game of life. Only the halo is copied off the buffer and exchanged using MPI. This code looks at the interoperability of GPU languages among current platforms.", + "laborHours": 1185.6, + "name": "GPULife", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnkelly/GPULife", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SANDAL is a particle-mesh simulation mini-app. The simple simulated physics propagates a set of particles in a constant, 2D wind field with Gaussian turbulence. SANDAL demonstrates the feasibility of formulating a computational physics problem using an alternative, modern design. Specifically, it is implemented using relational tables and queries, rather than array-based data model. It also is implemented with functional language design and cloud deployment, Scala and Apache Spark, rather than Fortran and MPI+X.", + "laborHours": 456.0, + "name": "Simple rANDom wALk simulation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/Sandal/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/Sandal", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-01-31" + }, + "description": "OpenStudio\u00ae is a cross-platform (Windows, Mac, and Linux) collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance. OpenStudio is an open source (LGPL) project to facilitate community development, extension, and private sector adoption. OpenStudio includes graphical interfaces along with a Software Development Kit (SDK). In addition to the graphical interface, OpenStudio allows building researchers and software developers to quickly get started through its multiple entry levels, including access through C++, Ruby, and C#. Users can leverage the Ruby interface to create OpenStudio Measures that can be easily shared and applied to OpenStudio Models.\n\nOPENSTUDIO\u00ae IS A REGISTERED TRADEMARK OF ALLIANCE FOR SUSTAINABLE ENERGY, LLC, THE MANAGER AND OPERATOR OF THE NATIONAL RENEWABLE ENERGY LABORATORY.", + "laborHours": 4456883.2, + "languages": [ + "Ruby", + "C++" + ], + "name": "OPENSTUDIO\u00ae [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "3.3.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-07-07" + }, + "description": "This translator takes fields from the HPXML and translates them into RESO\u2019s Data Dictionary, which is used in MLS systems for real estate transactions across the country. The purpose is to get energy efficiency data into the real estate transaction.", + "laborHours": 167.2, + "languages": [], + "name": "HPXML2RESO (Home Performance XML to Real Estate Standards Organization Data Dictionary Translator)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hpxml2reso", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Operating software for MET-2 Vaultbot project. Pan-tilt camera control, autonomous task planning, inventory integration functions.", + "laborHours": 1048.8, + "name": "Vaultbot ROS Package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/UTNuclearRoboticsPublic/task_planning", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "NREL's Developer Network, developer.nrel.gov, provides data that users can access to provide data to their own analyses, mobile and web applications. Developers can retrieve the data through a Web services API (application programming interface). The Developer Network handles overhead of serving up web services such as key management, authentication, analytics, reporting, documentation standards, and throttling in a common architecture, while allowing web services and APIs to be maintained and managed independently.", + "laborHours": 64736.8, + "name": "Developer Network", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/developer.nrel.gov/blob/master/source/terms.html.erb", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/developer.nrel.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software is designed for efficiently integrating large-size of multi-scale environmental data using the Bayesian framework. Suppose we need to estimate the spatial distribution of variable X with high spatial resolution. The available data include (1) direct measurements Z of the unknowns with high resolution in a subset of the spatial domain (small spatial coverage), (2) measurements C of the unknowns at the median scale, and (3) measurements A of the unknowns at the coarsest scale but with large spatial coverage. The goal is to estimate the unknowns at the fine grids by conditioning to all the available data. We first consider all the unknowns as random variables and estimate conditional probability distribution of those variables by conditioning to the limited high-resolution observations (Z). We then treat the estimated probability distribution as the prior distribution. Within the Bayesian framework, we combine the median and large-scale measurements (C and A) through likelihood functions. Since we assume that all the relevant multivariate distributions are Gaussian, the resulting posterior distribution is a multivariate Gaussian distribution. The developed software provides numerical solutions of the posterior probability distribution. The software can be extended in several different ways to solve more general multi-scale data integration problems.", + "laborHours": 684.0, + "name": "Bayesian Integration of multiscale environmental data", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jschen83/Multiscale-Bayesian-Integration/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jschen83/Multiscale-Bayesian-Integration", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OpenSHMEM is an effort to create a specification for a standardized API for parallel programming in the Partitioned Global Address Space. Along with the specification the project is also creating a reference implementation of the API. This implementation attempts to be portable, to allow it to be deployed in multiple environments, and to be a starting point for implementations targeted to particular hardware platforms. It will also serve as a springboard for future development of the API.", + "laborHours": 9469.6, + "name": "Open SHMEM Reference Implementation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/openshmem-org/openshmem/blob/master/ACKNOWLEDGEMENT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openshmem-org/openshmem", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Suite of Python Libraries that implement structure data format processing, multivariate analysis, and interactive visualization of microscopy data and other spectral imaging modalities, including scanning probe microscopy, electron microscopy, Bragg diffraction microscopy, and chemical imaging.", + "laborHours": 12783.2, + "name": "pyCroscopy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pycroscopy/pycroscopy", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The purpose of this software is to interpret and analyze data taken using the NI PXIe-5171R digitizer based data acquisition system for the UCNB and Nab experiments. The detection and data acquisition systems are identical for the 2 experiments, with some differences in analysis requirements. The software converts raw binary files produced by the NI DAQ into ROOT TTree format, performs waveform analysis using trapezoidal filter algorithms, pulse fitting, and noise analysis routines, and applies variable criteria to identify valid events in the data stream. The software will be used to perform analysis of the events for multi-channel coincidences, timing and energy studies, and event rates under different experimental conditions.", + "laborHours": 5456.8, + "name": "UCNB_Analyzer", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/UCNB_Analyzer", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "GraphBench is a benchmark suite for graph pattern mining and graph analysis systems. The benchmark suite is a significant addition to conducting apples-apples comparison of graph analysis software (databases, in-memory tools, triple stores, etc.)", + "laborHours": 19121.6, + "name": "GraphBench", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ssrangan/GraphBench/blob/master/Open%20Source%20Software%20License%20(Permissive%20May%202015)%20for%20GM-SPARQL.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ssrangan/GraphBench", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Availability of accessing the World Bank Data API through the R language was limited to one existing package, which is limited in its ability. The software provides access to all of the features in World Bank API in one software package for the R language and provides functions for searching and downloading data from the World Bank API.", + "laborHours": 729.6, + "name": "wbstats", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GIST-ORNL/wbstats/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GIST-ORNL/wbstats", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Mcqueuer is a simple tool that allows anyone from researchers to experienced developers to create multi-node/multi-core jobs by simply creating a file with a list of commands. Users simply combine tasks, which would otherwise each be their own job on the cluster, into a single file that is given to Mcqueuer. Mcqueuer then does the heavy lifting required to process the tasks in parallel in a single multi-node job. In addition, Mcqueuer provides load-balancing, which frees the user from having to worry about complex memory and CPU considerations, and instead focus on the processing itself.", + "laborHours": 198785.6, + "name": "Mcqueuer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/aaronrphillips/mcqr/blob/master/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aaronrphillips/mcqr", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "AE3D solves for the shear Alfven eigenmodes and eigenfrequencies in a torodal magnetic fusion confinement device. The configuration can be either 2D (e.g. tokamak, reversed field pinch) or 3D (e.g. stellarator, helical reversed field pinch, tokamak with ripple). The equations solved are based on a reduced MHD model and sound wave coupling effects are not currently included.", + "laborHours": 1428.8, + "name": "AE3D", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-Fusion/AE3D", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Stellgap calculates the shear Alfven gap structure for 3D configurations (stellarators, RFPs, 3D tokamaks). These codes are used to calculate shear Alfven continua for 3D configurations, both with and without sound wave coupling effects.", + "laborHours": 2462.4, + "name": "Stellgap", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-Fusion/Stellgap", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-19" + }, + "description": "GeoPlace software solves several problems related to efficient sensor placement for remote sensing. It consists of several components. \u201cGeoFoot\u201d finds efficient locations for centering a set of camera images, in order to ensure that the collection of images contains an entire region. It is built on a modified version of \u201cSimple MPS\u201d. GeoSubFoot selects non-overlapping rectangular subregions of a single camera image, in order to devote more resources for higher-fidelity sub-images of those regions. The goal is for the rectangular subregions to contain many user-specified pixels of interest. Simple MPS is a generic program that produces point-sample distributions with blue noise characteristics over arbitrary-dimensional squares. GeoFoot includes an extension of it to sampling from polygons in 2d, including both the inside of the polygon and slightly outside it.", + "laborHours": 2280.0, + "languages": [ + "C++", + "Shell", + "Makefile", + "Python" + ], + "name": "GeoPlace v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/GeoPlace?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cgvalic/GeoPlace", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DFNWorks is a suite of software for generating and solving flow and transport physics on a Discrete Fracture Network (DFN). The suite is composed of three components: DFNGen: Stochastic fracture generation, mesh generation, model setup; DFNFlow: Flow solution using PFLOTRAN or FEHM control volume formulation solver; DFNTrans: Particle tracking transport; DFNGen Algorithm Description: This is a workflow that uses Mathematica software, Python scripts written by the authors and the LaGriT software to generate; DFNFlow; The solution of flow in porous media is accomplished by coupling DFNGen output with the existing software packages FEHM and PFLOTRAN. The DFNWorks workflow involves modules and scripts that translate DFNGen output to formats compatible with FEHM and PFLOTRAN input. FEHM LA-CC-2012-083 PFLOTRAN LA-CC-09-047 LaGriT LA-CC-07-38 DFNTrans Stand alone particle tracking algorithm that takes FEHM/PFLOTRAN flow solution as output and computes velocity field and advects particles.", + "laborHours": 10700.8, + "name": "dfnWorks, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/dfnWorks/dfnWorks-Version1.0/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dfnWorks/dfnWorks-Version1.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code is a toy (short) version of CODE-2016-83. From a general perspective, the code represents an unsupervised adaptive machine learning algorithm that allows efficient and high performance de-mixing and feature extraction of a multitude of non-negative signals mixed and recorded by a network of uncorrelated sensor arrays. The code identifies the number of the mixed original signals and their locations. Further, the code also allows deciphering of signals that have been delayed in regards to the mixing process in each sensor. This code is high customizable and it can be efficiently used for a fast macro-analyses of data. The code is applicable to a plethora of distinct problems: chemical decomposition, pressure transient decomposition, unknown sources/signal allocation, EM signal decomposition. An additional procedure for allocation of the unknown sources is incorporated in the code.", + "laborHours": 1960.8, + "name": "shiftNMFk 1.1: Robust Nonnegative matrix factorization with kmeans clustering and signal shift, for allocation of unknown physical sources, toy version for open sourcing with publications", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/rNMF/ShiftNMFk.jl/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rNMF/ShiftNMFk.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "A Splunk App designed to parse and tabulate PathScan data.", + "laborHours": 15.2, + "name": "PathScan for Splunk", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jwernicke/pathscan-splunk", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jwernicke/pathscan-splunk", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Mads.jl (Model analysis and decision support in Julia) is a code that streamlines the process of using data and models for analysis and decision support. It is based on another open-source code developed at LANL and written in C/C++ (MADS; http://mads.lanl.gov; LA-CC-11- 035). Mads.jl can work with external models of arbitrary complexity as well as built-in models of flow and transport in porous media. It enables a number of data- and model-based analyses including model calibration, sensitivity analysis, uncertainty quantification, and decision analysis. The code also can use a series of alternative adaptive computational techniques for Bayesian sampling, Monte Carlo, and Bayesian Information-Gap Decision Theory. The code is implemented in the Julia programming language, and has high-performance (parallel) and memory management capabilities. The code uses a series of third party modules developed by others. The code development will also include contributions to the existing third party modules written in Julia; this contributions will be important for the efficient implementation of the algorithm used by Mads.jl. The code also uses a series of LANL developed modules that are developed by Dan O'Malley; these modules will be also a part of the Mads.jl release. Mads.jl will be released under GPL V3 license. The code will be distributed as a Git repo at gitlab.com and github.com. Mads.jl manual and documentation will be posted at madsjulia.lanl.gov.", + "laborHours": 150434.4, + "name": "Mads.jl", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/madsjulia/Mads.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HPSim is a GPU-accelerated online multi-particle beam dynamics simulation tool for ion linacs. It was originally developed for use on the Los Alamos 800-MeV proton linac. It is a \u201cz-code\u201d that contains typical linac beam transport elements. The linac RF-gap transformation utilizes transit-time-factors to calculate the beam acceleration therein. The space-charge effects are computed using the 2D SCHEFF (Space CHarge EFFect) algorithm, which calculates the radial and longitudinal space charge forces for cylindrically symmetric beam distributions. Other space- charge routines to be incorporated include the 3D PICNIC and a 3D Poisson solver. HPSim can simulate beam dynamics in drift tube linacs (DTLs) and coupled cavity linacs (CCLs). Elliptical superconducting cavity (SC) structures will also be incorporated into the code. The computational core of the code is written in C++ and accelerated using the NVIDIA CUDA technology. Users access the core code, which is wrapped in Python/C APIs, via Pythons scripts that enable ease-of-use and automation of the simulations. The overall linac description including the EPICS PV machine control parameters is kept in an SQLite database that also contains calibration and conversion factors required to transform the machine set points into model values used in the simulation.", + "laborHours": 31661.6, + "name": "HPSim, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/apphys/hpsim/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/apphys/hpsim", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The SIERRA Toolkit is a collection of libraries to facilitate the development of parallel engineering analysis applications. These libraries supply basic core services that an engineering application may need such as a parallel distributed and dynamic mesh database (for unstructured meshes), mechanics algorithm support (parallel infrastructure only), interfaces to parallel solvers, parallel mesh and data I/O, and various utilities (timers, diagnostic tools, etc.)", + "laborHours": 8344830.4, + "languages": [ + "C++" + ], + "name": "SIERRA Toolkit v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "The IonControl software is a set of python scripts and Field-Programmable-Gate-Array (FPGA) code designed to control a trapped ion research experiment. It enables one to generate the pulses (time resolution: 20ns) necessary to control the quantum states of trapped ions and allows one to collect and analyze measurement results from trapped ion systems.", + "laborHours": 228410.4, + "languages": [ + "CSS", + "HTML", + "TeX", + "JavaScript", + "PostScript", + "Python" + ], + "name": "IonControl v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IonControl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-11-06" + }, + "description": "VOLTTRON\u2122 is an agent execution platform providing services to its agents that allow them to easily communicate with physical devices and other resources. VOLTTRON\u2122 delivers an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls. It enables mobile and stationary software agents to perform information gathering, processing, and control actions. VOLTTRON\u2122 can independently manage a wide range of applications, such as HVAC systems, electric vehicles, distributed energy or entire building loads, leading to improved operational efficiency.", + "laborHours": 0.0, + "languages": [], + "name": "VOLTTRON Version 4", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron/releases/tag/4.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "4.0" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Electrostatics software under development since 1999. Soee http://www.poissonboltzmann.org/ for more detail.", + "laborHours": 262975.2, + "name": "APBS (Adaptive Poisson-Boltzmann Solver) and PDB2PQR", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electrostatics/apbs-pdb2pqr", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PyGeoTess is a Python interface module to the GeoTess gridding and earth model library from Sandia National Laboratories. It provides simplified access to a subset of the GeoTess C++ library, and takes advantage of Python's interactive interpreter and inline documentation system.", + "laborHours": 8299.2, + "name": "PyGeoTess 0.2.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LANL-Seismoacoustics/PyGeoTess/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-seismoacoustics/pygeotess", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Whole community shotgun sequencing of total DNA (i.e. metagenomics) and total RNA (i.e. metatranscriptomics) has provided a wealth of information in the microbial community structure, predicted functions, metabolic networks, and is even able to reconstruct complete genomes directly. Here we present ATLAS (Automatic Tool for Local Assembly Structures) a comprehensive pipeline for assembly, annotation, genomic binning of metagenomic and metatranscriptomic data with an integrated framework for Multi-Omics. This will provide an open source tool for the Multi-Omic community at large.", + "laborHours": 4438.4, + "name": "Automatic Tool for Local Assembly Structures", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/atlas", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The MC3 code is used to perform Monte Carlo simulations in the isothermal-isobaric ensemble (constant number of particles, temperature, and pressure) on molecular crystals. The molecules within the periodic simulation cell are treated as rigid bodies, alleviating the requirement for a complex interatomic potential. Intermolecular interactions are described using generic, atom-centered pair potentials whose parameterization is taken from the literature [D. E. Williams, J. Comput. Chem., 22, 1154 (2001)] and electrostatic interactions arising from atom-centered, fixed, point partial charges. The primary uses of the MC3 code are the computation of i) the temperature and pressure dependence of lattice parameters and thermal expansion coefficients, ii) tensors of elastic constants and compliances via the Parrinello and Rahman\u2019s fluctuation formula [M. Parrinello and A. Rahman, J. Chem. Phys., 76, 2662 (1982)], and iii) the investigation of polymorphic phase transformations. The MC3 code is written in Fortran90 and requires LAPACK and BLAS linear algebra libraries to be linked during compilation. Computationally expensive loops are accelerated using OpenMP.", + "laborHours": 0.0, + "name": "MC3, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cawkwell/MC3", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Software library for parallel rapid order N and graph-based recursive electronic structure solvers with applications to material science, chemistry, and molecular biology.", + "laborHours": 425.6, + "name": "Progress Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/progress/progress.github.io", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The code would be used in analyses of data from the LHC, to improve the sensitivity of their experiments to new exotic particles. The software minimizes a certain function, as defined in the above reference, for some input provided by the user. The output to the user is the global minimum of that function. The code finds the global minimum using the Nelder-Mead algorithm. All the codes for the minimization including the Nelder-Mead algorithm, is written by the author. The software is written in c++.", + "laborHours": 0.0, + "name": "Topness, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/michaelgraesser/topness/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/michaelgraesser/topness", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-03-28" + }, + "description": "Sirepo is an open source framework for cloud computing. The graphical user interface (GUI) for Sirepo, also known as the client, executes in any HTML5 compliant web browser on any computing platform, including tablets. The client is built in JavaScript, making use of the following open source libraries: Bootstrap, which is fundamental for cross-platform web applications; AngularJS, which provides a model\u2013view\u2013controller (MVC) architecture and GUI components; and D3.js, which provides interactive plots and data-driven transformations. The Sirepo server is built on the following Python technologies: Flask, which is a lightweight framework for web development; Jinja, which is a secure and widely used templating language; and Werkzeug, a utility library that is compliant with the WSGI standard. We use Nginx as the HTTP server and proxy, which provides a scalable event-driven architecture. The physics codes supported by Sirepo execute inside a Docker container. One of the codes supported by Sirepo is the Synchrotron Radiation Workshop (SRW). SRW computes synchrotron radiation from relativistic electrons in arbitrary magnetic fields and propagates the radiation wavefronts through optical beamlines. SRW is open source and is primarily supported by Dr. Oleg Chubar of NSLS-II at Brookhaven National Laboratory.", + "laborHours": 158824.8, + "name": "Sirepo for Synchrotron Radiation Workshop", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/radiasoft/sirepo", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Sirepo is an open source framework for cloud computing. The graphical user interface (GUI) for Sirepo, also known as the client, executes in any HTML5 compliant web browser on any computing platform, including tablets. The client is built in JavaScript, making use of the following open source libraries: Bootstrap, which is fundamental for cross-platform web applications; AngularJS, which provides a model\u2013view\u2013controller (MVC) architecture and GUI components; and D3.js, which provides interactive plots and data-driven transformations. The Sirepo server is built on the following Python technologies: Flask, which is a lightweight framework for web development; Jin-ja, which is a secure and widely used templating language; and Werkzeug, a utility library that is compliant with the WSGI standard. We use Nginx as the HTTP server and proxy, which provides a scalable event-driven architecture. The physics codes supported by Sirepo execute inside a Docker container. One of the codes supported by Sirepo is Warp. Warp is a particle-in-cell (PIC) code de-signed to simulate high-intensity charged particle beams and plasmas in both the electrostatic and electromagnetic regimes, with a wide variety of integrated physics models and diagnostics. At pre-sent, Sirepo supports a small subset of Warp\u2019s capabilities. Warp is open source and is part of the Berkeley Lab Accelerator Simulation Toolkit.", + "laborHours": 158824.8, + "name": "Sirepo - Warp", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/radiasoft/sirepo", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OSCARS is a general purpose code for computation of radiation from charged particles in motion.", + "laborHours": 18559.2, + "name": "Open Source Code for Advanced Radiation Simulation", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/dhidas/OSCARS/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dhidas/OSCARS", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Nanoindentation is a tool that allows the mechanical response of a variety of materials at the nano to micron length scale to be measured. Recent advances in spherical nanoindentation techniques have allowed for a more reliable and meaningful characterization of the mechanical response from nanoindentation experiments in the form on an indentation stress-strain curve. This code base, Spin, is written in MATLAB (The Mathworks, Inc.) and based on the analysis protocols developed by S.R. Kalidindi and S. Pathak [1, 2]. The inputs include the displacement, load, harmonic contact stiffness, harmonic displacement, and harmonic load from spherical nanoindentation tests in the form of an Excel (Microsoft) spreadsheet. The outputs include indentation stress-strain curves and indentation properties as well their variance due to the uncertainty of the zero-point correction in the form of MATLAB data (.mat) and figures (.png). [1] S. Pathak, S.R. Kalidindi. Spherical nanoindentation stress\u2013strain curves, Mater. Sci. Eng R-Rep 91 (2015). [2] S.R. Kalidindi, S. Pathak. Determination of the effective zero-point and the extraction of spherical nanoindentation stress-strain curves, Acta Materialia 56 (2008) 3523-3532.", + "laborHours": 440.8, + "name": "Spherical nanoindentation stress-strain analysis, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jsweaver/Spin", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-03-21" + }, + "description": "Arion is a library and tool set that enables researchers to holistically define test system models. To define a complex system for testing an algorithm or control requires expertise across multiple domains. Simulating a complex system requires the integration of multiple simulators and test hardware, each with their own specification languages and concepts. This requires extensive set of knowledge and capabilities. Arion was developed to alleviate this challenge. Arion is a library of Java libraries that abstracts the concepts from supported simulators into a cohesive model language that allows someone to build models to their needed level of fidelity and expertise. Arion is also a software tool that translates the users model back into the specification languages of the simulators and test hardware needed for execution.", + "laborHours": 10016.8, + "languages": [], + "name": "Arion", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/arion/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/arion", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A system for processing network packet capture streams, extracting metadata and generating flow records (via Argus). The system can be used by network security operators and analysts to enable forensic investigations for network security events.", + "laborHours": 1094.4, + "name": "Retro-Future", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cardi/timefind", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MADSpython (Model analysis and decision support tools in Python) is a code in Python that streamlines the process of using data and models for analysis and decision support using the code MADS. MADS is open-source code developed at LANL and written in C/C++ (MADS; http://mads.lanl.gov; LA-CC-11-035). MADS can work with external models of arbitrary complexity as well as built-in models of flow and transport in porous media. The Python scripts in MADSpython facilitate the generation of input and output file needed by MADS as wells as the external simulators which include FEHM and PFLOTRAN. MADSpython enables a number of data- and model-based analyses including model calibration, sensitivity analysis, uncertainty quantification, and decision analysis. MADSpython will be released under GPL V3 license. MADSpython will be distributed as a Git repo at gitlab.com and github.com. MADSpython manual and documentation will be posted at http://madspy.lanl.gov.", + "laborHours": 182.4, + "name": "MADSpython 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/madspython", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-11-26" + }, + "description": "MICOT is a tool for optimizing and controlling infrastructure systems. In includes modules for optimizing the operations of an infrastructure structure (for example optimal dispatch), designing infrastructure systems, restoring infrastructures systems, resiliency, preparing for natural disasters, interdicting networks, state estimation, sensor placement, and simulation of infrastructure systems. It implements algorithms developed at LANL that have been published in the academic community. This is a release of the of resilient design module of the MICOT.", + "laborHours": 12281858.4, + "languages": [], + "name": "Multi Infrastructure Control and Optimization Toolkit, Resilient Design Module (MICOT-RDT), version 2.X", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl-ansi/micot-rdt/blob/master/LICENCE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/micot", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-10" + }, + "description": "RmultiProcess software is designed to work with multiple correlated sensors. The characteristic that allows data to be filled in or the support to be changed is correlation, the interdependence between observations.", + "laborHours": 167.2, + "languages": [], + "name": "Multivariate Gaussian Process Model for Correlated Time Series in R", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/multivariate-gaussian-process-model-for-correlated-time-series-in-r", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Returns bitwise identical sums regardless of the order of the summands. Uses no branches and mostly integer operations. Designed to be vectorizeable.", + "laborHours": 60.8, + "name": "Branchless Reproducible Floating Point Summation With Integers, Version 1.x.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/peterahrens/BranchlessReproducibleFloatingPointWithIntegers/blob/master/brfpwi.c", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/peterahrens/BranchlessReproducibleFloatingPointWithIntegers", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DView is a time series data visualization tool that provides several different ways to plot time series datasets. It is particularly well suited for browsing the results of energy systems simulation programs such as BeOpt, SAM, and PVWatts.", + "laborHours": 205640.8, + "name": "DVIEW", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/wex", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This software presents a user-provided multivariate dataset as an interactive three dimensional visualization so that the user can explore the correlation between variables in the observations and the distribution of observations among the variables.", + "laborHours": 896.8, + "name": "Parallel Planes Information Visualization", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/infovis-parallel", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Clog is a library of charged particle stopping powers and related Coulomb logarithm processes in a plasma. The stopping power is a particularly useful quantity for plasma physics, as it measures the energy loss of per unit length of charged particle as it traverses a plasma. Clog's primary stopping power is the BPS (Brown-Preston-Singleton) theory.", + "laborHours": 5532.8, + "name": "Coulomb Logarithm, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/clog/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/clog", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "NJOY2016 is used to convert evaluations in the Evaluated Nuclear Data Files (ENDF) format into forms useful for practical applications such as fission and fusion reactor analysis, criticality safety, radiation shielding, nuclear waste management, nuclear medicine procedures, and more. It begins with the generation of pointwise libraries, including reaction and resonance reconstruction, Doppler broadening, radiation heating and damage, thermal scattering data, unresolved resonance data, and gas production. It reviews the production of libraries for the continuous-energy Monte Carlo code MCNP, multigroup neutron, photon, and particle cross sections and matrices, and photon interaction data. Uncertainty information for ENDF data is processed, including the capability for calculating covariances of resonance data, angular distributions, energy distributions, and radioactive nuclide production. NJOY can prepare and process thermal scattering data evaluations into application libraries. It can also plot cross sections, angular distributions and secondary emission spectra.", + "laborHours": 1945.6, + "name": "NJOY2016", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/njoy/NJOY21/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/njoy/NJOY21.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Tusas is a general / flexible software framework for solving coupled systems of onlinear partial differential equations. Tusas was originally developed for phase-field simulation of solidification. In order for Tusas to be effective, the PDEs must be compatible with structured or unstructured Lagrange (nodal) finite element discretizations and explicit (Euler) or implicit (Euler, Trapezoid, BDF2) temporal discretizations.", + "laborHours": 10442.4, + "name": "Tusas, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chrisknewman/tusas", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code implements the non-homogeneous poisson process model for estimating the rate of fast radio bursts. It includes modeling terms for the distribution of events in the Universe and the detection sensitivity of the radio telescopes and arrays used in observation. The model is described in LA-UR-16-26261.", + "laborHours": 121.6, + "name": "NHPP for FRBs, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/NHPP-for-FRBs/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/NHPP-for-FRBs", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "TBM3 is an open source package for computational simulations of quantum materials at multiple scales in length and time. The project originated to investigate the multiferroic behavior in transition-metal oxide heterostructures. The framework has also been designed to study emergent phemona in other quantum materials like 2-dimensional transition-metal dichalcogenides, graphene, topological insulators, and skyrmion in materials, etc. In the long term, we will enable the package for transport and time-resolved phenomena. TBM3 is currently a C++ based numerical tool package and framework for the design and construction of any kind of lattice structures with multi-orbital and spin degrees of freedom. The fortran based portion of the package will be added in the near future. The design of TBM3 is in a highly flexible and reusable framework and the tight-binding parameters can be modeled or informed by DFT calculations. It is currently GPU enabled and feature of CPU enabled MPI will be added in the future.", + "laborHours": 4286.4, + "name": "Tight-binding model for materials at mesoscale", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/TDIV/TBM3/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/TDIV/TBM3", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "An example of reading the Galacticus HDF5 file in R and a demonstration of some of the features of the data.", + "laborHours": 15.2, + "name": "Galacticus HDF5 Example, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/Galacticus-HDF5-Example/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/Galacticus-HDF5-Example", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PcapDB is a packet capture system designed to optimize the captured data for fast search in the typical (network incident response) use case. The technology involved in this software has been submitted via the IDEAS system and has been filed as a provisional patent. It includes the following primary components: capture: The capture component utilizes existing capture libraries to retrieve packets from network interfaces. Once retrieved the packets are passed to additional threads for sorting into flows and indexing. The sorted flows and indexes are passed to other threads so that they can be written to disk. These components are written in the C programming language. search: The search components provide a means to find relevant flows and the associated packets. A search query is parsed and represented as a search tree. Various search commands, written in C, are then used resolve this tree into a set of search results. The tree generation and search execution management components are written in python. interface: The PcapDB web interface is written in Python on the Django framework. It provides a series of pages, API's, and asynchronous tasks that allow the user to manage the capture system, perform searches, and retrieve results. Web page components are written in HTML,CSS and Javascript.", + "laborHours": 194301.6, + "name": "PcapDB: Search Optimized Packet Capture, Version 0.1.0.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dirtbags/pcapdb", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The JMP Add-In TopN-PFS provides an automated tool for finding layered Pareto front to identify the top N solutions from an enumerated list of candidates subject to optimizing multiple criteria. The approach constructs the N layers of Pareto fronts, and then provides a suite of graphical tools to explore the alternatives based on different prioritizations of the criteria. The tool is designed to provide a set of alternatives from which the decision-maker can select the best option for their study goals.", + "laborHours": 0.0, + "name": "TopN-Pareto Front Search", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/candcook/TopN-PFS/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/candcook/TopN-PFS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Code Analysis and Refactoring with Clang Tools is a small set of example code that demonstrates techniques for applying tools distributed with the open source Clang compiler. Examples include analyzing where variables are used and replacing old data structures with standard structures.", + "laborHours": 2675.2, + "name": "Code Analysis and Refactoring with Clang Tools, Version 0.1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/CoARCT", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A common operation in scientific visualization is to compute and render a contour of a data set. Given a function of the form f : R^d -> R, a level set is defined as an inverse image f^-1(h) for an isovalue h, and a contour is a single connected component of a level set. The Reeb graph can then be defined to be the result of contracting each contour to a single point, and is well defined for Euclidean spaces or for general manifolds. For simple domains, the graph is guaranteed to be a tree, and is called the contour tree. Analysis can then be performed on the contour tree in order to identify isovalues of particular interest, based on various metrics, and render the corresponding contours, without having to know such isovalues a priori. This code is intended to be the first data-parallel algorithm for computing contour trees. Our implementation will use the portable data-parallel primitives provided by Nvidia\u2019s Thrust library, allowing us to compile our same code for both GPUs and multi-core CPUs. Native OpenMP and purely serial versions of the code will likely also be included. It will also be extended to provide a hybrid data-parallel / distributed algorithm, allowing scaling beyond a single GPU or CPU.", + "laborHours": 204652.8, + "name": "Hybrid Parallel Contour Trees, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.kitware.com/vtk/vtk-m/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk-m", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The ParSplice code implements the Parallel Trajectory Splicing algorithm described in [1]. This method is part of the Accelerated Molecular Dynamics family of techniques developed in Los Alamos National Laboratory over the last 16 years. These methods aim at generating high-quality trajectories of ensembles of atoms in materials. ParSplice uses multiple independent replicas of the system in order to parallelize the generation of such trajectories in the time domain, enabling simulations of systems of modest size over very long timescales. ParSplice includes capabilities to store configurations of the system, to generate and distribute tasks across a large number of processors, and to harvest the results of these tasks to generate long trajectories. ParSplice is a management layer that orchestrate large number of calculations, but it does not perform the actual molecular dynamics itself; this is done by external molecular dynamics engines. [1] Danny Perez, Ekin D Cubuk, Amos Waterland, Efthimios Kaxiras, Arthur F Voter, Long-time dynamics through parallel trajectory splicing, Journal of chemical theory and computation 12, 18 (2015)", + "laborHours": 1398.4, + "name": "ParSplice, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/dannyperez/parsplice/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/dannyperez/parsplice", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "TRPS code was developed for the project \"Time Resolved Phonon Spectroscopy\". Routines contained in this piece of software were specially created to model phonon generation and tracking within materials that interact with ionizing radiation, particularly applicable to the modeling of cryogenic radiation detectors for dark matter and neutrino research. These routines were created to link seamlessly with the open source Geant4 framework for the modeling of radiation transport in matter, with the explicit intent of open sourcing them for eventual integration into that code base.", + "laborHours": 1124.8, + "name": "Time Resolved Phonon Spectroscopy, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/goett/TRPS/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/goett/TRPS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "It can be challenging to interface National Instruments LabVIEW (http://www.ni.com/labview/) with EPICS (http://www.aps.anl.gov/epics/). Such interface is required when an instrument control program was developed in LabVIEW but it also has to be part of global control system. This is frequently useful in big accelerator facilities. The Channel Access Server is written in LabVIEW, so it works on any hardware/software platform where LabVIEW is available. It provides full server functionality, so any EPICS client can communicate with it.", + "laborHours": 243.2, + "name": "EPICS Channel Access Server for LabVIEW", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/az9/LVCA/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/az9/LVCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Fortran language does not provide a standard library that implements generic containers, like linked lists, trees, dictionaries, etc. The GFC software provides an implementation of generic Fortran containers natively written in Fortran 2003/2008 language. The following containers are either already implemented or planned: Stack (done), Linked list (done), Tree (done), Dictionary (done), Queue (planned), Priority queue (planned).", + "laborHours": 8268.8, + "name": "Generic Fortran Containers (GFC)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/DmitryLyakh/GFC", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Flexible visible exploration of long, high-resolution time series from multiple sensor streams is a challenge in several domains. Falcon is a visual analytics approach that helps researchers acquire a deep understanding of patterns in log and imagery data. Falcon allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations with multiple levels of detail. These capabilities are applicable to the analysis of any quantitative time series.", + "laborHours": 0.0, + "name": "Falcon: A Temporal Visual Analysis System", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csteed/falcon", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DFNWorks is a suite of software for generating and solving flow and transport physics on a Discrete Fracture Network (DFN). The suite is composed of three components: DFNGen: Stochastic fracture generation, mesh generation, model setup; DFNFlow: Flow solution using PFLOTRAN or FEHM control volume formulation solver; DFNTrans: Particle tracking transport; DFNGen Algorithm Description: This is a workflow that uses C++ software version for fracture generation, Python scripts written by the authors and the LaGriT software to generate computational mesh. DFNFlow The solution of flow in porous media is accomplished by coupling DFNGen output with the existing software packages FEHM and PFLOTRAN. The DFNWorks workflow involves modules and scripts that translate DFNGen output to formats compatible with FEHM and PFLOTRAN input. FEHM LA-CC-2012-083 PFLOTRAN LA-CC-09-047 LaGriT LA-CC-07-38 DFNTrans Stand-alone particle tracking algorithm that takes FEHM/PFLOTRAN flow solution as output and computes velocity field and advects particles.", + "laborHours": 0.0, + "name": "dfnWorks, Version 2.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dfnWorks/dfnWorks-Version2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code is made to model the effect of muons in a future double beta decay array with the Geant4 software framework.", + "laborHours": 471.2, + "name": "Muon GUORE - Geant4 MACRO for nextGEN 0vBB", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/massarczyk/Muon_GUORE/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/massarczyk/Muon_GUORE", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Securely transferring timing information in the electrical grid is a critical component of securing the nation's infrastructure from cyber attacks. One solution to this problem is to use quantum information to securely transfer the timing information across sites. This software provides such an infrastructure using a standard Java webserver that pulls the quantum information from associated hardware.", + "laborHours": 699.2, + "name": "TASQC Quantum Key Transfer Program", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/TASQC/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/TASQC", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Finding Godsil-McKay switching sets in graphs is one way to demonstrate that a specific graph is not determined by its spectrum--the eigenvalues of its adjacency matrix. An important area of active research in pure mathematics is determining which graphs are determined by their spectra, i.e. when the spectrum of the adjacency matrix uniquely determines the underlying graph. We are interested in exploring the spectra of graphs in the Johnson scheme and specifically seek to determine which of these graphs are determined by their spectra. Given a graph G, a Godsil-McKay switching set is an induced subgraph H on 2k vertices with the following properties: I) H is regular, ii) every vertex in G/H is adjacent to either 0, k, or 2k vertices of H, and iii) at least one vertex in G/H is adjacent to k vertices in H. The software package examines each subset of a user specified size to determine whether or not it satisfies those 3 conditions. The software makes use of the massive parallel processing power of CUDA enabled GPUs. It also exploits the vertex transitivity of graphs in the Johnson scheme by reasoning that if G has a Godsil-McKay switching set, then it has a switching set which includes vertex 1. While the code (in its current state) is tuned to this specific problem, the method of examining each induced subgraph of G can be easily re-written to check for any user specified conditions on the subgraphs and can therefore be used much more broadly.", + "laborHours": 106.4, + "name": "CUDA Enabled Graph Subset Examiner", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jtjohnston/computational_combinatorics/blob/master/GM-switching/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jtjohnston/computational_combinatorics", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Hybrid programming models for beyond-CMOS technologies will prove critical for integrating new computing technologies alongside our existing infrastructure. Unfortunately the software infrastructure required to enable this is lacking or not available. XACC is a programming framework for extreme-scale, post-exascale accelerator architectures that integrates alongside existing conventional applications. It is a pluggable framework for programming languages developed for next-gen computing hardware architectures like quantum and neuromorphic computing. It lets computational scientists efficiently off-load classically intractable work to attached accelerators through user-friendly Kernel definitions. XACC makes post-exascale hybrid programming approachable for domain computational scientists.", + "laborHours": 454860.0, + "name": "XACC - eXtreme-scale Accelerator Programming Framework", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/xacc", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "There is a lack of state-of-the-art HPC simulation tools for simulating general quantum computing. Furthermore, there are no real software tools that integrate current quantum computers into existing classical HPC workflows. This product, the Quantum Virtual Machine (QVM), solves this problem by providing an extensible framework for pluggable virtual, or physical, quantum processing units (QPUs). It enables the execution of low level quantum assembly codes and returns the results of such executions.", + "laborHours": 15.2, + "name": "Quantum Virtual Machine (QVM)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-QCI/qvm", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/qvm", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "There is a lack of state-of-the-art quantum computing simulation software that scales on heterogeneous systems like Titan. Tensor Network Quantum Virtual Machine (TNQVM) provides a quantum simulator that leverages a distributed network of GPUs to simulate quantum circuits in a manner that leverages recent results from tensor network theory.", + "laborHours": 23332.0, + "name": "Tensor Network Quantum Virtual Machine (TNQVM)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-QCI/tnqvm/blob/master/examples/CMakeLists.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/tnqvm", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "There are many common software patterns and utilities for the ORNL Quantum Computing Institute that can and should be shared across projects. Otherwise we find duplication of code which adds unwanted complexity. This is a software product seeks to alleviate this by providing common utilities such as object factories, graph data structures, parameter input mechanisms, etc., for other software products within the ORNL Quantum Computing Institute. This work enables pure basic research, has no export controlled utilities, and has no real commercial value.", + "laborHours": 334.4, + "name": "QCI Common", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/common", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "In this era of data-driven decisions and discovery where Big Data is producing Bigger Data, data scientists at the Oak Ridge National Laboratory are leveraging unique leadership infrastructure (e.g., Urika XA and Urika GD appliances) to develop scalable algorithms for semantic, logical and statistical reasoning with Big Data (i.e., data stored in databases as well as unstructured data in documents). ORiGAMI is a next-generation knowledge-discovery framework that is: (a) knowledge nurturing (i.e., evolves seamlessly with newer knowledge and data), (b) smart and curious (i.e. using information-foraging and reasoning algorithms to digest content) and (c) synergistic (i.e., interfaces computers with what they do best to help subject-matter-experts do their best. ORiGAMI has been demonstrated using the National Library of Medicine's SEMANTIC MEDLINE (archive of medical knowledge since 1994).", + "laborHours": 136.8, + "name": "Oak Ridge Graph Analytics for Medical Innovation (ORiGAMI)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ssrangan/origami/blob/master/Open%20Source%20Software%20License.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ssrangan/origami", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Portage is a software library system for physics remapping (mapping physics variables from one computational mesh to another) either within a single simulation code or between two disparate simulation codes. Portage is designed to utilize advanced-architecture compute platforms and to be easily extensible by third parties.", + "laborHours": 73157.6, + "name": "Portage, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/laristra/portage/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laristra/portage", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "In order to support engineering analysis of Virtual Environment for Reactor Analysis (VERA) model results, the Consortium for Advanced Simulation of Light Water Reactors (CASL) needs a tool that provides visualizations of HDF5 files that adhere to the VERAOUT specification. VERAView provides an interactive graphical interface for the visualization and engineering analyses of output data from VERA. The Python-based software provides instantaneous 2D and 3D images, 1D plots, and alphanumeric data from VERA multi-physics simulations.", + "laborHours": 21675.2, + "name": "VERAView", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CASL/VERAview", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The iESM is a simulation code that represents the physical and biological aspects of Earth's climate system, and also includes the macro-economic and demographic properties of human societies. The human aspect of the simulation code is focused in particular on the effects of human activities on land use and land cover change, but also includes aspects such as energy economies. The time frame for predictions with iESM is approximately 1970 through 2100.", + "laborHours": 6406374.4, + "name": "Integrated Earth System Model (iESM)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ACME-Climate/iESM/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ACME-Climate/iESM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MultiMatTest is a demonstration code to support a talk and paper titled A Comparative Study of Multi-material Data Structures for Computational Physics Applications. The application times basic operations for different representations of multi-material data structures.", + "laborHours": 1155.2, + "name": "MultiMatTest, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/MultiMatTest/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL/MultiMatTest", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Ring current Atmosphere interactions Model with Self-Consistent magnetic field (B) is a unique code that combines a kinetic model of ring current plasma with a three dimensional force-balanced model of the terrestrial magnetic field. The kinetic portion, RAM, solves the kinetic equation to yield the bounce-averaged distribution function as a function of azimuth, radial distance, energy and pitch angle for three ion species (H+, He+, and O+) and, optionally, electrons. The domain is a circle in the Solar-Magnetic (SM) equatorial plane with a radial span of 2 to 6.5 RE. It has an energy range of approximately 100 eV to 500 KeV. The 3-D force balanced magnetic field model, SCB, balances the JxB force with the divergence of the general pressure tensor to calculate the magnetic field configuration within its domain. The domain ranges from near the Earth\u2019s surface, where the field is assumed dipolar, to the shell created by field lines passing through the SM equatorial plane at a radial distance of 6.5 RE. The two codes work in tandem, with RAM providing anisotropic pressure to SCB and SCB returning the self-consistent magnetic field through which RAM plasma is advected.", + "laborHours": 81259.2, + "name": "Ring current Atmosphere interactions Model with Self-Consistent Magnetic field", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/RAM-SCB/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/RAM-SCB", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Mercat is a highly scalable property software package for robust of analysis of features in next-generation sequencing data and observed unique peptides from metaproteomic data. Mercat is offered in python 3.5/anaconda3, is multiparellel and is easily installed using bioconda/conda recipes. Mercat inputs include assembled contigs, raw sequence reads from any platform, and unique peptide files obtained from proteomics with feature abundance counts tables. Mercat is the only software available that allows for direct analysis of data properties without a data-dependent search tools such as BLAST or diamond for compositional analysis of whole community shotgun sequencing (e.g. metagenomes and/or metatranscriptomes) or metaproteomic data.", + "laborHours": 380.0, + "name": "Mercat", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/mercat/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mercat", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pinyon is a tool that stores steps involved in creating a model derived from a collection of data. The main function of Pinyon is to store descriptions of calculations used to analyze or visualize the data in a database, and allow users to view the results of these calculations via a web interface. Additionally, users may also use the web interface to make adjustments to the calculations and rerun the entire collection of analysis steps automatically.", + "laborHours": 6505.6, + "name": "Pinyon, Version 0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/pinyon/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pinyon", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "System for converting DESIRE (Direct Executing Simulation in Real Time) simulation models to executable code models (C# / C++). These converted models are used as the basis for 2 products, one of which is the focus of this review: an engineering design interface for Fissile Solution Systems. ModelConverter.exe (C#) converts DESIRE model inputs to a C++ plug-in subclass. SimApp.exe (C# / C++) has a C++ dll that is a numerical integration engine that the Converted models plug into. The engineering design interface is a C# GUI that calls on the C++ dll to execute a particular converted model. The GUI allows the user to specify the length of a simulation, run the simulation, view data plots and data tables. Stability plots may also be produced and manipulated. The engineering design interface will be released as source code and executable; the model converter source is also intended for release.", + "laborHours": 13710.4, + "name": "SimApp 1.8.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/determan/SimApp1.8x/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/determan/SimApp1.8x.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Grappa is a latency tolerant runtime system for mass market computer systems comprised of multiple nodes having x86 multicore processors and infiniband interconnect. Grappa is designed to enable in-memory irregular applications written in the C++ programming language to scale up on multiprocessor systems. Grappa addresses the load balance, communication, and synchronization challenges posed by running applications that do not partition evenly across large systems. Two mechanisms are essential to its success: fast task switching and message aggregation. Fast task switching enables processors to tolerate communication and synchronization delays; aggregation sustains high bandwidth on low injection rate networks.", + "laborHours": 120764.0, + "name": "A Latency Tolerant Runtime System for Mass Market Computer Systems", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/uwsampa/grappa", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The GIBS software program is a Grand Canonical Monte Carlo (GCMC) simulation program (written in C++) that can be used for 1) computing the excess chemical potential of ions and the mean activity coefficients of salts in homogeneous electrolyte solutions; and, 2) for computing the distribution of ions around fixed macromolecules such as, nucleic acids and proteins. The solvent can be represented as neutral hard spheres or as a dielectric continuum. The ions are represented as charged hard spheres that can interact via Coulomb, hard-sphere, or Lennard-Jones potentials. In addition to hard-sphere repulsions, the ions can also be made to interact with the solvent hard spheres via short-ranged attractive square-well potentials.", + "laborHours": 3906.4, + "name": "A Grand Canonical Monte Carlo simulation program for computing ion distributions around biomolecules in hard sphere solvents", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/30876-615-os", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electrostatics/GIBS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Futility package contains the following: 1) Definition of the size of integers and real numbers; 2) A generic Unit test harness; 3) Definitions for some basic extensions to the Fortran language: arbitrary length strings, a parameter list construct, exception handlers, command line processor, timers; 4) Geometry definitions: point, line, plane, box, cylinder, polyhedron; 5) File wrapper functions: standard Fortran input/output files, Fortran binary files, HDF5 files; 6) Parallel wrapper functions: MPI, and Open MP abstraction layers, partitioning algorithms; 7) Math utilities: BLAS, Matrix and Vector definitions, Linear Solver methods and wrappers for other TPLs (PETSC, MKL, etc), preconditioner classes; 8) Misc: random number generator, water saturation properties, sorting algorithms.", + "laborHours": 99727.2, + "name": "Futility", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CASL/Futility", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software provides a real-time processing system for sonar to detect and track animals, and to extract water column biomass statistics in order to facilitate continuous monitoring of an underwater environment. The Nekton Interaction Monitoring System (NIMS) extracts and archives tracking and backscatter statistics data from a real-time stream of data from a sonar device. NIMS also sends real-time tracking messages over the network that can be used by other systems to generate other metrics or to trigger instruments such as an optical video camera. A web-based user interface provides remote monitoring and control. NIMS currently supports three popular sonar devices: M3 multi-beam sonar (Kongsberg), EK60 split-beam echo-sounder (Simrad) and BlueView acoustic camera (Teledyne).", + "laborHours": 164707.2, + "name": "Nekton Interaction Monitoring System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/nims/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/nims", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2022-11-18" + }, + "description": "Transactive Energy Simulation Platform (TESP) combines existing domain simulators in the electric power grid, buildings, and communication systems, with new transactive agents, growth models and evaluation scripts. The existing domain simulators include GridLAB-D for the distribution grid and single-family residential buildings, MATPOWER for transmission and bulk generation, EnergyPlus for large buildings and ns-3 for communication systems. More are planned for subsequent versions of TESP. The new elements are: TEAgents - simulate market participants and transactive systems for market clearing. Some of this functionality was extracted from GridLAB-D and implemented in Python for customization by PNNL and others. Growth Model - a means for simulating system changes over a multiyear period, including both normal load growth and specific investment decisions. Customizable in Python code. Evaluation Script - a means of evaluating different transactive systems through customizable post-processing in Python code. TESP will run on Linux, Windows and Mac OS X.", + "laborHours": 46892.0, + "languages": [], + "name": "Transactive Energy Simulation Platform", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/tesp", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Haystack is a software agent platform for user emulation. We are leveraging python and the SPADE software packages to develop an architecture and platform where software agents can be sent actuation behaviors, configured with different behavior profiles (time based, event based, probability based, etc.), and controlled/monitored from a central control unit. The haystack agent platform provides the ability to model and simulate user behavior in cyber systems. This eliminates the need to fund real users to provide this interaction, provides control such that researchers can randomize, hold-steady, or model whatever behavior that want to study without running afoul of IRB requirements, and provides a documented truth that enables understanding what happened in and experiment and provides for repeatability.", + "laborHours": 364.8, + "name": "Haystack", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/haystack", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code solves the gray thermal radiative transfer (TRT) equations in parallel using simple opacities and Cartesian meshes. Although Branson solves the TRT equations it is not designed to model radiation transport: Branson contains simple physics and does not have a multigroup treatment, nor can it use physical material data. The opacities have are simple polynomials in temperature there is a limited ability to specify complex geometries and sources. Branson was designed only to capture the computational demands of production IMC codes, especially in large parallel runs. It was also intended to foster collaboration with vendors, universities and other DOE partners. Branson is similar in character to the neutron transport proxy-app Quicksilver from LLNL, which was recently open-sourced.", + "laborHours": 33987.2, + "name": "Branson: A Mini-App for Studying Parallel IMC, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/branson/blob/develop/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/branson", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "WARP, which can stand for ``Weaving All the Random Particles,'' is a three-dimensional (3D) continuous energy Monte Carlo neutron transport code developed at UC Berkeley to efficiently execute on NVIDIA graphics processing unit (GPU) platforms. WARP accelerates Monte Carlo simulations while preserving the benefits of using the Monte Carlo method, namely, that very few physical and geometrical simplifications are applied. WARP is able to calculate multiplication factors, neutron flux distributions (in both space and energy), and fission source distributions for time-independent neutron transport problems. It can run in both criticality or fixed source modes, but fixed source mode is currently not robust, optimized, or maintained in the newest version. WARP can transport neutrons in unrestricted arrangements of parallelepipeds, hexagonal prisms, cylinders, and spheres. The goal of developing WARP is to investigate algorithms that can grow into a full-featured, continuous energy, Monte Carlo neutron transport code that is accelerated by running on GPUs. The crux of the effort is to make Monte Carlo calculations faster while producing accurate results. Modern supercomputers are commonly being built with GPU coprocessor cards in their nodes to increase their computational efficiency and performance. GPUs execute efficiently on data-parallel problems, but most CPU codes, including those for Monte Carlo neutral particle transport, are predominantly task-parallel. WARP uses a data-parallel neutron transport algorithm to take advantage of the computing power GPUs offer.", + "laborHours": 7083.2, + "name": "WARP", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sellitforcache/warp/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sellitforcache/warp", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Memory systems are expected to get evermore complicated in the coming years, and it isn't clear exactly what form that complexity will take. On the software side, a simple, flexible way of identifying and working with memory pools is needed. Additionally, most developers seek code portability and do not want to learn the intricacies of complex memory. Hence, we believe that a library for interacting with complex memory systems should expose two kinds of abstraction: First, a low-level, mechanism-based interface designed for the runtime or advanced user that wants complete control, with its focus on simplified representation but with all decisions left to the caller. Second, a high-level, policy-based interface designed for ease of use for the application developer, in which we aim for best-practice decisions based on application intent. We have developed such a library, called SICM: Simplified Interface to Complex Memory.", + "laborHours": 17829.6, + "name": "Simplified Interface to Complex Memory Hierarchies 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SICM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CHROTRAN is a fork of the widely-used PFLOTRAN flow and reactive transport numerical simulation code. It implements custom physics and chemistry appropriate to the design of in-situ reduction of heavy metals such as Cr(VI) in groundwater. CHROTRAN includes full dynamics for five species: the metal to be remediated, an electron donor, biofilm, a nontoxic conservative bio-inhibitor, and a biocide. Direct abiotic reduction by donor-metal interaction as well as donor-driven biomass growth and bio-reduction are modeled, along with crucial processes such as donor sorption, and biofilm inactivation. The software implementation handles heterogeneous flow fields, arbitrarily many chemical species and amendment injection points, and features full coupling between flow and reactive transport, allowing for assessment of the effect of bio-fouling.", + "laborHours": 173325.6, + "name": "CHROTRAN, 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/scottkalevhansen/CHROTRAN-release", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MASS1 simulates open channel hydrodynamics and transport in branched channel networks, using cross-section averaged forms of the continuity, momentum, and convection diffusion equations. Thermal energy transport (temperature), including meteorological influences is supported. The thermodynamics of total dissolved gas (TDG) can be directly simulated. MASS1 has been developed over the last 20 years. It is currently being used on DOE projects that require MASS1 to beopen source. Hence, the authors would like to distribute MASS1 in source form.", + "laborHours": 9910.4, + "name": "Modular Aquatic Simulation System 1D", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/mass1/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mass1", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Synthetic Proxy Infrastructure for Task Evaluation is a proxy application designed to support application developers in gauging the performance of various task granularities when determining how best to utilize task based programming models.The infrastructure is designed to provide examples of common communication patterns with a synthetic workload intended to provide performance data to evaluate programming model and platform overheads for the purpose of determining task granularity for task decomposition purposes. This is presented as a reference implementation of a proxy application with run-time configurable input and output task dependencies ranging from an embarrassingly parallel scenario to patterns with stencil-like dependencies upon their nearest neighbors. Once all, if any, inputs are satisfied each task will execute a synthetic workload (a simple DGEMM of in this case) of varying size and output all, if any, outputs to the next tasks.The intent is for this reference implementation to be implemented as a proxy app in different programming models so as to provide the same infrastructure and to allow for application developers to simulate their own communication needs to assist in task decomposition under various models on a given platform.", + "laborHours": 106.4, + "name": "Synthetic Proxy Infrastructure for Task Evaluation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/spite/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/spite", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The CosmicEmu implements a Gaussian process emulation scheme to predict the dark matter and dark matter + neutrino power spectra over a range of physical parameters that describe the composition and evolution of the Universe. The procedure can produce thousands of spectra per second, much faster than the complex n-body simulations used to produce the training set, which can take weeks per simulation. The training simulations, their design, and the general scheme is described in Lawrence et al. (2010), Heitmann et al. (2014), Heitmann et al. (2016), and an upcoming paper.", + "laborHours": 159311.2, + "name": "CosmicEmu, Version 2.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/CosmicEmu/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/CosmicEmu", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HELICS is designed to support very-large-scale (100,000+ federates) cosimulations with off-the-shelf power-system, communication, market, and end-use tools. Other key features include cross platform operating system support, the integration of both event driven (e.g., packetized communication) and time-series (e.g., power flow) simulations, and the ability to co-iterate among federates to ensure physical model convergence at each time step.", + "laborHours": 265848.0, + "name": "Hierarchical Engine for Large-scale Infrastructure Co-Simulation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GMLC-TDC/HELICS-src/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GMLC-TDC/HELICS-src", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ECoG ClusterFlow is a novel multi-scale visual analysis system for the detailed exploration of dynamic functional connectivity graphs obtained through electrocorticography.", + "laborHours": 576718.4, + "name": "ECoG Cluster Flow v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sugeerth/ECoG-ClusterFlow/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sugeerth/ECoG-ClusterFlow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Small Python package to compute tomographic reconstructions using a reconstruction method published in: Pelt, D.M., & De Andrade, V. (2017). Improved tomographic reconstruction of large-scale real-world data by filter optimization. Advanced Structural and Chemical Imaging 2: 17; and Pelt, D. M., & Batenburg, K. J. (2015). Accurately approximating algebraic tomographic reconstruction by filtered backprojection. In Proceedings of The 13th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (pp. 158-161).", + "laborHours": 395.2, + "name": "SIRT-FILTER v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/dmpelt/sirtfilter/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/dmpelt/sirtfilter", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "New contributions to the existing open source project called 'progressbars2.\" Improvements were created for use in JBEI software, but are generally useful to the open source software community.", + "laborHours": 2188.8, + "name": "progressbar2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WoLpH/python-progressbar", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Equilibrium thermodynamics underpins many of the technologies used throughout theoretical physics, yet verification of the various theoretical models in the open literature remains challenging. EOSlib provides a single, consistent, verifiable implementation of these models, in a single, easy-to-use software package. It consists of three parts: a software library implementing various published equation-of-state (EOS) models; a database of fitting parameters for various materials for these models; and a number of useful utility functions for simplifying thermodynamic calculations such as computing Hugoniot curves or Riemann problem solutions. Ready availability of this library will enable reliable code-to- code testing of equation-of-state implementations, as well as a starting point for more rigorous verification work. EOSlib also provides a single, consistent API for its analytic and tabular EOS models, which simplifies the process of comparing models for a particular application.", + "laborHours": 55753.6, + "name": "EOSlib, Version 3", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/EOSlib/blob/github/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EOSlib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Virtual Machine Builder is a graphical user interface for use and modification of virtual machine templates using Hashi Corp packer to perform virtual machine creation.", + "laborHours": 6566.4, + "name": "Virtual Machine Builder", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csd-dev-tools/VmBuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Jali is a parallel unstructured mesh infrastructure library designed for use by multi-physics simulations. It supports 2D and 3D arbitrary polyhedral meshes distributed over hundreds to thousands of nodes. Jali can read write Exodus II meshes along with fields and sets on the mesh and support for other formats is partially implemented or is (https://github.com/MeshToolkit/MSTK), an open source general purpose unstructured mesh infrastructure library from Los Alamos National Laboratory. While it has been made to work with other mesh frameworks such as MOAB and STKmesh in the past, support for maintaining the interface to these frameworks has been suspended for now. Jali supports distributed as well as on-node parallelism. Support of on-node parallelism is through direct use of the the mesh in multi-threaded constructs or through the use of \"tiles\" which are submeshes or sub-partitions of a partition destined for a compute node.", + "laborHours": 16841.6, + "name": "Jali - Unstructured Mesh Infrastructure for Multi-Physics Applications", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/jali", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "At exascale, the challenge becomes to develop applications that run at scale and use exascale platforms reliably, efficiently, and flexibly. Workflows become much more complex because they must seamlessly integrate simulation and data analytics. They must include down-sampling, post-processing, feature extraction, and visualization. Power and data transfer limitations require these analysis tasks to be run in-situ or in-transit. We expect successful workflows will comprise multiple linked simulations along with tens of analysis routines. Users will have limited development time at scale and, therefore, must have rich tools to develop, debug, test, and deploy applications. At this scale, successful workflows will compose linked computations from an assortment of reliable, well-defined computation elements, ones that can come and go as required, based on the needs of the workflow over time. We propose a novel framework that utilizes both virtual machines (VMs) and software containers to create a workflow system that establishes a uniform build and execution environment (BEE) beyond the capabilities of current systems. In this environment, applications will run reliably and repeatably across heterogeneous hardware and software. Containers, both commercial (Docker and Rocket) and open-source (LXC and LXD), define a runtime that isolates all software dependencies from the machine operating system. Workflows may contain multiple containers that run different operating systems, different software, and even different versions of the same software. We will run containers in open-source virtual machines (KVM) and emulators (QEMU) so that workflows run on any machine entirely in user-space. On this platform of containers and virtual machines, we will deliver workflow software that provides services, including repeatable execution, provenance, checkpointing, and future proofing. We will capture provenance about how containers were launched and how they interact to annotate workflows for repeatable and partial re-execution. We will coordinate the physical snapshots of virtual machines with parallel programming constructs, such as barriers, to automate checkpoint and restart. We will also integrate with HPC-specific container runtimes to gain access to accelerators and other specialized hardware to preserve native performance. Containers will link development to continuous integration. When application developers check code in, it will automatically be tested on a suite of different software and hardware architectures.", + "laborHours": 2629.6, + "name": "Build and Execute Environment", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/BEE/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/BEE", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Our Python module, colormap_module, presented here can be used to analyze and manipulate colormaps and has two main aims: (i) compare existing and new custom colormaps quantitatively by comparing their values in a color space, called CAM02-UCS, that directly shows how a human perceives their hue, saturation, and lightness values and (ii) create isoluminant colormaps from existing or custom colormaps and (iii) mix isoluminant colormap data with a 4th dimension of data by manipulating lightness values across the image and present the new image. Our module was designed to be a tool for the community to use as a whole, allowing scientists to present, analyze, and manipulate colormaps they have created and/or decided to use for a particular type of data. By being able to do this, the scientific community as a whole will think more about the colormaps they choose, see why particular colormaps are bad to use for certain types of data, and move toward using colormaps our eyes can interpret much more efficiently.", + "laborHours": 304.0, + "name": "colormap_util", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jamienunez/cmaputil/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jamienunez/cmaputil", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Route Sanitizer is ORNL's connected vehicle moving object database de-identification tool and a graphical user interface to ORNL's connected vehicle de-identification algorithm. It uses the Google Chrome (soon to be Electron) platform so it will run on different computing platforms. The basic de-identification strategy is record redaction: portions of a vehicle trajectory (e.g. sequences of precise temporal spatial records) are removed. It does not alter retained records. The algorithm uses custom techniques to find areas within trajectories that may be considered private, then it suppresses those in addition to enough of the trajectory surrounding those locations to protect against \"inference attacks\" in a mathematically sound way. Map data is integrated into the process to make this possible.", + "laborHours": 0.0, + "name": "Route Sanitizer: Connected Vehicle Trajectory De-Identification Tool", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmcarter9t/route-sanitizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "EDGE bioinformatics was developed to help biologists process Next Generation Sequencing data (in the form of raw FASTQ files), even if they have little to no bioinformatics expertise. EDGE is a highly integrated and interactive web-based platform that is capable of running many of the standard analyses that biologists require for viral, bacterial/archaeal, and metagenomic samples. EDGE provides the following analytical workflows: quality trimming and host removal, assembly and annotation, comparisons against known references, taxonomy classification of reads and contigs, whole genome SNP-based phylogenetic analysis, and PCR analysis. EDGE provides an intuitive web-based interface for user input, allows users to visualize and interact with selected results (e.g. JBrowse genome browser), and generates a final detailed PDF report. Results in the form of tables, text files, graphic files, and PDFs can be downloaded. A user management system allows tracking of an individual\u2019s EDGE runs, along with the ability to share, post publicly, delete, or archive their results.", + "laborHours": 155587.2, + "name": "Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform, Version 1.5 and 1.x.", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Bioinformatics/EDGE.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "A Git server (GitHub, GitLab, BitBucket) sends event notifications to the Civet server. These are either a \" Pull Request\" or a \"Push\" notification. Civet then checks the database to determine what tests need to be run and marks them as ready to run. Civet clients, running on dedicated machines, query the server for available jobs that are ready to run. When a client gets a job it executes the scripts attached to the job and report back to the server the output and exit status. When the client updates the server, the server will also update the Git server with the result of the job, as well as updating the main web page.", + "laborHours": 26615.2, + "languages": [], + "name": "CIVET: Continuous Integration, Verification, Enhancement, and Testing", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/civet", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Xanthos is a Python package designed to quantify and analyze global water availability in history and in future at 0.5\u00b0 \u00d7 0.5\u00b0 spatial resolution and a monthly time step under a changing climate. Its performance was also tested through real applications. It is open-source, extendable and convenient to researchers who work on long-term climate data for studies of global water supply, and Global Change Assessment Model (GCAM). This package integrates inherent global gridded data maps, I/O modules, Water-Balance Model modules and diagnostics modules by user-defined configuration.", + "laborHours": 1656.8, + "name": "Xanthos", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/xanthos", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-01-22" + }, + "description": "WindSE is a tool for modeling atmospheric fluid flow within a wind plant and performing optimization of the turbine positions or operating settings. WindSE is a python package that uses a FEniCS backend to perform wind farm simulations and optimization.", + "laborHours": 3146.4, + "languages": [ + "Python" + ], + "name": "WindSE: Wind Systems Engineering [SWR-17-03]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WindSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-10-01" + }, + "description": "The Functionally-Assembled Terrestrial Ecosystem Simulator (FATES) is a vegetation model for use in Earth system models (ESMs). The model includes a size- and age-structured representation of tree dynamics, competition between functionally diverse plant functional types, and the biophysics underpinning plant growth, competition, mortality, as well as the carbon, water, and energy exchange with the atmosphere. The FATES model is designed as a modular vegetation model that can be integrated within a host land model for inclusion in ESMs. The model is designed for use in global change studies to understand and project the responses and feedbacks between terrestrial ecosystems and the Earth system under changing climate and other forcings.", + "homepageURL": "https://zenodo.org/record/3825474", + "laborHours": 0.0, + "languages": [], + "name": "The Functionally-Assembled Terrestrial Ecosystem Simulator Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NGEET/fates-release/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://zenodo.org/record/3825474", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Charliecloud is a set of scripts to let users run a virtual cluster of virtual machines (VMs) on a desktop or supercomputer. Key functions include: 1. Creating (typically by installing an operating system from vendor media) and updating VM images; 2. Running a single VM; 3. Running multiple VMs in a virtual cluster. The virtual machines can talk to one another over the network and (in some cases) the outside world. This is accomplished by calling external programs such as QEMU and the Virtual Distributed Ethernet (VDE) suite. The goal is to let users have a virtual cluster containing nodes where they have privileged access, while isolating that privilege within the virtual cluster so it cannot affect the physical compute resources. Host configuration enforces security; this is not included in Charliecloud, though security guidelines are included in its documentation and Charliecloud is designed to facilitate such configuration. Charliecloud manages passing information from host computers into and out of the virtual machines, such as parameters of the virtual cluster, input data specified by the user, output data from virtual compute jobs, VM console display, and network connections (e.g., SSH or X11). Parameters for the virtual cluster (number of VMs, RAM and disk per VM, etc.) are specified by the user or gathered from the environment (e.g., SLURM environment variables). Example job scripts are included. These include computation examples (such as a \"hello world\" MPI job) as well as performance tests. They also include a security test script to verify that the virtual cluster is appropriately sandboxed. Tests include: 1. Pinging hosts inside and outside the virtual cluster to explore connectivity; 2. Port scans (again inside and outside) to see what services are available; 3. Sniffing tests to see what traffic is visible to running VMs; 4. IP address spoofing to test network functionality in this case; 5. File access tests to make sure host access permissions are enforced. This test script is not a comprehensive scanner and does not test for specific vulnerabilities. Importantly, no information about physical hosts or network topology is included in this script (or any of Charliecloud); while part of a sensible test, such information is specified by the user when the test is run. That is, one cannot learn anything about the LANL network or computing infrastructure by examining Charliecloud code.", + "laborHours": 4879.2, + "name": "Charliecloud", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/charliecloud", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Los Alamos sea ice model (CICE) is the result of an effort to develop a computationally efficient sea ice component for a fully coupled atmosphere\u2013land\u2013ocean\u2013ice global climate model. It was originally designed to be compatible with the Parallel Ocean Program (POP), an ocean circulation model developed at Los Alamos National Laboratory for use on massively parallel computers. CICE has several interacting components: a vertical thermodynamic model that computes local growth rates of snow and ice due to vertical conductive, radiative and turbulent fluxes, along with snowfall; an elastic-viscous-plastic model of ice dynamics, which predicts the velocity field of the ice pack based on a model of the material strength of the ice; an incremental remapping transport model that describes horizontal advection of the areal concentration, ice and snow volume and other state variables; and a ridging parameterization that transfers ice among thickness categories based on energetic balances and rates of strain. It also includes a biogeochemical model that describes evolution of the ice ecosystem. The CICE sea ice model is used for climate research as one component of complex global earth system models that include atmosphere, land, ocean and biogeochemistry components. It is also used for operational sea ice forecasting in the polar regions and in numerical weather prediction models.", + "laborHours": 51938.4, + "name": "CICE, The Los Alamos Sea Ice Model", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/CICE-Consortium/CICE/blob/master/LICENSE.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CICE-Consortium/CICE", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2025-03-26" + }, + "description": "URBANopt is a user interface for creating and running district and city scale building energy simulations. The framework is built around the OpenStudio Urban Measures which are part of the OpenStudio project. Building footprints, building height, building type, and other data can be imported from public records or other sources. Footprints and locations for new buildings and district systems can also be specified. OpenStudio Measures are used to create starting point energy models and to model energy design features and efficiency measures for each building. URBANopt allows a user to pose several scenarios such as \u201cwhat if 30% of the commercial retail buildings added roof top solar\u201d or \u201cwhat if all elementary schools converted to ground source heat pumps\u201d and then visualize the impacts at a district or city scale. URBANopt is capable of modeling existing buildings, new construction, and district energy systems. URBANopt can be used to explore options for achieving Zero Energy across a collection of buildings (e.g., Zero Energy Districts).", + "homepageURL": "https://www.nrel.gov/buildings/urbanopt.html", + "laborHours": 635147.2, + "languages": [], + "name": "URBANopt (Urban Renewable Building And Neighborhood Optimization) [SWR-16-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/buildings/urbanopt.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "FleCSPH is a multi-physics compact application that exercises FleCSI parallel data structures for tree-based particle methods. In particular, FleCSPH implements a smoothed-particle hydrodynamics (SPH) solver for the solution of Lagrangian problems in astrophysics and cosmology. FleCSPH includes support for gravitational forces using the fast multipole method (FMM).", + "laborHours": 10001.6, + "name": "FleCSPH - a parallel and distributed SPH implementation based on the FleCSI framework", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laristra/flecsph", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "In most Home Energy Management Systems (HEMS) available in the market, different devices running different communication protocols cannot interact with each other and exchange information. As a result of this integration, the information about different devices running different communication protocol can be accessible by other agents and devices running on VOLTTRON platform. The integration process can be used by any HEMS available in the market regardless of the programming language they use. If the existing HEMS provides an Application Programming Interface (API) based on the RESTFul architecture, that API can be used for integration. Our candidate HEMS in this project is home-assistant (Hass). An agent is implemented which can communicate with the Hass API and receives information about the devices loaded on the API. The agent publishes the information it receives on the VOLTTRON message bus so other agents can have access to this information. On the other side, for each type of devices, an agent is implemented such as Climate Agent, Lock Agent, Switch Agent, Light Agent, etc. Each of these agents is subscribed to the messages published on the message bus about their associated devices. These agents can also change the status of the devices by sending appropriate service calls to the API. Other agents and services on the platform can also access this information and coordinate their decision-making process based on this information.", + "laborHours": 109880.8, + "name": "Home Energy Management System - VOLTTRON Integration", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/VOLTTRON/volttron-applications/blob/master/ornl/HomeAssistant-VOLTTRON-Integration-Agents/License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron-applications", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The VisIT Java Client (JVC) library is a lightweight thin client that is designed and written purely in the native language of Java (the Python & JavaScript versions of the library use the same concept) and communicates with any new unmodified standalone version of VisIT, a high performance computing parallel visualization toolkit, over traditional or web sockets and dynamically determines capabilities of the running VisIT instance whether local or remote.", + "laborHours": 1383.2, + "name": "Visualization Software for VisIT Java Client", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/visit-vis/visit_java_client/blob/master/gov.lbnl.visit.swt/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/visit-vis/visit_java_client", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Knowledge graphs represent information as entities and relationships between them. For tasks such as natural language question answering or automated analysis of text, a knowledge graph provides valuable context to establish the specific type of entities being discussed. It allow us to derive better context about newly arriving information and leads to intelligent reasoning capabilities. We address two primary needs: A) Automated construction of knowledge graphs is a technically challenging, expensive process; and B) The ability to synthesize new information by monitoring newly emerging knowledge is a transformational capability that does not exist in state of the art systems.", + "laborHours": 19136.8, + "name": "NOUS: A Knowledge Graph Management System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/streaming-graphs/NOUS", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/streaming-graphs/NOUS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Pececillo is a proxy-app for the open source Truchas metal processing code (LA-CC-15-097). It implements many of the physics models used in Truchas: free-surface, incompressible Navier-Stokes fluid dynamics (e.g., water waves); heat transport, material phase change, view factor thermal radiation; species advection-diffusion; quasi-static, elastic/plastic solid mechanics with contact; electomagnetics (Maxwell's equations). The models are simplified versions that retain the fundamental computational complexity of the Truchas models while omitting many non-essential features and modeling capabilities. The purpose is to expose Truchas algorithms in a greatly simplified context where computer science problems related to parallel performance on advanced architectures can be more easily investigated. While Pececillo is capable of performing simulations representative of typical Truchas metal casting, welding, and additive manufacturing simulations, it lacks many of the modeling capabilites needed for real applications.", + "laborHours": 21705.6, + "name": "Pececillo", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/truchas/pececillo/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/truchas/pececillo", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Graphical user interface for use and modification of virtual machine templates using Hashi Corp packer to perform virtual machine creation.", + "laborHours": 6566.4, + "name": "ClockworkVMs", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csd-dev-tools/VmBuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The open source Project Haystack initiative defines meta data and communication standards related to data from buildings and intelligent devices. The Project Haystack REST API defines standard formats and operations for exchanging Haystack tagged data over HTTP. The HaystackRuby gem wraps calls to this REST API to enable Ruby application to easily integrate data hosted on a Project Haystack compliant server. The HaystackRuby gem was developed at the National Renewable Energy Lab to support applications related to campus energy. We hope that this tool may be useful to others.", + "laborHours": 425.6, + "name": "Haystack-Ruby", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/haystack_ruby", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-10-13" + }, + "description": "High-Throughput software platform to create/launch/analyze physics-related calculations. The front-end is a python API which allows the user to create any conceivable first-principles physics calculation. Is is coupled to an ipython interface to launch and retrieve large number of calculations. It was successfully used in high-throughput calculations of point defect formation enthalpies, compound formation enthalpies, and a genetic algorithm search of direct-gap silicon/germanium structures.", + "laborHours": 49506.4, + "languages": [ + "C++", + "Python" + ], + "name": "LaDa\u2122", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://pylada.github.io/pylada", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mdavezac/LaDa", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The MAGMA software package is a package created in the R scripting language that reads a SQL database and outputs tables and figures of important data. The SQL database is created by another R package called \u201crplexos\u201d and uses the .zip solution file output by PLEXOS, which is commercially available production cost modeling software.", + "laborHours": 3435.2, + "name": "Multi-area Grid Metrics Analyzer", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/MAGMA", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MAGMA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Knife-ovirt is code building on the chef, knife-cloud, fog, rbovirt projects that allows deployment of virtual machines on an ovirt cluster, and immediately bootstrap them into a chef managed infrastructure. (similar to knife-openstack project).", + "laborHours": 258.4, + "name": "Knife-ovirt", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/knife-ovirt", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software is intended to be part of an open source effort regarding soils data. The software provides customized data ingestion scripts for soil carbon related data sets and scripts for output databases that conform to common templates.", + "laborHours": 714.4, + "name": "Soil Carbon Data: long tail recovery", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ktoddbrown/soils-long-tail-recovery", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-07-19" + }, + "description": "The software was produced to reproduce biologically relevant results and present them using clear and elegant graphs.", + "laborHours": 3632.8, + "languages": [], + "name": "Supplemental Material for Bernstein-2017-founders-species", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/bernstein-2017-founders-species", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/brislawn-2018-founders-species", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SimulatorToFMU is a software package written in Python which allows users to export a memoryless Python-driven simulation program or script as a Functional Mock-up Unit (FMU) for model exchange or co-simulation.In CyDER (Cyber Physical Co-simulation Platform for Distributed Energy Resources in Smart Grids), SimulatorToFMU will allow exporting OPAL-RT as an FMU. 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YADAS features a versatile scheme for defining models, and another versatile scheme for defining sampling algorithms that includes a default starting place for most analyses.", + "laborHours": 3222.4, + "name": "YADAS, Version 0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/gertvv/yadas/blob/master/COPYING.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gertvv/yadas", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-01-31" + }, + "description": "RdTools\u2122 provides a set of tools for quantifying the degradation of photovoltaic systems and modules.", + "laborHours": 1003.2, + "languages": [ + "Python" + ], + "name": "RdTools\u2122 [SWR-17-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rdtools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.2.0-beta.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2022-07-21" + }, + "description": "PeleC is an adaptive-mesh compressible hydrodynamics code for reacting flows. 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The initial release includes an interface to reaction rate mechanism evaluation, transport coefficient evaluation, and a generalized equation of state (EOS) facility. Both generic evaluators and interfaces to code from externally available tools (Fuego for chemical rates, EGLib for transport coefficients) are provided.", + "laborHours": 2114760.8, + "languages": [ + "C++", + "C", + "Fortran", + "Python" + ], + "name": "PelePhysics [SWR-17-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/AMReX-Combustion/PelePhysics/blob/development/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Combustion/PelePhysics", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pacifica is a data management system developed for use at the Environmental and Molecular Sciences Laboratory (EMSL) used to collect, analyze, search and track data from instruments.", + "laborHours": 304.0, + "name": "Pacifica", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pacifica/pacifica", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-09-03" + }, + "description": "A Python direct-mode interface to OpenDSS, a distribution system simulator for electric power systems.", + "laborHours": 8238.4, + "languages": [ + "Python" + ], + "name": "OpenDSSDirect.py", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dss-extensions/OpenDSSDirect.py", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Standard Energy Efficiency Data Platform\u00ae (SEED Platform) provides public agencies and other organizations with a standardized but flexible, cost-effective, secure, enterprise data platform to manage portfolio scale building performance data from a variety of sources. The SEED Platform streamlines the administrative effort required by public agencies implementing building performance and transparency programs.", + "laborHours": 81031.2, + "name": "Standard Energy Efficiency Data Platform\u00ae", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/SEED-platform/seed/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SEED-platform/seed", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The LK scripting language is a simple and fast computer programming language designed for easy integration with existing software to enable automation of tasks. The LK language is used by NREL\u2019s System Advisor Model (SAM), the SAM Software Development Kit (SDK), and SolTrace products. LK is easy extensible and adaptable to new software due to its small footprint and is designed to be statically linked into other software. It is written in standard C++, is cross-platform (Windows, Linux, and OSX), and includes optional portions that enable direct integration with graphical user interfaces written in the open source C++ wxWidgets Version 3.0+ toolkit.", + "laborHours": 111248.8, + "name": "LK Scripting Language", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/lk/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/lk", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Quantized State Systems (QSS) Solver with Functional Mock-Up Units (FMU) Support", + "laborHours": 23560.0, + "name": "Quantized State Systems (QSS) Solver with Functional Mock-Up Units (FMU) Support", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/SOEP-QSS/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SOEP-QSS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "BSF is a highly efficient pairwise similarity algorithm enabling extensive data mining.", + "laborHours": 91.2, + "name": "Blazing Signature Filter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/bsf-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The PLEXOS Input Data Generator (PIDG) is a tool that enables PLEXOS users to better version their data, automate data processing, collaborate in developing inputs, and transfer data between different production cost modeling and other power systems analysis software. PIDG can process data that is in a generalized format from multiple input sources, including CSV files, PostgreSQL databases, and PSS/E .raw files and write it to an Excel file that can be imported into PLEXOS with only limited manual intervention.", + "laborHours": 1687.2, + "name": "PLEXOS Input Data Generator", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/PIDG/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PIDG", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "LEAF Version 2.0 is a framework comprising of three models RUSLE2, WEPS, and AGNPS. The framework can predict row crop, crop residue, and energy crop yields at a sub-field resolutions for various combinations of soil, climate and crop management and residue harvesting practices. It estimates the loss of soil, carbon, and nutrients to the atmosphere, to the groundwater, and to runoff. It also models the overland flow of water and washed-off sediments, nutrients and other chemicals to provide estimates of sediment, nutrient, and chemical loadings to water bodies within a watershed. AGNPS model and wash-off calculations are the new additions to this version of LEAF. Development of LEAF software is supported by DOE's BETO program.", + "laborHours": 0.0, + "languages": [], + "name": "Landscape Environmental Assessment Framework", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/LEAF", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "SIEVAS provides an immersive visualization framework for connecting multiple systems in real time for data science. SIEVAS provides the ability to connect multiple COTS and GOTS products in a seamless fashion for data fusion, data analysis, and viewing. It provides this capability by using a combination of micro services, real time messaging, and web service compliant back-end system.", + "laborHours": 15929.6, + "languages": [], + "name": "Scientific & Intelligence Exascale Visualization Analysis System", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/SIEVAS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "LUNUS software for generating 3D maps of diffuse scattering from macromolecular X-ray crystallography diffraction images. A set of tools needed for advanced refinement of crystal structures and crystallographic charge density models. Includes tools for processing X--ray diffraction images, charge density maps, and structure factors for analysis of diffuse X-ray scattering and charge density variations in crystallography. Specific methods include: elementary algebraic operations on images and 3D lattices; fourier transform of images and 3D lattices; image processing to measure diffuse intensity; crystallographic refinement; and 3D integration of diffuse intensity.", + "laborHours": 25353.6, + "name": "LUNUS, Version 0.1a", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mewall/lunus/blob/master/00LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mewall/lunus", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software implements a heterogeneous multiscale method (HMM), which involves solving a classical molecular dynamics (MD) problem and then computes the entropy production in order to compute the relaxation times towards equilibrium for use in a Bhatnagar-Gross-Krook (BGK) solver.", + "laborHours": 1900.0, + "name": "BGK-MD, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/gilshohet/plasma-bgkmd/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gilshohet/plasma-bgkmd", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Building on the existing Multiplicative Attribute Graph (MAG) model, the software relaxes the assumptions of the MAG model allowing dataset expansion while replicating statistical properties.", + "laborHours": 349.6, + "name": "Realistic Simulation of Property Graphs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/propgraph/pgm/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/propgraph/pgm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Nmrfit reads the output from a nuclear magnetic resonance (NMR) experiment and, through a number of intuitive API calls, produces a least-squares fit of Voigt-function approximations via particle swarm optimization.", + "laborHours": 380.0, + "name": "nmrfit", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/nmrfit/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/nmrfit", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "PolyPole is a numerical algorithm for the calculation of intra-granular fission gas release. In particular, the algorithm solves the gas diffusion problem in a fuel grain in time-varying conditions. The program has been extensively tested. PolyPole combines a high accuracy with a high computational efficiency and is ideally suited for application in fuel performance codes.", + "laborHours": 0.0, + "languages": [], + "name": "Polypole Program For The Calculation Of Intra-granular Fission Gas Release", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/PolyPole", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The Idaho National Laboratory (INL) has teamed with University of Idaho and Boise State University to make the use of ADs more attractive by implementing a two-stage AD and coupling additional processes to the system. The addition of a polyhydroxyalkanoate (PHA) reactor, algae cultivation system, and a biomass treatment system such as fast-pyrolysis or hydrothermal liquefaction (HTL) would further sequester carbon and nutrients, as well as add valuable products that can be sold or used on-site to mitigate costs. The Decision-support for Digester-Algae IntegRation for Improved Environmental and Economic Sustainability (DAIRIEES) technoeconomic model will play a key role in evaluating the effectiveness and viability of this system to achieve economic and environmental sustainability by the dairy industry.", + "laborHours": 0.0, + "languages": [], + "name": "Decision Support For Digester Algae Integration For Improved Environmental And Economic Sustainability", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/DAIRIEES", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The Water-Energy Simulation Toolset (WEST) is an interactive simulation model that helps visualize impacts of different stakeholders on water quantity and quality of a watershed. The case study is applied for the Snake River Basin with the fictional name Cutthroat River Basin. There are four groups of stakeholders of interest: hydropower, agriculture, flood control, and environmental protection. Currently, the quality component depicts nitrogen-nitrate contaminant. Users can easily interact with the model by changing certain inputs (climate change, fertilizer inputs, etc.) to observe the change over the entire system. Users can also change certain parameters to test their management policy.", + "laborHours": 0.0, + "languages": [], + "name": "Water Energy Simulation Toolset", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/WEST", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "This program has been designed to assist with the tracking of a sample from one analytical instrument to another such as SEM, microscopes, micro x-ray diffraction and other instruments where particular positions/locations on the sample are examined, photographed, etc. The software is designed to easily enter the position of fiducials and locations of interest such that in a future session in the same of different instrument the positions of interest can be re-found through using the known location fiducials in the current and reference session to transform the point into the current sessions coordinate system. The software is dialog box driven guiding the user through the necessary data entry and program choices. Information is stored in a series of text based extensible markup language (XML) files.", + "laborHours": 0.0, + "languages": [], + "name": "Cross-instrument Analysis Correlation Software", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/CIACS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "AMG is a parallel algebraic multigrid solver for linear systems arising from problems on unstructured grids. It has been derived directly from the BoomerAMG solver in the hypre library, a large linear solvers library that is being developed in the Center for Applied Scientific Computing (CASC) at LLNL and is very similar to the AMG2013 benchmark with additional optimizations. The driver provided in the benchmark can build various test problems. The default problem is a Laplace type problem with a 27-point stencil, which can be scaled up and is designed to solve a very large problem. A second problem simulates a time dependent problem, in which successively various smnllcr systems are solved.", + "laborHours": 44414.4, + "name": "Algebraic Multigrid Benchmark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AMG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The ProvEn Software is designed to analyze and monitor distributed scientific workflow application behavior in the context of its environment.", + "laborHours": 349.6, + "name": "Provenance Environment Services Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ProvenanceEnvironment", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is the repository for Building Energy Management Open Source Software (BEMOSS), which is an open source operating system that is engineered to improve sensing and control of equipment in small- and medium-sized commercial buildings. BEMOSS offers the following key features: (1) Open source, open architecture \u2013 BEMOSS is an open source operating system that is built upon VOLTTRON \u2013 a distributed agent platform developed by Pacific Northwest National Laboratory (PNNL). BEMOSS was designed to make it easy for hardware manufacturers to seamlessly interface their devices with BEMOSS. Software developers can also contribute to adding additional BEMOSS functionalities and applications. (2) Plug & play \u2013 BEMOSS was designed to automatically discover supported load controllers (including smart thermostats, VAV/RTUs, lighting load controllers and plug load controllers) in commercial buildings. (3) Interoperability \u2013 BEMOSS was designed to work with load control devices form different manufacturers that operate on different communication technologies and data exchange protocols. (4) Cost effectiveness \u2013 Implementation of BEMOSS deemed to be cost-effective as it was built upon a robust open source platform that can operate on a low-cost single-board computer, such as Odroid. This feature could contribute to its rapid deployment in small- or medium-sized commercial buildings. (5) Scalability and ease of deployment \u2013 With its multi-node architecture, BEMOSS provides a distributed architecture where load controllers in a multi-floor and high occupancy building could be monitored and controlled by multiple single-board computers hosting BEMOSS. This makes it possible for a building engineer to deploy BEMOSS in one zone of a building, be comfortable with its operation, and later on expand the deployment to the entire building to make it more energy efficient. (6) Ability to provide local and remote monitoring \u2013 BEMOSS provides both local and remote monitoring ability with role-based access control. (7) Security \u2013 In addition to built-in security features provided by VOLTTRON, BEMOSS provides enhanced security features, including BEMOSS discovery approval process, encrypted core-to-node communication, thermostat anti-tampering feature and many more. (8) Support from the Advisory Committee \u2013 BEMOSS was developed in consultation with an advisory committee from the beginning of the project. BEMOSS advisory committee comprises representatives from 22 organizations from government and industry.", + "laborHours": 153185.6, + "name": "Building Energy Management Open Source Software", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bemoss/BEMOSS3.5", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software is an application for Oelta3D, QT and OpenSceneGraph, all of which are extemal open source software.", + "laborHours": 2447.2, + "name": "Open Facility Viewer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Open-Facility-Viewer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OpenEIS was created to provide standard methods for authoring, sharing, testing, using, and improving algorithms for operational building energy efficiency with building managers and building owners. OpenEIS is designed as a no-cost/low-cost solution that will propagate the fault detection and diagnostic (FDD) solutions into the marketplace by providing state- of- the-art analytical and diagnostic algorithms. As OpenEIS penetrates the market, demand by control system manufacturers and integrators serving small and medium commercial customers will help push these types of commercial software tool offerings into the broader marketplace.", + "laborHours": 1036123.2, + "name": "Open Energy Information System version 2.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/VOLTTRON/openeis/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/openeis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The paramutate software package Is a tool to calculate the genotyplc and phenotyplc propagation of a gene drive that can be silenced with a homologuus trans-Inactivating panmutatlon, ln dlptera or other species with a slmUar-acttng pl RNA system/Plwi pathway. Method of SolaUon: paramutate uses rults of Mendelian, gene drive (I.e.. stimulated conversion), and maternal Inheritance to compute the propaptlon of a notional gene drive construct and Its trans-lnactlvat1n1 paramutatlon, throu1b a panmlctlc, fixed-size population reproducing In synchronous generations.", + "laborHours": 12813.6, + "name": "Reversible Gene Drive Mechanism Utilizing Trana Inactivating Paramutatlons In Insects (paramutale 0.9)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/RAJAPerf/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RAJAPerf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The Hybrid Toolkit facilitates moving research algorithms into a production environment by creating useful abstractions that separate analytics developers from the intricacies of the production data formats, data flows, and result representations. The toolkit also assists developers with activities such as creating analysis feature vectors, converting between data structures, and creating data pipelines.", + "laborHours": 13087.2, + "name": "The Hybrid Toolkit", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/The-Hybrid-Toolkit/tree/master/docs", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/The-Hybrid-Toolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Demeter-W, an open-access software written in Python, consists of extensible module packages. It is developed with statistical downscaling algorithms, to spatially and temporally downscale water demand data into finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. For better understanding of the driving forces and patterns for global water withdrawal, the researchers is able to utilize Demeter-W to reconstruct the data sets to examine the issues related to water withdrawals at fine spatial and temporal scales.", + "laborHours": 1124.8, + "name": "Demeter-W", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/demeter-w", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "EnergyPlus(TM) is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption - for heating, cooling, ventilation, lighting and plus and process loads - and water use in buildings.", + "laborHours": 2335920.8, + "name": "EnergyPlus", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/EnergyPlus/blob/develop/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlus", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-03-28" + }, + "description": "A Modelica based library for modeling thermal hydraulic energy systems and other multi-physics systems. \n\nExisting development tools for early stage design and scoping of energy systems are often time consuming to use, proprietary, and do not contain the necessary function to model complete systems (i.e., controls, primary, and secondary systems) in a common platform. The Modelica programming language based TRANSFORM tool (1) provides a standardized, common simulation environment for early design of energy systems (i.e., power plants), (2) provides a library of baseline component modules to be assembled into full plant models using available geometry, design, and thermal-hydraulic data, (3) defines modeling conventions for interconnecting component models, and (4) establishes user interfaces and support tools to facilitate simulation development (i.e., configuration and parameterization), execution, and results display and capture.", + "laborHours": 1732.8, + "languages": [], + "name": "TRANSFORM - TRANsient Simulation Framework of Reconfigurable Models", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-Modelica/TRANSFORM-Library/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-Modelica/TRANSFORM-Library", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The gr-uaslink software is an out of tree (OOT) module for GNU Radio. It provides a wrapper around pymavlink to allow MAVlink messages to be sent with GNU Radio.", + "laborHours": 7372.0, + "name": "gr-uaslink", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/deptofdefense/gr-uaslink", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HELICS ls a new open-source, cyber-physlcal-energy co-simulation framework for electric power systems. HELICS Is designed to support very-large-scale (100,000+ federates) co\u00adsimulations with off-the-shelf power-system, communication, market, and end-use tools. Other key features Include cross platform operating system support, the integration of both eventdrlven (e.g., packetlzed communication) and time-series (e.g.,power flow) simulations, and the ability to co-Iterate among federates to ensure physical model convergence at each time step.", + "laborHours": 265848.0, + "name": "Hiearchical Engine for Large Scale Infrastructure Simulation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GMLC-TDC/HELICS-src/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GMLC-Tdc/HELICS-src", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-11-06" + }, + "description": "VOLTTRON is an agent execution platform providing services to its agents that allow them to easily communicate with physical devices and other resources. VOLTTRON delivers an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls. It enables mobile and stationary software agents to perform information gathering, processing, and control actions. VOLTTRON can independently manage a wide range of applications, such as HVAC systems, electric vehicles, distributed energy or entire building loads, leading to improved operational efficiency.", + "laborHours": 0.0, + "languages": [], + "name": "VOLTTRON Version 5.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/VOLTTRON/volttron/blob/master/TERMS.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron/releases/tag/5.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "5.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-02-27" + }, + "description": "Originally developed in 1999, an updated version 8.8.0 with bug fixes was released on September 30th, 2017. EnergyPlus\u2122 is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption\u2014for heating, cooling, ventilation, lighting and plug and process loads\u2014and water use in buildings. EnergyPlus is a console-based program that reads input and writes output to text files. It ships with a number of utilities including IDF-Editor for creating input files using a simple spreadsheet-like interface, EP-Launch for managing input and output files and performing batch simulations, and EP-Compare for graphically comparing the results of two or more simulations. Several comprehensive graphical interfaces for EnergyPlus are also available. DOE does most of its work with EnergyPlus using the OpenStudio\u00ae software development kit and suite of applications. DOE releases major updates to EnergyPlus twice annually.", + "laborHours": 2335920.8, + "languages": [], + "name": "EnergyPlus\u2122 (SWR-17-23)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/EnergyPlus/blob/develop/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlus", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "ExaMPM is a mini-application for the Material Point Method (MPM) for studying the application of MPM to future exascale computing systems. MPM is a general method for computational mechanics and fluids and is used in a wide variety of science and engineering disciplines to study problems with large deformations, phase change, fracture, and other phenomena. ExaMPM provides a reference implementation of MPM as described in the 1994 work of Sulsky et.al. (Sulsky, Deborah, Zhen Chen, and Howard L. Schreyer. \"A particle method for history-dependent materials.\" Computer methods in applied mechanics and engineering 118.1-2 (1994): 179-196.). The software can solve basic MPM problems in solid mechanics using the original algorithm of Sulsky with explicit time integration, basic geometries, and free-slip and no-slip boundary conditions as described in the reference. ExaMPM is intended to be used as a starting point to design new parallel algorithms for the next generation of DOE supercomputers.", + "laborHours": 33911.2, + "name": "ExaMPM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ECP-copa/ExaMPM", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-copa/ExaMPM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ProRad is a computer program that is used to generate synthetic images of proton (or other charged particles) radiographs. The proton radiographs arc images that arc obtained by sending energetic protons (or electrons or positrons, for example) through 11 plasma where electric and/or magnetic fields alter the particles trajectory, Dnd the variations me imaged on RC film, image plate, or equivalent", + "laborHours": 988.0, + "name": "Proton Radiography Imager:Generates Synthetic Proton Radiographs", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/prorad/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/prorad", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-12-03" + }, + "description": "The Sandia Engineering Analysis Code Access System (SEACAS) is a suite of preprocessing, post processing, translation, visualization, and utility applications supporting finite element analysis software using the Exodus database file format.", + "laborHours": 692284.0, + "languages": [ + "MATLAB" + ], + "name": "Sandia Engineering Analysis Code Access System v. 2.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Python script for querying a list of web sites and their details from Splunk and dynamically creating tests for monitoring uptime. The data generated from this script is then sent back to Splunk for creating reports and alerts.", + "laborHours": 212.8, + "name": "Synthetic Transaction Test Generator for Websites", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/justinatpnnl/splunk_web_transactions_generator", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/justinatpnnl/splunk_web_transactions_generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Password management solutions exist, but few are designed for enterprise systems administrators sharing oncall rotations. Due to the Multi-Factor Level of Assurance 4 effort, DOE is now distributing PIV cards with cryptographically signed certificate and private key pairs to administrators and other security-significant users. We utilize this public key infrastructure (PKI) to encrypt passwords for other recipients in a secure way. This is cross platform (works on OSX and Linux systems), and has already been adopted internally by the NCCS systems administration staff to replace their old password book system.", + "laborHours": 1626.4, + "name": "PKPass", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/olcf/pkpass", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/pkpass", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A pipeline for scanning domains to measure things like speed, accessibility, and HTTPS.", + "laborHours": 2781.6, + "name": "domain-scan", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/18F/domain-scan/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/18F/domain-scan", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "libristra is a mathematical and computational utility and support library for codes. It includes utilities such as input parsing, commonly used mathematical routines, scientific units, etc.", + "laborHours": 18012.0, + "name": "libristra", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laristra/libristra", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Canary is an extensible water-quality change-detection tool for algorithm development. It has been developed in MATLAB and was developed as part of an IAG with the US EPA NHSRC.", + "homepageURL": "https://software.sandia.gov/trac/canary", + "laborHours": 0.0, + "name": "CANARYV1.5", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://software.sandia.gov/trac/canary", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "YADAS is a software system for statistical analysis, using Markov chain Monte carlo (MCMC). As such, it performs Monte Carlo integration of probability distributions and generates estimates of unknown quantities based on data and expert opinion if available. Its architecture makes it extensible enought to be helpful in the analysis of any statistical model, so it is particularly useful for statistic researchers. YADAS features a versatile scheme for defining models, and another versatile scheme for defining sampling algorithms that includes a default starting place for most analyses. Models are specified using bonds, which relate unknown parameters using a probability density function through functions that convert the parameters into arguments of the probability density. This structure appears to be versatile enough to be useful for virtually all statistical models. The updating algorighms emphasize componentwise random walk Metropolis algorighm updates, but YADAS also contains a framework for updating correlated parameters together. Reversible jump updates are also supported.", + "homepageURL": "http://yadas.lanl.gov/index.html", + "laborHours": 0.0, + "name": "YADAS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://yadas.lanl.gov/node34.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://yadas.lanl.gov/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "This software, a library, contains FORTRAN77 subroutines to calculate first and second derivatives up to 8th order, interpolations (1D and 2D) up to 10th order and filters up to 14th order. Only even orders are addressed and finite-difference stencils are implemented on a vertex-centered mesh. The primary aim of this library is to be used in block-structured adaptive mesh simulations where high order is desired. The interpolants in this library are essentially designed to do prolongations and restrictions between levels of rfinement - however, they assume that the refinement ratio is 2. The filters are provided to remove high wavenumber content from solutions in case Runge phenomenon occurs - a common occurrence in case of marginal resolution of the solution. Details of the derivation and use are to be found in \"Using high-order methods on adaptively refined block-structured meshes - discretizations, interpolations and filters\", by J. Ray, C.A. Kennedy, S. Lefantzi and H.N. Najm, Sandia Technical Report, SAND2005-7981. The software comes with a User's Guide and examples how to use it.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "HODIF: High-Order Discretizations, Interpolations and Filters for AMR", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HODIF", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Our work is aimed at providing a data store for system-level events and presenting a flexible query interface to those events. The work extends the functinality provided by the open source Request Tracker (RT) (http://www.bestpractical.com/rt) project witht the Asset Tracker (AT) addon (http://atwiki.chaka.net). We have developed an Event Tracker add-on to RT and an interface for gathering, dispatching, and inserting system events into Event Tracker. Data sources include data from all components of the system. Data is initially sent to a defined set of data filters. The data filters are capable of discarding specified data, throttling input, handling context-sensitive input, passing data through an external shell pipe command, and compressing multiple data enteries into a single event. The filters then pass the data on to an event dispatch engine. The dispatcher can print events to the screen as they happen, track them in the database, forward them on, or pass them on to an external command. By collecting all of the data into a single database, we are able to leverage the Query Builder interface supplied by RT to create, save, and restore almost any kind of query imaginable.", + "homepageURL": "https://sourceforge.net/projects/rasilience", + "laborHours": 0.0, + "name": "Reliability Availability Serviceability", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/rasilience", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "P-STET assists in the security technology decision making process from a costlbeneflt perspective. It aids in addressing such questions as whether to acquire and deploy new security technology, to re-configure an existing product or system, or to maintain status quo. P-STET offers both a qualitative and quantitative option. P-STET is most efficient when tailored to an organization's security cost/benefit environment. It then serves as both a guide to show what types of security questions should be addressed and as a means to analyze the data gathered from the questions to make an informed decision. The quantitative option provides a straightforward way to express costs/benefits in terms of dollars. It relies on the organization to quantify benefits or cost avoidances, and, therefore, best serves as a guide to ensure various cost and benefit angles are evaluated. The qualitative option allows the organization to assess costs by levels with respect to security and PCS budgets, operational impacts, and opportunity costs. Benefits are represented in terms of improvements to the organization's operations and are also assessed by levels with respect to some benchmark such as compliance with best practices. Results are displayed graphically using radar charts, allowing the user to make a more intuitive decision. The shaded area of each chart represents the overall cost and benefit of the security investment. A good investment is denoted when the ratio of benefit shaded area to cost shaded area is large.", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "PCS Security Technology Evaluation Tool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/P-STET", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "IBSimu(Ion Beam Simulator) is a computer program for making two and three dimensional ion optical simulations. The program can solve electrostatic field in a rectangular mesh using Poisson equation using Finite Difference method (FDM). The mesh can consist of a coarse and a fine part so that the calculation accuracy can be increased in critical areas of the geometry, while most of the calculation is done quickly using the coarse mesh. IBSimu can launch ion beam trajectories into the simulation from an injection surface or fomo plasma. Ion beam space charge of time independent simulations can be taken in account using Viasov iteration. Plasma is calculated by compensating space charge with electrons having Boltzmann energy distribution. The simulation software can also be used to calculate time dependent cases if the space charge is not calculated. Software includes diagnostic tools for plotting the geometry, electric field, space charge map, ion beam trajectories, emittance data and beam profiles.", + "homepageURL": "https://sourceforge.net/projects/ibsimu", + "laborHours": 0.0, + "name": "Ion Beam Simulator", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/ibsimu", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MpiGraph consists of an MPI application called mpiGraph written in C to measure message bandwidth and an associated crunch_mpiGraph script written in Perl to process the application output into an HTMO report. The mpiGraph application is designed to inspect the health and scalability of a high-performance interconnect while under heavy load. This is useful to detect hardware and software problems in a system, such as slow nodes, links, switches, or contention in switch routing. It is also useful to characterize how interconnect performance changes with different settings or how one interconnect type compares to another.", + "homepageURL": "https://sourceforge.net/projects/mpigraph", + "laborHours": 0.0, + "name": "mpiGraph", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/mpigraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "EPANET-BAM 1.0 is an augmented version of EPANET 2.00.10, open-source software distributed by the US Environmental Protection Agency that models flow and contaminant transport through water distribution pipe networks. EPANET-BAM uses a new Bulk advective Mixing (BAM) model to predict concentrations of an aqueous solute at the outlets of cross junctions in a water quality simulation.", + "laborHours": 0.0, + "languages": [], + "name": "EPANET-BAM", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/EPANET-BAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Provides the shell of a plugin based application environment that builds on MVC Framework to allow one to rapidly construct an application by using a collection of plugins. The MVC Shell is implemented in C# as a .NET 2.0 application that can then be used as a shell for building a plugin based application. The infrastructure allows for dynamically processing a specified collection of plugins in order to determine the functionality of the application, where all plugins operate within the context of the underlying MVC Framework environment.", + "homepageURL": "http://www.codeplex.com/mvcshell", + "laborHours": 0.0, + "name": "MVC Shell", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.codeplex.com/mvcshell", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The TEVA-SPOT Toolkit (SPOT) supports the design of contaminant warning systems (CWSs) that use real-time sensors to detect contaminants in municipal water distribution networks. Specifically, SPOT provides the capability to select the locations for installing sensors in order to maximize the utility and effectiveness of the CWS. SPOT models the sensor placement process as an optimization problem, and the user can specify a wide range of performance objectives for contaminant warning system design, including population health effects, time to detection, extent of contamination, volume consumed and number of failed detections. For example, a SPOT user can integrate expert knowledge during the design process by specigying required sensor placements or designating network locations as forbidden. Further, cost considerations can be integrated by limiting the design with user-specified installation costs at each location.", + "laborHours": 30.4, + "languages": [ + "C++", + "C", + "Python" + ], + "name": "TEVA-SPOT Toolkit 1.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TEVA-SPOT-Toolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-02-07" + }, + "description": "PSUADE is an software system that is used to study the relationships between the inputs and outputs of general simulation models for the purpose of performing uncertainty and sensitivity analyses on simulation models.", + "laborHours": 0.0, + "languages": [], + "name": "Problem Solving Environment for Uncertainty Analysis and Design Exploration", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "TaqSim simulates various types of PRC reactions, including multiplex reactions. Given a set of primers and dearch databases, TaqSim identifies amplicons that match user defined criteria and can generate output files in a number of formats allowing it to serve as a front-end or back-end for other software.", + "homepageURL": "http://staff.vbi.vt.edu/dyermd/publications/taqsim.html", + "laborHours": 0.0, + "name": "TaqMan PCR Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://staff.vbi.vt.edu/dyermd/publications/taqsim.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "STRIDE is a suite of benchmarks, 8 in total, which access a computers low level caches and memory in a variety of patterns. The resulting performance of the kernels provides significant insight into the performance that a real application may incur and dictate how certain algorithmic choices should be made.", + "homepageURL": "https://asc.llnl.gov/sequoia/benchmarks", + "laborHours": 0.0, + "name": "Stride Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://asc.llnl.gov/sequoia/benchmarks", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "iScore measures the interestingness of news article in a limited user environment. it is an online learning algorithm that combines a large set of disparate features to classify documents.", + "homepageURL": "https://sourceforge.net/projects/iscore", + "laborHours": 0.0, + "name": "iScore: news filtering software", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/iscore", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "VisIt is an interactive parallel visualization and graphical analysis tool for viewing scientific date on UNIX and PC platforms. Users can quickly generate visualizations from their data, animate them through time, manipulate them, and save the resulting images for presentations. VisIt contains a rich set of visualization features so that you can view your data in a variety of ways. It can be used to visualize scalar and vector fields defined on two- and three- dimensional (2D and 3D) structured and unstructured meshes. VisIt was designed to handle very large data set sizes in the terascale range and yet can also handle small data sets in the kilobyte range.", + "homepageURL": "https://visit.llnl.gov", + "laborHours": 1937164.0, + "languages": [], + "name": "A Distributed, Parallel Visualization and Analysis Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://wci.llnl.gov/simulation/computer-codes/visit/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://visit.llnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pianola is a software benchmark for measuring the performance of input/output (I/O) hardware and software. It works by monitoring the I/O activity of an existing application and storing the sequence of events, along with their timing, in a script. After some additional processing, a separate piece of software in this package can replay these I/) events and replicate their timing without reference to the original application. Therefore, Pianola allows users to create standalone I/O benchmarks that mimic the behavior of applications that either cannot be released or that are difficult for nonspecialists to configure, build or run.", + "homepageURL": "https://computation.llnl.gov/software-catalog", + "laborHours": 0.0, + "name": "Pianola Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://computation.llnl.gov/software-catalog", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The MDEF package contains capabilities ofr modeling the deformation of materials at the crystal scale. Primary code capabilities are: xoth \"strength\" and \"equation of state\" aspects of material response, post-processing utilities, utilities for comparing results with data from diffraction experiments.", + "homepageURL": "https://anisotropy.mae.cornell.edu/dplab/mdef", + "laborHours": 0.0, + "name": "Multi-scale and Multi-phase deformation of crystalline materials", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://anisotropy.mae.cornell.edu/dplab/mdef", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-03-27" + }, + "description": "Embody (Environment Modules Build) is a software build tool with integrated support for the environment-modules package. The tool eases and automates the task of building and installing software packages from source or binary distributions, as well as the management of associated module files. An administrator or software pool maintainer has to write a brief script for the installation process. These steps are usually described for manual execution, in a package's README or INSTALL file. It would be up to the site administrator to work out a procedure to capture the steps taken. This tool: streamlines and codifies the installation tasks in a common framework; it provides a self-documenting and unified way for maintaining package installations; uses bash shell variables and functions for portability; keeps log files of the proceedings. It is similar in intent and function to other existing tools, such as RPM, but has several novel features tailored for High Performance Computing (HPC) software deployments. The design goal is simplicity and decoupling from RPM's dependencies and its database, which enables coexistence of several builds. Useful on HPC systems, new builds can be deployed centrally to shared file systems and without affecting running jobs.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "EMBODY(Environmental Modules Build System Software)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MeDICi is an evolving middleware platform for building complex, high performance analytical applications. These applications typically comprise a pipeline of software components, each of which performs some analysis on incoming data and passes on its results to the next step in the pipeline.", + "homepageURL": "http://medici.pnl.gov/download_mif", + "laborHours": 0.0, + "name": "Middleware for Data Intensive Computing", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://medici.pnl.gov/standard_pnnl_oss_liscense", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://medici.pnl.gov/download_mif", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The MapReduce MPI library is a software tool for performing MapReduce operations on a distributed memory parallel computer via message passing (MPI). These are data-processing or computational operations which achieve parallelism by breaking a large task into two stages, a map and a reduce . Each of these are formulated as simple on-processor functions which the user can easily write. The library assigns independent tasks to processors and performs the parallel data movement and transformations behind the scenes.", + "laborHours": 13315.2, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "HTML", + "Python", + "Odin" + ], + "name": "MapReduce MPI library (MR-MPI) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mapreduce", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The FAST software package contains a variety of Python packages for applying and managing software tests. In version 2.0, FAST includes (1) the EXACT package, which supports the definition and execution of computational experiments, (2) the FAST package, which manages the distributed execution of software builds, and (3) general tools related to the PyUnit testing framework.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "FAST - A Framework for Agile Software Testing v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://software.sandia.gov/trac/fast/wiki/Licensing", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fast", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "SOLERGY simulates the operation and power output of a user-defined solar central receiver power plant for a time period of up to one year. SOLERGY utilizes recorded or simulated weather data and plant component performance models to calculate the power flowing through each part of the solar plant. A plant control subroutine monitors these powers and determines when to operate the various plant subsystems. The original version of the code was released in May 1987, within SAND86-8060 and was widely distributed. The Beta Version 1 to be released in 2009, includes some relatively small modifications to the original code.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Solergy (Beta Version 1)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/solergy", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Dimensionality Reduction Library is a C++ library for dimensionality reduction. In the context of this library, dimensionality reduction is considered to consist of 1)estimation of the intrinsic dimensionality using sampled data, 2) Finding maps that reduce the dimensionality of data (forward map) or increase the dimensionality of data (reverse map) and 3) mapping arbitray coordinates to high and low dimensionalities. The library is intended to provide a consistent interface to multiple dimensionality reduction algorithms with an efficient C++ interface that runs efficiently on multicore architectures. A few routines have been optimized with an option for GPU acceleration or distributed computation. Currently the library offers intrinsic dimensionality estimation using point-PCA reconstruction error and/ residual variance. The following dimensionality reduction methods have been implemented: Principal Component Analysis Multidimensional Scaling Locally Linear Embedding IsoMap Autoencoder Neutral Networks An executable is also supplied that can be built to allow for command-line access to the library routines. A description for an application of the library for molecular structure analysis has been published.", + "laborHours": 6976.8, + "languages": [ + "JavaScript" + ], + "name": "Dimensionality Reduction Library v 0.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/dimensionality-reduction-library", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "DELSOL calculates collector field performance and layout and optimal system design for solar thermal central receiver plants. The code consists of a detailed model of the optical performance, a simpler model of the non-optical performance, an algorithm for field layout, and a searching algorithm to find the best system design based on energy cost. The latter two features are coupled to a cost model of central receiver components and an economic model for calculating energy costs. The program optimizes the tower height, receiver size, field layout, heliostat spacings, and tower position at user specified power levels.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "DELSOL v. 3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/delsol", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The RSTT software computes predictions of the travel time of seismic energy traveling from a source to a receiver through 2.5D models of the seismic velocity distribution within the Earth. The two primary applications for the RSTT library are tomographic inversion studies and seismic event location calculations. In tomographic inversions studies, a seismologist begins with number of source-receiver travel time observations and an initial starting model of the velocity distribution within the Earth. A forward travel time calculator, such as the RSTT library, is used to compute predictions of each observed travel time and all of the residuals (observed minus predicted travel time) are calculated. The Earth model is then modified in some systematic way with the goal of minimizing the residuals. The Earth model obtained in this way is assumed to be a better model than the starting model if it has lower residuals. The other major application for the RSTT library is seismic event location. Given an Earth model, an initial estimate of the location of a seismic event, and some number of observations of seismic travel time thought to have originated from that event, location codes systematically modify the estimate of the location of the event with the goal of minimizing the difference between the observed and predicted travel times. The second application, seismic event location, is routinely implemented by the military as part of its effort to monitor the Earth for nuclear tests conducted by foreign countries.", + "laborHours": 0.0, + "languages": [ + "Python", + "Java", + "C++", + "C" + ], + "name": "Code for Calculating Regional Seismic Travel Time", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/rstt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "A library of utility classes for computer vision. Contains implementations of various well-known image processing techniques, such as interest point operators and region descriptors. Includes interfaces to various libraries for image and video I/O, as well as an interface to LAPACK/BLAS. FL was developed at the University of Illinois, Urbana-Champaign (UIUC) and released under an open source license. Version 1.2 was a maintenance release provided by SNL under the LGPL license. Version 1.3 is a maintenance release, containing the following changes: - Improved image format handling. Now handles strided and planar memory layouts and a wider range of pixel formats. - Improved image file I/O, including better support for metadata, a wider range of stored pixel types, and a couple of new file formats. - Improvements to DOG and SIFT, and efficiency improvements in low-level convolution. - Improvements to networking, including a generic TCP listener. - Various improvements to numerical processing. The HISTORY file included in the distribution contains a more detailed description of the changes.", + "laborHours": 35978.4, + "languages": [ + "CMake", + "C++" + ], + "name": "FL V1.3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.3" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-02-07" + }, + "description": "PSUDE is an software system that is used to study the relationships between the inputs and outputs of general simulation models for the purpose of performing uncertainty and sensitivity analyses on simulation models.", + "laborHours": 0.0, + "languages": [], + "name": "Problem Solving Environment for Uncertainty Analysis and Design Exploration", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.2.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "HOPSPACK is open source software for solving optimization problems without derivatives. Application problems may have a fully nonlinear objective function, bound constraints, and linear and nonlinear constraints. Problem variables may be continuous, integer-valued, or a mixture of both. The software provides a framework that supports any derivative-free type of solver algorithm. Through the framework, solvers request parallel function evaluation, which may use MPI (multiple machines) or multithreading (multiple processors/cores on one machine). The framework provides a Cache and Pending Cache of saved evaluations that reduces execution time and facilitates restarts. Solvers can dynamically create other algorithms to solve subproblems, a useful technique for handling multiple start points and integer-valued variables. HOPSPACK ships with the Generating Set Search (GSS) algorithm, developed at Sandia as part of the APPSPACK open source software project.", + "laborHours": 0.0, + "languages": [], + "name": "Hybrid Optimization Parallel Search PACKage", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hopspack", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "This OpenFabrics Alliance (OFA) OpenSM routing engine module provides credit-loop-free routing while supporting two quality of service (QoS) levels for an InfiniBand fabric with a 3D torus topology. In addition it is able to route around multiple failed fabric links or a single failed fabric switch without introducing credit loops, and without changing path Service Level (SL) values granted before the failure.This OFA OpenSM routing engine module improves the operational characteristics of a parallel computer built using an InfiniBand fabric with a 3D torus topology. By providing two QoS levels, it allows system administrators to prevent application interprocess communication and file system communication from impacting each other. By providing the capability to route traffic around failed fabric components, it enables repair of failed components without impacting jobs running on the computer system.", + "homepageURL": "http://downloads.openfabrics.org/OFED", + "laborHours": 0.0, + "name": "3D Torus Routing Engine Module for OFA OpenSM v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://downloads.openfabrics.org/OFED/README.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://downloads.openfabrics.org/OFED", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The MEGRAPHS software package provides a front-end to graphs and vectors residing on special-purpose computing resources. It allows these data objects to be instantiated, destroyed, and manipulated. A variety of primitives needed for typical graph analyses are provided. An example program illustrating how MEGRAPHS can be used to implement a PageRank computation is included in the distribution.The MEGRAPHS software package is targeted towards developers of graph algorithms. Programmers using MEGRAPHS would write graph analysis programs in terms of high-level graph and vector operations. These computations are transparently executed on the Cray XMT compute nodes.", + "laborHours": 0.0, + "languages": [], + "name": "Modular Environment for Graph Research and Analysis with a Persistent", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/megraphs", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The MultiThreaded Graph Library (MTGL) is a set of header files that implement graph algorithm in such a way that they can run on massively multithreaded architectures. It is based upon the Boost Graph Library, but doesn't use Boost since the latter doesn't run well on these architectures.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "The MultiThreaded Graph Library (MTGL)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mtgl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The MapReduceXMT library ports the MapReduce framework onto the Cray XMT. MapReduce is a programming paradigm and an approach to data management for unstructured problems. It has gained relevance due to its ability to map serial operations onto parallel distributed architectures, significantly improving developer/analyst productivity. The MapReduceXMT implements the key aspects of MapReduce for the Cray XMT, a massively threaded system that is inherently difficult to program. MapReduceXMT allows users to utilize the machine effectively and efficiently without extensive training in multi-threaded programming. The MapReduceXMT library ports the MapReduce framework onto the Cray XMT. MapReduce is a programming paradigm and an approach to data management for unstructured problems. It has gained relevance due to its ability to map serial operations onto parallel distributed architectures, significantly improving developer/analyst productivity. The MapReduceXMT implements the key aspects of MapReduce for the Cray XMT, a massively threaded system that is inherently difficult to program. MapReduceXMT allows users to utilize the machine effectively and efficiently without extensive training in multi-threaded programming.", + "laborHours": 0.0, + "languages": [], + "name": "MapReduceXMT v. Beta 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/map-reduce-xmt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This revision corrects some errors in SPRNG 1. Users of newer SPRNG versions can obtain the corrected files and build their version with it. This version also improves the scalability of some of the application-based tests in the SPRNG test suite. It also includes an interface to a parallel Mersenne Twister, so that if users install the Mersenne Twister, then they can test this generator with the SPRNG test suite and also use some SPRNG features with that generator.", + "homepageURL": "http://www.sprng.org", + "laborHours": 0.0, + "name": "SPRNG Scalable Parallel Random Number Generator LIbrary", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://creativecommons.org/licenses/by-nc-sa/4.0", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.sprng.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-15" + }, + "description": "Extensions to the AMPL/solver interface library (http://netlib.sandia.gov/ampl/solvers) to compute bounds on algebraic expressions, plus a test program. use in uncertainty quantification and global optimization algorithms. This software is not primarily for military applications.", + "homepageURL": "https://netlib.sandia.gov/ampl/solvers", + "laborHours": 0.0, + "languages": [], + "name": "Slope Extensions to ASL Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://netlib.sandia.gov/ampl/solvers/README", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://netlib.sandia.gov/ampl/solvers", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-18" + }, + "description": "Partially completed extensions for stochastic programming to the AMPL/solver interface library (ASL).modeling and experimenting with stochastic recourse problems. This software is not primarily for military applications.", + "homepageURL": "https://www.netlib.org/ampl/solvers", + "laborHours": 0.0, + "languages": [], + "name": "Partial ASL extensions for stochastic programming", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://netlib.sandia.gov/ampl/solvers/README", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.netlib.org/ampl/solvers", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Foobug is an application to assist a group of developers in keeping track of issues relevant to their shared interests. These are sometimes called \"bug-tracking\" or \"ticket-tracking\" systems.", + "homepageURL": "http://sourceforge.net/projects/foobug", + "laborHours": 0.0, + "name": "Foobug", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://sourceforge.net/projects/foobug", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Inline_System replaces a small subset of file query and manipulation commands, on computing platforms that do not offer a complete standard POSIX environment.", + "homepageURL": "https://sourceforge.net/projects/inlinesystem", + "laborHours": 0.0, + "name": "Inline_System", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/inlinesystem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "A C++ utility library that provides abstractions for common data types with debugging features, support for I/O redirection and support for portability.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "C++ Utility Library V4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/snl-dakota/dakota-packages", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "4.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Acro provides a software infrastructure that integrates a variety of optimization software libraries, as well as general-purpose libraries like UTILIB that support the development of parallel optimizers.", + "homepageURL": "https://software.sandia.gov/trac/acro", + "laborHours": 0.0, + "name": "Acro (A Common Repository for Optimizers) v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://software.sandia.gov/trac/acro", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The Cognitive Foundry is a unified collection of tools designed for research and applications that use cognitive modeling, machine learning, or pattern recognition. The software library contains design patterns, interface definitions, and default implementations of reusable software components and algorithms designed to support a wide variety of research and development needs. The library contains three main software packages: the Common package that contains basic utilities and linear algebraic methods, the Cognitive Framework package that contains tools to assist in implementing and analyzing theories of cognition, and the Machine Learning package that provides general algorithms and methods for populating Cognitive Framework components from domain-relevant data.", + "laborHours": 189939.2, + "languages": [ + "Java" + ], + "name": "Cognitive Foundry v. 3.0 (OSS)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/algorithmfoundry/Foundry", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-02-07" + }, + "description": "PSUADE is an software system that is used to study the relationships between the inputs and outputs of general simulation models for the purpose of performing uncertainty and sensitivity analyses on simulation models.", + "laborHours": 0.0, + "languages": [ + "C(80%), C++(20%)" + ], + "name": "Problem Solving Environment for Uncertainty Analysis and Design Exploration", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.3" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "This code consists of Matlab routines which enable the user to perform non-manifold surface reconstruction via triangulation from high dimensional point cloud data. The code was based on an algorithm originally developed in [Freedman (2007), An Incremental Algorithm for Reconstruction of Surfaces of Arbitrary Codimension Computational Geometry: Theory and Applications, 36(2):106-116]. This algorithm has been modified to accommodate non-manifold surface according to the work described in [S. Martin and J.-P. Watson (2009), Non-Manifold Surface Reconstruction from High Dimensional Point Cloud DataSAND #5272610].The motivation for developing the code was a point cloud describing the molecular conformation space of cyclooctane (C8H16). Cyclooctane conformation space was represented using points in 72 dimensions (3 coordinates for each molecule). The code was used to triangulate the point cloud and thereby study the geometry and topology of cyclooctane. Futures applications are envisioned for peptides and proteins.", + "laborHours": 0.0, + "languages": [], + "name": "NMTRI v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/NMTRI", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/NMTRI", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "BUHFS is a fuse-based POSIX compliant filesystem interface for HPSS. 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Before use, the computed signatures must be empirically tested in a wet lab.", + "homepageURL": "https://sourceforge.net/projects/primux", + "laborHours": 0.0, + "name": "PriMux", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/primux", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Provides python rountines to convert ENDF-6 formatted nuclear data (4) into the new GND structure. 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SWQM consists of a set of Matlab scripts that model the statistical variation that is expected in a water treatment facility's water, such as pH and chlorine levels.", + "homepageURL": "https://software.sandia.gov/trac/canary/downloader/download/category/10", + "laborHours": 0.0, + "name": "SWQM: Source Water Quality Modeling Software", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://software.sandia.gov/trac/canary/downloader/download/category/10", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://software.sandia.gov/trac/canary/downloader/download/category/10", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "G4beamline is a single-particle-tracking simulation code based on the Geant4 toolkit. It is specifically optimized for the realistic evaluation of beam lines. It is especially useful for evaluating future muon facilities.", + "homepageURL": "http://g4beamline.muonsinc.com", + "laborHours": 0.0, + "name": "G4beamline", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://g4beamline.muonsinc.com", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ] + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "THYME is an object oriented library for building models of wide area control and communications in electric power systems. This software is designed as a module to be used with existing open source simulators for discrete event systems in general and communication systems in particular. THYME consists of a typical model for simulating electro-mechanical transients (e.g., as are used in dynamic stability studies), data handling objects to work with CDF and PTI formatted power flow data, and sample models of discrete sensors and controllers.", + "homepageURL": "http://www.ornl.gov/~1qn/thyme/docs", + "laborHours": 0.0, + "name": "THYME: Toolkit for Hybrid Modeling of Electric Power Systems", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://web.ornl.gov/~nutarojj/thyme/docs/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.ornl.gov/~1qn/thyme/docs", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Bayesloc is a statistical model of the multiple seismic location system, including event hypocenters, corrections to model-based travel time predictions, assessments precision for measurement phase arrival times, and phase lavels which indicate phase ray path.", + "homepageURL": "https://www-gs.llnl.gov/nuclear-threat-reduction/nuclear-explosion-monitoring/bayesloc", + "laborHours": 0.0, + "name": "Bayesian Mulitple-Event Location", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www-gs.llnl.gov/nuclear-threat-reduction/nuclear-explosion-monitoring/bayesloc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CANARY -EDS provides probabilistic event detection based on analysis of time-series data from water quality or other sensors. CANARY also can compare patterns against a library of previously seen data to indicate that a certain pattern has reoccurred, suppressing what would otherwise be considered an event. CANARY can be configured to analyze previously recorded data from files or databases, or it can be configured to run in real-time mode directory from a database, or through the US EPA EDDIES software.", + "homepageURL": "https://software.sandia.gov/trac/canary", + "laborHours": 0.0, + "name": "Characterization and Analysis of Networked Array of Sensors for Event Detection (CANARY-EDS)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://software.sandia.gov/trac/canary", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The TChem toolkit is a software library that enables numerical simulations using complex chemistry and facilitates the analysis of detailed kinetic models. The toolkit provide capabilities for thermodynamic properties based on NASA polynomials and species production and consumption rates. It incorporates methods that can selectively modify reaction parameters for sensitivity analysis and uncertainty quantification. The library also contains several functions that provide analytically computed Jacobian matrices necessary for the efficient time advancement and analysis of detailed kinetic models.", + "homepageURL": "http://www.sandia.gov/tchem", + "laborHours": 0.0, + "name": "TChem", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.sandia.gov/tchem", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "LIME 0.5 is an initial version of a Lightweight Integrating Multi-physics Environment for coupling codes. LIME by itself is not a code for doing multiphysics simulations. Instead, LIME provides the key high-level software, a flexible but defined approach, and interface requirements for a collection of (potentially disparate) physics codes to be combined with strong coupling (when needed) though non-linear solution methods (e.g. JFNK, fixed point), thus creating a new multi-physics simulation capability customized for a particular need. The approach taken is designed to; preserve and leverage any important specialized algorithms and/or functionality an existing application may provide; minimize the requirements barrier for an application to participate; and work within advanced solver frameworks (e.g. as extensions to the Trilinos/NOX nonlinear solver libraries, PETSc, . . .). Of note is that components/physics codes that can be coupled within LIME are NOT limited to: components written in one particular language; a particular numerical discretization approach ( e.g. Finite Element); or physical models expressed as PDE's.", + "laborHours": 7326.4, + "languages": [ + "CMake", + "C++", + "Fortran" + ], + "name": "LIME 0.5", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/limeext", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-02-07" + }, + "description": "PSUADE is an software system that is used to study the releationships between the inputs and outputs of gerneral simulation models for the purpose of performing uncertainty and sensitivity analyses on simulation models.", + "laborHours": 0.0, + "languages": [], + "name": "Problem Solving Environment for Uncertainty Analysis and Design Exploration", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.4" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The All People's Simulator is a software package which can simulate a large number of people wandering randomly through a real city. It utilizes freely-available map data from the OpenStreetMaps project to create a map of city streets, then simulates people wandering through those streets. APS was designed to integrate with other work being done in the \"Megadroid\" LDRD, but is capable of functioning and providing value completely on its own.", + "laborHours": 547.2, + "languages": [ + "Go", + "Makefile" + ], + "name": "All People's Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/gosim?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gosim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Interatomic force and energy calculation subroutine tobe used with the molecular dynamics simulation code LAMMPS (Ref a.). The code evaluates the total energy and atomic forces (energy gradient) according to cubic spine-based variant (Ref b.) of the Modified Embedded Atom Method (MEAM).", + "homepageURL": "http://lammps.sandia.gov/download.html", + "laborHours": 0.0, + "name": "MEAM interatomic force calculation subroutine for LAMMPS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://lammps.sandia.gov/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The Water Security Toolkit (WST) provides software for modeling and analyzing water distribution systems to minimize the potential impact of contamination incidents. WST wraps capabilities for contaminant transport, impact assessment, and sensor network design with response action plans, including source identification, rerouting, and decontamination, to provide a range of water security planning and real-time applications.", + "laborHours": 695460.8, + "languages": [ + "C++", + "HTML", + "C", + "JavaScript", + "M4", + "Python" + ], + "name": "Water Security Toolkit", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/Water-Security-Toolkit?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Water-Security-Toolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "PHISH is a lightweight framework which a set of independent processes can use to exchange data as they run on the same desktop machine, on processors of a parallel machine, or on different machines across a network. This enables them to work in a coordinated parallel fashion to perform computations on either streaming, archived, or self-generated data. The PHISH distribution includes a simple, portable library for performing data exchanges in useful patterns either via MPI message-passing or ZMQ sockets. PHISH input scripts are used to describe a data-processing algorithm, and additional tools provided in the PHISH distribution convert the script into a form that can be launched as a parallel job.", + "laborHours": 6733.6, + "languages": [ + "C++", + "C", + "CMake", + "Makefile", + "Ring", + "Edge", + "Python" + ], + "name": "Parallel Harness for Informatic Stream Hashing", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/phish", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "This application simulates microstructural and compositional evolution in two-phase, two-component systems. It is designed to run within the SPPARKS solver and combines the kMC with solution to the Cahn-Hilliard Eq. for phase field.", + "laborHours": 165102.4, + "languages": [ + "C++", + "C" + ], + "name": "app_hybridPotts-phasefield.cpp", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spparks", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This application simulates simple solid state sintering by incorporating all the active mechanisms, namely, curvature-driven gain growth, pore shaping and migration by surface diffusion, and creation, diffusion and annihilation of vacancies. It is an application developed for SPPARKS and has to be run within this framework.", + "homepageURL": "http://spparks.sandia.gov", + "laborHours": 0.0, + "name": "app_sintering.cpp", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://spparks.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The plpdfa software is a product of an LDRD project at LLNL entitked \"Adaptive Sampling for Very High Throughput Data Streams\" (tracking number 11-ERD-035). This software was developed by a graduate student summer intern, Chris Challis, who worked under project PI Dan Merl furing the summer of 2011. The software the source code is implementing is a statistical analysis technique for clustering and classification of text-valued data. The method had been previously published by the PI in the open literature.", + "homepageURL": "http://cran.r-project.org", + "laborHours": 0.0, + "name": "Particle learning for probabilistic deterministic finite automata", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://cran.r-project.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DAQMAN is a flexible configurable interface that allows the user to build and operate a VME-based data acquisition system on a Linux workstation. It consists of two parts: a Java-based Graphical User Interface to configure the system, and a C-based utility that reads out the data and creates the output ASCII data file, with two levels of diagnostic tools. The data acquisition system requires a CAEN CONET-VME Bridge to communicate between the hardware in the VME crate and the Linux workstation. Data acquisition modules, such as ADCs, TDC, Scalers, can be loaded into the system, or removed easily. The GUI allows users to activate modules, and channels within modules by clicking on icons. Running configurations are stored; data are collected and can be viewed either as raw numbers, or by charts and histograms that update as the data are accumulated. Data files are written to disk in ASCII format, with a date and time stamp.", + "homepageURL": "https://www.bnl.gov/nsrl/userguide/data-aquisition.php", + "laborHours": 0.0, + "name": "DAQMAN - A flexible configurable data acquisition system", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.bnl.gov/nsrl/userguide/data-aquisition.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.bnl.gov/nsrl/userguide/data-aquisition.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HFBRHO is a physics computer code that is used to model the structure of the nucleus. It is an implementation of the nuclear energy Density Functional Theory (DFT), where the energy of the nucleus is obtained by integration over space of some phenomenological energy density, which is itself a functional of the neutron and proton densities. In HFBTHO, the energy density derives from the Skyrme effective two-body interaction between nucleons, nuclear superfluidity is treated at the Hartree-Fock-Bogoliubov (HFB) approximation, and axial-symmetry of the nuclear shape is assumed This version is the 2nd release of the program; the previous version has been published in Computer Physics Communications (1). It is the first version that has been partly developed at Lawrence Livermore National Laboratory.", + "homepageURL": "http://cpc.cs.qub.ac.uk/summaries/ADUI_v2_0.html", + "laborHours": 0.0, + "name": "HFBTHO", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://cpc.cs.qub.ac.uk/summaries/ADUI_v2_0.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "LMAT is designed to take as input a collection of raw metagenomic sequencer reads, and search each read against a reference genome database and assign a taxonomic label and confidence value to each read and report a summary of the predicted taxonomic contents of the metagenomic sample.", + "homepageURL": "https://sourceforge.net/projects/lmat", + "laborHours": 0.0, + "name": "Livermore Metagenomics Analysis Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/lmat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PERM is a C library for persistent heap management and is intended for use with a dynamic-memory allocator (e.g. malloc, free). The PERM memory allocator replaces the standard C dynamic memory allocation functions with compatible versions that provide persistent memory to application programs. Memory allocated with the PERM allocatory will persist between program invocations after a call to a checkpoint function. This function essentially saves the state of the heap and registered global variables to a file which may reside in flash memory or other node local storage. A few other functions are also provided by the library to manage checkpoint files. Global variables in an application can be marked persistent and be included in a checkpoint by using a compiler attribute defined as PERM. The PERM checkpoint methof is not dependent on the programming model ans works with distributed memory or shared memory programs.", + "homepageURL": "https://computation.llnl.gov/projects/memory-centric-architectures/download/perm-je-0.9.7.tgz", + "laborHours": 0.0, + "name": "Persistent heap Management library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://computation.llnl.gov/projects/memory-centric-architectures/download/perm-je-0.9.7.tgz", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MMA is a stand-alone memory management system for MPI clusters. It implements a shared Partitioned Global Address Space, where multiple MPI processes request objects from the allocator and the latter provides them with system-wide unique memory addresses for each object. It provides applications with an intuitive way of managing the memory system in a unified way, thus enabling easier writing of irregular application code.", + "homepageURL": "http://myrmics.com/download.php", + "laborHours": 0.0, + "name": "Myrmics Memory Allocator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://myrmics.com/downloads/mma_license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://myrmics.com/download.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GeoTess facilitates access to a multi-level triangular tessellation of a unit sphere, including find the index of the triangle in which an arbitrary position on the sphere resides and computing the interpolation coefficients that should be applied to data stored on the nodes of the tessellation that defines the triangle. It is very common for Earth scientists to store values of various Earth properties on a grid that spans the globe. For convenience, they almost always choose a grid which is evenly spaced in both latitude and longitude over the surface of the globe. While these grids are evenly spaced in latitude-longitude coordinates, they are in reality very unevenly spaced when cell size is evaluated in square km since lines of longitude converge at the poles. Tessellations consisting of a set of approximately equal area triangles that span the globe are much more efficient way to impose a grid onto the surface of a sphere. The GeoTess software facilitates interacting with a triangular tessellation of a sphere and could significantly increase the efficiency of Earth science software codes. The code can construct variable resolution triangular tessellations. It can also load a previously constructed tessellation from an input file and implements a \"walking triangle\" search algorithm to find the index of the triangle on the tessellation that contains a user specified point of interest. It also computes the interpolation coefficients that should be applied to data stored on the nodes of the containing triangle", + "laborHours": 135918.4, + "languages": [ + "Java", + "HTML" + ], + "name": "GeoTess v. 2.6.8", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GeoTessJava", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.6.8" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-19" + }, + "description": "SHOE is research code for characterizing and visualizing higher-order finite elements; it contains a framework for defining classes of interpolation techniques and element shapes; methods for interpolating triangular, quadrilateral, tetrahedral, and hexahedral cells using Lagrange and Legendre polynomial bases of arbitrary order; methods to decompose each element into domains of constant gradient flow (using a polynomial solver to identify critical points); and an isocontouring technique that uses this decomposition to guarantee topological correctness. Please note that this is an alpha release of research software and that some time has passed since it was actively developed; build- and run-time issues likely exist.", + "laborHours": 13360.8, + "languages": [ + "C++", + "C", + "CMake", + "Python" + ], + "name": "Sandia Higher Order Elements (SHOE) v 0.5 alpha", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/shoe", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "The Uncertainty Quantification (UQ) Toolkit is a software library for the characterizaton and propagation of uncertainties in computational models. For the characterization of uncertainties, Bayesian inference tools are provided to infer uncertain model parameters, as well as Bayesian compressive sensing methods for discovering sparse representations of high-dimensional input-output response surfaces, and also Karhunen-Lo\u00e8ve expansions for representing stochastic processes. Uncertain parameters are treated as random variables and represented with Polynomial Chaos expansions (PCEs). The library implements several spectral basis function types (e.g. Hermite basis functions in terms of Gaussian random variables or Legendre basis functions in terms of uniform random variables) that can be used to represent random variables with PCEs. For propagation of uncertainty, tools are provided to propagate PCEs that describe the input uncertainty through the computational model using either intrusive methods (Galerkin projection of equations onto basis functions) or non-intrusive methods (perform deterministic operation at sampled values of the random values and project the obtained results onto basis functions).", + "laborHours": 217101.6, + "languages": [ + "C++", + "C", + "Fortran" + ], + "name": "UQ Toolkit v 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/UQTk", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "CACTUS is a code that calculates the performance and aero/hydrodynamic loads of a wind or water turbine. The turbine may be either a vertical-axis or a horizontal-axis machine, and may consist of one or more blade curved or straight blades. The performance model is based on a lifting-line free wake formulation that calculates rotor power and blade loads in the time domain. The rotor is treated as a rotating rigid body, such that structural dynamical motions are not modeled. The turbine is assumed to operate within a steady, but possibly sheared, wind or current velocity. For marine hydrokinetic energy applications, the presence of a river/tidal channel bed and water surface boundaries may be modeled.", + "laborHours": 3587.2, + "languages": [ + "CMake", + "MATLAB", + "Fortran", + "GLSL", + "Python" + ], + "name": "Code for Axial and Crossflow Turbine Simulation", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CACTUS", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Our application, the Omics Metadata Management Software (OMMS), answers both needs, empowering experimentalists to generate intuitive, consistent metadata, and to perform bioinformatics analyses and information management tasks via a simple and intuitive web-based interface. Several use cases with short-read sequence datasets are provided to showcase the full functionality of the OMMS, from metadata curation tasks, to bioinformatics analyses and results management and downloading. The OMMS can be implemented as a stand alone-package for individual laboratories, or can be configured for web-based deployment supporting geographically dispersed research teams. Our software was developed with open-source bundles, is flexible, extensible and easily installed and run by operators with general system administration and scripting language literacy.", + "homepageURL": "http://omms.sandia.gov", + "laborHours": 0.0, + "name": "Omics Metadata Management Software v. 1 (OMMS)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://omms.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The RAPTOR computational pipeline identifies microbial nucleic acid sequences present in sequence data from clinical samples. It takes as input raw short-read genomic sequence data (in particular, the type generated by the Illumina sequencing platforms) and outputs taxonomic evaluation of detected microbes in various human-readable formats. This software was designed to assist in the diagnosis or characterization of infectious disease, by detecting pathogen sequences in nucleic acid sequence data from clinical samples. It has also been applied in the detection of algal pathogens, when algal biofuel ponds became unproductive. RAPTOR first trims and filters genomic sequence reads based on quality and related considerations, then performs a quick alignment to the human (or other host) genome to filter out host sequences, then performs a deeper search against microbial genomes. Alignment to a protein sequence database is optional. Alignment results are summarized and placed in a taxonomic framework using the Lowest Common Ancestor algorithm.", + "homepageURL": "http://bioinformatics.sandia.gov/software", + "laborHours": 0.0, + "name": "Rapid Threat Organism Recognition Pipeline", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://bioinformatics.sandia.gov/software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://bioinformatics.sandia.gov/software", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "NuMAD helps to enable efficient creation and use of high fidelity wind turbine blade models for structural and aerodynamic analysis. NuMAD is a GUI-based tool used to manage the specific geometry and materials inputs required to fully describe a wind turbine blade.", + "laborHours": 34321.6, + "languages": [ + "MATLAB", + "HTML" + ], + "name": "Numerical Manufacturing And Design tool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/NuMAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "graphMC consists of an implementation of a set of statistical tests that ensure that a Markov chain in the space of graphs has converged to its stationary distribution. The tests are applicable when the graphs have labelled nodes. The tests are applied to the binary time-series traced out by an edge between two selected nodes. The software fits models of a first-order Markov process and an independent draws from a binary distribution to the time-series and selects one based on the BIC scores of the two models. The package consists of (1) an implementation of a Markov chain driving a graph rewiring process that preserves the joint degree distribution of the graph, (2) implementation of the statistical test mentioned above and (3) two examples that show how the Markov chain infrastructure and the statistical tests can be used.", + "laborHours": 0.0, + "languages": [], + "name": "graphMC: A package for testing the independence of graphs", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/graphMC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "NetMOD is a tool to model the performance of global ground-based explosion monitoring systems. The initial version of the software supports the simulation of seismic detection capability. The tool provides a user interface to execute simulations based upon a hypothetical definition of the monitoring system configuration, geophysical properties of the Earth, and detection analysis criteria.", + "laborHours": 15.2, + "languages": [ + "Java" + ], + "name": "NetMOD", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/netmod", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software implements the generative graph algorithm described in the following reference: T. G. Kolda, A. Pinar, T. Plantenga and C. Seshadhri. A Scalable Generative Graph Model with Community Structure, arXiv:1302.6636, March 2013, http:l/arxiv.org/abs/1302.6636. The software also implements the clustering coefficient algorithms described in C. Seshadhri, A. Pinar and T. G. Kolda. Triadic Measures on Graphs: The Power of Wedge Sampling, in Proc. 2013 SIAM International Conference on Data Mining {SDM), May 2013.", + "laborHours": 0.0, + "languages": [], + "name": "FEASTPACK v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/feastpack", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Software to manipulate and describe crystal and molecular structures and set up structural refinements from multiple experimental inputs. Calculation and simulation of structure derived physical quantities. Library for creating customized refinements of atomic structures from available experimental and theoretical inputs.", + "homepageURL": "http://www.diffpy.org", + "laborHours": 0.0, + "name": "DiffPy-CMI-Python libraries for Complex Modeling Initiative", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.diffpy.org/products/diffpycmi/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.diffpy.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Polytope is a library that wraps several algorithms for generating the Voronoi diagram in both serial and distributed parallel.", + "homepageURL": "https://bitbucket.org/jjphatt/polytope", + "laborHours": 0.0, + "name": "Polytope", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/jjphatt/polytope/src/ef2ecd61b60b31a4b7ba95e88f893f2fd7382a80/LICENSE?at=default&fileviewer=file-view-default", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/jjphatt/polytope", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SolidSpheral is an extension of the Spheral open source meshless hydrodynamics method. SolidSpheral adds the capability to model solid materials using analytic equations of state, and a simple damage model to allow for the modeled materials to undergo dynamic damage evolution. SolidSpheral is a distributed parallel code employing MPI for the parallel framework.", + "homepageURL": "https://sourceforge.net/projects/spheral", + "laborHours": 0.0, + "name": "SolidShperal", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/spheral", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-01" + }, + "description": "The Toolkit for Adaptive Stochastic Modeling and Non-Intrusive ApproximatioN is a collection of robust libraries for high dimensional integration and interpolation as well as parameter calibration. The code consists of several modules that can be used individually or conjointly.", + "laborHours": 24624.0, + "languages": [], + "name": "Tasmanian", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/Tasmanian", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Code to support, enable, and expand monitoring of network devices, servers, and network services.", + "homepageURL": "http://mathias-kettner.de/checkmk.html", + "laborHours": 0.0, + "name": "check_mkcheck_mk (ORNL expansions)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://mathias-kettner.de/checkmk.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This package implements an optimal-scaling multigrid solver for the (non) linear systems that arise from the discretization of problems with evolutionary behavior. Typically, solution algorithms for evolution equations are based on a time-marching approach, solving sequentially for one time step after the other. Parallelism in these traditional time-integrarion techniques is limited to spatial parallelism. However, current trends in computer architectures are leading twards system with more, but not faster. processors. Therefore, faster compute speeds must come from greater parallelism. One approach to achieve parallelism in time is with multigrid, but extending classical multigrid methods for elliptic poerators to this setting is a significant achievement. In this software, we implement a non-intrusive, optimal-scaling time-parallel method based on multigrid reduction techniques. The examples in the package demonstrate optimality of our multigrid-reduction-in-time algorithm (MGRIT) for solving a variety of parabolic equations in two and three sparial dimensions. These examples can also be used to show that MGRIT can achieve significant speedup in comparison to sequential time marching on modern architectures.", + "homepageURL": "https://computation.llnl.gov/projects/parallel-time-integration-multigrid/software", + "laborHours": 0.0, + "name": "Parallel time integration software", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://computation.llnl.gov/projects/parallel-time-integration-multigrid/software", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "joiner@ameslab.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ThermoPhonon is a stand-alone code, which can be integrated into other software packages. Typically, it is used together with a density functional theory (DFT) code (such as VASP, Wien2k, AbInit, SIESTA) and a phonon code (such as Phonopy or Phon). The workflow is the following. Molecular dynamics (MD) in a supercell at a given temperature T is performed using another code. After sufficient equilibration, the output in the form of atomic positions and forces for a large number of selected MD steps is recorded into a file. If needed, one can modify this file by applying additional constraints, such as enforced crystal symmetry or subtracted motion of the center of mass. ThermoPhonon reads the file with atomic positions and forces and writes a new file with the force constants. Force constants can be used by another code (such as Phonopy or Phon) to produce phonon spectrum for plotting, in the assumption of known equilibrium atomic positions provided in a separate file.", + "homepageURL": "http://lib.dr.iastate.edu/ameslab_software/2", + "laborHours": 0.0, + "name": "ThermoPhonon", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://lib.dr.iastate.edu/ameslab_software/2", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "ForQint is a Fortran software library to adaptively integrate multivariable functions versus well known probability distributions (e.g. normal, lognormal, etc.) using quadrature rules. Such integration is known to be more efficient and accurate especially when the function evaluation is expensive. The library also FQint enables the creation of both full and sparse anisotropic multi-dimensional quadrature rules. These latter encompass different such as Gauss-Hermite, Gauss-Legendre, etc. The functions Maher Salloum, Bert Debusschere, Kenny Chowdhary and subroutines rely on the C++ Stokhos package of Trilinos (trilinos.sandia.gov) where the appropriate classes were wrapped into Fortran.", + "laborHours": 699.2, + "languages": [ + "Makefile", + "Fortran" + ], + "name": "ForQint", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ForQint", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The software is used to fit models of emission fields (e.g., fossil-fuel CO2 emissions) to sparse measurements of gaseous concentrations. Its primary aim is to provide an implementation and a demonstration for the algorithms and models developed in J. Ray, V. Yadav, A. M. Michalak, B. van Bloemen Waanders and S. A. McKenna, \"A multiresolution spatial parameterization for the estimation of fossil-fuel carbon dioxide emissions via atmospheric inversions\", accepted, Geoscientific Model Development, 2014. The software can be used to estimate emissions of non-reactive gases such as fossil-fuel CO2, methane etc. The software uses a proxy of the emission field being estimated (e.g., for fossil-fuel CO2, a population density map is a good proxy) to construct a wavelet model for the emission field. It then uses a shrinkage regression algorithm called Stagewise Orthogonal Matching Pursuit (StOMP) to fit the wavelet model to concentration measurements, using an atmospheric transport model to relate emission and concentration fields. Algorithmic novelties described in the paper above (1) ensure that the estimated emission fields are non-negative, (2) allow the use of guesses for emission fields to accelerate the estimation processes and (3) ensure that under/overestimates in the guesses do not skew the estimation.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "sparse-msrf:A package for sparse modeling and estimation of fossil-fuel CO2 emission fields", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sparse-msrf", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-19" + }, + "description": "Genomic islands are key mobile DNA elements in bacterial evolution, that can distinguish pathogenic strains from each other, or distinguish pathogenic strains from non-pathogenic strains. Their detection in genomes is a challenging problem. We present 3 main software components that attack the island detection problem on two different bases: 1) the preference of islands to insert in chromosomal tRNA or tmRNA genes (islander.pl), and 2) islands' sporadic occurrence among closely related strains. The latter principle is employed in both an algorithm (learnedPhyloblocks.pl) and a visualization method (panGenome.pl). Component islander.pl finds islands based on their preference for a particular target gene type. We annotate each tRNA and tmRNA gene, find fragments of each such gene as candidates for the distal ends of islands, and filter candidates to remove false positives. Component learnedPhyloblocks.pl uses islands found by islander.pl and other methods as a training set to find new islands. Reference genomes are aligned using mugsy, then the \"phylotypes\" or patterns of occurrence in the reference set are determined for each position in the target genome, and those phylotypes most enriched in the training set of islands are followed to detect yet more islands. Component panGenome.pl produces a big-data visualization of the chromosomally-ordered \"pan-genome\", that includes every gene of every reference genome (x-axis, pan-genome order; y-axis, reference genomes; color-coding, gene presence/absence etc.), islands appearing as dark patches.", + "laborHours": 18027.2, + "languages": [ + "Perl", + "C", + "Python" + ], + "name": "Genomic Island Identification Software v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TIGER", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "Matlab Toolbox for simulating the impact of solar energy on the distribution grid. The majority of the functions are useful for interfacing OpenDSS and MATLAB, and they are of generic use for commanding OpenDSS from MATLAB and retrieving GridPV Toolbox information from simulations. A set of functions is also included for modeling PV plant output and setting up the PV plant in the OpenDSS simulation. The toolbox contains functions for modeling the OpenDSS distribution feeder on satellite images with GPS coordinates. Finally, example simulations functions are included to show potential uses of the toolbox functions.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "OpenDSS" + ], + "name": "GridPV Toolbox", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gridpv", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The SPARTA package is software for simulating low-density fluids via the Direct Simulation Monte Carlo (DSMC) method, which is a particle-based method for tracking particle trajectories and collisions as a model of a multi-species gas. The main component of SPARTA is a simulation code which allows the user to specify a simulation domain, populate it with particles, embed triangulated surfaces as boundary conditions for the flow, overlay a grid for finding pairs of collision partners, and evolve the system in time via explicit timestepping. The package also includes various pre- and post-processing tools, useful for setting up simulations and analyzing the results. The simulation code runs either in serial on a single processor or desktop machine, or can be run in parallel using the MPI message-passing library, to enable faster performance on large problems.", + "laborHours": 267930.4, + "languages": [ + "C++", + "Shell", + "C", + "Roff", + "CMake", + "Python" + ], + "name": "Stochastic PArallel Rarefied-gas Time-accurate Analyzer", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sparta/sparta", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Performs a cross-correlation calculation to align images. This is particularly useful for aligning frames of a movie so that an object of interest does not spatially drift. For in situ microscopy experiments. Movies are collected where an object changes with time. At the same time, the object usually drifts too. This shifts the movie frames so that the object is aligned from frame to frame. Then it is easy to see the object changes without the added complication of it moving too.", + "homepageURL": "http://freesourcecode.net/matlabprojects/57416/drifty-shifty-deluxe-in-matlab#.Wczt52hyKUk", + "laborHours": 0.0, + "name": "Drifty shifty deluxe.m", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://freesourcecode.net/matlabprojects/57416/drifty-shifty-deluxe-in-matlab#.Wczt52hyKUk", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MGPT is an unclassified source code for the fast evaluation and application of quantum-based MGPT interatomic potentials for mrtals. The present version of MGPT has been developed entirely at LLNL, but is specifically designed for implementation in the open-source molecular0dynamics code LAMMPS maintained by Sandia National Laboratories. Using MGPT in LAMMPS, with separate input potential data, one can perform large-scale atomistic simulations of the structural, thermodynamic, defeat and mechanical properties of transition metals with quantum-mechanical realism.", + "homepageURL": "http://lammps.sandia.gov/download.html", + "laborHours": 0.0, + "name": "Fast Model Generalized Pseudopotential Theory Interatomic Potential Routine", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://lammps.sandia.gov/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "joiner@ameslab.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HostDesigner is a computer-aided molecular design code that enables the general application of de novo structure-based methods to problems in chemistry and material science. Its purpose is to identify organic molecules with 3D structures that match user-input specifications. To accomplish this, the code connects chemical fragments to build millions of potential molecules, evaluates the resulting structures based on geometric constraints, and outputs a rank-ordered list of candidates. Example applications include the design of metal ion sequestering agents for use in separations processes, molecules that form self-assembled nanoscale containers, and molecular building blocks for metal-organic frameworks.", + "homepageURL": "http://sourceforge.net/projects/hostdesigner-v3-0", + "laborHours": 0.0, + "name": "HostDesigner, Version 3", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://sourceforge.net/projects/hostdesigner-v3-0", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "This software generates environmental contours of extreme sea states using buoy observations of significant wave height and energy period or peak period. The code transforms these observations using principal component analysis (PCA) to create an uncorrelated representation of the data. The subsequent components are modeled using probability distributions and parameter fitting functions. The inverse first-order reliability method (I-FORM) is then applied to these models in order to generate an extreme event contour based on a given return period (i.e., 100 years).The subsequent contour is then transformed back into the original input space defined by the variables of interest in order to create an environmental contour of extreme sea states.", + "laborHours": 197.6, + "languages": [ + "MATLAB" + ], + "name": "Extreme_SeaState_Contour_v1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SNL-ESSC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "creinke@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-01-18" + }, + "description": "LuaCLRBridge is a library which provides an interface for hosting Lua within .NET applications and facilitating interoperability between the two runtimes.", + "homepageURL": "https://bitbucket.org/luaclrbridge/luaclrbridge/src", + "laborHours": 20748.0, + "languages": [ + "C#", + "C++/CLI" + ], + "name": "Lua-CLR Bridge", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/luaclrbridge/luaclrbridge/src", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Geospatial Toolkit is an NREL-developed map-based software application that integrates resource data and other geographic information systems (GIS) data for integrated resource assessment. The non-resource, country-specific data for each toolkit comes from a variety of agencies within each country as well as from global datasets. Originally developed in 2005, the Geospatial Toolkit was completely redesigned and re-released in November 2010 to provide a more modern, easier-to-use interface with considerably faster analytical querying capabilities. The revised version of the Geospatial Toolkit has been released for all original toolkit countries/regions and each software package is made available on NREL's website,", + "homepageURL": "http://www.nrel.gov/international/geospatial_toolkits.html", + "laborHours": 281245.6, + "name": "Geospatial Toolkit", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.nrel.gov/international/geospatial_toolkits.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This software contains a set of python modules \u2013 input, search, cluster, analysis; these modules read input files containing spatial coordinates and associated attributes which can be used to perform nearest neighbor search (spatial indexing via kdtree), cluster analysis/identification, and calculation of spatial statistics for analysis.", + "homepageURL": "http://spparks.sandia.gov", + "laborHours": 0.0, + "name": "cluster trials v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://spparks.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "Sandia SPT is designed as software to accompany a book chapter being published a methods chapter which provides an introduction on how to label and track individual proteins. The Sandia Simple Particle Tracking code uses techniques common to the image processing community, where its value is that it facilitates implementing the methods described in the book chapter by providing the necessary open-source code. The code performs single particle spot detection (or segmentation and localization) followed by tracking (or connecting the detected particles into trajectories). The book chapter, which along with the headers in each file, constitutes the documentation for the code is: Anthony, S.M.; Carroll-Portillo, A.; Timlon, J.A., Dynamics and Interactions of Individual Proteins in the Membrane of Living Cells. In Anup K. Singh (Ed.) Single Cell Protein Analysis Methods in Molecular Biology. Springer", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Sandia Simple Particle Tracking (Sandia SPT) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The SDET Tool is used to create open-access power grid data sets and facilitate updates of these data sets by the community. Pacific Northwest National Laboratory (PNNL) and its power industry and software vendor partners are developing an innovative sustainable data evolution technology (SDET) to create open-access power grid datasets and facilitate updates to these datasets by the power grid community. The objective is to make this a sustained effort within and beyond the ARPA-E GRID DATA program so that the datasets can evolve over time and meet the current and future needs for power grid optimization and potentially other applications in power grid operation and planning.", + "homepageURL": "https://egriddata.org/dataset/sdet-tool", + "laborHours": 0.0, + "name": "Sustainable Data Evolution Technology for Power Grid Optimization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://egriddata.org/dataset/sdet-tool", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://egriddata.org/dataset/sdet-tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "Socorro can be used to compute the ground-state electron density for a periodically repeated simulation cell in which the external potential is obtained from norm-conserving pseudopotentials or projector-augmented-wave functions. The ground-state electron density is computed by summation over one-electron orbitals which are obtained using the Kohn-Sham formulation of density-functional theory and which are expanded in a plane-wave basis. Various quantities can be computed from the ground-state solution, including atomic forces which can be used to optimize atom positions in the simulation cell and to perform molecular dynamics simulations.", + "laborHours": 0.0, + "languages": [ + "C", + "Fortran" + ], + "name": "Socorro Electronic Structure Software", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/socorro", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A set of programs and utilities for generating and manipulating data files in TSV (tab-separated value) or JSON format.", + "laborHours": 8755.2, + "name": "db, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl-chash/db/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-chash/db", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Computing a Voronoi or Delaunay tessellation from a set of points is a core part of the analysis of many simulated and measured datasets. As the scale of simulations and observations surpasses billions of particles, a distributed-memory scalable parallel algorithm is the only feasible approach. The primary contribution of this software is a distributed-memory parallel Delaunay and Voronoi tessellation algorithm based on existing serial computational geometry libraries that automatically determines which neighbor points need to be exchanged among the subdomains of a spatial decomposition. Other contributions include the addition of periodic and wall boundary conditions.", + "laborHours": 5502.4, + "name": "TESS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/diatomic/tess2", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Ravel is a tool for analyzing and visualizing parallel execution traces. It deduces a logical structure of parallel program events from the trace records and calculates comparative metrics. It displays the results of this analysis using multiple views at varying levels of detail to allow interactive exploration of the trace.", + "laborHours": 12555.2, + "name": "Ravel", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/scalability-llnl/Ravel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-07" + }, + "description": "PIKA is a MOOSE-based application for modeling micro-structure evolution of seasonal snow. The model will be useful for environmental, atmospheric, and climate scientists. Possible applications include application to energy balance models, ice sheet modeling, and avalanche forecasting. The model implements physics from published, peer-reviewed articles. The main purpose is to foster university and laboratory collaboration to build a larger multi-scale snow model using MOOSE. The main feature of the code is that it is implemented using the MOOSE framework, thus making features such as multiphysics coupling, adaptive mesh refinement, and parallel scalability native to the application. PIKA implements three equations: the phase-field equation for tracking the evolution of the ice-air interface within seasonal snow at the grain-scale; the heat equation for computing the temperature of both the ice and air within the snow; and the mass transport equation for monitoring the diffusion of water vapor in the pore space of the snow.", + "laborHours": 6840.0, + "languages": [], + "name": "Snow Micro-Structure Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/pika", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Lestre performs a high-speed scan of the Lustre metadata target, and provides a listing of files that match a user-specified criteria, such as modification time, inode number, or if its data resides on specific OSTs. The output format is configurable, as is the parameters it uses to perform IO.", + "laborHours": 2492.8, + "name": "Lester, the Lustre Lister", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-TechInt/lester", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This site allows state data contributors to validate their WFS services against a specified schema for tier 3 data. The application uses the USGIN models API at https://github.com/usgin/usginmodels.", + "laborHours": 4636.0, + "name": "Web Feature Service Validator", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/ContentModelCMS/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/ContentModelCMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Django site used to manage the approved information exchanges (content models) after creation and public comment at https://github.com/usgin-models.", + "laborHours": 14394.4, + "name": "Information Exchange management site", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/modelmanager", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "THE NGDS IS A USER-FRIENDLY, WEB-BASED APPLICATION TO SUPPORT FINDING, VISUALIZING, MAPPING, AND ACQUISITION OF DATA BY END-USERS. THIS APPLICATION ALLOWS USERS TO DISCOVER AND ACCESS RESOURCES MADE AVAILABLE ACROSS ALL NGDS NODES, AND TO SEARCH FOR DATA ACROSS THE SYSTEM BASED ON TOPIC, LOCATION, AND OR OTHER CRITERIA. STANDARDIZED METADATA DESCRIBING EACH DATASET PROVIDES THE USER WITH THE INFORMATION NECESSARY TO DETERMINE THE UTILITY OF THAT DATASET FOR THEIR PURPOSES. GEOGRAPHIC DATASETS CAN BE VISUALIZED THROUGH A MAP INTERFACE THAT ALLOWS USERS TO INSPECT THE DETAILS OF INDIVIDUAL DATA POINTS (E.G. WELLS, TEMPERATURE MEASUREMENTS, ETC.) FROM PROPERLY FORMATTED DATASETS. IN ADDITION TO VISUALIZATION WITHIN THE APPLICATION, THE INTERFACE PROVIDES THE INFORMATION NECESSARY FOR USERS TO ACCESS THE DATA FROM OTHER APPLICATIONS.", + "laborHours": 8816.0, + "name": "National Geothermal Database", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ngds/documents", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Django app for converting CSV records to XML metadata documents. This transformation from the metadata content model to parsed ISO XML documents allows for metadata integration into NGDS.", + "laborHours": 45.6, + "name": "CSV to ISO XML metadata transformation tool", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/usgincsv/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/usgincsv", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Not Specified", + "laborHours": 87278.4, + "name": "CASTRO", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/AMReX-Astro/Castro/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Astro/Castro", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-07-13" + }, + "description": "KINSOL is part of a software family called SUNDIALS: SUite of Nonlinear and Differential/Algebraic equation Solvers [1]. KINSOL is a general-purpose nonlinear system solver based on Newton-Krylov and fixed-point solver technologies [2].", + "laborHours": 213088.8, + "languages": [], + "name": "General purpose nonlinear system solver based on Newton-Krylov method", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Avalaunch implements a tree-based process launcher. It first bootstraps itself on to a set of compute nodes by launching children processes, which immediately connect back to the parent process to acquire info needed t launch their own children. Once the tree is established, user processes are started by broadcasting commands and application binaries through the tree. All communication flows over high-performance network protocols via spawnnet. The goal is to start MPI jobs having hundreds of thousands of processes within seconds.", + "laborHours": 21371.2, + "name": "Avalaunch", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/avalaunch/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/avalaunch", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The av_sys_image_mgr utility provides an interface for the creation, manipulation, and analysis of system boot images for computer systems. It is primarily intended to provide a convenient method for managing the introduction of changes to boot images for long-lived production HPC systems.", + "laborHours": 60.8, + "name": "Auto-Versioning Systems Image Manager", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NERSC/avs_image_mgr/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/avs_image_mgr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Enables UNIX and Mac OS X command line users to put (individually or batch mode) local ascii files into Google Documents, where the ascii is converted to Google Document format using formatting the user can specify.", + "laborHours": 425.6, + "name": "ascii2gdocs", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/stefanlasiewski/ascii2gdocs/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stefanlasiewski/ascii2gdocs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Atmospheric Radiation Measurement (ARM) Data Integrator (ADI) streamlines the development of scientific algorithms and analysis of time-series NetCDF data, and improves the content and consistency of the output data products produced by these algorithms. The framework automates the process of retrieving and preparing data for analysis, and allows users to design output data products through a graphical interface. It also provides a modular, flexible software development architecture that scientists can use to generate C, Python, and IDL source code templates that embed the pre and post processing logic allowing the scientist to focus on only their science. The input data, preprocessing, and output data specifications of algorithms are defined through a graphical interface and stored in a database. ADI implements workflow for data integration and supports user access to data through a library of software modules. Data preprocess capabilities supported include automated retrieval of data from input files, merging the retrieved data into appropriately sized chunks, and transformation of the data onto a common coordinate system grid. Through the graphical interface, users can view the details of both their data products and those in the ARM catalog and allows developers to use existing data product to build new data products. Views of the output data products include an overlay of how the design meets ARM archive's data standards providing the user with a visual cue indicating where their output violates an archive standard. The ADI libraries access the information provided through the GUI via a Postgres database. The ADI framework and its supporting components can significantly decrease the time and cost of implementing scientific algorithms while improving the ability of scientists to disseminate their results.", + "laborHours": 76.0, + "name": "ARM Data Integrator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ARM-DOE/ADI/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/ADI", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Physical device safety is typically implemented locally using embedded controllers, while operations safety is primarily performed in control centers. Safe operations can be enhanced by correct design of device-level control algorithms, and protocols, procedures and operator training at the control-room level, but all can fail. Moreover, these elements exchange data and issue commands via vulnerable communication layers. In order to secure these gaps and enhance operational safety, we believe monitoring of command sequences must be combined with an awareness of physical device limitations and automata models that capture safety mechanisms. One way of doing this is by leveraging specification-based intrusion detection to monitor for physical constraint violations. The method can also verify that physical infrastructure state is consistent with monitoring information and control commands exchanged between field devices and control centers. This additional security layer enhances protection from both outsider attacks and insider mistakes. We implemented specification-based SCADA command analyzers using physical constraint algorithms directly in the Bro framework and Broccoli APIs for three separate scenarios: a water heater, an automated distribution system, and an over-current protection scheme. To accomplish this, we added low-level analyzers capable of examining control system-specific protocol packets for both Modbus TCP and DNP3, and also higher-level analyzers able to interpret device command and data streams within the context of each device's physical capabilities and present operational state. Thus the software that we are making available includes the Bro/Broccoli scripts for these three scenarios, as well as simulators, written in C, of those scenarios that generate sample traffic that is monitored by the Bro/Broccoli scripts. In addition, we have also implemented systems to directly pull cyber-physical information from the OSIsoft PI historian system. We have included the Python scripts used to perform that monitoring.", + "laborHours": 43487.2, + "name": "HC-NIDS: signatures and simulations for detecting cyber-attacks aiming to cause damage against cyber-physical energy systems", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lbnl-cybersecurity/LBNL_Physics_Based_IDS/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/LBNL_Physics_Based_IDS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "IceNine is a MPI-parallel orientation reconstruction and microstructure analysis code. It's primary purpose is to reconstruct a spatially resolved orientation map given a set of diffraction images from a high energy x-ray diffraction microscopy (HEDM) experiment (1). In particular, IceNine implements the adaptive version of the forward modeling method (2, 3). Part of IceNine is a library used to for conbined analysis of the microstructure with the experimentally measured diffraction signal. The libraries is also designed for tapid prototyping of new reconstruction and analysis algorithms. IceNine is also built with a simulator of diffraction images with an input microstructure.", + "laborHours": 20778.4, + "name": "Adaptive Forward Modeling Method for Analysis and Reconstructions of Orientation Image Map", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/FrankieLi/IceNine/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FrankieLi/IceNine", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Coopr integrates Python packages for defining optimizers, modeling optimization applications, and managing computational experiments. A major driver for Coopr development is the Pyomo package that can be used to define abstract problems, create concrete problem instances, and solve these instances with standard solvers. Other Coopr packages include EXACT, a framework for managing computational experiments, SUCASA, a tool for customizing integer programming solvers, and OPT, a generic optimization interface.", + "laborHours": 314837.6, + "name": "COOPR: A COmmon Optimization Python Repository v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pyomo/pyomo", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "BECCA is a learning and control method based on the function of the human brain. The goal behind its creation is to learn to control robots in unfamiliar environments in a way that is very robust, similar to the way that an infant learns to interact with her environment by trial and error. As of this release, this software contains an application for controlling robot hardware through a socket. The code was created so as to make it extensible to new applications. It is modular, object-oriented code in which the portions of the code that are specific to one robot are easily separable from those portions that are the constant between implementations. BECCA makes very few assumptions about the robot and environment it is learning, and so is applicable to a wide range of learning and control problems.", + "laborHours": 927.2, + "languages": [ + "Python" + ], + "name": "Brain-Emulating Cognition and Control Architecture (BECCA) v. 0.2 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/becca", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2" + }, + { + "contact": { + "email": "westm@osti.gov" + }, + "date": { + "created": "2017-10-31", + "metadataLastUpdated": "2019-08-09" + }, + "description": "Main repo for managing the new DOE CODE site from the DOE Office of Scientific and Technical Information (OSTI).", + "laborHours": 2219.2, + "languages": [], + "name": "DOE CODE", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/doecode/doecode", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-11-08", + "metadataLastUpdated": "2023-08-14" + }, + "description": "bifacial_radiance contains a series of Python wrapper functions to make working with RADIANCE easier, particularly for the PV researcher interested in bifacial PV performance. Users can configure site details such as latitude / longitude, and ground albedo. A bifacial PV system is created with a number of PV modules in rows. The user can specify ground clearance height, row spacing, tilt and azimuth angle, etc. The scene is created, and annual or hourly irradiance profiles are applied to identify the rear irradiance fraction for a given condition.", + "laborHours": 13528.0, + "languages": [ + "Python" + ], + "name": "Bifacial_Radiance [SWR-18-03]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bifacial_radiance", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "billingsjj@ornl.gov" + }, + "date": { + "created": "2017-11-15", + "metadataLastUpdated": "2017-11-15" + }, + "description": "Ice Project Main repo", + "laborHours": 92902.4, + "name": "eclipse/ice", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eclipse/ice", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "billingsjj@ornl.gov" + }, + "date": { + "created": "2017-11-15", + "metadataLastUpdated": "2017-12-19" + }, + "description": "Eclipse advanced visualization project", + "laborHours": 40052.0, + "name": "eclipse/eavp", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eclipse/eavp", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "watsongr@ornl.gov" + }, + "date": { + "created": "2017-11-15", + "metadataLastUpdated": "2020-08-12" + }, + "description": "The PTP project provides an integrated development environment to support the development of parallel applications written in C, C++, and Fortran. This include support for the MPI, OpenMP and UPC programming models, as well as OpenSHMEM and OpenACC, support for a wide range of batch systems and runtime systems, including PBS/Torque, LoadLeveler, GridEngine, Parallel Environment, Open MPI, and MPICH2. A scalable parallel debugger and support for the integration of a wide range of parallel tools is also included.", + "homepageURL": "https://git.eclipse.org/c/ptp/org.eclipse.ptp.git", + "laborHours": 548841.6, + "languages": [], + "name": "Eclipse Parallel Tools Platform", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.eclipse.org/c/ptp/org.eclipse.ptp.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-11-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software is a plugin/installer for existing software. Composer (https://getcomposer.org) is a dependency manager for\nPHP. Installer plugins can be created through Composer's plugin API (https://getcomposer.org/doc/articles/custominstallers.\nmd) allowing certain types of packages to be automatically installed to specific paths. Plugins like this exist for\nseveral different frameworks: https://packagist.org/search/?q=installer&type=composer-plugin\nThis software is a plugin to install Drupal modules (https://www.drupal.org/). Drupal has begun supporting Composer as a means of installing and maintaining modules, but requires specific paths for it's various components. These paths can be\nmanually specified in the \"composer.json\" file, or can be automatically determined with a plugin. Currently an installer\nplugin does not exist for Drupal.", + "laborHours": 273.6, + "languages": [], + "name": "Drupal Installer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/drupal-installer", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-11-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A collection of R packages for statistical computing and analysis", + "laborHours": 7645.6, + "languages": [], + "name": "lhsego/sUtils", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lhsego/sUtils", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-11-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Asset Score Preview API Test Harness is PHP code that will be made publicly accessible to software developers\nsupporting the DOE commercial energy scoring efforts. Asset Score is a DOE funded web-based application that enables cities to interactively describe commercial buildings, identify assets that would affect the energy footprint of the building, and use the Asset Score models (FEDS, Open Studio) to determine the approximate energy score.", + "homepageURL": "https://buildingenergyscore.energy.gov", + "laborHours": 0.0, + "languages": [], + "name": "Asset Score API", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://buildingenergyscore.energy.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-11-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The ISDDD software program simulates a mathematical model, named ISD3 (\"ISDDD\"), developed for describing the time-, concentration- and particle size- dependent dissolution of particles, their delivery to cells, and the delivery and uptake of ions to cells in in vitro liquid test systems. The model is based on a specific formulation of the Population Balance Equation, derived for soluble particles. ISD3 solves for the size and spatial distribution of particle numbers, represented together as a particle number density (that is a function of particle location and diameter). From the number density, all other quantities, such as mass, concentration, size distribution and surface areas are derived. The model can be applied for any initial particle size distribution data by representing the data in terms of the number density. As a result, time dependent solutions can be obtained for all size ranges in a single run of the ISD3 simulation for a given particle type and\nmedia conditions. In the current implementation, particles are treated as spherical in shape and can be modeled as primary particles, agglomerates, or as primary particles coated with proteins. Ions are modeled as a lumped system with a uniform concentration in the liquid media. Particle transport is assumed to occur down the liquid column via diffusion and sedimentation (no fluid convection), and no aggregation/agglomeration, coagulation and break-up of the particles occur during transport. Cellular uptake kinetics of ions and particle dissolution kinetics are currently implemented using empirical models that were developed and calibrated for silver nanoparticles and ions. The ISD3 code is modular, allowing use of the existing equations for the dissolution model and ion uptake, but can be modified to include alternate models developed by the user. Application of ISD3 to another particle system would involve inputting parameters appropriate for the particles and model system. For particle uptake by cells, users have the option to use a no-flux or a perfectly absorbing \u2018sticky\u2019 boundary condition. For reactive boundary conditions, the user needs to modify a few lines of the code to express the desired form of the boundary condition (e.g., Robin type of boundary condition).", + "homepageURL": "http://nanodose.pnnl.gov/ModelDownload.aspx", + "laborHours": 0.0, + "languages": [], + "name": "ISDDD", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://nanodose.pnnl.gov/ModelDownload.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2017-12-11", + "metadataLastUpdated": "2018-01-10" + }, + "description": "As supercomputing resources increase, cosmological scientists are able to run more detailed and larger simulations generating massive amounts of data. Analyzing these simulations with an available open-source toolkit is important for collaborative Department of Energy scientific discovery across labs, universities, and other partners. Developed software as a part of this collection include: comparing data with other existing simulations, verifying and validating results with observation databases, new halo finder algorithms, and using analytical tools to get insights into the physics of the\ncosmological universe. The goal of this software project is to provide a set of open-source libraries, tools, and packages for large-scale cosmology that allows scientists to visualize, analyze, and compare large-scale simulation and observational\ndata sets. Developed software will provide a variety of methods for processing, visualization, and analysis of astronomical observation and cosmological simulation data. These tools are intended for deployment on multiple scientific computing\nplatforms, including but not limited to personal computers, cloud computing, experimental sites (telescopes) and high performance supercomputers.", + "laborHours": 101308.0, + "name": "Framework for Analysis and Visualization of Simulation Data (VizAly)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/VizAly", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-12-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "VOLTTRON Application tree (moved from volttron/applications)\nAutomated Identification of Re-tuning Measures", + "laborHours": 109880.8, + "languages": [], + "name": "VOLTTRON/volttron-applications", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron-applications", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-12-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Some of the most pressing machine learning applications such as cyber security and object recognition lack enough ground-truth training data to build a classifier. We solve this problem by using unsupervised deep learning techniques to determine when data were anomalous or deviated from the norm. Traditional methods require either specific context dependent expertise to construct models, or prior examples of events and large amounts of well-labeled data to perform machine learning. Some cutting-edge deep learning approaches have been used to characterize complex events, but these have not been applied to the streaming environment and require a great deal of data. We demonstrated the use of an autoencoder and relevant featurization techniques to both learn a feature space and then identify anomalous portions without the aid of labeled data or domain knowledge. In this way, we demonstrated the detection of anomalous features without domain knowledge or tagged examples, and delivered these features to users.", + "laborHours": 40371.2, + "languages": [], + "name": "pnnl/safekit", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/safekit", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-12-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ModME is a generalization and benchmark framework for the notion of semantic importance. It is primarily used in a stream reasoning context, where hidden information can be extracted out of the data streams.", + "laborHours": 18331.2, + "languages": [], + "name": "ModME", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/modme", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2017-12-13", + "metadataLastUpdated": "2018-05-02" + }, + "description": "CodeVision (formerly MassAV) is a malware analysis workflow system and repository. It began as a simple tool for analyzing a large malware corpus using multiple COTS antivirus engines in parallel. It has since evolved into a unified interface for collecting, storing and analyzing malicious executable code using a variety of COTS and GOTS backends. Not only can CodeVision receive samples from users via its command-line and web interfaces, but it can also operate on continuous network data feeds (e.g., perimeter e-mail attachments, HTTP downloads). The modular analysis framework and simple API give developers the ability to integrate custom and off-the-shelf analysis tools with ease. The system manages scheduling and dependencies, allowing modules to be chained together into analysis-driven workflows. The system is designed as a distributed, load-balanced web service, an architecture that allows it to scale horizontally by adding additional nodes.", + "homepageURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 7676.0, + "name": "Codevision 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-12-19", + "metadataLastUpdated": "2018-01-19" + }, + "description": "ScaLAPACK is a library of high-performance linear algebra routines for parallel distributed memory machines. ScaLAPACK solves dense and banded linear systems, least squares problems, eigenvalue problems, and singular value problems.", + "homepageURL": "http://www.netlib.org/scalapack", + "laborHours": 0.0, + "name": "ScaLAPACK - Scalable Linear Algebra PACKage", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.netlib.org/scalapack/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.netlib.org/scalapack", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-12-19", + "metadataLastUpdated": "2018-07-13" + }, + "description": "Chombo provides a set of tools for implementing finite difference and finite volume methods for the solution of partial differential equations on block-structured adaptively refined rectangular grids. Both elliptic and time-dependent modules are included. Chombo supports calculations in complex geometries with both embedded boundaries and mapped grids, and Chombo also supports particle methods. Most parallel platforms are supported, and cross-platform self-describing file formats are included.\n\nThe Chombo package is a product of the community of collaborators working with the Applied Numerical Algorithms Group part of the Computational Research Division at LBNL.\n\nChombo is a Swahili word meaning \"tool\" or \"container\".", + "homepageURL": "https://commons.lbl.gov/display/chombo/Chombo+-+Software+for+Adaptive+Solutions+of+Partial+Differential+Equations", + "laborHours": 0.0, + "languages": [], + "name": "Chombo", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://commons.lbl.gov/display/chombo/Chombo+copyright", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://commons.lbl.gov/display/chombo/Chombo+-+Software+for+Adaptive+Solutions+of+Partial+Differential+Equations", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "accawigk@ornl.gov" + }, + "date": { + "created": "2017-12-21", + "metadataLastUpdated": "2025-02-10" + }, + "description": "MEASUR-Tools-Suite is an energy efficiency calculation library in C++ with WebAssembly (WASM) for the Department of Energy Advanced Manufacturing and Materials Technologies Office and the Industrial Efficiency & Decarbonization Office (DOE AMMTO IEDO) Desktop, also known as MEASUR.", + "laborHours": 165695.2, + "languages": [ + "C++" + ], + "name": "MEASUR Tools Suite", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-AMO/MEASUR-Tools-Suite/blob/develop/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-AMO/MEASUR-Tools-Suite", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.8" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-01-09", + "metadataLastUpdated": "2018-01-10" + }, + "description": "REDUCE is a software toolset enabling cyber security analysts to rapidly discover relationships between malware samples, to extract temporal threat intelligence, and to develop actionable signatures for known and emerging threats. REDUCE performs automated static code analysis and identifies similarities between malware samples in order to support knowledge sharing about related pieces of malware. By integrating with well-established reverse engineering tools, REDUCE speeds up both deep-dive reverse engineering efforts and custom signature generation.", + "homepageURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "name": "REDUCE: Statistically-Guided Reverse Engineering Toolkit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-01-15", + "metadataLastUpdated": "2018-01-16" + }, + "description": "The converter extracts all the required feeder data information from \u201cOpendss format\u201d files also known as \u201c.dss\u201d files to construct the feeder data spreadsheets to be interfaced with the \u201cePHASORSIM\u201d simulator.", + "laborHours": 8664.0, + "name": "DSS2ePHASOR (\"OpenDSS\" files to \"ePHASORSIM\" interface files converter)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/DSS2ePHASOR/blob/master/README.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DSS2ePHASOR", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2018-01-23", + "metadataLastUpdated": "2019-07-30" + }, + "description": "PIVAuth provides a key based OpenSSH authentication method for use with SmartCards, HSPD-12, PIV, CAC, and similar credentials that support PKCS11. PIVAuth validates the x509 client certificate chain of trust and revocation status on each authenticiation attempt before converting he certificate into a format that Open SSH can make use of. PIVAuth makes use of Bash shell code andi ndustry standard utilities like OpenSSL and OpenLDAP/ It aims to be audit friendly, and easily understood by any Linux administrator.", + "laborHours": 167.2, + "languages": [], + "name": "PIVAuth", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bensallen/pivauth", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jbbrown@lbl.gov" + }, + "date": { + "created": "2018-01-23", + "metadataLastUpdated": "2018-01-24" + }, + "description": "pbdR-enabled HPC-compatible implementation of iRF. Tested on Titan.", + "laborHours": 5122.4, + "name": "Jromero1208/PBDRiRF", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Jromero1208/PBDRiRF", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-01-25", + "metadataLastUpdated": "2018-01-26" + }, + "description": "Swiftbat is a set of Python library routines and command-line utilities that have been developed for the purpose of retrieving, analyzing, and displaying data from NASA's Swift spacecraft, especially the data from the Swift Burst Alert Telescope (BAT).", + "laborHours": 744.8, + "name": "Swiftbat Python Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/swiftbat_python", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-01-26", + "metadataLastUpdated": "2018-01-26" + }, + "description": "We developed a grid reference system-based Unique Building Identifier (UBID). The method converts a building footprint on a map to a unique code. Unlike geographic coordinates (latitude and longitude), which require high precision and can only locate points on the earth, the UBID code records two-dimensional information about a building footprint in a concise and practical manner. The UBID itself is neither a database nor a data schema. Rather, it acts as an external common key between databases to facilitate data mapping. The developed ruleset ensures that individual implementers can reach the same conclusion utilizing publicly available digital maps. It can also automatically resolve discrepancies, caused by physical space or structure changes over time, during data exchange. The method is also flexible and scalable to identify a portion of a building or a group of buildings.", + "laborHours": 440.8, + "name": "Unique Building Identifier Generator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-01-29", + "metadataLastUpdated": "2018-01-29" + }, + "description": "The Fast Equilibration of Ocean Tracers Software (FEOTS) is a set of Fortran modules and programs for post-processing output from LANL's Parallel Ocean Program (POP). However, it is written so that it can be extended for use with other General Circulation Models. Tools are provided for aiding in the diagnosis of sparse matrices that capture advection and diffusion operators that are consistent with General Circulation Model discretizations. FEOTS additionally offers tools to make use of the diagnosed operators to run offline tracer models in forward or equilibration modes.", + "laborHours": 4119.2, + "name": "Fast Equilibration of Ocean Tracers Software", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/FEOTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-01-29", + "metadataLastUpdated": "2018-01-29" + }, + "description": "Software programs Red Pitaya to sweep frequency and records the in phase and quadrature response.", + "laborHours": 1489.6, + "name": "Resonant Ultrasound Spectroscopy Software", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ffb-LANL/resonant-ultrasound", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-01-29", + "metadataLastUpdated": "2018-01-29" + }, + "description": "RuleBuilder is a tool for drawing graphs represented by the BioNetGen rule-based modeling language (BNGL), a domain-specific language used to formulate mathematical models of biochemical interaction networks. This framework provides an intuitive plain-text representation of such networks using a graph-based formalism. The interactions between the model's components are graph-rewriting rules that denote the minimum context needed for the interaction to occur. In some cases the context required for reactions to occur can grow quite large, and the lengthy textual description of the interaction can be difficult to interpret or debug. RuleBuilder is designed to make this process simpler through visualization of individual rule or pattern strings. The software assists in the reading of existing models by converting the BNGL strings of interest into a graph-based representation composed of nodes and edges. RuleBuilder also enables the user to build the visual representation directly from its interface, composing the BNGL string as components and operators are added to the graphical object.", + "laborHours": 1368.0, + "name": "RuleBuilder", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/RuleWorld/RuleBuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "darve@stanford.edu" + }, + "date": { + "created": "2018-01-31", + "metadataLastUpdated": "2018-01-31" + }, + "description": "The regular weighted ensemble method simulation Python code was originally developed by H. Lee, Stanford. The bash \nscript for multiple simultaneous simulations was originally developed by S. Ahn, Stanford. The resampling method \nimplemented in the code is from E. Darve and J. Izaguirre (Chapter 7 in Schlick's \"Innovations in Biomolecular Modeling \nand Simulations.\"). The Concurrent Adaptive Sampling (CAS) algorithm Python code was developed on top of the regular \nweighted ensemble method code by S. Ahn, Stanford. Improvements on the parameter input file had been made by J. \nBirgmeier, Stanford.\n\nThere are two folders provided in this Github repository: **2D_Toy_Model_Code** and **MD_Code**. Each folder provides \nall of the needed code with input files for a particular example, e.g., toymodel1, toymodel2, and penta-alanine. In the \n2D_Toy_Model_Code, **Code_With_Proper_Files** will make a separate folder with many output files for each walker and\n**Code_Without_Proper_Files** will only output minimum number of files like flux.txt, total_weight_on_each_ball.txt, \ntotal_weight.txt, time_record.txt, etc.", + "laborHours": 2523.2, + "name": "CAS_Code", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/shirleyahn/CAS_Code", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "radercd@ornl.gov" + }, + "date": { + "created": "2018-02-01", + "metadataLastUpdated": "2020-09-24" + }, + "description": "Thermochimica is a software library that determines a unique combination of phases and their compositions at thermochemical equilibrium. Thermochimica can be used for stand-alone calculations or it can be directly coupled to other codes. This release of the software does not have a graphical user interface (GUI) and it can be executed from the command line or from an Application Programming Interface (API). Also, it is not intended for thermodynamic model development or for constructing phase diagrams. The main purpose of the software is to be directly coupled with a multi-physics code to provide material properties and boundary conditions for various physical phenomena. Significant research efforts have been dedicated to enhance computational performance through advanced algorithm development, such as improved estimation techniques and non-linear solvers. Various useful parameters can be provided as output from Thermochimica, such as: determination of which phases are stable at equilibrium, the mass of solution species and phases at equilibrium, mole fractions of solution phase constituents, thermochemical activities (which are related to partial pressures for gaseous species), chemical potentials of solution species and phases, and integral Gibbs energy (referenced relative to standard state). 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It acts as a channel access client, much like pyepics. The intention of the module is to provide better performance for embedded applications, rather than to provide an interactive interface. The most significant gains will be found when monitoring large waveforms that need to be processed before exposing them the Python layer.", + "laborHours": 2021.6, + "name": "pyca", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pyca/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pyca", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Python-based Channel Access Websockets Server. This is a tiny web server for getting channel access data via a WebSockets connection. Useful if you want to make a website that displays a real-time updating value of some PVs. Built with Bottle, PyEpics, and Geventwebsockets.", + "laborHours": 60.8, + "name": "pycaserver", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pycaserver", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "pydm is a PyQt-based framework for building user interfaces for control systems. The goal is to provide a no-code, drag-and-drop system to make simple screens, as well as a straightforward python framework to build complex applications.", + "laborHours": 17586.4, + "name": "Python Display Manager", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pydm/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pydm", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "This is a Python port of\u00a0Zyre\u00a01.0, implementing the same\u00a0ZRE protocol. Pyre does local area discovery and clustering. A Pyre node broadcasts UDP beacons, and connects to peers that it finds. This class wraps a Pyre node with a message-based API.", + "laborHours": 1216.0, + "name": "Pyre", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pyre", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "This packages generates a general purpose control server interface to an FPGA using PyRogue.", + "laborHours": 486.4, + "name": "PyROGUE General Purpose Control Server", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": 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"languages": [], + "name": "rogue-example", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.osti.gov/osti-public/rogue-example/-/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/rogue-example", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ] + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Vivado build system", + "laborHours": 1444.0, + "name": "ruckus", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/ruckus/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ruckus", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "The Skywalker software suite is a set of of Python tools designed to automatically deliver the photon beam to a number of experimental hutches at LCLS.", + "laborHours": 3967.2, + "name": "skywalker", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/skywalker/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/skywalker", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "SLAC Ultimate RTL Framework", + "laborHours": 195016.0, + "name": "surf", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/surf/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/surf", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "ZeroRM SQL Composition library", + "laborHours": 1596.0, + "name": "ZeroRM", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/zerorm/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/zerorm", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-02-16", + "metadataLastUpdated": "2018-02-16" + }, + "description": "KIVA-hpFE is a computer software for solving the physics of multi-species turbulent reactive flow in complex geometries having immersed moving parts. The code is written in Fortran 90/95 and can be used on any computer platform with any popular complier. The code is in 2 versions, a serial version and a parallel version utilizing MPICH2 type Message Passing Interface (MPI or Intel MPI) for solving distributed domains.", + "homepageURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/portfolio-software.php", + "laborHours": 0.0, + "name": "KIVA-hpFE version 1.0.1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/portfolio-software.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/portfolio-software.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SDK for controlling the Adaptable Multiple Power Supplies (AMPS boxes)", + "laborHours": 9013.6, + "languages": [], + "name": "AmpsSDK", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/AmpsSDK", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Ion mobility mass spectrometry data viewer and extractor, targeted toward PNNL's UIMF files", + "laborHours": 49065.6, + "languages": [], + "name": "Atreyu", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Atreyu", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Here, we present the implementation of a Bayesian model (BP-Quant) that uses statistically derived peptides signatures to identify peptides that are outside the dominant pattern, or the existence of multiple over-expressed patterns to improve relative protein abundance estimates. It is a research-driven approach that utilizes the objectives of the experiment, defined in the context of a standard statistical hypothesis, to identify a set of peptides exhibiting similar statistical behavior relating to a protein. This approach infers that changes in relative protein abundance can be used as a surrogate for changes in function, without necessarily taking into account the effect of differential post-translational modifications, processing, or splicing in altering protein function. BP-Quant is available as MatLab \u00ae and R packages here.", + "laborHours": 182.4, + "languages": [], + "name": "BP-Quant", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/BP-Quant", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "All the data and materials for the publication about the Blazing Signature Filter", + "laborHours": 516.8, + "languages": [], + "name": "BSF_publication", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/BSF_publication", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "BioPython scripts for conversion of GBK files or DNA-based FASTA files to protein FASTA files", + "laborHours": 121.6, + "languages": [], + "name": "BioPython Scripts", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/BioPython_Scripts", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Library for reading data files acquired on Bruker mass spectrometers.", + "laborHours": 729.6, + "languages": [], + "name": "Bruker Data Reader", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/BrukerDataReader", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Utility for manually and automatically adding datasets to DMS", + "laborHours": 10032.0, + "languages": [], + "name": "Buzzard", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Buzzard", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Allows for reading Agilent Chemstation .D folders using Dot.NET. The ChemstationMSFileReader provides C# or VB.NET access to reading Agilent Chemstation .D dataset folders, for example, from an Agilent single quadrupole GC-MS instrument.", + "laborHours": 942.4, + "languages": [], + "name": "ChemstationMSFileReader", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/ChemstationMSFileReader", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Given a list of proteins, finds all cross-linked peptides in the given Ion Mobility MS dataset. This application attempts to find all cross-linked peptides in the given Ion Mobility MS dataset. First, the FASTA file is read in and possible peptides are generated by digesting the protein(s) and assuming 1 max missed cleavage. The possible peptides are searched for in the given features by matching up the monoisotopic mass of the feature to the mass of the peptides. The mass ppm tolerance is an input parameter of the application. All possible cross-links of the unmodified peptides are then calculated and searched for in the Isotopic Peak data. A detailed csv results file is created at the end.", + "laborHours": 684.0, + "languages": [], + "name": "Crosslinking IMS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/CrossLinkingIMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Exports Sql Server database objects as schema files. Exported objects include tables, views, stored procedures, and functions,plus also database properties including database roles and logins. The program can also export table data to create SQL files with an Insert Into statement for each row.", + "laborHours": 4620.8, + "languages": [], + "name": "DB Schema Export Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DB-Schema-Export-Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PRISM Data Management System database schema. This is a collection of DDL files that define the database schema used by the Data Management System (DMS) component of the Pan-Omics Research Information Storage and Management system (PRISM) at the Pacific Northwest National Laboratory (PNNL). PRISM incorporates a diverse set of analysis tools and allows a wide range of operations to be incorporated, leveraing a state machine that is accessible to independent, distributed computational nodes. The system has scaled well as data volume has increased since 2002, while allowing adaptability for incorporating new and improved data analysis tools for more effective proteomics research.", + "laborHours": 462475.2, + "languages": [], + "name": "DBSchema_DMS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DBSchema_DMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a collection of DDL files that define the database schema used by the Mass and Time Tag System (MTS) component of the Pan-Omics Research Information Storage and Management system (PRISM) at the Pacific Northwest National Laboratory (PNNL). MTS is used to track and quantify peptides and proteins identified in proteomics and related samples.", + "laborHours": 116112.8, + "languages": [], + "name": "DBSchema_MTS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DBSchema_MTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Analysis Tool Manager is a part of PRISM, the Proteomics Research Information and Management System. The analysis manager performs automated processing of available job steps, tracked by the in the DMS_Pipeline database. Plugin DLLs implement the processing details for each analysis tool.", + "laborHours": 188297.6, + "languages": [], + "name": "DMS Analysis Tool Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Analysis-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Capture Task Manager is a part of PRISM, the Proteomics Research Information and Management System. The capture manager processes instrument data files, copying them from the instrument to storage servers, validating the data, creating QC graphics, and pushing the data into MyEMSL. Plugin DLLs implement the processing details for each tool.", + "laborHours": 110990.4, + "languages": [], + "name": "DMS Capture Task Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Capture-Task-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Email Manager obtains data from a SQL Server database using queries defined in a settings file, e-mailing the results of the queries to one or more people. Reports can be e-mailed daily or only on certain days. It also supports calling a stored procedure or querying WMI.", + "laborHours": 2143.2, + "languages": [], + "name": "DMS EMail Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-EMail-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This program examines the source folder on instrument computers to find files and folders. It creates a tab-delimited text file for each instrument, listing the names of the files and folders found. 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It supports rolling back local files to an older version and auto-deleting extra files.", + "laborHours": 2006.4, + "languages": [], + "name": "DMS Update Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Update-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PNNL Data Management System (DMS) is composed of a SQL Server backend and website front end to allow PNNL staff to track biomaterial, samples, instrument data, and result files from automated software analyses. 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It supports both in-memory sorts for smaller files and use of temporary swap files for large files. It can alternatively sort on a column in a tab-delimited or comma-separated file. 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The software uses a list of glycan targets to search for expected features in MS1 spectra. Features are characterized by monoisotopic mass, elution time, and isotopic fit score. Features are annotated by glycan family relationships and optionally by in-source fragmentation patterns.", + "laborHours": 321601.6, + "languages": [], + "name": "GlyQ-IQ", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/GlyQ-IQ", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This program processes IMS data in a UIMF file to align all frames to a base frame, adjusting the observed drift times of each frame to align with the base frame.", + "laborHours": 775.2, + "languages": [], + "name": "IMS Drift Time Aligner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/IMS-Drift-Time-Aligner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ImsInformed is a .NET class library that provides target identification workflows for peptides and metabolites alike in IMS experiment runs.", + "laborHours": 127345.6, + "languages": [], + "name": "ImsInformed Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/IMS-Informed-Library", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/IMS-Informed-Library", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "InfernoRDN can perform various downstream analyses on large scale datasets from proteomics and microarrays.", + "laborHours": 63353.6, + "languages": [], + "name": "InfernoRDN", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/InfernoRDN", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Informed Proteomics project includes algorithms for proteomic mass spectrometry data analysis. Although the back-end data access and some of the scoring routines are general purpose, this repository is currently maintained for top down MS/MS datasets.", + "laborHours": 335874.4, + "languages": [], + "name": "Informed Proteomics", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Informed-Proteomics", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The LC-IMS-MS Feature Finder finds LC-IMS-MS features and conformers using deisotoped features from DeconTools.\u00a0", + "laborHours": 2021.6, + "languages": [], + "name": "LC-IMS-MS Feature Finder", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LC-IMS-MS-Feature-Finder", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "LCMS raw data and MSGF+ results viewer. LcmsSpectator is a standalone Windows graphical user interface tool for viewing LC-MS data and identifications.", + "laborHours": 114304.0, + "languages": [], + "name": "LCMS-Spectator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/LCMS-Spectator/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LCMS-Spectator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "LIQUID is a software tool for identifying lipids in LC-MS/MS-based lipidomics data. It is described in publication\u00a0LIQUID: an-open source software for identifying lipids in LC-MS/MS-based lipidomics data\u00a0(doi: 10.1093/bioinformatics/btx046). LIQUID provides users with the capability to process high throughput data and contains a customizable target library and scoring model per project needs. The graphical user interface provides visualization of multiple lines of spectral evidence for each lipid identification, allowing rapid examination of data for making confident identifications of lipid molecular species.", + "laborHours": 76015.2, + "languages": [], + "name": "LIQUID", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LIQUID", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python scripts of SVM model training and testing used in a publication entitled 'A generalizable method for false-discovery rate estimation in mass spectrometry-based lipidomics'.", + "laborHours": 121.6, + "languages": [], + "name": "LipidFDR", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LipidFDR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Utility to show the shared folders on the local computer, or on a remote computer", + "laborHours": 212.8, + "languages": [], + "name": "ListWindowsShares", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/List-Windows-Shares", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A VB.NET DLL that can read mass spectrometry data from four file formats: mzXML, mzData, concatenated .dta files (_dta.txt), and Mascot Generic Format files (.mgf)", + "laborHours": 4225.6, + "languages": [], + "name": "MsDataFileReader", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MS-Data-File-Reader", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The MS File Info Scanner can be used to scan a series of MS data files (or data folders) and extract the acquisition start and end times, number of spectra, and the total size of the data. In addition, it can create 2D-plot graphics of the m/z values vs. time for QA purposes.", + "laborHours": 47348.0, + "languages": [], + "name": "MS File Info Scanner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MS-File-Info-Scanner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "DataProcessing toolbox for running MSGF+ and MASIC, then merging the results. Uses Windows batch files to automate the process for a folder of Thermo .Raw files", + "laborHours": 4575.2, + "languages": [], + "name": "MSGFPlus_MASIC_Toolbox", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MSGFPlus_MASIC_Toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Used to generate an Accurate Mass and Time tag database from local MS/MS search engine results (from SEQUEST, X!Tandem, or MSGF+)", + "laborHours": 36571.2, + "languages": [], + "name": "MTDB-Creator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MTDB-Creator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Mage suite of tools provide access to DMS files and metadata.", + "laborHours": 25262.4, + "languages": [], + "name": "Mage", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Mage", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a the code and data for a website created to display collision cross section data for metabolites and small molecules. This repository hosts two things. First is the source code (js) for a website created to display collision cross section data for metabolites and other small molecules. The second is the underlying CCS dataset. The growing interest in metabolomic and exposomic studies is also inciting a need for new techniques to analyze these diverse molecules. Mass spectrometry-based studies are often preferred for the confident identification of small molecules. Ion mobility spectrometry (IMS) is capable of separating molecules that have the same m/z but different conformational arrangements, which is very useful in metabolomic and exposomic analyses. As the desire for IMS measurements of metabolites continues to grow, so does the need for high quality collision cross section (CCS) values.", + "laborHours": 57425.6, + "languages": [], + "name": "Metabolomics Collision Cross Section Database and Server", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MetabolomicsCCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This program can calculate the molecular weight and percent composition of chemical formulas and amino acids, providing a graphical user interface to edit the formulas and parsing options. It recognizes user-definable abbreviations, custom elemental isotopes, and can display up to 20 compounds simultaneously. It also includes a Mole/Mass Converter, Formula Finder, Capillary Flow Modeller, Amino Acid Notation Converter, Peptide Sequence Fragmentation Modeler, Isotopic Distribution Calculator, and built-in calculator. Full program documentation is available by pressing F1 during program operation.", + "laborHours": 30962.4, + "languages": [], + "name": "Molecular Weight Calculator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Molecular-Weight-Calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MwtWinDLL contains utility functions for calculating the molecular weight and percent composition of chemical formulas and amino acids. It recognizes user-definable abbreviations and custom elemental isotopes. It also includes a Mole/Mass Converter, Formula Finder, Capillary Flow Modeller, Amino Acid Notation Converter, Isotopic Distribution Calculator, and Peptide Sequence Fragmentation Modeller. To use, simply include the DLL in a .NET project.", + "laborHours": 6596.8, + "languages": [], + "name": "Molecular Weight Calculator Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Molecular-Weight-Calculator-DLL", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Aligns multiple LC-MS datasets to one another after which LC-MS features can be matched to a database of peptides (typically an AMT tag database)", + "laborHours": 132179.2, + "languages": [], + "name": "MultiAlign", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MultiAlign", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Finds 3D XIC features across LC, m/z, and drift time dimensions", + "laborHours": 5472.0, + "languages": [], + "name": "Multidimensional Peak Finding", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Multidimensional-Peak-Finding", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MTS manager for retrieving files from MyEMSL; The MyEMSL MTS File Cache Manager is a part of PRISM, the Proteomics Research Information and Management System. The software processes the MyEMSL Download Queue in the Mass and Time Tag System (MTS) to download files required for processing.", + "laborHours": 456.0, + "languages": [], + "name": "MyEMSL MTS File Cache Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MyEMSL-MTS-File-Cache-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The MyEMSL Reader is a library used by manager programs in PRISM, the Proteomics Research Information and Management System. The library allows the managers to push files into MyEMSL and later search for and retrieve the files.", + "laborHours": 3024.8, + "languages": [], + "name": "MyEMSL Reader", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MyEMSL-Reader", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Converts an mzIdentML created by MS-GF+ to a tab-delimited text file.", + "laborHours": 334.4, + "languages": [], + "name": "MzidToTsvConverter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Mzid-To-Tsv-Converter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The OBO Data Converter reads an Ontology file in the OBO format and converts the data to a tab-delimited text file.", + "laborHours": 395.2, + "languages": [], + "name": "OBO-Data-Converter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/OBO-Data-Converter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The OxyDataPlotter library includes a WinForms control with a customizable instance of OxyPlot.", + "laborHours": 8284.0, + "languages": [], + "name": "OxyDataPlotter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/OxyDataPlotter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Peptide Hit Results Processor (PHRP) can be used to convert an X!Tandem results file (XML format), MSGF+ .tsv search result file, Sequest Synopsis/First Hits file, or Inspect search result into a series of tab-delimited text files summarizing the results. It will insert modification symbols into the peptide sequences for modified peptides. Parallel files are created containing sequence information, modification details, and protein information. The user can optionally provide a modification definition file that specifies the symbol to use for each modification mass.", + "laborHours": 514444.0, + "languages": [], + "name": "Peptide Hit Results Processor", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PHRP", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PNNL Biodiversity Plugin is a software tool for Skyline and is designed to allow pathway-centric browsing of peptides previously identified by LC-MS/MS. The plugin is designed to assist in SRM assay design or DIA data analysis. Users select an organism and biological pathway of interest, then the plugin shows information about the associated peptides.", + "laborHours": 282218.4, + "languages": [], + "name": "PNNL Biodiversity Library Plugin", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PNNL-Biodiversity-Library-Plugin", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PNNL Omics Library (PNNLOmics.dll) is a collection of data analysis, file I/O, and visualization routines used by several of the omics-related software developed at PNNL.", + "laborHours": 19516.8, + "languages": [], + "name": "PNNL OMICS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PNNL-Omics", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PRISM Class Library (PRISM.dll) is a collection of routines used by many of the software tools that support the Proteomics Research Information and Management System (PRISM) at PNNL. Although written for use by PRISM tools, the methods in the PRISM class library are general utility methods, and are not dependent on any PNNL resources.", + "laborHours": 15549.6, + "languages": [], + "name": "PRISM Class Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PRISM-Class-Library", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "C# reader/writer for mzIdentML files (.mzID). Also supports reading mzML files.", + "laborHours": 29609.6, + "languages": [], + "name": "PSI_Interface", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PSI-Interface", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PepAligner program can read a file containing peptides and align them to a file of protein sequences (.Fasta or delimited text) using Smith-Waterman alignment.", + "laborHours": 1550.4, + "languages": [], + "name": "PepAligner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PepAligner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Peptide Fragmentation Modeller is a command-line utility reads that reads in a text file of peptide sequences and generates the theoretical fragmentation pattern for each, outputting the results in a single concatenated DTA file, or in separate .Dta files. The ion intensity values are not predicted values; instead, b, c, y, and z ions are assigned an intensity of 100; while a ions and neutral loss ions receive an intensity of 20.", + "laborHours": 1717.6, + "languages": [], + "name": "Peptide Fragmentation Modeller", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Peptide-Fragmentation-Modeller", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PeptideListToXML application reads a tab-delimited text file created by the Peptide Hit Results Processor (PHRP) and creates a PepXML with the appropriate information. The various _SeqInfo files created by PHRP must be present in the same folder as the text file. If the MASIC Scan Stats file is also present, then elution time information will be extracted and included in the PepXML file. You should ideally also include the name of the parameter file used for the MS/MS search engine.", + "laborHours": 4104.0, + "languages": [], + "name": "PeptideListToXML", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PeptideListToXML", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Population Variation plug-in for the Skyline software program that can assist researchers in determining whether their target peptides have known mutations in the general human population.", + "laborHours": 5304.8, + "languages": [], + "name": "Population Variation Plug-In", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PopulationVariationPlugin", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Protein Digestion Simulator is a utility for processing\u00a0FASTA files\u00a0including converting to/from tab delimited text. 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The MSGF+ or X!Tandem results must be post-processed with the PeptideHitResultsProcessor (PHRP).", + "laborHours": 5548.0, + "languages": [], + "name": "SMAQC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/SMAQC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "CodeIgniter based website for browsing QC Metrics stored in DMS", + "laborHours": 51725.6, + "languages": [], + "name": "SMAQC_Website", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/SMAQC_Website", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SIPPER can be used to automatically detect and quantify partially labeled C13 peptides in a single dataset. It includes a GUI for manual visualization and annotation of detected LC-MS features. It also includes a Simple MS Viewer for exploring mass spectral data. 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It also verifies that the protein names, descriptions, and sequences are in the correct format.", + "laborHours": 3511.2, + "languages": [], + "name": "ValidateFastaFile", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Validate-Fasta-File", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Venn Diagram Plotter draws correctly proportioned and positioned two and three circle Venn diagrams (aka Euler diagrams) whose colors can be customized and the diagrams copied to the clipboard or saved to disk.", + "laborHours": 5152.8, + "languages": [], + "name": "Venn Diagram Plotter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Venn-Diagram-Plotter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python wrapper for Blazing Signature Filter; The Blazing Signature Filter (BSF) is a highly efficient pairwise similarity algorithm which enables extensive data mining within a reasonable amount of time.", + "laborHours": 319.2, + "languages": [], + "name": "bsf-py", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/bsf-py", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An example of reproducible proteomics data analysis.", + "laborHours": 76.0, + "languages": [], + "name": "celegans.aging", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/Artistic-2.0", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/celegans.aging", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The primary goal was to build a classifier that accurately predicts a binary response. We utilized a Lasso logistic regression classifier (LLRC) which simultaneously restricts the size of model coefficients and the number of quality metrics included the model.\u00a0Importantly the model does not treat false-negatives and false-positives as equally deleterious events.", + "laborHours": 364.8, + "languages": [], + "name": "glmnetGLR", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/glmnetGLR/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/glmnetGLR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a simple C# console program to validate and update the data from\u00a0MetabolomicsCCS", + "laborHours": 988.0, + "languages": [], + "name": "MetaboliteValidation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/metaboliteValidation", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Protein Coverage Summarizer can be used to determine the percent of the residues in each protein sequence that have been identified, based on a list of identified peptides. A graphical user interface (GUI) is provided to allow the user to select the input files, set the options, and browse the coverage results.", + "laborHours": 7569.6, + "languages": [], + "name": "Protein Coverage Summarizer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/protein-coverage-summarizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The RMD_RUNS function will log10 transform peptide peak intensity, that is, peptide abundance data and determine if any LC-MS analyses (ie,runs) in a N x P peptide data set are statistical outliers. The statistical analysis is based on summarizing each LC-MS run as a vector of q=5 summary statistics which describe the peptide abundance distribution for a specific run; a N x q matrix is then analyzed using robust PCA to compute a robust estimate of the covariance matrix used in a the calculation of a robut Mahalanobis distance.", + "laborHours": 243.2, + "languages": [], + "name": "rmd-runs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/rmd-runs", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "GAP codes for computing (pre)modular data from finite groups.", + "laborHours": 167.2, + "languages": [], + "name": "GroupTheoretical", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/GroupTheoretical", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Fortran 90 source code, example problems, and output conversion scripts for the STOMP-W simulator.\u00a0STOMP-W is a numerical simulator written in Fortran 90 for solving problems involving fluid flow and solute/species transport in variably saturated geologic media. The zipped file contains five directories: 1) src (the source code), 2) scripts (output conversion scripts written in perl, 3) prb-w-1 (example problem 1), 4) prb-w-2 (example problem 2), and 5) prb-w-3 (example problem 3). After downloading and unzipping the file, the user must create an executable from the files stored in the src directory. Generic instructions for compiling the source code is shown below as a UNIX/Linux command line, with f90 representing the user's Fortran 90 compiler.", + "laborHours": 73735.2, + "languages": [], + "name": "STOMP-W", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/STOMP-W", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ThermalTracker tracks birds and bats in thermal video. It will process video in any standard format that was recorded with a thermal video camera. The output is images of the flight tracks of birds and bats in PNG format, and a comma-separated value (CSV) file listing the details of the extracted flight tracks.", + "laborHours": 2796.8, + "languages": [], + "name": "ThermalTracker", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/ThermalTracker/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ThermalTracker", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This repository contains sample code written in PHP that allows you to access the Asset Score API.\u00a0The Department of Energy Building Energy Asset Score (Asset Score) is a national standardized tool for evaluating the physical and structural energy efficiency of commercial and multifamily residential buildings. The scoring tool will store user-provided data and generate an asset score and system evaluation for your building envelope and mechanical and electrical systems. The tool will also identify cost-effective upgrade opportunities and help you gain insight into the energy efficiency potential of your building.", + "laborHours": 2705.6, + "languages": [], + "name": "asset-score-api-test-harness", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/asset-score-api-test-harness/blob/master/Readme.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/asset-score-api-test-harness", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Trade-offs between microbiome diversity and productivity in a stratified microbial mat", + "laborHours": 456.0, + "languages": [], + "name": "bernstein-2016-productivity-and-diversity", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/bernstein-2016-productivity-and-diversity/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/bernstein-2016-productivity-and-diversity", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Primary and heterotrophic productivity relate to multi-kingdom diversity in a hypersaline mat", + "laborHours": 1292.0, + "languages": [], + "name": "bernstein-2017-productivity-and-diversity-2", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/bernstein-2017-productivity-and-diversity-2", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "BuildingSync\u00ae is a common schema for energy audit data that can be utilized by different software and databases involved in the energy audit process. It allows data to be more easily aggregated, compared and exchanged between different databases and software tools. This streamlines the energy audit process, improving the value of the data and facilitating achievement of greater energy efficiency.", + "laborHours": 134793.6, + "languages": [], + "name": "BuildingSync", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/BuildingSync/schema/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BuildingSync/schema", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This repository contains the\u00a0tutorial and package reference\u00a0for the\u00a0Smisc\u00a0package.", + "laborHours": 4043.2, + "languages": [], + "name": "docs-Smisc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/docs-Smisc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This repository contains the\u00a0tutorial and package reference\u00a0for the\u00a0rsed\u00a0package.", + "laborHours": 1200.8, + "languages": [], + "name": "docs-rsed", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/docs-rsed", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "eSTOMP-WR (exascale Subsurface Transport Over Multiple Phases) is a highly scalable (parallel), general-purpose tool for simulating subsurface flow and reactive transport in variably saturated geologic media. It's written in Fortran 90.", + "laborHours": 33728.8, + "languages": [], + "name": "eSTOMP-WR", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/eSTOMP-WR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ESTEEM is an interactive web-based prototype visualization tool to allow you to explore dynamic word embeddings across regions using siple keyword queries.", + "laborHours": 7995.2, + "languages": [], + "name": "ESTEEM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/esteem", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Extensible quality control dashboard built around FASTQ assessment. FQC is designed to better group FastQC result data across groups where each group is comprised of FASTQs related to an experiment or sequencing batch. Individual samples are grouped into paired-end sets when available and the dashboard's extensibility allows a user to add plots or tables as desired.", + "laborHours": 125795.2, + "languages": [], + "name": "FQC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/fqc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Faster clustering algorithms written in Java for multicore CPUs.", + "laborHours": 18285.6, + "languages": [], + "name": "Java Analytic Components Lite (JAC)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/jac-lite-clustering/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/jac-lite-clustering", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is supplemental material for a scientific paper. This project 'bernstein-2017-founders-species', explores community succession using a lake biofilm as a model. The code here was used to process and analyze environmental metadata and genetic sequencing data. Statistical tests and data visualization are included.\nThis code makes use of commodity software that is freely available and commonly used in this field. No new methods or techniques are introduced in this code.", + "laborHours": 167.2, + "languages": [], + "name": "jansson_snijders_collaborative_cross", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/jansson_snijders_collaborative_cross/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/jansson_snijders_collaborative_cross", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The JAT (Just Add Tests) Box is a preconfigured Behat Vagrant virtual machine.", + "laborHours": 152.0, + "languages": [], + "name": "JAT-Box", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/jatbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This code can be used to generate a damage map based on the presence of rubble. Rubble is often detectable in images with submeter resolution, and can indicate damage to structures from high winds or earthquakes. The process_images.py script outputs a mask indicating the pixels in the original image where rubble was detected. The mask can be used in a geospatial software application like ArcMap to generate a damage map based on the rubble density. The rubble detection mask will contain some false positives which are usually more isolated than true rubble, so a density map will provide a more accurate indication of affected areas than the indivdidual rubble detections will.", + "laborHours": 91.2, + "languages": [], + "name": "rubblepy", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/rubblepy/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/rubblepy", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This provides several Fortran for consistent handling of time series data. These are used by PNNL's\u00a0MASS1\u00a0and MASS2 codes.", + "laborHours": 2994.4, + "languages": [], + "name": "Time Series Fortran 90 Modules", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/time_series/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/time_series", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Uncertainty quantification code from PNNL", + "laborHours": 5882.4, + "languages": [], + "name": "uq", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/uq", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "nijhuis2@llnl.gov" + }, + "date": { + "created": "2018-02-23", + "metadataLastUpdated": "2018-07-19" + }, + "description": "A sequence-based annotation pipeline for phage", + "laborHours": 3830.4, + "languages": [], + "name": "PhATE (Phage Annotation Tool and Evaluator)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/phate", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An API library that allows communication with oVirt using the Go language.", + "laborHours": 1033.6, + "languages": [], + "name": "Go oVirt API", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/ovirtapi", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This code creates a new \"provider\" plugin to the terraform utility that allows it control virtual machines running in oVirt.", + "laborHours": 228.0, + "languages": [], + "name": "Terraform oVirt Provider", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/terraform-provider-ovirt", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-03-01", + "metadataLastUpdated": "2024-09-17" + }, + "description": "BioCompoundML is a software tool for rapidly screening chemicals by chemical properties, using machine learning.", + "laborHours": 8876.8, + "languages": [ + "Python" + ], + "name": "sandialabs/BioCompoundML", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/BioCompoundML", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "daibane@sandia.gov" + }, + "date": { + "created": "2018-03-01", + "metadataLastUpdated": "2020-09-01" + }, + "description": "Omega_h is a C++11 library that implements tetrahedron and triangle mesh adaptativity, with a focus on scalable HPC performance using (optionally) MPI, OpenMP, or CUDA. It is intended to provided adaptive functionality to existing simulation codes. Mesh adaptivity allows one to minimize both discretization error and number of degrees of freedom live during the simulation, as well as enabling moving object and evolving geometry simulations. Omega_h will do this for you in a way that is fast, memory-efficient, and portable across many different architectures, including NVIDIA GPUs.", + "laborHours": 35826.4, + "languages": [], + "name": "Omega_h", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SNLComputation/omega_h", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "barno1@llnl.gov" + }, + "date": { + "created": "2018-03-06", + "metadataLastUpdated": "2018-03-06" + }, + "description": "Tool for calibrating 1D coda seismic models", + "laborHours": 47712.8, + "name": "LLNL/coda-calibration-tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/coda-calibration-tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-06", + "metadataLastUpdated": "2020-03-03" + }, + "description": "The purpose of this code is to enable collaborative research in simulation of large deformation structural mechanics.\n\nParticularly, it will be used to investigate abstract physics coupling methods and algorithms for implicit solves on emerging computing hardware.", + "laborHours": 24836.8, + "languages": [], + "name": "SERAC", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/serac", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-03-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Executables for working with EnergyPlus Input Files (IDF) This project aims to provide a suite of executables for working with EnergyPlus Input Files (IDF). The project is developed using the Haskell programming language (c.f., https://www.haskell.org/).\nThe current release (version 0.1.0.0) includes a utility that \"pretty prints\" the input file (i.e., that decodes and then, immediately, re-encodes and displays the input file, viz., that sanitizes the input) and a utility that converts the input file into\na labeled graph in the DOT language (c.f., https://www.graphviz.org/doc/info/lang.html) for subsequent rendering using\nGraphviz Visualization Software (c.f., https://www.graphviz.org/).\n\nAn example workflow is to pipe the input file into the pretty printer, to pipe the result into the labeled graph converter, and then to pipe the result into Graphviz, yielding an image file that depicts the hierarchical and referential relationships between EnergyPlus Data Dictionary (IDD) classes that are detected within the input file.", + "laborHours": 152.0, + "languages": [], + "name": "pnnl/Haskell-IDF-Executable", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Haskell-IDF-Executable", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-03-06", + "metadataLastUpdated": "2018-03-15" + }, + "description": "Resonance Inspection encompasses a suite of techniques for the purpose of materials characterization and nondestructive evaluation. These techniques utilize the mechanical resonances of the sample(s) to determine and monitor material properties (e.g., elastic moduli, phase changes), sort mechanically defective parts, determine the presence/level of mechanical damage (micro-cracking, delaminations, disbonding, etc.) and monitor mass/density fluctuations to name a few applications. The Resonance Inspection Techniques & Analyses (RITA) system has been developed to facilitate these and other applications in a user friendly and cost effective package.", + "homepageURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "name": "Resonance Inspection Techniques & Analysis (RITA)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-07", + "metadataLastUpdated": "2018-03-20" + }, + "description": "ConveyorLC is a high throughput virtual screening pipeline for in-silico screening of virtual compound databases using high performance computing. The pipeline mainly includes four modules: receptor/target preparation, ligand preparation, VinaLC docking calculation, and molecular mechanics/generalized Born surface area rescoring.", + "laborHours": 68932.0, + "name": "Conveyor LC", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/XiaohuaZhangLLNL/conveyorlc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-03-15", + "metadataLastUpdated": "2018-03-15" + }, + "description": "XMOF2D is a library implementing the X-MOF (eXtended Moments of Fluid) interface reconstruction method on unstructured polygonal meshes with convex cells. Given a computational mesh with multi-material cells, for which volume fractions and centroids of contained materials are provided, piecewise linear material interfaces are constructed inside such cells using the Moment-of-Fluid (MOF) method. Additionally, a hierarchical mesh is created, where every multi-material cell of the computational mesh contains a local mesh with fully established local topology, as well as the parentage information to relate mesh entities from the local and the computational \nmeshes.", + "laborHours": 2082.4, + "name": "XMOF2D", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laristra/XMOF2D", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-03-15", + "metadataLastUpdated": "2018-03-15" + }, + "description": "PetaVision is an open source, object oriented neural simulation toolbox optimized for high-performance multi-core, multi-node computer architectures. PetaVision is intended for computational neuroscientists who seek to apply neuromorphic models to hard signal processing problems; both to improve on the performance of existing algorithms and/or to gain insight into the computational mechanisms underlying biological neural processing. \n\nPlease note that this assertion and ESTSC deposit are only for the portions of PetaVision which have been funded and written by LANL developers.", + "laborHours": 69342.4, + "name": "PetaVision version 2.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PetaVision/OpenPV", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-03-16", + "metadataLastUpdated": "2018-03-16" + }, + "description": "Plugin API for the LANL Mama (Morphological Analysis of Materials) application.", + "laborHours": 136.8, + "name": "MAMA Plugin API", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/mama-plugin-api", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-20", + "metadataLastUpdated": "2018-03-21" + }, + "description": "AMPE is a phase-field code. It evolves in time the Allen-Cahn equations associated with a phase\u00adfield model, coupled with the time-evolution of a composition field (in an alloy) and a temperature field which are described by diffusion equations. It can also solve the elasticity equations assuming mechanical equilibrium at every time-step. Grain orientations are described by normalized quaternions which also evolve in time according to Allen-Cahn type equations. ", + "laborHours": 58976.0, + "name": "AMPE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AMPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-20", + "metadataLastUpdated": "2018-03-20" + }, + "description": "VinaLC is based on a very popular PC-based molecular docking program, AutoDock Vina. The original Vina docking program was modified and parallelized, using an MPI and multithreading hybrid scheme, and potentially can be used in the future on exascale machines, without sacrificing accuracy.", + "laborHours": 4727.2, + "name": "VinaLC: Parallel Molecular Docking Program", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/XiaohuaZhangLLNL/VinaLC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2018-03-21", + "metadataLastUpdated": "2018-03-21" + }, + "description": "Image processing tools for computed tomography. This is an non-functioning, incomplete, and abandoned project.", + "laborHours": 3891.2, + "name": "pyRafters", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BrookhavenNationalLaboratory/pyRafters", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-03-26", + "metadataLastUpdated": "2019-04-17" + }, + "description": "Simsee is a program for generating artificial seeing data for simulations of astronomical surveys. It includes a jupyter notebook for deriving model parameters from Dual Image Motion Monitor (DIMM) data, and a program that reads these model parameters and creates a data file suitable for use by survey strategy simulation code (which is outside the scope of this package). It is specifically designed to provide input data for LSST\u2019s opsim4 survey simulator, but may be adapted for use with different simulators as well. The code is verified to work on a Linux workstation with an Intel Xeon E5-6980 CPU and 256GB or memory, but should work fine on systems with far more limited resources.", + "laborHours": 12479.2, + "languages": [], + "name": "simsee", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LSSTDESC/ObsStrat", + "status": "Production", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-03-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The goal of Computational Simulation of Online Social Behavior (SocialSim) is to develop innovative technologies for highfidelity computational simulation of online social behavior. SocialSim will focus specifically on information spread and evolution. Current computational approaches to social and behavioral simulation are limited in this regard. Top-down simulation approaches focus on the dynamics of a population as a whole, and model behavioral phenomena by assuming uniform or mostly-uniform behavior across that population. Such methods can easily scale to simulate massive populations, but can be inaccurate if there are specific, distinct variations in the characteristics of the population. In contrast, bottom-up simulation approaches treat population dynamics as an emergent property of the activities and interactions taking place within a diverse population. While such approaches can enable more accurate simulation of information spread, they do not readily scale to represent large populations. SocialSim aims to develop novel approaches to address these challenges.", + "laborHours": 8086.4, + "languages": [], + "name": "pnnl/socialsim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/socialsim", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-28", + "metadataLastUpdated": "2018-03-28" + }, + "description": "The program is a set of python scripts which extends the open source\nprogram Caffc lo allow it to learn to train a neuml network using self -supervised training. ", + "laborHours": 501.6, + "name": "Caffe Standardized Self-Supervised Scripts (CSSSS)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/selfsupervised", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "koziol@lbl.gov" + }, + "date": { + "created": "2018-03-30", + "metadataLastUpdated": "2023-05-16" + }, + "description": "The HDF5 library and file format implement the HDF5 data model for storing and managing data. This implementation supports an unlimited variety of datatypes and is designed for flexible and efficient I/O and for high volume and complex data. It is highly portable and extensible, allowing applications to evolve in their use of HDF5. The HDF5 Technology suite includes tools and applications for managing, manipulating, viewing, and analyzing data in the HDF5 format and other implementations.", + "laborHours": 0.0, + "languages": [], + "name": "HDF5-Version 1.12.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HDFGroup/hdf5", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-03-30", + "metadataLastUpdated": "2018-04-06" + }, + "description": "The numerical background of the FEHM computer code can be traced to the early 1970s when it was used to simulate geothermal and hot dry rock reservoirs. The primary use over a number of years was to assist in the understanding of flow fields and mass transport in the saturated and unsaturated zones below the potential Yucca Mountain repository. Today FEHM is used to simulate groundwater and contaminant flow and transport in deep and shallow, fractured and un-fractured porous media throughout the US DOE complex. FEHM has proved to be a valuable asset on a variety of projects of national interest including Environmental Remediation of the Nevada Test Site, the LANL Groundwater Protection Program, geologic CO2 sequestration, Enhanced Geothermal Energy (EGS) programs, Oil and Gas production, Nuclear Waste Isolation, and Arctic Permafrost. Subsurface physics has ranged from single fluid/single phase fluid flow when simulating basin scale groundwater aquifers to complex multifluid/ multi-phase fluid flow that includes phase change with boiling and condensing in applications such as unsaturated zone surrounding nuclear waste storage facility or leakage of CO2/brine through faults or wellbores. The numerical method used in FEHM is the control volume method (CV) for fluid flow and heat transfer equations which allows FEHM to exactly enforce energy/mass conservation; while an option is available to use the finite element (FE) method for displacement equations to obtain more accurate stress calculations. In addition to these standard methods, an option to use FE for flow is available, as well as a simple Finite Difference scheme.", + "laborHours": 1601304.8, + "name": "FEHM V3.0 - V3.X", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/FEHM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jodi@ecolibrium3.org" + }, + "date": { + "created": "2018-03-30", + "metadataLastUpdated": "2018-05-15" + }, + "description": "The Duluth Shines! application is an online solar map developed in partnership with the University of Minnesota-Duluth to allow the public to compute solar resources available on the rooftops of properties within the Duluth City Limits. The map links to a Minnesota DNR solar cost calculator.", + "homepageURL": "http://umd-cla-gis04.d.umn.edu/duluthshines", + "laborHours": 1945.6, + "languages": [], + "name": "Duluth Shines! Solar Map Application", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://solar.maps.umn.edu/products.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://umd-cla-gis04.d.umn.edu/duluthshines", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Scalable High-performance Algorithms and Data-structures.\nScalable High-performance Algorithms and Data-structures (SHAD) is an application programming interface based on a generic software library. It has a modular design that enables reuse of modules. The core of this software tool set is built on an Abstract Runtime interface and it's library includes the common data structures such as array, vector, map and set. It is designed to accommodate significant amount of data which can be accessed in massively parallel environments, and used as building blocks for SHAD extensions, i.e. higher level software libraries.", + "laborHours": 13573.6, + "languages": [], + "name": "pnnl/SHAD", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SHAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL Cost-Performance Tool (DOE-OE sponsored) for Estimation of Capital Costs for Redox Flow Batteries. Battelle IPID 30401. Copyright \u00a9 2013, Battelle Memorial Institute.", + "laborHours": 11688.8, + "languages": [], + "name": "PNNL-OE-Redox-Flow-Battery-Cost-Tool/PNNL-OE-Redox-Flow-Battery-Cost-Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-OE-Redox-Flow-Battery-Cost-Tool/PNNL-OE-Redox-Flow-Battery-Cost-Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-04-09", + "metadataLastUpdated": "2018-04-09" + }, + "description": "LH2TS enables to calculate the wasted H2 due to transfer and boil-off while using LH2 as a fuel for transportation. The supply chain from the liquefaction plant to the station can be modeled using real gas equations of state from REFPROP and heat transfer models. ", + "laborHours": 532.0, + "name": "LH2 Transfer Simulation ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/NASA-1.3", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LH2Transfer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-04-10", + "metadataLastUpdated": "2018-04-11" + }, + "description": "PyFEHM is an open-source Python library that provides classes and methods to support a scripting environment for the subsurface heat and mass transfer, and geomechanics code FEHM. It is inspired by a similar library, PyTOUGH, available for use with the TOUGH2 family of codes. ", + "laborHours": 34382.4, + "name": "pyFEHM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PyFEHM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-04-10", + "metadataLastUpdated": "2018-04-10" + }, + "description": "This piece of software aims at providing an implementation of methods to perform efficient optimization, probabilistic inference and model selection and learning for various type of networked systems. The software contains a suite of methods and functions that: 1) perform probabilistic inference and random sampling on networked models 2) select or learn networked models from data 3) solve optimization tasks with a networked structure Network models that are supported by these features include, but are not limited to, factor graphs and Markov random fields such as Ising models, Potts models, p-spins models, Gaussian random fields and restricted Boltzmann machine.", + "laborHours": 440.8, + "name": "Optimization, Inference and Learning for Advanced Networks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/GraphicalModelLearning.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-04-11", + "metadataLastUpdated": "2018-04-11" + }, + "description": "This code package solves the multi-species 1D-3V BGK kinetic model of Haack, Hauck, and Murillo [J. Stat. Phys., 168, 2017, Phys. Rev. E, submitted, 2017]. This model conserves mass, momentum, and energy and satisfies Boltzmann's H Theorem, i.e. entropy dissipation. Additionally, the collision model matches either the momentum or temperature relaxation rate of the Boltzmann equation. It can be run in 0D-3V and 1D-3V modes.", + "laborHours": 3070.4, + "name": "Multi-BGK", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Multi-BGK", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-04-12", + "metadataLastUpdated": "2020-11-02" + }, + "description": "ExaMiniMD is a proxy application for Molecular Dynamics (MD) codes such as LAMMPS. Its intend is to facilitate research and development on MD algorithms in particular in the context of CoDesign efforts with hardware vendors. Currently, ExaMiniMD implements a basic Lennard Jones two body potential as well as the SNAP many body potential, both of which are available in LAMMPS. It also includes basic neighbor list builds as well as constant energy integration as found in LAMMPS and other MD codes. A feature not generally available in other MD codes is a set of statistical correctness checks which will help other developers judge whether changes to the code still give correct answers. ExaMiniMD is using the Kokkos programming model to achieve performance portability and is able to run across all major HPC platforms (GPUs, ManyCore, CPUs).", + "laborHours": 3389.6, + "languages": [], + "name": "ECP-copa/ExaMiniMD", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ecp-copa/examinimd", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-04-12", + "metadataLastUpdated": "2021-08-16" + }, + "description": "FAODEL is a collection of libraries for implementing data management services on high-performance computing (HPC) platforms. It is composed of several components: (1) an RDMA portability library called NNTI for transporting data, (2) an in-application, restful API service, (3) a memory management library for network memory named Lunasa, (4) an asynchronous communication engine, and (5) a distributed key/blob service names Kelpie. Application developers may use these libraries to move data between the distributed nodes of one job to another, as well as to distributed storage resources. FAODEL is different than other communication libraries in that it supports both intra- and inter-job communication, features event-driven mechanisms, and provides high-level primitives for developers to reason about a platform\u2019s distributed resources.", + "laborHours": 108558.4, + "languages": [], + "name": "FAODEL", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/faodel/faodel", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2108.1" + }, + { + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-04-12", + "metadataLastUpdated": "2018-04-12" + }, + "description": "The MCMD 1.0 model is used to quantify mass and heat transfer for both direct contact and air gap membrane distillation technologies. The code is designed to be able to be extended to include many different membrane distillation configurations of which air-gap and direct contact are two examples that have already been implemented. ", + "laborHours": 6642.4, + "name": "Multi-Configuration Membrane Distillation Model 1.0 ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dlvilla/mcmd1", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ostrouchovg@ornl.gov" + }, + "date": { + "created": "2018-04-13", + "metadataLastUpdated": "2018-06-28" + }, + "description": "pbdR: This release script for pbdR 1.0 combines several repositories on GitHub and on CRAN with an installer script. We list authors of the subject repositories who are active maintainers.\n\nPackages are released under a variety of licenses noted in the release script.", + "laborHours": 136.8, + "languages": [ + "R" + ], + "name": "RBigData/release", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + }, + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + }, + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + }, + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/RBigData/release", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2018-04-13", + "metadataLastUpdated": "2021-11-08" + }, + "description": "MCT is a set of open-source software tools for creating coupled models. MCT is fully parallel and can be used to couple message-passing parallel models to create a parallel coupled model. MCT is available as a small library and a set of Fortran90 modules. Interoperability is through a simple API. 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By providing an external to the code XML file describing the various elements, their types, and how you wish to process them this run, the routines in the host code (either Fortran or C) can transparently change how they process the data.\n", + "laborHours": 260193.6, + "name": "ADIOS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornladios/ADIOS", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "A mini-app to represent the multipole resonance representation lookup cross section algorithm.\n", + "laborHours": 319.2, + "name": "RSBench", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/RSBench", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2020-08-25" + }, + "description": "\nE3SM is a state-of-the-art fully coupled model of the Earth's climate including important biogeochemical and cryospheric processes. It is intended to address the most challenging and demanding climate-change research problems and DOE mission needs while efficiently using DOE Leadership Computing Facilities. ", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v1.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v1.0.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v1.0" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-04-19", + "metadataLastUpdated": "2018-04-19" + }, + "description": "This software automates the production of standalone emulators for complex computer models. The end result of running the software is a piece of code called an emulator, a statistical approximation which predicts the output of complex computer simulation, but at a much faster speed. The emulator is built using a training set of inputs and outputs from the simulations. The input-output pairs are used in a Bayesian scheme to estimate the parameters of a Gaussian process based regression model that learns the input-output relationship. The estimated parameters are combined with a generic C skeleton to produce a compile-able instantiation of the emulator.", + "laborHours": 1854.4, + "name": "Emulator Generation Gadget", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EGG", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-19", + "metadataLastUpdated": "2023-08-16" + }, + "description": "bifacialvf is a self-contained view factor (or configuration factor) model which replicates a 5-row PV system of infinite extent perpendicular to the module rows. Single-axis tracking is supported, and hourly output files based on TMY inputs are saved. Spatial nonuniformity is reported, with multiple rear-facing irradiances collected on the back of each module row.\n\nBilinear interpolation code add-on to bifacialvf (description below) to pre-generate IV arrays and bifacial coefficients, and to examine the energy production with back side irradiance mismatch for either a portrait or landscape module.\nIncluded are IV curves and bifacial info for a Yingli (standard) module.\n\nBased on the publication: \"A Practical Irradiance Model for Bifacial PV Modules\" B. Marion, S. MacAlpine, C. Deline, A. Asgharzadeh, F. Toor, D. Riley, J. Stein, C. Hansen 2017 IEEE Photovoltaic Specialists Conference, Washington DC, 2017 URL: https://www.nrel.gov/docs/fy17osti/67847.pdf\n", + "laborHours": 1018.4, + "languages": [], + "name": "bifacialVF - Bifacial PV View Factor model [SWR 17-58]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bifacialvf", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-19", + "metadataLastUpdated": "2018-04-19" + }, + "description": "The HTEM DB is a public database and web application containing measurements of thin film materials collected using \"high throughput\" (combinatorial) synthesis and measurement processes. This software provides examples of utilizing the HTEM-DB API to access, plot and analyze the data contained therein.", + "laborHours": 364.8, + "name": "HTEM-DB API Examples", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/htem-api-examples", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-19", + "metadataLastUpdated": "2025-03-03" + }, + "description": "The WIND Toolkit Highly Scalable Data Service (HSDS) API examples provide example python software notebooks (software) and a javascript visualization that demonstrate use of the HDF Group's HSDS API utilizing data for NREL's WIND Toolkit.", + "laborHours": 699.2, + "languages": [ + "Jupyter Notebook" + ], + "name": "WIND Toolkit Highly Scalable Data Service (HSDS) API Examples [SWR-18-05]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/hsds-examples", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "fattebertj@ornl.gov" + }, + "date": { + "created": "2018-04-20", + "metadataLastUpdated": "2018-04-20" + }, + "description": "MGmol is a scalable O(N) First-Principles Molecular Dynamics code that is capable of performing large-scale electronics structure calculations and molecular dynamics simulations of atomistic systems.", + "laborHours": 62760.8, + "name": "LLNL/mgmol", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mgmol", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MOSART-WM - a large scale water management model", + "laborHours": 1322.4, + "languages": [], + "name": "IMMM-SFA/wm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/wm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-23", + "metadataLastUpdated": "2023-08-16" + }, + "description": "BRICR is software for translating NREL's BuildingSync\u2122 XML (BSXML) to OpenStudio\u00ae Workflow (OSW) files for simulation. Each BSXML contains information about a building as well as multiple possible energy efficiency upgrade options. An OSW file is created and run for each possible efficiency upgrade, the results of all simulations are stored in BSXML format.\n\nBRICR was jointly developed by NREL and LBNL for the San Francisco BayREN: Integrated Commercial Retrofits (BRICR) project funded under the DOE solicitation \"Solutions to Improve the Energy Efficiency of U.S. Small and Medium Commercial Buildings (DE-FOA-0001385)\":\n\nhttps://www.energy.gov/eere/buildings/downloads/san-francisco-bayren-integrated-commercial-retrofits", + "laborHours": 0.0, + "languages": [], + "name": "BRICR v0.2.0 (BayREN Integrated Commercial Retrofits) [SWR 18-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bricr/releases/tag/v0.2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.2.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-23", + "metadataLastUpdated": "2023-01-20" + }, + "description": "A python library used to estimate soiling losses from PV energy production data.", + "laborHours": 744.8, + "languages": [ + "Python" + ], + "name": "PV Soiling Detection [SWR-18-02]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pv_soiling", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.2.2" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-04-24", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The ns-3 topology generator provides a quick and easy way to create a network topology, and generate C++ simulation code for ns-3.", + "laborHours": 3116.0, + "languages": [], + "name": "Topology_Generator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Topology_Generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-04-24", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The ns-3 code generator provides a way to automatically generate C++ simulation code for ns-3 from a high level network topology description.", + "laborHours": 1854.4, + "languages": [], + "name": "idaholab/Code_Generator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Code_Generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-04-24", + "metadataLastUpdated": "2023-03-15" + }, + "description": "HPC job tracker is a wrapper script which will allow some of the resources a HPC application consumes to be tracked for the duration of the job.", + "laborHours": 456.0, + "languages": [], + "name": "HPC_Job_Tracker", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HPC_Job_Tracker", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-04-24", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Mesoscale Atomistic Glue Program for Integrated Execution", + "laborHours": 14333.6, + "languages": [], + "name": "magpie", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/magpie", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Interactive machine learning interface\nOur invention allows the user to interact with individual instances, see recommendations for similar items, and make\nadjustments. The scalable nature of our solution allows it to perform instantaneously from the user's perspective, even for\n100K+ data items.", + "laborHours": 13421.6, + "languages": [], + "name": "pnnl/chissl", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/chissl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Simulation software for biochemical systems that use mass action kinetics based on maximum entropy production.", + "laborHours": 47560.8, + "languages": [], + "name": "Simulations of State for Biology", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/Boltzmann", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-05-01", + "metadataLastUpdated": "2018-05-01" + }, + "description": "Phase Field Dislocation Dynamics (PFDD) is a phase field approach for tracking the motion and interactions of individual dislocations in materials, mostly face-centered cubic (fcc) metals. The phase field approach relies on scalar order parameters or phase field variables to track a quantity of interest. In PFDD, these phase field variables represent the passage of perfect dislocations across each active slip system, with one order parameter defined in each slip system. Partial dislocations are represented with linear combinations of the order parameters. The system is evolved through minimization of the total system energy, which is directly dependent on the phase field variables. All of the physics is described by the total energy functional that is derived from a thermodynamic basis, and the system kinetics are evolved using a Ginzburg-Landau (GL) equation.", + "laborHours": 3024.8, + "name": "Phase Field Dislocation Dynamics (PFDD)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Phase-Field-Dislocation-Dynamics-PFDD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-05-02", + "metadataLastUpdated": "2018-05-02" + }, + "description": "The software is an analyzer for automated sandbox analysis of malware on the OS X operating system. It runs inside an OS X virtual machine to collect data about what happens when a given file opened or run. As of August 2014, there was no sandbox software for Mac OS X malware, as it requires different methods from those used on the Windows OS (which most sandboxes are written for). This software adds OS X analysis capabilities to an existing open-source sandbox, Cuckoo Sandbox (https://cuckoosandbox.org/), which previously only worked for Windows. \n\nThe analyzer itself can take many different types of files as input: the traditional Mach-O and FAT executables, .app files, zip files, Python scripts, Java archives, and web pages, as well as PDFs and other documents. While the file is running, the analyzer also simulates rudimentary human interaction with clicks and mouse movements in order to bypass the tests some malware use to see if they are being analyzed. The analyzer outputs several different kinds of data: functions call traces, network captures, screenshots, and all created and modified files. This work also includes a static analysis Cuckoo module for Mach-O binary files. It extracts file structures, code library imports and exports, and signatures. This data can be used along with the analyzer results to create signatures for malware. ", + "laborHours": 1276.8, + "name": "sandialabs/mac-sandbox", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mac-sandbox", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-05-02", + "metadataLastUpdated": "2018-05-02" + }, + "description": "LAPART is an artificial neural network algorithm written in the Python programming language. The algorithm can learn patterns using multi-dimensional hyper boxes. It can also perfrom regression and classification calculations based on learned associations.", + "laborHours": 258.4, + "name": "sandialabs/lapart-python", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/lapart-python", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-05-02", + "metadataLastUpdated": "2018-05-02" + }, + "description": "The standard scenarios match (sssmatch) tool accepts limited information about an existing transmission system model and computes a new generation mix based on a.) matching a particular NREL Standard Scenario generation mix and b.) minimizing the distance between the system\u2019s original mix and the final one. The distance metric is computed on a nodal basis.", + "laborHours": 562.4, + "name": "sssmatch (Standard ScenarioS Match)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Smart-DS/sssmatch", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bjoo@jlab.org" + }, + "date": { + "created": "2018-05-08", + "metadataLastUpdated": "2018-05-08" + }, + "description": "QMP Message Passing Library. A simple wrapper for MPI to implement the QMP Interface.", + "laborHours": 8557.6, + "name": "QMP", + "organization": "Thomas Jefferson National Accelerator Facility (TJNAF)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://raw.githubusercontent.com/usqcd-software/qmp/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usqcd-software/qmp", + "status": "Production", + "tags": [ + "DOE CODE", + "Thomas Jefferson National Accelerator Facility (TJNAF)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bjoo@jlab.org" + }, + "date": { + "created": "2018-05-08", + "metadataLastUpdated": "2018-05-08" + }, + "description": "A library to read LIME files. LIME is a record oriented file format allowing binary and textual records to be kept in the same file. It is based on a proposed Internet standard by Microsoft called DIME which is now part of the .NET framework.", + "laborHours": 1869.6, + "name": "c-lime", + "organization": "Thomas Jefferson National Accelerator Facility (TJNAF)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://raw.githubusercontent.com/usqcd-software/c-lime/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usqcd-software/c-lime", + "status": "Development", + "tags": [ + "DOE CODE", + "Thomas Jefferson National Accelerator Facility (TJNAF)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-05-09", + "metadataLastUpdated": "2018-05-09" + }, + "description": "The RMA-MT benchmarks are a suite of performance tests for multi-threaded Message Passing Interface (MPI) Remote Memory Access (RMA) implementations. The suite includes tests for bandwidth and latency with any number of threads. This suite was originally developed and release by Sandia National Laboratory. LANL modifications to the suite include a complete re-write of much of the source code, bi-directional bandwidth, and message rate tests.", + "laborHours": 1155.2, + "name": "RMA-MT Benchmarks ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/rma-mt", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-05-09", + "metadataLastUpdated": "2018-05-09" + }, + "description": "The forms and workflow developed were designed to collect additional statistical information not normally available in out of- the-box implementations of the Remedy Action Request System designed by BMC Software. This workflow is used to collect additional information about users accessing the Remedy application, such as operating system and browser type. This information along with frequency of user logins, number of emails sent and received, and overall license usage help provide Remedy Administrators a better overview of the application they support. These custom forms and workflow work heavily with existing out-of-the-box forms in Remedy, and display the collected data to users through the product BMC\u2019s companion product Smart Reporting. ", + "laborHours": 60420.0, + "name": "Remedy Application Statistics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Remedy-Application-Statistics", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-05-10", + "metadataLastUpdated": "2018-05-22" + }, + "description": "Pyranda Is fortran 90 code which solves compact finite difference equations on a three dimensional fortran arrays, domain decomposed using the Message Passing Interface (MPI). The fortran source solves the linear system of equations which forms a pentadtagona1 matrix. Derivatives are used to construct hyperbolic partlal differential equation (PDE) operators, namely gradient, divergence, Laplacian, and curl operators. \n5. Solution Method:\nThe library provides a python Interface which facilitates problem setup and description. However, the core solver Is written in the fortran 90 language. The solver couples MPI communication and linear solves together so that a direct (non-iterative) solution to the linear system of equations can be computed with minimal communication. Domain decomposition is limited to a uniform data size but provides perfect load balancing. \n6. Computer for which the code Is written:", + "laborHours": 9849.6, + "languages": [], + "name": "PYRANDA", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pyranda", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-05-10", + "metadataLastUpdated": "2020-05-27" + }, + "description": "STAT is a light weight debugging tool that gathers and merges stack traces from all of the processes in a parallel application. STAT uses the MRNet tree based overlay network to broadcast commands from the tool front-end to the STAT daemons and for the front-end to gather the traces from the STAT daemons. As the traces propagate through the MRNet network tree, they are merged across all tasks to fonn a single call prefix tree. The call prefix tree can be examined to identify tuks with similar function call patterns and to delineate a small set of equivalence classes. A representative task from each of these classes can then be fed into a full feature debugger like TotalView for root cause analysis. ", + "laborHours": 27755.2, + "languages": [], + "name": "Stack Trace Analysis Tool (STAT)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/STAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-05-15", + "metadataLastUpdated": "2018-05-15" + }, + "description": "Mota is a library that provides several heuristics for mapping tasks to compute ranks (processes) on a networked computer cluster or supercomputer. It was originally designed for task placement of adaptive mesh refinement codes (AMR). It is multi-objective in the sense that it simultaneously balances (potentially multiple types of) computational load on each rank as well as the communication traffic between the boxes. The heuristics used for mapping include algorithms such as greedy list assignment and space-filling curves, as well as algorithms from graph analysis such as adjacency matrix bandwidth reduction, recursive bisection, and greedy graph placement.", + "laborHours": 1930.4, + "languages": [], + "name": "Mota Mapper: A Multi-Objective Topology-Aware Mapper Library", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-CoDEx/mota", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-05-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Global Memory and Threading runtime system", + "laborHours": 5228.8, + "languages": [], + "name": "pnnl/gmt", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/gmt", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-05-18", + "metadataLastUpdated": "2018-05-18" + }, + "description": "OpenStudio is a cross-platform collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance.\n\nThis disclosure includes two OpenStudio measures: (1) data center prototype models, and (2) occupant schedule generator. The data center models cover two sizes (small computer server rooms, stand-alone large data centers) and two IT load densities (average and high).", + "laborHours": 4456883.2, + "languages": [], + "name": "NREL/OpenStudio", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-05-18", + "metadataLastUpdated": "2018-05-21" + }, + "description": "MaDaTS provides an integrated data management and workflow execution framework on multi-tiered storage systems. Users of MaDaTS can execute a workflow by either specifying the workflow stages in a YAML description file, or use the API to manage the workflow through a Virtual Data Space (VDS) abstraction.", + "laborHours": 4484.0, + "languages": [], + "name": "\tManaging Data on Tiered Storage for Scientific Workflows (MaDaTS) v1.1.2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dghoshal-lbl/madats", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-05-22", + "metadataLastUpdated": "2025-03-26" + }, + "description": "The software was developed for the purpose of Microgrid Controller Procurement where multiple Microgrid Controller vendors were competing to prove the best performance. Each microgrid controller was connected to Real-Time Simulator (Opal-RT) where the Real-Time model of microgrid was simulated. Microgrid controllers were able to control most of the assets in the model. To be able to fairly compare controller's performance each controller was evaluated using exactly the same model, with the same initial conditions and exactly the same test sequence.\n\nThe microgrid evaluation test sequence lasted 100 minutes and consist of various grid disturbances to which a microgrid controller must respond. The microgrid and power system will experience multiple types of disturbances while performing dispatch functions. Many functions are tested in grid-connected and islanded modes such as unexpended failures of generators, energy storage trip events, and large load fluctuations. The test sequence focuses on fault scenarios that cause the highest short-circuit fault current contribution; force a swing bus or generator capable of being a swing bus offline; cause the most reconfigurations; and cause conflicting objectives for the microgrid controller. \n\nDuring the test sequence execution multiple datapoints are being recorded and stored. During data postprocessing key performance parameters are extracted allowing quantitative comparison of performance on multiple aspects including: resiliency, fuel utilization, grid interconnection, ancillary services and power quality and eventually after summing all key performance parameters by comparing the overall result.\n\nTo be able to perform such testing multiple tools had to be developed included in this repository including:\n- Real time model of microgrid (Urban-Banshee, Remote-smaller model)\n- Test sequence configuration tools\n- Test execution real-time scripts\n- Post processing scripts\n- Human Machine Interface software", + "homepageURL": "https://github.com/PowerSystemsHIL/EPHCC/tree/NREL_merge", + "laborHours": 242196.8, + "languages": [], + "name": "GHOST (Grid Hardware Open Source Testbed) [SWR-18-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PowerSystemsHIL/EPHCC/tree/NREL_merge", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-05-22", + "metadataLastUpdated": "2018-05-22" + }, + "description": "SolarPILOT\u2122advances the analytical flux image Hermite series approximation used in DELSOL3 by applying it to individual heliostat images rather than \"zones\", allowing characterization of a wide variety of heliostat field layouts. SolarPILOT also integrates the SolTrace Monte-Carlo ray tracing engine, providing improved receiver optical modeling capability, a user-friendly front end for geometry definition, and side-by-side validation of the analytical algorithms. The tool and source code are publicly available and are designed for third-party modification and extendability. The software is intended as a replacement for the more antiquated DELSOL3 algorithm originally developed at Sandia National Laboratory. The software will be used at NREL for power tower component design analysis and may be used at other laboratories, in academia, or as a third-party validation tool by some industry groups.", + "laborHours": 28743.2, + "languages": [], + "name": "SolarPILOT\u2122", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SolarPILOT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-05-23", + "metadataLastUpdated": "2018-05-23" + }, + "description": "ParELAGMC is a parallel distributed memory C++ library for multilevel Monte Carlo (MLMC) simulations with algebraically constructed coarse spaces for estimating statistical moments of a quantity of interest involving solutions of partial differential equations with uncertain coefficients. A primary focus of the library is the scalable generation of Gaussian random fields using a novel stochastic PDE (SPDE) sampling technique for large-scale simulations. A key feature in the SPDE sampling technique is a novel non-matching mesh embedding technique to mitigate artificial boundary artifacts that are inherent in the method. Example applications to uncertainty quantification of subsurface flow simulations in the mixed finite element setting are provided as well.", + "laborHours": 17905.6, + "languages": [], + "name": "Parallel Element Agglomeration Multilevel Monte Carlo Library (ParELAGMC)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/parelagmc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-05-23", + "metadataLastUpdated": "2018-05-23" + }, + "description": "Lightweight Python package for assembling, sharing, and running workflows, especially those associated with modifying, running, and analyzing simulation models.", + "laborHours": 699.2, + "languages": [], + "name": "layerstack", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Smart-DS/layerstack", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "A python client that talks to the PCDS logbook using the logbook webservice.\n", + "laborHours": 1352.8, + "languages": [], + "name": "LogBookClient", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/LogBookClient", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "Python interface to archiver appliance that most closely matches the legacy xpppython api.\n", + "laborHours": 440.8, + "languages": [], + "name": "archapp", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/archapp/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/archapp", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "LCLS-II MPS central node software.\n", + "laborHours": 629310.4, + "languages": [], + "name": "central_node_engine", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/central_node_engine/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/central_node_engine", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "LCLS-II MPS central node IOC.\n", + "laborHours": 10624.8, + "languages": [], + "name": "central_node_ioc", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/central_node_ioc/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/central_node_ioc", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "This package contains SQLAlchemy python classes that provide access to the MPS sqlite3 database.\n", + "laborHours": 6064.8, + "languages": [], + "name": "LCLS-II MPS Database", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/mps_database/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/mps_database", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "Collection of conda recipes for PCDS software at LCLS.\n", + "laborHours": 425.6, + "languages": [], + "name": "pcds-recipes", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pcds-recipes/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pcds-recipes", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "Maps URLs into experiment results folders after authz.\n", + "laborHours": 6779.2, + "languages": [], + "name": "pcds_expresults", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pcds_expresults", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "Geometry 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By first manipulating pairs of motors as joints, and then the stand as a collection of three unieque joints, higher level functions such as translate and rotate are created to help the operator quickly adjust the stand.\n", + "laborHours": 820.8, + "languages": [], + "name": "detrot", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/detrot/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/detrot", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-06-05", + "metadataLastUpdated": "2018-06-05" + }, + "description": "This is the repository for hxdhome developed at SLAC National Accelerator Laboratory.", + "laborHours": 836.0, + "languages": [], + "name": "hxdhome", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/hxdhome/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/hxdhome", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-06-05", + "metadataLastUpdated": "2018-06-05" + }, + "description": "A general repository of useful information for programming across the lab. This repository is oriented around tools, education, best practices, and general knowledge around programming and software development across the lab. We hope it will empower anyone who writes softare at the lab, whether it's analysis scripts in python, firmware for daq systems, web apps for communications, or just simple bash scripts.\n", + "laborHours": 60.8, + "languages": [], + "name": "Programming at SLAC", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/programming/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/programming", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-06-08", + "metadataLastUpdated": "2018-06-14" + }, + "description": "TaskAMR is a Cartesian Block Adaptive Mesh Refinement (AMR) code, written using the Regent/Legion parallel programming system, that solves Finite Volume calculations. 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Since then, the code has undergone an independent technical review as part of a submittal to the Nuclear Regulatory Commission for a generic license to apply the code to spent fuel storage system analysis. Modifications and improvements to the code have been combined to form Cycle 2. Cycle 3., the newest version of COBRA-SFS, has been validated and verified for transient applications, such as a storage cask thermal response to a pool fire.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Thermal Hydraulic Analysis of Spent Fuel Casks", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-13", + "metadataLastUpdated": "2022-09-14" + }, + "description": "Integrated system to compute long-term public health risks as the result of the release of hazardous and/or radioactive materials to air, groundwater, surface water, and overland transport pathways.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Multimedia Environmental Pollutant Assessment System", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "phuck@lbl.gov" + }, + "date": { + "created": "2018-06-14", + "metadataLastUpdated": "2019-06-26" + }, + "description": "Python Materials Genomics (pymatgen) is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. 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Workflow execution can be automated over arbitrary computing resources, including those that have a queueing system. 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The tool then serves as an interface to plotting and statistical software packages to facilitate the evaluation of the data and parameter estimation.", + "homepageURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [], + "name": "GeoMatTool, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2018-06-19" + }, + "description": "ROVER Is an application for distributed-memory volume rendering and simulated radiography focused on many-core architectures (e.g., GPU, CPU, and MIC). 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It provides a point table for each housing type that can be used to determine whether a proposed design meets the standard and how a design can be modified to meet the standard.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Yearly Energy Costs for Buildings", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2022-11-10" + }, + "description": "UNSAT-H Version 2.0 is a one-dimensional model that simulates the dynamic processes of infiltration, drainage, redistribution, surface evaporation, and the uptake of water from soil by plants. 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The boundary conditions can be controlled as either constant (potential or temperature) or flux conditions to reflect actual conditions at a given site.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Water and Heat Balance Model for Predicting Drainage Below the Plant Root Zone", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2018-06-19" + }, + "description": "Kappa and BioNetGen (BNGL) are prominent rule-based modeling languages for representing complex biochemical reaction networks. 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TRuML accommodates the languages' complexities and produces a semantically equivalent model in the alternate language of the input model when possible, and an approximate model in certain other cases.", + "laborHours": 1565.6, + "languages": [], + "name": "TRuML", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/TRuML", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2022-11-10" + }, + "description": "REOPT has been developed by Pacific Northwest Laboratory to provide information about remedial action technologies, including application and regulatory information for over 700 contaminants. REOPT is a user-friendly personal computer program and database that functions like an electronic encyclopedia, sorting and presenting information to quickly familiarize engineers and planners with available remediation technologies. The system will help users focus quickly on the remediation technologies most likely to be effective for a particular site and problem, and presents concise, easy-to-use information about those technologies, helping users identify the key factors and constraints to consider in evaluating the use of each technology. REOPT contains information on approximately 90 established (i.e., proven) remediation technologies that could potentially be used for DOE waste-site cleanup. REOPT also contains auxiliary information about hazardous and radioactive contaminants and the federal regulations that govern their disposal. REOPT contains data for approximately 90 remedial action technologies, divided into categories according to the portion of a remedial action (i.e., containment, treatment, disposal, etc.) that they relate to or perform. Technologies are also classified according to the contaminants to which they may be applied. Contaminants may be selected from a list of approximately 700 in ten organic and four inorganic categories. The information for each technology is organized into the broad categories of descriptive information, application information, and additional information sources; these are then subdivided to allow the user to access more specific information about the technology.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "An Electronic Encyclopedia of Remedial Options", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2018-06-19" + }, + "description": "PyDislocDyn is a suite of python programs designed to perform various calculations for basic research in dislocation dynamics in metals with simple crystal symmetries in the continuum limit. 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", + "laborHours": 1352.8, + "languages": [], + "name": "PyDislocDyn", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dblaschke-LANL/PyDislocDyn", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-06-20", + "metadataLastUpdated": "2024-09-18" + }, + "description": "NimbleSM is a Lagrangian finite-element code for solid mechanics. Its primary application is the solution of mechanics problems on nonuniform, three-dimensional meshes using either explicit transient dynamic or implicit quasi-static time integration. Additional features include multiscale modeling and the simulation of contact. The NimbleSM code base is designed for performance portability across varying hardware architectures.", + "laborHours": 19729.6, + "languages": [ + "C++", + "Shell", + "C", + "Gnuplot", + "CMake", + "Python" + ], + "name": "NimbleSM", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/nimblesm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-20", + "metadataLastUpdated": "2022-11-17" + }, + "description": "TAP-LOOP is a finite-difference program designed for steady-state and transient thermal analysis of recirculating fluid loops and associated heat transfer equipment; however, it is not limited to loop analysis. TAP-LOOP was developed to perform scoping and conceptual design analyses for closed test loops in the Fast Flux Test Facility (FFTF), but it can handle a variety of problems which can be described in terms of potentials, sources, sinks, and storage including, in addition to heat transfer problems, studies of potential fluid flow, electrical networks, and stress analysis.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Thermal Analysis of Closed Systems", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-06-21", + "metadataLastUpdated": "2018-06-21" + }, + "description": "Securely and quickly copy data from source to target. bbcp is a point-to-point network file copy application. It is capable of transferring files at approaching line speeds in the WAN.\n", + "laborHours": 7919.2, + "languages": [], + "name": "bbcp", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.slac.stanford.edu/~abh/bbcp/#_Toc392015168", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/bbcp", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-21", + "metadataLastUpdated": "2022-11-28" + }, + "description": "NRADA1.1 is a supplement to NRADA1.0. This version eliminates several bugs, and includes a few new features. The diskettes consist of a distributed subset of information representative of the extensive NRA databases and database access software maintained at the Pacific Northwest Laboratory which provide an introduction to the scope and style of the NRA Information Systems. Information in the NRA Summary, Inventory, and Bibliographic database is available upon request. Printed reports have been provided in the past. The completion of the NRADA1.1 is the realization of a long standing goal of the staff and advisory committee. Information may be easily distributed to the user in an electronic form which preserves the relationships between the various databases.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Nation Radiobiology Archives Distributed Access", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-22", + "metadataLastUpdated": "2022-12-07" + }, + "description": "SYSPLAN evaluates capital investment in customer side of the meter load leveling battery systems. Such systems reduce the customer's monthly electrical demand charge by reducing the maximum power load supplied by the utility during the customer's peak demand. System equipment consists of a large array of batteries, a current converter, and balance of plant equipment and facilities required to support the battery and converter system. The system is installed on the customer's side of the meter and controlled and operated by the customer. Its economic feasibility depends largely on the customer's load profile. Load shape requirements, utility rate structures, and battery equipment cost and performance data serve as bases for determining whether a load leveling battery system is economically feasible for a particular installation. Life-cycle costs for system hardware include all costs associated with the purchase, installation, and operation of battery, converter, and balance of plant facilities and equipment. The SYSPLAN spreadsheet software is specifically designed to evaluate these costs and the reduced demand charge benefits; it completes a 20 year period life cycle cost analysis based on the battery system description and cost data. A built-in sensitivity analysis routine is also included for key battery cost parameters. The life cycle cost analysis spreadsheet is augmented by a system sizing routine to help users identify load leveling system size requirements for their facilities. The optional XSIZE system sizing spreadsheet which is included can be used to identify a range of battery system sizes that might be economically attractive. XSIZE output consisting of system operating requirements can then be passed by the temporary file SIZE to the main SYSPLAN spreadsheet.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Load Leveling Battery System Costs", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-06-26", + "metadataLastUpdated": "2018-06-26" + }, + "description": "The Software is a toolbox for Dynamic Programming and Adaptive Dynamic Programming (ADP) that enables stochastic, multi-period decision optimization for arbitrary \"black box\" models. It\u2019s modular framework is designed to serve as a wrapper for other simulation tools. This enables forward-looking optimization under uncertainty to aid decision making by a variety of stakeholders when facing an increasingly uncertain future. ", + "laborHours": 5122.4, + "languages": [], + "name": "dynamo", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dynamo", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "czhu@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2018-06-27" + }, + "description": "FOCUS uses 3D curves to represent coils in fusion devices, mainly for toroidal devices including stellarators and tokamaks. For a given configuration, FOCUS can find optimal coils, which can produced the required magnetic field for confining the plasma meeting the user-specified physics and engineering constraints.", + "homepageURL": "https://princetonuniversity.github.io/FOCUS", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Flexible Optimized Coils Using Space curves (FOCUS)", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://princetonuniversity.github.io/FOCUS", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "version": "0.3.1" + }, + { + "contact": { + "email": "fpoli@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2022-01-02" + }, + "description": "TRANSP is a 1.5D equilibrium and transport solver for interpretation and prediction of tokamak discharges.", + "homepageURL": "https://transp.pppl.gov", + "laborHours": 1936723.2, + "languages": [], + "name": "TRANSP", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://transp.pppl.gov/license.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://transp.pppl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] + }, + { + "contact": { + "email": "czhu@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2018-06-27" + }, + "description": "Building on the theoretical foundations of Bruno & Laurence, that three-dimensional, (3D) magnetohydrodynamic (MHD) equilibria with \u201cstepped\u201d-pressure profiles are well-defined and guaranteed to exist, whereas 3D equilibria with integrable magnetic-fields and smooth pressure (or with non-integrable fields and continuous-but-fractal pressure) are pathological. Dr. S.R. Hudson wrote the \u201cStepped Pressure Equilibrium Code\u201d, (SPEC). SPEC finds minimal-plasma-energy states, subject to the constraints of conserved helicity and fluxes in a collection of nested sub-volumes by extremizing the multi-region, relaxed-MHD (MRxMHD), energy functional, introduced by Dr. M.J. Hole, Dr. S.R. Hudson & Prof. R.L. Dewar.", + "homepageURL": "https://princetonuniversity.github.io/SPEC", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Stepped-Pressure Equilibrium Code (SPEC)", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://princetonuniversity.github.io/SPEC", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] + }, + { + "contact": { + "email": "czhu@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2020-05-07" + }, + "description": "The STELLOPT code is designed to optimize 3D MHD equilibria to a set of target physics parameters encompassing stellarator design and 3D equilibrium reconstructions.", + "laborHours": 173812.0, + "languages": [ + "Fortran" + ], + "name": "STELLOPT", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PrincetonUniversity/STELLOPT", + "status": "Production", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "vcs": "git", + "version": "2.7.5" + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2023-01-17" + }, + "description": "GEOCITY is a large-scale simulation model which combines both engineering and economic submodels to systematically calculate the cost of geothermal district heating systems for space heating, hot-water heating, and process heating based upon hydrothermal geothermal resources. The GEOCITY program simulates the entire production, distribution, and waste disposal process for geothermal district heating systems, but does not include the cost of radiators, convectors, or other in-house heating systems. GEOCITY calculates the cost of district heating based on the climate, population, and heat demand of the district; characteristics of the geothermal resource and distance from the distribution center; well-drilling costs; design of the distribution system; tax rates; and financial conditions.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Geothermal District Heating Economics", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "ethier@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2018-07-26" + }, + "description": "Global, gyrokinetic PIC code in full general geometry used for studying core microturbulent transport in experimental tokamaks.", + "homepageURL": "https://theory.pppl.gov/research/research.php?rid=10#h47", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Gyrokinetic Tokamak Simulation code (GTS)", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://theorycodes.pppl.wikispaces.net/file/detail/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://theory.pppl.gov/research/research.php?rid=10#h47", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] + }, + { + "contact": { + "email": "sku@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2021-04-13" + }, + "description": "XGC (X-point included gyrokinetic code), Version 3 Primary Author: Seunghoe Ku (PPPL, sku@pppl.gov), Robert Hager (PPPL, rhager@pppl.gov) 31 July 2017 XGC is a gyrokinetic particle-in-cell code, which is sepeciallized in tokamak edge simulatin. 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", + "homepageURL": "http://tetra.mech.ubc.ca/GRUMMP", + "laborHours": 0.0, + "languages": [], + "name": "iMesh/GRUMMP", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://tetra.mech.ubc.ca/GRUMMP/License.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://tetra.mech.ubc.ca/GRUMMP", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-07-09", + "metadataLastUpdated": "2020-06-01" + }, + "description": "Cinema is a workflow and toolkit for capturing, storing and exploring extreme scale scientific data. 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The Cinema toolkit includes database specifications and software such as database writers, database viewers, algorithms and other support software that enable a wide variety of applications to write, operate on, and view Cinema databases.", + "laborHours": 5836.8, + "languages": [ + "C++", + "JavaScript", + "Python" + ], + "name": "Cinema Toolkit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "Kepler is a problem-solving environment for the analysis and modeling of scientific data. It simplifies the creation of executable models by using a visual representation of processes, or \u201cscientific workflows\u201d, which display the flow of data among discrete analysis and modeling components. ", + "laborHours": 8320267.2, + "languages": [], + "name": "Kepler", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.kepler-project.org/code/kepler/trunk/licenses.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.kepler-project.org/code/kepler", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "OpenAD is a tool for automatic differentiation (AD) of C/C++ numerical computer programs. For the C/C++ side the entire pipeline is encapsulated in single binary. While the C/C++ tool incarnation shares components with OpenAD its development is a separate effort and it was decided to retain for it the name \"ADIC\" which goes back to the previous generation of tools. ", + "homepageURL": "http://www.mcs.anl.gov/OpenAD", + "laborHours": 0.0, + "languages": [], + "name": "OpenAD", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://mercurial.mcs.anl.gov/ad/OpenAD/file/tip/COPYRIGHT#l1", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.mcs.anl.gov/OpenAD", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "Orio is an annotation system implemented in Python that enables developers to insert annotations into their source code (in C or Fortran). These annotations are used to trigger performance optimizations on a specified code fragment. ", + "laborHours": 117511.2, + "languages": [], + "name": "Orio", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/brnorris03/Orio", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "OSKI is the Optimized Sparse Kernel Interface, a collection of low-level C primitives that provide automatically tuned computational kernels on sparse matrices, for use in solver libraries and applications. ", + "homepageURL": "http://bebop.cs.berkeley.edu/oski", + "laborHours": 0.0, + "languages": [], + "name": "OSKI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://bebop.cs.berkeley.edu/oski/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://bebop.cs.berkeley.edu/oski", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "Matlab interface to PaToH, the Partitioning Tools for Hypergraph, a multilevel hypergraph partitioning tool that provides fast hypergraph partitioning.", + "homepageURL": "http://bmi.osu.edu/~umit/software.html#patoh", + "laborHours": 532.0, + "languages": [], + "name": "PaToH Matlab Interface", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://bmi.osu.edu/~umit/software.html#patoh", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "PLASMA is the Parallel Linear Algebra for Scalable Multi-core Architectures library uses out-of-order scheduling as the basis for scalable and highly efficient computational linear algebra.", + "homepageURL": "https://bitbucket.org/icl/plasma", + "laborHours": 16993.6, + "languages": [], + "name": "PLASMA", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/icl/plasma/src/72d60b0a5d61fe4e31dfbb24065db28adf9ec8e8/LICENSE?at=default&fileviewer=file-view-default", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/icl/plasma", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-11" + }, + "description": "SPRFSim is a code that performs RF/Beam interaction simulations for an ion LINAC. The input files can be constructed from scratch or parsed from PARMELA or TraceWin simulations. The code is written in Python, and relies on matplotlib and numpy. ", + "laborHours": 364.8, + "languages": [ + "Python" + ], + "name": "SPRFSim", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeinstei/SPRFSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "Rapide Surcharge d'Op\u00e9rateur pour la Diff\u00e9rentiation Automatique, a code generator to efficiently compute higher order derivatives via operator overloading. Rapsodia is intended for the computation of higher order derivative information of numerical models written in Fortran, C or C++ by automatic differentiation. ", + "homepageURL": "http://www.mcs.anl.gov/Rapsodia", + "laborHours": 0.0, + "languages": [], + "name": "Rapsodia", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.mcs.anl.gov/Rapsodia", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "SciRun is a problem solving environment for modeling, simulation and visualization of scientific problems; VACET extends the visualization component. ", + "laborHours": 612924.8, + "languages": [], + "name": "SCIRun", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SCIInstitute/SCIRun", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2020-06-01" + }, + "description": "The SUite of Nonlinear and DIfferential/ALgebraic equation Solvers was implemented with the goal of providing robust time integrators and nonlinear solvers that can easily be incorporated into existing simulation codes. The primary design goals were to require minimal information from the user, allow users to easily supply their own data structures underneath the solvers, and allow for easy incorporation of user-supplied linear solvers and preconditioners. ", + "laborHours": 213088.8, + "languages": [], + "name": "SUNDIALS", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "CVODE solves initial value problems for ordinary differential equation (ODE) systems. Part of the SUNDIALS SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. ", + "laborHours": 213088.8, + "languages": [], + "name": "SUNDIALS/CVODE", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "CVODES solves ordinary differential equation (ODE) systems and includes sensitivity analysis capabilities (forward and adjoint). Part of the SUNDIALS SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. ", + "laborHours": 213088.8, + "languages": [], + "name": "SUNDIALS/CVODES", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "IDA solves initial value problems for differential-algebraic equation (DAE) systems. Part of the SUNDIALS SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. ", + "laborHours": 213088.8, + "languages": [], + "name": "SUNDIALS/IDA", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2022-02-01" + }, + "description": "SuperLU is a general purpose library for the direct solution of large, sparse, nonsymmetric systems of linear equations on high performance machines.", + "laborHours": 119426.4, + "languages": [], + "name": "SuperLU", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/xiaoyeli/superlu/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xiaoyeli/superlu", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "High-accuracy water level data are needed to resolve the temporal and spatial hydraulic response to pumping in aquifers. However, the water-level data are typically affected by physical process unrelated to the aquifer pumping such as barometric pressure changes, tides, earthquakes, {\\etc}. We have developed a computational framework to correct for barometric and Earth tide effects using linear regression deconvolution, as an initial guess for a nonlinear residual minimization to account for pumping effects. The pumping effects are predicted using the Theis equation with initialization by Jacob's method. After minimizing the residuals between the observed data and Theis predicted pumping effects, the algorithm estimates storativity and transmissivity of the aquifer. The algorithm also provides information about the measurement accuracy of the collected water-level data. The computational framework CHiPBETA is developed in Python and demonstrated to analyze synthetic and real data.", + "laborHours": 4605.6, + "languages": [ + "Python" + ], + "name": "CHiPBETA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/zem/chipbeta", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-12" + }, + "description": "Anasazi is an extensible and interoperable framework for large-scale eigenvalue algorithms. Abstract interface supports Epetra and other linear algebra objects. To access the Anasazi package, please refer to the packages directory within the main Trilinos GitHub repository. \n\n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/Anasazi", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-12" + }, + "description": "AztecOO provides an object-oriented interface the the well-known Aztec Krylov-space iterative solver library. Uses the Epetra linear algebra services to define vector and operator objects. To access the AztecOO package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/AztecOO", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/tree/master/packages/aztecoo", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2019-04-17" + }, + "description": "kcron is a new package for Fermilab\u2019s Scientific Linux 7, which functions as a utility for getting Kerberos credentials in scheduled jobs. The code is written in BASH and C, and depends on Kerberos, POSIX syslog, and POSIX permissions. ", + "laborHours": 425.6, + "languages": [ + "Bash", + "C" + ], + "name": "kcron", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/scientificlinux/kcron", + "status": "Production", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-07-11", + "metadataLastUpdated": "2019-04-17" + }, + "description": "BigData Express is a high-performance data transfer service for big data. It has several salient features:\n\u2022\tBigData Express WebPortal is a distributed web application designed to support BigData Express services and functions. All BDE web portals use a common single-point sign-on service \u2013 Cilogon service \u2013 to obtain X.509 user certificates for secure access to BDE sites.\n\u2022\tBigData Express scheduler co-schedules Data Transfer Node(s), network, and storage resources for data transfer to achieve optimum performance.\n\u2022\tBigData Express AmoebaNet is a SDN-enabled network service that provide \u201cApplication-aware\u201d network. It allows application to program network at run-time for optimum performance. \n", + "homepageURL": "https://bigdataexpress.fnal.gov", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Java", + "JavaScript", + "Python" + ], + "name": "BigData Express", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bigdataexpress.fnal.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-11", + "metadataLastUpdated": "2018-07-11" + }, + "description": "This is a Fortran 95/2003 implementation of the Parallel Full Approximation Scheme in Space and Time (PFASST), which is a method for the time parallelization of ordinary and partial differential equations.", + "laborHours": 16476.8, + "languages": [], + "name": "libpfasst v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/libpfasst/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "IFPACK provides a suite of object-oriented algebraic preconditioners for the solution of preconditioned iterative solvers. To access the IFPACK package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/IFPACK", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/ifpack/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "Isorropia performs combinatorial scientific computing, with focus on partitioning and load balancing, but also supports coloring and ordering of sparse matrices. Isorropia provides an object-oriented interface to Zoltan using the Epetra linear algebra services. To access the Isorropia package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/Isorropia", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://trilinos.org/download/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "LOCA is the Library of Continuation Algorithms, whose objective is to compute families of solutions to the parameterized nonlinear equation F(x,p) = 0 and their bifurcations. To access the LOCA package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/LOCA", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/nox/Copyright_LOCA.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "ML is the Trilinos multigrid preconditioning package designed to solve large sparse linear systems of equations arising primarily from elliptic PDE discretizations. To access the ML package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/ML", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/ml/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "NOX is the Nonlinear Object-Oriented Solutions package of Trilinos, which enables the robust and efficient solution of the nonlinear equations of the form F(x) = 0. To access the NOX package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/NOX", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/nox/Copyright_NOX.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "Zoltan provides dynamic load balancing for parallel computing with a procedural C interface, with a variety of redistribution algorithms available. 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"languages": [], + "name": "ESGF Openid Relying Party (ORP)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esg-orp", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This repository contains a basic description and layout of the ESFG Publisher, with the latest version including the following updates: Support for CMIP6, integration of PrePARE, PID creation via RabbitMQ, cdf2cim included, and handler for non-netCDF and skip variable scan for multiple cases. http://esgf.github.io/esg-publisher/\n", + "laborHours": 24806.4, + "languages": [], + "name": "ESGF Publisher", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esg-publisher", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This module contains the next generation search functionality for the Earth System Grid Federation, built upon the Apache Solr search engine. 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Metadata records are generated by harvesting a remote metadata source (a hierarchy of THREDDS catalogs, a OAI repository, a CAS metadata catalog). - Searching the Solr engine content via a free text or faceted search.\n", + "laborHours": 12828.8, + "languages": [], + "name": "ESGF Search Component", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esg-search", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "Maven Repo Of ESGF Project Artifacts\n", + "laborHours": 3268.0, + "languages": [], + "name": "esgf-artifacts", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-artifacts", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "Scripts for building ESGF releases, creating repo mirrors and pushing binaries.\u00a0https://esgf.github.io/esgf-build/\n", + "laborHours": 197.6, + "languages": [], + "name": "esgf-build", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-build", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2021-07-06" + }, + "description": "New synthetic biology capabilities hold the promise of dramatically improving our ability to engineer biological systems. 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It also provides tooling that interacts with the data file (index.json) that gets generated, creating HTML pages based on the file with your output embedded in it, and also the ability to upload your results to a server to share with collaborators, sponsors, or anyone who's interested.\n", + "laborHours": 1444.0, + "languages": [], + "name": "Output Viewer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/output_viewer", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This is the repository for doxygen, GLVis - a lightweight OpenGL tool for accurate and flexible finite element visualization developed at Lawrence Livermore National Laboratory. 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It has convenience functions for getting 1st, and second derivatives, including mixed derivatives, but it can be used to get higher derivatives as well just by rerunning the derivers.\n", + "laborHours": 206203.2, + "languages": [], + "name": "C++ PolyFit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CxxPolyFit", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2020-05-27" + }, + "description": "Gotcha is a library that wraps functions. Tools can use gotcha to install hooks into other libraries, for example putting a wrapper function around libc's malloc.\n", + "laborHours": 2204.0, + "languages": [], + "name": "GOTCHA", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GOTCHA", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This is a simple example for how to create a tracer using\u00a0GOTCHA. It is also shows how a CMake project would integrate Gotcha. This includes testing Gotcha via direct invocation and using\u00a0LD_PRELOAD.\n", + "laborHours": 258.4, + "languages": [], + "name": "GOTCHA Tracer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GOTCHA-tracer", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "Flexible and extensible framework to emulate expected exascale architecture characteristics.\n", + "laborHours": 6232.0, + "languages": [], + "name": "Gremlins", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Gremlins", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This is experimental code for prototyping interfaces for dynamic simulations, sensitivity analysis and optimization. Target applications are power grids, but the methodology and the framework could be used in other areas without major modifications.\n", + "laborHours": 1915.2, + "languages": [], + "name": "GridKit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GridKit", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "A highly flexible floating point and integer compression plugin for the HDF5 library using ZFP compression.\n", + "laborHours": 1504.8, + "languages": [], + "name": "H5Z-ZFP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/H5Z-ZFP", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "LLNL Theme for Jekyll Websites.\n", + "laborHours": 136.8, + "languages": [], + "name": "Jekyll-LLNL-Theme", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Jekyll-LLNL-Theme", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "MacPatch simplifies the act of patching and installing software on Mac OS X based systems. 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MacPatch offers features and functionality that provide Mac OS X administrators with best possible patching solution to meet the challenges of supporting Mac OS X in a Workgroup or Enterprise.\n", + "laborHours": 97052.0, + "languages": [], + "name": "MacPatch", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MacPatch", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This processor adds the ability to upload AutoPkg packages to a MacPatch server.\n", + "laborHours": 288.8, + "languages": [], + "name": "MacPatchImporter for AutoPkg", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MacPatch-AutoPKG", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "MemAxes is a tool for visualizing memory access samples acquired by load/store sampling mechanisms like Intel PEBS or AMD IBS. It allows a user to view the data projected into various domains; specifically, the layout of the hardware resources, the code/variables, the dataset domain, and parallel coordinates.\n", + "laborHours": 5198.4, + "languages": [], + "name": "MemAxes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MemAxes", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "Mitos is a library and a tool for collecting sampled memory performance data to view with\u00a0MemAxes.\n", + "laborHours": 684.0, + "languages": [], + "name": "Mitos", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Mitos", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "Symbolic Regression (SR) is a genetic programming algorithm for finding mathematical functions that match a given set of data. It works by evolving an approximation function from a set of primitives. This makes it able to discover the form of the function, in addition to it's coefficients. It has even been shown to be able to discover natural physical laws from experimental data. Given that SR is one of the biggest success stories in genetic programming, it's surprising that there doesn't seem to be an easy-to-use, open-source SR program available. SoRa attempts to fill that gap. With SoRa any user should easily be able to provide experimental data and write a simple configuration file such that SoRa can find a set of good mathematical functions to match the data.\n", + "laborHours": 1550.4, + "languages": [], + "name": "SoRa: Symbolic Regression in Python", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SoRa", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This repository contains companion code and data for the SAE paper \"A Framework for Quantifying Measurement Uncertainties and Uncertainty Propagation in HCCI/LTGC Engine Experiments\", G. Petitpas, M. J. McNenly, R. A. Whitesides.\n", + "laborHours": 410.4, + "languages": [], + "name": "UQ_combustion", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/UQ_combustion", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "The software runs using the Priithon image analysis platform (https://github.com/sebhaase/priithon), which is part of this release. The version of this mac distribution is: Priithon_27_mac-20151127, which expands to a folder named Priithon_27_mac. The paper is the reference source for the wavelet algorithm in this distribution; \"A novel 3D wavelet-based filter for visualizing features in noisy biological data,\" J. Microsc. 219, 43-49 (2005). This distribution has been tested on Mac OS 10.9.5, 10.10.3, and 10.11.1\n", + "laborHours": 1069350.4, + "languages": [], + "name": "WVL", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/WVL", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2019-04-22" + }, + "description": "This software package is the Graphic User Interface (GUI) software component for the Sensor Suitcase Retro-Commissioning project, which is a sensor and analysis system to support monitoring-based retro-commissioning of small commercial buildings, performed by non-experts. \n\nSmall commercial buildings typically do not have the budgets or business economics to allow investing in energy efficiency enhancements the building retro-commissioning provides. In addition, they do not have in-house staff with expertise in building systems who can perform building retro-commissioning or identify energy efficiency improvement opportunities. \n\nThe solution to this problem is to develop a turn-key hardware/software solution (the RCx Sensor Suitcase) that can be used by non-experts to automatically generate low and no-cost energy efficiency rec commendations that will improve building operating costs, occupant comfort and building energy performance. \n\nThis is a joint project between Lawrence Berkeley National Laboratory, leading the development of the software and analysis elements, and Pacific Northwest National Laboratory (PNNL), leading the development of the hardware and sensor elements with an associated table-based configuration support tool. The project is funded by the U.S. Department of Energy. \n\nThis software package was developed as a proof-of-concept prototype for the sensor suitcase software component. The software component was developed with a Microsoft Excel spreadsheet which reads the sensor data and calls a MATLAB DLL to analyze the sensor data.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Retro-Commissioning Sensor Suitcase", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "This is the repository for annie-rose developed at Oak Ridge National Laboratory. 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", + "laborHours": 516.8, + "languages": [], + "name": "orsoqs", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/orsoqs", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "This is the repository for WeldPredictor developed at Oak Ridge National Laboratory. ", + "laborHours": 0.0, + "languages": [], + "name": "WeldPredictor", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/WeldPredictor", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Backstroke is a tool for reversible computation and supports C++11. It is a command line tool for generating reversible C++ source code and is distributed with a runtime library that can maintain all data necessary to support reversibility. The runtime library implements a so called Runtime State Store (RTSS) and is called rtss library. Backstroke implements a technique for incremental state saving (also called incremental check-pointing). Backstroke supports the simulator ROSS for parallel discrete event simulation (PDES) and can establish automatically the reversibility of ROSS models.\n", + "laborHours": 5031.2, + "languages": [], + "name": "backstroke", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/backstroke", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Blockbuster is a movie player designed for playing movies in the \"Streaming Movie\" format on large power walls. 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Hardware req.: Multi-platform; Type of files: Source code, installation instructions other; programmer documentation; user manual; electronic format.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 181138.4, + "languages": [], + "name": "Home Energy Saver v3 (website) and APIs", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2019-04-22" + }, + "description": "The software is a research tool for improving the reproducibility of simulations. It does this by keeping a log file of the input file and the input parameters; it also helps with running the same simulations on different computers such as desktops and clusters. 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SERA can allows creating models of the geometry of the tumor and surrounding tissue from CT or MRI data, and then planning and simulating the treatment of the tumor with Boron Neutron Capture Therapy. 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", + "laborHours": 1276.8, + "languages": [], + "name": "Very Low Overhead Transparent Multilevel ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-VeloC/AXL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-07-20", + "metadataLastUpdated": "2018-07-20" + }, + "description": "Rst2slldes Is a python extension package for the standard docuti!s documentation generation system. Docutlls translates a simple text markup language called reStructuredText Into a variety of formals, Including HTML and PDF. 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Besides slightly modifying Ule HTML output to work with reveal.js, the features added by rst2slldes are the ability to embed video, and to set reveal.js configuration options.", + "laborHours": 456.0, + "languages": [], + "name": "Generate reveal.js slfdeshow from reStructuredText", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/rst2slides", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-07-20", + "metadataLastUpdated": "2018-07-20" + }, + "description": "Generally, for encrypted communication to occur, a root trust must be established (usually In the form of a certificate authority) and used to sign communlcatln1 component's certificates that are used to perform encryption. This process ls rather Involved In a number of manual steps with arcane command syntax. Certlpy wraps the standard Python PyOpenSSL library to simplify the calls to create the above mentioned PKI (public key infrastructure) with both a command line and programming Interface. Certlpy was orlglnally created to automate and manage PKI within the open source JupyterHub project so that It could be deployed safely In Uvennore Computing. JupyterHub Is a collection of software components enabling Interactive python notebooks and reproducible science. To ensure secure communication throuahout, Certlpy signs and Issues certs to each component: enabling encryption and authentication (SSL). ", + "laborHours": 380.0, + "languages": [], + "name": "Simple utility for creat1n1 and signing SSL certificates.", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/certipy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-07-23", + "metadataLastUpdated": "2023-03-02" + }, + "description": "The software package provides several utilities written in LabView. These utilities don't form independent programs, but rather can be used as a library or controls in other labview programs. The utilities include several new controls (xcontrols), VIs for input and output routines, as well as other 'helper'-functions not provided in the standard LabView environment.", + "laborHours": 0.0, + "languages": [], + "name": "Labview utilities", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/atap-ibt-labview-utilities", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-23", + "metadataLastUpdated": "2018-08-13" + }, + "description": "The PIACE software is an approach to the parallel integration and chromosomal expansion (PIACE) of metabolic pathways, which extends the Chemical-Induced Chromosomal Expansion (CIChE) method. The software has little to no application outside the specific use case of a specific approach to isopentanol production and analysis of specific related data.", + "laborHours": 273.6, + "languages": [], + "name": "PIACE Project v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/PIACE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-07-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A lightweight Python package to simulate model interactions", + "laborHours": 1079.2, + "languages": [], + "name": "IMMM-SFA/proxymod", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/proxymod", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-23", + "metadataLastUpdated": "2018-08-13" + }, + "description": "This software performs multi-label segmentation of 2D/3D images. It is highly accurate, results rely on use of an Markov random field (MRF) formulation. It runs in both shared and distributed memory parallel modes. MRF algorithms are powerful tools in image analysis to explore contextual information of data.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Markov Random Fields for Image Segmentation (PMRF-IS) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tperciano/PMRF-IS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-07-24", + "metadataLastUpdated": "2018-07-24" + }, + "description": "OJINN Is an easy-to-use deep neural network model that requires fewer user-specified hyper-parameters than traditional neural networks. The algorithm leverages decision trees trained on the data to determine an appropriate deep neural network architectures and weight Initializations. Optional functions also select the learning rate, batch size. and number of training Iterations necessary to create an accurate model.", + "laborHours": 562.4, + "languages": [], + "name": "Deep Jointly-Informed neural networks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DJINN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-07-25", + "metadataLastUpdated": "2018-07-25" + }, + "description": "Owsim is a tool for generating minor modifications to the reference results so some types of minor changes in strategy may be evaluated using the same tool (MAF) without the need to produce complete opsim simulations. The specific modification included in the initial version of owsim is for triggered follow-up of transient events, but the tool is general enough to support different kinds of modifications as well.", + "laborHours": 12479.2, + "languages": [ + "Python" + ], + "name": "owsim", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LSSTDESC/ObsStrat", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-07-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The IGCAPT allows electric utility personnel to perform a static analysis of their communications network supporting smart grid architectures from a network utilization and performance standpoint. IGCAPT is meant to be a \"first order\" planning tool - the tool will accommodate estimates and best available data alongside default settings, which the user can then improve over time.", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "IGCAPT", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/IGCAPT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-25", + "metadataLastUpdated": "2018-07-27" + }, + "description": "This creation is used for standard energy performance tests of household and commercial refrigerators and other refrigeration equipment. It automates the door opening at a preset duration and velocity specified by the test procedure.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Universal Automated Refrigerator Door Opener", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ahakim@pppl.gov" + }, + "date": { + "created": "2018-07-26", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Gkeyll v2.0 (also known as Gkyl, or G2) is a computational plasma physics code mostly written in LuaJIT, with time-critical parts written in C++. Gkyl contains solvers for gyrokinetic equations, Vlasov-Maxwell equations, and multi-fluid equations. Gkeyll contains ab-initio and novel implementations of a number of algorithms, and perhaps is unique in using a JIT compiled typeless dynamic language for its implementation.\n\nOne of the main innovations in Gkeyll is the blurring of boundaries between user written code (i.e. input files) and backend solver code. In fact, there is no difference: the front-end and back-end are written in the same programming language, opening up a very powerful way of composing simulations. All solver objects (grids, data-structures, updaters) can be queried, modified and controlled by the user, allowing complete control over the full simulation cycle. The use of the highly optimized Just-in-Time (JIT) compiled LuaJIT as the main programming language ensures that user written code remains highly efficient. Of course, core kernels can always be written in C/C++ and hooked in via LuaJIT\u2019s powerful FFI facilities.", + "homepageURL": "https://theory.pppl.gov/research/research.php?rid=10#h44", + "laborHours": 0.0, + "languages": [ + "C++", + "C++", + "Lua" + ], + "name": "Gkeyll 2.0", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://theory.pppl.gov/research/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://theory.pppl.gov/research/research.php?rid=10#h44", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "version": "2.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-26", + "metadataLastUpdated": "2018-07-27" + }, + "description": "The software, titled Cryomodule-On-Chip (CMOC), simulates a cryomodule used for low-level RF acceleration in superconducting cavities. The model includes a state-space model of the accelerating fields inside the cavity, the mechanical resonances inside a cryomodule, and their interactions.", + "laborHours": 21690.4, + "languages": [], + "name": "CryoModule On Chip (CMOC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/CMOC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-07-26", + "metadataLastUpdated": "2018-08-03" + }, + "description": "MPAS-Analysis is a software package designed to process and analyze output data of the Model for Prediction Across Scales (MPAS) Ocean, Sea-Ice and Land-Ice model components. It is built primarily on the python language, with remapping of model unstructured-grid fields onto regular grids performed through the ESMF package, and with the computation of climatologies performed through the NCO package. The main purpose of MPAS-Analysis is to analyze the MPAS simulations in terms of ocean and ice metrics, in comparison with available observations, and therefore provide an accurate model evaluation and simulation assessment.", + "laborHours": 20489.6, + "languages": [], + "name": "MPAS-Analysis", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MPAS-Dev/MPAS-Analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ngorelen@pppl.gov" + }, + "date": { + "created": "2018-07-27", + "metadataLastUpdated": "2018-07-27" + }, + "description": "NOVA is a suite of codes including the linear ideal eigenmode solver to find the solutions of ideal magnetohydrodynamic (MHD) system of equations, including such effects as plasma compressibility and realistic tokamak geometry. The kinetic post-processor of the suite, NOVA-K, analyses those solutions to find their stability properties. NOVA-K evaluates the wave particle interaction of the eigenmodes such as Toroidal Alfv\u00e9n Eigenmodes (TAEs) or Reversed Shear Alfv\u00e9n Eigenmodes (RSAEs) by employing the quadratic form with the perturbed distribution function coming from the drift kinetic equations. In computations of the hot ion contribution to the growth rate NOVA-K makes use of the constant of motion to represent the hot particle drift orbits. \nNOVA is routinely used for AE structure computations and comparisons with the experimentally observed instabilities [M. A. Van Zeeland et al., Phys. Rev. Lett. 97, 135001 (2006), G. J. Kramer, Phys. Plasmas 13, 056104 (2006)]. The main limitations of NOVA code are caused by neglecting thermal ion finite Larmor radius (FLR), toroidal rotation, and drift effects for the eigenmode computations. Therefore it can not describe accurately radiative damping for example. Finite element methods are used in radial direction and Fourier harmonics are used in poloidal and toroidal directions.\n\nNOVA-K is able to predict various kinetic growth and damping rates perturbatively, such as the phase space gradient drive from energetic particles, continuum damping, radiative damping, ion/electron Landau damping and trapped electron collisional damping. ", + "homepageURL": "https://theory.pppl.gov/research/research.php?rid=10#h45", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "NOVA/NOVA-K", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://theory.pppl.gov/research/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://theory.pppl.gov/research/research.php?rid=10#h45", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "LMT is a distributed system that provides a \"top\"-like display of the activity levels of the server-side (MDS, OSSes, and LNET routers) nodes of one or more Lustre-based filesystems. It is possible to watch server metrics in real time, and to graph past behavior. The clients provide this capability, but it is also possible to directly mine the MySQL database, e.g. with SQL scripts and GNU plot.\n", + "laborHours": 8253.6, + "languages": [], + "name": "LMT (Lustre Monitoring Tool)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lmt", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "This repository contains LLNL's branches of Lustre.\n", + "laborHours": 450832.0, + "languages": [], + "name": "lustre", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lustre", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Some lustre-related scripts and utilities in use at LLNL.\n", + "laborHours": 1033.6, + "languages": [], + "name": "lustre-tools-llnl", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lustre-tools-llnl", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2020-02-05" + }, + "description": "Magpie contains a number of scripts for running Big Data software in HPC environments, including Hadoop and Spark. There is support for Lustre, Slurm, Moab, Torque. and LSF.\n", + "laborHours": 52607.2, + "languages": [], + "name": "Magpie", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/magpie", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Used for testing the metadata performance of a file system.\n", + "laborHours": 1565.6, + "languages": [], + "name": "mdtest", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mdtest", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Melodee (Modular Expression Language for Ordinary Differential Equation Editing) is a new language for ODE modeling and development. It has been designed to make it easy for domain experts to write modular equation systems. Using a familiar Matlab-like syntax, modelers can describe their systems of interests and combine them in new and novel ways at run time. Existing models can easily be converted to MELODEE because of its familiar semantics and syntax.\n", + "laborHours": 2325.6, + "languages": [], + "name": "Melodee ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/melodee", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2019-07-11" + }, + "description": "Mirror of MFEM - a lightweight, general, scalable C++ library for finite element methods. MFEM is a modular parallel C++ library for finite element methods. Its goal is to enable the research and development of scalable finite element discretization and solver algorithms through general finite element abstractions, accurate and flexible visualization, and tight integration with the hypre library.\n", + "homepageURL": "https://mfem.org", + "laborHours": 0.0, + "languages": [], + "name": "MFEM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://mfem.org", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "A light-weight MPI profiler.\u00a0http://llnl.github.io/mpiP\n", + "laborHours": 13558.4, + "languages": [], + "name": "mpiP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mpiP", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Allows safer access to model specific registers (MSRs).", + "laborHours": 2614.4, + "languages": [], + "name": "msr-safe", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/msr-safe", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Pynamic is a benchmark designed to test a system's ability to handle the Dynamic Linking and Loading requirements of Python-based scientific applications. This benchmark is developed to add a workload to our testing environment, workload that represents a newly emerging class of DLL behaviors. Pynamic builds on pyMPI, an MPI extension to Python. Our augmentation includes a code generator that automatically generates Python C-extension dummy codes and a glue layer that facilitates linking and loading of the generated dynamic modules into the resulting pyMPI. Pynamic is configurable, enabling modeling the static properties of a specific code. It does not, however, model any significant computations of the target and hence it is not subjected to the same level of control as the target code. In fact, HPC computer vendors and tool developers will be encouraged to add it to their testing suite once the code release is completed. An ability to produce and run this benchmark is an effective test for validating the capability of a compiler and a linker/loader as well as an OS kernel and other runtime systems of HPC computer vendors. In addition, the benchmark is designed as a stress test case for code development tools. 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This effort has begun the conversion of these TSG calculations into a Java application format from the original Excel spreadsheets. The original set of Excel spreadsheet calculation aids do not provide the same level of integration, usability, intuitiveness, and speed as a well-designed Java-based application. Achieving the best combination of these characteristics is highly important in an emergency response tool to mitigate a high stress situation and allow a faster, more robust response. Integration in a Java-based application allows for data to be better organized and communicated during the incident.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Technical Support Guidelines Calculator Tool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2018-10-23" + }, + "description": "HALucinator enables execution of firmware on a generic system emulation through interception of hardware abstraction library functions. This enables it to intercept the execution of functions that would interact with external hardware and to model the external hardware at a high-level of abstraction while maintaining correct firmware behavior. ", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HALucinator v. 0.1 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2024-08-07" + }, + "description": "QuESt is an open source, Python-based application suite for energy storage simulation and analysis. The initial release will include an application for energy storage valuation, an analysis where the maximum revenue of a hypothetical energy storage device is estimated using historical energy market data. This is done by determining the sequence of state of charge management actions that optimize revenue generation, assuming perfect foresight of the historical data. The initial release will also include a utility to obtain historical data directly from supported market operating entities for use in analysis. More applications will be added as they are developed. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python", + "CSS", + "HTML", + "Batchfile", + "kvlang", + "JavaScript" + ], + "name": "QuEST v. 1.6", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/snl-quest", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.6" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2018-09-07" + }, + "description": "The goal of this track is to develop blockchain-based ledgering solutions to log and query the user activities of accessing genomic datasets (e.g., GTEx) across multiple sites.", + "laborHours": 121.6, + "languages": [ + "Python" + ], + "name": "iDASH 2018: Task 1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.github.com/sandialabs/idash2018task1", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2018-08-27", + "metadataLastUpdated": "2018-08-27" + }, + "description": "A software suite for applying hierarchical matrices, specifically the \"hierarchically off-diagonal low rank\" (HODLR) format, to Gaussian process computing", + "laborHours": 1717.6, + "languages": [], + "name": "KernelMatrices.jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/cgeoga/kernelmatrices.jl", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-08-27", + "metadataLastUpdated": "2018-08-28" + }, + "description": "High Performance Computing clusters and supercomputers are expensive and complex systems to manage. The software tools to manage these systems are also aging to the point where they are no longer actively developed and their methodology is antiquated. There has been a surge of new methodologies and software tools developed by the cloud providers to maximize availability of services and scalability of server deployment. The authors would like to utilize these new software tools to distribute our proof of concept, named Kraken, that will be responsible for booting and managing LANL's HPC systems in the future", + "laborHours": 91.2, + "languages": [], + "name": "System Administration Tools", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/fast-image-creation", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2018-10-23" + }, + "description": "The Scribetabletop recorder allows usersto visually record and play backscenariosdeveloped during atabletop exercise. It offers a set of tools to visualize,organize, record data, and make decisions while usersdevelop scenarios.Datacan be viewed in both 2D and 3D and played backin real-time or at various speeds", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "SCRIBE 3D-Tabletop Recorder v. 1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Collection of Linux scripts and libraries to aid in common administration tasks and automation. Scripts are for LDAP, nagios, ansible, automatic emailing, license managers, and supporting functions", + "laborHours": 0.0, + "languages": [], + "name": "LinuxSA", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholabUnsupported/LinuxSA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2023-03-15" + }, + "description": "When developing Asp.Net Core applications for deployment in Linux or Docker environments, applications are no longer able to be configured to use Windows Authentication. Many organizations have an ADFS implementation that applications can authenticate off of, but during development there are issues with ADFS. This is a small set of applications that represent a dummy ADFS implementation that removes restrictions while developing locally.", + "laborHours": 0.0, + "languages": [], + "name": "FakeADFS", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/FakeADFS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2023-03-15" + }, + "description": "BlackBear is a MOOSE-based code for simulating degradation processes in concrete and other structural materials.", + "laborHours": 6110.4, + "languages": [], + "name": "Blackbear", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/blackbear", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2024-07-19" + }, + "description": "ACES is a modified version of LLVM for ARMv7-M micro controllers that enables automatic application of compartments to bare-metal system code. It breaks the single monolithic binary of these systems into multiple execution domains using a developer selected policy. This increases the difficulty of compromising the entire system, as the data, code, and peripherals accessible at any given point in execution limited to the subset identified by the policy.", + "laborHours": 1070247.2, + "languages": [ + "C++", + "Shell", + "HTML", + "C", + "Assembly", + "Rich Text Format" + ], + "name": "Automatic Compartments for Embedded Systems", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/ACES?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ACES", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-08-29", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The HPC Software stack testing framework", + "laborHours": 42240.8, + "languages": [], + "name": "hpcswtest", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/hpcswtest", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2020-09-01" + }, + "description": "ImagingSIMS is an open-source project for loading, analyzing, and visualizing secondary ion mass spectrometry (SIMS) data.", + "laborHours": 111887.2, + "languages": [], + "name": "ImagingSIMS/ImagingSIMS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ImagingSIMS/ImagingSIMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a JavaScript library for a storyline layout\nalgorithm. Storylines are adept at communicating\ncomplex change by encoding time on the x-axis and\nusing the proximity of lines in the y direction to\nrepresent interaction between entities. The library in\nthis disclosure takes as input a list of objects\ncontaining an id, time, and state. The output is a\ndata structure that can be used to conveniently\nrender a storyline visualization. Most importantly, the\nlibrary computes the y-coordinate of the entities over\ntime that decreases layout artifacts including\ncrossings, wiggles, and whitespace. This is\naccomplished through multi-objective, multi-stage\noptimization problem, where the output of one stage\nproduces input and constraints for the next stage.", + "laborHours": 15671.2, + "languages": [], + "name": "pnnl/sven", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/sven", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2018-08-30" + }, + "description": "The SDET Tool is used to create open-access power\ngrid data sets and facilitate updates of these data\nsets by the community. Pacific Northwest National\nLaboratory (PNNL) and its power industry and\nsoftware vendor partners are developing an\ninnovative sustainable data evolution technology\n(SDET) to create open-access power grid datasets\nand facilitate updates to these datasets by the power\ngrid community. The objective is to make this a\nsustained effort within and beyond the ARPA-E\nGRID DATA program so that the datasets can evolve\nover time and meet the current and future needs for\npower grid optimization and potentially other\napplications in power grid operation and planning.", + "homepageURL": "https://egriddata.org/dataset/sdet-tool", + "laborHours": 152.0, + "languages": [], + "name": "sdet-tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://egriddata.org/dataset/sdet-tool", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Multi-Speak - Secure Protocol Enterprise Access Kit", + "laborHours": 159189.6, + "languages": [], + "name": "pnnl/ms-speak", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ms-speak", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2018-08-31" + }, + "description": "BELLA is a long-read overlapper and read-to-read aligner that exploits novel approaches for selecting reliable k-mer seeds for filtering and for detecting overlapping read pairs to reconstruct the whole genome. BELLA uses a sparse matrix-matrix multiplication for high-performance overlap detection and then performs pairwise alignment on the overlapping read pairs. BELLA can be built with different pre-existing aligners to use on each read pair, so precision rates are determined by those aligners. Our evaluations include real and synthetic datasets with varying size and complexity and include recall, precision, and running time. BELLA's overlap detection retains nearly all true alignments, with recall rates that exceed other aligners, yet it filters enough read pairs that the running time, including pairwise alignments, is closer to tools that only perform overlapping and is significantly faster than tools that also perform alignment", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper (BELLA) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/aydozz/longreads", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-08-31", + "metadataLastUpdated": "2018-09-04" + }, + "description": "This software comprises a portable, open-source implementation of a runtime library to support applications written in the Unified Parallel C (UPC) language. This library implements the UPC-specific functionality, including shared-memory allocation and distributed locks. The network-dependent functionality is implemented as a thin wrapper around the separate GASNet (Global-Address Space Networking) library, which is required for operation. This software implements the \"Berkeley UPC Runtime Specification\", which is targeted by at least four separate UPC compiler front-ends. The implementation is highly portable and runs over hardware ranging from laptops to custom supercomputers. An external library is required for certain local memory allocation operations; a well-defined interface allows for multiple implementations of this library, but at present the \"umalloc\" library from LBNL is the only compatible implementation.", + "laborHours": 91230.4, + "languages": [], + "name": "Berkeley Unified Parallel C (UPC) runtime library", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upc-runtime", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-04" + }, + "description": "This high-performance ray tracing library provides very fast rendering, compact code, type flexibility via C++ 'generic programming' techniques, and ease of use through an application programming interface (API) that functions independently of any GUI, on-screen display, or other enclosing application. Kip supports constructive solid geometry models based on any of several built-in shapes and operators and allows for new, user-defined shapes and operators. Additional features include basic texturing, input/output of models using a simple human-readable file format with full error checking and detailed diagnostics, and support for shared data parallelism. Kip is written in pure, ANSI Standard C++, is entirely platform independent, and is very easy to use, as it requires no build system, configuration or installation scripts, wizards, special preprocessing, makefiles, or external libraries.", + "laborHours": 10001.6, + "languages": [], + "name": "Kip, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/staleyLANL/kip", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-04" + }, + "description": "Metamesh is a general-purpose C++ language library for creating data structures that represent meshes. An important difference between Metamesh and other \"mesh\" libraries is that Metamesh does not provide a specific mesh format, in the usual sense, or tools or a GUI by which users build specific meshes. Rather, it provides a mechanism by which mesh formats themselves can be built, based on their constituent parts and the relationships between them.Consider that a mesh in up to three space dimensions can, in principle, contain nodes (0d entities, or points), edges (1d entities), faces (2d entities), and cells (3d, or volumetric, entities). A node might be defined in terms of (x), (x,y), or (x,y,z) in Cartesian coordinates; or perhaps something else, in a different coordinate system. An edge is typically defined from two nodes; say, \"edge E goes from node A=(ax,ay) to node B=(bx,by).\" Faces can reasonably be defined in terms of nodes or edges, and cells in terms of nodes, edges, or faces. Note also that someone might wish to support general faces or cells, or only specific variants - say, triangular faces and tetrahedral cells, or quadrilateral faces and hexahedral cells. Or, perhaps, both triangular and quadrilateral faces (but no others), with prisms for each cell. Consider also that a mesh can have the same or a lesser dimension than that of its enclosing space. In 3d, for example, one could have a full 3d mesh, a 2d \"sheet\" mesh with no cells, a 1d \"parametrized curve\" with neither faces nor cells, or even a 1d \"point cloud.\" And, in addition to defining a mesh scheme, a user might wish to place additional data onto one or more mesh entities. Imagine, for example, a velocity at each node, a flux across each edge or face, and a mass or average density per cell. Metamesh supports all of this, through the use of C++ class and function templates, and template metaprogramming techniques. Programmers begin with constructs that Metamesh provides (or, users can define their own), and assemble them in particular ways in order to create particular mesh formats. Metamesh then provides functionality automatically to meshes that are constructed in this manner. Finally, Metamesh provides very general functions for spinning, extruding, visualizing, and performing input/output of whatever meshes a user builds with it.", + "laborHours": 7052.8, + "languages": [], + "name": "Metamesh, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/staleyLANL/metamesh", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2020-06-01" + }, + "description": "There is a sea (mar is Spanish for sea) of data out there that needs to be handled efficiently. Object Stores are filling the hole of managing large amounts of data efficiently. However, in many cases, and our HPC case in particular, we need a traditional file (POSIX) interface to this data as HPC I/O models have not moved to object interfaces, such as Amazon S3, CDMI, etc.Eventually Object Store providers may deliver file interfaces to their object stores, but at this point those interfaces are not ready to do the job that we need done. MarFS will glue together two existing scalable components: a file system's scalable metadata component that provides the file interface; and existing scalable object stores (from one or more providers). There will be utilities to do work that is not critical to be done in real-time so that MarFS can manage the space used by objects and allocated to individual users.", + "laborHours": 10244.8, + "languages": [], + "name": "MarFS, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mar-file-system/marfs", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-05" + }, + "description": "This program is a portable, open-source, compiler for the UPC language. It is based on the Open64 framework and has extensive support for optimizations. This compiler operates by translating UPC into ANSI/ISO C for compilation by a native compiler and linking with the UPC Runtime Library. This design eases portability to both shared- and distributed-memory parallel architectures. For proper operation it requires the \"Berkeley Unified Parallel C (UPC) Runtime Library\" and its dependencies. \n", + "laborHours": 2197342.4, + "languages": [], + "name": "Berkeley Unified Parallel C (BUPC) Compiler", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upc-translator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-04" + }, + "description": "The Performance Prediction Toolkit (PPT), is a scalable co-design tool that contains the hardware and middle-ware models, which accept proxy applications as input in runtime prediction. PPT relies on Simian, a parallel discrete event simulation engine in Python or Lua, that uses the process concept, where each computing unit (host, node, core) is a Simian entity. Processes perform their task through message exchanges to remain active, sleep, wake-up, begin and end. ", + "laborHours": 45478.4, + "languages": [], + "name": "Performance Prediction Toolkit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PPT", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-04" + }, + "description": "Quinoa is a set of computational tools that enables research and numerical analysis in fluid dynamics. At this time it remains a test-bed to experiment with various algorithms using fully asynchronous runtime systems. Currently, Quinoa consists of the following tools: (1) Walker, a numerical integrator for systems of stochastic differential equations in time. It is a mathematical tool to analyze and design the behavior of stochastic differential equations. It allows the estimation of arbitrary coupled statistics and probability density functions and is currently used for the design of statistical moment approximations for multiple mixing materials in variable-density turbulence. (2) Inciter, an overdecomposition-aware finite element field solver for partial differential equations using 3D unstructured grids. Inciter is used to research asynchronous mesh-based algorithms and to experiment with coupling asynchronous to bulk-synchronous parallel code. Two planned new features of Inciter, compared to the previous release (LA-CC-16-015), to be implemented in 2017, are (a) a simple Navier-Stokes solver for ideal single-material compressible gases, and (b) solution-adaptive mesh refinement (AMR), which enables dynamically concentrating compute resources to regions with interesting physics. Using the NS-AMR problem we plan to explore how to scale such high-load-imbalance simulations, representative of large production multiphysics codes, to very large problems on very large computers using an asynchronous runtime system. (3) RNGTest, a test harness to subject random number generators to stringent statistical tests enabling quantitative ranking with respect to their quality and computational cost. (4) UnitTest, a unit test harness, running hundreds of tests per second, capable of testing serial, synchronous, and asynchronous functions. (5) MeshConv, a mesh file converter that can be used to convert 3D tetrahedron meshes from and to either of the following formats: Gmsh, http://www.geuz.org/gmsh, Netgen, http://sourceforge.net/apps/mediawiki/netgen-mesher, ExodusII, http://sourceforge.net/projects/exodusii, HyperMesh, http://www.altairhyperworks.com/product/HyperMesh.", + "laborHours": 130020.8, + "languages": [], + "name": "Quinoa, Version 0.2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/quinoacomputing/quinoa", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2020-09-01" + }, + "description": "This package provides a basic toolkit for model validation and forecast verification, implemented in Python. The code is designed to aid model validation tasks for users of the standard scientific python stack. Functions and classes are provided to calculate a broad range of metrics for continuous and categorical predictions.", + "laborHours": 866.4, + "languages": [], + "name": "PyForecastTools", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/drsteve/PyForecastTools", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2018-09-07" + }, + "description": "MELCOR is a severe accident code developed at Sandia National Laboratories for the US Nuclear Regulatory Commission. It is an integral code with models describing the important physics that come into play during a severe accident. Such physics includes, but is not limited to, the heat-up of reactor core components, thermal hydraulics, oxidation of materials, core degradation, release of fission products from components and the transport of those fission products and other important aerosols through a reactor system, molten core/concrete interactions, and modeling of reactor safety systems. MELCOR modeling is general and flexible, using a \u201ccontrol volume\u201d approach to describe the plant system which has also allowed it to successfully model spent fuel pools.", + "homepageURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "MELCOR", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrc.gov/about-nrc/regulatory/research/obtainingcodes.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "2" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2018-09-07" + }, + "description": "MACCS is the NRC code used to estimate the offsite radiological consequences of potential severe accidents at nuclear power plants (NPPs). The code is used to perform probabilistic health and economic consequence assessment of hypothetical releases of radioactive material. Atmospheric dispersion and transport, wet and dry deposition, probabilistic treatment of meteorology, environmental transfer, countermeasure strategies, dosimetry, health effects, site specific characteristics, evacuation/sheltering activities, and economic impacts are addressed in the code.", + "homepageURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "WinMACCS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrc.gov/about-nrc/regulatory/research/obtainingcodes.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2018-09-07" + }, + "description": "MelMACCS is the interface tool that allows MELCOR plot files to be post processed to create MACCS source term data that can be imported directly into WinMACCS", + "homepageURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "laborHours": 0.0, + "languages": [ + "Visual Basic" + ], + "name": "MelMACCS ver. 2.0.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrc.gov/about-nrc/regulatory/research/obtainingcodes.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Archive Walker Software to read and examine PMU data to detect events and conditions for further analysis.", + "laborHours": 219837.6, + "languages": [], + "name": "pnnl/archive_walker", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/archive_walker", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2020-10-29" + }, + "description": "GridAPPS-D provides a method for developers to run their new applications on a real-time simulator with extensive modeling and tool support. GridAPPS-D is built around standard data models like the CIM. It readily interfaces to existing software products, which may also 1) use components of GridAPPS-D and 2) supplement or replace the built-in distribution simulator, facilitating the deployment of new ADMS applications to existing software products.", + "laborHours": 70862.4, + "languages": [], + "name": "GRIDAPPSD/GOSS-GridAPPS-D", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GRIDAPPSD/GOSS-GridAPPS-D", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2018-09-05" + }, + "description": "GASNet is a language-independent, networking middleware layer that provides network-independent, high-performance communication primitives including Remote Memory Access (RMA) and Active Messages (AM). It has been used to implement parallel programming models and libraries such as UPC, Co-Array Fortran, Titanium, Legion, Chapel, and many others. The interface is primarily intended as a compilation target and for use by runtime library writers (as opposed to end users), and the primary goals are high performance, interface portability, and expressiveness. GASNet stands for \"Global-Address Space Networking\". \n\n", + "laborHours": 93632.0, + "languages": [], + "name": "Global-Address Networking (GASNet-1) Library", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/gasnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The XFEMClipPartialElements tool is a plugin for the open-source Paraview visualization software to correctly visualize results with discontinuities represented using the extended finite element method (XFEM) in MOOSE-based codes.", + "laborHours": 182.4, + "languages": [], + "name": "XFEMParaviewPlugin", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/XFEMParaviewPlugin", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2018-09-07" + }, + "description": "This software provides mechanical/structural explanations for machine learning in chemistry.", + "laborHours": 2097.6, + "languages": [ + "Python" + ], + "name": "FeatureCreature", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/FeatureCreature", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The Sandia Strehl Calculator is designed to calculate the Gibson and Lanni point spread function (PSF), Strehl ratio, and ensquared energy, allowing non-design immersion, coverslip, and sample layers. It also uses Abbe number calculations to determine the refractive index at specific wavelengths when given the refractive index at a different wavelength and the dispersion. The theory behind the code is all fully developed in standard optics references. The novelty of the code is packaging it in a format that is accessible to general microscope users, not limited to individuals with expertise in both optics and computer programming.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Sandia Strehl Calculator Version", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Strehl", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Arcus is a library developed and used within an internally developed network configuration tool. Arcus is being open sourced not the configuration tool.", + "laborHours": 4301.6, + "languages": [ + "C#", + "Powershell" + ], + "name": "Arcus v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/arcus", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2024-07-19" + }, + "description": "This Python package provides high-performance implementations of the functions and examples presented in \"BiEntropy - The Approximate Entropy of a Finite Binary String\" by Grenville J. Croll, presented at ANPA 34 in 2013. https://arxiv.org/abs/1305.0954\n\nAccording to the paper, BiEntropy is \"a simple algorithm which computes the approximate entropy of a finite binary string of arbitrary length\" using \"a weighted average of the Shannon Entropies of the string and all but the last binary derivative of the string.\"", + "laborHours": 2021.6, + "languages": [ + "C", + "Python", + "Makefile" + ], + "name": "BiEntropy for Python v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/bientropy", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2019-07-30" + }, + "description": "This software adds a data handling module to the GNU Radio (GR) software defined radio (SDR) framework as well as some general-purpose function blocks (filters, metadata control, etc). This software is useful for processing bursty RF transmissions with GR, and serves as a base for applying SDR signal processing techniques to a whole burst of data at a time, as opposed to streaming data which GR.", + "laborHours": 11536.8, + "languages": [ + "C++", + "Python" + ], + "name": "GNU Radio Sandia Utilities v. 1.6", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gr-pdu_utils", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.6" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2024-09-18" + }, + "description": "R code that performs the analysis of a data set presented in the paper \u2018Leveraging Multiple Statistical Methods for Inverse Prediction in Nuclear Forensics Applications\u2019 by Lewis, J., Zhang, A., Anderson-Cook, C. It provides functions for doing inverse predictions in this setting using several different statistical methods. The data set is a publicly available data set from a historical Plutonium production experiment.", + "laborHours": 349.6, + "languages": [ + "R" + ], + "name": "Analysis Code - Data Analysis in 'Leveraging Multiple Statistical Methods for Inverse Prediction in Nuclear Forensics Applications' (LMSMIPNFA) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/LMSMIPNFA", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2018-09-06" + }, + "description": "Loop-Less Coe Generator for small even size matrices multiplication for AMD processor systems. Matrices are stored in double precision row-wise. Defining the sizes of double precision matrices required. Output is an assembly listing file. Stored as a text file. ", + "laborHours": 0.0, + "languages": [], + "name": "LOOP-LESS CODE GENERATOR FOR WELL-DEFINED COMPUTATIONAL TASKS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jesseYhWang/LLCGX", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2020-06-01" + }, + "description": "GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of Partitioned Global Address Space (PGAS) runtime systems and other alternative models in future exascale machines. The library is an evolution of the popular GASNet communication system, building upon over 15 years of lessons learned. \n\nGASNet is a language-independent, networking middleware layer that provides network-independent, high-performance communication primitives including Remote Memory Access (RMA) and Active Messages (AM). It has been used to implement parallel programming models and libraries such as UPC, Co-Array Fortran, Titanium, Legion, Chapel, and many others. The interface is primarily intended as a compilation target and for use by runtime library writers (as opposed to end users), and the primary goals are high performance, interface portability, and expressiveness. GASNet stands for \"Global-Address Space Networking\". \n", + "homepageURL": "http://gasnet.lbl.gov", + "laborHours": 235858.4, + "languages": [], + "name": "Global-Address Space Networking for Exascale", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://gasnet.lbl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-07", + "metadataLastUpdated": "2020-06-01" + }, + "description": "UPC++ is a C++11 library providing classes and functions that support Partitioned \nGlobal Address Space (PGAS) programming. We are revising the library under the auspices of the DOE's Exascale Computing Project, to meet the needs of applications requiring PGAS support. UPC++ is intended for implementing elaborate distributed data structures where communication is irregular or fine-grained. The UPC++ interfaces for moving non-contiguous data and handling memories with different optimal access methods are composable and similar to those used in conventional C++. The UPC++ programmer can expect communication to run at close to hardware speeds. \n\nThe key facilities in UPC++ are global pointers, that enable the programmer to express \nownership information for improving locality, one-sided communication, both put/get and RPC, futures and continuations. Futures capture data readiness state, which is useful in making scheduling decisions, and continuations provide for completion handling via callbacks. Together, these enable the programmer to chain together a DAG of operations to execute asynchronously as high-latency dependencies become satisfied.\n", + "laborHours": 20702.4, + "languages": [], + "name": "UPC++ V1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upcxx/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-10", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The DOE has funded Sandia National Labs (SNL) to develop an open-source modeling tool to guide the design and layout of marine hydrokinetic (MHK) arrays to maximize power production while minimizing environmental effects. This modeling framework simulates flows through and around a MHK arrays while quantifying environmental responses. As an augmented version of the Dutch company, Deltares\u2019s, environmental hydrodynamics code, Delft3D, SNL-Delft3D-CEC-FM includes a new module that simulates energy conversion (momentum withdrawal) by MHK current energy conversion devices with commensurate changes in the turbulent kinetic energy and its dissipation rate. SNL-Delft3D-CEC-FM modified the Delft3D flexible mesh flow solver, DFlowFM. The Following is a description of Deltares\u2019s open-source code Delft3D from which Delft3D-CEC is built upon. \u201cDelft3D is a world leading 3D modeling suite to investigate hydrodynamics, sediment transport and morphology and water quality for fluvial, estuarine and coastal environments. As per 1 January 2011, the Delft3D flow (FLOW), morphology (MOR) and waves (WAVE) modules are available in open source. The software is used and has proven his capabilities on many places around the world, like the Netherlands, USA, Hong Kong, Singapore, Australia, Venice, etc. The software is continuously improved and developed with innovating advanced modelling techniques as consequence of the research work of our institute and to stay world leading. The FLOW module is the heart of Delft3D and is a multi-dimensional (2D or 3D) hydrodynamic (and transport) simulation program which calculates non-steady flow and transport phenomena resulting from tidal and meteorological forcing on a curvilinear, boundary fitted grid or spherical coordinates. In 3D simulations, the vertical grid is defined following the so-called sigma coordinate approach or Z-layer approach. The MOR module computes sediment transport (both suspended and bed total load) and morphological changes for an arbitrary number of cohesive and non-cohesive fractions. Both currents and waves act as driving forces and a wide variety of transport formulae have been incorporated. For the suspended load this module connects to the 2D or 3D advection-diffusion solver of the FLOW module; density effects may be taken into account. An essential feature of the MOR module is the dynamic feedback with the FLOW and WAVE modules, which allow the flows and waves to adjust themselves to the local bathymetry and allows for simulations on any time scale from days (storm impact) to centuries (system dynamics). It can keep track of the bed composition to build up a stratigraphic record. The MOR module may be extended to include extensive features to simulate dredging and dumping scenarios. For over 30 years Deltares has been in the forefront of these types of combined morphological simulation techniques.\u201d", + "laborHours": 1149545.6, + "languages": [ + "Fortran", + "C++", + "Shell", + "C", + "MATLAB", + "Makefile" + ], + "name": "Sandia's Current Energy Conversion module for Flexible-Mesh Delft3D flow solver v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SNL-Delft3D-FM-CEC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-10", + "metadataLastUpdated": "2018-09-13" + }, + "description": "Software is an online self-service portal for testing M&V methods/tools using buildings' interval meter data. After registering as a user in the portal, that user can download test data files, run those test data files through their own M&V software, and then upload software modeling results to the online portal as a csv file. After the user has uploaded their modeling results the portal will develop statistical accuracy metrics for that M&V tool. The online portal will summarize test results for some or all of the submitted tests. This online portal has been developed by LBNL, and we have been collaborating with the Efficiency Valuation Organization (EVO) with the objective of EVO managing the portal as an ongoing service. Portal is currently posted at http://mvportal.evo-world.org/", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 3237.6, + "languages": [], + "name": "M&V Tool Testing Portal v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-10", + "metadataLastUpdated": "2020-09-08" + }, + "description": "System assessments typically yield large quantities of data from disparate sources for an analyst to scrutinize for issues. Netmeld is used to parse input from different file formats, store the data in a common format, allow users to easily query it, and enable analysts to tie different analysis tools together using a common back-end. ", + "laborHours": 10868.0, + "languages": [ + "C++", + "Python", + "SQL" + ], + "name": "Netmelt v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/netmeld/netmeld", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-10", + "metadataLastUpdated": "2021-08-30" + }, + "description": "The Dakota GUI is an interactive graphical analysis environment for creating, running, and interpreting Dakota optimization and uncertainty quantification studies. It includes problem (Dakota study) set-up, option specification, simulation interfacing, analysis execution, and results visualization. Through the use of wizards, templates, and views, Dakota GUI helps uses navigate Dakota\u2019s complex capability landscape.", + "homepageURL": "https://dakota.sandia.gov", + "laborHours": 3988282.4, + "languages": [ + "Java" + ], + "name": "Dakota Graphical User Interface", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v.6.12" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "CHGL is a hypergraph computation library for Chapel. It's primary contributions are data structures for hypergraphs and the algorithms to operate on these data structures.", + "laborHours": 6414.4, + "languages": [], + "name": "pnnl/chgl", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/chgl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This application works with the\u00a0Building Agent BACnet\u00a0library to provide stateful and modular control of device discovery, device OID lookup, and device polling/data scraping. Discovered devices and oids are persisted to a Mongo database, decoupling discovery from the polling process.", + "laborHours": 836.0, + "languages": [], + "name": "Stateful BACnet Scraper [SWR-13-26]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BACnet-state", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This directory tree contains the materials for the initial version of an openMDAO \"Driver\" object that wraps Sandia Lab's \"DAKOTA\" optimization and analysis code.", + "laborHours": 1048.8, + "languages": [ + "Python" + ], + "name": "DAKOTA_plugin, dakota_driver (pydakdriver) [SWR-13-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DAKOTA_plugin", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2018-09-12" + }, + "description": "HARP_Opt (Horizontal Axis Rotor Performance Optimization) utilizes MATLAB's optimization algorithms and the National Renewable Energy Laboratory's (NREL) WT-Perf blade element momentum (BEM) code to design axial-flow wind and water (i.e. hydrokinetic) turbine rotors. The code optimizes a rotor's performance for steady and uniform flows (no sheared or yawed flows). A variety of rotor control configurations can be designed using HARP_Opt, including fixed or variable rotor speed and fixed or variable blade pitch configuration. Blades with circular or non-circular roots are also supported.\n", + "laborHours": 5396.0, + "languages": [], + "name": "HARP_Opt: Horizontal Axis Rotor Performance Optimization", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HARP_Opt", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2018-09-12" + }, + "description": "The Parametric Analysis Tool (PAT) is part of the OpenStudio collection of software tools.\u00a0It is included in the OpenStudio installer.\n", + "laborHours": 1055837.6, + "languages": [], + "name": "Parametric Analysis Tool (PAT)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-PAT/blob/develop/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-PAT", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "The OpenStudio\u00ae Analysis Gem is used to communicate files to the OpenStudio Distributed Analysis. The purpose of this gem is to generate the analysis.json file, analysis.zip, and communicate with the server to upload the simulations. This gem does not create the cluster. To manage cloud resources use the OpenStudio Analysis Framework Helm Charts.", + "laborHours": 7767.2, + "languages": [ + "Ruby" + ], + "name": "OpenStudio\u00ae Analysis Gem [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-analysis-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.3.5" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "OpenStudio\u00ae AWS uses the OpenStudio AWS ruby class to launch a server and multiple workers for doing OpenStudio\u00ae/EnergyPlus\u00ae Analyses using Amazon AWS/EC2.", + "laborHours": 1261.6, + "languages": [ + "shell", + "Ruby" + ], + "name": "OpenStudio\u00ae AWS Gem [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-aws-gem/blob/develop/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-aws-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.8" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "This repository includes a suite of simulation tests that can be used to validate new OpenStudio\u00ae model objects as well as ensure that objects continue to work after they are added. Each new OpenStudio Model object should ideally have two simulation tests associated with it: - a Ruby one which verifies the Ruby API and, - an OSM one that verifies the OSM file can be loaded with future versions of OpenStudio. Both tests should result in a simulation-ready OpenStudio Model that can be simulated using EnergyPlus\u00ae. Both of these tests are located in the /model/simulationtests directory, the easiest way to add a new test is to find a related existing test and modify it. When new tests are added they must be added to the model_tests.rb file.", + "laborHours": 1593948.0, + "languages": [ + "Ruby", + "html", + "jupyter notebook" + ], + "name": "OpenStudio\u00ae Resources [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-resources/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-resources", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "OpenStudio\u00ae Server is a web application and distributed computing tool, which is the backbone of the OpenStudio Analysis Framework (OSAF). It is intended to make parametric analysis of building energy models accessible to architects, engineers, and designers via the OpenStudio PAT GUI or the OpenStudio Analysis Gem. OpenStudio Server analyses are defined by PAT projects or OSA's. Each analysis may include many OpenStudio simulations, as determined by project configuration.", + "laborHours": 42803.2, + "languages": [ + "R", + "Shell", + "HTML", + "Ruby", + "SCSS", + "JavaScript" + ], + "name": "OpenStudio\u00ae Server [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-server/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-server", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "3.7.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "This branch is the development branch for the OpenStudio\u00ae workflow gem.", + "laborHours": 216645.6, + "languages": [ + "Ruby", + "HTML" + ], + "name": "OpenStudio\u00ae Workflow Gem [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-workflow-gem/blob/develop/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-workflow-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.3.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2018-09-12" + }, + "description": "OpenWARP is an open source boundary element simulation tool based on the\u00a0NEMOH code. OpenWARP and NEMOH provide the ability to determine the frequency dependent added mass, radiation damping, and excitation coefficients that describe the behavior of a floating or submerged body in a wave field. These coefficients are widely used in conjunction with the Cummins equation to model the behavior of wave energy conversion devices, ships, offshore platforms, and other floating structures.\n", + "laborHours": 54872.0, + "languages": [], + "name": "OpenWARP", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenWARP", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2023-05-31" + }, + "description": "API Umbrella is an open source API management platform for exposing web service APIs. The basic goal of API Umbrella is to make life easier for both API creators and API consumers. Binary packages are available for download. Follow the quick setup instructions on the download page to begin running API Umbrella.", + "laborHours": 61088.8, + "languages": [ + "Lua", + "Ruby", + "JavaScript" + ], + "name": "API Umbrella [SWR-12-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/api-umbrella", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.15.1 / 2019-05-14" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2023-06-06" + }, + "description": "This is the repository for api-umbrella-cookbook developed at National Renewable Energy Laboratory. This repository has been archived by the owner, as it is no longer used. The files are now available as read-only.", + "laborHours": 136.8, + "languages": [ + "Ruby" + ], + "name": "api-umbrella-cookbook [SWR-12-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/api-umbrella-cookbook", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ADTKM Disruption Tolerant Key Management", + "laborHours": 2158.4, + "languages": [], + "name": "pnnl/ADTKM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ADTKM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-17", + "metadataLastUpdated": "2018-09-17" + }, + "description": "The Gas Reliability Analysis Integrated Library (GRAIL) is a prototype computational tool for solving a class of intra-day model-predictive control problems for a simplified network model of midstream natural gas pipeline systems. The model accurately resolves dynamic gas flows through long pipes using a non-ideal gas equation of state. It can be used to provide optimal intra-day flow schedules as well as spatiotemporal economic values of natural gas while ensuring that pipeline hydraulic limitations, compressor station constraints, operational factors, and pre-existing shipping contracts are satisfied. The inputs to the code are a model of the pipeline system as well as time-series data that specify boundary conditions on the network and time-dependent constraints on the optimal control problem. The outputs are time-series data that provide an approximately optimal solution of flows, pressures, compressor settings, and sensitivities to the objective function.", + "laborHours": 1976.0, + "languages": [], + "name": "Gas Reliability Analysis Integrated Library (GRAIL)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/grail", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-18", + "metadataLastUpdated": "2019-09-24" + }, + "description": "iTOUGH2 (inverse TOUGH2) provides inverse modeling capabilities for TOUGH2, a simulator for multi-dimensional, multi-phase, multi-component, non-isothermal flow and transport in fractured porous media. \n\niTOUGH2 performs sensitivity analyses, data-worth analyses, parameter estimation, and uncertainty propagation analyses in geosciences and reservoir engineering and other application areas. \n\niTOUGH2 supports a number of different combinations of fluids and components (equation-of-state (EOS) modules). In addition, the optimization routines implemented in iTOUGH2 can also be used for sensitivity analysis, automatic model calibration, and uncertainty quantification of any external code that uses text-based input and output files using the PEST protocol. \n\niTOUGH2 solves the inverse problem by minimizing a non-linear objective function of the weighted differences between model output and the corresponding observations. Multiple minimization algorithms (derivative-free, gradient-based, and second-order; local and global) are available. iTOUGH2 also performs Latin Hypercube Monte Carlo simulations for uncertainty propagation analyses. A detailed residual and error analysis is provided. \n\nThis upgrade includes (a) global sensitivity analysis methods, (b) dynamic memory allocation (c) additional input features and output analyses, (d) increased forward simulation capabilities, (e) parallel execution on multicore PCs and Linux clusters, and (f) bug fixes. \n", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 74130.4, + "languages": [], + "name": "iTOUGH2 v7.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-09-19", + "metadataLastUpdated": "2018-09-19" + }, + "description": "Chatterbug is a suite of proxy applications that represent the communication patterns commonly occurring in high performance computing codes.", + "laborHours": 684.0, + "languages": [], + "name": "Chatterbug", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/chatterbug", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-09-19", + "metadataLastUpdated": "2018-10-23" + }, + "description": "The Energy Market Price Response (EMPR) service is provided by the device, which shifts demand from high price periods in the day to low price periods. The device would consume energy when prices are low and release energy (or defer consumption) when prices are high. This load shifting benefits the individual consumers and society in general by shifting consumption to periods when production resources are available at lower costs. The service could be driven by price forecasts of the day-ahead market or shorter time periods. The service could be facilitated by demand response aggregators, utilities, or other load serving entities.", + "laborHours": 76.0, + "languages": [], + "name": "Dispatch Table", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/TomEdmunds/DispatchTable", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-09-19", + "metadataLastUpdated": "2018-09-19" + }, + "description": "CAMP provides a portable optimized implementation of template meta-programming primitives. All capabilities found within are available in other open source \nprojects, including metal and mpl among others, but no other library we know of supports all compilers required by LLNL codes. CAMP serves as an efficient facility for writing portable compile-time operations in C++ codes. It was \ndeveloped as part of the RAJA project to facilitate more complex compile-time introspection and better error message delivery to users, but has since proven useful in Umpire, CHAI and other pre-release LLNL software projects and is thus being re-factored to stand alone. \n\nThe CAMP library uses portable C++ template mechanisms almost exclusively, with the exception of intrinsics provided for performance by some compilers such as clang and gee. There are no private or protected interfaces and no proprietary information included in the source.\n\nAny and all future versions will limit themselves to implementing commonly available and well known primitives for compile-time manipulation of types.\n \nA new public github repository will be created to host the code independent of its current location in the raja repository, likely at github.com/llnl/camp. \n \n", + "laborHours": 22708.8, + "languages": [], + "name": "Concepts and Meta-Programming Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/raja", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-19", + "metadataLastUpdated": "2018-09-20" + }, + "description": "T2Well/ECO2N is a coupled wellbore and reservoir model for simulating the dynamics of CO2 injection and leakage through wellbores. It can be seen as an extension to standard TOUGH/ECO2N V2.0, and can be applied to situations relevant to geologic CO2 storage involving upward flow (e.g., leakage) and downward flow (injection). The new simulator integrates a wellbore-reservoir system by assigning the wellbore and reservoir to two different sub-domains in which flow is controlled by appropriate physical laws. In the reservoir, we model flow using a standard multiphase Darcy flow approach. In the wellbores, we use the Drift-Flux Model and related conservation equations for describing transient two-phase non-isothermal wellbore flow of CO2-water mixtures. The mass and thermal energy balance equations are solved numerically by a finite difference scheme with wellbore heat transmission to the surrounding rock handled either semi-analytically or numerically. The momentum balance equation for the flow in the wellbore is solved numerically with a semi-explicit scheme.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 7904.0, + "languages": [], + "name": "T2Well/ECO2N Version 1.0: Multiphase and Non-Isothermal Model for Coupled Wellbore-Reservoir Flow of Carbon Dioxide and Variable Salinity Water", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-09-21", + "metadataLastUpdated": "2018-09-21" + }, + "description": "This nonlinear program was developed from a nonlinear solver (called OASIS). During Phase I work, it was applied on a number of nonlinear-solver benchmarking problems and a few SLAC accelerator problems. By searching over only two optimization-control parameters, this Phase I work has enabled the development of a systematic procedure to facilitate the finding of a \"best-guessed\" global minimum solution for various types of problems with different size and complexity. This set of rules has been codified and has led to a versatile nonlinear program IMIGO.", + "homepageURL": "http://www.slac.stanford.edu/doecode/IMIGO_2011", + "laborHours": 167.2, + "languages": [], + "name": "IMIGO Software for Lattice Element Error Modeling in Accelerators", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.slac.stanford.edu/doecode/IMIGO_2011", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.slac.stanford.edu/doecode/IMIGO_2011", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The tool is designed to read, process, analyze, and report on data produced by phasor measurement units (PMUs). It has\nthree main functions:\nData ingestion and processing\nForced oscillation detection\nEvent tracking\nResult writing\nAmbient oscillation baselining\nSpectral analysis and event detection\nDominant mode identification\nResult writing\nData ingestion involves reading PMU data from CSV files, concatenating it, and applying standard signal processing\ntechniques to prepare the data for analysis.\nThe forced oscillation detection portion of the tool examines the data for evidence of a particular dynamic phenomenon in\npower systems known as forced oscillations. It is implemented with a periodogram-based method that was developed at\nPNNL. Forced oscillation events are tracked across time. Results are written to CSV files.\nThe ambient oscillation baselining portion of the tool is based on the Robust Modified Daniell-Welch (RMDW) spectral\nestimator, which was developed at PNNL. It produces estimates of the signal's ambient spectrum while detecting large\npower system events. The ambient spectrum is analyzed to identify the most observable (dominant) mode frequency. At\nthe end of each day, the tool applies the k-means clustering algorithm to distinguish between dominant system modes.\nResults are written to CSV files.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "Eastern Interconnection Situational Awareness Monitoring System (ESAMS) Oscillation Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software reads PMU (phasor measurement unit) data and creates features from the data that are used in analyses. It\nthen takes the past features from previous days of data and builds a baseline to understand the typical behavior of the\npower grid. This baseline is used by employing multivariate statistical algorithms like PCA (Principal Component Analysis),\nclustering (unsupervised learning), and classification (supervised learning). This baseline is then applied to new data to\ndetermine the state of the power grid, whether the behavior is typical or atypical, compared to what has been seen\npreviously. At the end of the day, the baseline is updated and the new baseline is used on the next day. When a time period\nis determined to be atypical, then drill down analyses are performed to help the user understand why the time period is\natypical. Plots and tables are used to show atypicality, including a performance envelope plot. This plot shows the typical\nbehavior of the variable or feature of interest, by plotting in the background the values of the variable from past days using\ncontour shading over time and then the new data over time. This allows the user to see how the new data differs from past\ndata at the same time.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "ESAMS Anomaly Detection Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The US / DOE Office of Nuclear Smuggling Detection and Deterrence (NSDD) Knowledge Management Mobile App will\nprovide password-protected direct access to non-sensitive information regarding the operations, maintenance, and\nsustainability of deployed radiation detection systems. This Mobile App will serve content managed on the NSDD\nKnowledge Management Website to users in a more user-friendly manner. The Mobile App will be cross-platform,\nfunctioning for both iOS and Android devices. The Mobile App will operate both with and without a network connection,\nprovide access to KMW content based on the users' interests, and strengthen analysis of NSDD's training effectiveness.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "NSDD Knowledge Management Mobile App", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "crop model yield change emulation", + "laborHours": 1748.0, + "languages": [], + "name": "JGCRI/persephone", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/persephone", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-25", + "metadataLastUpdated": "2019-09-23" + }, + "description": "\tBecquerel is a Python package for analyzing nuclear spectroscopic measurements. The core functionalities are reading and writing different spectrum file types, fitting spectral features, performing detector calibrations, and interpreting measurement results. It will include tools for plotting radiation spectra and fits of different spectral features, as well as convenient access to tabulated nuclear data. It relies heavily on the standard scientific Python stack of numpy, scipy, matplotlib, and pandas. It is intended to be general-purpose enough that it can be useful to anyone from an undergraduate taking a laboratory course to the advanced researcher.", + "laborHours": 4757.6, + "languages": [], + "name": "Becquerel (Bq) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-anp/becquerel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ZebrafishBMD: A software tool to perform benchmark dose calculations using toxicity screening data of high-throughput zebrafish assays.\nHigh-content imaging of larval zebrafish behavior can be used as a screening approach to rapidly evaluate the relative potential for chemicals to cause toxicity. However, most statistical methods applied to these data transform movement values to incidence-based \u201chits\u201d and calculate lowest effect levels (LELs), which loses individual fish resolution of behavior and defies hazard ranking due to reliance on applied dose levels. We developed a parallelizable workflow to calculate benchmark dose (BMD) values from dynamic, high-content zebrafish behavior data that scales for high throughput chemical screening. To capture the zebrafish movement response from light to dark stimulus, we summarized time-dependent data using both area under the curve and the immediate change at the transition point into two novel metrics that characterized abnormal behavior as a function of chemical concentration. The BMD workflow was applied to calculate BMD10 values of 1,060 ToxCast chemicals for 24 zebrafish endpoints, including behavior, mortality and morphology.\nZebrafishBMD implements the BMD workflow and provides Matlab scripts to read the data (stored in a specific structure) from a .mat file, to calculate the behavioral endpoint values from movement versus time data, to construct concentrationresponse\ncurves, to perform curve-fitting, and to calculate BMD10 values.", + "laborHours": 15.2, + "languages": [], + "name": "pnnl/ZebrafishBMD", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ZebrafishBMD", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-25", + "metadataLastUpdated": "2018-09-27" + }, + "description": "TOUGH2 is a numerical simulator for nonisothermal flows of multicomponent, multiphase fluids in one-, two-, and three-dimensional porous and fracture media. The chief applications for which TOUGH2 is designed are in geothermal reservoir engineering, nuclear waste disposal, environmental assessment and remediation, geologic carbon sequestration, and unsaturated and saturated zone hydrology. \n\nThe TOUGH2 V2.1 package is an upgrade of TOUGH2 V2.0 (CR-1574) and includes the following improvements and enhancements relative to TOUGH2 V2.0: \n\n- Includes all known bug fixes \n\n- The module TMVOC (CR-1820) is fully integrated \n\n- The module ECO2N (CR-2202) is fully integrated \n\n- A fluid property module ECO2M has been added, that can seamlessly model CO2 storage and leakage scenarios, including transitions between super- and sub-critical fluids, and phase changes between liquid and gaseous CO2. \n\nThe TOUGH2 V2.1 package also supports all legacy fluid property modules, i.e., those packaged into TOUGH2 V2.0 (CR-1574), which includes T2VOC (CR-1254).", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 5715.2, + "languages": [], + "name": "TOUGH2 V2.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-26", + "metadataLastUpdated": "2019-09-24" + }, + "description": "EOS7C is an equation of state module for the TOUGH2 program for CO2 or N2 in Methane (CH4) Reservoirs. In the present work, additions have been made to the EOS7C Version 1.0 module to include the Enhanced Coal Bed Methane (ECBM) modifications developed by Webb (2003). In addition, the Dusty Gas Model for gas-phase diffusion (Webb 2001) has been included. The ECBM modification to the EOS7C equation of state incorporate the extended Langmuir isothem for sorbing gases, including the change in porosity associated with the sorbed gas mass. Comparison to hand calculations for pure gas and binary mixture shows very good agreement. Application to a CO2 well injection problem by Law et al. (2002). The Dusty Model modification add options to calculate gas diffusion using the Dusty-Gas Model including separate and coupled approaches. Comparison to low-permeability pure gas diffusion data shows excellent agreement. The results from the DGM are compared to the Fick's Law behavior for diffusion across a capillary fringe. The differences between the models are small due to the relatively high permeability (10-11 m2) of the problem.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "EOS7C-ECBM Version 1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-27", + "metadataLastUpdated": "2019-09-24" + }, + "description": "EOS7C allows the user to model CO2 injection into natural gas reservoirs that contain methane. There are numerous natural gas modeling codes that can be easily modified to handle CO2, but the developer is not aware of any direct competitors. The current use of the code would be research on carbon sequestration or enhanced natural gas recovery (something the industry is not yet motivated to do). The code development was fully funded by DOE, contains no third party code as the developer has removed MA 28 from the manual, and fully written by LBNL employees. \n\nThe code will be distributed via the TOUGH website and requires the use of TOUGH 2 v2, with which it will be bundled. ", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 7159.2, + "languages": [], + "name": "EOS7C Version 1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "VOLTTRON Distributed Control System Platform", + "laborHours": 196657.6, + "languages": [], + "name": "VOLTTRON/volttron", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-27", + "metadataLastUpdated": "2019-09-24" + }, + "description": "This is a significant upgrade on the TOUGH2 code, which is only distributed via ESTSC. The executable version contains two pieces of third party code. The developer is in the process of obtaining permission to release an executable version with these third party libraries. At this point we will only release source code.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TOUGH2-MP Ver 2.0, the parallel version of TOUGH2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-27", + "metadataLastUpdated": "2019-09-24" + }, + "description": "ECO2N V2.0 is a fluid property module for the TOUGH2 simulator (Version 2.1) that was designed for applications to geologic sequestration of CO2 in saline aquifers and enhanced geothermal reservoirs. ECO2N V2.0 is an enhanced version of the previous ECO2N V1.0 module (Pruess, 2005). It expands the temperature range up to about 300oC whereas V1.0 can only be used for temperatures below about 110oC. V2.0 includes a comprehensive description of the thermodynamic and thermophysical properties of H2O - NaCl - CO2 mixtures, that reproduces fluid properties largely within experimental error for the temperature, pressure and salinity conditions 10 \u00b0C < T < 300 \u00b0C, P < 600 bar, and salinity up to halite saturation. This includes density, viscosity, and specific enthalpy of fluid phases as functions of temperature, pressure, and composition, as well as partitioning of mass components H2O, NaCl and CO2 among the different phases. In particular, V2.0 accounts for the effects of water on the thermophysical properties of the CO2-rich phase, which was ignored in V1.0, using a model consistent with the solubility models developed by Spycher and Pruess (2005, 2010). In terms of solubility models, V2.0 uses the same model for partitioning of mass components among the different phases (Spycher and Pruess, 2005) as V1.0 for the low temperature range (<99oC) but uses a new model (Spycher and Pruess, 2010) for the high temperature range (>109oC). In the transition range (99-109oC), a smooth interpolation is applied to estimate the partitioning as a function of the temperature. Flow processes can be modeled isothermally or non-isothermally, and phase conditions represented may include a single (aqueous or CO2-rich) phase, as well as two-phase (brine-CO2) mixtures. Fluid phases may appear or disappear in the course of a simulation, and solid salt may precipitate or dissolve. Note that the model cannot be applied to subcritical conditions that involves both liquid and gaseous CO2 unless thermol process is ignored (i.e.,isothermal run). For those cases, a user may use the fluid property module ECO2M (Pruess, 2011) instead.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "\tECO2N V2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-09-28", + "metadataLastUpdated": "2019-03-22" + }, + "description": "The framework stores HEP event data into a database and provides fast and scalable access to the data for distributed Python- and numpy-based analysis.", + "homepageURL": "http://cdcvs.fnal.gov/projects/nosql-ldrd", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "NoSQL BigData Project", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://cdcvs.fnal.gov/projects/nosql-ldrd", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "With Exascale performance and its challenges in\nmind, one ubiquitous concern among architects is energy efficiency.\nPetascale systems projected to Exascale systems are\nunsustainable at current power consumption rates. One major\ncontributor to system-wide power consumption is the number of\nmemory operations leading to data movement and management\ntechniques applied by the runtime system. To address this\nproblem, we present the concept of the Architected Composite\nData Types (ACDT) framework. The framework is made aware of\ndata composites, assigning them a specific layout, transformations\nand operators. Data manipulation overhead is amortized over a\nlarger number of elements and program performance and power\nefficiency can be significantly improved.", + "homepageURL": "http://hpc.pnl.gov/projects/POCR", + "laborHours": 0.0, + "languages": [], + "name": "POSCArchitected Composite Data Type Framework", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://hpc.pnl.gov/projects/POCR", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-28", + "metadataLastUpdated": "2018-10-01" + }, + "description": "EOS7CA is a TOUGH2 module for mixtures of a non-condensible gas (NCG) and air (with or without a gas tracer), an aqueous phase, and water vapor. The user can select the NCG as being CO2, N2, or CH4. EOS7CA uses a cubic equation of state with a multiphase version of Darcy's Law to model flow and transport of gas and aqueous phase mixtures over a range of pressures and temperatures appropriate to shallow subsurface porous media systems. The limitation to shallow systems arises from the use of Henry's Law for gas solubility which is appropriate for low pressures but begins to over-predict solubility starting at pressures greater than approximately 1 MPa (10 bar). The components modeled in EOS7CA are water, brine, NCG, gas tracer, air, and optional heat.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 7706.4, + "languages": [], + "name": "EOS7CA Version 1.0: TOUGH2 Module for Gas Migration in Shallow Subsurface Porous Media Systems", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-01", + "metadataLastUpdated": "2018-10-02" + }, + "description": "VTE is a library that allows fast and simple generation of C++ testers for modules written in Chisel and build an efficient interface to existing C++ based simulators. It contains Scala-based interface and C++ testbench class. Scala interface interacts with Firtl Interpreter and generates a basic set of C++ testbench files. These files contain the list of the Device Under Test (DUT) input-output ports as well as their parameters. C++ testbench provides functionalities similar to the Chisel PeekPokeTester, such as poke, expect, step functions. As a backend it uses Verilator.\n", + "laborHours": 562.4, + "languages": [], + "name": "Verilator Testbench Environment (VTE) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnlcomputerarch/vte", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-10-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Generate random global temperature fields with spatial and temporal correlation derived from an ESM", + "laborHours": 988.0, + "languages": [], + "name": "JGCRI/fldgen", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/fldgen", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-03", + "metadataLastUpdated": "2019-09-23" + }, + "description": "PICviewer is an easy-to-use graphical user interface for data analysis and visualization of Particle-In-Cell (PIC) simulations.", + "laborHours": 2781.6, + "languages": [], + "name": "Picviewer v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/ecp_warpx/picviewer/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-10-04", + "metadataLastUpdated": "2018-10-09" + }, + "description": "This code processes the images collected during high throughput tensile tests to measure the area of each specimen. First, the code identifies the reference images and primary sample images from list of images collected. Then, the size of the reference in the reference images is used to determine a scale (um/pixel) value which can be used to determine the size of each sample in an image. The subsequent sample images are processed to automatically detect the sample present and then identify the size in pixels. The measurements from two different views of the sample are then combined to determine the sample area (um2). ", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 228.0, + "languages": [ + "MATLAB" + ], + "name": "Area Values from Image Dimensions (AVID) v. 3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 3" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-04", + "metadataLastUpdated": "2022-02-16" + }, + "description": "Lidar (light detection and ranging) instruments are often used in wind energy studies in place of meteorological towers, as they can collect measurements at higher heights than met towers and are more easily moved to different parts of a site. While lidars can accurately measure mean wind speeds, they frequently measure different values of turbulence intensity (TI) than would be measured by a cup anemometer on a tower. Discrepancies in TI values are caused by several factors, including instrument noise and volume averaging. The inability of lidars to accurately measure turbulence is a significant barrier to replacing met towers with lidars in the future. There is currently no accepted standard process for quantifying and removing these errors in lidar TI measurements. The Software is an error reduction algorithm for lidar-measured turbulence. The algorithm is trained using co-located lidar and meteorological tower data. Lidar-measured parameters, such as wind speed, shear, and TI, will be used to predict the difference between the lidar- and tower-measured TI. The algorithm will be disseminated as a set of computer code that can be used by lidar users and manufacturers to correct lidar TI data in real time or in post-processing.", + "laborHours": 684.0, + "languages": [ + "Python" + ], + "name": "L-TERRA", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/L-TERRA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2024-09-19" + }, + "description": "BuildingSync\u00ae is a standardized language for commercial building energy audit data that software developers can use to exchange data between audit tools. Taking the form of an XML schema, BuildingSync can be required by building owners and audit program managers to allow data analysis and aggregation across multiple buildings in order to evaluate program performance and analyze trends. BuildingSync was developed using the standard energy data terminology defined in the Building Energy Data Exchange Specification (BEDES). BuildingSync is one of the first implementations of BEDES Version 1.0, and it was developed in close collaboration with the BEDES working groups. BuildingSync standardizes the format of the energy audit data itself. It is not intended to standardize the calculations performed on these data by engineers, analysts, software packages, or other audit tools. For more, see: https://buildingsync.net/", + "laborHours": 134793.6, + "languages": [ + "R", + "HTML", + "Ruby", + "Python" + ], + "name": "BuildingSync\u00ae [SWR-18-28]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/BuildingSync/schema/blob/develop-v2/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BuildingSync/schema", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2023-06-12" + }, + "description": "This repository contains all the methods to build, test, and release the gem available as rake tasks via bundler/gem_tasks.\n", + "laborHours": 11126.4, + "languages": [], + "name": "BCL Gem [SWR 21-64]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bcl-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This is the repository for capistrano_nrel_ext developed at National Renewable Energy Laboratory.", + "laborHours": 1003.2, + "languages": [ + "Ruby" + ], + "name": "capistrano_nrel_ext [no known SWR]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/capistrano_nrel_ext", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "This gem is an API client for DEnCity.org.", + "laborHours": 425.6, + "languages": [], + "name": "Dencity Gem", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/dencity-gem/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dencity-gem", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "This is the repository for dencity-scripts developed at National Renewable Energy Laboratory. ", + "laborHours": 273.6, + "languages": [], + "name": "dencity-scripts", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dencity-scripts", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "This is the repository for dencity-web developed at National Renewable Energy Laboratory.\n", + "laborHours": 17206.4, + "languages": [], + "name": "dencity-web", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dencity-web", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "Drupal VM\u00a0is a VM for Drupal, built with Ansible. Drupal VM makes building Drupal development environments quick and easy, and introduces developers to the wonderful world of Drupal development on virtual machines or Docker containers.", + "laborHours": 9576.0, + "languages": [], + "name": "Drupal VM", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/drupal-vm", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "This repository can be used to set up a Composer-Managed Drupal 8 site on\u00a0Pantheon.", + "laborHours": 288.8, + "languages": [], + "name": "Example Drops 8 Composer", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/example-drops-8-composer", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2021-03-16" + }, + "description": "Python scripting of GridLAB-D input files (.glm) derived from the Open Modeling Framework (OMF).", + "laborHours": 4666.4, + "languages": [], + "name": "glmgen", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/glmgen", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "4.1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2023-08-10" + }, + "description": "kaleidoscope is an R package developed to visualize PLEXOS scenarios as packaged by the rplexos R package. The package provides three types of visualizations intended to be used as coordinated views: a geographic diagram, a chord diagram, and dispatch charts. The geographic diagram provides a qualitative view of the study domain representing individual generator output and interregional transmission flows. The chord diagrams provide a more quantitative view of the net interchange between each of the regions. The dispatch charts are stacked and grouped bar charts providing an instantaneous snapshot of the generation mix by ISO and scenario.\n", + "laborHours": 425.6, + "languages": [ + "R" + ], + "name": "kaleidoscope", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/kaleidoscope/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/kaleidoscope", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2024-02-09" + }, + "description": "The Legacy OpenStudio\u00ae SketchUp Plug-in makes it easy to create and edit the building geometry in EnergyPlus\u00ae input files. This free plug-in also allows you to launch EnergyPlus simulations and view the results without leaving the SketchUp 3D drawing program.\n\nNote that active OpenStudio development has moved from the Legacy OpenStudio Plug-in to the more comprehensive OpenStudio suite of tools and libraries found here: https://github.com/NREL/OpenStudio. More information can be found at http://openstudio.net.\n\nThe OpenStudio Legacy Plug-in has been relaunched as Euclid by Big Ladder Software, the project's new homepage is http://bigladdersoftware.com/projects/euclid/.\n\nThe Legacy OpenStudio Plug-in was created by the National Renewable Energy Laboratory for the U.S. Department of Energy as an interface to the EnergyPlus simulation engine. Refer to the EnergyPlus webpage at energyplus.gov for an overview of the concept and features.\n\nUser support is available via the community moderated question and answer resource unmethours.com.", + "laborHours": 17571.2, + "languages": [ + "Ruby", + "HTML", + "JavaScript" + ], + "name": "Legacy OpenStudio\u00ae SketchUp Plug-in [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/legacy-openstudio", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.14" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "A widget for creating 2d geometry for building energy models.\n", + "laborHours": 19167.2, + "languages": [], + "name": "FloorspaceJS", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/openstudio-geometry-editor/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/openstudio-geometry-editor", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2024-02-09" + }, + "description": "OpenStudio\u00ae Standards is a Ruby Gem library that extends the OpenStudio SDK. It has four main use-cases:\n\nProvide higher level methods to help BEM users and developers to create OpenStudio models from existing geometry, or programmatically generated geometry\nCreate typical building models in OpenStudio format\nCreate a code baseline model from a proposed model\nCheck a model against a code/standard\nopenstudio-standards previously supported making the DOE/PNNL prototype buildings in OpenStudio format. This has since been deprecated, as the DOE/PNNL prototypes are intended for specific code comparisons under the Energy Policy Act and are not intended to accurately represent typical existing or new buildings. While openstudio-standards still creates typical buildings, these are not the same as the DOE/PNNL prototypes.", + "laborHours": 16303611.2, + "languages": [ + "Ruby" + ], + "name": "OpenStudio\u00ae Standards [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/openstudio-standards", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-11-26" + }, + "description": "The SEED Platform is a web-based application that helps organizations easily manage data on the energy performance of large groups of buildings. Users can combine data from multiple sources, clean and validate it, and share the information with others. The software application provides an easy, flexible, and cost-effective method to improve the quality and availability of data to help demonstrate the economic and environmental benefits of energy efficiency, to implement programs, and to target investment activity.", + "laborHours": 81031.2, + "languages": [], + "name": "Standard Energy Efficiency Data (SEED) Platform", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/seed/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SEED-platform/seed", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "Testing suite for the STREAMM-tools source code. 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The model accounts for heat and up to four mass components, i.e., water, CH4, hydrate, and water-soluble inhibitors such as salts or alcohols. These are partitioned among four possible phases (gas phase, liquid phase, ice phase and hydrate phase). Hydrate dissociation or formation, phase changes and the corresponding thermal effects are fully described, as are the effects of inhibitors. The model can describe all possible hydrate dissociation mechanisms, i.e., depressurization, thermal stimulation, salting-out effects and inhibitor-induced effects.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 9408.8, + "languages": [], + "name": "HYDRATE v1.5 OPTION OF TOUGH+ v1.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-10-11", + "metadataLastUpdated": "2019-03-22" + }, + "description": "SolCalc is a software suite that computes and displays magnetic fields generated by a three dimensional (3D) solenoid system. Examples of such systems are the Mu2e magnet system and Helical Solenoids for muon cooling systems. ", + "homepageURL": "http://partnerships.fnal.gov", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "SOLCALC", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://partnerships.fnal.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-11", + "metadataLastUpdated": "2018-10-15" + }, + "description": "RealGasBrine v1.0 is a numerical code that for the simulation of the behavior of gas-bearing porous and/fractured geologic media. 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The capabilities of the code include coupled flow and thermal effects, real gas behavior, Darcy and non-Darcy flow, several isotherm options of gas sorption onto the grains of the porous media, complex fracture descriptions, gas solubility into water, and geomechanical effects on flow properties. RealGasBrine v1.0 allows the study of flow and transport of fluids and heat over a wide range of time frames and spatial scales not only in gas reservoirs, but also in any problem involving the flow of gases in geologic media, including the geologic storage of greenhouse gas mixtures, the behavior of geothermal reservoirs with multi-component condensable (H2O and CO2) and non-condensable gas mixtures, the transport of water and released H2 in nuclear waste storage applications, etc.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 6414.4, + "languages": [], + "name": "RealGasBrine v1.0 option of TOUGH+ v1.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-11", + "metadataLastUpdated": "2024-10-25" + }, + "description": "OpenMDAO driver for DAKOTA (Design Analysis Kit for Optimization and Terascale Applications). This code connects the SANDIA National Laboratory's C++-based DAKOTA optimization and analysis tool with NASA\u2019s python-based openMDAO systems engineering framework. It allows DAKOTA to be used as an openMDAO \u201cDriver\u201d. DAKOTA contains a wide array of advanced sensitivity, uncertainty quantification, and optimization methods. These are now available in a \u201cpluggable\u201d way to any openMDAO based workflow.", + "laborHours": 684.0, + "languages": [ + "Python" + ], + "name": "DAKOTA Driver (WISDEM\u00ae) [SWR-13-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/dakota_driver", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-10-11", + "metadataLastUpdated": "2024-09-18" + }, + "description": "PECOS is Python package that provides a framework for studying, developing, and evaluating quantum error-correcting codes. 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It provides a description of the underlying physics and thermodynamics of non-isothermal flow, of the mathematical and numerical approaches, as well as a detailed explanation of the general (common to all applications) input requirements, options, capabilities and output specifications. The core code cannot run by itself: it needs to be coupled with the code for the specific TOUGH+ application option that describes a particular type of problem. The additional input requirements specific to a particular TOUGH+ application options and related illustrative examples can be found in the corresponding User's Manual.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 8876.8, + "languages": [], + "name": "TOUGH+ v1.5 Core Code", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-12", + "metadataLastUpdated": "2019-09-24" + }, + "description": "\tThe BubbleCluster algorithm was developed to help address the limitations of traditional genetic mapping tools when presented with large amounts of data. 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Input format is identical to that of the popular MSTMap package, aiding useability.", + "laborHours": 395.2, + "languages": [], + "name": "BubbleCluster v4", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/vstrnadova/BubbleCluster", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-15", + "metadataLastUpdated": "2018-10-17" + }, + "description": "This software is designed for the sole purpose of analyzing numerical lattice QCD results computed for one of the developers' research projects related to neutrinoless double beta decay, and will be distributed with their research publication. This software is provided to maximize the dissemination of the research results, to enable other scientists and the general public to easily check the results of their analysis, and also to be in compliance with the public availability of \"digital data\" as required by the DOE.", + "laborHours": 957.6, + "languages": [], + "name": "project_0vbb v1.0-beta", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/callat-qcd/project_0vbb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-16", + "metadataLastUpdated": "2018-10-17" + }, + "description": "fcompare is a software package that applies for comparing two curves generated from datasets in csv format. 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In addition, it can be used for Modelica library developer to do the unit test that verifies new model developments.", + "laborHours": 1018.4, + "languages": [], + "name": "funnel v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-srg/funnel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-16", + "metadataLastUpdated": "2018-10-17" + }, + "description": "The Distributed Energy Resources Customer Adoption Model (DER-CAM) is a powerful and comprehensive decision support tool that primarily serves the purpose of finding optimal distributed energy resource (DER) investments in the context of either buildings or multi-energy microgrids. \n\nVersion 5.9 introduces significant advancements to DER-CAM, including support for wholesale market integration (ancillary services), storage aging effects, improved solar thermal collector modeling, improved part-load efficiency modeling for conventional generators, added support for hydro generation, among others.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 5335.2, + "languages": [], + "name": "Distributed Energy Resources Customer Adoption Model (DER-CAM) v5.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-10-17", + "metadataLastUpdated": "2019-03-19" + }, + "description": "COMMON is a tool for collecting, storing, and displaying critical information to facilitate analysis on Microsoft Windows based IT systems. 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A unique feature is the creation of daily output files (JSON) from the data collected for off site evaluation by subject matter experts.", + "laborHours": 43988.8, + "languages": [ + "C#", + "JavaScript", + "TypeScript" + ], + "name": "COMMON \u2013 Communications System Monitor v. 1.5", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/common", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.5" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-23", + "metadataLastUpdated": "2023-05-05" + }, + "description": "This library provides a framework for working with large timeseries data from wind plants, such as SCADA. Its development has been motivated by the WP3 Benchmarking (PRUF) project, which aims to provide a reference implementation for plant-level performance assessment.", + "laborHours": 1337.6, + "languages": [ + "Python" + ], + "name": "OpenOA\u2122, FKA: Wind Plant Performance Project (WP3) Benchmarking", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenOA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.0rc2" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-23", + "metadataLastUpdated": "2018-10-24" + }, + "description": "Fast GridLAB-D file format parser", + "laborHours": 2006.4, + "languages": [], + "name": "glm", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/glm", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-10-25", + "metadataLastUpdated": "2018-10-26" + }, + "description": "The software decomposes n-component time-series data into persistence vectors and provide visualizations of various summaries of this information. Persistence vectors are a type of vector, based on multidimensional persistent homology theory, which have magnitudes and directions that reflect dominant trends in the multi-component data. The software is a collection of MATLAB scripts, and thus MATLAB runs the scripts. The master script that calls other scripts is called Snorri. The purpose is thus analysis of time-series data to extract dominant trends or events and to classify the type of event. The software produces characteristic vectors (an average of the persistence vectors), which can have directions that reflect the overall dominant trend in a time-series data set. The MATLAB scripts have been partially converted to the PYTHON language and no do not have the full functionality of the MATLAB and are not fully tested; the python scripts are to be covered under this copyright assertion. Two versions of the PYTHON scripts are included, called: mph25.py and mph38.py, each with their own main.py file.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 1444.0, + "languages": [ + "MATLAB" + ], + "name": "Snorri Version 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-30", + "metadataLastUpdated": "2019-09-23" + }, + "description": "This software is an extension to OTM (Open Traffic Models), which is an open-source traffic simulator maintained at the Institute of Transportation Studies at U.C. Berkeley. OTM-MPI provides functionality for running OTM simulations in distributed computing environments. Its functionality includes min-cut division of traffic networks (using METIS), deployment of sub-networks on multiple compute nodes, and inter-node MPI communications.", + "laborHours": 1155.2, + "languages": [], + "name": "OTM-MPI (Open Traffic Models - MPI)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ggomes/otm-mpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-30", + "metadataLastUpdated": "2019-09-23" + }, + "description": "TA_solver is a modular software framework for solving user equilibrium traffic assignment problems, both static and dynamic, utilizing the OTM (Open Traffic Models) API to encode traffic scenarios. The design is based on the formulation of the problem as a variational inequality. Unlike most existing traffic assignment software which focus on specific traffic models, TA_solver accommodates various traffic models, but also enables using parallel computation in high performance computing environments to speed up large-scale equilibrium calculations.", + "laborHours": 39033.6, + "languages": [], + "name": "TA_solver -- Traffic Assignment solver package", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ugirumurera/TA_solver", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-30", + "metadataLastUpdated": "2019-09-23" + }, + "description": "WarpX is a fully electromagnetic Particle-In-Cell code for the modeling of plasma-based particle accelerators. The code includes unique features such as mesh refinement and arbitrary-order analytical pseudo-spectral Maxwell solvers.", + "laborHours": 23712.0, + "languages": [], + "name": "WarpX v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-WarpX/WarpX", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-30", + "metadataLastUpdated": "2019-09-24" + }, + "description": "IDAES PSE capabilities support the design and optimization of innovative new advanced Process Systems Engineering (PSE) capabilities to improve the efficiency and reliability of the existing fleet of coal-fired power plants while accelerating the development of a broad range of advanced fossil energy systems.", + "laborHours": 99788.0, + "languages": [], + "name": "Institute for the Design of Advanced Energy Systems Process Systems Engineering Framework (IDAES PSE Framework) ", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/IDAES/idaes-pse/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaes/idaes-pse", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-31", + "metadataLastUpdated": "2019-09-23" + }, + "description": "The Dac-Man framework identifies, captures and manages change in large scientific datasets, and enables plug-in of domain-specific change analysis with minimal user effort.", + "laborHours": 4316.8, + "languages": [], + "name": "Data Change Management for Scientific Datasets on HPC systems", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dghoshal-lbl/dac-man", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-10-31", + "metadataLastUpdated": "2018-11-01" + }, + "description": "Velo is the domain independent collaboration environment originally created as the basis of the Geological Sequestration Software Suite (GS3) under the Carbon Sequestration Initiative (CSI) LDRD program at PNNL. The enviroment supports teams in performing scientific research including setting up computational models, running simulations, and\nanalyzing/visualizing simulation output.", + "laborHours": 461517.6, + "languages": [], + "name": "pnnl/velo", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/velo", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-11-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software tool, written in R, performs manipulations necessary to translate Human-Earth system model regional/sector emission outputs, such as those from PNNL's Global Change Assessment Model (GCAM), to gridded form needed by Earth System Models, such as DOEs E3SM (Energy Exascale Earth System Model) model. The tool takes as its primary input emissions in a standard community format, and produces CF-compliant netCDF gridded emission as its primary output. As intermediate output the tool produces downscaled emissions at the country level.", + "laborHours": 2508.0, + "languages": [ + "R" + ], + "name": "iiasa/emissions_downscaling", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/iiasa/emissions_downscaling", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-05", + "metadataLastUpdated": "2018-11-05" + }, + "description": "PV TOMCAT predicts the outdoor operating temperature and output power of a PV module based on measured physical properties and outdoor conditions. It includes a ray tracing model of a PV module, which runs in the commercial SunSolve ray tracer. Output from this model is combined with meteorological time series data to produce a combined input file for a finite-element model of heat conduction and radiation. Finally, this finite-element model is run in the commercial COMSOL Multiphysics software, producing time series outputs of temperature and power.", + "laborHours": 349.6, + "languages": [ + "Python" + ], + "name": "PV TOMCAT", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pv_tomcat", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-06", + "metadataLastUpdated": "2021-04-27" + }, + "description": "Gear-SCouP is an analytical model for the rating analysis of articulated spline coupling designs. Articulated splines are commonly used in the planetary stage of wind turbine gearboxes as the means of transmitting the driving torque while also improving load sharing. Direct measurement of spline loads and performance is extremely challenging because of limited accessibility and spline design standards are limited. For a given torque and shaft misalignment, Gear-SCouP quickly yields physical insights into relationships between the spline design parameters and resulting loads, bending, contact, and shear stresses, and safety factors considering various heat treatment methods. Results of this analytical model are compared well against several computational approaches under moderate misalignment. The computational time of Gear-SCouP is significantly less than other FE-based tools.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Gear-SCouP", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GEAR-SCouP", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "sfiligoii@fusion.gat.com" + }, + "date": { + "created": "2018-11-06", + "metadataLastUpdated": "2018-11-09" + }, + "description": "CGYRO is a multi-species spectral gyrokinetic solver with sonic rotation capability. It is an Eulerian GK solver specifically designed and optimized for collisional, electromagnetic, multiscale simulation. A key algorithmic aspect of CGYRO is the radially spectral formulation used to reduce the complicated integral gyroaveraging kernel into a multiplication in wavenumber space, but retaining the ability to treat profile variation important for edge plasmas. This makes it suitable for\nnext-generation computational systems that require high levels of parallel concurrency.\n", + "homepageURL": "http://gafusion.github.io/doc/download.html", + "laborHours": 160496.8, + "languages": [ + "Fortran" + ], + "name": "CGYRO", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://gafusion.github.io/doc/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://gafusion.github.io/doc/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "version": "16.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-07", + "metadataLastUpdated": "2018-11-07" + }, + "description": "The miniGraphics package provides a collection of reference implementations for parallel rendering. In particular, miniGraphics is focused on sort-last parallel rendering, which is the rendering algorithm of choice for HPC rendering. The miniGraphics package provides a collection of simple serial rendering systems and a collection of parallel image compositing methods, which can be combined to test the behavior of parallel rendering under different conditions.", + "laborHours": 42423.2, + "languages": [ + "C++" + ], + "name": "miniGraphics v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniGraphics", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-12", + "metadataLastUpdated": "2019-09-23" + }, + "description": "This is top-level lattice QCD code developed by employees at LBNL and LLNL. It currently compiles on top of the USQCD Chroma software stack. This code contains high-performance routines that are used in our research, and we intend to release this code publicly to ensure reproducibility and to meet our obligations for complying with the DOE Digital Data rules.", + "laborHours": 10822.4, + "languages": [], + "name": "lalibe v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/callat-qcd/lalibe", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-12", + "metadataLastUpdated": "2019-05-28" + }, + "description": "Suite of tools designed to simply data collection, extraction, reduction, and plotting for resonant soft x-ray scattering experiments performed at ALS beamline 4.0.2; speeds up the process of converting data into meaningful information for users to publish experimental results. \n\n* Python software routines for processing CCD images, including reciprocal space maps, diffraction peak alignment, resonant spectral profiles, line-cut comparisons, coordinate transforms, etc. \n* Scan file generator, optimized for typical uses cases, reduces burden on users by handling complex operations behind the scenes of a simplified user interface \n* Deployed at beamline endstation computers; packaged and deployable as standardized PyPI package \n* Under version control (git) and hosted on LBL-sponsored repository (bitbucket)", + "laborHours": 1991.2, + "languages": [], + "name": "ALS/Milo: BL402 RSXD data analysis", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/als.milo/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-11-13", + "metadataLastUpdated": "2018-11-13" + }, + "description": "This software is a C to Verilog converter. However it doesn't just generate any Verilog code, it is intended to generate Verilog code compatible with execution over quantum based D-Wave systems. ", + "laborHours": 410.4, + "languages": [], + "name": "Dwave compatible C to Verilog converter ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/c2verilog", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-13", + "metadataLastUpdated": "2018-11-16" + }, + "description": "TOUGHREACT is a numerical simulation program for chemically reactive non-isothermal flows of multiphase fluids in porous and fractured media. The program is written in Fortran 77 and was developed by introducing reactive chemistry into the multiphase flow code TOUGH2 V2. Interactions between mineral assemblages and fluids can occur under local equilibrium or kinetic rates. The gas phase can be chemically active. Precipitation and dissolution reactions can change formation porosity and permeability, and can also modify the unsaturated flow properties of the rock.\nThe code is distributed with a comprehensive user's guide that includes sample problems addressing geothermal reservoirs and hydrothermal systems, nuclear waste isolation, groundwater quality, sequestration of carbon dioxide in saline aquifers, and supergene copper enrichment. The TOUGHREACT-Pitzer V1.21 package supports the following fluid property modules packaged into TOUGH2 V2.0 (CR-1574): EOS1, EOS2, EOS3, EOS4, EOS7, EOS9, and ECO2N. This version incorporates a Pitzer ion interaction model for application to saline solutions. It is NOT compatible with the most recent TOUGHREACT V2 and relies on the previous TOUGHREACT V1.21.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TOUGHREACT-Pitzer V1.21", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-19", + "metadataLastUpdated": "2019-09-24" + }, + "description": "The TOUGHREACT Pitzer ion-interaction model version was developed based on the previous versions of TOUGHREACT. The main extensions include the Pitzer ion-interaction model for ionic activity calculation of solutions over a broad range of concentrations and the coupling of the vapor-pressure-lowering effect of salinity to phase partitioning.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TOUGHREACT Pitzer Ion-Interaction Model", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-20", + "metadataLastUpdated": "2018-11-20" + }, + "description": "Solves the electromagnetic forward problem for a plane wave or magnetic dipole fields impingent on a set of spherical shells in a whole space of uniform resistivity, relative permeability , and relative permitivity for electric fields and magnetic fields of internal origin at nrcv receivers and nf frequencies. For receivers outside the largest sphere these are standard secondary fields. Results are given in either time or frequency domain. Time domain results allow modelling turn-on or turn-off step function transmitter wave forms, or square pulse and half sine pulse wave funcitons with arbitrary pulse length and repetition rate. Pulses may be either uni-modal or bi-modal (alternating sign each half period).", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 4848.8, + "languages": [], + "name": "timesphere6.f software", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-20", + "metadataLastUpdated": "2020-11-03" + }, + "description": "SCEPTRE solves the linear Boltzmann transport equation for general one-, two- and three-dimensional unstructured-mesh Cartesian geometries. SCEPTRE can handle any particle type for which multigroup-Legendre cross sections are available. However, the code is designed primarily to model the transport of photons, electrons, and positrons through matter. SCEPTRE 2.0 includes several auxiliary packages for pre- and post-processing, regression testing, stochastic radiation transport, thermal radiation transport, and charged-particle transport in the presence of electromagnetic fields. SCEPTRE 2.0 includes sophisticated transport-synthetic acceleration and ray-effects mitigation capabilities.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "SCEPTRE v. 2.0 (Sandia Computational Engine for Particle Transport for Radiat", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 2.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-20", + "metadataLastUpdated": "2019-09-23" + }, + "description": "Software to provide fluid properties, including thermodynamic relationships, transport properties and reaction kinetics, for computational fluid dynamics packages.", + "laborHours": 2114760.8, + "languages": [], + "name": "PelePhysics v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Combustion/PelePhysics", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-21", + "metadataLastUpdated": "2019-09-23" + }, + "description": "The software, PICMI and AMI, establish conventions for the naming and structuring of input files for Particle-In-Cell and particle accelerator simulations.", + "laborHours": 501.6, + "languages": [], + "name": "Particle-In-Cell/Accelerator Modeling Interface", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/atap-ami", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-26", + "metadataLastUpdated": "2018-12-04" + }, + "description": "The md_viscoplastic software is a numerical implementation of the Munson-Dawson material model for rock salt. One inputs a deformation increment, a temperature increment, and the current stress state to md_viscoplastic. It returns the new stress state by numerically integrating ordinary differential equations. ", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "md_viscoplastic v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-11-26", + "metadataLastUpdated": "2018-11-27" + }, + "description": "Systems biology models written in the BioNetGen language often contain parameters that must be fit based on experimental data. PyBioNetFit is a software tool designed to fit parameters of BioNetGen models. The user is expected to provide a BioNetGen model that contains unknown parameters, along with one or more text files containing experimental data. PyBioNetFit will perform a series of calls to the BioNetGen simulator using different parameter sets, to identify the parameter set that best fits the data. The parameter search is dictated by the user's choice of one of several metaheuristic optimization algorithms, including differential evolution, particle swarm optimization, scatter search, and simulated annealing. The software supports parallelized computing on multi-core computers and on computing clusters. We expect this software to be a useful tool for researchers designing BioNetGen models in collaboration with experimentalists.", + "laborHours": 24715.2, + "languages": [], + "name": "PyBioNetFit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PyBNF", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-28", + "metadataLastUpdated": "2021-09-07" + }, + "description": "Radiographic Image Acquisition & Processing Software for Security Markets", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C#", + "WPF" + ], + "name": "X-Ray Toolkit (XTK) v. 3.1.x", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 3.1.x" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-12-18" + }, + "description": "Affect is a module written in the Python language that provides functions for post-processing data that are the result of computer simulations\u2014usually the result of the finite element method\u2014for engineering and physics systems and environments.", + "laborHours": 86275.2, + "languages": [ + "C", + "C++", + "Python", + "Cython" + ], + "name": "Affect v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kevincopps/affect", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2019-01-23" + }, + "description": "This software is a Python package designed to act as an interface between FEniCS and PETSc to facilitate the construction and application of parallel block solvers/preconditioners. The original intent of this software was to help enable Battery and Wind Farm simulations for use on high performance computing systems. The code is written in Python and uses the petsc4py module to access the more advance features of the PETSc Krylov Solver. In essence, pFibs is an interface to make accessing these features more streamlined. Additionally, pFibs also provides a template for building custom Python based preconditioning algorithms. ", + "laborHours": 1276.8, + "languages": [ + "Python" + ], + "name": "Parallel Fenics Implementation of Block Solvers (pFibs)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pfibs", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "This is View3D, version 3.2, a C program for the computation of geometric view factors. This version of View3D is included as part of the EnergyPlus installer package. The program utilizes a number of integration techniques to compute view factors between planar triangles or quadrilaterals in three dimensions.", + "laborHours": 3252.8, + "languages": [ + "C" + ], + "name": "View3D", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/View3D-3.2", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "3.2" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "The Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS) is a co-simulation platform that is currently under development as part of a GMLC project. The High Level Architecture (HLA) is a co-simulation standard, various implementations of which have been widely used for co-simulations for several years, particularly in the defense community. The objective of developing the HELICS-HLA interface is to provide the ability of making software connected with HLA implementations to work with software connected with HELICS. Since each HLA federation is dependent on the RTI being used, the HELICS-HLA interface developed here uses an implementation of the HLA, the Universal CPS Environment for Federation (UCEF), to create this interface. Both HELICS and UCEF are open source software. UCEF-gateway that enables the integration of HELICS and UCEF is also an open source software.", + "laborHours": 1109.6, + "languages": [], + "name": "HELICS-HLA", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GMLC-TDC/HELICS-HLA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "This software is an interface in Python for interacting with EPRI DBus software.", + "laborHours": 182.4, + "languages": [ + "Python" + ], + "name": "PyDBus", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pydbus", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2019-07-10" + }, + "description": "The Distribution Transformation Tool (DiTTo) provides a framework for converting between and modifying several different types of distribution model formats . These include commercial formats such as CYME, Synergi, DEW, ePHASORSIM as well as open source formats such as OpenDSS and GridLAB-D. DiTTo consists of an API which represents electrical equipment, configurations, settings and timeseries data. This API acts as an intermediary between different distribution model formats. Several modules for reading and writing the models connect to this API to facilitate easy conversion between formats. Once feeder models are converted into the intermediate API, analysis can be done on the feeder using a network module. The modification module allows changes to be made to the model in the intermediate API. This allows a clear workflow that supports reading a model from one format, performing analysis, making modifications and writing the model to a different format.", + "laborHours": 62639.2, + "languages": [ + "Python", + "Python" + ], + "name": "DiTTo (Distribution Transformation Tool)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ditto", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2023-08-15" + }, + "description": "Building Energy Simulation Test (BESTEST) is an NREL-developed method to validate the qualitative performance of different whole building simulations engines relative to each other. \nhttps://www.nrel.gov/docs/legosti/old/6231.pdf\n\nFor EnergyPlus\u00ae and OpenStudio\u00ae, generation of test cases, simulation, and reporting has been a manual or partially automated process that typically took a number of months after a new version of EnergyPlus came out. Building Energy Simulation Test - Generation Simulation and Reporting (BESTEST-GSR) was developed to fully automate this process so it is less error-prone, less time-consuming, and can be quickly run on request for any development branch of EnergyPlus and OpenStudio.\n\nThe initial use case is to directly support OpenStudio and EnergyPlus development, but the software is configured to support use by external software developers that build tools on top of EnergyPlus and/or OpenStudio. Tools built on top of OpenStudio can leverage the test generation, simulation, and reporting, while tools built on EnergyPlus can leverage the test simulation and reporting.\n\nThe model generation is accomplished by running OpenStudio measures for envelope, heating, or cooling test cases. At this stage the specified weather file required for a specific test case is assigned to the model. Simulation is enabled using the OpenStudio Command Line Interface (CLI) to run a series of OpenStudio and Reporting measures to a specified seed model. The specified workflow is defined with an OpenStudio OSW file. The first measure generates the test case model, while the second measure is a reporting measure that runs after the simulation to collect necessary simulation results from the EnergyPlus SQL file. The Reporting stage gathers data from individual OpenStudio OSW files and populates a series of BESTEST Microsoft Excel spreadsheets. BESTEST-GSR also gathers zip files from individual simulations for diagnostic purposes.", + "laborHours": 68339.2, + "languages": [], + "name": "BESTEST-GSR (Building Energy Simulation Test - Generation Simulation and Reporting) [SWR 18-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BESTEST-GSR", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2019-09-24" + }, + "description": "Parallel TOUGH + Hydrate, and other Parallel modules, takes TOUGH code to the next level by enabling parallel processing. TOUGH+ codes can be used for the solution of problems of fluid flow and heat transport in complex geologic media.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Parallel TOUGH+HYDRATE ", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "This tool can be used to enumerate the subdomains associated with a company by aggregating the results of multiple OSINT (Open Source Intelligence) tools.", + "laborHours": 1459.2, + "languages": [ + "Bash", + "Perl", + "Python", + "Ruby" + ], + "name": "Domain Reconniassance Robot (DR. ROBOT) Beta 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/dr_robot", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "Beta 0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "psychrometricsExt is a SkySpark extension that provides a set of psychrometric functions using equations from the ASHRAE Fundamentals handbook.", + "laborHours": 30.4, + "languages": [], + "name": "SkySpark psychrometricsExt ", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/psychrometricsExt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2024-03-11" + }, + "description": "Data structures in Julia to enable power systems analysis. Also, PowerSimulations.jl is a Julia package for power system modeling and simulation found at https://github.com/NREL/PowerSimulations.jl. The objectives of the package are: Provide a flexible modeling framework that can accommodate problems of different complexity and at different time-scales. Streamline the construction of large scale optimization problems to avoid repetition of work when adding/modifying model details. Exploit Julia's capabilities to improve computational performance of large scale power system simulations. The flexible modeling framework is enabled through a modular set of capabilities that enable scalable power system analysis and exploration of new analysis methods. The modularity of PowerSimulations results from the structure of the simulations enabled by the package: Simulations define a set of problems that can be solved using numerical techniques. Problems are generated by expressing model formulations against system data For example, an annual production cost modeling simulation can be created by formulating a unit commitment model against system data to assemble a set of 365 daily time-coupled scheduling problems.", + "laborHours": 8466.4, + "languages": [ + "Julia" + ], + "name": "PowerSystems.jl and PowerSimulations.jl [SWR-18-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PowerSystems.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.15.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-30" + }, + "description": "Solves the Poisson equation on three-dimensional network of line segments, each of uniform material properties, subject to boundary condition forcing.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 121.6, + "languages": [], + "name": "FLUXNET v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-12-03" + }, + "description": "The purpose of the ADAPT code is to generate Dynamic Event Trees (DET) using a user specified set of simulators. ADAPT can utilize any simulation tool which meets a minimal set of requirements. ADAPT is based on the concept of DET which uses explicit modeling of the deterministic dynamic processes that take place during a nuclear reactor plant system (or other complex system) evolution along with stochastic modeling. When DET are used to model different aspects of Probabilistic Risk Assessment (PRA), all accident progression scenarios starting from an initiating event are considered simultaneously. The DET branching occurs at user specified times and/or when an action is required by the system and/or the operator. These outcomes then decide how the dynamic system variables will evolve in time for each DET branch. Since two different outcomes at a DET branching may lead to completely different paths for system evolution, the next branching for these paths may occur not only at different times, but can be based on different branching criteria. The computational infrastructure allows for flexibility in ADAPT to link with different system simulation codes, parallel processing of the scenarios under consideration, on-line scenario management (initiation as well as termination), analysis of results, and user friendly graphical capabilities. The ADAPT system is designed for a distributed computing environment; the scheduler can track multiple concurrent branches simultaneously. The scheduler is modularized so that the DET branching strategy can be modified (e.g. biasing towards the worst case scenario/event). Independent database systems store data from the simulation tasks and the DET structure so that the event tree can be constructed and analyzed later. ADAPT is provided with a user-friendly client which can easily sort through and display the results of an experiment, precluding the need for the user to manually inspect individual simulator runs.", + "homepageURL": "http://www.sandia.gov/adapt", + "laborHours": 0.0, + "languages": [ + "Python 2", + "MySQL" + ], + "name": "ADAPT (Analysis of Dynamic Accident Progression Trees) Revision 5710", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.sandia.gov/adapt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "Revision 5710" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-11-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Unique Building Identification (UBID) for JavaScript\nThis is a line-for-line translation from the Python programming language to the JavaScript programming language of the UBID application programming interface (API): the \"encode\", \"decode\" and \"isValid\" UBID functions. No new functionality is introduced.", + "laborHours": 76.0, + "languages": [ + "Java" + ], + "name": "pnnl/buildingid-js", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid-js", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-11-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Unique Building Identification (UBID) for Ruby\nAn implementation of the Unique Building Identification (UBID) concept for the Ruby programming language. This work is a line-for-line port of the original implementation for the Python programming language (IPID: 31437-E). No new functionality is added.", + "laborHours": 76.0, + "languages": [ + "Ruby" + ], + "name": "pnnl/buildingid-rb", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid-rb", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-12-03", + "metadataLastUpdated": "2018-12-03" + }, + "description": "Code #1 solves the one-dimensional Poisson equation and outputs the band bending poteatial near a metal-semiconductor interface.\nCode #2 uses the output of code #1 and calculates the contact resistivity of the interface.\n", + "homepageURL": "http://www.sandia.gov/nanocarb/research.php", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Band Bending/Contact Resistivity Codes v. 1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.sandia.gov/nanocarb/research.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v1" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-12-03", + "metadataLastUpdated": "2018-12-04" + }, + "description": "pyperc is a Python package for invasion percolation which models multiphase fluid migration in porous \nmedia. The model accounts for capillary pressure, buoyancy, and gravity. Regular and unstructured grids can be used. A tuning parameter can be set to adjust the stochastic nature of the process. Graphics depict fluid migration according to the invasion pressure.\n", + "laborHours": 410.4, + "languages": [ + "Python" + ], + "name": "pyperc v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyperc", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-12-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PostgreSQL histograms for ActiveRecord relations.\nA plugin for the Ruby on Rails (RoR) web application development framework web application development framework that leverages the \"Active Relation\" relational algebra component to automatically formulate SQL statements for the construction of histograms.", + "laborHours": 76.0, + "languages": [ + "Ruby" + ], + "name": "pnnl/pg-histogram", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pg-histogram", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-05", + "metadataLastUpdated": "2018-12-05" + }, + "description": "The software is a flexible architecture used to integrate motors, analog data, digital signals, and instruments together to control scientific experiments and collect data during an experiment. The architecture supports features needed by scientists to quickly add new hardware to an experiment and to take and view data in a meaningful way. It does not perform analysis of the data, but provides basic visualization needed to evaluate the quality of the data as well as the calibration of the system.\n", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 60.8, + "languages": [], + "name": "BCS (Beamline Control System) v2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-12-05", + "metadataLastUpdated": "2023-05-30" + }, + "description": "Alfalfa is a web based software service that implements a virtual building control system using the EnergyPlus simulation as a backend. Conventional building energy simulation is non interactive, meaning that a simulation is started and run to completion without any user input during the simulation. Alfalfa allows a client to start a building simulation, then interactively read sensor locations and dynamically command actuators in realtime. The Alfalfa web service conforms to the Project Haystack standard, which is a specification adopted by many building control system vendors. The service enables Haystack compliant control system vendors to test their control modules and algorithms without the need for a physical building or modifying their hardware and software, enabling faster and cheaper development cycles. Alfalfa has use cases beyond control system testing. One example is building fault detection, where physical building performance can be compared to simulated values in realtime, indicating where there may be a problem in the building. Another use case is informing predictive control systems, where near future events are simulated to premptively guide control decisions in the real building. This software is web based and designed to be self service. Users of Alfalfa can upload an OpenStudio building model and begin communicating with the simulated building without any advanced setup or configuration, as if they were communicating a real building control system. Behind the scenes, Alfalfa makes extensive use of Amazon Web Services, in order to scale from a very small number of users and buildings, to extremely large numbers in a cost effective way.", + "laborHours": 31479.2, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Alfalfa [SWR 18-17]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/alfalfa", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.5.1" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-12-05", + "metadataLastUpdated": "2018-12-06" + }, + "description": "PLUMECALC is a post processor to random walk particle tracking simulations of subsurface solute transport. PLUMECALC takes results of a single particle tracking run without retention processes and incorporates the effects of matrix diffusion or other retention processes for a user-specified solute source.", + "laborHours": 3511.2, + "languages": [], + "name": "PLUMECALC, Version 2.3.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PLUMECALC", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-12-07", + "metadataLastUpdated": "2018-12-10" + }, + "description": "StCUDA is a software package for VisualWorks Smalltalk that contains classes and methods that interfaces Smalltalk to CUDA API's.\nSupporting class StCUDA contains the low level calls to the CUDA API's", + "laborHours": 440.8, + "languages": [], + "name": "StCUDA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/StCUDA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-11", + "metadataLastUpdated": "2019-09-24" + }, + "description": "This code is a set of modules designed to detect certain classes of cyber attacks against equipment in power distribution grid substations, including attacks against transformer tap changers and capacitor bank switches, as well as \"reconnaissance\" attacks against equipment in power grid substations.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1413.6, + "languages": [], + "name": "Analytics for Stream-Processing Architecture for Real-time Cyber-physical Security (Analytic-SPARCS) v0.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-12-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The first step toward the design of good error detection/correction techniques involves an understanding of an application\u2019s vulnerability to soft errors.\nTo study the behavior of iterative methods in the presence of soft errors, we inject errors during the execution of these methods. In particular, we study the impact of one error (single- or multi-bit) on the execution of iterative methods. We use real life datasets from the SuiteSparse Matrix Collection (https://sparse.tamu.edu) and widely used iterative solver library (Iterative Methods Library, IML++ v1.2a). We instrument the iterative solver implementations so that our error injection methodology can control the iteration, vector, position, number of bits and position of the bits of the error injection. We employed 6 solvers and 28 datasets, performed a total of 1,744,800 error injection runs and collected more than 2.5TB data.", + "laborHours": 60.8, + "languages": [], + "name": "pnnl/IMIC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/IMIC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-13", + "metadataLastUpdated": "2019-09-23" + }, + "description": "ButterflyPACK is a mathematical software for rapidly solving large-scale dense linear systems that exhibit off-diagonal rank-deficiency properties. These targeted systems are either matrices arising from discretized boundary integral equations, or frontal matrices in multi-frontal solvers for differential equations. ButterflyPACK relies on low-rank and butterfly formats under Hierarchical matrix, HODLR or HSS frameworks to compress, factor/precondition and solve the linear system in quasi-linear time. ButterflyPACK is particularly useful for large-scale ill-conditioned matrices arising from high-frequency wave equations involving multiple right-hand-sides. \n\nButterflyPACK is based on Fortran 2003, it also has interface written in C++. In addition, ButterflyPACK can be readily invoked from the software STRUMPACK. \n\nButterflyPACK supports hybrid MPI/OpenMP programming models.", + "laborHours": 25931.2, + "languages": [], + "name": "ButterflyPACK", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/liuyangzhuan/ButterflyPACK", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-13", + "metadataLastUpdated": "2020-12-28" + }, + "description": "Neural network was trained on the amino acid sequences of known two-component systems (2CS) pairs. The recommender algorithm uses learned model to select the most likely 2CS pair from an arbitrary set of protein pairs whose amino acid sequences are known.", + "laborHours": 1717.6, + "languages": [], + "name": "Predicting 2CS protein pairs with Deep Learning", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.code.sf.net/p/kinaseorakle/code", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2019-09-23" + }, + "description": "This software implements a new algorithm and its shared-memory parallelization for computing maximum cardinality matchings in bipartite graphs. The algorithm searches for augmenting paths via specialized breadth-first searches (BFS) from multiple source vertices, hence creating more parallelism than single source algorithms.", + "laborHours": 1003.2, + "languages": [], + "name": "Parallel Maximum Cardinality Matchings via Tree-Grafting", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/azadcse/ms-bfs-graft/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2019-09-23" + }, + "description": "Data Elavator allows extensive optimizations, such as overlapping read and write operations, choosing I/O modes, and aligning buffer boundaries. Is as much as 4.2X faster than Cray DataWarp, the start-of-art software for burst buffer, and 4X faster than directly writing to PFS.", + "laborHours": 53473.6, + "languages": [], + "name": "Data Elevator", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/sbyna/dataelevator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "Aluminum is an optimized GPU-aware communication library. It provides a generic Interface to high-performance allreduce algorithms, with support for additional collective operations in progress. Blocking and non-blocking algorithms and GPU-aware algorithms are supported. Aluminum contains custom Implementations and Interfaces to existing optimized communication libraries, exposed through a generic API. ", + "laborHours": 5578.4, + "languages": [], + "name": "Aluminum GPU-aware Communication Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Aluminum", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "Comb is a communication performance benchmarking tool. It is used to determine performance tradeoffs in implementing communication patterns on high performance computing (HPC) platforms. At its core comb runs combinations of communication patterns with execution patterns, and memory spaces. The current set of capabilities Comb provides includes:\no\tConfigurable structured mesh halo exchange communication.\no\tA variety of communication patterns based on grouping messages.\no\tA variety of execution patterns including serial, openmp threading, cuda, cuda batched kernels, and cuda persistent kernels.\no\tA variety of memory spaces including default system allocated memory, pinned host memory, cuda device memory, and cuda managed memory with different cuda memory advice.", + "laborHours": 8071.2, + "languages": [], + "name": "Comb", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Comb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "UEDGE is an interactive suite of physics packages using the Python or BASIS scripting systems. The original (circa 2007) Python version has been supplanted by a version developed under the FACETS SciDAC project [Cary 2008, Mccourt 2012]. The plasma is described by time-dependent 2D plasma fluid equations that include equations for density, velocity, ion temperature, electron temperature, electrostatic potential, and gas density in the edge region of a magnetic fusion energy confinement device. Slab, cylindrical, and toroidal geometries are allowed, and closed Wld open magnetic field-line regions are included. Classical transport is assumed along magnetic field lines, and anomalous transport is assumed across field lines. Multi-charge state impurities can be included with the corresponding line-radiation energy loss. ", + "laborHours": 71576.8, + "languages": [], + "name": "Unified EDGE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/UEDGE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "This project is intended to take a graph and build a smaller (upscaled) graph that is representative of the original in some way. We represent the graph Laplacian in a mixed form, solve some local eigenvalue problems to uncover near-nullspace modes, and use those modes as coarse degrees of freedom.", + "laborHours": 7584.8, + "languages": [], + "name": "GAUSS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gelever/GAUSS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "CKAN plugin for computing and displaying the phase diagram and defect formation energy diagram of a solar cell compound, when given the formation energies and defect formation energies.", + "laborHours": 9408.8, + "languages": [], + "name": "Solar Cell Phase and Defect Formation Energy Diagram", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SC-PD-FED", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "py-hostlist processes slurm-style hostlist strings and can return those strings in manipulated fashion.", + "laborHours": 653.6, + "languages": [], + "name": "py-hostlist", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/py-hostlist", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "SNLS (small non-linear solver) is a C++ library for solving non-linear systems. The emphasis is on small systems on equations for which direct factorization of the Jacobian is appropriate. The systems of equations may be numerically ill-conditioned. Implementation is amenable to GPU usage, with the idea that class instantiate would occur within device functions.", + "laborHours": 699.2, + "languages": [], + "name": "Small Non-Linear Solver", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SNLS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-18" + }, + "description": "SimUtil contains various small utility functions used in multiple HPC simulation codes here at LLNL, such as: simulation parameter input parsing, parallel file-IO, memory allocation, unit parsing, and helper functions for using MPI.", + "laborHours": 3024.8, + "languages": [], + "name": "Simulation Utility Library for HPC codes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/simutil", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-18" + }, + "description": "VPIC I/O Utilities provide scalable input and output code for writing and reading HDF5 data by the Vector Particle-in-cell (VPIC) simulation codes. The I/O utility writes particle, field, and hydro data from VPIC to HDF5 files. The filed and hydro codes also write XDMF files, which can be used by visualization tools such as ParaView to read and visualize the HDF5 data written.", + "laborHours": 744.8, + "languages": [], + "name": "VPIC IO utilities", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/dbin_sdm/viou/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-18" + }, + "description": "Cardioid is a cardiac multiscale simulation suite spanning from subcellular mechanisms up to simulations of organ-level clinical phenomena. The suite contains tools for simulating cardiac electrophysiology, cardiac mechanics, torso-ECGs, cardiac meshing and fiber generation tools.", + "laborHours": 161834.4, + "languages": [], + "name": "Cardioid", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/cardioid", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-18" + }, + "description": "MemSurfer is a software tool to compute bilayer membrane surfaces. These surfaces are found in the biophysical simulations, and generally analyzed using a set of python packages. MemSurfer offers new robust functionalities to compute the undulations in the surfaces, and relevant properties of the lipids *along* the surface, rather than along the projections, as done in many existing tools.", + "laborHours": 4088.8, + "languages": [], + "name": "MemSurfer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MemSurfer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Paracousti simulates 3-D acoustic wave propagation in fixed (non-moving) complex media. It solves the linear acoustic equations of motion using the velocity-pressure system of first order linear differential equations on a finite-difference Cartesian grid using Newton\u2019s law of motion and mass continuity equations. It also has the ability to incorporate acoustic attenuation to simulate non-recoverable energy losses via the velocity-memory-pressure system of linear differential equations. We assume stationary, non-heat conducting, adiabatic media (fluid) where the background sound speed and material density are fixed in time. Capabilities include massively parallel design, optimization for high contrast media interfaces, inclusion of arbitrary pressure and force sources defined by the user, inclusion of arbitrary pressure and velocity receivers defined by the user, acoustic wavefield snapshots in time for visualization, and convolutional perfectly matched layers to minimize artificial grid boundary reflections. Paracousti was built upon the foundational framework of TDAAPS (Time-Domain Atmospheric Acoustic Propagation Suite) by Neill Symons, Dave Aldridge, and Leiph Preston.", + "laborHours": 29488.0, + "languages": [ + "C++", + "C", + "MATLAB", + "Makefile", + "JavaScript" + ], + "name": "Paracousti v. 2.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Paracousti", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 2.0.0" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2019-04-17" + }, + "description": "The QuarkNet Data Acquisition (DAQ) circuit board is provided in a kit that includes a power supply, GPS capability with temperature sensor and cabling, and a USB link to the user\u2019s computer. The DAQ circuit board has 4 analog discriminator inputs and produces trigger time and pulse edge time data for 1- to 4-fold coincidence levels. The DAQ then checks for user-defined trigger multiplicity across the four inputs. If the pulses satisfy the trigger requirement, the DAQ encodes time information for each input. Timing on the DAQ is done with a local clock synchronized to GPS time (via local module) once per second. This gives local times of nearly one nanosecond precision recorded with the accuracy inherent in GPS time. The DAQ kit is equipped to measure ambient temperature and atmospheric pressure; it also can determine its latitude and longitude from the GPS unit. A laptop or desktop computer connects to the DAQ via USB for control and collection of formatted raw data. ", + "homepageURL": "http://quarknet.fnal.gov/toolkits/ati/fnaldet.html", + "laborHours": 0.0, + "languages": [ + "C", + "VHDL" + ], + "name": "QuarkNet DAQ Kit", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://partnerships.fnal.gov/licensing", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://quarknet.fnal.gov/toolkits/ati/fnaldet.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2020-05-27" + }, + "description": "The Umpire library consists of a collection of software components that provide memory and resource management capabilities that can be used by diverse high performance computing (HPC) applications. The current set of capabilities that Umpire provides Includes: \n\u2022\tFlexible allocators to provision memory In the range of available memory resources on a target system.\n\u2022\tAn extensible allocation strategy model, allowing custom algorithms to be used to allocate memory resources in a scalable and high\u00adperformance fashion.\n\u2022\tMemory-location aware operations that can be used to migrate and modify memory using specialized functions dependent on source and target data locations\n\u2022\tA set of Introspection capabilities to allow the user to query the state of the different allocators and memory allocations.", + "laborHours": 30096.0, + "languages": [], + "name": "Umpire", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Umpire", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-20" + }, + "description": "4.Brief Description:\nThis is a LAMMPS extension (LAMMPS \"fix\") to capture electron-ion interaction. We use this extension mechanism to generalize the two\u00ad\ntemperature model to include electron-phonon coupling. The extension is flexible enough to represent cascades, laser heating and equilibration and study energy transport with realistic electron-phonon coupling. ", + "laborHours": 1444.0, + "languages": [], + "name": "Electron-phonon dynamics for LAMMPS ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/USER-EPH", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2019-06-26" + }, + "description": "The non-routine event (NRE) detection and adjustment module provides algorithms to detect and to adjust changes in energy use that are not attributable to installed efficiency measures, and not accounted for in the baseline model's independent variables. The detection algorithm is based on statistical change point algorithm and the adjustment uses a data driven approach to quantify the changes in the energy use that are induced by the NRE.", + "laborHours": 653.6, + "languages": [], + "name": "Non-Routine Event Detection and Adjustment (NRE) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/nre", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-19" + }, + "description": "The Replicative Assessment of Spectroscopic Equipment (RASE) methodology is a semi-empirical approach to generating synthetic gamma-ray spectra for injection into a radionuclide identification algorithm of a vendor-provided detection system. RASE facilitates studies of the spectroscopic device performance and a quantitative assessment of its capabilities to correctly distinguish and identify isotopes of interest in realistic scenarios.", + "laborHours": 4088.8, + "languages": [], + "name": "RASE OSS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RASE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-20" + }, + "description": "CryoH2Vehicle enables to simulate the variations of the thermodynamic states of H2 inside nn onboard vessel, that undergoes n given duty cycle (park/drive/fill). Typical states of charge and boil-off losses can thus be estimated. ", + "laborHours": 380.0, + "languages": [], + "name": "Cryogenic H2 vehicle simulation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/cryoH2vehicle", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-19" + }, + "description": "The software Is an application for Oelta3D, QT and OpenSceneGraph, all of which are external open source software.", + "laborHours": 2447.2, + "languages": [], + "name": "Open Facility Viewer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Open-Facility-Viewer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-19" + }, + "description": "Using machine learning to score potential drug candidates may offer an advantage over traditional imprecise scoring functions because the parameters and model structure can be learned from the data. However, models may lack interpretability, are often overfit to the data, and are not generalizable to drug targets and chemotypes not in the training data. Benchmark datasets are prone to artificial enrichment and analogue bias due to the overrepresentation of certain scaffolds in experimentally determined active sets. Datasets can be evaluated using spatial statistics to quantify the dataset topology and better understand potential biases. Dataset clumping comprises a combination of self-similarity of actives and separation from decoys in chemical space and is associated with overoptimistic virtual screening results. This code explores methods of quantifying potential biases and examines some common benchmark datasets.", + "laborHours": 304.0, + "languages": [], + "name": "Small Molecule Evaluator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SmallMolEval", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-19" + }, + "description": "An agent-based simulation of the innate immune response to bacterial infection.", + "laborHours": 1124.8, + "languages": [], + "name": "Innate Immune Response Agent-based Model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/iirabm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-20" + }, + "description": "ADaPT Is a software library that Is used for mixed preclsk>n ftoatln1 point analysis.", + "laborHours": 456.0, + "languages": [], + "name": "Algorithmic Differentlation Applied to Floating-Point Precision Tuning", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/adapt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-20" + }, + "description": "NLPVis is a visualization system that, through a tight yet flexible integration between visualization elements and the underlying model, allows a user to interrogate the modal by perturbing the input, internal state, and prediction while observing changes. ", + "laborHours": 6551.2, + "languages": [], + "name": "NLPVis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/shusenl/nlpvis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-20" + }, + "description": "Sequedex is computer software to rapidly assign phylogeny and function to short sequences of nucleic acid or protein. In addition, Sequedex comprises functions required to generate underlying data modules as well as tools for analyzing assignments in a variety of contexts.", + "laborHours": 8724.8, + "languages": [], + "name": "Sequedex V2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/sequedex-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-12-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL grid related applications\nObject oriented design intended to facilitate reuse and extensibility of system features. The template enforces that needed structure and behaviors are available. Users may inherit and adapt these structures and behaviors to meet their specific requirements. Recognizes separation of the transactive system calculations into (1) scheduling of assets, (2) balancing of\nsupply and demand, and (3) coordination among independent agents. This separation facilitates useful computation boundaries in which computations can be completed without requiring end-to-end communication for each update. The code provides fundamental market solutions for balancing. The code provides mechanisms for inter-agent coordination. Allows event-driven agent interactions\u037e not limited to prescribed time intervals. Aggregates value and electricity at nodes and conveys opportunities up and down through the network.", + "laborHours": 8952.8, + "languages": [], + "name": "VOLTTRON/volttron-GS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron-GS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-02", + "metadataLastUpdated": "2025-03-26" + }, + "description": "The software is a simplified method for modeling the impact of arbitrary partial shading conditions on PV array performance.\nThe software implements a simple method for modeling shade loss: a database of shade impact results (loss percentages), generated using a validated, detailed simulation tool and encompassing a wide variety of shading scenarios. The database is intended to predict shading losses in crystalline silicon PV arrays and is accessed using basic inputs generally available in any PV simulation tool. Performance predictions using the database are within 1-2% of measured data for several partially shaded PV systems, and within 1% of those predicted by the full, detailed simulation tool on an annual basis. The shade loss database shows potential to considerably improve performance prediction for partially shaded PV systems.", + "homepageURL": "https://github.com/NREL/ssc/blob/develop/shared/lib_pv_shade_loss_mpp.cpp", + "laborHours": 2204.0, + "languages": [ + "C++" + ], + "name": "PV Shading Database [SWR-16-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ssc/blob/develop/shared/lib_pv_shade_loss_mpp.cpp", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-01-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "HyperNetX is a Python library of classes, algorithms, and generators for working with multi-way and nested relational data. Given a network of nodes and relationships, the base class HyperNetX.Entity is used to instantiate individual data elements along with their relationships to other elements of the network. By exploiting Python's dictionary data structure we capture both multi-way and nested data structures with constant time lookup. The base class HyperNetX.Hypergraph instantiates a network of this data into a hypergraph structure. Many of the common metrics and features of graphs, such as diameter, connectedness, and clustering coefficient, have analogous definitions with respect to hypergraphs, which are computed using algorithms in the HyperNetX library.", + "laborHours": 14789.6, + "languages": [ + "Python" + ], + "name": "pnnl/HyperNetX", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/HyperNetX", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-04", + "metadataLastUpdated": "2023-11-02" + }, + "description": "Keras layers for end-to-end learning on molecular structure. Based on Keras, Tensorflow, and RDKit. Source code used in the study Message-passing neural networks for high-throughput polymer screening. SEE ALSO https://github.com/NREL/alfabet", + "laborHours": 866.4, + "languages": [ + "Python" + ], + "name": "ALFABET\u2122 and nfp (Neural Fingerprint) [SWR-19-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/nfp", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-07", + "metadataLastUpdated": "2019-01-08" + }, + "description": "The Anno log annotation system provides tools for creating and querying annotations to supercomputing log data.", + "laborHours": 1109.6, + "languages": [], + "name": "Anno v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/agreiner/anno", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-08", + "metadataLastUpdated": "2019-09-23" + }, + "description": "Implementation of a flexible Grazing Incidence Small-Angle Scattering (GISAXS). Simulation code based on the Distorted Wave Born Approximation (DWBA) theory that effectively utilizes the parallel processing power provided by graphic processors and multicore processors. This constitutes a handy tool for experimentalists facing a massive flux of data, allowing them to accurately simulate the GISAXS process and analyze the produced data. The software computes the diffraction image for any given super position of custom shapes or morphologies in a user-defined region of the reciprocal space for all possible grazing incidence angles and in-plane sample rotations. This flexibility then allows to easily tackle a wide range of possible sample structures such as nanoparticles o top of or embedded in a substrate or a multilayered structure. In cases where the sample displays regions of significant refractive index contrast, an algorithm has been implemented to perform a slicing of the sample along the vertical direction and compute the averaging refractive index profile to be used as the reference geometry of the unpertubed system. Preliminary tests show good agreement with experimental data for a variety of commonly encountered nanostructures.", + "laborHours": 20033.6, + "languages": [], + "name": "HipGISAXS", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/hipgisaxs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-08", + "metadataLastUpdated": "2021-08-05" + }, + "description": "This is an open-source, empirical data-driven, virtual building energy analysis and retrofit targeting tool. The open-source tool will provide a fully-automated, \"no-cost/no-touch\" approach to screen large volumes of buildings for operational improvement and equipment upgrade opportunities and quantify associated potential energy and cost savings.", + "laborHours": 1292.0, + "languages": [], + "name": "Building Efficiency Targeting Tool for Energy Retrofits (BETTER) Analytical Engine", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-JCI-ICF/BETTER", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-09", + "metadataLastUpdated": "2019-06-26" + }, + "description": "Research Network Transfer Performance Predictor (netperf-predict) v 0.9", + "laborHours": 152.0, + "languages": [], + "name": "Research Network Transfer Performance Predictor (netperf-predict) v 0.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/tstat-dtn-analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "0.9" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-01-09", + "metadataLastUpdated": "2019-03-25" + }, + "description": "AIMFAST is a software code used to align facets on a dish or heliostat solar concentrator to a specific aimpoint strategy to minimize peak fluxes and maximize system optical performance. AIMFAST uses a large monitor or projection screen to display fringe patterns, and a machine vision camera to image the reflection of these patterns in the subject dish mirrors. From these images, a detailed map of surface normals can be generated and compared to design or fitted mirror shapes. This fitted comparison is then used to develop a single vector representing the orientation of the facets relative to the design orientation and provide near-real-time adjustment information to a communicating computer. The communicating computer can display adjustments or directly interface with adjustment tools. ", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 4879.2, + "languages": [ + "MATLAB" + ], + "name": "Alignment Implementation for Manufacturing using Fringe Analysis Slope Technique (AIMFAST) 2018.11.20", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "2018.11.20" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-09", + "metadataLastUpdated": "2019-01-15" + }, + "description": "The CBES API provides Application Programming Interface to a suite of functions to improve energy efficiency of buildings, including building energy benchmarking, preliminary retrofit analysis using a pre-simulation database DEEP, and detailed retrofit analysis using energy modeling with the EnergyPlus simulation engine. New capabilities in version 2.0 include renewable technologies (PV, storage), advanced HVAC systems, demand response measures, TDV (Time Dependent Valuation energy) metrics, as well as shading from adjacent buildings, trees or roof obstructions. The CBES API is used to power the LBNL CBES Web App. It can be used by third party developers and vendors.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1501972.8, + "languages": [], + "name": "Commercial Building Energy Saver, API (CBES API) v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-01-09", + "metadataLastUpdated": "2019-03-25" + }, + "description": "SOFAST is used to characterize the surface slope of reflective mirrors for solar applications. SOFAST uses a large monitor or projection screen to display fringe patterns, and a machine vision camera to image the reflection of these patterns in the subject mirror. From these images, a detailed map of surface normals can be generated and compared to design or fitted mirror shapes. SOFAST uses standard Fringe Reflection (Deflectometry) approaches to measure the mirror surface normals. SOFAST uses an extrinsic analysis of key points on the facet to locate the camera and monitor relative to the facet coordinate system. It then refines this position based on the measured surface slope and integrated shape of the mirror facet. The facet is placed into a reference frame such that key points on the facet match the design facet in orientation and position. This is key to evaluating a facet as suitable for a specific solar application. SOFAST reports the measurements of the facet as detailed surface normal location in a format suitable for ray tracing optical analysis codes. SOFAST also reports summary information as to the facet fitted shape (monomial) and error parameters. Useful plots of the error distribution are also presented.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 10822.4, + "languages": [], + "name": "Sandia Optical Fringe Analysis Slope Tool (SOFAST) v. 2018.11.20", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 2018.11.20" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-11", + "metadataLastUpdated": "2019-01-15" + }, + "description": "The CBES App is a web-based toolkit for use by small businesses and building owners and operators of small and medium size commercial buildings to perform energy benchmarking and retrofit analysis for buildings. 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The model efficiently describes Li diffusion dynamics in active material and electrolyte phases, charge transfer kinetics, charge balance, and electron transport processes. The model requires a separate pre-processing step to identify SVM parameters.\n", + "homepageURL": "https://www.nrel.gov/workingwithus/licensing.html", + "laborHours": 0.0, + "languages": [ + "C", + "MATLAB" + ], + "name": "State-variable model of porous electrode batteries 1-D electrochemical/thermal behavior", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrel.gov/workingwithus/licensing.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrel.gov/workingwithus/licensing.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-23", + "metadataLastUpdated": "2019-01-25" + }, + "description": "This computer software is a MATLAB standalone code for implementation of the Lumped Particle Domain model. 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The profiles are directly interpretable for non-destructive imaging of large imaging datasets that span the micron to millimeter size scale.", + "laborHours": 0.0, + "languages": [], + "name": "COMPACT", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/idaholabresearch-compact", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-23", + "metadataLastUpdated": "2023-12-13" + }, + "description": "The REopt\u00ae techno-economic decision support platform is used by NREL researchers to optimize energy systems for buildings, campuses, communities, microgrids, and more. REopt recommends the optimal mix of renewable energy, conventional generation, and energy storage technologies to meet cost savings, resilience, emissions reductions, and energy performance goals. The REopt\u00ae model provides concurrent, multiple technology integration and optimization capabilities to help organizations meet their cost savings and energy performance goals. Formulated as a mixed integer linear program, the REopt model recommends an optimally sized mix of renewable energy, conventional generation, and energy storage technologies; estimates the net present value of implementing those technologies; and provides a dispatch strategy for operating the technology mix at maximum economic efficiency. The REopt model was initially created to identify and prioritize cost-effective renewable energy projects across a portfolio of sites. The model is now also used to optimize the size and operating strategy of microgrids, storage, and energy/water systems.", + "homepageURL": "https://reopt.nrel.gov", + "laborHours": 130932.8, + "languages": [], + "name": "REopt\u00ae [SWR-12-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://reopt.nrel.gov/contacts.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://reopt.nrel.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-01-24", + "metadataLastUpdated": "2024-07-26" + }, + "description": "https://www.osti.gov/doecMatMCNP is a code for generating material cards for the MCNP radiation transport code. 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In addition to producing the material cards for MCNP, the code calculates the atomic (or number) density in atoms/barn-cm as well as the multiplier that should be used to convert neutron and gamma fluences into dose in the material specified.", + "laborHours": 4544.8, + "languages": [ + "Fortran", + "Python" + ], + "name": "MatMCNP v. 4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MatMCNP", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 4.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-24", + "metadataLastUpdated": "2019-01-24" + }, + "description": "An algorithm that infers the reaction SMARTS pattern for a biochemical reaction, given an atom-atom mapped reaction input. The algorithm can create patterns of variable specificity, depending on user needs. The SMARTS patterns can be used to computationally assess hypothetical biochemical reactions that would generate hypothetical or novel compounds. If all known compounds are run through all known SMARTS, a theoretical biochemical reaction network could be formed for biological discovery purposes.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 866.4, + "languages": [], + "name": "Automated Biochemical Reaction Coder (Reactionizer) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-01-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Generate random global temperature fields with spatial and temporal correlation derived from an ESM\nAs of version 2.0, fldgen allows to emulate any climate variable, not just ones that are approximately normally distributed, and it allows us to emulate climate variables in combinations, such as temperature and precipitation. These new capabilities can be used for risk modeling in areas such as drought and it agricultural impacts, where both temperature and moisture play a role.", + "laborHours": 988.0, + "languages": [], + "name": "JGCRI/fldgen", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/fldgen", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-25", + "metadataLastUpdated": "2019-01-31" + }, + "description": "The software is for detecting and identifying anomalies within gamma-ray spectra. The design enables quick implementation, testing, comparison, and deployment of different anomaly and identification algorithms. The software currently contains implementations of four algorithms, two of which are common place within the field, and two that novel research products from this effort.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 3815.2, + "languages": [], + "name": "Berkeley Anomaly Detection (BAD) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-28", + "metadataLastUpdated": "2019-01-29" + }, + "description": "PhyCA allows interpretation of a PhyloChip assay. 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The software depends on other software to be installed on the same machine as PhyCA.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1352.8, + "languages": [], + "name": "PhyCA-PhyloChip Analysis", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-28", + "metadataLastUpdated": "2019-01-29" + }, + "description": "The National Renewable Energy Laboratory, NREL and Argonne National Laboratory, ANL are creating an open-source situational awareness and decision support platform called WindView that provides grid operators with knowledge on the state and performance of wind power on their system. 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Once complete, it will be publicly available for industry and academic researchers.", + "laborHours": 9971.2, + "languages": [ + "JavaScript", + "css", + "html" + ], + "name": "WindView", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/windview/client", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-30", + "metadataLastUpdated": "2019-02-01" + }, + "description": "TOUGHREACT V3.32 is a 3-D reactive transport code that handles to non-isothermal, multiphase/multicomponent fluid flow, heat transport, aqueous and gaseous species advection-diffusion, and equilibrium/kinetic water-gas-rock-biological reactions. 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This request is to re-license the flux framework in full to LGPLv3 to better support vendor collaboration and allow use of external apache2 and similarly licensed libraries.\nflux is a framework for writing resource managers as well as a resource manager for HPC systems. It allows for hierarchical nesting and providing a portable interface for job scheduling across systems.", + "laborHours": 118028.0, + "languages": [], + "name": "Flux Resource Manager Framework", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/flux-framework/flux-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-01-31", + "metadataLastUpdated": "2019-02-01" + }, + "description": "Sonar contains software for managing a HPC performance-monitoring software stack. This includes streaming data into a distributed Kafka message queue, storing/querying from a distributed Cassandra database, and front-end tools for secure access, visualization, and analytics of facility-wide performance data.", + "laborHours": 790.4, + "languages": [], + "name": "Sonar", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sonar-driver", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-01", + "metadataLastUpdated": "2019-02-01" + }, + "description": "The invention simulates multi-dimensional, multi-phase, multi-component, non-isothermal flow and transport in fractured porous media, with applications in geosciences and reservoir engineering among others. The invention supports a number of different combinations of fluids and components from previous software versions.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TOUGH3 v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-02-04", + "metadataLastUpdated": "2019-02-05" + }, + "description": "The Hydrogen Dispenser Test Apparatus (HDTA) is used to validate hydrogen fueling station performance. This software takes the data generated from HDTA and compares it to fueling standards CSA HGV4.3 and SAE J2601. The software generates plots and metrics for pressure, temperature and IR communications from the HDTA.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "HDTADA", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HDTADA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "nlogan@pppl.gov" + }, + "date": { + "created": "2019-02-07", + "metadataLastUpdated": "2019-02-12" + }, + "description": "The Generalized Perturbed Equilibrium Code (GPEC) package contains a suite of non-axisymmetric stability and perturbed equilibrium force balance codes including DCON/RDCON/STRIDE (stability), GPEC (driven plasma response), and PENTRC (NTV torque). The perturbation calculations can optionally use ideal MHD throughout, kinetic MHD throughout, or a mix of ideal MHD outer layer and resistive MHD inner layer physics at the rational surfaces. \n\nEarlier versions of this software contained only the ideal MHD model, and results were published under the name of the Ideal Perturbed Equilibrium Code (IPEC).\n\nPrimary journal citations can be found on the landing page.", + "homepageURL": "http://princetonuniversity.github.io/GPEC", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Generalized Perturbed Equilibrium Code", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://princetonuniversity.github.io/GPEC", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://princetonuniversity.github.io/GPEC", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "version": "1.2" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-02-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A tool for inferring and analyzing forecast-guided dam and reservoir operations", + "laborHours": 410.4, + "languages": [], + "name": "IMMM-SFA/horizon", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/horizon", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-02-08", + "metadataLastUpdated": "2019-03-22" + }, + "description": "Resonance Control GUI for LCLS-II ResCtl System is a Qt5-based, python GUI used for interacting with an LCLS-II resonance control system for an 8-cavity cryomodule. The code is written in Python, and can use auxiliary software Qt5, pyqtgraph, numpy, and scipy. The code is operating system-agnostic, has no specific hardware requirements, and has no embedded source code.", + "homepageURL": "http://pip2.fnal.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Resonance Control GUI for LCLS-II ResCtl System", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://pip2.fnal.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-08", + "metadataLastUpdated": "2019-04-29" + }, + "description": "(based on Erbilgin et al., BMC Bioinformatics, 2017, 18:57). 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Studying the temporal substrate utilization by individuals is individuals in mixed cultures is an important first step in developing approaches to better model these biochemical processes and microbial communities found in nature. \n\nThe 2017-004 software is comprised of four custom iPython notebooks that were used for all computational tasks in the experimental work described in \"Dynamic substrate preferences predict metabolic properties of a simple microbial consortium\" (Erbilgin et al., BMC Bioinformatics, 2017). The results indicate that a significant portion of a model community's overall metabolism can be predicted based on the metabolism of the individuals. The results further suggest that, when the mixed culture's substrate depletion significantly deviates from such a prediction, this may highlight potential metabolic pathways affected by species-species microbial interactions, leading to hypotheses about how a particular microbial community's structure and function may be modulated to perform a particular biotechnological goal.", + "laborHours": 501.6, + "languages": [], + "name": "Predicting Coculture Substrate Depletion (PCSD) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biorack/bmc_bioinf_2016_erbilgin", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-08", + "metadataLastUpdated": "2019-02-19" + }, + "description": "\tWith the benefit of hindsight, it is easy to see that the readout of the human genome, spectacular milestone that it was, represents only the beginning of the \"omics\" information explosion. The technical side of the 'omics explosion--enabling researchers to efficiently readout terabytes of information spelling out whole genomes, transcriptomes, proteomes and metabolomes, does not per se provide a clear picture of how life works. Nor does it show us how we can engineer biology to solve the grand challenges of the 21st century: feeding 10 billion people with declining per capita supplies of arable land and clean water, sustaining biological diversity and slowing the increase in greenhouse gas formation, primarily carbon dioxide and methane. \n\nThe 2017-063 invention--Metabolites and Genes Integration Technology--proposes an integrated approach to correcting and connecting the dots of the 'omics explosion: linking genes to proteins, proteins to pathways, pathways to biochemical reactions and metabolites. The '063 invention is potentially transformational in that it can generate testable hypotheses across thousands of genes to predict their chemical and metabolic products. It can also do the reverse; i.e., starting from chemical and metabolic products it can generate testable hypotheses about which genes and pathways those molecules are linked to. Since we know that genomic, transcriptomic, proteomic and metabolomic databases are chock full or erroneous information, MAGI also has the unique benefit of correcting these errors through its own independent pathway of bidirectional hypothesis generation (genes=>proteins=>metabolites + metabolites=>proteins=>genes). Perfectly amenable to high-throughput hypothesis generation and experimentation, MAGI can transform our understanding of human, animal, plant and microbial biology over several decades, laying the essential knowledge foundation to addressing the grand scientific challenges of the 21st century.", + "laborHours": 1352.8, + "languages": [], + "name": "Metabolites Annotations and Genes Integrated (MAGI) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biorack/magi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-08", + "metadataLastUpdated": "2019-04-29" + }, + "description": "AERCalc is a software tool for evaluating the energy performance of window attachments (e.g., shading systems, attached window panels, etc.). All the annual energy modeling is performed by the EnergyPlus OS engine. The program incorporates a user-friendly GUI.", + "laborHours": 67564.0, + "languages": [], + "name": "AERCalc v1.2.10", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/AERCalc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "1.2.10" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-02-11", + "metadataLastUpdated": "2019-02-11" + }, + "description": "OpenDSSDirect.jl is a cross-platform Julia package implements a \"direct\" library interface to OpenDSS using dss_capi. OpenDSS is an open-source distribution system simulator. See OpenDSSDirect.py for a similar package in Julia.\n\nThis package is now available for Windows, Mac, and Linux.", + "laborHours": 7022.4, + "languages": [ + "Julia" + ], + "name": "OpenDSSDirect.jl", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dss-extensions/OpenDSSDirect.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-02-12", + "metadataLastUpdated": "2019-03-22" + }, + "description": "Skybright is a utility to estimate the sky brightness in images of the sky taken by optical astronomical telescopes. It uses a simple three component model, including airglow, scattered moonlight, and twilight. The code is derived from an extraction of the sky estimation code in obstac, the telescope scheduling code used by the Dark Energy Survey (written by the same author).", + "laborHours": 395.2, + "languages": [ + "Python" + ], + "name": "skybright", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ehneilsen/skybright", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-02-12", + "metadataLastUpdated": "2019-02-13" + }, + "description": "Enable developers to run the Granta MI Scripting Toolkit (MSTK) within a docker container. Developers who work with the MSTK can use this tool to test their code on various operating systems, as well as load custom Python libraries as desired. This can help to replicate an environment as close to production as possible. The MSTK does not officially support macOS, as such this docker project allows macOS users to quickly spin up an environment to develop with the toolkit without the need to use a dedicated VM.", + "laborHours": 106.4, + "languages": [], + "name": "mstk-docker", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mstk-docker", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-02-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "In order to support different hardware configurations, an extensible and modular software architecture was developed that could adapt to new requirements in an agile manner. This led to the design of an application programming interface or software development kit that would allow for the rapid integration of new hardware plugins, including AMPS, MIPS, and National Instruments, along with support for digitizers from vendors such as Acqiris. The use of ZeroMQ and a simple communication protocol allows for real time data display and analysis. This is achieved via a separate application simply called the AgMD1 Console. This application allows for low level foreign function interface (FFI) calls to the AGMD1 libraries to operate the U1084A analog-to-digital converter.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Falkor Data Station", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/business/default.aspx?topic=Licensing_Guidelines", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-02-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The acquisition of analog signal from a time of flight mass spectrometer requires robust, efficient, and fast software. Writing multi-threaded applications is inherently more challenging due to the potential for livelocks, deadlocks, and race conditions. Rust was identified as a \"safe\" language that has a compiler that statically checks the code for these potential problems and prevents compilation entirely if detected. Rust is a systems level language, on par with C / C++. However, it supports a thriving package management system similar to npm or NuGet and has other modern features which make it accessible for rapid prototyping and simplifies compilation procedures.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Falkor 'Rust' Acquisition Module", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/business/default.aspx?topic=Licensing_Guidelines", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-02-19", + "metadataLastUpdated": "2019-02-20" + }, + "description": "nSnare\u2122 analyses and categorizes log messages generated by various and customizable third party software packages using a custom multi-tiered rules engine. Each log message is either determined to be a false positive, or it is assigned a score based on the severity of the potential attack and confidence that the activity described by the log message is not a false positive. Log messages are then assigned to an event, which is a collection of log messages related to a single potential attack. Meta-analysis rules run on the collection of all logs within an event to correlate multiple related logs into a single known attack signature. When the sum of the scores of all logs within an event exceeds a pre-defined threshold, the event is labelled as an attack and an automated response is generated to block the attacker from connecting to any protected resources, called quarantining within the application, for a variable length of time. The length of time that the quarantine lasts for is based on the severity and frequency of the attack, along with historical information on the attacker and any third party provided threat intelligence data that the system has gathered. An additional random length of time is added to each quarantine so the algorithm cannot easily be learned and bypassed by a persistent attacker. A confidence score is generated based on a proprietary algorithm that determines the likelihood that the data which lead to the attacker getting quarantined was a false positive. A threat intelligence record is created for each detected attack, with details on the attacker, a summary of what triggered the quarantine, the severity of the attack and the confidence the system has that the attack is not the result of false data, which can then be shared with external entities so that they can also protect themselves from a related attack.\n\nThe software also includes a web based front end for analyzing the current quarantined attacks, removing a quarantine in the case of a false positive, viewing previously quarantined attacks, and tracking suspicious activity that the system is currently evaluating. The web interface also allows the creation and modification of rules used by the rules engine, and the maintenance of a whitelist of known good systems that should never be automatically quarantined.\n", + "homepageURL": "https://www.labpartnering.org/lab-technologies/09425b12-3332-4a90-892d-44dbb8e1be34", + "laborHours": 0.0, + "languages": [], + "name": "nSnare\u2122", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.labpartnering.org/lab-technologies/09425b12-3332-4a90-892d-44dbb8e1be34", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.labpartnering.org/lab-technologies/09425b12-3332-4a90-892d-44dbb8e1be34", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-25", + "metadataLastUpdated": "2019-05-31" + }, + "description": "WINGRIDDER V3.0 is a Windows-based software for designing and generating numerical grids for numerical simulators that are based on the \"integral finite difference\" or the \"control volume\" numerical scheme (e.g., TOUGH2, Pruess et al., 1996). The user can design and generate grid that properly represents the stratigraphic features, inclined faults, and repository. WINGRIDDER V3.0 is an upgrade from WINGRIDDER V2.0. This revision includes testable requirements as listed in the Requirements Document (RD), 10024-RD-3.0-00, Section 2. With new features, WINGRIDDER V3.0 adds the ability to generate a multiple-interactive-continuum (MINC) grid.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "WinGridder-A graphic grid generator for TOUGH2 simulators (WinGridder) v3.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-02-26", + "metadataLastUpdated": "2019-03-22" + }, + "description": "TRACE is a debugging and logging utility written in C/C++, perl, and shell", + "homepageURL": "https://cdcvs.fnal.gov/redmine/projects/trace", + "laborHours": 0.0, + "languages": [ + "C", + "C++" + ], + "name": "TRACE", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cdcvs.fnal.gov/redmine/projects/trace", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-02-27", + "metadataLastUpdated": "2019-02-27" + }, + "description": "PYB11Generator is a code generator to simplify using the open-source pybind11 package for interoperability between C++ and Python. PYB11Generator parses a description of the C++ code to be exposed to Python written in pure Python syntax, and generates the pybind11 C++ coding which can be compiled into a shared library allowing the C++ code to be used from Python. The purpose of PYB11Generator is to simplify this process of binding together C++ and Python, removing much of the redundant code needed by pybind11 such as trampoline classes for providing virtual function overrides in Python.", + "laborHours": 1231.2, + "languages": [], + "name": "PYB11Generator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmikeowen/pyb11generator", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-02-28", + "metadataLastUpdated": "2024-02-09" + }, + "description": "The OpenStudio\u00ae-ERI project allows calculating an Energy Rating Index (ERI) using the Department of Energy's open-source OpenStudio\u00ae/EnergyPlus\u00ae simulation platform. The building description is provided in an HPXML file format. The project supports: - ANSI/RESNET/ICC 301\u00a9 Standard for the Calculation and Labeling of the Energy Performance of Dwelling and Sleeping Units using an Energy Rating Index - ENERGY STAR Certification System for Homes and Apartments Using an ERI Compliance Path - IECC ERI Compliance Alternative (Section R406) - DOE ZERH Certification Using an ERI Compliance Path For more information on running simulations, generating HPXML files, etc., please visit the documentation at https://openstudio-eri.readthedocs.io/en/latest/", + "laborHours": 249295.2, + "languages": [ + "Ruby" + ], + "name": "OpenStudio\u00ae Energy Rating Index (ERI) Workflow (SWR-18-72)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-ERI", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.5.2" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-06", + "metadataLastUpdated": "2019-03-06" + }, + "description": "Ladybug Tools IN2 Measures is a collection of OpenStudio\u00ae measures, file formats, scripts, and related tools for integrating Ladybug Tools with energy modeling via OpenStudio. ", + "laborHours": 0.0, + "languages": [], + "name": "Ladybug Tools IN2 Measures", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ladybug-tools-in2/standards-measure", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-11", + "metadataLastUpdated": "2019-03-12" + }, + "description": "Coramin is a package that provides tools for developing tailored algorithms for mixed-integer nonlinear programming problems. This software includes the ability to:\n- Generate convex or piecewise relaxations of nonlinear optimization problems, addressing bilinear, quadratic, and convex/concave univariate functions\n- Perform optimization-based bounds tightening on all or subsets of the problem variables\n- Generate polyhedral envelopes for multi-linear functions", + "laborHours": 2006.4, + "languages": [ + "Python" + ], + "name": "Coramin v. 0.1 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Coramin/Coramin", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.1" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-11", + "metadataLastUpdated": "2019-03-12" + }, + "description": "Egret is a package that provides tools for building electric grid optimization models. This software includes objects and functions for parsing, storing, and managing electric grid data. Egret also includes the following electric grid models:\n- ACOPF (alternating current optimal power flow)\n- DCOPF \u2013 a linearized transmission model\n- ACOPF relaxations\n- Unit commitment\n- Economic dispatch", + "laborHours": 7174.4, + "languages": [ + "Python" + ], + "name": "Egret v. 0.1 (beta)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/grid-parity-exchange/Egret", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.1 (beta)" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2019-03-13" + }, + "description": "This software uses averaged weighted estimators to classify instances and then explicate the individual decision process in classification. The software has state of the art performance in accuracy, while maintaining full explainability. It does this by calculating hierarchically averaged probabilities for a large class of feature combinations and updating them \u2018on-the-fly\u2019. On the fly updating also allows the model to be accurate, relative to the total dataset, maintaining accuracy in real-time, without a need to retrain the classifier. ", + "laborHours": 31768.0, + "languages": [ + "C++", + "Python" + ], + "name": "AWE-ML: Averaged Weights for Explainable Machine Learning v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/aweml", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2019-03-13" + }, + "description": "Stitch is a new IO library focused around supporting simulations where only a small portion of the simulation space changes at each timestep. It improves storage efficiency by only storing the changed data and constructs on request a view of an arbitrary region at a given time by stitching together parts of various outputs. This enables scaling from a single process to 100s of nodes.", + "laborHours": 113270.4, + "languages": [ + "C", + "Python" + ], + "name": "Stitch v. 1.0 IO Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gflofst/stitch-io", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2019-03-12" + }, + "description": "The MPRM is a simulation code that is used to statistically quantify the performance and reliability of a microgrid operating in islanded mode. Performance can be expressed in terms of fuel efficiency, renewable penetration, and other operational characteristics of the grid. Reliability can be expressed in terms of frequency and magnitude of load loss on a tier-by-tier, bus-by-bus basis or on an", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 30612.8, + "languages": [], + "name": "The Microgrid Performance Reliability Model (MPRM) v. 1.50 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.50 Beta" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2019-03-12" + }, + "description": "The software generates and analyzes nuclear magnetic resonance spin diffusion simulations for the purpose of measuring domain sizes or spin diffusion constants in a heterogenous sample. Its primary capabilities are:\n1.\tIt solves the spin magnetization diffusion equation to simulate the results of a spin diffusion experiment using any structural input geometry, including structure models generated by molecular dynamics or other computational or experimental methods.\n2.\tIt compares the results of simulations on an input structure to experimental data, providing a data fitting algorithm to extract physical information from the experimental data via the simulation.\n3.\tIt can provide statistical measures to compare correlations between structural models, to determine domain clustering and connectedness, and to provide goodness-of-fit measures including chord length distributions, chi-squared values, Pearson coefficients and pair correlation functions.\n4.\tIt provides output reports, data files, and movies to visualize simulation results.\n", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 410.4, + "languages": [ + "MATLAB" + ], + "name": "NMR_DIFFSIM v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2019-03-12" + }, + "description": "Evaluating the effectiveness of data visualizations is a challenging undertaking and often relies on one-off human subject studies that test a visualization in the context of one specific task. Researchers across the fields of data science, visualization, and human-computer interaction are calling for foundational tools and principles that could be applied to assessing the effectiveness of data visualizations in a more rapid and generalizable manner. The visual saliency model for data visualizations described here addresses this need for evaluation tools. Visual saliency models assess the visual features (e.g. color, contrast, edges) of an image to predict which areas of that image will draw a viewer\u2019s attention. Providing predictions of where viewers will look in a visualization based on the saliency of the various regions and elements in that image could help designers to assess whether or not their design will draw the viewer\u2019s attention as intended. The Data Visualization Saliency model, a saliency model for data visualizations, consists of two parts: a text saliency map and a modified version of the Itti, Koch and Niebur model [1]. The final saliency map is a linear combination of the two. The text saliency map is created from an algorithm that computes the likelihood of belonging to a text region for each pixel of an input visualization image. The modified Itti model transforms the original input image to a representation in CIE LAB color space, which provides an accurate representation of perceptual color opponency.\n\nFor a given input data visualization image, the Data Visualization Saliency model computes and returns the visualization saliency map highlighting areas of the data visualization that will draw a viewer\u2019s attention. It also returns the lower level saliency maps for text and the modified Itti model.\n\n", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 1869.6, + "languages": [ + "MATLAB" + ], + "name": "Data Visualization Saliency v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2022-06-27" + }, + "description": "SolTrace is a software tool developed at the National Renewable Energy Laboratory (NREL) to model concentrating solar power (CSP) systems and analyze their optical performance.\n\nAlthough ideally suited for solar applications, the code can also be used to model and characterize many general optical systems. The creation of the code evolved out of a need to model more complex solar optical systems than could be modeled with existing tools.\n\nSolTrace can be installed either using the official NREL packaged distribution or from source code at the SolTrace open source project website. NREL welcomes contributions from programmers to the simulation engine or to the interface and encourages interested persons to get involved. More information on contributing, compiling the source code, and license requirements is available on the project website.(https://www.nrel.gov/csp/soltrace.html). For details on integration with SAM, see the SAM website. (https://sam.nrel.gov/)", + "laborHours": 10381.6, + "languages": [ + "C++", + "css", + "html", + "Tex", + "JavaScript", + "Python" + ], + "name": "SolTrace (Optical Analysis Software)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SolTrace", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.0.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-13", + "metadataLastUpdated": "2019-10-23" + }, + "description": "The Connected and Automated Vehicles Scenario Generation (CSG) model is a system dynamics model. It was built by NREL and funded by the U.S. Department of Energy under the Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility initiative. The purpose of the model is to simulate the \u201ctransitions from predominantly individual ownership of non-CAVs to various future scenarios of high connectivity/automation\u201d(Bush, Vimmerstedt, and Gonder 2019).", + "laborHours": 30.4, + "languages": [ + " STELLA Professional 1.9.1. " + ], + "name": "CSG-public", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CSG-public", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-13", + "metadataLastUpdated": "2023-05-30" + }, + "description": "The Alternative Fueling Station Locator app helps you find fueling stations that offer electricity, natural gas, biodiesel, ethanol (E85), propane, and hydrogen.\n\nUse your current location or enter a custom location to find the 20 closest stations within a 30-mile radius. View the stations on a map or see a list of stations ordered by distance from your location. Select your alternative fuel of choice and adjust the custom filters to fit your needs.\n\nSelect a station from the map or list to view contact info and other details:\n- address, phone number, and hours of operation\n- payment types accepted\n- public or private access\n- special services\n- compression (natural gas)\n- vehicle size access (natural gas)\n- number and types of chargers (electric)\n- blends available (biodiesel)\n- blender pumps (ethanol)\n\nThe free app draws information from the U.S. Department of Energy's Alternative Fuels Data Center, which houses the most comprehensive, up-to-date database of alternative fueling stations in the United States. The database contains location information for more than 25,000 alternative fueling stations throughout the country.", + "homepageURL": "https://afdc.energy.gov/stations#/find/nearest", + "laborHours": 29518.4, + "languages": [ + "JavaScript", + "HTML", + "CSS" + ], + "name": "Alternative Fueling Station Locator - ANDROID [SWR 17-07]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrel.gov/disclaimer.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://afdc.energy.gov/stations#/find/nearest", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "1.0.2 (as of 3/13/2019)" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-13", + "metadataLastUpdated": "2023-05-30" + }, + "description": "The free Alternative Fueling Station Locator app helps you find fueling stations that offer electricity, natural gas, biodiesel, E85, propane, or hydrogen.\n\nUse your current location or enter a custom location to find the 20 closest stations within a 30-mile radius. View the stations on a map or see a list of stations ordered by distance from your location. Select your alternative fuel of choice and adjust the custom filters to fit your needs.\n\nSelect a station from the map or list to view contact info and other details:\n- address, phone number, and hours of operation\n- payment types accepted\n- public or private access\n- special services\n- compression (natural gas)\n- vehicle size access (natural gas)\n- number and types of chargers (electric)\n- blends available (biodiesel)\n- blender pumps (ethanol)\n\nThe app draws information from the U.S. Department of Energy's Alternative Fuels Data Center, which houses the most comprehensive, up-to-date database of alternative fueling stations in the United States. The database contains location information for more than 15,000 alternative fueling stations throughout the country.", + "homepageURL": "https://afdc.energy.gov/stations#/find/nearest", + "laborHours": 29518.4, + "languages": [ + "Objective-C" + ], + "name": "Alternative Fueling Station Locator - APPLE [SWR 17-06]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrel.gov/disclaimer.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://afdc.energy.gov/stations#/find/nearest", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "1.1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-03-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Collection of measurements and metrics to be used on social network data. The task was to develop a set of measurements and metrics that can be used to measure the effectiveness of various social network simulations. Provides a collection of measurements and metrics. This takes a variety of metrics and measurements and packages them into a consistent framework.", + "laborHours": 23134.4, + "languages": [], + "name": "pnnl/socialsim_package", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/socialsim_package", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-14", + "metadataLastUpdated": "2019-03-18" + }, + "description": "As systems and devices become virtualized and deployed in the cloud, the hypervisor becomes an increasingly appropriate place to collect performance data, system state, system landscape, function calls, transaction traces, and other characteristics. We developed a method by which an introspection application may be coupled with a hypervisor to \u201creach into\u201d the VM with minimal intrusiveness to collect data critical to the reconstruction of events, files, and operations. Such a capability is required to take advantage of the hypervisor as an instrumentation platform and to integrate that data with more traditional collection mechanisms. The concept of a VM serviced by a lightweight hypervisor is a relatively new paradigm for forensic practitioners. Traditional forensic techniques, based on assumptions that the filesystem was directly interacting with the hardware through an abstraction, afforded the forensic practitioner the assumption that there was nothing controlling the application below the filesystem. This is not the case when using virtualized technologies. Hypervisors can covertly monitor, introspect and interact with the guest in a transparent fashion. The problems of storage and collection of actionable data are exhausting. The current challenge is most hypervisors do not expose a useful application programming interface (API) at a sufficient level to do transparent, fine-grained and customizable introspection. Scalable VM instrumentation and introspection at an in-depth level requires fast handling of events, as well as direct access to VM state. Furthermore, deep introspection benefits greatly from the ability to gather data from the hardware during the VM\u2019s exit to the hypervisor. All of this requires identical access to the system as the hypervisor itself; improper use of this ability could easily cause system instability. It is for this reason we believe that the hypervisor developers have been hesitant to grant this much control through their APIs. However, our approach leverages other means to collect and monitor the guests in a targeted fashion. Virtual machine introspection (VMI) is a technique used to monitor the runtime state of a system-level virtual machine. The runtime state can be may include processor registers, memory, disk, network, and any other hardware-level events\nA review of research literature and current VMI technologies exposed several limitations and tradeoffs in VMI approaches, including: the use of in-guest agents; kernel to user space transitions (dramatically slowing down processing); VMI tool pre-configuration requirements; hypervisor version lock-in or source code patching; reliance on operating system symbols; limited processor features due to hypervisor (even if the hardware could do more).\nTo address these constraints, a VMI tool was envisioned to provide the cloud forensic capabilities while having as few of these limitations as possible. The Kernel-based Virtual Machine Introspection (KVMi) tool was developed for hypervisors on Intel\u2019s x86-64 architecture. To meet performance, scoping and use-case demands, the follow criteria were applied to KVMi to support live, forensic data collection:\n\u2022\tShall not require in-guest agents.\n\u2022\tShall work with any recent version of modern hypervisors.\n\u2022\tShall introspect upon any guest (VM) running modern versions of Windows, Linux and OS X.\n\u2022\tShall have the ability to find and track operating system artifacts\n\u2022\tShall not require operating system symbol files.\n\u2022\tShall be able to fully handle VM-exits, bypassing execution of the hypervisor if necessary, to facilitate new features the hypervisor may not support.\n\u2022\tShall be compilable/loadable on a running system with standard build tools.\n", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 38273.6, + "languages": [ + "C" + ], + "name": "Sandia Cloud Forensics and Incident Response Platform v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-03-19", + "metadataLastUpdated": "2019-03-22" + }, + "description": "Synoptic is a system for graphical representation of real-time data in the Fermilab Accelerator Control System. It offers a means for domain experts to create, in a short time, coherent displays representing a machine or a process, along with actual readings from the control system indicating its current state. The displays can run either within a Java application, or in a conventional web browser as SVG images updated on the fly. Synoptic also optionally supports setting data back to the control system. The end users do not have to be familiar with programming, because displays are composed in a high-level graphical editor from preexisting building blocks: gauges, alarm indicators, static shapes, and such. Similarly, the runtime environment takes care of all internal \u201cplumbing and wiring\u201d between components and hides the complexity of the actual data acquisition protocols.\n\nThe open-source Java Synoptic Toolkit includes a core of Synoptic, free of dependencies from the proprietary infrastructure. It can be used with any data acquisition system, providing that an appropriate data access interface is developed. The product can be customized in a variety of ways, for instance, by developing specialized components for rendering data.\n", + "homepageURL": "http://synoptic.fnal.gov/opensource.html", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Java Synoptic Toolkit", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://synoptic.fnal.gov/opensource.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-03-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Dynamic, unsupervised quality control methodology for mass spectrometry", + "laborHours": 167.2, + "languages": [], + "name": "stanfill/QC-ART", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stanfill/QC-ART", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-28", + "metadataLastUpdated": "2019-03-28" + }, + "description": "This program calculates performance characteristics for a split flow recompression closed Brayton cycle. The user defines for the cycle; minimum temperature, minimum pressure, maximum temperature, maximum pressure, pinch temperature at the cold ends of the low temperature and high temperature recuperators, component fractional pressure drop, and efficiencies for each of the two turbines and each of the two compressors. All of these parameters except component fractional pressure drop and turbomachinery efficiencies are varies in separate do loops. In this way, minimum and maximum values for each of these parameters can be set. Results from each iteration are saved to a .csv file. Following completion of the program run, the .csv file can be read into a plotting package and the results can be plotted.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 121.6, + "languages": [], + "name": "CATS v. 2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 2" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-04-02", + "metadataLastUpdated": "2019-04-02" + }, + "description": "PTFREAD is an Excel Add-In used to post-process MELCOR plotfile data for plotting and animation of MELCOR results. ", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 21888.0, + "languages": [], + "name": "PTFREAD v. 188r", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 188r" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-03", + "metadataLastUpdated": "2019-04-03" + }, + "description": "Brief Description for Public Release:\nA collection of general code samples demonstrating issues encountered with using OpenMP4.5 (and some CUDA) during efforts to port codes to a GPU platform using IBM XL. These independent examples include both C++ and FORTRAN language usage, along with attempts to use OpenMP and CUDA in an interoperable manner. This suite of code samples is meant to supplement the examples provided by openmp.org at https://github.com/OpenMP/Examples, especially in regards to FORTRAN language support and OpenMP/CUDA interoperability.", + "laborHours": 2158.4, + "languages": [], + "name": "OpenMP 4.5 and CUDA C++ and FORTRAN code samples", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FGPU", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-04-03", + "metadataLastUpdated": "2019-04-03" + }, + "description": "Flexible Energy Scheduling Tool for Integrating Variable generation (FESTIV) is a tool that simulates the realistic representation of steady-state power system operations and scheduling performed by an independent system operator, regional transmission organization, or a vertically integrated regulated utility. 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It does this while having different objectives between the submodels; commitment of resources, dispatch and reserve commitment, and finally control.", + "laborHours": 10488.0, + "languages": [], + "name": "FESTIV (Flexible Energy Scheduling Tool for Integrating Variable generation)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/FESTIV_MODEL", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-08", + "metadataLastUpdated": "2019-04-08" + }, + "description": "ScrubJay allows users to query large collections of heterogeneous numerical dawets. 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ScrubJay makes large-scale analysis tractable, reproducible, and provides insights into HPC facilities.", + "laborHours": 1626.4, + "languages": [], + "name": "ScrubJay", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ScrubJay", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-08", + "metadataLastUpdated": "2019-04-08" + }, + "description": "Cygnus is a C++ code which is used to analyze Coulomb excitation experiments. In these experiments, the structure of nuclei is probed at low energy, so that only the electromagnetic interaction is involved. The excitation can then be solved semi-classically. 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For example, to solve for desired temperature and pressure, the reduced density must be adjusted to give the desired pressure. Iteration is accomplished using the Newton-Raphson method, though the secant method is also used in solving the fourth type of problem. H2OI95 has been used to conduct numerical studies of convergence and the problem of multiple numerical solutions, only some of which correspond to valid results. Obtaining valid results depends mainly on appropriate choice of starting values. The default values in H2OI95 appear to consistently lead to generally desired results. With modification (not addressed here), H2OI95 can be used to support SUPCRT92 (Johnson et al., 1992) and similar codes that compute chemical thermodynamic properties of species and reactions over a wide range of temperature and pressure (273.16-1273K and 0-1000 MPa).\n", + "laborHours": 15.2, + "languages": [], + "name": "H2OI95: A Stand-Alone Fortran Code for Evaluating the IAPWS-95 Equation-of-State Model for Water", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/H2OI95", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-08", + "metadataLastUpdated": "2019-04-08" + }, + "description": "libROM is a collection of C++ classes that compute reduced order models and hyperreduced order models for systems of ordinary differential equations. libROM includes parallel, adaptive methods for proper orthogonal decomposition, and parallel, non-adaptive methods for hyperreduction using the discrete empirical interpolation method.", + "laborHours": 16887.2, + "languages": [], + "name": "libROM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/libROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-08", + "metadataLastUpdated": "2019-04-08" + }, + "description": "CUDA is the programming model used to program NVIDIA GPUs, which are widely used in DOE supercomputers. FPChecker allows programmers to detect and fix hidden exceptions in the floating-point computations that CUDA executes. When a floating-point exception occurs (e.g., division by zero), GPUs cannot catch these errors. FPChecker intercepts each floating-point operations (addition, subtraction, multiplication and division) and reports to users where exceptions occur (file and line of code).", + "laborHours": 2280.0, + "languages": [], + "name": "FPChecker", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FPChecker", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-10", + "metadataLastUpdated": "2019-04-10" + }, + "description": "Metall provides simplified memory allocation interfaces for out-of-core applications that use block-addressable persistent memory devices to extend the capacity of main memory and to persistently store data on such devices. 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Metall has a similar APIs to\nBoost.Interprocess (BIP).", + "laborHours": 5943.2, + "languages": [], + "name": "Meta Allocator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/metall", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-10", + "metadataLastUpdated": "2019-04-10" + }, + "description": "The OpenRES is an open-source library of intermittent energy resources developed in the JModelica.org platform, and provides capability for performing long-term power grid dynamic simulation with renewable ancillary services (e.g., load ramp, frequency and voltage regulation).", + "laborHours": 45.6, + "languages": [], + "name": "OpenRES", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/OpenRES", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-10", + "metadataLastUpdated": "2019-04-11" + }, + "description": "MPI Usage is a python program that gathers statistics of MPI usage in MPI programs. It reports the MPI routines used in the program among other statistics, such as, the number of lines and languages used in the program (e.g., C, C++, Fortran, CUDA and OpenMP).", + "laborHours": 6900.8, + "languages": [], + "name": "MPI Usage", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MPI-Usage", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-04-11", + "metadataLastUpdated": "2021-08-30" + }, + "description": "The Compadre Toolkit solves a minimization problem, that once solved allows a user to reconstruct a function from sample data collected from a cloud of data sites. 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The minimization problem the toolkit solves is to find the optimal finite polynomial in a user specified finite dimensional space with regards to minimizing an objective function which measures a linear sampling functional applied to the polynomial, compared to the same sampling functional applied to the source function, weighted by a positive kernel that has compact support.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python" + ], + "name": "Compadre Toolkit ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/compadre", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-04-11", + "metadataLastUpdated": "2019-04-12" + }, + "description": "COMPOSE is scientific software to help to solve tracer transport equations, which are partial differential equations that model how chemical species move when carried by a fluid. It will be used in a future version of the open-source DOE Energy Exascale Earth System Model (E3SM) to help model the movement of chemical species in Earth\u2019s atmosphere as part of simulating the climate. In particular, COMPOSE help to implement semi-Lagrangian tracer transport and, more generally, property preserving remap of tracer fields. Logical components include Communication-Efficient Constrained Density Reconstructors (COMPOSE-CEDR) and Spherical Polygon Intersection and Quadrature with Kokkos (COMPOSE-SIQK).", + "laborHours": 3374.4, + "languages": [ + "C++" + ], + "name": "COMPOSE Version. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/COMPOSE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-04-11", + "metadataLastUpdated": "2019-04-12" + }, + "description": "Sella is a tool for locating and optimizing first order saddle points of arbitrary functions, with an emphasis on the potential energy surfaces of molecules. Sella uses ASE to interface with a variety of electronic structure theory packages. Sella can also be used to minimize functions, or find higher-order saddle points.", + "laborHours": 1869.6, + "languages": [], + "name": "Sella Beta Version 0.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zadorlab/sella", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "Beta Version 0.0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "HATS\u00a0allows\u00a0partner\u00a0countries\u00a0to\u00a0collect\u00a0data\u00a0on\u00a0all\u00a0of\u00a0their\u00a0handheld\u00a0radiation\u00a0detectors.\u00a0The\u00a0DataViewer\u00a0then\u00a0allows\u00a0them to\u00a0get\u00a0summaries\u00a0of\u00a0how\u00a0all\u00a0the\u00a0devices\u00a0are\u00a0performing\u00a0over\u00a0time,\u00a0pick\u00a0outliers\u00a0in\u00a0performance\u00a0so\u00a0they\u00a0can\u00a0be\u00a0fixed,\u00a0trend how\u00a0individual\u00a0devices\u00a0perform\u00a0over\u00a0time,\u00a0and\u00a0provide\u00a0reports\u00a0on\u00a0the\u00a0state\u00a0of\u00a0health\u00a0of\u00a0devices\u00a0they\u00a0service. 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Biocellion integrates simulations of individual cell behaviors, short-distance intercellular biomechanics, and extracellular molecular transport to understand and predict multicellular biological system behaviors in their entirety. This software release (Biocellion 3.1) updates previous Biocellion 2.0. The main updates include support for ellipsoid based cell biomechanics modeling and layer based initialization of multi-layered multicellular biological systems in addition to performance improvements and various API updates. Through Biocellion SPC (https://biocellion.com), these updates have been used to investigate skin biomechanics under different conditions (e.g. humidity) for Procter and Gamble. This is the only discrete agent based solution to allow seamless integration of individual cell level knowledge and measurements to a whole skin model to the best of our knowledge.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "Biocellion 3.1", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Wind and solar generation is increasing rapidly in the USA and around the world and has the potential to replace carbon emitting generation. 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This tool calculates reserves requirements of various types, such as day\u2010ahead, load following and regulation, as well as estimates the capacity of the generation fleet to provide the required reserves. The estimations are based on utilities\u2019 operational practices (such as forecasting, timeframe of reserve deployment), and it incorporates detailed synchronized variable and uncertain data from renewable generation and load. This tool uses a methodology that has been previously tested and applied to several systems: California Independent System Operator Corp., Columbia Grid, Northwest Power Pool, the Western Interconnection of the United States, and internationally in Honduras, Guatemala, El Salvador, Nicaragua, Costa Rica, and Panama.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "GRAF-Plan", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Network Collapse is a STEM education VR game for grade 6-12 students to interactively learn about how information is transmitted and protected on networks. Players assume the role of a router and must transfer incoming data packets to the correct outgoing pathway without losing too many. Eventually the player must also recognize a cyber-attack and turn on the best tool to protect their network. Six levels introduce core basic ideas with increasing complexity in game play to maintain engagement while learning new ideas. The game is designed to run on the standalone VR headset, Oculus Go.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "Network Collapse", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is collection of methods to control weld power and temperature with unprecedented accuracy, precision and process robustness. These control techniques are implemented on the spindle axis only and run independently from weld path and forge axis motion.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "Robust Temperature Control for Friction Stir Welding", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-04-29", + "metadataLastUpdated": "2019-04-30" + }, + "description": "Mass spectrometry (MS) is an analytical technique that enables all chemical species within a complex mixture to be resolved and identified based on their mass:charge ratio. MS is an increasingly important tool in life science research and development because it can resolve or separate small molecules, peptides, lipids, proteins, biopolymers and fragments of all of these structures. Unfortunately, the use of MS has been limited for lack of software tools to visualize, manipulate, store and transfer MS data. Ben Bowen, Oliver Ruebel and colleagues made a huge advance on the resolution of these limitations with the invention of \"OpenMSI\" (#2013-004), a computational method that makes the handling of these very large files (up to 50 Tb) much easier, especially for scientists with limited background in bioinformatics or sophisticated software applications of the type needed to handle such data files. \n\nWith the OpenMSI Arrayed Analysis Tool (OMAAT, #2016-188) invention, the authors take MS data analysis one step further by providing tolls for automatic sample position optimization and ion selection. Even though sample deposition technologies have improved greatly, there is always the chance of encountering outliers in a predefined roster, especially in very large sample sets. Manual curation of the data would be extremely time consuming, so the inventors have included an algorithm that automatically finds the outliers. OMAAT is written in Python with accompanying Jupyter (formerly iPython) notebook and is fully integrated with OpenMSI.", + "laborHours": 623.2, + "languages": [], + "name": "OpenMSI Arrayed Analysis Tools (OMAAT) v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/biorack/omaat/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biorack/omaat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Multidimensional Stoichiometric Compound Classification\nThis R code provides a quick access to the Multidimensional Stoichiometric Compound Classification (MSCC) constraints as published in Rivas-Ubach et al., 2018 Analytical Chemistry (DOI: 10.1021/acs.analchem.8b00529).", + "laborHours": 91.2, + "languages": [], + "name": "PNNL-Comp-Mass-Spec/MSCC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MSCC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The OMICS group at PNNL has developed a wide range of software utilities over the last 15+ years. These tools are used to manage data files, transform data, visualize data, and automate data processing. The software is distributed on GitHub as open source, typically under the Apache 2.0 license agreement. See https://github.com/PNNL-Comp-Mass-Spec Lipid analysis tool developed by PNNL", + "laborHours": 76015.2, + "languages": [], + "name": "PNNL-Comp-Mass-Spec/LIQUID", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LIQUID", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Abstract RunTime System (ARTS) aims to provide different levels of abstraction that trade-off performance and programmability and helps to connect upper layers of the software stack with the different computational substrates.", + "laborHours": 10108.0, + "languages": [], + "name": "pnnl/ARTS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ARTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2019-10-04" + }, + "description": "The Building Informatics Environment is a modeling environment based on the Modelica language. The environment allows users to create a computer model of a building and its energy systems with various time scales and physical resolutions. The environment can be used for rapid development of e.g. demand controls algorithms new HVAC system solutions and new operational strategies. Models for building energy and control systems are made available in the environment. The models can be used as provided or they can be changed or linked with each other in order to model the effects that a particular user is interested in.", + "laborHours": 100122.4, + "languages": [], + "name": "Modelica Buildings Library", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-srg/modelica-buildings", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2019-10-04" + }, + "description": "BuildingsPy is a Python package that can be used to run Modelica simulations and to process Modelica output files. It can also be used to run unit tests as part of the development of LBNL's Modelica Buildings library. The package provides functions to extract data series from the output file for further use in the python packages matplotlib for plotting and SciPy for scientific computing.", + "laborHours": 3936.8, + "languages": [], + "name": "BuildingsPy", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-srg/BuildingsPy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2021-05-11" + }, + "description": "The Software consists of a spreadsheet written in Microsoft Excel which provides an hourly simulation of a solar hot water heating system (including solar geometry, solar collector efficiency as a function of temperature, energy balance on storage tank and lifecycle cost analysis).", + "homepageURL": "https://www.labpartnering.org/lab-technologies/abbc8ccf-3984-416e-b276-4c9d8d192a9f", + "laborHours": 0.0, + "languages": [ + "excel" + ], + "name": "Solar Hot Water Hourly Simulation", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.labpartnering.org/lab-technologies/abbc8ccf-3984-416e-b276-4c9d8d192a9f", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.labpartnering.org/lab-technologies/abbc8ccf-3984-416e-b276-4c9d8d192a9f", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-05-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The hydrological emulator (HE) was built to mimic complex global hydrological models (GHMs) at a range of spatial scales. The HE was written in MATLAB and utilizes a genetic algorithm to calibrate the a, b, c, d, m parameters from the ABCD runoff algorithm to observed runoff from GHMs when forced by the same climate data. The HE employs two methods to choose from when processing basin data: lumped (by basin) and distributed (gridded). Both methods can be evaluated using the built-in Kling-Gupta efficiency as a measure of model performance when compared to the outputs from the more complex GHM. Testing shows that the HE is 7 orders of magnitude faster then the widely used Variable Infiltration Capacity (VIC) GHM.", + "laborHours": 2067.2, + "languages": [], + "name": "JGCRI/hydro-emulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/hydro-emulator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kalb@bnl.gov" + }, + "date": { + "created": "2019-05-02", + "metadataLastUpdated": "2019-05-02" + }, + "description": "BNL NowCasting software is used in conjunction with multiple ground-based, upward looking, high definition imagers to predict available solar resources in the zero - 30 minutes time frame. It takes HD images of the sky as input and conducts image pre-processing to correct image geometry, correct deformation caused by fish-eye lenses and remove extraneous parts of the image. It calculates the location of the sun and removes it to reduce distortion. A cloud detection/tracking algorithm was developed using both spectral and spatial information for discriminating clouds and clear sky based on their shape, size, and color. The software repeats the process with updated images generated every 30 seconds (or less) and then tracks the clouds as they move through the region of interest. Cloud motion determination is based on finding the maximal normalized cross-correlation between sequential images. The resolution of multiple imager views of clouds in the sky allows the system to estimate cloud height and categorize them into low or high cloud regimes that move at different rates. Additional input data on solar irradiance from pyranometers is ingested. The algorithm then determines the transmissivity of light and uses machine-learning techniques to predict the amount of available global horizontal irradiance (GHI) that will be available on the ground. Images from individual sets of cameras are stitched together to form regional forecasts that cover both generating facilities and distributed solar resources. The size of the nowcasting network is dependent on the number and location of imagers that are installed but has been demonstrated in an area up to 50 sq km", + "laborHours": 3693.6, + "languages": [ + "Python" + ], + "name": "BNL-NowCasting/SolarForecasting", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BNL-NowCasting/SolarForecasting", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-02", + "metadataLastUpdated": "2019-05-03" + }, + "description": "Supplementary Folder 1\" is documentation with embedded code. It is a supplement to a manuscript communicating results for a collaborative research project on the evolutionary mechanisms of fruit fly mating.", + "laborHours": 6049.6, + "languages": [], + "name": "Evolution of mechanisms that control mating in Drosophila males - \"Supplemental Folder 1\"", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aavilaherrera/flymating", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-02", + "metadataLastUpdated": "2019-05-02" + }, + "description": "Extends the JupyterHub LocalProcessSpawner to instead launch notebooks on a remote host (e.g. a login node).", + "laborHours": 243.2, + "languages": [], + "name": "SSHSpawner", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SSHSpawner", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "sprice@lanl.gov" + }, + "date": { + "created": "2019-05-02", + "metadataLastUpdated": "2019-05-06" + }, + "description": "The Model for Prediction Across Scales (MPAS) is a collaborative project for developing atmosphere, ocean, and other earth-system simulation components for use in climate, regional climate, and weather studies. The primary development partners are the climate modeling group at Los Alamos National Laboratory (COSIM) and the National Center for Atmospheric Research. Both primary partners are responsible for the MPAS framework, operators, and tools common to the applications; LANL has primary responsibility for the ocean, sea ice, and land ice models, and NCAR has primary responsibility for the atmospheric model.", + "laborHours": 244279.2, + "languages": [ + "C++", + "Fortran" + ], + "name": "MPAS-Dev/MPAS-Model", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MPAS-Dev/MPAS-Model", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "6.2" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-03", + "metadataLastUpdated": "2019-05-06" + }, + "description": "Collection of tools and code for evaluation testing of HPC orchestration solutions by HPCCEA summer students. These scripts and configuration files were written by HPCCEA summer students as part of their summer internship where they explore alternative solutions to our current HPC cluster management software. These scripts/configuration files range from using configuration management tools (Puppet, Chef, Ansible, Fabric, etc.) to scripting languages (Phython, BASH, Perl, etc.). Each year, new students will be added to the project and expand on previous years work.", + "laborHours": 1474.4, + "languages": [], + "name": "High Performance Computing Cluster Engineering Academy", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/HPCCEA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-03", + "metadataLastUpdated": "2019-05-06" + }, + "description": "We provide a self-contained package to load, process, and test the ICF JAG dataset. In particular, we include a Neural Network designed to act as a surrogate for the JAG 1D Simulator. The neural network is implemented in Tensorflow.\nWe include a Jupyter notebook which allows a user to load the dataset, load the neural network and train it such that given just the 5 input parameters, it predicts the scalars and images accurately. This can be done directly in the notebook, without any additional modifications. During training, intermediate predictions are also saved to disk (as specified by the user). We hope this serves as a starting point to build, test and play with the ICF-JAG simulation dataset.", + "laborHours": 532.0, + "languages": [], + "name": "Cycle Consistent Surrogate for Inertial Confinement Fusion", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rushilanirudh/icf-jag-cycleGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-03", + "metadataLastUpdated": "2019-05-06" + }, + "description": "While deep learning technologies for computer vision have developed rapidly since 2012, modeling of remote sensing systems has remained focused around human vision. In particular, remote sensing systems are usually constructed to optimize sensing cost-quality trade-offs with respect to human image interpretability. While some recent studies have explored remote sensing system design as a function of simple computer vision algorithm performance, there has been little work relating this design to the state-of-the-art in computer vision: deep learning with convolutional neural networks. We develop experimental systems to conduct this analysis, showing results with modern deep learning algorithms and recent overhead image data. Our results are compared to standard image quality measurements based on human visual perception, and we conclude not only that machine and human interpretability differ significantly, but that computer vision performance is largely self-consistent across a range of disparate conditions.\nThis repository contains all the code required to replicate the results of our research paper, and the corresponding docker environment in which that code can be executed. All code is written in Python3 and utilizes the PyTorch library (v1.0) for neural network model training and evaluation. Jupyter notebooks are used to visualize images transformed with our code, in addition to plotting experimental results. We also include the specific parameter files used to execute our experiments, with the intent that these experiments can be replicated.", + "laborHours": 2340.8, + "languages": [], + "name": "Remote Sensor Design for Visual Recognition with Convolutional Neural Networks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sepsense", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-06", + "metadataLastUpdated": "2019-05-13" + }, + "description": "The Design, Analysis, and Operations Toolkit (DAO-Tk) is a software package that allows users to explore design optimization, operations decision, and performance characterization of concentrating solar power tower plants. Users interface with the tool through a scripting language, and results are reported in time series tables, plots, runtime logs, and design outputs. Users choose from a list of variables such as tower height, solar multiple, design-point irradiance, thermal storage size, etc., and specify information about the system using a list of parameters. The software can then optimize the specified variables to reduce the cost of energy produced by the system while meeting certain production requirements, accounting for uncertain weather and electricity price forecasts, and correcting for equipment failures or repair time. The DAO-Tk software is the first comprehensive design tool of it's kind to incorporate all of these aspects while being deployed as open source. ", + "laborHours": 106536.8, + "languages": [], + "name": "Design, Analysis, and Operations Toolkit (DAO-Tk)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dao-tk", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-06", + "metadataLastUpdated": "2019-10-04" + }, + "description": "FERIS is an agent-based model that simulates the activity of a fleet of electric taxis in a metropolitan area. Agent activities include serving trips, rebalancing to anticipate future demand, and relocating to charge. The modeling framework allows researchers to study the impact of different routing algorithms, battery range, and charging infrastructure on fleet performance, energy consumption, environmental impact, and cost of service.", + "laborHours": 912.0, + "languages": [], + "name": "Routing and Infrastructure simulation for Shared Electric vehicles (RISE)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gb4uer/RISE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-06", + "metadataLastUpdated": "2019-10-04" + }, + "description": "This package is a set of tools in the Python language for preprocessing GPS trajectory data gathered from consumer devices, to detect and flag potentially erroneous data.", + "laborHours": 1048.8, + "languages": [], + "name": "TraVerSE: Trajectory Veracity for Simple Errors", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/bgerke/traverse", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-07", + "metadataLastUpdated": "2019-06-26" + }, + "description": "The Modelica IBPSA library is a free open-source library with basic models that codify best practices for the implementation of models for building and community energy and control systems. \n\nThe development of the IBPSA library is organized through the IBPSA Project 1 (https://ibpsa.github.io/project1) of the International Building Performance Simulation Association (IBPSA). \n\nThis library is typically not used directly by end-users. Rather, it is integrated by developers of other Modelica libraries for building and community energy systems, who then distribute it to end-users as part of their respective library.", + "laborHours": 36328.0, + "languages": [], + "name": "Modelica IBPSA Library v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ibpsa/modelica-ibpsa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-05-10", + "metadataLastUpdated": "2019-05-13" + }, + "description": "This is a follow on to a subset of SCR#2291.0, and represents a set of FPGA and Linux driver software that serves to enhance the Epiq Solutions Sidekiq line of products with very standard and well defined digital signal processing capabilities that are found on other such software defined radio hardware. This includes timed command support, sub-band tuners, and other generic DSP capabilities.\nSAND2019-3719 M", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "Sidekiq DSP v. 0.4", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 0.4" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-13", + "metadataLastUpdated": "2019-05-13" + }, + "description": "SLAPI is a command line tool that communicates with Spectra Logic tape libraries using their XML command reference. 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As part of this, the tool reports the estimated probability of a critically-oriented fault becoming activated as a result of the injection. The tool also allows a storage site operator to evaluate the likely value of different types of characterization on the knowledge of the geomechanical conditions and probability of induced seismicity. ", + "homepageURL": "https://edx.netl.doe.gov/dataset/state-of-stress-analysis-tool", + "laborHours": 334.4, + "languages": [], + "name": "State of Stress Analysis Tool (SOSAT)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://edx.netl.doe.gov/dataset/state-of-stress-analysis-tool", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-15" + }, + "description": "A unit library was needed to be able to represent units of a wide range of disciplines and be able to separate them from the numerical values for use in calculations. The main driver is converting units to a standardized unit set when dealing with user input and output. And be able to use the unit as a singular type that could contain any unit, and not introduce a huge number of types to represent all possible units. Because sometimes the unit type needs to be used inside virtual function calls which must strictly define a type. The libary also has its origin in power systems so support for per-unit operations was also lacking in the alternatives.", + "laborHours": 42985.6, + "languages": [], + "name": "units", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/units", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-15" + }, + "description": "Machine learning for predicting physics variables in Sedov blast simulation.", + "laborHours": 668.8, + "languages": [], + "name": "Machine Learning for Sedov Blast", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Sedov-ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-15" + }, + "description": "The Application Reporting and Termination Utility for Windows (terminate.exe) is a simple diagnostics and recovery tool designed to help LANDesk system administrators manage hung client applications on Windows systems. Terminate can either report on (tag) or stop (kill) a specified process on computers on which it is run. If KILL is specified, all processes that match the specified name and have a start time older than the specified minutes will be force stopped. If TAG is specified, all processes that match the name and have a start time older than the specified minutes will be reported to LANDesk inventory via the miniscan LANDesk client component.", + "laborHours": 364.8, + "languages": [], + "name": "Application Reporting and Termination Utility for Windows", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/david-frye/Terminate", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2025-03-26" + }, + "description": "These models are based on the 2015 Design Report of Dutta et al. found here: https://www.nrel.gov/docs/fy15osti/62455.pdf The models are distributed under the GNU General Public License. You will need a separate license to use the Aspen Plus and Microsoft Excel software packages in order to run the models. These models relate to an Aspen Plus process model for in situ and ex situ upgrading of fast pyrolysis vapors for the conversion of biomass to hydrocarbon fuels. It is based on conceptual designs that allow projections of future commercial implementations of the technologies based on a combination of research and existing commercial technologies. Results from the model are documented in a detailed design report NREL/TP-5100-62455 (available at http://www.nrel.gov/docs/fy15osti/62455.pdf). The model consists of the following key operations: (a) fast pyrolysis and vapor upgrading, (b) vapor condensation and recovery of an organic liquid and an aqueous phase, (c) hydroprocessing of the liquid organic phase to produce a fuel blendstock, (d) hydrogen production from off gases, (e) electricity production from excess heat, (f) other utilities such as cooling water, (g) wastewater utilization and treatment.", + "homepageURL": "https://www.nrel.gov/extranet/biorefinery/aspen-models", + "laborHours": 0.0, + "languages": [], + "name": "Ex Situ and In Situ Catalytic Fast Pyrolysis Models (ASPEN PLUS MODELS) [SWR-16-12]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/extranet/biorefinery/aspen-models", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-15" + }, + "description": "WUFI - Oak Ridge National Laboratory (ORNL)/Fraunhofer IBP is a menu-driven PC program which allows realistic calculation of the transient coupled one-dimensional heat and moisture transport in multi-layer building components exposed to natural weather. It is based on the newest findings regarding vapor diffusion and liquid transport in building materials and has been validated by detailed comparison with measurements obtained in the laboratory and on outdoor testing fields. Together with Oak Ridge National Laboratory (ORNL) Fraunhofer IBP has developed a special version of WUFI \u00ae for North America. WUFI\u00ae ORNL is a functionally limited free version of WUFI\u00ae Pro for non-commercial purposes. It contains climate data for 62 cities in the USA and Canada which are all available in the free version.", + "homepageURL": "https://web.ornl.gov/sci/buildings/tools/wufi", + "laborHours": 0.0, + "languages": [], + "name": "WUFI (W\u00e4rme and Feuchte Instation\u00e4r)-Oak Ridge National Laboratory (ORNL)/Fraunhofer IBP", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://web.ornl.gov/sci/buildings/tools/wufi", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://web.ornl.gov/sci/buildings/tools/wufi", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-16" + }, + "description": "The purpose of the ROSE Complier Framework Is to automate source code porting, source and binary code analysis, and source code translations such as platform optimization, binary code analysis, Identification of source code and binary code vulnerablllttes.", + "laborHours": 5605912.0, + "languages": [], + "name": "ROSE Compiler Framework ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rose-compiler/rose", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-16" + }, + "description": "Archer is a data race detector for OpenMP programs.\nArcher combines static and dynamic techniques to identify data races in large OpenMP applications, leading to low runtime and memory overheads, while still offering high accuracy and precision. It builds on open-source tools infrastructure such as LLVM, ThreadSanitizer, and OMPT to provide portability.", + "laborHours": 2903.2, + "languages": [], + "name": "Archer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PRUNERS/archer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-16", + "metadataLastUpdated": "2024-07-01" + }, + "description": "Daft is a Haskell library that implements the key constructs of relational algebra via static structural typing. Its DataCube typeclass supports selection, projection, aggregation, disaggregation, natural joins, semijoins, and antijoins. Instances of DataCube include both map- and function-based representations. An additional abstract data type provides Vinyl-style, keyed relational tables for which an embedded domain-specific language compactly represents relational operations. Utility types and functions support serialization to tab-separated-value data files, JSON arrays, MongoDB documents, and PostgreSQL tables, including automatic detection and verification of the schema for the input data.", + "laborHours": 1094.4, + "languages": [ + "Haskell" + ], + "name": "daft [SWR-17-53]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/daft", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-05-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Per sequence functional classification and Functional annotation in addition to linking those functions to taxonomic groups presents a challenge due to many established tools performing one task and not the other creating disparate downstream data. PerSeq aims to address these challenges by performing local alignments against a reference database annotated for both aspects, function and taxonomy, to annotate sequences individually. Downstream results are merged into count tables facilitating complex analyses based on observed function or functional potential in addition to being able to separate out function by taxonomic level to determine metabolic contributions by present organisms.", + "laborHours": 775.2, + "languages": [], + "name": "PNNL-CompBio/perseq", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/perseq", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dstotler@pppl.gov" + }, + "date": { + "created": "2019-05-22", + "metadataLastUpdated": "2019-05-22" + }, + "description": "DEGAS 2 [1], like its predecessor, DEGAS [2], uses the Monte Carlo approach to integrating the Boltzmann equation, allowing the treatment of complex geometries, atomic physics, and wall interactions. DEGAS 2 is written in a \"macro-enhanced'' version of FORTRAN via the FWEB library, providing an object oriented capability and simplifying tedious tasks, such as dynamic memory allocation and the reading and written of self-describing binary files. As a result, the code is extremely flexible and can be readily adapted to problems seemingly far removed from tokamak divertor physics, e.g., its use in simulating the diffusive evaporation of lithium in NSTX [3] and LTX [4]. DEGAS 2 has been extensively verified, as is documented in its User's Manual [5]. Experimental validation has been largely centered on the Gas Puff Imaging (GPI) technique for visualizing plasma turbulence in the tokamak edge. The validation against deuterium gas puff data from NSTX is described in the paper by B. Cao et al. [6] Analogous work with both deuterium and helium has been carried out on Alcator C-Mod. A related application of DEGAS 2 is in the interpretation of data from the Edge Neutral Density Diagnostic on NSTX [7] and NSTX-U. DEGAS 2 has been applied to many other devices, including JT-60U [8], ADITYA [9], and FRC experiments at Tri-Alpha Energy [10]. Neutral transport codes are frequently coupled to plasma simulation codes to allow a self-consistent plasma-neutral solution to be computed. Initially, DEGAS 2 was coupled to UEDGE [11]. More recently, DEGAS 2 has been coupled to the drift-kinetic XGC0 [12], and has been used in the development and testing of the simplified built-in neutral transport module in XGC1 [13]. A related project is a DEGAS 2-based synthetic GPI diagnostic for XGC1 [14].\n\n[1] D. P. Stotler & C. F. F. Karney, Contrib. Plasma Phys. 34, 392 (1994)\n[2] D. Heifetz, D. Post et al., J. Comp. Phys. 46, 309 (1982)\n[3] D. P. Stotler et al., J. Nucl. Mater. 415, S1058 (2011)\n[4] J. C. Schmitt et al., J. Nucl. Mater. 438, S1096 (2013)\n[5] DEGAS 2 Home Page\n[6] B. Cao et al., Fusion Sci. Tech. 64, 29 (2013)\n[7] D. P. Stotler et al., Phys. Plasmas 22, 082506 (2015)\n[8] H. Takenaga et al., Nucl. Fusion 41, 1777 (2001)\n[9] R. Dey et al., Nucl. Fusion 57, 086003 (2017)\n[10] E. M. Granstedt et al., Presented at 60th Annual Meeting of the APS Division of Plasma Physics\n[11] D. P. Stotler et al., Contrib. Plasma Phys. 40, 221 (2000)[\n[12] D. P. Stotler et al., Comput. Sci. Disc. 6, 015006 (2013)\n[13] D. P. Stotler et al., Nucl. Fusion 57, 086028 (2017)\n[14] D. P. Stotler et al., Nucl. Mater. 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The others can be found at the following DOIs: 10.11578/dc.20190522.1, 10.11578/dc.20190522.2, 10.11578/dc.20190522.4 and 10.11578/dc.20190522.5.", + "laborHours": 714.4, + "languages": [], + "name": "Berkeley Lab WINDOW Calc Engine (CalcEngine) v2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/Windows-CalcStandards", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-23", + "metadataLastUpdated": "2019-05-23" + }, + "description": "ldlms_plugins_llnl contains LLNL-developed plugins for LDMS (Lightweight Distributed Metric Service), which is software for low overhead monitoring, transport and storage of cluster metric data. 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The DCA++ code provides a state of the art implementation of the dynamical cluster approximation (DCA) and its DCA+ extension. 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It is designed to use existing energy simulation tools such as doe2.2 and SAMS to produce detailed results which are then processed at a higher level. ", + "laborHours": 425.6, + "languages": [], + "name": "Institutional Transformation v. 2.6", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IX2.6", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 2.6" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-06-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Structural Temporal Modeling\nGenerating a synthetic graph that is similar to a given real- world graph is a critical requirement for privacy preservation and benchmarking purposes. 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It includes server-side components in the form of web services that provide analytical functions such as data clustering and temporal analysis. The SRS client is accessed via a web browser and uses asynchronous javascript and XML (AJAX) to interact with and visualize the results of these web services. Users of SRS can query data sources that are connected to the SRS backend, and query results are presented in the form of coordinated visual displays in a web browser that depict temporal, topical, and spatial relationships in the results. SRS also includes an early stage graphical reasoning diagram interface that helps analysts express and test hypotheses. \nThis software was developed with funding from the Science and Technology Directorate of the U.S. Department of Homeland Security.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 35112.0, + "languages": [], + "name": "Scalable Reasoning System (SRS)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "2.x" + }, + { + "contact": { + "email": "kentpr@ornl.gov" + }, + "date": { + "created": "2019-06-13", + "metadataLastUpdated": "2020-09-09" + }, + "description": "QMCPACK is an open source C++ code that runs across multiple high performance computing architectures including accelerators. 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This program was designed for geothermal applications but is also useful as a tool to quickly speciate a large number of water analyses.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "GeoT V1.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2019-06-18", + "metadataLastUpdated": "2019-06-19" + }, + "description": "LATTE is a code used for computing the energy of, and forces acting on atoms in molecular materials using an implementation of the self-consistent charge tranfer tight-binding approximation. 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It does not make any policy decisions except for the block duration auto scaling. 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", + "laborHours": 76.0, + "languages": [], + "name": "ESnet docker", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/docker", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-07-05" + }, + "description": "No elephant flows - flow shuting for Arista switches using EOS API.\n", + "laborHours": 167.2, + "languages": [], + "name": "dumbno", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ncsa/dumbno/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/dumbno", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2020-09-08" + }, + "description": "ENOS is a prototype next-generation ESnet architecture for handling data-intensive science workflows. 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These logical central control plane capabilities can be evolved to become the operating system through which the network policies are implemented across the entire network and applications can program network behavior.", + "laborHours": 10138.4, + "languages": [], + "name": "ESnet Network Operating System (ENOS)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/enos/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/enos", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "Testing esmond documentation.", + "laborHours": 101718.4, + "languages": [], + "name": "esmond-test", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/esmond-test/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/esmond-test", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "Base templates for ESnet's GitHub pages. These pages are created using the Sphinx documentation package using the sphinx-bootstrap-theme with some pages. This repo is meant to be included into a project using git subtree and provides the overrides and customizations to the base theme.", + "laborHours": 152.0, + "languages": [], + "name": "esnet-gh-pages-base", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/esnet-gh-pages-base", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "Common React components for ESnet tools.", + "laborHours": 1368.0, + "languages": [], + "name": "ESnet React Base", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/esnet-react-base/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/esnet-react-base", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "Simple time series database for ESxSNMP.", + "laborHours": 1048.8, + "languages": [], + "name": "esxsnmp-tsdb", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/esxsnmp-tsdb/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/esxsnmp-tsdb", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "iperf is a tool for active measurements of the maximum achievable bandwidth on IP networks. 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In particular it shows an example of using: react-timeseries-charts, react-network-diagrams, and pond. 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As developed by the Department of Energy\u2019s high-performance science network ESnet, OSCARS was designed by network engineers who specialize in supporting the U.S. national laboratory system and its data-intensive collaborations.", + "laborHours": 127877.6, + "languages": [], + "name": "OSCARS", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/oscars", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "This is the repository for oscars-frontend developed by Energy Sciences Network (ESnet). 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The view will create Django Users and Groups as necessary.", + "laborHours": 288.8, + "languages": [], + "name": "shibboleth_session_auth", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/shibboleth_session_auth/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/shibboleth_session_auth", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "ESnet has designed a REST/JSON based lookup service called the \"simple Lookup Service\", or sLS. 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We also collaborate with Lawrence Livermore National Laboratory for modeling HPC interconnect systems", + "laborHours": 49278.4, + "languages": [], + "name": "CODES( CO-DESIGN OF EXASCALE STORAGE AND NETWORK ARCHITECTURES", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://xgitlab.cels.anl.gov/codes/codes.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-06-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A C++ Library for Influence Maximization\nRipples is a software framework to study the Influence Maximization problem. 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The examples directory contains a simple example of using React ART; you can also test out the art branch of the react-page project.", + "laborHours": 501.6, + "languages": [], + "name": "React ART", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/react-art", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "Seccubus automates regular vulnerability scans with various tools and aids security people in the fast analysis of its output, both on the first scan and on repeated scans. On repeated scan delta reporting ensures that findings only need to be judged when they first appear in the scan results or when their output changes.", + "laborHours": 128333.6, + "languages": [], + "name": "Seccubus V2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/Seccubus_v2", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "Graphite consists of two major components: the frontend Django webapp that runs under Apache/mod_wsgi and the the backend carbon-cache.py daemon.", + "laborHours": 42833.6, + "languages": [], + "name": "graphite-web", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/graphite-web", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-08", + "metadataLastUpdated": "2023-06-13" + }, + "description": "The BEopt\u2122 (Building Energy Optimization Tool) software provides capabilities to evaluate residential building designs and identify cost-optimal efficiency packages at various levels of whole-house energy savings along the path to zero net energy. BEopt can be used to analyze both new construction and existing home retrofits, as well as single-family detached and multi-family buildings, through evaluation of single building designs, parametric sweeps, and cost-based optimizations. BEopt provides detailed simulation-based analysis based on specific house characteristics, such as size, architecture, occupancy, vintage, location, and utility rates. Discrete envelope and equipment options, reflecting realistic construction materials and practices, are evaluated. BEopt uses EnergyPlus, the Department of Energy's flagship simulation engine. Simulation assumptions are based on the Building America Housing Simulation Protocols. The sequential search optimization technique used by BEopt: Finds minimum-cost building designs at different target energy-savings levels, Identifies multiple near-optimal designs along the path, allowing for equivalent solutions based on builder or contractor preference. BEopt has been developed by the National Renewable Energy Laboratory in support of the U. S. Department of Energy Building America program goal to develop market-ready energy solutions for new and existing homes.", + "homepageURL": "https://beopt.nrel.gov/home", + "laborHours": 657962.4, + "languages": [], + "name": "BEopt\u2122 (Building Energy Optimization Tool) [SWR-05-41]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://beopt.nrel.gov/BEopt_setup_2.8.0.0", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://beopt.nrel.gov/home", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "2.8.0.0" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-07-08", + "metadataLastUpdated": "2019-07-09" + }, + "description": "Service for publishing user code tarballs in cvmfs repositories", + "laborHours": 288.8, + "languages": [ + "Python" + ], + "name": "cvmfs-contrib/cvmfs-user-pub", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cvmfs-contrib/cvmfs-user-pub", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-10", + "metadataLastUpdated": "2019-07-10" + }, + "description": "Power system modeler-friendly tool for downloading wind and solar power and forecast data.", + "laborHours": 790.4, + "languages": [ + "Python" + ], + "name": "Renewable Resource and Power Data tool (R2PD)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Smart-DS/R2PD", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-10", + "metadataLastUpdated": "2023-05-26" + }, + "description": "The AirflowNetwork software provides the ability to simulate air movement and the resulting transport of contaminants and other materials within a building. The performance of air distribution systems, including supply and return leaks, and multizone airflows driven by outdoor wind and forced air during HVAC system operation are simulated using a nodal network representation of the building. The pressure network model implemented here is based on George Walton's AIRNET and was modified for inclusion in the EnergyPlus building energy modeling software. The algorithm were then extracted from EnergyPlus into a stand-alone package to facility use without the building energy model and more extensive testing and validation of the underlying operations.", + "laborHours": 192158.4, + "languages": [ + "C++" + ], + "name": "AirflowNetwork [SWR 19-45]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/AirflowNetwork", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-11", + "metadataLastUpdated": "2019-07-11" + }, + "description": "This program a new physical insight regarding efforts to evaluate electrochemical catalysts being developed for electrochemical energy conversion and storage. In particular, we ask: The methodology described here offers a solution to the problem of how to conduct Tafel analysis, which is used in determining electrocatalyst performance, in a quantitative manner, rather than through the qualitative guesswork it currently requires. This enables the measurement of electrocatalyst Tafel slopes and their associated parameters in a way that avoids the introduction of researcher bias, a problem to which current methods of Tafel fitting are prone. This procedure should significantly improve the ability of researchers working in the field of electrochemical energy conversion to rate and compare the catalyst materials being developed, advancing the characterization toolkit available to experimental electrochemists. \n\nThis work is born out of our general hypothesis that it should be possible to determine the proper regions for unambiguously fitting Tafel data by applying some set of physical constraints that link aspects of a Tafel plot to its corresponding J-V polarization curve. This algorithm applies such constraints and achieves the extraction of Tafel slopes in a wholly quantifiable and reliable fashion. Verification of this approach is achieved by pairing the theory with experiment, as the algorithm was tested using experimentally acquired data of three distinct, electrochemical reactions: platinum hydrogen evolution, iridium-catalyzed oxygen evolution, and platinum-catalyzed dioxygen reduction. For each of these cases, the algorithm predicts the same Tafel slope as those reported in long-established bodies of electrochemical literature, results suggesting the general applicability of this method for determining electrocatalyst Tafel slopes.", + "laborHours": 0.0, + "languages": [], + "name": "Tafel Fitter v1.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MEG-LBNL/Tafel_Fitter", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-11", + "metadataLastUpdated": "2019-07-12" + }, + "description": "A database, web API and portal will be developed that stores data from synchotron experiments. The data stored will be: \n- metadata about the experiment (who ran it, when it was conducted, what proposal and ESAF were covered) \n- references to raw data (e.g. images taken at the beamline) \n- references to derived data \n\nBeamline users and Beamline staff will have private access to view experiment data and assign web-friendly visualizations to it. They will also be use the portal to download some of the data taken at the beamline. They we will be able to create and approve experiment pages that can be viewed publicly. \n\nThe software created for this project will include replication and fail over technologies to maintain a high level of uptime. \n\nSoftware developed in this project will be: \n- database schema \n- web middleware to create a web API \n- web-based user interface code", + "laborHours": 4833.6, + "languages": [], + "name": "Splash v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/als-computing/splash", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2020-07-09" + }, + "description": "hypre is a library of high performance preconditioners and solvers featuring multigrid methods for the solution of large, sparse linear systems of equations on massively parallel computers.\n", + "laborHours": 0.0, + "languages": [], + "name": "hypre", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hypre-space/hypre/releases/tag/v2.17.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "V2.17.0" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-10-04" + }, + "description": "This software provides a basic Generative Adversarial Network (GAN) template for modeling 2D slices of N-body dark matter simulations, as part of the Exalearn project. The underlying design is a standard deep convolutional GAN, but we augment it with a technique we are calling multi-channel rescaling. This technique adds a second image channel to the output of the GAN, which represents the data in a different normalization in order to improve the quality of the results.", + "laborHours": 349.6, + "languages": [], + "name": "ExaGAN v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pzharrington/ExaGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-15" + }, + "description": "FUDGEFudge provides (Python based) tools to:\n\u2022 Store and modify nuclear data.\n\u2022 Convert ENDF-6 formatted nuclear data [1] into Generalized Nuclear\nData (GND) structure [2].\n\u2022 Convert LLNL\u2019s ENDL formatted nuclear data [3] into GND.\n\u2022 Plot data from GND files.\n\u2022 Check for physics problems in GND files.\n\u2022 Process nuclear data for use by Monte Carlo and/or deterministic\ncodes. Fudge contains hooks for the future addition of nuclear data\nprocessing routines.\nThe Fudge release includes samples of published ENDF-6 formatted data that\ncan be converted to the new GND format.\nThis software is the next release in a series of releases that began with GND\nversion 0.1 [2].", + "laborHours": 84664.0, + "languages": [], + "name": "fudge", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/paulromano/fudge", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "GIDIplus contains libraries for reading and using GNDS-formatted nuclear data.\n\nIt includes sub-packages\nGIDI, MCGIDI, PoPs, numerical Functions and status Message Reporting along with scripts for building and installing the entire library.", + "laborHours": 60359.2, + "languages": [], + "name": "Generalized Interaction Data Interface and associated packages", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "The Bridge Kernel is a Jupyter Kernel for connecting to compute backends that implement the bridge kernel (bk) protocol. The bk protocol is a client-server protocol that emphasizes minimal dependencies, easy embedding with MPI, secure connections + authentication, and non-local backends with automatic\ntunneling.", + "laborHours": 562.4, + "languages": [], + "name": "Bridge Kernel", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/bridge-kernel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "Implementation of the Progressive Hedging algorithm written in Julia utilizing JuMP. This is used to solve multistage optimization problems (e.g. Stochastic programs or capacity expansion models). The user uses the StructJuMP extension of JuMP to create the model and build up the scenario tree.", + "laborHours": 820.8, + "languages": [], + "name": "ProgressiveHedging.jl", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ProgressiveHedging.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "A comprehensive package to study lattice dynamics from first-principles. The interatomic force constants were fitted using the compressive sensing algorithm.", + "laborHours": 11734.4, + "languages": [], + "name": "Compressive sensing lattice dynamics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/csld", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "The General Interaction Data Interface (GIDI) is a C++ API that reads and writes nuclear reaction data stored in the General Nuclear Data Structure (GNDS). GNDS is a new \"format\" for storing nuclear reaction data developed by the Working Party on Evaluation Co-operation (OECD/NEA/WPEC) Subgroup 38. \n\nGNDS can store evaluated nuclear data as well as nuclear data processed for deterministic (multi-group) and Monte Carlo transport. GIDI handles and provides accesses to all forms of the GNDS nuclear data.\n\nFor multi-group data, GIDI provides functions to sum the data over all reactions. It also has functions for collapsing multi-group data to a small subset of groups and can transport correct multi-group data using the Pendlebury/Underhill formalism.\n\nThe GNDS definition supports data for a PROjectile hitting a TARget for a given Evaluation. In GIDI this is called a PROTARE. For example, a neutron hitting O-16 from the ENDF/B-VIII.0 evaluation.\n\nTo support a collection of protares, GIDI adds a Map class. The map class reads in a \"map\" file which specifies a list of projectile/target/evalaution's and their associated protare files. \n\nWith a map instance, a user can request a specific projectile/target/evaluation and the map instance will return the requested protare.", + "laborHours": 60359.2, + "languages": [ + "C++" + ], + "name": "General Interaction Data Interface", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.17" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-11-26" + }, + "description": "Software suite with multitask learning models. The pipeline includes functionality to process data, train, evaluate models, and generate reports.", + "laborHours": 1444.0, + "languages": [], + "name": "Multi-Task Learning Software Suite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MTL-suite", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "A new format for storing particle information (i.e., mass, spin, parity) has been developed. \n\nThe format is a subset of the Generalized Nuclear Data Structure (GNDS) developed for storing nuclear reaction data. \n\nA C++ library dubbed \"Property of Particles\" (PoPs) has been developed to read particle data in the GNDS\nformat. \n\nThe PoPs library provides functions for reading in a GNDS particle database as well as for accessing a particle and its properties.", + "laborHours": 60359.2, + "languages": [ + "C++" + ], + "name": "PoPsCpp", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "Sina is a tool set for modern scientific data management that provides flexible, light-weight support of non-bulk data capture for retention in and queries against SQL and noSQL data stores. HPC simulations traditionally maintain their data in files. Extracting data of interest for subsequent analysis then requires the time-consuming process of traversing directories and scraping data from files in a variety of formats. Sina facilitates capturing relevant data during execution or post-processing of simulation runs for retention in and queries from a modern data store. The tools are sufficiently general to allow for the inclusion of new fields as scientists learn more about their data. Libraries, currently in C++ and Python, and a command line interface (CLI) are provided.\nSina's flexibility starts with a general schema, in JSON, for the collection of non-bulk simulation data. JSON provides a flexible, human-readable representation of the data that of interest. Sina currently has a C++ library for simulations to write data to and read from a schema-compliant file for subsequent ingestion into one of the supported data stores. However, applications are free to write their data directly into a schema-compliant file. Python packages provide data ingestion, management, query, and export capabilities. A command line interface (CLI) provides simplified access to these features. A common application programming interface (API) is used to maintain and query data in any of the supported data stores, which are currently limited to SQL and Apache Cassandra (a column store). Tutorials, demonstrations, and examples illustrate aspects of the process using scripts and Jupyter notebooks.", + "laborHours": 5487.2, + "languages": [], + "name": "Simulation INsight and Analysis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Sina", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "The numericalFunction C library is designed to handle point-wise interpolative data representing a mathematical function. The library currently handles 1-d functions (i.e., functions of the format f(x)). \n\nThe main object is the ptwXYPoints C struct that holds list of x,y pairs sorted by ascending x-values with an interpolation rule. That is, it contains the 1-d function f(x) = y(x). \n\nFunctions are included that support common unitary and binary operations (e.g., negation, addition, multiplication). \n\nAs example, if f(x) and g(x) are two ptwXYPoints instances, then routines to calculate f(x) + g(x) and f(x) * g(x) are included.\n\nThe library support storage of data with lin-lin, lin-log, log-lin, log-log and flat (or histogram) interpolation.\n\nFunctions to convert any of the supported interpolation to lin-lin are included. However, many of the binary functions only support lin-lin interpolation.\n\nThe library also contains a C struct for storing a Legendre series representation of a 1-d function, and functions to convert Legendre series to and from a ptwXYPoints instance.\n\nA python interface to the library is included, with the ptwXYPoints C struct treated as a class. This class has many of the standard python math methods (e.g., __add__, __mul__).", + "laborHours": 60359.2, + "languages": [ + "Python" + ], + "name": "numericalFunctions", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-16" + }, + "description": "A Browser-based visualization of morphology, material, and chemical data extracted from chemical papers. This UI is focused for specifically nanomaterial synthesis papers. The visual analytic environment allows the user to explore a large number of papers quickly, through an interactive, intuitive, and visual way that helps see possible trends in the data. This exploration-oriented systems allows domain experts who may not have an extensive background in writing analysis code or database queries to easily express their idea to experiment on the data and view the results.\nThe visualization software requires the data in JSON format. The data packaged with the software is the result of 35k nanomaterial synthesis papers queried from Elsevier, created through a separate software pipeline. The data contains information such as the title, authors, chemicals, and created material and morphology.", + "laborHours": 2773893.6, + "languages": [], + "name": "Materials Informatics ChemVis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MI-ChemVis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-16" + }, + "description": "goTLS is an automated TLS certificate issuance and management tool for Windows, Mac, and Linux. \n\nIt can generate keys, CSRs, and optionally obtain the certificate with an internal Active Directory Certificate Services (ADCS) endpoint.", + "laborHours": 243.2, + "languages": [], + "name": "goTLS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gotls", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-16" + }, + "description": "Zero-order Reaction Kinetics (Zero-RK) is a software package that simulates chemically reacting systems in a computationally efficient manner. The fundamental advance embodied in Zero-RK is the numerical approach, which results in orders-of-magnitude reduction in simulation time while maintaining the accuracy of the results.", + "laborHours": 13497.6, + "languages": [], + "name": "Zero-Order Reaction Kinetics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/zero-rk", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-16" + }, + "description": "Unlike computer languages like C++ which has throw/catch, Python which has try/except and other newer computer languages, C has no built-in mechanism for handling exceptions (e.g., memory allocate failure or a divide by zero exceptions).\n\nWhile simple exception handling in the form of an integer parameter (e.g, errno) or an enum are often implemented in C programs, the richer types of exception reporting possible with newer computer languages are rarely implemented in C. \n\nThe statusMessageReporting package was created to facilitate rich exception reporting by C functions to their calling functions.\n\nThe statusMessageReporting (smr) package allows a function, called the generator, to communicate an exception to its calling function using a statusMessageReporting report. \n\nThe main parts of a report are:\n\n1)the level of the report called the status (valid levels are smr_status_Ok, smr_status_Info, smr_statusWarning and smr_status_Error)\n\n2) a string called the report's message and 3) two integer values, one representing the generator's ID, called the libraryID, and the other is the library's specific integer, called the code, that represents the type of exception the generator is reporting.\n\nThe code is similar to the errno for the C standard library. Since libraries are often developed independent of one another, they often use the same code values to represent different exceptions (e.g., one library may define the code 3 to be an error opening a file while another library may define the code 3 to be a divide-by-zero error) which is why the libraryID is needed. \n\nThat is, the equivalent of errno is the combination libraryID:code. To insure that each library's libraryID is unique, libraryIDs must be obtained from the function smr_registerLibrary.\n", + "laborHours": 60359.2, + "languages": [ + "Python" + ], + "name": "statusMessageReporting", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-16" + }, + "description": "SPIFY is a C++ library for parsing input files to be used in scientific computing applications.\n\nThe library allows an application developer to define a full set of required and optional input variable of different types\nand handles all of the parsing and validation.", + "laborHours": 912.0, + "languages": [ + "C++" + ], + "name": "Spify Parser of Input Files with YAML syntax", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/spify", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-17" + }, + "description": "WaterSystems.jl is a Julia package for defining water delivery infrastructure system data and problem definitions. The WaterSystems.jl package enables parsing from the EPANET *.inp file format and the expression of data for WaterSimulations.jl models. WaterSystems.jl defines a data schema for water infrastructure networks. ", + "laborHours": 167.2, + "languages": [ + "julia" + ], + "name": "WaterSystems.jl", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WaterSystems.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-17" + }, + "description": "This Matlab script implements a simple topology optimization algorithm that minimizes the compliance of a structure within a 3D prismatic design domain. \n\nIt uses a simple linear elastic finite element solver to solve the equilibrium equations, and the optimality criterion (00) method to update the design iteratively.\n\nThis functionality is identical to, or the simplest possible extension from 2D to 3D of, a 99-line Matlab code released in 2001 in a journal article by Sigmund. \n\nWhat is new in this code is our implementation of simple surrogate models for several truss micro-architectures, which converts this code to a multiscale design tool, whereas the original code is single-scale. \n\nThe development of these surrogate models and their implementation is described in a journal article we intend to submit. \n\nWe plan to include the full source code in an Appendix in this paper. \n\nThe code\u2019s primary function is as a pedagogical tool rather than as a finished software product. \n\nSigmund\u2019s 2001 paper describes the implementation line-by-line.\n\nWe are including this updated version of the code to allow the reader to understand exactly what changes must be made to a \u201cstandard\u201d topology optimization code to implement the surrogate models and thus multiscale design optimization.", + "laborHours": 91.2, + "languages": [ + "MATLAB" + ], + "name": "Matlab Code for Multiscale Topology Optimization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MultiscaleTopOpt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-19", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Tools to construct a model for sources of radioactive backgrounds in a low radioactivity dertector system\nBackground explorer simplifies or automates many of the tedious and error-prone tasks involved in creating a detailed radioactivity budget for a low background detector system. The tool also provides a rich web interface allowing even nontechnical users to easily modify the model assumptions and drill-down into the model and result details.\nBackend: https://github.com/bloer/bgmodelbuilder Web application: https://github.com/bloer/bgexplorer \nDemo/user template: https://github.com/bloer/bgexplorer-demo", + "laborHours": 2325.6, + "languages": [], + "name": "Background Explorer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bloer/bgmodelbuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2024-07-23" + }, + "description": "PyGSTi is a Python package for modeling and characterizing noise (errors) in small quantum information processors. In addition to being a basic framework for describing quantum circuits and noise models, it implements mainstream quantum characterization, verification, and validation (QCVV) protocols such as Gate Set Tomography (GST), Randomized Benchmarking (RB), Robust Phase Estimation, and Idle Tomography. It also implements prototype protocols used for timeseries analysis and crosstalk detection, all of which have the goal of better understanding the noise found in existing as-built experimental devices. The central protocol of pyGSTi (from where it derives its name) is Gate Set Tomography. GST is a theory and protocol for simultaneously estimating the state preparation, gate operations, and measurement effects of a physical system of one or many quantum bits (qubits). These estimates are based entirely on the statistics of experimental measurements, and their interpretation and analysis can provide a detailed understanding of the types of errors/imperfections in the physical system. In this way, GST provides not only a means of certifying the \u201cgoodness\u201d of qubits but also a means of debugging (i.e.\nimproving) them. The other protocols follow this similar pattern in that they use statistical inference and analysis of experimental data to estimate one or more properties of the noise in a\ndevice.", + "laborHours": 317619.2, + "languages": [ + "C++", + "CSS", + "HTML", + "Jupyter Notebook", + "Cython", + "Python" + ], + "name": "Python GST Implementation (PyGSTi) v. 0.9", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyGSTi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.9.12" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2020-06-15" + }, + "description": "HyRAM is a software toolkit for conducting quantitative risk assessment (QRA) and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM contains validated, simplified hydrogen behavior models, a standardized QRA approach, and engineering models and generic data relevant to hydrogen installations. HyRAM 1.0 was developed by Sandia National Laboratories for the U. S. Department of Energy.\nSAND2019-5270 M", + "laborHours": 21508.0, + "languages": [], + "name": "HyRAM (Hydrogen Risk Assessment Models) v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hyram", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 2.0" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2019-07-22" + }, + "description": "Scripts that enable emulating firmware by intercepting low-level hardware abstraction function calls and replacing their execution with abstractions of the hardware the intercepted functions are intended to interact with.", + "laborHours": 4316.8, + "languages": [], + "name": "HALucinator v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/embedded-sec/halucinator", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A JIRA Add-on that adds custom workflows and automation hooks for provisioning services within other Atlassian tools like Confluence, Bitbucket, and Crucible/Fisheye based on project keys", + "laborHours": 4727.2, + "languages": [], + "name": "pnnl/jira-aperture", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/jira-aperture", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2025-01-08" + }, + "description": "In silico chemical library engine for high-accuracy chemical property prediction", + "laborHours": 3815.2, + "languages": [], + "name": "pnnl/isicle", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/isicle", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Plan and visualize staff labor allocation. This package produces outputs in spreadsheet form that are easily navigable and informative. Outputs include staff-level individual summaries detailing project commitment monthly, project-level summaries highlighting the number of staff and hours per project within an organization, a staff overview summary containing funding probability considerations and visualization, all staff rundown of monthly commitments tied to visual indicators for over- and under-commitment, and overall summary charts and data for all staff and all project and their interrelation. labor_planner was designed for extension and reuse and the authors encourage continued community development.", + "laborHours": 668.8, + "languages": [], + "name": "Labor_Planner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/crvernon/labor_planner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-23", + "metadataLastUpdated": "2019-07-25" + }, + "description": "A critical component of designing solar energy projects that will have long-term profitability is the availability and access to accurate \u201cbankable data\u201d, methodologies and tools to understand the uncertainties in the data. The current solar energy performance and economic models used to convert solar resource data to power generation do not factor in or provide adequate information regarding the uncertainty in the solar resource information. The Solar resource uncertainty (SOLARUN) application assists stakeholders to quantify solar resource measurement uncertainty from radiometers which ultimately support in the decision-making process, speeds up the acceptance and deployment of projects and reduces risk to the financiers and developers.", + "laborHours": 319.2, + "languages": [], + "name": "SOLARUN (SolarResourceTools)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SolarResourceTools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-25", + "metadataLastUpdated": "2019-07-25" + }, + "description": "AnisWave2D is a 2D finite-difference code for simulating seismic wave propagation in fully anisotropic materials. The code is implemented to run in parallel over multiple processors and is fully portable. A mesh refinement algorithm has been utilized to allow the grid-spacing to be tailored to the velocity model, avoiding the over-sampling of high-velocity materials that usually occurs in fixed-grid schemes.", + "laborHours": 0.0, + "languages": [], + "name": "AnisWave2D", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sainslie1966/AnisWave2D", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL is developing an automated procedure to perform the system-level model validation for the Central America power grid, which includes six countries and one power system equivalent model for Mexico representation is also considered. The specific features for this invention are given as follows: 1) Automated case integration of Mexico equivalent model and Central America grid model\u037e 2) Automated power system event replay based on system-level dynamic simulations\u037e 3) Automated extraction and comparison of power flow conditions/measurements/quantities between SCADA/PMU data and simulated data for pre-event, during event and post-event stages\u037e 4) One procedure to identify potential mismatch in power flow conditions and erroneous model parameters in power system dynamic models.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Automated System-Level Model Validation for Central America", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Rapid Analytics for Disaster Response (RADR) is a disaster response and situational awareness system that provides actionable insights using image analytics derived from optical and radar-based remotely-sensed imagery (optical and radar satellite, airborne, UAS). Geospatial analysis can also interface with the image analytic results to understand potential impacts to critical infrastructure assets. The rapid response is driven by a lifecycle workflow that spans event monitoring and action, image acquisition and retrieval, image pre-processing, image analytics algorithm deployment, analytics packaging, and analytics delivery.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Rapid Analytics for Disaster Response (RADR)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Industrial Radiography Mobile Source Transit Security (IR-MSTS) Software and Firmware Applications and Components described here are part of a system developed under NNSA funding to track mobile radioactive sources used in the industrial radiography service industry. The individual software applications and libraries, and firmware executables work together and in conjunction with the electronic hardware components to provide situational awareness of the radioactive sources as they are transported from the home base of operations to a job site and back again. Industrial radiography devices are equipped with IR-MSTS components to provide near real time source location information. A Global Positioning System (GPS) is used to track the geographic location of the transport vehicle. Various sensors are used to detect and report tamper of the IR-MSTS components. Base Station application software, IR Dashboard, allows qualified personnel to track alarms, device information and locations and provides contact info of individuals that need to be notified should anomalous conditions be detected. Firmware for Industrial Radiography 31602 IR Cloud Services for Industrial Radiography 31600 PM-Mat Firmware for Industrial Radiography 31599 IR Dashboard for Industrial Radiography 31598 PM-Box Firmware for Industrial Radiography 31597 PM-Tag Firmware for Industrial Radiography 31596 VCU Firmware for Industrial Radiography 31595", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Industrial Radiography Mobile Source Transit Security Software and Firmware", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Well Logging Mobile Source Transit Security (WL-MSTS) system was developed under funding from the National Nuclear Security Administration (NNSA) Office of Radiological Security (ORS). The objective of the system is to track mobile radioactive sources used in the well-logging service industry in support of oil and gas exploration. The individual software applications and libraries, and firmware executables work together and in conjunction with the electronic hardware components to provide situational awareness of the radioactive sources as they are transported from the home base of operations to a job site and back again. Information flows in near real time from the transport vehicle carrying the sources to the end user's central monitoring center using both cellular and satellite communications. A combination of active radio-frequency (RF) tags (attached to source shields) and radiation sensing is used to monitor the proximity of the radioactive sources to the transport vehicle. A Global Positioning System (GPS) is used to track the geographic location of the transport vehicle. Various sensors are used to detect and report tamper of the WL-MSTS components. An in-Cab Unit (iCU) is used to provide local status of the monitoring system to the driver of the transport vehicle. A browser based application allows authorized engineers to interact with the monitoring system to configure it and check status. Base Station application software allows qualified personnel to track alarms, source information and source locations and provides contact info of individuals that need to be notified should anomalous conditions be detected.\nWell Logging Master Control Unit (MCU)\t31390\nWell Logging MSTS rTag firmware\t31433\nWell Logging - In Cab Unit firmware\t31432\nBLE Beacon Electronic Tag (eTag) Firmware\t31480\nHome Base Security Solution (HBSS) Vault Extender Scanner\t31566\nHome Base Security Solution (HBSS) Master Scanner Firmware\t31567\nWell Logging MSTS Message Parser Library\t31568\nWell Logging MSTS GSOC Viewer\t31569\nWell Logging MSTS Admin Tool\t31570\nWell Logging HBSS Bunker Automated Data Service (BADS)\t31571\nWell Logging HBSS Bunker Inventory Graphical System (BIGS)\t31572\nWell Logging Master Control Unit Overpack (WL-MCU-OP) Firmware\t31583", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "The Well Logging Mobile Source Transit Security (WL-MSTS) system", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2019-07-29" + }, + "description": "The scientific community performs a lot of redundant work when working with data. Researches tend to write their own code to perform basic functions for reading, visualizing, and analyzing the data. This strategy is unnecessarily time consuming, and potentially costly, for the individual researcher (as well as for programs). Open-source software disrupts that process and moves the development effort toward capabilities that can be used by the broader scientific community. The broader scientific community can then, in turn, contribute to and collaborate on efforts to improve the process for the individual researcher and program. Researchers will be able to do more science with fewer resources without the burden of developing code from the ground up. For any software to be adopted by a community, it needs to have a solid framework that will be easy to use and provide clear benefit worthy of the investment in participating. In support of this goal, our Atmospheric Data Community Toolkit will leverage the knowledge gained from the successful adoption of the Python Atmospheric Radiation Measurement User Facility Radar Toolkit (Py-ART) to build that framework. The framework will provide the environment to enable collaboration in the research community. This environment will allow the development of tools for funded programs, as well as provide researchers in the scientific community with code for advancing their work. Research programs will also be able to adopt code provided by the scientific community without having to develop it from scratch. The final goal of this proposed effort is to have a framework on GitHub that has the basic features that the atmospheric research community needs to begin working with and adopting, including, but not limited to, reading and visualization. We expect future effort will be needed for Argonne scientists to demonstrate their specific capabilities within this framework. This project will provide an avenue for other proposed research to be demonstrated, such as the Global Oceans/Argonne proposed Atmospheric Instrumentation Suite; edge computing National Science Foundation proposed effort; and the Computing, Environment, and Life Sciences Directorate's strategic effort on the Southern Great Plains climate observation site relating to water across the surface interface. ", + "laborHours": 3784.8, + "languages": [], + "name": "ATMOSPHERIC DATA COMMUNITY TOOLKIT (ACT)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-DIGR/ACT", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "A C++ implementation of a web_view interface being proposed for standardization by the C++ standards committee.", + "laborHours": 319.2, + "languages": [], + "name": "web_view", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hfinkel/web_view", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "GRChombo is a new numerical relativity code written to take full advantage of modern parallel computing techniques. GRChombo's features include full adaptive mesh refinement (AMR) with block structured Berger-Rigoutsos grid generation which supports non-trivial \"many-boxes-in-many-boxes\" meshing hierarchies, and massive parallelism through the Message Passing Interface (MPI). GRChombo evolves the Einstein equation with the standard BSSN formalism, with an option to turn on CCZ4 constraint damping if required. It can stably and accurately evolve vacuum black hole spacetimes such as binary black hole mergers, and non-vacuum spacetimes such as scalar collapses into black holes. ", + "laborHours": 6551.2, + "languages": [], + "name": "GRChombo", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GRChombo/GRChombo", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-31" + }, + "description": "PyARC is a wrapper script developed to integrate the Argonne Reactor Computation suite of neutronic codes into the NEAMS Workbench user interface. It contains the Workbench \"common input\" definition, handles some pre-processing, writes the native codes inputs, handles the runtime environment, and performs some post-processing. It was developed to facilitate access and utilization of the ARC codes, and facilitate transition to higher fidelity NEAMS codes.", + "laborHours": 21356.0, + "languages": [], + "name": "PyARC", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/neams-workbench/PyARC", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "OpenADR 2.0 a/b Virtual End Node (VEN) node for Node-Red.", + "laborHours": 1930.4, + "languages": [], + "name": "node-red-contrib-oadr-ven", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/node-red-contrib-oadr-ven", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "Calibrate high-pressure using Au or Ag powder diffraction. Designed to be used with spec files from the 4-ID-D beamline, Advanced Photon Source, Argonne National Laboratory. ", + "laborHours": 851.2, + "languages": [], + "name": "pypressxrd", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gfabbris/pypressxrd", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "To the author's knowledge, VALENCE is the only implementation of the variational subspace valence bond (VSVB) method. At Argonne, VSVB was developed from the ground up with extreme scalability and high performance on emerging hardware paradigms in mind. Thus, VSVB is the only quantum chemistry method that promises high accuracy with cross-cutting applicability at the exascale. VSVB also offers unique opportunities for machine learning and stands to revolutionize many fields across materials science, chemistry, and biology. The existence of an open-source software implementation of VSVB is an essential step in its development and support for the benefit of the community. ", + "laborHours": 4924.8, + "languages": [], + "name": "VALENCE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gdfletcher/VALENCE", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "This software is a package for assimilating data from multiple radars and models together to create a 3D wind retrieval over a region. The framework is based off of the minimization of a cost function related to the varying sensors, mass continuity, and model. Since it is open source the community is able to contribute and expand the package to use data from their own desired model or sensor. ", + "laborHours": 2675.2, + "languages": [], + "name": "PyDDA (Pythonic Direct Data Assimilation)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openradar/PyDDA", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dching@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2023-02-02" + }, + "description": "Tike is a library for reconstructing a 3D object from its diffraction measurements.", + "laborHours": 0.0, + "languages": [ + "CUDA", + "Python" + ], + "name": "Tike", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdvancedPhotonSource/tike.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "This is python software couples UrbanSim, a free software package to the Argonne Isomodel building energy model and provides a few analysis tools.", + "laborHours": 0.0, + "languages": [], + "name": "Urbansim to Isomodel", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/urbansim-isomodel", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-30" + }, + "description": "X-ray ptychography imaging at synchrotron facilities like the Advanced Photon Source (APS) involves controlling instrument hardwares to collect a set of diffraction patterns from overlapping coherent illumination spots on extended samples, managing data storage, reconstructing ptychographic images from acquired diffraction patterns, and providing the visualization of results and feedback. This brings up the need to develop a flexible, robust and user friendly processing pipeline for ptychographic data analysis. Here we present a software framework including visualization and ptychographic data reconstruction for streaming data analysis and reconstruction. ", + "laborHours": 4666.4, + "languages": [], + "name": "ptychopy", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kyuepublic/ptychopy", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "This IDL based GUI interface is for complete phase retrieval based on transport of intensity formalism. It provides routines for alignment of images, alignment of unflipped and flippped image stacks and finally various options for phase retrieval algorithm. ", + "laborHours": 1140.0, + "languages": [], + "name": "Full TIE Reconstruction", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cphatak/full_tie", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2020-06-01" + }, + "description": "Library for managing ensemble-like collections of computations", + "laborHours": 7311.2, + "languages": [], + "name": "LibEnsemble", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Libensemble/libensemble", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2024-08-07" + }, + "description": "SWinzip is a Matlab and C++ library for scientific lossy data compression and reconstruction using compressed sensing and tree-wavelets transforms. These methods are known for their large compression and usefulness in data analytics such as features extraction. Compressed sensing and wavelets methods rely heavily on sparse and dense linear algebra operations implemented through the Boost codes in our library. SWinzip accommodates data represented on both regular grids (e.g. image data) and point-clouds (e.g. unstructured meshes).\n\nIn SWinzip v2.0, there is more focus on wavelet compression and the following\nfeatures are added:\n\n- The matrix-free (direct) wavelet transform is implemented in both C++ and Matlab. A threshold-based compression can now be used. Examples for distributed compression are also added.\n- Python implementation of Alpert wavelet transforms\n- Field data comparison using wavelets in Matlab with global and local metrics", + "laborHours": 13740.8, + "languages": [ + "C++", + "C", + "MATLAB", + "Makefile", + "Python" + ], + "name": "SWinzip v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SWinzip", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 2.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "X-ray grating interferometry has been employed for a wide range of imaging applications by using the Talbot self-images of a grating. At synchrotron facilities, it has also been exploited to characterize the coherence and wavefront of the x-ray beam. The method is relatively straightforward, easy to implement, and provides accurate quantitative data. However, to exploit its full potential, it requires highly specialized, robust data analysis. If this works, we have set the framework for the development and dissemination of a robust open-source code called wavepy that is tailored to the data analysis for imaging and beam characterization using grating interferometry. Wavepy consists of a Python library for data analysis of x-ray grating interferometry. The library takes advantage of the python programming language capabilities and flexibility, and aims to be easy to collaborate, distribute, and integrate with other imaging packages. The main reason for using Python is twofold: to take advantage of a widely used language in the scientific community, and also to make extensive use of the existing Python libraries for numerical calculation and plotting, namely numpy, scipy and matplotlib. Installation is facilitated by using conda to solve dependencies. The development makes use of git for version control and collaborative development. The code is hosted in the GitHub repository https://github.com/APS-XSD-OPT-Group/wavepy. One of the reasons for using Python is to be able to integrate wavey with other projects, mainly DXchange to seamlessly load images of different formats, and TomoPy for tomography. The main code is a collection of functions that can be used in different ways, for instance, inside a development environment (DE) or by creating a graphical interface that uses wavepy underneath. ", + "laborHours": 3040.0, + "languages": [], + "name": "wavepy", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/APS-XSD-OPT-Group/wavepy", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "Supervised Learning Approach for Dynamic Sampling using Deep Neural Networks.", + "laborHours": 608.0, + "languages": [], + "name": "SLADS-Net", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cphatak/SLADS-Net", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "DeepHyper is a Python package and infrastructure that targets experimental research in DL search methods, scalability, and portability across high performance computing (HPC) systems. It comprises three modules: benchmarks, a collection of extensible and diverse DL hyperparameter search problems; search, a set of search algorithms for DL hyperparameter search; and evaluators, a common interface for evaluating hyperparameter configurations on HPC platforms. ", + "laborHours": 12388.0, + "languages": [], + "name": "DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/deephyper/deephyper", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "Decaf is a dataflow system for the parallel communication of coupled tasks in an HPC workflow and allows the user to allocate resources and execute custom code in the dataflow. The runtime for calling tasks is entirely message-driven. Such a message-driven runtime allows cyclic task dependencies in the workflow graph, for example, to enact computational steering based on the result of downstream tasks. Decaf can stand alone as a complete workflow system, or Decaf can also be used as the dataflow layer by one or more other workflow systems to form a heterogeneous task-based computing environment.", + "laborHours": 45372.0, + "languages": [], + "name": "Decaf", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tpeterka/decaf", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-31", + "metadataLastUpdated": "2019-07-31" + }, + "description": "Derivatives are required in many contexts: optimization, sensitivity analysis, uncertainty analysis, and parameter estimation. The radolc package is an interface to ADOL-C == a C++ library that facilitates the computation of first and higher derivatives of vector functions that are defined by computer programs. ADOL-C can compute gradients, the Jacobian matrix, the Hessian matrix, Jacobian vector products and Hessian vector products.", + "laborHours": 24852.0, + "languages": [], + "name": "radolc", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sriharikrishna/radolc", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-31", + "metadataLastUpdated": "2019-07-31" + }, + "description": "ENRICO is a code to automate the workflow for iteratively solving neutral particle transport via the OpenMC code and fluid dynamics via the Nek5000 code. It establishes a mapping between the geometry representation of a model in OpenMC and the spectral element mesh used by Nek5000 so that the output of each code can be used as the input of the other. Heat generation rates as solved by OpenMC are used as heat sources in a Nek5000 simulation, and the temperature/density fields from Nek5000 are used as inputs for the OpenMC model. Both OpenMC and Nek5000 are open-source, community-developed, simulation codes. ", + "laborHours": 34245.6, + "languages": [], + "name": "ENRICO: Exascale Nuclear Reactor Investigative Code ", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/enrico-dev/enrico", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-31", + "metadataLastUpdated": "2019-07-31" + }, + "description": "A source-to-source translation tool for assisting software developers in migrating from OpenACC to OpenMP 4.5", + "laborHours": 91.2, + "languages": [], + "name": "ACC2OMP", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/naromero77/ACC2OMP", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "velliquettet@ornl.gov" + }, + "date": { + "created": "2019-07-31", + "metadataLastUpdated": "2019-09-19" + }, + "description": "The Advanced Terrestrial Simulator (formerly sometimes known as the Arctic Terrestrial Simulator) is a code for solving ecosystem-based, integrated, distributed hydrology. Capabilities are largely based on solving various forms of Richards equation coupled to a surface flow equation, along with the needed sources and sinks for ecosystem and climate models. This can (but need not) include thermal processes (especially ice for frozen soils), evapo-transpiration, albedo-driven surface energy balances, snow, biogeochemistry, plant dynamics, deformation, transport, and much more.\n\nPreferred citation (including correct author order):\nEthan Coon, Markus Berndt, Ahmad Jan, Daniil Svyatsky, Adam Atchley, Eugene Kikinzon, Dylan Harp, Gianmarco Manzini, Eitan Shelef, Konstantin Lipnikov, Rao Garimella, Chonggang Xu, David Moulton, Satish Karra, Scott Painter, Elchin Jafarov, and Sergi Molins. 2019. Advanced Terrestrial Simulator. Next Generation Ecosystem Experiments Arctic Data Collection, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, USA. Version [xxx]. DOI link: https://doi.org/10.11578/dc.20190911.1", + "laborHours": 58231.2, + "languages": [], + "name": "Advanced Terrestrial Simulator", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/amanzi/ats", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-01", + "metadataLastUpdated": "2019-08-01" + }, + "description": "This software couples commercial and existing transmission system simulation software PSSE and distribution system simulation software OpenDSS to enable transmission and distribution (T&D) co-simulation. This tool is capable of both steady-state and dynamic T&D co-simulation. It is written in Python. It also integrates dynamic distributed energy resource (DER) models (Python-based standalone models developed under an EERE project) into OpenDSS to involve dynamics of DER. This tool allows transmission system entities to understand the full spectrum impact of DER on the bulk electric system (BES) and assists in ensuring secure and reliable grid planning and operations. ", + "laborHours": 4848.8, + "languages": [], + "name": "TDcosim - Transmission and Distribution System Co-simulation Tool", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tdcosim/TDcoSim", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-08-01", + "metadataLastUpdated": "2019-10-24" + }, + "description": "ML4Chem is a free, and open-source machine learning package for chemistry and materials sciences written in Python. It allows scientists to focus on applying the most commonly used machine learning models in chemistry and materials sciences with minimum effort.", + "laborHours": 2675.2, + "languages": [], + "name": "ML4Chem: Machine Learning for Chemistry and Materials v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/muammar/ml4chem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-02", + "metadataLastUpdated": "2019-08-02" + }, + "description": "This software allows the user to run simulations of a solar PV-Distributed energy resource connected to a stiff voltage source. It allows modifying DER parameters, introducing external disturbance events, and visualizing the simulation results. It models the PV-DER (inverter) using dynamic phasor concept. ", + "laborHours": 2401.6, + "languages": [], + "name": "Photovoltaic Distributed Energy Resource (PV-DER) Simulation Utility", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sibyjackgrove/SolarPV-DER-simulation-utility", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Sub-Regional Nexus Modeling\nMetis provides a framework allowing analysis of dynamics across multiple sectors including energy, water, land and socioeconomics at variable spatial and temporal scales. It is designed to be a flexible tool which can take inputs from both global integrated assessment models (IAMs) which capture global dynamics as well as more detailed models which capture specific sub-regional and sectoral details at finer resolutions. Metis integrates across tools by sharing data in standardized formats.", + "laborHours": 14348.8, + "languages": [], + "name": "JGCRI/metis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/metis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-08-05", + "metadataLastUpdated": "2019-10-03" + }, + "description": "BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets) uses a data brokering approach to synthesize diverse earth science data from a variety of remote sources in real-time without the need for additional storage. BASIN-3D is an extendable Django web framework application using a generalized data synthesis model that makes the synthesized data available via REpresentational State Transfer (REST) Application Programming Interface (API). We have currently implemented our data synthesis model to represent sensor-based time series earth science observations across a hierarchy of spatial locations. Supporting our data synthesis model is a plugin framework that allows developers to map data sources of interest to the BASIN-3D synthesis model\n", + "laborHours": 2143.2, + "languages": [], + "name": "Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets v1.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Watershed-Function-SFA/BASIN-3D", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-08-07", + "metadataLastUpdated": "2020-09-08" + }, + "description": "GPTune is an autotuning framework for exascale applications. Given an application with a set of parameters controlling its performance (e.g. runtime, memory and/or energy consumption, numerical accuracy, ...), GPTune aims at finding a combination of the parameters that yields the best possible performance. Although general enough, GPTune specializes in the tunning of expensive-to-run applications, where the cost of running the application is very expensive (in terms of computing power requirement and/or runtime).", + "laborHours": 38471.2, + "languages": [], + "name": "GPTune v.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gptune/GPTune", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-08-08", + "metadataLastUpdated": "2023-04-24" + }, + "description": "Researchers at NREL have developed a novel real-time control architecture to optimize the operation of DERs at residential, commercial, and industrial levels. The real-time system enables (portions of) feeders to emulate virtual power plants providing services to the rest of the grid, while ensuring satisfaction of electrical limits and maximizing customers\u2019 benefits. This system can be integrated with legacy hardware and/or new advanced systems to optimally manage both individually-controlled DERs and aggregations of DERs. By virtue of the proposed engineering approach, the DERs collectively regulate the powers at an electrical point to respond to grid dispatch signals such as an automatic generation control, a ramping signal, or a 5-minute dispatch. Overall, this architecture allows end customers to minimize their payments and partake in grid operations while guaranteeing power quality in the distribution network.", + "homepageURL": "https://www.labpartnering.org/p/lab-technologies/ce8d218e-4826-497d-aa9b-af23282648ec", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Real-Time Optimization of Distribution-level Energy Resources [SWR-18-27]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.federallabs.org/technology/real-time-optimization-of-distribution-level-energy-resources", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.labpartnering.org/p/lab-technologies/ce8d218e-4826-497d-aa9b-af23282648ec", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a database and associated data treatment that enables software for real-time Raman spectral analysis of sample streams in traditional flow and static solution cells and microfluidic devices. It will enable a chemometric approach to identify and quantify species of interest, including UO22+, nitric acid, and total nitrate. \nLicensed with right to sublicense.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Database and training set enabling real-time, on-line process monitoring", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-08-09", + "metadataLastUpdated": "2019-08-12" + }, + "description": "ExaCMech is a GPU-friendly library of constitutive models. Crystal-mechanics-based and porositymechanics-\nbased models are a principal focus.", + "laborHours": 1900.0, + "languages": [], + "name": "LLNL/ExaCMech", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/exacmech", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-08-09", + "metadataLastUpdated": "2019-10-11" + }, + "description": "When wind blows over snow, it self-organizes. This forms surface features, such as ripples and dunes, that alter the reflectivity and thermal conductivity of the snow.\n\nThese features have just begun to be studied by the snow and climate science communities (see 1, 2, 3 for recent work).\n\nWe created rescal-snow to provide a highly capable snow dune modelling toolkit, to enable snow scientists to study snow features in controlled numerical experiments, and produce high-quality quantitative output. \n\nWe hope that this model will be useful to researchers in snow science, geomorphology, and polar climate.", + "laborHours": 81836.8, + "languages": [], + "name": "LLNL/Rescal-snow", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Rescal-snow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "gord.stephen@nrel.gov" + }, + "date": { + "created": "2019-08-13", + "metadataLastUpdated": "2019-08-16" + }, + "description": "The Probabilistic Resource Adequacy Suite (PRAS) provides an open-source, research-oriented collection of tools for analysing the resource adequacy of a bulk power system. The simulation methods offered support everything from classical convolution-based analytical techniques through to high-performance sequential Monte Carlo methods supporting multi-region composite reliability assessment, including simulation of energy-limited resources such as storage.", + "laborHours": 76.0, + "languages": [ + "Julia" + ], + "name": "Probabilistic Resource Adequacy Suite (PRAS)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PRAS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-08-13", + "metadataLastUpdated": "2019-08-14" + }, + "description": "A small library that supports multilevel graph partitioning and graph embedding.", + "laborHours": 1763.2, + "languages": [], + "name": "Multilevel Graph Partitioning and Embedding", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/graph-embed", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-08-14", + "metadataLastUpdated": "2019-08-15" + }, + "description": "A Python library and GUI for doing comparisons of EnergyPlus\u00ae builds. EPRT is almost exclusively a developer tool for members of the EnergyPlus\u00ae development team to ensure that code changes are not impacting the test suite.", + "laborHours": 16856.8, + "languages": [ + "Python" + ], + "name": "EnergyPlus\u00ae Regression Tool (EPRT)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlusRegressionTool", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-08-15", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This is software developed in the course of my dissertation work, which was funded by Sandia. The software includes a library (the Streaming Analytics Machine or SAM) for expressing machine learning and subgraph matching over streaming data sources. It also includes a utility that will convert from a high-level language, the Streaming Analytics Language (SAL) to SAM.\n\nSAND2019-4322 M", + "laborHours": 13604.0, + "languages": [ + "C++", + "Jupyter Notebook", + "Scala", + "Python" + ], + "name": "Streaming Analytics Machine (SAM) v. 0.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.0.1" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-16", + "metadataLastUpdated": "2019-08-16" + }, + "description": "High performance parallel power flow solver that can be run in desktops as well as in high performance computing cluster. ", + "laborHours": 6216.8, + "languages": [], + "name": "PFLOW", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pflow-team/PFLOW", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-16", + "metadataLastUpdated": "2019-08-16" + }, + "description": "MAPSToTomoPy provides a graphical user interface (GUI) to control a work flow between MAPS and TomoPy, with tools for visualizing the sinograms of projection image sequences from particular elements and to use these to help correct misalignments of the rotation axis. The program also provides an integrated output of the 3D distribution of the detected elements for subsequent 3D visualization packages.", + "laborHours": 1535.2, + "languages": [], + "name": "MAPSToTomoPy", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdvancedPhotonSource/MAPSToTomoPy", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-16", + "metadataLastUpdated": "2019-08-19" + }, + "description": "ADUPROP is a scalable implementation for uncertainty propagation using the method of moments. The Taylor coefficients for the moments first (mean) and second moment (Covariance matrix) require the efficient computation of derivatives. ADUPROP leverages the technique of Automatic Differentiation (AD) to generate the implementation of derivative computations. ADUPROP solves a differential equation x' = f(x), where f(x) is a nonlinear function and the flow phi(x) of the differential equation is obtained using the usual discretization techniques: x_k+1 = phi(x_k). The user has only to provide f(x) and its Jacobian. For a given input mean and covariance matrix ADUPROP propagates this uncertainty information according to the method of moments. ", + "laborHours": 4940.0, + "languages": [], + "name": "ADUPROP", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/aduprop/aduprop", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-19", + "metadataLastUpdated": "2020-04-20" + }, + "description": "As a part of the annual Argonne Cyber Defense Competition, we develop 3 general categories of software: 1. Mock infrastructure components including ICS systems, web properties, etc.; 2. Visualization, monitoring, and network administration software; 3. Software to assist in the development of puzzles and challenges. We would like to use this disclosure to notify of the existence of this code and allow us to open source portions of the code that would be useful to our community building and education efforts associated with the Cyber Defense Competition. Software will only be released after each year's competition when it won't give a competitive advantage to future competitors. ", + "laborHours": 17084.8, + "languages": [], + "name": "Cyber Defense Competition Code ", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/cyber-defense-competition", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Metagenomic analysis is a computationally intensive task, this problem is compounded when many hundreds of samples need to be analyzed. We needed a program that would process the metagenomic sequencing data, manage computing resources, and combine the results into a unified output. We developed a script that prepares raw metagenomic sequencing data for analysis, configures analysis parameters, launches analysis jobs, keeps track of analysis progress, and combines analysis output. The analysis itself itself is done by the functionality provided by mothur (https://www.mothur.org/).", + "laborHours": 76.0, + "languages": [], + "name": "pnnl/metagenomic_analysis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/metagenomic_analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software tool implements a version of the N-SCRAD anomaly detection algorithm. This algorithm classifies a gamma-ray energy spectrum as either consistent or inconsistent with previously measured background and a set of predefined nuisance sources. N-SCRAD was originally developed for DOE/NNSA/NA-22 and has since been utilized in a variety of applications for various clients. The present software tool is intended to demonstrate the capabilities of N-SCRAD. The tool accepts input data as either text files or GADRAS binary files, and saves the output alarm metric as a text file. A separate parameter file allows advanced users to configure algorithm settings.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "N-SCRAD", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Use GrumPHP to ensure your files conform to the standards setup in your projects .editorconfig file. This plugin allows your Git pre-commit hooks to check your files for the proper file standards and reject a commit if any of your files don't conform.", + "laborHours": 136.8, + "languages": [], + "name": "GrumPHP Editor Config", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/editorconfig", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software takes JSON and YAML files, and after running them through a linter, sorts the keys of objects alphabetically. This helps prevent the following problems when checking these data/config files into repositories:\nProblems where the entire file looks like it was removed and added due to\nIndentation changes Key sorting differences\nMerging issues when 2 or more people add data to the same or similar locations", + "laborHours": 0.0, + "languages": [], + "name": "Pretty Linter GrumPhP", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pretty_lint", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-08-26", + "metadataLastUpdated": "2021-05-19" + }, + "description": "PathParser is a python-based computational tool for the thermodynamics and robustness analysis of native and designed metabolic pathways. The following functionalities are provided: 1 Max-min driving force (MDF) optimization. The Gibbs free energy change of the least favorable reaction will be maximized to evaluate thermodynamic feasibility of the entire pathway. 2 Protein cost estimation. The smallest enzyme investment will be assessed by calculating the minimal total enzyme cost supporting a given pathway flux. 3 Robustness analysis. Specifically, an ensemble of models is generated to simulate the system response to enzyme perturbation based on bifurcation theory and a continuation method. Probability of system failure and flux fold change against enzyme perturbation are estimated as well as a flux control index.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PathParser", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PathParser", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-08-26", + "metadataLastUpdated": "2019-08-27" + }, + "description": "Finds LASSO fit coefficient values of hyperspectral data for a Gaussian sigmoid basis function collection using LARS (least angle regression) methodology on a provided vector of sensor wavelength bins.", + "laborHours": 212.8, + "languages": [], + "name": "Hyperspectral Data Approximation by Gaussian Sigmoids", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/hydags", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The system allows for multiple people to \"crowdsource\" feature generation and also enables the system to use these features to suggest alternative features to the user. The user interacts with a \"canvas\", where they position icons representing pieces of data. A unique feature is that the data can be heterogeneous -- some of the icons can represent images, while others could be text, audio, etc. After the user positions items on the screen to their satisfaction, they press a button to commit the X/Y coordinates of each icon to a central database, where these positions are added as a latent feature to each item. The user also has the option to request new, untouched data be added to the canvas, and the system positions each new item according the pattern it has learned from the original data. Another unique feature is that the user can ask the system to refine their initial rough work. The system uses information theoretic measures to determine which features in the database best explain how the user positioned the icons on the screen. It then attempts to *incrementally* optimize the positions on the screen to best explain those features it isolated. The user can then adjust the positions to correct the system, or the user can request additional refinement to further optimize the positions. In this way, by incorporating user feedback and crowdsourced features, the system reduces the time required for a user to develop a rich classification scheme for large amounts of data.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "An Interactive System for Crowdsourcing Features Generation and Building Classifiers for Machine Learning (\"Sharkzor\")", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Unicorn Face provides novel \"n-shot learning\" capabilities, which enables conducting machine learning with small amounts of data in real time. The package is written in Python and provides mechanisms for training neural networks on CPUs and GPUs.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Unicorn Face", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Singular Binarized Neural Network based on GPU Bit Operations.", + "laborHours": 3024.8, + "languages": [], + "name": "GPU Accelerated Singular Binarized Neural Network Inference Framework", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/uuudown/SBNN", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-09-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL created a visualization tool that was tested with real control room operators and IT cybersecurity professionals. The tool enabled adequate communications between the two parties such that they were able to adequately address OT cybersecurity issues. The visualization tool was developed based on an iterative design process, factoring in observations and interviews with the end users, and considering the cognitive workload of the operations staff.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Cybersecurity Visualization Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-09-03", + "metadataLastUpdated": "2023-07-07" + }, + "description": "PySAM is a Python wrapper for the National Renewable Energy Laboratory\u2019s System Advisor Model (SAM). SAM is a performance and financial model designed to facilitate decision making for people involved in the renewable energy industry. PySAM provides a native Python interface for the models found in SAM Simulation Core, SSC.", + "laborHours": 127999.2, + "languages": [ + "Python" + ], + "name": "PySAM (Python Wrapper for System Advisor Model \"SAM\") [SWR-19-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pysam", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v4.2.0" + }, + { + "contact": { + "email": "miskowiecaj@ornl.gov" + }, + "date": { + "created": "2019-09-04", + "metadataLastUpdated": "2019-09-04" + }, + "description": "A graphical user interface for multipeak fitting Raman spectra, strongly based on lmfit.", + "laborHours": 380.0, + "languages": [ + "Python" + ], + "name": "PeakFitGUI", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/gxm/peakfitgui", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-09-04", + "metadataLastUpdated": "2019-09-04" + }, + "description": "MODEL FOR DESIGN, SIMULATION AND OPTIMIZATION OF MULTI-STAGE, MULTIPHASE SOLVENT EXTRACTION PROCESS", + "laborHours": 1611.2, + "languages": [], + "name": "SOLVENT EXTRACTION PROCESS SIMULATOR", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.github.com/solventx/gym-solventx", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-09-04", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ErrFilter is a tool that allows an analyst to explore data by defining simple Boolean filters on data. The tool also allows the user to sort the results by any attribute. The user sees both the distribution of filtered data as well as selected examples. The tool was designed to be applied generally to multivariate data associated with machine learning models.", + "laborHours": 65770.4, + "languages": [], + "name": "ErrFilter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/errfilter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-09-04", + "metadataLastUpdated": "2022-01-05" + }, + "description": "Software for solving nonlinear optimization problems where the objective and/or constraint functions are blackboxes.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "CONORBIT", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-09-09", + "metadataLastUpdated": "2019-09-10" + }, + "description": "SAMPA calculates the location of the Sun and Moon in the sky for the purpose of solar eclipse monitoring and for estimating the influence on solar irradiance. Valid from the year -2000 to 6000, with an uncertainty of +/- 0.0003 degrees for the Sun position and +/- 0.003 degrees for the Moon position. \n", + "homepageURL": "https://midcdmz.nrel.gov/solpos/sampa.html", + "laborHours": 0.0, + "languages": [], + "name": "SAMPA (Solar and Moon Position Algorithm)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://midcdmz.nrel.gov/sampa/#license", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://midcdmz.nrel.gov/solpos/sampa.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-09-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MPI+OpenMP implementation of Louvain method for Graph Community Detection, with a number of parallel heuristics/approximate computing techniques\nAlso called \"CuVite\"", + "laborHours": 4043.2, + "languages": [], + "name": "Exa-Graph/vite", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exa-Graph/vite", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-09-11", + "metadataLastUpdated": "2019-09-11" + }, + "description": "MinCostFlows.jl is a utility package in the Julia programming language for efficiently solving min-cost network flow problems through an implementation of the relaxation dual ascent method (Bertsekas, 1985, https://link.springer.com/article/10.1007/BF01586087). The use of a dual ascent method allows for warm-starting the solver with a solution from a previously-solved problem that need not be feasible for the new problem, providing computational performance benefits when repeatedly solving similar network flow problems. This approach is particularly useful for Monte Carlo power system resource adequacy models.", + "laborHours": 608.0, + "languages": [ + "Julia" + ], + "name": "MinCostFlows.jl", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MinCostFlows.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-09-12", + "metadataLastUpdated": "2023-12-13" + }, + "description": "The REopt\u00ae web tool (formerly known as REopt Lite\u00ae) evaluates the economic viability of grid-connected solar photovoltaics (PV), wind and battery storage at a commercial site. It allows building owners to identify the system sizes and dispatch strategy that minimize the site's life cycle cost of energy. REopt Lite\u00ae also estimates the amount of time a PV and/or wind and battery system can sustain the site's critical load during a grid outage and allows the user the choice of optimizing for energy resilience. The REopt\u00ae web tool may be found here: https://reopt.nrel.gov/tool/.", + "laborHours": 6581.6, + "languages": [], + "name": "REopt\u00ae web tool FKA: REopt Lite\u00ae [SWR-19-21]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/REopt-API-Analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-09-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "peppuR provides a machine learning pipeline for the integrative analysis of multiple and disparate data types coupled with an optimized ensemble feature selection method. The peppuR package is a suite of tools used to discover important insights to the multivariate relationship between features and biological outcome.", + "laborHours": 2994.4, + "languages": [], + "name": "pmartR/peppuR", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmartR/peppuR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-09-17", + "metadataLastUpdated": "2020-11-12" + }, + "description": "The National Thermal Generator Performance Database (NaTGenPD) is a code base used for the processing (extraction, cleaning, filtering, and fitting) and analysis of EPA CEMS data to produce a National Thermal Generator Performance Database.", + "laborHours": 2538.4, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "NaTGenPD (National Thermal Generator Performance Database)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NaTGenPD", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-09-19", + "metadataLastUpdated": "2019-10-02" + }, + "description": "Flexible communication routines that enable high-performance computing (HPC) applications to operate with less synchronization are a great benefit to application algorithm creation and developer productivity. Further, communication operations that reduce synchronization in HPC applications while continuing to scale well are critical to application performance in the exascale era. We have implemented mechanisms that allow an application to scalably execute bcast/iAllReduce from any MPI rank without specifying the origin of the message in advance, demonstrating application development flexibility, highly scalable operation, and reduced application synchronization.", + "laborHours": 11536.8, + "languages": [], + "name": "Rootless Operations for MPI (RLO) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/tonylbl/rootless-operations", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-09-19", + "metadataLastUpdated": "2019-10-01" + }, + "description": "Topology Reconfiguation is a simple algorithm to choose a network configuration with the least losses in a system with high penetration of renewable energy. It uses a linearized optimal power flow algorithm to identify the optimal setpoints of PV in a system, then performs an exhaustive search of switch configurations to find the loss minimizing solution, it repeats this process until convergence. At the end, the operator has a switch schedule for a 24 hour period that should minimize losses. VVC is a distributed algorithm in which PV units drive voltage at points within the network to 1 per unit through reactive power control. The VVC algorithm relies on extremum seeking control to provide the control. 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In order to remove the trusted third party our tool uses distributed ledger (Blockchain) technology. The ledger is used to store evidences (in the form of hash values). These values are used as an input in the integrity checking process.", + "laborHours": 1003.2, + "languages": [], + "name": "Blockchain Based Remote Data Integrity Checking Tool v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/hpc_data_integrity_code", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-10-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Maximo Json Client is a Microsoft .Net core class library. The function of the library is to abstract Http requests from\n.Net code to the IBM Maximo Json API (Json API). 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The code base is intended to serve as a support library for HDL designs.", + "laborHours": 35689.6, + "languages": [], + "name": "Bedrock v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/Bedrock", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-01", + "metadataLastUpdated": "2019-10-02" + }, + "description": "The BEDES Manager is a web-based application for archiving, searching, and editing BEDES terms and mapping them to terms in user applications. 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The Moirai are the Greek Fates, and this software is named Moirai to represent the fundamental influence of land data inputs on model outcomes. The primary function of the Moirai LDS is to combine spatially explicit input data (e.g., raster images) with tabular input data (e.g., crop price table) to generate tabular output data for a suite of variables. Some of these outputs replace the data provide by the Global Trade Analysis Project (GTAP), and other data replace and augment the original GCAM GIS processing. The Moirai LDS output data are aggregated by Geographic Land Unit (GLU) within each country. The GLU coverage is an input to the Moirai LDS (as a thematic raster image and an associated CSV file that maps the thematic integers to names), and the GLU boundaries can be determined arbitrarily. Previous versions of GCAM (and Moirai LDS) used only bioclimatic Agro-Ecological Zones (AEZs) and corresponding data that were provided by GTAP, as the GLUs. As a result, some AEZ terminology still exists in the code, but this terminology now refers more generally to GLUs. The Moirai LDS now enables any set of boundaries to be used as GLUs (including AEZs), allowing for more flexible generation of land use region boundaries (defined as the intersection of GLUs with geopolitical regions). The current default set of GLUs is the same set of 235 global watersheds as used by the GCAM water module. The GCAM 5.1 geopolitical regions (32 or 14) are included and used as inputs to Moirai to generate a mapping file between the Moirai outputs, which are at the level of the intersection between the GLUs and the country boundaries, and the geopolitical regions. The diagnostics scripts use this geopolitical region mapping in some cases. Moirai can also recalibrate three of the outputs (crop production, harvested area, and land rent) to a specified year that is the center of a five-year averaging window. No recalibration retains the circa 2000, 7-year average of the source data. The cucrrency-year for land rent can also be specified, and the default is 2001 to match the GTAP data.", + "laborHours": 7752.0, + "languages": [], + "name": "Moirai Land Data System (Moirai) v3.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/moirai", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-10-07", + "metadataLastUpdated": "2019-10-08" + }, + "description": "Software infrastructure for using a custom (user-written) scheduler with the SISPI control system of DECam, and an example template for such a scheduler. This version of the obstac code is only infrastructure for supporting writing a scheduler, not a functional scheduler in itself: earlier versions of obstac that include the DES scheduler are part of SISPI, and not included as part of this package.", + "laborHours": 623.2, + "languages": [ + "Python" + ], + "name": "obstac10", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ehneilsen/obstac10", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-10-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The current scripts utilize a well-known cluster analysis algorithm, called ordering points to identify the clustering structures (OPTICS), and an automatic cluster extraction algorithm for clustering analysis of 3D spatial data, specifically for the Atom Probe Tomography data. A hierarchical clustering scheme, together with density-based clustering, were implemented.", + "laborHours": 1778.4, + "languages": [], + "name": "pnnl/apt", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/apt", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-10-08", + "metadataLastUpdated": "2022-01-05" + }, + "description": "SKYSTRATA is a software as a service framework for managing and orchestrating containers across cloud systems.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "SKYSTRATA", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-10-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Work space for in development Economic Dispatch Application.\nMulti-purpose open-source control algorithms that will ensure real-time optimal operation, increase electric grid reliability, and lead to the goal of clean, efficient, reliable and affordable next generation building-integrated combine cooling, heating and power (CHP) system.The CHP system could include conventional heating, ventilation, air conditioning (HVAC) systems, distributed generation (DG), local storage (both thermal and electric) and local solar photovoltaic (PV) systems.", + "laborHours": 1459.2, + "languages": [], + "name": "VOLTTRON/econ-dispatch", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/volttron/econ-dispatch", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-10-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Unique Building Identifier (UBID)\nThis \"invention\" is an enhanced version of the UBID library and command-line executable that, in addition to encoding, decoding and validating UBIDs, also calculates UBID-based statistics and generates figures.", + "laborHours": 440.8, + "languages": [], + "name": "pnnl/buildingid", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-10-10", + "metadataLastUpdated": "2019-10-11" + }, + "description": "IMPLEMENTS PARALLEL GENETIC ALGORITHMS AND PHASE RETRIVAL METHOS FOR BRASS CDI TECHNIQUES. THE SOFTWARE HAS GOOD PERFORMANCE, IS EASY TO MAINTAIN AND INCLUDES MULTIPLE FEATURES TO GUIDE THE RECONSTRUCTION PROCESS.", + "laborHours": 3511.2, + "languages": [], + "name": "CDI RECONSTRUCTION (RECCDI)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdvancedPhotonSource/cdi", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kelleherme@ornl.gov" + }, + "date": { + "created": "2019-10-10", + "metadataLastUpdated": "2019-11-06" + }, + "description": "This software provides a framework for comparing different methods of finding the subtropical jet.\n\nIncluded in these is a new method for locating the subtropical jet. The tropopause gradient method uses the peak gradient in potential temperature along the dynamic tropopause to locate the subtropical jet.", + "laborHours": 2736.0, + "languages": [ + "Python" + ], + "name": "STJ_PV: Subtropical Jet Finding Framework", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mkstratos/stj_pv", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-11", + "metadataLastUpdated": "2024-04-26" + }, + "description": "The ResStock\u2122 analysis tool is helping states, municipalities, utilities, and manufacturers identify which home improvements save the most energy and money.With support from the U.S. Department of Energy (DOE), researchers at NREL developed ResStock. It's a versatile tool that takes a new approach to large-scale residential energy analysis by combining:\n\n- Large public and private data sources\n- Statistical sampling\n- Detailed subhourly building simulations\n- High-performance computing.\n- This combination achieves unprecedented granularity and most importantly\u2014accuracy\u2014in modeling the diversity of the single-family housing stock.", + "laborHours": 4008133.6, + "languages": [], + "name": "ResStock\u2122 [SWR-19-15 and SWR-20-07]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-BuildStock/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-BuildStock", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-10-11", + "metadataLastUpdated": "2019-10-11" + }, + "description": "This suite of code learns neural network models to emulate the dynamics of time series data. \n\nTo do so, it learns a set of \"neural shape functions\" that provide a common vocabulary for expressing the various dynamics operators. \n\nThe code is implemented in Python and TensorFlow.", + "laborHours": 152.0, + "languages": [ + "Python" + ], + "name": "Modeling Time Series Data with Ordinary Differential Equations and Neural Networks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tadesautels/PSINN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-10-14", + "metadataLastUpdated": "2019-10-14" + }, + "description": "A command line tool that converts a protocol specification into a target language.", + "homepageURL": "https://cdcvs.fnal.gov/redmine/projects/protocol-compiler/repository", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Protocol Compiler", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cdcvs.fnal.gov/redmine/projects/protocol-compiler/repository", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-14", + "metadataLastUpdated": "2019-10-15" + }, + "description": "This module mostly wraps the XIA C-library to control and readout the XIA-pixie16 module. It also includes some functions to analyze the data and to make control of the pixie16 more convienent in python.", + "laborHours": 2401.6, + "languages": [], + "name": "Pixie16 Python Interface (Pixie16) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/pypixie16/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-15", + "metadataLastUpdated": "2019-10-15" + }, + "description": "Code to perform operation count minimization for the evaluation of a large number of tensor contractions. A possible application is the efficient evaluation of correlation functions in lattice QCD calculations, where a reduction of computational complexity by an order of magnitude is achieved", + "laborHours": 364.8, + "languages": [], + "name": "Contraction Optimizer v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laphnn/contraction_optimizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-15", + "metadataLastUpdated": "2019-10-15" + }, + "description": "This is a controller for distributed energy resources (i.e. photovoltaics, storage,..) based on model predictive control. It is written in Python.", + "laborHours": 4453.6, + "languages": [], + "name": "Distributed Optimal and Predictive Energy Resources (DOPER) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/DOPER", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-15", + "metadataLastUpdated": "2019-10-15" + }, + "description": "GraphDot is a scikit-learn compatible library that implements GPU-accelerated graph kernels for similarity comparison between graphs.", + "laborHours": 1126912.8, + "languages": [], + "name": "GraphDot v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/yhtang/graphdot", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-16", + "metadataLastUpdated": "2019-10-16" + }, + "description": "SHEBO (surrogate optimization of problems with hidden constraints and expensive black-box objectives) is an efficient optimization algorithm that employs surrogate models to solve computationally expensive black-box simulation optimization problems that have hidden constraints. Hidden constraints are encountered when the objective function evaluation does not return a value for a parameter vector. These constraints are often encountered in optimization problems in which the objective function is computed by a black-box simulation code. SHEBO uses a combination of local and global search strategies together with an evaluability prediction function and a dynamically adjusted evaluability threshold to iteratively select new sample points.", + "laborHours": 319.2, + "languages": [], + "name": "Surrogate Optimization of Computationally Expensive Black-Box Problems with Hidden Constraints (SHEBO) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/julianem/shebo-hidden-constraint-optimization/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-16", + "metadataLastUpdated": "2019-10-17" + }, + "description": "FPEAM is a modeling framework that integrates agricultural and forestry production, supply data, and equipment budgets for those activities with methodologies for estimating air pollutant emissions.", + "laborHours": 4408.0, + "languages": [ + "Python" + ], + "name": "FPEAM (Feedstock Production to Air Emissions Model)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/fpeam", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-17", + "metadataLastUpdated": "2019-12-02" + }, + "description": "The webtool displays the following types of data:\n\nWastewater treatment plants (WWTP) with anaerobic digestion\nFacilities with anaerobic digestion onsite other than WWTP\nCombustion plants.\nManure locations.\nManure (non points)\nMunicipal solid waste locations\nCrop locations\nProcessor residue (non points)\nDistrict energy systems\nMixed use developments (non points)\nProcess heating and cooling locations\nBasic Usage\nUsers can interact with the map in the following ways:\n\nSelect the year of the analysis from a drop-down menu.\nSet the background layer as biomass availability or thermal consumption density from a drop-down menu.\nSelect whether the facility of interest is an Anaerobic Digestion or a Therochemical facility from a drop-down menu. This filters the biomass data by moisture and only shows the relevant portions based on the facility selection.\nSelect from a drop-down menu whether the biomass amounts will be shown as gross amounts or technical amounts.\nSet the radius for the search buffer in which the analysis will be performed.\nClick on any point data on the map to get more information.\nClick on the map, to given the signal of the query point location, from where the algorithmic process is going to initiate. This will show the available biomass locations and amounts that fall within the predefined buffer zone.\nDownload the data in a csv format for the entire county or the selected biomass that is inside the predefined buffer.\nReport whether there are errors in the data to us and we will work to the best of our abilities to confirm and fix any issues.\nThe outputs of the algorithmic process are going to appear on the screen after the computation is done. The outputs consist of the locations of all available biomass that are within the buffer zone from the clicked location. By clicking on any point the user can get more information on the nature and amounts of the biomass.", + "homepageURL": "https://biositing.jbei.org", + "laborHours": 11324.0, + "languages": [], + "name": "Biositing Webtool, v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://lead.jbei.org", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://biositing.jbei.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-21", + "metadataLastUpdated": "2019-10-21" + }, + "description": "This is a software utility for calculating pooling volumes and graphing quality control data of next generation sequencing libraries amplified with fluorescent intercalating agents and monitored by real-time quantitative PCR (qPCR). The tool is used to calculate pooling volumes of individual next generation sequencing libraries based on experimentally determined fluorescence values. To do this, fluorescent values are used as a proxy for relative concentration to determine the ratio of transfer volumes. The output is a \"transfer file\" that specifies the transfer volume and destination well of a given library. The tool can also be used to assess the quality of individual next generation sequencing libraries by melting curve analysis. The output are small-multiples graphs of the melting curves of individual sequencing libraries according to the specified plate layout.", + "laborHours": 152.0, + "languages": [], + "name": "Fluorescent Amplification of Next Generation Sequencing Libraries Tools (FA-NGS tools) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AgileBioFoundry/FA-NGS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2019-10-23" + }, + "description": "The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) has established a set of standardized high performance sequences of operation for Heating, Ventilation and Air Conditioning (HVAC) systems in buildings through their \"Guideline 36\". In order to achieve the intended performance, these sequences must be translated and programmed accurately in the Building Automation System (BAS) controllers. Standardizing these sequences will allow for a more efficient product delivery mechanism where the sequences are programmed and tested centrally by each manufacturer, and then distributed to their dealers/engineering contractors. This approach would minimize the need for each installer to re-interpret and program the sequences, reduces risk of errors, and reduces the time required for commissioning in the field.\n\nTo achieve this goal, a performance validation method is needed to provide independent confirmation that each manufacturer has programmed the Guideline 36 sequences accurately. A standardized method of test would also avoid the need for manual interpretation (and the associated human variability) that is required with typical functional testing approaches by automating the inputs and the range of expected responses. This software \"guideline36_conformance_test\" has been developed to conduct standardized, repeatable and manufacturer independent tests to validate that a BAS controller has been programmed in conformance with Guideline 36. Manufacturers would provide the controller (or the control program) and the software would run a suite of tests by setting a set of inputs to the controller and verifying the output signals from the controller matches the expected output as set by Guideline 36.\n\n", + "laborHours": 197.6, + "languages": [], + "name": "guideline36_conformance_test 0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/guideline36_conformance_test", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2019-10-23" + }, + "description": "The Behavior, Energy, Autonomy, and Mobility (BEAM) model is an integrated, agent-based travel demand simulation framework. Individual agents express preferences through a utility-maximizing evolutionary algorithm that minimizes each individual's cost and time spent traveling via diverse modal options, including the competition for scarce supply resources such as parking spaces and charging infrastructure. BEAM simulates the essential elements that compose a dynamic transportation system. From the road network, parking and charging infrastructure, to the transit system and a synthetic population with plans and preferences, the virtual system is an amalgamation of multiple spatially resolved layers that together represent an integrated transportation system. BEAM is an extension to the MATSim (Multi-Agent Transportation Simulation) model, where agents employ reinforcement learning across successive simulated days to maximize their personal utility through plan mutation (exploration) and selecting between previously executed plans (exploitation). The BEAM model shifts some of the behavioral emphasis in MATSim from across-day planning to within-day planning, where agents dynamically respond to the state of the system during the mobility simulation. In BEAM, agents can plan across all major modes of travel including driving, walking, biking, transit, and demand-responsive ride hailing.", + "laborHours": 58200.8, + "languages": [], + "name": "Behavior, Energy, Autonomy, Mobility Modeling Framework", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-UCB-STI/beam", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2021-02-22" + }, + "description": "MDBEngine is a class library that provides Microsoft Access (.mdb) database functionality to applications that require complex data entry. Example functionality supports undo/redo, data verification and warnings, referential integrity checks, change history tracking, and other capabilities to simplify the task of using a database in an application. SAND2019-9689 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Visual Basic .NET" + ], + "name": "MDBEngine v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2024-08-07" + }, + "description": "Software that employs an algorithm that rapidly and rigorously solves nonnegative least squares problems with many right hand sides. This is the latest internal version of MATLAB pseudocode that was described in a published in M. H. Van Benthem and M. R. Keenan, \"Fast algorithm for the solution of largescale non-negativity-constrained least squares problems,\" J. Chemom. 18(10), 441-450 (2004). Example code of this algorithm was included in the publication. This algorithm was also patented in M. H. Van Benthem and M. R. Keenan, \"Fast combinatorial algorithm for the solution of linearly constrained least squares problems,\"USPTO, Ed., Sandia Corporation, USA (2008). SAND2019-10098 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 45.6, + "languages": [ + "MATLAB" + ], + "name": "Fast Combinatorial Nonnegative Least Squares v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fcnnls", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2019-10-29" + }, + "description": "Software package for R and Python for analysis of extremes in climate data. Functions for fitting GEV and POT (via point process fitting) models for extremes in climate data, providing return values, return probabilities, and return periods for stationary and nonstationary models. Also provides differences in return values and differences in log return probabilities for contrasts of covariate values. Functions for estimating risk ratios for event attribution analyses, including uncertainty. Under the hood, many of the functions use functions from 'extRemes', including for fitting the statistical models.", + "laborHours": 8679.2, + "languages": [], + "name": "climextremes v0.2.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/lbl-cascade/climextremes-dev", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "burnsrl1@nv.doe.gov" + }, + "date": { + "created": "2019-10-24", + "metadataLastUpdated": "2019-11-19" + }, + "description": "QuickView PRO (QVPRO) is similar to QuickView but designed to focus on analysis. QuickView was designed for visualization only, adding analysis capabilities later. This made QuickView complicated when using it as an analysis tool. QVPRO uses the same analysis algorithms in a more streamlined workflow and has a user friendly GUI. QVPRO provides the unique capability of analyzing Photonic Doppler Velocimetry (PDV) data records from different PDV systems and still allows for processing hundreds of PDV data records in a practical manner.", + "homepageURL": "http://gitlab.osti.gov/doecode/dc-31683", + "laborHours": 881.6, + "languages": [], + "name": "QuickView PRO, QVPRO", + "organization": "Nevada National Security Site/Mission Support and Test Services LLC (MSTS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://gitlab.osti.gov/doecode/dc-31683", + "status": "Production", + "tags": [ + "DOE CODE", + "Nevada National Security Site/Mission Support and Test Services LLC (MSTS)" + ] + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-10-24", + "metadataLastUpdated": "2019-10-24" + }, + "description": "The principal purpose of this code is to determine bulk constitutive properties and response of polycrystalline materials. \n\nThis is a nonlinear quasi-static, implicit solid mechanics code built on the MFEM library based on an updated Lagrangian formulation (velocity based).\n\nWithin this context, there is flexibility in the type of constitutive model employed, with the code allowing for various UMATs to be interfaced within the code framework or for the use of the ExaCMech library.\n\nUsing crystal-mechanics-based constitutive models, the code can be used, for example, to compute homogenized response behavior over a polycrystal.\n", + "laborHours": 4180.0, + "languages": [], + "name": "ExaConstit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ExaConstit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.2.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-25", + "metadataLastUpdated": "2023-06-16" + }, + "description": "CatCost\u2122 is a state-of-the-art cost estimation tool designed to reduce the cost uncertainty associated with pre-commercial catalyst materials. The tool combines industry-standard cost estimation methods and resources into an intuitive suite of tools to bring actionable cost insight to every step of catalyst research and development. CatCost\u2122 allows the rapid development of comprehensive catalyst cost estimates. It incorporates detailed insight into manufacturing methods, especially for pre-commercial catalysts, without requiring any process design experience.\n\nThe tool has been designed from the ground up with a number of user-selectable estimation methods, pricing libraries, and ease-of-use features to tailor an estimate to a user's skill level and need for customization, empowering researchers of all skill-levels to make better R&D decisions throughout the catalyst development cycle. Our costing methods are fully transparent and enable power-users the ability to adjust any estimate to the economic realities of their operation.\n\nThe tool has been designed from the ground up with a number of user-selectable estimation methods, pricing libraries, and ease-of-use features to tailor an estimate to a user's skill level and need for customization, empowering researchers of all skill-levels to make better R&D decisions throughout the catalyst development cycle. Our costing methods are fully transparent and enable power-users the ability to adjust any estimate to the economic realities of their operation.\n\nFeatures include:\nRaw materials pricing: Libraries of common chemicals, cost scaling indices, guidance for obtaining bulk quotes, and methods for extrapolating laboratory-scale prices to bulk.\nSimplified step method for synthesis by a contract manufacturer: All-in hourly cost for process equipment using methods and data from tollers. (Excel-only in v1.0)", + "homepageURL": "https://catcost.chemcatbio.org", + "laborHours": 0.0, + "languages": [], + "name": "CatCost\u2122 (Catalyst Cost Estimation Tool) [SWR-18-74]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://catcost.chemcatbio.org/disclaimer", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://catcost.chemcatbio.org", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-10-25", + "metadataLastUpdated": "2019-10-25" + }, + "description": "Adiak is a computer science data management interface tool for collecting metadata about an application's runs and disseminating it to tools that subscribe to this data. Examples of this metadata could be what user is running an application, what systems it runs on, or application provided name/value pairs. \n\nAdiak's capabilities include automated reading of system-level metadata, and a generic type system for applications to register their own name/value metadata. \n\nAdiak is currently designed to provide a standard interface that can be integrated with MPI-based applications that run on high performance computing systems.\n\nExample tools that use Adiak metadata include performance analysis tools and workflow tools. By allowing the application to specify metadata to Adiak, which then disseminates it to tools, application developers do not have to write to tool-specific interfaces.\n\n", + "laborHours": 1170.4, + "languages": [], + "name": "Adiak", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/adiak", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-10-25", + "metadataLastUpdated": "2019-10-25" + }, + "description": "Web-based Interface for the N-Dimensional Data Analysis and Visualization System.", + "laborHours": 10913.6, + "languages": [ + "Python" + ], + "name": "NDDAV", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/NDDAV", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-29", + "metadataLastUpdated": "2019-10-29" + }, + "description": "Hardware simulation is an indispensable tool for designing chips as well as researching future architectures. Unfortunately, the slow rate of simulation can often bottleneck the design process, as designers must wait to see the results of a simulation before changing the design and starting a new simulation. The Essential Signal Simulation Enabled by Netlist Transforms (ESSENT) is a tool designed to accelerate hardware simulations. ESSENT takes in a design, uses graph algorithms to identify opportunities for conditional execution, and generates a simulator that leverages these opportunities. The generated simulator produces the exact same simulation results that would be returned by an unoptimized simulator, but in substantially less time. For input, ESSENT takes in designs formatted in FIRRTL (an open format).", + "laborHours": 1717.6, + "languages": [], + "name": "Essential Signal Simulation Enabled by Netlist Transforms (ESSENT) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ucsc-vama/essent", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-29", + "metadataLastUpdated": "2019-10-29" + }, + "description": "This package is developed as a backend for multi-layer and multi-time domain controller. One example are controller based on [Model Predictive Control] (MPC) where different modules with different time constants have to be coordinated to allow optimal control. In a simple example, the Weather Forecast must be acquired and processed, the MPC is computed, and finally the control is applied. All these modules typically run on the same time step (Time step: 5 minutes), but are different instances within the framework. The framework allows parallelization using the `multiprocessing` module. However, another real-time controller (Time step: 1 second) must be applied to react on instant system disturbances beyond the MPC time step. Last, a supervisory MPC controller (Time step: 1 hour) might be added to ensure global optimality.", + "laborHours": 501.6, + "languages": [], + "name": "Framework for Multi Layer Control in Python (FMLC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/FMLC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ellisjc@ornl.gov" + }, + "date": { + "created": "2019-10-30", + "metadataLastUpdated": "2019-10-30" + }, + "description": "P Finder is a GUI software application for the fast identification of the rnpB gene in prokaryote genomes", + "laborHours": 0.0, + "languages": [], + "name": "JChristopherEllis/P-Finder", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JChristopherEllis/P-Finder", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-30", + "metadataLastUpdated": "2019-10-30" + }, + "description": "Pairwise sequence alignment is one of the most compute-intense challenges for the analysis of genomics data and it can account for more than 90% of the runtime depending on the application. Despite the effort to reduce the computational cost introducing heuristics such as banded and x-drop alignment, the performance of state-of-the-art software is often unsatisfactory for long sequences. Recent advances in single-molecule sequencing technologies keep increasing the length of the sequences to align at the cost of higher error rates b ranging from 5% to 15% b, emphasizing the need for fast and accurate software.\n\nOur long-read alignment software, named Xavier, computes high-performance x-drop adaptive banded pairwise alignment exploiting instruction-level parallelism via Single-Instruction-Multiple-Data (SIMD) operations. Xavier uses a narrow bandwidth that appreciably improves performance reducing the search space for the optimal alignment. In our experiment, the adaptive mechanism enables Xavier to find the optimal alignment between related sequences even when the error rate is as high as 50%. Xavier achieves speed-up up to 5X over competitor software when enabling the x-drop termination and up to 415X when disabling it, with negligible accuracy loss.", + "laborHours": 456.0, + "languages": [], + "name": "Xavier: High-Performance X-Drop Adaptive Banded Pairwise Alignment (Xavier) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/giuliaguidi/xavier", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-30", + "metadataLastUpdated": "2019-10-30" + }, + "description": "This is a library of 27 abnormal (electrical) grid events recorded at LBNL campus. Each event lasts for about 1 second. The library is published for other researchers to develop control algorithms.", + "laborHours": 45.6, + "languages": [], + "name": "PMU event library v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/pmu_event_library", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-30", + "metadataLastUpdated": "2019-10-30" + }, + "description": "This package includes a variety of simulation models for distributed energy resources (i.e. photovoltacis, storage, inverter, controls, grid) in the language Modelica.", + "laborHours": 15.2, + "languages": [], + "name": "Smart Control of Distributed Energy Resources (SCooDER) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/SCooDER", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2019-10-31" + }, + "description": "This software implements the first base caller for nanopore data that calls bases directly from raw data. The basecRAWller algorithm has two major advantages over current nanopore base calling software: (1) streaming base calling and (2) base calling from information rich raw signal. The ability to perform truly streaming base calling as signal is received from the sequencer can be very powerful as this is one of the major advantages of this technology as compared to other sequencing technologies. As such enabling as much streaming potential as possible will be incredibly important as this technology continues to become more widely applied in biosciences. All other base callers currently employ the Viterbi algorithm which requires the whole sequence to employ the complete base calling procedure and thus precludes a natural streaming base calling procedure. The other major advantage of the basecRAWller algorithm is the prediction of bases from raw signal which contains much richer information than the segmented chunks that current algorithms employ. This leads to the potential for much more accurate base calls which would make this technology much more valuable to all of the growing user base for this technology.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1976.0, + "languages": [], + "name": "basecRAWller v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2020-01-20" + }, + "description": "Chordly is a JavaScript library that lets you detect and act upon user keyboard input. This is accomplished by wiring Chordly up to listen for key sequences, known as chords, entered by a user.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2019-11084 M\n", + "laborHours": 1185.6, + "languages": [ + "JavaScript" + ], + "name": "Chordly", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Chordly", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2024-06-18" + }, + "description": "DefectSegNet for semantic segmentation of defects in Steels\nThe first and most important step of automating defect analysis is perceptual defect identification. In terms of digital image processing, semantic segmentation best emulates human recognition of defect features \u2013 it identifies the crystallographic defects and where they are located in a TEM micrograph. We solved this problem by developing DefectSegNet, a novel hybrid CNN algorithm for robust and automated semantic segmentation of three crystallographic defects, including line dislocations, precipitates and voids, that are commonly observed in structural metals and alloys.", + "laborHours": 1033.6, + "languages": [], + "name": "DefectSegNet", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ZEMG-UCONN/DefectSegNet", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2023-05-08" + }, + "description": "This is a package for easy application of multiple machine learning models to a single problem, and comparison via various metrics. For a pretty detailed description of the models that are available in the tool, and a quite detailed description of the metrics that it pumps out, see the paper, \"A Machine Learning Decision Support Tool for Travel Demand Modeling\". Accessible at: https://github.com/NREL/TEAM-TDM/blob/master/paper/team_tdm.pdf\n", + "laborHours": 4119.2, + "languages": [ + "Perl", + "Jupyter Notebook", + "Tex", + "Python" + ], + "name": "TEAM-TDM: A Tool for Evaluating an Array of Machine Learning Travel Demand Models [SWR-18-64]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/TEAM-TDM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2019-11-04" + }, + "description": "The Industry Energy Tool (IET) is an open-source calculator tool designed for projecting energy and emissions impacts of industrial sector energy efficiency, material efficiency, and fuel switching. Projections are available at the county and Census Region levels. The IET is based on a detailed county-level energy data set for agriculture, mining, construction, and manufacturing industries. End use energy disaggregation is provided for manufacturing industries, and some agriculture and mining industries. Process temperature disaggregation is provided for most manufacturing industries.", + "laborHours": 2416.8, + "languages": [], + "name": "Industry Energy Tool", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Industry-Energy-Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-11-06", + "metadataLastUpdated": "2019-11-06" + }, + "description": "Dockerfiles for quantum simulators", + "laborHours": 152.0, + "languages": [ + "make", + "dockerfile" + ], + "name": "fermilab-qc/docker-quantum", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fermilab-qc/docker-quantum", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-07", + "metadataLastUpdated": "2020-11-06" + }, + "description": "VOLTTRON\u2122 Distributed Control System Platform\nVersion 7.0\nVOLTTRON\u2122 is an agent execution platform providing services to its agents that allow them to easily communicate with physical devices and other resources.\nVOLTTRON\u2122 delivers an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls. It enables mobile and stationary software agents to perform information gathering, processing, and control actions. VOLTTRON\u2122 can independently manage a wide range of applications, such as HVAC systems, electric vehicles, distributed energy or entire building loads, leading to improved operational efficiency.", + "laborHours": 0.0, + "languages": [], + "name": "VOLTTRON Version 7.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron/releases/tag/7.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "7.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-11-11", + "metadataLastUpdated": "2019-11-11" + }, + "description": "This project simplifies the registration and authentication of a Gitlab runner. \n\nThis allows administrators to create a set of static configuration files from which this script will build the appropriate, host-specific config needed to communicate with and accept jobs from Gitlab.", + "laborHours": 182.4, + "languages": [], + "name": "Gitlab Runner Auth", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/gitlab-runner-auth", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-11-12", + "metadataLastUpdated": "2019-11-12" + }, + "description": "User-defined elements in ANSYS enable programming of the finite element method to simulate the unique behavior of superconducting magnets. A set of electromagnetic and thermal user elements incorporate both quench and interfilament coupling current (IFCC) effects in a consistent manner, allowing for simulation of strongly coupled, multiphysics behavior typical of superconducting devices.", + "laborHours": 6870.4, + "languages": [], + "name": "SCPACK vR1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lnbrouwer/ANSYS_UEL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-11-13", + "metadataLastUpdated": "2019-11-13" + }, + "description": "Pairwise sequence alignment is one of the most computationally intensive kernels in genomic data analysis, accounting for more than 90% of the run time for key bioinformatics applications. This method is particularly expensive for third-generation sequences due to the high computational expense of analyzing these long read lengths (1Kb-1Mb). Given the quadratic overhead of exact pairwise algorithms such as Smith-Waterman, for long alignments, the community primarily relies on approximate algorithms that search only for high-quality alignments and stop early when one is not found. In this work, we present the first GPU optimization of the popular X-drop alignment algorithm, named LOGAN. Results show that our high-performance multi-GPU LOGAN implementation achieves up to 181.6 GCUPS and speed-ups up to 6.6x and 30.7x using 1 and 6 NVIDIA Tesla V100, respectively, over the state-of-the-art software running on two IBM Power9 processors using 168 threads, with equivalent accuracy. We also demonstrate a 2.3x LOGAN speed-up versus ksw2, a state-of-art vectorized algorithm for sequence alignment implemented in minimap2. To highlight the impact of our work on a real-world application, we couple the LOGAN aligner with a many-to-many long-read alignment software called BELLA, and demonstrate that our implementation improves the overall BELLA runtime by up to 10.6x. Finally, we adapt the Roofline model for our optimized kernel and demonstrate that our implementation is near-optimal on the NVIDIA Tesla V100s.", + "laborHours": 133851.2, + "languages": [], + "name": "LOGAN: High-Performance X-Drop Pairwise Alignment on GPU (LOGAN) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/albertozeni/LOGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-11-13", + "metadataLastUpdated": "2019-11-13" + }, + "description": "Radiance matrix algebraic methods enable efficient annual daylight simulation while preserving accuracy. The five sub-methods, 2 to 6 phase methods, enable scene components parameterization and separation of direct and diffuse flux transfer based on the user's need. However, the burden is on the user to figure out the which method, matrix basis, matrix resolution, simulation parameters to use to achieve the desired efficiency and accuracy to the end application. Several utility programs and an executive program (in-progress) were created to lower the entry barrier and to reduce human error when executing the simulation. This suite of programs should also reduce the burden of adopting Radiance matrix methods for third party software.", + "laborHours": 729.6, + "languages": [], + "name": "Framework for Radiance Simulation Control (Frads) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/frads", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-11-13", + "metadataLastUpdated": "2019-11-13" + }, + "description": "A plugin for the Grafana monitoring/dashboarding web application that provides \nan interface to data provided by GraphQL APIs, such as the \"Lens\" API service\nthat SCD maintains for batch job monitoring data.", + "laborHours": 1520.0, + "languages": [ + "JavaScript", + "TypeScript" + ], + "name": "fifemon-graphql-datasource", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fifemon/graphql-datasource", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Transparent Asynchronous Zero-copy Remote I/O (TAZeR) is a framework built to facilitate grid computing by easing the memory movement and management across geographically separated computing resources. TAZeR employs a multiclient/\nmulti-server paradigm where data is stored at on a remote server. Users preload an interposing library which upon application start-up, stands up an ephemeral lightweight client. The client captures POSIX I/O calls to TAZeR meta-files which contains the IP address/port of the remote server, the location of the file on remote server, and additional meta-data.\nThe client connects to the server using this information and begins downloading the file in parts optionally compressing the data.", + "laborHours": 8648.8, + "languages": [], + "name": "Transparent Asynchronous Zero-copy Remote I/O (TAZeR)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/tazer", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is an improved system for detecting a nuclear criticality event at RPL (325) building, named the Mark III Nuclear Criticality Detector (NCD), replacing the 40 year old Mark II. The materials are primarily schematic diagrams and other technical information that is of interest to a commercial manufacturer of similar equipment.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Nuclear Criticality Detector Mark-III", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-11-14", + "metadataLastUpdated": "2019-11-14" + }, + "description": "The software SAFIRE implements a fault injection tool to evaluate the impact of soft errors on parallel, multi-threaded applications.\n\nIt implements instruction-level fault models that emulate soft errors by flipping bits in the register operands of executed machine instructions.\n\nSAFIRE is based on the LLVM compiler and utilizes novel techniques to optimize instruction instrumentation and fault injection. \n\nBy detailed measurements, SAFIRE is multiple times faster than other state-of-the-art fault injection techniques, while having the same accuracy.", + "laborHours": 1362148.0, + "languages": [], + "name": "SAFIRE : Scalable and Accurate Fault Injection for Parallel Multi-threaded Applications", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/safire", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "v1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Software for detecting matching subgraphs within a temporal network dataset, such that the chronology ordering of the edges is identical to the query graph. This can be used to find patterns of behavior in temporal graph data that may be of interest for a particular use case. The resulting matching nodes, edges and subgraphs are then output for the user, including the number of times a particular node was found to be associated with a temporal subgraph match. The number of times a node is associated with a match may indicate that node is more noteworthy for the given use case.", + "laborHours": 2249.6, + "languages": [], + "name": "Temporal Subgraph Isomorphism Detector", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/temporal_subgraph_isomorphism", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "julia.dark@cfdrc.com" + }, + "date": { + "created": "2019-11-18", + "metadataLastUpdated": "2019-11-18" + }, + "description": "Peridot is a mesh free state-based peridynamics simulation developed using the Kokkos library for parallel execution. ", + "homepageURL": "https://www.cfd-research.com/products/peridot", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Peridot", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.cfd-research.com/products/peridot", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "version": "0.1.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python package to be used when working with the DDAO method of visualizing phosphatase activity in the rhizosphere. Includes a module with functions that generate figures for analysis of phosphatase levels in images of soil and root based on pixel intensity. These functions can be used on images with a single root or multiple roots. Figures include distance maps to show how phosphatase levels change as you move away from the root and along the roots themselves, line plots to show average phosphatase levels moving down the root and the soil surrounding the root, 2D histograms to show how phosphatase levels change moving away from the root, and 1D histograms to show overall differences in phosphatase distribution depending on whether a root was grown next to a phosphorus source or not.", + "laborHours": 273.6, + "languages": [], + "name": "pnnl/rhizo_phosph", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/rhizo_phosph", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-11-19", + "metadataLastUpdated": "2019-11-19" + }, + "description": "This software is to implement real-time energy dispatch for distributed energy resources such as distributed PV, using distributed control algorithm that NREL has developed. The software is developed using Python and is available as open-source. ", + "laborHours": 957.6, + "languages": [ + "Python" + ], + "name": "Real-Time Distributed Energy Resource Energy Dispatch Using Distributed Control", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DER-Dispatch", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-11-20", + "metadataLastUpdated": "2019-11-20" + }, + "description": "There are numerous options for renewable energy systems development. Location, size, type of system, and a number of other criteria need to be considered. The objective of this program is to determine the optimal size (capacity, Kilowatt (kW)) of a renewable energy generator, based on minimizing life cycle cost (LCC). The reason for developing such a program is driven by three major issues. First, the need to evaluate a very large number (tens of thousands) of project opportunity sites. Next, the need for data transfer efficiency and computational efficiency in on-line and mobile applications. And lastly, to increase the accuracy of screening studies, which are the earliest indicators of project opportunities. Many existing programs require the user to enter the size (kW) of the renewable energy system in order to start calculations. \n \nHowever, there are many factors that affect what the size should be including: renewable energy resources, utility rates, initial and maintenance costs, and economic parameters. NREL scientists have developed an algorithm that addresses the previous three major issues. Lifecycle cost is calculated based on: the sum of initial cost, plus the present value of operations and maintenance costs, costs involved with purchasing power from the utility company, and revenue involved with the sale of excess electricity back to the utility.\n\nThe algorithm computes the derivative of an equation for LCC as a function of the size of the renewable energy generator (P), then sets the derivative equal to zero (dLCC/dP=0), and solves for the value of (P) that minimizes life cycle cost. Once the size (P) has been determined, other project details may be calculated. This algorithm develops a closed-form solution for the optimal size of a renewable energy generator. Having a closed-form solution avoids problems of scale and speed that can be encountered with optimization algorithms. Incentives that affect initial cost or provide a payment for energy production are also represented.\n\nBecause the algorithm was built in terms of analytics (calculus) and not numeric methods, it can be easily implemented in any platform such as spreadsheets or mobile computing applications. The program is very accurate as long as the simplifying assumptions in the derivation apply: constant load (during daylight hours for PV, all hours for wind); a single rate for all power purchased from the utility; and a single rate for all power sold back to the utility. The program calculates energy saved on-site and energy sold back to the utility using a duration curve based on capacity factor. Data for the calculation is available on-line at www.nrel.gov/gis.", + "homepageURL": "https://www.labpartnering.org/p/lab-technologies/4d681f46-9778-4024-877c-6633a9617a0b", + "laborHours": 0.0, + "languages": [], + "name": "dlCC Optimization", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.labpartnering.org/p/lab-technologies/4d681f46-9778-4024-877c-6633a9617a0b", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.labpartnering.org/p/lab-technologies/4d681f46-9778-4024-877c-6633a9617a0b", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-11-25", + "metadataLastUpdated": "2019-11-25" + }, + "description": "The Modelica IBPSA MPC Library is a free open-source library with basic models that codify best practices for the implementation of models to be used in Nonlinear Model Predictive Control of building and community energy systems.\n\nThe development of the Modelica IBPSA MPC Library is organized through the IBPSA Project 1 (https://ibpsa.github.io/project1) of the International Building Performance Simulation Association (IBPSA).", + "laborHours": 15.2, + "languages": [], + "name": "Modelica IBPSA MPC Library v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ibpsa/modelica-ibpsa-mpc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Flow routing using a hexagonal grid.", + "laborHours": 2158.4, + "languages": [], + "name": "pnnl/hexwatershed", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/hexwatershed", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-12-02", + "metadataLastUpdated": "2021-09-07" + }, + "description": "HYbrid Battery Robust Energy Design (HYBRED) Tool is formulated as a mixed integer linear programming (MILP) model where discrete decisions are taken as of size of battery per type, choice of service each battery type can provide at a specific time (grid or dynamic regulatory service), and times of charging and discharging each battery. The potential charging sources are grid and renewables while the end users are commercial and industrial building loads, and electrical vehicles. The objective of the model is to maximize the batteries profit or in other words, to minimize the total battery cost. Major inputs to the model are solar irradiation profiles, time of use tariffs, buildings loads, dynamic regulatory service signal, various battery parameters, etc. Major outputs of the tool include battery sizes, costs and revenues, temporal profiles, and duration curves.", + "homepageURL": "https://www.labpartnering.org/p/lab-technologies/02761bf5-e886-43b9-b506-5be4b0416b99", + "laborHours": 0.0, + "languages": [], + "name": "HYBRED (HYbrid Battery Robust Energy Design Tool)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.labpartnering.org/p/lab-technologies/02761bf5-e886-43b9-b506-5be4b0416b99", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.labpartnering.org/p/lab-technologies/02761bf5-e886-43b9-b506-5be4b0416b99", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-02", + "metadataLastUpdated": "2019-12-02" + }, + "description": "A re-implementation of Quantile Kriging.\n\nQuantile Kriging was described by Matthew Plumlee & Rui Tuo in their 2014 paper \"Building Accurate Emulators for Stochastic Simulations via Quantile Kriging.\" \n\nWith computational savings when dealing with replication from the recent paper \"Practical heteroskedastic Gaussian process modeling for large simulation experiments\u201d, it is now possible to apply Quantile Kriging to a wider class of problems. \n\nIn addition to fitting the model, other useful tools are provided such as the ability to automatically perform leave-one-out cross validation.", + "laborHours": 288.8, + "languages": [], + "name": "Quantile Kriging R Package", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/quantkriging", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-02", + "metadataLastUpdated": "2019-12-02" + }, + "description": "Simplexdesign is a small collection of tools for the design of statistical experiments on Agent \nBased Models.\n\nIt includes a coordinate exchange algorithm for homogeneous agents, and more generally any simplex. \n\nThere is also an optimization algorithm for the case with multiple classes of homogeneous agents.", + "laborHours": 136.8, + "languages": [], + "name": "Simplex Design for Stochastic Simulations and Agent Based Models", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/simplexdesign", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-02", + "metadataLastUpdated": "2019-12-02" + }, + "description": "Python package for a systems approach to blur estimation and reduction", + "laborHours": 440.8, + "languages": [], + "name": "Systems Approach to Blur Estimation and Removal", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sabersw/pysaber", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-04", + "metadataLastUpdated": "2019-12-04" + }, + "description": "The National Energy Research Scientific Computing Center (NERSC) is the primary scientific computing facility for the Office of Science in the U.S. Department of Energy. NERSC houses top-ranked Cray supercomputers, and our staff works very closely with on-site Cray engineers, submitting 75 Cray cases per month on average. Until recently, submitting a Cray case was only possible by phone or email, and all subsequent updates were delivered manually. This process led to delays, errors during manual data entry, and greatly increased incident processing and resolution time. In 2018, NERSC deployed an API-based bidirectional integration that allowed to submit and update Cray cases directly from our Incident Management platform, thus streamlining our 24x7 operations and enhancing communication between our engineering teams. This solution is applicable to any Incident Management platform.", + "laborHours": 5532.8, + "languages": [], + "name": "ServiceNow/CrayPort Integration v2.1.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/crayport/crayport-app-code.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "oleg@dynamite.ai" + }, + "date": { + "created": "2019-12-04", + "metadataLastUpdated": "2021-12-02" + }, + "description": "DynamiteNSM is a free Network Security Monitor (NSM), built on top of several leading, enterprise-grade technologies. The tool provides network and cybersecurity operators with holistic insights into their networks while giving them the ability to deep-dive into lower-level activities. The solution presents powerful dashboards, giving comprehensive view into performance and threat-based metrics. Dynamite-NSM can be easily deployed in different environments including high-speed data centers, small-to-large enterprises, IoT & industrial networks, and even at home.\n\nDynamite-NSM handles massive volumes of network traffic through scalable ingestion and optimized network sensors. The solution includes two key components: the agent and the monitor. The agent analyzes and forwards network events, while the monitor processes incoming events and displays analytic information. The monitor component builds upon the OpenSearch stack and is coupled with network packet inspection by Zeek and Suricata. \n\nDynamite-NSM is designed to be deployed very quickly with minimal configuration. Unlike many other tools, it can be installed and managed with a standalone command-line utility. The system is inherently passive without disruption to the network. There is no need to install agents on every computer, perform network scans, or directly interact with network assets.", + "laborHours": 4620.8, + "languages": [], + "name": "DynamiteNSM", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DynamiteAI/dynamite-nsm", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-05", + "metadataLastUpdated": "2020-02-05" + }, + "description": "A central goal in experimental science is to explore and understand the composition-processing-structure-property relations of materials in their associated multi-dimensional parameter spaces, These parameter spaces can be thought of as the set of all conceivable combinations of the parameters affecting an experiment, including synthesis and processing conditions, material composition, and environmental conditions during the experiment. gpCAM analyzes data to steer the experiment. The software tool creates a surrogate model and associated uncertainties by performing a Gaussian process regression. Mathematical function optimization is then used to find measurements of maximum value.", + "laborHours": 1869.6, + "languages": [], + "name": "gpCAM v3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/MarcusMichaelNoack/gpcamv3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-05", + "metadataLastUpdated": "2019-12-05" + }, + "description": "The Localization and Mapping Platform (LAMP) software fuses radiation and contextual data to produce 3-D maps that locate and identify gamma-ray emitting sources in complex environments. It enables data collection, fusion, and processing onboard the LAMP system in handheld configurations, and enables near-real-time 3-D mapping from onboard an unmanned aerial system (UAS). This software enables a real-time 3-D gamma-ray mapping capability that is not available commercially. This software disclosure is for a new simultaneous gamma-ray and neutron mapping software update to the original LAMP software.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1124.8, + "languages": [], + "name": "Neutron Gamma LAMP Software version 1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-06", + "metadataLastUpdated": "2019-12-06" + }, + "description": "pyPicFusion is a standalone fusion reaction code that takes arbitrarily weighted macro-particles representing fusion reactants and generates fusion products. \n\nThe code takes into account the fusion cross-section and kinematics of the reaction to produce weighted fusion products with given velocities/energies in the laboratory frame.", + "laborHours": 364.8, + "languages": [ + "Python" + ], + "name": "pyPICfusion", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pyPICfusion", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-11", + "metadataLastUpdated": "2019-12-11" + }, + "description": "This repository contains code for the computational framework to build ML models for drug discovery\npurposes. \n\nOur end-to-end pipeline extracts features from model-ready datasets and trains and saves the model to our model zoo or to disk.\n\nOur pipeline generates a variety of molecular features and both shallow and deep ML models.\n\nThe HPC-specific module we have developed conducts efficient parallelized search of the model hyperparameter space and reports the best-performing hyperparameters for each of these feature/model combinations.", + "laborHours": 34656.0, + "languages": [], + "name": "Atom Modeling PipeLine", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ATOMconsortium/AMPL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-11", + "metadataLastUpdated": "2019-12-11" + }, + "description": "ompparser is a standalone and unified OpenMP parser, which is motivated by the facts that:\n\n1) The differences in terms of syntax and semantics of OpenMP constructs between C/C++ and Fortran\nare minor.\n\n2) Current OpenMP compilers often develop their own parsers, which represent redundant work.\n\nThe features of ompparser include:\n\n1) ompparser can be used standalone for static source code analysis, e.g. tools for semantics checking or similarity analysis between C/C++ and Fortran programs\n\n2) omppaser can be integrated into an OpenMP compiler implementation can reduce the development efforts, and there is no need to create and maintain two separate parsers for C/C++ and Fortran.\n\n3) ompparser provides a complete reference OpenMP grammar in the Backus-Naur Form that formally describes all the latest OpenMP language constructs.\n\nThis will help users understand the rules and restriction of the OpenMP standard, which no longer contains a reference grammar in its recent versions.\n", + "laborHours": 3769.6, + "languages": [], + "name": "Ompparser", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/passlab/ompparser", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-12-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Locating Luna is a STEM Education virtual reality game for grade 6-12 students. Users search for a lost dog in a dark swamp, calling out to the dog and lighting torches as they search. The app collects data on all user actions which are saved in a file for download. Teachers then have students use various tools to represent and analyze their data. This provides a common interactive experience for teachers to use in addressing computer science learning standards. Locations of key points of interest in the app (such as the dog) are randomly generated when the game is restarted\u037e however, replay without a restart of the game allows users to try the same scenario again with a different search strategy. This allows users to compare strategies using data. A teacher's guide supports use by teachers in the classroom.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Locating Luna", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-12-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Analysis and reporting for water and irrigation usage\nPNNL developed the Water Balance Tool, which provides a method to determine potable water consumption, by end-use, of a campus. A water balance compares the total water supply to the volume of water consumed by water-using equipment and applications. The output of the tool provides the estimated potable water consumption by major end-use and compares the sum of the end-uses to the total potable water supplied to the campus.", + "laborHours": 6824.8, + "languages": [], + "name": "pnnl/femp-water-balance", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/femp-water-balance", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lyon@fnal.gov" + }, + "date": { + "created": "2019-12-13", + "metadataLastUpdated": "2019-12-13" + }, + "description": "Linux style development, like what we do for particle physics experiments at Fermilab, is becoming more difficult on the Mac. Apple is moving to its own style of development that is often incompatible. For example,\n\n* System Integrity Protection (SIP) prevents using DYLD_LIBRARY_PATH, breaking the mechanism used by our development environment system, ups.\n\n* Mac headers and system libraries are not always compatible with those on Linux, necessitating platform dependent code.\n\n* XCode is more focused on Swift, Objective-C, and Mac or iOS-style development. XCode does not understand CMake builds natively.\n\nThe differences that Mac and XCode introduce are difficult to manage and many experiments have stopped making Mac builds. Despite these problems, Mac laptops remain powerful machines and the MacOS environment is advantageous in many other areas. Therefore, mitigating the problems with Linux style development is motivated.\n\nThis package contains a configuration for docker containers along with instructions for integrating with the Mac that make for an effective and efficient development platform for Linux style development of physics code. Instructions for using CLion for C++ development in this environment are given in the documentation for running CLion within the linux container or from the Mac host.\n\nNote that the containers and techniques here may also work on Windows. You will have to adapt the instructions for that platform.", + "laborHours": 410.4, + "languages": [ + "Bash", + "docker" + ], + "name": "devenv", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lyon-fnal/devenv", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-16", + "metadataLastUpdated": "2019-12-16" + }, + "description": "The software developed is a library for the Modelica language. The library includes different extremum seeking control algorithms and examples of possible usecases. It is also intended to export the models as so called Functional Mock-up Units, which are models supported by any kind of software which supports the Functional Mock-up Interface standard.", + "laborHours": 15.2, + "languages": [], + "name": "Extremum Seeking Library (ESL) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/ESL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2023-05-08" + }, + "description": "Persistent model serves as the baseline in the intra-hour forecasting of solar radiation due to the extensive computing efforts from the numerical weather prediction (NWP) models and the lack of surface observations in cloud as well as other atmospheric properties. The smart persistent model actively updates the extraterrestrial solar radiation with time and is an important improvement from the persistent model while the cloud conditions are assumed unchanged by giving constant clear-sky indexes. We developed a Physics-based Smart Persistent model for Intra-hour solar forecasting (PSPI) to further improve the accuracy of the smart persistent model. We used a cloud retrieval technique developed by Xie and Liu (2013) to estimate cloudy fraction and cloud albedo using surface-based observations of solar radiation. The solar radiation in future time steps is accurately given by actively computing individual cloud albedo related to the future solar position. Our evaluation studies indicated that the PSPI model significantly increased the accuracy in the short-term forecast of solar radiation, especially in thin cloud conditions or those covered by broken clouds.", + "laborHours": 410.4, + "languages": [ + "Python", + "Dockerfile" + ], + "name": "Solar-Forecast GridAPPS-D Application [SWR-18-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Solar-Forecasting", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2024-09-17" + }, + "description": "The PyEPANET package is a set of commands for the Python programming language that are built to wrap the EPANET toolkit library commands, without requiring the end user to program using the ctypes package. This package does not contain the \nEPANET code, nor does it implement the functions within the EPANET software, and it requires the separately downloaded or compiled EPANET2 toolkit dynamic library (epanet.dll, libepanet.so, or epanet.dylib) and/or the EPANET-MSX dynamic library in order to function. \n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 147744.0, + "languages": [ + "Python", + "C++", + "C" + ], + "name": "PyEPANET v. 0.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PyEPANET", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2024-06-11" + }, + "description": "Program uses linear, nodal finite elements to solve the space-fractional Helmholtz equation over segments of an arbitrary 3D graph.SAND2019-11082 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 1124.8, + "languages": [ + "Fortran" + ], + "name": "FRACHELM v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-04" + }, + "description": "PyApprox provides flexible and efficient tools for high-dimensional approximation and uncertainty quantification. PyApprox implements methods addressing various issues surrounding high-dimensional parameter spaces and limited evaluations of expensive simulation models with the goal of facilitating simulation-aided knowledge discovery, prediction and design. Tools are provided for: (i) building surrogates using polynomial chaos expansions using least squares, compressive sensing and interpolation; (ii) sparse grid interpolation and quadrature; (iii) low-rank tensor-decompositions; (iv) multi-fidelity approximation and sampling; (v) large-scale Bayesian inference; (vi) numerical solvers for canonical ordinary and partial differential equations useful for demonstration purposes; compressive sensing solvers (vii) and (viii) visualization. The code is intended to as a python toolbox but provides c++ code with Python interfaces to computationally expensive algorithms to increase performance. SANDS2019-5458 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. \n", + "laborHours": 48807.2, + "languages": [ + "C++", + "Python" + ], + "name": "Python Approximation Toolbox (PyApprox) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/pyapprox/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyapprox", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-05" + }, + "description": "This software examines raw Illumina sequence data files for cas genes and CRISPR arrays, either to be used as evidence of genome editing or for basic analysis of bacterial genomes. It translates sequencing reads into peptide sequences, and runs these against sensitive hidden Markov models for numerous Cas protein families. The set of hit read seeds is then expanded leftward and rightward by sequence matching to remaining reads, and after multiple cycles, this small fraction of the original reads is assembled to produce Cas operons. A separate mode using known CRISPR repeat sequences for a genus are used to identify CRISPR arrays that may be in genomic locations that are isolated from Cas genes.SAND2019-11770 M\n\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.\n", + "laborHours": 410.4, + "languages": [ + "Perl", + "Python" + ], + "name": "CasCollect: Detecting cas genes and CRISPR arrays in raw sequence data v1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CasCollect", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2024-08-07" + }, + "description": "A clear way to increase current capabilities for seismic nuclear explosion monitoring is to supplement the global International Monitoring System (IMS) network with openly available stations. The quality of openly available data is typically much lower than that of the IMS, given the wide variety of experimental goals and deployment conditions. Incorporating additional stations without properly identifying and mitigating data quality problems can actually degrade overall monitoring capabilities. Towards that objective, Pycheron, a python-based library for seismic data quality control (QC) was developed. Pycheron began as a translation of the Incorporated Research Institutions for Seismology (IRIS) Modular Utility for STAtistical kNowledge Gathering (MUSTANG) package (written in R) into Python, but has grown into a stand-alone package that includes significant additional functionality. Pycheron is intended to be implemented at the beginning of the data processing pipeline. The objectives of the library are to: automatically assess data quality and instrumentation health; maintain the highest quality of data possible; identify specific and key problems; alert downstream processing algorithms to any degradation in quality; improve our ability to process orders of magnitudes more data; and, serve as a basic service that all data processing within our program builds upon. Pycheron calculates metrics characterizing quality over time as well as creating QC masks to identify each interval with a QC problem. SAND2019-11607 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 34124.0, + "languages": [ + "Python", + "CSS", + "Fortran" + ], + "name": "Pycheron", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pycheron", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2019-12-19" + }, + "description": "A library of utility classes for computer vision. Contains implementations of various well-known image processing techniques, such as interest point operators and region descriptors. Includes interfaces to various libraries for image and video I/O, as well as an interface to LAPACK/BLAS. FL was developed at the University of Illinois, Urbana-Champaign (UIUC) and released under an open source license. Version 1.2 was a maintenance release provided by SNL under the LGPL license. Version 1.3 is a maintenance release, containing the following changes: - Improved image format handling. Now handles strided and planar memory layouts and a wider range of pixel formats. - Improved image file I/O, including better support for metadata, a wider range of stored pixel types, and a couple of new file formats. - Improvements to DOG and SIFT, and efficiency improvements in low-level convolution. - Improvements to networking, including a generic TCP listener. - Various improvements to numerical processing. The HISTORY file included in the distribution contains a more detailed description of the changes.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "FL V1.4", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.4" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-04" + }, + "description": "Deep learning has been applied with great success to the segmentation of 3D X-Ray Computed Tomography (CT) scans. Establishing the credibility of these segmentations requires uncertainty quantification (UQ) to identify problem areas. Bayesian neural networks (BNNs), which use variational inference to learn the posterior distribution of the neural network weights, have been proposed to incorporate UQ into deep learning models. This software is an implementation of a novel 3D Bayesian convolutional neural network (BCNN) that provides accurate binary segmentations and uncertainty maps for 3D volumes. In particular, the uncertainty maps generated by this BCNN capture continuity and visual gradients, making them interpretable as confidence intervals for segmentation usable in numerical simulations. SAND2019-12927 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 516.8, + "languages": [ + "Python" + ], + "name": "Bayesian Segmentation (BCNN) v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/bcnn", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-05" + }, + "description": "An entry to the IDASH PRIVACY & SECURITY WORKSHOP 2019 - secure genome analysis competition, Track I: Distributed Gene-Drug Interaction Data Sharing based on Blockchain and Smart Contracts. The entire codebase is comprised of a single solidity file, GeneDrugRepo.sol. Solidity is a smart contract language for the Ethereum blockchain platform. SAND2019-13419 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 106.4, + "languages": [ + "Solidity" + ], + "name": "GeneDrugRepo.sol", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/iDASH2019GeneDrug", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-05" + }, + "description": "Nalu-Wind is derived from Nalu-CFD (for which Sandia has an existing copyright assertion). Nalu-Wind is specific to the wind energy simulation space. SAND2019-10379 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 134398.4, + "languages": [], + "name": "Nalu-Wind v.1.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exawind/nalu-wind", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-01-20" + }, + "description": "PAO supports the formulation and analysis of mathematical models for complex optimization applications. This capability is commonly associated with algebraic modeling languages (AMLs), which support the description and analysis of mathematical models with a high-level language. PAO is derived from the Pyomo subpackage pyomo.bilevel, which has been deprecated. PAO supports the formulation and solution of optimization models that explicitly represent adversarial behavior. This includes variances of bilevel programming, including methods that represent challenging problems with discrete decisions and uncertain model parameters. SAND2019-14490 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PAO", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2019-12-19" + }, + "description": "fpzip is a C/C++ library for lossless and lossy compression of 1D, 2D, and 3D single- and double-precision floating-point arrays. \n\nAlthough designed for lossless compression, the user may optionally request lossy compression by specifying how many bits of precision per floating-point value to retain.\n\nFpzip supports streaming compression and decompression with either a memory buffer or a file as source or destination. \n\nIn addition to a simple C interface, fpzip comes with an executable for (de)compressing binary files.", + "laborHours": 1322.4, + "languages": [], + "name": "FPZIP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/fpzip", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.2.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-07-30" + }, + "description": "MPI library that supports serializing (and check-pointing) its MPI Stages is a communication library that allows nodes and programs in a computer cluster to communicate via the Message-Passing Interface (MPI).\n\nThe internal data objects of the library are serializable, i.e., the user can convert the MPI state or objects, such as groups or communicators, into byte streams and save them into a checkpoint file. \n\nLater users can load the checkpoint file and de-serialize previous objects into the library. \n\nSerialization/de-serialization is useful in MPI applications to recover from node failures.", + "laborHours": 9636.8, + "languages": [], + "name": "MPI Stages : A Serializable MPI Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/mpi-stages", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-12-23", + "metadataLastUpdated": "2024-10-25" + }, + "description": "Offshore Renewables Balance of System and Installation Tool (ORBIT) simulates balance of system and installation processes for offshore wind plants. It is intended to be used to study the effects of weather delays on offshore vessel logistics and for medium fidelity trade-off studies for offshore technologies.", + "laborHours": 10776.8, + "languages": [ + "Python" + ], + "name": "ORBIT (Offshore Renewables Balance of System and Installation Tool) WISDEM\u00ae [SWR-20-11]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/ORBIT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.8" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-23", + "metadataLastUpdated": "2021-07-22" + }, + "description": "GPU-BSW is a version of Smith-Waterman alignment algorithm which has been optimized to perform large number of sequence alignments on GPUs.", + "laborHours": 851.2, + "languages": [], + "name": "A Domain indEpendent sequence alignment strategy for gPu archiTectures (ADEPT) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/m-gul/GPU-BSW", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-01-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Biological Performance Assessment (BioPA) version 3, uses computational fluid dynamics (CFD) and particle trajectory simulations of the hydro-turbine to quantify the exposure of passing fish to a set of known injury mechanisms. By appropriate sampling of the fluid domain, the BioPA assigns exposure probabilities to each mechanism. The exposure probabilities are combined with dose- response data from laboratory stress studies of fish to produce a set of biological BioPA Scores. These metrics provide an objective measure that can be used to compare competing turbines or to refine a new design.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Biological Performance Assessment (BioPA) Toolset version 3", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "3" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-06", + "metadataLastUpdated": "2020-01-06" + }, + "description": "DiHydrogen is the second version of the Hydrogen fork of the well-known distributed linear algebra library, Elemental. \n\nDiHydrogen is a GPU-accelerated distributed multilinear algebra interface with a particular emphasis on the needs of the scalable distributed deep learning training and inference. \n\nDiHydrogen is part of the Livermore Big Artificial Neural Network (LBANN) software stack.", + "laborHours": 38456.0, + "languages": [], + "name": "DiHydrogen", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/dihydrogen", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-01-07", + "metadataLastUpdated": "2020-01-07" + }, + "description": "This software simulates and compares the losses in AC and DC buildings. It uses formatted load profile data from EnergyPlus, PV generation data from PVWatts, realistic converter efficiency curves based on product data, a battery controller based on excess PV, and a realistic wire model. The software includes Modelica code, which is an extension of the Buildings Library Electrical models. It also includes Python code, which manages the Modelica parametric simulations and plots results.", + "laborHours": 36571.2, + "languages": [], + "name": "Modelica Buildings Library Extension for AC and DC Building Comparison (Modelica DC Buildings) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dgerb/DCBuildingSimModelica", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-01-09", + "metadataLastUpdated": "2020-07-27" + }, + "description": "Brief Description for Public Release:\nVarity is a framework to identify variations in floating-point programs through randomized differential testing. Varity generates random tests that include floating-point operations and compile these tests with different compilers in a system. It also generates random floating-point inputs for the tests. When tests are executed, the results are compared to identify variations in the results. Varity helps users of a system to identify the compilers that produce the most similar results in the system.", + "laborHours": 15732.0, + "languages": [], + "name": "Varity", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Varity", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-01-09", + "metadataLastUpdated": "2020-01-09" + }, + "description": "This code is a simply python module that allows the user to read in the solar system value from a\nprovided database. It simply reads in the database, and calculates ratios with various values. Currently,\nthe solar system values from Lodders et al. (2009) are solely included. The tool is designed to assist a\nastrophysics / cosmochemist user in their daily life of calculating those ratios for programs and was\nwritten by the author to simplify his own life. A setup.py routine has been written as well. Release is\nanticipated via github as well as in the form of a pypi package.", + "laborHours": 121.6, + "languages": [], + "name": "Solar System Initial Abundnace Reader", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/iniabu", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The testbed \u201cPRIME\u201d is implemented as a typical end-to-end SCADA hierarchy, from the substation to the control center,\nusing a combination of a well-known power system simulator, power system control, hardware-in-the-loop (HIL) and\nindustry grade EMS software. Other cyber-physical testbeds have similar modularity. However, they lack flexibility in\nswapping out the software used for EMS, FEP, and the hardware used for RTU and relays as the computational\nsubsystems and the input/output (I/O) subsystems are tightly coupled and integrated. They tend to be tied to a single\nvendor. In our approach, the power system simulator and the hardware driver (analog output subsystems to drive HIL) are\ndecoupled and are interconnected through communication protocols as an interface. This provides an additional level of\nmodularity to the architecture creating an interoperable environment where power system simulators and hardware could\nbe interchanged as long as they support streaming of measurements/commands.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "PRIME", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A joint inverse module was developed by imposing structural similarities between different physical parameters and\nincorporated into the E4D geophysical simulator, a parallel multi-physics modeling and inversion code with unstructured\ntetrahedral mesh. The inversion capability of E4D can accommodate joint inversions of data from two or more geophysical\nmethods that are available in E4D and is suitable for large scale three-dimensional subsurface characterization or\nmonitoring. The joint inversion capability were tested using synthetic data from borehole electrical resistivity tomography\nand seismic survey.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "E4D Simulator with Joint Inversion Capability", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "chitra.sivaraman@pnnl.gov" + }, + "date": { + "created": "2020-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The MHKiT Code Hub is a collection of open-source marine renewable energy (MRE) software. The MHKiT code, developed in Python and MATLAB, includes modules for ingesting, quality controlling, processing, visualizing, and managing data. MHKiT-Python and MHKiT-MATLAB provide robust and verified functions in both Python and MATLAB that are needed by the MRE community to standardize data processing. Calculations and visualizations adhere to IEC technical specifications and other guidelines. Current functionality includes power performance, power quality, mechanical loads, resource tools, and data quality control for wave, tidal, and river applications.", + "laborHours": 579864.8, + "languages": [ + "MATLAB" + ], + "name": "MHKiT (Marine and Hydrokinetic Toolkit) - MATLAB", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MHKiT-Software/MHKiT-MATLAB", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "chitra.sivaraman@pnnl.gov" + }, + "date": { + "created": "2020-01-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The MHKiT Code Hub is a collection of open-source marine renewable energy (MRE) software. The MHKiT code, developed in Python and MATLAB, includes modules for ingesting, quality controlling, processing, visualizing, and managing data. MHKiT-Python and MHKiT-MATLAB provide robust and verified functions in both Python and MATLAB that are needed by the MRE community to standardize data processing. Calculations and visualizations adhere to IEC technical specifications and other guidelines. Current functionality includes power performance, power quality, mechanical loads, resource tools, and data quality control for wave, tidal, and river applications.", + "laborHours": 593985.6, + "languages": [ + "Python" + ], + "name": "MHKiT (Marine and Hydrokinetic Toolkit) - Python", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MHKiT-Software/MHKiT-Python", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2020-01-16", + "metadataLastUpdated": "2020-01-16" + }, + "description": "cubacpp provides a C++ binding for the excellent CUBA library, and to a lesser extent, to the GSL integration library GSL. cubacpp provides no new integration facilities. It merely provides a more convenient syntax for use of the CUBA (and GSL) integration routines, made possible by the features of the C++ programming language.", + "laborHours": 7995.2, + "languages": [], + "name": "cubacpp", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/mpaterno/cubacpp", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "gwright@pppl.gov" + }, + "date": { + "created": "2020-01-16", + "metadataLastUpdated": "2020-02-25" + }, + "description": "CUDA C Orbit Model\n\nNumerical guiding center code for toroidally confined plasma.", + "laborHours": 2812.0, + "languages": [ + "C", + "C", + "CUDA" + ], + "name": "cuOrbit", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PrincetonUniversity/cuOrbit", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "vcs": "git", + "version": "validation-alpha-rc1" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-24", + "metadataLastUpdated": "2020-01-24" + }, + "description": "Code takes a data file of input features of a set of digitized pulses and converts the file to three vectors describing a two-component Gaussian mixture model of the input pulses. \n\nThese three vectors can then be applied mathematically to a set of input feature data of digitized pulses to \ngenerate soft-scores describing the likelihood of each pulse's membership in each of the two Gaussian modeled components. \n\nThe operation of the code also displays graphics to the user for \ninterpreting the output vectors and\ndistribution of the soft-scores of the input data.", + "laborHours": 182.4, + "languages": [], + "name": "PSD GMM Trainer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/trainGMM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-27", + "metadataLastUpdated": "2020-01-27" + }, + "description": "AutoParBench is a benchmark framework to evaluate compilers and tools designed to automatically insert\nOpenMP directives. \n\nThe goal is to generate actional information (bug reports and feature requests) for compiler and tool developers.\n\nWe also want to drive the research for automatic parallelization using OpenMP and make OpenMP more declarative to reduce the burdens on OpenMP users.", + "laborHours": 209866.4, + "languages": [], + "name": "AutoParBench", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/autoparbench", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "Python class for handling encrypted elements in a config file. Extension of ConfigParser. This class overides the 'get' method of ConfigParser replacing it with Fernet symmetric encryption so that you can safely store encrypted passwords in an ini file.", + "laborHours": 152.0, + "languages": [ + "Python" + ], + "name": "CryptoConfig (ITS Data Management)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CryptoConfig", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "Identification of cell state based on objective metrics is a fundamental problem in developmental biology. With the advent of fluorescent activated cell sorting (FACS), transcriptomics, and (more recently) single-cell RNA sequencing, it has become possible to profile mRNA abundance of all genes in individual cells or cell types. This transcriptomic information for cell types is often characteristic, and can be used to classify cell types for cells with unknown identity. Previously, an algorithm was developed using a Bayesian method to derive specificity scores for all genes across all known cell types, and then to use these scores to assign the most likely cell type for a new transcriptomic profile. ICITools implements this Index of Cell Identity algorithm as an R package, making the method more easily distributed. In addition, this package implements slight improvements on the previous implementation by adding parallelization, small enhancements in speed, and the ability to customize some aspects of the specificity score computation method. The package does not alter the underlying algorithm, nor the overall functionality of the original methods.", + "laborHours": 380.0, + "languages": [], + "name": "ICITools v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/b-coli/ICITools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "The Remote Mirror Security project is a git hook used to evaluate a remote repository from which changes are mirrored and enforce a security policy before accepting changes.", + "laborHours": 866.4, + "languages": [], + "name": "Remote Mirror Security", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/remote-mirror-security", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "This software implements an active learning framework for Natural Language Processing (NLP) systems.\n\nIt is intended to be applied on scenarios where limited amount of labeled data is available to train a machine learning-based NLP classification system, but a large set of unlabeled documents exist. \n\nThis software will point, from the set of unlabeled documents, which ones we should label next so that the overall performance of the classifier is improved.", + "laborHours": 1064.0, + "languages": [], + "name": "Active Learning for NLP Systems", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AL_NLP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "The Detection Framework Testbed and Toolkit \n(DFTT) is a signal detection system that uses\nautomatically generated subspace and correlation detectors. \n\nDFTT is intended to facilitate the development and testing of algorithms for operating suites of such detectors. \n\nThe software is a generalization of the system described in Harris and Dodge (2011) and has been applied in contexts ranging from local borehole induced seismicity to large-scale teleseismic observations. \n\nThe software includes interactive applications for creating detection configurations, inspecting and \nediting templates, viewing detection statistics, viewing detected signals, classifying detectors and more.", + "laborHours": 102448.0, + "languages": [], + "name": "Detection Framework Testbed and Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DFTT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-31", + "metadataLastUpdated": "2020-01-31" + }, + "description": "Evaluate Copson's solution for the free expansion of an ideal gas into vacuum. \n\nThe solution for streamlines and characteristics are given along with a way to evaluate the solution for any (x,t) location.", + "laborHours": 334.4, + "languages": [], + "name": "Copson Expansion Solution", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/copson_expansion_solution", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "BuildingSyncRails is a library for the Ruby on Rails [1] web application development framework that leverages the Isomorphic library for the Ruby programming language (IPID Submission #11610) in order to provide BuildingSync [2] XML capabilities to Ruby on Rails applications. BuildingSyncRails provides the following capabilities:\nCapability to download the most recent version of the BuildingSync XML schema document from GitHub and to automatically convert said document into Ruby code.\nToolkit for constructing and manipulating Ruby objects that represent BuildingSync XML elements.\nBuildingSyncRails builds upon the capabilities of the Isomorphic library for the Ruby programming language\u037e specializing the generic capabilities of the Isomorphic library for BuildingSync specifically, e.g., by providing a library of BuildingSyncfriendly methods to simplify the construction of BuildingSync XML documents.", + "laborHours": 304.0, + "languages": [], + "name": "pnnl/building_sync_rails", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/building_sync_rails", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Isomorphic is a Ruby library for specifying isomorphisms between Ruby objects.\nThe inventive features of the new Ruby library are as follows:\nDomain-specific language (DSL) for declaration of isomorphisms between Ruby objects.\nFunctional references (viz., \"lenses\") for getter/setter operations.\nTo our knowledge, this is the first library of its kind for the Ruby programming language. Moreover, to our knowledge, this is the first implementation of the \"functional references\" concept within the Ruby programming language.", + "laborHours": 714.4, + "languages": [], + "name": "pnnl/isomorphic", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/isomorphic", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "GridPACK is a software framework consisting of a set of modules designed to simplify the development of programs that model the power grid and run on parallel, high performance computing platforms. It also contains several fully developed applications, including powerflow, dynamic simulation, state estimation, Kalman filter analysis (dynamic state estimation), contingency analysis and real time path rating. These applications can be used either standalone or as components in more complicated workflows that combine several different types of application together. The framework modules are available as a combination of libraries and software templates and consist of components for setting up and distributing power grid networks, support for modeling the behavior of individual buses and branches in the network, converting the network models to the corresponding algebraic equations, and parallel routines for manipulating and solving large algebraic systems. The framework also contains a module for distributing tasks evenly amongst computing resources, even if individual tasks vary widely in their execution times. Additional modules support input and output, basic statistical analysis of contingency based calculations, distributed data structures, as well as basic profiling and error management.", + "laborHours": 217861.6, + "languages": [], + "name": "GridOPTICS/GridPACK", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GridOPTICS/GridPACK", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-07", + "metadataLastUpdated": "2020-02-07" + }, + "description": "MHYSA is a conservative finite-difference code to solve the 1D, 2D, and 3D multispecies Navier-Stokes equations for hypersonic flow applications. \n\nIt supports Cartesian grids only and has the option of including immersed boundaries.\n- Solves 1D Euler and 2D and 3D Navier-Stokes equations.\n- Solves the PDEs over Cartesian grids.\n- Written entirely in C and uses the MPICH library. It also uses OpenMP threads but this is a work-inprogress.\n- Can be compiled with PETSc (http://www.mcs.anl.gov/petsc/), if available, where it can use PETSc's time integration module TS (http://www.mcs.anl.gov/petsc/petsc-current/src/ts/).\n- For 3-dimensional simulations, the immersed boundaries can be used to solve over non-Cartesian geometries.\n\nMHYSA has been developed to be scalable, and apart from the usual functionalities to solve a system of PDEs on distributed architectures, it provides scalable file I/O functions.\n", + "laborHours": 16704.8, + "languages": [], + "name": "Multispecies Hypersonic Flow Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/mhysa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-07", + "metadataLastUpdated": "2020-02-07" + }, + "description": "Bindee is a clang tool that outputs a simple pybind11 template given a C++ file for efficient generation of C++-Python bindings. \n\nBindee is intended to be a helper tool for minimizing initial user effort and\nsafeguarding against common runtime errors.\n\nBindee relies on two open-source software to produce bindings.\n\nClang's LibTooling enables bindee to traverse a C++ file's AST to pick out bindable variables and functions, or \"bindees.\"\n\nPyBind11 is templated, header-only library for generating C++-Python bindings for variables and functions.\n\nOperating purely in C++, bindee does not require learning any new API for accomplishing its task.\n\nAdditionally, picking the correct pybind11 API for a given bindable element is handled without interaction from the user. Any user input is denoted by '@TEXT@' string substitution.\n\nBindee is capable of generating modular bindings for public class methods, public class variables, enumerations, and free functions and variables. \n\nBindings for templates are also supported. \n\nFor those familiar with pybind11, bindee does not handle trampolines, C++ extensions through lambdas, or custom type casters.\n", + "laborHours": 1915.2, + "languages": [], + "name": "Bindee", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/bindee", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-02-10", + "metadataLastUpdated": "2020-02-10" + }, + "description": "This mini app is to measure performance of a kernel for computing the correlation energy of GAMESS (General Atomic and Molecular Electronic Structure System) application on multiple processor architectures.", + "laborHours": 760.0, + "languages": [], + "name": "GAMESS RI-MP2 MiniApp", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/NCSA", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jkwack/GAMESS_RI-MP2_MiniApp", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-12", + "metadataLastUpdated": "2020-02-12" + }, + "description": "Reinforcement learning (RL) aims to learn optimal strategies for control problems with complex, stochastic dynamics. \n\nStandard RL formulations assume that transition dynamics are the same across episodes. \n\nHowever, this is not the case for many real-world environments, e.g. a disease process in which each patient is unique. \n\nTransfer learning in RL aims to solve this problem; however, existing methods allow for multiple trials on a test episode.\n\nWe consider the \"single episode transfer\" setting in which a policy is evaluated on one and only one test episode; thus, any adaptation must occur during that episode. \n\nSingle episode policy transfer (SEPT) is a framework for finding optimal control policies in this setting. \n\nIn SEPT, a \"probe policy\" initially probes the environment to gain information about how that episode is unique. \n\nThen, the information gained from the probe becomes an additional input to the \"universal policy\" that controls the remainder of the episode. \n\nSEPT is a general algorithm and can be used with any existing RL algorithm, including in batch learning mode.\n", + "laborHours": 4058.4, + "languages": [], + "name": "Single Episode Policy Transfer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/011235813/sept", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-02-12", + "metadataLastUpdated": "2020-02-17" + }, + "description": "GEOPHIRES v2.0 is a geothermal techno-economic simulation tool upgraded from GEOPHIRES v1.2. The name stands for \"GEOthermal energy for Production of Heat and electricity (\u201cIR\u201d) Economically Simulated\". GEOPHIRES combines reservoir, wellbore, and surface plant technical models with cost correlations and levelized cost models to estimate the capital and operation and maintenance costs, instantaneous and lifetime energy production, and overall levelized cost of energy of a geothermal plant. In addition to electricity generation, direct-use heat applications and combined heat and power or cogeneration can be modeled. Various upgrades have been implemented to develop GEOPHIRES v2.0, including: updating the built-in cost correlations, coupling to the external reservoir simulator TOUGH2, enhancing the built-in wellbore simulator, converting the programming language to Python, and making the code open-source. Users are encouraged to build upon the tool, e.g. by implementing their own correlations or coupling to other simulators. ", + "laborHours": 1140.0, + "languages": [ + "Python" + ], + "name": "GEOPHIRES v2.0", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GEOPHIRES-v2", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-13", + "metadataLastUpdated": "2021-10-05" + }, + "description": "Holotomography is a non-destructive x-ray imaging technique which allows to visualize the interior morphology of object without damaging them. It is similar to x-ray computed tomography (CT), but unlike conventional CT, which is based on the attenuation of x-rays passing through the object, holotomography exploits the phase shift caused by the sample. This phase-contrast imaging allows to increase image contrast by recovering refractive index of materials and is proven to be more sensitive to density variations than conventional absorption-based X-ray imaging when applied to low-Z materials. In holotomography, the phase is retrieved by measuring the variations in intensity of the object at different sample to detector distances. Several algorithms exist to perform this task such as, contrast transfer function (CTF), transport of intensity equation (TIE), and a mixed approach which combine both TIE and CTF.", + "laborHours": 349.6, + "languages": [], + "name": "Holotomography Phase-Retrieval", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jbforien/phaseCT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-02-13", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Analytical Data Reduction Excel Macro", + "laborHours": 0.0, + "languages": [], + "name": "ADREM", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/ADREM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gwright@pppl.gov" + }, + "date": { + "created": "2020-02-14", + "metadataLastUpdated": "2020-02-19" + }, + "description": "The CQL family are Relativistic Collisional/QuasiLinear Fokker-Planck codes.\n\ncql3d_f90 is a derived work of the CompX CQL3D Fortran IV/77 GNU code. This F90 version uses derived types, modules, fixes several bugs, is distributed with a Centos7 (Docker) container, and includes automated CI tests.", + "homepageURL": "https://princetonuniversity.github.io/cql3d_f90", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "cql3d_f90", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://princetonuniversity.github.io/cql3d_f90", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Virtual reality for biomolecular electrostatics UnityMol-APBS (NIH iEdison No. 0685901-19-0009, Grant No. GM069702)\nVisualization of molecular electrostatics on a two-dimensional screen greatly diminishes the associated depth component.\nUsing a virtual world to explore molecular electrostatics allows researchers to be immersed within their data.", + "laborHours": 15.2, + "languages": [], + "name": "UnityMol-APBS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electrostatics/VR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Prototype software for virtual reality based instruction manual for transmission electron microscopy (TEM).", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "TEM Instruction", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "nsu@lifeeusa.com" + }, + "date": { + "created": "2020-02-18", + "metadataLastUpdated": "2020-09-09" + }, + "description": "Deep neural network-based force field enables researchers to study materials systems of large size and/or time scale efficiently with comparable accuracy to DFT-based methods. However, such force fields, if improperly trained or mistakenly selected, could result in ill-conditioned results. This SBIR Phase I project has explored the possibility to characterize and index force fields in Deep potential theme by quantizing local atomic environments of atoms in a simulation system. This project has also demonstrated the feasibility of building a public accessible web infrastructure providing high quality machine learning algorithm-based force field for next generation materials modeling and simulation to accelerate the study and discovery of new energy-related materials.", + "laborHours": 638.4, + "languages": [ + "Python" + ], + "name": "LEMD", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mogudaxia/LEMD.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-20", + "metadataLastUpdated": "2020-02-20" + }, + "description": "Symbolic regression is the task of finding tractable mathematical expressions that best fit an input\ndataset. \n\nDeep symbolic regression (DSR) searches the space of tractable mathematical expressions by using a recurrent neural network that generates mathematical expressions. \n\nThe network is trained using reinforcement learning.", + "laborHours": 4985.6, + "languages": [], + "name": "Deep Symbolic Regression", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/brendenpetersen/deep-symbolic-regression", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The SMDS detects RTU performance degradation and select operational faults and provides estimates of the accrued energy and cost impacts weekly after detection of a performance issue. It uses only two sensors per each RTU, outdoor-air temperature and total power demand, both collected at one-minute intervals. Software code based on the methodology and algorithms developed by PNNL in a collaborative develop effort with NorthWrite Inc. and Universal Devices implement the detection processes and estimation of energy and cost impacts. The methodology, algorithms and original prototype software were developed exclusively by PNNL. Two versions of the SMDS, the Hardware SMDS and the Cloud SMDS, have been prototyped and tested on buildings in the field and/or on data from buildings. Both versions use the same methodologies for detection of performance degradation and for detection of specific faults.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Smart Monitoring and Diagnostic System (SMDS)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Ion Mobility control software designed to work specifically with Thermo Fisher Scientific ion trap (specifically the Exactive / Q Exactive)", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Ion mobility control software (Ion Trap coupled)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "rgrandy@bnl.gov" + }, + "date": { + "created": "2020-03-02", + "metadataLastUpdated": "2020-03-02" + }, + "description": "An open-source package for 2D X-ray near-edge spectroscopy analysis", + "laborHours": 10761.6, + "languages": [ + "Python" + ], + "name": "PyXAS", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gmysage/pyxas", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-03-03", + "metadataLastUpdated": "2020-03-03" + }, + "description": "These are miscellaneous utility functions that I've developed and found useful in working with sequencing counts.\n\nPurpose: To collect often reused procedures in one open source location that can be shared and worked on publicly, and perhaps contributed back to other open source projects.\n\nFunction: Adds, divides, filters, summarizes tables of counts.\n\nCapabilities: Currently, the main capability is to reformat count tables for use with the ALDEx2 package.", + "laborHours": 34428.0, + "languages": [], + "name": "Microbial Ecology Toy Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/meco", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.9000" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-03-03", + "metadataLastUpdated": "2022-07-28" + }, + "description": "MTtime is a software tool developed for time domain inversion of complete seismic waveform data to obtain the seismic moment tensor. It supports both deviatoric and full moment tensor inversions as well as 1-D and 3-D basis Green's functions.", + "laborHours": 0.0, + "languages": [], + "name": "Time Domain Moment Tensor Inversion in Python", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mttime", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-03-03", + "metadataLastUpdated": "2020-03-03" + }, + "description": "This tool traces all memory accesses to stack (static allocation) and heap (dynamic allocation) on a trace run in a particular hardware and then estimates execution time on given arbitrary hardware configurations for hardware design space exploration.\n\nIt can also compute memory access statistics, such as reuse distance.", + "laborHours": 6353.6, + "languages": [], + "name": "Memory Analysis Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-03-03", + "metadataLastUpdated": "2020-05-27" + }, + "description": "MFEM is a free, lightweight, scalable C++ library for finite element methods. \n\nThe goal of MFEM is to enable research and development of scalable finite element discretization and solver algorithms through general finite element abstractions, accurate and flexible visualization, and tight integration with the hypre\nlibrary.\n\nConceptually, MFEM can be viewed as a finite element toolbox that provides the building blocks for developing finite element algorithms in a manner similar to that of MATLAB for linear algebra methods.", + "laborHours": 0.0, + "languages": [], + "name": "Modular Finite Element Methods", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfem/mfem/releases/tag/v4.1", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "4.1" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-03-04", + "metadataLastUpdated": "2023-05-31" + }, + "description": "reVX is a complementary toolset that enables the extraction, translation, and loading (ETL) of reV results into formats required by downstream models, such as RPM, ReEDS, and PLEXOS.\n\nSEE ALSO: https://github.com/NREL/revruns", + "laborHours": 12737.6, + "languages": [ + "Python" + ], + "name": "reVX (The Renewable Energy Potential Exchange Tool) [SWR-20-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/reVX", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-03-04", + "metadataLastUpdated": "2023-08-25" + }, + "description": "The Renewable Energy Potential (reV) model is a platform for the detailed assessment of renewable energy resources and their geospatial intersection with grid infrastructure and land use characteristics. The reV model currently supports photovoltaic (PV), concentrating solar power (CSP), and land-based wind turbine technologies. Modules in the reV framework function at different spatial and temporal resolutions, allowing for the assessment of resource potential, technical potential, and supply curves at varying levels of detail. The platform runs on the National Renewable Energy Laboratory\u2019s (NREL\u2019s) high-performance computing system, providing scalable and efficient performance from a single location up to a continent, for a single year or decades of time-series resource data. Coupled with NREL\u2019s System Advisor Model (SAM), reV supports resource assessments from 5-minute to hourly temporal resolutions and supports the analysis of long-term (i.e., year-on-year) variability of renewable generation (e.g., interannual variability and exceedance probabilities).", + "laborHours": 250526.4, + "languages": [ + "Python" + ], + "name": "reV (The Renewable Energy Potential Model - Open Source) [SWR-21-59, SWR-20-20 and SWR-17-34]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/reV", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2020-03-12", + "metadataLastUpdated": "2020-03-12" + }, + "description": "GlideinMonitor is a Web application that allows to view GlideinWMS\u2019s Glidein log files: it provides a user interface, tools to do quick searches and to decode the log content; it provides an efficient managed archive of the log files and a framework to add log processing, e.g. log sanitation.\nhttps://docs.google.com/document/d/1PqmQ_-_JtqK472DT-Y0D08yU1m-lPeFvrp8n4x9f5QE/edit?usp=sharing", + "homepageURL": "https://cdcvs.fnal.gov/redmine/projects/glideinwms/repository/glideinmonitor", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "GlideinMonitor", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cdcvs.fnal.gov/redmine/projects/glideinwms/repository/glideinmonitor", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] + }, + { + "contact": { + "email": "dzander@sandia.gov" + }, + "date": { + "created": "2020-03-12", + "metadataLastUpdated": "2021-03-05" + }, + "description": "Shadow is a PyTorch based library for semi-supervised machine learning via consistency regularization.", + "laborHours": 820.8, + "languages": [ + "Python" + ], + "name": "shadow-ssml", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/shadow", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bethany@lbl.gov" + }, + "date": { + "created": "2020-03-14", + "metadataLastUpdated": "2020-03-14" + }, + "description": "A supervised machine learning pipeline, MIMOSAS (Multisource Input Model Output Security Analysis Suite), has been developed for classification of multimodal data to inform nuclear security and proliferation detection scenarios. MIMOSAS provides an end-to-end data processing workflow, from data ingestion and pre-processing to model training and test set classification. The pipeline is specified via an input deck, making workflow customization effortless, and the framework is modular allowing for the easy addition of new learning algorithms. In the current build, the user selects from decision tree, random forest, and feed-forward neural network classifiers to train customizable models with built-in cross validation methods for hyperparameter optimization. Trained model outputs are stored with the associated metadata for rapid deployment. These can be applied in supervised classification to assess previously unseen data or for further training as new observations are added to the existing data set. MIMOSAS provides the capability to fuse a wide range of data sources (e.g., radiation, environmental, acoustic, seismic, imagery, etc.) to make, confirm, and correlate machine learning predictions for nuclear security applications.", + "laborHours": 5198.4, + "languages": [ + "Python" + ], + "name": "MIMOSAS", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://complexity.berkeley.edu/wp-content/uploads/2019/09/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nonproliferation/mimosas", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-03-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This development was conceived to help solve the problem of the large number of chemical structures that result from a large number of atoms. This includes large surface models, functionalized surfaces, or supported clusters, relevant to many chemical problems in Separations and Catalysis. The program was developed to address these issues, and also solve the problem associated with the need to know the large number of structures that are energetically close. Knowing\nhow many structures are similar allows us to develop better starting models for large scale simulations.", + "homepageURL": "https://store.pnnl.gov/content/north-west-potential-energy-surface-search-engine-nwpesse", + "laborHours": 0.0, + "languages": [], + "name": "NWPEsSE (North West Potential Energy Surface Search Engine)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/north-west-potential-energy-surface-search-engine-nwpesse", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2020-03-17", + "metadataLastUpdated": "2020-03-17" + }, + "description": "nubhlight is a code for simulating disks of materials around black holes formed after the in-spiral and merger of two-black holes. It is based on the open-source code bhlight. nubhlight models all relevant physics required to solve the post-merger disk problem. This includes: general relativity in a static spacetime, neutrino and weak physics, relativistic magnetohydrodynamics, and the ability to use open-sourced tabulated equations of state provided by stellarcollapse.org.\n", + "laborHours": 27344.8, + "languages": [], + "name": "lanl/nubhlight", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/nubhlight", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-03-18", + "metadataLastUpdated": "2020-04-03" + }, + "description": "The Multi-Area Frequency Response Integration Tool (MAFRIT) is the only software tool of its kind that integrates primary frequency response (turbine governor control) with secondary frequency response (automatic generation control). It simulates the power system dynamic response in full time spectrum with variable time steps from millisecond to minutes to hours and days. Capable of simulating both normal and event conditions, this tool can represent real power system operations and thus evaluate the primary and secondary reserves adequacy. This unique interaction of a turbine governor model and a novel automatic generation control model places special emphasis on electric power systems with high penetrations of renewable generation.", + "laborHours": 3967.2, + "languages": [ + "MATLAB" + ], + "name": "MAFRIT (Multi-Area Frequency Response Integration Tool)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MAFRIT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-03-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This package includes the implementation for four sparse linear algebra kernels: Sparse-Matrix-Vector-Multiplication (SpMV), Sparse-Triangular-Solve (SpTRSV), Sparse-Matrix-Transposition (SpTrans) and Sparse-Matrix-Matrix-Multiplication (SpMM) for Single-node Multi-GPU (scale-up) platforms such as NVIDIA DGX-1 and DGX-2.", + "laborHours": 5715.2, + "languages": [], + "name": "s-blas", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/s-blas", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-03-24", + "metadataLastUpdated": "2021-08-17" + }, + "description": "This open-source tool implements Circular Economy metrics for photovoltaic (PV) materials. It can be used to quantify and assign a value framework to efforts on re-design, reduction, replacement, reuse, recycling, and lifetime and reliability increases in the PV value chain.\n\nThe PV_ICE is leveraging published data from different sources on PV manufacturing and predicted technological changes. Input data is being compiled here\n\nThis tool will help implement circularity metrics, quantify and assign a value framework to efforts on re-design, reduction, replacement, reusage, recycling, and lifetime and reliability increases on PV.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PV_ICE: PV in the Circular Economy, Dynamic Energy and Materials Tool (PV ICE)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PV_ICE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v. 2" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-03-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Project Schedule Comparison and Visualization allows project schedules to be compared across time scales. It also allows for visualization of schedules in the form of a network graph. This compliments Gantt chart view in major project risk management software. The software mimics complex networks and makes it easy to visualize tasks and links. It produces a list with differences between snapshots. Selecting these differences renders a view focused on these changes in the network.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Project Schedule Comparison and Visualization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "rgrandy@bnl.gov" + }, + "date": { + "created": "2020-03-30", + "metadataLastUpdated": "2020-03-30" + }, + "description": "PyMDA allows for processing individual microcrystal data sets as progressive wedges to address radiation damage and allows for robust extraction of diffraction signals including weak anomalous signals through the implementation of unit-cell-based classification and an iterative outlier rejection strategy. PyMDA may be used routinely to process microcrystal data sets to produce one or more assembled data sets for structural analysis.", + "laborHours": 395.2, + "languages": [ + "Python" + ], + "name": "PyMDA", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qun-liu/PyMDA", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-04-02", + "metadataLastUpdated": "2023-08-16" + }, + "description": "Simple examples of bokeh streaming data. The plots are intended to be generic and able to infer some of the plot data from the structure of the data sent. The receiver accepts zlib compressed pickled python dictionaries.", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "bokeh streaming [SWR 19-08]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bokeh-streaming", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-04-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Software that runs a model of a physical process either generated from extrapolative machine learning or from canned physics simulators to generate realistic data for feeding deceptive controller decoys for defense.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Process model simulator for deception", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-04-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A creation of packages of metadata, data, and communication networks services that are designed to highly accurately mimic the behavior of specific models of control system devices such as relays, PLCs, RTUs, etc. The inventive nature is the packaging of these features together such that they mimic specific models of equipment where existing approaches\nfocus on generalized control devices.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "High fidelity OT Decoy Profiles/Services", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-04-08", + "metadataLastUpdated": "2020-04-09" + }, + "description": "Modelica is a modeling and simulation language similar to Matlab/Simulink. Modelica has many advantages, which will not be discussed here, over conventional software. The software project implements a parser of the Modelica language allowing for easy-to-implement transformations of Modelica files.\n", + "laborHours": 4985.6, + "languages": [ + "Modelica" + ], + "name": "Modelica Builder (ModBuild)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/urbanopt/modelica-builder", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-04-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Rechargeable lithium metal batteries are being intensively studied in recent years because of their high energy density which potentially could double the cell energy of state-of-art Li-ion batteries. However, cell design of realistic high-energy Li metal batteries is quite different with Li-ion batteries, not mentioning prediction of cycle life. A powerful software using machine learning will greatly accelerate academic research and industry battery manufacturing process.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Application of Machine Learning for Rechargeable Lithium Metal Battery Design and performance prediction", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "savaraa@ornl.gov" + }, + "date": { + "created": "2020-04-13", + "metadataLastUpdated": "2020-09-25" + }, + "description": "UnitTesterSG is a unit testing framework that is designed for nested and/or scientific/engineering data structures. It is designed primarily for testing the outputs if a single function or simulation run by storing the expected results file such that comparisons to the stored output can be made with unit tests after the function or software has been edited.\n\nThis module is designed to be able to unit test arrays, strings, as well as nested and deeply nested objects (including arrays with tuples inside, arrays with strings inside, etc.). The module is compatable with nested objects, and thus has a dependency on the nestedObjectsFunctions module within. The module takes *calculated* results and then compares them to *expected* results. If no expected results are available (or they do not match the calculated results) the module then offers to store the calculated results as expected results for next time.", + "laborHours": 319.2, + "languages": [ + "Python" + ], + "name": "UnitTesterSG", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdityaSavara/UnitTesterSG", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "5.0" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-04-17", + "metadataLastUpdated": "2020-04-20" + }, + "description": "The Resource Extraction Tool (rex) includes tools developed for reV and reVX related to the efficient access of, extraction from, and computation on NREL's renewable resource datasets (NSRDB and WTK).", + "laborHours": 8040.8, + "languages": [ + "Python" + ], + "name": "Resource Extraction Tool (rex)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/rex", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-05-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Automated Raabe table generationPyRaabe is a Python package to automate Raabe table -- a graph representation of airway geometry -- generation from a triangulated surface of an airway geometry. With a single command, it extracts a centerline from an input 3D surface mesh and subsequently computes the relevant attributes for the Raabe table, including length, diameter, bifurcation angle, and gravity angle. These can be used to inform downstream models, such as the Multiple-Path Particle Dosimetry (MPPD) model.", + "laborHours": 91.2, + "languages": [], + "name": "pnnl/pyraabe", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pyraabe", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-05-01", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The data of a nuclear utility or plant are stored in various isolated forms in different systems. These data have different structures and tools and are, therefore, used independently. The integration of data sources is often needed and is performed manually and on an as-needed basis. The integration of the data would enable creating a data warehouse for a single nuclear power plant (NPP) or multiple plants. A data model contains objects that make up a given domain along with their attributes and relationships and could be used as a standard for exchange between applications for simple integration and data aggregation. After a survey of existing models, it was determined that a new model was required to meet the scope of this problem. DIAMOND has been developed in the form of an ontology to meet these needs. An ontology is simply a data model that also acts as a taxonomy for the domain, organizing the objects in a hierarchy with the most general objects at the top.", + "laborHours": 30.4, + "languages": [], + "name": "Data Integration Aggregated Model For Nuclear Deployment", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DIAMOND", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-08", + "metadataLastUpdated": "2020-05-08" + }, + "description": "MFEM is a modular parallel C++ library for finite element methods. 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It enables users to transform the type of any\nvariables or operations. It guarantees the syntactic and semantic correctness of the generated code -- it\nwill always compile!\nIs", + "laborHours": 9697.6, + "languages": [], + "name": "Typeforge", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/typeforge", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-08", + "metadataLastUpdated": "2020-05-08" + }, + "description": "Benchmark Algorithm for Radio-Nuclide Identification (BARNI) is an automatic radionuclide identification\ntool for use with gamma-ray spectra. BARNI is designed to serve as a comparative tool for commercial\nvendor algorithms, such as those found in RadioIsotope Identification Devices (RIID). The tool\nincorporates an automated training routine allowing BARNI's classifier to be trained for a variety of\ndetectors. The identification algorithm uses a peak search, the results of which are used to build features\nthat are subsequently used for training a classifier. The user provided spectral templates allow BARNI to\nbe trained for any detector of the user's choice.\nIs", + "laborHours": 1641.6, + "languages": [], + "name": "Benchmark Algorithm for RadioNuclide Identification v1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/barni", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-08", + "metadataLastUpdated": "2020-05-08" + }, + "description": "The Direct-FUSE framework supports multiple FUSE file systems as well as other, custom user-level file\nsystems in user space without the need to cross the user/kernel boundary into the FUSE kernel module.\nAll layers of Direct-FUSE are in user space, and applications can directly use pre-defined unified file\nsystem calls to interact with different user-defined file systems. Our performance results show that Direct-\nFUSE can outperform some native FUSE file systems by 11.9% on average and does not add significant\noverhead over backend file systems.\n", + "laborHours": 13588.8, + "languages": [], + "name": "Direct-FUSE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/direct-fuse", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2025-04-14" + }, + "description": "The \"Secure Design and Development Cyber Security Capability Maturity Model\" (SD2-CM2) allows electrical system managers to assess the maturity of their cybersecurity systems, including designs reflecting internet of things devices (IOT). The content provides best practices in the field and users can assess the level of their designs. Modules are \"Content\" and \"Infrastructure\"", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 3986352.0, + "languages": [], + "name": "Secure Design and Development Cyber Security Capability Maturity Model\u201d (SD2-CM2)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2020-05-11" + }, + "description": "C++ template library to represent quantities in scientific computing. It enables a strong, compile-time,\ntyping of physical quantities. This typing includes information about:\n- representation: float, double, ...\n- unit: [ mass, length, time, angle ]\n- scale: kilo, milli, micro, ...\nIs", + "laborHours": 3040.0, + "languages": [], + "name": "Quantities need Representation, Unit and Scale", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/QRUS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2020-05-11" + }, + "description": "Narrows solves the discrete ordinates neutron transport equation using a neural network.", + "laborHours": 942.4, + "languages": [], + "name": "Narrows", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/narrows", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2020-05-11" + }, + "description": "Scanning Electron Microscopy (SEM) images provide a variety of structural and morphological\ninformation for the characterization of the nanomaterials. This code offers automatic recognition and\nquantitative analysis of SEM images in a high-throughput manner using computer vision and machine\nlearning techniques. The main function of this application is to extract particle size and morphology\ninformation of overlapping nanoparticles and core-shell nanostructures in a user friendly interface. The\ncode is written in C++ with QT environment, and has been tested on MacOSX.", + "laborHours": 3192.0, + "languages": [], + "name": "LIvermore SEM image Tools", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LIST", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2020-05-27" + }, + "description": "This is a program to convert a directory of Redvox JSON packets to a single HDF5 file.", + "laborHours": 228.0, + "languages": [], + "name": "PackageRedvoxToHdf5", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stevenmz/package-redvox-to-hdf5", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-12", + "metadataLastUpdated": "2020-05-12" + }, + "description": "QnD is a pure Python package for working with binary files. It has built-in support for HDF5, NetCDF3,\nand PDB formats. It provides a Pythonic, dict-like interface, and allows easy movement among time-like\n\"records\". Both reading and writing are enabled. The HDF and NetCDF capabilities rely on external\nlibraries, while the PDB support is part of QnD itself and entirely in Python. QnD works under Python 2\nand 3. For interactive use, much less typing is involved than for some other packages.", + "laborHours": 2310.4, + "languages": [], + "name": "Quick n Dirty", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/qnd", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-12", + "metadataLastUpdated": "2020-05-12" + }, + "description": "A whole cell model (WCM) is a comprehensive multi-scale computational model representing all the\nknown biochemical processes in a cell. It relies on a variety of intracellular pathway models and omics\ndata.\nThis computational framework enables seamless integration of diverse simulation methods used in WCM\nsuch as stochastic simulation algorithm (SSA), ordinary differential equations (ODE), flux balance\nanalysis (FBA), and logic-based approaches. These methods run simultaneously, not only for whole\npathways but also for subsets of reactions. Furthermore, we aim to enable dynamic switching between\nthe methods when beneficial.\nIs", + "laborHours": 12084.0, + "languages": [], + "name": "Whole cell simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/wcs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.4.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2020-05-13" + }, + "description": "Prediction of ligand-protein binding affinity from 3D atomic structures", + "laborHours": 2538.4, + "languages": [], + "name": "Fusion models for Atomic and molecular STructures", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FAST", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2020-05-13" + }, + "description": "This software is an implementation which is described in: \"Efficient Saliency Maps for Explainable AI\"\n(https://openreview.net/forum?id=ryxf9CEKDr). The toolkit is located in:\nhttps://mybitbucket.llnl.gov/projects/SAL/repos/smoe_lovi/browse. It is a set of of PyTorch related python\nscripts for extracting the what parts of an image are most salient to a deep neural network in an efficient\nmanner. This source will allow one to replicate the results in the paper referenced above.\nIs there", + "laborHours": 1170.4, + "languages": [], + "name": "Efficent XAI Information Saliency Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/fastcam", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2020-09-11" + }, + "description": "Modern processors offer a wide range of control and measurement features, such as performance\ncounters, power capping, and thermal control. These features are ultimately controlled through Model\nSpecific Registers (MSRs), which require elevated privileges for access. While this is often no problem on\nindividual workstations, it is a significant security risk on multi-user systems and large-scale compute\nclusters. The msr-safe kernel module provides controlled user-level access to MSRs through a\nwhitelisting mechanism.\nIs", + "laborHours": 2614.4, + "languages": [], + "name": "msr-safe", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/msr-safe", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.4.0" + }, + { + "contact": { + "email": "parkerpg@ornl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2023-04-13" + }, + "description": "ONCat is used to store information about neutron experiment data at SNS / HFIR. ONCat consists of an API with which various software clients can communicate to gain access to that information, as well as a web site (see landing page) which offers a way for experiment teams and instrument staff to easily view the metadata relating to experiments using just a web browser. The code is currently private and closed-source. Please contact oncat-support@ornl.gov for more information.", + "homepageURL": "https://oncat.ornl.gov", + "laborHours": 0.0, + "languages": [ + "Python", + "TypeScript" + ], + "name": "ONCat (ORNL Neutron Catalog)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://oncat.ornl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://oncat.ornl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2020-05-13" + }, + "description": "As power becomes an important resource to provision for modern HPC systems it becomes crucial to\nobtain deeper insights into application's power and thermal characteristics and to correlate application\ncontext with important system-level measurements. Existing profiling tools to monitor power and thermal\nmeasurements either operate at a granularity that is not fine enough to correlate with application-level\nevents that describe application context or are not equipped to sample application-level events\ntransparently. We introduce LibPowerMon, a lightweight, vendor-neutral user-level profiling framework to\nsimultaneously sample user-specified application events and system-level metrics at up to 1 kHz\nsampling intervals. At the application level, LibPowerMon provides a source-level phase markup interface\nto capture application context. At runtime level, LibPowerMon records MPI and OpenMP events and can\nbe extended to include other runtimes. At the system level, LibPowerMon samples power, thermal and\nrelevant metrics, and provides an extensible interface to system's control capabilities. In this release,\nLibPowerMon supports monitoring and control functionalities on the Intel, IBM Power9 and Nvidia Volta architectures.\n", + "laborHours": 0.0, + "languages": [], + "name": "LibPowerMon: A vendor-neutral system monitoring library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LibPowerMon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "Gecko is a C++ library for solving graph linear arrangement problems. Gecko orders the nodes of a\ngraph, representing data elements, that are connected by edges, representing affinity relations, with the\ngoal of minimizing a chosen functional of edge length. Gecko was primarily designed to minimize the\nproduct of edge lengths but can also be used to reduce bandwidth (maximum edge length) and 1-sum\n(sum of edge lengths), among others. Minimum-edge-product orderings generalize space-filling curve\norderings to geometryless graphs and find applications in data locality optimization, graph partitioning,\nand dimensionality reduction.\n", + "laborHours": 1216.0, + "languages": [], + "name": "gecko", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gecko", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "INQ is an engine for electronic structure calculations. INQ is implemented as a C++ library of components\ndesigned to build a parallel, portable code for electronic structure calculations, including ground state and\nexcited states. INQ is based on density functional theory (DFT). It can calculate ground state properties in\nDFT, and also excited states using time-dependent DFT (TDDFT) in real-time and linear-response. It\nimplements different approximations for the exchange and correlation part: semi-local functionals like\nLDAs, GGAs and metaGGAs, and hybrid functionals that are implemented through the ACE approach for\nfast execution.", + "laborHours": 92644.0, + "languages": [], + "name": "Electronic Structure Engine", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/inq", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-09-01" + }, + "description": "Linear Algebra Kernels and Graph Kernels are foundational technologies for scientific simulations. These foundational kernels need to run on several computer platforms that are popular for scientific simulations. KokkosKernels provides an implementation of different kernels that is portable to different architectures.", + "laborHours": 187370.4, + "languages": [], + "name": "Kokkos Kernels v. 0.9", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/kokkos-kernels", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2022-07-28" + }, + "description": "The most up-to-date location for Spack packages for Kokkos and Kokkos Kernels.", + "laborHours": 0.0, + "languages": [], + "name": "Kokkos Spack", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/kokkos-spack", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "Production-quality reference implementation of mdspan.", + "laborHours": 12068.8, + "languages": [], + "name": "Production-quality\u00a0mdspan\u00a0implementation", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/mdspan", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "Kokkos C++ Performance Portability Programming EcoSystem: Profiling and Debugging Tools. Performance profiling tools that can be optionally integrated into Kokkos-based applications and libraries.\n", + "laborHours": 115292.0, + "languages": [], + "name": "KokkosP Profiling Tools", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/kokkos/kokkos-tools/blob/master/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/kokkos-tools", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "The Kokkos Fortran Interop repository contains tools and interfaces which help interactions between Fortran portions of an applications and C++ portions using Kokkos.", + "laborHours": 20702.4, + "languages": [], + "name": "Fortran Language Compatibility Layer (FLCL)", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/kokkos-fortran-interop", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "This is the repository for kokkos/mdarray developed by the Exascale Computing Project (ECP). ", + "laborHours": 501.6, + "languages": [], + "name": "kokkos/mdarray", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/mdarray", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "This suite contains a number of kernel operations, called Parallel Research Kernels, plus a simple build system intended for a Linux-compatible environment. Most of the code relies on open standard programming models and thus can be executed on many computing systems.", + "laborHours": 57562.4, + "languages": [], + "name": "kokkos/Kernels", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/Kernels", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "A flexible package manager that supports multiple versions, configurations, platforms, and compilers.", + "laborHours": 133364.8, + "languages": [], + "name": "kokkos/spack", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/kokkos/spack/blob/develop/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/spack", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "Binding utilities used for MPI, OpenMP and GPUs. A script to set the process mask, OMP environment variables and CUDA environment variables to sane values if possible. Uses hwloc and nvidia-smi if available. Will preserve the current process binding, so it is safe to use with a queuing system or mpiexec.", + "laborHours": 228.0, + "languages": [], + "name": "kokkos/hpcbind", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/hpcbind", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "HPCG is a software package that performs a fixed number of multigrid preconditioned (using a symmetric Gauss-Seidel smoother) conjugate gradient (PCG) iterations using double precision (64 bit) floating point values.", + "laborHours": 2629.6, + "languages": [], + "name": "High Performance Conjugate Gradient Benchmark (HPCG)", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/kokkos/hpcg/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/hpcg", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2023-08-11" + }, + "description": "MPICH is a high-performance and widely portable implementation of the MPI-4 standard from the Argonne National Laboratory. This release has all MPI 4 functions and features required by the standard with the exception of support for the user-defined data representations for I/O.", + "laborHours": 425797.6, + "languages": [], + "name": "MPICH", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pmodels/mpich/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/mpich", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "The Open MPI Project is an open source Message Passing Interface implementation that is developed and maintained by a consortium of academic, research, and industry partners. Open MPI is therefore able to combine the expertise, technologies, and resources from all across the High Performance Computing community in order to build the best MPI library available. Open MPI offers advantages for system and software vendors, application developers and computer science researchers.", + "laborHours": 454890.4, + "languages": [], + "name": "OpenMPI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/open-mpi/ompi/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/open-mpi/ompi", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "CHAI is a library that handles automatic data migration to different memory spaces behind an array-style interface. It was designed to work with RAJA and integrates with it. CHAI could be used with other C++ abstractions, as well.", + "laborHours": 5320.0, + "languages": [], + "name": "CHAI v2.1", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/CHAI/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CHAI", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "Legion is a parallel programming model for distributed, heterogeneous machines.", + "laborHours": 433853.6, + "languages": [], + "name": "Legion", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/StanfordLegion/legion", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "Umap is a library that provides an mmap()-like interface to a simple, user- space page fault handler based on the userfaultfd Linux feature (starting with 4.3 linux kernel). The use case is to have an application specific buffer of pages cached from a large file, i.e. out-of-core execution using memory map.", + "laborHours": 3952.0, + "languages": [], + "name": "UMAP v2.0.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/umap", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "BOLT targets a high-performing OpenMP implementation, especially specialized for fine-grain parallelism. BOLT utilizes a lightweight threading model for its underlying threading mechanism. It currently adopts Argobots, a new holistic, low-level threading and tasking runtime, in order to overcome shortcomings of conventional OS-level threads. The current BOLT implementation is based on the OpenMP runtime in LLVM, and thus it can be used with LLVM/Clang, Intel OpenMP compiler, and GCC. More information about BOLT can be found at http://www.bolt-omp.org.", + "laborHours": 77763.2, + "languages": [], + "name": "BOLT: OpenMP over Lightweight Threads", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pmodels/bolt/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/bolt", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "fitzsimmonsm@ornl.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-18" + }, + "description": "Code to place polarized neutron reflectivity into bins of constant Qz with regard for Zeeman energy change to the spin-flip channel.\n The code is written as a Jupyter notebook. Example data are included as separate files (spin_down.txt and spin_up.txt). As a first step, run all cells in the notebook. Opportunities are identified for users to make their own choices for analysis of the data.\n The code is written to be a stand-alone operation on data collected from a pulse neutron source that have been previously normalized to the wavelength dependence of the incident beam spectrum, background subtracted, etc. The constant Qz binning (this code) is the last step to perform in the analysis (reduction) workflow. This step yields the the reflectivities for the four neutron spin cross-sections.\n A future intention is to create a version of this code that will be one module of many in the data analysis workflow.\n", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "Place polarized neutron reflectivity data in bins of constant wavevector transfer", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfitzsimmons44/reflectometry-analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "Argobots is a lightweight, low-level threading and tasking framework. ", + "laborHours": 32436.8, + "languages": [], + "name": "Argobots", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pmodels/argobots/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/argobots", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "The Global Extensible Open Power Manager (GEOPM) is a framework for exploring power and energy optimizations targeting high performance computing. 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You can specify how the data should be structured and whether it should undergo a grid transformation before you receive it, even when you know little about the structure of the stored data (i.e., its dimension order, grid, and domain).", + "laborHours": 9484.8, + "languages": [], + "name": "EzGet", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/EzGet", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "This is the repository for legacy lats library code developed at Lawrence Livermore National Laboratory (LLNL). 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Next we are going to provide a high level description of the APIs provided by Vcs.js including session management, data introspection and subsetting and plotting.\n", + "laborHours": 17176.0, + "languages": [], + "name": "vcs.js", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/vcs-js", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "This is the repository for distarray developed at Lawrence Livermore National Laboratory (LLNL). 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It has support for GitHub statuses and uses GitHub wiki for commit test logs.", + "laborHours": 304.0, + "languages": [], + "name": "Continous Improvement testbot (CI-bot)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/ci-bots", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "Metrics aka diagnostics for comparing models with observations or each other.", + "laborHours": 42286.4, + "languages": [], + "name": "uvcmetrics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + 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CARE expands that\nfunctionality, adding new features such as loop fusion capability and a portable interface for many\nnumerical algorithms. It provides all the basics for anyone wanting to write portable code.", + "laborHours": 9956.0, + "languages": [], + "name": "CHAI and RAJA Extensions", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CARE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.10" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "With function preserving projection (FPP), we aim to address high-dimensional data exploration\nchallenges common in many scientific applications. Instead of preserving the global or local geometric\nstructure of a dataset like traditional dimensionality reduction methods (e.g., principal component\nanalysis, t-stochastic neighborhood embedding), the proposed approach finds a linear projection that\nreveal interpretable (yet potentially nonlinear) pattern of the properties of interests defined on a highdimensional\ndomain (e.g., simulation yield defined on the input parameter space).\nThe key insight driving FPP is the fact that while non-linear embeddings are difficult to interpret, humans\nare highly skilled in understanding complex visual patterns. FPP lets users select the complexity of a\npattern they consider interpretable, allows to find a joint projection that explains multiple functions, and\nprovides a confidence statistic (akin to a p-value) indicating how salient the resulting pattern is. We\ndemonstrate the efficacy of the proposed method on several synthetic and scientific datasets for both\ncontinuous (regression) and discrete (classification) problems of interests and illustrate the scalability of\nFPP by finding an optimal projection for close to 40 gigabytes in around 10 minutes.\n", + "laborHours": 182.4, + "languages": [], + "name": "Function Preserving Projection", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/fpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "Devil Ray is a ray tracing library for high-order elements", + "laborHours": 38258.4, + "languages": [], + "name": "Devil Ray", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/devil_ray", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "C version of mpibind, an algorithm to map MPI tasks, threads, and GPU kernels to the hardware.", + "laborHours": 4468.8, + "languages": [], + "name": "C version of mpibind", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ac-mpibind", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "Hatchet is a Python-based library to analyze performance data that has a tree hierarchy (calling context\ntrees, call graphs, callpath traces, nested regions' timers, etc.).", + "laborHours": 29062.4, + "languages": [], + "name": "Hatchet", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/hatchet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-06-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A low-level OpenQASM benchmark suite for NISQ evaluation and simulation. Please see our paper for details.\nn this repository you will find a low-level and light-weighted benchmark suite based on IBM OpenQASM language (see spec). It collects commonly seen quantum algorithms and routines from various domains including chemistry, simulation, linear algebra, searching, optimization, arithmetic, machine learning, fault tolerance, cryptography, etc. QASMBench trades-off between generality and usability, covering the number of qubits ranging from 2 to 60K, and the circuit depth from 4 to 12M", + "laborHours": 4666.4, + "languages": [], + "name": "pnnl/QASMBench", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/QASMBench", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-06-05", + "metadataLastUpdated": "2023-04-27" + }, + "description": "(DG)2 is an impact analysis tool for electrical utilities to perform spatio-temporal analysis with solar and battery energy storage systems. The purpose of the tool is to help distribution utilities with identifying impacts and costs associated with locating a MW-scale solar farm and energy storage system at a certain location over other choices. This tool also assists utilities to assess the amount of reverse power flow at the transmission lines.", + "laborHours": 1854.4, + "languages": [ + "HTML", + "Python" + ], + "name": "(DG)2 (Distributed Generation for Distribution Grids) [SWR-18-63]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DG2", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-06-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python version of the AMES Wholesale Power Market Test Bed; no GUI. Previously hosted by Iowa State University; PNNL has assumed hosting. AMES existed in a non-version controlled and inconsistent form. PNNL added price-sensitive loads for transactive systems, with various other bug fixes and features.", + "laborHours": 2644.8, + "languages": [], + "name": "ames-market/psst", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ames-market/psst", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-06-10", + "metadataLastUpdated": "2020-06-10" + }, + "description": "RiskCat is designed to calculate probabilistic seismic hazard and risk at specified locations on the Earth's surface. 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It uses open source software, CCTop to identify potential guide RNA sequences, but adds value.", + "laborHours": 4408.0, + "languages": [], + "name": "guideRna and Sequence Region Extraction Tool (gRNA-SeqRET) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/grnadesigner/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-06-11", + "metadataLastUpdated": "2020-06-11" + }, + "description": "ScienceSearch-MI is a framework that generates metadata from scientific artifacts (papers, proposals, images) that is used to enable search.", + "laborHours": 11202.4, + "languages": [], + "name": "ScienceSearch Metadata Infrastructure (ScienceSearch-MI) v1.2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/sciencesearch/sciencesearch-mi/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-06-11", + "metadataLastUpdated": "2020-06-11" + }, + "description": "This gem contains methods to introduce variability to extend core OpenStudio SDK. 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The VOL connector, called H5Prov, transparently intercepts HDF5 calls and records operations at multiple levels, namely file, group, dataset, and data element levels.", + "laborHours": 0.0, + "languages": [], + "name": "Provenance VOL Connector for HDF5 (H5Prov) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://tonglinli@bitbucket.hdfgroup.org/scm/hdf5vol/provenance.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-06-11", + "metadataLastUpdated": "2020-06-11" + }, + "description": "This gem contains methods to introduce occupant-related variability to extend core OpenStudio SDK. 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The software also allows for embedding sensors for smart structures. The software relates to Battelle patents.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Ultrasonic Welding Bond Characterization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-06-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An easy to use tool for identifying energy saving retrofits for buildings.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "FEDS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "8" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-24", + "metadataLastUpdated": "2020-06-24" + }, + "description": "FRESCOX is a flexible, science-oriented, and general-purpose computer code that models direct\nreactions during the interaction of two atomic nuclei. FRESCOX is a coupled-channels program that can\nhave finite-range transfer interactions among any number of mass partitions, and any number of nuclear\nexcitations in each partition.", + "laborHours": 43532.8, + "languages": [], + "name": "Frescox", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Frescox", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-24", + "metadataLastUpdated": "2020-06-24" + }, + "description": "A flexible package manager that supports multiple versions, configurations, platforms, and compilers.", + "laborHours": 169312.8, + "languages": [], + "name": "Spack", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spack/spack", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-06-26", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Power Distribution Designing for Resilience Application (PowDDeR) is a software application to succinctly capture the capabilities of a power system to respond to disturbances, including natural or human (malicious or errors) caused disturbances. The software provides a measure of resilience for power systems.", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Power Distribution Designing For Resilience Application (powdder)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/PowDDeR", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-06-26", + "metadataLastUpdated": "2023-03-07" + }, + "description": "STOTS (Structured Threat Observation Tool Set) is a collection of tools that allow users in a test environment to create STIX v2 observable objects.", + "laborHours": 1140.0, + "languages": [ + "Python" + ], + "name": "Stots (structured Threat Observation Tool Set)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/STOTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-06-29", + "metadataLastUpdated": "2023-05-31" + }, + "description": "AMR-Wind is a massively parallel, block-structured adaptive-mesh, incompressible flow solver for wind turbine and wind farm simulations. 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The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2019 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2019 (v1.3.0.13520)" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-07-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A C++ Library for Influence Maximization", + "laborHours": 1687.2, + "languages": [], + "name": "pnnl/ripples", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ripples", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-07-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MPI implementation of Half-approximate Graph Matching", + "laborHours": 2568.8, + "languages": [], + "name": "Exa-Graph/mel", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exa-Graph/mel", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-08", + "metadataLastUpdated": "2020-07-08" + }, + "description": "Batoid is a c++ backed python optical raytracer. 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This software is no longer supported and users may use at their own risk.", + "laborHours": 90972.0, + "languages": [ + "Pascal" + ], + "name": "EPXMLPreprocessor", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EPXMLPreprocessor", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-07-13", + "metadataLastUpdated": "2023-11-02" + }, + "description": "MHKiT\u2122 -Python is a Python package designed for marine renewable energy applications to assist in data processing and visualization. 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", + "laborHours": 927.2, + "languages": [], + "name": "narrative-traefiker", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/narrative-traefiker", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This repository contains code for gathering and uploading KBase app errors from user job states in the catalog, workspace and execution engine. This repository is run through a cron job every night. The main function in the repo is get_errored_apps_EE2. The cron job calls the upload_errorlogs function that calls the main get_errored_apps_EE2 function.", + "laborHours": 684.0, + "languages": [], + "name": "KBase Error Logging", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/ErrorLogging", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "Creates indexes for Elasticsearch and ArangoDB from genomic data on KBase. This is a background service that listens to events from the KBase Workspace and automatically generates graph data and search indexes to enrich the workspace object data. It consumes event from a Kafka topic and sends data into ArangoDB and Elasticsearch. It is designed to have the service replicated in Rancher. Be sure to partition the topic to at least the number of running workers.", + "laborHours": 541758.4, + "languages": [], + "name": "KBase Index Runner/Knowledge Engine", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/index_runner_deluxe", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "Global config and spec files for the KBase elasticsearch stack.", + "laborHours": 349.6, + "languages": [], + "name": "KBase Elasticsearch Config", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/index_runner_spec", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "Common Java jar files needed across KBase.", + "laborHours": 1170.4, + "languages": [], + "name": "kbase/jars", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/jars", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "The Workspace Service (WSS) is primarily a language independent remote storage and retrieval system for KBase typed objects (TO) defined with the KBase Interface Description Language (KIDL).", + "laborHours": 75741.6, + "languages": [], + "name": "KBase Workspace Service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/workspace_deluxe", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "Specifications and config for the KBase Relation Engine. This repo holds the stored queries, schemas, and migrations for the relation engine graph database service. These specifications are used by the Relation Engine API.", + "laborHours": 3891.2, + "languages": [], + "name": "Relation Engine Spec", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/relation_engine_spec", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is a small HTTP interface around KBase's elasticsearch indexes.\n\n", + "laborHours": 5730.4, + "languages": [], + "name": "Search API", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/search_api2", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is the repository for \"condor-worker requirements\" developed by KBase.", + "laborHours": 592.8, + "languages": [], + "name": "condor-worker requirements", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/condor-worker", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "A simple plugin to view KBase types, type modules, and function specifications.", + "laborHours": 9393.6, + "languages": [], + "name": "Typeview KBase UI Plugin", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-typeview", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "Client side implementation of auth2 ui components. Includes login, logout, signup forms; account management, ID linking.\n\n", + "laborHours": 28910.4, + "languages": [], + "name": "KBase UI Auth2 Client", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-auth2-client", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is a kbase-ui plugin providing access to the KBase app catalog for both users, developers, and system admins.", + "laborHours": 19972.8, + "languages": [], + "name": "KBase UI Plugin - SDK Catalog Tool", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-catalog", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is the repository for \"KBase UI Dashboard\" developed by KBase.", + "laborHours": 10579.2, + "languages": [], + "name": "KBase UI Dashboard", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-dashboard", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This directory contains all current KBase Javascript clients, as of April 14, 2016. These are not likely to change very often, and the generation process to get the whole batch is not straightforward in all cases, so they've been included here. The clients are updated in src/kbase-clients by replacing the appropriate client file with the updated one from the home project. Before being used they must be prepared and placed into the dist directory under kb/service.", + "laborHours": 24365.6, + "languages": [], + "name": "KBase API clients", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-service-clients-js", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "savaraa@ornl.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-09-08" + }, + "description": "Parameter estimation for complex physical problems often suffers from finding 'solutions' that are not physically realistic. The CheKiPEUQ software provides tools for finding physically realistic parameter estimates.and CheKiPEUQ provide tools for making graphs of the parameter positions within parameter space as well as plots of the final simulation results.\n\nThe primary purpose of the CheKiPEUQ software is to enable more physically realistic parameter estimation from comparing simulations to experiments. Specifically, when prior knowledge is available about the region of parameter space which is physically realistic and when the level of uncertainty from experiment can be estimated. The software is intentionally general and can be used for almost any type of simulation. The software is made in a user friendly manner so that users can simply enter the required data and then run the program, following guidelines provided by the authors along with some trial and error. Examples are provided. Users do not need to understand the methodology that will be namedi in the following sentences. While CheKiPEUQ can be used for conventional parameter estimation and other uses, the primary uses for CheKiPEUQ are: 1) Bayesian Parameter Estimation, 2) Bayesian Model Discrimination, 3) Bayesian Design of Experiments. For more information see the project website, documentation, examples, and related publications.", + "laborHours": 109455.2, + "languages": [ + "Python" + ], + "name": "CheKiPEUQ", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdityaSavara/CheKiPEUQ", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is the repository for \"kbase-ui-plugin-dataview\" developed by KBase. ", + "laborHours": 49719.2, + "languages": [], + "name": "kbase-ui-plugin-dataview", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-dataview", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This repo contains a data search plugin for the KBase UI.", + "laborHours": 13892.8, + "languages": [], + "name": "KBase UI Plugin - Data Search", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-data-search", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "A kbase ui plugin for searching JGI JAMO data and copying it to a user's KBase staging area.", + "laborHours": 12296.8, + "languages": [], + "name": "JGI Search Plugin", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-jgi-search", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "A kbase-ui plugin which provides a view of a user's notification feeds.", + "laborHours": 7934.4, + "languages": [], + "name": "KBase UI Feeds Plugin", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-feeds", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This kbase-ui plugin is responsible for displaying a user profile - either the current user's profile if the path is #people or #user, or a given user profile if the path is #people/USERNAME or #user/USERNAME.", + "laborHours": 107737.6, + "languages": [], + "name": "User Profile Plugin", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-user-profile", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This repository contains code for gathering and uploading KBase system metrics from Condor API such as memory, disk and cpu usage, as well as job and queue information. This repository is run every hour through a cron job. The main function of the this repo is the 'get_system_report' function located in the 'get_system_reports' file. This function calls 'get_report machines' and 'get_report_jobs', because System Metrics is composed of information for Condor jobs - running and idle - and KBase machine information. The 'get_report_jobs' function calls a job function 'get_job_info' from the file 'calculate_queue_resources'. Within the queue resources file the 'get_job_info' function is main.", + "laborHours": 334.4, + "languages": [], + "name": "KBase System Metrics", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/SystemMetrics", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-27" + }, + "description": "Compiler optimizations can alter significantly the numerical results of scientific computing applications.\nWhen numerical results differ significantly between compilers, optimization levels, and floating-point\nhardware, these numerical inconsistencies can impact programming productivity. pLiner is a framework\nthat helps programmers identify locations in the source code that are highly affected by compiler\noptimizations. pLiner uses a novel approach to identify such code locations by enhancing the floatingpoint\nprecision of variables and expressions. Using a guided search to locate the most significant code\nregions, pLiner can report to users such locations at different granularities, file, function, and line of code.", + "laborHours": 18194.4, + "languages": [], + "name": "pLiner", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pLiner", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-27" + }, + "description": "mpibind is a memory-driven algorithm to map parallel hybrid applications to the underlying hardware\nresources transparently, efficiently, and portably. There are two fundamental aspects of this algorithm.\nFirst, unlike existing mappings, its primary design point is the memory system. Compute elements are\nselected based on the identified memory components and not vice versa. Second, it embodies a global\nawareness of hybrid programming abstractions as well as heterogeneous devices.", + "laborHours": 23590.4, + "languages": [], + "name": "A memory-driven mapping algorithm for heterogeneous systems", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mpibind", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-27" + }, + "description": "ZFP is a floating-point compression format gaining traction in high-performance computing applications. A\nsoftware implementation has demonstrated the ability to reduce data movement across communication\nchannels and to reduce the footprint of floating-point arrays in memory. Nevertheless, any benefit in\nperformance is limited to the spare compute cycles available before reaching bandwidth limitations. A\nhardware implementation of ZFP has the potential to substantially improve HPC application performance.\nHardware compression speedup over software alone on a single CPU core ranges from 15x for 1-D\narrays to over 200x for 3-D arrays.\nThe implementation of ZFP is sourced in SystemC to facilitate its evaluation in various architectures. The\nencode pipeline consists of several modules. Uncompressed blocks of floating-point numbers in IEEE\nformat flow into the pipeline in a stream and a compressed bitstream flows out from the pipeline. The\ndecode pipeline is the inverse of the encode pipeline. A modular design enables formats other than IEEE\n(such as posits) to be considered with minor adaptations. Best performance will be realized from the\nhardware ZFP unit when batches of blocks are processed at a time. The implementation supports 1-D, 2-\nD and 3-D blocks of floating-point numbers.\nThe hardware implementation of ZFP has been validated with the software implementation of ZFP. C++\ntemplate parameters are used to specify the bit width of floating-point numbers and the array dimension\nof the encoder. A test bench program has been created with several test cases, some with continuous\ndata that is ideal for ZFP, and others with extreme cases containing numbers near or at the maximum or\nminimum values supported by the number format.", + "laborHours": 2766.4, + "languages": [], + "name": "ZFP Hardware Implementation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/zhw.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.5" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-30" + }, + "description": "This Python package is developed for converting GROMACS files to ddcMD inputs. The code makes it\neasier for ddcMD users to convert GROMACS MD simulations into ddcMD. It is used in the MuMMI\nframework for multiscale MD simulations.", + "laborHours": 7812.8, + "languages": [], + "name": "ddcMD converter", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ddcMDconverter", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.3" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-27" + }, + "description": "ddcMD is a general purpose molecular dynamics (MD) code that supports MPI parallelism. MD codes are\nused for simulation of particles systems and capture all the many-body effects of the underlying particle\npotential that defines the physical system. Though MD can be used to model systems from the\nsubatomic to astrological length scales ddcMD is mainly focused on the atomic scale length scale, In\nthis release of ddcMD the support will be mainly for systems using the coarse-grain Martini potential, a\nparticle potential for biological systems.", + "laborHours": 38197.6, + "languages": [], + "name": "ddcMD.os", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ddcMD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-28", + "metadataLastUpdated": "2020-07-28" + }, + "description": "Logic in Memory Emulator (LiME) is a hardware/software tool specially designed for memory system evaluation and experiment. Emerging memories display a wide range of bandwidths, latencies, and capacities, making it challenging for the computer architect to navigate the design space of potential memory configurations, and for the application developer to assess performance implications of using such memories. With the LiME framework, architectural ideas can be prototyped in great detail yet with sufficient performance to support realistic evaluation on long running applications. LiME consists of two fundamental components: 1) the hardware and OS infrastructure for the emulator, and 2) a suite of benchmark applications to assist in characterizing the performance of current and future computer architectures. Some of the applications have been collected from other open source projects.\nUses:\nLogging, replay and analysis of an application's memory behavior Evaluate impact of emerging memory technology on application performance. Emulate complex memory interactions in whole applications orders of magnitude faster than software\nsimulation. Emulate acceleration hardware co-located with the memory subsystem.\nFeatures:\nCapture and log external memory accesses to a separate off-chip memory device without affecting application execution.\nMemory traces include the address, length, timestamp, and optionally the data for each transaction. Captured trace data can be saved to an SD card for off-line analysis.\nConfigure a wide range of memory latencies in sub-nanosecond increments that encompass highbandwidth and storage class memories.\nSpecify regions of interest (ROI) in applications to reduce the amount of trace data captured for analysis. Currently supports execution on Xilinx Zynq SoC which integrates an ARM processor with FPGA logic on a single device.\nApplications can be run under Linux or in bare metal mode on the ARM cores.", + "laborHours": 32041.6, + "languages": [], + "name": "Logic in Memory Emulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lime.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.2" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is a plugin for kbase-ui, which allows a KBase user to browse, view, and manage Organizations.", + "laborHours": 27785.6, + "languages": [], + "name": "KBase UI Plugin: Organizations", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-organizations", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "The job runner is started by the batch/resource manager system and is the component that actually executes the SDK module. 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This plugin provides a single top level component designed to serve both regular users and administrators. It's primary purpose is to allow the user to view their current and past jobs. Administrative users can use it to inspect jobs for all users.", + "laborHours": 8056.0, + "languages": [], + "name": "kbase-ui-plugin-job-browser2", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-job-browser2", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "Narrative method specs repo for use in the -ci (or other nonproduction) environments.", + "laborHours": 592.8, + "languages": [], + "name": "narrative_method_specs_ci ", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/narrative_method_specs_ci", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is the repository for \"NarrativeViewers\" developed by KBase. ", + "laborHours": 2508.0, + "languages": [], + "name": "NarrativeViewers", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/NarrativeViewers", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "The KBase SDK is a set of tools for developing KBase Apps that can be dynamically registered and run on the KBase platform. Apps are grouped into modules that include all code, dependencies, specification files, and documentation needed to define and run Apps in the KBase Narrative interface.", + "laborHours": 23484.0, + "languages": [], + "name": "KBase SDK", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kb_sdk", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "Biochemistry table plugin for KBase.", + "laborHours": 942.4, + "languages": [], + "name": "KBase UI Plugin - biochem Search", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-biochem-search", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "Utilities for reproducible imports into the Relation Engine from various data sources.", + "laborHours": 3891.2, + "languages": [], + "name": "Data import scripts for the Relation Engine (KBase)", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/relation_engine_importers", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This repo holds the source code for Sphinx documentation describing the KBase Software Development Kit.", + "laborHours": 1079.2, + "languages": [], + "name": "KBase SDK Documentation", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kb_sdk_docs", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "fitzsimmonsm@ornl.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-30" + }, + "description": "Code to map X-ray reflectivity data from real space to reciprocal space. \n The code is written as a Jupyter notebook. Example data are included as a separate file (example_data.csv). These data were collected on a Panalytical XRD system. As a first step, run all cells in the notebook. Opportunities are identified for users to make their own choices for choosing the boundaries of the region of interest to estimate background. A simple algorithm is used to estimate background from the outer regions of the data collection region, interpolating the result inside the region of interest. The background is removed and then the data mapped to Qx-Qz (reciprocal space) coordinates. The results are written as NumPy binary and Matlab formatted files.", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "Code to map Xray reflectivity data from real space to reciprocal space ", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfitzsimmons44/Xray-reflectometry", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "fitzsimmonsm@ornl.gov" + }, + "date": { + "created": "2020-07-31", + "metadataLastUpdated": "2020-07-31" + }, + "description": "A collection of modules or tools to produce reflectivity profiles from data acquired with unpolarized and polarized neutron beams using the BL4A (MagRef) instrument at the Spallation Neutron Source.\n\nThe Jupyter notebook approach offers transparency to the user on what is done with the data, and once the event mode data are stored as NumPy binary files empowers the user to perform the steps from their own laptop without the need for Mantid. The notebook offers two options for background subtraction, applies corrections for the wavelength dependence of the polarizer and flipper efficiencies, accounts for Zeeman energy splitting of the spin-flip channels, Qz-bins the data along contours of constant Qz, propagates errors and writes results in text format suitable for analysis with tools such as GenX.", + "laborHours": 1687.2, + "languages": [ + "Python" + ], + "name": "Tools to perform data reduction of time-of-flight data taken on BL4A (MagRef)\u2014a Jupyter notebook approach ", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfitzsimmons44/BL4A_MagRef_Data_Reduction_Tools", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-07-31", + "metadataLastUpdated": "2024-12-19" + }, + "description": "The calculator calculates levelized cost of energy (LCOE) for photovoltaic (PV) systems based on cost, performance, and reliability inputs for a baseline and a proposed technology. The user can choose inputs and watch the effect on LCOE to determine whether a proposed technology is cost-effective, perform trade-off analysis among different technology options, and do break-even analysis of cost or performance.", + "laborHours": 26204.8, + "languages": [ + "JavaScript" + ], + "name": "Comparative PV LCOE Calculator (Comparative Photovoltaic Levelized Cost of Energy Calculator) [SWR-20-86]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PVLCOE", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. 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It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2018 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2018" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. 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This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2017 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2017" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. 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This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2016 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2016" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. 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"email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "Type transformation specifications for the KBase search system. This repo contains specifications for how Workspace objects will be indexed in various KBase environments. Each environment(prod, next, appdev and ci) has a dedicated subdirectory with a set of type and typemapping yaml files.", + "laborHours": 608.0, + "languages": [], + "name": "Search Type Specification and Mapping", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/search_index_specs", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "Utility to simplify running applications in docker containers.", + "laborHours": 410.4, + "languages": [], + "name": "dockerize", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/dockerize", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "KBase apps are analysis tools that you can use in KBase. Apps interoperate seamlessly to enable a range of scientific workflows (see figure below). Some of the apps were written by KBase scientists and developers; others are third-party tools that were integrated into KBase with our Software Developer Kit (SDK). The number of apps available in KBase will increase rapidly as members of the community use our SDK to integrate their analysis tools into the KBase platform. The KBase App Catalog lists all of the currently available apps. This page is made so that KBase Apps show up on web searches.", + "laborHours": 5973.6, + "languages": [], + "name": "KBase App Catalog Static Page", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/KbaseAppCatalogStatic", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "The file ingest tool for Logstash and Elasticsearch, with KBase specific configuration.", + "laborHours": 15.2, + "languages": [], + "name": "filebeat", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/filebeat", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vossjm@ornl.gov" + }, + "date": { + "created": "2020-08-07", + "metadataLastUpdated": "2020-09-08" + }, + "description": "greg(g)d - Global runtime for eBPF-enabled gathering (w/ gumption) daemon\n\nRecently the linux kernel has added support for low-level kernel monitoring and\nprofiling through a in-kernel virtual machine. The tooling around these new\nfeatures (the extended Berkley Packet Filter or eBPF for short) is not mature\nand is difficult to use. Benefits from eBPF are especially hard to realize\nwhile trying to do large scale deployments and integrate with existing metric\nanalysis stacks. A tool was needed to enable loading and collecting data from\neBPF programs on large scale HPC systems.\n\nGiven the problems above it was obvious we needed some wrapper program to\ncompile, load, and collect data from eBPF programs running in the kernel. This\ntool needed to be lightweight without a heavy set of dependencies, relatively\nstable between different kernel versions, and integrate nicely with existing\nwidely used metric collection tools.\n\nWe wrote a program that wraps the eBPF tooling and sends data to our metric\ngathering tool. eBPF programs are either compiled using the host compiler\nstack, or loaded in the kernel directly from an object file. These programs are\nthen attached to the system calls that we want to profile. Whenever these\nsystem calls are run, the eBPF program collects information of interest and\nwrites that to memory. Our wrapper program polls these memory locations, reads\nand formats the data, then sends the information to a local unix socket. Our\nother monitoring tools are configured to read from that socket and send it to\nthe rest of our metric monitoring stack for analysis.", + "laborHours": 1033.6, + "languages": [ + "Go" + ], + "name": "Greggd", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/greggd", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-10", + "metadataLastUpdated": "2020-08-10" + }, + "description": "This is the repository for traefik_poc developed by KBase. ", + "laborHours": 60.8, + "languages": [], + "name": "traefik_poc", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/traefik_poc", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-10", + "metadataLastUpdated": "2020-08-10" + }, + "description": "Docker image that can be used to initialize a ceph cluster (until the ceph docker images catch up).", + "laborHours": 197.6, + "languages": [], + "name": "ceph_initialize", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/ceph_initialize", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-10", + "metadataLastUpdated": "2020-08-10" + }, + "description": "Store and serve static assets for KBase frontends.", + "laborHours": 106.4, + "languages": [], + "name": "KBase Static Assets for UI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/ui-assets", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-10", + "metadataLastUpdated": "2020-08-10" + }, + "description": "htcondor-restd fork with auth and dockerfile. REST-based API for HTCondor, using the Python bindings. Currently allows read-only queries for jobs (in-queue and historical), configuration, and machine status.", + "laborHours": 440.8, + "languages": [], + "name": "condor_restd", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/htcondor-restd", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-10", + "metadataLastUpdated": "2020-08-10" + }, + "description": "A KBase service for dynamically listing and accessing specifications and documentation for Narrative methods, apps, types, and categories of methods/apps. 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Note that (1) the prognostic CO2\nconfiguration of E3SM has not been scientifically validated, and (2) the regridding of emission\nfiles as currently implemented is not mass-conserving and is intended as a temporary workaround.\nWe do not advise using E3SMv1.1 for fully-coupled carbon cycle simulations where mass conservation\nis critical, but it is suitable for enabling use of the 3D CO2 tracer for diagnostic and testing purposes.\n\nSeveral bugs found after v1.0 have been fixed in this tag and changes made to default settings, including:\n EAM: adding limiters to avoid bad extrapolation in RRTMG, fixing an error in the calculation of NIR\n reflectance that affects cloud fields derived from MODIS simulator.\n ELM: fixing surface water and lakes, increasing the land field name size, fixing a memory leak in\n ELM CNStateType, fixing a snow compaction bug that was resulting in sporadic unphysical snow depths,\n adding a water budget in the land model (and fixing a water conservation error)\n MPAS-O: preventing thermo energy conservation errors by lowering the permitted surface flux error\n in the mushy layer picard iteration to 0.9*ferrmax, fixing a small bug in marine BGC,\n MPAS-SeaIce: Turning off mpas-seaice history files by default\n MOSART: Replacing the low-res (half-degree) MOSART file\n\nIn addition, the budget output has been turned on by default for any fully coupled case, and CIME was\nmodified to remove a bad term from E3SM water budgets. The CCSM_CO2_PPMV is now set correctly in BGC cases. A bugfix for the IEFLX output is included and the timestep for the EC60to30 mesh has been\nupdated. Finally, a number of minor bugfixes and technical improvements have been introduced in the\nEAM, ELM and MPAS-Ocean models.\n\nMachine updates for cascade, edison, eos, cori are included.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v1.1", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v1.1.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v1.1.0" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2020-08-25", + "metadataLastUpdated": "2020-08-25" + }, + "description": "Second release of E3SM v1.1\n\nThis update to v1.1.0 includes additional output variables and small changes to the\nECA configurations. 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In the present version of KSOME, the analytical expression required to calculate defect interaction radii are inputted via a text file. However, the ability to parse mathematical expressions from a text file can be extended to input the analytical expression to calculate other defect properties; including the expressions to calculate the change in the migration barriers of mobile defects due to long-range interaction with extended defects ", + "laborHours": 8968.0, + "languages": [ + "C++" + ], + "name": "Kinetic Simulations of Microstructural Evolution (KSOME)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/giridharnandipati/ksome", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2024-03-11" + }, + "description": "Realistic data-driven renewable energy scenarios for stochastic grid operation problems", + "laborHours": 39200.8, + "languages": [ + "MATLAB", + "Python", + "Jupyter Notebook", + "Tex" + ], + "name": "powerscenarios [SWR-20-50]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/powerscenarios", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "The JavaScript Data API is, like the Python API, custom wrapper code on top of the JavaScript library generated by Thrift. 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A new semver tag is generated, and the repo is merged into the canonical repo (KBase). 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The USGS DEM is a great resource; however, in order to be useful for automotive and traffic engineering applications, significant interpolation and filtering is required to achieve an accurate representation of gradient on the roadway. GradeIT employs a two-dimensional interpolation to approximate elevation at a point on the road from the nearest nodes in the DEM. Then, GradeIT applies multiple filtering techniques to smooth the elevation profile to a realistic road topology. Finally, road grade is derived from the elevation profile and returned as the primary output.", + "laborHours": 288.8, + "languages": [ + "Python" + ], + "name": "GradeIT (Road Grade Inference Tool)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/gradeit", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "Compression-based distance (CBD) is a simple, rapid, and accurate method to efficiently assess differences in microbiota samples. 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The distance has a value with a minimum of 0 meaning the communities are the same and a maximum of 1 meaning the communities are completely different.", + "laborHours": 729.6, + "languages": [], + "name": "Compression-Based Distance", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/cbd", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"Central Store Quality Control\" developed by KBase. 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", + "laborHours": 4605.6, + "languages": [], + "name": "protein_info_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/protein_info_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This module provides a method to work with the Inferelator algorithm from the Baliga Lab at the Institute for Systems Biology. The Inferelator algorithm infers regulatory networks from gene expression data, and takes as input cMonkey biclusters, a list of regulators, and expression data.", + "laborHours": 13148.0, + "languages": [], + "name": "Module Inferelator Version 1.0", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/inferelator", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This service wraps the ERDB software and allows querying the CDS via the ERDB using typecompiler generated clients rather than direct Perl imports of the ERDB code.", + "laborHours": 136.8, + "languages": [], + "name": "EDRB Service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/erdb_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "A module for sequence similarity service.", + "laborHours": 197.6, + "languages": [], + "name": "sim_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/sim_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "KBase service code for RDP. A classifier of rRNA amplicon data contributed by the RDB Project. Deploys both client and service.", + "laborHours": 608.0, + "languages": [], + "name": "RDPTools Services", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/rdptools", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "The KBase Data Importer allows users to upload data for use in KBase.", + "laborHours": 6064.8, + "languages": [], + "name": "KBase DataImporter v1.0", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/uploader", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This service has methods for finding Protein Structure Databank (PDB) entries with sequences similar to a KBase protein sequence, specified by either a MD5 id or a feature or coding sequence id. There are two functions, one for searching by MD5, and the other searching by feature ID (FID). ", + "laborHours": 1140.0, + "languages": [], + "name": "protein_structure_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/protein_structure_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "Simple wrappers around fba tools.", + "laborHours": 258.4, + "languages": [], + "name": "simple_fba", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/simple_fba", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "The code found in this repository contains the client and server code for the jnomics-manager. 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The user is able to specify different monomer pairings and degree of polymerization for different polymer chains.", + "laborHours": 1216.0, + "languages": [ + "Python", + "Python" + ], + "name": "m2p (Monomers to Polymers)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/m2p", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-09-24", + "metadataLastUpdated": "2020-09-24" + }, + "description": "This python toolkit has been developed to automate 3D segmentation of X-ray Computed Tomography (CT) data using convolutional neural networks - an AI methodology. 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It can also be used to develop new Monte Carlo models that hook to the existing solver and parallel infrastructure provided by the code.", + "laborHours": 165102.4, + "languages": [ + "C++", + "C" + ], + "name": "Stochastic Parallel PARticle Kinetic Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spparks", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-09-25", + "metadataLastUpdated": "2025-02-10" + }, + "description": "This software provides a collection of algorithms, an API, and a functional Web UI for the Distributed Wind\u2019s WindWatts project. DW WindWatts is a DOE WETO-funded project aimed at the development of tools to supporting the distributed wind industry, particularly with respect to siting and resource assessment. The computational framework and the back-end API are powering the easy to use front-end services available at: https://windwatts.nrel.gov.\n\nhttps://github.com/NREL/dw-tap-api; https://github.com/NREL/dw-tap; https://github.com/NREL/windwatts-data\n\nFor reference, this software was previously known as DW TAP Computational Framework.", + "laborHours": 9895.2, + "languages": [ + "JavaScript", + "Python" + ], + "name": "WindWatts Computational Framework and Web UI [SWR-20-100]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dw-tap-api", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-25", + "metadataLastUpdated": "2020-09-25" + }, + "description": "ATS is a Python-language program for automating test suites for software programs that do not interact with thier users, such as scripted scientific simulations. ATS features a decentralized approach especially suited to larger projects. In its multinode mode it can utilize many nodes of a cluster in order to do many test in parallel. It has features for submitting longer-running tests to a batch system and would have to be customized for use elsewhere.", + "homepageURL": "https://sourceforge.net/projects/ats-automatedtestingsystem", + "laborHours": 4544.8, + "languages": [ + "None" + ], + "name": "Automated Testing System", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/ats-automatedtestingsystem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "gord.stephen@nrel.gov" + }, + "date": { + "created": "2020-09-28", + "metadataLastUpdated": "2023-04-24" + }, + "description": "The Electricity Markets Investment Suite - Competitive Equilibrium (EMIS-CE) model is an optimization-based power system investment model developed at NREL. It attempts to approximate a market-driven investment equilibrium outcome under the assumption of idealized or perfect competition (e.g. no participants are able to exert market power or leverage exclusive cost advantages) and uncertain future conditions.", + "laborHours": 1079.2, + "languages": [ + "Julia" + ], + "name": "EMIS-CompetitiveEquilibrium.jl [SWR-19-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMIS-CompetitiveEquilibrium.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The construction of megaprojects has consistently demonstrated challenges for project managers in regard to meeting cost, schedule, and performance requirements. Megaproject construction challenges are common place within megaprojects with many active projects in the United States failing to meet cost and schedule efforts by significant margins. Currently, engineering teams operate in siloed tools and disparate teams where connections across design, procurement, and construction systems are translated manually or over brittle point-to-point integrations. The manual nature of data exchange increases the risk of silent errors in the reactor design, with each silent error cascading across the design. These cascading errors lead to uncontrollable risk during construction, resulting in significant delays and cost overruns. Deep Lynx allows for an integrated platform during design and operations of mega projects.", + "laborHours": 119244.0, + "languages": [ + "JavaScript" + ], + "name": "Deep Lynx: Digital Engineering Integration Hub", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2024-06-04" + }, + "description": "HERON is a modeling toolset and plugin for RAVEN to accelerate stochastic technoeconomic assessment of the economic viability of various grid-energy system configurations, especially with application to electrical grids and integrated energy systems (IES). The frameworks enabling this toolset are INL's RAVEN and its TEAL plugin. The toolset includes automated RAVEN workflow generation tools for performing stochastic analysis and optimization driven by technoeconomic factors. The workflows generated employ RAVEN for parametric or optimizing study of grid component characteristics, and again for stochastic sampling of regulated and deregulated markets, load, and weather histories. The toolset further provides methods for economically-optimal dispatch of system components given the stochastic samples of market, load, and weather histories. The toolset allows assembling of existing and new models through the RAVEN interface to the Modelica process modeling language.", + "laborHours": 14272.8, + "languages": [ + "Python" + ], + "name": "HERON", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HERON", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-13" + }, + "description": "TEAL is a financial performance calculator plugin for the RAVEN code, framework, resolving around the computation of Net Present Value and associated financial metrics. TEAL can make use of inflation rates, taxation, escalation factors, capital expenditure economy of scale scaling factors. The unique feature of TEAL is the capability to be linked with RAVEN external models and build corresponding cash flows using the variables computed by those external models. In addition to be able to use the capability to generate cash flows derived from complex physical models generated by RAVEN, another distinctive feature of TEAL is the capability to provide financial risk/probabilistic metrics that can empower RAVEN to perform optimization/analysis driven by financial risk augmentations. Optimization, robust optimization, parametric studies, large parallel simulations, sensitivity analysis, data mining, etc. are just some of the capabilities that can be leveraged.", + "laborHours": 4788.0, + "languages": [ + "Python" + ], + "name": "TEAL", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/TEAL", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Field Landscape Decision Support (FieLDS) is a decision support tool that assists agricultural producers and farm managers in selecting parts of the field that can be converted to bioenergy plants, like perennial grasses, from the conventional use, like corn or soybean growth. That conversion of parts of the field is done based on the specific landscape properties and the agricultural producer\u2019s priorities. The decision support tool generates a map of the field layout and spatially marks where to place each plant based on the spatial input from the user. Also, the user selects which priorities (sustainability indicators) are most relevant to them in their decision-making. By allowing the user to set the weights among the priorities, the tool empowers the user to generate field designs specific to their needs instead of imposing the developer\u2019s set of priorities, and increases the transparency of the decision process.", + "laborHours": 152.0, + "languages": [ + "Python" + ], + "name": "FieLDS", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/FieLDS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-13" + }, + "description": "WiiBin is a framework to determine architecture of an unknown binary and locate opcode sections within the same binary via supervised machine learning.", + "laborHours": 486.4, + "languages": [ + "Python" + ], + "name": "WiiBin", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/WiiBin", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-13" + }, + "description": "Structured Threat Automated Response (STAR) is a script that creates a python run-time for automated response action included in the Structure Threat Information Expression (STIX) Course of Action object. This script can parse a valid STIX json file and execute the included Course of Action.", + "laborHours": 76.0, + "languages": [ + "Python" + ], + "name": "STAR", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/STAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "yunl68@illinois.edu" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2020-09-29" + }, + "description": "BioCro is a model that predicts plant growth over time given crop-specific parameters and environmental data as input.\n\nIt uses models of key physiological and biophysical processes underlying plant growth (Humphries and Long, 1995), and has previously been used for predicting biomass yield and leaf area index of switchgrass, miscanthus, sugarcane and willow (Miguez et al., 2009; Jaiswal et al. 2017).\n\nThe latest version has been redesigned to closely represent a dynamical system, which makes it easier to implement new crops and provides more accurate simulations. Parameters to model energy sorghum have also been added.", + "laborHours": 10913.6, + "languages": [], + "name": "BioCro", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ebimodeling/biocro/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ebimodeling/biocro", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-11-05" + }, + "description": "JEGA is a software package that implements a multi-objective genetic algorithm (MOGA) for solution to multi-objective optimization problems (MOPS) and a single objective genetic algorithm (SOGA) for solution to single objective optimization problems (SOPS). JEGA is highly configurable and provides a rich set of algorithmic components for tailored optimization. It has been used successfully on many problems by users both internal and external to Sandia. By employing object-oriented design to implement abstractions of the key components making up the algorithms, JEGA provides a flexible and extensible problem-solving environment for design and performance analysis of computational models.", + "homepageURL": "https://dakota.sandia.gov", + "laborHours": 3988282.4, + "languages": [ + "C++ compiler" + ], + "name": "JEGA V 2.3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://dakota.sandia.gov/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-10-08" + }, + "description": "Silo is a library for reading and writing a wide variety of scientific data to binary, disk files. The files Silo produces and the data within them can be easily shared and exchanged between wholly independently developed applications running on disparate computing platforms. Consequently, Silo facilitates the development of general purpose tools for processing scientific data. One of the more popular tools that process Silo data files is the VisIt visualization tool.", + "homepageURL": "https://wci.llnl.gov/simulation/computer-codes/silo", + "laborHours": 110929.6, + "languages": [], + "name": "Silo", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://wci.llnl.gov/simulation/computer-codes/silo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-09-30" + }, + "description": "LULESH v1.0 is a 3D unstructured Lagrange hydrodynamics simulation written specifically to solve a standard analytical test problem, known as the Sedov problem. In this problem, a quantum of energy is deposited into a gas and propagates through the gas over time.", + "laborHours": 2933.6, + "languages": [ + "None" + ], + "name": "Livermore Unstructured Lagrange Explicit Shock Hydrodynamics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/lulesh", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-10-08" + }, + "description": "BRAID is a rewriting system for translating abstract intermediate descriptions into light-weight, \"pay only for what you need\" middleware wrappers. Initial capabilities will focus on language interoperability, remote method invocation (RMI), and interface contract enforcement wrappers from Scientific Interface Definition Language (SIDL) specifications. Language interoperability will be provided for software written in C, C++, Fortran, Java, and Python, as was done with Babel, but also a subset of PGAS/HPCS languages, such as Chapel, UPC, and X10. Interface contract enforcement wrappers will initially be supported in a subset of those languages.", + "homepageURL": "https://sourceforge.net/projects/compose-hpc", + "laborHours": 154523.2, + "languages": [], + "name": "BRAID", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/compose-hpc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-09-30" + }, + "description": "Establishes the input/output dependencies between individual application tasks, schedules and executes them on available computing resources in order of their dependencies. Uses statistical modeling algorithms to summarize the properties of the tasks to present to users a compact view of the surrent state of the overall application tasks and the effectiveness of various runtime optimizations on such tasks to improve utility of scheduling. Finally, uses statistical models to predict availability of computing resources", + "homepageURL": "https://sourceforge.net/projects/sched-minions", + "laborHours": 76121.6, + "languages": [ + "None" + ], + "name": "Minions Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/sched-minions", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-10-08" + }, + "description": "LRIOT is a test bench framework that is designed to generate sophisticated I/O rates that can stress high-performance memory and storage systems, such as non-volatile random access memories (NVRAM)and storage class memory. Furthermore, LRIOT provides the capabilities to mix multiple types of concurrency, namely threading and task parallelism, as well as distributed execution using Message Passing Interface (MPI) libraries. It will be used by algorithm designers to generate access patterns that mimic their application's behavior, and by system designers to test high-performance NVRAM storage.", + "laborHours": 760.0, + "languages": [ + "None" + ], + "name": "Livermore Random I/O Testbench", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/vanessen/lriot/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-09-30" + }, + "description": "Assessing primer specificity and predicting both desired and off-target amplification products is an essential step for robust PCR assay design. Code is described to predict potential polymerase chain reaction (PCR) amplicons in a large sequence database such as NCBI nt from either singleplex or a large multiplexed set of primers, allowing degenerate primer and probe bases, with target mismatch annotates amplicons with gene information automatically downloaded from NCBI, and optionally it can predict whether there are also TaqMan/Luminex probe matches within predicted amplicons.", + "homepageURL": "https://sourceforge.net/projects/simulatepcr", + "laborHours": 243.2, + "languages": [ + "PERL" + ], + "name": "PCR Amplicon Prediction from Multiplex Degenerate Primer and Probe Sets", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/simulatepcr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-10-08" + }, + "description": "ARKode is part of a software family called SUNDIALS: SUite of Nonlinear and Differential/ALgebraic equation Solvers [1]. The ARKode solver library provides an adaptive-step time integration package for stiff, nonstiff and multi-rate systems of ordinary differential equations (ODEs) using Runge Kutta methods [2].", + "homepageURL": "https://computation.llnl.gov/projects/sundials", + "laborHours": 103025.6, + "languages": [], + "name": "ARKode, v1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://computation.llnl.gov/projects/sundials", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-01-22" + }, + "description": "Spawn is a next generation building simulation engine designed to build on the strengths of NREL's venerable EnergyPlus engine, and add new advanced HVAC and controls modeling capability by incorporating the Modelica equation based modeling language. In effect, Spawn is a hybrid of the existing EnergyPlus and Modelica software products, with some new software to provide glue between the components in order to provide a seamless end user experience.", + "laborHours": 0.0, + "languages": [ + "C++", + "C" + ], + "name": "Spawn [SWR-SWR-20-10]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Spawn", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2023-05-16" + }, + "description": "The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.", + "laborHours": 0.0, + "languages": [ + "GAMS", + "Batchfile", + "MATLAB", + "Python", + "Python" + ], + "name": "RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/RODeO", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This Drupal Module extend the functionality of Drupal by modifying the output of dates to comply to the format of AP Style guide.", + "homepageURL": "https://www.drupal.org/project/date_ap_style", + "laborHours": 380.0, + "languages": [ + "PHP (99%)", + "JavaScript (1%)" + ], + "name": "Drupal Contributed Modules Date AP Style", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.drupal.org/project/date_ap_style", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "FRENSIE (the Framework for Research in Nuclear Science and Engineering) is a Monte Carlo code for solving linear particle transport problems with neutron, photon, and electron particles.", + "laborHours": 228927.2, + "languages": [ + "C++" + ], + "name": "Framework for Research in Nuclear Science and Engineering v. 0.3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lkersting/SCR-2123", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Phoenix is a Java Virtual Machine (JVM) based library for performing mathematical and astrodynamics calculations. It consists of two primary sub-modules, phoenix-math and phoenix-astrodynamics. The mathematics package has a variety of mathematical classes for performing 3D transformations, geometric reasoning, and numerical analysis. The astrodynamics package has various classes and methods for computing locations, attitudes, accesses, and other values useful for general satellite modeling and simulation. Methods for computing celestial locations, such as the location of the Sun and Moon, are also included. Phoenix is meant to be used as a library within the context of a larger application. For example, it could be used for a web service, desktop client, or to compute simple values in a scripting environment.", + "laborHours": 7721.6, + "languages": [ + "Scala/scalac/2.11" + ], + "name": "Phoenix v. 1.0-SNAPSHOT", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/phoenix/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/phoenix", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-26" + }, + "description": "SMASH is a collection of MATLAB programs, packages, and class definitions for analyzing experimental data.", + "laborHours": 330980.0, + "languages": [ + "MATLAB", + "HTML" + ], + "name": "Sandia Matlab AnalysiS Hierarchy toolbox v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SMASHtoolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The Sandia hyperspectral upper-bound spectrum algorithm (hyper-UBS) is a cosmic ray despiking algorithm for hyperspectral data sets. When naturally-occurring, high-energy (gigaelectronvolt) cosmic rays impact the earth\u2019s atmosphere, they create an avalanche of secondary particles which will register as a large, positive spike on any spectroscopic detector they hit. Cosmic ray spikes are therefore an unavoidable spectroscopic contaminant which can interfere with subsequent analysis. A variety of cosmic ray despiking algorithms already exist and can potentially be applied to hyperspectral data matrices, most notably the upper-bound spectrum data matrices (UBS-DM) algorithm by Dongmao Zhang and Dor Ben-Amotz which served as the basis for the hyper-UBS algorithm. However, the existing algorithms either cannot be applied to hyperspectral data, require information that is not always available, introduce undesired spectral bias, or have otherwise limited effectiveness for some experimentally relevant conditions. Hyper-UBS is more effective at removing a wider variety of cosmic ray spikes from hyperspectral data without introducing undesired spectral bias. In addition to the core algorithm the Sandia hyper-UBS software package includes additional source code useful in evaluating the effectiveness of the hyper-UBS algorithm. The accompanying source code includes code to generate simulated hyperspectral data contaminated by cosmic ray spikes, several existing despiking algorithms, and code to evaluate the performance of the despiking algorithms on simulated data.", + "laborHours": 0.0, + "languages": [ + "Mathworks Matlab R2015b" + ], + "name": "Sandia Hyperspectral Upper-Bound Spectrum Version 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Hyper-UBS", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "As parallel computing trends towards the exascale, scientific data produced by high-fidelity simulations are growing increasingly massive. For instance, a simulation on a three-dimensional spatial grid with 512 points per dimension that tracks 64 variables per grid point for 128 time steps yields 8 TB of data. By viewing the data as a dense five-way tensor, we can compute a Tucker decomposition to find inherent low-dimensional multilinear structure, achieving compression ratios of up to 10000 on real-world data sets with negligible loss in accuracy. So that we can operate on such massive data, we present the first-ever distributed-memory parallel implementation for the Tucker decomposition, whose key computations correspond to parallel linear algebra operations, albeit with nonstandard data layouts. Our approach specifies a data distribution for tensors that avoids any tensor data redistribution, either locally or in parallel. This software provides a method for compressing large-scale multiway data.", + "laborHours": 19364.8, + "languages": [ + "C++", + "Shell", + "CMake", + "MATLAB", + "Makefile", + "Python" + ], + "name": "TuckerCompressMPI v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TuckerMPI", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Fenix provides APIs to allow the users to add fault tolerance capability to MPI-based parallel programs in a transparent manner. Fenix-enabled programs can run through process failures during program execution using a pool of spare processes accommodated by Fenix.", + "laborHours": 3070.4, + "languages": [ + "CMake", + "C" + ], + "name": "Fenix, A Fault Tolerant Programming Framework for MPI Applications", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/epizon-project/Fenix", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "HyperHeadTail is a streaming algorithm for estimating the degree distribution of a graph from a stream of edges using very small storage space. Our algorithm builds upon the HeadTail algorithm of Simpson, Comandur, and McGregor [14], but extends it to handle repeat edges and variable-length sliding time windows, making it suitable for application to real-world streams such as those generated by network traffic or other communication networks.", + "laborHours": 684.0, + "languages": [ + "C++, Python" + ], + "name": "HyperHeadTail v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/HyperHeadTail?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HyperHeadTail", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This software uses a database of existing biological pathways to determine efficient routes for genetic engineering.", + "laborHours": 1413296.0, + "languages": [ + "Python" + ], + "name": "RetSynth v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/RetSynth", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "PV-RPM is intended to address more \u201creal world\u201d situations by coupling a photovoltaic system performance model with a reliability model so that inverters, modules, combiner boxes, etc. can experience failures and be repaired (or left unrepaired). The model can also include other effects, such as module output degradation over time or disruptions such as electrical grid outages. In addition, PV-RPM is a dynamic probabilistic model that can be used to run many realizations (i.e., possible future outcomes) of a system\u2019s performance using probability distributions to represent uncertain parameter inputs.", + "homepageURL": "https://sam.nrel.gov/photovoltaic/pvrpm.html", + "laborHours": 0.0, + "languages": [ + "For existing proof-of-concept, it was written in Goldsim in an object oriented format. The next vers" + ], + "name": "Photovoltaic Reliability Performance Model v 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sam.nrel.gov/photovoltaic/pvrpm.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sam.nrel.gov/photovoltaic/pvrpm.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Algebra, calculus, manipulation and optimization for small vectors and tensors.", + "laborHours": 8344830.4, + "languages": [], + "name": "MiniTensor v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This software collects sequence reads from Illumina next-generation sequencing to identify the counts of reads that support the mobilization of DNA.", + "laborHours": 1337.6, + "languages": [ + "Perl" + ], + "name": "Juxtaposer v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Juxtaposer", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Exomerge is a lightweight Python interface for manipulating ExodusII files.", + "laborHours": 4377.6, + "languages": [ + "Shell", + "Python" + ], + "name": "Exomerge v. 8.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/exomerge", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "8.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-26" + }, + "description": "PuLP/XtraPulp is software for partitioning graphs from several real-world problems. Graphs occur in several places in real world from road networks, social networks and scientific simulations. For efficient parallel processing these graphs have to be partitioned (split) with respect to metrics such as computation and communication costs. Our software allows such partitioning for massive graphs.", + "laborHours": 11795.2, + "languages": [ + "C++", + "C" + ], + "name": "PuLP/XtraPuLP : Partitioning Tools for Extreme-Scale Graphs", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PuLP", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Graphs occur in several places in real world from road networks, social networks and scientific simulations. Connectivity is a graph analysis software to graph connectivity in modern architectures like multicore CPUs, Xeon Phi and GPUs.", + "laborHours": 2796.8, + "languages": [ + "C++" + ], + "name": "Connectivity: Performance Portable Algorithms for graph connectivity v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Connectivity", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Graphs occur in several places in real world from road networks, social networks and scientific simulations. HPC Graph is a graph analysis software to analyze the properties such as connectivity, communities etc in extreme scale graphs.", + "laborHours": 2295.2, + "languages": [ + "C++", + "Makefile", + "C" + ], + "name": "HPCGraph v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HPCGraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Prove-It is a tool for proving and organizing general theorems using Python.", + "laborHours": 70953.6, + "languages": [ + "Python", + "Smarty", + "CSS", + "HTML", + "Jupyter Notebook", + "TeX" + ], + "name": "Prove-It v. 0.3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Prove-It", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.3" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "LabVIEW Task Manager is a debugging tool for use during code development in the National Instruments (NI) LabVIEW\u00ae IDE. While providing a dynamic & big-picture view of running code, an expandable/collapsible tree diagram displays detailed information (both static and dynamic) on all VIs in memory, belonging to a selected project/target. It allows for interacting with single or multiple selected VIs at a time, providing significant benefits while troubleshooting, and has the following features: Look & Feel similar to Windows\u00ae Task Manager; Selection of project/target; Lists all VIs in memory, grouped by class/library; Searches for and enumerates clones in memory; DropIn VI for including dynamically referenced clones (Clone Beacon); 'Refresh Now' (F5) re-reads all VIs in memory and adds new ones to the tree; Displays VI name, owning class/library, state, path, data size & code size; Displays VI FP Behavior, Reentrant?, Reentrancy Type, Paused? & Highlight?; Sort by any column, including by library name; Filter by item types vi, ctl, and vit/ctt; Filter out vi.lib and global VIs; Tracking of, and ability to toggle, execution highlighting on multiple selected VIs; Tracking of paused VIs with ability to Pause/Resume/TogglePause multiple selected VIs; DropIn VI for pausing on a condition; If a clone initiates a pause, a different pause symbol is used for all clones of that same reentrant original VI; Select multiple VIs and open or close their FPs or BDs; Double Click a VI from the tree to bring the BD (first choice) or FP to front, if already open; and Select multiple top-level VIs and Abort them.", + "laborHours": 1596.0, + "languages": [ + "National Instruments (NI) LabVIEW\u00ae, versions 2010 through 2016", + "LABVIEW", + "HTML" + ], + "name": "LabVIEW Task Manager v. 1.10.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/lavag/labview-task-manager/src/master/Documentation/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/LVTM", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.10" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Communities of uncultivated microbes are critical to ecosystem function and microorganism health, and a key objective of metagenomic studies is to analyze organism-specific metabolic pathways and reconstruct community interaction networks. This requires accurate assignment of genes to genomes, yet existing binning methods often fail to predict a reasonable number of genomes and report many bins of low quality and completeness. Furthermore, the performance of existing algorithms varies between samples and biotypes. Here, we present a dereplication, aggregation and scoring strategy, DAS Tool, that combines the strengths of a flexible set of established binning algorithms. DAS Tools applied to a constructed community generated more accurate bins than any automated method. Further, when applied to samples of different complexity, including soil, natural oil seeps, and the human gut, DAS Tool recovered substantially more near-complete genomes than any single binning method alone. Included were three genomes from a novel lineage . The ability to reconstruct many near-complete genomes from metagenomics data will greatly advance genome-centric analyses of ecosystems.", + "laborHours": 3344.0, + "languages": [ + "NA" + ], + "name": "Dereplication, Aggregation and Scoring Tool (DAS Tool) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cmks/DAS_Tool/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmks/DAS_Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Tempus is a software framework for the time integration of ordinary differential equations (ODEs), partial differential equations (PDEs), and differential-algebraic equations (DAEs). Examples of time-integration methods available are Forward Euler, Backward Euler, Explicit Runge-Kutta and Implicit Runge-Kutta methods. Tempus can be used from small systems of equations (e.g., single ODEs for the time evolution of plasticity models) to large-scale transient simulations requiring exascale computing (e.g., flow fields around reentry vehicles and magneto-hydrodynamics). Tempus will be released as part of Trilinos under a BSD open source license.", + "laborHours": 8344830.4, + "languages": [], + "name": "Tempus v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "A library for performing numerical computation with low-rank functions. The (C3) library enables performing continuous linear and multilinear algebra with multidimensional functions. Common tasks include taking \"matrix\" decompositions of vector- or matrix-valued functions, approximating multidimensional functions in low-rank format, adding or multiplying functions together, integrating multidimensional functions.", + "laborHours": 1999271.2, + "languages": [ + "C", + "HTML", + "SWIG", + "CMake", + "Tex", + "Python" + ], + "name": "Compressed Continuous Computation v. 12/20/2016", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/compressed-continuous-computation?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/compressed-continuous-computation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The purpose of this software is to function as a generalized ferroelectric material model. The material model is designed to work with existing finite element packages by providing updated information on material properties that are nonlinear and dependent on loading history. The two major nonlinear phenomena this model captures are domain-switching and phase transformation. The software itself does not contain potentially sensitive material information and instead provides a framework for different physical phenomena observed within ferroelectric materials. The model is calibrated to a specific ferroelectric material through input parameters provided by the user.", + "laborHours": 1079.2, + "languages": [ + "C++", + "C" + ], + "name": "General Nonlinear Ferroelectric Model v. Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/gnom3-fe?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gnom3-fe", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "ISPH code is developed to solve multi-physics meso-scale flow problems using implicit SPH method. In particular, the code can provides solutions for incompressible, multi phase flow and electro-kinetic flows.", + "laborHours": 19425.6, + "languages": [ + "C++", + "MATLAB" + ], + "name": "Implicit SPH v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/implicit-sph", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-25" + }, + "description": "Tensors (also known as multidimensional arrays or N-way arrays) are used in a variety of applications ranging from chemometrics to network analysis. The Tensor Toolbox provides classes for manipulating dense, sparse, and structured tensors using MATLAB's object-oriented features. It also provides algorithms for tensor decomposition and factorization, algorithms for computing tensor eigenvalues, and methods for visualization of results.", + "laborHours": 21386.4, + "languages": [ + "MATLAB", + "XSLT", + "C" + ], + "name": "Tensor Toolbox for MATLAB v. 3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tensor_toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "This software package can be used to build, train, and test a neural network machine learning model. The neural network architecture is specifically designed to embed tensor invariance properties by enforcing that the model predictions sit on an invariant tensor basis. This neural network architecture can be used in developing constitutive models for applications such as turbulence modeling, materials science, and electromagnetism.", + "laborHours": 380.0, + "languages": [ + "Python 2.7" + ], + "name": "Tensor Basis Neural Network v. 1.0 (beta)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tbnn", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "CIME is the software infrastructure for configuring, building, running, and testing an Earth system model. It can be developed and tested as stand-alone software, but its main role is to be integrating into the CESM and ACME Earth system models.", + "laborHours": 59827.2, + "languages": [ + "Python" + ], + "name": "CIME, Common Infrastructure for Modeling the Earth v. 5.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ESMCI/cime/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESMCI/cime", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "A simulation of a research processor-in-memory class computer architecture running the accumulation function of sparse matrix-matrix multiply.", + "laborHours": 1352.8, + "languages": [ + "C++" + ], + "name": "Superstrider simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.debenedictis.org/SuperStrider.cpp", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/superstrider", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The Fourier-Bessel Particle-In-Cell code is a scientific simulation software for relativistic plasma physics. It is a Particle-In-Cell code whose distinctive feature is to use a spectral decomposition in cylindrical geometry.\r\n\r\nThis decomposition allows to combine the advantages of spectral 3D Cartesian PIC codes (high accuracy and stability) and those of finite-difference cylindrical PIC codes with azimuthal decomposition (orders-of-magnitude speedup when compared to 3D simulations).\r\n\r\nThe code is built on Python and can run both on CPU and GPU (the GPU runs being typically 1 or 2 orders of magnitude faster than the corresponding CPU runs.)\r\n\r\nThe code has the exact same output format as the open-source PIC codes Warp and PIConGPU (openPMD format: openpmd.org) and has a very similar input format as Warp (Python script with many similarities). There is therefore tight interoperability between Warp and FBPIC, and this interoperability will increase even more in the future.", + "laborHours": 16233.6, + "languages": [ + "None" + ], + "name": "Fourier-Bessel Particle-In-Cell (FBPIC) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fbpic/fbpic", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Pyomo supports the formulation and analysis of mathematical models for complex optimization applications. This capability is commonly associated with algebraic modeling languages (AMLs), which support the description and analysis of mathematical models with a high-level language. Although most AMLs are implemented in custom modeling languages, Pyomo's modeling objects are embedded within Python, a full- featured high-level programming language that contains a rich set of supporting libraries.", + "laborHours": 0.0, + "languages": [ + "Python 2.6, 2.7, 3.4, 3.5" + ], + "name": "Pyomo v5.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pyomo/pyomo/releases/tag/5.0.1", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "LinkShop is a software tool for applying the method of Linkography to the analysis time-sequence data. LinkShop provides command line, web, and application programming interfaces (API) for input and processing of time-sequence data, abstraction models, and ontologies. The software creates graph representations of the abstraction model, ontology, and derived linkograph. Finally, the tool allows the user to perform statistical measurements of the linkograph and refine the ontology through direct manipulation of the linkograph.", + "laborHours": 10503.2, + "languages": [ + "Python 3, Javascript, C++" + ], + "name": "LinkShop v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/linkshop", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The statistical code, STEPWISE, evaluates variable importance by developing regression models between the observed response and input variables using either a forward, backward, or stepwise regression procedure on the raw or ranked data. The software will be used for performing sensitivity analysis on probabilistic results. Stepwise creates linear (or monotonic) regression of the output of interest using a set of input data in a stepwise fashion (i.e., adding one variable at a time). The program estimates parameters such as regression and standardized regressions coefficients for each selected input variables as well as the coefficient of determination of the resulting model", + "laborHours": 0.0, + "languages": [ + "FORTRAN" + ], + "name": "Stepwise v. 2.21", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/stepwise", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.21" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The CEED Software suite is a collection of generally applicable software tools focusing on the following computational motives: PDE discretizations on unstructured meshes, high-order finite element and spectral element methods and unstructured adaptive mesh refinement. All of this software is being developed as part of CEED, a co-design Center for Efficient Exascale Discretizations, within DOE's Exascale Computing Project (ECP) program.", + "homepageURL": "http://ceed.exascaleproject.org", + "laborHours": 0.0, + "languages": [ + "C++, C, Fortran, Shell, Python" + ], + "name": "Center for Efficient Exascale Discretizations Software Suite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ceed.exascaleproject.org/software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://ceed.exascaleproject.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Tensors, or multidimensional arrays, are a powerful mathematical means of describing multiway data. This software provides computational means for decomposing or approximating a given tensor in terms of smaller tensors of lower dimension, focusing on decomposition of large, sparse tensors. These techniques have applications in many scientific areas, including signal processing, linear algebra, computer vision, numerical analysis, data mining, graph analysis, neuroscience and more. The software is designed to take advantage of parallelism present emerging computer architectures such has multi-core CPUs, many-core accelerators such as the Intel Xeon Phi, and computation-oriented GPUs to enable efficient processing of large tensors.", + "laborHours": 606784.0, + "languages": [ + "C++", + "Shell", + "C", + "CMake", + "Makefile", + "Python" + ], + "name": "Genten: Software for Generalized Tensor Decompositions v. 1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/GenTen?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GenTen", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "SmartBlock offers reusable components that can provide data manipulation and transformation operations on different data streams without requiring recompilation for the new data types.", + "laborHours": 1292.0, + "languages": [ + "C++, C" + ], + "name": "SmartBlock v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gflofst/SmartBlock", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The RAJA Performance Suite is designed to evaluate performance of the RAJA performance portability library on a wide variety of important high performance computing (HPC) algorithmic lulmels. These kernels assess compiler optimizations and various parallel programming model backends accessible through RAJA, such as OpenMP, CUDA, etc. The Initial version of the suite contains 25 computational kernels, each of which appears in 6 variants: Baseline SequcntiaJ, RAJA SequentiaJ, Baseline OpenMP, RAJA OpenMP, Baseline CUDA, RAJA CUDA. All variants of each kernel perform essentially the same mathematical operations and the loop body code for each kernel is identical across all variants. There are a few kernels, such as those that contain reduction operations, that require CUDA-specific coding for their CUDA variants. ActuaJ computer instructions executed and how they run in parallel differs depending on the parallel programming model backend used and which optimizations are perfonned by the compiler used to build the Perfonnance Suite executable. The Suite will be used primarily by RAJA developers to perform regular assessments of RAJA performance across a range of hardware platforms and compilers as RAJA features are being developed. It will also be used by LLNL hardware and software vendor panners for new defining requirements for future computing platform procurements and acceptance testing. In particular, the RAJA Performance Suite will be used for compiler acceptance testing of the upcoming CORAUSierra machine {initial LLNL delivery expected in late-2017/early 2018) and the CORAL-2 procurement. The Suite will aJso be used to generate concise source code reproducers of compiler and runtime issues we uncover so that we may provide them to relevant vendors to be fixed.", + "laborHours": 12813.6, + "languages": [ + "CC++ I I standard required" + ], + "name": "RAJA Performance Suite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RAJAPerf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "In this software, we implement an adaptive, multivariate partitioning algorithm for solving mixed-integer nonlinear programs (MINLP) to global optimality. The algorithm combines ideas that exploit the structure of convex relaxations to MINLPs and bound tightening procedures", + "laborHours": 16279.2, + "languages": [ + "Julia, C++" + ], + "name": "A Polyhedral Outer-approximation, Dynamic-discretization optimization solver, 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl-ansi/Alpine.jl/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/Alpine.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "ExaSP2 is a reference implementation of typical linear algebra algorithms and workloads for a quantum molecular dynamics (QMD) electronic structure code. The algorithm is based on a recursive second-order Fermi-Operator expansion method (SP2) and is tailored for density functional based tight-binding calculations of material systems.", + "laborHours": 1048.8, + "languages": [ + "C" + ], + "name": "ExaSP2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ECP-copa/ExaSP2/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-copa/ExaSP2", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "TraceR Is a trace replay tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performance and understanding network behavior by simulating messaging In High Performance Computing applications on interconnection networks.", + "laborHours": 4803.2, + "languages": [ + "C++" + ], + "name": "Trace Replay and Network Simulation Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpcgroup/TraceR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "\"TopoMS\" is a visualization and analysis tool developed to enable interactive exploration of molecular systems, allowing the users perform Bader analysis as well as detailed analysis of molecular graph in complex systems.", + "laborHours": 23286.4, + "languages": [ + "C++" + ], + "name": "TopoMS-UI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TopoMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Collection of applications and cloud templates. Project currently based on www.packer.io for automation, www.github.com/boxcutter templates and the www.github.com/csd-dev-tools/ClockworkVMs application for wrapping both of the above for easy creation of virtual systems. Will in future also contain cloud templates tuned for various services, applications and purposes.", + "laborHours": 714.4, + "languages": [ + "Python, PyQt, JSON, GO" + ], + "name": "CloudStackProjectsNContributions", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csd-dev-tools/CloudStackProjectsNContributions", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The SpecTAD software represents a refactoring of the Temperature Accelerated Dynamics (TAD2) code authored by Arthur F. Voter and Blas P. Uberuaga (LA-CC-02-05). SpecTAD extends the capabilities of TAD2, by providing algorithms for both temporal and spatial parallelism. The novel algorithms for temporal parallelism include both speculation and replication based techniques. SpecTAD also offers the optional capability to dynamically link to the open-source LAMMPS package.", + "laborHours": 29032.0, + "languages": [ + "Fortran" + ], + "name": "SpecTAD", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/spectad", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-12-09" + }, + "description": "DEBS advances the resistive MHD equations via a combination of the explicit leapfrop method and the semi-implicit method. In this way the time step is limited by the CFL condition v*kmax*dt < 1, where v is the local flow velocity, NOT the wave propagation (sound plus Alfven) velocity. The code is thus able to take timesteps that are much larger than allowed by purely explicit codes. For the spatial discretization, DEBS uses a finite difference approximation for the radial variation and a Fourier representation for the variation of the fields in the poloidal and axial directions, i.e it assumes a doubly-periodic geometry. It advances the vector potential in lieu of the magnetic field and uses the Weyl gauge which assumes the electrostatic potential is zero", + "homepageURL": "http://www.tibbartech.com", + "laborHours": 7128.8, + "languages": [ + "fortran 77" + ], + "name": "DEBS MHD Code", + "organization": "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.tibbartech.com/contact", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.tibbartech.com", + "status": "Production", + "tags": [ + "DOE CODE", + "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "CallFlow Is a visualization tool to view and analyze Calling Context Tree (CCT) data provided by HPCToolkit.", + "laborHours": 25870.4, + "languages": [ + "D3, JavaScript" + ], + "name": "CallFlow", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/LLNL/CallFlow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The ShiftNMFk1.2 code, or as we call it, GreenNMFk, represents a hybrid algorithm combining unsupervised adaptive machine learning and Green's function inverse method. GreenNMFk allows an efficient and high performance de-mixing and feature extraction of a multitude of nonnegative signals that change their shape propagating through the medium. The signals are mixed and recorded by a network of uncorrelated sensors. The code couples Non-negative Matrix Factorization (NMF) and inverse-analysis Green's functions method. GreenNMF synergistically performs decomposition of the recorded mixtures, finds the number of the unknown sources and uses the Green's function of the governing partial differential equation to identify the unknown sources and their charecteristics. GreenNMF can be applied directly to any problem controlled by a known partial-differential parabolic equation where mixtures of an unknown number of sources are measured at multiple locations. Full GreenNMFk method is a subject LANL U.S. Patent application S133364.000 August, 2017. The ShiftNMFk 1.2 version here is a toy version of this method that can work with a limited number of unknown sources (4 or less).", + "laborHours": 760.0, + "languages": [ + "Matlab" + ], + "name": "ShiftNMFk 1.2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/rNMF/HNMF/blob/master/License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rNMF/HNMF", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "HIOP is a HPC solver for solving certain optimization problems arising in mathematical optimization of systems described by partial-differential equations (POEs).", + "laborHours": 51573.6, + "languages": [ + "C++ (95%), CMake (5%)" + ], + "name": "High-performance optimization solver", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/hiop/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/hiop", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "BIGSTICK Is a flexible configuration-Interaction open-source shell-model code for the many-fermion problem In a shell model (occupation representation) framework. BIGSTICK can generate energy spectra, static and transition one-body densities, and expectation values of scalar operators. Using the built-in Lanczos algorithm one can compute transition probabflity distributions and decompose wave functions into components defined by group theory.", + "laborHours": 40690.4, + "languages": [ + "Fortran 90" + ], + "name": "Flexible configuration-interaction shell-model many-body solver", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cwjsdsu/BigstickPublick", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "TreeScope Is a visualization tool to view and analyze network traffic on fat-tree networks, e.g., on cab.", + "laborHours": 2219.2, + "languages": [ + "D3, JavaScript" + ], + "name": "TreeScope Visualization Tool for Fat-tree Networks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TreeScope", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "MGmol ls a First-Principles Molecular Dynamics code. It relies on the Born-Oppenheimer approximation and models the electronic structure using Density Functional Theory, either LDA or PBE. Norm-conserving pseudopotentials are used to model atomic cores.", + "laborHours": 62760.8, + "languages": [ + "C++, parallellsm based on MPI" + ], + "name": "Multigrid based First-Principles Molecular Dynamics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mgmol", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The purpose of this model was to facilitate the design of a control system that uses fine grained control of residential and small commercial HVAC loads to counterbalance voltage swings caused by intermittent solar power sources (e.g., rooftop panels) installed in that distribution circuit. Included is the source code and pre-compiled 64 bit dll for adding building HVAC loads to an OpenDSS distribution circuit. As written, the Makefile assumes you are using the Microsoft C++ development tools.", + "homepageURL": "https://sourceforge.net/projects/sunlamp", + "laborHours": 1246.4, + "languages": [ + "Visual Studio 2015" + ], + "name": "Sunlamp", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sourceforge.net/p/sunlamp/code/ci/master/tree/copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/sunlamp", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Residential Simulation Tool was developed to understand the impact of residential load consumption on utilities including the role of demand response. This is complicated as many different residential loads exist and are utilized for different purposes. The tool models human behavior and contributes this to load utilization, which contributes to the electrical consumption prediction by the tool. The tool integrates a number of different databases from Department of Energy and other Government websites to support the load consumption prediction.", + "laborHours": 8694.4, + "languages": [ + "Matlab" + ], + "name": "Residential Simulation Tool", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/starkemr/Residential-Simulation-Tool/blob/master/LICENSE.md/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/starkemr/Residential-Simulation-Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "A cosmic ray Muon Flexible Framework for Spectral GENeration for Monte Carlo Applications (MUFFSgenMC) has been developed to support state-of-the-art cosmic ray muon tomographic applications. The flexible framework allows for easy and fast creation of source terms for popular Monte Carlo applications like GEANT4 and MCNP. This code framework simplifies the process of simulations used for cosmic ray muon tomography.", + "homepageURL": "https://www.mathworks.com/matlabcentral/fileexchange/65585-muffsgenmc", + "laborHours": 167.2, + "languages": [ + "Matlab R2017" + ], + "name": "MUFFSgenMC: An Open Source MUon Flexible Framework for Spectral GENeration for Monte Carlo Applications", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.mathworks.com/matlabcentral/fileexchange/65585-muffsgenmc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.mathworks.com/matlabcentral/fileexchange/65585-muffsgenmc", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "In developing visualizations for different data sets, the end solution often become dependent on the data being visualized. This causes engineers to have to re-develop many common components multiple times. The vis-react components library was designed to help enable creating visualizations that are independent of the underlying data. This library utilizes the React.js pattern of instantiating components that may be re-used. The library exposes an example application that allows other developers to understand how to use the components in the library.", + "laborHours": 691539.2, + "languages": [ + "Javascript" + ], + "name": "vis-react-components", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/vis-react-components", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "OddMon reads statistics information from multiple Lustre OSS's, forwards it to a central aggregator and then processes the data into a form suitable to inserting into a Splunk data store.", + "laborHours": 836.0, + "languages": [ + "Python 2.6" + ], + "name": "OddMon", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-TechInt/oddmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This program takes the users' Input data and fits a linear regression to it using the prescription presented by Mahon (1996). Compared to the commonly used York fit, this method has the correct prescription for measurement error \r\npropagation. This software should facilitate the proper fitting of measurements with a simple Interface.", + "laborHours": 304.0, + "languages": [ + "Python 2.7 (100%)" + ], + "name": "Fitting program for linear regressions according to Mahon (1996)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MahonFitting", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "smoothG is a collection of parallel C++ classes/functions that algebraically constructs reduced models of different resolutions from a given high-fidelity graph model. In addition, smoothG also provides efficient linear solvers for the reduced models. Other than pure graph problem, the software finds its application in subsurface flow and power grid simulations in which graph Laplacians are found", + "laborHours": 9986.4, + "languages": [ + "C++ (100%)" + ], + "name": "smoothG", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/LLNL/smoothG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "TopoMS Is an analysis tool for molecular and condensed-matter systems. It can be used for Bader analysis, study of charge transfer, bond detection, and computation of complete molecular graph.", + "laborHours": 23286.4, + "languages": [ + "C++" + ], + "name": "TopoMS, Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/TopoMS/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TopoMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-24" + }, + "description": "This software enables the user to produce Google Earth visualizations of turbine wake effects for wind farms. The visualizations are based on computations of statistical quantities that vary with wind direction and help quantify the effects on power production of upwind turbines on turbines in their wakes. The results of the software are plot images and kml files that can be loaded into Google Earth. The statistics computed are described in greater detail in the paper: S. Martin, C. H. Westergaard, and J. White (2016), Visualizing Wind Farm Wakes Using SCADA Data, in Wither Turbulence and Big Data in the 21st Century? Eds. A. Pollard, L. Castillo, L. Danaila, and M. Glauser. Springer, pgs. 231-254.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Wind Wake Watcher v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Wind-Wake-Watcher", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "loupe is a PMPl-based library to profile MPI routines in a parallel application.", + "laborHours": 304.0, + "languages": [ + "C++, Python" + ], + "name": "MPI Profiler", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/loupe", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "KVTree is a hierarchical, tree-structured, key-value data structure library that can be used and re-used by other tools.", + "laborHours": 3131.2, + "languages": [ + "C" + ], + "name": "KVTree", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/KVTree", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "MathWorks' MATLAB is widely used in academia and industry for prototyping, data analysis, data processing, etc. Many users compile their programs using the MATLAB Compiler to run on workstations/computing clusters via the free MATLAB Compiler Runtime (MCR). The MCR facilitates the execution of code calling Application Programming Interfaces (API) functions from both base MATLAB and MATLAB toolboxes. In a Linux environment, a sizable number of third-party runtime dependencies (i.e. shared libraries) are necessary. Unfortunately, to the MTLAB community's knowledge, these dependencies are not documented, leaving system administrators and/or end-users to find/install the necessary libraries either as runtime errors resulting from them missing or by inspecting the header information of Executable and Linkable Format (ELF) libraries of the MCR to determine which ones are missing from the system. To address various shortcomings, Docker Images based on Community Enterprise Operating System (CentOS) 7, a derivative of Redhat Enterprise Linux (RHEL) 7, containing recent (2015-2017) MCR releases and their dependencies were created. These images, along with a provided sample Docker Compose YAML Script, can be used to create a simulated computing cluster where MATLAB Compiler created binaries can be executed using a sample Slurm Workload Manager script.", + "laborHours": 45.6, + "languages": [ + "Bash 4.x, Docker 17.09" + ], + "name": "MCR Container Tools", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/mcr-container-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "OpenMP, a directive-based programming API, introduce directives for accelerator devices that programmers are starting to use more frequently in production codes. To make sure OpenMP directives work correctly across architectures, it is critical to have a mechanism that tests for an implementation's conformance to the OpenMP standard. This testing process can uncover ambiguities in the OpenMP specification, which helps compiler developers and users make a better use of the standard. We fill this gap through our validation and verification test suite that focuses on the offload directives available in OpenMP 4.5.", + "laborHours": 12479.2, + "languages": [ + "C/C++/Fortran" + ], + "name": "OpenMP 4.5 Validation and Verification Suite", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/crpl_cisc/sollve_vv", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "A computational method to automatically detect solar panels on rooftops to aid policy and financial assessment of solar distributed generation. The code automatically classifies parcels containing solar panels in the U.S. as residential or commercial. The code allows the user to specify an input dataset containing parcels and detected solar panels, and then uses information about the parcels and solar panels to automatically classify the rooftops as residential or commercial using machine learning techniques. The zip file containing the code includes sample input and output datasets for the Boston and DC areas.", + "laborHours": 197.6, + "languages": [ + "R/NA/3.4.0" + ], + "name": "Automatic Residential/Commercial Classification of Parcels with Solar Panel Detections", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/nset-ornl/ornlsolar/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nset-ornl/ornlsolar", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Boiler tubes in steam power plants experience exfoliation of oxide grown on the inner side of the tubes. In extreme cases, the exfoliation cause significant tube blockages that lead to forced power plant outages. It is thus desired to predict through modeling the propensity of exfoliation events in order to inform power plant operators of possible tube blockages. SpallMap solves for the stress-strain equations in an axisymmetric geometry, tracking the stress/strain evolution during boiler operation including outages at one-location along a boiler tube and compares it with scale damage criteria represented by Armitt diagram. The SPALLMAP code contains modules developed for oxide growth, stress analysis, and classical fracture mechanics correlations by taking into account the following phenomena and features, (a) Non-uniform thermal expansion coefficient of oxides and metal substrates, (b) Plant operation schedule with periodic alternate full-load and partial-load regimes, (c) axisymmetric formulation for cylindrical tubes, (d) Multiple oxide layers, (e) oxide-growth induced stresses, and (f) damage criteria from classical fracture mechanics. The computer program is written in FORTRAN90. Its modular structure was sought for allowing the best flexibility in updating the program by implementing new constitutive equations due to availability of new material property data and/or new physical phenomena.", + "laborHours": 0.0, + "languages": [ + "Fortran90" + ], + "name": "SPALLMAP", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/adisoft17/spallmap/blob/master/License_SpallMap_OpenSourceSoftware_ORNL.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/adisoft17/spallmap", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Samlab provides a workflow and data storage for machine learning experiment inputs and outputs using mongodb, and a web service to manage, search, visualize, and analyze the results.", + "laborHours": 7296.0, + "languages": [ + "Python" + ], + "name": "Sandia Machine Learning Laboratory", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/samlab/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/samlab", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2021-08-25" + }, + "description": "Charon is used to solve the drift-diffusion PDE Equations associated with semi-conductor physics. it is used to stimulate the operation of semi-conductor devices such as transistors and diodes. Additionally, the ode includes the functionality, but no the restricted data, to model these devices under the effects of neutron radiation.", + "homepageURL": "https://charon.sandia.gov", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Charon v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://charon.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The CSlib is a small, portable library which enables two (or more) independent simulation codes to be coupled, by exchanging messages with each other. Both codes link to the library when they are built, and can them communicate with each other as they run. The messages contain data or instructions that the two codes send back-and-forth to each other. The messaging can take place via files, sockets, or MPI. The latter is a standard distributed-memory message-passing library.", + "laborHours": 4240.8, + "languages": [ + "The CSlib can be used from programs written in C++, C, Fortran, or Python. The library itself is wr", + "Shell", + "Makefile" + ], + "name": "CSlib, a library to couple codes via Client/Server messaging", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://cslib.sandia.gov/open_source.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cslib", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The fftMPI library enables two and three dimensional Fast Fourier Transforms (FFTs) to be\r\nperformed efficiently in parallel on a variety of platforms from desktop machines to supercomputers. It allows for flexibility in the initial distribution of the FFT grid across processors, as well as the final output. It handles the data communication and reordering necessary to perform multi-dimensional FFTs in parallel. It relies on open-source or vendor-provided libraries to perform one dimensional FFTs on a single processor. It uses MPI for inter-processor communication, which is a standard distributed memory message-passing library.", + "laborHours": 8907.2, + "languages": [ + "The CSlib can be used from programs written in C++, C, Fortran, or Python.", + "Shell", + "Makefile" + ], + "name": "fftMPI, a library for performing 2d and 3d FFTs in parallel", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/fftmpi?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fftmpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "It compares the performance of several different algorithms for electronic structure simulation.", + "laborHours": 2188.8, + "languages": [ + "Shell", + "C", + "Python" + ], + "name": "Companion Software to \"Assessment of localized and randomized algorithms for electronic structure\"", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/linear-scaling-test", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "HOMMEXX is a global atmosphere dynamics and transport solver that uses a spectral element method, and is now written to be performance portable to many new computer architectures.", + "laborHours": 93723.2, + "languages": [ + "C++" + ], + "name": "HOMMEXX", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/E3SM-Project/HOMMEXX/blob/master/src/share/cxx/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/HOMMEXX", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "ShareAnalytics is a lightweight extensible platform for collaborative data analytics and facility characterization via Non-intrusive Load Monitoring (NILM). It consists of three core components: a full stack web application, a dashboard tool for analyzing streaming data and a High Performance Computing (HPC) cluster leveraging slurm for resource management to perform real time analysis. The entire framework is implemented in Docker for ease of deployment and to allow the user to test the platform before making a significant investment in hardware if they require additional computing resources. While many other platforms for analyzing streaming data exists, ShareAnalytics is unique in that HPC capabilities and facility characterization via scored analytics are fully integrated into the platform.", + "laborHours": 8755.2, + "languages": [ + "JavaScript / Bash" + ], + "name": "ShareAnalytics", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/ShareAnalytics", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Lab experiments involving digital signal processing tend to capture heterogeneous data that is binned into individual files. The structure of the whole experiment tends to get lost in this process, generating a \"mess\" of data that is difficult to summarize, and even more difficult to analyze in a consistent way. DataXray is a set of python routines that wraps publicly available open-source codes to create a consistent workflow for data and experiments, involving imaging, spectral and hyperspectral data. Routines are provided for data translation, slicing, visualization, multivariate statistics, integral transforms, feature extraction and reporting in the form of publication-grade figures.", + "laborHours": 2173.6, + "languages": [ + "Python 3.5" + ], + "name": "DataXray", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/glacio/data-xray/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This program implements a novel algorithm to obtain the density of state of a physical system, expanded in a chosen basis set. Unlike existing algorithms that return the density of states as a numerical array, this algorithm avoids binning of a continuous variable and is able to express the density of states in an analytical form. It is thus suitable for the study of the statistical mechanics and thermodynamic properties of physical systems where the density of a continuous state variable is of interest. The new algorithm presented here is a special reweighting method in classical Monte Carlo approaches. In particular, it can be regarded as a descendant and a hybrid method closely related to the multicanonical method and Wang--Landau sampling.", + "laborHours": 106.4, + "languages": [ + "Python3" + ], + "name": "HistogramFreeMUCA", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yingwaili/HistogramFreeMUCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Physics simulations that use particles in their algorithms are ubiquitous on modern high performance computers. Cabana is a C++ library for developing particle-based simulations on heterogeneous high performance computing platforms. Cabana provides general data structures and algorithms for common particle operations in a way that is both performant and portable on HPC systems. This includes particle data structure allocatable and configurable on GPU and CPU architectures, and threaded and distributed algorithms for sorting particles, halo exchanges, neighbor list generation, and other basic particle operations.", + "laborHours": 32528.0, + "languages": [ + "C++/clang,GCC,Intel,NVCC" + ], + "name": "Cabana", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-copa/Cabana", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Existing tools for computational anatomy and image registration are not aimed at HPC environments. As such they are not easily adapted to multimode platforms and contain inefficient batch processing modes. Lagomorph addresses this by providing an easy to install and use pure python implementation of very efficient image registration and atlas building which is aimed at extreme-scale anatomical studies using modern HPC and GPU resources.", + "laborHours": 3192.0, + "languages": [ + "Python 3.6" + ], + "name": "Lagomorph", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jacobhinkle/lagomorph/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jacobhinkle/lagomorph", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Kelvin is a multiphysics sintering simulation software that uses the material point method to simulate the thermomechanical behavior of metal parts.", + "laborHours": 2264.8, + "languages": [ + "C++, gcc 8.x" + ], + "name": "Kelvin", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/kelvin/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/kelvin", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "VeraRun provides users a command-line utility that determines the sequence of VERA codes and utilities to be executed, calculates and determines PBS directives and job parameters, creates a job script, and submits the script on behalf of the user. While hiding all the details, the script allows the user to set PBS parameters explicitly. VeraRun is implemented as a Python package with host-specific configurations and job script templates. Host configurations are stored in JavaScript Object Notation (JSON) files and specify machine characteristics (e.g., number of nodes, number of processors per node, memory available per node, location of VERA installations). Job templates are Bash scripts with parameters substituting for host-specific PBS directives and controls. These files are named by the hostname, thus making VeraRun extensible to other systems and environments. VeraRun reads the VERA input file to determine code and execution environment requirements, creating and optionally submitting a job script.", + "laborHours": 21675.2, + "languages": [ + "Python 2 or 3" + ], + "name": "VeraRun", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/casl/VeraView", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Information extraction and coding of free-text pathology reports is an important activity for cancer registries to support national cancer surveillance. Cancer registrars must process high volumes of pathology reports on an annual basis. We investigated an automated approach using a convolutional neural networks (CNNs) for extracting the primary site, laterality, histology, behavior, and histological grade from unstructured cancer pathology text reports. Our multi-task learning (MTL) with hard parameter sharing approach is used to train a multi-task MT-CNN model for all the tasks. The performance of our proposed approach was compared against a state of-the-art CNN and the commonly used SVM classifier. We observed that the proposed model consistently outperformed the baseline models, especially for the less prevalent classes. Also, the results demonstrate the potential of the proposed method for handling class imbalance within each task.", + "laborHours": 273.6, + "languages": [ + "Python" + ], + "name": "Multi-Task Convolutional Neural Networks for Natural Text Classification", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CBIIT/pilot3_MT-CNN_ORNL", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The code is a set of first-principles based thermodynamic properties calculations for materials properties at finite temperature. It provides a collection of commonly used Monte Carlo algorithms, interfaced with a few external codes that carry out density functional theory calculations, such as Quantum Espresso and Local Self-consistent Multiple Scattering. The code provides high accuracy thermodynamic calculations that are comparable to real-world materials properties.", + "laborHours": 4453.6, + "languages": [ + "C++11" + ], + "name": "Oak Ridge Wang-Landau (OWL)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/owl-suite/OWL", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Many universities have published highly accurate open source face recognition algorithms, but configuring and using those algorithms can be very difficult due to poor documentation and challenges with installing the right software and libraries. Comparing research results is also a problem due to uncontrolled research methods. Provide baseline face recognition implementations that can be used for evaluating algorithm accuracy. The software provides a consistent web service interface to face recognition algorithms that can be used to support research in biometrics. The software uses protobuf and grpc services to publish standardized interfaces to the algorithms. The software also provides Docker container support which allows services to be easily started and configured on new machines. Reproducible baseline configurations are provided to serve as bench marks for publications in this area.", + "laborHours": 35613.6, + "languages": [ + "Python 3" + ], + "name": "Face Recognition from Oak Ridge (FaRO)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/faro", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "A challenging scientific problem that will benefit from exascale computing is predictive simulation of two- and three-dimensional quantum many-body Hamiltonians in condensed matter physics, together with the related strong entanglement problems in quantum chemistry and quantum computing. Efficient numerical simulations will require new insights into wavefunction compression algorithms that scale on extremely heterogeneous HPC architectures. To address this need, we propose to develop a scalable math library of parallel multi-linear algebraic numerical primitives for hierarchical tensor compression. Our library will subsequently be used for building an efficient, performance-portable HPC framework for simulating strongly correlated quantum systems. In particular, our will will be the first to deliver a massively parallel implementation of the multiscale entanglement renormalization ansatz (MERA), a hierarchical tensor decomposition quantum scheme capable of expressing local expectation values of strongly entangled higher-dimensional quantum systems efficiently. To address the extreme complexity and high computational cost of such schemes, we will automate their parallel implementation by delivering an integrated software framework, ExaTN (Exascale Tensor Networks), that will process hierarchical tensor representations on exascale HPC systems via an asymchronous task-based programming model. As a specific application, our framework will provide scientists with a capability of simulating strongly entangled quantum systems, thus positioning ORNL as a strategic leader in modeling of strongly correlated materials.", + "laborHours": 173097.6, + "languages": [ + "C++ using clang and/or gcc versions compliant with C++11" + ], + "name": "ExaTN", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-qci/exatn", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The QCOR compiler provides a mechanism for the expression and compilation of quantum code alongside standard, modern C++. It does so through integration with Clang and its robust abstract syntax tree analysis tools, as well as integration with the XACC infrastructure.", + "laborHours": 62228.8, + "languages": [ + "C++, Clang/GCC with C++11 support" + ], + "name": "QCOR", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-qci/qcor", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "ExaTENSOR is a software math library for performing basic numerical tensor algebra operations on distributed heterogeneous HPC platforms. The library provides the following basic numerical tensor algebra primitives: tensor contraction, tensor product, tensor addition, tensor scaling by a scalar, etc. ExaTENSOR supports dense, block-sparse and hierarchical block-sparse tensors stored and processed across many heterogeneous HPC nodes (node equipped with NVIDIA GPU and Intel Xeon Phi have been considered so far). The architecture of ExaTENSOR is based on the concept of domain-specific virtual processor (DSVP), that is, an intermediate software layer capable of processing domain-specific instructions, in this case, numerical tensor algebra instructions. In this way, a separation of the domain-specific algorithm expression and hardware-agnostic algorithm execution is achieved, thus ensuring portability of the applications which use ExaTENSOR as a numerical backend.", + "laborHours": 85591.2, + "languages": [ + "Fortran 2003", + "C/C++", + "gcc-8.1", + "intel-1.8", + "xl-16.1.1" + ], + "name": "ExaTENSOR", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/ExaTENSOR", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Iterative Random Forest (iRF) is an improvement upon the classic Random Forest, using weighted iterations to distill the forests. Ranger is a C++ implementation of random forest or recursive partitioning, particularly suited for high dimensional data. Ranger-Based iRF uses Ranger as a base Random Forest codebase upon which iterative and scalability aspects have been added.", + "laborHours": 6976.8, + "languages": [ + "C++/gnu-cmake" + ], + "name": "Ranger-based Iterative Random Forest", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Jromero1208/RangerBasediRF", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Current software uses a least squares statistical method. For each model parameter, current software yields a point estimate and estimated standard error for each point estimate. In contrast, we have employed a Bayesian approach with sampling algorithm to provide a full posterior probability density function on each model parameter. This yields a different type of solution (probabilistic) with better fidelity. The Quantitative Uncertainty Analysis for Diffraction (QUAD) package returns a matrix of affect model parameters as a function of iteration through the MCMC analysis. QUAD is a Python code that allows for analysis of X-ray and neutron diffraction data to infer the structure of materials with quantifiable certainty. The code uses Bayesian statistics and Markov chain sampling algorithms to create posterior probability distributions on all material structure parameters that are modeled by a researcher. The statistical packages use the open source GSASII project as a library to calculate model diffraction patterns.", + "laborHours": 653.6, + "languages": [ + "Python" + ], + "name": "Quantitative Uncertainty Analysis for Diffraction", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/rabroughton/QUAD/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rabroughton/QUAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "TRITON is a 2D hydraulic, digital elevation model (DEM)-based model that accepts a variety of flow inputs including point-based inflow hydrographs, external boundary conditions, and runoff (i.e., excess rainfall). It provides information of flood maps and temporal evolution of water depth at each grid cell point at user-specified output time. Its unique feature is that TRITON can run on single or multiple CPUs and GPUs, proving to be very flexible in terms of system architecture.", + "laborHours": 5168.0, + "languages": [ + "C++, CUDA" + ], + "name": "TRITON", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/hydro/triton/-/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/hydro/triton", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The code \"STEMDL\" provides highly-optimized multi-gpu implementations of DL models of applicability in electron microscopy via the use of mixed-precision arithmetic, native graph construction and evaluation in Tensorflow, and adaptive scaling of learning parameters to avoid numerical instabilities due to reduced precision. STEMDL also uses low-level methods from the Horovod library for gradient communication and reduction and adds an additional optimization by allowing the user to scheduling the gradient reduction operations based on their position within the layers of a neural net. STEMDL provides optimized I/O routines for data staging and data reading/writing in both Tensorflow and Pytorch using multi-processing and asynchronous transfer between host and device.\r\n.", + "laborHours": 147014.4, + "languages": [ + "Python 2.7/3.x" + ], + "name": "STEMDL", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/disMultiABM/stemdl", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "RDF triplestores are great tools for online graph analytic processing (i.e., graph pattern query processing), but they do not provide graph mining capabilities (e.g., PageRank, connected-component analysis, node eccentricity, etc.). The software title \u201cTripleGraph\u201d is a graph analysis toolkit, which uses an RDF triplestore as its backend for creating, manipulating, mining, and programming with large scale property graphs. It allows users to run various graph mining algorithms easily. User can import edgelist-formatted (homogeneous graph) or JSON-formatted graph (property graph) into the RDF triplestore using the provided tool and perform various analysis such as (1) Node/edge retrieval and manipulation, (2) Pathfinding between two given nodes, (3) Running graph mining algorithms (PageRank/Personalized PageRank, Single Source Shortest Path/Multi-Source Shortest Path, Connected Component, Node Eccentricity, Peer Pressure Clustering). It supports standard graph data format and works with a standard SPARQL endpoint like Jena Fuseki. It allows users to perform online graph analytic processing and graph mining on the same platform (a triplestore).", + "laborHours": 380.0, + "languages": [ + "Python 2.7" + ], + "name": "TripleGraph", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/liza183/TripleGraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The code \u201cminiWeather\u201d solves the 2-D Euler equations with a Finite-Volume method on a regular Cartesian grid with Runge-Kutta time stepping, 4th-order hypervisocisty, and 4th-order spatial accuracy. The code is primarily a parallel programming training mini application in Fortran, C, and C++ with MPI, OpenMP, OpenMP offload, OpenACC, and C++ portability approaches. It can also serve as a mini application for acceptance testing for new machines and compilers for both functionality and performance.", + "laborHours": 7828.0, + "languages": [ + "C++11, any C++11 compiler can be used" + ], + "name": "miniWeather", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mrnorman/miniWeather", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The software \"eeyore\" solves the problem of running Markov chain Monte Carlo (MCMC) algorithms on Bayesian neural networks. There is software for MCMC algorithms and software for neural network (such as PyTorch and TensorFlow), but there are limited solutions for combining the two. The main idea is to create a subclass of the 'torch.nn.Module' for defining Bayesian neural networks with the desired functionality required by MCMC taking the form of additional methods in that sub-class. This way, neural network functionality of PyTorch is exposed to the developer and user, allowing to develop MCMC methods on top of it through a simple API. The code implements Langevin Monte Carlo algorithms and population MCMC algorithms, as well as combinations of these, for Bayesian neural networks. This kind of functionality is not available elsewhere, to the best of the authors' knowledge. Moreover, a simple API is available that allows to implement new MCMC algorithms in the future.", + "laborHours": 2614.4, + "languages": [ + "Python (v3.6 onwards)" + ], + "name": "eeyore", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/papamarkou/eeyore", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "In NAMSA, we introduce two main solutions to address the limitations of MSA-type algorithms for simulation of electron scattering/microscopy data: just-in-time compilation and work partitioning via MPI and GPU-to-GPU communication. First, the just-in-time (JIT) compilation strategy produces optimally tuned CUDA C++ kernels due to the data layout being perfectly known at runtime and compiled via calls from the Python interpreter. NAMSA automatically optimizes the 2-D FFT planning, and CUDA multi-streams scheduling/launching of probe simulations. With NAMSA, we can simulate electron scattering/microscopy on hundreds to thousands of GPUs, while removing the major limitations of memory and bandwidth from MSA.", + "laborHours": 2766.4, + "languages": [ + "Python (2.7/3.X), CUDA C++ /NVCC/10.01" + ], + "name": "NAMSA", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/disMultiABM/namsa", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "P Finder is written in C# and has been tested in multiple 64-bit Windows environments (Windows 7/8/Vista). It has a user-friendly graphical user interface (GUI) that allows for intuitive RNase P RNA identification and/or annotation. The user can select from four search criteria including the use multiple threads. In addition, the user can determine what display data they wish to incorporate in the output such as: bitscore, E-value, percent ID, start location, end location, the strand in which the sequence is located, and of course the sequence itself. P Finder is the only available algorithm that is capable of not only identifying the RNase P RNA for annotation but also differentiating among the five different RNase P RNA structural types (A, B, C, M, and T) with the option to select these data types for display in the final output.", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "P Finder", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JChristopherEllis/P-Finder", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "CoMet is an application for finding epistatic and pleiotropic relationships from large quantities of genomic data. It solves these large combinatorial problems on GPU-accelerated systems with thousands of compute nodes. Its methods include the 2-way Proportional Similarity method, the Custom Correlation Coefficient and the DUO method. CoMet was developed at the Oak Ridge Leadership Computing Facility in collaboration with the Computational Biology and Bioinformatics Group at Oak Ridge National Laboratory.", + "laborHours": 18361.6, + "languages": [ + "GNU C++, NVIDIA NVCC" + ], + "name": "CoMet", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wdj/comet", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The code titled \u201ceBPF Community ID Calculation\u201d allows easy correlation of monitoring logs with existing network forensics logs on high-performance computing (HPC) systems. This code implements the Community ID Flow Hashing standard to calculate community ID Flow identifiers. These identifiers will be used to correlate host forensics logs with network forensics logs. The correlation provides valuable insight and the ability to easily pivot between disparate data sources. The computer code removes the libpcap dependency from the code base.", + "laborHours": 167.2, + "languages": [ + "Golang. 1.13" + ], + "name": "eBPF Community ID Calculation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stefanmaerz/eBPF_communityID", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2022-05-06" + }, + "description": "\u201cThe code \u201cCertificate Validation Libraries\u201d provides the ability to validate x509 certificates in python using a simple library. These libraries validate certificates in 3 ways: 1) validation that certificate has not expired. 2) validation that certificate has not been revoked and 3) validation of certificate's digital signature. The benefits of this code is that one can properly validate x509 certificates, thus strengthening the security of systems using these libraries.\u201d", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "Certification Validation Libraries", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/certification-validation-libraries", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "In the era of machine learning, we often need to run the same code/script many times with little or no variations (e.g., performance evaluation, data preprocessing, data generation, hyperparameter tuning, etc.). It is not a problem when you just need to do that a few times, but when the number of repetitions becomes very large, it can be a daunting task. The code \u201cSerial2Parallel\u201d provides an easy way for users to be able to run many numbers of any serial code/scripts in a parallel manner across multiple nodes in an message passing interface (MPI) cluster. The code includes the server program that deals with task pool management and client program that processes task. The server gets the tasks ready and waits for clients' connections. The client code pulls tasks from the server and processes them. The client code will run in parallel.", + "laborHours": 136.8, + "languages": [ + "Python 3" + ], + "name": "Serial2Parallel", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/liza183/Serial2Parallel", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/liza183/Serial2Parallel", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The software \u201cMEUMAPPS\u201d is a h high-performance computing code used to simulate microstructure evolution associated with diffusional solid-state transformations in structural alloys. Understanding microstructure evolution during thermo-mechanical processing of structural alloys is the first step towards designing and processing alloys for specific applications by meeting property requirements demanded by the application. In this instance, the code is an important component in predicting processing-structure linkages during additive manufacturing of structural alloys as a function of processing parameters and alloy composition used in an additive manufacturing process. The code provides a detailed three-dimensional distribution of different types of phases / constituents and their morphologies, as well as the compositions of these phases that make up the microstructure. The microstructure is simulated by solving the governing partial differential equations using a Fourier Spectral Method.", + "laborHours": 851.2, + "languages": [ + "Fortran/PGI/19.9" + ], + "name": "MEUMAPPS (Microstructure Evolution Using Massively Parallel Phase-field Simulations)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/meumapps_ss", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-05", + "metadataLastUpdated": "2024-07-19" + }, + "description": "KARMA4 is a C++ library for autoregressive moving average (ARMA) modeling and forecasting of time-series data while incorporating both process and observation error. KARMA4 is designed for fitting and forecasting of time-series data for predictive purposes.", + "laborHours": 471.2, + "languages": [ + "C++", + "MATLAB", + "Makefile" + ], + "name": "KARMA4", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/KARMA4", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-10-05", + "metadataLastUpdated": "2020-10-05" + }, + "description": "The invention improves accuracy of metabolite identification by combining direct infusion ESI-MS with one-dimensional 1H-NMR spectroscopy. First, we apply a standard 1H-NMR metabolite identification protocol by matching the chemical shift, J-coupling and intensity information of experimental NMR signals against the NMR signals of standard metabolites in a metabolomics reference libraries. This generates a list of candidate metabolites. The list contains both false positive and ambiguous identifications. The software tool (the invention) takes the list of candidate metabolites, generated from NMRbased metabolite identification, and then calculates, for each of the candidate metabolites, the monoisotopic mass-tocharge (m/z) ratios for each commonly observed ion, fragment and adduct feature. These are then used to assign m/z ratios in experimental ESI-MS spectra of the same sample. Detection of the signals of a given metabolite in both NMR and MS spectra resolves the ambiguities, and therefore, significantly improves the confidence of the identification.", + "laborHours": 15.2, + "languages": [ + "Software is compiled and interpreted for the Java Virtual Machine (JVM) version 6 or higher." + ], + "name": "Unambiguous Metabolite Identification in High-Throughput Metabolomics by Hybrid 1H-NMR/ESI-MS1 Approach", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/unambiguous-metabolite-identification-hybrid-1d-1h-nmresi-ms1-approach", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-NMR-EPR/MATLAB-1D_1H_NMR_ESI_MS1-WebApp", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-10-05", + "metadataLastUpdated": "2020-10-05" + }, + "description": "Algorithms and software code to detect and diagnose faulty operations with economizer operations.", + "laborHours": 109880.8, + "languages": [ + "Linux" + ], + "name": "Active and Passive Economizer Diagnostics for Rooftop and Air-Handling Units", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron-applications", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-10-05", + "metadataLastUpdated": "2020-10-05" + }, + "description": "The ILC algorithm prioritizes available loads for curtailment in large and small/medium size commercial buildings.", + "laborHours": 109880.8, + "languages": [ + "Python" + ], + "name": "Intelligent Load Control", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron-applications", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-10-07", + "metadataLastUpdated": "2023-05-08" + }, + "description": "Open Energy Data Initiative (OpenEDI): Advancing Analytics and Research Innovation through Improved Data Access. The Open Energy Data Initiative (OEDI) aims to improve and automate access of high-value energy data sets across the U.S. Department of Energy\u2019s (DOE\u2019s) programs, offices, and national laboratories. Sponsored by the DOE, this platform is being implemented by the National Renewable Energy Laboratory (NREL) to make data actionable and discoverable by researchers and industry to accelerate analysis and advance innovation. Partners at other national laboratories will help utilize the platform for analysis, can be directly involved in determining requirements, and will be resources for providing new datasets that can be shared with the public to expand innovation.", + "laborHours": 20322.4, + "languages": [ + "Python", + "Dockerfile" + ], + "name": "Open Energy Data Initiative (OpenEDI) - Open Data Access Tools (OEDI-ODAT) [SWR 20-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openEDI/open-data-access-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.2.1" + }, + { + "contact": { + "email": "gaoz@ornl.gov" + }, + "date": { + "created": "2020-10-08", + "metadataLastUpdated": "2021-03-05" + }, + "description": "Membrane-based dehumidification is currently being considered as a promising solution for the building application due to its low cost and very limited energy consumption. Developing a simple and efficient open-source code simulation tool is important for boosting the optimization and evaluation of such device in HVAC community. This paper reports a first-order physics based model which accounts for the fundamental heat and mass transfer of humid-air vapor at feed side to flow stream at permeate side. The current model comprises two membrane mass transfer submodels (i.e. microstructure model and performance map model); and it adopts a segment-by-segment methodology for discretizing heat and mass transfer governing equations. The model is capable of simulating both dehumidifiers and energy recovery ventilators with parallel-flow cross-flow, and counter-flow configurations. The model was validated with the measurements at appropriate device. The practices in dehumidification and energy recovery exchangers are also discussed. The model and open-source codes are expected to become a solid fundament for developing a more comprehensive and accurate membrane-based dehumidification in the future. ", + "laborHours": 1200.8, + "languages": [ + "C++" + ], + "name": "MBMS1.0: An Open-Source Code for Modeling and Simulation of Membrane-Based Dehumidification and Energy Recovery", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MBMS/C-CODE_FOR_MEMBRANE_BASED_MODEL", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "MBMS. 1.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-10-13", + "metadataLastUpdated": "2020-10-19" + }, + "description": "ExaPF is a HPC package in Julia for solving power flow (PF) on a GPU. It currently solves PF using the Newton-Raphson algorithm on NVIDA GPUs.", + "laborHours": 6080.0, + "languages": [], + "name": "ExaPF", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exanauts/EXaPF.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-10-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Automated NGFC system design tool set to develop optimized, next-generation solid oxide fuel cell (SOFC)\nbased natural gas fuel cell (NGFC) system designs with >70% fuel efficiency and <30 g/kWh CO2 emissions", + "laborHours": 39261.6, + "languages": [], + "name": "NGFC-Lib/NGFC-Lib", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NGFC-Lib/NGFC-Lib", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-10-19", + "metadataLastUpdated": "2020-10-19" + }, + "description": "RELOG is a supply chain optimization package focusing on reverse logistics and reverse manufacturing. For example,the package can be used to determine where to build recycling plants, what sizes should they have and which customers should be served by which plants. The package supports customized reverse logistics pipelines, with multiple types of\nplants, multiple types of product and multiple time periods.\n", + "laborHours": 24411.2, + "languages": [], + "name": "RELOG", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-CEEESA/RELOG", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "fattebertj@ornl.gov" + }, + "date": { + "created": "2020-10-20", + "metadataLastUpdated": "2020-10-20" + }, + "description": "Loewdin orthonormalization of distributed tall-skinny matrix using Schulz iteration", + "laborHours": 1869.6, + "languages": [ + "C++" + ], + "name": "ORNL/ParrLO", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/ParrLO", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-10-21", + "metadataLastUpdated": "2020-10-21" + }, + "description": "JPype is a Python module to provide full access to Java from within Python. It allows Python to make use of Java only libraries, exploring and visualization of Java structures, development and testing of Java libraries, scientific computing, and much more. By gaining the best of both worlds using Python for rapid prototyping and Java for strong typed production code, JPype provides a powerful environment for engineering and code development. This is achieved not through re-implementing Python, as Jython has done, but rather through interfacing at the native level in both virtual machines. This shared memory based approach achieves decent computing performance, while providing the access to the entirety of CPython and Java libraries.", + "laborHours": 34656.0, + "languages": [], + "name": "JPype", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Thrameos/jpype", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-10-21", + "metadataLastUpdated": "2020-10-21" + }, + "description": "Compilers transform program source code to machine executable code. During this transformation, they perform a number of compiler optimizations to improve the performance of the generated executable\ncode. Importantly, applying those optimizations depends on the source code structure, such as the parallel programming model used to\nparallelize an algorithm. Often, implementations of the same algorithm with different programming models have vastly different performance because the compiler optimized them differently. We create FAROS, a framework to structure and automate the analysis of compiler optimizations on programs. FAROS automates the building process, execution profiling, and analysis of compiler optimization of programs, through a configuration interface. It outputs compiler optimization reports to show which\noptimizations applied to which line of source code, leveraging compilation remarks output by the compiler. Also, FAROS supports\nbenchmarking performance of different program versions by collecting execution time results. In this first release of FAROS, we provide a configuration file to analyze compiler optimization differences for sequential vs OpenMP compilation, including 38 programs consisting of HPC proxy/mini/large applications, and NAS and Rodina kernels for analysis. ", + "laborHours": 1976.0, + "languages": [], + "name": "A Framework for the Analysis of Compiler Optimizations", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FAROS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-10-26", + "metadataLastUpdated": "2023-04-24" + }, + "description": "The Electricity Markets Investment Suite Approximate Equilibrium (EMIS-AE) package is developed at NREL and provides a solution capability to solve generation expansion equilibrium problems in the electricity markets. EMIS-AE is designed to capture the evolution of the electricity generation portfolio resulting from the interactions of heterogeneous investors under different policy and market designs. The investment problem for each generation company (GENCO) is a bi-level problem with the investment decision made in the upper level and market clearing condition in the lower level, which traditionally is represented as a Mathematical Program with Equilibrium Constraint (MPEC). EMIS-AE provides a predictive model to be trained for estimating the system-wide revenues for each technology type across energy, ancillary services and capacity markets given the amount of installed capacity on the grid. The profit maximization investment problem for each GENCO is solved using a global search algorithm, which uses the predictive model to evaluate the objective function. To solve for the strategic equilibrium, each GENCO\u2019s problem is plugged into a diagonalization algorithm that is generally used in multi-leader, single-follower bi-level problems.", + "laborHours": 1520.0, + "languages": [ + "Julia", + "Python" + ], + "name": "EMISApproximateEquilibrium.jl [SWR-19-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMISApproximateEquilibrium.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-10-26", + "metadataLastUpdated": "2023-04-24" + }, + "description": "In support of the Electricity Markets and Investment Suite, this repository hold data set used in the following julia packages EMISApproximateEquilibrium.jl, EMISCompetitiveEquilibrium.jl, and EMISAgentSimulation.jl.", + "laborHours": 137073.6, + "languages": [ + "HTML" + ], + "name": "EMIS-Data [SWR-19-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMIS-Data", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-10-26", + "metadataLastUpdated": "2023-04-24" + }, + "description": "The Electricity Markets Investment Suite Agent-based Simulation (EMIS-AS) model is an agent-based model developed at NREL for simulating annual investment and retirement decisions of heterogeneous investors in the electricity sector. EMIS-AS is designed to capture the evolution of the electricity generation portfolio resulting from the interactions of heterogeneous investors under different policy and market designs. EMIS-AS not only allows end-users to customize market products and rules, but also to capture investors' heterogeneous financing parameters, technology preferences, beliefs about the future (forecasts), ability to update those forecasts, and risk preferences under uncertainty.", + "laborHours": 5046.4, + "languages": [ + "Julia" + ], + "name": "EMIS Agent Simulation Model (Electricity Markets Investment Suite) [SWR-19-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMISAgentSimulation.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-27", + "metadataLastUpdated": "2020-10-29" + }, + "description": "CEDS produces consistent estimates of global air emissions species data during the industrial era (1750 - present).", + "laborHours": 24122.4, + "languages": [ + "R version 3.3+" + ], + "name": "Community Emissions Data System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/JGCRI/CEDS#license-section", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/CEDS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-27", + "metadataLastUpdated": "2020-10-29" + }, + "description": "The lightweight heap profiling tool memP Version 1 provides a library that can be used with MPI applications that make use of heap memory allocations to provide profile data based on the per-task high-water-mark of heap allocation. The memP output is generated as a text report that can present summary information or specific detail of the allocation call site data for each task The memP library source code is based on teh mpiP MPI profiling library (http://mpip.sourceforge.net), but is substantially different in functionality and organization.", + "homepageURL": "https://sourceforge.net/projects/memp", + "laborHours": 9226.4, + "languages": [], + "name": "memP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/memp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-27", + "metadataLastUpdated": "2020-10-29" + }, + "description": "The PRESTA MPI Benchmark software is a project that is used to evaluate the network communication performance of computer systmes using the Message Passing Interface (MPI) communication library.", + "laborHours": 2705.6, + "languages": [], + "name": "PRESTA MPI Benchmark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/phloem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-27", + "metadataLastUpdated": "2020-10-29" + }, + "description": "The Axom library consists of n collection of software components that provide core computer science infrastructure capabilities that can be shared by diverse high performance computing (HPC) applications. The current set of capabilities that Axom provides includes: Customizable support for error/warning and diagnostic message reporting and coordination among components of integrated applications (e.g., physics packages, libraries, etc.); Scalable parallel aggregation and filtering of message logging; In memory datastore for hierarchical, mesh-aware simulation data. The datastore supports data description, allocation, deallocation. parallel l/0, etc; Mesh data model abstractions that enable the development of mesh-based computational algorithms that work with many diverse, application\u00b7 specific mesh types; and Computational geometry primitives for developing high performance parallel algorithms based on spatial geometry and meshes, e.g., spatial acceleration data structures, sets, maps, relations, etc.", + "laborHours": 229945.6, + "languages": [ + "C++ 11, Fortran 03 standards" + ], + "name": "Axom", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/axom", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-28", + "metadataLastUpdated": "2020-10-29" + }, + "description": "General multi-physics simulation framework targeting exascale computing platforms.", + "laborHours": 337546.4, + "languages": [ + "C++", + "Python" + ], + "name": "GEOSX Simulation Framework", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GEOSX/GEOSX", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2020-11-02" + }, + "description": "Peak Map is a software tool that allows users to generate nuclide library files for gamma spectroscopy from a nuclear data reference. SAND2019-15220 M\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 7995.2, + "languages": [ + "C#" + ], + "name": "Peak Map", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/Peak-Map/blob/master/PeakMap/LICENSE.rtf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Peak-Map", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-07-29" + }, + "description": "This is software in Python that simulates the quantum approximate optimization algorithm (QAOA) as described in https://arxiv.org/abs/1411.4028. The software has customization that speeds up simulation and provides interface to the Rapid Optimization Library (ROL) developed at Sandia. SAND2019-8935 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 820.8, + "languages": [ + "Python" + ], + "name": "Quantum Approximate Optimization Algorithm in Python", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyQAOA", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-08-07" + }, + "description": "ARG is a computational simulation tool. It generates user-configurable reports, including graphs and images, from user data in various formats.SAND2019-9525 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 10366.4, + "languages": [ + "TeX", + "Perl", + "Python" + ], + "name": "Automatic Report Generator (ARG)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/arg", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-07-30" + }, + "description": "TestSNAP is a stand-alone prototype of the SNAP force kernel used in the LAMMPS molecular dynamics code. It contains synthetic input data (neighbor atom positions) and reference output data (forces on atoms) for several different SNAP models. The prototype performs the force calculation repeatedly, checking the results against the reference data. At the end it reports the grind time [msec/atomstep] and RMS force error [eV/A]. This allows performance experts to quickly test new hardware and software strategies, obtain a realistic performance estimate and verify that the computation was performed correctly. SAND2019-12243 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 181153.6, + "languages": [ + "C" + ], + "name": "TestSNAP", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TestSNAP", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-08-07" + }, + "description": "COEK (C++ Optimization Expression Kernel) is a C++ library that supports the expression and manipulation of algebraic expressions commonly used in optimization applications. COEK. Supports several mechanisms for defining and managing expressions and performing automatic differentiation. COEK also includes low-level interfaces for defining optimization models and interfacing with optimization solvers.SAND2019-14491 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 98070.4, + "languages": [ + "C++", + "Cmake", + "C", + "AMPL", + "NMODL", + "Python" + ], + "name": "COEK", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/coek", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-09-20" + }, + "description": "PAO supports the formulation and analysis of mathematical models for complex optimization applications. This capability is commonly associated with algebraic modeling languages (AMLs), which support the description and analysis of mathematical models with a high-level language. PAO is derived from the Pyomo subpackage pyomo.bilevel, which has been deprecated. PAO supports the formulation and solution of optimization models that explicitly represent adversarial behavior. This includes variances of bilevel programming, including methods that represent challenging problems with discrete decisions and uncertain model parameters.", + "laborHours": 12357.6, + "languages": [ + "Python" + ], + "name": "PAO", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pao", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-09-18" + }, + "description": "Diventi provides a write optimized index of network logs such as netflow or zeek. The program will ingest various network traffic logs (zeek connection logs or NetflowV5, v9 or IPFix logs) and index each IP address and time of its activity. This database can then be queried for timely tracking of network activity. It currently uses the ft-index library from Percona but is adaptable to any key-value store that supports the Berkeley DB api.SAND2019-15037 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 6642.4, + "languages": [ + "C++", + "Makefile", + "Python" + ], + "name": "Diventi", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/opendiventi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2021-03-05" + }, + "description": "Semi-supervised machine learning via consistency regularization", + "laborHours": 820.8, + "languages": [], + "name": "Shadow", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/shadow", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/shadow", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-08-07" + }, + "description": "POEK (Python Optimization Expression Kernel) is a Python library that supports the expression and manipulation of algebraic expressions commonly used in optimization applications. POEK interfaces with the COEK library to support fast methods for defining and managing expressions and performing automatic differentiation. POEK also interfaces with COEK to directly interface with optimization solvers (i.e. without relying on file I/O). SAND2019-14492 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 98070.4, + "languages": [ + "C++", + "C", + "CMake", + "AMPL", + "NMODL", + "Python" + ], + "name": "POEK", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/coek", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "savaraa@ornl.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2020-10-30" + }, + "description": "There is a need to provide a way for dev-users (Scientists, Engineers, and other Software Developers) to get credit (citations) when they contribute to an important software package - particularly a large package that is already established. Various solutions (including cross package) solutions do exist, but a simple standard format that can work between multiple packages and multiple languages in a modular way is not widely available. \n\nCiteSoft_py is a python implementation of CiteSoft. CiteSoft is a plain text standard consisting of a format and a protocol that exports the citations for the end-users for whichever softwares they have used. CiteSoft has been designed so that software dev-users can rely upon it regardless of coding language or platform, and even for cases where multiple codes are working in a coupled manner. The CiteSoft_py implementation includes python decorators to make wrappers for facile use.\n\nThe purpose is that when dev-users (scientists, engineers and professional programmers) contribute to a collaborative software project, that the appropriate citations (e.g., journal article, conference proceeding) are provided to the end-user. The end-user does not need to know how to use a command line interface, API, etc. ", + "laborHours": 258.4, + "languages": [ + "Python" + ], + "name": "CiteSoft_Py", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdityaSavara/CiteSoft_py", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Spitfire is a Python and C++ code for solving canonical flame structure problems to build tabulated chemistry models for the simulation of large-scale fires. Spitfire is a modular software with performance critical code written in C++, abstract numerical methods provided in Python, and chemistry tabulation techniques made convenient for high-level use by non-expert users. It facilitates both high-level usage and novel research in tabulated chemistry approaches. SAND2019-11791 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 60739.2, + "languages": [ + "C++", + "Cython", + "Python" + ], + "name": "Spitfire", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Spitfire", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2020-11-05" + }, + "description": "Tools for extracting and viewing information from zip archives. Simply extracts and displays zip file metadata in a format convenient for analysts.SAND2020-0168 M\n", + "laborHours": 364.8, + "languages": [ + "Python" + ], + "name": "sandialabs/xyz", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/xyz", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.20181129" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2024-07-29" + }, + "description": "miniGAN is a python-based machine learning proxy application for generative adversarial networks, developed through the Exascale Computing Project's (ECP) ExaLearn project. It will be included in the main ECP proxy application and the machine learning proxy application suite. It is a proxy for ECP cosmological(CosmoFlow, ExaGAN) and wind energy(ExaWind) applications. miniGAN will be distributed to ECP hardware vendors as part of hardware codesign. miniGAN uses the Numpy/PyTorch/TensorFlow/Keras/Horovod frameworks and libraries. It also relies on the Kokkos and Kokkos-Kernels packages developed here at Sandia Labs. SAND2020-2038 M\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 516.8, + "languages": [ + "Shell", + "Python" + ], + "name": "miniGAN: a proxy application for generative adversarial networks", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2024-07-29" + }, + "description": "The Java Software Extensibility Library provides tools that help Java software developers produce flexible and extensible Java applications. The major components include a Plugin Library and a Polymorphic Map data structure. The Plugin Library provides developers with a Plugin Registry and a standard pattern for designing, versioning, registering, retrieving, and annotating plugins. It also enables advanced capabilities such as loading plugins at runtime, and creating/loading encrypted plugin packages. The Polymorphic Map data structure facilitates the storage and retrieval of objects of varying types within a single data structure; while maintaining type safety. The library also provides a standard design pattern for producing application-specific \"Domain Maps\" and \"Closed Domain Maps\".SAND2020-3816 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 5715.2, + "languages": [ + "Java" + ], + "name": "Java Software Extensibility Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/jsel", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.9.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2024-08-07" + }, + "description": "Robust Phase Estimation (RPE) is a quantum algorithm to determine the relative phases of eigenstates of a unitary operator. This code implements the classical portion of the RPE algorithm, useful both in simulation (e.g., Sandia's pyGSTi or IBM's Qiskit simulators) and on actual quantum hardware (e.g., IBM's Qiskit Quantum Experience). It additionally implements improvements in these dependent software packages, for both required core function of the RPE and improved usability. SAND2020-12547 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 91.2, + "languages": [ + "Python" + ], + "name": "Python Robust Phase Estimation (PyRPE)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyRPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2024-09-18" + }, + "description": "A set of subroutines that interact with an existing computer program, Quantum Espresso (QE), that takes a set of electronic orbitals from QE and propagates them forward in time in response to a number of perturbations. These perturbations include the motion of ions and a wide spectrum of applied electromagnetic fields (e.g., static magnetic fields, slowly-varying electric fields, x-rays, etc.). From the time evolution of the electronic orbitals comes time-varying values of physical observables like the electronic charge and current densities and atomic forces. These are further post-processed to yield properties of interest like stopping powers, conductivities, and the dynamic structure factor. The electronic orbitals are described in a plane wave basis and the equations of motion are carried out using a unitary or approximately unitary time propagation algorithm. Related work will include subroutines for interfacing this capability, as well as others that already exist within QE, with a fork of QE that is more extensible and modular.SAND2019-12611 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1519589.6, + "languages": [ + "Shell", + "HTML", + "C", + "Roff", + "Fortran", + "PostScript" + ], + "name": "Real-time time-dependent density functional theory in Quantum Espresso and related codes", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/qe-rt-tddft", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "mohror1@llnl.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-01" + }, + "description": "Workflow I/O Emulation Framework", + "laborHours": 4529.6, + "languages": [ + "C", + "C++", + "Perl", + "C", + "python" + ], + "name": "LLNL/Wemul", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/wemul", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2025-02-13" + }, + "description": "GentenMPI is software to compute low-rank approximations of sparse data tensors. These methods are often used for unsupervised machine learning to find significant properties of sparse, unstructured data sets. GentenMPI uses the same algorithms that are available in Sandia's open-source codes TensorToolbox and Genten, but GentenMPI provides distributed memory implementations of these algorithms using infrastructure from Sandia's open-source Trilinos framework. GentenMPI includes an implementation CP-ALS (canonical polyadic decomposition via alternating least squares optimization, first published in 1970 by Carroll & Chang and Harshman); its distributed memory implementation uses Trilinos' Map-based distribution of data to processors and Trilinos' communication operations designed for sparse matrix-vector multiplication. Its performance is comparable to other open-source CP-ALS implementations (e.g., the SPLATT tool of Smith and Karypis). GentenMPI also include a distributed memory implementation of GCP-SGD (generalized canonical polyadic decomposition via stochastic gradient descent, first published in 2019 by Hong, Kolda and Deursch); the implementation closely follows that in TensorToolbox, and exploits a block-based data distribution to perform sampling in parallel. GentenMPI is written in C++ and relies on the MPI (Message Passing Interface) library available on most distributed memory computers. SAND2020-12648 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 12448.8, + "languages": [ + "C++", + "Cmake" + ], + "name": "GentenMPI", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GentenMPI", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-04" + }, + "description": "This is a small but pretty quiz application written in Python for Flask that is meant to be easy to understand for new users of Flask, but not necessarily optimized for performance or security.SAND2020-12216 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 501.6, + "languages": [], + "name": "flasquiz", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/flasquiz", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-12" + }, + "description": "The SEMS Pipeline Framework Infrastructure (SPiFI) library is a collection of utilities that simplify the development of Continuous Integration (CI) / Continuous Delivery (CD) pipelines within the Jenkins testing application.\nThe goal of SPiFI is to provide a layer of convenience functions for common tasks a pipeline developer will need to implement, such as timeouts, automatic retries, dry-run testing, concurrent test launching, results aggregation, and email notifications to accelerate pipeline development. SPiFI enables the DevOPs engineer to focus more on what their pipeline should do rather than how to implement certain details within the restricted programming environment provided by the Jenkins application.SAND2020-12550 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 8664.0, + "languages": [ + "Groovy" + ], + "name": "SEMS Pipeline Framework Infrastructure", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SPiFI", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-13" + }, + "description": "Set of Matlab scripts to investigate properties of IMEX time stepping methods. Scripts include discretization of a system of linearized equations. One script plots numerical dispersion against analytical dispersion of the system. Another set of scripts uses the system to break it into stiff and non stiff part to investigate stability of Implicit-Explicit Runge-Kutta methods. \n\nScripts are based on \nThuburn, J. and Woollings, T. J., Vertical Discretizations for Compressible Euler Equation Atmospheric Models Giving Optimal Representation of Normal Modes , 2005 and\nLock, S.-J. and Wood, N. and Weller, H., Numerical analyses of Runge-Kutta implicit-explicit schemes for horizontally explicit, vertically implicit solutions of atmospheric models, 2014\nexpanding ideas from these two papers.\n\nScripts are used to develop IMEX schemes. SAND2020-12594 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 668.8, + "languages": [ + "MATLAB" + ], + "name": "sta-imex (scripts to investigate stability of IMEX methods)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/sta-imex", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.01" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-03" + }, + "description": "This is software lets one explore the data released as part of the COVID-19 Open Research Dataset Challenge. It downloads and analyzes the natural language text of the data set and then creates a 2D visualization that can be used to explore it. SAND2020-12185 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 152.0, + "languages": [], + "name": "Galen View", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/galen-view/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/galen-view", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2021-03-30" + }, + "description": "WeightedAFL (WAFL) is an improvement to open source fuzzer, American Fuzzy Lop (AFL). Fuzzers modify input to target programs in order to produce crashes and other unintended output in those target programs. WAFL integrates directly with AFL to determine offsets within a buffer that will improve performance metrics. WAFL uses various machine learning techniques to learn these offsets. WAFL also provides a novel software engineering solution to integrate with AFL and allows contributors to quickly write and test algorithms in python. SAND2020-12546 O\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [], + "name": "WeightedAFL", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/sandialabs/wafl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This MATLAB pseudocode perform multivariate curve resolution (MCR) using PCA scores & loadings of data as inputs. It employs rigorous least squares equality and inequality constraints for all elements in the solution factor matrices. It also can be used to perform nonnegative matrix factorization.\nSAND2020-12650 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 91.2, + "languages": [ + "MATLAB" + ], + "name": "Multivariate Curve Resolution (MCR) using Principal Components Inputs and Rigorous Equality and Inequality Constraints", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mcr", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-08-07" + }, + "description": "This is a method of performing trilinear analysis on large data sets using a modification of the PARAFAC-ALS algorithm. It iteratively decomposes the data matrix into a core matrix and three loading matrices based on the Tucker1 model. The algorithm is particularly useful for data sets that are too large to upload into a computer?s main memory. While the performance advantage in utilizing our algorithm is dependent on the number of data elements and dimensions of the data array, we have seen a significant performance improvement over operating PARAFAC-ALS on the full data set.\nSAND2020-12649 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 60.8, + "languages": [ + "MATLAB" + ], + "name": "PARAFAC_T1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PARAFAC_T1", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-07-29" + }, + "description": "Code developed in conjunction with a research paper. This code demonstrates how to identify static graph snapshots from a stream of communication events. A second, related code generates simulated communication events with known split moments for accuracy testing.SAND2020-12245 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 653.6, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "EASEE: Edge Advertisements into Snapshots using Evolving Expectations", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Easee", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-01" + }, + "description": "Prescient is a software package for simulating electricity grid (power systems) operations, under both nominal and extreme event conditions. Core functionality includes discrete event simulation, commitment and dispatch optimization, probabilistic scenario construction, and reporting/visualization. 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The FLMD parser outputs the metadata as a JSON and can be configured to updated the source file or produce an external companion file.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ESS-DIVE File Level Metadata Extractor", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/ngee-arctic/ess-dive-meta", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/ngee-arctic/ess-dive-meta", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-04", + "metadataLastUpdated": "2024-09-18" + }, + "description": "This code solves a steady state heat equation problem on a wire with random walks implemented using a spiking neural algorithm. 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SAND2019-13500 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1246.4, + "languages": [ + "C++" + ], + "name": "Packet2Vec", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/packet2vec", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-09", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Parapint is a Python package for parallel solution of dynamic optimization problems. SAND2020-12446 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 3359.2, + "languages": [ + "Python" + ], + "name": "Parapint", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/parapint", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-09", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The code that was developed is called SAMM (Semi-Analytic MagLIF Model). In 2015, McBride and Slutz published all of the equations that are solved by the code in the original SAMM paper: R. D. McBride and S. A. Slutz, ?A semi-analytic model of magnetized liner inertial fusion?, Phys. Plasmas 22, 052708 (2015); http://doi.org/10.1063/1.4918953. The SAMM code is now implemented in both the MATLAB and Python programming languages. Students from multiple universities have requested copies of the code so that they can become more familiar with the MagLIF concept. We would like to seek an open-source solution. There is no market value to this code, as there are plenty of more sophisticated simulation codes already available; SAMM is merely a simplified model that is purely for educational purposes. In fact, at least one graduate student (from the University of California, San Diego) has already implemented and published his own modified version of the model: J. Narkis, H. U. Rahman, J. C. Valenzuela, F. Conti, R. D. McBride, D. Venosa, and F. N. Beg, ?A semi-analytic model of gas-puff liner-on-target magneto-inertial fusion?, Phys. Plasmas 26, 032708 (2019); https://doi.org/10.1063/1.5086056. SAND2020-12244 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 4438.4, + "languages": [ + "Python" + ], + "name": "Semi-analytic model of magnetized liner inertial fusion", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pysamm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-11-09", + "metadataLastUpdated": "2022-01-05" + }, + "description": "QTensor is a quantum circuit simulator designed to run efficiently in parallel mode on large supercomputers. It is based on the tensor network representation of quantum circuits. The simulator is flexible and agnostic to both the connectivity map of the quantum device and the types of gates used in the circuit.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "QTENSOR", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-11-09", + "metadataLastUpdated": "2022-01-05" + }, + "description": "A methodology and tool for computing the benefits and costs of Advanced Distribution Management Systems (DMS) for Grid Modernization. It suggests an approach for monetizing the \"functional\" benefits, expressed in non-monetary terms, such as System Average Interruption Duration Index/System Average Interruption Frequency Index (SAIDI/SAIFI) reduction and improved efficiency, using commonly available technical and financial parameters. It offers a model for individual utilities to determine the estimated costs and benefits using their own specific data. Where actual utility-specific data is not available, industry default values are offered. The model uses discounted cash flow (DCF) analysis to evaluate the economic justification for an investment in DMS.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "DVCalc", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Reduced-order Models (ROMs). ROMs are \"compressed\" approximations of high-fidelity computational models. Implementing ROM methods in production codes is typically intrusive, i.e. the native codes must be adapted and modified, with individual ROM methods reimplemented in every application code. This clearly constitutes an obstacle to users who want to use ROMs. To address this, we have developed Pressio, which is a C++ header-only ROM library that can be used by an application code in a non-intrusive fashion. The main objectives behind the design of Pressio are: (a) support for general computational models (data structures, PDE types); (b) heterogeneous hardware (CPU, GPU); (c) performance; and (d) extensibility. Using metaprogramming techniques, Pressio detects and leverages the application?s native linear algebra data structures (e.g. vector and matrix) to run the ROM methods. The application only needs to expose the velocity vector and Jacobian matrix via an adapter class. Pressio checks at compile time that the target application meets the correct API. The library is structured in several modular packages including (a) non-linear least-square solvers (e.g. Gauss-Newton with and without line-search); (b) singular value decomposition (for the computation of the ROM generalized coordinates) and (c) algebraic hyper-reduction.SAND2019-5878 M", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 49354.4, + "languages": [ + "C++" + ], + "name": "Pressio", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2021-10-01" + }, + "description": "This code is comprised of example problems to show implementation details of our SCITECH 2021 paper :Open-Source, Object-Oriented, Multi-Phase Pseudospectral Optimization Using Pyomo.\" Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2020-13973", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Pyomo Optimization Example Problems v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyomo_optimization_example_problems", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2022-04-13" + }, + "description": "SAND2020-13696 M BigDNA takes a user input fast DNA sequence and outputs overlapping long PCR primers for Gibson Assembly. The software can design primers that remove gene products, insert new gene products, or completely circularize long DNAs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Perl", + "Python" + ], + "name": "BigDNA", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/bigdna", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2024-08-07" + }, + "description": "IIA is a solver for optimizing integer matrix problems Ax=b. It was developed to decide the number of mesh edges on model curves (intervals) for quad and hex meshing. Meshing schemes impose constraints ranging from the mild requirement (i.e. that any quad mesh must have an even number of edges on its boundary) to structured mapped patches where opposite sides of a rectangle must have exactly equal numbers of edges. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.\nSAND2020-13618 M", + "laborHours": 2004074.4, + "languages": [ + "C++" + ], + "name": "IIA Incremental Interval Assignment", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IntervalAssignment", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2020-11-10" + }, + "description": "Software application: Sandia RPM Lane Simulator.\nSimulates Rapiscan radiation portal monitors and network cameras that are in use in the NNSA Nuclear Smuggling Detection and Deterrence (NSDD) program. SAND2019-3741 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 28728.0, + "languages": [], + "name": "Sandia RPM Lane Simulator ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SRLS", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2020-11-18" + }, + "description": "Submission-beluga is an open-source optimal control software that uses publicly available indirect methods to model inequality constraints at boundaries. This release of beluga introduces a method known as UTM, modified handling of constraints to support the UTM method, and includes bug fixes and related requirements changes.SAND2020-12847 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 20337.6, + "languages": [], + "name": "beluga", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2024-09-12" + }, + "description": "The Verdict code verifies the correctness of a finite element mesh stored in the Exodus II fine format. Verdict calculates multiple quality metrics for each individual element, verifies local and global connectivity, analyzes interfaces between element blocks, predicts the probability topology of the mesh, and prints out any problems discovered. SAND2019-7026 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 10138.4, + "languages": [ + "C++", + "CMake" + ], + "name": "Verdict", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/verdict", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2024-08-07" + }, + "description": "This work presents a method of performing PARAFAC2 factorization of a three-way data using a compact representation of the data. The data are decomposed into a core matrix and sets of orthogonal loading matrices. The algorithm is particularly useful for very large data sets and essentially permits imposition of nonnegativity in all three modes. SAND2019-10097 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 91.2, + "languages": [ + "MATLAB" + ], + "name": "CANDELINC2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CANDELINC2", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2024-08-07" + }, + "description": "The Chemical Asset Tracker, CAT, is a web-based (browser) application for tracking chemical inventories. The application records information about stored chemicals from user input (via the keyboard, barcode readers, or mobile device) and stores that information into a database. A tiered user login controls access to functions in the application. A user interface is provided that allows users to search the database and update data in the database. SAND2019-7525 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 194772.8, + "languages": [ + "C#", + "Python" + ], + "name": "Chemical Asset Tracker (CAT)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ChemicalAssetTracker", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2021-02-09" + }, + "description": "This software is extended from HPX, open source software (the copyright belongs to Louisiana State University). SAND2019-5457 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.\n", + "laborHours": 696965.6, + "languages": [], + "name": "HPXr, HPX with Resilience Extension", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/STEllAR-GROUP/hpx/blob/master/LICENSE_1_0.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/STEllAR-GROUP/hpx", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2024-08-07" + }, + "description": "Principal component analysis (PCA) is arguably the most popular tool in multivariate exploratory data analysis. We consider the question of how to handle heterogeneous variables that include continuous, binary, and ordinal. In the probabilistic interpretation of low-rank PCA, the data has a normal multivariate distribution and, therefore, normal marginal distributions for each column. If some marginals are continuous but not normal, the semiparametric copula-based principal component analysis (COCA) method is an alternative to PCA that combines a Gaussian copula with nonparametric marginals. If some marginals are discrete or semi-continuous, we present a new extended PCA (XPCA) method that also uses a Gaussian copula and nonparametric marginals and accounts for discrete variables in the likelihood calculation by integrating over appropriate intervals. Like PCA, the factors produced by XPCA can be used to find latent structure in data, build predictive models, and perform dimensionality reduction. We implement the new model, XPCA, and its ancestors PCA and COCA in both R and Python. This software provides implementations of XPCA, COCA, and probabilistic PCA in both R and Python. XPCA is written in arXiv report https://arxiv.org/abs/1808.07510. SAND2019-10591 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 425.6, + "languages": [ + "Python" + ], + "name": "XPCA -Python Implementation", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/xpca", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2020-11-11" + }, + "description": "Gulliver is a C# utility package and library engineered for the manipulation of arbitrary sized byte arrays accounting for appropriate endianness and jagged byte length. Functionality includes the as previously unsupported standard set of boolean algebraic operations, bitwise shifting, and unsigned endian aware mathematical addition, subtraction, and comparison. Gulliver exists to free developers from managing byte ordering and operations and the low level as was previously required by the standard C# language distributions.SAND2019-8990 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.\n", + "laborHours": 3724.0, + "languages": [ + "C++" + ], + "name": "Gulliver", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Gulliver", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "facklerpw@ornl.gov" + }, + "date": { + "created": "2020-11-17", + "metadataLastUpdated": "2020-11-17" + }, + "description": "Custom spatial subdivision of N-dimensional lattice region in GPU memory. An extension of the method of a hyper-octree is used to allow for arbitrary subdivision ratios in each dimension. In addition, the decision to refine (or select) a given sub-region is based on a user-provided callback, allowing for arbitrary refinement domains to be expressed either geometrically or programmatically.", + "laborHours": 2432.0, + "languages": [ + "C++" + ], + "name": "Parallel Lattice Subpaving Map (plsm)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-Fusion/plsm", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-11-18", + "metadataLastUpdated": "2020-11-20" + }, + "description": "SEEDling is intended to simplify the merging of multiple data sources prior to importing into the SEED platform. Geographic information about buildings and taxlots is often obtained from various data sources, and the process of synthesizing this information for many buildings across a city can be burdensome for city data managers. SEEDling uses GIS tools to automate and simplify this process, as well as apply criteria for SEED inclusion (ex: sqft > 50k) and assign UBIDs, to create records that can be easily imported into the SEED platform.", + "laborHours": 87628.0, + "languages": [], + "name": "SEEDling", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SEED-platform/seedling", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-20", + "metadataLastUpdated": "2020-11-30" + }, + "description": "A-PRIME, is a collection of scripts designed to provide Accelerated Climate Model for Energy (ACME) model developers and analysts with a variety of analysis of the model needed to determine if the model is producing the desired results, depending on the goals of the simulation. The software is csh scripts based at the top level to enable scientist to provide the input parameters. Within the scripts, the csh scripts calls code to perform the postprocessing of the raw data analysis and create plots for visual assessment.", + "laborHours": 5107.2, + "languages": [ + "Csh; python/2.7.3; bash; ncl/6.3.0; nco/4.6.4" + ], + "name": "ACME Priority Metrics (A-PRIME)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/a-prime", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "Simulations and analyses of data from hexagonally pixelated detectors require conversions from a Cartesian coordinate system to and from a hexagonal pixel index. This software builds and indexes the detector geometry, calculates neighbors and coordinate system conversions, and provides a framework for plotting analysis results.", + "laborHours": 440.8, + "languages": [ + "C++;gcc;4.8.4" + ], + "name": "HexFinder", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/leahbroussard/HexFinder/-/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/leahbroussard/HexFinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The Workbench Analysis Sequence Processor (WASP) was developed to streamline lexing, parsing, access, validation, and analysis of ascii text files.", + "laborHours": 81426.4, + "languages": [], + "name": "Workbench Analysis Sequence Processor", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/neams-workbench/wasp/-/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/neams-workbench/wasp", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The J-integral vs. crack growth resistance curve (J-R curve) is a useful tool for evaluating material fracture toughness in the ductile condition. A widely accepted practice for conducting tests to obtain J-R curves is ASTM standard E1820, in which the normalization method was introduced as an alternative method for determining the J-R curve. The normalization method requires solely force-displacement data, together with initial and final crack size measurements from a specimen to derive the J-R curve. Because of the elimination of the compliance measurement, the normalization method significantly simplifies testing requirements to obtain J-R curve. Despite these advantages, the analysis procedures of the normalization method are quite complicated to follow, which may limit the wide application of this method. To address this, we have developed a software with user-friendly graphic interface to perform automated normalization analysis. Any users, even without detailed knowledge of the normalization analysis, can use this software to derive J-R curves based on the ASTM E1820 normalization method.", + "laborHours": 4301.6, + "languages": [ + "MATLAB" + ], + "name": "Automated J-R Curve Analysis Based on the ASTM E1820 Normalization Method", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/xc8/ANJR", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/xc8/ANJR", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "Developers at ORNL explored how a deep learning (DL) approach based on hierarchical attention networks (HANs) can improve model performance for multiple information extraction tasks from unstructured cancer pathology reports compared to conventional methods that do not sufficiently capture syntactic and semantic contexts from free-text documents. The HAN was implemented for 2 information extraction tasks: (1) primary site, matched to 12 International Classification of Diseases for Oncology topography codes (7 breast, 5 lung primary sites), and (2) histological grade classification, matched to G1\u2013G4. Our results demonstrate that for both information tasks, HAN performed significantly better compared to the conventional ML and DL techniques.", + "laborHours": 501.6, + "languages": [ + "Python 2.7" + ], + "name": "PathRepHAN: Hierarchical attention networks for pathology report classification", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/v33/PathRepHAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "Machine learning (ML) models often contain numerous hyperparameters, free parameters that must be set before the models can be trained. As the number of model hyperparameters increases, their optimization becomes significantly more challenging as we face a combinatorial increase in potential model configurations. Similarly, there is an increased chance that our models\u2019 hyperparameters interact in complex ways. HyperSpace allows a user to optimize complex machine learning algorithms based on their hyperparameters. HyperSpace works by parallelizing parameter search spaces, running Bayesian model based optimization (SMBO) over each of these spaces in parallel. It was designed to be as minimally invasive as possible such that very little change to existing code will be needed to get a user started.", + "laborHours": 1717.6, + "languages": [ + "Python 3" + ], + "name": "HyperSpace", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yngtodd/hyperspace", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2024-08-23" + }, + "description": "This code solves the Vlasov-Poisson equations in 6-dimensions without approximation. It uses sparse grid discretization to solve the high-dimensional PDEs. The code functions as a discontinuous Galerkin finite element solver. Advantages/benefits include no approximations, supports high-dimensionality, leadership-scale capability, and implicit time advance.", + "laborHours": 33029.6, + "languages": [ + "C++17" + ], + "name": "Adaptive Sparse Grid Discretization (ASGarD)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/project-asgard/asgard/releases/tag/v0.5.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v0.5.0" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "A collection of MATLAB scripts forming a toolbox for video (frame by frame) detection and tracking of beads imaged with fluorescence microscope for estimating bead flow and location tracks. Scripts accept tiff image stacks of video frames and provide bead locations and tracked positions over frames in stack. Various utility functions are also provided to assist in data I/O. A custom solution for specific data source - specifically, the software works well for noisy/out of focus florescence microscopy images.", + "laborHours": 7645.6, + "languages": [ + "MATLAB/2018a" + ], + "name": "Bead-Tracking Toolbox for MATLAB", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dnbornl/beadtracking", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "Data science capabilities are becoming important more and more. Even though there exist many data science and machine learning tools, they are not intuitive for many traditional scientists who are not familiar with programming. ASCENDS provides easy and intuitive interfaces (command-line interface, graphical user interface) to users so they can use data science capabilities without having to understand programming language. ASCENDS performs data visualization, machine learning model training, storing and prediction (regression problem), automatic hyperparameter tuning, and supports various machine learning models including random forest, kernel ridge, nearest neighbor, neural network, etc. Users can use standard CSV (comma separated values) format data set and investigate the feature columns that are highly correlated to a target column; further, they can learn ML models, then store and use them for predictions. The tool is supposed to be generically applicable so that it can be used for many different applications.", + "laborHours": 101414.4, + "languages": [ + "Python 3.7" + ], + "name": "ASCENDS: Advanced Data SCiENce Toolkit for Non-Data Scientists", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornlpmcp/ASCENDS", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The PySCL (Python Standard Composition Library) is a library that provides a standard and consistent method of specifying the material mixtures for a given problem. The library enables software to use standard nuclide names and convenient naturally occurring composition and elemental abundances.", + "laborHours": 22055.2, + "languages": [ + "Python" + ], + "name": "PySCL", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/neams-workbench/PySCL", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "There is a need to easily and uniformly capture, access, enrich, organize, search, and collaborate on working scientific data sets across geographically distributed experiment, computation, and data analytics facilities. DataFed provides a set of services and applications enabling simple and uniform cross-facility scientific data management with federated (distributed) data repositories. This solution greatly reduces effort required by scientist to organize and/or move data between facilities/institutes, Reduces likelihood of misidentification and subsequent misuse of data, and improves scientific reproducibility through deep, domain-specific context and provenance capture.", + "laborHours": 83797.6, + "languages": [ + "C++11 GCC 5.x or grerater; Python 3" + ], + "name": "DataFed", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/DataFed", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The software titled \"nccd\" is used for running residual neural networks (ResNets) on images of nuclear canisters. The software provides only the code for the implementation (based on the fastai library), but it does not share the image data. The compute code allows the use of residual nets (and more generally of other deep learning models) for classifying images from nuclear canisters as corroded. or intact. An image is considered to be corroded if it contains pitting or stress corrosion cracks. The code trains ResNets on image tiles extracted from original images from nuclear canisters, and then implements a classification rule, which can be applied to a validation set to decide if each original image is corroded or intact. The software automates the process of using images taken from nuclear canisters to detect corrosion. It provides also scope for future research directions on the basis of the existing research and code.", + "laborHours": 486.4, + "languages": [ + "Python (v3.6 onwards)" + ], + "name": "Nuclear Canister Corrosion Detection", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/papamarkou/nccd", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2021-03-05" + }, + "description": "Air dehumidification processes are important and significantly impact both the performance of building ventilation and air conditioning systems, and the health of occupants. In a membrane-based dehumidifier, a permselective membrane is adopted to separate the two flow streams at feed and permeate sides. The feed side is continuously supplied with humid air at atmospheric pressure, while the permeate side is connected to a vacuum pump to produce vacuum or a low permeate vapor pressure as a driving force for water vapor permeation. The software MBMS 1.0 enables modeling and simulation of the design and configuration optimization of a membrane-based air-to-air (A2A) or air-to-vapor (A2V) device. A first-order physical-constant model was developed to reasonably account for the fundamental heat and mass transfer processes involved.", + "laborHours": 1200.8, + "languages": [ + "C", + "C++" + ], + "name": "MBMS1.0: An Open-Source Code for Modeling and Simulation of Membrane-Based Dehumidification and Energy Recovery", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MBMS/C-CODE_FOR_MEMBRANE_BASED_MODEL", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "MBMS. 1.0" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The existing methodologies for gathering and computing zonal statistics from the combination of a raster image and a shapefile either require advanced programming knowledge in at least one language or the use of proprietary software such as ArcGIS. The software \u201cChoppy Lite\u201d offers several solutions for acquiring zonal statistics that can be used without proprietary software or programming knowledge. This software provides a Docker-based ecosystem, allowing users of any experience level to simply run a single line command in a terminal prompt independent of the operating system. Intermediate to advanced users can import the class provided by the software package into their own Python scripts.", + "laborHours": 425.6, + "languages": [ + "Python 3.8" + ], + "name": "Choppy Lite", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nset-ornl/choppy", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The software code titled \u201cScripts for Running Multiple Lunes of Evidence Analysis\u201d enables high throughput network analysis; efficient analysis of large multi-omic networks in order to rank genes by connectivity. This code creates a set of scripts that take omic networks as input as well as list of known genes and calculates scores for all other genes in genome based on connectivity to those genes and does so accurately and efficiently. In addition, it aids the user in performing a validation check of observed data to random. The code outputs a table of all genes in the genome with LOE scores and scores observed data versus random.", + "laborHours": 76.0, + "languages": [ + "Python 3.6" + ], + "name": "Scripts for Running Multiple Lines of Evidence Analysis", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/afurches/Cell_Wall_LOE", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2022-02-15" + }, + "description": "SLiDE (Scalable Linked Dynamic Equilibrium) replicates the blueNOTE (National Open source Tools for general Equilibrium analysis) datastream from the Wisconsin National Data Consortium. From there, it produces a recursive dynamic computable general equilibrium model of the US states and eventually the global/national economies. The datastream operations have been set up to allow for scalability of both regions and sectors represented. The model has the capability to flexibly define functional forms similar to other general equilibrium model construction software.", + "laborHours": 3724.0, + "languages": [ + "Julia" + ], + "name": "Scalable Linked Dynamic Equilibrium (SLiDE)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/slide", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The Panel-Segmentation package is a computer vision (CV) framework for automated metadata extraction for solar PV arrays using satellite imagery. With Panel-Segmentation, a user inputs a set of latitude-longitude coordinates to automatically generate a satellite image using the Google Maps API, and runs the image through a deep learning framework to get a pixel-by-pixel representation of the solar panel(s) in an image. If a solar array is located, the user can then perform spectral clustering to cluster individual solar arrays in an image (if applicable), and run each cluster through an azimuth estimation algorithm. This package framework is versatile, allowing for future CV techniques to be added and/or modified. ", + "laborHours": 2158.4, + "languages": [ + "Python" + ], + "name": "Panel-Segmentation", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Panel-Segmentation", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-12-03", + "metadataLastUpdated": "2023-10-11" + }, + "description": "CatCost\u2122 enables catalyst researchers to develop comprehensive estimates of the cost to produce pre-commercial catalysts early in the catalyst development process. It includes both web browser and Excel-based tools, each with distinct strengths. The web tool includes powerful visualization capabilities, while the Excel tool allows for high degrees of control and customization by power users. The CatCost\u2122 Python Data Tools are designed to facilitate the transfer of data from the Excel tool to the web tool, so that users can take advantage of both the powerful visualization in the web tool and the higher degree of customization available in the excel tool. Rather than painstakingly copying entries from estimates, the materials, equipment, and spent catalyst libraries from Excel to a JSON format for the web tool, the CatCost\u2122 Data Tools provide an intuitive applet which allows them to simply choose which library or estimate they wish to transfer, and then returns files that integrate smoothly with the web version of the tool.", + "laborHours": 1824.0, + "languages": [ + "Python" + ], + "name": "CatCost\u2122 Data Tools [SWR-20-59]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/catcost-data-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MEEDS is a cybersecurity solution that empowers under resourced owners and operators of critical energy infrastructure to rapidly identify and detect the publicly exposed and vulnerable operational technology (OT) and other critical Industrial Control and Energy Delivery Systems.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Mitigation of External Exposure of Energy Delivery System (MEEDS).", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Thermoelectric Capacity at Risk Analysis Tool for ERCOT. capratTX is a unique R package, featuring algorithms for simulating water storages that provide cooling water for thermoelectric power plants. The tool may be used to compute long-term \"capacity at risk\" under a range of future climate\nprojections.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/capratTX", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/capratTX", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-12-09", + "metadataLastUpdated": "2020-12-09" + }, + "description": "coreFPU is a simple test code designed to detect bac CPU's.", + "laborHours": 0.0, + "languages": [], + "name": "coreFPUtest Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/coreFPUtest/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/coreFPUtest", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-12-11", + "metadataLastUpdated": "2024-01-04" + }, + "description": "The Distributed Generation Market Demand (dGen\u2122) model is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The National Renewable Energy Laboratory (NREL) developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States within a single modeling platform. The dGen model builds on, extends, and provides significant advances over NREL\u2019s SolarDS model (Denholm et al. 2009), which is now deprecated.", + "laborHours": 17540.8, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "dGen\u2122 (Distributed Generation Market Demand Model) [SWR-17-09]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dgen", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-14", + "metadataLastUpdated": "2020-12-14" + }, + "description": "Palm/FastFootprints implements two method for rapid memory footprint access diagnostics. The two methods are whole program and precise. Current footprint analyses can cause 200\u00d7 or more slowdown with realistic inputs and are therefore impractical. The whole-program method reduces the overhead to 10% by computing upper bounds, but still yields interprocedural insight through a call path profile. Our precise method uses additional static analysis and profiling to refine the upper bounds for intra-procedural loop nests.", + "laborHours": 0.0, + "languages": [], + "name": "Palm/FastFootprint", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab-hub/palm/palm-memory", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-14", + "metadataLastUpdated": "2020-12-14" + }, + "description": "BigFlowSim is a workflow I/O simulator that captures key implementation choices for remote I/O, including intensity, reuse, locality, access pattern, and data movement. With BigFlowSim, it is possible to generate synthetic benchmarks, and then perform sensitivity analyses to quantify the effects of the various I/O parameters. In addition to generating synthetic workflows, BigFlowSim is also able to replay traces (of I/O access) captured from execution of actual distributed scientific workflows.", + "laborHours": 0.0, + "languages": [], + "name": "BigFlowSim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab-hub/tazer/tazer-bigflow-sim", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-14", + "metadataLastUpdated": "2020-12-14" + }, + "description": "MIAMI was designed for Pin 2. Unfortunately, Pin 2 is deprecated and no longer runs on modern versions of Linux. For example, it does not work on RHEL 7.x. In particular, Pin 2 requires a C++ ABI <= GCC 4.4.", + "laborHours": 0.0, + "languages": [], + "name": "MIAMI-NW", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab-hub/palm/miami-nw", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "OpenCGRA is an open-source framework for modeling, testing, and evaluating CGRAs. The first open-source integrated framework able to support the full top-to-bottom design flow for specializing and implementing CGRAs: modeling at different abstraction levels (functional level, cycle level, register-transfer level) with compiler support, verification at different granularities (unit testing, integration testing, property-based testing), simulation, generation of synthesizable Verilog, and characterization (area, power, and timing).", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/OpenCGRA", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/OpenCGRA", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "Dynamic Importance (DynIm) Sampling is a new approach for importance sampling in high-dimensional space. DynIm has two key characteristics. (1) Importance sampling: The notion of importance of candidate samples is used to guide the sampling, where importance is defined based on the (dis)similarity from previously selected samples (via Euclidean distance metric). (2) Dynamic sampling: The sampling can be performed dynamically, as new candidates are generated and new samples must be selected.\nDynIm was developed as part of a machine learning based coupling of scales in large multiscale simulations and can be used for a variety of applications.", + "laborHours": 0.0, + "languages": [], + "name": "Dynamic Importance Sampling", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/dynim", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "Archspec aims at providing a standard set of human-understandable labels for various aspects of a system architecture like CPU, network fabrics, etc. and APIs to detect, query and compare them. This project grew out of Spack and is currently under active development. At present it supports APIs to detect and model compatibility relationships among different CPU microarchitectures.", + "laborHours": 0.0, + "languages": [], + "name": "archspec", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/archspec/archspec", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "Software including a Bayesian multitask learning model. The pipeline includes functionality to process data, train, evaluate models, and generate reports.", + "laborHours": 0.0, + "languages": [], + "name": "Bayesian Multitask with Structure Learning", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/bmsl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "CRADL captures performance metrics of machine learning algorithms operating on mesh data from multiphysics\ncodes This proxy application is a tool to explore scalability of inference on HPC platforms, and also gather performance metrics for inference on new machine learning specific hardware. CRADL is designed to give users as fine a control as possible over an inference simulation. Users may\nselect the number of cycles, amount of data, and batch size to pass to the accelerator of choice. Additionally the user may select a number of performance optimization libraries and flags. CRADL comes packaged with a repository of anonymized multi-physics simulation data, as well as a\npretrained model for inference. The code allows a user to load their own pre-trained model and data if they wish. The code can operate in multiple parallelization schemes, with performance enhancing options such as half-precision libraries, PyTorch benchmarking, and pinned memory with non-blocking data transfers.\n", + "laborHours": 0.0, + "languages": [], + "name": "Concurrent Relaxation through Accelerated Deep Learning", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CRADL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "HavoqGT (Highly Asynchronous Visitor Queue Graph Toolkit) is a framework for expressing\nasynchronous vertex-centric graph algorithms, and executing them on High Performance Computing (HPC) systems. It provides a vertex 'visitor' interface, where actions are defined at an individual vertex level, and contains a suite of classic graph algorithms. HavoqGT is capable of processing large graphs stored in NVRAM (SSDs) using a memory mapped interface.\n", + "laborHours": 15139.2, + "languages": [], + "name": "Highly Asynchronous Visitor Queue Graph Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/havoqgt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.2" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "Very early stages of a simple tool able to create multiple automated requests of different Independent System Operators (ISOs) data, and download it in comma separated value (.csv) files.\n", + "laborHours": 0.0, + "languages": [], + "name": "ISO Data Automated Request Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ISO-DART", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "MPIDiff is a C++ library for pairing a correct version of an executable with a version that may have bugs\nor race conditions in it. The correct version checks that the data communicated from the other program\nmatches its own and reports any differences.", + "laborHours": 0.0, + "languages": [], + "name": "MPIDiff", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MPIDiff", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-12-18", + "metadataLastUpdated": "2020-12-21" + }, + "description": "This library includes in-progress code for the optimization of materials and molecules using reinforcement learning. This project seeks to develop a generalized machine learning approach for optimizing targeted, and often complex, functional properties over the space of possible material structures, allowing faster identification of promising candidates. Electronic and transport properties of materials are determined by their molecular structure (for molecules) or their crystal structure (for in-organic crystalline materials). The atomic composition, bonding, and 3-D-spatial arrangement in these systems therefore represent a vast, discontinuous search space for optimal candidates. This library implements AlphaZero style reinforcement learning applied to two worked examples: the optimization of stable organic radicals for redox flow batteries, and the determination of stable electrolyte species for solid state batteries. The current code contains proof-of-concept results run on the Eagle HPC system, while the completed package will be a flexible tool for material optimization across of number of energy-relevant fields, which leverages cloud compute resources for the majority of the computational heavy lifting.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "rlmolecule: A library for general-purpose material and molecular optimization using AlphaZero-style reinforcement learning", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rlmolecule", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-12-23", + "metadataLastUpdated": "2023-06-09" + }, + "description": "Modern high-performance buildings exhibit an increasing number of building loads that use direct current (DC) electricity internally, rather than alternating current (AC), due to the advent of low-cost computing and advanced power electronics. Powering DC devices from the AC grid requires AC/DC power conversion, which introduces energy losses and reduces efficiency. As DC loads proliferate, the cumulative wasted energy associated with hundreds of millions of AC/DC converters has become one of the broadest energy savings opportunities in buildings.\n\nDC power distribution systems have been proposed as an elegant and transformative solution to the problem of DC devices. In a DC distribution system, the building's wires carry DC electricity, rather than AC; and a few centralized, highly efficient AC/DC converters replace the many smaller, less efficient converters that serve individual DC loads. Unfortunately, the trade-offs associated with DC distribution systems are not well understood. Reported energy savings associated with DC power distribution differ widely and have not been well validated.\n\nThe Building Electrical Efficiency Analysis Model (BEEAM) is a Modelica library that simulates the efficiency of building electrical distribution systems using harmonic power flow. BEEAM can model a wide variety of building distribution topologies, including three-phase AC, single-phase AC, unipolar DC, bipolar DC, and hybrid networks under both balanced and unbalanced load conditions. BEEAM accurately models power electronic converter losses, provides granular estimates of losses throughout the distribution system, and properly models efficiency at part load conditions. Users can package BEEAM within a functional mockup unit (FMU), enabling co-simulation with other modeling platform, such as EnergyPlus. In summary, BEEAM provides a tool suite for fair and accurate comparison of the efficiency of building electrical distribution systems, including AC, DC, and hybrid systems.", + "laborHours": 0.0, + "languages": [ + "Modelica", + "MATLAB", + "Ruby", + "Jupyter ", + "Python" + ], + "name": "BEEAM (Building Electrical Efficiency Analysis Model) [SWR-20-107]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BEEAM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "obriense@ornl.gov" + }, + "date": { + "created": "2020-12-29", + "metadataLastUpdated": "2020-12-29" + }, + "description": "Neutron multiplicity analysis is a widely used technique in international safeguards and is most commonly applied to the assay of product and scrap materials in the production of mixed oxide fuel. The typical neutron multiplicity analysis applies only a crude, almost cursory, uncertainty\nanalysis limited to propagation of statistical errors in the derived singles, doubles, and triples count rates through the point source model. An assay result without a properly assigned uncertainty has little value, and an assay result with a significantly understated uncertainty can lead to\nboth unsafe facility operations and an increased misclassification rate for the item of interest. We have developed a complete and robust total measurement uncertainty treatment for multiplicity analysis that incorporates instrumental, environmental and nuclear data error contributions.", + "laborHours": 0.0, + "languages": [ + "Visual Basic .NET" + ], + "name": "Multiplicity TMU Estimator", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/multTMU/multTMU", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Deep learning approaches which incorporate geophysical data and readings from multiple remote sensing platforms for predictive mapping of vegetation over very large, ecologically diverse regions.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/fieryfuture", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/fieryfuture", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Framework that can produce visually compelling articles for project research. The design of our framework is centered around simplifying content creation so that researchers unfamiliar with the underlying technology stack can still produce informative, beautiful research documents with interactive and visual features.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Deep-Learning-Control-with-Embedded-Physical-Structure", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Deep-Learning-Control-with-Embedded-Physical-Structure", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Open source release of Python Systems Library which contains benchmark datasets, system emulators, and data loading codes.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/slim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/slim", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "software library of structured linear maps that can be used as drop in replacements for Pytorch linear layers.\nThese maps can be used to enforce physically realistic outcomes to data-driven machine learning scientific modeling problems.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/psl", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/psl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2021-01-12" + }, + "description": "The (wind) turbine-models GitHub repo hosts an archive/database of turbine models already in the public domain. This includes mainly tabular power and thrust (when available) curve data in .csv files, other technical data, as well as documentation and references built with Sphinx/GitHub Pages. There is a script called \"curve_parser.py\" to assist with the parsing of power and thrust curves, but this repo is mostly a central location for turbine model data.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "turbine-models", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/turbine-models", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-12", + "metadataLastUpdated": "2024-02-27" + }, + "description": "Industrial Control Systems protocol parsers plugins for the Zeek network security monitoring framework. Currently we have four fully developed protocol parsers but we plan on adding more in the future. The protocol parsers we currently have developed are for BACnet, DNP3, Ethernet/IP, and Modbus.", + "laborHours": 0.0, + "languages": [], + "name": "Industrial Control Systems Network Protocol Parsers", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/cisagov/ICSNPP", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2023-03-08" + }, + "description": "LIGGGHTS-INL is a capability-extended version of LIGGGHTS. LIGGGHTS is an Open Source Discrete Element Method Particle Simulation Software (https://www.cfdem.com/media/DEM/docu/Manual.html). LIGGGHTS stands for LAMMPS improved for general granular and granular heat transfer simulations. LAMMPS is a classical molecular dynamics simulator. It is widely used in the field of Molecular Dynamics (https://lammps.sandia.gov/doc/Manual.html). Thanks to physical and algorithmic analogies, LAMMPS is a very good platform for DEM simulations. LAMMPS offers a GRANULAR package to perform these kinds of simulations. LIGGGHTS aims to improve those capability with the goal to apply it to industrial applications.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Granular Flow", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/LIGGGHTS-INL", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2023-03-15" + }, + "description": "This software produces general location descriptions from time-series location data collected from mobile devices that record global positioning system (GPS) coordinates over time. The purpose of this software is to convert detailed location history data, which is considered personally identifiable information (PII), into non-traceable, anonymized, generic information that is useful to researchers but does not contain PII. The software is specifically designed for use with trigger-based data that describe the parked locations and dwell times of automobiles.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Location Generalizer", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Location-Generalizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Hierarchical Parallel Tensor Infrastructure (HiParTI), is to support fast essential sparse tensor operations and tensor decompositions on multicore CPU and GPU architectures. It consists of sparse tensor decompositions, CANDECOMP/PARAFAC (CP) and Tucker decompositions, fundamental tensor operations, and tensor transformations", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/HiParTI", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/HiParTI", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2023-05-26" + }, + "description": "By 2050, there could be as many as 10 million photovoltaic (PV) modules that have reached their end of life. The circular economy (CE) proposes to tackle waste issues by maximizing value retention in the economy but transitioning to a CE implies certain stakeholder behaviors. In this context, we propose an agent-based model (ABM) to account for social factors in CE strategies assessment of end-of-life PV modules. Four different types of agents are represented and five possible end-of-life pathways are modeled. A machine-learning metamodel is used to explore the parameter space of the ABM. Results show that excluding social factors underestimates the effect that lower recycling prices have on material circularity by 100% and highlight the limitation of the reuse strategy as, even in an ideal case, used modules only provide a third of demand in the United States. The ABM could be developed to compute the environmental impacts of end-of-life pathways.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "ABSiCE (Agent-Based Simulations of the Circular Economy) [SWR 20-113]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ABSiCE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2021-01-14" + }, + "description": "Implementation of the SISSO regression algorithm in MATLAB. The SISSO regression algorithm iteratively selects model features from candidates, converging even when the number of possible features is much greater than the number of available data points.\n\nIncludes a test script that validates the algorithm by replicating the results using data and procedure from https://analytics-toolkit.nomad-coe.eu/hub/user-redirect/notebooks/tutorials/compressed_sensing.ipynb.\n\nPython code from the SISSO regressor in 'sisso.py', from the link above, was used as the basis for developing the MATLAB implementation. The SISSO regression algorithm is detailed by the original authors in R. Ouyang, S. Curtarolo, E. Ahmetcik et al., Phys. Rev. Mater. 2, 083802 (2018), R. Ouyang, E. Ahmetcik, C. Carbogno, M. Scheffler, and L. M. Ghiringhelli, J. Phys.: Mater. 2, 024002 (2019).", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "SISSO (Sure-independence-screening sparsifying-operator regressor)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SISSORegressor_MATLAB", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-19", + "metadataLastUpdated": "2023-03-13" + }, + "description": "SR2ML is a software package which contains a set of safety and reliability models designed to be interfaced with the INL developed RAVEN code. These models can be employed to perform both static and dynamic system risk analysis and determine risk importance of specific elements of the considered system. Two classes of reliability models have been developed; the first class includes all classical reliability models (Fault-Trees, Event-Trees, Markov models and Reliability Block Diagrams) which have been extended to deal not only with Boolean logic values but also time dependent values. The second class includes several components aging models. Models of these two classes are designed to be included in a RAVEN ensemble model to perform time dependent system reliability analysis (dynamic analysis). Similarly, these models can be interfaced with system analysis codes to determine failure time of systems and evaluate accident progression (static analysis).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Safety Risk Reliability Model Library", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/SR2ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-19", + "metadataLastUpdated": "2023-03-08" + }, + "description": "LOGOS is a software package which contains a set of discrete optimization models that can be employed for capital budgeting optimization problems. More specifically, provided a set of items (characterized by cost and reward values) and constraints, these models select the best combination of items which maximizes overall reward and satisfies the provided constraints. The developed models are based on different versions of the knapsack optimization algorithms. Two main classes of optimization models have been initially developed: deterministic and stochastic. Stochastic optimization models evolve deterministic models by explicitly considering data uncertainties (associated to constraints or item cost and reward). These models can be employed as stand-alone models or interfaced with the INL developed RAVEN code to propagate data uncertainties and analyze the generated data (i.e., sensitivity analysis).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "LOGOS", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/LOGOS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-19", + "metadataLastUpdated": "2023-03-15" + }, + "description": "CMIP model explores various charging infrastructure network designs to serve a free-floating car-sharing fleet and determine the charging downtime experienced by the fleet for each design. Development of the CMIP model had two major steps: (1) describing modeling assumptions and (2) developing an integer program (IP) that jointly optimizes decisions about locations to install DC fast chargers and EV-to-charger assignments. The CMIP model integrates an EV charging model, EV energy consumption model, and heterogeneous, real-world vehicle use data with an integer programming optimization model to identify optimal location of new charging stations and calculate vehicle downtime for charging. The CMIP model can be applied to understand: (a) the reduction of EV fleet downtime if an additional fast-charging station is added to the current infrastructure and (b) to what extent total vehicle downtime would be sensitive to additional charging infrastructure.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Charging-management And Infrastructure-planning (cmip) Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/CMIP", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-01-22", + "metadataLastUpdated": "2021-01-22" + }, + "description": "Tracktable is a toolkit for analysis and visualization of the trajectories of moving objects. Its main focus is on air and sea traffic. It can also work with more abstract trajectories such as eye tracking data. We supply a set of core data structures, input/output routines, math and machine learning algorithms that operate on those data structures, and visualization algorithms to produce movies and still images of the results.\n", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Tracktable ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/tracktable", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tracktable", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1 (Alpha)" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-01-22", + "metadataLastUpdated": "2024-09-23" + }, + "description": "Laika BOSS (Binary Object Scanning System), often written as \"Laikaboss\", is an object scanner and intrusion detection system that strives to be scalable, flexible, and verbose. Its goal is to take arbitrary file input and extract all relevant subfiles and metadata for use in helping analysts determine the function and maliciousness of a file at a glance. This is an extension to the original code developed by Lockheed Martin.", + "laborHours": 11901.6, + "languages": [ + "Dockerfile", + "Shell", + "YARA", + "JavaScript", + "Vue", + "Python" + ], + "name": "Laika BOSS (Binary Object Scanning System)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/laikaboss", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.00+2821.g2403134" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-25", + "metadataLastUpdated": "2021-01-26" + }, + "description": "ModuleOT is an open hardware security platform which provides all features necessary for securing remote energy resources. The platform consists of a physical bump in-the wire device which runs a custom-built application built with Go and Python and leverages AES-NI Instruction set available on modern hardware for cryptographic acceleration. By combining these features, ModuleOT acts as an all-in-one low-cost solution to enable cryptographically secured communications to any critical remote servers or devices. Because the software application has been built using Golang, this source can be easily compiled for different hardware platforms. The module is designed to provide the following core features: (1) encrypted communications across an untrusted network, (2) certificate-based authentication with secure storage, (3) hardware cryptographic acceleration, (4) IP-based whitelisting, (5) local firewall management, and (6) legacy (RS485) device support.\n", + "laborHours": 0.0, + "languages": [], + "name": "ModuleOT", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ModuleOT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Processing temperature is decisive to the properties and performance of the product in friction extrusion. However, the constantly varying thermal boundary conditions result in an unstable processing temperature even fixed die rotational speed and feed rate were implemented, which extensively disturb the stability of the process and the quality of the\nproduct. It is key to maintain the process temperature to ensure the properties of the product is uniform. What's more, a controlled processing temperature enables the properties of the product to be manipulatable between parts and between\ndifferent locations of one part", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Temperature controlled friction extrusion process", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-27", + "metadataLastUpdated": "2024-03-04" + }, + "description": "DES_HVAC is a repository of a Parametric Analysis Tool (PAT) project and for scripts related to modeling of different HVAC systems for buildings in a district served by a district thermal energy system.\n\nThe Measures directory contains the new measures developed to extract data from the simulations. Update these measures and not the measures in the Test Suite measures directory. PAT should be used to update the measures in the Test Suite project.\n\nThe Test directory contains a PAT project for testing the functionality of the measures. The PAT project is named HVAC_Test and can be opened in PAT > 3.x.", + "laborHours": 0.0, + "languages": [], + "name": "URBANopt\u2122 District Energy Systems HVAC Measures (DES_HVAC) [SWR-21-30]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/urbanopt/DES_HVAC", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stewartsl@ornl.gov" + }, + "date": { + "created": "2021-01-29", + "metadataLastUpdated": "2022-02-08" + }, + "description": "The Transformer eXplainability and eXploration library is intended to aid in the explorability and explainability of transformer classification networks, or transformer language models with sequence classification heads. The basic function of this library is to take a trained transformer and test/train dataset and produce an ipywidget dashboard which can be displayed in a jupyter notebook or in jupyter lab.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Transformer eXplainability and eXploration", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/tx2", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "johnsonsr@ornl.gov" + }, + "date": { + "created": "2021-01-31", + "metadataLastUpdated": "2021-02-01" + }, + "description": "Flibcpp is a library for use by application developers that provides native Fortran interfaces to existing high-quality algorithms and containers implemented in C++ and available on all modern computer systems.", + "laborHours": 0.0, + "languages": [ + "C++", + "Fortran", + "SWIG" + ], + "name": "Flibcpp", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/swig-fortran/flibcpp", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-02-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PaKman: A Scalable Algorithm for Generating Genomic Contigs on Distributed Memory Machines. PaKman presents a fully distributed method that tackles assembly of large genomes through the combinationof a novel data-structure (PaK-Graph) and algorithmic strategies to simplify communication and I/O footprint during the\nassembly process.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/pakman", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pakman", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-03", + "metadataLastUpdated": "2021-03-04" + }, + "description": "Python implementation of the Method of Moving Asymptotes optimization algorithm described in[Svanberg, K., The method of moving asymptotes- a new method for structural optimization. International journal for numerical methods in engineering, 1987. 24(2): p.359 (https://onlinelibrary.wiley.com/doi/abs/10.1002/nme.1620240207). Originally implemented in[GetDP](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=717799) [project](https://gitlab.onelab.info/getdp/getdp), although it has been deleted in their repository.", + "laborHours": 0.0, + "languages": [], + "name": "Method of Moving Asymptotes Optimization Algorithm in Python", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pyMMAopt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-03", + "metadataLastUpdated": "2021-02-03" + }, + "description": "We perform a comparison study of two topology optimizations methods applied to the design of a two fluids heat exchanger modeled with a coupled thermal-flow problem. The flow follows an isothermal and\nincompressible Stokes-Brinkman equation and the heat transfer is governed by a convection-diffusion\nequation without internal generation and high Peclet number. To keep the two fluid phases separated, we solve two Stokes-Brinkman equations, where the Brinkman term models the other phase as a solid. These two velocity fields are then fed to the heat transfer equation. Our goal is to maximize the enthalpy at the cold outlet while constraining the pressure drop. We first solve the design modeling the solid and fluid phases with a volume fraction variable. A SIMP-like penalization in the Brinkman term drives the optimization to a discrete design. The cost and constraint function\nderivatives are calculated with the library pyadjoint and the optimization is performed by IPOPT. We present optimized designs in two dimensions and discuss the influence of the parameters.\n", + "laborHours": 0.0, + "languages": [], + "name": "Two dimensional topology optimization of heat exchangers with the volume fraction method", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/2DHEVF", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-03", + "metadataLastUpdated": "2021-02-04" + }, + "description": "B.MPI3 is a C++ library wrapper for standard MPI-3. B.MPI3 is designed following the principles of Boost\nand the STL. B.MPI3 is unrelated to the official, now deprecated, MPI-C++ interface. It provides an iterator-based interface and MPI-3 features (RMA and Shared memory). B.MPI3 is written from scratch in C++14.\n", + "laborHours": 0.0, + "languages": [], + "name": "B.MPI3", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/b-mpi3/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/b-mpi3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-03", + "metadataLastUpdated": "2021-03-11" + }, + "description": "The Chebyshev Interaction Model for Efficient Simulation (ChIMES) is a machine-learned interatomic potential targeting chemistry in condensed phase systems. ChIMES models are able to approach\nquantum-accuracy through a systematically improvable explicitly many-bodied basis comprised of linear combinations of Chebyshev polynomials. Though originally developed as to enable description of organic molecular materials, ChIMES has successfully been applied to systems spanning ambient water to molten carbon, and leveraged as correction for density functional based tight binding simulations. The\nChIMES calculator comprises a flexible toolset for evaluating ChIMES interactions (e.g. in simulations, single point calculations, etc). Users have the option of directly imbedding the ChIMES calculator within their codes, or evaluating interactions through the beginner-friendly serial interface, each of which have\nPython, C++, C, and Fortran API's.", + "laborHours": 0.0, + "languages": [], + "name": "chimes_calculator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rk-lindsey/chimes_calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-02-05", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The NRIC Digital Engineering Ecosystem is a software suite designed to eliminate procedural failures in the engineering lifecycle of complex projects. It focuses on improving the flow of scheduling data, safety information, engineering requirements, and CAD files among stakeholders of complex engineering projects. The project comprises software adapters that move engineering data from disparate software tools in and out of a central database. The ecosystem is designed to efficiently incorporate data sources from many different engineering toolsets, making it software agnostic, and adaptable to many different engineering applications.", + "laborHours": 0.0, + "languages": [ + "JavaScript" + ], + "name": "NRIC Digital Engineering Ecosystem", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/IDEAS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-02-05", + "metadataLastUpdated": "2023-03-13" + }, + "description": "TMAP8 is a MOOSE application for solving 0-1D scalar diffusion-reactive transport. It contains unique custom syntax for 0D or 1D geometric/algebraic entities that make it more usable for 0-1D transport than standard MOOSE syntax.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "TMAP8", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/TMAP8", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-08", + "metadataLastUpdated": "2021-02-08" + }, + "description": "The Fat Crayon Toolkit (FCT) provides python modules for assisting in the design and visualization of\nboreholes and tunnels and their relationship with natural features such as fractures. Distances of closest\napproach among the boreholes can be calculated, along with other key design metrics. Additionally, the shear propensity of natural fractures (either deterministic or stochastic) can be visualized in either 3D (as\nVTK files) or in 2D (stereonets). The example provided demonstrates a test bed developed for the\nEnhanced Geothermal Systems (EGS) Collab project. This material is based upon work supported by the\nGeothermal Office of the Department of Energy and the Sanford Underground Research Facility and was\nprepared by LLNL under Contract DE-AC52-07NA27344.", + "laborHours": 0.0, + "languages": [], + "name": "Fat Crayon Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/joepmorris/FatCrayonToolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2021-02-17" + }, + "description": "SAND2021-1508 O\nThe Pynta code is designed to automatically characterize chemical reactions relevant to heterogeneous catalysis in which gas-phase molecules interact with crystal facets of a solid. It organizes multiple quantum chemistry calculations to carry out this task. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python 3", + "bash script" + ], + "name": "Pynta v. 1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zadorlab/pynta", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2021-1654 O\nThe Python Material Tensor code (PyMTensor) applies crystal symmetries to arbitrary material tensors. It uses symbolic algebra to exactly determine the zero tensor components and the relationships between the nonzero components for all crystallographic point groups. It is capable of computing components of higher-order material tensors needed when treating nonlinear effects. It has a simple and flexible interface for inputting tensor rank information and any known symmetries between tensor indices.Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 562.4, + "languages": [ + "Python", + "Sage" + ], + "name": "PyMTensor 1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pymtensor", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2021-1511 O. The code takes a description of a system comprised of two leads that are sources and sinks of electrons, a set of abstract sites that those electrons can occupy, and their connectivity. It then predicts the current passing between the two leads through the set of abstract sites. There are numerical parameters that define the rate at which electrons tunnel between sites and another parameter that determines the energy of having two electrons on the same site. When the ratio of these energies and biases are set just right, they can be used to predict the existence of Coulomb blockade in which no current flows because the energetic penalty would be too high. That is, the code predicts a current and the absence of a current which is predictive of Coulomb blockade. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 182.4, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "Fermi-Hubbard Transport Solver v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/FermiHubbardTransport", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2021-05-18" + }, + "description": "SAND2021-0624 O Watchr is a Jenkins plugin for tracking the performance of subroutines over many individual builds. It reads build-generated performance reports and displays the data contained in these performance reports as a series of graphs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Java", + "JavaScript", + "Java", + "Java" + ], + "name": "Watchr 3.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/watchr-jenkins/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/watchr-jenkins", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2021-02-17" + }, + "description": "SAND2021-1505 O. TINES is an open source software providing math infrastructure for solving many stiff time ordinary differential equations (ODEs) and/or differential algebraic equations (DAEs) using a batch hierarchical parallelism. The code is written using a parallel programming model (i.e., Kokkos) to future-proof the next generation parallel computing platforms such as GPU accelerators. This code is developed to support Exascale Catalytic Chemistry (ECC) Project. The code provides fundamental math helpers that can aid other research projects. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "TINES - Time Integration, Newton and Eigen Solver v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Tines", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "slatterysr@ornl.gov" + }, + "date": { + "created": "2021-02-17", + "metadataLastUpdated": "2021-02-17" + }, + "description": "Picasso is a C++ template library for the development of exascale-class particle-in-cell methods. It contains data structures for particle and grid management using the ECP Kokkos and Cabana libraries, abstractions for particle and grid discretizations, and tools for interface tracking and reconstruction with particles.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "picassodev/picasso", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/picassodev/picasso", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-02-17", + "metadataLastUpdated": "2021-02-17" + }, + "description": "The Omics Mock Generator (OMG) library is used to provide the synthetic multiomics data needed to test the computational tools for bioengineering metabolic models. Since experimental multiomics data is expensive and non-trivial to produce, OMG provides a quick and easy way to produce large amounts of multiomics data that are based on plausible metabolic assumptions.", + "laborHours": 0.0, + "languages": [], + "name": "Omics Mock Generator Library (OMG) v0.1.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AgileBioFoundry/multiomicspaper", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-02-17", + "metadataLastUpdated": "2021-02-17" + }, + "description": "\tTransportation is the fastest-growing source of greenhouse gas (GHG) emissions and energy consumption globally. The convergence of shared mobility, vehicle automation, and electrification has the potential to drastically reduce transportation impacts, but requires careful integration with rapidly evolving electricity systems. We have developed the GEM Model (Grid-Integrated Electric Mobility) to examine these interactions with a U.S.-wide simulation framework encompassing private electric vehicles (EVs); shared automated EVs (SAEVs); charging infrastructure; controlled EV charging; and a grid economic dispatch model to simulate mobility futures exclusively using EVs. We find that an SAEV fleet 9% the size of today's active vehicles can satisfy trip demand with only 2.6 million chargers (0.2 per EV). Controlled EV charging can also reduce electricity demand variability, significantly reducing GHG emissions and decreasing solar curtailment by about one-third. While private EVs with uncontrolled charging would reduce GHG emissions by 53% compared to gasoline vehicles, SAEVs could achieve a 70% reduction.", + "laborHours": 0.0, + "languages": [], + "name": "Grid-Integrated Electric Mobility Model (GEM) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-UCB-STI/gem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-02-17", + "metadataLastUpdated": "2021-02-18" + }, + "description": "gpCAM is tailored to be used by experimentalists who want to steer experiments autonomously. It is based on a Gaussian process (GP). Its strength compared to other software lies in its flexibility, which together with the right training, makes it more powerful than any GP-based software. However, that means, that the software in as-is mode cannot reach its full potential.", + "laborHours": 0.0, + "languages": [], + "name": "gpCAM v6", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/MarcusMichaelNoack/gpcam", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-02-19", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The software is a list of Abaqus User MATerial subroutines (VUMAT) for modeling granular flow physics. It includes (1) density dependent Mohr-Coulomb model, (2) density dependent Drager-Prager\\Cap model, (3)Gudehus-Bauer hypoplastic model, and (4) critical state-based NorSand model.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Granular Flow Constitutive Model Add-ons For Abaqus", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/GranularFlowModels", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-24", + "metadataLastUpdated": "2021-02-24" + }, + "description": "This source code includes tutorials targeting a general audience that will help users to use high performance computing environments and systems at Livermore Computing and beyond. Examples of HPC tools covered include mpi and posix. Tutorials may include source code demonstrating usage.", + "laborHours": 0.0, + "languages": [], + "name": "High Performance Computing tutorials", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/HPC-Tutorials", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-24", + "metadataLastUpdated": "2021-02-24" + }, + "description": "Saloon is a Vim plugin that simplifies Python code linter / fixer configuration and usage.\nSaloon's menu lets developers toggle which static analysis tools to use and delegates those changes to\nALE's (Asynchronous Lint Engine) API. Since prospector (python linter aggregate) already handles multiple tools, and is integrated with ALE, most of the actual linting will initially be handled via prospector calls.", + "laborHours": 0.0, + "languages": [], + "name": "Saloon", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Saloon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-02-24", + "metadataLastUpdated": "2021-02-24" + }, + "description": "H2FillS: Hydrogen Filling Simulation\nThe Hydrogen Filling Simulation (H2FillS) software is a thermodynamic model designed to track and report on the transient change in hydrogen temperature, pressure, and mass flow when filling a fuel cell electric vehicle (FCEV).\n\nH2FillS simulates gas flow from the hydrogen station to the FCEV storage system. Using empirical fueling data sets, the model has been validated over a range of fueling conditions to match common light-duty FCEV fill profiles. Overall, it provides significant benefits to the light-duty fueling market and fill knowledge gaps of the interaction between a hydrogen station and an FCEV.\n\nCapabilities\nUse the comprehensive H2FillS model to:\n\nSafely design and operate a hydrogen fueling station\nSupport code refinement with readily available data\nDevelop system and operational improvements to reduce capital or operating costs at hydrogen stations or on-board FCEVs.\nHow It Works\nH2FillS uses a \"drag-and-drop\" graphical user interface to simulate station and vehicle systems with preset parameters for common hydrogen station components as default values. When needed, users can define their own parameters to create their own station or vehicle components.\n\nDownload H2FillS in Two Steps\nRead the terms of the end user software license agreement.\nRegister to download the software.\nThere are two versions of the model:\n\nA full-station model starts the simulation at high-pressure ground storage, runs through a dispenser, and ends at a vehicle storage system.\nA partial-station model starts at the dispenser breakaway and consists solely of the dispenser components and the vehicle storage system.\nH2FillS will automatically output fill performance data from the vehicle by tracking pressure and temperature throughout the fill. Users can input their own fill profiles into the model to run a variety of simulations.", + "homepageURL": "https://www.nrel.gov/hydrogen/h2fills.html", + "laborHours": 0.0, + "languages": [], + "name": "H2Fills\u2122", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrel.gov/hydrogen/h2fills-agreement-registration.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrel.gov/hydrogen/h2fills.html", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-02-24", + "metadataLastUpdated": "2021-03-05" + }, + "description": "With this COUNT software, we can run a simple query on a campus's Wireless Local Area Network controller (WLAN controller) to obtain the number of connected devices per access point across the whole campus and this can be used as a proxy for the actual number of occupants in the campus. 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The examples provided are a representation of the DFW airport for curbside dropoff and and pickup.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "Athena - Digital Twin and Infrastructure Model [SWR 20-106]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/athena-forecast", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-02-25", + "metadataLastUpdated": "2021-02-25" + }, + "description": "Science Capsule captures the processing and data life cycle across machines, organizations, people, and science domains. 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PyFloT implementation has only be validated using the GNU compiler toolchain.", + "laborHours": 0.0, + "languages": [], + "name": "PyFloT v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hbrunie/PyFloT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v0.1" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-01", + "metadataLastUpdated": "2021-03-01" + }, + "description": "The Neurodata Extensions Catalog (NDX Catalog) is a novel web archive and associated software tools that enable users to easily create, search for, test, review, and install extensions to the Neurodata Without Borders (NWB) data standard for neurophysiology. 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The openPMD-CCD software module adds interfaces to organize camera (CCD) images in hierarchical data files.\n\nThis software provides modern I/O storage formats from high-performance computing and provides bindings for integration into experimental control systems, e.g. via Python 3 and LabView 2020.", + "laborHours": 0.0, + "languages": [], + "name": "A Python Module for Storing CCD Images with openPMD (openPMD-CCD) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openPMD/openPMD-CCD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v0.1.0" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-01", + "metadataLastUpdated": "2021-03-01" + }, + "description": "The purpose of this microbenchmark is to provide a means to explore different programming methodologies using a simple, but not trivial, mathematical kernel. The kernel is based on the matrix vector product in the MFDn nuclear configuration interaction code's LOBPCG eigensolver. This particular mathematical operation is a key element in the solution of systems of equations and block eigensolvers.", + "laborHours": 0.0, + "languages": [], + "name": "CSBCOO SPMM: Compressed Sparse Block Coordinate format sparse matrix dense vector multiply benchmark (CSBCOO SPMM) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/nersc-proxies/csbcoo-spmm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-01", + "metadataLastUpdated": "2021-03-01" + }, + "description": "CALAND is a system of algorithms (.r files) and data developed to quantify the impacts of various suites of California State-supported land use and land management strategies on landscape carbon and greenhouse gas emissions (CO2, CH4, and optional black carbon) relative to a baseline scenario for the Draft California 2030 Natural and Working Lands Climate Change Implementation Plan (2019).", + "laborHours": 0.0, + "languages": [], + "name": "California Natural and Working Lands Carbon and Greenhouse Gas Model (CALAND) v3.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aldivi/caland", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v3.0.0" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-01", + "metadataLastUpdated": "2021-03-01" + }, + "description": "Reeber is a library for shared- and distributed-memory parallel computation of merge trees", + "laborHours": 0.0, + "languages": [], + "name": "Reeber v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mrzv/reeber", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v2.0" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-02", + "metadataLastUpdated": "2021-03-02" + }, + "description": "MLDAS is a Python-written package for exploratory data analysis and deep learning training on Distributed Acoustic Sensing data. 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Various SLURM scripts as well as a tutorial have also been made available to allow geophysicists to quickly and easily implement the available tools in their analysis workflow on supercomputer facilities.", + "laborHours": 0.0, + "languages": [], + "name": "Machine Learning for Distributed Acoustic Sensing data (MLDAS) v1.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ml4science/mldas", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-02", + "metadataLastUpdated": "2021-03-02" + }, + "description": "The balance of demand and supply in the electric power grid is a crucial element to grid reliability. 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This project introduces an open-source dataset for 143 days of four-second regulation data, and the SynAS Python module to synthetically generate frequency regulation signals of arbitrary length.", + "laborHours": 0.0, + "languages": [], + "name": "Synthetic Ancillary Service Generator (SynAS) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/SynAS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-02", + "metadataLastUpdated": "2021-03-02" + }, + "description": "pandas-sacct is a small python utility which provides a pandas dataframe based interface to Slurm's accounting database.", + "laborHours": 0.0, + "languages": [], + "name": "pandas-sacct v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/pandas-sacct", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-03-02", + "metadataLastUpdated": "2024-09-10" + }, + "description": "This software is used with a microcontroller to control an aerosol jet printing system. 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The dynamics of the quantum system is modeled by Schroedinger's equation, which takes to form of a linear system of ordinary differential equations (ODE). Juqbox.jl solves this ODE by numerical time stepping and applies a gradient-based optimization technique to determine control pulses for driving an initial state to a final state, according to the desired logical gate transformation. To evaluate the gradient, Juqbox.jl applies the ``first discretize, then optimize'' approach based on a discrete adjoint time stepping\ntechnique. The actual optimization is performed by the open source Ipopt libaray. Juqbox.jl is written in the Julia programming language which, among many other features, provides a convenient interface to the Ipopt library.", + "laborHours": 0.0, + "languages": [], + "name": "Juqbox.jl", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Juqbox.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2021-03-11" + }, + "description": "MT-xGEMM is a simple driver for benchmarking xGEMM Level 3 BLAS functions. 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It implements the method as well as related data analysis functions.", + "laborHours": 0.0, + "languages": [], + "name": "Dynamical Components Analysis (DCA) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BouchardLab/DynamicalComponentsAnalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2021-03-12" + }, + "description": "Dynamical Components Analysis is a Python implementation of the method described in \"Unsupervised discovery of temporal structure in noisy data with dynamical components analysis\". It implements the method as well as related data analysis functions.", + "laborHours": 0.0, + "languages": [], + "name": "Dynamical Components Analysis (DCA) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BouchardLab/DynamicalComponentsAnalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2021-03-11" + }, + "description": "This is a software utility used to maximize next-generation sequencing data output without compromising quality values. The DNA Sequencing Optimizer is used to determine the optimal amount of library to load. To do this a supervised machine learning model predicts cluster density, a measure of how much DNA is bound to the sequence, from the concentration of DNA loaded. The output is a plot that is used by experimentalists to determine the best DNA library concentration to load onto the sequencer.", + "laborHours": 0.0, + "languages": [], + "name": "DNA Sequencing Optimizer v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/library_loading_concentration_prediction", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2021-03-12" + }, + "description": "FlexDRL is a framework that can be used as a benchmarking tool to evaluate different Deep Reinforcement Learning algorithms in a building energy management setting. OpenAI Gym was used as wrapper to the co-simulation environment (EnergyPlus for envelope and HVAC and Modelica for battery and PV) to interface with DRL algorithms, which are developed in PyTorch. In order to facilitate the usage of FlexDRL, all the required dependencies have been packaged into a Docker container.", + "laborHours": 0.0, + "languages": [], + "name": "FlexDRL v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/FlexDRL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2023-03-15" + }, + "description": "TAPsolver is a python package, which automates TAP simulation and analysis routines. TAPsolver is built around the python packages FEniCS and Dolfin-Adjoint, which help take advantage of model adjoints to provide automatic derivatives. TAPsolver is flexible, with reaction mechanisms and rate constants that can be set through input files that allow users to take advantage of the different functionalities, which include sensitivity analyses, parameter optimization and uncertainty quantification.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Tapsolver: A Python Package For The Simulation And Analysis Of Tap Reactor Experiments", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/medford-group/TAPsolver", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "prokopenkoav@ornl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2025-04-17" + }, + "description": "ArborX library tackles a problem of efficiently finding geometric objects that are close in space. Variations of this problem, such as finding the nearest neighbors of a point, or finding all objects within a certain distance, are inherent components of applications in many fields. The data may be large so that solving the problem efficiently may require significant computational resources, such as multiple processors or accelerators such as general purpose GPUs.\n\nArborX' main advantage in its ability to solve large problems efficiently utilizing a combination of distributed and on-node parallelism. ArborX can be run efficiently on a wide variety of hardware, including GPUs from different vendors, which distinguishes it from other available libraries which typically choose only few of these. The other advantage is that it supports both types of user problems: spatial problems (useful for intersections and finding objects within certain distance), and nearest neighbor problems. ArborX also supports flexible interface in its interaction with a user. Particularly, it allows a user to call user's own function on a positive match, a functionality not rarely available in other libraries.\n\nArborX implements construction and traversal algorithms using efficient tree structures, such as bounding volume hierarchy (BVH). At its core, it uses linear BVH for its low construction cost and sufficient quality. ArborX is written using C++, and is parallelized using the message passing interface (MPI) for the distributed communication, and the Kokkos library for on-node parallelism. This approach allows ArborX to be run on a wide variety of hardware, from common laptops and desktops to supercomputers while using the same codebase. ArborX also implements several advanced algorithms using geometric search, such as density-based clustering algorithm DBSCAN.", + "laborHours": 16492.0, + "languages": [ + "C++" + ], + "name": "ArborX", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/arborx/ArborX", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-03-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a trained machine learning model written in Pytorch for automated control of the FlexyAir\n(https://ocl.sk/hardware/flexyair/) dynamical system control educational device. This software is to be released to support our demonstration of our deepMPC methods on embedded hardware to control a real (albeit tutorial) physical system with control actuators.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/FlexyAirDeepMPC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/FlexyAirDeepMPC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "lukensjm@ornl.gov" + }, + "date": { + "created": "2021-03-12", + "metadataLastUpdated": "2021-03-12" + }, + "description": "This code provides examples of a new, self-contained approach for Bayesian quantum state estimation which offers improved computational efficiency compared to previous approaches. Leveraging advances in machine learning and statistics, our formulation relies on highly efficient preconditioned Crank-Nicolson sampling and a pseudo-likelihood. Details of the theory behind it can be found in our paper https://doi.org/10.1088/1367-2630/ab8efa", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "BayesQuanTom", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmlukens/BayesQuanTom", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-15", + "metadataLastUpdated": "2021-03-15" + }, + "description": "The software is a general optimizer, simliar to scipy.minimize, but using advanced methods and it is HPC ready.", + "laborHours": 0.0, + "languages": [], + "name": "HGDL v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/hgdl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "version": "v1" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-03-15", + "metadataLastUpdated": "2021-03-15" + }, + "description": "Flexible API for combinating and generating parsers given a JSON schema.", + "laborHours": 0.0, + "languages": [], + "name": "Generalized Nuclear Data - Mim", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GeneralizedNuclearData/Mim/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GeneralizedNuclearData/Mim", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-03-15", + "metadataLastUpdated": "2021-03-15" + }, + "description": "Schemas defining the GNDS format. Hosting the schemas in a public place allows anyone to refer to them and a common place to store them.", + "laborHours": 0.0, + "languages": [], + "name": "Generalized Nuclear Data - schemas ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GeneralizedNuclearData/schemas/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GeneralizedNuclearData/schemas", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-03-15", + "metadataLastUpdated": "2021-03-15" + }, + "description": "This repository describes the goals and governance of WPEC Subgroup 43 (SG43). This subgroup is tasked with creating infrastructure for the Generalized Nuclear Data (GND) format.", + "laborHours": 0.0, + "languages": [], + "name": "Generalized Nuclear Data - WPEC Subgroup 43", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GeneralizedNuclearData/SG43/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GeneralizedNuclearData/SG43", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-16", + "metadataLastUpdated": "2021-03-16" + }, + "description": "We present a parallel algorithm and scalable implementation for genome analysis, specifically the problem of finding overlaps and alignments for data from \"third generation\" long read sequencers. While long sequences of DNA offer enormous advantages for biological analysis and insight, current long read sequencing instruments have high error rates and therefore require different approaches to analysis than their short read counterparts. Our work focuses on an efficient distributed-memory parallelization of an accurate single-node algorithm for overlapping and aligning long reads. We achieve scalability of this irregular algorithm by addressing the competing issues of increasing parallelism, minimizing communication, constraining the memory footprint, and ensuring good load balance. The resulting application, DiBELLA, is the first distributed memory overlapper and aligner specifically designed for long reads and parallel scalability.", + "homepageURL": "https://sourceforge.net/projects/dibella", + "laborHours": 0.0, + "languages": [], + "name": "Distributed Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper (DiBELLA) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/dibella", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-16", + "metadataLastUpdated": "2021-03-16" + }, + "description": "This is a OpenStudio measure that calculates and reports the system-level key performance indicators (KPIs) for evaluating building energy performance at the system level. The systems are defined by the service it provides in commercial buildings, which include (1) lighting, (2) Miscellaneous Electric Loads (MELs), (3) Heating, Ventilation and Air Conditioning (HVAC), and (4) Service Water Heating (SWH).", + "homepageURL": "https://bcl.nrel.gov/node/85162", + "laborHours": 0.0, + "languages": [], + "name": "OpenStudio System-level KPI Reporting Measure v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bcl.nrel.gov/node/85162", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-16", + "metadataLastUpdated": "2021-03-22" + }, + "description": "The ability to analyze network flow characteristics is critical to understand network patterns that can help us understand how our networks are behaving. Merope is a collection of many unsupervised learning approaches and visualizers to allow networks to be more visual and analytical.", + "laborHours": 0.0, + "languages": [], + "name": "Merope: Unsupervised Learning for Network Operations (Merope) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/hylia_networkprediction", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pmaffetto@bnl.gov" + }, + "date": { + "created": "2021-03-16", + "metadataLastUpdated": "2021-03-16" + }, + "description": "The application of the XCA package as first demonstrated in aXiv:2008.00283. \n\nABSTRACT: The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain manual, time consuming, error prone, and impossible to scale. With the advent of autonomous robotic scientists or self-driving labs, contemporary techniques prohibit the integration of XRD. Here, we describe a computer program for the autonomous characterization of XRD data, driven by artificial intelligence (AI), for the discovery of new materials. Starting from structural databases, we train an ensemble model using a physically accurate synthetic dataset, which output probabilistic classifications --- rather than absolutes --- to overcome the overconfidence in traditional neural networks. This AI agent behaves as a companion to the researcher, improving accuracy and offering unprecedented time savings, and is demonstrated on a diverse set of organic and inorganic materials challenges. This innovation is directly applicable to inverse design approaches, robotic discovery systems, and can be immediately considered for other forms of characterization such as spectroscopy and the pair distribution function.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "bnl/pub-Maffettone_2020_08", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bnl/pub-Maffettone_2020_08", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-03-18", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2021-3242 O\nPyNetUQ is a Python library for network uncertainty propagation. Custom interface classes for components are modeled individually with potentially distinct simulation tools. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 972.8, + "languages": [ + "Python", + "SWIG", + "Assembly" + ], + "name": "PyNetUQ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PyNetUQ", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-03-19", + "metadataLastUpdated": "2021-03-19" + }, + "description": "Open SHMEM is an increasingly popular standard of the SHMEM programing model. OSHMPI provides a light weight Open SHMEM implementation on top of the portable MPI Interface", + "laborHours": 0.0, + "languages": [], + "name": "OSHMPI: Open SHMEM Implementation over MPI", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/oshmpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-03-21", + "metadataLastUpdated": "2024-08-07" + }, + "description": "Principal component analysis (PCA) is arguably the most popular tool in multivariate exploratory data analysis. We consider the question of how to handle heterogeneous variables that include continuous, binary, and ordinal. In the probabilistic interpretation of low-rank PCA, the data has a normal multivariate distribution and, therefore, normal marginal distributions for each column. If some marginals are continuous but not normal, the semiparametric copula-based principal component analysis (COCA) method is an alternative to PCA that combines a Gaussian copula with nonparametric marginals. If some marginals are discrete or semi-continuous, we present a new extended PCA (XPCA) method that also uses a Gaussian copula and nonparametric marginals and accounts for discrete variables in the likelihood calculation by integrating over appropriate intervals. Like PCA, the factors produced by XPCA can be used to find latent structure in data, build predictive models, and perform dimensionality reduction. We implement the new model, XPCA, and its ancestors PCA and COCA in both R and Python. This software provides implementations of XPCA, COCA, and probabilistic PCA in both R and Python. XPCA is written in arXiv report https://arxiv.org/abs/1808.07510. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.\nSAND2019-10591 M", + "laborHours": 592.8, + "languages": [ + "R" + ], + "name": "XPCA - R Implementation", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/xpcaR", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-03-21", + "metadataLastUpdated": "2024-09-10" + }, + "description": "GNN Parametrized Differential Operators is an example code and layer implementation for using the parameterized differential operator used in conference submissions. 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TaskWorks is compatible with MPI and is designed to work efficiently with HPC applications that perform.", + "laborHours": 0.0, + "languages": [], + "name": "TaskWorks v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/taskworks", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-01", + "metadataLastUpdated": "2021-04-01" + }, + "description": "In recent years advances in the performance of machine learning methods have considerably improved the ability to accurately extract information from images. 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This includes one-way communication for most applications and two-way loose coupling for customizable applications Providing the sequence and timing of events that lead to the specified outcomes when calculating results Traditional aspects of components with basic events, fault trees, and event trees are all captured in a dynamic framework of state diagrams, which are displayed.", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Event-modeled Risk Assessment Using Linked Diagrams", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/EMRALD", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Combining planning models with operational details allows the industry to proactively investigate future resource and load scenarios, rather than react to their implementation in real time. In this project, the following tasks are proposed. 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Once it is so configured, a reliable Hydra network of ASICs remains that can be reconfigured later to respond to damage or malfunction of one or more of the constituent ASICs.", + "homepageURL": "https://sites.google.com/lbl.gov/hydra2020-132/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Hydra Network Automatic Configuration (Hydra Autoconfig) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/hydra2020-132/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-08", + "metadataLastUpdated": "2021-04-08" + }, + "description": "The Building Performance Database (BPD) is the largest publicly-available source of measured energy performance data for buildings in the United States. 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Version 2.1 included a major update for multiple years of data and refactoring of code for faster queries.", + "homepageURL": "https://buildings.lbl.gov/cbs/bpd", + "laborHours": 0.0, + "languages": [], + "name": "Building Performance Database API (BPD API) v2.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://buildings.lbl.gov/cbs/bpd", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-04-09", + "metadataLastUpdated": "2021-06-15" + }, + "description": "Quantum programs are represented as circuits, or sequences of gates. 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As communications interfaces or other actions are taken that affect the flow of data, SPEMMCRA can show whether the microgrid operation is adversely affected by what is intended to mitigate a cybersecurity event.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Scalable, Physical Effects Measureable Microgridfor Cyber Resilience Analysis", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/SPEMMCRA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-13", + "metadataLastUpdated": "2021-04-13" + }, + "description": "We design a modular FPGA (field-programmable gate array) based system called QubiC to control and measure a superconducting quantum processing unit. 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AMReX supports algorithms that solve systems of partial differential equations (PDEs) in simple or complex geometries, and those that use particles and/or particle-mesh operations to represent component physical processes.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "AMReX", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Codes/amrex", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "marc.day@nrel.gov" + }, + "date": { + "created": "2021-04-14", + "metadataLastUpdated": "2021-04-14" + }, + "description": "An adaptive mesh hydrodynamics simulation code for low Mach number reacting flows", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "PeleLM", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Combustion/PeleLM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.0.0" + }, + { + "contact": { + "email": "asalmgren@lbl.gov" + }, + "date": { + "created": "2021-04-14", + "metadataLastUpdated": "2021-04-14" + }, + "description": "Nyx is a highly parallel, adaptive mesh, finite-volume N-body compressible hydrodynamics solver for cosmological simulations. Nyx code solves equations of compressible hydrodynamics on an adaptive grid hierarchy coupled with an N-body treatment of dark matter. The gas dynamics in Nyx uses a finite volume methodology on a set of 3-D Eulerian grids; dark matter is represented as discrete particles moving under the influence of gravity. Particles are evolved via a particle-mesh method, using Cloud-in-Cell deposition/interpolation scheme. Both baryonic and dark matter contribute to the gravitational field. In addition, Nyx includes physics needed to accurately model the intergalactic medium: in optically thin limit and assuming ionization equilibrium, the code calculates heating and cooling processes of the primordial-composition gas in an ionizing ultraviolet background radiation field. Additional physics capabilities are under development.", + "laborHours": 0.0, + "languages": [ + "C++", + "C++" + ], + "name": "Nyx", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Astro/Nyx", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "sluedtke@lanl.gov" + }, + "date": { + "created": "2021-04-15", + "metadataLastUpdated": "2021-06-28" + }, + "description": "Vector Particle-in-Cell (VPIC) is a general purpose particle-in-cell simulation code for modeling kinetic plasmas in one, two, or three spatial dimensions. 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These include: the ability to treat electromagnetic materials (scalar and tensor dielectric, conductivity, and diamagnetic material properties); multiple emission models, including user-configurable models; arbitrary, user-configurable boundary conditions for particles and fields; user- definable simulation units; a suite of \"standard\" diagnostics, as well as user-configurable diagnostics; a Monte-Carlo treatment of collisional processes capable of treating binary and unary collisions and secondary particle generation; and, flexible checkpoint-restart semantics enabling VPIC checkpoint files to be read as input for subsequent simulations. VPIC has a native I/O format that interfaces with the high-performance visualization software Ensight and Paraview. While the common use cases for VPIC employ low-order particles on rectilinear meshes, a framework exists to treat higher-order particles and curvilinear meshes, as well as more advanced field solvers.", + "laborHours": 0.0, + "languages": [ + "C++", + "C" + ], + "name": "VPIC v.1.2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vpic", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "1.2" + }, + { + "contact": { + "email": "ajnonaka@lbl.gov" + }, + "date": { + "created": "2021-04-15", + "metadataLastUpdated": "2021-04-15" + }, + "description": "MAESTROeX is a massively parallel, finite-volume C++/F90 solver for low Mach number astrophysical flows. The code utilizes a low Mach number equation set allowing for more efficient, long-time integration of highly subsonic flows compared to compressible approaches. The recommended range of applicability is for flows where the Mach number does not exceed~0.1.", + "laborHours": 0.0, + "languages": [ + "C++", + "Fortran" + ], + "name": "MAESTROeX", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Astro/MAESTROeX", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "20.11" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-05-27" + }, + "description": "Processing and analyzing brain imaging is crucial in both scientific development and clinical field. In this software package, we build a pipeline that integrates automatic registration, segmentation, and quantitative analysis for subjects' CT scans. Leveraging diffeomorphic transformations, we enable optimized forward and inverse mappings between an image and the reference. Furthermore, we extract localized features from deformation field based on an online template process, which advances statistical learning downstream. The created templates, atlas as well as our methods provide the brain imaging community tools for AI implementations.", + "laborHours": 0.0, + "languages": [], + "name": "Automated CT registration, segmentation, and quantification (AutoCT) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/LBL_TBI/autoct", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-16" + }, + "description": "We introduce HUNTRESS (Histogrammed UNion Tree REconStruction heuriStic), a computational method for tumor phylogeny reconstruction from noisy genotype matrices derived from single-cell sequencing data, whose running time is linear with the number of cells and quadratic with the number of mutations. Provided that the input genotype matrix includes no false positives, each cellular subpopulation is at least a user defined fraction of the total number of cells, and the number of cells are much bigger than the number of mutations considered, HUNTRESS computes the ground truth tumor phylogeny with high probability. On simulated data HUNTRESS is faster than available alternatives with comparable or better accuracy. Additionally, the phylogenies reconstructed by HUNTRESS on two single-cell sequencing data sets agree with the best known evolutionary scenarios for the associated tumors.", + "laborHours": 0.0, + "languages": [], + "name": "HUNTRESS: a fast heuristic for reconstructing phylogenetic trees of tumor evolution (HUNTRESS) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PASSIONLab/HUNTRESS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-18" + }, + "description": "The National Renewable Energy Laboratory Wind Analysis Library (NRWAL) contains --A library of wind cost equations, --Dynamic Python tools for intuitive equation handling, --Ready-to-use configs for basic users, and --Easy equation manipulation without editing source code.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "NREL Wind Analysis Library (NRWAL)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NRWAL", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "Ipmipower implements power control through IPMI over LAN v1.5. 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The user can choose to implement or use a matrix-vector multiplication routine in any form convenient. Most of the arithmetic computations in the software are done through calls to BLAS and LAPACK. The software is written in Fortran 90. Because Fortran 90 offers many utility functions such functions such as dynamic memory management, timing functions, random number generator and so on, the program is easily portable to different machines without modifying the source code. It can also be easily accessed from other language such as C or C-+. Since the software is highly modularized, it is relatively easy to adopt it for different type of situations. For example if the eigenvalue problem may have some symmetry and only a portion of the physical domain is discretized, then the dot-product routine needs to be modified. In this software, this modification is limited to one subroutine. It also can be instructed to write checkpoint files so that it can be restarted at a later time.", + "homepageURL": "https://sdm.lbl.gov/~kewu/trlan.html", + "laborHours": 0.0, + "languages": [ + "Fortran 90" + ], + "name": "Thick-Restart Laczos Method for Symmetric Eigenvalue Problems", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sdm.lbl.gov/~kewu/trlan-license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sdm.lbl.gov/~kewu/trlan.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "The Berkeley Disk Resource Manager (B-DRM) is a middleware component whose function is to provide dynamic space allocation and file management of a shared disk system on the Grid. It provides space allocation and dynamic information on storage availability for the planning and execution of Grid jobs. The B-DRM manages two types of resources: space and files. Vi1en managing space, the B-DRM allocates space to the requesting client based on a default space quota, Then managing files, the B-DRM allocates space for files, invokes file transfer services to move files into the space, pins files for a certain lifetime, releases files upon the client's request, and uses file replacement policies to optimize the use of the shared space. The B-DRM is designed to provide effective sharing of files, by monitoring the activity of shared files, and making dynamic decisions on which files to replace when space is needed. In addition, the B-DRM performs automatic garbage collection of unused files when space is needed by removing selected files that were released by the client or whose lifetime has expired. The BDRM supports requests to get multiple files in a single call, manages a queue of the requested files, brings in as many files as the space quota permits, and continues to reuse the space when files are released to stream files to the client until the entire request is satisfied. Similarly, the B-DRM supports requests to put multiple files into its space, streaming files into the allocated space and reusing the space if necessary.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "gcc 2.9x" + ], + "name": "Berkeley Disk Resource Manager", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This software is a library for C and C++ programmers to use for fast and efficient parsing and processing of symbolic expressions, or s-expressions. An s-expression is a text-representation of a tree data structure, and is the basis for the syntax of the LISP and Scheme programming languages. Multiple similar libraries exist, but this one was designed from the ground up for speed, efficiency, and simplicity.", + "laborHours": 0.0, + "languages": [ + "Any ANSI-C compiler" + ], + "name": "Small, Fast S-Expression Library, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mjsottile/sfsexp/blob/master/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mjsottile/sfsexp", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "Ipmiconsole is a tool and library that allows a user to establish a console session with a remote machine using the IPMI Serial over LAN (SOL) protocol", + "homepageURL": "https://www.gnu.org/software/freeipmi/index.html", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "ipmiconsole", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "WebLogo is a web based application designed to make the generation of sequence logos as easy and painless as possible. Sequence logos are a graphical representation of an amino acid or nucleic acid multiple sequence alignment developed by Tom Schneider and Mike Stephens. Each logo consists of stacks of symbols, one stack for each position in the sequence. The overall height of the stack indicates the sequence conservation at that position, while the height of symbols within the stack indicates the relative frequency of each amino or nucleic acid at that position. In general, a sequence logo provides a richer and more precise description of, for example, a binding site, than would a consensus sequence.", + "homepageURL": "http://weblogo.berkeley.edu", + "laborHours": 0.0, + "languages": [], + "name": "WebLogo", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://weblogo.berkeley.edu", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Toba is an extensible personal information retrieval system. It supports various plugins which the user uses to create and store bits of information. It comes configured to store meeting notes, task items, issue, and business development opportunities. Plugins could be written to support almost any kind of digital information. So with the right plugins, Toba could become a full fledged contact manager, project management application, programmer's toolkit, or almost any other type of data storage/search/retrieval application imaginable. Toba comes with a built in command line interface and via a plugin it has a fully scripting language (jython). The information stored can be searched by keyword or through SQL queries.", + "laborHours": 0.0, + "languages": [], + "name": "TOBA", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/toba", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This package implements system-level checkpointing of scientific applications running on Linux clusters in a manner suitable for implementing preemption, migration and fault recovery by a batch scheduler The design includes documented interfaces for a cooperating application or library to implement extensions to the checkpoint system, such as consistent checkpointing of distributed MPI applications Using this package with an appropriate MPI implementation, the vast majority of scientific applications which use MPI for communication are checkpointable without any modifications to the application source code. Extending VMAdump code used in the bproc system, the BLCR kernel modules provide three additional features necessary for useful system-level checkpointing of scientific applications(installation of bproc is not required to use BLCR) First, this package provides the bookkeeping and coordination required for checkpointing and restoring multi-threaded and multi-process applications running on a single node Secondly, this package provides a system call interface allowing checkpoints to be requested by any authorized process, such as a batch scheduler. Thirdly, this package provides a system call interface allowing applications and/or application libraries to extend the checkpoint capabilities in user space, for instance to provide coordination of checkpoints of distributed MPI applications. The \"Iibcr\" library in this package implements a wrapper around the system call interface exported by the kernel modules, and maintains bookkeeping to allow registration of callbacks by runtime libraries This library also provides the necessary thread-safety and signal-safety mechanisms Thus, this library provides the means for applications and run-time libraries, such as MPI, to register callback functions to be run when a checkpoint is taken or when restarting from one. This library may also be used as a LD_PRELOAD to enable checkpointing of applications with development releases of BLCR (which cannot preempt unmodified applications otherwise). This package also includes simple command line utilities to request a checkpoint or restart of a process. These provide the means for a user, system administrator, or batch scheduler to use BLCR.", + "homepageURL": "https://crd.lbl.gov/departments/computer-science/class/research/past-projects/BLCR", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Lab Checkpoint/Restart for Linux", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://crd.lbl.gov/departments/computer-science/class/research/past-projects/BLCR", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://crd.lbl.gov/departments/computer-science/class/research/past-projects/BLCR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This library implements a memory allocator/manager which ask its host program or library for memory refions to manage rather than requesting them from the operating system. This allocator supports multiple distinct heaps within a single executable, each of which may grow either upward or downward in memory. The GNU mmalloc library has been modified in such a way that its allocation algorithms have been preserved, but the manner in which it obtains regions to manage has been changed to request memory from the host program or library. Additional modifications allow the allocator to manage each heap as either upward or downward-growing. By allowing the hosting program or library to determine what memory is managed, this package allows a greater degree of control than other memory allocation/management libraries. Additional distinguishing features include the ability to manage multiple distinct heaps with in a single executable, each of which may grow either upward or downward in memory. The most common use of this library is in conjunction with the Berkeley Unified Parallel C (UPC) Runtime Library. This package is a modified version of the LGPL-licensed \"mmalloc\" allocator from release 5.2 of the \"gdb\" debugger's source code.", + "laborHours": 0.0, + "languages": [ + "Any ANSI C compiler." + ], + "name": "The Unobtrusive Memory Allocator", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upc-runtime/src/master/umalloc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This package permits a scientist to perform computations using an arbitrarily high level of numeric precision (the equivalent of hundreds or even thousands of digits), by making only minor changes to conventional C++ or Fortran-90 soruce code. This software takes advantage of certain properties of IEEE floating-point arithmetic, together with advanced numeric algorithms, custom data types and operator overloading. Also included in this package is the \"Experimental Mathematician's Toolkit\", which incorporates many of these facilities into an easy-to-use interactive program.", + "homepageURL": "https://www.davidhbailey.com/dhbsoftware", + "laborHours": 0.0, + "languages": [ + "C++ and F90 compilers" + ], + "name": "An Arbitrary Precision Computation Package", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.davidhbailey.com/dhbsoftware", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.davidhbailey.com/dhbsoftware", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "Akenti is an authorization service for distributed resources. The authorization policy is kept in distributed certificates signed by one or more stakeholders for the resources. The package consists of the following components: Java GUI tools to create and sign the policy certificates C++ libraries to do make access decisions based on the policy certificates A standalone authorization server that make access decisions C interfaces to the libraries and server", + "homepageURL": "https://dst.lbl.gov/ACSSoftware/Akenti", + "laborHours": 0.0, + "languages": [ + "gcc 2.95.3, jdk 1.3" + ], + "name": "Akenti Authorization System", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://dst.lbl.gov/ACSSoftware/Akenti/download.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dst.lbl.gov/ACSSoftware/Akenti", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This package permits a scientist to perform computations using a precision level of either 32 or 64 decimal digits, by making only minor changes to conventional C++ or Fortran-90 source code. This software takes advantage of certain properties of IEEE floating-point arithmetic, together with advanced numeric algorithms, custom datatypes and operator overloading.", + "homepageURL": "https://www.davidhbailey.com/dhbsoftware", + "laborHours": 0.0, + "languages": [], + "name": "QD: A Double-Double/Quad-Double Package", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.davidhbailey.com/dhbsoftware", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.davidhbailey.com/dhbsoftware", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "AMELIA is an application with focus on particle physics processes in ATLAS. This will allow students and other users to decode the collision events that unfold after the head-on collisions of protons at the Large hadron Collider. AMELIA uses the Irrlicht engine for the 3D graphics and wxWidgets for the interface. It uses the best aspects of technical animation and allows users to control 3D representations of collision events and to manipulate 3D models of the detector and see how particles are detected as they pass through. It allows the user to rotate, zoom and select virtual pieces of the ATLAS detector and events. The characteristics of the events (momentum etc.) can also be read, and one can select tracks for analysis, activate context-oriented media, etc. This framework intends to integrate different types of media into a single product. This way, videos, animations, sound, interactive visualization and data analysis will be bound together in the same package.-", + "homepageURL": "https://sourceforge.net/projects/amelia", + "laborHours": 0.0, + "languages": [], + "name": "Atlas Multimedia Educational Lab for Interactive Analysis", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/amelia", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "DRQAT (Demand Response Quick Assessment Tool) is the tool for assessing demand response saving potentials for large commercial buildings. This tool is based on EnergyPlus simulations of prototypical buildings and HVAC equipment. The opportunities for demand reduction and cost savings with building demand responsive controls vary tremendously with building type and location. The assessment tools will predict the energy and demand savings, the economic savings, and the thermal comfort impact for various demand responsive strategies. Users of the tools will be asked to enter the basic building information such as types, square footage, building envelope, orientation, utility schedule, etc. The assessment tools will then use the prototypical simulation models to calculate the energy and demand reduction potential under certain demand responsive strategies, such as precooling, zonal temperature set up, and chilled water loop and air loop set points adjustment.", + "homepageURL": "https://buildings.lbl.gov/demand-response-quick-assessment-tool-drqat", + "laborHours": 0.0, + "languages": [], + "name": "Demand Response Quick Assessment Tool", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://buildings.lbl.gov/demand-response-quick-assessment-tool-drqat", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://buildings.lbl.gov/demand-response-quick-assessment-tool-drqat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Ipmi-fru retrieves field replacement unit (FRU) information, such as product name, manufacturer, and serial numbers, from a motherboard. It retrieves this information using the IPMI protocol.", + "homepageURL": "https://www.gnu.org/software/freeipmi/index.html", + "laborHours": 0.0, + "languages": [], + "name": "ipmi-fru", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The GAM/GAMV GUI provides a graphic user interface to public domain FORTRAN codes (gam, version 2.0 and gamv, version 2.0) that were developed at Stanford University in 1998 (see Deutsch and Journel, 1998). The gam and gamv codes allow for calculation of different measures of spatial variability and spatial correction from a set of available data. The GAM/GAMV GUI accesses the executable versions of the gam and gamv software, initiates the calculations by the executables and manages the outputs of the executables in a user friendly graphical manner. Additionally, the GAM/GAMV GUI code then provides the user with both automatic and interactive tools in a graphical interface to fit models to the calculations of the spatial variation/correlation of the data. The GAM/GAMV GUI software allows the user to get various parameters for the gam and gamv executables that do the actual calculations by using dialog boxes, it provides some error checking as these parameters are set and then allows the user to run the calculation by calling the executable compiled from the previously developed FORTRAN software. The resulting output of the gam or gamv codes can be visualized in the GAM/GAMV GUI interface. The visualization portion of GAM/GAMV allows for both automatic and manual fitting of the model of spatial variation/correlation. GAM/GAMV GUI can be run in batch mode from the command line without invoking the graphical interface.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "GAM/GAMV GUI", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/GAM-GAMV-GUI-AND-K3TD?tab=readme-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GAM-GAMV-GUI-AND-K3TD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The KT3D GUI provides a graphic user interface to a public domain FORTRAN code (kt3d) that was developed at Stanford University in 1998 (see Deutsch and Journel, 1998). The kt3d software contains the implementation of several kriging algorithms that complete spatial estimation onto a grid or a set of points from a set of available data and using a variogram model to describe the spatial variation of the data. The variogram model is calculated and modeled using the GAM/GAMV GUI software described separately. The KT3D GUI software allows the user to set various parameters for the FORTRAN code by using dialog boxes, it provides some error checking as these parameters are set and then allows the user to run the calculation by calling the executable compiled from the previously developed FORTRAN software. The resulting output of the kt3d code can be visualized in the KT3D GUI in several ways. If a gridded estimation problem is selected, color maps of the estimated values and the kriging variance are displayed in side by side images. If either jackknifing or cross-validation options are selected, then a series of user-defined X-Y plots can be created.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "KT3D GUI", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/GAM-GAMV-GUI-AND-K3TD?tab=readme-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GAM-GAMV-GUI-AND-K3TD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Dr. L provides two-dimensional visualizations of very large abstract graph structures. it can be used for data mining applications including biology, scientific literature, and social network analysis. Dr. L is a graph layout program that uses a multilevel force-directed algorithm. A graph is input and drawn using a force-directed algorithm based on simulated annealing. The resulting layout is clustered using a single link algorithm. This clustering is used to produce a coarsened graph (fewer nodes) which is then re-drawn. this process is repeated until a sufficiently small graph is produced. The smallest graph is drawn and then used as a basis for drawing the original graph by refining the series of coarsened graphs that were produced. The layout engine can be run in serial or in parallel.", + "homepageURL": "https://www.sandia.gov/smartin/software.html", + "laborHours": 0.0, + "languages": [ + "g++ and bash" + ], + "name": "Dr.L: Distributed Recursive (Graph) Layout", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.sandia.gov/smartin/software.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Provides a basic collection of utility plugins for use in the MVC Shell or MVC Framework environment. The MVC PluginLib is implemented in C# as a collection of.NET 2.0 frameworks that implement MVC Framework and MVC Shell compatible plugins. Three plugins are provided at this time, with more to be added over time: ApplicationInfoPlugin - provides basic information about the running application IronPythonPlugin - provides an IronPython based interactive shell environment ProgressBarPlugin - provides a basic progress bar implementation.", + "homepageURL": "https://archive.codeplex.com/?p=mvcpluginlib", + "laborHours": 0.0, + "languages": [], + "name": "MVC Plugin Lib", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://archive.codeplex.com/?p=mvcpluginlib", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Provides a reusable model-view-controller application programming interface (API) for use in the rapid development of graphical user interface applications in the .NET 2.0 framework. This includes a mechanism for adding new data stores, data sources, data analyses, and visualizations in the form of plugins.] The MVC Framework is implemented in C# as a .NET 2.0 framework that can then be built against when developing applications. The infrastructure allows for presenting application specific views (visualizations) to the user to interact with. Based on the interactions the user makes with a view, requests are generated which in turn are handled by the central controller facility. The controller handles the request in an application specific manner by routing the request to appropriate data stores, data accessors or data analyzers. Retrieved or processed data is published to subscribed components for further processing or for presentation to the user.", + "homepageURL": "http://www.codeplex.com/mvcframework", + "laborHours": 0.0, + "languages": [ + ".NET Framework 2.0" + ], + "name": "MVC Framework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.codeplex.com/mvcframework", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-22" + }, + "description": "This software is a set of utility libraries and tools developed in support of multiple scientific simulation projects. These libraries provide many general-purpose capabilities, such as a compact, extensible, machine-independent binary file format for various forms of scientific data, a Fortran-callable command parser that supports symbolic variables, looping, and conditional constructs, a Fortran-callable interface to ITT Corporation's callable IDL graphics and data analysis, a multi-block, 2D electrostatic solver, a machine-independent Fortran interface to standard system services, and various Fortran-callable dynamic memory services. In some cases, C interfaces are also provided. In addition, some tools that use these various libraries are available. A brief description of each library/tool follows: PFF library - PFF is a compact, extensible, machine-independent binary file format for various forms of scientific data. Two libraries are provided: one designed to be called from Fortran 77, and the other designed to be called from C or C++. Dataset types for several varieties of scientific data are built into the library, and new dataset types can be added. The libraries provide support for reading/writing these datasets from/to PFF files, as well as functionality for interactive processing of PFF files and the data they contain. Tools for manipulating, converting, and comparing PFF data are also available.", + "laborHours": 42043.2, + "languages": [ + "C++", + "C", + "Fortran", + "Python" + ], + "name": "Hermes Utility Libraries and Tools", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hermes-util", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The Transport version 3 (T3) system uses the Network News Transfer Protocol (NNTP) to move data from sources to a Data Repository (DR). Interested recipients subscribe to newsgroups to retrieve data. Data in transport is protected by AES-256 and RSA cryptographic services provided by the external OpenSSL cryptographic libraries.", + "homepageURL": "https://svn.pnl.gov/transport", + "laborHours": 0.0, + "languages": [ + "Python and Perl" + ], + "name": "Transport Version 3", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://svn.pnl.gov/transport", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.pnl.gov/transport", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The software calculates the interior eigenstates of a nanosystem with a given Hamiltonian. This is used for nonselfconsistent calculations of electron and hole states for large (a few thousands to hundreds of thousands of atoms) nanostructures. The electron wave function is represented by a planewave basis set. FFT is used to transform the wavefunction from reciprocal space to real space to be applied to the potential. Nonlocal pseudopotentlals are used in the Hamiltonian and spin-orbit interactions are included. One primary approach to calculate the interior eigenstates in the code is to use the folded spectrum method. Several numerical algorithms are implemented in this package, including the conjugated gradient method, the Jacobi-Davidson method, and the LOPCG method. The user can select different algorithms based on their particular problem and number of wavefunctions needed to be solved.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Fortran 90 and C" + ], + "name": "Pescan", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "GenOpt is a generic optimization program for nonlinear, constrained optimization. For evaluating the objective function, any simulation program that communicates over text files can be coupled to GenOpt without code modification. No analytic properties of the objective function are used by GenOpt. Optimization algorithms and numerical methods can be implemented in a library and shared among users. GenOpt offers an interlace between the optimization algorithm and its kernel to make the implementation of new algorithms fast and easy. Different algorithms of constrained and unconstrained minimization can be added to a library. Algorithms for approximation derivatives and performing line-search will be implemented. The objective function is evaluated as a black-box function by an external simulation program. The kernel of GenOpt deals with the data I/O, result storage and report, interlace to the external simulation program, and error handling. An abstract optimization class offers methods to interface the GenOpt kernel and the optimization algorithm library.", + "homepageURL": "http://simulationresearch.lbl.gov/GO", + "laborHours": 0.0, + "languages": [], + "name": "Generic Optimization Program", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://simulationresearch.lbl.gov/GO/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://simulationresearch.lbl.gov/GO", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The Building Controls Virtual Test Bed (BCVTB) is a modular software environment that is based on the Ptolemy II software environment. The BCVTB can be used for design and analysis of heterogenous systems, such as building energy and controls systems. Our additions to Ptolemy II allow users to Couple to Ptolemy II simulation software such as EnergyPlus, MATLAB/Simulink or Dymola for data exchange during run-time. Future versions of the BCVTS will also contain an interface to BACnet which is a communication protocol for building Control systems, and interfaces to digital/analog converters that allow communication with controls hardware. Through Ptolemy II, the BCVTB provides a graphical model building environment, synchronizes the exchanged data and visualizes the system evolution during run- time.", + "homepageURL": "https://simulationresearch.lbl.gov/bcvtb", + "laborHours": 0.0, + "languages": [], + "name": "Building Controls Virtual Test Bed", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://simulationresearch.lbl.gov/bcvtb/License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://simulationresearch.lbl.gov/bcvtb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Voro++ is a software library for the Computation of 3D Voronoi cells. It is primarily designed for applications in physics and materials science, where Voronoi cells can be a useful tool in the analysis of densely-packed particle systems. For a set of points in a space, the Voronoi cell of each particle is defined as the region which is closer to that particle than any other. Originally defined by Georgy Voronci [1], it has become a powerful tool in many scientific fields, whenever region of space must be divided between constituent points or particles [2]. Over the past twenty years, the algorithms for computing Voronoi cells have been well-studied, and several high-quality software packages are available. However, some (such as Triangle [3] are designed for the 2D case. Others, such as QHull [4], make use of algorithms for computing complete tessellations. This can offer limited flexibility, such as for handling complex boundary conditions, where direct cell-by-cell manipulation is beneficial. Voro++ is a library of C++ classes for direct computation of 3D Voronoi cells. The author believes this the first general purpose library that takes full advantage of the C++ class structure, making it simple to use, modify, and incorporate into other programs. The author has received considerable interest from other academic institutions about making use of the code. Features include: -- Rapid computation times, two to three times faster than Qhull in some typical cases -- Support for floating point inaccuracies and degenerate cases -- Support for curved and planar walls; periodic and non-periodic boundary conditions -- Support for radical Voronoi tessellations and neighbor list computations --Straightforward generalization to a parallel/ multicore architecture.", + "homepageURL": "http://math.lbl.gov/voro++", + "laborHours": 0.0, + "languages": [], + "name": "VORO++", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://math.lbl.gov/voro++/download", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://math.lbl.gov/voro++", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Nek5000 is high-order spectral element code used for the simulation of incompressible fluid flow, MHD, and heat transfer in general three-dimensional domains that has been specifically developed for deployment on large-scale distributed memory parallel architectures. The code features state of the art matrix free multilevel iterative solvers coupled with stable second and third order operator-split stepping schemes. Scalable performance has been established onup to 32,000 processors and the overall quality of the algorithmic approach, implementation, and performance were recognized with the award of the Gordon Bell Prize in 1999.", + "laborHours": 0.0, + "languages": [ + "f77/C" + ], + "name": "Nek5000", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/Nek5000/Nek5000/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Nek5000/Nek5000", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Ipmi-dcmi supports motherboards compliant to the Data Center Management Interface (DCMI) specification, DCMI features include asset management and power limit management.", + "homepageURL": "https://www.gnu.org/software/freeipmi/index.html", + "laborHours": 0.0, + "languages": [], + "name": "ipmi-dcmi", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "This is a Matlab toolbox for investigating the application of cluster ensembles to data classification, with the objective of improving the accuracy and/or speed of clustering. The toolbox divides the cluster ensemble problem into four areas, providing functionality for each. These include, (1) synthetic data generation, (2) clustering to generate individual data partitions and similarity matrices, (3) consensus function generation and final clustering to generate ensemble data partitioning, and (4) implementation of accuracy metrics. With regard to data generation, Gaussian data of arbitrary dimension can be generated. The kcenters algorithm can then be used to generate individual data partitions by either, (a) subsampling the data and clustering each subsample, or by (b) randomly initializing the algorithm and generating a clustering for each initialization. In either case an overall similarity matrix can be computed using a consensus function operating on the individual similarity matrices. A final clustering can be performed and performance metrics are provided for evaluation purposes.", + "homepageURL": "https://www.mathworks.com/matlabcentral/fileexchange/23941-matlab-cluster-ensemble-toolbox", + "laborHours": 0.0, + "languages": [], + "name": "Matlab Cluster Ensemble Toolbox", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.mathworks.com/matlabcentral/fileexchange/23941-matlab-cluster-ensemble-toolbox", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.mathworks.com/matlabcentral/fileexchange/23941-matlab-cluster-ensemble-toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Zonetool is a utility for managing signed DNS zones and managing DNSSEC keys. It maintains the state of managed DNS zones and uses the BIND utilities to actually perform key generation, zone signing, and validation. DNS administrators will use Zonetool to initially deploy and further maintain a signed DNS zone.", + "laborHours": 0.0, + "languages": [], + "name": "Zonetool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/zonetool", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "PACT is a set of tools to help software developers create applications that will run on any platform and data that can be written/read on any platform.", + "homepageURL": "https://code.google.com/p/pactnew", + "laborHours": 0.0, + "languages": [], + "name": "Portable Application Code Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.google.com/p/pactnew", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Provides a tool with which create and characterize a very large set of matrix-based visual analogy problems that have properties that are similar to Raven's Progressive Matrices (RPMs)\u2122. The software uses the same underlying patterns found in RPMs to generate large numbers of unique matrix problems using parameters chosen by the researcher. Specifically, the software is designed so that researchers can choose the type, direction, and number of relations in a problem and then create any number of unique matrices that share the same underlying structure (e.g. changes in numerosity in a diagonal pattern) but have different surface features (e.g. shapes, colors).Raven's Progressive Matrices (RPMs) \u2122 are a widely-used test for assessing intelligence and reasoning ability. Since the test is non-verbal, it can be applied to many different populations and has been used all over the world. However, there are relatively few matrices in the sets developed by Raven, which limits their use in experiments requiring large numbers of stimuli. This tool creates a matrix set in a systematic way that allows researchers to have a great deal of control over the underlying structure, surface features, and difficulty of the matrix problems while providing a large set of novel matrices with which to conduct experiments.", + "laborHours": 0.0, + "languages": [], + "name": "Sandia Generated Matrix Tool (SGMT) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Matrices", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The ESnet On-Demand Secure Circuits and Advance Reservation System (OSCARS) is a prototype service enabling advance reservation of guaranteed bandwidth secure virtual circuits. OSCARS operates within the Energy Sciences Network (ESnet), and has provisions for interoperation with other network domains. OSCARS utilizes the Web services model and standards to implement communication with the system and between domains, and for authentication, authorization, and auditing (AAA). The management and operation of end-to-end virtual circuits within the network is done at the layer 3 network level. Multi-Protocol Label Switching (MPLS) and the Resource Reservation Protocol (RSVP) are used to create the virtual circuits or Label Switched Paths (LSP's). Quality of Service (QoS) is used to provide bandwidth guarantees.", + "homepageURL": "https://www.es.net/engineering-services/oscars", + "laborHours": 0.0, + "languages": [ + "None" + ], + "name": "Oscars", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.es.net/engineering-services/oscars", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The national Water, Energy and Carbon Sequestration Simulation Model (WECSsim) is an analysis tool that can be used at the local, regional and national scale to address a potentially combined system using a coal or natural gas-fired power plant, a geologic carbon sequestration system in saline formations, and water extraction and treatment. With this combined system for geologic storage of CO2 in saline formations, the treated saline formation water could be used as cooling water in the power plant. The key areas addressed in this tool include applying a data reduction process to existing NatCarb saline formation data to select the most viable formations for CO2 injection, water withdrawal and treatment metrics, and developing a national model to address the multiple combinations of power plants and saline formations. This model can be utilized by decision makers to understand the economic benefits and tradeoffs of this combined system. WECSsim allows for sensitivity analyses for capital costs, variables costs, CO2 sequestration and water treatment systems' costs. The main goal of the WECSsim model is to allow interested individuals or groups the ability to run custom power plant, CO2 sequestration and water use scenarios for different regions of the country and understand the associated economics, longevity and potential of the CO2 sequestration and water extraction systems.", + "laborHours": 0.0, + "languages": [ + "PowerSim Studio 7" + ], + "name": "Water, Energy and Carbon Sequestration Model (WECSsim) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/WECSSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Zoltan2 is a refactoring of the open-source Zoltan library that enables Zoltan users to take better advantage of current and emerging high performance computing architectures and software tools. Like Zoltan, Zoltan2 is a toolkit of combinatorial scientific computing algorithms that enable better performance of scientific codes via improved data locality and parallel scalability. Specifically Zoltan2 partitions data, colors graphs, and orders matrices. Zoltan2 is a software library written in template C++; it supports a wider range of data types and problem sizes than Zoltan. It will be available as part of Sandia's Trilinos framework of scientific computing packages.", + "laborHours": 8344830.4, + "languages": [], + "name": "Zoltan2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Impiseld stores IPMI based hardware events into normal system logs.", + "homepageURL": "https://www.gnu.org/software/freeipmi/index.html", + "laborHours": 0.0, + "languages": [], + "name": "ipmiseld", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Warp is a multidimensional discrete-particle beam simulation program designed to be applicable where the beam space-charge is non-negligible or dominant. It is being developed in a collaboration among LLNL, LBNL and the University of Maryland. It was originally designed and optimized for heave ion fusion accelerator physics studies, but has received use in a broader range of applications, including for example laser wakefield accelerators, e-cloud studies in high enery accelerators, particle traps and other areas. At present it incorporates 3-D, axisymmetric (r,z) planar (x-z) and transverse slice (x,y) descriptions, with both electrostatic and electro-magnetic fields, and a beam envelope model. The code is guilt atop the Python interpreter language.", + "laborHours": 0.0, + "languages": [], + "name": "Particle-in-cell/accelerator code for space-charge dominated beam simulation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/warp/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "We study the detection of mutations, sequencing errors, and homologous horizontal gene transfers (HGT) in a set of closely related microbial genomes. We base the model on single nucleotide polymorphisms (SNP's) and break the genomes into blocks to handle the rearrangement problem. Then we apply a synamic programming algorithm to model whether changes within each block are likely a result of mutations, sequencing errors, or HGT.", + "homepageURL": "https://sourceforge.net/projects/hgtfinder", + "laborHours": 0.0, + "languages": [], + "name": "Detection of homologous horizontal gene transfer in SNP data", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sourceforge.net/projects/hgtfinder/files", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/hgtfinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The function of the World Oil Market Model (WOMM) is to calculate a world oil price. SEDS will set start and end dates for the forecast period, and a time increment (assumed to be 1 year in the initial version). The WOMM will then randomly select an Annual Energy Outlook (AEO) oil price case and calibrate itself to that case. As it steps through each year, the WOMM will generate a stochastic supply shock to OPEC output and accept a new estimate of U.S. petroleum demand from SEDS. The WOMM will then calculate a new oil market equilibrium for the current year. The world oil price at the new equilibrium will be sent back to SEDS. When the end year is reached, the process will begin again with the selection of a new AEO forecast. Iterations over forecasts will continue until SEDS has completed all its simulation runs.", + "homepageURL": "https://www.nrel.gov/analysis/seds/oil-market-module.html", + "laborHours": 0.0, + "languages": [ + "Lumina Decision System's Analytica version 4.3" + ], + "name": "Stochastic Energy Deployment System (SEDS) World Oil Model (WOM)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/analysis/seds/download-model.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/analysis/seds/oil-market-module.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The EDEN toolkit facilitates exploratory data analysis and visualization of global climate model simulation datasets. EDEN provides an interactive graphical user interface (GUI) that helps the user visually construct dynamic queries of the characteristically large climate datasets using temporal ranges, variable selections, and geographic areas of interest. EDEN reads the selected data into a multivariate visualization panel which features an extended implementation of parallel coordinates plots as well as interactive scatterplots. The user can query data in the visualization panel using mouse gestures to analyze different ranges of data. The visualization panel provides coordinated multiple views whereby selections made in one plot are propagated to the other plots.", + "laborHours": 0.0, + "languages": [ + "Java 1.6 or higher" + ], + "name": "Ensemble Data Analysis ENvironment (EDEN)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/csteed/eden/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csteed/eden", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "FREYA is a computer code that generates complete fission events. The output includes the energy and momentum of these final state particles: fission products, prompt neutrons and prompt photons. The version of FREYA that is to be released is a module for MCNP6.", + "homepageURL": "http://nuclear.llnl.gov/simulations", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Event-by-event fission simulation code, generates complete fission events", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://nuclear.llnl.gov/simulations", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://nuclear.llnl.gov/simulations", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2022-11-16" + }, + "description": "EQ3/6 is a software package for modeling geochemical interactions between aqueous solution, solids, and gases, following principles of chemical thermodynamics and chemical kinetics. It is useful for interpreting aqueous solution chemical compositions and for calculating the consequences of reaction of such solutions with minerals, other solids, and gases. It is designed to run in a command line environment. EQPT is a thermodynamic data file preprocessor. EQ3NR is a speciation-solubility code. EQ6 is a reaction path code.", + "laborHours": 0.0, + "languages": [], + "name": "EQ3/6 A Software Package for Geochemical Modeling", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/eq3_6", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "CorAL is a software Library designed to aid in the analysis of femtoscipic data. Femtoscopic data are a class of measured quantities used in heavy-ion collisions to characterize particle emitting source sizes. The most common type of this data is two-particle correleations induced by the Hanbury-Brown/Twiss (HBT) Effect, but can also include correlations induced by final-state interactions between pairs of emitted particles in a heavy-ion collision. Because heavy-ion collisions are complex many particle systems, modeling hydrodynamical models or hybrid techniques. Using the CRAB module, CorAL can turn the output from these models into something that can be directley compared to experimental data. CorAL can also take the raw experimentally measured correlation functions and image them by inverting the Koonin-Pratt equation to extract the space-time emission profile of the particle emitting source. This source function can be further analyzed or directly compared to theoretical calculations.", + "homepageURL": "https://asc.llnl.gov/CORAL-benchmarks", + "laborHours": 0.0, + "languages": [ + "C++, Python" + ], + "name": "Correlation Algorithm Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://asc.llnl.gov/CORAL-benchmarks", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://asc.llnl.gov/CORAL-benchmarks", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Community detection has become a fundamental operation in numerous graph-theoretic applications. It is used to reveal natural divisions that exist within real world networks without imposing prior size or cardinality constraints on the set of communities. Despite its potential for application, there is only limited support for community detection on large-scale parallel computers, largely owing to the irregular and inherently sequential nature of the underlying heuristics. In this paper, we present parallelization heuristics for fast community detection using the Louvain method as the serial template. The Louvain method is an iterative heuristic for modularity optimization. Originally developed by Blondel et al. in 2008, the method has become increasingly popular owing to its ability to detect high modularity community partitions in a fast and memory-efficient manner. However, the method is also inherently sequential, thereby limiting its scalability. Here, we observe certain key properties of this method that present challenges for its parallelization, and consequently propose heuristics that are designed to break the sequential barrier. For evaluation purposes, we implemented our heuristics using OpenMP multithreading, and tested them over real world graphs derived from multiple application domains (e.g., internet, citation, biological). Compared to the serial Louvain implementation, our parallel implementation is able to produce community outputs with a higher modularity for most of the inputs tested, in comparable number of iterations, while providing real speedups of up to 8x using 32 threads. In addition, our parallel implementation was able to exhibit weak scaling properties on up to 32 threads.", + "laborHours": 0.0, + "languages": [], + "name": "Grappolo", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exa-Graph/grappolo", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The PNNL Prony Ringdown graphical user interface is one analysis tool included in the Dynamic System Identification toolbox (DSI Toolbox). The Dynamic System Identification toolbox is a MATLAB-based collection of tools for parsing and analyzing phasor measurement unit data, especially in regards to small signal stability. It includes tools to read the data, preprocess it, and perform small signal analysis. 5. Method of Solution: The Dynamic System Identification Toolbox (DSI Toolbox) is designed to provide a research environment for examining phasor measurement unit data and performing small signal stability analysis. The software uses a series of text-driven menus to help guide users and organize the toolbox features. Methods for reading in populate phasor measurement unit data are provided, with appropriate preprocessing options for small-signal-stability analysis. The toolbox includes the Prony Ringdown GUI and basic algorithms to estimate information on oscillatory modes of the system, such as modal frequency and damping ratio.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Prony Ringdown GUI (CERTS Prony Ringdown, part of the DSI Tool Box)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ftuffner/DSIToolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "FABLE is a Fortran to C++ source-to-source conversion tool. This enables the continued development of new methods even while switching programming languages. FABLE is available under a nonrestrictive open source license. In FABLE the analysis of the Fortran source is separated from the generation of the C++ source. Therefore parts of FABLE could be reused for other target languages. Hardware req.: Multi-platform; types of files: source code, sample problem Input data, sample problem output, installation instructions, user guide.", + "laborHours": 0.0, + "languages": [ + "fortran" + ], + "name": "FABLE - automatic Fortran to C++ conversion", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cctbx/cctbx_project/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cctbx/cctbx_project", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-09-08" + }, + "description": "Alquimia provides a generic interface between flow and transport simulators (drivers) and biogeochemical reaction capabilities (engines). Alquimia consists of two parts: an application programming interface, API, and a wrapper library. The API describes in detail how information is exchanged between the driver and the engine. This includes the function call signatures and data structures required for implementing alquimia in a mixed language (C/C++/Fortran) programming environment. The library is an implementation of the documented API, providing an interface into the biogeochemistry routines supplied by other codes: Alquimia does not do any geochemical calculations. Version 1.0 provides interfaces to the open source codes (BSD) CrunchFlow/CrunchTope and (LGPL) PFLOTRAN. Version 1.0 meets the policies set forth by (and is part of) the Extreme-scale Scientific Software Development Kit, xSDK version 0.6.0.", + "laborHours": 0.0, + "languages": [ + "C++", + "Fortran" + ], + "name": "Alquimia", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LBL-EESA/alquimia-dev/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-EESA/alquimia-dev", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Warewulf is a scalable systems management suite originally developed to manage large high-performance Linux clusters. Focused on general scalable systems management, it includes a framework for system configuration, management, provisioning/installation, monitoring, event notification, and more via a modular plugin architecture. Install the components and features you need or leverage the existing system configuration stored within Warewulf to create custom solutions to meet your performance needs. One of the goals of the project is to grow the project by allowing other organizations and developers to contribute back to the project under an open source BSD license. We have been successful with gaining support within the open source community already and have contributors and support in not only the government and academic space but also the commercial sector (e.g. Intel). Being both open source and vendor neutral puts Warewulf in a unique position to be supported and utilized as an open standard in High Performance Computing (HPC). Warewulf is an active member of various HPC initiatives and groups and is considered one of the most utilized, extensible and scalable clustering toolkits available.", + "laborHours": 0.0, + "languages": [], + "name": "Warewulf 3.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://warewulf.lbl.gov/trac/browser/trunk/common/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/warewulf/warewulf3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "COMFEN supports the systematic evaluation of alternative fenestration systems for project-specific commercial building applications. COMFEN provides simplified Excel-based user interface that focuses attention on key variables in fenestration design. Under the hood in EnergyPlus, a sophisticated analysis engine that dynamically simulate the effects of these key fenestration variables on energy consumption, peak energy demand, and thermal and visual comfort. The results from the EnergyPlus simulation are presented in graphical and tabular format within the simplified user interface for up to four comparative fenestration design cases to help users move toward optimal fenestration design choices for their project.", + "homepageURL": "https://windows.lbl.gov/software/comfen", + "laborHours": 0.0, + "languages": [], + "name": "COMFEN", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://windows.lbl.gov/software/comfen", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://windows.lbl.gov/software/comfen", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Bulk Data Mover (BDM) is a high-level data transfer management tool. BDM handles the issue of large variance in file sizes and a big portion of small files by managing the file transfers with optimized transfer queue and concurrency management algorithms. For example, climate simulation data sets are characterized by large volume of files with extreme variance in file sizes. The BDN achieves high performance using a variety of techniques, including multi-threaded concurrent transfer connections, data channel caching, load balancing over multiple transfer servers, and storage i/o pre-fetching. Logging information from the BDM is collected and analyzed to study the effectiveness of the transfer management algorithms. The BDM can accept a request composed of multiple files or an entire directory. The request also contains the target site and directory where the replicated files will reside. If a directory is provided at the source, then the BDM will replicate the structure of the source directory at the target site. The BDM is capable of transferring multiple files concurrently as well as using parallel TCP streams. The optimal level of concurrency or parallel streams depends on the bandwidth capacity of the storage systems at both ends of the transfer as well as achievable bandwidth of the wide-area network. Hardware req.-PC, MAC, Multi-platform & Workstation; Software req.: Compile/version-Java 1.50_x or above; Type of files: source code, executable modules, installation instructions other, user guide; URL: http://sdm.lbl.gov/bdm/", + "homepageURL": "https://sdm.lbl.gov/bdm", + "laborHours": 0.0, + "languages": [ + "java 1.50{sub minus}x or above" + ], + "name": "Bulk Data Mover", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sdm.lbl.gov/bdm/License.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sdm.lbl.gov/bdm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "DataMover-Lite (DML) is a client program whose purpose is to automatically manage multi-file transfers to clients. It expects as its input a transfer-instruction file, and a local target directory where the files will be moved to. The input file contains the Logical File Names (LFNs) and the transfer URLs (TURLs) of files that need to be transferred. The TURLs can have various protocols depending on the server that manages the files, including gridftp, ftp, https, and srm. Given a multi-file request for a large number of files, the DML can issue concurrently a number of transfers in order to get the files. The number of transfers it can issue is set as a parameter and is usually less than 10. For example, if the multi-file is for 100 files, the DML may keep active only 5 transfers at any one time. When any of the 5 transfers completes it will initiate another transfer. It is not necessary for a single request to contain files whose TURLs have same protocol. If the request to the DML contains TURLs with various protocols, the DML will contact the various servers on different threads according to each TURL's protocol. The DMK take care if scheduling the transfers, monitoring their progress, releasing the files, and getting the authorization for each file to be transferred.", + "homepageURL": "https://sdm.lbl.gov/dml", + "laborHours": 0.0, + "languages": [ + "java 1.5.0{sub minus}x or above" + ], + "name": "DataMover-Lite", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sdm.lbl.gov/dml/DMLLicense.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sdm.lbl.gov/dml", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "minomond is a simple software package built to unobtrrusively collect large amounts of trending data on computer systems, and send that data to one or more external trending data aggregation services. The goal is to enable ongoing recording of many metrics from many nodes in order to identify historical patterns and provide historical visibility into systems problems. minimond is intended to replace large collections of ad hoc scripts that are commonly used for this purpose. minomond is built with an emphasis on simplicity and extensibility, and is intended to supplement, not replace, other availability and trending data monitoring systems.", + "laborHours": 0.0, + "languages": [], + "name": "Minimond", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NERSC/minimond/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/minimond", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "BEST-Cities is designed to provide city authorities with strategies they can follow to reduce city-wide carbon dioxide (CO2) and methane (CH4) emissions. The tool quickly assesses local energy use and energy-related CO2 emissions across nine sectors (i.e., industry, public and commercial buildings, residential buildings, transportation, power and heat, street lighting, water & wastewater, solid waste, and urban green space), giving officials a comprehensive perspective on their local carbon performance. Cities can also use the tool to benchmark their energy and emissions performance to other cities inside and outside China, and identify those sectors with the greatest energy saving and emissions reduction potential.", + "homepageURL": "https://china.lbl.gov/best-cities", + "laborHours": 0.0, + "languages": [], + "name": "Benchmarking and Energy Saving Tool for Low Carbon Cities (BEST Cities)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://china.lbl.gov/best-cities", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://china.lbl.gov/best-cities", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "bobby.kitchens@srnl.doe.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Mesh2d is a Fortran90 program designed to generate two-dimensional structured grids of the form [x(i),y(i,j)] where [x,y] are grid coordinates identified by indices (i,j). The x(i) coordinates alone can be used to specify a one-dimensional grid. Because the x-coordinates vary only with the i index, a two-dimensional grid is composed in part of straight vertical lines. However, the nominally horizontal y(i,j0) coordinates along index i are permitted to undulate or otherwise vary. Mesh2d also assigns an integer material type to each grid cell, mtyp(i,j), in a user-specified manner. The complete grid is specified through three separate input files defining the x(i), y(i,j), and mtyp(i,j) variations.", + "homepageURL": "http://srnl.doe.gov/downloads/Mesh2d_distribution.zip", + "laborHours": 0.0, + "languages": [ + "Fortran90 compiler / N/A" + ], + "name": "Mesh2d", + "organization": "Savannah River Site (SRS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://srnl.doe.gov/downloads/Mesh2d_distribution.zip", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://srnl.doe.gov/downloads/Mesh2d_distribution.zip", + "status": "Production", + "tags": [ + "DOE CODE", + "Savannah River Site (SRS)" + ] + }, + { + "contact": { + "email": "bobby.kitchens@srnl.doe.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "DLLExternalCode is the a general dynamic-link library (DLL) interface for linking GoldSim (www.goldsim.com) with external codes. The overall concept is to use GoldSim as top level modeling software with interfaces to external codes for specific calculations. The DLLExternalCode DLL that performs the linking function is designed to take a list of code inputs from GoldSim, create an input file for the external application, run the external code, and return a list of outputs, read from files created by the external application, back to GoldSim. Instructions for creating the input file, running the external code, and reading the output are contained in an instructions file that is read and interpreted by the DLL.", + "homepageURL": "http://srnl.doe.gov/downloads/DllExternalCode_distribution.zip", + "laborHours": 0.0, + "languages": [ + "Fortran90 compiler" + ], + "name": "DLLExternalCode", + "organization": "Savannah River Site (SRS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://srnl.doe.gov/downloads/DllExternalCode_distribution.zip", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://srnl.doe.gov/downloads/DllExternalCode_distribution.zip", + "status": "Production", + "tags": [ + "DOE CODE", + "Savannah River Site (SRS)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Analytical application performance models are critical for diagnosing performance-limiting resources, optimizing systems, and designing machines. Creating models, however, is difficult. Furthermore, models are frequently expressed in forms that are hard to distribute and validate. The Performance and Architecture Lab Modeling tool, or Palm, is a modeling tool designed to make application modeling easier. Palm provides a source code modeling annotation language. Not only does the modeling language divide the modeling task into sub problems, it formally links an application's source code with its model. This link is important because a model's purpose is to capture application behavior. Furthermore, this link makes it possible to define rules for generating models according to source code organization. Palm generates hierarchical models according to well-defined rules. Given an application, a set of annotations, and a representative execution environment, Palm will generate the same model. A generated model is a an executable program whose constituent parts directly correspond to the modeled application. Palm generates models by combining top-down (human-provided) semantic insight with bottom-up static and dynamic analysis. A model's hierarchy is defined by static and dynamic source code structure. Because Palm coordinates models and source code, Palm's models are 'first-class' and reproducible. Palm automates common modeling tasks. For instance, Palm incorporates measurements to focus attention, represent constant behavior, and validate models. Palm's workflow is as follows. The workflow's input is source code annotated with Palm modeling annotations. The most important annotation models an instance of a block of code. Given annotated source code, the Palm Compiler produces executables and the Palm Monitor collects a representative performance profile. The Palm Generator synthesizes a model based on the static and dynamic mapping of annotations to program behavior. The model -- an executable program -- is a hierarchical composition of annotation functions, synthesized functions, statistics for runtime values, and performance measurements.", + "laborHours": 0.0, + "languages": [ + "C/C++ Language compiler" + ], + "name": "Performance and Architecture Lab Modeling Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.pnnl.gov/perf-lab-hub/palm/palm/-/blob/master/README-license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab-hub/palm/palm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Morph is a framework and domain-specific language (DSL) that helps parse and transform structured documents. It currently supports several file formats including XML, JSON, and CSV, and custom formats are usable as well.", + "laborHours": 0.0, + "languages": [ + "Scala 2.10x/. JVM 1.7+" + ], + "name": "morph", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stucco-archive/morph", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Building energy efficient retrofit energy savings and cost-effectiveness analysis.", + "homepageURL": "https://china.lbl.gov/combat", + "laborHours": 0.0, + "languages": [], + "name": "Commercial Building Analysis Tool for Building Energy Efficient Retrofit - COMBAT", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://china.lbl.gov/combat", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://china.lbl.gov/combat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Tracktable is designed for analysis and rendering of the trajectories of moving objects such as planes, trains, automobiles and ships. Its purpose is to operate on large sets of trajectories (millions) to help a user detect, analyze and display patterns. It will also be used to disseminate trajectory research results from Sandia's PANTHER Grand Challenge LDRD.", + "laborHours": 0.0, + "languages": [ + "C++", + "Shell", + "C", + "Jupyter Notebook", + "CMake", + "Python" + ], + "name": "TrackTable Trajectory Analysis", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tracktable", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "WINDOW features include: - Microsoft Windows TM interface - algorithms for the calculation of total fenestration product U-values and Solar Heat Gain Coefficient consistent with ASHRAE SPC 142, ISO 15099, and the National Fenestration Rating Council - a Condensation Resistance Index in accordance with the NFRC 500 Standard - and integrated database of properties - imports data from other LBNL window analysis software: - Import THERM file into the Frame Library - Import records from IGDB and OPtics5 into the Glass Library for the optical properties of coated and uncoated glazings, laminates, and applied films. Program Capabilities WINDOW 7.2 offers the following features: The ability to analyze products made from any combination of glazing layers, gas layers, frames, spacers, and dividers under any environmental conditions and at any tilt; The ability to model complex glazing systems such as venetian blinds and roller shades. Directly accessible libraries of window system components, (glazing systems, glazing layers, gas fills, frame and divider elements), and environmental conditions; The choice of working in English (IP), or Systeme International (SI) units; The ability to specify the dimensions and thermal properties of each frame element (header, sills, jamb, mullion) in a window; A multi-band (wavelength-by-wavelength) spectral model; A Glass Library which can access spectral data files for many common glazing materials from the Optics5database; A night-sky radiative model; A link with the DOE-2.1E and Energy Plus building energy analysis program. Performance Indices and Other Results For a user-defined fenestration system and user-defined environmental conditions, WINDOW calculates: The U-value, solar heat gain coefficient, shading coefficient, and visible transmittance for the complete window system; The U-value, solar heat gain coefficient, shading coefficient, and visible transmittance for the glazing system (center-of-glass values); The U-values of the frame and divider elements and corresponding edge-of-glass areas (based on generic correlations); The total solar and visible transmittance and reflectances of the glazing system. Color properties, i.e. L*, a*, and b* color coordinates, dominant wavelength, and purity for transmitted and reflected (outdoor) solar radiation; The damage-weighted transmittance of the glazing system between 0.3 an 0.38 microns; The angular dependence of the solar and visible transmittances, solar and visible reflectances, solar absorptance, and solar heat gain coefficient of the glazing system; The percent relative humidity of the inside and outside air for which condensation will occur on the interior and exterior glazing surfaces respectively; The center-of-glass temperature distribution.", + "homepageURL": "https://windows.lbl.gov/software/window", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Lab WINDOW", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://windows.lbl.gov/window-license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://windows.lbl.gov/software/window", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Octopus is a scientific program aimed at the ab initio virtual experimentation on a hopefully ever-increasing range of system types. Electrons are described quantum-mechanically within density-functional theory (DFT), in its time-dependent form (TDDFT) when doing simulations in time. Nuclei are described classically as point particles. Electron-nucleus interaction is described within the pseudopotential approximation.", + "laborHours": 3054820.0, + "languages": [], + "name": "Octopus", + "organization": "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/octopus-code/octopus/blob/develop/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/octopus-code/octopus", + "status": "Production", + "tags": [ + "DOE CODE", + "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "This software package provides tools for astrophysical experiments which record data in the form of individual time streams from discrete detectors. TOAST provides tools from meta-data manipulation and job set up, I/O operation, telescope pointing reconstruction, and map-making. It also provides tools for constructing simulated observations.", + "laborHours": 0.0, + "languages": [ + "Any Standard C++ complier which supports the BOOST software package" + ], + "name": "Time Ordered Astrophysics Scalable Tools", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/tskisner/toast/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tskisner/TOAST", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Cambio opens data files from common gamma radiation detectors, displays a visual representation of it, and allows the user to edit the meta-data, as well as convert the data to a different file format.", + "laborHours": 0.0, + "languages": [ + "Requires C++03 compliant compiler" + ], + "name": "Cambio", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cambio", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bobby.kitchens@srnl.doe.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Gnuforplot Graphics is a Fortran90 program designed to generate two and three dimensional plots of data on a personal computer. The program uses calls to the open source code Gnuplot to generate the plots. Two Fortran90 programs have been written to use the Gnuplot graphics capabilities. The first program, named Plotsetup.f90 reads data from output files created by either the Stadium or LeachXS/Orchestra modeling codes and saves the data in arrays for plotting. This program then calls Gnuforplot which takes the data array along with user specified parameters to set plot specifications and issues Gnuplot commands that generate the screen plots. The user can view the plots and optionally save copies in jpeg format.", + "homepageURL": "http://sti.srs.gov/fulltext/Software/gnuforplot_rev_11-4-15.zip", + "laborHours": 0.0, + "languages": [ + "Fortran90" + ], + "name": "GnuForPlot Graphics", + "organization": "Savannah River Site (SRS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://sti.srs.gov/fulltext/Software/gnuforplot_rev_11-4-15.zip", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://sti.srs.gov/fulltext/Software/gnuforplot_rev_11-4-15.zip", + "status": "Production", + "tags": [ + "DOE CODE", + "Savannah River Site (SRS)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2022-06-15" + }, + "description": "The MapRE (Multi-criteria Analysis for Planning Renewable Energy) GIS (Geographic Information Systems) Tools are a set of ArcGIS tools to a) conduct site suitability analysis for wind and solar resources using inclusion and exclusion criteria, and create resource maps, b) create project opportunity areas and compute various attributes such as cost, distances to existing and planned infrastructure. and environmental impact factors; and c) calculate and update various attributes for already processed renewable energy zones. In addition, MapRE data sets are geospatial data of renewable energy project opportunity areas and zones with pre-calculated attributes for several countries. These tools and data are available at mapre.lbl.gov.", + "homepageURL": "http://mapre.lbl.gov", + "laborHours": 0.0, + "languages": [], + "name": "MapRE GIS Tools & Data (MapRE)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://mapre.lbl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Time-lapse ERT imaging for monitoring both natural and engineered subsurface processes has advanced rapidly over the past 15-20 years. However, imaging results generally required a significant amount of manual and computational effort, and therefore were not available while the process was occurring. Although the value of real-time imaging was recognized, several obstacles prevented it's implementation. E4D_RT addresses these obstacles by 1) providing specialized algorithms that negate the need for user intervention, thereby automating the time-lapse data processing steps, 2) linking field data collection systems with parallel supercomputing systems via wireless data transfer link, and 3) addressing the computational burdens by utilizing distributed memory supercomputing resources, thereby enabling rapid data processing and imaging results.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "E4D_RT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/E4D/blob/master/E4D_LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/E4D", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Singularity is a container solution designed to facilitate mobility of compute across systems and HPC infrastructures. It does this by creating minimal containers that are defined by a specfile and files from the host system are used to build the container. The resulting container can then be launched by any Linux computer with Singularity installed regardless if the programs inside the container are present on the target system, or if they are a different version, or even incompatible versions. Singularity achieves extreme portability without sacrificing usability thus solving the need of mobility of compute. Singularity containers can be executed within a normal/standard command line process flow.", + "laborHours": 0.0, + "languages": [ + "ANY C COMPLIER" + ], + "name": "Singularity v1.x", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpcng/singularity", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "These Drupal Modules extend the functionality of Drupal by including specific styles for dates and tabs, publishing options for scheduled and immediate publication of content modes, field visibility in content forms, keyword block filters (taxonomy based), adding content nodes to a specified queue for display in views, and status display of workflow settings.", + "laborHours": 0.0, + "languages": [ + "PHP (99%)", + "JavaScript (1%)" + ], + "name": "Drupal Contributed Modules", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.drupalcode.org/project/field_visibility", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Analysis scripts for data from the NDCX-II experiment.", + "laborHours": 0.0, + "languages": [], + "name": "NDCX-II Python Module", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/berkeleylab/atap-ndcxii-python/src/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/atap-ndcxii-python", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "WARNO is a software system designed to monitor the radars in the ARM Radar Network. It allows real time monitoring and tracking of instrument state and condition. It provides a web portal on the front end to interact with users, a REST API webpoint for interactions with third party systems, and an internal distributed architecture to allow it to be deployed at multiple sites.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Watchdog for ARM Radar Network Operations", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ARM-DOE/warno/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/warno", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "GRIDDER is a simple interactive grid generation tool for creating orthogonal, 2D quadrilateral or 3D hexahedral grids. Grid spacing can be even, logarithmic, or geometric. Gridder creates orthogonal one-dimensional, two-dimensional, or three- dimensional grids. Each dimension can have multiple regions, each with different nodal spacing. This spacing can be equal spacing, geometric spacing, or logarithmic spacing. The resulting grid can be output in AVS (Advanced Visualization Systems) format, Tracer 30, Vectors, or FEHM format. Coordinate and connectivity data are output for AVS, but only coordinate data is output for Tracer30. As it runs, Gridder prompts the user for input such as number of dimensions, number of regions in each dimension, coordinates of region borders, number of divisions in each region, spacing specifications of each region, and output format. The Gridder can also accept the necessary information from a file, bypassing the interactive interface. Every time the interactive interface is used, the input parameters are saved to a file so that the same grid can be regenerated from that file.", + "laborHours": 0.0, + "languages": [ + "c", + "gcc version 4.8.2" + ], + "name": "Gridder, Version 3", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/gridder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "SEDS is an economy-wide energy model of the U.S. The model captures dynamics between supply, demand, and pricing of the major energy types consumed and produced within the U.S. These dynamics are captured by including: the effects of macroeconomics; the resources and costs of primary energy types such as oil, natural gas, coal, and biomass; the conversion of primary fuels into energy products like petroleum products, electricity, biofuels, and hydrogen; and lastly the end- use consumption attributable to residential and commercial buildings, light and heavy transportation, and industry. Projections from SEDS extend to the year 2050 by one-year time steps and are generally projected at the national level. SEDS differs from other economy-wide energy models in that it explicitly accounts for uncertainty in technology, markets, and policy. SEDS has been specifically developed to avoid the computational burden, and sometimes fruitless labor, that comes from modeling significantly low-level details. Instead, SEDS focuses on the major drivers within the energy economy and evaluates the impact of uncertainty around those drivers.", + "homepageURL": "https://www.nrel.gov/analysis/seds", + "laborHours": 0.0, + "languages": [ + "Ruby" + ], + "name": "Stochastic Energy Deployment System", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/analysis/seds/download-model.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/analysis/seds", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Generates data for the associated paper and its supplementary data table, which are sets of residues and poles that define rational functions to approximate the Fermi-Dirac distribution.", + "laborHours": 440.8, + "languages": [ + "C" + ], + "name": "Companion software to: Minimax Rational Approximation of the Fermi-Dirac Distribution v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fermi-rational-approximation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "This algorithm processes high-rate 3-phase signals to identify the start time of each signal and estimate its envelope as data features. The start time and magnitude of each signal during the steady state is also extracted. The features can be used to detect abnormal signals. This algorithm is developed to analyze Exxeno's 3-phase voltage and current data recorded from refrigeration systems to detect device failure or degradation.", + "homepageURL": "https://store.pnnl.gov/content/data-feature-extraction-high-rate-3-phase-data", + "laborHours": 0.0, + "languages": [ + "Algorithm" + ], + "name": "Data Feature Extraction for High-Rate 3-Phase Data", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/data-feature-extraction-high-rate-3-phase-data", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "A trans-active energy micro-grid controller is implemented in the VOLTTRON distributed control platform. The system uses the price of electricity as the mechanism for conducting transactions that are used to manage energy use and to balance supply and demand. In order to allow testing and analysis of the control system, the implementation is designed to run completely as a software simulation, while allowing the inclusion of selected hardware that physically manages power. Equipment to be integrated with the micro-grid controller must have an IP (Internet Protocol)-based network connection and a software \"driver\" must exist to translate data communications between the device and the controller.", + "laborHours": 0.0, + "languages": [ + "NA" + ], + "name": "Price Based Local Power Distribution Management System (Local Power Distribution Manager) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LBNL-ETA/LPDM/blob/CBERD/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/LPDM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The PeakWorks software is designed to assist in the quantitative analysis of atom probe tomography (APT) generated mass spectra. Specifically, through an interactive user interface, mass peaks can be identified automatically (defined by a threshold) and/or identified manually. The software then provides a means to assign specific elemental isotopes (including more than one) to each peak. The software also provides a means for the user to choose background subtraction of each peak based on background fitting functions, the choice of which is left to the users discretion. Peak ranging (the mass range over which peaks are integrated) is also automated allowing the user to chose a quantitative range (e.g. full-widthhalf- maximum). The software then integrates all identified peaks, providing a background-subtracted composition, which also includes the deconvolution of peaks (i.e. those peaks that happen to have overlapping isotopic masses). The software is also able to output a 'range file' that can be used in other software packages, such as within IVAS. A range file lists the peak identities, the mass range of each identified peak, and a color code for the peak. The software is also able to generate 'dummy' peak ranges within an outputted range file that can be used within IVAS to provide a means for background subtracted proximity histogram analysis.", + "homepageURL": "https://store.pnnl.gov/content/peakworks", + "laborHours": 0.0, + "languages": [ + "MatLab" + ], + "name": "PeakWorks", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/peakworks", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "FermiLib is an open source software package designed to facilitate the development and testing of algorithms for simulations of fermionic systems on quantum computers. Fermionic simulations represent an important application of early quantum devices with a lot of potential high value targets, such as quantum chemistry for the development of new catalysts. This software strives to provide a link between the required domain expertise in specific fermionic applications and quantum computing to enable more users to directly interface with, and develop for, these applications. It is an extensible Python library designed to interface with the high performance quantum simulator, ProjectQ, as well as application specific software such as PSI4 from the domain of quantum chemistry. Such software is key to enabling effective user facilities in quantum computation research.", + "laborHours": 0.0, + "languages": [ + "PYTHON 2.7" + ], + "name": "FermiLib v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ProjectQ-Framework/FermiLib", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Screamer is a special purpose circuit code developed for the design of Pulsed Power systems. It models electrical circuits which have a restricted topology in order to provide a fast-running tool while still allowing configurations general enough for most Pulsed Power system designs", + "laborHours": 0.0, + "languages": [ + "Fortran and C++" + ], + "name": "Screamer version 4.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/screamer", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "4.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "A parallelization of the k-means++ seed selection algorithm on three distinct hardware platforms: GPU, multicore CPU, and multithreaded architecture. K-means++ was developed by David Arthur and Sergei Vassilvitskii in 2007 as an extension of the k-means data clustering technique. These algorithms allow people to cluster multidimensional data, by attempting to minimize the mean distance of data points within a cluster. K-means++ improved upon traditional k-means by using a more intelligent approach to selecting the initial seeds for the clustering process. While k-means++ has become a popular alternative to traditional k-means clustering, little work has been done to parallelize this technique. We have developed original C++ code for parallelizing the algorithm on three unique hardware architectures: GPU using NVidia's CUDA/Thrust framework, multicore CPU using OpenMP, and the Cray XMT multithreaded architecture. By parallelizing the process for these platforms, we are able to perform k-means++ clustering much more quickly than it could be done before.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel k-means++", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/patrickmackey/parallel_kpp/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/patrickmackey/parallel_kpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "A software library for parsing and manipulating frequency-domain data files that have been processed using the Bruker TopSpin NMR software package. In the context of NMR, the term \"processed\" indicates that the end-user of the Bruker TopSpin NMR software package has (a) Fourier transformed the raw, time-domain data (the Free Induction Decay) into the frequency-domain and (b) has extracted the list of NMR peaks.", + "laborHours": 0.0, + "languages": [ + "Ruby" + ], + "name": "Software Library for Bruker TopSpin NMR Data Files", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/EMSL-NMR-EPR/Ruby-Bruker-TopSpin-Library/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-NMR-EPR/Ruby-Bruker-TopSpin-Library", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "A machine learning based approach is developed to detect events that have rarely been seen in the historical data. The data can include building energy consumption, sensor data, environmental data and any data that may affect the building's energy consumption. The algorithm is a modified nonlinear Bayesian support vector machine, which examines daily energy consumption profile, detect the days with abnormal events, and diagnose the cause of the events.", + "homepageURL": "https://store.pnnl.gov/content/bayesian-support-vector-machine-bsvm", + "laborHours": 0.0, + "languages": [ + "Matlab R2014a" + ], + "name": "Bayesian Support Vector Machine (BSVM)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/bayesian-support-vector-machine-bsvm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The BSEPACK contains a set of subroutines for solving the Bethe-Salpeter Eigenvalue (BSE) problem. This type of problem arises in this study of optical excitation of nanoscale materials. The BSE problem is a structured non-Hermitian eigenvalue problem. The BSEPACK software can be used to compute all or subset of eigenpairs of a BSE Hamiltonian. It can also be used to compute the optical absorption spectrum without computing BSE eigenvalues and eigenvectors explicitly. The package makes use of the ScaLAPACK, LAPACK and BLAS.", + "homepageURL": "https://sites.google.com/a/lbl.gov/bsepack", + "laborHours": 0.0, + "languages": [ + "FORTRAN" + ], + "name": "Bethe-Salpeter Eigenvalue Solver Package (BSEPACK) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sites.google.com/a/lbl.gov/bsepack/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sites.google.com/a/lbl.gov/bsepack", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Sparx, a new environment for Cryo-EM image processing; Cryo-EM, Single particle reconstruction, principal component analysis; Hardware Req.: PC, MAC, Supercomputer, Mainframe, Multiplatform, Workstation. Software Req.: operating system is Unix; Compiler C++; type of files: source code, object library, executable modules, compilation instructions; sample problem input data. Location/transmission: http://sparx-em.org; User manual & paper: http://sparx-em.org;", + "homepageURL": "http://sparx-em.org", + "laborHours": 0.0, + "languages": [], + "name": "Sparx PCA Module", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://sparx-em.org/sparxwiki/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://sparx-em.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Tigres provides a programming library to compose and execute large-scale data-intensive scientific workflows from desktops to supercomputers. DOE User Facilities and large science collaborations are increasingly generating large enough data sets that it is no longer practical to download them to a desktop to operate on them. They are instead stored at centralized compute and storage resources such as high performance computing (HPC) centers. Analysis of this data requires an ability to run on these facilities, but with current technologies, scaling an analysis to an HPC center and to a large data set is difficult even for experts. Tigres is addressing the challenge of enabling collaborative analysis of DOE Science data through a new concept of reusable \"templates\" that enable scientists to easily compose, run and manage collaborative computational tasks. These templates define common computation patterns used in analyzing a data set.", + "homepageURL": "http://tigres.lbl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Template Interfaces for Agile Parallel Data-Intensive Science", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://dst.lbl.gov/ACSSoftware/tigres/docs/tigres-0.2.0/license_agreement.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://tigres.lbl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Demeter is a fully extensible, community-based land use land cover (LULC) downscaling and change detection model that allows for customization and/or additions from its user base.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Demeter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/demeter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2023-03-15" + }, + "description": "MASTODON has the capability to model stochastic nonlinear soil-structure interaction (NLSSI) in a dynamic probabilistic risk assessment framework. The NLSSI simulations include structural dynamics, time integration, dynamic porous media flow, nonlinear hysteretic soil constitutive models, geometric nonlinearities (gapping, sliding, and uplift). MASTODON is also the MOOSE based master application for dynamic PRA of external hazards.", + "laborHours": 28287.2, + "languages": [ + "C++" + ], + "name": "Mastodon", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/mastodon", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "Revision 1.0" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Problem Solved: A novel technique for regression and sensitivity analysis of C1 function f problematic input dimension given observations (x_i, f(x_i), f'(x_i)). Solution Provided by the Code: Active Manifolds reduces the problem to analysis/regression of a 1 dimensional analogue by exploiting geometric properties of the function.", + "laborHours": 0.0, + "languages": [ + "Python 2.7" + ], + "name": "Active Manifolds ICML 2019 Paper Results Code", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/bridgesra/active-manifold-icml2019-code", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bridgesra/active-manifold-icml2019-code", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-04-17", + "metadataLastUpdated": "2021-06-15" + }, + "description": "The FasTensor implements the native array data programming mode namely SLOPE for modern data analysis tasks. It is designed to work in parallel on supercomputer and can handle terabyte data analysis tasks. It is thousand times faster than other data analysis systems such as Apache Spark and 38% faster than TensorFlow in dealing with large scale scientific data analysis. It has wide applications in image data analysis and mesh data analysis tasks in physical simulations and other fields.", + "laborHours": 0.0, + "languages": [], + "name": "FasTensor (FT) v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/fastensor/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-04-18", + "metadataLastUpdated": "2024-07-01" + }, + "description": "The Records API (application program interface) for Advanced Energy System Design (AESD) enables software that serves multidimensional record-oriented data to interoperate with software than uses such data. In the context of the Records API, multidimensional data records are simply tuples of real numbers, integers, and character strings, where each data value is tagged by a variable name, according to a pre-defined schema, and each record is assigned a unique integer identifier. Conceptually, these records are isomorphic to rows in a relational database, JSON objects, or key-value maps. Records servers might supply static datasets, sensor measurements that periodically update as new telemetry become available, or the results of simulations as the simulations generate new output. Records client software might display or analyze the data, but in the case of simulations the client request the creation of new ensembles for specified input parameters. It is also possible to chain records clients and servers together so that a client consuming data from a server might transform that data and serve it to additional clients. This minimalist API avoids imposing burdensome metadata, structural, or implementation requirements on developers by relying on open-source technologies that are readily available for common programming languages. In particular, the API has been designed to place the least possible burden on services that provide data. This document defines the message format for the Records API, a transport mechanism for communicating the data, and the semantics for interpreting it. The message format is specified as Google Protocol Buffers and the transport mechanism uses WebSockets. We discuss three major use cases for serving and consuming records data: (i) static data, (ii) dynamically augmented data, (iii) on-demand simulations, (iv) with filters, and (v) with bookmarks. Separate implementations of the API exist in C++, Haskell, JavaScript, Python, and R.", + "laborHours": 0.0, + "languages": [], + "name": "AESD (Advanced Energy System Design) Records API [SWRs-17-50, 17-51, 17-52]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/AESD/blob/master/libs/Haskell/records/LICENSE", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/AESD", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-04-18", + "metadataLastUpdated": "2021-04-18" + }, + "description": "The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an open-source tool for visualizing variable renewable resource forecasts and ramp alerts for significant up/down ramps in renewable resource and the consequent net-load. The modular dashboard of RAVIS contains configurable panes for viewing- probabilistic time series forecasts, ramp event alerts on the look-ahead timeline, spatially resolved resource sites and forecasts, and system simulation and market clearing data such as transmission lines utilization, nodal prices and available generation flexibility.", + "laborHours": 0.0, + "languages": [ + "JavaScript" + ], + "name": "Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ravis-nrel/ravis", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-04-19", + "metadataLastUpdated": "2024-07-01" + }, + "description": "The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "Fast All-sky Radiation Model for Solar applications (FARMS) [SWR-16-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/farms", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "charles.tripp@nrel.gov" + }, + "date": { + "created": "2021-04-20", + "metadataLastUpdated": "2021-04-26" + }, + "description": "KRoad is a 2-dimensional, lightweight, vehicle driver simulator that uses 3-dimensional vehicle driving model considerations, i.e. state-of-the-art friction models, and enables the driver to make control decisions with less computation time and programmer effort required than is with full-fidelity 3d simulators. KRoad is fully compatible with OpenAI gym, and contains a factored gym framework for composing gyms from various components (process, reward function, observation function, termination conditions, etc.). KRoad is additionally compatible with the RLlib distributed reinforcement learning environment, running under the Ray distributed python framework.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "K_Road (KRoad)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/K_Road", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-21", + "metadataLastUpdated": "2021-04-21" + }, + "description": "ArQTiC is a domain-specific full-stack software package built for the dynamic simulations of materials on quantum computers. Its main contributions include providing a software library for high-level programming of such simulations on quantum computers, and providing post-processing capabilities that allow users to more efficiently analyze results from the quantum computer. Paired with the power to optimize and execute quantum circuits, ArQTiC opens the field of dynamic materials simulations on quantum computers to a broader community of scientists from a wider range of domain sciences, paving the way for accelerated progress towards physical quantum supremacy.", + "laborHours": 0.0, + "languages": [], + "name": "Architecture for Quantum Time-dependent Circuits (ArQTIC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lebassman/ArQTiC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-21", + "metadataLastUpdated": "2021-04-21" + }, + "description": "H5bench benchmark suite contains a list of applications that are used to measure the HDF5 I/O performance from various aspects.", + "laborHours": 0.0, + "languages": [], + "name": "H5bench: a benchmark suite for parallel HDF5 (H5bench) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/h5bench", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-21", + "metadataLastUpdated": "2021-04-21" + }, + "description": "the Xilinx tools relay on a component on the board (FTDI chip) to have a small memory from a particular manufacturer (Digilent) to serve as a bridge to the FPGA. What the software we're requesting to release simply does is to run between the Xilinx tools (one of them is called Vivado but there are others) and our boards so that we don't need that memory on our boards. The protocol the software uses to communicate with the Xilinx tools is called XVC (Xilinx Virtual Cable). This server code runs on the computer that is physically connected to the FPGA board, but the Xilinx tools that communicate with it can run either on that computer or some other computer connected to it over the network, this is where the network component comes into play.", + "laborHours": 0.0, + "languages": [], + "name": "XVC FTDI JTAG v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/XVC-FTDI-JTAG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Ruleset Checking Tool (RCT) will be a tool for verifying implementation of a ruleset (such as ASHRAE Standard 90.1 Appendix G) in building performance modeling (BPM) tools.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/ruleset-checking-tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ruleset-checking-tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "npablant@pppl.gov" + }, + "date": { + "created": "2021-04-22", + "metadataLastUpdated": "2021-04-22" + }, + "description": "XICSRT is a general purpose, photon based, raytracing code intended for both optical and x-ray raytracing.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "xicsrt", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PrincetonUniversity/xicsrt", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-22", + "metadataLastUpdated": "2021-04-22" + }, + "description": "This python package pulls hourly weather information from the NCEI server, cleans the data and prepares it for use with LBNL's M&V2.0 tools.", + "laborHours": 0.0, + "languages": [], + "name": "NOAA Weather Data Scraper", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/NWDS", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-22", + "metadataLastUpdated": "2021-04-22" + }, + "description": "This software package is a set of Python-based tools for forecasting future time series of electrical power demand for a granular set of customer types in California, based on historical data on individual customers' demand, combined with aggregate forecasts of demand growth.", + "homepageURL": "https://buildings.lbl.gov/download-phase-3-dr-potential-study", + "laborHours": 0.0, + "languages": [], + "name": "LBNL-Load", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://buildings.lbl.gov/download-phase-3-dr-potential-study", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-22", + "metadataLastUpdated": "2021-04-22" + }, + "description": "The neural network constructed of 3D convolutional and fully connected layers was trained on the simulated mass distribution of the Universe with the purpose to recover the values of cosmological parameters used to generate the Universe.", + "laborHours": 0.0, + "languages": [], + "name": "Regression of 3D Sky Map to Cosmological Parameters (CosmoFlow) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/balewski/cosmoflow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Toolkit to implement and explore transfer learning-based strategies to address unsatisfactory accuracy of models for estimating building energy consumption when available field data for training is sparse or of unacceptable quality", + "laborHours": 0.0, + "languages": [], + "name": "transBEAM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jainmilan/transBEAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-04-23", + "metadataLastUpdated": "2021-06-15" + }, + "description": "The Empirical Roofline Tool (ERT) empirically determines the machine characteristics (CPU or GPU-accelerated) that are needed to generate the machine characteristics for the roofline model.", + "laborHours": 0.0, + "languages": [], + "name": "Empirical Roofline Tool (ERT) v1.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/cs-roofline-toolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "version": "v1.1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-04-23", + "metadataLastUpdated": "2021-04-23" + }, + "description": "Deep learning tools for enhancing the spatial resolution of wind data. The software is developed in Python using the TensorFlow deep learning package. Models for diversity super-resolution is provided. Included in the package are pretrained models with example code/data to perform the super-resolution as well as tools of training models for different enhancement- or data-types. The super-resolution is an inherently ill-conditioned problem, with multiple high-resolution fields plausibly mapping to the same coarse field. Considitional GANs provide a framework for generating a distribution of high-resolution realizations from a given low-resolution input. Stochastic estimation is used to inform the network of the expected degree and location of sub-grid diversity. The package includes a pretrained network to generate distributions of 10x-enhanced fields of wind data.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Diverse Super-Resolution (diversity_SR)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/diversity_SR", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-04-25", + "metadataLastUpdated": "2021-06-15" + }, + "description": "A general framework to extract topological information (via topological data analysis) from some type of point cloud data, to be used in downstream machine learning tasks.", + "laborHours": 0.0, + "languages": [], + "name": "molecule-tda v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/a1k12/molecule-tda", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-29", + "metadataLastUpdated": "2021-07-14" + }, + "description": "Pseudo random number generators (PRNGs) are crucial for nu- merous applications in HPC ranging from molecular dynamics to quantum chemistry, and hydrodynamics. Our optimized implementation generates the same random number sequence as the original well-characterized MRG8. MRG8-AVX512 achieves a substantial 69% improvement compared to Intel's MKL, and MRG8-GPU shows a maximum 3.36x speedup compared to NVIDIA's cuRAND library.", + "laborHours": 0.0, + "languages": [], + "name": "MRG8 Random Number Generator Library (MRG8) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kenmiura/mrg8", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-29", + "metadataLastUpdated": "2021-04-29" + }, + "description": "Metabolomics, or the identification and cataloging of biologically relevant compounds, is required for the dynamic study of living systems. Plants, for instance, have thousands of compounds which may vary by tissue compartment, life cycle status, weather, soil and water. Even with the most advanced chemical detection systems at our disposal, the identification of metabolites is an exhaustive exercise and filled with uncertainty. What is different about LBNL #2019-106 is the use of machine learning and chemical spectra to add specificity to the provisional identification of a chemical species; e.g., chromatographic retention or the fragmentation spectrum of a selected ion. However, even under the best of circumstances, the provisional identification is associated with a very high level of uncertainty unless and until it is cross-referenced to similar compounds and other deductive approaches. Here, the inventors introduce a machine-learning which promises to enhance the productivity of post-mass spectrometry assessment.", + "laborHours": 0.0, + "languages": [], + "name": "spectral processing (spectral_processing) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biorack/simile", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-29", + "metadataLastUpdated": "2021-04-29" + }, + "description": "A predictive, stable, and interpretable machine learning tool: the iterative random forest algorithm (iRF). iRF discovers high-order interactions among variables with the same order of computational cost as random forests (RF). We have demonstrated the utility of iRF in several applications in the biological and environmental sciences. It is a general purpose machine learning framework for building \"explainable\" predictive engines.", + "laborHours": 0.0, + "languages": [], + "name": "iRF v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/karlkumbier/iRF2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vchendrix@lbl.gov" + }, + "date": { + "created": "2021-04-29", + "metadataLastUpdated": "2021-06-17" + }, + "description": "BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets) uses a data brokering approach to synthesize diverse earth science data from a variety of remote sources in real-time without the need for additional storage. BASIN-3D is an extendable Python application using a generalized data synthesis model that makes the synthesized data available via Application Programming Interface (API). We have currently implemented our data synthesis model to represent sensor-based time series earth science observations across a hierarchy of spatial locations. Supporting our data synthesis model is a plugin framework that allows developers to map data sources of interest to the BASIN-3D synthesis model.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets (basin3d)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/BASIN-3D/basin3d", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-05-02", + "metadataLastUpdated": "2021-06-15" + }, + "description": "The software is a python module that makes it easy to create reusable interfaces to control common hardware used in experiments.", + "laborHours": 0.0, + "languages": [], + "name": "Hardware-control v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/hardware-control", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-05-02", + "metadataLastUpdated": "2021-06-15" + }, + "description": "A pipeline to estimate the limits of detection and resolution of transcription factor encoded biosensors", + "laborHours": 0.0, + "languages": [], + "name": "Monte Carlo Markov Chain Biosensor Analysis (MCMCBA) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/biosensor_characterization_public", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-04", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Molecular dynamics simulations often rely on parameterized atomistic potentials, which can be inaccurate compared to ab initio simulation methods. However, dynamic ab initio simulations come with high computational cost. Deep learning techniques offer a method to obtain both high accuracy and low cost predictions of dynamics. Our method gives a prediction of the structural dynamics of a molecule accounting for the prior dynamics, giving high-accuracy predictions at low computational cost", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/mol_dgnn", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mol_dgnn", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-04", + "metadataLastUpdated": "2021-05-05" + }, + "description": "SAND2021-4824 O mapdfn.py takes the output of dfnWorks describing a discrete fracture network (DFN) and converts the DFN to an equivalent porous medium representation. This is done by looping through cells in a 3-D model domain, tagging those intersected by fractures, and calculating effective properties. Coordinate transformations are imported from an open source script (transformations.py) developed at the University of California. An associated driver script, mapdfn2pflotran.py, calls the functions in mapdfn.py and writes the mapdfn.py output to hdf5 files for use with PFLOTRAN. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-4824 O", + "laborHours": 0.0, + "languages": [ + "Python3" + ], + "name": "Mapdfn.py", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/pflotran/mapdfn/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-05-06", + "metadataLastUpdated": "2021-06-15" + }, + "description": "We have developed a simple, minimally invasive monitoring framework that enables us to capture key metrics from Python user processes. This is part of a larger effort to collect data across our entire data-intensive science workload at NERSC. The approach for Python is inspired by a similar framework developed for Blue Waters at NCSA. Both frameworks leverage standard Python features, sitecustomize and atexit, to capture Python imports of interest and other job data. The customs package decomposes the information capture into separate inspection and reporting interfaces.", + "laborHours": 0.0, + "languages": [], + "name": "Customs: Inspect and Report Python Imports (customs) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/customs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v1" + }, + { + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-05-09", + "metadataLastUpdated": "2021-06-15" + }, + "description": "The Adapter Python IO software, in short Adapter or the Adapter software, encapsulates certain Python IO capabilities used for loading in and writing out data when performing analytical Python code runs. 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TOGA uses an approach based on the Peng-Robinson equation of state (PR-EOS) to calculate the thermophysical properties of the gas and oil phases including the gas/oil components dissolved in the aqueous phase, and uses a mixing model to estimate the thermophysical properties of the aqueous phase.", + "homepageURL": "https://tough.lbl.gov/licensing-download/tough-related-codes-licensing-download", + "laborHours": 0.0, + "languages": [], + "name": "TOGA: A TOUGH code for modeling three-phase, multi-component, and non-isothermal processes involved in CO2-based Enhanced Oil Recovery (TOGA) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://marketplace.lbl.gov/search?q=toga", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://tough.lbl.gov/licensing-download/tough-related-codes-licensing-download", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-13", + "metadataLastUpdated": "2021-06-28" + }, + "description": "The MAPIT - Material Accountancy Performance Indicator Toolkit includes statistical tests and calculations based on open literature that calculate safeguards metrics. 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Currently the Nettest framework incorporates lperf-vl.2, a simple ping type test, and a tuned TCP test that uses a given required throughput and ping results to determine the round trip time to set a buffer size (based on the delay bandwidth product) and then performs an iperf TCP throughput test. Additional network test tools can be integrated into the Nettest framework in the future.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Net Test", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "This software provides a framework for building application layter overlay networks. It includes example overlays that can be used without modification. Also provided are example multicast and routing protocols that can be used with the overlays.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Generic Overlay Framework", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "We are developing a peer-to-peer system to support secure, location independent information sharing in the scientific community. Once complete, this system will allow seamless and secure sharing of information between multiple collaborators. The owners of information will be able to control how the information is stored, managed, and shared. In addition, users will have faster access to information updates within a collaboration. Groups collaborating on scientific experiments have a need to share information and data. This information and data is often represented in the form of files and database entries. In a typical scientific collaboration, there are many different locations where data would naturally be stored. This makes It difficult for collaborators to find and access the information they need. Our goal is to create a lightweight file-sharing system that makes it easy for collaborators to find and use the data they need. This system must be easy-to-use, easy-to-administer, and secure. Our information-sharing tool uses group communication, in particular the InterGroup protocols, to reliably deliver each query to all of the current participants in a scalable manner, without having to discover all of their identities. We will use the Secure Group Layer (SGL) and Akenti to provide security to the participants of our environment, SGL will provide confidentiality, integrity, authenticity, and authorization enforcement for the InterGroup protocols and Akenti will provide access control to other resources.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Java 1.4 or higher" + ], + "name": "Secure Information Sharing", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "This toolkit supports component-level model-based fault detection methods in commercial building HVAC systems. The toolbox consists of five basic modules: a parameter estimator for model calibration, a preprocessor, an AHU model simulator, a steady-state detector, and a comparator. Each of these modules and the fuzzy logic rules for fault diagnosis are described in detail. The toolbox is written in C++ and also invokes the SPARK simulation program.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "HVAC Fault Detection and Diagnosis Toolkit", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "The Beowulf Distributed process Space (Bproc) software stack is comprised of UNIX/Linux kernel modifications and a support library by which a cluster of machines, each running their own private kernel, can present itself as a unified process space to the user. A Bproc cluster contains a single front-end machine and many back-end nodes which receive and run processes given to them by the front-end. Any process which is migrated to a back-end node is also visible as a ghost process on the fron-end, and may be controlled there using traditional UNIX semantics (e.g. ps(1), kill(1), etc). This software is a Perl extension to the Bproc library which enables the Perl programmer to make direct calls to functions within the Bproc library. See http://www.clustermatic.org, http://bproc.sourceforge.net, and http://www.perl.org", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "gcc or equivalent ANSI C compiler." + ], + "name": "Perl Extension to the Bproc Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "Bag is a miniature pcap filter which takes pcap input (or input off the wire) using a bpf filter, if specified, and then writes the output to stdout or a file (in pcap format). It depends for some aspects of its functionality on a libpcap library which uses a shared memory packet capture ring bugger. There are two build in modules: chcksum and session. the build in chcksum modules is used to anonymize the ip addresses and repair any checksums in the stream. % bag -r /tmp/*.pcap -Cchucksum, 128.1 65: 10.10 The session module generates sessions which are defined as a series of packets that have two things in common. the first is a unique five-tuple composed oi an IP protocol, IP source address, IP source port, IP destination address, and IP destination port. The second is that if the originating packet is associated with a bi-directional service such as ftpltcp, characteristics and data will be kept for both flows involved with the service. The only protocols evaluated beyond the IP header are ICMP, TCP and UDP. A session can last for as long as bag is running. However, under normal conditions, sessions are generated every time they appear to have closed down. There is a man page included with the distribution which goes into more detail.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [], + "name": "BAG (Continuous Round Robin Packet Capture)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "GROK is web based Internet Protocol (IP) search tool designed to help the user find and analyze network sessions in close to real time (5 minute). It relies on the output generated by a packet capture and session summary tool called BAG. The bag program runs on a linux system, and continuously generates 5 minute full packet capture ILIBPCAP files, Internet session summary files, and interface statistic files, round-robin, over a period limited to the amount of disc storage available to the system. In the LANL case, an 8 terabyte file system accommodates seven days of data (most of the time). Summary information, such as top 20 outgoing and incoming network services (such as www/tcp or 161/udp) along with network interface statistics which indicate the health of the capture system are plotted every 5 minutes for display by the GROK web server. The grok home page presents the analyst with a set of search criteria used to query the information being collected by the bag program. Since the information ultimately resides in \"pcap\" files, other pcap aware programs such as bro ethereal, nosehair, smacqq, snort, and tcpdump have been incorporated into groks web interface. Clickable documentation is available for each search criteria.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [], + "name": "GROK", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "INET's was developed in the 80's when the Internet was in it's infancy and various vendors were attempting to get into the ball game with half baked code that indicated a lack of understanding about basic IP standards in the area of IP and ICMP. Various test applications were written to test conformance to the early Internet RFC's especially ICMP. The INET program allows the user to exercise various minor internet services provided by a specified service host. See the DDN Protocol Handbook, Volume Two, Section 8 for a detailed description of various minor applications which one might attempt to exercise. The unix network daemon \"inetd\" was the inspiration for the name \"inet\". A simple C library generated at the time was recently used to build a program called 'dp' shich GROK uses to transfer BAG session information to some backend data collector such as DISARM (LA-CC number 05-D47)", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "gcc 3.2.3 through gcc 4.0.3" + ], + "name": "inet", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "PMI is a XML framework for formulating tests of software and software environments which operate in a relatively push button manner, i.e., can be automated, and that provide results that are readily consumable/publishable via RSS. Insofar as possible the tests are carried out in manner congruent with real usage. PMI drives shell scripts via a perl program which is charge of timing, validating each test, and controlling the flow through sets of tests. Testing in PMI is built up hierarchically. A suite of tests may start by testing basic functionalities (file system is writable, compiler is found and functions, shell environment behaves as expected, etc.) and work up to large more complicated activities (execution of parallel code, file transfers, etc.) At each step in this hierarchy a failure leads to generation of a text message or RSS that can be tagged as to who should be notified of the failure. There are two functionalities that PMI has been directed at. 1) regular and automated testing of multi user environments and 2) version-wise testing of new software releases prior to their deployment in a production mode.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "C, Fortran" + ], + "name": "Production Maintenance Infrastructure", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-24" + }, + "description": "ChISELS is used for the theoretical modeling of detailed surface chemistry and consomitant surface evolutions occurring during microsystem fabrication processes conducted at low pressures. Examples include physical vapor deposition (PVD), low pressure chemical vapor deposition (PECVD), and plasma etching. Evolving interfaces are represented using the level-set method and the evolution equations time integrated using a Semi-Lagrangian approach. A Ballistic transport model is employed to solve for the fluxes incident on each of the surface elements. Surface chemistry leading to etching or deposition is computed by either coupling to Surface Chemkin (a commercially available code) or by providing user defined subroutines. The computational meshes used are quad-trees (2-D) and oct-trees (3-D), constructed such that grid refinement is localized to regions near the surface interfaces. As the interface evolves, the mesh is dynamically reconstructed as needed for the grid to remain fine only around the interface. For parallel computation, a domain decomposition scheme with dynamic load balancing is used to distribute the computational work across processors.", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Chemically Induced Surface Evolutions with Level Sets", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/chisels", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The Terascale Simulation Tools and Technologies (TSTT) center is a collaboration between several universities and DOE laboratories, and is funded by the DOE Scientific Discovery for Advanced Computing (SciDAC) program. The primary objective of the (TSTT) center is to develop technologies that enable application scientists to easily use multiple mesh and discretization strageties within a single simulation on terascale computers. This is accomplished through the development of common functional interfaces to geometry, mesh, and other simulation data. This package is Sandia's implementation of these interfaces.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Terascale Simulation Tolls and Technologies", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The purpose of the Aggregate Remote Memory Copy (ARMCI) library is to provide a general- purpose, efficient, and Widely portable remote memory access (RMA) operations (one-sided communication) optimized for Contiguous and noncontiguous (strided, scatter/gather, I/O vector) data transfers. In addition, ARMCI includes a set of atomic and mutual exclusion operations. The development ARMCI is driven by the need to support the global-address space communication model in context of distributed regular or irregular distributed data structures, communication libraries, and compilers. ARMCI is a standalone system that could be used to support user-level libraries and applications that use MPI or PVM.", + "homepageURL": "https://hpc.pnl.gov/armci", + "laborHours": 0.0, + "languages": [], + "name": "Aggregate Remote Memory Copy Interface", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://hpc.pnl.gov/armci", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://hpc.pnl.gov/armci", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "Self-Configuring Network Monitor (SCNM) is a passive monitoring that can collect packet headers from any point in a network path. SCNM uses special activation packets to automatically activate monitors deployed at the layer three ingress and egress routers of the wide-area network, and at critical points within the site networks. Monitoring output data is sent back to the application data source or destination host. No modifications are required to the application or network routing infrastructure in order to activate monitoring of traffic for an application. This ensures that the monitoring operation does not add a burden to the networks administrator.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Self-Configuring Network Monitor", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "Visapult is software pipeline of two components, a backend and viewer, used to perform pipelined and distributed memory parallel, Image Based Rendering assisted volume rendering of 3D scalar data on structured rectilinear grids. Visapult implements a two-stage volume rendering pipeline using two software components called the \"backend\" and the \"viewer.\" The backend reads 3D scientific data from some source in a domain-decomposed fashion, and performs software volume rendering on each block of data. Results, which consist of six images per block (representing the six primary view axes) are transmitted over parallel sockets to the viewer. The viewer receives each block's worth of data, constructs an internal scene graph, and presents the resulting rendering to the human viewer. The human user can interactively transform the 3D model to obtain a view from any angle. Whereas full-resolution volume rendering is extremely computer and bandwidth intensive, the Visapult architecture is designed to perform the most demanding part of volume rendering on a parallel computer. Yet, the viewer maintains interactive rendering rates independent of the size of the original volume, and independent of network bandwidth.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "C and C++" + ], + "name": "VISAPULT", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "This program tests distributed filesystems using small files for lock and metadata contention. It is useful for debugging.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Distributed File System Test Using Small FilesV1.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "Procdn is a collection of software that provides support in the Linux kernel for Globus distinguished name (DNs). The primary component is a Linux kernel module that creates data structures in the kernel for associating DNs with user processes. The other components included with the software help initiate this mapping in the kernel, including patches for the Flobus toolkit and a sample implementation for various batch scheduler systems. In addition, the software includes some utilities for listing current mappings in the kernel.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "PROCDN", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The NetLogger Toolkit is designed to monitor, under actual operating conditions, the behavior of all the elements of the application-to-application communication path in order to determine exactly where time is spent within a complex system. Using NetLogger, distributed application components are modified to produce timestamped logs of \"interesting\" events at all the critical points of the distributed system. Events from each component are correlated, which allows one to characterize the performance of all aspects of the system and network in detail. The NetLogger Toolkit itself consists of four components an API and library of functions to simplify the generation of application-level event logs, a set of tools for collecting and sorting log files, an event archive system, and a tool for visualization and analysis of the log files. In order to instrument an application to produce event logs, the application developer inserts calls to the NetLogger API at all the critical points in the code, then links the application with the NetLogger library. All the tools in the NetLogger Toolkit share a common log format, and assume the existence of accurate and synchronized system clocks. NetLogger messages can be logged using an easy-to-read text based format based on the lETF-proposed ULM format, or a binary format that can still be used through the same API but that is several times faster and smaller, with performance comparable or better than binary message formats such as MPI, XDR, SDDF-Binary, and PBIO. The NetLogger binary format is both highly efficient and self-describing, thus optimized for the dynamic message construction and parsing of application instrumentation. NetLogger includes an \"activation\" API that allows NetLogger logging to be turned on, off, or modified by changing an external file This IS useful for activating logging in daemons/services (e g GndFTP server). The NetLogger reliability API provides the ability to specify backup logging locations and periodically try to reconnect broken TCP pipe. A typical use for this is to store data on local disk while net is down. An event archiver can log one or more incoming NetLogger streams to a local disk file (netlogd) or to a mySQL database (netarchd). We have found exploratory, visual analysis of the log event data to be the most useful means of determining the causes of performance anomalies The NetLogger Visualization tool, niv, has been developed to provide a flexible and interactive graphical representation of system-level and application-level events.", + "homepageURL": "http://netlogger.lbl.gov", + "laborHours": 0.0, + "languages": [], + "name": "The NetLogger Toolkit V2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://netlogger.lbl.gov/software/netlogger-license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://netlogger.lbl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The IRCD is an IRC server that was originally distributed by the IRCD Hybrid developer team for use as a server in IRC message over the public Internet. By supporting the IRC protocol defined in the IRC RFC, IRCD allows the users to create and join channels for group or one-to-one text-based instant messaging. It stores information about channels (e.g., whether it is public, secret, or invite-only, the topic set, membership) and users (who is online and what channels they are members of). It receives messages for a specific user or channel and forwards these messages to the targeted destination. Since server-to-server communication is also supported, these targeted destinations may be connected to different IRC servers. Messages are exchanged over TCP connections that remain open between the client and the server. The IRCD is being used within the Pervasive Computing Collaboration Environment (PCCE) as the 'chat server' for message exchange over public and private channels. After an LBNLSecureMessaging(PCCE chat) client has been authenticated, the client connects to IRCD with its assigned nickname or 'nick.' The client can then create or join channels for group discussions or one-to-one conversations. These channels can have an initial mode of public or invite-only and the mode may be changed after creation. If a channel is public, any one online can join the discussion; if a channel is invite-only, users can only join if existing members of the channel explicitly invite them. Users can be invited to any type of channel and users may be members of multiple channels simultaneously. For use with the PCCE environment, the IRCD application (which was written in C) was ported to Linux and has been tested and installed under Linux Redhat 7.2. The source code was also modified with SSL so that all messages exchanged over the network are encrypted. This modified IRC server also verifies with an authentication server that the client is who he or she claims to be and that this user is authorized to ain access to the IRCD.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Secure IRC Server", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The LBNLSecureMessaging application enables collaboration among colocated or geograhically dispersed users by supporting secure synchronous and asynchronous communication. This application is the graphical user interface client that is meant to be used in conjunction with servers (LBNL's PCCEServer and a customized IRC server) to allow group and one-to-one conversations via text-based instant messaging. Conversations may be private (by invitation only) or public (open to any member of a collaboratory group_ and they may be permanent and on-going or temporary and ad hoc. Users may leave notes for other people who are online or offline. By providing presence and awareness information, collaborators can easily locate each other and rendezvous. Written in Java/Swing, this application is cross-platform. To gain access to functionality, users have to be registered with an authorization server (PCCEServer) that maintains an access control list. Thus a collaboration group is comprised of a set of PCCE-registered users. Registered users can log in via either X.509 certificate or a username and password combination. PKI and SSL are used to authenticate servers and clients and to encrypt messages sent over the network. The LBNLSecureMessaging application offers instant messaging capabilities in a secure environment that provides data integrity, privacy authorization, and authentication.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "LBNL SecureMessaging", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The PCCEServer application is a server that should be used in conjunction with the LBNLSecureMessaging user interface to enable secure synchronous and asynchronous messaging. It provides authentication and authorization services for members of a collaboration group via PKI/SSL and maintains an access control list. Members of collaboration groups using the LBNLSecureMessaging client must register identifying information. including username and password and an optional X.509 certificate, with the PCCEServer. This registration not only restricts access to instant messaging, but augments the LBNLSecureMessaging's IRC-based chat facility with persistence. Users register permanent unique user ids by which they are known to other users in the system and create permanent venues intended for group conversations on a tong-term or continuous basis. In addition, the PCCEServer enhances instant messaging with presence and awareness information such as user availability, and it allows users to leave notes asynchronously for other users who are online or offline. Written in Java, it is a standalone application that can run on any platform that supports a Java Virtual Machine.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Java Version 1.4 or higher (including JSSE)" + ], + "name": "PCCEServer", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "pyGlobus provides a high-level object-oriented interface to the Globus Toolkit(r). It offers similar performance to the underlying toolkit, while allowing for easier programming.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "pyGlobus", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "Existing reliable ordered group communication protocols have been developed for local-area networks and do not in general scale well to a large number of nodes and wide-area networks. The InterGroup suite of protocols is a scalable group communication system that introduces an unusual approach to handling group membership, and supports a receiver-oriented selection of service. The protocols are intended for a wide-area network, with a large number of nodes, that has highly variable delays and a high message loss rate, such as the Internet. The levels of the message delivery service range from unreliable unordered to reliable timestamp ordered.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "InterGroup Protocols", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "PyGridWare wsdl2python stub generator is used to automatically generate Python bindings to a Web Service given a Web Service Description Language (WSDL) file.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "PYGridWare wsdl2python: python client stub generator", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "PyGridWare WSDL and XMLSchema interpreter is used to automatically generate python code that maps directly to the XMLSchema objects and WSLD PortTypes.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Python 2.0+" + ], + "name": "PyGrid WSDL and XML Schema interpreter", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "PyWSSecurity provides a Python implementation of the XML Digital Signature standard. It also provides an implementation of WS-Secure Convresation protocol.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "PyWSSecurity", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "PyGridWare OGSI Hosting Container provides a Python container for building Open Grid Services Infrastructure (OGSI) services. It provides a complete implementation of the OGSI standards.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "PyGridware OGSI Hosting Container", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Conservative Remapper (CORE) is a C++ language software library for remapping cell masses and cell-averaged densities on unstructured two dimensional grids, maintaining conservation of total mass in the process. CORE contains implementation of two remapping algorithms: a new, efficient \"swept region\" algorithm, and a more traditional algorithm basedon the computation of cell intersections. Grids may be Cartesian or cylindrical, and cells may have three or more vertices, with no upper limit. CORE can run in serial and in parallel, but in order to achieve wide applicability, CORE used no particular parallel communication library. Instead it achieves parallel communication through strategically placed, user defined callbacks. Users can also provide callbacks to redefine different parts or subcomponents of the remapping process. CORE allows the use of different data types, e.g. single-, double-, and quadruple- precision floating-point numbers, through the use of C++ templates. Using CORE is simple, and requires no configuration scripts or makefiles.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "Any ANSI-compliant C++ compiler" + ], + "name": "Conservative Remapper", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The ThreatView project is based on our prior work with the existing ParaView open-source scientific visualization application. Where ParaView provides a grapical client optimized scientific visualization over the VTK parallel client server architecture, ThreatView provides a client optimized for more generic visual analytics over the same architecture. Because ThreatView is based on the VTK parallel client-server architecture, data sources can reside on remote hosts, and processing and rendering can be performed in parallel. As seen in Fig. 1, ThreatView provides four main methods for visualizing data: Landscape View, which displays a graph using a landscape metaphor where clusters of graph nodes produce \"hills\" in the landscape; Graph View, which displays a graph using a traditional \"ball-and-stick\" style; Table View, which displays tabular data in a standard spreadsheet; and Attribute View, which displays a tabular \"histogram\" of input data - for a selected table column, the Attribute View displays each unique value within the column, and the number of times that value appears in the data. There are two supplemental view types: Text View, which displays tabular data one-record-at-a-time; and the Statistics View, which displays input metadata, such as the number of vertices and edges in a graph, the number of rows in a table, etc.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "ThreatView", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The \"Fuel Cycle Services Needs Estimator\", Version 2.0 allows users to estimate the amount of uranium enrichment services needed and amount of spent nuclear fuel produced by a given fleet of nuclear power reactors through 2050 based on user-determined information about the size of a reactor fleet and average characteristics of reactors in that fleet. The program helps users evaluate the current and future supply of nuclear fuel cycle services. The program also allows users to compare the enrichment needs and spent fuel production of more up to seven defined nuclear power reactor fleets and to aggregate estimated needs. Version 2.0 of the program has an additions of new graphs to show results of calculations (calculation capabilities and other graphing tools included in version 1.o), maps showing flows of material based on calculation results, and additional calculation capabilities that allow the user to compare supply to demand (demand calculations included in version 1.0). Default values for seven selected nuclear energy programs in East Asia are included for reference and comparison. The program was designed using the dynamic simulation software, Powersim.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "Fuel Cycle Services Needs Estimator v.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "TIIA is designed to perform ecological and human risk assessments for environmental contaminants in air, water, soil, and sediment. It uses a novel approach that applies to radionuclides and hazardous chemicals, based on a food web approach. Stochastic calculations (i.e., those that allow for propagation of uncertainty in a numerical fashion) are allowed.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Toolkit for Integrated Impact Assessments version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-22" + }, + "description": "HEMLOCK (Heterogeneous Ensemble Machine Learning Open Classification Kit) is a software tool for constructing, evaluating, and applying heterogeneous ensemble data models for use in solving supervised machine learning problems. Specifically, the main class of problems targeted by HEMLOCK is the problem of multiple-class classification (also called labeling or categorization) of data with continuous or discrete features. HEMLOCK consists of various data readers, machine learning algorithms, model combination and comparison routines, evaluation methods for model performance testing, and interfaces to external, state-of-the-art machine learning software libraries.", + "laborHours": 2720.8, + "languages": [ + "Java" + ], + "name": "HEMLOCK", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/HEMLOCK?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HEMLOCK", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "These are patches to Sun Microsystems open source OpenSSO project to fix various bugs and incorporate changes for Sandia and NNSA to use the product including fixes to improve OpenSSO's authentication and authorization abilities. These fixes will then by incorporated by Sun into their Sun Access Manager product, which is used by various DOE/NNSA plants and labs. Having Sun maintain these changes will relieve SNL and DOE from the cost of maintaining the changes themselves.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "OpenSSO Project Patches", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-25" + }, + "description": "NIDR (New Input Deck Reader) is a facility for processing block-structured input to large programs. NIDR was written to simplify maintenance of DAKOTA (a program for uncertainty quantification and optimization), to provide better error checking of input and to allow use of aliases in the input. While written to support DAKOTA input conventions, NIDR itself is independent of DAKOTA and can be used in many kinds of programs. The initial version of NIDR was copyrighted in 2008. We have since extended NIDR to support a graphical user interface called Jaguar for DAKOTA. In the Review and Approval process for an updated paper on NIDR, the Classification Approver states that a new copyright assertion should be performed.processing input to programs. NIDR is not primarily for military applications.", + "laborHours": 0.0, + "languages": [ + "C++/C" + ], + "name": "NIDR (New Input Deck Reader) V2.0 2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/nidr", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.02" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "libdinterpose is a Linux, C convenience library to assist you in writing interposer libraries to help you debug programs.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "lib debug interpose", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Master stores information about each node in a computer cluster, similar to an asset tracking program. Records changes and events happening on the system. Master is a networked client/server with a database backend.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Multi Admin/System Tracking-Environment Resource", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "GIO is an application programmer interface (API) or library for high performance IO that is designed for climate models that operate on a geodesic grid. GIO uses a combination of configuration files and API calls to define the mapping of internal model data to output variables in standard climate data formats. The mapping from model data to model output includes method of data slicing, aggregation, and linearization using a morton ordering approach. The data is then persisted through a standard interface that can be implemented using several different high level parallel libraries. Both Parallel NetCDF and NetCDF4 interfaces are provided. GIO is designed to run on supercomputing systems or multi-processor clusters with parallel file systems.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Geodesic IO Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The SWTools code is an infrastructure to facilitate the management of third-party software installations. SWTools is infrastructure code that works with user-supplied build and test scripts resulting in a mostly-automated software build and test framework. The framework tries to simplify the work required to deal with upgrades, whether they be compiler, operating system, or application upgrades. The code also automates the collection of as much reporting data as possible including user-facing web pages. Inventory and user documentation will be kept up to date dynamically; that is, the same documentation that the installer writes for local users of the system will be made available online, and all web based inventory information will be dynamically updated.", + "homepageURL": "https://www.olcf.ornl.gov/center-projects/swtools", + "laborHours": 0.0, + "languages": [ + "Python 2.5 or Korn shell script" + ], + "name": "SWTools", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.olcf.ornl.gov/center-projects/swtools", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.olcf.ornl.gov/center-projects/swtools", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "An important rate-limiting step in the resonance assignment process is accurate identification of resonance peaks in MNR spectra. NMR spectra are noisy. Hence, automatic peak-picking programs must navigate between the Scylla of reliable but incomplete picking, and the Charybdis of noisy but complete picking. Each of these extremes complicates the assignment process: incomplete peak-picking results in the loss of essential connectivities, while noisy picking conceals the true connectivities under a combinatiorial explosion of false positives. Intermediate processing can simplify the assignment process by preferentially removing false peaks from noisy peak lists. This is accomplished by requiring consensus between multiple NMR experiments, exploiting a priori information about NMR spectra, and drawing on empirical statistical distributions of chemical shift extracted from the BioMagResBank. Experienced NMR practitioners currently apply many of these techniques \"by hand\", which is tedious, and may appear arbitrary to the novice. To increase efficiency, we have created a systematic and automated approach to this process, known as APART. Automated pre-processing has three main advantages: reduced tedium, standardization, and pedagogy. In the hands of experienced spectroscopists, the main advantage is reduced tedium (a rapid increase in the ratio of true peaks to false peaks with minimal effort). When a project is passed from hand to hand, the main advantage is standardization. APART automatically documents the peak filtering process by archiving its original recommendations, the accompanying justifications, and whether a user accepted or overrode a given filtering recommendation. In the hands of a novice, this tool can reduce the stumbling block of learning to differentiate between real peaks and noise, by providing real-time examples of how such decisions are made.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [], + "name": "Automated Pre-processing for NMR Assignments with Reduced Tedium", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The security group at NERSC recently undertook a project to gain access to this information from user ssh logins. Our solution was to modify the SSH daemon to export information about user names, authentication, keystrokes, file transfers, remote command execution and a variety of SSH related metadata in as agnostic a way as possible. In addition to improved system auditing, we added the Pittsburgh Supercomputing Performance improvement patches as well.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Instrumented OpenSSH", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Software tool based on a structured methodology for conducting laboratory biosafety risk assessments by biosafety experts. Software is based upon an MCDA scheme and uses peer reviewed criteria and weights. The software was developed upon Microsoft's .net framework. The methodology defines likelihood and consequence of a laboratory exposure for thirteen unique scenarios and provides numerical relative risks for each of the relevant thirteen. The software produces 2-d graphs reflecting the relative risk and a sensitivity analysis which highlights the overall importance of each factor. The software works as a set of questions with absolute scales and uses a weighted additive model to calculate the likelihood and consequence.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Windows.NET" + ], + "name": "Biosafety Risk Assessment Model", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-22" + }, + "description": "HNQ is a low level benchmark code used to characterize storage hardware performance.", + "laborHours": 334.4, + "languages": [ + "C" + ], + "name": "HNQ Version 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hnq", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Drekar is a code written for solving the low-mach incompressible Navier-Stokes and magnetohydrodynamics equations. It implements a stabilized Galerkin finite element discretization of the incompressible Navier-Stokes equations and a variational multiscale stabilized formulation for magnetohydrodynamics published by Codina. Drekar contains the front end physics description of the problem and then leverages 30 open source Trilinos packages to solve the problem. It relies on Trilinos for all parallel capabilities. The code will be released open source under the LGPL license. The code will be used by the partners of the Consortium for Advanced Simulation of Light Water Reactors (CASL), an Energy Innovation Hub funded by DOE to simulate fluid flow and heat transfer inside nuclear reactors. Additionally the code will be used for fundamental research collaborations in magnetohydrodynamics and computational fluid dynamics.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++ / various compilers" + ], + "name": "Drekar", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The software provides a simple web api to allow users to request a time window where a file will not be removed from cache. HPSS provides the concept of a \"purge lock\". When a purge lock is set on a file, the file will not be removed from disk, entering tape only state. A lot of network file protocols assume a file is on disk so it is good to purge lock a file before transferring using one of those protocols. HPSS's purge lock system is very coarse grained though. A file is either purge locked or not. Nothing enforces quotas, timely unlocking of purge locks, or managing the races inherent with multiple users wanting to lock/unlock the same file. The Purge Lock Server lets you, through a simple REST API, specify a list of files to purge lock and an expire time, and the system will ensure things happen properly.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C", + "PHP" + ], + "name": "Purge Lock Server", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "MyEMSL provides the following features: user-assisted upload of data from scientific instruments to an archive, tracking data though the upload process, providing metadata for recovery of uploaded data, providing users with access to the data. These features are supplied by a mixture of open source software and internally developed software. MyESML also provides a notification system that allows the system to communicate with users and other parts of the MyEMSL system. This allows the system to support automated workflows and user interaction. Reprocessing of already ingested data is also supported.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C, Python, PHP, Go, C#, Javascript" + ], + "name": "MyEMSL", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The software package, processMC, is a python script that allows for the rapid modeling of small , noisy quantum systems and the computation of the averaged quantum evolution map.", + "laborHours": 228.0, + "languages": [ + "Python 2.6" + ], + "name": "Quantum Process Matrix Computation by Monte Carlo", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/processMC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "COYOTE is designed for the analysis of steady and transient, multi-dimensional, nonlinear heat conduction problems. The spatial discretization technique is based on the Galerkin finite element method. The code contains a library of linear and quadratic elements and incudes bars and shells. COYOTE Implicit and explicit time integration methods, with adaptive time step control, are available for transient problems and fixed-point methods are used for Conjugate gradient iterative methods are used for the matrix solution. Coupled enclosure radiation with efficient view factor computation is included. Simulation capabilities include material motion, dynamic radiation enclosures, contact boundary conditions, multipoint constraints, material (element) addition, and deletion, bulk nodes, chemically reactive materials, and coupling with other mechanics codes. The code is designed for single or multi-processor computing", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "COYOTE", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The STAYSL PNNL Suite of software provides a set of tools for working with neutron activation rates measured in a nuclear fission reactor, an accelerator-based neutron source, or any neutron field to determine the neutron flux spectrum through a generalized least-squares approach. This process is referred to as neutron spectral adjustment since the preferred approach is to use measured data to adjust neutron spectra provided by neutron physics calculations. The input data consist of the reaction rates based on measured activities, an initial estimate of the neutron flux spectrum, neutron activation cross sections and their associated uncertainties (covariances), and relevant correction factors. The output consists of the adjusted neutron flux spectrum and associated covariance matrix, which is useful for neutron dosimetry and radiation damage calculations. The software suite consists of the STAYSL PNNL, SHIELD, BCF, and NJpp Fortran codes and the SigPhi Calculator spreadsheet tool. In addition, the development of this software suite and associated data libraries used the third-party NJOY99 Fortran code (http://t2.lanl.gov/nis/codes/njoy99/). The NJOY99 and NJpp codes are used to assemble cross section and covariance input data libraries (for both SHIELD and STAYSL PNNL) from the International Reactor Dosimetry File of 2002 (IRDF-2002; http://www-nds.iaea.org/irdf2002/) developed by the Nuclear Data Section of the International Atomic Energy Agency (Vienna, Austria). The BCF, SigPhi Calculator, and SHIELD software tools are used to calculate corrected activation rates and neutron self-shielding correction factors, which are inputs to the STAYSL PNNL code.", + "homepageURL": "https://www.pnnl.gov/projects/staysl-pnnl-software-suite-reactor-dosimetry", + "laborHours": 0.0, + "languages": [], + "name": "STAYSL PNNL Suite", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/projects/staysl-pnnl-software-suite-reactor-dosimetry", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/projects/staysl-pnnl-software-suite-reactor-dosimetry", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The LMDT software automates the process of the load composite model data preparation in the format supported by the major power system software vendors (GE and Siemens). Proper representation of the load composite model in power system dynamic analysis is very important. Software tools for power system simulation like GE PSLF and Siemens PSSE already include algorithms for the load composite modeling. However, these tools require that the input information on composite load to be provided in custom formats. Preparation of this data is time consuming and requires multiple manual operations. The LMDT software enables to automate this process. Software is designed to generate composite load model data. It uses the default load composition data, motor information, and bus information as an input. Software processes the input information and produces load composition model. Generated model can be stored in .dyd format supported by GE PSLF package or .dyr format supported by Siemens PSSE package.", + "homepageURL": "https://svn.pnl.gov/LoadTool", + "laborHours": 0.0, + "languages": [], + "name": "Load Model Data Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://svn.pnl.gov/LoadTool#License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.pnl.gov/LoadTool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "This software is used to combine output files US EPA CAp88-PC software (http://www.epa.gov/radiation/assessment/CAP88/aboutcap88.html) and estimate input parameters for CAP88-PC. Also includes features for tabular and graphical review of results.", + "homepageURL": "http://rneshaps.r-forge.r-project.org", + "laborHours": 0.0, + "languages": [], + "name": "Rneshaps", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://rneshaps.r-forge.r-project.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The software interpolates tabular data, such as for equations of state, provided on an unstructured triangular grid. In particular, interpolation occurs in a two dimensional space by looking up the triangle in which the desired evaluation point resides and then performing a linear interpolation over the n-tuples associated with the nodes of the chosen triangle. The interface to the interpolation routines allows for automated conversion of units from those tabulated to the desired output units. when multiple tables are included in a data file, new tables may be generated by on-the-fly mixing of the provided tables", + "laborHours": 1656.8, + "languages": [ + "C", + "Fortran" + ], + "name": "Sandia Unstructured Triangle Tabular Interpolation Package v 0.1 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/UTri", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software generates data tables for thermodynamic and transport properties of materials as described by a set of input models. For each input model parameterization, an associated table is created on an unstructured triangular grid. These grids all conform to the same topology. A statistical accuracy guarantee is provided for the tabular representation of the model. Details of the model and table specification are given in a XML input deck.", + "laborHours": 69798.4, + "languages": [ + "lc/C++/FORTRAN" + ], + "name": "Sandia Unstructured Triangle Table Generator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/SUTTG?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SUTTG", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SOS is software that stores data values in a set of structured flat files. The data is organized in the files based upon functions specified by the user in order to enable fast insertion and retrieval of data.", + "laborHours": 54036.0, + "languages": [ + "C", + "Roff", + "RPC", + "Cython", + "M4", + "Python" + ], + "name": "Scalable Object Store v. 1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ovis-hpc/sos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This package assists in genome assembly. extendFromReads takes as input a set of Illumina (eg, MiSeq) DNA sequencing reads, a query seed sequence and a direction to extend the seed. The algorithm collects all seed-- ]matching reads (flipping reverse-- ]orientation hits), trims off the seed and additional sequence in the other direction, sorts the remaining sequences alphabetically, and prints them aligned without gaps from the point of seed trimming. This produces a visual display distinguishing the flanks of multi- ]copy seeds. A companion script hitMates.pl collects the mates of seed-- ]hi]ng reads, whose alignment reveals longer extensions from the seed. The collect/trim/sort strategy was made iterative and scaled up in the script denovo.pl, for de novo contig assembly. An index is pre-- ]built using indexReads.pl that for each unique 21-- ]mer found in all the reads, records its gfate h of extension (whether extendable, blocked by low coverage, or blocked by branching after a duplicated sequence) and other characteristics. Importantly, denovo.pl records all branchings that follow a branching contig endpoint, providing contig- ]extension information", + "laborHours": 30.4, + "languages": [ + "perl" + ], + "name": "extendFromReads", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/extendFromReads", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-24" + }, + "description": "JAGUAR is a Java software tool for automatically rendering a graphical user interface (GUI) from a structured input specification. It is designed as a plug-in to the Eclipse workbench to enable users to create, edit, and externally execute analysis application input decks and then view the results. JAGUAR serves as a GUI for Sandia's DAKOTA software toolkit for optimization and uncertainty quantification. It will include problem (input deck)set-up, option specification, analysis execution, and results visualization. Through the use of wizards, templates, and views, JAGUAR helps uses navigate the complexity of DAKOTA's complete input specification. JAGUAR is implemented in Java, leveraging Eclipse extension points and Eclipse user interface. JAGUAR parses a DAKOTA NIDR input specification and presents the user with linked graphical and plain text representations of problem set-up and option specification for DAKOTA studies. After the data has been input by the user, JAGUAR generates one or more input files for DAKOTA, executes DAKOTA, and captures and interprets the results", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "JAva GUi for Applied Research (JAGUAR) v 3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/jaguar", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "This piece of software is a new feature implemented inside an existing open-source library. Specifically, it is a new implementation of a density functional (HSE, short for Heyd-Scuseria-Ernzerhof) for a repository of density functionals, the libxc library. It fixes some numerical problems with existing implementations, as outlined in a scientific paper recently submitted for publication. Density functionals are components of electronic structure simulations, which model properties of electrons inside molecules and crystals.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C, any up-to-date compiler should suffice" + ], + "name": "HSE12 implementation in libxc", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The Megatux platform enables the emulation of large scale (multi-million node) distributed systems. In particular, it allows for the emulation of large-scale networks interconnecting a very large number of emulated computer systems. It does this by leveraging virtualization and associated technologies to allow hundreds of virtual computers to be hosted on a single moderately sized server or workstation. Virtualization technology provided by modern processors allows for multiple guest OSs to run at the same time, sharing the hardware resources. The Megatux platform can be deployed on a single PC, a small cluster of a few boxes or a large cluster of computers. With a modest cluster, the Megatux platform can emulate complex organizational networks. By using virtualization, we emulate the hardware, but run actual software enabling large scale without sacrificing fidelity.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C/Python" + ], + "name": "Megatux", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software provides a general interface for querying thermodynamic states of material models along with implementation of both general and specific equation of state models. In particular, models are provided for the IAPWS-IF97 and IAPWS95 water standards as well as the associated water standards for viscosity, thermal conductivity, and surface tension. The interface supports implementation of models in a variety of independent variable spaces. Also, model support routines are included that allow for coupling of models and determination and representation of phase boundaries.", + "laborHours": 3009.6, + "languages": [ + "CMake", + "C++", + "C" + ], + "name": "Sandia Equation of State Model Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/SESML?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SESML", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Rnnotator is an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads.", + "homepageURL": "https://sites.google.com/a/lbl.gov/rnnotator/home", + "laborHours": 0.0, + "languages": [], + "name": "Rnnotator 3.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sites.google.com/a/lbl.gov/rnnotator/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sites.google.com/a/lbl.gov/rnnotator/home", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "CLaMS-\"Classifer for Metagenonic Sequences\" is a Java application for binning assembled metagenomes wings user-specified training sequence sets and other user-specified initial parameters. Since ClAmS analyzes and matches sequence composition-based genomic signatures, it is much faster than binning tools that rely on alignments to homologs; CLaMS can bin ~20,000 sequences in 3 minutes on a laptop with a 2.4 Ghz. Intel Core 2 Duo processor and 2 GB Ram. CLaMS is meant to be desktop application for biologist and can be run on any machine under any operating system on which the Java Runtime Environment is enabled. CLaMS is freely available in both GVI-based and command-line based forms.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "JRE" + ], + "name": "CLaMS: Classifier for Metagenomic Sequences", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Application that uses the Python low-level socket interface to pass network traffic between devices on the local side of a NAT router and the WAN side of the NAT router. This application is designed to generate traffic that complies with the Energy Star Small Network Equipment Test Method.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Python 2.7" + ], + "name": "Network Traffic Generator for Low-rate Small Network Equipment Software", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "StruMF is an algebraic structured preconditioner for the interative solution of large sparse linear systems. The preconditioner corresponds to a multifrontal variant of sparse LU factorization in which some dense blocks of the factors are approximated with low-rank matrices. It is algebraic in that it only requires the linear system itself, and the approximation threshold that determines the accuracy of individual low-rank approximations. Favourable rank properties are obtained using a block partitioning which is a refinement of the partitioning induced by nested dissection ordering.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "C compilers" + ], + "name": "Structured Multifrontal Sparse Solver", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The raw computational power GPU Accelerators enables fast denoising of 3D MR images using bilateral filtering, anisotropic diffusion, and non-local means. This software addresses two facets of this promising application: what tuning is necessary to achieve optimal performance on a modern GPU? And what parameters yield the best denoising results in practice? To answer the first question, the software performs an autotuning step to empirically determine optimal memory blocking on the GPU. To answer the second, it performs a sweep of algorithm parameters to determine the combination that best reduces the mean squared error relative to a noiseless reference image.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "GPU-Accelerated Denoising in 3D (GD3D)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The Single Cell Data Decontamination Pipeline is a fully-automated software tool which classifies unscreened contigs from single cell datasets through a combination of homology and feature-based methodologies using the organism's nucleotide sequences and known NCBI taxonomony. The software is freely available to download and install, and can be run on any system.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "ProDeGe: A Computational Protocol for fully Automated Decontamination of Genomic Data", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "TabVar: A Python library for manipulating datasets in the form of tabulated variables. Tables in tabvar contain many columns representing independent variables, but exactly one distinguished column for the dependent variable. Having a single distinguished column allows a natural lifting of arithmetic operators to tables, much (and in fact fully generalizing) multidimensional array arithmetic. The convenient syntax of whole-table arithmetic, along with the usual operations of filtering and aggregation, and all in the setting of python's interactive REPL allows for rapid exploration of datasets.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TabVar: Tabulated Variables", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "batchacct provides convenient library and command-line access to batch system accounting data for GridEngine and SLURM schedulers. It can be used to perform queries useful for data analysis of the accounting data alone or for integrative analysis in the context of a larger query.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "gcc/4.8 or higher" + ], + "name": "QQACCT", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Mini-PIC is an electrostatic particle-in-cell (PIC} testbed application for development of MPl+X applications on next generation platforms.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++98" + ], + "name": "Mini-PIC", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Mingus provides hybrid coupled local/non-local mechanics analysis capabilities that extend several traditional methods to applications with inherent discontinuities. Its primary features include adaptations of solid mechanics, fluid dynamics and digital image correlation that naturally accommodate dijointed data or irregular solution fields by assimilating a variety of discretizations (such as control volume finite elements, peridynamics and meshless control point clouds). The goal of this software is to provide an analysis framework form multiphysics engineering problems with an integrated image correlation capability that can be used for experimental validation and model", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++, CNU or Clang" + ], + "name": "Mingus Discontinuous Multiphysics", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "In the field of mathematical finance, a \"backtest\" is the usage of historical market data to assess the performance of a proposed trading strategy. It is a relatively simple matter for a present-day computer system to explore thousands, millions or even billions of variations of a proposed strategy, and pick the best performing variant as the \"optimal\" strategy \"in sample\" (i.e., on the input dataset). Unfortunately, such an \"optimal\" strategy often performs very poorly \"out of sample\" (i.e. on another dataset), because the parameters of the invest strategy have been oversit to the in-sample data, a situation known as \"backtest overfitting\". While the mathematics of backtest overfitting has been examined in several recent theoretical studies, here we pursue a more tangible analysis of this problem, in the form of an online simulator tool. Given a input random walk time series, the tool develops an \"optimal\" variant of a simple strategy by exhaustively exploring all integer parameter values among a handful of parameters. That \"optimal\" strategy is overfit, since by definition a random walk is unpredictable. Then the tool tests the resulting \"optimal\" strategy on a second random walk time series. In most runs using our online tool, the \"optimal\" strategy derived from the first time series performs poorly on the second time series, demonstrating how hard it is not to overfit a backtest. We offer this online tool, \"Simple Example of Backtest Overfitting (SEBO)\", to facilitate further research in this area.", + "homepageURL": "http://datagrid.lbl.gov/backtest", + "laborHours": 0.0, + "languages": [ + "Phython 2.7" + ], + "name": "Simple Example of Backtest Overfitting (SEBO)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://datagrid.lbl.gov/backtest", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://datagrid.lbl.gov/backtest", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "VAWTGen is a mesh generator for creating a finite element beam mesh of arbitrary vertical-axis wind turbines (VAWT). The software accepts input files specifying tower and blade structural and aerodynamic descriptions and constructs a VAWT using a minimal set of inputs. VAWTs with an arbitrary number of blades can be constructed with or without a central tower. Strut connections between the tower and blades can be specified in an arbitrary manner. The software also facilitates specifying arbitrary joints between structural components and concentrated structural tenns (mass and stiffness). The output files which describe the VAWT configuration are intended to be used with the Offshore Wind ENergy Simulation (OWENS) Toolkit software for structural dynamics analysis of VAWTs. Furthermore, VAWTGen is useful for visualizing output from the OWENS analysis software.", + "laborHours": 912.0, + "languages": [ + "MATLAB" + ], + "name": "Vertical-Axis Wind Turbine Mesh Generator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/VAWTGen?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/VAWTGen", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "This software allows a student/user at some point during the flow of content on a web page to input comments and rate the content with things such as: 1) True false 2) Text Comments 3) Ratings 1-5 4) etc. This information is stored anonymously in the database and can be retrieved and reported on.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + ".NET 4.5x" + ], + "name": "Survey Administration Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This software package provides a common \"front end\" for various math operations that are relevant to astrophysical data processing. This includes special function evaluation, fast Fourier transforms, streamed random number generation and spherical geometry projections. Computer-vendor specific libraries and internal algorithms can be selected on different systems in order to achieve the best possible performance on all systems. This software is still in an early state of development. ", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Any Standard C++ compiler which supports the BOOST software package" + ], + "name": "Machine Optimized Analysis Tools", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The Open Smart Energy Gateway (OpenSEG) aims to provide near-real time smart meter data to consumers without the delays or latencies associated with it being transported to the utility data center and then back to the consumer's application. To do this, the gateway queries the local Smart Meter to which it is bound to get energy consumption information at pre-defined intervals (minimum interval is 4 seconds). OpenSEG then stores the resulting data internally for retrieval by an external application.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Open Smart Energy Gateway (OpenSEG)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Phisherman is an online software tool that was created to help experimenters study phishing. It can potentially be re-purposed to run other human studies. Phisherman enables studies to be run online, so that users can participate from their own computers. This means that experimenters can get data from subjects in their natural settings. Alternatively, an experimenter can also run the app online in a lab-based setting, if that is desired. The software enables the online deployment of a study that is comprised of three main parts: (1) a consent page, (2) a survey, and (3) an identification task, with instruction/transition screens between each part, allowing the experimenter to provide the user with instructions and messages. Upon logging in, the subject is taken to the permission page, where they agree to or do not agree to take part in the study. If the subject agrees to participate, then the software randomly chooses between doing the survey first (and identification task second) or the identification task first (and survey second). This is to balance possible order effects in the data. Procedurally, in the identification task, the software shows the stimuli to the subject, and asks if she thinks it is a phish (yes/no) and how confident she is about her answer. The subject is given 5 levels of certainty to select from, labeled \"low\" (1), to \"medium\" (3), to \"high\" (5), with the option of picking a level between low and medium (2), and between medium and high (4). After selecting his/her confidence level, then the \"Next\" button activates, allowing a user to move to the next email. The software saves a given subject's progress in the identification task, so that she may log in and out of the site. The consent page is a space for the experimenter to provide the subject with human studies board /internal review board information, and to formally consent to participate in the study. The survey is a space for the experimenter to provide questions and spaces for the users to input answers (allowing both multiple-choice and free-answer options). Phisherman includes administrative pages for managing the stimuli and users. This includes a tool for the experimenter to create, preview, edit, delete (if desired), and manage stimuli (emails). The stimuli may include pictures (uploaded to an appropriate folder) and links, for realism. The software includes a safety feature that prevents the user from going to any link location or opening a file/image. Instead of re-directing the subject's browser, the software provides a pop-up box with the URL location of where the user would have gone. Another administrative page may be used to create fake subject accounts for testing the software prior to deployment, as well as to delete subject accounts when necessary. Data from the experiment can be downloaded from another administrative page.", + "laborHours": 3800.0, + "languages": [ + "Groovy", + "CSS", + "JavaScript" + ], + "name": "Phisherman v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/phisherman", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Computational Fluid Dynamics is an important area in scientific computing where, despite the use of multi-threading, obtaining good performance at each core is still extremely challenging. The challenges are primarily due to memory bandwidth limitations and difficulties in using short SIMD engines effectively. One strategy to improve in-core performance involves using a hierarchical data layout made of small cubical structures of the problem states that can fit well in the cache hierarchy. Even for such a hierarchical data layout, finite-differencing equations can be easily expressed but at the expense of some inefficiency. The transformations to overcome the inefficiencies are highly tedious and error-prone. Therefore, we built a source-to-source translator called CFDbuilder to automate the transformations using directives. We see up to 6.92x performance improvement with one of our advection codes using such an approach. We believe such an approach could enable library and application writers to build efficient CFD libraries.", + "laborHours": 8831.2, + "languages": [ + "Java", + "Makefile", + "GAP" + ], + "name": "CFDbuilder", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/CFDbuilder?tab=License-1-ov-file", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CFDbuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Suite of programs for evaluating endothelial function, including protocol execution, data acquisition, and analysis", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "GCC 4.x" + ], + "name": "Software Suite for Endothelial Function Assessment", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Flexibility from distributed energy resources presents an enormous potential to provide various services to the smart grid. In this paper, we propose a unified hierarchical framework for aggregation and coordination of various flexible loads, such as commercial building Heating, Ventilation, and Air-Conditioning (HVAC) systems, Thermostatically Controlled Loads (TCLs), Distributed Energy Storages (DESs), residential Pool Pumps (PPs), and Electric Vehicles (EVs). Moreover, a multistage Nash-bargaining-based control strategy is proposed to coordinate different aggregations of flexible loads for demand response. Case studies are provided to demonstrate the efficacy of our proposed framework and coordination strategy in managing peak power demand in a community.", + "homepageURL": "https://store.pnnl.gov/content/multi-period-nash-bargaining-coordination-distributed-energy-resources", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Multi-period Nash bargaining for Coordination of Distributed Energy Resources", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/multi-period-nash-bargaining-coordination-distributed-energy-resources", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/multi-period-nash-bargaining-coordination-distributed-energy-resources", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The approach is based on classical Density Functional Theory (cDFT) coupled with the Poisson-Nernst-Planck (PNP) transport kinetics model and quantum mechanical description of short-range interaction and elementary transport processes. The model we proposed and implemented is fully atomistic, taking into account pairwise short-range and manybody long-range interactions. But in contrast to standard molecular dynamics (MD) simulations, where long-range manybody interactions are evaluated as a sum of pair-wise atom-atom contributions, we include them analytically based on well-established theories of electrostatic and excluded volume interactions in multicomponent systems. This feature of the PNP/cDFT approach allows us to reach well beyond the length-scales accessible to MD simulations, while retaining the essential physics of interatomic interactions from first principles and in a parameter-free fashion.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "FORTRAN" + ], + "name": "cDF Theory Software for mesoscopic modeling of equilibrium and transport phenomena", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The Designs for Risk Evaluation and Management (DREAM) tool was developed as part of the effort to quantify the risk of geologic storage of carbon dioxide (CO2) under the U.S. Department of Energy's National Risk Assessment Partnership (NRAP). DREAM is an optimization tool created to identify optimal monitoring schemes that minimize the time to first detection of CO2 leakage from a subsurface storage formation. DREAM acts as a post-processer on user-provided output from subsurface leakage simulations. While DREAM was developed for CO2 leakage scenarios, it is applicable to any subsurface leakage simulation of the same output format. The DREAM tool is comprised of three main components: (1) a Java wizard used to configure and execute the simulations, (2) a visualization tool to view the domain space and optimization results, and (3) a plotting tool used to analyze the results. A secondary Java application is provided to aid users in converting common American Standard Code for Information Interchange (ASCII) output data to the standard DREAM hierarchical data format (HDF5). DREAM employs a simulated annealing approach that searches the solution space by iteratively mutating potential monitoring schemes built of various configurations of monitoring locations and leak detection parameters. This approach has proven to be orders of magnitude faster than an exhaustive search of the entire solution space. The user's manual illustrates the program graphical user interface (GUI), describes the tool inputs, and includes an example application.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Designs for Risk Evaluation and Management", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The OpenSHMEM Analyzer is a compiler-based tool that can help users detect errors and provide useful analyses about their OpenSHMEM applications. The tool is built on top of the OpenUH compiler (a branch of Open64 compiler) and presents OpenSHMEM information as feedback to the user. Some of the analyses it provides include checks for correct usage of symmetric variables in OpenSHMEM calls, out-of-bounds checks for symmetric data, checks for the correct initialization of pointers to symmetric data, and symmetric data alias information.", + "homepageURL": "http://www.openshmem.org/site/OSA", + "laborHours": 0.0, + "languages": [ + "C, C++ / GCC / 4.3.4" + ], + "name": "The OpenSHMEM Analyzer", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.openshmem.org/site/node/58", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.openshmem.org/site/OSA", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "GFS is a simulation engine that is used for the characterization of Accelerator performance parameters based on the machine layout, configuration and noise sources. It combines extensively tested Feedback models with a longitudinal phase space tracking simulator along with the interaction between the two via beam-based feedback using a computationally efficient simulation engine. The models include beam instrumentation, considerations on loop delays for in both the R and beam-based feedback loops, as well as the ability to inject noise (both correlated and uncorrelated) at different points of the machine including a full characterization of the electron gun performance parameters.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Global Feedback Simulator", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The Dynamic Contingency Analysis Tool (DCAT) is an open-platform and publicly available methodology to help develop applications that aim to improve the capabilities of power system planning engineers to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. Outputs from the DCAT will help find mitigation solutions to reduce the risk of cascading outages in technically sound and effective ways. The current prototype DCAT implementation has been developed as a Python code that accesses the simulation functions of the Siemens PSS/E planning tool (PSS/E). It has the following features: It uses a hybrid dynamic and steady-state approach to simulating the cascading outage sequences that includes fast dynamic and slower steady-state events. It integrates dynamic models with protection scheme models for generation, transmission, and load. It models special protection systems (SPSs)/remedial action schemes (RASs) and automatic and manual corrective actions. Overall, the DCAT attempts to bridge multiple gaps in cascading-outage analysis in a single, unique prototype tool capable of automatically simulating and analyzing cascading sequences in real systems using multiprocessor computers. While the DCAT has been implemented using PSS/E in Phase I of the study, other commercial software packages with similar capabilities can be used within the DCAT framework.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Dynamic Contingency Analysis Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software generates predicted results of differential scanning calorimetry experiments for samples of palladium in a perforated capsule in an atmosphere containing a mixture of hydrogen isotopologues and helium. It can also be used to predict the results of absorption-desorption experiments at constant temperature and solid-phase isotopic ratio.", + "laborHours": 0.0, + "languages": [ + "GNU Octave 3.6.4 or later" + ], + "name": "HDTHe calorimetry v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HDTHe", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This software provides a means for computing only the largest few entries of the product of two matrices, both exactly and approximately (using randomized sampling techniques). The purpose of the code is to demonstrate both the time it takes to solve the problem as well as the accuracy of the approximate approach. It is also meant to serve as a foundation to test the applicability of the sampling technique to related problems in data mining, including maximum inner product search, nearest neighbor search, and maximum cosine similarity.", + "laborHours": 6794.4, + "languages": [ + "Matlab, C, C++", + "Java", + "Makefile", + "HTML" + ], + "name": "diamond-sampling", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DiamondSampling", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Many applications of high performance embedded computing are limited by performance or power bottlenecks. We have designed SEAK, a new benchmark suite, (a) to capture these bottlenecks in a way that encourages creative solutions to these bottlenecks? and (b) to facilitate rigorous, objective, end-user evaluation for their solutions. To avoid biasing solutions toward existing algorithms, SEAK benchmarks use a mission-centric (abstracted from a particular algorithm) and goal-oriented (functional) specification. To encourage solutions that are any combination of software or hardware, we use an end-user blackbox evaluation that can capture tradeoffs between performance, power, accuracy, size, and weight. The tradeoffs are especially informative for procurement decisions. We call our benchmarks future proof because each mission-centric interface and evaluation remains useful despite shifting algorithmic preferences. It is challenging to create both concise and precise goal-oriented specifications for mission-centric problems. This paper describes the SEAK benchmark suite and presents an evaluation of sample solutions that highlights power and performance tradeoffs.", + "homepageURL": "https://hpc.pnl.gov/SEAK", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "The Suite for Embedded Applications and Kernels", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://hpc.pnl.gov/SEAK", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://hpc.pnl.gov/SEAK", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Arrows is a software package that combines NWChem, SQL and NOSQL databases, email, and social networks (e.g. Twitter, Tumblr) that simplifies molecular and materials modeling and makes these modeling capabilities accessible to all scientists and engineers. EMSL Arrows is very simple to use. The user just emails chemical reactions to arrows@emsl.pnnl.gov and then an email is sent back with thermodynamic, reaction pathway (kinetic), spectroscopy, and other results. EMSL Arrows parses the email and then searches the database for the compounds in the reactions. If a compound isn't there, an NWChem calculation is setup and submitted to calculate it. Once the calculation is finished the results are entered into the database and then results are emailed back.", + "homepageURL": "https://store.pnnl.gov/content/emsl-arrows", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Environmental and Molecular Science Laboratory Arrow", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/emsl-arrows", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/emsl-arrows", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "INT is a toolkit for computing radiative heat exchange between particles. The algorithm is based on the the 'Photon Monte Carlo\" approach described by Wang and Modest and implemented as a library that can be interfaced with a variety of CFD codes to analyze radiative heat transfer in particle laden flows.", + "homepageURL": "https://www.nrel.gov/workingwithus/licensing.html", + "laborHours": 0.0, + "languages": [ + "FORTRAN" + ], + "name": "IHT: Tools for Computing Insolation Absorption by Particle Laden Flows", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/workingwithus/licensing.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/workingwithus/licensing.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "FAST is a simulation tool (computer software) for modeling tlie dynamic response of horizontal-axis wind turbines. FAST employs a combined modal and multibody structural-dynamics formulation in the time domain.", + "laborHours": 0.0, + "languages": [ + "Fortran", + "C", + "MATLAB (for Simulink interface)" + ], + "name": "FAST Simulation Tool Containing Methods for Predicting the Dynamic Response of Wind Turbines", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/OpenFAST/openfast", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This software package collects various open source and freely available codes and algorithms to compute and archive the categorical data for certain semisimple braided monoidal categories. In particular, it computes the data for of group theoretical categories for academic research.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "GAP / Python" + ], + "name": "Software for Computing, Archiving, and Querying Semisimple Braided Monoidal Category Data", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Xi-CAM aims to provide a community driven platform for multimodal analysis in synchrotron science. The platform core provides a robust plugin infrastructure for extensibility, allowing continuing development to simply add further functionality. Current modules include tools for characterization with (GI)SAXS, Tomography, and XAS. This will continue to serve as a development base as algorithms for multimodal analysis develop. Seamless remote data access, visualization and analysis are key elements of Xi-CAM, and will become critical to synchrotron data infrastructure as expectations for future data volume and acquisition rates rise with continuously increasing throughputs. The highly interactive design elements of Xi-cam will similarly support a generation of users which depend on immediate data quality feedback during high-throughput or burst acquisition modes.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Xi-CAM v1.2.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "A Powersim Studio implementation of the system dynamics\u2019 \u2018Molecules of Structure\u2019. The original implementation was in Ventana\u2019s Vensim language by James Hines. The molecules are fundamental constructs of the system dynamics simulation methodology.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Powersim Studio 7, Feature Pack 3, Service Release 9" + ], + "name": "Molecules in Studio v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This method employs the concept of federation, which is defined as the use of existing models that represent aspects of a system in specific domains (such as physical and cyber security domains) and building interfaces to link all of domain models. Federation seeks to build on existing bodies of work. Some examples include the Common Information Models (CIM) maintained by the International Electrotechnical Commission Technical Committee 57 (IEC TC 57) for the electric power industry. Another relevant model is the CIM maintained by the Distributed Management Task Force (DMTF)? this CIM defines a representation of the managed elements in an Information Technology (IT) environment. The power system is an example of a cyber-physical system, where the cyber systems, consisting of computing infrastructure such as networks and devices, play a critical role in the operation of the underlying physical electricity delivery system. Measurements from remote field devices are relayed to control centers through computer networks, and the data is processed to determine suitable control actions. Control decisions are then relayed back to field devices. It has been observed that threat actors may be able to successfully compromise this cyber layer in order to impact power system operation. Therefore, future control center applications must be wary of potentially compromised measurements coming from field devices. In order to ensure the integrity of the field measurements, these applications could make use of compromise indicators from alternate sources of information such as cyber security. Thus, modern control applications may require access to data from sources that are not defined in the local information model. In such cases, software application interfaces will require integration of data objects from cross-domain data models. When incorporating or federating different domains, it is important to have subject matter experts work together, recognizing that not everyone has the same knowledge, responsibilities, focus, or skill set.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Federation of UML models for cyber physical use cases", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This code is a highly modular framework for developing smoothed particle hydrodynamic (SPH) simulations running on parallel platforms. The compartmentalization of the code allows for rapid development of new SPH applications and modifications of existing algorithms. The compartmentalization also allows changes in one part of the code used by many applications to instantly be made available to all applications.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Linux" + ], + "name": "Smoothed Particle Hydrodynamic Simulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "P-Mart was designed specifically to allow cancer researchers to perform robust statistical processing of publicly available cancer proteomic datasets. To date an online statistical processing suite for proteomics does not exist. The P-Mart software is designed to allow statistical programmers to utilize these algorithms through packages in the R programming language as well as offering a web-based interface using the Azure cloud technology. The Azure cloud technology also allows the release of the software via Docker containers.", + "homepageURL": "https://pmart.labworks.org/index.html", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "P-Mart", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://pmart.labworks.org/index.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://pmart.labworks.org/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Typically environmental management problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly integration into a series of models with different complexity for various types of model analyses where the data are applied as soft and hard model constraints. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions). To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian- Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org). The ZEM framework is open-source and can be applied to any environmental management site. The framework will be open-source and released under GPL V3 license.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "Advanced Computational Framework for Environmental Management ZEM, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Akuna is a user environment that enables geoscientists to create conceptual models for subsurface investigations. These conceptual models can be augmented to create numerical models for specific subsurface simulators, and Akuna enables these simulations to be executed on supercomputers, and the results analyzed and visualized. Akuna is designed to easily support multiple subsurface simulators by using a novel, declarative approach that describes the specific features (input file formats, execution modes, output formats) of a simulator in an external data file, based on this data file, Akuna user interfaces are dynamically generated by Akuna, greatly reducing the effort and cost required to support a new simulator.", + "homepageURL": "https://store.pnnl.gov/content/akuna", + "laborHours": 0.0, + "languages": [ + "HPC languages" + ], + "name": "Akuna", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/akuna", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/akuna", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "An application that provides users with ex post information on foregone travel conclusions to induce travel behavioral change.", + "homepageURL": "https://www.nrel.gov/workingwithus/licensing.html", + "laborHours": 0.0, + "languages": [ + "Python 2.7, Javascript, Ruby" + ], + "name": "Retrospective Mobility Analysis", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/workingwithus/licensing.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/workingwithus/licensing.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "LibIsopach is a toolkit for high performance distributed immersive visualization, leveraging modern OpenGL. It features a multi-process scenegraph, explicit instance rendering, mesh generation, and three-dimensional user interaction event processing.", + "homepageURL": "https://www.nrel.gov/workingwithus/licensing.html", + "laborHours": 11126.4, + "languages": [ + "C++14" + ], + "name": "LibIsopach", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/workingwithus/licensing.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/workingwithus/licensing.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The software allows users of the OpenDSS grid modeling software to access their load flow models using a GUI interface developed in MATLAB. The circuit definitions are entered into a Microsoft Excel spreadsheet which makes circuit creation and editing a much simpler process than the basic text-based editors used in the native OpenDSS interface. Plot tools have been developed which can be accessed through a MATLAB GUI once the desired parameters have been simulated.", + "homepageURL": "https://sourceforge.net/projects/electricdss", + "laborHours": 0.0, + "languages": [ + "MATLAB, Delphi (http://www.embarcadero.com), currently version Delphi XE2, Free Pascal" + ], + "name": "Matlab-Excel Interface for OpenDSS", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sourceforge.net/p/electricdss/code/HEAD/tree/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/electricdss", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "PNNL developed a new tool for oscillation analysis and baselining. This tool has been developed under a new DOE Grid Modernization Laboratory Consortium (GMLC) Project (GM0072 - \u201cSuite of open-source applications and models for advanced synchrophasor analysis\u201d) and it is based on the open platform for PMU analysis. The Oscillation Baselining and Analysis Tool (OBAT) performs the oscillation analysis and identifies modes of oscillations (frequency, damping, energy, and shape). The tool also does oscillation event baselining (fining correlation between oscillations characteristics and system operating conditions).", + "homepageURL": "https://svn.pnl.gov/OBAT", + "laborHours": 0.0, + "languages": [ + "VB.NET (MS Visual Studio 2012)" + ], + "name": "Oscillation Baselining and Analysis Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://svn.pnl.gov/OBAT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.pnl.gov/OBAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Gap Resolution is a software package that was developed to improve Newbler genome assemblies by automating the closure of sequence gaps caused by repetitive regions in the DNA. This is done by performing the follow steps:1) Identify and distribute the data for each gap in sub-projects. 2) Assemble the data associated with each sub-project using a secondary assembler, such as Newbler or PGA. 3) Determine if any gaps are closed after reassembly, and either design fakes (consensus of closed gap) for those that closed or lab experiments for those that require additional data. The software requires as input a genome assembly produce by the Newbler assembler provided by Roche and 454 data containing paired-end reads.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Gap Resolution", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Data management tool designed for the Advanced Simulation Capability for Environmental Management (ASCEM) framework. Distinguishing features of this gateway include: (1) handling of complex geometry data, (2) advance selection mechanism, (3) state of art rendering of spatiotemporal data records, and (4) seamless integration with a distributed workflow engine.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "ASCEM Data Brower (ASCEMDB) v0.8", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The software contains a MATLAB implementation of the Generalized Preconditioned Locally Harmonic Residual (GPLHR) method for solving standard and generalized non-Hermitian eigenproblems. The method is particularly useful for computing a subset of eigenvalues, and their eigen- or Schur vectors, closest to a given shift. The proposed method is based on block iterations and can take advantage of a preconditioner if it is available. It does not need to perform exact shift-and-invert transformation. Standard and generalized eigenproblems are handled in a unified framework.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Generalized Preconditioned Locally Harmonic Residual Eigensolver (GPLHR) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Energy Operation Model (EOM) simulates the operation of the electric grid at the zonal scale, including inter-zonal transmission constraints. It generates the production cost, power generation by plant and category, fuel usage, and locational marginal price (LMP) with a flexible way to constrain the power production by environmental constraints, e.g. heat waves, drought conditions). Different from commercial software such as PROMOD IV where generator capacity and heat rate efficiency can only be adjusted on a monthly basis, EOM calculates capacity impacts and plant efficiencies based on hourly ambient conditions (air temperature and humidity) and cooling water availability for thermal plants. What is missing is a hydro power dispatch.", + "homepageURL": "https://store.pnnl.gov/content/energy-operation-model-eom", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Energy Operation Model", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/energy-operation-model-eom", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/energy-operation-model-eom", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "High performance parallel computation of sparse inverse covariance matrix estimation.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "MPI C++ COMPLIER WITH OPENmp SUPPORT" + ], + "name": "HP-CONCORD v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This software (Asset Scoring Tool) is designed to help building owners and managers to gain insight into the as-built efficiency of their buildings. It is a web tool where users can enter their building information and obtain an asset score report. The asset score report consists of modeled building energy use (by end use and by fuel type), building systems (envelope, lighting, heating, cooling, service hot water) evaluations, and recommended energy efficiency measures. The intended users are building owners and operators who have limited knowledge of building energy efficiency. The scoring tool collects minimum building data (~20 data entries) from users and build a full-scale energy model using the inference functionalities from Facility Energy Decision System (FEDS). The scoring tool runs real-time building energy simulation using EnergyPlus and performs life-cycle cost analysis using FEDS. An API is also under development to allow the third-party applications to exchange data with the web service of the scoring tool.", + "homepageURL": "https://buildingenergyscore.energy.gov", + "laborHours": 0.0, + "languages": [ + "Ruby, C# Javascript" + ], + "name": "Commercial Building Energy Asset Score", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://buildingenergyscore.energy.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://buildingenergyscore.energy.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2025-02-12" + }, + "description": "Two dimension, depth-averaged hydrodynamic and transport model.", + "laborHours": 46284.0, + "languages": [ + "Fortran 90" + ], + "name": "pnnl/mass2", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mass2", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The tool is intended to facilitate hydropower development and water resource planning by improving synthesis and interpretation of disparate spatial datasets that are considered in development actions (e.g., hydrological characteristics, environmentally and culturally sensitive areas, existing or proposed water power resources, climate-informed forecasts). The tool enables this capability by providing a unique framework for assimilating, relating, summarizing, and visualizing disparate spatial data through the use of spatial aggregation techniques, relational geodatabase platforms, and an interactive web-based Geographic Information Systems (GIS). Data are aggregated and related based on shared intersections with a common spatial unit; in this case, industry-standard hydrologic drainage areas for the U.S. (National Hydrography Dataset) are used as the spatial unit to associate planning data. This process is performed using all available scalar delineations of drainage areas (i.e., region, sub-region, basin, sub-basin, watershed, sub-watershed, catchment) to create spatially hierarchical relationships among planning data and drainages. These entity-relationships are stored in a relational geodatabase that provides back-end structure to the web GIS and its widgets. The full technology stack was built using all open-source software in modern programming languages. Interactive widgets that function within the viewport are also compatible with all modern browsers.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Basin Assessment Spatial Planning Platform", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "NIMROD uses a combination of semi-implicit and implicit time-stepping algorithms to advance the equations of extended magnetohydrodynamics. It uses 2D spectral elements and Fourier series for the third periodic direction.", + "homepageURL": "https://www.tibbartech.com/technology", + "laborHours": 0.0, + "languages": [ + "Fortran 90" + ], + "name": "NIMROD magnetohydrodynamics code", + "organization": "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.tibbartech.com/technology", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.tibbartech.com/technology", + "status": "Production", + "tags": [ + "DOE CODE", + "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The problem being solved is obtaining 3D images of objects from a collection of 2D projection images. he computer code provides GPU-based codes to reconstruct objects in 3D from 2D projection images.", + "laborHours": 0.0, + "languages": [ + "Python 3, GNU C" + ], + "name": "pyMBIR", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/svvenkatakrishnan/pyMBIR", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Accelerated linear algebra libraries often come with C-style of interfaces or even older Fortran77 standards, which makes it difficult to use within generic template programming environment of modern C++. For example, the BLAS and derived standards such as cuBLAS do not accept overloads and a different functions have to be called for each input type, thus it is very challenging to write a single template that handles multiple precision modes and works well with different C++ containers. HALA offers a series of templates that wrap around the BLAS/cuBLAS and other similar methods, automatically infer the relevant types and call the appropriate back-end. The templates work out-of-the-box with all C++ standard vector-like containers and can be easily extended (with template specializations) to handle user-provided containers. The HALA API is also overloaded to handle both GPU and CPU cases with a single \"engine\" class, thus a single high-level algorithms can utilize both CPU or GPU backends, i.e., the HALA API is unified and handles the variations between cuBLAS and BLAS. In addition to BLAS and cuBLAS, wrapper templates are provided for subset of LAPACK, cuSparse, and Cholmod methods. Work is in progress to complete as many of these standards as possible. HALA also includes a module for low-level extended register vectorization for complex number arithmetic and several simple solvers that build on the basic linear algebra capabilities. A single unified C++ API will benefit fast prototyping and easily writing code that is portable across GPU/CPU platforms as well as precision types and user containers. Note that HALA does not provide any accelerated algorithms, it simply serves as a \"handy\" front-end to other standards.", + "laborHours": 0.0, + "languages": [ + "C++ (gcc6 and 7 or clang 5 and 6)" + ], + "name": "HALA: Handy Accelerated Linear Algebra", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LIBHALA/hala", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-24", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The aDORe repository architecture, designed and implemented for ingesting, storing, and accessing a vast collection of Digital Objects. aDORe was originally created for use at the Research Library of the Los Alamos National Laboratory. The aDORe architecture is highly modular and standards-based. In the architecture, the MPEG-21 Digital Item Declaration Language is used as the XML-based format to represent Digital Objects that can consist of multiple datastreams as Open Archival Information System Archival Information Packages (OAIS AIPs).", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "Java/1.5" + ], + "name": "A Modular, Standards-based Digital Object Repository", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-24", + "metadataLastUpdated": "2021-06-10" + }, + "description": "According to the North American Electric Reliability Corporation (NERC) definition: \"Frequency response is a measure of an Interconnection's ability to stabilize frequency immediately following the sudden loss of generation or load, and is a critical component of the reliable operation of the Bulk-Power System, particularly during disturbances and recoveries. Failure to maintain frequency can disrupt the operation of equipment and initiate disconnection of power plant equipment to prevent it from being damaged, which could lead to wide-spread blackouts.\" Frequency Response Tool automates the power system frequency response analysis process. The tool performs initial estimation of the system frequency parameters (initial frequency, minimum frequency, settling point). User can visually inspect and adjust these parameters. The tool also calculates the frequency response performance metrics of the system, archives the historic events and baselines the system performance. Frequency response performance characteristics of the system are calculated using phasor measurement unit (PMU) information. Methodology of the frequency response performance assessment implemented in the tool complies with the NERC Frequency response standard.", + "homepageURL": "https://svn.pnl.gov/FRTool", + "laborHours": 0.0, + "languages": [ + "VB.NET" + ], + "name": "Frequency Response Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://svn.pnl.gov/FRTool#License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.pnl.gov/FRTool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-24", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The Demand Response (DR) Dispatch Tool uses price profiles to dispatch demand response resources and create load modifying profiles. These annual profiles are used as inputs to production cost models and regional planning tools (e.g., PROMOD). The tool has been effectively implemented in transmission planning studies conducted by the Western Electricity Coordinating Council via its Transmission Expansion Planning and Policy Committee. The DR Dispatch Tool can properly model the dispatch of DR resources for both reliability and economic conditions.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Demand Response Dispatch Tool", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-24", + "metadataLastUpdated": "2021-06-10" + }, + "description": "BioStudio is a library of algorithms for the design of large synthetic DNA, with an emphasis on the chromosome scale.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "perl 5.10" + ], + "name": "BioStudio", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-24", + "metadataLastUpdated": "2024-09-11" + }, + "description": "The Battery Lifecycle (BLC) Framework is an open-source platform that provides tools to visualize and share battery data from material characterization, cell testing, manufacturing, and field testing through the technology development cycle. BLC has three components: data importers, a front-end for querying the data and creating visualizations, and an application programming interface to provide access to the data from Python. BLC has been deployed for tracking the development of a battery from the lab to a manufacturing line and systems installed in the field and for comparing studies of multiple cells of the same battery chemistry and configuration. The code was developed around Redash, a robust open-source extract-transform-load engine. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. 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It enables data collection, fusion, and processing onboard the LAMP system in handheld configurations, and enables near-real-time 3-D mapping from onboard an unmanned aerial system (UAS). 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In particular, this framework allows the use of reinforcement learning through the standardized Functional Mock-up Interface, an open industry standard for co-simulation. First application was the development of a controller for dynamic fa\u00e7ade and heating ventilation and air conditioning (HVAC) systems.", + "laborHours": 0.0, + "languages": [], + "name": "Functional Mock-up Interface - Machine Learning Center (FMI-MLC) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/FMI-MLC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2021-05-27" + }, + "description": "QCLAB++ is a high-level C++ library of template headers for quantum gates and quantum circuits.", + "laborHours": 0.0, + "languages": [], + "name": "QCLAB++ v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QuantumComputingLab/qclabpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2022-06-13" + }, + "description": "WaterTAP is a new open source library of water-specific models built on the IDAES Integrated Platform to support the design and optimization of integrated water treatment systems, improve existing systems and enable the analysis of new designs incorporating emerging technologies. 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The scope of the model covers multiple stages of the biomass life cycle spanning feedstock harvest, collection, transportation and handling, preprocessing, and storage. The model determines the total logistics cost per dry metric ton ($/DM ton) for biomass and breaks down the costs for important cost categories including ownership related costs such as interest and depreciation, insurance, housing, and taxes as well as operating costs like repairs and maintenance, labor costs, and fuel and lube costs.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Stochastic Techno Economic Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/STEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "smith84@llnl.gov" + }, + "date": { + "created": "2021-06-02", + "metadataLastUpdated": "2021-06-29" + }, + "description": "ParFlow is an open-source, modular, parallel watershed flow model. It includes fully-integrated overland flow, the ability to simulate complex topography, geology and heterogeneity and coupled land-surface processes including the land-energy budget, biogeochemistry and snow (via CLM). It is multi-platform and runs with a common I/O structure from laptop to supercomputer. ParFlow is the result of a long, multi-institutional development history and is now a collaborative effort between CSM, LLNL, UniBonn and UCB. ParFlow has been coupled to the mesoscale, meteorological code ARPS and the NCAR code WRF.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Python", + "Tcl" + ], + "name": "ParFlow", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/parflow/parflow/releases/tag/v3.8.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.8.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-06-03", + "metadataLastUpdated": "2021-06-04" + }, + "description": "Five computationally expensive stencil evaluation routines from SW4(https://github.com/geodynamics/sw4 GPL license) have been extracted and packaged with a driver to create a mini-app for evaluating compiler and GPU performance. The kernels can executed on AMD and Nvidia GPUs with and without RAJA. The kernel driver generates synthetic inputs, checks for correctness and measures kernel run times. ", + "laborHours": 0.0, + "languages": [], + "name": "SW4 Curvilinear Kernels", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SW4CK", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-03", + "metadataLastUpdated": "2021-06-03" + }, + "description": "The Berkeley Quantum Synthesis Toolkit (BQSKit) is an optimizing quantum compiler and research vehicle that combines ideas from several projects at LBNL into one easily accessible and quickly extensible software package. The ideas in the QFAST, QSearch, LEAP, and QFactor software tools (all licensed through ipo.lbl.gov) all build upon one another. By combining these into one package, we create symbiotic interactions between the tools. This means better results, better throughput, less to maintain, and greater surface area to the public. Additionally, the BQSKit tool will create a research platform for future work here at LBNL.", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Quantum Synthesis Toolkit (BQSKit) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BQSKit/bqskit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "Dendro-GRCA is a parallel and distributed partial differential equation solver to perform large scale simulations in general relativistic computational astrophysics problems such as merging black holes and neutron stars and also many other problems in computational astrophysics. This toolkit, the Dendro library is a large scale distributed memory adaptive octree framework. Dendro consists of efficient parallel data structures and algorithms to perform finite element methods and finite difference methods on 2:1 balanced arbitrary adaptive octrees. ", + "laborHours": 0.0, + "languages": [], + "name": "Dendro-GRCA ver. 2.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Dendro-GRCA", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The holistic analysis and understanding of the latent (that is, not-directly observable) variables and patterns buried in large datasets is crucial for data-driven science, decision making and emergency response. Such exploratory analyses require devising unsupervised learning methods for data mining and extraction of the latent features, and non-negative matrix factorization (NMF) is one of the prominent such methods. % to extract interpretable latent features, with dimensionality reduction for data mining and blind source separation. NMF is based on compute-intense non-convex constrained minimization, which, for large datasets requires fast and distributed algorithms. However, current parallel implementations of NMF fail to estimate the number of latent features. In practice, identifying these features is both difficult and significant for pattern recognition and latent feature analysis, especially for large dense matrices. In this paper, we introduce a distributed NMF algorithm coupled with distributed custom clustering followed by a stability analysis on dense data, which we call DnMFk, to determine the number of latent variables. The results on synthetic data and the classical Swimmer data set demonstrate the accuracy of model determination while scaling nearly linearly across multiple processors for large data. Further, we employ DnMFk to determine the number of hidden features from a tera byte (TB) matrix.", + "laborHours": 0.0, + "languages": [], + "name": "DnMFk ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/DnMFkCPP", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "Identifying nucleic acid sequences of interest in complex metagenomic samples is often likened to \u201cfinding a needle in haystack\u201d. While the polymerase chain reaction (PCR) can provide unparalleled, selective enrichment of known sequences from complex metagenomic samples, traditional (endpoint and real-time) PCR assays only provide \u201cyes\u201d or \u201cno\u201d results and, more significantly, can be prone to database \u201coverfitting\u201d. Overfitting occurs during the computational PCR primer design process, which typically uses all of the available target and near-neighbor sequences to predict highly specific PCR primers. Even though the number of known sequences continues to grow exponentially, we have still only sequenced a small fraction of the sequence diversity that occurs in nature. As a result, PCR primers that appear to offer \u201cperfect\u201d target discrimination (i.e. no false positives or negatives) fail when experimentally tested against unsequenced targets and/or near-neighbors. These assay failures can also become apparent when PCR primers are computationally screened against sequences that were not included in the original design process. As a result, PCR assays are said to suffer from \u201csignature erosion\u201d. A useful strategy to overcome signature erosion is to not rely on single, or even a handful, of target-specific PCR primers, but instead use hundreds or thousands of different primer pairs in a single \u201cmultiplexed\u201d (or even megaplex) PCR. In much the same way that financial index funds can outperform hand-picked individual stocks, an ensemble of primer pairs can tolerate the failure of many individual pairs and still provide robust target enrichment. Next generation sequencing enables a digital readout of all of the sequences (or \u201camplicons\u201d) that are amplified during a successful PCR. This amplicon sequence information can be used by bioinformatics analysis programs to identify the most likely organisms, reject closely-related near-neighbors and uncover phenotypic (e.g. antibiotic resistance) and forensic (e.g. informative SNP) markers.\n\nHowever, it is still challenging to design a large set of primer pairs for multiplex PCR. These challenges include selecting individual primers that do not form hairpins, homo-dimers or hetero-dimers, as these unwanted reactions reduce the assay sensitivity by reducing the effective concentration of the effected primers. Primers must bind to their intended target sequences with similar affinities and produce similar length amplicons to ensure uniform amplicon enrichment. Amplicons that form stable secondary structures should be avoided to prevent any \u201cstalling\u201d of the DNA polymerase that could reduce the enrichment level. In addition, unintended PCR amplification, caused by primers that happen to bind in close proximity and in the correct orientation to non-target sequences, must be avoided to maintain a sufficient signal to noise level for target enrichment and detection. Finally, it is essential to experimentally test a multiplex PCR design strategy. Experiments can uncover software bugs and design flaws that would otherwise reduce the level of target enrichment. In particular, experimentally measuring assay performance on both known (sequenced) and unknown (unsequenced) targets and backgrounds will help bound the expected target enrichment levels for deployed assays.", + "laborHours": 0.0, + "languages": [], + "name": "PCRamp", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Bioinformatics/PCRamp", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The developed software is an HPC cluster model and collaboration tool which provides the\nfollowing features:\n- Construction of HPC cluster nodes\n- Complex interaction and dependency between HPC cluster nodes\n- Construction of fully software stacks (OS, data base, scheduler, libraries) internal to the\ncluster environment\n- Cluster nodes may be implemented via arbitrary providers (virtual machines, containers)\n- Complex interaction and dependency between HPC node\u2019s software stacks\n- Verification test framework between nodes and their software stacks\nThis is being used for active projects. This is intended to be used to provide consistent, coordinated scenario measurements,\nconfiguration and collaboration among the DoE TriLabs and other USG HPC sites in the\nforeseeable future, to accomplish DoE HPC CCE goals.", + "laborHours": 0.0, + "languages": [], + "name": "HPC Cluster Modeler and CoLaboration Platform", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/hpc-collab", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The capacity for big data manipulation and analysis has greatly evolved in the modern digital world due to varying sources such as social networks, medical scans, surveillance and monitoring systems, etc. Data mining and deep learning techniques are currently being utilized to understand the latent representation of the data using unsupervised approaches and also are known for their fast processing time. Even though these frameworks exhibit superior performance in supervised learning applications, however they are restricted in their algorithmic complexity and prove ineffective in computing the optimal latent representations for unsupervised applications. Non-Negative Matrix Factorization (NMF) techniques have proven effective in finding the most complex latent representations applied to a wide field of applications involving dimension reduction techniques applied to the fields of topic modeling, text mining, background separation in image/video datasets, anomaly detections and cancer detection. However NMF needs apriori information about the latent dimensionality. PyDnNMFk has NMF coupled with custom clustering that enables the recognition of the unknown latent dimensionality of the data along with the ability for an accurate reconstruction of the Factors. As the data size grows, the bottleneck due to the hardware computing/memory abilities grows too. Even though shared-memory based multiprocessing NMF frameworks perform faster compared to single core implementations, still the latency gives rise to the long wait times which might be an issue for time constraint applications. This raises the need for an optimal high performance implementation of NMF where the distributed memory and inter-process communication across massively parallel cores across multiple nodes tends to address the challenge. Hence we also provide Distributed implementation of NMFk, which can effectively factorize with identifying the latent dimensionality on exa-scale data. The implementations include a shared-memory multiprocessing based k estimation( pynNMFk), distributed memory inter-processor implementation(pyDnNMFk) and GPU factorization based implementation(pyGnNMFk) . The factor updates are based on Forbenius norm/KL divergence minimization criteria. ", + "laborHours": 0.0, + "languages": [], + "name": "pyDnMFk (Python Distributed Non Negative Matrix Factorization with determination of hidden features)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyDNMFk", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "PIDOTS is a software application for studying an alternative iterative and parallel solution technique for linear, deterministic neutral-particle radiation transport. The code solves a very generic, simplified\u2014i.e., dumb\u2014form of the system of relevant system of equations. PIDOTS is less capable than the open source proxy application SNAP. Given limitations introduced by the equations as well as limitations in data and meshing, PIDOTS is incapable of performing real physics simulations or addressing actual physics questions for transport. Instead of using transport mesh sweeps that we see in many production codes (and SNAP), PIDOTS uses a Jacobi or Jacobi-like iterative scheme that updates the flux information between adjacent, decoupled subdomains. By completely decoupling subdomains, PIDOTS permits massively large-scale decomposition (i.e., tens of thousands of processes or more) of the spatial mesh, making it an interesting alternative to mesh sweeps, worth continued studying and development. ", + "laborHours": 0.0, + "languages": [], + "name": "PIDOTS: Parallel Integral Discrete Ordinates Transport Solver v1.xx", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pidots", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "This code contains an implementation of Micromorphic continuum mechanics in the style of Eringen and Suhubi [1] developed during Nathan Miller's PhD thesis under the supervision of Richard Regueiro. The code is written in a finite deformation framework and contains micromoprhic constitutive models which can be used to simulate various solid mechanics problems. Interfaces to Abaqus and the Idaho National Laboratory code MOOSE are included as a part of the functionality with the possibility of extending to additional codes in the future.\n\n[1] A.Cemal Eringen, E.S. Suhubi, \"Nonlinear theory of simple micro-elastic solids\u2014I\", International Journal of Engineering Science, Volume 2, Issue 2, 1964, Pages 189-20", + "laborHours": 0.0, + "languages": [], + "name": "Tardigrade", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/tardigrade", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The Programming Repository for In Situ Modeling (PRISM) is a set of tools for fitting statistics and machine learning models to simulation data inside the simulations as they are running. By fitting models inside running simulations, PRISM can be used to analyze simulation data that is otherwise inaccessible because of I/O and storage bottlenecks associated with exascale and other future high performance computing architectures. The tools are designed to implement a wide variety of data analyses with an emphasis on spatiotemporal hierarchical Bayesian models. PRISM is efficient, scalable, and streaming with estimation based on variational inference, advanced Monte Carlo techniques, and fast optimization methods. The core modeling components aid this goal by imposing sparsity and approximate inference wherever possible. These components are written in Julia, a high-level programming language designed for high performance. PRISM also contains tools for interfacing with large-scale scientific simulations written in Fortran and C/C++. This layer of abstraction allows the data scientist to construct analysis models in Julia without concern for the implementation details of the simulation capability. With these components, PRISM can be used to unlock the full scientific potential of next-generation HPC simulations.", + "laborHours": 0.0, + "languages": [], + "name": "Programming Repository for In Situ Modeling", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PRISM", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The multimat_1drdg code is a one-dimensional code which is used to prototype the numerical method published in \u201cPandare, A. K., Waltz, J., & Bakosi, J. (2019). A Reconstructed Discontinuous Galerkin method for Multi-Material Hydrodynamics with Sharp-Interfaces. International Journal for Numerical Methods in Fluids.\u201d It solves the multi-fluid dynamics equations (arbitrary number of fluids) using the third-order Reconstructed Discontinuous Galerkin (rDG) method. A few academic test problems from previous published literature are included as initial setup options.", + "laborHours": 0.0, + "languages": [], + "name": "multimat_1drdg", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/multimat_1drdg", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The Automated Testing System (ATS) is an open-source, Python-based tool for automating the running of tests of an application across a broad range of high performance computers.", + "laborHours": 0.0, + "languages": [], + "name": "Automated Testing System", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ATS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "Dante is a probabilistic flu forecasting model. The methodology was developed to produce real-time flu forecasts in the U.S. The software to execute Dante is a collection of R scripts and JAGS files. It takes publicly available data from the US Centers for Disease Control and Prevention (CDC) as input. It runs R scrips and JAGS code to produce model output. ", + "laborHours": 0.0, + "languages": [], + "name": "Dante", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Dante", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2022-09-15" + }, + "description": "FIDUCIA: Filtered Diode Unfolder (using) Cubic-spline Algorithm Fiducia is a DANTE signal deconvolver based on the cubic splines method. Given time-resolved DANTE data across a number of K-edge filtered channels, this code can produce time-resolved x-ray spectra with coarse spectral resolution, as well as time-resolved x-ray flux and radiation temperature for a given source. The main application for this code is for diagnosing and constraining hohlraum drives on high energy density plasma physics experiments at the OMEGA Laser Facility and the National Ignition Facility. Spectral unfolds are created by assuming each DANTE channel provides information on the x-ray intensity in a particular photon energy band defined by its K-edge filter. The combination of multiple DANTE channels sensitive to different photon energies then provides coarse spectral information. The overall x-ray spectrum is approximated as a series of cubic splines corresponding to each energy band, which reduces the process of unfolding x-ray spectra from time-resolved DANTE channel data to a series of matrix operations folded with the DANTE response functions. By reducing the spectral deconvolution to a series of matrix operations, DANTE analysis is accelerated to the point where it could be feasibly used for on-the-fly characterization of hohlraum drives during experiments, with no additional assumptions about the shape of the x-ray spectrum.", + "laborHours": 0.0, + "languages": [], + "name": "Fiducia", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/fiducia", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-07" + }, + "description": "As high-performance computing reaches exascale, data analysis and visualization will need to shift from a predominantly post hoc approach to an in situ paradigm \u2013 running while the simulation is running. Memory and I/O bandwidth growth is expected to lag behind concurrency growth by orders of magnitude. This will require new in situ algorithms and tools that can leverage emerging accelerator technology to sufficiently decrease the volume of data moved on the machine and amount saved to persistent storage. As part of the Department of Energy\u2019s Exascale Computing Project (ECP), the ALPINE and team at Los Alamos National Laboratory (LANL) is collaboratively developing open source solutions with DOE leadership laboratories, universities, and industry partners to address these challenges. The ECP ALPINE project is developing filters and algorithms to support the in situ analysis and visualization goals of ECP application codes. Prototypes of the filters and algorithms are written in C++ and Python while production versions are written in VTK or VTK-m. These filters and algorithms will be available in commonly used visualization tools and infrastructures such as ParaView, VisIt, and Ascent and will be deployed on exascale machines at the DOE Leadership Computing Facilities. The primary users of these projects will be both at Los Alamos National Laboratory and will include application codes at institutions across the Exascale Computing Project (https://www.exascaleproject.org/).", + "laborHours": 0.0, + "languages": [], + "name": "ECP Collaborative Software Development for In Situ Data Analysis and Visualization", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/alpine-lanl", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2022-01-11" + }, + "description": "Python-based Sampling Toolkit (PySTK) is a set of python functions developed for efficient data reduction via sampling for large-scale time-varying complex scientific datasets. PySTK provides a range of capabilities: starting from naive random sampling of data to a more sophisticated data-drives feature-preserving sampling for regular grid datasets. PySTK further includes the option of visualization the samples using open-source library Visualization ToolKit (VTK), reconstruction from the samples, and fast sample-based query mechanism for scientific datasets. PySTK is designed to be efficient yet extendable, as it strives to handle large datasets using primarily the Numpy-based operations. This toolkit uses the python-based multi-threading for effective use of available resources. Not only the big supercomputers, modern day laptops and desktops are used for data analysis purposes by the domain experts and data analysts. PySTK seamlessly enables the use of such hardware to handle big data sets. PySTK can be used to explore large datasets generated by HPC simulations with intelligent sampling algorithms and exploit the existing hardware for efficient data analysis. Aside from the sampling code, PySTK will further contain the related documentation, test/demo cases, details of its build system, unit test harness, and a scholarly bibliography.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "PySTK: Python-Based Sampling Toolkit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-06-07", + "metadataLastUpdated": "2024-10-25" + }, + "description": "The windfarm operations and maintenance cost-benefit analysis tool (WOMBAT) is software to simulate the operations and maintenance phase of either onshore or offshore windfarms. WOMBAT is a medium-fidelity tool that is designed to model turbine, cable, and substation failures at the subassembly level, but is flexible enough that individual component or asset-level modeling can also be performed. WOMBAT enables users to model technological improvements, the use of a wide range of service equipment from drone repairs and remote resets to heavy lift vessels and crawler cranes, to analyze cost trends with varying trade-offs in conjunction with energy production, availability and a growing range of metrics. \n\nThis library provides a tool to simulate the operation and maintenance phase (O&M) of distributed, land-based, and offshore windfarms using a discrete event simulation framework.\n\nWOMBAT is written around the SimPy discrete event simulation framework. Additionally, this is supported using a flexible and modular object-oriented code base, which enables the modeling of arbitrarily large (or small) windfarms with as many or as few failure and maintenance tasks that can be encoded.\n\nPlease note that this is still heavily under development, so you may find some functionality to be incomplete at the current moment, but rest assured the functionality is expanding. With that said, it would be greatly appreciated for issues or PRs to be submitted for any improvements at all, from fixing typos (guaranteed to be a few) to features to testing.\n\nAlso available at: https://pypi.org/project/wombat/", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "WOMBAT (Windfarm Operations and Maintenance cost-Benefit Analysis Tool) WISDEM\u00ae [SWR-21-68]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/WOMBAT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "V0.9.3" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-06-07", + "metadataLastUpdated": "2022-09-13" + }, + "description": "KiteFAST is a simulator for airborne wind energy systems based on NREL's OpenFAST whole turbine simulator. KiteFAST is a multi-physics engineering tool for modeling the coupled aero-servo-elastic dynamics of airborne wind energy systems i.e. a wind-energy kite. The engineering model is like NREL's OpenFAST tool for land-based or offshore horizontal-axis wind turbines atop towers, in that KiteFAST models the important physical phenomena and system couplings, including the wind/aerodynamic excitation and full-system dynamics response (fuselage, wings, tail, stabilizers, pylons, nacelles, rotors, tether, ground station, control surfaces, and controller) under both normal (for fatigue) and extreme (for ultimate) loading conditions. The configuration of the wind-energy kite is assumed to have one fuselage; two wings (starboard, port) attached to the fuselage; one vertical stabilizer attached the fuselage; two horizontal stabilizers (starboard, port) attached to the vertical stabilizer; one or more pylons per wing, each with two rotors (top, bottom); one ground-station-fixed tether with a bridal connection to the wings, and nominal circular motion of the energy kite in the port (left) direction. The general configuration of the control surfaces assumes one or more flaps per wing, two rudders on the vertical stabilizer, two elevators per horizontal stabilizer, and rotors with variable speed and rotor-collective blade pitch. KiteFAST was developed from (1) the existing MBDyn open-source multi-body dynamics code; (2) the existing/modified OpenFAST modules NWTC Subroutine Library, AirfoilInfo, InflowWind, MoorDyn, and TurbSim; and (3) new source code for a) generating MBDyn models of the energy kite (KiteMBDyn Preprocessor), b) computing quasi-steady energy-kite aerodynamics (KiteAeroDyn, KiteAeroDyn Driver, KiteVSM, ActuatorDisk), c) interfacing an energy-kite controller, and d) coupling the various KiteFAST modules together (KiteFASTMBD).", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Fortran", + "Python", + "Jupyter Notebook", + "Roff", + "C", + "C++" + ], + "name": "KiteFAST", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/OpenFAST/KiteFAST", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-10", + "metadataLastUpdated": "2021-06-11" + }, + "description": "This software package contains a simple calculator that can be used to estimate savings from implementing a retrofit of HVAC controls to ASHRAE Guideline 36 in a multi-zone office building. Implemented in Excel, the calculator has a user-interface front-end to configure parameters of the case study, such as location, building size, and existing control strategies, and a back-end containing results from a large number of pre-run annual energy simulations. The software package also contains the simulation models and associated pre- and post-processing scripts to generate these results.", + "laborHours": 0.0, + "languages": [], + "name": "Guideline 36 Savings Calculator v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/G36SavingsCalculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-10", + "metadataLastUpdated": "2021-06-11" + }, + "description": "We have developed a series of compact RF mixing boards by integrating I/Q quadrature mixing, IF(intermediate frequency)/LO(local oscillator)/RF power level adjustments, and DC (direct current) bias fine tuning on a 40 mm \u00d7 80 mm 4-layer PCB (printed circuit board) board with EMI (electromagnetic interference) shielding.", + "laborHours": 0.0, + "languages": [], + "name": "RF mixing modules for superconducting qubit room temperature control systems v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/LBL-QubiC/rfmixingmodules", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-10", + "metadataLastUpdated": "2021-06-11" + }, + "description": "In short, the GENESPACE pipeline conducts analysis of orthology networks, constrained within syntenic regions. Since analyses are limited to local tests conducted within syntenic blocks, GENESPACE is agnostic to ploidy, duplicated regions, inversions or other whole-genome chromosomal complexities that are common across many evolutionary lineages. This advantage allows for evolutionary tests in polyploids (e.g. switchgrass, manuscript in review), species with ancient, but retained whole-genome duplications (e.g. pecan, manuscript in prep), high levels of tandem array proliferation (e.g. eukalypts, manuscript in review) and many other factors that can confound comparative genomic analyses. The major advances of GENESPACE are three-fold: First, this is the first R package to integrate visualization and analysis of large-scale comparative genomics. R, which offers a high-level environment for graphical and statistical exploration of data, is often speed- and memory-limited and not used for computationally intensive tasks such as comparative genomics. The highly efficient C++ scripts used in GENESPACE (via data.table) permit a much faster and computationally lightweight implementation of comparative genomics than is currently available. Second, the pipeline itself is novel. To the best of our knowledge, no other program accomplishes synteny-constrained and ploidy-agnostic comparative genomics. Since nearly all plants and many animals have a history of whole-genome duplications, this is a major and necessary advance to the field. Third, GENESPACE offers high-level and intuitive multi-genome graphical outputs. The dotplots and 'riparian' plots produced herein, which are produced entirely through original R code, are publication-ready and easily customizable.", + "laborHours": 0.0, + "languages": [], + "name": "GENESPACE R Package (GENESPACE) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/plant/genespace-r", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-15", + "metadataLastUpdated": "2021-06-16" + }, + "description": "Heliostat Aimpoint and Layout Optimization Software (HALOS) is an open-source software package that allows users to explore solar field layout optimization, aimpoint strategy optimization, and performance characterization of concentrating solar power tower plants. Users interface with the tool through python, and results are reported in time series tables, plots, runtime logs, and flat-file outputs. Users choose from a list of variables such as tower height, receiver capacity, flux limits, design-point irradiance, etc., and specify information about the system using a small collection of flat files. The software can then optimize the specified variables (e.g., aimpoints for each heliostat) to maximize the thermal energy delivered to the receiver while adhering to flux limits. HALOS is implemented to be flexible with respect to flux characterization methods, but includes a direct connection to NREL's SolarPILOT\u2122 software via its python API so that users can utilize high-fidelity flux simulation methods that have already been developed.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HALOS (Heliostat Aimpoint and Layout Optimization Software)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HALOS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-16", + "metadataLastUpdated": "2021-06-17" + }, + "description": "OSIF is a tool that allows the user to easily fit electrochemical impedance spectra of proton exchange membrane fuel cells to a commonly accepted equivalent circuit model. The fitted parameters provide insight into the physical properties of the cell which allow the user to support experimental hypotheses.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "OSIF (Open Source Impedance Fitter)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OSIF", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This model links global demand and supply of three intertwined materials cobalt (Co), copper (Cu) and nickel (Ni) in a simulation market model with explicit consideration of electric vehicle (EV) and battery scenarios. By incorporating feedback between supply, demand, prices and capacity expansion, we quantify realistic production scenarios for both primary (mining) and secondary sources (recycling). Furthermore, to understand the magnitude of material (battery) demand from the in-use EV stock, we also consider demand to replace end-of-life (EOL) batteries. We seek to answer the following questions: 1) How will production from both primary and secondary sources react to various EV deployment scenarios and battery-chemistry combinations? 2) How much supply might promising/potential new (mining) projects contribute to supply? 3) What is the impact of reducing battery lifetime? 4) If recycling rates are increased for all 3 materials, what are the implications for Co production?", + "laborHours": 0.0, + "languages": [], + "name": "Cobalt-copper-nickel Supply Chains Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/CoCuNi", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "The finite difference optimizer (FIDO), is a tool for optimizing finite difference discretization stencils for stability. It supports uniform Cartesian meshes as well as cut-cell meshes. FIDO is a driver program with a configurable objective function that is meant to be coupled with a solver.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "FIDO", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "SEPIA (Simulation-Enabled Prediction, Inference, and Analysis) is a Python port, with user interface enhancements, of GPMSA software. GPMSA is released as LACC-06-079. \nThe software performs analysis and uncertainty quantification, by comparing experimental observations to ensembles of computer simulations. \nThis software is based on the methodology of Higdon et.al 2008, https://doi.org/10.1198/016214507000000888 .", + "laborHours": 0.0, + "languages": [], + "name": "SEPIA (Simulation-Enabled Prediction, Inference, and Analysis)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SEPIA", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "Software for converting data to DNA. The purpose of the software is to convert binary data file(s) into a collection of DNA oligo descriptions that can be synthesized and provide long-term data storage. The software is designed to target the unique properties of DNA synthesis and sequencing and include error correction codes that can recover the data despite the high error rates of the current DNA state of the art techniques.", + "laborHours": 0.0, + "languages": [], + "name": "ACOMA (Formerly LADNAC)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/adscodex", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-28" + }, + "description": "Electric grid transformation with the proliferation of distributed energy resources (DER), such as solar photovoltaic (PV), wind, advanced energy storage technologies, and electric vehicles, and the growing use of communication technologies in both transmission and distribution systems are increasing the need to capture the interactions among these systems. Advanced modeling, control, and simulation tools that can perform co-simulation of electric power systems with other domains become indispensable to accurately model these interactions. To address this need, we have developed a codebase that integrates an electric power distribution system simulator, DER models, and DER controls. The codebase is based on OpenDSS, a distribution system simulator, and an existing open source co-simulation framework called HELICS. The contribution and uniqueness of the proposed codebase is that it tailors the generic HELICS framework specifically for distribution grid-related applications. The codebase includes an OpenDSS wrapper that controls the simulation, implements advanced DER controls, and extracts power flows, voltages, and other power system element information from the the distribution network modeled in OpenDSS. Sample HELICS federates, including a federate for OpenDSS, are provided that can communicate messages through the HELICS interface. Sample federates can be modified and additional HELICS federates can be added by the user depending on their use case requirements. SEE ALSO: https://github.com/NREL/dss-cosim", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "OpenDSS-wrapper (Distribution System Co-simulator with Distributed Energy Resource Controls)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenDSS-wrapper", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "VPIC is a general-purpose Particle-In-Cell (PIC) simulation code for modeling multi-species kinetic plasmas in one, two, or three spatial dimensions. VPIC can solve equations of motion for different plasma species using kinetic or fluid descriptions. To solve for the kinetic species, VPIC employs a variety of explicit and implicit time-stepping schemes to update charged particle positions and velocities. In contrast, the fluid species is advanced in time by solving a number of fluid moment equations on a spatial grid using finite-difference methods. The electromagnetic fields are also solved on a spatial grid using either the full Maxwell equations, or a low frequency quasi-neutral approximation that uses an Ohm's law for the electric field. To couple the kinetic particle quantities with the grid-based field and fluid-moment descriptions requires that electromagnetic fields are interpolated from spatial grid points to the particle positions, and current densities are collected from the particles onto the spatial grid points. The VPIC code has been optimized for modern computing architectures and uses Message Passing Interface (MPI) calls for multi-node execution, in addition to exploiting node-level data-parallelism. The current feature set for VPIC includes a flexible input deck format capable of treating a wide variety of problems. These include: the ability to treat electromagnetic materials (scalar and tensor dielectric, conductivity, and diamagnetic material properties); multiple emission models, including user-configurable models; arbitrary, user-configurable boundary conditions for particles and fields; user-definable simulation units; a suite of \"standard\" diagnostics, as well as user-configurable diagnostics; a Monte-Carlo treatment of collisional processes capable of treating binary and unary collisions and secondary particle generation; and, flexible checkpoint-restart semantics enabling VPIC checkpoint files to be read as input for subsequent simulations. While the common use cases for VPIC employ low-order particles on rectilinear meshes, a framework exists to treat higher-order particles and curvilinear meshes, as well as more advanced field solvers.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "VPIC", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "Singular value decomposition (SVD) is a matrix factorization widely used for dimensionality reduction, data analytics, information retrieval and unsupervised learning. In the SVD's applications for big-data, usually, only the singular values are calculated. However, new methods, such as the tensor network factorization, require an accurate retrieval of a substantial number of singular vectors for truncated SVD. Also, many real-world datasets are too big to fit directly into the memory, which mandates the development of out-of-memory algorithms that work with data that is primarily on the disk. Here, building upon a previous work, we present a method for computation of the singular vectors of matrices that cannot fit into the memory. We also describe ways for reducing the communication during the computation of the left and right reflectors, needed to compute the singular vectors, and introduce a method for reducing the block-sizes, needed to hide communication on parallel file systems.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Out-of-memory SVD", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "This disclosure is related to code contributions to the LLVM compiler infrastructure (see http://llvm.org). This includes all the projects encompassed in LLVM as well as a new addition that supports the Fortran programming language. In quick summary, the LLVM Project is a collection of modular and reusable compiler and toolchain technologies. This includes C/C++, Go, runtime systems for OpenMP, and various other supporting pieces such as a debugger and linker. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "LLVM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "This disclosure covers LANL's contributions of source code to the already open source Legion Programming System. This covers example codes, contributions to the system's base source code, new features, bug fixes, associated documentation, and benchmarks. \n\nLegion is a data-centric parallel programming system for writing portable high performance programs targeted at distributed heterogeneous architectures. Legion presents abstractions which allow programmers to describe properties of program data (e.g. independence, locality). By making the Legion programming system aware of the structure of program data, it can automate many of the tedious tasks programmers currently face, including correctly extracting task- and data-level parallelism and moving data around complex memory hierarchies. A novel mapping interface provides explicit programmer controlled placement of data in the memory hierarchy and assignment of tasks to processors in a way that is orthogonal to correctness, thereby enabling easy porting and tuning of Legion applications to new architectures. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "The Legion Programming System", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "The Stable, High-Order, Cut-Cell Solver (SHOCCS), solves a variety of partial differential equations (PDE's) involving complicated bodies on a simple Cartesian mesh through the use of a novel cut-cell approach.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "SHOCCS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "This is a one-temperature diffusion code designed to model supernova explosions.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Simple Supernova Light-Curve Code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "lvPortDriver and the lvPortDriver virtual library are functions that enable LabVIEW code to run an EPICS (Experimental Physics and\nIndustrial Control System) IOC (Input/Output Controller), and communicate with it.\nThe EPICS records interface just as they would with any other asynPortDriver device.\nlvPortDriver is an asynPortDriver class (asynPortDriver is written by Mark Rivers, University of Chicago) that stores parameters in the parameter library (inherits from the base class). Arrays functions have been overridden to store data in LabVIEW's (LabVIEW is developed by National Instruments) native format.\nC wrappers permit LabVIEW to call the C++ code necessary to read and write parameters, and to be notified of changes in parameters by asyn. This notification is achieved though a user event that provides LabVIEW with the new value and status.\nA LabVIEW virtual library includes VIs that call these wrapper functions. The LabVIEW code is responsible for initializing the driver, and creating all the parameters that will be used. Parameter names are stored as variant properties, so their indicies can be looked-up via an O(log(N)) mechanism.\nThe example code included consists of a queue-driven state machine that does a simulated diagnostic measurement (does a specified number of waits for a specified time, and records the actual time between steps). A caQtDM screen is used to control the example measurement and plot the results by interfacing via an EPICS IOC with the included database.", + "laborHours": 0.0, + "languages": [], + "name": "lvPortDriver 1.X", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/lvPortDriver", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "ELEMENTS is a C++ library of mathematical functions and computer routines to support a broad range of numerical methods on diverse element types including: a) serendipity linear, quadratic, and cubic elements; b) arbitrary order tensor-product space elements b) high-order spectral elements; and d) a linear space-time element. The ELEMENTS library can be used for research and development of both continuous and discontinuous finite element methods for solving a diverse range of partial differential equations. The library has functions for calculating quantities that are commonly used in continuous and discontinuous finite element methods such as the gradient of a basis function, the Jacobi matrix, the inverse Jacobi matrix, the determinant of the Jacobi matrix, and a physical position inside the element, to name a few examples. The library supports both Gauss\u2013Legendre and Gauss\u2013Lobatto quadrature rules up to 8 quadrature points in each coordinate direction. The library has a mesh class designed for unstructured meshes and supports sub-cell decomposition that is used with advanced discontinuous numerical methods. Novel routines exist in the mesh class for connectivity across various mesh entities including: nodes, vertices, quadrature points, surfaces, elements, subcells, subcell-corners, and subcell-faces. These routines have simple interfaces and are cleverly designed for computational performance. The mesh class is designed to minimize memory usage.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "ELEMENTS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "We have developed a mechanistic model of leaf utilization of nitrogen for assimilation (LUNA V1.0) to predict the photosynthetic capacity at the global scale under different environmental conditions. We adopt an optimality hypothesis to nitrogen allocation among light capture, electron transport, carboxylation, and respiration. The LUNA model is able to reasonably capture the measured spatial and temporal patterns of the photosynthetic capacity as it explains ~55% of the global variation in the observed values of maximum carboxylation rate (Vc,max25) and ~65% of the variation in the observed values of maximum electron transport rate (Jmax25).", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "LUNA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "The Scalable Unusual Message Detector (SUD) is a scalable software program for finding anomalous log messages on a single machine or cluster in near real time. This program is able to detect unusual messages by turning the text into sets of ngrams, which are multiple sets of tokens/words per message, and comparing incoming messages with the saved ngrams. A set of rules are used for determining if the saved ngrams match an incoming message based on the size of the incoming message. This tools is intended to final unusual/anomalous messages to find critical events that system administrators are not expecting. Currently the algorithms/methods are being used on HPC\u2019s scalalble log analysis machine. Work is being done to port the algorithms/methods to a standalone tool.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Scalable Unusual Syslog Message Detector", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "The Joint Genome Institute (JGI) has developed JGI Analysis Workflow Service (JAWS) as a framework to run computational workflows. The purpose of JAWS is to improve the reusability and robustness of bioinformatic (or any) workflows in evolving and/or diverse high-performance computing (HPC), large cluster, and cloud environments. JAWS moves data and code to user-specified compute resources, executes computation, and returns results. JAWS implements Cromwell, developed at the Broad Institute, to make use of Workflow Description Language (WDL). Additionally, JAWS implements containers (compatible with Docker, Shifter, and Singularity) to ensure use of well-defined compute environments and workflow task codebases. 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The Catch2 unit-testing framework currently lacks support for handling C-style assertions via the \"assert\" macro. The source code being disclosed adds the ability to verify that C-style assertions are caught when expected and registered with the Catch2 framework by making direct additions to the Catch2 software. This source code will be contributed back to the Catch2 project on Github and copyright will need to cover any alterations required by the project owners on Github including alterations to source code, documentation, testing, etc. Ideally, the changes made herein will be released under the Boost Software License Version 1.0.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Catch2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/catchorg/Catch2/blob/devel/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-12" + }, + "description": "Truchas-PBF is a specialization of LANL's open source Truchas software (LA-CC-15-097) that is designed to simulate the powder bed fusion (PBF) additive manufacturing process for metal materials. 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These features of the data set make it uniquely positioned in the deep representation learning field because of its compositionally and hierarchical organization, while retaining diverse types of variation in the realizations.", + "laborHours": 0.0, + "languages": [], + "name": "HangulFonts v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BouchardLab/HangulFontsDatasetGenerator.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This license is for a computer-science focused subset of the XCP-3 developed shared component libraries (SHACL), referred to as SHACL Utilities. 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The libraries are semi-independent repositories and are developed with an emphasis on performance and sharing code between applications.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Shared Component Library - Utilities", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "As HPC physics simulations grow ever larger in size, accessing the data generated by them becomes an increasingly difficult challenge. 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Data is stored as Subject-Predicate-Object triples that can be searched for in any combination and can return ranges of data instead of just a single data point, allowing for fast, parallel extraction of large amounts of data from storage in significantly less time than existing methods are able to obtain the same data.", + "laborHours": 0.0, + "languages": [], + "name": "HXHIM: The Hexa-dimensional Hashing Indexing Middleware", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/hxhim", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "This software is an open-source Python library that provides a collection of advanced algorithms to address computational imaging and inverse problems arising in the analysis of scientific data. 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Supporting visualization and analysis of results will also be provided. 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James Ahrens (Director, ISTI & Senior Staff Scientist, Data Science at Scale, CCS-7) is the founder and design lead of ParaView. With over a million downloads, ParaView is one of the leading data analysis and visualization applications and is widely used by scientific users within the Department of Energy Office of Science (SC) and the DOE National Nuclear Security Agency (NNSA). VTK is an open-source software visualization library based on C++ and includes interface layers for Python and Java. ParaView extensively uses the VTK libraries for its graphics and analysis. First open-sourced under LA_CC Number 99_44, this work has been continuously funded over the years under Department of Energy contracts. The goal of this software project is to continue the collaborative development of open-source general use case contributions to ParaView and VTK by LANL researchers. The developed software will provide open-source computer science algorithms, interfaces, filters, visualization approaches, and data analysis modules that will be merged into ParaView and VTK for general use by ParaView and VTK users. 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The signatures applied must be consistent in role, size and placement on the pdf drawings. The software provides the ability to process these signatures in a batch mode, signing multiple pdf drawings, selectable by either folder and/or file selections.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Sign Drawings (Electronic Signatures)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Ethon is a research code that implements well-known hydrodynamics methods (finite-volume and Discontinuous Galerkin) to solve the compressible Euler equations with a simple ideal gas equation of state and no additional physics using a block-based adaptive mesh refinement (AMR) infrastructure. 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The software toolset is developed at Los Alamos National Laboratory for the National High Magnetic Field Laboratory user program within the scope of the High Magnetic Field Science Designated Unclassified Subject Area.", + "homepageURL": "https://github.com/ffb-LANL/High-Magnetic-Field-Science-Toolset", + "laborHours": 0.0, + "languages": [], + "name": "High Magnetic Field Science Toolset", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ffb-LANL/High-Magnetic-Field-Science-Toolset", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "v1.5" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-02" + }, + "description": "We develop a lightweight, easy-to-use plotting package based on Python and matplotlib for scalar data visualization. The package contains eight plotting functions that can efficiently and conveniently render one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) regular-grid scalar data into publication-quality figures of various formats. These plotting functions include plotting 1D scalar data as a curve or a set of colored scatter points, showing 2D regular-grid scalar data as an image, wiggles, or contours, and displaying 3D regular-grid scalar data as a volume or three orthogonal slices in the image or contour form. We develop this package to facilitate quick rendering of 1D, 2D and 3D scalar data into visually decent forms with simple commands and options. The package is also capable of rendering various fonts, subscripts, superscripts, and mathematical symbols on plots in a consistent manner. Example plots demonstrate the efficiency, convenience, and versatility of our plotting package in generating high-quality plots. We make our plotting package open-source at GitHub, a United States-based global company that provides hosting for software development version control.", + "laborHours": 0.0, + "languages": [], + "name": "Pymplot: An open-source, lightweight plotting package based on Python and matplotlib", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pymplot", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-28" + }, + "description": "fuelcell is a Python package designed to standardize and streamline the analysis of electrochemical data. 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The Conditioner is a command-line tool for reading ADMS data from ZMQ, resampling, and exporting over a websocket. The Chart is an example of a charting tool for ADMS applications, using a ZMQ message bus.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Real Time Streaming Data visualization tooling (RTS Data Vis App)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rts-vis-app", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "From a single data description file, this package generates a simple but complete RESTful web interface to a relational database, in the form of containers that run in a Docker environment. This initial version produces containers that are intended for use on the NERSC Spin platform. It was developed as a foundation for the smart catalog created for LDRD FY20 ACTS: Accelerating COVID-19 Testing with Screening.", + "laborHours": 0.0, + "languages": [], + "name": "REST Interface Generator (RESTInG) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dani-lbnl/resting.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "vchendrix@lbl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets) uses a data brokering approach to synthesize diverse earth science data from a variety of remote sources in real-time without the need for additional storage. 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Supporting our data synthesis model is a plugin framework that allows developers to map data sources of interest to the BASIN-3D synthesis model.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets (django-basin3d)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BASIN-3D/django-basin3d", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2021-06-24" + }, + "description": "The Distributed Energy Resource Cybersecurity Framework (DERCF) provides U.S. federal government sites with a tool to assess the cybersecurity posture\u2014or health\u2014of their distributed energy resource (DER) systems.", + "homepageURL": "https://dercf.nrel.gov", + "laborHours": 0.0, + "languages": [], + "name": "DERCF (Distributed Energy Resource Cybersecurity Framework)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://dercf.nrel.gov/auth/#/register", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://dercf.nrel.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2024-07-01" + }, + "description": "cloud-fs (Cloud File System Utilities) is a generalized file-system handler that will dynamically determine if files are local or on the cloud (currently AWS) and perform basic file-system operations.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "cloud_fs (Cloud File System Utilities) [SWR-21-83]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/cloud_fs", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2021-06-24" + }, + "description": "KSSOLV is a MATLAB toolbox for solving Kohn-Sham density functional theory based electronic structure eigenvalue problems. It uses an object oriented features of MATLAB to represent atom, molecules, wavefunctions and Hamiltonians and their operations. It is designed to make it easier for users to prototype and test new algorithms for solving the Kohn-Sham problem. KSSOLV2.0 contains significant improvement over the original KSSOLV described in a paper published in ACM Transaction on Mathematical Software (attached). In addition to performing ground state calculation for small molecules, it can also perform geometry optimization for both molecules and solids. It uses standard pseudopotentials and implements local density approximation, generalized gradient approximation and hybrid functionals. Future releases will also include time-dependent DFT and post DFT calculations such as the GW quasi-particle energy calculation and Bethe-Salpeter equation solver for optical absorption.", + "laborHours": 0.0, + "languages": [], + "name": "Kohn-Sham Solver (KSSOLV) v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/kssolv2.0/src/release", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2021-06-24" + }, + "description": "The DIVA software interfaces a process in which researchers design their DNA with a web-based graphical user interface (DeviceEditor), submit their designs to a central queue, and a few weeks later receive their sequence-verified clonal constructs. Each researcher independently designs the DNA to be constructed with a web-based BioCAD tool, and presses a button to submit their designs to a central queue. Researchers have web-based access to their DNA design queues, and can track the progress of their submitted designs as they progress from \"evaluation\", to \"waiting for reagents\", to \"in progress\", to \"complete\". Researchers access their completed constructs through the central DNA repository. Along the way, all DNA construction success/failure rates are captured in a central database. his success/failure rate data can be leveraged to refine the DNA assembly design process.", + "homepageURL": "https://agilebiofoundry.org/capabilities/diva-biocad", + "laborHours": 0.0, + "languages": [], + "name": "DIVA/DeviceEditor (DIVA) v5.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://agilebiofoundry.org/capabilities/diva-biocad", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://agilebiofoundry.org/capabilities/diva-biocad", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2021-06-24" + }, + "description": "H5bench benchmark suite contains a list of applications that are used to measure the HDF5 I/O performance from various aspects.", + "laborHours": 0.0, + "languages": [], + "name": "H5bench: a benchmark suite for parallel HDF5 (H5bench) v0.6", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/h5bench", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lioukaihsin@utexas.edu" + }, + "date": { + "created": "2021-06-27", + "metadataLastUpdated": "2021-06-27" + }, + "description": "PARSEC is a computer code that solves the Kohn-Sham equations by expressing electron wave-functions directly in real space, without the use of explicit basis sets. It uses norm-conserving pseudopotentials (Troullier-Martins and other varieties). It is designed for ab initio quantum-mechanical calculations of the electronic structure of matter, within density-functional theory.\nPARSEC is optimized for massively parallel computing environment, but it is also compatible with serial machines. A finite-difference approach is used for the calculation of spatial derivatives. Owing to the sparsity of the Hamiltonian matrix, the Kohn-Sham equations are solved by direct diagonalization, with the use of extremely efficient sparse-matrix eigensolvers. Some of its features are: Choice of boundary conditions: periodic (on all three directions), or confined. Structural relaxation. Simulated annealing. Langevin molecular dynamics. Polarizability calculations (confined-system boundary conditions only). Spin-orbit coupling. Non-collinear magnetism.", + "laborHours": 0.0, + "languages": [ + "Fortran", + "Python" + ], + "name": "Pseudopotential Algorithm for Real-Space Electronic Structure Calculations", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/real-space/parsec", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "version": "1.4" + }, + { + "contact": { + "email": "lioukaihsin@utexas.edu" + }, + "date": { + "created": "2021-06-27", + "metadataLastUpdated": "2021-06-27" + }, + "description": "NanoGW can perform the following calculations:\n\n1. Linear-response time-dependent density functional theory (by solving Casida equation)\n2. Full-frequency GW calculation with or without LDA vertex function (does not support spin-orbit coupling)\n3. Construct and solve Bethe-Salpeter equation\n\nNanoGW has been tested thoroughly and optimized for molecules and nanoclusters. It runs particularly efficient for small-size (less than 30 atoms) molecules or clusters. This package can also deal with crystalline systems. However, its functionality for dealing crystals has not been thoroughly tested yet.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "NanoGW", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/real-space/nanogw", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-06-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python library for analyzing the internal structure of deep neural networks.", + "laborHours": 22374.4, + "languages": [ + "Python" + ], + "name": "pnnl/DeepDataProfiler", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/deepdataprofiler", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-28", + "metadataLastUpdated": "2021-06-28" + }, + "description": "Hybrid Power Plants (HPPs) have the potential to increase the value of renewable energy systems and decrease their costs through shared development (e.g., permitting) and infrastructure (e.g., collection system). Prior work has identified potential cost savings and technical and economic performance improvements for solar plus storage plants. However, additional research is needed to understand cost drivers that are specific to hybrid wind plants. Here we analyze the potential for shared infrastructure cost savings at one type of hybrid plant: wind plus solar photovoltaic (PV). To perform this analysis, we developed a new open-source, Python-based cost modeling tool: the Hybrid Balance-of-System (BOS) Systems Engineering model (HybridBOSSE). HybridBOSSE is an extension of NREL's LandBOSSE tool.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HybridBOSSE (Hybrid Balance-of-System (BOS) Systems Engineering Model)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HybridBOSSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-06-29", + "metadataLastUpdated": "2022-10-17" + }, + "description": "SAND2021-8720 O PyRIID is a Python package that provides methods for generating gamma spectra synthetically and offers models that can input a gamma spectrum and predict what radioisotope is present in it. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525", + "laborHours": 0.0, + "languages": [ + "Python 3.5 +" + ], + "name": "PyRIID v.2.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyriid", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0.0" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-06-29", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This software is a python package that interacts with the Application Programming Interface (API) suite provided by Deep Lynx. A python codebase may import this package in order to have access to these methods for communicating with a Deep Lynx instance.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deep-Lynx-Python-Package", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-Python-Package", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-06-29", + "metadataLastUpdated": "2021-06-29" + }, + "description": "pyMPI is an implementation of the Message Passing Interface (MPI) in the python language. pyMPI is intended to support fast development of actual or prototypical parallel applications as well as to provide a tool for teaching parallel programming methods without the intricacies of higher level languages.", + "homepageURL": "https://sourceforge.net/projects/pympi", + "laborHours": 0.0, + "languages": [], + "name": "pyMPI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/pympi", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-06-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "CFA ARENA is a novel programming model with the support of a runtime targeting asynchronous data-centric execution paradigm in a distributed system. All the machine nodes in ARENA are connected by a ring network to bring the specialized computation to the data rather than the reverse to minimize data movement. The programming interfaces are implemented using C++", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/arena", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/arena", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-07-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "We are using existing deep learning modeling architectures and data representation techniques, but we are consolidating the methods into a single set of training and evaluation scripts. Additionally, we test and evaluate the performance of the models on the largest set of solubility measurements available to date.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/solubility-prediction-paper", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/solubility-prediction-paper", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-01", + "metadataLastUpdated": "2021-07-01" + }, + "description": "Graphene U-Net is a library that provides a simplified platform for training deep neural networks for the task of microscopy image segmentation. It contains functions and classes that make the process of training a neural network simple such that non-ML experts can train and evaluate models on their own datasets. It uses Pytorch as a backend and can run on both CUDA-enable GPUs and CPUs. It contains the main library file Microscopy_Unet.py as well as unet.py which contains the UNET model used for this software. This can be replaced with any other fully convolutional deep learning architecture with relative ease.", + "laborHours": 0.0, + "languages": [], + "name": "Graphene U-Net v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnlcomputerarch/graphene-u-net", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-01", + "metadataLastUpdated": "2021-07-01" + }, + "description": "The Web of Registries Search (WoRs) is a web based software application that enables users to search for publicly available biological parts using keywords or sequence fragments. For the initial version (1.0.0) of the application, WoRS targets 10 sources of biological part data: the GenBank NIH genetic sequence database (https://www.ncbi.nlm.nih.gov/genbank/), the iGem parts registry (parts.igem.org), the Addgene plasmid repository (https://www.addgene.org/), and 7 Inventory of Composable Elements (ACS Synbio, JGI, JBEI, JBEI Public, ABF, SynBerc, ABF Public) registry instances. WoRs has built-in automated web scrapers which extract data from sources that do not have a public or well-defined application programming interface (API). They extract as much public data as they can find and create a searchable index to speed up searches. Included in the indexed information is the source of the information.", + "laborHours": 0.0, + "languages": [], + "name": "Web of Registries Search (WoRS) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/wors", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-01", + "metadataLastUpdated": "2021-07-01" + }, + "description": "Enhances accessibility of the Automated Recommendation Tool (ART), by adding on a graphical user interface, user authentication, and by exposing a REST API. Enables authenticated remote users and applications to interface with ART and to leverage remote computing resources to perform runs.", + "homepageURL": "https://sites.google.com/lbl.gov/art/home", + "laborHours": 0.0, + "languages": [], + "name": "ART Front End v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/art/licensing-code", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/art/home", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-01", + "metadataLastUpdated": "2021-07-08" + }, + "description": "Multi-modal Free-moving Data Fusion (MFDF) is a python package that implements low and high-level functionality for performing qualitative and quantitative gamma-ray imaging analyses. Such analyses enable the use of gamma-ray spectrometers and/or imagers to estimate the distribution and quantity of radiological materials in an environment. Free-moving 3D imaging requires additional information about the 3D trajectory and orientation of the system, however all of these methods can be applied to 2D static gamma-ray imaging as well. The package includes methods (MLEM and MAP) for distributed source reconstruction, methods (PSL) for point source reconstruction, the ability to ingest and utilize quantitative detector response functions (for absolute analyses), and the ability to perform 3D estimation of dose-rates from quantitative reconstructions.", + "homepageURL": "https://ipo.lbl.gov/multimodal-free-moving-data-fusion-for-gamma-ray-imaging-analysis", + "laborHours": 0.0, + "languages": [], + "name": "Multi-modal Free-moving Data Fusion (MFDF) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/multimodal-free-moving-data-fusion-for-gamma-ray-imaging-analysis", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/multimodal-free-moving-data-fusion-for-gamma-ray-imaging-analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Here we have developed a pipeline for the fast evaluation of viral emerging risks (FEVER) that generates primer and probe sets for genetically diverse viruses. The goal of probe design is to produce a short nucleotide sequence (called a K-mer, as it is of length K) that reacts with SARS-CoV-2 without also reacting to background material that may be present in the sample that is being tested. Other desirable properties of the probe, making it more effective in the experimental setup, include maintaining a high G/C content and reducing the \"hairpin propensity\" (ie, the tendency of the probe string to fold over on itself) by ensuring that any self-complementary pairs of sub-strings in the probe are sufficiently short. The mathematical formalization of the problem is expressed in terms of a constrained optimization, with G/C content and length of self-complementary sub-strings taken as constraints, while maximizing coverage of the probe. A probe is said to \"cover\" a SARS-CoV-2 sequence if the probe's K-mer appears as a sub-sequence of that sequence. Thus, coverage is defined as the number of sequences in the database that are covered by the probe. \"Exact\" coverage corresponds to an exact match of probe and sub-sequence; \"off-by-m\" coverage corresponds to an approximate match in which all but m nucleotides agree. Given a database of SARS-CoV-2 sequences, the single probe design problem is to find a string of length K, subject to the constraints of G/C content and hairpin aversion, which covers as many SARS-CoV-2 sequences as possible. For the multi-probe design problem, we seek P probes instead of just one, and a P-probe design is said to cover a SARS-CoV-2 sequence if any one of the probes cover it. Selection of K=31 was used because it was short enough that a single probe can cover a large fraction of the sequences in the SARS-CoV-2 database, but long enough that it won't accidentally cover potential background sequences. ", + "laborHours": 0.0, + "languages": [], + "name": "FEVER Probe Design Algorithm", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jt-lanl/fever-probes", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The software in development is a model of convection to be added to a public domain 1-dimensional supernova code. The supernova code models the collapse and explosion of stars. Without a convection module, the 1-dimensional code does not include the effects of convection under an entropy gradient. The modules that will be integrated into this code will calculate this convection.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Core-Collapse Supernova Code with New Convection Algorithms", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Two quantum graph algorithms (as python scripts) that run on the D-Wave Quantum Annealer are included for copyright. The Quantum Graph Partitioning software takes a graph as input and the number of partitions of equal size desired. This is transformed into a quadratic unconstrained binary optimization (QUBO) that is run as a quantum-classical algorithm using D-Wave/qbsolv. The Quantum Community Detection software takes a graph and the maximum number of communities/clusters desired. This is transformed into a quadratic unconstrained binary optimization (QUBO) that is run as a quantum-classical algorithm using D-Wave/qbsolv.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Quantum Graph Algorithms", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "ACD is a collection of python routines for detecting anomalous changes in pairs of images. The images can be panchromatic or multispectral (even hyperspectral), and for most of the algorithms in the collection, the two images need not have the same number of spectral bands. The general idea is to distinguish anomalous changes, which are assumed to be rare, from pervasive differences, which are assumed to occur throughout large portions of the image. The anomalous changes are candidates for actual, possibly interesting, changes on the ground, while the pervasive differences might for instance be due to different illumination or calibration during the acquisition of the two images.", + "laborHours": 0.0, + "languages": [], + "name": "ACD - Anomalous Change Detection software in python", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jt-lanl/acd", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The Geppetto application, developed in collaboration between Los Alamos National Laboratory and the DARPA MediFor program, provides an analysis platform for deepfake video detection. Geppetto provides a web interface and backend software that orchestrates the upload and analysis processes for a set of videos. This disclosure covers the user interface for Geppetto. ", + "laborHours": 0.0, + "languages": [], + "name": "Geppetto User Interface (UI)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/geppetto-ui", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "FlexFlow is a deep learning framework and engine, built using the Legion Programming System, that accelerates distributed deep neural network training by automatically discovering fast parallelization strategies. This is achieved by using a guided randomized search to find a fast parallelization strategy for a specific parallel machine architecture. To accelerate this search, FlexFlow introduces a novel execution simulator that can accurately predict a parallelization strategy\u2019s performance and is three orders of magnitude faster than prior approaches that execute each strategy. FlexFlow currently out-performs common industry software frameworks like Google's TensorFlow/Keras and Facebook's PyTorch by factors ranging from 3 to 15 times.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "FlexFlow ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-06" + }, + "description": "Versatile Object-oriented Toolkit for Coarse-graining Applications (VOTCA) is a Coarse-grained modeling package, which focuses on the analysis of molecular dynamics data, the development of systematic coarse-graining techniques as well as methods used for simulating microscopic charge (and exciton) transport in disordered semiconductors. It was originally developed at the Max Planck Institute for Polymer Research. VOTCA has 2 major parts, the Coarse-graining toolkit (VOTCA-CSG) and the Excitation Transport Toolkit (VOTCA-XTP). All of them are based on the VOTCA Tools library, which implements shared procedures. Coarse-graining toolkit (VOTCA-CSG) VOTCA-CSG supports a variety of different coarse-graining methods, incl. (iterative) Boltzmann Inversion, Inverse Monte Carlo, Force Matching (also known as the multiscale coarse-graining method) and the Relative entropy method and hybrid combinations of those as well as optimization-driven approaches, like simplex and CMA. To gather statistics VOTCA-CSG can use multiple molecular dynamics package incl. GROMACS, DL_POLY, ESPResSo, ESPResSo++, LAMMPS and HOOMD-blue for sampling. Excitation Transport toolkit (VOTCA-XTP) VOTCA-XTP allows to simulate excitation transport and properties. Therefore, it provides its own implementation of GW-BSE and a basic DFT implementation, employing localized basis sets. Polarized QM/MM calculations for excited states are provided in the Thole framework. It features interfaces to more external Quantum Chemistry packages (Gaussian, NWChem and ORCA) for large scale production runs.", + "laborHours": 0.0, + "languages": [], + "name": "Contribute to VOTCA package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/votca/votca", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The program \u201cEMCCD Calibration\u201d is software to provide accurate calibration of the gain and analogue-to-digital conversation factor for a variety of scientific imaging devices, such as electron-multiplying charge-coupled device (EMCCD) cameras, complementary metal-oxide semiconductor (sCMOS), and intensified charge coupled device (ICCD) cameras. The software implements new calibration methods that are described in a manuscript intended for publication under the title \u201cFrom Noise to Harmony: Calibration Methods for Electron Multiplying CCD Cameras\u201d. The software provides ready-to-use tools for researchers using EMCCD, sCMOS, or ICCD cameras.", + "laborHours": 0.0, + "languages": [], + "name": "EMCCD Calibration", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ryand-LANL/EMCCD-calibration", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "MF-LBM is a high-performance lattice Boltzmann code for direct numerical simulation of three-dimensional multiphase flow in porous media. The main features of the code include: 1) implemented with advanced multiphase and wetting models that enable simulation of supercritical CO2 (scCO2) and brine displacement in real rock geometries; 2) extensively optimized for modern SIMD/SIMT processors/co-processors, such as GPU; 3) based on MPI-OpenACC/OpenMP hybrid programing model that enables high portability; 4) overlapped communication and computation that enables high scalability; 5) designed for flow simulations on digital rock images or complex microfluidic devices.", + "laborHours": 0.0, + "languages": [], + "name": "MF-LBM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MF-LBM", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "ARMO is a software tool for solving Alignment and Registration problems via Mathematical Optimization.\nGiven different 3D point clouds of overlapping areas, the tool can fix alignment issues by finding the optimal rotation and translation operations.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "ARMO", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Analysis scripts associated with \u201cHydraulically-vulnerable trees survive on deep-water access in a tropical forest community\u201d\n\nThis dataset contains R scripts for all the analyses to reproduce the manuscript, \u201cChitra-Tarak, Rutuja, Chonggang Xu, Kristina Anderson-Teixeira, Jeff Chambers, Matteo Detto, Boris Faybishenko, Rosie Fisher, Ryan Knox, Charlie Koven, Lara Kueppers, Nobert Kunert, Stefan J. Kupers, Nathan G. McDowell, Brent Newman, Steve Paton, Laurent Ruiz, Lawren Sack, Jeffrey Warren, Brett Wolfe, Cynthia Wright, S. Joseph Wright, Joseph Zailaa, Sean M. McMahon. Hydraulically-vulnerable trees survive on deep-water access in a tropical forest community. To be submitted\u201d. These scripts are divided into two parts: the first set of scripts prepare files for running and processing simulations from the model, Energy Exascale Earth System Land Model-Functionally Assembled Advanced Terrestrial simulator (ELM-FATES) to obtain soil water availability by depth at BCI, Panama, and the second set of scripts are associated with all the analyses related to the inverse modeling for tree rooting depths at BCI. ", + "laborHours": 0.0, + "languages": [], + "name": "Analysis scripts associated with manuscript, \u201cHydraulically-vulnerable trees survive on deep-water access during droughts in a tropical forest\u201d", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/bci.elm.fates.hydrology", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-09-20" + }, + "description": "Los Alamos National Laboratory is embarking on a project to set a new standard in genome mapping through development of unique 4D genomics capabilities. We will develop and deploy open source software tools to discover fundamental cellular functions that are hijacked by viruses to cause disease. Given LANL\u2019s breadth of expertise in genomics, high performance computing, and advanced visualization, we are uniquely positioned to build the nascent 4D genomics field to help determine the 4D spatial-temporal architecture and dynamic reconfiguration of the human genome for any application. The goal of this software project is to create a web-based interactive application, with a complete web software stack, that provides a way to browse, visualization, query and annotate curated sets of related genomic data. The software will provide an intuitive interface to this complex data, utilizing a set of custom and off-the-shelf components integrated into specific configurations of coordinated data views. To achieve this, the project will provide components, algorithms and integrated applications and will be available as an open source project that can be used by others to view related sets of data. The primary users of this platform will include institutional users at Los Alamos National Laboratory, scientists and researchers from collaborative institutions, and others interested in exploring multi-modal genomic databases.", + "laborHours": 0.0, + "languages": [], + "name": "4D Genome Browser", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/4DGB", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The Nuclear Data Access Tool Kit (NDATK) is a C++ API that provides continuous energy neutron and photon libraries corresponding to multigroup neutron libraries. It uses libraries named to match Nuclear Data Interface (NDI) libraries and tells the host code where the continuous energy data is. Like NDI, it includes multi-temperature data.", + "laborHours": 0.0, + "languages": [], + "name": "Nuclear Data Access Tool Kit NDATK", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/NDATK", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The SHIELDS Particle Tracing Model (PTM) is a large-scale particle tracing code, primarily intended for magnetospheric applications. It provides a fast, parallel computing-friendly, and versatile framework for tracing charged particles in arbitrary electric and magnetic fields. To support a broad range of test particle applications, full Lorentz motion can be modeled as well as guiding center motion. Switching strategies allow accurate and efficient test particle tracing across regions where the guiding center approximation may not be maintained. PTM supports tracing of particle motion both forwards and backwards in time. For backwards tracing, PTM can launch particles from a specified location and trace until stopping criteria are met. These stopping criteria can include crossing a surface in space, or a time limit. For forwards tracing particles can be launched from specified points or spatial regions. The code is designed to allow many applications without requiring recompilation, instead providing a rich, user-configurable interface that allows use of different modes at runtime. Model results are stored in user-selected format for post-processing including Liouville mapping of particle fluxes from source to target location. PTM includes pre-processing for field configurations, tools for setting up runs, and post-processing capabilities to enable scientific use. Sample applications include specifying the geosynchronous particle boundary for inner magnetosphere modeling, and determining access of solar energetic protons.", + "laborHours": 0.0, + "languages": [], + "name": "SHIELDS-PTM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SHIELDS-PTM", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Anaerobic Digestion Model No 1 (ADM1) is a mathematical model used by researchers to simulate the anaerobic digestion process that converts organic matter into biogas. The reduction of biosolids during anaerobic digestion reduces the solids handling cost while the biogas produced can be used to generate heat and electricity to offset the cost of heat and electricity at water resource recovery facilities. The original version of the ADM1 developed by the International Water Associations Task Group for Mathematical Modelling of Anaerobic Digestion Processes was created to describe the kinetics and stoichiometry of the primary biochemical processes in anaerobic digestion. The EES-16 team modified the ADM1 by adding mathematical terms which separate the solids retention time from hydraulic retention time to simulate novel AD technologies, integrating the model into one package in C++ language, introducing sophisticated implicit solvers by linking it to the PETSc package which allows fast and scalable (parallel) solution for the system of differential equations in the ADM1. Also, we created an easy-to-navigate interface with tutorial examples documented in the ipython notebook allowing customization of the operating conditions and reactor configurations for the simulation of the model.", + "laborHours": 0.0, + "languages": [], + "name": "Anaerobic Digestion Model", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ADM1F", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "I am submitting an umbrella/blanket disclosure because I am working on several inter-related projects in a fast-moving research area. The general theme is statistical analysis and visualization of SARS-CoV-2 viral genetic sequence data in order to learn about epidemiology. Examples of research questions are: How do viral genetic relationships relate to contact tracing links? How does viral genetics reflect signatures of transmission from one person to another? Do some genetic variants have a consistent transmission advantage?", + "laborHours": 0.0, + "languages": [], + "name": "Blanket Phylogenetic and genetic analyses of SARS-CoV-2 epidemiology", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eeg-lanl/sarscov2-selection", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Alignment of replicate time series can be useful for identifying shared but time-warps behavior in time series data such as monitoring temperature or network communication patterns for cyberphysical systems. This learning of common behavior is a first step for identifying abnormal behavior such as intrusion or anomalies. We developed the alignts R package to provide an R implementation of Listgarten (2004) with advancements described in Grosskopf (submitted 2021). The package is programmed in R and Fortran 95 with OpenMP support. The package includes functions for aligning a collection of nominally replicate time series, making forecast predictions of future states conditioned on the current data, and carrying out particle filtering for estimating uncertainty in the state of the system in an on-line data collection environment. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "alignts", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "singularity-eos is a library that provides a unified interface and performance portable implementations of equations of state (EOS). The library includes a set of simple analytic models that are all published in the open literature and generic tabulated EOS capabilities that build on a generic table interpolation library that is being released under a separate disclosure. However, absolutely no tabulated data for material EOS is included in singularity-eos. Instead, users of singularity-eos need to provide the tabulated data.", + "laborHours": 0.0, + "languages": [], + "name": "singularity-eos", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/singularity-eos", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "tkonstant@bnl.gov" + }, + "date": { + "created": "2021-07-04", + "metadataLastUpdated": "2021-07-05" + }, + "description": "Code and data for training CNN-Encoder-Decoder model described in the publication 'Noise reduction in X-ray photon correlation spectroscopy with convolutional neural networks encoder-decoder models.'", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "CNN-Encoder-Decoder Model", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bnl/CNN-Encoder-Decoder", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-06", + "metadataLastUpdated": "2021-07-06" + }, + "description": "Watchr is a Java library that processes time-series data and generates HTML graphs. It is primarily used to track the performance of subroutines over time. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.\nSAND2021-7299 O", + "laborHours": 0.0, + "languages": [ + "Java", + "Java" + ], + "name": "watchr-core", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/watchr-core", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-07", + "metadataLastUpdated": "2021-07-07" + }, + "description": "The CENS code translates Evaluated Nuclear Structure Data File, ENSDF, into application-specific formats, such as\nReference Input Parameter Library, RIPL, as well as into a generic XML format. Although ENSDF contains the most updated\nnuclear structure information, its complex format and philosophy of purely experimental basis often prevent direct use in\npractical applications in fundamental and applied science. CENS reads the adopted discrete levels, their spin and parity,\nand gamma-ray branching ratios etc. compiled in ENSDF, and estimates some missing information as needed by\nconsidering the statistical properties of nuclear structure, then prints out the nuclear structure data in more readable\nformats. CENS is written in C++, about 5,000 lines in total. A user's manual is also provided in HTML in the same package.\n[LAUR 21-22523]", + "laborHours": 0.0, + "languages": [], + "name": "CENS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/toshihikokawano/CENS", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-07", + "metadataLastUpdated": "2021-07-07" + }, + "description": "GoFigure is a code repository for a set of tools for the analysis and retrieval of technical images, or figures, such as drawings and plots. The goal of these tools is to automate the understanding of technical content contained in scientific images. Computer vision algorithms are automating the analysis of content in images and these tools will extend these innovations for images of scientific content. GoFigure includes tools for analyzing the context, topology and shape information in images, as well as graph-based matching algorithms for fast retrieval of similar images. These components are written in Python, a high-level programming language that takes advantage of the Python eco-system of high-quality open-source packages for computer vision, graph algorithms and machine learning.", + "laborHours": 0.0, + "languages": [], + "name": "GoFigure", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GoFigure-LANL/GoFigure", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-07-08", + "metadataLastUpdated": "2021-10-01" + }, + "description": "The Water Technoeconomic Assessment Pipe-Parity Platform (WaterTAP3) was developed under the National Alliance for Water Innovation (NAWI) to facilitate consistent technoeconomic assessments of desalination treatment trains. The WaterTAP3 is an analytically robust modeling tool that can be used to evaluate water technology cost, energy, environmental, and resiliency tradeoffs across different water sources, sectors, and scales. The model simulates steady-state water treatment train performance and costs including flow and constituent mass balance across unit processes, based on source water conditions, configurations of treatment technologies, and system-level techno-economic assumptions. Users can build a new treatment train by connecting any number of unit processes, specific for their context and system, or selecting a train from the treatment train library. The model contains various technical and cost parameter options for a range of treatment processes and a library of influent water quality characteristics for a variety of source waters and case studies. Users can customize water quality parameters to evaluate the technology performance in their context. The model can be set up for different assessment needs including simulation, optimization, and uncertainty and sensitivity analyses. The results from WaterTAP3 can help identify trade-offs among the different system performance metrics, with insight on how particular technologies or systems promote pipe-parity. The flexibility and comprehensive scope of the tool makes it a promising solution to industry-wide water technoeconomic evaluations, leading to more informed water investment decisions and technologies. As a user-friendly, open-source platform, WaterTAP3 can be used by industry, academia, policymakers, planners, and those with or without extensive analytical experience.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "WaterTAP3 (The Water Technoeconomic Assessment Pipe-Parity Platform)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WaterTAP3", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-12", + "metadataLastUpdated": "2021-07-12" + }, + "description": "NchooseK represents a suite of software tools that seeks to unify and facilitate the exploitation of circuit-model quantum computers and quantum annealers. Numerous types of software will be included in this suite including compilers, preprocessors, optimizers, translators, run-time systems, support tools and scripts, and technology demonstrations.", + "laborHours": 0.0, + "languages": [], + "name": "NchooseK", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/NchooseK", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-07-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Verification and Validation Assuring Reliability and Security (VARS) project team has developed the proof-of-concept VARS framework which will be implemented in the form of a software tool called Risk-Informed Verification and Validation Recommendation (RIVVR). The framework will provide Energy Delivery System (EDS) stakeholders with cybersecurity focused verification and validation (V&V) approach which includes list of potentially relevant vulnerabilities to test or address, pre-procurement guidance, and separate lists of relevant standards, tools, and techniques (ST2) to be considered by utilities and vendors", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "VARS Framework", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-12", + "metadataLastUpdated": "2021-07-12" + }, + "description": "Distributed energy resource management systems (DERMS) are being deployed in feeders with high distributed energy resource (DER) penetration to provide visibility of DERs and enable DER control strategies for grid operators. DERMS can support centralized grid controls by aggregating individual DER information into a single virtual DER model. This codebase creates algorithms for a DERMS platform that are able to aggregate a set of DERs that can be modeled as batteries, create a virtual battery model for centralized grid controls, and dispatch power setpoints to the individual DERs based on a desired virtual power setpoint received from the centralized grid control. It integrates with existing co-simulation frameworks and models for buildings, DERs, and distribution systems. While the DERMS is designed to work with batteries, it can be used with any DER that can be defined by a generalized battery model.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Virtual Battery Aggregator (Virtual Battery Aggregator for Distributed Energy Resource Management Systems)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/virtual-battery-aggregator", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ahearin@anl.gov" + }, + "date": { + "created": "2021-07-13", + "metadataLastUpdated": "2021-07-13" + }, + "description": "Halotools is a specialized python package for building simulation-based models of cosmological structure formation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "halotools", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/astropy/halotools", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "0.7" + }, + { + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-07-14", + "metadataLastUpdated": "2023-08-14" + }, + "description": "This is a basic package for creating Bewley Lattice Diagrams in Python. https://nrel.github.io/bewley", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "Bewley Lattice Diagram [SWR-19-17]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bewley", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-14", + "metadataLastUpdated": "2021-07-14" + }, + "description": "Intuitive GUI for manipulating microscope stages, allowing to align crystallographic data with stages, allowing to align crystallographic data with stage coordinates and microscope images. Simulates kinematic diffraction patterns and Kikuchi line patterns. Simulated patterns can be displayed as overlay to actually measured data, allowing manual fingerprinting and angular alignment. Crystallographic data is fed to the program in form of CIF (crystallographic information file) files, which are available from many databases and cover virtually all crystal structure ever reported in any journal. Actual goniometer scales can be linearized by lookup tables, program can be used with any microscope goniometer, double tilt and tilt-rotation type. Software requirements: Win32 platform (XP); Compiler/Version: Borland C++ Builder 5; Type of files: Executable modules; Hardware requirement: PC", + "laborHours": 0.0, + "languages": [], + "name": "KSpaceNavigator (KSN)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/kspacenavigator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-14", + "metadataLastUpdated": "2021-07-14" + }, + "description": "Lightweight C++11 multithreading tasking system featuring thread-pool, task-groups, and lock-free task queue.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Tasking Library (PTL) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jrmadsen/PTL.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-07-15", + "metadataLastUpdated": "2021-07-15" + }, + "description": "Frontend for the Software Defined Accelerators from Machine Learning Tools Environment (SODALITE) and the Software Defined Architectures for Data Analytics (SO(DA)^2) projects. This frontend takes in input json files from trained neural networks from the most common machine learning tools (PyTorch, TensorFlow, MxNet, etc.) and the related h5 files with weights, and generate the related MLIR (multilevel intermediate representation) linear algebra dialect. This allows the neural networks to be ingested by the rest of the SODA toolchain.", + "laborHours": 0.0, + "languages": [], + "name": "SODA frontend", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/sodalite/soda-frontend", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2021-07-15", + "metadataLastUpdated": "2021-07-15" + }, + "description": "Configure a Hashicorp Vault server for use with htgettoken", + "laborHours": 0.0, + "languages": [ + "Bash", + "Python" + ], + "name": "fermitools/htvault-config", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fermitools/htvault-config", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-07-19", + "metadataLastUpdated": "2021-07-19" + }, + "description": "This script converts files from the XML format to the CLI format.", + "laborHours": 0.0, + "languages": [], + "name": "AMXML to CLI converter", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CLDruzgalski/AM_fileConverters", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "allus@ornl.gov" + }, + "date": { + "created": "2021-07-20", + "metadataLastUpdated": "2021-09-28" + }, + "description": "Parallel computer code for the simulator for dynamics of power systems which has the capability to initiate the system and create different faults for the dynamic analysis. The code is based on time-parallel method (Parareal) with Adaptive Method Reduction (AMR). The coarse solvers for the Parareal algorithm include several Semi Analytical Solution methods. Also, Integrated simulation of coupled transmission and distribution systems can be studied.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "RAPID", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/PowerSystems/rapid", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-07-21", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This model was developed to assess the viability of US Lithium supply from geothermal brine and the potential supply chain impact of extracting Lithium from this source. This model links global demand and supply of lithium (Li) considering different electric vehicle (EV) demand scenarios. We seek to answer the following questions: \u2022 What is the economic potential of Li extraction from US geothermal sources? \u2022 Is geothermal Li extraction technology a viable investment in the US? \u2022 What is the potential supply chain impact of Li supply from US geothermal sources?", + "laborHours": 0.0, + "languages": [], + "name": "Lithium Supply Analysis Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/LISA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-22", + "metadataLastUpdated": "2021-07-22" + }, + "description": "The Decision-support and Emissions Prediction Interactive Cities Tool (DEPICT) aims at predicting the cross-sectoral (building construction, operation and vehicles) energy consumption and greenhouse gases emissions at campus and urban scale. It leverages capabilities of multiple modeling tools: EnergyPlus for building operation, CalEEMod for building construction and gas vehicle, BEAM for electric vehicles and SAM for building\u2013integrated photovoltaics. It distinguishes from other cross-sectoral model such as CalEEMod or BEST in that it uses physical models, rather than empirical models, for all sectors, which allows for a more accurate and customizable quantification. It is relevant for short-term multi-sectoral decision making by developers and city planners and long-term policy making by municipal and state officials. Information about all the developers", + "homepageURL": "https://buildings.lbl.gov/impel/people/lit/lit5", + "laborHours": 0.0, + "languages": [], + "name": "Decision-support and Emissions Prediction Interactive Cities Tool", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://buildings.lbl.gov/impel/people/lit/lit5", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://buildings.lbl.gov/impel/people/lit/lit5", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-22", + "metadataLastUpdated": "2021-07-22" + }, + "description": "Software toolchain to program the MMC on Marble boards", + "laborHours": 0.0, + "languages": [], + "name": "Marble MMC v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/Marble-MMC.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-22", + "metadataLastUpdated": "2021-07-22" + }, + "description": "Some different SYCL implementations of the reduction operation. The parallel reduction kernel aggregates vector elements into a single result. It consists of four ways to implement the reduction operation using two different data management strategies, which we could not find elsewhere as a single package.", + "laborHours": 0.0, + "languages": [], + "name": "sycl-reduction benchmark v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/nersc-proxies/sycl-reduction.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2021-07-23", + "metadataLastUpdated": "2021-07-23" + }, + "description": "We propose a stable, distributed approach to perform AA that accelerates the convergence rate of stochastic first-order optimizers to train neural networks.\nDifferently from previous works, we do not alter neither the scheme to perform AA nor the loss function minimized during the training. \nTo improve robustness against stagnation, we customize general guidelines that suggest to relax the frequency of AA corrections by performing AA only at the end of an entire training epoch. \nTo improve robustness of AA against the stochastic oscillations of first-order optimizers, we average the gradients computed on consecutive stochastic optimization updates. The improved regularity of the converging sequence and the reduced amplitude of stochastic oscillations across consecutive optimization steps allows AA to efficiently extrapolate an improved converging sequence, thereby overcoming limitations of existing approaches to perform AA on stochastic optimization.\n \n", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AADL: Anderson Accelerated Deep Learning", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/AADL.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2021-07-26" + }, + "description": "The Multi-scenario Extreme Weather Simulator (MEWS) takes existing historical weather data and inserts trends and extreme events such as heat waves, hurricanes, extreme precipitation, or winter storms. The code includes functionality for projecting increasing frequency and duration of such events over a large range of statistically sampled realizations of the future. These weather files can then be used in building energy simulations through the Energy Plus software created by DOE. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-8658 O", + "laborHours": 0.0, + "languages": [ + "Python", + "cython" + ], + "name": "Multi-Scenario Extreme Weather Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MEWS", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2023-08-14" + }, + "description": "This wind turbine digital twin software (wtDigiTwin) provides a digital twin solution for wind turbine applications. The focus of wtDigiTwin is to estimate loads, motions and environmental conditions for an operating wind turbine. The program uses supervisory control and data acquisition (SCADA) measurements as inputs, together with a wind turbine model. The wind industry is currently challenged by the high cost of operation and maintenance. These costs could be mitigated if component failures are predicted, but such predictions are difficult unless the turbines are equipped with expensive measuring devices. The alternative is to use a digital twin such as wtDigiTwin to estimate the necessary signals. wtDigiTwin can perform online prediction of signals that are otherwise not measured, using a limited set of reliable measurements and a physics-based model. The predicted signals can be used in applications that have direct cost benefits: 1) real-time estimation of the fatigue consumption of key components of the wind turbine; 2) root cause analyses and failure detections ; 3) lifetime reassessments ; 4) improvements to follow-on designs. The current version provides examples to estimate wind speed, thrust, torque, tower-top position, and tower loads on an onshore wind turbine using the following measurements tower top acceleration, generator torque, pitch, and rotational speed. The model combines a linear state-space model, a wind speed estimator, and a Kalman filter algorithm that integrates measurements with the state model to perform state estimations. The state space model is obtained either using OpenFAST linearizations, or using the yams package provided with the software.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python" + ], + "name": "wtDigiTwin (Wind Turbine Digital Twin) [SWR-21-15]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/wtDigiTwin", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2021-07-26" + }, + "description": "MoorPy is a quasi-static mooring model and a suite of associated functions for mooring system analysis. The core model supports quasi-static analysis of moored floating systems including any arrangement of mooring lines and floating platforms. It solves the distributed position and tension of each mooring line segment using standard catenary equations. Floating platforms can be represented with linear hydrostatic characteristics. MoorPy automatically computes a floating system's equilibrium state and can be queried to identify a mooring system's nonlinear force-displacement relationships. Linearized stiffness matrices are efficiently computed using semi-analytic Jacobians. MoorPy also includes plotting functions and a library of mooring component property and cost coefficients. MoorPy can be used directly from Python scripts to perform mooring design and analysis tasks, or it can be coupled with other tools to compute quasi-static mooring reactions as part of a larger simulation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "MoorPy (Quasi-Static Mooring Analysis in Python)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MoorPy", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2024-09-19" + }, + "description": "The Role-Based Access Control (RBAC) for Distributed Energy Resources (DER) software is an automated and transparent stack for RBAC administrators to interact with RBAC policy. The package includes demonstrations of centralized and decentralized RBAC implementation. Both include simulated DER entities that are stored automatically in a centralized Lightweight Directory Access Protocol (LDAP) server. It also includes a REST-API to serve the HTTP requests of the RBAC administrators. A complete front-end is included to serve the users' needs. This software may be used by industry (DER vendors/utilities) as well as the research community to determine if a centralized or decentralized solution fits better the needs of an RBAC model in a DER environment. Additionally, parts of this software may be useful for developing implementations for specific needs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8292 O", + "laborHours": 87582.4, + "languages": [ + "JavaScript", + "Vue", + "CSS", + "Python", + "Makerfile", + "SCSS" + ], + "name": "Role-Based Access Control for Distributed Energy Resources v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/RBAC_Centralized", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2021-08-16" + }, + "description": "The Sudoku Online Testing Framework provides a configurable basis for testing user interactions to solve visualization-related problems with sudoku puzzles and games. It consists of a server, a client, and test code. The python server implements sudoku puzzle logic and board selection functions. The JavaScript client implements a graphical user interface (GUI) front-end to display the puzzles and facilitate interactions with users. Within the GUI, logical rules may be selected. Cells may be selected to \u201cpivot\u201d on to make a board for each possible value in the cell. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-6409 O", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Sudoku Online Testing Framework v.0.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sudoku-online", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-27", + "metadataLastUpdated": "2023-05-16" + }, + "description": "Risk Informed Timelines (RIT) is a more modern and holistic method for understanding how access delay timelines are developed and utilized in physical security system evaluations. The software utilizes Bayesian methods to combine subject matter expert judgement and small performance test datasets in a consistent and defensible way. It allows a more holistic view of delay performance that provides distributions of task times and task success probabilities to account for tasks that, if failed, would result in failure of the attack. The RIT methodology is meant to enable security risk managers to begin the transition into more comprehensive delay timeline analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. 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API users prepare the input data and analysis configurations in a JSON format and send it to the web application via an HTTP request. The web application runs the analytical workflow on the back end and returns an HTTP response in JSON format. 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The tentative features include 1) listing the sites with basic site general info, 2) querying how much data & metadata are available, 3) subsetting a target site list for download, 4) parsing data & metadata, 5) cleaning & summarizing data, 6) data visualization and 7) listing target sites' contacts & DOI.", + "laborHours": 0.0, + "languages": [], + "name": "amerifluxr v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chuhousen/amerifluxr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "singularity-opac is a library for providing a unified interface for opacities, emissivities, and scattering cross-sections for materials and use in simulation codes. 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The analysis is focused on the N-terminal domain (NTD) and Receptor Binding domain (RBD) epitope regions, and aims to choose a set of variant forms that collectively cover a large fraction of the sequences in the alignment as a whole (globally) but also that cover large fractions of sequences collected on the different continents. The software provides a set of Spike protein sequences in a standard (fasta) sequence format.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "SHIVER", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "The CELL Adaptive mesh Refinement (CELLAR) application provides cell-based adaptive mesh refinement data structures and execution for parallel computing architectures. This application also includes example tests that exercise iteration patterns over the mesh entities (cells, edges, faces). The application is written in C++ and Fortran.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "CELLAR", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "We develop algorithms and software that uses the D-Wave 2000Q quantum annealer to solve several types of Boolean tensor factorization problems. 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Although current quantum technology is still fairly restricted in the problems it can tackle, we show that complex tensor factorization problems as the ones addressed by us can be solved efficiently and accurately.", + "laborHours": 0.0, + "languages": [], + "name": "QBTNs - Quantum Boolean Tensor Networks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyQBTNs", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "pyCP_APR is a tensor decomposition and anomaly detection Python library that is designed for the fast analysis of large datasets by accelerating computation speed using GPUs. pyCP_APR uses the CANDECOMP/PARAFAC Alternating Poisson Regression (CP-APR) tensor factorization algorithm utilizing both Numpy and PyTorch backend. While the Numpy backend can be used for the analysis of both sparse and dense tensors, the PyTorch backend provides a faster decomposition of large and sparse tensors on the GPU. pyCP_APR's Scikit-learn like API allows comfortable interaction with the library, and includes the methods for statistical anomaly detection via the p-values obtained from the CP-APR factorization.", + "laborHours": 0.0, + "languages": [], + "name": "pyCP_APR", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyCP_APR", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "R code to fit generalized Bayesian Adaptive Smoothing Spline (GBASS) models for nonlinear regression. The approach is similar to the Bayesian MARS approach of Francom & Sanso (2020), but allows for non-Gaussian likelihoods. 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The software also contains a \"translator\" that enables the export of \"robustified\" items with Robust Links-enhanced HTML code.", + "laborHours": 0.0, + "languages": [], + "name": "Zotero Robust Links Extension", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Zotero-Robust-Links-Extension", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "Clustering methods are heavily dependent on the algorithm of choice, as well as the chosen hyperparameters of the algorithm and their sensitivity to data scales is largely unknown. In our software, we introduce a tensor clustering that relays on discrete wavelet transform to analyze the effects of course-graining on clustering of high-dimensional tensor data. Our method CGC allows us to understand how the different scales affect clustering. The scale of data is an important feature with regards to clustering. CGC calculates the normalized mutual information drop off at different length scales which illustrates certain resolutions are producing novel clusters. Consequently, in addition to running several clustering algorithms, it is also important to include several coarse-grain clusterings into a cluster ensemble.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "CGC", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-08-03" + }, + "description": "FIERRO is a modern C++ code intended to simulate quasi-static solid mechanics problems and transient, compressible material dynamic problems with Lagrangian methods, which have meshes with constant mass elements that move with the material. 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No physical data exists within the code.", + "laborHours": 0.0, + "languages": [], + "name": "FIERRO V.X", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Fierro", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "This software converts XML files created by the Netfabb software to the XML format used by the Intelligent Feed Forward (IFF) tools developed at LLNL.", + "laborHours": 0.0, + "languages": [], + "name": "Netfabb to IFF XML converter", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CLDruzgalski/AM_fileConverters", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2022-06-16" + }, + "description": "The Ubiquitous Traffic Volume Estimation System uses Machine Learning (ML) algorithms to provide accurate estimates of number vehicles on the roadway (ubiquitous traffic volume) based on inputs such as commercial probe traffic data that includes average vehicle speed and probe counts, roadway characteristics, weather, time of day, and day of week, and reference volume counts from a limited number of automatic traffic recorder stations. The Ubiquitous Traffic Volume Estimation System estimates traffic volumes 24 hours a day, 7 days a week, and 365 days a year on all major corridors and freeways in Denver metropolitan area and is being expanded to the whole state of Colorado. The methodology and code developed in this effort can be easily customized to other states and cities where similar data is available.", + "laborHours": 0.0, + "languages": [ + "R", + "Jupyter Notebook" + ], + "name": "Ubiquitous Traffic Volume Estimation System", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/TrafficVolumeEstimation", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-05" + }, + "description": "GPos is a software that was created to determine the properties of positron beams resulting from the interaction of the LBNL BELLA center PetaWatt laser-driven plasma-capillary accelerated electron beam and the atoms of a thin solid target. GPos is written in C++, easily compiled with cmake and the spack package manager, which allows for multi-thread and MPI parallel computing. Its functions expand on the Geant4 toolkit library and allow for propagation of the modelled particles through vacuum drift distances with a focusing element (thin lens approximation). Users can change beam-foil-drift-lens parameters - to adapt GPos to other particle sources and infrastructures - in a simple input file. The code particle data output format, openPMD, which is compatible, for example, with the input of the ECP WarpX project code used to explore the physics of particle acceleration in plasmas. Using GPos in conjunction to WarpX allowed us to test various configurations for designing a high-quality and high-energy positron source at BELLA -required for us to address positron acceleration challenges in the development of future linear colliders. GPos can also be advantageous when tackling the physics of muon sources for future muon colliders as well as for the investigation of positron sources in lower energy regimes for applications like annihilation spectroscopy and astrophysical gamma-ray-bursts.", + "laborHours": 0.0, + "languages": [], + "name": "Geant4 based positron beam source (GPos) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LDAmorim/GPos", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-05" + }, + "description": "eProject Builder (ePB) is a secure, web-based system that enables agencies and ESCOs to securely: (1) preserve, track, and access energy project information for the life of the contract (2) quickly generate data and reports for their portfolio of projects (3) develop project scenarios using standardized amortization calculations (4) benchmark new projects against historical project data", + "homepageURL": "https://sites.google.com/lbl.gov/2021-124/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "eProject Builder (ePB) v3.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2021-124/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-124/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-05" + }, + "description": "A Machine Learning Platform that connects beamline scientists and machine learning (ML) researchers so that the ML researchers can quickly distribute their ML models to beamline scientists, and beamline scientists can give feedback to help ML researchers improve their models.", + "laborHours": 0.0, + "languages": [], + "name": "MLExchange v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mlexchange/mlex", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-06" + }, + "description": "Fast Free Fermion Compiler (F3C) is an application-specific quantum circuit compiler for time-evolution circuits of spin Hamiltonian systems that can be mapped to free fermions.", + "laborHours": 0.0, + "languages": [], + "name": "F3C++ v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QuantumComputingLab/f3cpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-06" + }, + "description": "Fast Free Fermion Compiler (F3C) is an application-specific quantum circuit compiler for time-evolution circuits of spin Hamiltonian systems that can be mapped to free fermions. F3C is the Matlab software version and the related F3C++ is the C++ software version.", + "laborHours": 0.0, + "languages": [], + "name": "F3C v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QuantumComputingLab/f3c", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-11" + }, + "description": "The District EnErgy Planner - DEEP is an Mixed Integer Linear Programming (MILP) optimization software tool to solve district energy system, technology configuration, operation strategies, and energy retail business schemes. DEEP takes user input energy demand on heating, cooling and electricity demand. Energy loss through pipeline is calculated for heating and cooling from central plants. The optimal system configuration to minimize the district energy system life cycle cost or minimize CO2 emission is calculated based on energy balance equations and various constraints. The recent update on DEEP include a feature of waste heat utilization energy balance based optimization to take into accounts of different temperature bands of heat into account to maximize system efficiency. Another feature is to optimize district energy retail by provide optimal pricing scheme for heating, cooling and electricity to end users to incorporate district to grid demand response.", + "laborHours": 0.0, + "languages": [], + "name": "District EnErgy Planner (DEEP) v2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/deep_ceg_lbl/deep_ceg_lbl/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-06", + "metadataLastUpdated": "2021-09-21" + }, + "description": "The Exploration Toolkit (ExTK) is a reusable Extended Reality (XR) system developed for incorporating and exploring 3-Dimensional (3-D) computer aided design (CAD) models in XR, with a primary focus on Augmented Reality (AR). The ExTK consists of a Developer Mode and a User Mode. In Developer Mode, ExTK provides developers with the ability to easily import 3-D CAD models and activate desired exploration functionality and layout. Multiple models can be added to a single instantiation of the ExTK using Unity's Scene capability. Exploration functions include scaling, rotating, explode/contract, animations, hiding parts, submodules, and measurement functions. In User Mode, ExTK provides a menu system that allows users to select models and initiate exploration functions. ExTK is architected for reusability and developers can customize the ExTK layout and functions according to application needs. ExTK is designed to be hardware agnostic, although initial development focused on the Microsoft HoloLens as the primary deployment platform. The ExTK is developed using the Unity Game Engine Development Platform. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1506 O", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Exploration ToolKit (ExTK)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ExTK", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-06", + "metadataLastUpdated": "2024-07-23" + }, + "description": "CoMTE is a novel explainability technique that provides counterfactual explanations for supervised machine learning frameworks on multivariate time series data. CoMTE outperforms state-of-the-art explainability methods on several different machine learning frameworks and data sets in comprehensibility and robustness. CoMTE can be used to debug machine learning frameworks and gain a better understanding of the underlying multivariate time series data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1686 O", + "laborHours": 471.2, + "languages": [ + "Jupyter Notebook", + "Rust", + "Python" + ], + "name": "CoMTE: Counterfactual Explanations for Supervised Machine Learning Frameworks on Multivariate Time Series Data", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CoMTE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-08-06", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This repository contains data ingestion, feature extraction, and analysis code used in NREL Technical report \"Clustering Analysis of Commercial Vehicles Using Automatically Extracted Features from Time Series Data.\" The code is written in Python. The ETL and feature extraction code must be run in a Spark context. The analysis code can be run without Spark, provided you have pre-computed features in a CSV file. Analysis code related to the NREL Technical Report NREL/TP-2C00-74212. Includes PySpark functions to perform trip segmentation and feature extraction over big time series data in Apache Spark. Includes \"domain specific\" features such as Aerodynamic Speed (ft/s), Characteristic Acceleration (ft/s2), Percent Below 55 (%), Percent Zero (%), Stops Per Mile, Average Speed (mph), Maximum Speed (mph), and Speed Standard Deviation (mph). Includes Pyspark UDF to compute \"domain agnostic\" features using the TSFresh library. This software record also includes the analysis notebooks and code to generate the results in the previously mentioned technical report.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Code Artifact for: Clustering Analysis of Commercial Vehicles Using Automatically Extracted Features from Time Series Data [SWR-21-96]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/clustering-analysis-domain-agnostic-features-2018", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-06", + "metadataLastUpdated": "2023-03-15" + }, + "description": "This tool can be used to determine a least-cost feedstock mix from crop residue, energy crop and MSW to meet conversion specifications, while also identifying appropriate depot locations and size, given that depot can be co-located with the biorefinery or can be located in any counties in the biofinery\u2019s supply shed.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Multi-feedstock Supply Chain Optimization Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/MFSCO", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "sarat@ornl.gov" + }, + "date": { + "created": "2021-08-06", + "metadataLastUpdated": "2021-08-06" + }, + "description": "Climate kernels for Co-design These kernels originate from the Energy Exascale Earth System Model (E3SM). They are intended for sharing with interested parties for co-design purposes.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "E3SM Co-design Kernels", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/codesign-kernels", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-09", + "metadataLastUpdated": "2024-07-23" + }, + "description": "EUForia is a general-purpose model checker that solves reachability problems in dynamical systems. It implements an abstraction-refinement process in which the system is iteratively approximated until it can prove or disprove that a system state is reachable. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-3020 O", + "laborHours": 23499.2, + "languages": [ + "C++", + "Shell", + "Nix", + "CMake", + "Makefile", + "Python" + ], + "name": "EUForia", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/euforia", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "devarakondar@ornl.gov" + }, + "date": { + "created": "2021-08-11", + "metadataLastUpdated": "2021-08-11" + }, + "description": "The AGU/AMS Abstract Search and Display Software is a standalone web application which enables the searching, storing, and displaying of abstracts featured at the annual American Geophysical Union (AGU) and American Meteorological Society (AMS) meetings. This application is designed for those who wish to host a standalone web application and feature a select subset of posters and talks scheduled for the AGU/AMS meetings. Please read the entirety of this README.md file before attempting to download and use the application. There are three views available via the UI: Lookup - enables searching and submitting posters for displaying on the summary view Manual Submission - allows individual manual submission of posters given a poster ID Summary - displays all posters submitted by users from the lookup view", + "laborHours": 0.0, + "languages": [], + "name": "AGU/AMS Abstract Search and Display Software", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/arm-data-science-integration/poster-api-wrapper", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-08-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The EXPERT toolkit contains next-gen AI capabilities to detect, anticipate, and reason about proliferation expertise evolution from unstructured dynamic multilingual real-world data.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/EXPERT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/EXPERT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-11", + "metadataLastUpdated": "2021-08-11" + }, + "description": "EScp is a high speed transfer tool with a similar command line syntax to scp. Unlike SCP it is designed to transfer files at high speed, thus far we have been able to show 100gbit/s transfers, although I expect that the throughput should scale in proportion to the network interface, i.e. I expect 400gbit/s performance on our 400gbit/s test bed. EScp achieves good performance through an innovative design (multithreaded, zero copy transfers), along with pluggable filters and I/O engines. As an example, you can switch from POSIX i/O to UIO by checking a different engine. It also natively supports encryption, and cheksums for file verification and transport security. AAA is through standard SSH (same as SCP). By taking advantage of filters, EScp supports transferring unstructured data and/or I/O to non-posix data sources. Examples include streaming data (i.e. from equipment), transferring data to the cloud, and/or supporting non-posix file systems (like HPSS).", + "laborHours": 0.0, + "languages": [], + "name": "ESnet Secure Copy (EScp) v0.6", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/EScp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-11", + "metadataLastUpdated": "2021-08-13" + }, + "description": "1. Segmentation We provide scripts for the model definition of the U-net architecture adapted from: https://github.com/jvanvugt/pytorch-unet/blob/master/unet.py We developed scripts for preparing the lung segmentation data set. We developed scripts for training the U-Net architecture. We developed scripts for applying the trained U-Net model to perform the ROI Hide and Seek protocol on the classification dataset to create the modified dataset. 2. Classification We provide scripts for the training of the COVID-Net models provided by Linda Wang, this code is adapted from her github repository: https://github.com/lindawangg/COVID-Net/tree/d7b36831d854f57de5bc7557217f5439e86e016f. These scripts were modified to save training log information as well as to load the provided models in their github repo. We developed scripts for training standard Neural Network Models (resnet 50, vgg 11, Alexnet) on the COVID datsets along with the ROI Hide and Seek altered datasets.", + "laborHours": 0.0, + "languages": [], + "name": "ROI Hide and Seek Protocol v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electro1111/COVID_19_CXR_CLASSIFICATION", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "We developed an analysis framework for quantitatively interpreting results from multi-color fluorescence microscopy data. When the emission signal from fluorescent probes (i.e. from biological microscopy or in single-particle microscopy) is spectrally separated before detection, the resulting signals contain information about the strengths of each probe. We built a model to deconvolve the raw data into quantitative descriptions of either of the wavelength of a single probe or the relative strengths among multiple probes. This approach requires only spectrally separating the image data into two or more channels, as opposed to fully resolving the spectral profile, thus allowing other microscopy techniques to be used simultaneously. Our analysis framework incorporates the response features of the optical and imaging elements used to produce the spectral separation, yielding highly quantitative interpretations of the underlying behaviors that give rise to the data.", + "laborHours": 0.0, + "languages": [], + "name": "Quantitative analysis method for multi-color microscopy", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ryand-LANL/DualColorAnalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "MF-LBM-nanopore is a high-performance lattice Boltzmann code for direct numerical simulation of flow in nano-porous media with confinement effects. The main features of the code include: 1) implemented with adsorption and slip modules that enable simulation of flow in nano-porous media with confinement effects; 2) extensively optimized for modern SIMD/SIMT processors/co-processors, such as GPU; 3) based on MPI-OpenACC/OpenMP hybrid programing model that enables high portability. The main application of the code is in modeling shale gas flow.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "MF-LBM-nanopore", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "The era of exascale computing opens new venues for innovations and discoveries in many scientific, engineering, and commercial fields. However, with the exa flops also come the extra-large high-dimensional data generated by high performance computing. High-dimensional data is presented as multidimensional arrays, aka tensors. The presence of latent (not directly observable) structures in the tensor allows a unique representation and compression of the data by classical tensor factorization techniques. However, the classical tensor methods are not always stable or they can be exponential in their memory requirements, which makes them not suitable for high-dimensional tensors. Tensor train (TT) is a state-of-the-art tensor network introduced for factorization of high-dimensional tensors. TT transforms the initial high-dimensional tensor in a network of three-dimensional tensors that requires only a linear storage. Many real-world data, such as, density, temperature, population, probability, etc., are non-negative and for an easy interpretation, the algorithms preserving non-negativity are preferred. Here, we introduce a distributed non-negative tensor-train and demonstrate its scalability and the compression on synthetic and real world big datasets.", + "laborHours": 0.0, + "languages": [], + "name": "DNTTD (Distributed Non-Negative Tensor Train Decomposition)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyDNTNK", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "A python class has been developed to help streamline the creation of customizable Github applications Python Class for Github Application Development (Py-CGAD). Py-CGAD contains an interface for interacting with Github\u2019s RESTful API by automatically handling authentication and providing common functionality through simple methods. These methods include uploading files to a repository, posting and getting statuses among others. Py-CGAD is generic and can be used as a template for quickly building a variety of different application of interest to the mission of the lab and the public in general.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Python Class for Github Application Development (Py-CGAD)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "XSPIKE (eXplore the SPIKE protein) identifies sites of high variability (high entropy) in amino acid sequences of the Spike protein of the SARS CoV-2 virus. Among these sites, it further identifies correlations between pairs of them, and provides both graphical and tabular display of that information. It also provides a table of occurrences of co-occurring patterns found among natural sequences, featuring associations within those most highly variable sites to emphasize common covariation patterns; this table includes information about the number of sequences in which those patterns are seen, broken out by continent, and provides as context a list of mutations for each pattern that corresponds to the differences between the reference sequence (usually the Wuhan form) and the most common full sequence that exhibits that pattern.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "xSpike", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-27" + }, + "description": "The copyrightable material is a set of software whose goal is to explore the use of Monte Carlo methods at extreme processor counts. This will include application software, libraries, middleware, various system software, and possibly compilers and translators", + "laborHours": 0.0, + "languages": [], + "name": "Billion-Core Monte Carlo", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/c2nova", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-19" + }, + "description": "BdNMC is a Monte Carlo that simulates the creation, propagation and detection of dark sector particles in particle physics experiments. Dark sector particles are defined as any particles which are weakly coupled to matter and are expected to travel large distances in matter without interaction. The code takes input from some initial distribution or list of Standard Model particles and generates a list of dark sector particles. The generated dark sector particles are propagated to a defined detector volume, where they are then checked for their probability to interact with the detector through either decay or scattering. The code outputs an expected number of interaction events to the user, and may optionally produce an additional output file of all of the particles simulated by the code for each interaction event. This contribution makes corrections and updates to several of the physics formulas and functions implemented in the BdNMC simulation code related to Coherent Captain Mills experiment's physics analyses.", + "laborHours": 0.0, + "languages": [], + "name": "Contribution to Open Source Software BdNMC", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/BdNMC_LANL", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "PANACEA provides a means for generating unique configurations. The primary motivation for its development stems from the need to generate unique configurations for the purpose of training machine learned interatomic potentials. PANCEA is a C++ library with python and linux scripts. The C++ library is the engine which provides can be installed and used to measure the disorder/order of a system via the information entropy. The python and linux scripts provide useful helper functionality such as visualization of files that can be output from the library.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Portable Approach for Novel Arrangements using a Cross Entropy Algorithm (PANACEA)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "Amanzi provides a flexible and extensible multiphase, multicomponent, flow and reactive transport simulation capability for environmental applications. It also includes thermal and geomechanical processes in the subsurface. It includes toolsets for meshing infrastructure, discretizations, and solvers for the resulting nonlinear systems of equations. The framework Arcos (LA-CC-14-053), provides the internal data management, process and coupling interfaces, and runtime configuration through a directed acyclic graph [1]. The code is parallel and makes use of open-source parallel frameworks such as Trilinos [2] developed at Sandia National Laboratory and PETSc (the Portable Extensible Toolkit for Scientific Computing) [3] developed at Argonne National Laboratory. Rudimentary geochemistry capabilities are included in Amanzi, while a state-of-the-art geochemistry support is provided through the Alquimia interface library, which can use well established open-source geochemistry engines (e.g., PFLOTRAN or CrunchFlow). In addition, support for GPUs is being developed through the Kokkos [4] performance portability library. Amanzi is used to model contaminant migration at various DOE waste sites (e.g., Hanford, and Savannah River), and is generally applicable to contaminant migration in groundwater under partially saturated nonisothermal conditions and its interaction with surface water. Development of Amanzi is funded by the DOE Office of Science, primarily through programs in the DOE Office of Biological and Environmental Research (BER) and internally through LDRD. [1] Coon, E. T., J. D. Moulton, and S. L. Painter, Managing complexity in simulations of land surface and near-surface processes, Environmental Modelling & Software, 78, pp. 134-149, 2016. http://dx.doi.org/10.1016/j.envsoft.2015.12.017 [2] Trilinos, https://trilinos.github.io/ [3] Portable, Extensible Toolkit for Scientific Computation, https://www.mcs.anl.gov/petsc/ [4] Kokkos C++ Performance Portability Programming EcoSystem, https://github.com/kokkos", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Amanzi 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "The Advanced Terrestrial Simulator (ATS) is a code for solving multiscale ecosystem-based, integrated, distributed hydrology. It builds on the multi-physics framework and toolsets (mesh infrastructure, discretizations, solvers) provided by Amanzi (original release LA-CC-10-069, new release pending in FCI) and is a key driver of development of the flexible multiphysics framework Acros (LA-CC-14-053). Capabilities are largely based on solving various forms of variably saturated subsurface flow (e.g., Richards equation) coupled to a surface flow equation, along with the needed sources and sinks for ecosystem and climate models. This can (but need not) include thermal processes (especially ice for frozen soils), evapo-transpiration, albedo-driven surface energy balances, snow, biogeochemistry, plant dynamics, deformation, solute and contaminant transport, erosion and sediment transport, and much more. It is unique in its thermal integrated hydrology capabilities, which include thermal energy with freeze/thaw processes in both the surface and subsurface water, and its reactive transport capabilities, which are also coupled in both surface and subsurface water. Like Amanzi, the ATS uses the Alquimia interface library to couple its transport capabilities with biogeochemical reaction engines (e.g., PFLOTRAN and CrunchFlow). The ATS has been used to explore how a wide range of ecosystems function under a variety of environmental drivers, including the evolution of polygonal permafrost in the warming arctic [1,2], the impact of forest fires on the water quality of streams in the Jaramillo watershed, and the impact of seawater intrusion on vegetation in salt water marshes on the Delaware. \n\n[1] Painter, S. L., E. T. Coon, A. L. Atchley, M. Berndt, R. Garimella, J. D. Moulton,D. Svyatskiy, and C. J. Wilson, Integrated surface/subsurface permafrost thermal hydrology: Model formulation and proof-of-concept simulations,Water Resour. Res.,52,6062\u20136077, 2016. https://doi.org/10.1002/2015WR018427\n[2] Jafarov, E. E., E. T. Coon, D. R. Harp, C. J. Wilson, S. L. Painter, A. L. Atchley, V. E. Romanovsky, Modeling the role of preferential snow accumulation in through talik development and hillslope groundwater flow in a transitional permafrost landscape, Environmental Research Letters, 13(10):105006, 2018. https://doi.org/10.1088/1748-9326/aadd30", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Advanced Terrestral Simulator (ATS) 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-08-16", + "metadataLastUpdated": "2021-08-16" + }, + "description": "The pySMARTS module contains functions for calling SMARTS: Simple Model of the Atmospheric Radiative Transfer of Sunshine, from NREL, developed by Dr. Christian Gueymard. SMARTS software can be obtained from: https://www.nrel.gov/grid/solar-resource/smarts.html Users will be responsible to obtain a copy of SMARTS from NREL, honor it's license, and download the SMART files into their PVLib folder. This wrapper is shared under a BSD-3-Clause License, and was originally coded in Matlab by Juan Russo (2001), updated and ported to python by Silvana Ayala (2019-2020).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "pySMARTS: SMARTS Python Wrapper (Simple Model of the Atmospheric Radiative Transfer of Sunshine)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pySMARTS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "Version: 0.18" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-16", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The Intermode Communication Protocol Wrapper, or Icypaw, structures and facilitates communication between endpoints in a network. It is used to connect various independent software and hardware components into one loosely organized system controllable from one or more locations. The code uses the MQTT protocol to communicate and enhances it with a useful framework. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8293 O", + "laborHours": 4909.6, + "languages": [ + "Python" + ], + "name": "Icypaw", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IcyPaw", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-17", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Reduced-order Models (ROMs). ROMs are \"compressed\" approximations of high-fidelity computational models. Implementing ROM methods in production codes is typically intrusive, i.e. the native codes must be adapted and modified, with individual ROM methods reimplemented in every application code. This clearly constitutes an obstacle to users who want to use ROMs. To address this, we have developed Pressio, which is a C++ header-only ROM library that can be used by an application code in a non-intrusive fashion. The main objectives behind the design of Pressio are: (a) support for general computational models (data structures, PDE types); (b) heterogeneous hardware (CPU, GPU); (c) performance; and (d) extensibility. Using metaprogramming techniques, Pressio detects and leverages the application?s native linear algebra data structures (e.g. vector and matrix) to run the ROM methods. The application only needs to expose the velocity vector and Jacobian matrix via an adapter class. Pressio checks at compile time that the target application meets the correct API. The library is structured in several modular packages including (a) non-linear least-square solvers (e.g. Gauss-Newton with and without line-search); (b) singular value decomposition (for the computation of the ROM generalized coordinates) and (c) algebraic hyper-reduction.SAND2019-5878 M", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Pressio v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pressio", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "parishcm@ornl.gov" + }, + "date": { + "created": "2021-08-17", + "metadataLastUpdated": "2021-08-17" + }, + "description": "Applies machine learning to analyze individual or sets of X-ray energy dispersive spectroscopy spectrum images acquired in the electron microscope.", + "laborHours": 0.0, + "languages": [], + "name": "EDS Montage", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/nmp/eds_montage", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This software improves upon the Clifford gate+T gate magic state strong simulation algorithm by Brayvi and Gosset. It provides a better stabilizer state decomposition that scales as 2^{0.463t}, an improvement over 2^{0.468t}, for t T gate magic states. This code enables simulations of universal quantum computing with that asymptotic scaling cost. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525 SAND2020-14293 O", + "laborHours": 0.0, + "languages": [], + "name": "Stabilizer Rank Strong Simulation v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Stabilizer-Rank-Strong-Simulation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2024-09-19" + }, + "description": "Universal quantum circuits can be formulated in the Pauli measurement-based formalism as input T gate magic states, Clifford gates, and then multi-Pauli measurements. This code simulates single-Pauli measurements to show some theoretical bounds on the cost of full multi-Pauli measurements. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2020-14080 O", + "laborHours": 0.0, + "languages": [], + "name": "Gauss Sum Strong Simulation v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Gauss-Sum-Strong-Simulation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-18" + }, + "description": "The SPARSIFY algorithm implemented by the code allows for classical simulation of universal quantum computer sample outcomes. The code sparsifies the stabilizer decomposition of a qubit t-tensored T gate magic state to some additive error. This is accomplished by either independent L1 sampling or with correlated L1 sampling to supplement an independent subset, which offers a more efficient decomposition: for a given t, a sparser decomposition is sufficient with correlated L1 sampling to satisfy a given additive error. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8296 O", + "homepageURL": "https://s3miclassical.com/gitweb", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Weak Simulation v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://s3miclassical.com/gitweb", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-18" + }, + "description": "Pilgrim is a profiling tool for MPI applications. It tracks the communication activities in an MPI application and records them as logs for further analysis. It allows users to have a better insight into the execution of their application and identify potential performance bottlenecks.", + "laborHours": 0.0, + "languages": [], + "name": "PILGRIM", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/pilgrim", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2023-07-21" + }, + "description": "As the size of turbulent flow simulations continues to grow, in situ data compression is becoming increasingly important for visualization, analysis, and restart checkpointing. For these applications, single-pass compression techniques with low computational and communication overhead are crucial. In this paper we present a deep-learning approach to in situ compression using an autoencoder architecture that is customized for three-dimensional turbulent flows and is well suited for contemporary heterogeneous computing resources. The autoencoder is compared against a recently introduced randomized single-pass singular value decomposition (SVD) for three different canonical turbulent flows: decaying homogeneous isotropic turbulence, a Taylor-Green vortex, and turbulent channel flow. Our proposed fully convolutional autoencoder architecture compresses turbulent flow snapshots by a factor of 64 with a single pass, allows for arbitrarily sized input fields, is cheaper to compute than the randomized single-pass SVD for typical simulation sizes, performs well on unseen flow configurations, and has been made publicly available. The results reported here show that the autoencoder dramatically outperforms a randomized single-pass SVD with similar compression ratio and yields comparable performance to a higher-rank decomposition with an order of magnitude less compression in regard to preserving a number of important statistical quantities such as turbulent kinetic energy, enstrophy, and Reynolds stresses.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AEflow (Autoencoder fluid flow compression network) [SWR-22-29]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/AEflow", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This package is a set of extensions to MOOSE (https://moose.inl.gov) adding anisotropic graphite material models for irradiation creep and swelling. The goal of the package is to provide a framework to model graphite components for use in future high temperature nuclear reactors.", + "laborHours": 0.0, + "languages": [], + "name": "GOOSE (GRAPHITE OBJECT-ORIENTED SIMULATION ENVIRONMENT)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/goose", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-18" + }, + "description": "A digital twin for synchrotron-based tomography for generating synthetic datasets from ground-truth phantoms. The code outputs greyscale projection images / tomographic volumes with realistic artifacts such as noise and phase-contrast and emulates their dependence on the acquisition parameters defining the beam and detector configuration. Some ground-truth phantoms are included with the code.", + "laborHours": 0.0, + "languages": [], + "name": "TomoTwin: A simple digital twin for synchrotron tomography", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aniketkt/TomoTwin", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-18" + }, + "description": "Real-time steering of time-resolved or in-situ X-ray tomography requires capturing changes in morphological descriptors in a sample (e.g., porosity, particle size, and crack width) during continuous data acquisition. 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As a faster and unsupervised alternative, a feature-extraction approach using a convolutional autoencoders was developed, where the latent space of the encoder responds to relative changes in morphology with-out prior knowledge of the morphological descriptors.", + "laborHours": 0.0, + "languages": [], + "name": "TomoEncoders: 3D Autoencoders for feature extraction in X-ray tomography", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aniketkt/TomoEncoders", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-19", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This code is designed to reconstruct magnetic field deflections, and thus the path-integrated magnetic field, from sets of proton images at two distinct proton probe energies. A differential evolution (DE) algorithm is used to iteratively update a population of solution candidates of the magnetic deflections of the protons for reconstructing the input images, selecting improved candidates as they are discovered. 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Data analysis is both challenging and time consuming. Novices often rely on the assistance of an expert, such as the instrument scientist who supported them at the facility where the experiment was performed, to analyze their data. The high flux provided by modern facilities makes it possible to study dozens of samples or sample conditions during a single trip. Ultimately, the high throughput of modern instruments limits access to instrument scientists. A bottleneck in the research effort results that reduces facility productivity. Sas-temper seeks to address this problem, as well as the intrinsic difficulties of being confident in non-linear least squared fitting of data, by providing tools that automate much of the manual process of initial data fitting and refinement, as well as by providing tools for characterizing the nature of the parameter space that fits the measured data. The tools provided by sas-temper help small-angle scattering practitioners transition data into results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "sas-temper", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/wt3/sas_temper", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-19", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This software package contains utilities for ingesting battery cycling data from various equipment and converting it to a common file format including metadata. 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The model is implemented using Tensorflow and the training dataset is generated using physics-based atomistic simulations. Custom codes are written to handle the resampling of diffraction images to oversampling ratios appropriate for the neural network model.", + "laborHours": 0.0, + "languages": [], + "name": "NEURAL NETWORK FOR COHERENT DIFFRACTION IMAGE INVERSION", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hyiprc/3D-CDI-NN", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-19", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This package estimates future potential for utility customers to provide various forms of demand response (DR) based on granular forecasts of energy demand by customer type and a database of DR-enabling technologies.", + "homepageURL": "https://buildings.lbl.gov/download-phase-3-dr-potential-study", + "laborHours": 0.0, + "languages": [], + "name": "DR-Path", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://buildings.lbl.gov/download-phase-3-dr-potential-study", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2021-08-20" + }, + "description": "This study develops a neural network-based approach for emulating high-resolution modeled precipitation data with comparable statistical properties but at greatly reduced computational cost. The key idea is to use combination of low-and high- resolution simulations to train a neural network to map from the former to the latter. Specifically, we define two types of CNNs, one that stacks variables directly and one that encodes each variable before stacking, and we train each CNN type both with a conventional loss function, such as mean square error (MSE), and with a conditional generative adversarial network (CGAN), for a total of four CNN variants. We compare the four new CNN-derived high-resolution precipitation results with precipitation generated from original high resolution simulations, a bilinear interpolater and the state-of-the-art CNN-based super-resolution (SR) technique. Results show that the SR technique produces results similar to those of the bilinear interpolator with smoother spatial and temporal distributions and smaller data variabilities and extremes than the original high resolution simulations. While the new CNNs trained by MSE generate better results over some regions than the interpolator and SR technique do, their predictions are still not as close as the original high resolution simulations. The CNNs trained by CGAN generate more realistic and physically reasonable results, better capturing not only data variability in time and space but also extremes such as intense and long-lasting storms. The new proposed CNN-based downscaling approach can downscale precipitation from 50~km to 12~km in 14~min for 30~years", + "laborHours": 0.0, + "languages": [], + "name": "DSGAN", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lzhengchun/DSGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2021-08-20" + }, + "description": "Massively Parallel, Portable, and Reproducible Tractography (MaPPeRTrac) is a brain tractography workflow for high performance computing. It incorporates novel technologies to simplify and accelerate neuroimaging research.", + "laborHours": 0.0, + "languages": [], + "name": "MaPPeRTrac", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MaPPeRTrac", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The application is being developed with the goal of preventing the entropy of all the different single purpose applications. This application utilizes a framework that enables different file formats to be read and understood through plugins dynamically loaded to the main application containing the framework. The main application provides interoperability to all the different plugins, this allows each file format to convert to every other file format that has been read. There is no theoretical limit to the number of plugins that can be used by the application. Even though the plugins may be individually written and serve a purpose like single use scripts, the plugins can only be used with the main application, this forces the application and plugins to be linked. In theory this will force better data management, or at least the bundling of the main application with the plugins.", + "laborHours": 0.0, + "languages": [ + "C++", + "JavaScript" + ], + "name": "Vulcan Digital Engineering Application", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/VDEA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The number of power outages have been on the rise as extreme weather patterns have been occurring more frequently due to climate change. These outages have an economic impact in the billions of dollar. The modernization of the power grid and adoption of high penetration of distributed generation such as wind and solar have the potential to reduce the number and length of time of these power outages. However, planners and operators need a way to value the resilience the distributed assets provide to the grid. PowDDeR is a tool that allows them to evaluate the resilience each asset provides as well as how they provide resilience over the connected network.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Power Distribution Designing For Resilience Application", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/PowDDeR-Python", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2023-03-13" + }, + "description": "PyEmission is a Python library for estimation of vehicular emissions and fuel consumption. This tool covers a wide range of light duty motor vehicles including passenger car, SUV, passenger truck, and light commercial truck. The tool only takes second-by-second driving cycle and vehicle characteristics data as inputs and generate results of vehicular emissions (CO2, CO, NOx, and HC) and fuel consumption.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Python Library For Vehicular Emission Estimation", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/PyEmission", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2023-03-13" + }, + "description": "This is a simple wrapper script that will be used to enable the use of a two-factor authentication mechanism for downloading NCRC controlled codes through the popular \"Conda\" distribution mechanism.", + "laborHours": 0.0, + "languages": [], + "name": "Ncrc-client", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/ncrc-client", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-23", + "metadataLastUpdated": "2021-08-23" + }, + "description": "The Ducted Assembly Steady State Heat transfer software (DASSH) performs full core, steady state, subchannel temperature calculations for hexagonal, ducted assemblies. DASSH is targeted for use in the early stages of the reactor design process when assembly characteristics may not be defined or are undergoing considerable changes. DASSH provides a relatively rapid assessment of the temperature and flow distribution to inform reactor design updates and analysis.", + "laborHours": 0.0, + "languages": [], + "name": "DUCTED ASSEMBLY STEADY STATE HEAT TRANSFER SOFTWARE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dassh-dev/dassh", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-23", + "metadataLastUpdated": "2021-08-24" + }, + "description": "This software uses AI tools for enhanced functional imaging using Lorentz transmission electron microscopy by retrieving phase shift at higher spatial resolution, and under noisy conditions. This is a companion code for a publication that is currently being submitted (APT # 164160).", + "laborHours": 0.0, + "languages": [], + "name": "AD_LTEM", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/danielzt12/AD_LTEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-24", + "metadataLastUpdated": "2021-08-24" + }, + "description": "cuSZ is a CUDA implementation of the world-widely used SZ lossy compressor. It is the first error-bounded lossy compressor on GPUs for scientific data, which significantly improves SZ's throughput in GPU-based heterogeneous HPC systems.", + "laborHours": 0.0, + "languages": [], + "name": "cuSZ:CUDA-based Error-Bounded Lossy Compressor for Scientific Data Scientific Data", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/szcompressor/cuSZ", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-24", + "metadataLastUpdated": "2021-08-24" + }, + "description": "kSZ is a Kokkos-based implementation of the world-widely used SZ lossy compressor. We use Kokkos because it provides abstractions for both parallel execution of code and data management, which can be used to support portable implementation across different accelerator technologies. Kokkos can support OpenMP/OpenMPTarget, oneAPI, Pthreads, and CUDA as backend programming models.", + "laborHours": 0.0, + "languages": [], + "name": "kokkosSZ (kSZ) A Portable Cellerator Implementation of SZ using Kokkos Programming Model", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/szcompressor/kokkosSZ", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-24", + "metadataLastUpdated": "2021-08-24" + }, + "description": "x-ray fluorescence (XRF) imaging typically involves the creation and analysis of 3D data sets, where at each scan position a full energy dispersive x-ray spectrum is recorded. This allows one to later process the data in a variety of different approaches, e.g., by spectral region of interest (ROI) summation with or without background subtraction, principal component analysis, or fitting. XRF-Maps is a C++ open source software package that implements these functions to provide a tool set for the analysis of XRF data sets.", + "laborHours": 0.0, + "languages": [], + "name": "XRF-MAPS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdvancedPhotonSource/XRF-Maps", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-24", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The Deep Lynx MOOSE Adapter connects the Deep Lynx data warehouse with any MOOSE executable. The Adapter can receive events from Deep Lynx and will take incoming data to format a template input file for the MOOSE executable. Returns from the MOOSE run are sent back to Deep Lynx for use by other applications.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deep Lynx MOOSE Adapter", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-MOOSE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "obriense@ornl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "Determine uranium and plutonium concentrations of solutions using K-edge densitometry. Returns estimates, including the uncertainty, for the mass densities of U, Pu, Np, Am, Bi, and the matrix. GUI that allows users to select high resolution gamma spectrum files of measurements of vials of solutions containing U/Pu. These spectra are fit to find to find k-edge and x-ray fluorescence peaks. The user can adjust and set fit variables, such as vial size, spectrum parameters, detector specifications, and attenuation coefficients. Technique is an accurate and rapid assay technique commonly used in nuclear fuel reprocessing facilities. The measurement is a typical international safeguards tool for accountancy of U and Pu for dissolved product solutions.", + "laborHours": 0.0, + "languages": [ + "Fortran", + "Visual Basic" + ], + "name": "MEKED Fit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/meked/HybridKedge/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/meked/HybridKedge", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "QuanSimBench is a software program that performs a gate-by-gate simulation of a quantum computer with a full state vector formulation. It simulates a simplified version of Shor's algorithm with increasing number of qubits until resources are exhausted. The score (states/s) is how fast the Approximate Quantum Fourier Transform can be computed (the modular exponentiation is not timed). The goal is to quantify the ability of a computer to simulate ideal quantum circuits.", + "laborHours": 0.0, + "languages": [], + "name": "QuanSimBench", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/datavortex/QuanSimBench", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "The tool inputs cryo electron microscopy (cryo-EM) 3-D reconstructions and an accompanying 3-D atomistic model of a molecular complex. It uses molecular simulation to guide the atomistic model into the 3-D reconstruction, making the atomistic model more consistent with the 3-D reconstruction. This will not be distributed by LANL. This was designed with the intention of being open to the public.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Cryo electron microscopy fitting ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "The number of nucleic acid sequences in GenBank has been growing exponentially for almost 40 years. With the rapid adoption of high throughput, relatively inexpensive sequencing devices, the amount of available \u201craw\u201d, unassembled sequence in the Sequence Read Archive (SRA) is significantly greater than the traditional GenBank \u201ccomplete\u201d and \u201cWGS\u201d sequence categories combined. The SRA is an invaluable data trove that contains sequence reads that reflect the enormous diversity of modern genomic science from \u201cA\u201d (aardvark gut metagenome) to \u201cZ\u201d (zebra finch auditory lobule RNA-seq). \n\nHowever, as a result of the explosive growth of the SRA traditional methods for querying sequence databases (e.g. BLAST) can no longer keep up. Instead of finding the list of best matching database sequences for a given search query (usually accompanied by pairwise sequence alignments), new search algorithms have been developed to identify the \u201csamples\u201d (i.e. collections of short, sequenced reads from a single biological sample) that are most \u201csimilar\u201d to the query sequence. These search algorithms represent collections of sequences (both the query and the database entries) as mathematical sets of short, fixed-length sequences (\u201ck-mers\u201d) and then rank potential matches between the query set and each of the database sets using the fraction of k-mers that are shared between each pair of sets (e.g. the Jaccard distance).\n\nDue to the large amount of sequence data stored in the SRA, a na\u00efve, \u201cbrute-force\u201d approach that attempts to enumerate and store the k-mers associated with each biological sample in the SRA will quickly exhaust the available storage of most high-performance computing centers. Instead, the primary innovation of the new search algorithms is the application Bloom filters (and related computer science data structures) to the massive sequence search problem. A Bloom filter provides a pragmatic trade-off between \u201cset size\u201d and \u201cmatch certainty\u201d. By using one or more hash functions to map k-mers to a smaller set of numbers, the size of k-mers used to represent a collection of sequence reads can be dramatically reduced. This brings the added benefit that smaller set sizes can be computationally compared more quickly. However, there is no bioinformatic \u201cfree-lunch\u201d \u2013 the similarity between two Bloom filters now only approximates the similarity between the underlying k-mer sets. Thanks to the properties of the hash functions used to build the Bloom filters, the approximation is \u201cone-sided\u201d \u2013 the Bloom filter-based similarity can be greater, but never less, than the true k-mer set similarity. This leads to a non-zero probability of false discovery, where a predicted database match to a query sequence is not actually similar to the query. Thankfully, the probability of a false negative (i.e. failing to report a database match that is actually similar to the query) is zero. In addition, there is practical statistics-based guidance that enables implementing a Bloom filter with a known, user-specified false discovery rate.", + "laborHours": 0.0, + "languages": [], + "name": "KWAGE (FORMERLY BIGSI++)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Bioinformatics/KWAGE", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": " The Block-Structured Adaptive Mesh Refinement (BAMR++) application provides block-structured adaptive mesh refinement data structures and an execution model for parallel computing architectures. This application also includes example tests that exercise iteration patterns over the mesh entities (cells, edges, faces). The application is written in C++.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "BAMR++", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-09-24" + }, + "description": "PYSEQM is a package for performing semi-empirical quantum mechanical (SEQM) simulations on molecular systems utilizing PyTorch. SEQM simulations determine molecular properties (energy, electron density, dipole moment, ect.) by solving an approximate Schr\u00f6dinger equation for the motions of electrons in a molecule. The use of PyTorch provides three specific advantages. First, it allows the calculations to be offloaded to GPU accelerators, giving an order of magnitude increase in speed. Second, back propagation is used to get atomic forces (derivative of the total energy with respect to atomic position) at the same computational cost as the energy calculation itself. Finally, the use of PyTorch makes for a natural interface to modern machine learning methods, which can be used to adjust the semi-empirical parameters build into SEQM methods. Additionally, PYSEQM implements various other optimizations for performing quantum mechanics based molecular dynamics, including SP2 for rapid GPU based solution of the self-consistent field algorithm, and the extended Lagrangian method for rapid QM-MD.", + "laborHours": 0.0, + "languages": [], + "name": "PYSEQM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PYSEQM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "This software simulates drawdown in an underground reservoir or aquifer using superposition of the Theis solution. Examples in the repository perform physics-informed machine learning in order to train a neural network to manage reservoir or aquifer pressures.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "MultiTheisDP", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "The River and Basin Profiler (RaBPro) represents a set of python tools that help characterize and analyze rivers and watersheds from a digital elevation model (DEM). RaBPro contains three primary functions: First, RaBPro will delineate watersheds for any given points within a DEM. Second, RaBPro will extract the elevation and slope profiles for flowlines (rivers) within the DEM. Finally, RaBPro provides convenient zonal statistics functionality for characterizing watersheds using auxiliary data the the user provides.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "River and Basin Profiler", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "Two Python files, entSpectroscopy.py and simulateCircuitsScript.py, containing the necessary code to reproduce the experiments for our recent work \"Qubit-efficient entanglement spectroscopy using qubit resets\" LA-UR-20-25416 (https://arxiv.org/abs/2010.03080). This paper described new quantum algorithms, also known as circuits, and described experiments testing these algorithms both on real quantum hardware and in simulators. The file entSpectroscopy.py contains functions which take parameters describing the input (e.g. input size) and output descriptions of quantum circuits by implementing the algorithms described in our paper. These circuit descriptions are created as `QuantumCircuit` objects using the Python library qiskit, and our simulation experiments use simulators provided by qiskit. The file also contains helper functions for processing the results of these circuits and for calculating the statistical uncertainty in the results, both according to formulas given in our paper. Finally, entSpectroscopy.py includes helper functions for easily preparing the qiskit simulator according to given noise parameters. The file simulateCircuitsScript.py demonstrates how we performed our experiments by calling functions in entSpectroscopy.py. This script takes as input parameters from the command line and hardcoded data, uses functions in entSpectroscopy.py to get circuit descriptions, simulates those circuits using qiskit, and outputs and plots the results.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Qubit-efficient entanglement spectroscopy", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "maldonadopbp@ornl.gov" + }, + "date": { + "created": "2021-08-29", + "metadataLastUpdated": "2021-08-29" + }, + "description": "In this simulation study, cycle-to-cycle fuel control was used to reduce CCV by injecting additional fuel in operating conditions with sporadic misfires and partial burns. An optimal control policy was proposed that utilizes 1) a physics-based model that tracks in-cylinder gas composition and 2) a one-step-ahead prediction of the combustion efficiency based on a kernel density estimator. The optimal solution, however, presents a tradeoff between the reduction in combustion CCV and the increase in fuel injection quantity required to stabilize the charge. Such a tradeoff can be ad- just by a single parameter embedded in the cost function.", + "homepageURL": "https://codeocean.com/capsule/8130780/tree", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Next-Cycle Optimal Fuel Control for Cycle-to-Cycle Variability Reduction in EGR-Diluted Combustion", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://codeocean.com/capsule/8130780/tree", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2021-08-30" + }, + "description": "Dakota GUI is a graphical analysis environment for Sandia\u2019s Dakota software for optimization and uncertainty quantification. This version of the Dakota GUI includes new functionality such as plotting capabilities, Eclipse-based resource management, and integration with the SAW-IF Next Gen Workflow editor. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10629 O", + "homepageURL": "https://dakota.sandia.gov/download.html", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Dakota Graphical User Interface v.6.14", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v.6.14" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2021-08-30" + }, + "description": "Sandia's Dakota software supports science and engineering transformation through advanced exploration of simulations. Specifically, Dakota manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to: (1) enhance understanding of risk, (2) improve products, and (3) assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a computational model. Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. The algorithms implemented in Dakota aim to address challenges in performing these analyses with complex science and engineering models from desktop to high performance computers. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-10468 O", + "homepageURL": "https://dakota.sandia.gov/download.html", + "laborHours": 0.0, + "languages": [ + "C++", + "C++" + ], + "name": "DAKOTA (Design Analysis Kit for Optimization and Terascale) v.6.14", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "6.14" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2021-08-30" + }, + "description": "It is an unsupervised representation algorithm used to learn morphometric properties from cellular objects. Many similar/identical open source implementations are widely available in tensorflow, pytorch, etc. And ours is implemented in matlab.", + "homepageURL": "https://bbds.lbl.gov/project/lgg-cms", + "laborHours": 0.0, + "languages": [], + "name": "stacked predictive sparse decomposition (SPSD) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bbds.lbl.gov/project/lgg-cms", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2021-08-30" + }, + "description": "Calibr8 provides an application to rapidly prototype and perform material model calibration for complex plasticity models using advanced adjoint or forward sensitivity analyses for execution on massively parallel machines. These techniques can be orders of magnitude faster than traditional finite difference approaches for material model calibration. The underlying technology used in Calibr8 is automatic differentiation, which allows for the rapid implementation and testing of new plasticity models within its framework. Additionally, Calibr8 can perform adjoint-based error estimation to approximate discretization errors for user-implemented plasticity models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10630 O", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Calibr8 v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/calibr8", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2024-04-26" + }, + "description": "ComStock\u2122 is an analytic methodology for modeling the energy usage of the commercial building stock within the United States of America. The commercial building stock is represented through a sampling of complex probabilistic distributions of various features of interest for modeling energy usage within commercial buildings. Each sample from these distributions is converted into a building energy model based on the features of that specific sample. Each building energy model can be simulated as is, but additional changes can be made to the model through addition of energy conservation measures, component faults, or other desired alterations. The results of the simulations are then processed to provide insights for various stakeholders, including but not limited to policy makers, engineers, and marketers.", + "laborHours": 0.0, + "languages": [ + "Ruby" + ], + "name": "ComStock\u2122 [SWR-19-33 and SWR-20-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ComStock", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-08-31", + "metadataLastUpdated": "2024-06-18" + }, + "description": "HIPPO software is a Python implementation of the HIPPO technology. The HIPPO technology provides the computational and modeling capabilities for managing electricity market operations and for designing and prototyping future markets. The current software can solve the day-ahead unit commitment problem and perform simultaneous feasibility test. It can be used to handle industry scale electricity market.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "HIPPO Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-08-31", + "metadataLastUpdated": "2025-03-26" + }, + "description": "The International Jobs and Economic Development Impacts (I-JEDI) model is a free, online tool for analyzing the economic impacts of renewable energy development. The tool estimates the potential gross economic impacts of wind, solar, biomass and geothermal energy projects for a specific country.\n\nI-JEDI estimates the employment, earnings, gross domestic product, and output from the construction and operation of renewable energy projects and across the domestic supply chain. The model results include total economic impacts as well as impacts by industry (e.g., construction, manufacturing, banking services, etc.). This information helps align renewable energy action with key economic development goals. I-JEDI was developed through the USAID-NREL Partnership to support informed renewable energy decisions.", + "homepageURL": "https://www.i-jedi.org/scenario/start", + "laborHours": 0.0, + "languages": [], + "name": "I-JEDI (International Jobs and Economic Development Impacts) [SWR-19-20]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/disclaimer.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.i-jedi.org/scenario/start", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "v.10" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-09-01", + "metadataLastUpdated": "2021-09-21" + }, + "description": "Sequential Training ToolKit, or STTK, is a software toolkit plugin for the Unity development platform that enables software developers to easily develop structured Sequential Training applications for gaming and extended reality (XR) environments. STTK is architected to easily import the toolkit as a plugin for the Unity platform and then interact with the graphical user interface (GUI) for drag-and-drop functionality. STTK also includes easy add-on plugins for Prefabs and auto-builds a State Machine. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-3059 O", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Sequential Training ToolKit - STTK", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/STTK", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-09-01", + "metadataLastUpdated": "2021-09-21" + }, + "description": "The Menu Framework is a reusable Extended Reality multi-level menu system for the Unity Development Platform. The menu structure is architected for reusability to suit whatever need the developer may have for a multi-level, reusable menu framework. Menu Framework's architecture, GUI, and functionality are based on the paper \"Extended Reality for Enhanced Training and Knowledge Capture\" (SAND2020-2361C). This tool uses the Microsoft Mixed Reality ToolKit (MRTK) built in functionality to provide a suite of functionalities including bounding box, follow me, minimize, maximize, settings, and help commands. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1507 O", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "MenuFramework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MenuFramework", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2021-09-01", + "metadataLastUpdated": "2021-10-16" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). 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Using the tool again will integrate these label and color coding into the existing analysis table to aid in conducting an evaluation of the network traffic.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Network Architecture Verification & Validation Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/NAVV", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "3" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2021-09-02", + "metadataLastUpdated": "2021-10-16" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model \u00ae (2021 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2021 (v1.3.0.13857)" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-02", + "metadataLastUpdated": "2021-09-02" + }, + "description": "GALATIC is a CUDA template library for performing Sparse Matrix - Sparse Matrix multiplication (SpGEMM) over arbitrary semirings on the GPU. 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The radkit libraries have associated Robot Operating System packages for use in real-time and robotic systems.", + "homepageURL": "https://sites.google.com/lbl.gov/2021-084/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "radkit v1.2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2021-084/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-084/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-08", + "metadataLastUpdated": "2021-10-06" + }, + "description": "DTX Explorer is a tool to generate interactive data visualizations of Darshan I/O traces collected from HPC applications. 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The GSM additionally provides its clients with sub-model libraries to allow them to model desired physics within their own physical models.", + "laborHours": 0.0, + "languages": [], + "name": "The Generalized Spallation Model", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/generalized-spallation-model", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2021-09-24" + }, + "description": "dbprocessing is a python framework for automating data processing pipelines. 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While the framework is written in python, it can run software in any language but may require a \u201cwrapper\u201d to translate the dbprocessing command line arguments to the form expected by the software.", + "laborHours": 0.0, + "languages": [], + "name": "dbprocessing", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/dbprocessing", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2022-01-11" + }, + "description": "These codes and scripts will perform analyses related to genetic, evolutionary and epidemiological investigations of pathogen spread. 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Our research under which these codes are developed is supported by the NIH, which requires us to share codes with other researchers.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Code for pathogen evolution and epidemiology", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2021-09-10" + }, + "description": "A collection of python scripts to load in data from supernovae simulations and use that data to model chemistry and astrophysical dust formation.", + "laborHours": 0.0, + "languages": [], + "name": "sndust", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/sndust", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2021-09-10" + }, + "description": "Understanding flow and transport in fractured rock is an important national priority, which includes environmental protection, resource development, infrastructure development, and seismic risk. In energy resources formations, such as tight sandstone formations, shale formations and coal beds with very low permeability, as well as nuclear waste repository sites, networks of fractures are typically the principal pathways for fluid and gas flow and contaminant transport. A Discrete Fracture Network (DFN) approach is an advanced method to mimic discrete pathways for fluid flow through a fractured rock mass. DFN models represent deterministically and stochastically defined fractures observed at subsurface media and to predict flow and transport for individual sites. In order to achieve accurate flow and transport predictions, a high-quality computational mesh is required. The geometric features (fractures, fracture intersections, spaces between fracture intersections, etc.) that must be resolved in a generated DFN typically span a wide range of spatial scales and make the efficient automated generation of high-quality meshes a challenge. To deal with these challenges, many approaches deform the DFN to align its features with a mesh. The proposed nudging technique allows for the production of a high-quality conforming Delaunay triangulation of a DFN without significant modification of fractures location, size, orientation, and topology. The nudging technique is based on the feature rejection algorithm for meshing (FRAM). Using FRAM, the DFN mesh is constructed so that all the features in the network, e.g., length of intersections between fractures and distance between lines of intersection of a fracture are equal to or larger than a user-defined minimum length scale, h. FRAM performs well in the case of stochastically defined networks, where fractures size, positions, orientation, etc., are sampled from given probabilistic distributions. However, reproducing a DFN with deterministically defined fractures where fractures position, orientation and size are rigidly defined, is not possible using the standard version of FRAM. This nudging technique is developed to accompany FRAM and produce high quality mesh on a DFN with both stochastic and deterministic fractures. The essence of the nudging technique is in the fracture perturbation in fracture location and fracture orientation in the way that keeps the fracture within a distance h of their original position and do not create any features smaller than h. If needed, the nudging approach applies multiple times until the desired requirements on distance are met with no significant fracture network deformation and no original connectivity modification. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Nudging Technique for Robust Meshing of Intersecting Polygons in Discrete Fracture Networks v1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "State of Stress Analysis Tool (for carbon sequestration). The SOSAT tool provides value during GCS site screening and characterization phases to target collection of specific additional data to constrain uncertainties in geomechanical risk and to help operators to make informed decisions during the operational phase (Appriou et al., 2019). The capability represented in SOSAT, therefore, helps build stakeholder confidence that geomechanical risks are understood and manageable", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/SOSAT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SOSAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Codebase for analyzing large atomistic simulation results using graph analytics. Analysis of large molecular simulations is difficult due to size and memory constrains in commonly used analysis software. This code was developed to analyze an ~8 million atom polycrystalline Al system under shear, with a particular emphasis on identifying defect structures. This code applies graph theory to reduce the system to components of interest and applies associated algorithms to characterize these components.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/galas", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/galas", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The concept of the software is for a user to input the desired decay period and initial isotopic distribution and radioactivity, and RA-Decay will return the new isotopic distribution and radioactivity including the progeny ingrowth.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "RA Decay", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-09-15", + "metadataLastUpdated": "2023-05-26" + }, + "description": "Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by NREL. This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript \"Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning\", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nrel.gov for any questions.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "AI-BATT-OS (Autonomous Identification of Battery Life Models \u2013 Open Source) [SWR 21-17 and SWR 21-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/AI-Batt-OS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-09-15", + "metadataLastUpdated": "2021-09-15" + }, + "description": "Predictive modeling of patient tumor growth response to drug treatment is severely limited by a lack of experimental data for training. Combining experimental data from several studies is an attractive approach, but presents two problems: batch effects and limited data for individual drugs and cell lines. Batch effects are caused by systematic procedural differences among studies, which causes systematic experimental outcome differences. Directly using these experimental results as features for machine learning commonly causes problems when training on one study and testing on another. This severely limits a model's ability to perform well on new experiments. Even after combining studies, predicting outcomes on new patient tumors remains an open challenge. We propose a semi-supervised, autoencoder-based, machine learning procedure, which learns a smaller set of gene expression features that are robust to batch effects using background information on a cell line or tissue's tumor type. We implemented this reduced feature representation and show that the new feature space clusters strongly according to tumor type. This experiment is carried out across multiple studies: CCLE, CTRP, gCSI, GDSC, NCI60, and patient derived tumors. We hypothesize that using a batch effect resistant feature set across studies will improve prediction performance. Genome Data Commons (GDC) gene expression profiles for publicly available human tissues and cell lines from NCI60 and CCLE were processed using the semi-supervised learning procedure. Our autoencoder repurposes the 'center loss' (CL) cost function of Wen et. al. to learn a more generalized set of features using the cell line or tissue's tumor type. ", + "laborHours": 0.0, + "languages": [], + "name": "RNA-seq latent featurizer using center loss cost function", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CBIIT/NCI-DOE-Collab-Pilot1-Semi-Supervised-Feature-Learning-with-Center-Loss", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-09-15", + "metadataLastUpdated": "2021-09-15" + }, + "description": "Axom is an open-source library of \"building block\" software components that provide core infrastructure capabilities for HPC applications. Such capabilities include: input file parsing and verification for various file formats, format specification for material shape input to multi-material simulations and tools for placing those shapes on meshes, parallel distributed coordination of diagnostic messages, geometric primitives, spatial queries and spatial search acceleration data structures, in memory key-value data store for managing simulation data and parallel file I/O. Axom components are used widely across LLNL Advanced Simulation and Computing program applications. It is also part of the LLNL institutionally-supported RADIUSS project, which promotes and funds its adoption by projects across LLNL.", + "laborHours": 229945.6, + "languages": [], + "name": "Axom", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/axom", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.6.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-09-16", + "metadataLastUpdated": "2021-09-16" + }, + "description": "Fast ion transport along the electrode thickness is required for Lithium ion battery (LIB) to sustain continuous high-rate discharge or charge currents, which is a desired feature for the fast charging of electric vehicle batteries. Advance in LIB electrode manufacturing allows to control, to a certain extent, the electrode microstructure architecture in order to improve the macroscopic performances of these devices. For instance, several groups have experimentally tested architectures tailored specifically to increase the through plane ionic diffusion in regards for fast charge application by adding channels or groove-like large pores oriented along the electrode thickness. These voids do not replace the existing pores of the electrode microstructure but consist in a second, coarser, pore network, called the secondary pore network (SPN). The model quantifies the impact of SPN on ionic diffusion with a composite electrode through a simple analytical approach, considering various pore channel geometries and comparing to standard electrodes with identical gravimetric and identical volumetric specific theoretical capacity. The goal is to find optimal SPN design parameters according to three optimization objectives aiming to balance the improved overall through-plane, thanks to the coarse aligned channels, and the degraded in-plane diffusion, due to the porous matrix densification required to maintain gravimetric and volumetric specific theoretical capacity. The analytical model must be considered as a pre-screening tool to quickly investigate large design space, that can be refined later with more complex electrochemical CPU-expensive numerical models.", + "laborHours": 0.0, + "languages": [], + "name": "Secondary Pore Network Design Optimization Analytical Diffusion Model for Lithium Ion Battery", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Secondary_pore_network", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2023-03-13" + }, + "description": "Temporal analysis of products statistical analysis package (tapsap) is a package for reading, cleaning, analyzing and making inference of temporal analysis of products (TAP) information. This package is designed with the intent for collaboration within the TAP community for advancing TAP analysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Temporal Analysis Of Products Statistical Analysis Processing", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/tapsap", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Procedure for reverse engineering binary files and storing the result in a graph database structure for later analysis. This is achieved through the use of Python, angr, and OrientDB Community Edition.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DISCOverflow", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/idaholab/DISCOverflow/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DISCOverflow", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "3.6 and up" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-17" + }, + "description": "The Devastator runtime is a modern C++ implementation of optimistic parallel discrete event simulation methods. Devastator allows simulation application code to productively specify their component and event functionality with C++14 constructs. It utilizes GASNet-EX for distributed memory communication and includes parallel performance optimizations such as light-weight thread message queues and asynchronous GVT. Furthermore, it supports efficient event broadcasts and pause-rewind-resume functionality to support periodic load balancing and outer loop optimization algorithms.", + "laborHours": 0.0, + "languages": [], + "name": "Devastator Parallel Discrete Event Simulation Runtime (Devastator) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cychan-lbnl/devastator.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-17" + }, + "description": "LW3D is code for modeling beam dynamics in particle accelerators including Lienard-Wiechert self-fields. It is similar to codes like IMPACT-T except that the Poisson solver is replaced by a Lienard-Wiechert solver. Along with space-charge effects, the code can model effects like coherent synchrotron radiation.", + "laborHours": 0.0, + "languages": [], + "name": "LW3D v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LienardWiechert/LW3D", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-20" + }, + "description": "DASSA (Parallel DAS Data Storage and Analysis) provides a data storage engine and analysis engine for data from distributed acoustic sensing and other methods. It supports various data analysis operations, from FFT , signal filter, cross-correlation, compression, stacking etc.", + "laborHours": 0.0, + "languages": [], + "name": "DASSA v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/dbin_sdm/dassa/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-21" + }, + "description": "A suite of non-proprietary C-like procedures (code) that compile and run within the commercial Igor Pro data analysis program (wavemetrics.com) have been developed for the data file loading, plotting and analysis of Angle-Resolved Photoemission Spectroscopy (ARPES) data. The data file loading procedures are more specific to ARPES data acquisition and file formats at Advanced Light Source (ALS) beamlines, while plotting and analysis procedures are more generic to processing of 1D, 2D and higher dimensional dataset arrays with some specific tools tailored to the ARPES technique.", + "homepageURL": "https://sites.google.com/lbl.gov/2021-158/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Igor Pro procedures for ARPES analysis (ARPES Igor procedures) v21.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-158/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-17" + }, + "description": "H5TurboPFor is a wrapper for the TurboPFor-Integer-Compression for HDF5 library. Basically, it enables the HDF5 library to compress integer data using the TurboPFor.", + "laborHours": 0.0, + "languages": [], + "name": "H5TurboPFor v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/berkeleysdm/H5TurboPFor.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-21", + "metadataLastUpdated": "2021-09-21" + }, + "description": "The Localization and Mapping Platform (LAMP) software fuses radiation and contextual data to produce 3-D maps that locate and identify gamma-ray emitting sources in complex environments. It enables data collection, fusion, and processing in near-real-time and on-board in several configurations, including handheld and unmanned aerial system (UAS) form factors.", + "homepageURL": "https://sites.google.com/lbl.gov/2018-041/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Localization and Mapping Platform Software (LAMP Software) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2018-041/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2018-041/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-21", + "metadataLastUpdated": "2021-09-21" + }, + "description": "Occupant schedules at room level are crucial information to building energy modeling which quantifies occupant-related energy efficiency technologies and controls for new building design as well as existing building retrofits to reduce energy use and GHG emissions in buildings. The Occupancy Simulator Solver is an executable software component that simulates the stochastic behavior of occupant presence and movement in a building using the Markov-chain model. Occupancy Simulator Solver is the calculation engine of the web App Occupancy Simulator, which takes high level input on occupants, spaces and events, then calls the Solver to simulate occupant movement and generate occupant schedules for each space. The generated schedules capture diversity and stochastic nature of occupant activities (e.g., in office, meetings, breaks, lunch). These schedules are stored in CSV files and can be downloaded from the App and used for building performance simulation.", + "homepageURL": "https://sites.google.com/lbl.gov/2019-163/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Occupancy Simulator Solver v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2019-163/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2019-163/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-21", + "metadataLastUpdated": "2021-09-21" + }, + "description": "The Radiological Anomaly Detection and Identification (RADAI) software package is a python library for implementing, training, and storing algorithms that detect and identify anomalies in gamma-ray spectra. The library defines a general framework for implementing detection (binary) and identification (classification) algorithms, objects to encapsulate the results of analyses, a variety of temporal filtering tools that can be used in constructing algorithms, and conceptual design that allows easy reading and writing of algorithms (and their time dependent state). In addition to this framework, the library includes implementations of a variety of algorithms from the scientific literature including: gross-counts k-sigma, SPRT, N-SCRAD, Region of Interest, and Censored Energy Window. The implementation of these algorithms within the RADAI package was done to facilitate user-initiated training and configuration to by applied to different gamma-ray detector types. Finally, benchmarked and synthetic datasets will be made available for standardized algorithm characterization with corresponding utilities in the RADAI package for data access and processing.", + "laborHours": 0.0, + "languages": [], + "name": "Radiological Anomaly Detection And Identification (RADAI) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/lbl-anp/radai/radai", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A data annotation tool that integrates with the python Jupyter notebook environment.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/diet-parselantro", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/diet-parselantro", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "DM-Sim: Quantum Simulator on GPU Cluster using Density Matrix: a new simulation approach that significantly reduces communication overhead.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/DM-Sim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/DM-Sim", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2021-09-22" + }, + "description": "A library for solving large scale power system stochastic multi-period security-constrained optimization problems on next generation exascale architectures", + "laborHours": 0.0, + "languages": [], + "name": "ExaGo", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/exasgd/frameworks/exago", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Dynamics-based deep learning methods to modernize current scientific computing methods. Neuromancer is currently capable of solving inverse problems for a system of ordinary differential equations. The functionality includes system identification and constrained optimal control of unknown or partially known ODEs.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/neuromancer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/neuromancer", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A data-driven performance verification framework, which conducts automated output-based verification of building performance (especially control requirements which be only verified via time-series output)", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/ANIMATE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ANIMATE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2021-09-22" + }, + "description": "FunFact is a Python package for functional factorization of matrices and higher-order tensors", + "laborHours": 0.0, + "languages": [], + "name": "FunFact v0.6", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yhtang/FunFact.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2021-09-22" + }, + "description": "Simcov is an agent-based model of the spread of viral infections and the immune response in human lung at the cellular level. It is designed to scale well on HPC systems. No other software like it currently exists.", + "laborHours": 0.0, + "languages": [], + "name": "simcov v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdaptiveComputationLab/simcov.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "oeschts@ornl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2021-09-23" + }, + "description": "To reduce hand/wrist pain from frequent computer use I decided to create a program that will convert voice to common keyboard/mouse actions in order to reduce clicks/keypresses. It is not intended to replace the keyboard and mouse, but rather to reduce their use, hence the name Sidekick. Sidekick handles transcription, mouse movement/click/wheel, and common commands.\n", + "laborHours": 0.0, + "languages": [], + "name": "Sidekick", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/oeschsec/Sidekick---voice-controlled-keyboard-and-mouse", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A software for a multi-challenge power-flow grid optimization competition was developed. The platform brings together high performance computing clusters, webservers, databases, competition datasets, schedulers, evaluation codes, and a multitude of language compilers and optimization solvers to host the competition. The original video announcing the competition, from former Secretary Perry, at: https://www.youtube.com/watch?v=hZwX3P9vS8M", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Grid Optimization (GO) Competition Platform", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ConverterBlocks uses the output of detailed electromagnetic transient (EMT) simulations to produce generalized block diagram models of power electronic systems. The process uses deep learning with customized block architectures. The outputs are reduced-order models that meet specified accuracy requirements, while providing important advantages over the original EMT models: ConverterBlock models have fewer nodes and can take longer time steps, resulting in shorter simulation times ConverterBlock models are continuously differentiable, making them compatible with control design methodsGeneralized block diagram modeling of power electronic converters for grid solar and storage applications.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/pecblocks", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pecblocks", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Distributed photovoltaics protection software toolkit The code package includes several important functions for design and analysis of new grid protection schemes, for scenarios of distributed photovoltaic (DPV) generation approaching 100% of the peak feeder load, i.e., high-penetration DPV. Convert distribution feeder models, used by planning engineers, to electromagnetic transient (EMT) models that produce waveforms for advanced relay algorithms. Visualize the results of protection scheme operation. Tools to determine distance relay settings on distribution systems. Tools to predict the performance of time-domain, incremental distance relay algorithms", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/DPVPROT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/DPVPROT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "NWQSim is a quantum circuit simulation environment developed at PNNL. It currently includes two major components: a state-vector simulator (SV-Sim) and a density matrix simulator (DM-Sim) and we may add more components, such as a Clifford simulator, in the future effort. NWQSim has two language interface: C/C++ and Python. It supports Q#/QDK frontend through QIR and QIR-runtime. It supports Qiskit and Cirq frontends through OpenQASM. NWQSim runs on several backends: Intel-CPU, Intel-Xeon-Phi, AMD-CPU, AMD-GPU, NVIDIA-GPU, and IBM-CPU. It supports three modes: (1) single processor, such as a single CPU (with and without AVX2 and AVX512 acceleration), a single NVIDIA GPU or a single AMD GPU\u037e (2) single-node-multi-processors, such as multi-CPUs/Xeon-Phis, multi-NVIDA/AMD GPUs\u037e (3) multi-nodes, such as a CPU cluster, a Xeon-Phi cluster (e.g., ANL Theta, NERSC Cori), an NVIDIA cluster (e.g., ORNL Summit, NERSC Perlmutter).", + "laborHours": 0.0, + "languages": [], + "name": "NWQ-sim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/sv-sim", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Subgraph Based Learning of Contextual Embedding\na framework bridging static representation learning methods using global information from the entire graph with localized attention driven mechanisms to learn contextual node representations.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/SLiCE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SLiCE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Two datadriven predictive approaches, namely, {\\em Koopman Operator Theoretic (KOT)-based} model and {\\em Graph Neural Network (GNN)-based model}, to enable effective power system state predictions. The KOT-based approaches (Robust\nDMD, deepDMD) capture the power system evolution as a linear dynamical system on an abstract space. The GNNs model the spatio-temporal correlations using graph convolutional network and are called Spatio-Temporal Graph Convolutional\nNetwork (STGCN). These predictive models are trained, tested and compared rigorously based on their predictions of frequencies in the IEEE 68 bus system when subjected to a disturbance. GridSTAGE framework developed at Pacific Northwest National Laboratory is leveraged to generate multiple datasets (in the form of PMU measurements) for training and testing by strategically creating load changes across the spatial locations of the network", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/grid_prediction", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/grid_prediction", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "Codes developed by ASC supported personnel for generating semi-analytic solutions to traditional verification test problems. \n\nConcrete example is a script written to do a numerical integral of an analytic function that serves as a known solution to a complex differential equation. This is very useful when checking if your general purpose physics code can produce the solution you expect when it starts from a set of known initial conditions. If the form of the integral is complex, the only way to evaluate the integral is to write a code that performs the integration numerically.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "ASC Blanket Disclosure 5", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "Software developed by ASC personnel and that includes physics which aims to understand astrophysics-only applications. \n\nThis provides a list of concrete code types allowed within this Blanket, but here I offer more detail about what each of those types entail.\n- Galactic Chemical Evolution: Uses prescriptions to define the synthesis of heavy elements from various astrophysical objects (stars, supernovae, novae, big bang), and then represents the rate at which these astrophysical objects occur within our galaxy. The convolution of the rate of incidence with the material released by each instance gives a prediction for the chemical evolution of the galaxy.\n- Stellar Population Synthesis: Uses prescriptions for the rate of occurrence of various properties or events in the life of a star (its initial mass, whether it has a binary companion, its binary distance separation, etc) to model what happens to the stars as they evolve. Gives a sense of what a population of stars should look like statistically speaking. Useful for predicting, for example, how many binary stars will merge in our galaxy in the next 1 million years, or how many supernovae do we expect to see with current telescopes.\n- Hydrostatic equilibrium, time-implicit, stellar evolution codes: Uses equilibrium equations to show how the structure of a star must change throughout its life. Assumes that gravity is equally balanced by stellar pressure at all times. Includes nucleosynthesis network for calculating energy generation from nuclear burning in the star. This energy generation holds the star up against the gravitational forces trying to collapse the star. Hydrodynamic timescales are not resolved, only hydrostatic is considered. \n- Astrophysical nuclear / astrophysical chemical network codes: Solves a system of rate equations that describe the network of elements involved in nuclear or chemical evolution for astrophysical events (e.g. supernovae, stars, big bang, protostars, interstellar medium). These codes are designed for use in post-process, which means that the density and temperature conditions in a fluid element are defined versus time and fed into these codes. Then, these codes report back how the nuclear or chemical makeup of the fluid element would evolve based on those conditions. There is no feedback from the energy released by that evolution on the fluid element\u2019s conditions.\n-Astrophysical orbital dynamics codes: Calculates the orbits of a set of point masses according to the laws of gravity (e.g. planetary systems, solar system asteroids, extra-solar planet orbits\u2026).", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "ASC Blanket Disclosure 4", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2022-01-06" + }, + "description": "Modern data scientists are tasked to analyze ever-growing data sets with increasingly complex relationships. Tensor decompositions have come to play a central role in identifying underlying latent structures in higher-order data. The problem of fitting tensor models to different distributions is complicated by the combinations of size, dimensionality, and sparsity present in real world data. The situation demands efficient algorithms designed for shared-memory and distributed systems. This work will present new research that tackles these challenges on several different fronts, leveraging optimizations in numerical algorithms and sparse tensor representations in heterogeneous high performance computing environments.", + "laborHours": 0.0, + "languages": [], + "name": "pyDRESCALk", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyDRESCALk", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "Code used in the generation, application, and execution of model and methods related to work in theoretical and computational biology specifically surrounding the evolution, ecology, and epidemiology of infectious disease. This code included the implementation of models used for data analysis, code to generate figures, code to process and manipulate data for said purposes, and code to execute published analyses. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Blanket software for theoretical and computational biology applications", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "PALM-LANL is a model system for conducting large-eddy simulations, that is, simulations of turbulence that only resolve the largest turbulent eddies and rely on a turbulence closure scheme to represent the smallest turbulent eddies. PALM-LANL is based on PALM version 5.0 but it contains numerous modifications by LANL authors to add research capabilities. PALM is written for atmosphere and ocean turbulence; PALM-LANL includes modifications and additions to the ocean turbulence components, analysis, and data output capabilities. ", + "laborHours": 0.0, + "languages": [], + "name": "LANL Contributions to Parallelized large-Eddy Simulation Model Formerly PALM-LANL", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/palm_lanl", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "The \"Wrapper for the optimization of cross-section generation in OpenMC\" is Python-based software that runs the open-source Monte Carlo code OpenMC (https://docs.openmc.org/en/stable/ ) to generate cross-sections for any reactor geometry. The wrapper then optimizes those cross sections. The optimization aims to choose an energy group structure and a scattering representation that maximize accuracy with respect to continuous-energy results while avoiding significant computational expense. It then outputs these cross-sections in an ISOXML format readable by the Idaho National Lab code suite MOOSE (Olin William Calvin, Mark D DeHart, \u201cArchitecture for the Performance of Nuclear Fuel Depletion Calculations\u201d, Idaho National Laboratory report, November 2019). The expected use-cases of this software include: -finding the best group structure and scattering representation for a specific reactor -testing the appropriateness of energy group structures for different reactor types -comparing energy group structures and scattering representations to each other -generating cross sections for use in deterministic codes, including ones found in the MOOSE suite The example reactor geometry included in this release is a generic reactor design, not based on any reactor in existence or in development. It was fabricated for the sole purpose of being a \u201ctestbed-geometry\u201d upon which to develop this tool. Since the tool is designed to be generic, the nature of the test geometry is not very important, however, it is valuable to include as an example for users who are unfamiliar with developing reactor geometries for OpenMC.", + "laborHours": 0.0, + "languages": [], + "name": "Wrapper for the optimization of cross-section generation in OpenMC", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/TOGA.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "The Sequence Read Archive (SRA) is a cloud-based repository of biological sequence data provided by the National Center for Biotechnology Information. 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The \u201csracat\u201d tool provides a fast, reliable conversion utility for use-cases that do not require ordered reads.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "sracat", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "This version used only for additional G-cases in the v1 Cryosphere campaign. MPAS-Ocean: Update MPAS-source to GM varying, add namelist options for 3D varying GM bolus Kappa Flags are added to enable the 3D varying GM bolus Kappa, it is enabled by default and is on whenever the GM parameterization is on. Output of kappaGM3D and the phase speed are added to monthly history as well Differences from v1.2 simulations include above and all of those listed in the v1.3.0-beta tag.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v1.3", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v1.3.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v1.3.0" + }, + { + "contact": { + "email": "bernholdtde@ornl.gov" + }, + "date": { + "created": "2021-09-26", + "metadataLastUpdated": "2021-09-28" + }, + "description": "IPS is an environment to orchestrate complex coupled simulation workflows on parallel computers. 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The biogeochemical calculations using CE-QUAL-ICM kinetics are conducted over the same finite-volume mesh and in the FVCOM framework.", + "laborHours": 0.0, + "languages": [], + "name": "FVCOM-ICM4.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ssmc/fvcom-icm4.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2021-09-27", + "metadataLastUpdated": "2022-11-18" + }, + "description": "First release of version 2 of the Energy Exascale Earth System Model. The atmosphere component remains EAM. Major changes since version 1 include: all column-physics parameterizations are computed on a separate grid that has approximately half the number of points of the dynamics grid, a new nonhydrostatic dynamical core (running in hydrostatic mode) with semi-Lagrangian tracer transport, CLUBB updated from v1 to v2, a new convective trigger (dCAPE/ULL) based on the dynamic Convective Available Potential Energy (CAPE) (dCAPE) and the Unrestricted Launch Level (ULL) concepts is used in ZM. minimum cloud droplet number changed, gravity wave drag energy conservation fixed and new tunings used, dust emission size distribution changed to emit more coarse dust particles The land component is still ELM. Major changes since version 1 include: using SNICAR-AD for radiation in snow to match the sea-ice model and fixing bugs in snow compaction and water state calculation. The ocean component remains MPAS-ocean. Major change since version 1 include: Redi isopycnal mixing has been updated, tested, and tuned in combination with the Gent-McWilliams parameterization, a sign error was fixed in the 3rd-order flux routines, the mesh used in low-resolution coupled cases was modified and the time steps adjusted, new regionally refined meshes were created, one focused on North America and another on the Southern Ocean, including ice shelf cavities. The sea-ice component remains MPAS-seaice. Major changes since version 1 include: A new heat- and freshwater-conserving coupling of frazil ice, turning off of SSH filtering, addition of SNICAR-AD and snow grain aging. The land-ice component remains MPAS-Albany-landIce (MALI) and is a static ice sheet. There is more out-of-the-box support for cryosphere configurations including the new regionally refined configuration around Antarctica with ice shelf cavities. The river model is MOSART. The half-degree river mesh was redone so it no longer treats Black and Caspian seas as ocean. The coupler remains cpl7/MCT. Major changes since version 1 include handling of ice shelf melt fluxes (heat / freshwater exchange with the ocean), and data icebergs. All components allow regional refinement of their meshes and two separate example of refinement, one in and around North America and one around Antarctica and the Southern Ocean, are provided.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v2.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v2.0.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v2.0.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "OpenMC is an open source, community-developed framework for performing Monte Carlo particle transport calculations.It is capable of simulating neutron and photon transport below ~50 MeV and also includes a model for bremsstrahlung\nproduction of photons by electrons/positrons. Fixed source, k-eigenvalue, and subcritical multiplication problems can be\nsolved. Problem geometries can be modeled either using constructive solid geometry or a CAD representation. A flexible and efficient tally system enables a wide variety of physical quantities to be tallied and analyzed. OpenMC can run in\nparallel using a hybrid MPI and OpenMP programming model and has been extensively tested on leadership class supercomputers. A built-in Bateman equation solver enables the modeling of material composition changes due to\nirradiation. One of the unique features of OpenMC is its rich, extensible Python and C/C++ programming interfaces that enable programming pre- and post-processing, multigroup cross section generation, workflow automation, multiphysics\ncoupling, and the visualization of geometry and tally results. In addition to the core Monte Carlo transport solver and associated APIs, OpenMC includes a Python-based nuclear data interface that enables power users to inspect, modify,and perform various types of nuclear data processing on ENDF, ACE, and OpenMC\u00bfs native HDF5 files", + "laborHours": 0.0, + "languages": [], + "name": "OpenMC", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openmc-dev/openmc", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The Infrastructure Expression: Discovery Tools is a toolset that allows for the automated collection of various network, hardware, and software vulnerabilities and details to be collected from systems on a given network. These details are then converted into a STIX 2.1 format, allowing for easy viewing in existing applications as well as sharing and interfacing with tools that already use the STIX 2.1 format.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Infrastructure Expression: Discovery Tools", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/IX-DiscoveryTools", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "3" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "The MIRA project comprises of a set of Python drivers that enable rigorous intercomparison of remapping algorithms by providing the infrastructure for computing the numerical metrics of interest for ESM. This work is funded by the SciDAC Coupling Approaches for Next-Generation Architectures (CANGA) project.", + "laborHours": 0.0, + "languages": [], + "name": "METRICS FOR INTERCOMPARISON OF REMAPPING ALGORITHMS (MIRA)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CANGA/MIRA-Datasets", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Unit operations for the MSW sorting process include shredding, magnets for ferrous separation, screening, air classification, eddy current for non-ferrous separation, and near-infrared detection for plastic recovery. 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Enthalpy and density of the non-conventional materials were defined using non-conventional material properties.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Aspenplus Model For Msw Sorting Process", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/AspenPlus", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "MPI-distributed expert-focused C++-based modeling system that is designed for use on large computing clusters and supercomputers.", + "laborHours": 0.0, + "languages": [], + "name": "Repast for High-Performance Computing )Repast HPC", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Repast/repast.hpc", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "ChiSIM is a framework for implementing agent-based models that simulate the mixing of a synthetic population. 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For example, an agent may expose other agents to a disease in an epidemiological model.", + "laborHours": 0.0, + "languages": [], + "name": "The Chicago Social Interaction Model (ChiSIM)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Repast/chiSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-30" + }, + "description": "PIRT is a tomography inversion code that incorporates center of rotation correction written with the goal of being scalable on HPC systems. PIRT is built upon PETSc (which handles the optimization routines, data management and parallel I/O), Boost (which handles geometry routines) and FFTW (for position correction cost function evaluation).", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Iterative Reconstruction for Tomography", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-30" + }, + "description": "CityCOVID is a detailed agent-based model that represents the behaviors, contacts and COVID-19 disease progression of millions of residents in a large urban area.", + "homepageURL": "https://www.anl.gov/dis/citycovid", + "laborHours": 0.0, + "languages": [], + "name": "CityCOVID", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/dis/citycovid", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/dis/citycovid", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "UUDEX describes a communications architecture and protocol suite that allows organizations to exchange data and information. It does this by defining relations between a set of client nodes that share data via a set of server nodes. The primary focus of UUDEX is to facilitate communications between control centers, operations centers, and other trusted organization.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/UUDEX", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/UUDEX", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "Symbolic regression software that formulates a symbolic regression problem as a mixed-integer nonlinear optimization problem, and solves it using a sequential tree construction heuristic", + "laborHours": 0.0, + "languages": [], + "name": "STreCH", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jongeunkim/STreCH", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-30" + }, + "description": "Models the generation asset investment decisions of individual utility \"agents\" in a user-specified electricity market. Agents employ limited local resources and information to evaluate projections of future market events, and determine when and how quickly they should construct new generation assets to respond to market trends and the retirement of existing system assets. ABCE is implemented in Python and Julia, and can be connected to the ANL A-LEAF electricity system optimization code; the contribution from A-LEAF is completely compartmentalized in the code's execution and will not be released as open-source at this time.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "ABCE (Agent Based Capacity Expansion)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-30" + }, + "description": "The software develops a framework for training intelligent agent to conduct automatic service restoration in power distribution systems. The framework is based on imitation learning paradigm with a mixed-integer programming based expert and environment. The software also provides access to reinforcement learning baseline comparison.", + "laborHours": 0.0, + "languages": [], + "name": "IntelliHealer: Imitation Learning Online Service Restoration", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/whoiszyc/IntelliHealer", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "This repository consists of various code examples demonstrating common patterns used in High-Performance Computing (HPC). Indeed, examples showcasing innovative usage of newly developed capabilities of HPC libraries are highly demanded by the HPC community. This repository's goal is to fulfill those requests.", + "laborHours": 0.0, + "languages": [], + "name": "HPC-PATTERNS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/argonne-lcf/HPC-Patterns", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-30" + }, + "description": "The software performs Monte Carlo simulations for artificial spin ice (ASI) structures. ASIs are composed of magnetic nano islands on varying lattice geometries. The software computes the dipolar energy of the neighboring islands and determines their ground state configuration. Various thermodynamic parameters are also calculated during the simulations. 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SAND2021-2714 O", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "ParseGen v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/parsegen-cpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-10-04", + "metadataLastUpdated": "2024-01-03" + }, + "description": "The U.S. Department of Energy's Bioenergy Technologies Office and the National Renewable Energy Laboratory (NREL) developed the BSM (Bioenergy Scenario Model) to explore the development of a U.S. biofuels industry. The BSM is a system dynamics model built on the STELLA software platform. 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Instead, it is best used to (1) analyze and evaluate alternate policies; (2) generate scenarios; (3) identify high-impact levers and bottlenecks to system evolution; and (4) seed focused discussion among policymakers, analysts, and stakeholders.", + "laborHours": 0.0, + "languages": [ + "STELLA" + ], + "name": "BSM (Bioenergy Scenario Model) FKA: Biomass Scenario Model [SWR-09-09]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bsm-public", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-10-04", + "metadataLastUpdated": "2024-01-25" + }, + "description": "The Caltalyst Layer Crack Detector, or CLCD (\"clicked\") is a program that takes in optical micrographs of catalyst coatings for PEM fuel cells or electrolyzers and calculates the percent area that consist of cracks. It does so using a custom algorithm that searches for dark features larger than the background graininess of the catalyst layer.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Caltalyst Layer Crack Detector, or CLCD (\"clicked\") [SWR-20-60]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Caltalyst-Layer-Crack-Detector-CLCD", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-10-04", + "metadataLastUpdated": "2024-03-19" + }, + "description": "A circular economy emphasizes the efficient use of all resources (e.g., materials, land, water). Despite anticipated overall benefits to society, the transition to a circular economy is likely to create regional differences in impacts. Current tools are unable to fully evaluate these potential externalities, which will be important for informing research prioritization and regional decision making. The Circular Economy Lifecycle Assessment and VIsualization (CELAVI) framework allows stakeholders to quantify and visualize potential regional and sectoral transfers of impacts that could result from transitioning to a circular economy, with particular focus on energy materials. The framework uses system dynamics to model material flows for multiple circular economy pathways and decisions are based on learning-by-doing and are implemented via cost and strategic value of different circular economy pathways. It uses network theory to track the spatial and sectoral flow of functional units across a graph and discrete event simulation to to step through time and evaluate lifecycle assessment data at each time step. The framework is designed to be flexible and scalable to accommodate multiple energy materials and multiple energy technologies. 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The model developed in Simulink has been designed and tuned to match the governor-turbine response for a real-world hydropower unit owned by Idaho Falls Power (IFP). The Simulink and RSCAD models enable real-time testing in a hardware-in-the-loop (HIL) implementation using OPAL-RT and RTDS digital real-time simulators, respectively. An automatic initialization for dynamic simulation has also been integrated to each model in both Simulink and RSCAD. The RSCAD initialization involves a novel python-based interfacing for automatic modification of the initial conditions in the model. The parameters of these models can be tuned to match other hydropower plants in this class.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python", + "Simulink" + ], + "name": "Bulb-style Kaplan Turbine - Run-of-the-river (ror) Hydro Governor And Turbine Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Hydropower_Unit_Models", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kimj@ornl.gov" + }, + "date": { + "created": "2021-10-20", + "metadataLastUpdated": "2021-10-27" + }, + "description": "A unified framework across multiple programming platforms", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Fortran", + "Python" + ], + "name": "IRIS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/iris", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-21", + "metadataLastUpdated": "2021-10-21" + }, + "description": "ScalES is a high performance software package for performing large scale electronic structure calculations on high performance supercomputers.", + "laborHours": 0.0, + "languages": [], + "name": "Scalable Electronic Structure (ScalES) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/scales/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-21", + "metadataLastUpdated": "2021-10-21" + }, + "description": "MFDn kernels is a collection of small subroutines designed to capture essential characteristics of the Many-Fermion Dynamics---nuclear (MFDn) application (DOI: 10.1016/j.procs.2010.04.012). 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The package includes a Simulink S-Function that allows communication to the data broker via inter process communication; a data broker, which orchestrates communication between the emulated control system network and the simulation; an endpoint, which facilitates communication between the data broker and PLC's on the control network using ModBus/TCP; and an example PLC structured text files that work with OpenPLC, an open source emulated PLC. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-11479 O", + "laborHours": 0.0, + "languages": [ + "Python", + "Simulink", + "S Function", + "C Code", + "Python" + ], + "name": "OT Emulation Data Broker", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SMARTT", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-11-03", + "metadataLastUpdated": "2024-07-30" + }, + "description": "OptML is an open-source Python package that provides modeling and solution capabilities for optimization problems with embedded machine learning models. OptML is a collaborative open-source project that includes advanced algorithms from the academic community for efficient solution of these problems. Sandia contributions to this package include the development of interfaces between these algorithms and Pyomo. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10861 O", + "laborHours": 1155.2, + "languages": [ + "Python" + ], + "name": "OptML", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/OptML", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-11-03", + "metadataLastUpdated": "2021-11-03" + }, + "description": "HyRAM+ is a software toolkit for conducting quantitative risk assessment (QRA) and consequence modeling for hydrogen and other alternative fuels infrastructure and transportation systems. HyRAM+ contains validated, simplified release behavior models, a standardized QRA approach, and engineering models and generic data relevant to hydrogen installations. HyRAM (hydrogen-only) versions 1.0 to 3.1 were developed by Sandia for the U.S. Department of Energy (DOE) Hydrogen and Fuel Cell Technologies Office (HFTO). The U.S. DOE Vehicle Technologies Office (VTO) and U.S. Department of Transportation (DOT) Pipeline and Hazardous Material Safety Administration (PHMSA) contributed to the development of HyRAM+ version 4.0 regarding the addition of methane (natural gas) and propane models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10862 O", + "laborHours": 21508.0, + "languages": [], + "name": "HyRAM+ (Hydrogen Plus Other Alternative Fuels Risk Assessment Models) v.4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hyram", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 4.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A successful architecture that depicts the relationship between the energy market engineering requirements and blockchain requirements\n(shown as enablers). Software includes sequential and relational architectures supported by the UML flow diagrams. For a successful blockchain agnostic implementation of energy markets, the proposed architecture/blueprint supported by prototype implementation is very efficient. The proposed invention also depicts various means of the use of\nblockchain technology for energy market systems.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Blockchain smart contracts for energy markets", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "We present PyOECP, a Python-based flexible open-source software for estimating and modeling the complex permittivity obtained from the open-ended coaxial probe (OECP) technique. The transformation of the measured reflection coefficient to complex permittivity is performed based on two different models, including the capacitance model and the antenna model. The software library contains dielectric spectra of common reference liquids, which can be used to transform the reflection coefficient into the dielectric spectra. Several Python routines that are commonly employed (e.g., SciPy and NumPy) are only required so that the users can alter the software structure depending on their needs. The modeling algorithm exploits the Markov chain Monte Carlo method for the data regression. The discrete relaxation models can be built by a proper combination of well-known relaxation models. In addition to these models, the electrode polarization, which is a common measurement artifact for interpreting the dielectric spectra, can be incorporated in the modeling algorithm. A continuous relaxation model, which solves the Fredholm integral equation of the first kind (a mathematically ill-posed problem) is also included.", + "laborHours": 0.0, + "languages": [], + "name": "PyOECP: A flexible open-source software for the measurement and modeling of the dielectric spectrum from the reflection coefficient", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tyoon124/PyOECP", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "This is software that will be used to do data analytics in experimental workflows for x-ray mesoscale science. This tool set will provide a mechanism for supporting experiments in many ways, from collecting calibration information and raw data, to managing and viewing data to extracting crystallographic and physical parameters. It will eventually include development of a fully automated workflow that will include statistical information and prediction capabilities to support the scientists in decision-making and replanning their experiments when necessary.", + "laborHours": 0.0, + "languages": [], + "name": "Mesoscale Science Data Analytics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/fiteos", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": " When faced with biological threats, our ability to provide early warning, situational awareness, and decision support will depend on whether we can rapidly and accurately detect threat pathogens in clinical and environmental samples. While next generation sequencing technology and advanced analytic methods provide the means to identify the organisms present in metagenomic samples from clinical and environmental sources, proper identification of pathogens in these samples requires a comprehensive resource providing in-depth knowledge of known pathogens. Because there are myriad species, including rare and uncommon taxa, in metagenomic samples, it is not always possible to recognize pathogens by name. As time will most likely be a critical factor in outbreak situations, it may not be possible to consult with subject matter experts for pathogen identification. \n To effectively safeguard the security and safety of people, animals and plants, we must have detailed knowledge of the biological agents (pathogens), infectious diseases, and food-borne illnesses that could potentially cause harm. Prior to any mass event, relevant information must be identified, gathered together and integrated in ways that will make it most useful to the biosurveillence analysts in real-time during an actual event. This type of knowledge falls within the realm of a disease ontology, which integrates the various types of data associated with disease states. Having a comprehensive, curated, globally applicable disease ontology is critical to determine the severity of disease outbreaks, which in turn can inform predictive epidemiological models. For a disease ontology to be useful in biosurveillance applications, detailed information about the organisms that cause particular diseases (pathogens), as well as vectors that transmit the disease-causing pathogens, must be included in the ontology. \n While various websites and publications provide lists of pathogens and a few relevant features that may be useful, there is currently no single resource that provides a comprehensive curated list of all known human, animal and agriculturally relevant pathogens. To remedy this deficiency, we are developing a comprehensive pathogen knowledgebase, encompassing all known pathogens of humans, animals and plants. Having pathogen information already integrated into a usable knowledgebase will enable real-time analyses during an actual event, will facilitate the analysis of post-event data on pathogen-mediated disease outbreaks, and may contribute to improved predictive epidemiological models. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Pathogen Knowledge Base", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "DevOps cloud on the fly provides automated virtual machine creation on demand. This is accomplished using two very powerful software tools: Packer and Vagrant.", + "laborHours": 0.0, + "languages": [], + "name": "DevOps Cloud on the fly", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/devOpsCloudOnTheFly", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "System benchmarking provides a means to compare or assess the performance of hardware or software against a point of reference. Because of the multitude of factors that ultimately influence a benchmark\u2019s results, reproducibility is challenging. To aid in this, we present a software framework named bueno that provides mechanisms to automate many arduous, error-prone benchmarking tasks: environmental setup; program compilation/execution; data storage and analysis.", + "laborHours": 0.0, + "languages": [], + "name": "bueno", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/bueno", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Blockchain Applicability and Cybersecurity Frameworks is the implementation of an earlier invention disclosure and Provisional Patent Application: S-146,805, Battelle IPID 31608-E. \u2014BAF walks a user (or an interested party) through ~100 controls to determine various factors, including:\n1. Does the application need a blockchain?\n2. If the application needs a blockchain, does it need a private blockchain or permissionless/public blockchain?\n3. What kind of consensus is most suitable for the application? The current version of BAF evaluates between four consensus mechanisms: proof-of-work, proof-of-stake, proof-of-burn, and proof-of-authority.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Blockchain Applicability and Cybersecurity Frameworks (BAF)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "Rossi Alpha View (RAV) is a teaching aid for explaining what a Rossi-alpha distribution is and how it is generated. The software provides graphical user interface (GUI) in which a pulse train is shown from which a Rossi-alpha distribution is generated as pulses appear. The source strength, correlated fraction, and speed of the pulse train can be adjusted as well as the die-away time and efficiency of the hypothetical detector from which the pulses would be generated. Additionally, neutron coincidence counting principles are illustrated through the software by showing a reals plus accidentals (R+A) gate and an accidentals (A) gate with an adjustable pre-delay, gate width, and long delay.", + "laborHours": 0.0, + "languages": [], + "name": "Rossi Alpha View", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/RossiAlphaView", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "The micron level generalized defect dynamics code is a numerical tool predicting the overall mechanical response and microstructure evolutions of metals deforming by dislocation glide, cross slip and climb and point defect diffusion and clustering. The tool relies on the use of a Fast Fourier Transform mechanical solver allowing for the computation of mechanical fields resulting from the presence of dislocations, grain boundaries and second phases. The code leverages both field defect mechanics and cluster dynamics modeling framework.\n\n\tThe primary intent of this tool is to validate and calibrate mathematical constitutive models used to describe the mechanical response and microstructure evolutions of metals. This is achieved by tracking the evolution of an ensemble of dislocations and of points defects subjected to mechanical loading. The code can simulate complex microstructures and physical phenomena associated with plasticity. As such, it can be applied to metals with any crystal symmetry (face centered cubic, body centered cubic, hexagonal closed packed). Further, the model can be applied to single crystalline and to polycrystalline aggregates. Simulation volumes can be subjected to mixed boundary conditions (i.e. stress and strain) and the effect of free surfaces can also be accounted for such as to mimic plasticity in thin films and in micropillars.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Generalized defect dynamics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "The TAIl Particle Solver (TaiPS) described in this abstract evaluates the fast ion and electron distribution for inertial confinement fusion applications (ICF). The code was developed under a Laboratory Directed Research and Development (LDRD) project. The code falls under the Los Alamos Plasma Simulation (LAPS) framework, though it operates as a stand alone code. We would like to make it open source in order to enable its use by the broader ICF community. TaiPS solves the non-relativistic Fokker-Planck equation in 1D-2V geometry for a fast particle tail. Up to four ion species are evolved along with the electron population. A suite of approximate collision operators is present: (i) a test particle collision operator, (ii) a linearized Fokker-Planck collision operator, and (iii) and a nonlinear Fokker-Planck collision operator. The tail solution is matched to a bulk distribution function, whose form is evaluated from a Braginskii closure [S. Braginskii, Reviews of plasma physics]. The code utilizes a Chang-Cooper discretization in energy [J. Chang and G. Cooper, Journal of Computational Physics 6, 1 (1970)], a Legendre expansion in the pitch coordinate, and finite different in configuration space. The code has mostly been used to evaluate steady state solutions, though time stepping can be done utilizing PETSc's suite of explicit and implicit schemes. The primary applications of the code are to take the fast ion or electron tail distribution and use them to evaluate the fusion reactivity or various diagnostic signals such as Bremsstrahlung radiation. A separate code has been written to evaluate the fusion reactivity, whereas Bremsstrahlung radiation is evaluated by codes developed by Grisha Kagan's collaborators. Publications that have utilized this code are contained in Refs. [X.-Z. Tang, H. Berk, Z. Guo, and C. McDevitt, Physics of Plasmas 21, 032707 (2014), X.-Z. Tang, C. McDevitt, Z. Guo, and H. Berk, EPL (Europhysics Letters) 105, 32001 (2014), X.-Z. Tang, C. McDevitt, Z. Guo, and H. Berk, Physics of Plasmas 21, 032706 (2014), C. McDevitt, X.-Z. Tang, Z. Guo, and H. Berk, Physics of Plasmas 21, 032708 (2014), C. J. McDevitt, X.-Z. Tang, and Z. Guo, Physics of Plasmas 24, 112702 (2017), C. J. McDevitt, X.-Z. Tang, and Z. Guo, Plasma Physics and Controlled Fusion 61, 025005 (2018), C. McDevitt, X.-Z. Tang, Z. Guo, and H. Berk, Physics of Plasmas 21, 102705 (2014)].", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "TaiPS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "rkmlviewer is an application designed to read and display data encoded in the Keyhole Markup Language.\nThe application provides a graphical window with a first person style camera to view KML files in 3d.\nThe application is built to display \"large scale\" data (not suitable for resolution > 100km)\nrkmlviewer is written in Go, uses OpenGL 3.3 for rendering, and GLFW for cross platform windowing support.\nrkmlviewer contains a command line (ncurses style) gui to select application options at runtime.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "rkmlviewer", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "Matlab Resistive Wake Calculator \nThis is a Matlab code that calculates the resistive wake from an undulator beam pipe. The code is based on a published paper by Bane and Stupakov [1]. The code can calculate the wake for a round or a flat beam pipe, and can calculate the wake for different types of metal (for example, Aluminum or Copper). The code can be used to simply calculate the wake (\u201cGenericACWakeForGen\u201d), or it can be used to append a wake calculation to an input file for the free electron laser code Genesis [2] (\u201cReadFullBeam\u201d). The code can also be used to simply plot out the impedances or wakes of a round or flat beam (\u201cCalcZbarFlat\u201d and \u201cZbarAC\u201d). The top level code, \u201cReadFullBeam\u201d is designed to read an output from the beam code Elegant [3] that has been converted to Genesis format using the command \u201cElegant2Genesis.\u201d \n\n\nReferences:\n[1] K. Bane and G. Stupakov, \u201cResistive Wall Wakefield in the LCLS Undulator,\u201d Proc. Of 2005 Part. Accel. Conf., Knoxville, TN, p. 3390 \u2013 3392.\n[2] S. Reiche, \u201cGENESIS 1.3: a fully 3D time-dependent FEL simulation code,\u201d Nucl. Inst. Methods in Phys. A, 429 (1999) 243-248.\n[3] M. Borland, \u201celegant: A Flexible SDDS-Compliant Code for Accelerator Simulation,\u201d Advanced Photon Source LS-287, September 2000.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "QuinnsWakeCalculator", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2021-11-08", + "metadataLastUpdated": "2021-11-08" + }, + "description": "Model Coupling Tookit", + "laborHours": 34184.8, + "languages": [], + "name": "Model Coupling Toolkit v2.11", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MCSclimate/MCT", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "2.11" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-11-08", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This collection of python scripts is the co-optimizer, or the co-optima scenario analysis tool. This release (V0.2) is intended primarily to analysis such as done to support co-optima project planning and identification of potentially fruitful research directions rather than specify particular fuel blends. The intention of this release is to add concreteness to the co-optimization concepts, and facilitate discussion between the teams and stakeholders as the tool evolves. The user interface is currently non-existant from a productions standpoint. Questions, comments, and rants can be directed to Ray.Grout@nrel.gov", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "Co-Optima Co-Optimizer (Co-optimization of fuels and engines Co-optimizer) [SWR-18-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/cooptima-co-optimizer", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "V0.2" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-11-10", + "metadataLastUpdated": "2024-03-11" + }, + "description": "NREL's PowerGridworld provides a modular simulation environment for training heterogenous, grid-aware, multi-agent reinforcement learning (RL) policies at scale. The package enables the user to create component gym environments that can be composed into more complex agents. For example, a grid interactive building environment can be created by composing together component environments each encapsulating the building, PV, and battery physics. These multi-component environments can then be combined into multi-agent simulation where each agent's power consumption/injection becomes an input for solving the optimal power flow on a distribution feeder modeled in OpenDSS. Information from OpenDSS, such as bus voltages and line flows, can be included in the agents' observation spaces to enable grid-aware rewards. The default API for the PowerGridworld simulator conforms to RLLib's MultiAgent API and thus enables distributed training using HPC and cloud resources.", + "laborHours": 0.0, + "languages": [], + "name": "PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems [SWR-22-07]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PowerGridworld", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-11-10", + "metadataLastUpdated": "2022-01-28" + }, + "description": "PS-Samp is a software that reduces a given dataset by pruning data. Data is downselected such that it uniformly spans the phase-space, thereby ensuring that the full dataset is correctly represented. The algorithm relies on estimating the probability map of the data and using it to construct an acceptance probability. The software is designed to handle very large data sets.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PS-Samp (Phase-Space Sampling)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Phase-space-sampling", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "buonassisi@mit.edu" + }, + "date": { + "created": "2021-11-10", + "metadataLastUpdated": "2021-11-10" + }, + "description": "This is a code and data repository to conduct Bayesian Optimization with knowledge constraints for manufacturing process of perovskite solar cells ", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PV-Lab/SL-PerovskiteOpt", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PV-Lab/SL-PerovskiteOpt", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-11-12", + "metadataLastUpdated": "2023-05-25" + }, + "description": "Hydropower is one of the most mature forms of renewable energy generation. The United States (US) has almost 103 GW of installed, with 80 GW of conventional generation and 23 GW of pumped hydropower [1]. Moreover, the potential for future development on Non-Powered Dams is up to 10 GW. With the US setting its goals to become carbon neutral [2], more renewable energy in the form of hydropower needs to be integrated with the grid. Currently, there are no publicly available tool that can estimate the hydropower potential for existing hydropower dams or other non-powered dams. The HydroGenerate is an open-source python library that has the capability of estimating hydropower generation based on flow rate either provided by the user or received from United States Geological Survey (USGS) water data services. The tool calculates the efficiency as a function of flow based on the turbine type either selected by the user or estimated based on the \u201chead\u201d provided by the user.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Hydrogenerate: Open Source Python Tool To Estimate Hydropower Generation Time-series", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HydroGenerate", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "3.6 or newer" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-11-15", + "metadataLastUpdated": "2021-11-16" + }, + "description": "Archparse is a Python package that holds the purpose and capability of converting the contents of a text file to a functioning neural network based on the Tensorflow 2.X framework. This is able to be done with minimal written Python code and next to no knowledge of how to build models with Tensorflow directly. More specifically Archparse parses a text file with extension \".arch\" which contains neural network architecture information that corresponds to either the Tensorflow 2.X API or custom code written with the Tensorflow 2.X API. Included in the initial version is the capacity to easily produce sequential autoencoders and sequential neural networks.", + "laborHours": 0.0, + "languages": [], + "name": "Archparse", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EnderWiggin14/ARCHPARSE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-11-15", + "metadataLastUpdated": "2021-11-16" + }, + "description": "Optvis is a web application to visualize control flow graphs, call graphs, disassembly code from a binary or executable. The main use case is visualizing the compiler optimizations in binary code.", + "laborHours": 0.0, + "languages": [], + "name": "Optvis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CcNav", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-11-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "We show how to model discrete ordinary differential equations (ODE) with algebraic nonlinearities as deep neural networks with varying degrees of prior knowledge.\nWe derive the stability guarantees of the network layers based on the implicit constraints imposed on the weight's eigenvalues. Moreover, we show how to use barrier methods to generically handle additional inequality constraints.\nWe demonstrate the prediction accuracy of learned neural ODEs evaluated on open-loop simulations compared to ground truth dynamics with bi-linear terms.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/neural_ODE_ICLR2020", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/neural_ODE_ICLR2020", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-11-16", + "metadataLastUpdated": "2021-11-16" + }, + "description": "Genealogical importance splitting marches towards a rare event by iteratively selecting and replicating realizations that are headed towards a rare event. The replication step is made difficult when applied to deterministic systems as the initial conditions of the offspring realizations need to be adjusted. Typically, a random perturbation is applied to the offspring. For some cases, this cloning technique may not be adequate and prevent variance reduction in the probability estimate. A GAN-based replication process is proposed to address this limitation. The perturbations applied to the clones are physically consistent instead of being randomly chosen. The proposed method allows reducing the variance in the probability estimation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "GANISP (GAN-assisted Importance SPlitting)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GANISP", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jgoodall@ornl.gov" + }, + "date": { + "created": "2021-11-17", + "metadataLastUpdated": "2021-11-17" + }, + "description": "Capture packet data from a computer's network interface in a scalable manner and making it available to search and filter across the most commonly used fields", + "laborHours": 0.0, + "languages": [ + "Go" + ], + "name": "jgoodall/mercury", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jgoodall/mercury", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v1.0.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-19", + "metadataLastUpdated": "2021-11-19" + }, + "description": "The presented python code provides wrapper functions for two decomposition algorithms: One algorithm to decompose Maximum Clique problems and one to decompose Minimum Vertex Cover problems. The functions take as input a networkx graph object, and decompose either problem on the input graph recursively into subproblems such that the optimal solution can be constructed from the optimal solutions of both subproblems. The recursion ends as soon as the subproblems reach a pre-specified size limit by the user, and they can be solved using any method provided in advance by the user as external function. This includes exact solvers or an adiabatic quantum annealer.", + "laborHours": 0.0, + "languages": [], + "name": "Decomposition Algorithms for Scalable Quantum Annealing", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Decomposition-Algorithms-for-Scalable-Quantum-Annealing", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-19", + "metadataLastUpdated": "2021-11-19" + }, + "description": "HSNMon is a robust high speed network monitoring daemon that provides insight into network availability, hardware failure, and network performance for switches and network cards. HSNMon collects counters, forwarding tables, and error information at high resolution using publicly available Omni-Path Management APIs. The collected data can be forwarded into multiple logging infrastructures including syslog and message queuing systems. HSNMon is only the infrastructure for collecting the network data. It does not include any collected data or proprietary LANL information", + "laborHours": 0.0, + "languages": [], + "name": "HSNMon: High-Speed Monitoring Software for Omni-Path", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/hsnmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-19", + "metadataLastUpdated": "2021-11-19" + }, + "description": "materialsCloudCompute (mCC) is a software package for running easily parallelizable materials science theoretical computations on Amazon Web Services (AWS) infrastructure. mCC provides tools to partition out computational problem into smaller subproblems which can be run in parallel, and ensure that each of those subproblems completes successfully. It utilizes the following AWS services: EC2, S3, and RDS. It operates by launch a managing EC2 instance, which can launch worker instances that perform the calculations. The Managing instance tracks the subproblems and ensures that the Worker instances continue to operation, killing and relaunching them if they fail.", + "laborHours": 0.0, + "languages": [], + "name": "materialsCloudCompute", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/materialsCloudCompute", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-19", + "metadataLastUpdated": "2021-11-19" + }, + "description": "This computer code uses the concept of the parallax to compute the x, y and z coordinates of points found using transmission electron microscopy (TEM), or any transmission imaging technique, using two images, each taken at a different perspective of the region containing the points. Points correspond, but are not limited, to the center of cavities or precipitates, positions of irradiation black dot damage, positions along a dislocation line, or positions along where an interface meets a free surface. Features can include dislocations, interfaces, cavities, precipitates, inclusions etc. The x, y and z coordinates of the points are output in a text file. The code also allows the user to visualize the features containing the points in three dimensions.", + "laborHours": 0.0, + "languages": [], + "name": "Obtain3D_open", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Obtain3D_open", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ostrouchovg@ornl.gov" + }, + "date": { + "created": "2021-11-20", + "metadataLastUpdated": "2021-11-23" + }, + "description": "Clusters medical trajectories (unequally spaced and unequal length time series) aligned by an intervention time. Performs k-means clustering, where each mean is a thin plate spline fit to all points in a cluster. Distance is MSE across trajectory points to cluster spline. Provides silhouette plots and Adjusted Rand Index evaluations of the number of clusters. Scales well to large data with multicore parallelism available to speed computation.", + "homepageURL": "https://cran.r-project.org/package=clustra", + "laborHours": 0.0, + "languages": [ + "R" + ], + "name": "clustra", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cran.r-project.org/package=clustra", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0.1.5" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-22", + "metadataLastUpdated": "2021-11-22" + }, + "description": "The low-tilt tomographic reconstruction (LoTToR) method is a post-processing method to correct the missing-wedge artifact, which contains a model-free iteration process under a set of constraints in real and reciprocal spaces. A proof of concept is conducted by using the LoTToR on a phantom, i.e., a simulated 3D reconstruction from a low-tilt series of images, including that within a tilt range of \u00b115\u00b0. The method is validated by using both negative-staining (NS) and cryo-electron tomography (cryo-ET) experimental data. A significantly reduced missing-wedge artifact verifies the capability of LoTToR, suggesting a new tool to support the future study of macromolecular dynamics, fluctuation and chemical activity from the viewpoint of single-molecule 3D structure determination. Moreover, the software can be used for hospital computer tomography (CT) to reduce the radiation damage to patients without reducing the CT image quality.", + "homepageURL": "https://rengroup.lbl.gov/page6/page6-LoTToR-download.html", + "laborHours": 0.0, + "languages": [], + "name": "LoTToR: An Algorithm for Missing-Wedge Correction of the Low-Tilt Tomographic 3D Reconstruction of a Single-Molecule Structure (LoTToR) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://rengroup.lbl.gov/page6/page6-LoTToR-download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-11-22", + "metadataLastUpdated": "2023-03-08" + }, + "description": "A graphical user interface (GUI) that helps analyze data from coincidence Doppler broadening positron annihilation spectroscopy. It is a quick tool to rapidly reduce large data and conveniently analyze multiple datasets.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Coincidence Doppler Broadening Analysis Program", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/CDB_Analysis_Program", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-12-20" + }, + "description": "Millstone is a mechanics solver for geological processes, focusing on coupling to reservoir simulators. It solves the linear balance of momentum with incremental poroelastic stress rate formulations under quasistatic assumptions.", + "homepageURL": "https://link.springer.com/article/10.1007/s11242-019-01254-6", + "laborHours": 0.0, + "languages": [], + "name": "Millstone", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2018-140/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://link.springer.com/article/10.1007/s11242-019-01254-6", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "SoDa is an irradiance-based synthetic Solar Data generation tool to generate realistic sub-minute solar photovoltaic (PV) power time series, that emulate the weather pattern for a certain geographical location. Our tool relies on the National Solar Radiation Database (NSRDB) to obtain irradiance and weather data patterns for the site. Irradiance is mapped onto a PV model estimate of a solar plant's 30-min power output, based on the configuration of the panel. We use a stochastic model with a switching behavior due to different weather regimes as provided by the cloud type label in the NSRDB, with parameters for the cloudy states trained on the high-resolution solar power measurements from a Phasor Measurement Unit (PMU).", + "laborHours": 0.0, + "languages": [], + "name": "SoDa: An Irradiance-Based Synthetic Solar Data Generation Tool (SoDa) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Ignacio-Losada/SoDa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "Floorspace.js is a 2D geometry editor. Users can define an explicit floor plan for each story of a building. A story-by-story interface makes it easy to develop space geometry and assign properties. Referencing satellite imagery or floor plan images, when available, speeds up geometry entry. Conversion of 2D to 3D geometry is currently out of scope for Floorspace.js, a reference implementation is available in the OpenStudio\u00ae SDK. Explicit floor plans allow more building-specific information than parameterized shoe-boxes but less information than a full 3D BIM model. Sloped walls, complex roofs, detailed shading structures, and other complex 3D structures are out of FloorspaceJS's scope. In general, if users have a 3D BIM model in a tool that can export a useful BEM representation then it is better to use that export than to recreate a new model using FloorspaceJS. Re-usability and minimal dependencies were key design considerations for software developers. Web technologies can be used in both online and desktop applications. The editor was written in pure JavaScript for maximum portability and re-usability. A custom JavaScript Object Notation (JSON) file format was developed to ease integration with other applications. Custom JSON schema design was a key part of FloorspaceJS development.", + "laborHours": 0.0, + "languages": [ + "C++", + "JavaScript", + "Vue" + ], + "name": "Floorspace.js", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/floorspace.js", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "V0.8.0" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "Background: Codon2Vec is an embedding neural network that predicts 'high' or 'low' gene expression directly from the protein-coding sequences. Embedding neural networks are commonly used for natural language processing (NLP) applications. Analogous to how an English sentence is a string of words, a gene can be thought of as a string of codons. Similar to how NLP neural networks model English sentences as a non-random sequence of words, we considered a coding sequence as a non-random non-overlapping array of codons (k-mers of length = 3). Value Proposition: - Codon2Vec achieved a high median AUC-ROC score of 83.8% when trained and applied to transcriptomic data from 300 fungal species - Unlike Codo2Vec, conventional methods predicting for expression based on codon usage rely on a priori knowledge of optimal codons or a set of reference genes. - Unlike Codon2vec, these methods do not account for the effect of codon order on gene expression. - Codon2Vec neural network bypasses the need for artisanal feature selection step that is necessary for traditional machine learning models.", + "laborHours": 0.0, + "languages": [], + "name": "Codon2Vec v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rhondene/Codon2Vec", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "HYPPO is a hyperparameter optimization (HPO) software that uses surrogate modeling and uncertainty quantification to provide reliable neural network architectures. Similar state-of-the-art HPO technologies do not use such features and mostly perform random searches to explore the parameter space, which can easily become computationally expensive. Using HYPPO, the user is able to reduce by an order of magnitude the number of evaluations necessary to identify the most optimal region in the hyperparameter space. Finally, using asynchronous nested parallelism, we are able to decrease by two orders of magnitude the amount of time required to complete the HPO process.", + "laborHours": 0.0, + "languages": [], + "name": "HYPPO v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/hpo-uq/hyppo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "This software can be used to tune the HPC operations of a Cray system running Slurm workload manager software. This includes many of the customizations that NERSC has made over the past three years. In particular these customizations allow for complex site-local policies to be implemented and managed in a scalable way, or add unique capabilities to slurm via our plugins, including: * performance software integration and compute node staging * temporary directory/dynamic user content management automation * software defined networking integration", + "laborHours": 0.0, + "languages": [], + "name": "NERSC Slurm Software Configurations and Plugins", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/nersc-slurm-contrib", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "turcksinbr@ornl.gov" + }, + "date": { + "created": "2021-11-29", + "metadataLastUpdated": "2021-11-29" + }, + "description": "Thermal field simulation of the additive manufacturing process enhanced using data assimilation.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "adamantine-sim/adamantine", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/adamantine-sim/adamantine", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-11-29", + "metadataLastUpdated": "2021-11-29" + }, + "description": "Symmetric Positive Definite (SPD) enforcement layers for PyTorch. Regardless of the input, the output of these layers will always be a SPD tensor! The `Cholesky` layer uses a cholesky factorization to enforce SPD, and the `Eigen` layer uses an eigendecomposition to enforce SPD. Both layers take in some tensor of shape `[batch_size, input_shape]` and output a SPD tensor of shape`[batch_size, output_shape, output_shape]`. The relationship between input and output is defined by the following. ```python input_shape = sum([i for i in range(output_shape + 1)]) ``` The layers have no learnable parameters, and merely serve to transform a vector space to a SPD matrix space.", + "laborHours": 0.0, + "languages": [], + "name": "spdlayers", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/spdlayers", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-11-29", + "metadataLastUpdated": "2021-11-30" + }, + "description": "A package containing utility components for running processes and managing tasks.", + "laborHours": 0.0, + "languages": [], + "name": "pyaestro", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FrankD412/pyaestro", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2021-12-02" + }, + "description": "SAND2021-0565 O PRIME is a modeling framework designed for the real-time characterization and forecasting of partially observed epidemics. The method is designed to help guide medical resource allocation in the early epoch of the outbreak. Characterization is the estimation of infection spread parameters using daily counts of symptomatic patients. The estimation problem is posed as one of Bayesian inference and solved using a Markov Chain Monte Carlo technique. The framework can accommodate multiple epidemic waves and can help identify different disease dynamics at the regional, state, and country levels. Examples are provided using publicly available COVID-19 data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PRIME", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PRIME", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "fattebertj@ornl.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2021-12-02" + }, + "description": "Library to compute equilibrium compositions and equal chemical potential compositions in binary and ternary alloys.\nThis library supports thermodynamic data formulated according to CALPHAD (Computer Coupling of Phase Diagrams and Thermochemistry) models, as well as dilute binary alloys.\nOne major aim is to solve the Kim-Kim-Suzuki (KKS) equations to obtain local compositions given a local mixture of two phases.\nThese quantities are then used to evaluate the phase-field model driving force (right handside of time-evolution equation), as well as the energy\ndensity", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "ORNL/Thermo4PFM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/Thermo4PFM", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2021-12-02" + }, + "description": "SAND2021-4723 O CausalFS is a Python package that evaluates causal relationships between dataset features and the metric to be predicted. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "CausalFS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CausalFS", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2024-07-26" + }, + "description": "SAND2021-4823 O InterSpec decodes and displays gamma radiation data from a variety of handheld, laboratory, and fixed installation detector types. Once loaded, InterSpec provides a means to interactively analyze the data via a peak-based methodology. InterSpec assists with isotope identification and determines the source strength and shielding characteristics of the measured item. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "HTML", + "C++", + "Shell", + "Makefile", + "C" + ], + "name": "InterSpec v. 1.0.8", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/InterSpec", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.8" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2021-12-02" + }, + "description": "SAND2021-6830 O Capp is a minimal package manager that supports the dependencies of one application. Its value in comparison to other package managers is its high portability across operating systems and its simplicity and usability for High Performance Computing (HPC) programmers. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "CMAKE" + ], + "name": "CApp v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/capp", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "weberb@ornl.gov" + }, + "date": { + "created": "2021-12-03", + "metadataLastUpdated": "2024-01-18" + }, + "description": "A python VNC client written from scratch using python's socket library", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "pyvnc_client", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/pyvnc_client", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-12-07", + "metadataLastUpdated": "2023-03-28" + }, + "description": "Performs Multi-Tiered Iterative Phasing for Single Particle Imaging. The Spinifel code uses distributed computing (using MPI and Legion) to spread work across many compute nodes. On-node computation is accelerated using GPGPUs (using CuPy, and CUDA).", + "laborHours": 0.0, + "languages": [], + "name": "MTIP Single Particle Imaging (Spinifel) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/mtip/spinifel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-12-07", + "metadataLastUpdated": "2021-12-20" + }, + "description": "In order to support the California state goals to reduce the carbon and pollution emissions (AB2127), The goal of this project (HEVI-Pro) is to project the charging infrastructure needs by future medium- and heavy- duty electric vehicles, and assess optimal deployment the infrastructure in California and provide grid impacts analysis. The MHDV projections will also consider transportation system and electric system interaction with light duty vehicles. The project consists of 2 approaches in general: top-down approach that takes aggregated MHDV adoptions as the inputs and provide the county-level projections of charging load profile and infrastructure need, and the bottom-up approach that that incorporates more granular (temporal, spatial and duty-cycle-specific) behaviors of a variety of MHDVs into activity simulations/optimizations for further analysis.", + "homepageURL": "https://sites.google.com/lbl.gov/2020-157/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Medium and Heavy-Duty Electric Vehicle Infrastructure - Load Operations and Deployment (HEVI-LOAD) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2020-157/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2020-157/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-21" + }, + "description": "The ability to embed molecules in a numeric space is essential in order to build mathematical and machine-learning models describing molecular properties or other processes affected by molecules. MACAW is a cheminformatic tool that allows embedding small molecules into a multidimensional numeric space. In the embedding, each molecule is assigned a numeric vector that captures information of the molecule in relation to other molecules, and that vector can be used as input to mathematical models. Molecules that are more similar to each other are embedded closer in this numeric space, whereas molecules that are more different are embedded further away. One advantage of the MACAW embedding technology compared to established alterantives is that it is fast and does not require extensive computational resources or expertise. In particular, MACAW embeddings can be used as input to mathematical models without the need for variable cleaning or feature selection, saving time and simplifying their use. On the other hand, MACAW also contains methods to generate new molecules and to recommend new molecules satisfying a desired molecular property. The generation of new molecules can be biased based on an input set of molecules, effectively generating molecular diversity around it. In its turn, MACAW's molecular recommendation tool is a novel method for evolving molecules in silico towards a desired molecular specification. In this method, the biased molecular generator tool is applied iteratively in combination with a molecular selection step. As a result, in each iteration the molecules selected by the software are increasingly closer to the desired specification. Both the molecular generation and the molecular recommendation tools are very fast, efficient, and intuitive to use.", + "homepageURL": "https://sites.google.com/lbl.gov/2021-187/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "MACAW v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2021-187/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-187/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2024-05-02" + }, + "description": "The Wind-Plant Integrated System Design and Engineering Model (WISDEM\u00ae) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM\u00ae is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM\u00ae turbine design capability. Please install all of the pre-requisites prior to installing WISDEM\u00ae by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM\u00ae development, please visit the official NREL systems engineering for wind energy website. https://www.nrel.gov/wind/systems-engineering.html", + "laborHours": 229778.4, + "languages": [ + "C", + "Fortran", + "Python" + ], + "name": "WISDEM\u00ae (Wind-Plant Integrated System Design and Engineering Model) [SWR-14-05]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/WISDEM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.4.1" + }, + { + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-20" + }, + "description": "The package contains algorithms for the estimation of sprout/plant density and the corresponding enhanced plant vigor from remotely sensed (RS) images. These algorithms aim to improve the plant characterization and monitoring in the early season when the soil component is significant compared to the plant spatial coverage. In such a scenario, the identification of sprouts (or plants) and the estimation of plant vegetation indexes can be performed only using UAV-acquired images. Additionally, because of the extremely high resolution, gridding becomes necessary to improve visualization and provide more informative maps. However, to capture the real range of values of the VIs, it is important to avoid the inclusion of those pixels belonging to the soil component. The sprout/plant density estimation algorithm takes in input a classification map and uses the vegetation class to estimates the plant density within a user-defined grid using a floating window. Similarly, the enhanced plant vigor algorithm takes in input the vegetation index and the classification map. The enhanced vegetation index is computed for each pixel as the average value among those pixels that belong to the vegetation class within a floating window. The software is developed for the MATLAB environment.", + "homepageURL": "https://ipo.lbl.gov/plant-density-and-enhanced-plant-vigor-estimation-algorithms-for-high-resolution-images-2019-179", + "laborHours": 0.0, + "languages": [], + "name": "Plant density and enhanced plant vigor estimation for high-resolution images v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/plant-density-and-enhanced-plant-vigor-estimation-algorithms-for-high-resolution-images-2019-179", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/plant-density-and-enhanced-plant-vigor-estimation-algorithms-for-high-resolution-images-2019-179", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "UMT is a Sn deterministic thermal radiative transport Fortran proxy application. Its primary purpose is to research how data layout, programming paradigms and architectures effect the implementation and performance of Sn transport in Fortran on unstructured meshes. It is based on the LLNL Teton Sn deterministic thermal radiative transport code.", + "laborHours": 0.0, + "languages": [], + "name": "UMT", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/UMT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "A PyTorch implementation of \"Learning Mesh-based Simulation with Graph Networks\" (Pfaff et al., 2021) to build and train graph neural network surrogates for CFD simulation.", + "laborHours": 0.0, + "languages": [], + "name": "MeshGraphNets", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CCSI-Toolset/MGN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "A framework for building and training neural network surrogates for CFD simulation, with a focus on quickly simulating volume fraction dynamics for carbon capture efficiency prediction. Augments the Deep Fluids (Kim et al., 2019) approach as described in our paper \"Latent Space Simulation for Carbon Capture Design Optimization\" (Bartoldson et al., 2021).", + "laborHours": 0.0, + "languages": [], + "name": "Deeper Fluids", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CCSI-Toolset/DeeperFluids", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "YGM provides a simplified distributed memory communication framework based on a mailbox abstraction for HPC applications. YGM is designed for irregular data-driven applications that communicate small message payloads in an all-to-all fashion. YGM aggregates and routes messages into larger payloads to gain greater bandwidth utilization on modern HPC interconnects. YGM has been demonstrated up to 131k cores of IBM BG/P Sequoia and 96k cores of Catalyst at LLNL, and contains a set of graph-inspired benchmarks.", + "laborHours": 0.0, + "languages": [], + "name": "YGM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ygm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-10" + }, + "description": "Zero-RK is a software package that simulates chemically reacting systems using sparse, preconditioned, adaptive matrix methods to achieve orders-of-magnitude reduction in simulation time while maintaining accurate results.", + "laborHours": 13497.6, + "languages": [], + "name": "Zero-Order Reaction Kinetics v3.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/zero-rk", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "Background: Machine learning (ML) based risk stratification models of Electronic Health records (EHR) data may help to optimize treatment of COVID-19 patients, but are often limited by their lack of clinical interpretability and cost of laboratory tests. We develop a ML based tool for predicting adverse outcomes based on EHR data to optimize clinical utility under a given cost structure. This cohort study was performed using deidentified EHR data from COVID-19 patients from ProMedica Healthcare in northwest Ohio and southeastern Michigan. Methods: We tested performance of various ML approaches for predicting either increasing ventilatory support or mortality and the set of model features under a budget constraint was optimized via exhaustive search across all combinations of features. Results: The optimal sets of features for predicting ventilation under any budget constraint included demographics and comorbidities (DCM), basic metabolic panel (BMP), D-dimer, lactate dehydrogenase (LDH), erythrocyte sedimentation rate (ESR), CRP, brain natriuretic peptide (BNP), and procalcitonin and for mortality included DCM, BMP, complete blood count, D-dimer, LDH, CRP, BNP, procalcitonin and ferritin. Conclusions: This study presents a quick, accurate and cost-effective method to evaluate risk of deterioration for patients with SARS-CoV-2 infection at the time of clinical evaluation.", + "laborHours": 0.0, + "languages": [], + "name": "Budget Constrained Machine Learning for Early Prediction of Adverse Outcomes for COVID-19 Patients", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/BCML-COVID19", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "This code repository contains the implementation of the \"High-Performance Approximate Computing\" (HPAC) toolkit. The toolkit allows you to approximate your own C/C++. The developer uses \"pragma's\" to annotate code regions as approximate. The compiler extensions lower these pragmas to either compiletime approximate techniques or runtime approximation techniques. At execution time, the implemented runtime system decides which annotated regions it should approximate. HPAC also provides a set of script utilities. The utilities perform a grid search within approximation parameters and performance. The user can analyze the raw data to identify optimal approximation techniques for the application.", + "laborHours": 0.0, + "languages": [], + "name": "High Performance Approximate Computing", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/HPAC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2023-09-11" + }, + "description": "OCHRE\u2122: Object-Oriented Controllable High-Resolution Residential Energy Model\n\nA high-fidelity, high-resolution residential building model with behind-the-meter DERs and flexible load models that integrates with controllers and distribution models in building-to-grid co-simulation platforms.\n\nThe full documentation for OCHRE can be found at https://ochre-docs-final.readthedocs.io/en/latest/", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "OCHRE\u2122 (Object-Oriented Controllable High-Resolution Residential Energy Model) [SWR-19-71]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OCHRE", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.8.3-beta" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "Code framework to perform simulations of nuclear reactions with incident particles including gammas, protons, neutrons, deuterons, tritons, helium-3, and alphas to develop nuclear data libraries and study nuclear reaction phenomona. The code can model nuclear reactions or initial populations specified by the user. The decays principally follow the compound-nucleus hypothesis and the statistical decay of Hauser and Feshbach. The code models nuclear decays with a Monte Carlo process that tracks the decay of each state. Data libraries are produced that can be translated into GNDS (generalized Nuclear Data Structure). YAHFC can also be used as an event generator, with individual decays written to disk for offline analysis. Both serial and MPI versions are provided. YAHFC does NOT perform transport of nuclear reactions through materials, only the primary reaction with a target material.", + "laborHours": 0.0, + "languages": [], + "name": "Yet Another Hauser-Feshbach Code", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Yet-Another-Hauser-Feshbach-Code", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "MuMMI Core is the central component of the Multiscale Machine-Learned Modeling Infrastructure (MuMMI), a scalable and generalizable framework that couples pairs of models using machine learning and in situ feedback across three scales of resolution.", + "laborHours": 0.0, + "languages": [], + "name": "Multiscale Machine-Learned Modeling Infrastructure Core", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mummi-framework/mummi-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "MuMMI RAS is the application component of the Multiscale Machine-Learned Modeling Infrastructure (MuMMI). It simulates RAS protein interactions at three scales of resolution coupled with ML-based selection and in-situ feedback. MuMMI RAS is particularly configured for massive scale, running thousands of simultaneous jobs with several terabytes of data on Lassen and Summit.", + "laborHours": 0.0, + "languages": [], + "name": "Multiscale Machine-Learned Modeling Infrastructure RAS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mummi-framework/mummi-ras", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "The code performs image intensity normalization. A new intensity normalization method is presented, which works well with images whose pixel intensity distribution follow a Gamma Probability Distribution. Some examples are provided to show the normalization effect. This new intensity normalization method is also compared to some other well-established intensity normalization methods.", + "laborHours": 0.0, + "languages": [], + "name": "cdf_normalize", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xiaotingzhong/image_intensity_gamma_normalization", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "Converts XML file formats to CLI format for 3D printing; combines equivalent polyline segments (laser power, velocity, focus/spot-size) into a single polyline for a given path. Also plots CLI file format with respect to power for a single specified layer, or the entire file, for 3D printed applications.", + "laborHours": 0.0, + "languages": [], + "name": "AMXML to CLI multi-segment polyline converter and plotter", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CLDruzgalski/AM_fileConverters", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "weberb@ornl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "ORNL conducted an experiment to test COTS (commercial off the shelf) SOAR tools. Vendors interested in entering their tool into the experiment were asked to submit information videos about their tool for phase 1 to down-select which tools should make it through to the testing phase. SOC operators were assigned to watch a subset of the videos such that each video was assigned to the same number of operators. After watching all the videos, operators completed surveys which asked them to grade basic aspects about the tool as best as they could based on the provided video, and asked them to rank the order of their interest in the vendors they were assigned to watch videos on. The problem solved was how do we aggregate the results of the surveys and each of the operator's ranked lists into an overall ranking of all the tools. In addition, it was desirable to be able to work on this code before final results were collected from operators, so code to generate fake data was developed to output in the same output as the survey results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Soar Survey Scoring", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/soar_survey_scoring", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "C-PACE Market Assessment Tool This tool was developed for the U.S. Department of Energy\u2019s Commercial Property Assessed Clean Energy (C-PACE) Working Group to support state and local governments creating, joining, and implementing C-PACE programs. This tool allows users to input a jurisdiction (city, county, or state) and automate a report with building characteristics, energy use, and energy efficiency savings opportunities for commercial buildings in that jurisdiction. The report generated by the tool identifies jurisdiction-specific energy end uses, building use types, and building technologies that a local C-PACE program should consider focusing on to more effectively allocate limited resources and maximize energy savings and investment.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/CPACE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/CPACE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "GLVis is a lightweight tool for accurate and flexible finite element visualization. GLVis uses OpenGL with interactive refinement to accurately represent curved high-order meshes and a wide variety of finite element grid functions defined on them.", + "laborHours": 17343.2, + "languages": [], + "name": "GL Visualization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/glvis/glvis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "4.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "Quandary numerically simulates and optimizes the time-evolution of open quantum systems. The underlying dynamics are modelled by Lindblad's master equation, a linear ordinary differential equation (ODE) describing quantum systems interacting with the environment. Quandary solves this ODE numerically by applying a time-stepping integration scheme, and utilizes a gradient-based optimization approach to determine optimal control pulses that drive the quantum system to a desired target state. Two optimization objectives are considered: (a) Unitary gate optimization that finds controls to realize a unitary gate transformation, and (b) optimal reset that aims to drive the quantum system to the ground states. Gradient-based optimization schemes utilizing Petsc's Tao optimization package are applied to generate control pulses that minimize the respective measure. To evaluate the gradient of the objective function, the discrete adjoint method is used while leveraging techniques from Algorithmic Differentiation to produce exact and consistent gradients. To mitigate excessive execution run times, the software can be build together with the XBraid software library which provides a parallelization strategy to distribute the time-evolution of the underlying dynamics onto multiple processor.", + "laborHours": 0.0, + "languages": [], + "name": "Quandary", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/quandary", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "Clippy (CLI + PYthon) is a Python language interface to HPC resources. Precompiled binaries that execute on HPC systems are exposed as methods to a dynamically-created Clippy Python object, where they present a familiar interface to researchers, data scientists, and others. Clippy allows these users to interact with HPC resources in an easy, straightforward environment - at the REPL, for example, or within a notebook - without the need to learn complex HPC behavior and arcane job submission commands.", + "laborHours": 0.0, + "languages": [], + "name": "Clippy", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/clippy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-14" + }, + "description": "Summary: To address the need for improved tools for annotation and comparative genomics of bacteriophage genomes, we developed multiPhATE2. As an extension of the multiPhATE code, multiPhATE2 includes comparative genomics codes for gene matching among sets of input bacteriophage genomes, and scales well to large input data sets due to incorporation of multiprocessing in the functional annotation and comparative genomics subsystems. Furthermore, additional search algorithms and databases have been added to the functional annotation subsystem. MultiPhATE2 was implemented in Python 3.7, and runs as a command-line code under Linux or MAC-OS.", + "laborHours": 0.0, + "languages": [], + "name": "Multi-genome Phage Annotation Toolkit and Evaluator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/multiPhATE2", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "Lighter version of the Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE)", + "laborHours": 0.0, + "languages": [], + "name": "psuade-lite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade-lite", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.8" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "The code for regularized adversarial domain adaption is provided here. The RADA methodology is developed for correcting climate model biases using an adversarial learning strategy. The code here covers the data processing, the algorithm, the baseline models, and the evaluation.", + "laborHours": 0.0, + "languages": [], + "name": "RADA", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/panbaoxiang/RADA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "swadling1@llnl.gov" + }, + "date": { + "created": "2021-12-13", + "metadataLastUpdated": "2021-12-20" + }, + "description": "MATLAB Functions for calculating the Thomson scattering cross-section", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "LLNL/Thomson-Scattering-Cross-Section-Calculator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Thomson-Scattering-Cross-Section-Calculator", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-14", + "metadataLastUpdated": "2021-12-14" + }, + "description": "Code to calculate Thomson scattering cross sections.", + "laborHours": 0.0, + "languages": [], + "name": "Thomson scattering Cross section Calculator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Thomson-Scattering-Cross-Section-Calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-14", + "metadataLastUpdated": "2021-12-14" + }, + "description": "The Replicative Assessment of Spectrometric Equipment (RASE) is a software for evaluating the performance of radiation detectors and isotope identification algorithms. It uses a semi-empirical approach to rapidly generate synthetic spectra and inject into detector's software to obtain nuclide identification response. RASE facilitates studies of spectroscopic device performance and a quantitative assessment of its capabilities to correctly distinguish and identify isotopes of interest in realistic scenarios.", + "laborHours": 4088.8, + "languages": [], + "name": "Replicative Assessment of Spectroscopic Equipment", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RASE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-14", + "metadataLastUpdated": "2021-12-14" + }, + "description": "This code has been previous released as open source under LLNL-CODE-529294. The HEXRD program comprises a library of X-ray diffraction analysis tools and a stand-alone GUI application. While there are many software packages that provide similar capabilities, HEXRD was designed to provide an extremely flexible and extensible basis for describing a broad array of X-ray diffraction instruments; this includes both mono- and poly-chromatic modalities as well as poly- and single-crystal samples. The high-level objects include Material: an abstraction for defining crystalline materials, including unit cell parameters and anisotropic elastic moduli Imageseries: an interface for series of diffraction images containing one or more frames, including provisions for metadata. Instrument: an abstraction of an X-ray diffraction instrument including support for the definition of multiple detector elements as well as powder, Laue, and mono-chromatic single/multi-grain diffraction analysis modalities (including attendant calibration routines). The hexrdgui package is a standalone PySide2/Qt5 GUI built on top of hexrd. The 0.8.1 release includes various bug fixes as well as some new functionality in the GUI, including: o Enhancements to the import tools for LLNL diffraction instruemtns (PXRDIP and TARDIS) o The ability to save 1-d LeBail fits of integrated diffraction spectra.", + "laborHours": 0.0, + "languages": [], + "name": "Highly Extensible X-ray Diffraction Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HEXRD/hexrd", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.8.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-14", + "metadataLastUpdated": "2021-12-16" + }, + "description": "Massively Parallel and Portable Genomic Sequence Analysis (mappgene) is a sequencing analysis workflow for high performance computing. It incorporates novel technologies to simplify and accelerate genetics research.", + "laborHours": 0.0, + "languages": [], + "name": "Massively Parallel and Portable Genomic Sequence Analysis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mappgene", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2024-07-01" + }, + "description": "Reducing greenhouse gas emissions remains a critical challenge for the transportation and chemical sectors. The electrochemical reduction of carbon dioxide is a potential pathway for production of fuels and chemicals that uses atmospheric carbon dioxide as a feedstock. Here we present an analysis of the potential for carbon dioxide captured from point sources and via direct air capture to be utilized in electrochemical reduction under different market scenarios. Using a numerical optimization framework and national data sets, scenarios for nationwide production of ethylene, formate, and carbon monoxide are evaluated at scales comparable to current production of these molecules in the United States. We show that developing a network for production of these products at scale requires capture and utilization of significant portions of the carbon dioxide that is currently emitted from large stationary point sources. Because carbon dioxide point sources are spatially and compositionally variable, their use for carbon dioxide reduction depends on electricity prices, capture cost, and location. If the power sector in the United States is decarbonized, carbon dioxide supply decreases significantly, increasing the importance of utilizing other carbon dioxide streams, and increasing the likelihood that direct air capture plays a role in supplying carbon dioxide feedstocks. These findings provide a first insight into the feedstock and energy constraints for carbon dioxide reduction.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "CO2ROpt (Feedstock Allocation Optimization Model) [SWR-22-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CO2ROpt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "Danish is a forward modeling package for curvature wavefront sensing in the geometric limit.", + "laborHours": 0.0, + "languages": [], + "name": "danish", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmeyers314/danish", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "CUDAMicroBench is a collection of fourteen microbenchmarks that demonstrate performance challenges in CUDA programming and techniques to optimize the CUDA programs to address these challenges. It also includes examples and techniques for using advanced CUDA features such as data shuffling between threads, dynamic parallelism, etc that can help users optimize the CUDA program for performance.", + "laborHours": 0.0, + "languages": [], + "name": "CUDAMicroBench", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CUDAMicroBench", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "This repo demonstrates how to use the LLNL developed Gaussian process hyperparameter estimation method, MuyGPS, for image classification using Zwicky Transient Facility (ZTF) data.", + "laborHours": 0.0, + "languages": [], + "name": "ZTF_image_classification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Kerianne28/ZTF_image_classification", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-23" + }, + "description": "MuyGPs is a GP estimation method that affords fast hyperparameter optimization by way of performing leave-one-out cross-validation. MuyGPs achieves best-in-class speed and scalability by limiting inference to the information contained in k nearest neighborhoods for prediction locations for both hyperparameter optimization and tuning. This feature affords the optimization of hyperparameters by way of leave-one-out cross-validation, as opposed to the more expensive loglikelihood evaluations requires by similar sparse methods", + "laborHours": 0.0, + "languages": [], + "name": "MuyGPyS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MuyGPyS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "These scripts document the code used to analyze the Death Valley Regional Flow System (DVRFS) microbial community for a manuscript titled \"Subsurface Planktonic Microbial Communities Reflect Regional-Scale Groundwater Hydraulic Connectivity\".", + "laborHours": 0.0, + "languages": [], + "name": "DVRFS Microbiome 2021 Manuscript Code", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/2021_DVRFS_microbiome", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "Source code for Brain Attend and Decode paper. Functional magnetic resonance imaging (fMRI) is a neuroimaging modality that captures the blood oxygen level in a subject's brain while the subject either rests or performs a variety of functional tasks under different conditions. Given fMRI data, the problem of inferring the task, known as task state decoding, is challenging due to the high dimensionality (hundreds of million sampling points per datum) and complex spatio-temporal blood flow patterns inherent in the data. In this work, we propose to tackle the fMRI task state decoding problem by casting it as a 4D spatiotemporal classification problem. We present a novel architecture called Brain Attend and Decode (BAnD), that uses residual convolutional neural networks for spatial feature extraction and self-attention mechanisms for temporal modeling. We achieve significant performance gain compared to previous works on a 7-task benchmark from the large-scale Human Connectome Project-Young Adult (HCP-YA) dataset. We also investigate the transferability of BAnD's extracted features on unseen HCP tasks, either by freezing the spatial feature extraction layers and retraining the temporal model, or finetuning the entire model. The pre-trained features from BAnD are useful on similar tasks while finetuning them yields competitive results on unseen tasks/conditions.", + "laborHours": 0.0, + "languages": [], + "name": "Attend and Decode: 4D fMRI Task State Decoding Using Attention Models", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/BAnD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1." + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2023-03-13" + }, + "description": "This code allows for a geologic cross-sectional profile to be obtained from a user-drawn profile line within a web map application.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Interactive Web Mapping Tools And Custom Subsurface Cross-sections For Interdisciplinary Geologic Investigation", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/SFWDSubsurface", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "This model is a cellular automata-based algorithm used to predict grain-scale microstructure development. Nucleation and growth of existing grains are considered in an initially liquid domain, where the temperature field evolution is either driven through heat transport simulation data or a frozen temperature approximation (i.e., a constant cooling rate and a fixed thermal gradient). The growth of grains is based on the decentered octahedron algorithm published by Gandin and Rappaz (https://doi.org/10.1016/S1359-6454(96)00303-5), where the grain envelopes are tracked as approximations of the evolving dendritic growth front. The input heat transport data, which can come from simulation of an arbitrary processing technique, consists of coordinates and times at which said coordinates fall below the liquidus and solidus temperatures for the final time. As a result, only the final solidification of a given region is modeled (no remelting). The code is designed to be compatible with pre-Exascale architectures, and uses MPI and the Kokkos library to decompose the computational domain and offload solidification calculations to GPUs.", + "laborHours": 0.0, + "languages": [], + "name": "Exascale-capable cellular automaton for nucleation and grain growth", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ExaCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2022-03-17" + }, + "description": "krowkee is a toolkit for scalably and efficiently summarizing many data streams in distributed memory. krowkee is intended for applications where one needs to summarize huge loosely structured data, such as matrices or graphs, where individual components such rows/columns or vertex adjacency information are impractical to store and directly inspect. krowkee ingests these objects as data streams - unstructured, arbitrarily ordered lists of updates - and accumulates summaries thereof in the form of data sketches.", + "laborHours": 0.0, + "languages": [], + "name": "krowkee", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/krowkee", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "XPlacer Machine Learning Guided Data Placement uses machine learning model to assist programmers to select the data placement advises for application running on HPC system with Nvidia GPUs. XPlacer Machine Learning Guided Data Placement consists three components: (1) 4 revised benchmarks from Rodinia benchmarks; (2) compiler script and execution script to generate variants, and collect training data for the machine learning model; (3) the scripts to post-process the collected data and generate the machine leaning model.", + "laborHours": 0.0, + "languages": [], + "name": "XPlacer Machine Learning Guided Data Placement", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/peihunglin/XPlacer-ML-DataPlacement", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "The topology optimization community has regularly employed optimization algorithms from the operations research community. However, these algorithms are implemented in the sequence space l2 instead of the\nproper function space where the design variable resides. In this software, we benchmark the mesh independent implementation of pyMMAopt with three common problems in topology optimization. We show how the volume fraction variable discretization on non-uniform meshes affects the convergence of\nl2 based optimization algorithms and how pyMMAopt successfully achieves mesh independent convergence.", + "homepageURL": "https://zenodo.org/record/5526481#.YU36FMZOmL8", + "laborHours": 0.0, + "languages": [], + "name": "Mesh independency in topology optimization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://zenodo.org/record/5526481#.YU36FMZOmL8", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "0.0.1" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-12-30", + "metadataLastUpdated": "2021-12-30" + }, + "description": "JOBS EV estimates economic impact associated with deploying electric vehicle supply equipment. It is a derivative of the other JOBS models available at the ES website.", + "homepageURL": "https://jobsfc.es.anl.gov", + "laborHours": 0.0, + "languages": [], + "name": "JOBS EV", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://jobsfc.es.anl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-12-30", + "metadataLastUpdated": "2022-01-03" + }, + "description": "PowerSAS.m is a robust, efficient and scalable power grid analysis framework based on semi-analytical solutions (SAS) technology for MATLAB/Octave users. It provides various functionalities for power grid analysis including steady-state analysis, dynamic analysis and hybrid extended-term analysis. It features high numerical robustness, enhanced computational performance and highly customizable and extensible user interfaces.", + "laborHours": 0.0, + "languages": [], + "name": "POWERSAS.m ( A POWER GRID ANALYSIS TOOKBOX BASED ON SEMI-ANALYTICAL SOLUTION APPROACH)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ANL-CEEESA/powersas.m/blob/release/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-CEEESA/powersas.m", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-03" + }, + "description": "This code performs fast interpolation for volume datasets, specifically, Laplace and Matern interpolation where missing data are on a grid of arbitrary dimension.", + "laborHours": 0.0, + "languages": [], + "name": "LaplaceInterpolation.jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/vishwas1984/LaplaceInterpolation.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-03" + }, + "description": "Slepians.jl is a package that solves the concentration problem of Slepian, Landau and Pollak, numerically. Loosely speaking, we find a function that is both finite in extent and has a Fourier transform which lies in a certain domain. In a single dimension, with discrete sampling, the discrete prolate spheroidal sequences solve this optimization problem.", + "laborHours": 0.0, + "languages": [], + "name": "Slepians.jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lootie/Slepians.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-04" + }, + "description": "The code is a python implementation of the optimization algorithm that is proposed in \"Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints\" (Apt# 163042). The code is not a general purpose optimization software but is designed to solve the specific class of optimization problems in the aforementioned article. To allow reproducibility it is implemented close to the theoretical framework that has been developed in the aforementioned article. It will be published without any third-party dependencies except for python and some popular and widespread python libraries.", + "laborHours": 0.0, + "languages": [], + "name": "TRUST REGION METHOD FOR BOUND-CONSTRAINED MPCCS WITH NONLINEAR OBJECTIVE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/paulmanns/slpcc", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-05" + }, + "description": "AutoPhaseNN is a deep learning (DL) based approach for solving the phase problem. By combining the 3D convolutional neural network (CNN) with the physics of the imaging technique, AutoPhaseNN is trained to learn the inversion from the measured intensity to the amplitude and phase images without labeled data. Once trained, AutoPhaseNN is ~100X faster than conventional iterative phase retrieval methods,", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "AUTOPHASENN: UNSUPERVISED PHYSICS-AWARE DEEP LEARNING FOR PHASE RETRIEVAL", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-05" + }, + "description": "The software being disclosed is the Reference Governor plug-in for Risk Analysis Virtual Environment (RAVEN) developed in Idaho National Laboratory. This software is used as a part of the supervisory control system for integrated energy system project, which can receive the original control variable issued by the upstream control system, then adjust the control variable based on the system states and performance projection of the downstream power-generating systems, in order to keep the response of the downstream systems within all the thermal mechanical constraints.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "REFERENCE GOVERNOR PLUG-IN FOR RAVEN", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-01-05", + "metadataLastUpdated": "2022-01-05" + }, + "description": "Converts XML format files to VTK format files for visualization of 3D printing.", + "laborHours": 0.0, + "languages": [], + "name": "Convert XML to VTK", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CLDruzgalski/AM_fileConverters", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "000" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "This is a set of utilities for reading and manipulating PIO files written in python and C++. These files are intended to be building blocks for other scripts / programs that will use them to do great things. The PIO format itself is described in LA-UR-05-7425 at page 102 and embodied in code LA-CC-05-052. In addition to reading the raw PIO files, the bundled utilities will expand variable that use a compressed sparse row notation", + "laborHours": 0.0, + "languages": [], + "name": "PIO Tools", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/piotools", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "One complication to infectious disease forecasting efforts is delay in reporting of cases, where real-time data often under-report the true disease burden. This pair of R scripts (1) provides example code demonstrating several strategies to account for the reporting delay and improve disease forecasts and (2) applies these methods using publicly-available data on dengue fever case reporting in Puerto Rico from 1990 to 2009.", + "laborHours": 0.0, + "languages": [], + "name": "Correcting for reporting delay: an example using dengue fever data", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbeesleyBIOSTAT/Reporting_Delay_Example_Code", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "As data volume increases in HPC centers, storing data in reasonable amounts of space and time while maintaining data integrity and recoverability becomes ever more difficult. ZFS is a filesystem that provides these features, among many others, that make it attractive for usage in HPC environments. It has the ability to compress data, compute checksums, and compute redundancy codes within the same runtime, rather than compute each separately, without knowledge of the underlying structure of the filesystem. However, measurements have shown that compression on CPUs can be incredibly inefficient and significantly reduce the performance of ZFS. The ZFS Interface for Accelerators (Z.I.A.) was developed to provide an interface to route data to accelerators while being processed by ZFS, so that the ZFS infrastructure and features are maintained, while allowing for ZFS administrators to provide faster implementations of compression, or other features, to their instance of ZFS.", + "laborHours": 0.0, + "languages": [], + "name": "ZFS Interface For Accelerators", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/zfs", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-24" + }, + "description": "The Data Processing Services Module (DPUSM) provides the ability to perform pluggable compression, erasure coding, checksuming and other important file system operations within the Linux kernel. The pluggable provider interface allows for the use of hardware acceleration of those services. In-kernel file systems are then able to use these functions to use these accelerators to perform operations that are normally run on the processor, resulting in improved file system performance. Third parties will register \"providers\" with the DPUSM to communicate with their respective accelerators. Providers will implement functions with DPUSM API signatures so that the DPUSM can translate the data inputted by users of the DPUSM into data that providers recognize.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Data Processing Unit Services Module", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "HPXML is a consensus data transfer standard for residential buildings. Over several years, multiple versions of the standard have been released. This tool accepts an HPXML file in an older version and translates it to a newer version.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HPXML Version Translator", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hpxml_version_translator", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "PsDNS is a Python package which makes it easy to solve partial differential equation using a pseudo-spectral method. The code uses Python classes and Numpy-like arrays to provide a simple interface with which users can construct equations, integrators, and diagnostics. It also includes implementation for common problems, in particular, the incompressible Navier-Stokes equation in a periodic domain, which is commonly used as a benchmark problem for turbulence research. PsDNS uses MPI to allow massively parallel computation for large problems.", + "laborHours": 0.0, + "languages": [], + "name": "PsDNS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PsDNS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "The Memento Protocol Validator software provides a suite of tools to validate compliance with the Memento protocol. The Memento protocol is an interoperability solution for accessing web archiving information with the DateTime dimension.", + "laborHours": 0.0, + "languages": [], + "name": "Memento Protocol Validator Software", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/memento-validator", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "To support and accelerate the development of simulation protocols in atomistic modelling, we introduce an integrated development environment (IDE) for computational materials science called pyiron (http://pyiron.org). The pyiron IDE combines a web based source code editor, a job management system for build automation, and a hierarchical data management solution. The core components of the pyiron IDE are pyiron objects based on an abstract class, which links application structures such as atomistic structures, projects, jobs, simulation protocols and computing resources with persistent storage and an interactive user environment. The simulation protocols within the pyiron IDE are constructed using the Python programming language. To highlight key concepts of this tool as well as to demonstrate its ability to simplify the implementation and testing of simulation protocols we discuss two applications. In these examples we show how pyiron supports the whole life cycle of a typical simulation, seamlessly combines ab initio with empirical potential calculations, and how complex feedback loops can be implemented. While originally developed with focus on ab initio thermodynamics simulations, the concepts and implementation of pyiron are general thus allowing to employ it for a wide range of simulation topics.", + "laborHours": 0.0, + "languages": [], + "name": "LANL Contributions to pyiron: An integrated development environment for computational materials science", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pyiron/pyiron_contrib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chaic@ornl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "This package (SUrface-wave Grader with ARtificial intelligence or SUGAR) automatically assigns a quality score to surface-wave seismograms (SAC format) using a trained artificial neural network model (included). Specifically, the python script 01_apply_ann.py calculates probability scores for a list of SAC files. You may consider seismograms with probability scores larger than 0.5 as acceptable data. Note no scores will be given to seismograms that do not pass an initial check (e.g., insufficient number of data points). See https://doi.org/10.1002/essoar.10507941.3 for more details.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ccp137/SUGAR", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ccp137/SUGAR", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "Link Parser Library is a Python library for parsing HTTP Link header format. Link Parser extracts information about relationships to other resources from Link Header and translates it into an easy to use Json structure.", + "laborHours": 0.0, + "languages": [], + "name": "Link Parser Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/link-parse", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "fanchercm@ornl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "pyRS is a python software package that was designed to meet the data reduction and analysis needs of the neutron residual stress mapping user community at Oak Ridge National Laboratory (ORNL). pyRS incorporates separate modules that provide a streamlined workflow for reducing raw neutron events into 1D intensity vs. scattering angle and subsequent analysis to extract the interatomic spacing and intensity for residual stress and texture analysis. Users can access the modules through either a graphical or command-line interface. pyRS saves data into a single HDF5 file, in which the metadata, reduced diffraction data, and peak analysis results are passed between different modules.", + "laborHours": 0.0, + "languages": [], + "name": "Python Residual Stress Analysis (pyRS)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/neutrons/PyRS.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "DistGANs is a Python package to perform distributed training of conditional generative adversarial neural networks for multi-class labeled image data.\nDistGANs partitionins the training data according to data labels, and enhances scalability by performing a parallel training where multiple generators are concurrently trained, each one of them focusing on a single data label.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DistGANS- Distributed Generative Adversarial Neural Networks", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/DistGANs", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0" + }, + { + "contact": { + "email": "craigca@ornl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-01-07" + }, + "description": "A tool to quickly perform recon in the init process of a given firmware.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "initAnalysis", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Codeman655/initAnalysis", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-01-07" + }, + "description": "XPlacer/Tracer is a dynamic analysis tool that finds bad memory access patterns in heterogeneous codes. XPlacer/Tracer consists of two components. (1) A configurable ROSE plugin for source code instrumentation of heterogeneous code written in the C/C++ and CUDA programming languages. (2) A sample configuration that instruments memory accesses to dynamic memory in CPU and GPU codes, and a runtime library that tracks these memory accesses at runtime. The collected information is reported in form of a textual summary or as memory map that can be converted to images.", + "laborHours": 0.0, + "languages": [], + "name": "XPlacer/Tracer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/XPL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.5" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-01-07" + }, + "description": "This routine is to be used with the open source package for seismic wave propagation\nSPECFEM3D_Globe version v7.0.2-111-gf469578\n(https://geodynamics.org/cig/software/specfem3d_globe/) to implement the LLNL S-, P-, Rayleigh, Love wave model (SPiRaL). It handles 3D radial isotropic crustal and mantle properties, as well as 410-660 topography.", + "laborHours": 0.0, + "languages": [], + "name": "LLNL S-, P-, Rayleigh, Love wave model implementation into SPECFEM3D_Globe", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/geodynamics/specfem3d_globe.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "accawigk@ornl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-03-22" + }, + "description": "MEASUR your energy savings with the free DOE MEASUR software The Department of Energy (DOE), with Oak Ridge National Laboratory (ORNL), released version 1.0 of their energy efficiency software tool MEASUR (Manufacturing Energy Assessment Software for Utility Reduction). MEASUR has been available for several years as a beta version, being tested by industry experts and real users, and will continue to be updated and improved in the coming years. It is an integrated suite of tools to aid manufacturers in improving the efficiency of energy systems and equipment within a plant, including motors, pumps, fans, process heating, steam, and compressed air. Additionally, there are modules for wastewater energy analysis and to help perform energy treasure hunts. Several calculators are also included, allowing users to independently perform smaller calculations and analyses (such as estimating pump head, performing a fan traverse analysis, estimating waste heat recovery potential, and cataloging compressed air leaks). The MEASUR modules are based on previous DOE software tools that have been used by industry since the early 2000s (such as MotorMaster, AirMaster+, PSAT, PHAST, and FSAT). The original tools only ran on Windows operating systems, and by Windows 10, most of them were inoperable. DOE started their energy efficiency software tool revitalization effort in 2016, first with PSAT (for pumps), then began to integrate the other tools and expand their functionality and utility. The new MEASUR suite provides an extensively more user-friendly, modern, and versatile set of tools. All the assessment modules and most of the calculators have several visual components and graphs and detailed help text for every user input. To help reach international users, the tool utilizes Google translate and users can easily change unit systems, even converting existing user inputs if desired. The assessment files can be organized within the internal file system and easily shared to other users, regardless of their operating system. The entire suite is free, open-source, and can be downloaded on Windows, Mac, or Linux operating systems.", + "laborHours": 0.0, + "languages": [ + "TypeScript", + "CSS", + "HTML", + "Node.js", + "Angular8", + "Electron" + ], + "name": "MEASUR - Manufacturing Energy Assessment Software for Utility Reduction", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-AMO/AMO-Tools-Desktop/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-AMO/AMO-Tools-Desktop", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-01-07" + }, + "description": "Zero-RK is a software package that simulates chemically reacting systems using sparse, preconditioned, adaptive matrix methods to achieve orders-of-magnitude reduction in simulation time while maintaining accurate results", + "laborHours": 13497.6, + "languages": [], + "name": "Zero-Order Reaction Kinetics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Zero-RK", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "borreguerojm@ornl.gov" + }, + "date": { + "created": "2022-01-09", + "metadataLastUpdated": "2022-01-11" + }, + "description": "drtsans is highly modular, allowing users to customize collected data as well as test hypothetical or simulated neutron events data. Instrument scientists can use the advance features of drtsans to calibrate their instruments and reduced large quantities of datasets in a streamlined mode. Users can correct the collected data with dark current subtraction and normalization by neutron flux, detector sensitivity, solid angle subtended by the detectors, and scaling to absolute units. Conversion from time-of-flight and/or wavelength to 1D or 2D momentum transfer renders the final scattering quantities amenable to analysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "drtsans", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/sns-hfir-scse/sans/sans-backend", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.2.0" + }, + { + "contact": { + "email": "bassbc@ornl.gov" + }, + "date": { + "created": "2022-01-10", + "metadataLastUpdated": "2022-01-10" + }, + "description": "Automatic Building Energy Modeling (AutoBEM, https://bit.ly/AutoBEM) has been used to create an OpenStudio and EnergyPlus building energy model of 122.9 million U.S. buildings (https://bit.ly/ModelAmerica). Simulating and analyzing a model of every building for large areas (e.g. cities) is often not feasible. This dynamic archetyping capability uses a representative building and calculates a floor-space multiplier that allows millions of buildings to be represented by less than 100 buildings. This script (WRF_Archetypes_Parallel.py) calculates these building archetypes for each of the grid cells from a Weather Research and Forecasting (WRF) model in a parallel fashion. The script works by looping through each of the grid cells in the shapefile in parallel, spatially joining the building metadata table to each grid cell, aggregating relevant archetypes and calculating necessary statistics related to area and number of buildings in each cell. The output is a table (.csv) in which each row is an archetype building with properties about that building as well as statistics that relate that building to the total cell (such as an area multiplier). The following inputs are required: WRF zone shapefile (.shp) (wrf-grids-origin_Vegas_Select_100.geojson) The projection of the shapefile (\"EPSG:XXXX\") Input table containing building metadata for area corresponding to shapefile (.csv) (https://zenodo.org/record/4552901#.YZQEotDMJPY - ClarkCounty2.csv) The number of cores that will be parallelized (integer) The output file name for the archetype table (.csv) Sample command line inputs: python3 ~/WRF_Archetypes_Parallel.py -i ~/wrf-grids-origin_Vegas_Select_100.geojson -c ~/ClarkCounty2.csv -o ~/OutputArchetypes.csv -j 72 -e EPSG:4326 Using Geopandas Version 0.9.0", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AutoBEM-DynamicArchetypes", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-BTRIC/AutoBEM-DynamicArchetypes", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "39s@ornl.gov" + }, + "date": { + "created": "2022-01-10", + "metadataLastUpdated": "2022-01-10" + }, + "description": "Software attempts to detect, estimate the composition, and segment phases from Energy Dispersive Spectroscopy datasets. ", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Autodidactic VB-GMM for Multispectral Microscopy Data", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esrah-ap-niht/Microscopy-VB-GMM", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "gureckywl@ornl.gov" + }, + "date": { + "created": "2022-01-10", + "metadataLastUpdated": "2024-01-24" + }, + "description": "The computer code uses a parallel simulated annealing framework with embedded machine learning components to solve multi-constrained optimization problems. The software automatically balances the execution of low and high fidelity physics models within the optimization procedure. The low fidelity model is used to rapidly explore the design space while the high fidelity physics model is executed sparingly to account for complex design constraints that are not resolved by the quickly executing low fidelity model.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ML-PSA", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/ml-psa/ml-psa", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2022-01-11", + "metadataLastUpdated": "2022-01-11" + }, + "description": "This package provides a secure transport layer connecting mini-applications run as components of a server infrastructure. The guiding principle is that mini-apps should be \"actors\" -- able to expose a set of API calls to the network and to have a shared trust model for knowing who is calling which API function and who takes\nresponsibility for the result.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Actor API", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/99R/actor_api", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0.0" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-01-12", + "metadataLastUpdated": "2023-03-08" + }, + "description": "There is a rising need for the measurement and understanding of hydrogen transport properties in materials for the energy and transportation industries. The Hydrogen Permeation Analysis Tool (HyPAT) provides a user friendly interface for batch analysis of dynamic hydrogen permeation data to calculate the transport properties permeability, solubility, and diffusivity. A built in literature database provides an easy comparison to known values. A common method for measuring these hydrogen transport properties is dynamic pressure rise permeation experiments, for example, those done in the Static Gas Absorption and Permeation (SGAP) experiment at INL. Most laboratories develop individual, in-house codes for data analysis. HyPAT provides a platform that can be adopted by other user groups for such experimental analysis and significantly reduce personnel time spent performing data analysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Hydrogen Permeation Analysis Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HyPAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "moriano@ornl.gov" + }, + "date": { + "created": "2022-01-12", + "metadataLastUpdated": "2022-01-12" + }, + "description": "Modern vehicles are complex cyber-physical systems made of hundreds of electronic control units (ECUs) that communicate over controller area networks (CANs). This inherited complexity has expanded the CAN attack surface which is vulnerable to message injection attacks. These injections change the overall timing characteristics of messages on the bus, and thus, to detect these malicious messages, time-based intrusion detection systems (IDSs) have been proposed. However, time-based IDSs are usually trained and tested on low-fidelity datasets with unrealistic, labeled attacks. This makes difficult the task of evaluating, comparing, and validating IDSs. Here we detail and benchmark four time-based IDSs against the newly published ROAD dataset, the first open CAN IDS dataset with real (non-simulated) stealthy attacks with physically verified effects. We found that methods that perform hypothesis testing by explicitly estimating message timing distributions have lower performance than methods that seek anomalies in a distribution related statistic. In particular, these \u201cdistribution-agnostic\u201d based methods outperform \u201cdistribution-based\u201d methods by at least 55% in area under the precision-recall curve (AUC-PR). Our results expand the body of knowledge of CAN time-based IDSs by providing details of these methods and reporting their results when tested on datasets with real advanced attacks. Finally, we develop an after-market plug-in detector using lightweight hardware, which can be used to deploy the best performing IDS method on nearly any vehicle.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Time-Based CAN IDS Paper Results Code", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmoriano/can-time-based-ids-benchmark", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-01-12", + "metadataLastUpdated": "2022-01-12" + }, + "description": "Data processing routines and moment tensor inversion of PNE data", + "laborHours": 0.0, + "languages": [], + "name": "PNE moment tensor inversions", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/PNE_MTINV", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dewittsj@ornl.gov" + }, + "date": { + "created": "2022-01-13", + "metadataLastUpdated": "2022-01-14" + }, + "description": "Many materials, metal alloys in particular, have features on the on micrometer or nanometer scale that have a large impact on the properties of the material. These features are known as the microstructure of the material. Understanding why and how the microstructure forms in a material is of fundamental scientific interest as well as of significant technological interest. The capability to predict microstructure evolution in a material allows the intentional design of microstructures and hence the intentional design of material properties. The phase-field method is one of the leading methods for predicting microstructure evolution. One of the most significant problems for phase-field models is their computational expense. Even limited phase-field simulations can easily require thousands of CPU core-hours to complete, which significantly limits their use. This code provides both a general framework for creating scalable, GPU-accelerated phase-field model applications as well as several applications themselves. The code is capable of using hundreds of GPUs efficiently, which greatly reduces the time required to perform simulations. The code is written with an emphasis on performance portability, that is the ability for the code to run efficiently on a number of different computing architectures without modification of the source code. The performance portability of this code is primarily enabled through the use of two libraries, Kokkos (performance portable data structures and execution patterns) and heFFTe (performance portable distributed 3D fast Fourier transforms). The code consists of a core library, applications, and tests. The core library includes shared functionality between applications. This includes interfaces with fast Fourier transform (FFT) libraries such as heFFTe, data structures based on Kokkos, file input and output capabilities, and a solver for infinitesimal strain mechanical equilibrium problems. Five applications are included in the code. The flagship application is the MEUMAPPS-SS application, which implements the Kim-Kim-Suzuki phase-field model for precipitation for an arbitrary number of phases and components in a metal alloy. Five simpler applications are also included that solve the Eshelby inclusion problem, Allen-Cahn equation, the coupled Allen-Cahn and diffusion equations, and the Cahn-Hilliard equation. The code includes two applications to solve the Cahn-Hilliard equation, one with constant-step-size first-order time integration and the second with adaptive high-order time integration.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "MEUMAPPS (C++ Version)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/meumapps/meumapps/-/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/meumapps/meumapps", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-01-13", + "metadataLastUpdated": "2023-03-08" + }, + "description": "ISOPOD (InverSe OPtimizatiOn and Design) will be a MOOSE (Multiphysics Object Oriented Simulation Environment)-based framework which will iteratively estimate the parameters by minimizing the difference between simulated and experimental observables. While inverse optimization has long been used for parameter estimation, the unique feature of ISOPOD is rapid solution of new inverse problems, leading to accelerated Research, Development and Demonstration (RD&D) for complex parameter estimation problems. This will be achieved by extending the software structure of MOOSE to inverse optimization, as well as building on the unique automatic differentiation feature of MOOSE.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Isopod (inverse Optimization And Design): Moose-based Application For Performing Inverse Optimization On Multiphysics Modeling And Simulation", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/isopod", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-01-13", + "metadataLastUpdated": "2022-01-13" + }, + "description": "Lighter version of the Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE)", + "laborHours": 0.0, + "languages": [], + "name": "psuade-lite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade-lite", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.9.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-01-14", + "metadataLastUpdated": "2022-01-14" + }, + "description": "To date, quantitative prediction on CPUs has been limited to laborious `white-box' methods\u037e and learning has been limited to special cases such as best-case (throughput) performance. We present Qualm, a method for learning quantitative performance of optimized latency", + "laborHours": 0.0, + "languages": [], + "name": "Qualm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab/qualm/qualm", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-14", + "metadataLastUpdated": "2022-01-14" + }, + "description": "A scalable software framework for reinforcement learning environments and agents/policies used for the Design and Control applications", + "laborHours": 0.0, + "languages": [], + "name": "EXARL-Easily eXtendable Architecture for Reinforcement Learning", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exalearn/exarl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "tkonstant@bnl.gov" + }, + "date": { + "created": "2022-01-18", + "metadataLastUpdated": "2022-01-19" + }, + "description": "Code used for generating results in the publication: \"Machine learning enabling high-throughput and remote operations at large-scale user facilities\"", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Machine learning enabling high-throughput and remote operations at large-scale user facilities", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bnl/pub-ML_examples", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-01-19", + "metadataLastUpdated": "2022-01-19" + }, + "description": "The Gravitation and Mesh Adaptation (GaMA) toolbox consists of a set of Matlab classes for modeling the environment around asteroids and comets. A variety of gravitational models and supporting algorithms from are consolidated alongside a custom meshing utility tailored for the application. This allows the user to work within a single streamlined environment to import and manipulate surface definitions, probe the dynamical environment, integrate trajectories, and post-process results. For other applications, modified surface meshes can be exported. Gravity Models: 1) Werner's analytic polyhedron model 2) Mascon model 3) Gottlieb's spherical harmonic model 4) Approximate polyhedron models 5) Curvilinear surface models 6) Custom composite models Meshing Features: 1) Array-based half-edge data structure 2) Supports curvilinear surface definitions up to degree 4 3) Ray-tracing 4) Coarsening 5) Feature-based refinement 6) Projection 7) Smoothing 8) Mesh quality validity tests 9) Mesh repair Additional Features: 1) Solar radiation pressure model 2) Distant 3rd body model 3) Collision detection 4) Trajectory integration and post-processing 5) Visualization of surface fields", + "laborHours": 0.0, + "languages": [], + "name": "Gravitation and Mesh Adaption", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmpearl/GaMA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "diazab@nv.doe.gov" + }, + "date": { + "created": "2022-01-20", + "metadataLastUpdated": "2022-01-20" + }, + "description": "QuickView PRO (QVPRO) is similar to QuickView but designed to focus on analysis. QuickView was designed for visualization only, adding analysis capabilities later. This made QuickView complicated when using it as an analysis tool. QVPRO uses the same analysis algorithms in a more streamlined workflow and has a user friendly GUI. QVPRO provides the unique capability of analyzing Photonic Doppler Velocimetry (PDV) data records from different PDV systems and still allows for processing hundreds of PDV data records in a practical manner.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "QVPRO", + "organization": "Nevada National Security Site/Mission Support and Test Services LLC (MSTS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://gitlab.osti.gov/doecode/dc-31683", + "status": "Development", + "tags": [ + "DOE CODE", + "Nevada National Security Site/Mission Support and Test Services LLC (MSTS)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-01-21", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The Deep Lynx UNC is a small utility written in Python that uses only basic Python libraries and the Deep Lynx Python Software Development Kit (SDK). It queries Deep Lynx for tasks that indicate some data to be run in the UNC's environment. Once a task is acquired, the UNC retrieves the associated data and provides it to some other application for processing, waits for output, and sends the output from the other application to Deep Lynx. As data flows only from the UNC to Deep Lynx, this software solves the problem of connecting Deep Lynx with applications and resources that exist in a network where the network can reach Deep Lynx, but Deep Lynx cannot reach that network (unidirectional network).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deep Lynx Unidirectional Network Connector", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-UNC", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-01-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL contributions to project site managed by federal agency. Schema Grapher is an application that takes in CSV datasets and converts them to RDF for loading into a graph database. Schema Grapher is responsible for the extract and transform part of an ETL (i.e., extract, transform, load) pipeline.", + "laborHours": 0.0, + "languages": [], + "name": "Schema Grapher", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/schema-grapher", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-01-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL contribution to project managed by federal agency. SignalGen is a software application that generates synthetic RDF graphs that satisfy the constraints specified in a search template. The purpose of this tool is most to aid in the development of the graph search engine and ensure it is able to find known graph patterns.", + "laborHours": 0.0, + "languages": [], + "name": "SignalGen", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/signalgen", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "Remote Key/Value storage service for Mochi.", + "laborHours": 0.0, + "languages": [], + "name": "Yokan", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-yokan/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-yokan", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "Bedrock is Mochi's service bootstrapping mechanism.", + "laborHours": 0.0, + "languages": [], + "name": "Bedrock", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-bedrock/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-bedrock", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "mochi-quintain is a microservice (i.e., a Mochi provider) that responds to parameterized RPCs to generate synthetic concurrent server load.", + "laborHours": 0.0, + "languages": [], + "name": "mochi-quintain", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-quintain/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-quintain", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "Margo provides Argobots-aware bindings to the Mercury RPC library. Margo combines Mercury and Argobots to simplify development of distributed services. Mercury operations are presented as conventional blocking operations, and RPC handlers are presented as sequential threads. 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The calculation takes inputs from a variety of publicly available data sources (e.g., utility tariffs from the Utility Rate Database; EV charging station locations from the Alternative Fuels Data Center; energy price forecasts from the Energy Information Administration) and produces the current LCOC, considering when, where, and how light-duty EVs are recharged. In addition, the lifetime fuel cost savings (LFCS) calculation estimates the discounted fuel cost savings for a new battery EV (BEV) or plug-in hybrid EV (PHEV) over a 15-year time horizon using state-level gasoline price and LCOC projections.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook", + "Python" + ], + "name": "LCOC (Levelized Cost of Light-Duty EV Charging Calculator)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/lcoc-ldevs", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-02-23", + "metadataLastUpdated": "2022-02-24" + }, + "description": "SAND2021-15064 O ROMANS, or Reduced Order Modeling for Accelerating Numerical Simulations, is an open source software for accelerating numerical simulations. 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V2W-BERT optimizes the learnable parameters \u03b8 of F\u03b8 in two steps. In the first step, the pre-trained BERT language model is further fine-tuned with CVE/CWE descriptions specific to cyber security. In the second step, the trained BERT model is employed in a Siamese network architecture to establish links between CVEs and CWEs. The architecture takes a specific CVE-CWE pair as input and predicts whether the CVE belongs to the CWE or not, with a confidence value. V2W-BERT includes a Mask Language Model (LM) based Reconstruction Decoder to ensure that the descriptions\u2019 contexts are not changed too much during the training process.", + "laborHours": 0.0, + "languages": [], + "name": "Cybersecurity-Tools/V2W-BERT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Cybersecurity-Tools/V2W-BERT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2022-02-28", + "metadataLastUpdated": "2022-02-28" + }, + "description": "This package implements a EventLoop class that manages concurrent coroutines.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "frobnitzem/aiowire", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/frobnitzem/aiowire", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "2.1.0" + }, + { + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2022-02-28", + "metadataLastUpdated": "2022-02-28" + }, + "description": "A package for working with lists distributed over MPI.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "frobnitzem/mpi_list", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/frobnitzem/mpi_list", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.3.0" + }, + { + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2022-02-28", + "metadataLastUpdated": "2022-02-28" + }, + "description": "This package represents remote datasets. It provides a context object that acts as a proxy to an [mpi_list](https://pypi.org/project/mpi-list/) context running on a remote server.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "MPI Remote", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/99R/mpi-remote", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-02-28", + "metadataLastUpdated": "2022-02-28" + }, + "description": "The Optimization Plugin library (\"op\") is a lightweight general optimization solver interface. The primary purpose of op is to simplify the process of integrating different optimization solvers (serial or parallel) with scalable parallel physics engines. By design it has several features that help make this a reality. The core abstraction interface was developed to encompass a large class of optimization problems in an optimizer-agnostic way. This enables us to describe the optimization problem once and then use a variety of supported \"op\" optimizers with ideally no code-changes. The abstraction interface is made up of lightweight wrappers that make it easy to integrate with existing simulation codes. This makes integration less intrusive and should minimize changes to existing physics codes. The \"op\" interface includes an assortment of utility methods that help specify parallel communication patterns as well as methods to convert from optimization-specific interfaces to the more general \"op\" interface. Lastly a dynamic library linking interface is provided to allow for use of proprietary optimization engines without explicit reference in the source code, along with standard shared library interfaces for opensource engines.", + "laborHours": 0.0, + "languages": [], + "name": "Optimization Plugin Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/op", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Software that orchestrate data processing and management for mass spectrometry workflows and data products. Stack presented contains a web application, data processing job scheduling, and data processing workers for data processing and management.", + "laborHours": 0.0, + "languages": [], + "name": "EMSL-Computing/CoreMS-Portal", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-Computing/CoreMS-Portal", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "zimmercj@ornl.gov" + }, + "date": { + "created": "2022-03-02", + "metadataLastUpdated": "2022-03-02" + }, + "description": "Spectral is a portable and transparent middleware library to enable use of the node-local burst buffers for accelerated application output on Summit and Frontier. It is used to enable large scientific applications to leverage the performance benefit of the in-node NVMe storage for periodic checkpoints without having to modify the application code. Spectral acheives this by intercepting write only file creates, redirecting the output, and then transfering the file to the original destination when the file is closed. Spectrals migration agent runs on the isolated core of each reserved node, so it does not occupy resources and based on some parameters the user could define which folder to be copied to the GPFS.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Spectral", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/cz7/spectral-io/-/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/cz7/spectral-io", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2022-03-03", + "metadataLastUpdated": "2022-03-03" + }, + "description": "Data Driven Anderson Acceleration for Physics Informed Neural Networks to solve high dimensional partial differential equations", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "DD-AADL", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/DD-AADL", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-03", + "metadataLastUpdated": "2022-03-03" + }, + "description": "Code for the paper Learning Interpretable Models Through Multi-Objective Neural Architecture Search by Zachariah Carmichael, Tim Moon, and Sam Ade Jacobs. Monumental advances in deep learning have led to unprecedented achievements across a multitude of domains. While the performance of deep neural networks is indubitable, the architectural design and interpretability of such models are nontrivial. Research has been introduced to automate the design of neural network architectures through neural architecture search (NAS). Recent progress has made these methods more pragmatic by exploiting distributed computation and novel optimization algorithms. However, there is little work in optimizing architectures for interpretability. To this end, we propose a multiobjective distributed NAS framework that optimizes for both task performance and introspection. We leverage the non-dominated sorting genetic algorithm (NSGA-II) and explainable AI (XAI) techniques to reward architectures that can be better comprehended by humans. The framework is evaluated on several image classification datasets. We demonstrate that jointly optimizing for introspection ability and task error leads to more disentangled architectures that perform within tolerable error.", + "laborHours": 0.0, + "languages": [], + "name": "Explainable Neural Architecture Search (XNAS)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/XNAS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0" + }, + { + "contact": { + "email": "obriense@ornl.gov" + }, + "date": { + "created": "2022-03-04", + "metadataLastUpdated": "2022-03-04" + }, + "description": "Uses spectral fitting of X-Ray fluorescence to obtain the density (g/L) of transuranics.", + "laborHours": 0.0, + "languages": [ + "Visual Basic" + ], + "name": "MEXRF", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/multTMU/MEXRF", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Minos Computing Library (MCL) is a task-based programming language and runtime for extremely heterogeneous systems. MCL facilitates writing program for heterogeneous devices and porting applications across different systems and devices. MCL supports asynchronous execution of computing tasks on all available heterogeneous devices, including GPUs, FGPAs, fixed-point accelerators, and AI accelerators. MCL provides a high-level programming interface and automatically and autonomously performs resource management, load balancing, and locality-aware scheduling.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/mcl-runtime", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mcl-runtime", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Amalgamate existing climate data to create monthly climate variable fields. The STITCHES python library provides a user-friendly interface to top-down climate emulation.", + "laborHours": 0.0, + "languages": [], + "name": "JGCRI/stitches", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jgcri/stitches", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Prepare and format the inputs for Hector. This software was developed out of a need to help support Hector, PNNL\u2019s simple climate model continue to grow", + "laborHours": 0.0, + "languages": [], + "name": "JGCRI/hectordata", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jgcri/hectordata", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2022-03-10", + "metadataLastUpdated": "2022-03-10" + }, + "description": "Reaction Rover is a software application designed to enable reaction optimization with little or no human intervention and to provide a flexible platform to facilitate rapid testing, automation, and implementation of new reaction optimization algorithms. Toward these goals, Reaction Rover is designed to be modular, allowing the optimization algorithm, analyzer, and reactor components to be changed for any given process using easily integrated plugins. The Reaction Rover platform is a key development that enables the testing, use, and automation of machine learning (ML) and non-ML optimizers in a variety of laboratory situations.", + "laborHours": 0.0, + "languages": [ + "LabVIEW", + "Python" + ], + "name": "Reaction Rover", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/RxnRover/RxnRover/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/RxnRover/RxnRover", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-03-10", + "metadataLastUpdated": "2024-01-04" + }, + "description": "DISCO is a suite of software for configuring and parallelizing large numbers of distribution power flow simulations and analyzing the results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DISCO (Distribution Integration Solution Cost Options) [SWR-20-02]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/disco", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.2.1" + }, + { + "contact": { + "email": "landryne@ornl.gov" + }, + "date": { + "created": "2022-03-10", + "metadataLastUpdated": "2022-03-10" + }, + "description": "This code is used to determine the different types of pleiotropy among genes and multiple phenotypes", + "laborHours": 0.0, + "languages": [], + "name": "Multi-Phenotype Association (MPA) Decomposition", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/daweighill/MPA_decomp", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "The stochastic and hybrid representation electronic structure by density functional theory (SHRED) calculates microscopic material properties using time-dependent, nonadiabatic, and ground-state density functional theory (DFT) with a periodic basis. It can utilize deterministic, stochastic, and hybrid representations of the electronic orbitals. This provides a capability for highly parallelized computation of DFT for larger systems and/or higher temperatures. Thus, the code is particularly suited for calculation of material properties in the warm and hot dense matter regimes.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "SHRED: Stochastic and Hybrid Representation Electronic structure by Density functional theory", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This is a software package to predict electromagnetic counterpart production associated with gravitational-wave observations from binary neutron star and neutron star - black hole mergers. This reads in posterior distributions of signal parameters produced by parameter estimation pipelines analyzing gravitational-wave data and predicts whether an electromagnetic transient will be produced and observable in the sky. The code relies on open-source, easy-to-use software tools.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "PyKilonova", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "The goal of the isrhostinfo project is to enumerate security-significant Red Hat host application configuration data and send that data via syslog to an enterprise log server for analysis and monitoring. The project includes binaries for the RHEL7 and RHEL8 distros, python3 source code for RHEL6 support, bash helper scripts and the .yml configurations to enable another individual or organization to modify the source code and build organization-specific rpms through Gitlab and open-source CentOS Docker images.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "rhelhostinfo", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "The Generic Learning User Enablement Code (GLUE Code) is a modular framework designed to couple different scientific\napplications to support use cases including multiscale methods and various forms of machine learning. The workflow was\ninitially designed around supporting active learning as an alternative to coupled applications to support multiscale\nmethods but has been written in a sufficiently modular way that different machine learning methods can be utilized.\nApplication programming interfaces (API) are available for C, C++, Fortran, and Python with support for various storage\nformats including SQL databases and HDF5. The code also provides direct coupling with high performance computing job\nschedulers such as Slurm and Flux. The associated open source repository will include source code, build infrastructure,\ndocumentations, and examples demonstrating how to use the GLUE Code with oopen source ICF and Porous Media\napplications", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Generic Learning User Enablement Code (GLUE Code)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This software is a package of MATLAB functions which analyzes optical flow data to perform analysis on the motion contained in microscopy videos taken of beating heart cells. The resulting information is used to quantify key features of the motion such as frequency, magnitude, and correlation. This software can be applied to analyze different types of movement such as heart and muscle cell contractions frequency, beat strength, and overall beat synchronization.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "CardioFlow", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This project calculates the absolute detection efficiency, defined as the ratio of particles emitted by a source to particles detected using the Geant4 and MCNP radiation transport codes.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Absolute efficiency calculations in Geant4 and MCNP6 for a simple geometry", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "thavappiragm@ornl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "A molecular docking mini-app, GPU-accelerated particle-grid based protein ligand docking programs that can be used for virtual drug discovery compound screens based on a molecular recognition model, that analysis a three-dimensional model of an interaction between a protein and a small molecule (ligand). The miniMDock is developed using multiple programming models/APIs and can be used to evaluate performance portability of molecular docking applications over different heterogeneous systems.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "C", + "C++", + "Cuda", + "Hip" + ], + "name": "miniMDock", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + }, + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-PE/miniMDock", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "Unified Reaction Structures for Astrophysics (URSA) defines a format for nuclear inputs used in the simulation of astrophysical nucleosynthesis. Data of this type is currently stored, transferred, and implemented using a disparate patchwork of data formats and supporting codes. URSA intends to unify these disparate data sources/formats into a single data structure that accommodates the fullest possible range of different reaction types arising in astrophysical environments (e.g., transfer, pickup, or capture reactions; radioactive decay; or delayed particle emission, among many other possibilities). Furthermore, URSA provides a modern and efficient C++ library that existing and/or future astrophysics simulation codes may link against to directly implement nuclear data libraries constructed within the URSA format. In this approach, URSA will ensure that nuclear data inferred from measurements and generated by new facilities such as the Facility for Rare Isotope Beams (FRIB) is appropriately and consistently used in astrophysical applications.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Unified Reaction Structures for Astrophysics (URSA)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "Advanced high-fidelity modelling capabilities are available to evaluate hydraulic fracture growth, fluid flow in fracture networks, fluid-rock heat and mass transfer, geomechanical coupling, geochemical coupling, and electrical power production. While all these components must be considered to design geothermal wells and well fields, as of yet, no models couple all these processes efficiently enough for timely making during ongoing projects. Here we present a new modelling tool to inform rapid decision making for well design, drilling, and operation in fracture-dominated geothermal systems. This new tool, which we call the Geothermal Design Tool (GeoDT), evaluates 3D well placement, natural and hydraulic fracture stimulation by fluid injection, induced seismicity risk, long term flow behavior, heat transfer to flowing fluid over time, and transient electrical power production. Instead of using only first-principles and the common simplifying assumptions that are typical of high-fidelity models, this model is based more on experiment derived scaling relations that, by their nature, include the effect of multi-scale complex effects. This approach helps to avoid misleading simplifications while, at the same time, including small-scale complexities that are often too cumbersome or ill-defined to directly include in higher-fidelity models. The final product is a tool that can model 20 years of dynamic geothermal fluid production from a stimulated fracture dominated systems in seconds using a desktop computer.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Geothermal Design Tool (GeoDT)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "To solve an optimization problem using a commercial quantum annealer, one has to represent the problem of interest as an Ising or a quadratic unconstrained binary optimization (QUBO) problem and submit its coefficients to the annealer, which then returns a user-specified number of low-energy solutions. It would be useful to know what happens in the quantum processor during the anneal process so that one could design better algorithms or suggest improvements to the hardware. However, existing quantum annealers are not able to directly extract such information from the processor. Hence, in this work we develop methods to use advanced features of D-Wave 2000Q to indirectly infer information about the dynamics of the state evolution during the anneal process. Specifically, D-Wave 2000Q allows the user to customize the anneal schedule, that is, the schedule with which the anneal fraction is changed from the start to the end of the anneal. Using this feature, we design a set of modified anneal schedules whose outputs can be used to generate information about the states of the system at user-defined time points during a standard anneal. With this process, called slicing, we obtain approximate distributions of lowest-energy anneal solutions as the anneal time evolves. We use our technique to obtain a variety of insights into the annealer, such as the state evolution during annealing, when individual bits in an evolving solution flip during the anneal process and when they stabilize, and we introduce a technique to estimate the freeze-out point of both the system as well as of individual qubits. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Slicing D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "Quantum annealers offer an efficient way to compute high quality solutions of NP-hard problems when expressed in a QUBO (quadratic unconstrained binary optimization) or an Ising form. This is done by mapping a problem onto the physical qubits and couplers of the quantum chip, from which a solution is read after a process called quantum annealing. However, this process is subject to multiple sources of biases, including poor calibration, leakage between adjacent qubits, control biases, etc., which might negatively influence the quality of the annealing results. In this software, we aim at mitigating the effect of such biases for solving constrained optimization problems, by offering a two-step method, and apply it to Graph Partitioning. In the first step, we measure and reduce any biases that result from implementing the constraints of the problem. In the second, we add the objective function to the resulting bias-corrected implementation of the constraints, and send the problem to the quantum annealer. We apply this concept to Graph Partitioning, an important NP-hard problem, which asks to find a partition of the vertices of a graph that is balanced (the constraint) and minimizes the cut size (the objective). We develop methods for an iterative method to correct any such biases. We demonstrate that, after adding the objective, solving the resulting bias-corrected Ising problem on the quantum annealer results in a higher solution accuracy.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Graph Partitioning Bias Reduction for D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2023-01-17" + }, + "description": "The D-Wave quantum annealers make it possible to obtain high quality solutions of NP-hard problems by mapping a problem in a QUBO (quadratic unconstrained binary optimization) or Ising form to the physical qubit connectivity structure on the D-Wave chip. However, the latter is restricted in that only a fraction of all pairwise couplers between physical qubits exists. Modeling the connectivity structure of a given problem instance thus necessitates the computation of a minor embedding of the variables in the problem specification onto the logical qubits, which consist of several physical qubits \"chained\" together to act as a logical one. After annealing, it is however not guaranteed that all chained qubits get the same value (-1 or +1 for an Ising model, and 0 or 1 for a QUBO), and several approaches exist to assign a final value to each logical qubit (a process called \"unembedding\"). In this software, we develop tailored unembedding techniques for four important NP-hard problems: the Maximum Clique, Maximum Cut, Minimum Vertex Cover, and Graph Partitioning problems. Our techniques are simple and yet make use of structural properties of the problem being solved. Using Erd\\H{o}s-R\\'enyi random graphs as inputs, we compare our unembedding techniques to three popular ones (majority vote, random weighting, and minimize energy). We demonstrate that our proposed algorithms outperform the currently available ones in that they yield solutions of better quality, while being computationally equally efficient.", + "laborHours": 0.0, + "languages": [], + "name": "Advanced Unembedding Algorithms for D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/custom-unembedding-algorithms-QA", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "We developed software which finds HGain schedules that can be used to encode initial solutions into a quantum annealer in a similar manner to the reveres annealing feature on the D-Wave 2000Q. With the newer generations of the D-Wave annealer, more advanced features are available which allow the user to have greater control of the anneal process. We study how such features can help in improving the quality of the solutions returned by the annealer. Specifically, we focus on two of these features: reverse annealing and h-gain. Reverse annealing (RA) was designed to allow refining a known solution by backward annealing from a classical state representing the solution to a mid-anneal point where a transverse field is present, followed by an ordinary forward anneal, which is hoped to improve on the previous solution.The h-gain (HG) feature stands for time-dependent gain in Hamiltonian linear ($h$) biases and was originally developed to help study freezeout times and phase transitions in spin glasses. Here we apply HG to bias the quantum state in the beginning of the annealing process towards the known solution as in the RA case, but using a different apparatus. We also investigate a hybrid reverse annealing/h-gain schedule, which has a backward phase resembling an RA step and whose forward phase uses the HG idea. To optimize the parameters of the schedules, we employ a Bayesian optimization framework. We test all techniques on a variety of input problems including the weighted Maximum Cut problem and the weighted Maximum Clique problem. Our results show that each technique may dominate the others depending on the input instance, and that the HG technique is a viable alternative to RA for some problems.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Encoding Initial Solutions using the HGain feature on D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This code package computes the multi-species BGK kinetic model of Haack, Hauck, and Murillo [J. Stat. Phys., 168, 2017]. It uses a block adaptive mesh refinement (AMR) framework derived from the open-source, Parthenon performance portable AMR framework to provide refinement in the (up to) six dimensional phase space. It includes an atomic ionization model, accurate collision physics across coupling regimes, self-consistent electric fields, and allows for degeneracy in the electronic screening. This kinetic model greatly extends the temperature regime and the spatiotemporal scales for modeling moderately coupled plasmas.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Zapp", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "We developed software which optimizes the selection of spin reversal's on the D-Wave 2000Q for individual problems. Commercial quantum annealers from D-Wave Systems make it possible to obtain approximate solutions of high quality for certain NP-hard problems in nearly constant time. Before solving a problem on D-Wave, several pre-processing methods can be applied, one of them being the so-called spin reversal or gauge transform. The spin reversal transform flips the sign of selected variables and coefficients of the Ising or QUBO (quadratic unconstrained binary optimization) representation of the problem that D-Wave minimizes. The spin reversal transform leaves the ground state of the Ising model invariant, but can average out the biases induced through analog and systematic errors on the device, thus improving the quality of the solution that D-Wave returns. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Genetic Algorithms for Optimizing Spin Reversals on D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "The work done on the open source MPI.jl package was done in order to allow it to work with a streaming, in-situ Gaussian process. The addition was to add the capability for the Julia package to use the MPI non-blocking Barrier, Ibarrier. This involved addition of a small chunk of code to the existing package basically replicating the function for the existing blocking MPI barrier but adapted handle the MPI Ibarrier interface.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "MPI.jl Contribution", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2023-06-16" + }, + "description": "The SCC software calculates the step response characteristics based on the data collected from the plant. The tools available to characterize the step response needs a plant model. Our tool calculates the characteristics based on the data captured from the plant. This prevents the user from building a plant model and directly calculates the response.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SCC (Step characteristics calculator) [SWR-21-80]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/scc", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "Data assimilation methods are algorithms that incorporate observational data into models in order to improve their forecast and predictability. 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The code is written in Fortran and includes Python wrappers.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Data Assimilation Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This software consists of LANL contributions to the pFUnit unit testing framework, developed and copyrighted by NASA/Goddard Space Flight Center.\n\npFUnit is a unit testing framework enabling JUnit-like testing of serial and MPI-parallel software written in Fortran. The LANL contributions will consist of adding support for new platforms/compilers not currently supported (including IBM XL and Cray), and fixing bugs found in the process.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Contributions to pFUnit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/NASA-1.3", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "Colormapping in scientific visualization is one of the most common methods for scientists to gain insight into their data and communicate findings. The utility of a visualization is highly linked to its colormap. A suboptimal colormap may hide information or introduce spurious artifacts. Empirical design guidelines\u2014uniformity, discriminative power, order, and smoothness\u2014are usually only applied ad hoc, guidelines are often contradictory, and theory is not sufficiently developed to use a purely algorithmic approach.\n\nWe write code to generate, edit, optimize, compare, and export colormaps that satisfy these design guidelines in a rigorous mathematical way making use of differential geometry.", + "laborHours": 0.0, + "languages": [], + "name": "Colormaps", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/color", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2023-07-07" + }, + "description": "Interfacing voltage source with a load and a current source with a sink are challenging. The model developed under this software is used to interface voltage source with a sink and a current source with the sink.", + "laborHours": 0.0, + "languages": [], + "name": "IBSL (Interface between source and load) [SWR-21-81]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/IBSL", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "hendersonsc@ornl.gov" + }, + "date": { + "created": "2022-03-14", + "metadataLastUpdated": "2022-03-21" + }, + "description": "Saline is an Application Programming Interface (API) which provides a useful quality assured interface to data from thermo-physical property data models.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Saline", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/neams/saline", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-03-14", + "metadataLastUpdated": "2022-03-14" + }, + "description": "A neural network for segmenting and processing Lorentz TEM images of skyrmion lattices. This software based on U-Net architecture is capable of identifying skyrmions in out-of-focus Lorentz TEM images based on training data. This isspecifically useful for analyzing large area data from in-situ experiments.", + "laborHours": 0.0, + "languages": [], + "name": "SkX_NN: Neural Network for skyrmion identification in Lorentz TEM", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Art-MC/SkX_NN", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Flow routing using a hexagonal grid.", + "laborHours": 2158.4, + "languages": [ + "Python" + ], + "name": "pnnl/hexwatershed v2.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/hexwatershed", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-03-17", + "metadataLastUpdated": "2024-02-26" + }, + "description": "Flash-X is a highly composable multiphysics software system that can be used to simulate physical phenomena in several scientific domains. 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A part of the redesign is a utilizing a newly designed performance portability layer that is language agnostic.", + "homepageURL": "https://flash-x.org", + "laborHours": 0.0, + "languages": [ + "C++", + "C", + "Fortran", + "Python" + ], + "name": "Flash-X", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://flash-x.org", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-17", + "metadataLastUpdated": "2022-03-17" + }, + "description": "The CMEC module manager package is designed install and update CMEC modules (https://cmec.llnl.gov/). CMEC modules are independent climate model analysis packages. Individual scripts are provided in the module manager that outline the installation process for each module in a robust way, and a wrapper python script is provided that lets users install a chosen CMEC package with a single command.", + "laborHours": 0.0, + "languages": [], + "name": "CMEC Module Manager", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmecmetrics/cmec-module-man", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "youngsr@ornl.gov" + }, + "date": { + "created": "2022-03-18", + "metadataLastUpdated": "2022-03-18" + }, + "description": "A Julia library for training neural networks with privacy.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "ORNLJulia/Privacy.jl", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNLJulia/Privacy.jl", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-03-21", + "metadataLastUpdated": "2022-04-18" + }, + "description": "The Virtual Engineering (VE, vebio) project provides a set of Python modules to enable users to connect mathematical models of unit operations to predict outcomes for an entire chemical process. This VE approach is currently being developed to support the beginning-to-end simulation of the low-temperature conversion of lignocellulosic biomass to a fuel precursor, but the underlying communication functions can be readily extended to connect models from other domains. The models and features currently included in the VE library include a models/simulations for pretreatment, enzymatic hydrolysis, and aerobic bioreaction.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Fortran", + "Python", + "Tex", + "shell" + ], + "name": "Virtual Engineering (VE) (vebio)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/VirtualEngineering", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-03-21", + "metadataLastUpdated": "2023-09-11" + }, + "description": "The Photovoltaic Dynamic Material Flow Assessment (PV DMFA) model (also referred to here as \u201cThe model\u201d) is a computational framework written in Python based on utility-scale PV electricity generation to quantify time-series stocks and flows of PV materials primarily in crystalline silicon PV technologies. The model evaluates cradle-to-cradle life cycle of utility-scale solar PV systems in the United States in the period 2000-2100. PV DMFA serves as a sustainability analysis tool to assess the impacts of different material circularity practices (i.e., reduce, reuse/refurbish, remanufacture, and recycle), PV module design shifts and sensitivity of material processing and technology related parameters to material installations, waste creation and raw material depletion in PV material supply chains. This tool enables advanced planning for future material needs and informs sustainable pathways for PV material management in the circular economy. This tool could be helpful to a wide range of stakeholders; Particularly, researchers and manufacturers looking for technoeconomic and/or environmental life cycle analysis (LCA) feedback for renewable energy (RE) systems.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "PV DMFA [SWR-21-105]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PV-DMFA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-21", + "metadataLastUpdated": "2022-04-08" + }, + "description": "This code is for the topology optimization of porous electrodes. It was used to produce the results in Roy, T., Salazar de Troya, M.A., Worsley, M.A. and Beck, V.A., 2021. Topology optimization for the design of porous electrodes. arXiv preprint arXiv:2111.12059.", + "laborHours": 0.0, + "languages": [], + "name": "Topology Optimization for Porous Electrodes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TOPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "kyager@bnl.gov" + }, + "date": { + "created": "2022-03-22", + "metadataLastUpdated": "2022-03-22" + }, + "description": "Collection of tools (Python scripts) for scientific experiments: SciAnalysis (analyze image-like data), SciControl (instrument control), and SciVis (visualize data).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "kevinyager/SciTools", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kevinyager/SciTools", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "We have developed a deep learning based method to decode the protein-ligand interactions and predict their probability of binding. We use 3-Dimensional structure of proteins and ligand molecules with the ligand docked to the receptor and use the information at the interaction region to assess the binding of the protein-ligand complex.", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-CompBio/pf-gnn_pli", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/pf-gnn_pli", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The terrestrial dycores will solve tightly coupled conservation of water and energy equations. While the land dycore will simulate processes for a three-dimensional subsurface coupled to a one-dimensional plant\u2019s vascular system, the river dycore will simulate two-dimensional processes in the river.", + "laborHours": 0.0, + "languages": [], + "name": "TDycores-Project/TDycore", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/TDycores-Project/Tdycore", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "TEMWizard is used to visualize results from Atomap, an open-source software tool for determining the position and other features of atomic columns in transmission electron microscopy images.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Temwizard", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Temwizard", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2023-07-07" + }, + "description": "This is a repository with the tools developed for predicting energy produced at Open-Source Reservoir (OSR). It includes both simulation data for OSR, as well as Jupyter notebooks for training and evaluating prediction models. OSR was constructed based on the data from Brady Hot Springs reservoir (Nevada, USA) but has a number of sufficiently modified characteristics and does not disclose any sensitive data.", + "laborHours": 0.0, + "languages": [ + "JUPYTER NOTEBOOK" + ], + "name": "geothermal_osr (Energy Predictor for Geothermal Open Source Reservoir) [SWR-22-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/geothermal_osr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2023-07-11" + }, + "description": "PVwindow simulates photovoltaic window properties by allowing the user build stacks of thin film materials that compose the window layers. The only needed inputs are the complex refractive indices and thicknesses of the materials. The software will simulate the optical transmission, front reflection, and back reflection of the stack using the transfer matrix method. Properties specific to PV window optics such as visible transmittance and color are also calculated. The optics code extracts the number of absorbed photons in the PV absorber layer and solves the single diode equation to yield theoretical photovoltaic metrics such as power conversion efficiency, fill factor, open circuit voltage, and short circuit current of the PV window when illuminated at an arbitrary angle or from either side of the stack. The software tool ultimately allows researchers to design photovoltaic windows and simulate their properties. The software also exports files that can be read into LBL Window software or into the EnergyPlus and Open Studio building energy modeling software to determine larger scale energy impacts of PV window integration.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PVwindow (Photovoltaic Window Simulator) [SWR-22-01]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PVwindow", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2022-03-24" + }, + "description": "The Delaunay density diagnostic helps detect and assess geometric scales within unstructured numerical data sets. The algorithm was first introduced in the paper \"Data-driven geometric scale detection via Delaunay interpolation\" by Andrew Gillette and Eugene Kur, 2022. 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To use the Streaming Statistics library, the user chooses a statistic, constructs an object for it, and then \"adds\" values to it, which means the statistic is augmented.", + "laborHours": 0.0, + "languages": [], + "name": "Streaming Statistics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/STREAMSTAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Python package for organizing and calculating cross-sectoral interdependency flow values. 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Using these tools, facility owners can evaluate their overall cybersecurity posture. These tools are web-based front-end tools. This is an upgrade of the tools available from the earlier version in DOE CODE ID: #41457", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "FEMP Cyber Security Arsenal", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "2" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The software implements the methodology of cybersecurity training architecture and is leveraged to build a turn-key based simulated cyberattack game in which the player assumes the facility manager's role and must defend the OT network from adaptive cyberattacks by directly configuring the physical network environment and implementing security policies.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Network Defense Workforce Development System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "pillairr@ornl.gov" + }, + "date": { + "created": "2022-03-28", + "metadataLastUpdated": "2022-03-28" + }, + "description": "The modeling tool developed in the current project provides lifetime assessment of three candidate materials 740H, 282 and 625 for sCO2/molten salts heat exchanger. The tool incorporated physics-based models that accounted for all relevant underlying degradation mechanisms (creep and corrosion). Reduced-order models enabled rapid simulations of realistic component lifetimes (~100kh) while still retaining the fidelity of the complex models.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "rishipillai/CSP-CorrCreep_ORNL", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rishipillai/CSP-CorrCreep_ORNL", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "qians@ornl.gov" + }, + "date": { + "created": "2022-03-28", + "metadataLastUpdated": "2022-03-29" + }, + "description": "It takes multiple data sets from small-angle neutron scattering experiment at different contrast conditions to synthetically use DENSS algorithm (https://www.nature.com/articles/nmeth.4581) to combine all the information from each data set. As the multiple data set contains more information than a single data, all information in the multiple data set are collectively contribute to the final single synthetic structure that represents a molecular particle structure.", + "laborHours": 0.0, + "languages": [], + "name": "DENSS-Multiple", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/q3n/denss-multiple", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-04-01" + }, + "description": "The ROI-finder software is being developed for use by several Microscopy Group beamlines at Argonne National Laboratory, including 2-ID microprobes and 9-ID-B Bionanoprobe which use multi-scale scanning fluorescence microscopy to acquire elemental maps (multi-modal image data). Microscopy experiments require scan of samples at a coarse resolution followed by ROI identification using feature detection based on domain expertise. Finer resolution scans are then conducted based on identified ROI. The decision-making process based on domain expertise will be difficult to perform for faster data rates and much larger sampling volumes anticipated after APS-U necessitating the need for the ROI-finder software. The ROI- finder detects regions of interest through a continuous learning process, starting with a unsupervised representation learning and improving its recommendations through supervised learning and an interactive tool for user annotation. The scope of ongoing development efforts includes the integration of image registration module to correlate optical and X-ray images, extraction of feature morphology as well as elemental signatures in the image space and incorporation of beamtime streaming data by the scanning probe via EPICS.", + "laborHours": 0.0, + "languages": [], + "name": "XRF-ROI Finder: Machine Learning to Guide Region-of-Interest Scanning for X-ray Fluorescence Microscopy", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/arshadzahangirchowdhury/ROI-Finder", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "The TargetID pipeline enables rapid identification and characterization of binding sites in SARS-CoV-2 proteins as well as the core chemical components with which these sites interact.", + "laborHours": 0.0, + "languages": [], + "name": "Drug Target and Chemotype Identification Pipeline", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TargetID", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2023-07-27" + }, + "description": "pyvisco is a Python library that supports the identification of Prony series parameters for linear viscoelastic materials described by a Generalized Maxwell model. 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This routine is helpful in Finite Element simulations where reducing the computational complexity of the linear viscoelastic material models can shorten the simulation time.\n\nSee also, https://pypi.org/project/pyvisco/", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "pyvisco [SWR-22-30]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pyvisco", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2023-07-27" + }, + "description": "Model predictive control (MPC) is a system or process control technique for making decisions under uncertainty via rolling look-ahead optimizations at each control step where only the current step decisions are applied, and the rest are discarded. In this work, we developed an MPC for a critical load restoration (CLR) in power distribution systems to recover system service (electricity delivery) following an extreme event-triggered substation outage. The method considers the problem of controlling distributed energy resources (DERs) of the distribution system with the objective of achieving maximum load pick up while satisfying distribution network flow and voltage constraints. A linearized optimal power flow (OPF) model is employed to represent the physics of the network. The problem formulation is augmented with a ramping (up) reserve product for the DERs to ensure improved and upward monotonic load restoration as time evolves. Simulation analysis and performance tests are performed using a modified IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage battery. The software is developed using various software packages in Julia and Python. The MPC model is implemented using the JuMP optimization language in Julia while the data analytics including renewable generation and load demand forecasts, running the MPC simulation and visualizations is performed in Python.", + "laborHours": 0.0, + "languages": [ + "Julia", + "Python" + ], + "name": "MPC4CLR (Model-Predictive-Control-for-Critical-Load-Restoration-in-Power-Distribution-Systems) [SWR-22-24]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mpc4clr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "SAND2022-3576 O tenzing provides techniques for improving the performance of key applications and libraries. The program is specified as a directed acyclic graph of operations. It uses Monte-Carlo tree search to explore the design space of possible implementations and applies machine learning to the observed empirical performance to deliver design guidance to users. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++", + "C++", + "CUDA", + "Python 3" + ], + "name": "tenzing", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tenzing", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SAND2022-3548 O This code contains scripts that allow users to generate molecular electron densities, train a machine learning model to predict electron densities, and analyze the accuracy of machine learned electron densities. It accompanies a publication titled \"Cracking the Quantum Scaling Limit with Machine Learned Electron Densities.\u201d Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1565.6, + "languages": [ + "Python", + "Jupyter notebook" + ], + "name": "equivariant_electron_density", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/equivariant_electron_density", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-09-19" + }, + "description": "Hybrid-RL-MPC4CLR was developed as a hybrid controller for active distribution grid critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. The RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while the MPC models grid operations incorporating the RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. The developers formulated the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The software is developed using various software packages in Python. The MPC's optimal power flow (OPF) model is implemented using the Pyomo package, the RL simulation environment is implemented using the MPC simulation with various scenarios of renewable energy and load demand profiles and power outage beginning times, based on the OpenAI Gym framework. The RL agent training is performed using the RLlib Ray package. The RL algorithm is trained offline using historical forecasts of renewable generation and load demand profiles. Simulation analysis and performance tests are conducted using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "python" + ], + "name": "Hybrid-RL-MPC4CLR (Hybird-Reinforcement-Learning-Model-Predictive-Control-for-Reserve-Policy-Assisted-Critical-Load-Restoration-in-Distribution-Grids)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hybrid-rl-mpc4clr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-09-19" + }, + "description": "RLC4CLR demonstrates using a reinforcement learning controller (RLC) to solve a critical load restoration (CLR) problem, which improves the grid resilience after a substation outage event. RLC4CLR consists of two parts. (1) RL environment: This environment encapsulates the CLR problem to be solved and provides interfacing functions to follow the standard OpenAI Gym format. A power system simulator, i.e., OpenDSS, is included to provide the power flow solution. Controller inputs and outputs (RL state and action) as well as the reward are defined in this environment as well. In summary, the RL environment is the problem formulation from which the RL agent can learn. (2) RL training script: The training script enables the RL agent to learn its control policy by interacting with the RL environment. For RL training, an open-sourced RL library, i.e., RLlib, is leveraged which is based on a distributed computing framework (Ray). The training script is designed to be able to be run on both local machine or the NREL HPC system. Other components of RLC4CLR include input data, e.g., grid model (standard IEEE test feeders), and other files used for results analysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "RLC4CLR (Reinforcement Learning Controller for Critical Load Restoration Problems)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rlc4clr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "SAND2021-15055 O Limbo provides a programmatic interface for accessing computer vision training data. It is organized in the Limbo format. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://limbo-ml.readthedocs.io/en/latest", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "Limbo", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://limbo-ml.readthedocs.io/en/latest", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "SAND2021-15054 O PyNucleus is a finite element code for nonlocal equations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python", + "C++" + ], + "name": "PyNucleus", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PyNucleus", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "SAND2021-15053 O ManiPIO is a Python-based tool used to test Programmable Logic Controllers (PLCs), Industrial Control Systems (ICS), and ICS networks. It reads an input script to construct complex Events on ICS networks and uses the ModBus communication standard to communicate. Users can use ManiPIO to construct complex timelines of ICS communication events to simulate any number of network-based scenarios. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ManiPIO - Manipulate Process I/O", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SMARTT", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "gillette7@llnl.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-30" + }, + "description": "This code implements algorithms described in: \"Data-driven geometric scale detection via Delaunay interpolation\" Andrew Gillette and Eugene Kur, 2022 https://arxiv.org/abs/2203.05685", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "LLNL/ddd", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ddd", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "albertop@iastate.edu" + }, + "date": { + "created": "2022-03-30", + "metadataLastUpdated": "2022-03-31" + }, + "description": "Implementation of homogeneous models (PFR and PaSR for applications to biomass pyrolysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Homogeneous models for biomass pyrolysis", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Biomass-Autothermal-Pyrolysis/HomogeneousModels", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "colettima@ornl.gov" + }, + "date": { + "created": "2022-03-31", + "metadataLastUpdated": "2022-03-31" + }, + "description": "Gremlin is an evolutionary algorithm that discovers weaknesses in machine learning models.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Gremlin", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/markcoletti/gremlin", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v0.3" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-03-31", + "metadataLastUpdated": "2022-03-31" + }, + "description": "densegranFoam is a dense granular material flow solver developed using the OpenFoam Computational Fluid Dynamics (CFD) tool. 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The primary focus of the solver is to simulate shear rate dependency on the dense granular flow bulk behavior.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Python" + ], + "name": "densegranFoam", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/densegranFoam", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "albertop@iastate.edu" + }, + "date": { + "created": "2022-03-31", + "metadataLastUpdated": "2022-03-31" + }, + "description": "Eulerian-Eulerian CFD models with bidisperse kinetic theory of the granular flow, and kinetics for biomass pyrolysis. The models were implemented in customized versions of OpenFOAM.", + "laborHours": 0.0, + "languages": [ + "C", + "C++" + ], + "name": "CFD codes for biomass pyrolysis", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Biomass-Autothermal-Pyrolysis/CFDCodes", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "albertop@iastate.edu" + }, + "date": { + "created": "2022-03-31", + "metadataLastUpdated": "2022-03-31" + }, + "description": "Reduced-order model that takes the biomass biochemical composition as input and returns the primary pyrolysis products in a dictionary. ", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Reduced-order model for biomass pyrolysis", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Biomass-Autothermal-Pyrolysis/ReducedOrderModel", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-04-01", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The purpose of Scramble is to provide a cross validation method to ensure machine learning model accuracy in cases where model classes have heterogeneous N values.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Scramble", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Scramble", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-04-05", + "metadataLastUpdated": "2022-07-26" + }, + "description": "JADE provides a simple, flexible interface to submit jobs to an HPC. JADE is an HPC workflow management system that enables researchers to run simulations efficiently. It provides a simple, flexible interface to define jobs, as well as dependencies between jobs, and then dispatch them to an HPC with maximized parallelization. It also provides detailed error reporting and resource utilization statistics to aid in debugging problems.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "JADE", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/jade", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "smith84@llnl.gov" + }, + "date": { + "created": "2022-04-05", + "metadataLastUpdated": "2022-04-05" + }, + "description": "ParFlow is an open-source, modular, parallel watershed flow model. It includes fully-integrated overland flow, the ability to simulate complex topography, geology and heterogeneity and coupled land-surface processes including the land-energy budget, biogeochemistry and snow (via CLM). It is multi-platform and runs with a common I/O structure from laptop to supercomputer. ParFlow is the result of a long, multi-institutional development history and is now a collaborative effort between CSM, LLNL, UniBonn and UCB. ParFlow has been coupled to the mesoscale, meteorological code ARPS and the NCAR code WRF.", + "laborHours": 138532.8, + "languages": [ + "C", + "C++", + "Python", + "Tcl" + ], + "name": "ParFlow", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/parflow/parflow", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.10.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-05", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SAND2021-14370 O Tesuract (tensor surrogate approximation and computation) provides Python tools to build machine learning regressors that include polynomial chaos expansions. The software also offers methods for creation regressors for tensor outputs such as spatially varying fields and using a reduced order modeling methodology. The library is built on and compatible with the scikit-learn API, which allows integration with one of the most ubiquitous machine learning Python libraries out there. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 24639.2, + "languages": [ + "Python" + ], + "name": "tesuract v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tesuract", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-08", + "metadataLastUpdated": "2022-04-08" + }, + "description": "Due to recent improvements in image resolution and acquisition speed, materials microscopy is experiencing an explosion of published imaging data. The standard publication format, while sufficient for traditional data ingestion scenarios where a select number of images can be critically examined and curated manually, is not conducive tolarge-scale data aggregation or analysis, hindering data sharing and reuse. Most images in publications are presented as components of a larger figure with their explicit context buried in the main body or caption text, so even if aggregated, collections of images with weak or no digitized contextual labels have limited value. To solve the problem of curating labeled microscopy data from literature, we introduce the EXSCLAIM! Python toolkit for the automatic EXtraction, Separation, and Caption-based natural Language Annotation of IMages from scientific literature. The software is implemented through a three part pipeline: the JournalScraper, which searches the web and downloads figures and captions based on a user provided query, the CaptionDistributor, which separates caption text based on the subfigure each portion of the caption refers to, and the FigueSeparator, which separates figures into component subfigures and extracts other visual information. Also included is a Django user interface for exploring the resulting dataset.", + "laborHours": 0.0, + "languages": [], + "name": "EXSCLAIM!", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MaterialEyes/exsclaim", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2022-04-11", + "metadataLastUpdated": "2022-04-11" + }, + "description": "METS-R ADDSEVS simulator is a high fidelity, parallel, agent-based evacuation simulator for multi-modal energy-optimal trip scheduling in real-time (METS-R) at transportation hubs. It consists of two modules. The first one is the traffic simulator module; the second one is the high-performance computing (HPC) module. More details can be found at https://umnilab.github.io/METS-R_doc/.", + "homepageURL": "https://umnilab.github.io/METS-R_doc", + "laborHours": 0.0, + "languages": [], + "name": "An agent-based deployment decision-support system for electric vehicle services", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://umnilab.github.io/METS-R_doc", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2022-04-11", + "metadataLastUpdated": "2022-04-11" + }, + "description": "R3IT is a free and open-source web application that allows utilities to automate the processing of solar interconnection requests. It handles request submission, request review workflows, payment collection, signature collection, email notifications for any status changes, and optionally an automated engineering screening and approval process.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "R3IT: Rapid, Rural, Resilient Interconnection Toolkit", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dpinney/r3it", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-04-12", + "metadataLastUpdated": "2023-08-17" + }, + "description": "A surprisingly non-trivial technical challenge is to associate points in space (e.g., GPS data) with specific segments of a road network or map. The software package ( allows users to match GPS point data to a road network (commonly known as \"map matching\"). The software is designed such that a user could match a set of GPS points to a variety of different road network representations using a variety of map matching algorithms. There are currently several \"built-in\" road networks and map matching algorithms but the software has been designed to enable new ones to be added with minimal overhead.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Mappymatch FKA: YAMM (Yet Another Map-Matcher) [SWR 22-38] ", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/yamm", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-04-12", + "metadataLastUpdated": "2022-04-12" + }, + "description": "BinFPE is a tool that detects floating-point exceptions (NaN, infinity, and subnormal quantities) in NVIDIA GPU applications using binary instrumentation. It requires no re-compilation of the application and can analyze libraries. The tool extends NVBit (https://github.com/NVlabs/NVBit), which is provided by NVIDIA Labs to analyze binaries. When the tool detects a floating-point exception it reports to the user the location of the exception (file and line number).", + "laborHours": 0.0, + "languages": [], + "name": "BinFPE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/BinFPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-04-13", + "metadataLastUpdated": "2022-04-13" + }, + "description": "This code performs an optimization over the structure of a porous electrode formed from a lattice of unit cells. This is a steepest descent version of the code used in: V. A. Beck, J. J. Wong, C. F. Jekel, D. A. Tortorelli, S. E. Baker, E. B. Duoss and M. A. Worsley, Computational design of microarchitected porous electrodes for redox flow batteries, J. Power Sources, 2021, 512, 230453.", + "laborHours": 0.0, + "languages": [], + "name": "Lattice Optimization for Porous Electrode", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LOPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software contains a routine for active sampling of a DFT-generated dataset for training a neural network potential (SchNet). Major updates to the base SchNet code are also included to accommodate large systems (100s of atoms). We also provide code to apply the neural network potential in dynamic shear simulations.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Active-Sampling-for-Atomistic-Potentials", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Active-Sampling-for-Atomistic-Potentials", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "Provides an easy to use high-level interface to Web100. 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Towards this goal we are developing a Pervasive Collaborative Computing Environment (PCCE) within which participants can rendezvous and interact with each other. The PCCE aims to support continuous or ad hoc collaboration, target daily tasks and base connectivity, be easy to use and install across multiple platforms, leverage off of existing components when possible, use standards-based components, and leverage off of Grid services (e.g., security and directory services). A key concept for this work is \"incremental trust\", which allows the system's \"trust\" of a given user to change dynamically. PCCE Jabber client software: This leverages Jabber. an open Instant Messaging (IM) protocol and the related Internet Engineering Task Force (IETF) standards \"XMPP\" and \"XMPP-IM\" to allow collaborating parties to chat either one-on-one or in \"chat rooms\". Standard Jabber clients will work within this framework, but the software will also include extensions to a (multi-platform) GUI client (Gaim) for X.509-based security, search, and incremental trust. This software also includes Web interfaces for managing user registration to a Jabber server. PCCE Jabber server software: Extensions to the code, database, and configuration files for the dominant open-source Jabber server, \"jabberd\". Extensions for search, X.509 security, and incremental trust. Note that the jabberd software is not included as part of this software.", + "homepageURL": "https://dst.lbl.gov/ACSSoftware/pccejt/Home", + "laborHours": 0.0, + "languages": [], + "name": "Pervasive Collaboratorive Computing Environment Jabber Toolkit", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://dst.lbl.gov/ACSSoftware/pccejt/Home/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dst.lbl.gov/ACSSoftware/pccejt/Home", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "Non-encrypted, TCP-streams, host-to-host file copy utility intended to enable greater transfer rates, while having the basic user-interface concept of BSD rcp. The underlying design provides the opportunity to maximize performance by allocating supplemental IP sockets as dedicated and optimizable data-channels, in a mode similar to FTP. Additionally, a parallel I/O scheme, based on the HPSS paradigm, is also employed, offering potentials for multiple-sockets over a single network connection (which, in many circumstances, especially those in involving heterogeneous host platforms, or large latency situations, can capture more bandwidth), and also the distribution of the sockets across a manifold of parallel IP network connections.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "MPSCP", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "The L3 system is a computational steering environment for image processing and scientific computing. It consists of an interactive graphical language and interface. Its purpose is to help advanced users in controlling their computational software and assist in the management of data accumulated during numerical experiments. L3 provides a combination of features not found in other environments; these are: - textual and graphical construction of programs - persistence of programs and associated data - direct mapping between the scripts, the parameters, and the produced data - implicit hierarchial data organization - full programmability, including conditionals and functions - incremental execution of programs The software includes the l3 language and the graphical environment. The language is a single-assignment functional language; the implementation consists of lexer, parser, interpreter, storage handler, and editing support, The graphical environment is an event-driven nested list viewer/editor providing graphical elements corresponding to the language. These elements are both the representation of a users program and active interfaces to the values computed by that program.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "L3 Interactive Data Language", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "ProteinShop is a graphical environment that facilitates a solution to the protein prediction problem through a combination of unique features and capabilities. These include: 1. 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It contains two principle components: a multi-paradigm simulation engine and a graphical user interface. EMPaSE models are defined through a hierarchically-defined set of computational modules that define the simulation logic. Inter-module communication occurs through two complimentary systems: pull-based \"ports\" for general computation patterns and push-based \"plugs\" for event processing. Entities (i.e. agents) within the simulation operate within an abstract multi-network environment. The EMPaSE simulation engine is designed around a flexible plug-in architecture, allowing simulations to import computational modules, engine customizations, and interfaces to external applications from independent plug-in libraries. The EMPaSE GUI environment provides an environment for graphically constructing, executing, and debugging EMPaSE models. As with the simulation engine, the GUI is constructed on top of an extensible architecture that supports rapid customization of the user experience through external plug-in libraries.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "gcc>=3.4.2 or Microsfot Visual Studio 2005" + ], + "name": "EMPaSE: an Extensible Multi-Paradigm Simulation Environment", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "JBlulce (Java Beam Line Universal Integrated Configuration Environment is a data acquisition software for macromolecular crystallography conforming user interface of the SSRL Blulce that has become a de-factor standard in the field. Besides this interface conformity, JBlulce is a unique system in terms of architecture, spec, capability and software implementation. It features only two software layers, the JBlulce clients and the EPICS servers, as compared to three layers present in Blulce and most of similar systems. This layers reduction provides a faster communication with hardware and an easier access to advanced hardware capabilities like on-the-fly scanning. Then JBlulce clients are designed to operate in parallel with the other beamline controls which streamlines the tasks performed by staff such as beamline preparation, maintenance, auditing and user assistance. Another distinction is the deployment of multiple plugins that can be written in any programming language thus involving more staff into the development. further on, JBlulce makes use of unified motion controls allowing for easy scanning and optimizing of any beamline component. Finally, the graphic interface is implemented in Java making full use of rich Java libraries and Jave IDE for debugging. to compare, Blulce user interface is implemented with aging Tcl/tk language providing very restricted capabilities. JBlulce makes full use of the industrial power and wide drivers selection of EPICS in controlling hardware; all hardware communication is routed via multiple EPICS servers residing on local area network. JBlulce also includes several EPICS State Notation servers aimed at making hardware communication more robust. Besides using EPICS for controlling hardware, JBlulce extensively uses EPICS databases for efficient communications between multiple instances of JBlulce clients and JBlulce plugins that can run in parallel on different computers. All of the above makes JBlulce one of the biggest and most sophisticated EPICS client projects to date. JBlulce configuration is stored in my SQL database which provides flexibility in tuning the system. The database is also accessible by the plugins. From the users perspective JBlulce provides all standard features of data acquisition software for macromolecular crystallography plus such unique capabilities as one click beamline energy change that may involve switching undulator harmonics, mirrors lanes and beam realignment, automated diffraction rtastering for finding small crystals and sweet spots on poorly diffracting crystals with automated scoring of raster cells by the number of reflections; data collection along a vector; automated on-the-fly fluorescent tastering, a faster and lower-irradiation compliment to the diffraction raster; fully automated fluorescence measurements for MAD that include signal optimization, fast on the fly energy scanning and automated adapting of scan range to chemical shifts; fly-scan minibeam realignment; automated loop and crystal centering, controls for sample automounter, automated screening, data collection auditing, remote access and a lot more.", + "homepageURL": "https://www.gmca.aps.anl.gov/jbluice-epics", + "laborHours": 0.0, + "languages": [ + "SUN JDK 1.6, Perl 5, EPICS 3.14, SNL 2.0" + ], + "name": "JBlulce Data Acquisition Software for Macromolecular Crystallography", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.gmca.aps.anl.gov/jbluice-epics/jbluice-license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gmca.aps.anl.gov/jbluice-epics", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The Relational Blackboard (RBB) is an extension of the H2 Relational Database to support discrete events and timeseries data. The original motivation for RBB is as a knowledge base for cognitive systems and simulations. It is useful wherever there is a need for persistent storage of timeseries (i.e. samples of a continuous process generating numerical data) and semantic labels for the data. The RBB is an extension to the H2 Relational Database, which is open-source. RBB is a set of stored procedures for H2 allowing data to be labeled, queried, and resampled.", + "laborHours": 62107.2, + "languages": [ + "Java", + "HTML" + ], + "name": "Relational Blackboard", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/RelationalBlackboard", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "STUCCO will be a scalable visual analytics solution that identifies and collects endogenous and exogenous data from data sources not traditionally associated with cyber security to enable both the identification of relevant, non-security data with cyber security event data and the display of an overview of global security threats.", + "homepageURL": "https://stucco.github.io", + "laborHours": 0.0, + "languages": [ + "Node.js 0.6 or higher" + ], + "name": "STUCCO", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/stucco/stucco.github.io/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://stucco.github.io", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "The iGlobe system is a desktop-based visualization and analysis environment which allows seamless integration of multiple geospatial data sets from varied sources and provides an interface to interactively analyze the different data sets and apply sophisticated data analysis and mining algorithms in a near real time fashion. The framework is highly desirable in domains such as earth and climate sciences where great emphasis is placed on simultaneous analysis of different data sets such as remote sensing images, climate model simulation outputs, and other environmental and demographic databases, to understand weather and climate systems and the impact of climate change in nature and people.", + "homepageURL": "https://cse.buffalo.edu/~chandola/iglobe/iglobe.html", + "laborHours": 0.0, + "languages": [ + "JAVA Java (TM) SE runtime Environment Version 1.6.0" + ], + "name": "iGlobe: An Interactive Visualization and Analysis Framework for Geospatial Data", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://cse.buffalo.edu/~chandola/iglobe/iglobe.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cse.buffalo.edu/~chandola/iglobe/iglobe.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "EnergyPlus is a whole building energy simulation program that engineers, architects and researchers use to model energy and water use in buildings. Modeling the performance of a building with EnergyPlus enables building professionals to optimize the building design to use less energy and water. Each version of EnergyPlus is tested extensively before release. EnergyPlus models heating, cooling, lighting, ventilation, other energy flows, and water use. EnergyPlus includes many innovation simulation capabilities: time-steps less than an hour, modular systems and plant integrated with heat balance-based zone simulation, multizone air flow, thermal comfort, water use, natural ventilation, and photovoltaic systems. EnergyPlus runs on the Windows, Macintosh, and Linux platforms. Free add-ons and other third party software products are available for use with EnergyPlus.", + "laborHours": 0.0, + "languages": [ + "Intel Fortran V11" + ], + "name": "EnergyPlus Version 7", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://energyplus.net/licensing", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlusRelease/releases/tag/7.0.0.036", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "7.0.0.036" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "meraculous2 is a whole genome shotgun assembler for short-reads that is capable of assembling large, polymorphic genomes with modest computational requirements. Meraculous relies on an efficient and conservative traversal of the subgraph of the k-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. Additional features include (1) handling of allelic variation using \"bubble\" structures within the deBruijn graph, (2) gap closing of repetitive and low quality regions using localized assemblies, and (3) an improved scaffolding algorithm that produces more complete assemblies without compromising on scaffolding accuracy", + "homepageURL": "https://sourceforge.net/projects/meraculous20", + "laborHours": 0.0, + "languages": [ + "GCC g++>=4.63" + ], + "name": "Meraculous2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/meraculous20", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "The MRPA++ computer code simulates neutron scattering and superconductivity in correlated electron systems. It uses a random-phase approximation (RPA) / Bardeen-Cooper-Schrieffer (BCS) theory to predict the neutron scattering cross section of realistic multi-orbital tight-binding models with Hubbard-like electron-electron interactions for the normal and superconducting states. It can also be used to calculate the pairing interaction in these models using an RPA approximation and to predict the superconducting gap structure.", + "laborHours": 0.0, + "languages": [ + "C++/Gnu g++ (GCC)/4.1.2" + ], + "name": "MRPA++", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/maierta/MRPAPP/blob/master/Open%20Source%20Software%20License%20MRPAPP.doc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maierta/MRPAPP", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "This web site provides a single online system for AASG State Geothermal Data participants to integrate their data into the NGDS, discovering how to digitize at-risk, legacy, geothermal-relevant data and combine it with existing digital data to create a publicly accessible system.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "State Geothermal Data data delivery tools", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "This program simulates the beam propagation of weather radar pulses under particular and realistic atmospheric conditions (without using the assumption of standard refraction conditions). It consists of two modules: radiosondings_refract_index_many.pro (MAIN MODULE) beam_propagation_function.pro(EXTERNAL FUNCTION) FOR THE MAIN MODULE, THE CODE DOES OUTPUT--INTO A FILE--THE BEAM HEIGHT AS A FUNCTION OF RANGE. THE RADIOSONDE INPUT FILES SHOULD BE ALREADY AVAILABLE BY THE USER. FOR EXAMPLE, RADIOSONDE OBSERVATION FILES CAN BE OBTAINED AT: RADIOSONDE OBSERVATIONS DOWNLOADED AT \"http://weather.uwyo.edu/upperair/soounding.html\" OR \"http://jervis.pyr.ec.gc.ca\" THE EXTERNAL FUNCTION DOES THE ACTUAL COMPUTATION OF BEAM PROPAGATION. IT INCLUDES CONDITIONS OF ANOMALOUS PROPAGATION AND NEGATIVE ELEVATION ANGLES. THE EQUATIONS USED HERE WERE DERIVED BY EDWIN CAMPOS, BASED ON THE SNELL-DESCARTES LAW OF REFRACTION, CONSIDERING THE EARTH CURVATURE. THE PROGRAM REQUIRES A COMPILER FOR THE INTERACTIVE DATA LANGUAGE (IDL). DESCRIPTION AND VALIDATION DETAILS HAVE BEEN PUBLISHED IN THE PEER-REVIEWED SCIENTIFIC LITERATURE, AS FOLLOWS: Campos E. 2012. Estimating weather radar coverage over complex terrain, pp.26-32, peer reviewed, in Weather Radar and Hydrology, edited by Moore RJ, Cole SJ and Illingworth AJ. International Association of Hydrological Sciences (IAHS) Press, IAHS Publ. 351. ISBN 978-1-907161-26-1.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [ + "Interactive Data Language" + ], + "name": "Beam Propagator for Weather Radars, Modules 1 and 2", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "The Biogeochemical Transport and Reaction Model (BeTR) is a F90 code that enables reactive transport modeling in land modules of earth system models (e.g. CESM, ACME). The code adopts the Objective-Oriented-Design, and allows users to plug in their own biogeochemical (BGC) formulations/codes, and compare them to other existing BGC codes in those ESMs. The code takes information of soil physics variables, such as variables, such as temperature, moisture, soil density profile; water flow, etc., from a land model to track the movement of different chemicals in presence of biogeochemical reactions.", + "laborHours": 0.0, + "languages": [ + "N/A" + ], + "name": "Biogeochemical Transport and Reaction Model (BeTR) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/BeTR-biogeochemistry-modeling/sbetr/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BeTR-biogeochemistry-modeling/sbetr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "A closed-loop proportional-integral (PI) control software is provided for fully mechanically controlled automated electron microscopic tomography. The software is developed based on Gatan DigitalMicrograph, and is compatible with Zeiss LIBRA 120 transmission electron microscope. However, it can be expanded to other TEM instrument with modification. The software consists of a graphical user interface, a digital PI controller, an image analyzing unit, and other drive units (i.e.: image acquire unit and goniometer drive unit). During a tomography data collection process, the image analyzing unit analyzes both the accumulated shift and defocus value of the latest acquired image, and provides the results to the digital PI controller. The digital PI control compares the results with the preset values and determines the optimum adjustments of the goniometer. The goniometer drive unit adjusts the spatial position of the specimen according to the instructions given by the digital PI controller for the next tilt angle and image acquisition. The goniometer drive unit achieves high precision positioning by using a backlash elimination method. The major benefits of the software are: 1) the goniometer drive unit keeps pre-aligned/optimized beam conditions unchanged and achieves position tracking solely through mechanical control; 2) the image analyzing unit relies on only historical data and therefore does not require additional images/exposures; 3) the PI controller enables the system to dynamically track the imaging target with extremely low system error.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "A Closed-Loop Proportional-Integral (PI) Control Software for Fully Mechanically Controlled Automated Electron Microscopic Tomography", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "Beam Instrumentation Development System (BIDS) is a collection of common support libraries and modules developed during a series of Low-Level Radio Frequency (LLRF) control and timing/synchronization projects. BIDS includes a collection of Hardware Description Language (HDL) libraries and software libraries. The BIDS can be used for the development of any FPGA-based system, such as LLRF controllers. HDL code in this library is generic and supports common Digital Signal Processing (DSP) functions, FPGA-specific drivers (high-speed serial link wrappers, clock generation, etc.), ADC/DAC drivers, Ethernet MAC implementation, etc.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "G++, ISE" + ], + "name": "Beam Instrument Development System", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-23" + }, + "description": "miniTri is a miniapplication developed as part of the Mantevo project. Given a graph, miniTri enumerates all triangles in this graph and computes a metric for each triangle based on the triangle edge and vertex degree. The output of miniTri is a summary of this metric. miniTri mimics the computational requirements of an important set of data science applications. Several approaches to this problem are included in the miniTri software.", + "laborHours": 5791.2, + "languages": [ + "C, C++", + "Makefile" + ], + "name": "miniTri Mantevo miniapp v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/miniTri?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniTri", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "GEECS (Generalized Equipment and Experiment Control System) monitors and controls equipment distributed across a network, performs experiments by scanning input variables, and collects and stores various types of data synchronously from devices. Examples of devices include cameras, motors and pressure gauges. GEEKS is based upon LabView graphical object oriented programming (GOOP), allowing for a modular and scalable framework. Data is published for subscription of an arbitrary number of variables over TCP. A secondary framework allows easy development of graphical user interfaces for a combined control of any available devices on the control system without the need of programming knowledge. This allows for rapid integration of GEECS into a wide variety of systems. A database interface provides for devise and process configuration while allowing the user to save large quantities of data to local or network drives.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "LABVIEW 2011 OR LATER" + ], + "name": "GEECS (Generalized Equipment and Experiment Control System)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient distributed algorithms to solve the problem for big data sets. We propose a high-performance distributed-memory parallel algorithm that computes the factorization by iteratively solving alternating non-negative least squares (NLS) subproblems for $\\WW$ and $\\HH$. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). As opposed to previous implementation, our algorithm is also flexible: It performs well for both dense and sparse matrices, and allows the user to choose any one of the multiple algorithms for solving the updates to low rank factors $\\WW$ and $\\HH$ within the alternating iterations.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "HPC-NMF: A High-Performance Parallel Algorithm for Nonnegative Matrix Factorization", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ramkikannan/planc/blob/master/license.dat", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ramkikannan/planc", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-29" + }, + "description": "The purpose of the DYNAMIC software system is to perform simulations to validate a new research concept called \u201cChaotic Logic\u201d which we recently published. The problem to be solved is to simulate certain networks of nonlinearly-interacting dynamical variables, and collect statistics on their behavior, to show that they can reliably perform useful computations. The dynamical trajectories for such networks are computed by time integration of their Hamilton\u2019s equations.", + "laborHours": 2827.2, + "languages": [ + "Python 3.5.2" + ], + "name": "DYNAMIC - The Nonlinear Dynamical Network Simulator v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/dynamic", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "The ExaSAT framework automates the extraction of parameterized performance models directly from source code using compiler analysis. Its parameterized analytic model enables quantitative evaluation of a broad range of hardware design trade-offs and software optimizations on a variety of different performance metrics, with a primary focus on data movement as a metric. ExaSAT analysis provides insights in the hardware and software tradeoffs and lays the groundwork for exploring a more targeted set of design points using cycle-accurate architectural simulators and emulators.", + "laborHours": 0.0, + "languages": [ + "NA" + ], + "name": "ExaSat: An Exascale Static Analysis Tool (ExaSat) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LBL-CoDEx/exasat/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-CoDEx/exasat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "Modern cosmology and plasma physics codes are now capable of simulating trillions of particles on petascale systems. Each timestep output from such simulations is on the order of 10s of TBs. Summarizing and visualizing raw particle data is challenging, and scientists often focus on density structures, whether in the real 3D space, or a high-dimensional phase space. In this work, code was developed for reading 10s of terabytes of data and for writing the resultant cluster IDs for each particle. This code will be part of a highly scalable version of the clustering algorithm DBSCAN, and apply it to the largest datasets produced by state-of-the-art codes. The overall function of BD-CATS (Big Data Clustering at Trillion Particles Scale) is to perform end-to-end analysis: loading the data, dynamic partitioning, computing kdtrees, performing clustering analysis, and storing the results. 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Plasmas 14 072706 (2007).", + "laborHours": 0.0, + "languages": [], + "name": "Linear Grains", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LIGR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-04-18", + "metadataLastUpdated": "2024-03-11" + }, + "description": "OPFLearn.jl is a Julia package for creating datasets for machine learning approaches to solving AC optimal power flow (AC OPF). 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However, current rule-based and machine learning models for this purpose are limited in how efficiently and effectively they can do this. 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This visualization tool apart from having pedagogic application can serve as a tool for discovering previously unknown phenomena in the nuclear chart.", + "laborHours": 0.0, + "languages": [], + "name": "ANDES (ARGONNE NUCLEAR DATA EXPLORATION SOFTWARE) - Physics Tools", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.phy.anl.gov/andes/physics-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-05-19", + "metadataLastUpdated": "2022-10-06" + }, + "description": "The Machine Learning Pipeline (ML Pipeline) allows the user to fit a model to predict a dependent variable, y, based on a feature set, X. 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ML Pipeline accomplishes all this, while remaining simple to use and interpret.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "ML Pipeline (Machine Learning Pipeline) [SWR-22-35]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Machine-Learning-Pipeline", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-05-19", + "metadataLastUpdated": "2022-06-15" + }, + "description": "The software allows for queueing and dispatch of tasks of small, varied, or uncertain runtimes across multiple HPC jobs, resources, and other computing systems. 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Our current studies indicate a ten-fold performance gain by using graphics-processing-units (GPU) compared to a single processor for representative problem sizes (2 million cell mesh).", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "mesoflow [SWR-22-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mesoflow", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-05-25", + "metadataLastUpdated": "2023-04-12" + }, + "description": "Synthetic dIstribution Network Generator is a standalone python module that is able to create synthetic distribution models for OpenDSS using GIS datasets. 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This package is meant to supplement the scientific community use of Gaussian process prediction with derivatives. 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The goal of the tools is to provide machine learning modeling capabilities for rejecting interference. Recent related machine learning algorithms for signal processing have focused mostly on speech enhancement or multi-speaker speech separation; the tools in SplitML will extend these innovations to generic time-domain signals of interest. SplitML includes tools for generating synthetic noisy signals, code for customized machine learning models applicable to interference rejection, and tools for evaluating such algorithms against standard signal processing techniques. These components are written in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning and signal processing.", + "laborHours": 0.0, + "languages": [], + "name": "SplitML", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SplitML", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Ray tracing and ray casting have been extensively studied by the graphics and visualization community to create images. Many different algorithms as well as optimizations techniques have been developed to help speed up these two techniques and make best use of different hardware. However, ray tracing and ray casting can also be used for scientific purposes. While graphics applications focus on photon interactions, scientific application will also monitor the interaction of photons, electrons, neutrons, alpha particles, and other particles. For example, ray casting can be used in cosmology to study the re-ionization of the early universe where ultraviolet photons broke atoms apart and ray tracing of ions can be used to study mass spectography. For this project, the aim is to investigate how techniques, frameworks, algorithms, optimizations, ... developed by the graphics community could be modified and applied to solve scientific problems requiring the tracing of different particles.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Agnostic Particle Tracing", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2022-07-15" + }, + "description": "Test suite of quantum algorithms for Noisy Intermediate Scale Quantum (NISQ) computers. The test suite includes benchmark-style code for quantum volume circuits (QV), fairness sampling circuits, quantum telecloning circuits, and other NISQ benchmark style algorithms on small problems (i.e., up to 100 qubits), such as Variational Quantum Eigensolver (VQE), Hamiltonian Simulation, and Grover unstructured search example circuits. These benchmark-style applications are implemented in quantum software packages, mostly IBM's QISKIT, but may include vendor-specific frameworks, such as PyQuil (for Rigetti) or Q\\# for Microsoft, or CirQ (for Google) as the test suite grows with the vendor sample. The test suite also includes numerical simulation code for Quantum Alternating Operator Ansatz (QAOA) algorithms, VQE, Hamiltonian Simulation and search examples. Numerical simulation code simulates quantum computers on classical computers, which is only possible for small problem instances; the implementation framework of choice is typically within Python, using the numpy/scipy libraries as well as extensions to the Julia language.", + "laborHours": 0.0, + "languages": [], + "name": "NISQ Benchmarking", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Quantum-Volume-in-Practice", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2022-07-15" + }, + "description": "The Sunny package is an existing open source software to support the simulation of magnetic spin systems. It is available online under the MIT license here: https://github.com/SunnySuite/Sunny.jl The package aims to include the following features: - Analysis for symmetry-allowed interactions - Monte Carlo algorithms for simulating equilibrium configurations. - Schemes for integrating spin dynamics. - Inference of model Hamiltonians - Support for generalized SU(N) spins - Tools for interpreting experimental data, such as diffraction data, magnetization curves, and heat capacity data", + "laborHours": 0.0, + "languages": [], + "name": "Contributing to Sunny open source code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SunnySuite/Sunny.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PUFFIn software package is a graphical user interface that allows for photon and electron beam calculations using the\nPENELOPE computer code. It prepares the required input files and displays the resulting output data. It can be used by\nanyone interested in the interaction of photon or electron beams with matter", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "PUFFIn", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SOCRATES is a Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites. It provides tools to retrieve, filter,\nselect, and view Hanford data and to perform multiple types of data analyses. SOCRATES currently includes four data\nanalytics modules", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "SOCRATES", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Chernobyl Bibliographic Search System (Chernolit TM) provides bibliographic data in a usable format for research studies relating to the Chernobyl nuclear accident that occurred in the former Ukrainian Republic of the USSR in 1986. Chernolit TM is a portable and easy to use product. The bibliographic data is provided under the control of a graphical user interface so that the user may quickly and easily retrieve pertinent information from the large database. The user may search the database for occurrences of words, names, or phrases; view bibliographic references on screen; and obtain reports of selected references. Reports may be viewed on the screen, printed, or accumulated in a folder that is written to a disk file when the user exits the software. Chernolit TM provides a cost-effective alternative to multiple, independent literature searches. Forty-five hundred references concerning the accident, including abstracts, are distributed with Chernolit TM. The data contained in the database were obtained from electronic literature searches and from requested donations from individuals and organizations. These literature searches interrogated the Energy Science and Technology database (formerly DOE ENERGY) of the DIALOG Information Retrieval Service. Energy Science and Technology, provided by the U.S. DOE, Washington, D.C., is a multi-disciplinary database containing references to the world's scientific and technical literature on energy. All unclassified information processed at the Office of Scientific and Technical Information (OSTI) of the U.S. DOE is included in the database. In addition, information on many documents has been manually added to Chernolit TM. Most of this information was obtained in response to requests for data sent to people and/or organizations throughout the world.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Chernobyl Bibliographic Search System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "SID characterizes natural language based documents so that they may be related and retrieved based on content similarity. This technology processes textual documents, autonomously identifies the major topics of the document set, and constructs an interpretable, high dimensional representation of each document. SID also provides the ability to interactively re-weight representations based on user needs, so that users may analyze the data set from multiple points of view. The particular advantages SID offers are speed, data compression, flexibility in representation, and incremental processing.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "System for Information Discovery", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "SID characterizes natural language based documents so that they may be related and retrieved based on content similarity. This technology processes textual documents, autonomously identifies the major topics of the document set, and constructs an interpretable, high dimensional representation of each document. SID also provides the ability to interactively reweight representations based on user need, so users may analyze the dataset from multiple points of view. The particular advantages SID offers are speed, data compression, flexibility in representation, and incremental processing. SPIRE consists of software for visual analysis of text-based information sources. This technology enables users to make discoveries about the content of very large sets of textual documents without requiring the user to read or presort the documents. It employs algorithms for text and word proximity analysis to identify the key themes within the documents. The results of this analysis are projected onto a visual spatial proximity display (Galaxies or Themescape) where document proximity represents the degree of relatedness of theme.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "System for Information Discovery - SPIRE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Acoustic Inspection Device (AID) is an instrument used to interrogate materials with ultrasonic acoustic waves. The AID application software program runs under the Microsoft Windows 98 or Windows 2000 operating system. Is serves as the instrument controller and provides the user interface for the instrument known as the Acoustic Inspection Device (AID). The program requests, acquires, and analyzes acoustic waveforms from the AID hardware (pulser/receiver module, digitizer, and communications link). Graphical user displays of the AID application program include the real-time display of ultrasonic acoustic waveforms and analytical results including acoustic time-of-flight, velocity, and material identification. This program utilizes a novel algorithm, developed at PNNL, that automatically extracts the time-of-flight and amplitude data from the raw waveform and compares the extracted data to a material database.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Acoustic Inspection Device V1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The D3P system is designed to provide a very fast imaging system in order to search for weapons on persons in an airport environment. The complete vision of the D3P system is to have two array systems facing each other. Version 2.3 of the software is designed to control and process data from a single panel. A second panel is expected to be added at a future date and the software will be modified at that time to integrate the images from two panels at one time. The D3P software can be segmented into three specific tasks. The first task is data acquisition and scanner control. At the operator's request, this task commands the scanner to move and the radar transceiver-array to send data to the computer system in a known and well-ordered manner. The array is moved over the complete aperture in 1 to 2 seconds. At the completion of the array movement the second software task reconstructs the high-resolution image from the radar data utilizing the integrated DSP board. The third task displays the result to the computer screen for user review and analysis.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Dual Panal Planar Portal", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The CS system is designed to provide a very fast imaging system in order to search for weapons on persons in an airport environment. The Cylindrical Scanner moves a vertical transceiver array rapidly around a person standing stationary. The software can be segmented in to three specific tasks. The first task is data acquisition and scanner control. At the operator's request, this task commands the scanner to move and the radar transceiver array to send data to the computer system in a known and well-ordered manner. The array is moved over the complete aperture in 10 to 12 seconds. At the completion of the array movement the second software task automatically reconstructs the high-resolution image from the radar data utilizing the integrated DSP boards. The third task displays the resulting images, as they become available, to the computer screen for user review and analysis.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Cylindrical Scanner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "TRA was developed as a computer tool for the DOE Office of River Protection (ORP) that will provides the capability to visualize and rapidly understand information about the risks associated with the River protection Project (RPP). Previously, technical and programmatic risk management within ORP had relied heavily on risk lists and other techniques that presented risk information but did not place it in perspective of the overall project. This made it difficult for ORP senior management to understand the risk information presented, prioritize their activities, and provide direction to ORP staff and contractors about how to manage specific risk events. The TRA visualization tool, provides the appropriate context and perspective that allows senior management to effectively manage risks. Basically, the TRA overlays information about risks associated with specific activities and their magnitudes on top of the project baseline schedule. this provides senior management with information about the magnitudes of specific risk events as well as their timing, and allows them to focus their attention and resources on the risks that merit attention and possible further action. The TRA tool can also be used to display other types of information associated with scheduled activities, such as cost to date, technical performance, schedule performance, etc. Additionally, the base of the 3-dimensional representation can be changed to other types of graphics, such as maps, process flow diagrams, etc., which allows the display of other types of information, such as hazards, health and safety risks, and system availability.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Topographical Risk Assessment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Code for Internal Dosimetry Software Package (CINDY1.4) was developed to assist in the interpretation of bioassay data, provide bioassay projections, and evaluate committed and calendar-year doses from intake or bioassay measurement data. CINDY1.4 addresses the U.S. Department of Energy's (DOE) Order 5480.11 and the U.S. Nuclear Regulatory Commission's (NRC) 10 CFR 20 by providing the capabilities to calculate organ dose equivalents and effective dose equivalents using the International Commission on radiological Protection (ICRP) 30 approach. Biokinetic models, which allow user-modified parameter values, are used to estimate intakes based on bioassay data using weighted and unweighted least-squares regression between measured and expected bioassay values, to estimate organ burdens as well as urinary and fecal excretion rates from a given intake, and to determine organ doses for annual, 50-year, calendar year, or any other time point. Intakes to be considered may be either acute or chronic, and may consist of many combinations of intake routes, radionuclides, and physical and chemical forms. A four-compartment input model (with user defined parameters) is used for wounds and absorption. Direct injection can be simulated as direct absorption. Appropriate metabolic models for each radionuclide are selected by the user from menus. Metabolic models available in CINDY1.4 are the ICRP 30 lung model, ICRP 30 gastrointestinal model, ICRP 30 general systematic model, Johnson and Dunford tritium model, ICRP 30 tritium model, including the Johnson HT lung model, Johnson alkaline earth model, ICRP 54 iodine model, tellurium-iodine model, Jones excretion model, Durbin excretion model, ICRP 54 excretion models, Wrenn-Lipsztein uranium model, Fisher Modified Wrenn-Lipsztein uranium model, and the ICRP 30 carbon model. 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WebOSB is able to disseminate real-time status information support the timely sharing of information with constant, dynamic updates via personal computers and the Internet between emergency operations centers (EOCs), incident command centers, and to users outside the EOC who need to know the information (hospitals, shelters, schools). The WebOSB application far exceeds outdated information-sharing methods used by emergency workers: whiteboards, Word and Excel documents, or even locality-specific Web sites. WebOSB's capabilities include the following elements: - Secure access. Multiple users can access information on WebOSB from any personal computer with Internet access and a secure ID. Privileges are use to control access and distribution of status information and to identify users who are authorized to add or edit information. - Simultaneous update. WebOSB provides options for users to add, display, and update dynamic information simultaneously at all locations involved in the emergency management effort, A single status board can be updated from multiple locations enabling shelters and hospitals to post bed availability or list decontamination capability. - On-the-fly modification. Allowing the definition of an existing status board to be modified on-the-fly can be an asset during an emergency, where information requirements can change quickly. The status board designer feature allows an administrator to quickly define, modi,, add to, and implement new status boards in minutes without needing the help of Web designers and computer programmers. - Publisher/subscriber notification. As a subscriber, each user automatically receives notification of any new information relating to specific status boards. The publisher/subscriber feature automatically notified each user of any new information relating to specific status boards. WebOSB can be installed to fit the specific needs of an emergency management community. 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The software also includes utilities to switch into the chroot environment from the command-line and a pluggable authentication module (PAM) allowing transparent startup of the chroot environment for users.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "gcc" + ], + "name": "CHOS", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Amber Plug-in for ProteinShop has two main components: an AmberEngine library to compute the protein energy models, and a module to solve the energy minimization problem using an optimization algorithm in the OPTI-+ library. Together, these components allow the visualization of the protein folding process in ProteinShop. AmberEngine is a object-oriented library to compute molecular energies based on the Amber model. The main class is called ProteinEnergy. Its main interface methods are (1) \"init\" to initialize internal variables needed to compute the energy. (2) \"eval\" to evaluate the total energy given a vector of coordinates. Additional methods allow the user to evaluate the individual components of the energy model (bond, angle, dihedral, non-bonded-1-4, and non-bonded energies) and to obtain the energy of each individual atom. The Amber Engine library source code includes examples and test routines that illustrate the use of the library in stand alone programs. The energy minimization module uses the AmberEngine library and the nonlinear optimization library OPT++. OPT++ is open source software available under the GNU Lesser General Public License. The minimization module currently makes use of the LBFGS optimization algorithm in OPT++ to perform the energy minimization. Future releases may give the user a choice of other algorithms available in OPT++.", + "homepageURL": "https://sourceforge.net/projects/proteinshop", + "laborHours": 0.0, + "languages": [], + "name": "Amber Plug-In for Protein Shop", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/proteinshop", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Program is a suite of Windows-based software applications and services for ingesting, storing, and analyzing large quantities of disparate information. The software supports the ingestion and storage of any information that can be represented in eXtensible Markup Language (XML) format. Stored information can be subsequently retrieved via search operations, then \"visualized\" in multiple ways using a client application that supports a variety of analytical functions. Visualization capabilities include tools for depicting a variety of relationships that may be present in the information, including geospatial, temporal, topical, categorical, and network relationships.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++, Microsoft.net2003 7.1" + ], + "name": "Framework for an Information Visualization System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Skummee is a collection of cluster monitoring tools.", + "homepageURL": "https://sourceforge.net/projects/skummee", + "laborHours": 0.0, + "languages": [], + "name": "Skummee", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/skummee", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "A log viewing and filtering tool.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "LogJam", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/logjam", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "CORE is an architecture to bridge the gaps between disparate data integration and delivery of disparate information visualization. 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It allows the user to specify a variety of different node layout and communication routine variations and reports the maximal observed bandwidth across all specified options. 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It can run in wo modi: using a static or a random mapping of tasks to torus locations. 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The first 8 of those 40 ranks are expected to be on the 'core' node being benchmarked, while the rest of the ranks are on separate nodes.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Sequoia Messaging Rate Benchmark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/sequoia-messaging-rate-benchmark", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The system implements a flexible and extensible scene graph for the visualization and analysis of scientific information.", + "laborHours": 0.0, + "languages": [], + "name": "Simple and Flexible Scene Graph", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/simple-and-flexible-scene-graph", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Whole Building Energy Diagnostician v. 3.x software detects anomalies in energy consumption of buildings and major building systems using metered energy-use data and measured values of driving variables (e.g., outdoor-air temperature, outdoor-air relative humidity, and building occupancy schedule). The software then provides alarms for anomalous consumption and information on energy and cost impacts. This version is intended to be implemented as a world wide web application and made accessible to end users by use of a Web browser and an Internet connection, but the web interface is not provided as part of the software - a web service provider must provide the web-based graphical user interface.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Whole Building Energy Diagnostician, version 3.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "DCAF is a software library containing analytic functions for encoding, mapping, structuring, and providing access to relations among a collection of entities and deriving attribute and structural features for the purposes of providing an interpretable representation of the information within a collection.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Deep Center Analytical Foundations v. 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "GreenArrow is a visualization program for displaying directed graphs that can use text in place of lines to represent the edges between nodes. This text can be animated to show the link direction, and allow for more text to be displayed then would normally be allowed. The text is also tapered and arced to show direction. The node labels can be wrapped around the node to avoid label crossing as well. The program is interactive, and allows the user to zoom, pan and rotate a graph, as well as manipulate the individual nodes.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "GreenArrow version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "AKEA provides tools for the creation, maintenance, visualization, and analysis of information expressed in semantic graph form. It is capable of taking information expressed in unstructured text documents or structured data documents (e.g., spreadsheets, databases), ingesting it and extracting entities and relationships of interest, then presenting said information in graphical form. In addition, it contains tools for applying traditional social network analysis algorithms to the generated graphs in order to identify key players or entities with particular characteristics, geospatial and temporal visualization of said data, and user-controlled storage of information to support future analysis needs.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Analyst-Driven Knowledge Enhancement & Analysis version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The purpose of the Collaborative Analytical Toolbox (CAT) is to provide a comprehensive, enabling, collaborative problem solving environment that enables users to more effectively apply and improve their analytical and problem solving capabilities. CAT is a software framework for integrating other tools and data sources. It includes a set of core services for collaboration and information exploration and analysis, and a framework that facilitates quickly integrating new ideas, techniques, and tools with existing data sources.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java", + "C++, J++" + ], + "name": "Collaborative Analytical Toolbox version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The PHD automatically detects and diagnoses faults with respect to four major aspects of packaged heating, ventilating, and air conditioning (HVAC) unit operation: 1) air handling in which return-air and outdoor-air are mixed, then conditioned to appropriate temperature and humidity conditions, 2) vapor-compression refrigerant loop operation, 3) overall unit efficiency and its potential degradation over time, and 4) operation scheduling. When faults are detected, the software provides alarm codes corresponding to the detected problem(s). These alarms map into explanations of the faults, possible causes for them, and suggested actions to remedy the faults. For air handling, the software also estimates energy and cost impacts of faults. The software is intended for implementation on a hardware systems that includes sensors, sensor signal processing, micro-processor unit for running this software, and communication to a web server. Results are made available to users via the world wide web using a computer with Web browser and Internet connection for access. The graphical web-based interface must be provided by an application service provider (not part of this software).", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Packaged HVAC Unit Diagnostician version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "VZIN integrates visual analytics capabilities into popular desktop tools to aid a user in searching and understanding an information space. VZIN allows users to Drag-Drop-Visualize-Explore-Organize information within tools such as Microsoft Office, Windows Explorer, Excel, and Outlook. VZIN is tailorable to specific client or industry requirements. VZIN follows the desktop metaphors so that advanced analytical capabilities are available with minimal user training.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Visual Information for the Desktop, version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "SYNTH was designed to synthesize the results of typical gamma-ray spectroscopy experiments. The code allows a user to specify the physical characteristics of a gamma-ray source, the quantity of radionuclides emitting gamma radiation, the source-to-detector distance and the presence and type of any intervening absorbers, the size and type of the gamma-ray detector, and the electronic set-up used to gather the data.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "SYNTH - Gamma Ray Spectrum Synthesizer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "CORE is an architecture to bridge the gaps between disparate data integration and delivery of disparate information visualization. The CORE Technology Program includes a suite of tools and user-centered staff that can facilitate rapid delivery of a deployable integrated information to users. Integration of Air Force data streams, summarizing the information and providing team members with the information they need to rapidly understand and respond.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Common Operating and Response Environment - U.S. Air Force", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "CORE is an architecture to bridge the gaps between disparate data integration and delivery of disparate information visualization. The CORE Technology Program includes a suite of tools and user-centered staff that can facilitate rapid delivery of a deployable integrated information to users.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "CORE - Performance Feedback System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "System allows for information to be collected, shared, and commented on by a large group of users. The interaction with the system is independent of time and location, so that input of information and conversations can occur more naturally as they currently do with email.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Situational Awareness for Strategic Leadership (part of CORE system)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Resource management and workflow capability applied to engineering design situational awareness, providing the ability to make assignments and track progress through the construction and maintenance life cycle of an engineered structure.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Resource Tracking and Workflow System - part of the CORE system", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "A data integration system to support the US Customs and Border Protection Officers to supervise and make decisions for container inspections. CORE is designed to act as a framework to bridge the gaps between disparate data integration and delivery of disparate information visualization.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Container Security - part of the CORE system", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "EMTA is a stand-alone computer program that has been developed for the computation of elastic properties and thermal expansion coefficients (thermoelastic properties) of discontinuous fiber composites. EMTA stands for the Eshelby-Mori-Tanaka approach. It implements the standard and modified Mori-Tanaka models that use the Eshelby's equivalent inclusion method. EMTA carries out the Eshelby-Mori-Tanaka homogenization procedure accounting for the constituents (fiber and matrix) properties such as the elastic properties and thermal expansion coefficients (CTEs) of the fibers and of the matrix. It also accounts for the constituents features such as fiber length and orientation distributions, fiber curvature, and imperfect fiber/matrix interfaces. The outputs of an EMTA execution are the elastic properties (engineering constants) and CTEs of the as-formed composite in the defined material coordinate system. These results can readily be used in engineering applications and designs that require these properties.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Eshelby-Mori-Tanaka Approach", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "EMTA-NLA is a computer program for analyzing the nonlinear stiffness, strength, and thermo-elastic properties of discontinuous fiber composite materials. Discontinuous fiber composites are chopped-fiber reinforced polymer materials that are formed by injection molding or compression molding techniques. The fibers tend to align during forming as the composite flows and fills the mold. EMTA-NLA can read the fiber orientation data from the molding software, Autodesk Moldflow Plastics Insight, and calculate the local material properties for accurately analyzing the warpage, stiffness, and strength of the as-formed composite part using the commercial NLA software. Therefore, EMTA-NLA is a unique assembly of mathematical algorithms that provide a one-of-a-kind composites constitutive model that links these two powerful commercial software packages.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "EMTA-NLA", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The ESG-CET system consist of two major components: 1) Gateways that support portal services, which serve as interfaces to end-users who can search, discover, and request data and data products, and 2) Data Nodes where the data actually resides. The Data is \"published\" to the Data Node, which makes the data visible to a Gateway and enables its delivery to end-users. It is expected that Gateways will only be installed by a small number of centers devoted to serving data (e.g., LLNL/PCMDI, NCAR, GFDL, DADC, DKRZ, ANU, JAMSTEC), whereas it is hoped that most climate modeling centers will install the Data Node software through which they can serve their model output.", + "laborHours": 0.0, + "languages": [], + "name": "Earth System Grid (ESG) Data Node Software Stack", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/earth-system-grid-esg-data-node-software-stack", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Fit event counting histograms.", + "laborHours": 0.0, + "languages": [], + "name": "Levenberg-Marquardt Minimization for Poisson Distributed Data", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/levenberg-marquardt-minimization-for-poisson-distributed-data", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Pacific Northwest National Laboratory (PNNL) has developed a prototype stream extraction algorithm that semi-automatically extracts and characterizes streams using a variety of multisensor imagery and digital terrain elevation data. The system is currently optimized for three types of single-band imagery: radar, visible, and thermal. Method of Solution: DRAGON: (1) classifies pixels into clumps of water objects based on the classification of water pixels by spectral signatures and neighborhood relationships, (2) uses the morphology operations (erosion and dilation) to separate out large lakes (or embayment), isolated lakes, ponds, wide rivers and narrow rivers, and (3) translates the river objects into vector objects. In detail, the process can be broken down into the following steps. A. Water pixels are initially identified using on the extend range and slope values (if an optional DEM file is available). B. Erode to the distance that defines a large water body and then dilate back. The resulting mask can be used to identify large lake and embayment objects that are then removed from the image. Since this operation be time consuming it is only performed if a simple test (i.e. a large box can be found somewhere in the image that contains only water pixels) that indicates a large water body is present. C. All water pixels are clumped (in Imagine terminology clumping is when pixels of a common classification that touch are connected) and clumps which do not contain pure water pixels (e.g. dark cloud shadows) are removed D. The resulting true water pixels are clumped and water objects which are too small (e.g. ponds) or isolated lakes (i.e. isolated objects with a small compactness ratio) are removed. Note that at this point lakes have been identified has a byproduct of the filtering process and can be output has vector layers if needed. E. At this point only river pixels are left in the image. To separate out wide rivers all objects in the image are eroded by the half width of narrow rivers. This causes all narrow rivers to be removed and leaves only the core of wide rivers. This core is dilated out by the same distance to create a mask that is used with the original river image to separate out rivers into two separate images of narrow rivers and wide rivers F. If in the image that contains wide rivers there are small isolated short (less than 300 meters if NGA criteria is used) segments these segments are transferred to the narrow river file in order to be treated has parts of single line rivers G. The narrow river file is optionally dilated and eroded. This closing has the effect of removing small islands, filling small gaps, and smoothing the outline. H. The user also has the option of closing objects in the wide river file. However, this depends on the degree to which the user wants to remove small islands in the large rivers. I. To make the translation from raster to single vector easier the objects in the narrow river image are reduced to a single center line (i.e. thinned) with binary morphology operations.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Drainage Algorithm for Geospatial Knowledge", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The RAD3D software solves the critical heat transfer mechanisms that occur in production glass furnaces. The code includes state-of-the-art solution algorithms for efficient radiant interaction of the heating elements, furnace walls and internal furnace components. The code specifically solves the coupled radiative and conductive heating of semi-transparent materials such as glass to calculate the temperature distribution in the glass during processing.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Radiation Heat Transfer in 3 Dimensions for Semi-Transparent Materials....", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Polisher is a software package designed to facilitate the error correction of an assembled genome using Illumia read data. The software addresses substandard regions by automatically correcting consensus errors and/or suggesting primer walking reactions to improve the quality of the bases.", + "laborHours": 0.0, + "languages": [ + "Perl" + ], + "name": "Polisher", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/polisher", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "MANGO software is to provide a solution for improving small signal stability of power systems through adjusting operator-controllable variables using PMU measurement. System oscillation problems are one of the major threats to the grid stability and reliability in California and the Western Interconnection. These problems result in power fluctuations, lower grid operation efficiency, and may even lead to large-scale grid breakup and outages. This MANGO software aims to solve this problem by automatically generating recommended operation procedures termed Modal Analysis for Grid Operation (MANGO) to improve damping of inter-area oscillation modes. The MANGO procedure includes three steps: recognizing small signal stability problems, implementing operating point adjustment using modal sensitivity, and evaluating the effectiveness of the adjustment. The MANGO software package is designed to help implement the MANGO procedure.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab, Python script, batch script, PSAT Python script" + ], + "name": "Modal Analysis for Grid Operation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "FLOWER was written as a refactoring/reimplementation of the existing Flo software used by the Cooperative Protection Program (CPP) to provide network flow summaries for analysis by the Operational Analysis Center (OAC) and other US Department of Energy cyber security elements. FLOWER is designed and tested to operate at 10 gigabits/second, nearly 10 times faster than competing solutions. FLOWER output is optimized for importation into SQL databases for categorization and analysis. FLOWER is written in C++ using current best software engineering practices.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "FLOWER IPv4/IPv6 Network Flow Summarization software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Liquid Chromatography-Ion Mobility-time of Flight Instrument Control and Data Visualization software is designed to control instrument voltages for the Ion Mobility drift tube. It collects and stores information collected from the Agilent TOF instrument and analyses/displays the ion intensity information acquired. The software interface can be split into 3 categories -- Instrument Settings/Controls, Data Acquisition, and Viewer. The Instrument Settings/Controls prepares the instrument for Data Acquisition. The Viewer contains common objects that are used by Instrument Settings/Controls and Data Acquisition. Intensity information is collected in 1 nanosec bins and separated by TOF pulses called scans. A collection of scans are stored side by side making up an accumulation. In order for the computer to keep up with the stream of data, 30-50 accumulations are commonly summed into a single frame. A collection of frames makes up an experiment. The Viewer software then takes the experiment and presents the data in several possible ways, each frame can be viewed in TOF bins or m/z (mass to charge ratio). The experiment can be viewed frame by frame, merging several frames, or by viewing the peak chromatogram. The user can zoom into the data, export data, and/or animate frames. Additional features include calibration of the data and even post-processing multiplexed data.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C#, C++" + ], + "name": "LC-IM-TOF Instrument Control & Data Visualization Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Wrapper Induction is a software package that allows for unsupervised, semi-supervised, and manual extraction of social media data independent of language or site architecture. A large range of blog formats is available to individuals as means of publishing data to the internet. Blogs are a source of rich information for analysts. With a growing volume of information and blog engines, there is an increased need for automatic or semi-automatic extraction of that data for processing to help deliver results to analysts. Wrapper Induction is designed to automatically or semi-automatically create a template that can be used to harvest blog data from websites. Blogs are in a variety of formats and languages. Wrapper Induction creates a template and extracts blog data in a way that is independent of a specified blog format or language.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java, Javascript" + ], + "name": "Wrapper Induction Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "GridLAB-D is a new power system simulation tool that provides valuable information to users who design and operate electric power transmission and distribution systems, and to utilities that wish to take advantage of the latest smart grid technology. This special release of GridLAB-D was developed to study the proposed Smart Grid technology that is used by Battelle Memorial Institute in the AEP gridSMART demonstration project in Northeast Columbus, Ohio.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C, C++, Java" + ], + "name": "GridLAB-D/SG", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "A hybrid demand response simulator is developed to test different control algorithms for centralized and distributed demand response (DR) programs in a small distribution power grid. The HDRS is designed to model a wide variety of DR services such as peak having, load shifting, arbitrage, spinning reserves, load following, regulation, emergency load shedding, etc. The HDRS does not model the dynamic behaviors of the loads, rather, it simulates the load scheduling and dispatch process. The load models include TCAs (water heaters, air conditioners, refrigerators, freezers, etc) and non-TCAs (lighting, washer, dishwasher, etc.) The ambient temperature changes, thermal resistance, capacitance, and the unit control logics can be modeled for TCA loads. The use patterns of the non-TCA can be modeled by probability of use and probabilistic durations. Some of the communication network characteristics, such as delays and errors, can also be modeled. Most importantly, because the simulator is modular and greatly simplified the thermal models for TCA loads, it is very easy and fast to be used to test and validate different control algorithms in a simulated environment.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab/Simlink" + ], + "name": "A Hybrid Demand Response Simulator Version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "DSOM (Decision Support for Operations and Maintenance) is an expert operations and maintenance system that integrates plant operations, fuel management, and maintenance processes. The DSOM package provides operators with the information they need for cost-effective operating decisions creating savings in fuel, personnel, maintenance, and plant life extension. DSOM provides operators real-time system performance information to allow them to determine if the plant is malfunctioning or running below expectations. By catching potential problems, DSOM enables plants to operate safely at peak efficiency, while providing a higher level of reliability and safety.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++", + "Java", + "PHP" + ], + "name": "Decision Support for Operations and Maintenance IV", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Tool Gear Version 2 is an expanded collection of programs and software libraries that form the infrastructure on which software tools may be built. The software tools help application developers understand the performance of the programs or help them find programming errors. Tool Gear includes components for gathering data from target programs, either through direct instrumentations or by parsing the output of third-party tools, transmitting the data to a database, organizing and storing the data, presenting it through a variety of graphical interfaces. Tool Gear is designed to be an extensible system, so users can manage a variety of data and create new ways to present it. Tool Gear is designed to work with both sequential and parallel programs on multiple computer platforms", + "laborHours": 0.0, + "languages": [], + "name": "Tool Gear Version 2.3", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/tool-gear-version-2.3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The CLOMP_TM benchmark was developed to measure the overheads of various mechanisms used to guarantee the generation of correct results in threaded code even when multiple threads might be accessing and/or updating the same memory location at the same time. This includes widely supported mechanisms like OpenMP Atomic and Open MP Critical as well as new mechanisms like Transactional Memory (TM) and Speculative Execution (SE) of threads. The CLOMP_TM benchmark is highly configurable to allow a variety of problem sizes, atomic update region sizes, and potential race condition opportunities to be studied. A wide variety of checks are done on the results to verify the expected answer was actually generated. Thus CLOMP_TM can be used both to measure the overhead for various mechanisms and to check the correctness of their implementation.", + "laborHours": 0.0, + "languages": [], + "name": "CLOMP_TM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/clomp-tm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "ASSA is a software application that processes binary data into summarized index tables that can be used to organize features contained within the data. ASSA's index tables can also be used to search for user specified features. ASSA is designed to organize and search for patterns in unstructured binary data streams or archives, such as video, images, audio, and network traffic. ASSA is basically a very general search engine used to search for any pattern in any binary data stream. It has uses in video analytics, image analysis, audio analysis, searching hard-drives, monitoring network traffic, etc.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++, C, Fortran, Python, PHP, Javascript, HTML" + ], + "name": "All Source Sensor Analysis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "MSI QuickView is a software designed to provide a graphical user interface (GUI) for greatly speeding up experimental feedback (visualization and analysis) of mass spectrometry imaging (MSI or IMS) data during data acquisition. Often different software loads the entire data set, i.e., all lines of data into computer memory (RAM). This causes out of memory errors for larger datasets. We solved this in MSI QuickView by reading in the data one line at a time. Only the required information (e.g. the final pixel values for that line of heat map) is maintained in RAM. Interim analysis options include the mean intensity vs. m/z spectrum, intensity vs. time spectrums for up to 6 different m/z values or ranges chosen by the user and heat maps for each line. This assists in validating the usefulness of the particular experiment after scanning the first few lines. In addition, the tool facilitates further processing and analysis of the massive datasets. The user can manually pick different m/z values, time ranges, scroll through the spectra for any line in the data without having to load it in manually, save multiple images, change aspect ratios for the heat maps, and process the heat maps in multiple ways including overlaying images at different m/z values, displaying up to 9 different heat maps, alignment of scans along each line etc. There is no manipulation of the data required by the user to visualize the data.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "MATLAB, Java" + ], + "name": "Mass Spectrometry Imaging Quick View", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "LC-IMS-MS Feature Finder is a command line software application which searches for possible molecular ion signatures in multidimensional liquid chromatography, ion mobility spectrometry, and mass spectrometry data by clustering deisotoped peaks with similar monoisotopic mass values, charge states, elution times, and drift times. The software application includes an algorithm for detecting multiple conformations and co-eluting species in the ion mobility dimension. LC-IMS-MS Feature Finder is designed to create an output file with detected features that includes associated information about the detected features.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "LC-IMS-MS Feature Finder", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The BioPA provides turbine designers with a set of tools that can be used to assess biological risks of turbines during the design phase, before expensive construction begins. The toolset can also be used to assess existing installations under a variety of operating conditions, supplementing data obtained through expensive field testing. The BioPA uses computational fluid dynamics (CFD) simulations of a turbine design to quantify the exposure of passing fish to a set of known injury mechanisms. By appropriate sampling of the fluid domain, the BioPA assigns exposure probabilities to each mechanism. The exposure probabilities are combined with dose-response data from laboratory stress studies of fish to produce a set of biological BioPA Scores. These metrics provide an objective measure that can be used to compare competing turbines or to refine a new design. The BioPA process can be performed during the turbine design phase and is considerably less expensive than prototype-scale field testing.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Tecplot Macro, Python, Visual Basic" + ], + "name": "Biological Performance Assessment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Spindle is software infrastructure that solves file system scalability problems associated with starting dynamically linked applications in HPC environments. When an HPC applications starts up thousands of processes at once, and those processes simultaneously access a shared file system to look for shared libraries, it can cause significant performance problems for both the application and other users. Spindle scalably coordinates the distribution of shared libraries to an application to avoid hammering the shared file system.", + "laborHours": 0.0, + "languages": [], + "name": "Spindle", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/hpc/Spindle/blob/devel/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/spindle", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "SOFC-MP is a simulation tool developed at PNNL to evaluate the tightly coupled multi-physical phenomena in SOFCs. The purpose of the tool is to allow SOFC manufacturers to numerically test changes in planar stack design to meet DOE technical targets. The SOFC-MP 2D module is designed for computational efficiency to enable rapid engineering evaluations for operation of tall symmetric stacks. It can quickly compute distributions for the current density, voltage, temperature, and species composition in tall stacks with co-flow or counter-flow orientations. The 3D module computes distributions in entire 3D domain and handles all planner configurations: co-flow, counter-flow, and cross-flow. The detailed data from 3D simulation can be used as input for structural analysis. SOFC-MP GUI integrates both 2D and 3D modules, and it provides user friendly pre-processing and post-processing capabilities.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++, FORTRAN, C#" + ], + "name": "Solid Oxide Fuel Cell - Multi-Physics and GUI", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "BMA-NIS is a package/library designed to be called by a script (e.g. Perl or Python). The software itself is written in the language of R. The software assists electric power delivery systems in planning resource availability and demand, based on historical data and current data variables. Net Interchange Schedule (NIS) is the algebraic sum of all energy scheduled to flow into or out of a balancing area during any interval. Accurate forecasts for NIS are important so that the Area Control Error (ACE) stays within an acceptable limit. To date, there are many approaches for forecasting NIS but all none of these are based on single models that can be sensitive to time of day and day of week effects.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "R" + ], + "name": "System for NIS Forecasting Based on Ensembles Analysis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "RUT software is designed for use by the Balancing Authorities to predict and display additional requirements caused by the variability and uncertainty in load and generation. The prediction is made for the next operating hours as well as for the next day. The tool predicts possible deficiencies in generation capability and ramping capability. This deficiency of balancing resources can cause serious risks to power system stability and also impact real-time market energy prices. The tool dynamically and adaptively correlates changing system conditions with the additional balancing needs triggered by the interplay between forecasted and actual load and output of variable resources. The assessment is performed using a specially developed probabilistic algorithm incorporating multiple sources of uncertainty including wind, solar and load forecast errors. The tool evaluates required generation for a worst case scenario, with a user-specified confidence level.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "VB.NET" + ], + "name": "Ramping and Uncertainty Prediction Tool - Analysis and Visualization of Wind Generation Impact on Electrical Grid", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "ESIOS is a software program developed at Pacific Northwest National Laboratory (PNNL) that performs intra-hour dispatch and automatic generation control (AGC) simulations for electric power system frequency regulation and load/variable generation following. The program dispatches generation resources at minute interval to meet control performance requirements, while incorporating stochastic models of forecast errors and variability with generation, load, interchange and market behaviors. The simulator also contains an operator model that mimics manual actions to adjust resource dispatch and maintain system reserves. Besides simulating generation fleet intra-hour dispatch, ESIOS can also be used as a test platform for the design and verification of energy storage, demand response, and other technologies helping to accommodate variable generation.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Python, Java" + ], + "name": "Electric System Intra-hour Operation Simulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Profile Interface Generator (PIG) is a tool for loosely coupling applications and performance tools. It enables applications to write code that looks like standard C and Fortran functions calls, without requiring that applications link to specific implementations of those function calls. Performance tools can register with PIG in order to listen to only the calls that give information they care about. This interface reduces the build and configuration burden on application developers and allows semantic instrumentation to live in production codes without interfering with production runs.", + "laborHours": 0.0, + "languages": [], + "name": "Profile Interface Generator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/profile-interface-generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "DAMPI is a dynamic testing/verification tool that scalably covers non-deterministic interactions of MPI (e.g., sildcard-receives).", + "laborHours": 0.0, + "languages": [], + "name": "The Dynamic Analyzer for MPI: the first dynamic analyzer of MPI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/the-dynamic-analyzer-for-mpi-the-first-dynamic-analyzer-of-mpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "LIQUID (Lipid Informed Quantitation and Identification) is a software program that has been developed to enable users to conduct both informed and high-throughput global liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based lipidomics analysis. This newly designed desktop application can quickly identify and quantify lipids from LC-MS/MS datasets while providing a friendly graphical user interface for users to fully explore the data. Informed data analysis simply involves the user specifying an electrospray ionization mode, lipid common name (i.e. PE(16:0/18:2)), and associated charge carrier. A stemplot of the isotopic profile and a line plot of the extracted ion chromatogram are also provided to show the MS-level evidence of the identified lipid. In addition to plots, other information such as intensity, mass measurement error, and elution time are also provided. Typically, a global analysis for 15,000 lipid targets.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Lipid Informed Quantitation and Identification", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Electrical resistivity tomography ERT is a method of imaging the electrical conductivity of the subsurface. Electrical conductivity is a useful metric for understanding the subsurface because it is governed by geomechanical and geochemical properties that drive subsurface systems. ERT works by injecting current into the subsurface across a pair of electrodes, and measuring the corresponding electrical potential response across another pair of electrodes. Many such measurements are strategically taken across an array of electrodes to produce an ERT data set. These data are then processed through a computationally demanding process known as inversion to produce an image of the subsurface conductivity structure that gave rise to the measurements. Data can be inverted to provide 2D images, 3D images, or in the case of time-lapse 3D imaging, 4D images. ERT is generally not well suited for environments with buried electrically conductive infrastructure such as pipes, tanks, or well casings, because these features tend to dominate and degrade ERT images. This reduces or eliminates the utility of ERT imaging where it would otherwise be highly useful for, for example, imaging fluid migration from leaking pipes, imaging soil contamination beneath leaking subsurface tanks, and monitoring contaminant migration in locations with dense network of metal cased monitoring wells. The location and dimension of buried metallic infrastructure is often known. If so, then the effects of the infrastructure can be explicitly modeled within the ERT imaging algorithm, and thereby removed from the corresponding ERT image. However, there are a number of obstacles limiting this application. 1) Metallic infrastructure cannot be accurately modeled with standard codes because of the large contrast in conductivity between the metal and host material. 2) Modeling infrastructure in true dimension requires the computational mesh to be highly refined near the metal inclusions, which increases computational demands. 3) The ERT imaging algorithm requires specialized modifications to accommodate high conductivity inclusions within the computational mesh. The solution to each of these challenges was implemented within E4D (formerly FERM3D), which is a parallel ERT imaging code developed at PNNL (IPID #30249). The infrastructure modeling module implement in E4D uses a method of decoupling the model at the metallic interface(s) boundaries, into several well posed sub-problems (one for each distinct metallic inclusion) that are subsequently solved and recombined to form the global solution. The approach is based on the immersed interface method, with has been applied for similar problems in other fields (e.g. semiconductor industry). Comparisons to analytic solutions have shown the results to be very accurate, addressing item 1 above. The solution is implemented about an unstructured mesh, which enables arbitrary shapes to be efficiently modelled, thereby addressing item 2 above. In addition, the algorithm is written in parallel and shows excellent scalability, which also addresses equation 2 above. Finally, because only the boundaries of metallic inclusions are modeled, there are no high conductivity cells within the modeling mesh, and the problem described by item 3 above is no longer applicable.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "gfortran/intel" + ], + "name": "Parallel Infrastructure Modeling and Inversion Module for E4D", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "This software code is designed to track generator state variables in real time using the Ensemble Kalman Filter method with the aid of PMU measurements. This code can also be used to calibrate dynamic model parameters by augmenting parameters in the state variable vector.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab" + ], + "name": "Grid State Estimation Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Designed for building energy managers, utilities and firms providing energy services, FEDS provides a comprehensive and user-friendly method for users to quickly and accurately identifying energy conversion and end-use technology improvements that offer maximum savings in energy usage and cost. FEDS enables the user to assess energy efficiency and consumption, identify retrofit opportunities, select minimum life cycle costs, determine payback, and prioritize investments in energy efficiency retrofit projects for multiple or single buildings across a particular site. As part of the life-cycle cost optimization it also considers several options for partial or complete abandonment of central energy plants including: individual technologies dropping off a thermal loop, a loop and all technologies dropping off a central plant, and all technologies and loops dropping off a central plant resulting in its complete abandonment. Improvements in release 7.0 include: FEDS 7.0 is now a full hourly simulation model (runs every hour of the year as opposed to the previous simplified hourly approach which ran 9 24-hour periods to represent each month). Enhanced building operation and occupancy modeling; New HVAC technology options (VAV, Economizers, Demand Controlled Ventilation, Terminal Reheat, Subcool Dehumidification); Additional chiller types; New lighting technologies (LED, Halogen, Induction, additional fluorescent options); Completely updated retrofit cost and performance data; Regional cost data tied to zip code (previously applied state level averages); Updated and enhanced reporting capabilities; and New pier floor model", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++, Microsoft Visual Studio" + ], + "name": "Facility Energy Decision System (FEDS) version 7.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "This work extends Biocellion 1.0 to solve advection-reaction-diffusion and incompressible Navier-Stokes partial differential equations to model water/blood flow. Biocellion is a software framework to simulate a large number of cells using high-performance parallel computers. The version 1.0 allows software users to describe biological system behaviors as a set of rules describing how individual cells behave and how cells locally interact with neighboring cells or the surrounding micro-environment. However, the version 1.0 does not support users to incorporate water/blood flow into the model, which is important to properly capture long distance communications between distant cells. This extension (version 2.0) integrates two partial differential equation solvers to the Biocellion framework to solve this limitation. Navier-Stokes equation solvers (for incompressible flow) are added to compute flow rate, and advection-reaction-diffusion equation solvers are added to update molecular concentrations considering both advection (due to flow) and local diffusion.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Biocellion Version 2.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "FELIX is a physics computer code used to model fission fragment mass distributions in a fully quantum-mechanical, microscopic framework that only relies on our current knowledge of nuclear forces. It is an implementation of the time-dependent generator coordinate method (TDGCM), which simulates the dynamics of a collective quantum wave-packet assuming the motion is adiabatic. In typical applications of the TDGCM, the nuclear collective wavepacket is obtained as a superposition of wavefunctions obtained by solving the Hartree-Fock-Bogoliubov equations of nuclear density functional theory (DFT). The program calculates at each time step the coefficients of that superposition.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Finite Element Solver for Fission Dynamics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/finite-element-solver-for-fission-dynamics", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Developed to solve specific problem: Assist transmission planning for regional transfers in interconnected power systems. This work was originated in a study for the U.S. Department of State, to recommend transmission reinforcements for the Central American regional system that interconnects 6 countries. Transmission planning analysis is currently performed by engineers with domain-specific and system-specific knowledge without a unique methodology. The software codes of this disclosure assists engineers by defining systematic analysis procedures to help identify weak points and make decisions on transmission planning of regional interconnected power systems. Transmission Planning Analysis Tool groups PSS/E results of multiple AC contingency analysis and voltage stability analysis and QV analysis of many scenarios of study and arrange them in a systematic way to aid power system planning engineers or transmission operators in effective decision-making process or in the offline study environment.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab/ 7.11.0" + ], + "name": "Transmission Planning Analysis Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "SWIFT is a computer code that is designed to do research level signal analysis on seismic waveforms, including visualization, filtering and measurement. LLNL is using this code, amplitude and global tomography efforts.", + "laborHours": 0.0, + "languages": [ + "JAVA 100%" + ], + "name": "Seismic waveform viewer, processor and calculator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/seismic-waveform-viewer-processor-and-calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The battery storage sizing tool developed at Pacific Northwest National Laboratory can be used to evaluate economic performance and determine the optimal size of battery storage in different use cases considering multiple power system applications. The considered use cases include i) utility owned battery storage, and ii) battery storage behind customer meter. The power system applications from energy storage include energy arbitrage, balancing services, T&D deferral, outage mitigation, demand charge reduction etc. Most of existing solutions consider only one or two grid services simultaneously, such as balancing service and energy arbitrage. ES-select developed by Sandia and KEMA is able to consider multiple grid services but it stacks the grid services based on priorities instead of co-optimization. This tool is the first one that provides a co-optimization for systematic and local grid services.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Optimal Sizing Tool for Battery Storage in Grid Applications", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2025-04-14" + }, + "description": "ABCD is a four-level hierarchy with human supervisors at the top, a top-level agent called a Sergeant controlling each enclave, Sentinel agents located at each monitored host, and mobile Sensor agents that swarm through the enclaves to detect cyber malice and misconfigurations. The code comprises four parts: (1) the core agent framework, (2) the user interface and visualization, (3) test-range software to create a network of virtual machines including a simulated Internet and user and host activity emulation scripts, and (4) a test harness to allow the safe running of adversarial code within the framework of monitored virtual machines.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 371898.4, + "languages": [ + "Python 2.6 or later" + ], + "name": "Ant-Based Cyber Defense", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Contingency analysis based approach for quantifying and examining the resiliency of a cyber system in respect to confidentiality, integrity and availability. A graph representing an organization's cyber system and related resources is used for the availability contingency analysis. The mission critical paths associated with an organization are used to determine the consequences of a potential contingency. A node (or combination of nodes) are removed from the graph to analyze a particular contingency. The value of all mission critical paths that are disrupted by that contingency are used to quantify its severity. A total severity score can be calculated based on the complete list of all these contingencies. A simple n1 analysis can be done in which only one node is removed at a time for the analysis. We can also compute nk analysis, where k is the number of nodes to simultaneously remove for analysis. A contingency risk score can also be computed, which takes the probability of the contingencies into account. In addition to availability, we can also quantify confidentiality and integrity scores for the system. These treat user accounts as potential contingencies. The amount (and type) of files that an account can read to is used to compute the confidentiality score. The amount (and type) of files that an account can write to is used to compute the integrity score. As with availability analysis, we can use this information to compute total severity scores in regards to confidentiality and integrity. We can also take probability into account to compute associated risk scores.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++11 QtCreator 5.3" + ], + "name": "Cyber Contingency Analysis version 1.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The battery storage evaluation tool developed at Pacific Northwest National Laboratory is used to run a one-year simulation to evaluate the benefits of battery storage for multiple grid applications, including energy arbitrage, balancing service, capacity value, distribution system equipment deferral, and outage mitigation. This tool is based on the optimal control strategies to capture multiple services from a single energy storage device. In this control strategy, at each hour, a lookahead optimization is first formulated and solved to determine the battery base operating point. The minute-by-minute simulation is then performed to simulate the actual battery operation.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab MCR" + ], + "name": "Battery Storage Evaluation Tool, version 1.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Look-ahead dynamic simulation software system incorporates the high performance parallel computing technologies, significantly reduces the solution time for each transient simulation case, and brings the dynamic simulation analysis into on-line applications to enable more transparency for better reliability and asset utilization. It takes the snapshot of the current power grid status, functions in parallel computing the system dynamic simulation, and outputs the transient response of the power system in real time.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Linux" + ], + "name": "Look-ahead Dynamic Simulation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Methodology that interpolates low time-resolution data (e.g., hourly) to high time-resolution (e.g., minutely) with variability patterns extracted from historical records. Magnitude of the variability inserted into the low time resolution data can be adjusted according to the installed capacity represented by the low time-resolution data compared to that by historical records. This approach enables detailed analysis of the impacts from wind and solar on power system intra-hour operations and balancing reserve requirements even with only hourly data. It also allows convenient creation of high resolution wind or solar generation data with various degree of variability to investigate their operational impacts. The methodology comprises of the following steps: 1. Smooth the historical data (set A) with an appropriate window length l to get its trend (set B); l can be a fraction of an hour (e.g., 15 minutes) or longer than an hour, of which the length of the variability patterns will be; 2. Extract the variable component (set C) of historical data by subtracting the smooth trend from it, i.e. set C = set A - set B 3. For each window length l of the variable component data set, find the average value x (will call it base component) of the corresponding window of the historical data set; 4. Define a series of segments (set D) that the values of data will be grouped into, e.g. (0, 0.1), (0.1, 0.2), ..., (0.9, 1.0) after normalization; Link each variability pattern to a data segment based on its corresponding base component x; after this step, each data segment should be linked to multiple variability patterns after this step; 5. Use spline function to interpolate the low time-resolution forecast data (set E) to become a high time-resolution smooth curve (set F); 6. Based on the window length l , calculate the average value y in each window length of set F; find the data segment that y belongs to; then randomly select one of the variability patterns linked to this data segment; 7. Add the selected variability pattern in each window to set F to get the high time-resolution data (set G) with variability observed from historical data set A; a coefficient k can be multiplied to the selected variability pattern to reflect the potential difference in variability between forecast set E and historical data set A caused by installation capacity and other factors. 8. After set G is constructed, variability statistics can be checked for set A and set G for comparison. Adjust the coefficient k if necessary to achieve desired variability in the reconstructed data.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Interpolating Low Time-Resolution Forecast Data", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Power system operation requires maintaining a continuous balance between system demand and generation within certain constraints. Traditionally, the balancing processes are based on deterministic models, which do not consider possible random deviations of system generation and load from their predicted values. With the increasing penetration of the renewable generation, unexpected balancing problems can happen due to the deviations. This can result in serious risks to system reliability and efficiency. When the available balancing reserve is not enough to cover the predicted net load range with uncertainty, deficiency of balancing needs occurs. In this case, it is necessary to commit or de-commit additional conventional generators to achieve the desired confidence level for the balancing needs. The framework is built for solving this problem. The ramping tool engine is used to predict additional balancing requirements caused by the variability and uncertainty of the renewable energy, under the constraints of the generation ramping capability and interchange schedule. The web browser- based GUI is used to visualize the data in web-environment, which provides flexibility to allow user to see the ramping outputs in any platform. The GOSS structure provides strong support to allow easy communication between ramping engine, and system inputs, as well as the GUI.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java 8.x" + ], + "name": "A Framework to Support Generator Ramping Uncertainty Analysis and Visualization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The STOMP simulator is a suite of numerical simulators developed by Pacific Northwest National Laboratory for addressing problems involving coupled multifluid hydrologic, thermal, geochemical, and geomechanical processes in the subsurface. The simulator has been applied to problems concerning environmental remediation, environmental stewardship, carbon sequestration, conventional petroleum production, and the production of unconventional hydrocarbon fuels. The simulator is copyrighted by Battelle Memorial Institute, and is available outside of PNNL via use agreements. To promote the open exchange of scientific ideas the simulator is provided as source code. A demonstration version of the simulator has been developed, which will provide potential new users with an executable (not source code) implementation of the software royalty free. Demonstration versions will be offered via the STOMP website for all currently available operational modes of the simulator. The demonstration versions of the simulator will be configured with the direct banded linear system solver and have a limit of 1,000 active grid cells. This will provide potential new users with an opportunity to apply the code to simple problems, including many of the STOMP short course problems, without having to pay a license fee. Users will be required to register on the STOMP website prior to receiving an executable.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Fortran 90" + ], + "name": "Subsurface Transport Over Multiple Phases Demonstration Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The software was created in the process of developing a system known as the Smart Monitoring and Diagnostic System (SMDS) for packaged air conditioners and heat pumps used on commercial buildings (known as RTUs). The SMDS provides automated remote monitoring and detection of performance degradation and faults in these RTUs and could increase the awareness by building owners and maintenance providers of the condition of the equipment, the cost of operating it in degraded condition, and the quality of maintenance and repair service when it is performed. The SMDS provides these capabilities and would enable conditioned-based maintenance rather than the reactive and schedule-based preventive maintenance commonly used today, when maintenance of RTUs is done at all. Improved maintenance would help ensure persistent peak operating efficiencies, reducing energy consumption by an estimated 10% to 30%.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C#, C++, PHP, JavaScript, MSSQL query, .NET" + ], + "name": "Methodology for Automated Detection of Degradation and Faults in Packaged Air Conditioners and Heat Pumps Using Only Two Sensors", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The PPMV is used to validate generator model using disturbance recordings. The PPMV tool contains a collection of power plant models and model validation studies, as well as disturbance recordings from a number of historic grid events. The user can import data from a new disturbance into the database, which converts PMU and SCADA data into GE PSLF format, and then run the tool to validate (or invalidate) the model for a specific power plant against its actual performance. The PNNL PPMV tool enables the automation of the process of power plant model validation using disturbance recordings. The tool uses PMU and SCADA measurements as input information. The tool automatically adjusts all required EPCL scripts and interacts with GE PSLF in the batch mode. The main tool features includes: The tool interacts with GE PSLF; The tool uses GE PSLF Play-In Function for generator model validation; Database of projects (model validation studies); Database of the historic events; Database of the power plant; The tool has advanced visualization capabilities; and the tool automatically generates reports.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "EPCL" + ], + "name": "Power Plant Model Validation Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "MultiSpeaker is a software application that parses wsdl and xsd files that define the MultiSpeak protocol. The MultiSpeak protocol (www.multispeak.org) is a SOA-based integration architecture that defines the complex communications between various endpoints of a utility company. MultiSpeaker parses the files and presents an easy to read and understand representation of the underlying protocol. The user may then use visual clues to know what message elements are required, descriptions for the elements along with valid entries. The user may then edit or modify the payload of the actual messages. MultiSpeaker also provides a mechanism for scheduling multiple modified protocol messages.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Qt" + ], + "name": "Multispeaker", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Fishes and marine mammals may suffer a range of potential effects from exposure to intense underwater sound generated by anthropogenic activities such as pile driving, shipping, sonars, and underwater blasting. Several underwater sound recording (USR) devices have been built to acquire samples of the underwater sound generated by anthropogenic activities. Software becomes indispensable for processing and analyzing the audio files recorded by these USRs. The new Aquatic Acoustic Metrics Interface Utility Software (AAMI) is specifically designed for analysis of underwater sound recordings to provide data in metrics that facilitate evaluation of the potential impacts of the sound on aquatic animals. In addition to the basic functions, such as loading and editing audio files recorded by USRs and batch processing of sound files, the software utilizes recording system calibration data to compute important parameters in physical units. The software also facilitates comparison of the noise sound sample metrics with biological measures such as audiograms of the sensitivity of aquatic animals to the sound, integrating various components into a single analytical frame.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab" + ], + "name": "Aquatic Acoustic Metrics Interface", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "SADE is a software package for rapidly assembling analytic pipelines to manipulate data. The packages consists of the engine that manages the data and coordinates the movement of data between the tasks performing a function, a set of core libraries consisting of plugins that perform common tasks, and a framework to extend the system supporting the development of new plugins. Currently through configuration files, a pipeline can be defined that maps the routing of data through a series of plugins. Pipelines can be run in a batch mode or can process streaming data; they can be executed from the command line or run through a Windows background service. There currently exists over a hundred plugins, over fifty pipeline configurations, and the software is now being used by about a half-dozen projects.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Windows.Net framework 4.5, C#" + ], + "name": "Streaming Analytics and Data Engineering", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "T.Rex is used to explore tabular data sets containing up to ten million records to help rapidly understand a previously unknown data set. Analysis can quickly identify patterns of interest and the records and fields that capture those patterns. T.Rex contains a growing set of deep analytical tools and supports robust export capabilities that selected data can be incorporated into to other specialized tools for further analysis. T.Rex is flexible in ingesting different types and formats of data, allowing the user to interactively experiment and perform trial and error guesses on the structure of the data; and also has a variety of linked visual analytic tools that enable exploration of the data to find relevant content, relationships among content, trends within the content, and capture knowledge about the content. Finally, T.Rex has a rich export capability, to extract relevant subsets of a larger data source, to further analyze their data in other analytic tools.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "T.Rex", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "CB-EMS is the latest implementation of DSOM (Decision Support for Operations and Maintenance), which was previously patented by PNNL. CB-EMS WAS specifically designed for contingency bases for the US Army. It is a software package that is designed to monitor energy consumption at an Army contingency base to alert the camp manager when the systems are wasting energy. It's main feature that separates it from DSOM is it's ability to add systems using a plug and play menu system.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Contingency Base Energy Management System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The Sensor Fish collects information that can be used to evaluate conditions encountered by juvenile salmonids and other fish as they pass through hydroelectric dams on their way to the ocean. Sensor Fish are deployed in turbines, spillways, and sluiceways and measure changes in pressure, angular rate of change, and linear acceleration during passage. The software is need to make Sensor Fish fully functional and easy to use. Sensor Fish Communicator (SFC) links to Sensor Fish, allowing users to control data collection settings and download data. It may also be used to convert native raw data (.raw2) files into Comma Separated Variable (.csv) files and plot the results. The multiple capabilities of the SFC allow hardware communication, data conversion, and data plotting with one application.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "c++" + ], + "name": "Sensor Fish Communicator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The algorithm develops a single health score for office computers, today just Windows, but we plan to extend this to Apple computers. The score is derived from various parameters, including: CPU Utilization; Memory Utilization; Various Error logs; Disk Problems; and Disk write queue length. It then uses a weighting scheme to balance these parameters and provide an overall health score. By using these parameters, we are not just assessing the theoretical performance of the components of the computer, rather we are using actual performance metrics that are selected to be a more realistic representation of the experience of the person using the computer. This includes compensating for the nature of their use. If there are two identical computers and the user of one places heavy demands on their computer compared with the user of the second computer, the former will have a lower health score. This allows us to provide a 'fit for purpose' score tailored to the assigned user. This is very helpful data to inform the mangers when individual computers need to be replaced. Additionally it provides specific information that can facilitate the fixing of the computer, to extend it's useful lifetime. This presents direct financial savings, time savings for users transferring from one computer to the next, and better environmental stewardship.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Multiple" + ], + "name": "Computer Health Score", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The embodiment of this work is a table top game to explore cyber security and network defense concepts and cost. The game structure is such that it provides players an immersive environment to play a given role in cyber security to investigate the result of infrastructure and response decisions.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "The Defender's Role in Cyber Security", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The Xenon International Automated Control software monitors, displays status, and allows for manual operator control as well as fully automatic control of multiple commercial and PNNL designed hardware components to generate and transmit atmospheric radioxenon concentration measurements every six hours.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "gcc-c++" + ], + "name": "Xenon International Automated Control", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Representation learning is a deep-learning based technique for extracting features from data for the purpose of machine learning. This requires a large amount of data, on order tens of thousands to millions of samples, to properly teach the deep neural network. This a system for continuous representation learning, where the system may be improved with a small number of additional samples (order 10-100). The unique characteristics of this invention include a human-computer feedback component, where assess the quality of the current representation and then provides a better representation to the system. The system then mixes the new data with old training examples to avoid overfitting and improve overall performance of the system. The model can be exported and shared with other users, and it may be applied to additional images the system hasn't seen before.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "multi" + ], + "name": "Continous Representation Learning via User Feedback", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The ECE application forecasts annual costs of preventive and corrective maintenance for budgeting purposes. Features within the application enable the user to change the specifications of the model to customize your forecast to best fit their needs and support \u201cwhat if\u201d analysis. Based on the user's selections, the ECE model forecasts annual maintenance costs. Preventive maintenance costs include the cost of labor to perform preventive maintenance activities at the specific frequency and labor rate. Corrective maintenance costs include the cost of labor and the cost of replacement parts. The application presents forecasted maintenance costs for the next five years in two tables: costs by year and costs by site.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++, other" + ], + "name": "Equipment Cost Estimator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "A robust three-dimensional solver was needed to accurately and efficiently estimate the time sequence of locations of fish tagged with acoustic transmitters and vocalizing marine mammals to describe in sufficient detail the information needed to assess the function of dam-passage design alternatives and support Marine Renewable Energy. An approximate maximum likelihood solver was developed using measurements of time difference of arrival from all hydrophones in receiving arrays on which a transmission was detected. Field experiments demonstrated that the developed solver performed significantly better in tracking efficiency and accuracy than other solvers described in the literature.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "A 3D approximate maximum likelihood localization solver", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "If transmission path ratings are determined in real time and optimized control methods can be implemented, congestion problems can be more effectively managed using the existing transmission assets, reducing congestion costs, avoiding capital expenditures for new physical assets, increasing revenues from the existing system, and maintaining reliability. In just one illustrative case, a BPA study has shown that a 1000-MW rating increase for a transmission path generates $15M in annual revenue, even if only 25% of the increased margin can be tapped for just 25% of the year.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "multi" + ], + "name": "A real-time path rating calculation tool powered by HPC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The Retrocommissioning Sensor Suitcase is targeted for use in small commercial buildings of less than 50,000 square feet of floor space that regularly receive basic services such as maintenance and repair, but don't have in-house energy management staff or buildings experts. The Suitcase is designed to be easy-to-use by building maintenance staff, or other professionals such as telecom and alarm technicians. The software in the hand-held is designed to guide the staff to input the building and system information, deploy the sensors in proper location, configure the sensor hardware, and start the data collection.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "MS" + ], + "name": "Sensor Suitcase Tablet Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "This software is a set of analytical tools to evaluate the physical and biological performance of existing, refurbished, or newly installed conventional hydro-turbines nationwide where fish passage is a regulatory concern. The current version is based on information collected by the Sensor Fish. Future version will include other technologies. The tool set includes data acquisition, data processing, and biological response tools with applications to various turbine designs and other passage alternatives. The associated database is centralized, and can be accessed remotely. We have demonstrated its use for various applications including both turbines and spillways.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "MS" + ], + "name": "Hydropower Biological Evaluation Tools", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Incorporation of real-time component information using equipment condition assessment (ECA) through the development of enhanced risk monitors (ERM) for active components in advanced reactor (AR) and advanced small modular reactor (SMR) designs. We incorporate time-dependent failure probabilities from prognostic health management (PHM) systems to dynamically update the risk metric of interest. This information is used to augment data used for supervisory control and plant-wide coordination of multiple modules by providing the incremental risk incurred due to aging and demands placed on components that support mission requirements.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "MS" + ], + "name": "Methodology for Risk-informed O&M decision making in power plants", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Developed for the Midcontinent Independent System Operator, Inc. (MISO), HIPPO-Unit Commitment Version 1 is for solving security constrained unit commitment problem. The model was developed to solve MISO's cases. This version of codes includes I/O module to read in MISO's csv files, modules to create a state-based mixed integer programming formulation for solving MIP, and modules to test basic procedures to solve MIP via HPC.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Python 2.7.7" + ], + "name": "HIPPO Unit Commitment Version 1", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "CyPSA seeks to organize and gain insight into the diverse sets of data that a critical infrastructure provider must manage. Specifically CyPSA inventories, manages, and analyzes assets and relations among those assets. A variety of interfaces are provided. CyPSA inventories assets (both cyber and physical). This may include the cataloging of assets through a common interface. Data sources used to generate a catalogue of assets include PowerWorld, NPView, NMap Scans, and device configurations. Depending upon the role of the person using the tool the types of assets accessed as well as the data sources through which asset information is accessed may vary. CyPSA allows practitioners to catalogue relations among assets and these may either be manually or programmatically generated. For example, some common relations among assets include the following: Topological Network Data: Which devices and assets are connected and how? Data sources for this kind of information include NMap scans, NPView topologies (via Firewall rule analysis). Security Metrics Outputs: The output of various security metrics such as overall exposure. Configure Assets:CyPSA may eventually include the ability to configure assets including relays and switches. For example, a system administrator would be able to configure and alter the state of a relay via the CyPSA interface. Annotate Assets: CyPSA also allows practitioners to manually and programmatically annotate assets. Sources of information with which to annotate assets include provenance metadata regarding the data source from which the asset was loaded, vulnerability information from vulnerability databases, configuration information, and the output of an analysis in general.", + "laborHours": 0.0, + "languages": [ + "Java, Python" + ], + "name": "Cyber-Physical Security Assessment (CyPSA) Toolset", + "organization": "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/bigezy/Armadillo/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bigezy/Armadillo", + "status": "Production", + "tags": [ + "DOE CODE", + "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Software that runs on smartphones and desktop web browsers and notifies border officials of radiation alarms. It displays images and data associated with an alarm and provides a variety of reports. DOE had a need for discrete notification. 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The authors\u2019 best performance from 10-fold cross-validation was an f1 score of 0.85 using a J48 classifier on a balanced dataset of deleted and non-deleted tweets.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 684.0, + "languages": [ + "Multiple possible" + ], + "name": "Methods for Determining Likelihood of Tweet Deletion", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "This is a MATLAB-based tool to post process simulation results in the EPRI software TRANSCARE, for massive cascading failure analysis following severe disturbances. There are a few key modules available in this tool, including: 1. automatically creating a contingency list to run TRANSCARE simulations, including substation outages above a certain kV threshold, N-k (1, 2 or 3) generator outages and branch outages; 2. read in and analyze a CKO file of PCG definition, an initiating event list, and a CDN file; 3. post process all the simulation results saved in a CDN file and perform critical event corridor analysis; 4. provide a summary of TRANSCARE simulations; 5. Identify the most frequently occurring event corridors in the system; and 6. Rank the contingencies using a user defined security index to quantify consequences in terms of total load loss, total number of cascades, etc.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab" + ], + "name": "A cascading failure analysis tool for post processing TRANSCARE simulations", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "GCA is a visual analytic tool for power grid contingency analysis to provide more decision support for power grid operations. 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The data can be either manual retrieved by this software or the data historian source can push to a listening endpoint provided by this software.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deep Lynx Data Historian", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-Data-Historian", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-26", + "metadataLastUpdated": "2022-07-26" + }, + "description": "Code to perform scattering calculations between GPT and Geant4.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/lume-scatter", + "organization": "SLAC National Accelerator 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Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "This is a PAM module that lets you log in via SSH to servers using OpenID Connect credentials, instead of SSH Keys or a username and password combination. It uses the OAuth2 Device Flow, which means that during the login process, you will click a link and log in to your OpenID Connect Provider, which will then authenticate you for the SSH session. This module will then check if you're in the right group(s) or have a specified username, and allow or deny access.", + "laborHours": 0.0, + "languages": [], + "name": "PAM module for OAuth 2.0 Device flow", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pam_oauth2_device", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "Tools for running elegant.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/lume-elegant", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/lume-elegant", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "This is the original code for the SMuRF cryostat board. The board is bases on the microchip's microcontroller PIC32MX795F512L. The code was developed using Microchip's MPLAB X and the MPLAB Harmony Configuration (MHC) framework.", + "laborHours": 0.0, + "languages": [], + "name": "SMuRF Cryostat board PIC code", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/smurfc/blob/C04/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/smurfc", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "Basic kubeadm installation", + "laborHours": 0.0, + "languages": [], + "name": "ansible-role-kubeadm", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ansible-role-kubeadm", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "A simple application that exposes a MongoDB instance as a read only REST service.", + "laborHours": 0.0, + "languages": [], + "name": "psdm_mongo_ws", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/psdm_mongo_ws", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "Rucio is a software framework that provides functionality to organize, manage, and access large volumes of scientific data using customisable policies. The data can be spread across globally distributed locations and across heterogeneous data centers, uniting different storage and network technologies as a single federated entity. Rucio offers advanced features such as distributed data recovery or adaptive replication, and is highly scalable, modular, and extensible. Rucio has been originally developed to meet the requirements of the high-energy physics experiment ATLAS, and is continuously extended to support LHC experiments and other diverse scientific communities.", + "laborHours": 0.0, + "languages": [], + "name": "Rucio - Scientific Data Management", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/rucio", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "UC Santa Cruz Head and Neck.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/ucsc-hn", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/ucsc-hn/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ucsc-hn", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "This Ansible role allows you to install chrony and manage its configuration.", + "laborHours": 0.0, + "languages": [], + "name": "Ansible Role: chrony", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ansible-role-chrony", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "Gafaelfawr is a FastAPI application for the authorization and management of tokens, including their issuance and revocation.", + "laborHours": 0.0, + "languages": [], + "name": "Gafaelfawr", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/gafaelfawr", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This invention is a Ruby \"gem\" (library) that provides clients for ENERGY STAR Portfolio Manager (ESPM) Web Services,\nInventive features:\n100% coverage of version 18.0 of the ESPM API.\nAutomated mapping between ESPM XML schemas and Ruby objects.\nClients for both the \"live\" and \"test\" ESPM API environments.\nDebugging mode with HTTP request/response logging.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/portfoliomanager-rb", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/portfoliomanager-rb", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Simple Building Calculator is a web application that estimates annual energy\nuse using regression models that have been fit to simulation results for the DOE\nCommercial Prototype Building Models. The tool is a single-page application that\nwill allow a user to rapidly analyze the impact of energy efficiency measures and\ndesign options on building performance. As it uses linear regression models rather\nthan more complicated machine learning models or physics based simulation, the\ntool can deploy easily and run client-side.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/simple-building-calculator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/simple-building-calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Performance curve generator for building energy simulation. Copper is a tool in the form of Python package that can be used to generate metric specific performance curves for\nbuilding energy simulations.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/copper", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/copper", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "This is a standalone Fortran code (mie_scat) that calculates the mie scattering cross sections, absorption cross sections, and efficiency coefficients of dust grains. It includes a separate file (miegrn) that functions as a wrapper function between PHOENIX (a proprietary radiative transfer code to model stellar atmospheres) and the mie scattering calculations. Miegrn works to determine the input parameters for mie_scat and then feeds the resultant data back into PHOENIX.", + "laborHours": 0.0, + "languages": [], + "name": "mie_scat", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/mie_scat", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "Computes the atomic positions in cleaved crystal lattices. The current version of the code allows to cleave the lattices with different planes that are readily available. The cleavages can be performed on any type of lattices. The code constructs a slab that can be used to study surface properties.", + "laborHours": 0.0, + "languages": [], + "name": "LANL Crystal Cut (LCC)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/LCC", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "Protective vaccines and reliable diagnostics are essential tools for controlling viral diseases. However, the efficacy of these tools can be diminished by mutations in viral genomes. The delay between the emergence of new viral strains and the redesign of vaccines and diagnostics allows for continued viral transmission. Is it possible to address this challenge by computationally predicting viral genome sequence evolution? Can we \u201cfuture-proof\u201d vaccines and diagnostics by targeting both current and anticipated future sequence variants? While predicting viral evolution is still an unsolved, \u201cgrand challenge\u201d problem in biology, the large, and rapidly growing, number of SARS-CoV-2 genome sequences provide an opportunity to quantify the ability of machine learning to predict viral genome sequence evolution. Towards this end, we have developed a simple computational model for predicting viral evolution at the level of individual nucleotides. The key metric for quantifying the per-base, prediction accuracy for viral evolution is the Mann-Whitney U statistic (or, equivalently, the area under the receiver operator curve). Since the Mann-Whitney U statistic is not a differentiable function, existing deep leaning packages (like Pytorch and Keras/TensorFlow) are not useful, as they require that the accuracy metric/objective function be analytically differentiable with respect to the model parameters. To overcome this challenge, we have implemented custom software, \u201cFutureTense\u201d, that can train a machine learning model by maximizing the non-differentiable Mann-Whitney U statistic. This software trains a machine learning model by exploring along the direction of the discrete gradient of the Mann-Whitney U statistic in the model parameter space. Parallel computing and genome sequence-specific optimizations are used to accelerate model training. The resulting machine learning model learns the observed high C->U mutation rates in the SARS-CoV-2 genome (which are potentially induced by host defenses) and provides prediction accuracies that are significantly better than one would expect from random chance. While predicting viral evolution is still quite far from a solved problem, the surprising performance of this simple model gives hope that the accuracy of predicting viral genome evolution can be further increased by more sophisticated approaches.", + "laborHours": 0.0, + "languages": [], + "name": "FutureTense", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/FutureTense", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "Carbon fluxes in terrestrial ecosystems and their response to environmental change are a major source of uncertainty in the modern carbon cycle. The National Ecological Observatory Network (NEON) presents the opportunity to merge eddy covariance (EC)-derived fluxes with CO2 isotope ratio measurements to gain insights into carbon cycle processes. Collected continuously and consistently across >40 sites, NEON EC and isotope data facilitate novel integrative analyses. However, currently provisioned atmospheric isotope data are uncalibrated, greatly limiting ability to perform cross-site analyses. Here, we present two approaches to calibrating NEON CO2 isotope ratios, along with an R package to calibrate NEON data. We find that calibrating CO2 isotopologues independently yields a lower d13C bias (<0.05\u2030) and higher precision (<0.40\u2030) than directly correcting d13C with linear regression (bias: <0.11\u2030, precision: 0.42\u2030), but with slightly higher error and lower precision in calibrated CO2 mole fraction. The magnitude of the corrections to d13C and CO2 mole fractions vary substantially by site, underscoring the need for users to apply a consistent calibration framework to data in the NEON archive. Post-calibration data sets show that site mean annual d13C correlates negatively with precipitation, temperature, and aridity, but positively with elevation. Forested and agricultural ecosystems exhibit larger gradients in CO2 and d13C than other sites, particularly during the summer and at night. The overview and analysis tools developed here will facilitate cross-site analysis using NEON data, provide a model for other continental-scale observational networks, and enable new advances leveraging the isotope ratios of specific carbon fluxes.", + "laborHours": 0.0, + "languages": [], + "name": "NEONiso R Package, versions greater than 0.5.2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/NEONiso", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "WORM (Write One, Run Many) is an easy to use, cross platform, embedded and extensible, functional programming language designed to facilitate the creation of input-decks for computer codes that use standard ASCII text files for input. WORM makes it easy to create generic (yet, complex and powerful) reusable models. Additionally its nature allows for complex calculations and routines to be coded once and easily reused, further simplifying the creation of input decks. WORM (Write One, Run Many) is a powerful and versatile tool designed to improve the efficiency of today\u2019s criticality safety analyst by allowing: + input decks for parametric studies to be created quickly and easily, + calculations and variables to be imbedded into any input deck, thus allowing for meaningful parameter specifications, + problems to be specified using any combination of units, and + complex mathematically defined models to be created. A very simple syntax is employed, and therefore the WORM is easy to learn. A WORM model is essentially a standard input deck with some of its numerical values replaced by WORM code. WORM code may include and evaluate the following mathematical operators and functions: addition, subtraction, multiplication, division, exponentiation, modulus, sine, cosine, tangent, arcsine, arccosine, arctangent, the natural logarithm, logarithm base 10, integer truncation, absolute value, and random number. Several common constants, e.g., pi, e, and Avogadros\u2019s Number (both as 6.022e23 and 0.6022), are predefined in WORM. Additionally, many unit conversion factors are also predefined: millimeters, meters, inches, feet, yards, and mils to centimeters; kilograms, pounds, and ounces to grams; liters, milliliters, gallons, and fluid ounces to cubic centimeters; and angular degrees to radians. For parametric studies, WORM supports various shorthand list specifications: the explicit step size, linear interpolation, and logarithmic interpolation. The list notation sequentially assigns multiple values to a name. WORM creates an input deck for each value of the name. If multiple lists are used, WORM steps through each list individually, i.e., WORM creates input decks corresponding to each and every permutation of the list values. Additionally, a library of standard material definitions and Perl subroutines are included. Any one of these files can be incorporated into the subject model with a simple WORM read command. WORM is completely written in Perl, the Practical Extraction and Reporting Language. Perl is one of the most portable programming languages available today. As such, the WORM works on practically any computer platform.", + "laborHours": 0.0, + "languages": [], + "name": "WORM (Write One, Read Many)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rsartor-lanl/worm-1.7.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "The Department of Energy and the National Cancer Institute have developed new software for conducting multi-scale simulations of complex systems. This software, called the Multiscale Machine-Learned Modeling Infrastructure (MuMMI), couples simulations on three spatial scales to study slow, large-scale reorganizations of biomolecular systems with the speed of continuum and coarse-grained models while revealing selected interactions at full atomic precision. In these simulations, coarse-to-fine model conversions are used to spawn relevant fine-scale simulations along chosen order parameters, and fine-to-coarse feedback is used to iteratively improve the accuracy and multi-scale consistency of coarse-scale and continuum simulations. The complete MuMMI framework will be reviewed and released as open-source software by Lawrence Livermore National Laboratory. This review covers a subset of the MuMMI components that were developed exclusively at the Los Alamos National Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "components for the MuMMI software release", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cneale-LANL/MuMMI-C21095", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "New diagnostics to obtain high-temporal resolution observation of surface velocity provide a rich collection of data from high-explosive (HE) experiments. Using this data to estimate the temporal evolution of an imploding, HE-driven surface is of great interest for validating simulation of the physical system and for design of future experiments. This is the code for a paper in which we propose a method for using a Gaussian process to estimate the surface position over time and provide uncertainty estimates on that reconstruction accounting for measurement error, uncertainty to sparse spatial sampling velocity data, and robustness to outlying observations. In the paper, the code is applied on data from a hemispherical HE implosion experiment. This code is for release with the paper for peer-review, replicating the results and making the figures from the paper.", + "laborHours": 0.0, + "languages": [], + "name": "Code for paper \"Reconstructing an Implosion with Space-Time Smoothing of Velocimetry Traces\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PDV_Reconstruction", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "The BPP package contains R code to perform Bayesian projection pursuit regression under various regression settings. Bayesian projection pursuit regression learns the functional relationship between inputs and outputs by considering a sum of functions of one dimensional projections of the inputs. This is useful as a general machine learning software.", + "laborHours": 0.0, + "languages": [], + "name": "BPP R package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gqcollins/BayesPPR", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dixitmb@ornl.gov" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2022-08-02" + }, + "description": "SolidPAC: Solid-State Battery Performance Analyzer and Calculator SolidPAC is an interactive experimental toolkit developed at Oak Ridge National Laboratory to enable the design of a solid-state battery for user-specified application requirements. The toolkit is flexible enough to assist the battery community in quantifying the impact of materials chemistry and fractions, electrode thicknesses and loadings, and electron flows on cell energy density and cost, and to be able to utilize inverse engineering concepts to correlate cell energy density output to materials and cell design inputs. The toolkit allows users to assess and extrapolate the impact of battery design and choice of cell components on cell-level energy density of a solid-state battery. SolidPAC brings practicality to the design of solid-state batteries.", + "homepageURL": "https://www.ornl.gov/content/solidpac", + "laborHours": 0.0, + "languages": [ + "LabVIEW" + ], + "name": "SolidPAC", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.ornl.gov/content/solidpac", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SAND2020-14229 O This software builds on an open source Kinetic Monte Carlo library to evaluate the incorporation rate of semiconductor dopant atoms in an Atomic Precision Advanced Manufacturing (APAM) process. 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For details on the approach please see our paper, and when referencing this code please cite our paper: Bridges, Robert A., Sean Oesch, Miki E. Verma, Michael D. Iannacone, Kelly MT Huffer, Brian Jewell, Jeff A. Nichols et al. \"Beyond the Hype: A Real-World Evaluation of the Impact and Cost of Machine Learning-Based Malware Detection.\" arXiv preprint arXiv:2012.09214 (2022). @misc{bridges2022beyond, doi = {10.48550/ARXIV.2012.09214}, url = {https://arxiv.org/abs/2012.09214}, author = {Bridges, Robert A. and Oesch, Sean and Verma, Miki E. and Iannacone, Michael D. and Huffer, Kelly M. T. and Jewell, Brian and Nichols, Jeff A. and Weber, Brian and Beaver, Justin M. and Smith, Jared M. and Scofield, Daniel and Miles, Craig and Plummer, Thomas and Daniell, Mark and Tall, Anne M.}, title = {Beyond the Hype: A Real-World Evaluation of the Impact and Cost of Machine Learning-Based Malware Detection}, publisher = {arXiv}, year = {2022}, } Repository contents: readme.md fake-data-table.csv This is a table of simulated data from two malware detectors, with randomly generated results suitable for running the cost model code as an example. config.py - provides global variables with input parameters needed for the cost model. model.py - provides the functions needed to run the cost model with examples on the fake data and three simulated detectors. Includes the complementary cost model--computes savings/costs of adding a network detector to a host detector. make_plots.py - shows example plots varying parameters. plots/ # contents populated by ./code/make_plots.py", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Beyond The Hype paper code", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bridgesra/beyond-the-hype-paper-code/releases/tag/tag", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "pi" + }, + { + "contact": { + "email": "bridgesra@ornl.gov" + }, + "date": { + "created": "2022-08-22", + "metadataLastUpdated": "2022-08-23" + }, + "description": "Contains anonymized and obfuscated data from the SOAR (AI ATAC 3) user study and code to produce correlation plots. The experiment, data, and our results are found in our paper https://arxiv.org/abs/2208.06075. Please cite our paper when using this data or code. @article{bridges2022testing, title={Testing SOAR Tools in Use}, author={Bridges, Robert A and Rice, Ashley E and Oesch, Sean and Nichols, Jeff A and Watson, Cory and Spakes, Kevin and Norem, Savannah and Huettel, Mike and Jewell, Brian and Weber, Brian and others}, journal={arXiv preprint arXiv:2208.06075}, year={2022} } file: anonymized_obfuscated_data.csv The data in this table is not the \"raw\" data. It has been user- and SOAR-tool anonymized; SOAR tool names have been removed, as have participant user ids. Probabilistic techniques to obfuscate the data by adding noise while retaining its characteristics have been performed. To ensure utility of the anonymized data, we provide code to reproduce the Subcategory Average Correlation heatmap, found in the publication. While the SOAR tool names have been removed, a binary indicator for if the test data per row is from a SOAR tool or from a baseline environment (full SOC tool suite but no SOAR tool). The likert columns correspond to questions posed to the users (participants) during and after working investigations with a SOAR tool or in a baseline environment (full SOC tool stack but with no SOAR tool). Sentiment columns correspond to answers given by analysts to free response questions. Transcriptions of their responses are quantified with sentiment analysis. The ticket columns report quality and completion of tickets from the test investigations based on percent of correctness according to a gold standard (rubric). The window swapping and time columns report the number of times the participant changed windows in an investigation (quantifying context switching), and the duration of the investigation (quantifying efficiency), respectively. User identification information has been removed. There are four columns of user/participant demographics documenting their familiarity with SOAR tools, job role (SOC analyst or other), number of years working in their security-related job role, and the number of different security operation centers (SOCs) they have supported. These have all been converted to binary variables. 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This software can be applied to non-reacting solids dominant flows in silos, hoppers and screw conveyors as well as in high temperature reacting systems such as screw kilns and auger reactors.", + "laborHours": 0.0, + "languages": [ + "C++", + "C", + "Python" + ], + "name": "BDEM (Discrete-element-simulator for high-solids granular flows) [SWR-22-72]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BDEM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-08-24", + "metadataLastUpdated": "2023-04-24" + }, + "description": "The well-known Fresnel equations solve for the reflection and transmission of light for precise incident angles. 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Ocelot is written in Python. 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PyTREES is designed to input LIBS data in the format provided by the ChemCam team [1]. PyTREES then applies appropriate pre-processing to this data [2], and implements several regression methods for predicting oxides from spectra. The regression methods include: ensemble methods (random forest, extra trees, and gradient boosting regression) and blended submodels using the \u201cdouble blending\u201d technique. PyTREES additionally implements methods for quantifying the importance of features in regression model: (1) mean decrease in impurity (MDI) and (2) permutation importance to investigate the wavelengths used by the regression methods. [1] Gasda et al. (2021). Spectrochim Acta B, 181, 106223. [2] Clegg et al. (2017). Spectrochim Acta B , 129, 64\u201385.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "PyTREES", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-09-15", + "metadataLastUpdated": "2022-09-19" + }, + "description": "VelocityGAN is a software to solve subsurface imaging problems. 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It implements an efficient data processing conveyor allowing to overlap all data transfers with computations. First, independent Python threads are started for reading data chunks from the hard disk into a Python data queue and for writing reconstructed chunks from the Python queue to the hard disk. Second, CPU-GPU data transfers are overlapped with GPU computations by using CUDA streams.", + "laborHours": 0.0, + "languages": [], + "name": "TOMOCUPY", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tomography/tomocupy", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-09-19", + "metadataLastUpdated": "2023-04-24" + }, + "description": "CYMEpy is a high-level Python package that provides users HELICS bindings for CYMEDIST, CYME\u2019s distribution system simulator.", + "laborHours": 0.0, + "languages": [], + "name": "CyMEpy [SWR-21-20]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GMLC-TDC/cymepy", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-09-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Software that delivers optimal design parameters and performance predictions for cylindrical cells, which can range in size from microbatteries to EV batteries, is developed. The software utilizes machine learning and includes a graphical user interface to enable rapid prototyping and to accelerate energy storage research, development, and manufacturing. The Cylindrical battery design V1.0 comprises of three types of cylindrical batteries, Microbattery (Primary), Microbattery (Secondary) and 18650/21700/xxxxx Cylindrical battery. The software was developed in MATLAB. The software has the capability to output the cell design with the capacity ranges from several mAh to several million Ah.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Cylindrical battery design app", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-10-06" + }, + "description": "A model structure to support representation of power system dispatching for optimal power flow that includes bid-in demands for load. Used to support the ARPA-E GO-3 competition.", + "laborHours": 0.0, + "languages": [ + "Python", + "TeX" + ], + "name": "Bid-DS-data-model (Demand Side Bidding Data Model) [SWR-22-80]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Smart-DS/Bid-DS-data-model", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.0.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "The consolidated code is deployed in an embedded GPU System (Jetson AGX Xavier Developer Kit), performs inference on the pVA stream sent from the X-ray detector. The inferred output is sent back to the local detector machine as a PVA stream and can be viewed in an ImageJ viewer.", + "laborHours": 0.0, + "languages": [], + "name": "REAL-TIME EDGE INFERENCE FOR PTYCHOGRAPHIC NANOSCALE XRAY IMAGING", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/vbanakha/edgePtychoNN", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "Argonne National Laboratory has worked on electrochemical energy storage for several decades. The focus on lithium-ion chemistries started in the early 1990s, developing new materials, synthesis methods, and performance characterizations. Sponsored by the U.S. Department of Energy, Energy Efficiency and Renewable Energy, Vehicle Technologies Office (DOE-EERE-VTO), Argonne has led with many advances. The experimental activities were complemented with multi-scale modeling that ranged from the atomic to the system (manufacturing processes and automobiles) level. The Battery Performance and Cost (BatPaC) model is a calculation method based on Microsoft\u00bf Office Excel spreadsheets that have been developed at Argonne for estimating the performance and manufacturing cost of lithium-ion batteries for electric-drive vehicles including hybrid-electrics (HEV), plug-in hybrids (PHEV) and pure electrics. The effort is being funded by the Vehicle Technology Office (VTO), which is part of the Energy Efficiency and Renewable Energy (EERE) office of the U.S. Department of Energy (USDOE). BatPaC was first developed in 2007, was subsequently peer-reviewed, and it has served Argonne researchers and the greater battery community in studying the impact of material properties on performance at the pack level. With further developments, the model now allows the design of cells and battery packs for automotive applications, to meet performance requirements (power, energy, recharge time), and estimates the cost of manufacturing the designed batteries. Since the cost depends on the materials he design, and the manufacturing process, this bottom-up model/tool enables the user to study their effects. Designed or the lithium-ion cell and battery researcher, BatPaC helps answer many questions by being 1.Transparent in the assumptions made and the method of calculation 2.Capable of designing a battery specifically for the requirements of an application 3.Constrained by the physical limitations that govern battery performance 4. A bottom-up calculation approach to account for every cost factors. BatPaC predicts the impact of promising materials (and their properties) on the performance metrics relevant for the different applications. Researchers can use the specific capacities and the half-cell voltages of a particular set of electrode materials to calculate the mass and volume of a cell to develop a model incorporating the properties of all the other materials in the cell and the design of the cell enclosure. These calculations not only reveal the impact of an improved material but also enable researchers to calculate the material properties that would be needed to meet the performance criteria of a full battery pack. With this information, researchers can provide he battery industry with realistic expectations that will help it more successfully advance novel battery technologies an Applications.", + "homepageURL": "https://www.anl.gov/cse/batpac-model-software", + "laborHours": 0.0, + "languages": [], + "name": "BATPAC--VERSION 5.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/cse/batpac-model-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2023-03-15" + }, + "description": "A-LEAF is an electricity market simulation framework. It includes models for short-term market operations and long-term investment planning of generation, storage, and transmission. Model formulations include least cost and two-stage market equilibrium. Simulations can be flexibly structured over one or more years, including options for periodic samples or jumping to a single future year. Years can be simulated as 365 consecutive days at hourly or 5-minute sample rates, or they can be subsampled using a representative day group selection algorithm.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "A-LEAF", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "pycreep is a Python software package for modeling and correlating time-dependent material data like the results of creep rupture and creep deformation tests. The package provides a means to generate models for these test data which can be used to determine design material properties, like those used in the ASME Boiler and Pressure Vessel Code.", + "laborHours": 0.0, + "languages": [], + "name": "PYCREEP", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/pycreep", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "The \"X-RAY DETECTOR GAIN MAP CALCULATION\" was developed by Argonne National Laboratory.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "X-RAY DETECTOR GAIN MAP CALCULATION", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "This software organizes the collection of information necessary to evaluate heat stress and compare it to the exposure limits of the American Conference of Industrial Hygienists.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "HEAT STRESS TIME WEIGHTED AVERAGE CALCULATOR", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-23" + }, + "description": "BatchScan provides an interactive graphical user interface (GUI) that allows visualization of X-ray microscopic data,\nselection of scan coordinates, and execution of desired scan coordinates in a single software package. In addition to the\nthree primary functionalities, BatchScan also maintains an active list of scans that users inserted and updates lifetime\nfeedback on scan status.\n", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "BATCHSCAN", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-23" + }, + "description": "A suite of tools for efficient maximum likelihood optimization of parametric Gaussian process models", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "gpmaxlik.jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "This is a prototype framework initially developed as part of an international consortium (aica-iwg.org/) for NATO ACT in 2021 under an LGPL license (Blakely/ANL did 100% of the coding). It is intended to serve as a reference model and collaborative project for researchers interested in working on self-defending software agents. It consists of a set of Docker containers that allow simulation of a network environment, including a manager agent that has capabilities for observing network activities, using automated decision making to select appropriate defensive/proactive actions, and putting those actions into practice. It is currently at an \"MVP\" level but we are continuing to add to this and have submitted a DHS S&T CAP proposal to build an open source community around it.", + "laborHours": 0.0, + "languages": [], + "name": "AUTONOMOUS INTELLIGENCE CYBERDEFENSE AGENT (AICA)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aica-iwg/aica-agent", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2023-03-16" + }, + "description": "A generic simulation tool for power grid and general dynamic systems based on semi-analytical solutions (SAS) technology.", + "laborHours": 0.0, + "languages": [], + "name": "Generic Semi-Analytical Simulation Tool (GenSAS)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-CEEESA/gensas", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2023-03-14" + }, + "description": "ParMOO is a Python library for solving multiobjective simulation optimization problems, while exploiting problem structure. ParMOO stands for \"parallel multiobjective optimization\".", + "laborHours": 0.0, + "languages": [], + "name": "PARMOO", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/parmoo/parmoo", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "This program was developed to calculate rovibrational levels by solving n-dimensional potentials. The program is capable of generating the necessary grid and, once the potential energy for those coordinates has been calculated, solving it for the given dimensionality. The potential is solved using the universal Discrete Variable Representation (DVR) originally developed by Colbert and Miller [Colbert1992]. While the implementation can entertain both aperiodic and periodic potentials, the intrinsic target are soft and large-amplitude motions of non-rigid molecules. For the present purpose, non-rigid molecules are defined as those with at least one internal coordinate that undergoes a large amplitude motion [Bunker1998]. The potentials of these vibrational motions are poorly approximated with harmonic oscillators. The current implementation is in practice limited to solving 1 and 2 dimensional potentials due to the strongly scaling cost of these methods with increased dimensionality. [Colbert1992] Colbert, D. T.; Miller, W. H. A Novel Discrete Variable Representation for Quantum-Mechanical Reactive Scattering via the S-Matrix Kohn Method. J. Chem. Phys. 1992, 96, 1982\u00bf1991. http://doi.org/10.1063/1.462100 [Bunker1998] Bunker, P. R.; Jensen P. Molecular Symmetry and Spectroscopy, 2nd ed.; NRC Research Press: Ottawa 1998. .. [Colbert1992] Colbert, D. T.; Miller, W. H. A Novel Discrete Variable Representation for Quantum-Mechanical Reactive Scattering via the S-Matrix Kohn Method. J. Chem. Phys. 1992, 96, 1982\u00bf1991. http://doi.org/10.1063/1.462100 .. [Bunker] Bunker, P. R.; Jensen P. Molecular Symmetry and Spectroscopy, 2nd ed.; NRC Research Press: Ottawa 1998.", + "laborHours": 0.0, + "languages": [], + "name": "CM-DVR", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Dbross/CM_DVR", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-24", + "metadataLastUpdated": "2022-09-24" + }, + "description": "The bittree is a memory efficient data structure for storing the entire structure of an octree AMR \nmesh. It also yields an efficient algorithm for mapping from a block's coordinates in the domain to \nits index along the space filling Morton curve.\n\n", + "laborHours": 0.0, + "languages": [], + "name": "BITTREE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Flash-X/Bittree", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-24", + "metadataLastUpdated": "2022-09-27" + }, + "description": "Achieving the U.S. government's target of net-zero greenhouse gas (GHG) emissions by 2050 will require technological transformations and energy sector migration towards low-carbon or carbon-negative options. 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A reference scenario is developed using Energy Information Administration (EIA AEO) projection of economic activities for 2020-2050, GHG emissions data from Environmental Protection Agency's (EPA) inventory of GHG sources and sinks for 2019, and emission factors from Argonne's Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model (GREET\u00ae) tool. We consider several carbon reduction approaches including replacement and scale-up of electricity generation with renewables, partial electrification of the transportation sector complimented with biofuels, improvements in building energy efficiency, replacement of natural gas with renewable hydrogen, mitigation of methane emissions from waste and natural gas, agricultural decarbonization, and carbon dioxide removal pathways. The scenario we analyze indicates the potential to achieve 80-90% decarbonization economy-wide relative to a 200X baseline.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "DECARBONIZATION SCENARIO ANALYSIS MODEL", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-25", + "metadataLastUpdated": "2022-09-27" + }, + "description": "M\u00c6STRO stands for Multi-fidelity Adaptive Ensemble Stochastic Trust Region Optimization and it is a plug n play derivate fee stochastic optimization solver. 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Then the trust region is moved and the iterations continue until a satisfactory convergence criteria is met.", + "laborHours": 0.0, + "languages": [], + "name": "maestro", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HEPonHPC/maestro", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-09-26", + "metadataLastUpdated": "2022-09-26" + }, + "description": "The Assured Timing Detector Status Display allows for Web browser hosted monitoring of system health and annunciation of timing anomaly alerts reported by the companion Assured Timing Detector software.", + "laborHours": 0.0, + "languages": [], + "name": "Assured Timing Detector - Status Display", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ATD-SD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-09-26", + "metadataLastUpdated": "2022-09-26" + }, + "description": "The Assured Timing Detector software provides an implementation in C++ of an adaptable, model-based system for monitoring a timing signal for anomalies versus a reference time source ensemble", + "laborHours": 0.0, + "languages": [], + "name": "Assured Timing Detector", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ATD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "shiversrm@ornl.gov" + }, + "date": { + "created": "2022-09-27", + "metadataLastUpdated": "2022-09-28" + }, + "description": "This software provides a fast way to perform efficient sparse matrix multiplication followed by top-n multiplication result selection. 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Instructions for compiling bindings which can be called from Python are included with this package as well.", + "laborHours": 0.0, + "languages": [ + "Go", + "Python" + ], + "name": "Fast Sparse-Vector Cosine Similarity in Go", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/sparse-gosine-similarity", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-09-27", + "metadataLastUpdated": "2022-11-02" + }, + "description": "The HIVE\u2122 platform is a mobility services simulation platform developed to provide insight on the energy, infrastructure, service, and economic outcomes of various mobility as a service (MaaS) options. The HIVE platform takes a set of spatiotemporal travel origin-destination pairs and simulates the operation of a predefined mobility service fleet, incorporating request pooling, and various operational and charging behaviors. Hive specializes at modeling fleets of automated electric vehicles (AEVs) and can be used to site and size direct current fast charge (DCFC) stations and measure grid impacts of large-scale AEV fleets serving real-world MaaS trip demand (similar to taxis, Uber, Lyft, etc.). Potential outcomes from a Hive simulation include level of service, total vehicle miles traveled (VMT), deadheading (zero passenger) miles, simultaneous and total energy loads, average occupancy, and more. Hive is developed to generalize to new regions and can be customized to handle many scenarios and operating conditions.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HIVE\u2122 [SWR-19-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hive", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-09-27", + "metadataLastUpdated": "2022-09-27" + }, + "description": "This code provides Finite Element solvers for Electrochemical Transport. A few examples from the literature are reproduced, with a focus on CO2 electrolysis. 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This work also includes a scalable preconditioner.", + "laborHours": 0.0, + "languages": [], + "name": "Finite Element Method for Electrochemical Transport", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/echemfem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-09-29", + "metadataLastUpdated": "2022-11-07" + }, + "description": "NOODLES is a protocol specification for collaborative visualization. It allows software tools of any type to participate in an analysis or visualization session. 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Analysis on speed, package weight, energy consumption, # of drones, and battery replacements. This software developed tools for drone deployment optimization for direct delivery by introducing a new model that presents new insights addressing real-life issues. Specifically, this developed a new mixed-integer programming model with both time windows and battery replacements.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Optimization Models For Drone Deployment", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/OMDD", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-09-30", + "metadataLastUpdated": "2022-09-30" + }, + "description": "Sandia's Dakota software supports science and engineering transformation through advanced exploration of simulations. 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Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-10468 O", + "homepageURL": "https://dakota.sandia.gov", + "laborHours": 0.0, + "languages": [ + "C++", + "C++" + ], + "name": "DAKOTA (Design Analysis Kit for Optimization and Terascale) v.6.16", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "6.16" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-09-30", + "metadataLastUpdated": "2022-09-30" + }, + "description": "HyRAM+ is a software toolkit for conducting quantitative risk assessment (QRA) and consequence modeling for hydrogen and other alternative fuels infrastructure and transportation systems. HyRAM+ contains validated, simplified release behavior models, a standardized QRA approach, and engineering models and generic data relevant to hydrogen installations. HyRAM (hydrogen-only) versions 1.0 to 3.1 were developed by Sandia for the U.S. Department of Energy (DOE) Hydrogen and Fuel Cell Technologies Office (HFTO). The U.S. DOE Vehicle Technologies Office (VTO) and U.S. Department of Transportation (DOT) Pipeline and Hazardous Material Safety Administration (PHMSA) contributed to the development of HyRAM+ version 4.0 regarding the addition of methane (natural gas) and propane models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10862 O", + "laborHours": 21508.0, + "languages": [ + "C#", + "Python" + ], + "name": "HyRAM+ (Hydrogen Plus Other Alternative Fuels Risk Assessment Models) v.4.1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hyram", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 4.1.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-09-30", + "metadataLastUpdated": "2022-09-30" + }, + "description": "Flux is a framework for writing resource managers as well as a resource manager for HPC systems. It allows for hierarchical nesting and providing a portable interface for job scheduling across systems. The flux-k8s software provides an interface between Flux and Kubernetes so the two frameworks can use each other's functionality. The code is currently licensed under the LGPL-3.0 License, but we request to re-license the code to promote outside collaboration and community adoption.", + "laborHours": 0.0, + "languages": [], + "name": "Kubernetes Bindings for the Flux Workload Manager", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/flux-framework/flux-k8s", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "weberb@ornl.gov" + }, + "date": { + "created": "2022-09-30", + "metadataLastUpdated": "2024-01-18" + }, + "description": "This framework allows experiment authors to use one local process to orchestrate many simultaneous trials of an experiment on remote resources. When several of these processes are run in parallel, it becomes possible to orchestrate thousands of remote experiment trials on an entire remote cluster using a single orchestration, or \"boss\" node.", + "laborHours": 0.0, + "languages": [], + "name": "experiment_orchestration", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/experiment_orchestration", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-09-30", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SAND2021-15136 O\nReplete is a Java library that contains several common and useful utilities in a variety of categories including expression parsing, multi-threading, data pipelines, user interface, database connectivity, Unix shell emulation, information generalization, and Maven standardization. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 138168.0, + "languages": [ + "Java" + ], + "name": "Replete v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/replete", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2022-10-05" + }, + "description": "SAND2021-13952 O Cloud Feature Tracker (CFTrack) is an application for following low-cloud motion in Geostationary Operational Environmental Satellite (GOES) R-series imagery. 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Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 486.4, + "languages": [ + "Python" + ], + "name": "PlasMod0 v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PlasMod0", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-14", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-12602 O\nBalrog uses mathematical methods to calculate spectral line shapes in high-energy-density plasmas. 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Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [], + "name": "Balrog", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/balrog", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-14", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-12903 O\nclif contains code to perform climate fingerprinting. 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Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 22161.6, + "languages": [ + "python" + ], + "name": "clif", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/clif", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-14", + "metadataLastUpdated": "2024-07-27" + }, + "description": "SAND2022-12599 O statMechCrack is a Python package providing an API to run calculations based on certain statistical mechanical models for cracks and crack growth. 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Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 11278.4, + "languages": [ + "C++", + "Groovy", + "CMake" + ], + "name": "VoroCrust-Meshing v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/vorocrust-meshing", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-14", + "metadataLastUpdated": "2022-10-14" + }, + "description": "SAND2022-12598 O\nThe Polymer Modeling Library is a software package for modeling polymer chains, networks, and materials by applying existing theories and methods. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Rust", + "Python" + ], + "name": "Polymer Modeling Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Polymers", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-14", + "metadataLastUpdated": "2022-10-14" + }, + "description": "SAND2022-13281 O\nEDAT is a suite of tools for analyzing time-dependent electron densities produced by time-dependent density functional theory (TDDFT) simulations of ion-irradiated materials and surfaces. The code\u2019s key capabilities include various routines to extract the number of electrons emitted from a surface, the energy spectrum of these emitted electrons, and the number of electrons captured by the ion. The code is written in Python and can interface with multiple TDDFT codes.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "EDAT", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-16", + "metadataLastUpdated": "2022-10-16" + }, + "description": "SAND2022-4010 O Pyomo supports the formulation and analysis of mathematical models for complex optimization applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 314837.6, + "languages": [ + "Python 2.6, 2.7, 3.4, 3.5" + ], + "name": "Pyomo v6.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pyomo/pyomo", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "6.2" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-16", + "metadataLastUpdated": "2022-10-21" + }, + "description": "SAND2022-3281 O Weak Simulation sparsifies the stabilizer decomposition of a qubit t-tensored T gate magic state to some additive error. It can accomplish this either by independent L1 sampling like in the popular SPARSIFY algorithm or with correlated L1 sampling, which offers a more efficient decomposition. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://s3miclassical.com/gitweb", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Weak Simulation v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://s3miclassical.com/gitweb", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-16", + "metadataLastUpdated": "2022-10-16" + }, + "description": "SAND2021-4823 O InterSpec decodes and displays gamma radiation data from a variety of handheld, laboratory, and fixed installation detector types. Once loaded, InterSpec provides a means to interactively analyze the data via a peak-based methodology. InterSpec assists with isotope identification and determines the source strength and shielding characteristics of the measured item. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++", + "JavaScript", + "C++", + "HTML" + ], + "name": "InterSpec v. 1.0.9", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/InterSpec", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.9" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-16", + "metadataLastUpdated": "2022-10-16" + }, + "description": "SAND2021-11479 O The OT Emulation Data Broker system allows Simulink models to be connected to an emulated control system network. The package includes a Simulink S-Function that allows communication to the data broker via inter process communication; a data broker, which orchestrates communication between the emulated control system network and the simulation; an endpoint, which facilitates communication between the data broker and PLC's on the control network using ModBus/TCP; and an example PLC structured text files that work with OpenPLC, an open source emulated PLC. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C", + "Python", + "Simulink", + "S Function" + ], + "name": "OT Emulation Data Broker v.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SMARTT", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-10-17", + "metadataLastUpdated": "2022-10-17" + }, + "description": "This software is used to disentangle the forced-versus-unforced components of tropospheric temperature change over the satellite era (after 1979) using maps of surface temperature change as a predictor. In general, the software assembles training datasets (from pre-computed surface temperature trend maps and domain averaged tropospheric warming rates), trains statistical/machine learning (ML) algorithms, applies the trained statistical/ML model to climate model data and observations, and then saves the results. A leave-one-out approach is used in which the statistical/ML models are iteratively trained on (N- 1) climate model and then applied to the remaining climate model (and observations). Each model includes a large ensemble (i.e., >10) of model simulations. The software relies on scikit-learn ridge regression, PLS regression, and neural network algorithms.", + "laborHours": 0.0, + "languages": [], + "name": "MSU Disentanglement Analysis Software", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MDAS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2022-10-17", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural Networks (DNNs), Neural ODEs, and Symplectic Neural Networks (SympNets) used with state-of-the-art sampling schemes like Hamiltonian Monte Carlo (HMC) and the No-U-Turn-Sampler (NUTS).", + "laborHours": 0.0, + "languages": [], + "name": "BIhNNs", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/BIhNNs", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2022-10-17", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The purpose of this code is to automatically create random C programs that are guaranteed to have bugs of a particular \"interestingness\". We are using this to train learning machines to fuzz programs better. Other people might want to use it for training humans to examine software.", + "laborHours": 0.0, + "languages": [ + "python 3" + ], + "name": "Buggy-Program-Program", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Buggy-Program-Program", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2022-10-18", + "metadataLastUpdated": "2023-03-13" + }, + "description": "Scoring Threat Objects Analysis Tool", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "python3" + ], + "name": "cisagov/STOAT", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cisagov/STOAT/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cisagov/STOAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-10-18", + "metadataLastUpdated": "2023-02-07" + }, + "description": "ERAD is a software product for computing resiliency and equity metrics in power distribution system. It uses graph database technology to store, query and compute metrics making it highly scalable and available. Metrics can be computed for various resiliency scenarios such as fire, flooding, earthquake.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "ERAD (Equitable Resiliency Analysis tool for Distribution System) [SWR-22-75]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/erad", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "39s@ornl.gov" + }, + "date": { + "created": "2022-10-20", + "metadataLastUpdated": "2022-10-20" + }, + "description": "Reads proprietary electron microscope vendor files and exports them in a standardized open source HDF5 format.", + "laborHours": 0.0, + "languages": [], + "name": "Microscopy Parser", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esrah-ap-niht/Microscopy-VB-GMM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2022-10-26", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The optimization tool denoted as the \u201cHydropower Flexibility Valuation Tool\u201d aims to maximize the revenue from market participation after satisfying flow requirements, considering a range of power market price signals and water availability scenarios.", + "laborHours": 0.0, + "languages": [], + "name": "HFVT", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HFVT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-10-27", + "metadataLastUpdated": "2022-10-27" + }, + "description": "TEE-ACM2 is a library that computes matrix chain multiplication efficiently on GPUs, using a blocking strategy to load data. The library will provide an energy efficient algorithm for chain Matrix Multiplication, by minimizing both computations and off chip data transfers on the GPUs.", + "laborHours": 0.0, + "languages": [], + "name": "TEE-ACM2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/TEE-ACM2", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-10-27", + "metadataLastUpdated": "2022-10-27" + }, + "description": "This R code consists of three scripts, described below.\n1. ILI_LHC_sample.R The first script generate 10,000 samples from the total\nparameter space formed by the ranges of the following five parameters inputted\ninto the ILI model: transmission rate (beta), per capita rate of progress from\nexposed to infectious state (gamma_1), per capita rate of progress through initial\ninfectious state (gamma_2), per capita rate of progress through hospitalized state\n(gamma_3), and per capita rate of progress through non-hospitalized infectious\nstate (gamma_4). The output is LHS_samples.csv, for input into the global\nsensitivity script, ILI_SEIR.\n2. ILI_SEIR.R The second script solves a standard Susceptible-Exposed-Infected-\nRecovered (SEIR) model (a system of Ordinary Differential Equations (ODEs)),\nruns global sensitivity analyses, and generates plots showing the impact of the\ninput variables on the response variables for each virus.\n3. virus_sims.R The third script solves a standard Susceptible-Exposed-Infected-\nRecovered (SEIR) model (a system of Ordinary Differential Equations (ODEs)),\naimed at modeling outbreaks for five common upper respiratory viruses within a\ncontained population. The output of this code is an epidemic curve to show\ntiming and magnitude of the epidemic peak for each virus.\nNote: for all three scripts, the parameter values must be hard-coded by the user or the\noutput will not be accurate.", + "laborHours": 0.0, + "languages": [], + "name": "ILI Code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ILI", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-10-27", + "metadataLastUpdated": "2022-10-27" + }, + "description": "A collection of iterators built on NVIDIA's thrust library driven by a small domain specific language", + "laborHours": 0.0, + "languages": [], + "name": "thrust iterators", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/thrust-iterators", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-11-03", + "metadataLastUpdated": "2023-04-11" + }, + "description": "Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The code has gone through five rounds of development with images used to train the models. This advancement allows for automated real-time data collection, identification, and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. We will discuss the two open source and publicly available machine learning models developed within this scope of this work: 1) a binary model with a 97.5% accuracy in identifying the difference between an object and an empty scene, including wind turbine and clouds; and 2) a multiple classification model with the capability of identifying the type of object detected: bats (90% accuracy), birds (83% accuracy), insects (69% accuracy) and non-biological (99% accuracy).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "BFSVBF (BatFinder Smart Video BioFilter) [SWR-22-87] and Multi-class BatFinder Smart Video BioFilter Keras", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BatFinder_Smart_Video_BioFilter", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-11-03", + "metadataLastUpdated": "2023-05-05" + }, + "description": "Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source 3D computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The machine learning has been trained on 3D data and allows for automated real-time data collection, identification and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. This machine learning model is an added feature to the previous BatFinder Smart Video BioFilter and increases the accuracy of that systems classification by increasing the accuracy of identifying bats (90% accuracy) and insects (69% accuracy) to a 97% accuracy. There are two object classifier machine learning models, Binary and multi-classification. Binary object classifier labeled BatFinder_Smart_Video_BioFilter.h5 distinguishes between biological objects and non-biological objects. The main goal of this object classifier is to ignore the turbine blades while detecting biological object flying withing the rotor swept area of the turbine. Non-biological objects have a probability of 0 and biological objects have a probability of 1. Multi-classifier labeled Multiclass_BatFinder_Smart_Video_BioFilter.h5 distinguishes between bats, birds, insects and non-biological.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "3DBFSVBF (3D BatFinder Smart Video BioFilter and Multi-class BatFinder Smart Video BioFilter) [SWR-22-88]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BatFinder_Smart_Video_BioFilter", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Code to run the experiments of the Neurips 2022 paper [On the Symmetries of Deep Learning Models and their Internal Representations](https://arxiv.org/abs/2205.14258).", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/modelsym", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/modelsym", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "salkork@ornl.gov" + }, + "date": { + "created": "2022-11-08", + "metadataLastUpdated": "2022-11-08" + }, + "description": "SalineMoose is a MOOSE wrapper for the open-source Saline code, which is an interface for fluid property databsae files. This code is meant to provide access to Saline, which can easily be integrated into MOOSE-based codes that need access to the fluid thermophysical properties that Saline can provide. Wrapping Saline in SalineMoose allows MOOSE codes to use the native MOOSE build system for linking Saline to their MOOSE application.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "SalineMoose", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/neams/saline_moose/-/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/neams/saline_moose", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "vogl2@llnl.gov" + }, + "date": { + "created": "2022-11-09", + "metadataLastUpdated": "2022-11-15" + }, + "description": "A platform for building collaborative autonomy-focused applications.", + "laborHours": 0.0, + "languages": [], + "name": "Skywing", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Skywing/releases/tag/v0.1", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-11-10", + "metadataLastUpdated": "2022-11-10" + }, + "description": "LOKI is a simulation code that models weakly-coupled plasma evolution using Eulerian kinetic models in four phase space dimensions. The code is useful to understand basic plasma nonlinear plasma physics phenomena - in particular, wave-particle and wave-wave resonances that occur in laser plasma interactions. LOKI can simulate fundamental physical process in low-density plasmas on a scale of hundreds of light wavelengths. It does so by solving the relativistic Vlasov and Valsov-Fokker-Planck differential transport equations describing the collision less and low-collisionality evolution of charged particles in electromagnetic fields in two configuration space and two velocity space dimensions. 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Finally, the data can be transformed into 3D-\u0394PDF maps using the punch-and-fill method after symmetrization.", + "laborHours": 0.0, + "languages": [], + "name": "NXREFINE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/axmas-anl/nxrefine", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-11-14", + "metadataLastUpdated": "2022-11-22" + }, + "description": "Sulfur TES ML contains code originally created to develop surrogate ML models to mimic the utility of CFD simulations of Sulfur TES systems. 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Challenges to large-scale adoption of this additive manufacturing method include identifying light dosage parameters and monitoring during fabrication. A research team from LLNL, Iowa State University, and Georgia Tech is applying machine learning models to tackle these challenges-i.e., accelerate the process of identifying optimal light dosage parameters and automate the detection of part quality. Funded by LLNL's Laboratory Directed Research and Development Program, the project team has curated a video dataset of TPL processes for parameters such as light dosages, photo-curable resins, and structures. Both raw and labeled versions of the datasets are available on the links in the Open Data Initiative page. The code uses the labeled dataset. Notebook compiled by Nisha Mulakken (mulakken1@llnl.gov) for LLNL Open Data Initiative, Summer 2022. Original code provided by research team. Publications: X.Y. Lee, S.K. Saha, S. Sarkar, B. Giera. \"Automated detection of part quality during two-photon lithography via deep learning.\" Additive Manufacturing 36, December 2020: doi.org/10.1016/j.addma.2020.101444 X.Y. Lee, S.K. Saha, S. Sarkar, B. Giera. \"wo Photon lithography additive manufacturing: Video dataset of parameter sweep of light dosages, photo-curable resins, and structures.\" Data in Brief 32, October 2020. doi.org/10.1016/j.dib.2020.106119.", + "laborHours": 0.0, + "languages": [], + "name": "ODI notebook additive_manufacturing_video_2022", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnlopendata/additive_manufacturing_video_2022", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2022-11-16", + "metadataLastUpdated": "2022-11-16" + }, + "description": "First patch release of v2.0.0 Changes since v2.0.0 [Important change] Fix ocean threading bug seen in debug cases on Chrysalis with Intel 20.0.4. Was introduced around time of v2.0.0 tag. Does not change v2.0.0 answers on Chrysalis because those didn't use threading or debugging. [EAM] Add semi-lagrangian tracer transport for theta-l (F90 and C++), add new algorithm for finding tropopause, add DSCREAM to allow v2 and SCREAM settings in same code such as adjust_ps [EAM-MMF] 60L default, allow C++ back end of RRTMGP (EAM too). [EAMxx] add nu-top functionality, fix forcing functor, add ttype9 and dcmip2012 tests 2.1, 2.2, and 3 HOMME: remove obsolete remap algs, option to specify dynamics alg indep of tracer, new sponge layer, add imex tests [ELM] Add topography-based subgrid (topounits), add FATES-ELM Nitro., Phos. and CH4 coupling, add land-use ts for NARRM, add lulc for SSP3 RCP7, Fix nutrient fertilization exp test and carbon isotope flux, Fix xactive lnd dry deposition, add lake water storage option, fix plant hydraulics 2d params, fix carbon budget calc, fix soil nutrient conc. bug, fix mosart dam bug, add test for new ELM, MOSART features, fix bug in O3 dry dep stomatal resistances, fix plant hydraulics restart BFB error, update mkmapdata. [MOSART] fix bug for reading the latitude from an unstructured input file, fix oversat in bubble test. [MPAS-ocean] Add CFC11, CFC12 tracers, add 2D spherical transport tests, fix del4 tracer mixing, add MARBL ocean tracer mixing, modify harmonic analysis options, add GPU port of vmix routines, fix calc of ML-averaged BV freq. [MPAS-seaice] Change extents of initial polar disks for oRRS18to6v3 grid, fix ice BGC with MARBL, update spherical test cases, fix DON coupling, Remove Cf from sea ice constants. [MPAS-landice] add CRYO1850-4xCO2 compset [CIME] add GCP, ANL GCE, Spock, Perlmutter, deprecate config_compilers.xml, fix and clean-up cmake macros, fix slurm bindings, refactor CIME internal testing, cleanup SCORPIO perf data, allow position independent compset naming, [also] update v2 benchmarking suite, extend e3sm_prod with throughput and memory checks", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v2.0.1", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v2.0.1", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v2.0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Web server and RESTful backend services for APBS and PDB2PQR\nThis software was developed to deploy APBS (https://github.com/Electrostatics/apbs) and PDB2PQR\n(https://github.com/Electrostatics/pdb2pqr) on Azure to address a gap left by the closing of the previous hosting service at\nUCSD", + "laborHours": 0.0, + "languages": [], + "name": "Electrostatics/apbs-rest", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://creativecommons.org/publicdomain/zero/1.0", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electrostatics/apbs-rest", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SSASSE software is responsible for validating, and verifying\u202finnovative safe scanning methodologies, models, architectures, and prototypes to\u202fsafely assess\u202foperational technology (OT) installed in critical energy infrastructure.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/ssass-e", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ssass-e", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Mapping software with pre-loaded global and local maps", + "laborHours": 0.0, + "languages": [], + "name": "JGCRI/rmap", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/rmap", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "FENATE: Fast Evaluation of Network Architecture -- Toolchain and Environment. Our framework is comprised of scalable\ntools to both skeletonize and simulate MPI communication patterns providing a functional view of the network under\ninvestigation (trading off accuracy for speed)", + "laborHours": 0.0, + "languages": [], + "name": "FENATE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/FENATE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Transfer Learning From Existing Diseases Via Hierarchical Multi-Modal BERT Models", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/TransMED", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/TransMED", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Python package that provides an interface to raw MS data in the MZA format.", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-m-q/mzapy", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-m-q/mzapy", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Designs for Risk Evaluation and Management (DREAM) tool was developed as part of the effort to quantify the risk of\ngeologic storage of carbon dioxide (CO2) under the U.S. Department of Energy\u2019s National Risk Assessment Partnership\n(NRAP). DREAM is an optimization tool created to identify optimal monitoring schemes that minimize the time to first\ndetection of CO2 leakage from a subsurface storage formation. DREAM acts as a post-processer on user-provided output\nfrom subsurface leakage simulations. While DREAM was developed for CO2 leakage scenarios, it is applicable to any\nsubsurface leakage simulation of the same output format", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/dream_v3", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/dream_v3", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Archive Sprinter tool is designed to efficiently process synchrophasor measurements from electric power grids and\nexport data signatures that summarize the grid's behavior. Parallel processing will allow data to be processed quickly to\nenable practical analyses of archives spanning years. The grid's behavior will be summarized using a wide-array of\nsignatures calculated from the input data.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/archive-sprinter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/archive-sprinter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "zulissi@andrew.cmu.edu" + }, + "date": { + "created": "2022-11-18", + "metadataLastUpdated": "2022-11-18" + }, + "description": "CatGym is a deep reinforcement learning (DRL) environment for predicting the thermal surface reconstruction pathways and their associated kinetic barriers in crystalline solids under reaction conditions. The DRL agent iteratively changes the positions of atoms in the near-surface region to generate kinetic pathways to accessible local minima involving changes in the surface compositions.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "catgym", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ulissigroup/catgym", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-11-18", + "metadataLastUpdated": "2022-11-18" + }, + "description": "The autodataman tool is intended to be a very lightweight climate data database and data distribution engine.", + "laborHours": 0.0, + "languages": [], + "name": "Autodataman", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmecmetrics/autodataman", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2022-11-18", + "metadataLastUpdated": "2022-12-23" + }, + "description": "Second patch release of v2.0.0 Changes since v2.0.1 [Important change] Add and update SSP370 and SSP585 cases, add tests, fix use-case files, Change ocean and sea-ice IC for ARRM60to10. [EAM] allow thetaxx as a CAM_TARGET, enable northamericax4v1pg2_WC14to60E2r3 for AMIP, fix ndrop initialization, allow up to 15 history files. [EAMxx] allow use of readnl [EAM-MMF] allow transient SST case for C++ MMF, remove specific task/thread count for ESMT test, modify the variance transport diagnostic, reorg tests, [HOMME] Allow optional sponge layer. [ELM] add 2 land-atm compsets, update FATES to API 17.0.0, allow FATES sp mode, allow ELM harvest to drive FATES harvest, fix memleaks, reduce test build times, modified parameters for miscanthus and switchgrass based on calibration [MPAS-Ocean] turn on ocean BGC in BGC cases, fix interface locations for 60L PHC grid, add mode spec to conservation check streams, allow oRRS18to6v3 grid to run with JRA, update ocean and sea ice ICs for ARRM60to10 (needed for v2), GPU port of thickness tendency, add CMPASO-JRA1p4, [MPAS framework] Add new reproducible global sum module for MPAS components, Add mostRecentAccessTime attribute to streams [MPAS-landice] Update MALI version and Greenland mesh [MPAS-seaice] add single-cell test case, fix BGC restart, Adds omp critical directives for ice warnings seen on cori. [CIME] Fix component namelist creation bugs when NINST>1, add OpenACC, OpenMP and CXX GPU tests, fix nonBFB tests, stop using config_compilers, reduce ELM test build times with shared executable, update OpenMPI on Chrysalis. fix baseline handling, provenance handling with update to cime6.0.33, also use component-specific config_pes files and add the ones from master [Machine updates] cori modules after maint, Chrysalis to OpenMPI-4.1.3 [run_e3sm] replace default case name and group. [Externals] update SCORPIO to 1.3.2", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v2.0.2", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v2.0.2", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v2.0.2" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "We investigate substituting a parallel, half-approximation for maximum weight matching instead of an exact computation. Our experiments show that the resulting difference in solution quality is negligible. 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The MFC modulates the flexible GEB in the lower level with guaranteed thermal comfort of end users in response to the optimal pricing and power signals determined in the upper layer using a Stackelberg game integrated with aggregate virtual battery constraints. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable even on small, embedded devices. This software code enables the use of residential and small-size commercial buildings to offer a potentially substantial source of ancillary grid services that are currently underutilized. A hierarchical, model-free transactive building control provides a smooth interface between the grid service requests of utilities and the reliable control required by participating buildings. Model-free control, which supports distributed control architecture, will be a more scalable solution that can be deployed in neighborhood-size systems as well as individual buildings. The proposed approach contributes to the body of knowledge on two main aspects. First, it couples the MFC with the game-theoretic control and proposes a scalable model-free transactive control approach. MFC does not require any modeling effort or model training for the various building loads. This is very beneficial since deriving an accurate model for every single unit participating in DR programs and obtaining all the parameters about the units (e.g., thermal coefficients, standby losses) are infeasible. Also, MFC is computationally efficient, easily deployable even on small, embedded devices, and can be implemented in real time. Second, it integrates the concept of virtual battery into DR via the Stackelberg game. 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Additionally, the scripts implement analysis methods to evaluate and explore the results of the method. 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In TriPoll, users define their own callback functions that get executed on the metadata of each triangle within a\ngraph as triangles are identified. This functionality makes it possible for users to perform advanced analyses and gather statistics about specific classes of triangles of interest.", + "laborHours": 0.0, + "languages": [], + "name": "TriPoll", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/tripoll", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "qinwu@bnl.gov" + }, + "date": { + "created": "2022-12-23", + "metadataLastUpdated": "2022-12-23" + }, + "description": "Kinetics of a reaction network that follows mass-action rate laws can be described with a system of ordinary differential equations (ODEs) with polynomial right-hand side. 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Importantly, we have implemented various measures to apply physical constraints and chemical knowledge in the training to regularize the solution space.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PolyODENet", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ICKMod/PolyODENet/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ICKMod/PolyODENet", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-01-03", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This application allows parallel development of simulator screens for the Human System Simulation Laboratory and connection of the backend simulators for various power plants", + "laborHours": 0.0, + "languages": [], + "name": "General-Simulator-Intermediary", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/General-Simulator-Intermediary", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-01-03", + "metadataLastUpdated": "2023-05-17" + }, + "description": "Caldera ICM is part of Caldera software platform, a suite of collective, open-source tools that was developed to improve the state of the art in modeling the impacts of Electric Vehicle (EV) charging on the grid. The foundation of Caldera ICM is it\u2019s first-of-its-kind library of high-fidelity charging models for a wide variety of vehicles, validated by test data under a range of operating conditions. The charging models are used to accurately model the EV charging on an electric vehicle supply equipment (EVSE) \u2013 also known as a charger. ICM uses as inputs, the EV characteristics such as battery size, battery chemistry (i.e. NMC, LTO), watt hour per mile, inverter efficiency and max charge rate; as well as EVSE characteristics such as max current and supply equipment type (i.e. L2 vs XFC). Using these inputs Caldera ICM creates an uncontrolled charging profile curve for each compatible EV-EVSE pair. These charge profiles can be used stand alone to estimate charge duration given start State Of Charge (SOC) and end SOC or charge energy size given start SOC and charge duration. In Caldera Grid, another tool in the Caldera software platform, these charge profiles are used to represent EV charging as a load on the grid using charge event data such as EV type, SE type, start SOC, final SOC, park start time and park end time. ICM currently supports energy shifting Smart Charge Management (SCM) strategies such as \"Time Of Use (TOU) immediate\u201d, \u201cTOU random\u201d and \u201crandom start\u201d by delaying the charge to start at a preferable time with respect to the strategy and, one voltage support SCM strategy named autonomous voltage control strategy by providing reactive power back to the electric grid.", + "laborHours": 0.0, + "languages": [], + "name": "Caldera Infrastructure Charge Module (ICM)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Caldera_ICM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-01-03", + "metadataLastUpdated": "2023-05-17" + }, + "description": "Caldera Grid is part of Caldera software platform, a suite of collective, open-source tools that was developed to improve the state of the art in modeling the impacts of Electric Vehicle (EV) charging on the grid. Caldera Grid is a co-simulation framework implemented using Hierarchical Engine for Large scale Infrastructure Co-Simulation (HELICS). The framework facilitates the co-simulation of EV charging and Smart Charge Management (SCM) strategies in Caldera Infrastructure Charge Model (ICM) with distribution level grid models in OpenDSS. Vehicle energy needs and charge session requirements generated using Caldera Charge Decision Module (CDM) are fed in as input to Caldera Grid. The EV charging models in Caldera ICM simulates both the uncontrolled charging loads as well as loads modified by the SCM strategies to develop distributed load profiles for each grid node hosting an Electric Vehicle Supply Equipment (EVSE) \u2013 also known as chargers. These loads were simulated in OpenDSS alongside existing distribution feeder loads. Each of these models are co-simulated in a HELICS federate. The HELICS co-simulation framework facilitates communication and synchronization between the federates. By co-simulating EV loads and distribution feeder loads, Caldera Grid can assess the potential grid impacts of EV charging on distribution feeders under various grid conditions. A control strategy federate is implemented with an interface where control strategies based on feedback from EV charging status and grid conditions can be developed and implemented. The platform can also support multiple control strategies in a single co-simulation.", + "laborHours": 0.0, + "languages": [], + "name": "Caldera_Grid", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Caldera_Grid", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-04", + "metadataLastUpdated": "2023-01-04" + }, + "description": "This software contains the code for a data-driven model to produce high-resolution (< 1 km2) estimates of temperature, salinity, and turbidity over decadal time scales as required by next-generation Earth Systems Models. Our model fits daily MODIS Aqua reflectance data to surface observations (< 1 m depth) from 2000-2021 in Chesapeake Bay, USA.", + "laborHours": 0.0, + "languages": [], + "name": "Geographically aware estimates of remotely sensed water properties for Chesapeake Bay", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DOE-ICoM/geowq-chesapeake", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-04", + "metadataLastUpdated": "2023-01-04" + }, + "description": "Ring Pull Strain Analysis (RPSA) is a framework for analysis of Digital Image Correlation (DIC) data of gaugeless ring pull testing. It is meant for analysis of rings cut from tube cross sections and pulled in a displacement-controlled tensile test. This code takes load frame data, images take during testing, and csv files from the DIC analysis of those images and allows the user to analyze and plot data from the test. Some important features of the software include getting the strain values as a function of radial distance and angle, plotting of the strain around the ring, and stress-strain analysis of the load frame data.", + "laborHours": 0.0, + "languages": [], + "name": "Ring Pull Strain Analysis", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/RingPullStrainAnalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-04", + "metadataLastUpdated": "2023-01-04" + }, + "description": "Architector is a 3D chemical structure generation software package designed to take minimal 2D information about ligands and metal centers and generates chemically sensible 3D conformers and stereochemistry of the organometallic compounds. Architector is capable of high-throughput in-silico construction of s-, p-, d-, and f-block organometallic complexes. Architector represents a transformative step towards cross-periodic table computational design of metal complex chemistry.", + "laborHours": 0.0, + "languages": [], + "name": "Architector", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Architector", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-04", + "metadataLastUpdated": "2023-01-04" + }, + "description": "The Orthogonal Diffusion Discretizations (ODD) library is a collection of low order (Diffusion, P1, Ray Tracing, and Variable Eddington Factor (VEF)) thermal radiation solvers for orthogonal structured grids driven by an application programing interface (API).", + "laborHours": 0.0, + "languages": [], + "name": "ODD (Version 0.X)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ODD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-04", + "metadataLastUpdated": "2023-01-04" + }, + "description": "EAP Patterns: Memory access and iteration patterns from the EAP code base with the physics removed. This is intended to be a serial app representing memory access patterns. We will populate the data structures from EAP output files to provide representative patterns of face and cell loops within the EAP code base The arguments to the program are the EAP output file and the number of MPI processors to emulate. Currently there is no MPI in the application and the number of processors represents a means of emulating the halo (clone) cells around the domain of the given processor. An optional argument `processor_ID` can be provided to specify the processor to emulate. In the future we plan to include the ability to run multiple MPI ranks to more accurately represent the on-node demands on memory bandwidth.", + "laborHours": 0.0, + "languages": [], + "name": "EAP Patterns", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/eap-patterns", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-15185 O Differentially Private DBSCAN is a differential private clustering algorithm used for running experiments and conducting data analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 76.0, + "languages": [ + "Python3" + ], + "name": "Differentially Private DBSCAN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DP_DBSCAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2023-06-22" + }, + "description": "SAND2022-14744 O The Deep Learning Denoiser uses a trained deep convolutional neural network (CNN) model to decompose an input waveform into a signal and noise waveform. In the approach, the CNN provides a signal mask and a noise mask for an input signal. The Short-Time Fourier Transform (STFT) of the estimated signal is obtained by multiplying the signal mask with the STFT of the input signal. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deep Learning Denoiser", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Deep-Learning-Denoiser", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2023-01-12" + }, + "description": "SAND2022-14694 O CrystalVR is a CAD2VR plugin which enables the import of crystallographic information files (CIF) into a virtual reality (VR) environment for visualization and interaction. Crystallographic data is incredibly complex and difficult to navigate and visualize on a two-dimensional or 2D screen. CrystalVR empowers users to step inside their crystals, allowing them to intuitively grow, shrink, and scale the crystal structure. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "CrystalVR", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "2022.0.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2023-05-16" + }, + "description": "The HOMP software module is contained within NREL's Hybrid Optimization and Performance Platform (HOPP) at this URL: https://github.com/NREL/HOPP/tree/feature/HOMP. HOMP is a python-based software module which can be used concurrently with the Hybrid Optimization and Performance Platform (HOPP) to model, simulate, and optimize degradation, reliability, and operations and maintenance of hybrid power plant components. The program currently models lithium ion battery, PEM electrolyzer, wind turbine, and solar PV array components, which enables users to understand the design and operation tradeoffs of hybrid power plants. For instance, HOMP enables users to answer questions like: how large does a battery bank need to be to achieve optimal charge/discharge rates for performance and reliability? How does plant design change for different objectives (e.g., profit versus resilience)? Under what conditions is it better to produce electricity versus hydrogen? How do we optimally control hybrid power plants to reduce downtime and increase performance?", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "PowerBuilder", + "Python" + ], + "name": "HOMP (Hybrid Operation and Maintenance Platform) [SWR-22-81]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HOPP", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-14659 O The Wind Energy Intrusion Detection System uses a human-machine interface (HMI) to parse results and analyze for anomalies. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "Wind Energy Intrusion Detection System", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/wind_hids", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Protein-DNA Interaction Workflow (PDI Workflow), a pipeline that focuses on generating\nhigh-quality docking and molecular dynamics simulations for Protein-DNA complexes. This allows us to take DNA\nsequences with unknown tertiary structures, accurately predict their structure, dock them with the desired target protein,\nand then simulate their interactions using molecular dynamics simulations", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Auto_PDI", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "3D-MolGNNRL, couples reinforcement learning (RL) to a deep\ngenerative model based on 3D-Scaffold to generate target candidates specific to a protein pocket building up atom by\natom from the core scaffold. 3D-MolGNNRL provides an efficient way to optimize key features within a protein pocket using\na parallel graph neural network model. The agent learns to build molecules in 3D space while optimizing the binding\naffinity, potency, and synthetic accessibility of the candidates generated for the SARS-CoV-2 Main protease", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "3D_MolGNN_RL", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "control software for an automated liquid chromatography sample injection and\nseparation system. It is related to a PNNL invention report 31630-E, Method for direct delivering trace samples from smallsize\nwells to liquid chromatography and mass spectrometry. The main purpose of the control software is to enable\nautomated sample injection from a nanowell device.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Autosampler software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A method for prediction of cell regulation to maximize cell growth rate while maintaining the solvent capacity\nof the cell. Prediction is formulated as an optimization problem using a thermodynamic framework that can leverage\nexperimental data. We develop a formulation and variable initialization procedure that allows for computing solutions of\nthe optimization with an interior point method", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Pathway_Controlled_Optimization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Pathway_Controlled_Optimization", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2023-01-12" + }, + "description": "First release of version 2.1 of the Energy Exascale Earth System Model. [ATM] The atmosphere component remains EAM. There are no major changes in the default configuration since 2.0. New features include: A semi-lagrangian tracer transport for theta-l dycore, a new algorithm for finding the tropopause, new RRM mesh configurations. Add and update SSP370 and SSP585 cases. Restore the FIDEAL case. [LAND] The land component is ELM. There are no major changes in the default configuration since 2.0. Several option features have been added including: implementation of topography-based subgrid structure (topounits) and accompanying parameterizations and atmospheric forcing downscaling methods; a new plant hydraulics scheme; two-way land-river hydrological coupling through the infiltration of floodplain water; an implementation of perennial crops; updates to the SNICAR-AD snow radiative transfer model; and implementation of soil erosion and sediment yield in ELM-Erosion. Each of these new changes is modular in design and can be turned on or off as the user specifies; they are currently being tested in different \u201cBGC\u201d configurations. [OCEAN] The ocean component remains MPAS-Ocean. Major change since version 2.0 include the addition of the Fox-Kemper et al. 2011 parameterization for submesocale eddies, a correction for barotropic thickness consistency that reduces divergence noise, and the addition of an ocean carbon conservation analysis member. [SEAICE] The sea-ice component remains MPAS-Seaice. Major changes since version 2.0 include: A correction to how shortwave parameters are interpolated in the snicar-ad 5-band radiation scheme, the addition of a sea ice carbon conservation analysis member, updates to the default sea ice biogeochemistry namelist parameters to be consistent with version 2.0 improvements to nitrogen cycling and a correction in the ice-ocean dissolved organic nitrogen coupling. [LAND ICE] The land-ice component remains MPAS-Albany-landIce (MALI). Major changes since 2.0 include an update to the MALI version and the Greenland mesh.[RIVER] The river model is MOSART. There are no major changes in the default configuration since 2.0. A major new optional feature is two-way river-ocean hydrological coupling between MOSART and MPAS-O. This change can be turned on or off as the user specifies, and is being tested in different configurations. [COUPLER] The coupler remains cpl7/MCT. Major changes since version 2.0 include: Carbon budget calculated when heat/water budgets active. Fix a bug in land-atm fluxes for tri-grid configurations. [OTHER] a small bug in the zenith angle calculation was fixed in the data models.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v2.1.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v2.1.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v2.1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-01-11", + "metadataLastUpdated": "2023-03-29" + }, + "description": "The Beam Characterization System (BCS) is an image-processing tool for estimating heliostat tracking errors. A large mirror, or heliostat, reflects the sun onto a distant target. A carefully calibrated camera then takes an image of this target to capture the shape of the reflected beam. The software kit hosts a series of scripts to identify key features and run analysis on the captured images.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "BCS (CSP Beam Characterization System) [SWR-23-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NREL-Beam-Characterization", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The molecular graphics program, PyMol, was employed to produce all images in the training/validation/testing datasets. A\nPyMol script identified the clusters of interest from a list of all proteins containing 1) Fe (III) and Fe (II) ion and 2) FeS,\nrespectively. A PyMol script and a Python webscraper were also used to classify [2Fe-2S] cofactors into three classes:\nstandard, Rieske, and other and to identify iron atoms with four cysteine residues. We also used the pyMol script to rotate\namino acids for training", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/mlprotein", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mlprotein", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "mcarbone@bnl.gov" + }, + "date": { + "created": "2023-01-15", + "metadataLastUpdated": "2023-01-15" + }, + "description": "Neural network ensembles for X-ray absorption spectroscopy of molecules and materials. Companion code for preprint https://arxiv.org/abs/2210.00336.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AI-multimodal/XAS-NNE", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AI-multimodal/XAS-NNE", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git", + "version": "v0.1.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-17", + "metadataLastUpdated": "2023-01-17" + }, + "description": "This software builds on PHAME developed at LANL to generate phylogenetic trees of bacterial whole genome sequences. Where PHAME uses whole genome alignments to generate informative sites to base tress on, PHAME-OuS annotates bacterial genes, identifies orthologous sequences, aligns related proteins, uses those alignments to inform transcript alignments, then builds trees with several methods. The first is a conventional gene concatenation and ML tree estemation method. The second attempts to reconcile gene tree with a unified species tree using quartets (ASTRAL). Both methods allow filtering of gene lists on number of species represented, length, and gappiness in order to tune noise-to-signal for tree estimation", + "laborHours": 0.0, + "languages": [], + "name": "OrthoPhylo", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/OrthoPhylo", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2023-01-17", + "metadataLastUpdated": "2023-08-24" + }, + "description": "This open-source tool aims to provide a powerful and flexible platform for simulating electromagnetic transients (EMT) of large-scale inverter-based resource (IBR)-dominated power systems. The purpose of making it open source is to foster a community of EMT simulation and assist in exploring new EMT algorithms and applying advanced computational techniques to EMT simulation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ParaEMT (NREL's EMT Simulator: An Open Source, and HPC-Compatible Large-Scale Power System Electro-Magnetic Transient (EMT) Simulator) [SWR-22-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ParaEMT_public", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ghawalyjm@ornl.gov" + }, + "date": { + "created": "2023-01-18", + "metadataLastUpdated": "2023-01-18" + }, + "description": "Code accompanying the \"Introduction to Machine Learning\" short course for the 2022 IEEE NSS MIC RTSD conference.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "IEEE Short Course 4: Introduction to Machine Learning", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jghawaly/IEEE_Intro2ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "nutarojj@ornl.gov" + }, + "date": { + "created": "2023-01-19", + "metadataLastUpdated": "2023-01-19" + }, + "description": "Convert Collada 3D model files to a voxel model.", + "laborHours": 0.0, + "languages": [], + "name": "tovox", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/1qn/tovox", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "vincent@sacksteder.com" + }, + "date": { + "created": "2023-01-24", + "metadataLastUpdated": "2023-02-21" + }, + "description": "ComDMFT is an ab initio code for simulating correlated quantum materials with crystalline symmetry. It combines DFT or qsGW calculations with impurity problems describing strong on-atom correlations. The impurity problem is set up using Wannier90 and cRPA, and can be solved with DMFT and CTQMC.", + "laborHours": 0.0, + "languages": [], + "name": "ComDMFT", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/comscope/ComDMFT", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-01-24", + "metadataLastUpdated": "2023-04-05" + }, + "description": "These datasets describe multiple facets of the temporal complementarity of co-located hybrid renewable energy systems throughout the United States. Several metrics characterizing the complementarity of generation profiles are provided on an annual and monthly basis (for both hourly and daily aggregations). These generation profiles are underpinned by hourly resource data (e.g., the WIND Toolkit and National Solar Radiation Database (NSRDB)) spanning the multi-year period 2007-2013. The data include complementarity results for greater than 1.76 million individual locations within the continental United States (CONUS). The data are intended to accompany two publications on the topic of temporal complementarity: 1) Harrison-Atlas, Dylan, Caitlin Murphy, Anna Schleifer, and Nicholas Grue. \"Temporal complementarity and value of wind-PV hybrid systems across the United States.\" Renewable Energy 201 (2022): 111-123, doi:10.1016/j.renene.2022.10.060; and 2) Murphy, Caitlin, Harrison-Atlas, Dylan, Nicholas Grue, Vahan Gevorgian, Juan Gallego-Calderon, Shiloh Elliot and Thomas Mosier. \u201cA Resource Assessment for FlexPower\u201d. NREL Technical Report.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "Data on temporal complementarity of hybrid renewable energy systems [SWR-23-09]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Renewable-Complementarity", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-01-25", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Bayesian Model Calibration (BayCal) toolkit is a software plugin for Risk Analysis Virtual Environment (RAVEN) framework, arming at inversely quantifying the uncertainties associated with simulation model parameters based on available experiment data. BayCal seeks statistical inference of the uncertain input parameters that are consistent with the available measurement data or observed data. The unique feature of BayCal is the capability to be linked with RAVEN to build corresponding calibration workflows for complex multi-physics simulations. In addition to be able to use the machine learning capability of RAVEN to significantly reduce the computational cost of expensive simulation models, another distinctive feature of BayCal is the capability to deal with high-dimensional correlated model outputs, such as time series observations at multiple locations, via principal component analysis (PCA) technique.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Baycal", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/BayCal", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-01-25", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This code provides annotation and an interface to 10+ hours of video activities in a high performance datacenter with 20+ different types of anomalous activities. The purpose is to enable machine learning for video surveillance systems in high performance computing centers. This is the first code of this type addressing the space of high performance computing datacenters.", + "laborHours": 0.0, + "languages": [], + "name": "Anomalous And Normal High Performance Computing Datacenter Activities", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HPCACT-2022", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-01-27", + "metadataLastUpdated": "2023-01-27" + }, + "description": "Cardinal is a code that automates the workflow for iteratively solving neutral particle transport via the OpenMC code and computational fluid dynamics via the NekRS code within the Multiphysics Object Oriented Simulation Environment (MOOSE), a finite element framework for solving general partial differential equations. Cardinal establishes a mapping between the Monte Carlo geometry representation used in OpenMC and the spectral element mesh used in NekRS to other physics applications built upon the MOOSE framework, allowing high-resolution particle transport and fluid dynamics physics feedback to the MOOSE application ecosystem. Heat generation rates as solved by OpenMC are used as heat sources in MOOSE, while the temperature and density fields from NekRS are used as conjugate heat transfer boundary conditions and/or source fields in MOOSE. OpenMC, Nek5000, and MOOSE are open source, community-developed simulation codes.", + "laborHours": 0.0, + "languages": [], + "name": "CARDINAL", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/neams-th-coe/cardinal", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Building Re-tuning Simulator (BRS) is a Re-tuning focused modeling and building automation system simulation environment.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Building Re-tuning Simulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-02-01", + "metadataLastUpdated": "2023-02-06" + }, + "description": "OEDI-SI (formerly known as GADAL (Grid Algorithms and Data Analytics Library)) provides a library for connecting Algorithms and Datasets in a co-simulation framework can be found at the following URLS: https://github.com/openEDI/GADAL; https://github.com/openEDI/sgidal-example; https://github.com/openEDI/gadal-ieee123", + "laborHours": 0.0, + "languages": [], + "name": "Open Energy Data Initiative \u2013 Systems Integration (OEDI-SI) f/k/a GADAL (Grid Algorithms and Data Analytics Library) [SWR-22-86]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openEDI/gadal-ieee123", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-02", + "metadataLastUpdated": "2023-02-07" + }, + "description": "PSUADE (Problem Solving testbed for Uncertainty Analysis and Design Exploration) is a mathematical software useful for performing uncertainty quantification and sensitivity analysis.", + "laborHours": 0.0, + "languages": [], + "name": "PSUADE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.1" + }, + { + "contact": { + "email": "passarellals@ornl.gov" + }, + "date": { + "created": "2023-02-06", + "metadataLastUpdated": "2023-02-06" + }, + "description": "This model uses an unsupervised sentence encoder proposed by Liu et al. (2021) to create better sentence representations for the SPECTER transformer model.", + "laborHours": 0.0, + "languages": [], + "name": "mirror-SPECTER", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://huggingface.co/Linseypass/mirror-SPECTER", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "jcreed2@ncsu.edu" + }, + "date": { + "created": "2023-02-07", + "metadataLastUpdated": "2023-02-08" + }, + "description": "This project is a code base for a tethered energy-harvesting kite system, that is able to operate in both a water or wind environment. The project is broken into: Classes - containing classes for things such as the kite, the environment, the flight controller, the tethers, ect. Compositions - contains simulink block diagrams for using instances of the classes, for things such as the kite, the environment, the flight controller, the tethers, ect. Units - basically Simulink library files used in many places to perform fundamental operations Master Simulink model - where all the compositions are run together Test scripts - scripts to run the master Simulink model under various conditions The key components of the model are the kite vehicle, the tethers, the ground station, the environment, the flight controller, and high level controllers.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Simulink" + ], + "name": "Ocean Kite Project", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NCSUCORE/DoEOceanKiteProject/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NCSUCORE/DoEOceanKiteProject.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kallander2@llnl.gov" + }, + "date": { + "created": "2023-02-07", + "metadataLastUpdated": "2023-02-17" + }, + "description": "Trestles is a modified H.264 decoder that allows access to the uncompressed transformed residual pixel and motion vector values that are contained (in compressed form) in the H.264 NAL units (a.k.a. video bitstream).", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Trestles", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/trestles", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "kentpr@ornl.gov" + }, + "date": { + "created": "2023-02-08", + "metadataLastUpdated": "2023-02-08" + }, + "description": "QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support.", + "laborHours": 0.0, + "languages": [ + "C++17" + ], + "name": "QMCPACK v3.16.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/NCSA", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QMCPACK/qmcpack/releases/tag/v3.16.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v3.16.0" + }, + { + "contact": { + "email": "spannausat@ornl.gov" + }, + "date": { + "created": "2023-02-08", + "metadataLastUpdated": "2023-08-22" + }, + "description": "The National Cancer Institute (NCI) monitors population level cancer trends as part of its Surveillance, Epidemiology, and End Results (SEER) program. This program consists of state or regional level cancer registries which collect, analyze, and annotate cancer pathology reports. From these annotated pathology reports, each individual registry aggregates cancer phenotype information and summary statistics about cancer prevalence to facilitate population level monitoring of cancer incidence. Extracting cancer phenotype from these reports is a labor intensive task, requiring specialized knowledge about the reports and cancer. Automating this information extraction process from cancer pathology reports has the potential to improve not only the quality of the data by extracting information in a consistent manner across registries, but to improve the quality of patient outcomes by reducing the time to assimilate new data and enabling time-sensitive applications such as precision medicine. Here we present FrESCO: Framework for Exploring Scalable Computational Oncology, a modular deep-learning natural language processing (NLP) library for extracting pathology information from clinical text documents.", + "laborHours": 0.0, + "languages": [], + "name": "FrESCO", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DOE-NCI-MOSSAIC/FrESCO", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v0.2.3" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-02-09", + "metadataLastUpdated": "2023-03-08" + }, + "description": "To more effectively and completely convert STIX1 data to STIX2.", + "laborHours": 0.0, + "languages": [], + "name": "Enhanced_STIX_Elevator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/idaholab/Enhanced_STIX_Elevator/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Enhanced_STIX_Elevator", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-02-09", + "metadataLastUpdated": "2023-03-13" + }, + "description": "Resilience of Microgrids with Adaptive capacity and Inertia calculates the maximum size of a disturbance a microgrid could withstand before frequency limits are violated. The results are based on power generation assets in the microgrid and its inertia.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Resilience Of Microgrids With Adaptive Capacity And Inertia", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/ReMAIn", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wanh@ornl.gov" + }, + "date": { + "created": "2023-02-13", + "metadataLastUpdated": "2023-02-13" + }, + "description": "ASHRAE Standard 205 - Heat Pump Design Model supply; This package helps OEMs to convert HPDM output files to STD 205 format; it also provides some RS sample tables.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HPDM-STD205", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/HPDM-STD205", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-15", + "metadataLastUpdated": "2023-02-15" + }, + "description": "Hermes-3 is a plasma simulation model built on BOUT++, developed as part of research studies of the edge and divertor regions of magnetically confined fusion plasmas such as tokamaks. The main purpose of this model is multi-species simulation of plasmas containing a mixture of deuterium, tritium, helium and other plasma and neutral gas species.", + "laborHours": 0.0, + "languages": [], + "name": "Hermes-3", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bendudson/hermes-3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-02-16", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Stitch is a new IO library focused around supporting simulations where only a small portion of the simulation space changes at each timestep. It improves storage efficiency by only storing the changed data and constructs on request a view of an arbitrary region at a given time by stitching together parts of various outputs. This enables scaling from a single process to 100s of nodes. The earlier version performance of the library as the data size scaled was too slow. Changes were made to improve the performance by a factor of about 30x in the production applications. 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We find that although a surprising degree of transfer is possible between certain do- mains, it is not so successful between others. 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This collection of tools has been built into an R package for easy use at LANL and in the probabilistic numerics community.", + "laborHours": 0.0, + "languages": [], + "name": "gpde", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/gpde", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-02-24", + "metadataLastUpdated": "2023-02-24" + }, + "description": "This software contains the code for Bayesian uncertainty analysis of global lake area. Computed uncertainties are compared against more conventional estimation using lake size-abundance distributions. 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This project includes a template WAVES modsim repository which is used for the tutorials and for integration and regression testing of the WAVES extensions to SCons.", + "laborHours": 0.0, + "languages": [], + "name": "WAVES: WAVES Analysis for Verified Engineering Simulatio", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/waves", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "mazeauej@ornl.gov" + }, + "date": { + "created": "2023-02-27", + "metadataLastUpdated": "2023-02-27" + }, + "description": "[Atomic Simulation Environment](https://wiki.fysik.dtu.dk/ase/): A Python library for working with atoms", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ase", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ase/ase", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-28", + "metadataLastUpdated": "2023-02-28" + }, + "description": "DeltaUQ is a PyTorch library for uncertainty quantification with deep neural networks. 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Is there", + "laborHours": 0.0, + "languages": [], + "name": "nvidia dataframe library patch to support parquet indexing", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rapidsai/cudf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-28", + "metadataLastUpdated": "2023-02-28" + }, + "description": "MetallData is an HPC platform for interactive data science applications at HPC-scales. 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Wintap can support a wide variety of applications across production operations, cyber security operations, and cyber security research.", + "laborHours": 0.0, + "languages": [], + "name": "Wintap", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Wintap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "6.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-01", + "metadataLastUpdated": "2023-03-01" + }, + "description": "This code provides fast Gaussian process prediction algorithms based on the MuyGPs scalable hyperparameter optimization algorithm. 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Such an effort that brings in more developers to use and contribute to lab software can further improve the quality of the software, and developer experience at the lab. 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This work was not funded by, nor was any work performed under any DOE contract.", + "laborHours": 0.0, + "languages": [ + "Bash", + "C", + "Python" + ], + "name": "Klippy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Laikulo/klippy-tooling", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.11.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-07", + "metadataLastUpdated": "2023-03-07" + }, + "description": "LaSDI is a data-driven physical simulation software that forms a latent space for a given high-fidelity model and discovers a set of ordinary differential equations for the latent space dynamics. 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A concept of local dynamics identification procedure is introduced to enable a parametric model, which enhances the accuracy level over a given parameter space.", + "laborHours": 0.0, + "languages": [], + "name": "Latent Space Dynamics Identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LaSDI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-07", + "metadataLastUpdated": "2023-06-23" + }, + "description": "GENTANGLE is a high performance containerized pipeline for the computational design of two overlapping genes translated in different reading frames of the genome that can be used to design and test gene entanglements for new microbial engineering projects using arbitrary sets of user specified gene pairs.", + "laborHours": 0.0, + "languages": [], + "name": "Gene Tuples ArraNGed in overLapping Elements", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BiosecSFA/gentangle", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-07", + "metadataLastUpdated": "2023-10-20" + }, + "description": "Operational Forecasting of Induced Seismicity (ORION) is an open-source toolkit developed as part of the US Department of Energy SMART and NRAP programs. ORION is designed to help both expert and non-expert users understand the seismic hazard at a site. This tool analyzes how the seismic hazard evolves during injection of fluid, and can be used to identify potential mitigation strategies for observed or forecasted seismic activity. ORION is built using Python, and has an optional GUI where users can easily configure model parameters, evaluate temporal and spatial forecasts, and inspect key data (seismicity, fluid injection, pressure models, etc.).", + "laborHours": 0.0, + "languages": [], + "name": "Operational Forecasting of Induced Seismicity", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NRAP/orion", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "0.5" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-03-08", + "metadataLastUpdated": "2023-09-18" + }, + "description": "Thermal tank model that accounts for phase change of the tank medium.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "pytank (Python Thermal Tank Model) [SWR-22-76]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ThermalTank", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-03-10", + "metadataLastUpdated": "2024-01-29" + }, + "description": "The demand-side grid model harnesses decades of sector-specific energy modeling expertise to understand current and future U.S. electricity load for power systems analyses. The API provides tools for submitting datasets to dsgrid projects, validating individual datasets and project data as a whole, querying, analysis, and visualization.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook", + "Shell" + ], + "name": "dsgrid (Demand-Side Grid Toolkit) [SWR-21-52]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dsgrid/dsgrid", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-13", + "metadataLastUpdated": "2023-03-13" + }, + "description": "SF-23-005 PyOED is a highly extensible scientific package that enables developing and testing model-constrained optimal experimental design (OED) for inverse problems. Specifically, PyOED aims to be a comprehensive Python toolkit for model-constrained OED. The package targets scientists and researchers interested in understanding the details of OED formulations and approaches. It is also meant to enable researchers to experiment with standard and innovative OED technologies with a wide range of test problems (e.g., simulation models). OED, inverse problems (e.g., Bayesian inversion), and data assimilation (DA) are closely related research fields, and their formulations overlap significantly. Thus, PyOED is continuously being expanded with a plethora of Bayesian inversion, DA, and OED methods as well as new scientific simulation models, observation error models, and observation operators. These pieces are added such that they can be permuted to enable testing OED methods in various settings of varying complexities. The PyOED core is completely written in Python and utilizes the inherent object-oriented capabilities; however, PyOED is meant to be extensible rather than scalable. Specifically, PyOED is developed to ``enable rapid development and benchmarking of OED methods with minimal coding effort and to maximize code reutilization.'' PyOED will be continuously expanded with a plethora of Bayesian inversion, DA, and OED methods as well as new scientific simulation models, observation error models, and observation operators.", + "laborHours": 0.0, + "languages": [], + "name": "PYOED: AN ETENSIBLE SUITE FOR DATA ASSIMILATION AND MODEL-CONSTRAINED OPTIMAL DESIGN OF EXPERIMENTS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ahmedattia/pyoed", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-13", + "metadataLastUpdated": "2023-03-14" + }, + "description": "SF-22-160 Elastemp is a software to obtain the quasi-harmonic temperature dependent elastic constants of material. Elastemp integrates with VASP quantum-mechanical simulation package and with Phonopy package to perform dynamic calculations. Elastemp is capable of creating symmetry dependent deformations, run static and dynamic calculations to obtain the helmholtz energies from which quasi-harmonic temperature dependent elastic constants are obtained.", + "laborHours": 0.0, + "languages": [], + "name": "ELASTEMP", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Karthik-Balas/elastemp", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-13", + "metadataLastUpdated": "2023-03-14" + }, + "description": "SF-22-156 Machine learning (ML) models and applications in materials design and discovery typically involve the use of feature representations or descriptors followed by a learning algorithm that maps them to user desired properties of interest. Most popular mathematical formulation-based descriptors are not unique across atomic environments and suffer from transferability issues across different application domains and/or material classes. The CEGANN code provides a unified interface to facilitate material characterization across materials across multiple scales (from atomic to mesoscale) and diverse classes of materials ranging from metals oxides, non-metals, and even hierarchical materials such as zeolites and semi ordered materials such as mesophases. CEGANN implements a Graph Attention Network (GAT) type convolution architecture. The details of network architecture can be found in the paper https://doi.org/10.48550/arXiv.2207.10168. The software comes with pretrained examples and dataset for the classification of the following representative systems: (1) Structure-level representation such as space group (2) Structural dimensionality (e.g., bulk, 2D, clusters etc.) (3) Grain boundary identification (4) Nucleation and growth of a zeolite polymorph (5) Characterization of binary mesophases and their phase transitions (6) Growth of ice. The code is written in python programming language.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "CEGANN: CRYSTAL EDGE GRAPH ATTENTION NEURAL NETWORK", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sbanik2/CEGANN", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-03-13", + "metadataLastUpdated": "2023-03-13" + }, + "description": "MALAMUTE combines MOOSE module functionality with realistic materials and geometries for arbitrary-Eulerian-Lagrangian (ALE) and level-set based laser melting and welding applications and electric-field assisted sintering (EFAS) applications.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "idaholab/malamute", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/malamute", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2023-03-14" + }, + "description": "SF-22-157 NEML2 is an extension of an earlier open source code developed at ANL (SF-xxxx) called NEML. These libraries provide tools for constructing and using models of engineering materials, with a focus on high temperature materials for nuclear reactor applications. The software include tools for setting up material models, calibrating models, storing models for later use in other simulations, and running simple \"material point\" simulations of the material behavior. The main difference between NEML and NEML2 is the new software has been complete restructured to run on GPUs and other accelerators in order to improve the performance of methods used to train constitutive models against data and to improve the performance of the final models in production environments, like finite element software. While over time we expect NEML2 to become more-or-less feature complete with NEML we are filing a new software disclosure because (1) the library has been complete restructured and (2) we want to host NEML2 in a separate repository.", + "laborHours": 0.0, + "languages": [], + "name": "NEML2 - THE NEW ENGINEERING MATERIAL MODEL LIBRARY, VERSION 2", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/reverendbedford/neml2", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2023-03-14" + }, + "description": "GSAS-II is a comprehensive data analysis and simulation software package for determining atomistic structures from single-crystal and powder diffraction data. X-ray, neutron and electron data may be used. Constant-wavelength, time-of-flight and pink-beam sources may be employed and analyses may combine different types of data. The package is oriented towards materials characterization problems, but protein crystallography, pair-distribution function analysis, small-angle scattering and reflectometry analysis are all included. GSAS-II provides tools for indexing and solving structures from powder diffraction data, in addition to structure, data and results visualization tools", + "laborHours": 0.0, + "languages": [], + "name": "GSAS-II (GENERAL STRUCTURE AND ALAYSIS SYSTEM-II)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://subversion.xray.aps.anl.gov/pyGSAS/trunk", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2023-03-14" + }, + "description": "SF-22-136 Deep learning has been shown as a successful method for various tasks, and its popularity results in numerous open-source deep learning software tools. Deep learning has been applied to a broad spectrum of scientific domains such as cosmology, particle physics, computer vision, fusion, and astrophysics. Scientists have performed a great deal of work to optimize the computational performance of deep learning frameworks. However, the same cannot be said for I/O performance. As deep learning algorithms rely on big-data volume and variety to effectively train neural networks accurately, I/O is a significant bottleneck on large-scale distributed deep learning training. DLIO, is a novel representative benchmark suite built based on the I/O profiling of the selected workloads. DLIO can be utilized to accurately emulate the I/O behavior of modern deep learning applications. Using DLIO, application developers and system software solution architects can identify potential I/O bottlenecks in their applications and guide optimizations to boost the I/O performance leading to lower training times. The storage vendor can also use DLIO as a guide for designing and optimize the storage and filesystem targeting at deep learning application.", + "laborHours": 0.0, + "languages": [], + "name": "DLIO: A DATA-CENTRIC BENCHMARK FOR DEEP LEARNING APPLICATIONS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/argonne-lcf/dlio_benchmark", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A topology-based anomaly detection tool for temporal varying data. The input is json or CSV formatted data with a timestamp field identified. The algorithm computes vectorizations (using a vectorization config file) of time windows of data and computes a topological measure of anomalousness. The output is a sequence of anomaly scores for each time window", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/PHANTOM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/PHANTOM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Interconnection Innovation e-Xchange (i2x) Test Systems allows for scripted customizations of social behavior, recovery operations, investment decisions, and metrics in a simplified Python module. Public test systems allow for replication of results by other stakeholders", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/i2x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/i2x", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2023-03-14" + }, + "description": "SF-22-121 Graph convolutional neural networks (GCNN) are powerful machine learning models that apply a message-passing algorithm on adjacent nodes in a graph. Due to the natural representation of molecules via discrete graphs (where nodes encode atoms and edges encode bonds), GCNNs are an intuitive machine learning model chemical space informatics, including the prediction of polymer properties. Here, molecules are represented in feature and adjacency matrices where they are directly used as inputs to a GCNN.", + "laborHours": 0.0, + "languages": [], + "name": "GRAPH CONVOLUTIONAL NEURAL NETWORK (GCNN)FOR POLYMER PROPERTY PREDICTION", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AI4Plastics/AI4Plastics", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "luh1@ornl.gov" + }, + "date": { + "created": "2023-03-15", + "metadataLastUpdated": "2023-03-15" + }, + "description": "This is an opensource library for benchmarking the system's GPU mixed precision capabilities. The software calculates solution of the system of linear equation in 64bit accuracy using mixed precision techniques and iterative refinement. Original benchmark designed is done by ICL, and it is name HPL-MxP (HPL-AI)", + "laborHours": 0.0, + "languages": [ + "C++", + "C" + ], + "name": "OpenMxP-Opensource Mixed Precision Computing", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/at-aaims/openMxP", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-03-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Locally Competitive Algorithm (LCA) is a dynamical sparse solver that uses only local computations, allowing for massively parallel implementations on compatible neuromorphic architectures such as Intel's Loihi research chip. In this invention, we show how unsupervised dictionary learning with spiking LCA can be implemented on GPUs and Intel's Loihi research chip.", + "laborHours": 0.0, + "languages": [], + "name": "LCA", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/LCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-17", + "metadataLastUpdated": "2023-03-17" + }, + "description": "SF-22-099 Pressure-film Open Source Scanning and Mapping (POSSM) is software that analyses images of pressure-film (scans or photographs). POSSM collects data from that analysis in order to produce a number of visual aides, including pressure maps, histograms, and 3d surface plots. POSSM is designed to be able to analyze an entire folder full of images, exporting numeric data as .csv files and visual graphics as .png files.", + "laborHours": 0.0, + "languages": [], + "name": "PRESSURE-FILM OPEN SOURCE SCANNING AND MAPPING", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PatrickGrider/POSSM", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lagergrenjh@ornl.gov" + }, + "date": { + "created": "2023-03-20", + "metadataLastUpdated": "2023-03-21" + }, + "description": "In this work, we use few-shot learning to segment the body and vein architecture of Populus trichocarpa leaves from high-resolution scans obtained in the UC Davis common garden. Leaf and vein segmentation are formulated as separate tasks, in which convolutional neural networks (CNNs) are used to iteratively expand partial segmentations until reaching stopping criteria. Our leaf and vein segmentation approaches use just 50 and 8 manually traced images for training, respectively, and are applied to a set of 2,634 top and bottom leaf scans. We show that both methods achieve high segmentation accuracy, in some cases exceeding even human-level segmentation. The leaf and vein segmentations are subsequently used to extract 68 morphological traits using traditional open-source image processing tools, which are validated using real-world physical measurements. For a biological perspective, we perform a genome-wide association study using the \"vein density\" trait to discover novel genetic architectures associated with multiple physiological processes relating to leaf development and function. In addition to sharing all of the few-shot learning code, we are releasing all images, manual segmentations, model predictions, 68 extracted leaf phenotypes, and a new set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Few-shot leaf segmentation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jlager/few-shot-leaf-segmentation", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-03-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Home of PoolDilutionR, a package for easily calculating gross rates from isotope pool dilution data.", + "laborHours": 0.0, + "languages": [ + "R" + ], + "name": "COMPASS-DOE/PoolDilutionR", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/COMPASS-DOE/PoolDilutionR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-21", + "metadataLastUpdated": "2023-03-21" + }, + "description": "This is a variant of LaSDI where it minimizes both reconstruction loss terms of auto encoder and dynamics regression loss terms simultaneously. Plus, an active learning framework is adopted so that a physics-informed greedy sampling point can be added to enhance the performance of gLaSDI. It is written in python and several examples are included in this software.", + "laborHours": 0.0, + "languages": [], + "name": "Greedy Latent Space Dynamics Identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gLaSDI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "datepa@ornl.gov" + }, + "date": { + "created": "2023-03-22", + "metadataLastUpdated": "2023-03-28" + }, + "description": "A matrix-based simulator for neuromorphic computing.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ORNL/superneuro-mat", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/superneuromat", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "gunaratnecs@ornl.gov" + }, + "date": { + "created": "2023-03-22", + "metadataLastUpdated": "2023-03-28" + }, + "description": "A GPU-based multi-agent simulation framework for neuromorphic computing", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SuperNeuroABM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/superneuroabm", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-27", + "metadataLastUpdated": "2023-03-27" + }, + "description": "Productivity Frameworks for HPC will include container recipes, build recipes, continuous integration scripts, and other software aimed at testing the portability of containerized HPC software across platforms and interconnects. In particular, it tests the utility of bind-mounting at the MPI layer (rather than the underlying fabric layer) to leverage a standardized protocol and avoid various technical debt and vendor lock-in. Since MPIs are often ABI-incompatible, trampolines such as the open-source Wi4MPI will be tested when such cases arise.", + "laborHours": 0.0, + "languages": [], + "name": "Productivity frameworks for HPC", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/productivity-frameworks", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-03-28", + "metadataLastUpdated": "2023-03-29" + }, + "description": "The UEDGE Toolbox supplies an object-based interface and a wide array of tools used for running and analyzing UEDGE simulations. The toolbox provides routines for setting up UEDGE cases using YAML input files, shorthand commands for restoring converged solutions, as well as plotting profiles and surface plots of any of the parameters in UEDGE. Furthermore, the toolbox provides the necessary objects for compiling and analyzing parameter scans consisiting of several UEDGE simulations.", + "laborHours": 0.0, + "languages": [], + "name": "UEDGE toolbox", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/UETOOLS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-29", + "metadataLastUpdated": "2023-03-29" + }, + "description": "Linux kernel driver for the Cray ClusterStor E1000 NVMe slot LEDs. This driver allows us to set the 'fault' and 'locate' LEDs on a CrayE1000 slot to indicate which drive has failed. Is there", + "laborHours": 0.0, + "languages": [], + "name": "Linux kernel driver for Cray ClusterStor E1000 NVMe slot LEDs", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tonyhutter/e1000_nvme_led", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-03-30", + "metadataLastUpdated": "2023-05-08" + }, + "description": "Recently, numerous data-driven approaches to control an electric grid using machine learning techniques have been investigated. With the advancement of reinforcement learning (RL) based techniques, gradually the conventional optimization based solvers are being replaced with RL approach where there is uncertainty in the environment such as renewable generation or cyber system emulation. However, to train an agent efficiently, it requires numerous interactions with an environment to learn the best policies. There are numerous RL environments for the power systems based on some well-known simulators, similarly there are environment for communication domains. While majority of the cyber emulators are based in an UNIX environment, the power simulators are based in the Windows-based operating system, the generation of cyber-physical mixed domain RL environment has been challenging. Existing co-simulation methods are efficient but resource and time intensive to generate large scale data set for training RL agents. Hence, this software focuses on development and validation of a mixed domain RL environment using Open DSS for the physical side and leverages a discrete event simulator python package, SimPy, for cyber-side emulation which is Operating Systems agnostic. Further utilizing this software co-simulation and training RL agents for re-routing based resilient control for network reconfiguration and volt-var control in power distribution feeder are performed.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DSS-SimPy-RL (Open-DSS and SimPy based Cyber-Physical RL environment) [SWR-23-29]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DSS-SimPy-RL", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-03-30", + "metadataLastUpdated": "2023-04-06" + }, + "description": "Accurate energy forecasting is becoming critical due to many reasons: i ) optimal distributed energy resources operations and dispatch, ii) fault detection and diagnostics, and iii) meeting operational energy efficiency targets. Wattile uses deep learning (DL) for the building's short-term load forecasting application. Two specific types of neural networks called, Long Short Term Memory (LSTM) and Sequence-to-Sequence (S2S) models are used to make predictions. Forecasting models are trained using online historical weather and occupancy indicator data streams from the Intelligent Campus Program's data acquisition systems at the National Renewable Energy Laboratory (NREL) for main meters and sub-meters of multiple building types. These models use probabilistic methods to provide quantile-based forecasts in addition to nominal conditional median predictions of electricity consumption.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "Wattile: Probabilistic Deep Learning-based Forecasting of Building Energy Consumption [SWR-20-94]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Wattile", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-03-31", + "metadataLastUpdated": "2023-03-31" + }, + "description": "xCDAT is an extension of xarray for climate data analysis on structured grids. It serves as a modern successor to the Community Data Analysis Tools (CDAT) library. Xarray is an \"open source project and Python package that introduces labels in the form of dimensions, coordinates, and attributes on top of raw NumPy-like arrays, which allows for more intuitive, more concise, and less error-prone user experience. Xarray includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures\" (source: https://xarray.dev/). The goal of xCDAT is to provide generalizable features and utilities for simple and robust analysis of climate data. xCDAT's design philosophy is focused on reducing the overhead required to accomplish certain tasks in xarray. Some key xCDAT features are inspired by or ported from the core CDAT library, while others leverage powerful libraries in the xarray ecosystem (e.g., xESMF and cf_xarray) to deliver robust APIs.", + "laborHours": 0.0, + "languages": [], + "name": "Xarray Climate Data Analysis Tools", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xCDAT/xcdat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.5.0" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-04-04", + "metadataLastUpdated": "2023-04-04" + }, + "description": "The ezAlign is aimed at clustering coarse grain simulation to find common or uncommon occurrences and convert coarse (CG) grained coordinate and topology files to atomistic formats. We use a PointNet based approach to map individual frames of simulation to points in a latent space. These points are then clustered using a variety of clustering methods. Clusters are analyzed to associate them with states in the simulation. Frames can be chosen from these clusters based on proximity to cluster centers. ezAlign takes CG coordinate and topology files and converts and outputs their corresponding atomistic formats using an alignment and relaxation procedure. ezAlign is designed to convert complex, solvated biological systems including lipid membranes with drug-like molecules using GROMACS. A GROMACS checkpoint (.cpt) file is also outputted to enable continuation simulations that retain the equilibrated atomic velocities. Independent atomistic coordinates and topologies for every molecule must already be included in ezAlign/files. A number of commonly simulated biological molecules are currently provided.", + "laborHours": 0.0, + "languages": [], + "name": "ezAlign", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ezAlign", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "morelandkd@ornl.gov" + }, + "date": { + "created": "2023-04-04", + "metadataLastUpdated": "2023-04-05" + }, + "description": "VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures. VTK-m supports the fine-grained concurrency for data analysis and visualization algorithms required to drive extreme scale computing by providing abstract models for data and execution that can be applied to a variety of algorithms across many different processor architectures.", + "laborHours": 204652.8, + "languages": [ + "C++" + ], + "name": "VTK-m v. 2.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk-m", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "2.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-04-05", + "metadataLastUpdated": "2023-11-27" + }, + "description": "EMF Biomass Data Interpreter was developed for the transportation team of the Energy Modeling Forum (EMF) 37: Deep Decarbonization and High Electrification Scenarios for North America project. It parses results from different modeling groups to show how biomass might be employed under electrification.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "EMF Biomass Data Interpreter [SWR-23-06]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMF_Data_Interpreter", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-04-06", + "metadataLastUpdated": "2023-04-06" + }, + "description": "GHEDesigner is a Python package for designing ground heat exchangers (GHE) used with ground source heat pump (GSHP) systems.", + "laborHours": 0.0, + "languages": [ + "PYTHON" + ], + "name": "GHEDesigner [SWR-23-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BETSRG/GHEDesigner", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-04-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "NetViz is an app built to visualize communication and power networks. Developed under the CINDER project at PNNL.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Netviz", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Netviz", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-04-13", + "metadataLastUpdated": "2023-04-13" + }, + "description": "The AMG2023 benchmark solves two diffusion problems with a linear solver preconditioned with algebraic multigrid. The code only contains a driver, a Makefile, and a documentation file. It requires an installation of the open source software library hypre that needs to be downloaded elsewhere and is not included here. Its purpose is to benchmark linear solver performance on high performance computers.", + "laborHours": 0.0, + "languages": [], + "name": "AMG2023", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AMG2023", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-04-13", + "metadataLastUpdated": "2023-04-13" + }, + "description": "This code along with the included data allows users to train machine learning models on network packet data.", + "laborHours": 0.0, + "languages": [], + "name": "IdahoLabResearch/INLIDD", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/INLIDD", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-04-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This research code base includes functions to compute statistics of image distributions in (spatial DFT) frequency space, train deep learning image classifiers on these distributions with variable depth and weight decay, and finally measure the sensitivity of the trained models to perturbations along (spatial DFT) frequency components.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/frequency_sensitivity", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/frequency_sensitivity", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-04-14", + "metadataLastUpdated": "2023-11-01" + }, + "description": "The Xyce Parallel Electronic Simulator simulates electronic circuit behavior in DC, AC, HB, MPDE and transient mode using standard analog (DAE) and/or device (PDE) device models including several age and radiation aware devices. It supports a variety of computing platforms (both serial and parallel) computers. Lastly, it uses a variety of modern solution algorithms dynamic parallel load-balancing and iterative solvers.! ! Xyce is primarily used to simulate the voltage and current behavior of a circuit network (a network of electronic devices connected via a conductive network). As a tool, it is mainly used for the design and analysis of electronic circuits.! ! Kirchoff's conservation laws are enforced over a network using modified nodal analysis. This results in a set of differential algebraic equations (DAEs). The resulting nonlinear problem is solved iteratively using a fully coupled Newton method, which in turn results in a linear system that is solved by either a standard sparse-direct solver or iteratively using Trilinos linear solver packages, also developed at Sandia National Laboratories.", + "laborHours": 0.0, + "languages": [ + "C++", + "Perl", + "Python" + ], + "name": "Xyce(\u2122) Parallel Electronic Simulator v.7.6", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Xyce/Xyce", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "7.6" + }, + { + "contact": { + "email": "kerteszv@ornl.gov" + }, + "date": { + "created": "2023-04-19", + "metadataLastUpdated": "2023-04-19" + }, + "description": "Support for the following electrochemical techniques: \u00b7 cyclic voltammogram (CV) \u00b7 linear sweep voltammogram (LSV) \u00b7 differential pulse voltammogram (DPV) \u00b7 chronoamperometry (CA) Specific application: low-cost DIY potentiostat, demonstrating electrochemistry in the educational sector", + "homepageURL": "https://u.pcloud.link/publink/show?code=XZyeQqVZWfpzv3qm0HJ40WFUBDEmzhUcJfP7", + "laborHours": 0.0, + "languages": [ + "Delphi/Object Pascal" + ], + "name": "HunStat v4.10", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://u.pcloud.link/publink/show?code=XZyeQqVZWfpzv3qm0HJ40WFUBDEmzhUcJfP7", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "4.10" + }, + { + "contact": { + "email": "radercd@ornl.gov" + }, + "date": { + "created": "2023-04-24", + "metadataLastUpdated": "2023-04-24" + }, + "description": "Boiler tubes in steam power plants experience tube blockages due to exfoliation of oxide grown on the inner side of the tubes. In extreme cases, significant tube blockages can lead to forced power plant outages. It is thus desired to predict through modeling the amount of tube blockage in order to inform power plant operators of possible forced outages. SpalLoop solves for the stress-strain equations in an axisymmetric geometry, tracking the stress/strain evolution during boiler operation including outages for the entire boiler tube length. At each operational outage, i.e., temperature excursions down to room temperature, the amount of exfoliated area for the entire tube loop is estimated the amount of tube blockage is predicted based assumed blockage geometry and site. The SpaLLoop code contains modules developed for oxide growth, stress analysis, tube loop geometry, blockage area by taking into account the following phenomena and features, (a) Plant operation schedule with periodic alternate full-load and partial-load regimes and shut-downs, i.e., temperature excursions from high-load to room temperature, (b) axisymmetric formulation for cylindrical tubes, (c) oxide growth in a temperature gradient with multiple oxide layers, (d) geometry of a boiler tube with a single tube loop or two tube loops, (e) temperature variation along the tube length based on hot gas temperature distribution outside the tube and inlet steam temperature, (f) non-uniform oxide growth along the tube length according to the local steam tube temperature, (g) exfoliated area module: at each operational outage considered, the amount of exfoliated area and exfoliated volume along the tube is estimated, (h) blockage module: at each operational outage considered, the exfoliated volume/mass for each tube loop is estimated from which the amount of tube blockage is predicted based on given blockage geometry (length, location, and geometry). The computer program is written in FORTRAN90. Its modular structure was sought for allowing the best flexibility in updating the program by implementing new constitutive equations due to availability of new material property data and/or new physical phenomena.", + "laborHours": 0.0, + "languages": [ + "Fortran90" + ], + "name": "SPALLOOP", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/adisoft17/spallop/blob/master/License_Spalloop_OpenSourceSoftware_ORNL.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/adisoft17/spallop", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-04-24", + "metadataLastUpdated": "2023-04-24" + }, + "description": "CMEC driver is a command line tool that runs earth system evaluation modules.", + "laborHours": 0.0, + "languages": [], + "name": "CMEC driver", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmecmetrics/cmec-driver", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.1.9" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "Geospatial Analysis Pipelines (GAPs) is a framework designed to scale single-location geospatial models to a High-Performance Computing (HPC) environment.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "GAPs (Geospatial Analysis Pipelines)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/gaps", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-05-03" + }, + "description": "Multiverse is a code repository for a set of tools for Bayesian model selection for neural networks. The goal of the tools is to provide capabilities for selecting among prior and model specifications for Bayesian neural networks. Multiverse will include tools for creating Bayesian neural networks, evaluating the Bayesian model evidence, and performing inference in Bayesian neural networks. These components are written in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning and signal processing.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Multiverse: Bayesian model selection for neural networks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "The software is code for analyzing, debugging, and solving optimization models. The code implements several algorithms and provides convenient APIs to apply these algorithms to optimization models. The algorithms are primarily based on graph theory. They compute well-known partitions of graphs, and use these partitions to provide the user information about their optimization model, including diagnosing certain types of structural modeling errors. Some algorithms may be used as a subroutine to solve an optimization problem, and may call an optimization solver to facilitate this. Well-known linear algebra routines are called to provide further diagnostics. The software contains no data and no models other than toy models used for testing.", + "laborHours": 0.0, + "languages": [], + "name": "Tools for analysis of optimization models", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/JuMPIn.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "DEPDOSE is an open-source computer application which combines the KDEP respiratory tract deposition software with committed equivalent dose coefficient tables from the DC_PAK internal dosimetry package. DEPDOSE allows the user to rapidly produce tables of dose coefficients to workers and members of the public inhaling a precisely defined, user-specified aerosols using the ICRP 60 series methodology. Combined with a plume dispersion modeling system such as QUIC, this makes it possible to predict radiation doses downstream from an accidental or intentional release of radioactive materials. For this work, a radioactive plume was calculated to members of the public downstream from a plausible release of radionuclides into the atmosphere.", + "laborHours": 0.0, + "languages": [], + "name": "DEPDOSE", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/DEPDOSE", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "shasta wrapper was written as an interface with which to manage clusters running CSM (Cray System Management) with the purpose being: * Showcase the shortcomings of the provided Cray System Management software to the vendor * Provide practical and easy to use tool to manage a clsuter running Cray System Management", + "laborHours": 0.0, + "languages": [], + "name": "Shasta Wrapper", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/shasta_wrapper", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-05-03" + }, + "description": "FIERRO is a parallel C++ code designed to simulate fluid mechanics, heat transfer, and solid mechanics in two- and three-dimensional space. 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The micromechanical solvers can also help research efforts create continuum-scale constitutive models for solids, as a function of the microstructure, in situ in a calculation or in a stand-alone manner. No physical data exists within the code.", + "laborHours": 0.0, + "languages": [], + "name": "Fierro Version 2.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Fierro", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "2.x" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "MATAR is a C++ software library to allow developers to easily create and use dense and sparse data representations that are also portable across disparate architectures using Kokkos.", + "laborHours": 0.0, + "languages": [], + "name": "Matrix and Array (MATAR) Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MATAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stewartsl@ornl.gov" + }, + "date": { + "created": "2023-04-27", + "metadataLastUpdated": "2023-04-27" + }, + "description": "The Interactive Corpus Analysis Tool (ICAT) is an interactive machine learning dashboard for unlabeled text/natural language processing datasets that allows a user to iteratively and visually define features, explore and label instances of their dataset, and simultaneously train a logistic regression model. ICAT was created to allow subject matter experts in a specific domain to directly train their own models for unlabeled datasets visually, without needing to be a machine learning expert or needing to know how to code the models themselves. This approach allows users to directly leverage the power of machine learning, but critically, also involves the user in the development of the machine learning model.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Interactive Corpus Analysis Tool", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/icat", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "brownjm@ornl.gov" + }, + "date": { + "created": "2023-04-27", + "metadataLastUpdated": "2023-04-27" + }, + "description": "Julia language version of the SAMMY R-matrix code", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "Jammy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/brownjm1968/Jammy", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-04-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Python tool for determination of lipid double bond locations from OzID data", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-m-q/lipidoz", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-m-q/lipidoz", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "xuanji.yu@case.edu" + }, + "date": { + "created": "2023-04-29", + "metadataLastUpdated": "2023-04-29" + }, + "description": "PV Performance Loss Rate Estimation using Spatio-temporal Graph Neural Networks\n\nPVplr-stGNN is a Python 3 package developed by the SDLE Research Center at Case Western Reserve University in Cleveland OH. This repository contains the full source PVplr-stGNN package. The package contains the PV-stGAE for missingness data detection and imputation and PV-DynGNN for PLR estimation.", + "homepageURL": "https://pypi.org/project/PVplr-stGNN", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PVplr-stGNN 0.1.10", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://pypi.org/project/PVplr-stGNN", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "version": "0.1.10" + }, + { + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2023-05-01", + "metadataLastUpdated": "2023-05-01" + }, + "description": "HydraGNN is an Oak Ridge National Laboratory (ORNL)-branded implementation of distributed multi-tasking graph neural networks that supports several scientific applications within the ORNL portfolio to support the US-DOE mission.\n\nNew or improved capabilities included in v2.0.0 release are as follows:\n\n1) Enhancement in message passing layers through class inheritance\n2) Adding transformation to ensure translation and rotation invariance\n3) Supporting various optimizers\n4) Atomic descriptors\n5) Integration with continuous CI test\n6) Distributed printouts and timers\n7) Profiling\n8) Support of ADIOS2 for scalable data loading\n9) Large-scale system support, including Summit (ORNL) and Perlmutter (NERSC)", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HydraGNN 2.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/HydraGNN/releases/tag/v2.0.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v2.0.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-02", + "metadataLastUpdated": "2023-05-02" + }, + "description": "The Coda Envelope Ratio Tool (CERT) allows for calculating seismic envelopes from waveforms and measuring the amplitude ratios for multiple events against each other to invert for seismic source information. The methodology is based on Walter, W. R., Yoo, S.-H., Mayeda, K., and G\u00f6k, R. (2017), Earthquake stress via event ratio levels: Application to the 2011 and 2016 Oklahoma seismic sequences, Geophys. Res. Lett., 3147- 3155, 44, doi:10.1002/2016GL072348.", + "laborHours": 47712.8, + "languages": [], + "name": "Coda Envelope Ratio Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/coda-calibration-tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.19" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-02", + "metadataLastUpdated": "2023-05-02" + }, + "description": "mkite is a distributed computing platform for materials simulation. mkite is built with the server-client pattern, decoupling production databases from client runners. When used in combination with message brokers, mkite enables any available client to perform calculations without prior hardware specification on the server side. Furthermore, the software enables the creation of complex workflows with multiple inputs and branches, facilitating the exploration of combinatorial chemical spaces. The mkite suite provides recipes and tools to interact with package such as VASP, but is extensible to any other simulation package. Finally, mkite helps keeping the provenance of calculations in a SQL database. A complete description of the software is available at https://arxiv.org/abs/2301.08841.", + "laborHours": 0.0, + "languages": [], + "name": "mkite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mkite-group/mkite_db", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "set of data collection forms implemented as a web app to be used for quality assurance purposes by residential efficiency contractors during the installation process. There are data collection forms for several efficiency measures including heat pump, heat pump water heater, attic weatherization, and basement weatherization.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Remote-QA-Web-App", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Remote-QA-Web-App", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-05-04", + "metadataLastUpdated": "2023-05-30" + }, + "description": "A python library to aid in modeling and understanding light- and elevated temperature-induced degradation (LETID) and boron-oxygen light-induced degradation (B-O LID) in silicon solar cells and wafers\n\nhttps://github.com/NREL/PVDegradationTools/blob/main/pvdeg/letid.py\nhttps://github.com/NREL/PVDegradationTools/blob/main/pvdeg/collection.py", + "laborHours": 3617.6, + "languages": [ + "PYTHON" + ], + "name": "pyletid [SWR 23-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PVDegradationTools", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-05-04", + "metadataLastUpdated": "2023-05-05" + }, + "description": "PVAnalytics inputs long term (multiple years) photovoltaic (PV) outdoor sensor data and completes autonomous quality assurance (QA) analysis on the data. Time series data from individual sensors such as electric meters, inverter outputs, irradiance, and temperature sensors are compared to physically expected outputs of these sensors under clear sky conditions based on the latitude, longitude, and orientation of the PV system. PVAnalytics outputs as QA pass or fail for each sensor, reasons determined for failure, time series flags identifying QA thresholds have been exceeded, flags for sunny days, the time zone found for the given sensor, sensor drift, time periods for passing data, and results of orientation checks.", + "laborHours": 0.0, + "languages": [ + "python" + ], + "name": "PVAnalytics [SWR-20-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pvlib/pvanalytics", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.3" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "BoltzmannMFX is a biological simulation code that solves chemical reaction networks using maximum entropy methods. It uses modules from MFiX-Exa and is based on the AMReX framework for massively parallel block-structured adaptive mesh applications.", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-CompBio/BoltzmannMFX", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/BoltzmannMFX", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The QC-GN2OMS2 neural network was designed to predict mass spectra better than currently available approaches. Fundamentally the neural net is designed to input the structure of a molecule and collision energy value then output a spectra datafile for the end user. This software is able to make predictions orders of magnitude faster (milliseconds) than QC methods and with 50-60% greater accuracy than rules approaches.", + "laborHours": 0.0, + "languages": [], + "name": "QC-GN2OMS2", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-m-q/qcgnoms", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2023-05-08" + }, + "description": "Compiler optimizations can alter the numerical results of scientific computing applications. When numerical results differ significantly between compilers, optimization levels, and floating-point hardware, these numerical inconsistencies can impact programming productivity. Ciel is a framework that helps programmers identify locations in the source code that are affected by compiler optimizations in CPU and GPU code. Ciel uses a floating-point precision enhancement strategy, guided by a recursive bisection search algorithm with increasing search granularity, to identify the program expressions that induce numerical inconsistencies due to compiler optimizations.", + "laborHours": 0.0, + "languages": [], + "name": "Ciel", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Ciel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2023-05-09" + }, + "description": "PhaseTorch is a python package that implements algorithms for forward and inverse problem solutions in X-ray phase contrast tomography (XPCT). XPCT is useful to reconstruct the 3D distribution of the refractive index decrement and absorption index of an imaged object. PhaseTorch implements algorithms for simulation, reconstruction, and analysis of XPCT data. PhaseTorch provides algorithms for simulation of XPCT data of an object with known refractive and absorption indices. It contains algorithms for reconstructing the projections of the absorption index and refractive index decrement. ", + "laborHours": 0.0, + "languages": [], + "name": "Algorithms for Forward and Inverse Problem Solutions in Phase Contrast Tomography", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/phasetorch/phasetorch", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2023-05-08" + }, + "description": "\tThe CRT Command Line Interface is a software tool released as public domain software in 2007 by Charles Bland and can be downloaded under http://www.room220.com/crt/.\n\nThe last CRT-CLI release update was in 2008 and bumped up its version number to 1.2.\n\nWe used the CRT-CLI tool in our IMG Annotation Pipeline and over the years modified the original code based on suggestions made by our in-house experts to add more functionality, e.g. being able to detect truncated repeats at the edge of sequences or repeats containing Ns, additional output file options, and additional identity and similarity control parameters.", + "laborHours": 0.0, + "languages": [], + "name": "\tCRISPR Recognition Tool (CRT) - Command Line Interface (IMGAP Version) (CRT-CLI) v1.8.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/img/img-pipelines/crt-cli-imgap-version", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "sarat@ornl.gov" + }, + "date": { + "created": "2023-05-09", + "metadataLastUpdated": "2023-05-09" + }, + "description": "Performance Analytics for Computational Experiments (PACE) is an end-to-end performance monitoring infrastructure to summarize performance data collected from Department of Energy\u2019s (DOE) climate model experiments to derive insights and present them through a web portal. PACE automatically captures provenance/timing data from simulations run on DOE supercomputers.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "PACE", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/pace", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-05-11", + "metadataLastUpdated": "2023-05-22" + }, + "description": "The Hydrogen Financial Analysis Scenario Tool, H2FAST, provides a quick and convenient in-depth financial analysis for hydrogen and nonhydrogen systems and services.\n\nH2FAST is available as a downloadable Excel spreadsheet. The model uses a generally accepted accounting principles analysis framework and provides annual projections of income statements, cash flow statements, and balance sheets. H2FAST allows users to generate a side-by-side scenario analysis, where a base system can be tested by varying key operating or financing parameters. Detailed capital structure, taxation, and incentives are included. The model has built-in risk analysis allowing impact assessment of parameters bearing user-specified uncertainty ranges. Financial articulation is presented in graphical and tabular format for the user-specified analysis period. The model is self-documented, with embedded help functions and annotation of input parameters.\n\nNote: The model is also flexible for providing analysis for International Financial Reporting Standards by adjusting inputs for compliance with their rules.\n\nThe H2FAST framework has been used for analysis of a variety of systems, e.g., retail hydrogen refueling stations with incentives analysis, ammonia production, methane pyrolysis, seasonal energy storage, hydrogen fleet operations, electric vehicle charging with time of use rate structures, combined heat and power systems, hydrogen production pathways, and hydrogen transmission and distribution. The example cases available for download are intended to demonstrate model functionality and should be populated with user-specific analysis values such as CapEx, OpEx, and capital structure.", + "homepageURL": "https://www.nrel.gov/hydrogen/h2fast.html", + "laborHours": 0.0, + "languages": [ + "Excel" + ], + "name": "H2FAST: Hydrogen Financial Analysis Scenario Tool [SWR 15-06]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/hydrogen/assets/pdfs/h2fast_spreadsheet_user_manual.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/hydrogen/h2fast.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-05-17", + "metadataLastUpdated": "2023-05-22" + }, + "description": "Provides an XSD framework within the Common Information Model \u2013 IEC 61970 Part 7 \u2013 for the integration of dynamic line ratings within the utility software systems. 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Overall this program can take in a large collection of articles and create a profile of them, displaying what disciplines and areas are covered in the collection. 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The variables are read and the desired values are taken and added to an array in the correct format. This array is then converted into a python array for future use. The code also utilizes MATPOWER's ability to construct different power flow scenarios and repeat them a chosen number of times. Each iteration will add a new line to the formatted array so that the final output is a matrix has a height equal to the number of repetition used.", + "laborHours": 0.0, + "languages": [ + "Matlab Programming Language" + ], + "name": "Training Data Regarding Optimal Power Flow For Efficient Machine Learning", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/TROPFE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2023-05-19", + "metadataLastUpdated": "2023-05-19" + }, + "description": "A framework for developing modular software.", + "laborHours": 0.0, + "languages": [], + "name": "NWChemEx-Project/PluginPlay", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NWChemEx-Project/PluginPlay", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Confidence Estimation for Mass Spectrometry Proteomics. Crema is an open-source Python tool that estimates the false discovery rate (FDR) of a set of peptide-spectrum matches\nthat result from proteomics data analysis. Crema implements standard FDR estimation methods that are widely used within\nthe field. This package is meant to be simple, easy to use, stand-along, and easy to maintain.", + "laborHours": 0.0, + "languages": [], + "name": "Noble-Lab/crema", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Noble-Lab/crema", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Evaluates the reserve requirements for power system balancing areas based on variability and uncertainty of load as well as wind and solar generation scenarios. The tool uses minute\u2010by\u2010minute site\u2010specific generation and load information, as well as information from generation and load forecasting algorithms used in the balancing areas. The Balancing\u2010Plan Tool can be used directly by utility planners and operators to aid in the integration of intermittent renewable resources. The tool provides reserve requirements of various kinds, such as day\u2010ahead, load following and regulation, as well as estimates the capacity of the generation fleet to provide the require reserves.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "GRAF-Plan for Vietnam", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The invention is a set of algorithms and calculations for a performance-based\nmodel to translate wildfire burn potential to actual transmission line outages\nin real-time in an interactive application that uses geospatial data sets on the\nwildfire burn potential as well as detailed grid topographical datasets.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Wildfires Risk Evaluation of the System (WiRES) Framework Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-25", + "metadataLastUpdated": "2023-05-25" + }, + "description": "THE DATA SCIENCE INSTITUTE WILL BE INVITING STUDENTS FROM UC MERCED AND UC\nRIVERSIDE TO PARTICIPATE IN A DATA SCIENCE CHALLENGE AT LLNL. IN THE CHALLENGE,\nTHE STUDENTS WILL EXPLORE A DATA-DRIVEN APPROACH TO RECONSTRUCTING ELECTROANATOMICAL\nMAPS OF THE HEART AT CLINICALLY RELEVANT RESOLUTIONS, COMBINING\nINPUT FROM THE STANDARD 12-LEAD ECG WITH ADVANCED MACHINE LEARNING\nTECHNIQUES. THE DATA THE STUDENTS WILL HAVE ACCESS TO HAS BEEN IM REVIEWED FOR\nEXTERNAL RELEASE. (LLNL-MI-835833) THESE NOTEBOOKS WILL PROVIDE THE STUDENTS\nWITH INSTRUCTIONS OF HOW TO LOAD THE DATA AND WORK WITH THE DATA, ALONG WITH\nTUTORIALS TO DO BASIC MACHINE LEARNING TASKS LIKE LOGISTIC REGRESSION AND IMAGE\nCLASSIFICATION.", + "laborHours": 0.0, + "languages": [], + "name": "2023 Data Science Challenge Notebooks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/landajuela/cardiac_challenge", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-31", + "metadataLastUpdated": "2023-05-31" + }, + "description": "DFTF converts Redfish events to messages on a Kafka bus. DFTF subscribes to events in Redfish,\nspecifically Alerts and CrayTelemetry. It listens for HTTP POST requests containing event data, reduces\nthe data, serializes the reduced data using Avro, and publishes the data to topics in Kafka.", + "laborHours": 0.0, + "languages": [], + "name": "Drink From The Firehose", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/dftf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-05-31", + "metadataLastUpdated": "2023-06-07" + }, + "description": "SAND2021-6722 O\nThis is a fitness tracking mobile application and server created to train college-level students to build full stack software. The front end is written using an open-source framework called Flutter. The API server is written using an open-source python framework called Flask. The app functions as a workout tracker and is intentionally partially functional for the purpose of training students during the live workshops hosted by Sandia's HR recruiting teams. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Dart", + "Python" + ], + "name": "NSU Hack-a-Thon Workshop v.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ohon3/sandia-hackathon-fall2021", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-06-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software was developed to solve the problem of curating and validating individual metabolic models and combining\nthem into different consortia.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl-predictive-phenomics/concerto", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/concerto", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-09-18" + }, + "description": "This software supports the paper, \"Exploring the scaling limitations of the variational quantum eigensolver with the bond dissociation of hydride diatomic molecules,\" published in the International Journal of Quantum Chemistry, whose abstract is as follows: Materials simulations involving strongly correlated electrons pose fundamental challenges to state-of-the-art electronic structure methods but are hypothesized to be the ideal use case for quantum computing. To date, no quantum computer has simulated a molecule of a size and complexity relevant to real-world applications, despite the fact that the variational quantum eigensolver (VQE) algorithm can predict chemically accurate total energies. Nevertheless, because of the many applications of moderately-sized, strongly correlated systems, such as molecular catalysts, the successful use of the VQE stands as an important waypoint in the advancement toward useful chemical modeling on near-term quantum processors. In this paper, we take a significant step in this direction. We lay out the steps, write, and run parallel code for an (emulated) quantum computer to compute the bond dissociation curves of the TiH, LiH, NaH, and KH diatomic hydride molecules using VQE. TiH was chosen as a relatively simple chemical system that incorporates d orbitals and strong electron correlation. Because current VQE implementations on existing quantum hardware are limited by qubit error rates, the number of qubits available, and the allowable gate depth, recent studies have focused on chemical systems involving s and p block elements. Through VQE + UCCSD calculations of TiH, we evaluate the near-term feasibility of modeling a molecule with d-orbitals on real quantum hardware. We demonstrate that the inclusion of d-orbitals and the use of the UCCSD ansatz, which are both necessary to capture the correct TiH physics, dramatically increase the cost of this problem. We estimate the approximate error rates necessary to model TiH on current quantum computing hardware using VQE+UCCSD and show them to likely be prohibitive until significant improvements in hardware and error correction algorithms are available.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "tih_vqe [SWR-23-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/tih-vqe", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2024-07-01" + }, + "description": "OCHRE\u2122 Gymnasium is a Python framework for conducting reinforcement learning research on residential building energy management problems. It is a lightweight wrapper around OCHRE, a Python-based thermal-electric residential building simulator developed in-house at NREL. OCHRE Gymnasium adheres to the standard OpenAI Gym API for a reinforcement learning environment. Detailed Sphinx documentation will be auto-generated and accompany this codebase. This documentation will detail the API, provide examples of how to use the code, etc.", + "laborHours": 29928.8, + "languages": [ + "Python" + ], + "name": "OCHRE\u2122 Gymnasium (ochre_gym) [SWR-23-47]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ochre_gym", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2024-06-05" + }, + "description": "A Python package for directed evolution on a protein sequence with gradient-based discrete Markov chain monte carlo (MCMC). Users are able to compose custom models that map sequence to function with pretrained models, including protein language models (PLMs), to guide and constrain search. Our package natively integrates with the HuggingFace platform and supports PLMs from transformers.\n\nOur MCMC sampler identifies promising amino acids to mutate via model gradients taken with respect to the input (i.e., sensitivity analysis). We allow users to compose their own custom target function for MCMC by leveraging the Product of Experts MCMC paradigm. Each model is an \"expert\" that contributes its own knowledge about the protein's fitness landscape to the overall target function. The sampler is designed to be more efficient and effective than brute force and random search while maintaining most of the generality and flexibility.\n\nAdditional information can be found in the related publication: https://iopscience.iop.org/article/10.1088/2632-2153/accacd", + "laborHours": 820.8, + "languages": [ + "PYTHON", + "Jupyter Notebook" + ], + "name": "EvoProtGrad (Directed Evolution for Proteins with Gradients) [SWR-23-48]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EvoProtGrad", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-08-28" + }, + "description": "The residential and commercial building stock in the United States is responsible for a significant percentage of energy consumption and greenhouse gas emissions. Electrification of end-uses, as well as decarbonizing the electrical grid through renewable energy sources such as solar and wind, constitutes the pathway to zero-emission buildings. Forecasting day-ahead building energy consumption is an integral part of this solution. Currently, specialized forecasting models are hand-made for each individual building, which is time-consuming, expensive, and leads to duplicated efforts. BuildingsBench is a Python software framework for training and comparing generalized machine learning models for universal building load forecasting. This challenge tasks a single foundational model to generalize its forecasts for a wide variety of buildings, across geographic regions, building types, weather patterns, and more. This software provide code for pre-training such models and subsequently evaluating their performance on a suite of hundreds of diverse real and synthetic buildings.\n\nBuildingsBench is a platform for:\n\n- Large-scale pretraining with the synthetic Buildings-900K dataset for short-term load forecasting (STLF). Buildings-900K is statistically representative of the entire U.S. building stock and is extracted from the NREL End-Use Load Profiles database.\n\n- Benchmarking on two tasks evaluating generalization: zero-shot STLF and transfer learning for STLF.\n\nWe provide an index-based PyTorch Dataset for large-scale pretraining, easy data loading for multiple real building energy consumption datasets as PyTorch Tensors or Pandas DataFrames, simple (persistence) to advanced (transformer) baselines, metrics management, and more.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "BuildingsBench: A Benchmark for Universal Building Load Forecasting [SWR-23-51]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BuildingsBench", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "A new version of the verification tool ExactPack, 1.7.0, includes three new solvers: A Radshocks solver, Riemann solver and an Elastic-Plastic Piston problem solver. The code has been refactored to work with Python 3. All Fortran code has been removed and solvers implemented in Fortran have been re-implemented in Python where necessary. All unit tests have been converted to use the Pytest format and all the GUI, CLI and verification analysis code has been removed.", + "laborHours": 0.0, + "languages": [], + "name": "ExactPack", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ExactPack", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "Understanding how inaccuracies in visualizations affect users\u2019 perception and understanding of scientific data is hard. Inaccuracies in visualizations are quite common and could arise from a range of sources such as errors in the original dataset arising from compression artifacts, errors in the capturing device, noise during transmission of the data, effects due to the algorithm being used to convert data to visualization images, images generated from neural networks, and sources we have yet to discover. Many image quality assessment metrics have been developed to quantify image errors. However, these are usually focused on \u201cnatural images\u201d rather than visualizations of scientific data. Common image quality assessment metrics (IQAs) include MSE, PSNR, perceptual metrics such SSIM, FSIM as well as perceptual metrics using deep learning approaches. However, a critical part of understanding how errors are perceived by humans, and subsequently developing more accurate quality assessment metrics, is through user evaluation studies.\n\nThe goal of this software is to develop a visualization quality assessment (VQA) process that will enable the generation of VQAs that can be used to quantify errors in scientific data visualizations. The VQA development process will include software to support user evaluation experimental design, analysis of visualization differences against standard quality metrics, and the ability to develop additional VQA metrics specific to scientific visualization images. ", + "laborHours": 0.0, + "languages": [], + "name": "Visualization Quality Assessment", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vizStudy", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-06" + }, + "description": "Light-matter interactions play an important role in many branches of physics, chemistry, energy, and materials science. In the strong coupling regime, light-matter interactions are able to tune the materials properties via the formation of new quasiparticles, such as plasmons and polaritons. However, theoretical and numerical modeling of the light-matter interaction-mediated processes remain a big challenge because light-matter interactions are fundamentally multiscale and multiphysics problems involving multiple interactions between electrons, nuclei, and photons at different time/length scales. In the current community, light-matter interactions were treated at different levels of theoretical complexity in quantum chemistry and quantum optics. In quantum optics or quantum photonics, the matter is usually simplified as a few-level system, and the light is treated quantum-mechanically. On the other hand, quantum chemistry explores first-principles methods, including both single-particle and many-body-based techniques, to describe the electronic properties of matter in detail. However, light is usually prescribed as a classical electromagnetic field, and the light-matter interaction is taken into account as an external potential via classical approximations. This software is designed to fill current modeling shortcomings by delivering a first-ever scalable multiscale platform for simulating light-matter interactions in realistic electromagnetic environments. The software solves Maxwell and Schrodinger equations self-consistent on the heterogeneous platforms. It implements HF/DFT, TDDFT, and coupled-cluster counterparts for light-matter interactions and adopts modular programming to offload massively parallel algorithms on a large number of CPU/GPUs.", + "laborHours": 0.0, + "languages": [], + "name": "Multiscale Ecosystem for solving Maxwell-Schrodinger equations of open quantum systems (OpenMS) ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/OpenMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "Dimension reduction techniques have long been an important topic in statistics, and active subspaces (AS) have received much attention this past decade in the computer experiments literature. The most common approach towards estimating the AS is to use Monte Carlo with numerical gradient evaluation. This software takes a new approach towards estimating the active subspace, in which Multivariate Adaptive Regression Splines (MARS) is used as a surrogate model, and relevant calculation are obtained analytically. Using a MARS surrogate has many advantages including improved scaling, better estimation of active subspaces in high dimensions and the ability to handle a large number of prior distributions in closed form. This software is also capable of conducting a so-called \"concordance analysis\", using a generalization of ASs which we refer to as \"Co-Active\" subspaces. ", + "laborHours": 0.0, + "languages": [], + "name": "Concordance", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/knrumsey-lanl/concordance", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "Ume is an open-source collection of data structures for unstructured computational meshes and some simple algorithms that operate on them. These algorithms mimic the memory access patterns of a common class of operations found in several of the computational physics simulation codes developed at Los Alamos National Laboratory. The intent is that Ume can be used by hardware vendors to understand the memory traffic created by complex codes in a simplified environment, and to explore new means of optimization for that traffic. Ume is provided as a source-code C++ library and includes several applications that demonstrate the use of that library.", + "laborHours": 0.0, + "languages": [], + "name": "Ume: Unstructured Mesh Explorations", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/UME", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "LANL science workflows generate complex data sets and ensembles of data requiring significant compute and storage resources. 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The abstraction layer API allows the user to query a range of data types: raw output, processed data, configuration data, machine learning models, performance data, etc. In addition to the abstraction backend API, the DSI project is developing client-driven query APIs and UIs to support specific user workflows.", + "laborHours": 0.0, + "languages": [], + "name": "Data Science Infrastructure SOFTWARE", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/dsi", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-07" + }, + "description": "The ratio of heavy-to-light stable isotope abundance in water vapor is a tracer of atmospheric processes including evapotranspiration, condensation, mixing, and transport. Measurements of these isotope ratios at the surface, in the atmospheric column, or from satellites provide insights into atmospheric processes that cannot be gained from measurements of water vapor mixing ratios alone. A number of theoretical models for how water vapor isotope ratios should vary in response to atmospheric processes have been developed, and LANL contributions to the isoWater R package provides a simplified interface for calculating expected vapor isotope ratios based on these models and adding them to plots of water vapor isotope ratios.", + "laborHours": 0.0, + "languages": [], + "name": "LANL contributions to isoWater R package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/isoWater", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-05" + }, + "description": "The purpose of the current request is to enable LANL employees to contribute computer source code to the existing public repository of the MoDELib software package. This software implements discrete dislocation dynamics (DDD) and finite element (FEM) methods and is currently a vital component of an ongoing DR project at LANL, in collaboration with its original author and maintainer Giacomo Po. Contributions from LANL employees would aim to enhance the reliability, accuracy, and performance of MoDELib simulations using LANL's high performance computing platforms through bug fixes, algorithmic refinements, and parallelization.", + "laborHours": 0.0, + "languages": [], + "name": "Contributions to MoDELib SOFTWARE", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nickjulian-LANL/MoDELib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "Harmony is a finite element ALE code for solving the equations of fluid dynamics for single-material flows with arbitrary mesh motion in three dimensional geometry. ", + "laborHours": 0.0, + "languages": [], + "name": "Harmony code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Harmony", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-05" + }, + "description": "The scientific and public health communities responded to the COVID-19 pandemic with\nsample acquisition and genome sequencing on a scale that eclipsed all prior sequencing\nefforts. While this can only be characterized as a resounding success story that has\ncemented the use of genomics for epidemiological investigations for any future infectious\ndisease outbreak, several retrospective studies are cataloging an array of lessons learned\nand issues that have yet to be addressed in order to realize the full potential of genomics as\na routine biosurveillance tool. We have been both developing methods to accurately assess\nSARS-CoV-2 genomes from complex samples, and analyzing the large volumes of\ninternational data, both at the consensus level and the raw sequencing data. During the\ncourse of our investigations and similar to other groups, we have examined COVID-19\nsamples with signatures from multiple lineages of SARS-CoV-2 and will describe some of\nour findings during the development of a novel workflow that incorporates detection and\nreporting of potential co-infection within samples and also highlights any evidence of\nwithin-host recombination.", + "laborHours": 0.0, + "languages": [], + "name": "Recombinant And Mix-Infection Finder for SARS-CoV-2 sample", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ramifi", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-05", + "metadataLastUpdated": "2023-07-31" + }, + "description": "This tool provides interfaces for ingesting real-time unit commitment data (e.g., from a grid operator's control room energy management system) and calculating system inertia estimates based on the H-constant method, before relaying those estimates to customizable visualization or logging outputs.", + "laborHours": 0.0, + "languages": [ + "Go", + "CSS", + "HTML", + "JavaScript" + ], + "name": "G-PST Inertia Monitoring Tool [SWR-23-54]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/G-PST/inertia", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-06-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "3D printing design documents for a bearing-less centrifugal water pump comprised of an impeller rotor enclosing a permanent magnet which is\ndriven by a second permanent magnet rotated by an electric motor.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Bearing-less Centrifugal Pump (non-levitated, non-electromagnetic)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-06-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "3D design documents for 3D printing. The holes in the electrode cage are designed to condense hydrogen into progressively larger\nbubbles, and to direct the flow of hydrogen from the cathode up and out of the bioreactor so it is kept away from the anode\nand collected as nearly pure hydrogen.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Electrode Cage for Hydrogen Production", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-06-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "3D printable reactor base provides all of the mixing innovations needed to make excellent mixing reactors at any scale", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Hybrid Bioreactor for Enhanced Mixing Efficiency", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-06-06", + "metadataLastUpdated": "2023-06-16" + }, + "description": "Zero-RK is a software package that simulates chemically reacting systems using sparse, preconditioned,\nadaptive matrix methods to achieve orders-of-magnitude reduction in simulation time while maintaining\naccurate results.", + "laborHours": 13497.6, + "languages": [], + "name": "Zero-Order Reaction Kinetics v. 3.4.hip", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/zero-rk", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.4.hip" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-07", + "metadataLastUpdated": "2023-06-07" + }, + "description": "AIIO uses Artificial Intelligence for Job-Level and Automatic I/O Performance Bottleneck Diagnosis.", + "laborHours": 0.0, + "languages": [], + "name": "AIIO v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/aiio", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-07", + "metadataLastUpdated": "2023-06-07" + }, + "description": "The AmeriFlux BASE Flux/Met Data QA/QC and Processing (AMF-BASE-QAQC) code provides tools to review and prepare continuous flux/met data submitted to the AmeriFlux Management Project for publication as the AmeriFlux BASE data product. The code provides 3 core functionalities: Format QA/QC assesses submitted data files for compliance with the required submission format; Data QA/QC assesses the data quality; BASE Publish prepares the data for publication.", + "laborHours": 0.0, + "languages": [], + "name": "AmeriFlux BASE Flux/Met Data QA/QC and Processing (AMF-BASE-QAQC) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMF-FLX/AMF-BASE-QAQC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-07", + "metadataLastUpdated": "2023-06-12" + }, + "description": "This software generates QED fields in which the photon has a finite mass, and also the 0-mode subtracted scheme. They are intended to be used with lattice QCD calculations to understand the QED corrections to nuclear physics processes that are being computed with lattice QCD. To the best of my knowledge, this will be the only publicly available software that generates background QED configurations with massive photons. ", + "laborHours": 0.0, + "languages": [], + "name": "noncompact_u1 (qed_m) v1.0.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/callat-qcd/qed_m", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "colemanjs@ornl.gov" + }, + "date": { + "created": "2023-06-13", + "metadataLastUpdated": "2024-05-07" + }, + "description": "AdditiveFOAM is a continuum heat transfer and fluid flow code for metal additive manufacturing developed on the OpenFOAM CFD Framework. The main components of AdditiveFOAM include: a dynamic heat source model representing heat input from independently moving beams; a robust and efficient thermodynamic solver for solid-liquid phase change in metal alloys; a library to export thermal data to ExaCA\u2014 a cellular automata (CA) code used for predicting solidification grain growth. By integrating these capabilities, AdditiveFOAM offers valuable insights into the process-structure relationships of metal additive manufacturing components.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "AdditiveFOAM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/AdditiveFOAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-15", + "metadataLastUpdated": "2023-06-15" + }, + "description": "MetaBAT-LR is an extension to the metaBAT program, which adds functionalities to leverage various datasets (long-reads, Hi-C) to improve the completeness of metagenome binning while keeping contamination levels low. It trains a random forest model using the self-supervised training paradigm to predict linkage information among metagenome scaffolds, then uses this information to recruit unbinned scaffolds and merge incomplete bins that are from the same species.", + "laborHours": 0.0, + "languages": [], + "name": "MetaBAT-LR v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/project-metabat/metabat-lr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-06-19", + "metadataLastUpdated": "2023-06-19" + }, + "description": "This software is intended to facilitate the sending of data from DeepLynx to some human machine interface (HMI). The HMI would read the data generated by this software and potentially make a physical change on a process which the HMI controls. This software enables a digital twin using DeepLynx to talk to an HMI, thereby making autonomous updates to the physical asset which is being twinned.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deeplynx Supervisory Control Adapter", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-Supervisory-Control", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-06-20", + "metadataLastUpdated": "2023-06-20" + }, + "description": "AutoCog is a framework to design programming models (PM) for language models (LM). 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These tools were used in the manuscript entitled \"Continuous-Time Probabilistic Models for\nLongitudinal Electronic Health Records.\"", + "laborHours": 0.0, + "languages": [], + "name": "Continuous-Time Models for Longitudinal Data", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/alankaplan/CTMLD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-21", + "metadataLastUpdated": "2023-08-28" + }, + "description": "A2E2G is a platform that integrates 1) forecasting tools to account for weather uncertainty, with 2) aerodynamic wind plant models to account for wake dynamics and wind plant operation, and 3) economic models to advise on operation for a wind power plant that offers grid services in addition to energy. 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The code is assembled into a Python package and can be easily downloaded and installed from the A2E2g repository (https://github.com/NREL/a2e2g).", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "A2E2G (Atmosphere to Electrons to the Grid platform) [SWR-23-22]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/a2e2g", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-21", + "metadataLastUpdated": "2023-06-21" + }, + "description": "Stacker is a library and command-line tool for interacting with components of the Elastic Stack remotely\nusing their APIs. 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This package can be used with both CPU and GPU with CUDA.", + "laborHours": 0.0, + "languages": [], + "name": "LivermorE Al Projector for Computed Tomography Tasks ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/leap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-23", + "metadataLastUpdated": "2023-06-30" + }, + "description": "This toolset generates heterogeneous spatial layouts, aimed at representing forest fuels applicable to wildland fire modeling. 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More broadly, Tribol supports the research, development, and\nimplementation of numerical methods for interface physics.\n", + "laborHours": 0.0, + "languages": [], + "name": "Tribol Interface Physics Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Tribol", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-27", + "metadataLastUpdated": "2023-06-27" + }, + "description": "This software offers methods and functions for training calibrated out-of-distribution detectors for medical\nimage classification tasks. It includes functionalities for training, synthesizing data augmentations,\ncalibration, and out-of-distribution detection. Developed using PyTorch, this software is compatible with\nstandard neural network architectures used for imaging data. Additionally, it provides capabilities to compute evaluation metrics for assessing the performance and quality of the detectors.", + "laborHours": 0.0, + "languages": [], + "name": "Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/OODmedic", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-06-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Open Source Exascale Computational Chemistry Software", + "laborHours": 0.0, + "languages": [], + "name": "ExaChem/exachem", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ExaChem/exachem", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-28", + "metadataLastUpdated": "2023-06-28" + }, + "description": "PyTorch code for cardiac electrical imaging using the 12-lead ECG. This code is associated with the\npaper from CINC 2022. If you use this code, please cite:\nPaper : https://cinc.org/2022/Program/accepted/26_Preprint.pdf\nDataset : https://library.ucsd.edu/dc/object/bb29449106\nThe code support two tasks:\nTask 1: Activation Map Reconstruction from ECG\nTask 2: Transmembrane potential Reconstruction from ECG", + "laborHours": 0.0, + "languages": [], + "name": "Machine Learning for Cardiac Electrical Imaging", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/landajuela/cardiac_ml", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0." + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-28", + "metadataLastUpdated": "2023-06-30" + }, + "description": "This is a script and the associated test input/output that will accompany a new manuscript (soon to be submitted for publication). 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This script is released as documentation for the manuscript, but there is no specific invention, and most bioinformaticians would be able to recreate a comparable script in a matter of days (if not hours) based on the description in the manuscript.", + "laborHours": 0.0, + "languages": [], + "name": "Custom script used in 'Updated virophage taxonomy and distinction from polinton-like viruses' (Virophage_Scripts) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/simroux/ICTV_VirophageSG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-28", + "metadataLastUpdated": "2023-06-28" + }, + "description": "\tHaxall-based Fault Correction is a set of fault auto-correction algorithms implemented using the Axon language. These algorithms can automatically fix equipment and control problems as they arise and improve the operation of building Heating, Ventilation, and Air Conditioning (HVAC) systems. The coded auto-correction algorithms include mitigation of rogue zones, ASHRAE Guideline 36 static pressure and supply air reset, resolution of control hunting due to improper settings in a proportional-integral-derivative controller, correction of biased temperature sensors, etc. FDD tools with enhanced auto-correction capability can resolve control problems as they are detected, increasing energy savings and emissions reductions while freeing up operational staff expertise for the hardest facility problems.", + "laborHours": 0.0, + "languages": [], + "name": "Haxall-based (Axon) fault auto-correction package for building HVAC system (Haxall-based Fault Correction) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/haxall-based-fault-correction", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gureckywl@ornl.gov" + }, + "date": { + "created": "2023-06-29", + "metadataLastUpdated": "2023-06-29" + }, + "description": "The software solves the time dependent, one dimensional (1D) coupled mass and momentum balance equations governing the elastic flow of water through the penstock, turbine and draft tube in a hydroelectric facility using a high order finite volume based method. The numerical method is based on the Kurganov-Tadmor central method paired with the Monotonic Upstream-centered Scheme for Conservation Laws (MUSCL). This solution method accurately resolves the fast transient behavior of the flow, including water hammer. Additionally, the software estimates the full 3D flow field within the turbine chamber in real time, a feat that is made possible by leveraging pre-computed CFD results by utilizing a reduced order modeling method based on an efficient randomized singular value decomposition (SVD) driven proper orthogonal decomposition (POD) with POD-mode weight regression. The reduced order model of the 3D flow is directly coupled to the 1D elastic flow model so the entire flow field through the penstock and turbine system is resolved quickly and with high fidelity.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DT-HYDRO", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/dt-hydro/dt-hydro-cfd", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0.0.1" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-30", + "metadataLastUpdated": "2023-06-30" + }, + "description": "edit-initramfs.sh is a simple script to extract, edit, and rebuild an initramfs image. This makes it easy to quickly make edits to the contents of an initramfs.\n", + "laborHours": 0.0, + "languages": [], + "name": "edit-initramfs.sh", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tonyhutter/edit-initramfs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-07-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PTM-Psi is a Python 3 package that combines several capabilities to streamline the workflow to interrogate the impact of\nPTMs on proteins using well-established software packages. The workflow of the PTM-Psi software package includes\ninput files and launch instances from standard packages such as AlphaFold, NWChem, GROMACS, and the Autodock\nSuite", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/PTMPSI", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ptmpsi", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-07-03", + "metadataLastUpdated": "2023-07-03" + }, + "description": "Provides a central location for viewing and comparing different methods for downscaling coarse resolution\nclimate model output.", + "laborHours": 0.0, + "languages": [], + "name": "Downscaled Climate Data Dashboard", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Downscaled-Climate-Data-Dashboard", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-07-06", + "metadataLastUpdated": "2024-10-16" + }, + "description": "Battery life modeling often involves a lot of manual parameter fitting and is not easy for users to adopt the model and use it. To reduce the difficulties for users to adopt battery lifetime models, an automatic battery lifetime modeling analysis and simulation tool suite, Auto-BLAST, has been developed. Auto-BLAST includes a lithium-loss-base life model, a battery electric model, and an algorithm which automatically fits all key parameters in the electric and life models using user provided data. The models and algorithm are packaged into two user-friendly GUIs, Auto-LifeMod, for easy battery life prognostic model fitting and Auto-LifeSim, for easy battery lifetime simulation. The lithium-loss-based life model adopts a similar model framework that models degradations using aging rate models, using battery cycling data to predict battery degradation and expected lifetime. The electric model is an equivalent circuit model which simulates battery voltage responses based on current/power demand profiles. The auto-fitting algorithm uses the user-input data to generate custom battery life model(s). Two GUIs, wrapping around the life model and the auto-fitting algorithm, provide friendly interfaces for users to generate a life model and use it for case study. One GUI requires summary data from accelerated battery life degradation tests as an input and produces battery life models predicting (a) capacity degradation, and (b) resistance growth of the battery. The GUI displays the electrical model response and the input experimental data against the life model predictions with fitted model parameters and fitting error. The GUI also generates an output file to save the fitted model parameters. The second GUI uses the life model from the first GUI and a user-defined battery cycling profile to predict battery lifetime degradation and expected lifetime. Predicted capacity and resistance vs. time are plotted in the GUI and saved to output file. There is a user guide for both GUIs", + "homepageURL": "https://labpartnering.org/technologies/a298da24-0625-42a8-9693-a81d839529d7", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Auto-BLAST (AutoBLAST) [SWR-20-93]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://labpartnering.org/technologies/a298da24-0625-42a8-9693-a81d839529d7", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://labpartnering.org/technologies/a298da24-0625-42a8-9693-a81d839529d7", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-06", + "metadataLastUpdated": "2023-07-06" + }, + "description": "\tQuantitative Universal Option Prioritizer (QUOP) is a three-layer analytical hierarchy process (AHP) based multi-criteria decision-making option evaluation and prioritization tool. Decision-making often entails evaluation of options. Such competing options can either be mutual substitutes or cumulative means to achieve an objective. The options themselves can be methods, tools, technologies, processes, etc. Stakeholders involved in achieving the objective may view each option characteristic differently, depending on their needs and preferences. The QUOP tool enables a streamlined quantitative collaborative process of weighing the opinion of each stakeholder in evaluating the options. The evaluation may also be performed under different scenarios, for instance, various option potential estimates, prices, or end-user demand projections. The QUOP tool can find application in both public and private sectors, as well as on an individual level. The major advantage of using the QUOP decision-making tool is in documenting the quantified stakeholder opinion, therefore the background to each decision made, while simultaneously maintaining high transparency and stakeholder involvement. The tool is particularly suitable for decisions involving a high number of options and option characteristics, that is, aspects of each option that matter to the stakeholders", + "laborHours": 0.0, + "languages": [], + "name": "Quantitative Universal Option Prioritizer (QUOP) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/QUOP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-06", + "metadataLastUpdated": "2023-07-06" + }, + "description": "The High Speed Digitizer firmware is an FPGA gateware and embedded firmware that run on evaluation kits (either Xilinx ZCU111 or Xilinx ZCU208 ) that digitizes signals up to 4GSPS and 4GHz analog bandwidth, which can be synchronized to the accelerator timing system, providing synchronous sampling frequency/phase digitization. In addition to these capabilities, a proof of concept for a beam position monitor is also present, providing an envelope detection algorithm capable of determining the transverse beam position for an electron circular accelerator, such as ALS/ALS-U.", + "laborHours": 0.0, + "languages": [], + "name": "High Speed Digitizer Firmware (HSD) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/LBNL-Digitizers", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for \"Faster Parallel Exact Density Peaks Clustering\" paper.\n\nHuang, Yihao, Shangdi Yu, and Julian Shun. \"Faster Parallel Exact Density Peaks Clustering.\"\u00a0SIAM Conference on Applied and Computational Discrete Algorithms (ACDA23). Society for Industrial and Applied Mathematics, 2023.\n", + "laborHours": 0.0, + "languages": [], + "name": "Faster Parallel Exact Density Peaks Clustering", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/michaelyhuang23/ParCluster", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper: \n\nZhi Wei Gan, Grace Cai, Noble Harasha, Nancy Lynch, and Julian Shun.\nParSwarm: A C++ Framework for Evaluating Distributed Algorithms for Robot Swarms.\nProceedings of the Workshop on Advanced Tools, Programming Languages, and Platforms for Implementing and Evaluating Algorithms for Distributed Systems (ApPLIED), Article No. 14, pp. 1-5, 2023.\n", + "laborHours": 0.0, + "languages": [], + "name": "ParSwarm: A C++ Framework for Evaluating Distributed Algorithms for Robot Swarms", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zhiweigan/geo-swarm-framework", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper:\n\nShangdi Yu and Julian Shun.\nParallel Filtered Graphs for Hierarchical Clustering.\nProceedings of the IEEE International Conference on Data Engineering (ICDE), 2023.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Filtered Graphs for Hierarchical Clustering", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yushangdi/par-filtered-graph-clustering", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper:\n\nYihao Huang, Claire Wang, Jessica Shi, and Julian Shun.\nEfficient Algorithms for Parallel Bi-core Decomposition.\nProceedings of the SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS), pp. 17-32, 2023.", + "laborHours": 0.0, + "languages": [], + "name": "Efficient Algorithms for Parallel Bi-core Decomposition", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/clairebookworm/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper:\n\nJessica Shi, Louisa Huang, and Julian Shun.\nParallel Five-Cycle Counting Algorithms.\nACM Journal of Experimental Algorithmics (JEA), Vol. 27, Article No. 4:1, pp.1-23, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Five-Cycle Counting Algorithms", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper:\n\nYiqiu Wang, Rahul Yesantharao, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun.\nParGeo: A Library for Parallel Computational Geometry.\nProceedings of the European Symposium on Algorithms (ESA), pp. 88:1-88:19, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "ParGeo: A Library for Parallel Computational Geometry", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/ParGeo", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nJessica Shi and Julian Shun.\nParallel Algorithms for Butterfly Computations.\nMassive Graph Analytics, pp. 287-330, 2022. (Earlier version appears in APOCS 2020.)", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Algorithms for Butterfly Computations", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeshi96/parbutterfly", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nQuanquan Liu, Jessica Shi, Shangdi Yu, Laxman Dhulipala, and Julian Shun.\nParallel Batch-Dynamic Algorithms for k-Core Decomposition and Related Graph Problems.\nProceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), pp. 191-204, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Batch-Dynamic Algorithms for k-Core Decomposition and Related Graph Problems", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qqliu/batch-dynamic-kcore-decomposition", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nJessica Shi, Laxman Dhulipala, and Julian Shun.\nTheoretically and Practically Efficient Parallel Nucleus Decomposition.\nProceedings of the VLDB Endowment, 15(3), pp. 583-596, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "Theoretically and Practically Efficient Parallel Nucleus Decomposition", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeshi96/arb-nucleus-decomp", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nShangdi Yu, Yiqiu Wang, Yan Gu, Laxman Dhulipala, and Julian Shun.\nParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain.\nProceedings of the VLDB Endowment, 15(2), pp. 285-298, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yushangdi/parChain", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nYiqiu Wang, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun.\nGeoGraph: A Framework for Graph Processing on Geometric Data.\nACM SIGOPS Operating Systems Review, Vol. 55 Issue 1, pp. 38-46, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "GeoGraph: A Framework for Graph Processing on Geometric Data", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/GeoGraph", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper (https://github.com/ParAlg/gbbs/tree/master/benchmarks/CliqueCounting):\n\nJessica Shi, Laxman Dhulipala, and Julian Shun.\nParallel Clique Counting and Peeling Algorithms.\nProceedings of the SIAM Conference on Applied and Computational Discrete Algorithms (ACDA), pp. 135-146, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Clique Counting and Peeling Algorithms", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nYiqiu Wang, Shangdi Yu, Yan Gu, and Julian Shun.\nA Parallel Batch-Dynamic Data Structure for the Closest Pair Problem.\nProceedings of the International Symposium on Computational Geometry (SoCG), pp. 60:1-60:16, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "A Parallel Batch-Dynamic Data Structure for the Closest Pair Problem", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wangyiqiu/closest-pair", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nYiqiu Wang, Shangdi Yu, Yan Gu, and Julian Shun.\nFast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering.\nProceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pp. 1982-1995, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wangyiqiu/hdbscan", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper (https://github.com/ParAlg/gbbs/tree/master/benchmarks/SCAN/IndexBased):\n\nTom Tseng, Laxman Dhulipala, and Julian Shun.\nParallel Index-Based Structural Graph Clustering and Its Approximation.\nProceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pp. 1851-1864, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Index-Based Structural Graph Clustering and Its Approximation", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-11" + }, + "description": "Source code for paper (https://github.com/ParAlg/gbbs/tree/tri_merge/benchmarks/TriangleCounting/DhulipalaLiuShunYu20):\n\nLaxman Dhulipala, Quanquan Liu, Julian Shun, and Shangdi Yu.\nParallel Batch-Dynamic k-Clique Counting.\nProceedings of the SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS), pp. 129-143, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Batch-Dynamic k-Clique Counting", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nChangwan Hong, Laxman Dhulipala, and Julian Shun.\nExploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs.\nProceedings of International Conference on Parallel Architectures and Compilation Techniques (PACT), pp. 55-69, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "Exploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hochawa/gconn", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nLaxman Dhulipala, Changwan Hong, and Julian Shun.\nConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms.\nProceedings of the VLDB Endowment, 14(4), pp. 653-667, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "ConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-11" + }, + "description": "Source code for paper (https://github.com/ParAlg/gbbs/tree/semi_asymmetric): \n\nLaxman Dhulipala, Charles McGuffey, Hongbo Kang, Yan Gu, Guy Blelloch, Phillip Gibbons, and Julian Shun.\nSage: Parallel Semi-Asymmetric Graph Algorithms for NVRAMs.\nProceedings of the VLDB Endowment, 13(9), pp. 1598-1613, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "Sage: Parallel Semi-Asymmetric Graph Algorithms for NVRAMs", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\n\nYiqiu Wang, Yan Gu, and Julian Shun.\nTheoretically-Efficient and Practical Parallel DBSCAN.\nProceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pp. 2555-2571, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "Theoretically-Efficient and Practical Parallel DBSCAN", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wangyiqiu/dbscan", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nLaxman Dhulipala, Jessica Shi, Tom Tseng, Guy Blelloch, and Julian Shun.\nThe Graph Based Benchmark Suite (GBBS).\nProceedings of the Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA), pp. 1-8, 2020.\n\nWebsite: https://paralg.github.io/gbbs/", + "laborHours": 0.0, + "languages": [], + "name": "The Graph Based Benchmark Suite (GBBS)", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nJulian Shun.\nPractical Parallel Hypergraph Algorithms.\nProceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), pp. 232-249, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "Practical Parallel Hypergraph Algorithms", + "organization": "Contractor (CONTR)", + "permissions": { + 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See https://graphit-lang.org/ for more info.", + "laborHours": 0.0, + "languages": [], + "name": "GraphIt: A high-performance graph domain specific language", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GraphIt-DSL/graphit", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nLaxman Dhulipala, Guy Blelloch, and Julian Shun.\nLow-Latency Graph Streaming Using Compressed Purely-Functional Trees.\nProceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), pp. 918-934, 2019.", + "laborHours": 0.0, + "languages": [], + "name": "Low-Latency Graph Streaming Using Compressed Purely-Functional Trees", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ldhulipala/aspen", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nOmar Obeya, Endrias Kahssay, Edward Fan, and Julian Shun.\nTheoretically-Efficient and Practical Parallel In-Place Radix Sorting.\nProceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), pp. 213-224, 2019.", + "laborHours": 0.0, + "languages": [], + "name": "Theoretically-Efficient and Practical Parallel In-Place Radix Sorting", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/omarobeya/parallel-inplace-radixsort", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nYu Xia, Xiangyao Yu, William Moses, Julian Shun, and Srini Devadas.\nLiTM: A Lightweight Deterministic Software Transactional Memory System.\nProceedings of the International Workshop on Programming Models and Applications for Multicores and Manycores (PMAM), pp. 1-10, 2019.", + "laborHours": 0.0, + "languages": [], + "name": "LiTM: A Lightweight Deterministic Software Transactional Memory System", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yuxiamit/LiTM", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-07-12", + "metadataLastUpdated": "2023-07-12" + }, + "description": "The Deep Lynx MATLAB Adapter is a Python application that connects the Deep Lynx data warehouse with any MATLAB simulation.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python" + ], + "name": "Deep Lynx Matlab Adapter", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-MATLAB", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-07-12", + "metadataLastUpdated": "2023-07-12" + }, + "description": "This code provides natural language annotation and labels for multiple activities in high performance. The purpose is to enable machine learning for natural language processing algorithms with high performance computing systems. ", + "laborHours": 0.0, + "languages": [ + "python3", + "yml" + ], + "name": "Hpc Natural Language Understanding (nlu) Dataset", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HPC_Natural_Language_Understanding_-NLU-_Dataset", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-18" + }, + "description": "This software is a Rust package that interacts with the Application Programming Interface (API) suite provided by DeepLynx. A Rust codebase may import this package in order to have access to these methods for communicating with a DeepLynx instance.", + "laborHours": 0.0, + "languages": [ + "Rust" + ], + "name": "Deeplynx Rust Sdk", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-Rust_SDK", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "CmdWebCtrl is a utility that runs a given command and provides a simple web interface for viewing\nanything it outputs to the console, along with providing some simple controls for restarting it.", + "laborHours": 0.0, + "languages": [], + "name": "CmdWebCtrl", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GMLC-TDC/CmdWebCtrl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "ctrl-flow is a software that assists users in selecting a building control sequence from a library of control sequences that are implemented in the Modelica Buildings Library. The software allows selecting, configuring and editing the control sequences. It also allows exporting the sequence for use in building project design documents in Modelica-based simulations. The export will be in a json intermediate format, in the Modelica Language, in the Control Description Language and in English language format, such as in a Word document. The software functions as a web based application that includes a graphical user interface.", + "laborHours": 0.0, + "languages": [], + "name": "ctrl-flow v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-srg/ctrl-flow-dev.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "ERF is a next-generation regional atmospheric modeling code for simulation mesoscale atmospheric flows. Its capabilities include the ability to model advection, diffusion, turbulence, terrain and moisture physics.", + "laborHours": 0.0, + "languages": [], + "name": "Energy Research and Forecasting (ERF) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/erf-model/ERF", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "GPU-FPX is a tool based on NVBit that detects and analyzes floating-point exceptions on NVIDIA GPUs through binary instrumentation. Its purpose is to detect and report the occurrences of floating-point exceptions during numerical computations, offering efficient location detections and exception flow. GPUFPX achieves exceptional performance, being 16x faster than comparable prior tools, such as BinFPE.", + "laborHours": 0.0, + "languages": [], + "name": "GPU-FPX", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GPU-FPX", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "Given a pre-trained neural network, Inference-Engine performs maps network inputs to outputs by executing the forward pass through the provided network. Although the predominant programming language for machine-learning is Python, most high-performance computing (HPC) applications are written in Fortran, C, or C++. Inference-Engine aims to support HPC programs and is written in Fortran, a language with a large feature set supporting interoperability with C. This software exposes concurrency in a portable way by using standard language features that some modern Fortran compilers can exploit with various optimizations, including offloading computation to a Graphics Processing Unit (GPU). In particular, this software makes extensive use of Fortran's \"do concurrent\" parallel loop construct, implicitly parallel array statements, and pure procedures that can be invoked inside \"do concurrent\" blocks. Inference-Engine also supports dynamic choice of inference methods at runtime. Two current options include one method that uses Fortran's \"dot_product\" intrinsic function inside \"do concurrent\" blocks and another method that instead uses Fortran' \"matmul\" array intrinsic function. We plan to investigate automatic compiler offloading of \"do concurrent\" calculations to GPUs and compile-time substitution of optimized libraries such as the Basic Linear Algebra Library (BLAS) for \"matmul\" invocations. We also envision the potential for the choice of which method to use could happen at program launch based on in situ performance measurements on any given platform.", + "laborHours": 0.0, + "languages": [], + "name": "Inference-Engine v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/Inference-Engine", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "Direct-Sampling Beam Position Monitor is an FPGA gateware and embedded firmware that run on evaluation kits (either Xilinx ZCU111 or Xilinx ZCU208 ) that digitizes signals up to 4GSPS and 4GHz analog bandwidth, which can be synchronized to the accelerator timing system, providing synchronous sampling frequency/phase digitization. In addition to these capabilities, a proof of concept for a beam position monitor is also present, providing an envelope detection algorithm capable of determining the transverse beam position for an electron circular accelerator, such as ALS/ALS-U.", + "laborHours": 0.0, + "languages": [], + "name": "Direct-Sampling Beam Position Monitor (dsbpm) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/LBNL-DSBPM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "Software networking library to allow an FPGA ethernet core (such as Badger: https://gitlab.lbl.gov/hdl-libraries/bedrock/-/tree/master/badger) to be used in a soft-core processor or microcontroller.", + "laborHours": 0.0, + "languages": [], + "name": "Bantamweight Badger UDP support (BWUDP) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/BWUDP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "The dual event generator is a event-based timing system implementation capable of synchronizing (with respect to clock, events and triggers) hundreds of downstreams devices. This has been in use by ALS for many years and this is a similar implementation, but with a synchronized dual-master frequency , as opposed to just one in a more conventional approach.", + "laborHours": 0.0, + "languages": [], + "name": "Dual Event Generator (dual-evg) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/LBNL-Dual-EVG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-14" + }, + "description": "The Electricity Bill Calculator Library is a generic tool for manipulating the tariffs of electricity, with an emphasis on commercial Time-Of-Use (TOU) rates in the U.S. and residential Net Energy Metering tariffs in CA. Typical uses of the package are price signal generation and bill computation. To generate price signals from a specific tariff and given a time window, the tool creates a pandas dataframes containing the various components of the electricity charges, at each time step. This is particularly useful for Demand Response (DR) applications, such as price-based optimization of energy in buildings. The tool also computes bills given a building's power consumption and a specific tariff and returning the corresponding cost of electricity, as well as a breakdown per type of rate.", + "laborHours": 0.0, + "languages": [], + "name": "Electricity Bill Calculator (elecprice) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/elecprice", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "A software program for experimenting with holographic teleportation protocol on quantum computers. The code implements the protocol that was proposed in https://arxiv.org/abs/1911.06314.\n\nThe code is an end-to-end software solution that facilitates conducting the holographic teleportation experiments on state-of-the-art and emergent generations of QPUs supported by the Qiskit and tket SDKs. The code bundles all stages of an experiment as a single configurable workflow allowing faster development and experimentation cycles.\n\nFeatures:\n1. Easy switching between Qiskit and tket quantum compilers.\n2. Semi-automatic facilities for finding optimal compilation solutions beyond what Qiskit and tket provide by default.\n3. Experiment resolution scaling (based on automatic jobs' batching).\n4. Automatic experiment scaling over qubits.\n5. Automatic readout error mitigation.\n6. Automatic reproducibility analysis.\n7. Standalone error-mitigation tools (randomized compiling, mitigation with estimation circuits, zero-noise extrapolation)", + "laborHours": 0.0, + "languages": [], + "name": "QGLab v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ishapova/qglab", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "FABLE is a s light-weight software package for easy generation of quantum circuits that block encode arbitrary matrices.", + "laborHours": 0.0, + "languages": [], + "name": "FABLE v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QuantumComputingLab/fable", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "\tFusionML_RF consists of multiple codes and trained machine learning (ML) models that perform low-cost output modeling from the Genray-CQL3D. Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. For example, completing a single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time. On the other hand, these ML models achieve ~ms of inference time with high accuracy across the input parameter space. This software collection consists of multiple components. (1) codes that use ML methods and precomputed Genray-CQL3D simulation output to build regression models that enable approximate computations of Genray-CLQ3D outputs from arbitrary but physically meaningful input parameters (surrogate modeling); (2) three trained models created by the team, using a database of 16,000+ GENRAY/CQL3D simulations, to study the performance of ML models for surrogate modeling; (3) codes that load the trained models and simulation data, and then compute mean squared error between the models' predictions and the ground truth of simulation output data. This collection is being made available in conjunction with a scientific publication about the work to promote reusability and provide an artifact of the scientific work.", + "laborHours": 0.0, + "languages": [], + "name": "Fusion RF Modeling Machine Learning (FusionML_RF) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FusionRFModelingMachineLearning/genray-cql3d-ml", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-07-14", + "metadataLastUpdated": "2023-07-14" + }, + "description": "Surfactant is a tool to generate an SBOM for the files in a directory/system based on information contained in various file format, including but not limited to PE, ELF, Mach-O, Java classes, .NET\nassemblies, and various source code files/scripts. Gathered information can be output in a variety of different SBOM formats, and functionality is provided to manipulate and analyze SBOMs (merging, manual additions, querying info, etc). Users are able to add new features via a plugin system.", + "laborHours": 0.0, + "languages": [], + "name": "Surfactant", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Surfactant", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-07-17", + "metadataLastUpdated": "2023-07-17" + }, + "description": "'deeplynx-timeseries-loader' is a library designed to make it as easy as possible for users to download and access timeseries or tabular data from DeepLynx.", + "laborHours": 0.0, + "languages": [ + "Rust" + ], + "name": "Deeplynx-loader", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-Timeseries-Loader", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-07-18", + "metadataLastUpdated": "2024-01-19" + }, + "description": "Symmetry-protected subspaces in quantum systems are subspaces demarcated by a conserved quantity of that quantum system. We introduce two classical algorithms, which efficiently compute and elucidate features of these subspaces. The first algorithm explores the entire symmetry-protected subspace of an initial state in time complexity linear to the size of the subspace by closing local basis state-to-basis state transitions. The second algorithm determines, with bounded error, if a given measurement outcome of a dynamically-generated state is within the symmetry-protected subspace of the state in which the dynamical system is initialized. This software is paired with the paper of the same name at https://arxiv.org/pdf/2302.08586.pdf.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "ADoSPSiQS (Automated Detection of Symmetry-Protected Subspaces in Quantum Simulations ) [SWR-23-55]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SymmetryDetectionForQuantumSim", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-07-18", + "metadataLastUpdated": "2023-07-18" + }, + "description": "A Python script that parsers Saleae Logic 2 output files into useful data sets.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Saleae Logic 2 Output File Parser", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Saleae_Output_Parser", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-07-20", + "metadataLastUpdated": "2023-07-20" + }, + "description": "The Resilience Development for Electric Energy Delivery Systems (ResDEEDS) tool walks users through the process of evaluating electric energy delivery systems (EEDS) for resiliency. It implements the steps of the INL Resilience Framework for EEDS and provides automated tracking of resilience planning and suggestions for mitigating hazards.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Resilience Development For Electric Energy Delivery Systems", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/ResDEEDS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-07-21", + "metadataLastUpdated": "2023-07-25" + }, + "description": "AMSLib provides infrastructure to tightly couple multi-scale physics simulation code with ML surrogate\nmodel inference. It provides a wholistic runtime execution paradigm to supports uncertainty quantification,\nsurrogate model inference, persistent data storing throughout the execution of a simulation.", + "laborHours": 0.0, + "languages": [], + "name": "Autonomous MultiScale Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.0.alpha" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-07-24", + "metadataLastUpdated": "2024-10-16" + }, + "description": "Battery Lifetime Analysis and Simulation Toolsuite (BLAST) provides a library of battery lifetime and degradation models for various commercial lithium-ion batteries from recent years. Degradation models are identified from publicly available lab-based aging data using NREL's battery life model identification toolkit. The battery life models predicted the expected lifetime of batteries used in mobile or stationary applications as functions of their temperature and use (state-of-charge, depth-of-discharge, and charge/discharge rates). Model implementation is in both Python and MATLAB programming languages. The MATLAB code also provides example applications (stationary storage and EV), climate data, and simple thermal management options. For more information on battery health diagnostics, prediction, and optimization, see NREL's Battery Lifespan webpage.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python", + "Jupyter Notebook" + ], + "name": "BLAST-Lite (Battery Lifetime Analysis and Simulation Tool - Lite) [SWR-22-69] Related to: BLAST aka: BLAST-Py", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BLAST-Lite", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-07-25", + "metadataLastUpdated": "2023-11-13" + }, + "description": "The Wind Farm Wake Comparison Framework (Wcomp) is a software tool to facilitate the comparison of a specific collection of wind farm wake modeling tools: Python-based, steady-state, analytical wake modeling utilities. Wcomp integrates another software project, windIO, to create a consistent method for describing a wind farm flow control problem. Additionally, a data structure is included to represent the outputs a wind farm flow control simulation. Well-described interfaces allow existing wake modeling tools to plug into this framework.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Wcomp (Wind Farm Wake Comparison Framework) [SWR-23-72]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/wcomp", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-07-25", + "metadataLastUpdated": "2023-07-25" + }, + "description": "See the SAM\u2122 website to build a desktop version of the National Renewable Energy Laboratory's (NREL's) System Advisor Model\u2122 (SAM). https://sam.nrel.gov/\n\nThe System Advisor Model\u2122 (SAM\u2122) is a free techno-economic software model that facilitates decision-making for people in the renewable energy industry:\n\n-Project managers and engineers\n-Policy analysts\n-Technology developers\n-Researchers\nSAM can model many types of renewable energy systems:\n\n-Photovoltaic systems, from small residential rooftop to large utility-scale systems\n-Battery storage with Lithium ion, lead acid, or flow batteries for front-of-meter or behind-the-meter applications\n-Concentrating Solar Power systems for electric power generation, including parabolic trough, power tower, and linear Fresnel\n-Industrial process heat from parabolic trough and linear Fresnel systems\n-Wind power, from individual turbines to large wind farms\n-Marine energy wave and tidal systems\n-Solar water heating\n-Fuel cells\n-Geothermal power generation\n-Biomass combustion for power generation\n-High concentration photovoltaic systems\n\nSAM's financial models are for the following types of projects:\n\n-Residential and commercial projects where the renewable energy system is on the customer side of the electric utility meter (behind the meter), and power from the system is used to reduce the customer's electricity bill.\n\n-Power purchase agreement (PPA) projects where the system is connected to the grid at an interconnection point, and the project earns revenue through power sales. The project may be owned and operated by a single owner or by a partnership involving a flip or leaseback arrangement.\n\n-Third party ownership where the system is installed on the customer's (host) property and owned by a separate entity (developer), and the host is compensated for power generated by the system through either a PPA or lease agreement.\n\nFor a more detailed description of SAM, see Blair et al. (2018), System Advisor Model (SAM) General Description (Version 2017.9.5), NREL/TP-6A20-70414. \n\nhttps://www.nrel.gov/docs/fy18osti/70414.pdf\n", + "laborHours": 552915.2, + "languages": [ + "C++", + "LK script" + ], + "name": "SAM\u2122 (System Advisor Model\u2122) [SWR-16-02, SWR-10-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SAM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2020.2.29" + }, + { + "contact": { + "email": "haunab@ornl.gov" + }, + "date": { + "created": "2023-07-25", + "metadataLastUpdated": "2023-08-02" + }, + "description": "Tools for building containers to ease building Klipper and CanBoot for multiple targets.\n\nNote: This is being submitted to DOECODE as per instructions received after providing notification of creation of IP outside of work as part of a site-specific IP assignment agreement. This work was not funded by, nor was any work performed under any DOE contract.", + "laborHours": 0.0, + "languages": [ + "Bash", + "C", + "Z shell" + ], + "name": "Klipper Firmware Tools", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laikulo/Klipper-firmware.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "realsimxil@gmail.com" + }, + "date": { + "created": "2023-07-27", + "metadataLastUpdated": "2023-07-28" + }, + "description": "Real-Sim is a multi-resolution X-in-the-loop simulation framework to support inclusive testing and evaluation of CAVs before actual implementation in the real world. Real-Sim framework connects different simulation components and integrates various traffic and vehicle simulation tools, virtual environments, and XIL systems through a Flexible Interface for XIL Simulation (FIXS). Connections among different tools are transparent to users and handled by the interface behind the scenes. Co-simulation of various vehicle and traffic simulation tools with different XIL systems can be easily achieved and become a transparent \"plug-and-play\" process to users.", + "laborHours": 0.0, + "languages": [], + "name": "Real-Sim Flexible Interface for X-in-the-loop Simulation (FIXS)", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Real-Sim-XIL/FIXS", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "Metabolic Context Species Interaction Networks (MetConSIN) generates microbe-metabolte and metabolite-metabolite interaction networks using constraint based metabolic modeling. To do this, MetConSIN simulates with the dynamic FBA system and saves the sequence of interaction networks implied by that system, as well as the time-average network.", + "laborHours": 0.0, + "languages": [], + "name": "MetConSIN", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/metconsin", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "This code enables fitting a model of an infectious disease outbreak, customized for when available data is a combination of case counts and symptom survey responses. This is just a small bit of code being used only for a publication; we need to release it to fulfill a journal's requirement that our work be reproducible.", + "laborHours": 0.0, + "languages": [], + "name": "Outbreak analysis from case count and survey data", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eeg-lanl/cov2-china2022", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "HopPyBar is a python program to import, analyze, and export split-Hopkinson pressure bar (SHPB, also known as Kolsky bar) data. Traditional analysis offers a black box approach, where input data is converted to analyzed output by performing a series of calculations without user involvement. This program serves as a developmental platform to \"white box\" the data analysis process. Data streams can be captured (in-situ) to enable advanced or unconventional analyses, statistics, and comparisons. Additionally, the program is geared towards the standardized forms of input and output used at LANL to streamline analysis, but the open nature of the program makes additional input/output schemes straightforward to add. General workflow will import SHPB data in one of a number of formats, identify relevant portions of data signals, and convert to stress-strain-strain rate to show material behavior as a function of dynamic testing.", + "laborHours": 0.0, + "languages": [], + "name": "HopPyBar", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/HopPyBar", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "LCA-PyTorch is a code repository which contains PyTorch implementations of the Locally Competitive Algorithm (LCA), which is a biologically-plausible sparse coding model. LCA-PyTorch allows for the training, testing, and analysis of single layer LCA networks, multi-layer LCA networks, and hybrid LCA-based deep neural network models on a wide variety of applications and data types. LCA-PyTorch was developed in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning. LCA-PyTorch interfaces heavily with the open-source PyTorch Python package. ", + "laborHours": 0.0, + "languages": [], + "name": "LCA-PyTorch", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/lca-pytorch", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "We would like to disclose two scripts, written in Jupyter notebook, in which we implement the \"Blackout Diffusion Process\" described in the manuscript \"Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces\" (LA-UR-23-20509), to be submitted to the International Conference of Machine Learning (ICML). The abstract of the manuscript is append below. \n\n==\nTypical generative diffusion models rely on a Gaussian diffusion process for training the backward transformations, which can then be used generate samples from Gaussian noise. However, real world data often takes place in discrete-state spaces, which occur in many scientific applications. Here, we develop a theoretical formulation for arbitrary discrete-state Markov processes in the forward diffusion process. We relate the theory to the existing continuous-state Gaussian diffusion and identify the corresponding reverse-time stochastic process and score function in the continuous-time setting, and the reverse-time mapping in the discrete-time setting. As an example of this framework, we introduce \"Blackout Diffusion\", which learns to produce samples from an empty image instead of from noise. Numerical experiments on the CIFAR-10 dataset confirm the feasibility of generative diffusion modeling in a discrete space. Generalizing from specific (Gaussian) forward processes to a more general framework also sheds light on how to interpret generative diffusion models and their mathematical structure, which we comment on.", + "laborHours": 0.0, + "languages": [], + "name": "Code for the manuscript titled \"Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Blackout-Diffusion", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "\"Bluehat\" is a collection of python routines to facilitate the analysis of spectral (multispectral and hyperspectral) remote sensing\nimagery, with an emphasis on various kind of target detection. The package provides collections of utilities that developers can use in producing algorithms for specific target detection scenarios.\n\nAlthough \"bluehat\" is mostly expected to be used for remote sensing imagery (which often comes from satellite sensors), and although early versions of \"bluehat\" were used to design algorithms that were then rewritten for onboard processing; \"bluehat\" itself is not not specially designed for space and/or satellite application.", + "laborHours": 0.0, + "languages": [], + "name": "BlueHat", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jt-lanl/bluehat", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "reevest@ornl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "Phase-field framework built on the Cabana particle library", + "laborHours": 0.0, + "languages": [], + "name": "CabanaPF", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/CabanaPF", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "luszczek@icl.utk.edu" + }, + "date": { + "created": "2023-07-30", + "metadataLastUpdated": "2023-07-30" + }, + "description": "SLIP (Surrogate Launching and Integration Platform) is a software ecosystem for downloading and running ML/AI benchmarks.\nSLIP automatically downloads and sets up the code and data running a benchmark. The large data sets and model code are cached locally with a specific ID within a designated cache directory.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SLIP (Surrogate Launching and Integration Platform)", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/icl-utk-edu/slip.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "luszczek@icl.utk.edu" + }, + "date": { + "created": "2023-07-30", + "metadataLastUpdated": "2023-07-30" + }, + "description": "SABATH provides benchmarking infrastructure for evaluating scientific ML/AI models. It contains support for scientific machine learning surrogates from external repositories. The software dependences are explicitly exposed in the surrogate model definition, which allows the use of advanced optimization, communication, and hardware features.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SABATH: Surrogate AI Benchmarking Applications' Testing Harness", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/icl-utk-edu/sabath.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-07-31", + "metadataLastUpdated": "2023-07-31" + }, + "description": "GPLaSDI is a software that introduces GPLaSDI, a novel LaSDI-based framework that relies on Gaussian\nprocess (GP) for latent space ODE interpolations. Using GPs offers two significant advantages. First, it\nenables the quantification of uncertainty over the reduced order model (ROM) predictions. Second,\nleveraging this prediction uncertainty allows for efficient adaptive training through a greedy selection of\nadditional training data points. This approach does not require prior knowledge of the underlying PDEs.\nConsequently, GPLaSDI is inherently non-intrusive and can be applied to problems without a known PDE\nor its residual. We demonstrate the effectiveness of our approach on the Burgers equation, Vlasov\nequation for plasma physics, and a rising thermal bubble problem. Our proposed method achieves\nbetween 200 and 100,000 times speed-up, with up to 7% relative error.", + "laborHours": 0.0, + "languages": [], + "name": "GPLaSDI: Gaussian Process Latent Space Dynamics Identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GPLaSDI", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2024-09-09" + }, + "description": "SAND2022-3463 O\nThis code is intended to accompany the journal manuscript, \u201cSub-resolution modeling of the apparent mass loss in quantitative broadband X-ray radiography.\" The manuscript covers in detail how to improve the quantitative mass distribution measurements made for optical diagnostics of multiphase flows. The code contains four separate script files in MATLAB format to support the objective of improving mass measurements.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 349.6, + "languages": [ + "MATLAB" + ], + "name": "Codes for sub-resolution modeling of the apparent mass loss in quantitative broadband X-ray radiography", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/X-ray-Imaging-Apparent-Mass-Loss-Error", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2024-09-09" + }, + "description": "SAND2022-7288 O\nThe exodus_helper Python package is a set of tools that allows a user to query and create datasets in the Exodus II format for use in finite element analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 2280.0, + "languages": [ + "Python" + ], + "name": "exodus_helper", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/exodus_helper", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-02" + }, + "description": "SAND2022-7062 O\nThe Analytical Tool to Evaluate Heterogeneous Neuromorphic Architectures (ATHENA) quickly evaluates performance metrics like energy, area, and latency for an AI/ML network. It currently supports the evaluation of analog neural networks. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 203832.0, + "languages": [ + "C++", + "Python" + ], + "name": "Analytical Tool to evaluate Heterogeneous Neuromorphic Architectures (ATHENA)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "We introduce the Binned Large Interval Network Kernel approach for scoring fragmentation mass spectra similarity which takes advantage of sparse matrix multiplication. This enables BLINK to perform 100 million comparisons while maintaining 98% accuracy in 2.2 seconds making it over 1,000 times faster than the current implementations.", + "laborHours": 0.0, + "languages": [], + "name": "BLINK v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biorack/blink", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "\tAutodiDAQt automates and simplifies writing data acquisition software for spectroscopy and microscopy. 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This reduces the time to get experiments running from months to hours and increases reliability for scientific experiments.\n\nAutodiDAQt metaprograms from instrument drivers directly, where possible.", + "laborHours": 0.0, + "languages": [], + "name": "AutodiDAQt v1.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chstan/autodiDAQt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "Caffeine is the CoArray Fortran Framework of Efficient Interfaces to Network Environments. Caffeine aims to produce a parallel runtime library that will support Fortran compilers with a programming-model-agnostic application binary interface (ABI) to various lower-level communication libraries. The current version of Caffeine uses the GASNet-EX networking middleware, also developed at Berkeley Lab. On many combinations of applications and platforms, GASNet-EX outperforms the widely used Message Passing Interface (MPI). Through GASNet-EX's support for communicating between graphics processing units (GPU), GASNet-EX has features that specifically target the emerging, leading-edge exascale computing platforms.", + "laborHours": 0.0, + "languages": [], + "name": "Caffeine v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/berkeleylab/caffeine", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "HAMR is a library defining an accelerator technology agnostic memory model that bridges between accelerator technologies (CUDA, HIP, ROCm, OpenMP, Sycl, OpenCL, Kokos, etc) and traditional CPUs in heterogeneous computing environments. HAMR is light weight and implemented in modern C++. HAMR can be used to manage memory with in a single code or as a data model for coupling codes in a technologically agnostic way. HAMR provides a Python module for coupling C++ and Python codes which implements zero-copy data transfers to and from Python using the Numpy array interface and Numba CUDA array interface protocols.", + "laborHours": 0.0, + "languages": [], + "name": "HAMR - Heterogeneous Accelerator Memory Resource (HAMR) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-EESA/HAMR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "PDCVOL is an extension software originated from the Proactive Data Containers (PDC) software (LBNL Track Code 2017-098), it is an HDF5 VOL connector that allows HDF5 applications to store and access data with the PDC system without the need to modify their code. The application can take advantage of the PDC optimization features and achieve better I/O performance.", + "laborHours": 0.0, + "languages": [], + "name": "PDC VOL Connector (PDCVOL) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/vol-pdc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "This is a data analysis package designed for analyzing correlation functions generated with lattice QCD calculations. The purpose is to make a centralized software suite for use by all members of my collaboration, so that various members can spend less time developing their own analysis codes, and more time extracting the interesting physics from our calculations. There are also 3 independent collaborations that have expressed interest in using this code, so there is some expectation it will be used in the broader international lattice QCD community.", + "laborHours": 0.0, + "languages": [], + "name": "Collaboration 51 Correlation Function Analysis Suite (c51_corr_analysis) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/callat-qcd/c51_corr_analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "This is a web service that allows users to request an identifier for a sequence in a specific database, given another identifier for the same sequence with respect to another given database. This process is called ID mapping. It's a minimalist service (fast, no database server) that will be significantly easier to use in a container environment.", + "laborHours": 0.0, + "languages": [], + "name": "Sequence ID Map (SeqIDMap) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/jgi-kbase/seqidmap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "The code consists of two scripts that assign functional domains to RNA virus proteins. They achieve this by aggregating the outputs of multiple freely available tools and clustering the domains into high hierarchy clusters.", + "laborHours": 0.0, + "languages": [], + "name": "RNA virus annotation pipeline (RVAP) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/rvmt-jgi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "ImpactX is the next generation of the IMPACT-Z code. It is a s-based simulation code for modeling intense beams in particle accelerators using symplectic tracking methods and includes collective effects. It is multi-node parallel and supports modern compute hardware such as GPUs, modern algorithms such as mesh-refinement and realistic geometries (embedded boundaries).", + "laborHours": 0.0, + "languages": [], + "name": "ImpactX v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-WarpX/impactx", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "\tThe Feedstock to Function (F2F) tool was designed to help scientists and companies explore viable biofuels and bioproducts early in the R&D cycle to support more productive experimentation, while reducing early-stage exploration from months/years to days/weeks (feedstock-to-function.lbl.gov). The tool focuses on using machine learning to predict biomass-derived molecule properties, while evaluating the cost, benefits, and risks of promising molecules for sustainable aviation fuels. The tool successfully predicts (within 15% of experimental values) high-throughput aviation properties for over 10,000 molecules while enabling users to explore new possibilities and opportunities rapidly and effortlessly. It also links to lightweight life-cycle analysis and techno-economic tools for cost and emissions analyses. Predicted molecule properties include melting point, boiling point, flash point, yield sooting index, and heat of combustion.\n\nTo date, F2F is more expansive and outperforms several other molecule property prediction models while enabling users (scientists, companies, and policy makers) to explore new possibilities and opportunities rapidly and effortlessly. F2F provides the foundation for developing an adaptive computational tool that predicts properties, cost, benefits, and risk of promising new and uncertified alternative jet fuel pathways and their blending effects.", + "laborHours": 0.0, + "languages": [], + "name": "Feedstock to Function (F2F) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tylerhuntington/feedstock-to-function", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "smol is a Python implementation of the Cluster Expansion Method and extensions of this methodology; which is used to fit applied lattice models from first principle calculations for subsequent use in Monte Carlo simulations for computing thermodynamic and statistical properties of atomic configuration. smol has a several notable advantages over other similar software packages. The first being its Python implementation which makes it easy to use even for users with little software and coding skills. Despite being implemented in Python, essential Monte Carlo routines are implemented in Cython such that performance is not compromised and is competitive even to similar software implemented in C/C++. Furthermore, the package has specific functionality for handling complex ionic materials (such as cathodes and electrolytes) that is not readily available in other packages. Lastly, the software has a flexible and modular design with the intention of making it fast and efficient to develop and extend the methodology.", + "laborHours": 0.0, + "languages": [], + "name": "Statistical Mechanics on Lattices (smol) v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CederGroupHub/smol", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "deep-taxon is a package for training neural networks for classifying genomic sequence data. deep-taxon provides tools for converting genomic sequence data into high performance computing file formats capable of training neural networks at scale.", + "laborHours": 0.0, + "languages": [], + "name": "deep-taxon v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exabiome/deep-taxon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "villezk@ornl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-11-21" + }, + "description": "BOOTS is a package for optimal selection of candidate operating points in large-scale manufacturing applications. It is designed to optimally select operating points to maximize predicted values of product quality and resource efficiency according to a data-driven model. The package is based on the use of a multi-input multi-output (MIMO) Gaussian process model to describe the relationships between inputs (operating points) and outputs (product quality and resource efficiency). This package does not provide any site- or process-specific information.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "BOOTS: Bayesian Optimization for Optimal Test Selection", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/krisvillez/boots", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "v1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Model for HVAC system optimization in multi-family housing market.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Model Based Real Time HVAC Systems Optimization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Optimization of HVAC systems in multi-family housing market.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "System Architecture for Real-time HVAC optimization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "SAND2022-12898 O\nDGTile is a lightweight C++17 adaptive mesh library meant to support explicit discontinuous Galerkin applications on high performance computing machines. DGTile uses a block-based adaptive mesh refinement approach, where the underlying mesh data structure is an octree in three dimensions, where each leaf node of the tree represents a Cartesian grid. Over each grid, DGTile provides modal discontinuous Galerkin basis functions to facilitate simulations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++17" + ], + "name": "DGTile", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DGTile", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-03", + "metadataLastUpdated": "2023-08-08" + }, + "description": "This Git repository contains codes for the 'Graph Learning in Physical-informed Mesh-reduced Space for Real-world Dynamic Systems' paper that will be published in 2023 SIGKDD. This work uses physical-informed prior (PiP) information to learn and predict fluid dynamics in a reduced mesh space. We propose a two-stage graph-based model for fluid velocity field reconstruction and prediction. In the first stage, we learn a subgraph autoencoder to summarize the information in a mesh-reduced space using physical-informed priors. In the second stage, we learn a dynamics predictor to predict subgraph evolution. We demonstrate the effectiveness of our model on two fluid flow datasets: lid-driven cavity flow data and cylinder flow data. This code is also applicable for any other dynamic systems with corresponding data.", + "laborHours": 0.0, + "languages": [], + "name": "Graph Learning in Physical-informed Mesh-reduced Space for Real-world Dynamic Systems", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Yeping-Hu/MeshGraph-RealDynSys", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2024-01-05" + }, + "description": "FLORIS is a controls-focused wind farm simulation software incorporating steady-state engineering wake models into a performance-focused Python framework. It has been in active development at NREL since 2013 and the latest release is FLORIS v3.5.Online documentation is available at https://nrel.github.io/floris.\n\nThe software is in active development and engagement with the development team is highly encouraged. If you are interested in using FLORIS to conduct studies of a wind farm or extending FLORIS to include your own wake model, please join the conversation in GitHub Discussions!\n\nhttps://www.nrel.gov/wind/floris.html", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "FLORIS v3.5 Wake Modeling and Wind Farm Controls Software [SWR-17-43 and SWR-14-20]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/floris", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.5" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2023-08-07" + }, + "description": "SAND2023-11957O\nSDynPy software can be used in digital signal processing, modal analysis, and geometry algorithms that are available in open literature, specifically the Synthesize Modes and Correlate and polynomial-based multiple reference modal fitters. This software can be used to perform structural dynamic testing and analysis. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SDynPy: A Structural Dynamics Python Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sdynpy", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": " v.0.6.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2023-08-07" + }, + "description": "SAND2023-12116O\nWiretap is an offensive security software package meant for penetration testers and red teams. Unlike a traditional VPN, Wiretap transparently proxies networking traffic without requiring administrator privileges. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Golang", + "Go" + ], + "name": "Wiretap", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/wiretap", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.5" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-15186 O\nYoDawg CI Runner builds a container that hosts a Gitlab runner as a service. It provides the ability to run Podman in a nested fashion as part of a CI workflow (i.e., \"Podman-in-Podman\u201d). This allows CI jobs to be run on HPC resources by standard users through an on-demand batch scheduler. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 45.6, + "languages": [ + "Dockerfile", + "Shell" + ], + "name": "YoDawg CI Runner", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/yodawg-ci-runner", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2023-08-08" + }, + "description": "SAND2022-14468 O\nThe Python ISMAGS subgraph isomorphism algorithm is a translation of a java-based algorithm. It used for finding unique occurrences of a motif subgraph within a larger network graph. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Python ISMAGS subgraph isomorphism algorithm", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ISMAGS-in-Python", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-08", + "metadataLastUpdated": "2023-08-08" + }, + "description": "SAND2023-11967O\nGeneric Data Display (GD2) is a real-time data visualization application that can display user-defined input data. The open-source software is comprised of a back end system written in Python, and a front end user interface written in JavaScript. The back end system collects data from a variety of input sources, such as message queue, HTTP, XML, JSON, and others. The front end displays data in an Open MCT web interface, and users can configure the system by providing JSON formatted configuration files. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "python" + ], + "name": "Generic Data Display (GD2)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/generic-data-display", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-08-08", + "metadataLastUpdated": "2023-09-19" + }, + "description": "SDOM is designed to accurately represent the operation of energy storage across different timescales, including long-duration and seasonal applications, and the spatiotemporal diversity and complementarity among VRE sources. SDOM uses an hourly temporal resolution, a fine spatial resolution for VRE sources, and a 1-year optimization window. SDOM assumes that all builds of VRE are accompanied by sufficient additional transmission capacity to allow full utilization of these additional resources. Nuclear, hydropower, and other renewable generation (e.g., biomass and geothermal energy sources) are fixed based on operational data (time series) for a given year; thus, SDOM minimizes total system cost using conventional generators as balancing units and using VRE and storage technologies to achieve a user-defined carbon-free or renewable energy target. The total system cost includes capital costs, fixed operation-and-maintenance (FO&M) costs, variable operation-and-maintenance (VO&M) costs, and fuel cost for power generation and storage technologies.", + "laborHours": 0.0, + "languages": [ + "GAMS", + "Python" + ], + "name": "SDOM (Storage Deployment Optimization Model) [SWR-21-73]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SDOM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-08", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-11904O\nThis collection of original scripts is made up of Python, Makefile, and Vim. Each script performs a single commonly used function in an encapsulated manner that can easily integrate into larger application-specific software. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1641.6, + "languages": [ + "C", + "Python", + "Vim Script" + ], + "name": "Useful python scripts", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/penney-scripts", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-08", + "metadataLastUpdated": "2024-07-29" + }, + "description": "SAND2023-05829O\nROMNet is a toolbox built on the Tensorflow library for training reduced-order, neural operator surrogate models. The software is used for training reduced order neural operator surrogate models for dynamical systems applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 16446.4, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "ROMNet: Neural-Network-Based Surrogates for Reduced-Order Model Dynamics", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/romnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A tool for developing parametric inputs for other software.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/gparm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/gparm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2023-08-09" + }, + "description": "pylibROM introduces python binder for libROM through pybind11. Through python interface, users who are familiar with python can take advantage of capabilities available in libROM that is fully parallelized C++ library for reduced order modeling. libROM itself is an open source code developed at LLNL. libROM is available at https://github.com/LLNL/libROM .", + "laborHours": 0.0, + "languages": [], + "name": "python binder for libROM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pylibROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2023-08-10" + }, + "description": "SAND2023-05661O\nThe proactive intrusion detection and mitigation system (PIDMS) provides grid-edge situational awareness for cybersecurity defense by capturing real-time distributed energy resource (DER) network traffic and performance data with a novel approach that improves the detection and prevention of cyber-physical attacks. \nThe PIDMS addresses the grid-edge security gap with real-time analysis of both network traffic and photovoltaic performance data to deliver a novel, cyber-physical intrusion detection system (IDS) approach that increases the accuracy and effectiveness of detection and mitigation. \nThis hybrid IDS analysis enables dual monitoring that increases the workload of the adversary; both cyber and physical data would have to be simultaneously spoofed to evade detection. Furthermore, monitoring and analyzing cyber data are insufficient in some cases. For example, in an insider threat aimed at disrupting inverter grid-support functions where proper credentials and authentication are achieved, only the altered PV performance would indicate abnormal behavior. All in all, the PIDMS provides novel capabilities for:\n\u2022\tDistributed, real-time cyber-physical detection and mitigation analysis\n\u2022\tCybersecurity defense for grid-edge systems\n\u2022\tAnalysis framework that can provide situational awareness across the transmission, distribution, and DER systems\nThe PIDMS sensor is designed to collect cyber-physical data, process the data using machine-learning algorithms, detect abnormal events, and deploy mitigations. \nWith these goals, the main functional PIDMS objectives are: \n\u2022\tCapability to collect cyber-physical data\n\u2022\tOnboard storage of cyber-physical data\n\u2022\tPeer-to-peer communication\n\u2022\tComputationally efficient machine-learning algorithms\n\u2022\tOnline cyber-physical data analysis\n\u2022\tAlerting/visualization capabilities\n\u2022\tMitigation deployment capability with bump-in-the-wire (BITW) implementation \nEach of these functional objectives enable PIDMS to perform effective cyber-physical intrusion detection and mitigation.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Bash Scripts", + "Python" + ], + "name": "Proactive Intrusion Detection and Mitigation System", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2023-08-10" + }, + "description": "+++ This repository was archived by the owner on May 4, 2020. It is now read-only. +++\n\nAn offshore balance of station (BOS) model for estimating the costs in assembly, installation, financing, and decommissioning of offshore wind plants.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python", + "makefile" + ], + "name": "OffshoreBOS (Offshore Wind Balance-of-Station (BOS) Model) \"S\" was originally \"System\" [SWR-16-27]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/OffshoreBOS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Public release of a version of the cross-reference capability of the UBID software that is\nfeature-limited to cross-reference via Jaccard similarity coefficient (viz., intersection-over-union or \"IoU\") [2] over a\nquadtree-based spatial index only.", + "laborHours": 440.8, + "languages": [], + "name": "Unique Building Identifier (UBID) cross-reference using intersection-over-union (IoU) over quadtreebased spatial index", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2024-07-30" + }, + "description": "SAND2023-05682O\nThe Energy Storage Sizing, Placement, and Valuation for Distribution software allows a user to simulate sizing, placement, and operation of one or more storage assets on a distribution grid. Among its features are measuring differences to determine the best combinations, and options for configuring and comparing results. This new simulation capability leverages the Open Distribution System Simulator and the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS).\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 6840.0, + "languages": [ + "Python", + "kvlang" + ], + "name": "Energy Storage Sizing, Placement and Valuation for Distribution Networks", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/quest-ssim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2023-08-09" + }, + "description": "NREL's advanced hosting capacity analysis and System Analysis Reports can help utilities, policymakers, and solar developers better understand the impact of adding new distributed photovoltaic (DPV) systems to the electrical distribution system.\nAdvanced hosting capacity analysis considers the thresholds at which new DPV systems will trigger upgrades or changes to the electrical distribution system and evaluates the cost of different options for expanding the hosting capacity.\n\nIt is one part of NREL's work to help stakeholders better understand the distribution system costs associated with integrating new DPV systems at different penetration levels.\n\nNREL's analysis uses a bottom-up methodology that involves simulating distribution systems. The analysis considers sequential increases in hosting capacity and corresponding upgrade costs from a baseline scenario with no DPV up to penetration levels greater than 100% of peak load.", + "laborHours": 0.0, + "languages": [], + "name": "DERHCAT (Distributed Energy Resource Hosting Capacity Analysis Tool) [SWR-16-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SystemsAnalysisReports", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-07249O\nThe 2-D Surface Temperature Simulation Data and Matlab software can estimate 2D temperature fields from electrical measurements along the edge of the 2D domain.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 91.2, + "languages": [ + "Matlab" + ], + "name": "2-D Surface Temperature Simulation Data and Matlab Scripts", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/2-D-Surface-Temperature-Simulation-Data", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-06591O\nThrough National Alliance for Water Innovation funding, Sandia will be contributing to the Water treatment Technoeconomic Assessment Platform (WaterTAP) project. WaterTAP is an open-source, Python-based software package that supports the technoeconomic assessment of full water treatment trains. WaterTAP includes a modular water treatment model library spanning a broad set of water treatment processes composed of unit, property, and costing models.", + "laborHours": 1656.8, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "Sandia Contributions to WaterTAP", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/watertap-org/watertap-renrtl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2023-08-10" + }, + "description": "SAND2023-06672O\nThe Protection Settings Optimizer (PSO) uses system and fault data as inputs to formulate the problem of calculating relay settings as a mixed integer, nonlinear optimization problem (MINLP). The MINLP is solved using a genetic algorithm-based optimizer that attempts to find settings to reduce the relay operating times. \n\nThe PSO protects the power system by using the steady-state fault voltages and currents, which then calculates the optimal device setting to protect the power system.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Protection settings optimizer", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Protection-settings-optimizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2023-08-14" + }, + "description": "SAND2023-06720O\nHod Carrier is a simple proof-of-concept library for moving data from host to NVIDIA BlueField device memory using remote direct memory access. The Hod Carrier software also facilitates research activities related to the potential uses of NVIDIA BlueField data processing unit devices. Using well-established technologies (e.g., RDMA over Infiniband), it will move data from the host to the data processing unit\u2019s memory. This software is a middleware utility for moving data without regard to its semantic meaning. Its operation is fundamentally unaffected by storage allocation. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python", + "bash shell scripts" + ], + "name": "Hod Carrier ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hod-carrier", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2023-08-10" + }, + "description": "SAND2023-05377O\nThe Modal Aerosol Model with 4 fixed modes (MAM4xx) is a performance-portable, C++ implementation for modeling the chemical reactions of aerosols in the atmosphere. MAM4xx is part of the Energy Exascale Earth System Model (E3SM). The E3SM project is an ongoing Earth system modeling, simulation, and prediction project that optimizes the use of DOE laboratory resources to meet the science needs of the nation and the mission needs of DOE. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "MAM4xx", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eagles-project/mam4xx", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Commercial Parking Application is a web-based application that alerts delivery drivers in real time to available parking\nspaces near their destinations. Parking availability can be viewed on a map in real-time, using sensor data supplied by\nexternal services. The app can be viewed with a web browser on a mobile device or PC. Currently the app supports\nconnections to real time sensors from Lacuna, Fybr, Cleverciti, and Automotus", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/parking", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/parking", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2023-08-10" + }, + "description": "SAND2023-05107O\nJuliaOceanWaves is a collection of packages and functions for modeling wave energy converters. The open-source software is designed to be used by the wave energy community to model new concepts, perform design optimization, and more.\nCapabilities include: \n\u2022\tA representation of ocean wave spectra and input/output (e.g. read from National Oceanic and Atmospheric Administration buoys) and post-processing functionalities; \n\u2022\tA solver for the linear potential flow radiation and diffraction equations for wave forcing on floating structures. \n\u2022\tSolving the floating body linear dynamics in the frequency domain. \nFuture additions to the software will include solving non-linear floating body dynamics in the time-domain through time-marching Ordinary Differential Equation solvers and the pseudo-spectral optimization method.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "JuliaOceanWaves", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmichelenstrofer/JuliaOceanWaves", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2023-08-10" + }, + "description": "SAND2023-05455O\nReposcanner provides a highly modular, extensible framework for defining routines for mining data from software repositories and performing analyses on that data to yield valuable insights on team behaviors. Reposcanner features seamless support for different version control platforms like GitHub, Gitlab, and Bitbucket; smart parsing of URLs; intelligent credential management capabilities; and a comprehensive test suite. Reposcanner is connected to the Exascale Computing Project and is intended for research purposes.", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "Reposcanner ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bssw-psip/bssw-psip.github.io", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-13", + "metadataLastUpdated": "2023-08-13" + }, + "description": "SAND2023-05484O\nQuantification of Uncertainties in Neural Networks (QUiNN) is a python library centered around various probabilistic wrappers over PyTorch modules in order to provide uncertainty estimation in neural network (NN) predictions. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "QUiNN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/quinn", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-13", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-05551O\nIgor, an open-source software, manages large clusters of users in a high-performance computing community. The systems allows users to choose an operating system and reserve and request hosts. The administrative side sets up and executes requests from users while simultaneously giving them tools to manage and enforce reservation policies and user access to the hosts.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 20930.4, + "languages": [ + "Go", + "Shell", + "JavaScript", + "Vue" + ], + "name": "Igor", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/igor", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-13", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-05510O\nGNATFinder is a software tool for extracting graphical neural activity threads (GNATs) from spiking neural networks. GNATFinder efficiently extracts GNATs from spiking neural network data. A GNAT is a graph that represents the causal relationships between individual spikes in a spiking network using a combination of the network connectivity structure and the timing of individual spikes. The software allows for identifying similar, repeating threads that often reappear in a dataset. Using quadtree data structures to recursively subdivide the time interval over which spikes were produced by the spiking network, GNATFinder allows for efficient pairwise comparisons of spike times to determine the degree of causal relatedness among all pairs of spikes in a dataset. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 440.8, + "languages": [ + "C", + "C++" + ], + "name": "GNATFinder", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GNATFinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-13", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-06608O\nThe EAM-X Potential Generator code establishes parameters that describe interactions between atoms in pure metals and alloys. The open-source software allows for the understanding of the relationship between general properties of atoms and macroscopic properties of metals. The code reads in values for the parameters of the model and outputs a table that describes the interactions. This code will be published by Acta Materialia along with two papers describing the method. The output of this code is meant for use by the LAMMPS simulation code created by Sandia. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [], + "name": "EAM-X Potential Generator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/EAM-X-Potential-Generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-15" + }, + "description": "CyQuanDyn is a collection of codes developed for modelling the phonon-induced carrier pumping in ZrTe5 system. Codes in the collection include 1) TLS: time-dependent two-orbital spinless fermion Bogoliubov-de Gennes Hamiltonian simulation, 2) TDSE: ab initio time-dependent Schr\u00f6dinger equation simulation of the ZrTe5 system under the periodic modulation of A1g Raman mode. Associated publication is T. Jiang, P. P. Orth, L. Luo, L.-L. Wang, F. Zhang, C.-Z. Wang, J. Zhao, K.-M. Ho, J. Wang, and Y.-X. Yao, Ab-Initio Simulations of Coherent Phonon-Induced Pumping of Carriers in ZrTe5. [arXiv:2304.08449 (2023).](https://arxiv.org/abs/2304.08449)", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "cyquandyn", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/lmqc/cyquandyn", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "version": "3.8" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Simulation tool for electrical grid security. It is possible to select from pre-loaded power system topologies, enable different grid controls\n(like AGC, power system stabilizer), add faults, tweak different parameters, add pre-modeled attack scenarios, and run\nbatch simulations to generate data needed for research.", + "laborHours": 0.0, + "languages": [], + "name": "GridSTAGE (aka PowerDrone)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/GridSTAGE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Identifying single molecules from fluorescence images obtained by a camera and obtain their location and intensity has\nmany applications. We have developed an efficient mathematical algorithm for this task and translate it into computer\nsoftware. Our algorithm are fast, stable and accurate comparing other programs to do the similar task. We have used our\nsoftware in several scientific research areas, such as tracking receptors in live cells, super resolution fluorescence\nmicroscopy, and counting mRNA copies in cells.", + "laborHours": 0.0, + "languages": [], + "name": "flifish", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hudehong/flifish", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-15" + }, + "description": "Mappymatch is a pure-python package developed and open sourced by the National Renewable Energy Laboratory. It contains a collection of \"Matchers\" that enable matching a GPS trace (series of GPS coordinates) to a map.\n\nAs of 8/14/2023, The current matchers are:\n\nLCSSMatcher: A matcher that implements the LCSS algorithm described in this paper. Works best with high resolution GPS traces.\n\nOsrmMatcher: A light matcher that pings an OSRM server to request map matching results. See the official documentation for more info.\n\nValhallaMatcher: A matcher to ping a Valhalla server for map matching results.\nCurrently supported map formats are:\n\nOpen Street Maps\n\nNOTE: This software was formerly known as YAMM (Yet Another Map-Matcher)", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Mappymatch [SWR 22-38]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mappymatch", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.4.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A transpiler that incorporates several key features. It includes a mapping and routing method, a\nprocess for decomposing gates into basis gates compatible with IBM machines, and a remapping method designed to\nenhance simulation performance. Compared to the state-of-art transpiler qiskit, we have dramatically speed up in various\nbenchmarks.", + "laborHours": 0.0, + "languages": [], + "name": "QASMTrans", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/qasmtrans", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-14" + }, + "description": "The BEopt\u2122 (Building Energy Optimization Tool) software provides capabilities to evaluate residential building designs and identify cost-optimal efficiency packages at various levels of whole-house energy savings along the path to zero net energy.\n\nThe BEopt software can be used to analyze both new construction and existing home retrofits, as well as single-family detached and multi-family buildings, through evaluation of single building designs, parametric sweeps, and cost-based optimizations.\n\nThe BEopt software provides detailed simulation-based analysis based on specific house characteristics, such as size, architecture, occupancy, vintage, location, and utility rates. Discrete envelope and equipment options, reflecting realistic construction materials and practices, are evaluated.\n\nThe BEopt software uses EnergyPlus\u00ae, the Department of Energy's flagship simulation engine. Simulation assumptions are based on ANSI/RESNET/ICC Standards and the Building America Housing Simulation Protocols.\n\nThe sequential search optimization technique used by the BEopt software:\n\nFinds minimum-cost building designs at different target energy-savings levels\nIdentifies multiple near-optimal designs along the path, allowing for equivalent solutions based on builder or contractor preference.\n\nDownload\n\nA BEopt\u2122 Version 3.0.1 Beta release (Mar. 16, 2023) is now available. Download the BEopt 3.0.1 Beta setup file.", + "homepageURL": "https://www.nrel.gov/buildings/beopt.html?utm_medium=print&utm_source=buildings&utm_campaign=beopt", + "laborHours": 0.0, + "languages": [], + "name": "BEopt\u2122 (Building Energy Optimization Tool) version 3.0.1 3/16/2023 [SWR-05-41]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://beopt.nrel.gov/BEopt_setup_2.8.0.0", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrel.gov/buildings/beopt.html?utm_medium=print&utm_source=buildings&utm_campaign=beopt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "3.0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-17" + }, + "description": "Building Energy Simulation Test (BESTEST) is an NREL-developed method to validate the qualitative performance of different whole building simulations engines relative to each other. \nhttps://www.nrel.gov/docs/legosti/old/6231.pdf\n\nThe purpose of this repository is to generate BESTEST test case models, run simulations, and populate data for ASHRAE Standard 140 reporting spreadsheets for EnergyPlus\u00ae based whole building simulation tools. It was originally setup for 2014 version of Standard 140. In May of 2022 it was updated to the 2020 version of Standard 140. This update included updates and additions to existing test suites, the bulk of which was in Section 5.2 (Building Thermal Envelope and Fabric Load Tests). We did not add Section 5.5 Airside HVAC Equipment Performance, but we hope to add that later in 2022. At some point we also hope to add Section 5.2.4 ground modeling, which is currently excluded.\n\nSupported Tools\nThe default IDF generation is based on the OpenStudio\u00ae CLI, but the workflow supports a 'Bring your own IDF' use case. Additionally, for non-EnergyPlus\u00ae based tools the post processing scripts can be used if simulation results are provided as a CSV file.The scripts on this repository should work on Mac, Windows, and Linux.\n\nDependencies\nInstall OpenStudio\u00ae 3.4.0\nmake sure command line can recognize the 'openstudio' command\nThis includes EnergyPlus\u00ae 22.1\nInstall Ruby on your system if it isn't already setup.\n2.7 is used for development but other versions may work\nSince OpenStudio has its own embedded Ruby, which is used for running measures, you don't necessarily have to use a version of Ruby supported by OpenStudio.\nInstall RubyXL Ruby gem\nThis is used to modify Microsoft Excel spreadsheets\nInstall Parallel Ruby gem\nThis allows the CLI to run simulations in parallel", + "laborHours": 68339.2, + "languages": [ + "Ruby", + "HTML" + ], + "name": "BESTEST-GSR (Building Energy Simulation Test - Generation Simulation and Reporting) 2023 [SWR 18-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BESTEST-GSR", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "OpenStudio 3.4.0 EnergyPlus 22.1 Std 140 ver 2020" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-14" + }, + "description": "The bifacial_radiance software contains a series of Python wrapper functions to make working with RADIANCE easier, particularly for the PV researcher interested in bifacial PV performance. For more information, check out our documentation, Tutorials in the form of Jupyter Notebooks, or refer to our Wiki and Issues page.\n\nInstallation\nhttps://youtu.be/4A9GocfHKyM This video shows how to install the bifacial_radiance software and all associated software needed. More info on the Wiki. Instructions are also shown below.\n\nFor detailed instructions of how to install bifacial_radiance, you can also refer to the installation guide.\n\nA GUI has been added in version 3.0. The GUI reads/writes all input parameters necessary to run a simulation, and runs the specified simulation by calling the correct functions with the specified parameters. So no need to use a journal or a script! But you still need to install following the procedure below.", + "laborHours": 13528.0, + "languages": [ + "C++", + "Python", + "Tex" + ], + "name": "Bifacial_Radiance v0.4.2 [SWR-18-03]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bifacial_radiance", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.2" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-14" + }, + "description": "bifacialvf is a self-contained view factor (or configuration factor) model which replicates a 5-row PV system of infinite extent perpendicular to the module rows. \nSingle-axis tracking is supported, and hourly output files based on TMY inputs are saved. Spatial nonuniformity is reported, with multiple rear-facing irradiances collected on the back of each module row.\n\nBilinear interpolation code add-on to bifacialvf (description below) to pre-generate IV arrays and bifacial coefficients, and to examine the energy production with back side irradiance mismatch for either a portrait or landscape module.\nIncluded are IV curves and bifacial info for a Yingli (standard) module.\n\nBased on the publication: \"A Practical Irradiance Model for Bifacial PV Modules\" B. Marion, S. MacAlpine, C. Deline, A. Asgharzadeh, F. Toor, D. Riley, J. Stein, C. Hansen 2017 IEEE Photovoltaic Specialists Conference, Washington DC, 2017 URL: https://www.nrel.gov/docs/fy17osti/67847.pdf\n", + "laborHours": 1018.4, + "languages": [ + "Python" + ], + "name": "bifacialVF - Bifacial PV View Factor model 2022 [SWR 17-58]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bifacialvf", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.8.1" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-08-15", + "metadataLastUpdated": "2023-08-15" + }, + "description": "ORCA is a modeling toolset to accelerate real-time control and optimization of digital twins, including virtual models of facilities, physical facilities, and interconnections to allow optimal control of physical facilities using virtual models. ORCA is enabled by INL's RAVEN and DeepLynx software codes.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Optimization Of Real-time Capacity Allocation", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/ORCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-08-15", + "metadataLastUpdated": "2023-09-11" + }, + "description": "NMACFoam is a computational fluid dynamics tool for simulating flow and solids transport in membrane-spacer channels pertaining to reverse osmosis or nanofiltration applications. It is developed on the OpenFOAM framework and allows for simulating spacers with complex geometries. It includes porous wall boundary conditions for membranes and can accurately capture concentration polarization effects. One can perform large calculations at module-scale domain sizes using high performance computing resources with NMACFoam, which scales to 1000s of processors for problems with 1-10 million cells.", + "laborHours": 0.0, + "languages": [ + "C++", + "python", + "C" + ], + "name": "NMACFoam (Numerical-model for Membrane-spacer Assemblies and Configurations in OpenFOAM) [SWR-23-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NMACFoam", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-08-15", + "metadataLastUpdated": "2023-09-14" + }, + "description": "This software is a suite of Python files and Jupyter notebooks supporting the calculation of cost and financial parameters for the Annual Technology Baseline (ATB) electricity data, including capital expenditures, levelized cost of energy, and debt fractions using the ATB input data.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "ATB-calc (Annual Technology Baseline Calculators) [SWR-23-60]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ATB-calc", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-15", + "metadataLastUpdated": "2023-08-15" + }, + "description": "This is the code for the paper [Multi-Agent Reinforcement Learning for Adaptive Mesh\nRefinement](https://arxiv.org/abs/2211.00801), published at AAMAS 2023. It contains the implementation\nof a new algorithm, called Value Decomposition Graph Network (VDGN), for applying multi-agent\nreinforcement learning to the problem of adaptive mesh refinement (AMR). It also contains the\nimplementation of a multi-agent environment for AMR on a linear advection problem. VDGN is the first\nlearning algorithm to display anticipatory refinement behavior in AMR, and it outperforms local error\nthreshold-based heuristic strategies.", + "laborHours": 0.0, + "languages": [], + "name": "Code for Value Decomposition Graph Network and environment for AMR on linear advection", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/011235813/marl-amr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Correlate packets to the responsible processes in Linux systems. Diagnose connections by adding process information.", + "laborHours": 0.0, + "languages": [], + "name": "HoneProject/Linux-Sensor", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HoneProject/Linux-Sensor", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Hone sensors are packet-process correlation engines that log the relationships between applications and the communications they are responsible for. Hone sensors are available for a variety of platforms including Linux, Windows, and MacOSX", + "laborHours": 0.0, + "languages": [], + "name": "HONE Sensor Wireshark Shim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HoneProject/Wireshark-Shim", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-16", + "metadataLastUpdated": "2024-01-03" + }, + "description": "The U.S. Department of Energy's (DOE's) Bioenergy Technologies Office and the National Renewable Energy Laboratory (NREL) developed the BSM (Bioenergy Scenario model) to explore the development of a U.S. biofuels industry. The BSM is a system dynamics model built on the STELLA software platform. The model represents the dynamic interactions of the major sectors of the biofuels industry\u2014feedstock production, feedstock logistics, biomass to biofuels conversion, and biofuels end use, including fuels inventory, dispensing, distribution, fuel use, and the vehicle fleet. The BSM represents contextual aspects of the developing biofuels industry, including investment in new biomass to biofuel conversion technologies, competition from petroleum fuels, vehicle demand for biofuels, and various government policies, using all of these to simulate the development of the industry. The purpose of the BSM is to generate and explore plausible scenarios for the evolution of a biofuels industry in the United States, and as a high-level system model it is not designed for precise, quantitative forecasting. Instead, it is best used to (1) analyze and evaluate alternate policies; (2) generate scenarios; (3) identify high-impact levers and bottlenecks to system evolution; and (4) seed focused discussion among policymakers, analysts, and stakeholders.", + "laborHours": 0.0, + "languages": [ + "STELLA" + ], + "name": "BSM (Bioenergy Scenario Model) 2023 FKA: Biomass Scenario Model [SWR-09-09]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bsm-public", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2023 release" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-16", + "metadataLastUpdated": "2023-08-16" + }, + "description": "BRICR is software for translating NREL's BuildingSync\u2122 XML (BSXML) to OpenStudio\u00ae Workflow (OSW) files for simulation. Each BSXML contains information about a building as well as multiple possible energy efficiency upgrade options. An OSW file is created and run for each possible efficiency upgrade, the results of all simulations are stored in BSXML format.\n\nBRICR was jointly developed by NREL and LBNL for the San Francisco BayREN: Integrated Commercial Retrofits (BRICR) project funded under the DOE solicitation \"Solutions to Improve the Energy Efficiency of U.S. Small and Medium Commercial Buildings (DE-FOA-0001385)\":\n\nhttps://www.energy.gov/eere/buildings/downloads/san-francisco-bayren-integrated-commercial-retrofits", + "laborHours": 127847.2, + "languages": [ + "Ruby" + ], + "name": "BRICR [SWR 18-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bricr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.2.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-23" + }, + "description": "FE-DWBA is a software package that computes the x-ray scattering patterns of objects that locate on \na surface or buried next to a surface, such as the nano-circuits and nano-patterns of the mask used \nin the extreme ultraviolet lithography. It can incorporate the dynamical scattering effect (photons \nscattered multiple times), which is predominant in surface scattering and yield high-fidelity \nscattering patterns. The application includes surface imaging using x-rays, and critical dimension \ndetermination for semiconductor manufacturing.\n\n", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "FINITE-ELEMENT DISTORED WAVE BORN APPROXIMATION FOR SURFACE SCATTERING", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-17" + }, + "description": "SONICC computes density and velocity transfer functions for use in the initial conditions of \nmassive neutrino\ncosmological simulations. The transfer functions are backscaled using a scale-dependent growth \nfunction that produces self-consistent evolution for all three matter species (cold dark matter, \nbaryons, massive neutrinos) in the Newtonian forward model of cosmological simulations.\n\n", + "laborHours": 0.0, + "languages": [], + "name": "sf-23-021 SONICC (SCALE-DEPENDENT OMEGA FOR NEUTRINO INITIAL CONDITION CODES)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.cels.anl.gov/hacc/sonicc", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-18" + }, + "description": "SF-23-006 FAST (FAST AUTONOMOUS SCANNING TOOLKIT)The software is deployed on an edge computing device at the beamline computer attached to a \nscanning microscope. It iteratively analyzes the data collected, then identifies new scan positions \nto scan next and directs the positioners that move the sample (or probe beam) to these positions. \nOverall, it identifies a sparse set of scan positions that are sufficient to image the full sample. \nThis can reduce the scan time by >60%.\n\n", + "laborHours": 0.0, + "languages": [], + "name": "FAST (FAST AUTONOMOUS SCANNING TOOLKIT)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/saugatkandel/fast_smart_scanning", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-17" + }, + "description": "SF-23-008 This project is a Julia implementation of the Gradient Optimization of Analytic conTrols (GOAT) \noptimal control\nmethodology. It integrates with other packages in Julia's ecosystem to provide memory-efficient, \nparallelized solutions to quantum optimal control tasks. A prototype implementation of some of these algorithms was initially developed and funded by the \nASCR Early Career Research Award program under PI Travis Humble at Oak Ridge National Laboratory. \nThe current version was funded under the ASCR AIDE-QC Program under PI Paul Hovland. The current \npackage to be released has a novel implementation, syntax, and structure making it substantially \ndifferent than the original prototype (which was not released under copyright to the best of my \nknowledge).\n", + "laborHours": 0.0, + "languages": [], + "name": "GOAT. jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MCS-Quantum/GOAT.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-23" + }, + "description": "SF-23-061 A Python package that provides a streamlined interface to Griffin along with support for integration with PyARC and Workbench.\n", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "PYGRIFFIN", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-18" + }, + "description": "SF-23-026 This software computes effective transport properties of composite materials involving fibers and nanoparticles using a\nrandom-walk algorithm that efficiently scales to an arbitrary number of processes and cores. Effective transport\nproperties (thermal, electrical) are key to bridge the microstructure of complex materials with its macroscopic behavior.\nTraditional approaches either use effective medium approximations (closed mathematical expressions that are\napproximation for certain conditions) or continuum simulation models such as finite element or finite volume, which\nrequire the generation of a mesh for each configuration explored. cowalker leverages the equivalence between laplacian\nor heat equation-based models and random walks to compute the asymptotic transport properties from an ensemble of\nfirst sojourn times of a random walker moving through the composite material. This allows us to directly define a\ncomposite material as a collection of particles and use algorithms developed for molecular dynamics to quickly compute\nthe intersection of the walker with the different interfaces in the material. cowalker is developed in C++, and it relies on\nthe GNU Scientific Library for random generation. cowalker is currently delivered as source code, so the GSL library is\nnot included in cowalker's distribution. A more userfriendly version, cowalker.jl is currently in development and will be\nreleased as part of cowalker.\n", + "laborHours": 0.0, + "languages": [], + "name": "COWALKER:EFFECTIVE TRANSPORT PROPERTIES OF COMPOSITE MATERIALS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spikingnn/spikingtorch", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-23" + }, + "description": "FireCat performs multiscale simulations by coupling ab initio microkinetic simulations from CatMAP with two-dimensional continuum transport simulations from EchemFEM (Firedrake). This coupling is performed in an iterative fashion. The examples provided here are specific to electrochemical CO2 reduction to CO on Au electrodes.\n", + "laborHours": 0.0, + "languages": [], + "name": "FireCat", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/firecat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.01" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-21" + }, + "description": "SF-23-071\nJobrunner is a command line tool to manage and deploy computing jobs, organize complex workloads, and enforce a\ndirectory based hierarchy to enable reuse of files and bash scripts within a project. Organization details of a directory\ntree are encoded in Jobfiles which serve as an index of files/scripts, and indicate their purpose when deploying or\nsetting up a job. It is a flexible tool that allows users to design 16 their own directory structure, perserve their design,\nand maintain 17 consistency with increase in complexity of the project.\n", + "laborHours": 0.0, + "languages": [], + "name": "JOBRUNNER", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/akashdhruv/Jobrunner", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "georgea@ornl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-18" + }, + "description": "PoliMOR is a scalable, automated, and customizable policy engine framework for multi-tiered parallel file systems. It is composed of single-purpose agents that handle tasks such as gathering file metadata, making policy decisions, and then executing actions based on those policies. These agents are designed to communicate using distributed message queues, allowing the number of individual agents to be scaled up as needed. PoliMOR automates the data management tasks by precluding the need for admin intervention. The agents in PoliMOR can be customized to integrate any utilities/tools that perform tasks like metadata scanning and data placement management.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python" + ], + "name": "PoliMOR", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/olcf/polimor/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/polimor", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-24" + }, + "description": "SF-23-067\nBoxKit is a library that provides building blocks to parallelize and scale data science, high performance computing, and\nmachine learning applications for block-structured datasets. Spatial data from simulations and experiments can be\naccessed and managed using tools available in this library when working with more data analysis oriented packages like\nSciKit (https://github.com/scikit-learn/scikit-learn) and FlowNet (https://github.com/NVIDIA/flownet2-pytorch)", + "laborHours": 0.0, + "languages": [], + "name": "BOXKIT", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/akashdhruv/BoxKit", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-21", + "metadataLastUpdated": "2023-08-21" + }, + "description": "SF-23-084\nThis software provides enhanced authorization and access control support to be used in tandem with the open source\nTerminal Access Controller Access Control System (TACACS+) software tac_plus; providing Authentication,\nAuthorization and Auditing (AAA) capabilities for networking devices.\n", + "laborHours": 0.0, + "languages": [], + "name": "TACPLUS-DO-AUTH", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/argonne-lcf/tacplus-do-auth", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Cylindrical Fast Backprojection (CFBP) is a novel image reconstruction algorithm developed at PNNL that radically\nincreases the efficiency of normal backprojection techniques and is ideally suited to microwave and millimeter-wave\nimaging systems based on scanned linear arrays such as current and next-generation cylindrical body scanners in\ncommon use for aviation security screening. T", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Cylindrical Fast Backprojection", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Fayda application developed as a part of the Reaction Roulette m/q LDRD project (76006) primarily exists as a data\nvisualization, analysis and predictive platform for data collected using atomic tandem inductively coupled plasma mass\nspectrometry (ICP-MS/MS)", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Fayda", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Rhizogrid guided molecular root imaging workflow enables investigating root rhizosphere interactions in a near native\nenvironment. Non-invasive root images are captured, and three-dimensional root images are reconstructed using x-ray\ncomputed tomography technique. Root and rhizosphere samples are then harvested and processed for root-rhizosphere\nmetabolite and microbial profiling.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Rhizogrids and 3D molecular root imaging workflow", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "lees4@ornl.gov" + }, + "date": { + "created": "2023-08-23", + "metadataLastUpdated": "2023-08-28" + }, + "description": "Atomistic simulation with artificial intelligence (AI) is an emerging tool for understanding materials' properties and behaviors and predicting novel materials with optimized/targeted properties. Neural network potentials (NNPs) are outstanding in this field as they have shown a comparable accuracy to ab initio electronic structure calculations for reproducing potential energy surfaces while being several orders of magnitude faster. However, such NNPs can perform poorly outside of their training domain and typically fail catastrophically in the prediction of rare events in molecular dynamics (MD) simulations. For effective AL loops to distinguish the informative data from enhanced sampled configurations, we developed a decision engine by configurational similarity and uncertainty quantification (UQ) with data augmentation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AL-ASMR: Active Learning of Atomistic Surrogate Models for Rare Events", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/al-asmr/blob/master/license.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/al-asmr", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-23", + "metadataLastUpdated": "2023-08-23" + }, + "description": "ParaDiS, or Parallel Dislocation Simulator, is a simulation tool that performs direct numerical simulation of\ndislocation ensembles, the carriers of plasticity, to predict the strength in crystalline materials from the\nfundamental physics of defect motion, evolution, and interaction.\nThe code has been successfully deployed on high performance computing architectures and used to\nstudy the origins of strength and strain hardening for cubic crystals, the strength of micro-pillars, and\nirradiated materials at LLNL. The ParaDiS code has been successfully deployed on more than one\nhundred thousand CPU's with over ten million active degrees of freedom.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Dislocation Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ParaDiS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "4.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "We would like to disclose a code based on Python/Pytorch, in which we implement the data-driven physics-informed machine learning of Lagrangian large eddy simulation that is described in the manuscript \"Lagrangian Large Eddy Simulations via Physics-Informed Machine Learning \". High-Reynolds number Homogeneous Isotropic Turbulence is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as Large Eddy Simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about the effects of sub-grid scales on the resolved scales. Here, we take an alternative approach and design novel LES heuristics stated in terms of Lagrangian particles moving with the flow. Our \\emph{Lagrangian LES}, thus L-LES, is described by equations generalizing the weakly compressible Smoothed Particle Hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from Direct Numerical Simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The sub-grid scale contributions are modeled separately with physical constraints to account for the effects from un-resolved scales. We build the resulting model under the Differentiable Programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our Lagrangian LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.", + "laborHours": 0.0, + "languages": [], + "name": "Code for the manuscript \"Lagrangian Large Eddy Simulations vis Physics-informed Machine Learning\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Lagrangian-LES", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "FriendlyNets provides a method for assessing the promotion/inhibition effect on a microbe of a microbial community using a network of community interactions. At its core, FriendlyNets judges how much a network promotes or inhibits one of its nodes. It does this by assuming a set of dynamical systems represented by the network and using the resulting dynamics. FriendlyNets is also packaged with functions for generating a network from a set of genome-scale metabolic models (commonly called GSMs or GEMs) by simulating pairwise growth.", + "laborHours": 0.0, + "languages": [], + "name": "FriendlyNets", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/friendlyNets", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "The duqling R package is a tool for facilitating reproducible research in UQ and ML by providing easy-to-use and consistent access to a wide variety of popular (public) test functions", + "laborHours": 0.0, + "languages": [], + "name": "duqling", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/knrumsey/duqling", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "This software is being developed to support data analysis and simulation for the growing field of outer heliosphere physics. In particular, this software will allow data analysis, inference, and simulation of physical mechanisms describing how energetic neutral atoms behave that originate from the solar system's boundary with the interstellar medium. ", + "laborHours": 0.0, + "languages": [], + "name": "Program Repository for Tools for Heliophysics Science (Theseus)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Theseus", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "The Renewable Energy Potential (reV) model is a first-of-its-kind detailed spatio-temporal modeling assessment tool that empowers users to calculate renewable energy capacity, generation, and cost based on geospatial intersection with grid infrastructure and land-use characteristics.\n\nThe National Renewable Energy Laboratory (NREL) developed the reV model to help utility planners, regional and national agencies, project and land developers, and researchers assess renewable energy resource potential. Available as open source since February 2020, the reV model currently supports photovoltaic, concentrating solar power, and wind turbine technologies. The tool can model a single site up to an entire continent at temporal resolutions ranging from five minutes to hourly, spanning a single year or multiple decades.\n\nBy automating access to resource data at unprecedented scale, fidelity, and flexibility, the reV model integrates formerly disparate analysis frameworks in the fields of resource modeling, technical potential, and renewable energy cost supply curves.\n\nThe reV model currently provides broad coverage across North America, South and Central Asia, the Middle East, South America, and South Africa to inform national- and international-scale analyses as well as regional infrastructure and deployment planning.", + "laborHours": 250526.4, + "languages": [ + "Python", + "PowerBuilder" + ], + "name": "reV (The Renewable Energy Potential Model - Open Source) [SWR-21-59, SWR-20-20 and SWR-17-34]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/reV", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.8.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-28", + "metadataLastUpdated": "2023-08-28" + }, + "description": "This package evaluates an analytic formula for the change in velocity imparted to an asteroid by a 1 or 2\nkeV black body source given the radius of the asteroid, the standoff distance, the x-ray yield, the density\nof the asteroid, and the fit coefficients for the 1 or 2 keV black body source (provided in the module).\nThree variations of the formula are given; the \"original\" form, the \"modified\" form that accounts for the\nangle of incidence in calculating the melt depth, and a form based on an \"impulse\" model.\nEach formula is fit to simulations of spherical asteroids of uniform composition illuminated by black body\nx-rays.", + "laborHours": 0.0, + "languages": [], + "name": "Analytic_Deflection_of_Asteroids_by_NEDs", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Analytic_Deflection_of_Asteroids_by_NEDs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-28", + "metadataLastUpdated": "2023-08-28" + }, + "description": "In the event of a potentially catastrophic asteroid impact, with sufficient warning time, deploying a nuclear\ndevice remains a powerful option for planetary defense if a kinetic impactor proves insufficient. Predicting\nthe effectiveness of a potential nuclear deflection or disruption mission depends on accurate multiphysics\nsimulations of the device's x-ray energy deposition into the asteroid and the resulting material ablation.\nThese simulations span many orders of magnitude, require a variety of different complex physics\npackages, and are computationally expensive. Having an efficient and accurate way of modeling this\nsystem is necessary for exploring a mission's sensitivity to the asteroid's range of physical properties. To\nexpedite future simulations, we present a completed x-ray energy deposition model developed using the\nradiation-hydrodynamics code Kull which can be used to initiate a nuclear mitigation mission hydrocode.\nThe model spans a wide variety of possible mission initial conditions: four different asteroid-like materials\n(Silicon Dioxide, Forsterite, Iron, and Ice), two different source spectra (1 and 2 keV blackbodies), and\nthen a broad range of radiation fluences (0.0001 to 1 kt per square meter), source durations (10 to 100\nns), and asteroid porosities (0 to 80 percent). Using blowoff momentum as the primary metric, the modelinitiated\nsimulation results match the full radiation-hydrodynamics results to within 10 percent. Please\nreference the journal article: Burkey et al., X-Ray Energy Deposition Model for Simulating Asteroid\nResponse to a Nuclear Planetary Defense Mitigation Mission, Planetary Science Journal, (2023) for more\ninformation.", + "laborHours": 0.0, + "languages": [], + "name": "NED_Asteroid_Energy_Deposition", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/NED_Asteroid_Energy_Deposition", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-28", + "metadataLastUpdated": "2023-08-28" + }, + "description": "The Regional Energy Deployment System (ReEDS\u2122) Model 2.0 is a free, open-access tool that empowers users to explore least-cost pathways for large-scale power sector transformation. NREL's flagship energy capacity planning model for the North American electricity system allows users to examine the interactions between policy, technology, economics, and the environment when integrating renewables onto the grid from now through 2050.\n\nThis GitHub repository contains the source code for NREL's ReEDS\u2122 2.0model. Users of this source code agree to the ReEDS licensing agreement: https://nrel.gov/analysis/reeds/request-access.html.\n\n The ReEDS 2.0 model source code is available at no cost from the National Renewable Energy Laboratory (NREL). The ReEDS 2.0 model can be downloaded or cloned from https://github.com/NREL/ReEDS_OpenAccess. New users must request access to the ReEDS repository through https://nrel.gov/analysis/reeds/request-access.html.\n\nA ReEDS training video (recorded in July 2020 and based on the 2019 version of ReEDS) is available on the NREL YouTube channel at https://youtu.be/Cdo27F18AZA. In addition, the Open-Access ReEDS Webinar from October 2019 gives an overview of the 2019 ReEDS model and how it works (https://www.youtube.com/watch?v=QpRtvs_0kkA).", + "laborHours": 0.0, + "languages": [ + "Python", + "R", + "GAMS", + "Jupyter Notebook" + ], + "name": "ReEDS\u2122 2.0 (Regional Energy Deployment System Model) Version 2.0 [SWR-20-36 and SWR-09-14]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ReEDS-2.0", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "Version 2.0" + }, + { + "contact": { + "email": "georgea@ornl.gov" + }, + "date": { + "created": "2023-08-29", + "metadataLastUpdated": "2023-08-30" + }, + "description": "Performance of file systems shift during their life cycles. Evaluating this performance change over time is not trivial. Complexity arises in the interplay between external (i.e. application I/O workloads) and internal (i.e. the filesystem state) factors. Many benchmarks can test how a filesystem performs at the current snapshot state, but to observe the change over time necessitates that the filesystem state mutate (age) between benchmark runs. For a large-scale HPC parallel filesystem, the sheer scale and amount of interacting components during I/O operations magnify these challenges. LCIO addresses the question - how will the filesystem perform at different stages of its life cycle? LCIO is a synthetic benchmark, which provides the file system aging process to increase the amount of information that existing benchmarks like IOR and MDTest yield, as well as provide additional points of data that will be useful to system architects and engineers.", + "laborHours": 0.0, + "languages": [ + "C", + "Python" + ], + "name": "LCIO", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/olcf/lcio/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/lcio", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-09-13" + }, + "description": "MemLeap is a GPU Memory Profiler built atop Nvbit (NVidia Binary Instrumentation Tool) framework. It\nanalyzes memory accesses to memory objects in GPU memory, including Unified Memory, to optimize\nmemory usage and reveal performance bottlenecks.", + "laborHours": 0.0, + "languages": [], + "name": "MemLeap GPU Memory Profiler", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IBPeng/memleap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-08-30" + }, + "description": "This software is used to compute numerous properties for the liquid and vapor phases of sodium.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Sodium Fluid Properties", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/sodium", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-08-30" + }, + "description": "This software is used to compute numerous properties for the liquid and vapor phases of potassium.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Potassium Fluid Properties", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + 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The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model \u00ae (2023 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2023 (v1.3.0.14xxx)" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-09-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Predicting Interactions of Aerosol and Clouds in Large Eddy Simulation (PINACLES) is a high-performance, massively\nparallel, anelastic atmospheric model written in Python", + "laborHours": 0.0, + "languages": [], + "name": "pinacles", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pinacles", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-09-11", + "metadataLastUpdated": "2023-09-11" + }, + "description": "Exawind-driver is a C++ code that is part of the ExaWind software stack. 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This generator can provide a robust adversarial attack against any unseen attack.", + "laborHours": 0.0, + "languages": [], + "name": "AdversarialTensors", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/AdversarialTensors", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "This software describes computational tasks for quantum computers that are derived from LANL basic science research applications such as the modeling of materials, chemicals and compounds at atomic scales. 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The secondary focus of the software are codes for assessing the limitations of conducting quantum computations on classical computers.", + "laborHours": 0.0, + "languages": [], + "name": "Quantum Application Specifications and Benchmarks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/qc-applications", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-10-17" + }, + "description": "UQ4ML is a code repository for a set of tools for the development of robust machine learning methods, uncertainty quantification and explainability of machine learning methods. The goal of these tools is to develop more robust and statistically rigorous machine learning methods for scientific applications. These tools are developed in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Robust Machine Learning", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "LEAD is a suite of scripts to enable rapid estimation of model parameters for damage models for ductile materials using machine learning. In its current version, the only supported damage model is TEPLA, though others are planned. The data we train on are comprised of free surface velocity data as well as porosity data. Some details about our method can be found in the preprint LA-UR-23-20468 (arxiv.org/abs/2301.07790)", + "laborHours": 0.0, + "languages": [], + "name": "LEAD - LEArning Damage", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dblaschke-LANL/LEAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "Seismic interpretation aims to extract quantitative and interpretable attributes from a seismic image produced using some migration method to inform characteristics of a subsurface reservoir or target of interest. Current paradigms for computing seismic attributes mostly rely on single-task algorithms. We develop an iterative, multi-task machine learning method to learn and infer multiple attributes from a seismic image. This method is composed of two stages: a multi-task inference stage and a multi-modal, multi-task refinement stage. The basic mechanism of this method is that we train a multi-task inference neural network (NN) to estimate a set of attributes, including a relative geological time (RGT), a denoised higher-resolution (DHR) seismic image, and multiple fault attributes (including probability, dip, and strike), from a low-resolution, noisy seismic image; then we input the inferred attributes to a multi-task refinement NN to enhance the raw inference results iteratively. The two multi-task NNs are trained separately based on synthetic seismic images and associated attributes generated by a geological modeling algorithm. The software we intend to release is a PyTorch implementation of this multi-task learning method for both 2D and 3D cases along with scripts to run the training/validation. The algorithm and software can be a useful tool for automatic seismic interpretation.", + "laborHours": 0.0, + "languages": [], + "name": "Iterative multi-task learning and inference from seismic images", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/mtl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "NuDustc++ is a nucleating and sputtering dust code. It takes in the temperature-density profiles, abundance data, and chemistry network. It creates a binned size distribution from user input data to track certain grain sizes. NuDustc++ loads the data and calculates where and when a shock is detected in the input data. Using a runge-Kutta DoPri 5 integrator, it calculates nucleation and growth of grains by solving a system of coupled non-linear ODEs. It calculates sputtering based on the presence or lack of a shock by either integrating over energy or summing up the sputtering yield contributions per gas species. It is used to determine and track dust grain nucleation, growth, and erosion (sputtering) in gaseous systems to determine characteristics of the produced grain distribution.", + "laborHours": 0.0, + "languages": [], + "name": "NuDustC++", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/nuDustC", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2024-08-27" + }, + "description": "This repository contains a python package of neural network interpretability techniques (interpretability) and a keras callback to easily compute and capture data related to these techniques (values metrics) during training. It was developed to be used with NREL's BUTTER Deep Learning Experimental Framework, but does not depend on this framework and may be useful to projects outside of this framework.\n\nThe vision for this codebase is to collect algorithms for explainable artificial intelligence (XAI) in a single framework that is easy to use, easy to read, and can be expand upon. Here, we package XAI algorithms into a module called \"metrics\", which are implemented as python functions. The return type of a metric is typically a dictionary holding data of multiple data types, such as real values and numpy matrices. Callbacks and any other connector code is provided as necessary in a separate module to make these metrics more easily usable. This project depends on Tensorflow's Keras API, although it would be nice to try and support multiple backends one day.\n\nRelated to: https://github.com/NREL/BUTTER-Empirical-Deep-Learning-Experimental-Framework", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "BUTTER-Clarifier [SWR-23-61]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BUTTER-Clarifier", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pcicilio@alaska.edu" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-28" + }, + "description": "This R script takes reads the csv file of stream-wise velocity data and generates a new time series of with comparable but distinct noise using the Langevin method and library. It simulates a time series measured at 1/10 the sampling rate by calculating a moving average of 10, though other sampling rates can be calculated by adjusting the moving average window.\n\nA stationary signal is calculated by taking the difference of the original signal and the moving average, then normalizing by the standard deviation of the moving average. The stationary signal is used to calculate drift and diffusion coefficients. Those coefficients are used to generate a new stationary signal.\n\nThe new stationary signal is un-normalized and added to the moving average (or new equivalent signal) to create a new up-sampled velocity time-series.", + "laborHours": 0.0, + "languages": [], + "name": "ADCP Upsample", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/acep-uaf/ADCP_Upsample", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pcicilio@alaska.edu" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "MiGRIDS is a software that models islanded microgrid power systems with different controls and components. For example, using load and resource data from a microgrid, you could model it with additional wind turbines, battery etc. You could also try out different dispatch schemes to see which one worked best.\n\nMiGRIDS is designed to help optimize the size and dispatch of grid components in a microgrid. While a grid connect feature is expected to be added in the future, islanded operation is the focus. Note that this is a basic implementation and more features and functionality (such as a GUI) are coming!\n\nMiGRIDS runs time-step energy balance simulations for different grid components and controls. In smaller microgrid environments, dispatch decisions are being made on the order of seconds. In order to fully capture their effect, this tool lets you run simulations on the order of seconds. The end result is a more realistic representation of what can be achieved by integrating different components and control strategies in a grid.", + "laborHours": 0.0, + "languages": [], + "name": "MiGRIDS", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/acep-uaf/MiGRIDS_DOE_MarineMicrogrids", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-09-25", + "metadataLastUpdated": "2023-09-28" + }, + "description": "Finite-difference methods are widely used to simulate infrasound propagation in the atmosphere.\nFlexibility of finite-difference scheme allows implementation of highly heterogeneous media for sound\npropagation as well as complex source models for sound generation. While full 3-D finite-difference\nmethods have been utilized for local infrasound propagation with pronounced topography, 2-D modeling\napproach has been preferred for regional and global propagation as full 3-D methods generally require\nenormous computational resources. Infrasound propagation is often simulated with a second-order finite difference\nscheme. This lowest-order finite-difference scheme is robust and straightforward to implement\ncomplex boundary conditions, but the solution includes large error with numerical dispersion and\ndissipation. This large numerical error may make the second-order finite-difference not optimal for long range\ninfrasound propagation modeling as the numerical dispersion degrades the accuracy of the solution\nunacceptably. Here, we developed a high-order finite-difference solver for long-range infrasound\nsimulation. The high-order scheme is particularly popular for linear wave modeling in aeroacoustics\nowing to its low-dispersive and low-dissipative behavior. We develop and evaluate a high-order finite difference\nscheme in 2-D axisymmetric coordinates. The axisymmetry allows to approximate 3-D\nspherical sound propagation and amplitude attenuation by a 2-D method. AC2Dr is developed to simulate\ninfrasound propagation in realistic atmosphere, but can be used for linear acoustic waves in general\nmaterials with background flow. AC2Dr in an axisymmetric coordinates allows for spherical radiation of\nacoustic waves from compact sources.", + "laborHours": 0.0, + "languages": [], + "name": "Acoustic Codes in 2D Spherical Coordinate", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AC2Dr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "pcicilio@alaska.edu" + }, + "date": { + "created": "2023-09-27", + "metadataLastUpdated": "2023-09-27" + }, + "description": "WEC-GRID is an open-source Python library crafted to simulate the integration of Wave Energy Converters (WECs) and Current Energy Converters (CECs) into renowned power grid simulators like PSS\u00aeE & PyPSA.", + "laborHours": 0.0, + "languages": [], + "name": "WEC-GRID", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/acep-uaf/WEC-GRID", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-09-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DEIMoS Graphical User Interface was created as an interface for DEIMoS: Data Extraction for Integrated\nMultidimensional Spectrometry. DEIMoS is a Python package to process data from mass spectrometry instrument\ndeveloped at PNNL.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/deimos_gui", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/deimos_gui", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-09-28", + "metadataLastUpdated": "2023-09-28" + }, + "description": "SSGUI is a web-based application that integrates the integrative genomics browser (IGV) with upstream alignment pipelines enabling rapid analysis of a batch of next-generation sequencing (NGS) samples. The input to SSGUI is an NGS file system directory that is organized by experiment and reference sequence. The output is an online dashboard containing various sequencing statistics for each sample and an integrated IGV plugin enabling rapid analysis of aligned NGS reads.", + "laborHours": 0.0, + "languages": [], + "name": "SSGUI v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/ssgui", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-09-28", + "metadataLastUpdated": "2023-09-28" + }, + "description": "MVP stands for Multi-choice Viromics Pipeline. It is a pipeline that utilizes a suite of state-of-art tools:\n\ngeNomad to identify viruses, proviruses, and plasmids in sequencing data,\n\nCheckV to assess the quality, and completeness of identified viral genomes, including identification of host contamination for integrated proviruses,\nA custom code for a rapid genome clustering based on pairwise ANI,\n\nBowtie2, Samtools, and CoverM to calculate coverage of individual viral genomes by read mapping,\nA custom code to create a vOTU table of abundance,\n\nMMseqs2 to compare viral proteins to multiple databases.\n\nIt provides a quick, and intuitive pipeline to get viral sequences and corresponding properties that can be used for downstream analyses.", + "laborHours": 0.0, + "languages": [], + "name": "Multi-choice Viromics Pipeline (MVP) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ccoclet/mvp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-09-28", + "metadataLastUpdated": "2023-09-28" + }, + "description": "This software is used to process the raw data from the GridSweep instrument, a device developed under subcontract by McEachern Laboroatories for a DOE GMLC project. The software scrubbs, demodulates, and transforms point on wave voltage timeseries data into frequency/voltage amplitude/time data. It also has a GUI that allows for user selection of processed experimental data and graphing in heatmaps or 3-D plots. It was created alongside the GridSweep instrument as a part of the same project and is required to be open-source.", + "laborHours": 0.0, + "languages": [], + "name": "GridSweep Processing and Graphing Software v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/jsmacdonald/gridsweep-processing/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "khutto30@gatech.edu" + }, + "date": { + "created": "2023-09-29", + "metadataLastUpdated": "2023-09-29" + }, + "description": "Hardware/software co-designed systems are increasingly prevalent due to trends such as the adoption of hardware accelerators and the availability of heterogeneous system-on-chip (SoC) architectures. A potential security concern arising from hardware/software interaction in heterogeneous computing architectures is the possibility of software-based attacks on reconfigurable hardware, and vice versa. This is especially important when considering remote updates of the software, hardware, or both combined. In this work, we have created a remote update scheme that relies on a physical unclonable function (PUF) and multiple updating parties to deliver hardware/software updates in a secure fashion. The scheme, GridTrust, provides a high level of assurance that the system only accepts updates from approved entities while also preventing common remote attacks from compromising the security of the update process. As shown above, an attacker has multiple opportunities to attack. GridTrust\u2019s protection features help to prevent any single attack from the locations shown in Figure 1 from succeeding.\n\nThe GridTrust scheme follows a few key tenets; (1) the usage of auditable open-source software, (2) software update authorization via two distinct entities, (3) and device authentication via a hardware fingerprinting technique known as a PUF. Used together, these techniques harden cybersecurity defenses in the electric grid supply chain against both a third-party actor and a malicious lone-wolf insider.", + "laborHours": 0.0, + "languages": [ + "Rust" + ], + "name": "GridTrust", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/huttokd/GridTrust", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2023-09-29", + "metadataLastUpdated": "2023-09-29" + }, + "description": "A novel Hybrid CUCKOO SEARCH determines combinatorial global optimum SCRAPs for specified point and pair correlations in high-entropy alloys having proper distributions.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python" + ], + "name": "Super-Cell Random APproximates(SCRAPs): A Multicomponent Alloy Structure Design Tool", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DuaneDJohnson/Hybrid-Cuckoo-Search", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2023-09-29", + "metadataLastUpdated": "2023-09-29" + }, + "description": "CMakePPLang is an object-oriented extension to the CMake language written entirely using the original CMake language, with the goal of making projects built on CMake easier to create and maintain.", + "laborHours": 0.0, + "languages": [ + "CMake" + ], + "name": "CMakePP/CMakePPLang", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CMakePP/CMakePPLang", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-09-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Deep Learning models for multi- and hyper-spectral imaging data", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/gumby-spectral-imaging", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/gumby-spectral-imaging", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "mcarbone@bnl.gov" + }, + "date": { + "created": "2023-10-01", + "metadataLastUpdated": "2023-10-01" + }, + "description": "A greatly abstracted machine learning suite built for ease of use, powered by Hydra + Lightning", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Crescendo", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://GitHub.com/matthewcarbone/crescendo", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "version": "0.0.1" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-10-02", + "metadataLastUpdated": "2023-10-05" + }, + "description": "DFLEXLIBS is a library/repository of HVAC-based demand flexibility control applications developed using Python. The library is based on portable control applications that exclusively contain control logic and are abstract to building details, such as point names and communication protocols. The library leverages semantic models and control platform-oriented interfaces to configure and run the controls in specific buildings. To date, the library contains two applications and two interfaces (for BOPTEST and VOLTTRON) and has been demonstrated in five heterogeneous buildings.", + "laborHours": 0.0, + "languages": [], + "name": "Demand Flexibility Controls Library using Semantics (DFLEXLIBS) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/DFLEXLIBS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-10-03", + "metadataLastUpdated": "2023-10-03" + }, + "description": "The Python binding for AMReX, pyAMReX, bridges the worlds of block-structured codes and data science: it provides zero-copy application GPU data access for AI/ML, in situ analysis, application coupling and enables rapid, massively parallel prototyping.", + "laborHours": 0.0, + "languages": [], + "name": "pyAMReX v23.08", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Codes/pyamrex", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-10-03", + "metadataLastUpdated": "2023-10-03" + }, + "description": "The Justice 40 tool provides a quantitative framework to support decision-making around equitable energy interventions at the community level. The tool calculates the optimal portfolio of policy interventions that explicitly mitigates energy insecurity of an eligible population, by reducing its disproportionate energy burden. The place-based analysis assumes a spatial census tract-level resolution and distinguishes different sociodemographic groups within each tract.\n\nInstead of focusing on a specific technology, the underlying J40 model captures the combined effect of a set of policy interventions, currently including weatherization, rooftop solar, community solar and community wind. For each tract, the model chooses the optimal (least cost) combination of interventions to address the disproportionate burden, considering the specific population demographics and techno-economic potentials of technologies. Mathematically, this problem is formalized as an optimization model and formulated as a linear program.", + "laborHours": 0.0, + "languages": [], + "name": "Justice 40 Tool (J40 Tool) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNLgrid/j40model", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-10-04", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Light sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as\nthe entire mouse brain. We fine-tuned an existing model, TrailMap, using expert labeled data from axonal structures in neocortex. Without\nchanging the network architecture, we implemented nnU-Net framework modifications in data augmentation, data\nforeground sampling, window learning rate, and the inference overlap method. The resulting model from these combined\napproaches yielded an improved F1 score", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/brain_ohsu", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/brain_ohsu", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-09", + "metadataLastUpdated": "2023-10-30" + }, + "description": "RouteE-Powertrain is a tool for predicting energy usage over a set of road links.\n\nRouteE-Powertrain is a Python package that allows users to work with a set of pre-trained mesoscopic vehicle energy prediction models for a varity of vehicle types. Additionally, users can train their own models if \"ground truth\" energy consumption and driving data are available. RouteE-Powertrain models predict vehicle energy consumption over links in a road network, so the features considered for prediction often include traffic speeds, road grade, turns, etc.\n\nThe typical user will utilize RouteE's catalog of pre-trained models. Currently, the catalog consists of light-duty vehicle models, including conventional gasoline, diesel, hybrid electric (HEV), and battery electric (BEV). These models can be applied to link-level driving data (in the form of pandas dataframes) to output energy consumption predictions.\n\nUsers that wish to train new RouteE models can do so. The model training function of RouteE enables users to use their own drive-cycle data, powertrain modeling system, and road network data to train custom models.\n\nhttps://pypi.org/project/nrel.routee.powertrain/\npip install nrel.routee.powertrain", + "laborHours": 0.0, + "languages": [ + "Shell", + "Rust", + "Python" + ], + "name": "RouteE-Powertrain [SWR-19-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/routee-powertrain", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-10-09", + "metadataLastUpdated": "2023-10-09" + }, + "description": "Limited-Angle Computed Tomography (LACT) is a non-destructive evaluation technique used in a variety\nof applications ranging from security to medicine. The limited angle coverage in LACT is often a dominant\nsource of severe artifacts in the reconstructed images, making it a challenging inverse problem. We\npresent DOLCE, a new deep model-based framework for LACT that uses a conditional diffusion model as\nan image prior. Diffusion models are a recent class of deep generative models that are relatively easy to\ntrain due to their implementation as image denoisers. DOLCE can form high-quality images from severely\nunder-sampled data by integrating data-consistency updates with the sampling updates of a diffusion\nmodel, which is conditioned on the transformed limited-angle data. We show through extensive\nexperimentation on several challenging real LACT datasets that, the same pre-trained DOLCE model\nachieves the SOTA performance on drastically different types of images. Additionally, we show that,\nunlike standard LACT reconstruction methods, DOLCE naturally enables the quantification of the\nreconstruction uncertainty by generating multiple samples consistent with the measured data.", + "laborHours": 0.0, + "languages": [], + "name": "DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wustl-cig/DOLCE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-09", + "metadataLastUpdated": "2024-01-17" + }, + "description": "RouteE Compass is an energy-aware routing engine for the NREL-developed RouteE ecosystem of software tools with the following key features:\n\n- Dynamic and extensible search objectives that allow customized blends of distance, time, cost, and energy (via RouteE Powertrain) at query-time\n\n- Core engine written in Rust for improved runtimes, parallel query execution, and the ability to load nation-sized road networks into memory\n\n-Rust, HTTP, and Python APIs for integration into different research pipelines and other software\n\nRouteE Compass is a part of the RouteE family of mobility tools created at the National Renewable Energy Laboratory (NREL).", + "laborHours": 0.0, + "languages": [ + "Rust", + "Python" + ], + "name": "RouteE-Compass [SWR-23-95]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/routee-compass", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.6.1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-09", + "metadataLastUpdated": "2023-10-09" + }, + "description": "MARBLES (Multi-scale Adaptively Refined Boltzmann LatticE Solver) is an open-source computational fluid dynamics package powered by the lattice Boltzmann equations and built on AMReX. In the lattice Boltzmann method, local collisions between meso-scale fictitious particles drive the governing equations which enables MARBLES to easily simulate flow around complex and/or moving geometry without the generation of a body-conforming mesh. Using AMReX data structures and operations ensures a high level of computational performance and parallel scaling on heterogenous architectures while also naturally supporting locally enhanced grid resolution and fidelity through automatic mesh refinement. New domains and problem definitions are easily specified through an input file with examples and guidance on all options and variables provided in the MARBLES documentation.", + "laborHours": 0.0, + "languages": [ + "C++", + "CMake" + ], + "name": "MARBLES (Multi-scale Adaptively Refined Boltzmann LatticE Solver) [SWR-23-37]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/marbles", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-10-11", + "metadataLastUpdated": "2023-10-11" + }, + "description": "MaCaw is a MOOSE-based application that enables domain-decomposed neutral particle transport calculations in MOOSE. It leverages the ray tracing MOOSE module for unstructured mesh tracking and OpenMC for collision physics, handling material definitions, and tallying quantities.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Macaw", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/macaw", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-10-11", + "metadataLastUpdated": "2023-10-11" + }, + "description": "This software gathers irrigation data as well as evapotranspiration rates to understand the on field water balances and track water usage.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Irrigation Monitor", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/irrmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-11", + "metadataLastUpdated": "2023-10-17" + }, + "description": "The Energy Language Model (ELM) software provides interfaces to apply Large Language Models (LLMs) like ChatGPT and GPT-4 to energy research.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ELM (Energy Language Model) [SWR-23-94]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/elm", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "peless@ornl.gov" + }, + "date": { + "created": "2023-10-13", + "metadataLastUpdated": "2023-10-17" + }, + "description": "Library of GPU-resident linear solvers", + "laborHours": 0.0, + "languages": [ + "C++", + "CUDA", + "HIP" + ], + "name": "ReSolve", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/ReSolve", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-10-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software includes the Jupyter notebooks, model pretraining and evaluation code for the EXPERT 2.0 Human-AI\nReasoning Engine V0.1. It supports pre-training a Human-AI model for reasoning over multi-layer network representations.\nIt includes prompt-based evaluation framework in a Jupyter notebook for AI reasoning and Jupyter widgets with AI-based\ntechniques for evidence generation and uncertainty quantification to support human-AI reasoning.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/EXPERT2", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/EXPERT2", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-10-19", + "metadataLastUpdated": "2023-10-19" + }, + "description": "In post-crash situations, passengers, bystanders, and first responders are exposed to the immediate safety risks of stranded energy in electric vehicle (EV) batteries. A potentially damaged battery with an unknown state of safety might go into a thermal runaway without proper handling, leading to potential loss of life and property damage. Therefore, it is imperative to develop methods, guidelines and tools to handle the post-crash EVs appropriately and minimize safety risks from immediately after an EV accident to final disposal or re-entry to the road. \nThis software tool:\n(1) provides quick access to EV specification, \n(2) estimate stranded energy left in an EV after a crash specific to EVs in a user-friendly way, \n(3) inform EV structure/disconnect for appropriate quick post-crash handling,\n(4) perform the calculation for the first responder to decide on onsite or offsite discharge, and\n(5) feature appropriate battery disposal and education/lessons learned.\nThis software tool will directly help the emergency responders to handle EV post-crash situations effectively and safely.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python", + "SQL" + ], + "name": "Ev Info And Incident Response Solutions", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/EVIRS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-10-20", + "metadataLastUpdated": "2023-10-20" + }, + "description": "This is a toy problem intended as an example on which to test V/UQ tools for multi-physics problems (coupled sub-models). It has grown from the solution to a graduate-school homework problem that has been posted on open-source (https://github.com/PhilipSmith-Canada/EthyleneOxideHomeWork).", + "laborHours": 0.0, + "languages": [], + "name": "ToyProblem-EthyleneOx", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/smith-LANL/ToyProblem-EthyleneOx", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-10-20", + "metadataLastUpdated": "2023-10-20" + }, + "description": "This software is being developed to support data analysis, modeling, and simulation for the growing field of heliosphere physics. In particular, this software will implement data analysis, modeling, inference, and simulation of physical mechanisms describing how energetic neutral atoms behave within the Earth\u2019s heliosphere and in the interstellar medium beyond.", + "laborHours": 0.0, + "languages": [], + "name": "Software for Heliospheric Science", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/IBEX_RibbonSeparation", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-10-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Interactive user-interface application for deep probabilistic day-ahead net-load forecasting. This application allows a utility\noperator and/or other end-user to access through an easy interface the powers of advanced deep AI/ML algorithms for\ngenerating day-ahead probabilistic forecast of net-load. Also known as \"VRN3P\"", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Forte", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Forte", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-10-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PFLOTRAN leverages massively parallel, high performance computing to simulate large-scale non-isothermal multiphase\nflow, multicomponent reactive transport and electrical resistivity tomography (ERT) problems in the subsurface\nenvironment. Researchers have employed PFLOTRAN to simulate these Earth system processes on leadership class\nsupercomputers for over two decades. The code is designed to predict the future estate of environmental systems and\nbetter inform stakeholders in the regulatory decision making process (e.g., fate of contaminants, long-term stewardship for\nnuclear waste, impact of climate change, etc.). A diverse team of scientists oversees PFLOTRAN development and\nmaintenance under an open-source licensing agreement and manages contributions from an international community of\nresearchers.", + "laborHours": 0.0, + "languages": [], + "name": "PFLOTRAN 5", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/pflotran/pflotran/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "5" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-10-25", + "metadataLastUpdated": "2023-11-08" + }, + "description": "The purpose of this code is to provide a high-fidelity model of Type-5 wind turbine drivetrain for grid integration and transient stability studies. The increasing integration of renewable energy resources in evolving bulk power system (BPS) is impacting the system\u2019s inertia. Type-5 wind turbine generation has the potential to behave like a traditional synchronous generator and can help mitigate the aforementioned impact. A hydraulic torque converter (TC) and gearbox with torque limiting feature are integral parts of a Type-5 wind turbine unit. A generic and high-fidelity model of a Type-5 wind turbine drivetrain is not openly and widely available for grid integration and transient stability studies. This hinders appropriate assessment of Type-5 wind power plant's contribution to the BPS resilience. This work develops and validates a TC model based on those generally used in automobile's transmission system.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Open Source High Fidelity Modeling Of A Type-5 Wind Turbine Drivetrain", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Type_5_Wind_Turbine_Drivetrain", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-26", + "metadataLastUpdated": "2023-12-08" + }, + "description": "PV Aerodynamic Design Engineering (PVade) is an open-source fluid-structure interaction (FSI) solver which can accurately simulate wind loads and aerodynamic stability in solar-tracking PV arrays. PVade\u2019s pressure profiles and inertial load time series can be used as inputs into mechanical module models to study degradation mechanisms including cracking of cells, weathering of cracked cells, and glass breakage. This software enables PV plant owners to predict optimal high-wind stow strategies under a variety of weather and site conditions.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PVade (PV Aerodynamic Design Engineering) [SWR-23-49]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PVade", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-10-26", + "metadataLastUpdated": "2023-11-08" + }, + "description": "The purpose of this software is to pull data from the Oracle Primavera P6 scheduling tool and bring it into the DeepLynx data warehouse.", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "P6 Deeplynx Adapter", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/p6-deeplynx-adapter", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-10-30", + "metadataLastUpdated": "2023-10-30" + }, + "description": "The LLNL Automized Surface Titration Model (L-ASTM) is a community data-driven surface complexation\nmodeling workflow for simulating potentiometric titration of mineral surfaces. The model accepts raw\nexperimental potentiometric titration data formatted in a findable, accessible, interoperable, and reusable\n(FAIR) structure. The workflow was coded in Python and coupled to PHREEQC for surface complexation\nmodeling and PEST for data fitting and parameter estimation.", + "laborHours": 0.0, + "languages": [], + "name": "LLNL Automized Surface Titration Model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LLNL-ASTM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-30", + "metadataLastUpdated": "2024-04-05" + }, + "description": "NREL conducted comprehensive field measurements of the atmospheric turbulent wind conditions and the resulting structural wind loads on parabolic troughs at the Nevada Solar One plant from October 2021 to June, 2023. The measurement set-up included meteorological masts and structural load sensors on four trough rows. Additionally, NREL commissioned a lidar scanning the horizontal plane over the trough field. The high-resolution data set, characterizing the complex flow field and resulting structural loads, is available at https://data.openei.org/submissions/5938. The processing routines published here were used to create the data from the instruments' raw data.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "NSO Processing Scripts (NSO wind loading data set processing scripts) [SWR-23-86]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NSO_processing_scripts", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-10-30", + "metadataLastUpdated": "2023-10-30" + }, + "description": "JSAC is a Java implementation of the Seismic Analysis Code (SAC2000,\nhttps://github.com/LLNL/SAC2000). It is intended to bring the most commonly used features of SAC2000\nup to date with modern standards, support parallelized computation where possible, and implement\nimprovements in algorithms and numerics.", + "laborHours": 0.0, + "languages": [], + "name": "JSAC", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/JSAC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-10-30", + "metadataLastUpdated": "2023-10-30" + }, + "description": "The seismic response processing module is a Java based library that provides support for removing\ninstrument response signals from seismic recordings. The response module provides support for\nEvalResp, PZF, PAZ, FAP, PAZFIR, PAZFAP, FIRFAP, and CSS response types and parallel processing\nsupport for transfer operations. Additionally, the response module uses the JSR-363 units of\nmeasurement specification to allow for transfer to and from a wide range of units types to represent the\ntime-series.", + "laborHours": 0.0, + "languages": [], + "name": "Seismic Response Processing Module", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/response", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-31", + "metadataLastUpdated": "2023-11-06" + }, + "description": "Energy systems models typically take the form of complex partial differential equations which make multiple forward calculations prohibitively expensive. Fast and data-efficient construction of surrogate models is of utmost importance for applications that require parameter exploration such as design optimization and Bayesian calibration. In presence of a large number of parameters, surrogate models that capture correct dependencies may be difficult to construct with traditional techniques. The issue is addressed here with the formulation of the surrogate model constructed via Physics-Informed Neural Networks (PINN) which capture the dependence with respect to the parameters to estimate, while using a limited amount of data. Since forward evaluations of the surrogate model are cheap, parameter exploration is made inexpensive, even when considering a large number of parameters.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PINNSTRIPES (Physics-Informed Neural Network SurrogaTe for Rapidly Identifying Parameters in Energy Systems) [SWR-22-12]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PINNSTRIPES", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "martins@ornl.gov" + }, + "date": { + "created": "2023-11-01", + "metadataLastUpdated": "2024-01-30" + }, + "description": "A kubernetes based pipeline for analyzing hyperspectral data", + "laborHours": 0.0, + "languages": [], + "name": "HyperKube", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/StantonMartin/hyperkube", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-11-02", + "metadataLastUpdated": "2023-11-02" + }, + "description": "MSR-Genie is a vendor-neutral tool for fast and efficient queries about model-specific registers (MSRs).\nThe tool allows end users to query bi-directionally across MSR lists as well as processor families and\nmodels, and provides them with guidance on appropriate bitmasks. The msr-genie tool is open-source\nand easily extensible, and currently supports 30 Intel processor models and two-thousand unique MSRs.", + "laborHours": 0.0, + "languages": [], + "name": "msr-genie", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/msr-genie", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-03" + }, + "description": "LANL developed a benchmark of software code for radiation testing of microprocessors several years ago, and it was published under an open-source license on GitHub. Publishing the software is necessary for other researchers to adopt and implement this benchmark for radiation testing of other microprocessors to standardize test practices so that test data can be compared across different microprocessors. The original codes have been used several times by other organizations to test a wide range of microcontrollers and microprocessors. \nAfter several years of research, LANL is ready to update the benchmark. Changes include:\n1.\tAddition of new codes that allow common software codes to be tested,\n2.\tAddition of new codes that instrument more microprocessor circuitry, \n3.\tAddition of input patterns that allow for a more compressive understanding of how the memory layout affects the sensitivity to radiation-induced faults and better use of automated test pattern generation standards, and\n4.\tModification of current codes for faster and more resilient detection, reporting and correction of radiation-induced faults.\nThese codes have been tested by LANL researchers over the last few years, which has been published in the open literature. As the code base for the new benchmarks are stable, it is time to release the update to the GitHub repository, where the original codes were released.", + "laborHours": 0.0, + "languages": [], + "name": "Update to the Microcontroller Benchmark for Radiation Testing", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/benchmark_codes", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-03" + }, + "description": "The software provides machine learning analysis and visualization to detect patterns in microbiome data, including topic modeling, probabilistic graphical modeling, conventional machine learning methods, and deep learning. The software is written in python and R, it uses some python and R libraries as well as big open-source libraries like sklearn, networkX, pytorch (python), pgmpy (python), and bnlearn (R). It also has a script to use for MALLET and DTM (open-source packages for topic modeling, written in Java).", + "laborHours": 0.0, + "languages": [], + "name": "ML for microbiomes", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ML-for-microbiomes", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-03" + }, + "description": "The unambiguous identification of compounds from their electron ionization mass (EI-MS) spectra remains a significant unsolved problem in the field of metabolomics and analytical chemistry as a whole. Typically EI-MS spectra are compared using various mathematical operations that convert the spectral similarity or differences into a distance-like metric that roughly approximates the similarity of any two spectra. A commonly used metric for this is the cosine similarity metric which has values close to one for very similar spectra and a value of zero for very dissimilar spectra; however, no metric is perfect. Due to the prevalence of structurally-similar compounds such as isomers and the prevalence of certain fragmentation patterns across structurally-dissimilar compounds, the unambiguous assignment of EI-MS spectra compounds remains difficult. Frequently, querying an observed EI-MS spectrum against a large database such as the NIST17 library yields multiple possible assignments requiring the end user to distinguish between multiple high scoring hits, or multiple low scoring hits while keeping in mind that the correct hit may not be in the database at all. Although techniques such as orthogonal information from techniques such as chromatography can greatly aid in unambiguous assignment, this also requires more complicated experimental designs and access to more complicated analytical instrumentation.\nSubstructures can be trivially detected and represented as strings using a previously published technique called node coloring from a known chemical structure. However, for experimentally-derived EI-MS spectra this information must be derived from the spectra itself (i.e., because we do not know what compound it represents). To achieve this, the software uses techniques from the field of machine learning and a large training dataset of EI-MS spectra corresponding to known structures annotated with substructure strings, to build models that can predict the presence of a given chemical substructure from an EI-MS spectrum directly.If these predictions are of high-quality (i.e., are unlikely to be false positives), the presence of one or more predicted substructures can be used to constrain the number of possible hits for a query spectrum. Mathematically, this restriction could be expressed in many forms, but the most straight-forward implementation is to weight the cosine similarity of a query spectrum and a plausible database match with a Tanimoto-like coefficient based on the ratio of the number of substructures predicted to the number of substructures present in the potential database hit.\nDetermining which combination of models best reduces assignment ambiguity will be achieved using a combination of manual curation and optimization techniques such as genetic algorithms. This software will perform all the steps necessary to construct said models from a training dataset and evaluate them using a holdout dataset. Various statistical analyses can be performed to determine if this approach does decrease assignment ambiguity. For example, if this approach works, on average, the rank-order of the correct assignment for the holdout set of EI-MS spectra should decrease and the weighted cosine similarities for most of the possible matches in the database should be better than the unweighted cosine similarities. Furthermore, this same pipeline can be used on real experimental data to generate less ambiguous assignments.", + "laborHours": 0.0, + "languages": [], + "name": "EI_MS_ML", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EI_MS_ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-03" + }, + "description": "Machine learning (ML) of interatomic potentials show great promise to accelerate scientific simulation, e.g., by emulating expensive computations at a high accuracy but much reduced computational cost. Training datasets are calculated from computationally expensive ab initio quantum mechanics methods, density functional theory (DFT). Trained on this data, an ML model can be very successful in predicting energy and forces for new atomic configurations. A critical factor is the quality and diversity of the training dataset. Thus, a highly automated approach to dataset construction based on active learning framework is designed suitable for material physics.\n\nThe active learning scheme begins with fully randomized atomic configurations. Then, many Molecular Dynamics (MD) trajectories are simulated using current ML potentials, where each MD trajectory is initialized to a random disordered configuration. The temperature is varied in order to diversify the sampled configuration during these simulations. The variance of predictions for eight neural networks within an ensemble is analyzed to determine whether the model is operating as expected. This helps in determining whether collecting more data would be helpful to the model by checking the ensemble variance is greater than the threshold. In this case, the MD trajectory is terminated and the final atomic configuration is placed on a queue (SQL database) for DFT calculations and added to training dataset. Periodically, ML model is retrained to the updated training model. This Active Learning loop is iterated until the cost of MD simulations becomes prohibitively expensive. The MD simulations will hopefully be sufficiently robust to support nucleation after many active learning iterations. In this sense, active learning scheme must automatically discover the important low energy and nonequilibrium physics.", + "laborHours": 0.0, + "languages": [], + "name": "Active Learning Framework", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/alf", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-08" + }, + "description": "VPSC is a mean-field polycrystal plasticity code for the prediction of the mechanical response and microstructure evolution\nof polycrystalline aggregates. The VPSC code is the computational realization of the visco-plastic self-consistent theory of polycrystal deformation. Both the theory and details of its numerical implementation were originally reported by R.A.\nLebensohn and C.N. Tom\u00e9: \"A self-consistent approach for the simulation of plastic deformation and texture development\nof polycrystals: application to Zirconium alloys\", Acta Metallurgica et Materialia 41, 2611 (1993). Since then, the VPSC code\nhas experienced several improvements and extensions and it is nowadays extensively used to simulate plastic deformation\nof polycrystalline aggregates and to interpret experimental evidence on metals, minerals and polymers.", + "laborHours": 0.0, + "languages": [], + "name": "Viscoplastic selfconsistent (VPSC) code (version 8, open source)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vpsc_code", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-11-08", + "metadataLastUpdated": "2023-11-08" + }, + "description": "The purpose of the software is to provide initial machine learning results to an unknown data set.", + "laborHours": 0.0, + "languages": [ + "Python", + "R" + ], + "name": "Digital Twin Analytics Search", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Digital-Twin-Analytics-SEARCH", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wilsonbe@ornl.gov" + }, + "date": { + "created": "2023-11-08", + "metadataLastUpdated": "2023-11-08" + }, + "description": "Earthdata Pub is a toolset that provides forms and workflows so that a data producer can request archival of their NASA-funded data, NASA can determine which (if any) DAAC is appropriate to that data, and the selected DAAC can work with the data producer to get the data and metadata necessary for publication.", + "laborHours": 0.0, + "languages": [], + "name": "Earthdata Pub", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eosdis-nasa/earthdata-pub", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-11-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Low precision-based nearest neighboring particle searching algorithm.This work introduces a computationally efficient Nearest Neighbor Particles Searching (NNPS) algorithm tailored for the\nmeshfree Smoothed Particle Hydrodynamics (SPH) method in large-deformation problems simulations. The innovation lies\nin the strategic use of low-precision float-point 16 (FP16) in NNPS for efficiency purpose.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/lpNNPS4SPH", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/lpNNPS4SPH", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-11-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a repository for work conducted in our research paper we would like to make open source. The main features are\nthat we forked another open source library and added functionality that enabled us to compute neural-kernel objects using\nrandom vector projection software for both computer vision and large language text models. The new features are\nspecifically code that enables the calculation of objects we define and refer to as the projection pseudo neural tangent\nkernel and the projection trace neural tangent kernel\u037e both of which are approximations of the empirical neural tangent\nkernel. The software that computes the projections themselves are not part of the invention, but are necessarily tied to our\nsoftware and licensed via MIT license, and BSD 2 license.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/projection_ntk", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/projection_ntk", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-11-14", + "metadataLastUpdated": "2023-11-16" + }, + "description": "ThermalNetwork is software to size distributed ground heat exchangers for district-connected ground-source heat pump systems. The intended audience includes Ground Source Heat Pump Designers.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "ThermalNetwork [SWR-23-101]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/thermalNetwork", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-11-14", + "metadataLastUpdated": "2023-11-14" + }, + "description": "Official code for the NeurIPS 2023 paper \"Neural Image Compression: Generalization, Robustness, and\nSpectral Biases\". This code can be used to:\n- Computing spectral distortion errors of images compressed with traditional codes or neural image\ncompression models (as proposed in the aformentioned paper)\n- Visualize power spectral densities and fourier heatmaps (as proposed in the aformentioned paper)\n- Train and test a variety of neural image compression models", + "laborHours": 0.0, + "languages": [], + "name": "Out of distribution evaluation for neural image compression", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/klieberman/ood_nic", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-11-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Model-based Deep Reinforcement Learning for Real-time Grid Emergency Voltage Control. A model-based Deep Reinforcement Learning (DRL) framework where a deep neural network (DNN)-based\nsurrogate model is utilized within the control policy learning framework, making the learning process faster and more\nsample efficient", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/MBDRL", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/MBDRL", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-11-15", + "metadataLastUpdated": "2023-11-15" + }, + "description": "Open OnDemand is a software tool that is used to access HPC resources. It provides a framework for organizations to create apps and other additional functionality that may be useful to the organization. This code expands upon the pre-existing INL applications, including the NEAMS Workbench application, MOOSE Herd applications, and others. These changes significantly expand upon the functionality originally provided. Due to the extensive functionality that we added, these changes would not be added to the original application but would function as a standalone application that other organizations would be able to utilize on their own systems.", + "laborHours": 0.0, + "languages": [ + "Bash", + "JavaScript", + "Ruby", + "HTML", + "CSS", + "yml" + ], + "name": "Inl Open Ondemand Applications", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HPC_OOD", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-17", + "metadataLastUpdated": "2023-11-17" + }, + "description": "This software is an open-source Python library that provides tools for processing hyperspectral neutron time-of-flight radiography data. This type of data allows material decomposed reconstructions to be generated with the use of material characteristic spectral responses and the algorithms provided in this code library. The software library will contain tools for pre-processing the neutron measurement data, estimating measurement system parameters, reconstructing material decomposed radiographs, and computing material decomposed computed tomography (CT). Furthermore, it will have capability to generate and process simulated neutron time-of-flight data with the goal of benchmarking and demonstrating the tools that are provided. The software will include thorough documentation and application examples.", + "laborHours": 0.0, + "languages": [], + "name": "TRINIDI (Time-of-Flight Resonance Imaging with Neutrons for Isotopic Density Inference)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/trinidi", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-17", + "metadataLastUpdated": "2023-11-17" + }, + "description": "The Trees program is a pre-processing tool used to virtually build forest fuel arrays to be read into FIRETEC, QUIC-Fire, or similar wildland fire related tool which requires the conversion of raw collected forest data to a digitalized voxelization of the fuels.", + "laborHours": 0.0, + "languages": [], + "name": "Trees", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Trees", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-17", + "metadataLastUpdated": "2023-11-21" + }, + "description": "Automatically summarizing a collection of documents requires analyzing their features using various operations. Hypercane is a framework for building algorithms for sampling files from a collection. Sampling is a vital part of automatic summarization. Hypercane ties together many existing third-party libraries. These libraries include those for processing web resources, natural language processing for analyzing text and filtering documents, and machine learning for clustering summarization candidates. A user can run up to more than 70 operations on a corpus in the order of their choosing. Through these operations, they can create custom automatic summarization algorithms to help them process the corpus of their choice. Details of the algorithms possible with Hypercane are available in Jones 2021. Details of running Hypercane are available in Jones et al.; 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Hypercane", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/hypercane", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-17", + "metadataLastUpdated": "2023-11-21" + }, + "description": "This disclosure is for version 2.x of a mesoscale model called Phase Field Dislocation Dynamics (PFDD). PFDD is used for investigating deformation in nanoscale (grain sizes of ~300 nm and less) materials, such as metals and alloys. This approach models the motion and interaction of individual defects, namely dislocations, in the material using scalar-valued phase field variables, also called order parameters. The system is evolved through energy minimization thus the model calculates the total energy density in terms of the phase field variables. The energy minimization is completed using the Ginzburg-Landau equation, and is implemented with explicit time integration. The total system energy can be comprised of several terms, including the strain energy (which describes dislocation-dislocation interactions), the energy due to an applied stress (dislocation interactions with the applied stress), and a core/lattice (perfect dislocations) or generalized stacking fault (partial dislocations) energy (described the dislocation core structure). The latter term in particular may vary based on the crystal structure being modeled and is typically informed using lower length scale (e.g., atomistic) approaches, although no such (atomistic) calculations are completed within the PFDD algorithm. This basic formulation was previously reviewed by Los Alamos National Laboratory and released under license number C17113. This previously reviewed version we will henceforth refer to as PFDD v1.0. \n\nPFDD v1.0 consisted of 2 codes (one parallel and one serial) plus input files, all written in the C language. This new disclosure is addressing the next versions of the PFDD, versions 2.x. There have been several enhancements of PFDD v1.0, which are described here and included in the attached code, which we will refer to as PFDD v2.0. There are also several new features described here that are either planned or already in process and are expected to be subsequent releases, i.e., v2.1, v2.2, ...v2.x.", + "laborHours": 0.0, + "languages": [], + "name": "Phase Field Dislocation Dynamics (PFDD) version 2.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Phase-Field-Dislocation-Dynamics-PFDD-2.x", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-11-27", + "metadataLastUpdated": "2023-12-20" + }, + "description": "The Wind Asset Value Estimation System (WAVES) model is a coupling framework for core NREL techno economic analysis software models to estimate capital expenditures (ORBIT), operational expenditures (WOMBAT), and energy production (FLORIS) for offshore wind power plants. Existing workflows to couple the three models for lifecycle performance and cost estimation require a large amount of manual and error-prone setup to combine both shared inputs and dependent outputs, as such WAVES's primary functionality is to wrap the core logic for running standard modeling workflows to ensure shared settings and entangled results are correctly and efficiently combined every time. SEE ALSO: https://pypi.org/project/WAVES/", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "WAVES (Wind Asset Value Estimation System) [SWR-23-81]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WAVES", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.5" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-11-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Similarity learning of two mass spectrometry runs solely using MS1 data", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/deep_scoreMS1", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/deep_scoreMS1", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-11-28", + "metadataLastUpdated": "2023-11-30" + }, + "description": "The Advanced Locomotive Technology and Rail Infrastructure Optimization System (ALTRIOS) is a unique, fully integrated, open-source software tool to evaluate strategies for deploying advanced locomotive technologies and associated infrastructure for cost-effective decarbonization. ALTRIOS simulates freight-demand driven train scheduling, mainline meet-pass planning, locomotive dynamics, train dynamics, energy conversion efficiencies, and energy storage dynamics of line-haul train operations. Because new locomotives represent a significant long-term capital investment and new technologies must be thoroughly demonstrated before deployment, this tool provides guidance on the risk/reward tradeoffs of different technology rollout strategies. An open, integrated simulation tool is invaluable for identifying future research needs and making decisions on technology development, routes, and train selection. ALTRIOS was developed as part of a collaborative effort by a team comprising the National Renewable Energy Laboratory (NREL), University of Illinois Urbana-Champaign (UIUC), Southwest Research Institute (SwRI), and BNSF Railway.\n\nPython Package: https://pypi.org/project/altrios/\nRust Crate: https://crates.io/crates/altrios-core", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ALTRIOS (Advanced Locomotive Technology and Rail Infrastructure Optimization System) [SWR-22-54]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ALTRIOS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "V0.1.3" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-12-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Database of building energy standards data for building energy simulation.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/building-energy-standards-data", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/building-energy-standards-data", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-12-05", + "metadataLastUpdated": "2023-12-05" + }, + "description": "We present an open-source Python-based framework that can be used for objective evaluation of\nAtmospheric Rivers (ARs) in climate models. With a comprehensive pool of pre-defined metrics, this\npackage is useful for systematic AR evaluation across a range of model simulations, such as the MIPs in\nCMIP5/6 models and large ensemble experiments.", + "laborHours": 0.0, + "languages": [], + "name": "PCMDI PMP Interactive Visualization Web Page, Atmospheric River Metrics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kristinchang3/peak_season_cmec", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-12-05", + "metadataLastUpdated": "2023-12-05" + }, + "description": "scaleupROM is a scalable, physics-constrained reduced order model (ROM). It aims to provide robust,\naccelerated physics predictions at extrapolated scales, based on the small, component-level data. This is\nimplemented by combining projection-based ROM with discontinuous Galerkin domain decomposition, in\nthe framework of MFEM and libROM. It currently supports the Poisson equation and Stokes flow\nequation, and more work is in progress toward general, nonlinear physics systems.", + "laborHours": 0.0, + "languages": [], + "name": "Scalable Reduced Order Model with Discontinuous Galerkin Domain Decomposition", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/scaleupROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-12-07", + "metadataLastUpdated": "2024-11-01" + }, + "description": "UWLi is a user interface for modifying Universal Workflow Language (UWL) files. UWL is a data format used to represent high fidelity scientific procedures in a generalized, field agnostic workflow format.\n\nSee related publication: https://arxiv.org/pdf/2409.05899", + "laborHours": 3040.0, + "languages": [ + "Smarty", + "Python" + ], + "name": "UWLi (Universal Workflow Language Interface) [SWR-24-12]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Universal-Workflow-Language-Interface", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-12-11", + "metadataLastUpdated": "2024-02-09" + }, + "description": "The Production Financial Analysis Scenario Tool (ProFAST) provides a quick and convenient in-depth financial analysis for production facilities. The model uses a generally accepted accounting principles analysis framework and provides annual projections of income statements, cash flow statements, and balance sheets. ProFAST allows users to calculate the levelized cost of the produced commodity by providing an expected financial performance, or on the other hand, calculate the financial performance based on an input price. Model inputs generally capital expenditures, operating expenditures, and financing structure. The programmatic approach of ProFAST allows users to easily perform large sensitivity analyses and integrates easily with other python tools.", + "homepageURL": "https://github.com/NREL/ProFAST", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ProFAST (Production Financial Analysis Scenario Tool) [SWR-23-88]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://github.com/NREL/ProFAST/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://github.com/NREL/ProFAST", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-12-13", + "metadataLastUpdated": "2023-12-18" + }, + "description": "BuildStockQuery is a python library designed to simplify and streamline the process of querying massive, terabyte-scale datasets generated by ResStock(TM). ResStock (SWR-19-15) is a U.S. DOE-supported, NREL-built, national residential building energy stock model that enables a new approach to large-scale residential energy analysis across the U.S. by combining large public and private data sources, statistical sampling, detailed sub-hourly building simulations, and high-performance computing. \n\nBuildStockQuery offers an intuitive Object-Oriented Programming (OOP) interface to the ResStock output dataset allowing users to easily perform common queries and receive results in familiar pandas DataFrame format, abstracting away the need for complex SQL query. By initializing a query object with the pertinent Athena database and table names, users can easily query for various kinds of insights, for example, timeseries electricity for an end use for a given state grouped by building types.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "BuildStockQuery [SWR-23-58]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/buildstock-query", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-12-13", + "metadataLastUpdated": "2023-12-13" + }, + "description": "To achieve the desired particle size of biomass feedstocks during preprocessing for trouble-free handling and conversion to produce biofuels and bioproducts, the raw materials must undergo a crucial milling process. The particle size of biomass plays a critical role in subsequent biofuel manufacturing, where a larger area-to-volume ratio facilitates efficient synthesis while balancing the impact of moisture on biomass storage. To optimize biofuel production efficiency and overcome these challenges, it is imperative to accurately predict the particle size distribution (PSD) of the biomass in the design of efficient preprocessing systems. The population balance model (PBM), upon empirical calibration and validation, can provide rapid prediction of post-milling PSD of granular biomass. However, PSD has limitations related to mass conservation and the absence of moisture considerations. To overcome these drawbacks, a deep learning model called the enhanced deep neural operator (DNO+) is implemented in the code. This model not only retains the capabilities of the PBM in handling complex mapping functions but also incorporates additional factors influencing the system. By considering various experimental conditions such as sieve size and moisture content, the trained DNO+ model can effectively predict the PSD after milling for any given feed PSD. To further reduce the reliance on experimental data, the PBM is integrated into the DNO+ model, resulting in a physics-informed DNO+ (PIDNO+). The PIDNO+ model addresses the non-conservation of quality exhibited by the PBM while inheriting the advantages of the DNO+ model in considering multiple influencing factors. Moreover, the PIDNO+ model significantly reduces the amount of data required for model training. Both deep learning models, i.e., DNO+ and PIDNO+, are excellent in predictive performance, offering swift and accurate machine learning-based predictions. The use of this code that contains these models will assist in guiding the proper milling equipment selection and operational conditions to achieve the desired biomass particle sizes, ensuring the efficiency of subsequent biofuel and bioproduct production processes.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Smart Preprocessing & Robust Integration Emulator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/SPRITE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-12-15", + "metadataLastUpdated": "2024-04-19" + }, + "description": "Ryujin (https://github.com/conservation-laws/ryujin) is a high-performance finite-element software for solving mathematical partial differential equations (PDEs) with dominant hyperbolic structures. The author of this request, Eric Tovar, is using Ryujin as a high-performance tool for his Mark Kac postdoctoral fellowship research at LANL. Eric would like to contribute openly to the ryujin software without changing its core functionality. This includes: (i) bug fixes; (ii) re-organization of code for performance and syntactic updates including documentation; (iii) implementation of new PDE numerical methods that align with the core solver; (iv) implementation of new initial state configurations for target applications.", + "laborHours": 0.0, + "languages": [], + "name": "LANL contribution to ryujin, an open source finite element solver", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EricTovar-LANL/ryujin-contribution.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-12-15", + "metadataLastUpdated": "2023-12-15" + }, + "description": "Software tools for quantifying atmospheric variability and uncertainty for use in uncertainty quantification of acoustic/infrasound propagation simulations.", + "laborHours": 0.0, + "languages": [], + "name": "stochprop", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Seismoacoustics/stochprop", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-12-15", + "metadataLastUpdated": "2023-12-15" + }, + "description": "This is code associated with the publication \u201cNonparametric Multi-shape Modeling with Uncertainty Quantification,\u201d authored by Hengrui Luo (Lawrence Berkeley National Laboratory) and Justin Strait (Los Alamos National Laboratory). The code is used to fit multiple-output Gaussian process (GP) models of planar closed curves to collections of ordered point sets, allowing for flexible nonlinear prediction of the underlying curve under dense or sparse point set samplings and with or without noise, as well as tractable uncertainty quantification. To do this, we employ use of a periodic kernel to account for the nonlinear input space of closed curves, and combine with coregionalization models to account for dependence both (i) between curve coordinates, and (ii) between pairs of curves. Functions in the code are capable of fitting these models, as well as performing additional tasks with the fitted curves such as (a) shape registration and alignment, (b) shape averaging, and (c) fitting for curve sub-populations / clusters.", + "laborHours": 0.0, + "languages": [], + "name": "Code for multi-shape Gaussian process (GP) fitting with uncertainty quantification (UQ)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/multishapeGP", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-12-15", + "metadataLastUpdated": "2023-12-15" + }, + "description": "Class and supporting functions to utilize an object oriented approach to F-ANOVA", + "laborHours": 0.0, + "languages": [], + "name": "F-ANOVA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/F-ANOVA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-12-20", + "metadataLastUpdated": "2023-12-20" + }, + "description": "PECAN2, Pose Classification with 3D Atomic Network 2, presents an innovative approach to pose\nclassification in computational modeling, particularly in the context of molecular docking. Traditional\nmethods like docking, which rely on physics-based calculations, are prone to inaccuracies in predicting\nbinding poses during experimental testing. While machine learning (ML) approaches, such as ML-driven\npose classification, have been introduced to address these issues, they often depend on the availability of\ncrystal structure data.\nIn contrast, PECAN2 introduces a novel pose classification method that operates independently of crystal\nstructures. Instead, it utilizes a 3D atomic neural network with Point Cloud Network (PCN) to establish\ncorrelations between docking scores and experimental data. This approach marks a departure from\nprevious studies that heavily relied on crystal structures for labeling.\nThe key innovation lies in the ability of PECAN2 to enhance the performance of molecular docking by\nfiltering out false positives and false negatives through the correlation between docking scores and\nexperimental data.", + "laborHours": 0.0, + "languages": [], + "name": "PECAN2", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/PECAN2", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-12-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A multi-task neural network for the simultaneous identification of multiple compounds from XRD data obtained in a synchrotron-based hydrothermal fluid system. To enhance the alignment between the training and test datasets, random noise is introduced into the synthetic training dataset, and minor labeled experimental data is incorporated. Additionally, we employ a weighted cross-entropy loss function to address data imbalances and ensure smoother model training.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/mlxrd", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mlxrd", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wehart@sandia.gov" + }, + "date": { + "created": "2024-01-02", + "metadataLastUpdated": "2024-01-02" + }, + "description": "Pypm supports the analysis of time series data to identify patterns that reflect the execution of a known process. Pypm uses a process model to identify patterns, where the execution of a process is decomposed into a sequence of related activities. A process model describes the activities used in the process, dependencies between activities that constrain their execution, resources needed to execute each activity and information about the activities that are observable.\n\nPypm implements process matching algorithms that infer a schedule of the activities in a process model to maximize the alignement of the process with observational data. Pypm uses numerical optimization to search for a maximal match score. When data is labeled and associated with the resources in the process model, then integer programming methods are used to find an optimal match. For unlabeled data, tabu search methods are used to predict data labels, which can then be used by integer programming methods.\n\nPypm solvers address a variety of complicating concerns, including variable-duration process activities, gaps in activity execution, preferences for compact matches, and tailored methods that depend on data characteristics.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "pypm", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pypm", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-02", + "metadataLastUpdated": "2024-01-09" + }, + "description": "This repository contains all of the methods for the NSRDB data processing pipeline. The NSRDB is a serially complete collection of hourly and half-hourly values of meteorological data and the three most common measurements of solar radiation: global horizontal, direct normal and diffuse horizontal irradiance.", + "laborHours": 0.0, + "languages": [ + "HTML", + "C", + "Jupyter Notebook", + "Python" + ], + "name": "NSRDB (National Solar Radiation Database Software) [SWR-23-77]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/nsrdb", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "4.0.1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-03", + "metadataLastUpdated": "2024-03-11" + }, + "description": "PowerSimulations.jl is a Julia-based BSD- licensed power system operations simulation tool developed as a flexible and open source software for quasi-static power systems simulations including Production Cost Models. 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The LCOM tool requires an existing ROSE installation configured\nwith the GNAT 2019 compiler.", + "laborHours": 0.0, + "languages": [], + "name": "ROSE LCOM Tools", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ROSE-LCOM-Tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.5" + }, + { + "contact": { + "email": "zhangc@ornl.gov" + }, + "date": { + "created": "2024-01-08", + "metadataLastUpdated": "2024-01-09" + }, + "description": "Tutorial on graph neural network (GNN) for the digital twin (DT) team at ORNL.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Graph neural network tutorial for digital twin application", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/KedoKudo/DT_GNN_Tutorial", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "zhangc@ornl.gov" + }, + "date": { + "created": "2024-01-08", + "metadataLastUpdated": "2024-01-08" + }, + "description": "Contains software that is used to process the raw tpx3 data into hit and events.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "ornlneutronimaging/mcpevent2hist", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornlneutronimaging/mcpevent2hist", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "2.2.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-10", + "metadataLastUpdated": "2024-03-11" + }, + "description": "PowerSystems.jl is a package to organize and manipulate data for the study of energy systems with diverse modeling requirements. This software serves two main purposes: to reduce the burden of large power system data set development, and to promote reproducible research and simulation. PowerSystems.jl implements an abstract hierarchy to represent and customize power systems data and includes data containers for quasi-static and dynamic simulation applications. Key features include efficient management of large quantities of time series data, optimized serialization, and comprehensive validation capabilities.\n\nFor further information regarding the Sienna modeling framework at NREL, see: https://www.nrel.gov/analysis/sienna.html", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "PSY (PowerSystems.jl) [SWR-23-105]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-Sienna/PowerSystems.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.2.2" + }, + { + "contact": { + "email": "dewittsj@ornl.gov" + }, + "date": { + "created": "2024-01-10", + "metadataLastUpdated": "2024-01-10" + }, + "description": "This repository contains example implementations of phase-field codes primarily for educational purposes. These codes demonstrate how a simple phase-field models can be implemented as an introduction for researchers new to the area (students, new staff, collaborators from different domains, etc.). \n\nThe computer code includes highly documented Jupyter notebooks that implement phase-field models and analyze the results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Phase-Field Method Tutorial Codes", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/pf_tutorial_codes", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "mazeauej@ornl.gov" + }, + "date": { + "created": "2024-01-11", + "metadataLastUpdated": "2024-01-11" + }, + "description": "C++ Project Euler files", + "laborHours": 0.0, + "languages": [], + "name": "mazeau/project-euler", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mazeau/project-euler", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stewartsl@ornl.gov" + }, + "date": { + "created": "2024-01-12", + "metadataLastUpdated": "2024-01-12" + }, + "description": "Dimensionally aligned signal projection (DASP) algorithms are used to analyze fast Fourier transforms (FFTs) and generate visualizations that help focus on the harmonics for specific signals. At a high level, these algorithms extract the FFT segments around each harmonic frequency center, and then align them in equally sized arrays ordered by increasing distance from the base frequency. This allows for a focused view of the harmonic frequencies, which, among other use cases, can enable machine learning algorithms to more easily identify salient patterns. \n \nThe DASP library is implemented in Python and contains four types of algorithms for implementing these feature engineering techniques: fixed harmonically aligned signal projection (HASP), decimating HASP, interpolating HASP, and frequency aligned signal projection (FASP). Each algorithm returns a numerical array, which can be visualized as an image. For consistency FASP, which is the terminology used for the short-time Fourier transform, has been implemented as part of the library to provide a similar interface to the STFT of the raw signal. Additionally, the library contains an algorithm to generate artificial signals with basic customizations such as the base frequency, sample rate, duration, number of harmonics, noise, and number of signals.\n \nFinally, the library provides multiple interactive visualizations, each implemented using IPyWidgets and work in a Jupyter environment. A dashboard-style visualization is provided, which contains some common signal-processing visual components (signal, FFT, spectrogram) updating in unison with the HASP functions (see Figure 1 below). Separate from the dashboard, an independent visualization is provided for each of the DASP algorithms as well as the artificial signal generator. These visualizations are included in the library to aid in developing an intuitive understanding how the algorithms are affected by different input signals and parameter selections.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Dimensionally Aligned Signal Processing Algorithms", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/dasp-stacker", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "sabaua@ornl.gov" + }, + "date": { + "created": "2024-01-12", + "metadataLastUpdated": "2024-01-30" + }, + "description": "Code for modeling solidification microstructure based on the Cellular Automata method for binary/pseudo-binary alloys.\n\nThis code is derived from the open-source software uMatIC developed at the Imperial College London https://www.imperial.ac.uk/engineering-alloys/research/software", + "laborHours": 0.0, + "languages": [ + "C", + "cmake" + ], + "name": "muMatScale", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lang-yuan/muMatScale", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-12", + "metadataLastUpdated": "2024-01-22" + }, + "description": "We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE)7. We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.\n\nScientific publication available here: https://pubs.acs.org/doi/full/10.1021/acs.est.2c04246", + "laborHours": 0.0, + "languages": [ + "Python", + "Shell" + ], + "name": "LiAISON (Life-cycle Assessment Integration into Scalable Open-source Numerical models) [SWR-24-01]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/LiAISON", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.0.1" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2024-01-15", + "metadataLastUpdated": "2024-01-25" + }, + "description": "Montepy is an object-oriented Python interface for MCNP input files. It excels at reading, editing, creating, and writing MCNP input files. The Monte Carlo N Particle (MCNP) code is a Monte Carlo transport solver for simulating many different types of radiation problems and is developed by Los Alamos National Laboratory. Montepy creates an object-oriented interface for the MCNP input file to allow for efficient automated modifications to large, complex simulations.", + "laborHours": 0.0, + "languages": [ + "python3.8" + ], + "name": "Montepy", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/MontePy", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2024-01-15", + "metadataLastUpdated": "2024-01-15" + }, + "description": "AcCCS is a collection of scripts that leverage open-source code, off-the-shelf hardware, and published protocol specifications to create a flexible and inexpensive test and evaluation device for the Electric Vehicle industry. AcCCS is capable of emulating either an Electric Vehicle (EV) or Electric Vehicle Supply Equipment (EVSE). It provides a flexible set of Python scripts to test and evaluate the various communication protocols between the Electric Vehicle Communication Controller (EVCC) and Supply Equipment Communication Controller (SECC). This capability is useful for cybersecurity researchers, automotive OEMs, and EVSE manufactures.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Access Capabilities Through Ccs Communications Protocol (acccs)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/AcCCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2024-01-15", + "metadataLastUpdated": "2024-02-06" + }, + "description": "This project brings together a multidisciplinary team to develop tools and analysis that will help U.S. industry accelerate deployment of floating PV on reservoirs and estuaries through producing:\n\u2022\tA tool to assess potential environmental interactions of FPV on reservoirs and estuaries and thresholds for corresponding impacts.\n\u2022\tA tailored FPV-specific techno-economic tool to guide users on financial performance and corresponding design considerations.\n\u2022\tA synthesized tool, AquaPV, that combines the environmental and economic tools.\n\u2022\tA set of case studies on an open-loop reservoir with a traditional hydropower plant (i.e., connected to a natural waterbody), closed-loop reservoir with a proposed pumped storage hydropower plant (i.e., manmade and disconnected from a natural waterbody), and a marine estuary (i.e., where a river meets the ocean), with an FPV system designed and modeled for each site.\n\u2022\tA review of regulatory, environmental, and stakeholder opportunities and challenges to identify clear regulatory and environmental pathways to siting FPV on U.S. reservoirs.\n\u2022\tA novel, high-fidelity geospatial resource assessment to estimate FPV technical potential on reservoirs in the United States.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Aquapv", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/AquaPV", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-17", + "metadataLastUpdated": "2024-01-31" + }, + "description": "VSP selects the appropriate number and location of environmental samples to ensure that the results of statistical tests performed to provide input to risk decisions have the required confidence and performance. VSP Version 5.0 provides sample-size equations or algorithms needed by specific statistical tests appropriate for specific environmental sampling objectives. It also provides data quality assessment and statistical analysis functions to support evaluation of the data and determine whether the data support decisions regarding sites suspected of contamination. The easy-to-use program is highly visual and graphic. VSP runs on personal computers with Microsoft Windows operating systems (98, NT, 2000, Millennium Edition, CE, and XP) Designed primarily for project managers and users without expertise in statistics, VSP is applicable to two- and three-dimensional populations to be sampled (e.g., rooms and buildings, surface soil, a defined layer of subsurface soil, water bodies, and other similar applications) for studies of environmental quality. VSP is also applicable for designing sampling plans for assessing chem./rad/bio threat and hazard identification within rooms and buildings, and for designing geophysical surveys for UXO identification.", + "homepageURL": "https://www.pnnl.gov/projects/visual-sample-plan", + "laborHours": 0.0, + "languages": [], + "name": "Visual Sample Plan", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/projects/visual-sample-plan", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/projects/visual-sample-plan", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-17", + "metadataLastUpdated": "2024-01-31" + }, + "description": "ProMAT is a software tool for statistically analyzing data from enzyme-linked immunosorbent assay microarray experiments. The software estimates standard curves, sample protein concentrations and their uncertainties for multiple assays. ProMAT generates a set of comprehensive figures for assessing results and diagnosing process quality. The tool is available for Windows or Mac, and is distributed as open-source Java and R code.", + "homepageURL": "https://www.pnnl.gov/statistics/ProMAT", + "laborHours": 0.0, + "languages": [], + "name": "ProMat", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/statistics/ProMAT", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/statistics/ProMAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-17", + "metadataLastUpdated": "2024-01-31" + }, + "description": "The Bayesian Estimator of Protein-Protein Association Probabilities (BEPro3) is a software tool for estimating probabilities of protein-protein association between bait and prey protein pairs using data from multiple-bait, multiple-replicate, protein LC-MS/MS affinity isolation experiments. BEPro3 is public domain software, has been tested on Windows XP and version 10.4 or newer of the Mac OS 10.4, and is freely available. A user guide, example dataset with analysis and additional documentation are included with the BEPro3 download.", + "homepageURL": "http://www.pnl.gov/statistics/BEPro3", + "laborHours": 0.0, + "languages": [ + "R, JAVA" + ], + "name": "Bayesian Estimator of Protein-Protein Association Probabilities", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.pnl.gov/statistics/BEPro3", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.pnl.gov/statistics/BEPro3", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-01-17", + "metadataLastUpdated": "2024-01-31" + }, + "description": "Passively maps IP networks using data generated by other network monitoring tools as well as using network device configuration files. 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DATING includes the GEAR package for the numerical solution of the rate equations and DPLOT for plotting the time-dependence of the calculated cumulative damage-fraction, creep strain, radiation damage recovery, and temperature decay.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "None" + ], + "name": "Temperature for Spent Fuel Dry Storage (DATING-M)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-19", + "metadataLastUpdated": "2025-01-31" + }, + "description": "CMS provides an inventory of all chemicals on order or being held in the laboratory, to provide a specific location for all chemical containers, to ensure that health and safety regulatory codes are being upheld, and to provide PNNL staff with hazardous chemical information to better manage their inventories. 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The primary entry point is the Spawn command line interface.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "CMake" + ], + "name": "Spawn v.0.5.0 Released 12.15.2023 [SWR-SWR-20-10]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Spawn", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.5.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-01-22", + "metadataLastUpdated": "2024-01-22" + }, + "description": "WindSE is a python package that uses a FEniCS backend to perform wind farm simulations and optimization. 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Additionally, three distinct tools have been developed:\nPV Hosting Capacity: This tool allows users to determine the additional amount of photovoltaic (PV) generation that can be\nintegrated into the system without breaching operational constraints.\nEV Hosting Capacity: This tool focuses on identifying the capacity for incorporating extra electric vehicle (EV) load into the\nsystem without surpassing operational limitations.\nProject Impact Analysis Tool: This tool is designed to assess and report all potential grid violations associated with a\nspecific project, providing valuable insights into its impact on the distribution grid.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Grid Modeling and Hosting Capacity Analysis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "gureckywl@ornl.gov" + }, + "date": { + "created": "2024-01-24", + "metadataLastUpdated": "2024-01-24" + }, + "description": "This software package performs time series forecasting for engineering systems using neural controlled differential equations. 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Additionally, by utilizing a novel combination of a variational autoencoder and neural controlled differential equations, the AIRES-NODE package is capable of producing probabilistic future forecasts.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AIRES-NODE", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/AIRES/aires-node", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0.0.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-01-25", + "metadataLastUpdated": "2024-01-25" + }, + "description": "NREL's Campus Energy Modeling project provides a suite of simulation tools for integrated, data driven energy modeling of commercial buildings and campuses using Simulink. 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Battery degradation, charging strategies, and drive patterns play an important role in each of these elements.", + "homepageURL": "https://labpartnering.org/technologies/55f86d47-38e0-41b5-aa8c-bc4020564b1b", + "laborHours": 0.0, + "languages": [], + "name": "Complete Battery Ownership Model And Cost Calculator (BOM) [SWR-20-28]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://labpartnering.org/technologies/55f86d47-38e0-41b5-aa8c-bc4020564b1b", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://labpartnering.org/technologies/55f86d47-38e0-41b5-aa8c-bc4020564b1b", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-02-06" + }, + "description": "HydroPowerSimulations is an extension to NREL's PowerSimulations.jl software that enables the modeling and analysis of hydropower systems.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "HPS (HydroPowerSimulations.jl) [SWR-23-110]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-Sienna/HydroPowerSimulations.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.8.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-29" + }, + "description": "We seek to release SuperNu, Version 4.x, as a continuation of development for the open source SuperNu software. 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These features are intended to improve the fidelity and/or better understand uncertainty in supernova and kilonova light curve calculations.", + "laborHours": 0.0, + "languages": [], + "name": "SuperNu Version 4.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SuperNu", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "Materials Analysis Using Diffraction (MAUD) is an open source Rietveld refinement program which fits diffraction models to\ndiffraction spectra allowing quantitative diffraction analysis. 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The scripting language facilitates batch, custom, and reproducible Rietveld refinements of large datasets.", + "laborHours": 0.0, + "languages": [], + "name": "MAUD Interface Tool Kit (MILK)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MILK", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-02-29" + }, + "description": "Development of a prototype, code-based life cycle assessment framework, the Harmonized Impacts across Products, Scenarios, and Technologies for Environmental and Resource metrics (HIPSTER), to coherently assess outputs of prospective NREL models across environmental and resource use metrics. 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In FY22, HIPSTER was successfully applied using scenarios from the ReEDS\u2122 model, NREL's flagship capacity expansion model resulting in cradle-to-grace time-series life cycle impacts across LCA midpoints and resource use metrics.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HIPSTER (Harmonized Impacts across Products, Scenarios, and Technologies for Environmental and Resource metrics) [SWR-24-17]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HIPSTER", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.0.1 beta" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-11-15" + }, + "description": "Quinoa is a set of computational tools that enables research and numerical analysis in fluid and solid dynamics.", + "laborHours": 130020.8, + "languages": [], + "name": "Quinoa, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/quinoacomputing/quinoa", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-30" + }, + "description": "This script illustrates the advantages of loychikSD_NP, e.g. acts as a demonstration of the higher-order spectral density.", + "laborHours": 0.0, + "languages": [], + "name": "Modeling Script", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SpectralDensities", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "This is the script to calculate higher-order spectral densities.", + "laborHours": 0.0, + "languages": [], + "name": "Extract Bandwidth Statistical Properties", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SpectralDensities", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "The feature interpretability code is a python module that interprets and analyzes neural networks trained on hydrodynamic simulation output in the form of numpy arrays. The code takes trained neural networks and extracts internal model states in the form of images. Additionally, tools for covariance analysis of network weights and predictions are provided. This code is built on the TensorFlow and PyTorch python libraries, and includes trained networks and example input data for demonstration purposes.", + "laborHours": 0.0, + "languages": [], + "name": "Feature Interpretability", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/feature_interpretability", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "SurFE-XD is a mesoscale finite element framework to model surface diffusion under mutliphysics environments. The code uses legacy C++ library dolphin wrapped with python in a FEniCS driven unified form language and just-in-time (JIT) compilation setting. The purpose of the release is to attract wide-ranging usage of the code along with publication supplementation to support reproducibility of scientific data. SurFE-XD has been originally conceived under the LDRD-DR funding for \u201cHigh-Gradient (C-BAND) Breakdown tolerant accelerator materials project. Currently SrFE-XD support electrostatics and Thermo-elasticity driven surface diffusion kernels. Releasing the code will also enable to include contributions from other physical regimes e.g., plasticity and electrodynamics etc as well portability to GPU-based platforms.", + "laborHours": 0.0, + "languages": [], + "name": "SurFE-XD (Surface curvature-driven Finite Elements model for Diffusion under eXtreme conditions)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sbagchi-LANL/SurFE-XD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-02-22" + }, + "description": "Tardigrade is a collection of functions, libraries, and stand-alone code which enables the simulation of materials using the higher-order micromorphic framework. The tools present are the interface to INL's MOOSE code which is used as the underlying FEA solver, several constitutive equations (linear elasticity, a pressure-sensitive elasto-plastic model, crystal plasticity, and additional models for geo-materials) useful for demonstration purposes and the simulation of some materials, the micromorphic filter which converts DNS information to micromorphic stress-deformation quantities, and the overlap coupling framework which enables multi-scale simulations of a coupled higher-order macroscale and a classically defined microscale.", + "laborHours": 0.0, + "languages": [], + "name": "Tardigrade, Version 1.1x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/tardigrade", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "1.1x" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "Historically, codes for simulating supernovae (such as Arepo, FLASH or LEAFS) have been at the forefront of scientific high-performance computing to the immense computational resources required for full 3D simulations. However, given the shift towards heterogenous HPC architectures, many current-generation codes are at the risk of losing their competitiveness as they are only designed to run on homogeneous CPU-only systems. There exist several efforts to enable these codes for GPU\u2019s, however, these efforts only consider specific architectures or vendors (e.g., implement only CUDA or HIP), limiting themselves to a small range of exascale computing systems.\nFrameworks such as Kokkos aim to provide a framework which is agnostic of the targeted architecture, enabling the development of performant and portable code.\nIn the Ares code, we develop a performance portable tool to simulate supernovae based on the Parthenon Framework, which in turn uses Kokkos in the background. Here, the Parthenon Framework provides an interface to the underlying mesh-refinement routines, which form the backbone of our code. In addition, we incorporate the already existing Singularity-EOS toolkit to provide us with various equations of state, primarily the Helmholtz equation of state. We also include the JINA Reaclib as a basis for our nuclear network solver. Finally, we implement a gravity solver to complete the required physics.\nThis setup will provide us with a minimal code base to simulate supernova in a similar style to the tried-and-tested Arepo code, but in a futureproof performance portable framework.", + "laborHours": 0.0, + "languages": [], + "name": "ARES v1.x - Performance Portable Tool to Simulate Supernovae based on Parthenon Framework", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/AresPK", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-29" + }, + "description": "DeBoinR (Density Boxplots in R) takes in a set of Probability Density Functions (PDFs), calculates outliers based on several notions of distance, and visualizes these outliers via functional boxplots. This code is written as a stand-along R package with the hopes of eventually submitting it to CRAN. The package is written in generality; it would be useful to any researching looking to analyze a general ensemble of PDFs.", + "laborHours": 0.0, + "languages": [], + "name": "DeBoinR: Density Boxplots in R", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/deboinr", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2024-01-31", + "metadataLastUpdated": "2024-01-31" + }, + "description": "New or improved capabilities included in v3.0 release are as follows:\n\n1. Enhancement in message passing layers through generalization of the class inheritance to enable the inclusion of a broader set of message passing policies\nInclusion of equivariant message passing layers from the original implementations of:\nSchNet (https://pubs.aip.org/aip/jcp/article/148/24/241722/962591/SchNet-A-deep-learning-architecture-for-molecules); DimeNet++ (https://arxiv.org/abs/2011.14115); EGNN models (https://arxiv.org/pdf/2102.09844.pdf)\n2. Restructuring of class inheritance for data management\n3. Support of DDStore https://github.com/ORNL/DDStore capabilities for improved distributed data parallelism on large volumes of data that cannot fit on intra-node memory capacities\n4. Large-scale system support for OLCF-Crusher and OLCF-Frontier", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HydraGNN v3.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/HydraGNN/releases/tag/v3.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v3.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-02-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Tool for water system owners to estimate the cost of system interruption or loss. Publicly available for download (.zip file) at https://www.pnnl.gov/media/24681", + "homepageURL": "https://www.pnnl.gov/media/24681", + "laborHours": 0.0, + "languages": [], + "name": "Drinking Water System Energy Resilience Value Estimator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://creativecommons.org/publicdomain/zero/1.0/legalcode", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/media/24681", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "leblondtr@ornl.gov" + }, + "date": { + "created": "2024-02-01", + "metadataLastUpdated": "2024-02-01" + }, + "description": "We introduce the Trapped-Ion Surface Code Compiler (TISCC), a software tool that generates circuits for a universal set of surface code patch operations in terms of a native trapped-ion gate set. To accomplish this, TISCC manages an internal representation of a trapped-ion system where a repeating pattern of trapping zones and junctions is arranged in an arbitrarily large rectangular grid. Surface code operations are compiled by instantiating surface code patches on the grid and using methods to generate transversal operations over data qubits, rounds of error correction over stabilizer plaquettes, and/or lattice surgery operations between neighboring patches. Beyond the implementation of a basic surface code instruction set, TISCC contains corner movement functionality and a patch translation that is implemented using ion movement alone. Except in the latter case, all TISCC functionality is extensible to alternative grid-like hardware architectures. TISCC output has been verified using the Oak Ridge Quasi-Clifford Simulator (ORQCS).", + "laborHours": 0.0, + "languages": [], + "name": "ORNL-QCI/TISCC", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-QCI/TISCC/blob/v1.0.0/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/TISCC", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-02-08", + "metadataLastUpdated": "2024-02-20" + }, + "description": "This notebook makes seismic phase travel time predictions using machine learning. There are 3 different\nmachine learning models corresponding to the three regimes: local, regional, and teleseismic. After\nreading in the test data and splitting into the 3 regimes, we use precomputed scalers to scale the input\nfeatures used to make the travel time predictions. We then load the machine learning models and use\nthem to predict travel times for test data.", + "homepageURL": "https://gdo-maltte.llnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Machine Learning Travel Time emulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gdo-maltte.llnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "choij@ornl.gov" + }, + "date": { + "created": "2024-02-09", + "metadataLastUpdated": "2024-02-12" + }, + "description": "DDStore is designed to addresses random, read-oriented, global shuffle operations for data-intensive deep learning applications. By preserving global shuffling, DDStore ensures that deep learning model maintains high accuracy and generalizability when it is trained with large volume of data using HPC facilities.", + "laborHours": 0.0, + "languages": [], + "name": "DDStore", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/DDStore", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-02-09", + "metadataLastUpdated": "2024-03-04" + }, + "description": "The OpenStudio\u00ae-ERI project allows calculating an Energy Rating Index (ERI) using the Department of Energy's open-source OpenStudio\u00ae/EnergyPlus\u00ae simulation platform. The building description is provided in an HPXML file format. \nThe project supports: \n- ANSI/RESNET/ICC 301\u00a9 Standard for the Calculation and Labeling of the Energy Performance of Dwelling and Sleeping Units using an Energy Rating Index \n- ENERGY STAR Certification System for Homes and Apartments Using an ERI Compliance Path \n- IECC ERI Compliance Alternative (Section R406) \n- DOE ZERH Certification Using an ERI Compliance Path For more information on running simulations, generating HPXML files, etc., please visit the documentation at https://openstudio-eri.readthedocs.io/en/latest/", + "laborHours": 249295.2, + "languages": [ + "Ruby" + ], + "name": "OpenStudio\u00ae-ERI (Energy Rating Index (ERI) Workflow) [SWR-18-72] 1.7.0 Released 12/14/2023", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-ERI", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.7.0" + }, + { + "contact": { + "email": "wieselquiswa@ornl.gov" + }, + "date": { + "created": "2024-02-12", + "metadataLastUpdated": "2024-02-15" + }, + "description": "OLM focuses on managing the ORIGEN reactor library, which is a special collection of data that enables rapid spent fuel calculations with SCALE/ORIGAMI.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ORIGEN Library Manager", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/scale/code/olm", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-02-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "a new release of the software tool that includes newly developed algorithms housed along\npreviously released ones within a single user interface.\nThe new functionalities are:\nCCS raw data converter (iEdison No. 0685901-23-0100), IPID 32762-E.\nIM-MS-DDA converter and data format (iEdison No. 0685901-23-0099), IPID 32761-E.\nThe previously developed functionalities are:\nPNNL-PreProcessor, IPID 31727-E.\n2DLC-MS to LC-IM-MS data file converter, IPID 32136-E.\nIMS data file transformations, IPID 32137-E.\nRemarks about the PNNL-PreProcessor:\nDirectly reads Agilent MassHunter (.d) data files and generates new Agilent MassHunter (.d) data files with\nenhanced raw signal quality and/or transformed data. Can also process UIMF files.\nHas both command-line and graphical user interfaces.\nPNNL provides the software executable, freely available for download (https://pnnl-comp-massspec.github.io/PNNL-PreProcessor) and it can be utilized by Agilent customers for non-commercial use.\nThe source code is not publicly available, an internal source code repository is maintained at PNNL", + "homepageURL": "https://pnnl-comp-mass-spec.github.io/PNNL-PreProcessor", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-PreProcessor v5.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://pnnl-comp-mass-spec.github.io/PNNL-PreProcessor", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://pnnl-comp-mass-spec.github.io/PNNL-PreProcessor", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "5" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-02-14", + "metadataLastUpdated": "2024-04-30" + }, + "description": "The Holistic Electricity Model (HEM) is a computational framework for analyzing electricity systems in their entirety, from the points of view of all key stakeholders.\n\nRelated publication: https://ieeexplore.ieee.org/document/10128887", + "laborHours": 7159.2, + "languages": [ + "Julia" + ], + "name": "HEM (HolisticElectricityModel.jl) [SWR-21-62]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel-hem/HolisticElectricityModel.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "maiterthm@ornl.gov" + }, + "date": { + "created": "2024-02-14", + "metadataLastUpdated": "2024-06-21" + }, + "description": "This project provides the AR/VR interface to ORNL's exascale digital twin.\nThe main functionality is implemented using Unreal Engine 5.1 for Desktop or\nMicrosoft Hololens2 based visualization and interation with the system.\nThe digital twin provides data ingestion from telemetry, as well as triggering\nand interacting with simulations developed for the wider ExaDigiT project at\nORNL, as well as for the LUMI system at CSC and other CrayEX Supercomputers.\nFor the overarching project, see ExaDigiT at https://exadigit.github.io,\nwith the code repositories at https://code.ornl.gov/exadigit.", + "laborHours": 25262.4, + "languages": [], + "name": "exadigitUE5", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/exadigit/exadigitue5.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "yakubovs@ornl.gov" + }, + "date": { + "created": "2024-02-15", + "metadataLastUpdated": "2024-02-15" + }, + "description": "This project enables user authentication on servers using OpenID Connect tokens. It includes a PAM module for SSH login via an OIDC token and a utility for executing commands and copying files on behalf of a user, also utilizing an OIDC token for authentication.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "OIDC Utils", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PaNGalaxy/oidc-utils", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-02-15", + "metadataLastUpdated": "2024-02-21" + }, + "description": "The National Renewable Energy Laboratory (NREL) and the U.S. Department of Energy's (DOE) Weatherization Assistance Program (WAP) are collaborating with the home energy retrofit industry to support the development of skilled workers. The Installer Badges Toolkit provides a flexible, customizable, and voluntary approach to training and skills recognition for WAP implementers, utility programs, private-sector workers, and contractors.\n\nIn Fiscal Year 2018, DOE, along with the Crew Leader scheme committee, determined the Retrofit Installer Technician (RIT) Job Task Analysis (JTA) could be eliminated and its tasks inserted in the Crew Leader JTA. The RIT tasks became the basis of the Installer Badges.\n\nThe Badges Toolkit was updated in 2020 to add licensing and copyright agreements. Users must cite the copyright information when using or distributing copies of the Badges Toolkit in any way. The technical content has remained unchanged from previous versions of the Badges Toolkit.\n\nThe Toolkit for home retrofits consists of 25 Badges, each representing different energy efficiency tasks that an installer could perform on a home. Each Badge defines the desired outcome, criteria to verify, applicable material requirements, and references to Standard Work Specifications (SWS) or other relevant standards.\n\nThe Badges provide a consistent approach to training by ensuring that installers in different regions are learning the same skills nationwide. Organizations can also customize the Toolkit by choosing only those Badges that are relevant to their program.\n\nThe Badges Toolkit includes five pieces:\n\n\"How to Use the Badges Toolkit\" provides a brief overview of how a Grantee, Subgrantee, or training provider may approach using the toolkit.\nThe \"Badges Toolkit: Worksheet\" includes what to consider when determining whether and how to best incorporate the Badges into a weatherization assistance program.\nThe \"Crew Leader Job Task Analysis Spreadsheet\" indicates how the Badges align with specific areas of the JTA.\nThe \"Installer Badges Passport\" features separate pages for each Badge, which include places for the installer and the supervisor/trainer to record the number of times a task has been successfully completed.\nThe \"Installer Badges Verification Criteria\" includes sample inspection checklists for each Badge. These can be modified as needed based on approved variance requests or more stringent requirements. They also provide a basis for consistent inspections and awarding of Badges.\n \n\nNote: All elements of the Badges Toolkit are designed for use by potential program implementers. They are not off-the-shelf products intended for immediate deployment. Program implementers must review and modify as needed, revise verification criteria to match local requirements, complete worksheets, and otherwise define the parameters of their own badging program.", + "homepageURL": "https://sws.nrel.gov/installerbadges", + "laborHours": 0.0, + "languages": [], + "name": "GHEP WIBT (Guidelines for Home Energy Professionals Weatherization Installer Badges Toolkit) [SWR-20-69]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://creativecommons.org/licenses/by-nc/4.0/deed.en", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sws.nrel.gov/installerbadges", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-02-16", + "metadataLastUpdated": "2024-02-16" + }, + "description": "The Single-Family and Manufactured Interactive 3D houses can be used as a self-guided learning tool by anyone interested in learning more about retrofit strategies of common weatherization measures. Alternatively, the tool can be used by training organizations for a more structured learning experience when paired with a learning activity or trainer-led demonstration.", + "homepageURL": "https://www.energy.gov/scep/wap/weatherization-installer-job-aids-and-single-family-interactive-3d-house", + "laborHours": 0.0, + "languages": [], + "name": "3D House (3DH) [SWR-22-83]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.energy.gov/sites/default/files/2023-09/License-and-Agreement-3D-house_9.22.23.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.energy.gov/scep/wap/weatherization-installer-job-aids-and-single-family-interactive-3d-house", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-02-22", + "metadataLastUpdated": "2024-04-01" + }, + "description": "Data-based closure models are increasingly being used to replace physic-based closure models because of their flexibility and the growing availability of data. However, closure models are subject to uncertainty because of lack of data in parts of the input space (epistemic uncertainty) or because of noise in the data (aleatoric uncertainty). This software contains a toolbox for training bayesian neural nets that can estimate both uncertainties. A specific treatment is provided to ensure accuracy outside of the data distribution. A set of tools are provided to reduce the dimensionality of the uncertain parameter space, thereby enabling fast uncertainty propagation.", + "laborHours": 3328.8, + "languages": [ + "PureBasic", + "Jupyter", + "Python", + "Shell" + ], + "name": "MLUQ (Uncertainty quantification for ML closure models) [SWR-24-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mluq-prop", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "reevest@ornl.gov" + }, + "date": { + "created": "2024-02-23", + "metadataLastUpdated": "2024-02-23" + }, + "description": "Finite difference heat transfer using Cabana for additive manufacturing", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Finch", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-MDF/Finch", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-02-26", + "metadataLastUpdated": "2024-05-08" + }, + "description": "Co-optimized Machine-Learned Manifolds (CMLM) is a data-driven approach for developing reduced-order manifold models for high-dimensional chemically reacting systems. It involves a specially designed neural network, the training of which simultaneously optimizes linear combinations of species that define the manifold, nonlinear mapping to outputs of interest such as reaction rates, and (optionally) subfilter closure for large eddy simulation. This software package provides an implementation of the CMLM approach in Python using the PyTorch machine learning library. A few example cases are included, showing how the tool can be applied to different types of data from 0D and 1D reacting simulations performed using Cantera. The neural networks can be saved in a format that is readable by the Pele suite of combustion solvers for use in reacting computational fluid dynamics simulations.\n\nThis software repository contains several python scripts to perform various tasks associated with the Co-optimized Machine Learned Manifolds (CMLM) model, which is described in Perry, Henry de Frahan, and Yellapantula, CNF, 2022 (https://doi.org/10.1016/j.combustflame.2022.112286). This includes not only the code that defines the CMLM model, but also scripts to generate suitable training data, scripts to pre-process the data, scripts to train the CMLM model, and scripts to plot the output, as well as various other helper files. The scripts depend on several commonly used python libraries for data analysis and chemical reaction computations. The trained models that result from this tool are designed to work with the an interface being implemented in the Pele suite of reacting flow solvers (https://github.com/AMReX-Combustion).", + "laborHours": 1778.4, + "languages": [ + "Python" + ], + "name": "CMLM (Co-Optimized Machine-Learned Manifolds) [SWR-23-41]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/cmlm", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-02-27", + "metadataLastUpdated": "2024-02-27" + }, + "description": "INL engineers developed a special purpose software framework designed to establish real-time connections between multiple running Unity instances.\n\nThe framework is developed in Unity, a game engine development platform. \n\nThis framework programmatically attaches functions to engineering models, enabling users to interact with, observe, and make changes to virtual models. These interactions are broadcasted through websocket connections, and received by other engineers in real-time.", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Multiplayer Engineering", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Multiplayer_Engineering", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "brownjm@ornl.gov" + }, + "date": { + "created": "2024-02-27", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This is a collection of public data produced by AMPX or curated from quality sources that the SCALE code system relies on for user problem input.", + "laborHours": 15.2, + "languages": [], + "name": "SCALE/DB-Public", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/scale/code/db-public/-/blob/main/LICENSE", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/scale/data/db-public", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-02-27", + "metadataLastUpdated": "2024-06-05" + }, + "description": "EnergyPlus\u2122 is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption and water use in buildings.\n\nThis is the EnergyPlus Development Repository.\n\nThe Department of Energy maintains a public website for EnergyPlus where you can find much more information about the program. https://energyplus.net/\n\nFor detailed developer information, consult the wiki. https://github.com/NREL/EnergyPlus/wiki\n\nMany users (and developers) of EnergyPlus are active on Unmet Hours, so that's a great place to start if you have a question about EnergyPlus or building simulation. https://unmethours.com/questions/\n\nFor more in-depth, developer-driven support, please utilize the EnergyPlus Helpdesk. https://energyplushelp.freshdesk.com/support/home", + "laborHours": 2335920.8, + "languages": [ + "C++", + "Fortran", + "Python", + "Jupyter Notebook", + "Visual Basic 6.0", + "CMake" + ], + "name": "EnergyPlus\u2122 v.23.2.0 2023 [SWR-17-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/EnergyPlus?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlus", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "23.2.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-02-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Efficient Graph Neural Network for Predicting Molecular Properties software can compare the prediction quality with ab initio DFT results reported by the high-performance state-of-theart NWChem quantum chemistry package [1] through Mean Absolute Error (MAE) obtained by the fitting between DFT and\nmodel predictions i.e, MPNN [2]. We also demonstrated the performance benefits by grouping large molecules by atom\nsizes, and executing GNN models on different types of resources. Since the training times depend on the number of\natoms, we demonstrate the impact of distributing the workloads on two GPUs with varying capabilities (e.g., NVIDIA A100\nvs. GeForce RTX 2080 Ti) to optimize the efficiency. We are at the precipice of broad adoption of GNNs for molecular\nproperty prediction tasks\u037e hence, our work is timely by comparing model prediction against classical approaches with the\nintent of providing initial screening for specific classes of molecules.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/emp-gnn", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/emp-gnn", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Fair Bagging Boosting Models is a software implementation of a framework for building, measuring bias and correcting bias in 3 popular forest machine learning models: gradient boosted trees (GBT), random forest (RF), and XGBoost models, using the XGBoost library. The framework takes advantage of the flexibility in XGBoost library to represent gradient boosted tree and random forest models, as well as the ability to use custom loss function.", + "laborHours": 1216.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "Fair Bagging Boosting Models [SWR-24-38]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Fair_Bagging_Boosting_Models", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2024-03-01", + "metadataLastUpdated": "2024-03-04" + }, + "description": "First release of version 3.0 of the Energy Exascale Earth System Model. \nThe fully coupled cases now run by default in a \u201ctri-grid\u201d configuration where the land and river model share a higher-resolution (0.5 degree) lat-lon grid while the atmosphere and ocean are on their own grids. [ATM] component is EAM. Vertical res. has been increased from 72 to 80 layers; horizontal res. remains ne30pg2. Atmospheric physics have had significant additions and changes since version 2. Added: interactive gas chemistry in stratosphere and troposphere; size mode for prognostic treatment of stratospheric sulfate aerosol; explicit representation of secondary organic aerosols (SOA) sources; a new dust emission scheme; Predicted Particle Properties (P3) for stratiform clouds; cloud microphysics for convective clouds; MCSP to represent the effects of organized mesoscale convective systems; rougher topography. Improved: aerosol wet removal processes to reduce the overestimation of aerosols and thus aerosol forcing; numerical coupling of aerosol emission, vertical mixing and dry deposition; cloud base mass flux adjustment in ZM; lower stratospheric vertical grid and surrogate-accelerated parameter optimization. Re-tuned: Dimethyl sulfide (DMS) emission, number of monolayers for black carbon (BC) aging, and hygroscopicity of particulate organic matter (kPOM). [LAND] component is ELM. The default configuration for ELM has been switched from vegetation leaf area specified as a static monthly time series based on satellite data to a dynamic vegetation growth model. This implementation uses prognostic coupled carbon, nitrogen, and phosphorus cycles (C-N-P) for vegetation and soil biogeochemistry; the relative demand (RD) approach to resolve competition between plants and soil microbes for available nutrients; the converging trophic cascade (CTC) model for organization of plant litter and soil organic matter pools. The model also includes: A computationally efficient radiative transfer parameterization (TOP), which is based on the Monte Carlo simulations, accounts for subgrid topographic effects on solar radiation; Changed the order of sublimation and dew on snow depth calculation to ensure that snow depth is not accidentally set to a negative value. [RIVER] model is still MOSART. [OCEAN] component remains MPAS-Ocean. Major change since version 2.1 include: Using a new Icosahedral 30 km mesh with Ice Shelf Cavities (IcoswISC30E3r5) for low-resolution coupled simulations. Switched coupled surface pressure to pressure at mean sea level which reduces errors in gradient term for sea ice. Improvements to the Redi isopycnal mixing scheme; Improved computational efficiency of the ocean component by changing the baroclinic time stepping method. [SEA-ICE] component is MPAS-Seaice and has had many improvements since 2.1; Added Icepack as the default sea ice column physics; Switched to high-frequency sea ice coupling as the default surface stress flux option for all meshes; Reduced the maximum number of sea ice atmospheric turbulent flux iterations; Decreased the dynamics minimum concentration sea ice and the ice mass per unit area cutoff; Reduced standard monthly sea ice output by removing sea ice age, first year ice tracers, and level ice volume and area; Added or updated checks on configuration settings. [LAND-ICE] component remains MPAS-Albany-landIce (MALI). The version of MALI has been updated to include higher-order advection and time integration. The land-ice component is not yet supported in production configurations with v3. [COUPLER] remains cpl7/MCT. A new property-preserving map procedure enables high-order flux maps between components for selected fields. In v3 LR cases, applied to all atmosphere-to-surface fluxes except precip. Calculation of gustiness between atmosphere, ocean and land was rationalized. Default processor layouts for the low-resolution configuration are available on Perlmutter and other DOE platforms.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v3.0.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v3.0.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v3.0.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-03-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Atmospheric Radiation Measurement Program developed a value added product that could run autonomously to\ndetermine planetary boundary height using radiosondes. This product has produced data for 117 unique sites and\nfacilities for more than 10 years. The initial software was released around 2013 and data has been produced since 2001 for\nsome sites.", + "laborHours": 0.0, + "languages": [], + "name": "ARM-DOE/adi-vap-pblhtsonde", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/adi-vap-pblhtsonde", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "liny@ornl.gov" + }, + "date": { + "created": "2024-03-04", + "metadataLastUpdated": "2024-03-04" + }, + "description": "IRAD (Ion Irradiation and Radiation Damage) is an open-source GUI for SRIM-like vacancy production and implanted ion profile calculations. Using updated databases, IRAD is accessible at https://code.ornl.gov/liny/irad for Windows systems. It performs energy-corrected Iradina calculations, automatically determining dpa and implanted ion concentration, considering total ion fluence. Additional results like ion trajectories, final positions, stopping power distribution, etc., are available. Advanced settings permit customization of parameters such as stopping power database, incident ion angle, and 3D target simulations.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "IRAD", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/liny/irad", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-05", + "metadataLastUpdated": "2024-03-14" + }, + "description": "The interplay between energy, climate, and weather is becoming more complex as our changing climate continues to affect the weather we experience which in turn drives changes in the ever increasing share of renewable energy generation and energy demand. Energy system analyses commonly rely on meteorological inputs to estimate renewable energy generation and energy demand; however, these inputs rarely represent the estimated impacts of future climate change. Climate models and publicly available climate change datasets can be used for this purpose, but the selection of inputs from the myriad of available models and datasets is a nuanced and often subjective process. There is no single perfect climate model or dataset for all applications. In this repository, we include software and the corresponding assessments of various global climate models (GCMs) from the Coupled Model Intercomparison Project (CMIP6), evaluating their skills with respect to the historical climate and comparing of their future projections of climate change. We focus on variables that directly affect the energy system including the representation of extreme values that can drive grid resilience events. The objective of this repository is not to recommend the best climate model and dataset for a given analysis, but instead to provide a reference to facilitate the selection of climate models and datasets in subsequent work.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "gcm_eval (NREL Global Climate Model Evaluation) [SWR-24-37]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/gcm_eval", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-05", + "metadataLastUpdated": "2024-03-07" + }, + "description": "Numerical simulations can accelerate scale up and optimization of bioreactors. This project provides a toolbox to facilitate such numerical simulations in OpenFOAM. The tool box contains 1) mesh generations tools for several typical bio reactor types in OpenFOAM 2) Inverse modeling tools to calibrate models using available experimental data 3) post processing tools that accelerate and streamline the analysis of the numerical simulations.", + "laborHours": 0.0, + "languages": [ + "C++", + "Liquid" + ], + "name": "BiRD (BioReactorDesign) [SWR-24-35]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BioReactorDesign", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "foleymk@ornl.gov" + }, + "date": { + "created": "2024-03-07", + "metadataLastUpdated": "2024-03-12" + }, + "description": "The Hydropower Fleet Intelligence application can integrate hydropower facilities data sources to perform analyses on asset age, reliability and costs, as well as produce visualizations that combine time series data collected by mechanical component sensors with event history.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python", + "TypeScript" + ], + "name": "Hydropower Fleet Intelligence", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/HydroFleetIntel/blob/main/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/HydroFleetIntel", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "datepa@ornl.gov" + }, + "date": { + "created": "2024-03-07", + "metadataLastUpdated": "2024-03-07" + }, + "description": "Machine Learning on Adiabatic Quantum Computers (MAQ) is a library of algorithms used to train machine learning models on adiabatic quantum computers.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "MAQ: Machine Learning on Adiabatic Quantum Computers", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/prasannadate/maq", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-07", + "metadataLastUpdated": "2024-04-16" + }, + "description": "GRAVI (GRid Analysis and Visualization Interface) is a web application for viewing and analyzing nodal Production Cost Model (PCM) and Capacity Expansion Model (CEM) simulations. The web application provides the ability to animate geospatially coupled timeseries data in an agnostic way regardless of the underlying simulation tool used to generate the data. GRAVI also provides capabilities to animate non-geospatial data relevant to a PCM or CEM model. Furthermore, this web application can be tailored as an real-time operational tool to better understand a live grid.", + "laborHours": 1535.2, + "languages": [ + "TypeScript", + "CSS", + "JavaScript", + "Python" + ], + "name": "GRid Analysis and Visualization Interface (GRAVI) [SWR-24-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GRAVI", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-03-07", + "metadataLastUpdated": "2024-10-28" + }, + "description": "T3CO (Transportation Technology Total Cost of Ownership), is open source software for modeling total cost of ownership for commercial vehicles with advanced powertrains.\n\nT3CO is a modeling framework for determining geospatially and temporally optimized total cost of ownership (TCO) for vehicle powertrain technologies. T3CO runs NREL's FASTSim\u2122 software for a representative set of operating conditions to minimize TCO based on vehicle parameters that affect purchase and operating costs (e.g., fuel/electricity consumption, asset depreciation, opportunity costs associated with charging time) while simultaneously ensuring that firm performance constraints (e.g. zero-to-sixty time, gradeability) are satisfied. T3CO will enable the user to control which powertrain parameters are used in optimizing TCO, and these parameters will be modified by a multi-objective optimization (MOO) algorithm to identify a Pareto-optimal solution set. The optimization algorithm will be modular so that users can choose from many different MOO options or insert their own user-defined optimization tool.\n\nNREL T3CO Homepage: https://www.nrel.gov/transportation/t3co.html\nPyPI package: https://pypi.org/project/t3co/", + "laborHours": 5289.6, + "languages": [ + "Python" + ], + "name": "T3CO (Transportation Technology Total Cost of Ownership) Open Source [SWR-21-54]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/T3CO", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-03-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An R package to prepare, process, and synthesize FAOSTAT data for global agroeconomic and multisector dynamic modeling", + "laborHours": 0.0, + "languages": [], + "name": "JGCRI/gcamfaostat", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/gcamfaostat", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-08", + "metadataLastUpdated": "2025-04-03" + }, + "description": "Test-grid-buildouts is a set of notebooks for creating buildouts of synthetic transmission grids with various levels of renewable energy. Workflows can be used to augment various test grid with varying levels of wind/solar generation. Aggregated renewable energy time series (actuals and scenarios) at grid buses can then be used for various transmission grid operation problems. Highly customizable workflow consists of parsing of synthetic grid files, setting up SAM & reV simulations, application of exclusion masks, creating of custom renewable generators on the grid, aggregating of power time series, and writing of modified grid description files.", + "laborHours": 6824.8, + "languages": [ + "Jupyter Notebook" + ], + "name": "test-grid-buildouts [SWR-23-112]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/test-grid-buildouts", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-09", + "metadataLastUpdated": "2024-03-20" + }, + "description": "This software implements a data-driven framework to uncover mechanistic models of dynamics directly from time-resolved coherent X-ray scattering measurements. It employs neural differential equations to parameterize unknown real-space dynamics and incorporates a computational scattering forward model to relate real-space predictions to reciprocal-space observations.", + "laborHours": 0.0, + "languages": [], + "name": "DATA-DRIVEN DISCOVERY OF DYNAMICS FROM TIME-RESOLVED COHERENT SCATTERING", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ninarina12/dynamiCXS", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-09", + "metadataLastUpdated": "2024-03-13" + }, + "description": "This is a graphical user interface (GUI) that can be deployed in a Node-RED environment and be configured to provide monitoring and control of an ISO 15118 EV Charger (DC or AC).", + "laborHours": 0.0, + "languages": [], + "name": "ISO 15118 Node-Red Dashboard", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/node-red/node-red", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-09", + "metadataLastUpdated": "2024-03-26" + }, + "description": "RMEM - a prototyping platform to explore the usage of RMA-based strategies in GPU-to-GPU communication.\nThe implementation relies on libfabric (BSD-2 or GNUv2) to explore different synchronization approach and their associated performance. It is compatible with different network technologies such as InfiniBand, SlingShot-11, and TCP. It provides to the user host-to-host and device-to-device communication. The latter can be initiated either from the host, or from the device.", + "laborHours": 0.0, + "languages": [], + "name": "RMEM-REMOTE MEMORY", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/rmem", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-03-11", + "metadataLastUpdated": "2024-03-11" + }, + "description": "This model provides a cost estimate for transporting CO2 via truck or rail in the United States using\ncommercially available equipment and technologies. The model includes an analysis of direct and indirect\nCO2 emissions to determine costs per net tonne of CO2 transported. Publicly available data and methods\npublished in the peer-reviewed literature are used to the extent possible; references are available at the\nbottom of the \"Calculations\" sheet. Upstream (i.e., liquefaction, buffer storage) and downstream (i.e.,\nbuffer storage, reconditioning) activities are included in the model of emissions and costs. All capital and\noperating expenditures are estimated in the \"Calculations\" sheet. The cost of financing the project is\ndetermined in the \"FINEX\" sheet. All user inputs are done via drop down menus in on the \"User Interface\"\nsheet. Summary results are also provided on the \"User Interface\" sheet.", + "laborHours": 0.0, + "languages": [], + "name": "Multimodal CO2 Transportation Cost Model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/myers79/MuMo-CoCo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-03-11", + "metadataLastUpdated": "2024-03-11" + }, + "description": "This patch will implement the new size statistics standard in the Rust implementation of Apache Arrow\nand Parquet (https://github.com/apache/arrow-rs/). This allows an uncompressed and unencoded size to\nbe known prior to uncompressing and unencoding data stored in parquet files.", + "laborHours": 0.0, + "languages": [], + "name": "Implement the size statistics Parquet standard in the Rust implementation of Arrow and Parquet.", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/apache/arrow-rs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-03-11", + "metadataLastUpdated": "2024-03-11" + }, + "description": "OPFLearn.jl is a Julia package for creating datasets for machine learning approaches to solving AC optimal power flow (AC OPF). It was developed to provide researchers with a standardized way to efficiently create AC OPF datasets that are representative of more of the AC OPF feasible load space compared to typical dataset creation methods. The OPFLearn dataset creation method uses a relaxed AC OPF formulation to reduce the volume of the unclassified input space throughout the dataset creation process. Over time this input space tightens around the relaxed AC OPF feasible region to increase the percentage of feasible load profiles found while uniformly sampling the input space. Load samples are processed using AC OPF formulations from PowerModels.jl. More information on the dataset creation method can be found in our publication, \"OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets\". To use OPFLearn.jl a PowerModels network data dictionary is required (can be loaded from Matpower \".m\" files) to define the network the dataset is being created for.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "OPFLearn.jl v0.1.2 5/18/2023 [SWR-21-109]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OPFLearn.jl", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.1.1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-03-11", + "metadataLastUpdated": "2024-03-11" + }, + "description": "A circular economy emphasizes the efficient use of all resources (e.g., materials, land, water). Despite anticipated overall benefits to society, the transition to a circular economy is likely to create regional differences in impacts. Current tools are unable to fully evaluate these potential externalities, which will be important for informing research prioritization and regional decision making. The Circular Economy Lifecycle Assessment and VIsualization (CELAVI) framework allows stakeholders to quantify and visualize potential regional and sectoral transfers of impacts that could result from transitioning to a circular economy, with particular focus on energy materials. The framework uses system dynamics to model material flows for multiple circular economy pathways and decisions are based on learning-by-doing and are implemented via cost and strategic value of different circular economy pathways. It uses network theory to track the spatial and sectoral flow of functional units across a graph and discrete event simulation to to step through time and evaluate lifecycle assessment data at each time step. The framework is designed to be flexible and scalable to accommodate multiple energy materials and multiple energy technologies. The primary goal of CELAVI is to help answer questions about how material flows and environmental and economic impacts of energy systems might change if the circularity of energy systems increases.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "CELAVI (Circular Economy Lifecycle Assessment and VIsualization) v.1.3.1 9/30/2022 [SWR-20-87]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/celavi", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v.1.3.1" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-12", + "metadataLastUpdated": "2024-03-19" + }, + "description": "This program provides a fixed-grid quadrature algorithm to compute integrals in the self-energy of the quark propagator within the Maris-Tandy model. The quark propagator both on t he spacelike real axis and at complex-valued momenta is determined from its Schwinger-Dyson equation (SDE). We first apply an iterative solver to find the quark propagator on the spacelike real axis. The propagator at complex-valued momenta is then computed from its self-energy based on this solution, where \ndemanding integrals are encountered. In order to compute of these integrals, we apply customized variable transformations for the radial integral after subtracting the asymptotics. We subsequently apply an optional compound of quadrature rules for the angular integral.", + "laborHours": 0.0, + "languages": [], + "name": "SDE_quark", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/shaoyangjia/SDE_quark", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-12", + "metadataLastUpdated": "2024-03-19" + }, + "description": "This is a small kernel that was used to collect data for an upcoming paper. We would like to have the code be open source so that the reviewers (and then readers) of the paper can see the whole code, and can reproduce/verify our results. This is not a fully featured application, it cannot produce any useful simulation results, it just executes a small abstracted kernel using synthetic data. The purpose of the kernel is to understand the basic performance characteristics of an HPC kernel on novel AI accelerator architectures. The main kernel is written in the CSL coding language for use with the Cerebras WSE-2 AI accelerator. The kernel represented is the Monte Carlo cross section lookup kernel, which is a small kernel used by the Monte Carlo neutral particle transport algorithm. There is also a baseline kernel written in CUDA that we will include in the repository to form a basis for comparing the WSE-2 to GPU.", + "laborHours": 0.0, + "languages": [], + "name": "MONTE CARLO CROSS SECTION LOOKUP KERNEL FOR THE CEREBRAS WSE-2 IN CSL", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-science/mc_on_accelerators", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kwons@ornl.gov" + }, + "date": { + "created": "2024-03-12", + "metadataLastUpdated": "2024-03-13" + }, + "description": "There is high demand for high-throughput calculations of phase equilibria based on the CALPHAD method (CALculation of PHAse Diagram). High-throughput calculations are possible through HPC, currently by a commercial program called Thermo-Calc. However, the number of nodes/processors are limited to the number of purchased license (16 processors per license). This program provides a toolkit for high-throughput calculations of phase equilibria by the CALPHAD method. The program is prepared for Python environment, so that it can be easily installed and used together with other open-source programs. The program can be run in supercomputer.", + "laborHours": 0.0, + "languages": [ + "Fortran", + "Python" + ], + "name": "Equilipy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/Equilipy", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2024-02120O\nThis program enumerates and classifies all possible functional elements in several different categories within the Ballistic Asynchronous Reversible Computing (barc) model of computation. barc software is a research tool that is being used to help document the possible digital behaviors of primitive functional elements in the ABRC a.k.a. BARC model of computation. \n\nThe method of operation of this software leverages elementary concepts and methods from discrete mathematics: combinatorics (permutations), partitions and equivalence classes, symmetry transformations, and the theory of finite groups. Implementation is in Python programming language. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 562.4, + "languages": [ + "Python" + ], + "name": "BARC Element Classifier (barc)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/barcs", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-15" + }, + "description": "SAND2024-02099O\nThe software is designed to allow researchers to perform kinetic Monte Carlo (KMC) simulations of catalytic reactions on a 2D lattice. The code is written efficiently to run on a variety of shared memory computing architectures (e.g. GPU, multi-core) and to natively express the full complexity of lateral interactions on reaction rates. The software allows researchers to perform KMC simulations of catalytic reactions on a 2D lattice. It uses parallel shared-memory computing architectures to reduce run-times and allows for simultaneous simulation of multiple independent runs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python", + "C++" + ], + "name": "KinCat v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/KinCat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-15" + }, + "description": "SAND2024-01982O\nThe Searchlight Source Code is software for creating, managing, and dismantling experiments. It also is a simple web server that mimics an online training module with scripts to automate a client. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python", + "html", + "CSS", + "PHP" + ], + "name": "Searchlight Source Code", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "kentpr@ornl.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-19" + }, + "description": "QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support.", + "laborHours": 0.0, + "languages": [ + "C++17" + ], + "name": "QMCPACK v3.17.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/QMCPACK/qmcpack?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QMCPACK/qmcpack/releases/tag/v3.17.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v3.17.0" + }, + { + "contact": { + "email": "kentpr@ornl.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-19" + }, + "description": "QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support.", + "laborHours": 0.0, + "languages": [ + "C++17" + ], + "name": "QMCPACK v3.17.1", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/QMCPACK/qmcpack?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QMCPACK/qmcpack/releases/tag/v3.17.1", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v3.17.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-15" + }, + "description": "SAND2024-01823O\nThe HawaiiCoast_GT dataset validates anomaly detection algorithms on marine vessel tracks. The software also curates the dataset by extracting, filtering, cleaning, correlating, and computing. The codebase demonstrates the overarching methodology for deriving datasets like HawaiiCoast_GT. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HawaiiCoast_GT Code Generation", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HawaiiCoast_GT_Code_Generation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-18" + }, + "description": "SAND2024-01664O\nThis software demonstrates the usage of the Variational Kalman Filtering with Hinf-Based Correction software, which can be used to calculate the mean and covariance of the estimate of a high-dimensional parameter. The software performs this task faster than the traditional Kalman filtering technique. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Variational Kalman Filtering with Hinf-Based Correction v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/VKF-with-Hinf-Based-Correction-for-Robust-Bayesian-Learning", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2024-01501O\nLogical Activation Functions software is a PyTorch implementation from the paper, \"Logical Activation Functions for Training Arbitrary Probabilistic Boolean Logic.\" The activation functions approximate logit-space marginalization of probabilistic truth tables from probabilistic interpretations of inputs. They also provide a general methodology to approximate logical relationships between abstract antecedents and consequents for machine learning architectures. They do not target any specific application or use-case. By training probabilistic truth tables, these activation functions can capture more expressive relationships in a neural network than typical elementwise activation functions. \n\nThis code is only designed for a single compute node with a GPU and is limited to machine learning architectures than can fit within the memory of a single GPU. \n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 608.0, + "languages": [ + "C++", + "Python", + "Cuda", + "Shell" + ], + "name": "Logical Activation Functions v.1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/logic-act", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "mdelben@lbl.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-20" + }, + "description": "BerkeleyGW is a versatile, massively parallel, GPU-enabled, modular software package for quantum many-body perturbation theory applied to study the excited state properties of electrons in materials. It employs the ab-initio GW and GW plus Bethe-Salpeter equation (GW-BSE) methods and beyond. It can be used to investigate a wide range of materials from bulk crystals to clusters and 2D/1D materials, adapting to insulating, metallic, and semi-metallic systems alike. Journal article: https://doi.org/10.1016/j.cpc.2011.12.006", + "homepageURL": "https://berkeleygw.org/download", + "laborHours": 0.0, + "languages": [], + "name": "BerkeleyGW", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://berkeleygw.org/download", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "haunab@ornl.gov" + }, + "date": { + "created": "2024-03-18", + "metadataLastUpdated": "2024-03-18" + }, + "description": "A tool to compile firmware and flash same to Klipper MCUs\n\nNote: This is a personal project being submitted to DOE CODE as per instruction from ORNL's TTS office.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Klipper Quick Flash", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laikulo/klipper-quickflash.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-19" + }, + "description": "SAND2024-02969O\nThe NetCDFFile provides a generic interface to NetCDF and/or PnetCDF library calls, allowing the user to write generic code to read and write from NetCDF files. The NetCDFFile library requires a C++20 compliant compiler as well as NetCDF and PnetCDF libraries installed on the machine. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "NetCDFFile v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-19" + }, + "description": "SAND2024-02520O\nTensor SQL Database performs certain relational database management system/structured query language (RDBMS/SQL) queries faster than is possible using existing state-of-the-art databases. Tensor SQL is optimized for sparse linear algebra problems and other whole-table queries. Currently, the database is being used only for research and program development. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "TenSQL v.2023.01.20", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TenSQL", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2023.01.20" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-19" + }, + "description": "SAND2024-02435O\nThe software coloring allows applications written in the C++ language to generate publication-quality 2D plots. Its functionality is similar to Microsoft Excel's chart functionality or the Python language's matplotlib package. The value of coloring is that it is written purely in C++ and thus can be compiled on systems where Python is not available and linked into high performance computing software. \n\nFor drawing shapes onto an image, coloring uses the mathematical definition of quadratic Bezier splines and uses Newton's method to search for the closest point on a spline to a given query point. This is then used to do accurate sub-pixel sampling to get clean, non-pixelated images. For working with the actual plot data, coloring has basic statistical methods such as finding maxima and minima as well as axis scaling such as logarithms. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++17 version" + ], + "name": "coloring v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/coloring", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-19" + }, + "description": "SAND2024-01427O\nMesoscale Multiphysics Phase Field Simulator (MEMPHIS) is used for solving interfacial problems and can be applied to many evolutionary problems. Some examples are solidification dynamics, viscous fingering, fracture mechanics, hydrogen embrittlement, vesicle dynamics, electro-mechanical degradation of batteries, aging of microstructures, and segregation. MEMPHIS is written in Fortran 90 in a modular fashion, where model and numerical solvers are decoupled from one another. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "fortran 90" + ], + "name": "MEMPHIS (Mesoscle Multiphysics Phase Field Simulator v.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-20" + }, + "description": "SAND2024-01365O\nThe Graph Neural Networks and Applied Linear Algebra is companion software for the educational article with the same title. The software provides illustrative examples of graph neural networks in Matlab and Python. These stand-alone algorithms are for educational purposes. \n\nThe software also includes graph neural network-based algorithms for a trainable Jacobi iteration as well as diffusion coefficient estimation. The software provides human-interpretable implementations of Graph Neural Networks in Matlab and Python. These implementations are not optimized for performance and instead emphasize readability. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python" + ], + "name": "Graph Neural Networks and Applied Linear Algebra v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gnn-applied-linear-algebra", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-04-22" + }, + "description": "This software introduces a high-level interface designed to simplify solving linear systems using hypre, a\nrenowned library for such computational challenges. It is crafted to be accessible and user-friendly,\nmaking the powerful capabilities of hypre available to a broader audience without requiring in-depth\ntechnical knowledge. The interface is characterized by its use of YAML for input, a format celebrated for\nits structured yet straightforward readability. This choice ensures that users can easily configure the\nsoftware to meet their specific needs. Additionally, the software boasts an intuitive API that encapsulates\nhypre's functionalities, making it easier for users to interact with the process of solving linear systems. It is\nparticularly beneficial for prototyping, offering a quick and efficient means to test various solver and\npreconditioner configurations. Furthermore, the software allows for the creation of an offline testing\nframework in which predefined linear systems are read from files and benchmarked with user-defined\nsolution strategies. This makes it an invaluable tool for developers and researchers exploring and\nvalidating their computational models. Overall, the software serves as a bridge, bringing the advanced\ncomputational capabilities of hypre closer to users who may need more specialized technical expertise,\nthereby facilitating innovation and exploration in the field of numerical linear algebra.", + "laborHours": 3845.6, + "languages": [], + "name": "hypredrive: high-level interface for solving linear systems with hypre", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hypre-space/hypredrive", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-20" + }, + "description": "EB_Profiler, v2.2 is a LabVIEW program which uses computed tomography to determine the power\ndistribution in the beams of electron beam welders. It requires that the National Instruments LabVIEW\nRun-Time Engine be installed. The program takes in beam profile data from a data acquisition device or\nfrom a data file. Beam parameters necessary for calculations are entered by the user or automatically\nextracted from header information in the data file. The result is a two-dimensional reconstruction of the\npower distribution in the beam.", + "homepageURL": "https://softwarelicensing.llnl.gov/product/ebprofiler-v22", + "laborHours": 0.0, + "languages": [], + "name": "EB_Profiler", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://softwarelicensing.llnl.gov/product/ebprofiler-v22", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "2.2" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-21" + }, + "description": "SAND2024-01324O\nMrHyDE, which stands for Multi-resolution Hybridized Differential Equations, is a general-purpose C++ package for the solution of coupled multiphysics and multiscale systems on massively parallel computing systems. \n\nMrHyDE is designed to enable moving beyond forward simulation for multiscale applications which includes optimization, control, uncertainty quantification, and stochastic inversion. The framework provides interfaces to several packages within the Trilinos framework and leverages automatic differentiation to enable adjoint capabilities for large-scale, gradient-based optimization. MrHyDE provides automated multiscale capabilities through a subgrid model interface and multiscale Dirichlet-to-Neumann maps. \n\nFor extreme-scale applications, MrHyDE provides in situ data-compression algorithms to reduce memory requirements while maintaining performance. MrHyDE is a general-purpose, computational framework for the solution of multiscale and multiphysics applications. It uses a combination of structure-preserving, physics-compatible discretizations, fully implicit methods, multi-resolution schemes, or fully explicit methods. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python" + ], + "name": "MrHyDE v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MrHyDE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2024-01302O\nNeuralRW-Loihi: Spiking Discrete Time Markov Chain Simulator for Intel Loihi is a neuromorphic script that generates a random walk simulation of a discrete-time Markov Chain for the Loihi neuromorphic hardware. The code was used to produce the paper \"Neuromorphic scaling advantages for energy-efficient random walk computations\" by Smith et al., 2021. It was published in Nature Electronics. \n\nThe software provides code for implementing the discrete time Markov chain random walks on Intel's Loihi Neuromorphic platform. In addition, it provides an example problem through a mini app.", + "laborHours": 1352.8, + "languages": [ + "Python" + ], + "name": "NeuralRW-Loihi: Spiking Discrete Time Markov Chain Simulator for Intel Loihi v", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Neural-Random-Walker", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-26" + }, + "description": "SAND2024-01293O\nThe Code for BALDR Study 07.05 software reproduces results from the BALDR study concerning \"A Semi-Supervised Learning Method to Produce Explainable Radioisotope Proportion Estimates for NaI-based Synthetic and Measured Gamma Spectra.\" \n\nThe code for BALDR Study 07.05 can reproduce a scientific study following the step numbers within the file names. Using synthetic and measured data to find the best model for the radioisotope proportion estimation task of interest, the study generated results for inclusion in a paper. The high-level methods involved are neural networks, semi-supervised learning, and out-of-distribution detection. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python 3.8 - 3.10" + ], + "name": "Code for BALDR Study 07.05 v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/BALDR-Study-07.05", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-20" + }, + "description": "SAND2024-01234O\nTICC is a clustering algorithm that labels a sequence of data points according to numerical properties. This library is a Python implementation of the algorithm described in \"Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data\" (Hallac et al. 2017). It includes documentation, performance improvements, examples, and test coverage. \n\nThis library allows users to automatically segment a series of multivariate data points according to their covariance\u2014that is, the way the values at each data point are changing in relation to one another. This is useful for identifying periods in which a system is behaving. For example, if a sensor is measuring a car's velocity, steering wheel angle, braking and acceleration, TICC can determine when the car was stopped, beginning/exiting a turn, slowing or accelerating at an intersection, or driving on straight or curved roads. TICC can be applied to measure multiple quantities at known times.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "TICC Clustering Library v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fast_ticc", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-20" + }, + "description": "SAND2024-01061O\nThe HiFiPDV-2 software is similar to other photonic Doppler velocimetry (PDV) analysis codes in that it converts signals from intensity-time space to frequency-time space using a short-time Fourier transform (STFT). It then analyzes peaks of the resulting power spectral density information to extract the velocity-time history. \n\nThe unique aspects of HiFiPDV and HiFiPDV-2 are that this reduction process is repeated for an array of reasonable STFT input variables. The resulting population distribution of output velocity-time histories is evaluated to determine the most likely velocity history and its associated uncertainty. This uncertainty is defined as the systematic uncertainty of the PDV signal as it is a function of input values to the reduction process. The HiFiPDV-2 program brings new functionality and efficiency to these calculations\u2014most notably significant reductions in memory usage and calculation times, the ability to evaluate frequency-shifted signals, and the ability to filter out baseline signals. \n\nDevelopers recommend that users have at least 2 GB of RAM per CPU core in their system. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "HiFiPDV2 v. 2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HiFiPDV2", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Behind-the-meter Infrastructure Costs for Electrification Progression (BICEP) model quantifies the behind-the-meter (BTM) electrical upgrades required for decarbonization through electrification by comparing the expected change in capacity requirements from the electrification technologies to the existing capacity in distributed energy resources (DER) stock (including buildings).", + "laborHours": 0.0, + "languages": [], + "name": "Behind-the-meter Infrastructure Costs for Electrification Progression (BICEP) Model", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/BICEP", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-26" + }, + "description": "The codes reproduce the figures of the manuscript entitled \"Shallow Soil Response to a Buried Chemical Explosion with Geophones and Distributed Acoustic Sensing\" submitted to Journal of Geophysical Research - Solid Earth. Geophone data and Distributed acoustic sensing (DAS) data recorded during the Phase II of the The Source Physics Experiment (SPE) along a fiber-optic cable offshore were processed to understand the response of the shallow subsurface to an explosion. This Ground-based Nuclear Detonation Detection (GNDD), Low Yield Nuclear Monitoring (LYNM), and Source Physics Experiment (SPE) research was funded by the National Nuclear Security Administration, Defense Nuclear Nonproliferation Research and Development (NNSA DNN R&D).", + "laborHours": 0.0, + "languages": [], + "name": "Codes for \"Shallow Soil Response to a Buried Chemical Explosion with Geophones and Distributed Acoustic Sensing\" DAG - 01101646", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lviens-LANL/2024_DAG", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "MATLAB code that executes a numerical simulation in the open-source software, SPINACH, which is written for MATLAB. The simulation was used as data in our published paper (https://doi.org/10.1016/j.jmr.2023.107540).", + "laborHours": 0.0, + "languages": [], + "name": "Earth's Field NMR SPINACH Simulation Code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EFNMR_LANL", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "This code analyzes openly available, downscaled climate model output and counts days in a year that are available to conduct prescribed fire based on meteorological prescription data obtained from US land management agencies.", + "laborHours": 0.0, + "languages": [], + "name": "Analysis of prescribed fire days in climate model output", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ajonko/RxFire", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "Following the Open Research requirements for AGU journals, we must release the code used to perform the experiment described in our recent publication, posted at (https://arxiv.org/abs/2312.04722). This code fits a joint emulator to data from a Discrete Fracture Network (DFN) simulation, performed using the open-source software DFNworks (https://dfnworks.lanl.gov/). 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It does not include any files other than python scripts, modules, or notebooks.", + "laborHours": 0.0, + "languages": [], + "name": "Vistransformers Explained", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vision_transformers_explained", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This script is used to read the infinitely growing data files created by a Campbell Data Logger to extract hourly data and\nwrite the content to hourly output files.", + "laborHours": 0.0, + "languages": [], + "name": "MRE-Code-Hub/extract_loggernet", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MRE-Code-Hub/extract_loggernet", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2024-03-26", + "metadataLastUpdated": "2024-03-26" + }, + "description": "This repository provide capabilities to generate multiple process groups within the PyTorch distributed environment. \n\nThe partitions of processes into groups allows to generate multiple independent version of distributed data parallelism (DDP) in order to perform scalable ensemble learning (EL) and hyperparameter optimization (HPO).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "MultiDistTorch: Generation of multiple processes groups within PyTorch distributed environments for hierarchical parallelization", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/MultiDistTorch", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "gunaratnecs@ornl.gov" + }, + "date": { + "created": "2024-03-27", + "metadataLastUpdated": "2024-03-27" + }, + "description": "SAGESim: Scalable Agent-based GPU-Enabled Simulator is a distributed GPU agent-based modeling framework in Python. 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Users will be able to apply these equations to characterize different components of complex systems based on available data. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "A python package for analyzing Resilience of Complex Systems (pyRoCS) v.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyrocs", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0" + }, + { + "contact": { + "email": "krawczukpn@ornl.gov" + }, + "date": { + "created": "2024-03-28", + "metadataLastUpdated": "2024-03-28" + }, + "description": "BARDI: Batch-processing Abstraction for Raw Data Integration", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "BARDI", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DOE-NCI-MOSSAIC/bardi", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.3.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-01", + "metadataLastUpdated": "2024-04-11" + }, + "description": "This repository contains python scripts and numerical data accompanying the paper:\n\"Leveraging Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning,\" Tyler Chang, Andrew Gillette, Romit Maulik, 2024. The following subdirectories are included:\n- \"interpolants\" contains our interpolation scripts used for all studies\n- \"experiments\" contains scripts demonstrating our experiments with synthetic data\n- \"airfoil\" contains scripts demonstrating our experiments with the publicly available UIUC airfoil dataset. Further instructions are provided in READMEs within the sub-directories.", + "laborHours": 0.0, + "languages": [], + "name": "Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/interpML", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-01", + "metadataLastUpdated": "2024-04-01" + }, + "description": "This code performs estimation of a mixture model involving heterogeneous data types. The resulting\nmodel can be used to calculate likelihoods of underlying model components.", + "laborHours": 273.6, + "languages": [], + "name": "Heterogeneous Data Type Mixture Model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/alankaplan/HDTMM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-01", + "metadataLastUpdated": "2024-06-28" + }, + "description": "The Differential Equation System Solver (DESS) is a Rust crate implementing fixed-step and adaptive-step solvers and designed especially for modeling physical systems. 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In addition to allowing users to directly input equations to solve, DESS allows users to optionally specify and define relationships between nodes in their system, which the package then translates into a system of equations via the Rust macro system, leading to simpler and more intuitive code.", + "laborHours": 5791.2, + "languages": [ + "Rust", + "Python" + ], + "name": "DESS (Differential Equation System Solver) [SWR-24-48]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/de-system-solver", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "OpenEDI - System Integration (OEDI-SI) - PNNL Distributed Optimal Power Flow (DOPF)", + "laborHours": 3404.8, + "languages": [], + "name": "pnnl/oedisi_dopf", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/oedisi_dopf", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software implements an algorithm for finding triplets of hyperedges with specified size relations. 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The simulator is engineered to analyze the impact of various system configurations and erasure coding policies on system durability and network overhead. It supports a comprehensive range of parameters including disk capacity, disk I/O bandwidth, failure rates, network bandwidth, and system scale, accommodating various erasure coding approaches such as Single-Level Erasure Coding (SLEC), Multi-Level Erasure Coding (MLEC), and Local Reconstruction Codes (LRC).\n\nMLEC-Sim provides support for multiple chunk placement policies, including clustered parity and declustered parity, and encompasses a variety of repair methods like Repair-ALL, Repair-FCO, Repair-HYB, and Repair-MIN. It is capable of simulating disk failures through a variety of means, including distribution-based or trace-based mechanisms, and can handle complex multi-level (de)clustered placements and repair processes.\n\nA key feature of MLEC-Sim is its adoption of the splitting simulation method for evaluating system durabilities at extremely high levels, which are challenging to assess with traditional simulation approaches. This feature allows for a detailed evaluation of system resilience under a range of conditions, aiding in the selection of appropriate erasure coding solutions for enhancing system durability.\n\nMLEC-Sim contributes to the field of data storage and reliability by providing a tool for the detailed evaluation of the durability and efficiency of erasure coding configurations, intended for use by researchers and practitioners in the design and optimization of storage systems.", + "laborHours": 15078.4, + "languages": [ + "Python" + ], + "name": "MLEC-Sim: A Simulator for Evaluating Multi-Level Erasure Coding", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ucare-uchicago/mlec-sim/blob/main/LICENSE.rtf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ucare-uchicago/mlec-sim", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-04", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The invention was developed to solve the problem of representing all systems biology knowledge about an organism in one database.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl-predictive-phenomics/concerto v2.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/Concerto", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "2.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-04", + "metadataLastUpdated": "2024-04-16" + }, + "description": "REST2 is the high-performance solar radiation model for cloudless-sky irradiance, illuminance, and photosynthetically active radiation.", + "laborHours": 288.8, + "languages": [ + "Python" + ], + "name": "REST2 [SWR-23-96]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rest2", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-04", + "metadataLastUpdated": "2024-04-04" + }, + "description": "The National Renewable Energy Laboratory (NREL) has developed a data acquisition system to support laboratory (component) and in-water validation and testing of Marine Renewable Energy (MRE) technologies. The Modular Ocean Data AcQuisition System (MODAQ) is a robust system built on industrial grade hardware that can acquire high-quality and summary data from many sensor and instrument types. MODAQ includes modules to perform real-time QC screening, system health monitoring, and send alerts. MODAQ is also part of a larger data management, processing, visualization, and archiving system.", + "laborHours": 16917.6, + "languages": [ + "HTML", + "LabVIEW", + "SaltStack", + "JavaScript" + ], + "name": "MODAQ (Modular Offshore Data Acquisition System) [SWR-24-58]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MODAQ", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "HNS Rigid Body Simulatoris a tool for performing rigid-body dynamics simulations of nanoscale systems (e.g., macromolecular\nassemblies) in Python.", + "laborHours": 988.0, + "languages": [], + "name": "pnnl/HNSRigidBodySimulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/HNSRigidBodySimulator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The software manages a database of historical hydrology and power systems operations data and based on some newly developed algorithms helps generate and\ntranslate historical hydrology data into estimations of steady-state and dynamic model parameters based on user inputs of hydro conditions which can be imported to\nexisting power system simulators.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Hydropower Modeling Gap Tools", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-04-25" + }, + "description": "This package implements a data store for components and time series in support of Python-based modeling packages. While it is designed to support teams modeling transmission and distribution systems for electrical grids, it can be used by any package that needs to store components (e.g., generators and buses) that have quantities (e.g., power and voltage) which may vary over time.\n\nThe package was inspired by InfrastructureSystems.jl (https://github.com/NREL-Sienna/InfrastructureSystems.jl).", + "laborHours": 2021.6, + "languages": [ + "Python" + ], + "name": "InfraSys (Infrastructure Systems) [SWR-24-42]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/infrasys", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.0.3" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-04-25" + }, + "description": "Grid Data Models (GDM) is a collection of pydantic data models for power distribution and transmission system components. These data models can be easily serialized and deserialized. GDM provides a standard interface for accessing power system component data with built in validation.\n\nSee also: https://pypi.org/project/grid-data-models/", + "laborHours": 1976.0, + "languages": [ + "Python" + ], + "name": "GDM (Grid Data Models) [SWR-24-31]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-Distribution-Suites/grid-data-models", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.1.2" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-07-19" + }, + "description": "This is a vehicular networking simulator designed to enable synchronized network simulation with vehicle traffic simulation software. The communications model is based on the 3GPP LTE-V2X Mode 4 protocol, but includes several other wireless network protocol models as well. This simulator includes both a V2X network simulation implemented in ns-3 as well as an interface to automatically configure, run, and interact with a set of ns-3 instances based on network size and available hardware. This software has been tested with Aimsun NEXT 2.0 simulator (with V2X SDK), but uses a generic interface for compatibility with any comparable vehicle traffic simulator across the HELICS co-simulation framework. This software is intended as a generalized extension to vehicle traffic simulation, and does not model any vehicle traffic on its own.", + "laborHours": 755713.6, + "languages": [ + "C++", + "Python" + ], + "name": "N-S3 Cellular Vehicle-to-Everything (C-V2X) Cosimulation Framework [SWR-24-54]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NS3-C-V2X-Cosimulation-Framework", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-04-10", + "metadataLastUpdated": "2024-04-10" + }, + "description": "Context-Aware Language Model for Science (CALMS) is designed to assist scientists with instrument operations and complex experimentation. CALMS consists of a large-language model (LLM) augmented with context and tool use abilities. With the ability to retrieve relevant information from facility documentation, CALMS can answer simple questions on scientific capabilities and other operational procedures. With the ability to interface with software tools and experimental hardware, CALMS can operate scientific instruments in a conversational manner.", + "laborHours": 67427.2, + "languages": [], + "name": "CALMS: CONTEXT-AWARE LANGUAGE MODEL FOR SCIENCE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mcherukara/CALMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-11", + "metadataLastUpdated": "2024-04-11" + }, + "description": "A workflow is a series of dependent computations which are executed to\nyield an experimental result, much like sheet music describes a musical\nperformance. Dynamic workflows are like improvisational jazz, in which\nthe musicians create unique, situation-driven, collaborative variations\non themes. Dynamic workflows can potentially yield better results, save\ncomputation, and/or save human decision-making effort versus pre-specified\nor manual workflows, as they need not run the exhaustive set of studies\nwhich might be required in a pre-specified set, and they make their own\nexperimental design decisions at run time. If you have an existing\nMaestro study where you would like to save computation and/or human time,\nImprov is for you.\nImprov provides core capabilities for creating a simple, hierarchical structure over Maestro studies,\nallowing you to connect ``experimental'' Maestro strudies with decision-making code to select parameters\nand run corresponding studies.", + "laborHours": 2492.8, + "languages": [], + "name": "Improv Dynamic Workflows", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/improvwf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-11", + "metadataLastUpdated": "2024-04-11" + }, + "description": "Train and use machine learning models; select protein sequences for simulation and laboratory testing.\nCode implements key decision steps in this process. Provided for review purposes and public release.", + "laborHours": 2736.0, + "languages": [], + "name": "Review materials for Computationally Restoring the Potency of a Clinical Antibody", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CRPCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "v2" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-15", + "metadataLastUpdated": "2024-04-15" + }, + "description": "A python package that helps with working with MSI Windows installers, by providing a library and utilities\nto read information from the file, extract embedded files, and update/write MSI files. Functionality is\nsimilar to https://wiki.gnome.org/msitools and https://github.com/mdsteele/rust-msi but written in pure\nPython so that it can easily be installed and used on a wider variety of systems.", + "laborHours": 288.8, + "languages": [], + "name": "PyMSI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nightlark/pymsi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.0" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-04-15", + "metadataLastUpdated": "2024-04-15" + }, + "description": "This tool, the Non-Powered Dam Hydropower Development and Ranking Opportunity Tool (NPD HYDRO), allows users to prioritize or rank NPD sites for future development based on user-defined priorities. Benefits can be evaluated in several categories: the grid, community, industry, and environment (represented by the GCIE impact scores in the tool. In addition, the tool provides the user with a qualitative measure for the feasibility of adding energy storage during NPD conversion, specifically battery, hydrogen electrolysis, and pumped-storage hydropower (PSH). By taking a holistic approach to the potential range of benefits provided by NPD conversions with results tailored to the user\u2019s priorities, NPD HYDRO provides the opportunity for national-level screening and enables users to focus on the sites that are most closely aligned with their interests.", + "laborHours": 4696.8, + "languages": [ + "Python" + ], + "name": "NPD Hydro", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/NPD_Hydro", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "stipekcw@ornl.gov" + }, + "date": { + "created": "2024-04-16", + "metadataLastUpdated": "2024-04-16" + }, + "description": "This project's goal is to ingest morphology features (2D) and infer height (3D) for individual buildings:\n\nThe following breaks the vivald process into the respective steps\nIdentify 2D buildings from AOI\nGenerate morphology features using the Gauntlet feature morphology process\nPlease see Clinton Stipek for availability of Gauntlet features\nRun a recursive feature eliminator to streamline modelling process\nHyper-tune parameters via bayesian optimization\nInfer building heights at a building-by-building level leveraging a XGBoost algorithm", + "laborHours": 136.8, + "languages": [ + "Python" + ], + "name": "vivaldi", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/stipekcw/vivaldi/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stipekcw/vivaldi", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v0.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-17", + "metadataLastUpdated": "2024-04-17" + }, + "description": "SSAPy is a python package allowing for fast and precise orbital modeling. SSAPy is designed with speed\nand accuracy in mind and offers the following capabilities:\n- A variety of integrators, including Runge-Kutta, SciPy, SGP4, etc.\n- Customizable force propagation models, including a variety of Earth gravity models, lunar gravity,\nradiation pressure, etc.\n- Multiple-hypothesis tracking (MHT) UCT linker\n- Vectorized computations\n- Short arc probabilistic orbit determination\n- Conjunction probability estimation\n- Uncertainty quantification\n- Monte Carlo data fusion\n- Support for multiple coordinate frames (with coordinate frame conversions)", + "laborHours": 6976.8, + "languages": [], + "name": "Space Situational Awareness for Python", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SSAPy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-05-03" + }, + "description": "Ring Pull Strain Analysis (RPSA) is a framework for analysis of Digital Image Correlation (DIC) data of gaugeless ring pull testing. It is meant for analysis of rings cut from tube cross sections and pulled in a displacement-controlled tensile test. This code takes load frame data, images take during testing, and csv files from the DIC analysis of those images and allows the user to analyze and plot data from the test. Some important features of the software include getting the strain values as a function of radial distance and angle, plotting of the strain around the ring, and stress-strain analysis of the load frame\ndata. Additional capability is included with Ring Pull Coating Analysis (RPCA, also part of the software). Additional images are taken of samples with an outer coating and are used to correlate failure of the coating with strain values measured with DIC.", + "laborHours": 0.0, + "languages": [], + "name": "Ring Pull Strain Analysis", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/RingPullStrainAnalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "1.1" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-22" + }, + "description": "The Memento Proxy software transforms Invenio systems on the web into repositories that are compliant with the Memento protocol.", + "laborHours": 425.6, + "languages": [], + "name": "InvenioRDM Memento Proxy", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/invenio-memento-proxy", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "NRAP-Open-IAM is an open-source software product that enables quantification of containment effectiveness and leakage risk at storage sites in the context of system uncertainties and variability.", + "laborHours": 114197.6, + "languages": [], + "name": "LANL Contribution to NRAP-Open-IAM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NRAP/OpenIAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "The ThunderBoltz application programming interface (API) code is written in Python and is comprised of a set of tools to facilitate compilation of the ThunderBoltz code, as well as fast assembly and formatting of input files for the ThunderBoltz code, post-processing tools of ThunderBoltz results, plotting tools, and runs/schedules the ThunderBoltz code executable for calculations. The ThunderBoltz API code is utilized for importing and manipulating input cross section sets, input conditions, and any other simulation settings made available within the ThunderBoltz input deck via user-defined settings or via automatic generation. The API comes with a set of plotting capabilities of input cross sections, results from ThunderBoltz, and post-processed results carried out with the API.", + "laborHours": 5502.4, + "languages": [], + "name": "ThunderBoltz API", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ThunderBoltz", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "Supports characterization of explosive events by providing estimates of device parameters such as yield, height of burst/depth of burial, geolocation, and event time with uncertainty quantification.", + "laborHours": 16932.8, + "languages": [], + "name": "MultiPEM Toolbox", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MultiPEM_Toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "Minervachem is a tool for cheminformatics and machine learning in chemistry. It includes both algorithms from existing literature and algorithms which we have developed. Its features center around two main themes: molecular representations and algorithms, both for molecular machine learning. It provides a scikit-learn transformer interface for molecular featurization and an estimator interface for machine learning algorithms. It also provides visualization tools for explaining machine learning predictions. We aim to continue developing this software to improve its performance and usability and expand its capabilities within the realm of molecular machine learning, cheminformatics, and visualization.", + "laborHours": 1398.4, + "languages": [], + "name": "minervachem", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/minervachem", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "HERMES - High-speed Event Retrieval and Management for Enhanced Spectral imaging code. \nThis code is meant to unpack and process neutron imaging data from the TPX3Cam made by Amsterdam Scientific Instruments. The TPX3Cam utilizes the Timepix3 chip in a single photon counting mode of image acquisition. The photon counting data streaming off the TPX3Cam needs to be process and analyzed in order to create final images. Therefore we are developing both python and cpp codes to allow for users of the TPX3Cam to efficiently analyze data and create images.", + "laborHours": 1261.6, + "languages": [], + "name": "HERMES", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/hermes", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-22", + "metadataLastUpdated": "2024-04-22" + }, + "description": "ExaDiS, or Exascale Dislocation Simulator, is a set of software modules written to enable numerical\nsimulations of large groups of moving and interacting dislocations, line defects in crystals responsible for\ncrystal plasticity. By tracking time evolution of sufficiently large dislocation ensembles, ExaDiS predicts\nplasticity response and plastic strength of crystalline materials. ExaDiS is built around a library of core\nfunctions for Discrete Dislocation Dynamics method specifically written to perform efficient computations\non GPUs.", + "laborHours": 8040.8, + "languages": [], + "name": "Exascale Dislocation Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/exadis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-24", + "metadataLastUpdated": "2024-04-25" + }, + "description": "The National Solar Radiation Database (NSRDB) is NREL\u2019s flagship solar data resource. With over 20 years of high-resolution surface irradiance data covering most of the western hemisphere, the NSRDB is a crucial public data asset. A fundamental input to accurate surface irradiance in the NSRDB is high quality cloud property data. Cloud properties are used in radiative transfer calculations and are sourced from satellite imagery. Improving the accuracy of cloud property inputs is a tractable method for improving the accuracy of the irradiance data in the NSRDB. For example, in July of 2018, an average location in the Continental United States is missing cloud property data for nearly one quarter of all daylight cloudy timesteps. This project aims to improve the cloud data inputs to the NSRDB by using machine learning techniques to exploit the NSRDB\u2019s massive data resources. More accurate cloud property input data will yield more accurate surface irradiance data in the NSRDB, providing direct benefit to researchers at NREL and to public data users everywhere.", + "laborHours": 1626.4, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "MLClouds [SWR-24-24]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mlclouds", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "huettelmr@ornl.gov" + }, + "date": { + "created": "2024-04-26", + "metadataLastUpdated": "2024-04-26" + }, + "description": "Systemd Snapshot is a static analysis tool for Linux systems that use systemd. It aims to enumerate, aggregate, and investigate systemd services without requiring an operational system. The tool produces a set of JSON files that consolidates not only systemd information, but additional forensic information associated with systemd artifacts. A graph is also produced based on the relationships and ordering defined in systemd unit files and the binaries they specify.", + "laborHours": 0.0, + "languages": [], + "name": "Systemd Snapshot", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/Systemd_Snapshot", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-26", + "metadataLastUpdated": "2024-04-26" + }, + "description": "This software provides a data-driven approach for efficiently identifying high impedance faults (HIFs) in distribution systems. To tackle the nonlinearity of the voltage current trajectory of HIFs, we first formulate linear least squares problems to approximate the trajectory with piecewise functions. Then we collect the function features of all segments as inputs and use the support vector machine approach to efficiently identify HIFs at different locations.", + "laborHours": 60.8, + "languages": [ + "Python" + ], + "name": "A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems [SWR-24-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openEDI/oedisi-hif-identification", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-04-26", + "metadataLastUpdated": "2024-04-26" + }, + "description": "ComStock\u2122 is an NREL model of the U.S. commercial building stock. The model takes some building characteristics from the U.S. Department of Energy's (DOE's) Commercial Prototype Building Models and Commercial Reference Building. However, unlike many other building stock models, ComStock also combines these with a variety of additional public- and private-sector data sets. Collectively, this information provides high-fidelity building stock representation with a realistic diversity of building characteristics.\n\nThis repository contains the source code used to build and execute ComStock models, including upgrade scenarios. In addition, the sampling of buildings characteristics used for the initial ComStock (V1.0) release is provided. The ComStock model is under active calibration and development, which is publicly visible on this repository.\n\nExecution of the ComStock workflow is managed through the buildstockbatch repository, a shared asset of ResStock\u2122 and ComStock\u2122 , specifically developed to scale to execution of tens of millions of simulations through multiple infrastructure providers.\n\nThe dataset output from the initial ComStock (V1.0) release can be found at the accompanying ComStock data viewer website and additional information about ComStock found on the NREL Buildings Website. For more details about ongoing model development please consult the End Use Load Profiles website.\n\nComStock is a direct result of the NREL residential stock modeling tool ResStock\u2122 (recipient of a R&D100 award) and was inspired by the high-fidelity solar & storage adoption model dGen\u2122. Additionally, this tool would not be possible without the decades of work undertaken by the OpenStudio\u00ae and EnergyPlus\u00ae visionaries and contributors, significant funding, feedback and support from the Los Angeles Department of Water and Power, and the Department of Energy's Building Technology Office ongoing support of and investment in building energy modeling software.\n\n is an analytic methodology for modeling the energy usage of the commercial building stock within the United States of America. The commercial building stock is represented through a sampling of complex probabilistic distributions of various features of interest for modeling energy usage within commercial buildings. Each sample from these distributions is converted into a building energy model based on the features of that specific sample. Each building energy model can be simulated as is, but additional changes can be made to the model through addition of energy conservation measures, component faults, or other desired alterations. The results of the simulations are then processed to provide insights for various stakeholders, including but not limited to policy makers, engineers, and marketers.", + "laborHours": 0.0, + "languages": [ + "Python", + "Ruby" + ], + "name": "ComStock\u2122 2024 Release 1 [SWR-19-33 and SWR-20-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ComStock", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2024 Release 1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-04-26", + "metadataLastUpdated": "2024-04-26" + }, + "description": "The ResStock\u2122 analysis tool was built on NREL's OpenStudio\u00ae platform, and is a project geared at modeling existing residential building stocks at national, regional, or local scales with a high-degree of granularity (e.g., one physics-based simulation model for every 200 dwelling units), using the EnergyPlus\u00ae simulation engine. Information about ComStock\u2122, a sister tool for modeling the commercial building stock, can be found here: https://www.nrel.gov/buildings/comstock.html\nThis repository contains:\nHousing characteristics of the U.S. residential building stock, in the form of conditional probability distributions stored as tab-separated value (.tsv) files. Comments at the bottom of each file document data sources and assumptions for each.\nA library of housing characteristic \"options\" that translate high-level characteristic parameters into arguments for OpenStudio measures, and which are referenced by the housing characteristic .tsv files and building energy upgrades defined in project definition files\nProject definition files:\nv2.3.0 and later: buildstockbatch YML files openable in any text editor\nv2.2.5 and prior: Project folder openable in PAT\nUnit-level OpenStudio Measures for automatically constructing OpenStudio Models of each representative dwelling unit model:\nv3.0.0 and later: OpenStudio-HPXML Measures\nv2.5.0 and prior: OpenStudio Measures\nHigher-level OpenStudio Measures for controlling simulation inputs and outputs\nThis repository does not contain software for running ResStock simulations, which can be found as follows:\n\nVersions 2.3.0 and later only support the use of buildstockbatch for deploying simulations on high-performance or cloud computing. Version 2.3.0 also removed separate projects for single-family detached and multifamily buildings, in lieu of a combined project_national representing the U.S. residential building stock. See the changelog for more details.\nVersions 2.2.5 and prior support the use of the publicly available OpenStudio-PAT software as an interface for deploying simulations on cloud computing. Read the documentation for v2.2.5.", + "laborHours": 2638370.4, + "languages": [ + "Python", + "Ruby" + ], + "name": "ResStock\u2122 v3.2.0 [SWR-19-15 and SWR-20-07]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/resstock/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/resstock", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.2.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-29", + "metadataLastUpdated": "2024-04-29" + }, + "description": "This code solves for the one-dimensional concentration and temperature distribution within a carbon\ncapture column using a homogenized absorber model. These solutions are compared to experimental\ndata.", + "laborHours": 927.2, + "languages": [], + "name": "DynamicSimCCS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DynamicSimCCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.01" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-04-30", + "metadataLastUpdated": "2024-04-30" + }, + "description": "Parsnip has three parts. The first part is the front-end user experience. The front end will be a graphical representation of the intermediate language. Once a user is satisfied with the information on the front end, Parsnip translates the data from the visual application into the second part of Parsnip - the intermediate language. More advanced users may skip the front end and generate their own intermediate language files. The final part is the backend which takes the intermediate language files and generates Zeek and Spicy code.\nParsnip will not completely replace parser developers. Many protocols have unique challenges requiring manual effort; however, the goal of Parsnip is to automate at least 90% of the development that largely consists of repetitive tasks. Parsnip output will compile a functioning parser but may not include all PDU types or parse all data.", + "laborHours": 5973.6, + "languages": [ + "JavaScript", + "Python", + "Jinja2" + ], + "name": "Parsnip Parser Creation Application", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cisagov/parsnip", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Identification and zonal classification of the faults is a decisive factor in the relay\u2019s decision to trip or not. Different types of\nfault like three-phase, line-to-line-to-ground and single-line-to-ground can occur at various locations in the feeder. These\nfaults are seen as the variation in the instantaneous values of three-phase voltages and currents, i.e., waveforms, that are\nmeasured at the relay location. The objective of this work is to develop a machine learning model that can\nidentify a fault and classify it to various protection zones based on measured waveforms. In this work, a data-driven relay\nbased on Convolutional Neural Network (CNN) is proposed for fault identification in distribution feeders with high\npenetration solar PV. The proposed CNN model takes local current and voltage waveforms as input and classify it into\nfault, no-fault or a capacitor switching. Further, the CNN also attempts to identify fault zones based on the images of\nwaveforms. The overall testing accuracy of the trained model exceeds 95%.", + "laborHours": 60.8, + "languages": [], + "name": "Convolution Neural Network for Fault Identification in Distribution Feeder with High Penetration Solar PV", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/DPVCNN", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-05-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a dashboard for exploring the results of machine learning models for predicting molecular properties from\nmolecular structure. It includes tools for:\n1. Modifying molecules to observe the change in predicted properties\n2. Exploring the relationship between molecular structure and predicted properties\n3. Recommending structurally similar molecules with improved properties\n4. Exploring the impact of data subsampling on model performance metrics", + "laborHours": 532.0, + "languages": [], + "name": "Dashboard for Visualizing Molecular Property Prediction Machine Learning Results", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mol-ml-dashboard", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-05-02", + "metadataLastUpdated": "2024-05-02" + }, + "description": "The Wind-Plant Integrated System Design and Engineering Model (WISDEM\u00ae) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM\u00ae is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM\u00ae turbine design capability. Please install all of the pre-requisites prior to installing WISDEM\u00ae by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM\u00ae development, please visit the official NREL systems engineering for wind energy website. https://www.nrel.gov/wind/systems-engineering.html", + "laborHours": 229778.4, + "languages": [ + "C", + "Fortran", + "Python" + ], + "name": "WISDEM\u00ae v3.15.2 2024 (Wind-Plant Integrated System Design and Engineering Model) [SWR-14-05]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/WISDEM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.15.2" + }, + { + "contact": { + "email": "degrawjw@ornl.gov" + }, + "date": { + "created": "2024-05-06", + "metadataLastUpdated": "2024-10-01" + }, + "description": "hippogryph is a Python package for the generation of multiblock structured grids with the grid locations determined by a mapping. A structured grid is a grid for which there is a relationship between the physical space coordinates x, y, and z and three indices i, j, and k and a multiblock grid is constructed from a set of subgrids (\"blocks\"). A \"mapped\" grid is a grid for which there is a transformation f such that the nodal locations are determined by applying this mapping to the indices: (x, y, z) = f(i, j, k). While it is possible to represent most structured grids in this form, the focus here is on mappings that are known beforehand and not computed using the numerical calculations that are commonly used within the field of numerical grid generation. The grid is first constructed in index space using primitive shapes, and then the physical space grid is constructed from the mapping, usually a tensor-product type mapping where x=f(i), y=f(j), and z=f(k), though more mappings may be added in the future. hippogryph can read and write grids in the structured Plot3D format as well as the unstructured Exodus II format.", + "laborHours": 5274.4, + "languages": [ + "Python" + ], + "name": "hippogryph", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jasondegraw/hippogryph", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-05-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "CIMantic Graphs (aka CIM-Graph) is a new python library developed by PNNL to reduce the burden of working with the\nCommon Information Model. CIMantic Graphs takes a novel approach of building in-memory labeled property graphs for\ncreating, parsing, and editing CIM power system models.", + "laborHours": 38729.6, + "languages": [], + "name": "CIMantic Graphs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CIM-Tools/CIM-Graph", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2024-05-09", + "metadataLastUpdated": "2024-05-09" + }, + "description": "This software is for an application, designed for phones and/or tablets, to assist microbiome researchers collecting samples in the field to also collect metadata in a standardized and systematic way. The type of samples covered would be e.g. soil sample from a forest, sediment sample from a lake, or water sample in the ocean. The app allows users to collect sample information and metadata in an easy and intuitive way, and connects to the NMDC submission portal (https://data.microbiomedata.org/submission/home) a website from where users can review the samples they collected and add more information if necessary.", + "laborHours": 19076.0, + "languages": [], + "name": "NMDC Field Notes Phone Application (NMDC Field Notes) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/microbiomedata/nmdc-field-notes", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2024-05-09", + "metadataLastUpdated": "2024-05-15" + }, + "description": "EOS7MG is a new TOUGH3 module for modeling water, brine, and multiple gas mixtures in the subsurface multiphase flow system. The module allows mixture of as more as three gas components selecting from a list of predefined gases (CH4, C2H6, C3H8, H2S, CO2, N2, NO2, H2, and AIR). EOS7MG was developed based on EOS7C and inherited the general modeling capabilities of the TOUGH3 platform. It uses cubic equation of states for gas density, viscosity, and enthalpy calculation. The module provides the selection options for Peng-Robinson, Redlich-Kwong, or Soave-Redlich-Kwong equations of state. The subsurface flow and transport of gas and aqueous phase mixtures over a wide range of pressures and temperatures is modeled with a multiphase Darcy's Law and an accurate chemical equilibrium approach as originally implemented in EOS7C is used for calculation of the solubilities of different mass components. EOS7MG was designed to allow flexible number of components based on the number of gases included in the model. The potential application of this module may include subsurface gas storage, energy storage, CCS, enhanced gas recovery, and more.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 36039.2, + "languages": [], + "name": "TOUGH3/EOS7MG (EOS7MG) v1.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://marketplace.lbl.gov/tough", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-05-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A multi-modal few-shot learning approach is used to identify similarities between particles obtained from environmental samples. The inferred similarities are then used in a similarity graph to identify groupings and outliers in the sample", + "laborHours": 668.8, + "languages": [], + "name": "FLAMINGo: Few shot Learning Analysis of Multi-modal Inference Network Graphs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/particlefsl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "femtotime is a library for time tracking which uses 128 bit integers\nto allow tracking time with femtosecond resolution.\n\nThe API takes the form of a C++ class GPStime, which allows setting,\ngetting, manipulation, and conversion of time. The conversion to and\nfrom UTC tracks leapseconds.", + "laborHours": 1033.6, + "languages": [], + "name": "femtotime", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/femtotime", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "Tensor ELF is a user-friendly parallel tensor decomposition Python toolbox that includes a suite of machine learning algorithms for CPU and GPU architectures for the analysis of sparse and dense data including utility tools for pre-processing and post-processing.", + "laborHours": 32756.0, + "languages": [], + "name": "Tensor Extraction of Latent Features (TELF)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/T-ELF", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "ASAUM is a C++ library for representing distributed, multi-block structed and unstructured meshes. The library is meant to provide users with the ability to read/write, partition, and query the large distributed meshes that are commonly used in scientific computing.", + "laborHours": 14926.4, + "languages": [], + "name": "ASAUM--Adaptive Structured and Unstructured Mesh", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ASAUM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "Allows the user to fit a classical event categorization matrix (ECM) model, and a novel Bayesian event categorization matrix model, both of which are used for nuclear detonation detection.", + "laborHours": 1276.8, + "languages": [], + "name": "ezECM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/skoermer-LANL/ezECM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "Code for my PhD thesis that creates meshes using gmsh and code I wrote to create high-order hybrid meshes to use for testing a hybrid method between spectral element method and generalized finite differences. It also uses a tetrahedral mesh improvement method called \"stellar\" to improve mesh quality near a curved boundary.", + "laborHours": 1900.0, + "languages": [], + "name": "mgsflib", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Jacobj-LANL/mgsflib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "The software is a set of test problems for nonlinear optimization algorithms, including subroutines such as linear algebra routines and automatic differentiation algorithms. The test problems come from chemical engineering open literature, and describe optimization tasks related to the design and operation of processes such as carbon capture, Hydrogen production, heat exchange, and distillation.", + "laborHours": 167.2, + "languages": [], + "name": "A set of test problems for nonlinear optimization", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Robbybp/pselib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "It is a machine learning code written in python. The code is an inherent part of a paper (#LA-UR-24-22420). The code is required to be available on github as a part of paper submission process in the journal.", + "laborHours": 1079.2, + "languages": [], + "name": "Conditional latent autoregressive recurrent model (CLARM)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/clarm", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "Hop-Decorate is a python code developed as part of the LDRD funded project: 20220063DR: Accelerated Dynamics Across Computational and Physical Scales with the aim of using molecular dynamics and statics techniques to generate atomistic databases of defect transport in chemically complex materials using automated energy barrier calculations.", + "laborHours": 1109.6, + "languages": [], + "name": "Hop Decorate", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Hop-Decorate", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "RIDDL is a suite of software tools that enable AI/ML analysis of infrasound data. Methods and capabilities include construction, evaluation, and application of models for infrasound signal analysis, construction of synthetic data useful for construction and evaluation, as well as various other advanced data science tools enabling infrasound signal detection and categorization as well as downstream analysis methods such as localization and characterization of detected sources.", + "laborHours": 760.0, + "languages": [], + "name": "Robust Infrasound Detection via Deep Learning (RIDDL)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Seismoacoustics/riddl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "HPSim is a GPU-accelerated online multi-particle beam dynamics simulation tool for ion linacs. It was originally developed for use on the Los Alamos 800-MeV proton linac with the goal of providing a fast and accurate tool for realistic beam simulations of the actual operating linac. It runs on a GPU equipped workstation. The simulation parameters mirror those of the actual accelerator and can be manipulated through Python scripts in an offline mode or track them\nwhen connected via EPICS in an online mode.", + "laborHours": 33272.8, + "languages": [], + "name": "High Performance Simulator (HPSim", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/enchuanhuang/hpsim", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-22" + }, + "description": "DiscoFluxM is software for modeling the deformation behavior of crystalline materials within the third-party finite-element based software, MOOSE. The software enables full-field crystal plasticity finite element simulations of deformation processes of metals and other crystalline materials. DiscoFluxM is an implementation of the DiscoFlux theoretical and algorithmic framework for coupling single-crystal plasticity with dislocation transport. The \ncontinuum mesoscale modeling framework is founded upon a nonlocal dislocation-density based crystal plasticity theory. The nonlocal theory couples continuum dislocation transport with an otherwise spatially-local single-crystal model employing nonlinear thermoelasticity and crystallographic plasticity. Dislocation transport is modeled by enforcing dislocation conservation at a slip-system level through the solution of advection-diffusion equations. The configuration of geometrically necessary dislocation density gives rise to a back-stress that inhibits or accentuates the flow of dislocations.", + "laborHours": 1778.4, + "languages": [], + "name": "DiscoFluxM version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/subhendu-LANL/DiscoFluxM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "The Pipeline Hydrogen Decarbonization and Repurposing Analyzers (P-HyDRAs) are a set of prototype computational tools for simulating and optimizing midstream natural gas pipeline system operations subject to location and time-dependent hydrogen blending. 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The outputs are time-series data that provide a predictive simulation of gas flows, mass fractions, and pressures, or with additional degrees of freedom give an approximately optimal solution for gas injections/withdrawals, compressor settings, and sensitivities to the objective function that provide locational values of energy.", + "laborHours": 5198.4, + "languages": [], + "name": "Pipeline Hydrogen Decarbonization and Repurposing Analyzers (P-HyDRAs)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/phydras", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gureckywl@ornl.gov" + }, + "date": { + "created": "2024-05-21", + "metadataLastUpdated": "2024-05-21" + }, + "description": "The CORRLA-RS package provides a suite of statistical methods for sampling multidimensional distributions and to conduct sensitivity and correlation analysis of large scale data in the Rust programming language. The software provides a unique solution to multidimensional constrained sampling problems utilizing a combination of parallelized Markov Chain Monte Carlo methods and traditional rejection sampling. The sensitivity and correlation analysis methods are backed by a high performance randomized singular value decomposition implementation which enables datasets larger than the random access memory (RAM) size to be analyzed. Additionally, CORRLA-RS implements the active subspace identification method using a KD-Tree and the randomized singular value decomposition acting in concert.", + "laborHours": 1824.0, + "languages": [ + "Rust" + ], + "name": "CORRLA-RS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wgurecky/CORRLA_RS", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-05-21", + "metadataLastUpdated": "2024-05-21" + }, + "description": "Ingest is an application that allows project owners to solicit data from users and require them to fill out metadata along with those uploads. It is an application developed in Elixir/Phoenix and is a web based platform.", + "laborHours": 11491.2, + "languages": [ + "Elixir", + "Erlang" + ], + "name": "Ingest", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Ingest", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-05-23", + "metadataLastUpdated": "2024-09-25" + }, + "description": "The Transient Fault Detection Algorithm (TFDA) is an algorithm to detect the non-fault and transient fault conditions, and classify the fault types. This is part of OEDI-SI project (https://data.openei.org/search?q=oedi%20si).", + "laborHours": 45.6, + "languages": [ + "Python" + ], + "name": "TFDA (Transient Fault Detection Algorithm) [SWR-24-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Transient-Fault-Detection", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-05-28", + "metadataLastUpdated": "2024-05-28" + }, + "description": "This code allows us to generate a model to predict ground state electron densities directly from atomic\nstructure thereby bypassing the need to perform direct DFT calculations. It is based on many body\ncorrelation descriptors defined in https://arxiv.org/abs/2004.14442 (IM release numbers: LLNL-JRNL-\n808791 and LLNL-JRNL-840698). The code reads in electron densities, in CHGCAR format used by the\nDFT code VASP, calculates many-body correlation descriptors based on atoms surrounding a grid point\nand then uses linear regression to obtain the fitting parameters.", + "laborHours": 2508.0, + "languages": [], + "name": "Interpretable, Extensible Linear Regression Model for Electron Density Prediction", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gopal-iyer/interpretable_ML_charge_density", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-05-28", + "metadataLastUpdated": "2024-05-28" + }, + "description": "Matlab based experiments that implement multiple ray tracing methods for deterministic radiation\ntransport, including the Surface Method as described in the PhD Thesis, \"CONSERVATIVE FIRSTCOLLISION\nSOURCE TREATMENT FOR RAY EFFECT MITIGATION IN DISCRETE-ORDINATE\nRADIATION TRANSPORT SOLUTIONS\" by Alex Christensen.", + "laborHours": 1550.4, + "languages": [], + "name": "Surface Method Raytracer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/abcbitz/First_Collision_Source_Treatment", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-05-28", + "metadataLastUpdated": "2024-05-28" + }, + "description": "Machine Learning script to predict groundwater ages based on auxiliary features in a publicly available\ndataset, based on publicly available software libraries. Code applied to data from the Groundwater\nAmbient Monitoring and Assessment (GAMA) program in California, including well location and\nconstruction information, chemical constituents and isotopic tracers, and land use metrics.", + "laborHours": 577.6, + "languages": [], + "name": "Ground Water Age Predictor", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GWAP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-05-28", + "metadataLastUpdated": "2024-05-28" + }, + "description": "A user friendly, graphical, open-source implementation of the multiple benefits framework to non-energy-benefits incorporating additional aspects to make the tool effective for use in the United States. The software will be distributed as web, desktop and/or mobile apps.", + "laborHours": 21128.0, + "languages": [ + "TypeScript", + "HTML" + ], + "name": "NEB-Tool (Multiple Non Energy Benefits Tool) [SWR-24-08]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/NEB-Tool/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NEB-Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-05-29", + "metadataLastUpdated": "2024-05-29" + }, + "description": "GPT-crafted control software and graphical user interface for Keithley 2400 Source Measure Units and global optimization algorithm. It contains Numba-compatible self-adaptive differential evolution algorithm for optimization tasks.\n\nThis software is comprised of two repositories: \nhttps://github.com/NREL/Keithley_GPT\nhttps://github.com/NREL/DE", + "laborHours": 288.8, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "I-V characterization and parameter extraction tool [SWR-24-59]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-05-30", + "metadataLastUpdated": "2024-09-24" + }, + "description": "In-situ FTIR Spectral Deconvolution contains scripts for the fitting of gaussians to convoluted FTIR spectra. It was specifically developed to handle a time-series of in situ ATR-FTIR spectra, split the spectra into its individual gaussians, and track those peaks as they shift in intensity and energy. Along with the actual fitting script, this repository contains several support scripts for data analysis and recall of prior fit results.", + "laborHours": 532.0, + "languages": [ + "Python" + ], + "name": "In-situ FTIR Spectral Deconvolution [SWR-24-60]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/In-Situ-FTIR-SpectralDeconvolution", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "martindalena@ornl.gov" + }, + "date": { + "created": "2024-05-30", + "metadataLastUpdated": "2024-05-30" + }, + "description": "IPyOverlay is a Python library that provides several IPyWidget components for use within the Jupyter software ecosystem. These components add novel UI capabilities to enable details-on-demand interaction paradigms by providing the ability to render widgets on top of other widgets with arbitrary and controllable positioning. This capability enables adding click-and-draggable overlay windows containing other widgets, right-click context menus, and more complex tooltip functionality.", + "laborHours": 820.8, + "languages": [ + "Python" + ], + "name": "IPyOverlay", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl/ipyoverlay", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "allenmr@ornl.gov" + }, + "date": { + "created": "2024-05-31", + "metadataLastUpdated": "2024-06-05" + }, + "description": "This new version of NATURF, Version 1.0, builds on Version 0 by streamlining the code, decreasing its runtime and combining multiple modules into one convenient pip-installable package.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Neighborhood Adaptive Tissues for Urban Resilience Futures (NATURF) V1.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/naturf", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-06-01", + "metadataLastUpdated": "2024-06-06" + }, + "description": "The main function of ACCERT (The Algorithm for the Capital Cost Estimation of Reactor Technologies) is to provide an item-by-item estimate of the cost of a facility, at present a nuclear reactor complex, primarily nuclear power stations. The core of ACCERT is the large number of algorithms that have been developed and will continue to be developed. ACCERT is also a general methodology \nfor identifying and organizing the individual items that are estimated using the ACCERT algorithms. \nACCERT also summarize status and results; to save results and pull information from previous analyses; and to provide an interactive dynamic graphical user interface for a wide range of functions and visualizations.", + "laborHours": 16340.0, + "languages": [], + "name": "ACCERT", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/accert-dev/ACCERT", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-06-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An unsupervised segmentation method for structural analysis of Scanning Transmission\nElectron Microscopy (STEM) images", + "laborHours": 212.8, + "languages": [], + "name": "GraphEM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/GraphEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-06-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "CACTUS is an innovative LLM\u2010based agent that combines the cognitive capabilities of large language models with domain\u2010specific tools. By integrating\ncheminformatics tools, CACTUS assists researchers in tasks such as molecular property prediction, similarity searching, and drug\u2010likeness assessment.", + "laborHours": 729.6, + "languages": [], + "name": "CACTUS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/cactus", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "brewerwh@ornl.gov" + }, + "date": { + "created": "2024-06-04", + "metadataLastUpdated": "2024-06-28" + }, + "description": "ExaDigiT is a framework for developing comprehensive digital twins of liquid-cooled supercomputers, which has three main modules: (1) a python-based Resource Allocator and Power Simulator (RAPS), (2) a Modelica-based Thermo-Fluidic cooling model, and (3) a C++-based augmented reality model built on Unreal Engine 5. RAPS either simulates workloads or replays historical workloads from system telemetry, and is able to predict dynamic energy consumption, as well as interact with the cooling model to predict cooling system behavior. Such a tool can be used together with reinforcement learning algorithms to provide an end-to-end optimization tool for data centers.", + "laborHours": 775.2, + "languages": [ + "Python" + ], + "name": "ExaDigiT/RAPS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/exadigit/raps", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "hahnse@ornl.gov" + }, + "date": { + "created": "2024-06-04", + "metadataLastUpdated": "2024-06-05" + }, + "description": "AGILE GETRS provides an optimized implementation of DETRS that is faster than vendor optimized libraries for small (< 4000) problem sizes. These small problems sizes are of interest to researchers in the Grid Research Integration and Deployment Center (GRID-C) researching real-time power electronics simulations.\n\nIn addition to our implementation of DETRS, this code provides a test using Google Benchmark which generates matrices of various sizes, fills them with random numbers, runs GETRS, verifies the solution is correct and reports average runtime and other performance metrics.", + "laborHours": 288.8, + "languages": [ + "C++" + ], + "name": "AGILE GETRS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/ldrd_intersect_agile/agile_getrs", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "v0.1.0" + }, + { + "contact": { + "email": "dewittsj@ornl.gov" + }, + "date": { + "created": "2024-06-04", + "metadataLastUpdated": "2024-06-04" + }, + "description": "Determining the appropriate material data is often a bottleneck for performing calculations/simulations of industrial/experimental processes and resulting material structures and properties. Beyond the time it takes to find the appropriate values in the literature, many judgement calls are involved in choosing the values. These judgement calls can lead to inconsistencies between steps in research workflow, where different material parameter values are used.\n\nMist solves this problem by providing a mechanism to store, share, and use material information in convenient human-readable and machine-readable formats. Mist has an extensible ontology for defining a wide variety of material information, currently focused on metal alloy applications. Examples include: alloy composition, density, liquidus temperature, and the coefficient of thermal expansion.\n\nMist converts between standardized machine-readable data formats (e.g. JSON), specialized input format for simulation tools, and human-readable documents (e.g. LaTeX, Markdown). For parameters defined by an equation (e.g. a polynomial function) or a list of tabulated values, Mist can evaluate parameter values at requested conditions. Mist also provides an API for direct usage of the Mist data structures in calculations, if supported.", + "laborHours": 410.4, + "languages": [ + "Python" + ], + "name": "Mist", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-MDF/mist", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "dewittsj@ornl.gov" + }, + "date": { + "created": "2024-06-04", + "metadataLastUpdated": "2024-06-04" + }, + "description": "Many computationally unintensive models for material process-structure-property connections exist in the literature (e.g. journal articles and textbooks). However, to our knowledge there is no existing compilation of these models in one package. Many industrially and research relevant workflows involve combinations of many of these models and if the models have inconsistent interfaces, building these workflows can be challenging.\n\nRamen provides a collection of computationally unintensive models for calculating material process-structure-property relationships from the literature, as well as related tools (e.g. for plotting results). These models use a consistent interface structure and all leverage material data files and data structures from the Mist library (also developed at ORNL).\n\nRamen provides a structured package for combining many standard models in one place, with a standardized interface. This approach makes combining models in long/complex chains easy and straightforward.", + "laborHours": 228.0, + "languages": [ + "Python" + ], + "name": "Ramen", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-MDF/ramen", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-05", + "metadataLastUpdated": "2024-06-05" + }, + "description": "SAND2024-04584O\nR package for applying the VEESA pipeline method is a technique used for explainable machine learning with functional data. The VEESA pipeline makes use of the elastic-shape analysis framework for functional data. It also implements functional principal component analysis and permutation feature importance. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 486.4, + "languages": [ + "R" + ], + "name": "VEESA R package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/veesa", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-06", + "metadataLastUpdated": "2024-06-06" + }, + "description": "SAND2024-01003O\nZPAL is a Python software development kit designed for use by network automation engineers. It is an application programming interface (API) wrapper that is compatible with ZPE System's Nodegrid API. ZPE produces networking equipment. ZPAL simplifies connections to the ZPE Nodegrid API and makes configuration changes on the associated networking equipment.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 896.8, + "languages": [ + "Python" + ], + "name": "ZPAL v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ZPAL", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-06", + "metadataLastUpdated": "2024-06-11" + }, + "description": "SAND2024-00946O\nPython codes used in \"Trade-offs in the latent representation of microstructure evolution,\" a manuscript accepted for publication in Acta Materialia, are part of a repository. The code was developed to perform analysis of microstructure evolution. \n\nThe repository consists of two main directories: models, which train and test models such as autoencoders and diffusion maps, and analysis, which analyzes microstructures. Source code is used to perform dimensionality reduction of microstructure data for analysis of its evolution in time. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Python codes for the paper - \"Trade-offs in the latent representation of microstructure evolution\"", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-06", + "metadataLastUpdated": "2024-06-06" + }, + "description": "SAND2024-00922O\nThis software uses electroluminescence images to predict power loss due to cell cracks in photovoltaic modules. The software will incorporate trained variational autoencoder(s) to parameterize cell cracks detected in electroluminescence images of photovoltaic modules and relate cracks to electrical properties; reduced-order models of finite element simulations of electrical behavior of photovoltaic modules under thermomechanical stresses; reduced-order models of stress distributions; inside photovoltaic modules resulting from x-ray topography experiments; and image segmentation and splining methods to analyze x-ray topography measurements of cracked photovoltaic cells. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "pvcracks", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pvcracks", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-06", + "metadataLastUpdated": "2024-06-06" + }, + "description": "SAND2024-00905O\nConstitutive Models via Automatic Differentiation (CMAD) provides a software framework for solving constitutive or material model calibration problems. It relies on JAX's automatic differentiation capabilities to compute the derivatives needed for both forward and adjoint sensitivity analyses. The software can be used to implement constitutive models and calibrate the parameters from experimental data. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1550.4, + "languages": [ + "Python" + ], + "name": "Constitutive Models via Automatic Differentiation v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cmad", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-07", + "metadataLastUpdated": "2024-06-13" + }, + "description": "SAND2023-07883O\nKokkos software implements C++ performance portability programming models, tools and math libraries, which enables science and engineering software developers to use single-source codes for a wide range of computer architectures. Kokkos also provides implementations of existing and proposed C++ standard features that support programming model and math libraries that are used for implementing performance-portable scientific and engineering applications. The Kokkos libraries provide algorithms, data structures, and tools to enable high-performance computing developers to write performance-portable code. Capabilities fall into three broad categories: Kokkos Core, Kokkos Kernels, and Kokkos Tools.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 119700.0, + "languages": [ + "C++" + ], + "name": "Kokkos v.4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/kokkos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "4.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-07", + "metadataLastUpdated": "2024-06-07" + }, + "description": "SAND2023-07864O\nScribe Network API is an add-on tool for Scribe3D software. Scribe Network API documents tabletop exercises in trainings and plays back simulated videos of the scenarios and responses. Users can apply the software to compiled projects, or to a simple visual studio project solution package. The software runs a web application that relays information between computers using Scribe3D through a web application, or web app. The web app involves a representational state transfer (REST) application programming interface that handles sending and receiving Scribe save files and an SQL server that stores the save files. This follow-on package allows users to facilitate a networked tabletop exercise. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 11764.8, + "languages": [ + "C#", + "SQL" + ], + "name": "Scribe Network API v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/scribe3d-api", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-07", + "metadataLastUpdated": "2024-06-07" + }, + "description": "Wetlands have often been described as the \u201cEarth\u2019s kidneys\u201d because wetlands have the ability filter pollutants and purify water. Based upon wetland storage capacity, average daily flow, and inflow nutrient loading this model estimates potential load reductions of nitrate and orthophosphate) from a constructed surface flow wetland (CW). The model relies upon equations, coefficients, and models provided by Cheng et al. 2020 and Cheng & Basu 2017.\nNitrogen (N) and phosphorus are important nutrients to ecosystems, but high concentrations can lead to water quality issues. Major sources of these nutrients come from agricultural areas where fertilizer is applied in large quantitates and/or animal waste is present. Excess nitrate and phosphorus may result in overgrowth of algae, which can decrease the dissolved oxygen in water, thereby harming and killing fish and other aquatic species. This model evaluates water purification results and estimates cost to install a surface flow constructed wetlands.", + "laborHours": 197.6, + "languages": [ + "Python" + ], + "name": "Wetlands Geoprocessor (v 1.0)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/Wetlands_Geoprocessor", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-07", + "metadataLastUpdated": "2024-06-07" + }, + "description": "The proposed code, named FROG (Fusion neutron Generator) is built upon the open-source particle transport Monte Carlo toolkit Geant4. Geant4 provides C++ classes that can be leveraged to build application-specific codes dealing with the transport of particles through matter. Geant4-based codes are applied in high-energy particle physics experiments, medical applications, shielding, and space applications for example.\n\nThe FROG code allows the user to define the geometry of a neutron converter device shaped as a hollow cylinder, where a neutron breeding material such as lithium deuteride (LiD) is cladded by two concentric cylinders. Such neutron converter is then placed inside a regular nuclear fission reactor, where thermal neutrons will react with the neutron breeder material (typically, Lithium 6), and through a series of reactions, will generate high-energy neutrons \u2013 neutrons whose kinetic energy are around 14 MeV. The hollowed central portion can hold a specimen that will be bombarded by high-energy neutrons created inside the neutron breeding material. Figuratively speaking, this type of device transforms neutrons from thermal (~0.625 eV) to fusion (~14 MeV) energies and is sometimes termed \u201cfusion-to-thermal neutron converters\u201d in the literature. \n\nThe code consists of C++ source file compiled and linked to generate an executable. The user can select the dimensions of the converter (radius, length, and thickness of the breeder material), the breeder material type, the cladding material, and the specimen material that will be activated or irradiated. As input, the neutron flux for a specific location inside a reactor, for instance, positions in ATR, is required. As output, the code predicts the number of high-energy neutrons produced, the total neutron flux and fluence as well as its detailed spectrum. \n\nThe physics involved in such device is very complex, as it requires modeling neutron transport, light-ion (tritons) transport, as well as fusion reactions. The Geant4 toolkit provides the required physical models.", + "laborHours": 1489.6, + "languages": [ + "C++" + ], + "name": "Fusion Neutron Generator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/thermal_to_fusion_converter", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bridgesra@ornl.gov" + }, + "date": { + "created": "2024-06-11", + "metadataLastUpdated": "2024-06-11" + }, + "description": "This code allows reproduction of results in the paper\n\n\"Are Normalizing Flows the Key to Unlocking the Exponential Mechanism? \" https://arxiv.org/abs/2311.09200\n\nThe code here provides implementation of our experiments where we test if we can training models with ExpM+NF alongside and in comparison with DPSGD and non-private training.", + "laborHours": 21994.4, + "languages": [], + "name": "ExpM+NF MIMIC III experiments", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bridgesra/expm_nf_mimic3_results_code", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2024-06-11", + "metadataLastUpdated": "2024-06-17" + }, + "description": "AMES-Fit is a program used to automatically fit the multi-field solid-state NMR spectra of half-integer quadrupolar nuclei. Due to the high dimensional space, gradient algorithms have failed to address the fitting of such data, which is at present done manually. AMES-Fit diverges from these approaches by using an adaptive step size random search algorithm to fit the NMR spectra to consistently find the global best fit parameters.", + "laborHours": 1140.0, + "languages": [ + "C++" + ], + "name": "Automatic Multiple Experiment Simulation and Fitting (Ames-Fit)", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fperras/AMES-Fit", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2024-06-12", + "metadataLastUpdated": "2024-06-12" + }, + "description": "Axolotl is a Python library for scalable distributed genome and metagenome data analysis. Existing tools and systems that we rely on are struggling to keep up with the rapid explosion of genomic data. Compounding this issue, developing scalable solutions require a steep learning curve in parallel programming, which presents a barrier to academic researchers. While we do have scalable solutions for specific tasks, we lack comprehensive, end-to-end solutions. It's this gap in our toolkit that we aim to address with Axolotl. The Axolotl library is built for easy parallel processing, efficiently handling multiple tasks or large datasets simultaneously, and scaling up to meet the demands of extensive genomic data analysis.", + "laborHours": 2158.4, + "languages": [], + "name": "Axolotl: a scalable genomics library based on Apache Spark (Axolotl) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGI-Bioinformatics/axolotl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-12", + "metadataLastUpdated": "2024-06-12" + }, + "description": "RhizoNet is designed for the semantic segmentation of plant root scans, utilizing a sophisticated deep learning network known as Residual Unet. It specializes in processing color images of plants cultivated in a hydroponic EcoFAB system, captured using an Epson scanner. The core of the algorithm is based on Residual U-nets, which significantly improve prediction accuracy. This is achieved through the implementation of a convex hull operation, which effectively delineates the primary root component by leveraging spatio-temporal image data. This enables researchers to accurately assess predicted biomass and monitor plant growth over time.", + "laborHours": 608.0, + "languages": [], + "name": "RhizoNet: semantic segmentation of plant roots using CNN (RhizoNet) v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/rhizonet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "semalek@lbl.gov" + }, + "date": { + "created": "2024-06-12", + "metadataLastUpdated": "2024-06-17" + }, + "description": "The proposed system is written in the hardware description language (HDL) verilog targeting an FPGA board. It is intended as a testbed to explore architecture tradeoffs in multi-tiled heterogeneous architectures. Although we target FPGAs, the system can be implemented as a monolithic SoC or a package comprised of many chiplets that are interconnected in the same package using a NoC. The proposed NoC is lightweight and follows an axi-lite interface. The endpoints of the NoC are a heterogeneous mix of \"tiles\" as endpoints that are general purpose processors, fixed function accelerators, and programmable accelerators. We assume that the network interfaces for the NoC endpoints are all addressable in a global name-space in that they represent an address range (for memory addresses) or a range of unique identifiers that are associated with each individual tile. This makes the functionality abstract from the standpoint of the NoC design details. Message queues offer a direct inter-processor interface between peer general purpose cores and diverse accelerators that comprise an SoC. Although they share the same NoC infrastructure for inter-tile communication within an SoC or SiP, the hardware message queues bypass the memory hierarchy and thus do not pollute the memory state or invoke the cache coherence mechanism.", + "laborHours": 39656.8, + "languages": [], + "name": "P38 heterogeneous multi-tiled system with support for message queues (MoSAIC) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnlcomputerarch/MoSAIC-P38", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-12", + "metadataLastUpdated": "2024-06-12" + }, + "description": "This software allows to analyze XRF maps, XFS spectra and XAS spectra collected at the Advanced Light Source's Beamline 10.3.2.\n\nFeatures include:\n1) XRF maps:\n- process XRF maps, all elemental maps are saved as bmp automatically and labeled with the incident energy used, the scale bar is also labeled and can be controlled.\n- XRF elemental correlation plots, save the correlation plots automatically\n- Extract single or multiple transects in XRF maps on one or several regions of interest, each transect profile is numbered and saved in a corresponding folder, along with the corresponding maps showing transect location.\n\n2) XFS spectra\n- save in log10 scale the XFS spectra, either a single or multiple files all at once. The files are saved as .bmp.\n- XFS spectra are labeled according to tabulated fluorescence emission lines.\n\n3) XAS spectra\n- allows to plot individual scalers in the raw data.\n- allows calibration of the spectra using an Io internal glitch present in all spectra and performing 1st derivative.\n- Least-square linear combination fitting of XANES or extended XANES spectra using a database of standards using 1, 2 or 3 components maximum. It also provides the 5 top combinations and provide the user for the possibility of saving the 2nd, 3rd, 4th and 5th best combinations in addition to the best one. The processed spectra (pre-edge background substracted, post-edge normalized), the fits and residuals are automatically saved.\nA table of the component, with fit% and SSN is provided and saved automatically as well.", + "laborHours": 16400.8, + "languages": [], + "name": "XRF-XFS-XAS-Auto v1.0 - Beta release", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/als-computing/bl1032", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-13", + "metadataLastUpdated": "2024-06-13" + }, + "description": "DTX Explorer is a tool to generate interactive data visualizations of Darshan I/O traces collected from HPC applications. Its goal is to provide an easy and interactive way for researchers and developers to explore their application's I/O behavior and detect possible I/O bottlenecks that are impacting performance.", + "laborHours": 0.0, + "languages": [], + "name": "DXT Explorer v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/dxt-explorer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-13", + "metadataLastUpdated": "2024-06-17" + }, + "description": "PILATES allows for flexibly and at-scale coupling of multiple models to allow for multi-scale and multi-resolution simulation of regional-scale transport networks. In particular, it couples the MATSim-derived transportation modeling framework for Behavior, Energy, Autonomy and Mobility (BEAM) with other models operating at different time scales. Rather than tightly coupling supply and demand models using shared agents and memory within the same software process, PILATES orchestrates different model runs in a containerized framework. This structure requires passing information from the demand models to BEAM in the format of a synthetic population and agent plans, and from BEAM to the demand models in terms or origin/destination tables (also known as \"skims\"). This allows it to take advantage of the behavioral sophistication of existing activity-based models as well as the reinforcement learning structure of MATSim replanning and adopted by BEAM, in a way that requires minimal changes to existing models. It also takes advantage of the computational performance of BEAM, which allows for simulations with millions of agents to complete in reasonable time as well as allowing for detailed mechanistic simulation of the operation of on-demand modes.", + "laborHours": 4894.4, + "languages": [], + "name": "Platform for Integrated Land use And Transportation Experiments and Simulation (PILATES) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-UCB-STI/PILATES", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "edoardo.apra@pnnl.gov" + }, + "date": { + "created": "2024-06-13", + "metadataLastUpdated": "2024-06-17" + }, + "description": "NWChem is a computational chemistry software package which includes quantum chemical and molecular dynamics functionality. It aims to be scalable both in its ability to treat large problems efficiently, and in its usage of available parallel computing resources.", + "laborHours": 5977217.6, + "languages": [ + "C", + "Fortran", + "Python" + ], + "name": "NWChem", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/nwchemgit/nwchem/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nwchemgit/nwchem", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "7.2.2" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-06-13", + "metadataLastUpdated": "2024-06-13" + }, + "description": "This package includes three parts, (1) gov.llnl.math, (2)gov.llnl.utility and (3)gov.llnl.rtk, which are utilized\nin the development of Radiation Detector Simulator (RadSim) project. RadSim is being developed to\nprovide the capability to: (1) simulate radiation source emissions, (2) interpolate results from radiation\ntransport tools into a common format to prepare incident flux, and (3) model radiation detector response\nto rapidly produce synthetic radiation measurement templates. RadSim is targeted for open-source\nrelease, which will enable researchers and industry partners to model gamma-ray detectors response to\nsimulated flux from the transport tool of their choice. The techniques and implementation will be entirely\ntransparent, which will allow for improvements and boutique modifications by future researchers beyond\nthe lifespan of this specific project.\nThe first tool of the package, gov.llnl.math, includes classes and functions to define and perform basic\nmath operations. Some of the example features available in the package include defining statistical\ndistributions and performing algebra and matrix operations, all of which are already accessible on publicly\navailable software packages such as MATLAB and ROOT. The second package gov.llnl.utility includes\ntools commonly used to enable optimization and readability of various data structures such as Java lists\nand external xml files. Lastly, the gov.llnl.rtk package includes classes and functions to implement\nmethods commonly used in radiation physics, such as data structures to represent and characterize\nphoton spectra and tools to apply well-defined and published methods to calibrate a given spectra.", + "laborHours": 93373.6, + "languages": [], + "name": "RadSim: Math, Utility & RTK", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RadSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2025-03-26" + }, + "description": "The WETO Stack software is a collection of data, data analysis scripts, and website content produced through the Holistic Modeling Project\u2019s Portfolio Coordination task. The purpose of the software is to characterize the collection of wind energy software projects supported by the U.S. Department of Energy\u2019s Wind Energy Technologies Office. The included data contains characteristics of the actively funded software projects, and the data analysis scripts provide insights into the breadth, depth, and maturity of the collection of software projects. The website content presents the results of the analyses as well as reports from workshops and other events. It can be viewed at https://nrel.github.io/WETOStack/index.html.", + "homepageURL": "https://github.com/NREL/WETOStack", + "laborHours": 5076.8, + "languages": [ + "Python", + "TeX", + "Makefile" + ], + "name": "WETO Stack [SWR-24-81]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://creativecommons.org/licenses/by-nc-nd/4.0/?ref=chooser-v1", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://github.com/NREL/WETOStack", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2024-09-16" + }, + "description": "The NREL Wattile extension, nrelWattileExt, provides an interface between SkySpark, an energy management and analytics software, and Wattile, an NREL-developed Python package for probabilistic prediction of building energy consumption. Wattile models predict discrete quantiles of the probability distribution of a target quantity (typically energy consumption) using the historical time series data from one or more predictors (typically weather data). Within SkySpark, predictions from Wattile models can be used for measurement & verification of building performance, detection of energy anomalies, and fault detection.\n\nRelated to: https://github.com/NREL/Wattile", + "laborHours": 182.4, + "languages": [ + "Dockerfile", + "Fantom" + ], + "name": "nrelWattileExt (SkySpark Wattile Extension) [SWR-24-73]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/nrelWattileExt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The software framework, AMReX, supports the development of block-structured adaptive mesh refinement (AMR) algorithms for solving systems of partial differential equations. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving the essential local descriptions of different physical processes in complex multiphysics algorithms. AMR uses a hierarchical representation of the solution at multiple levels of resolution where the solution on each level is defined on the union of data containers at that resolution. These data containers, which represent the solution over a logically rectangular subregion of the domain, can contain field data defined on a mesh, Lagrangian particles or combinations of both. In addition to these basic data types, AMReX supports a multilevel embedded boundary representation of complex geometry; linear solvers for cell-centered and nodal data; asynchronous I/O in a native format readable by ParaView, VisIt and yt; and interfaces to hypre and PETSc solvers. AMReX enables applications to run on distributed memory architectures with multicore CPUs and with GPU accelerators. AMReX uses a lightweight abstraction layer that effectively hides the details of the architecture from the application. The framework currently supports CUDA, HIP and SYCL for GPU acceleration and OpenMP for multi-core CPU architectures.", + "laborHours": 0.0, + "languages": [], + "name": "AMReX v2024", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Codes/amrex", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2024-06-14" + }, + "description": "This software provides functions to perform visual predicate estimation by leveraging the pre-trained\nvision-language model CLIP. In addition to training the prediction estimator with a labeled dataset, it also\nperforms performance evaluation and visualization of results.", + "laborHours": 927.2, + "languages": [], + "name": "CLIP Representation Enhanced Predicate Estimation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CREPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2024-06-14" + }, + "description": "These codes estimate effective diffusivity for species transport in materials and simultaneously fit multiple temperatures of measured isotherm and effective diffusivities for sorption transport of species through materials. Assumes triple-mode type sorption thermodynamics with mobile and immobile species in quasi-equilibrium.", + "laborHours": 349.6, + "languages": [], + "name": "FitIsoAndDeff and DeffCalculator Matlab Codes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/foley352/polymer-diffusion", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "01" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ATLAS is a comprehensive vehicle transaction and technology adoption microsimulator. ATLAS evolves the fleet mix of individual households by simulating the transaction (vehicle addition, disposal, and replacement) and choice (vehicle type, vintage, powertrain, and tenure) decisions in response to the co-evolving demographics, land use, and vehicle technology simulations. Different from the existing vehicle models that are either static or aggregated (e.g. stock model), ATLAS is fully disaggregated and dynamic following a sequential and circumstantial decision-making trajectory. This fine-grained approach not only enhances the realism of the simulation but also provides a nuanced understanding of the dynamics inherent in vehicle fleet evolution. ATLAS outputs are fully compatible with subsequent agent-based transportation modeling system and can enable distributional effect analysis regarding the fleet turnover among heterogeneous populations. ATLAS expands the typical new sale focused vehicle choice modeling to including used vehicle transactions that are of increasing interests to understanding the vehicle adoption behavior among lower income households.", + "laborHours": 2173.6, + "languages": [], + "name": "Automobile and Technology Lifecycle-Based Assignment (ATLAS) v2.0.12", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-science-it/atlas-release", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2024-06-19", + "metadataLastUpdated": "2024-06-19" + }, + "description": "We introduce HTESP (High-Throughput Electronic Structure Package), an automated tool designed for high-throughput ab initio calculations. HTESP simplifies the entire workflow, including data extraction, input files generation, calculation submission, result collection, and plotting. The package is implemented in Python and Bash languages. In this paper, we provide detailed information about the package, its installation process and some illustrative examples to demonstrate its usage. Additionally, the package includes comprehensive online documentation on input parameters and tutorials to assist users.", + "laborHours": 14060.0, + "languages": [ + "Bash", + "Python" + ], + "name": "High-throughput electronic structure package", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Neraaz/HTESP", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "Polyglot utilizes a combination of custom and open source tools and libraries to provide developers with a consistent environment for building tools, etc. for a wide variety of targets with minimal changes to the code being built. It supports a variety of architectures and operating systems/firmware in as target-agnostic way as possible. This allows for developers to minimize the amount of time/effort required to port tools\u2014in particular, forensic tools\u2014to a wide variety of targets.\nThe project is comprised of two main components: a frontend toolchain that understands how to utilize other tools in order to build code for a specific target, and a minimalistic C library specific to Polyglot. These collectively provide the method to build code for a specific target, and the capability for code to interact with the underlying operating system when run on the target. Both components are written in a way to minimize the amount of target-specific knowledge required to both develop and utilize the project.", + "laborHours": 4347.2, + "languages": [ + "C", + "C++", + "Python" + ], + "name": "Polyglot Framework", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/polyglot", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "The C library component of Polyglot.\nPolyglot utilizes a combination of custom and open source tools and libraries to provide developers with a consistent environment for building tools, etc. for a wide variety of targets with minimal changes to the code being built. It supports a variety of architectures and operating systems/firmware in as target-agnostic way as possible. This allows for developers to minimize the amount of time/effort required to port tools-in particular, forensic tools-to a wide variety of targets.\nThe project is comprised of two main components: a frontend toolchain that understands how to utilize other tools in order to build code for a specific target, and a minimalistic C library specific to Polyglot. These collectively provide the method to build code for a specific target, and the capability for code to interact with the underlying operating system when run on the target. Both components are written in a way to minimize the amount of target-specific knowledge required to both develop and utilize the project.", + "laborHours": 31129.6, + "languages": [ + "C" + ], + "name": "Polyglot C Library", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/polyglot-libc", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "This code is a web-based front-end only (HTML, CSS, JS) chatbot interface for any OpenAI compatible text completion API.", + "laborHours": 638.4, + "languages": [ + "JavaScript", + "HTML", + "CSS" + ], + "name": "Front-end Only Chatbot Interface", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HPC_OOD_Chat", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-26" + }, + "description": "Complex engineering systems such as nuclear power plants (NPPs) generate and collect large amounts of equipment reliability (ER) data elements that contain information on the status of components, assets, and systems. Some of this information is textual in form and can be found in documents such as incident reports (IRs) and work orders (WOs). Analyses of textual data in current NPPs-using natural language processing (NLP) methods-have been expanded over the last decade, and it is only recently that the true potential of such analyses has emerged. So far, applications of NLP methods have mostly been limited to classification and prediction, the goal being to identify the nature of the textual element (e.g., safety or non-safety related). Here, we target a more complex problem: automatically extracting knowledge from a textual element in order to assist system engineers in conducting system health assessments. Knowledge extraction is a very broad concept, and its definition may vary depending on the application context. Our methods are a blend of both rule-based and machine learning (ML) algorithms. For our purposes, knowledge extraction means identifying the systems or assets mentioned in a given textual element, as well as the type of event described (e.g., component failure or maintenance activity). In addition, we want to capture details such as measured quantities and the temporal/cause-effect relations between events. In this tool, we also demonstrate how textual data elements are preprocessed in order to handle typos, acronyms, and abbreviations. One main feature of these methods is that they are not based solely on data, but are in fact model-based. In other words, they also rely on MBSE models that are designed to capture-from a functional point of view-the architecture of the systems/assets under consideration. The main purpose of such models is to digitally emulate system engineers' knowledge of system and asset architecture and to identify dependencies among systems, assets, and components. Provided these models, analyses of textual and numeric ER data can be performed by first identifying the OPM model elements to which the ER data elements are referring. The relationships between ER data elements are then identified by checking for any temporal or logical dependencies.", + "laborHours": 7265.6, + "languages": [ + "Python" + ], + "name": "Digital Analytics, Causal Knowledge Acquisition and Reasoning for Technical Language Processing", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DACKAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "The Many-Body Adaptive Configuration Interaction Suite (MACIS) is a modern C++ software infrastructure for the development of selected-configuration interaction (sCI) methods for the fermionic many-body problem in quantum chemistry and materials science. MACIS provides a high-performance, parallel implementation of the Adaptive Sampling Configuration Interaction (ASCI) method as related solvers such as self-consistent orbital optimization and the evaluation of excited states and spectral functions. Unlike existing sCI software, MACIS is developed as a modular software infrastructure which allows it to exist both as a standalone sCI solver and as a library to integrate into existing many-body codes. This modularity allows MACIS to be quickly extensible, including its integration with other sCI methods and high-performance solvers.", + "laborHours": 18696.0, + "languages": [], + "name": "Many-Body Adaptive Configuration Interaction Suite (MACIS) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wavefunction91/MACIS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "Scripts for analyzing microbial community taxonomy and function, running statistical tests, and making complex graphics.", + "laborHours": 14440.0, + "languages": [], + "name": "SF_Microbe_Methane (SFMM) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cliffbueno/SF_microbe_methane", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-25" + }, + "description": "Geant-4 based detector simulations in c++ which combines simulation and analysis into a single framework to precisely model detector components and analyze experimental data. Ratpac allows the user to easily build new detector geometries and configurations through both the source library and through configurable text files at runtime.", + "laborHours": 48883.2, + "languages": [], + "name": "Ratpac-Two v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rat-pac/ratpac-two", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "REMORA (previously known as ROMS-X) is a GPU-enabled regional ocean modeling code with the same core capabilities as the Regional Ocean Modeling System (ROMS) code.", + "laborHours": 11187.2, + "languages": [], + "name": "REMORA v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/seahorce-scidac/REMORA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "This repository contains data and code for statistically comparing soil microbial communities across four different wetland sites and making publication quality figures. It is similar to other microbiome analysis but is specific for this project.", + "laborHours": 834145.6, + "languages": [], + "name": "EastCoast v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cliffbueno/EastCoast", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-26" + }, + "description": "Open source Node-Red \"nodes\" to support the Open Charge Point Protocol (OCPP) 2.0.1 protocol.", + "laborHours": 15899.2, + "languages": [], + "name": "node-red-contrib-ocpp2", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/node-red-contrib-ocpp2", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "SynthFirm is a large-scale agent-based freight demand model which generates a complete synthetic population of firms in the U.S. and the business-to-business commodity flows between them. Using publicly available data sources as inputs, SynthFirm simulates detailed firm and fleet characteristics, commodity production and consumption, formation of supply chains, and selection of shipping modes, all of which are essential drivers of commodity flow at a disaggregate level.", + "laborHours": 19456.0, + "languages": [], + "name": "Firm Synthesizer and Supply-chain Simulator (SynthFirm) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-UCB-STI/SynthFirm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-26" + }, + "description": "The Inventory of Composable Elements (ICE) is an open source registry software platform for managing information about biological parts. It is capable of recording information about plasmids, microbial host strains and seeds, as well as DNA parts. Includes features such as DNA sequence visualization, editing and annotation, auto-aligning sequencing trace files against reference templates, SBOL XML/RDF support, and web-of-registries functionality. The web of registries functionality provides strong support for distributed interconnected use and enables sharing and transfer of biological parts across various independent ICE instances. ICE adopts modern software development principles, leveraging component-base frameworks, offering a REST API for convenient third-party integration and emphasizing scalability, security, and service integrations for dynamic content availability. The source code is hosted at https://github.com/JBEI/ice. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects.", + "laborHours": 45037.6, + "languages": [], + "name": "Inventory of Composable Elements (ICE) v6.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/ice", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "Fusion Transfer Learning (FTL) model provides a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. The knowledge transfer process leverages a pre-trained neural encoder-decoder network, initially trained on linear simulations, to effectively capture nonlinear dynamics. The low-dimensional embeddings extract the coherent structures of interest, while preserving the inherent dynamics of the complex system. Experimental results highlight FTL's capacity to capture transitional behaviors and dynamical features in plasma dynamics -- a task often challenging for conventional methods. The model developed in this study is generalizable and can be extended broadly through transfer learning to address various magnetohydrodynamics (MHD) modes.", + "laborHours": 91.2, + "languages": [], + "name": "FTL: Transfer Learning Nonlinear Plasma Dynamic Transitions in Low Dimensional Embeddings (FTL) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zhbai/FTL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-27" + }, + "description": "For the development of magnets for particle accellerators, the tool ROXIE from CERN has become a de facto standard. This script interprets the output files of ROXIE and translates them into a VTK file that can be read in ParaView for visualization.", + "laborHours": 273.6, + "languages": [], + "name": "rox2vtk v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmesse/rox2vtk.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "The software program, referred to as BELFEM, is a specialized finite element code designed for the magnetodynamic modeling of high-temperature superconducting (HTS) tapes. It incorporates novel mixed finite element formulations, particularly the h-\u03d5-formulation with thin-shell simplification, to efficiently simulate larger geometries. This methodology is extremely promising for predicting the electrodynamic performance of HTS tapes used in superconducting cables and magnets, offering the benefit of reduced computational cost. Compared to similar technologies like COMSOL Multiphysics and GetDP, BELFEM's performance benchmarking indicates superior efficiency in its thin-shell implementation. In the future, it will also support features like thermal coupling and inter-tape current sharing, enhancing its utility in research and development, particularly in nuclear fusion applications. The intent is to develop BELFEM as a robust and efficient tool for the HTS community, contributing to the analysis and design of superconducting cables and magnets.", + "laborHours": 97416.8, + "languages": [], + "name": "Berkeley Lab Finite Element Framework (BELFEM) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmesse/belfem.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Active learning algorithms based on surrogate models to solve black-box optimization problems and other scientific applications.", + "laborHours": 4332.0, + "languages": [ + "Jupyter Notebook", + "R", + "Python" + ], + "name": "BBOpt (Black-Box Opt) [SWR-24-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bbopt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "This package includes three parts, (1) gov.bnl.nndc.ensdf, (2) gov.nist.xray and (3) gov.nist.physics.n42, which are utilized in the development of Radiation Detector Simulator (RadSim) project. RadSim is being developed to provide the capability to: (1) simulate radiation source emissions, (2) interpolate results from radiation transport tools into a common format to prepare incident flux, and (3) model radiation detector response to rapidly produce synthetic radiation measurement templates. RadSim is targeted for open-source release, which will enable researchers and industry partners to model gamma-ray detectors response to simulated flux from the transport tool of their choice. The first tool of the package, gov.bnl.nndc.ensdf, includes functionality to parse and split publicly available decay records in ENSDF format, and pull the relevant information from ENSDF libraries. The second tool, gov.nist.xray, provides Xray information using the public NIST database. Lastly, gov.nist.physics.n42, is a tool used to convert an N42 xml file into a Java object that can be interfaced within a Java program.", + "laborHours": 93373.6, + "languages": [], + "name": "RadSim: ENSDF, Xray and N42", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RadSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "Modelling and solution library for security-constrained AC optimal power flow problems that uses nonlinear programming methods (interior-point methods) and solvers (Ipopt, HiOp). The code is written in C++ and provides parallel computing capabilities in the form of task parallelism (solving contingency problems in parallel). Code can run on a variety of commodity high-performance computing.", + "laborHours": 11886.4, + "languages": [], + "name": "Grid Optimization Lawrence Livermore Nonlinear Programming", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gollnlp/gollnlp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-24", + "metadataLastUpdated": "2024-06-27" + }, + "description": "The software package in question is a collection of simulation models in the Modelica language, representing a variety of mechanical system designs and envelope conditions related to LBL's FLEXLAB facility. The collection of models also features multiple controls sequences that can be simulated with the FLEXLAB model to simulate different demand flexibility scenarios. Additionally, this package will feature datasets from 3 experimental tests, used for calibration, validation and comparison against the Modelica models, this includes weather data that can be used to replicate different scenarios in simulation across the same weather conditions experienced in real experiments. Given FLEXLAB high level of instrumentation and available data, the models are calibrated across multiple measurement points, and thus results from the extension of this model to other climate zones or control sequences, would provide high level of confidence.", + "laborHours": 0.0, + "languages": [], + "name": "Hardware In the Loop for Demand Flexibility (HIL4DF) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/HIL4DF", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-24", + "metadataLastUpdated": "2024-06-24" + }, + "description": "This is a parallel variable population multi-objective optimizer with an adaptive unified differential evolution algorithm or a genetic algorithm.\nIt can also be used for single objective optimization.\nSome features of this code include:\n1) The population size varies from generation to generation to save the total # of objective function evaluations.\n2) The population is uniformly distributed to a number of parallel processors for simultaneous objective function evaluation.\n3) The objective function evaluation can be attained from an external simulation program with control variables in its input file and objectives calculated from its output files.\n4) The optimizer includes an adaptive unified differential evolution algorithm and a real value genetic algorithm. The parameters in the unified differential evolution algorithm can be chosen to attain any mutation schemes in the published literature.", + "laborHours": 836.0, + "languages": [], + "name": "Parallel Variable Population Multi-Objective Optimizer (pvpmoo) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qianglbl/PVPmoo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-25", + "metadataLastUpdated": "2024-07-03" + }, + "description": "This program is used to subset metagenomic functional profiles to a list of desired taxa.", + "laborHours": 15.2, + "languages": [], + "name": "KO_by_taxa v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cliffbueno/KO_by_taxa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-25", + "metadataLastUpdated": "2024-06-25" + }, + "description": "It is a serial/parallel code for fast electron beam longitudinal\nforward or backward tracking through an electron linear accelerator.\n\nThis codes includes longitudinal space-charge effect, structure\nand resistive wall wakefields, and longitudinal coherent synchrotron radiation effect.\n\nTo use it as a parallel code, please comment out the \"use mpistub\" in BeamBunch.f90, rename mpif.h as mpif.hh,\nand use the Makefile_parallel as Makefile.", + "laborHours": 942.4, + "languages": [], + "name": "Electron Beam Longitudinal Tracking (EBLT) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qianglbl/EBLT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-25", + "metadataLastUpdated": "2024-06-25" + }, + "description": "This software was designed as a sequence validation tool for the assembly of synthetic constructs. It analyzes FASTQ files against a list of reference sequences, combining the results from eight sequencing libraries to generate a summary, and the files needed to view the results in the Integrative Genomics Viewer (IGV) application for manual verification. This was developed for FASTQ files generated by PacBio sequencing, but could be used on any FASTQ files that do not have paired end reads. It can be used to analyze one - eight libraries at a time, and assumes that each construct sequence in the reference will be in each pool, however, this is not a requirement. This is used to identify which libraries of pooled sequences contains a perfect match, or fixable match to the reference file.\n\nThis pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up, as well as the user friendly html summary that is generated.", + "laborHours": 9363.2, + "languages": [], + "name": "Synthetic Biology PacBio/JAWS QC Analysis (PBJ) v3.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/jgi-synbio-public/synbioqc-pbj", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-27", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This software was designed as a sequence validation tool for the assembly of synthetic constructs, where the constructs have a high degree of similarity and thus are barcoded prior to the sequencing library prep. It demultiplexes each FASTQ file for each barcode, then analyzes the resulting FASTQ files against a list of reference sequences for that barcode/library, combining the results from eight sequencing libraries to generate a summary, and the files needed to view the results in the Integrative Genomics Viewer (IGV) application for manual verification. This was developed for FASTQ files generated by PacBio sequencing, but could be used on any FASTQ files that do not have paired end reads. It can be used to analyze one - eight libraries at a time. Each construct is independently analyzed with only the sequences with the same barcode, in the same pooled library. Then the results are combined into a user friendly summary. This is used to identify which libraries of pooled sequences contains a perfect match, or fixable match to the reference file. This pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up, as well as the user friendly html summary that is generated.", + "laborHours": 3800.0, + "languages": [], + "name": "SynBio QC Dual Barcode QC (DBC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/jgi-synbio-public/synbioqc-dual_barcode", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-27", + "metadataLastUpdated": "2024-06-27" + }, + "description": "ICDFO is python and matlab/octave code for a set of for interpolation-based optimization methods for composite derivative-free optimization. These methods are applicable when a user wishes to maximize or minimize a function that depends on some blackbox component/simulation for which derivatives with respect to the decision variables are not available. The methods include pounders and goombah.", + "laborHours": 3040.0, + "languages": [], + "name": "Interpolation-Based Composite Derivative-Free Optimization (IBCDFO) v0.01", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/POptUS/IBCDFO", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-27", + "metadataLastUpdated": "2024-06-27" + }, + "description": "The Scientific sofTware Research for User experience, Design, Engagement, and Learning project (STRUDEL) will create, using user research methodologies, a planning framework and design system for scientific software that will guide and support the development of highly functional and usable user interfaces.", + "laborHours": 323243.2, + "languages": [], + "name": "Scientific sofTware Research for User experience, Design, Engagement, and Learning (STRUDEL) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/strudel-science/strudel-kit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-28", + "metadataLastUpdated": "2024-06-28" + }, + "description": "Increases in sequencing capacity, combined with rapid accumulation of publications and associated data resources, have increased the complexity of maintaining associations between literature and genomic data. As the volume of literature and data have exceeded the capacity of manual curation, automated approaches to maintaining and confirming associations among these resources have become necessary. Here we present the Data Citation Explorer (DCE), which discovers literature incorporating genomic data whether or not provenance was clearly indicated. This service provides advantages over manual curation methods including consistent resource coverage, metadata enrichment, documentation of new use cases, and identification of conflicting metadata. The service reduces labor costs associated with manual review, improves the quality of genome metadata maintained by the U.S. Department of Energy Joint Genome Institute (JGI), and increases the number of known publications that incorporate its data products. The DCE facilitates an understanding of JGI impact, improves credit attribution for data generators, and can encourage data sharing by allowing scientists to see how reuse amplifies the impact of their original studies.", + "laborHours": 16036.0, + "languages": [ + "ABAP" + ], + "name": "Data Citation Explorer (DCE) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/data-citation-explorer/data-citation-explorer-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-06-28", + "metadataLastUpdated": "2024-07-15" + }, + "description": "EVI-OnDemand is a simulation platform which estimates fast-charging infrastructure requirements necessary to support ride-hailing electrification. The tool belongs to the broader EVI-X family, a consortium of infrastructure modeling tools created by researchers at the National Renewable Energy Laboratory (NREL).", + "laborHours": 228.0, + "languages": [ + "Python" + ], + "name": "EVI-OnDemand [SWR-21-115]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EVI-OnDemand", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kumarv@ornl.gov" + }, + "date": { + "created": "2024-06-28", + "metadataLastUpdated": "2025-03-31" + }, + "description": "ExaDigiT is a framework for developing comprehensive digital twins of liquid-cooled supercomputers, which has three main modules: (1) a python-based Resource Allocator and Power Simulator (RAPS), (2) a Modelica-based Thermo-Fluidic cooling model, and (3) a C++-based augmented reality model built on Unreal Engine 5. The Modelica-based cooling model is primarily built-on the open-source Transient Simulation Framework\nof Reconfigurable Models (TRANSFORM) library and the open-source autocsm library.\nThe library follows the templating architecture developed in the TRANSFORM and the autocsm libraries. This tool can be easily extended to model other Frontier-like liquid cooled supercomputers.", + "laborHours": 395.2, + "languages": [], + "name": "datacenterCoolingModel", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/exadigit/datacenterCoolingModel", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-07-01", + "metadataLastUpdated": "2024-07-01" + }, + "description": "Artifact Description of the Cerebras TriLabs SC'24 conference paper. Include details and procedures for how to reproduce timing computations.", + "laborHours": 45.6, + "languages": [], + "name": "Cerebras TriLabs SC'24 paper Artifact Description", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CerebrasTrilabs-SC24AD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-07-01", + "metadataLastUpdated": "2024-07-01" + }, + "description": "The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.", + "laborHours": 0.0, + "languages": [ + "Python", + "Shell" + ], + "name": "Fast All-sky Radiation Model for Solar applications (FARMS) 2023 [SWR-16-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/farms", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.5" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-07-01", + "metadataLastUpdated": "2024-07-01" + }, + "description": "cloud-fs (Cloud File System Utilities) is a generalized file-system handler that will dynamically determine if files are local or on the cloud (currently AWS) and perform basic file-system operations.", + "laborHours": 0.0, + "languages": [ + "Python", + "Shell" + ], + "name": "cloud_fs (Cloud File System Utilities) 10.6.2021 [SWR-21-83]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/cloud_fs", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.0.8" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SAND2024-01036O\nThe updated Sandia Solution Mining Code (SANSMIC) modeling software models the dissolution of underground salt cavern walls due to raw-water injection (leaching), assuming an oil blanket. A previous version of this software modeled the impacts of leaching at the Strategic Petroleum Reserve and has been used in research for several decades, but the source code was not available. The new version will enhance current research as additional subsurface storage of energy in solution-mined caverns increases. It will also allow research reproducibility by making the software available to the wider research community. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 2021.6, + "languages": [ + "C++", + "Python" + ], + "name": "SANSMIC v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sansmic", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-03", + "metadataLastUpdated": "2024-07-03" + }, + "description": "SAND2024-08373O\nTwinMe4AD is a Python-based software tool designed for anomaly detection using digital twins that closely mimic real, wearable healthcare datasets. The tool is invaluable for scenarios where collecting data is either expensive or impractical, serving as a privacy-preserving solution. Sensitive information is protected by training deep learning models on synthetic data derived from real datasets. One of TwinMe4AD's key features is its anomaly detection capability, which is based on fourth-order moments of parameters. This versatile approach can be applied across a range of datasets, from univariate to multivariate, making it compatible with various types of data. It also generates synthetic twins using Wasserstein Generative Adversarial Networks (WGANs), allowing users to create a small cohort of a population similar to that of a village population. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1550.4, + "languages": [ + "Python 3.6" + ], + "name": "TwinMe4AD: WGAN-based Digital Twins for Anomaly Detection", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TwinMe4AD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-08", + "metadataLastUpdated": "2024-07-16" + }, + "description": "SAND2021-6741 O\nphenix is Sandia's orchestration tool that allows users to quickly deploy, un-deploy, and interact with SCEPTRE ICS environments. phenix is an orchestration tool used for managing the creation, configuration, and deployment of modeling and simulation environments. As an abstraction layer on top of an underlying virtual machine manager called minimega, phenix organizes the network, application, and scenario information for a given deployment. It allows users to create, configure, and deploy experiments in a repeatable and rapid fashion. An application framework provides the flexibility to manipulate an experiment to suit various needs and requirements. phenix also includes a web-based graphical user interface (GUI) where experiments can be created, configured, and interacted with.", + "laborHours": 131145.6, + "languages": [ + "Go", + "Javascript", + "Vue" + ], + "name": "phenix v. 7.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sceptre-phenix", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "7.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-07-09", + "metadataLastUpdated": "2024-07-09" + }, + "description": "Python software package for PCA analysis of ToF-SIMS spectra data", + "laborHours": 805.6, + "languages": [], + "name": "Automated ToF-SIMS PCA Analysis Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pca-analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-07-10", + "metadataLastUpdated": "2024-07-10" + }, + "description": "This is the official code for the ICML 2024 paper \"Adversarial Robustness Limits via Scaling-Law and\nHuman-Alignment Studies\". This code extends that of Wang et al. (2023) to facilitate state-of-the-art\nCIFAR-10 adversarial robustness, via training of WideResNet models on various large synthetic datasets.\nThe code also facilitates derivation of the various scaling laws put forth in our ICML paper, which we use\nto compute efficient training settings.", + "laborHours": 4544.8, + "languages": [], + "name": "Adversarial Robustness Limits", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bbartoldson/Adversarial-Robustness-Limits", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-07-11", + "metadataLastUpdated": "2024-07-11" + }, + "description": "LCUSS is a collection of scripts used to improve productivity on HPC systems for both administrators and\ngeneral users. It will include general scripts for user management, scripts for helping users interact with\nLC resource management software (e.g. SLURM and Flux), and scripts to automate common user\ncommand-line tasks on LC and other HPC machines. These scripts are intended to be made available to\nall LC users. Hosting them on GitHub will allow LC staff, users, and collaborators to work on them\ntogether.", + "laborHours": 60.8, + "languages": [], + "name": "Livermore Computing User and System Scripts", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LCUSS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-11", + "metadataLastUpdated": "2024-07-11" + }, + "description": "REFA is designed to help transmission planners better understand the financial, environmental and economic benefits of reconductoring upgrades, using traditional or advanced conductors. More specifically, the tool enables grid planners and utilities to demonstrate the entire lifetime value of reconductoring projects, providing potential justifications for projects with higher Capex - the purchase of long-term physical or fixed assets used in a business's operations. Existing tools are designed to compare technical aspects of different conductor applications. They typically do not allow a cost-benefit analysis over the lifetime of the conductor's operations.", + "homepageURL": "https://gridintegration.lbl.gov/refa", + "laborHours": 98800.0, + "languages": [], + "name": "Reconductoring Economic and Financial Analysis Tool (REFA) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://gridintegration.lbl.gov/refa", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://gridintegration.lbl.gov/refa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-11", + "metadataLastUpdated": "2024-07-11" + }, + "description": "A Python package that provides differentially private queries optimized for energy systems' data. It may be used to publish queries such as clustering, averaging, metadata inference, etc. that are useful for a variety of grid-related analytics, including cyberattack detection.", + "laborHours": 410.4, + "languages": [], + "name": "CEDS Differential Privacy (CEDSDP) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/CEDSKMeans", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This Python package implements a high-level interface to access the data published by the Particle Data Group (PDG) in the Review of Particle Physics (the \"Review\").\n\nThe Particle Data Group is an international collaboration led by the PDG group at LBNL. The PDG summarizes the established knowledge in the field of particle physics in a single publication, the Review of Particle Physics. The Review is published and updated online (see https://pdg.lbl.gov) each year, and published in a scientific journal every other year. It is currently licensed under a CC BY-NC 4.0 license. In 2021 PDG was designated by the Office of Science as a SC PuRe Data Resource. The Review is one of the most highly cited publications in the field of particle physics.\n\nThe PDG Python API is part of PDG's efforts to make all data provided in the Review available in machine-readable format. This data includes the PDG world averages (or best limits) on particle masses, widths or lifetimes, branching fractions, magnetic moments, form factors, coupling constant ratios, and searches, as well as particle quantum numbers. It also includes detailed information on how PDG arrived at its averages, such as e.g. tables of published measurements with comments and footnotes, information on the consistency of published measurements, and detailed fit information.", + "laborHours": 988.0, + "languages": [], + "name": "Python package for machine-readable access to PDG data (PDG Python API) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/particledatagroup/api", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "The Advanced Fenestration Controller is the result of 5+ years of R&D to develop an advanced control system for Dynamic Facades (e.g., automated shades, blinds, etc.), electric lighting, and HVAC system in buildings. It can dynamically control those technologies to reduce electricity cost while increasing comfort. The work in FY22 focused on open-sourcing our development, per agreement with DOE.", + "laborHours": 2523.2, + "languages": [], + "name": "Advanced Fenestration Controller (AFC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/AFC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2025-01-30" + }, + "description": "Tardigrade-examples is a repository of computational workflows that exercise the Tardigrade software package. The Tardigrade software package is an implementation of Eringen\u2019s micromorphic continuum theory with capabilities to support multiscale material modeling. These capabilities include homogenization through the Micromorphic Filter, calibration of micromorphic material models, and macroscale simulation in Tardigrade-MOOSE. This repository investigates continuum upscaling of various direct numerical simulations (DNS) conducted in Abaqus finite element (FE), Ratel FE, and GEOS material point method (MPM) software. Verification of the upscaling workflow is first investigated by considering DNS of trivial stress states for homogeneous materials, results of which indicate that classical continuum behavior is recovered as expected. DNS of heterogeneous materials are then considered.", + "laborHours": 10579.2, + "languages": [], + "name": "Tardigrade-examples V0.1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Tardigrade-examples", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This library is a collection of python modules that define, train, and analyze vision-transformer (ViT) machine learning models. The code implements, with mild modifications, ViT models that have been made publicly available through publication and GitHub code. The training data for these models is hydrodynamic simulation output in the form of numpy arrays. This library contains code to train these ViT models on the hydrodynamic simulation output with a variety of hyperparameters, and to compare the results of such models. Furthermore, the library contains definitions of simple convolutional neural network (CNN) machine learning architectures which can be trained on the same hydrodynamic simulation output. These are included as a reference point to compare the ViT models to. Additionally, the library includes trained ViT and CNN models and example input data for demonstration purposes. The code is based on the PyTorch python library.", + "laborHours": 2006.4, + "languages": [], + "name": "Hyperparameter Studies for Vision Transformers Trained on High-Fidelity Simulations", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/CNN-T2TViT-comparison", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This code compares the runtimes between the Dirichlet Dempster-Shafer Model (DSM) against the competition method, the Simplex DSM. Besides the code used to implement the Dirichlet DSM, all code to be released implements existing methods that are not novel algorithms nor any major innovations to existing software.", + "laborHours": 547.2, + "languages": [], + "name": "Code for Experiment in Publication \u201cA New Method for Multinomial Inference using Dempster-Shafer Theory\u201d", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/dempster-shafer-multinomial", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "Software for performing calculations of physical systems, both equilibrium and dynamical, using convex constraints.", + "laborHours": 425.6, + "languages": [], + "name": "Convex methods for physics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/concave", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "PLEIADES: Python Libraries Extensions for Isotopic Analysis via Detailed Extraction of SAMMY. \n\nThis is a Python package that configures and executes the code SAMMY, which is an open sourced R-Matrix fitting code from ORNL. Additionally, PLEIADES includes python packages to analyze SAMMY results and process them into isotopic images.", + "laborHours": 1504.8, + "languages": [], + "name": "LANL contributions to PLEIADES", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PLEIADES", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This framework aids in Transcription factor binding site prediction given DNA sequence information and DNA biophysical characteristics computed by pyDNA-EPBD. This framework utilizes a large language model for binding site prediction.", + "laborHours": 10564.0, + "languages": [], + "name": "EPBD-BERT", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EPBD-BERT", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "DISSIDE uses novel unsupervised learning to select samples that best represent the strongest a\npriori discrete pattern in a given data set. It further removes major outliers and \"noisy\" samples\nthat do not fit discrete patterns well or represent outliers in groups below a defined n value. It\nthen estimates the fit and strength of the a priori discrete pattern using both unconstrained and\nconstrained methods for raw and cleaned data", + "laborHours": 744.8, + "languages": [], + "name": "DISSIDE: Dynamic In Silico Sample Identification for Discrete Evaluation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lebrun-LANL/DISSIDE-Dynamic-In-Silico-Sample-Identification-for-Discrete-Evaluation", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "pySimFrac is a python library for generating 3D synthetic fracture realizations, integrating with fluid simulators, and performing analysis.", + "laborHours": 1398.4, + "languages": [], + "name": "pySimFrac", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pySimFrac", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "We would like to create an open source repository in LANL's github on code written in Julia, in which we implement and extend the data-driven Mori-Zwanzig method for extracting large-scale spatio-temporal structures from data, which we call MZMD. This method is an extension of Dynamic Mode Decomposition (DMD) in which Mori-Zwanzig memory kernels are included into the associated companion matrix. In the code we would like to release, we apply MZMD to a flow over a cylinder with Reynolds number 100 rather than the much larger data set used in the associated manuscript. DMD is used extensively in the fluid dynamics community mainly for extracting large scale spatio-temporal structures (patters) from flow data. This is useful for understanding the key mechanisms that generate certain complex dynamical process relevant in engineering design. In MZMD, we improve upon DMD by adding the Mori-Zwanzig memory kernels, and show this improvement is especially important in strongly nonlinear regions of the flow.", + "laborHours": 304.0, + "languages": [], + "name": "Code for the manuscript \"Mori-Zwanzig Modal Decomposition\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MoriZwanzigModalDecomposition.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This Fortran code consists of multiple modules with a focus on simplifying array operations, image processing, and numerical computation especially for computational geophysics applications. We intend to use this code to demonstrate the application and usefulness of Fortran interface and templates for generic programming, especially for computational geophysics and seismology applications. The code has several notable features. Firstly, it is based on a modularized structure, where each module contains multiple functions but with a focus of functionality. Secondly, it heavily uses interfaces and templates for improving the genericness and convenience of the resulting code, where a same function interface can enclose a group of functions that perform the same functionality but with inputs/output variables of different data types. Thirdly, it includes a variety of generic functions with an emphasis on array operations, such as rotation, flipping, cropping, padding, fast Fourier transform, Gaussian blurring, interpolation, and so on. We name this package FLIP \u2013 a generic Fortran Library based on Interfaces and Templates.", + "laborHours": 33105.6, + "languages": [], + "name": "FLIT: A Generic Fortran Library based on Interfaces and Templates", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/flit", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "weberb@ornl.gov" + }, + "date": { + "created": "2024-07-15", + "metadataLastUpdated": "2024-07-15" + }, + "description": "Cyberwheel is a high fidelity training environment for autonomous cyber defense agents that includes both simulation and emulation capabilities. Cyberwheel simplifies customization of the training network and easily allows redefining the agent\u2019s reward function, observation space, and action space to support rapid experimentation of novel approaches to agent design. It also provides visibility into agent behaviors necessary for agent evaluation and sufficient documentation and examples to lower the barrier to entry.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Cyberwheel", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl/cyberwheel", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-07-15", + "metadataLastUpdated": "2024-08-26" + }, + "description": "A 3D microstructure resolving electrochemical transport and interfacial chemistry solver. \n\nElectrode microstructure plays an important role in determining the performance of an electrochemical system, e.g. lithium ion battery. EchemAMR is a microstructure scale model that solves the governing equations for ion transport, electrical current continuity, interfacial chemistry and structural mechanics. Complex microstructure geometries from imaging can be directly imported into EchemAMR. A volume fraction based description of the geometry on Cartesian grid with an immersed interface formulation enables simplified meshing and large-scale simulations with millions of degrees of freedom. EchemAMR has been tested against systems with analytic solutions for numerical convergence and highly resolved lithium ion battery microstructures. EchemAMR demonstrates excellent mass conversation and efficient scaling on heterogenous High-Performance Computing (HPC) with central and graphics processing units.", + "laborHours": 8253.6, + "languages": [ + "C++", + "HTML", + "C", + "Jupyter Notebook", + "MATLAB", + "Python" + ], + "name": "EchemAMR (electro-chemical microsctructure scale models with adaptive meshing) [SWR-23-111]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/echemAMR", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "LowFive is a new data transport layer based on the HDF5 data model, for in situ workflows. Executables using LowFive can communicate in situ (using in-memory data and MPI message passing), reading and writing traditional HDF5 files to physical storage, and combining the two modes. Minimal and often no source-code modification is needed for programs that already use HDF5. LowFive maintains deep copies or shallow references of datasets, configurable by the user. More than one task can produce (write) data, and more than one task can consume (read) data, accommodating fan-in and fan-out in the workflow task graph. LowFive supports data redistribution from n producer processes to m consumer processes.", + "laborHours": 212161.6, + "languages": [], + "name": "LowFive v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/diatomic/LowFive", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The event fanout-receiver is an event-based timing system implementation capable of synchronizing (with respect to clock, events and triggers) to an upstream event generator. This can be used in 2 modes: fanout or receiver. the first one receives 1 upstream timing streams and fanouts it to 36. The second one receives and decodes the stream. This has been in use by ALS for many years and this is a similar implementation, but providing a more flexible configuration", + "laborHours": 8618.4, + "languages": [], + "name": "Event Fanout/Receiver (evfr) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/LBNL-EVFR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The IMG Annotation Pipeline is a collection of Bash and Python scripts to control a workflow for structural and functional annotation of prokaryotic genomes, metagenomes, and metatranscriptomes. The bash scripts in general control the overall workflow and are wrappers around 3rd party executables (not included in repo) that predict features or functions. Whereas the Python scripts do post-processing of raw output in terms of filtering or format transformation and in some cases contain some logic for picking the correct predictions or resolving overlaps. The pipeline is tailored to produce results required by IMG (https://img.jgi.doe.gov/) and is executed on every dataset submitted to IMG via https://img.jgi.doe.gov/submit. These consist of internal genomes, metagenomes and metatranscriptomes sequenced and assembled at the JGI, as well as datasets submitted by external users (non-lab/JGI affiliates).", + "laborHours": 3556.8, + "languages": [], + "name": "IMG Annotation Pipeline (IMGAP) v5.1.13", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/img/img-pipelines/img-annotation-pipeline", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "This software helps the user mathematically determine the losses in a boost converter they are designing. They can enter the component parasitic values from their component datasheets, and the software will calculate exactly where the losses are coming from. This can help the designer target and reduce specific sources of loss. It also helps system engineers compare the losses between AC and DC versions of the boost converter. Finally, it establishes a set of mathematical equations to help academics study loss theoretically.", + "laborHours": 562.4, + "languages": [], + "name": "Boost Converter Loss Analysis v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dgerb/Boost-Converter-Loss-Analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "We created a cloud-based application for running AlphaFold2 and related structural programs called Foldy. Foldy is built on Helm / Kubernetes, which enables a facile production deployment and a scalable backend. Once set up by an institution, Foldy requires no software expertise from its users. It can be used to predict the structure of large proteins (up to 3000 amino acids), to visualize Pfam and antiSMASH annotations, and to perform ligand docking with Autodock Vina.", + "laborHours": 32224.0, + "languages": [], + "name": "Foldy v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/foldy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "nexport is a lightweight python 3 package which enables neural network developers to export the weights and biases of trained networks to useful file types. It provides I/O support for applications which require specific data types for instantiating neural networks in various inference environments. It was initially developed to support exporting to the data structure used by 'inference-engine', a Fortran inference package.", + "laborHours": 471.2, + "languages": [], + "name": "Neural Network Export Package (nexport) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/nexport", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Lasy is a Python library that facilitates numerical simulations of the interaction of complex laser pulses with plasmas.\n\nMore specifically, lasy offers many ways to define complex laser pulses (e.g. from commonly-known analytical formulas, from experimental measurements, etc.) and then computes and saves the corresponding laser field in a standardized file. This file can then be read by external plasma simulation codes, that will then simulate the interaction between the complex laser pulse and a plasma.\n\nLasy is useful for instance for numerical simulations of plasma-based particle accelerators, plasma-based laser amplification, etc. Lasy avoids having to duplicate the code that defines complex laser pulses in each plasma simulation codes, and instead provides a trusted, centralized implementation.", + "laborHours": 1763.2, + "languages": [], + "name": "lasy v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LASY-org/lasy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "This algorithm will identify the genesis and track the lifecycle of atmospheric rivers. It can be applied in different global atmospheric river detection algorithms. It is one of the earliest atmospheric river lifecycle tracking algorithms.", + "laborHours": 60.8, + "languages": [], + "name": "Depth-First Atmospheric River lifecycle Tracking (DART) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-EESA/DART", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Jupyter notebooks to reconstruct and visualize microCT data from ALS beamline 8.3.2. Relies on standard tomography and image processing tools (astra, tomopy, itk, scikit-image) and ipywidgets (sliders, drop down menus, etc) to make parameter selection and data visualization easy for users.", + "laborHours": 1854.4, + "languages": [], + "name": "als microct recon (microct) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/als-computing/microct", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Tsuchinoko is a Qt application for adaptive experiment execution and tuning. Live visualizations show details of measurements, and provide feedback on the adaptive engine's decision-making process. The parameters of the adaptive engine can also be tuned live to explore and optimize the search procedure.\n\nWhile Tsuchinoko is designed to allow custom adaptive engines to drive experiments, the gpCAM engine is a featured inclusion. This tool is based on a flexible and powerful Gaussian process regression at the core.\n\nA Tsuchinoko system includes 4 distinct components: the GUI client, an adaptive engine, and execution engine, and a core service. These components are separable to allow flexibility with a variety of distributed designs.", + "laborHours": 3967.2, + "languages": [], + "name": "Tsuchinoko v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/tsuchinoko", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-11-06" + }, + "description": "This software is a pipeline used to identify the distribution of user-specified sequences in oligo pools that have been sequenced on the MiSeq platform for quality control purposes. The software counts instances of user-specified sequences (inserts or spacers) identified in sequencing data, returning the distribution of sequences in each pool and the length distribution of all the sequences. Among other types similar types of projects, this can be used to assess the quality of a guideRNA library once it has been inserted into the vector of choice to ensure that there is an even distribution of all the individual protospacers in the pool.\n\nThis pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up.", + "laborHours": 1960.8, + "languages": [], + "name": "SynBio QC-Library QC (LibQC) v2.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.jgi.doe.gov/jgi-synbio-public/synbioqc-libqc/-/blob/main/LICENSE?ref_type=heads", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/jgi-synbio-public/synbioqc-libqc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-09-30" + }, + "description": "This software library serves as a Python wrapper for Geotab's Altitude API. It streamlines querying of the API, converts loosely structured API outputs into a standardized tabular data format, and enables analysis of the resulting data tables. It also includes example notebooks showing how to use the library.", + "laborHours": 668.8, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "Python wrapper library and analysis functions for Geotab Altitude API [SWR-24-77]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Geotab_Altitude_Wrapper", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "We have developed some scripts and tools that compliment an existing open-source product (Podman, https://podman.io/). This enables podman to function as a high-performance container solution. This capability is similar to Shifter and Singularity (both developed at LBNL). The advantage of leveraging Podman is it has greater support in the broader community outside of HPC and has capabilities missing from many of the HPC-only solutions.\n\nThe specific enhancements we wish to share our how to enable Podman to scale to very large HPC jobs and our integrations we have done to utilize high-performance interconnects and GPUs.", + "laborHours": 1140.0, + "languages": [], + "name": "Podman-hpc v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/podman-hpc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The ESnet SmartNIC is a collection of Verilog based FPGA design software, as well as drivers to interact with the FPGA. It provides an infrastructure framework for FPGA based hardware acceleration of network packet use cases. Different research and production applications can be easily written for the SmartNIC. Its advantage is that it reduces the development time for new applications by providing a pre-existing shell library for common functions.", + "laborHours": 15838.4, + "languages": [], + "name": "ESnet SmartNIC v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/esnet-smartnic-hw", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Build Optimization Software Tools (BOOST) accelerate the design of DNA, RNA and protein sequences for their synthesis and assembly in an automated and scalable fashion.\n\nThe BOOST Juggler automates the following two design tasks:\n- Reverse-Translation of protein sequences into DNA sequences\n- Codon Juggling of DNA sequences\n\nThe BOOST Polisher provides the following design tasks:\n- The Verification of DNA sequences against DNA synthesis constraints\n- The Modification of DNA sequences in case they violate any DNA synthesis constraint\nIn addition, the BOOST Polisher can be instructed to verify and modify DNA sequences against sequence patterns, such as restriction sites.\n\nThe BOOST Partitioner supports both Gibson/chewback and Yeast assembly (also known as Transformation-Associated Recombination, or TAR) methods when performing the decomposition of large sequences that exceed the maximum length of DNA synthesis into synthesizable building blocks. The Partitioner can be instructed to find building blocks with appropriate overlap sequences, making their assembly into the complete construct more efficient.\n\nBOOST Workflows enable, in a customized fashion, the execution of the Juggler, Polisher, and Partitioner tools on a batch of sequences.", + "homepageURL": "https://marketplace.lbl.gov/biosciences/computational-biology/BOOST", + "laborHours": 0.0, + "languages": [], + "name": "Build Optimization Software Tools (BOOST) v2.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/license-agreements-marketplace-licenses", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://marketplace.lbl.gov/biosciences/computational-biology/BOOST", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The program is expected to be a useful tool during operation of a range of solar-driven electrochemical devices, such as PV-electrolyzers and photoelectrochemical (PEC) devices. It makes use of current-voltage data collected during operation, operation parameters that are easily accessible for many devices of interest. The program captures the time-dependence of loss mechanisms at play during PEC device operation and opens the door for real-time optimizations of operational parameters like the feed humidity to minimize performance losses. Currently, the program is useful for applications where the current-voltage polarization response of the photoabsorber and electrolyzer are pre-recorded, and changes over time can be estimated based on the pre-recorded current-voltage scans. More complicated scenarios that involve permanent degradation of the PV component or complex calculations of the electrolyzer current-voltage characteristics may be included in future versions of this software. Aside from the possibility of deconvoluting loss mechanisms, this software can also reveal possible performance benefits by convective PV cooling when the photoabsorber is integrated into the electrolysis cell. The latter can highlight why certain device architectures may be beneficial over others. No similar technologies are known to the developer.", + "laborHours": 927.2, + "languages": [], + "name": "Current-Voltage Analysis Tool for Solar Fuel Production (CATS) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MEG-LBNL/Current-Voltage-Analysis-Tool-for-Solar-Fuel-Production-CATS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "With the falling costs of solar arrays and battery storage and reduced reliability of the grid due to natural disasters, small-scale local generation and storage resources are beginning to proliferate. However, very few software options exist for integrated control of building loads, batteries and other distributed energy resources. The available software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice, and are often incapable of operating independently of the grid during blackouts. In this software package, we present the \"Solar+ Optimizer\" (SPO), a control platform that provides demand flexibility, resiliency and reduced utility bills, built using open-source software. SPO employs Model Predictive Control (MPC) to produce real time optimal control strategies for the building loads and the distributed energy resources on site. SPO is designed to be vendor-agnostic, protocol-independent and resilient to loss of wide-area network connectivity. The software was evaluated in a real convenience store in northern California with on-site solar generation, battery storage and control of HVAC and commercial refrigeration loads. Preliminary tests showed price responsiveness of the building and cost savings of more than 10% in energy costs alone.", + "laborHours": 20200.8, + "languages": [], + "name": "SolarPlus-Optimizer v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/SolarPlus-Optimizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-18" + }, + "description": "Drishti is a command-line tool to guide end-users in optimizing I/O in their applications by detecting typical I/O performance pitfalls and providing a set of recommendations.", + "laborHours": 1170.4, + "languages": [], + "name": "Drishti v0.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/drishti", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-18" + }, + "description": "Markov chain Monte Carlo sampler useful for a variety of problems for optimization, numerical integration, and generating draws from a probability distribution. They are often used in physical and mathematical problems, especially when it is difficult or impossible to use other approaches.\n\nThis disclosure is for new bug fixes and enhancements to an existing open source library that is already in the public domain under the MIT license.\nhttps://github.com/jellis18/PTMCMCSampler", + "laborHours": 1246.4, + "languages": [], + "name": "Bug fixes / enhancements to Parallel tempering Markov chain Monte Carlo sampler (PTMCMCSampler) v3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nanograv/PTMCMCSampler", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-17" + }, + "description": "The program extends the analysis capabilities of existing profilers through additional analysis to provide insights about communication computation overlap, communication modeling, and broad performance summaries of CPU, GPU and memory. This allows users to understand how their applications are spending time and where performance bottlenecks are.", + "laborHours": 410.4, + "languages": [], + "name": "NEthing v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/nething", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-17" + }, + "description": "This is a security automation tool heavily influenced by the tool written at NCSA https://github.com/ncsa/bhr-site.\n\nThe tool is a web interface that aims to centralize information on blocking malicious traffic. There is a list of currently blocked traffic, a place for other tools to automatically add traffic they deem malicious, as well as for human users to input blocks.\n\n* Logging and auditing, to determine who made what change and when\n* Automated expiration of changes (e.g. an exception is added for 2 weeks, after which time it will be removed)\n* Validation of changes and verification that the change has been applied\n* Fine-grained role-based access", + "laborHours": 2888.0, + "languages": [], + "name": "Security Catch and Release Automation Manager (SCRAM) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet-security/scram", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-17" + }, + "description": "This is an announcement service for JupyterHub that JupyterHub admins can manage through a JupyterHub-styled UI. JupyterHub administrators can use it to communicate with their hub's users about status, upcoming outages, or share news. It allows admins to post a current announcement, and show previous announcements in reverse chronological order. It provides a REST API hook that admins can use to post the latest announcement on JupyterHub itself (with custom templates).", + "laborHours": 440.8, + "languages": [], + "name": "jupyterhub-announcement v0.8", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rcthomas/jupyterhub-announcement", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-17" + }, + "description": "This repository will host the software, data models and documentation developed as part of the California Energy Commission (CEC) funded California Load Flexibility Research and Development Hub (CalFlexHub) project. The main objectives of CalFlexHub are:\n- Identify, develop, evaluate, demonstrate and deploy cost-effective, scalable, building load-flexible (LF) technologies that are consistent with building energy efficiency, appliance, and load management standards.\n- Create a portfolio of LF RDD&D technology projects across various building types and sizes including single-family-residential, multi-family, commercial buildings and integrated campuses.\n- Deploy LF technologies to demonstrate the ability for 99% of the state's customers to receive the load management standards price and marginal GHG signals.", + "laborHours": 60.8, + "languages": [], + "name": "California Load Flexibility Research and Development Hub (CalFlexhub) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/CalFlexHub", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-07-18", + "metadataLastUpdated": "2024-07-18" + }, + "description": "The software contains\n(a) the source codes to generate Point-on-Wave (PoW) transient data for any feeder model in Alternative Transient Program\n(ATP) format. Codes provide options to change different steady state settings, including the loading condition and PV\ncapacity and transient state setting like faults type, location and initiation time\n(b) data post-processing source code to converted data from native format to COMTRADE, csv, HDF5\n(c) Docker container to train CNN to classify fault locations by protective zone. The container takes dataset and other\ntraining parameters (sampling rate, training epochs, batch size etc) as input to train CNN. The container writes back the\ntrained CNN model, training and testing metrics and plots to the local workstation", + "laborHours": 501.6, + "languages": [], + "name": "Data-Driven Protection Software to classify fault locations by protective zone in distribution systems with high PV penetration", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/oedisi_transients", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-18", + "metadataLastUpdated": "2024-07-18" + }, + "description": "Despite advances in microscopy, imaging techniques only capture a very small spatial and temporal fraction of T cell activity within a tissue. For this reason, we have pursued the development of a virtual T cell model. Matcha's objective is to design virtual T cells that move like biological T cells. The virtual T cells will match the speed and turning angle distributions of biological cells. In addition, Matcha will also attempt to match the volume patrolled by the biological cells and the dependence on speed and turning angle on the previous speed.", + "laborHours": 790.4, + "languages": [], + "name": "Motility Analysis of T-Cell Histories in Activation (Matcha) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/matcha", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-18", + "metadataLastUpdated": "2024-07-18" + }, + "description": "As demand flexibility becomes more common, the mix and frequency of a range of demand flexibility strategies will introduce potential biases into baselines, i.e., the time period immediately prior to a LS event may include other LS or DF events. Baseline degradation assessment provides an approach to quantify how these biases begin to compromise predictive accuracy. Heatmaps, based on each month of the year provides a granular view of a given model's predictive capability. However, for comparing multiple algorithms, separately for weekdays and weekends, aggregating results to seasons provides a simpler means of comparison while still allowing for review of variations by time of day and time of year", + "laborHours": 1398.4, + "languages": [], + "name": "Grid Services Load Shift Baseline Degradation Analysis Methodology v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sgfernandes/Loadshift", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-07-22", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The DeepLynx Airflow Provider Package is a python package used to interact with the data warehouse DeepLynx when using the workflow orchestration tool Apache Airflow. This python package is packaged together using the airflow package standard so that it can be easily installed and used in any Apache Airflow environment. This package is meant to encapsulate the DeepLynx API for use in Airflow so that any interactions with DeepLynx that a user may want to use in their Airflow workflow can be easily accomplished using this provider package. This allows us to develop, implement, and test our DeepLynx-Airflow interactions in one provider package repository, and then easily install and use this package in any airflow instance. This DeepLynx Airflow Provider Package will be used extensively by the DeepLynx DAG repository.", + "laborHours": 1079.2, + "languages": [ + "Python" + ], + "name": "Deeplynx Airflow Provider Package", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/airflow-provider-deeplynx", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-07-23", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Code allows users to easily pull publications from PubMed, OSTI, and SCOPUS\u037e identify biological terms and extract\ntheir contexts from these papers\u037e and determine which terms are related to other terms using one of the eleven wrapped\nalgorithms", + "laborHours": 501.6, + "languages": [], + "name": "Natural Language Processing for Biological Relationship Extraction", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/biological_relationship_extraction", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-23", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This is a repository for scripts and documents to help reproduce the results in \"A Global Phylogenomic Analysis of the Shiitake Genus Lentinula\".", + "laborHours": 516.8, + "languages": [], + "name": "Scripts for \"A Global Phylogenomic Analysis of the Shiitake Genus Lentinula\" v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/jgi-lentinula/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-23", + "metadataLastUpdated": "2024-07-26" + }, + "description": "iPHoP is a bioinformatic tools that uses a set of approaches to predict the potential host of novel bacteriophages (viruses infecting bacteria) that are only known by their genome sequence, and not cultivated in the laboratory. Existing technologies typically rely on a single method, and the main advantage of iPHoP is its ability to integrate the results from multiple methods into a single prediction. This is of interest for microbial ecology researchers, as they often analyze novel bacteriophage genomes that they were able to assemble from metagenomes, but they don't know which bacteria these phages infect.", + "laborHours": 3116.0, + "languages": [], + "name": "Integrated Phage-Host Prediction tool (iPHoP) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/srouxjgi/iphop", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-23", + "metadataLastUpdated": "2024-07-23" + }, + "description": "BioParts is a web based search portal for biological parts available in the public domain. It combines the ease and convenience of modern web search engines with the capabilities of bioinformatics search tools such as BLAST. This portal, available at bioparts.org, allows anyone to search for publicly accessible biological part information (e.g., NCBI, iGEM, SynBioHub, Addgene), including parts publicly accessible through ICE Registries. Additionally, the portal offers a REST API that enables third-party applications and tools to access the portal's functionality programmatically. While there are several standalone biological part repositories, there doesn't exist an application that indexes these publicly available parts and enables features such as keyword and BLAST searches along with automatic sequence annotation.", + "laborHours": 27694.4, + "languages": [], + "name": "Biological Parts Search Portal (BioParts) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/BioParts", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-24", + "metadataLastUpdated": "2024-07-24" + }, + "description": "This software library presents efficient and multithreaded implementations of matrix low rank approximation via column selection in C++17 code. The algorithms are described in Fornace, Mark, and Michael Lindsey. \"Column and row subset selection using nuclear scores: algorithms and theory for Nystro m approximation, CUR decomposition, and graph Laplacian reduction.\" arXiv preprint arXiv:2407.01698 (2024). The presented methods are by-and-large ver novel, have provable approximation guarantees, multiple use-cases, and exhibit higher quality approximations on a variety of studied examples.", + "laborHours": 927.2, + "languages": [], + "name": "nuclear-score-maximization v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfornace/nuclear-score-maximization", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-24", + "metadataLastUpdated": "2024-07-31" + }, + "description": "The software has two main features: (1) identify data movement trends in HPC data centers that use network flow monitoring (2) analyze the performance of individual data flows under the existing data movement management strategy and identify performance bottlenecks that impede timely data availability for science workflows. Its main advantage is that it is tailored for HPC network traffic by considering HPC data movement management intricacies.", + "laborHours": 349.6, + "languages": [], + "name": "Network performance analysis for HPC datacenters (net_perf) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/annna-gian/nersc_net_perf.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-07-26", + "metadataLastUpdated": "2024-07-26" + }, + "description": "system2atoms is a suite of models that can simulate the performance of hydrogen\ninfrastructure across multiple scales. Examples of the different scale levels include:\n1. System Scale - techno-economic analysis for hydrogen applications,\nintegration of hydrogen infrastructure with the electrical grid,\nand supply and demand constraints across applications\n2. Component Scale - continuous-flow catalyst beds, electrochemical conversion\nunits, gas-phase separators, pumps, compressors, storage tanks, evaporators,\nheaters, and coolers\n3. Material Scale - surface reactions, degradation mechanisms, and catalyst\npoisoning", + "laborHours": 20079.2, + "languages": [], + "name": "system2atoms", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/systems2atoms", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-27", + "metadataLastUpdated": "2024-07-27" + }, + "description": "SAND2021-14236 O\nPMatch is a function matching plugin for Ghidra. PMatch uses hashing and p-code to create function databases and complete function matching on other binary files. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 349.6, + "languages": [ + "Python" + ], + "name": "PMatch v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/halucinator_PMatch", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-27", + "metadataLastUpdated": "2024-07-27" + }, + "description": "SAND2022-4247 O\nLocOO3d is used to estimate the location of seismic events by comparing estimates of the arrival time for seismic waves from hypothesized locations to observed arrival times. LocOO3d also computes errors in estimated locations through the computation of an \u201cerror ellipsoid\u201d around the optimal event location.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 291095.2, + "languages": [], + "name": "LocOO3d v.1.1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Salsa3DSoftware", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-27", + "metadataLastUpdated": "2024-07-27" + }, + "description": "SAND2022-4256 O\nOnline version control platforms offer insight into traffic and engagement with source code repositories, but only in limited ways and over short windows of time. Scientific software teams at Sandia National Laboratories and elsewhere want to collect and store engagement data to help tell their story and the impact their work has on the community. Repometer aims to supplement existing capabilities by collecting timely and insightful data from GitHub and GitLab repositories and passing it to a database for longer-term storage.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1793.6, + "languages": [ + "Python" + ], + "name": "Repometer v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Repometer", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-27", + "metadataLastUpdated": "2024-09-12" + }, + "description": "SAND2022-13232 O\nThe sbovqaopt package provides a surrogate-based optimizer for variational quantum algorithms as introduced in the journal publication of the same title. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "sbovqaopt: Surrogate-based optimizer for variational quantum algorithms v.0.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sbovqaopt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-07-29", + "metadataLastUpdated": "2024-07-29" + }, + "description": "Lack of harmonic rich datasets limits the ability to have fine grained load models at grid edge. We aim to develop\nmathematical models for power electronic based load combinations at grid edge to help replicate current and future\nevolving load conditions", + "laborHours": 30.4, + "languages": [], + "name": "Continual Load Modelling", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Continual-Load-Modelling-HELM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "klaskyhb@ornl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "The program summarizer.py is the product of the 'Automating Data Collection with Large Language Models (LLMs): Summarization and CSV Generation' project. This project aims to automate data collection from Internet content using LLMs. This project integrates zero-shot learning concepts, as the agents were not previously trained on the particular subjects of the inputted sources, and Retrieval Augmented Generation (RAG).\nThis summarizer program summarizes characteristics of the URL sources which are specified by the user. As written, the program identifies six characteristics of the inputs: source_name, source_creator, source_url, source_overview, source_data, and number_of_datapoints. However, this program is designed to be highly generalizable, so throughout the code, docstrings specify what parameters and variables should be changed for the user to utilize this program on their own inputs and characteristics. This repository contains example outputs for two datasets: one on the health effects of air pollutions and one on congenital heart defects.", + "laborHours": 258.4, + "languages": [ + "Python" + ], + "name": "Automating Data Collection with Large Language Models: Summarization and CSV Generation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/summer_2024/summarization", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "Summer 2024" + }, + { + "contact": { + "email": "klaskyhb@ornl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "Given the text files of LLM outputs for specific variables about numerous databases and the reference Excel sheets to compare the LLM outputs to, this program will generate Excel sheets and CSV files of evaluations to describe the LLMs' performances. When the program is executed, these files can be located in ./evals. All folders within ./evals are named by the time which the program finished.\nThe main focus of this pipeline is to evaluate the database descriptions using BERTScore, SacreBLEU, and MoverScore. However, multiple different types of metadata aside from descriptions.", + "laborHours": 410.4, + "languages": [ + "Python" + ], + "name": "Large Language Model Output Evaluator", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/summer_2024/llm_output_evaluation", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "Summer 2024" + }, + { + "contact": { + "email": "klaskyhb@ornl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "This project evaluates a set of prompts to test their performance on specific tasks for large language models (LLMs), in order to find the optimal prompt to enhance task performance.", + "laborHours": 1018.4, + "languages": [ + "Python" + ], + "name": "Complete Prompt Permutation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/summer_2024/prompt_engineering/complete-prompt-permutation", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "Summer 2024" + }, + { + "contact": { + "email": "klaskyhb@ornl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "This project evaluates a set of prompts to test their performance on specific summarization tasks for large language models (LLMs), in order to find the optimal prompt to enhance task performance. This is a slightly more generalized version of the complete-prompt-permutation project, with different strengths.", + "laborHours": 304.0, + "languages": [ + "Python" + ], + "name": "Template Prompt Permutation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/summer_2024/prompt_engineering/template-prompt-permutation", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "Summer 2024" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "This is a C ++ acquisition API for neurophysiological data in the NeurodataWithoutBorders (NWB) data standard.", + "laborHours": 1869.6, + "languages": [], + "name": "AqNWB v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NeurodataWithoutBorders/aqnwb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "Code to organize, prepare, and segment multi-scan, larger-than-memory, volumetric dataset. Deep learning segmentation uses pytorch-lightning for code organization, logging and metrics, and multi-GPU parallelization of training and prediction. Also uses moani for volumetric data augmentation and model implementation (currently U-Net++). Training can be done slice-by-slice with 2D models trained on 2D patches either aligned with or perpendicular to the electrode plane, or with 3D models on 3D patches. Sparse labels can be used to minimize required hand-labeling -- less than 0.1% of the entire dataset was labeled. Also includes code for data preparation (alignment/cropping/patching).", + "laborHours": 714.4, + "languages": [], + "name": "batteryNET v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/batteryNET", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-31", + "metadataLastUpdated": "2024-07-31" + }, + "description": "SAND2024-08428O\nThe IDB Loader is a database designed to hold gamma spectra. IDB is a web-accessible database of reference gamma spectra for measuring uranium (U) and plutonium (Pu) isotopic composition. The database, developed by the International Atomic Energy Agency (IAEA), provides access to well-characterized groups of gamma spectra curated by international experts in gamma spectroscopy. It was created to promote sustainability and maintenance of software used to determine the isotopic abundances of U and Pu. The IDB Loader works by uploading one set of spectral data into an existing IDB. The Data Loader package includes documentation describing the IDB's table, the format of the spectral data, and a description of the loader program. The IDB is currently hosted by the IAEA at: https://nds.iaea.org/idb \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 4104.0, + "languages": [ + "Java" + ], + "name": "IDB Loader", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IDB_Loader", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-08-01", + "metadataLastUpdated": "2024-09-12" + }, + "description": "Publicly available collections of drug-like molecules have grown to comprise tens of billions of compounds\ndue to advances in combinatorial chemistry. Traditional methods for identifying \"hit\" molecules from a\nlarge collection of potential drug-like candidates have relied on biophysical theory to compute\napproximations to the Gibbs free energy of the binding interaction between the drug and its protein target.\nThese approaches have the major drawback that they require exceptional computing capabilities for\neven relatively small collections of molecules.\nHyperdimensional Computing (HDC) is a recently-proposed learning paradigm that represents data with\nhigh-dimension binary vectors; this allows the use of low-precision binary vector arithmetic to create\nmodels of the data that can be learned without the need for the gradient-based optimization required in\nmany conventional machine learning and deep learning methods. This algorithmic simplicity allows for\nacceleration in hardware that has been previously demonstrated in a range of application areas. We\nconsider existing HDC approaches for molecular property classification and introduce two novel\nencodings of a commonly-used molecular representation, the extended connectivity fingerprint (ECFP).\nWe show that HDC-based inference methods are as much as 91 times more efficient than traditional\nmachine learning methods, and achieve an acceleration of nearly nine orders of magnitude compared to\nmolecular docking. Our results show that HDC accelerated methods retain competitive accuracy on a\nnumber of well-studied tasks such as molecular property predictions using the MoleculeNet dataset, and\nbind/no-bind activity classification using the DUD-E and LIT-PCBA datasets.\nOur work thus motivates further investigation into molecular representation learning to develop ultraefficient\npre-screening tools.", + "laborHours": 6064.8, + "languages": [], + "name": "HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/hdbind", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-02", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Pore2Chip is a Python module designed to streamline the process of analyzing X-ray computed tomography (XCT) images\nof soil and creating 2D micromodel designs based on that analysis.", + "laborHours": 11962.4, + "languages": [], + "name": "Pore2Chip", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-Computing/Pore2Chip", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-05", + "metadataLastUpdated": "2024-08-05" + }, + "description": "An R package built to match proteoform isotoping distributions to mass spectrum, quantitatively select\nmatches of high quality, and visualize those matches in a trelliscope display.", + "laborHours": 3085.6, + "languages": [], + "name": "IsoMatchMS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-HubMAP-Proteoform-Suite/IsoMatchMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-05", + "metadataLastUpdated": "2024-08-05" + }, + "description": "Benchmark dataset that harmonizes drug\nresponse data across thousands of patient samples and cancer model systems enabling the training and benchmarking of\nAI/ML algorithms at scale.", + "laborHours": 112662.4, + "languages": [], + "name": "CoderData", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/coderdata", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-08-05", + "metadataLastUpdated": "2024-08-05" + }, + "description": "The present work details the creation of a high-fidelity Monte Carlo methodology for analyzing the run-in and subsequent approach to equilibrium for PBRs. The methodology entails a Python module wrapped around Serpent so as to perform neutronics calculations, move pebbles, refuel the core, and discharge pebbles, thereby modeling the explicit behavior of the PBR run-in. The code kugelpy is within the GitHub repository `pyrates`.", + "laborHours": 3116.0, + "languages": [ + "Python" + ], + "name": "Framework For Performing Time-dependent Pebble Bed Reactor Simulations", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/kugelpy", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-08-05", + "metadataLastUpdated": "2024-08-05" + }, + "description": "The code here provides the training/testing of using Fourier Neural Operator for geological carbon storage applications", + "laborHours": 456.0, + "languages": [], + "name": "3D FNO model for geological carbon storage", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qingkaikong/3DFNO_GCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-06", + "metadataLastUpdated": "2024-09-12" + }, + "description": "The Fortran programming language standard defines a broad feature set supporting the interoperability of Fortran programs with program written according to the C programming language standard. Among Fortran's C-interoperability features is a a C header file \"ISO_Fortran_binding.h\" This header file defines the interface to various C data structures and functions that C programs may use to access Fortran data entities. The ISO_Fortran_binding_m software defines a native Fortran module that presents an interface to these same data structures and functions. ISO_Fortran_bind_m thus enables Fortran programs to access and manipulate Fortran entities in ways that precisely mirror what C programs can do using ISO_Fortran_binding.h. ISO_Fortran_binding_m facilitates writing portable standard-conforming Fortran programs that emulate non-interoperable features, e.g., dynamic polymorphism, in a standard-conforming interoperable way similar but broader than what is demonstrated in Berkeley Lab's Caffeine software [1]. ISO_Fortran_binding_m also enables a Fortran programmer to extend Fortran's capabilities to emulate certain C functionality such as memory address arithmetic or computing C's \"sizeof\" function.\n\n[1] https://github.com/BerkeleyLab/caffeine/blob/213e3df1c319f0663306354414f352acda42a24f/src/caffeine/collective_subroutines/co_reduce_s.f90#L88\n[2] https://github.com/BerkeleyLab/ISO_Fortran_binding_m/blob/0c585362bb4f2c72cf9049c800a7115b529ec533/src/iso_fortran_binding_m.F90#L196", + "laborHours": 167.2, + "languages": [], + "name": "ISO_Fortran_binding_m v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/ISO_Fortran_binding_m", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-06", + "metadataLastUpdated": "2024-08-06" + }, + "description": "Julienne is a compiler-portable unit-testing framework for Fortran software projects, including those that use the parallel/accelerator-programming features of Fortran 2023. Julienne achieves portability across compilers through minimalism and isolation. The minimal design ensures that Julienne uses only features supported by the majority of Fortran compilers. The isolation through zero dependencies ensures that no other projects block Julienne from building with a particular compiler.\n\nJulienne also contains with additional services that support its unit-testing code. These include functions for manipulating strings, command lines and input/output format strings; and a user-defined collective subroutine for verifying that all processes pass a test in parallel testing.\n\nJulienne's name derives from the term for vegetables sliced into thin strings: julienne vegetables. Julienne captures the authors' most frequently used thin slice of the Veggies and Sourcery software repositories while avoiding certain compiler limitations of the those two packages.", + "laborHours": 972.8, + "languages": [], + "name": "Julienne v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/julienne", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-06", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The Mbin software, is a software toolkit that implements the IMG metagenome binning pipeline. The software allows the user to process input metagenome contigs, and produces metagenome assembled genomes (metagenome bins) and valuation metrics per bin including completion and contamination estimates, quality assignment, predicted lineage and eukaryotic potential. It is currently packed as a portable docker container and provides the advantage of running the process of binning and analysis of the bins generated, using a suite of tools run sequentially with controls in place to capture errors and optional arguments to run a modified version depending on individual needs and capabilities.", + "laborHours": 0.0, + "languages": [], + "name": "Mbin v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/metagenome-science-program/mbin-docker", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-06", + "metadataLastUpdated": "2024-08-07" + }, + "description": "The levelized cost of avoided CO2 (LCAC) tool facilitates techno-economic calculations for various decarbonization technologies. It comprises two components to accomplish this: an input workbook based on MS Excel and a web-based output tool. The workbook acts as the input sheet, using the user-provided decarbonization measures and their impacts on lifetime energy consumption, energy costs, and CO2 emissions to compute LCAC (expressed in $/metric ton of avoided CO2). The workbook is uploaded to a web-based tool to generate an LCAC curve. This graphical representation illustrates the economic comparison of all decarbonization measures for purposes such as implementation prioritization. We are unaware of any publicly available tools with similar capabilities.", + "laborHours": 881.6, + "languages": [], + "name": "Levelized Cost of Avoided CO2 tool (LCAC tool) v0.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IACDecarb/IAC-Decarb-Tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-06", + "metadataLastUpdated": "2024-08-13" + }, + "description": "Facility CO2 Flow Tool assists facilities and entities to visualize their CO2 flows for accounting and decarbonization purposes. To do so, the suite offers two components \u2013 an MS Excel-based input workbook and a web-based visualization tool. The workbook serves as the input sheet, utilizing the user-provided process and equipment-level energy consumption data to calculate the corresponding CO2 emissions. The web-based tool utilizes the data from this workbook to generate a Sankey diagram. This diagram visually represents the CO2 flow originating from the fuel and electricity consumption within the facility/entity boundary.", + "laborHours": 881.6, + "languages": [], + "name": "Facility CO2 Flow Tool (FCFT) v0.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IACDecarb/IAC-Decarb-Tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-08-07", + "metadataLastUpdated": "2024-12-11" + }, + "description": "Via-wind is an open-source tool for conducting visual impact assessments for wind turbines.\n\nIt combines geographic information system (GIS) and 3D simulation methods to account for the key factors driving the visual impact of installed wind turbines, including distance, viewing angle, turbine orientation, visual exposure, and the cumulative effects of multiple turbines.\n\nThis software is optimized for use in high-performance computing environments to enable large scale (e.g., country-wide) analysis, but can also be run on a single server or personal computer.\n\nFor more information, please see the related journal article: https://www.sciencedirect.com/science/article/pii/S0306261924021846", + "laborHours": 1900.0, + "languages": [ + "Python" + ], + "name": "via-wind (A Visual Impact Assessment Tool for Wind Turbines) [SWR-24-87]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/via-wind", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.12" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-08-08", + "metadataLastUpdated": "2024-08-26" + }, + "description": "The Django Query Logger (DQL) is a tool that allows developers of Django web applications to stream the raw database queries that are being executed in real-time from any Django application for review, profiling, filtering, formatting, and analysis.\n\nReference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or Alliance for Sustainable Energy, LLC. The views and opinions of authors expressed in the available or referenced documents do not necessarily state or reflect those of the United States Government or Alliance.", + "laborHours": 562.4, + "languages": [ + "TypeScript", + "SCSS", + "HTML" + ], + "name": "DQL (Django Query Logger) [SWR-24-96]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/django-query-logger", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-08", + "metadataLastUpdated": "2024-09-12" + }, + "description": "LTAU (Loss Trajectory Analysis for Uncertainty) is a technique for estimating the uncertainty in a model's\npredictions for any regression task by approximating the cumulative distribution function (CDF) of the\nmodel's errors over the course of training. The approximated CDF, combined with a similarity search\nalgorithm in the model's descriptor space, can then be used to estimate the likelihood that the model's\npredictions on any given test point will fall below a chosen threshold. LTAU-FF (LTAU in atomistic Force\nFields) is the application of LTAU specifically for use with atomistic force fields.", + "laborHours": 896.8, + "languages": [], + "name": "LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ltau-ff", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-08", + "metadataLastUpdated": "2024-08-08" + }, + "description": "Global Pathway Selection (GPS) is an algorithm to effectively generates reduced (skeletal) chemistry\nmechanisms, which speeds up simulations and can be used as a systematic analytics tool to extract\ninsights from complex reacting system. This release is an extension of the original code to run in parallel\nand to use LLNL's Zero-RK solver for fast solution of chemical problems.", + "laborHours": 10351.2, + "languages": [], + "name": "Global Pathway Selection with Zero-RK", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GPS-Z", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.4" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-08", + "metadataLastUpdated": "2024-09-12" + }, + "description": "QUESTS provides a strategy to quantify the uncertainty and the information content (entropy) of datasets\nof atomistic simulations. The code implements the calculation of a descriptor, compares information\ncontents of datasets, verifies whether given structures are contained in specific datasets, and more. This\ncode base enables better design of training sets for machine learning force fields as well as\nunderstanding some thermodynamic properties of materials.", + "laborHours": 714.4, + "languages": [], + "name": "QUESTS: Quick Uncertainty and Entropy from STructural Similarity", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dskoda/quests", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2025-02-24" + }, + "description": "This algorithm can process small or large (>1000 curves) batches of data and output arrays with the reduction peak start,\nend, halfway point, and area in each curve in a file of the user's choice", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 532.0, + "languages": [], + "name": "Automated Quantification of Cyclic Voltammetry Reactions", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This software contains the code for a machine learning-based pipeline for creating persistent waterbody databases used in hydrologic routing. It consists of three components, 1) a PyTorch library (TorchWBType) for classifying/labeling arbitrary waterbodies into lakes and non-lakes, 2) a batch processing orchestrator (wbextractor) for delineating waterbodies from remote sensing imagery, and 3) graphing/analysis scripts for reproducing the plots in an associated journal article (LA-UR-24-22590).", + "laborHours": 1140.0, + "languages": [], + "name": "High resolution hydrologic routing with machine learning assisted waterbody classification", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VeinsOfTheEarth/waterbody_classification_ms", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "Algorithms for phylogenetic tree inference.", + "laborHours": 456.0, + "languages": [], + "name": "Inferring trees from limited data", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/distphylo", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "The code provides machine learning, data collection, and computer science tools used to detect undocumented orphaned wells in United States from aerial imagery.", + "laborHours": 258.4, + "languages": [], + "name": "UOWDetection", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/uow", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "AdvEP is a code repository which contains PyTorch implementations of various adversarial attacks on a deep neural network trained with Equilibrium Propagation (EP), which is a neuromorphic learning framework. AdvEP allows for the training, testing, and conducting white/black-box attacks of EP models on a wide variety of applications and datasets. AdvEP is based on the open-source code https://github.com/Laborieux-Axel/Equilibrium-Propagation which was developed to train energy models. AdvEP was created by modifying the original code to perform and test against adversarial attacks. AdvEP was developed in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning. AdvEP interfaces heavily with the open-source PyTorch Python package as well as the open-source Adversarial Robustness Toolbox (ART) package.", + "laborHours": 4058.4, + "languages": [], + "name": "AdvEP", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/AdvEP", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "Much strain-specific sequence data exists in research conducted before the deployment of large sequencing repositories, making it challenging to identify and validate the identity of strains used in these studies through bioinformatics and phenotyping. The American Type Culture Collection (ATCC) is an organization that sells a wide variety of microbes with strain-level taxonomy classification and associated sequenced reference genomes. Currently, ATCC does not provide a method for searching for sequence similarity between a query sequence and their database of reference genomes. Here I propose the software ATCCfinder, which utilizes ATCC application interface software (API) to generate query-able databases from ATCC Genome resources.", + "laborHours": 349.6, + "languages": [], + "name": "ATCCfinder - Download and Search the ATCC Genome Portal", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ATCCfinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This software enables the calculation of the pressure field based on experimental velocity measurements utilizing the matrix-based omnidirectional pressure integration algorithm developed by Dr. John Charonko and Dr. Fernando Zigunov, which is several orders of magnitude faster than the current state of the art.", + "laborHours": 2401.6, + "languages": [], + "name": "Matrix-based Omnidirectional Pressure Integratio", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pressure-osmosis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This code is a collection of python code that defines, trains, and tests Log-Additive Convolutional Neural Networks. The model components and training routine are based on the PyTorch python library. The code implements the Log-Additive Convolutional Neural Networks as described in Pagendam et al. 2023. In addition to the Log-Additive Convolutional Neural Networks, this library also defines the Log-Normal Density loss function as described in Pagendam et al. 2023. Code from this paper is not publicly available, so the Pytorch implementation of this type of model is unique to this library.", + "laborHours": 744.8, + "languages": [], + "name": "PyTorch Implementation of Log-Additive Convolutional Neural Networks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pagendam-callis-groundwaterML", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "We plan to release the code used to perform the experiment described in our recent publication, entitled \u201cDetermining the dominant factors for carbon-1 mineralization in three-dimensional fracture networks.\u201d This code fits a joint emulator to data from several Discrete Fracture Network (DFN) simulations, performed using the open-source software DFNworks (https://dfnworks.lanl.gov/). All code to be released implements existing methods; there are no novel algorithms nor any major innovations to existing software.", + "laborHours": 4043.2, + "languages": [], + "name": "Code for Experiment in Publication \u201cDetermining the dominant factors for carbon-1 mineralization in three-dimensional fracture networks\u201d", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/mineralization_dfnworks", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "The software provides machine learning analysis and visualization to detect patterns in epigenetic data, including conventional machine learning and statistical methods, and open-source packages like pyBigWig (https://github.com/deeptools/pyBigWig) for data processing. The software is written in python, it uses some python libraries.", + "laborHours": 1200.8, + "languages": [], + "name": "Machine learning tools for epigenetics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/epigen", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This Fortran code is to accompany a manuscript to be submitted to Computers & Geosciences, a high-impact, peer-reviewed journal in computer methods for geosciences research. \n\nThis Fortran code focuses on generation of synthetic geological models using a multi-randomization strategy. Generating high-fidelity synthetic geological models, including realistic seismic reflector migration images, faults, salt bodies, and relative geological time images, is the key for many supervised machine learning methods that aim to delineate faults and other geological properties of interest from seismic migration images. Our package contains two major functionalities: generating 2D synthetic random geological models and generating 3D synthetic random geological models. In each step of the generation process, we set random values for key properties of a geological model to improve the fidelity of the resulting geological model. The package also includes example codes on how to use the random geological model generation subroutines. We name this package RGM \u2013 Random Geological Model generation package.", + "laborHours": 2280.0, + "languages": [], + "name": "RGM: Random Geological Model Generation Package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/rgm", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This Fortran code focuses on traveltime computation and tomography based on eikonal equation. Specifically, the package provides three major functionalities: (1) forward modeling of traveltime from single-point or ensemble source based on factorized eikonal equation, (2) adjoint-state first-arrival traveltime tomography based on picked first arrival traveltime using steepest descent, conjugate gradient, or limited-memory BFGS inversion scheme, and (3) adjoint-state joint transmission-reflection tomography based on picked first-arrival and reflection traveltimes. The package applies to forward modeling and tomography based on traveltime in 2D and 3D isotropic regular-grid models. We name this package LATTE \u2013 Los Alamos TravelTime package based on Eikonal equation. \n\n* The code is for accompanying a journal paper under preparation. The paper will be submitted via LA-UR separately later.", + "laborHours": 7949.6, + "languages": [], + "name": "LATTE: Los Alamos TravelTime package based on Eikonal equation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/latte_traveltime", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This software is being developed to link infectious disease sequence data to epidemiological models to support forecasting efforts for public health impact. More specifically, this software will allow data analysis, feature extraction, data synthesis, inference, and forecasting of sequence data for infectious diseases (e.g., COVID, flu, dengue) and forecasting of public health outcomes (e.g., cases, hospitalizations, deaths).", + "laborHours": 638.4, + "languages": [], + "name": "Program Repository for Tools for Analyzing Infectious Disease Sequence Data and Forecasting Public Health Outcomes", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/precog", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This software is developed for researchers to evaluate the energy performance of of dynamic windows in the world-wide climate, and this first version focuses on thermochromic windows. We bring new indicators (necessity level and recommendation index) to the evaluation system for thermochromic windows. We estimate the majority users of this software tool will be non-commercial academic researchers. But commercial companies can also use it to optimize their products and estimate where their product has the most promising market.", + "laborHours": 258.4, + "languages": [], + "name": "PyDynamicWindow v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/PyDynamicWindow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "myoon@ornl.gov" + }, + "date": { + "created": "2024-08-13", + "metadataLastUpdated": "2024-09-17" + }, + "description": "In the field of first-principles calculations, the creation and modification of input geometry files is a fundamental step. These files are essential for defining the atomic structures used in simulations and come in a variety of formats such as CIF, POSCAR, and XYZ. Traditionally, editing these files for specific requirements has been done manually or through GUI-based tools such as VESTA.\n\nHowever, manual and GUI-based methods fall short in high-throughput scenarios, especially when running on high-performance computing (HPC) systems. There, the need for fast and automated batch processing of geometry files becomes apparent - a need that is not adequately addressed by existing methods.\n\nThe Atomic Simulation Environment (ASE) Python library provides a robust solution with its array of geometry modification functions and support for multiple file types. However, this robustness comes at the cost of complexity: effective use of ASE requires knowledge of Python programming, which can be a hurdle for users who are not well versed in programming.\n\nTo address this gap, we developed a utility that encapsulates the functionality of ASE in a more accessible interface. This tool solves the problem of requiring extensive programming knowledge to manipulate geometry files in high-throughput computations. It provides a command-line solution that allows batch processing without the need for direct code intervention.\n\nIn addition, our tool enhances customization through user-generated plug-in files. This allows for customized modifications that can evolve as users' needs change. By simplifying the process of converting and modifying geometry files, our utility significantly reduces the effort required to prepare simulations for HPC environments.", + "laborHours": 1079.2, + "languages": [], + "name": "CompMatORNL - aseconv", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CompMatORNL/aseconv", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-14", + "metadataLastUpdated": "2024-08-14" + }, + "description": "BiG-SLiCE was originally an open source Python-based command line bioinformatics software that offers a highly scalable clustering analysis on biosynthetic gene clusters (BGC) data. It allows a simultaneous analysis of millions of BGCs, exceeding the capability of other existing tools (around one hundred thousands). As a tradeoff, the clustering accuracy is relatively lower and sometimes fall short in corner cases and specific BGC classes such as the RiPPs (Ribosomally-translated, Post-translationally modified Peptides).\n\nIn BiG-SLiCE V2 (developed in LBNL), the clustering algorithm has been significantly improved to deliver a much accurate result even for RiPPs and other previous corner case classes. Moreover, the speed of the overall pipeline has been improved by 50-100%. Finally, additional features were implemented to support downstream analyses of BiG-SLiCE results, such as customized tabular (TSV/CSV) and columnar (Parquet) outputs.", + "laborHours": 29837.6, + "languages": [], + "name": "BiG-SLiCE 2 v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/SAKautsar/bigslice_v2", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-14", + "metadataLastUpdated": "2024-08-14" + }, + "description": "A library of Axon code and Trio files in active use at LBNL to analyze and display data related to the operation of buildings in the Haxall or SkySpark environment.", + "laborHours": 15.2, + "languages": [], + "name": "Haxall and Haystack Data Analysis for Building Operations (Data Analysis for Operations) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ralphou/data-analysis-operations", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "Psychart is a graphical program developed for NERSC for accurately monitoring air conditions for the air cooled HPC equipment. Psychart will live directly in the OMNI system as a Grafana plugin. It employs the use of Psychrolib and the Grafana Starter Panel to create a front-end program that plots the state of the environmental air on a psychrometric chart. It is highly customizable, allowing the user to modify graph bounds, optionally show ASHRAE data center comfort regions, change the series point color, and more. What sets Psychart apart from other existing psychrometric charts is its ability to plot in real-time. Other psychrometric charts that can be found online require manual input of data and do not seamlessly integrate with Grafana.", + "laborHours": 12676.8, + "languages": [], + "name": "Psychrometric Chart v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nicfv/Psychart", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "GTNet is a neural network capable of identifying the species from which a genomic sequence was derived. Its main use will be in processing metagenomic sequences generated in microbiome research.", + "laborHours": 714.4, + "languages": [], + "name": "The Genome Taxonomy Network (GTNet) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exabiome/gtnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "PPO and Friends (PPOAF) is a pytorch implementation of proximal policy optimization for single- and\nmulti-agent reinforcement learning (the PPO), along with several optimizations and add-ons (the Friends)\nto enable efficient MPI-parallelized model training on HPC clusters.", + "laborHours": 6536.0, + "languages": [], + "name": "PPO And Friends", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ppo_and_friends", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "Kinetics05 uses a variety of linear and nonlinear regression methods, depending on the model to be fitted.\nIsoconversional methods use linear regression, supplemented by empirical correlations between model\nparameters and reaction profile characteristics. Distributed activation energy and nucleation-growth\nmodels use nonlinear regression, with the exception of the discrete distribution model, which uses a\nnested constrained linear-nonlinear regression method.", + "homepageURL": "https://softwarelicensing.llnl.gov/product/kinetics05oss", + "laborHours": 6688.0, + "languages": [], + "name": "Kinetics05_OSS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://softwarelicensing.llnl.gov/product/kinetics05oss", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "0" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "We introduce a new encoder-decoder system that overcomes adaptability and scalability issues. We adapt multiple CNNs as encoders, allowing for the definition of multiple function parameter arguments to structure the models according to the targeted datasets and scientific problem.\n\nWe leverage the flexibility of the U-Net architecture to act as a scalable decoder. The CRF-RNN layer is integrated into the decoder as an optional final layer, keeping the entire system fully compatible with back-propagation.", + "laborHours": 1474.4, + "languages": [], + "name": "U-Net Decoder CRF v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mavaylon1/UNet_Decoder_CRF", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-09-16" + }, + "description": "The software \"BaseBuddy\" (basebuddy.lbl.gov) is a user-friendly web app designed for codon optimization of heterologous genes. Codon optimization is a widely used technique to enhance the expression levels of non-native genes. Our app is built on the DNA Chisel Python library (Zulkower and Rosser, 2020), which offers highly customizable and transparent gene optimization. Unlike DNA Chisel, which is a command-line interface software with numerous optional functions, our web app simplifies the process for users. Additionally, while DNA Chisel relies on the outdated Kazusa codon usage database, our app introduces the option to utilize the most recent version of the CoCoPUTs database (Athey et al., 2017). By incorporating CoCoPUTs, we also expand the range of target organisms and maintain up-to-date sequencing data for more accurate codon optimization results.", + "laborHours": 167.2, + "languages": [], + "name": "BaseBuddy v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jbei/basebuddy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-18", + "metadataLastUpdated": "2024-08-20" + }, + "description": "The repo that provides data archive for DOE PoSeiDon project. It also contains scripts and instructions to parse the data.", + "laborHours": 349.6, + "languages": [], + "name": "FlowBench Raw Data Archive", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/FlowBench-Raw-Workflow-Data", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-18", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Flow-Bench is a benchmark dataset for anomaly detection techniques in computational workflows. Flow-Bench contains workflow execution traces, executed on distributed infrastructure, that include systematically injected anomalies (labeled), and offers both the raw execution logs and a more compact parsed version. In this GitHub repository, apart from the logs and traces, you will find sample code to load and process the parsed data using pytorch, as well as, the code used to parse the raw logs and events.", + "laborHours": 14272.8, + "languages": [], + "name": "Flow-Bench: A Dataset for Computational Workflow Anomaly Detection", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/FlowBench", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Repo for running Large Language Models for Anomaly Detection in Computational Workflows. Include datasets for 1000Genome, Montage, and Predict Future Sales workflows.", + "laborHours": 3617.6, + "languages": [], + "name": "Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context Learning", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/LLM_AD", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-20" + }, + "description": "This repository provides a set of scripts and tools for conducting network research, including performance analysis, buffer status inspection, and RTT probing. It is designed to streamline network data collection and post-processing, primarily leveraging iperf and other network utilities. The primary goal of the RADT dataset is to provide researchers with detailed insights into the interactions between TCP Congestion Control Algorithms (CCAs) and Active Queue Management (AQM) algorithms under different network conditions, enabling the development of more advanced, AI-driven CCAs.", + "laborHours": 1368.0, + "languages": [], + "name": "RADT Scripts for Network Research", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/RADT_scripts_for_network_research", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Clang Unified Parallel C 2 C (Clang UPC2C) translator compiles programs written in the UPC (Unified Parallel C) language to ISO C99, with calls to the Berkeley UPC runtime system. The Clang UPC2C compiler extends the capabilities of the Clang LLVM C frontend to comply with the UPC Language Specification version 1.3. The compiler generates programs that run on a wide variety of systems ranging from workstations to leadership-class supercomputers, in conjunction with the Berkeley UPC runtime and GASNet communication system. In addition to the standard UPC libraries, Clang UPC2C also provides access to Berkeley UPC library extensions.", + "laborHours": 1682077.6, + "languages": [], + "name": "Clang UPC2C Translator (Clang UPC2C) v9.0.1-1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/clangupc/clang-upc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-20" + }, + "description": "Clang Unified Parallel C (Clang UPC) provides a compilation and execution environment for programs written in the UPC (Unified Parallel C) language. The Clang UPC compiler extends the capabilities of the Clang LLVM C compiler to comply with the UPC Language Specification version 1.3. It includes support for UPC collectives and a configurable pointer-to-shared representation. The compiler generates programs that run on a wide variety of systems ranging from workstations to leadership-class supercomputers, in conjunction with the Berkeley UPC runtime and GASNet communication system. This compiler generates assembly code / object code directly for Intel processors and IBM PowerPC.", + "laborHours": 1155.2, + "languages": [], + "name": "Clang UPC Compiler (Clang UPC) v3.9.1-1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://clangupc.github.io/clang-upc2c", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/clangupc/upc2c", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This work applies thermography (Thermal infrared imaging) on building images to identify defects inside of them. The objective is to segment the defect area from the non-defect area automatically without human intervention\u2014a machine vision approach.", + "laborHours": 471.2, + "languages": [], + "name": "Thermal anomaly and rooftop unit (RTU) detection in buildings through machine learning (TAR) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/TAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-19" + }, + "description": "The Land-based Balance-of-System Systems Engineering (LandBOSSE) model is a systems engineering tool that estimates the balance-of-system (BOS) costs associated with installing utility scale wind plants (10, 1.5 MW turbines or larger). It can execute on macOS and Windows. At this time, for both platforms, it is a command line tool that needs to be accessed from the command line.\n\nThe methods used to develop this model (specifically, LandBOSSE Version 2.1.0) are described in greater detail the following report:\n\nEberle, Annika, Owen Roberts, Alicia Key, Parangat Bhaskar, and Katherine Dykes. 2019. NREL\u2019s Balance-of-System Cost Model for Land-Based Wind. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-72201. https://www.nrel.gov/docs/fy19osti/72201.pdf.", + "laborHours": 1884.8, + "languages": [ + "Python" + ], + "name": "LandBOSSE (Land-Based Balance Of System) 2023 [SWR-18-43]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/LandBOSSE", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.5.0" + }, + { + "contact": { + "email": "olattjv@ornl.gov" + }, + "date": { + "created": "2024-08-20", + "metadataLastUpdated": "2024-08-20" + }, + "description": "The J1939 Decoder package is a set of scripts that will allow one to decode J1939 messages.", + "laborHours": 15.2, + "languages": [], + "name": "J1939 Decoder", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/joornl/J1939-Decoder", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "knappgl@ornl.gov" + }, + "date": { + "created": "2024-08-20", + "metadataLastUpdated": "2024-08-20" + }, + "description": "The additive manufacturing (AM) community has been developing digital factory tools over the past decade to better leverage the multi-modal process data coming out of the advanced manufacturing process. As a result, numerous databases of additive manufacturing process data exist in the literature and in the archival storage of disparate research groups. While some efforts have been made to create a standard ontology for storing and sharing AM data, in practice a variety of data structures are used to store AM build data, even within a single institution. This causes many problems for maintainability and extensibility when attempting to integrate computational modeling tools with experimental data to either validate models or to provide further insight into results and trends.\n\nMyna is a Python-based framework that aims to decrease the effort needed to connect individual computational models to the variety of AM process data that exist in different research groups and institutions. This type of software is sometimes referred to as \"middleware\" or \u201cglueware,\u201d in that it connects disparate databases and applications into a single computational ecosystem. Instead of maintaining unique interfaces between each application and each database, developers can create a single interface from each application to Myna and thereby gain access to the implemented database connections. Similarly, developing a database connection in Myna provides access to the developed simulation applications. This framework greatly simplifies the maintainability of model applications that rely on experimental data. Using external simulation tools, users will also be able to run pre-configured workflows using the built-in workflow manager. Several examples of input files are provided with Myna for different workflows, including melt pool geometry predictions and detailed melt pool and solidification microstructure predictions.", + "laborHours": 4043.2, + "languages": [ + "Python" + ], + "name": "Myna", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-MDF/Myna", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-20", + "metadataLastUpdated": "2024-08-21" + }, + "description": "The MicroEleX code package contains a variety of models and algorithms for physical modeling of microelectronic circuitry, including electrostatics, electrodynamics, superconducting physics, micromagnetics, multi-ferroic systems, and quantum transport. MicroEleX leverages the AMReX software framework to provide scalability on GPU-based supercomputing architectures. The code is open source and designed to be algorithmically flexible so developers can incorporate enhanced or customized physics.", + "laborHours": 81669.6, + "languages": [], + "name": "Exascale-Enabled Models and Algorithms for Microelectronics Applications (MicroEleX) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Microelectronics/artemis.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-20", + "metadataLastUpdated": "2024-08-20" + }, + "description": "Repo that contains code and example data for workflow anomaly detection with graph neural networks", + "laborHours": 13832.0, + "languages": [], + "name": "Graph Neural Network for Anomaly Detection and Classification in Scientific Workflows", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/FlowGAD", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-22", + "metadataLastUpdated": "2024-09-16" + }, + "description": "MSD-LIVE, the MultiSector Dynamics \u2013 Living, Intuitive, Value-adding, Environment, is a flexible and scalable data and code\nmanagement system combined with a distributed computational platform that will enable MSD researchers to document\nand archive their data, run their models and analysis tools, and share their data, software, and multi-model workflows\nwithin a robust Community of Practice. MSD-LIVE will facilitate a new open, collaborative, resource-rich, technology-facilitated,\ncommunity-driven way of doing MSD research.", + "laborHours": 0.0, + "languages": [], + "name": "msdlive-cli-distro", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MSD-LIVE/msdlive-cli-distro", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-23", + "metadataLastUpdated": "2024-08-23" + }, + "description": "Genetic Algorithms meets Deep RL for Hyperparameters Hyperparameter optimization and architecture search can easily become cumbersome and finding the right hyperparameters can seriously impact the robustness of the deep RL application being developed.\n\nWe use genetic algorithms to evolve optimum deep RL architectures in a scalable manner.\n\nHPS-RL is designed to work with multiple gym enviornments, allow users to test their own optimization functions and tune multi-objective parameters in multiple deep RL algorithms. HPS-RL uses multi-threading and is being extended with mpipy for distributed processing on HPC.\n\nhttps://arxiv.org/abs/2201.11182", + "laborHours": 1915.2, + "languages": [], + "name": "HPS-RL: Hyperparameter tuning for deep RL applications (HPS-RL) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SelfDrivingNetworkLab/hps-rl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "moriano@ornl.gov" + }, + "date": { + "created": "2024-08-23", + "metadataLastUpdated": "2024-08-23" + }, + "description": "Source code to replicate the results of the paper: Benchmarking Unsupervised Online IDS for Masquerade Attacks in CAN (arXiv:2406.13778 [cs.CR])", + "laborHours": 1246.4, + "languages": [], + "name": "pmoriano/benchmarking-unsupervised-online-IDS-masquerade-attacks", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmoriano/benchmarking-unsupervised-online-IDS-masquerade-attacks", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-09052O\nQuasi-Newton Variational Bayes (QNVB) is a training algorithm that performs high-dimensional variational inference on machine learning models. It provides mechanisms to calibrate and control model uncertainty during training. The PyTorch implementation of projective integral updates for Gaussian mean-fields supports the manuscript, \"Projective Integral Updates for High-Dimensional Variational Inference.\"\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 243.2, + "languages": [ + "Python", + "PyTorch" + ], + "name": "Quasi-Newton Variational Bayes v.3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/qnvb", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08987O\nOpenCSP analyzes and improves the performance of optical mirrors that reflect sunlight and concentrate it onto a receiver. The algorithms in this library analyze the flow of light from an original source\u2014such as the sun\u2014reflecting off one or more mirrors, and onto a receiver, optical screen, or camera. OpenCSP also analyzes optical systems using other techniques, such as shape or slope comparison. The software calculates aggregate properties of the optical system, such as its efficiency, manufacturing error, pointing control error, expected performance, and other useful parameters. \n\nOpenCSP also includes high-level tools, such as Open SOFAST, a program that obtains high-resolution measurement of CSP mirrors, full heliostats, and other CSP collectors. OpenCSP supports producing meaningful output data to help CSP designers and field operators improve the performance of their systems. OpenCSP also includes classes and functions that support these calculations, including input utilities, analysis output libraries, geometric constraint analysis for drone flight planning, and more. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 40188.8, + "languages": [ + "Python" + ], + "name": "OpenCSP v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/OpenCSP", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08793O\nQuESt Equity cross-references several public databases for power plant pollution and demographics to assess energy equity and environmental justice for energy storage projects. It also calculates the impacts of power plant pollution in disadvantaged communities. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 387828.0, + "languages": [ + "Python" + ], + "name": "QuESt Equity v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/snl-quest-equity", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "This is an Excel-based time-independent discount cash flow calculator for LWR-HTSE systems. The tool incorporates (1) discounted cash flow and levelized cost of hydrogen (LCOH) analysis, (2) sensitivity analysis with respect to select financial performance metrics with output \u2018tornado\u2019 charts, (3) profitability analysis represented by heat maps using the two most sensitive parameters, (4) electricity versus hydrogen production preference analysis by comparing change in net present value (?NPV) between NPP-HTSE and business-as-usual electricity production for the grid, and (5) competitiveness analysis by comparing the calculated LCOH for NPP-HTSE with that of steam methane reforming, which is the conventional process to produce hydrogen.", + "laborHours": 0.0, + "languages": [ + "Visual Basic" + ], + "name": "Nuclear Integrated Hydrogen Production Analysis Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/NIHPA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "The platform of optimal experiment management, POEM, powered with automated machine learning to accelerate the discovery of optimal solutions, and automatically guide the design of experiments to be evaluated. POEM currently supports 1) random model explorations for experiment design, 2) sparse grid model explorations with Gaussian Polynomial Chaos surrogate model to accelerate experiment design ,3) time-dependent model sensitivity and uncertainty analysis to identify the importance features for experiment design, 4) model calibrations via Bayesian inference to integrate experiments to improve model performance, and 5) Bayesian optimization for optimal experimental design. In addition, POEM aims to simplify the process of experimental design for users, enabling them to analyze the data with minimal human intervention, and improving the technological output from research activities.", + "laborHours": 2933.6, + "languages": [ + "Python" + ], + "name": "Platform Of Optimal Experiment Management", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/POEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08641O\nExoToComsol models capability-sharing. For example, the software can develop a multiphysics modeling chain using physics modeling capabilities from different research institutions using either SIERRA or COMSOL. The converter program allows exporting user-defined, region-of-interest from a large FE model, which results in a finer mesh of the submodel that can be used for subsequent analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 152.0, + "languages": [ + "python" + ], + "name": "ExoToComsol v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ExoToComsol", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08619O\nThe DISCO GUI software, written in MATLAB, allows for data calibration for X-ray diffraction work at Sandia National Labs\u2019 Z Machine. The program manually identifies and manipulates images from seven fiber bundles based on a calibration reticle. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 212.8, + "languages": [ + "MATLAB" + ], + "name": "DISCO GUI v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DISCO_GUI", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08606O\nThe pyNuMAD software is used for managing wind turbine blade model data. pyNuMAD specializes in defining the geometry, materials, and boundary conditions for structural analysis of wind turbine blades. This includes loading in data files and providing an interface for users to make updates to the model. The software also features meshing functionality, which takes the blade model and creates a shell or brick mesh for use in finite element analysis. A typical user workflow might be: load in blade information from a yaml file, make adjustments to the blade properties, update the blade based on the adjustments, create a mesh of the blade, export this blade to another software for structural analysis.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 12646.4, + "languages": [ + "Python" + ], + "name": "pyNuMAD v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyNuMAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-30" + }, + "description": "SAND2024-08598O\nThe Quantum Instrumentation Control Kit Defect Arbitrary Waveform Generator (QICKDAWG) characterizes nitrogen-vacancy centers in diamond and other defects. It does this by using a radio frequency system-on-a-chip (RFSoC) field programmable gate array (FPGA). QICKDAWG synthesizes microwave pulses from the RFSoC to change the spin state of the defects. The software also allows for laser control using the RFSoC, which optically pumps defects. Ultimately, QICKDAWG supports the implementation of RFSoC FPGAs in defect characterization. This replaces the slow, expensive, traditional hardware, thus lowering the cost and time for defect characterization. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 144278.4, + "languages": [ + "Python" + ], + "name": "Quantum Instrumentation Control Kit Defect Arbitrary Waveform Generator (QICKDAWG) v.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/qick-dawg", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "This tool provides codes to prune and quantize vision transformers (ViTs). The tool will allow developers and researchers to speed up inference of ViTs and deploy them on CPUs.", + "laborHours": 425.6, + "languages": [], + "name": "prune_quant_vit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kshitij11/PQV-Mobile", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-27", + "metadataLastUpdated": "2024-08-27" + }, + "description": "CIGEN is a tool that finds input ranges that cause high compiler-induced numerical inconsistencies in\nnumerical programs written in a compiled language. Numerical program behavior may diverge when they\nare compiled and ran differently. Many factors, such as different hardware architectures (for example, the\nx87 FPU with its 80-bit registers), different compilers, or different optimization flags may cause the results\nof floating-point computations to become inconsistent. This kind of inconsistencies are known as\ncompiler-induced numerical inconsistencies. Given a program with floating-point inputs and an output,", + "laborHours": 3739.2, + "languages": [], + "name": "CIGEN", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CIGEN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-27", + "metadataLastUpdated": "2024-08-27" + }, + "description": "This software combines nonlinear-manifold reduced order models (NM-ROMs) with domain\ndecomposition (DD) techniques. NM-ROMs, which utilize a shallow, sparse autoencoder trained with full\norder model (FOM) snapshot data, approximate the FOM state on a nonlinear manifold. These models\noffer advantages over linear-subspace ROMs (LS-ROMs) particularly in scenarios with slowly decaying\nKolmogorov n-width. However, the training of NM-ROMs involves a number of parameters that scale with\nthe size of the FOM, and storing high-dimensional FOM snapshots can significantly increase the cost of\nROM training for extreme-scale problems.\nTo mitigate these costs, the software employs DD to partition the FOM into smaller subdomains,\ncomputes NM-ROMs for each, and then integrates these to form a global NM-ROM. This strategy offers\nmultiple benefits: it enables parallel training of subdomain NM-ROMs, reduces the number of parameters\nneeded, decreases the dimensional requirements of subdomain FOM training data, and allows for\ncustomization to the unique characteristics of each FOM subdomain. The use of a shallow, sparse\nautoencoder architecture in each subdomain NM-ROM facilitates the application of hyper-reduction (HR),\nsimplifying the nonlinear complexities and enhancing computational speed.\nThis software marks the inaugural application of NM-ROM combined with HR to a DD problem. It features\nan algebraic DD reformulation of the FOM, training of NM-ROMs with HR for each subdomain, and\nemploys a sequential quadratic programming (SQP) solver for the evaluation of the coupled global NMROM.\nThe effectiveness of the DD NM-ROM with HR is numerically demonstrated on the 2D steady-state\nBurgers' equation, showing an order of magnitude improvement in accuracy over the DD LS-ROM with\nHR.", + "laborHours": 3055.2, + "languages": [], + "name": "Domain-decomposition nonlinear manifold reduced order model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DD-NM-ROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-08-27", + "metadataLastUpdated": "2024-09-10" + }, + "description": "FRISM simulates day-to-day freight activities including end-consumer shopping, distribution channel, and carrier operation with e-commerce dynamics between passenger and freight travel. It outputs an assignment of different shipments to carriers and tour plans of the carriers' vehicles to transport shipments from their origins to their destinations.", + "laborHours": 6171.2, + "languages": [ + "Python", + "Shell" + ], + "name": "FRISM (FReight Integrated Simulation Model) [SWR-24-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/FRISM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-08-28", + "metadataLastUpdated": "2024-08-28" + }, + "description": "(SF-24-031) Software PolyLaue, having ANL OPEN SOURCE LICENSE, will be extended by KITWARE, INC. New functionality, including file manager, visualizer and mapping routine will substantially improve the procedure to identify single-crystals across compression with Laue diffraction technique.", + "laborHours": 1565.6, + "languages": [], + "name": "EXTENDED VERSION OF SOFTWARE POLYLAUE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PolyLaue/PolyLaue", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-28", + "metadataLastUpdated": "2024-08-28" + }, + "description": "Hydropower simulation model that allows for changes to inflow scenarios.", + "laborHours": 988.0, + "languages": [], + "name": "9505-PNNL/wmpy_power", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/9505-PNNL/wmpy_power", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-28", + "metadataLastUpdated": "2024-08-29" + }, + "description": "Volt-VAR and Volt-Watt functionality in photovoltaic (PV) smart inverters provide mechanisms to ensure system voltage magnitudes and power factors remain within acceptable limits. However, these control functions can become unstable, introducing oscillations in system voltages when not appropriately configured or maliciously altered during a cyberattack. In the event that Volt-VAR and Volt-Watt control functions in a portion of PV smart inverters in a distribution grid are unstable, the proposed adaptation scheme utilizes the remaining and stably-behaving PV smart inverters and other Distributed Energy Resources to mitigate the effect of the instability in real-time. The adaptation mechanism is entirely decentralized, model-free, communication-free, and requires virtually no external configuration. This repository provides code to simulate the algorithm in experiments on the IEEE 37 node test feeder.", + "laborHours": 1626.4, + "languages": [], + "name": "Adaptive Control Algorithm to Adjust Settings in Photovoltaic Inverters for Electric Grid Cybersecurity (DERAC) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/smart-inverter-adaptive-control", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-29", + "metadataLastUpdated": "2024-08-30" + }, + "description": "T2DM adds two-dimensional hydrodynamic dispersion to TOUGH2/EOS7C. T2DM can be used when modeling flow and transport of brine in porous media to account for hydrodynamic dispersion.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 775.2, + "languages": [], + "name": "T2DM v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-09-16" + }, + "description": "PyCIGAR is a python software package that merges off-the-shelf reinforcement learning libraries (RLLib and Ray) with electric power distribution system simulation tools (OpenDSS and a custom power flow solver built by LBL). PyCIGAR enables the training of neural networks to optimize the behavior of different components in the electric distribution grid, such as control systems in photovoltaic rooftop solar inverters and electric battery storage systems. The software package has been used to train neural networks to update settings in photovoltaic rooftop solar inverter control systems to mitigate cyber attacks on other solar photovoltaic rooftop devices.", + "laborHours": 13391.2, + "languages": [], + "name": "Reinforcement Learning for Distribution Grid Optimization (PyCIGAR) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/ceds-cigar", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "TOUGHREACT V4.12 is a 3-D reactive transport code that handles to non-isothermal, multiphase/multicomponent fluid flow, heat transport, aqueous and gaseous species advection-diffusion, and equilibrium/kinetic water-gas-rock-biological reactions.\n\nTOUGHREACT V4.12 is based on TOUGHREACT V3.3, with several new features including: an option to compute activity coefficients using the Pitzer ion interaction model; implementation of ECO2N V2.0 for temperatures up to 300 C; options to simulate forward and reverse osmosis, including 2D Poiseuille flow; addition of EOS8 and revisions for EOS5 and EWASG with H2(g); addition of gas species decay, various new output formats and time step control options; many bug fixes.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 39428.8, + "languages": [], + "name": "TOUGHREACT V4.12", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "This software contains a set of components that allow us to measure and analyze the use and performance of computer networks using existing off the shelf Open Source components organized into a scalable and extensible system. The components were developed for and used within ESnet's Stardust Measurement Environment. The components are used to collect, process and display network measurement data in an architecture that employs a combination of Elasticsearch, Logstash and Grafana. The advantage of this approach is we can tailor system behavior to our analytical needs and expand its capability with new types of network measurement without waiting for a commercial vendor to support our fairly niche use cases. Additionally we have existing collaborations within our community that came about from prior research efforts that will benefit from the release of this software so that others can also contribute features.", + "laborHours": 16340.0, + "languages": [], + "name": "Stardust Network Measurement Components (esnet-stardust-components) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/stardust-snmp-pipeline", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "This jupyter notebook calculates basic statistics (e.g., mean, standard deviation, coefficient of variation) and simple graphs (e.g., bar graphs, line plots) for data from the Experiment Data Depot (EDD) to provide rapid and reproducible assessment of data quality to aid research efforts across the JBEI and ABF projects. It rapidly and reproducibly calculates basic statistical values for data stored in the EDD which aids researchers and strengthens comparisons across different experiments and projects.", + "laborHours": 288.8, + "languages": [], + "name": "EDD Basic Stats and Graphs Notebook analysis (EDD BSG Notebook) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/Omics-Data-QA-QC-tool", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "City Buildings, Energy, and Sustainability (CityBES) is a web-based data and computing platform, focusing on energy modeling and analysis of a city's building stock to support district or city-scale building energy efficiency programs. CityBES uses an international open data standard, CityGML, to represent and exchange 3D city models. CityBES employs EnergyPlus to simulate building energy use and savings from energy efficient retrofits. Other CityBES features include energy benchmarking, district heating and cooling system modeling, rooftop PV analysis, building performance visualization, heat resilience modeling, as well as urban scale mapping of microclimate and heat vulnerability at census tract level. Different from other tools, CityBES uses integrated open and standard 3D city building data and models each individual building using EnergyPlus. CityBES can be used by urban planners, city energy managers, building owners, utilities, energy consultants and researchers.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 170468.0, + "languages": [], + "name": "CityBES v2021", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-11-07" + }, + "description": "The IRViz package provides easy to use graphical user interface for the analysis of IR data.", + "laborHours": 3222.4, + "languages": [], + "name": "IRViz v0.0.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/irviz", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "The software contains only one perl script that take advantage of a module published 8 years ago from the public domain (https://github.com/dongyingwu/TreeOTU) . It take a phylogenetic tree, and select a give number (user defined) of taxa that represent the maximize phylogenetic diversity from the tree.", + "laborHours": 577.6, + "languages": [], + "name": "maximize phylogenetic diversity taxa selection script (maxPD.pl) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/maxpd/src/master", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "This software uses machine learning models to perform inference on X-ray diffraction powder patterns, output from a diffractometer, to estimate all 6 unit cell parameters of crystalline lattices. Novel aspects of this software originated from the incorporation of concepts from crystallography to an ML-based approach; The resulting method achieves new performance capabilities without significant loss of accuracy and with less computationally intensive models.", + "laborHours": 258.4, + "languages": [], + "name": "Machine Learning Based System for Automated Estimation of Crystal Unit Cell Parameters from X-ray Diffraction Powder Patterns (MLCell) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cctbx-xfel/MLCell", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "This package contains the code for the paper Evaluating Physics Informed Neural Network Performance\nfor Seismic Discrimination Between Earthquake published at Seismological Research Letters. There are\none Jupyter notebook and demo data so that the audience can run build a machine learning model with\nthe P/S ratios as a physics loss in addition to the data driven loss.t", + "laborHours": 106.4, + "languages": [], + "name": "Evaluating Physics Informed Neural Network Performance for Seismic Discrimination Between Earthquake", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qingkaikong/PhysicsML-PINN-EmpiricalRelationship", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "(SF-24-012) Stopping power describes the rate that a material slows radiation particles passing through it and is useful in designing many technologies. Few organizations can perform new measurements, which require significant resources and rare equipment, and all others rely on coarse approximations \nrendered from pre-existing data. Methods for computing stopping power in new materials, such as time-dependent density functional theory (TD-DFT), have only recently (circa-2015) become available but are too computationally costly to use frequently enough to have a pronounced impact. We have created a method that opens a pathway to computing stopping power without any need for experimental \ndata by combining electronic structure computations and machine learning.", + "laborHours": 2979.2, + "languages": [], + "name": "Machine learning and TDDFT software for stopping power computation", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/globus-labs/stopping-power-ml", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Spinbox is a piece of software that facilitates quantum mechanical calculations relevant to Monte Carlo simulation of atomic nuclei. At the front lines of research on the nuclear many-body problem are a large number of supercomputer-scale simulation codes. These codes produce valuable results but can be hard to understand, especially for those without intimate knowledge of the relevant theoretical methods.\nThus, tools that fill pedagogical roles are extremely valuable. Spinbox makes it easy for one to replicate and analyze the computational processes relevant to a Quantum Monte Carlo (QMC) simulation that may be difficult to\nunderstand/debug/analyze due to the scale of the corresponding simulation software.\nSpinbox is written in Python using other state-of-the-art Python modules for numerical calculations. While a number of Python libraries exist that are suited to general quantum many-body calculations, the motivation of Spinbox is quite particular.\nIn Diffusion Monte Carlo methods (DMC, GFMC, AFDMC), the central calculation is the imaginary-time propagation of individual samples of the many-body wavefunction.\nAlthough quantum wavefunctions generally must be described by a probability distribution over a basis, DMC imbues particles (within one sample) with classical spatial coordinates. This method is unusual, so other Python packages are typically not set up to do this easily. Furthermore, the software has built-in options for nuclear systems assuming isospin symmetry, which can be set up with other libraries but is a nontrivial process to do so. Features:\n- numerical representation of samples of the many-body wavefunctions, including tensor-product states (used in AFDMC)\n- numerical representation of many-body operators, including tensor-product operators: general, spin, imaginary-time propagation, etc.\n- the correct associated arithmetic and algebra, implemented as class methods\n- classes for representing realistic nuclear two- and three-body Hamiltonians (e.g. Argonne V18, Illinois NNN)\n- large-scale parallel integration over random variables, crucial for the AFDMC method\nMy goal is to make this package open source so that anyone may use it and contribute to it, particularly other researchers doing AFDMC calculations", + "laborHours": 7022.4, + "languages": [], + "name": "Spinbox: tools for many-body quantum systems in a Monte Carlo context", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmrfox/spinbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SF-24-077 Our software generates a circuit that prepares a specified target quantum state. It generates circuits with CNOT counts of O(mn), where m is the number of nonzero amplitudes of the state and n is the number of qubits. The method does not require ancillas. It is designed for sparse states, but works for any quantum state. Our method is based on the new perspective of dynamic continuous time quantum walks for quantum state preparation. This is an intuitive perspective where a graph is \nfirst constructed to traverse the basis states. The method works by 1.) construct a graph of the basis states, 2.) transform the graph into quantum walks, and 3.) construct the final gate based \ncircuit optimized with our control reduction method.", + "laborHours": 243.2, + "languages": [], + "name": "Arbitrary State Preparation via Quantum Walks Software", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GaidaiIgor/quantum_walks", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SF-24-051 PBS_Utils is a collection of tools and libraries for administrating a PBSPro/OpenPBS system.", + "laborHours": 3860.8, + "languages": [], + "name": "PBS_UTILS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.cels.anl.gov/aig-public/pbs_utils", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SF-24-054 Octeres is a collection of tools and libraries for processing large amounts of\nsupercomputer data.", + "laborHours": 11688.8, + "languages": [], + "name": "Octeres", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.cels.anl.gov/aig-public/octeres", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-09-03", + "metadataLastUpdated": "2024-09-03" + }, + "description": "Use of media compiler and ART to perform media optimization for titer maximization in flaviolin producing P. putida", + "laborHours": 3754.4, + "languages": [], + "name": "Flaviolin_Media_Optimization_C2 v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/Flaviolin_media_opt_C2", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-09-03", + "metadataLastUpdated": "2024-09-03" + }, + "description": "Use of media compiler and ART to perform media optimization", + "laborHours": 153976.0, + "languages": [], + "name": "Flaviolin_Media_Optimization_C1 v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/Flaviolin_media_opt_C1", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-09-03", + "metadataLastUpdated": "2024-09-19" + }, + "description": "This software is used in a media optimization pipeline. It is used to calculate stock concentrations, volumes and instructions for the liquid handler used in ESE (Biomek NX-S8).", + "laborHours": 341969.6, + "languages": [], + "name": "Media Compiler v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/media_compiler", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-09-04", + "metadataLastUpdated": "2024-09-06" + }, + "description": "This software is an API for create and modify XML that are used for Plexos.\n\nDISCLAIMER: PLEXOS is a registered trademark of Energy Exemplar Pty Ltd (\"Owner\"). Owner has no affiliation to or participation in this software. Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or Alliance for Sustainable Energy, LLC (\"Alliance\"). The views and opinions of authors expressed in the available or referenced documents do not necessarily state or reflect those of the United States Government or Alliance.", + "laborHours": 1246.4, + "languages": [ + "Python" + ], + "name": "Database Manager for use with PLEXOS XML files [SWR-24-90]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/plexosdb", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.0.2" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-04", + "metadataLastUpdated": "2024-09-04" + }, + "description": "This software showcases the enhanced capabilities of the Latent Space Dynamics Identification (LaSDI)\nalgorithm through the application of the weak form, resulting in WLaSDI. WLaSDI first compresses the\ndata, then projects it onto test functions, and subsequently learns the local latent space models. Notably,\nWLaSDI demonstrates significantly improved robustness to noise. Using weak-form equation learning\ntechniques, WLaSDI achieves local latent space modeling. Compared to the standard sparse\nidentification of nonlinear dynamics (SINDy) used in LaSDI, the variance reduction of the weak form\nensures robust and precise latent space recovery, enabling fast, robust, and accurate simulations.\nWe demonstrate the efficacy of WLaSDI against LaSDI using several common benchmark examples,\nincluding viscid and inviscid Burgers', radial advection, and heat conduction. For instance, in 1D inviscid\nBurgers' simulations with up to 100% Gaussian white noise, WLaSDI maintains relative errors\nconsistently below 6%, whereas LaSDI errors can exceed 10,000%. Similarly, in radial advection\nsimulations, WLaSDI keeps relative errors below 16%, compared to potential errors of up to 10,000% with\nLaSDI. Additionally, WLaSDI achieves significant speedups, such as a 140X speedup in 1D Burgers'\nsimulations compared to the corresponding full order model.", + "laborHours": 2690.4, + "languages": [], + "name": "Weak-Form Latent Space Dynamics Identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MathBioCU/PyWLaSDI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-04", + "metadataLastUpdated": "2024-09-19" + }, + "description": "Traditional linear subspace reduced order models (LS-ROMs) are able to accelerate physical simulations\nin which the intrinsic solution space falls into a subspace with a small dimension, i.e., the solution space\nhas a small Kolmogorov n-width. However, for physical phenomena not of this type, e.g., any advection-dominated\nflow phenomena such as in traffic flow, atmospheric flows, and air flow over vehicles, a lowdimensional\nlinear subspace poorly approximates the solution. To address cases such as these, we have\ndeveloped a fast and accurate physics-informed neural network ROM, namely nonlinear manifold ROM\n(NM-ROM), which can better approximate high-fidelity model solutions with a smaller latent space\ndimension than the LS-ROMs. Our software takes advantage of the existing numerical methods that are\nused to solve the corresponding full order models. The efficiency is achieved by developing a hyper-reduction\ntechnique in the context of the NM-ROM. Numerical results show that neural networks can learn\na more efficient latent space representation on advection-dominated data from 1D and 2D Burgers'\nequations. A speedup of up to 2.6 for 1D Burgers' and a speedup of 11.7 for 2D Burgers' equations are\nachieved with an appropriate treatment of the nonlinear terms through a hyper-reduction technique.", + "laborHours": 20170.4, + "languages": [], + "name": "Nonlinear manifold reduced order model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/NM-ROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-05", + "metadataLastUpdated": "2024-09-19" + }, + "description": "This software showcases a latent space dynamics identification method, namely tLaSDI, that embeds the\nfirst and second principles of thermodynamics. The latent variables are learned through an autoencoder\nas a nonlinear dimension reduction model. The latent dynamics are constructed by a neural network-based\nmodel that precisely preserves certain structures for the thermodynamic laws through the\nGENERIC formalism. An abstract error estimate is established, which provides a new loss formulation\ninvolving the Jacobian computation of autoencoder. The autoencoder and the latent dynamics are\nsimultaneously trained to minimize the new loss. Computational examples demonstrate the effectiveness\nof tLaSDI, which exhibits robust generalization ability, even in extrapolation. In addition, an intriguing\ncorrelation is empirically observed between a quantity from tLaSDI in the latent space and the behaviors\nof the full-state solution.", + "laborHours": 2188.8, + "languages": [], + "name": "Thermodynamics-informed latent space dynamics identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pjss1223/tLaSDI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "greenwoodms@ornl.gov" + }, + "date": { + "created": "2024-09-05", + "metadataLastUpdated": "2024-09-05" + }, + "description": "A template system-of-systems modeling approach for\nautomating the development, deployment, and integration of cooling system models (CSMs) for supercomputing facilities within the ExaDigiT framework.\n\nAutoCSM is a Python-based framework to assist in CSM developers in accelerating the creation and deployment of system-level thermal-hydraulic CSMs. The intention is for this tool specifically to help standardize digital twin workflows for ExaDigiT. However, this tool can be used independent of ExaDigiT (and even other systems besides CSMs).", + "laborHours": 532.0, + "languages": [ + "Python", + "Modelica" + ], + "name": "AutoCSM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/exadigit/AutoCSM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2024-09-05", + "metadataLastUpdated": "2024-09-05" + }, + "description": "This project uses the NanoMsg next-generation library to receive data, temporarily store in an in-memory buffer, and then send it out. The buffer handles a high-bandwidth stream from multiple producers (sources) to multiple consumers (sinks).", + "laborHours": 456.0, + "languages": [ + "Python" + ], + "name": "nng_stream", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/frobnitzem/nng_stream", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0.6" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-09", + "metadataLastUpdated": "2024-09-09" + }, + "description": "The AiiDA-INQ plugin will allow the INQ code developed at the lab to utilize the AiiDA workflow manager\nwhich enables high-throughput workflows. This includes provenance tracking, restart capabilities, job\ncalculators, and other capabilities", + "laborHours": 1246.4, + "languages": [], + "name": "AiiDA-INQ plugin", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/aiida-inq", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-09", + "metadataLastUpdated": "2024-09-19" + }, + "description": "The Common Electric Power Transmission System Model (CTM) is an intuitive, extensible, language-agnostic,\nand error-resistant specification of electric power network components parameter names and\nunits, and relation between components, intended for use by the research community developing new\ncomputational methods for power systems operations and simulation. Power system datasets following\nthe CTM specification can be read as dictionaries and manipulated in that form in most programming\nlanguages (e.g., Python, Julia, C++). This standard data structure in CTM makes it easy to work in\nmultiple power systems domains (e.g., economic operation, reliability assessment, electricity markets,\nstability assessment, etc.) without requiring conversions between use-case-specific file formats with\ninformation loss in the process. This repository specifies CTM as a JSON Schema, provides\ndocumentation, derivate (code-generated) implementations of CTM, and example data and usage of the\nschema for important use cases.", + "laborHours": 1081616.8, + "languages": [], + "name": "Common Electric Power Transmission System Model JSON Schema Specification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ctm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "v0.1-alpha" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-09", + "metadataLastUpdated": "2024-09-19" + }, + "description": "This program will generate random points for electrons within the dimensions given by a parameter input\nfile. Based on these randomly generated electron positions and the nuclear positions given by a position\ninput file it will generate a value for the total electronic energy of an isolated system. This total electronic\nenergy is calculated using the electronic Hamiltonian for a monoatomic system with atoms having the\nsame number of protons and neutrons. The size of the system is defined by the parameter input file. The\nprogram will do this many times to generate a distribution of theoretically possible electronic total energies\nof the system. A user can then compare the total electronic energy given by their electronic structure\nmethod to make sure it falls within the distribution of theoretically possible values.", + "laborHours": 243.2, + "languages": [], + "name": "Uncertainty Quantification for Electronic Hamiltonian", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/linyang-121/UQEH-p", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-09-10", + "metadataLastUpdated": "2025-02-24" + }, + "description": "The proposed framework derives a set of\nquality metrics to provide critical insights into and tracking of grid operations, sensor performance, sensor longevity, and\nevent statistics. Power grid engineers can utilize this information to identify problems with existing sensor locations and\nproblematic power grid assets including generators, transmission lines, load centers, and substations. This information\ncan also be used to identify unexpected/abnormal behavior of power grid components, improve power grid observability,\nand operational monitoring, and thus enhance real-time decision-making support system. Power grid planners can utilize\nthis information to augment existing sensing architecture with new sensors and improve the observability of the network.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Sensor Data Analytics and Data Quality Assessment Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-11", + "metadataLastUpdated": "2024-09-18" + }, + "description": "SAND2021-0503 O\n\nThe epi_inference software supports the prediction of disease transmission parameters from data.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 7637437.6, + "languages": [ + "Python" + ], + "name": "epi_inference v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/epi_inference", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-09-11", + "metadataLastUpdated": "2024-10-25" + }, + "description": "MemFriend was developed to focus on providing a comprehensive view of access patterns by analysing spatial-temporal\nlocality between pairs of memory locations. It is intended to aid in data layout optimizations, and data placement decisions.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/MemFriend", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/memgaze", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-09-12" + }, + "description": "The software suite uses a microservice architecture using Docker and `docker-compose`. The microservices are as follows:\n1. User interface. This interface is written in JavaScript using the Svelte framework. It exposes form elements and a 3D visualizer to prompt the user through the definition of microstructure parameters, and setting parameters for mesh generation and refinement.\n2. Mesh generator. This is a container running the Python package for DREAM3D to generate a voxelized mesh that represents a microstructure defined by the user in the interface.\n3. Cubit runner. This is a secure shell protocol tool that makes the submitting the DREAM mesh to an HPC instance and starts to run Cubit shell commands to smooth the grain boundaries with its `sculpt` library, applies user-defined boundary node sets, and bundles and returns the simulation-ready meshes and input files as a zipped directory.", + "laborHours": 10001.6, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Mesh Computing Remote Automatic Workflow", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/MURMUR", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-09-12" + }, + "description": "This is the repository for all code related to the AGN-201 Nuclear Reactor Digital Twin at Idaho State University. The goal of this code repository is to consolidate all pieces required to run the AGN-201 Digital Twin in the [DeepLynx](https://github.com/idaholab/Deep-Lynx) ecosystem. This is the first successfully launched digital twin of a fissile nuclear reactor that we are aware of. While the code is not complex, the problems of networking, policy, and initial groundwork were significant to overcome.", + "laborHours": 54461.6, + "languages": [ + "Python", + "Rust" + ], + "name": "Agn-201 Digital Twin", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/agn201_Digital_Twin", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "martins@ornl.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-09-19" + }, + "description": "Field Expedition Routing and Navigation (FERN) is an IOS app funded by the Center for Bioenergy Innovation (CBI). It allows an end user to make trips to collect novel data points. It allows user to return to previously surveyed points to collect more data. It calculates the optimal route to use to sample points needed for return trips. A companion php/database application is required for full functionality. Links to this open source project are in the README. FERN can use the default GPS on an Iphone but it also optimized for Arrow Gold GPS. Other external GPS could be supported by modifying this code and adding the proper routines.", + "laborHours": 2097.6, + "languages": [ + "Swift" + ], + "name": "exnehilo7/fielddata-lite-iOS-app", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exnehilo7/fielddata-lite-iOS-app", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-09-12" + }, + "description": "BuildingSync\u00ae is a building data exchange schema to better enable integration between software tools and building data workflows. The schema's original use case was focused on commercial building energy audits; however, several additional use cases have been realized including building energy modeling and more high-level generic building data exchange.\n\nBuildingSync helps streamline the data exchange process, improving the value of the data, minimizing duplication of effort for subsequent building data collection efforts (including audits), and facilitating the achievement of greater energy efficiency. This in done in part by standardizing on (a) reporting audits in an electronic format, (b) tracking proposed, implemented, and discarded energy conservation measures, and (c) storing building characteristics (at multiple levels) for audits, benchmarking, and building energy analysis.\n\nBuildingSync has several documents and tools available to help users understand how to best leverage BuildingSync. The list below are only a subset of the resources available. If new resources are discovered, then feel free to create a new pull request with the additions.\n\nGeneric BuildingSync information is available on the DOE website and the project website.\n\nBuildingSync Examples - These examples are kept up to date and show a wide range of implementations. Any new update to BuildingSync is required to pass validation on these example files.\n\nBuildingSync Use Case Validator allows for users to determine if their instance complies with a specific use case for BuildingSync by checking if the required elements are implemented in an uploaded instance. An API is also provided for automated integration into other tools. Also, the website contains an easy way to view the entirety of the schema and how elements relate to the Building Exchange Data Exchange Specification. The Validator is open sourced here\nUse Case TestSuite provides a Python package for easier generation of BuildingSync use cases. BuildingSync use cases depend on the generation of schematron documents, which is time-consuming and difficult to implement well. The TestSuite allows users to define a use case using a more palatable CSV template, which it then turns into a Schematron document. The source code is available here.\n\nBuildingSync to OpenStudio/EnergyPlus. The translator is open sourced here. This project will translate a Level 1 (and partial Level 2) ASHRAE Energy Audit to a fully defined OpenStudio and EnergyPlus model. This project is in early Beta testing and any feedback is welcome!", + "laborHours": 134793.6, + "languages": [ + "Python", + "Ruby" + ], + "name": "BuildingSync\u00ae v.2.5.0 2024 [SWR-18-28]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BuildingSync/schema", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.5.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Chemical Webscraper uses the chrome web browser to search for and collect cost data for chemicals from specified distribution websites.", + "laborHours": 304.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "Chemical Webscraper [SWR-24-105]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ChemicalWebScraper", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-17", + "metadataLastUpdated": "2024-10-17" + }, + "description": "A suite of beamline controls software based on the Bluesky framework. 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CROPSR is a product of the DOE Center for Advanced Bioenergy and Bioproducts Innovation (CABBI).", + "laborHours": 486.4, + "languages": [], + "name": "CROPSR: An Automated Platform for Complex Genome-Wide CRISPR gRNA Design and Validation", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/H2muller/CROPSR", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-09-18", + "metadataLastUpdated": "2024-09-18" + }, + "description": "R2X is a tool that allows modeler to convert input/output models to other input/out models (e.g., ReEDS\u2122 to Plexos). This is tools is built as a parser of inputs that uses infrasys to create a network representation that then is used to create custom files as input for other models.", + "laborHours": 6672.8, + "languages": [ + "Python" + ], + "name": "R2X (ReEDS\u2122 to X) [SWR-24-91]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/R2X", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-18", + "metadataLastUpdated": "2024-09-18" + }, + "description": "Python scripts for physics informed machine learning for time-dependent problems. The code implements\nhard constrained sequential physics-informed neural networks (HCSPINNs) using JAX library. The details\nof the method and implementation can be found in the following paper:\nRoy, P., & Castonguay, S. (2024). Exact Enforcement of Temporal Continuity in Sequential Physics-\nInformed Neural Networks. arXiv preprint arXiv:2403.03223. (https://arxiv.org/abs/2403.03223)", + "laborHours": 1444.0, + "languages": [], + "name": "PhyML", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/PhyML", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-09-20", + "metadataLastUpdated": "2024-09-20" + }, + "description": "The MTINV toolkit (2002-present) is a collection of computer codes and applications written to invert for\nthe moment tensor of a seismic source given the three components of ground motion recorded at regional\nseismic stations (e.g., Ichinose et al., 2003). The computer codes and workflow are organized to\ngenerate moment tensor solutions for a range of source depths and origin times because of the trade-off\nbetween these two quantities. The metric used is the variance reduction and variance reduction\nmodulated by the percent double-couple to determine the best-fit moment-tensor solution. We can solve\nfor a deviatoric moment tensor with a constraint added for no isotropic component although this constraint\ncan be lifted for estimating the full moment tensor like mining collapses or explosion sources.", + "laborHours": 40325.6, + "languages": [], + "name": "Moment Tensor Inversion Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mtinv", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "4.0.2" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-23", + "metadataLastUpdated": "2024-09-23" + }, + "description": "SF-24-041 aldsim is a Python module that provides a set of ALD models that allow the user to explore the \nbehavior of self-limited chemistries inside common reactor configurations.", + "laborHours": 106.4, + "languages": [], + "name": "aldsim", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aldsim/aldsim", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-09-24", + "metadataLastUpdated": "2024-09-24" + }, + "description": "The Spectral Efficiency and Tandem Performance Calculators allow users to test material types for use in tandem photovoltaic devices to better understand if a given material could work well. The Spectral Efficiency (SE) calculator takes a set of current vs voltage (I-V) and quantum efficiency (QE) data along with a spectrum input and plots the spectral efficiency of the cells represented by the datasets for the spectrum provided. The Tandem Performance calculator uses the calculated spectral efficiency of top and bottom cells and the transmission data of the top cell to calculate performance metrics for a tandem device in either a two or four terminal architecture. The SE and Tandem Performance calculators are based on the following publication: Yu, Z., Leilaeioun, M. & Holman, Z. Selecting tandem partners for silicon solar cells. Nat Energy 1, 16137 (2016).", + "laborHours": 957.6, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "Spectral Efficiency and Tandem Performance Calculators [SWR-24-92]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SE-and-Tandems", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "spongda@ornl.gov" + }, + "date": { + "created": "2024-09-24", + "metadataLastUpdated": "2024-10-18" + }, + "description": "The FAR3d model calculates the linear and nonlinear stability properties of energetic particle driven Alfven instabilities for both\ntokamak and stellarator plasma confinement devices using gyro-landau closure methods. This is an important fundamental\nphysics problem for existing fusion energy experiments and for future fusion reactors.", + "laborHours": 16492.0, + "languages": [ + "Fortran" + ], + "name": "FAR3d", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DSfusion/FAR3d", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "SAND2024-12627O\nCausal Spatiotemporal Stencil Learning (CaStLe) is an algorithm for enabling spatiotemporal causal discovery of local dynamics on regularly gridded datasets. CaStLe computes causal graphs over a grid depicting local spatiotemporal causal dependence between neighboring grid cells. It first projects the given gridded spatiotemporal data to a 3x3 reduced coordinate space, in which each grid is represented by a time series that contains the generalized causal dependence between neighboring cells. Then, it augments a given causal discovery algorithm to identify the causal parents of the center cell in the reduced 3x3 space in the Parent Identification Phase (PIP). The result of the PIP is called a stencil. Finally, the algorithm expands the stencil to represent the original grid space.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "Causal Spatiotemporal Stencil Learning (CaStLe)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "SAND2024-12593O\nThe Behavioral Models of Differential Models with a Hammerstein Model code demonstrates how to generate training data, how to use the training data to create a transfer function for the linear time invariant portion of the behavioral model, and how to test that model. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Behavioral Models of Differential Models with a Hammerstein Model", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-10-18" + }, + "description": "SAND2024-11403O\nThe Bayesian Calibration of Stochastic Agent-based Model via Random Forest is a code that was developed in concurrence with an article by the same name that was written for a journal. The code reproduces simulation results and plots from the article. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 603090.4, + "languages": [ + "Python", + "R" + ], + "name": "Bayesian calibration of stochastic agent based model via random forest", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Bayesian-calibration-of-stochastic-agent-based-model-via-random-forest", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "A data ontology defined using the W3C Web Ontology Language (OWL) format. It defines classes and attributes for objects directly implicated in manufacturing such as materials, preform geometries, and manufacturing processes and settings. It also includes classes to describe entities that are instrumental to making digital twins and performing predictive activities on manufacturing data such as designs of experiment and predictive models.", + "laborHours": 0.0, + "languages": [], + "name": "Advanced Manufacturing Basic Entity Relationships Ontology", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/AMBER", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "The Dispatch Optimization Variable Engine (DOVE) is software tool written in python, developed at Idaho National Laboratory (INL) that provides an easily accessible application-programming-interface (API) to performing resource dispatch optimization analysis for integrated energy system (IES) configurations. DOVE is an integral part of the Framework for Optimization of Resources and Economics (FORCE) software suite and is leveraged by codes such as the Holistic Energy Resource Optimization Network (HERON) and the Optimization of Real-Time Capacity Allocation (ORCA). The philosophy behind DOVE is to provide a modular software solution to IES planning and operation by utilizing state-of-the-art algorithms and machine learning. The goal is to accurately capture the dispatching behavior of a complex energy system given varying time-dependent signals for demand and commodity pricing.", + "laborHours": 1535.2, + "languages": [ + "Python" + ], + "name": "Dispatch Optimization Variable Engine", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DOVE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "SAND2024-11300O\nTChem-atm is a software library that was developed to solve complex kinetic models for atmospheric chemistry applications. TChem-atm interface employs a hierarchical parallelism design to exploit the massive parallelism available from modern computing platforms. It also supports gas atmospheric chemistry applications, e.g., the energy exascale earth system model. TChem can be used as a box model or coupled with a climate model to compute the time evolution of gas tracer species. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 34519.2, + "languages": [ + "C++" + ], + "name": "TChem-atm v1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TChem-atm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "SAND2024-11256O\nThe Code for BALDR Study 07.04 software reproduces results from the BALDR study concerning \"Multilabel Proportion Prediction and Out-of-Distribution Detection on Gamma Spectra of Short-Lived Fission Products.\" This code can reproduce a scientific study following the step numbers present in the file names. The scientific study uses synthetic and measured data to find the best model for the radioisotope proportion estimation task of interest and generates results. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1577790.4, + "languages": [ + "Python 3.8" + ], + "name": "Code for BALDR Study 07.04", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/BALDR-Study-07.04", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "The Cyber-Informed Engineering Microgrid Analysis Tool (CIEMAT) leverages the Department of Energy\u2019s Cyber-Informed Engineering to prompt engineering designers and operators through an analysis of the critical functions to be supported by a microgrid installations, the criticality of those functions, the impacts of denial, disruption or misuse of those functions on the microgrid and dependent functions, and the mitigations which could best prevent impacts to those functions resulting from cyber attack. Through use of this tool, microgrid designers and operators can quickly identify appropriate engineering mitigations to limit impacts from cyber attack and functions where engineering and operational staff can prioritize and guide the application of cybersecurity protections to best support the resiliency of the system.", + "laborHours": 0.0, + "languages": [], + "name": "Cyber-informed Engineering Microgrid Analysis Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/CIEMAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pearce8@llnl.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "Thicket is a python-based toolkit for Exploratory Data Analysis (EDA) of parallel performance data that enables performance optimization and understanding of applications\u2019 performance on supercomputers. It bridges the performance tool gap between being able to consider only a single instance of a simulation run (e.g., single platform, single measurement tool, or single scale) and finding actionable insights in multi-dimensional, multi-scale, multi-architecture, and multi-tool performance datasets.", + "laborHours": 18452.8, + "languages": [ + "Python" + ], + "name": "LLNL/thicket", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/thicket", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pearce8@llnl.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "An open collaborative repository for reproducible specifications of HPC benchmarks and cross site benchmarking environments", + "laborHours": 7280.8, + "languages": [ + "Python" + ], + "name": "LLNL/benchpark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/benchpark", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-09-26", + "metadataLastUpdated": "2024-09-26" + }, + "description": "Automatically label regions of histology images.", + "laborHours": 684.0, + "languages": [], + "name": "PNNL-HubMAP-Proteoform-Suite/UnsupervisedSegmentation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-HubMAP-Proteoform-Suite/UnsupervisedSegmentation", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-09-26", + "metadataLastUpdated": "2024-09-26" + }, + "description": "Differentiable land surface model reimplementing an existing simulator, CANOAK, in JAX\u2014a Google-developed Python package for high-performance machine learning research using automatic differentiation. The model's\npurpose is to perform hybrid land surface modeling that seamlessly couples process-based components with deep neural\nnetworks", + "laborHours": 18118.4, + "languages": [], + "name": "pnnl/JAX-CanVeg", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/JAX-CanVeg", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "mcdonnellmt@ornl.gov" + }, + "date": { + "created": "2024-09-27", + "metadataLastUpdated": "2024-10-15" + }, + "description": "Interconnected Science Ecosystem - Software Development Kit (INTERSECT-SDK)", + "laborHours": 6064.8, + "languages": [ + "Python" + ], + "name": "INTERSECT-SDK (Python)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/INTERSECT-SDK/python-sdk", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "delchinimg@ornl.gov" + }, + "date": { + "created": "2024-09-30", + "metadataLastUpdated": "2024-10-01" + }, + "description": "VERTEX-CFD is primary used for safety analysis and design optimization of fusion blankets. VERTEX-CFD has a highly flexible code structure that facilitates the addition of new features such as equations, boundary conditions, and source terms. VERTEX-CFD is designed to run on CPU- and GPU-enabled high-performance computing (HPC) platforms by relying on Kokkos. The code architecture supports a plug-and-play approach allowing equations to be coupled by selecting the correct set of input parameters in the XML format input file. A set of verification and validation problems were run to test VERTEX-CFD solver. VERTEX-CFD implements the incompressible Navier-Stokes equations coupled to a temperature equation and magneto-hydrodynamic equations. This code is being developed for fusion applications.", + "laborHours": 34792.8, + "languages": [ + "C++", + "Python", + "CUDA" + ], + "name": "VERTEX-CFD", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/delcmo/Vertex-CFD", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "Version 1.0" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2024-09-30", + "metadataLastUpdated": "2024-10-02" + }, + "description": "E3SM v3.0.1. First patch release of v3.0. The main purpose of this release is to introduce additional compsets used in v3 simulations and also fix some bugs found in compsets released with 3.0.0. [BUG FIXES] WCYCL20TR and F20TR have an updated landuse timeseries file. Those compsets and F2010 also have corrected nitrogen deposition and population density files for years after 1990. Except for those compsets, the simulated climate is identical for compsets released in v3.0.0. [NEW COMPSETS] New fully coupled compsets, including WCYCLSSP245, WCYCLSSP370, and WCYCLSSP585, which simulate future climate scenarios based on different socio-economic pathways. New single-forcing compsets like WCYCL20TR-GHG (greenhouse gases), and WCYCL20TR-aer (aerosols), allow simulations focusing on specific climate drivers. Two fully coupled compsets with dynamic ice sheets are also available. [GENERAL] Documentation for all components has been created at https://docs.e3sm.org/E3SM/ . All components have new optional features but the defaults have not changed for v3.0.0 supported compsets. The supported resolution is still a \"tri-grid\" as described in v3.0.0. [ATM] Add ability to calculate zonal mean quantities for QBO. Add new diagnostic to output CCN fields per mass of air. Add four new joint histograms to the MODIS simulator. Add alternative data stream control for SO2 species. Fix diagnostic output of in-cloud qc, nc, qi, and ni in P3. Created new User and Technical guide for EAM. Restore ability to output variable along ship/flight tracks Major update to PAM in EAM-MMF: Add adaptive subcycling in driver and enable variance transport by default. Add compsets to facilitate the E3SM-MMF (and E3SM) contributions to phase 1 & 2 of the radiative-convective equilibrium model inter-comparison project (RCEMIP). [LAND] Several fixes to C,N, P balance checks. Optionally modify the ELM snowcapping routing scheme along with the snow and firn compaction schemes to include changes made by Schneider et al. (2022); optionally implement the new snow thermal conductivity calculation method introduced in Fourteau et al. (2021); introduce a new optional format for PFT physiology files (paramfile) that allows user to specify a flexible number of PFTs. Add a LULC file for 1850-2015 at r025; allow output of land fraction used in dust mobilization. [OCEAN] Modify SSS restoring to include under sea ice by default. Fix GOTM interface for vertical mixing. Assign alkalinity equals DIC in sea ice melt, switch ice-shelf melt fluxes to Paolo 2023. Add frazil to ice-shelf melt rates, add distinct passive tracer background vert diffusivity, add parametrized tidal mixing effects to ice shelf basal melt, and add subglacial discharge at grounding line. Improve checks for ocean conservation. [LAND-ICE] Add support for dynamic Greenland Ice sheet and Antarctic Ice Sheet meshes for MALI. Add MALI thermal solver bug fix and improved iceberg handling. Activate MALI thermal solver and update configuration to be relevant to both AIS and GIS grids. [SEA-ICE] Merged vertically resolved biogeochemistry and aerosols from the standard MPAS-Seaice column package into the Icepack library, enabling the option to use Icepack for active biogeochemistry and aerosol simulations. Added a namelist option to use a spatial field for dust-iron solubility rather than a constant. Added capability to read atmospheric dust fluxes and dust-iron solubility maps from an input file. \n[COUPLER] Add ability to robustly recover from failures during restart-file writing, and cryo fields to coupler budget accounting. [Included libraries] update SCORPIO to v1.6.5, Kokkos to 4.2, CIME to 6.1.18. SCORPIO 1.6.5 includes improved support for Perlmutter and Frontier. A new rearranger, PIO_REARR_ANY, was added that lets the library choose the appropriate data rearranger to use.The default I/O NetCDF format (for reading and writing) is changed from \"64-bit offset\" (NetCDF CDF2) to \"64bit-data\" (NetCDF CDF5).", + "laborHours": 1762470.4, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v3.0.1", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v3.0.1", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v3.0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-01", + "metadataLastUpdated": "2024-10-02" + }, + "description": "To maintain/improve the\ndistribution system fault-tolerance for a grid with high penetration of distributed energy resources requires improvement,\nBlockchain can add value to improve fault-tolerant grid operations. That can be achieved using blockchain's core features\nof distributed consensus-based decision-making process and immutability.", + "laborHours": 20672.0, + "languages": [], + "name": "Blockchain-based fault tolerant grid operations system", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/dltDFLISR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2024-10-02", + "metadataLastUpdated": "2024-10-02" + }, + "description": "The missing certificate infrastructure for web APIs.", + "laborHours": 1383.2, + "languages": [ + "Python" + ], + "name": "certified", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/certified.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "bostelmannf@ornl.gov" + }, + "date": { + "created": "2024-10-03", + "metadataLastUpdated": "2024-10-03" + }, + "description": "For most of their lifetime, pebble-bed reactors (PBRs) operate at an equilibrium state in which the core is filled with fuel pebbles at various levels of burnup. A fuel pebble travels multiple times in so-called passes through the reactor before it reaches its target discharge burnup and is replaced with a fresh fuel pebble. Given the stochastic nature of the fuel pebble travel paths and consequently the individual fuel pebble histories, it is not possible with standard methods developed for traditional reactor concepts to calculate the fuel inventory in the reactor core. \nAn iterative approach, the SCALE Leap-In method for Cores at Equilibrium (SLICE), was developed to generate region-average fuel inventory for a PBR. The SLICE code enables automatic generation of input files for the SCALE code system (https://www.ornl.gov/scale), management of the SCALE result files, and analysis of results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SLICE", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/scale/code/slice", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-10-03", + "metadataLastUpdated": "2024-10-03" + }, + "description": "This replication package is a case study on automated deductive verification for Rust for practical\nprograms. It is a companion artifact to a corresponding usability study on verification titled \"Union-Find\nand Usability: A Case Study and Analysis of Rust Formal Verifiers\". It seeks to answer the question \"Can\nRust developers today use Rust verifiers to verify their code?\". To answer this question, the study\ncontrasts the verification experience of two mature Rust verifiers, Creusot and Prusti, by using the tools to\ndevelop a verified implementation of union-find in Rust. The union-find implementation is based on real-world code as used in the popular egg E-graph library. The artifact consists of two different verified\nlibraries, one using Creusot and one using Prusti. The libraries have similar Rust interfaces and high-level\nproofs but differ in their details: Creusot and Prusti have different annotation languages and support\ndifferent proof styles. Each implementation can be verified with its respective tool and compiles as a\ntraditional Rust development.", + "homepageURL": "https://zenodo.org/records/13887654", + "laborHours": 456.0, + "languages": [], + "name": "Replication Package for \"Union-Find and Usability: A Case Study and Analysis of Rust Formal Verifier", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://zenodo.org/records/13887654", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-04", + "metadataLastUpdated": "2024-10-04" + }, + "description": "Cell performance optimization is important for improving the system efficiency of a redox flow battery. To gain better insights into key controlling factors Of system efficiency, this work first proposed a theoretical model for a unit cell by extending a two-dimensional analytic model to a full cell. The model is then used for cell performance optimization after validating it with experimental and numerical modeling data.", + "laborHours": 1808.8, + "languages": [], + "name": "pnnl/EZBattery", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/EZBattery", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-10-04", + "metadataLastUpdated": "2024-10-04" + }, + "description": "EWSMod-2D: A Fortran Code for 2D Elastic-Wave Sensitivity Modeling", + "laborHours": 547.2, + "languages": [], + "name": "lanl/ews", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ews", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-10-04", + "metadataLastUpdated": "2024-10-04" + }, + "description": "The python routines are outlined in detail to perform the methods and results in the manuscript under review in the journal Geophysical Research Letters titled \u201cSeismic features predict ground motions during repeating caldera collapse sequence\u201d with LA-UR-23-33345. All routines are written in open source python and were applied to publicly available data sets. The codes formats the data into the appropriate structure required to train a boosted tree regression model. Other codes produce figure results.", + "laborHours": 486.4, + "languages": [], + "name": "cjohnson-LANL/GRL_Kilauea", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cjohnson-LANL/GRL_Kilauea", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2025-02-24" + }, + "description": "Sonar image classification with Convolution\nNeural Network (CNN)", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 42073.6, + "languages": [], + "name": "Deep Learning for Automated Fish Detection from Sonar Images", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2024-10-07" + }, + "description": "The Fields to Farms methodology illustrates the generation of farm parcels from the Crop Data Layer (CDL), a raster dataset containing 133 categories representing various crop types and land uses. This methodology involves two primary steps: Field Delineation and Farm Aggregation. The code specifically addresses the aggregation of pre-delineated fields within a county to form farms, adhering to predefined criteria for farm size categories. It is assumed that the field delineation process, which involves creating vector polygons from CDL raster, has been completed beforehand, possibly through external tools or methods. Upon initialization, the script processes county-level fields, preparing them for farm aggregation. In the Farm Aggregation phase, the code iteratively combines delineated fields into farms based on specified criteria, continuing until the aggregated farm size meets predefined thresholds derived from data from the 2017 National Agricultural Statistics Service (NASS) census. Throughout this iterative process, the script dynamically adjusts the aggregation to ensure alignment with the desired distribution reported by NASS. The resulting output of the script is a GeoDataFrame containing classified farms, which are subsequently saved as GeoPackage files. These files enable further analysis and visualization, facilitating comprehensive exploration of the farm landscape generated through the methodology.", + "laborHours": 76.0, + "languages": [ + "Python" + ], + "name": "Field To Farm Aggregation For Agricultural Systems", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Field2Farm", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2024-10-07" + }, + "description": "The DeepLynx DAG repository will contain several Airflow DAGs (Directed Acyclic Graphs) which will be used in the context of DeepLynx's deployed Apache Airflow instance. These DAGs will be used for multiple data management tasks for DeepLynx data, including but not limited to:\n- bringing data from various sources and tools into DeepLynx\n- managing sequential data workflows, such as running Python scripts on data to perform analysis and returning the results to DeepLynx\n- performing any necessary transformation or pre-processing on data coming into DeepLynx from external sources or out of DeepLynx to go to external applications", + "laborHours": 258.4, + "languages": [ + "Python" + ], + "name": "Deeplynx Dag Repository", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DLDAGS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2024-10-07" + }, + "description": "Siting Lab contains a collection of user-friendly tutorials and guides for working with the Siting Lab (https://data.openei.org/siting_lab) data within the context of the reV model. The python code examples demonstrate the creation and transformation of Siting Lab data into reV compliant format as well as working with the reV model inputs and outputs.\n\nSpecifically, Siting Lab provides a collection of Jupyter Notebooks that serve as guides for working with data from NREL's spatial analysis portfolio. These notebooks teach users how to create and interact with reV data in order to facilitate external use of the model. The guides in this repository reference NREL's Supply Curve data as well as Siting Lab spatial data available on OEDI.", + "laborHours": 532.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "Siting Lab [SWR-24-95]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SitingLab", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2024-10-07" + }, + "description": "This software accompanies an NREL-designed machine for observing changes in optical density of 16 biological samples growing in Hungate tubes. It involves hardware & app for Multi-Tube OD Reader.\n\nOur Multi-Tube-OD-Reader device is based on the TubeOD reader (linked below), but with a housing to maximize throughput.\n\nThis repository contains the schematics for 3D printing an enclosure, a parts list for constructing, and the code for controlling the 16-tube, in-line optical density monitoring device. This device and software are particularly useful for researchers studying microbes that grow well in Hungate tubes, but are not amenable to growth in microplate readers.\n\nRelated publication: https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2021.790576/full", + "laborHours": 623.2, + "languages": [ + "Python" + ], + "name": "Multi-tube-OD-reader [SWR-24-126]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Multi-Tube-OD-Reader", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-09", + "metadataLastUpdated": "2024-10-09" + }, + "description": "SAND2021-2751 O\nThe Offshore Wind ENergy Simulation Toolkit (OWENS) is a collection of aerodynamic, structural, hydrodynamic, drivetrain, controls, composite structure and mesh preprocessing, and data postprocessing. OWENS is primarily an ontology, or glue code, pulling together many open-source and Sandia-developed libraries to model the aero-servo-hydro-elastic physics of wind and marine energy turbines. The toolkit\u2019s intended use is for arbitrary aeroelastic rotor configurations analysis including vertical-axis wind turbines, horizontal-axis wind turbines, and analogous marine energy applications for fixed-bottom and floating configurations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525", + "laborHours": 11962.4, + "languages": [ + "Julia", + "Fortran" + ], + "name": "Offshore Wind ENergy Simulation Toolkit (OWENS)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/OWENS.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.00" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-09", + "metadataLastUpdated": "2024-10-09" + }, + "description": "SAND2024-13027O\nThe CHMMPP: A c++ Library for Constrained Hidden Markov Models (HMM) software supports the analysis of multivariate time series data to detect patterns using HMM. Many applications involve the detection and characterization of hidden or latent states in a complex system using observable states and variables. This software supports inference of latent states integrating both an HMM and application-specific constraints that reflect known relationships in hidden states. The CHMMPP software supports application-specific and generic methods for constrained inference. This includes a framework for customized Viterbi methods, constrained inference of hidden states with A* and integer programming methods, and various constraint-informed methods for learning HMM model parameters. CHMMPP focuses on supporting generic methods that enable the agile expression of complex sets of constraints that naturally arise in many real-world applications.", + "laborHours": 4028.0, + "languages": [ + "C++" + ], + "name": "CHMMPP: A c++ library for constrained Hidden Markov Models", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/chmmpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-10-10", + "metadataLastUpdated": "2024-10-10" + }, + "description": "This software provides dislocation-type defect identification and segmentation using a standard open source computer vision model, YOLOv8, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of expert annotated micrographs for training. This model demonstrates the ability to segment both dislocation lines and loops concurrently in micrographs with high pixel noise levels and on multiple alloys. It includes multiple layers of frozen layers used for transfer learning from multidisciplinary data and is extensible to alloys that are not included in the training dataset.", + "laborHours": 136.8, + "languages": [ + "Python" + ], + "name": "Post Irradiation Examination Dislocation Defect Detection Software", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/PANDA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-14", + "metadataLastUpdated": "2024-10-14" + }, + "description": "APT Clustering Visualizer", + "laborHours": 197.6, + "languages": [], + "name": "pnnl/APTVIZ", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/APTVIZ", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-14", + "metadataLastUpdated": "2024-10-14" + }, + "description": "Vidyut3d is a massively-parallel plasma-fluid solver for low-temperature plasmas (LTPs) that supports both local field (LFA) and local mean energy (LMEA) approximations, as well as complex gas and surface-phase chemistry. The solver supports 2D and 3D domains, and uses AMReX's adaptive mesh refinement capabilities to increase the grid resolution around complex structures (e.g. streamer heads and sheaths) while maintaining a tractable problem size. Vidyut specializes in simulating various types of gas-phase discharges, as well as plasma/surface interactions and surface chemistry (e.g. for plasma-mediated catalysis applications). The solver also supports hybrid CPU/GPU parallelization strategies, and has demonstrated excellent scaling on various HPC architectures for problem sizes consisting of O(100 M) control volumes.", + "laborHours": 21173.6, + "languages": [ + "C++", + "Python" + ], + "name": "Vidyut3d: A Non-Equilibrium Plasma Modeling Tool [SWR-24-101]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/vidyut3d", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-15", + "metadataLastUpdated": "2024-10-15" + }, + "description": "SAND2024-11125O\nThe Maximum Switching Throughput Density Estimator software performs a simple analysis that estimates the maximum logic switching throughput density that\u2019s achieved in various CMOS technology nodes on the International Roadmap for Devices and Systems. This software utilizes simple device models and optimization techniques, performing a simple sweep over a range of possible logic supply voltages, and analytically calculating the maximum switching frequency for the given logic voltage that meets the power density constraint. It does this by using simple models of power dissipation in conventional and fully adiabatic switching. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 167.2, + "languages": [ + "MATLAB" + ], + "name": "Maximum Switching Throughput Density Estimator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/max-cmos-throughput", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v.0.15w (beta) script version" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-15", + "metadataLastUpdated": "2024-10-15" + }, + "description": "SAND2024-10158O\nPython HITMIX is a software package for computing hitting time moments of vertices in a graph. Hitting time moments can be used to rank the strengths of relationships between vertices in a graph. Examples are provided for computing and using hitting time moments on generic graphs and similarity graphs arising from the analysis of text documents in information retrieval applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 243.2, + "languages": [ + "python" + ], + "name": "Python HITMIX", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hitmix", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-10-16", + "metadataLastUpdated": "2024-10-16" + }, + "description": "This package consists of simulations of control algorithms being proposed for upcoming adaptive optics\nprojects for exoplanet direct imaging, in which one wavefront affector (deformable mirror) is controlled by\ntwo wavefront sensors. Simulations include time-domain behavior under various assumed conditions,\nparameter optimization routines for the controllers, and stability analysis.", + "laborHours": 2295.2, + "languages": [], + "name": "Control Algorithms for Multi-Wavefront Sensor Adaptive Optics for Astronomical Exoplanet Imaging", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/multiwfs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-17", + "metadataLastUpdated": "2024-10-17" + }, + "description": "SAND2024-08692O\nThe Gaussian Integral Inner Products (GIIP) calculates the integral of squared difference of atomic density functions minimized over the orthogonal group. It uses the hyper-spherical coverings library to sample orthogonal group.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 17069.6, + "languages": [ + "Python 3" + ], + "name": "GIIP (Gaussian Integral Inner Products)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/giip", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-17", + "metadataLastUpdated": "2024-11-04" + }, + "description": "SAND2024-08577O\nCanonical and Noncanonical Hamiltonian Operator Inference is research code that applies old and new model reduction algorithms to well-known and publicly available \"toy\" problems. It applies operator inference (OpInf) methods for model reduction to several benchmark hyperbolic partial differential equations: linear wave, Korteweg-de Vries, Benjamin-Bona-Mahoney, and linear elasticity.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 576171.2, + "languages": [ + "Python 3.8" + ], + "name": "Canonical and Noncanonical Hamiltonian Operator Inference", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HamiltonianOpInf", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-10-18", + "metadataLastUpdated": "2024-10-18" + }, + "description": "FTTN is a test suite to evaluate the numerical behaviors of matrix accelerators of GPUs (NVIDIA Tensor\nCores and AMD Matrix Cores) in a quick and simple setting. Matrix accelerators are heavily used in\ntoday's computationally intense applications to speed up matrix multiplications. This test suite provides a\ncomprehensive study on the numerical behaviors of these accelerators, including support for subnormals,\nrounding modes, extra precision bits and FMA features.\nIs there", + "laborHours": 1474.4, + "languages": [], + "name": "FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FTTN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "hespelersc@ornl.gov" + }, + "date": { + "created": "2024-10-22", + "metadataLastUpdated": "2024-10-22" + }, + "description": "Fault detection in Controller Area Network (CAN) systems is crucial for ensuring the reliability and safety of automotive and industrial applications. This study investigates and compares the effectiveness of time series classification models for supervised fault detection in CAN data. This repository contains the code and data for our benchmarking experiment aimed at detecting intermittent faults in automotive Controller Area Network (CAN) data. The goal of this project is to compare various machine learning (ML) and deep learning (DL) models using different Time Series Cross-Validation (TSCV) techniques to evaluate their effectiveness in a streaming environment for fault detection.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Multivariate Time Series Intermittent Fault Detectionin Controller Area Network CAN", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/TovNephesh/Multivariate-Time-Series-Intermittent-Fault-Detection-in-Controller-Area-Network-CAN-", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08551O\nThe Spatial Environmental Assessment Tool (SEAT) evaluates potential environmental risk associated with marine energy device deployment by coupling modeled impacts with risk severity maps. As a graphical user interface-based software, it interacts with marine energy stressor and receptor data to evaluate the risk of changes to marine environment. SEAT, which relies on spatial and temporal data, is a plug-in for geospatial software QGIS. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 4286.4, + "languages": [ + "python" + ], + "name": "Spatial Environmental Assessment Tool (SEAT)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seat-qgis-plugin", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08549O\nPyTorch Circuit-Aware Bit-Cell Modeling, a Python library, demonstrates circuit-aware training for analog machine learning accelerators. Built upon PyTorch, this software provides hardware-aware versions of common neural network layers to mitigate non-ideal behavior from novel hardware. The software provides accurate forward and backward pass estimates for hardware-mapped neural networks that are implemented in crossbars (arrays) that contain a non-linear transistor selector device. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 3784.8, + "languages": [ + "python" + ], + "name": "PyTorch Circuit-Aware Bit-Cell Modeling", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08546O\nThe underground hydrogen gas salt cavern (uh2sc) simulator software will be used to understand how hydrogen gas injection and extraction rates affect energy efficiency of weekly to monthly H2 storage. Salt cavern dynamics include: Heat transfer to the surrounding walls, gas dynamics, dissolution into brine at the bottom of caverns, multi-species gas mixtures of H2 and natural gas or other cushion gasses, and structural creep of the salt cavern or closure due to under-pressure in the cavern. The model is designed to interface with surface hydrogen system dynamics models via co-simulation. This is so it can be used as an individual tool to understand injection and extraction of H2, common faults in caverns (i.e. a leak vs. creep closure or other issues), model predictive control, and other applications. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 15.2, + "languages": [ + "Python" + ], + "name": "uh2sc simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/uh2sc", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08545O\nAlpheus is the code implementation of an advanced data structure addressing the technical challenge of analyzing a continuous data stream that is too big to fit in a computer's memory. Alpheus reports when explicitly-defined conditions on the data in the stream are met. Though the software doesn\u2019t have a specific application domain, it was built to address challenges in cybersecurity. The software includes a representative cybersecurity data set, as well as simulated attack and benign activity.\n\nThe software\u2019s capabilities are critical to real-world application. For example, it can operate with unlimited-sized data streams while maintaining the same theoretical performance and reporting guarantees. The code\u2019s authors also improved execution performance by leveraging persistent memory. \n\nThe code is designed for use by the technical reviewers for the Algorithm Engineering and Experiments conference run by the Society for Industrial and Applied Mathematics.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "python", + "Bash" + ], + "name": "Alpheus", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08541O\nSTTPHAWKES software solution is a Bayesian estimation approach to a Hawkes process model that treats missing data as a latent variable in the estimation. The open-source software will be released to the R CRAN repository and Sandia National Labs\u2019 Github.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 3526.4, + "languages": [ + "R", + "C++" + ], + "name": "STPPHAWKES", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/stpphawkes", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-11-05" + }, + "description": "SAND2024-08539O\nThe High Performance GMRES Mixed-Precision (HPG-MxP) is a benchmark for ranking high-performance supercomputers, allowing use of mixed-precision. Similar to HPCG benchmark, it is designed to profile the computers' capabilities to perform the computational and communication tasks that are commonly found in important classes of real-world applications. At the same time, like HPL-MxP benchmark, it allows the use of mixed-precision arithmetic, while ensuring the double-precision accuracy of the computed solution.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 2888.0, + "languages": [ + "C++" + ], + "name": "High-Performance GMRES Mixed-Precision (HPG-MxP) Benchmark", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/iyamazaki/hpcg", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08511O\nThe Hydrogen Extremely Low Probability of Rupture (HELPR) software toolkit provides probabilistic fracture assessments of natural gas infrastructure for transporting hydrogen. Using probabilistic sampling and sensitivity analysis\u2014along with engineering fatigue and fracture mechanics\u2014 the software develops models that can predict structural integrity measures for natural gas pipelines under stress. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 7630.4, + "languages": [ + "Python", + "QML" + ], + "name": "Hydrogen Extremely Low Probability of Rupture Version 1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/helpr", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08478O\nThe spot_bt_ros tool allows users to easily construct complex autonomous behaviors for Boston Dynamic's Spot robot without having to overly rely on the Spot software development kit (SDK). This package specifically allows a user to run the Robot Operating System 2 alongside the SDK. Using a form-of-state machine called a \"behavior tree,\u201d the software develops different \"leaves\" or actions that the robot undergoes. Attaching multiple actions in sequence creates a \"branch\" and several of these make up the \"tree.\"\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1687.2, + "languages": [ + "python 3.10", + "ROS Humble" + ], + "name": "spot_bt_ros v.0.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spot_bt_ros", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08430O\nspot_bt allows users to easily construct complex, autonomous behaviors without having to overly rely on Boston Dynamic\u2019s Spot robot software development kit. Using a form-of-state machine called a \"behavior tree,\" the software develops and applies different \"leaves\" or actions to the robot. Attaching multiple actions in sequence creates a \"branch,\" and a series of these make up the \"tree.\" The software works on any x86 or aarch64 hardware but must run on a Linux OS. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525", + "laborHours": 1550.4, + "languages": [ + "Python 3.10" + ], + "name": "spot_bt v.0.1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spot_bt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.1" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-24", + "metadataLastUpdated": "2024-10-24" + }, + "description": "The Renewable Energy and Storage Cybersecurity Research (RESCue) project is a collaborative effort aimed at securing the rapidly growing deployment of transmission-connected hybrid renewable energy systems, consisting of a combination of wind, solar, and/or energy storage equipment, against escalating cyber threats. This project brings together major original equipment manufacturers (OEMs) of wind, solar, and energy storage, along with major asset owners and DOE National Laboratories, to collectively identify cyber threats, assess risks, and develop robust cybersecurity strategies and solutions. The development of hybrid reference architectures has provided comprehensive blueprints for the secure design and integration of hybrid renewable energy systems, accounting for their unique characteristics and interdependencies. Additionally, NREL has created a cyber-resilient design framework that integrates cybersecurity considerations from the start of the system lifecycle, ensuring security is \"baked in\" from the initial design phase.\n\nThe research thrusts for the project included (i) development of hybrid reference architectures and (ii) a cyber-resilient design framework for hybrid energy systems. The reference architectures has provided comprehensive blueprints for the secure design and integration of hybrid renewable energy systems, accounting for their unique characteristics and interdependencies. Additionally, NREL has created a cyber-resilient design framework that integrates cybersecurity considerations from the start of the system lifecycle, ensuring security is \"baked in\" from the initial design phase. A demonstration experiment was developed for one of the architectures using NREL's Cyber Range resources. This experiment configuration, deployable using open-source tools, is provided here in this repository. Additional models were developed for the wind and solar architectures as well, however the configurations for only the Energy Storage scenario are provided here: https://www.nrel.gov/docs/fy24osti/89921.pdf", + "laborHours": 2173.6, + "languages": [ + "Python", + "Shell" + ], + "name": "RESCue Model (RESCue Experiment and Model) [SWR-24-84]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/RESCue", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-24", + "metadataLastUpdated": "2025-01-08" + }, + "description": "Acoustic tomography seeks the best-fit fluctuating velocity and temperature fields that explain a collection of signal travel times in a region of interest. This codebase defines an end-to-end framework for executing turbulent field retrievals from acoustic signals, acoustic signal design and processing tools for the physical array, and analysis tool that leverage virtual acoustic tomography arrays based on large-eddy simulations of the atmospheric boundary layer.", + "laborHours": 22739.2, + "languages": [ + "CSS", + "HTML", + "TeX", + "JavaScript", + "Python" + ], + "name": "ATom (Acoustic Tomography Processing Suite) [SWR-24-120]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ATom", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2024-10-24", + "metadataLastUpdated": "2024-10-24" + }, + "description": "The Behavior, Energy, Autonomy, and Mobility (BEAM) model is an integrated, agent-based travel demand simulation framework. Individual agents express preferences through a utility- maximizing evolutionary algorithm that minimizes each individual\u2019s cost and time spent traveling via diverse modal options, including the competition for scarce supply resources such as parking spaces and charging infrastructure. BEAM simulates the essential elements that compose a dynamic transportation system. From the road network, parking and charging infrastructure, to the transit system and a synthetic population with plans and preferences, the virtual system is an amalgamation of multiple spatially resolved layers that together represent an integrated transportation system. \n\nBEAM is an extension to the MATSim (Multi-Agent Transportation Simulation) model, where agents employ reinforcement learning across successive simulated days to maximize their personal utility through plan mutation (exploration) and selecting between previously executed plans (exploitation). The BEAM model shifts some of the behavioral emphasis in MATSim from across-day planning to within- day planning, where agents dynamically respond to the state of the system during the mobility simulation. In BEAM, agents can plan across all major modes of travel including driving, walking, biking, transit, and demand-responsive ride hailing. It is designed to integrate with other open source transportation models, such as ActivitySim.", + "laborHours": 58200.8, + "languages": [], + "name": "Behavior, Energy, Autonomy, Mobility Modeling Framework (BEAM) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-UCB-STI/beam", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "lensor@illinois.edu" + }, + "date": { + "created": "2024-10-29", + "metadataLastUpdated": "2024-10-29" + }, + "description": "The robust nature of the non-conventional yeast Issatchenkia orientalis allows it to grow under highly acidic conditions and therefore, has gained increasing interest in producing organic acids using a variety of carbon sources. Recently, the development of a genetic toolbox for I. orientalis, including an episomal plasmid, characterization of multiple promoters and terminators, and CRISPR-Cas9 tools, has eased the metabolic engineering efforts in I. orientalis. However, multiplex engineering is still hampered by the lack of efficient multicopy integration tools. To facilitate the construction of large, complex metabolic pathways by multiplex CRISPR-Cas9-mediated genome editing, we developed a bioinformatics pipeline to identify and prioritize genome-wide intergenic loci and characterized 47 gRNAs located in 21 intergenic regions. These loci are screened for guide RNA cutting efficiency, integration efficiency of a gene cassette, the resulting cellular fitness, and GFP expression level. We further developed a landing pad system using components from these well-characterized loci, which can aid in the integration of multiple genes using single guide RNA and multiple repair templates of the user\u2019s choice. We have demonstrated the use of the landing pad for simultaneous integrations of 2, 3, 4, or 5 genes to the target loci with efficiencies greater than 80%. As a proof of concept, we showed how the production of 5-aminolevulinic acid can be improved by integrating five copies of genes at multiple sites in one step. We have further demonstrated the efficiency of this tool by constructing a metabolic pathway for succinic acid production by integrating five gene expression cassettes using a single guide RNA along with five different repair templates, leading to the production of 9 g/L of succinic acid in batch fermentations. This study demonstrates the effectiveness of a single gRNA-mediated CRISPR platform to build complex metabolic pathways in a non-conventional yeast. This landing pad system will be a valuable tool for the metabolic engineering of I. orientalis.", + "laborHours": 197.6, + "languages": [], + "name": "A Landing Pad System for Multicopy Gene Integration in Issatchenkia orientalis", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Zhao-Group/Landing-pad-model", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-29", + "metadataLastUpdated": "2024-10-29" + }, + "description": "PLUMES2.0 is a revived version of the Visual Plumes model that was developed by Dr. Walter Frick at USEPA. PLUMES2.0\nand Visual Plumes are codes that compute initial and far-field dilution of buoyant discharges into receiving fresh or marine\nenvironments.", + "laborHours": 15.2, + "languages": [ + "Fortran" + ], + "name": "PLUMES 2.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ssmc-uw/PLUMES2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-10-30", + "metadataLastUpdated": "2024-10-30" + }, + "description": "Biofuels policies induce land use changes (LUC), including cropland expansion and crop switching, and this in turn alters water and soil management practices. Policies differ in the extent and type of land use changes they induce and therefore in their impact on water resources. We quantify and compare the spatially varying water impacts of biofuel crops stemming from LUC induced by two different biofuels policies by coupling a biophysical model with an economic model to simulate the economically viable mix of crops, land uses, and crop management choices under alternative policy scenarios. We assess the outputs of an economic model with a high-resolution crop-water model for major agricultural crops and potential cellulosic feedstocks in the US to analyze the impacts of three alternative policy scenarios on water balances: a counterfactual \u2018no-biofuels policy\u2019 (BAU) scenario, a volumetric mandate (Mandate) scenario, and a clean fuel-intensity standard (CFS) scenario incentivizing fuels based on their carbon intensities. While both biofuel policies incentivize more biofuels than in the counterfactual, they differ in the mix of corn ethanol and advanced biofuels from miscanthus and switchgrass (more corn ethanol in Mandate and more cellulosic biofuels in CFS). The two policies differ in their impact on irrigated acreage, irrigation demand, groundwater use and runoff. Net irrigation requirements increase 0.7% in Mandate and decrease 3.8% in CFS, but in both scenarios increases are concentrated in regions of Kansas and Nebraska that rely upon the Ogallala aquifer for irrigation water. Our study illustrates the importance of accounting for the overall LUC and shifts in agricultural production and management practices in response to policies when assessing the water impacts of biofuels.", + "laborHours": 1185.6, + "languages": [], + "name": "jacobteter/CropWatR", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jacobteter/CropWatR", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-10-31", + "metadataLastUpdated": "2024-10-31" + }, + "description": "Untargeted metabolomics can detect more than 10\u202f000 peaks in a single LC\u2013MS run. The correspondence between these peaks and metabolites, however, remains unclear. Here, we introduce a Peak Annotation and Verification Engine (PAVE) for annotating untargeted microbial metabolomics data. The workflow involves growing cells in 13C and 15N isotope-labeled media to identify peaks from biological compounds and their carbon and nitrogen atom counts. Improved deisotoping and deadducting are enabled by algorithms that integrate positive mode, negative mode, and labeling data. To distinguish metabolites and their fragments, PAVE experimentally measures the response of each peak to weak in-source collision induced dissociation, which increases the peak intensity for fragments while decreasing it for their parent ions. The molecular formulas of the putative metabolites are then assigned based on database searching using both m/z and C/N atom counts. Application of this procedure to Saccharomyces cerevisiae and Escherichia coli revealed that more than 80% of peaks do not label, i.e., are environmental contaminants. More than 70% of the biological peaks are isotopic variants, adducts, fragments, or mass spectrometry artifacts yielding \u223c2000 apparent metabolites across the two organisms. About 650 match to a known metabolite formula based on m/z and C/N atom counts, with 220 assigned structures based on MS/MS and/or retention time to match to authenticated standards. Thus, PAVE enables systematic annotation of LC\u2013MS metabolomics data with only \u223c4% of peaks annotated as apparent metabolites.", + "laborHours": 562.4, + "languages": [], + "name": "xxing9703/PAVE", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xxing9703/PAVE", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Plasmids harbor transferable genes that contribute to the functional repertoire of microbial communities, yet their contributions to metagenomes are often overlooked. Environmental plasmids have the potential to spread antibiotic resistance to clinical microbial strains. In soils, high microbiome diversity and high variability in plasmid characteristics present a challenge for studying plasmids. To improve the understanding of soil plasmids, we present RefSoil+, a database containing plasmid sequences from 922 soil microorganisms. Soil plasmids were larger than other described plasmids, which is a trait associated with plasmid mobility. There was a weak relationship between chromosome size and plasmid size and no relationship between chromosome size and plasmid number, suggesting that these genomic traits are independent in soil. We used RefSoil+ to inform the distributions of antibiotic resistance genes among soil microorganisms compared to those among nonsoil microorganisms. Soil-associated plasmids, but not chromosomes, had fewer antibiotic resistance genes than other microorganisms. These data suggest that soils may offer limited opportunity for plasmid-mediated transfer of described antibiotic resistance genes. RefSoil+ can serve as a reference for the diversity, composition, and host associations of plasmid-borne functional genes in soil, a utility that will be enhanced as the database expands. Our study improves the understanding of soil plasmids and provides a resource for assessing the dynamics of the genes that they carry, especially genes conferring antibiotic resistances.", + "laborHours": 304.0, + "languages": [], + "name": "ShadeLab/RefSoil_plasmids", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ShadeLab/RefSoil_plasmids", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-12-10" + }, + "description": "An R implementation of a modified version of the sparse Bayesian polynomial chaos expansion algorithm of Shao et al., (2017).", + "laborHours": 501.6, + "languages": [], + "name": "khaos", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/knrumsey/khaos", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2025-04-24" + }, + "description": "Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. We train a random forest machine learning model to predict snow depth from variability in ground surface temperature. To our knowledge, this is the first time that small ground surface temperature sensors have been used to estimate snow depth. The model performs well at sites where the model was trained and at pan-arctic evaluation sites (RMSE <= 0.15 m). Small temperature sensors are cheap and easy-to-deploy, so this technique enables spatially distributed and temporally continuous snowpack monitoring to an extent previously infeasible. The model is flexible and can be applied to datasets retroactively to retrieve snow depth estimates at additional sites. This code package includes a *.joblib file of the trained random forest model and a *.ipynb file showing how to clean input data, train the random forest model, and apply the model.", + "laborHours": 45.6, + "languages": [], + "name": "Code Description for \"Brief Communication: Monitoring snow depth using small, cheap, and easy-to-deploy ground surface temperature sensors\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cbachand-LANL/iButton-SnowDepth-ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "This package contains R&D python codes that can nowcast >2 MeV electron distributions in the Earth's outer radiation belt, using LANL's GPS electron data (publicly available) as the primary driver. Functions of this PreMevE-MEO model has been described with details in a manuscript titled \"PreMevE-MEO: Predicting Ultra-relativistic Electrons Using Observations from GPS Satellites\" (LA-UR-24-23843), which has been submitted to Space Weather Journal.", + "laborHours": 2568.8, + "languages": [], + "name": "cheny-lanl/PreMevE-MEO-2024", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cheny-lanl/PreMevE-MEO-2024", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Python library for the calculation of benchmark dose response curves", + "laborHours": 1337.6, + "languages": [ + "Python" + ], + "name": "PNNL-CompBio/bmdrc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/bmdrc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "A collection of solid body modeling tools for 2D sketched, 2D axisymmetric, and 3D revolved models. It also contains general purpose meshing and image generation utilities appropriate for any model, not just those created with this package. Implemented for Abaqus and Cubit as backend modeling and meshing software. Orginal implementation targeted Abaqus so most options and descriptions use Abaqus modeling concepts and language.\n\nTurbo-Turtle makes a best effort to maintain common behaviors and features across each third-party software\u2019s modeling concepts. As much as possible, the work for each subcommand is performed in Python 3 to minimize solution approach duplication in third-party tools. The third-party scripting interface is only accessed when creating the final tool specific objects and output. The tools contained in this project can be expanded to drive other meshing utilities in the future, as needed by the user community.\n\nThis project derives its name from the origins as a sphere partitioning utility following the turtle shell (or soccer ball) pattern.s.", + "laborHours": 5000.8, + "languages": [], + "name": "Turbo-Turtle v0.12.1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-aea/turbo-turtle", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Rayleigh is a 3-D convection code designed for the study of dynamo behavior in spherical geometry. It evolves the incompressible and anelastic MHD equations in spherical geometry using a pseudo-spectral approach.", + "laborHours": 34169.6, + "languages": [], + "name": "LANL contributions to Rayleigh", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/geodynamics/Rayleigh", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Multiplexed proteomics has emerged as a powerful tool to measure relative protein expression levels across multiple conditions. The relative protein abundances are inferred by comparing the signals generated by isobaric tags, which encode the samples\u2019 origins. Intuitively, the trust associated with a protein measurement depends on the similarity of ratios from the protein\u2019s peptides and the signal-strength of these measurements. However, typically the average peptide ratio is reported as the estimate of relative protein abundance, which is only the most likely ratio with a very naive model. Moreover, there is no sense on the confidence in these measurements. Here, we present a mathematically rigorous approach that integrates peptide signal strengths and peptide-measurement agreement into an estimation of the true protein ratio and the associated confidence (BACIQ).\n\nThe main advantages of BACIQ are:\n\nIt removes the need to threshold reported peptide signal based on an arbitrary cut-off, thereby reporting more measurements from a given experiment;\nConfidence can be assigned without replicates;\nFor repeated experiments BACIQ provides confidence intervals for the union, not the intersection, of quantified proteins; and\nFor repeated experiments, BACIQ confidence intervals are more predictive than confidence intervals based on protein measurement agreement.\nTo demonstrate the power of BACIQ, we reanalyzed previously published data on subcellular protein movement upon treatment with an Exportin-1 inhibiting drug. We detect ~2x more highly significant movers, down to subcellular localization changes of ~1% . Thus, our method drastically increases the value obtainable from quantitative proteomics experiments helping researchers to interpret their data and prioritize resources. To make our approach easily accessible we distribute it via a Python/Stan package.", + "laborHours": 364.8, + "languages": [], + "name": "wuhrlab/BACIQ", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/wuhrlab/BACIQ/?tab=GPL-3.0-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wuhrlab/BACIQ", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2025-02-24" + }, + "description": "Code built on Archive Walker. The Generator Scorecard analyzes power grid measurements to automate the process of evaluating the performance of generators. The tool includes three aspects: frequency response, voltage response, and voltage schedule tracking.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 201217.6, + "languages": [], + "name": "Generator Scorecard", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Crowd-sourcing incorporates common citizens as rich sources of data and is promising for environmental monitoring. In this paper, we propose and test the idea of incorporating incentives to crowd-sourcing management for rainfall monitoring. Specifically, we modeled the allocation of incentives (quantitatively measurable and limited rewards) among crowd-sourcing participants for a theoretical rainfall monitoring case. For this purpose, we developed an integrated model comprising a reward allocation component to represent the decision\u2010making process of a central manager, an agent\u2010based model to simulate the interactions between the manager and participants, and a rainfall simulation model to evaluate the effectiveness of various reward allocation policies. We simulated six reward allocation policies of varying levels of administrative cost, and consideration of participant and rainfall spatial heterogeneities. The results suggest the performance of each policy to improve with the reward budget and their spatial uniformity. Among the six policies tested, we found that the participant density weighted maximum participation policy yields the most accurate estimation of rainfall intensity due to its more explicit consideration of the spatial distribution of participants; however, this policy associates with a high administrative cost. This highlights the trade\u2010off between performance and cost in designing effective reward allocation policies. This paper provides a physical and behavior simulation modeling tool to study the feasibility and complexity of reward\u2010based participant management for crowd-sourcing rainfall monitoring. The proposed crowd-sourcing method is beneficial for a wide range of applications that require rainfall data with fine resolution, such as stormwater management and water availability and biomass assessment for food and energy crops.", + "laborHours": 319.2, + "languages": [], + "name": "Pan-YANG/RA-ABM", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pan-YANG/RA-ABM", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "This script is intended to provide a starting point for users to implement the equivalent soil mass (ESM) approach for calculating soil organic carbon (SOC) stocks and SOC mass percentages (commonly called \u201cSOC concentration\u201d). The user should read this readme file and understand how the script works before using it. The script contains some basic error checking algorithms, but it cannot catch all data entry mistakes. It is possible to misuse the script and produce invalid results. The script was designed to work on individual soil cores that have been divided into three or more contiguous segments, as the cubic spline function contains four coefficients. The script has not been tested on soil cores containing fewer than three contiguous segments. If only one segment is present, interpolation will necessarily be linear rather than cubic, which is expected to result in higher predictive error (Wendt & Hauser, 2013). Considering the wide range of potential applications, the script should not be expected to function correctly in all situations. The user is encouraged to modify or rewrite the script to meet their specific needs.", + "laborHours": 76.0, + "languages": [], + "name": "cabbi-bio/ESM-R-script", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cabbi-bio/ESM-R-script/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cabbi-bio/ESM-R-script", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-11-03", + "metadataLastUpdated": "2024-11-03" + }, + "description": "A python library to enable readout of data from commercial H3D gamma-ray detectors. This software perform readout of data and system status, as well as starting and stopping measurements, with either WebREST (HTTP), XML (N42.42), or Binary (FlatBuffers) interfaces.", + "laborHours": 1550.4, + "languages": [], + "name": "H3D Data Acquisition Software (H3DDAQ) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/lbl-anp/h3d_tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-04", + "metadataLastUpdated": "2024-11-19" + }, + "description": "Scikit-SUNDAE provides Python bindings to SUNDIALS integrators. The implicit differential algebraic (IDA) solver and C-based variable-coefficient ordinary differential equations (CVODE) solver are both included.\n\nThe name SUNDAE combines (SUN)DIALS and DAE, which stands for differential algebraic equations. Solvers specific to DAE problems are not frequently available in Python. An ordinary differential equation (ODE) solver is also included for completeness. ODEs can be categorized as a subset of DAEs (i.e., DAEs with no algebraic constraints).\n\nhttps://pypi.org/project/scikit-sundae", + "laborHours": 8375.2, + "languages": [ + "Makefile", + "C", + "Python", + "Cython" + ], + "name": "scikit-SUNDAE ((SUN)DIALS Differential Algebraic Equations) [SWR-24-137]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/scikit-sundae", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-04", + "metadataLastUpdated": "2024-11-04" + }, + "description": "CoNSEPT is a tool to predict gene expression in various cis and trans contexts. Inputs to CoNSEPT are enhancer sequence, transcription factor levels in one or many trans conditions, TF motifs (PWMs), and any prior knowledge of TF-TF interactions.", + "laborHours": 90166.4, + "languages": [], + "name": "PayamDiba/Manuscript_tools", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PayamDiba/Manuscript_tools", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-04", + "metadataLastUpdated": "2024-11-04" + }, + "description": "A dynamic systems model of C4 photosynthesis was developed based on the previous NADP-ME metabolic model for maize (Wang et al., 2014 ab). The NADP-ME metabolic model is an ordinary differential equation model including all individual steps in C4 photosynthetic carbon metabolism. Here, the model is extended to include posttranslational regulation and temperature response of enzyme activities, dynamic stomata conductance, and leaf energy balance. This model is written in Matlab (R2019a)\n\nSteady-state and dynamic gas exchange data for maize (B73), sugarcane (CP88-1762) and sorghum (Tx430) were measured in a greenhouse in Urbana, IL from July 25, 2019 through August 8, 2019. Data include:\n\nCO2 response curves\nLight response curves\nPhotosynthetic induction curves measured in the transition from darkness to high light (1800 \u03bcmol m-2 s-1), data logged every 1 min.\nPhotosynthetic induction in the transition from darkness to high light (1800 \u03bcmol m-2 s-1) to determine the kinetics of rubisco activation in these C4 crops (\u03c4_Rubisco), data logged every 10 s.\nGas exchange under fluctuating light. After dark adaptation, the leaves undergo three light change steps, light intensity was set as 1800 \u00b5mol m-2 s-1, 200 \u00b5mol m-2 s-1 and 1800 \u00b5mol m-2 s-1 for each 1800 s step.", + "laborHours": 1261.6, + "languages": [], + "name": "yuwangcn/C4_dynamic_model", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yuwangcn/C4_dynamic_model", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-11-04", + "metadataLastUpdated": "2024-11-04" + }, + "description": "A simple tool allowing recording the execution of a GPU (CUDA) kernel and replaying that kernel as an\nindependent executable.\nThe tool operates in 3 phases. During compile time the user needs to apply a provided LLVM pass to\ninstrument the code. The pass detects all device global variables\nand device functions and stores this information with the respective LLVM-IR in the global device\nmemory. The compilation generates a record-able executable.\nThe second phase involves running the application executable with a desired input and using\nLD_PRELOAD to enable recording. When recording before invoking a device kernel\nthe pre-loaded library stores device memory in persistent storage and associates the memory with the\ndevice kernel and an LLVM IR file. At the end of the recorded execution\nthe pre-load library generates a database in the form of a JSON file containing information regarding the\nLLVM-IR files and the snapshots of device memory.\nDuring the third and last phase the user can replay the execution of an kernel as a separate independent\nexecutable. Besides executing it the user can modify the LLVM IR file and\nauto-tune parameters such as kernel launch-bounds or kernel runtime execution parameters (e.g. Kernel\nBlock and Grid Dimensions).\nIs", + "laborHours": 1687.2, + "languages": [], + "name": "Mneme", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Olympus-HPC/Mneme", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.0.alpha" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2024-11-05", + "metadataLastUpdated": "2024-11-05" + }, + "description": "Based on the well-established GREET model mainly for the United States (U.S.), Argonne National Laboratory (ANL), with the support of the U.S. Department of Energy (DOE), has collaborated with the International Energy Agency (IEA) to develop a global version of the R&D GREET model, referred to as GREET+. GREET+ is a consistent and comparable life cycle analysis (LCA) modeling platform to evaluate life-cycle energy use and greenhouse gas (GHG) emissions of vehicle/fuel systems and technologies. It examines the energy and GHG impacts of technological advancements in different world regions through 2050.\n\nThe GREET+ model builds upon the Excel platform of the R&D GREET\u00ae 2022 rev1 model and ANL\u2019s previous efforts on two regionalized GREET versions, i.e., China-GREET for China and MENA-GREET for Middle East and North Africa (MENA). GREET+ covers 16 regions and countries, including Canada, the USA, Mexico, Brazil, Central and South America region A, Central and South America region B, the European Union, China, India, Japan, South Korea, Southeast Asia and Oceania, MENA, Central and South Africa, the UK, and Norway. The current version of GREET+ focuses on the background data of the fuel cycle (or well-to-wheels, WTW), enabling the generation of region-specific WTW results for fuels and vehicles technologies of interest.", + "homepageURL": "https://greet.anl.gov/greet_plus", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "GREET+ Model 2024", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.anl.gov/greet_plus", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "2024" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-05", + "metadataLastUpdated": "2024-12-04" + }, + "description": "Microbial lipid metabolism is an attractive route for producing oleochemicals. The predominant strategy centers on heterologous thioesterases to synthesize desired chain-length fatty acids. To convert acids to oleochemicals (e.g., fatty alcohols, ketones), the narrowed fatty acid pool needs to be reactivated as coenzyme A thioesters at cost of one ATP per reactivation \u2013 an expense that could be saved if the acyl-chain was directly transferred from ACP- to CoA-thioester. Here, we demonstrate such an alternative acyl-transferase strategy by heterologous expression of PhaG, an enzyme first identified in Pseudomonads, that transfers 3-hydroxy acyl-chains between acyl-carrier protein and coenzyme A thioester forms for creating polyhydroxyalkanoate monomers. We use it to create a pool of acyl-CoA\u2019s that can be redirected to oleochemical products. Through bioprospecting, mutagenesis, and metabolic engineering, we develop three strains of Escherichia coli capable of producing over 1\u2009g/L of medium-chain free fatty acids, fatty alcohols, and methyl ketones.", + "laborHours": 157304.8, + "languages": [], + "name": "Pfleger-Lab/Metabolic-Modeling---Yield-Analysis-of-PhaG", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pfleger-Lab/Metabolic-Modeling---Yield-Analysis-of-PhaG", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-05", + "metadataLastUpdated": "2024-11-05" + }, + "description": "Genes belonging to the same functional group may include numerous and variable gene sequences, making characterizing and quantifying difficult. Therefore, high-throughput design tools are needed to simultaneously create primers for improved quantification of target genes. We developed MetaFunPrimer, a bioinformatic pipeline, to design primers for numerous genes of interest. This tool also enables gene target prioritization based on ranking the presence of genes in user-defined references, such as environment-specific metagenomes. Given inputs of protein and nucleotide sequences for gene targets of interest and an accompanying set of reference metagenomes or genomes, MetaFunPrimer generates primers for ranked genes of interest. To demonstrate the usage and benefits of MetaFunPrimer, a total of 78 primer pairs were designed to target observed ammonia monooxygenase subunit A (amoA) genes of ammonia-oxidizing bacteria (AOB) in 1,550 publicly available soil metagenomes. We demonstrate computationally that these amoA-AOB primers can cover 94% of the amoA-AOB genes observed in the 1,550 soil metagenomes compared with a 49% estimated coverage by previously published primers. Finally, we verified the utility of these primer sets in incubation experiments that used long-term nitrogen fertilized or unfertilized soils. High-throughput quantitative PCR (qPCR) results and statistical analyses showed significant differences in relative quantification patterns between the two soils, and subsequent absolute quantifications also confirmed that target genes enumerated by six selected primer pairs were significantly more abundant in the nitrogen-fertilized soils. This new tool gives microbial ecologists a new approach to assess functional gene abundance and related microbial community dynamics quickly and affordably.", + "laborHours": 136.8, + "languages": [], + "name": "jialiu232/MetaFunPrimer_paper_info", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jialiu232/MetaFunPrimer_paper_info", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-05", + "metadataLastUpdated": "2024-11-05" + }, + "description": "In the repository are example scripts that perform uncertainty injection and propagation to flux balance analysis with outputs for a small sample size (for demonstration purpose only). For proper analysis, user should download the scripts and run for a large sample size (e.g., 10,000 samples).\n\nIf you use the scripts, please cite the following Metabolic Engineering article: \u201cQuantifying the propagation of parametric uncertainty on flux balance analysis\u201d (https://doi.org/10.1016/j.ymben.2021.10.012)\n\nThere are two subdirectories:\n\n/uncFBA/uncBiom: injection of normally distributed noise to biomass precursor coeffcients and ATP maintenance (growth-associated ATP maintenance (GAM) and non-growth associated ATP maintenance (NGAM))\n/uncFBA/uncRHS: departure from steady-state by adding noise drawn from normal distribution to the RHS terms of mass balance constraints", + "laborHours": 108452.0, + "languages": [], + "name": "maranasgroup/uncFBA", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/uncFBA", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-11-06", + "metadataLastUpdated": "2024-11-06" + }, + "description": "CH4ESE is an EXI conversion tool developed in Python3 that utilizes the open-source EXIficient implementation of the W3C EXI format specification. CH4ESE can be used to translate to and from EXI format using the command line with input data or using the web server for live-translation.", + "laborHours": 1580.8, + "languages": [ + "Python" + ], + "name": "Conversion Helper 4 Easy Serialization Of Exi (ch4ese)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/CH4ESE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-06", + "metadataLastUpdated": "2024-11-06" + }, + "description": "The emergence of the cellulosic bioeconomy requires not only adequate technological, economic, and policy advances, but also effective communication and coordination among the multiple stakeholders in the bioeconomy community. Aiming to facilitate stakeholder communication and collaboration for cellulosic bioeconomy growth, an agent-based model is developed as a community communication tool in this study. The tool simulates the behaviors and interactions of key stakeholders, as well as the responses and interactions between the stakeholders and biophysical, socioeconomic, and environmental conditions. The agent behavior rules are developed and validated based on behavior and economic theories and information attained from a stakeholder focus group study and a land use survey.", + "laborHours": 3891.2, + "languages": [], + "name": "cabbi-bio/BECT-ABM", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cabbi-bio/BECT-ABM", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-08", + "metadataLastUpdated": "2024-11-08" + }, + "description": "The code takes expert-labeled segmented images of irradiated and unirradiated pellets and trains DeepConvolutional\nNeural Networks to segment these images into defects, backgrounds, and boundaries. The code calculated qualitative\nmicrostructural information from these segmented images to facilitate the comparison of unirradiated and irradiated\npellets", + "laborHours": 3404.8, + "languages": [], + "name": "pnnl/defect_detection", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/defect_detection", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-08", + "metadataLastUpdated": "2024-11-08" + }, + "description": "Triacetic acid lactone (TAL) can be microbially produced and further chemically upgraded to several high-value chemicals. In this work, several acidic and basic ion-exchange resins and activated charcoal were evaluated for their ability to adsorb microbially produced TAL. Activated charcoal and a weak base resin, Dowex 66, showed similar TAL adsorption capacity of 0.18 \u00b1 0.002 g/g. At 15% w/v activated charcoal, about 98% of TAL present in fermentation broth could be adsorbed. Further, ethanol washing allowed recovery of 72% of adsorbed TAL. A biorefinery producing TAL from sucrose was designed, simulated, and evaluated (through technoeconomic analysis) under uncertainty, for an estimated TAL minimum product selling price (MPSP) of $4.27/kg [$3.71\u22124.94/kg; 5th-95th percentiles] for the current state of technology and $2.83/kg [$2.46\u20133.29/kg] following potential near-term improvements to fermentation. Thus, this work provides an adsorptive process to recover microbially produced TAL that can be chemically upgraded to several industrial products.", + "laborHours": 121159.2, + "languages": [], + "name": "BioSTEAMDevelopmentGroup/Bioindustrial-Park/TAL", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BioSTEAMDevelopmentGroup/Bioindustrial-Park", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-08", + "metadataLastUpdated": "2024-11-08" + }, + "description": "Efforts to manage soils for carbon (C) sequestration remain limited by our understanding of how differences in plant traits and microbial traits mechanistically drive soil organic C (SOC) storage. Addressing this uncertainty is particularly critical in bioenergy agriculture, due to its potential to enhance soil C and provide a C neutral fuel. As such, we examined differences between two contrasting feedstocks, Zea mays (corn) and Miscanthus x giganteus (miscanthus), in the ability of their litter to form new chemically resistant particulate SOC vs. physically protected mineral associated SOC and used this data to improve the parameterization of a microbial SOC model. We tested a hypothesized conceptual model whereby easy to decompose corn litters drive greater microbial carbon use efficiency (CUE) and the formation of more mineral associated SOC over particulate SOC than more complex miscanthus litters. To do this, we performed a soil microcosm experiment where we added 13C enriched aboveground and belowground litters to soils and traced the fate of the 13C into microbial respiration and SOC pools. We found that corn litters promoted higher microbial CUE (0.37) than miscanthus litters (0.24). In turn, corn litter formed approximately 50% more mineral associated SOC than miscanthus litters. Similarly, structurally complex root litters promoted a lower CUE and formed less mineral associated SOC than leaf and shoot litters for both crops. When we used our data to parameterize the SOC model, we found that modeling microbial trait differences uniquely allowed the model to capture the fate of litter C in SOC. Collectively, we found a robust link between litter quality, microbial efficiency, and the formation of SOC. This link bridges the empirical uncertainty in how different crops can form new soil C and provides an empirical basis for modeling SOC transformations.", + "laborHours": 121.6, + "languages": [], + "name": "BrzostekEcologyLab/CORPSE-soil-jars", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BrzostekEcologyLab/CORPSE-soil-jars", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-08", + "metadataLastUpdated": "2024-11-08" + }, + "description": "Saccharomyces cerevisiae is an important model organism and a workhorse in bioproduction. Here, we reconstructed a compact and tractable genome-scale resource balance analysis (RBA) model (i.e., named scRBA) to analyze metabolic fluxes and proteome allocation in a computationally efficient manner. Resource capacity models such as scRBA provide the quantitative means to identify bottlenecks in biosynthetic pathways due to enzyme, compartment size, and/or ribosome availability limitations. ATP maintenance rate and in vivo apparent turnover numbers (kapp) were regressed from metabolic flux and protein concentration data to capture observed physiological growth yield and proteome efficiency and allocation, respectively. Estimated parameter values were found to vary with oxygen and nutrient availability. Overall, this work (i) provides condition-specific model parameters to recapitulate phenotypes corresponding to different extracellular environments, (ii) alludes to the enhancing effect of substrate channeling and post-translational activation on in vivo enzyme efficiency in glycolysis and electron transport chain, and (iii) reveals that the Crabtree effect is underpinned by specific limitations in mitochondrial proteome capacity and secondarily ribosome availability rather than overall proteome capacity.", + "laborHours": 1134406.4, + "languages": [], + "name": "maranasgroup/scRBA", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/scRBA", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "A software framework to study, from the performance and energy perspective, the efficacy of GPU-resident\nparallel Conjugate Gradient (CG) linear solver with different preconditioner options, including Gauss-Seidel, Jacobi, and\nincomplete Cholesky. We also propose a novel GPU-based preconditioner, in which the triangular solves are approximated\nby an iterative process", + "laborHours": 3556.8, + "languages": [], + "name": "pnnl/LAP", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/LAP", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "LAP v 2" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "NeuralMie was developed to improve the representation of aerosol optical properties in E3SM, the DOE's Earth system\nmodel. NeuralMie is able to closely emulate numerical solutions to the problem at a fraction of the computational cost.\nTAMie was written to generate training data for NeuralMie.", + "laborHours": 182.4, + "languages": [], + "name": "pnnl/NEURALMIE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/NEURALMIE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "Hybridization brings together chromosome sets from two or more distinct progenitor species. Genome duplication associated with hybridization, or allopolyploidy, allows these chromosome sets to persist as distinct subgenomes during subsequent meioses. Here, we present a general method for identifying the subgenomes of a polyploid based on shared ancestry as revealed by the genomic distribution of repetitive elements that were active in the progenitors. This subgenome-enriched transposable element signal is intrinsic to the polyploid, allowing broader applicability than other approaches that depend on the availability of sequenced diploid relatives. We develop the statistical basis of the method, demonstrate its applicability in the well-studied cases of tobacco, cotton, and Brassica napus, and apply it to several cases: allotetraploid cyprinids, allohexaploid false flax, and allooctoploid strawberry. These analyses provide insight into the origins of these polyploids, revise the subgenome identities of strawberry, and provide perspective on subgenome dominance in higher polyploids.", + "laborHours": 91.2, + "languages": [], + "name": "amsession/Kmer-based-Subgenome-Mapping", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/amsession/Kmer-based-Subgenome-Mapping", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE\u2014a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.", + "laborHours": 592.8, + "languages": [], + "name": "maslov-group/FUN-PROSE", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maslov-group/FUN-PROSE", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "Repository for Kinetic Estimation Tool Capturing Heterogeneous Datasets Using Pyomo (KETCHUP), a flexible parameter estimation tool that leverages a primal-dual interior-point algorithm to solve a nonlinear programming (NLP) problem that identifies a set of parameters capable of recapitulating the steady-state fluxes and concentrations in wild-type and perturbed metabolic networks.", + "laborHours": 76577.6, + "languages": [], + "name": "maranasgroup/KETCHUP", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/KETCHUP", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "Supplemental sequence processing and R statistical analysis for publication which compares the microbiome of 27 Zea cultivars: 12 Inbred maize genotypes, 9 hybrids, and 6 wild teosinte. The project contains amplicon data for various genes: 16S rRNA, ITS, bacterial amoA, Archeal amoA, nirS, nirK, and nosZ. In addition to functional potential assay data, and N2O flux.", + "laborHours": 927.2, + "languages": [], + "name": "favela3/Maize.N-cycle.Function", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/favela3/Maize.N-cycle.Function", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "BioSTEAM is a fast and flexible package for the design, simulation, and techno-economic analysis of biorefineries under uncertainty. BioSTEAM\u2019s framework is built to streamline and automate early-stage technology evaluations and to enable rigorous sensitivity and uncertainty analyses. Complete biorefinery configurations are available at the Bioindustrial-Park GitHub repository, BioSTEAM\u2019s premier repository for biorefinery models and results. The long-term growth and maintenance of BioSTEAM is supported through both community-led development and the research institutions invested in BioSTEAM. Through the open-source and community-lead platform, BioSTEAM aims to foster communication and transparency within the biorefinery research community for an integrated effort to expedite the evaluation of candidate biofuels and bioproducts.\n\nAdditionally, an agile life cycle assessment (LCA) platform has been designed to interface with BioSTEAM, BioSTEAM-LCA. This open-source, installable package allows users to perform streamlined LCAs of biorefineries. The focus of BioSTEAM-LCA is to streamline and automate early-stage environmental impact analyses of processes and technologies, and to enable rigorous sensitivity and uncertainty analyses linking process design, performance, economics, and environmental impacts.", + "laborHours": 23924.8, + "languages": [], + "name": "BioSTEAMDevelopmentGroup/biosteam", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/BioSTEAMDevelopmentGroup/biosteam?tab=License-1-ov-file#readme", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BioSTEAMDevelopmentGroup/biosteam", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and underlying mechanisms; however, there has been no systematic comparison of these models characterizing their relative strengths and shortcomings. Here, we interrogated a rich data set of neuroectodermal enhancers in Drosophila, representing cis- and trans- sources of expression variation, with a suite of biophysical and machine learning models. We performed rigorous comparisons of thermodynamics-based models implementing different mechanisms of activation, repression and cooperativity. Moreover, we developed a convolutional neural network (CNN) model, called CoNSEPT, that learns enhancer \u2018grammar\u2019 in an unbiased manner. CoNSEPT is the first general-purpose CNN tool for predicting enhancer function in varying conditions, such as different cell types and experimental conditions, and we show that such complex models can suggest interpretable mechanisms. We found model-based evidence for mechanisms previously established for the studied system, including cooperative activation and short-range repression. The data also favored one hypothesized activation mechanism over another and suggested an intriguing role for a direct, distance-independent repression mechanism. Our modeling shows that while fundamentally different models can yield similar fits to data, they vary in their utility for mechanistic inference.", + "laborHours": 349.6, + "languages": [], + "name": "PayamDiba/CoNSEPT", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PayamDiba/CoNSEPT", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.", + "laborHours": 24441.6, + "languages": [], + "name": "maranasgroup/yeastsMFA", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/yeastsMFA", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.", + "laborHours": 1246.4, + "languages": [], + "name": "maranasgroup/k-sacce306", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/k-sacce306", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "Metabolic efficiency profoundly influences organismal fitness. Heterotrophs, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. While respiration is more energy-efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (i.e. faster). Through quantitative flux analysis and proteomics, we find however that mitochondrial respiration is actually more proteome-efficient than aerobic glycolysis. This is shown across yeasts, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which is valuable for hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth, but outgrow respiratory cells in oxygen limitation. Thus, aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.", + "laborHours": 1535.2, + "languages": [], + "name": "yihuishen/metabolic_flux_regulation", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yihuishen/metabolic_flux_regulation", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "Metabolic efficiency profoundly influences organismal fitness. Heterotrophs, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. While respiration is more energy-efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (i.e. faster). Through quantitative flux analysis and proteomics, we find however that mitochondrial respiration is actually more proteome-efficient than aerobic glycolysis. This is shown across yeasts, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which is valuable for hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth, but outgrow respiratory cells in oxygen limitation. Thus, aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.", + "laborHours": 11415.2, + "languages": [], + "name": "yihuishen/T_cell_MFA", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yihuishen/T_cell_MFA", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "Hydrodynamics And Radiative Diffusion Solver based on FleCSI framework", + "laborHours": 6475.2, + "languages": [], + "name": "HARD", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/HARD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "The code is a transformer model to forecast SARS-CoV-2 lineage frequencies in the future.", + "laborHours": 11445.6, + "languages": [], + "name": "CoVTransformer", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ruianke/CoVTransformer", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "SOURCES is a code for computing neutron source rates and spectra from spontaneous fission (including delayed neutrons) and (alpha,n) reactions in homogeneous materials and (alpha,n) reactions in single-interface and two-interface geometries. SOURCES is a Los Alamos National Laboratory (LANL) code that is written in FORTRAN and distributed through the Radiation Safety Information Computation Center (RSICC). LANL\u2019s last release of SOURCES to RSICC was SOURCES4C in 2002. This disclosure covers the latest version of SOURCES, SOURCES4D. This version adds sensitivity capabilities for (alpha,n) sources in homogeneous materials. Specifically, SOURCES4D writes new output that can be used to calculate, in post-processing, first and second derivatives of the (alpha,n) source rate density and spectrum with respect to nuclide densities in a homogeneous material and first derivatives of the (alpha,n) source rate density and spectrum with respect to nuclide stopping powers and (alpha,n) cross sections (nuclear data). These derivatives are useful for uncertainty quantification, predictive modeling, and other applications in neutron transport problems.", + "laborHours": 2310.4, + "languages": [], + "name": "SOURCES4D", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SOURCES4D", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "hFlux is open source, lightweight, easy-to-use toolkit for simulation code developers working with magnetic fields to seamlessly check their intermediate results throughout the development of simulation codes.", + "laborHours": 76.0, + "languages": [], + "name": "hFlux", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/obeznosov-LANL/hFlux", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "CoH3 (CoH ver.3) is an optical model, exciton pre-equilibrium, and Hauser-Feshbach statistical model code, which calculates nuclear reaction cross sections for medium to heavy targets in the keV to MeV energy region. This program is written in standard C++, divided into approximately 200 source and header files. CoH solves the Schroedinger equation for optical potentials defined in the code, and calculates differential elastic scattering, reaction, and total cross sections, for neutron, proton, deuteron, triton, 3He, and alpha-particle. Deformed optical potentials are solved with the coupled-channels method, in which the ground state rotational band members, or vibrational phonon states are coupled. The optical model gives particle transmission coefficients that are fed into the statistical model calculations. CoH includes the pre-equilibrium model (exciton model), the direct/semidirect capture model, and the multi-stage Hauser-Feshbach statistical decay with width fluctuation correction based on the Gaussian orthogonal ensemble. For weakly coupled levels, the DWBA (distorted wave Born approximation) method is used to calculate the direct inelastic scattering process to the excited states.", + "laborHours": 31251.2, + "languages": [], + "name": "coh3", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/toshihikokawano/coh3", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "The tools used are the modified, enhanced and extended versions of the open source BatSim and BatSched suite, including visualization tools (Evalys) derived from those toolstacks.", + "laborHours": 562.4, + "languages": [], + "name": "LANL-contributed enhancements to BatSim toolstack, including VizUtil, derivative of and enhancement of Evalys", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/BatsimGantt-LANL", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2025-01-08" + }, + "description": "Ensuring accurate detection and attribution of abnormal releases of radioactive material is critical for protecting human health and safety. Most commonly, such detection is accomplished via active monitoring approaches involving the collection of physical samples. This is labor intensive and limits the temporal and spatial resolution of any detected events to a relatively coarse level. As an alternative first step towards passive monitoring, we developed an approach using eddy flux tower data records to identify signals from a known abnormal release and quantify the extent to which that signal also occurs at other times in the data record. Through two case-studies, one of which targeted the Fukushima nuclear disaster and the other targeting an abnormal release event at a radioisotope production facility in Fleurus Belgium, we tested our approach and identified several potential heretofore unidentified abnormal releases that were consistent with atmospheric circulation patterns and/or wind direction from known release sites. Because our approach is relatively simple and is resistant to systematic errors in the observational record, it has broad applicability beyond specific constituents and ecosystem types to identify a wide variety of limited-duration anomalies in flux tower data to ensure human health and industrial safety.", + "laborHours": 2872.8, + "languages": [], + "name": "Eddy covariance towers as sentinels of abnormal radioactive material releases", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/fluxnet-sentinels", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-11-18", + "metadataLastUpdated": "2024-11-18" + }, + "description": "Faraday is a high-temperature electrolysis data visualization tool, which reveals the performance of various button cells under test conditions. These tests and the resulting analytics on their data constitute a state of the industry as the US Department of Energy pushes for the production of hydrogen.\n\nFaraday leverages the Idaho National Laboratory's DeepLynx data warehouse to standardize and query button cell data. Faraday programmatically accesses this data in DeepLynx by traversing the schema, represented by a custom ontology.\n\nThe user interface queries DeepLynx for timeseries data associated with specific button cells in the warehouse, and renders them using JavaScript charts. Additional charting and data analysis techniques are made possible by an auxiliary Python server.", + "laborHours": 4712.0, + "languages": [ + "Python", + "TypeScript" + ], + "name": "Faraday: A High-temperature Electrolysis Data Explorer", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholabresearch/faraday", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-18", + "metadataLastUpdated": "2024-11-18" + }, + "description": "You've found the official code repository for the paper \"SysCaps: Language Interfaces for Simulation Surrogates of Complex Systems,\" presented at the Foundation Models for Science: Progress, Opportunities, and Challenges workshop at NeurIPS 2024. Our paper conjectures that interfaces (both text templates as well as conversational) makes interacting with simulation surrogate models for complex systems more intuitive and accessible for both non-experts and experts. \"System captions\", or SysCaps, are text-based descriptions of systems based on information contained in simulation metadata. Our paper's goal is to train multimodal regression models that take text inputs (SysCaps) and timeseries inputs (exogenous system conditions such as hourly weather) and regress timeseries simulation outputs (e.g. hourly building energy consumption). The experiments in our paper with building and wind farm simulators, which can be reproduced using this codebase, aim to help us understand whether a) accurate regression in this setting is possible and b) if so, how well can we do it.\n\nPaper: https://arxiv.org/abs/2405.19653", + "laborHours": 4651.2, + "languages": [ + "Python", + "Jupyter Notebook", + "Shell" + ], + "name": "SysCaps (Language Interfaces for Simulation Surrogates of Complex Systems) [SWR-24-97]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SysCaps", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-19", + "metadataLastUpdated": "2024-11-19" + }, + "description": "This software is a simple, light-weight python package to generate pytorch compatible machine learning graph dataset representing electric power distribution system. User is able to use these graph datasets to test their graph generation artificial intelligence (AI) models, link prediction AI models, graph classification AI models and so much more. This package uses grid-data-models (https://github.com/NREL-Distribution-Suites/grid-data-models) as input data format for power distribution system. NREL-Ditto (https://github.com/NREL-Distribution-Suites/ditto) tool can be leveraged to transform popular distribution system file formats such as opendss, cyme and synergi to grid-data-models.", + "laborHours": 187963.2, + "languages": [ + "Python" + ], + "name": "Distribution System Dataset Generator for AI Applications [SWR-24-75]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-Distribution-Suites/gridai", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-19", + "metadataLastUpdated": "2024-12-12" + }, + "description": "The WEBAT (Wind Energy with Bat AI-based Tracker) is a Python-based bat tracking software, integrating machine learning and computer vision with infrared thermal sensors to enhance the monitoring and protection of bats in proximity to wind turbines.", + "laborHours": 440.8, + "languages": [ + "Python", + "Shell" + ], + "name": "WEBAT (Wind Energy with Bat AI-based Tracker) [SWR-24-121]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WEBAT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-19", + "metadataLastUpdated": "2024-11-19" + }, + "description": "Extracting Attributes in a Simple DictionarY of CIM (EASY-CIM) is a python library to reduce the\ntime and burden of model queries using simplified data representations of CIM power system models.", + "laborHours": 2128.0, + "languages": [], + "name": "PNNL-CIM-Tools/EASY-CIM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CIM-Tools/EASY-CIM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-20", + "metadataLastUpdated": "2024-11-20" + }, + "description": "We apply semantic\nboosting to the Segment Anything Model (SAM) to obtain microstructure segmentation for transmission electron\nmicroscopy. Our booster, SAM-I-Am, extracts geometric and textural features of various intermediate masks to perform\nmask removal and mask merging operations", + "laborHours": 1155.2, + "languages": [], + "name": "pnnl/SAMIAm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SAMIAm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-20", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Our SuperSAM approach transforms the\nSegment Anything Model (SAM) into an `elastic' supernetwork, enabling the derivation of subnetworks with\nvarying architectures tailored to a wide range of resource constraints.", + "laborHours": 3663.2, + "languages": [], + "name": "pnnl/SuperSAM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SuperSAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "mukherjeed@ornl.gov" + }, + "date": { + "created": "2024-11-24", + "metadataLastUpdated": "2024-11-24" + }, + "description": "Ptychography through Differentiable Programming\nThe aim of this project is to write the forward problem: aka writing the microscope data generation, both for electron and optical microscopes in JAX so that it's end to end differentiable and using this differentiability to run modern optimizers such as Adam and Adagrad to solve for the inverse problem - which is ptychography in our case.", + "laborHours": 577.6, + "languages": [ + "Python" + ], + "name": "ptyrodactyl", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/intersect-em/pterodactyl", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "2024.08.26" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-11-25", + "metadataLastUpdated": "2024-11-25" + }, + "description": "The Dependency Analysis Project creates datasets from package management ecosystems to determine\nwhat package a file was likely installed by, and provides tools to recognize implicit dependencies when\nsource code is available for a variety of language ecosystems. The overarching goal is to help answer the\nquestion: what software does a system use?", + "laborHours": 182.4, + "languages": [], + "name": "Dependency Analysis Project", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/dapper", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-25", + "metadataLastUpdated": "2024-11-25" + }, + "description": "This package is a wrapper for the well-known Thevenin equivalent circuit model for simulating battery behavior with a focus on ease of use. The model is comprised of a single series resistor followed by any number of parallel RC pairs. \n\nThe package includes an intuitive \"experiment\" interface, which simplifies the programming of constant or dynamic current, voltage, and/or power-driven loads, making it ideal for a wide range of applications, from basic tests to complex simulations. It also supports state-of-charge (SOC) and temperature-dependent properties, allowing the model to be more easily calibrated against real cells.", + "laborHours": 2036.8, + "languages": [ + "Python" + ], + "name": "thevenin: An Equivalent Circuit Modeling Package [SWR-24-132]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/thevenin", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-25", + "metadataLastUpdated": "2024-11-25" + }, + "description": "Aerosol process analysis in model-native Spectral Element (SE) grid. Aerosol Diagnostics on Model Native Grid is a Python-based tool designed for diagnosing aerosol processes in E3SM. It is\nparticularly designed to analyze simulation data on the model-native spectral element (SE) grid, soit is also known as\nAerosol SE Diagnostics or \u201casediag\u201d", + "laborHours": 1884.8, + "languages": [], + "name": "eagles-project/asediag", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eagles-project/asediag", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-25", + "metadataLastUpdated": "2024-11-25" + }, + "description": "OpenStudio-HPXML allows running residential EnergyPlus\u2122 simulations using an HPXML file for the building description. It is intended to be used by user interfaces or other automated software workflows that automatically produce the HPXML file.\n\nOpenStudio-HPXML can accommodate a wide range of different building technologies and geometries. End-to-end simulations typically run in 3-10 seconds, depending on complexity, computer platform and speed, etc.\n\nFor more information on running simulations, generating HPXML files with the appropriate inputs to run EnergyPlus, etc., please visit the documentation linked below.\n\nhttps://openstudio-hpxml.readthedocs.io/en/latest", + "laborHours": 418608.0, + "languages": [ + "Python", + "Ruby" + ], + "name": "OpenStudio\u00ae HPXML workflow [SWR-25-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-HPXML", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.9.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-26", + "metadataLastUpdated": "2024-12-11" + }, + "description": "The ninterp crate provides multivariate interpolation over a regular, sorted, nonrepeating grid of any dimensionality. A variety of interpolation strategies are implemented, however more are likely to be added. Extrapolation beyond the range of the supplied coordinates is supported for 1-D linear interpolators, using the slope of the nearby points.\n\nThere are hard-coded interpolators for lower dimensionalities (up to N = 3) for better runtime performance.\n\nAll interpolation is handled through instances of the Interpolator enum, with the selected tuple variant containing relevant data. Interpolation is executed by calling Interpolator::interpolate.", + "laborHours": 820.8, + "languages": [ + "Rust" + ], + "name": "ninterp: N-dimensional interpolation Rust crate [SWR-25-25]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ninterp", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.0" + }, + { + "contact": { + "email": "john.brewer@netl.doe.gov" + }, + "date": { + "created": "2024-11-26", + "metadataLastUpdated": "2024-11-26" + }, + "description": "Reuse of Existing Pipelines for Adapted Carbon Transport (REPACT) is an Excel-based screening tool. This tool enables the user to determine whether a pipeline originally deployed for natural gas transport, can be reused for CO2 transport. The tool along with its associated user's manual walk through an intended usage statement, setup instructions, a list of inputs and outputs in the tool, and frequently used protocols. Please note that this is a first-pass screening tool. The approach presented within this tool is valid for high-level evaluation only and should not be used to make engineering, financial, and/or regulatory decisions. See the User Manual at this link: https://www.netl.doe.gov/energy-analysis/details?id=126f2dad-6d53-423e-8aaa-70954e0a2a9c.", + "homepageURL": "https://netl.doe.gov/energy-analysis/details?id=c699a604-ded1-45cd-b1c0-247b1405aeeb", + "laborHours": 0.0, + "languages": [], + "name": "REPACT Tool", + "organization": "National Energy Technology Laboratory (NETL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://netl.doe.gov/energy-analysis/details?id=c699a604-ded1-45cd-b1c0-247b1405aeeb", + "status": "Development", + "tags": [ + "DOE CODE", + "National Energy Technology Laboratory (NETL)" + ], + "version": "0" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2024-12-03", + "metadataLastUpdated": "2024-12-04" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model \u00ae (2024 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2024" + }, + { + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2024-12-03", + "metadataLastUpdated": "2024-12-04" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model \u00ae (2024 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2024 (v1.3.0.14xxx)" + }, + { + "contact": { + "email": "sundararajaa@ornl.gov" + }, + "date": { + "created": "2024-12-04", + "metadataLastUpdated": "2025-01-06" + }, + "description": "Existing frameworks to forecast time-series photovoltaic (PV) output power and consumer load for microgrid operations and controls assume a near-continuous availability of real-time input features from the field assets such as PV inverters, energy meters, and weather station. These incoming data points are used to periodically retrain models and update forecast snapshots over a moving horizon window, be it one hour-ahead, one-day ahead, or one-week ahead. However, such frameworks are not resilient to disruptions in data availability caused by losses in communications between the field sensors and data loggers. Hence, there is a need for programs that assume no availability of real-time microgrid asset data and still make reliable forecasts that can be used for decision-making. Such programs would be apt to function in extreme weather events such as hurricanes and would use lightweight recursive time-series models to independently forecast solar irradiance and ambient temperature, then compute PV power from those forecasts, as well as independently forecast consumer load.\n\n\tThe codebase performs forecasting for the scenario of when the microgrid does not have a reliable access to forecasts or real-time observations of solar irradiance (I) and ambient temperature (AT) and load (Load) to be able to adequately forecast, in real-time, the PV power production or a business' load. In this case, using historical values of PV power and load, a univariate forecasting of generation and consumption are respectively made. The use-case in particular has two sub-scenarios: one, a normal 7-day ahead forecast where the unavailability of real-time data is assumed due to infrastructure issues such as loss of communication or sensor maintenance or service downtimes. Whereas a hurricane-caused unavailability of real-time data requires a second model trained specifically on historical hurricane days to be able to capture the extreme day behavior of generation in particular, and load if applicable.\n\nA gradient boosted regression tree comprises an ensemble of additive models that map between the input of historical values (be it irradiance, temperature, or load) and their corresponding output forecasts of a given horizon such that the individual learner predictions are summed up over the total number of such learners in the ensemble to produce an aggregate forecast. A weighting mechanism is applied to the training data in each iteration, where actual and forecast values are compared to penalize incorrect forecasts by increasing the weight and reducing it to reward correct forecasts.\n\nThe code's benefits are that it: (a) accounts for a contingency where communication loss renders newly measured real-time data unavailable for model tuning and snapshot updates; (b) presents blind forecasting that recursively determines the next time-step value in a horizon using the forecast of the same attribute from a prior step; and (c) employs lightweight models that, once trained, can reliably generalize for different horizons, which make them suitable for enhancing the resilience of field microgrids prone to extreme events that encounter disruptions to data availability.", + "homepageURL": "https://code.ornl.gov/6a6/pv-and-load-forecasting-use-case-3.git", + "laborHours": 182.4, + "languages": [ + "Python" + ], + "name": "PV Generation and Load Forecasting for Adjuntas PR Community Microgrids", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/6a6/pv-and-load-forecasting-use-case-3.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "bilheuxjm@ornl.gov" + }, + "date": { + "created": "2024-12-09", + "metadataLastUpdated": "2024-12-09" + }, + "description": "The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) provides pulsed neutrons with energies varying from epithermal to cold. 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Thus, we have been focusing on creating a Python-based interface that allows fast data processing and instantaneous mapping and fitting of the Bragg edges, and their evolution through time. Python libraries and Jupyter notebooks have been implemented to facilitate decision making during an experiment. The advantage of the notebooks is the possibility to guide an experiment as they can quickly process and display Bragg edge data. These notebooks can be used independently, or can be combined in a Python Graphical User Interface (GUI) tool called iBeatles. This interface permits visualization and fitting of the Bragg edges, and ultimately back-projects the fitting results onto the radiographs to display a strain map. Assuming data collection has sufficient statistics, the strain mapping analysis can be performed on a pixel-by-pixel basis. This development is a step forward toward a better user experience at the future VENUS beamline in terms of live feedback and productivity. Analysis that used to take days of switching between different applications can now be done in minutes within the", + "laborHours": 36449.6, + "languages": [ + "Python" + ], + "name": "Imaging Bragg Edge Analysis TooLs for Engineering Structures (iBeatles)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornlneutronimaging/iBeatles", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-12-09", + "metadataLastUpdated": "2024-12-09" + }, + "description": "pyzag is a library for efficiently training generic models defined with a recursive nonlinear function. We developed it primarily to provide an efficient means to train NEML2 models\n it can be used to train other, more general types of models.", + "laborHours": 1079.2, + "languages": [], + "name": "sf-24-103", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/applied-material-modeling/pyzag", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-10", + "metadataLastUpdated": "2025-02-24" + }, + "description": "We will employ a machine learning approach with intelligent data mining and\ndatabase construction to analyze enormous data repositories for identifying and\nextracting geographic-dependent cell design specifications from publicly accessible\ngrid-scale energy storage usage databases in an automated way at scale.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 53169.6, + "languages": [], + "name": "LIB Design Module for Grid Energy System Application", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-10", + "metadataLastUpdated": "2025-02-24" + }, + "description": "This software was developed to aid in the automation of electron microscopy. Identification of sample landmarks in\nimaging data is critical for automated imaging systems.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 60.8, + "languages": [], + "name": "BoxEM: Automated Grid Edge Detection for Electron Micrographs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-11", + "metadataLastUpdated": "2025-02-24" + }, + "description": "PTMdiscoverer is a new approach that leverages generative AI to accelerate the discovery of post-translational\nmodifications (PTMs) in proteomics experiments.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 182.4, + "languages": [], + "name": "PTMdiscoverer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "cheny4@ornl.gov" + }, + "date": { + "created": "2024-12-12", + "metadataLastUpdated": "2024-12-13" + }, + "description": "This project is mainly about the operation optimization of three networked microgrids (MG), including centralized optimization and distributed optimization. The alternating direction method of multipliers (ADMM) algorithm is used for distributed optimization. In the distribution network considered here, there is a Distribution Management system (DMS) as the system coordinator and several networked microgrids. In grid-connected mode, power could be imported or exported at the distribution substation bus according to the utility rate, and the exchanged power at point of common coupling (PCC) of any microgrid has a limitation. In islanded mode, the power\nimports/exports at the distribution substation are zero. In both grid-connected and islanded mode, the distribution substation is taken as a slack bus with fixed voltage magnitude.", + "homepageURL": "https://code.ornl.gov/cheny4/networked-microgrids-optimization", + "laborHours": 12372.8, + "languages": [ + "Python" + ], + "name": "Networked Microgrids Optimization", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/cheny4/networked-microgrids-optimization", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "SCF: Seismicity-Constrained Fault Detection and Characterization", + "laborHours": 2143.2, + "languages": [], + "name": "SCF: Seismicity-Constrained Fault Detection and Characterization", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/scf", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Collection of tools designed to parse documents, such as PDFs, and extract structured elements including URLs, citation contexts, tables, formulas, and figures. This toolset leverages AI-based text extraction and classification methods, providing robust solutions for various scholarly resources processing needs.", + "laborHours": 1520.0, + "languages": [], + "name": "Library-AI-Toolset", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Library-AI-Toolset", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Monte Carlo thermal radiation transport code", + "laborHours": 1687.2, + "languages": [], + "name": "lanl/jaybenne", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/jaybenne", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "We develop a software called Physics-Preserved Graph Network (PPGN) to accurately locate faults at the node level with limited observability and labeled training data. PPGN has a unique two-stage graph neural network architecture. The first stage learns the graph embedding to represent the entire network using a few measured nodes. The second stage finds relations between the labeled and unlabeled data samples to further improve the location accuracy.", + "laborHours": 471.2, + "languages": [], + "name": "Physics-Preserved Graph Networks for Real-Time Fault Location", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PPGN.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Astrophysical multifluid radiation hydrodynamics code", + "laborHours": 11172.0, + "languages": [], + "name": "artemis", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/artemis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Code developed to fit and analyze viral load data for acute respiratory infections such as SARS-CoV-2. The code can also implement different treatments and generate in-silicon cohorts to examine the effects of treatments.", + "laborHours": 3708.8, + "languages": [], + "name": "A-general-code-for-analyzing-viral-load-in-acute-respiratory-infection", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tinphan-LANL/A-general-code-for-analyzing-viral-load-in-acute-respiratory-infection", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "The ScholarGuard framework aims to address the gap in archiving and preservation efforts for scholarly artifacts beyond traditional research papers, such as software source code, datasets, presentation slides, workflows, protocols, videos, and more. It introduces a prototype system designed to automatically track researchers' outputs across various scholarly productivity portals on the open web, including platforms like GitHub, Slideshare, Figshare, and Wikipedia.\nThe system detects the availability of new scholarly artifacts and applies modern web archiving technology to create a durable archival record, including high-level metadata for each artifact. This metadata is displayed within the system, linking both to the live version and the archived version of the resource, ensuring long-term accessibility and preservation of diverse research outputs.\nThe software serves as a critical tool for preserving the broader spectrum of scholarly contributions, facilitating visibility, searchability, and long-term access to research artifacts beyond the traditional scope of journal publications.", + "laborHours": 52531.2, + "languages": [], + "name": "ScholarGuard", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ScholarGuard", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Checkpoint-restart", + "laborHours": 1930.4, + "languages": [], + "name": "Checkpoint", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Checkpoint", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Virtual register for performing addition and subtraction of floating-point numbers without loss of precision", + "laborHours": 440.8, + "languages": [], + "name": "Virtreg", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Virtreg", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Optimization and Machine Learning Toolbox-Embed trained machine learning predictors in JuMP", + "laborHours": 2857.6, + "languages": [], + "name": "MathOptAI.jl", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/MathOptAI.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Automatically detect chemostat optical density dilution cycles and calculate growth rate regression slopes.", + "laborHours": 623.2, + "languages": [], + "name": "chemostat_regression", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/chemostat_regression", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Utility to bin continuous variables and estimate mutual information based on B-Spline binning.", + "laborHours": 152.0, + "languages": [], + "name": "pnnl-predictive-phenomics/bspline_mutual_information", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/bspline_mutual_information", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "This is a simple python code to calculate jet quenching for nuclear modification factors in relativistic\nheavy-ion collisions. This code can be used to generate all results specified in RR0010127, to be\nsubmitted to Physical Review C.", + "laborHours": 1124.8, + "languages": [], + "name": "A simple model for jet quenching in Heavy Ion Physics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ez-Quench", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "xju@lbl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "This repository contains a set of Tracking models that can be used as a service.", + "laborHours": 562.4, + "languages": [ + "Python" + ], + "name": "Tracking as a Service", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xju2/tracking-as-a-service/releases/tag/v1.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v1.0" + }, + { + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2024-12-16", + "metadataLastUpdated": "2024-12-18" + }, + "description": "E3SM v3.0.2. Second patch release of v3.0. The main purpose of this release is to fix the forcing specifications of single-forcing compsets introduced in v3.0.1\n[BUG FIXES] These compsets are changed: WCYCL20TR-GHG, WCYCL20TR-aer, WCYCL20TR-xGHG-xaer, WCYCL20TR-xaer. Core to the changes is to separate the transient aerosol and chemical precursors for different single forcing compsets. New virtually transient forcing files are introduced to satisfy the unified data stream control for surface and elevated emissions. Historical evolution of stratospheric ozone is moved from the all-else configuration to the GHG only configuration. Except for those compsets, the simulated climate is identical for compsets released in v3.0.0 and released/updated in v3.0.1.\n[ATM] fix output of r_lch4 and r_lco_h reaction rates. Downstream merge from SCREAM repo.\n[LND] The precision of a few real variables is fixed during model initialization. New parameterizations are added for the burial of shrubs by snow; however, these parameterizations are not on by default.\n[OCEAN] fix bug in data sub-glacial runoff. Add new SOwISC12to30E3r3 mesh.\n[SEA-ICE] Update BGC history fields.\n[LAND-ICE] Add ERA5r025 configurations for new IGERA5ELM_MLI compsets\n[WAVES] Change location of WW3 compilation, update wave developer test suite.\n[DATA-MODEL] Add support for new JRA forcing through year 2023.", + "laborHours": 1769751.2, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v3.0.2", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v3.0.2", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v3.0.2" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-16", + "metadataLastUpdated": "2024-12-16" + }, + "description": "An ensemble machine learning method to improve spectral similarity scores for GC-MS data", + "laborHours": 197.6, + "languages": [], + "name": "PNNL-m-q/metabolomics_ensemble_score", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-m-q/metabolomics_ensemble_score", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-12-16", + "metadataLastUpdated": "2024-12-16" + }, + "description": "The marine carbon management software is an open-source Python based software that contains generic models for marine carbon capture, marine carbon dioxide removal, marine carbon capture and utilization, marine carbon capture and storage. 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The application extends the framework to handle structural problems with a consistent large deformation\nframework as well as adding miscellaneous utility routines we have found useful in our work on high temperature\nstructural design.\n(Provide additional information if necessary in Supplemental section below.)\nYear code", + "laborHours": 10503.2, + "languages": [], + "name": "SF-19-055 deer", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/deer", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-12-19", + "metadataLastUpdated": "2024-12-19" + }, + "description": "Solar receiver structural life estimation tool. 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Memote is a software tool that provides a suite of tests to ensure the quality and consistency of\nmetabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate\nupdates to the GEM, ensuring that model modifications improve or maintain the model's integrity.", + "laborHours": 159676.0, + "languages": [], + "name": "pnnl-predictive-phenomics/csc052-gem", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc052-GEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-23", + "metadataLastUpdated": "2024-12-23" + }, + "description": "Genome-Scale Metabolic Model of CarbStor Community member Microbacterium (csc031) Continuous Validation with\nMemote\nThese repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model\n(GEM) using Memote. 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Memote is a software tool that provides a suite of tests to ensure the quality and consistency of\nmetabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate\nupdates to the GEM, ensuring that model modifications improve or maintain the model's integrity", + "laborHours": 140280.8, + "languages": [], + "name": "pnnl-predictive-phenomics/csc009-gem", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc009-GEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-23", + "metadataLastUpdated": "2024-12-23" + }, + "description": "Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Rhodococcus\nThese repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model\n(GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of\nmetabolic models. 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Memote is a software tool that provides a suite of tests to ensure the quality and consistency of\nmetabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate\nupdates to the GEM, ensuring that model modifications improve or maintain the model's integrity.", + "laborHours": 138289.6, + "languages": [], + "name": "pnnl-predictive-phenomics/csc043-gem", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc043-GEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-12-23", + "metadataLastUpdated": "2024-12-23" + }, + "description": "EyeON: Eye on Operational technology\nSoftware Supply Chain attacks have risen drastically over the past few years, none more well-known and\nimpactful than the SolarWinds compromise. Criminal organizations inserted an attack vector into a\nspecific version of the source code, giving themselves an air of credibility. Once news broke on\nSolarWinds, identifying compromised sites was very difficult, even knowing the culprit update.\nSoftware Bills of Materials (SBOM) have been touted as the solution to reclaiming control of your software\nsupply chain. Deployment of SBOMs has been slow, however, due to conflicting standards, opaque\nstorage requirements, and vendor adoption. Additionally, the path from obtaining an SBOM and securing\nyour supply chain is unclear; how can an SBOM library be leveraged to provide insight to your attack\nsurface? The EyeON tool, sponsored by Department of Energy Cybersecurity, Energy Security, and\nEmergency Response (DoE CESER), aims to address these gaps by providing an encapsulated solution\nto tracking which updates have been installed in an enterprise, and alerting system administrators to\nvulnerabilities as they become known.\nSimilar to a virus scanner, EyeON is a command line tool to parse either a single file, nested directory\nstructure, or filesystem. It collects data such as signature (hashes), version information, VirusTotal tags,\ncompiler, compilation date, and code signing information. Users will anonymously submit scan data\nperiodically to DoE CESER, who will then compile a database of known software products employed by\nCritical Infrastructure and broadcast alerts based on discovered flaws as they arise.", + "laborHours": 1580.8, + "languages": [], + "name": "EyeON", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pEyeON", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-01-02", + "metadataLastUpdated": "2025-01-02" + }, + "description": "Swift is a fast Fourier transform based spectral solver based on the MOOSE framework. It supports GPU accelerated semi-implicit solves of partial differential equations, such as those used for phase field mesoscale microstructure evolution.", + "laborHours": 140736.8, + "languages": [ + "C++" + ], + "name": "Swift", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/swift", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-01-08", + "metadataLastUpdated": "2025-01-08" + }, + "description": "A wind farm optimization suite for wind energy that is built for modular, gradient-enabled multi-disciplinary and multi-fidelity optimizations.\n\nDig into wind farm design.\n\nAn ard is a type of simple and lightweight plow, used through the single-digit centuries to prepare a farm for planting. The intent of Ard is to be a modular, full-stack multi-disciplinary optimization tool for wind farms.\n\nThe problem with wind farms is that they are complicated, multi-disciplinary objects. They are aerodynamic machines, with complicated control systems, power electronic devices, social and political objects, and the core value (and cost) of complicated financial instruments. Moreover, the design of one of these aspects affects all the rest!\n\nArd seeks to make plant-level design choices that can incorporate these different aspects and their interactions to make wind energy projects more successful.", + "laborHours": 1504.8, + "languages": [ + "Python", + "Jupyter Notebook", + "Shell" + ], + "name": "Ard [SWR-25-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/Ard", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-01-08", + "metadataLastUpdated": "2025-01-08" + }, + "description": "Powering the Blue Economy Hardware-in-the-Loop models (PBE-HIL) is a repository of Power Hardware-in-the-loop models developed for typical Powering the Blue Economy market loads and power requirements. The HIL models were developed to be as generic and functional as possible, meaning that the user can easily configure these models to represent their unique PBE design. These PBE load and power requirement HIL models can then be used to inform marine energy converter (MEC) and power electronics design, as well as be used in laboratory testing using HIL equipment, leading to improved understanding of MEC performance and lower risk prior to open-water MEC deployment.", + "laborHours": 52318.4, + "languages": [ + "C", + "Python", + "HTML" + ], + "name": "PBE-HIL (Powering the Blue Economy Hardware-in-the-Loop models) [SWR-25-37]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PBE-HIL", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "moorea@osti.gov" + }, + "date": { + "created": "2025-01-10", + "metadataLastUpdated": "2025-01-10" + }, + "description": "The Replicative Assessment of Spectrometric Equipment (RASE) is a software for evaluating the\nperformance of radiation detectors and isotope identification algorithms. It uses a semi-empirical\napproach to rapidly generate synthetic spectra and inject into detector's software to obtain nuclide\nidentification response. RASE facilitates studies of spectroscopic device performance and a quantitative\nassessment of its capabilities to correctly distinguish and identify isotopes of interest in realistic scenarios", + "laborHours": 4088.8, + "languages": [], + "name": "Replicative Assessment of Spectroscopic Equipment v3.0", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RASE", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "wongey@ornl.gov" + }, + "date": { + "created": "2025-01-14", + "metadataLastUpdated": "2025-01-14" + }, + "description": "The QIR Execution Engine library provides interfaces for easily processing Quantum Intermediate Representation code using the LLVM execution engine.", + "laborHours": 3435.2, + "languages": [], + "name": "QIR-EE", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/qiree", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-01-15", + "metadataLastUpdated": "2025-01-15" + }, + "description": "Tool for building CIM models \"from scratch\"", + "laborHours": 48518.4, + "languages": [], + "name": "PNNL-CIM-Tools/CIM-Builder", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CIM-Tools/CIM-Builder", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kotevskao@ornl.gov" + }, + "date": { + "created": "2025-01-16", + "metadataLastUpdated": "2025-04-15" + }, + "description": "This is a repository for PETINA: Privacy prEservaTIoN Algorithms.", + "laborHours": 106.4, + "languages": [ + "Python" + ], + "name": "OKotevska/petina", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/OKotevska/petina", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.11" + }, + { + "contact": { + "email": "alexanderwg@ornl.gov" + }, + "date": { + "created": "2025-01-17", + "metadataLastUpdated": "2025-01-23" + }, + "description": "Here, we develop MIJAMP (MIJAMP Is Just A MethylBED Parser), a software package that was developed to discover methylated motifs from the output of ONT\u2019s Modkit or other data in the methylBED format. MIJAMP employs a human-driven refinement strategy that empirically validates all motifs against genome-wide methylation data, thus eliminating false, under-, or overexplained motifs. MIJAMP can also report methylation data on a specific, user-defined motif.", + "laborHours": 334.4, + "languages": [ + "Python" + ], + "name": "MIJAMP", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/alexander-public/mijamp", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-01-17", + "metadataLastUpdated": "2025-01-17" + }, + "description": "Funded by the DOE's Bioenergy Technology Office through the Feedstock-Conversion Interface Consortium, INL researchers developed this code to model biomass freestock flow in various handling equipment, such as hoppers and augers. 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The FeatherWing is powered through the vehicle's auxiliary power (from cigarette lighter) socket via a micro USB cable. 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Agents behaviors correspond to components in the real Integrated Water-Power System. The model simulate actions and interactions of these (autonomous) agents to analyze their effects on the overall system. \nAgents in the water system capture components of water collection, treatment, transportation, distribution and use (e.g. pipe, canal, pump, water demands for agriculture, etc.). Agents in the power system capture components of power generation, transportation, distribution and use (electricity demands, sources, etc.).", + "laborHours": 744.8, + "languages": [ + "Python" + ], + "name": "Interdependent Water And Power Infrastructure Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Integrated_Water_Power_System", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-04", + "metadataLastUpdated": "2025-02-04" + }, + "description": "This codebase was designed to tackle the problem of how to directly utilize experimental omics measurements with a\ngenome scale metabolic model of the organism of the study. Most models only loosely utilize known experimental\nquantities to constrain model simulation.", + "laborHours": 12312.0, + "languages": [], + "name": "pnnl-predictive-phenomics/emll", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/Emll", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-04", + "metadataLastUpdated": "2025-02-04" + }, + "description": "Consistent Reproduction of Phenotype", + "laborHours": 608.0, + "languages": [], + "name": "pnnl-predictive-phenomics/crop", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/Crop", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-05", + "metadataLastUpdated": "2025-02-05" + }, + "description": "Code for implementing BMCA for Synechococcus elongatus", + "laborHours": 377689.6, + "languages": [], + "name": "pnnl-predictive-phenomics/syn_bmca", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/Syn_bmca", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-05", + "metadataLastUpdated": "2025-02-05" + }, + "description": "The software was developed to solve the problem of continuous validation for genome-scale model of S. elongatus.\nThe origin of the work was due to the difficulty of curating genome-scale metabolic models, and memote was invented to\nsolve this problem.", + "laborHours": 224762.4, + "languages": [], + "name": "pnnl-predictive-phenomics/SElon-GEM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/SElon-GEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-05", + "metadataLastUpdated": "2025-02-24" + }, + "description": "Our software is designed to only work on novel NCAA side chains and parameterize for the CHARMM potential. This works\naround the detailed analysis and manual parameter fitting of many existing software programs. Our approach is also more\nspecific than those used in Rosetta where we calculate parameters specific for each NCAA rather than assuming\ntransferability.", + "homepageURL": "https://github.com/pnnl/ncap", + "laborHours": 1626.4, + "languages": [], + "name": "NCAP - Non-Canonical Amino Acid Parameterization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://github.com/pnnl/ncap", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://github.com/pnnl/ncap", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2025-02-05", + "metadataLastUpdated": "2025-02-05" + }, + "description": "A plug and play techno-economic analysis (TEA) and lifecycle assessment (LCA) tool was built that could incorporate new projects into the California ARCHES LLC Hydrogen hub, and generate results for the project, as well as the overall hub on an annual basis. The model was first constructed in Microsoft Excel and ArcGIS, but required labor intensive updating and manual decision making regarding the matching of hydrogen supplier and offtaker and estimation of transportation distances and utility sources. The project team converted the Excel model used for the ARCHES LLC hub conceptualization into a highly flexible and nearly completely automated R code. The R code runs the TEA and LCA, as well as provides mapping capabilities that automatically link projects by latitude and longitude to nearby utilities.", + "laborHours": 4484.0, + "languages": [], + "name": "Hydrogen Hub Systems Analysis and Mapping Tool (ParaCraft) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/calgem/Paracraft", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-05", + "metadataLastUpdated": "2025-02-24" + }, + "description": "This technology was developed to address the need for monitoring bird and bat activity at offshore locations for wind\nenergy", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 12844.0, + "languages": [], + "name": "ThermalTracker", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-06", + "metadataLastUpdated": "2025-02-06" + }, + "description": "SAND2025-01123O\nE3SMFC is a software tool that integrates a feedback controller algorithm into the E3SM climate model to regulate sulfur dioxide injection, aiming to achieve specific climate outcomes. The program uses proportional-integral-derivative feedback control to adjusts sulfur dioxide levels in both spatial and temporal dimensions. It will only operate on computers that can run the DOE climate model E3SM. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1769751.2, + "languages": [ + "Fortran", + "Python" + ], + "name": "E3SMFC", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/E3SMFC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-07", + "metadataLastUpdated": "2025-02-07" + }, + "description": "IdPP is a Python package that provides a framework for the curation and analysis of molecular properties from\nmultidimensional mass spectrometry (MS) measurements. The main components of the package are organized around a\nmolecular property database and identification probability analysis", + "laborHours": 349.6, + "languages": [], + "name": "pnnl/idpp_rtp", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/idpp_rtp", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "kentpr@ornl.gov" + }, + "date": { + "created": "2025-02-09", + "metadataLastUpdated": "2025-02-10" + }, + "description": "QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support.", + "laborHours": 1334484.0, + "languages": [ + "C++17" + ], + "name": "QMCPACK v4.0.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/license/uoi-ncsa-php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QMCPACK/qmcpack", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v4.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-10", + "metadataLastUpdated": "2025-02-10" + }, + "description": "SAND2025-01223O\n\"Exploring the Transferability of Machine-Learning Models\" is a software tool that trains and tests machine-learning models using simulated data. It includes Python scripts and a Jupyter Notebook to train models to predict material properties from X-ray diffraction profiles. The software provides a template for developing predictive models without requiring proprietary data. It streamlines the model training process and validates model transferability across different datasets. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Code for \"Exploring the Transferability of Machine-Learning Models\"", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v1" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2025-02-10", + "metadataLastUpdated": "2025-02-10" + }, + "description": "This work develops the NSBC (non-stationary bias correction) methodology to correct temperature\nprojection bias from E3SM.\nThe NSBC deep learning framework consists of a three-part architecture: an auto-encoder for\ncompressing the spatial information, an LSTM for predicting annual temperature mean, and a U-Net for\ncapturing the residual bias in temperature. The non-stationary bias correction (NSBC) framework can\ncorrect the non-stationarity of the biases of the climate models, which significantly improves the accuracy\nof future temperature prediction and improves the overestimation of extreme high temperatures that many\nexisting bias correction methods suffer from.\nGetting started\n1. Obtain the historical climate simulation and observation data.\nThe E3SM simulation data are available through https://aims2.llnl.gov/search/cmip6/.\nThe pseudo observations, the Geophysical Fluid Dynamics Laboratory (GFDL)-ESM4 model (Krasting et\nal., 2018) are available through https://aims2.llnl.gov/search/cmip6/.\nThe spatial resolution of E3SM and pseudo observation datasets are both regridded to a common 1\u00b0\nresolution grid using conservative interpolation. The regridded E3SM and pseudo observation with 1\u00b0\nresolution can be found throught ./data/.\n2. Train the Auto-encoder model.\nPython 0-autoencoder.py\n3. Train the LSTM\nPython 1-LSTM.py\n4. Generate the annual mean temperature based on trained LSTM\nPython 2-generate_annual_mean_LSTM.py\n5. Train the U-Net.\nPython 3-unet.py\n6. Evaluation and compared with the baseline\nPython 4_evaluation.py\nIs there a deadline approaching that requires the release of yo", + "laborHours": 684.0, + "languages": [], + "name": "Deep Learning-based Non-Stationary Bias Correction (NSBC)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/NSBC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2025-02-11", + "metadataLastUpdated": "2025-02-11" + }, + "description": "Multi-Level Monte Carlo Methods in Chemical Applications with Lennard-Jones Potentials and other Landscapes with Isolated Singularities", + "laborHours": 1854.4, + "languages": [ + "Python" + ], + "name": "ORNL/MLMC", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/MLMC", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "martins@ornl.gov" + }, + "date": { + "created": "2025-02-13", + "metadataLastUpdated": "2025-02-27" + }, + "description": "The bioenergy.org website is the end product of the Data Sharing Shared Research objective for the Bioenergy Centers. The objective is to Enhance BRC data legacy through the development and use of shared software tools to make previously published datasets more findable and accessible through the Inter-BRC Data Products Portal, and to explore the use of generative AI to assist in the exploration of published datasets. The software repository is released per the license information below.", + "laborHours": 1839.2, + "languages": [ + "JavaScript" + ], + "name": "Bioenergy Research Centers Data Sharing Portal", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/bioenergy-research-centers/bioenergy.org?tab=License-1-ov-file", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bioenergy-research-centers/bioenergy.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-14", + "metadataLastUpdated": "2025-02-24" + }, + "description": "The Aviation Security Screening Optimizer for Risk and Throughput (ASSORT) is designed to assess risk-based\napproaches for passenger screening and checkpoint operations. Additionally, ASSORT is exploring various traveler\ncategories \u2014 general, trusted, and trusted-plus \u2014 along with different checkpoint screening Concept of Operations\ntailored to each traveler type", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 1200.8, + "languages": [], + "name": "Aviation Security Screening Optimizer for Risk and ThroughputASSORT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "dewittsj@ornl.gov" + }, + "date": { + "created": "2025-02-14", + "metadataLastUpdated": "2025-02-14" + }, + "description": "A key step in almost all scientific endeavors is answering the question: Given this data I already collected, what new data do I expect will yield the most useful information toward my scientific objective? The area of (sequential) experimental design has long been investigating answers to this question, but in recent years techniques from the machine learning subfield of active learning are increasingly applied. Researchers need a simple software tool for active learning applied to experimental design that can easily integrate into their existing workflows.\n\nThis computer code, Dial, provides a microservice in ORNL's INTERSECT ecosystem for active learning applied to experimental design. By being part of the INTERSECT ecosystem, Dial is simple to integrate into any INTERSECT-based workflow. Dial provides multiple backend options, where a backend is an implementation of a specific active learning method. Users can select the backend that performs best for their application. Developers can also add new backends as needed.\n\nAt its core, Dial receives a set of pre-existing measurements and input parameter bounds and then recommends one or more new sets of parameters to measure. Dial also includes interfaces to other microservices in the INTERSECT ecosystem so that it can be incorporated into INTERSECT campaigns.\n\nDial provides a simple, yet powerful interface to convert automated INTERSECT workflows into autonomous workflows that adapt based on the results that are obtained. A shared microservice for active learning prevents duplicated effort by each application team implementing its own adaptive design of experiments tool.", + "laborHours": 668.8, + "languages": [ + "Python" + ], + "name": "Dial", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/INTERSECT-DIAL/dial", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "A River dynamical core for E3SM", + "laborHours": 11400.0, + "languages": [], + "name": "RDycore/RDycore", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rdycore/rdycore", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00929O\nVessel Integrated Turbine Assessment for LCOE (VITAL) is a user-friendly software tool that optimizes the design and control of hydrokinetic turbines deployed from floating vessels. It uses data about rotor blade performance, vessel parameters, tidal data, and cost models. This data is used to determine the best turbine design and control strategies to minimize the levelized cost of energy (LCOE). This application can enhance the efficiency and cost-effectiveness of tidal energy projects. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 653.6, + "languages": [ + "Python" + ], + "name": "Vessel Integrated Turbine Assessment for LCOE (VITAL) v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00927O\nCORRA is a software tool that helps evaluate the costs and benefits of inspecting and repairing wind turbine blades. It combines probabilistic analysis of blade damage with economic analysis to calculate the overall cost of energy production. CORRA can compare different maintenance strategies and their impact on energy costs, which aids in the optimization of wind turbine operations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Cost Optimized Risk and Reliability Assessment Tool v.0.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00898O\nFork of Reflow is a software tool that extends the functionality of NASA Reflow to support relevant projects. It provides automated reasoning support for floating-point roundoff error in numerical computer programs. The tool integrates with Frama-C and the PVS theorem prover to specify and verify program properties, ensuring compliance with specifications through weakest-precondition style analysis. This fork enhances automated reasoning features and enables direct analysis of C code, making it suitable for applications involving small programs with floating-point computations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Haskell", + "PVS", + "C" + ], + "name": "Fork of Reflow v.1.0.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0.2" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00852O\nDecLib is a software library that aids in the study and application of discrete exterior calculus (DEC) in physical systems. It offers a range of models in fluid and solid mechanics that help users understand complex dynamics like shallow water and compressible Euler equations. DecLib preserves the inherent structures of these systems to ensure accurate and reliable simulations. It is a user-friendly application for exploring geometric mechanics and enhancing the study of physical phenomena. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DecLib v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00777O\nHy2.0-eos-lasso is a software tool that derives an equation of state (EOS) using the compound energy formalism (CEF) with LASSO-based parameter fitting. It uses experimental and density functional theory (DFT) data to derive accurate EOS parameters. This tool is designed for users familiar with CEF and aims to facilitate reproducibility in academic research by meeting open-sourcing requirements. Hy2.0-eos-lasso addresses fundamental materials modeling challenges by providing a robust method for EOS parameter fitting. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Hy2.0-eos-lasso v.0.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.0.0" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00731O\nNorma is a software tool that simplifies the testing of algorithms and concepts for coupling and multiphysics, with a focus on solid mechanics and heat conduction. 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Additionally, the simulator can trip lines and subsequently update and dispatch AGC signals, running power flow analysis after each tripping event.", + "laborHours": 197.6, + "languages": [ + "Python" + ], + "name": "Electric Grid Simulator For Human Factor Research", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/PSSE_for_Human_factor_research", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-18", + "metadataLastUpdated": "2025-02-18" + }, + "description": "The Lagrangian Droplet cloud microphysics scheme uses high-resolution data of air velocity, temperature, and water\nvapor mixing ratio to drive particle-based simulations of cloud microphysics. 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At it's core, it is an extensible framework composed of bash scripting and GNU parallel. HPC System Administrator will find it useful in that it encapsulates desired functions and allows them to be assembled in a way familiar to administrators - through pipes. In fact, NodeMan functions can work with common command line tools as long as they use stdin/stdout. System Administrators can construct moderately complex logic and filtering on a compact command line that would normally require a substantial shell script. In the spirit of clush and pdsh, it is able to run commands remotely on nodes. Additionally, NodeMan is more flexible. For example, it can interact with IPMI and naturally processes node lists for orchestrating different tools. The library of useful pre-built functions is growing. System administrators can easily create new functions and make it their own.", + "laborHours": 440.8, + "languages": [], + "name": "Nodeman: A Node Management Tool For Hpc Clusters", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/nodeman", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-20", + "metadataLastUpdated": "2025-02-20" + }, + "description": "An automated workflow and introduces new approaches to curate existing cybersecurity\nknowledge from multiple sources. It also proposes AI/ML-based methods to infer knowledge alignments across different\nrepositories.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 608.0, + "languages": [], + "name": "Cyber Knowledge Alignment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-20", + "metadataLastUpdated": "2025-02-20" + }, + "description": "We propose a generalized framework which performs an optimal partitioning of a limited budget into various\norganizational sectors in order to improve the cybersecurity of a smart device or component in the Cyber Physical Energy\nSystem (CPS). The framework identifies the adversarial threats and possible attack sequences which can be performed to\nexploit cyber vulnerabilities of the component. Thereafter, we formulate an Mixed Integer Linear Programming (MILP)\noptimization problem which aims to evaluate the optimal budget partitions in order to minimize the number of highly likely\nattack sequences. Though we provide results for using the framework in CPES, the proposed methodology can be\nextended for multiple domains with a set of known adversarial and mitigation actions.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 3526.4, + "languages": [], + "name": "Optimal Mitigation Planning For Adversarial Scenarios", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-20", + "metadataLastUpdated": "2025-02-20" + }, + "description": "Underwater video analysis software.", + "laborHours": 13771.2, + "languages": [], + "name": "pnnl/EyeSea", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/EyeSea", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-20", + "metadataLastUpdated": "2025-02-20" + }, + "description": "This repository contains the code necessary to process any new data for the Superfund Research Program Analytics Portal.", + "laborHours": 2447.2, + "languages": [], + "name": "PNNL-CompBio/srpAnalytics", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/srpAnalytics", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "sullivanhe@ornl.gov" + }, + "date": { + "created": "2025-02-21", + "metadataLastUpdated": "2025-02-21" + }, + "description": "This is the official implementation of ResSR [1]. ResSR is a computationally efficient MSI-SR method that achieves high-quality reconstructions by using a closed-form spectral decomposition along with a spatial residual correction. ResSR applies singular value decomposition to identify correlations across spectral bands, uses pixel-wise computation to upsample the MSI, and then applies a residual correction process to correct the high-spatial frequency components of the upsampled bands. While ResSR is formulated as the solution to a spatially-coupled optimization problem, we use pixel-wise regularization and derive an approximate closed-form solution, resulting in a pixel-wise algorithm with a dramatic reduction in computation that achieves state-of-the-art reconstructions.\n\n[1] Duba-Sullivan, H., Reid, E. J., Voisin, S., Bouman, C. A., & Buzzard, G. T. (2024). ResSR: A Computationally Efficient Residual Approach to Super-Resolving Multispectral Images. arXiv preprint arXiv:2408.13225.", + "laborHours": 532.0, + "languages": [ + "Python" + ], + "name": "hdsullivan/ResSR", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hdsullivan/ResSR", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2025-02-23", + "metadataLastUpdated": "2025-02-23" + }, + "description": "SF-25-008 This software optimizes quantum circuits using a two-step process. The first step, Clifford Extraction, moves the Clifford gates to the end of the circuit and includes circuit\noptimizations. The second step, Clifford Absorption, then addresses these extracted gates on a classical computer. By reducing the number of gates that need to run on the quantum device, the software achieves a significantly lower gate count.", + "laborHours": 66956.0, + "languages": [], + "name": "QuCLEAR", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/revilooliver/QuCLEAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-24", + "metadataLastUpdated": "2025-02-24" + }, + "description": "BioPAC is the Biological and other Particles in Aerosols Classifier. It is a software to assist in the accurate measurement\nand identification of primary biological aerosol particles, which play a pivotal role in mediating the reciprocal relationships\nbetween biological systems and atmospheric conditions.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 334.4, + "languages": [], + "name": "BioPac", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-02-24", + "metadataLastUpdated": "2025-03-11" + }, + "description": "GeoGridFusion facilitates the usage and storage of gridded geospatial satellite data by users outside of the National Renewable Lab (NREL), particularly those without access to high-performance computing (HPC) resources. This tool builds on work done by the PVDegradationTools project for DuraMAT, with the goal of making our advancements from this project widely accessible.\n\nThis repo contains utilities to allow for the storage of user downloaded geospatial weather data by providing a local datastore for storage and spatial queries, supporting large-scale analyses without the need for HPC resources.", + "laborHours": 9393.6, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "GeoGridFusion (Open-Source Geospatial Toolkit for Solar Data Integration\u200b) [SWR-25-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GeoGridFusion", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-25", + "metadataLastUpdated": "2025-02-25" + }, + "description": "The FEMP Cyber Security Arsenal is a family of cyber security tools for the federal facility owners and operators. Using these tools, facility owners can evaluate their overall cybersecurity posture. These tools are web-based front-end tools. The tools are meant to help federal owners and operators to evaluate their overall cybersecurity posture. These tools are developed based on the NIST Cybersecurity framework, risk management framework, and DOE C2M2 architectures. Version 3 provides significant updates and features in ten areas", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 126038.4, + "languages": [], + "name": "FEMP Cybersecurity Arsenal", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "3" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-25", + "metadataLastUpdated": "2025-02-25" + }, + "description": "A content repository for the life cycle inventory (LCI) rooftop unit (RTU) data collection template, a data collection template for the linked openLCA model Life Cycle Assessment (LCA) for automated Environmental Product Declaration (EPD) results generation.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Rooftop-Unit-LCI-Template", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Rooftop-Unit-LCI-Template", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "coellopereea@ornl.gov" + }, + "date": { + "created": "2025-02-25", + "metadataLastUpdated": "2025-02-25" + }, + "description": "An utility to benchmark the quality of an HPC and Quantum Computers integration. The benchmark allows the definition of a set of users for which a set of configurable quantum applications will be randomly selected. Example of currently supported quantum applications: VQE, PyMatching, RB. Users can create custom applications and use them together with the core applications. QStone generates different portable files (.tar.gz), each supporting a different user and a different scheduler (currently supporting: slurm, lsf, bare_metal). During execution of the benchmark, QStone gathers information on each steps of the applications, allowing investigations on bottlenecks and/or resource constraints at the interface between Quantum and HPC.", + "laborHours": 1611.2, + "languages": [ + "Python" + ], + "name": "QStone", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/riverlane/QStone", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.2.1" + }, + { + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-27", + "metadataLastUpdated": "2025-03-04" + }, + "description": "SAND2025-00659O\nMAPLE is a software tool that uses epigenomic data to predict gene expression. MAPLE uses a set of epigenomic modifications to determine the effect on gene expression in a specific subset of species. The algorithm can be trained on additional species and epigenomic modifications, enhancing its predictive capabilities. EAGLE employs a hybrid neural network architecture, featuring a convolutional front-end and a multi-head attention layer, to process pre-processed signal data as input. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 243.2, + "languages": [ + "Python" + ], + "name": "MAPLE v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MAPLE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" + }, + { + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2025-02-27", + "metadataLastUpdated": "2025-02-27" + }, + "description": "Simple Julia scrips for solving AC power flow, AC optimal power flow, and security-constrained AC\noptimal power flow.\nThese scripts are intended for experimentation with different (possibly, new) methods, formulations, and\nsettings for solving these power system problem. Their implementation, therefore, intentionally avoids\nexcessive encapsulation, which makes other packages difficult to modify by non-developers.", + "laborHours": 1307.2, + "languages": [], + "name": "Exascale Julia Grid Optimization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/exajugo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-03-05", + "metadataLastUpdated": "2025-03-05" + }, + "description": "HydroBoost is the most realistic revenue optimization tool for the hybridization of hydropower and battery energy storage systems to date. The innovative representation of how operators actually schedule hydropower in practice results in more realistic predictions of revenue and operations. Unlike other optimization tools, HydroBoost generates forecast energy prices with uncertainty to use in the optimization. This allows HydroBoost to give users a range of potential revenue with an upper bound using the perfect foresight pricing and a lower bound using a naive persistence forecast model. Additional forecast can be generated and used in the optimization, such as additive models, random forest, and neural networks to give further insight into potential revenue. \n\nHydroBoost has been designed to be applicable for both run-of-river and reservoir storage sites. The primary focus is on the day-ahead market and requires year-long data with an hour time-step. All time-series input and constraints are contained in an Excel worksheet for convince. The user will run the forecasting generation first with a Python script to give the optimization model the necessary requirements. Next the optimization is ran using Julia and results are generated and stored into a directory as csv files.\n\nHydroBoost includes an additional module to generate figures based on the results of the optimization simulation. The results help analyze the results and users to draw insights into how the hydro and battery systems are operated and the revenue each is producing. Additionally, the difference between the perfect foresight model and models that include forecast can easily be inspected.", + "laborHours": 1322.4, + "languages": [ + "Julia", + "Python" + ], + "name": "Hydroboost", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HydroBoost", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-03-05", + "metadataLastUpdated": "2025-03-05" + }, + "description": "This was written in React, using Typescript, Vite, and Material UI", + "laborHours": 10336.0, + "languages": [ + "JavaScript", + "TypeScript" + ], + "name": "Lbl/bctc Ldrd Graphical User Interface", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Solvent_Extraction_Experiment_GUI", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "khana@ornl.gov" + }, + "date": { + "created": "2025-03-06", + "metadataLastUpdated": "2025-03-07" + }, + "description": "HVAC is a high-performance caching system designed for large-scale AI training workloads.", + "laborHours": 684.0, + "languages": [ + "C++", + "C" + ], + "name": "High Velocity AI Cache (HVAC)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/akhanaornl/hvac.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "The Graph-based Learning of Aerosol Dynamics (GLAD) package implements a Graph Network-based Simulator (GNS), a machine learning framework that has been used to simulate particle-based fluid dynamics models", + "laborHours": 1079.2, + "languages": [], + "name": "pnnl/glad", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/glad", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Natural products have provided a rich reservoir of beneficial compounds in public health including antibiotics, therapeutics, and immunosuppressants. These natural products are synthesized by enzymes encoded by Biosynthetic Gene Clusters (BGCs), clusters of co-localized biosynthetic genes. Computational detection of BGCs has become a crucial step in natural product discovery. While this process has been facilitated in bacterial and fungal organisms thanks to the currently available tools (e.g., antiSMASH), a large spectrum of eukaryotic organisms have been neglected by these existing tools due to the scarcity and incompleteness of genome annotation resources. Here, we introduce Biosynthetic Gene cluster Extensive Search Tool (BiGEST) to provide an extensive annotation-free search for BGCs in diverse eukaryotic organisms. As a result, BiGEST uncovers eukaryotic BGCs that could be undetected by other BGC detection tools.", + "laborHours": 5639.2, + "languages": [], + "name": "BiGEST", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/BiGEST", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "The software being developed for this project has two mains aims. First, a Bayesian Model Calibration (BMC) procedure is being developed to calibrate a spallation model that simulates protons hitting a spacecraft orbiting earth to real data. The procedure will be developed for general data (there is no data release requested as part of this code release). Second, an inverse physics modeling task is being undertaken to map the number of resulting neutrons observed from this process to the expected number of protons that hit the model. This second task is of statistical interest; to publish on it, the code will need to be open source.", + "laborHours": 197.6, + "languages": [], + "name": "Code Release for \u201cUnlocking Extreme Space Weather through Advanced Modeling of Legacy Vela Spacecraft\u201d ER", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vela_sep", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Libra is a Python package that extends support of its parent package, SQLAlchemy. Libra\u2019s primary functionality supports the dynamic creation of object-oriented analogs of SQL tables from a variety of user-defined, text-based schema definition formats and provides quality control and analysis tools and methods", + "laborHours": 501.6, + "languages": [], + "name": "Libra", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Seismoacoustics/libra", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Latent Feature Attacks on Non-negative Matrix Factorization", + "laborHours": 1003.2, + "languages": [], + "name": "LaFA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/LaFA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Analyze virus genetic sequences to identify lineages that are spreading especially rapidly.", + "laborHours": 121.6, + "languages": [], + "name": "Graph theory approach to estimate the rate of SARS-CoV-2 lineage spread from early genetic sequence data", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ruianke/CoV2-GenomicGraphTheory-PCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-12" + }, + "description": "Software, Documentation, Tutorials, Testing data, Example data for processing, analysis, filtering, querying, visualization and otherwise transforming genomic data for scientific analysis and discovery.", + "laborHours": 45.6, + "languages": [], + "name": "epicsuite(EAS)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/epicsuite/epicsuite-readthedocs", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-12" + }, + "description": "Seismic amplitudes offer vital information about explosion source characteristics, including discrimination and yield estimation. To take advantage of this, we developed an interactive Python package to measure, control data quality, generate broad area propagation models and perform discrimination and estimate yield. Propagation models are essential in support of transportable yield and broad area discrimination. The key benefit of this package will be its ability to continuously integrate data and new techniques. The AmpSuite framework will provide standardized, repeatable, and accurate model generation and characterization routines. The capability is crucial for monitoring agencies tasked with rapid and high-quality seismic event characterization.\nThe AmpSuite software includes a series of independent modules to perform:\n\u2022 Direct Phase Amplitude Measurement and Storage\n\u2022 Coda Envelope Measurement and Storage\n\u2022 Data Quality Control\n\u2022 New Propagation Model Developments\n\u2022 Seismic Discrimination and Analysis\n\u2022 Yield Estimation\nand supporting utility software. The AmpSuite software provides comprehensive solutions for monitoring agencies seeking to optimize model generation and event analysis within a contemporary Python framework. Stakeholders (AFTAC) have begun to move towards the Python language for scientific analysis as a new workforce emerges.", + "laborHours": 440.8, + "languages": [], + "name": "AmpSuite", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/AmpSuite", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "We developed the atomistic-coarse-grained multiscale MD simulation method in the OpenMM simulation package by iterating between the all-atom (AA) and coarse-grained (CG) MD simulations to enhance the sampling of biomolecular conformations. As the free energy surfaces are flattened during CG MD simulations, we can accelerate the transitions between different low-energy conformations. The AA-CG-AA cycles are repeated, facilitating the accelerated sampling of biomolecular conformations at a CG level, while the finer atomistic interactions are refined with AA simulators.", + "laborHours": 304.0, + "languages": [], + "name": "Multiscale Molecular Dynamics Simulations: Accelerating Conformational Sampling of Biomolecular Systems by Iterating All-Atom and Coarse-Grained Simulations", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/iMMD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Repository of the codes developed for the paper titled \"Liouville Flow Importance Sampler\"", + "laborHours": 775.2, + "languages": [], + "name": "LFIS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/LFIS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "VerifyIO is a tool designed for verifying I/O consistency semantics in High-Performance Computing (HPC)\napplications. It addresses the challenges of ensuring correctness and portability across different I/O\nconsistency models, such as POSIX, Commit, Session, and MPI-IO. By analyzing execution traces,\ndetecting conflicts, and verifying synchronization adherence, VerifyIO provides actionable insights for both\napplication developers and I/O library designers.", + "laborHours": 760.0, + "languages": [], + "name": "VerifyIO: Verifying Adherence to Parallel I/O Consistency Semantics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wangvsa/VerifyIO", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "peless@ornl.gov" + }, + "date": { + "created": "2025-03-10", + "metadataLastUpdated": "2025-03-10" + }, + "description": "Modeling framework for power systems simulations and analysis.", + "laborHours": 10320.8, + "languages": [ + "C++" + ], + "name": "GridKit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/GridKit", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-12", + "metadataLastUpdated": "2025-03-12" + }, + "description": "P. putida KT2440 and related engineered strains.", + "laborHours": 232043.2, + "languages": [], + "name": "CRISPR-CARB/Pseudomonas_putida_KT2440_GEM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CRISPR-CARB/Pseudomonas_putida_KT2440_GEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "mtatonett@bnl.gov" + }, + "date": { + "created": "2025-03-13", + "metadataLastUpdated": "2025-03-13" + }, + "description": "It is a pre-trained model for processing blurred and noisy tomographic reconstruction taken from a fast fly-scan.", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "ultra_fast_tomo", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gmysage/ultra_fast_tomo", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-03-13", + "metadataLastUpdated": "2025-03-13" + }, + "description": "Ampworks is a collection of tools designed to process experimental battery data with a focus on model-relevant analyses. It currently provides functions for incremental capacity analysis and GITT data processing, helping extract key properties for life and physics-based models (e.g., SPM and P2D). Some tools, like the incremental capacity analysis module, also include graphical user interfaces for ease of use.\n\nhttps://github.com/NREL/ampworks/\nhttps://pypi.org/project/ampworks/", + "laborHours": 2082.4, + "languages": [ + "Python" + ], + "name": "ampworks: Battery analysis tools in Python [SWR-25-39]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ampworks", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-14", + "metadataLastUpdated": "2025-03-14" + }, + "description": "genome-scale model of Rhodobacter sphaeroides and flux analysis", + "laborHours": 265772.0, + "languages": [], + "name": "CRISPR-CARB/Rhodobacter_sphaeroides_GEMs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CRISPR-CARB/Rhodobacter_sphaeroides_GEMs", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "burtscher@txstate.edu" + }, + "date": { + "created": "2025-03-14", + "metadataLastUpdated": "2025-03-14" + }, + "description": "This repository contains the code and related scripts for 4 high-performance lossless compression algorithms for single- and double-precision floating-point data. They are named SPratio, SPspeed, DPratio, and DPspeed. The compressors work on CPUs and GPUs and deliver state-of-the-art throughputs and compression ratios.", + "laborHours": 4453.6, + "languages": [], + "name": "FPcompress", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/burtscher/FPcompress", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "burtscher@txstate.edu" + }, + "date": { + "created": "2025-03-14", + "metadataLastUpdated": "2025-03-14" + }, + "description": "This repository holds the PFPL code. PFPL is a guaranteed-error-bound lossy compressor/decompressor that produces bit-for-bit identical files on CPUs and GPUs. It supports absolute (ABS), relative (REL), and normalized-absolute (NOA) point-wise error bounds for single- and double-precision inputs in IEEE 754 binary format. It yields good compression ratios at high throughputs.", + "laborHours": 4316.8, + "languages": [], + "name": "PFPL", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/burtscher/PFPL", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-03-17", + "metadataLastUpdated": "2025-03-17" + }, + "description": "FuelLib is a library that utilizes the group contribution method (GCM) for calculating thermodynamic properties of hydro-carbon jet fuels.\n\nFuelLib utilizes the tables and functions of the GCM as proposed by Constantinou and Gani (1994) and Constantinou, Gani and O'Connel (1995), with additional physical properties discussed in Govindaraju & Ihme (2016). The code is based on Pavan B. Govindaraju's Matlab implementation of the GCM, and has been expanded to include additional thermodynamic properties and mixture properties. The fuel library contains gas chromatography (GC x GC) data for a variety of fuels ranging from simple single component fuels to complex jet fuels. The GC x GC data for POSF jet fuels comes from Edwards (2020).", + "laborHours": 532.0, + "languages": [ + "Python" + ], + "name": "FuelLib (Fuel Library) [SWR-25-26]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/FuelLib", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "congg@ornl.gov" + }, + "date": { + "created": "2025-03-17", + "metadataLastUpdated": "2025-03-17" + }, + "description": "We propose TransPlatformer for translating toxicogenomics from one platform to another. Transcriptomic profiling has evolved through multiple generations of technology, from microarrays (e.g., Affymetrix, CodeLink) to more recent high-throughput sequencing and targeted panels such as S1500+. Microarrays, which dominated gene expression studies in the early 2000s, provided affordable and high-throughput transcript quantification but suffered from cross-hybridization issues and limited dynamic range . RNA-Seq, introduced in the late 2000s, revolutionized transcriptomics by enabling unbiased and comprehensive gene expression analysis, albeit at higher costs and computational demands .\n\nDespite advances, many studies rely on historical microarray data, necessitating the translation of legacy data into modern platforms to ensure continuity and comparability. This translation is complicated by factors such as platform-specific probe design, differences in transcript coverage, and batch effects . Existing methods for cross-platform mapping include statistical normalization, machine learning models, and biological anchoring approaches.\n\nThe ability to translate transcriptomic data between platforms has broad implications, including enhanced meta-analyses, improved toxicological modeling, and better integration of historical datasets with contemporary research. TransPlatformer seeks to contribute to this effort by evaluating translation methodologies and proposing novel strategies to improve cross-platform gene expression harmonization.\n\nIn this repository there are code examples for TransPlatformer implementation", + "laborHours": 592.8, + "languages": [ + "Python" + ], + "name": "TransPlatformer", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/goooopy/TransPlatformer", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2025-03-17", + "metadataLastUpdated": "2025-03-17" + }, + "description": "Sigma is a header-only C++ library for uncertainty propagation throughout mathematical operations on floating point values.", + "laborHours": 1231.2, + "languages": [ + "C++", + "GCC 12-14", + "Clang 14", + "MSVC" + ], + "name": "QCUncertainty/sigma", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QCUncertainty/sigma", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-19", + "metadataLastUpdated": "2025-03-19" + }, + "description": "MUPPET is a tool for OpenMP programs that identifies program modifications, called mutations, aimed at\nimproving program performance. Existing performance optimization techniques, including profiling-based\nand auto-tuning techniques, fail to indicate program modifications at the source level thus preventing their\nportability across compilers. MUPPET aims to help HPC developers reason about performance defects\nand missed opportunities to improve performance at the source code level.", + "laborHours": 12570.4, + "languages": [], + "name": "MUPPET: An automated OpenMP mutation testing framework for performance optimization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MUPPET", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "gonzalesjj@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "Mind the Gap is an algorithm for detecting areas of missing data in building footprints.", + "laborHours": 440.8, + "languages": [ + "Python" + ], + "name": "ORNL/mind_the_gap", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/mind_the_gap/blob/main/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/mind_the_gap", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "This package is part of the Likeness Python toolkit, which generates high-fidelity synthetic populations for human dynamics modeling. The LiveLike package provides a high-level wrapper for generating synthetic populations via Census APIs based on the American Community Survey (ACS) 5-Year Estimates. Synthetic populations are virtual representations of people and households produced for small census areas (block groups, tracts) and can be attributed by a variety of demographic, economic, social, worker, student, mobility, housing, health, and communication characteristics found in the ACS.", + "laborHours": 4636.0, + "languages": [ + "Python" + ], + "name": "LiveLike", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/livelike/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/livelike", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.4.7" + }, + { + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "The PyMEDM package is a Python-native port of Penalized-Maximum Entropy Dasymetric Modeling (P-MEDM) method. While the original implementation of P-MEDM consists of an R interface over a model written in C++, PyMEDM combines both capabilities in a common language that interfaces with other utilities in the Likeness stack. PyMEDM is also GPU-enabled via JAX , which supports High-Performance Computing (HPC) applications.", + "laborHours": 1580.8, + "languages": [ + "Python" + ], + "name": "PyMEDM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/pymedm/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/pymedm", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "2.2.3" + }, + { + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "This package is part of the Likeness Python toolkit, which generates high-fidelity synthetic populations for human dynamics modeling. The PMEDM-Legacy package provides a Python interface for using the original implementation of Penalized-Maximum Entropy Dasymetric Modeling (P-MEDM) method, written in R/C++, for statistically matching population survey data from the American Community Survey's Public-Use Microdata Sample (PUMS) to sub-county spatial scales. To achieve this, it interfaces with a companion R package in the Likeness stack, PMEDMrcppPal, via the rpy2 Python-R bridge.", + "laborHours": 486.4, + "languages": [ + "Python" + ], + "name": "PMEDM-Legacy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/pmedm-legacy/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/pmedm-legacy", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.5" + }, + { + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "This package is part of the Likeness Python toolkit, which generates high-fidelity synthetic populations for human dynamics modeling. It primarily supports the PMEDM-Legacy package, which provides a Python interface for using the original implementation of Penalized-Maximum Entropy Dasymetric Modeling (P-MEDM) method, written in R/C++, for statistically matching population survey data from the American Community Survey's Public-Use Microdata Sample (PUMS) to sub-county spatial scales. Model inputs specified in the Python environment are converted to R variables and passed to the PMEDMrcpp model with PMEDMrcppPal.", + "laborHours": 91.2, + "languages": [ + "R" + ], + "name": "PMEDMrcpp-Pal", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/pmedmrcpp-pal/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/pmedmrcpp-pal", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.1" + }, + { + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "This package is part of the Likeness Python toolkit, which generates high-fidelity synthetic populations for human dynamics modeling.", + "laborHours": 577.6, + "languages": [ + "Python" + ], + "name": "Likeness-Vitals", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/likeness-vitals/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/likeness-vitals", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.4.3" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-21", + "metadataLastUpdated": "2025-03-21" + }, + "description": "This is a tool for long term prognosis of redox flow battery parameter degradation which uses Transformer-based deep\nlearning models for time series forecasting which was developed as part of the ROVI project.", + "laborHours": 19592.8, + "languages": [], + "name": "pnnl/battery-degradation-prognosis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/battery-degradation-prognosis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-21", + "metadataLastUpdated": "2025-03-21" + }, + "description": "repligit will be a python library which implements the git transfer protocol allowing git repositories to be\nmirrored between two locations without storing state locally.", + "laborHours": 152.0, + "languages": [], + "name": "repligit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/repligit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-24", + "metadataLastUpdated": "2025-03-24" + }, + "description": "Using the genome annotation as input, Pathway-tools generates a database containing all the information that can be\ninferred from the genome. The Pathway/Genome database (PGDB) can subsequently be curated manually\nLicensed under the CC-BY-4.0 license", + "laborHours": 106.4, + "languages": [], + "name": "pnnl-predictive-phenomics/csc052cyc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl-predictive-phenomics/csc052cyc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc052cyc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-24", + "metadataLastUpdated": "2025-03-24" + }, + "description": "Using the genome annotation as input, Pathway-tools generates a database containing all the information that can be\ninferred from the genome. The Pathway/Genome database (PGDB) can subsequently be curated manually", + "laborHours": 136.8, + "languages": [], + "name": "pnnl-predictive-phenomics/csc040cyc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl-predictive-phenomics/csc040cyc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc040cyc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-24", + "metadataLastUpdated": "2025-03-24" + }, + "description": "Organism-specific Pathway/Genome databases enable the analysis, visualization and interrogation of metabolism,\nregulation, and genetics.\nLicensed under the CC-BY-4.0 license", + "laborHours": 212.8, + "languages": [], + "name": "pnnl-predictive-phenomics/csc031cyc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl-predictive-phenomics/csc031cyc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc031cyc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-24", + "metadataLastUpdated": "2025-03-24" + }, + "description": "Using the genome annotation as input, Pathway-tools generates a database containing all the information that can be\ninferred from the genome. The Pathway/Genome database (PGDB) can subsequently be curated manually.\nLicensed under the CC-BY-4.0 license", + "laborHours": 76.0, + "languages": [], + "name": "pnnl-predictive-phenomics/csc009cyc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl-predictive-phenomics/csc009cyc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc009cyc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-24", + "metadataLastUpdated": "2025-03-24" + }, + "description": "Organism-specific Pathway/Genome databases enable the analysis, visualization and interrogation of metabolism,\nregulation, and genetics.\nLicensed under the CC-BY-4.0 license", + "laborHours": 121.6, + "languages": [], + "name": "pnnl-predictive-phenomics/csc043cyc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl-predictive-phenomics/csc043cyc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc043cyc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "haunab@ornl.gov" + }, + "date": { + "created": "2025-03-25", + "metadataLastUpdated": "2025-04-22" + }, + "description": "A CLI for interacting with Klipper components.", + "laborHours": 45.6, + "languages": [ + "Python" + ], + "name": "klipperctl", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Laikulo/klipperctl.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-25", + "metadataLastUpdated": "2025-03-25" + }, + "description": "In this work, we detail two uncertainty quantification (UQ) methods that provide complementary information. Readout\nensembling, by finetuning only the readout layers of an ensemble of foundation models, provides information about model\nuncertainty. Amending the final readout layer to predict upper and lower quantiles replaces point predictions with\ndistributional predictions, which provide information about uncertainty within the underlying training data. We\ndemonstrate our approach with the MACE-MP-0 model, applying UQ to both the foundation model and a series of finetuned\nmodels. The uncertainties produced by the ensemble and quantile methods are demonstrated to be distinct measures by\nwhich the quality of the NNP output can be judged.", + "laborHours": 33485.6, + "languages": [], + "name": "pnnl/SNAP", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/snap", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "gautama@ornl.gov" + }, + "date": { + "created": "2025-03-26", + "metadataLastUpdated": "2025-03-26" + }, + "description": "NeuroCoreX is an open-source codebase that enables the implementation of brain-inspired, energy-efficient neuromorphic computing models on FPGA hardware. Designed to support real-time learning, all-to-all neural connectivity, and flexible network architectures, NeuroCoreX offers a hands-on, accessible platform for exploring biologically inspired models of neural computation. It empowers researchers, students, and developers to implement and experiment with adaptive systems\u2014bringing the power of neuromorphic computing to a broader community through a low-cost, scalable, and reconfigurable framework.", + "laborHours": 0.0, + "languages": [ + "VHDL" + ], + "name": "NeuroCoreX: Brain-Inspired Computing from Code to Circuit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/NeuroCoreX", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-03-26", + "metadataLastUpdated": "2025-03-26" + }, + "description": "Urban heat is a growing concern, particularly in dense metropolitan areas where high temperatures increase the risk of heat-related illness and drive energy expenses for cooling. Estimating the effects of urban heat remains a challenge due to limitations in describing the built environment, computational constraints, and the need for high-resolution data. This software presents open-source, computationally efficient machine learning methods that enhance the accuracy of urban temperature estimates compared to historical reanalysis data. Models trained using this software have been applied to urban microclimates in Los Angeles and Seattle showing greater accuracy and less bias when compared to low-resolution reanalysis datasets like ERA5 and even when compared to high-resolution mesoscale numerical weather models like WRF with an urban canopy model. Initial findings highlight how machine learning can support urban heat resilience planning by enabling improved assessments of local heat islands, mitigation strategies, and their energy implications.\n\nThis software is an extension of (sup3r).\n\nThis software supports the following publication:\n\nBuster, Grant, et al. Tackling Extreme Urban Heat: A Machine Learning Approach to Assess the Impacts of Climate Change and the Efficacy of Climate Adaptation Strategies in Urban Microclimates. arXiv:2411.05952, arXiv, 8 Nov. 2024. arXiv.org, https://doi.org/10.48550/arXiv.2411.05952.\n\nAnd has related public data records available at:\n\nBuster, Grant, Cox, Jordan, Benton, Brandon, and King, Ryan. Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI). United States: N.p., 16 Oct, 2024. Web. https://data.openei.org/submissions/6220.", + "laborHours": 775.2, + "languages": [ + "Python" + ], + "name": "sup3ruhi (Super Resolution for Renewable Resource Data and Urban Heat Islands) [SWR-25-05]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/sup3ruhi", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "dietzdt@ornl.gov" + }, + "date": { + "created": "2025-03-27", + "metadataLastUpdated": "2025-03-28" + }, + "description": "Acceptance and regression testing of a High Performance Computing (HPC) system requires an automated and reproducible framework and tool for running and logging results. Manually running tests across a system is labor intensive and prone to reproducibility errors. The OLCF Test Harness (OTH) provides a framework in which to document required tests for a HPC system. The OTH then provides tools to execute and log results of these tests in an automated fashion.", + "laborHours": 22496.0, + "languages": [ + "Python" + ], + "name": "OLCF Test Harness", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/olcf/olcf-test-harness/blob/devel/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/olcf-test-harness", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "3.0" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-31", + "metadataLastUpdated": "2025-03-31" + }, + "description": "This software provides methods and functions for training deep image classification models based on the\nprinciple of anchoring. It features a user-friendly PyTorch wrapper that facilitates the easy conversion of\nany model into an anchored model. The software supports various standard datasets and includes scripts\nfor conducting evaluations. Developed with PyTorch, it is compatible with common neural network\narchitectures used for image data. Additionally, it offers tools for computing evaluation metrics to assess\nmodel performance.", + "laborHours": 2872.8, + "languages": [], + "name": "Anchoring", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/anchoring", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-31", + "metadataLastUpdated": "2025-03-31" + }, + "description": "The Program for Climate Model Diagnosis & Intercomparison (PCMDI) Metrics Package (PMP) is used to\nprovide \"quick-look\" objective comparisons of Earth System Models (ESMs) with one another and\navailable observations. The PMP provides a diverse suite of analysis utilities each of which produce\nsummary statistics that gauge the consistency between climate model simulations and available\nobservations. The primary application of the PMP is to evaluate simulations from the Coupled Model\nIntercomparison Project (CMIP). It can also be used to provide objective performance summaries during\nthe model development process as well as selected research purposes.", + "laborHours": 173112.8, + "languages": [], + "name": "PCMDI Metrics Package", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PCMDI/pcmdi_metrics", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.8.2" + }, + { + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-31", + "metadataLastUpdated": "2025-03-31" + }, + "description": "This code is used to conduct topology optimization of a general full cell energy storage device. The anode\nand cathode designs are optimized simultaneously, allowing possibility for interdigitation. 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By clustering similar documents together, this Windows-based software unveils common themes and reveals hidden relationships within the collection. IN-SPIRE\u2122 allows analysts to spend more time exploring the information they find most relevant and less time sifting through the masses of irrelevant documents.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 3747666.4, + "languages": [], + "name": "IN-SPIRE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "5" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-15", + "metadataLastUpdated": "2025-04-15" + }, + "description": "INFRA-COMPASS is an innovative software tool that harnesses the power of Large Language Models (LLMs) to automate the compilation and continued maintenance of an inventory of state and local codes and ordinances pertaining to energy infrastructure.", + "laborHours": 5274.4, + "languages": [ + "Python", + "Rust" + ], + "name": "INFRA-COMPASS (Infrastructure Continuous Ordinance Mapping for Planning and Siting Systems) [SWR-25-62]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/COMPASS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v.0.3.0" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-15", + "metadataLastUpdated": "2025-04-15" + }, + "description": "A domain-aware generative framework that takes 3D coordinates of the molecule and scaffold as an input\nand generates 3D coordinates of novel therapeutic candidates as an output while preserving the desired scaffolds. 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This code can be used to produce vision\nlanguage models (VLMs), like LLaVA, with enhanced robustness to adversarial attacks (e.g. jailbreaks).", + "laborHours": 225188.0, + "languages": [], + "name": "Double Visual Defense", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zw615/Double_Visual_Defense", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" + }, + { + "contact": { + "email": "prokopenkoav@ornl.gov" + }, + "date": { + "created": "2025-04-16", + "metadataLastUpdated": "2025-04-17" + }, + "description": "ArborX library tackles a problem of efficiently finding geometric objects that are close in space. 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+ "laborHours": 9165.6, + "languages": [], + "name": "Yoke", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Yoke", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-04-18", + "metadataLastUpdated": "2025-04-18" + }, + "description": "FleCSI Linear Algebra Package", + "laborHours": 7964.8, + "languages": [], + "name": "flecsolve", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/flecsolve", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-04-18", + "metadataLastUpdated": "2025-04-18" + }, + "description": "A probabilistic programming language for python built on numpy", + "laborHours": 1124.8, + "languages": [], + "name": "arianna-ppl", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/arianna-ppl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-04-18", + "metadataLastUpdated": "2025-04-18" + }, + "description": "scons-novice is a re-write of the Software Carpentry https://software-carpentry.org/ \"make-novice\" source material https://github.com/swcarpentry/make-novice used to create the webpage lesson plan \"Automation and Make\" http://swcarpentry.github.io/make-novice/ which is licensed as under the Creative Commons Attribution license (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/.\n\nscons-novice changes the lesson to teach SCons instead of Make.", + "laborHours": 2264.8, + "languages": [], + "name": "scons-novice", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-aea/scons-novice", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-04-18", + "metadataLastUpdated": "2025-04-18" + }, + "description": "A Probabilistic Kernel-Based n-ary Classification Method for Sets of Observations", + "laborHours": 334.4, + "languages": [], + "name": "KeNary", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/KeNary", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-04-18", + "metadataLastUpdated": "2025-04-18" + }, + "description": "The Bilinear Ensemble Actuation Synthesis Toolkit (BEAST) is a computational platform that optimizes time-varying control signals to achieve a specified transfer of states governed by bilinear ensemble systems in which model parameters are subject to uncertainty.", + "laborHours": 197.6, + "languages": [], + "name": "BEAST", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/BEAST", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-21", + "metadataLastUpdated": "2025-04-21" + }, + "description": "CLIQUE provides insight into the nature of current activity on network infrastructure through visual representations of typical and atypical patterns.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 76927.2, + "languages": [], + "name": "Correlation Layers for Information Query and Exploration", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "kincaidkc@ornl.gov" + }, + "date": { + "created": "2025-04-21", + "metadataLastUpdated": "2025-04-21" + }, + "description": "CaptureFOAM provides utilities for fast and accurate direct air capture (DAC) contactor simulations, based on the OpenFOAM framework. At the core, CaptureFOAM is a suite of mass transfer and chemistry models built upon the OpenFOAM thin film model, which allows coarser mesh resolution and less constrictive time step requirements when compared to a traditional volume of fluid approach. This allows CaptureFOAM to conduct device-scale simulations for complex geometries including commercial packing materials and novel contactor shapes, matching experimental results in a wide variety of applications.", + "laborHours": 1200.8, + "languages": [ + "C++" + ], + "name": "CaptureFOAM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/CaptureFOAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-21", + "metadataLastUpdated": "2025-04-21" + }, + "description": "BHResist is a pure python library for computing thermal resistance within single-u, double-u, and coaxial grouted borehole heat exchangers. For single and double u-tube configurations, the methods use the 1st-order closed-form multipole approximations, which typically produces results with less than 1% error when compared to the 10th-order multipole method. Coaxial borehole methods apply a simple 1D resistance network method.\n\nThis is intended to be a lightweight library that can be easily imported into any other Python tool, with no bulky dependencies.", + "laborHours": 896.8, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "BHResist [SWR-25-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BHResist", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-22", + "metadataLastUpdated": "2025-04-22" + }, + "description": "This is a research code which is intended to be made available to researchers to the password-protected simtk.org\nwebsite which hosts the lung deposition simulation project \"In-silico LADDER: Lung Aerosol Dosimetry for Drug and\nEnvironmental Research\" headed by NIH PI Prof. Chantal Darquenne (UCSD). Industrial applications are more accurate\ndeposition predictions of medical aerosols, including potentially subject-specific exposures.\nAccessing the code requires registration.", + "homepageURL": "https://simtk.org/projects/insilico_ladder", + "laborHours": 851.2, + "languages": [], + "name": "multiBreath.py", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://simtk.org/projects/insilico_ladder", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-22", + "metadataLastUpdated": "2025-04-22" + }, + "description": "Code repository to assist the planning, management, and data analysis of experiment field campaigns including atmospheric sensors, remote sensing devices, and renewable energy plants.", + "laborHours": 1839.2, + "languages": [ + "Python" + ], + "name": "FIEXTA (FIeld EXperiments Tool Arsenal) [SWR-24-129]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/FIEXTA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-22", + "metadataLastUpdated": "2025-04-22" + }, + "description": "T3CO-Go is a web-based dashboard with a user interface to modify input assumptions, run the T3CO tool, and visualize results. The dashboard, built using Python, can be run on a local server when installed from PyPI or hosted on the cloud and embedded in a webpage. T3CO-Go allows even non-Python-proficient users to customize their T3CO experience and gain insights from results customized for their analysis purpose.\n\nSee also, PyPI Package: https://pypi.org/project/t3co-go/", + "laborHours": 410.4, + "languages": [ + "Python" + ], + "name": "T3CO-Go: A web-based dashboard for the Transportation Technology Total Cost of Ownership tool [SWR-25-38]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/t3co_go", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.2" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-22", + "metadataLastUpdated": "2025-04-22" + }, + "description": "This script, developed by NREL, implements an inertia estimation algorithm using a sliding window approach. The inertia (H) is estimated based on frequency deviations and active power deviations, utilizing the swing equation from power system dynamics. An example application is provided using the WECC 240-bus system.", + "laborHours": 30.4, + "languages": [ + "Python" + ], + "name": "Open-Source Ambient-Signal-Based Inertia Monitoring Tool for Power systems [SWR-25-59]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Open-Source-Ambient-Signal-Based-Inertia-Monitoring-Tool-for-Power-systems", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-23", + "metadataLastUpdated": "2025-04-23" + }, + "description": "Computationally efficient flood simulation using Lagrangian rivulets.", + "laborHours": 1383.2, + "languages": [], + "name": "DOE-ICoM/Torrent.jl", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DOE-ICoM/Torrent.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-24", + "metadataLastUpdated": "2025-04-24" + }, + "description": "Code base to run Streamlit Value of Information App for binary decision with geothermal techno economics.\n\nAn open-source VOI app that models binary decisions (e.g. do something (drill) or walk away (do nothing)) and binary geothermal scenarios (positive or negative) has been developed. Users can input their anticipated economic values (profits or losses) directly into the value matrix to represent all four combinations of these actions and geothermal possibilities. VOI in general requires probabilities to be assigned for \u201cprobability of success\u201d, or probability of experiencing a positive geothermal scenario versus negative. The users of the App can toggle this probability of success both in the demo problem and in the Value of Imperfect Information problem. The VOI App allows users to upload their own labeled data to evaluate how well it allows them to distinguish between positive versus negative sites. We have been using IGNENIOUS data to test and demonstrate; industry members have prepared their own labeled data, and have present their examples from diverse use cases at a conference workshop. \n\nThe VOI App is open to the public at: https://voigeothermalrising.streamlit.app", + "laborHours": 440.8, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "Value of Information App (Value of Information App for Binary Geothermal Decisions and Binary Geothermal Possibilities) (Negative/Positive) [SWR-25-15]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Value_of_Information_App", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "peless@ornl.gov" + }, + "date": { + "created": "2025-04-25", + "metadataLastUpdated": "2025-04-25" + }, + "description": "The software provides Ipopt optimization package an interface to the Re::Solve linear solver library. Re::Solve features GPU-resident direct and iterative linear solvers that could be used to accelerate optimization computations.", + "laborHours": 106688.8, + "languages": [], + "name": "Ipopt Interface to Re::Solve Linear Solver", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/Ipopt", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" + }, + { + "contact": { + "email": "tancw@stanford.edu" + }, + "date": { + "created": "2025-04-28", + "metadataLastUpdated": "2025-04-28" + }, + "description": "BatteryOS is a software package for software virtualization of batteries, particularly grid-attached batteries in homes and home battery/solar installations. BatteryOS allows users to aggregate and partition batteries and supports a simple driver interface for connecting it to physical batteries. BatteryOS was developed as part of the TrustDER: Trusted, Private and Scalable Coordination of Distributed Energy Resources project at Stanford University, funded by the Department of Energy in Agreement DE-OE0000919. The project concluded in the summer of 2024.\n\nThe BatteryOS (BOS) package is consisted of software and drivers for creating and managing virtual batteries. It includes support for private battery aggregation. BatteryOSv1 was the first Python implementation; BatteryOSv2 was the first C++ implementation; BatteryOSv3 is the final, cleaned-up C++ implementation.", + "laborHours": 12859.2, + "languages": [], + "name": "BatteryOS", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Stanford-New-Energy-Systems/BatteryOS", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" + } + ], + "version": "2.0.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/\tCRISPR_Recognition_Tool__CRT__-_Command_Line_Interface__IMGAP_Version___CRT-CLI__v1.8.3.json" "b/agency-indexes/DoE/\tCRISPR_Recognition_Tool__CRT__-_Command_Line_Interface__IMGAP_Version___CRT-CLI__v1.8.3.json" new file mode 100644 index 00000000..d397094a --- /dev/null +++ "b/agency-indexes/DoE/\tCRISPR_Recognition_Tool__CRT__-_Command_Line_Interface__IMGAP_Version___CRT-CLI__v1.8.3.json" @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2023-05-08" + }, + "description": "\tThe CRT Command Line Interface is a software tool released as public domain software in 2007 by Charles Bland and can be downloaded under http://www.room220.com/crt/.\n\nThe last CRT-CLI release update was in 2008 and bumped up its version number to 1.2.\n\nWe used the CRT-CLI tool in our IMG Annotation Pipeline and over the years modified the original code based on suggestions made by our in-house experts to add more functionality, e.g. being able to detect truncated repeats at the edge of sequences or repeats containing Ns, additional output file options, and additional identity and similarity control parameters.", + "laborHours": 0.0, + "languages": [], + "name": "\tCRISPR Recognition Tool (CRT) - Command Line Interface (IMGAP Version) (CRT-CLI) v1.8.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/img/img-pipelines/crt-cli-imgap-version", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/\tECO2N_V2.0.json" "b/agency-indexes/DoE/\tECO2N_V2.0.json" new file mode 100644 index 00000000..d18c41d4 --- /dev/null +++ "b/agency-indexes/DoE/\tECO2N_V2.0.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-27", + "metadataLastUpdated": "2019-09-24" + }, + "description": "ECO2N V2.0 is a fluid property module for the TOUGH2 simulator (Version 2.1) that was designed for applications to geologic sequestration of CO2 in saline aquifers and enhanced geothermal reservoirs. ECO2N V2.0 is an enhanced version of the previous ECO2N V1.0 module (Pruess, 2005). It expands the temperature range up to about 300oC whereas V1.0 can only be used for temperatures below about 110oC. V2.0 includes a comprehensive description of the thermodynamic and thermophysical properties of H2O - NaCl - CO2 mixtures, that reproduces fluid properties largely within experimental error for the temperature, pressure and salinity conditions 10 \u00b0C < T < 300 \u00b0C, P < 600 bar, and salinity up to halite saturation. This includes density, viscosity, and specific enthalpy of fluid phases as functions of temperature, pressure, and composition, as well as partitioning of mass components H2O, NaCl and CO2 among the different phases. In particular, V2.0 accounts for the effects of water on the thermophysical properties of the CO2-rich phase, which was ignored in V1.0, using a model consistent with the solubility models developed by Spycher and Pruess (2005, 2010). In terms of solubility models, V2.0 uses the same model for partitioning of mass components among the different phases (Spycher and Pruess, 2005) as V1.0 for the low temperature range (<99oC) but uses a new model (Spycher and Pruess, 2010) for the high temperature range (>109oC). In the transition range (99-109oC), a smooth interpolation is applied to estimate the partitioning as a function of the temperature. Flow processes can be modeled isothermally or non-isothermally, and phase conditions represented may include a single (aqueous or CO2-rich) phase, as well as two-phase (brine-CO2) mixtures. Fluid phases may appear or disappear in the course of a simulation, and solid salt may precipitate or dissolve. Note that the model cannot be applied to subcritical conditions that involves both liquid and gaseous CO2 unless thermol process is ignored (i.e.,isothermal run). For those cases, a user may use the fluid property module ECO2M (Pruess, 2011) instead.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "\tECO2N V2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/\tIndependent_Metadata_Update_VOL_Connector_for_HDF5__IMM_VOL__v0.1.json" "b/agency-indexes/DoE/\tIndependent_Metadata_Update_VOL_Connector_for_HDF5__IMM_VOL__v0.1.json" new file mode 100644 index 00000000..831d0180 --- /dev/null +++ "b/agency-indexes/DoE/\tIndependent_Metadata_Update_VOL_Connector_for_HDF5__IMM_VOL__v0.1.json" @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-08-18", + "metadataLastUpdated": "2020-08-18" + }, + "description": "We have built a new framework that enables independent metadata updates within HDF5 files. Our framework includes the following components: an overlay network that's optimized for 1-to-All and All-to-All communication; root-less/server-less Bcast and AllReduce operations for reduced synchronization; a distributed consensus-making platform; an execution order keeping system, and a progress engine for generic threadless concurrence handling.", + "laborHours": 0.0, + "languages": [], + "name": "\tIndependent Metadata Update VOL Connector for HDF5 (IMM VOL) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://tonglinli@bitbucket.hdfgroup.org/scm/hdf5vol/imm_vol.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/\tManaging_Data_on_Tiered_Storage_for_Scientific_Workflows__MaDaTS__v1.1.2.json" "b/agency-indexes/DoE/\tManaging_Data_on_Tiered_Storage_for_Scientific_Workflows__MaDaTS__v1.1.2.json" new file mode 100644 index 00000000..0fd8320f --- /dev/null +++ "b/agency-indexes/DoE/\tManaging_Data_on_Tiered_Storage_for_Scientific_Workflows__MaDaTS__v1.1.2.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-05-18", + "metadataLastUpdated": "2018-05-21" + }, + "description": "MaDaTS provides an integrated data management and workflow execution framework on multi-tiered storage systems. Users of MaDaTS can execute a workflow by either specifying the workflow stages in a YAML description file, or use the API to manage the workflow through a Virtual Data Space (VDS) abstraction.", + "laborHours": 4484.0, + "languages": [], + "name": "\tManaging Data on Tiered Storage for Scientific Workflows (MaDaTS) v1.1.2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dghoshal-lbl/madats", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/\tdiBELLA_2D:_Parallel_String_Graph_Construction_and_Transitive_Reduction_for_De_Novo_Assembly__diBELLA_2D__v1.0.json" "b/agency-indexes/DoE/\tdiBELLA_2D:_Parallel_String_Graph_Construction_and_Transitive_Reduction_for_De_Novo_Assembly__diBELLA_2D__v1.0.json" new file mode 100644 index 00000000..41b918f0 --- /dev/null +++ "b/agency-indexes/DoE/\tdiBELLA_2D:_Parallel_String_Graph_Construction_and_Transitive_Reduction_for_De_Novo_Assembly__diBELLA_2D__v1.0.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2021-03-11" + }, + "description": "In this work we present a 2D distributed memory algorithm for overlap detection and introduce a novel design and implementation for layout simplification where we perform a transitive reduction from overlap graph to string graph in the context of de novo genome assembly.", + "laborHours": 0.0, + "languages": [], + "name": "\tdiBELLA 2D: Parallel String Graph Construction and Transitive Reduction for De Novo Assembly (diBELLA 2D) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PASSIONLab/diBELLA.2D", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/1D_EDIPIC.json b/agency-indexes/DoE/1D_EDIPIC.json new file mode 100644 index 00000000..380fc405 --- /dev/null +++ b/agency-indexes/DoE/1D_EDIPIC.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "apritch@pppl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-21" + }, + "description": "EDIPIC codes were developed for simulation of kinetic effects in low-temperature plasmas. They can be used for simulation of plasmas in electrostatic approximation and include many atomistic and plasma-surface interaction processes needed for simulations of low temperature plasmas. These codes include a detailed model of secondary electron emission induced by electrons and ions. The Monte-Carlo model of electron-neutral collisions and the Langevin model of Coulomb collisions for electrons are also implemented.", + "laborHours": 0.0, + "languages": [ + "C", + "Fortran" + ], + "name": "1D EDIPIC", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PrincetonUniversity/EDIPIC", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/2-D_Surface_Temperature_Simulation_Data_and_Matlab_Scripts.json b/agency-indexes/DoE/2-D_Surface_Temperature_Simulation_Data_and_Matlab_Scripts.json new file mode 100644 index 00000000..473945c8 --- /dev/null +++ b/agency-indexes/DoE/2-D_Surface_Temperature_Simulation_Data_and_Matlab_Scripts.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-07249O\nThe 2-D Surface Temperature Simulation Data and Matlab software can estimate 2D temperature fields from electrical measurements along the edge of the 2D domain.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 91.2, + "languages": [ + "Matlab" + ], + "name": "2-D Surface Temperature Simulation Data and Matlab Scripts", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/2-D-Surface-Temperature-Simulation-Data", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/2023_Data_Science_Challenge_Notebooks.json b/agency-indexes/DoE/2023_Data_Science_Challenge_Notebooks.json new file mode 100644 index 00000000..d56ee378 --- /dev/null +++ b/agency-indexes/DoE/2023_Data_Science_Challenge_Notebooks.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-25", + "metadataLastUpdated": "2023-05-25" + }, + "description": "THE DATA SCIENCE INSTITUTE WILL BE INVITING STUDENTS FROM UC MERCED AND UC\nRIVERSIDE TO PARTICIPATE IN A DATA SCIENCE CHALLENGE AT LLNL. IN THE CHALLENGE,\nTHE STUDENTS WILL EXPLORE A DATA-DRIVEN APPROACH TO RECONSTRUCTING ELECTROANATOMICAL\nMAPS OF THE HEART AT CLINICALLY RELEVANT RESOLUTIONS, COMBINING\nINPUT FROM THE STANDARD 12-LEAD ECG WITH ADVANCED MACHINE LEARNING\nTECHNIQUES. THE DATA THE STUDENTS WILL HAVE ACCESS TO HAS BEEN IM REVIEWED FOR\nEXTERNAL RELEASE. (LLNL-MI-835833) THESE NOTEBOOKS WILL PROVIDE THE STUDENTS\nWITH INSTRUCTIONS OF HOW TO LOAD THE DATA AND WORK WITH THE DATA, ALONG WITH\nTUTORIALS TO DO BASIC MACHINE LEARNING TASKS LIKE LOGISTIC REGRESSION AND IMAGE\nCLASSIFICATION.", + "laborHours": 0.0, + "languages": [], + "name": "2023 Data Science Challenge Notebooks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/landajuela/cardiac_challenge", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/2D-DIC_Challenge_MATLAB_Analysis_Code_v._1.0.json b/agency-indexes/DoE/2D-DIC_Challenge_MATLAB_Analysis_Code_v._1.0.json new file mode 100644 index 00000000..2b87fdbc --- /dev/null +++ b/agency-indexes/DoE/2D-DIC_Challenge_MATLAB_Analysis_Code_v._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-05-24", + "metadataLastUpdated": "2024-07-24" + }, + "description": "This code replicates the analysis completed in the published article (see reference below) for the 2D-DIC Challenge (https://sem.org/dic-challenge/), conducted under the auspices of the Society for Experimental Mechanics (SEM). The purpose of the DIC Challenge is to provide a set of vetted and standard images, which all users and developers of Digital Image Correlation (DIC) software can use -DIC Challenge results from Sample 14 and Sample 15 of the DIC-Challenge images, and computes various statistics on the data, such as the noise, bias, and spatial resolution. \n\nP.L. Reu, E. Toussaint, E. Jones, H.A. Bruck, M. Iadicola, R. Balcaen, D.Z. Turner, T. Siebert, P. Lava, M. Simonsen (2018) Exp. Mech. 58(7):1067-1099, https://doi.org/10.1007/s11340-017-0349-0.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "2D-DIC Challenge MATLAB Analysis Code v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/2-D-DIC-Challenge", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/3DBFSVBF__3D_BatFinder_Smart_Video_BioFilter_and_Multi-class_BatFinder_Smart_Video_BioFilter__[SWR-22-88].json b/agency-indexes/DoE/3DBFSVBF__3D_BatFinder_Smart_Video_BioFilter_and_Multi-class_BatFinder_Smart_Video_BioFilter__[SWR-22-88].json new file mode 100644 index 00000000..2738f5be --- /dev/null +++ b/agency-indexes/DoE/3DBFSVBF__3D_BatFinder_Smart_Video_BioFilter_and_Multi-class_BatFinder_Smart_Video_BioFilter__[SWR-22-88].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-11-03", + "metadataLastUpdated": "2023-05-05" + }, + "description": "Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source 3D computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The machine learning has been trained on 3D data and allows for automated real-time data collection, identification and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. This machine learning model is an added feature to the previous BatFinder Smart Video BioFilter and increases the accuracy of that systems classification by increasing the accuracy of identifying bats (90% accuracy) and insects (69% accuracy) to a 97% accuracy. There are two object classifier machine learning models, Binary and multi-classification. Binary object classifier labeled BatFinder_Smart_Video_BioFilter.h5 distinguishes between biological objects and non-biological objects. The main goal of this object classifier is to ignore the turbine blades while detecting biological object flying withing the rotor swept area of the turbine. Non-biological objects have a probability of 0 and biological objects have a probability of 1. Multi-classifier labeled Multiclass_BatFinder_Smart_Video_BioFilter.h5 distinguishes between bats, birds, insects and non-biological.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "3DBFSVBF (3D BatFinder Smart Video BioFilter and Multi-class BatFinder Smart Video BioFilter) [SWR-22-88]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BatFinder_Smart_Video_BioFilter", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/3DThesis__3D_THErmal_Simulation_Software_.json b/agency-indexes/DoE/3DThesis__3D_THErmal_Simulation_Software_.json new file mode 100644 index 00000000..f9b47955 --- /dev/null +++ b/agency-indexes/DoE/3DThesis__3D_THErmal_Simulation_Software_.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "radercd@ornl.gov" + }, + "date": { + "created": "2019-06-13", + "metadataLastUpdated": "2020-09-09" + }, + "description": "There is a need for a way to simulate the heat transfer conditions for the entire layer of a build (both temperature and solidification gradient and velocity). CFD models could do this but those may take months to finish a simulation. The solution is an adaptive integration scheme for a analytic, conduction-only approach for a volumetric Gaussian heat source. Because this is analytic, it also allows increased functionality as well. 3DThesis can simulate heat transfer conditions for a volumetric Gaussian heat source moving in an arbitrary path at a point in time. This allows for the calculation of discrete snapshots of the temperature field or even the final solidification gradients and velocities.", + "laborHours": 1611.2, + "languages": [ + "C++(11)", + "GCC", + "Visual C++", + "Intel" + ], + "name": "3DThesis (3D THErmal Simulation Software)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/JamieStumpORNL/3DThesis", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/3D_FNO_model_for_geological_carbon_storage.json b/agency-indexes/DoE/3D_FNO_model_for_geological_carbon_storage.json new file mode 100644 index 00000000..8ed738a4 --- /dev/null +++ b/agency-indexes/DoE/3D_FNO_model_for_geological_carbon_storage.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-08-05", + "metadataLastUpdated": "2024-08-05" + }, + "description": "The code here provides the training/testing of using Fourier Neural Operator for geological carbon storage applications", + "laborHours": 456.0, + "languages": [], + "name": "3D FNO model for geological carbon storage", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qingkaikong/3DFNO_GCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/3D_House__3DH__[SWR-22-83].json b/agency-indexes/DoE/3D_House__3DH__[SWR-22-83].json new file mode 100644 index 00000000..3281fa45 --- /dev/null +++ b/agency-indexes/DoE/3D_House__3DH__[SWR-22-83].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-02-16", + "metadataLastUpdated": "2024-02-16" + }, + "description": "The Single-Family and Manufactured Interactive 3D houses can be used as a self-guided learning tool by anyone interested in learning more about retrofit strategies of common weatherization measures. Alternatively, the tool can be used by training organizations for a more structured learning experience when paired with a learning activity or trainer-led demonstration.", + "homepageURL": "https://www.energy.gov/scep/wap/weatherization-installer-job-aids-and-single-family-interactive-3d-house", + "laborHours": 0.0, + "languages": [], + "name": "3D House (3DH) [SWR-22-83]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.energy.gov/sites/default/files/2023-09/License-and-Agreement-3D-house_9.22.23.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.energy.gov/scep/wap/weatherization-installer-job-aids-and-single-family-interactive-3d-house", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/3D_MolGNN_RL.json b/agency-indexes/DoE/3D_MolGNN_RL.json new file mode 100644 index 00000000..2500b64d --- /dev/null +++ b/agency-indexes/DoE/3D_MolGNN_RL.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "3D-MolGNNRL, couples reinforcement learning (RL) to a deep\ngenerative model based on 3D-Scaffold to generate target candidates specific to a protein pocket building up atom by\natom from the core scaffold. 3D-MolGNNRL provides an efficient way to optimize key features within a protein pocket using\na parallel graph neural network model. The agent learns to build molecules in 3D space while optimizing the binding\naffinity, potency, and synthetic accessibility of the candidates generated for the SARS-CoV-2 Main protease", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "3D_MolGNN_RL", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/3D_Torus_Routing_Engine_Module_for_OFA_OpenSM_v._1.0.json b/agency-indexes/DoE/3D_Torus_Routing_Engine_Module_for_OFA_OpenSM_v._1.0.json new file mode 100644 index 00000000..c859793a --- /dev/null +++ b/agency-indexes/DoE/3D_Torus_Routing_Engine_Module_for_OFA_OpenSM_v._1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "This OpenFabrics Alliance (OFA) OpenSM routing engine module provides credit-loop-free routing while supporting two quality of service (QoS) levels for an InfiniBand fabric with a 3D torus topology. In addition it is able to route around multiple failed fabric links or a single failed fabric switch without introducing credit loops, and without changing path Service Level (SL) values granted before the failure.This OFA OpenSM routing engine module improves the operational characteristics of a parallel computer built using an InfiniBand fabric with a 3D torus topology. By providing two QoS levels, it allows system administrators to prevent application interprocess communication and file system communication from impacting each other. By providing the capability to route traffic around failed fabric components, it enables repair of failed components without impacting jobs running on the computer system.", + "homepageURL": "http://downloads.openfabrics.org/OFED", + "laborHours": 0.0, + "name": "3D Torus Routing Engine Module for OFA OpenSM v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://downloads.openfabrics.org/OFED/README.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://downloads.openfabrics.org/OFED", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/4D_Genome_Browser.json b/agency-indexes/DoE/4D_Genome_Browser.json new file mode 100644 index 00000000..ad382499 --- /dev/null +++ b/agency-indexes/DoE/4D_Genome_Browser.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-09-20" + }, + "description": "Los Alamos National Laboratory is embarking on a project to set a new standard in genome mapping through development of unique 4D genomics capabilities. We will develop and deploy open source software tools to discover fundamental cellular functions that are hijacked by viruses to cause disease. Given LANL\u2019s breadth of expertise in genomics, high performance computing, and advanced visualization, we are uniquely positioned to build the nascent 4D genomics field to help determine the 4D spatial-temporal architecture and dynamic reconfiguration of the human genome for any application. The goal of this software project is to create a web-based interactive application, with a complete web software stack, that provides a way to browse, visualization, query and annotate curated sets of related genomic data. The software will provide an intuitive interface to this complex data, utilizing a set of custom and off-the-shelf components integrated into specific configurations of coordinated data views. To achieve this, the project will provide components, algorithms and integrated applications and will be available as an open source project that can be used by others to view related sets of data. The primary users of this platform will include institutional users at Los Alamos National Laboratory, scientists and researchers from collaborative institutions, and others interested in exploring multi-modal genomic databases.", + "laborHours": 0.0, + "languages": [], + "name": "4D Genome Browser", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/4DGB", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/9505-PNNL_wmpy_power.json b/agency-indexes/DoE/9505-PNNL_wmpy_power.json new file mode 100644 index 00000000..40fccd10 --- /dev/null +++ b/agency-indexes/DoE/9505-PNNL_wmpy_power.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-28", + "metadataLastUpdated": "2024-08-28" + }, + "description": "Hydropower simulation model that allows for changes to inflow scenarios.", + "laborHours": 988.0, + "languages": [], + "name": "9505-PNNL/wmpy_power", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/9505-PNNL/wmpy_power", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A-LEAF.json b/agency-indexes/DoE/A-LEAF.json new file mode 100644 index 00000000..1ab3dedb --- /dev/null +++ b/agency-indexes/DoE/A-LEAF.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2023-03-15" + }, + "description": "A-LEAF is an electricity market simulation framework. It includes models for short-term market operations and long-term investment planning of generation, storage, and transmission. Model formulations include least cost and two-stage market equilibrium. Simulations can be flexibly structured over one or more years, including options for periodic samples or jumping to a single future year. Years can be simulated as 365 consecutive days at hourly or 5-minute sample rates, or they can be subsampled using a representative day group selection algorithm.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "A-LEAF", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/A-general-code-for-analyzing-viral-load-in-acute-respiratory-infection.json b/agency-indexes/DoE/A-general-code-for-analyzing-viral-load-in-acute-respiratory-infection.json new file mode 100644 index 00000000..47435420 --- /dev/null +++ b/agency-indexes/DoE/A-general-code-for-analyzing-viral-load-in-acute-respiratory-infection.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Code developed to fit and analyze viral load data for acute respiratory infections such as SARS-CoV-2. The code can also implement different treatments and generate in-silicon cohorts to examine the effects of treatments.", + "laborHours": 3708.8, + "languages": [], + "name": "A-general-code-for-analyzing-viral-load-in-acute-respiratory-infection", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tinphan-LANL/A-general-code-for-analyzing-viral-load-in-acute-respiratory-infection", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A2E2G__Atmosphere_to_Electrons_to_the_Grid_platform__[SWR-23-22].json b/agency-indexes/DoE/A2E2G__Atmosphere_to_Electrons_to_the_Grid_platform__[SWR-23-22].json new file mode 100644 index 00000000..a8b8cc89 --- /dev/null +++ b/agency-indexes/DoE/A2E2G__Atmosphere_to_Electrons_to_the_Grid_platform__[SWR-23-22].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-21", + "metadataLastUpdated": "2023-08-28" + }, + "description": "A2E2G is a platform that integrates 1) forecasting tools to account for weather uncertainty, with 2) aerodynamic wind plant models to account for wake dynamics and wind plant operation, and 3) economic models to advise on operation for a wind power plant that offers grid services in addition to energy. The A2E2G platform can be used as a high-level controller for a wind plant for market participation and real-time wind plant control. \n \nThe A2E2g platform is a holistic Python tool with modules that can be run to 1) advise on market participation and 2) control and operate a wind power plant in real time. The A2E2g framework assumes two stages: the first stage is in day-ahead and the second stage is in real-time. Managing uncertainty is key in the first stage and managing variability is key in the second stage. The different components have models written and developed in the Python programming language. The code is assembled into a Python package and can be easily downloaded and installed from the A2E2g repository (https://github.com/NREL/a2e2g).", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "A2E2G (Atmosphere to Electrons to the Grid platform) [SWR-23-22]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/a2e2g", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AADL:_Anderson_Accelerated_Deep_Learning.json b/agency-indexes/DoE/AADL:_Anderson_Accelerated_Deep_Learning.json new file mode 100644 index 00000000..5c5cb0ab --- /dev/null +++ b/agency-indexes/DoE/AADL:_Anderson_Accelerated_Deep_Learning.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2021-07-23", + "metadataLastUpdated": "2021-07-23" + }, + "description": "We propose a stable, distributed approach to perform AA that accelerates the convergence rate of stochastic first-order optimizers to train neural networks.\nDifferently from previous works, we do not alter neither the scheme to perform AA nor the loss function minimized during the training. \nTo improve robustness against stagnation, we customize general guidelines that suggest to relax the frequency of AA corrections by performing AA only at the end of an entire training epoch. \nTo improve robustness of AA against the stochastic oscillations of first-order optimizers, we average the gradients computed on consecutive stochastic optimization updates. The improved regularity of the converging sequence and the reduced amplitude of stochastic oscillations across consecutive optimization steps allows AA to efficiently extrapolate an improved converging sequence, thereby overcoming limitations of existing approaches to perform AA on stochastic optimization.\n \n", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AADL: Anderson Accelerated Deep Learning", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/AADL.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AASG_Geothermal_Data_submissions_tracking_application_and_site..json b/agency-indexes/DoE/AASG_Geothermal_Data_submissions_tracking_application_and_site..json new file mode 100644 index 00000000..1477843b --- /dev/null +++ b/agency-indexes/DoE/AASG_Geothermal_Data_submissions_tracking_application_and_site..json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Django app for tracking individual state's progress in their contributions to the National Geothermal Data System.", + "laborHours": 561214.4, + "name": "AASG Geothermal Data submissions tracking application and site.", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/aasgtrack/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/aasgtrack", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AASG_State_Geothermal_Data_Repository_for_the_National_Geothermal_Data_System..json b/agency-indexes/DoE/AASG_State_Geothermal_Data_Repository_for_the_National_Geothermal_Data_System..json new file mode 100644 index 00000000..55a7080c --- /dev/null +++ b/agency-indexes/DoE/AASG_State_Geothermal_Data_Repository_for_the_National_Geothermal_Data_System..json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This Drupal metadata and documents capture and management system is a repository, used for maintenance of metadata which describe resources contributed to the AASG State Geothermal Data System. The repository also provides an archive for files that are not hosted by the agency contributing the resource. Data from all 50 state geological surveys is represented here, and is contributed in turn to the National Geothermal Data System.", + "laborHours": 6444.8, + "name": "AASG State Geothermal Data Repository for the National Geothermal Data System.", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/metadata-repository", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ABCE__Agent_Based_Capacity_Expansion_.json b/agency-indexes/DoE/ABCE__Agent_Based_Capacity_Expansion_.json new file mode 100644 index 00000000..c7f7533f --- /dev/null +++ b/agency-indexes/DoE/ABCE__Agent_Based_Capacity_Expansion_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-30" + }, + "description": "Models the generation asset investment decisions of individual utility \"agents\" in a user-specified electricity market. Agents employ limited local resources and information to evaluate projections of future market events, and determine when and how quickly they should construct new generation assets to respond to market trends and the retirement of existing system assets. ABCE is implemented in Python and Julia, and can be connected to the ANL A-LEAF electricity system optimization code; the contribution from A-LEAF is completely compartmentalized in the code's execution and will not be released as open-source at this time.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "ABCE (Agent Based Capacity Expansion)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ABSiCE__Agent-Based_Simulations_of_the_Circular_Economy__[SWR_20-113].json b/agency-indexes/DoE/ABSiCE__Agent-Based_Simulations_of_the_Circular_Economy__[SWR_20-113].json new file mode 100644 index 00000000..5b621f31 --- /dev/null +++ b/agency-indexes/DoE/ABSiCE__Agent-Based_Simulations_of_the_Circular_Economy__[SWR_20-113].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2023-05-26" + }, + "description": "By 2050, there could be as many as 10 million photovoltaic (PV) modules that have reached their end of life. The circular economy (CE) proposes to tackle waste issues by maximizing value retention in the economy but transitioning to a CE implies certain stakeholder behaviors. In this context, we propose an agent-based model (ABM) to account for social factors in CE strategies assessment of end-of-life PV modules. Four different types of agents are represented and five possible end-of-life pathways are modeled. A machine-learning metamodel is used to explore the parameter space of the ABM. Results show that excluding social factors underestimates the effect that lower recycling prices have on material circularity by 100% and highlight the limitation of the reuse strategy as, even in an ideal case, used modules only provide a third of demand in the United States. The ABM could be developed to compute the environmental impacts of end-of-life pathways.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "ABSiCE (Agent-Based Simulations of the Circular Economy) [SWR 20-113]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ABSiCE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ACC2OMP.json b/agency-indexes/DoE/ACC2OMP.json new file mode 100644 index 00000000..128c2d83 --- /dev/null +++ b/agency-indexes/DoE/ACC2OMP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-31", + "metadataLastUpdated": "2019-07-31" + }, + "description": "A source-to-source translation tool for assisting software developers in migrating from OpenACC to OpenMP 4.5", + "laborHours": 91.2, + "languages": [], + "name": "ACC2OMP", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/naromero77/ACC2OMP", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ACCERT.json b/agency-indexes/DoE/ACCERT.json new file mode 100644 index 00000000..c6eb6823 --- /dev/null +++ b/agency-indexes/DoE/ACCERT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-06-01", + "metadataLastUpdated": "2024-06-06" + }, + "description": "The main function of ACCERT (The Algorithm for the Capital Cost Estimation of Reactor Technologies) is to provide an item-by-item estimate of the cost of a facility, at present a nuclear reactor complex, primarily nuclear power stations. The core of ACCERT is the large number of algorithms that have been developed and will continue to be developed. ACCERT is also a general methodology \nfor identifying and organizing the individual items that are estimated using the ACCERT algorithms. \nACCERT also summarize status and results; to save results and pull information from previous analyses; and to provide an interactive dynamic graphical user interface for a wide range of functions and visualizations.", + "laborHours": 16340.0, + "languages": [], + "name": "ACCERT", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/accert-dev/ACCERT", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ACD_-_Anomalous_Change_Detection_software_in_python.json b/agency-indexes/DoE/ACD_-_Anomalous_Change_Detection_software_in_python.json new file mode 100644 index 00000000..2d8800a3 --- /dev/null +++ b/agency-indexes/DoE/ACD_-_Anomalous_Change_Detection_software_in_python.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "ACD is a collection of python routines for detecting anomalous changes in pairs of images. The images can be panchromatic or multispectral (even hyperspectral), and for most of the algorithms in the collection, the two images need not have the same number of spectral bands. The general idea is to distinguish anomalous changes, which are assumed to be rare, from pervasive differences, which are assumed to occur throughout large portions of the image. The anomalous changes are candidates for actual, possibly interesting, changes on the ground, while the pervasive differences might for instance be due to different illumination or calibration during the acquisition of the two images.", + "laborHours": 0.0, + "languages": [], + "name": "ACD - Anomalous Change Detection software in python", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jt-lanl/acd", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ACME_Priority_Metrics__A-PRIME_.json b/agency-indexes/DoE/ACME_Priority_Metrics__A-PRIME_.json new file mode 100644 index 00000000..f3816b7e --- /dev/null +++ b/agency-indexes/DoE/ACME_Priority_Metrics__A-PRIME_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-20", + "metadataLastUpdated": "2020-11-30" + }, + "description": "A-PRIME, is a collection of scripts designed to provide Accelerated Climate Model for Energy (ACME) model developers and analysts with a variety of analysis of the model needed to determine if the model is producing the desired results, depending on the goals of the simulation. The software is csh scripts based at the top level to enable scientist to provide the input parameters. Within the scripts, the csh scripts calls code to perform the postprocessing of the raw data analysis and create plots for visual assessment.", + "laborHours": 5107.2, + "languages": [ + "Csh; python/2.7.3; bash; ncl/6.3.0; nco/4.6.4" + ], + "name": "ACME Priority Metrics (A-PRIME)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/a-prime", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ACOMA__Formerly_LADNAC_.json b/agency-indexes/DoE/ACOMA__Formerly_LADNAC_.json new file mode 100644 index 00000000..e5ac3317 --- /dev/null +++ b/agency-indexes/DoE/ACOMA__Formerly_LADNAC_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "Software for converting data to DNA. The purpose of the software is to convert binary data file(s) into a collection of DNA oligo descriptions that can be synthesized and provide long-term data storage. The software is designed to target the unique properties of DNA synthesis and sequencing and include error correction codes that can recover the data despite the high error rates of the current DNA state of the art techniques.", + "laborHours": 0.0, + "languages": [], + "name": "ACOMA (Formerly LADNAC)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/adscodex", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ADAPT.json b/agency-indexes/DoE/ADAPT.json new file mode 100644 index 00000000..78534b93 --- /dev/null +++ b/agency-indexes/DoE/ADAPT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "Adaptive Thresholds for Feature Extraction.\n", + "laborHours": 456.0, + "languages": [], + "name": "ADAPT", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ADAPT", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ADAPT__Analysis_of_Dynamic_Accident_Progression_Trees__Revision_5710.json b/agency-indexes/DoE/ADAPT__Analysis_of_Dynamic_Accident_Progression_Trees__Revision_5710.json new file mode 100644 index 00000000..06c6bdd6 --- /dev/null +++ b/agency-indexes/DoE/ADAPT__Analysis_of_Dynamic_Accident_Progression_Trees__Revision_5710.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-12-03" + }, + "description": "The purpose of the ADAPT code is to generate Dynamic Event Trees (DET) using a user specified set of simulators. ADAPT can utilize any simulation tool which meets a minimal set of requirements. ADAPT is based on the concept of DET which uses explicit modeling of the deterministic dynamic processes that take place during a nuclear reactor plant system (or other complex system) evolution along with stochastic modeling. When DET are used to model different aspects of Probabilistic Risk Assessment (PRA), all accident progression scenarios starting from an initiating event are considered simultaneously. The DET branching occurs at user specified times and/or when an action is required by the system and/or the operator. These outcomes then decide how the dynamic system variables will evolve in time for each DET branch. Since two different outcomes at a DET branching may lead to completely different paths for system evolution, the next branching for these paths may occur not only at different times, but can be based on different branching criteria. The computational infrastructure allows for flexibility in ADAPT to link with different system simulation codes, parallel processing of the scenarios under consideration, on-line scenario management (initiation as well as termination), analysis of results, and user friendly graphical capabilities. The ADAPT system is designed for a distributed computing environment; the scheduler can track multiple concurrent branches simultaneously. The scheduler is modularized so that the DET branching strategy can be modified (e.g. biasing towards the worst case scenario/event). Independent database systems store data from the simulation tasks and the DET structure so that the event tree can be constructed and analyzed later. ADAPT is provided with a user-friendly client which can easily sort through and display the results of an experiment, precluding the need for the user to manually inspect individual simulator runs.", + "homepageURL": "http://www.sandia.gov/adapt", + "laborHours": 0.0, + "languages": [ + "Python 2", + "MySQL" + ], + "name": "ADAPT (Analysis of Dynamic Accident Progression Trees) Revision 5710", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.sandia.gov/adapt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "Revision 5710" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ADARA.json b/agency-indexes/DoE/ADARA.json new file mode 100644 index 00000000..0d2d8e88 --- /dev/null +++ b/agency-indexes/DoE/ADARA.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The ADARA software is a collection of programs which gather neutron scattering data from multiple detector banks, multiplex the data into a single stream and distribute that stream to analysis, reduction and translation utilities in real-time.", + "laborHours": 26280.8, + "name": "ADARA", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ADARA-Neutrons/adara", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ADCP_Upsample.json b/agency-indexes/DoE/ADCP_Upsample.json new file mode 100644 index 00000000..9cbfb8bb --- /dev/null +++ b/agency-indexes/DoE/ADCP_Upsample.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pcicilio@alaska.edu" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-28" + }, + "description": "This R script takes reads the csv file of stream-wise velocity data and generates a new time series of with comparable but distinct noise using the Langevin method and library. It simulates a time series measured at 1/10 the sampling rate by calculating a moving average of 10, though other sampling rates can be calculated by adjusting the moving average window.\n\nA stationary signal is calculated by taking the difference of the original signal and the moving average, then normalizing by the standard deviation of the moving average. The stationary signal is used to calculate drift and diffusion coefficients. Those coefficients are used to generate a new stationary signal.\n\nThe new stationary signal is un-normalized and added to the moving average (or new equivalent signal) to create a new up-sampled velocity time-series.", + "laborHours": 0.0, + "languages": [], + "name": "ADCP Upsample", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/acep-uaf/ADCP_Upsample", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ADIC.json b/agency-indexes/DoE/ADIC.json new file mode 100644 index 00000000..2c386551 --- /dev/null +++ b/agency-indexes/DoE/ADIC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-02", + "metadataLastUpdated": "2018-07-02" + }, + "description": "ADIC is a tool for the automatic differentiation (AD) of programs written in ANSI C. Given the source code and a user's specification of dependent and independent variables, ADIC generates an augmented C code that computes the partial derivatives of all of the specified dependent variables with respect to all of the specified independent variables in addition to the original result. ", + "homepageURL": "http://www.mcs.anl.gov/research/projects/adic", + "laborHours": 0.0, + "languages": [], + "name": "ADIC", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.mcs.anl.gov/research/projects/adic/register.htm", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.mcs.anl.gov/research/projects/adic", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ADIFOR.json b/agency-indexes/DoE/ADIFOR.json new file mode 100644 index 00000000..1589f079 --- /dev/null +++ b/agency-indexes/DoE/ADIFOR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-02", + "metadataLastUpdated": "2018-07-02" + }, + "description": "ADIFOR is a tool for the automatic differentiation of Fortran 77 programs. Given a Fortran 77 source code and a user's specification of dependent and independent variables, ADIFOR will generate an augmented derivative code that computes the partial derivatives of all of the specified dependent variables with respect to all of the specified independent variables in addition to the original result. ", + "homepageURL": "http://www.mcs.anl.gov/research/projects/adifor", + "laborHours": 0.0, + "languages": [], + "name": "ADIFOR", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.mcs.anl.gov/research/projects/adifor/AdiforGet.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.mcs.anl.gov/research/projects/adifor", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ADIOS.json b/agency-indexes/DoE/ADIOS.json new file mode 100644 index 00000000..53b4115d --- /dev/null +++ b/agency-indexes/DoE/ADIOS.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "The Adaptable IO System (ADIOS) provides a simple, flexible way for scientists to describe the data in their code that may need to be written, read, or processed outside of the running simulation. By providing an external to the code XML file describing the various elements, their types, and how you wish to process them this run, the routines in the host code (either Fortran or C) can transparently change how they process the data.\n", + "laborHours": 260193.6, + "name": "ADIOS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornladios/ADIOS", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ADIOS_Schema_reader_for_VTK.json b/agency-indexes/DoE/ADIOS_Schema_reader_for_VTK.json new file mode 100644 index 00000000..a7015f4e --- /dev/null +++ b/agency-indexes/DoE/ADIOS_Schema_reader_for_VTK.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-05-14" + }, + "description": "This is an implementation of a VTK class that can read data from an ADIOS file. Specifically, it interprets a schema embedded in the attributes of the ADIOS metadata to determine the structure of the data.", + "laborHours": 767204.8, + "languages": [], + "name": "ADIOS Schema reader for VTK", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/paraview/paraview", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ADREM.json b/agency-indexes/DoE/ADREM.json new file mode 100644 index 00000000..e34acdce --- /dev/null +++ b/agency-indexes/DoE/ADREM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-02-13", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Analytical Data Reduction Excel Macro", + "laborHours": 0.0, + "languages": [], + "name": "ADREM", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/ADREM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ADUPROP.json b/agency-indexes/DoE/ADUPROP.json new file mode 100644 index 00000000..7883e44d --- /dev/null +++ b/agency-indexes/DoE/ADUPROP.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-16", + "metadataLastUpdated": "2019-08-19" + }, + "description": "ADUPROP is a scalable implementation for uncertainty propagation using the method of moments. The Taylor coefficients for the moments first (mean) and second moment (Covariance matrix) require the efficient computation of derivatives. ADUPROP leverages the technique of Automatic Differentiation (AD) to generate the implementation of derivative computations. ADUPROP solves a differential equation x' = f(x), where f(x) is a nonlinear function and the flow phi(x) of the differential equation is obtained using the usual discretization techniques: x_k+1 = phi(x_k). The user has only to provide f(x) and its Jacobian. For a given input mean and covariance matrix ADUPROP propagates this uncertainty information according to the method of moments. ", + "laborHours": 4940.0, + "languages": [], + "name": "ADUPROP", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/aduprop/aduprop", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/AD_LTEM.json b/agency-indexes/DoE/AD_LTEM.json new file mode 100644 index 00000000..69cb0d30 --- /dev/null +++ b/agency-indexes/DoE/AD_LTEM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-23", + "metadataLastUpdated": "2021-08-24" + }, + "description": "This software uses AI tools for enhanced functional imaging using Lorentz transmission electron microscopy by retrieving phase shift at higher spatial resolution, and under noisy conditions. This is a companion code for a publication that is currently being submitted (APT # 164160).", + "laborHours": 0.0, + "languages": [], + "name": "AD_LTEM", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/danielzt12/AD_LTEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ADoSPSiQS__Automated_Detection_of_Symmetry-Protected_Subspaces_in_Quantum_Simulations___[SWR-23-55].json b/agency-indexes/DoE/ADoSPSiQS__Automated_Detection_of_Symmetry-Protected_Subspaces_in_Quantum_Simulations___[SWR-23-55].json new file mode 100644 index 00000000..96902095 --- /dev/null +++ b/agency-indexes/DoE/ADoSPSiQS__Automated_Detection_of_Symmetry-Protected_Subspaces_in_Quantum_Simulations___[SWR-23-55].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-07-18", + "metadataLastUpdated": "2024-01-19" + }, + "description": "Symmetry-protected subspaces in quantum systems are subspaces demarcated by a conserved quantity of that quantum system. We introduce two classical algorithms, which efficiently compute and elucidate features of these subspaces. The first algorithm explores the entire symmetry-protected subspace of an initial state in time complexity linear to the size of the subspace by closing local basis state-to-basis state transitions. The second algorithm determines, with bounded error, if a given measurement outcome of a dynamically-generated state is within the symmetry-protected subspace of the state in which the dynamical system is initialized. This software is paired with the paper of the same name at https://arxiv.org/pdf/2302.08586.pdf.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "ADoSPSiQS (Automated Detection of Symmetry-Protected Subspaces in Quantum Simulations ) [SWR-23-55]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SymmetryDetectionForQuantumSim", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AE3D.json b/agency-indexes/DoE/AE3D.json new file mode 100644 index 00000000..fc6e9189 --- /dev/null +++ b/agency-indexes/DoE/AE3D.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "AE3D solves for the shear Alfven eigenmodes and eigenfrequencies in a torodal magnetic fusion confinement device. The configuration can be either 2D (e.g. tokamak, reversed field pinch) or 3D (e.g. stellarator, helical reversed field pinch, tokamak with ripple). The equations solved are based on a reduced MHD model and sound wave coupling effects are not currently included.", + "laborHours": 1428.8, + "name": "AE3D", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-Fusion/AE3D", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AERCalc_v1.2.10.json b/agency-indexes/DoE/AERCalc_v1.2.10.json new file mode 100644 index 00000000..6578a46d --- /dev/null +++ b/agency-indexes/DoE/AERCalc_v1.2.10.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-08", + "metadataLastUpdated": "2019-04-29" + }, + "description": "AERCalc is a software tool for evaluating the energy performance of window attachments (e.g., shading systems, attached window panels, etc.). All the annual energy modeling is performed by the EnergyPlus OS engine. The program incorporates a user-friendly GUI.", + "laborHours": 67564.0, + "languages": [], + "name": "AERCalc v1.2.10", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/AERCalc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "1.2.10" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AESD__Advanced_Energy_System_Design__Records_API_[SWRs-17-50,_17-51,_17-52].json b/agency-indexes/DoE/AESD__Advanced_Energy_System_Design__Records_API_[SWRs-17-50,_17-51,_17-52].json new file mode 100644 index 00000000..0c6d7da5 --- /dev/null +++ b/agency-indexes/DoE/AESD__Advanced_Energy_System_Design__Records_API_[SWRs-17-50,_17-51,_17-52].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-04-18", + "metadataLastUpdated": "2024-07-01" + }, + "description": "The Records API (application program interface) for Advanced Energy System Design (AESD) enables software that serves multidimensional record-oriented data to interoperate with software than uses such data. In the context of the Records API, multidimensional data records are simply tuples of real numbers, integers, and character strings, where each data value is tagged by a variable name, according to a pre-defined schema, and each record is assigned a unique integer identifier. Conceptually, these records are isomorphic to rows in a relational database, JSON objects, or key-value maps. Records servers might supply static datasets, sensor measurements that periodically update as new telemetry become available, or the results of simulations as the simulations generate new output. Records client software might display or analyze the data, but in the case of simulations the client request the creation of new ensembles for specified input parameters. It is also possible to chain records clients and servers together so that a client consuming data from a server might transform that data and serve it to additional clients. This minimalist API avoids imposing burdensome metadata, structural, or implementation requirements on developers by relying on open-source technologies that are readily available for common programming languages. In particular, the API has been designed to place the least possible burden on services that provide data. This document defines the message format for the Records API, a transport mechanism for communicating the data, and the semantics for interpreting it. The message format is specified as Google Protocol Buffers and the transport mechanism uses WebSockets. We discuss three major use cases for serving and consuming records data: (i) static data, (ii) dynamically augmented data, (iii) on-demand simulations, (iv) with filters, and (v) with bookmarks. Separate implementations of the API exist in C++, Haskell, JavaScript, Python, and R.", + "laborHours": 0.0, + "languages": [], + "name": "AESD (Advanced Energy System Design) Records API [SWRs-17-50, 17-51, 17-52]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/AESD/blob/master/libs/Haskell/records/LICENSE", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/AESD", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AEflow__Autoencoder_fluid_flow_compression_network__[SWR-22-29].json b/agency-indexes/DoE/AEflow__Autoencoder_fluid_flow_compression_network__[SWR-22-29].json new file mode 100644 index 00000000..97ebc5d5 --- /dev/null +++ b/agency-indexes/DoE/AEflow__Autoencoder_fluid_flow_compression_network__[SWR-22-29].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2023-07-21" + }, + "description": "As the size of turbulent flow simulations continues to grow, in situ data compression is becoming increasingly important for visualization, analysis, and restart checkpointing. For these applications, single-pass compression techniques with low computational and communication overhead are crucial. In this paper we present a deep-learning approach to in situ compression using an autoencoder architecture that is customized for three-dimensional turbulent flows and is well suited for contemporary heterogeneous computing resources. The autoencoder is compared against a recently introduced randomized single-pass singular value decomposition (SVD) for three different canonical turbulent flows: decaying homogeneous isotropic turbulence, a Taylor-Green vortex, and turbulent channel flow. Our proposed fully convolutional autoencoder architecture compresses turbulent flow snapshots by a factor of 64 with a single pass, allows for arbitrarily sized input fields, is cheaper to compute than the randomized single-pass SVD for typical simulation sizes, performs well on unseen flow configurations, and has been made publicly available. The results reported here show that the autoencoder dramatically outperforms a randomized single-pass SVD with similar compression ratio and yields comparable performance to a higher-rank decomposition with an order of magnitude less compression in regard to preserving a number of important statistical quantities such as turbulent kinetic energy, enstrophy, and Reynolds stresses.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AEflow (Autoencoder fluid flow compression network) [SWR-22-29]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/AEflow", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AGILE_GETRS.json b/agency-indexes/DoE/AGILE_GETRS.json new file mode 100644 index 00000000..c5830bc9 --- /dev/null +++ b/agency-indexes/DoE/AGILE_GETRS.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "hahnse@ornl.gov" + }, + "date": { + "created": "2024-06-04", + "metadataLastUpdated": "2024-06-05" + }, + "description": "AGILE GETRS provides an optimized implementation of DETRS that is faster than vendor optimized libraries for small (< 4000) problem sizes. These small problems sizes are of interest to researchers in the Grid Research Integration and Deployment Center (GRID-C) researching real-time power electronics simulations.\n\nIn addition to our implementation of DETRS, this code provides a test using Google Benchmark which generates matrices of various sizes, fills them with random numbers, runs GETRS, verifies the solution is correct and reports average runtime and other performance metrics.", + "laborHours": 288.8, + "languages": [ + "C++" + ], + "name": "AGILE GETRS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/ldrd_intersect_agile/agile_getrs", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "v0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AGU_AMS_Abstract_Search_and_Display_Software.json b/agency-indexes/DoE/AGU_AMS_Abstract_Search_and_Display_Software.json new file mode 100644 index 00000000..7062dfe1 --- /dev/null +++ b/agency-indexes/DoE/AGU_AMS_Abstract_Search_and_Display_Software.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "devarakondar@ornl.gov" + }, + "date": { + "created": "2021-08-11", + "metadataLastUpdated": "2021-08-11" + }, + "description": "The AGU/AMS Abstract Search and Display Software is a standalone web application which enables the searching, storing, and displaying of abstracts featured at the annual American Geophysical Union (AGU) and American Meteorological Society (AMS) meetings. This application is designed for those who wish to host a standalone web application and feature a select subset of posters and talks scheduled for the AGU/AMS meetings. Please read the entirety of this README.md file before attempting to download and use the application. There are three views available via the UI: Lookup - enables searching and submitting posters for displaying on the summary view Manual Submission - allows individual manual submission of posters given a poster ID Summary - displays all posters submitted by users from the lookup view", + "laborHours": 0.0, + "languages": [], + "name": "AGU/AMS Abstract Search and Display Software", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/arm-data-science-integration/poster-api-wrapper", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/AI-BATT-OS__Autonomous_Identification_of_Battery_Life_Models_\342\200\223_Open_Source__[SWR_21-17_and_SWR_21-36].json" "b/agency-indexes/DoE/AI-BATT-OS__Autonomous_Identification_of_Battery_Life_Models_\342\200\223_Open_Source__[SWR_21-17_and_SWR_21-36].json" new file mode 100644 index 00000000..8de930d3 --- /dev/null +++ "b/agency-indexes/DoE/AI-BATT-OS__Autonomous_Identification_of_Battery_Life_Models_\342\200\223_Open_Source__[SWR_21-17_and_SWR_21-36].json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-09-15", + "metadataLastUpdated": "2023-05-26" + }, + "description": "Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by NREL. This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript \"Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning\", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nrel.gov for any questions.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "AI-BATT-OS (Autonomous Identification of Battery Life Models \u2013 Open Source) [SWR 21-17 and SWR 21-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/AI-Batt-OS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AI-multimodal_XAS-NNE.json b/agency-indexes/DoE/AI-multimodal_XAS-NNE.json new file mode 100644 index 00000000..261db786 --- /dev/null +++ b/agency-indexes/DoE/AI-multimodal_XAS-NNE.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "mcarbone@bnl.gov" + }, + "date": { + "created": "2023-01-15", + "metadataLastUpdated": "2023-01-15" + }, + "description": "Neural network ensembles for X-ray absorption spectroscopy of molecules and materials. Companion code for preprint https://arxiv.org/abs/2210.00336.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AI-multimodal/XAS-NNE", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AI-multimodal/XAS-NNE", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git", + "version": "v0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AIIO_v0.0.1.json b/agency-indexes/DoE/AIIO_v0.0.1.json new file mode 100644 index 00000000..92d8cc67 --- /dev/null +++ b/agency-indexes/DoE/AIIO_v0.0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-07", + "metadataLastUpdated": "2023-06-07" + }, + "description": "AIIO uses Artificial Intelligence for Job-Level and Automatic I/O Performance Bottleneck Diagnosis.", + "laborHours": 0.0, + "languages": [], + "name": "AIIO v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/aiio", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AIRES-NODE.json b/agency-indexes/DoE/AIRES-NODE.json new file mode 100644 index 00000000..04297ca9 --- /dev/null +++ b/agency-indexes/DoE/AIRES-NODE.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "gureckywl@ornl.gov" + }, + "date": { + "created": "2024-01-24", + "metadataLastUpdated": "2024-01-24" + }, + "description": "This software package performs time series forecasting for engineering systems using neural controlled differential equations. Neural controlled differential equations are continuous time analogues to recurrent neural networks. AIRES-NODE is particularly well suited for dynamic systems which are subject to external forcing terms and time-dependent boundary conditions. AIRES-NODE provides an encoder-decoder architecture which allows for variable-length forecasts to be made and is not limited to a fixed time step size when forecasting. Additionally, by utilizing a novel combination of a variational autoencoder and neural controlled differential equations, the AIRES-NODE package is capable of producing probabilistic future forecasts.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AIRES-NODE", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/AIRES/aires-node", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AL-ASMR:_Active_Learning_of_Atomistic_Surrogate_Models_for_Rare_Events.json b/agency-indexes/DoE/AL-ASMR:_Active_Learning_of_Atomistic_Surrogate_Models_for_Rare_Events.json new file mode 100644 index 00000000..4700778f --- /dev/null +++ b/agency-indexes/DoE/AL-ASMR:_Active_Learning_of_Atomistic_Surrogate_Models_for_Rare_Events.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "lees4@ornl.gov" + }, + "date": { + "created": "2023-08-23", + "metadataLastUpdated": "2023-08-28" + }, + "description": "Atomistic simulation with artificial intelligence (AI) is an emerging tool for understanding materials' properties and behaviors and predicting novel materials with optimized/targeted properties. Neural network potentials (NNPs) are outstanding in this field as they have shown a comparable accuracy to ab initio electronic structure calculations for reproducing potential energy surfaces while being several orders of magnitude faster. However, such NNPs can perform poorly outside of their training domain and typically fail catastrophically in the prediction of rare events in molecular dynamics (MD) simulations. For effective AL loops to distinguish the informative data from enhanced sampled configurations, we developed a decision engine by configurational similarity and uncertainty quantification (UQ) with data augmentation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AL-ASMR: Active Learning of Atomistic Surrogate Models for Rare Events", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/al-asmr/blob/master/license.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/al-asmr", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/ALFABET\342\204\242_and_nfp__Neural_Fingerprint__[SWR-19-13].json" "b/agency-indexes/DoE/ALFABET\342\204\242_and_nfp__Neural_Fingerprint__[SWR-19-13].json" new file mode 100644 index 00000000..dfb030b3 --- /dev/null +++ "b/agency-indexes/DoE/ALFABET\342\204\242_and_nfp__Neural_Fingerprint__[SWR-19-13].json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-04", + "metadataLastUpdated": "2023-11-02" + }, + "description": "Keras layers for end-to-end learning on molecular structure. Based on Keras, Tensorflow, and RDKit. Source code used in the study Message-passing neural networks for high-throughput polymer screening. SEE ALSO https://github.com/NREL/alfabet", + "laborHours": 866.4, + "languages": [ + "Python" + ], + "name": "ALFABET\u2122 and nfp (Neural Fingerprint) [SWR-19-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/nfp", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ALGEBRA_v.1.27.json b/agency-indexes/DoE/ALGEBRA_v.1.27.json new file mode 100644 index 00000000..a1faed6f --- /dev/null +++ b/agency-indexes/DoE/ALGEBRA_v.1.27.json @@ -0,0 +1,40 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The ALGEBRA program allows the user to manipulate data from a finite element analysis before it is plotted. The finite element output data is in the form of variable values (e.g., stress, strain, and velocity components) in an EXODUS II database. The ALGEBRA program evaluates user-supplied functions of the data and writes the results to an output EXODUS II database that can be read by plot programs.", + "homepageURL": "https://github.com/sandialabs/seacas", + "laborHours": 693758.4, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "ALGEBRA v.1.27", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.27" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ALS_Milo:_BL402_RSXD_data_analysis.json b/agency-indexes/DoE/ALS_Milo:_BL402_RSXD_data_analysis.json new file mode 100644 index 00000000..dc9b8414 --- /dev/null +++ b/agency-indexes/DoE/ALS_Milo:_BL402_RSXD_data_analysis.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-12", + "metadataLastUpdated": "2019-05-28" + }, + "description": "Suite of tools designed to simply data collection, extraction, reduction, and plotting for resonant soft x-ray scattering experiments performed at ALS beamline 4.0.2; speeds up the process of converting data into meaningful information for users to publish experimental results. \n\n* Python software routines for processing CCD images, including reciprocal space maps, diffraction peak alignment, resonant spectral profiles, line-cut comparisons, coordinate transforms, etc. \n* Scan file generator, optimized for typical uses cases, reduces burden on users by handling complex operations behind the scenes of a simplified user interface \n* Deployed at beamline endstation computers; packaged and deployable as standardized PyPI package \n* Under version control (git) and hosted on LBL-sponsored repository (bitbucket)", + "laborHours": 1991.2, + "languages": [], + "name": "ALS/Milo: BL402 RSXD data analysis", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/als.milo/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ALTRIOS__Advanced_Locomotive_Technology_and_Rail_Infrastructure_Optimization_System__[SWR-22-54].json b/agency-indexes/DoE/ALTRIOS__Advanced_Locomotive_Technology_and_Rail_Infrastructure_Optimization_System__[SWR-22-54].json new file mode 100644 index 00000000..a554ed83 --- /dev/null +++ b/agency-indexes/DoE/ALTRIOS__Advanced_Locomotive_Technology_and_Rail_Infrastructure_Optimization_System__[SWR-22-54].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-11-28", + "metadataLastUpdated": "2023-11-30" + }, + "description": "The Advanced Locomotive Technology and Rail Infrastructure Optimization System (ALTRIOS) is a unique, fully integrated, open-source software tool to evaluate strategies for deploying advanced locomotive technologies and associated infrastructure for cost-effective decarbonization. ALTRIOS simulates freight-demand driven train scheduling, mainline meet-pass planning, locomotive dynamics, train dynamics, energy conversion efficiencies, and energy storage dynamics of line-haul train operations. Because new locomotives represent a significant long-term capital investment and new technologies must be thoroughly demonstrated before deployment, this tool provides guidance on the risk/reward tradeoffs of different technology rollout strategies. An open, integrated simulation tool is invaluable for identifying future research needs and making decisions on technology development, routes, and train selection. ALTRIOS was developed as part of a collaborative effort by a team comprising the National Renewable Energy Laboratory (NREL), University of Illinois Urbana-Champaign (UIUC), Southwest Research Institute (SwRI), and BNSF Railway.\n\nPython Package: https://pypi.org/project/altrios/\nRust Crate: https://crates.io/crates/altrios-core", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ALTRIOS (Advanced Locomotive Technology and Rail Infrastructure Optimization System) [SWR-22-54]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ALTRIOS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "V0.1.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AMG2023.json b/agency-indexes/DoE/AMG2023.json new file mode 100644 index 00000000..53551ed1 --- /dev/null +++ b/agency-indexes/DoE/AMG2023.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-04-13", + "metadataLastUpdated": "2023-04-13" + }, + "description": "The AMG2023 benchmark solves two diffusion problems with a linear solver preconditioned with algebraic multigrid. The code only contains a driver, a Makefile, and a documentation file. It requires an installation of the open source software library hypre that needs to be downloaded elsewhere and is not included here. Its purpose is to benchmark linear solver performance on high performance computers.", + "laborHours": 0.0, + "languages": [], + "name": "AMG2023", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AMG2023", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AML.json b/agency-indexes/DoE/AML.json new file mode 100644 index 00000000..ff40d306 --- /dev/null +++ b/agency-indexes/DoE/AML.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "AML is a library to manage byte-addressable memory devices. The library is designed as a collection of building blocks, so that users can create custom\nmemory management policies for allocation and placement of data across devices.", + "laborHours": 8208.0, + "languages": [], + "name": "AML", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://xgitlab.cels.anl.gov/argo/aml", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/AMPE.json b/agency-indexes/DoE/AMPE.json new file mode 100644 index 00000000..82cc8098 --- /dev/null +++ b/agency-indexes/DoE/AMPE.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-20", + "metadataLastUpdated": "2018-03-21" + }, + "description": "AMPE is a phase-field code. It evolves in time the Allen-Cahn equations associated with a phase\u00adfield model, coupled with the time-evolution of a composition field (in an alloy) and a temperature field which are described by diffusion equations. It can also solve the elasticity equations assuming mechanical equilibrium at every time-step. Grain orientations are described by normalized quaternions which also evolve in time according to Allen-Cahn type equations. ", + "laborHours": 58976.0, + "name": "AMPE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AMPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AMPL_extensions_for_stochastic_programming.json b/agency-indexes/DoE/AMPL_extensions_for_stochastic_programming.json new file mode 100644 index 00000000..dd6b01b8 --- /dev/null +++ b/agency-indexes/DoE/AMPL_extensions_for_stochastic_programming.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "Addition of support for random variables as described in SAND2006-4717C to the AMPL language processor; See http://www.ampl.com. This was in connection with Incoming License Agreement Number 04-I00039 between Sandia National Labs and AMPL Optimization LLC. Addition of support for random variables as described in SAND2006-4717C to the AMPL language processor; See http://www.ampl.com. This was in connection with Incoming License Agreement Number 04-I00039 between Sandia National Labs and AMPL Optimization LLC.", + "homepageURL": "https://ampl.com/products/solvers/open-source", + "laborHours": 0.0, + "languages": [ + "the subet of C++ recognized by cfront" + ], + "name": "AMPL extensions for stochastic programming", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ampl.com/products/solvers/open-source", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ampl.com/products/solvers/open-source", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/AMR-Wind_[SWR-20-85].json b/agency-indexes/DoE/AMR-Wind_[SWR-20-85].json new file mode 100644 index 00000000..3e59c9dc --- /dev/null +++ b/agency-indexes/DoE/AMR-Wind_[SWR-20-85].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-06-29", + "metadataLastUpdated": "2023-05-31" + }, + "description": "AMR-Wind is a massively parallel, block-structured adaptive-mesh, incompressible flow solver for wind turbine and wind farm simulations. The solver is built on top of the AMReX library. AMReX is developed at LBNL , NREL , and ANL as part of the Block-Structured AMR Co-Design Center in DOE's Exascale Computing Project. AMReX library provides the mesh data structures, mesh adaptivity, as well as the linear solvers used for solving the governing equations. The primary applications for AMR-Wind are: performing large-eddy simulations (LES) of atmospheric boundary layer (ABL) flows, simulating wind farm turbine-wake interactions using actuator disk or actuator line models for turbines, and as a background solver when coupled with a near-body solver with overset methodology to perform blade-resolved simulations of multiple wind turbines within a wind farm.", + "laborHours": 57182.4, + "languages": [ + "CMake", + "C++", + "Python" + ], + "name": "AMR-Wind [SWR-20-85]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exawind/amr-wind", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AMReX.json b/agency-indexes/DoE/AMReX.json new file mode 100644 index 00000000..b7c6801d --- /dev/null +++ b/agency-indexes/DoE/AMReX.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "asalmgren@lbl.gov" + }, + "date": { + "created": "2021-04-14", + "metadataLastUpdated": "2021-04-14" + }, + "description": "AMReX is a software framework for the development and implementation of massively parallel algorithms using block-structured adaptive mesh refinement (AMR). Block-structured AMR provides the basis for the temporal and spatial discretization strategy for a large variety of applications of interest to the DOE. AMReX provides a unified infrastructure with the functionality needed for applications to be able to effectively and efficiently utilize machines from laptops to exascale accelerator-based architectures. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving accurate descriptions of different physical processes in complex multi-physics algorithms. AMReX supports algorithms that solve systems of partial differential equations (PDEs) in simple or complex geometries, and those that use particles and/or particle-mesh operations to represent component physical processes.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "AMReX", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Codes/amrex", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AMReX_v2024.json b/agency-indexes/DoE/AMReX_v2024.json new file mode 100644 index 00000000..9bc9fd22 --- /dev/null +++ b/agency-indexes/DoE/AMReX_v2024.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The software framework, AMReX, supports the development of block-structured adaptive mesh refinement (AMR) algorithms for solving systems of partial differential equations. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving the essential local descriptions of different physical processes in complex multiphysics algorithms. AMR uses a hierarchical representation of the solution at multiple levels of resolution where the solution on each level is defined on the union of data containers at that resolution. These data containers, which represent the solution over a logically rectangular subregion of the domain, can contain field data defined on a mesh, Lagrangian particles or combinations of both. In addition to these basic data types, AMReX supports a multilevel embedded boundary representation of complex geometry; linear solvers for cell-centered and nodal data; asynchronous I/O in a native format readable by ParaView, VisIt and yt; and interfaces to hypre and PETSc solvers. AMReX enables applications to run on distributed memory architectures with multicore CPUs and with GPU accelerators. AMReX uses a lightweight abstraction layer that effectively hides the details of the architecture from the application. The framework currently supports CUDA, HIP and SYCL for GPU acceleration and OpenMP for multi-core CPU architectures.", + "laborHours": 0.0, + "languages": [], + "name": "AMReX v2024", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Codes/amrex", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AMXML_to_CLI_converter.json b/agency-indexes/DoE/AMXML_to_CLI_converter.json new file mode 100644 index 00000000..b27e8848 --- /dev/null +++ b/agency-indexes/DoE/AMXML_to_CLI_converter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-07-19", + "metadataLastUpdated": "2021-07-19" + }, + "description": "This script converts files from the XML format to the CLI format.", + "laborHours": 0.0, + "languages": [], + "name": "AMXML to CLI converter", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CLDruzgalski/AM_fileConverters", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AMXML_to_CLI_multi-segment_polyline_converter_and_plotter.json b/agency-indexes/DoE/AMXML_to_CLI_multi-segment_polyline_converter_and_plotter.json new file mode 100644 index 00000000..6e84065c --- /dev/null +++ b/agency-indexes/DoE/AMXML_to_CLI_multi-segment_polyline_converter_and_plotter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "Converts XML file formats to CLI format for 3D printing; combines equivalent polyline segments (laser power, velocity, focus/spot-size) into a single polyline for a given path. Also plots CLI file format with respect to power for a single specified layer, or the entire file, for 3D printed applications.", + "laborHours": 0.0, + "languages": [], + "name": "AMXML to CLI multi-segment polyline converter and plotter", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CLDruzgalski/AM_fileConverters", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ANDES__ARGONNE_NUCLEAR_DATA_EXPLORATION_SOFTWARE__-_Physics_Tools.json b/agency-indexes/DoE/ANDES__ARGONNE_NUCLEAR_DATA_EXPLORATION_SOFTWARE__-_Physics_Tools.json new file mode 100644 index 00000000..76f59413 --- /dev/null +++ b/agency-indexes/DoE/ANDES__ARGONNE_NUCLEAR_DATA_EXPLORATION_SOFTWARE__-_Physics_Tools.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-05-19", + "metadataLastUpdated": "2022-05-19" + }, + "description": "A collection of physics tools used by the ANDES. The Argonne Nuclear Data Exploration Software (ANDES) is a collection of open-source C++ codes and ROOT scripts that enable the visualization of patterns emerging from nuclear data. From this global view, well-known phenomena such as major nuclear shell closures and pairing effects near N=Z nuclei, as well as more subtle features, such as quantum phase transition around the Zr isotopes or the charge radius staggering in the Hg isotopes, can be observed. This visualization tool apart from having pedagogic application can serve as a tool for discovering previously unknown phenomena in the nuclear chart.", + "laborHours": 0.0, + "languages": [], + "name": "ANDES (ARGONNE NUCLEAR DATA EXPLORATION SOFTWARE) - Physics Tools", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.phy.anl.gov/andes/physics-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ANDES__ARGONNE_NUCLEAR_DATA_EXPLORATION_SOFTWARE__-_ndviz.json b/agency-indexes/DoE/ANDES__ARGONNE_NUCLEAR_DATA_EXPLORATION_SOFTWARE__-_ndviz.json new file mode 100644 index 00000000..52fc79e1 --- /dev/null +++ b/agency-indexes/DoE/ANDES__ARGONNE_NUCLEAR_DATA_EXPLORATION_SOFTWARE__-_ndviz.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-09-12", + "metadataLastUpdated": "2022-05-19" + }, + "description": "The Argonne Nuclear Data Exploration Software (ANDES) is a collection of open-source C++ codes and ROOT scripts that enable the visualization of patterns emerging from nuclear data. From this global view, well-known phenomena such as major nuclear shell closures and pairing effects near N=Z nuclei, as well as more subtle features, such as quantum phase transition around the Zr isotopes or the charge radius staggering in the Hg isotopes, can be observed. This visualization tool apart from having pedagogic application can serve as a tool for discovering previously unknown phenomena in the nuclear chart.", + "laborHours": 0.0, + "languages": [], + "name": "ANDES (ARGONNE NUCLEAR DATA EXPLORATION SOFTWARE) - ndviz", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.phy.anl.gov/andes/ndviz", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ANTFARM.json b/agency-indexes/DoE/ANTFARM.json new file mode 100644 index 00000000..620c1de5 --- /dev/null +++ b/agency-indexes/DoE/ANTFARM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-01-17", + "metadataLastUpdated": "2024-01-31" + }, + "description": "Passively maps IP networks using data generated by other network monitoring tools as well as using network device configuration files. Organizes network data, such as names, device types, device addresses, traffic data, etc. in a database for analysis and extraction into a network visualization tool.", + "laborHours": 0.0, + "languages": [], + "name": "ANTFARM", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ccss-sandia/antfarm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/APBS__Adaptive_Poisson-Boltzmann_Solver__and_PDB2PQR.json b/agency-indexes/DoE/APBS__Adaptive_Poisson-Boltzmann_Solver__and_PDB2PQR.json new file mode 100644 index 00000000..09ceec5b --- /dev/null +++ b/agency-indexes/DoE/APBS__Adaptive_Poisson-Boltzmann_Solver__and_PDB2PQR.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Electrostatics software under development since 1999. Soee http://www.poissonboltzmann.org/ for more detail.", + "laborHours": 262975.2, + "name": "APBS (Adaptive Poisson-Boltzmann Solver) and PDB2PQR", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electrostatics/apbs-pdb2pqr", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/API_Umbrella_[SWR-12-16].json b/agency-indexes/DoE/API_Umbrella_[SWR-12-16].json new file mode 100644 index 00000000..e27faeb3 --- /dev/null +++ b/agency-indexes/DoE/API_Umbrella_[SWR-12-16].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2023-05-31" + }, + "description": "API Umbrella is an open source API management platform for exposing web service APIs. The basic goal of API Umbrella is to make life easier for both API creators and API consumers. Binary packages are available for download. Follow the quick setup instructions on the download page to begin running API Umbrella.", + "laborHours": 61088.8, + "languages": [ + "Lua", + "Ruby", + "JavaScript" + ], + "name": "API Umbrella [SWR-12-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/api-umbrella", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.15.1 / 2019-05-14" +} \ No newline at end of file diff --git a/agency-indexes/DoE/APPRENTICE.json b/agency-indexes/DoE/APPRENTICE.json new file mode 100644 index 00000000..0f0582bb --- /dev/null +++ b/agency-indexes/DoE/APPRENTICE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-03-30", + "metadataLastUpdated": "2021-03-30" + }, + "description": "SF-19-096 In this software, there are multiple approaches to compute approximations to multivariate functions. This includes: (a) an approach that builds on Stieltjes process to efficiently compute the coefficients of the rational approximation, (b) an approach that is based on an optimization formulation to get pole-free coefficients of the rational approximation and (c) approaches that finds the coefficients of rational and polynomial approximations by finding the linear \nleast-squares solution using singular value decomposition.\n\n", + "laborHours": 0.0, + "languages": [], + "name": "APPRENTICE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HEPonHPC/apprentice", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/APPROD:_An_App_to_Prod_Values_in_Deterministic_Models.json b/agency-indexes/DoE/APPROD:_An_App_to_Prod_Values_in_Deterministic_Models.json new file mode 100644 index 00000000..d7a0ec3c --- /dev/null +++ b/agency-indexes/DoE/APPROD:_An_App_to_Prod_Values_in_Deterministic_Models.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-04-14", + "metadataLastUpdated": "2021-04-14" + }, + "description": "The software takes any deterministic simulation code (non-specific) and modifies identified variables in the input-deck for the simulation code before launching a \"run\" of the code. This process is repeated N times and is useful for Probabilistic Risk Assessment studies as well as any other study requiring many parametric changes to variables in a deterministic code.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "APPROD: An App to Prod Values in Deterministic Models", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/Argonne-National-Laboratory/APPROD/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/APPROD", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ARES_v1.x_-_Performance_Portable_Tool_to_Simulate_Supernovae_based_on_Parthenon_Framework.json b/agency-indexes/DoE/ARES_v1.x_-_Performance_Portable_Tool_to_Simulate_Supernovae_based_on_Parthenon_Framework.json new file mode 100644 index 00000000..22b89f60 --- /dev/null +++ b/agency-indexes/DoE/ARES_v1.x_-_Performance_Portable_Tool_to_Simulate_Supernovae_based_on_Parthenon_Framework.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "Historically, codes for simulating supernovae (such as Arepo, FLASH or LEAFS) have been at the forefront of scientific high-performance computing to the immense computational resources required for full 3D simulations. However, given the shift towards heterogenous HPC architectures, many current-generation codes are at the risk of losing their competitiveness as they are only designed to run on homogeneous CPU-only systems. There exist several efforts to enable these codes for GPU\u2019s, however, these efforts only consider specific architectures or vendors (e.g., implement only CUDA or HIP), limiting themselves to a small range of exascale computing systems.\nFrameworks such as Kokkos aim to provide a framework which is agnostic of the targeted architecture, enabling the development of performant and portable code.\nIn the Ares code, we develop a performance portable tool to simulate supernovae based on the Parthenon Framework, which in turn uses Kokkos in the background. Here, the Parthenon Framework provides an interface to the underlying mesh-refinement routines, which form the backbone of our code. In addition, we incorporate the already existing Singularity-EOS toolkit to provide us with various equations of state, primarily the Helmholtz equation of state. We also include the JINA Reaclib as a basis for our nuclear network solver. Finally, we implement a gravity solver to complete the required physics.\nThis setup will provide us with a minimal code base to simulate supernova in a similar style to the tried-and-tested Arepo code, but in a futureproof performance portable framework.", + "laborHours": 0.0, + "languages": [], + "name": "ARES v1.x - Performance Portable Tool to Simulate Supernovae based on Parthenon Framework", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/AresPK", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ARGONNE_DISCOVERY_CLOUD_SDK&CLI.json b/agency-indexes/DoE/ARGONNE_DISCOVERY_CLOUD_SDK&CLI.json new file mode 100644 index 00000000..390fa342 --- /dev/null +++ b/agency-indexes/DoE/ARGONNE_DISCOVERY_CLOUD_SDK&CLI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-29", + "metadataLastUpdated": "2021-09-29" + }, + "description": "Software development kit and command-line interface to access and interact with the Argonne Discovery Cloud platform. Software code can be used to enable software developers to add their own integrates into their own software.", + "laborHours": 0.0, + "languages": [], + "name": "ARGONNE DISCOVERY CLOUD SDK&CLI", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AD-SDL/adc-rdm-sdk", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ARKode,_v1.0.json b/agency-indexes/DoE/ARKode,_v1.0.json new file mode 100644 index 00000000..6bcadf5f --- /dev/null +++ b/agency-indexes/DoE/ARKode,_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-10-08" + }, + "description": "ARKode is part of a software family called SUNDIALS: SUite of Nonlinear and Differential/ALgebraic equation Solvers [1]. The ARKode solver library provides an adaptive-step time integration package for stiff, nonstiff and multi-rate systems of ordinary differential equations (ODEs) using Runge Kutta methods [2].", + "homepageURL": "https://computation.llnl.gov/projects/sundials", + "laborHours": 103025.6, + "languages": [], + "name": "ARKode, v1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://computation.llnl.gov/projects/sundials", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ARM-DOE_adi-vap-pblhtsonde.json b/agency-indexes/DoE/ARM-DOE_adi-vap-pblhtsonde.json new file mode 100644 index 00000000..caf63fec --- /dev/null +++ b/agency-indexes/DoE/ARM-DOE_adi-vap-pblhtsonde.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-03-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Atmospheric Radiation Measurement Program developed a value added product that could run autonomously to\ndetermine planetary boundary height using radiosondes. This product has produced data for 117 unique sites and\nfacilities for more than 10 years. The initial software was released around 2013 and data has been produced since 2001 for\nsome sites.", + "laborHours": 0.0, + "languages": [], + "name": "ARM-DOE/adi-vap-pblhtsonde", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/adi-vap-pblhtsonde", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ARM-Development_qc_aod.json b/agency-indexes/DoE/ARM-Development_qc_aod.json new file mode 100644 index 00000000..5fa54e20 --- /dev/null +++ b/agency-indexes/DoE/ARM-Development_qc_aod.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-08-19", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Repository for the QCAOD VAP", + "laborHours": 395.2, + "languages": [], + "name": "ARM-Development/qc_aod", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-Development/qc_aod", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ARMO.json b/agency-indexes/DoE/ARMO.json new file mode 100644 index 00000000..fa2773d2 --- /dev/null +++ b/agency-indexes/DoE/ARMO.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "ARMO is a software tool for solving Alignment and Registration problems via Mathematical Optimization.\nGiven different 3D point clouds of overlapping areas, the tool can fix alignment issues by finding the optimal rotation and translation operations.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "ARMO", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ARM_Data_Integrator.json b/agency-indexes/DoE/ARM_Data_Integrator.json new file mode 100644 index 00000000..7be28e0d --- /dev/null +++ b/agency-indexes/DoE/ARM_Data_Integrator.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Atmospheric Radiation Measurement (ARM) Data Integrator (ADI) streamlines the development of scientific algorithms and analysis of time-series NetCDF data, and improves the content and consistency of the output data products produced by these algorithms. The framework automates the process of retrieving and preparing data for analysis, and allows users to design output data products through a graphical interface. It also provides a modular, flexible software development architecture that scientists can use to generate C, Python, and IDL source code templates that embed the pre and post processing logic allowing the scientist to focus on only their science. The input data, preprocessing, and output data specifications of algorithms are defined through a graphical interface and stored in a database. ADI implements workflow for data integration and supports user access to data through a library of software modules. Data preprocess capabilities supported include automated retrieval of data from input files, merging the retrieved data into appropriately sized chunks, and transformation of the data onto a common coordinate system grid. Through the graphical interface, users can view the details of both their data products and those in the ARM catalog and allows developers to use existing data product to build new data products. Views of the output data products include an overlay of how the design meets ARM archive's data standards providing the user with a visual cue indicating where their output violates an archive standard. The ADI libraries access the information provided through the GUI via a Postgres database. The ADI framework and its supporting components can significantly decrease the time and cost of implementing scientific algorithms while improving the ability of scientists to disseminate their results.", + "laborHours": 76.0, + "name": "ARM Data Integrator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ARM-DOE/ADI/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/ADI", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ART_Front_End_v1.json b/agency-indexes/DoE/ART_Front_End_v1.json new file mode 100644 index 00000000..f92e4356 --- /dev/null +++ b/agency-indexes/DoE/ART_Front_End_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-01", + "metadataLastUpdated": "2021-07-01" + }, + "description": "Enhances accessibility of the Automated Recommendation Tool (ART), by adding on a graphical user interface, user authentication, and by exposing a REST API. Enables authenticated remote users and applications to interface with ART and to leverage remote computing resources to perform runs.", + "homepageURL": "https://sites.google.com/lbl.gov/art/home", + "laborHours": 0.0, + "languages": [], + "name": "ART Front End v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/art/licensing-code", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/art/home", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ASAUM--Adaptive_Structured_and_Unstructured_Mesh.json b/agency-indexes/DoE/ASAUM--Adaptive_Structured_and_Unstructured_Mesh.json new file mode 100644 index 00000000..31e35a8b --- /dev/null +++ b/agency-indexes/DoE/ASAUM--Adaptive_Structured_and_Unstructured_Mesh.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "ASAUM is a C++ library for representing distributed, multi-block structed and unstructured meshes. The library is meant to provide users with the ability to read/write, partition, and query the large distributed meshes that are commonly used in scientific computing.", + "laborHours": 14926.4, + "languages": [], + "name": "ASAUM--Adaptive Structured and Unstructured Mesh", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ASAUM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ASCEM_Data_Brower__ASCEMDB__v0.8.json b/agency-indexes/DoE/ASCEM_Data_Brower__ASCEMDB__v0.8.json new file mode 100644 index 00000000..25d8b27f --- /dev/null +++ b/agency-indexes/DoE/ASCEM_Data_Brower__ASCEMDB__v0.8.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Data management tool designed for the Advanced Simulation Capability for Environmental Management (ASCEM) framework. Distinguishing features of this gateway include: (1) handling of complex geometry data, (2) advance selection mechanism, (3) state of art rendering of spatiotemporal data records, and (4) seamless integration with a distributed workflow engine.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "ASCEM Data Brower (ASCEMDB) v0.8", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ASCENDS:_Advanced_Data_SCiENce_Toolkit_for_Non-Data_Scientists.json b/agency-indexes/DoE/ASCENDS:_Advanced_Data_SCiENce_Toolkit_for_Non-Data_Scientists.json new file mode 100644 index 00000000..e4987a93 --- /dev/null +++ b/agency-indexes/DoE/ASCENDS:_Advanced_Data_SCiENce_Toolkit_for_Non-Data_Scientists.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "Data science capabilities are becoming important more and more. Even though there exist many data science and machine learning tools, they are not intuitive for many traditional scientists who are not familiar with programming. ASCENDS provides easy and intuitive interfaces (command-line interface, graphical user interface) to users so they can use data science capabilities without having to understand programming language. ASCENDS performs data visualization, machine learning model training, storing and prediction (regression problem), automatic hyperparameter tuning, and supports various machine learning models including random forest, kernel ridge, nearest neighbor, neural network, etc. Users can use standard CSV (comma separated values) format data set and investigate the feature columns that are highly correlated to a target column; further, they can learn ML models, then store and use them for predictions. The tool is supposed to be generically applicable so that it can be used for many different applications.", + "laborHours": 101414.4, + "languages": [ + "Python 3.7" + ], + "name": "ASCENDS: Advanced Data SCiENce Toolkit for Non-Data Scientists", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornlpmcp/ASCENDS", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ASC_Blanket_Disclosure_4.json b/agency-indexes/DoE/ASC_Blanket_Disclosure_4.json new file mode 100644 index 00000000..fe59c299 --- /dev/null +++ b/agency-indexes/DoE/ASC_Blanket_Disclosure_4.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "Software developed by ASC personnel and that includes physics which aims to understand astrophysics-only applications. \n\nThis provides a list of concrete code types allowed within this Blanket, but here I offer more detail about what each of those types entail.\n- Galactic Chemical Evolution: Uses prescriptions to define the synthesis of heavy elements from various astrophysical objects (stars, supernovae, novae, big bang), and then represents the rate at which these astrophysical objects occur within our galaxy. The convolution of the rate of incidence with the material released by each instance gives a prediction for the chemical evolution of the galaxy.\n- Stellar Population Synthesis: Uses prescriptions for the rate of occurrence of various properties or events in the life of a star (its initial mass, whether it has a binary companion, its binary distance separation, etc) to model what happens to the stars as they evolve. Gives a sense of what a population of stars should look like statistically speaking. Useful for predicting, for example, how many binary stars will merge in our galaxy in the next 1 million years, or how many supernovae do we expect to see with current telescopes.\n- Hydrostatic equilibrium, time-implicit, stellar evolution codes: Uses equilibrium equations to show how the structure of a star must change throughout its life. Assumes that gravity is equally balanced by stellar pressure at all times. Includes nucleosynthesis network for calculating energy generation from nuclear burning in the star. This energy generation holds the star up against the gravitational forces trying to collapse the star. Hydrodynamic timescales are not resolved, only hydrostatic is considered. \n- Astrophysical nuclear / astrophysical chemical network codes: Solves a system of rate equations that describe the network of elements involved in nuclear or chemical evolution for astrophysical events (e.g. supernovae, stars, big bang, protostars, interstellar medium). These codes are designed for use in post-process, which means that the density and temperature conditions in a fluid element are defined versus time and fed into these codes. Then, these codes report back how the nuclear or chemical makeup of the fluid element would evolve based on those conditions. There is no feedback from the energy released by that evolution on the fluid element\u2019s conditions.\n-Astrophysical orbital dynamics codes: Calculates the orbits of a set of point masses according to the laws of gravity (e.g. planetary systems, solar system asteroids, extra-solar planet orbits\u2026).", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "ASC Blanket Disclosure 4", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ASC_Blanket_Disclosure_5.json b/agency-indexes/DoE/ASC_Blanket_Disclosure_5.json new file mode 100644 index 00000000..38076b51 --- /dev/null +++ b/agency-indexes/DoE/ASC_Blanket_Disclosure_5.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "Codes developed by ASC supported personnel for generating semi-analytic solutions to traditional verification test problems. \n\nConcrete example is a script written to do a numerical integral of an analytic function that serves as a known solution to a complex differential equation. This is very useful when checking if your general purpose physics code can produce the solution you expect when it starts from a set of known initial conditions. If the form of the integral is complex, the only way to evaluate the integral is to write a code that performs the integration numerically.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "ASC Blanket Disclosure 5", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ASP__Adaptive_Splines_for_Prediction__[SWR-22-66].json b/agency-indexes/DoE/ASP__Adaptive_Splines_for_Prediction__[SWR-22-66].json new file mode 100644 index 00000000..1072fe27 --- /dev/null +++ b/agency-indexes/DoE/ASP__Adaptive_Splines_for_Prediction__[SWR-22-66].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-09-02", + "metadataLastUpdated": "2023-03-29" + }, + "description": "This software package provides functionality to fit piecewise cubic splines to model the relationship between a univariate X (independent variable) and a univariate Y (dependent variable). The output is akin to linear regression but has higher \"capacity\" in that it can learn more complicated relationships despite leveraging only a single predictor. It thus can learn very reasonable relationships between X and Y with minimal effort. The canonical intended use case is for predicting electric demand (Y) from temperature (X). There can be complicated, non-linear relationships between these two variables, but these can be reasonably approximated by the sum of: 1) an \"aggregate\" relationship between daily average temperature and daily average demand, and 2) intra-day patterns represented as hourly offsets from the daily average load. The spline functionality is used for learning a robust \"aggregate\" relationship without the inconvenience of manual feature engineering while still ensuring robust results. The model fitting workhorse is R's built-in smooth.spline. This package provides a suite of options for controlling how smooth.spline fits a spline to the data. In particular, it is designed to return a model with a single critical point (i.e., a single location along the domain/support where the first derivative is zero). This is to ensure that predicted changes in electric demand are always positive as temperatures become more extreme. This helps to prevent overfitting, particularly when the input data has few observations or has significant uncertainty from other sources.", + "laborHours": 0.0, + "languages": [], + "name": "ASP (Adaptive Splines for Prediction) [SWR-22-66]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/adaptive-splines", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ATB-calc__Annual_Technology_Baseline_Calculators__[SWR-23-60].json b/agency-indexes/DoE/ATB-calc__Annual_Technology_Baseline_Calculators__[SWR-23-60].json new file mode 100644 index 00000000..56f59d0f --- /dev/null +++ b/agency-indexes/DoE/ATB-calc__Annual_Technology_Baseline_Calculators__[SWR-23-60].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-08-15", + "metadataLastUpdated": "2023-09-14" + }, + "description": "This software is a suite of Python files and Jupyter notebooks supporting the calculation of cost and financial parameters for the Annual Technology Baseline (ATB) electricity data, including capital expenditures, levelized cost of energy, and debt fractions using the ATB input data.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "ATB-calc (Annual Technology Baseline Calculators) [SWR-23-60]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ATB-calc", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ATCCfinder_-_Download_and_Search_the_ATCC_Genome_Portal.json b/agency-indexes/DoE/ATCCfinder_-_Download_and_Search_the_ATCC_Genome_Portal.json new file mode 100644 index 00000000..44b649ea --- /dev/null +++ b/agency-indexes/DoE/ATCCfinder_-_Download_and_Search_the_ATCC_Genome_Portal.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "Much strain-specific sequence data exists in research conducted before the deployment of large sequencing repositories, making it challenging to identify and validate the identity of strains used in these studies through bioinformatics and phenotyping. The American Type Culture Collection (ATCC) is an organization that sells a wide variety of microbes with strain-level taxonomy classification and associated sequenced reference genomes. Currently, ATCC does not provide a method for searching for sequence similarity between a query sequence and their database of reference genomes. Here I propose the software ATCCfinder, which utilizes ATCC application interface software (API) to generate query-able databases from ATCC Genome resources.", + "laborHours": 349.6, + "languages": [], + "name": "ATCCfinder - Download and Search the ATCC Genome Portal", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ATCCfinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ATIS.json b/agency-indexes/DoE/ATIS.json new file mode 100644 index 00000000..9ad14eb1 --- /dev/null +++ b/agency-indexes/DoE/ATIS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2022-11-30", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Any Threat Intelligence to STIX (ATIS) autogenerates and enriches STIX bundles with data from open source threat intelligence sources.", + "laborHours": 0.0, + "languages": [], + "name": "ATIS", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/ATIS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ATMOSPHERIC_DATA_COMMUNITY_TOOLKIT__ACT_.json b/agency-indexes/DoE/ATMOSPHERIC_DATA_COMMUNITY_TOOLKIT__ACT_.json new file mode 100644 index 00000000..4ddf1fb7 --- /dev/null +++ b/agency-indexes/DoE/ATMOSPHERIC_DATA_COMMUNITY_TOOLKIT__ACT_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2019-07-29" + }, + "description": "The scientific community performs a lot of redundant work when working with data. Researches tend to write their own code to perform basic functions for reading, visualizing, and analyzing the data. This strategy is unnecessarily time consuming, and potentially costly, for the individual researcher (as well as for programs). Open-source software disrupts that process and moves the development effort toward capabilities that can be used by the broader scientific community. The broader scientific community can then, in turn, contribute to and collaborate on efforts to improve the process for the individual researcher and program. Researchers will be able to do more science with fewer resources without the burden of developing code from the ground up. For any software to be adopted by a community, it needs to have a solid framework that will be easy to use and provide clear benefit worthy of the investment in participating. In support of this goal, our Atmospheric Data Community Toolkit will leverage the knowledge gained from the successful adoption of the Python Atmospheric Radiation Measurement User Facility Radar Toolkit (Py-ART) to build that framework. The framework will provide the environment to enable collaboration in the research community. This environment will allow the development of tools for funded programs, as well as provide researchers in the scientific community with code for advancing their work. Research programs will also be able to adopt code provided by the scientific community without having to develop it from scratch. The final goal of this proposed effort is to have a framework on GitHub that has the basic features that the atmospheric research community needs to begin working with and adopting, including, but not limited to, reading and visualization. We expect future effort will be needed for Argonne scientists to demonstrate their specific capabilities within this framework. This project will provide an avenue for other proposed research to be demonstrated, such as the Global Oceans/Argonne proposed Atmospheric Instrumentation Suite; edge computing National Science Foundation proposed effort; and the Computing, Environment, and Life Sciences Directorate's strategic effort on the Southern Great Plains climate observation site relating to water across the surface interface. ", + "laborHours": 3784.8, + "languages": [], + "name": "ATMOSPHERIC DATA COMMUNITY TOOLKIT (ACT)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-DIGR/ACT", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ATom__Acoustic_Tomography_Processing_Suite__[SWR-24-120].json b/agency-indexes/DoE/ATom__Acoustic_Tomography_Processing_Suite__[SWR-24-120].json new file mode 100644 index 00000000..55f6cd9a --- /dev/null +++ b/agency-indexes/DoE/ATom__Acoustic_Tomography_Processing_Suite__[SWR-24-120].json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-24", + "metadataLastUpdated": "2025-01-08" + }, + "description": "Acoustic tomography seeks the best-fit fluctuating velocity and temperature fields that explain a collection of signal travel times in a region of interest. This codebase defines an end-to-end framework for executing turbulent field retrievals from acoustic signals, acoustic signal design and processing tools for the physical array, and analysis tool that leverage virtual acoustic tomography arrays based on large-eddy simulations of the atmospheric boundary layer.", + "laborHours": 22739.2, + "languages": [ + "CSS", + "HTML", + "TeX", + "JavaScript", + "Python" + ], + "name": "ATom (Acoustic Tomography Processing Suite) [SWR-24-120]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ATom", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AUTONOMOUS_INTELLIGENCE_CYBERDEFENSE_AGENT__AICA_.json b/agency-indexes/DoE/AUTONOMOUS_INTELLIGENCE_CYBERDEFENSE_AGENT__AICA_.json new file mode 100644 index 00000000..b8e3a73e --- /dev/null +++ b/agency-indexes/DoE/AUTONOMOUS_INTELLIGENCE_CYBERDEFENSE_AGENT__AICA_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "This is a prototype framework initially developed as part of an international consortium (aica-iwg.org/) for NATO ACT in 2021 under an LGPL license (Blakely/ANL did 100% of the coding). It is intended to serve as a reference model and collaborative project for researchers interested in working on self-defending software agents. It consists of a set of Docker containers that allow simulation of a network environment, including a manager agent that has capabilities for observing network activities, using automated decision making to select appropriate defensive/proactive actions, and putting those actions into practice. It is currently at an \"MVP\" level but we are continuing to add to this and have submitted a DHS S&T CAP proposal to build an open source community around it.", + "laborHours": 0.0, + "languages": [], + "name": "AUTONOMOUS INTELLIGENCE CYBERDEFENSE AGENT (AICA)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aica-iwg/aica-agent", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AUTOPERF.json b/agency-indexes/DoE/AUTOPERF.json new file mode 100644 index 00000000..96c14670 --- /dev/null +++ b/agency-indexes/DoE/AUTOPERF.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-19", + "metadataLastUpdated": "2021-08-19" + }, + "description": "AutoPerf is a collection of modules for low-overhead performance monitoring on HPC systems, the modules collect monitoring data such as MPI data, network counter data etc. Autoperf modules interoperate with the Open source Darshan software (xgitlab.cels.anl.gov/darshan/) as submodules and leverages the Darshan's log recording and analysis framework.", + "laborHours": 0.0, + "languages": [], + "name": "AUTOPERF", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/argonne-lcf/autoperf", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AUTOPHASENN:_UNSUPERVISED_PHYSICS-AWARE_DEEP_LEARNING_FOR_PHASE_RETRIEVAL.json b/agency-indexes/DoE/AUTOPHASENN:_UNSUPERVISED_PHYSICS-AWARE_DEEP_LEARNING_FOR_PHASE_RETRIEVAL.json new file mode 100644 index 00000000..a6f00350 --- /dev/null +++ b/agency-indexes/DoE/AUTOPHASENN:_UNSUPERVISED_PHYSICS-AWARE_DEEP_LEARNING_FOR_PHASE_RETRIEVAL.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-05" + }, + "description": "AutoPhaseNN is a deep learning (DL) based approach for solving the phase problem. By combining the 3D convolutional neural network (CNN) with the physics of the imaging technique, AutoPhaseNN is trained to learn the inversion from the measured intensity to the amplitude and phase images without labeled data. Once trained, AutoPhaseNN is ~100X faster than conventional iterative phase retrieval methods,", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "AUTOPHASENN: UNSUPERVISED PHYSICS-AWARE DEEP LEARNING FOR PHASE RETRIEVAL", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/AWE-ML:_Averaged_Weights_for_Explainable_Machine_Learning_v._1.0.json b/agency-indexes/DoE/AWE-ML:_Averaged_Weights_for_Explainable_Machine_Learning_v._1.0.json new file mode 100644 index 00000000..464f9c36 --- /dev/null +++ b/agency-indexes/DoE/AWE-ML:_Averaged_Weights_for_Explainable_Machine_Learning_v._1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2019-03-13" + }, + "description": "This software uses averaged weighted estimators to classify instances and then explicate the individual decision process in classification. The software has state of the art performance in accuracy, while maintaining full explainability. It does this by calculating hierarchically averaged probabilities for a large class of feature combinations and updating them \u2018on-the-fly\u2019. On the fly updating also allows the model to be accurate, relative to the total dataset, maintaining accuracy in real-time, without a need to retrain the classifier. ", + "laborHours": 31768.0, + "languages": [ + "C++", + "Python" + ], + "name": "AWE-ML: Averaged Weights for Explainable Machine Learning v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/aweml", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AWE.json b/agency-indexes/DoE/AWE.json new file mode 100644 index 00000000..37c25a41 --- /dev/null +++ b/agency-indexes/DoE/AWE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "Workflow and resource management system for bioinformatics data analysis.", + "laborHours": 11521.6, + "languages": [], + "name": "AWE", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/AWE", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_3D_approximate_maximum_likelihood_localization_solver.json b/agency-indexes/DoE/A_3D_approximate_maximum_likelihood_localization_solver.json new file mode 100644 index 00000000..2b98d2cb --- /dev/null +++ b/agency-indexes/DoE/A_3D_approximate_maximum_likelihood_localization_solver.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "A robust three-dimensional solver was needed to accurately and efficiently estimate the time sequence of locations of fish tagged with acoustic transmitters and vocalizing marine mammals to describe in sufficient detail the information needed to assess the function of dam-passage design alternatives and support Marine Renewable Energy. An approximate maximum likelihood solver was developed using measurements of time difference of arrival from all hydrophones in receiving arrays on which a transmission was detected. Field experiments demonstrated that the developed solver performed significantly better in tracking efficiency and accuracy than other solvers described in the literature.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "A 3D approximate maximum likelihood localization solver", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Closed-Loop_Proportional-Integral__PI__Control_Software_for_Fully_Mechanically_Controlled_Automated_Electron_Microscopic_Tomography.json b/agency-indexes/DoE/A_Closed-Loop_Proportional-Integral__PI__Control_Software_for_Fully_Mechanically_Controlled_Automated_Electron_Microscopic_Tomography.json new file mode 100644 index 00000000..8cee16a0 --- /dev/null +++ b/agency-indexes/DoE/A_Closed-Loop_Proportional-Integral__PI__Control_Software_for_Fully_Mechanically_Controlled_Automated_Electron_Microscopic_Tomography.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "A closed-loop proportional-integral (PI) control software is provided for fully mechanically controlled automated electron microscopic tomography. The software is developed based on Gatan DigitalMicrograph, and is compatible with Zeiss LIBRA 120 transmission electron microscope. However, it can be expanded to other TEM instrument with modification. The software consists of a graphical user interface, a digital PI controller, an image analyzing unit, and other drive units (i.e.: image acquire unit and goniometer drive unit). During a tomography data collection process, the image analyzing unit analyzes both the accumulated shift and defocus value of the latest acquired image, and provides the results to the digital PI controller. The digital PI control compares the results with the preset values and determines the optimum adjustments of the goniometer. The goniometer drive unit adjusts the spatial position of the specimen according to the instructions given by the digital PI controller for the next tilt angle and image acquisition. The goniometer drive unit achieves high precision positioning by using a backlash elimination method. The major benefits of the software are: 1) the goniometer drive unit keeps pre-aligned/optimized beam conditions unchanged and achieves position tracking solely through mechanical control; 2) the image analyzing unit relies on only historical data and therefore does not require additional images/exposures; 3) the PI controller enables the system to dynamically track the imaging target with extremely low system error.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "A Closed-Loop Proportional-Integral (PI) Control Software for Fully Mechanically Controlled Automated Electron Microscopic Tomography", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Data-Driven_Approach_for_High-Impedance_Fault_Localization_in_Distribution_Systems_[SWR-24-13].json b/agency-indexes/DoE/A_Data-Driven_Approach_for_High-Impedance_Fault_Localization_in_Distribution_Systems_[SWR-24-13].json new file mode 100644 index 00000000..b8a0fdee --- /dev/null +++ b/agency-indexes/DoE/A_Data-Driven_Approach_for_High-Impedance_Fault_Localization_in_Distribution_Systems_[SWR-24-13].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-26", + "metadataLastUpdated": "2024-04-26" + }, + "description": "This software provides a data-driven approach for efficiently identifying high impedance faults (HIFs) in distribution systems. To tackle the nonlinearity of the voltage current trajectory of HIFs, we first formulate linear least squares problems to approximate the trajectory with piecewise functions. Then we collect the function features of all segments as inputs and use the support vector machine approach to efficiently identify HIFs at different locations.", + "laborHours": 60.8, + "languages": [ + "Python" + ], + "name": "A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems [SWR-24-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openEDI/oedisi-hif-identification", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Distributed,_Parallel_Visualization_and_Analysis_Tool.json b/agency-indexes/DoE/A_Distributed,_Parallel_Visualization_and_Analysis_Tool.json new file mode 100644 index 00000000..85235193 --- /dev/null +++ b/agency-indexes/DoE/A_Distributed,_Parallel_Visualization_and_Analysis_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "VisIt is an interactive parallel visualization and graphical analysis tool for viewing scientific date on UNIX and PC platforms. Users can quickly generate visualizations from their data, animate them through time, manipulate them, and save the resulting images for presentations. VisIt contains a rich set of visualization features so that you can view your data in a variety of ways. It can be used to visualize scalar and vector fields defined on two- and three- dimensional (2D and 3D) structured and unstructured meshes. VisIt was designed to handle very large data set sizes in the terascale range and yet can also handle small data sets in the kilobyte range.", + "homepageURL": "https://visit.llnl.gov", + "laborHours": 1937164.0, + "languages": [], + "name": "A Distributed, Parallel Visualization and Analysis Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://wci.llnl.gov/simulation/computer-codes/visit/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://visit.llnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Domain_indEpendent_sequence_alignment_strategy_for_gPu_archiTectures__ADEPT__v1.0.json b/agency-indexes/DoE/A_Domain_indEpendent_sequence_alignment_strategy_for_gPu_archiTectures__ADEPT__v1.0.json new file mode 100644 index 00000000..499f8c35 --- /dev/null +++ b/agency-indexes/DoE/A_Domain_indEpendent_sequence_alignment_strategy_for_gPu_archiTectures__ADEPT__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-23", + "metadataLastUpdated": "2021-07-22" + }, + "description": "GPU-BSW is a version of Smith-Waterman alignment algorithm which has been optimized to perform large number of sequence alignments on GPUs.", + "laborHours": 851.2, + "languages": [], + "name": "A Domain indEpendent sequence alignment strategy for gPu archiTectures (ADEPT) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/m-gul/GPU-BSW", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Framework_for_the_Analysis_of_Compiler_Optimizations.json b/agency-indexes/DoE/A_Framework_for_the_Analysis_of_Compiler_Optimizations.json new file mode 100644 index 00000000..fbce0147 --- /dev/null +++ b/agency-indexes/DoE/A_Framework_for_the_Analysis_of_Compiler_Optimizations.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-10-21", + "metadataLastUpdated": "2020-10-21" + }, + "description": "Compilers transform program source code to machine executable code. During this transformation, they perform a number of compiler optimizations to improve the performance of the generated executable\ncode. Importantly, applying those optimizations depends on the source code structure, such as the parallel programming model used to\nparallelize an algorithm. Often, implementations of the same algorithm with different programming models have vastly different performance because the compiler optimized them differently. We create FAROS, a framework to structure and automate the analysis of compiler optimizations on programs. FAROS automates the building process, execution profiling, and analysis of compiler optimization of programs, through a configuration interface. It outputs compiler optimization reports to show which\noptimizations applied to which line of source code, leveraging compilation remarks output by the compiler. Also, FAROS supports\nbenchmarking performance of different program versions by collecting execution time results. In this first release of FAROS, we provide a configuration file to analyze compiler optimization differences for sequential vs OpenMP compilation, including 38 programs consisting of HPC proxy/mini/large applications, and NAS and Rodina kernels for analysis. ", + "laborHours": 1976.0, + "languages": [], + "name": "A Framework for the Analysis of Compiler Optimizations", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FAROS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Framework_to_Support_Generator_Ramping_Uncertainty_Analysis_and_Visualization.json b/agency-indexes/DoE/A_Framework_to_Support_Generator_Ramping_Uncertainty_Analysis_and_Visualization.json new file mode 100644 index 00000000..b96b5960 --- /dev/null +++ b/agency-indexes/DoE/A_Framework_to_Support_Generator_Ramping_Uncertainty_Analysis_and_Visualization.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Power system operation requires maintaining a continuous balance between system demand and generation within certain constraints. Traditionally, the balancing processes are based on deterministic models, which do not consider possible random deviations of system generation and load from their predicted values. With the increasing penetration of the renewable generation, unexpected balancing problems can happen due to the deviations. This can result in serious risks to system reliability and efficiency. When the available balancing reserve is not enough to cover the predicted net load range with uncertainty, deficiency of balancing needs occurs. In this case, it is necessary to commit or de-commit additional conventional generators to achieve the desired confidence level for the balancing needs. The framework is built for solving this problem. The ramping tool engine is used to predict additional balancing requirements caused by the variability and uncertainty of the renewable energy, under the constraints of the generation ramping capability and interchange schedule. The web browser- based GUI is used to visualize the data in web-environment, which provides flexibility to allow user to see the ramping outputs in any platform. The GOSS structure provides strong support to allow easy communication between ramping engine, and system inputs, as well as the GUI.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java 8.x" + ], + "name": "A Framework to Support Generator Ramping Uncertainty Analysis and Visualization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Grand_Canonical_Monte_Carlo_simulation_program_for_computing_ion_distributions_around_biomolecules_in_hard_sphere_solvents.json b/agency-indexes/DoE/A_Grand_Canonical_Monte_Carlo_simulation_program_for_computing_ion_distributions_around_biomolecules_in_hard_sphere_solvents.json new file mode 100644 index 00000000..f9bc4e06 --- /dev/null +++ b/agency-indexes/DoE/A_Grand_Canonical_Monte_Carlo_simulation_program_for_computing_ion_distributions_around_biomolecules_in_hard_sphere_solvents.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The GIBS software program is a Grand Canonical Monte Carlo (GCMC) simulation program (written in C++) that can be used for 1) computing the excess chemical potential of ions and the mean activity coefficients of salts in homogeneous electrolyte solutions; and, 2) for computing the distribution of ions around fixed macromolecules such as, nucleic acids and proteins. The solvent can be represented as neutral hard spheres or as a dielectric continuum. The ions are represented as charged hard spheres that can interact via Coulomb, hard-sphere, or Lennard-Jones potentials. In addition to hard-sphere repulsions, the ions can also be made to interact with the solvent hard spheres via short-ranged attractive square-well potentials.", + "laborHours": 3906.4, + "name": "A Grand Canonical Monte Carlo simulation program for computing ion distributions around biomolecules in hard sphere solvents", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/30876-615-os", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electrostatics/GIBS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Hybrid_Demand_Response_Simulator_Version_1.0.json b/agency-indexes/DoE/A_Hybrid_Demand_Response_Simulator_Version_1.0.json new file mode 100644 index 00000000..27911ce1 --- /dev/null +++ b/agency-indexes/DoE/A_Hybrid_Demand_Response_Simulator_Version_1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "A hybrid demand response simulator is developed to test different control algorithms for centralized and distributed demand response (DR) programs in a small distribution power grid. The HDRS is designed to model a wide variety of DR services such as peak having, load shifting, arbitrage, spinning reserves, load following, regulation, emergency load shedding, etc. The HDRS does not model the dynamic behaviors of the loads, rather, it simulates the load scheduling and dispatch process. The load models include TCAs (water heaters, air conditioners, refrigerators, freezers, etc) and non-TCAs (lighting, washer, dishwasher, etc.) The ambient temperature changes, thermal resistance, capacitance, and the unit control logics can be modeled for TCA loads. The use patterns of the non-TCA can be modeled by probability of use and probabilistic durations. Some of the communication network characteristics, such as delays and errors, can also be modeled. Most importantly, because the simulator is modular and greatly simplified the thermal models for TCA loads, it is very easy and fast to be used to test and validate different control algorithms in a simulated environment.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab/Simlink" + ], + "name": "A Hybrid Demand Response Simulator Version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Landing_Pad_System_for_Multicopy_Gene_Integration_in_Issatchenkia_orientalis.json b/agency-indexes/DoE/A_Landing_Pad_System_for_Multicopy_Gene_Integration_in_Issatchenkia_orientalis.json new file mode 100644 index 00000000..8ed1ab9d --- /dev/null +++ b/agency-indexes/DoE/A_Landing_Pad_System_for_Multicopy_Gene_Integration_in_Issatchenkia_orientalis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "lensor@illinois.edu" + }, + "date": { + "created": "2024-10-29", + "metadataLastUpdated": "2024-10-29" + }, + "description": "The robust nature of the non-conventional yeast Issatchenkia orientalis allows it to grow under highly acidic conditions and therefore, has gained increasing interest in producing organic acids using a variety of carbon sources. Recently, the development of a genetic toolbox for I. orientalis, including an episomal plasmid, characterization of multiple promoters and terminators, and CRISPR-Cas9 tools, has eased the metabolic engineering efforts in I. orientalis. However, multiplex engineering is still hampered by the lack of efficient multicopy integration tools. To facilitate the construction of large, complex metabolic pathways by multiplex CRISPR-Cas9-mediated genome editing, we developed a bioinformatics pipeline to identify and prioritize genome-wide intergenic loci and characterized 47 gRNAs located in 21 intergenic regions. These loci are screened for guide RNA cutting efficiency, integration efficiency of a gene cassette, the resulting cellular fitness, and GFP expression level. We further developed a landing pad system using components from these well-characterized loci, which can aid in the integration of multiple genes using single guide RNA and multiple repair templates of the user\u2019s choice. We have demonstrated the use of the landing pad for simultaneous integrations of 2, 3, 4, or 5 genes to the target loci with efficiencies greater than 80%. As a proof of concept, we showed how the production of 5-aminolevulinic acid can be improved by integrating five copies of genes at multiple sites in one step. We have further demonstrated the efficiency of this tool by constructing a metabolic pathway for succinic acid production by integrating five gene expression cassettes using a single guide RNA along with five different repair templates, leading to the production of 9 g/L of succinic acid in batch fermentations. This study demonstrates the effectiveness of a single gRNA-mediated CRISPR platform to build complex metabolic pathways in a non-conventional yeast. This landing pad system will be a valuable tool for the metabolic engineering of I. orientalis.", + "laborHours": 197.6, + "languages": [], + "name": "A Landing Pad System for Multicopy Gene Integration in Issatchenkia orientalis", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Zhao-Group/Landing-pad-model", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Latency_Tolerant_Runtime_System_for_Mass_Market_Computer_Systems.json b/agency-indexes/DoE/A_Latency_Tolerant_Runtime_System_for_Mass_Market_Computer_Systems.json new file mode 100644 index 00000000..9f909d89 --- /dev/null +++ b/agency-indexes/DoE/A_Latency_Tolerant_Runtime_System_for_Mass_Market_Computer_Systems.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Grappa is a latency tolerant runtime system for mass market computer systems comprised of multiple nodes having x86 multicore processors and infiniband interconnect. Grappa is designed to enable in-memory irregular applications written in the C++ programming language to scale up on multiprocessor systems. Grappa addresses the load balance, communication, and synchronization challenges posed by running applications that do not partition evenly across large systems. Two mechanisms are essential to its success: fast task switching and message aggregation. Fast task switching enables processors to tolerate communication and synchronization delays; aggregation sustains high bandwidth on low injection rate networks.", + "laborHours": 120764.0, + "name": "A Latency Tolerant Runtime System for Mass Market Computer Systems", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/uwsampa/grappa", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Modular,_Standards-based_Digital_Object_Repository.json b/agency-indexes/DoE/A_Modular,_Standards-based_Digital_Object_Repository.json new file mode 100644 index 00000000..db9aeac1 --- /dev/null +++ b/agency-indexes/DoE/A_Modular,_Standards-based_Digital_Object_Repository.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-24", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The aDORe repository architecture, designed and implemented for ingesting, storing, and accessing a vast collection of Digital Objects. aDORe was originally created for use at the Research Library of the Los Alamos National Laboratory. The aDORe architecture is highly modular and standards-based. In the architecture, the MPEG-21 Digital Item Declaration Language is used as the XML-based format to represent Digital Objects that can consist of multiple datastreams as Open Archival Information System Archival Information Packages (OAIS AIPs).", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "Java/1.5" + ], + "name": "A Modular, Standards-based Digital Object Repository", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Parallel_Batch-Dynamic_Data_Structure_for_the_Closest_Pair_Problem.json b/agency-indexes/DoE/A_Parallel_Batch-Dynamic_Data_Structure_for_the_Closest_Pair_Problem.json new file mode 100644 index 00000000..b80f72d0 --- /dev/null +++ b/agency-indexes/DoE/A_Parallel_Batch-Dynamic_Data_Structure_for_the_Closest_Pair_Problem.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nYiqiu Wang, Shangdi Yu, Yan Gu, and Julian Shun.\nA Parallel Batch-Dynamic Data Structure for the Closest Pair Problem.\nProceedings of the International Symposium on Computational Geometry (SoCG), pp. 60:1-60:16, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "A Parallel Batch-Dynamic Data Structure for the Closest Pair Problem", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wangyiqiu/closest-pair", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Polyhedral_Outer-approximation,_Dynamic-discretization_optimization_solver,_1.x.json b/agency-indexes/DoE/A_Polyhedral_Outer-approximation,_Dynamic-discretization_optimization_solver,_1.x.json new file mode 100644 index 00000000..3fe446ea --- /dev/null +++ b/agency-indexes/DoE/A_Polyhedral_Outer-approximation,_Dynamic-discretization_optimization_solver,_1.x.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "In this software, we implement an adaptive, multivariate partitioning algorithm for solving mixed-integer nonlinear programs (MINLP) to global optimality. The algorithm combines ideas that exploit the structure of convex relaxations to MINLPs and bound tightening procedures", + "laborHours": 16279.2, + "languages": [ + "Julia, C++" + ], + "name": "A Polyhedral Outer-approximation, Dynamic-discretization optimization solver, 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl-ansi/Alpine.jl/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/Alpine.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Python_Module_for_Storing_CCD_Images_with_openPMD__openPMD-CCD__v0.1.0.json b/agency-indexes/DoE/A_Python_Module_for_Storing_CCD_Images_with_openPMD__openPMD-CCD__v0.1.0.json new file mode 100644 index 00000000..c9a556c8 --- /dev/null +++ b/agency-indexes/DoE/A_Python_Module_for_Storing_CCD_Images_with_openPMD__openPMD-CCD__v0.1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-01", + "metadataLastUpdated": "2021-03-01" + }, + "description": "openPMD is an open meta-data schema that provides meaning and self-description to data sets in science and engineering. The openPMD-CCD software module adds interfaces to organize camera (CCD) images in hierarchical data files.\n\nThis software provides modern I/O storage formats from high-performance computing and provides bindings for integration into experimental control systems, e.g. via Python 3 and LabView 2020.", + "laborHours": 0.0, + "languages": [], + "name": "A Python Module for Storing CCD Images with openPMD (openPMD-CCD) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openPMD/openPMD-CCD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_Tool_for_Interactive_Protein_Manipulation.json b/agency-indexes/DoE/A_Tool_for_Interactive_Protein_Manipulation.json new file mode 100644 index 00000000..bd2c053d --- /dev/null +++ b/agency-indexes/DoE/A_Tool_for_Interactive_Protein_Manipulation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "ProteinShop is a graphical environment that facilitates a solution to the protein prediction problem through a combination of unique features and capabilities. These include: 1. Helping researchers automatically generate 3D protein structures from scratch by using the sequence of amino acids and secondary structure specifications as input. 2. Enabling users to apply their accumulated biochemical knowledge and intuition during the interactive manipulation of structures. 3. Facilitating interactive comparison and analysis of alternative structures through visualization of free energy computed during modeling. 4. Accelerating discovery of low-energy configurations by applying local optimizations plug-in to user-selected protein structures. ProteinShop v.2.0 includes the following new features: - Visualizes multiple-domain structures - Automatically creates a user-specified number of beta-sheet configurations - Provides the interface and the libraries for energy visualization and local minimization of protein structures - Reads standard POB files without previous editing.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "A Tool for Interactive Protein Manipulation", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_cascading_failure_analysis_tool_for_post_processing_TRANSCARE_simulations.json b/agency-indexes/DoE/A_cascading_failure_analysis_tool_for_post_processing_TRANSCARE_simulations.json new file mode 100644 index 00000000..23ee3e95 --- /dev/null +++ b/agency-indexes/DoE/A_cascading_failure_analysis_tool_for_post_processing_TRANSCARE_simulations.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "This is a MATLAB-based tool to post process simulation results in the EPRI software TRANSCARE, for massive cascading failure analysis following severe disturbances. There are a few key modules available in this tool, including: 1. automatically creating a contingency list to run TRANSCARE simulations, including substation outages above a certain kV threshold, N-k (1, 2 or 3) generator outages and branch outages; 2. read in and analyze a CKO file of PCG definition, an initiating event list, and a CDN file; 3. post process all the simulation results saved in a CDN file and perform critical event corridor analysis; 4. provide a summary of TRANSCARE simulations; 5. Identify the most frequently occurring event corridors in the system; and 6. Rank the contingencies using a user defined security index to quantify consequences in terms of total load loss, total number of cascades, etc.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab" + ], + "name": "A cascading failure analysis tool for post processing TRANSCARE simulations", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_memory-driven_mapping_algorithm_for_heterogeneous_systems.json b/agency-indexes/DoE/A_memory-driven_mapping_algorithm_for_heterogeneous_systems.json new file mode 100644 index 00000000..40240ed9 --- /dev/null +++ b/agency-indexes/DoE/A_memory-driven_mapping_algorithm_for_heterogeneous_systems.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-27" + }, + "description": "mpibind is a memory-driven algorithm to map parallel hybrid applications to the underlying hardware\nresources transparently, efficiently, and portably. There are two fundamental aspects of this algorithm.\nFirst, unlike existing mappings, its primary design point is the memory system. Compute elements are\nselected based on the identified memory components and not vice versa. Second, it embodies a global\nawareness of hybrid programming abstractions as well as heterogeneous devices.", + "laborHours": 23590.4, + "languages": [], + "name": "A memory-driven mapping algorithm for heterogeneous systems", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mpibind", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_python_package_for_analyzing_Resilience_of_Complex_Systems__pyRoCS__v.0.0.json b/agency-indexes/DoE/A_python_package_for_analyzing_Resilience_of_Complex_Systems__pyRoCS__v.0.0.json new file mode 100644 index 00000000..19c376a8 --- /dev/null +++ b/agency-indexes/DoE/A_python_package_for_analyzing_Resilience_of_Complex_Systems__pyRoCS__v.0.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-28", + "metadataLastUpdated": "2024-03-28" + }, + "description": "SAND2024-01040O\nPyRoCS software synthesizes mathematical equations from several domains\u2014including information theory, ecology, and engineering sciences\u2014to support resilience analysis for complex systems. Resilience is the ability of the complex system being analyzed to withstand, operate through, and recover from a disruption. The complex system can be a physical system such as an electric grid, an organization such as a company, or even a subfunction of an organization. \n\nExisting mathematical equations for resilience analysis are found within multiple domains including information theory, biological sciences, and complex systems. This package synthesizes and refactors equations from these various domains to make them more generalizable for application across different types of complex systems relevant for resilience analysis. Users will be able to apply these equations to characterize different components of complex systems based on available data. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "A python package for analyzing Resilience of Complex Systems (pyRoCS) v.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyrocs", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_real-time_path_rating_calculation_tool_powered_by_HPC.json b/agency-indexes/DoE/A_real-time_path_rating_calculation_tool_powered_by_HPC.json new file mode 100644 index 00000000..f8b7d5aa --- /dev/null +++ b/agency-indexes/DoE/A_real-time_path_rating_calculation_tool_powered_by_HPC.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "If transmission path ratings are determined in real time and optimized control methods can be implemented, congestion problems can be more effectively managed using the existing transmission assets, reducing congestion costs, avoiding capital expenditures for new physical assets, increasing revenues from the existing system, and maintaining reliability. In just one illustrative case, a BPA study has shown that a 1000-MW rating increase for a transmission path generates $15M in annual revenue, even if only 25% of the increased margin can be tapped for just 25% of the year.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "multi" + ], + "name": "A real-time path rating calculation tool powered by HPC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_set_of_test_problems_for_nonlinear_optimization.json b/agency-indexes/DoE/A_set_of_test_problems_for_nonlinear_optimization.json new file mode 100644 index 00000000..c32b6c81 --- /dev/null +++ b/agency-indexes/DoE/A_set_of_test_problems_for_nonlinear_optimization.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "The software is a set of test problems for nonlinear optimization algorithms, including subroutines such as linear algebra routines and automatic differentiation algorithms. The test problems come from chemical engineering open literature, and describe optimization tasks related to the design and operation of processes such as carbon capture, Hydrogen production, heat exchange, and distillation.", + "laborHours": 167.2, + "languages": [], + "name": "A set of test problems for nonlinear optimization", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Robbybp/pselib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/A_simple_model_for_jet_quenching_in_Heavy_Ion_Physics.json b/agency-indexes/DoE/A_simple_model_for_jet_quenching_in_Heavy_Ion_Physics.json new file mode 100644 index 00000000..d2c9f21c --- /dev/null +++ b/agency-indexes/DoE/A_simple_model_for_jet_quenching_in_Heavy_Ion_Physics.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "This is a simple python code to calculate jet quenching for nuclear modification factors in relativistic\nheavy-ion collisions. This code can be used to generate all results specified in RR0010127, to be\nsubmitted to Physical Review C.", + "laborHours": 1124.8, + "languages": [], + "name": "A simple model for jet quenching in Heavy Ion Physics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ez-Quench", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Absolute_efficiency_calculations_in_Geant4_and_MCNP6_for_a_simple_geometry.json b/agency-indexes/DoE/Absolute_efficiency_calculations_in_Geant4_and_MCNP6_for_a_simple_geometry.json new file mode 100644 index 00000000..9c567f7a --- /dev/null +++ b/agency-indexes/DoE/Absolute_efficiency_calculations_in_Geant4_and_MCNP6_for_a_simple_geometry.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This project calculates the absolute detection efficiency, defined as the ratio of particles emitted by a source to particles detected using the Geant4 and MCNP radiation transport codes.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Absolute efficiency calculations in Geant4 and MCNP6 for a simple geometry", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/AbstractHandle.json b/agency-indexes/DoE/AbstractHandle.json new file mode 100644 index 00000000..ed454f94 --- /dev/null +++ b/agency-indexes/DoE/AbstractHandle.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-13", + "metadataLastUpdated": "2020-08-13" + }, + "description": "This service provides interface to grant information and set ACLs for a node from shock service. It also provides interface to write typed object Handle to a persistnent store (MongoDB) that can be later retrieved.", + "laborHours": 1869.6, + "languages": [], + "name": "AbstractHandle", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/handle_service2", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Accelerating_Serial_Code_for_GPUs.json b/agency-indexes/DoE/Accelerating_Serial_Code_for_GPUs.json new file mode 100644 index 00000000..fdd942ba --- /dev/null +++ b/agency-indexes/DoE/Accelerating_Serial_Code_for_GPUs.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "This tutorial will show how to parallelize a simple Monte Carlo operation using a GPU accelerator.\n", + "laborHours": 91.2, + "name": "Accelerating Serial Code for GPUs", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/Accelerating-Serial-Code", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Access_Capabilities_Through_Ccs_Communications_Protocol__acccs_.json b/agency-indexes/DoE/Access_Capabilities_Through_Ccs_Communications_Protocol__acccs_.json new file mode 100644 index 00000000..a6c438b6 --- /dev/null +++ b/agency-indexes/DoE/Access_Capabilities_Through_Ccs_Communications_Protocol__acccs_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2024-01-15", + "metadataLastUpdated": "2024-01-15" + }, + "description": "AcCCS is a collection of scripts that leverage open-source code, off-the-shelf hardware, and published protocol specifications to create a flexible and inexpensive test and evaluation device for the Electric Vehicle industry. AcCCS is capable of emulating either an Electric Vehicle (EV) or Electric Vehicle Supply Equipment (EVSE). It provides a flexible set of Python scripts to test and evaluate the various communication protocols between the Electric Vehicle Communication Controller (EVCC) and Supply Equipment Communication Controller (SECC). This capability is useful for cybersecurity researchers, automotive OEMs, and EVSE manufactures.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Access Capabilities Through Ccs Communications Protocol (acccs)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/AcCCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Acoustic_Codes_in_2D_Spherical_Coordinate.json b/agency-indexes/DoE/Acoustic_Codes_in_2D_Spherical_Coordinate.json new file mode 100644 index 00000000..5a7f5364 --- /dev/null +++ b/agency-indexes/DoE/Acoustic_Codes_in_2D_Spherical_Coordinate.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-09-25", + "metadataLastUpdated": "2023-09-28" + }, + "description": "Finite-difference methods are widely used to simulate infrasound propagation in the atmosphere.\nFlexibility of finite-difference scheme allows implementation of highly heterogeneous media for sound\npropagation as well as complex source models for sound generation. While full 3-D finite-difference\nmethods have been utilized for local infrasound propagation with pronounced topography, 2-D modeling\napproach has been preferred for regional and global propagation as full 3-D methods generally require\nenormous computational resources. Infrasound propagation is often simulated with a second-order finite difference\nscheme. This lowest-order finite-difference scheme is robust and straightforward to implement\ncomplex boundary conditions, but the solution includes large error with numerical dispersion and\ndissipation. This large numerical error may make the second-order finite-difference not optimal for long range\ninfrasound propagation modeling as the numerical dispersion degrades the accuracy of the solution\nunacceptably. Here, we developed a high-order finite-difference solver for long-range infrasound\nsimulation. The high-order scheme is particularly popular for linear wave modeling in aeroacoustics\nowing to its low-dispersive and low-dissipative behavior. We develop and evaluate a high-order finite difference\nscheme in 2-D axisymmetric coordinates. The axisymmetry allows to approximate 3-D\nspherical sound propagation and amplitude attenuation by a 2-D method. AC2Dr is developed to simulate\ninfrasound propagation in realistic atmosphere, but can be used for linear acoustic waves in general\nmaterials with background flow. AC2Dr in an axisymmetric coordinates allows for spherical radiation of\nacoustic waves from compact sources.", + "laborHours": 0.0, + "languages": [], + "name": "Acoustic Codes in 2D Spherical Coordinate", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AC2Dr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Acoustic_Inspection_Device_V1.0.json b/agency-indexes/DoE/Acoustic_Inspection_Device_V1.0.json new file mode 100644 index 00000000..89730a7d --- /dev/null +++ b/agency-indexes/DoE/Acoustic_Inspection_Device_V1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Acoustic Inspection Device (AID) is an instrument used to interrogate materials with ultrasonic acoustic waves. The AID application software program runs under the Microsoft Windows 98 or Windows 2000 operating system. Is serves as the instrument controller and provides the user interface for the instrument known as the Acoustic Inspection Device (AID). The program requests, acquires, and analyzes acoustic waveforms from the AID hardware (pulser/receiver module, digitizer, and communications link). Graphical user displays of the AID application program include the real-time display of ultrasonic acoustic waveforms and analytical results including acoustic time-of-flight, velocity, and material identification. This program utilizes a novel algorithm, developed at PNNL, that automatically extracts the time-of-flight and amplitude data from the raw waveform and compares the extracted data to a material database.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Acoustic Inspection Device V1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Acro__A_Common_Repository_for_Optimizers__v._2.0.json b/agency-indexes/DoE/Acro__A_Common_Repository_for_Optimizers__v._2.0.json new file mode 100644 index 00000000..dc818259 --- /dev/null +++ b/agency-indexes/DoE/Acro__A_Common_Repository_for_Optimizers__v._2.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Acro provides a software infrastructure that integrates a variety of optimization software libraries, as well as general-purpose libraries like UTILIB that support the development of parallel optimizers.", + "homepageURL": "https://software.sandia.gov/trac/acro", + "laborHours": 0.0, + "name": "Acro (A Common Repository for Optimizers) v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://software.sandia.gov/trac/acro", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Active_Harmony.json b/agency-indexes/DoE/Active_Harmony.json new file mode 100644 index 00000000..feaedfc9 --- /dev/null +++ b/agency-indexes/DoE/Active_Harmony.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-02", + "metadataLastUpdated": "2018-07-02" + }, + "description": "Active Harmony provides software architecture that supports distributed execution of computational objects, and allows applications to be tuned with minimal changes to the application and library source code. It can be used to improve the performance of an application during execution taking into account observed performance. ", + "laborHours": 13619.2, + "languages": [], + "name": "Active Harmony", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ActiveHarmony/harmony", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Active_Learning_Framework.json b/agency-indexes/DoE/Active_Learning_Framework.json new file mode 100644 index 00000000..d105e09d --- /dev/null +++ b/agency-indexes/DoE/Active_Learning_Framework.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-03" + }, + "description": "Machine learning (ML) of interatomic potentials show great promise to accelerate scientific simulation, e.g., by emulating expensive computations at a high accuracy but much reduced computational cost. Training datasets are calculated from computationally expensive ab initio quantum mechanics methods, density functional theory (DFT). Trained on this data, an ML model can be very successful in predicting energy and forces for new atomic configurations. A critical factor is the quality and diversity of the training dataset. Thus, a highly automated approach to dataset construction based on active learning framework is designed suitable for material physics.\n\nThe active learning scheme begins with fully randomized atomic configurations. Then, many Molecular Dynamics (MD) trajectories are simulated using current ML potentials, where each MD trajectory is initialized to a random disordered configuration. The temperature is varied in order to diversify the sampled configuration during these simulations. The variance of predictions for eight neural networks within an ensemble is analyzed to determine whether the model is operating as expected. This helps in determining whether collecting more data would be helpful to the model by checking the ensemble variance is greater than the threshold. In this case, the MD trajectory is terminated and the final atomic configuration is placed on a queue (SQL database) for DFT calculations and added to training dataset. Periodically, ML model is retrained to the updated training model. This Active Learning loop is iterated until the cost of MD simulations becomes prohibitively expensive. The MD simulations will hopefully be sufficiently robust to support nucleation after many active learning iterations. In this sense, active learning scheme must automatically discover the important low energy and nonequilibrium physics.", + "laborHours": 0.0, + "languages": [], + "name": "Active Learning Framework", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/alf", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Active_Learning_for_NLP_Systems.json b/agency-indexes/DoE/Active_Learning_for_NLP_Systems.json new file mode 100644 index 00000000..84237e83 --- /dev/null +++ b/agency-indexes/DoE/Active_Learning_for_NLP_Systems.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "This software implements an active learning framework for Natural Language Processing (NLP) systems.\n\nIt is intended to be applied on scenarios where limited amount of labeled data is available to train a machine learning-based NLP classification system, but a large set of unlabeled documents exist. \n\nThis software will point, from the set of unlabeled documents, which ones we should label next so that the overall performance of the classifier is improved.", + "laborHours": 1064.0, + "languages": [], + "name": "Active Learning for NLP Systems", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AL_NLP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Active_Manifolds_ICML_2019_Paper_Results_Code.json b/agency-indexes/DoE/Active_Manifolds_ICML_2019_Paper_Results_Code.json new file mode 100644 index 00000000..faf92bd6 --- /dev/null +++ b/agency-indexes/DoE/Active_Manifolds_ICML_2019_Paper_Results_Code.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Problem Solved: A novel technique for regression and sensitivity analysis of C1 function f problematic input dimension given observations (x_i, f(x_i), f'(x_i)). Solution Provided by the Code: Active Manifolds reduces the problem to analysis/regression of a 1 dimensional analogue by exploiting geometric properties of the function.", + "laborHours": 0.0, + "languages": [ + "Python 2.7" + ], + "name": "Active Manifolds ICML 2019 Paper Results Code", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/bridgesra/active-manifold-icml2019-code", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bridgesra/active-manifold-icml2019-code", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Active_and_Passive_Economizer_Diagnostics_for_Rooftop_and_Air-Handling_Units.json b/agency-indexes/DoE/Active_and_Passive_Economizer_Diagnostics_for_Rooftop_and_Air-Handling_Units.json new file mode 100644 index 00000000..cb94e84f --- /dev/null +++ b/agency-indexes/DoE/Active_and_Passive_Economizer_Diagnostics_for_Rooftop_and_Air-Handling_Units.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-10-05", + "metadataLastUpdated": "2020-10-05" + }, + "description": "Algorithms and software code to detect and diagnose faulty operations with economizer operations.", + "laborHours": 109880.8, + "languages": [ + "Linux" + ], + "name": "Active and Passive Economizer Diagnostics for Rooftop and Air-Handling Units", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron-applications", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Actor_API.json b/agency-indexes/DoE/Actor_API.json new file mode 100644 index 00000000..ca4bf725 --- /dev/null +++ b/agency-indexes/DoE/Actor_API.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2022-01-11", + "metadataLastUpdated": "2022-01-11" + }, + "description": "This package provides a secure transport layer connecting mini-applications run as components of a server infrastructure. The guiding principle is that mini-apps should be \"actors\" -- able to expose a set of API calls to the network and to have a shared trust model for knowing who is calling which API function and who takes\nresponsibility for the result.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Actor API", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/99R/actor_api", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Acute_shortage_ventilator_software.json b/agency-indexes/DoE/Acute_shortage_ventilator_software.json new file mode 100644 index 00000000..f199d44a --- /dev/null +++ b/agency-indexes/DoE/Acute_shortage_ventilator_software.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "sanderb@slac.stanford.edu" + }, + "date": { + "created": "2021-03-08", + "metadataLastUpdated": "2021-03-09" + }, + "description": "This software package is used for the acute shortage ventilator developed to battle against the Covid crisis on a global scale. All information on the project can be found here:\nmedia announcements:\nhttps://www6.slac.stanford.edu/news/2020-08-13-slac-scientists-invent-low-cost-emergency-ventilator-and-share-design-free.aspx\nofficial paper:\nhttps://www.medrxiv.org/content/10.1101/2020.07.20.20158147v1\nTechnology:\nhttp://techfinder.stanford.edu/technologies/S20-256_acute-shortage-ventilator\nwebsite:\nhttps://www.slac-asv.net/", + "laborHours": 0.0, + "languages": [], + "name": "Acute shortage ventilator software", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pabv_control", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Adapter_Python_IO__Adapter__v1.0.json b/agency-indexes/DoE/Adapter_Python_IO__Adapter__v1.0.json new file mode 100644 index 00000000..a3f871e9 --- /dev/null +++ b/agency-indexes/DoE/Adapter_Python_IO__Adapter__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-05-09", + "metadataLastUpdated": "2021-06-15" + }, + "description": "The Adapter Python IO software, in short Adapter or the Adapter software, encapsulates certain Python IO capabilities used for loading in and writing out data when performing analytical Python code runs. More specificcally, it provides a Python API to load data tables from various formats such as XLSX (MS Excel), CSV, and database, into Python code as Pandas DataFrames, as well as to write out tables into a database or CSV files. The Adapter software standardizes a way to point the code to one or multiple input files of one or multiple formats. Therefore, its main feature is the ability to convert data tables identified in one main and, optionally, one or more additional input files, into database tables and Pandas DataFrames for downstream usage in any compatible software. In addition to the loading capability, an instance of the Adapter IO object has the capability to write data out. If the write capability is invoked, all loaded tables are written as either a single database or a set of CSV files, or both, to a location specified in the dedicated input table.", + "laborHours": 0.0, + "languages": [], + "name": "Adapter Python IO (Adapter) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/Adapter", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Adaptive_Control_Algorithm_to_Adjust_Settings_in_Photovoltaic_Inverters_for_Electric_Grid_Cybersecurity__DERAC__v0.1.json b/agency-indexes/DoE/Adaptive_Control_Algorithm_to_Adjust_Settings_in_Photovoltaic_Inverters_for_Electric_Grid_Cybersecurity__DERAC__v0.1.json new file mode 100644 index 00000000..1bd22fbd --- /dev/null +++ b/agency-indexes/DoE/Adaptive_Control_Algorithm_to_Adjust_Settings_in_Photovoltaic_Inverters_for_Electric_Grid_Cybersecurity__DERAC__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-28", + "metadataLastUpdated": "2024-08-29" + }, + "description": "Volt-VAR and Volt-Watt functionality in photovoltaic (PV) smart inverters provide mechanisms to ensure system voltage magnitudes and power factors remain within acceptable limits. However, these control functions can become unstable, introducing oscillations in system voltages when not appropriately configured or maliciously altered during a cyberattack. In the event that Volt-VAR and Volt-Watt control functions in a portion of PV smart inverters in a distribution grid are unstable, the proposed adaptation scheme utilizes the remaining and stably-behaving PV smart inverters and other Distributed Energy Resources to mitigate the effect of the instability in real-time. The adaptation mechanism is entirely decentralized, model-free, communication-free, and requires virtually no external configuration. This repository provides code to simulate the algorithm in experiments on the IEEE 37 node test feeder.", + "laborHours": 1626.4, + "languages": [], + "name": "Adaptive Control Algorithm to Adjust Settings in Photovoltaic Inverters for Electric Grid Cybersecurity (DERAC) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/smart-inverter-adaptive-control", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Adaptive_Forward_Modeling_Method_for_Analysis_and_Reconstructions_of_Orientation_Image_Map.json b/agency-indexes/DoE/Adaptive_Forward_Modeling_Method_for_Analysis_and_Reconstructions_of_Orientation_Image_Map.json new file mode 100644 index 00000000..313538cf --- /dev/null +++ b/agency-indexes/DoE/Adaptive_Forward_Modeling_Method_for_Analysis_and_Reconstructions_of_Orientation_Image_Map.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "IceNine is a MPI-parallel orientation reconstruction and microstructure analysis code. It's primary purpose is to reconstruct a spatially resolved orientation map given a set of diffraction images from a high energy x-ray diffraction microscopy (HEDM) experiment (1). In particular, IceNine implements the adaptive version of the forward modeling method (2, 3). Part of IceNine is a library used to for conbined analysis of the microstructure with the experimentally measured diffraction signal. The libraries is also designed for tapid prototyping of new reconstruction and analysis algorithms. IceNine is also built with a simulator of diffraction images with an input microstructure.", + "laborHours": 20778.4, + "name": "Adaptive Forward Modeling Method for Analysis and Reconstructions of Orientation Image Map", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/FrankieLi/IceNine/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FrankieLi/IceNine", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Adaptive_Optics_Control_GUI_for_the_Habitable_Worlds_Observatory.json b/agency-indexes/DoE/Adaptive_Optics_Control_GUI_for_the_Habitable_Worlds_Observatory.json new file mode 100644 index 00000000..832ad098 --- /dev/null +++ b/agency-indexes/DoE/Adaptive_Optics_Control_GUI_for_the_Habitable_Worlds_Observatory.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-04-10", + "metadataLastUpdated": "2025-04-10" + }, + "description": "This GUI explores various whether various adaptive optics control-related parameter can reach NASA's\nHabitable Worlds Observatory mission requirement of 10 pm rms over 10 minutes, building off of Fig. 4 in\nDouglas et al. 2019 (DOI: 10.3847/1538-3881/aaf385).", + "laborHours": 182.4, + "languages": [], + "name": "Adaptive Optics Control GUI for the Habitable Worlds Observatory", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/hwo1dGUI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Adaptive_Sampling_Proxy_Application.json b/agency-indexes/DoE/Adaptive_Sampling_Proxy_Application.json new file mode 100644 index 00000000..f5320057 --- /dev/null +++ b/agency-indexes/DoE/Adaptive_Sampling_Proxy_Application.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ASPA is an implementation of an adaptive sampling algorithm [1-3], which is used to reduce the computational expense of computer simulations that couple disparate physical scales. The purpose of ASPA is to encapsulate the algorithms required for adaptive sampling independently from any specific application, so that alternative algorithms and programming models for exascale computers can be investigated more easily.", + "laborHours": 19167.2, + "name": "Adaptive Sampling Proxy Application", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exmatex/aspa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Adaptive_Self_Tuning.json b/agency-indexes/DoE/Adaptive_Self_Tuning.json new file mode 100644 index 00000000..24abfd57 --- /dev/null +++ b/agency-indexes/DoE/Adaptive_Self_Tuning.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The AST software includes numeric methods to 1) adjust STA/LTA signal detector trigger level (TL) values and 2) filter detections for a network of sensors. AST adapts TL values to the current state of the environment by leveraging cooperation within a neighborhood of sensors. The key metric that guides the dynamic tuning is consistency of each sensor with its nearest neighbors: TL values are automatically adjusted on a per station basis to be more or less sensitive to produce consistent agreement of detections in its neighborhood. The AST algorithm adapts in near real-time to changing conditions in an attempt to automatically self-tune a signal detector to identify (detect) only signals from events of interest.", + "laborHours": 319.2, + "languages": [ + "Python" + ], + "name": "Adaptive Self Tuning", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/Adaptive-Self-Tuning?tab=readme-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Adaptive-Self-Tuning", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Adaptive_Sparse_Grid_Discretization__ASGarD_.json b/agency-indexes/DoE/Adaptive_Sparse_Grid_Discretization__ASGarD_.json new file mode 100644 index 00000000..d5c76623 --- /dev/null +++ b/agency-indexes/DoE/Adaptive_Sparse_Grid_Discretization__ASGarD_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2024-08-23" + }, + "description": "This code solves the Vlasov-Poisson equations in 6-dimensions without approximation. It uses sparse grid discretization to solve the high-dimensional PDEs. The code functions as a discontinuous Galerkin finite element solver. Advantages/benefits include no approximations, supports high-dimensionality, leadership-scale capability, and implicit time advance.", + "laborHours": 33029.6, + "languages": [ + "C++17" + ], + "name": "Adaptive Sparse Grid Discretization (ASGarD)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/project-asgard/asgard/releases/tag/v0.5.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v0.5.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AddBound,_AssignRock,_CutCavity,_EOS9EOS3,_DeleteElement,_MINC2MESH,_MoveMesh,_Perm2Mesh__All_versions_1.0_.json b/agency-indexes/DoE/AddBound,_AssignRock,_CutCavity,_EOS9EOS3,_DeleteElement,_MINC2MESH,_MoveMesh,_Perm2Mesh__All_versions_1.0_.json new file mode 100644 index 00000000..4801c08e --- /dev/null +++ b/agency-indexes/DoE/AddBound,_AssignRock,_CutCavity,_EOS9EOS3,_DeleteElement,_MINC2MESH,_MoveMesh,_Perm2Mesh__All_versions_1.0_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-14", + "metadataLastUpdated": "2021-05-14" + }, + "description": "The software is a collection of small pre- and post-processing utility programs in support of the TOUGH suite of simulators.", + "homepageURL": "https://tough.lbl.gov/software/tough-pre-and-post-processors", + "laborHours": 0.0, + "languages": [], + "name": "AddBound, AssignRock, CutCavity, EOS9EOS3, DeleteElement, MINC2MESH, MoveMesh, Perm2Mesh (All versions 1.0)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://tough.lbl.gov/software/tough-pre-and-post-processors", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/AdditiveFOAM.json b/agency-indexes/DoE/AdditiveFOAM.json new file mode 100644 index 00000000..c3ca7b6d --- /dev/null +++ b/agency-indexes/DoE/AdditiveFOAM.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "colemanjs@ornl.gov" + }, + "date": { + "created": "2023-06-13", + "metadataLastUpdated": "2024-05-07" + }, + "description": "AdditiveFOAM is a continuum heat transfer and fluid flow code for metal additive manufacturing developed on the OpenFOAM CFD Framework. The main components of AdditiveFOAM include: a dynamic heat source model representing heat input from independently moving beams; a robust and efficient thermodynamic solver for solid-liquid phase change in metal alloys; a library to export thermal data to ExaCA\u2014 a cellular automata (CA) code used for predicting solidification grain growth. By integrating these capabilities, AdditiveFOAM offers valuable insights into the process-structure relationships of metal additive manufacturing components.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "AdditiveFOAM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/AdditiveFOAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Adiak.json b/agency-indexes/DoE/Adiak.json new file mode 100644 index 00000000..d1f288ec --- /dev/null +++ b/agency-indexes/DoE/Adiak.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-10-25", + "metadataLastUpdated": "2019-10-25" + }, + "description": "Adiak is a computer science data management interface tool for collecting metadata about an application's runs and disseminating it to tools that subscribe to this data. Examples of this metadata could be what user is running an application, what systems it runs on, or application provided name/value pairs. \n\nAdiak's capabilities include automated reading of system-level metadata, and a generic type system for applications to register their own name/value metadata. \n\nAdiak is currently designed to provide a standard interface that can be integrated with MPI-based applications that run on high performance computing systems.\n\nExample tools that use Adiak metadata include performance analysis tools and workflow tools. By allowing the application to specify metadata to Adiak, which then disseminates it to tools, application developers do not have to write to tool-specific interfaces.\n\n", + "laborHours": 1170.4, + "languages": [], + "name": "Adiak", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/adiak", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AdvEP.json b/agency-indexes/DoE/AdvEP.json new file mode 100644 index 00000000..3fab05b2 --- /dev/null +++ b/agency-indexes/DoE/AdvEP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "AdvEP is a code repository which contains PyTorch implementations of various adversarial attacks on a deep neural network trained with Equilibrium Propagation (EP), which is a neuromorphic learning framework. AdvEP allows for the training, testing, and conducting white/black-box attacks of EP models on a wide variety of applications and datasets. AdvEP is based on the open-source code https://github.com/Laborieux-Axel/Equilibrium-Propagation which was developed to train energy models. AdvEP was created by modifying the original code to perform and test against adversarial attacks. AdvEP was developed in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning. AdvEP interfaces heavily with the open-source PyTorch Python package as well as the open-source Adversarial Robustness Toolbox (ART) package.", + "laborHours": 4058.4, + "languages": [], + "name": "AdvEP", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/AdvEP", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Advanced_Computational_Framework_for_Environmental_Management_ZEM,_Version_1.x.json b/agency-indexes/DoE/Advanced_Computational_Framework_for_Environmental_Management_ZEM,_Version_1.x.json new file mode 100644 index 00000000..0f4fda97 --- /dev/null +++ b/agency-indexes/DoE/Advanced_Computational_Framework_for_Environmental_Management_ZEM,_Version_1.x.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Typically environmental management problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly integration into a series of models with different complexity for various types of model analyses where the data are applied as soft and hard model constraints. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions). To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian- Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org). The ZEM framework is open-source and can be applied to any environmental management site. The framework will be open-source and released under GPL V3 license.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "Advanced Computational Framework for Environmental Management ZEM, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Advanced_Fenestration_Controller__AFC__v1.0.json b/agency-indexes/DoE/Advanced_Fenestration_Controller__AFC__v1.0.json new file mode 100644 index 00000000..3a97c611 --- /dev/null +++ b/agency-indexes/DoE/Advanced_Fenestration_Controller__AFC__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "The Advanced Fenestration Controller is the result of 5+ years of R&D to develop an advanced control system for Dynamic Facades (e.g., automated shades, blinds, etc.), electric lighting, and HVAC system in buildings. It can dynamically control those technologies to reduce electricity cost while increasing comfort. The work in FY22 focused on open-sourcing our development, per agreement with DOE.", + "laborHours": 2523.2, + "languages": [], + "name": "Advanced Fenestration Controller (AFC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/AFC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Advanced_Manufacturing_Basic_Entity_Relationships_Ontology.json b/agency-indexes/DoE/Advanced_Manufacturing_Basic_Entity_Relationships_Ontology.json new file mode 100644 index 00000000..3e338aec --- /dev/null +++ b/agency-indexes/DoE/Advanced_Manufacturing_Basic_Entity_Relationships_Ontology.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "A data ontology defined using the W3C Web Ontology Language (OWL) format. It defines classes and attributes for objects directly implicated in manufacturing such as materials, preform geometries, and manufacturing processes and settings. It also includes classes to describe entities that are instrumental to making digital twins and performing predictive activities on manufacturing data such as designs of experiment and predictive models.", + "laborHours": 0.0, + "languages": [], + "name": "Advanced Manufacturing Basic Entity Relationships Ontology", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/AMBER", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Advanced_Terrestral_Simulator__ATS__1.x.json b/agency-indexes/DoE/Advanced_Terrestral_Simulator__ATS__1.x.json new file mode 100644 index 00000000..4c604e3d --- /dev/null +++ b/agency-indexes/DoE/Advanced_Terrestral_Simulator__ATS__1.x.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "The Advanced Terrestrial Simulator (ATS) is a code for solving multiscale ecosystem-based, integrated, distributed hydrology. It builds on the multi-physics framework and toolsets (mesh infrastructure, discretizations, solvers) provided by Amanzi (original release LA-CC-10-069, new release pending in FCI) and is a key driver of development of the flexible multiphysics framework Acros (LA-CC-14-053). Capabilities are largely based on solving various forms of variably saturated subsurface flow (e.g., Richards equation) coupled to a surface flow equation, along with the needed sources and sinks for ecosystem and climate models. This can (but need not) include thermal processes (especially ice for frozen soils), evapo-transpiration, albedo-driven surface energy balances, snow, biogeochemistry, plant dynamics, deformation, solute and contaminant transport, erosion and sediment transport, and much more. It is unique in its thermal integrated hydrology capabilities, which include thermal energy with freeze/thaw processes in both the surface and subsurface water, and its reactive transport capabilities, which are also coupled in both surface and subsurface water. Like Amanzi, the ATS uses the Alquimia interface library to couple its transport capabilities with biogeochemical reaction engines (e.g., PFLOTRAN and CrunchFlow). The ATS has been used to explore how a wide range of ecosystems function under a variety of environmental drivers, including the evolution of polygonal permafrost in the warming arctic [1,2], the impact of forest fires on the water quality of streams in the Jaramillo watershed, and the impact of seawater intrusion on vegetation in salt water marshes on the Delaware. \n\n[1] Painter, S. L., E. T. Coon, A. L. Atchley, M. Berndt, R. Garimella, J. D. Moulton,D. Svyatskiy, and C. J. Wilson, Integrated surface/subsurface permafrost thermal hydrology: Model formulation and proof-of-concept simulations,Water Resour. Res.,52,6062\u20136077, 2016. https://doi.org/10.1002/2015WR018427\n[2] Jafarov, E. E., E. T. Coon, D. R. Harp, C. J. Wilson, S. L. Painter, A. L. Atchley, V. E. Romanovsky, Modeling the role of preferential snow accumulation in through talik development and hillslope groundwater flow in a transitional permafrost landscape, Environmental Research Letters, 13(10):105006, 2018. https://doi.org/10.1088/1748-9326/aadd30", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Advanced Terrestral Simulator (ATS) 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Advanced_Terrestrial_Simulator.json b/agency-indexes/DoE/Advanced_Terrestrial_Simulator.json new file mode 100644 index 00000000..4f7e850a --- /dev/null +++ b/agency-indexes/DoE/Advanced_Terrestrial_Simulator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "velliquettet@ornl.gov" + }, + "date": { + "created": "2019-07-31", + "metadataLastUpdated": "2019-09-19" + }, + "description": "The Advanced Terrestrial Simulator (formerly sometimes known as the Arctic Terrestrial Simulator) is a code for solving ecosystem-based, integrated, distributed hydrology. Capabilities are largely based on solving various forms of Richards equation coupled to a surface flow equation, along with the needed sources and sinks for ecosystem and climate models. This can (but need not) include thermal processes (especially ice for frozen soils), evapo-transpiration, albedo-driven surface energy balances, snow, biogeochemistry, plant dynamics, deformation, transport, and much more.\n\nPreferred citation (including correct author order):\nEthan Coon, Markus Berndt, Ahmad Jan, Daniil Svyatsky, Adam Atchley, Eugene Kikinzon, Dylan Harp, Gianmarco Manzini, Eitan Shelef, Konstantin Lipnikov, Rao Garimella, Chonggang Xu, David Moulton, Satish Karra, Scott Painter, Elchin Jafarov, and Sergi Molins. 2019. Advanced Terrestrial Simulator. Next Generation Ecosystem Experiments Arctic Data Collection, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, USA. Version [xxx]. DOI link: https://doi.org/10.11578/dc.20190911.1", + "laborHours": 58231.2, + "languages": [], + "name": "Advanced Terrestrial Simulator", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/amanzi/ats", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Advanced_Tri-lab_Software_Environment__ATSE_.json b/agency-indexes/DoE/Advanced_Tri-lab_Software_Environment__ATSE_.json new file mode 100644 index 00000000..95092f3a --- /dev/null +++ b/agency-indexes/DoE/Advanced_Tri-lab_Software_Environment__ATSE_.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-09-18" + }, + "description": "The Advanced Tri-lab Software Environment (ATSE) is an effort to build an open, modular, extensible, community-engaged, and vendor-adaptable software ecosystem that enables the prototyping of new technologies for improving the ASC computing environment. The initial target for ATSE is to accelerate the maturity of the Arm ecosystem for supporting ASC computing and the high-performance computing community more broadly. ATSE provides an integrated and optimized software stack that includes: 1) Application development environment and libraries including compilers, math libraries, tools, MPI, and OpenMP, 2) Low-level system software including optimized Linux, network stack, file systems, containers, and virtual machines, 3) Job scheduling and management including workload manager, application launcher, and user tools, and 4) System administration and management tools supporting booting, monitoring, and operating system image management. SAND2020-12377 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1748.0, + "languages": [ + "C++", + "Dockerfile", + "Shell", + "Roff", + "BitBake", + "Python" + ], + "name": "Advanced Tri-lab Software Environment (ATSE)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/atse", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Advanced_Unembedding_Algorithms_for_D-Wave_Quantum_Annealers.json b/agency-indexes/DoE/Advanced_Unembedding_Algorithms_for_D-Wave_Quantum_Annealers.json new file mode 100644 index 00000000..0ab9a3f7 --- /dev/null +++ b/agency-indexes/DoE/Advanced_Unembedding_Algorithms_for_D-Wave_Quantum_Annealers.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2023-01-17" + }, + "description": "The D-Wave quantum annealers make it possible to obtain high quality solutions of NP-hard problems by mapping a problem in a QUBO (quadratic unconstrained binary optimization) or Ising form to the physical qubit connectivity structure on the D-Wave chip. However, the latter is restricted in that only a fraction of all pairwise couplers between physical qubits exists. Modeling the connectivity structure of a given problem instance thus necessitates the computation of a minor embedding of the variables in the problem specification onto the logical qubits, which consist of several physical qubits \"chained\" together to act as a logical one. After annealing, it is however not guaranteed that all chained qubits get the same value (-1 or +1 for an Ising model, and 0 or 1 for a QUBO), and several approaches exist to assign a final value to each logical qubit (a process called \"unembedding\"). In this software, we develop tailored unembedding techniques for four important NP-hard problems: the Maximum Clique, Maximum Cut, Minimum Vertex Cover, and Graph Partitioning problems. Our techniques are simple and yet make use of structural properties of the problem being solved. Using Erd\\H{o}s-R\\'enyi random graphs as inputs, we compare our unembedding techniques to three popular ones (majority vote, random weighting, and minimize energy). We demonstrate that our proposed algorithms outperform the currently available ones in that they yield solutions of better quality, while being computationally equally efficient.", + "laborHours": 0.0, + "languages": [], + "name": "Advanced Unembedding Algorithms for D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/custom-unembedding-algorithms-QA", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AdversarialTensors.json b/agency-indexes/DoE/AdversarialTensors.json new file mode 100644 index 00000000..5a9547c2 --- /dev/null +++ b/agency-indexes/DoE/AdversarialTensors.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "This library builds a framework for defending ML models against adversarial attacks. The library will be developed at various stages leading to publication and software release at each stage. We employ tensor decomposition strategies as preprocessing stages for the first stage to provide robustness against the prominent adversarial noise. In the second stage, we develop a latent noise generator capable of generating novel adversarial noise that threatens the existing state-of-the-art defense strategy. In the third stage, we develop a UNSUP-GAN model, where the generator is trained to denoise against latent noise and most adversarial noises. This generator can provide a robust adversarial attack against any unseen attack.", + "laborHours": 0.0, + "languages": [], + "name": "AdversarialTensors", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/AdversarialTensors", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Adversarial_Robustness_Limits.json b/agency-indexes/DoE/Adversarial_Robustness_Limits.json new file mode 100644 index 00000000..8dcb23ec --- /dev/null +++ b/agency-indexes/DoE/Adversarial_Robustness_Limits.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-07-10", + "metadataLastUpdated": "2024-07-10" + }, + "description": "This is the official code for the ICML 2024 paper \"Adversarial Robustness Limits via Scaling-Law and\nHuman-Alignment Studies\". This code extends that of Wang et al. (2023) to facilitate state-of-the-art\nCIFAR-10 adversarial robustness, via training of WideResNet models on various large synthetic datasets.\nThe code also facilitates derivation of the various scaling laws put forth in our ICML paper, which we use\nto compute efficient training settings.", + "laborHours": 4544.8, + "languages": [], + "name": "Adversarial Robustness Limits", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bbartoldson/Adversarial-Robustness-Limits", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Aerial_3D_Building_Reconstruction_from_Drone_Imagery__A3DBR__v1.json b/agency-indexes/DoE/Aerial_3D_Building_Reconstruction_from_Drone_Imagery__A3DBR__v1.json new file mode 100644 index 00000000..d85d5b0b --- /dev/null +++ b/agency-indexes/DoE/Aerial_3D_Building_Reconstruction_from_Drone_Imagery__A3DBR__v1.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-25", + "metadataLastUpdated": "2021-03-25" + }, + "description": "This toolkit is composed of several modules for extracting buildings geometrical and thermal characteristics from RGB and thermal imagery captured using a drone.\n- Building 3D reconstruction module: leverage a photogrammetry software to construct a 3D point cloud from RGB drone imagery, which is then used in conjunction with image processing and geometric methods to extract building footprint and building height (i.e., 3D model of the building).\n- Windows to wall ratio estimation module: leverage deep learning semantic segmentation modeling to detect windows on 2D drone RGB images. The detected windows are then projected onto the extracted building 3D model (using building 3D reconstruction module) and their area is computed to obtain window to wall ratio estimation.\n- Thermal anomalies detection module: leverage image processing and machine learning algorithm to detect on 2D drone thermal images potential thermal anomalies within building's facades and roofs.", + "laborHours": 0.0, + "languages": [], + "name": "Aerial 3D Building Reconstruction from Drone Imagery (A3DBR) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/a3dbr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Aeroelastic_Systems_Engineering_Module_[SWR_14-26].json b/agency-indexes/DoE/Aeroelastic_Systems_Engineering_Module_[SWR_14-26].json new file mode 100644 index 00000000..adee2408 --- /dev/null +++ b/agency-indexes/DoE/Aeroelastic_Systems_Engineering_Module_[SWR_14-26].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-05-22" + }, + "description": "Small pieces of software that wraps the FAST model so that FAST can be integrated to WISDEM. NOTE: THIS REPOSITORY IS DEPRECATED AND WAS ARCHIVED (READ-ONLY) IN NOVEMBER 2019. NREL's WISDEM\u00ae software has moved to a single, integrated repository at https://github.com/wisdem/wisdem", + "laborHours": 11536.8, + "languages": [ + "Python" + ], + "name": "Aeroelastic Systems Engineering Module [SWR 14-26]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/aeroelasticse", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Affect_v._0.1.json b/agency-indexes/DoE/Affect_v._0.1.json new file mode 100644 index 00000000..41e04ccd --- /dev/null +++ b/agency-indexes/DoE/Affect_v._0.1.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-12-18" + }, + "description": "Affect is a module written in the Python language that provides functions for post-processing data that are the result of computer simulations\u2014usually the result of the finite element method\u2014for engineering and physics systems and environments.", + "laborHours": 86275.2, + "languages": [ + "C", + "C++", + "Python", + "Cython" + ], + "name": "Affect v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kevincopps/affect", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Aggregate_Remote_Memory_Copy_Interface.json b/agency-indexes/DoE/Aggregate_Remote_Memory_Copy_Interface.json new file mode 100644 index 00000000..dca26ed8 --- /dev/null +++ b/agency-indexes/DoE/Aggregate_Remote_Memory_Copy_Interface.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The purpose of the Aggregate Remote Memory Copy (ARMCI) library is to provide a general- purpose, efficient, and Widely portable remote memory access (RMA) operations (one-sided communication) optimized for Contiguous and noncontiguous (strided, scatter/gather, I/O vector) data transfers. In addition, ARMCI includes a set of atomic and mutual exclusion operations. The development ARMCI is driven by the need to support the global-address space communication model in context of distributed regular or irregular distributed data structures, communication libraries, and compilers. ARMCI is a standalone system that could be used to support user-level libraries and applications that use MPI or PVM.", + "homepageURL": "https://hpc.pnl.gov/armci", + "laborHours": 0.0, + "languages": [], + "name": "Aggregate Remote Memory Copy Interface", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://hpc.pnl.gov/armci", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://hpc.pnl.gov/armci", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Agile_Cradle-to-Grave__Agile_C2G__v1.json b/agency-indexes/DoE/Agile_Cradle-to-Grave__Agile_C2G__v1.json new file mode 100644 index 00000000..71d624f0 --- /dev/null +++ b/agency-indexes/DoE/Agile_Cradle-to-Grave__Agile_C2G__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-07", + "metadataLastUpdated": "2021-03-07" + }, + "description": "The concept for the AgileC2G Model is based on well-documented input-output methods first introduced by Wassily Leontief. These matrices are more commonly used to represent monetary inputs and outputs by sector. In contrast, the developers have constructed a model that uses a customized matrix consisting of key products and services (in place of sectors) that are directly and/or indirectly relevant to bioenergy systems (and energy systems more broadly). Their matrix tracks inputs and outputs based on physical units and uses prices only to complete the required calculations before converting total requirements back to physical units of interest.", + "laborHours": 0.0, + "languages": [], + "name": "Agile Cradle-to-Grave (Agile C2G) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/olgakavvada/biofuels_lca_tool/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "version": "v1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Agn-201_Digital_Twin.json b/agency-indexes/DoE/Agn-201_Digital_Twin.json new file mode 100644 index 00000000..59c5d3b5 --- /dev/null +++ b/agency-indexes/DoE/Agn-201_Digital_Twin.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-09-12" + }, + "description": "This is the repository for all code related to the AGN-201 Nuclear Reactor Digital Twin at Idaho State University. The goal of this code repository is to consolidate all pieces required to run the AGN-201 Digital Twin in the [DeepLynx](https://github.com/idaholab/Deep-Lynx) ecosystem. This is the first successfully launched digital twin of a fissile nuclear reactor that we are aware of. While the code is not complex, the problems of networking, policy, and initial groundwork were significant to overcome.", + "laborHours": 54461.6, + "languages": [ + "Python", + "Rust" + ], + "name": "Agn-201 Digital Twin", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/agn201_Digital_Twin", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Agnostic_Particle_Tracing.json b/agency-indexes/DoE/Agnostic_Particle_Tracing.json new file mode 100644 index 00000000..54da20f9 --- /dev/null +++ b/agency-indexes/DoE/Agnostic_Particle_Tracing.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Ray tracing and ray casting have been extensively studied by the graphics and visualization community to create images. Many different algorithms as well as optimizations techniques have been developed to help speed up these two techniques and make best use of different hardware. However, ray tracing and ray casting can also be used for scientific purposes. While graphics applications focus on photon interactions, scientific application will also monitor the interaction of photons, electrons, neutrons, alpha particles, and other particles. For example, ray casting can be used in cosmology to study the re-ionization of the early universe where ultraviolet photons broke atoms apart and ray tracing of ions can be used to study mass spectography. For this project, the aim is to investigate how techniques, frameworks, algorithms, optimizations, ... developed by the graphics community could be modified and applied to solve scientific problems requiring the tracing of different particles.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Agnostic Particle Tracing", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/AiiDA-INQ_plugin.json b/agency-indexes/DoE/AiiDA-INQ_plugin.json new file mode 100644 index 00000000..b280a64e --- /dev/null +++ b/agency-indexes/DoE/AiiDA-INQ_plugin.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-09", + "metadataLastUpdated": "2024-09-09" + }, + "description": "The AiiDA-INQ plugin will allow the INQ code developed at the lab to utilize the AiiDA workflow manager\nwhich enables high-throughput workflows. This includes provenance tracking, restart capabilities, job\ncalculators, and other capabilities", + "laborHours": 1246.4, + "languages": [], + "name": "AiiDA-INQ plugin", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/aiida-inq", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Air_Fluid_Properties.json b/agency-indexes/DoE/Air_Fluid_Properties.json new file mode 100644 index 00000000..faf008d9 --- /dev/null +++ b/agency-indexes/DoE/Air_Fluid_Properties.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-08-30" + }, + "description": "This software is used to compute numerous properties for air.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Air Fluid Properties", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/air", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AirflowNetwork.json b/agency-indexes/DoE/AirflowNetwork.json new file mode 100644 index 00000000..64d39075 --- /dev/null +++ b/agency-indexes/DoE/AirflowNetwork.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "degrawjw@ornl.gov" + }, + "date": { + "created": "2022-06-16", + "metadataLastUpdated": "2022-10-10" + }, + "description": "AirflowNetwork is a C++ implementation of the pressure network approach to bulk air movement and contaminant transport, primarily in the context of buildings. It is a descendant of NIST AIRNET (the precursor to NIST's CONTAM) and COMIS. This modeling technique divides the building's total volume up into a set of well-mixed zones that communicate via airflows through openings that are part of the building. Parts of this code have been extracted from EnergyPlus (U.S. DOE's whole building energy simulation program) and other parts are new development.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "AirflowNetwork", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/building-performance-modeling/AirflowNetwork", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AirflowNetwork_[SWR_19-45].json b/agency-indexes/DoE/AirflowNetwork_[SWR_19-45].json new file mode 100644 index 00000000..ee3ef345 --- /dev/null +++ b/agency-indexes/DoE/AirflowNetwork_[SWR_19-45].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-10", + "metadataLastUpdated": "2023-05-26" + }, + "description": "The AirflowNetwork software provides the ability to simulate air movement and the resulting transport of contaminants and other materials within a building. The performance of air distribution systems, including supply and return leaks, and multizone airflows driven by outdoor wind and forced air during HVAC system operation are simulated using a nodal network representation of the building. The pressure network model implemented here is based on George Walton's AIRNET and was modified for inclusion in the EnergyPlus building energy modeling software. The algorithm were then extracted from EnergyPlus into a stand-alone package to facility use without the building energy model and more extensive testing and validation of the underlying operations.", + "laborHours": 192158.4, + "languages": [ + "C++" + ], + "name": "AirflowNetwork [SWR 19-45]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/AirflowNetwork", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/AirfoilPrep.py__WISDEM\302\256__[SWR_13-18].json" "b/agency-indexes/DoE/AirfoilPrep.py__WISDEM\302\256__[SWR_13-18].json" new file mode 100644 index 00000000..94d4e17b --- /dev/null +++ "b/agency-indexes/DoE/AirfoilPrep.py__WISDEM\302\256__[SWR_13-18].json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-10-25" + }, + "description": "A Python module for preprocessing and evaluating aerodynamic ainoil data---primarily for wind turbine applications.", + "laborHours": 1884.8, + "languages": [ + "Python" + ], + "name": "AirfoilPrep.py (WISDEM\u00ae) [SWR 13-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/airfoilpreppy", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Airport_Risk_Assessment_Model__ARAM_.json b/agency-indexes/DoE/Airport_Risk_Assessment_Model__ARAM_.json new file mode 100644 index 00000000..02ad6677 --- /dev/null +++ b/agency-indexes/DoE/Airport_Risk_Assessment_Model__ARAM_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-05-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Airport Risk Assessment Model (ARAM) model automatically determines the optimal allocation of limited security resources to minimize total risk to the airport. At the same time, the model adds an element of randomness to the, reducing the predictability of asset schedules and further increasing countermeasure effectiveness.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Airport Risk Assessment Model (ARAM)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Akenti_Authorization_System.json b/agency-indexes/DoE/Akenti_Authorization_System.json new file mode 100644 index 00000000..14734fde --- /dev/null +++ b/agency-indexes/DoE/Akenti_Authorization_System.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "Akenti is an authorization service for distributed resources. The authorization policy is kept in distributed certificates signed by one or more stakeholders for the resources. The package consists of the following components: Java GUI tools to create and sign the policy certificates C++ libraries to do make access decisions based on the policy certificates A standalone authorization server that make access decisions C interfaces to the libraries and server", + "homepageURL": "https://dst.lbl.gov/ACSSoftware/Akenti", + "laborHours": 0.0, + "languages": [ + "gcc 2.95.3, jdk 1.3" + ], + "name": "Akenti Authorization System", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://dst.lbl.gov/ACSSoftware/Akenti/download.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dst.lbl.gov/ACSSoftware/Akenti", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Akuna.json b/agency-indexes/DoE/Akuna.json new file mode 100644 index 00000000..67062afe --- /dev/null +++ b/agency-indexes/DoE/Akuna.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Akuna is a user environment that enables geoscientists to create conceptual models for subsurface investigations. These conceptual models can be augmented to create numerical models for specific subsurface simulators, and Akuna enables these simulations to be executed on supercomputers, and the results analyzed and visualized. Akuna is designed to easily support multiple subsurface simulators by using a novel, declarative approach that describes the specific features (input file formats, execution modes, output formats) of a simulator in an external data file, based on this data file, Akuna user interfaces are dynamically generated by Akuna, greatly reducing the effort and cost required to support a new simulator.", + "homepageURL": "https://store.pnnl.gov/content/akuna", + "laborHours": 0.0, + "languages": [ + "HPC languages" + ], + "name": "Akuna", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/akuna", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/akuna", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Alarm_System_Web_Monitor.json b/agency-indexes/DoE/Alarm_System_Web_Monitor.json new file mode 100644 index 00000000..ecf33635 --- /dev/null +++ b/agency-indexes/DoE/Alarm_System_Web_Monitor.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "kasemirk@ornl.gov" + }, + "date": { + "created": "2021-10-12", + "metadataLastUpdated": "2021-10-12" + }, + "description": "Web display for Kafka-based alarms. Provides a simple read-only display of current alarms, similar to the Phoebus alarm table view. Part of ORNL-EPICS", + "laborHours": 0.0, + "languages": [ + "Java", + "JavaScript" + ], + "name": "Alarm System Web Monitor", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-epics/alarm-webmon", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Albany_2.0.json b/agency-indexes/DoE/Albany_2.0.json new file mode 100644 index 00000000..4400e538 --- /dev/null +++ b/agency-indexes/DoE/Albany_2.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "New to version 2.0 of Albany is the development of equations sets for specific application areas. These are independent research and development efforts that have chosen to use Albany as their software deployment vehicle. Because of synergies between the projects, they remain in the same code repository and are all releasing together as the Albany software.", + "laborHours": 364222.4, + "name": "Albany 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gahansen/Albany", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Albany_v._3.0.json b/agency-indexes/DoE/Albany_v._3.0.json new file mode 100644 index 00000000..1bc8a87d --- /dev/null +++ b/agency-indexes/DoE/Albany_v._3.0.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The Albany code is a general-purpose finite element code for solving partial differential equations (PDEs). Albany is a research code that demonstrates how a PDE code can be built by interfacing many of the open-source software libraries that are released under Sandia's Trilinos project. Part of the mission of Albany is to be a testbed for new Trilinos libraries, to refine their methods, usability, and interfaces. Albany includes hooks to optimization and uncertainty quantification algorithms, including those in Trilinos as well as those in the Dakota toolkit. Because of this, Albany is a desirable starting point for new code development efforts that wish to make heavy use of Trilinos. Albany is both a framework and the host for specific finite element applications. These applications have project names, and can be controlled by configuration option when the code is compiled, but are all developed and released as part of the single Albany code base, These include LCM, QCAD, FELIX, Aeras, and ATO applications.", + "laborHours": 195228.8, + "languages": [ + "Shell", + "C", + "CMake", + "MATLAB", + "Python", + "GLSL" + ], + "name": "Albany v. 3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Albany", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Albany_v_1.0.json b/agency-indexes/DoE/Albany_v_1.0.json new file mode 100644 index 00000000..ecafe9d2 --- /dev/null +++ b/agency-indexes/DoE/Albany_v_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Albany code is a general purpose finite element code for solving partial differential equations (PDEs). Albany is a research code that demonstrates how a PDE code can be built by interfacing many of the open-source software libraries that are released under Sandia's Trilinos project. Part of the mission of Albany is to be a testbed for new Trilinos libraries, to refine their methods, usability, and interfaces. Albany also serves as a demonstration code on how to build an application code against an installed Trilinos project. Because of this, Albany is a desirable starting point for new code development efforts that wish to make heavy use of Trilinos. The physics solved in Albany are currently only very academic problems, such as heat transfer, linear elasticity, and nonlinear elasticity. Albany includes hooks to optimization and uncertainty quantification algorithms, including those in the Dakota toolkit.", + "laborHours": 364222.4, + "name": "Albany v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gahansen/Albany", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Alert_Triage_v_0.1_beta.json b/agency-indexes/DoE/Alert_Triage_v_0.1_beta.json new file mode 100644 index 00000000..dc666783 --- /dev/null +++ b/agency-indexes/DoE/Alert_Triage_v_0.1_beta.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "In the cyber security operations of a typical organization, data from multiple sources are monitored, and when certain conditions in the data are met, an alert is generated in an alert management system. Analysts inspect these alerts to decide if any deserve promotion to an event requiring further scrutiny. This triage process is manual, time-consuming, and detracts from the in-depth investigation of events. We have created a software system that uses supervised machine learning to automatically prioritize these alerts. In particular we utilize active learning to make efficient use of the pool of unlabeled alerts, thereby improving the performance of our ranking models over passive learning. We have demonstrated the effectiveness of our system on a large, real-world dataset of cyber security alerts.", + "laborHours": 2508.0, + "name": "Alert Triage v 0.1 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/alert-triage", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Alexa_v._1.0.json b/agency-indexes/DoE/Alexa_v._1.0.json new file mode 100644 index 00000000..24058507 --- /dev/null +++ b/agency-indexes/DoE/Alexa_v._1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-29" + }, + "description": "Provides test-bed for physics on heterogeneous supercomputers.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++11" + ], + "name": "Alexa v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Alfalfa_[SWR_18-17].json b/agency-indexes/DoE/Alfalfa_[SWR_18-17].json new file mode 100644 index 00000000..fcf5bf76 --- /dev/null +++ b/agency-indexes/DoE/Alfalfa_[SWR_18-17].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-12-05", + "metadataLastUpdated": "2023-05-30" + }, + "description": "Alfalfa is a web based software service that implements a virtual building control system using the EnergyPlus simulation as a backend. Conventional building energy simulation is non interactive, meaning that a simulation is started and run to completion without any user input during the simulation. Alfalfa allows a client to start a building simulation, then interactively read sensor locations and dynamically command actuators in realtime. The Alfalfa web service conforms to the Project Haystack standard, which is a specification adopted by many building control system vendors. The service enables Haystack compliant control system vendors to test their control modules and algorithms without the need for a physical building or modifying their hardware and software, enabling faster and cheaper development cycles. Alfalfa has use cases beyond control system testing. One example is building fault detection, where physical building performance can be compared to simulated values in realtime, indicating where there may be a problem in the building. Another use case is informing predictive control systems, where near future events are simulated to premptively guide control decisions in the real building. This software is web based and designed to be self service. Users of Alfalfa can upload an OpenStudio building model and begin communicating with the simulated building without any advanced setup or configuration, as if they were communicating a real building control system. Behind the scenes, Alfalfa makes extensive use of Amazon Web Services, in order to scale from a very small number of users and buildings, to extremely large numbers in a cost effective way.", + "laborHours": 31479.2, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Alfalfa [SWR 18-17]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/alfalfa", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.5.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Algebraic_Multigrid_Benchmark.json b/agency-indexes/DoE/Algebraic_Multigrid_Benchmark.json new file mode 100644 index 00000000..832dbf78 --- /dev/null +++ b/agency-indexes/DoE/Algebraic_Multigrid_Benchmark.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "AMG is a parallel algebraic multigrid solver for linear systems arising from problems on unstructured grids. It has been derived directly from the BoomerAMG solver in the hypre library, a large linear solvers library that is being developed in the Center for Applied Scientific Computing (CASC) at LLNL and is very similar to the AMG2013 benchmark with additional optimizations. The driver provided in the benchmark can build various test problems. The default problem is a Laplace type problem with a 27-point stencil, which can be scaled up and is designed to solve a very large problem. A second problem simulates a time dependent problem, in which successively various smnllcr systems are solved.", + "laborHours": 44414.4, + "name": "Algebraic Multigrid Benchmark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AMG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Algorithmic_Differentlation_Applied_to_Floating-Point_Precision_Tuning.json b/agency-indexes/DoE/Algorithmic_Differentlation_Applied_to_Floating-Point_Precision_Tuning.json new file mode 100644 index 00000000..b1deb327 --- /dev/null +++ b/agency-indexes/DoE/Algorithmic_Differentlation_Applied_to_Floating-Point_Precision_Tuning.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-20" + }, + "description": "ADaPT Is a software library that Is used for mixed preclsk>n ftoatln1 point analysis.", + "laborHours": 456.0, + "languages": [], + "name": "Algorithmic Differentlation Applied to Floating-Point Precision Tuning", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/adapt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Algorithms_for_Forward_and_Inverse_Problem_Solutions_in_Phase_Contrast_Tomography.json b/agency-indexes/DoE/Algorithms_for_Forward_and_Inverse_Problem_Solutions_in_Phase_Contrast_Tomography.json new file mode 100644 index 00000000..e6d37aa3 --- /dev/null +++ b/agency-indexes/DoE/Algorithms_for_Forward_and_Inverse_Problem_Solutions_in_Phase_Contrast_Tomography.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2023-05-09" + }, + "description": "PhaseTorch is a python package that implements algorithms for forward and inverse problem solutions in X-ray phase contrast tomography (XPCT). XPCT is useful to reconstruct the 3D distribution of the refractive index decrement and absorption index of an imaged object. PhaseTorch implements algorithms for simulation, reconstruction, and analysis of XPCT data. PhaseTorch provides algorithms for simulation of XPCT data of an object with known refractive and absorption indices. It contains algorithms for reconstructing the projections of the absorption index and refractive index decrement. ", + "laborHours": 0.0, + "languages": [], + "name": "Algorithms for Forward and Inverse Problem Solutions in Phase Contrast Tomography", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/phasetorch/phasetorch", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AlignmentSetEditor.json b/agency-indexes/DoE/AlignmentSetEditor.json new file mode 100644 index 00000000..3d4eeeb7 --- /dev/null +++ b/agency-indexes/DoE/AlignmentSetEditor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "A reads alignment set editor. A KBase module generated by the KBase SDK.", + "laborHours": 2173.6, + "languages": [], + "name": "AlignmentSetEditor", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/AlignmentSetEditor", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Alignment_Implementation_for_Manufacturing_using_Fringe_Analysis_Slope_Technique__AIMFAST__2018.11.20.json b/agency-indexes/DoE/Alignment_Implementation_for_Manufacturing_using_Fringe_Analysis_Slope_Technique__AIMFAST__2018.11.20.json new file mode 100644 index 00000000..c20883d2 --- /dev/null +++ b/agency-indexes/DoE/Alignment_Implementation_for_Manufacturing_using_Fringe_Analysis_Slope_Technique__AIMFAST__2018.11.20.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-01-09", + "metadataLastUpdated": "2019-03-25" + }, + "description": "AIMFAST is a software code used to align facets on a dish or heliostat solar concentrator to a specific aimpoint strategy to minimize peak fluxes and maximize system optical performance. AIMFAST uses a large monitor or projection screen to display fringe patterns, and a machine vision camera to image the reflection of these patterns in the subject dish mirrors. From these images, a detailed map of surface normals can be generated and compared to design or fitted mirror shapes. This fitted comparison is then used to develop a single vector representing the orientation of the facets relative to the design orientation and provide near-real-time adjustment information to a communicating computer. The communicating computer can display adjustments or directly interface with adjustment tools. ", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 4879.2, + "languages": [ + "MATLAB" + ], + "name": "Alignment Implementation for Manufacturing using Fringe Analysis Slope Technique (AIMFAST) 2018.11.20", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "2018.11.20" +} \ No newline at end of file diff --git a/agency-indexes/DoE/All_Particle_In_Fission_Reactor_-_Energy_Deposition.json b/agency-indexes/DoE/All_Particle_In_Fission_Reactor_-_Energy_Deposition.json new file mode 100644 index 00000000..5178e39c --- /dev/null +++ b/agency-indexes/DoE/All_Particle_In_Fission_Reactor_-_Energy_Deposition.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-02-18", + "metadataLastUpdated": "2025-02-18" + }, + "description": "This product includes software developed by Members of the Geant4 Collaboration (http://cern.ch/geant4). The basic principle of ALFRED consists of a k-eigenvalue module in which all generated particles are tracked and all deposited energy is accounted for. An eigenvalue module updates the neutron source after each run based on the neutrons emitted at each fission in the previous run. As a result, the source distribution converges to the fundamental mode of the steady-state eigenvalue problem of the associated critical reactor. ALFRED leverages the High Precision neutron transport package.", + "laborHours": 1018.4, + "languages": [ + "C++" + ], + "name": "All Particle In Fission Reactor - Energy Deposition", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/ALFRED", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/All_People's_Simulator.json b/agency-indexes/DoE/All_People's_Simulator.json new file mode 100644 index 00000000..db80d719 --- /dev/null +++ b/agency-indexes/DoE/All_People's_Simulator.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The All People's Simulator is a software package which can simulate a large number of people wandering randomly through a real city. It utilizes freely-available map data from the OpenStreetMaps project to create a map of city streets, then simulates people wandering through those streets. APS was designed to integrate with other work being done in the \"Megadroid\" LDRD, but is capable of functioning and providing value completely on its own.", + "laborHours": 547.2, + "languages": [ + "Go", + "Makefile" + ], + "name": "All People's Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/gosim?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gosim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/All_Source_Sensor_Analysis.json b/agency-indexes/DoE/All_Source_Sensor_Analysis.json new file mode 100644 index 00000000..0ae23d82 --- /dev/null +++ b/agency-indexes/DoE/All_Source_Sensor_Analysis.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "ASSA is a software application that processes binary data into summarized index tables that can be used to organize features contained within the data. ASSA's index tables can also be used to search for user specified features. ASSA is designed to organize and search for patterns in unstructured binary data streams or archives, such as video, images, audio, and network traffic. ASSA is basically a very general search engine used to search for any pattern in any binary data stream. It has uses in video analytics, image analysis, audio analysis, searching hard-drives, monitoring network traffic, etc.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++, C, Fortran, Python, PHP, Javascript, HTML" + ], + "name": "All Source Sensor Analysis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Alpheus.json b/agency-indexes/DoE/Alpheus.json new file mode 100644 index 00000000..c92f5753 --- /dev/null +++ b/agency-indexes/DoE/Alpheus.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08545O\nAlpheus is the code implementation of an advanced data structure addressing the technical challenge of analyzing a continuous data stream that is too big to fit in a computer's memory. Alpheus reports when explicitly-defined conditions on the data in the stream are met. Though the software doesn\u2019t have a specific application domain, it was built to address challenges in cybersecurity. The software includes a representative cybersecurity data set, as well as simulated attack and benign activity.\n\nThe software\u2019s capabilities are critical to real-world application. For example, it can operate with unlimited-sized data streams while maintaining the same theoretical performance and reporting guarantees. The code\u2019s authors also improved execution performance by leveraging persistent memory. \n\nThe code is designed for use by the technical reviewers for the Algorithm Engineering and Experiments conference run by the Society for Industrial and Applied Mathematics.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "python", + "Bash" + ], + "name": "Alpheus", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Alquimia.json b/agency-indexes/DoE/Alquimia.json new file mode 100644 index 00000000..b6e983d8 --- /dev/null +++ b/agency-indexes/DoE/Alquimia.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-09-08" + }, + "description": "Alquimia provides a generic interface between flow and transport simulators (drivers) and biogeochemical reaction capabilities (engines). Alquimia consists of two parts: an application programming interface, API, and a wrapper library. The API describes in detail how information is exchanged between the driver and the engine. This includes the function call signatures and data structures required for implementing alquimia in a mixed language (C/C++/Fortran) programming environment. The library is an implementation of the documented API, providing an interface into the biogeochemistry routines supplied by other codes: Alquimia does not do any geochemical calculations. Version 1.0 provides interfaces to the open source codes (BSD) CrunchFlow/CrunchTope and (LGPL) PFLOTRAN. Version 1.0 meets the policies set forth by (and is part of) the Extreme-scale Scientific Software Development Kit, xSDK version 0.6.0.", + "laborHours": 0.0, + "languages": [ + "C++", + "Fortran" + ], + "name": "Alquimia", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LBL-EESA/alquimia-dev/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-EESA/alquimia-dev", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Alternative_Fueling_Station_Locator_-_ANDROID_[SWR_17-07].json b/agency-indexes/DoE/Alternative_Fueling_Station_Locator_-_ANDROID_[SWR_17-07].json new file mode 100644 index 00000000..410c8b80 --- /dev/null +++ b/agency-indexes/DoE/Alternative_Fueling_Station_Locator_-_ANDROID_[SWR_17-07].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-13", + "metadataLastUpdated": "2023-05-30" + }, + "description": "The Alternative Fueling Station Locator app helps you find fueling stations that offer electricity, natural gas, biodiesel, ethanol (E85), propane, and hydrogen.\n\nUse your current location or enter a custom location to find the 20 closest stations within a 30-mile radius. View the stations on a map or see a list of stations ordered by distance from your location. Select your alternative fuel of choice and adjust the custom filters to fit your needs.\n\nSelect a station from the map or list to view contact info and other details:\n- address, phone number, and hours of operation\n- payment types accepted\n- public or private access\n- special services\n- compression (natural gas)\n- vehicle size access (natural gas)\n- number and types of chargers (electric)\n- blends available (biodiesel)\n- blender pumps (ethanol)\n\nThe free app draws information from the U.S. Department of Energy's Alternative Fuels Data Center, which houses the most comprehensive, up-to-date database of alternative fueling stations in the United States. The database contains location information for more than 25,000 alternative fueling stations throughout the country.", + "homepageURL": "https://afdc.energy.gov/stations#/find/nearest", + "laborHours": 29518.4, + "languages": [ + "JavaScript", + "HTML", + "CSS" + ], + "name": "Alternative Fueling Station Locator - ANDROID [SWR 17-07]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrel.gov/disclaimer.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://afdc.energy.gov/stations#/find/nearest", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "1.0.2 (as of 3/13/2019)" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Alternative_Fueling_Station_Locator_-_APPLE_[SWR_17-06].json b/agency-indexes/DoE/Alternative_Fueling_Station_Locator_-_APPLE_[SWR_17-06].json new file mode 100644 index 00000000..3d8617cf --- /dev/null +++ b/agency-indexes/DoE/Alternative_Fueling_Station_Locator_-_APPLE_[SWR_17-06].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-13", + "metadataLastUpdated": "2023-05-30" + }, + "description": "The free Alternative Fueling Station Locator app helps you find fueling stations that offer electricity, natural gas, biodiesel, E85, propane, or hydrogen.\n\nUse your current location or enter a custom location to find the 20 closest stations within a 30-mile radius. View the stations on a map or see a list of stations ordered by distance from your location. Select your alternative fuel of choice and adjust the custom filters to fit your needs.\n\nSelect a station from the map or list to view contact info and other details:\n- address, phone number, and hours of operation\n- payment types accepted\n- public or private access\n- special services\n- compression (natural gas)\n- vehicle size access (natural gas)\n- number and types of chargers (electric)\n- blends available (biodiesel)\n- blender pumps (ethanol)\n\nThe app draws information from the U.S. Department of Energy's Alternative Fuels Data Center, which houses the most comprehensive, up-to-date database of alternative fueling stations in the United States. The database contains location information for more than 15,000 alternative fueling stations throughout the country.", + "homepageURL": "https://afdc.energy.gov/stations#/find/nearest", + "laborHours": 29518.4, + "languages": [ + "Objective-C" + ], + "name": "Alternative Fueling Station Locator - APPLE [SWR 17-06]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrel.gov/disclaimer.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://afdc.energy.gov/stations#/find/nearest", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "1.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Aluminum_GPU-aware_Communication_Library.json b/agency-indexes/DoE/Aluminum_GPU-aware_Communication_Library.json new file mode 100644 index 00000000..5d00d3c4 --- /dev/null +++ b/agency-indexes/DoE/Aluminum_GPU-aware_Communication_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "Aluminum is an optimized GPU-aware communication library. It provides a generic Interface to high-performance allreduce algorithms, with support for additional collective operations in progress. Blocking and non-blocking algorithms and GPU-aware algorithms are supported. Aluminum contains custom Implementations and Interfaces to existing optimized communication libraries, exposed through a generic API. ", + "laborHours": 5578.4, + "languages": [], + "name": "Aluminum GPU-aware Communication Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Aluminum", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Amalgam.json b/agency-indexes/DoE/Amalgam.json new file mode 100644 index 00000000..f7e6bfba --- /dev/null +++ b/agency-indexes/DoE/Amalgam.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Amalgam is a system that allows you to generate collections of files that work with conventional tools but take up minimal extra space on storage. If you already are archiving files in a file system and don't want to make multiple copies of whole files in order to ship the data somewhere then this system is for you. Amalgam consists of tools that allow you to create and get information about '.amalgam' files which contain just the metadata associated with a set of files. It also contains a fuse file system that, using amalgam files, will dynamically create traditional tar files. With this setup, you can see multiple orders of magnitude reduction in storage requirements for temporary data collections.", + "laborHours": 638.4, + "name": "Amalgam", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/amalgam", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Amanzi_1.x.json b/agency-indexes/DoE/Amanzi_1.x.json new file mode 100644 index 00000000..b12854f8 --- /dev/null +++ b/agency-indexes/DoE/Amanzi_1.x.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "Amanzi provides a flexible and extensible multiphase, multicomponent, flow and reactive transport simulation capability for environmental applications. It also includes thermal and geomechanical processes in the subsurface. It includes toolsets for meshing infrastructure, discretizations, and solvers for the resulting nonlinear systems of equations. The framework Arcos (LA-CC-14-053), provides the internal data management, process and coupling interfaces, and runtime configuration through a directed acyclic graph [1]. The code is parallel and makes use of open-source parallel frameworks such as Trilinos [2] developed at Sandia National Laboratory and PETSc (the Portable Extensible Toolkit for Scientific Computing) [3] developed at Argonne National Laboratory. Rudimentary geochemistry capabilities are included in Amanzi, while a state-of-the-art geochemistry support is provided through the Alquimia interface library, which can use well established open-source geochemistry engines (e.g., PFLOTRAN or CrunchFlow). In addition, support for GPUs is being developed through the Kokkos [4] performance portability library. Amanzi is used to model contaminant migration at various DOE waste sites (e.g., Hanford, and Savannah River), and is generally applicable to contaminant migration in groundwater under partially saturated nonisothermal conditions and its interaction with surface water. Development of Amanzi is funded by the DOE Office of Science, primarily through programs in the DOE Office of Biological and Environmental Research (BER) and internally through LDRD. [1] Coon, E. T., J. D. Moulton, and S. L. Painter, Managing complexity in simulations of land surface and near-surface processes, Environmental Modelling & Software, 78, pp. 134-149, 2016. http://dx.doi.org/10.1016/j.envsoft.2015.12.017 [2] Trilinos, https://trilinos.github.io/ [3] Portable, Extensible Toolkit for Scientific Computation, https://www.mcs.anl.gov/petsc/ [4] Kokkos C++ Performance Portability Programming EcoSystem, https://github.com/kokkos", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Amanzi 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Amber_Plug-In_for_Protein_Shop.json b/agency-indexes/DoE/Amber_Plug-In_for_Protein_Shop.json new file mode 100644 index 00000000..023c9541 --- /dev/null +++ b/agency-indexes/DoE/Amber_Plug-In_for_Protein_Shop.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Amber Plug-in for ProteinShop has two main components: an AmberEngine library to compute the protein energy models, and a module to solve the energy minimization problem using an optimization algorithm in the OPTI-+ library. Together, these components allow the visualization of the protein folding process in ProteinShop. AmberEngine is a object-oriented library to compute molecular energies based on the Amber model. The main class is called ProteinEnergy. Its main interface methods are (1) \"init\" to initialize internal variables needed to compute the energy. (2) \"eval\" to evaluate the total energy given a vector of coordinates. Additional methods allow the user to evaluate the individual components of the energy model (bond, angle, dihedral, non-bonded-1-4, and non-bonded energies) and to obtain the energy of each individual atom. The Amber Engine library source code includes examples and test routines that illustrate the use of the library in stand alone programs. The energy minimization module uses the AmberEngine library and the nonlinear optimization library OPT++. OPT++ is open source software available under the GNU Lesser General Public License. The minimization module currently makes use of the LBFGS optimization algorithm in OPT++ to perform the energy minimization. Future releases may give the user a choice of other algorithms available in OPT++.", + "homepageURL": "https://sourceforge.net/projects/proteinshop", + "laborHours": 0.0, + "languages": [], + "name": "Amber Plug-In for Protein Shop", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/proteinshop", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/AmeriFlux_BASE_Flux_Met_Data_QA_QC_and_Processing__AMF-BASE-QAQC__v1.0.0.json b/agency-indexes/DoE/AmeriFlux_BASE_Flux_Met_Data_QA_QC_and_Processing__AMF-BASE-QAQC__v1.0.0.json new file mode 100644 index 00000000..dda4f66a --- /dev/null +++ b/agency-indexes/DoE/AmeriFlux_BASE_Flux_Met_Data_QA_QC_and_Processing__AMF-BASE-QAQC__v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-07", + "metadataLastUpdated": "2023-06-07" + }, + "description": "The AmeriFlux BASE Flux/Met Data QA/QC and Processing (AMF-BASE-QAQC) code provides tools to review and prepare continuous flux/met data submitted to the AmeriFlux Management Project for publication as the AmeriFlux BASE data product. The code provides 3 core functionalities: Format QA/QC assesses submitted data files for compliance with the required submission format; Data QA/QC assesses the data quality; BASE Publish prepares the data for publication.", + "laborHours": 0.0, + "languages": [], + "name": "AmeriFlux BASE Flux/Met Data QA/QC and Processing (AMF-BASE-QAQC) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMF-FLX/AMF-BASE-QAQC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Amesh_v1.0.json b/agency-indexes/DoE/Amesh_v1.0.json new file mode 100644 index 00000000..188c3e17 --- /dev/null +++ b/agency-indexes/DoE/Amesh_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-03", + "metadataLastUpdated": "2021-06-15" + }, + "description": "Amesh generates discretized grids for numerical modeling of flow and transport problems in which the formulation is based on the integral finite difference method (IFDM). For example, the output of Amesh can be used directly as input to the TOUGH2 or TOUGH3 numerical simulators. Amesh can generate 1D, 2D, or 3D numerical grids for a given set of locations, i.e., the centers of each discrete sub-domain. In the 2D areal plane Voronoi tessellation is used.", + "laborHours": 0.0, + "languages": [], + "name": "Amesh v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/amesh-v1.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "version": "v1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Amesos2_Templated_Direct_Sparse_Solver_Package.json b/agency-indexes/DoE/Amesos2_Templated_Direct_Sparse_Solver_Package.json new file mode 100644 index 00000000..eb393aa9 --- /dev/null +++ b/agency-indexes/DoE/Amesos2_Templated_Direct_Sparse_Solver_Package.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "Amesos2 is a templated direct sparse solver package. Amesos2 provides interfaces to direct sparse solvers, rather than providing native solver capabilities. Amesos2 is a derivative work of the Trilinos package Amesos.", + "laborHours": 8344830.4, + "languages": [], + "name": "Amesos2 Templated Direct Sparse Solver Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Amesos_Solver_Package.json b/agency-indexes/DoE/Amesos_Solver_Package.json new file mode 100644 index 00000000..655dc7d2 --- /dev/null +++ b/agency-indexes/DoE/Amesos_Solver_Package.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "Amesos is the Direct Sparse Solver Package in Trilinos. The goal of Amesos is to make AX=S as easy as it sounds, at least for direct methods. Amesos provides interfaces to a number of third party sparse direct solvers, including SuperLU, SuperLU MPI, DSCPACK, UMFPACK and KLU. Amesos provides a common object oriented interface to the best sparse direct solvers in the world. A sparse direct solver solves for x in Ax = b. where A is a matrix and x and b are vectors (or multi-vectors). A sparse direct solver flrst factors A into trinagular matrices L and U such that A = LU via gaussian elimination and then solves LU x = b. Switching amongst solvers in Amesos roquires a change to a single parameter. Yet, no solver needs to be linked it, unless it is used. All conversions between the matrices provided by the user and the format required by the underlying solver is performed by Amesos. As new sparse direct solvers are created, they will be incorporated into Amesos, allowing the user to simpty link with the new solver, change a single parameter in the calling sequence, and use the new solver. Amesos allows users to specify whether the matrix has changed. Amesos can be used anywhere that any sparse direct solver is needed.", + "laborHours": 8344830.4, + "languages": [], + "name": "Amesos Solver Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Amethyst.json b/agency-indexes/DoE/Amethyst.json new file mode 100644 index 00000000..00ce0f39 --- /dev/null +++ b/agency-indexes/DoE/Amethyst.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2022-10-05" + }, + "description": "SAND2021-15049 O\nAmethyst is a digital assistant artificial intelligence (AI) similar in functional scope to Apple or Amazon systems. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Python3" + ], + "name": "Amethyst", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AmpSuite.json b/agency-indexes/DoE/AmpSuite.json new file mode 100644 index 00000000..9ed0921c --- /dev/null +++ b/agency-indexes/DoE/AmpSuite.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-12" + }, + "description": "Seismic amplitudes offer vital information about explosion source characteristics, including discrimination and yield estimation. To take advantage of this, we developed an interactive Python package to measure, control data quality, generate broad area propagation models and perform discrimination and estimate yield. Propagation models are essential in support of transportable yield and broad area discrimination. The key benefit of this package will be its ability to continuously integrate data and new techniques. The AmpSuite framework will provide standardized, repeatable, and accurate model generation and characterization routines. The capability is crucial for monitoring agencies tasked with rapid and high-quality seismic event characterization.\nThe AmpSuite software includes a series of independent modules to perform:\n\u2022 Direct Phase Amplitude Measurement and Storage\n\u2022 Coda Envelope Measurement and Storage\n\u2022 Data Quality Control\n\u2022 New Propagation Model Developments\n\u2022 Seismic Discrimination and Analysis\n\u2022 Yield Estimation\nand supporting utility software. The AmpSuite software provides comprehensive solutions for monitoring agencies seeking to optimize model generation and event analysis within a contemporary Python framework. Stakeholders (AFTAC) have begun to move towards the Python language for scientific analysis as a new workforce emerges.", + "laborHours": 440.8, + "languages": [], + "name": "AmpSuite", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/AmpSuite", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AmpsSDK.json b/agency-indexes/DoE/AmpsSDK.json new file mode 100644 index 00000000..00067ed6 --- /dev/null +++ b/agency-indexes/DoE/AmpsSDK.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SDK for controlling the Adaptable Multiple Power Supplies (AMPS boxes)", + "laborHours": 9013.6, + "languages": [], + "name": "AmpsSDK", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/AmpsSDK", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/An_Arbitrary_Precision_Computation_Package.json b/agency-indexes/DoE/An_Arbitrary_Precision_Computation_Package.json new file mode 100644 index 00000000..14384926 --- /dev/null +++ b/agency-indexes/DoE/An_Arbitrary_Precision_Computation_Package.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This package permits a scientist to perform computations using an arbitrarily high level of numeric precision (the equivalent of hundreds or even thousands of digits), by making only minor changes to conventional C++ or Fortran-90 soruce code. This software takes advantage of certain properties of IEEE floating-point arithmetic, together with advanced numeric algorithms, custom data types and operator overloading. Also included in this package is the \"Experimental Mathematician's Toolkit\", which incorporates many of these facilities into an easy-to-use interactive program.", + "homepageURL": "https://www.davidhbailey.com/dhbsoftware", + "laborHours": 0.0, + "languages": [ + "C++ and F90 compilers" + ], + "name": "An Arbitrary Precision Computation Package", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.davidhbailey.com/dhbsoftware", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.davidhbailey.com/dhbsoftware", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/An_Electronic_Encyclopedia_of_Remedial_Options.json b/agency-indexes/DoE/An_Electronic_Encyclopedia_of_Remedial_Options.json new file mode 100644 index 00000000..603e69f5 --- /dev/null +++ b/agency-indexes/DoE/An_Electronic_Encyclopedia_of_Remedial_Options.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2022-11-10" + }, + "description": "REOPT has been developed by Pacific Northwest Laboratory to provide information about remedial action technologies, including application and regulatory information for over 700 contaminants. REOPT is a user-friendly personal computer program and database that functions like an electronic encyclopedia, sorting and presenting information to quickly familiarize engineers and planners with available remediation technologies. The system will help users focus quickly on the remediation technologies most likely to be effective for a particular site and problem, and presents concise, easy-to-use information about those technologies, helping users identify the key factors and constraints to consider in evaluating the use of each technology. REOPT contains information on approximately 90 established (i.e., proven) remediation technologies that could potentially be used for DOE waste-site cleanup. REOPT also contains auxiliary information about hazardous and radioactive contaminants and the federal regulations that govern their disposal. REOPT contains data for approximately 90 remedial action technologies, divided into categories according to the portion of a remedial action (i.e., containment, treatment, disposal, etc.) that they relate to or perform. Technologies are also classified according to the contaminants to which they may be applied. Contaminants may be selected from a list of approximately 700 in ten organic and four inorganic categories. The information for each technology is organized into the broad categories of descriptive information, application information, and additional information sources; these are then subdivided to allow the user to access more specific information about the technology.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "An Electronic Encyclopedia of Remedial Options", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/An_Interactive_System_for_Crowdsourcing_Features_Generation_and_Building_Classifiers_for_Machine_Learning__\"Sharkzor\"_.json" "b/agency-indexes/DoE/An_Interactive_System_for_Crowdsourcing_Features_Generation_and_Building_Classifiers_for_Machine_Learning__\"Sharkzor\"_.json" new file mode 100644 index 00000000..f60da765 --- /dev/null +++ "b/agency-indexes/DoE/An_Interactive_System_for_Crowdsourcing_Features_Generation_and_Building_Classifiers_for_Machine_Learning__\"Sharkzor\"_.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The system allows for multiple people to \"crowdsource\" feature generation and also enables the system to use these features to suggest alternative features to the user. The user interacts with a \"canvas\", where they position icons representing pieces of data. A unique feature is that the data can be heterogeneous -- some of the icons can represent images, while others could be text, audio, etc. After the user positions items on the screen to their satisfaction, they press a button to commit the X/Y coordinates of each icon to a central database, where these positions are added as a latent feature to each item. The user also has the option to request new, untouched data be added to the canvas, and the system positions each new item according the pattern it has learned from the original data. Another unique feature is that the user can ask the system to refine their initial rough work. The system uses information theoretic measures to determine which features in the database best explain how the user positioned the icons on the screen. It then attempts to *incrementally* optimize the positions on the screen to best explain those features it isolated. The user can then adjust the positions to correct the system, or the user can request additional refinement to further optimize the positions. In this way, by incorporating user feedback and crowdsourced features, the system reduces the time required for a user to develop a rich classification scheme for large amounts of data.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "An Interactive System for Crowdsourcing Features Generation and Building Classifiers for Machine Learning (\"Sharkzor\")", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/An_agent-based_deployment_decision-support_system_for_electric_vehicle_services.json b/agency-indexes/DoE/An_agent-based_deployment_decision-support_system_for_electric_vehicle_services.json new file mode 100644 index 00000000..b997f0dc --- /dev/null +++ b/agency-indexes/DoE/An_agent-based_deployment_decision-support_system_for_electric_vehicle_services.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2022-04-11", + "metadataLastUpdated": "2022-04-11" + }, + "description": "METS-R ADDSEVS simulator is a high fidelity, parallel, agent-based evacuation simulator for multi-modal energy-optimal trip scheduling in real-time (METS-R) at transportation hubs. It consists of two modules. The first one is the traffic simulator module; the second one is the high-performance computing (HPC) module. More details can be found at https://umnilab.github.io/METS-R_doc/.", + "homepageURL": "https://umnilab.github.io/METS-R_doc", + "laborHours": 0.0, + "languages": [], + "name": "An agent-based deployment decision-support system for electric vehicle services", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://umnilab.github.io/METS-R_doc", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Anaerobic_Digestion_Model.json b/agency-indexes/DoE/Anaerobic_Digestion_Model.json new file mode 100644 index 00000000..da325a24 --- /dev/null +++ b/agency-indexes/DoE/Anaerobic_Digestion_Model.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Anaerobic Digestion Model No 1 (ADM1) is a mathematical model used by researchers to simulate the anaerobic digestion process that converts organic matter into biogas. The reduction of biosolids during anaerobic digestion reduces the solids handling cost while the biogas produced can be used to generate heat and electricity to offset the cost of heat and electricity at water resource recovery facilities. The original version of the ADM1 developed by the International Water Associations Task Group for Mathematical Modelling of Anaerobic Digestion Processes was created to describe the kinetics and stoichiometry of the primary biochemical processes in anaerobic digestion. The EES-16 team modified the ADM1 by adding mathematical terms which separate the solids retention time from hydraulic retention time to simulate novel AD technologies, integrating the model into one package in C++ language, introducing sophisticated implicit solvers by linking it to the PETSc package which allows fast and scalable (parallel) solution for the system of differential equations in the ADM1. Also, we created an easy-to-navigate interface with tutorial examples documented in the ipython notebook allowing customization of the operating conditions and reactor configurations for the simulation of the model.", + "laborHours": 0.0, + "languages": [], + "name": "Anaerobic Digestion Model", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ADM1F", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Analysing_Scales_of_Precipitation.json b/agency-indexes/DoE/Analysing_Scales_of_Precipitation.json new file mode 100644 index 00000000..ee909848 --- /dev/null +++ b/agency-indexes/DoE/Analysing_Scales_of_Precipitation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-10-29", + "metadataLastUpdated": "2021-10-29" + }, + "description": "The Analysing Scales of Precipitation (ASoP) package is being interfaced with the DOE Coordinated Model Evaluation Capabilities (CMEC) project. Users will be able to use the cmec-driver software to easily run ASoP and generate precipitation metrics as part of climate model evaluation workflows. These metrics provide information about the spatial and temporal patterns of precipitation at different timescales.", + "laborHours": 0.0, + "languages": [], + "name": "Analysing Scales of Precipitation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nick-klingaman/ASoP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Analysis_Code_-_Data_Analysis_in_'Leveraging_Multiple_Statistical_Methods_for_Inverse_Prediction_in_Nuclear_Forensics_Applications'__LMSMIPNFA__v._1.0.json b/agency-indexes/DoE/Analysis_Code_-_Data_Analysis_in_'Leveraging_Multiple_Statistical_Methods_for_Inverse_Prediction_in_Nuclear_Forensics_Applications'__LMSMIPNFA__v._1.0.json new file mode 100644 index 00000000..88990fd6 --- /dev/null +++ b/agency-indexes/DoE/Analysis_Code_-_Data_Analysis_in_'Leveraging_Multiple_Statistical_Methods_for_Inverse_Prediction_in_Nuclear_Forensics_Applications'__LMSMIPNFA__v._1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2024-09-18" + }, + "description": "R code that performs the analysis of a data set presented in the paper \u2018Leveraging Multiple Statistical Methods for Inverse Prediction in Nuclear Forensics Applications\u2019 by Lewis, J., Zhang, A., Anderson-Cook, C. It provides functions for doing inverse predictions in this setting using several different statistical methods. The data set is a publicly available data set from a historical Plutonium production experiment.", + "laborHours": 349.6, + "languages": [ + "R" + ], + "name": "Analysis Code - Data Analysis in 'Leveraging Multiple Statistical Methods for Inverse Prediction in Nuclear Forensics Applications' (LMSMIPNFA) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/LMSMIPNFA", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Analysis_of_prescribed_fire_days_in_climate_model_output.json b/agency-indexes/DoE/Analysis_of_prescribed_fire_days_in_climate_model_output.json new file mode 100644 index 00000000..4500f834 --- /dev/null +++ b/agency-indexes/DoE/Analysis_of_prescribed_fire_days_in_climate_model_output.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "This code analyzes openly available, downscaled climate model output and counts days in a year that are available to conduct prescribed fire based on meteorological prescription data obtained from US land management agencies.", + "laborHours": 0.0, + "languages": [], + "name": "Analysis of prescribed fire days in climate model output", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ajonko/RxFire", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Analysis_scripts_associated_with_manuscript,_\342\200\234Hydraulically-vulnerable_trees_survive_on_deep-water_access_during_droughts_in_a_tropical_forest\342\200\235.json" "b/agency-indexes/DoE/Analysis_scripts_associated_with_manuscript,_\342\200\234Hydraulically-vulnerable_trees_survive_on_deep-water_access_during_droughts_in_a_tropical_forest\342\200\235.json" new file mode 100644 index 00000000..85bfda48 --- /dev/null +++ "b/agency-indexes/DoE/Analysis_scripts_associated_with_manuscript,_\342\200\234Hydraulically-vulnerable_trees_survive_on_deep-water_access_during_droughts_in_a_tropical_forest\342\200\235.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Analysis scripts associated with \u201cHydraulically-vulnerable trees survive on deep-water access in a tropical forest community\u201d\n\nThis dataset contains R scripts for all the analyses to reproduce the manuscript, \u201cChitra-Tarak, Rutuja, Chonggang Xu, Kristina Anderson-Teixeira, Jeff Chambers, Matteo Detto, Boris Faybishenko, Rosie Fisher, Ryan Knox, Charlie Koven, Lara Kueppers, Nobert Kunert, Stefan J. Kupers, Nathan G. McDowell, Brent Newman, Steve Paton, Laurent Ruiz, Lawren Sack, Jeffrey Warren, Brett Wolfe, Cynthia Wright, S. Joseph Wright, Joseph Zailaa, Sean M. McMahon. Hydraulically-vulnerable trees survive on deep-water access in a tropical forest community. To be submitted\u201d. These scripts are divided into two parts: the first set of scripts prepare files for running and processing simulations from the model, Energy Exascale Earth System Land Model-Functionally Assembled Advanced Terrestrial simulator (ELM-FATES) to obtain soil water availability by depth at BCI, Panama, and the second set of scripts are associated with all the analyses related to the inverse modeling for tree rooting depths at BCI. ", + "laborHours": 0.0, + "languages": [], + "name": "Analysis scripts associated with manuscript, \u201cHydraulically-vulnerable trees survive on deep-water access during droughts in a tropical forest\u201d", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/bci.elm.fates.hydrology", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Analyst-Driven_Knowledge_Enhancement_&_Analysis_version_1.0.json b/agency-indexes/DoE/Analyst-Driven_Knowledge_Enhancement_&_Analysis_version_1.0.json new file mode 100644 index 00000000..fe0b5048 --- /dev/null +++ b/agency-indexes/DoE/Analyst-Driven_Knowledge_Enhancement_&_Analysis_version_1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "AKEA provides tools for the creation, maintenance, visualization, and analysis of information expressed in semantic graph form. It is capable of taking information expressed in unstructured text documents or structured data documents (e.g., spreadsheets, databases), ingesting it and extracting entities and relationships of interest, then presenting said information in graphical form. In addition, it contains tools for applying traditional social network analysis algorithms to the generated graphs in order to identify key players or entities with particular characteristics, geospatial and temporal visualization of said data, and user-controlled storage of information to support future analysis needs.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Analyst-Driven Knowledge Enhancement & Analysis version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Analytic_Deflection_of_Asteroids_by_NEDs.json b/agency-indexes/DoE/Analytic_Deflection_of_Asteroids_by_NEDs.json new file mode 100644 index 00000000..98de28be --- /dev/null +++ b/agency-indexes/DoE/Analytic_Deflection_of_Asteroids_by_NEDs.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-28", + "metadataLastUpdated": "2023-08-28" + }, + "description": "This package evaluates an analytic formula for the change in velocity imparted to an asteroid by a 1 or 2\nkeV black body source given the radius of the asteroid, the standoff distance, the x-ray yield, the density\nof the asteroid, and the fit coefficients for the 1 or 2 keV black body source (provided in the module).\nThree variations of the formula are given; the \"original\" form, the \"modified\" form that accounts for the\nangle of incidence in calculating the melt depth, and a form based on an \"impulse\" model.\nEach formula is fit to simulations of spherical asteroids of uniform composition illuminated by black body\nx-rays.", + "laborHours": 0.0, + "languages": [], + "name": "Analytic_Deflection_of_Asteroids_by_NEDs", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Analytic_Deflection_of_Asteroids_by_NEDs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Analytical_Tool_to_evaluate_Heterogeneous_Neuromorphic_Architectures__ATHENA_.json b/agency-indexes/DoE/Analytical_Tool_to_evaluate_Heterogeneous_Neuromorphic_Architectures__ATHENA_.json new file mode 100644 index 00000000..63895d7f --- /dev/null +++ b/agency-indexes/DoE/Analytical_Tool_to_evaluate_Heterogeneous_Neuromorphic_Architectures__ATHENA_.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-02" + }, + "description": "SAND2022-7062 O\nThe Analytical Tool to Evaluate Heterogeneous Neuromorphic Architectures (ATHENA) quickly evaluates performance metrics like energy, area, and latency for an AI/ML network. It currently supports the evaluation of analog neural networks. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 203832.0, + "languages": [ + "C++", + "Python" + ], + "name": "Analytical Tool to evaluate Heterogeneous Neuromorphic Architectures (ATHENA)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Analytics_for_Stream-Processing_Architecture_for_Real-time_Cyber-physical_Security__Analytic-SPARCS__v0.9.json b/agency-indexes/DoE/Analytics_for_Stream-Processing_Architecture_for_Real-time_Cyber-physical_Security__Analytic-SPARCS__v0.9.json new file mode 100644 index 00000000..7e2fab45 --- /dev/null +++ b/agency-indexes/DoE/Analytics_for_Stream-Processing_Architecture_for_Real-time_Cyber-physical_Security__Analytic-SPARCS__v0.9.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-11", + "metadataLastUpdated": "2019-09-24" + }, + "description": "This code is a set of modules designed to detect certain classes of cyber attacks against equipment in power distribution grid substations, including attacks against transformer tap changers and capacitor bank switches, as well as \"reconnaissance\" attacks against equipment in power grid substations.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1413.6, + "languages": [], + "name": "Analytics for Stream-Processing Architecture for Real-time Cyber-physical Security (Analytic-SPARCS) v0.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Anchor.json b/agency-indexes/DoE/Anchor.json new file mode 100644 index 00000000..5985ef88 --- /dev/null +++ b/agency-indexes/DoE/Anchor.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "vossjm@ornl.gov" + }, + "date": { + "created": "2020-11-03", + "metadataLastUpdated": "2020-11-03" + }, + "description": "Extensible diskless booting dracut module", + "laborHours": 1672.0, + "languages": [ + "Bash" + ], + "name": "Anchor", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/anchor", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Anchoring.json b/agency-indexes/DoE/Anchoring.json new file mode 100644 index 00000000..0829151a --- /dev/null +++ b/agency-indexes/DoE/Anchoring.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-31", + "metadataLastUpdated": "2025-03-31" + }, + "description": "This software provides methods and functions for training deep image classification models based on the\nprinciple of anchoring. It features a user-friendly PyTorch wrapper that facilitates the easy conversion of\nany model into an anchored model. The software supports various standard datasets and includes scripts\nfor conducting evaluations. Developed with PyTorch, it is compatible with common neural network\narchitectures used for image data. Additionally, it offers tools for computing evaluation metrics to assess\nmodel performance.", + "laborHours": 2872.8, + "languages": [], + "name": "Anchoring", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/anchoring", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AnisWave2D.json b/agency-indexes/DoE/AnisWave2D.json new file mode 100644 index 00000000..9bcd899f --- /dev/null +++ b/agency-indexes/DoE/AnisWave2D.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-25", + "metadataLastUpdated": "2019-07-25" + }, + "description": "AnisWave2D is a 2D finite-difference code for simulating seismic wave propagation in fully anisotropic materials. The code is implemented to run in parallel over multiple processors and is fully portable. A mesh refinement algorithm has been utilized to allow the grid-spacing to be tailored to the velocity model, avoiding the over-sampling of high-velocity materials that usually occurs in fixed-grid schemes.", + "laborHours": 0.0, + "languages": [], + "name": "AnisWave2D", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sainslie1966/AnisWave2D", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Anno_v1.json b/agency-indexes/DoE/Anno_v1.json new file mode 100644 index 00000000..bf0df317 --- /dev/null +++ b/agency-indexes/DoE/Anno_v1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-07", + "metadataLastUpdated": "2019-01-08" + }, + "description": "The Anno log annotation system provides tools for creating and querying annotations to supercomputing log data.", + "laborHours": 1109.6, + "languages": [], + "name": "Anno v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/agreiner/anno", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Anomalous_And_Normal_High_Performance_Computing_Datacenter_Activities.json b/agency-indexes/DoE/Anomalous_And_Normal_High_Performance_Computing_Datacenter_Activities.json new file mode 100644 index 00000000..1a97e8f0 --- /dev/null +++ b/agency-indexes/DoE/Anomalous_And_Normal_High_Performance_Computing_Datacenter_Activities.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-01-25", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This code provides annotation and an interface to 10+ hours of video activities in a high performance datacenter with 20+ different types of anomalous activities. The purpose is to enable machine learning for video surveillance systems in high performance computing centers. This is the first code of this type addressing the space of high performance computing datacenters.", + "laborHours": 0.0, + "languages": [], + "name": "Anomalous And Normal High Performance Computing Datacenter Activities", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HPCACT-2022", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ansible_Role:_chrony.json b/agency-indexes/DoE/Ansible_Role:_chrony.json new file mode 100644 index 00000000..916614e2 --- /dev/null +++ b/agency-indexes/DoE/Ansible_Role:_chrony.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "This Ansible role allows you to install chrony and manage its configuration.", + "laborHours": 0.0, + "languages": [], + "name": "Ansible Role: chrony", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ansible-role-chrony", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ansible_Role_for_Docker_CE__Community_Edition_.json b/agency-indexes/DoE/Ansible_Role_for_Docker_CE__Community_Edition_.json new file mode 100644 index 00000000..05262f1c --- /dev/null +++ b/agency-indexes/DoE/Ansible_Role_for_Docker_CE__Community_Edition_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-23", + "metadataLastUpdated": "2022-08-23" + }, + "description": "This Ansible role installs and configures Docker CE (Community Edition) on several different Linux distributions.", + "laborHours": 0.0, + "languages": [], + "name": "Ansible Role for Docker CE (Community Edition)", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ansible-role-docker-ce", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ant-Based_Cyber_Defense.json b/agency-indexes/DoE/Ant-Based_Cyber_Defense.json new file mode 100644 index 00000000..38a47b5e --- /dev/null +++ b/agency-indexes/DoE/Ant-Based_Cyber_Defense.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2025-04-14" + }, + "description": "ABCD is a four-level hierarchy with human supervisors at the top, a top-level agent called a Sergeant controlling each enclave, Sentinel agents located at each monitored host, and mobile Sensor agents that swarm through the enclaves to detect cyber malice and misconfigurations. The code comprises four parts: (1) the core agent framework, (2) the user interface and visualization, (3) test-range software to create a network of virtual machines including a simulated Internet and user and host activity emulation scripts, and (4) a test harness to allow the safe running of adversarial code within the framework of monitored virtual machines.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 371898.4, + "languages": [ + "Python 2.6 or later" + ], + "name": "Ant-Based Cyber Defense", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Application_Reporting_and_Termination_Utility_for_Windows.json b/agency-indexes/DoE/Application_Reporting_and_Termination_Utility_for_Windows.json new file mode 100644 index 00000000..6a67d4a8 --- /dev/null +++ b/agency-indexes/DoE/Application_Reporting_and_Termination_Utility_for_Windows.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-15" + }, + "description": "The Application Reporting and Termination Utility for Windows (terminate.exe) is a simple diagnostics and recovery tool designed to help LANDesk system administrators manage hung client applications on Windows systems. Terminate can either report on (tag) or stop (kill) a specified process on computers on which it is run. If KILL is specified, all processes that match the specified name and have a start time older than the specified minutes will be force stopped. If TAG is specified, all processes that match the name and have a start time older than the specified minutes will be reported to LANDesk inventory via the miniscan LANDesk client component.", + "laborHours": 364.8, + "languages": [], + "name": "Application Reporting and Termination Utility for Windows", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/david-frye/Terminate", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Application_of_Machine_Learning_for_Rechargeable_Lithium_Metal_Battery_Design_and_performance_prediction.json b/agency-indexes/DoE/Application_of_Machine_Learning_for_Rechargeable_Lithium_Metal_Battery_Design_and_performance_prediction.json new file mode 100644 index 00000000..1b91482f --- /dev/null +++ b/agency-indexes/DoE/Application_of_Machine_Learning_for_Rechargeable_Lithium_Metal_Battery_Design_and_performance_prediction.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-04-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Rechargeable lithium metal batteries are being intensively studied in recent years because of their high energy density which potentially could double the cell energy of state-of-art Li-ion batteries. However, cell design of realistic high-energy Li metal batteries is quite different with Li-ion batteries, not mentioning prediction of cycle life. A powerful software using machine learning will greatly accelerate academic research and industry battery manufacturing process.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Application of Machine Learning for Rechargeable Lithium Metal Battery Design and performance prediction", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Aprepro_-_Algebraic_Preprocessor.json b/agency-indexes/DoE/Aprepro_-_Algebraic_Preprocessor.json new file mode 100644 index 00000000..09326fb2 --- /dev/null +++ b/agency-indexes/DoE/Aprepro_-_Algebraic_Preprocessor.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Aprepro is an algebraic preprocessor that reads a file containing both general text and algebraic, string, or conditional expressions. It interprets the expressions and outputs them to the output file along with the general text. Aprepro contains several mathematical functions, string functions, and flow control constructs. In addition, functions are included that, with some additional files, implement a units conversion system and a material database lookup system.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "Aprepro - Algebraic Preprocessor", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AqNWB_v0.1.json b/agency-indexes/DoE/AqNWB_v0.1.json new file mode 100644 index 00000000..0bb7f5fb --- /dev/null +++ b/agency-indexes/DoE/AqNWB_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "This is a C ++ acquisition API for neurophysiological data in the NeurodataWithoutBorders (NWB) data standard.", + "laborHours": 1869.6, + "languages": [], + "name": "AqNWB v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NeurodataWithoutBorders/aqnwb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Aquapv.json b/agency-indexes/DoE/Aquapv.json new file mode 100644 index 00000000..abe9e25d --- /dev/null +++ b/agency-indexes/DoE/Aquapv.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2024-01-15", + "metadataLastUpdated": "2024-02-06" + }, + "description": "This project brings together a multidisciplinary team to develop tools and analysis that will help U.S. industry accelerate deployment of floating PV on reservoirs and estuaries through producing:\n\u2022\tA tool to assess potential environmental interactions of FPV on reservoirs and estuaries and thresholds for corresponding impacts.\n\u2022\tA tailored FPV-specific techno-economic tool to guide users on financial performance and corresponding design considerations.\n\u2022\tA synthesized tool, AquaPV, that combines the environmental and economic tools.\n\u2022\tA set of case studies on an open-loop reservoir with a traditional hydropower plant (i.e., connected to a natural waterbody), closed-loop reservoir with a proposed pumped storage hydropower plant (i.e., manmade and disconnected from a natural waterbody), and a marine estuary (i.e., where a river meets the ocean), with an FPV system designed and modeled for each site.\n\u2022\tA review of regulatory, environmental, and stakeholder opportunities and challenges to identify clear regulatory and environmental pathways to siting FPV on U.S. reservoirs.\n\u2022\tA novel, high-fidelity geospatial resource assessment to estimate FPV technical potential on reservoirs in the United States.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Aquapv", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/AquaPV", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Aquatic_Acoustic_Metrics_Interface.json b/agency-indexes/DoE/Aquatic_Acoustic_Metrics_Interface.json new file mode 100644 index 00000000..3e00ad3b --- /dev/null +++ b/agency-indexes/DoE/Aquatic_Acoustic_Metrics_Interface.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Fishes and marine mammals may suffer a range of potential effects from exposure to intense underwater sound generated by anthropogenic activities such as pile driving, shipping, sonars, and underwater blasting. Several underwater sound recording (USR) devices have been built to acquire samples of the underwater sound generated by anthropogenic activities. Software becomes indispensable for processing and analyzing the audio files recorded by these USRs. The new Aquatic Acoustic Metrics Interface Utility Software (AAMI) is specifically designed for analysis of underwater sound recordings to provide data in metrics that facilitate evaluation of the potential impacts of the sound on aquatic animals. In addition to the basic functions, such as loading and editing audio files recorded by USRs and batch processing of sound files, the software utilizes recording system calibration data to compute important parameters in physical units. The software also facilitates comparison of the noise sound sample metrics with biological measures such as audiograms of the sensitivity of aquatic animals to the sound, integrating various components into a single analytical frame.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab" + ], + "name": "Aquatic Acoustic Metrics Interface", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Arbitrary_State_Preparation_via_Quantum_Walks_Software.json b/agency-indexes/DoE/Arbitrary_State_Preparation_via_Quantum_Walks_Software.json new file mode 100644 index 00000000..5b528496 --- /dev/null +++ b/agency-indexes/DoE/Arbitrary_State_Preparation_via_Quantum_Walks_Software.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SF-24-077 Our software generates a circuit that prepares a specified target quantum state. It generates circuits with CNOT counts of O(mn), where m is the number of nonzero amplitudes of the state and n is the number of qubits. The method does not require ancillas. It is designed for sparse states, but works for any quantum state. Our method is based on the new perspective of dynamic continuous time quantum walks for quantum state preparation. This is an intuitive perspective where a graph is \nfirst constructed to traverse the basis states. The method works by 1.) construct a graph of the basis states, 2.) transform the graph into quantum walks, and 3.) construct the final gate based \ncircuit optimized with our control reduction method.", + "laborHours": 243.2, + "languages": [], + "name": "Arbitrary State Preparation via Quantum Walks Software", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GaidaiIgor/quantum_walks", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ArborX.json b/agency-indexes/DoE/ArborX.json new file mode 100644 index 00000000..b3e3ae25 --- /dev/null +++ b/agency-indexes/DoE/ArborX.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "prokopenkoav@ornl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2025-04-17" + }, + "description": "ArborX library tackles a problem of efficiently finding geometric objects that are close in space. Variations of this problem, such as finding the nearest neighbors of a point, or finding all objects within a certain distance, are inherent components of applications in many fields. The data may be large so that solving the problem efficiently may require significant computational resources, such as multiple processors or accelerators such as general purpose GPUs.\n\nArborX' main advantage in its ability to solve large problems efficiently utilizing a combination of distributed and on-node parallelism. ArborX can be run efficiently on a wide variety of hardware, including GPUs from different vendors, which distinguishes it from other available libraries which typically choose only few of these. The other advantage is that it supports both types of user problems: spatial problems (useful for intersections and finding objects within certain distance), and nearest neighbor problems. ArborX also supports flexible interface in its interaction with a user. Particularly, it allows a user to call user's own function on a positive match, a functionality not rarely available in other libraries.\n\nArborX implements construction and traversal algorithms using efficient tree structures, such as bounding volume hierarchy (BVH). At its core, it uses linear BVH for its low construction cost and sufficient quality. ArborX is written using C++, and is parallelized using the message passing interface (MPI) for the distributed communication, and the Kokkos library for on-node parallelism. This approach allows ArborX to be run on a wide variety of hardware, from common laptops and desktops to supercomputers while using the same codebase. ArborX also implements several advanced algorithms using geometric search, such as density-based clustering algorithm DBSCAN.", + "laborHours": 16492.0, + "languages": [ + "C++" + ], + "name": "ArborX", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/arborx/ArborX", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ArborX_2.0.json b/agency-indexes/DoE/ArborX_2.0.json new file mode 100644 index 00000000..ba953a67 --- /dev/null +++ b/agency-indexes/DoE/ArborX_2.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "prokopenkoav@ornl.gov" + }, + "date": { + "created": "2025-04-16", + "metadataLastUpdated": "2025-04-17" + }, + "description": "ArborX library tackles a problem of efficiently finding geometric objects that are close in space. Variations of this problem, such as finding the nearest neighbors of a point, or finding all objects within a certain distance, are inherent components of applications in many fields. The data may be large so that solving the problem efficiently may require significant computational resources, such as multiple processors or accelerators such as general purpose GPUs. ArborX' main advantage in its ability to solve large problems efficiently utilizing a combination of distributed and on-node parallelism. ArborX can be run efficiently on a wide variety of hardware, including GPUs from different vendors, which distinguishes it from other available libraries which typically choose only few of these. The other advantage is that it supports both types of user problems: spatial problems (useful for intersections and finding objects within certain distance), and nearest neighbor problems. ArborX also supports flexible interface in its interaction with a user. Particularly, it allows a user to call user's own function on a positive match, a functionality not rarely available in other libraries. ArborX implements construction and traversal algorithms using efficient tree structures, such as bounding volume hierarchy (BVH). At its core, ArborX uses linear BVH for its low construction cost and sufficient quality. ArborX implements both spatial and nearest-neighbor traversal algorithms. ArborX also provides several clustering algorithms (minimum spanning tree, DBSCAN, HDBSCAN*), interpolation using minimum least squares and ray tracing. ArborX is written using C++, and is parallelized using the message passing interface (MPI) for the distributed communication, and the Kokkos library for on-node parallelism. This approach allows ArborX to be run on a wide variety of hardware, from common laptops and desktops to supercomputers while using the same codebase.", + "laborHours": 16492.0, + "languages": [ + "C++" + ], + "name": "ArborX 2.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/arborx/ArborX", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Archer.json b/agency-indexes/DoE/Archer.json new file mode 100644 index 00000000..a51819bf --- /dev/null +++ b/agency-indexes/DoE/Archer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-16" + }, + "description": "Archer is a data race detector for OpenMP programs.\nArcher combines static and dynamic techniques to identify data races in large OpenMP applications, leading to low runtime and memory overheads, while still offering high accuracy and precision. It builds on open-source tools infrastructure such as LLVM, ThreadSanitizer, and OMPT to provide portability.", + "laborHours": 2903.2, + "languages": [], + "name": "Archer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PRUNERS/archer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Architector.json b/agency-indexes/DoE/Architector.json new file mode 100644 index 00000000..b055ab39 --- /dev/null +++ b/agency-indexes/DoE/Architector.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-04", + "metadataLastUpdated": "2023-01-04" + }, + "description": "Architector is a 3D chemical structure generation software package designed to take minimal 2D information about ligands and metal centers and generates chemically sensible 3D conformers and stereochemistry of the organometallic compounds. Architector is capable of high-throughput in-silico construction of s-, p-, d-, and f-block organometallic complexes. Architector represents a transformative step towards cross-periodic table computational design of metal complex chemistry.", + "laborHours": 0.0, + "languages": [], + "name": "Architector", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Architector", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Architecture_for_Quantum_Time-dependent_Circuits__ArQTIC__v1.0.json b/agency-indexes/DoE/Architecture_for_Quantum_Time-dependent_Circuits__ArQTIC__v1.0.json new file mode 100644 index 00000000..7dc81789 --- /dev/null +++ b/agency-indexes/DoE/Architecture_for_Quantum_Time-dependent_Circuits__ArQTIC__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-21", + "metadataLastUpdated": "2021-04-21" + }, + "description": "ArQTiC is a domain-specific full-stack software package built for the dynamic simulations of materials on quantum computers. Its main contributions include providing a software library for high-level programming of such simulations on quantum computers, and providing post-processing capabilities that allow users to more efficiently analyze results from the quantum computer. Paired with the power to optimize and execute quantum circuits, ArQTiC opens the field of dynamic materials simulations on quantum computers to a broader community of scientists from a wider range of domain sciences, paving the way for accelerated progress towards physical quantum supremacy.", + "laborHours": 0.0, + "languages": [], + "name": "Architecture for Quantum Time-dependent Circuits (ArQTIC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lebassman/ArQTiC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Archparse.json b/agency-indexes/DoE/Archparse.json new file mode 100644 index 00000000..133bebd8 --- /dev/null +++ b/agency-indexes/DoE/Archparse.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-11-15", + "metadataLastUpdated": "2021-11-16" + }, + "description": "Archparse is a Python package that holds the purpose and capability of converting the contents of a text file to a functioning neural network based on the Tensorflow 2.X framework. This is able to be done with minimal written Python code and next to no knowledge of how to build models with Tensorflow directly. More specifically Archparse parses a text file with extension \".arch\" which contains neural network architecture information that corresponds to either the Tensorflow 2.X API or custom code written with the Tensorflow 2.X API. Included in the initial version is the capacity to easily produce sequential autoencoders and sequential neural networks.", + "laborHours": 0.0, + "languages": [], + "name": "Archparse", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EnderWiggin14/ARCHPARSE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Arcus_v._1.0.json b/agency-indexes/DoE/Arcus_v._1.0.json new file mode 100644 index 00000000..44be370c --- /dev/null +++ b/agency-indexes/DoE/Arcus_v._1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Arcus is a library developed and used within an internally developed network configuration tool. Arcus is being open sourced not the configuration tool.", + "laborHours": 4301.6, + "languages": [ + "C#", + "Powershell" + ], + "name": "Arcus v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/arcus", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ard_[SWR-25-18].json b/agency-indexes/DoE/Ard_[SWR-25-18].json new file mode 100644 index 00000000..947233fa --- /dev/null +++ b/agency-indexes/DoE/Ard_[SWR-25-18].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-01-08", + "metadataLastUpdated": "2025-01-08" + }, + "description": "A wind farm optimization suite for wind energy that is built for modular, gradient-enabled multi-disciplinary and multi-fidelity optimizations.\n\nDig into wind farm design.\n\nAn ard is a type of simple and lightweight plow, used through the single-digit centuries to prepare a farm for planting. The intent of Ard is to be a modular, full-stack multi-disciplinary optimization tool for wind farms.\n\nThe problem with wind farms is that they are complicated, multi-disciplinary objects. They are aerodynamic machines, with complicated control systems, power electronic devices, social and political objects, and the core value (and cost) of complicated financial instruments. Moreover, the design of one of these aspects affects all the rest!\n\nArd seeks to make plant-level design choices that can incorporate these different aspects and their interactions to make wind energy projects more successful.", + "laborHours": 1504.8, + "languages": [ + "Python", + "Jupyter Notebook", + "Shell" + ], + "name": "Ard [SWR-25-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/Ard", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Area_Values_from_Image_Dimensions__AVID__v._3.json b/agency-indexes/DoE/Area_Values_from_Image_Dimensions__AVID__v._3.json new file mode 100644 index 00000000..a2f0ba90 --- /dev/null +++ b/agency-indexes/DoE/Area_Values_from_Image_Dimensions__AVID__v._3.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-10-04", + "metadataLastUpdated": "2018-10-09" + }, + "description": "This code processes the images collected during high throughput tensile tests to measure the area of each specimen. First, the code identifies the reference images and primary sample images from list of images collected. Then, the size of the reference in the reference images is used to determine a scale (um/pixel) value which can be used to determine the size of each sample in an image. The subsequent sample images are processed to automatically detect the sample present and then identify the size in pixels. The measurements from two different views of the sample are then combined to determine the sample area (um2). ", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 228.0, + "languages": [ + "MATLAB" + ], + "name": "Area Values from Image Dimensions (AVID) v. 3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Argo_containers.json b/agency-indexes/DoE/Argo_containers.json new file mode 100644 index 00000000..57a119ae --- /dev/null +++ b/agency-indexes/DoE/Argo_containers.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "Argo Containers are a resource isolation facility built on top of the cgroup interface of the Linux kernel.These are not your typical containers. We do not support namespaces, chroot or any of the usual \"virtualization\" facilities regularly associated with\ncontainers. Instead, we focus on the ability to limit how a group of process can access the cpu, memory and other resources of the system.", + "laborHours": 3572.0, + "languages": [], + "name": "Argo containers", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://xgitlab.cels.anl.gov/argo/containers", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Argobots.json b/agency-indexes/DoE/Argobots.json new file mode 100644 index 00000000..4a3f136d --- /dev/null +++ b/agency-indexes/DoE/Argobots.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "Argobots is a lightweight, low-level threading and tasking framework. ", + "laborHours": 32436.8, + "languages": [], + "name": "Argobots", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pmodels/argobots/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/argobots", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Aries_Network_Performance_Counters_Monitoring_Library.json b/agency-indexes/DoE/Aries_Network_Performance_Counters_Monitoring_Library.json new file mode 100644 index 00000000..fd369aa9 --- /dev/null +++ b/agency-indexes/DoE/Aries_Network_Performance_Counters_Monitoring_Library.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "AriesNCL is a library to monitor and record network router tile performance counters on the Aries router of Cray's Cascade/XC30 platform.", + "laborHours": 152.0, + "name": "Aries Network Performance Counters Monitoring Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ariesncl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Arion.json b/agency-indexes/DoE/Arion.json new file mode 100644 index 00000000..1154a847 --- /dev/null +++ b/agency-indexes/DoE/Arion.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-03-21" + }, + "description": "Arion is a library and tool set that enables researchers to holistically define test system models. To define a complex system for testing an algorithm or control requires expertise across multiple domains. Simulating a complex system requires the integration of multiple simulators and test hardware, each with their own specification languages and concepts. This requires extensive set of knowledge and capabilities. Arion was developed to alleviate this challenge. Arion is a library of Java libraries that abstracts the concepts from supported simulators into a cohesive model language that allows someone to build models to their needed level of fidelity and expertise. Arion is also a software tool that translates the users model back into the specification languages of the simulators and test hardware needed for execution.", + "laborHours": 10016.8, + "languages": [], + "name": "Arion", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/arion/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/arion", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Aristos_Optimization_Package.json b/agency-indexes/DoE/Aristos_Optimization_Package.json new file mode 100644 index 00000000..15088d83 --- /dev/null +++ b/agency-indexes/DoE/Aristos_Optimization_Package.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Aristos is a Trilinos package for nonlinear continuous optimization, based on full-space sequential quadratic programming (SQP) methods. Aristos is specifically designed for the solution of large-scale constrained optimization problems in which the linearized constraint equations require iterative (i.e. inexact) linear solver techniques. Aristos' unique feature is an efficient handling of inexactness in linear system solves. Aristos currently supports the solution of equality-constrained convex and nonconvex optimization problems. It has been used successfully in the area of PDE-constrained optimization, for the solution of nonlinear optimal control, optimal design, and inverse problems.", + "laborHours": 8344830.4, + "name": "Aristos Optimization Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ascent.json b/agency-indexes/DoE/Ascent.json new file mode 100644 index 00000000..cad4f220 --- /dev/null +++ b/agency-indexes/DoE/Ascent.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "A flyweight in situ visualization and analysis runtime for multi-physics HPC simulations.", + "laborHours": 213514.4, + "languages": [], + "name": "Ascent", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/Alpine-DAV/ascent/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Alpine-DAV/ascent", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Aspenplus_Model_For_Msw_Sorting_Process.json b/agency-indexes/DoE/Aspenplus_Model_For_Msw_Sorting_Process.json new file mode 100644 index 00000000..227fb174 --- /dev/null +++ b/agency-indexes/DoE/Aspenplus_Model_For_Msw_Sorting_Process.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Unit operations for the MSW sorting process include shredding, magnets for ferrous separation, screening, air classification, eddy current for non-ferrous separation, and near-infrared detection for plastic recovery. The MIXCINC module within Aspen Plus was selected to handle mixed solid streams containing inert (metals and glass) and non-conventional materials (paper, plastics, biomass, organic waste). The Peng-Robinson equation of state with Boston-Mathias modifications was applied to predict properties for a nonconventional solids mix. Enthalpy and density of the non-conventional materials were defined using non-conventional material properties.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Aspenplus Model For Msw Sorting Process", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/AspenPlus", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AssemblyAPI.json b/agency-indexes/DoE/AssemblyAPI.json new file mode 100644 index 00000000..7a1e61be --- /dev/null +++ b/agency-indexes/DoE/AssemblyAPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-13", + "metadataLastUpdated": "2020-08-13" + }, + "description": "Data API for Assembly Object.", + "laborHours": 1307.2, + "languages": [], + "name": "AssemblyAPI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/assembly_api", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AssemblySequenceAPI.json b/agency-indexes/DoE/AssemblySequenceAPI.json new file mode 100644 index 00000000..6b93dd93 --- /dev/null +++ b/agency-indexes/DoE/AssemblySequenceAPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "This is the repository for \"AssemblySequenceAPI\" developed by KBase. ", + "laborHours": 442912.8, + "languages": [], + "name": "AssemblySequenceAPI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/AssemblySequenceAPI", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AssemblyUtil.json b/agency-indexes/DoE/AssemblyUtil.json new file mode 100644 index 00000000..dc5374bb --- /dev/null +++ b/agency-indexes/DoE/AssemblyUtil.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "Set of KBase functions for interacting with Assemblies and ContigSets using the KBase data_api.", + "laborHours": 165953.6, + "languages": [], + "name": "AssemblyUtil", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/AssemblyUtil", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Assembly_Service.json b/agency-indexes/DoE/Assembly_Service.json new file mode 100644 index 00000000..f7c6fda3 --- /dev/null +++ b/agency-indexes/DoE/Assembly_Service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-18", + "metadataLastUpdated": "2020-08-18" + }, + "description": "An extensible framework for genome assembly. This is a service to assemble genomes and metagenomes with user's choice of assembly software. It currently supports more than 20 assemblers and processing modules.", + "laborHours": 8861.6, + "languages": [], + "name": "Assembly Service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/assembly", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Assert_v2.0.0.json b/agency-indexes/DoE/Assert_v2.0.0.json new file mode 100644 index 00000000..42188194 --- /dev/null +++ b/agency-indexes/DoE/Assert_v2.0.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "dobonachea@lbl.gov" + }, + "date": { + "created": "2025-04-04", + "metadataLastUpdated": "2025-04-04" + }, + "description": "A Fortran utility for the run-time checking of program requirements and for providing diagnostic error output inside pure procedures", + "laborHours": 699.2, + "languages": [ + "Fortran" + ], + "name": "Assert v2.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/berkeleylab/assert", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "2.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Asset_Score_API.json b/agency-indexes/DoE/Asset_Score_API.json new file mode 100644 index 00000000..0656a69e --- /dev/null +++ b/agency-indexes/DoE/Asset_Score_API.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-11-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Asset Score Preview API Test Harness is PHP code that will be made publicly accessible to software developers\nsupporting the DOE commercial energy scoring efforts. Asset Score is a DOE funded web-based application that enables cities to interactively describe commercial buildings, identify assets that would affect the energy footprint of the building, and use the Asset Score models (FEDS, Open Studio) to determine the approximate energy score.", + "homepageURL": "https://buildingenergyscore.energy.gov", + "laborHours": 0.0, + "languages": [], + "name": "Asset Score API", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://buildingenergyscore.energy.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Associated_Particle_Imaging_for_Carbon__APIC__v1.json b/agency-indexes/DoE/Associated_Particle_Imaging_for_Carbon__APIC__v1.json new file mode 100644 index 00000000..27e272c6 --- /dev/null +++ b/agency-indexes/DoE/Associated_Particle_Imaging_for_Carbon__APIC__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2021-09-07" + }, + "description": "The software is used to control an Associated Particle Imaging (API) imaging system that can measure the 3d carbon distribution in soil. Furthermore, the software is used to analyze the data from the instrument.", + "homepageURL": "https://ibt.lbl.gov/projects/software", + "laborHours": 0.0, + "languages": [], + "name": "Associated Particle Imaging for Carbon (APIC) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ibt.lbl.gov/projects/software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ibt.lbl.gov/projects/software", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Assured_Timing_Detector.json b/agency-indexes/DoE/Assured_Timing_Detector.json new file mode 100644 index 00000000..4902755e --- /dev/null +++ b/agency-indexes/DoE/Assured_Timing_Detector.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-09-26", + "metadataLastUpdated": "2022-09-26" + }, + "description": "The Assured Timing Detector software provides an implementation in C++ of an adaptable, model-based system for monitoring a timing signal for anomalies versus a reference time source ensemble", + "laborHours": 0.0, + "languages": [], + "name": "Assured Timing Detector", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ATD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Assured_Timing_Detector_-_Status_Display.json b/agency-indexes/DoE/Assured_Timing_Detector_-_Status_Display.json new file mode 100644 index 00000000..a17ce088 --- /dev/null +++ b/agency-indexes/DoE/Assured_Timing_Detector_-_Status_Display.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-09-26", + "metadataLastUpdated": "2022-09-26" + }, + "description": "The Assured Timing Detector Status Display allows for Web browser hosted monitoring of system health and annunciation of timing anomaly alerts reported by the companion Assured Timing Detector software.", + "laborHours": 0.0, + "languages": [], + "name": "Assured Timing Detector - Status Display", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ATD-SD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Asynchronous_I_O_VOL_Connector__AsyncVOL__v0.1.json b/agency-indexes/DoE/Asynchronous_I_O_VOL_Connector__AsyncVOL__v0.1.json new file mode 100644 index 00000000..90d73b3a --- /dev/null +++ b/agency-indexes/DoE/Asynchronous_I_O_VOL_Connector__AsyncVOL__v0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-08-18", + "metadataLastUpdated": "2020-08-18" + }, + "description": "Asynchronous I/O is becoming increasingly popular with the large amount of data access required by scientific applications. They can take advantage of an asynchronous interface by scheduling I/O as early as possible and overlap computation or communication with I/O operations, which hides the cost associated with I/O and improves the overall performance.", + "laborHours": 0.0, + "languages": [], + "name": "Asynchronous I/O VOL Connector (AsyncVOL) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.hdfgroup.org/scm/hdf5vol/async.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Asynchronous_Transfer_Library.json b/agency-indexes/DoE/Asynchronous_Transfer_Library.json new file mode 100644 index 00000000..361bb01f --- /dev/null +++ b/agency-indexes/DoE/Asynchronous_Transfer_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-07-20", + "metadataLastUpdated": "2018-07-20" + }, + "description": "AXL provides a common C interface to many vendor-specific NVM technologies. In addition, AXL provides a synchronous transfer method. We expect this component to be reused by the VeloC and SCR software packages. ", + "laborHours": 1276.8, + "languages": [], + "name": "Asynchronous Transfer Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-VeloC/AXL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Athena_-_Digital_Twin_and_Infrastructure_Model_[SWR_20-106].json b/agency-indexes/DoE/Athena_-_Digital_Twin_and_Infrastructure_Model_[SWR_20-106].json new file mode 100644 index 00000000..a113d35a --- /dev/null +++ b/agency-indexes/DoE/Athena_-_Digital_Twin_and_Infrastructure_Model_[SWR_20-106].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-02-25", + "metadataLastUpdated": "2023-06-01" + }, + "description": "The software provides database access and analysis code for project ATHENA data. In particular, it provides (1) access to the AWS RDS database and (2) supporting code for analysis. Additionally, the software contains all the code related to modeling the Dallas-Fort Worth International Airport (DFW) curbside (CTA modeling) using SUMO simulator. It demonstrates how to install, run and derive useful data from SUMO simulations. We will describe the basic files needed to run a simulation and how those files are generated. The software also has code for generating simulations representing different traffic management policies for DFW and simulating those policies on personal computer or on NREL's Eagle supercomputer. The examples provided are a representation of the DFW airport for curbside dropoff and and pickup.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "Athena - Digital Twin and Infrastructure Model [SWR 20-106]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/athena-forecast", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Athena_-_Shuttle_Bus_Optimization_and_Event_Driven_Simulator_[SWR_20-105].json b/agency-indexes/DoE/Athena_-_Shuttle_Bus_Optimization_and_Event_Driven_Simulator_[SWR_20-105].json new file mode 100644 index 00000000..66944e46 --- /dev/null +++ b/agency-indexes/DoE/Athena_-_Shuttle_Bus_Optimization_and_Event_Driven_Simulator_[SWR_20-105].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-02-25", + "metadataLastUpdated": "2023-06-01" + }, + "description": "The primary purpose of the software is to optimize shuttle routes to and from terminals, given some airport campus location like the rental car center. This code was developed as part of the DOE funded Athena project. One aspect of the Athena project was to investigate if the optimization of shuttle routes that move passengers to and from the five DFW terminals and the rental car center could result in lower energy consumption from the shuttle fleet while still maintaining an acceptable level of service to passengers. Hence, the optimization done by the code determines a set of shuttle routes, the type of shuttle on each route, and the number of shuttles servicing each route. The optimization aims to make these choices in a way that the energy consumption per hour by the fleet is minimized.\n\nAdditionally, the software can fast simulate airport shuttle operations with collected data. The simulation inputs are passenger arrival rates, shuttle routes and frequencies, and simulation configurations. The outputs include: time dependent shuttle energy level, time dependent charging station usage, time dependent number of passengers on each bus, time dependent number of passengers at each bus stop, history of number of passengers left at each bus stop, route history of fleet shuttle buses and on-demand buses, and time dependent bus distance traveled.", + "laborHours": 0.0, + "languages": [], + "name": "Athena - Shuttle Bus Optimization and Event Driven Simulator [SWR 20-105]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/athena-bus", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Atlas_Multimedia_Educational_Lab_for_Interactive_Analysis.json b/agency-indexes/DoE/Atlas_Multimedia_Educational_Lab_for_Interactive_Analysis.json new file mode 100644 index 00000000..21da485c --- /dev/null +++ b/agency-indexes/DoE/Atlas_Multimedia_Educational_Lab_for_Interactive_Analysis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "AMELIA is an application with focus on particle physics processes in ATLAS. This will allow students and other users to decode the collision events that unfold after the head-on collisions of protons at the Large hadron Collider. AMELIA uses the Irrlicht engine for the 3D graphics and wxWidgets for the interface. It uses the best aspects of technical animation and allows users to control 3D representations of collision events and to manipulate 3D models of the detector and see how particles are detected as they pass through. It allows the user to rotate, zoom and select virtual pieces of the ATLAS detector and events. The characteristics of the events (momentum etc.) can also be read, and one can select tracks for analysis, activate context-oriented media, etc. This framework intends to integrate different types of media into a single product. This way, videos, animations, sound, interactive visualization and data analysis will be bound together in the same package.-", + "homepageURL": "https://sourceforge.net/projects/amelia", + "laborHours": 0.0, + "languages": [], + "name": "Atlas Multimedia Educational Lab for Interactive Analysis", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/amelia", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Atom_Modeling_PipeLine.json b/agency-indexes/DoE/Atom_Modeling_PipeLine.json new file mode 100644 index 00000000..676805a2 --- /dev/null +++ b/agency-indexes/DoE/Atom_Modeling_PipeLine.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-11", + "metadataLastUpdated": "2019-12-11" + }, + "description": "This repository contains code for the computational framework to build ML models for drug discovery\npurposes. \n\nOur end-to-end pipeline extracts features from model-ready datasets and trains and saves the model to our model zoo or to disk.\n\nOur pipeline generates a variety of molecular features and both shallow and deep ML models.\n\nThe HPC-specific module we have developed conducts efficient parallelized search of the model hyperparameter space and reports the best-performing hyperparameters for each of these feature/model combinations.", + "laborHours": 34656.0, + "languages": [], + "name": "Atom Modeling PipeLine", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ATOMconsortium/AMPL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Atom_Trajectory_Viewer.json b/agency-indexes/DoE/Atom_Trajectory_Viewer.json new file mode 100644 index 00000000..1f93ad6f --- /dev/null +++ b/agency-indexes/DoE/Atom_Trajectory_Viewer.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Atom Trajectory Viewer is a visualization tool developed to enable interactive exploration of atomic trajectories and corresponding statistics in molecular dynamics.", + "laborHours": 12996.0, + "name": "Atom Trajectory Viewer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bhatiaharsh/TrajectoryExplorer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Atreyu.json b/agency-indexes/DoE/Atreyu.json new file mode 100644 index 00000000..d233ff1f --- /dev/null +++ b/agency-indexes/DoE/Atreyu.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Ion mobility mass spectrometry data viewer and extractor, targeted toward PNNL's UIMF files", + "laborHours": 49065.6, + "languages": [], + "name": "Atreyu", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Atreyu", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Attend_and_Decode:_4D_fMRI_Task_State_Decoding_Using_Attention_Models.json b/agency-indexes/DoE/Attend_and_Decode:_4D_fMRI_Task_State_Decoding_Using_Attention_Models.json new file mode 100644 index 00000000..cd8f13d1 --- /dev/null +++ b/agency-indexes/DoE/Attend_and_Decode:_4D_fMRI_Task_State_Decoding_Using_Attention_Models.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "Source code for Brain Attend and Decode paper. Functional magnetic resonance imaging (fMRI) is a neuroimaging modality that captures the blood oxygen level in a subject's brain while the subject either rests or performs a variety of functional tasks under different conditions. Given fMRI data, the problem of inferring the task, known as task state decoding, is challenging due to the high dimensionality (hundreds of million sampling points per datum) and complex spatio-temporal blood flow patterns inherent in the data. In this work, we propose to tackle the fMRI task state decoding problem by casting it as a 4D spatiotemporal classification problem. We present a novel architecture called Brain Attend and Decode (BAnD), that uses residual convolutional neural networks for spatial feature extraction and self-attention mechanisms for temporal modeling. We achieve significant performance gain compared to previous works on a 7-task benchmark from the large-scale Human Connectome Project-Young Adult (HCP-YA) dataset. We also investigate the transferability of BAnD's extracted features on unseen HCP tasks, either by freezing the spatial feature extraction layers and retraining the temporal model, or finetuning the entire model. The pre-trained features from BAnD are useful on similar tasks while finetuning them yields competitive results on unseen tasks/conditions.", + "laborHours": 0.0, + "languages": [], + "name": "Attend and Decode: 4D fMRI Task State Decoding Using Attention Models", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/BAnD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1." +} \ No newline at end of file diff --git a/agency-indexes/DoE/Auto-BLAST__AutoBLAST__[SWR-20-93].json b/agency-indexes/DoE/Auto-BLAST__AutoBLAST__[SWR-20-93].json new file mode 100644 index 00000000..f4a23464 --- /dev/null +++ b/agency-indexes/DoE/Auto-BLAST__AutoBLAST__[SWR-20-93].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-07-06", + "metadataLastUpdated": "2024-10-16" + }, + "description": "Battery life modeling often involves a lot of manual parameter fitting and is not easy for users to adopt the model and use it. To reduce the difficulties for users to adopt battery lifetime models, an automatic battery lifetime modeling analysis and simulation tool suite, Auto-BLAST, has been developed. Auto-BLAST includes a lithium-loss-base life model, a battery electric model, and an algorithm which automatically fits all key parameters in the electric and life models using user provided data. The models and algorithm are packaged into two user-friendly GUIs, Auto-LifeMod, for easy battery life prognostic model fitting and Auto-LifeSim, for easy battery lifetime simulation. The lithium-loss-based life model adopts a similar model framework that models degradations using aging rate models, using battery cycling data to predict battery degradation and expected lifetime. The electric model is an equivalent circuit model which simulates battery voltage responses based on current/power demand profiles. The auto-fitting algorithm uses the user-input data to generate custom battery life model(s). Two GUIs, wrapping around the life model and the auto-fitting algorithm, provide friendly interfaces for users to generate a life model and use it for case study. One GUI requires summary data from accelerated battery life degradation tests as an input and produces battery life models predicting (a) capacity degradation, and (b) resistance growth of the battery. The GUI displays the electrical model response and the input experimental data against the life model predictions with fitted model parameters and fitting error. The GUI also generates an output file to save the fitted model parameters. The second GUI uses the life model from the first GUI and a user-defined battery cycling profile to predict battery lifetime degradation and expected lifetime. Predicted capacity and resistance vs. time are plotted in the GUI and saved to output file. There is a user guide for both GUIs", + "homepageURL": "https://labpartnering.org/technologies/a298da24-0625-42a8-9693-a81d839529d7", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Auto-BLAST (AutoBLAST) [SWR-20-93]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://labpartnering.org/technologies/a298da24-0625-42a8-9693-a81d839529d7", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://labpartnering.org/technologies/a298da24-0625-42a8-9693-a81d839529d7", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Auto-Versioning_Systems_Image_Manager.json b/agency-indexes/DoE/Auto-Versioning_Systems_Image_Manager.json new file mode 100644 index 00000000..7ae01099 --- /dev/null +++ b/agency-indexes/DoE/Auto-Versioning_Systems_Image_Manager.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The av_sys_image_mgr utility provides an interface for the creation, manipulation, and analysis of system boot images for computer systems. It is primarily intended to provide a convenient method for managing the introduction of changes to boot images for long-lived production HPC systems.", + "laborHours": 60.8, + "name": "Auto-Versioning Systems Image Manager", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NERSC/avs_image_mgr/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/avs_image_mgr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AutoBEM-DynamicArchetypes.json b/agency-indexes/DoE/AutoBEM-DynamicArchetypes.json new file mode 100644 index 00000000..52bf68f8 --- /dev/null +++ b/agency-indexes/DoE/AutoBEM-DynamicArchetypes.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "bassbc@ornl.gov" + }, + "date": { + "created": "2022-01-10", + "metadataLastUpdated": "2022-01-10" + }, + "description": "Automatic Building Energy Modeling (AutoBEM, https://bit.ly/AutoBEM) has been used to create an OpenStudio and EnergyPlus building energy model of 122.9 million U.S. buildings (https://bit.ly/ModelAmerica). Simulating and analyzing a model of every building for large areas (e.g. cities) is often not feasible. This dynamic archetyping capability uses a representative building and calculates a floor-space multiplier that allows millions of buildings to be represented by less than 100 buildings. This script (WRF_Archetypes_Parallel.py) calculates these building archetypes for each of the grid cells from a Weather Research and Forecasting (WRF) model in a parallel fashion. The script works by looping through each of the grid cells in the shapefile in parallel, spatially joining the building metadata table to each grid cell, aggregating relevant archetypes and calculating necessary statistics related to area and number of buildings in each cell. The output is a table (.csv) in which each row is an archetype building with properties about that building as well as statistics that relate that building to the total cell (such as an area multiplier). The following inputs are required: WRF zone shapefile (.shp) (wrf-grids-origin_Vegas_Select_100.geojson) The projection of the shapefile (\"EPSG:XXXX\") Input table containing building metadata for area corresponding to shapefile (.csv) (https://zenodo.org/record/4552901#.YZQEotDMJPY - ClarkCounty2.csv) The number of cores that will be parallelized (integer) The output file name for the archetype table (.csv) Sample command line inputs: python3 ~/WRF_Archetypes_Parallel.py -i ~/wrf-grids-origin_Vegas_Select_100.geojson -c ~/ClarkCounty2.csv -o ~/OutputArchetypes.csv -j 72 -e EPSG:4326 Using Geopandas Version 0.9.0", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "AutoBEM-DynamicArchetypes", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-BTRIC/AutoBEM-DynamicArchetypes", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AutoCSM.json b/agency-indexes/DoE/AutoCSM.json new file mode 100644 index 00000000..2ec392f2 --- /dev/null +++ b/agency-indexes/DoE/AutoCSM.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "greenwoodms@ornl.gov" + }, + "date": { + "created": "2024-09-05", + "metadataLastUpdated": "2024-09-05" + }, + "description": "A template system-of-systems modeling approach for\nautomating the development, deployment, and integration of cooling system models (CSMs) for supercomputing facilities within the ExaDigiT framework.\n\nAutoCSM is a Python-based framework to assist in CSM developers in accelerating the creation and deployment of system-level thermal-hydraulic CSMs. The intention is for this tool specifically to help standardize digital twin workflows for ExaDigiT. However, this tool can be used independent of ExaDigiT (and even other systems besides CSMs).", + "laborHours": 532.0, + "languages": [ + "Python", + "Modelica" + ], + "name": "AutoCSM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/exadigit/AutoCSM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AutoEM.json b/agency-indexes/DoE/AutoEM.json new file mode 100644 index 00000000..f12f77de --- /dev/null +++ b/agency-indexes/DoE/AutoEM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-17", + "metadataLastUpdated": "2025-04-17" + }, + "description": "AutoEM is a software application intended to fully automate EM experiments. This automation includes incorporation of a\nMachine Learning component that will provide feedback analysis and experiment modification in a fully hands-free\nmanner. AutoEM incorporates control of multiple devices, communication with external applications, and user visualization\nof images, device status, and ML feedback.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 425.6, + "languages": [], + "name": "AutoEM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/AutoParBench.json b/agency-indexes/DoE/AutoParBench.json new file mode 100644 index 00000000..ce2fbc26 --- /dev/null +++ b/agency-indexes/DoE/AutoParBench.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-27", + "metadataLastUpdated": "2020-01-27" + }, + "description": "AutoParBench is a benchmark framework to evaluate compilers and tools designed to automatically insert\nOpenMP directives. \n\nThe goal is to generate actional information (bug reports and feature requests) for compiler and tool developers.\n\nWe also want to drive the research for automatic parallelization using OpenMP and make OpenMP more declarative to reduce the burdens on OpenMP users.", + "laborHours": 209866.4, + "languages": [], + "name": "AutoParBench", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/autoparbench", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Auto_PDI.json b/agency-indexes/DoE/Auto_PDI.json new file mode 100644 index 00000000..b4bdda2b --- /dev/null +++ b/agency-indexes/DoE/Auto_PDI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Protein-DNA Interaction Workflow (PDI Workflow), a pipeline that focuses on generating\nhigh-quality docking and molecular dynamics simulations for Protein-DNA complexes. This allows us to take DNA\nsequences with unknown tertiary structures, accurately predict their structure, dock them with the desired target protein,\nand then simulate their interactions using molecular dynamics simulations", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Auto_PDI", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Autodataman.json b/agency-indexes/DoE/Autodataman.json new file mode 100644 index 00000000..e1784a06 --- /dev/null +++ b/agency-indexes/DoE/Autodataman.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-11-18", + "metadataLastUpdated": "2022-11-18" + }, + "description": "The autodataman tool is intended to be a very lightweight climate data database and data distribution engine.", + "laborHours": 0.0, + "languages": [], + "name": "Autodataman", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmecmetrics/autodataman", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/AutodiDAQt_v1.1.0.json b/agency-indexes/DoE/AutodiDAQt_v1.1.0.json new file mode 100644 index 00000000..0fd95339 --- /dev/null +++ b/agency-indexes/DoE/AutodiDAQt_v1.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "\tAutodiDAQt automates and simplifies writing data acquisition software for spectroscopy and microscopy. After defining only how to communicate with instruments and hardware, autodiDAQt generates user interfaces for long running acquisition applications, handlings data collation and retention, and provides remote communication to analysis computers. This reduces the time to get experiments running from months to hours and increases reliability for scientific experiments.\n\nAutodiDAQt metaprograms from instrument drivers directly, where possible.", + "laborHours": 0.0, + "languages": [], + "name": "AutodiDAQt v1.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chstan/autodiDAQt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Autodidactic_VB-GMM_for_Multispectral_Microscopy_Data.json b/agency-indexes/DoE/Autodidactic_VB-GMM_for_Multispectral_Microscopy_Data.json new file mode 100644 index 00000000..f2d85a98 --- /dev/null +++ b/agency-indexes/DoE/Autodidactic_VB-GMM_for_Multispectral_Microscopy_Data.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "39s@ornl.gov" + }, + "date": { + "created": "2022-01-10", + "metadataLastUpdated": "2022-01-10" + }, + "description": "Software attempts to detect, estimate the composition, and segment phases from Energy Dispersive Spectroscopy datasets. ", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Autodidactic VB-GMM for Multispectral Microscopy Data", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esrah-ap-niht/Microscopy-VB-GMM", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Autoencoder_Node_Saliency.json b/agency-indexes/DoE/Autoencoder_Node_Saliency.json new file mode 100644 index 00000000..2bf67577 --- /dev/null +++ b/agency-indexes/DoE/Autoencoder_Node_Saliency.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-07-31", + "metadataLastUpdated": "2018-07-31" + }, + "description": "Autoencoder node saliency (ANS) is a novel method intended to explain the lenrning tasks perfonned in the hidden layer of an autoencoder. ANS ranks the hidden nodes based on their ability to perfonn a given learning task. It identifies the hidden node that best distinguishes between two classes of data points. The weights from the identified hidden nodes correspond to original features that contribute to the data differentiation.", + "laborHours": 106.4, + "languages": [], + "name": "Autoencoder Node Saliency", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ANS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automata-based_Debugging_for_Dissimilar_Parallel_Tasks.json b/agency-indexes/DoE/Automata-based_Debugging_for_Dissimilar_Parallel_Tasks.json new file mode 100644 index 00000000..d1fc4ea6 --- /dev/null +++ b/agency-indexes/DoE/Automata-based_Debugging_for_Dissimilar_Parallel_Tasks.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "AutomaDeD is a tool that automatically diagnoses performance and correctness faults in MPI applications. It creates time and control-flow models of processes in an MPI program, and when a failure occus, these models are analyzed probabilistically to find the origin of the failure. The output of the tool is MPI processes ranked by the abnormality degree and regions of code where faults are first manifested. The granularity of code region is an MPI call or a computation region between two MPI calls.", + "laborHours": 6308.0, + "name": "Automata-based Debugging for Dissimilar Parallel Tasks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/automaDeD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automated_Biochemical_Reaction_Coder__Reactionizer__v1.json b/agency-indexes/DoE/Automated_Biochemical_Reaction_Coder__Reactionizer__v1.json new file mode 100644 index 00000000..07f63512 --- /dev/null +++ b/agency-indexes/DoE/Automated_Biochemical_Reaction_Coder__Reactionizer__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-24", + "metadataLastUpdated": "2019-01-24" + }, + "description": "An algorithm that infers the reaction SMARTS pattern for a biochemical reaction, given an atom-atom mapped reaction input. The algorithm can create patterns of variable specificity, depending on user needs. The SMARTS patterns can be used to computationally assess hypothetical biochemical reactions that would generate hypothetical or novel compounds. If all known compounds are run through all known SMARTS, a theoretical biochemical reaction network could be formed for biological discovery purposes.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 866.4, + "languages": [], + "name": "Automated Biochemical Reaction Coder (Reactionizer) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automated_CT_registration,_segmentation,_and_quantification__AutoCT__v1.0.json b/agency-indexes/DoE/Automated_CT_registration,_segmentation,_and_quantification__AutoCT__v1.0.json new file mode 100644 index 00000000..4d9c1001 --- /dev/null +++ b/agency-indexes/DoE/Automated_CT_registration,_segmentation,_and_quantification__AutoCT__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-05-27" + }, + "description": "Processing and analyzing brain imaging is crucial in both scientific development and clinical field. In this software package, we build a pipeline that integrates automatic registration, segmentation, and quantitative analysis for subjects' CT scans. Leveraging diffeomorphic transformations, we enable optimized forward and inverse mappings between an image and the reference. Furthermore, we extract localized features from deformation field based on an online template process, which advances statistical learning downstream. The created templates, atlas as well as our methods provide the brain imaging community tools for AI implementations.", + "laborHours": 0.0, + "languages": [], + "name": "Automated CT registration, segmentation, and quantification (AutoCT) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/LBL_TBI/autoct", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automated_CT_registration,_segmentation,_and_quantification__AutoCT__v1.1.json b/agency-indexes/DoE/Automated_CT_registration,_segmentation,_and_quantification__AutoCT__v1.1.json new file mode 100644 index 00000000..17da86e2 --- /dev/null +++ b/agency-indexes/DoE/Automated_CT_registration,_segmentation,_and_quantification__AutoCT__v1.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-07", + "metadataLastUpdated": "2021-10-07" + }, + "description": "Processing and analyzing brain imaging is crucial in both scientific development and clinical field. In this software package, we build a pipeline that integrates automatic registration, segmentation, and quantitative analysis for subjects' CT scans. Leveraging diffeomorphic transofrmations, we enable optimized forward and inverse mappings between an image and the reference. Furthermore, we extract localized features from deformation field based on an online template process, which advances statistical learning downstream. The created templates, atlas as well as our methods provide the brain imaging community tools for AI implementations", + "laborHours": 0.0, + "languages": [], + "name": "Automated CT registration, segmentation, and quantification (AutoCT) v1.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/LBL_TBI/autoct/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automated_J-R_Curve_Analysis_Based_on_the_ASTM_E1820_Normalization_Method.json b/agency-indexes/DoE/Automated_J-R_Curve_Analysis_Based_on_the_ASTM_E1820_Normalization_Method.json new file mode 100644 index 00000000..9bbc4832 --- /dev/null +++ b/agency-indexes/DoE/Automated_J-R_Curve_Analysis_Based_on_the_ASTM_E1820_Normalization_Method.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The J-integral vs. crack growth resistance curve (J-R curve) is a useful tool for evaluating material fracture toughness in the ductile condition. A widely accepted practice for conducting tests to obtain J-R curves is ASTM standard E1820, in which the normalization method was introduced as an alternative method for determining the J-R curve. The normalization method requires solely force-displacement data, together with initial and final crack size measurements from a specimen to derive the J-R curve. Because of the elimination of the compliance measurement, the normalization method significantly simplifies testing requirements to obtain J-R curve. Despite these advantages, the analysis procedures of the normalization method are quite complicated to follow, which may limit the wide application of this method. To address this, we have developed a software with user-friendly graphic interface to perform automated normalization analysis. Any users, even without detailed knowledge of the normalization analysis, can use this software to derive J-R curves based on the ASTM E1820 normalization method.", + "laborHours": 4301.6, + "languages": [ + "MATLAB" + ], + "name": "Automated J-R Curve Analysis Based on the ASTM E1820 Normalization Method", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/xc8/ANJR", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/xc8/ANJR", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automated_Pre-processing_for_NMR_Assignments_with_Reduced_Tedium.json b/agency-indexes/DoE/Automated_Pre-processing_for_NMR_Assignments_with_Reduced_Tedium.json new file mode 100644 index 00000000..fe1f3274 --- /dev/null +++ b/agency-indexes/DoE/Automated_Pre-processing_for_NMR_Assignments_with_Reduced_Tedium.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "An important rate-limiting step in the resonance assignment process is accurate identification of resonance peaks in MNR spectra. NMR spectra are noisy. Hence, automatic peak-picking programs must navigate between the Scylla of reliable but incomplete picking, and the Charybdis of noisy but complete picking. Each of these extremes complicates the assignment process: incomplete peak-picking results in the loss of essential connectivities, while noisy picking conceals the true connectivities under a combinatiorial explosion of false positives. Intermediate processing can simplify the assignment process by preferentially removing false peaks from noisy peak lists. This is accomplished by requiring consensus between multiple NMR experiments, exploiting a priori information about NMR spectra, and drawing on empirical statistical distributions of chemical shift extracted from the BioMagResBank. Experienced NMR practitioners currently apply many of these techniques \"by hand\", which is tedious, and may appear arbitrary to the novice. To increase efficiency, we have created a systematic and automated approach to this process, known as APART. Automated pre-processing has three main advantages: reduced tedium, standardization, and pedagogy. In the hands of experienced spectroscopists, the main advantage is reduced tedium (a rapid increase in the ratio of true peaks to false peaks with minimal effort). When a project is passed from hand to hand, the main advantage is standardization. APART automatically documents the peak filtering process by archiving its original recommendations, the accompanying justifications, and whether a user accepted or overrode a given filtering recommendation. In the hands of a novice, this tool can reduce the stumbling block of learning to differentiate between real peaks and noise, by providing real-time examples of how such decisions are made.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [], + "name": "Automated Pre-processing for NMR Assignments with Reduced Tedium", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automated_Quantification_of_Cyclic_Voltammetry_Reactions.json b/agency-indexes/DoE/Automated_Quantification_of_Cyclic_Voltammetry_Reactions.json new file mode 100644 index 00000000..d1d24b62 --- /dev/null +++ b/agency-indexes/DoE/Automated_Quantification_of_Cyclic_Voltammetry_Reactions.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2025-02-24" + }, + "description": "This algorithm can process small or large (>1000 curves) batches of data and output arrays with the reduction peak start,\nend, halfway point, and area in each curve in a file of the user's choice", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 532.0, + "languages": [], + "name": "Automated Quantification of Cyclic Voltammetry Reactions", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automated_Recommendation_Tool__ART__v2.0.json b/agency-indexes/DoE/Automated_Recommendation_Tool__ART__v2.0.json new file mode 100644 index 00000000..f73796b1 --- /dev/null +++ b/agency-indexes/DoE/Automated_Recommendation_Tool__ART__v2.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-07", + "metadataLastUpdated": "2021-04-07" + }, + "description": "Mention other applications, bayesian inference + machine learning", + "homepageURL": "https://github.com/JBEI/ART#license", + "laborHours": 0.0, + "languages": [], + "name": "Automated Recommendation Tool (ART) v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://github.com/JBEI/ART#license", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automated_Registration_of_Vector_Data_to_Overhead_Imagery.json b/agency-indexes/DoE/Automated_Registration_of_Vector_Data_to_Overhead_Imagery.json new file mode 100644 index 00000000..0c991a29 --- /dev/null +++ b/agency-indexes/DoE/Automated_Registration_of_Vector_Data_to_Overhead_Imagery.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "laverdiereml@ornl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "Python script to automate the alignment of vector data to target, high-resolution images. Each feature of the vector dataset is iterated and compared to the target image. The pixels surrounding the feature in the target image are extracted and are converted to gray-scale, denoised, followed by line extraction. A cross-correlation is calculated between the original feature and the extracted lines. The pixel with the highest score is recorded and the offset between the location of the highest pixel and the feature centroid is calculated. This essentially calculates a displacement vector for each feature. This offset is then applied to the original feature geometry to properly align it with the target image.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Automated Registration of Vector Data to Overhead Imagery", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ChuckDoug/featureshift", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automated_System-Level_Model_Validation_for_Central_America.json b/agency-indexes/DoE/Automated_System-Level_Model_Validation_for_Central_America.json new file mode 100644 index 00000000..1cd5f61f --- /dev/null +++ b/agency-indexes/DoE/Automated_System-Level_Model_Validation_for_Central_America.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL is developing an automated procedure to perform the system-level model validation for the Central America power grid, which includes six countries and one power system equivalent model for Mexico representation is also considered. The specific features for this invention are given as follows: 1) Automated case integration of Mexico equivalent model and Central America grid model\u037e 2) Automated power system event replay based on system-level dynamic simulations\u037e 3) Automated extraction and comparison of power flow conditions/measurements/quantities between SCADA/PMU data and simulated data for pre-event, during event and post-event stages\u037e 4) One procedure to identify potential mismatch in power flow conditions and erroneous model parameters in power system dynamic models.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Automated System-Level Model Validation for Central America", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automated_Testing_System.json b/agency-indexes/DoE/Automated_Testing_System.json new file mode 100644 index 00000000..5caf10ce --- /dev/null +++ b/agency-indexes/DoE/Automated_Testing_System.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The Automated Testing System (ATS) is an open-source, Python-based tool for automating the running of tests of an application across a broad range of high performance computers.", + "laborHours": 0.0, + "languages": [], + "name": "Automated Testing System", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ATS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automated_ToF-SIMS_PCA_Analysis_Tool.json b/agency-indexes/DoE/Automated_ToF-SIMS_PCA_Analysis_Tool.json new file mode 100644 index 00000000..d55f8815 --- /dev/null +++ b/agency-indexes/DoE/Automated_ToF-SIMS_PCA_Analysis_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-07-09", + "metadataLastUpdated": "2024-07-09" + }, + "description": "Python software package for PCA analysis of ToF-SIMS spectra data", + "laborHours": 805.6, + "languages": [], + "name": "Automated ToF-SIMS PCA Analysis Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pca-analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automated_deduction_for_first-order_logic_with_equality.json b/agency-indexes/DoE/Automated_deduction_for_first-order_logic_with_equality.json new file mode 100644 index 00000000..53606800 --- /dev/null +++ b/agency-indexes/DoE/Automated_deduction_for_first-order_logic_with_equality.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "Otter 3.3 is the current version of ANL's automated deduction system designed to search for proofs and countermodels of conjectures stated in first-order logic with equality. It is used mostly for research in mathematics and logic and also for various applications requiring deductive data processing.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Automated deduction for first-order logic with equality", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automatic_Building_Feature_Extraction_Toolkit__AutoBFE__v1.0.json b/agency-indexes/DoE/Automatic_Building_Feature_Extraction_Toolkit__AutoBFE__v1.0.json new file mode 100644 index 00000000..c9921700 --- /dev/null +++ b/agency-indexes/DoE/Automatic_Building_Feature_Extraction_Toolkit__AutoBFE__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-01", + "metadataLastUpdated": "2021-04-01" + }, + "description": "In recent years advances in the performance of machine learning methods have considerably improved the ability to accurately extract information from images. Identification of building characteristics from imagery is an example of an application that is time consuming and costly to perform manually, and where automatic feature extraction holds great promise. A major contribution of the work conducted in this project is the provision of open, transparent, and replicable solutions for buildings features extraction from images (e.g., satellite/aerial images). In this first version of the toolkit we are focussing on extracting building footprints from satellite/aerial images using state of the art deep learning image segmentation algorithms.", + "laborHours": 0.0, + "languages": [], + "name": "Automatic Building Feature Extraction Toolkit (AutoBFE) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/AutoBFE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automatic_Compartments_for_Embedded_Systems.json b/agency-indexes/DoE/Automatic_Compartments_for_Embedded_Systems.json new file mode 100644 index 00000000..2f6735f2 --- /dev/null +++ b/agency-indexes/DoE/Automatic_Compartments_for_Embedded_Systems.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2024-07-19" + }, + "description": "ACES is a modified version of LLVM for ARMv7-M micro controllers that enables automatic application of compartments to bare-metal system code. It breaks the single monolithic binary of these systems into multiple execution domains using a developer selected policy. This increases the difficulty of compromising the entire system, as the data, code, and peripherals accessible at any given point in execution limited to the subset identified by the policy.", + "laborHours": 1070247.2, + "languages": [ + "C++", + "Shell", + "HTML", + "C", + "Assembly", + "Rich Text Format" + ], + "name": "Automatic Compartments for Embedded Systems", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/ACES?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ACES", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automatic_Differentiation_Package.json b/agency-indexes/DoE/Automatic_Differentiation_Package.json new file mode 100644 index 00000000..3adbdc25 --- /dev/null +++ b/agency-indexes/DoE/Automatic_Differentiation_Package.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Sacado is an automatic differentiation package for C++ codes using operator overloading and C++ templating. Sacado provide forward, reverse, and Taylor polynomial automatic differentiation classes and utilities for incorporating these classes into C++ codes. Users can compute derivatives of computations arising in engineering and scientific applications, including nonlinear equation solving, time integration, sensitivity analysis, stability analysis, optimization and uncertainity quantification.", + "laborHours": 8344830.4, + "name": "Automatic Differentiation Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automatic_Multiple_Experiment_Simulation_and_Fitting__Ames-Fit_.json b/agency-indexes/DoE/Automatic_Multiple_Experiment_Simulation_and_Fitting__Ames-Fit_.json new file mode 100644 index 00000000..258dca29 --- /dev/null +++ b/agency-indexes/DoE/Automatic_Multiple_Experiment_Simulation_and_Fitting__Ames-Fit_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2024-06-11", + "metadataLastUpdated": "2024-06-17" + }, + "description": "AMES-Fit is a program used to automatically fit the multi-field solid-state NMR spectra of half-integer quadrupolar nuclei. Due to the high dimensional space, gradient algorithms have failed to address the fitting of such data, which is at present done manually. AMES-Fit diverges from these approaches by using an adaptive step size random search algorithm to fit the NMR spectra to consistently find the global best fit parameters.", + "laborHours": 1140.0, + "languages": [ + "C++" + ], + "name": "Automatic Multiple Experiment Simulation and Fitting (Ames-Fit)", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fperras/AMES-Fit", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automatic_Report_Generator__ARG_.json b/agency-indexes/DoE/Automatic_Report_Generator__ARG_.json new file mode 100644 index 00000000..5dbf7092 --- /dev/null +++ b/agency-indexes/DoE/Automatic_Report_Generator__ARG_.json @@ -0,0 +1,40 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-08-07" + }, + "description": "ARG is a computational simulation tool. It generates user-configurable reports, including graphs and images, from user data in various formats.SAND2019-9525 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 10366.4, + "languages": [ + "TeX", + "Perl", + "Python" + ], + "name": "Automatic Report Generator (ARG)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/arg", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automatic_Residential_Commercial_Classification_of_Parcels_with_Solar_Panel_Detections.json b/agency-indexes/DoE/Automatic_Residential_Commercial_Classification_of_Parcels_with_Solar_Panel_Detections.json new file mode 100644 index 00000000..a11b36d4 --- /dev/null +++ b/agency-indexes/DoE/Automatic_Residential_Commercial_Classification_of_Parcels_with_Solar_Panel_Detections.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "A computational method to automatically detect solar panels on rooftops to aid policy and financial assessment of solar distributed generation. The code automatically classifies parcels containing solar panels in the U.S. as residential or commercial. The code allows the user to specify an input dataset containing parcels and detected solar panels, and then uses information about the parcels and solar panels to automatically classify the rooftops as residential or commercial using machine learning techniques. The zip file containing the code includes sample input and output datasets for the Boston and DC areas.", + "laborHours": 197.6, + "languages": [ + "R/NA/3.4.0" + ], + "name": "Automatic Residential/Commercial Classification of Parcels with Solar Panel Detections", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/nset-ornl/ornlsolar/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nset-ornl/ornlsolar", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automatic_Tool_for_Local_Assembly_Structures.json b/agency-indexes/DoE/Automatic_Tool_for_Local_Assembly_Structures.json new file mode 100644 index 00000000..ff7c6e23 --- /dev/null +++ b/agency-indexes/DoE/Automatic_Tool_for_Local_Assembly_Structures.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Whole community shotgun sequencing of total DNA (i.e. metagenomics) and total RNA (i.e. metatranscriptomics) has provided a wealth of information in the microbial community structure, predicted functions, metabolic networks, and is even able to reconstruct complete genomes directly. Here we present ATLAS (Automatic Tool for Local Assembly Structures) a comprehensive pipeline for assembly, annotation, genomic binning of metagenomic and metatranscriptomic data with an integrated framework for Multi-Omics. This will provide an open source tool for the Multi-Omic community at large.", + "laborHours": 4438.4, + "name": "Automatic Tool for Local Assembly Structures", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/atlas", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automating_Data_Collection_with_Large_Language_Models:_Summarization_and_CSV_Generation.json b/agency-indexes/DoE/Automating_Data_Collection_with_Large_Language_Models:_Summarization_and_CSV_Generation.json new file mode 100644 index 00000000..d0ceb6b6 --- /dev/null +++ b/agency-indexes/DoE/Automating_Data_Collection_with_Large_Language_Models:_Summarization_and_CSV_Generation.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "klaskyhb@ornl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "The program summarizer.py is the product of the 'Automating Data Collection with Large Language Models (LLMs): Summarization and CSV Generation' project. This project aims to automate data collection from Internet content using LLMs. This project integrates zero-shot learning concepts, as the agents were not previously trained on the particular subjects of the inputted sources, and Retrieval Augmented Generation (RAG).\nThis summarizer program summarizes characteristics of the URL sources which are specified by the user. As written, the program identifies six characteristics of the inputs: source_name, source_creator, source_url, source_overview, source_data, and number_of_datapoints. However, this program is designed to be highly generalizable, so throughout the code, docstrings specify what parameters and variables should be changed for the user to utilize this program on their own inputs and characteristics. This repository contains example outputs for two datasets: one on the health effects of air pollutions and one on congenital heart defects.", + "laborHours": 258.4, + "languages": [ + "Python" + ], + "name": "Automating Data Collection with Large Language Models: Summarization and CSV Generation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/summer_2024/summarization", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "Summer 2024" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automation_Tool_to_Create_Chronological_AC_Power_Flow_Cases_for_Large_Interconnected_Systems.json b/agency-indexes/DoE/Automation_Tool_to_Create_Chronological_AC_Power_Flow_Cases_for_Large_Interconnected_Systems.json new file mode 100644 index 00000000..585af954 --- /dev/null +++ b/agency-indexes/DoE/Automation_Tool_to_Create_Chronological_AC_Power_Flow_Cases_for_Large_Interconnected_Systems.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Combining planning models with operational details allows the industry to proactively investigate future resource and load scenarios, rather than react to their implementation in real time. In this project, the following tasks are proposed. The methodologies we developed to resolve current challenges in importing and solving the chronological AC power flow is a three-stage process.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Automation Tool to Create Chronological AC Power Flow Cases for Large Interconnected Systems", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automaton_&_Cognition.json b/agency-indexes/DoE/Automaton_&_Cognition.json new file mode 100644 index 00000000..0f0816cb --- /dev/null +++ b/agency-indexes/DoE/Automaton_&_Cognition.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-06-20", + "metadataLastUpdated": "2023-06-20" + }, + "description": "AutoCog is a framework to design programming models (PM) for language models (LM). It permits\nresearchers to devise Cognitive Architectures where traditional Artificial Intelligence algorithms are\nexecuted by Language Models.", + "laborHours": 0.0, + "languages": [], + "name": "Automaton & Cognition", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AutoCog", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Automobile_and_Technology_Lifecycle-Based_Assignment__ATLAS__v2.0.12.json b/agency-indexes/DoE/Automobile_and_Technology_Lifecycle-Based_Assignment__ATLAS__v2.0.12.json new file mode 100644 index 00000000..1aba8ccc --- /dev/null +++ b/agency-indexes/DoE/Automobile_and_Technology_Lifecycle-Based_Assignment__ATLAS__v2.0.12.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ATLAS is a comprehensive vehicle transaction and technology adoption microsimulator. ATLAS evolves the fleet mix of individual households by simulating the transaction (vehicle addition, disposal, and replacement) and choice (vehicle type, vintage, powertrain, and tenure) decisions in response to the co-evolving demographics, land use, and vehicle technology simulations. Different from the existing vehicle models that are either static or aggregated (e.g. stock model), ATLAS is fully disaggregated and dynamic following a sequential and circumstantial decision-making trajectory. This fine-grained approach not only enhances the realism of the simulation but also provides a nuanced understanding of the dynamics inherent in vehicle fleet evolution. ATLAS outputs are fully compatible with subsequent agent-based transportation modeling system and can enable distributional effect analysis regarding the fleet turnover among heterogeneous populations. ATLAS expands the typical new sale focused vehicle choice modeling to including used vehicle transactions that are of increasing interests to understanding the vehicle adoption behavior among lower income households.", + "laborHours": 2173.6, + "languages": [], + "name": "Automobile and Technology Lifecycle-Based Assignment (ATLAS) v2.0.12", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-science-it/atlas-release", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Autonomous_MultiScale_Library.json b/agency-indexes/DoE/Autonomous_MultiScale_Library.json new file mode 100644 index 00000000..6d37a29b --- /dev/null +++ b/agency-indexes/DoE/Autonomous_MultiScale_Library.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-07-21", + "metadataLastUpdated": "2023-07-25" + }, + "description": "AMSLib provides infrastructure to tightly couple multi-scale physics simulation code with ML surrogate\nmodel inference. It provides a wholistic runtime execution paradigm to supports uncertainty quantification,\nsurrogate model inference, persistent data storing throughout the execution of a simulation.", + "laborHours": 0.0, + "languages": [], + "name": "Autonomous MultiScale Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.0.alpha" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Autosampler_software.json b/agency-indexes/DoE/Autosampler_software.json new file mode 100644 index 00000000..bd8c54be --- /dev/null +++ b/agency-indexes/DoE/Autosampler_software.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "control software for an automated liquid chromatography sample injection and\nseparation system. It is related to a PNNL invention report 31630-E, Method for direct delivering trace samples from smallsize\nwells to liquid chromatography and mass spectrometry. The main purpose of the control software is to enable\nautomated sample injection from a nanowell device.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Autosampler software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Autotune.json b/agency-indexes/DoE/Autotune.json new file mode 100644 index 00000000..0c55bb76 --- /dev/null +++ b/agency-indexes/DoE/Autotune.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Autotune software code uses an island-based evolutionary algorithm to solve multi-objective optimization problems. For the code provided, this has been applied to the whole-building simulation engine EnergyPlus to allow a software description of a building to be calibrated to measured data.", + "laborHours": 7068.0, + "name": "Autotune", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-BTRIC/Autotune/blob/master/LICENCE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-BTRIC/Autotune", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Avalaunch.json b/agency-indexes/DoE/Avalaunch.json new file mode 100644 index 00000000..7881c324 --- /dev/null +++ b/agency-indexes/DoE/Avalaunch.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Avalaunch implements a tree-based process launcher. It first bootstraps itself on to a set of compute nodes by launching children processes, which immediately connect back to the parent process to acquire info needed t launch their own children. Once the tree is established, user processes are started by broadcasting commands and application binaries through the tree. All communication flows over high-performance network protocols via spawnnet. The goal is to start MPI jobs having hundreds of thousands of processes within seconds.", + "laborHours": 21371.2, + "name": "Avalaunch", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/avalaunch/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/avalaunch", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Avatar_Tools.json b/agency-indexes/DoE/Avatar_Tools.json new file mode 100644 index 00000000..93362f9c --- /dev/null +++ b/agency-indexes/DoE/Avatar_Tools.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2021-01-13" + }, + "description": "Supervised machine learning is the process of using past experience to predict the future. \"Ensembles\" are a machine-learning meta-method that can be applied to most machine learning algorithms. Ensembles generally greatly improve accuracy, reduce or remove most of the design issues presented by machine learning, and are admirably suited to parallel and distributed computation. The Avatar Tools codes are an implementation of ensembles specifically for decision trees. Some features that distinguish Avatar Tools from other \"ensembles for decision trees\" codes are: (1) Does the bookkeeping necessary for out of bag (OOB) validation. (2) Can use OOB validation to automatically determine optimal ensemble size. (3) Provides an MPI-based parallel implementation, for distributed operation. (4) Provides convenient tools for cross-validation, to assess the accuracy provided by a training set. SAND2020-3858 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C", + "Python" + ], + "name": "Avatar Tools", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/avatar", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Aviation_Security_Screening_Optimizer_for_Risk_and_ThroughputASSORT.json b/agency-indexes/DoE/Aviation_Security_Screening_Optimizer_for_Risk_and_ThroughputASSORT.json new file mode 100644 index 00000000..6cbe80c3 --- /dev/null +++ b/agency-indexes/DoE/Aviation_Security_Screening_Optimizer_for_Risk_and_ThroughputASSORT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-14", + "metadataLastUpdated": "2025-02-24" + }, + "description": "The Aviation Security Screening Optimizer for Risk and Throughput (ASSORT) is designed to assess risk-based\napproaches for passenger screening and checkpoint operations. Additionally, ASSORT is exploring various traveler\ncategories \u2014 general, trusted, and trusted-plus \u2014 along with different checkpoint screening Concept of Operations\ntailored to each traveler type", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 1200.8, + "languages": [], + "name": "Aviation Security Screening Optimizer for Risk and ThroughputASSORT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Axolotl:_a_scalable_genomics_library_based_on_Apache_Spark__Axolotl__v1.0.0.json b/agency-indexes/DoE/Axolotl:_a_scalable_genomics_library_based_on_Apache_Spark__Axolotl__v1.0.0.json new file mode 100644 index 00000000..ec9b8fb1 --- /dev/null +++ b/agency-indexes/DoE/Axolotl:_a_scalable_genomics_library_based_on_Apache_Spark__Axolotl__v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2024-06-12", + "metadataLastUpdated": "2024-06-12" + }, + "description": "Axolotl is a Python library for scalable distributed genome and metagenome data analysis. Existing tools and systems that we rely on are struggling to keep up with the rapid explosion of genomic data. Compounding this issue, developing scalable solutions require a steep learning curve in parallel programming, which presents a barrier to academic researchers. While we do have scalable solutions for specific tasks, we lack comprehensive, end-to-end solutions. It's this gap in our toolkit that we aim to address with Axolotl. The Axolotl library is built for easy parallel processing, efficiently handling multiple tasks or large datasets simultaneously, and scaling up to meet the demands of extensive genomic data analysis.", + "laborHours": 2158.4, + "languages": [], + "name": "Axolotl: a scalable genomics library based on Apache Spark (Axolotl) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGI-Bioinformatics/axolotl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Axom.json b/agency-indexes/DoE/Axom.json new file mode 100644 index 00000000..20765770 --- /dev/null +++ b/agency-indexes/DoE/Axom.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-09-15", + "metadataLastUpdated": "2021-09-15" + }, + "description": "Axom is an open-source library of \"building block\" software components that provide core infrastructure capabilities for HPC applications. Such capabilities include: input file parsing and verification for various file formats, format specification for material shape input to multi-material simulations and tools for placing those shapes on meshes, parallel distributed coordination of diagnostic messages, geometric primitives, spatial queries and spatial search acceleration data structures, in memory key-value data store for managing simulation data and parallel file I/O. Axom components are used widely across LLNL Advanced Simulation and Computing program applications. It is also part of the LLNL institutionally-supported RADIUSS project, which promotes and funds its adoption by projects across LLNL.", + "laborHours": 229945.6, + "languages": [], + "name": "Axom", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/axom", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.6.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/B.MPI3.json b/agency-indexes/DoE/B.MPI3.json new file mode 100644 index 00000000..c9786104 --- /dev/null +++ b/agency-indexes/DoE/B.MPI3.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-03", + "metadataLastUpdated": "2021-02-04" + }, + "description": "B.MPI3 is a C++ library wrapper for standard MPI-3. B.MPI3 is designed following the principles of Boost\nand the STL. B.MPI3 is unrelated to the official, now deprecated, MPI-C++ interface. It provides an iterator-based interface and MPI-3 features (RMA and Shared memory). B.MPI3 is written from scratch in C++14.\n", + "laborHours": 0.0, + "languages": [], + "name": "B.MPI3", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/b-mpi3/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/b-mpi3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BACnet_Client_[SWR-13-26].json b/agency-indexes/DoE/BACnet_Client_[SWR-13-26].json new file mode 100644 index 00000000..e6868bc5 --- /dev/null +++ b/agency-indexes/DoE/BACnet_Client_[SWR-13-26].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-06-12" + }, + "description": "The BACnet Client is designed to gather data from building control systems through the BACnet protocol and send to various destinations for data logging and collection.", + "laborHours": 15625.6, + "languages": [ + "Java" + ], + "name": "BACnet Client [SWR-13-26]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BACnet", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BAG__Continuous_Round_Robin_Packet_Capture_.json b/agency-indexes/DoE/BAG__Continuous_Round_Robin_Packet_Capture_.json new file mode 100644 index 00000000..1e60083a --- /dev/null +++ b/agency-indexes/DoE/BAG__Continuous_Round_Robin_Packet_Capture_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "Bag is a miniature pcap filter which takes pcap input (or input off the wire) using a bpf filter, if specified, and then writes the output to stdout or a file (in pcap format). It depends for some aspects of its functionality on a libpcap library which uses a shared memory packet capture ring bugger. There are two build in modules: chcksum and session. the build in chcksum modules is used to anonymize the ip addresses and repair any checksums in the stream. % bag -r /tmp/*.pcap -Cchucksum, 128.1 65: 10.10 The session module generates sessions which are defined as a series of packets that have two things in common. the first is a unique five-tuple composed oi an IP protocol, IP source address, IP source port, IP destination address, and IP destination port. The second is that if the originating packet is associated with a bi-directional service such as ftpltcp, characteristics and data will be kept for both flows involved with the service. The only protocols evaluated beyond the IP header are ICMP, TCP and UDP. A session can last for as long as bag is running. However, under normal conditions, sessions are generated every time they appear to have closed down. There is a man page included with the distribution which goes into more detail.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [], + "name": "BAG (Continuous Round Robin Packet Capture)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/BAMR++.json b/agency-indexes/DoE/BAMR++.json new file mode 100644 index 00000000..b75771df --- /dev/null +++ b/agency-indexes/DoE/BAMR++.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": " The Block-Structured Adaptive Mesh Refinement (BAMR++) application provides block-structured adaptive mesh refinement data structures and an execution model for parallel computing architectures. This application also includes example tests that exercise iteration patterns over the mesh entities (cells, edges, faces). The application is written in C++.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "BAMR++", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/BARC_Element_Classifier__barc_.json b/agency-indexes/DoE/BARC_Element_Classifier__barc_.json new file mode 100644 index 00000000..3121fdb5 --- /dev/null +++ b/agency-indexes/DoE/BARC_Element_Classifier__barc_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2024-02120O\nThis program enumerates and classifies all possible functional elements in several different categories within the Ballistic Asynchronous Reversible Computing (barc) model of computation. barc software is a research tool that is being used to help document the possible digital behaviors of primitive functional elements in the ABRC a.k.a. BARC model of computation. \n\nThe method of operation of this software leverages elementary concepts and methods from discrete mathematics: combinatorics (permutations), partitions and equivalence classes, symmetry transformations, and the theory of finite groups. Implementation is in Python programming language. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 562.4, + "languages": [ + "Python" + ], + "name": "BARC Element Classifier (barc)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/barcs", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BARDI.json b/agency-indexes/DoE/BARDI.json new file mode 100644 index 00000000..02ffb3ff --- /dev/null +++ b/agency-indexes/DoE/BARDI.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "krawczukpn@ornl.gov" + }, + "date": { + "created": "2024-03-28", + "metadataLastUpdated": "2024-03-28" + }, + "description": "BARDI: Batch-processing Abstraction for Raw Data Integration", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "BARDI", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DOE-NCI-MOSSAIC/bardi", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BASEJumper.json b/agency-indexes/DoE/BASEJumper.json new file mode 100644 index 00000000..73324daf --- /dev/null +++ b/agency-indexes/DoE/BASEJumper.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "A small web app for interfacing with HPSS in an automatic fashion.\n", + "laborHours": 425.6, + "languages": [], + "name": "BASEJumper", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/basejump", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BASIC_HARTREE-FOCK_PROXY_APPLICTION.json b/agency-indexes/DoE/BASIC_HARTREE-FOCK_PROXY_APPLICTION.json new file mode 100644 index 00000000..d866f8eb --- /dev/null +++ b/agency-indexes/DoE/BASIC_HARTREE-FOCK_PROXY_APPLICTION.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-05-17", + "metadataLastUpdated": "2021-05-17" + }, + "description": "This proxy application simulates the compute load and data-movement of the kernel of the Hartree-Fock method in quantum chemistry. The proxy features a simplified algorithm for computing electron repulsion integrals that is easily offloaded to GPUs.", + "laborHours": 0.0, + "languages": [], + "name": "BASIC HARTREE-FOCK PROXY APPLICTION", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gdfletcher/basic-hf-proxy", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BATCHSCAN.json b/agency-indexes/DoE/BATCHSCAN.json new file mode 100644 index 00000000..02950804 --- /dev/null +++ b/agency-indexes/DoE/BATCHSCAN.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-23" + }, + "description": "BatchScan provides an interactive graphical user interface (GUI) that allows visualization of X-ray microscopic data,\nselection of scan coordinates, and execution of desired scan coordinates in a single software package. In addition to the\nthree primary functionalities, BatchScan also maintains an active list of scans that users inserted and updates lifetime\nfeedback on scan status.\n", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "BATCHSCAN", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/BATPAC--VERSION_5.0.json b/agency-indexes/DoE/BATPAC--VERSION_5.0.json new file mode 100644 index 00000000..4cb6204f --- /dev/null +++ b/agency-indexes/DoE/BATPAC--VERSION_5.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "Argonne National Laboratory has worked on electrochemical energy storage for several decades. The focus on lithium-ion chemistries started in the early 1990s, developing new materials, synthesis methods, and performance characterizations. Sponsored by the U.S. Department of Energy, Energy Efficiency and Renewable Energy, Vehicle Technologies Office (DOE-EERE-VTO), Argonne has led with many advances. The experimental activities were complemented with multi-scale modeling that ranged from the atomic to the system (manufacturing processes and automobiles) level. The Battery Performance and Cost (BatPaC) model is a calculation method based on Microsoft\u00bf Office Excel spreadsheets that have been developed at Argonne for estimating the performance and manufacturing cost of lithium-ion batteries for electric-drive vehicles including hybrid-electrics (HEV), plug-in hybrids (PHEV) and pure electrics. The effort is being funded by the Vehicle Technology Office (VTO), which is part of the Energy Efficiency and Renewable Energy (EERE) office of the U.S. Department of Energy (USDOE). BatPaC was first developed in 2007, was subsequently peer-reviewed, and it has served Argonne researchers and the greater battery community in studying the impact of material properties on performance at the pack level. With further developments, the model now allows the design of cells and battery packs for automotive applications, to meet performance requirements (power, energy, recharge time), and estimates the cost of manufacturing the designed batteries. Since the cost depends on the materials he design, and the manufacturing process, this bottom-up model/tool enables the user to study their effects. Designed or the lithium-ion cell and battery researcher, BatPaC helps answer many questions by being 1.Transparent in the assumptions made and the method of calculation 2.Capable of designing a battery specifically for the requirements of an application 3.Constrained by the physical limitations that govern battery performance 4. A bottom-up calculation approach to account for every cost factors. BatPaC predicts the impact of promising materials (and their properties) on the performance metrics relevant for the different applications. Researchers can use the specific capacities and the half-cell voltages of a particular set of electrode materials to calculate the mass and volume of a cell to develop a model incorporating the properties of all the other materials in the cell and the design of the cell enclosure. These calculations not only reveal the impact of an improved material but also enable researchers to calculate the material properties that would be needed to meet the performance criteria of a full battery pack. With this information, researchers can provide he battery industry with realistic expectations that will help it more successfully advance novel battery technologies an Applications.", + "homepageURL": "https://www.anl.gov/cse/batpac-model-software", + "laborHours": 0.0, + "languages": [], + "name": "BATPAC--VERSION 5.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/cse/batpac-model-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/BBOpt__Black-Box_Opt__[SWR-24-57].json b/agency-indexes/DoE/BBOpt__Black-Box_Opt__[SWR-24-57].json new file mode 100644 index 00000000..15083268 --- /dev/null +++ b/agency-indexes/DoE/BBOpt__Black-Box_Opt__[SWR-24-57].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Active learning algorithms based on surrogate models to solve black-box optimization problems and other scientific applications.", + "laborHours": 4332.0, + "languages": [ + "Jupyter Notebook", + "R", + "Python" + ], + "name": "BBOpt (Black-Box Opt) [SWR-24-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bbopt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BBTools.json b/agency-indexes/DoE/BBTools.json new file mode 100644 index 00000000..341ad082 --- /dev/null +++ b/agency-indexes/DoE/BBTools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-08", + "metadataLastUpdated": "2020-09-08" + }, + "description": "This module makes BBTools available in KBase.", + "laborHours": 3465.6, + "languages": [], + "name": "BBTools", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/BBTools", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BCL_Gem_[SWR_21-64].json b/agency-indexes/DoE/BCL_Gem_[SWR_21-64].json new file mode 100644 index 00000000..35207274 --- /dev/null +++ b/agency-indexes/DoE/BCL_Gem_[SWR_21-64].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2023-06-12" + }, + "description": "This repository contains all the methods to build, test, and release the gem available as rake tasks via bundler/gem_tasks.\n", + "laborHours": 11126.4, + "languages": [], + "name": "BCL Gem [SWR 21-64]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bcl-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BCS__Beamline_Control_System__v2.json b/agency-indexes/DoE/BCS__Beamline_Control_System__v2.json new file mode 100644 index 00000000..fff02583 --- /dev/null +++ b/agency-indexes/DoE/BCS__Beamline_Control_System__v2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-05", + "metadataLastUpdated": "2018-12-05" + }, + "description": "The software is a flexible architecture used to integrate motors, analog data, digital signals, and instruments together to control scientific experiments and collect data during an experiment. The architecture supports features needed by scientists to quickly add new hardware to an experiment and to take and view data in a meaningful way. It does not perform analysis of the data, but provides basic visualization needed to evaluate the quality of the data as well as the calibration of the system.\n", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 60.8, + "languages": [], + "name": "BCS (Beamline Control System) v2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/BCS__CSP_Beam_Characterization_System__[SWR-23-13].json b/agency-indexes/DoE/BCS__CSP_Beam_Characterization_System__[SWR-23-13].json new file mode 100644 index 00000000..fed56175 --- /dev/null +++ b/agency-indexes/DoE/BCS__CSP_Beam_Characterization_System__[SWR-23-13].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-01-11", + "metadataLastUpdated": "2023-03-29" + }, + "description": "The Beam Characterization System (BCS) is an image-processing tool for estimating heliostat tracking errors. A large mirror, or heliostat, reflects the sun onto a distant target. A carefully calibrated camera then takes an image of this target to capture the shape of the reflected beam. The software kit hosts a series of scripts to identify key features and run analysis on the captured images.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "BCS (CSP Beam Characterization System) [SWR-23-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NREL-Beam-Characterization", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BD-CATS-IO.json b/agency-indexes/DoE/BD-CATS-IO.json new file mode 100644 index 00000000..53700383 --- /dev/null +++ b/agency-indexes/DoE/BD-CATS-IO.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "Modern cosmology and plasma physics codes are now capable of simulating trillions of particles on petascale systems. Each timestep output from such simulations is on the order of 10s of TBs. Summarizing and visualizing raw particle data is challenging, and scientists often focus on density structures, whether in the real 3D space, or a high-dimensional phase space. In this work, code was developed for reading 10s of terabytes of data and for writing the resultant cluster IDs for each particle. This code will be part of a highly scalable version of the clustering algorithm DBSCAN, and apply it to the largest datasets produced by state-of-the-art codes. The overall function of BD-CATS (Big Data Clustering at Trillion Particles Scale) is to perform end-to-end analysis: loading the data, dynamic partitioning, computing kdtrees, performing clustering analysis, and storing the results. BD-CATS-IO provides the functionality of loading the data and storing the results.", + "laborHours": 0.0, + "languages": [], + "name": "BD-CATS-IO", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/hpc-io/BD-CATS-IO/blob/main/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/BD-CATS-IO", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BDEM__Discrete-element-simulator_for_high-solids_granular_flows__[SWR-22-72].json b/agency-indexes/DoE/BDEM__Discrete-element-simulator_for_high-solids_granular_flows__[SWR-22-72].json new file mode 100644 index 00000000..e0182ba1 --- /dev/null +++ b/agency-indexes/DoE/BDEM__Discrete-element-simulator_for_high-solids_granular_flows__[SWR-22-72].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-08-24", + "metadataLastUpdated": "2023-04-24" + }, + "description": "BDEM is a discrete element method based simulation tool developed specifically for modeling high-solids granular flows that include polydispersity, heat-transfer, moving boundaries and chemistry. Our solver provides facilities for simulating spherical/non-spherical particles with modified contact and friction models in complex dynamic geometries defined using level-sets or triangulated files. The solver is developed on top of NREL's open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Simulations at the scale of several millions to billion particles have been performed using this software on large scale computing resources. This software can be applied to non-reacting solids dominant flows in silos, hoppers and screw conveyors as well as in high temperature reacting systems such as screw kilns and auger reactors.", + "laborHours": 0.0, + "languages": [ + "C++", + "C", + "Python" + ], + "name": "BDEM (Discrete-element-simulator for high-solids granular flows) [SWR-22-72]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BDEM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BEAST.json b/agency-indexes/DoE/BEAST.json new file mode 100644 index 00000000..bc31e68c --- /dev/null +++ b/agency-indexes/DoE/BEAST.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-04-18", + "metadataLastUpdated": "2025-04-18" + }, + "description": "The Bilinear Ensemble Actuation Synthesis Toolkit (BEAST) is a computational platform that optimizes time-varying control signals to achieve a specified transfer of states governed by bilinear ensemble systems in which model parameters are subject to uncertainty.", + "laborHours": 197.6, + "languages": [], + "name": "BEAST", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/BEAST", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BEDES_Mapping_Manager_v1.0.json b/agency-indexes/DoE/BEDES_Mapping_Manager_v1.0.json new file mode 100644 index 00000000..6a19372f --- /dev/null +++ b/agency-indexes/DoE/BEDES_Mapping_Manager_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-01", + "metadataLastUpdated": "2019-10-02" + }, + "description": "The BEDES Manager is a web-based application for archiving, searching, and editing BEDES terms and mapping them to terms in user applications. BEDES is a standard data dictionary for building energy related terms.\nThe BEDES Manager can be used in the following ways:\n- Search for BEDES terms, including composite terms.\n- Create new composite terms for use in application mappings.\n- Create, manage and export application mappings.", + "laborHours": 62335.2, + "languages": [], + "name": "BEDES Mapping Manager v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/BEDES-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BEEAM__Building_Electrical_Efficiency_Analysis_Model__[SWR-20-107].json b/agency-indexes/DoE/BEEAM__Building_Electrical_Efficiency_Analysis_Model__[SWR-20-107].json new file mode 100644 index 00000000..ba877600 --- /dev/null +++ b/agency-indexes/DoE/BEEAM__Building_Electrical_Efficiency_Analysis_Model__[SWR-20-107].json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-12-23", + "metadataLastUpdated": "2023-06-09" + }, + "description": "Modern high-performance buildings exhibit an increasing number of building loads that use direct current (DC) electricity internally, rather than alternating current (AC), due to the advent of low-cost computing and advanced power electronics. Powering DC devices from the AC grid requires AC/DC power conversion, which introduces energy losses and reduces efficiency. As DC loads proliferate, the cumulative wasted energy associated with hundreds of millions of AC/DC converters has become one of the broadest energy savings opportunities in buildings.\n\nDC power distribution systems have been proposed as an elegant and transformative solution to the problem of DC devices. In a DC distribution system, the building's wires carry DC electricity, rather than AC; and a few centralized, highly efficient AC/DC converters replace the many smaller, less efficient converters that serve individual DC loads. Unfortunately, the trade-offs associated with DC distribution systems are not well understood. Reported energy savings associated with DC power distribution differ widely and have not been well validated.\n\nThe Building Electrical Efficiency Analysis Model (BEEAM) is a Modelica library that simulates the efficiency of building electrical distribution systems using harmonic power flow. BEEAM can model a wide variety of building distribution topologies, including three-phase AC, single-phase AC, unipolar DC, bipolar DC, and hybrid networks under both balanced and unbalanced load conditions. BEEAM accurately models power electronic converter losses, provides granular estimates of losses throughout the distribution system, and properly models efficiency at part load conditions. Users can package BEEAM within a functional mockup unit (FMU), enabling co-simulation with other modeling platform, such as EnergyPlus. In summary, BEEAM provides a tool suite for fair and accurate comparison of the efficiency of building electrical distribution systems, including AC, DC, and hybrid systems.", + "laborHours": 0.0, + "languages": [ + "Modelica", + "MATLAB", + "Ruby", + "Jupyter ", + "Python" + ], + "name": "BEEAM (Building Electrical Efficiency Analysis Model) [SWR-20-107]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BEEAM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BERTeley_v0.0.1.json b/agency-indexes/DoE/BERTeley_v0.0.1.json new file mode 100644 index 00000000..d8b8e1f5 --- /dev/null +++ b/agency-indexes/DoE/BERTeley_v0.0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-05-17", + "metadataLastUpdated": "2023-05-17" + }, + "description": "This python package allows for the grouping of scientific articles based on their content, and generates topic words based on the groups. Overall this program can take in a large collection of articles and create a profile of them, displaying what disciplines and areas are covered in the collection. Researchers will be able to input another researcher's published works and get a summary of the kind of content available in the publications.", + "laborHours": 0.0, + "languages": [], + "name": "BERTeley v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/berteley", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BESTEST-GSR__Building_Energy_Simulation_Test_-_Generation_Simulation_and_Reporting__2023_[SWR_18-23].json b/agency-indexes/DoE/BESTEST-GSR__Building_Energy_Simulation_Test_-_Generation_Simulation_and_Reporting__2023_[SWR_18-23].json new file mode 100644 index 00000000..2ead4351 --- /dev/null +++ b/agency-indexes/DoE/BESTEST-GSR__Building_Energy_Simulation_Test_-_Generation_Simulation_and_Reporting__2023_[SWR_18-23].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-17" + }, + "description": "Building Energy Simulation Test (BESTEST) is an NREL-developed method to validate the qualitative performance of different whole building simulations engines relative to each other. \nhttps://www.nrel.gov/docs/legosti/old/6231.pdf\n\nThe purpose of this repository is to generate BESTEST test case models, run simulations, and populate data for ASHRAE Standard 140 reporting spreadsheets for EnergyPlus\u00ae based whole building simulation tools. It was originally setup for 2014 version of Standard 140. In May of 2022 it was updated to the 2020 version of Standard 140. This update included updates and additions to existing test suites, the bulk of which was in Section 5.2 (Building Thermal Envelope and Fabric Load Tests). We did not add Section 5.5 Airside HVAC Equipment Performance, but we hope to add that later in 2022. At some point we also hope to add Section 5.2.4 ground modeling, which is currently excluded.\n\nSupported Tools\nThe default IDF generation is based on the OpenStudio\u00ae CLI, but the workflow supports a 'Bring your own IDF' use case. Additionally, for non-EnergyPlus\u00ae based tools the post processing scripts can be used if simulation results are provided as a CSV file.The scripts on this repository should work on Mac, Windows, and Linux.\n\nDependencies\nInstall OpenStudio\u00ae 3.4.0\nmake sure command line can recognize the 'openstudio' command\nThis includes EnergyPlus\u00ae 22.1\nInstall Ruby on your system if it isn't already setup.\n2.7 is used for development but other versions may work\nSince OpenStudio has its own embedded Ruby, which is used for running measures, you don't necessarily have to use a version of Ruby supported by OpenStudio.\nInstall RubyXL Ruby gem\nThis is used to modify Microsoft Excel spreadsheets\nInstall Parallel Ruby gem\nThis allows the CLI to run simulations in parallel", + "laborHours": 68339.2, + "languages": [ + "Ruby", + "HTML" + ], + "name": "BESTEST-GSR (Building Energy Simulation Test - Generation Simulation and Reporting) 2023 [SWR 18-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BESTEST-GSR", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "OpenStudio 3.4.0 EnergyPlus 22.1 Std 140 ver 2020" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BESTEST-GSR__Building_Energy_Simulation_Test_-_Generation_Simulation_and_Reporting__[SWR_18-23].json b/agency-indexes/DoE/BESTEST-GSR__Building_Energy_Simulation_Test_-_Generation_Simulation_and_Reporting__[SWR_18-23].json new file mode 100644 index 00000000..0bd9bc5f --- /dev/null +++ b/agency-indexes/DoE/BESTEST-GSR__Building_Energy_Simulation_Test_-_Generation_Simulation_and_Reporting__[SWR_18-23].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2023-08-15" + }, + "description": "Building Energy Simulation Test (BESTEST) is an NREL-developed method to validate the qualitative performance of different whole building simulations engines relative to each other. \nhttps://www.nrel.gov/docs/legosti/old/6231.pdf\n\nFor EnergyPlus\u00ae and OpenStudio\u00ae, generation of test cases, simulation, and reporting has been a manual or partially automated process that typically took a number of months after a new version of EnergyPlus came out. Building Energy Simulation Test - Generation Simulation and Reporting (BESTEST-GSR) was developed to fully automate this process so it is less error-prone, less time-consuming, and can be quickly run on request for any development branch of EnergyPlus and OpenStudio.\n\nThe initial use case is to directly support OpenStudio and EnergyPlus development, but the software is configured to support use by external software developers that build tools on top of EnergyPlus and/or OpenStudio. Tools built on top of OpenStudio can leverage the test generation, simulation, and reporting, while tools built on EnergyPlus can leverage the test simulation and reporting.\n\nThe model generation is accomplished by running OpenStudio measures for envelope, heating, or cooling test cases. At this stage the specified weather file required for a specific test case is assigned to the model. Simulation is enabled using the OpenStudio Command Line Interface (CLI) to run a series of OpenStudio and Reporting measures to a specified seed model. The specified workflow is defined with an OpenStudio OSW file. The first measure generates the test case model, while the second measure is a reporting measure that runs after the simulation to collect necessary simulation results from the EnergyPlus SQL file. The Reporting stage gathers data from individual OpenStudio OSW files and populates a series of BESTEST Microsoft Excel spreadsheets. BESTEST-GSR also gathers zip files from individual simulations for diagnostic purposes.", + "laborHours": 68339.2, + "languages": [], + "name": "BESTEST-GSR (Building Energy Simulation Test - Generation Simulation and Reporting) [SWR 18-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BESTEST-GSR", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/BEopt\342\204\242__Building_Energy_Optimization_Tool__[SWR-05-41].json" "b/agency-indexes/DoE/BEopt\342\204\242__Building_Energy_Optimization_Tool__[SWR-05-41].json" new file mode 100644 index 00000000..559629db --- /dev/null +++ "b/agency-indexes/DoE/BEopt\342\204\242__Building_Energy_Optimization_Tool__[SWR-05-41].json" @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-08", + "metadataLastUpdated": "2023-06-13" + }, + "description": "The BEopt\u2122 (Building Energy Optimization Tool) software provides capabilities to evaluate residential building designs and identify cost-optimal efficiency packages at various levels of whole-house energy savings along the path to zero net energy. BEopt can be used to analyze both new construction and existing home retrofits, as well as single-family detached and multi-family buildings, through evaluation of single building designs, parametric sweeps, and cost-based optimizations. BEopt provides detailed simulation-based analysis based on specific house characteristics, such as size, architecture, occupancy, vintage, location, and utility rates. Discrete envelope and equipment options, reflecting realistic construction materials and practices, are evaluated. BEopt uses EnergyPlus, the Department of Energy's flagship simulation engine. Simulation assumptions are based on the Building America Housing Simulation Protocols. The sequential search optimization technique used by BEopt: Finds minimum-cost building designs at different target energy-savings levels, Identifies multiple near-optimal designs along the path, allowing for equivalent solutions based on builder or contractor preference. BEopt has been developed by the National Renewable Energy Laboratory in support of the U. S. Department of Energy Building America program goal to develop market-ready energy solutions for new and existing homes.", + "homepageURL": "https://beopt.nrel.gov/home", + "laborHours": 657962.4, + "languages": [], + "name": "BEopt\u2122 (Building Energy Optimization Tool) [SWR-05-41]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://beopt.nrel.gov/BEopt_setup_2.8.0.0", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://beopt.nrel.gov/home", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "2.8.0.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/BEopt\342\204\242__Building_Energy_Optimization_Tool__version_3.0.1_3_16_2023_[SWR-05-41].json" "b/agency-indexes/DoE/BEopt\342\204\242__Building_Energy_Optimization_Tool__version_3.0.1_3_16_2023_[SWR-05-41].json" new file mode 100644 index 00000000..1ffddc30 --- /dev/null +++ "b/agency-indexes/DoE/BEopt\342\204\242__Building_Energy_Optimization_Tool__version_3.0.1_3_16_2023_[SWR-05-41].json" @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-14" + }, + "description": "The BEopt\u2122 (Building Energy Optimization Tool) software provides capabilities to evaluate residential building designs and identify cost-optimal efficiency packages at various levels of whole-house energy savings along the path to zero net energy.\n\nThe BEopt software can be used to analyze both new construction and existing home retrofits, as well as single-family detached and multi-family buildings, through evaluation of single building designs, parametric sweeps, and cost-based optimizations.\n\nThe BEopt software provides detailed simulation-based analysis based on specific house characteristics, such as size, architecture, occupancy, vintage, location, and utility rates. Discrete envelope and equipment options, reflecting realistic construction materials and practices, are evaluated.\n\nThe BEopt software uses EnergyPlus\u00ae, the Department of Energy's flagship simulation engine. Simulation assumptions are based on ANSI/RESNET/ICC Standards and the Building America Housing Simulation Protocols.\n\nThe sequential search optimization technique used by the BEopt software:\n\nFinds minimum-cost building designs at different target energy-savings levels\nIdentifies multiple near-optimal designs along the path, allowing for equivalent solutions based on builder or contractor preference.\n\nDownload\n\nA BEopt\u2122 Version 3.0.1 Beta release (Mar. 16, 2023) is now available. Download the BEopt 3.0.1 Beta setup file.", + "homepageURL": "https://www.nrel.gov/buildings/beopt.html?utm_medium=print&utm_source=buildings&utm_campaign=beopt", + "laborHours": 0.0, + "languages": [], + "name": "BEopt\u2122 (Building Energy Optimization Tool) version 3.0.1 3/16/2023 [SWR-05-41]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://beopt.nrel.gov/BEopt_setup_2.8.0.0", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrel.gov/buildings/beopt.html?utm_medium=print&utm_source=buildings&utm_campaign=beopt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "3.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BFSVBF__BatFinder_Smart_Video_BioFilter__[SWR-22-87]_and_Multi-class_BatFinder_Smart_Video_BioFilter_Keras.json b/agency-indexes/DoE/BFSVBF__BatFinder_Smart_Video_BioFilter__[SWR-22-87]_and_Multi-class_BatFinder_Smart_Video_BioFilter_Keras.json new file mode 100644 index 00000000..d4479182 --- /dev/null +++ b/agency-indexes/DoE/BFSVBF__BatFinder_Smart_Video_BioFilter__[SWR-22-87]_and_Multi-class_BatFinder_Smart_Video_BioFilter_Keras.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-11-03", + "metadataLastUpdated": "2023-04-11" + }, + "description": "Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The code has gone through five rounds of development with images used to train the models. This advancement allows for automated real-time data collection, identification, and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. We will discuss the two open source and publicly available machine learning models developed within this scope of this work: 1) a binary model with a 97.5% accuracy in identifying the difference between an object and an empty scene, including wind turbine and clouds; and 2) a multiple classification model with the capability of identifying the type of object detected: bats (90% accuracy), birds (83% accuracy), insects (69% accuracy) and non-biological (99% accuracy).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "BFSVBF (BatFinder Smart Video BioFilter) [SWR-22-87] and Multi-class BatFinder Smart Video BioFilter Keras", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BatFinder_Smart_Video_BioFilter", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BGK-MD,_Version_1.0.json b/agency-indexes/DoE/BGK-MD,_Version_1.0.json new file mode 100644 index 00000000..4c2e5589 --- /dev/null +++ b/agency-indexes/DoE/BGK-MD,_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software implements a heterogeneous multiscale method (HMM), which involves solving a classical molecular dynamics (MD) problem and then computes the entropy production in order to compute the relaxation times towards equilibrium for use in a Bhatnagar-Gross-Krook (BGK) solver.", + "laborHours": 1900.0, + "name": "BGK-MD, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/gilshohet/plasma-bgkmd/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gilshohet/plasma-bgkmd", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BHR_Site.json b/agency-indexes/DoE/BHR_Site.json new file mode 100644 index 00000000..31343b2e --- /dev/null +++ b/agency-indexes/DoE/BHR_Site.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "This is the Blackhole Router Site/API endpoint. It does not make any policy decisions except for the block duration auto scaling. It basically acts as a message queue between bhr clients adding blocks, and bhr clients implementing blocks.\n\n", + "laborHours": 6034.4, + "languages": [], + "name": "BHR Site", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/bhr-site/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/bhr-site", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BHResist_[SWR-25-57].json b/agency-indexes/DoE/BHResist_[SWR-25-57].json new file mode 100644 index 00000000..edef1b87 --- /dev/null +++ b/agency-indexes/DoE/BHResist_[SWR-25-57].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-21", + "metadataLastUpdated": "2025-04-21" + }, + "description": "BHResist is a pure python library for computing thermal resistance within single-u, double-u, and coaxial grouted borehole heat exchangers. For single and double u-tube configurations, the methods use the 1st-order closed-form multipole approximations, which typically produces results with less than 1% error when compared to the 10th-order multipole method. Coaxial borehole methods apply a simple 1D resistance network method.\n\nThis is intended to be a lightweight library that can be easily imported into any other Python tool, with no bulky dependencies.", + "laborHours": 896.8, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "BHResist [SWR-25-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BHResist", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BIORAD.json b/agency-indexes/DoE/BIORAD.json new file mode 100644 index 00000000..43a442da --- /dev/null +++ b/agency-indexes/DoE/BIORAD.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-01-24", + "metadataLastUpdated": "2025-01-30" + }, + "description": "Machine learning prediction of protein-protein binding affinity", + "laborHours": 3952.0, + "languages": [], + "name": "BIORAD", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/BIORAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BITTREE.json b/agency-indexes/DoE/BITTREE.json new file mode 100644 index 00000000..2913c018 --- /dev/null +++ b/agency-indexes/DoE/BITTREE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-24", + "metadataLastUpdated": "2022-09-24" + }, + "description": "The bittree is a memory efficient data structure for storing the entire structure of an octree AMR \nmesh. It also yields an efficient algorithm for mapping from a block's coordinates in the domain to \nits index along the space filling Morton curve.\n\n", + "laborHours": 0.0, + "languages": [], + "name": "BITTREE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Flash-X/Bittree", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BIhNNs.json b/agency-indexes/DoE/BIhNNs.json new file mode 100644 index 00000000..1c78146f --- /dev/null +++ b/agency-indexes/DoE/BIhNNs.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2022-10-17", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural Networks (DNNs), Neural ODEs, and Symplectic Neural Networks (SympNets) used with state-of-the-art sampling schemes like Hamiltonian Monte Carlo (HMC) and the No-U-Turn-Sampler (NUTS).", + "laborHours": 0.0, + "languages": [], + "name": "BIhNNs", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/BIhNNs", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BLAST-Lite__Battery_Lifetime_Analysis_and_Simulation_Tool_-_Lite__[SWR-22-69]_Related_to:_BLAST_aka:_BLAST-Py.json b/agency-indexes/DoE/BLAST-Lite__Battery_Lifetime_Analysis_and_Simulation_Tool_-_Lite__[SWR-22-69]_Related_to:_BLAST_aka:_BLAST-Py.json new file mode 100644 index 00000000..a6a1b439 --- /dev/null +++ b/agency-indexes/DoE/BLAST-Lite__Battery_Lifetime_Analysis_and_Simulation_Tool_-_Lite__[SWR-22-69]_Related_to:_BLAST_aka:_BLAST-Py.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-07-24", + "metadataLastUpdated": "2024-10-16" + }, + "description": "Battery Lifetime Analysis and Simulation Toolsuite (BLAST) provides a library of battery lifetime and degradation models for various commercial lithium-ion batteries from recent years. Degradation models are identified from publicly available lab-based aging data using NREL's battery life model identification toolkit. The battery life models predicted the expected lifetime of batteries used in mobile or stationary applications as functions of their temperature and use (state-of-charge, depth-of-discharge, and charge/discharge rates). Model implementation is in both Python and MATLAB programming languages. The MATLAB code also provides example applications (stationary storage and EV), climate data, and simple thermal management options. For more information on battery health diagnostics, prediction, and optimization, see NREL's Battery Lifespan webpage.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python", + "Jupyter Notebook" + ], + "name": "BLAST-Lite (Battery Lifetime Analysis and Simulation Tool - Lite) [SWR-22-69] Related to: BLAST aka: BLAST-Py", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BLAST-Lite", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BLINK_v1.json b/agency-indexes/DoE/BLINK_v1.json new file mode 100644 index 00000000..dc91af6a --- /dev/null +++ b/agency-indexes/DoE/BLINK_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "We introduce the Binned Large Interval Network Kernel approach for scoring fragmentation mass spectra similarity which takes advantage of sparse matrix multiplication. This enables BLINK to perform 100 million comparisons while maintaining 98% accuracy in 2.2 seconds making it over 1,000 times faster than the current implementations.", + "laborHours": 0.0, + "languages": [], + "name": "BLINK v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biorack/blink", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BLOT_Ver._1.65.json b/agency-indexes/DoE/BLOT_Ver._1.65.json new file mode 100644 index 00000000..15e8b266 --- /dev/null +++ b/agency-indexes/DoE/BLOT_Ver._1.65.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "BLOT is a graphic program for post-processing finite element analyses output in the EXODUS II database format. It is command driven with free-format input and can drive graphics devices supported by the Sandia Virtual Device Interface. BLOT produces mesh plots of the analysis output variables including deformed mesh plots, line contours, filled (painted) contours, vector plots of two/three variables (velocity vectors), and symbol plots of scalar variables (discrete cracks). Features include pathlines of analysis variables drawn on the mesh, element selection by material, element birth and death, multiple views combining several displays on each plot, symmetry mirroring, and node and element numbering. X-Y plots of the analysis variables include time vs. variable plots or variable vs. variable plots, and distance vs. variable plots at selected time steps where distance is the accumulated distance between pairs of nodes or element centers. BLOT is written in as portable a form as possible. Fortran code is written in ANSI Standard FORTRAN-77. Machine-specific routines are limited in number and are grouped together to minimize the time required to adapt them to a new system. SEACAS codes have been ported to several Unix systems", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "BLOT Ver. 1.65", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.65" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BLT.json b/agency-indexes/DoE/BLT.json new file mode 100644 index 00000000..582bd45c --- /dev/null +++ b/agency-indexes/DoE/BLT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "A streamlined CMake build system foundation for developing HPC software.\n", + "laborHours": 83767.2, + "languages": [], + "name": "BLT", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/blt", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BLT_Plugin_PHPMD_Validator.json b/agency-indexes/DoE/BLT_Plugin_PHPMD_Validator.json new file mode 100644 index 00000000..2e0f88ae --- /dev/null +++ b/agency-indexes/DoE/BLT_Plugin_PHPMD_Validator.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-08-26", + "metadataLastUpdated": "2022-08-26" + }, + "description": "A plugin tool for testing PHP code according to the Mess Detector rules extending functionality to users of Acquia BLT for Drupal.", + "laborHours": 0.0, + "languages": [], + "name": "BLT Plugin PHPMD Validator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/blt-phpmd", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BNL-NowCasting_SolarForecasting.json b/agency-indexes/DoE/BNL-NowCasting_SolarForecasting.json new file mode 100644 index 00000000..68fc9b64 --- /dev/null +++ b/agency-indexes/DoE/BNL-NowCasting_SolarForecasting.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "kalb@bnl.gov" + }, + "date": { + "created": "2019-05-02", + "metadataLastUpdated": "2019-05-02" + }, + "description": "BNL NowCasting software is used in conjunction with multiple ground-based, upward looking, high definition imagers to predict available solar resources in the zero - 30 minutes time frame. It takes HD images of the sky as input and conducts image pre-processing to correct image geometry, correct deformation caused by fish-eye lenses and remove extraneous parts of the image. It calculates the location of the sun and removes it to reduce distortion. A cloud detection/tracking algorithm was developed using both spectral and spatial information for discriminating clouds and clear sky based on their shape, size, and color. The software repeats the process with updated images generated every 30 seconds (or less) and then tracks the clouds as they move through the region of interest. Cloud motion determination is based on finding the maximal normalized cross-correlation between sequential images. The resolution of multiple imager views of clouds in the sky allows the system to estimate cloud height and categorize them into low or high cloud regimes that move at different rates. Additional input data on solar irradiance from pyranometers is ingested. The algorithm then determines the transmissivity of light and uses machine-learning techniques to predict the amount of available global horizontal irradiance (GHI) that will be available on the ground. Images from individual sets of cameras are stitched together to form regional forecasts that cover both generating facilities and distributed solar resources. The size of the nowcasting network is dependent on the number and location of imagers that are installed but has been demonstrated in an area up to 50 sq km", + "laborHours": 3693.6, + "languages": [ + "Python" + ], + "name": "BNL-NowCasting/SolarForecasting", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BNL-NowCasting/SolarForecasting", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BOLT:_OpenMP_over_Lightweight_Threads.json b/agency-indexes/DoE/BOLT:_OpenMP_over_Lightweight_Threads.json new file mode 100644 index 00000000..b83cd610 --- /dev/null +++ b/agency-indexes/DoE/BOLT:_OpenMP_over_Lightweight_Threads.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "BOLT targets a high-performing OpenMP implementation, especially specialized for fine-grain parallelism. BOLT utilizes a lightweight threading model for its underlying threading mechanism. It currently adopts Argobots, a new holistic, low-level threading and tasking runtime, in order to overcome shortcomings of conventional OS-level threads. The current BOLT implementation is based on the OpenMP runtime in LLVM, and thus it can be used with LLVM/Clang, Intel OpenMP compiler, and GCC. More information about BOLT can be found at http://www.bolt-omp.org.", + "laborHours": 77763.2, + "languages": [], + "name": "BOLT: OpenMP over Lightweight Threads", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pmodels/bolt/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/bolt", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BOOTS:_Bayesian_Optimization_for_Optimal_Test_Selection.json b/agency-indexes/DoE/BOOTS:_Bayesian_Optimization_for_Optimal_Test_Selection.json new file mode 100644 index 00000000..2a8ee8ae --- /dev/null +++ b/agency-indexes/DoE/BOOTS:_Bayesian_Optimization_for_Optimal_Test_Selection.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "villezk@ornl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-11-21" + }, + "description": "BOOTS is a package for optimal selection of candidate operating points in large-scale manufacturing applications. It is designed to optimally select operating points to maximize predicted values of product quality and resource efficiency according to a data-driven model. The package is based on the use of a multi-input multi-output (MIMO) Gaussian process model to describe the relationships between inputs (operating points) and outputs (product quality and resource efficiency). This package does not provide any site- or process-specific information.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "BOOTS: Bayesian Optimization for Optimal Test Selection", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/krisvillez/boots", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "v1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BOUT++.json b/agency-indexes/DoE/BOUT++.json new file mode 100644 index 00000000..28d2817a --- /dev/null +++ b/agency-indexes/DoE/BOUT++.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The BOUT++ is a C++ framework for developing plasma fluid simulation codes, and has been developed by the University of York/UK and the LLNL Fusion Energy Program from the original 3D boundary turbulence 2-fluid edge simulation code BOUT. The aim of BOUT++ is to automate the common tasks needed for simulation codes, and to separate the complicated details such as differential geometry, parallel communication, and file input/output from the user-specified equations to be solved. The BOUT++ consists of BOUT++ library and physics modules. BOUT++ modules contains the coding for the specific set of physics equations and boundary conditions for particular physics problems using defined functions in BOUT++ library to perform standard differential operators.", + "laborHours": 77748.0, + "name": "BOUT++", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/boutproject/BOUT-2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BOUndary_Plasma_Turbulence.json b/agency-indexes/DoE/BOUndary_Plasma_Turbulence.json new file mode 100644 index 00000000..0812d02c --- /dev/null +++ b/agency-indexes/DoE/BOUndary_Plasma_Turbulence.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "BOUT is a parallelized 3D nonlocal electromagnetic turbulence code. The principal calculations are the boundary plasma turbulence in a realistic magnetic geometry. BOUT uses fluid Braginskii equations for plasma vorticity, density, electron and ion temperature and Parallel mementum. With sources added in the core-edge region and sinks in the scrape-off-layer (SOL), BOUT follows the self-consistent profile evolution together with turbulence. BOUT also includes coupling to a magnetohyfrodynamic equlibrium (EFIT package) and a two-dimensional hydrodynamic edge transport model (UEDGE package).", + "laborHours": 3298.4, + "name": "BOUndary Plasma Turbulence", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/boutproject/hermes", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BOXKIT.json b/agency-indexes/DoE/BOXKIT.json new file mode 100644 index 00000000..8b052b39 --- /dev/null +++ b/agency-indexes/DoE/BOXKIT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-24" + }, + "description": "SF-23-067\nBoxKit is a library that provides building blocks to parallelize and scale data science, high performance computing, and\nmachine learning applications for block-structured datasets. Spatial data from simulations and experiments can be\naccessed and managed using tools available in this library when working with more data analysis oriented packages like\nSciKit (https://github.com/scikit-learn/scikit-learn) and FlowNet (https://github.com/NVIDIA/flownet2-pytorch)", + "laborHours": 0.0, + "languages": [], + "name": "BOXKIT", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/akashdhruv/BoxKit", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BP-Quant.json b/agency-indexes/DoE/BP-Quant.json new file mode 100644 index 00000000..5b0792b5 --- /dev/null +++ b/agency-indexes/DoE/BP-Quant.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Here, we present the implementation of a Bayesian model (BP-Quant) that uses statistically derived peptides signatures to identify peptides that are outside the dominant pattern, or the existence of multiple over-expressed patterns to improve relative protein abundance estimates. It is a research-driven approach that utilizes the objectives of the experiment, defined in the context of a standard statistical hypothesis, to identify a set of peptides exhibiting similar statistical behavior relating to a protein. This approach infers that changes in relative protein abundance can be used as a surrogate for changes in function, without necessarily taking into account the effect of differential post-translational modifications, processing, or splicing in altering protein function. BP-Quant is available as MatLab \u00ae and R packages here.", + "laborHours": 182.4, + "languages": [], + "name": "BP-Quant", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/BP-Quant", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BPP_R_package.json b/agency-indexes/DoE/BPP_R_package.json new file mode 100644 index 00000000..99696f9b --- /dev/null +++ b/agency-indexes/DoE/BPP_R_package.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "The BPP package contains R code to perform Bayesian projection pursuit regression under various regression settings. Bayesian projection pursuit regression learns the functional relationship between inputs and outputs by considering a sum of functions of one dimensional projections of the inputs. This is useful as a general machine learning software.", + "laborHours": 0.0, + "languages": [], + "name": "BPP R package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gqcollins/BayesPPR", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BRAID.json b/agency-indexes/DoE/BRAID.json new file mode 100644 index 00000000..41ff854c --- /dev/null +++ b/agency-indexes/DoE/BRAID.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-10-08" + }, + "description": "BRAID is a rewriting system for translating abstract intermediate descriptions into light-weight, \"pay only for what you need\" middleware wrappers. Initial capabilities will focus on language interoperability, remote method invocation (RMI), and interface contract enforcement wrappers from Scientific Interface Definition Language (SIDL) specifications. Language interoperability will be provided for software written in C, C++, Fortran, Java, and Python, as was done with Babel, but also a subset of PGAS/HPCS languages, such as Chapel, UPC, and X10. Interface contract enforcement wrappers will initially be supported in a subset of those languages.", + "homepageURL": "https://sourceforge.net/projects/compose-hpc", + "laborHours": 154523.2, + "languages": [], + "name": "BRAID", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/compose-hpc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/BRICR_[SWR_18-33].json b/agency-indexes/DoE/BRICR_[SWR_18-33].json new file mode 100644 index 00000000..3b0d9331 --- /dev/null +++ b/agency-indexes/DoE/BRICR_[SWR_18-33].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-16", + "metadataLastUpdated": "2023-08-16" + }, + "description": "BRICR is software for translating NREL's BuildingSync\u2122 XML (BSXML) to OpenStudio\u00ae Workflow (OSW) files for simulation. Each BSXML contains information about a building as well as multiple possible energy efficiency upgrade options. An OSW file is created and run for each possible efficiency upgrade, the results of all simulations are stored in BSXML format.\n\nBRICR was jointly developed by NREL and LBNL for the San Francisco BayREN: Integrated Commercial Retrofits (BRICR) project funded under the DOE solicitation \"Solutions to Improve the Energy Efficiency of U.S. Small and Medium Commercial Buildings (DE-FOA-0001385)\":\n\nhttps://www.energy.gov/eere/buildings/downloads/san-francisco-bayren-integrated-commercial-retrofits", + "laborHours": 127847.2, + "languages": [ + "Ruby" + ], + "name": "BRICR [SWR 18-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bricr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BRICR_v0.2.0__BayREN_Integrated_Commercial_Retrofits__[SWR_18-33].json b/agency-indexes/DoE/BRICR_v0.2.0__BayREN_Integrated_Commercial_Retrofits__[SWR_18-33].json new file mode 100644 index 00000000..b8320171 --- /dev/null +++ b/agency-indexes/DoE/BRICR_v0.2.0__BayREN_Integrated_Commercial_Retrofits__[SWR_18-33].json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-23", + "metadataLastUpdated": "2023-08-16" + }, + "description": "BRICR is software for translating NREL's BuildingSync\u2122 XML (BSXML) to OpenStudio\u00ae Workflow (OSW) files for simulation. Each BSXML contains information about a building as well as multiple possible energy efficiency upgrade options. An OSW file is created and run for each possible efficiency upgrade, the results of all simulations are stored in BSXML format.\n\nBRICR was jointly developed by NREL and LBNL for the San Francisco BayREN: Integrated Commercial Retrofits (BRICR) project funded under the DOE solicitation \"Solutions to Improve the Energy Efficiency of U.S. Small and Medium Commercial Buildings (DE-FOA-0001385)\":\n\nhttps://www.energy.gov/eere/buildings/downloads/san-francisco-bayren-integrated-commercial-retrofits", + "laborHours": 0.0, + "languages": [], + "name": "BRICR v0.2.0 (BayREN Integrated Commercial Retrofits) [SWR 18-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bricr/releases/tag/v0.2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BSF_publication.json b/agency-indexes/DoE/BSF_publication.json new file mode 100644 index 00000000..e3534398 --- /dev/null +++ b/agency-indexes/DoE/BSF_publication.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "All the data and materials for the publication about the Blazing Signature Filter", + "laborHours": 516.8, + "languages": [], + "name": "BSF_publication", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/BSF_publication", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BSM__Bioenergy_Scenario_Model__2023_FKA:_Biomass_Scenario_Model_[SWR-09-09].json b/agency-indexes/DoE/BSM__Bioenergy_Scenario_Model__2023_FKA:_Biomass_Scenario_Model_[SWR-09-09].json new file mode 100644 index 00000000..a52f4dc8 --- /dev/null +++ b/agency-indexes/DoE/BSM__Bioenergy_Scenario_Model__2023_FKA:_Biomass_Scenario_Model_[SWR-09-09].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-16", + "metadataLastUpdated": "2024-01-03" + }, + "description": "The U.S. Department of Energy's (DOE's) Bioenergy Technologies Office and the National Renewable Energy Laboratory (NREL) developed the BSM (Bioenergy Scenario model) to explore the development of a U.S. biofuels industry. The BSM is a system dynamics model built on the STELLA software platform. The model represents the dynamic interactions of the major sectors of the biofuels industry\u2014feedstock production, feedstock logistics, biomass to biofuels conversion, and biofuels end use, including fuels inventory, dispensing, distribution, fuel use, and the vehicle fleet. The BSM represents contextual aspects of the developing biofuels industry, including investment in new biomass to biofuel conversion technologies, competition from petroleum fuels, vehicle demand for biofuels, and various government policies, using all of these to simulate the development of the industry. The purpose of the BSM is to generate and explore plausible scenarios for the evolution of a biofuels industry in the United States, and as a high-level system model it is not designed for precise, quantitative forecasting. Instead, it is best used to (1) analyze and evaluate alternate policies; (2) generate scenarios; (3) identify high-impact levers and bottlenecks to system evolution; and (4) seed focused discussion among policymakers, analysts, and stakeholders.", + "laborHours": 0.0, + "languages": [ + "STELLA" + ], + "name": "BSM (Bioenergy Scenario Model) 2023 FKA: Biomass Scenario Model [SWR-09-09]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bsm-public", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2023 release" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BSM__Bioenergy_Scenario_Model__FKA:_Biomass_Scenario_Model_[SWR-09-09].json b/agency-indexes/DoE/BSM__Bioenergy_Scenario_Model__FKA:_Biomass_Scenario_Model_[SWR-09-09].json new file mode 100644 index 00000000..71d42c81 --- /dev/null +++ b/agency-indexes/DoE/BSM__Bioenergy_Scenario_Model__FKA:_Biomass_Scenario_Model_[SWR-09-09].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-10-04", + "metadataLastUpdated": "2024-01-03" + }, + "description": "The U.S. Department of Energy's Bioenergy Technologies Office and the National Renewable Energy Laboratory (NREL) developed the BSM (Bioenergy Scenario Model) to explore the development of a U.S. biofuels industry. The BSM is a system dynamics model built on the STELLA software platform. The model represents the dynamic interactions of the major sectors of the biofuels industry\u2014feedstock production, feedstock logistics, biomass to biofuels conversion, and biofuels end use, including fuels inventory, dispensing, distribution, fuel use, and the vehicle fleet. The BSM represents contextual aspects of the developing biofuels industry, including investment in new biomass to biofuel conversion technologies, competition from petroleum fuels, vehicle demand for biofuels, and various government policies, using all of these to simulate the development of the industry. The purpose of the BSM is to generate and explore plausible scenarios for the evolution of a biofuels industry in the United States, and as a high-level system model it is not designed for precise, quantitative forecasting. Instead, it is best used to (1) analyze and evaluate alternate policies; (2) generate scenarios; (3) identify high-impact levers and bottlenecks to system evolution; and (4) seed focused discussion among policymakers, analysts, and stakeholders.", + "laborHours": 0.0, + "languages": [ + "STELLA" + ], + "name": "BSM (Bioenergy Scenario Model) FKA: Biomass Scenario Model [SWR-09-09]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bsm-public", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BUTTER-Clarifier_[SWR-23-61].json b/agency-indexes/DoE/BUTTER-Clarifier_[SWR-23-61].json new file mode 100644 index 00000000..3271ee03 --- /dev/null +++ b/agency-indexes/DoE/BUTTER-Clarifier_[SWR-23-61].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2024-08-27" + }, + "description": "This repository contains a python package of neural network interpretability techniques (interpretability) and a keras callback to easily compute and capture data related to these techniques (values metrics) during training. It was developed to be used with NREL's BUTTER Deep Learning Experimental Framework, but does not depend on this framework and may be useful to projects outside of this framework.\n\nThe vision for this codebase is to collect algorithms for explainable artificial intelligence (XAI) in a single framework that is easy to use, easy to read, and can be expand upon. Here, we package XAI algorithms into a module called \"metrics\", which are implemented as python functions. The return type of a metric is typically a dictionary holding data of multiple data types, such as real values and numpy matrices. Callbacks and any other connector code is provided as necessary in a separate module to make these metrics more easily usable. This project depends on Tensorflow's Keras API, although it would be nice to try and support multiple backends one day.\n\nRelated to: https://github.com/NREL/BUTTER-Empirical-Deep-Learning-Experimental-Framework", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "BUTTER-Clarifier [SWR-23-61]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BUTTER-Clarifier", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BUTTER:_An_Empirical_Deep_Learning_Experimental_Framework_[SWR-22-42].json b/agency-indexes/DoE/BUTTER:_An_Empirical_Deep_Learning_Experimental_Framework_[SWR-22-42].json new file mode 100644 index 00000000..bf15de76 --- /dev/null +++ b/agency-indexes/DoE/BUTTER:_An_Empirical_Deep_Learning_Experimental_Framework_[SWR-22-42].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-05-19", + "metadataLastUpdated": "2023-11-06" + }, + "description": "BUTTER ( An Empirical Deep Learning Experimental Framework) is a system with which empirical deep learning experiments can be conducted and their results, including training and model performance characteristics, can be accumulated for further analysis.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "BUTTER: An Empirical Deep Learning Experimental Framework [SWR-22-42]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BUTTER-Empirical-Deep-Learning-Experimental-Framework", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Backend_For_Frontend.json b/agency-indexes/DoE/Backend_For_Frontend.json new file mode 100644 index 00000000..f7a0c051 --- /dev/null +++ b/agency-indexes/DoE/Backend_For_Frontend.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-09", + "metadataLastUpdated": "2020-09-09" + }, + "description": "Backend for Frontend was developed to shift API calls and data wrangling within browser script to server script to aim faster loading, quicker data structure modification to fit UI development needs, and to provide reusable data structures.", + "laborHours": 243.2, + "languages": [], + "name": "Backend For Frontend", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/user-profile-ui-bff", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Background_Explorer.json b/agency-indexes/DoE/Background_Explorer.json new file mode 100644 index 00000000..ae133988 --- /dev/null +++ b/agency-indexes/DoE/Background_Explorer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-19", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Tools to construct a model for sources of radioactive backgrounds in a low radioactivity dertector system\nBackground explorer simplifies or automates many of the tedious and error-prone tasks involved in creating a detailed radioactivity budget for a low background detector system. The tool also provides a rich web interface allowing even nontechnical users to easily modify the model assumptions and drill-down into the model and result details.\nBackend: https://github.com/bloer/bgmodelbuilder Web application: https://github.com/bloer/bgexplorer \nDemo/user template: https://github.com/bloer/bgexplorer-demo", + "laborHours": 2325.6, + "languages": [], + "name": "Background Explorer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bloer/bgmodelbuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Badger:_The_Ocelot_Optimizer_Rebirth.json b/agency-indexes/DoE/Badger:_The_Ocelot_Optimizer_Rebirth.json new file mode 100644 index 00000000..ebf6ce02 --- /dev/null +++ b/agency-indexes/DoE/Badger:_The_Ocelot_Optimizer_Rebirth.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-06", + "metadataLastUpdated": "2022-07-06" + }, + "description": "Ocelot optimizer rebirth.", + "laborHours": 0.0, + "languages": [], + "name": "Badger: The Ocelot Optimizer Rebirth", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/Badger", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bake.json b/agency-indexes/DoE/Bake.json new file mode 100644 index 00000000..ada85ddd --- /dev/null +++ b/agency-indexes/DoE/Bake.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-31", + "metadataLastUpdated": "2022-01-31" + }, + "description": "Bake is a microservice (i.e., Mochi provider) for high performance bulk storage of raw data regions. Bake uses modular backends to store data on persistent memory, conventional file systems, or other storage media.", + "laborHours": 0.0, + "languages": [], + "name": "Bake", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-bake/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-bake", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Balrog.json b/agency-indexes/DoE/Balrog.json new file mode 100644 index 00000000..2916cae8 --- /dev/null +++ b/agency-indexes/DoE/Balrog.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-14", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-12602 O\nBalrog uses mathematical methods to calculate spectral line shapes in high-energy-density plasmas. Line shapes are a result of atomic perturbations by their surrounding plasmas, and this model captures much of the physics and generates model spectrum that can be used in data analysis and as an input for other models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [], + "name": "Balrog", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/balrog", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Band_Bending_Contact_Resistivity_Codes_v._1.json b/agency-indexes/DoE/Band_Bending_Contact_Resistivity_Codes_v._1.json new file mode 100644 index 00000000..bd4ab613 --- /dev/null +++ b/agency-indexes/DoE/Band_Bending_Contact_Resistivity_Codes_v._1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-12-03", + "metadataLastUpdated": "2018-12-03" + }, + "description": "Code #1 solves the one-dimensional Poisson equation and outputs the band bending poteatial near a metal-semiconductor interface.\nCode #2 uses the output of code #1 and calculates the contact resistivity of the interface.\n", + "homepageURL": "http://www.sandia.gov/nanocarb/research.php", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Band Bending/Contact Resistivity Codes v. 1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.sandia.gov/nanocarb/research.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bantamweight_Badger_UDP_support__BWUDP__v1.0.json b/agency-indexes/DoE/Bantamweight_Badger_UDP_support__BWUDP__v1.0.json new file mode 100644 index 00000000..bb0a7fd9 --- /dev/null +++ b/agency-indexes/DoE/Bantamweight_Badger_UDP_support__BWUDP__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "Software networking library to allow an FPGA ethernet core (such as Badger: https://gitlab.lbl.gov/hdl-libraries/bedrock/-/tree/master/badger) to be used in a soft-core processor or microcontroller.", + "laborHours": 0.0, + "languages": [], + "name": "Bantamweight Badger UDP support (BWUDP) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/BWUDP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BaseBuddy_v1.json b/agency-indexes/DoE/BaseBuddy_v1.json new file mode 100644 index 00000000..63c598f9 --- /dev/null +++ b/agency-indexes/DoE/BaseBuddy_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-09-16" + }, + "description": "The software \"BaseBuddy\" (basebuddy.lbl.gov) is a user-friendly web app designed for codon optimization of heterologous genes. Codon optimization is a widely used technique to enhance the expression levels of non-native genes. Our app is built on the DNA Chisel Python library (Zulkower and Rosser, 2020), which offers highly customizable and transparent gene optimization. Unlike DNA Chisel, which is a command-line interface software with numerous optional functions, our web app simplifies the process for users. Additionally, while DNA Chisel relies on the outdated Kazusa codon usage database, our app introduces the option to utilize the most recent version of the CoCoPUTs database (Athey et al., 2017). By incorporating CoCoPUTs, we also expand the range of target organisms and maintain up-to-date sequencing data for more accurate codon optimization results.", + "laborHours": 167.2, + "languages": [], + "name": "BaseBuddy v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jbei/basebuddy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Basic_Matrix_Library__bml_,_Version_0.x.json b/agency-indexes/DoE/Basic_Matrix_Library__bml_,_Version_0.x.json new file mode 100644 index 00000000..5b8682c6 --- /dev/null +++ b/agency-indexes/DoE/Basic_Matrix_Library__bml_,_Version_0.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The basic matrix library (bml) is a collection of various matrix data formats (in dense and sparse) and their associated algorithms for basic matrix operations.", + "laborHours": 38319.2, + "name": "Basic Matrix Library (bml), Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/bml/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qmmd/bml", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Basin_Assessment_Spatial_Planning_Platform.json b/agency-indexes/DoE/Basin_Assessment_Spatial_Planning_Platform.json new file mode 100644 index 00000000..505918de --- /dev/null +++ b/agency-indexes/DoE/Basin_Assessment_Spatial_Planning_Platform.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The tool is intended to facilitate hydropower development and water resource planning by improving synthesis and interpretation of disparate spatial datasets that are considered in development actions (e.g., hydrological characteristics, environmentally and culturally sensitive areas, existing or proposed water power resources, climate-informed forecasts). The tool enables this capability by providing a unique framework for assimilating, relating, summarizing, and visualizing disparate spatial data through the use of spatial aggregation techniques, relational geodatabase platforms, and an interactive web-based Geographic Information Systems (GIS). Data are aggregated and related based on shared intersections with a common spatial unit; in this case, industry-standard hydrologic drainage areas for the U.S. (National Hydrography Dataset) are used as the spatial unit to associate planning data. This process is performed using all available scalar delineations of drainage areas (i.e., region, sub-region, basin, sub-basin, watershed, sub-watershed, catchment) to create spatially hierarchical relationships among planning data and drainages. These entity-relationships are stored in a relational geodatabase that provides back-end structure to the web GIS and its widgets. The full technology stack was built using all open-source software in modern programming languages. Interactive widgets that function within the viewport are also compatible with all modern browsers.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Basin Assessment Spatial Planning Platform", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/BatteryOS.json b/agency-indexes/DoE/BatteryOS.json new file mode 100644 index 00000000..b5136966 --- /dev/null +++ b/agency-indexes/DoE/BatteryOS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "tancw@stanford.edu" + }, + "date": { + "created": "2025-04-28", + "metadataLastUpdated": "2025-04-28" + }, + "description": "BatteryOS is a software package for software virtualization of batteries, particularly grid-attached batteries in homes and home battery/solar installations. BatteryOS allows users to aggregate and partition batteries and supports a simple driver interface for connecting it to physical batteries. BatteryOS was developed as part of the TrustDER: Trusted, Private and Scalable Coordination of Distributed Energy Resources project at Stanford University, funded by the Department of Energy in Agreement DE-OE0000919. The project concluded in the summer of 2024.\n\nThe BatteryOS (BOS) package is consisted of software and drivers for creating and managing virtual batteries. It includes support for private battery aggregation. BatteryOSv1 was the first Python implementation; BatteryOSv2 was the first C++ implementation; BatteryOSv3 is the final, cleaned-up C++ implementation.", + "laborHours": 12859.2, + "languages": [], + "name": "BatteryOS", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Stanford-New-Energy-Systems/BatteryOS", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Battery_Lifecycle_Framework.json b/agency-indexes/DoE/Battery_Lifecycle_Framework.json new file mode 100644 index 00000000..5a2e9b6c --- /dev/null +++ b/agency-indexes/DoE/Battery_Lifecycle_Framework.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-24", + "metadataLastUpdated": "2024-09-11" + }, + "description": "The Battery Lifecycle (BLC) Framework is an open-source platform that provides tools to visualize and share battery data from material characterization, cell testing, manufacturing, and field testing through the technology development cycle. BLC has three components: data importers, a front-end for querying the data and creating visualizations, and an application programming interface to provide access to the data from Python. BLC has been deployed for tracking the development of a battery from the lab to a manufacturing line and systems installed in the field and for comparing studies of multiple cells of the same battery chemistry and configuration. The code was developed around Redash, a robust open-source extract-transform-load engine. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-4546 O", + "laborHours": 380.0, + "languages": [ + "Python", + "Jupyter Notebook", + "Shell" + ], + "name": "Battery Lifecycle Framework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/battery-archive-sandbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Battery_Storage_Evaluation_Tool,_version_1.x.json b/agency-indexes/DoE/Battery_Storage_Evaluation_Tool,_version_1.x.json new file mode 100644 index 00000000..e5abb659 --- /dev/null +++ b/agency-indexes/DoE/Battery_Storage_Evaluation_Tool,_version_1.x.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The battery storage evaluation tool developed at Pacific Northwest National Laboratory is used to run a one-year simulation to evaluate the benefits of battery storage for multiple grid applications, including energy arbitrage, balancing service, capacity value, distribution system equipment deferral, and outage mitigation. This tool is based on the optimal control strategies to capture multiple services from a single energy storage device. In this control strategy, at each hour, a lookahead optimization is first formulated and solved to determine the battery base operating point. The minute-by-minute simulation is then performed to simulate the actual battery operation.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab MCR" + ], + "name": "Battery Storage Evaluation Tool, version 1.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bayati_Kim_Saberi_random_graph_sampler.json b/agency-indexes/DoE/Bayati_Kim_Saberi_random_graph_sampler.json new file mode 100644 index 00000000..72b54f98 --- /dev/null +++ b/agency-indexes/DoE/Bayati_Kim_Saberi_random_graph_sampler.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-16" + }, + "description": "This software package implements the algorithm from a paper by Bayati, Kim, and Saberi (first reference below) to generate a uniformly random sample of a graph with a prescribed degree distribution.", + "laborHours": 1094.4, + "languages": [ + "MATLAB", + "C++", + "C" + ], + "name": "Bayati Kim Saberi random graph sampler", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/bisquik", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Baycal.json b/agency-indexes/DoE/Baycal.json new file mode 100644 index 00000000..5ab819fc --- /dev/null +++ b/agency-indexes/DoE/Baycal.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-01-25", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Bayesian Model Calibration (BayCal) toolkit is a software plugin for Risk Analysis Virtual Environment (RAVEN) framework, arming at inversely quantifying the uncertainties associated with simulation model parameters based on available experiment data. BayCal seeks statistical inference of the uncertain input parameters that are consistent with the available measurement data or observed data. The unique feature of BayCal is the capability to be linked with RAVEN to build corresponding calibration workflows for complex multi-physics simulations. In addition to be able to use the machine learning capability of RAVEN to significantly reduce the computational cost of expensive simulation models, another distinctive feature of BayCal is the capability to deal with high-dimensional correlated model outputs, such as time series observations at multiple locations, via principal component analysis (PCA) technique.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Baycal", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/BayCal", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BayesQuanTom.json b/agency-indexes/DoE/BayesQuanTom.json new file mode 100644 index 00000000..d024fe69 --- /dev/null +++ b/agency-indexes/DoE/BayesQuanTom.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "lukensjm@ornl.gov" + }, + "date": { + "created": "2021-03-12", + "metadataLastUpdated": "2021-03-12" + }, + "description": "This code provides examples of a new, self-contained approach for Bayesian quantum state estimation which offers improved computational efficiency compared to previous approaches. Leveraging advances in machine learning and statistics, our formulation relies on highly efficient preconditioned Crank-Nicolson sampling and a pseudo-likelihood. Details of the theory behind it can be found in our paper https://doi.org/10.1088/1367-2630/ab8efa", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "BayesQuanTom", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmlukens/BayesQuanTom", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bayesian_Estimator_of_Protein-Protein_Association_Probabilities.json b/agency-indexes/DoE/Bayesian_Estimator_of_Protein-Protein_Association_Probabilities.json new file mode 100644 index 00000000..9dbafa92 --- /dev/null +++ b/agency-indexes/DoE/Bayesian_Estimator_of_Protein-Protein_Association_Probabilities.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-17", + "metadataLastUpdated": "2024-01-31" + }, + "description": "The Bayesian Estimator of Protein-Protein Association Probabilities (BEPro3) is a software tool for estimating probabilities of protein-protein association between bait and prey protein pairs using data from multiple-bait, multiple-replicate, protein LC-MS/MS affinity isolation experiments. BEPro3 is public domain software, has been tested on Windows XP and version 10.4 or newer of the Mac OS 10.4, and is freely available. A user guide, example dataset with analysis and additional documentation are included with the BEPro3 download.", + "homepageURL": "http://www.pnl.gov/statistics/BEPro3", + "laborHours": 0.0, + "languages": [ + "R, JAVA" + ], + "name": "Bayesian Estimator of Protein-Protein Association Probabilities", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.pnl.gov/statistics/BEPro3", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.pnl.gov/statistics/BEPro3", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bayesian_Integration_of_multiscale_environmental_data.json b/agency-indexes/DoE/Bayesian_Integration_of_multiscale_environmental_data.json new file mode 100644 index 00000000..4cd279b6 --- /dev/null +++ b/agency-indexes/DoE/Bayesian_Integration_of_multiscale_environmental_data.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software is designed for efficiently integrating large-size of multi-scale environmental data using the Bayesian framework. Suppose we need to estimate the spatial distribution of variable X with high spatial resolution. The available data include (1) direct measurements Z of the unknowns with high resolution in a subset of the spatial domain (small spatial coverage), (2) measurements C of the unknowns at the median scale, and (3) measurements A of the unknowns at the coarsest scale but with large spatial coverage. The goal is to estimate the unknowns at the fine grids by conditioning to all the available data. We first consider all the unknowns as random variables and estimate conditional probability distribution of those variables by conditioning to the limited high-resolution observations (Z). We then treat the estimated probability distribution as the prior distribution. Within the Bayesian framework, we combine the median and large-scale measurements (C and A) through likelihood functions. Since we assume that all the relevant multivariate distributions are Gaussian, the resulting posterior distribution is a multivariate Gaussian distribution. The developed software provides numerical solutions of the posterior probability distribution. The software can be extended in several different ways to solve more general multi-scale data integration problems.", + "laborHours": 684.0, + "name": "Bayesian Integration of multiscale environmental data", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jschen83/Multiscale-Bayesian-Integration/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jschen83/Multiscale-Bayesian-Integration", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bayesian_Mulitple-Event_Location.json b/agency-indexes/DoE/Bayesian_Mulitple-Event_Location.json new file mode 100644 index 00000000..b604b081 --- /dev/null +++ b/agency-indexes/DoE/Bayesian_Mulitple-Event_Location.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Bayesloc is a statistical model of the multiple seismic location system, including event hypocenters, corrections to model-based travel time predictions, assessments precision for measurement phase arrival times, and phase lavels which indicate phase ray path.", + "homepageURL": "https://www-gs.llnl.gov/nuclear-threat-reduction/nuclear-explosion-monitoring/bayesloc", + "laborHours": 0.0, + "name": "Bayesian Mulitple-Event Location", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www-gs.llnl.gov/nuclear-threat-reduction/nuclear-explosion-monitoring/bayesloc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bayesian_Multitask_with_Structure_Learning.json b/agency-indexes/DoE/Bayesian_Multitask_with_Structure_Learning.json new file mode 100644 index 00000000..f8bf7bcf --- /dev/null +++ b/agency-indexes/DoE/Bayesian_Multitask_with_Structure_Learning.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "Software including a Bayesian multitask learning model. The pipeline includes functionality to process data, train, evaluate models, and generate reports.", + "laborHours": 0.0, + "languages": [], + "name": "Bayesian Multitask with Structure Learning", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/bmsl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bayesian_Segmentation__BCNN__v.1.json b/agency-indexes/DoE/Bayesian_Segmentation__BCNN__v.1.json new file mode 100644 index 00000000..89d0b642 --- /dev/null +++ b/agency-indexes/DoE/Bayesian_Segmentation__BCNN__v.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-04" + }, + "description": "Deep learning has been applied with great success to the segmentation of 3D X-Ray Computed Tomography (CT) scans. Establishing the credibility of these segmentations requires uncertainty quantification (UQ) to identify problem areas. Bayesian neural networks (BNNs), which use variational inference to learn the posterior distribution of the neural network weights, have been proposed to incorporate UQ into deep learning models. This software is an implementation of a novel 3D Bayesian convolutional neural network (BCNN) that provides accurate binary segmentations and uncertainty maps for 3D volumes. In particular, the uncertainty maps generated by this BCNN capture continuity and visual gradients, making them interpretable as confidence intervals for segmentation usable in numerical simulations. SAND2019-12927 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 516.8, + "languages": [ + "Python" + ], + "name": "Bayesian Segmentation (BCNN) v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/bcnn", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bayesian_Support_Vector_Machine__BSVM_.json b/agency-indexes/DoE/Bayesian_Support_Vector_Machine__BSVM_.json new file mode 100644 index 00000000..6ac6ead7 --- /dev/null +++ b/agency-indexes/DoE/Bayesian_Support_Vector_Machine__BSVM_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "A machine learning based approach is developed to detect events that have rarely been seen in the historical data. The data can include building energy consumption, sensor data, environmental data and any data that may affect the building's energy consumption. The algorithm is a modified nonlinear Bayesian support vector machine, which examines daily energy consumption profile, detect the days with abnormal events, and diagnose the cause of the events.", + "homepageURL": "https://store.pnnl.gov/content/bayesian-support-vector-machine-bsvm", + "laborHours": 0.0, + "languages": [ + "Matlab R2014a" + ], + "name": "Bayesian Support Vector Machine (BSVM)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/bayesian-support-vector-machine-bsvm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bayesian_calibration_of_stochastic_agent_based_model_via_random_forest.json b/agency-indexes/DoE/Bayesian_calibration_of_stochastic_agent_based_model_via_random_forest.json new file mode 100644 index 00000000..241a2646 --- /dev/null +++ b/agency-indexes/DoE/Bayesian_calibration_of_stochastic_agent_based_model_via_random_forest.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-10-18" + }, + "description": "SAND2024-11403O\nThe Bayesian Calibration of Stochastic Agent-based Model via Random Forest is a code that was developed in concurrence with an article by the same name that was written for a journal. The code reproduces simulation results and plots from the article. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 603090.4, + "languages": [ + "Python", + "R" + ], + "name": "Bayesian calibration of stochastic agent based model via random forest", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Bayesian-calibration-of-stochastic-agent-based-model-via-random-forest", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bead-Tracking_Toolbox_for_MATLAB.json b/agency-indexes/DoE/Bead-Tracking_Toolbox_for_MATLAB.json new file mode 100644 index 00000000..a823bf7d --- /dev/null +++ b/agency-indexes/DoE/Bead-Tracking_Toolbox_for_MATLAB.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "A collection of MATLAB scripts forming a toolbox for video (frame by frame) detection and tracking of beads imaged with fluorescence microscope for estimating bead flow and location tracks. Scripts accept tiff image stacks of video frames and provide bead locations and tracked positions over frames in stack. Various utility functions are also provided to assist in data I/O. A custom solution for specific data source - specifically, the software works well for noisy/out of focus florescence microscopy images.", + "laborHours": 7645.6, + "languages": [ + "MATLAB/2018a" + ], + "name": "Bead-Tracking Toolbox for MATLAB", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dnbornl/beadtracking", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Beam_Instrument_Development_System.json b/agency-indexes/DoE/Beam_Instrument_Development_System.json new file mode 100644 index 00000000..11754808 --- /dev/null +++ b/agency-indexes/DoE/Beam_Instrument_Development_System.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "Beam Instrumentation Development System (BIDS) is a collection of common support libraries and modules developed during a series of Low-Level Radio Frequency (LLRF) control and timing/synchronization projects. BIDS includes a collection of Hardware Description Language (HDL) libraries and software libraries. The BIDS can be used for the development of any FPGA-based system, such as LLRF controllers. HDL code in this library is generic and supports common Digital Signal Processing (DSP) functions, FPGA-specific drivers (high-speed serial link wrappers, clock generation, etc.), ADC/DAC drivers, Ethernet MAC implementation, etc.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "G++, ISE" + ], + "name": "Beam Instrument Development System", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Beam_Propagator_for_Weather_Radars,_Modules_1_and_2.json b/agency-indexes/DoE/Beam_Propagator_for_Weather_Radars,_Modules_1_and_2.json new file mode 100644 index 00000000..f77643be --- /dev/null +++ b/agency-indexes/DoE/Beam_Propagator_for_Weather_Radars,_Modules_1_and_2.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "This program simulates the beam propagation of weather radar pulses under particular and realistic atmospheric conditions (without using the assumption of standard refraction conditions). It consists of two modules: radiosondings_refract_index_many.pro (MAIN MODULE) beam_propagation_function.pro(EXTERNAL FUNCTION) FOR THE MAIN MODULE, THE CODE DOES OUTPUT--INTO A FILE--THE BEAM HEIGHT AS A FUNCTION OF RANGE. THE RADIOSONDE INPUT FILES SHOULD BE ALREADY AVAILABLE BY THE USER. FOR EXAMPLE, RADIOSONDE OBSERVATION FILES CAN BE OBTAINED AT: RADIOSONDE OBSERVATIONS DOWNLOADED AT \"http://weather.uwyo.edu/upperair/soounding.html\" OR \"http://jervis.pyr.ec.gc.ca\" THE EXTERNAL FUNCTION DOES THE ACTUAL COMPUTATION OF BEAM PROPAGATION. IT INCLUDES CONDITIONS OF ANOMALOUS PROPAGATION AND NEGATIVE ELEVATION ANGLES. THE EQUATIONS USED HERE WERE DERIVED BY EDWIN CAMPOS, BASED ON THE SNELL-DESCARTES LAW OF REFRACTION, CONSIDERING THE EARTH CURVATURE. THE PROGRAM REQUIRES A COMPILER FOR THE INTERACTIVE DATA LANGUAGE (IDL). DESCRIPTION AND VALIDATION DETAILS HAVE BEEN PUBLISHED IN THE PEER-REVIEWED SCIENTIFIC LITERATURE, AS FOLLOWS: Campos E. 2012. Estimating weather radar coverage over complex terrain, pp.26-32, peer reviewed, in Weather Radar and Hydrology, edited by Moore RJ, Cole SJ and Illingworth AJ. International Association of Hydrological Sciences (IAHS) Press, IAHS Publ. 351. ISBN 978-1-907161-26-1.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [ + "Interactive Data Language" + ], + "name": "Beam Propagator for Weather Radars, Modules 1 and 2", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bearing-less_Centrifugal_Pump__non-levitated,_non-electromagnetic_.json b/agency-indexes/DoE/Bearing-less_Centrifugal_Pump__non-levitated,_non-electromagnetic_.json new file mode 100644 index 00000000..1d0db3b9 --- /dev/null +++ b/agency-indexes/DoE/Bearing-less_Centrifugal_Pump__non-levitated,_non-electromagnetic_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-06-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "3D printing design documents for a bearing-less centrifugal water pump comprised of an impeller rotor enclosing a permanent magnet which is\ndriven by a second permanent magnet rotated by an electric motor.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Bearing-less Centrifugal Pump (non-levitated, non-electromagnetic)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Becquerel__Bq__v0.1.json b/agency-indexes/DoE/Becquerel__Bq__v0.1.json new file mode 100644 index 00000000..e6c55b3e --- /dev/null +++ b/agency-indexes/DoE/Becquerel__Bq__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-25", + "metadataLastUpdated": "2019-09-23" + }, + "description": "\tBecquerel is a Python package for analyzing nuclear spectroscopic measurements. The core functionalities are reading and writing different spectrum file types, fitting spectral features, performing detector calibrations, and interpreting measurement results. It will include tools for plotting radiation spectra and fits of different spectral features, as well as convenient access to tabulated nuclear data. It relies heavily on the standard scientific Python stack of numpy, scipy, matplotlib, and pandas. It is intended to be general-purpose enough that it can be useful to anyone from an undergraduate taking a laboratory course to the advanced researcher.", + "laborHours": 4757.6, + "languages": [], + "name": "Becquerel (Bq) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-anp/becquerel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bedrock.json b/agency-indexes/DoE/Bedrock.json new file mode 100644 index 00000000..49d1bda4 --- /dev/null +++ b/agency-indexes/DoE/Bedrock.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "Bedrock is Mochi's service bootstrapping mechanism.", + "laborHours": 0.0, + "languages": [], + "name": "Bedrock", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-bedrock/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-bedrock", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bedrock_v1.0.json b/agency-indexes/DoE/Bedrock_v1.0.json new file mode 100644 index 00000000..70a0a555 --- /dev/null +++ b/agency-indexes/DoE/Bedrock_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-01", + "metadataLastUpdated": "2019-10-02" + }, + "description": "Bedrock is a code set of firmware libraries written in Verilog used by LBNL for accelerator controls and other applications. A set of commonly used building blocks in DSP (Digital Signal Processing) are present such as a CORDIC implementation, CIC filters, etc. Other useful functions include an in-fabric Ethernet core implementation to communicate with FPGAs over the network and support drivers for components such as ADCs and DACs we have used in our designs. The code base is intended to serve as a support library for HDL designs.", + "laborHours": 35689.6, + "languages": [], + "name": "Bedrock v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/Bedrock", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Behavior,_Energy,_Autonomy,_Mobility_Modeling_Framework.json b/agency-indexes/DoE/Behavior,_Energy,_Autonomy,_Mobility_Modeling_Framework.json new file mode 100644 index 00000000..c523ee2b --- /dev/null +++ b/agency-indexes/DoE/Behavior,_Energy,_Autonomy,_Mobility_Modeling_Framework.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2019-10-23" + }, + "description": "The Behavior, Energy, Autonomy, and Mobility (BEAM) model is an integrated, agent-based travel demand simulation framework. Individual agents express preferences through a utility-maximizing evolutionary algorithm that minimizes each individual's cost and time spent traveling via diverse modal options, including the competition for scarce supply resources such as parking spaces and charging infrastructure. BEAM simulates the essential elements that compose a dynamic transportation system. From the road network, parking and charging infrastructure, to the transit system and a synthetic population with plans and preferences, the virtual system is an amalgamation of multiple spatially resolved layers that together represent an integrated transportation system. BEAM is an extension to the MATSim (Multi-Agent Transportation Simulation) model, where agents employ reinforcement learning across successive simulated days to maximize their personal utility through plan mutation (exploration) and selecting between previously executed plans (exploitation). The BEAM model shifts some of the behavioral emphasis in MATSim from across-day planning to within-day planning, where agents dynamically respond to the state of the system during the mobility simulation. In BEAM, agents can plan across all major modes of travel including driving, walking, biking, transit, and demand-responsive ride hailing.", + "laborHours": 58200.8, + "languages": [], + "name": "Behavior, Energy, Autonomy, Mobility Modeling Framework", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-UCB-STI/beam", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Behavior,_Energy,_Autonomy,_Mobility_Modeling_Framework__BEAM__v1.0.json b/agency-indexes/DoE/Behavior,_Energy,_Autonomy,_Mobility_Modeling_Framework__BEAM__v1.0.json new file mode 100644 index 00000000..b85668c2 --- /dev/null +++ b/agency-indexes/DoE/Behavior,_Energy,_Autonomy,_Mobility_Modeling_Framework__BEAM__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2024-10-24", + "metadataLastUpdated": "2024-10-24" + }, + "description": "The Behavior, Energy, Autonomy, and Mobility (BEAM) model is an integrated, agent-based travel demand simulation framework. Individual agents express preferences through a utility- maximizing evolutionary algorithm that minimizes each individual\u2019s cost and time spent traveling via diverse modal options, including the competition for scarce supply resources such as parking spaces and charging infrastructure. BEAM simulates the essential elements that compose a dynamic transportation system. From the road network, parking and charging infrastructure, to the transit system and a synthetic population with plans and preferences, the virtual system is an amalgamation of multiple spatially resolved layers that together represent an integrated transportation system. \n\nBEAM is an extension to the MATSim (Multi-Agent Transportation Simulation) model, where agents employ reinforcement learning across successive simulated days to maximize their personal utility through plan mutation (exploration) and selecting between previously executed plans (exploitation). The BEAM model shifts some of the behavioral emphasis in MATSim from across-day planning to within- day planning, where agents dynamically respond to the state of the system during the mobility simulation. In BEAM, agents can plan across all major modes of travel including driving, walking, biking, transit, and demand-responsive ride hailing. It is designed to integrate with other open source transportation models, such as ActivitySim.", + "laborHours": 58200.8, + "languages": [], + "name": "Behavior, Energy, Autonomy, Mobility Modeling Framework (BEAM) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-UCB-STI/beam", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Behavioral_Models_of_Differential_Models_with_a_Hammerstein_Model.json b/agency-indexes/DoE/Behavioral_Models_of_Differential_Models_with_a_Hammerstein_Model.json new file mode 100644 index 00000000..3a17cf42 --- /dev/null +++ b/agency-indexes/DoE/Behavioral_Models_of_Differential_Models_with_a_Hammerstein_Model.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "SAND2024-12593O\nThe Behavioral Models of Differential Models with a Hammerstein Model code demonstrates how to generate training data, how to use the training data to create a transfer function for the linear time invariant portion of the behavioral model, and how to test that model. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Behavioral Models of Differential Models with a Hammerstein Model", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Behind-the-meter_Infrastructure_Costs_for_Electrification_Progression__BICEP__Model.json b/agency-indexes/DoE/Behind-the-meter_Infrastructure_Costs_for_Electrification_Progression__BICEP__Model.json new file mode 100644 index 00000000..5e39c6e4 --- /dev/null +++ b/agency-indexes/DoE/Behind-the-meter_Infrastructure_Costs_for_Electrification_Progression__BICEP__Model.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Behind-the-meter Infrastructure Costs for Electrification Progression (BICEP) model quantifies the behind-the-meter (BTM) electrical upgrades required for decarbonization through electrification by comparing the expected change in capacity requirements from the electrification technologies to the existing capacity in distributed energy resources (DER) stock (including buildings).", + "laborHours": 0.0, + "languages": [], + "name": "Behind-the-meter Infrastructure Costs for Electrification Progression (BICEP) Model", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/BICEP", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Benchmark_Algorithm_for_RadioNuclide_Identification_v1.0.json b/agency-indexes/DoE/Benchmark_Algorithm_for_RadioNuclide_Identification_v1.0.json new file mode 100644 index 00000000..edb5776e --- /dev/null +++ b/agency-indexes/DoE/Benchmark_Algorithm_for_RadioNuclide_Identification_v1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-08", + "metadataLastUpdated": "2020-05-08" + }, + "description": "Benchmark Algorithm for Radio-Nuclide Identification (BARNI) is an automatic radionuclide identification\ntool for use with gamma-ray spectra. BARNI is designed to serve as a comparative tool for commercial\nvendor algorithms, such as those found in RadioIsotope Identification Devices (RIID). The tool\nincorporates an automated training routine allowing BARNI's classifier to be trained for a variety of\ndetectors. The identification algorithm uses a peak search, the results of which are used to build features\nthat are subsequently used for training a classifier. The user provided spectral templates allow BARNI to\nbe trained for any detector of the user's choice.\nIs", + "laborHours": 1641.6, + "languages": [], + "name": "Benchmark Algorithm for RadioNuclide Identification v1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/barni", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Benchmarking_and_Energy_Saving_Tool_for_Low_Carbon_Cities__BEST_Cities_.json b/agency-indexes/DoE/Benchmarking_and_Energy_Saving_Tool_for_Low_Carbon_Cities__BEST_Cities_.json new file mode 100644 index 00000000..eeeefc9b --- /dev/null +++ b/agency-indexes/DoE/Benchmarking_and_Energy_Saving_Tool_for_Low_Carbon_Cities__BEST_Cities_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "BEST-Cities is designed to provide city authorities with strategies they can follow to reduce city-wide carbon dioxide (CO2) and methane (CH4) emissions. The tool quickly assesses local energy use and energy-related CO2 emissions across nine sectors (i.e., industry, public and commercial buildings, residential buildings, transportation, power and heat, street lighting, water & wastewater, solid waste, and urban green space), giving officials a comprehensive perspective on their local carbon performance. Cities can also use the tool to benchmark their energy and emissions performance to other cities inside and outside China, and identify those sectors with the greatest energy saving and emissions reduction potential.", + "homepageURL": "https://china.lbl.gov/best-cities", + "laborHours": 0.0, + "languages": [], + "name": "Benchmarking and Energy Saving Tool for Low Carbon Cities (BEST Cities)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://china.lbl.gov/best-cities", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://china.lbl.gov/best-cities", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/BerkeleyGW.json b/agency-indexes/DoE/BerkeleyGW.json new file mode 100644 index 00000000..85091af3 --- /dev/null +++ b/agency-indexes/DoE/BerkeleyGW.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "mdelben@lbl.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-20" + }, + "description": "BerkeleyGW is a versatile, massively parallel, GPU-enabled, modular software package for quantum many-body perturbation theory applied to study the excited state properties of electrons in materials. It employs the ab-initio GW and GW plus Bethe-Salpeter equation (GW-BSE) methods and beyond. It can be used to investigate a wide range of materials from bulk crystals to clusters and 2D/1D materials, adapting to insulating, metallic, and semi-metallic systems alike. Journal article: https://doi.org/10.1016/j.cpc.2011.12.006", + "homepageURL": "https://berkeleygw.org/download", + "laborHours": 0.0, + "languages": [], + "name": "BerkeleyGW", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://berkeleygw.org/download", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_Anomaly_Detection__BAD__v1.0.json b/agency-indexes/DoE/Berkeley_Anomaly_Detection__BAD__v1.0.json new file mode 100644 index 00000000..d4b19036 --- /dev/null +++ b/agency-indexes/DoE/Berkeley_Anomaly_Detection__BAD__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-25", + "metadataLastUpdated": "2019-01-31" + }, + "description": "The software is for detecting and identifying anomalies within gamma-ray spectra. The design enables quick implementation, testing, comparison, and deployment of different anomaly and identification algorithms. The software currently contains implementations of four algorithms, two of which are common place within the field, and two that novel research products from this effort.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 3815.2, + "languages": [], + "name": "Berkeley Anomaly Detection (BAD) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_Disk_Resource_Manager.json b/agency-indexes/DoE/Berkeley_Disk_Resource_Manager.json new file mode 100644 index 00000000..92323eaf --- /dev/null +++ b/agency-indexes/DoE/Berkeley_Disk_Resource_Manager.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "The Berkeley Disk Resource Manager (B-DRM) is a middleware component whose function is to provide dynamic space allocation and file management of a shared disk system on the Grid. It provides space allocation and dynamic information on storage availability for the planning and execution of Grid jobs. The B-DRM manages two types of resources: space and files. Vi1en managing space, the B-DRM allocates space to the requesting client based on a default space quota, Then managing files, the B-DRM allocates space for files, invokes file transfer services to move files into the space, pins files for a certain lifetime, releases files upon the client's request, and uses file replacement policies to optimize the use of the shared space. The B-DRM is designed to provide effective sharing of files, by monitoring the activity of shared files, and making dynamic decisions on which files to replace when space is needed. In addition, the B-DRM performs automatic garbage collection of unused files when space is needed by removing selected files that were released by the client or whose lifetime has expired. The BDRM supports requests to get multiple files in a single call, manages a queue of the requested files, brings in as many files as the space quota permits, and continues to reuse the space when files are released to stream files to the client until the entire request is satisfied. Similarly, the B-DRM supports requests to put multiple files into its space, streaming files into the allocated space and reusing the space if necessary.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "gcc 2.9x" + ], + "name": "Berkeley Disk Resource Manager", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_Efficient_Long-Read_to_Long-Read_Aligner_and_Overlapper__BELLA__v1.0.json b/agency-indexes/DoE/Berkeley_Efficient_Long-Read_to_Long-Read_Aligner_and_Overlapper__BELLA__v1.0.json new file mode 100644 index 00000000..58826f0d --- /dev/null +++ b/agency-indexes/DoE/Berkeley_Efficient_Long-Read_to_Long-Read_Aligner_and_Overlapper__BELLA__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2018-08-31" + }, + "description": "BELLA is a long-read overlapper and read-to-read aligner that exploits novel approaches for selecting reliable k-mer seeds for filtering and for detecting overlapping read pairs to reconstruct the whole genome. BELLA uses a sparse matrix-matrix multiplication for high-performance overlap detection and then performs pairwise alignment on the overlapping read pairs. BELLA can be built with different pre-existing aligners to use on each read pair, so precision rates are determined by those aligners. Our evaluations include real and synthetic datasets with varying size and complexity and include recall, precision, and running time. BELLA's overlap detection retains nearly all true alignments, with recall rates that exceed other aligners, yet it filters enough read pairs that the running time, including pairwise alignments, is closer to tools that only perform overlapping and is significantly faster than tools that also perform alignment", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper (BELLA) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/aydozz/longreads", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_Hierarchical_Resource_Manager.json b/agency-indexes/DoE/Berkeley_Hierarchical_Resource_Manager.json new file mode 100644 index 00000000..55d0466e --- /dev/null +++ b/agency-indexes/DoE/Berkeley_Hierarchical_Resource_Manager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "This software was developed by Lawrence Berkeley National Laboratory.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Hierarchical Resource Manager", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_Lab_Checkpoint_Restart_for_Linux.json b/agency-indexes/DoE/Berkeley_Lab_Checkpoint_Restart_for_Linux.json new file mode 100644 index 00000000..db14cd72 --- /dev/null +++ b/agency-indexes/DoE/Berkeley_Lab_Checkpoint_Restart_for_Linux.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This package implements system-level checkpointing of scientific applications running on Linux clusters in a manner suitable for implementing preemption, migration and fault recovery by a batch scheduler The design includes documented interfaces for a cooperating application or library to implement extensions to the checkpoint system, such as consistent checkpointing of distributed MPI applications Using this package with an appropriate MPI implementation, the vast majority of scientific applications which use MPI for communication are checkpointable without any modifications to the application source code. Extending VMAdump code used in the bproc system, the BLCR kernel modules provide three additional features necessary for useful system-level checkpointing of scientific applications(installation of bproc is not required to use BLCR) First, this package provides the bookkeeping and coordination required for checkpointing and restoring multi-threaded and multi-process applications running on a single node Secondly, this package provides a system call interface allowing checkpoints to be requested by any authorized process, such as a batch scheduler. Thirdly, this package provides a system call interface allowing applications and/or application libraries to extend the checkpoint capabilities in user space, for instance to provide coordination of checkpoints of distributed MPI applications. The \"Iibcr\" library in this package implements a wrapper around the system call interface exported by the kernel modules, and maintains bookkeeping to allow registration of callbacks by runtime libraries This library also provides the necessary thread-safety and signal-safety mechanisms Thus, this library provides the means for applications and run-time libraries, such as MPI, to register callback functions to be run when a checkpoint is taken or when restarting from one. This library may also be used as a LD_PRELOAD to enable checkpointing of applications with development releases of BLCR (which cannot preempt unmodified applications otherwise). This package also includes simple command line utilities to request a checkpoint or restart of a process. These provide the means for a user, system administrator, or batch scheduler to use BLCR.", + "homepageURL": "https://crd.lbl.gov/departments/computer-science/class/research/past-projects/BLCR", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Lab Checkpoint/Restart for Linux", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://crd.lbl.gov/departments/computer-science/class/research/past-projects/BLCR", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://crd.lbl.gov/departments/computer-science/class/research/past-projects/BLCR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_Lab_Finite_Element_Framework__BELFEM__v0.1.json b/agency-indexes/DoE/Berkeley_Lab_Finite_Element_Framework__BELFEM__v0.1.json new file mode 100644 index 00000000..deb26e38 --- /dev/null +++ b/agency-indexes/DoE/Berkeley_Lab_Finite_Element_Framework__BELFEM__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "The software program, referred to as BELFEM, is a specialized finite element code designed for the magnetodynamic modeling of high-temperature superconducting (HTS) tapes. It incorporates novel mixed finite element formulations, particularly the h-\u03d5-formulation with thin-shell simplification, to efficiently simulate larger geometries. This methodology is extremely promising for predicting the electrodynamic performance of HTS tapes used in superconducting cables and magnets, offering the benefit of reduced computational cost. Compared to similar technologies like COMSOL Multiphysics and GetDP, BELFEM's performance benchmarking indicates superior efficiency in its thin-shell implementation. In the future, it will also support features like thermal coupling and inter-tape current sharing, enhancing its utility in research and development, particularly in nuclear fusion applications. The intent is to develop BELFEM as a robust and efficient tool for the HTS community, contributing to the analysis and design of superconducting cables and magnets.", + "laborHours": 97416.8, + "languages": [], + "name": "Berkeley Lab Finite Element Framework (BELFEM) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmesse/belfem.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_Lab_WINDOW.json b/agency-indexes/DoE/Berkeley_Lab_WINDOW.json new file mode 100644 index 00000000..891d81b6 --- /dev/null +++ b/agency-indexes/DoE/Berkeley_Lab_WINDOW.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "WINDOW features include: - Microsoft Windows TM interface - algorithms for the calculation of total fenestration product U-values and Solar Heat Gain Coefficient consistent with ASHRAE SPC 142, ISO 15099, and the National Fenestration Rating Council - a Condensation Resistance Index in accordance with the NFRC 500 Standard - and integrated database of properties - imports data from other LBNL window analysis software: - Import THERM file into the Frame Library - Import records from IGDB and OPtics5 into the Glass Library for the optical properties of coated and uncoated glazings, laminates, and applied films. Program Capabilities WINDOW 7.2 offers the following features: The ability to analyze products made from any combination of glazing layers, gas layers, frames, spacers, and dividers under any environmental conditions and at any tilt; The ability to model complex glazing systems such as venetian blinds and roller shades. Directly accessible libraries of window system components, (glazing systems, glazing layers, gas fills, frame and divider elements), and environmental conditions; The choice of working in English (IP), or Systeme International (SI) units; The ability to specify the dimensions and thermal properties of each frame element (header, sills, jamb, mullion) in a window; A multi-band (wavelength-by-wavelength) spectral model; A Glass Library which can access spectral data files for many common glazing materials from the Optics5database; A night-sky radiative model; A link with the DOE-2.1E and Energy Plus building energy analysis program. Performance Indices and Other Results For a user-defined fenestration system and user-defined environmental conditions, WINDOW calculates: The U-value, solar heat gain coefficient, shading coefficient, and visible transmittance for the complete window system; The U-value, solar heat gain coefficient, shading coefficient, and visible transmittance for the glazing system (center-of-glass values); The U-values of the frame and divider elements and corresponding edge-of-glass areas (based on generic correlations); The total solar and visible transmittance and reflectances of the glazing system. Color properties, i.e. L*, a*, and b* color coordinates, dominant wavelength, and purity for transmitted and reflected (outdoor) solar radiation; The damage-weighted transmittance of the glazing system between 0.3 an 0.38 microns; The angular dependence of the solar and visible transmittances, solar and visible reflectances, solar absorptance, and solar heat gain coefficient of the glazing system; The percent relative humidity of the inside and outside air for which condensation will occur on the interior and exterior glazing surfaces respectively; The center-of-glass temperature distribution.", + "homepageURL": "https://windows.lbl.gov/software/window", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Lab WINDOW", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://windows.lbl.gov/window-license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://windows.lbl.gov/software/window", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_Lab_WINDOW_Calc_Engine__CalcEngine__v1.json b/agency-indexes/DoE/Berkeley_Lab_WINDOW_Calc_Engine__CalcEngine__v1.json new file mode 100644 index 00000000..26822621 --- /dev/null +++ b/agency-indexes/DoE/Berkeley_Lab_WINDOW_Calc_Engine__CalcEngine__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-08-13" + }, + "description": "Calculation of thermal and optical properties of glass, windows and shades. Calculation code only, no GUI.", + "laborHours": 1626.4, + "languages": [], + "name": "Berkeley Lab WINDOW Calc Engine (CalcEngine) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/WinCalc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_Lab_WINDOW_Calc_Engine__CalcEngine__v2.json b/agency-indexes/DoE/Berkeley_Lab_WINDOW_Calc_Engine__CalcEngine__v2.json new file mode 100644 index 00000000..831f69d4 --- /dev/null +++ b/agency-indexes/DoE/Berkeley_Lab_WINDOW_Calc_Engine__CalcEngine__v2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-22", + "metadataLastUpdated": "2019-05-28" + }, + "description": "Calculation of thermal and optical properties of glass, windows, and shades. Calculational code only, no GUI.\n\nThe software hosted at this repository is one out of five repositories that make up this entire project. The others can be found at the following DOIs: 10.11578/dc.20190522.1, 10.11578/dc.20190522.2, 10.11578/dc.20190522.4 and 10.11578/dc.20190522.5.", + "laborHours": 714.4, + "languages": [], + "name": "Berkeley Lab WINDOW Calc Engine (CalcEngine) v2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/Windows-CalcStandards", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_Nuclear_Data_Cloud__BDC__v2.3.json b/agency-indexes/DoE/Berkeley_Nuclear_Data_Cloud__BDC__v2.3.json new file mode 100644 index 00000000..738d1109 --- /dev/null +++ b/agency-indexes/DoE/Berkeley_Nuclear_Data_Cloud__BDC__v2.3.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-29" + }, + "description": "The software was developed to serve and curate arbitrarily large datasets comprising data acquired from various mobile platforms. The software is contained in a number of server and client libraries. The former manage the ingestion, indexing, querying, and serving of the data. The latter libraries are distributed for Linux, Mac OSX, and Windows and enable users to interact with data downloaded from the service either in the form of an HDF5 file or streamed in a BSON data chunk. Using the Berkeley Data Cloud, researchers from varying fields can collaborate, compare results and curate both their raw data and the derived products of their analysis.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Nuclear Data Cloud (BDC) v2.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_PhyloChip_Analysis_Algorithm_2007.json b/agency-indexes/DoE/Berkeley_PhyloChip_Analysis_Algorithm_2007.json new file mode 100644 index 00000000..773a709c --- /dev/null +++ b/agency-indexes/DoE/Berkeley_PhyloChip_Analysis_Algorithm_2007.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-22", + "metadataLastUpdated": "2019-01-31" + }, + "description": "The Berkeley PhyloChip Analysis Algorithm 2007 (BPAA-07) interprets the raw fluorescent intensity values collected from the PhyloChip surface and produces quantitative values corresponding to the abundance of each microbe within a PhyloChip sample. Additionally the algorithm produces a confidence score for the detection of each microbe.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 2219.2, + "languages": [], + "name": "Berkeley PhyloChip Analysis Algorithm 2007", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_Quantitative_Genome_Browser.json b/agency-indexes/DoE/Berkeley_Quantitative_Genome_Browser.json new file mode 100644 index 00000000..a7e5b52b --- /dev/null +++ b/agency-indexes/DoE/Berkeley_Quantitative_Genome_Browser.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "The Berkeley Quantitative Genome Browser provides graphical browsing functionality for genomic data organized, at a minimum, by sequence and position. While supporting the annotation browsing features typical of many other genomic browsers, additional emphasis is placed on viewing and utilizing quantitative data. Data may be read from GFF, SGR, FASTA or any column delimited format. Once the data has been read into the browser's buffer, it may be searched. filtered or subjected to mathematical transformation. The browser also supplies some graphical design manipulation functionality geared towards preparing figures for presentations or publication. A plug-in mechanism enables development outside the core functionality that adds more advanced or esoteric analysis capabilities. BBrowse's development and distribution is open-source and has been built to run on Linux, OSX and MS Windows operating systems.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "g++ 4.2.0 or later" + ], + "name": "Berkeley Quantitative Genome Browser", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_Quantum_Synthesis_Toolkit__BQSKit__v1.json b/agency-indexes/DoE/Berkeley_Quantum_Synthesis_Toolkit__BQSKit__v1.json new file mode 100644 index 00000000..66f50f38 --- /dev/null +++ b/agency-indexes/DoE/Berkeley_Quantum_Synthesis_Toolkit__BQSKit__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-03", + "metadataLastUpdated": "2021-06-03" + }, + "description": "The Berkeley Quantum Synthesis Toolkit (BQSKit) is an optimizing quantum compiler and research vehicle that combines ideas from several projects at LBNL into one easily accessible and quickly extensible software package. The ideas in the QFAST, QSearch, LEAP, and QFactor software tools (all licensed through ipo.lbl.gov) all build upon one another. By combining these into one package, we create symbiotic interactions between the tools. This means better results, better throughput, less to maintain, and greater surface area to the public. Additionally, the BQSKit tool will create a research platform for future work here at LBNL.", + "laborHours": 0.0, + "languages": [], + "name": "Berkeley Quantum Synthesis Toolkit (BQSKit) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BQSKit/bqskit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_Unified_Parallel_C__BUPC__Compiler.json b/agency-indexes/DoE/Berkeley_Unified_Parallel_C__BUPC__Compiler.json new file mode 100644 index 00000000..ad283292 --- /dev/null +++ b/agency-indexes/DoE/Berkeley_Unified_Parallel_C__BUPC__Compiler.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-05" + }, + "description": "This program is a portable, open-source, compiler for the UPC language. It is based on the Open64 framework and has extensive support for optimizations. This compiler operates by translating UPC into ANSI/ISO C for compilation by a native compiler and linking with the UPC Runtime Library. This design eases portability to both shared- and distributed-memory parallel architectures. For proper operation it requires the \"Berkeley Unified Parallel C (UPC) Runtime Library\" and its dependencies. \n", + "laborHours": 2197342.4, + "languages": [], + "name": "Berkeley Unified Parallel C (BUPC) Compiler", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upc-translator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Berkeley_Unified_Parallel_C__UPC__runtime_library.json b/agency-indexes/DoE/Berkeley_Unified_Parallel_C__UPC__runtime_library.json new file mode 100644 index 00000000..f903bf87 --- /dev/null +++ b/agency-indexes/DoE/Berkeley_Unified_Parallel_C__UPC__runtime_library.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-08-31", + "metadataLastUpdated": "2018-09-04" + }, + "description": "This software comprises a portable, open-source implementation of a runtime library to support applications written in the Unified Parallel C (UPC) language. This library implements the UPC-specific functionality, including shared-memory allocation and distributed locks. The network-dependent functionality is implemented as a thin wrapper around the separate GASNet (Global-Address Space Networking) library, which is required for operation. This software implements the \"Berkeley UPC Runtime Specification\", which is targeted by at least four separate UPC compiler front-ends. The implementation is highly portable and runs over hardware ranging from laptops to custom supercomputers. An external library is required for certain local memory allocation operations; a well-defined interface allows for multiple implementations of this library, but at present the \"umalloc\" library from LBNL is the only compatible implementation.", + "laborHours": 91230.4, + "languages": [], + "name": "Berkeley Unified Parallel C (UPC) runtime library", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upc-runtime", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bethe-Salpeter_Eigenvalue_Solver_Package__BSEPACK__v0.1.json b/agency-indexes/DoE/Bethe-Salpeter_Eigenvalue_Solver_Package__BSEPACK__v0.1.json new file mode 100644 index 00000000..30d02839 --- /dev/null +++ b/agency-indexes/DoE/Bethe-Salpeter_Eigenvalue_Solver_Package__BSEPACK__v0.1.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The BSEPACK contains a set of subroutines for solving the Bethe-Salpeter Eigenvalue (BSE) problem. This type of problem arises in this study of optical excitation of nanoscale materials. The BSE problem is a structured non-Hermitian eigenvalue problem. The BSEPACK software can be used to compute all or subset of eigenpairs of a BSE Hamiltonian. It can also be used to compute the optical absorption spectrum without computing BSE eigenvalues and eigenvectors explicitly. The package makes use of the ScaLAPACK, LAPACK and BLAS.", + "homepageURL": "https://sites.google.com/a/lbl.gov/bsepack", + "laborHours": 0.0, + "languages": [ + "FORTRAN" + ], + "name": "Bethe-Salpeter Eigenvalue Solver Package (BSEPACK) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sites.google.com/a/lbl.gov/bsepack/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sites.google.com/a/lbl.gov/bsepack", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Better_Userspace_HPSS_File_System.json b/agency-indexes/DoE/Better_Userspace_HPSS_File_System.json new file mode 100644 index 00000000..0d35144f --- /dev/null +++ b/agency-indexes/DoE/Better_Userspace_HPSS_File_System.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "BUHFS is a fuse-based POSIX compliant filesystem interface for HPSS. BUHFS was written to provide users with a stable, POSIX compliant interface to EMSL new HPSS based Scientific Data Archive, Aurora.", + "homepageURL": "https://svn.pnl.gov/esp/wiki/ReleasePage", + "laborHours": 0.0, + "name": "Better Userspace HPSS File System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://svn.pnl.gov/esp/wiki/ReleasePage", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.pnl.gov/esp/wiki/ReleasePage", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bewley_Lattice_Diagram_[SWR-19-17].json b/agency-indexes/DoE/Bewley_Lattice_Diagram_[SWR-19-17].json new file mode 100644 index 00000000..ec7d7436 --- /dev/null +++ b/agency-indexes/DoE/Bewley_Lattice_Diagram_[SWR-19-17].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-07-14", + "metadataLastUpdated": "2023-08-14" + }, + "description": "This is a basic package for creating Bewley Lattice Diagrams in Python. https://nrel.github.io/bewley", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "Bewley Lattice Diagram [SWR-19-17]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bewley", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Beyond_The_Hype_paper_code.json b/agency-indexes/DoE/Beyond_The_Hype_paper_code.json new file mode 100644 index 00000000..70d75be1 --- /dev/null +++ b/agency-indexes/DoE/Beyond_The_Hype_paper_code.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "bridgesra@ornl.gov" + }, + "date": { + "created": "2022-08-22", + "metadataLastUpdated": "2022-10-06" + }, + "description": "This is example code on fake data from our Beyond The Hype paper. It provides a cost-benefit analysis for reasoning about malware detectors. For details on the approach please see our paper, and when referencing this code please cite our paper: Bridges, Robert A., Sean Oesch, Miki E. Verma, Michael D. Iannacone, Kelly MT Huffer, Brian Jewell, Jeff A. Nichols et al. \"Beyond the Hype: A Real-World Evaluation of the Impact and Cost of Machine Learning-Based Malware Detection.\" arXiv preprint arXiv:2012.09214 (2022). @misc{bridges2022beyond, doi = {10.48550/ARXIV.2012.09214}, url = {https://arxiv.org/abs/2012.09214}, author = {Bridges, Robert A. and Oesch, Sean and Verma, Miki E. and Iannacone, Michael D. and Huffer, Kelly M. T. and Jewell, Brian and Nichols, Jeff A. and Weber, Brian and Beaver, Justin M. and Smith, Jared M. and Scofield, Daniel and Miles, Craig and Plummer, Thomas and Daniell, Mark and Tall, Anne M.}, title = {Beyond the Hype: A Real-World Evaluation of the Impact and Cost of Machine Learning-Based Malware Detection}, publisher = {arXiv}, year = {2022}, } Repository contents: readme.md fake-data-table.csv This is a table of simulated data from two malware detectors, with randomly generated results suitable for running the cost model code as an example. config.py - provides global variables with input parameters needed for the cost model. model.py - provides the functions needed to run the cost model with examples on the fake data and three simulated detectors. Includes the complementary cost model--computes savings/costs of adding a network detector to a host detector. make_plots.py - shows example plots varying parameters. plots/ # contents populated by ./code/make_plots.py", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Beyond The Hype paper code", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bridgesra/beyond-the-hype-paper-code/releases/tag/tag", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "pi" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BiEntropy_for_Python_v._1.0.json b/agency-indexes/DoE/BiEntropy_for_Python_v._1.0.json new file mode 100644 index 00000000..0e500889 --- /dev/null +++ b/agency-indexes/DoE/BiEntropy_for_Python_v._1.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2024-07-19" + }, + "description": "This Python package provides high-performance implementations of the functions and examples presented in \"BiEntropy - The Approximate Entropy of a Finite Binary String\" by Grenville J. Croll, presented at ANPA 34 in 2013. https://arxiv.org/abs/1305.0954\n\nAccording to the paper, BiEntropy is \"a simple algorithm which computes the approximate entropy of a finite binary string of arbitrary length\" using \"a weighted average of the Shannon Entropies of the string and all but the last binary derivative of the string.\"", + "laborHours": 2021.6, + "languages": [ + "C", + "Python", + "Makefile" + ], + "name": "BiEntropy for Python v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/bientropy", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BiG-SLiCE_2_v1.0.0.json b/agency-indexes/DoE/BiG-SLiCE_2_v1.0.0.json new file mode 100644 index 00000000..21153238 --- /dev/null +++ b/agency-indexes/DoE/BiG-SLiCE_2_v1.0.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-14", + "metadataLastUpdated": "2024-08-14" + }, + "description": "BiG-SLiCE was originally an open source Python-based command line bioinformatics software that offers a highly scalable clustering analysis on biosynthetic gene clusters (BGC) data. It allows a simultaneous analysis of millions of BGCs, exceeding the capability of other existing tools (around one hundred thousands). As a tradeoff, the clustering accuracy is relatively lower and sometimes fall short in corner cases and specific BGC classes such as the RiPPs (Ribosomally-translated, Post-translationally modified Peptides).\n\nIn BiG-SLiCE V2 (developed in LBNL), the clustering algorithm has been significantly improved to deliver a much accurate result even for RiPPs and other previous corner case classes. Moreover, the speed of the overall pipeline has been improved by 50-100%. Finally, additional features were implemented to support downstream analyses of BiG-SLiCE results, such as customized tabular (TSV/CSV) and columnar (Parquet) outputs.", + "laborHours": 29837.6, + "languages": [], + "name": "BiG-SLiCE 2 v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/SAKautsar/bigslice_v2", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/BiGEST.json b/agency-indexes/DoE/BiGEST.json new file mode 100644 index 00000000..b431d7d0 --- /dev/null +++ b/agency-indexes/DoE/BiGEST.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Natural products have provided a rich reservoir of beneficial compounds in public health including antibiotics, therapeutics, and immunosuppressants. These natural products are synthesized by enzymes encoded by Biosynthetic Gene Clusters (BGCs), clusters of co-localized biosynthetic genes. Computational detection of BGCs has become a crucial step in natural product discovery. While this process has been facilitated in bacterial and fungal organisms thanks to the currently available tools (e.g., antiSMASH), a large spectrum of eukaryotic organisms have been neglected by these existing tools due to the scarcity and incompleteness of genome annotation resources. Here, we introduce Biosynthetic Gene cluster Extensive Search Tool (BiGEST) to provide an extensive annotation-free search for BGCs in diverse eukaryotic organisms. As a result, BiGEST uncovers eukaryotic BGCs that could be undetected by other BGC detection tools.", + "laborHours": 5639.2, + "languages": [], + "name": "BiGEST", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/BiGEST", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BiRD__BioReactorDesign__[SWR-24-35].json b/agency-indexes/DoE/BiRD__BioReactorDesign__[SWR-24-35].json new file mode 100644 index 00000000..c180e701 --- /dev/null +++ b/agency-indexes/DoE/BiRD__BioReactorDesign__[SWR-24-35].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-05", + "metadataLastUpdated": "2024-03-07" + }, + "description": "Numerical simulations can accelerate scale up and optimization of bioreactors. This project provides a toolbox to facilitate such numerical simulations in OpenFOAM. The tool box contains 1) mesh generations tools for several typical bio reactor types in OpenFOAM 2) Inverse modeling tools to calibrate models using available experimental data 3) post processing tools that accelerate and streamline the analysis of the numerical simulations.", + "laborHours": 0.0, + "languages": [ + "C++", + "Liquid" + ], + "name": "BiRD (BioReactorDesign) [SWR-24-35]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BioReactorDesign", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bid-DS-data-model__Demand_Side_Bidding_Data_Model__[SWR-22-80].json b/agency-indexes/DoE/Bid-DS-data-model__Demand_Side_Bidding_Data_Model__[SWR-22-80].json new file mode 100644 index 00000000..13690c72 --- /dev/null +++ b/agency-indexes/DoE/Bid-DS-data-model__Demand_Side_Bidding_Data_Model__[SWR-22-80].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-10-06" + }, + "description": "A model structure to support representation of power system dispatching for optimal power flow that includes bid-in demands for load. Used to support the ARPA-E GO-3 competition.", + "laborHours": 0.0, + "languages": [ + "Python", + "TeX" + ], + "name": "Bid-DS-data-model (Demand Side Bidding Data Model) [SWR-22-80]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Smart-DS/Bid-DS-data-model", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bifacial_Radiance_[SWR-18-03].json b/agency-indexes/DoE/Bifacial_Radiance_[SWR-18-03].json new file mode 100644 index 00000000..2319996f --- /dev/null +++ b/agency-indexes/DoE/Bifacial_Radiance_[SWR-18-03].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-11-08", + "metadataLastUpdated": "2023-08-14" + }, + "description": "bifacial_radiance contains a series of Python wrapper functions to make working with RADIANCE easier, particularly for the PV researcher interested in bifacial PV performance. Users can configure site details such as latitude / longitude, and ground albedo. A bifacial PV system is created with a number of PV modules in rows. The user can specify ground clearance height, row spacing, tilt and azimuth angle, etc. The scene is created, and annual or hourly irradiance profiles are applied to identify the rear irradiance fraction for a given condition.", + "laborHours": 13528.0, + "languages": [ + "Python" + ], + "name": "Bifacial_Radiance [SWR-18-03]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bifacial_radiance", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bifacial_Radiance_v0.4.2_[SWR-18-03].json b/agency-indexes/DoE/Bifacial_Radiance_v0.4.2_[SWR-18-03].json new file mode 100644 index 00000000..4ba013be --- /dev/null +++ b/agency-indexes/DoE/Bifacial_Radiance_v0.4.2_[SWR-18-03].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-14" + }, + "description": "The bifacial_radiance software contains a series of Python wrapper functions to make working with RADIANCE easier, particularly for the PV researcher interested in bifacial PV performance. For more information, check out our documentation, Tutorials in the form of Jupyter Notebooks, or refer to our Wiki and Issues page.\n\nInstallation\nhttps://youtu.be/4A9GocfHKyM This video shows how to install the bifacial_radiance software and all associated software needed. More info on the Wiki. Instructions are also shown below.\n\nFor detailed instructions of how to install bifacial_radiance, you can also refer to the installation guide.\n\nA GUI has been added in version 3.0. The GUI reads/writes all input parameters necessary to run a simulation, and runs the specified simulation by calling the correct functions with the specified parameters. So no need to use a journal or a script! But you still need to install following the procedure below.", + "laborHours": 13528.0, + "languages": [ + "C++", + "Python", + "Tex" + ], + "name": "Bifacial_Radiance v0.4.2 [SWR-18-03]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bifacial_radiance", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BigDNA.json b/agency-indexes/DoE/BigDNA.json new file mode 100644 index 00000000..55776839 --- /dev/null +++ b/agency-indexes/DoE/BigDNA.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2022-04-13" + }, + "description": "SAND2020-13696 M BigDNA takes a user input fast DNA sequence and outputs overlapping long PCR primers for Gibson Assembly. The software can design primers that remove gene products, insert new gene products, or completely circularize long DNAs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Perl", + "Python" + ], + "name": "BigDNA", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/bigdna", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BigData_Express.json b/agency-indexes/DoE/BigData_Express.json new file mode 100644 index 00000000..30a5a2e4 --- /dev/null +++ b/agency-indexes/DoE/BigData_Express.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-07-11", + "metadataLastUpdated": "2019-04-17" + }, + "description": "BigData Express is a high-performance data transfer service for big data. It has several salient features:\n\u2022\tBigData Express WebPortal is a distributed web application designed to support BigData Express services and functions. All BDE web portals use a common single-point sign-on service \u2013 Cilogon service \u2013 to obtain X.509 user certificates for secure access to BDE sites.\n\u2022\tBigData Express scheduler co-schedules Data Transfer Node(s), network, and storage resources for data transfer to achieve optimum performance.\n\u2022\tBigData Express AmoebaNet is a SDN-enabled network service that provide \u201cApplication-aware\u201d network. It allows application to program network at run-time for optimum performance. \n", + "homepageURL": "https://bigdataexpress.fnal.gov", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Java", + "JavaScript", + "Python" + ], + "name": "BigData Express", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bigdataexpress.fnal.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/BigFlowSim.json b/agency-indexes/DoE/BigFlowSim.json new file mode 100644 index 00000000..f9fe0097 --- /dev/null +++ b/agency-indexes/DoE/BigFlowSim.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-14", + "metadataLastUpdated": "2020-12-14" + }, + "description": "BigFlowSim is a workflow I/O simulator that captures key implementation choices for remote I/O, including intensity, reuse, locality, access pattern, and data movement. With BigFlowSim, it is possible to generate synthetic benchmarks, and then perform sensitivity analyses to quantify the effects of the various I/O parameters. In addition to generating synthetic workflows, BigFlowSim is also able to replay traces (of I/O access) captured from execution of actual distributed scientific workflows.", + "laborHours": 0.0, + "languages": [], + "name": "BigFlowSim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab-hub/tazer/tazer-bigflow-sim", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Billion-Core_Monte_Carlo.json b/agency-indexes/DoE/Billion-Core_Monte_Carlo.json new file mode 100644 index 00000000..573b76ff --- /dev/null +++ b/agency-indexes/DoE/Billion-Core_Monte_Carlo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-27" + }, + "description": "The copyrightable material is a set of software whose goal is to explore the use of Monte Carlo methods at extreme processor counts. This will include application software, libraries, middleware, various system software, and possibly compilers and translators", + "laborHours": 0.0, + "languages": [], + "name": "Billion-Core Monte Carlo", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/c2nova", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BinFPE.json b/agency-indexes/DoE/BinFPE.json new file mode 100644 index 00000000..4a2c7bdb --- /dev/null +++ b/agency-indexes/DoE/BinFPE.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-04-12", + "metadataLastUpdated": "2022-04-12" + }, + "description": "BinFPE is a tool that detects floating-point exceptions (NaN, infinity, and subnormal quantities) in NVIDIA GPU applications using binary instrumentation. It requires no re-compilation of the application and can analyze libraries. The tool extends NVBit (https://github.com/NVlabs/NVBit), which is provided by NVIDIA Labs to analyze binaries. When the tool detects a floating-point exception it reports to the user the location of the exception (file and line number).", + "laborHours": 0.0, + "languages": [], + "name": "BinFPE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/BinFPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Binary_Driller.json b/agency-indexes/DoE/Binary_Driller.json new file mode 100644 index 00000000..c095879a --- /dev/null +++ b/agency-indexes/DoE/Binary_Driller.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-09-30", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Binary Driller (BD) is a visualization tool which uses the data produced from the Troglodyte tool developed on the Deep Learning Malware project. Binary Driller performs function matching using the provided function embeddings (function representations), then displays the matches for each function in a layout that mimics the location of each function within the binary.", + "laborHours": 0.0, + "languages": [], + "name": "Binary Driller", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/BinDrill", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bindee.json b/agency-indexes/DoE/Bindee.json new file mode 100644 index 00000000..f42ff888 --- /dev/null +++ b/agency-indexes/DoE/Bindee.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-07", + "metadataLastUpdated": "2020-02-07" + }, + "description": "Bindee is a clang tool that outputs a simple pybind11 template given a C++ file for efficient generation of C++-Python bindings. \n\nBindee is intended to be a helper tool for minimizing initial user effort and\nsafeguarding against common runtime errors.\n\nBindee relies on two open-source software to produce bindings.\n\nClang's LibTooling enables bindee to traverse a C++ file's AST to pick out bindable variables and functions, or \"bindees.\"\n\nPyBind11 is templated, header-only library for generating C++-Python bindings for variables and functions.\n\nOperating purely in C++, bindee does not require learning any new API for accomplishing its task.\n\nAdditionally, picking the correct pybind11 API for a given bindable element is handled without interaction from the user. Any user input is denoted by '@TEXT@' string substitution.\n\nBindee is capable of generating modular bindings for public class methods, public class variables, enumerations, and free functions and variables. \n\nBindings for templates are also supported. \n\nFor those familiar with pybind11, bindee does not handle trampolines, C++ extensions through lambdas, or custom type casters.\n", + "laborHours": 1915.2, + "languages": [], + "name": "Bindee", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/bindee", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BioCro.json b/agency-indexes/DoE/BioCro.json new file mode 100644 index 00000000..95ecebea --- /dev/null +++ b/agency-indexes/DoE/BioCro.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "yunl68@illinois.edu" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2020-09-29" + }, + "description": "BioCro is a model that predicts plant growth over time given crop-specific parameters and environmental data as input.\n\nIt uses models of key physiological and biophysical processes underlying plant growth (Humphries and Long, 1995), and has previously been used for predicting biomass yield and leaf area index of switchgrass, miscanthus, sugarcane and willow (Miguez et al., 2009; Jaiswal et al. 2017).\n\nThe latest version has been redesigned to closely represent a dynamical system, which makes it easier to implement new crops and provides more accurate simulations. Parameters to model energy sorghum have also been added.", + "laborHours": 10913.6, + "languages": [], + "name": "BioCro", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ebimodeling/biocro/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ebimodeling/biocro", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BioLUC__Bioenergy_and_Land_Use_Change__[SWR_13-08].json b/agency-indexes/DoE/BioLUC__Bioenergy_and_Land_Use_Change__[SWR_13-08].json new file mode 100644 index 00000000..02055986 --- /dev/null +++ b/agency-indexes/DoE/BioLUC__Bioenergy_and_Land_Use_Change__[SWR_13-08].json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-08-17" + }, + "description": "The National Renewable Energy Laboratory (NREL) has developed a new system dynamics global LUC model intended to examine LUC attributed to biofuel production. The BioLUC model represents major global, stocks, flows and produces results under different food and biofuel demand assumptions, with flexible regional divisions. This model is not intended to generate precise numerical estimates, but instead to provide insights into the drivers and dynamic interactions of LUC, population, dietary choices, and biofuel policy.", + "laborHours": 15.2, + "languages": [], + "name": "BioLUC (Bioenergy and Land Use Change) [SWR 13-08]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://creativecommons.org/licenses/by-sa/3.0/legalcode", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bioluc", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BioPac.json b/agency-indexes/DoE/BioPac.json new file mode 100644 index 00000000..d88c0ef4 --- /dev/null +++ b/agency-indexes/DoE/BioPac.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-24", + "metadataLastUpdated": "2025-02-24" + }, + "description": "BioPAC is the Biological and other Particles in Aerosols Classifier. It is a software to assist in the accurate measurement\nand identification of primary biological aerosol particles, which play a pivotal role in mediating the reciprocal relationships\nbetween biological systems and atmospheric conditions.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 334.4, + "languages": [], + "name": "BioPac", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/BioPython_Scripts.json b/agency-indexes/DoE/BioPython_Scripts.json new file mode 100644 index 00000000..52767c51 --- /dev/null +++ b/agency-indexes/DoE/BioPython_Scripts.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "BioPython scripts for conversion of GBK files or DNA-based FASTA files to protein FASTA files", + "laborHours": 121.6, + "languages": [], + "name": "BioPython Scripts", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/BioPython_Scripts", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BioSTEAMDevelopmentGroup_Bioindustrial-Park_TAL.json b/agency-indexes/DoE/BioSTEAMDevelopmentGroup_Bioindustrial-Park_TAL.json new file mode 100644 index 00000000..b76c2f00 --- /dev/null +++ b/agency-indexes/DoE/BioSTEAMDevelopmentGroup_Bioindustrial-Park_TAL.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-08", + "metadataLastUpdated": "2024-11-08" + }, + "description": "Triacetic acid lactone (TAL) can be microbially produced and further chemically upgraded to several high-value chemicals. In this work, several acidic and basic ion-exchange resins and activated charcoal were evaluated for their ability to adsorb microbially produced TAL. Activated charcoal and a weak base resin, Dowex 66, showed similar TAL adsorption capacity of 0.18 \u00b1 0.002 g/g. At 15% w/v activated charcoal, about 98% of TAL present in fermentation broth could be adsorbed. Further, ethanol washing allowed recovery of 72% of adsorbed TAL. A biorefinery producing TAL from sucrose was designed, simulated, and evaluated (through technoeconomic analysis) under uncertainty, for an estimated TAL minimum product selling price (MPSP) of $4.27/kg [$3.71\u22124.94/kg; 5th-95th percentiles] for the current state of technology and $2.83/kg [$2.46\u20133.29/kg] following potential near-term improvements to fermentation. Thus, this work provides an adsorptive process to recover microbially produced TAL that can be chemically upgraded to several industrial products.", + "laborHours": 121159.2, + "languages": [], + "name": "BioSTEAMDevelopmentGroup/Bioindustrial-Park/TAL", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BioSTEAMDevelopmentGroup/Bioindustrial-Park", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BioSTEAMDevelopmentGroup_biosteam.json b/agency-indexes/DoE/BioSTEAMDevelopmentGroup_biosteam.json new file mode 100644 index 00000000..5ed362a6 --- /dev/null +++ b/agency-indexes/DoE/BioSTEAMDevelopmentGroup_biosteam.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "BioSTEAM is a fast and flexible package for the design, simulation, and techno-economic analysis of biorefineries under uncertainty. BioSTEAM\u2019s framework is built to streamline and automate early-stage technology evaluations and to enable rigorous sensitivity and uncertainty analyses. Complete biorefinery configurations are available at the Bioindustrial-Park GitHub repository, BioSTEAM\u2019s premier repository for biorefinery models and results. The long-term growth and maintenance of BioSTEAM is supported through both community-led development and the research institutions invested in BioSTEAM. Through the open-source and community-lead platform, BioSTEAM aims to foster communication and transparency within the biorefinery research community for an integrated effort to expedite the evaluation of candidate biofuels and bioproducts.\n\nAdditionally, an agile life cycle assessment (LCA) platform has been designed to interface with BioSTEAM, BioSTEAM-LCA. This open-source, installable package allows users to perform streamlined LCAs of biorefineries. The focus of BioSTEAM-LCA is to streamline and automate early-stage environmental impact analyses of processes and technologies, and to enable rigorous sensitivity and uncertainty analyses linking process design, performance, economics, and environmental impacts.", + "laborHours": 23924.8, + "languages": [], + "name": "BioSTEAMDevelopmentGroup/biosteam", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/BioSTEAMDevelopmentGroup/biosteam?tab=License-1-ov-file#readme", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BioSTEAMDevelopmentGroup/biosteam", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BioStudio.json b/agency-indexes/DoE/BioStudio.json new file mode 100644 index 00000000..8679655b --- /dev/null +++ b/agency-indexes/DoE/BioStudio.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-24", + "metadataLastUpdated": "2021-06-10" + }, + "description": "BioStudio is a library of algorithms for the design of large synthetic DNA, with an emphasis on the chromosome scale.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "perl 5.10" + ], + "name": "BioStudio", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Biocellion_3.1.json b/agency-indexes/DoE/Biocellion_3.1.json new file mode 100644 index 00000000..e5c4203c --- /dev/null +++ b/agency-indexes/DoE/Biocellion_3.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Biocellion is a software platform to accelerate modeling and simulation of multicellular biological systems. Biocellion integrates simulations of individual cell behaviors, short-distance intercellular biomechanics, and extracellular molecular transport to understand and predict multicellular biological system behaviors in their entirety. This software release (Biocellion 3.1) updates previous Biocellion 2.0. The main updates include support for ellipsoid based cell biomechanics modeling and layer based initialization of multi-layered multicellular biological systems in addition to performance improvements and various API updates. Through Biocellion SPC (https://biocellion.com), these updates have been used to investigate skin biomechanics under different conditions (e.g. humidity) for Procter and Gamble. This is the only discrete agent based solution to allow seamless integration of individual cell level knowledge and measurements to a whole skin model to the best of our knowledge.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "Biocellion 3.1", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Biocellion_Version_2.0.json b/agency-indexes/DoE/Biocellion_Version_2.0.json new file mode 100644 index 00000000..313a247f --- /dev/null +++ b/agency-indexes/DoE/Biocellion_Version_2.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "This work extends Biocellion 1.0 to solve advection-reaction-diffusion and incompressible Navier-Stokes partial differential equations to model water/blood flow. Biocellion is a software framework to simulate a large number of cells using high-performance parallel computers. The version 1.0 allows software users to describe biological system behaviors as a set of rules describing how individual cells behave and how cells locally interact with neighboring cells or the surrounding micro-environment. However, the version 1.0 does not support users to incorporate water/blood flow into the model, which is important to properly capture long distance communications between distant cells. This extension (version 2.0) integrates two partial differential equation solvers to the Biocellion framework to solve this limitation. Navier-Stokes equation solvers (for incompressible flow) are added to compute flow rate, and advection-reaction-diffusion equation solvers are added to update molecular concentrations considering both advection (due to flow) and local diffusion.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Biocellion Version 2.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/BiochemistryAPI.json b/agency-indexes/DoE/BiochemistryAPI.json new file mode 100644 index 00000000..e2c76008 --- /dev/null +++ b/agency-indexes/DoE/BiochemistryAPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-08", + "metadataLastUpdated": "2020-09-08" + }, + "description": "This module serves Biochemistry data for KBase.", + "laborHours": 429658.4, + "languages": [], + "name": "BiochemistryAPI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/BiochemistryAPI", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bioenergy_Research_Centers_Data_Sharing_Portal.json b/agency-indexes/DoE/Bioenergy_Research_Centers_Data_Sharing_Portal.json new file mode 100644 index 00000000..92efbd17 --- /dev/null +++ b/agency-indexes/DoE/Bioenergy_Research_Centers_Data_Sharing_Portal.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "martins@ornl.gov" + }, + "date": { + "created": "2025-02-13", + "metadataLastUpdated": "2025-02-27" + }, + "description": "The bioenergy.org website is the end product of the Data Sharing Shared Research objective for the Bioenergy Centers. The objective is to Enhance BRC data legacy through the development and use of shared software tools to make previously published datasets more findable and accessible through the Inter-BRC Data Products Portal, and to explore the use of generative AI to assist in the exploration of published datasets. The software repository is released per the license information below.", + "laborHours": 1839.2, + "languages": [ + "JavaScript" + ], + "name": "Bioenergy Research Centers Data Sharing Portal", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/bioenergy-research-centers/bioenergy.org?tab=License-1-ov-file", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bioenergy-research-centers/bioenergy.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Biogeochemical_Transport_and_Reaction_Model__BeTR__v1.json b/agency-indexes/DoE/Biogeochemical_Transport_and_Reaction_Model__BeTR__v1.json new file mode 100644 index 00000000..608c7b3f --- /dev/null +++ b/agency-indexes/DoE/Biogeochemical_Transport_and_Reaction_Model__BeTR__v1.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "The Biogeochemical Transport and Reaction Model (BeTR) is a F90 code that enables reactive transport modeling in land modules of earth system models (e.g. CESM, ACME). The code adopts the Objective-Oriented-Design, and allows users to plug in their own biogeochemical (BGC) formulations/codes, and compare them to other existing BGC codes in those ESMs. The code takes information of soil physics variables, such as variables, such as temperature, moisture, soil density profile; water flow, etc., from a land model to track the movement of different chemicals in presence of biogeochemical reactions.", + "laborHours": 0.0, + "languages": [ + "N/A" + ], + "name": "Biogeochemical Transport and Reaction Model (BeTR) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/BeTR-biogeochemistry-modeling/sbetr/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BeTR-biogeochemistry-modeling/sbetr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Biological_Parts_Search_Portal__BioParts__v1.0.0.json b/agency-indexes/DoE/Biological_Parts_Search_Portal__BioParts__v1.0.0.json new file mode 100644 index 00000000..9de803fe --- /dev/null +++ b/agency-indexes/DoE/Biological_Parts_Search_Portal__BioParts__v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-23", + "metadataLastUpdated": "2024-07-23" + }, + "description": "BioParts is a web based search portal for biological parts available in the public domain. It combines the ease and convenience of modern web search engines with the capabilities of bioinformatics search tools such as BLAST. This portal, available at bioparts.org, allows anyone to search for publicly accessible biological part information (e.g., NCBI, iGEM, SynBioHub, Addgene), including parts publicly accessible through ICE Registries. Additionally, the portal offers a REST API that enables third-party applications and tools to access the portal's functionality programmatically. While there are several standalone biological part repositories, there doesn't exist an application that indexes these publicly available parts and enables features such as keyword and BLAST searches along with automatic sequence annotation.", + "laborHours": 27694.4, + "languages": [], + "name": "Biological Parts Search Portal (BioParts) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/BioParts", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Biological_Performance_Assessment.json b/agency-indexes/DoE/Biological_Performance_Assessment.json new file mode 100644 index 00000000..3f82578b --- /dev/null +++ b/agency-indexes/DoE/Biological_Performance_Assessment.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The BioPA provides turbine designers with a set of tools that can be used to assess biological risks of turbines during the design phase, before expensive construction begins. The toolset can also be used to assess existing installations under a variety of operating conditions, supplementing data obtained through expensive field testing. The BioPA uses computational fluid dynamics (CFD) simulations of a turbine design to quantify the exposure of passing fish to a set of known injury mechanisms. By appropriate sampling of the fluid domain, the BioPA assigns exposure probabilities to each mechanism. The exposure probabilities are combined with dose-response data from laboratory stress studies of fish to produce a set of biological BioPA Scores. These metrics provide an objective measure that can be used to compare competing turbines or to refine a new design. The BioPA process can be performed during the turbine design phase and is considerably less expensive than prototype-scale field testing.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Tecplot Macro, Python, Visual Basic" + ], + "name": "Biological Performance Assessment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Biological_Performance_Assessment__BioPA__Toolset_version_3.json b/agency-indexes/DoE/Biological_Performance_Assessment__BioPA__Toolset_version_3.json new file mode 100644 index 00000000..600faf52 --- /dev/null +++ b/agency-indexes/DoE/Biological_Performance_Assessment__BioPA__Toolset_version_3.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-01-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Biological Performance Assessment (BioPA) version 3, uses computational fluid dynamics (CFD) and particle trajectory simulations of the hydro-turbine to quantify the exposure of passing fish to a set of known injury mechanisms. By appropriate sampling of the fluid domain, the BioPA assigns exposure probabilities to each mechanism. The exposure probabilities are combined with dose- response data from laboratory stress studies of fish to produce a set of biological BioPA Scores. These metrics provide an objective measure that can be used to compare competing turbines or to refine a new design.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Biological Performance Assessment (BioPA) Toolset version 3", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Biosafety_Risk_Assessment_Model.json b/agency-indexes/DoE/Biosafety_Risk_Assessment_Model.json new file mode 100644 index 00000000..acc3c431 --- /dev/null +++ b/agency-indexes/DoE/Biosafety_Risk_Assessment_Model.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Software tool based on a structured methodology for conducting laboratory biosafety risk assessments by biosafety experts. Software is based upon an MCDA scheme and uses peer reviewed criteria and weights. The software was developed upon Microsoft's .net framework. The methodology defines likelihood and consequence of a laboratory exposure for thirteen unique scenarios and provides numerical relative risks for each of the relevant thirteen. The software produces 2-d graphs reflecting the relative risk and a sensitivity analysis which highlights the overall importance of each factor. The software works as a set of questions with absolute scales and uses a weighted additive model to calculate the likelihood and consequence.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Windows.NET" + ], + "name": "Biosafety Risk Assessment Model", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Biosecurity_Risk_Assessment_Methodology__BioRAM__v._2.0.json b/agency-indexes/DoE/Biosecurity_Risk_Assessment_Methodology__BioRAM__v._2.0.json new file mode 100644 index 00000000..ee42b165 --- /dev/null +++ b/agency-indexes/DoE/Biosecurity_Risk_Assessment_Methodology__BioRAM__v._2.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "Sandia National Laboratories International Biological Threat Reduction Dept (SNL/IBTR) has an ongoing mission to enhance biosecurity assessment methodologies, tools, and guise. These will aid labs seeking to implement biosecurity as advocated in the recently released WHO's Biorisk Management: Lab Biosecurity Guidance. BioRAM 2.0 is the software tool developed initially using the SNL LDRD process and designed to complement the \"Laboratory Biosecurity Risk Handbook\" written by Ren Salerno and Jennifer Gaudioso defining biosecurity risk assessment methodologies.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "Biosecurity Risk Assessment Methodology (BioRAM) v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Biositing_Webtool,_v1.json b/agency-indexes/DoE/Biositing_Webtool,_v1.json new file mode 100644 index 00000000..84fdc20f --- /dev/null +++ b/agency-indexes/DoE/Biositing_Webtool,_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-17", + "metadataLastUpdated": "2019-12-02" + }, + "description": "The webtool displays the following types of data:\n\nWastewater treatment plants (WWTP) with anaerobic digestion\nFacilities with anaerobic digestion onsite other than WWTP\nCombustion plants.\nManure locations.\nManure (non points)\nMunicipal solid waste locations\nCrop locations\nProcessor residue (non points)\nDistrict energy systems\nMixed use developments (non points)\nProcess heating and cooling locations\nBasic Usage\nUsers can interact with the map in the following ways:\n\nSelect the year of the analysis from a drop-down menu.\nSet the background layer as biomass availability or thermal consumption density from a drop-down menu.\nSelect whether the facility of interest is an Anaerobic Digestion or a Therochemical facility from a drop-down menu. This filters the biomass data by moisture and only shows the relevant portions based on the facility selection.\nSelect from a drop-down menu whether the biomass amounts will be shown as gross amounts or technical amounts.\nSet the radius for the search buffer in which the analysis will be performed.\nClick on any point data on the map to get more information.\nClick on the map, to given the signal of the query point location, from where the algorithmic process is going to initiate. This will show the available biomass locations and amounts that fall within the predefined buffer zone.\nDownload the data in a csv format for the entire county or the selected biomass that is inside the predefined buffer.\nReport whether there are errors in the data to us and we will work to the best of our abilities to confirm and fix any issues.\nThe outputs of the algorithmic process are going to appear on the screen after the computation is done. The outputs consist of the locations of all available biomass that are within the buffer zone from the clicked location. By clicking on any point the user can get more information on the nature and amounts of the biomass.", + "homepageURL": "https://biositing.jbei.org", + "laborHours": 11324.0, + "languages": [], + "name": "Biositing Webtool, v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://lead.jbei.org", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://biositing.jbei.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Blackbear.json b/agency-indexes/DoE/Blackbear.json new file mode 100644 index 00000000..6c889043 --- /dev/null +++ b/agency-indexes/DoE/Blackbear.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2023-03-15" + }, + "description": "BlackBear is a MOOSE-based code for simulating degradation processes in concrete and other structural materials.", + "laborHours": 6110.4, + "languages": [], + "name": "Blackbear", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/blackbear", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Blanket_Disclosure_Viral_Dynamics_modelling.json b/agency-indexes/DoE/Blanket_Disclosure_Viral_Dynamics_modelling.json new file mode 100644 index 00000000..0152f504 --- /dev/null +++ b/agency-indexes/DoE/Blanket_Disclosure_Viral_Dynamics_modelling.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2021-09-13" + }, + "description": "The codes are used to analyze biological data, plot figures, and generate results for papers that will be published as a result of the execution of our NIH grant.", + "laborHours": 0.0, + "languages": [], + "name": "Blanket Disclosure Viral Dynamics modelling", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/gamma-dde", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Blanket_Phylogenetic_and_genetic_analyses_of_SARS-CoV-2_epidemiology.json b/agency-indexes/DoE/Blanket_Phylogenetic_and_genetic_analyses_of_SARS-CoV-2_epidemiology.json new file mode 100644 index 00000000..e87ef68f --- /dev/null +++ b/agency-indexes/DoE/Blanket_Phylogenetic_and_genetic_analyses_of_SARS-CoV-2_epidemiology.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "I am submitting an umbrella/blanket disclosure because I am working on several inter-related projects in a fast-moving research area. The general theme is statistical analysis and visualization of SARS-CoV-2 viral genetic sequence data in order to learn about epidemiology. Examples of research questions are: How do viral genetic relationships relate to contact tracing links? How does viral genetics reflect signatures of transmission from one person to another? Do some genetic variants have a consistent transmission advantage?", + "laborHours": 0.0, + "languages": [], + "name": "Blanket Phylogenetic and genetic analyses of SARS-CoV-2 epidemiology", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eeg-lanl/sarscov2-selection", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Blanket_software_for_theoretical_and_computational_biology_applications.json b/agency-indexes/DoE/Blanket_software_for_theoretical_and_computational_biology_applications.json new file mode 100644 index 00000000..cba96dd4 --- /dev/null +++ b/agency-indexes/DoE/Blanket_software_for_theoretical_and_computational_biology_applications.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "Code used in the generation, application, and execution of model and methods related to work in theoretical and computational biology specifically surrounding the evolution, ecology, and epidemiology of infectious disease. This code included the implementation of models used for data analysis, code to generate figures, code to process and manipulate data for said purposes, and code to execute published analyses. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Blanket software for theoretical and computational biology applications", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Blazing_Signature_Filter.json b/agency-indexes/DoE/Blazing_Signature_Filter.json new file mode 100644 index 00000000..bf4482f7 --- /dev/null +++ b/agency-indexes/DoE/Blazing_Signature_Filter.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "BSF is a highly efficient pairwise similarity algorithm enabling extensive data mining.", + "laborHours": 91.2, + "name": "Blazing Signature Filter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/bsf-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BlendPATH__Blending_Pipeline_Analysis_Tool_for_Hydrogen__[SWR-24-10].json b/agency-indexes/DoE/BlendPATH__Blending_Pipeline_Analysis_Tool_for_Hydrogen__[SWR-24-10].json new file mode 100644 index 00000000..b1c924d0 --- /dev/null +++ b/agency-indexes/DoE/BlendPATH__Blending_Pipeline_Analysis_Tool_for_Hydrogen__[SWR-24-10].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-08", + "metadataLastUpdated": "2024-04-16" + }, + "description": "BlendPATH provides case-by-case techno-economic analysis for potential projects where hydrogen is blended into a natural gas transmission pipeline. BlendPATH estimates 1) the transmission pipeline modifications and operating conditions necessary to blend hydrogen to a user specified volume faction of hydrogen in pipeline gas and 2) the incremental capital and operating expenses to prepare said transmission pipeline for hydrogen blending. BlendPATH is developed in Python and requires SAInt, a underlying commercial natural gas pipeline network modeling software, to run. Pipeline modification and operation condition estimation is guided by ASME B31.12. The intent of this software is to target application for projects in the initial project assessment stage and provide the user with the capability of assess promising opportunities before the use proceeds with further detailed pipeline evaluation based on a probable economic outcome.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "BlendPATH (Blending Pipeline Analysis Tool for Hydrogen) [SWR-24-10]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BlendPATH", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Blockchain-based_fault_tolerant_grid_operations_system.json b/agency-indexes/DoE/Blockchain-based_fault_tolerant_grid_operations_system.json new file mode 100644 index 00000000..be3158de --- /dev/null +++ b/agency-indexes/DoE/Blockchain-based_fault_tolerant_grid_operations_system.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-01", + "metadataLastUpdated": "2024-10-02" + }, + "description": "To maintain/improve the\ndistribution system fault-tolerance for a grid with high penetration of distributed energy resources requires improvement,\nBlockchain can add value to improve fault-tolerant grid operations. That can be achieved using blockchain's core features\nof distributed consensus-based decision-making process and immutability.", + "laborHours": 20672.0, + "languages": [], + "name": "Blockchain-based fault tolerant grid operations system", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/dltDFLISR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Blockchain_Applicability_and_Cybersecurity_Frameworks__BAF_.json b/agency-indexes/DoE/Blockchain_Applicability_and_Cybersecurity_Frameworks__BAF_.json new file mode 100644 index 00000000..0b627e5c --- /dev/null +++ b/agency-indexes/DoE/Blockchain_Applicability_and_Cybersecurity_Frameworks__BAF_.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Blockchain Applicability and Cybersecurity Frameworks is the implementation of an earlier invention disclosure and Provisional Patent Application: S-146,805, Battelle IPID 31608-E. \u2014BAF walks a user (or an interested party) through ~100 controls to determine various factors, including:\n1. Does the application need a blockchain?\n2. If the application needs a blockchain, does it need a private blockchain or permissionless/public blockchain?\n3. What kind of consensus is most suitable for the application? The current version of BAF evaluates between four consensus mechanisms: proof-of-work, proof-of-stake, proof-of-burn, and proof-of-authority.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Blockchain Applicability and Cybersecurity Frameworks (BAF)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Blockchain_Based_Remote_Data_Integrity_Checking_Tool_v1.0.json b/agency-indexes/DoE/Blockchain_Based_Remote_Data_Integrity_Checking_Tool_v1.0.json new file mode 100644 index 00000000..5b934d2e --- /dev/null +++ b/agency-indexes/DoE/Blockchain_Based_Remote_Data_Integrity_Checking_Tool_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-09-30", + "metadataLastUpdated": "2019-10-01" + }, + "description": "Computer System Security: The software is used to perform remote data integrity checking without relying on a single third party. In order to remove the trusted third party our tool uses distributed ledger (Blockchain) technology. The ledger is used to store evidences (in the form of hash values). These values are used as an input in the integrity checking process.", + "laborHours": 1003.2, + "languages": [], + "name": "Blockchain Based Remote Data Integrity Checking Tool v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/hpc_data_integrity_code", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Blockchain_smart_contracts_for_energy_markets.json b/agency-indexes/DoE/Blockchain_smart_contracts_for_energy_markets.json new file mode 100644 index 00000000..19875bf5 --- /dev/null +++ b/agency-indexes/DoE/Blockchain_smart_contracts_for_energy_markets.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A successful architecture that depicts the relationship between the energy market engineering requirements and blockchain requirements\n(shown as enablers). Software includes sequential and relational architectures supported by the UML flow diagrams. For a successful blockchain agnostic implementation of energy markets, the proposed architecture/blueprint supported by prototype implementation is very efficient. The proposed invention also depicts various means of the use of\nblockchain technology for energy market systems.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Blockchain smart contracts for energy markets", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bloom_Filter_framework_for_Web_Archives.json b/agency-indexes/DoE/Bloom_Filter_framework_for_Web_Archives.json new file mode 100644 index 00000000..80fc0d37 --- /dev/null +++ b/agency-indexes/DoE/Bloom_Filter_framework_for_Web_Archives.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-06-15", + "metadataLastUpdated": "2022-06-15" + }, + "description": "The software provides a framework to build a fast look up layer that reflects the holdings of an archive or database and operates between search/discovery system and disk storage. The software utilizes Bloom filter (BF) data structure. The discovery service powered by the Bloom filter layer comes with a very high level of accuracy yet space-saving, since BF compresses data to fit into RAM.", + "laborHours": 0.0, + "languages": [], + "name": "Bloom Filter framework for Web Archives", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/bloomfiltersforwebarchives", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bloom_filter_de-identifier.json b/agency-indexes/DoE/Bloom_filter_de-identifier.json new file mode 100644 index 00000000..7979e85b --- /dev/null +++ b/agency-indexes/DoE/Bloom_filter_de-identifier.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-09-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A bloom filter is a binary data structure that is designed to be memory efficient and able to determine whether an element is present in a set. The bloom filter is a\nprobabilistic data structure. It can tell you whether an element, or set of elements, is likely to exist within a set. It can also tell you whether an element, or set of\nelements, does not exist within a set. So false positives are probable, but false negatives are not.\nOur novel approach utilizes the bloom filter to determine how many bigrams (two letter sequence) each value has in common. The resulting metric approximates the\nrelative similarity of two text values.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Bloom filter de-identifier", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BlueGene_L_Specific_Modification_to_MRNet:_Multicast_Reduction_Network.json b/agency-indexes/DoE/BlueGene_L_Specific_Modification_to_MRNet:_Multicast_Reduction_Network.json new file mode 100644 index 00000000..c110c1fd --- /dev/null +++ b/agency-indexes/DoE/BlueGene_L_Specific_Modification_to_MRNet:_Multicast_Reduction_Network.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MRNet is a software tree-based overlay network developed at the University of Wisconsin, Madison that provides a scalable communication mechanism for parallel tools. MRNet uses a tree topology of networked processes between a user tool and distributed tool daemons. This tree topology allows scalable multicast communication from the tool to the daemons. The internal nodes of the tree can be used to distribute computation and analysis on data sent from the tool daemons to the tool. This release covers modifications that we have made to the Wisconsin implementation to port this software to the BlueGene/L architecture. It also covers some additional files that were created for this port.", + "laborHours": 68460.8, + "name": "BlueGene/L Specific Modification to MRNet: Multicast/Reduction Network", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dyninst/mrnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BlueHat.json b/agency-indexes/DoE/BlueHat.json new file mode 100644 index 00000000..1117bb8b --- /dev/null +++ b/agency-indexes/DoE/BlueHat.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "\"Bluehat\" is a collection of python routines to facilitate the analysis of spectral (multispectral and hyperspectral) remote sensing\nimagery, with an emphasis on various kind of target detection. The package provides collections of utilities that developers can use in producing algorithms for specific target detection scenarios.\n\nAlthough \"bluehat\" is mostly expected to be used for remote sensing imagery (which often comes from satellite sensors), and although early versions of \"bluehat\" were used to design algorithms that were then rewritten for onboard processing; \"bluehat\" itself is not not specially designed for space and/or satellite application.", + "laborHours": 0.0, + "languages": [], + "name": "BlueHat", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jt-lanl/bluehat", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Blue_Gene_Q_Network_Performance_Counters_Monitoring_Library.json b/agency-indexes/DoE/Blue_Gene_Q_Network_Performance_Counters_Monitoring_Library.json new file mode 100644 index 00000000..a767e726 --- /dev/null +++ b/agency-indexes/DoE/Blue_Gene_Q_Network_Performance_Counters_Monitoring_Library.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "BGQNCL is a library to monitor and record network performance counters on the 5D torus interconnection network of IBM's Blue Gene/Q platform.", + "laborHours": 152.0, + "name": "Blue Gene/Q Network Performance Counters Monitoring Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/bgqncl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bond_order_potential_module_for_LAMMPS.json b/agency-indexes/DoE/Bond_order_potential_module_for_LAMMPS.json new file mode 100644 index 00000000..6636c463 --- /dev/null +++ b/agency-indexes/DoE/Bond_order_potential_module_for_LAMMPS.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "pair_bop is a module for performing energy calculations using the Bond Order Potential (BOP) for use in the parallel molecular dynamics code LAMMPS. The bop pair style computes BOP based upon quantum mechanical incorporating both sigma and pi bondings. By analytically deriving the BOP pair bop from quantum mechanical theory its transferability to different phases can approach that of quantum mechanical methods. This potential is extremely effective at modeling 111-V and II-VI compounds such as GaAs and CdTe. This potential is similar to the original BOP developed by Pettifor and later updated by Murdock et al. and Ward et al.", + "laborHours": 1281025.6, + "name": "Bond order potential module for LAMMPS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lammps/lammps", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Boost_Converter_Loss_Analysis_v0.1.json b/agency-indexes/DoE/Boost_Converter_Loss_Analysis_v0.1.json new file mode 100644 index 00000000..fd0374b0 --- /dev/null +++ b/agency-indexes/DoE/Boost_Converter_Loss_Analysis_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "This software helps the user mathematically determine the losses in a boost converter they are designing. They can enter the component parasitic values from their component datasheets, and the software will calculate exactly where the losses are coming from. This can help the designer target and reduce specific sources of loss. It also helps system engineers compare the losses between AC and DC versions of the boost converter. Finally, it establishes a set of mathematical equations to help academics study loss theoretically.", + "laborHours": 562.4, + "languages": [], + "name": "Boost Converter Loss Analysis v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dgerb/Boost-Converter-Loss-Analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BoxEM:_Automated_Grid_Edge_Detection_for_Electron_Micrographs.json b/agency-indexes/DoE/BoxEM:_Automated_Grid_Edge_Detection_for_Electron_Micrographs.json new file mode 100644 index 00000000..5b9cd248 --- /dev/null +++ b/agency-indexes/DoE/BoxEM:_Automated_Grid_Edge_Detection_for_Electron_Micrographs.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-10", + "metadataLastUpdated": "2025-02-24" + }, + "description": "This software was developed to aid in the automation of electron microscopy. Identification of sample landmarks in\nimaging data is critical for automated imaging systems.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 60.8, + "languages": [], + "name": "BoxEM: Automated Grid Edge Detection for Electron Micrographs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Boxfish.json b/agency-indexes/DoE/Boxfish.json new file mode 100644 index 00000000..cb33030c --- /dev/null +++ b/agency-indexes/DoE/Boxfish.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Boxfish is a tool for visualizing performance data. It allows users to quickly project performance data gathered from parallel applications onto intuitive domains. It also includes a projection mechanism that automatically finds relations in performance data so the the data can easily be mapped onto non-obviously related domains. For this release, Boxfish allows performance data to be projected onto the nodes and links of a computer network, as well as onto grids or patch-structured applications. This allows a user of the visualization tool to quickly see correlations between performance data and network structure, application data, or communication patterns.", + "laborHours": 225005.6, + "name": "Boxfish", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/boxfish/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/boxfish", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Brain-Emulating_Cognition_and_Control_Architecture__BECCA__V1.0_beta.json b/agency-indexes/DoE/Brain-Emulating_Cognition_and_Control_Architecture__BECCA__V1.0_beta.json new file mode 100644 index 00000000..ce79adc4 --- /dev/null +++ b/agency-indexes/DoE/Brain-Emulating_Cognition_and_Control_Architecture__BECCA__V1.0_beta.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "BECCA is a learning and control method based on the function of the human brain. The goal behind its creation is to learn to control robots in unfamiliar environments in a way that is very robust, similar to the way that an infant learns to interact with her environment by trial and error. As of this release, this software contains two simulations of BECCA controlling robots: one is a one degree-of-freedom spinner robot and the other is a 7 degree-of-freedom serial link arm with a terminal gripper. In addition, the software contains code that identifies synonyms in a untagged corpus of ASCII words. This last is a demonstration of BECCA's ability to generate abstract concepts from concrete experience. The BECCA simulation is coded so as to make it extensible to new applications. It is modular, object-oriented code in which the portions of the code that are specific to one simulation are easily separable from those portions that are the constant between implementations. BECCA makes very few assumptions about the robot and environment it is learning, and so is applicable to a wide range of learning and control problems.", + "laborHours": 927.2, + "languages": [ + "Python" + ], + "name": "Brain-Emulating Cognition and Control Architecture (BECCA) V1.0 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/becca", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Brain-Emulating_Cognition_and_Control_Architecture__BECCA__v._0.2_beta.json b/agency-indexes/DoE/Brain-Emulating_Cognition_and_Control_Architecture__BECCA__v._0.2_beta.json new file mode 100644 index 00000000..c69faf26 --- /dev/null +++ b/agency-indexes/DoE/Brain-Emulating_Cognition_and_Control_Architecture__BECCA__v._0.2_beta.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "BECCA is a learning and control method based on the function of the human brain. The goal behind its creation is to learn to control robots in unfamiliar environments in a way that is very robust, similar to the way that an infant learns to interact with her environment by trial and error. As of this release, this software contains an application for controlling robot hardware through a socket. The code was created so as to make it extensible to new applications. It is modular, object-oriented code in which the portions of the code that are specific to one robot are easily separable from those portions that are the constant between implementations. BECCA makes very few assumptions about the robot and environment it is learning, and so is applicable to a wide range of learning and control problems.", + "laborHours": 927.2, + "languages": [ + "Python" + ], + "name": "Brain-Emulating Cognition and Control Architecture (BECCA) v. 0.2 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/becca", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Branchless_Reproducible_Floating_Point_Summation_With_Integers,_Version_1.x.x.json b/agency-indexes/DoE/Branchless_Reproducible_Floating_Point_Summation_With_Integers,_Version_1.x.x.json new file mode 100644 index 00000000..6d069295 --- /dev/null +++ b/agency-indexes/DoE/Branchless_Reproducible_Floating_Point_Summation_With_Integers,_Version_1.x.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Returns bitwise identical sums regardless of the order of the summands. Uses no branches and mostly integer operations. Designed to be vectorizeable.", + "laborHours": 60.8, + "name": "Branchless Reproducible Floating Point Summation With Integers, Version 1.x.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/peterahrens/BranchlessReproducibleFloatingPointWithIntegers/blob/master/brfpwi.c", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/peterahrens/BranchlessReproducibleFloatingPointWithIntegers", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Branson:_A_Mini-App_for_Studying_Parallel_IMC,_Version_1.0.json b/agency-indexes/DoE/Branson:_A_Mini-App_for_Studying_Parallel_IMC,_Version_1.0.json new file mode 100644 index 00000000..0f9f09e4 --- /dev/null +++ b/agency-indexes/DoE/Branson:_A_Mini-App_for_Studying_Parallel_IMC,_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code solves the gray thermal radiative transfer (TRT) equations in parallel using simple opacities and Cartesian meshes. Although Branson solves the TRT equations it is not designed to model radiation transport: Branson contains simple physics and does not have a multigroup treatment, nor can it use physical material data. The opacities have are simple polynomials in temperature there is a limited ability to specify complex geometries and sources. Branson was designed only to capture the computational demands of production IMC codes, especially in large parallel runs. It was also intended to foster collaboration with vendors, universities and other DOE partners. Branson is similar in character to the neutron transport proxy-app Quicksilver from LLNL, which was recently open-sourced.", + "laborHours": 33987.2, + "name": "Branson: A Mini-App for Studying Parallel IMC, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/branson/blob/develop/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/branson", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bridge_Kernel.json b/agency-indexes/DoE/Bridge_Kernel.json new file mode 100644 index 00000000..3a28f905 --- /dev/null +++ b/agency-indexes/DoE/Bridge_Kernel.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "The Bridge Kernel is a Jupyter Kernel for connecting to compute backends that implement the bridge kernel (bk) protocol. The bk protocol is a client-server protocol that emphasizes minimal dependencies, easy embedding with MPI, secure connections + authentication, and non-local backends with automatic\ntunneling.", + "laborHours": 562.4, + "languages": [], + "name": "Bridge Kernel", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/bridge-kernel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Broker_for_Assimilation,_Synthesis_and_Integration_of_eNvironmental_Diverse,_Distributed_Datasets__basin3d_.json b/agency-indexes/DoE/Broker_for_Assimilation,_Synthesis_and_Integration_of_eNvironmental_Diverse,_Distributed_Datasets__basin3d_.json new file mode 100644 index 00000000..b72a4975 --- /dev/null +++ b/agency-indexes/DoE/Broker_for_Assimilation,_Synthesis_and_Integration_of_eNvironmental_Diverse,_Distributed_Datasets__basin3d_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "vchendrix@lbl.gov" + }, + "date": { + "created": "2021-04-29", + "metadataLastUpdated": "2021-06-17" + }, + "description": "BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets) uses a data brokering approach to synthesize diverse earth science data from a variety of remote sources in real-time without the need for additional storage. BASIN-3D is an extendable Python application using a generalized data synthesis model that makes the synthesized data available via Application Programming Interface (API). We have currently implemented our data synthesis model to represent sensor-based time series earth science observations across a hierarchy of spatial locations. Supporting our data synthesis model is a plugin framework that allows developers to map data sources of interest to the BASIN-3D synthesis model.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets (basin3d)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/BASIN-3D/basin3d", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Broker_for_Assimilation,_Synthesis_and_Integration_of_eNvironmental_Diverse,_Distributed_Datasets__django-basin3d_.json b/agency-indexes/DoE/Broker_for_Assimilation,_Synthesis_and_Integration_of_eNvironmental_Diverse,_Distributed_Datasets__django-basin3d_.json new file mode 100644 index 00000000..eaf88647 --- /dev/null +++ b/agency-indexes/DoE/Broker_for_Assimilation,_Synthesis_and_Integration_of_eNvironmental_Diverse,_Distributed_Datasets__django-basin3d_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "vchendrix@lbl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets) uses a data brokering approach to synthesize diverse earth science data from a variety of remote sources in real-time without the need for additional storage. BASIN-3D is an extendable Django web framework application using a generalized data synthesis model that makes the synthesized data available via Application Programming Interface (API). This extends the basin3d Python framework for data synthesis (http://github.com/BASIN-3D/basin3d).We have currently implemented our data synthesis model to represent sensor-based time series earth science observations across a hierarchy of spatial locations. Supporting our data synthesis model is a plugin framework that allows developers to map data sources of interest to the BASIN-3D synthesis model.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets (django-basin3d)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BASIN-3D/django-basin3d", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Broker_for_Assimilation,_Synthesis_and_Integration_of_eNvironmental_Diverse,_Distributed_Datasets_v1.1.0.json b/agency-indexes/DoE/Broker_for_Assimilation,_Synthesis_and_Integration_of_eNvironmental_Diverse,_Distributed_Datasets_v1.1.0.json new file mode 100644 index 00000000..f032b4c0 --- /dev/null +++ b/agency-indexes/DoE/Broker_for_Assimilation,_Synthesis_and_Integration_of_eNvironmental_Diverse,_Distributed_Datasets_v1.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-08-05", + "metadataLastUpdated": "2019-10-03" + }, + "description": "BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets) uses a data brokering approach to synthesize diverse earth science data from a variety of remote sources in real-time without the need for additional storage. BASIN-3D is an extendable Django web framework application using a generalized data synthesis model that makes the synthesized data available via REpresentational State Transfer (REST) Application Programming Interface (API). We have currently implemented our data synthesis model to represent sensor-based time series earth science observations across a hierarchy of spatial locations. Supporting our data synthesis model is a plugin framework that allows developers to map data sources of interest to the BASIN-3D synthesis model\n", + "laborHours": 2143.2, + "languages": [], + "name": "Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets v1.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Watershed-Function-SFA/BASIN-3D", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bruker_Data_Reader.json b/agency-indexes/DoE/Bruker_Data_Reader.json new file mode 100644 index 00000000..f7fea236 --- /dev/null +++ b/agency-indexes/DoE/Bruker_Data_Reader.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Library for reading data files acquired on Bruker mass spectrometers.", + "laborHours": 729.6, + "languages": [], + "name": "Bruker Data Reader", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/BrukerDataReader", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BrzostekEcologyLab_CORPSE-soil-jars.json b/agency-indexes/DoE/BrzostekEcologyLab_CORPSE-soil-jars.json new file mode 100644 index 00000000..13baabcc --- /dev/null +++ b/agency-indexes/DoE/BrzostekEcologyLab_CORPSE-soil-jars.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-08", + "metadataLastUpdated": "2024-11-08" + }, + "description": "Efforts to manage soils for carbon (C) sequestration remain limited by our understanding of how differences in plant traits and microbial traits mechanistically drive soil organic C (SOC) storage. Addressing this uncertainty is particularly critical in bioenergy agriculture, due to its potential to enhance soil C and provide a C neutral fuel. As such, we examined differences between two contrasting feedstocks, Zea mays (corn) and Miscanthus x giganteus (miscanthus), in the ability of their litter to form new chemically resistant particulate SOC vs. physically protected mineral associated SOC and used this data to improve the parameterization of a microbial SOC model. We tested a hypothesized conceptual model whereby easy to decompose corn litters drive greater microbial carbon use efficiency (CUE) and the formation of more mineral associated SOC over particulate SOC than more complex miscanthus litters. To do this, we performed a soil microcosm experiment where we added 13C enriched aboveground and belowground litters to soils and traced the fate of the 13C into microbial respiration and SOC pools. We found that corn litters promoted higher microbial CUE (0.37) than miscanthus litters (0.24). In turn, corn litter formed approximately 50% more mineral associated SOC than miscanthus litters. Similarly, structurally complex root litters promoted a lower CUE and formed less mineral associated SOC than leaf and shoot litters for both crops. When we used our data to parameterize the SOC model, we found that modeling microbial trait differences uniquely allowed the model to capture the fate of litter C in SOC. Collectively, we found a robust link between litter quality, microbial efficiency, and the formation of SOC. This link bridges the empirical uncertainty in how different crops can form new soil C and provides an empirical basis for modeling SOC transformations.", + "laborHours": 121.6, + "languages": [], + "name": "BrzostekEcologyLab/CORPSE-soil-jars", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BrzostekEcologyLab/CORPSE-soil-jars", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BubbleCluster_v4.json b/agency-indexes/DoE/BubbleCluster_v4.json new file mode 100644 index 00000000..015106df --- /dev/null +++ b/agency-indexes/DoE/BubbleCluster_v4.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-12", + "metadataLastUpdated": "2019-09-24" + }, + "description": "\tThe BubbleCluster algorithm was developed to help address the limitations of traditional genetic mapping tools when presented with large amounts of data. The BubbleCluster software is a tool for the initial stage in the genetic mapping pipeline -- clustering genetic markers into linkage groups. BubbleCluster was designed to tackle large genetic marker data sets, and has been tested on input of up to 1.6M markers. Input format is identical to that of the popular MSTMap package, aiding useability.", + "laborHours": 395.2, + "languages": [], + "name": "BubbleCluster v4", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/vstrnadova/BubbleCluster", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Budget_Constrained_Machine_Learning_for_Early_Prediction_of_Adverse_Outcomes_for_COVID-19_Patients.json b/agency-indexes/DoE/Budget_Constrained_Machine_Learning_for_Early_Prediction_of_Adverse_Outcomes_for_COVID-19_Patients.json new file mode 100644 index 00000000..d5367ab9 --- /dev/null +++ b/agency-indexes/DoE/Budget_Constrained_Machine_Learning_for_Early_Prediction_of_Adverse_Outcomes_for_COVID-19_Patients.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "Background: Machine learning (ML) based risk stratification models of Electronic Health records (EHR) data may help to optimize treatment of COVID-19 patients, but are often limited by their lack of clinical interpretability and cost of laboratory tests. We develop a ML based tool for predicting adverse outcomes based on EHR data to optimize clinical utility under a given cost structure. This cohort study was performed using deidentified EHR data from COVID-19 patients from ProMedica Healthcare in northwest Ohio and southeastern Michigan. Methods: We tested performance of various ML approaches for predicting either increasing ventilatory support or mortality and the set of model features under a budget constraint was optimized via exhaustive search across all combinations of features. Results: The optimal sets of features for predicting ventilation under any budget constraint included demographics and comorbidities (DCM), basic metabolic panel (BMP), D-dimer, lactate dehydrogenase (LDH), erythrocyte sedimentation rate (ESR), CRP, brain natriuretic peptide (BNP), and procalcitonin and for mortality included DCM, BMP, complete blood count, D-dimer, LDH, CRP, BNP, procalcitonin and ferritin. Conclusions: This study presents a quick, accurate and cost-effective method to evaluate risk of deterioration for patients with SARS-CoV-2 infection at the time of clinical evaluation.", + "laborHours": 0.0, + "languages": [], + "name": "Budget Constrained Machine Learning for Early Prediction of Adverse Outcomes for COVID-19 Patients", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/BCML-COVID19", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bug_Reports.json b/agency-indexes/DoE/Bug_Reports.json new file mode 100644 index 00000000..2819ceed --- /dev/null +++ b/agency-indexes/DoE/Bug_Reports.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-03", + "metadataLastUpdated": "2019-07-03" + }, + "description": "Unified issue-tracker for bugs in the data acquisition, management, and analysis software at NSLS-II.", + "laborHours": 60.8, + "languages": [], + "name": "Bug Reports", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/Bug-Reports", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bug_fixes___enhancements_to_Parallel_tempering_Markov_chain_Monte_Carlo_sampler__PTMCMCSampler__v3.json b/agency-indexes/DoE/Bug_fixes___enhancements_to_Parallel_tempering_Markov_chain_Monte_Carlo_sampler__PTMCMCSampler__v3.json new file mode 100644 index 00000000..9fc6f8e7 --- /dev/null +++ b/agency-indexes/DoE/Bug_fixes___enhancements_to_Parallel_tempering_Markov_chain_Monte_Carlo_sampler__PTMCMCSampler__v3.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-18" + }, + "description": "Markov chain Monte Carlo sampler useful for a variety of problems for optimization, numerical integration, and generating draws from a probability distribution. They are often used in physical and mathematical problems, especially when it is difficult or impossible to use other approaches.\n\nThis disclosure is for new bug fixes and enhancements to an existing open source library that is already in the public domain under the MIT license.\nhttps://github.com/jellis18/PTMCMCSampler", + "laborHours": 1246.4, + "languages": [], + "name": "Bug fixes / enhancements to Parallel tempering Markov chain Monte Carlo sampler (PTMCMCSampler) v3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nanograv/PTMCMCSampler", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Buggy-Program-Program.json b/agency-indexes/DoE/Buggy-Program-Program.json new file mode 100644 index 00000000..13a0a085 --- /dev/null +++ b/agency-indexes/DoE/Buggy-Program-Program.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2022-10-17", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The purpose of this code is to automatically create random C programs that are guaranteed to have bugs of a particular \"interestingness\". We are using this to train learning machines to fuzz programs better. Other people might want to use it for training humans to examine software.", + "laborHours": 0.0, + "languages": [ + "python 3" + ], + "name": "Buggy-Program-Program", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Buggy-Program-Program", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BuildStockQuery_[SWR-23-58].json b/agency-indexes/DoE/BuildStockQuery_[SWR-23-58].json new file mode 100644 index 00000000..e8debffd --- /dev/null +++ b/agency-indexes/DoE/BuildStockQuery_[SWR-23-58].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-12-13", + "metadataLastUpdated": "2023-12-18" + }, + "description": "BuildStockQuery is a python library designed to simplify and streamline the process of querying massive, terabyte-scale datasets generated by ResStock(TM). ResStock (SWR-19-15) is a U.S. DOE-supported, NREL-built, national residential building energy stock model that enables a new approach to large-scale residential energy analysis across the U.S. by combining large public and private data sources, statistical sampling, detailed sub-hourly building simulations, and high-performance computing. \n\nBuildStockQuery offers an intuitive Object-Oriented Programming (OOP) interface to the ResStock output dataset allowing users to easily perform common queries and receive results in familiar pandas DataFrame format, abstracting away the need for complex SQL query. By initializing a query object with the pertinent Athena database and table names, users can easily query for various kinds of insights, for example, timeseries electricity for an end use for a given state grouped by building types.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "BuildStockQuery [SWR-23-58]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/buildstock-query", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BuildTestGenome.json b/agency-indexes/DoE/BuildTestGenome.json new file mode 100644 index 00000000..c16e2376 --- /dev/null +++ b/agency-indexes/DoE/BuildTestGenome.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This module is useful for preparation of small Genome objects in tests of methods dealing with protein translations in CDSs only.", + "laborHours": 4940.0, + "languages": [], + "name": "BuildTestGenome", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/BuildTestGenome", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Build_Optimization_Software_Tools__BOOST__v2.0.0.json b/agency-indexes/DoE/Build_Optimization_Software_Tools__BOOST__v2.0.0.json new file mode 100644 index 00000000..126b2ba0 --- /dev/null +++ b/agency-indexes/DoE/Build_Optimization_Software_Tools__BOOST__v2.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Build Optimization Software Tools (BOOST) accelerate the design of DNA, RNA and protein sequences for their synthesis and assembly in an automated and scalable fashion.\n\nThe BOOST Juggler automates the following two design tasks:\n- Reverse-Translation of protein sequences into DNA sequences\n- Codon Juggling of DNA sequences\n\nThe BOOST Polisher provides the following design tasks:\n- The Verification of DNA sequences against DNA synthesis constraints\n- The Modification of DNA sequences in case they violate any DNA synthesis constraint\nIn addition, the BOOST Polisher can be instructed to verify and modify DNA sequences against sequence patterns, such as restriction sites.\n\nThe BOOST Partitioner supports both Gibson/chewback and Yeast assembly (also known as Transformation-Associated Recombination, or TAR) methods when performing the decomposition of large sequences that exceed the maximum length of DNA synthesis into synthesizable building blocks. The Partitioner can be instructed to find building blocks with appropriate overlap sequences, making their assembly into the complete construct more efficient.\n\nBOOST Workflows enable, in a customized fashion, the execution of the Juggler, Polisher, and Partitioner tools on a batch of sequences.", + "homepageURL": "https://marketplace.lbl.gov/biosciences/computational-biology/BOOST", + "laborHours": 0.0, + "languages": [], + "name": "Build Optimization Software Tools (BOOST) v2.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/license-agreements-marketplace-licenses", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://marketplace.lbl.gov/biosciences/computational-biology/BOOST", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Build_and_Execute_Environment.json b/agency-indexes/DoE/Build_and_Execute_Environment.json new file mode 100644 index 00000000..4ac51f37 --- /dev/null +++ b/agency-indexes/DoE/Build_and_Execute_Environment.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "At exascale, the challenge becomes to develop applications that run at scale and use exascale platforms reliably, efficiently, and flexibly. Workflows become much more complex because they must seamlessly integrate simulation and data analytics. They must include down-sampling, post-processing, feature extraction, and visualization. Power and data transfer limitations require these analysis tasks to be run in-situ or in-transit. We expect successful workflows will comprise multiple linked simulations along with tens of analysis routines. Users will have limited development time at scale and, therefore, must have rich tools to develop, debug, test, and deploy applications. At this scale, successful workflows will compose linked computations from an assortment of reliable, well-defined computation elements, ones that can come and go as required, based on the needs of the workflow over time. We propose a novel framework that utilizes both virtual machines (VMs) and software containers to create a workflow system that establishes a uniform build and execution environment (BEE) beyond the capabilities of current systems. In this environment, applications will run reliably and repeatably across heterogeneous hardware and software. Containers, both commercial (Docker and Rocket) and open-source (LXC and LXD), define a runtime that isolates all software dependencies from the machine operating system. Workflows may contain multiple containers that run different operating systems, different software, and even different versions of the same software. We will run containers in open-source virtual machines (KVM) and emulators (QEMU) so that workflows run on any machine entirely in user-space. On this platform of containers and virtual machines, we will deliver workflow software that provides services, including repeatable execution, provenance, checkpointing, and future proofing. We will capture provenance about how containers were launched and how they interact to annotate workflows for repeatable and partial re-execution. We will coordinate the physical snapshots of virtual machines with parallel programming constructs, such as barriers, to automate checkpoint and restart. We will also integrate with HPC-specific container runtimes to gain access to accelerators and other specialized hardware to preserve native performance. Containers will link development to continuous integration. When application developers check code in, it will automatically be tested on a suite of different software and hardware architectures.", + "laborHours": 2629.6, + "name": "Build and Execute Environment", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/BEE/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/BEE", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BuildingSync.json b/agency-indexes/DoE/BuildingSync.json new file mode 100644 index 00000000..a8f5c2cc --- /dev/null +++ b/agency-indexes/DoE/BuildingSync.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "BuildingSync\u00ae is a common schema for energy audit data that can be utilized by different software and databases involved in the energy audit process. It allows data to be more easily aggregated, compared and exchanged between different databases and software tools. This streamlines the energy audit process, improving the value of the data and facilitating achievement of greater energy efficiency.", + "laborHours": 134793.6, + "languages": [], + "name": "BuildingSync", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/BuildingSync/schema/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BuildingSync/schema", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/BuildingSync\302\256_[SWR-18-28].json" "b/agency-indexes/DoE/BuildingSync\302\256_[SWR-18-28].json" new file mode 100644 index 00000000..dfaf7d11 --- /dev/null +++ "b/agency-indexes/DoE/BuildingSync\302\256_[SWR-18-28].json" @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2024-09-19" + }, + "description": "BuildingSync\u00ae is a standardized language for commercial building energy audit data that software developers can use to exchange data between audit tools. Taking the form of an XML schema, BuildingSync can be required by building owners and audit program managers to allow data analysis and aggregation across multiple buildings in order to evaluate program performance and analyze trends. BuildingSync was developed using the standard energy data terminology defined in the Building Energy Data Exchange Specification (BEDES). BuildingSync is one of the first implementations of BEDES Version 1.0, and it was developed in close collaboration with the BEDES working groups. BuildingSync standardizes the format of the energy audit data itself. It is not intended to standardize the calculations performed on these data by engineers, analysts, software packages, or other audit tools. For more, see: https://buildingsync.net/", + "laborHours": 134793.6, + "languages": [ + "R", + "HTML", + "Ruby", + "Python" + ], + "name": "BuildingSync\u00ae [SWR-18-28]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/BuildingSync/schema/blob/develop-v2/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BuildingSync/schema", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/BuildingSync\302\256_v.2.5.0_2024_[SWR-18-28].json" "b/agency-indexes/DoE/BuildingSync\302\256_v.2.5.0_2024_[SWR-18-28].json" new file mode 100644 index 00000000..381af9a2 --- /dev/null +++ "b/agency-indexes/DoE/BuildingSync\302\256_v.2.5.0_2024_[SWR-18-28].json" @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-09-12" + }, + "description": "BuildingSync\u00ae is a building data exchange schema to better enable integration between software tools and building data workflows. The schema's original use case was focused on commercial building energy audits; however, several additional use cases have been realized including building energy modeling and more high-level generic building data exchange.\n\nBuildingSync helps streamline the data exchange process, improving the value of the data, minimizing duplication of effort for subsequent building data collection efforts (including audits), and facilitating the achievement of greater energy efficiency. This in done in part by standardizing on (a) reporting audits in an electronic format, (b) tracking proposed, implemented, and discarded energy conservation measures, and (c) storing building characteristics (at multiple levels) for audits, benchmarking, and building energy analysis.\n\nBuildingSync has several documents and tools available to help users understand how to best leverage BuildingSync. The list below are only a subset of the resources available. If new resources are discovered, then feel free to create a new pull request with the additions.\n\nGeneric BuildingSync information is available on the DOE website and the project website.\n\nBuildingSync Examples - These examples are kept up to date and show a wide range of implementations. Any new update to BuildingSync is required to pass validation on these example files.\n\nBuildingSync Use Case Validator allows for users to determine if their instance complies with a specific use case for BuildingSync by checking if the required elements are implemented in an uploaded instance. An API is also provided for automated integration into other tools. Also, the website contains an easy way to view the entirety of the schema and how elements relate to the Building Exchange Data Exchange Specification. The Validator is open sourced here\nUse Case TestSuite provides a Python package for easier generation of BuildingSync use cases. BuildingSync use cases depend on the generation of schematron documents, which is time-consuming and difficult to implement well. The TestSuite allows users to define a use case using a more palatable CSV template, which it then turns into a Schematron document. The source code is available here.\n\nBuildingSync to OpenStudio/EnergyPlus. The translator is open sourced here. This project will translate a Level 1 (and partial Level 2) ASHRAE Energy Audit to a fully defined OpenStudio and EnergyPlus model. This project is in early Beta testing and any feedback is welcome!", + "laborHours": 134793.6, + "languages": [ + "Python", + "Ruby" + ], + "name": "BuildingSync\u00ae v.2.5.0 2024 [SWR-18-28]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BuildingSync/schema", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.5.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Building_Controls_Virtual_Test_Bed.json b/agency-indexes/DoE/Building_Controls_Virtual_Test_Bed.json new file mode 100644 index 00000000..f1f6a3b0 --- /dev/null +++ b/agency-indexes/DoE/Building_Controls_Virtual_Test_Bed.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The Building Controls Virtual Test Bed (BCVTB) is a modular software environment that is based on the Ptolemy II software environment. The BCVTB can be used for design and analysis of heterogenous systems, such as building energy and controls systems. Our additions to Ptolemy II allow users to Couple to Ptolemy II simulation software such as EnergyPlus, MATLAB/Simulink or Dymola for data exchange during run-time. Future versions of the BCVTS will also contain an interface to BACnet which is a communication protocol for building Control systems, and interfaces to digital/analog converters that allow communication with controls hardware. Through Ptolemy II, the BCVTB provides a graphical model building environment, synchronizes the exchanged data and visualizes the system evolution during run- time.", + "homepageURL": "https://simulationresearch.lbl.gov/bcvtb", + "laborHours": 0.0, + "languages": [], + "name": "Building Controls Virtual Test Bed", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://simulationresearch.lbl.gov/bcvtb/License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://simulationresearch.lbl.gov/bcvtb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Building_Efficiency_Targeting_Tool_for_Energy_Retrofits__BETTER__Analytical_Engine.json b/agency-indexes/DoE/Building_Efficiency_Targeting_Tool_for_Energy_Retrofits__BETTER__Analytical_Engine.json new file mode 100644 index 00000000..ab6b1c5f --- /dev/null +++ b/agency-indexes/DoE/Building_Efficiency_Targeting_Tool_for_Energy_Retrofits__BETTER__Analytical_Engine.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-08", + "metadataLastUpdated": "2021-08-05" + }, + "description": "This is an open-source, empirical data-driven, virtual building energy analysis and retrofit targeting tool. The open-source tool will provide a fully-automated, \"no-cost/no-touch\" approach to screen large volumes of buildings for operational improvement and equipment upgrade opportunities and quantify associated potential energy and cost savings.", + "laborHours": 1292.0, + "languages": [], + "name": "Building Efficiency Targeting Tool for Energy Retrofits (BETTER) Analytical Engine", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-JCI-ICF/BETTER", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Building_Efficiency_Targeting_Tool_for_Energy_Retrofits__BETTER__Application_Programing_Interface__API___BETTER_API__v1.0.json b/agency-indexes/DoE/Building_Efficiency_Targeting_Tool_for_Energy_Retrofits__BETTER__Application_Programing_Interface__API___BETTER_API__v1.0.json new file mode 100644 index 00000000..2c7b2889 --- /dev/null +++ b/agency-indexes/DoE/Building_Efficiency_Targeting_Tool_for_Energy_Retrofits__BETTER__Application_Programing_Interface__API___BETTER_API__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-29", + "metadataLastUpdated": "2021-07-29" + }, + "description": "The BETTER API allows advanced users and developers to access BETTER's analytical functionalities via HTTP requests from their own software platform without using the BETTER web-interface. API users prepare the input data and analysis configurations in a JSON format and send it to the web application via an HTTP request. The web application runs the analytical workflow on the back end and returns an HTTP response in JSON format. The user can then decide to render the results or further process it.", + "homepageURL": "https://sites.google.com/lbl.gov/2021-128/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Building Efficiency Targeting Tool for Energy Retrofits (BETTER) Application Programing Interface (API) (BETTER API) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2021-128/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-128/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Building_Efficiency_Targeting_Tool_for_Energy_Retrofits__BETTER__Web_Application__BETTER_Web_App__v1.0.json b/agency-indexes/DoE/Building_Efficiency_Targeting_Tool_for_Energy_Retrofits__BETTER__Web_Application__BETTER_Web_App__v1.0.json new file mode 100644 index 00000000..9e154728 --- /dev/null +++ b/agency-indexes/DoE/Building_Efficiency_Targeting_Tool_for_Energy_Retrofits__BETTER__Web_Application__BETTER_Web_App__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-29", + "metadataLastUpdated": "2021-07-29" + }, + "description": "The Building Efficiency Targeting Tool for Energy Retrofits (BETTER) V.1.0 web application identifies cost-saving energy and emissions reductions in buildings and portfolios, without site visits or complex modeling. With minimal data entry, BETTER benchmarks a building's or portfolio's energy use against peers; quantifies energy, cost, and greenhouse gas (GHG) reduction potential; and recommends energy efficiency measures for individual buildings or portfolios, targeting specific energy savings levels. The source code of BETTER's modular, cross-platform analytical engine has previously been disclosed (2019-001) and is available on GitHub and can be adopted, redeveloped, and redistributed freely under an open-source license, allowing users to incorporate BETTER's analytical capabilities into their own software platforms and tools. The BETTER V.1.0 web application, developed with the Django web-framework and the Model-View-Controller (MVC) architecture being disclosed here, provides a graphical user interface (GUI) for any user to view the software tutorials, download and upload a data entry template, configure and run the BETTER analyses, and view the final analytical reports.", + "homepageURL": "https://sites.google.com/lbl.gov/2021-127/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Building Efficiency Targeting Tool for Energy Retrofits (BETTER) Web Application (BETTER Web App) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2021-127/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-127/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Building_Energy_Management_Open_Source_Software.json b/agency-indexes/DoE/Building_Energy_Management_Open_Source_Software.json new file mode 100644 index 00000000..cde1fa47 --- /dev/null +++ b/agency-indexes/DoE/Building_Energy_Management_Open_Source_Software.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is the repository for Building Energy Management Open Source Software (BEMOSS), which is an open source operating system that is engineered to improve sensing and control of equipment in small- and medium-sized commercial buildings. BEMOSS offers the following key features: (1) Open source, open architecture \u2013 BEMOSS is an open source operating system that is built upon VOLTTRON \u2013 a distributed agent platform developed by Pacific Northwest National Laboratory (PNNL). BEMOSS was designed to make it easy for hardware manufacturers to seamlessly interface their devices with BEMOSS. Software developers can also contribute to adding additional BEMOSS functionalities and applications. (2) Plug & play \u2013 BEMOSS was designed to automatically discover supported load controllers (including smart thermostats, VAV/RTUs, lighting load controllers and plug load controllers) in commercial buildings. (3) Interoperability \u2013 BEMOSS was designed to work with load control devices form different manufacturers that operate on different communication technologies and data exchange protocols. (4) Cost effectiveness \u2013 Implementation of BEMOSS deemed to be cost-effective as it was built upon a robust open source platform that can operate on a low-cost single-board computer, such as Odroid. This feature could contribute to its rapid deployment in small- or medium-sized commercial buildings. (5) Scalability and ease of deployment \u2013 With its multi-node architecture, BEMOSS provides a distributed architecture where load controllers in a multi-floor and high occupancy building could be monitored and controlled by multiple single-board computers hosting BEMOSS. This makes it possible for a building engineer to deploy BEMOSS in one zone of a building, be comfortable with its operation, and later on expand the deployment to the entire building to make it more energy efficient. (6) Ability to provide local and remote monitoring \u2013 BEMOSS provides both local and remote monitoring ability with role-based access control. (7) Security \u2013 In addition to built-in security features provided by VOLTTRON, BEMOSS provides enhanced security features, including BEMOSS discovery approval process, encrypted core-to-node communication, thermostat anti-tampering feature and many more. (8) Support from the Advisory Committee \u2013 BEMOSS was developed in consultation with an advisory committee from the beginning of the project. BEMOSS advisory committee comprises representatives from 22 organizations from government and industry.", + "laborHours": 153185.6, + "name": "Building Energy Management Open Source Software", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bemoss/BEMOSS3.5", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Building_Performance_Database_API__BPD_API__v2.1.json b/agency-indexes/DoE/Building_Performance_Database_API__BPD_API__v2.1.json new file mode 100644 index 00000000..42105b6a --- /dev/null +++ b/agency-indexes/DoE/Building_Performance_Database_API__BPD_API__v2.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-08", + "metadataLastUpdated": "2021-04-08" + }, + "description": "The Building Performance Database (BPD) is the largest publicly-available source of measured energy performance data for buildings in the United States. It contains information about the building's energy use, location, and physical and operational characteristics. The BPD can be used by building owners, operators, architects and engineers to compare a building's energy efficiency against customized peer groups, identify energy efficiency opportunities, and set energy efficiency targets. It can also be used by energy efficiency program implementers and policymakers to analyze energy efficiency features and trends in the building stock. The BPD compiles data from various data sources, converts it into a standard format, cleanses and quality checks the data, and provides users with access to the data in a way that maintains anonymity for data providers. This software is the database and the Application Programming Interface (API). Users can utilize the BPD's data to develop their own applications using the API. Version 2.1 included a major update for multiple years of data and refactoring of code for faster queries.", + "homepageURL": "https://buildings.lbl.gov/cbs/bpd", + "laborHours": 0.0, + "languages": [], + "name": "Building Performance Database API (BPD API) v2.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://buildings.lbl.gov/cbs/bpd", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Building_Re-tuning_Simulator.json b/agency-indexes/DoE/Building_Re-tuning_Simulator.json new file mode 100644 index 00000000..2b58d1b4 --- /dev/null +++ b/agency-indexes/DoE/Building_Re-tuning_Simulator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Building Re-tuning Simulator (BRS) is a Re-tuning focused modeling and building automation system simulation environment.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Building Re-tuning Simulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/BuildingsBench:_A_Benchmark_for_Universal_Building_Load_Forecasting_[SWR-23-51].json b/agency-indexes/DoE/BuildingsBench:_A_Benchmark_for_Universal_Building_Load_Forecasting_[SWR-23-51].json new file mode 100644 index 00000000..c3b0ffbf --- /dev/null +++ b/agency-indexes/DoE/BuildingsBench:_A_Benchmark_for_Universal_Building_Load_Forecasting_[SWR-23-51].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-08-28" + }, + "description": "The residential and commercial building stock in the United States is responsible for a significant percentage of energy consumption and greenhouse gas emissions. Electrification of end-uses, as well as decarbonizing the electrical grid through renewable energy sources such as solar and wind, constitutes the pathway to zero-emission buildings. Forecasting day-ahead building energy consumption is an integral part of this solution. Currently, specialized forecasting models are hand-made for each individual building, which is time-consuming, expensive, and leads to duplicated efforts. BuildingsBench is a Python software framework for training and comparing generalized machine learning models for universal building load forecasting. This challenge tasks a single foundational model to generalize its forecasts for a wide variety of buildings, across geographic regions, building types, weather patterns, and more. This software provide code for pre-training such models and subsequently evaluating their performance on a suite of hundreds of diverse real and synthetic buildings.\n\nBuildingsBench is a platform for:\n\n- Large-scale pretraining with the synthetic Buildings-900K dataset for short-term load forecasting (STLF). Buildings-900K is statistically representative of the entire U.S. building stock and is extracted from the NREL End-Use Load Profiles database.\n\n- Benchmarking on two tasks evaluating generalization: zero-shot STLF and transfer learning for STLF.\n\nWe provide an index-based PyTorch Dataset for large-scale pretraining, easy data loading for multiple real building energy consumption datasets as PyTorch Tensors or Pandas DataFrames, simple (persistence) to advanced (transformer) baselines, metrics management, and more.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "BuildingsBench: A Benchmark for Universal Building Load Forecasting [SWR-23-51]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BuildingsBench", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BuildingsPy.json b/agency-indexes/DoE/BuildingsPy.json new file mode 100644 index 00000000..661e9de0 --- /dev/null +++ b/agency-indexes/DoE/BuildingsPy.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2019-10-04" + }, + "description": "BuildingsPy is a Python package that can be used to run Modelica simulations and to process Modelica output files. It can also be used to run unit tests as part of the development of LBNL's Modelica Buildings library. The package provides functions to extract data series from the output file for further use in the python packages matplotlib for plotting and SciPy for scientific computing.", + "laborHours": 3936.8, + "languages": [], + "name": "BuildingsPy", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-srg/BuildingsPy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bulb-style_Kaplan_Turbine_-_Run-of-the-river__ror__Hydro_Governor_And_Turbine_Model.json b/agency-indexes/DoE/Bulb-style_Kaplan_Turbine_-_Run-of-the-river__ror__Hydro_Governor_And_Turbine_Model.json new file mode 100644 index 00000000..f28274a9 --- /dev/null +++ b/agency-indexes/DoE/Bulb-style_Kaplan_Turbine_-_Run-of-the-river__ror__Hydro_Governor_And_Turbine_Model.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-10-20", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This software package includes hydro governor and turbine models developed in Simulink (Mathworks Inc.) and RSCAD (RTDS Technologies) for low-head bulb-style Kaplan turbine hydropower plants. The model developed in Simulink has been designed and tuned to match the governor-turbine response for a real-world hydropower unit owned by Idaho Falls Power (IFP). The Simulink and RSCAD models enable real-time testing in a hardware-in-the-loop (HIL) implementation using OPAL-RT and RTDS digital real-time simulators, respectively. An automatic initialization for dynamic simulation has also been integrated to each model in both Simulink and RSCAD. The RSCAD initialization involves a novel python-based interfacing for automatic modification of the initial conditions in the model. The parameters of these models can be tuned to match other hydropower plants in this class.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python", + "Simulink" + ], + "name": "Bulb-style Kaplan Turbine - Run-of-the-river (ror) Hydro Governor And Turbine Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Hydropower_Unit_Models", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bulk_Data_Mover.json b/agency-indexes/DoE/Bulk_Data_Mover.json new file mode 100644 index 00000000..46ef61e3 --- /dev/null +++ b/agency-indexes/DoE/Bulk_Data_Mover.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Bulk Data Mover (BDM) is a high-level data transfer management tool. BDM handles the issue of large variance in file sizes and a big portion of small files by managing the file transfers with optimized transfer queue and concurrency management algorithms. For example, climate simulation data sets are characterized by large volume of files with extreme variance in file sizes. The BDN achieves high performance using a variety of techniques, including multi-threaded concurrent transfer connections, data channel caching, load balancing over multiple transfer servers, and storage i/o pre-fetching. Logging information from the BDM is collected and analyzed to study the effectiveness of the transfer management algorithms. The BDM can accept a request composed of multiple files or an entire directory. The request also contains the target site and directory where the replicated files will reside. If a directory is provided at the source, then the BDM will replicate the structure of the source directory at the target site. The BDM is capable of transferring multiple files concurrently as well as using parallel TCP streams. The optimal level of concurrency or parallel streams depends on the bandwidth capacity of the storage systems at both ends of the transfer as well as achievable bandwidth of the wide-area network. Hardware req.-PC, MAC, Multi-platform & Workstation; Software req.: Compile/version-Java 1.50_x or above; Type of files: source code, executable modules, installation instructions other, user guide; URL: http://sdm.lbl.gov/bdm/", + "homepageURL": "https://sdm.lbl.gov/bdm", + "laborHours": 0.0, + "languages": [ + "java 1.50{sub minus}x or above" + ], + "name": "Bulk Data Mover", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sdm.lbl.gov/bdm/License.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sdm.lbl.gov/bdm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Bulk_Data_Upload_Plugin.json b/agency-indexes/DoE/Bulk_Data_Upload_Plugin.json new file mode 100644 index 00000000..98e0eff1 --- /dev/null +++ b/agency-indexes/DoE/Bulk_Data_Upload_Plugin.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "Wraps the bulk upload plugin in an iframe in a plugin.", + "laborHours": 45539.2, + "languages": [], + "name": "Bulk Data Upload Plugin", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/kbase-ui-plugin-bulk-ui", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/BurstFS.json b/agency-indexes/DoE/BurstFS.json new file mode 100644 index 00000000..583e524f --- /dev/null +++ b/agency-indexes/DoE/BurstFS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "A Distributed Burst Buffer File System.\n", + "laborHours": 21371.2, + "languages": [], + "name": "BurstFS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/burstfs", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ButterflyPACK.json b/agency-indexes/DoE/ButterflyPACK.json new file mode 100644 index 00000000..54097bb8 --- /dev/null +++ b/agency-indexes/DoE/ButterflyPACK.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-13", + "metadataLastUpdated": "2019-09-23" + }, + "description": "ButterflyPACK is a mathematical software for rapidly solving large-scale dense linear systems that exhibit off-diagonal rank-deficiency properties. These targeted systems are either matrices arising from discretized boundary integral equations, or frontal matrices in multi-frontal solvers for differential equations. ButterflyPACK relies on low-rank and butterfly formats under Hierarchical matrix, HODLR or HSS frameworks to compress, factor/precondition and solve the linear system in quasi-linear time. ButterflyPACK is particularly useful for large-scale ill-conditioned matrices arising from high-frequency wave equations involving multiple right-hand-sides. \n\nButterflyPACK is based on Fortran 2003, it also has interface written in C++. In addition, ButterflyPACK can be readily invoked from the software STRUMPACK. \n\nButterflyPACK supports hybrid MPI/OpenMP programming models.", + "laborHours": 25931.2, + "languages": [], + "name": "ButterflyPACK", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/liuyangzhuan/ButterflyPACK", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Buzzard.json b/agency-indexes/DoE/Buzzard.json new file mode 100644 index 00000000..ff5c835e --- /dev/null +++ b/agency-indexes/DoE/Buzzard.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Utility for manually and automatically adding datasets to DMS", + "laborHours": 10032.0, + "languages": [], + "name": "Buzzard", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Buzzard", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/C++_PolyFit.json b/agency-indexes/DoE/C++_PolyFit.json new file mode 100644 index 00000000..9a9b974e --- /dev/null +++ b/agency-indexes/DoE/C++_PolyFit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "C++ PolyFit is a simple least-squares polynomial fitter (Polynomial Regression) for C++. It can fit multidimensional polynomials up to 3 dimensions (ie F(x,y,z)), evaluate them, and get derivatives and evaluate those. It has convenience functions for getting 1st, and second derivatives, including mixed derivatives, but it can be used to get higher derivatives as well just by rerunning the derivers.\n", + "laborHours": 206203.2, + "languages": [], + "name": "C++ PolyFit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CxxPolyFit", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/C++_Utility_Library_V4.0.json b/agency-indexes/DoE/C++_Utility_Library_V4.0.json new file mode 100644 index 00000000..b11ed1cf --- /dev/null +++ b/agency-indexes/DoE/C++_Utility_Library_V4.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "A C++ utility library that provides abstractions for common data types with debugging features, support for I/O redirection and support for portability.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "C++ Utility Library V4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/snl-dakota/dakota-packages", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "4.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/C2QA_bosonic-qiskit.json b/agency-indexes/DoE/C2QA_bosonic-qiskit.json new file mode 100644 index 00000000..77e19bda --- /dev/null +++ b/agency-indexes/DoE/C2QA_bosonic-qiskit.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-08-23", + "metadataLastUpdated": "2025-02-13" + }, + "description": "Extension of Qiskit to support hybrid boson-qubit simulations for the NQI C2QA effort.", + "laborHours": 4772.8, + "languages": [], + "name": "C2QA/bosonic-qiskit", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/C2QA/bosonic-qiskit", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CACTUS.json b/agency-indexes/DoE/CACTUS.json new file mode 100644 index 00000000..718b6130 --- /dev/null +++ b/agency-indexes/DoE/CACTUS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-06-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "CACTUS is an innovative LLM\u2010based agent that combines the cognitive capabilities of large language models with domain\u2010specific tools. By integrating\ncheminformatics tools, CACTUS assists researchers in tasks such as molecular property prediction, similarity searching, and drug\u2010likeness assessment.", + "laborHours": 729.6, + "languages": [], + "name": "CACTUS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/cactus", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CAEN_HV_Power_Supply_EPICS_IOC.json b/agency-indexes/DoE/CAEN_HV_Power_Supply_EPICS_IOC.json new file mode 100644 index 00000000..841e1fe7 --- /dev/null +++ b/agency-indexes/DoE/CAEN_HV_Power_Supply_EPICS_IOC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2022-08-02" + }, + "description": "EPICS IOC to control CAEN HV Power Supplies.", + "laborHours": 0.0, + "languages": [], + "name": "CAEN HV Power Supply EPICS IOC", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/CAENHV/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/CAENHV", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CALMS:_CONTEXT-AWARE_LANGUAGE_MODEL_FOR_SCIENCE.json b/agency-indexes/DoE/CALMS:_CONTEXT-AWARE_LANGUAGE_MODEL_FOR_SCIENCE.json new file mode 100644 index 00000000..b526adbe --- /dev/null +++ b/agency-indexes/DoE/CALMS:_CONTEXT-AWARE_LANGUAGE_MODEL_FOR_SCIENCE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-04-10", + "metadataLastUpdated": "2024-04-10" + }, + "description": "Context-Aware Language Model for Science (CALMS) is designed to assist scientists with instrument operations and complex experimentation. CALMS consists of a large-language model (LLM) augmented with context and tool use abilities. With the ability to retrieve relevant information from facility documentation, CALMS can answer simple questions on scientific capabilities and other operational procedures. With the ability to interface with software tools and experimental hardware, CALMS can operate scientific instruments in a conversational manner.", + "laborHours": 67427.2, + "languages": [], + "name": "CALMS: CONTEXT-AWARE LANGUAGE MODEL FOR SCIENCE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mcherukara/CALMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CAMELLIA.json b/agency-indexes/DoE/CAMELLIA.json new file mode 100644 index 00000000..e06490d5 --- /dev/null +++ b/agency-indexes/DoE/CAMELLIA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "Camellia offers a framework for development of solvers for the discontinuous Petrov-Galerkin methodology of Demkowicz and Gopalakrishnan as well as other finite element methodologies. Spatially 1D-3D meshes are supported, and space-time elements are supported for all spatial topologies. Both h and p adaptivity are supported. A general interface for direct and iterative solvers is provided; a geometric multigrid preconditioner is also provided. The core computational kernels take advantage of MPI to execute in parallel.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "CAMELLIA", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CANARYV1.5.json b/agency-indexes/DoE/CANARYV1.5.json new file mode 100644 index 00000000..cfab2ffc --- /dev/null +++ b/agency-indexes/DoE/CANARYV1.5.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Canary is an extensible water-quality change-detection tool for algorithm development. It has been developed in MATLAB and was developed as part of an IAG with the US EPA NHSRC.", + "homepageURL": "https://software.sandia.gov/trac/canary", + "laborHours": 0.0, + "name": "CANARYV1.5", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://software.sandia.gov/trac/canary", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CANDELINC2.json b/agency-indexes/DoE/CANDELINC2.json new file mode 100644 index 00000000..00f05e5f --- /dev/null +++ b/agency-indexes/DoE/CANDELINC2.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2024-08-07" + }, + "description": "This work presents a method of performing PARAFAC2 factorization of a three-way data using a compact representation of the data. The data are decomposed into a core matrix and sets of orthogonal loading matrices. The algorithm is particularly useful for very large data sets and essentially permits imposition of nonnegativity in all three modes. SAND2019-10097 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 91.2, + "languages": [ + "MATLAB" + ], + "name": "CANDELINC2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CANDELINC2", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CARDINAL.json b/agency-indexes/DoE/CARDINAL.json new file mode 100644 index 00000000..5d90f1b8 --- /dev/null +++ b/agency-indexes/DoE/CARDINAL.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-01-27", + "metadataLastUpdated": "2023-01-27" + }, + "description": "Cardinal is a code that automates the workflow for iteratively solving neutral particle transport via the OpenMC code and computational fluid dynamics via the NekRS code within the Multiphysics Object Oriented Simulation Environment (MOOSE), a finite element framework for solving general partial differential equations. Cardinal establishes a mapping between the Monte Carlo geometry representation used in OpenMC and the spectral element mesh used in NekRS to other physics applications built upon the MOOSE framework, allowing high-resolution particle transport and fluid dynamics physics feedback to the MOOSE application ecosystem. Heat generation rates as solved by OpenMC are used as heat sources in MOOSE, while the temperature and density fields from NekRS are used as conjugate heat transfer boundary conditions and/or source fields in MOOSE. OpenMC, Nek5000, and MOOSE are open source, community-developed simulation codes.", + "laborHours": 0.0, + "languages": [], + "name": "CARDINAL", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/neams-th-coe/cardinal", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CASTRO.json b/agency-indexes/DoE/CASTRO.json new file mode 100644 index 00000000..15418362 --- /dev/null +++ b/agency-indexes/DoE/CASTRO.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Not Specified", + "laborHours": 87278.4, + "name": "CASTRO", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/AMReX-Astro/Castro/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Astro/Castro", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CAS_Code.json b/agency-indexes/DoE/CAS_Code.json new file mode 100644 index 00000000..9ca3956c --- /dev/null +++ b/agency-indexes/DoE/CAS_Code.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "darve@stanford.edu" + }, + "date": { + "created": "2018-01-31", + "metadataLastUpdated": "2018-01-31" + }, + "description": "The regular weighted ensemble method simulation Python code was originally developed by H. Lee, Stanford. The bash \nscript for multiple simultaneous simulations was originally developed by S. Ahn, Stanford. The resampling method \nimplemented in the code is from E. Darve and J. Izaguirre (Chapter 7 in Schlick's \"Innovations in Biomolecular Modeling \nand Simulations.\"). The Concurrent Adaptive Sampling (CAS) algorithm Python code was developed on top of the regular \nweighted ensemble method code by S. Ahn, Stanford. Improvements on the parameter input file had been made by J. \nBirgmeier, Stanford.\n\nThere are two folders provided in this Github repository: **2D_Toy_Model_Code** and **MD_Code**. Each folder provides \nall of the needed code with input files for a particular example, e.g., toymodel1, toymodel2, and penta-alanine. In the \n2D_Toy_Model_Code, **Code_With_Proper_Files** will make a separate folder with many output files for each walker and\n**Code_Without_Proper_Files** will only output minimum number of files like flux.txt, total_weight_on_each_ball.txt, \ntotal_weight.txt, time_record.txt, etc.", + "laborHours": 2523.2, + "name": "CAS_Code", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/shirleyahn/CAS_Code", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CATS_v._2.json b/agency-indexes/DoE/CATS_v._2.json new file mode 100644 index 00000000..8d5ec67c --- /dev/null +++ b/agency-indexes/DoE/CATS_v._2.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-28", + "metadataLastUpdated": "2019-03-28" + }, + "description": "This program calculates performance characteristics for a split flow recompression closed Brayton cycle. The user defines for the cycle; minimum temperature, minimum pressure, maximum temperature, maximum pressure, pinch temperature at the cold ends of the low temperature and high temperature recuperators, component fractional pressure drop, and efficiencies for each of the two turbines and each of the two compressors. All of these parameters except component fractional pressure drop and turbomachinery efficiencies are varies in separate do loops. In this way, minimum and maximum values for each of these parameters can be set. Results from each iteration are saved to a .csv file. Following completion of the program run, the .csv file can be read into a plotting package and the results can be plotted.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 121.6, + "languages": [], + "name": "CATS v. 2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CApp_v.1.0.0.json b/agency-indexes/DoE/CApp_v.1.0.0.json new file mode 100644 index 00000000..815a5a03 --- /dev/null +++ b/agency-indexes/DoE/CApp_v.1.0.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2021-12-02" + }, + "description": "SAND2021-6830 O Capp is a minimal package manager that supports the dependencies of one application. Its value in comparison to other package managers is its high portability across operating systems and its simplicity and usability for High Performance Computing (HPC) programmers. 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The primary goal of CELAVI is to help answer questions about how material flows and environmental and economic impacts of energy systems might change if the circularity of energy systems increases.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "CELAVI (Circular Economy Lifecycle Assessment and VIsualization) v.1.3.1 9/30/2022 [SWR-20-87]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/celavi", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v.1.3.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CELLAR.json b/agency-indexes/DoE/CELLAR.json new file mode 100644 index 00000000..d392fd9d --- /dev/null +++ b/agency-indexes/DoE/CELLAR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "The CELL Adaptive mesh Refinement (CELLAR) application provides cell-based adaptive mesh refinement data structures and execution for parallel computing architectures. This application also includes example tests that exercise iteration patterns over the mesh entities (cells, edges, faces). The application is written in C++ and Fortran.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "CELLAR", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CENS.json b/agency-indexes/DoE/CENS.json new file mode 100644 index 00000000..b48dead4 --- /dev/null +++ b/agency-indexes/DoE/CENS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-07", + "metadataLastUpdated": "2021-07-07" + }, + "description": "The CENS code translates Evaluated Nuclear Structure Data File, ENSDF, into application-specific formats, such as\nReference Input Parameter Library, RIPL, as well as into a generic XML format. Although ENSDF contains the most updated\nnuclear structure information, its complex format and philosophy of purely experimental basis often prevent direct use in\npractical applications in fundamental and applied science. CENS reads the adopted discrete levels, their spin and parity,\nand gamma-ray branching ratios etc. compiled in ENSDF, and estimates some missing information as needed by\nconsidering the statistical properties of nuclear structure, then prints out the nuclear structure data in more readable\nformats. CENS is written in C++, about 5,000 lines in total. A user's manual is also provided in HTML in the same package.\n[LAUR 21-22523]", + "laborHours": 0.0, + "languages": [], + "name": "CENS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/toshihikokawano/CENS", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CEWAM__Circular_Economy_Wind_Agent-based_Model__[SWR-21-120].json b/agency-indexes/DoE/CEWAM__Circular_Economy_Wind_Agent-based_Model__[SWR-21-120].json new file mode 100644 index 00000000..e00dded0 --- /dev/null +++ b/agency-indexes/DoE/CEWAM__Circular_Economy_Wind_Agent-based_Model__[SWR-21-120].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-11-01", + "metadataLastUpdated": "2024-07-01" + }, + "description": "The Circular Economy Wind Agent-based Model (CEWAM) is an agent-based model built with the MESA python library. The tool enables studying various circular economy strategies by simulating actors decisions.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "CEWAM (Circular Economy Wind Agent-based Model) [SWR-21-120]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CEWAM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CFD_codes_for_biomass_pyrolysis.json b/agency-indexes/DoE/CFD_codes_for_biomass_pyrolysis.json new file mode 100644 index 00000000..a9e2c2d6 --- /dev/null +++ b/agency-indexes/DoE/CFD_codes_for_biomass_pyrolysis.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "albertop@iastate.edu" + }, + "date": { + "created": "2022-03-31", + "metadataLastUpdated": "2022-03-31" + }, + "description": "Eulerian-Eulerian CFD models with bidisperse kinetic theory of the granular flow, and kinetics for biomass pyrolysis. The models were implemented in customized versions of OpenFOAM.", + "laborHours": 0.0, + "languages": [ + "C", + "C++" + ], + "name": "CFD codes for biomass pyrolysis", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Biomass-Autothermal-Pyrolysis/CFDCodes", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CFDbuilder.json b/agency-indexes/DoE/CFDbuilder.json new file mode 100644 index 00000000..4695bad3 --- /dev/null +++ b/agency-indexes/DoE/CFDbuilder.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Computational Fluid Dynamics is an important area in scientific computing where, despite the use of multi-threading, obtaining good performance at each core is still extremely challenging. The challenges are primarily due to memory bandwidth limitations and difficulties in using short SIMD engines effectively. One strategy to improve in-core performance involves using a hierarchical data layout made of small cubical structures of the problem states that can fit well in the cache hierarchy. Even for such a hierarchical data layout, finite-differencing equations can be easily expressed but at the expense of some inefficiency. The transformations to overcome the inefficiencies are highly tedious and error-prone. Therefore, we built a source-to-source translator called CFDbuilder to automate the transformations using directives. We see up to 6.92x performance improvement with one of our advection codes using such an approach. We believe such an approach could enable library and application writers to build efficient CFD libraries.", + "laborHours": 8831.2, + "languages": [ + "Java", + "Makefile", + "GAP" + ], + "name": "CFDbuilder", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/CFDbuilder?tab=License-1-ov-file", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CFDbuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CFDverify.json b/agency-indexes/DoE/CFDverify.json new file mode 100644 index 00000000..e2b34f46 --- /dev/null +++ b/agency-indexes/DoE/CFDverify.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "weinmeistejr@ornl.gov" + }, + "date": { + "created": "2025-01-23", + "metadataLastUpdated": "2025-01-24" + }, + "description": "Estimating the discretization error of computational fluid dynamics (CFD) or other scientific codes as part of solution verification is often a non-trivial part of the analysis process. Methods can be complicated and may include assumptions/qualifications that need to be checked during analysis. CFD analysts, therefore, are likely to make errors when trying to conduct this necessary analysis on their own in not knowing about the best method for their problem, not correctly implementing a method, or in not have diagnostic tools to determine if the method was correctly applied.", + "laborHours": 486.4, + "languages": [ + "Python" + ], + "name": "CFDverify", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/cfd-verify", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CFTrack_v.1.0.json b/agency-indexes/DoE/CFTrack_v.1.0.json new file mode 100644 index 00000000..71ed2a47 --- /dev/null +++ b/agency-indexes/DoE/CFTrack_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2022-10-05" + }, + "description": "SAND2021-13952 O Cloud Feature Tracker (CFTrack) is an application for following low-cloud motion in Geostationary Operational Environmental Satellite (GOES) R-series imagery. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "python 3.7+" + ], + "name": "CFTrack v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CFTrack", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CGC.json b/agency-indexes/DoE/CGC.json new file mode 100644 index 00000000..924682e5 --- /dev/null +++ b/agency-indexes/DoE/CGC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "Clustering methods are heavily dependent on the algorithm of choice, as well as the chosen hyperparameters of the algorithm and their sensitivity to data scales is largely unknown. In our software, we introduce a tensor clustering that relays on discrete wavelet transform to analyze the effects of course-graining on clustering of high-dimensional tensor data. Our method CGC allows us to understand how the different scales affect clustering. The scale of data is an important feature with regards to clustering. CGC calculates the normalized mutual information drop off at different length scales which illustrates certain resolutions are producing novel clusters. Consequently, in addition to running several clustering algorithms, it is also important to include several coarse-grain clusterings into a cluster ensemble.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "CGC", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CGYRO.json b/agency-indexes/DoE/CGYRO.json new file mode 100644 index 00000000..c464085c --- /dev/null +++ b/agency-indexes/DoE/CGYRO.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "sfiligoii@fusion.gat.com" + }, + "date": { + "created": "2018-11-06", + "metadataLastUpdated": "2018-11-09" + }, + "description": "CGYRO is a multi-species spectral gyrokinetic solver with sonic rotation capability. It is an Eulerian GK solver specifically designed and optimized for collisional, electromagnetic, multiscale simulation. A key algorithmic aspect of CGYRO is the radially spectral formulation used to reduce the complicated integral gyroaveraging kernel into a multiplication in wavenumber space, but retaining the ability to treat profile variation important for edge plasmas. This makes it suitable for\nnext-generation computational systems that require high levels of parallel concurrency.\n", + "homepageURL": "http://gafusion.github.io/doc/download.html", + "laborHours": 160496.8, + "languages": [ + "Fortran" + ], + "name": "CGYRO", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://gafusion.github.io/doc/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://gafusion.github.io/doc/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "version": "16.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CHAI_and_RAJA_Extensions.json b/agency-indexes/DoE/CHAI_and_RAJA_Extensions.json new file mode 100644 index 00000000..0854b51b --- /dev/null +++ b/agency-indexes/DoE/CHAI_and_RAJA_Extensions.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "CHAI and RAJA provide an excellent base on which to build portable codes. CARE expands that\nfunctionality, adding new features such as loop fusion capability and a portable interface for many\nnumerical algorithms. It provides all the basics for anyone wanting to write portable code.", + "laborHours": 9956.0, + "languages": [], + "name": "CHAI and RAJA Extensions", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CARE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.10" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CHAI_v2.1.json b/agency-indexes/DoE/CHAI_v2.1.json new file mode 100644 index 00000000..b47e48c4 --- /dev/null +++ b/agency-indexes/DoE/CHAI_v2.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "CHAI is a library that handles automatic data migration to different memory spaces behind an array-style interface. It was designed to work with RAJA and integrates with it. CHAI could be used with other C++ abstractions, as well.", + "laborHours": 5320.0, + "languages": [], + "name": "CHAI v2.1", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/CHAI/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CHAI", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CHMMPP:_A_c++_library_for_constrained_Hidden_Markov_Models.json b/agency-indexes/DoE/CHMMPP:_A_c++_library_for_constrained_Hidden_Markov_Models.json new file mode 100644 index 00000000..355dae36 --- /dev/null +++ b/agency-indexes/DoE/CHMMPP:_A_c++_library_for_constrained_Hidden_Markov_Models.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-09", + "metadataLastUpdated": "2024-10-09" + }, + "description": "SAND2024-13027O\nThe CHMMPP: A c++ Library for Constrained Hidden Markov Models (HMM) software supports the analysis of multivariate time series data to detect patterns using HMM. Many applications involve the detection and characterization of hidden or latent states in a complex system using observable states and variables. This software supports inference of latent states integrating both an HMM and application-specific constraints that reflect known relationships in hidden states. The CHMMPP software supports application-specific and generic methods for constrained inference. This includes a framework for customized Viterbi methods, constrained inference of hidden states with A* and integer programming methods, and various constraint-informed methods for learning HMM model parameters. CHMMPP focuses on supporting generic methods that enable the agile expression of complex sets of constraints that naturally arise in many real-world applications.", + "laborHours": 4028.0, + "languages": [ + "C++" + ], + "name": "CHMMPP: A c++ library for constrained Hidden Markov Models", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/chmmpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CHOS.json b/agency-indexes/DoE/CHOS.json new file mode 100644 index 00000000..effde01b --- /dev/null +++ b/agency-indexes/DoE/CHOS.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "CHOS is a framework that facilitates concurrently supporting multiple Linux distributions on a single system. This is primarily accomplished using the change root (chroot) method built into the Linux kernel. However, CHOS provides an additional kernel module that allows the same chroot file structure to be Used for multiple systems. The software also includes utilities to switch into the chroot environment from the command-line and a pluggable authentication module (PAM) allowing transparent startup of the chroot environment for users.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "gcc" + ], + "name": "CHOS", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CHROTRAN,_1.0.json b/agency-indexes/DoE/CHROTRAN,_1.0.json new file mode 100644 index 00000000..272b9388 --- /dev/null +++ b/agency-indexes/DoE/CHROTRAN,_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CHROTRAN is a fork of the widely-used PFLOTRAN flow and reactive transport numerical simulation code. It implements custom physics and chemistry appropriate to the design of in-situ reduction of heavy metals such as Cr(VI) in groundwater. CHROTRAN includes full dynamics for five species: the metal to be remediated, an electron donor, biofilm, a nontoxic conservative bio-inhibitor, and a biocide. Direct abiotic reduction by donor-metal interaction as well as donor-driven biomass growth and bio-reduction are modeled, along with crucial processes such as donor sorption, and biofilm inactivation. The software implementation handles heterogeneous flow fields, arbitrarily many chemical species and amendment injection points, and features full coupling between flow and reactive transport, allowing for assessment of the effect of bio-fouling.", + "laborHours": 173325.6, + "name": "CHROTRAN, 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/scottkalevhansen/CHROTRAN-release", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CHiPBETA.json b/agency-indexes/DoE/CHiPBETA.json new file mode 100644 index 00000000..6c48e7bc --- /dev/null +++ b/agency-indexes/DoE/CHiPBETA.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "High-accuracy water level data are needed to resolve the temporal and spatial hydraulic response to pumping in aquifers. However, the water-level data are typically affected by physical process unrelated to the aquifer pumping such as barometric pressure changes, tides, earthquakes, {\\etc}. We have developed a computational framework to correct for barometric and Earth tide effects using linear regression deconvolution, as an initial guess for a nonlinear residual minimization to account for pumping effects. The pumping effects are predicted using the Theis equation with initialization by Jacob's method. After minimizing the residuals between the observed data and Theis predicted pumping effects, the algorithm estimates storativity and transmissivity of the aquifer. The algorithm also provides information about the measurement accuracy of the collected water-level data. The computational framework CHiPBETA is developed in Python and demonstrated to analyze synthetic and real data.", + "laborHours": 4605.6, + "languages": [ + "Python" + ], + "name": "CHiPBETA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/zem/chipbeta", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CICE,_The_Los_Alamos_Sea_Ice_Model.json b/agency-indexes/DoE/CICE,_The_Los_Alamos_Sea_Ice_Model.json new file mode 100644 index 00000000..5583124b --- /dev/null +++ b/agency-indexes/DoE/CICE,_The_Los_Alamos_Sea_Ice_Model.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Los Alamos sea ice model (CICE) is the result of an effort to develop a computationally efficient sea ice component for a fully coupled atmosphere\u2013land\u2013ocean\u2013ice global climate model. It was originally designed to be compatible with the Parallel Ocean Program (POP), an ocean circulation model developed at Los Alamos National Laboratory for use on massively parallel computers. CICE has several interacting components: a vertical thermodynamic model that computes local growth rates of snow and ice due to vertical conductive, radiative and turbulent fluxes, along with snowfall; an elastic-viscous-plastic model of ice dynamics, which predicts the velocity field of the ice pack based on a model of the material strength of the ice; an incremental remapping transport model that describes horizontal advection of the areal concentration, ice and snow volume and other state variables; and a ridging parameterization that transfers ice among thickness categories based on energetic balances and rates of strain. It also includes a biogeochemical model that describes evolution of the ice ecosystem. The CICE sea ice model is used for climate research as one component of complex global earth system models that include atmosphere, land, ocean and biogeochemistry components. It is also used for operational sea ice forecasting in the polar regions and in numerical weather prediction models.", + "laborHours": 51938.4, + "name": "CICE, The Los Alamos Sea Ice Model", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/CICE-Consortium/CICE/blob/master/LICENSE.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CICE-Consortium/CICE", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CIGEN.json b/agency-indexes/DoE/CIGEN.json new file mode 100644 index 00000000..34fd40a9 --- /dev/null +++ b/agency-indexes/DoE/CIGEN.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-27", + "metadataLastUpdated": "2024-08-27" + }, + "description": "CIGEN is a tool that finds input ranges that cause high compiler-induced numerical inconsistencies in\nnumerical programs written in a compiled language. Numerical program behavior may diverge when they\nare compiled and ran differently. Many factors, such as different hardware architectures (for example, the\nx87 FPU with its 80-bit registers), different compilers, or different optimization flags may cause the results\nof floating-point computations to become inconsistent. This kind of inconsistencies are known as\ncompiler-induced numerical inconsistencies. Given a program with floating-point inputs and an output,", + "laborHours": 3739.2, + "languages": [], + "name": "CIGEN", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CIGEN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CIME,_Common_Infrastructure_for_Modeling_the_Earth_v._5.0.json b/agency-indexes/DoE/CIME,_Common_Infrastructure_for_Modeling_the_Earth_v._5.0.json new file mode 100644 index 00000000..c7c476c4 --- /dev/null +++ b/agency-indexes/DoE/CIME,_Common_Infrastructure_for_Modeling_the_Earth_v._5.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "CIME is the software infrastructure for configuring, building, running, and testing an Earth system model. It can be developed and tested as stand-alone software, but its main role is to be integrating into the CESM and ACME Earth system models.", + "laborHours": 59827.2, + "languages": [ + "Python" + ], + "name": "CIME, Common Infrastructure for Modeling the Earth v. 5.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ESMCI/cime/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESMCI/cime", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CIMantic_Graphs.json b/agency-indexes/DoE/CIMantic_Graphs.json new file mode 100644 index 00000000..ac1c7e0c --- /dev/null +++ b/agency-indexes/DoE/CIMantic_Graphs.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-05-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "CIMantic Graphs (aka CIM-Graph) is a new python library developed by PNNL to reduce the burden of working with the\nCommon Information Model. CIMantic Graphs takes a novel approach of building in-memory labeled property graphs for\ncreating, parsing, and editing CIM power system models.", + "laborHours": 38729.6, + "languages": [], + "name": "CIMantic Graphs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CIM-Tools/CIM-Graph", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CIVET:_Continuous_Integration,_Verification,_Enhancement,_and_Testing.json b/agency-indexes/DoE/CIVET:_Continuous_Integration,_Verification,_Enhancement,_and_Testing.json new file mode 100644 index 00000000..67391b4e --- /dev/null +++ b/agency-indexes/DoE/CIVET:_Continuous_Integration,_Verification,_Enhancement,_and_Testing.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "A Git server (GitHub, GitLab, BitBucket) sends event notifications to the Civet server. These are either a \" Pull Request\" or a \"Push\" notification. Civet then checks the database to determine what tests need to be run and marks them as ready to run. Civet clients, running on dedicated machines, query the server for available jobs that are ready to run. When a client gets a job it executes the scripts attached to the job and report back to the server the output and exit status. When the client updates the server, the server will also update the Git server with the result of the job, as well as updating the main web page.", + "laborHours": 26615.2, + "languages": [], + "name": "CIVET: Continuous Integration, Verification, Enhancement, and Testing", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/civet", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CLIP_Representation_Enhanced_Predicate_Estimation.json b/agency-indexes/DoE/CLIP_Representation_Enhanced_Predicate_Estimation.json new file mode 100644 index 00000000..0f5a4b24 --- /dev/null +++ b/agency-indexes/DoE/CLIP_Representation_Enhanced_Predicate_Estimation.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2024-06-14" + }, + "description": "This software provides functions to perform visual predicate estimation by leveraging the pre-trained\nvision-language model CLIP. In addition to training the prediction estimator with a labeled dataset, it also\nperforms performance evaluation and visualization of results.", + "laborHours": 927.2, + "languages": [], + "name": "CLIP Representation Enhanced Predicate Estimation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CREPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CLMPI:_Clock_MPI.json b/agency-indexes/DoE/CLMPI:_Clock_MPI.json new file mode 100644 index 00000000..542f0ca9 --- /dev/null +++ b/agency-indexes/DoE/CLMPI:_Clock_MPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "CLMPI is a PMPI wrapper for piggybacking Lamport-clock.", + "laborHours": 2264.8, + "languages": [], + "name": "CLMPI: Clock MPI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PRUNERS/CLMPI", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CLOMP_TM.json b/agency-indexes/DoE/CLOMP_TM.json new file mode 100644 index 00000000..0974071a --- /dev/null +++ b/agency-indexes/DoE/CLOMP_TM.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The CLOMP_TM benchmark was developed to measure the overheads of various mechanisms used to guarantee the generation of correct results in threaded code even when multiple threads might be accessing and/or updating the same memory location at the same time. This includes widely supported mechanisms like OpenMP Atomic and Open MP Critical as well as new mechanisms like Transactional Memory (TM) and Speculative Execution (SE) of threads. The CLOMP_TM benchmark is highly configurable to allow a variety of problem sizes, atomic update region sizes, and potential race condition opportunities to be studied. A wide variety of checks are done on the results to verify the expected answer was actually generated. Thus CLOMP_TM can be used both to measure the overhead for various mechanisms and to check the correctness of their implementation.", + "laborHours": 0.0, + "languages": [], + "name": "CLOMP_TM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/clomp-tm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CLaMS:_Classifier_for_Metagenomic_Sequences.json b/agency-indexes/DoE/CLaMS:_Classifier_for_Metagenomic_Sequences.json new file mode 100644 index 00000000..0a4f7db8 --- /dev/null +++ b/agency-indexes/DoE/CLaMS:_Classifier_for_Metagenomic_Sequences.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "CLaMS-\"Classifer for Metagenonic Sequences\" is a Java application for binning assembled metagenomes wings user-specified training sequence sets and other user-specified initial parameters. Since ClAmS analyzes and matches sequence composition-based genomic signatures, it is much faster than binning tools that rely on alignments to homologs; CLaMS can bin ~20,000 sequences in 3 minutes on a laptop with a 2.4 Ghz. Intel Core 2 Duo processor and 2 GB Ram. CLaMS is meant to be desktop application for biologist and can be run on any machine under any operating system on which the Java Runtime Environment is enabled. CLaMS is freely available in both GVI-based and command-line based forms.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "JRE" + ], + "name": "CLaMS: Classifier for Metagenomic Sequences", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CM-DVR.json b/agency-indexes/DoE/CM-DVR.json new file mode 100644 index 00000000..1c97c95a --- /dev/null +++ b/agency-indexes/DoE/CM-DVR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "This program was developed to calculate rovibrational levels by solving n-dimensional potentials. The program is capable of generating the necessary grid and, once the potential energy for those coordinates has been calculated, solving it for the given dimensionality. The potential is solved using the universal Discrete Variable Representation (DVR) originally developed by Colbert and Miller [Colbert1992]. While the implementation can entertain both aperiodic and periodic potentials, the intrinsic target are soft and large-amplitude motions of non-rigid molecules. For the present purpose, non-rigid molecules are defined as those with at least one internal coordinate that undergoes a large amplitude motion [Bunker1998]. The potentials of these vibrational motions are poorly approximated with harmonic oscillators. The current implementation is in practice limited to solving 1 and 2 dimensional potentials due to the strongly scaling cost of these methods with increased dimensionality. [Colbert1992] Colbert, D. T.; Miller, W. H. A Novel Discrete Variable Representation for Quantum-Mechanical Reactive Scattering via the S-Matrix Kohn Method. J. Chem. Phys. 1992, 96, 1982\u00bf1991. http://doi.org/10.1063/1.462100 [Bunker1998] Bunker, P. R.; Jensen P. Molecular Symmetry and Spectroscopy, 2nd ed.; NRC Research Press: Ottawa 1998. .. [Colbert1992] Colbert, D. T.; Miller, W. H. A Novel Discrete Variable Representation for Quantum-Mechanical Reactive Scattering via the S-Matrix Kohn Method. J. Chem. Phys. 1992, 96, 1982\u00bf1991. http://doi.org/10.1063/1.462100 .. [Bunker] Bunker, P. R.; Jensen P. Molecular Symmetry and Spectroscopy, 2nd ed.; NRC Research Press: Ottawa 1998.", + "laborHours": 0.0, + "languages": [], + "name": "CM-DVR", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Dbross/CM_DVR", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CMEC_Module_Manager.json b/agency-indexes/DoE/CMEC_Module_Manager.json new file mode 100644 index 00000000..1e64f091 --- /dev/null +++ b/agency-indexes/DoE/CMEC_Module_Manager.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-17", + "metadataLastUpdated": "2022-03-17" + }, + "description": "The CMEC module manager package is designed install and update CMEC modules (https://cmec.llnl.gov/). CMEC modules are independent climate model analysis packages. Individual scripts are provided in the module manager that outline the installation process for each module in a robust way, and a wrapper python script is provided that lets users install a chosen CMEC package with a single command.", + "laborHours": 0.0, + "languages": [], + "name": "CMEC Module Manager", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmecmetrics/cmec-module-man", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CMEC_driver.json b/agency-indexes/DoE/CMEC_driver.json new file mode 100644 index 00000000..2d53cf46 --- /dev/null +++ b/agency-indexes/DoE/CMEC_driver.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-04-24", + "metadataLastUpdated": "2023-04-24" + }, + "description": "CMEC driver is a command line tool that runs earth system evaluation modules.", + "laborHours": 0.0, + "languages": [], + "name": "CMEC driver", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmecmetrics/cmec-driver", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.1.9" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CMLM__Co-Optimized_Machine-Learned_Manifolds__[SWR-23-41].json b/agency-indexes/DoE/CMLM__Co-Optimized_Machine-Learned_Manifolds__[SWR-23-41].json new file mode 100644 index 00000000..3e774c61 --- /dev/null +++ b/agency-indexes/DoE/CMLM__Co-Optimized_Machine-Learned_Manifolds__[SWR-23-41].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-02-26", + "metadataLastUpdated": "2024-05-08" + }, + "description": "Co-optimized Machine-Learned Manifolds (CMLM) is a data-driven approach for developing reduced-order manifold models for high-dimensional chemically reacting systems. It involves a specially designed neural network, the training of which simultaneously optimizes linear combinations of species that define the manifold, nonlinear mapping to outputs of interest such as reaction rates, and (optionally) subfilter closure for large eddy simulation. This software package provides an implementation of the CMLM approach in Python using the PyTorch machine learning library. A few example cases are included, showing how the tool can be applied to different types of data from 0D and 1D reacting simulations performed using Cantera. The neural networks can be saved in a format that is readable by the Pele suite of combustion solvers for use in reacting computational fluid dynamics simulations.\n\nThis software repository contains several python scripts to perform various tasks associated with the Co-optimized Machine Learned Manifolds (CMLM) model, which is described in Perry, Henry de Frahan, and Yellapantula, CNF, 2022 (https://doi.org/10.1016/j.combustflame.2022.112286). This includes not only the code that defines the CMLM model, but also scripts to generate suitable training data, scripts to pre-process the data, scripts to train the CMLM model, and scripts to plot the output, as well as various other helper files. The scripts depend on several commonly used python libraries for data analysis and chemical reaction computations. The trained models that result from this tool are designed to work with the an interface being implemented in the Pele suite of reacting flow solvers (https://github.com/AMReX-Combustion).", + "laborHours": 1778.4, + "languages": [ + "Python" + ], + "name": "CMLM (Co-Optimized Machine-Learned Manifolds) [SWR-23-41]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/cmlm", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CMakePP_CMakePPLang.json b/agency-indexes/DoE/CMakePP_CMakePPLang.json new file mode 100644 index 00000000..eed83d59 --- /dev/null +++ b/agency-indexes/DoE/CMakePP_CMakePPLang.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2023-09-29", + "metadataLastUpdated": "2023-09-29" + }, + "description": "CMakePPLang is an object-oriented extension to the CMake language written entirely using the original CMake language, with the goal of making projects built on CMake easier to create and maintain.", + "laborHours": 0.0, + "languages": [ + "CMake" + ], + "name": "CMakePP/CMakePPLang", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CMakePP/CMakePPLang", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CMakePP_CMinx.json b/agency-indexes/DoE/CMakePP_CMinx.json new file mode 100644 index 00000000..5994e759 --- /dev/null +++ b/agency-indexes/DoE/CMakePP_CMinx.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2022-11-15", + "metadataLastUpdated": "2022-11-15" + }, + "description": "Generates API documentation for CMake functions and macros", + "laborHours": 0.0, + "languages": [], + "name": "CMakePP/CMinx", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CMakePP/CMinx", + "status": "Development", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CNN-Encoder-Decoder_Model.json b/agency-indexes/DoE/CNN-Encoder-Decoder_Model.json new file mode 100644 index 00000000..3ea58e7f --- /dev/null +++ b/agency-indexes/DoE/CNN-Encoder-Decoder_Model.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "tkonstant@bnl.gov" + }, + "date": { + "created": "2021-07-04", + "metadataLastUpdated": "2021-07-05" + }, + "description": "Code and data for training CNN-Encoder-Decoder model described in the publication 'Noise reduction in X-ray photon correlation spectroscopy with convolutional neural networks encoder-decoder models.'", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "CNN-Encoder-Decoder Model", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bnl/CNN-Encoder-Decoder", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CO2ROpt__Feedstock_Allocation_Optimization_Model__[SWR-22-13].json b/agency-indexes/DoE/CO2ROpt__Feedstock_Allocation_Optimization_Model__[SWR-22-13].json new file mode 100644 index 00000000..b93f221c --- /dev/null +++ b/agency-indexes/DoE/CO2ROpt__Feedstock_Allocation_Optimization_Model__[SWR-22-13].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2024-07-01" + }, + "description": "Reducing greenhouse gas emissions remains a critical challenge for the transportation and chemical sectors. The electrochemical reduction of carbon dioxide is a potential pathway for production of fuels and chemicals that uses atmospheric carbon dioxide as a feedstock. Here we present an analysis of the potential for carbon dioxide captured from point sources and via direct air capture to be utilized in electrochemical reduction under different market scenarios. Using a numerical optimization framework and national data sets, scenarios for nationwide production of ethylene, formate, and carbon monoxide are evaluated at scales comparable to current production of these molecules in the United States. We show that developing a network for production of these products at scale requires capture and utilization of significant portions of the carbon dioxide that is currently emitted from large stationary point sources. Because carbon dioxide point sources are spatially and compositionally variable, their use for carbon dioxide reduction depends on electricity prices, capture cost, and location. If the power sector in the United States is decarbonized, carbon dioxide supply decreases significantly, increasing the importance of utilizing other carbon dioxide streams, and increasing the likelihood that direct air capture plays a role in supplying carbon dioxide feedstocks. These findings provide a first insight into the feedstock and energy constraints for carbon dioxide reduction.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "CO2ROpt (Feedstock Allocation Optimization Model) [SWR-22-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CO2ROpt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/COBRApyBasedFBA.json b/agency-indexes/DoE/COBRApyBasedFBA.json new file mode 100644 index 00000000..c74784cd --- /dev/null +++ b/agency-indexes/DoE/COBRApyBasedFBA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-08", + "metadataLastUpdated": "2020-09-08" + }, + "description": "Wrapper of COBRApy FBA functions in KBase replacing some functionality in the fba_tools module.", + "laborHours": 1444.0, + "languages": [], + "name": "COBRApyBasedFBA", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/COBRApyBasedFBA", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CODES__CO-DESIGN_OF_EXASCALE_STORAGE_AND_NETWORK_ARCHITECTURES.json b/agency-indexes/DoE/CODES__CO-DESIGN_OF_EXASCALE_STORAGE_AND_NETWORK_ARCHITECTURES.json new file mode 100644 index 00000000..65fda227 --- /dev/null +++ b/agency-indexes/DoE/CODES__CO-DESIGN_OF_EXASCALE_STORAGE_AND_NETWORK_ARCHITECTURES.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-06-25", + "metadataLastUpdated": "2019-06-25" + }, + "description": "The goal of the CODES project is use highly parallel simulation to explore the design of exascale \nstorage architectures and distributed data-intensive science facilities. Our simulations build upon \nthe Rensselaer Optimistic Simulation System (ROSS), a discrete event simulation framework that \nallows simulations to be run in parallel, decreasing the simulation run time of massive simulations \nto hours. We are using ROSS to explore topics including large-scale storage systems, I/O workloads, \nHPC network fabrics, distributed science systems, and data-intensive computation environments. The \nCODES project is a collaboration between the Mathematics and Computer Science department at Argonne National Laboratory and Rensselaer Polytechnic Institute. We also collaborate with Lawrence Livermore National Laboratory for modeling HPC interconnect systems", + "laborHours": 49278.4, + "languages": [], + "name": "CODES( CO-DESIGN OF EXASCALE STORAGE AND NETWORK ARCHITECTURES", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://xgitlab.cels.anl.gov/codes/codes.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/COEK.json b/agency-indexes/DoE/COEK.json new file mode 100644 index 00000000..da087209 --- /dev/null +++ b/agency-indexes/DoE/COEK.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-08-07" + }, + "description": "COEK (C++ Optimization Expression Kernel) is a C++ library that supports the expression and manipulation of algebraic expressions commonly used in optimization applications. COEK. Supports several mechanisms for defining and managing expressions and performing automatic differentiation. COEK also includes low-level interfaces for defining optimization models and interfacing with optimization solvers.SAND2019-14491 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 98070.4, + "languages": [ + "C++", + "Cmake", + "C", + "AMPL", + "NMODL", + "Python" + ], + "name": "COEK", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/coek", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/COILOPT++.json b/agency-indexes/DoE/COILOPT++.json new file mode 100644 index 00000000..f529adbb --- /dev/null +++ b/agency-indexes/DoE/COILOPT++.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jbreslau@pppl.gov" + }, + "date": { + "created": "2018-07-03", + "metadataLastUpdated": "2018-08-07" + }, + "description": "COILOPT++ is a code for designing optimal modular and saddle coils for stellarators. Given a topologically toroidal plasma equilibrium surface with a specified normal magnetic field component, one or more toroidal winding surfaces enclosing the plasma surface, and initial guesses for one or more coil shapes for each winding surface, COILOPT++ employs a variety of local and global optimization algorithms to adjust the coil shapes to best satisfy a specified set of physical and geometric constraints. Typical coil representations are cylic cubic B-splines, for which it is possible to specify that a segment of modular coil about the outboard midplane be completely vertical to improve device accessibility.", + "homepageURL": "https://theory.pppl.gov/research/research.php?rid=10#h12", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "COILOPT++", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://theory.pppl.gov/research/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://theory.pppl.gov/research/research.php?rid=10#h12", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/COMBIgor__A_data_assistant_for_combinatorial_scientists_in_Igor_Pro__[SWR-19-16].json b/agency-indexes/DoE/COMBIgor__A_data_assistant_for_combinatorial_scientists_in_Igor_Pro__[SWR-19-16].json new file mode 100644 index 00000000..0320ea53 --- /dev/null +++ b/agency-indexes/DoE/COMBIgor__A_data_assistant_for_combinatorial_scientists_in_Igor_Pro__[SWR-19-16].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-13", + "metadataLastUpdated": "2024-12-19" + }, + "description": "Combinatorial materials science experiments involve synthesis and spatially-resolved characterization of thin film sample libraries. As a result, the modern combinatorial materials science laboratory produces large, diverse, and complex data sets, requiring automation of analysis and visualization techniques. COMBIgor is a software package aimed to assist a combinatorial material scientists with large volumes of experimental data. This package, written in Igor Pro, offers a systematic approach to the loading, processing, and visualizing combinatorial data sets. COMBIgor is designed to be expanded on a laboratory, group, or individual basis to adopt additional loading, processing and visualization capabilities. By utilizing COMBIgor software package the burden of data management in combinatorial materials science experiments can be significantly reduced.", + "laborHours": 13588.8, + "languages": [], + "name": "COMBIgor (A data assistant for combinatorial scientists in Igor Pro) [SWR-19-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CombIgor", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/COMFEN.json b/agency-indexes/DoE/COMFEN.json new file mode 100644 index 00000000..559917f9 --- /dev/null +++ b/agency-indexes/DoE/COMFEN.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "COMFEN supports the systematic evaluation of alternative fenestration systems for project-specific commercial building applications. COMFEN provides simplified Excel-based user interface that focuses attention on key variables in fenestration design. Under the hood in EnergyPlus, a sophisticated analysis engine that dynamically simulate the effects of these key fenestration variables on energy consumption, peak energy demand, and thermal and visual comfort. The results from the EnergyPlus simulation are presented in graphical and tabular format within the simplified user interface for up to four comparative fenestration design cases to help users move toward optimal fenestration design choices for their project.", + "homepageURL": "https://windows.lbl.gov/software/comfen", + "laborHours": 0.0, + "languages": [], + "name": "COMFEN", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://windows.lbl.gov/software/comfen", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://windows.lbl.gov/software/comfen", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/COMMON_\342\200\223_Communications_System_Monitor_v._1.5.json" "b/agency-indexes/DoE/COMMON_\342\200\223_Communications_System_Monitor_v._1.5.json" new file mode 100644 index 00000000..0f5565c5 --- /dev/null +++ "b/agency-indexes/DoE/COMMON_\342\200\223_Communications_System_Monitor_v._1.5.json" @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-10-17", + "metadataLastUpdated": "2019-03-19" + }, + "description": "COMMON is a tool for collecting, storing, and displaying critical information to facilitate analysis on Microsoft Windows based IT systems. COMMON was developed to provide insight into the IT infrastructure for operational radiation detection systems, but is applicable to most Windows-based operating systems and TCP/IP network components. The COMMON tool aggregates a host of important Windows Management Instrumentation (WMI) information and as well as network ping responses to provide valuable insight into the performance of the IT system. A unique feature is the creation of daily output files (JSON) from the data collected for off site evaluation by subject matter experts.", + "laborHours": 43988.8, + "languages": [ + "C#", + "JavaScript", + "TypeScript" + ], + "name": "COMMON \u2013 Communications System Monitor v. 1.5", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/common", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/COMPACT.json b/agency-indexes/DoE/COMPACT.json new file mode 100644 index 00000000..8994822b --- /dev/null +++ b/agency-indexes/DoE/COMPACT.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2019-01-23", + "metadataLastUpdated": "2023-03-07" + }, + "description": "The code extrapolates the nearest neighbor particle spacing and sizing from collected X-ray images. The profiles are directly interpretable for non-destructive imaging of large imaging datasets that span the micron to millimeter size scale.", + "laborHours": 0.0, + "languages": [], + "name": "COMPACT", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/idaholabresearch-compact", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/COMPASS-DOE_PoolDilutionR.json b/agency-indexes/DoE/COMPASS-DOE_PoolDilutionR.json new file mode 100644 index 00000000..622e638a --- /dev/null +++ b/agency-indexes/DoE/COMPASS-DOE_PoolDilutionR.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-03-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Home of PoolDilutionR, a package for easily calculating gross rates from isotope pool dilution data.", + "laborHours": 0.0, + "languages": [ + "R" + ], + "name": "COMPASS-DOE/PoolDilutionR", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/COMPASS-DOE/PoolDilutionR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/COMPOSE_Version._1.0.json b/agency-indexes/DoE/COMPOSE_Version._1.0.json new file mode 100644 index 00000000..9122e88c --- /dev/null +++ b/agency-indexes/DoE/COMPOSE_Version._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-04-11", + "metadataLastUpdated": "2019-04-12" + }, + "description": "COMPOSE is scientific software to help to solve tracer transport equations, which are partial differential equations that model how chemical species move when carried by a fluid. It will be used in a future version of the open-source DOE Energy Exascale Earth System Model (E3SM) to help model the movement of chemical species in Earth\u2019s atmosphere as part of simulating the climate. In particular, COMPOSE help to implement semi-Lagrangian tracer transport and, more generally, property preserving remap of tracer fields. Logical components include Communication-Efficient Constrained Density Reconstructors (COMPOSE-CEDR) and Spherical Polygon Intersection and Quadrature with Kokkos (COMPOSE-SIQK).", + "laborHours": 3374.4, + "languages": [ + "C++" + ], + "name": "COMPOSE Version. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/COMPOSE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CONORBIT.json b/agency-indexes/DoE/CONORBIT.json new file mode 100644 index 00000000..9f936a7d --- /dev/null +++ b/agency-indexes/DoE/CONORBIT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-09-04", + "metadataLastUpdated": "2022-01-05" + }, + "description": "Software for solving nonlinear optimization problems where the objective and/or constraint functions are blackboxes.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "CONORBIT", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/COOPR:_A_COmmon_Optimization_Python_Repository_v._1.0.json b/agency-indexes/DoE/COOPR:_A_COmmon_Optimization_Python_Repository_v._1.0.json new file mode 100644 index 00000000..fbda60c9 --- /dev/null +++ b/agency-indexes/DoE/COOPR:_A_COmmon_Optimization_Python_Repository_v._1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Coopr integrates Python packages for defining optimizers, modeling optimization applications, and managing computational experiments. A major driver for Coopr development is the Pyomo package that can be used to define abstract problems, create concrete problem instances, and solve these instances with standard solvers. Other Coopr packages include EXACT, a framework for managing computational experiments, SUCASA, a tool for customizing integer programming solvers, and OPT, a generic optimization interface.", + "laborHours": 314837.6, + "name": "COOPR: A COmmon Optimization Python Repository v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pyomo/pyomo", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CORAL_Prototype_Implementation__CORAL__v0.1.json b/agency-indexes/DoE/CORAL_Prototype_Implementation__CORAL__v0.1.json new file mode 100644 index 00000000..69bda60c --- /dev/null +++ b/agency-indexes/DoE/CORAL_Prototype_Implementation__CORAL__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-25", + "metadataLastUpdated": "2021-03-30" + }, + "description": "This is prototype code that implements many of the concepts in our invention, \"The CORAL Framework for FAIR Data Management and Analysis\" (ROI 2019-123, attached). The code includes a back end module that interfaces with third party open source software (ArangoDB), and a front end user interface (UI) that allows user interaction with the software through a web interface.", + "laborHours": 0.0, + "languages": [], + "name": "CORAL Prototype Implementation (CORAL) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmchandonia/CORAL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CORE_-_Performance_Feedback_System.json b/agency-indexes/DoE/CORE_-_Performance_Feedback_System.json new file mode 100644 index 00000000..689eec0b --- /dev/null +++ b/agency-indexes/DoE/CORE_-_Performance_Feedback_System.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "CORE is an architecture to bridge the gaps between disparate data integration and delivery of disparate information visualization. The CORE Technology Program includes a suite of tools and user-centered staff that can facilitate rapid delivery of a deployable integrated information to users.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "CORE - Performance Feedback System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CORRLA-RS.json b/agency-indexes/DoE/CORRLA-RS.json new file mode 100644 index 00000000..7b6c4e57 --- /dev/null +++ b/agency-indexes/DoE/CORRLA-RS.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "gureckywl@ornl.gov" + }, + "date": { + "created": "2024-05-21", + "metadataLastUpdated": "2024-05-21" + }, + "description": "The CORRLA-RS package provides a suite of statistical methods for sampling multidimensional distributions and to conduct sensitivity and correlation analysis of large scale data in the Rust programming language. The software provides a unique solution to multidimensional constrained sampling problems utilizing a combination of parallelized Markov Chain Monte Carlo methods and traditional rejection sampling. The sensitivity and correlation analysis methods are backed by a high performance randomized singular value decomposition implementation which enables datasets larger than the random access memory (RAM) size to be analyzed. Additionally, CORRLA-RS implements the active subspace identification method using a KD-Tree and the randomized singular value decomposition acting in concert.", + "laborHours": 1824.0, + "languages": [ + "Rust" + ], + "name": "CORRLA-RS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wgurecky/CORRLA_RS", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/COSUBS.json b/agency-indexes/DoE/COSUBS.json new file mode 100644 index 00000000..82e00869 --- /dev/null +++ b/agency-indexes/DoE/COSUBS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "COSUBS (COrrelated Sampling Using Batch Statistics) reads MCNP6 output files and propagates the statistical uncertainties of various combinations of tallies using batch statistics, accounting for correlations.", + "laborHours": 0.0, + "languages": [], + "name": "COSUBS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/COSUBS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/COWALKER:EFFECTIVE_TRANSPORT_PROPERTIES_OF_COMPOSITE_MATERIALS.json b/agency-indexes/DoE/COWALKER:EFFECTIVE_TRANSPORT_PROPERTIES_OF_COMPOSITE_MATERIALS.json new file mode 100644 index 00000000..3649d06d --- /dev/null +++ b/agency-indexes/DoE/COWALKER:EFFECTIVE_TRANSPORT_PROPERTIES_OF_COMPOSITE_MATERIALS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-18" + }, + "description": "SF-23-026 This software computes effective transport properties of composite materials involving fibers and nanoparticles using a\nrandom-walk algorithm that efficiently scales to an arbitrary number of processes and cores. Effective transport\nproperties (thermal, electrical) are key to bridge the microstructure of complex materials with its macroscopic behavior.\nTraditional approaches either use effective medium approximations (closed mathematical expressions that are\napproximation for certain conditions) or continuum simulation models such as finite element or finite volume, which\nrequire the generation of a mesh for each configuration explored. cowalker leverages the equivalence between laplacian\nor heat equation-based models and random walks to compute the asymptotic transport properties from an ensemble of\nfirst sojourn times of a random walker moving through the composite material. This allows us to directly define a\ncomposite material as a collection of particles and use algorithms developed for molecular dynamics to quickly compute\nthe intersection of the walker with the different interfaces in the material. cowalker is developed in C++, and it relies on\nthe GNU Scientific Library for random generation. cowalker is currently delivered as source code, so the GSL library is\nnot included in cowalker's distribution. A more userfriendly version, cowalker.jl is currently in development and will be\nreleased as part of cowalker.\n", + "laborHours": 0.0, + "languages": [], + "name": "COWALKER:EFFECTIVE TRANSPORT PROPERTIES OF COMPOSITE MATERIALS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spikingnn/spikingtorch", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/COYOTE.json b/agency-indexes/DoE/COYOTE.json new file mode 100644 index 00000000..969e73a0 --- /dev/null +++ b/agency-indexes/DoE/COYOTE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "COYOTE is designed for the analysis of steady and transient, multi-dimensional, nonlinear heat conduction problems. The spatial discretization technique is based on the Galerkin finite element method. The code contains a library of linear and quadratic elements and incudes bars and shells. COYOTE Implicit and explicit time integration methods, with adaptive time step control, are available for transient problems and fixed-point methods are used for Conjugate gradient iterative methods are used for the matrix solution. Coupled enclosure radiation with efficient view factor computation is included. Simulation capabilities include material motion, dynamic radiation enclosures, contact boundary conditions, multipoint constraints, material (element) addition, and deletion, bulk nodes, chemically reactive materials, and coupling with other mechanics codes. The code is designed for single or multi-processor computing", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "COYOTE", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CPSW:_Common_Platform_Software.json b/agency-indexes/DoE/CPSW:_Common_Platform_Software.json new file mode 100644 index 00000000..e6e58ae2 --- /dev/null +++ b/agency-indexes/DoE/CPSW:_Common_Platform_Software.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-07", + "metadataLastUpdated": "2022-07-07" + }, + "description": "The \u201cCommon Platform Software\u201d is a package which facilitates communication with common platform firmware. It is intended to provide basic access to firmware features while hiding details of the communication protocols involved. CPSW implements abstractions for entities like registers and devices and hides low-level details such as addressing or routing information, byte-order etc.", + "laborHours": 0.0, + "languages": [], + "name": "CPSW: Common Platform Software", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/cpsw/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/cpsw", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CRISPR-CARB_Pseudomonas_putida_KT2440_GEM.json b/agency-indexes/DoE/CRISPR-CARB_Pseudomonas_putida_KT2440_GEM.json new file mode 100644 index 00000000..c6330326 --- /dev/null +++ b/agency-indexes/DoE/CRISPR-CARB_Pseudomonas_putida_KT2440_GEM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-12", + "metadataLastUpdated": "2025-03-12" + }, + "description": "P. putida KT2440 and related engineered strains.", + "laborHours": 232043.2, + "languages": [], + "name": "CRISPR-CARB/Pseudomonas_putida_KT2440_GEM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CRISPR-CARB/Pseudomonas_putida_KT2440_GEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CRISPR-CARB_Rhodobacter_sphaeroides_GEMs.json b/agency-indexes/DoE/CRISPR-CARB_Rhodobacter_sphaeroides_GEMs.json new file mode 100644 index 00000000..ec585f94 --- /dev/null +++ b/agency-indexes/DoE/CRISPR-CARB_Rhodobacter_sphaeroides_GEMs.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-14", + "metadataLastUpdated": "2025-03-14" + }, + "description": "genome-scale model of Rhodobacter sphaeroides and flux analysis", + "laborHours": 265772.0, + "languages": [], + "name": "CRISPR-CARB/Rhodobacter_sphaeroides_GEMs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CRISPR-CARB/Rhodobacter_sphaeroides_GEMs", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CRISPR-CARB_nocap.json b/agency-indexes/DoE/CRISPR-CARB_nocap.json new file mode 100644 index 00000000..b782b8d8 --- /dev/null +++ b/agency-indexes/DoE/CRISPR-CARB_nocap.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-18", + "metadataLastUpdated": "2025-02-18" + }, + "description": "Network Optimization and Causal Analysis of Perturb-seq (NOCAP) is a software package for causal inference of gene\nregulation networks using data from perturb-seq.", + "laborHours": 1003.2, + "languages": [], + "name": "CRISPR-CARB/nocap", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/crispr-carb/nocap", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CROPSR:_An_Automated_Platform_for_Complex_Genome-Wide_CRISPR_gRNA_Design_and_Validation.json b/agency-indexes/DoE/CROPSR:_An_Automated_Platform_for_Complex_Genome-Wide_CRISPR_gRNA_Design_and_Validation.json new file mode 100644 index 00000000..a533f66f --- /dev/null +++ b/agency-indexes/DoE/CROPSR:_An_Automated_Platform_for_Complex_Genome-Wide_CRISPR_gRNA_Design_and_Validation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "lensor@illinois.edu" + }, + "date": { + "created": "2024-09-18", + "metadataLastUpdated": "2024-09-19" + }, + "description": "CROPSR is a python tool designed for genome-wide gRNA design and evaluation for CRISPR experiments, with special focus on complex genomes such as those found in energy-producing crops. CROPSR is a product of the DOE Center for Advanced Bioenergy and Bioproducts Innovation (CABBI).", + "laborHours": 486.4, + "languages": [], + "name": "CROPSR: An Automated Platform for Complex Genome-Wide CRISPR gRNA Design and Validation", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/H2muller/CROPSR", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CSBCOO_SPMM:_Compressed_Sparse_Block_Coordinate_format_sparse_matrix_dense_vector_multiply_benchmark__CSBCOO_SPMM__v1.0.json b/agency-indexes/DoE/CSBCOO_SPMM:_Compressed_Sparse_Block_Coordinate_format_sparse_matrix_dense_vector_multiply_benchmark__CSBCOO_SPMM__v1.0.json new file mode 100644 index 00000000..599a9c84 --- /dev/null +++ b/agency-indexes/DoE/CSBCOO_SPMM:_Compressed_Sparse_Block_Coordinate_format_sparse_matrix_dense_vector_multiply_benchmark__CSBCOO_SPMM__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-01", + "metadataLastUpdated": "2021-03-01" + }, + "description": "The purpose of this microbenchmark is to provide a means to explore different programming methodologies using a simple, but not trivial, mathematical kernel. The kernel is based on the matrix vector product in the MFDn nuclear configuration interaction code's LOBPCG eigensolver. This particular mathematical operation is a key element in the solution of systems of equations and block eigensolvers.", + "laborHours": 0.0, + "languages": [], + "name": "CSBCOO SPMM: Compressed Sparse Block Coordinate format sparse matrix dense vector multiply benchmark (CSBCOO SPMM) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/nersc-proxies/csbcoo-spmm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CSG-public.json b/agency-indexes/DoE/CSG-public.json new file mode 100644 index 00000000..fd731055 --- /dev/null +++ b/agency-indexes/DoE/CSG-public.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-13", + "metadataLastUpdated": "2019-10-23" + }, + "description": "The Connected and Automated Vehicles Scenario Generation (CSG) model is a system dynamics model. It was built by NREL and funded by the U.S. Department of Energy under the Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility initiative. The purpose of the model is to simulate the \u201ctransitions from predominantly individual ownership of non-CAVs to various future scenarios of high connectivity/automation\u201d(Bush, Vimmerstedt, and Gonder 2019).", + "laborHours": 30.4, + "languages": [ + " STELLA Professional 1.9.1. " + ], + "name": "CSG-public", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CSG-public", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CSPlib.json b/agency-indexes/DoE/CSPlib.json new file mode 100644 index 00000000..b72d135f --- /dev/null +++ b/agency-indexes/DoE/CSPlib.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-09-30", + "metadataLastUpdated": "2021-09-30" + }, + "description": "This computational singular perturbation library (CSPlib) software is useful for analysis of chemical kinetic systems. The code is used to analyze and describe the dynamical landscape underlying the time evolution of a chemical system. Given a database of state vectors, it allows the analysis of the source term and Jacobian matrix of the chemical system, the identification and decoupling of fast and slow processes, and the analysis of cause-and-effect relationships in the coupled system dynamics. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-2391 O", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "CSPlib", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CSPlib", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CSV_to_ISO_XML_metadata_transformation_tool.json b/agency-indexes/DoE/CSV_to_ISO_XML_metadata_transformation_tool.json new file mode 100644 index 00000000..5f8c924f --- /dev/null +++ b/agency-indexes/DoE/CSV_to_ISO_XML_metadata_transformation_tool.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Django app for converting CSV records to XML metadata documents. This transformation from the metadata content model to parsed ISO XML documents allows for metadata integration into NGDS.", + "laborHours": 45.6, + "name": "CSV to ISO XML metadata transformation tool", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/usgincsv/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/usgincsv", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CSlib,_a_library_to_couple_codes_via_Client_Server_messaging.json b/agency-indexes/DoE/CSlib,_a_library_to_couple_codes_via_Client_Server_messaging.json new file mode 100644 index 00000000..88006052 --- /dev/null +++ b/agency-indexes/DoE/CSlib,_a_library_to_couple_codes_via_Client_Server_messaging.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The CSlib is a small, portable library which enables two (or more) independent simulation codes to be coupled, by exchanging messages with each other. Both codes link to the library when they are built, and can them communicate with each other as they run. The messages contain data or instructions that the two codes send back-and-forth to each other. The messaging can take place via files, sockets, or MPI. The latter is a standard distributed-memory message-passing library.", + "laborHours": 4240.8, + "languages": [ + "The CSlib can be used from programs written in C++, C, Fortran, or Python. The library itself is wr", + "Shell", + "Makefile" + ], + "name": "CSlib, a library to couple codes via Client/Server messaging", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://cslib.sandia.gov/open_source.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cslib", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CT_SEGNET:_AOMATED_3D_SEGMENTATION_WITH_DEEP_LEARNING.json b/agency-indexes/DoE/CT_SEGNET:_AOMATED_3D_SEGMENTATION_WITH_DEEP_LEARNING.json new file mode 100644 index 00000000..91b7481d --- /dev/null +++ b/agency-indexes/DoE/CT_SEGNET:_AOMATED_3D_SEGMENTATION_WITH_DEEP_LEARNING.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-09-24", + "metadataLastUpdated": "2020-09-24" + }, + "description": "This python toolkit has been developed to automate 3D segmentation of X-ray Computed Tomography (CT) data using convolutional neural networks - an AI methodology. Specifically, it binarizes CT scans with a focus on accurate surfaced Determination, with applications including but not limited to metrology of metallic components, surface characterization of manufactured components and porosity measurements in opaque media. In addition, subroutines for training with\nnew manually annotated data, including data augmentation methods have been provided. The toolkit operates on any arbitrarily sized CT volumes and is tested on up to sizes 3000^3 on a desktop workstation. In principle, this algorithm is scalable to larger CT volumes on GPU clusters. Briefly, the 3D segmentation algorithm is powered by a 2D convolutional\nneural network (CNN) and systematically slices, patches 3D data and feeds into the CNN. At the output end, the data is stitched back into a 3D segmented volume which is exactly aligned with the input volume. The 2D architecture offers\nlower GPU memory requirement while maintaining accuracy, which has been characterized on high-resolution CT scans\nof fuel injector nozzles. The package is built on top of TensorFlow / Keras and exploits CUDA-based GPU computing for\nthe CNN path and parallelization over CPU for the 2D-3D image processing operations.\n(", + "laborHours": 1793.6, + "languages": [], + "name": "CT SEGNET: AOMATED 3D SEGMENTATION WITH DEEP LEARNING", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aniketkt/CTSegNet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CTrilinos_v_1.0.json b/agency-indexes/DoE/CTrilinos_v_1.0.json new file mode 100644 index 00000000..9cc22a05 --- /dev/null +++ b/agency-indexes/DoE/CTrilinos_v_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CTrilinos provides a C language interface to a subset of Trilinos. The interface hides the object-oriented nature of Trilinos by allowing these objects to be acted upon using a set of three integers that uniquely identify the object. No pointers to the underlying objects are made available for direct manipulation, protecting against segmentation faults. CTrilinos serves as a base layer over which the ForTrilinos linking layer operates, facilitating the use Trilinos from object-oriented Fortran.CTrilinos can be applied wherever the supported underlying Trilinos packages can be applied.", + "laborHours": 18164.0, + "name": "CTrilinos v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/CTrilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CUDAMicroBench.json b/agency-indexes/DoE/CUDAMicroBench.json new file mode 100644 index 00000000..2e4c8f0a --- /dev/null +++ b/agency-indexes/DoE/CUDAMicroBench.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "CUDAMicroBench is a collection of fourteen microbenchmarks that demonstrate performance challenges in CUDA programming and techniques to optimize the CUDA programs to address these challenges. It also includes examples and techniques for using advanced CUDA features such as data shuffling between threads, dynamic parallelism, etc that can help users optimize the CUDA program for performance.", + "laborHours": 0.0, + "languages": [], + "name": "CUDAMicroBench", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CUDAMicroBench", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CUDA_Enabled_Graph_Subset_Examiner.json b/agency-indexes/DoE/CUDA_Enabled_Graph_Subset_Examiner.json new file mode 100644 index 00000000..4e783f8a --- /dev/null +++ b/agency-indexes/DoE/CUDA_Enabled_Graph_Subset_Examiner.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Finding Godsil-McKay switching sets in graphs is one way to demonstrate that a specific graph is not determined by its spectrum--the eigenvalues of its adjacency matrix. An important area of active research in pure mathematics is determining which graphs are determined by their spectra, i.e. when the spectrum of the adjacency matrix uniquely determines the underlying graph. We are interested in exploring the spectra of graphs in the Johnson scheme and specifically seek to determine which of these graphs are determined by their spectra. Given a graph G, a Godsil-McKay switching set is an induced subgraph H on 2k vertices with the following properties: I) H is regular, ii) every vertex in G/H is adjacent to either 0, k, or 2k vertices of H, and iii) at least one vertex in G/H is adjacent to k vertices in H. The software package examines each subset of a user specified size to determine whether or not it satisfies those 3 conditions. The software makes use of the massive parallel processing power of CUDA enabled GPUs. It also exploits the vertex transitivity of graphs in the Johnson scheme by reasoning that if G has a Godsil-McKay switching set, then it has a switching set which includes vertex 1. While the code (in its current state) is tuned to this specific problem, the method of examining each induced subgraph of G can be easily re-written to check for any user specified conditions on the subgraphs and can therefore be used much more broadly.", + "laborHours": 106.4, + "name": "CUDA Enabled Graph Subset Examiner", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jtjohnston/computational_combinatorics/blob/master/GM-switching/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jtjohnston/computational_combinatorics", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CVLIB-D.json b/agency-indexes/DoE/CVLIB-D.json new file mode 100644 index 00000000..91622510 --- /dev/null +++ b/agency-indexes/DoE/CVLIB-D.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "CVLIB-D is a javascript framework to facilitate the creation of viewer applications for Spec-D Advanced Cinema Databases.\n\nBecause of the wide variety of data that Spec-D can represent, viewers for Spec-D databases often have to be custom-built for viewing a specific kind of data. This CVLIB-D is a not a viewer itself, but a library which handles the connection between Sources, Displays and Input/Output Structures as outlined in the databases JSON file to allow for the very easy creation of highly-customizable viewer applications.", + "laborHours": 988.0, + "languages": [], + "name": "CVLIB-D", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cvlibd/blob/master/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cvlibd", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CVLIB_-_Cinema_Viewer_Library.json b/agency-indexes/DoE/CVLIB_-_Cinema_Viewer_Library.json new file mode 100644 index 00000000..a537a539 --- /dev/null +++ b/agency-indexes/DoE/CVLIB_-_Cinema_Viewer_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "CVLIB is a library which provides a JavaScript API to Paraview Cinema databases for visualization in the Browser.\n\nIn contrast to other Cinema viewers this library is focusing on modular expandability. Most applications have additional viewer requirements such as specialized data visualizations, aggregations, interactions, and other features a generic all-in-one viewer can not provide. Hence, CVLIB provides functions to access Cinema databases, process queries, create viewer UI elements, render results, and interact with the visualization so that users can build their own custom viewer.", + "laborHours": 10366.4, + "languages": [], + "name": "CVLIB - Cinema Viewer Library", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cvlib/blob/master/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cvlib", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CYME_Model_Data_Extractor.json b/agency-indexes/DoE/CYME_Model_Data_Extractor.json new file mode 100644 index 00000000..01170721 --- /dev/null +++ b/agency-indexes/DoE/CYME_Model_Data_Extractor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-14", + "metadataLastUpdated": "2022-09-14" + }, + "description": "Extract a CYME MDB file to its constituent tables in CSV format.", + "laborHours": 0.0, + "languages": [], + "name": "CYME Model Data Extractor", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/cyme-extract-pypi", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/C_version_of_mpibind.json b/agency-indexes/DoE/C_version_of_mpibind.json new file mode 100644 index 00000000..d8bd84a3 --- /dev/null +++ b/agency-indexes/DoE/C_version_of_mpibind.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "C version of mpibind, an algorithm to map MPI tasks, threads, and GPU kernels to the hardware.", + "laborHours": 4468.8, + "languages": [], + "name": "C version of mpibind", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ac-mpibind", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cabana.json b/agency-indexes/DoE/Cabana.json new file mode 100644 index 00000000..8bc690ac --- /dev/null +++ b/agency-indexes/DoE/Cabana.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Physics simulations that use particles in their algorithms are ubiquitous on modern high performance computers. Cabana is a C++ library for developing particle-based simulations on heterogeneous high performance computing platforms. Cabana provides general data structures and algorithms for common particle operations in a way that is both performant and portable on HPC systems. This includes particle data structure allocatable and configurable on GPU and CPU architectures, and threaded and distributed algorithms for sorting particles, halo exchanges, neighbor list generation, and other basic particle operations.", + "laborHours": 32528.0, + "languages": [ + "C++/clang,GCC,Intel,NVCC" + ], + "name": "Cabana", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-copa/Cabana", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CabanaPD.json b/agency-indexes/DoE/CabanaPD.json new file mode 100644 index 00000000..b4a36dde --- /dev/null +++ b/agency-indexes/DoE/CabanaPD.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "reevest@ornl.gov" + }, + "date": { + "created": "2022-08-23", + "metadataLastUpdated": "2022-09-16" + }, + "description": "CabanaPD is a meshfree peridynamics application built with Cabana and Kokkos. Kokkos enables performance portability across hardware architectures and Cabana provides particle capabilities including multi-node MPI support. The main components of CabanaPD are particle initialization, neighbor list generation, force and energy computation, time integration, and multi-node particle communication. In addition, options for creating pre-cracked regions and particle boundary conditions are available. CabanaPD currently enables two common force models: prototype microelastic brittle (PMB) and linear peridynamic solid (LPS). For both of these models, versions with and without fracture as well as linearized model options are available. CabanaPD is designed to be extensible for addition of more complex force models, boundary conditions, etc.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "CabanaPD", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/CabanaPD", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CabanaPF.json b/agency-indexes/DoE/CabanaPF.json new file mode 100644 index 00000000..5543fecd --- /dev/null +++ b/agency-indexes/DoE/CabanaPF.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "reevest@ornl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "Phase-field framework built on the Cabana particle library", + "laborHours": 0.0, + "languages": [], + "name": "CabanaPF", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/CabanaPF", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Caffe_Standardized_Self-Supervised_Scripts__CSSSS_.json b/agency-indexes/DoE/Caffe_Standardized_Self-Supervised_Scripts__CSSSS_.json new file mode 100644 index 00000000..2b871358 --- /dev/null +++ b/agency-indexes/DoE/Caffe_Standardized_Self-Supervised_Scripts__CSSSS_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-28", + "metadataLastUpdated": "2018-03-28" + }, + "description": "The program is a set of python scripts which extends the open source\nprogram Caffc lo allow it to learn to train a neuml network using self -supervised training. ", + "laborHours": 501.6, + "name": "Caffe Standardized Self-Supervised Scripts (CSSSS)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/selfsupervised", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Caffeine_v0.1.0.json b/agency-indexes/DoE/Caffeine_v0.1.0.json new file mode 100644 index 00000000..01fcad93 --- /dev/null +++ b/agency-indexes/DoE/Caffeine_v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "Caffeine is the CoArray Fortran Framework of Efficient Interfaces to Network Environments. Caffeine aims to produce a parallel runtime library that will support Fortran compilers with a programming-model-agnostic application binary interface (ABI) to various lower-level communication libraries. The current version of Caffeine uses the GASNet-EX networking middleware, also developed at Berkeley Lab. On many combinations of applications and platforms, GASNet-EX outperforms the widely used Message Passing Interface (MPI). Through GASNet-EX's support for communicating between graphics processing units (GPU), GASNet-EX has features that specifically target the emerging, leading-edge exascale computing platforms.", + "laborHours": 0.0, + "languages": [], + "name": "Caffeine v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/berkeleylab/caffeine", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Caldera_Grid.json b/agency-indexes/DoE/Caldera_Grid.json new file mode 100644 index 00000000..3bcffa91 --- /dev/null +++ b/agency-indexes/DoE/Caldera_Grid.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-01-03", + "metadataLastUpdated": "2023-05-17" + }, + "description": "Caldera Grid is part of Caldera software platform, a suite of collective, open-source tools that was developed to improve the state of the art in modeling the impacts of Electric Vehicle (EV) charging on the grid. Caldera Grid is a co-simulation framework implemented using Hierarchical Engine for Large scale Infrastructure Co-Simulation (HELICS). The framework facilitates the co-simulation of EV charging and Smart Charge Management (SCM) strategies in Caldera Infrastructure Charge Model (ICM) with distribution level grid models in OpenDSS. Vehicle energy needs and charge session requirements generated using Caldera Charge Decision Module (CDM) are fed in as input to Caldera Grid. The EV charging models in Caldera ICM simulates both the uncontrolled charging loads as well as loads modified by the SCM strategies to develop distributed load profiles for each grid node hosting an Electric Vehicle Supply Equipment (EVSE) \u2013 also known as chargers. These loads were simulated in OpenDSS alongside existing distribution feeder loads. Each of these models are co-simulated in a HELICS federate. The HELICS co-simulation framework facilitates communication and synchronization between the federates. By co-simulating EV loads and distribution feeder loads, Caldera Grid can assess the potential grid impacts of EV charging on distribution feeders under various grid conditions. A control strategy federate is implemented with an interface where control strategies based on feedback from EV charging status and grid conditions can be developed and implemented. The platform can also support multiple control strategies in a single co-simulation.", + "laborHours": 0.0, + "languages": [], + "name": "Caldera_Grid", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Caldera_Grid", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Caldera_Infrastructure_Charge_Module__ICM_.json b/agency-indexes/DoE/Caldera_Infrastructure_Charge_Module__ICM_.json new file mode 100644 index 00000000..2fd20afc --- /dev/null +++ b/agency-indexes/DoE/Caldera_Infrastructure_Charge_Module__ICM_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-01-03", + "metadataLastUpdated": "2023-05-17" + }, + "description": "Caldera ICM is part of Caldera software platform, a suite of collective, open-source tools that was developed to improve the state of the art in modeling the impacts of Electric Vehicle (EV) charging on the grid. The foundation of Caldera ICM is it\u2019s first-of-its-kind library of high-fidelity charging models for a wide variety of vehicles, validated by test data under a range of operating conditions. The charging models are used to accurately model the EV charging on an electric vehicle supply equipment (EVSE) \u2013 also known as a charger. ICM uses as inputs, the EV characteristics such as battery size, battery chemistry (i.e. NMC, LTO), watt hour per mile, inverter efficiency and max charge rate; as well as EVSE characteristics such as max current and supply equipment type (i.e. L2 vs XFC). Using these inputs Caldera ICM creates an uncontrolled charging profile curve for each compatible EV-EVSE pair. These charge profiles can be used stand alone to estimate charge duration given start State Of Charge (SOC) and end SOC or charge energy size given start SOC and charge duration. In Caldera Grid, another tool in the Caldera software platform, these charge profiles are used to represent EV charging as a load on the grid using charge event data such as EV type, SE type, start SOC, final SOC, park start time and park end time. ICM currently supports energy shifting Smart Charge Management (SCM) strategies such as \"Time Of Use (TOU) immediate\u201d, \u201cTOU random\u201d and \u201crandom start\u201d by delaying the charge to start at a preferable time with respect to the strategy and, one voltage support SCM strategy named autonomous voltage control strategy by providing reactive power back to the electric grid.", + "laborHours": 0.0, + "languages": [], + "name": "Caldera Infrastructure Charge Module (ICM)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Caldera_ICM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Calibr8_v.1.0.json b/agency-indexes/DoE/Calibr8_v.1.0.json new file mode 100644 index 00000000..3bcce45c --- /dev/null +++ b/agency-indexes/DoE/Calibr8_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2021-08-30" + }, + "description": "Calibr8 provides an application to rapidly prototype and perform material model calibration for complex plasticity models using advanced adjoint or forward sensitivity analyses for execution on massively parallel machines. These techniques can be orders of magnitude faster than traditional finite difference approaches for material model calibration. The underlying technology used in Calibr8 is automatic differentiation, which allows for the rapid implementation and testing of new plasticity models within its framework. Additionally, Calibr8 can perform adjoint-based error estimation to approximate discretization errors for user-implemented plasticity models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10630 O", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Calibr8 v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/calibr8", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/California_Load_Flexibility_Research_and_Development_Hub__CalFlexhub__v0.1.json b/agency-indexes/DoE/California_Load_Flexibility_Research_and_Development_Hub__CalFlexhub__v0.1.json new file mode 100644 index 00000000..102f0667 --- /dev/null +++ b/agency-indexes/DoE/California_Load_Flexibility_Research_and_Development_Hub__CalFlexhub__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-17" + }, + "description": "This repository will host the software, data models and documentation developed as part of the California Energy Commission (CEC) funded California Load Flexibility Research and Development Hub (CalFlexHub) project. The main objectives of CalFlexHub are:\n- Identify, develop, evaluate, demonstrate and deploy cost-effective, scalable, building load-flexible (LF) technologies that are consistent with building energy efficiency, appliance, and load management standards.\n- Create a portfolio of LF RDD&D technology projects across various building types and sizes including single-family-residential, multi-family, commercial buildings and integrated campuses.\n- Deploy LF technologies to demonstrate the ability for 99% of the state's customers to receive the load management standards price and marginal GHG signals.", + "laborHours": 60.8, + "languages": [], + "name": "California Load Flexibility Research and Development Hub (CalFlexhub) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/CalFlexHub", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/California_Natural_and_Working_Lands_Carbon_and_Greenhouse_Gas_Model__CALAND__v3.0.0.json b/agency-indexes/DoE/California_Natural_and_Working_Lands_Carbon_and_Greenhouse_Gas_Model__CALAND__v3.0.0.json new file mode 100644 index 00000000..a70fcede --- /dev/null +++ b/agency-indexes/DoE/California_Natural_and_Working_Lands_Carbon_and_Greenhouse_Gas_Model__CALAND__v3.0.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-01", + "metadataLastUpdated": "2021-03-01" + }, + "description": "CALAND is a system of algorithms (.r files) and data developed to quantify the impacts of various suites of California State-supported land use and land management strategies on landscape carbon and greenhouse gas emissions (CO2, CH4, and optional black carbon) relative to a baseline scenario for the Draft California 2030 Natural and Working Lands Climate Change Implementation Plan (2019).", + "laborHours": 0.0, + "languages": [], + "name": "California Natural and Working Lands Carbon and Greenhouse Gas Model (CALAND) v3.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aldivi/caland", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v3.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Caliper_Compiler_Suite.json b/agency-indexes/DoE/Caliper_Compiler_Suite.json new file mode 100644 index 00000000..f2cd1ff0 --- /dev/null +++ b/agency-indexes/DoE/Caliper_Compiler_Suite.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "This is an alpha release of a set of compiler tools that lives alongside Caliper.", + "laborHours": 456.0, + "languages": [], + "name": "Caliper Compiler Suite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/caliper-compiler", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Caliper_Context_Annotation_Library.json b/agency-indexes/DoE/Caliper_Context_Annotation_Library.json new file mode 100644 index 00000000..4bbfd0a4 --- /dev/null +++ b/agency-indexes/DoE/Caliper_Context_Annotation_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "To understand the performance of parallel programs, developers need to be able to relate performance measurement data with context information, such as the call path / line numbers or iteration numbers where measurements were taken. Caliper provides a generic way to specify and collect multi-dimensional context information across the software stack, and provide ti to third-party measurement tools or write it into a file or database in the form of context streams.", + "laborHours": 35096.8, + "languages": [], + "name": "Caliper Context Annotation Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/Caliper/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Caliper", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CallFlow.json b/agency-indexes/DoE/CallFlow.json new file mode 100644 index 00000000..43603836 --- /dev/null +++ b/agency-indexes/DoE/CallFlow.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "CallFlow Is a visualization tool to view and analyze Calling Context Tree (CCT) data provided by HPCToolkit.", + "laborHours": 25870.4, + "languages": [ + "D3, JavaScript" + ], + "name": "CallFlow", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/LLNL/CallFlow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Callpath_Library.json b/agency-indexes/DoE/Callpath_Library.json new file mode 100644 index 00000000..d30370ed --- /dev/null +++ b/agency-indexes/DoE/Callpath_Library.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The \"Callpath Library\" is a software abstraction layer over a number of stack tracing utilities. It allows tool develoopers to conveniently represent and mNipulate call paths gathered fro U. Wisconsin's Stackwalker API and GNU Backtrace.", + "laborHours": 699.2, + "name": "Callpath Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/callpath", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Caltalyst_Layer_Crack_Detector,_or_CLCD__\"clicked\"__[SWR-20-60].json" "b/agency-indexes/DoE/Caltalyst_Layer_Crack_Detector,_or_CLCD__\"clicked\"__[SWR-20-60].json" new file mode 100644 index 00000000..e67fa4c4 --- /dev/null +++ "b/agency-indexes/DoE/Caltalyst_Layer_Crack_Detector,_or_CLCD__\"clicked\"__[SWR-20-60].json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-10-04", + "metadataLastUpdated": "2024-01-25" + }, + "description": "The Caltalyst Layer Crack Detector, or CLCD (\"clicked\") is a program that takes in optical micrographs of catalyst coatings for PEM fuel cells or electrolyzers and calculates the percent area that consist of cracks. It does so using a custom algorithm that searches for dark features larger than the background graininess of the catalyst layer.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Caltalyst Layer Crack Detector, or CLCD (\"clicked\") [SWR-20-60]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Caltalyst-Layer-Crack-Detector-CLCD", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cambio.json b/agency-indexes/DoE/Cambio.json new file mode 100644 index 00000000..3cf920d2 --- /dev/null +++ b/agency-indexes/DoE/Cambio.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Cambio opens data files from common gamma radiation detectors, displays a visual representation of it, and allows the user to edit the meta-data, as well as convert the data to a different file format.", + "laborHours": 0.0, + "languages": [ + "Requires C++03 compliant compiler" + ], + "name": "Cambio", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cambio", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CameraLink_Gateway.json b/agency-indexes/DoE/CameraLink_Gateway.json new file mode 100644 index 00000000..01691658 --- /dev/null +++ b/agency-indexes/DoE/CameraLink_Gateway.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-26", + "metadataLastUpdated": "2022-07-26" + }, + "description": "This is the repository for \"CameraLink Gateway\" developed by SLAC National Accelerator Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "CameraLink Gateway", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/cameralink-gateway/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/cameralink-gateway", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Campus_Energy_Model_for_Control_and_Performance_Validation_[SWR-15-13].json b/agency-indexes/DoE/Campus_Energy_Model_for_Control_and_Performance_Validation_[SWR-15-13].json new file mode 100644 index 00000000..064bd8c0 --- /dev/null +++ b/agency-indexes/DoE/Campus_Energy_Model_for_Control_and_Performance_Validation_[SWR-15-13].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-01-25" + }, + "description": "The core of the modeling platform is an extensible block library for the MATLAB/Simulink software suite. The platform enables true co-simulation (interaction at each simulation time step) with NREL's state-of-the-art modeling tools and other energy modeling software.", + "laborHours": 3024.8, + "languages": [], + "name": "Campus Energy Model for Control and Performance Validation [SWR-15-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CampusEnergyModeling", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Campus_Energy_Modeling__2015__[SWR-15-13].json b/agency-indexes/DoE/Campus_Energy_Modeling__2015__[SWR-15-13].json new file mode 100644 index 00000000..bac1a22b --- /dev/null +++ b/agency-indexes/DoE/Campus_Energy_Modeling__2015__[SWR-15-13].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-01-25", + "metadataLastUpdated": "2024-01-25" + }, + "description": "NREL's Campus Energy Modeling project provides a suite of simulation tools for integrated, data driven energy modeling of commercial buildings and campuses using Simulink. The tools enable development of fully interconnected models for commercial campus energy infrastructure, including electrical distribution systems, district heating and cooling, onsite generation (both conventional and renewable), building loads, energy storage, and control systems.", + "laborHours": 3024.8, + "languages": [ + "Java", + "MATLAB", + "HTML" + ], + "name": "Campus Energy Modeling (2015) [SWR-15-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CampusEnergyModeling", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.2.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CanTrilBat.json b/agency-indexes/DoE/CanTrilBat.json new file mode 100644 index 00000000..4597629d --- /dev/null +++ b/agency-indexes/DoE/CanTrilBat.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "This application can determine the performance and chemical behavior of batteries in 1D when they are cycled. With CanTrilBat, we are developing predictive phenomenological models for battery systems to predict operating performance and rate limiting steps in the performance of battery models. Particular attention is paid to primary and secondary chemistry mechanisms, such as the thermal runaway mechanisms experienced in secondary lithium ion batteries or self-discharge reaction mechanism that all batteries experience to one extent or another. The first application of this model has been for modeling the performance of thermal batteries. However, an implementation for secondary ion batteries is next. CanTrilBat applications solves transient problems involving batteries. It is a 1-D application that represents 3-D physical systems that can be reduced using the porous flow approximation for the anode, cathode, and separator. A control volume formulation is used to track conserved quantities. An operator-split approach is used to calculate the chemistry, diffusion and electronic transport that occurs within cathode and anode particles, allowing for the reduction in code complexity.", + "laborHours": 6177492.8, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "M4", + "Fortran" + ], + "name": "CanTrilBat", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cantrilbat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CanTrilBat_and_Cantera_apps_v1.0_beta.json b/agency-indexes/DoE/CanTrilBat_and_Cantera_apps_v1.0_beta.json new file mode 100644 index 00000000..5cf9435d --- /dev/null +++ b/agency-indexes/DoE/CanTrilBat_and_Cantera_apps_v1.0_beta.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This application can determine the performance and chemical behavior of batteries in 1D when they are cycled. With CanTrilBat, we are developing predictive phenomenological models for battery systems to predict operating performance and rate limiting steps in the performance of battery models. Particular attention is paid to primary and secondary chemistry mechanisms, such as the thermal runaway mechanisms experienced in secondary lithium ion batteries or self-discharge reaction mechanism that all batteries experience to one extent or another. The first application of this model has been for modeling the performance of thermal batteries. However, an implementation for secondary ion batteries is next. CanTrilBat applications solves transient problems involving batteries. It is a 1-D application that represents 3-D physical systems that can be reduced using the porous flow approximation for the anode, cathode, and separator. A control volume formulation is used to track conserved quantities. An operator-split approach is used to calculate the chemistry, diffusion and electronic transport that occurs within cathode and anode particles, allowing for the reduction in code complexity. All jacobian operations in CanTrilBat utilize numerical jacobians. A home grown predictor corrector scheme is used for time step control, and a home grown newton solver is used to relax the equations at each time step. Trilinos is used to solve for the resulting linear systems equation A block text input format is used to initialize options for the CanTriBat program. Within this block are the names of several XML input files, which specify the chemistry mechanism. These XML input files are read by low level Cantera routines, and serve to initialize the electrode and electrolyte chemistry mechanisms and transport properties. A GUI implementation has been contracted out to a university professor, but has not been implemented yet. It?s expected that CanTriBat will have the capability to do adaptive grid refinement in later versions. Grids will be halved based on an complicated set of heuristic criteria, based on how well the mesh captures changes to the first and second derivatives of selected solution components. Primary emphasis is given towards converged profiles for IV performance.", + "laborHours": 6177492.8, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "M4", + "Fortran" + ], + "name": "CanTrilBat and Cantera_apps v1.0 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cantrilbat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Canonical_and_Noncanonical_Hamiltonian_Operator_Inference.json b/agency-indexes/DoE/Canonical_and_Noncanonical_Hamiltonian_Operator_Inference.json new file mode 100644 index 00000000..4c420604 --- /dev/null +++ b/agency-indexes/DoE/Canonical_and_Noncanonical_Hamiltonian_Operator_Inference.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-17", + "metadataLastUpdated": "2024-11-04" + }, + "description": "SAND2024-08577O\nCanonical and Noncanonical Hamiltonian Operator Inference is research code that applies old and new model reduction algorithms to well-known and publicly available \"toy\" problems. It applies operator inference (OpInf) methods for model reduction to several benchmark hyperbolic partial differential equations: linear wave, Korteweg-de Vries, Benjamin-Bona-Mahoney, and linear elasticity.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 576171.2, + "languages": [ + "Python 3.8" + ], + "name": "Canonical and Noncanonical Hamiltonian Operator Inference", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HamiltonianOpInf", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cantera_and_Cantera_Electrolyte_Thermodynamics_Objects.json b/agency-indexes/DoE/Cantera_and_Cantera_Electrolyte_Thermodynamics_Objects.json new file mode 100644 index 00000000..5bc1f4c3 --- /dev/null +++ b/agency-indexes/DoE/Cantera_and_Cantera_Electrolyte_Thermodynamics_Objects.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Cantera is a suite of object-oriented software tools for problems involving chemical kinetics, thermodynamics, and/or transport processes. It is a multi-organizational effort to create and formulate high quality 0D and 1D constitutive modeling tools for reactive transport codes.Institutions involved with the effort include Sandia, MIT, Colorado School of Mines, U. Texas, NASA, and Oak Ridge National Labs. Specific to Sandia's contributions, the Cantera Electrolyte Thermo Objects (CETO) packages is comprised of add-on routines for Cantera that handle electrolyte thermochemistry and reactions within the overall Cantera package. Cantera is a C++ Cal Tech code that handles gas phase species transport, reaction, and thermodynamics. With this addition, Cantera can be extended to handle problems involving liquid phase reactions and transport in electrolyte systems, and phase equilibrium problemsinvolving concentrated electrolytes and gas/solid phases. A full treatment of molten salt thermodynamics and transport has also been implemented in CETO. The routines themselves consist of .cpp and .h files containing C++ objects that are derived from parent Cantera objects representing thermodynamic functions. They are linked unto the main Cantera libraries when requested by the user. As an addendum to the main thermodynamics objects, several utility applications are provided. The first is multiphase Gibbs free energy minimizer based on the vcs algorithm, called vcs_cantera. This code allows for the calculation of thermodynamic equilibrium in multiple phases at constant temperature and pressure. Note, a similar code capability exists already in Cantera. This version follows the same algorithm, but gas a different code-base starting point, and is used as a research tool for algorithm development. The second program, cttables, prints out tables of thermodynamic and kinetic information for thermodynamic and kinetic objects within Cantera. This program serves as a \"Get the numbers out\" utility for Cantera, and as such it is very useful as a verification tool. These add-on utilities are encapsulated into a directory structure named cantera_apps, whose installation uses autoconf and also utilizes Cantera's application environment (i.e., they utilize Cantera as a library).", + "laborHours": 97432.0, + "name": "Cantera and Cantera Electrolyte Thermodynamics Objects", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Cantera/cantera", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cap.json b/agency-indexes/DoE/Cap.json new file mode 100644 index 00000000..f5258324 --- /dev/null +++ b/agency-indexes/DoE/Cap.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "Identification of core annotation pipeline (CAP). The repository for workflow development to integrate in-house workflows into KBase. These scripts integrate assemblies, abundances, and annotations into a Phyloseq object, specifically genes which are core among multiple metagenomes.", + "laborHours": 136.8, + "languages": [], + "name": "CAP", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/cap", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Capacitor.json b/agency-indexes/DoE/Capacitor.json new file mode 100644 index 00000000..f7ef7a88 --- /dev/null +++ b/agency-indexes/DoE/Capacitor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Capacitor implements an aggregate job launcher and manager for\u00a0flux, offering features similar to those provided by job arrays or tools like\u00a0CRAM.", + "laborHours": 1428.8, + "languages": [], + "name": "Capacitor", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/flux-framework/capacitor", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CaptureFOAM.json b/agency-indexes/DoE/CaptureFOAM.json new file mode 100644 index 00000000..868ca7cd --- /dev/null +++ b/agency-indexes/DoE/CaptureFOAM.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "kincaidkc@ornl.gov" + }, + "date": { + "created": "2025-04-21", + "metadataLastUpdated": "2025-04-21" + }, + "description": "CaptureFOAM provides utilities for fast and accurate direct air capture (DAC) contactor simulations, based on the OpenFOAM framework. At the core, CaptureFOAM is a suite of mass transfer and chemistry models built upon the OpenFOAM thin film model, which allows coarser mesh resolution and less constrictive time step requirements when compared to a traditional volume of fluid approach. This allows CaptureFOAM to conduct device-scale simulations for complex geometries including commercial packing materials and novel contactor shapes, matching experimental results in a wide variety of applications.", + "laborHours": 1200.8, + "languages": [ + "C++" + ], + "name": "CaptureFOAM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/CaptureFOAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Carbon_Dioxide_Fluid_Properties.json b/agency-indexes/DoE/Carbon_Dioxide_Fluid_Properties.json new file mode 100644 index 00000000..ce051a8f --- /dev/null +++ b/agency-indexes/DoE/Carbon_Dioxide_Fluid_Properties.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-08-30" + }, + "description": "This software is used to compute numerous properties for the liquid and vapor phases of carbon dioxide.", + "laborHours": 0.0, + "languages": [], + "name": "Carbon Dioxide Fluid Properties", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/carbon_dioxide", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CardioFlow.json b/agency-indexes/DoE/CardioFlow.json new file mode 100644 index 00000000..2a701261 --- /dev/null +++ b/agency-indexes/DoE/CardioFlow.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This software is a package of MATLAB functions which analyzes optical flow data to perform analysis on the motion contained in microscopy videos taken of beating heart cells. The resulting information is used to quantify key features of the motion such as frequency, magnitude, and correlation. This software can be applied to analyze different types of movement such as heart and muscle cell contractions frequency, beat strength, and overall beat synchronization.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "CardioFlow", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cardioid.json b/agency-indexes/DoE/Cardioid.json new file mode 100644 index 00000000..f86e44a2 --- /dev/null +++ b/agency-indexes/DoE/Cardioid.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-18" + }, + "description": "Cardioid is a cardiac multiscale simulation suite spanning from subcellular mechanisms up to simulations of organ-level clinical phenomena. The suite contains tools for simulating cardiac electrophysiology, cardiac mechanics, torso-ECGs, cardiac meshing and fiber generation tools.", + "laborHours": 161834.4, + "languages": [], + "name": "Cardioid", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/cardioid", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CasCollect:_Detecting_cas_genes_and_CRISPR_arrays_in_raw_sequence_data_v1.json b/agency-indexes/DoE/CasCollect:_Detecting_cas_genes_and_CRISPR_arrays_in_raw_sequence_data_v1.json new file mode 100644 index 00000000..9f07a26c --- /dev/null +++ b/agency-indexes/DoE/CasCollect:_Detecting_cas_genes_and_CRISPR_arrays_in_raw_sequence_data_v1.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-05" + }, + "description": "This software examines raw Illumina sequence data files for cas genes and CRISPR arrays, either to be used as evidence of genome editing or for basic analysis of bacterial genomes. It translates sequencing reads into peptide sequences, and runs these against sensitive hidden Markov models for numerous Cas protein families. The set of hit read seeds is then expanded leftward and rightward by sequence matching to remaining reads, and after multiple cycles, this small fraction of the original reads is assembled to produce Cas operons. A separate mode using known CRISPR repeat sequences for a genus are used to identify CRISPR arrays that may be in genomic locations that are isolated from Cas genes.SAND2019-11770 M\n\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.\n", + "laborHours": 410.4, + "languages": [ + "Perl", + "Python" + ], + "name": "CasCollect: Detecting cas genes and CRISPR arrays in raw sequence data v1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CasCollect", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cassandra_Labview_Driver__binary_protocol_v3_.json b/agency-indexes/DoE/Cassandra_Labview_Driver__binary_protocol_v3_.json new file mode 100644 index 00000000..58750790 --- /dev/null +++ b/agency-indexes/DoE/Cassandra_Labview_Driver__binary_protocol_v3_.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2023-02-28", + "metadataLastUpdated": "2023-02-28" + }, + "description": "The software package provides LABView Vis to connect directly to a Cassandra database using the cassandra binary protocol version 3.", + "laborHours": 0.0, + "languages": [ + "Labview 2013 or above" + ], + "name": "Cassandra Labview Driver (binary protocol v3)", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/atap-labview-cassandra-driver/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/CatCost\342\204\242_Data_Tools_[SWR-20-59].json" "b/agency-indexes/DoE/CatCost\342\204\242_Data_Tools_[SWR-20-59].json" new file mode 100644 index 00000000..1a23ff61 --- /dev/null +++ "b/agency-indexes/DoE/CatCost\342\204\242_Data_Tools_[SWR-20-59].json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-12-03", + "metadataLastUpdated": "2023-10-11" + }, + "description": "CatCost\u2122 enables catalyst researchers to develop comprehensive estimates of the cost to produce pre-commercial catalysts early in the catalyst development process. It includes both web browser and Excel-based tools, each with distinct strengths. The web tool includes powerful visualization capabilities, while the Excel tool allows for high degrees of control and customization by power users. The CatCost\u2122 Python Data Tools are designed to facilitate the transfer of data from the Excel tool to the web tool, so that users can take advantage of both the powerful visualization in the web tool and the higher degree of customization available in the excel tool. Rather than painstakingly copying entries from estimates, the materials, equipment, and spent catalyst libraries from Excel to a JSON format for the web tool, the CatCost\u2122 Data Tools provide an intuitive applet which allows them to simply choose which library or estimate they wish to transfer, and then returns files that integrate smoothly with the web version of the tool.", + "laborHours": 1824.0, + "languages": [ + "Python" + ], + "name": "CatCost\u2122 Data Tools [SWR-20-59]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/catcost-data-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/CatCost\342\204\242__Catalyst_Cost_Estimation_Tool__[SWR-18-74].json" "b/agency-indexes/DoE/CatCost\342\204\242__Catalyst_Cost_Estimation_Tool__[SWR-18-74].json" new file mode 100644 index 00000000..ef819f1f --- /dev/null +++ "b/agency-indexes/DoE/CatCost\342\204\242__Catalyst_Cost_Estimation_Tool__[SWR-18-74].json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-25", + "metadataLastUpdated": "2023-06-16" + }, + "description": "CatCost\u2122 is a state-of-the-art cost estimation tool designed to reduce the cost uncertainty associated with pre-commercial catalyst materials. The tool combines industry-standard cost estimation methods and resources into an intuitive suite of tools to bring actionable cost insight to every step of catalyst research and development. CatCost\u2122 allows the rapid development of comprehensive catalyst cost estimates. It incorporates detailed insight into manufacturing methods, especially for pre-commercial catalysts, without requiring any process design experience.\n\nThe tool has been designed from the ground up with a number of user-selectable estimation methods, pricing libraries, and ease-of-use features to tailor an estimate to a user's skill level and need for customization, empowering researchers of all skill-levels to make better R&D decisions throughout the catalyst development cycle. Our costing methods are fully transparent and enable power-users the ability to adjust any estimate to the economic realities of their operation.\n\nThe tool has been designed from the ground up with a number of user-selectable estimation methods, pricing libraries, and ease-of-use features to tailor an estimate to a user's skill level and need for customization, empowering researchers of all skill-levels to make better R&D decisions throughout the catalyst development cycle. Our costing methods are fully transparent and enable power-users the ability to adjust any estimate to the economic realities of their operation.\n\nFeatures include:\nRaw materials pricing: Libraries of common chemicals, cost scaling indices, guidance for obtaining bulk quotes, and methods for extrapolating laboratory-scale prices to bulk.\nSimplified step method for synthesis by a contract manufacturer: All-in hourly cost for process equipment using methods and data from tollers. (Excel-only in v1.0)", + "homepageURL": "https://catcost.chemcatbio.org", + "laborHours": 0.0, + "languages": [], + "name": "CatCost\u2122 (Catalyst Cost Estimation Tool) [SWR-18-74]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://catcost.chemcatbio.org/disclaimer", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://catcost.chemcatbio.org", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CatHub.json b/agency-indexes/DoE/CatHub.json new file mode 100644 index 00000000..58f2318c --- /dev/null +++ b/agency-indexes/DoE/CatHub.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2023-09-19", + "metadataLastUpdated": "2023-09-19" + }, + "description": "Python API for the Surface Reactions database on Catalysis-Hub.org, used for querying and uploading data.", + "laborHours": 0.0, + "languages": [], + "name": "CatHub", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SUNCAT-Center/CatHub", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CatMAP.json b/agency-indexes/DoE/CatMAP.json new file mode 100644 index 00000000..c9f24708 --- /dev/null +++ b/agency-indexes/DoE/CatMAP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2023-09-19", + "metadataLastUpdated": "2023-09-19" + }, + "description": "Mirror of official CatMAP repository, contains the numbers solver.", + "laborHours": 0.0, + "languages": [], + "name": "CatMAP", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sudarshanv01/catmap-mirror", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Catalyst__ALPINE_.json b/agency-indexes/DoE/Catalyst__ALPINE_.json new file mode 100644 index 00000000..7b1d9ec0 --- /dev/null +++ b/agency-indexes/DoE/Catalyst__ALPINE_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "ParaView Catalyst (Catalyst) is an in situ use case library, with an adaptable application programming interface (API), that orchestrates the delicate alliance between simulation and analysis and/or visualization tasks. It brings the renown, scaling capabilities of VTK and ParaView to bear on the in situ use case. The analysis and visualization tasks can be implemented in C++ or Python, and Python scripts can be crafted from scratch or using the ParaView GUI to interactively setup Catalyst scripts.", + "homepageURL": "https://www.paraview.org/in-situ", + "laborHours": 4751398.4, + "languages": [], + "name": "Catalyst (ALPINE)", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.paraview.org/paraview-license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.paraview.org/in-situ", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Catch2.json b/agency-indexes/DoE/Catch2.json new file mode 100644 index 00000000..07555851 --- /dev/null +++ b/agency-indexes/DoE/Catch2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "The Catch2 library is an open-source unit-testing framework available on GitHub (https://github.com/catchorg/Catch2). The Catch2 unit-testing framework currently lacks support for handling C-style assertions via the \"assert\" macro. The source code being disclosed adds the ability to verify that C-style assertions are caught when expected and registered with the Catch2 framework by making direct additions to the Catch2 software. This source code will be contributed back to the Catch2 project on Github and copyright will need to cover any alterations required by the project owners on Github including alterations to source code, documentation, testing, etc. Ideally, the changes made herein will be released under the Boost Software License Version 1.0.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Catch2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/catchorg/Catch2/blob/devel/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CausalFS.json b/agency-indexes/DoE/CausalFS.json new file mode 100644 index 00000000..5842945d --- /dev/null +++ b/agency-indexes/DoE/CausalFS.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2021-12-02" + }, + "description": "SAND2021-4723 O CausalFS is a Python package that evaluates causal relationships between dataset features and the metric to be predicted. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "CausalFS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CausalFS", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Causal_Spatiotemporal_Stencil_Learning__CaStLe_.json b/agency-indexes/DoE/Causal_Spatiotemporal_Stencil_Learning__CaStLe_.json new file mode 100644 index 00000000..069f6a74 --- /dev/null +++ b/agency-indexes/DoE/Causal_Spatiotemporal_Stencil_Learning__CaStLe_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "SAND2024-12627O\nCausal Spatiotemporal Stencil Learning (CaStLe) is an algorithm for enabling spatiotemporal causal discovery of local dynamics on regularly gridded datasets. CaStLe computes causal graphs over a grid depicting local spatiotemporal causal dependence between neighboring grid cells. It first projects the given gridded spatiotemporal data to a 3x3 reduced coordinate space, in which each grid is represented by a time series that contains the generalized causal dependence between neighboring cells. Then, it augments a given causal discovery algorithm to identify the causal parents of the center cell in the reduced 3x3 space in the Parent Identification Phase (PIP). The result of the PIP is called a stencil. Finally, the algorithm expands the stencil to represent the original grid space.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "Causal Spatiotemporal Stencil Learning (CaStLe)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Celeritas.json b/agency-indexes/DoE/Celeritas.json new file mode 100644 index 00000000..9bc27ac3 --- /dev/null +++ b/agency-indexes/DoE/Celeritas.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "johnsonsr@ornl.gov" + }, + "date": { + "created": "2022-10-11", + "metadataLastUpdated": "2022-10-26" + }, + "description": "Celeritas is a new Monte Carlo transport code designed for high-performance simulation of high-energy physics detectors.", + "laborHours": 0.0, + "languages": [ + "C++", + "CUDA" + ], + "name": "Celeritas", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/celeritas-project/celeritas", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CentOS_7_Lite_for_diskless_systems.json b/agency-indexes/DoE/CentOS_7_Lite_for_diskless_systems.json new file mode 100644 index 00000000..532f3baf --- /dev/null +++ b/agency-indexes/DoE/CentOS_7_Lite_for_diskless_systems.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-14", + "metadataLastUpdated": "2022-07-14" + }, + "description": "This repository contains the code used to generate CentOS 7 diskless images, which can be boot using IPXE.", + "laborHours": 0.0, + "languages": [], + "name": "CentOS 7 Lite for diskless systems", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/centos7-diskless-builder/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/centos7-diskless-builder", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Center_for_Efficient_Exascale_Discretizations_Software_Suite.json b/agency-indexes/DoE/Center_for_Efficient_Exascale_Discretizations_Software_Suite.json new file mode 100644 index 00000000..d30e0d7a --- /dev/null +++ b/agency-indexes/DoE/Center_for_Efficient_Exascale_Discretizations_Software_Suite.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The CEED Software suite is a collection of generally applicable software tools focusing on the following computational motives: PDE discretizations on unstructured meshes, high-order finite element and spectral element methods and unstructured adaptive mesh refinement. All of this software is being developed as part of CEED, a co-design Center for Efficient Exascale Discretizations, within DOE's Exascale Computing Project (ECP) program.", + "homepageURL": "http://ceed.exascaleproject.org", + "laborHours": 0.0, + "languages": [ + "C++, C, Fortran, Shell, Python" + ], + "name": "Center for Efficient Exascale Discretizations Software Suite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ceed.exascaleproject.org/software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://ceed.exascaleproject.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Central_Store_Quality_Control.json b/agency-indexes/DoE/Central_Store_Quality_Control.json new file mode 100644 index 00000000..51da40cc --- /dev/null +++ b/agency-indexes/DoE/Central_Store_Quality_Control.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"Central Store Quality Control\" developed by KBase. ", + "laborHours": 547.2, + "languages": [], + "name": "Central Store Quality Control", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/cs_qc", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cerebras_TriLabs_SC'24_paper_Artifact_Description.json b/agency-indexes/DoE/Cerebras_TriLabs_SC'24_paper_Artifact_Description.json new file mode 100644 index 00000000..64c9a306 --- /dev/null +++ b/agency-indexes/DoE/Cerebras_TriLabs_SC'24_paper_Artifact_Description.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-07-01", + "metadataLastUpdated": "2024-07-01" + }, + "description": "Artifact Description of the Cerebras TriLabs SC'24 conference paper. Include details and procedures for how to reproduce timing computations.", + "laborHours": 45.6, + "languages": [], + "name": "Cerebras TriLabs SC'24 paper Artifact Description", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CerebrasTrilabs-SC24AD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cerebro.json b/agency-indexes/DoE/Cerebro.json new file mode 100644 index 00000000..2194eb42 --- /dev/null +++ b/agency-indexes/DoE/Cerebro.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Cerebro is a collection of cluster monitoring tools and libraries.\n", + "laborHours": 68232.8, + "languages": [], + "name": "Cerebro", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/cerebro", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Certification_Validation_Libraries.json b/agency-indexes/DoE/Certification_Validation_Libraries.json new file mode 100644 index 00000000..724c2fc9 --- /dev/null +++ b/agency-indexes/DoE/Certification_Validation_Libraries.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2022-05-06" + }, + "description": "\u201cThe code \u201cCertificate Validation Libraries\u201d provides the ability to validate x509 certificates in python using a simple library. These libraries validate certificates in 3 ways: 1) validation that certificate has not expired. 2) validation that certificate has not been revoked and 3) validation of certificate's digital signature. The benefits of this code is that one can properly validate x509 certificates, thus strengthening the security of systems using these libraries.\u201d", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "Certification Validation Libraries", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/certification-validation-libraries", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ChIMES_AL_Driver.json b/agency-indexes/DoE/ChIMES_AL_Driver.json new file mode 100644 index 00000000..401446d5 --- /dev/null +++ b/agency-indexes/DoE/ChIMES_AL_Driver.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-09-29", + "metadataLastUpdated": "2022-09-30" + }, + "description": "The ChIMES AL Driver is a python-based workflow tool for generating ChIMES models.", + "laborHours": 0.0, + "languages": [], + "name": "ChIMES AL Driver", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rk-lindsey/al_driver", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Characterization_and_Analysis_of_Networked_Array_of_Sensors_for_Event_Detection__CANARY-EDS_.json b/agency-indexes/DoE/Characterization_and_Analysis_of_Networked_Array_of_Sensors_for_Event_Detection__CANARY-EDS_.json new file mode 100644 index 00000000..f6f83186 --- /dev/null +++ b/agency-indexes/DoE/Characterization_and_Analysis_of_Networked_Array_of_Sensors_for_Event_Detection__CANARY-EDS_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CANARY -EDS provides probabilistic event detection based on analysis of time-series data from water quality or other sensors. CANARY also can compare patterns against a library of previously seen data to indicate that a certain pattern has reoccurred, suppressing what would otherwise be considered an event. CANARY can be configured to analyze previously recorded data from files or databases, or it can be configured to run in real-time mode directory from a database, or through the US EPA EDDIES software.", + "homepageURL": "https://software.sandia.gov/trac/canary", + "laborHours": 0.0, + "name": "Characterization and Analysis of Networked Array of Sensors for Event Detection (CANARY-EDS)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://software.sandia.gov/trac/canary", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Characterizing_possible_failure_modes_in_physics-informed_neural_networks__characterizing-pinns-failure-modes__v0.1.0.json b/agency-indexes/DoE/Characterizing_possible_failure_modes_in_physics-informed_neural_networks__characterizing-pinns-failure-modes__v0.1.0.json new file mode 100644 index 00000000..e1913461 --- /dev/null +++ b/agency-indexes/DoE/Characterizing_possible_failure_modes_in_physics-informed_neural_networks__characterizing-pinns-failure-modes__v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-14", + "metadataLastUpdated": "2021-10-14" + }, + "description": "This software provides an implementation of the physics-informed neural network setup for different differential equations. It provides a way to solve differential equations using machine learning, via a physical constraint term in the loss function. Physics-informed neural networks are a popular approach, but here, the failures of such an approach are characterized and better solutions and training procedures are provided.", + "laborHours": 0.0, + "languages": [], + "name": "Characterizing possible failure modes in physics-informed neural networks (characterizing-pinns-failure-modes) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/a1k12/characterizing-pinns-failure-modes/blob/main/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/a1k12/characterizing-pinns-failure-modes.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Charging-management_And_Infrastructure-planning__cmip__Model.json b/agency-indexes/DoE/Charging-management_And_Infrastructure-planning__cmip__Model.json new file mode 100644 index 00000000..6e04ec14 --- /dev/null +++ b/agency-indexes/DoE/Charging-management_And_Infrastructure-planning__cmip__Model.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-19", + "metadataLastUpdated": "2023-03-15" + }, + "description": "CMIP model explores various charging infrastructure network designs to serve a free-floating car-sharing fleet and determine the charging downtime experienced by the fleet for each design. Development of the CMIP model had two major steps: (1) describing modeling assumptions and (2) developing an integer program (IP) that jointly optimizes decisions about locations to install DC fast chargers and EV-to-charger assignments. The CMIP model integrates an EV charging model, EV energy consumption model, and heterogeneous, real-world vehicle use data with an integer programming optimization model to identify optimal location of new charging stations and calculate vehicle downtime for charging. The CMIP model can be applied to understand: (a) the reduction of EV fleet downtime if an additional fast-charging station is added to the current infrastructure and (b) to what extent total vehicle downtime would be sensitive to additional charging infrastructure.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Charging-management And Infrastructure-planning (cmip) Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/CMIP", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Charliecloud.json b/agency-indexes/DoE/Charliecloud.json new file mode 100644 index 00000000..8446c048 --- /dev/null +++ b/agency-indexes/DoE/Charliecloud.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Charliecloud is a set of scripts to let users run a virtual cluster of virtual machines (VMs) on a desktop or supercomputer. Key functions include: 1. Creating (typically by installing an operating system from vendor media) and updating VM images; 2. Running a single VM; 3. Running multiple VMs in a virtual cluster. The virtual machines can talk to one another over the network and (in some cases) the outside world. This is accomplished by calling external programs such as QEMU and the Virtual Distributed Ethernet (VDE) suite. The goal is to let users have a virtual cluster containing nodes where they have privileged access, while isolating that privilege within the virtual cluster so it cannot affect the physical compute resources. Host configuration enforces security; this is not included in Charliecloud, though security guidelines are included in its documentation and Charliecloud is designed to facilitate such configuration. Charliecloud manages passing information from host computers into and out of the virtual machines, such as parameters of the virtual cluster, input data specified by the user, output data from virtual compute jobs, VM console display, and network connections (e.g., SSH or X11). Parameters for the virtual cluster (number of VMs, RAM and disk per VM, etc.) are specified by the user or gathered from the environment (e.g., SLURM environment variables). Example job scripts are included. These include computation examples (such as a \"hello world\" MPI job) as well as performance tests. They also include a security test script to verify that the virtual cluster is appropriately sandboxed. Tests include: 1. Pinging hosts inside and outside the virtual cluster to explore connectivity; 2. Port scans (again inside and outside) to see what services are available; 3. Sniffing tests to see what traffic is visible to running VMs; 4. IP address spoofing to test network functionality in this case; 5. File access tests to make sure host access permissions are enforced. This test script is not a comprehensive scanner and does not test for specific vulnerabilities. Importantly, no information about physical hosts or network topology is included in this script (or any of Charliecloud); while part of a sensible test, such information is specified by the user when the test is run. That is, one cannot learn anything about the LANL network or computing infrastructure by examining Charliecloud code.", + "laborHours": 4879.2, + "name": "Charliecloud", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/charliecloud", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Charon_v._2.0.json b/agency-indexes/DoE/Charon_v._2.0.json new file mode 100644 index 00000000..e26de2cc --- /dev/null +++ b/agency-indexes/DoE/Charon_v._2.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2021-08-25" + }, + "description": "Charon is used to solve the drift-diffusion PDE Equations associated with semi-conductor physics. it is used to stimulate the operation of semi-conductor devices such as transistors and diodes. Additionally, the ode includes the functionality, but no the restricted data, to model these devices under the effects of neutron radiation.", + "homepageURL": "https://charon.sandia.gov", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Charon v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://charon.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Chatterbug.json b/agency-indexes/DoE/Chatterbug.json new file mode 100644 index 00000000..5ec61407 --- /dev/null +++ b/agency-indexes/DoE/Chatterbug.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-09-19", + "metadataLastUpdated": "2018-09-19" + }, + "description": "Chatterbug is a suite of proxy applications that represent the communication patterns commonly occurring in high performance computing codes.", + "laborHours": 684.0, + "languages": [], + "name": "Chatterbug", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/chatterbug", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CheKiPEUQ.json b/agency-indexes/DoE/CheKiPEUQ.json new file mode 100644 index 00000000..25f4d7cb --- /dev/null +++ b/agency-indexes/DoE/CheKiPEUQ.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "savaraa@ornl.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-09-08" + }, + "description": "Parameter estimation for complex physical problems often suffers from finding 'solutions' that are not physically realistic. The CheKiPEUQ software provides tools for finding physically realistic parameter estimates.and CheKiPEUQ provide tools for making graphs of the parameter positions within parameter space as well as plots of the final simulation results.\n\nThe primary purpose of the CheKiPEUQ software is to enable more physically realistic parameter estimation from comparing simulations to experiments. Specifically, when prior knowledge is available about the region of parameter space which is physically realistic and when the level of uncertainty from experiment can be estimated. The software is intentionally general and can be used for almost any type of simulation. The software is made in a user friendly manner so that users can simply enter the required data and then run the program, following guidelines provided by the authors along with some trial and error. Examples are provided. Users do not need to understand the methodology that will be namedi in the following sentences. While CheKiPEUQ can be used for conventional parameter estimation and other uses, the primary uses for CheKiPEUQ are: 1) Bayesian Parameter Estimation, 2) Bayesian Model Discrimination, 3) Bayesian Design of Experiments. For more information see the project website, documentation, examples, and related publications.", + "laborHours": 109455.2, + "languages": [ + "Python" + ], + "name": "CheKiPEUQ", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdityaSavara/CheKiPEUQ", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CheckV_v0.0.1.json b/agency-indexes/DoE/CheckV_v0.0.1.json new file mode 100644 index 00000000..7b167c45 --- /dev/null +++ b/agency-indexes/DoE/CheckV_v0.0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-06-10", + "metadataLastUpdated": "2020-06-10" + }, + "description": "CheckV is a command line python script which assesses the quality of viral genomes. It will be primarily (if not exclusively) used for academic applications and applied to viral genomes identified from environmental surveys.", + "laborHours": 1352.8, + "languages": [], + "name": "CheckV v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/checkv", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Checkpoint-Restart_in_User_Space.json b/agency-indexes/DoE/Checkpoint-Restart_in_User_Space.json new file mode 100644 index 00000000..f25eecd6 --- /dev/null +++ b/agency-indexes/DoE/Checkpoint-Restart_in_User_Space.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CRUISE implements a user-space file system that stores data in main memory and transparently spills over to other storage, like local flash memory or the parallel file system, as needed. CRUISE also exposes file contents fo remote direct memory access, allowing external tools to copy files to the parallel file system in the background with reduced CPU interruption.", + "laborHours": 4772.8, + "name": "Checkpoint-Restart in User Space", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/cruise/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/cruise", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Checkpoint.json b/agency-indexes/DoE/Checkpoint.json new file mode 100644 index 00000000..775a361a --- /dev/null +++ b/agency-indexes/DoE/Checkpoint.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Checkpoint-restart", + "laborHours": 1930.4, + "languages": [], + "name": "Checkpoint", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Checkpoint", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Chemical_Asset_Tracker__CAT_.json b/agency-indexes/DoE/Chemical_Asset_Tracker__CAT_.json new file mode 100644 index 00000000..89d8d1e5 --- /dev/null +++ b/agency-indexes/DoE/Chemical_Asset_Tracker__CAT_.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2024-08-07" + }, + "description": "The Chemical Asset Tracker, CAT, is a web-based (browser) application for tracking chemical inventories. The application records information about stored chemicals from user input (via the keyboard, barcode readers, or mobile device) and stores that information into a database. A tiered user login controls access to functions in the application. A user interface is provided that allows users to search the database and update data in the database. SAND2019-7525 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 194772.8, + "languages": [ + "C#", + "Python" + ], + "name": "Chemical Asset Tracker (CAT)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ChemicalAssetTracker", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Chemical_Management_System.json b/agency-indexes/DoE/Chemical_Management_System.json new file mode 100644 index 00000000..d4c64d1c --- /dev/null +++ b/agency-indexes/DoE/Chemical_Management_System.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-19", + "metadataLastUpdated": "2025-01-31" + }, + "description": "CMS provides an inventory of all chemicals on order or being held in the laboratory, to provide a specific location for all chemical containers, to ensure that health and safety regulatory codes are being upheld, and to provide PNNL staff with hazardous chemical information to better manage their inventories. CMS is comprised of five major modules: 1) chemical purchasing, 2) chemical inventory, 3) chemical names, properties, and hazard groups, 4) reporting, and 5) system administration.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "None" + ], + "name": "Chemical Management System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Chemical_Webscraper_[SWR-24-105].json b/agency-indexes/DoE/Chemical_Webscraper_[SWR-24-105].json new file mode 100644 index 00000000..f83b54b4 --- /dev/null +++ b/agency-indexes/DoE/Chemical_Webscraper_[SWR-24-105].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Chemical Webscraper uses the chrome web browser to search for and collect cost data for chemicals from specified distribution websites.", + "laborHours": 304.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "Chemical Webscraper [SWR-24-105]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ChemicalWebScraper", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Chemically_Induced_Surface_Evolutions_with_Level_Sets.json b/agency-indexes/DoE/Chemically_Induced_Surface_Evolutions_with_Level_Sets.json new file mode 100644 index 00000000..d6eb450a --- /dev/null +++ b/agency-indexes/DoE/Chemically_Induced_Surface_Evolutions_with_Level_Sets.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-24" + }, + "description": "ChISELS is used for the theoretical modeling of detailed surface chemistry and consomitant surface evolutions occurring during microsystem fabrication processes conducted at low pressures. Examples include physical vapor deposition (PVD), low pressure chemical vapor deposition (PECVD), and plasma etching. Evolving interfaces are represented using the level-set method and the evolution equations time integrated using a Semi-Lagrangian approach. A Ballistic transport model is employed to solve for the fluxes incident on each of the surface elements. Surface chemistry leading to etching or deposition is computed by either coupling to Surface Chemkin (a commercially available code) or by providing user defined subroutines. The computational meshes used are quad-trees (2-D) and oct-trees (3-D), constructed such that grid refinement is localized to regions near the surface interfaces. As the interface evolves, the mesh is dynamically reconstructed as needed for the grid to remain fine only around the interface. For parallel computation, a domain decomposition scheme with dynamic load balancing is used to distribute the computational work across processors.", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Chemically Induced Surface Evolutions with Level Sets", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/chisels", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ChemstationMSFileReader.json b/agency-indexes/DoE/ChemstationMSFileReader.json new file mode 100644 index 00000000..93daf6b6 --- /dev/null +++ b/agency-indexes/DoE/ChemstationMSFileReader.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Allows for reading Agilent Chemstation .D folders using Dot.NET. The ChemstationMSFileReader provides C# or VB.NET access to reading Agilent Chemstation .D dataset folders, for example, from an Agilent single quadrupole GC-MS instrument.", + "laborHours": 942.4, + "languages": [], + "name": "ChemstationMSFileReader", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/ChemstationMSFileReader", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Chernobyl_Bibliographic_Search_System.json b/agency-indexes/DoE/Chernobyl_Bibliographic_Search_System.json new file mode 100644 index 00000000..e874c30d --- /dev/null +++ b/agency-indexes/DoE/Chernobyl_Bibliographic_Search_System.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Chernobyl Bibliographic Search System (Chernolit TM) provides bibliographic data in a usable format for research studies relating to the Chernobyl nuclear accident that occurred in the former Ukrainian Republic of the USSR in 1986. Chernolit TM is a portable and easy to use product. The bibliographic data is provided under the control of a graphical user interface so that the user may quickly and easily retrieve pertinent information from the large database. The user may search the database for occurrences of words, names, or phrases; view bibliographic references on screen; and obtain reports of selected references. Reports may be viewed on the screen, printed, or accumulated in a folder that is written to a disk file when the user exits the software. Chernolit TM provides a cost-effective alternative to multiple, independent literature searches. Forty-five hundred references concerning the accident, including abstracts, are distributed with Chernolit TM. The data contained in the database were obtained from electronic literature searches and from requested donations from individuals and organizations. These literature searches interrogated the Energy Science and Technology database (formerly DOE ENERGY) of the DIALOG Information Retrieval Service. Energy Science and Technology, provided by the U.S. DOE, Washington, D.C., is a multi-disciplinary database containing references to the world's scientific and technical literature on energy. All unclassified information processed at the Office of Scientific and Technical Information (OSTI) of the U.S. DOE is included in the database. In addition, information on many documents has been manually added to Chernolit TM. Most of this information was obtained in response to requests for data sent to people and/or organizations throughout the world.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Chernobyl Bibliographic Search System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Chip_Analysis_and_Characterization.json b/agency-indexes/DoE/Chip_Analysis_and_Characterization.json new file mode 100644 index 00000000..4c8e0469 --- /dev/null +++ b/agency-indexes/DoE/Chip_Analysis_and_Characterization.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-25", + "metadataLastUpdated": "2022-08-25" + }, + "description": "Characterize and analyze Integrated Circuits images.", + "laborHours": 0.0, + "languages": [], + "name": "Chip Analysis and Characterization", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/cac/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/cac", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Chombo.json b/agency-indexes/DoE/Chombo.json new file mode 100644 index 00000000..5cf581c7 --- /dev/null +++ b/agency-indexes/DoE/Chombo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-12-19", + "metadataLastUpdated": "2018-07-13" + }, + "description": "Chombo provides a set of tools for implementing finite difference and finite volume methods for the solution of partial differential equations on block-structured adaptively refined rectangular grids. Both elliptic and time-dependent modules are included. Chombo supports calculations in complex geometries with both embedded boundaries and mapped grids, and Chombo also supports particle methods. Most parallel platforms are supported, and cross-platform self-describing file formats are included.\n\nThe Chombo package is a product of the community of collaborators working with the Applied Numerical Algorithms Group part of the Computational Research Division at LBNL.\n\nChombo is a Swahili word meaning \"tool\" or \"container\".", + "homepageURL": "https://commons.lbl.gov/display/chombo/Chombo+-+Software+for+Adaptive+Solutions+of+Partial+Differential+Equations", + "laborHours": 0.0, + "languages": [], + "name": "Chombo", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://commons.lbl.gov/display/chombo/Chombo+copyright", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://commons.lbl.gov/display/chombo/Chombo+-+Software+for+Adaptive+Solutions+of+Partial+Differential+Equations", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Choppy_Lite.json b/agency-indexes/DoE/Choppy_Lite.json new file mode 100644 index 00000000..9c3fb168 --- /dev/null +++ b/agency-indexes/DoE/Choppy_Lite.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The existing methodologies for gathering and computing zonal statistics from the combination of a raster image and a shapefile either require advanced programming knowledge in at least one language or the use of proprietary software such as ArcGIS. The software \u201cChoppy Lite\u201d offers several solutions for acquiring zonal statistics that can be used without proprietary software or programming knowledge. This software provides a Docker-based ecosystem, allowing users of any experience level to simply run a single line command in a terminal prompt independent of the operating system. Intermediate to advanced users can import the class provided by the software package into their own Python scripts.", + "laborHours": 425.6, + "languages": [ + "Python 3.8" + ], + "name": "Choppy Lite", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nset-ornl/choppy", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Chordly.json b/agency-indexes/DoE/Chordly.json new file mode 100644 index 00000000..49c1ee5f --- /dev/null +++ b/agency-indexes/DoE/Chordly.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2020-01-20" + }, + "description": "Chordly is a JavaScript library that lets you detect and act upon user keyboard input. This is accomplished by wiring Chordly up to listen for key sequences, known as chords, entered by a user.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2019-11084 M\n", + "laborHours": 1185.6, + "languages": [ + "JavaScript" + ], + "name": "Chordly", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Chordly", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Chroma.json b/agency-indexes/DoE/Chroma.json new file mode 100644 index 00000000..0acc2ecb --- /dev/null +++ b/agency-indexes/DoE/Chroma.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "edwards@jlab.org" + }, + "date": { + "created": "2018-02-08", + "metadataLastUpdated": "2018-02-11" + }, + "description": "The Chroma package supports data-parallel programming constructs for lattice field theory and in particular lattice QCD. It uses the SciDAC QDP++ data-parallel programming (in C++) that presents a single high-level code image to the user, but can generate highly optimized code for many architectural systems including single node workstations, multi and many-core nodes, clusters of nodes via QMP, and classic vector computers.", + "laborHours": 672037.6, + "name": "Chroma", + "organization": "Thomas Jefferson National Accelerator Facility (TJNAF)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JeffersonLab/chroma", + "status": "Production", + "tags": [ + "DOE CODE", + "Thomas Jefferson National Accelerator Facility (TJNAF)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ciel.json b/agency-indexes/DoE/Ciel.json new file mode 100644 index 00000000..9c6d754d --- /dev/null +++ b/agency-indexes/DoE/Ciel.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2023-05-08" + }, + "description": "Compiler optimizations can alter the numerical results of scientific computing applications. When numerical results differ significantly between compilers, optimization levels, and floating-point hardware, these numerical inconsistencies can impact programming productivity. Ciel is a framework that helps programmers identify locations in the source code that are affected by compiler optimizations in CPU and GPU code. Ciel uses a floating-point precision enhancement strategy, guided by a recursive bisection search algorithm with increasing search granularity, to identify the program expressions that induce numerical inconsistencies due to compiler optimizations.", + "laborHours": 0.0, + "languages": [], + "name": "Ciel", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Ciel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema:Debye-Scherrer.json b/agency-indexes/DoE/Cinema:Debye-Scherrer.json new file mode 100644 index 00000000..7ddd201d --- /dev/null +++ b/agency-indexes/DoE/Cinema:Debye-Scherrer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "Cinema:Debye-Scherrer is an interactive visualization tool for exploring datasets, and it has been applied to multi-dataset Rietveld analyses for the validation of the analyses, scientific discovery, and experimental design.", + "laborHours": 2629.6, + "languages": [], + "name": "Cinema:Debye-Scherrer", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_debye_scherrer/blob/master/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_debye_scherrer", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema_Bandit.json b/agency-indexes/DoE/Cinema_Bandit.json new file mode 100644 index 00000000..0809e7c7 --- /dev/null +++ b/agency-indexes/DoE/Cinema_Bandit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "A multi-view application for analysis and visualization of experimental data.", + "laborHours": 2280.0, + "languages": [], + "name": "Cinema Bandit", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_bandit/blob/master/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_bandit", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema_Change_Detection.json b/agency-indexes/DoE/Cinema_Change_Detection.json new file mode 100644 index 00000000..fee3d76d --- /dev/null +++ b/agency-indexes/DoE/Cinema_Change_Detection.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "A R command line tool that takes as input a Cinema database and produces a new Cinema database with change detection results using Myers et al. This tool also produces a change detection png image and json file to be used with the Cinema:Newsfeed.", + "laborHours": 228.0, + "languages": [], + "name": "Cinema Change Detection", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_change_detection/blob/master/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_change_detection", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema_Components.json b/agency-indexes/DoE/Cinema_Components.json new file mode 100644 index 00000000..4f5539e3 --- /dev/null +++ b/agency-indexes/DoE/Cinema_Components.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "A javascript library containing prebuilt components for viewing and querying Cinema SpecD databases.", + "laborHours": 4423.2, + "languages": [], + "name": "Cinema Components", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_components/blob/master/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_components", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema_EMUI.json b/agency-indexes/DoE/Cinema_EMUI.json new file mode 100644 index 00000000..7073482d --- /dev/null +++ b/agency-indexes/DoE/Cinema_EMUI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "This is a cross-platform viewer for the EMU emulator. With it, the user can run emulations and view the results in real time. This builds on the Cinema:Scope project.", + "laborHours": 15.2, + "languages": [], + "name": "Cinema EMUI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_emui/blob/master/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_emui", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema_Examples.json b/agency-indexes/DoE/Cinema_Examples.json new file mode 100644 index 00000000..4b8780b8 --- /dev/null +++ b/agency-indexes/DoE/Cinema_Examples.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "This repository contains examples of cinema databases.", + "laborHours": 1672.0, + "languages": [], + "name": "Cinema Examples", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_examples/blob/master/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_examples", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema_Explorer.json b/agency-indexes/DoE/Cinema_Explorer.json new file mode 100644 index 00000000..be213ff4 --- /dev/null +++ b/agency-indexes/DoE/Cinema_Explorer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "This is a general viewer for all Cinema Databases following Specification D.\n\n", + "laborHours": 456.0, + "languages": [], + "name": "Cinema Explorer", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_explorer/blob/master/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_explorer", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema_Newsfeed_Viewer.json b/agency-indexes/DoE/Cinema_Newsfeed_Viewer.json new file mode 100644 index 00000000..e9b3bee4 --- /dev/null +++ b/agency-indexes/DoE/Cinema_Newsfeed_Viewer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "This is the repository for the cinema newsfeed viewer developed by the Exascale Computing Project (ECP) and Los Alamos National Laboratory (LANL).", + "laborHours": 881.6, + "languages": [], + "name": "Cinema Newsfeed Viewer", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_newsfeed/blob/master/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_newsfeed", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema_Quest.json b/agency-indexes/DoE/Cinema_Quest.json new file mode 100644 index 00000000..4d4cf841 --- /dev/null +++ b/agency-indexes/DoE/Cinema_Quest.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "An interactive visual tool for querying Cinema Database ensembles.", + "laborHours": 2204.0, + "languages": [], + "name": "Cinema Quest", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_quest/blob/master/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_quest", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema_Scope_v0.1.json b/agency-indexes/DoE/Cinema_Scope_v0.1.json new file mode 100644 index 00000000..297611f7 --- /dev/null +++ b/agency-indexes/DoE/Cinema_Scope_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "This is a cross-platform viewer for Cinema databases. The project contains a set of components for accessing and viewing databases which can be used to build other viewers and Cinema applications.", + "laborHours": 6308.0, + "languages": [], + "name": "Cinema Scope v0.1", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_scope/blob/master/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_scope", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema_Spec_A_SQL_for_Python__cinema_asqlpy_.json b/agency-indexes/DoE/Cinema_Spec_A_SQL_for_Python__cinema_asqlpy_.json new file mode 100644 index 00000000..7a47912e --- /dev/null +++ b/agency-indexes/DoE/Cinema_Spec_A_SQL_for_Python__cinema_asqlpy_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "cinema_asqlpy is a package that allows SQL queries on Cinema Spec A databases in Python.", + "laborHours": 562.4, + "languages": [], + "name": "Cinema Spec A SQL for Python (cinema_asqlpy)", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_asqlpy/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_asqlpy", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema_Toolkit.json b/agency-indexes/DoE/Cinema_Toolkit.json new file mode 100644 index 00000000..3cafb2c4 --- /dev/null +++ b/agency-indexes/DoE/Cinema_Toolkit.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-07-09", + "metadataLastUpdated": "2020-06-01" + }, + "description": "Cinema is a workflow and toolkit for capturing, storing and exploring extreme scale scientific data. It is a highly interactive image-based approach to data analysis and exploration that promotes investigation of large scientific datasets, and is\neasily integrated into existing workflows through extensions to widely used open source tools. In short, many different images of the dataset are captured and stored in a database, along with metadata describing the images. This provides a method of exploration that is unlike other current methods. This novel approach supports interactive exploration of a wide range of results, while still significantly reducing data movement and storage. The Cinema toolkit includes database specifications and software such as database writers, database viewers, algorithms and other support software that enable a wide variety of applications to write, operate on, and view Cinema databases.", + "laborHours": 5836.8, + "languages": [ + "C++", + "JavaScript", + "Python" + ], + "name": "Cinema Toolkit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema_Tutorial_for_Supercomputing_2019.json b/agency-indexes/DoE/Cinema_Tutorial_for_Supercomputing_2019.json new file mode 100644 index 00000000..d4e78926 --- /dev/null +++ b/agency-indexes/DoE/Cinema_Tutorial_for_Supercomputing_2019.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "This repository includes examples and materials for a Cinema tutorial.", + "laborHours": 1322.4, + "languages": [], + "name": "Cinema Tutorial for Supercomputing 2019", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_tutorial_2019-11_SC", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema_Tutorials.json b/agency-indexes/DoE/Cinema_Tutorials.json new file mode 100644 index 00000000..65d61a71 --- /dev/null +++ b/agency-indexes/DoE/Cinema_Tutorials.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "Current cinema tutorial that includes slides and examples. ", + "laborHours": 547.2, + "languages": [], + "name": "Cinema Tutorials", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_tutorial_2019-01_ECP/blob/master/2019-01_ECP/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_tutorial_2019-01_ECP", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinema_View.json b/agency-indexes/DoE/Cinema_View.json new file mode 100644 index 00000000..4ccd9383 --- /dev/null +++ b/agency-indexes/DoE/Cinema_View.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "A simple viewer that displays a single or multiple Cinema databases. These must be image-based Cinema databases following the current CSV-based specification. Cinema:View is is easily customizable to include other elements through direct editing of the html or json.", + "laborHours": 273.6, + "languages": [], + "name": "Cinema View", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_view/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_view", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cinemagic_Python_Tools.json b/agency-indexes/DoE/Cinemagic_Python_Tools.json new file mode 100644 index 00000000..c57e775f --- /dev/null +++ b/agency-indexes/DoE/Cinemagic_Python_Tools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "A set of python tools for reading, writing and viewing Cinema databases.", + "laborHours": 3146.4, + "languages": [], + "name": "Cinemagic Python Tools", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinemagic/blob/master/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinemagic", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Cinema\302\240library__cinema_lib_.json" "b/agency-indexes/DoE/Cinema\302\240library__cinema_lib_.json" new file mode 100644 index 00000000..c42c6ed0 --- /dev/null +++ "b/agency-indexes/DoE/Cinema\302\240library__cinema_lib_.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "cinema_lib is a set of tools and library for interacting with a Cinema database (currently Spec A and Spec D) through Python and the command line tool, cinema.", + "laborHours": 1824.0, + "languages": [], + "name": "Cinema\u00a0library (cinema_lib)", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_lib/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_lib", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CircularGenomeAdvanced.json b/agency-indexes/DoE/CircularGenomeAdvanced.json new file mode 100644 index 00000000..a78cc857 --- /dev/null +++ b/agency-indexes/DoE/CircularGenomeAdvanced.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-08", + "metadataLastUpdated": "2020-09-08" + }, + "description": "Graphical maps of circular genomes that show sequence features, base composition plots, analysis results and sequence similarity plots.", + "laborHours": 1322.4, + "languages": [], + "name": "CircularGenomeAdvanced", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/CircularGenomeAdvanced", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CiteSoft_Py.json b/agency-indexes/DoE/CiteSoft_Py.json new file mode 100644 index 00000000..1fcaf681 --- /dev/null +++ b/agency-indexes/DoE/CiteSoft_Py.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "savaraa@ornl.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2020-10-30" + }, + "description": "There is a need to provide a way for dev-users (Scientists, Engineers, and other Software Developers) to get credit (citations) when they contribute to an important software package - particularly a large package that is already established. Various solutions (including cross package) solutions do exist, but a simple standard format that can work between multiple packages and multiple languages in a modular way is not widely available. \n\nCiteSoft_py is a python implementation of CiteSoft. CiteSoft is a plain text standard consisting of a format and a protocol that exports the citations for the end-users for whichever softwares they have used. CiteSoft has been designed so that software dev-users can rely upon it regardless of coding language or platform, and even for cases where multiple codes are working in a coupled manner. The CiteSoft_py implementation includes python decorators to make wrappers for facile use.\n\nThe purpose is that when dev-users (scientists, engineers and professional programmers) contribute to a collaborative software project, that the appropriate citations (e.g., journal article, conference proceeding) are provided to the end-user. The end-user does not need to know how to use a command line interface, API, etc. ", + "laborHours": 258.4, + "languages": [ + "Python" + ], + "name": "CiteSoft_Py", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdityaSavara/CiteSoft_py", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CityBES_v2021.json b/agency-indexes/DoE/CityBES_v2021.json new file mode 100644 index 00000000..a2f0555f --- /dev/null +++ b/agency-indexes/DoE/CityBES_v2021.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "City Buildings, Energy, and Sustainability (CityBES) is a web-based data and computing platform, focusing on energy modeling and analysis of a city's building stock to support district or city-scale building energy efficiency programs. CityBES uses an international open data standard, CityGML, to represent and exchange 3D city models. CityBES employs EnergyPlus to simulate building energy use and savings from energy efficient retrofits. Other CityBES features include energy benchmarking, district heating and cooling system modeling, rooftop PV analysis, building performance visualization, heat resilience modeling, as well as urban scale mapping of microclimate and heat vulnerability at census tract level. Different from other tools, CityBES uses integrated open and standard 3D city building data and models each individual building using EnergyPlus. CityBES can be used by urban planners, city energy managers, building owners, utilities, energy consultants and researchers.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 170468.0, + "languages": [], + "name": "CityBES v2021", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CityCOVID.json b/agency-indexes/DoE/CityCOVID.json new file mode 100644 index 00000000..0c8feb4b --- /dev/null +++ b/agency-indexes/DoE/CityCOVID.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-30" + }, + "description": "CityCOVID is a detailed agent-based model that represents the behaviors, contacts and COVID-19 disease progression of millions of residents in a large urban area.", + "homepageURL": "https://www.anl.gov/dis/citycovid", + "laborHours": 0.0, + "languages": [], + "name": "CityCOVID", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/dis/citycovid", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/dis/citycovid", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Clang_UPC2C_Translator__Clang_UPC2C__v9.0.1-1.json b/agency-indexes/DoE/Clang_UPC2C_Translator__Clang_UPC2C__v9.0.1-1.json new file mode 100644 index 00000000..f7b2fee9 --- /dev/null +++ b/agency-indexes/DoE/Clang_UPC2C_Translator__Clang_UPC2C__v9.0.1-1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Clang Unified Parallel C 2 C (Clang UPC2C) translator compiles programs written in the UPC (Unified Parallel C) language to ISO C99, with calls to the Berkeley UPC runtime system. The Clang UPC2C compiler extends the capabilities of the Clang LLVM C frontend to comply with the UPC Language Specification version 1.3. The compiler generates programs that run on a wide variety of systems ranging from workstations to leadership-class supercomputers, in conjunction with the Berkeley UPC runtime and GASNet communication system. In addition to the standard UPC libraries, Clang UPC2C also provides access to Berkeley UPC library extensions.", + "laborHours": 1682077.6, + "languages": [], + "name": "Clang UPC2C Translator (Clang UPC2C) v9.0.1-1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/clangupc/clang-upc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Clang_UPC_Compiler__Clang_UPC__v3.9.1-1.json b/agency-indexes/DoE/Clang_UPC_Compiler__Clang_UPC__v3.9.1-1.json new file mode 100644 index 00000000..03a1e3fa --- /dev/null +++ b/agency-indexes/DoE/Clang_UPC_Compiler__Clang_UPC__v3.9.1-1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-20" + }, + "description": "Clang Unified Parallel C (Clang UPC) provides a compilation and execution environment for programs written in the UPC (Unified Parallel C) language. The Clang UPC compiler extends the capabilities of the Clang LLVM C compiler to comply with the UPC Language Specification version 1.3. It includes support for UPC collectives and a configurable pointer-to-shared representation. The compiler generates programs that run on a wide variety of systems ranging from workstations to leadership-class supercomputers, in conjunction with the Berkeley UPC runtime and GASNet communication system. This compiler generates assembly code / object code directly for Intel processors and IBM PowerPC.", + "laborHours": 1155.2, + "languages": [], + "name": "Clang UPC Compiler (Clang UPC) v3.9.1-1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://clangupc.github.io/clang-upc2c", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/clangupc/upc2c", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Climate_Data_Analysis_Tools.json b/agency-indexes/DoE/Climate_Data_Analysis_Tools.json new file mode 100644 index 00000000..627c9da2 --- /dev/null +++ b/agency-indexes/DoE/Climate_Data_Analysis_Tools.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Climate Data Analysis Tools (CDAT) is a software infrastructure that uses an object-oriented scripting language to link together separate software subsystems and packages thus forming an integrated environment for solving model diagnosis problems, The power of the system comes from Python and its ability to seamlissly interconnect software. Python provides a general purpose and full-featured scripting language with a variety of user interfaces including command-line interaction, stand-alone scripts (applications) and fraphical user interfaces (GUI). The CDAT subsystems, implemented as modules, provide access to and management of gridded data (Climate Data Management Systems or CDMS); large-array numerical operations (Numerical Python); and visualization (Visualization and Control System or VCS).", + "laborHours": 78644.8, + "name": "Climate Data Analysis Tools", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/UV-CDAT/uvcdat/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/UV-CDAT/uvcdat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Clippy.json b/agency-indexes/DoE/Clippy.json new file mode 100644 index 00000000..b4e4ad7e --- /dev/null +++ b/agency-indexes/DoE/Clippy.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "Clippy (CLI + PYthon) is a Python language interface to HPC resources. Precompiled binaries that execute on HPC systems are exposed as methods to a dynamically-created Clippy Python object, where they present a familiar interface to researchers, data scientists, and others. Clippy allows these users to interact with HPC resources in an easy, straightforward environment - at the REPL, for example, or within a notebook - without the need to learn complex HPC behavior and arcane job submission commands.", + "laborHours": 0.0, + "languages": [], + "name": "Clippy", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/clippy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ClockworkVMs.json b/agency-indexes/DoE/ClockworkVMs.json new file mode 100644 index 00000000..5f62708d --- /dev/null +++ b/agency-indexes/DoE/ClockworkVMs.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Graphical user interface for use and modification of virtual machine templates using Hashi Corp packer to perform virtual machine creation.", + "laborHours": 6566.4, + "name": "ClockworkVMs", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csd-dev-tools/VmBuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CloudStackProjectsNContributions.json b/agency-indexes/DoE/CloudStackProjectsNContributions.json new file mode 100644 index 00000000..289cf8a3 --- /dev/null +++ b/agency-indexes/DoE/CloudStackProjectsNContributions.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Collection of applications and cloud templates. Project currently based on www.packer.io for automation, www.github.com/boxcutter templates and the www.github.com/csd-dev-tools/ClockworkVMs application for wrapping both of the above for easy creation of virtual systems. Will in future also contain cloud templates tuned for various services, applications and purposes.", + "laborHours": 714.4, + "languages": [ + "Python, PyQt, JSON, GO" + ], + "name": "CloudStackProjectsNContributions", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csd-dev-tools/CloudStackProjectsNContributions", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CmdWebCtrl.json b/agency-indexes/DoE/CmdWebCtrl.json new file mode 100644 index 00000000..b053e706 --- /dev/null +++ b/agency-indexes/DoE/CmdWebCtrl.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "CmdWebCtrl is a utility that runs a given command and provides a simple web interface for viewing\nanything it outputs to the console, along with providing some simple controls for restarting it.", + "laborHours": 0.0, + "languages": [], + "name": "CmdWebCtrl", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GMLC-TDC/CmdWebCtrl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Co-Optima_Co-Optimizer__Co-optimization_of_fuels_and_engines_Co-optimizer__[SWR-18-57].json b/agency-indexes/DoE/Co-Optima_Co-Optimizer__Co-optimization_of_fuels_and_engines_Co-optimizer__[SWR-18-57].json new file mode 100644 index 00000000..b15c349f --- /dev/null +++ b/agency-indexes/DoE/Co-Optima_Co-Optimizer__Co-optimization_of_fuels_and_engines_Co-optimizer__[SWR-18-57].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-11-08", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This collection of python scripts is the co-optimizer, or the co-optima scenario analysis tool. This release (V0.2) is intended primarily to analysis such as done to support co-optima project planning and identification of potentially fruitful research directions rather than specify particular fuel blends. The intention of this release is to add concreteness to the co-optimization concepts, and facilitate discussion between the teams and stakeholders as the tool evolves. The user interface is currently non-existant from a productions standpoint. Questions, comments, and rants can be directed to Ray.Grout@nrel.gov", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "Co-Optima Co-Optimizer (Co-optimization of fuels and engines Co-optimizer) [SWR-18-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/cooptima-co-optimizer", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "V0.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Co-PylotDB_-_A_Python-Based_Single-Window_User_Interface_for_Transmitting_Information_to_a_Database.json b/agency-indexes/DoE/Co-PylotDB_-_A_Python-Based_Single-Window_User_Interface_for_Transmitting_Information_to_a_Database.json new file mode 100644 index 00000000..72877cd7 --- /dev/null +++ b/agency-indexes/DoE/Co-PylotDB_-_A_Python-Based_Single-Window_User_Interface_for_Transmitting_Information_to_a_Database.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-12-11" + }, + "description": "Co-PylotDB, written completely in Python, provides a user interface (UI) with which to select user and data file(s), directories, and file content, and provide or capture various other information for sending data collected from running any computer program to a pre-formatted database table for persistent storage. The interface allows the user to select input, output, make, source, executable, and qsub files. It also provides fields for specifying the machine name on which the software was run, capturing compile and execution lines, and listing relevant user comments. Data automatically captured by Co-PylotDB and sent to the database are user, current directory, local hostname, current date, and time of send. The UI provides fields for logging into a local or remote database server, specifying a database and a table, and sending the information to the selected database table. If a server is not available, the UI provides for saving the command that would have saved the information to a database table for either later submission or for sending via email to a collaborator who has access to the desired database.", + "laborHours": 64448.0, + "languages": [ + "Python" + ], + "name": "Co-PylotDB - A Python-Based Single-Window User Interface for Transmitting Information to a Database", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PYLOTDB", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CoExpression.json b/agency-indexes/DoE/CoExpression.json new file mode 100644 index 00000000..8bfbe047 --- /dev/null +++ b/agency-indexes/DoE/CoExpression.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "This is the repository for \"CoExpression\" developed by KBase. This module contains coex_filter and coex_cluster methods.", + "laborHours": 2675.2, + "languages": [], + "name": "CoExpression", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/coexpression", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CoMD_Implementation_Suite_in_Emerging_Programming_Models.json b/agency-indexes/DoE/CoMD_Implementation_Suite_in_Emerging_Programming_Models.json new file mode 100644 index 00000000..6f5d6a86 --- /dev/null +++ b/agency-indexes/DoE/CoMD_Implementation_Suite_in_Emerging_Programming_Models.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CoMD-Em is a software implementation suite of the CoMD [4] proxy app using different emerging programming models. It is intended to analyze the features and capabilities of novel programming models that could help ensure code and performance portability and scalability across heterogeneous platforms while improving programmer productivity. Another goal is to provide the authors and venders with some meaningful feedback regarding the capabilities and limitations of their models. The actual application is a classical molecular dynamics (MD) simulation using either the Lennard-Jones method (LJ) or the embedded atom method (EAM) for primary particle interaction. The code can be extended to support alternate interaction models. The code is expected ro run on a wide class of heterogeneous hardware configurations like shard/distributed/hybrid memory, GPU's and any other platform supported by the underlying programming model.", + "laborHours": 1337.6, + "name": "CoMD Implementation Suite in Emerging Programming Models", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/CoMD-Chapel/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CoMD-Chapel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CoMTE:_Counterfactual_Explanations_for_Supervised_Machine_Learning_Frameworks_on_Multivariate_Time_Series_Data.json b/agency-indexes/DoE/CoMTE:_Counterfactual_Explanations_for_Supervised_Machine_Learning_Frameworks_on_Multivariate_Time_Series_Data.json new file mode 100644 index 00000000..6982d605 --- /dev/null +++ b/agency-indexes/DoE/CoMTE:_Counterfactual_Explanations_for_Supervised_Machine_Learning_Frameworks_on_Multivariate_Time_Series_Data.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-06", + "metadataLastUpdated": "2024-07-23" + }, + "description": "CoMTE is a novel explainability technique that provides counterfactual explanations for supervised machine learning frameworks on multivariate time series data. CoMTE outperforms state-of-the-art explainability methods on several different machine learning frameworks and data sets in comprehensibility and robustness. CoMTE can be used to debug machine learning frameworks and gain a better understanding of the underlying multivariate time series data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1686 O", + "laborHours": 471.2, + "languages": [ + "Jupyter Notebook", + "Rust", + "Python" + ], + "name": "CoMTE: Counterfactual Explanations for Supervised Machine Learning Frameworks on Multivariate Time Series Data", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CoMTE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CoMet.json b/agency-indexes/DoE/CoMet.json new file mode 100644 index 00000000..f63b0f47 --- /dev/null +++ b/agency-indexes/DoE/CoMet.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "CoMet is an application for finding epistatic and pleiotropic relationships from large quantities of genomic data. It solves these large combinatorial problems on GPU-accelerated systems with thousands of compute nodes. Its methods include the 2-way Proportional Similarity method, the Custom Correlation Coefficient and the DUO method. CoMet was developed at the Oak Ridge Leadership Computing Facility in collaboration with the Computational Biology and Bioinformatics Group at Oak Ridge National Laboratory.", + "laborHours": 18361.6, + "languages": [ + "GNU C++, NVIDIA NVCC" + ], + "name": "CoMet", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wdj/comet", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CoSyR_.json b/agency-indexes/DoE/CoSyR_.json new file mode 100644 index 00000000..7f69b9bc --- /dev/null +++ b/agency-indexes/DoE/CoSyR_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-25", + "metadataLastUpdated": "2021-05-25" + }, + "description": "C20129 CoSyR is a unique particle beam dynamics simulation code developed using MPI + Kokkos on multi-GPU platforms. This new simulation code tackles a fundamental problem of the nonlinear dynamics of a particle beam from its complete self-fields, particularly the radiation fields, which underpins many accelerator design issues in high brightness beam applications as well as those arising in the development of advanced accelerators.", + "laborHours": 0.0, + "languages": [], + "name": "CoSyR ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/cosyr.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CoVTransformer.json b/agency-indexes/DoE/CoVTransformer.json new file mode 100644 index 00000000..ed9972b2 --- /dev/null +++ b/agency-indexes/DoE/CoVTransformer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "The code is a transformer model to forecast SARS-CoV-2 lineage frequencies in the future.", + "laborHours": 11445.6, + "languages": [], + "name": "CoVTransformer", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ruianke/CoVTransformer", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cob_Control.json b/agency-indexes/DoE/Cob_Control.json new file mode 100644 index 00000000..41598dc0 --- /dev/null +++ b/agency-indexes/DoE/Cob_Control.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-21", + "metadataLastUpdated": "2022-07-21" + }, + "description": "Python scripts for parallel-controlling RCE's on a SLAC COB.", + "laborHours": 0.0, + "languages": [], + "name": "Cob Control", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/CobControl", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cobalt-copper-nickel_Supply_Chains_Model.json b/agency-indexes/DoE/Cobalt-copper-nickel_Supply_Chains_Model.json new file mode 100644 index 00000000..956a12ed --- /dev/null +++ b/agency-indexes/DoE/Cobalt-copper-nickel_Supply_Chains_Model.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This model links global demand and supply of three intertwined materials cobalt (Co), copper (Cu) and nickel (Ni) in a simulation market model with explicit consideration of electric vehicle (EV) and battery scenarios. By incorporating feedback between supply, demand, prices and capacity expansion, we quantify realistic production scenarios for both primary (mining) and secondary sources (recycling). Furthermore, to understand the magnitude of material (battery) demand from the in-use EV stock, we also consider demand to replace end-of-life (EOL) batteries. We seek to answer the following questions: 1) How will production from both primary and secondary sources react to various EV deployment scenarios and battery-chemistry combinations? 2) How much supply might promising/potential new (mining) projects contribute to supply? 3) What is the impact of reducing battery lifetime? 4) If recycling rates are increased for all 3 materials, what are the implications for Co production?", + "laborHours": 0.0, + "languages": [], + "name": "Cobalt-copper-nickel Supply Chains Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/CoCuNi", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Coda_Envelope_Ratio_Tool.json b/agency-indexes/DoE/Coda_Envelope_Ratio_Tool.json new file mode 100644 index 00000000..9667ca00 --- /dev/null +++ b/agency-indexes/DoE/Coda_Envelope_Ratio_Tool.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-02", + "metadataLastUpdated": "2023-05-02" + }, + "description": "The Coda Envelope Ratio Tool (CERT) allows for calculating seismic envelopes from waveforms and measuring the amplitude ratios for multiple events against each other to invert for seismic source information. The methodology is based on Walter, W. R., Yoo, S.-H., Mayeda, K., and G\u00f6k, R. (2017), Earthquake stress via event ratio levels: Application to the 2011 and 2016 Oklahoma seismic sequences, Geophys. Res. Lett., 3147- 3155, 44, doi:10.1002/2016GL072348.", + "laborHours": 47712.8, + "languages": [], + "name": "Coda Envelope Ratio Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/coda-calibration-tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.19" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Code_Analysis_and_Refactoring_with_Clang_Tools,_Version_0.1.json b/agency-indexes/DoE/Code_Analysis_and_Refactoring_with_Clang_Tools,_Version_0.1.json new file mode 100644 index 00000000..f28779da --- /dev/null +++ b/agency-indexes/DoE/Code_Analysis_and_Refactoring_with_Clang_Tools,_Version_0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Code Analysis and Refactoring with Clang Tools is a small set of example code that demonstrates techniques for applying tools distributed with the open source Clang compiler. Examples include analyzing where variables are used and replacing old data structures with standard structures.", + "laborHours": 2675.2, + "name": "Code Analysis and Refactoring with Clang Tools, Version 0.1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/CoARCT", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Code_Artifact_for:_Clustering_Analysis_of_Commercial_Vehicles_Using_Automatically_Extracted_Features_from_Time_Series_Data_[SWR-21-96].json b/agency-indexes/DoE/Code_Artifact_for:_Clustering_Analysis_of_Commercial_Vehicles_Using_Automatically_Extracted_Features_from_Time_Series_Data_[SWR-21-96].json new file mode 100644 index 00000000..eb9d0e93 --- /dev/null +++ b/agency-indexes/DoE/Code_Artifact_for:_Clustering_Analysis_of_Commercial_Vehicles_Using_Automatically_Extracted_Features_from_Time_Series_Data_[SWR-21-96].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-08-06", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This repository contains data ingestion, feature extraction, and analysis code used in NREL Technical report \"Clustering Analysis of Commercial Vehicles Using Automatically Extracted Features from Time Series Data.\" The code is written in Python. The ETL and feature extraction code must be run in a Spark context. The analysis code can be run without Spark, provided you have pre-computed features in a CSV file. Analysis code related to the NREL Technical Report NREL/TP-2C00-74212. Includes PySpark functions to perform trip segmentation and feature extraction over big time series data in Apache Spark. Includes \"domain specific\" features such as Aerodynamic Speed (ft/s), Characteristic Acceleration (ft/s2), Percent Below 55 (%), Percent Zero (%), Stops Per Mile, Average Speed (mph), Maximum Speed (mph), and Speed Standard Deviation (mph). Includes Pyspark UDF to compute \"domain agnostic\" features using the TSFresh library. This software record also includes the analysis notebooks and code to generate the results in the previously mentioned technical report.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Code Artifact for: Clustering Analysis of Commercial Vehicles Using Automatically Extracted Features from Time Series Data [SWR-21-96]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/clustering-analysis-domain-agnostic-features-2018", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Code_Description_for_\"Brief_Communication:_Monitoring_snow_depth_using_small,_cheap,_and_easy-to-deploy_ground_surface_temperature_sensors\".json" "b/agency-indexes/DoE/Code_Description_for_\"Brief_Communication:_Monitoring_snow_depth_using_small,_cheap,_and_easy-to-deploy_ground_surface_temperature_sensors\".json" new file mode 100644 index 00000000..d5e67ce8 --- /dev/null +++ "b/agency-indexes/DoE/Code_Description_for_\"Brief_Communication:_Monitoring_snow_depth_using_small,_cheap,_and_easy-to-deploy_ground_surface_temperature_sensors\".json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2025-04-24" + }, + "description": "Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. We train a random forest machine learning model to predict snow depth from variability in ground surface temperature. To our knowledge, this is the first time that small ground surface temperature sensors have been used to estimate snow depth. The model performs well at sites where the model was trained and at pan-arctic evaluation sites (RMSE <= 0.15 m). Small temperature sensors are cheap and easy-to-deploy, so this technique enables spatially distributed and temporally continuous snowpack monitoring to an extent previously infeasible. The model is flexible and can be applied to datasets retroactively to retrieve snow depth estimates at additional sites. This code package includes a *.joblib file of the trained random forest model and a *.ipynb file showing how to clean input data, train the random forest model, and apply the model.", + "laborHours": 45.6, + "languages": [], + "name": "Code Description for \"Brief Communication: Monitoring snow depth using small, cheap, and easy-to-deploy ground surface temperature sensors\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cbachand-LANL/iButton-SnowDepth-ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Code_Release_for_\342\200\234Unlocking_Extreme_Space_Weather_through_Advanced_Modeling_of_Legacy_Vela_Spacecraft\342\200\235_ER.json" "b/agency-indexes/DoE/Code_Release_for_\342\200\234Unlocking_Extreme_Space_Weather_through_Advanced_Modeling_of_Legacy_Vela_Spacecraft\342\200\235_ER.json" new file mode 100644 index 00000000..e866d89f --- /dev/null +++ "b/agency-indexes/DoE/Code_Release_for_\342\200\234Unlocking_Extreme_Space_Weather_through_Advanced_Modeling_of_Legacy_Vela_Spacecraft\342\200\235_ER.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "The software being developed for this project has two mains aims. First, a Bayesian Model Calibration (BMC) procedure is being developed to calibrate a spallation model that simulates protons hitting a spacecraft orbiting earth to real data. The procedure will be developed for general data (there is no data release requested as part of this code release). Second, an inverse physics modeling task is being undertaken to map the number of resulting neutrons observed from this process to the expected number of protons that hit the model. This second task is of statistical interest; to publish on it, the code will need to be open source.", + "laborHours": 197.6, + "languages": [], + "name": "Code Release for \u201cUnlocking Extreme Space Weather through Advanced Modeling of Legacy Vela Spacecraft\u201d ER", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vela_sep", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Code_for_\"Exploring_the_Transferability_of_Machine-Learning_Models\".json" "b/agency-indexes/DoE/Code_for_\"Exploring_the_Transferability_of_Machine-Learning_Models\".json" new file mode 100644 index 00000000..252ce612 --- /dev/null +++ "b/agency-indexes/DoE/Code_for_\"Exploring_the_Transferability_of_Machine-Learning_Models\".json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-10", + "metadataLastUpdated": "2025-02-10" + }, + "description": "SAND2025-01223O\n\"Exploring the Transferability of Machine-Learning Models\" is a software tool that trains and tests machine-learning models using simulated data. It includes Python scripts and a Jupyter Notebook to train models to predict material properties from X-ray diffraction profiles. The software provides a template for developing predictive models without requiring proprietary data. It streamlines the model training process and validates model transferability across different datasets. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Code for \"Exploring the Transferability of Machine-Learning Models\"", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Code_for_Axial_and_Crossflow_Turbine_Simulation.json b/agency-indexes/DoE/Code_for_Axial_and_Crossflow_Turbine_Simulation.json new file mode 100644 index 00000000..e8b605fd --- /dev/null +++ b/agency-indexes/DoE/Code_for_Axial_and_Crossflow_Turbine_Simulation.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "CACTUS is a code that calculates the performance and aero/hydrodynamic loads of a wind or water turbine. The turbine may be either a vertical-axis or a horizontal-axis machine, and may consist of one or more blade curved or straight blades. The performance model is based on a lifting-line free wake formulation that calculates rotor power and blade loads in the time domain. The rotor is treated as a rotating rigid body, such that structural dynamical motions are not modeled. The turbine is assumed to operate within a steady, but possibly sheared, wind or current velocity. For marine hydrokinetic energy applications, the presence of a river/tidal channel bed and water surface boundaries may be modeled.", + "laborHours": 3587.2, + "languages": [ + "CMake", + "MATLAB", + "Fortran", + "GLSL", + "Python" + ], + "name": "Code for Axial and Crossflow Turbine Simulation", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CACTUS", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Code_for_BALDR_Study_07.04.json b/agency-indexes/DoE/Code_for_BALDR_Study_07.04.json new file mode 100644 index 00000000..a3b781d2 --- /dev/null +++ b/agency-indexes/DoE/Code_for_BALDR_Study_07.04.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "SAND2024-11256O\nThe Code for BALDR Study 07.04 software reproduces results from the BALDR study concerning \"Multilabel Proportion Prediction and Out-of-Distribution Detection on Gamma Spectra of Short-Lived Fission Products.\" This code can reproduce a scientific study following the step numbers present in the file names. The scientific study uses synthetic and measured data to find the best model for the radioisotope proportion estimation task of interest and generates results. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1577790.4, + "languages": [ + "Python 3.8" + ], + "name": "Code for BALDR Study 07.04", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/BALDR-Study-07.04", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Code_for_BALDR_Study_07.05_v.1.0.0.json b/agency-indexes/DoE/Code_for_BALDR_Study_07.05_v.1.0.0.json new file mode 100644 index 00000000..9d5082f8 --- /dev/null +++ b/agency-indexes/DoE/Code_for_BALDR_Study_07.05_v.1.0.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-26" + }, + "description": "SAND2024-01293O\nThe Code for BALDR Study 07.05 software reproduces results from the BALDR study concerning \"A Semi-Supervised Learning Method to Produce Explainable Radioisotope Proportion Estimates for NaI-based Synthetic and Measured Gamma Spectra.\" \n\nThe code for BALDR Study 07.05 can reproduce a scientific study following the step numbers within the file names. Using synthetic and measured data to find the best model for the radioisotope proportion estimation task of interest, the study generated results for inclusion in a paper. The high-level methods involved are neural networks, semi-supervised learning, and out-of-distribution detection. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python 3.8 - 3.10" + ], + "name": "Code for BALDR Study 07.05 v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/BALDR-Study-07.05", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Code_for_Calculating_Regional_Seismic_Travel_Time.json b/agency-indexes/DoE/Code_for_Calculating_Regional_Seismic_Travel_Time.json new file mode 100644 index 00000000..1fb7e14a --- /dev/null +++ b/agency-indexes/DoE/Code_for_Calculating_Regional_Seismic_Travel_Time.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The RSTT software computes predictions of the travel time of seismic energy traveling from a source to a receiver through 2.5D models of the seismic velocity distribution within the Earth. The two primary applications for the RSTT library are tomographic inversion studies and seismic event location calculations. In tomographic inversions studies, a seismologist begins with number of source-receiver travel time observations and an initial starting model of the velocity distribution within the Earth. A forward travel time calculator, such as the RSTT library, is used to compute predictions of each observed travel time and all of the residuals (observed minus predicted travel time) are calculated. The Earth model is then modified in some systematic way with the goal of minimizing the residuals. The Earth model obtained in this way is assumed to be a better model than the starting model if it has lower residuals. The other major application for the RSTT library is seismic event location. Given an Earth model, an initial estimate of the location of a seismic event, and some number of observations of seismic travel time thought to have originated from that event, location codes systematically modify the estimate of the location of the event with the goal of minimizing the difference between the observed and predicted travel times. The second application, seismic event location, is routinely implemented by the military as part of its effort to monitor the Earth for nuclear tests conducted by foreign countries.", + "laborHours": 0.0, + "languages": [ + "Python", + "Java", + "C++", + "C" + ], + "name": "Code for Calculating Regional Seismic Travel Time", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/rstt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Code_for_Experiment_in_Publication_\342\200\234A_New_Method_for_Multinomial_Inference_using_Dempster-Shafer_Theory\342\200\235.json" "b/agency-indexes/DoE/Code_for_Experiment_in_Publication_\342\200\234A_New_Method_for_Multinomial_Inference_using_Dempster-Shafer_Theory\342\200\235.json" new file mode 100644 index 00000000..41b28372 --- /dev/null +++ "b/agency-indexes/DoE/Code_for_Experiment_in_Publication_\342\200\234A_New_Method_for_Multinomial_Inference_using_Dempster-Shafer_Theory\342\200\235.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This code compares the runtimes between the Dirichlet Dempster-Shafer Model (DSM) against the competition method, the Simplex DSM. Besides the code used to implement the Dirichlet DSM, all code to be released implements existing methods that are not novel algorithms nor any major innovations to existing software.", + "laborHours": 547.2, + "languages": [], + "name": "Code for Experiment in Publication \u201cA New Method for Multinomial Inference using Dempster-Shafer Theory\u201d", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/dempster-shafer-multinomial", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Code_for_Experiment_in_Publication_\342\200\234Determining_the_dominant_factors_for_carbon-1_mineralization_in_three-dimensional_fracture_networks\342\200\235.json" "b/agency-indexes/DoE/Code_for_Experiment_in_Publication_\342\200\234Determining_the_dominant_factors_for_carbon-1_mineralization_in_three-dimensional_fracture_networks\342\200\235.json" new file mode 100644 index 00000000..cd535292 --- /dev/null +++ "b/agency-indexes/DoE/Code_for_Experiment_in_Publication_\342\200\234Determining_the_dominant_factors_for_carbon-1_mineralization_in_three-dimensional_fracture_networks\342\200\235.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "We plan to release the code used to perform the experiment described in our recent publication, entitled \u201cDetermining the dominant factors for carbon-1 mineralization in three-dimensional fracture networks.\u201d This code fits a joint emulator to data from several Discrete Fracture Network (DFN) simulations, performed using the open-source software DFNworks (https://dfnworks.lanl.gov/). All code to be released implements existing methods; there are no novel algorithms nor any major innovations to existing software.", + "laborHours": 4043.2, + "languages": [], + "name": "Code for Experiment in Publication \u201cDetermining the dominant factors for carbon-1 mineralization in three-dimensional fracture networks\u201d", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/mineralization_dfnworks", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Code_for_Experiment_in_Publication_\342\200\234Sensitivity_Analysis_in_the_Presence_of_Intrinsic_Stochasticity_for_Discrete_Fracture_Network_Simulations\342\200\235.json" "b/agency-indexes/DoE/Code_for_Experiment_in_Publication_\342\200\234Sensitivity_Analysis_in_the_Presence_of_Intrinsic_Stochasticity_for_Discrete_Fracture_Network_Simulations\342\200\235.json" new file mode 100644 index 00000000..ffc4feb5 --- /dev/null +++ "b/agency-indexes/DoE/Code_for_Experiment_in_Publication_\342\200\234Sensitivity_Analysis_in_the_Presence_of_Intrinsic_Stochasticity_for_Discrete_Fracture_Network_Simulations\342\200\235.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "Following the Open Research requirements for AGU journals, we must release the code used to perform the experiment described in our recent publication, posted at (https://arxiv.org/abs/2312.04722). This code fits a joint emulator to data from a Discrete Fracture Network (DFN) simulation, performed using the open-source software DFNworks (https://dfnworks.lanl.gov/). All code to be released implements existing methods; there are no novel algorithms nor any major innovations to existing software.", + "laborHours": 0.0, + "languages": [], + "name": "Code for Experiment in Publication \u201cSensitivity Analysis in the Presence of Intrinsic Stochasticity for Discrete Fracture Network Simulations\u201d", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/sa_for_dfns", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Code_for_INternal_DosimetrY.json b/agency-indexes/DoE/Code_for_INternal_DosimetrY.json new file mode 100644 index 00000000..67e8879c --- /dev/null +++ b/agency-indexes/DoE/Code_for_INternal_DosimetrY.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Code for Internal Dosimetry Software Package (CINDY1.4) was developed to assist in the interpretation of bioassay data, provide bioassay projections, and evaluate committed and calendar-year doses from intake or bioassay measurement data. CINDY1.4 addresses the U.S. Department of Energy's (DOE) Order 5480.11 and the U.S. Nuclear Regulatory Commission's (NRC) 10 CFR 20 by providing the capabilities to calculate organ dose equivalents and effective dose equivalents using the International Commission on radiological Protection (ICRP) 30 approach. Biokinetic models, which allow user-modified parameter values, are used to estimate intakes based on bioassay data using weighted and unweighted least-squares regression between measured and expected bioassay values, to estimate organ burdens as well as urinary and fecal excretion rates from a given intake, and to determine organ doses for annual, 50-year, calendar year, or any other time point. Intakes to be considered may be either acute or chronic, and may consist of many combinations of intake routes, radionuclides, and physical and chemical forms. A four-compartment input model (with user defined parameters) is used for wounds and absorption. Direct injection can be simulated as direct absorption. Appropriate metabolic models for each radionuclide are selected by the user from menus. Metabolic models available in CINDY1.4 are the ICRP 30 lung model, ICRP 30 gastrointestinal model, ICRP 30 general systematic model, Johnson and Dunford tritium model, ICRP 30 tritium model, including the Johnson HT lung model, Johnson alkaline earth model, ICRP 54 iodine model, tellurium-iodine model, Jones excretion model, Durbin excretion model, ICRP 54 excretion models, Wrenn-Lipsztein uranium model, Fisher Modified Wrenn-Lipsztein uranium model, and the ICRP 30 carbon model. For Windows 95 or Windows NT an alternate CD is required.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Code for INternal DosimetrY", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Code_for_Value_Decomposition_Graph_Network_and_environment_for_AMR_on_linear_advection.json b/agency-indexes/DoE/Code_for_Value_Decomposition_Graph_Network_and_environment_for_AMR_on_linear_advection.json new file mode 100644 index 00000000..9962862d --- /dev/null +++ b/agency-indexes/DoE/Code_for_Value_Decomposition_Graph_Network_and_environment_for_AMR_on_linear_advection.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-15", + "metadataLastUpdated": "2023-08-15" + }, + "description": "This is the code for the paper [Multi-Agent Reinforcement Learning for Adaptive Mesh\nRefinement](https://arxiv.org/abs/2211.00801), published at AAMAS 2023. It contains the implementation\nof a new algorithm, called Value Decomposition Graph Network (VDGN), for applying multi-agent\nreinforcement learning to the problem of adaptive mesh refinement (AMR). It also contains the\nimplementation of a multi-agent environment for AMR on a linear advection problem. VDGN is the first\nlearning algorithm to display anticipatory refinement behavior in AMR, and it outperforms local error\nthreshold-based heuristic strategies.", + "laborHours": 0.0, + "languages": [], + "name": "Code for Value Decomposition Graph Network and environment for AMR on linear advection", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/011235813/marl-amr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Code_for_multi-shape_Gaussian_process__GP__fitting_with_uncertainty_quantification__UQ_.json b/agency-indexes/DoE/Code_for_multi-shape_Gaussian_process__GP__fitting_with_uncertainty_quantification__UQ_.json new file mode 100644 index 00000000..b25d0ff3 --- /dev/null +++ b/agency-indexes/DoE/Code_for_multi-shape_Gaussian_process__GP__fitting_with_uncertainty_quantification__UQ_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-12-15", + "metadataLastUpdated": "2023-12-15" + }, + "description": "This is code associated with the publication \u201cNonparametric Multi-shape Modeling with Uncertainty Quantification,\u201d authored by Hengrui Luo (Lawrence Berkeley National Laboratory) and Justin Strait (Los Alamos National Laboratory). The code is used to fit multiple-output Gaussian process (GP) models of planar closed curves to collections of ordered point sets, allowing for flexible nonlinear prediction of the underlying curve under dense or sparse point set samplings and with or without noise, as well as tractable uncertainty quantification. To do this, we employ use of a periodic kernel to account for the nonlinear input space of closed curves, and combine with coregionalization models to account for dependence both (i) between curve coordinates, and (ii) between pairs of curves. Functions in the code are capable of fitting these models, as well as performing additional tasks with the fitted curves such as (a) shape registration and alignment, (b) shape averaging, and (c) fitting for curve sub-populations / clusters.", + "laborHours": 0.0, + "languages": [], + "name": "Code for multi-shape Gaussian process (GP) fitting with uncertainty quantification (UQ)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/multishapeGP", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Code_for_paper_\"Reconstructing_an_Implosion_with_Space-Time_Smoothing_of_Velocimetry_Traces\".json" "b/agency-indexes/DoE/Code_for_paper_\"Reconstructing_an_Implosion_with_Space-Time_Smoothing_of_Velocimetry_Traces\".json" new file mode 100644 index 00000000..80429096 --- /dev/null +++ "b/agency-indexes/DoE/Code_for_paper_\"Reconstructing_an_Implosion_with_Space-Time_Smoothing_of_Velocimetry_Traces\".json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "New diagnostics to obtain high-temporal resolution observation of surface velocity provide a rich collection of data from high-explosive (HE) experiments. Using this data to estimate the temporal evolution of an imploding, HE-driven surface is of great interest for validating simulation of the physical system and for design of future experiments. This is the code for a paper in which we propose a method for using a Gaussian process to estimate the surface position over time and provide uncertainty estimates on that reconstruction accounting for measurement error, uncertainty to sparse spatial sampling velocity data, and robustness to outlying observations. In the paper, the code is applied on data from a hemispherical HE implosion experiment. This code is for release with the paper for peer-review, replicating the results and making the figures from the paper.", + "laborHours": 0.0, + "languages": [], + "name": "Code for paper \"Reconstructing an Implosion with Space-Time Smoothing of Velocimetry Traces\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PDV_Reconstruction", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Code_for_pathogen_evolution_and_epidemiology.json b/agency-indexes/DoE/Code_for_pathogen_evolution_and_epidemiology.json new file mode 100644 index 00000000..1d6fb9a3 --- /dev/null +++ b/agency-indexes/DoE/Code_for_pathogen_evolution_and_epidemiology.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2022-01-11" + }, + "description": "These codes and scripts will perform analyses related to genetic, evolutionary and epidemiological investigations of pathogen spread. The codes and scripts manipulate data from HIV and other pathogens and their hosts, with the goal to perform scientific investigations on how such pathogens spread, evolve, and cause disease. These codes and scripts are typically developed for specific analyses, performed by specialized scientists. It is often required by journals to make such codes available upon publication, so other scientists can check results and adapt the codes for their own research. Our research under which these codes are developed is supported by the NIH, which requires us to share codes with other researchers.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Code for pathogen evolution and epidemiology", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Code_for_the_manuscript_\"Lagrangian_Large_Eddy_Simulations_vis_Physics-informed_Machine_Learning\".json" "b/agency-indexes/DoE/Code_for_the_manuscript_\"Lagrangian_Large_Eddy_Simulations_vis_Physics-informed_Machine_Learning\".json" new file mode 100644 index 00000000..95ee51f6 --- /dev/null +++ "b/agency-indexes/DoE/Code_for_the_manuscript_\"Lagrangian_Large_Eddy_Simulations_vis_Physics-informed_Machine_Learning\".json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "We would like to disclose a code based on Python/Pytorch, in which we implement the data-driven physics-informed machine learning of Lagrangian large eddy simulation that is described in the manuscript \"Lagrangian Large Eddy Simulations via Physics-Informed Machine Learning \". High-Reynolds number Homogeneous Isotropic Turbulence is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as Large Eddy Simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about the effects of sub-grid scales on the resolved scales. Here, we take an alternative approach and design novel LES heuristics stated in terms of Lagrangian particles moving with the flow. Our \\emph{Lagrangian LES}, thus L-LES, is described by equations generalizing the weakly compressible Smoothed Particle Hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from Direct Numerical Simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The sub-grid scale contributions are modeled separately with physical constraints to account for the effects from un-resolved scales. We build the resulting model under the Differentiable Programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our Lagrangian LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.", + "laborHours": 0.0, + "languages": [], + "name": "Code for the manuscript \"Lagrangian Large Eddy Simulations vis Physics-informed Machine Learning\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Lagrangian-LES", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Code_for_the_manuscript_\"Mori-Zwanzig_Modal_Decomposition\".json" "b/agency-indexes/DoE/Code_for_the_manuscript_\"Mori-Zwanzig_Modal_Decomposition\".json" new file mode 100644 index 00000000..41983564 --- /dev/null +++ "b/agency-indexes/DoE/Code_for_the_manuscript_\"Mori-Zwanzig_Modal_Decomposition\".json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "We would like to create an open source repository in LANL's github on code written in Julia, in which we implement and extend the data-driven Mori-Zwanzig method for extracting large-scale spatio-temporal structures from data, which we call MZMD. This method is an extension of Dynamic Mode Decomposition (DMD) in which Mori-Zwanzig memory kernels are included into the associated companion matrix. In the code we would like to release, we apply MZMD to a flow over a cylinder with Reynolds number 100 rather than the much larger data set used in the associated manuscript. DMD is used extensively in the fluid dynamics community mainly for extracting large scale spatio-temporal structures (patters) from flow data. This is useful for understanding the key mechanisms that generate certain complex dynamical process relevant in engineering design. In MZMD, we improve upon DMD by adding the Mori-Zwanzig memory kernels, and show this improvement is especially important in strongly nonlinear regions of the flow.", + "laborHours": 304.0, + "languages": [], + "name": "Code for the manuscript \"Mori-Zwanzig Modal Decomposition\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MoriZwanzigModalDecomposition.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Code_for_the_manuscript_titled_\"Blackout_Diffusion:_Generative_Diffusion_Models_in_Discrete-State_Spaces\".json" "b/agency-indexes/DoE/Code_for_the_manuscript_titled_\"Blackout_Diffusion:_Generative_Diffusion_Models_in_Discrete-State_Spaces\".json" new file mode 100644 index 00000000..eafb429e --- /dev/null +++ "b/agency-indexes/DoE/Code_for_the_manuscript_titled_\"Blackout_Diffusion:_Generative_Diffusion_Models_in_Discrete-State_Spaces\".json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "We would like to disclose two scripts, written in Jupyter notebook, in which we implement the \"Blackout Diffusion Process\" described in the manuscript \"Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces\" (LA-UR-23-20509), to be submitted to the International Conference of Machine Learning (ICML). The abstract of the manuscript is append below. \n\n==\nTypical generative diffusion models rely on a Gaussian diffusion process for training the backward transformations, which can then be used generate samples from Gaussian noise. However, real world data often takes place in discrete-state spaces, which occur in many scientific applications. Here, we develop a theoretical formulation for arbitrary discrete-state Markov processes in the forward diffusion process. We relate the theory to the existing continuous-state Gaussian diffusion and identify the corresponding reverse-time stochastic process and score function in the continuous-time setting, and the reverse-time mapping in the discrete-time setting. As an example of this framework, we introduce \"Blackout Diffusion\", which learns to produce samples from an empty image instead of from noise. Numerical experiments on the CIFAR-10 dataset confirm the feasibility of generative diffusion modeling in a discrete space. Generalizing from specific (Gaussian) forward processes to a more general framework also sheds light on how to interpret generative diffusion models and their mathematical structure, which we comment on.", + "laborHours": 0.0, + "languages": [], + "name": "Code for the manuscript titled \"Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces\"", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Blackout-Diffusion", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Code_to_map_Xray_reflectivity_data_from_real_space_to_reciprocal_space_.json b/agency-indexes/DoE/Code_to_map_Xray_reflectivity_data_from_real_space_to_reciprocal_space_.json new file mode 100644 index 00000000..8f5a7f4c --- /dev/null +++ b/agency-indexes/DoE/Code_to_map_Xray_reflectivity_data_from_real_space_to_reciprocal_space_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "fitzsimmonsm@ornl.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-30" + }, + "description": "Code to map X-ray reflectivity data from real space to reciprocal space. \n The code is written as a Jupyter notebook. Example data are included as a separate file (example_data.csv). These data were collected on a Panalytical XRD system. As a first step, run all cells in the notebook. Opportunities are identified for users to make their own choices for choosing the boundaries of the region of interest to estimate background. A simple algorithm is used to estimate background from the outer regions of the data collection region, interpolating the result inside the region of interest. The background is removed and then the data mapped to Qx-Qz (reciprocal space) coordinates. The results are written as NumPy binary and Matlab formatted files.", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "Code to map Xray reflectivity data from real space to reciprocal space ", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfitzsimmons44/Xray-reflectometry", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CoderData.json b/agency-indexes/DoE/CoderData.json new file mode 100644 index 00000000..4ad5d4f2 --- /dev/null +++ b/agency-indexes/DoE/CoderData.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-05", + "metadataLastUpdated": "2024-08-05" + }, + "description": "Benchmark dataset that harmonizes drug\nresponse data across thousands of patient samples and cancer model systems enabling the training and benchmarking of\nAI/ML algorithms at scale.", + "laborHours": 112662.4, + "languages": [], + "name": "CoderData", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/coderdata", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Codes_for_\"Shallow_Soil_Response_to_a_Buried_Chemical_Explosion_with_Geophones_and_Distributed_Acoustic_Sensing\"_DAG_-_01101646.json" "b/agency-indexes/DoE/Codes_for_\"Shallow_Soil_Response_to_a_Buried_Chemical_Explosion_with_Geophones_and_Distributed_Acoustic_Sensing\"_DAG_-_01101646.json" new file mode 100644 index 00000000..1006861f --- /dev/null +++ "b/agency-indexes/DoE/Codes_for_\"Shallow_Soil_Response_to_a_Buried_Chemical_Explosion_with_Geophones_and_Distributed_Acoustic_Sensing\"_DAG_-_01101646.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-26" + }, + "description": "The codes reproduce the figures of the manuscript entitled \"Shallow Soil Response to a Buried Chemical Explosion with Geophones and Distributed Acoustic Sensing\" submitted to Journal of Geophysical Research - Solid Earth. Geophone data and Distributed acoustic sensing (DAS) data recorded during the Phase II of the The Source Physics Experiment (SPE) along a fiber-optic cable offshore were processed to understand the response of the shallow subsurface to an explosion. This Ground-based Nuclear Detonation Detection (GNDD), Low Yield Nuclear Monitoring (LYNM), and Source Physics Experiment (SPE) research was funded by the National Nuclear Security Administration, Defense Nuclear Nonproliferation Research and Development (NNSA DNN R&D).", + "laborHours": 0.0, + "languages": [], + "name": "Codes for \"Shallow Soil Response to a Buried Chemical Explosion with Geophones and Distributed Acoustic Sensing\" DAG - 01101646", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lviens-LANL/2024_DAG", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Codes_for_sub-resolution_modeling_of_the_apparent_mass_loss_in_quantitative_broadband_X-ray_radiography.json b/agency-indexes/DoE/Codes_for_sub-resolution_modeling_of_the_apparent_mass_loss_in_quantitative_broadband_X-ray_radiography.json new file mode 100644 index 00000000..365a4da0 --- /dev/null +++ b/agency-indexes/DoE/Codes_for_sub-resolution_modeling_of_the_apparent_mass_loss_in_quantitative_broadband_X-ray_radiography.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2024-09-09" + }, + "description": "SAND2022-3463 O\nThis code is intended to accompany the journal manuscript, \u201cSub-resolution modeling of the apparent mass loss in quantitative broadband X-ray radiography.\" The manuscript covers in detail how to improve the quantitative mass distribution measurements made for optical diagnostics of multiphase flows. The code contains four separate script files in MATLAB format to support the objective of improving mass measurements.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 349.6, + "languages": [ + "MATLAB" + ], + "name": "Codes for sub-resolution modeling of the apparent mass loss in quantitative broadband X-ray radiography", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/X-ray-Imaging-Apparent-Mass-Loss-Error", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Codevision_0.x.json b/agency-indexes/DoE/Codevision_0.x.json new file mode 100644 index 00000000..74ddf1f0 --- /dev/null +++ b/agency-indexes/DoE/Codevision_0.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2017-12-13", + "metadataLastUpdated": "2018-05-02" + }, + "description": "CodeVision (formerly MassAV) is a malware analysis workflow system and repository. It began as a simple tool for analyzing a large malware corpus using multiple COTS antivirus engines in parallel. It has since evolved into a unified interface for collecting, storing and analyzing malicious executable code using a variety of COTS and GOTS backends. Not only can CodeVision receive samples from users via its command-line and web interfaces, but it can also operate on continuous network data feeds (e.g., perimeter e-mail attachments, HTTP downloads). The modular analysis framework and simple API give developers the ability to integrate custom and off-the-shelf analysis tools with ease. The system manages scheduling and dependencies, allowing modules to be chained together into analysis-driven workflows. The system is designed as a distributed, load-balanced web service, an architecture that allows it to scale horizontally by adding additional nodes.", + "homepageURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 7676.0, + "name": "Codevision 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Codon2Vec_v1.0.json b/agency-indexes/DoE/Codon2Vec_v1.0.json new file mode 100644 index 00000000..f8a0abce --- /dev/null +++ b/agency-indexes/DoE/Codon2Vec_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "Background: Codon2Vec is an embedding neural network that predicts 'high' or 'low' gene expression directly from the protein-coding sequences. Embedding neural networks are commonly used for natural language processing (NLP) applications. Analogous to how an English sentence is a string of words, a gene can be thought of as a string of codons. Similar to how NLP neural networks model English sentences as a non-random sequence of words, we considered a coding sequence as a non-random non-overlapping array of codons (k-mers of length = 3). Value Proposition: - Codon2Vec achieved a high median AUC-ROC score of 83.8% when trained and applied to transcriptomic data from 300 fungal species - Unlike Codo2Vec, conventional methods predicting for expression based on codon usage rely on a priori knowledge of optimal codons or a set of reference genes. - Unlike Codon2vec, these methods do not account for the effect of codon order on gene expression. - Codon2Vec neural network bypasses the need for artisanal feature selection step that is necessary for traditional machine learning models.", + "laborHours": 0.0, + "languages": [], + "name": "Codon2Vec v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rhondene/Codon2Vec", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cognitive_Foundry_v._3.0__OSS_.json b/agency-indexes/DoE/Cognitive_Foundry_v._3.0__OSS_.json new file mode 100644 index 00000000..277e76f2 --- /dev/null +++ b/agency-indexes/DoE/Cognitive_Foundry_v._3.0__OSS_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The Cognitive Foundry is a unified collection of tools designed for research and applications that use cognitive modeling, machine learning, or pattern recognition. The software library contains design patterns, interface definitions, and default implementations of reusable software components and algorithms designed to support a wide variety of research and development needs. The library contains three main software packages: the Common package that contains basic utilities and linear algebraic methods, the Cognitive Framework package that contains tools to assist in implementing and analyzing theories of cognition, and the Machine Learning package that provides general algorithms and methods for populating Cognitive Framework components from domain-relevant data.", + "laborHours": 189939.2, + "languages": [ + "Java" + ], + "name": "Cognitive Foundry v. 3.0 (OSS)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/algorithmfoundry/Foundry", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Coherent_Combination_Propagation_Method.json b/agency-indexes/DoE/Coherent_Combination_Propagation_Method.json new file mode 100644 index 00000000..b3db8027 --- /dev/null +++ b/agency-indexes/DoE/Coherent_Combination_Propagation_Method.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-10", + "metadataLastUpdated": "2022-08-10" + }, + "description": "Full scalar wave propagation (spectral) using the Angular Spectrum Method.", + "laborHours": 0.0, + "languages": [], + "name": "Coherent Combination Propagation Method", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/CCPM", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Coincidence_Doppler_Broadening_Analysis_Program.json b/agency-indexes/DoE/Coincidence_Doppler_Broadening_Analysis_Program.json new file mode 100644 index 00000000..1112cfcc --- /dev/null +++ b/agency-indexes/DoE/Coincidence_Doppler_Broadening_Analysis_Program.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-11-22", + "metadataLastUpdated": "2023-03-08" + }, + "description": "A graphical user interface (GUI) that helps analyze data from coincidence Doppler broadening positron annihilation spectroscopy. It is a quick tool to rapidly reduce large data and conveniently analyze multiple datasets.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Coincidence Doppler Broadening Analysis Program", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/CDB_Analysis_Program", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Collabmaps.json b/agency-indexes/DoE/Collabmaps.json new file mode 100644 index 00000000..d996fc5e --- /dev/null +++ b/agency-indexes/DoE/Collabmaps.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Collabmaps is a tool for generating an interactive map that can be displayed in a web browser to visualize connections between research institutions publishing on specific scientific topics. It also highlights the most highly cited papers and top authors at each institution.", + "laborHours": 7098.4, + "name": "Collabmaps", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Collabmaps", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Collaboration_51_Correlation_Function_Analysis_Suite__c51_corr_analysis__v0.1.0.json b/agency-indexes/DoE/Collaboration_51_Correlation_Function_Analysis_Suite__c51_corr_analysis__v0.1.0.json new file mode 100644 index 00000000..4ff68aff --- /dev/null +++ b/agency-indexes/DoE/Collaboration_51_Correlation_Function_Analysis_Suite__c51_corr_analysis__v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "This is a data analysis package designed for analyzing correlation functions generated with lattice QCD calculations. The purpose is to make a centralized software suite for use by all members of my collaboration, so that various members can spend less time developing their own analysis codes, and more time extracting the interesting physics from our calculations. There are also 3 independent collaborations that have expressed interest in using this code, so there is some expectation it will be used in the broader international lattice QCD community.", + "laborHours": 0.0, + "languages": [], + "name": "Collaboration 51 Correlation Function Analysis Suite (c51_corr_analysis) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/callat-qcd/c51_corr_analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Collaborative_Analytical_Toolbox_version_1.0.json b/agency-indexes/DoE/Collaborative_Analytical_Toolbox_version_1.0.json new file mode 100644 index 00000000..862bc7f4 --- /dev/null +++ b/agency-indexes/DoE/Collaborative_Analytical_Toolbox_version_1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The purpose of the Collaborative Analytical Toolbox (CAT) is to provide a comprehensive, enabling, collaborative problem solving environment that enables users to more effectively apply and improve their analytical and problem solving capabilities. CAT is a software framework for integrating other tools and data sources. It includes a set of core services for collaboration and information exploration and analysis, and a framework that facilitates quickly integrating new ideas, techniques, and tools with existing data sources.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java", + "C++, J++" + ], + "name": "Collaborative Analytical Toolbox version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Colormaps.json b/agency-indexes/DoE/Colormaps.json new file mode 100644 index 00000000..99477376 --- /dev/null +++ b/agency-indexes/DoE/Colormaps.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "Colormapping in scientific visualization is one of the most common methods for scientists to gain insight into their data and communicate findings. The utility of a visualization is highly linked to its colormap. A suboptimal colormap may hide information or introduce spurious artifacts. Empirical design guidelines\u2014uniformity, discriminative power, order, and smoothness\u2014are usually only applied ad hoc, guidelines are often contradictory, and theory is not sufficiently developed to use a purely algorithmic approach.\n\nWe write code to generate, edit, optimize, compare, and export colormaps that satisfy these design guidelines in a rigorous mathematical way making use of differential geometry.", + "laborHours": 0.0, + "languages": [], + "name": "Colormaps", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/color", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ComDMFT.json b/agency-indexes/DoE/ComDMFT.json new file mode 100644 index 00000000..a1b4ef09 --- /dev/null +++ b/agency-indexes/DoE/ComDMFT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "vincent@sacksteder.com" + }, + "date": { + "created": "2023-01-24", + "metadataLastUpdated": "2023-02-21" + }, + "description": "ComDMFT is an ab initio code for simulating correlated quantum materials with crystalline symmetry. It combines DFT or qsGW calculations with impurity problems describing strong on-atom correlations. The impurity problem is set up using Wannier90 and cRPA, and can be solved with DMFT and CTQMC.", + "laborHours": 0.0, + "languages": [], + "name": "ComDMFT", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/comscope/ComDMFT", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/ComStock\342\204\242_2024_Release_1_[SWR-19-33_and_SWR-20-32].json" "b/agency-indexes/DoE/ComStock\342\204\242_2024_Release_1_[SWR-19-33_and_SWR-20-32].json" new file mode 100644 index 00000000..0629bce1 --- /dev/null +++ "b/agency-indexes/DoE/ComStock\342\204\242_2024_Release_1_[SWR-19-33_and_SWR-20-32].json" @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-04-26", + "metadataLastUpdated": "2024-04-26" + }, + "description": "ComStock\u2122 is an NREL model of the U.S. commercial building stock. The model takes some building characteristics from the U.S. Department of Energy's (DOE's) Commercial Prototype Building Models and Commercial Reference Building. However, unlike many other building stock models, ComStock also combines these with a variety of additional public- and private-sector data sets. Collectively, this information provides high-fidelity building stock representation with a realistic diversity of building characteristics.\n\nThis repository contains the source code used to build and execute ComStock models, including upgrade scenarios. In addition, the sampling of buildings characteristics used for the initial ComStock (V1.0) release is provided. The ComStock model is under active calibration and development, which is publicly visible on this repository.\n\nExecution of the ComStock workflow is managed through the buildstockbatch repository, a shared asset of ResStock\u2122 and ComStock\u2122 , specifically developed to scale to execution of tens of millions of simulations through multiple infrastructure providers.\n\nThe dataset output from the initial ComStock (V1.0) release can be found at the accompanying ComStock data viewer website and additional information about ComStock found on the NREL Buildings Website. For more details about ongoing model development please consult the End Use Load Profiles website.\n\nComStock is a direct result of the NREL residential stock modeling tool ResStock\u2122 (recipient of a R&D100 award) and was inspired by the high-fidelity solar & storage adoption model dGen\u2122. Additionally, this tool would not be possible without the decades of work undertaken by the OpenStudio\u00ae and EnergyPlus\u00ae visionaries and contributors, significant funding, feedback and support from the Los Angeles Department of Water and Power, and the Department of Energy's Building Technology Office ongoing support of and investment in building energy modeling software.\n\n is an analytic methodology for modeling the energy usage of the commercial building stock within the United States of America. The commercial building stock is represented through a sampling of complex probabilistic distributions of various features of interest for modeling energy usage within commercial buildings. Each sample from these distributions is converted into a building energy model based on the features of that specific sample. Each building energy model can be simulated as is, but additional changes can be made to the model through addition of energy conservation measures, component faults, or other desired alterations. The results of the simulations are then processed to provide insights for various stakeholders, including but not limited to policy makers, engineers, and marketers.", + "laborHours": 0.0, + "languages": [ + "Python", + "Ruby" + ], + "name": "ComStock\u2122 2024 Release 1 [SWR-19-33 and SWR-20-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ComStock", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2024 Release 1" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/ComStock\342\204\242_[SWR-19-33_and_SWR-20-32].json" "b/agency-indexes/DoE/ComStock\342\204\242_[SWR-19-33_and_SWR-20-32].json" new file mode 100644 index 00000000..dd4bccba --- /dev/null +++ "b/agency-indexes/DoE/ComStock\342\204\242_[SWR-19-33_and_SWR-20-32].json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2024-04-26" + }, + "description": "ComStock\u2122 is an analytic methodology for modeling the energy usage of the commercial building stock within the United States of America. The commercial building stock is represented through a sampling of complex probabilistic distributions of various features of interest for modeling energy usage within commercial buildings. Each sample from these distributions is converted into a building energy model based on the features of that specific sample. Each building energy model can be simulated as is, but additional changes can be made to the model through addition of energy conservation measures, component faults, or other desired alterations. The results of the simulations are then processed to provide insights for various stakeholders, including but not limited to policy makers, engineers, and marketers.", + "laborHours": 0.0, + "languages": [ + "Ruby" + ], + "name": "ComStock\u2122 [SWR-19-33 and SWR-20-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ComStock", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Comb.json b/agency-indexes/DoE/Comb.json new file mode 100644 index 00000000..b67bc4f9 --- /dev/null +++ b/agency-indexes/DoE/Comb.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "Comb is a communication performance benchmarking tool. It is used to determine performance tradeoffs in implementing communication patterns on high performance computing (HPC) platforms. At its core comb runs combinations of communication patterns with execution patterns, and memory spaces. The current set of capabilities Comb provides includes:\no\tConfigurable structured mesh halo exchange communication.\no\tA variety of communication patterns based on grouping messages.\no\tA variety of execution patterns including serial, openmp threading, cuda, cuda batched kernels, and cuda persistent kernels.\no\tA variety of memory spaces including default system allocated memory, pinned host memory, cuda device memory, and cuda managed memory with different cuda memory advice.", + "laborHours": 8071.2, + "languages": [], + "name": "Comb", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Comb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Combined_Thermal-Water_Microgrid_Model.json b/agency-indexes/DoE/Combined_Thermal-Water_Microgrid_Model.json new file mode 100644 index 00000000..e4102c98 --- /dev/null +++ b/agency-indexes/DoE/Combined_Thermal-Water_Microgrid_Model.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-10", + "metadataLastUpdated": "2024-09-09" + }, + "description": "SAND2022-3874 O\nThe Combined Thermal-Water Microgrid Model is a set of three models combined with controls algorithms for a Water Thermal Storage (WTS), Ground Source Heat Pump (GSHP), and Thermal Bridge Loop (TBL) that serves a residential neighborhood. The model allows a parametric investigation of volume of water storage versus number of ground heat exchanger bore-holes versus seasonal energy efficiency measures. The code is being released as open source so that the entire study can be replicated per an open access journal publication. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 2006.4, + "languages": [ + "Python" + ], + "name": "Combined Thermal-Water Microgrid Model", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/wts_gshp_tbl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Combining_Deep_Learning_with_Physics_Based_Features_in_Explosion-Earthquake_Discrimination.json b/agency-indexes/DoE/Combining_Deep_Learning_with_Physics_Based_Features_in_Explosion-Earthquake_Discrimination.json new file mode 100644 index 00000000..cfab39c7 --- /dev/null +++ b/agency-indexes/DoE/Combining_Deep_Learning_with_Physics_Based_Features_in_Explosion-Earthquake_Discrimination.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-06-20", + "metadataLastUpdated": "2022-06-20" + }, + "description": "This package contains the code for the paper Combining Deep Learning with Physics Based Features in Explosion-Earthquake Discrimination published at Geophysical Research Letters. There are two Jupyter notebooks, one for building and training the two-branch model, and the other is visualizing the deep learning branch using GradCAM.", + "laborHours": 0.0, + "languages": [], + "name": "Combining Deep Learning with Physics Based Features in Explosion-Earthquake Discrimination", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qingkaikong/PhysicsML-CombineFeatures", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Combining_Multiple_Pairwise_Structure-based_Alignments.json b/agency-indexes/DoE/Combining_Multiple_Pairwise_Structure-based_Alignments.json new file mode 100644 index 00000000..ccd73c9d --- /dev/null +++ b/agency-indexes/DoE/Combining_Multiple_Pairwise_Structure-based_Alignments.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CombAlign is a new Python code that generates a gapped, one-to-many, multiple structure-based sequence alignment(MSSA) given a set of pairwise structure-based alignments. In order to better define regions of similarity among related protein structures, it is useful to detect the residue-residue correspondences among a set of pairwise structure alignments. Few codes exist for constructing a one-to-many, multiple sequence alignment derived from a set of structure alignments, and we perceived a need for creating a new tool for combing pairwise structure alignments that would allow for insertion of gaps in the reference structure.", + "laborHours": 243.2, + "name": "Combining Multiple Pairwise Structure-based Alignments", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/Protein", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Commercial_Building_Analysis_Tool_for_Building_Energy_Efficient_Retrofit_-_COMBAT.json b/agency-indexes/DoE/Commercial_Building_Analysis_Tool_for_Building_Energy_Efficient_Retrofit_-_COMBAT.json new file mode 100644 index 00000000..3feb7fc5 --- /dev/null +++ b/agency-indexes/DoE/Commercial_Building_Analysis_Tool_for_Building_Energy_Efficient_Retrofit_-_COMBAT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Building energy efficient retrofit energy savings and cost-effectiveness analysis.", + "homepageURL": "https://china.lbl.gov/combat", + "laborHours": 0.0, + "languages": [], + "name": "Commercial Building Analysis Tool for Building Energy Efficient Retrofit - COMBAT", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://china.lbl.gov/combat", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://china.lbl.gov/combat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Commercial_Building_Energy_Asset_Score.json b/agency-indexes/DoE/Commercial_Building_Energy_Asset_Score.json new file mode 100644 index 00000000..79e366d5 --- /dev/null +++ b/agency-indexes/DoE/Commercial_Building_Energy_Asset_Score.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This software (Asset Scoring Tool) is designed to help building owners and managers to gain insight into the as-built efficiency of their buildings. It is a web tool where users can enter their building information and obtain an asset score report. The asset score report consists of modeled building energy use (by end use and by fuel type), building systems (envelope, lighting, heating, cooling, service hot water) evaluations, and recommended energy efficiency measures. The intended users are building owners and operators who have limited knowledge of building energy efficiency. The scoring tool collects minimum building data (~20 data entries) from users and build a full-scale energy model using the inference functionalities from Facility Energy Decision System (FEDS). The scoring tool runs real-time building energy simulation using EnergyPlus and performs life-cycle cost analysis using FEDS. An API is also under development to allow the third-party applications to exchange data with the web service of the scoring tool.", + "homepageURL": "https://buildingenergyscore.energy.gov", + "laborHours": 0.0, + "languages": [ + "Ruby, C# Javascript" + ], + "name": "Commercial Building Energy Asset Score", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://buildingenergyscore.energy.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://buildingenergyscore.energy.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Commercial_Building_Energy_Saver,_API__CBES_API__v2.0.json b/agency-indexes/DoE/Commercial_Building_Energy_Saver,_API__CBES_API__v2.0.json new file mode 100644 index 00000000..7db4ad11 --- /dev/null +++ b/agency-indexes/DoE/Commercial_Building_Energy_Saver,_API__CBES_API__v2.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-09", + "metadataLastUpdated": "2019-01-15" + }, + "description": "The CBES API provides Application Programming Interface to a suite of functions to improve energy efficiency of buildings, including building energy benchmarking, preliminary retrofit analysis using a pre-simulation database DEEP, and detailed retrofit analysis using energy modeling with the EnergyPlus simulation engine. New capabilities in version 2.0 include renewable technologies (PV, storage), advanced HVAC systems, demand response measures, TDV (Time Dependent Valuation energy) metrics, as well as shading from adjacent buildings, trees or roof obstructions. The CBES API is used to power the LBNL CBES Web App. It can be used by third party developers and vendors.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1501972.8, + "languages": [], + "name": "Commercial Building Energy Saver, API (CBES API) v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Commercial_Building_Energy_Saver,_Web_App_v2.0.json b/agency-indexes/DoE/Commercial_Building_Energy_Saver,_Web_App_v2.0.json new file mode 100644 index 00000000..3f06d4e8 --- /dev/null +++ b/agency-indexes/DoE/Commercial_Building_Energy_Saver,_Web_App_v2.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-11", + "metadataLastUpdated": "2019-01-15" + }, + "description": "The CBES App is a web-based toolkit for use by small businesses and building owners and operators of small and medium size commercial buildings to perform energy benchmarking and retrofit analysis for buildings. The CBES App analyzes the energy performance of user's building for pre- and post-retrofit, in conjunction with user's input data, to identify recommended retrofit measures, energy savings and economic analysis for the selected measures.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 12622353.6, + "languages": [], + "name": "Commercial Building Energy Saver, Web App v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Common_Electric_Power_Transmission_System_Model_JSON_Schema_Specification.json b/agency-indexes/DoE/Common_Electric_Power_Transmission_System_Model_JSON_Schema_Specification.json new file mode 100644 index 00000000..013584af --- /dev/null +++ b/agency-indexes/DoE/Common_Electric_Power_Transmission_System_Model_JSON_Schema_Specification.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-09", + "metadataLastUpdated": "2024-09-19" + }, + "description": "The Common Electric Power Transmission System Model (CTM) is an intuitive, extensible, language-agnostic,\nand error-resistant specification of electric power network components parameter names and\nunits, and relation between components, intended for use by the research community developing new\ncomputational methods for power systems operations and simulation. Power system datasets following\nthe CTM specification can be read as dictionaries and manipulated in that form in most programming\nlanguages (e.g., Python, Julia, C++). This standard data structure in CTM makes it easy to work in\nmultiple power systems domains (e.g., economic operation, reliability assessment, electricity markets,\nstability assessment, etc.) without requiring conversions between use-case-specific file formats with\ninformation loss in the process. This repository specifies CTM as a JSON Schema, provides\ndocumentation, derivate (code-generated) implementations of CTM, and example data and usage of the\nschema for important use cases.", + "laborHours": 1081616.8, + "languages": [], + "name": "Common Electric Power Transmission System Model JSON Schema Specification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ctm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "v0.1-alpha" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Common_Information_Model_Profile_For_Dynamic_Line_Rating.json b/agency-indexes/DoE/Common_Information_Model_Profile_For_Dynamic_Line_Rating.json new file mode 100644 index 00000000..addcbe5d --- /dev/null +++ b/agency-indexes/DoE/Common_Information_Model_Profile_For_Dynamic_Line_Rating.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-05-17", + "metadataLastUpdated": "2023-05-22" + }, + "description": "Provides an XSD framework within the Common Information Model \u2013 IEC 61970 Part 7 \u2013 for the integration of dynamic line ratings within the utility software systems. ", + "homepageURL": "https://cimug.ucaiug.org/Standards%20Artifacts/Forms/AllItems.aspx?RootFolder=%2FStandards%20Artifacts%2FUCA%20TF%2014%2FINL%2DDLR&FolderCTID=0x0120001062F2F1DF27704DBB748ABBDC3B3AA2&View=%7BFEBD8EE1%2D6B40%2D42F6%2DB228%2DCCF131291FBE%7D", + "laborHours": 0.0, + "languages": [ + "xml" + ], + "name": "Common Information Model Profile For Dynamic Line Rating", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cimug.ucaiug.org/Standards%20Artifacts/Forms/AllItems.aspx?RootFolder=%2FStandards%20Artifacts%2FUCA%20TF%2014%2FINL%2DDLR&FolderCTID=0x0120001062F2F1DF27704DBB748ABBDC3B3AA2&View=%7BFEBD8EE1%2D6B40%2D42F6%2DB228%2DCCF131291FBE%7D", + "status": "Development", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Common_Operating_and_Response_Environment.json b/agency-indexes/DoE/Common_Operating_and_Response_Environment.json new file mode 100644 index 00000000..7c92a66b --- /dev/null +++ b/agency-indexes/DoE/Common_Operating_and_Response_Environment.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "CORE is an architecture to bridge the gaps between disparate data integration and delivery of disparate information visualization. The CORE Technology Program includes a suite of tools and user-centered staff that can facilitate rapid delivery of a deployable integrated information to users.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "PhP/Java script" + ], + "name": "Common Operating and Response Environment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Common_Operating_and_Response_Environment_-_U.S._Air_Force.json b/agency-indexes/DoE/Common_Operating_and_Response_Environment_-_U.S._Air_Force.json new file mode 100644 index 00000000..6a3f7120 --- /dev/null +++ b/agency-indexes/DoE/Common_Operating_and_Response_Environment_-_U.S._Air_Force.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "CORE is an architecture to bridge the gaps between disparate data integration and delivery of disparate information visualization. The CORE Technology Program includes a suite of tools and user-centered staff that can facilitate rapid delivery of a deployable integrated information to users. Integration of Air Force data streams, summarizing the information and providing team members with the information they need to rapidly understand and respond.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Common Operating and Response Environment - U.S. Air Force", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Communication_Graph_Generator_for_Parallel_Programs.json b/agency-indexes/DoE/Communication_Graph_Generator_for_Parallel_Programs.json new file mode 100644 index 00000000..ebdef75e --- /dev/null +++ b/agency-indexes/DoE/Communication_Graph_Generator_for_Parallel_Programs.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Graphator is a collection of relatively simple sequential programs that generate communication graphs/matrices for commonly occurring patterns in parallel programs. Currently, there is support for five communication patterns: two-dimensional 4-point stencil, four-dimensional 8-point stencil, all-to-alls over sub-communicators, random near-neighbor communication, and near-neighbor communication.", + "laborHours": 91.2, + "name": "Communication Graph Generator for Parallel Programs", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/graphator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Community_Emissions_Data_System.json b/agency-indexes/DoE/Community_Emissions_Data_System.json new file mode 100644 index 00000000..b2e9113e --- /dev/null +++ b/agency-indexes/DoE/Community_Emissions_Data_System.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-27", + "metadataLastUpdated": "2020-10-29" + }, + "description": "CEDS produces consistent estimates of global air emissions species data during the industrial era (1750 - present).", + "laborHours": 24122.4, + "languages": [ + "R version 3.3+" + ], + "name": "Community Emissions Data System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/JGCRI/CEDS#license-section", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/CEDS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CompMatORNL_-_aseconv.json b/agency-indexes/DoE/CompMatORNL_-_aseconv.json new file mode 100644 index 00000000..2ab2beba --- /dev/null +++ b/agency-indexes/DoE/CompMatORNL_-_aseconv.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "myoon@ornl.gov" + }, + "date": { + "created": "2024-08-13", + "metadataLastUpdated": "2024-09-17" + }, + "description": "In the field of first-principles calculations, the creation and modification of input geometry files is a fundamental step. These files are essential for defining the atomic structures used in simulations and come in a variety of formats such as CIF, POSCAR, and XYZ. Traditionally, editing these files for specific requirements has been done manually or through GUI-based tools such as VESTA.\n\nHowever, manual and GUI-based methods fall short in high-throughput scenarios, especially when running on high-performance computing (HPC) systems. There, the need for fast and automated batch processing of geometry files becomes apparent - a need that is not adequately addressed by existing methods.\n\nThe Atomic Simulation Environment (ASE) Python library provides a robust solution with its array of geometry modification functions and support for multiple file types. However, this robustness comes at the cost of complexity: effective use of ASE requires knowledge of Python programming, which can be a hurdle for users who are not well versed in programming.\n\nTo address this gap, we developed a utility that encapsulates the functionality of ASE in a more accessible interface. This tool solves the problem of requiring extensive programming knowledge to manipulate geometry files in high-throughput computations. It provides a command-line solution that allows batch processing without the need for direct code intervention.\n\nIn addition, our tool enhances customization through user-generated plug-in files. This allows for customized modifications that can evolve as users' needs change. By simplifying the process of converting and modifying geometry files, our utility significantly reduces the effort required to prepare simulations for HPC environments.", + "laborHours": 1079.2, + "languages": [], + "name": "CompMatORNL - aseconv", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CompMatORNL/aseconv", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Compadre_Toolkit_.json b/agency-indexes/DoE/Compadre_Toolkit_.json new file mode 100644 index 00000000..482b4fc0 --- /dev/null +++ b/agency-indexes/DoE/Compadre_Toolkit_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-04-11", + "metadataLastUpdated": "2021-08-30" + }, + "description": "The Compadre Toolkit solves a minimization problem, that once solved allows a user to reconstruct a function from sample data collected from a cloud of data sites. The solution to this minimization can also be used to assemble a linear system that can be solved numerically using some other software. The minimization problem the toolkit solves is to find the optimal finite polynomial in a user specified finite dimensional space with regards to minimizing an objective function which measures a linear sampling functional applied to the polynomial, compared to the same sampling functional applied to the source function, weighted by a positive kernel that has compact support.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python" + ], + "name": "Compadre Toolkit ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/compadre", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Companion_Software_to_\"Assessment_of_localized_and_randomized_algorithms_for_electronic_structure\".json" "b/agency-indexes/DoE/Companion_Software_to_\"Assessment_of_localized_and_randomized_algorithms_for_electronic_structure\".json" new file mode 100644 index 00000000..a89ad5fe --- /dev/null +++ "b/agency-indexes/DoE/Companion_Software_to_\"Assessment_of_localized_and_randomized_algorithms_for_electronic_structure\".json" @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "It compares the performance of several different algorithms for electronic structure simulation.", + "laborHours": 2188.8, + "languages": [ + "Shell", + "C", + "Python" + ], + "name": "Companion Software to \"Assessment of localized and randomized algorithms for electronic structure\"", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/linear-scaling-test", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Companion_software_to:_Minimax_Rational_Approximation_of_the_Fermi-Dirac_Distribution_v._1.0.json b/agency-indexes/DoE/Companion_software_to:_Minimax_Rational_Approximation_of_the_Fermi-Dirac_Distribution_v._1.0.json new file mode 100644 index 00000000..8373716a --- /dev/null +++ b/agency-indexes/DoE/Companion_software_to:_Minimax_Rational_Approximation_of_the_Fermi-Dirac_Distribution_v._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Generates data for the associated paper and its supplementary data table, which are sets of residues and poles that define rational functions to approximate the Fermi-Dirac distribution.", + "laborHours": 440.8, + "languages": [ + "C" + ], + "name": "Companion software to: Minimax Rational Approximation of the Fermi-Dirac Distribution v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fermi-rational-approximation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Comparative_PV_LCOE_Calculator__Comparative_Photovoltaic_Levelized_Cost_of_Energy_Calculator__[SWR-20-86].json b/agency-indexes/DoE/Comparative_PV_LCOE_Calculator__Comparative_Photovoltaic_Levelized_Cost_of_Energy_Calculator__[SWR-20-86].json new file mode 100644 index 00000000..cbd624f1 --- /dev/null +++ b/agency-indexes/DoE/Comparative_PV_LCOE_Calculator__Comparative_Photovoltaic_Levelized_Cost_of_Energy_Calculator__[SWR-20-86].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-07-31", + "metadataLastUpdated": "2024-12-19" + }, + "description": "The calculator calculates levelized cost of energy (LCOE) for photovoltaic (PV) systems based on cost, performance, and reliability inputs for a baseline and a proposed technology. The user can choose inputs and watch the effect on LCOE to determine whether a proposed technology is cost-effective, perform trade-off analysis among different technology options, and do break-even analysis of cost or performance.", + "laborHours": 26204.8, + "languages": [ + "JavaScript" + ], + "name": "Comparative PV LCOE Calculator (Comparative Photovoltaic Levelized Cost of Energy Calculator) [SWR-20-86]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PVLCOE", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Compare_Gene_Profiles.json b/agency-indexes/DoE/Compare_Gene_Profiles.json new file mode 100644 index 00000000..c7faa5f7 --- /dev/null +++ b/agency-indexes/DoE/Compare_Gene_Profiles.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Compare Gene Profiles (CGP) performs pairwise gene content comparisons among a relatively large set of related bacterial genomes. CGP performs pairwise BLAST among gene calls from a set of input genome and associated annotation files, and combines the results to generate lists of common genes, unique genes, homologs, and genes from each genome that differ substantially in length from corresponding genes in the other genomes. CGP is implemented in Python and runs in a Linux environment in serial or parallel mode.", + "laborHours": 1763.2, + "name": "Compare Gene Profiles", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/Genome", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Compiler-RT.json b/agency-indexes/DoE/Compiler-RT.json new file mode 100644 index 00000000..0e146cb9 --- /dev/null +++ b/agency-indexes/DoE/Compiler-RT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "This directory and its subdirectories contain source code for the compiler support routines.", + "laborHours": 247364.8, + "languages": [], + "name": "Compiler-RT", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PRUNERS/compiler-rt", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Complete-Active-Space_Tensor-Network__CAS-TN__Ansatz_Library.json b/agency-indexes/DoE/Complete-Active-Space_Tensor-Network__CAS-TN__Ansatz_Library.json new file mode 100644 index 00000000..1874789d --- /dev/null +++ b/agency-indexes/DoE/Complete-Active-Space_Tensor-Network__CAS-TN__Ansatz_Library.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "maradzikee@ornl.gov" + }, + "date": { + "created": "2022-08-19", + "metadataLastUpdated": "2022-08-19" + }, + "description": "Scalable full configuration interaction based on the parameterization of the electronic wavefunction that is based on particle number, instead of (spin) orbital number.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Complete-Active-Space Tensor-Network (CAS-TN) Ansatz Library", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/elvis-maradzike/cas-tn", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Complete_Battery_Ownership_Model_And_Cost_Calculator__BOM__[SWR-20-28].json b/agency-indexes/DoE/Complete_Battery_Ownership_Model_And_Cost_Calculator__BOM__[SWR-20-28].json new file mode 100644 index 00000000..065eb101 --- /dev/null +++ b/agency-indexes/DoE/Complete_Battery_Ownership_Model_And_Cost_Calculator__BOM__[SWR-20-28].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-01-25", + "metadataLastUpdated": "2024-01-29" + }, + "description": "This software is an advanced TCO calculator that takes into account various scenarios of vehicle and component costs, battery and fuel price forecasts, drive patterns, battery wear, charging infrastructure costs, purchase incentives, financing, ownership, and other criteria. The vehicle economics considered include vehicle and related infrastructure purchases, financing, fuel (gasoline and electricity) costs, non-fuel operating and maintenance costs, battery replacement, salvage value, and any costs passed on by a third party such as a service provider to account for the installation, use, and availability of infrastructure. Battery degradation, charging strategies, and drive patterns play an important role in each of these elements.", + "homepageURL": "https://labpartnering.org/technologies/55f86d47-38e0-41b5-aa8c-bc4020564b1b", + "laborHours": 0.0, + "languages": [], + "name": "Complete Battery Ownership Model And Cost Calculator (BOM) [SWR-20-28]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://labpartnering.org/technologies/55f86d47-38e0-41b5-aa8c-bc4020564b1b", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://labpartnering.org/technologies/55f86d47-38e0-41b5-aa8c-bc4020564b1b", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Complete_Prompt_Permutation.json b/agency-indexes/DoE/Complete_Prompt_Permutation.json new file mode 100644 index 00000000..b5194c34 --- /dev/null +++ b/agency-indexes/DoE/Complete_Prompt_Permutation.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "klaskyhb@ornl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "This project evaluates a set of prompts to test their performance on specific tasks for large language models (LLMs), in order to find the optimal prompt to enhance task performance.", + "laborHours": 1018.4, + "languages": [ + "Python" + ], + "name": "Complete Prompt Permutation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/summer_2024/prompt_engineering/complete-prompt-permutation", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "Summer 2024" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CompoundSetUtils.json b/agency-indexes/DoE/CompoundSetUtils.json new file mode 100644 index 00000000..f1a93df6 --- /dev/null +++ b/agency-indexes/DoE/CompoundSetUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-08", + "metadataLastUpdated": "2020-09-08" + }, + "description": "A utility module for upload and download of chemical compound sets.", + "laborHours": 40827.2, + "languages": [], + "name": "CompoundSetUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/CompoundSetUtils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Comprehensive_Manufacturing_Assessment_Tool.json b/agency-indexes/DoE/Comprehensive_Manufacturing_Assessment_Tool.json new file mode 100644 index 00000000..1e0d5ddd --- /dev/null +++ b/agency-indexes/DoE/Comprehensive_Manufacturing_Assessment_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-07-08", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The CMAT software provides the user with a fully customizable decision support framework that analyzes the optimal supply chain configurations for a given industrial electronic waste (e-waste) recycling and refurbishment process. The software optimizes the logistics operations, helps to identify the best recycling process configuration, and generates valuable insights regarding the economic performance of different categories of e-waste. The ultimate purpose of the model is to provide insights on questions pertinent to the e-waste recycling industry including how to increase efficiency and reduce costs, energy consumption, and greenhouse gas emissions.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Comprehensive Manufacturing Assessment Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/CMAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Compressed_Continuous_Computation_v.__12_20_2016.json b/agency-indexes/DoE/Compressed_Continuous_Computation_v.__12_20_2016.json new file mode 100644 index 00000000..b0687ce1 --- /dev/null +++ b/agency-indexes/DoE/Compressed_Continuous_Computation_v.__12_20_2016.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "A library for performing numerical computation with low-rank functions. The (C3) library enables performing continuous linear and multilinear algebra with multidimensional functions. Common tasks include taking \"matrix\" decompositions of vector- or matrix-valued functions, approximating multidimensional functions in low-rank format, adding or multiplying functions together, integrating multidimensional functions.", + "laborHours": 1999271.2, + "languages": [ + "C", + "HTML", + "SWIG", + "CMake", + "Tex", + "Python" + ], + "name": "Compressed Continuous Computation v. 12/20/2016", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/compressed-continuous-computation?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/compressed-continuous-computation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Compression-Based_Distance.json b/agency-indexes/DoE/Compression-Based_Distance.json new file mode 100644 index 00000000..fc0b6c61 --- /dev/null +++ b/agency-indexes/DoE/Compression-Based_Distance.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "Compression-based distance (CBD) is a simple, rapid, and accurate method to efficiently assess differences in microbiota samples. CBD characterizes the similarities between microbial communities via the amount of repetition or overlap in order to determine microbial community distance. CBD relies on the fact that more repetitive data is the more it can be compressed. By combining 16S rRNA hypervariable tag data from different samples and assessing the relative amounts of compression, there is a proxy for the similarities between the communities. The amount of compression is converted to a distance by taking compression gained by combining the datasets over the total compressed size of the individual datasets. The distance has a value with a minimum of 0 meaning the communities are the same and a maximum of 1 meaning the communities are completely different.", + "laborHours": 729.6, + "languages": [], + "name": "Compression-Based Distance", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/cbd", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Compressive_sensing_lattice_dynamics.json b/agency-indexes/DoE/Compressive_sensing_lattice_dynamics.json new file mode 100644 index 00000000..66d04e4b --- /dev/null +++ b/agency-indexes/DoE/Compressive_sensing_lattice_dynamics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "A comprehensive package to study lattice dynamics from first-principles. The interatomic force constants were fitted using the compressive sensing algorithm.", + "laborHours": 11734.4, + "languages": [], + "name": "Compressive sensing lattice dynamics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/csld", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Computation_of_graph_hitting_time_moments;_Chapel_code_implementation..json b/agency-indexes/DoE/Computation_of_graph_hitting_time_moments;_Chapel_code_implementation..json new file mode 100644 index 00000000..7229af64 --- /dev/null +++ b/agency-indexes/DoE/Computation_of_graph_hitting_time_moments;_Chapel_code_implementation..json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The project that developed this is unclassified, with the mandate to produce open source code. This code computes the hitting time moments of a graph using a linear algebra configuration. The goal of this work is to explore the performance capabilities of the Chapel programming language. Toward that end, we generate random adjacency matrices which represent a random graph. The code can also read in an adjacency matrix from a file. The main computation is the Conjugate Gradient method.SAND2020-12651 M.\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [], + "name": "Computation of graph hitting time moments; Chapel code implementation.", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/htm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Computer_Health_Score.json b/agency-indexes/DoE/Computer_Health_Score.json new file mode 100644 index 00000000..88b7798b --- /dev/null +++ b/agency-indexes/DoE/Computer_Health_Score.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The algorithm develops a single health score for office computers, today just Windows, but we plan to extend this to Apple computers. The score is derived from various parameters, including: CPU Utilization; Memory Utilization; Various Error logs; Disk Problems; and Disk write queue length. It then uses a weighting scheme to balance these parameters and provide an overall health score. By using these parameters, we are not just assessing the theoretical performance of the components of the computer, rather we are using actual performance metrics that are selected to be a more realistic representation of the experience of the person using the computer. This includes compensating for the nature of their use. If there are two identical computers and the user of one places heavy demands on their computer compared with the user of the second computer, the former will have a lower health score. This allows us to provide a 'fit for purpose' score tailored to the assigned user. This is very helpful data to inform the mangers when individual computers need to be replaced. Additionally it provides specific information that can facilitate the fixing of the computer, to extend it's useful lifetime. This presents direct financial savings, time savings for users transferring from one computer to the next, and better environmental stewardship.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Multiple" + ], + "name": "Computer Health Score", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Computer_Programs_For_Analysis_Of_Thermally_Reactive_Tracer_Tests_In_Geothermal_Reservoirs.json b/agency-indexes/DoE/Computer_Programs_For_Analysis_Of_Thermally_Reactive_Tracer_Tests_In_Geothermal_Reservoirs.json new file mode 100644 index 00000000..631c6b40 --- /dev/null +++ b/agency-indexes/DoE/Computer_Programs_For_Analysis_Of_Thermally_Reactive_Tracer_Tests_In_Geothermal_Reservoirs.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-01-22", + "metadataLastUpdated": "2025-01-22" + }, + "description": "The Tracer Analysis Toolbox (TAT) is a stand-alone executable software package that focuses on reservoir monitoring, using changes in concentration of thermally degrading tracers between and injection well and a production well to reflect the temperature-time histories along flow paths through the reservoir. By conducting such tests periodically, the thermal evolution of the flow paths connecting injection wells to production wells can be monitored. Because this approach is sensitive to temperature along the whole path, it can detect changes well before they occur at the distal end of the path (i.e., the production well). Thus, the thermally degrading tracer method provides early detection of thermal decline before it impacts that well.\nThe goal of TAT is to simplify planning of a reactive tracer monitoring campaign and interpretation of results by providing: (1) tracer test planning and analysis tools to define the necessary kinetic parameters, injection concentrations, and other tracer parameters that are suitable for the expected reservoir residence time and temperature, (2) identification of tracers with suitable characteristics (defined by (1)) and (3) a suite of analysis programs to analyze tracer test results.", + "laborHours": 2644.8, + "languages": [ + "MATLAB" + ], + "name": "Computer Programs For Analysis Of Thermally Reactive Tracer Tests In Geothermal Reservoirs", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/Tracer_Analysis_Toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ConMan:_The_Console_Manager.json b/agency-indexes/DoE/ConMan:_The_Console_Manager.json new file mode 100644 index 00000000..73c7ef44 --- /dev/null +++ b/agency-indexes/DoE/ConMan:_The_Console_Manager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "ConMan is a serial console management program designed to support a large number of console devices and simultaneous users.", + "laborHours": 8527.2, + "languages": [], + "name": "ConMan: The Console Manager", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dun/conman", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Concentric_Spherical_GNN_for_3D_Representation_Learning.json b/agency-indexes/DoE/Concentric_Spherical_GNN_for_3D_Representation_Learning.json new file mode 100644 index 00000000..d316c227 --- /dev/null +++ b/agency-indexes/DoE/Concentric_Spherical_GNN_for_3D_Representation_Learning.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-09", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SAND2022-1325 O This codebase implements a new deep learning model for 3D representation learning. It includes experiments on open-source point cloud and 3D mesh datasets, namely ModelNet40 and ShapeNet. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1109.6, + "languages": [ + "Python" + ], + "name": "Concentric Spherical GNN for 3D Representation Learning", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/CSNN", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Concepts_and_Meta-Programming_Library.json b/agency-indexes/DoE/Concepts_and_Meta-Programming_Library.json new file mode 100644 index 00000000..6367234e --- /dev/null +++ b/agency-indexes/DoE/Concepts_and_Meta-Programming_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-09-19", + "metadataLastUpdated": "2018-09-19" + }, + "description": "CAMP provides a portable optimized implementation of template meta-programming primitives. All capabilities found within are available in other open source \nprojects, including metal and mpl among others, but no other library we know of supports all compilers required by LLNL codes. CAMP serves as an efficient facility for writing portable compile-time operations in C++ codes. It was \ndeveloped as part of the RAJA project to facilitate more complex compile-time introspection and better error message delivery to users, but has since proven useful in Umpire, CHAI and other pre-release LLNL software projects and is thus being re-factored to stand alone. \n\nThe CAMP library uses portable C++ template mechanisms almost exclusively, with the exception of intrinsics provided for performance by some compilers such as clang and gee. There are no private or protected interfaces and no proprietary information included in the source.\n\nAny and all future versions will limit themselves to implementing commonly available and well known primitives for compile-time manipulation of types.\n \nA new public github repository will be created to host the code independent of its current location in the raja repository, likely at github.com/llnl/camp. \n \n", + "laborHours": 22708.8, + "languages": [], + "name": "Concepts and Meta-Programming Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/raja", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Concordance.json b/agency-indexes/DoE/Concordance.json new file mode 100644 index 00000000..13598e5f --- /dev/null +++ b/agency-indexes/DoE/Concordance.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "Dimension reduction techniques have long been an important topic in statistics, and active subspaces (AS) have received much attention this past decade in the computer experiments literature. The most common approach towards estimating the AS is to use Monte Carlo with numerical gradient evaluation. This software takes a new approach towards estimating the active subspace, in which Multivariate Adaptive Regression Splines (MARS) is used as a surrogate model, and relevant calculation are obtained analytically. Using a MARS surrogate has many advantages including improved scaling, better estimation of active subspaces in high dimensions and the ability to handle a large number of prior distributions in closed form. This software is also capable of conducting a so-called \"concordance analysis\", using a generalization of ASs which we refer to as \"Co-Active\" subspaces. ", + "laborHours": 0.0, + "languages": [], + "name": "Concordance", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/knrumsey-lanl/concordance", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Concurrent_Relaxation_through_Accelerated_Deep_Learning.json b/agency-indexes/DoE/Concurrent_Relaxation_through_Accelerated_Deep_Learning.json new file mode 100644 index 00000000..f13dc117 --- /dev/null +++ b/agency-indexes/DoE/Concurrent_Relaxation_through_Accelerated_Deep_Learning.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "CRADL captures performance metrics of machine learning algorithms operating on mesh data from multiphysics\ncodes This proxy application is a tool to explore scalability of inference on HPC platforms, and also gather performance metrics for inference on new machine learning specific hardware. CRADL is designed to give users as fine a control as possible over an inference simulation. Users may\nselect the number of cycles, amount of data, and batch size to pass to the accelerator of choice. Additionally the user may select a number of performance optimization libraries and flags. CRADL comes packaged with a repository of anonymized multi-physics simulation data, as well as a\npretrained model for inference. The code allows a user to load their own pre-trained model and data if they wish. The code can operate in multiple parallelization schemes, with performance enhancing options such as half-precision libraries, PyTorch benchmarking, and pinned memory with non-blocking data transfers.\n", + "laborHours": 0.0, + "languages": [], + "name": "Concurrent Relaxation through Accelerated Deep Learning", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CRADL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ConditionSetUtils.json b/agency-indexes/DoE/ConditionSetUtils.json new file mode 100644 index 00000000..2faa1c61 --- /dev/null +++ b/agency-indexes/DoE/ConditionSetUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "This is the repository for \"ConditionSetUtils\" developed by KBase. A KBase module generated by the KBase SDK.", + "laborHours": 760.0, + "languages": [], + "name": "ConditionSetUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ConditionSetUtils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ConditionUtils.json b/agency-indexes/DoE/ConditionUtils.json new file mode 100644 index 00000000..6617bfcf --- /dev/null +++ b/agency-indexes/DoE/ConditionUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "This is the repository for \"ConditionUtils\" developed by KBase. A KBase module generated by the KBase SDK.", + "laborHours": 2340.8, + "languages": [], + "name": "ConditionUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ConditionUtils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Conditional_latent_autoregressive_recurrent_model__CLARM_.json b/agency-indexes/DoE/Conditional_latent_autoregressive_recurrent_model__CLARM_.json new file mode 100644 index 00000000..318c7ff3 --- /dev/null +++ b/agency-indexes/DoE/Conditional_latent_autoregressive_recurrent_model__CLARM_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "It is a machine learning code written in python. The code is an inherent part of a paper (#LA-UR-24-22420). The code is required to be available on github as a part of paper submission process in the journal.", + "laborHours": 1079.2, + "languages": [], + "name": "Conditional latent autoregressive recurrent model (CLARM)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/clarm", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ConductorIdentification_[SWR-21-58].json b/agency-indexes/DoE/ConductorIdentification_[SWR-21-58].json new file mode 100644 index 00000000..1c497641 --- /dev/null +++ b/agency-indexes/DoE/ConductorIdentification_[SWR-21-58].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-02-16", + "metadataLastUpdated": "2024-12-19" + }, + "description": "This is a novel data-driven model that can identify power system model impedance for local utilities. The model builds a multi-category logistic regression that is trained on local utility secondary system partial GIS data, and then the model can be used to predict the conductor types/impedance for the local utilities secondary models.", + "laborHours": 0.0, + "languages": [ + "jupyter" + ], + "name": "ConductorIdentification [SWR-21-58]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ConductorIdentification", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Conduit_-_Scientific_Data_Exchange_Library_for_HPC_Simulations.json b/agency-indexes/DoE/Conduit_-_Scientific_Data_Exchange_Library_for_HPC_Simulations.json new file mode 100644 index 00000000..0ce3653c --- /dev/null +++ b/agency-indexes/DoE/Conduit_-_Scientific_Data_Exchange_Library_for_HPC_Simulations.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Conduit is a C++ software library that helps software developers with data representation and data exchange in scientific simulations", + "laborHours": 94012.0, + "name": "Conduit - Scientific Data Exchange Library for HPC Simulations", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/conduit/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/conduit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Confronting_Domain_Shift_in_Trained_Neural_Networks.json b/agency-indexes/DoE/Confronting_Domain_Shift_in_Trained_Neural_Networks.json new file mode 100644 index 00000000..922ae413 --- /dev/null +++ b/agency-indexes/DoE/Confronting_Domain_Shift_in_Trained_Neural_Networks.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2024-09-09" + }, + "description": "SAND2021-15138 O\nThis code accompanies a paper published in the Proceedings of Machine Learning Research (PMLR), \u201cConfronting Domain Shift in Trained Neural Networks.\u201d Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 319.2, + "languages": [ + "Python" + ], + "name": "Confronting Domain Shift in Trained Neural Networks", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/confronting_domain_shift", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Conjoin.json b/agency-indexes/DoE/Conjoin.json new file mode 100644 index 00000000..96876160 --- /dev/null +++ b/agency-indexes/DoE/Conjoin.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "Conjoin is a code for joining sequentially in time multiple exodusII database files. It is used to create a single results or restart file from multiple results or restart files which typically arise as the result of multiple restarted analyses. The resulting output file will be the union of the input files with a status variable indicating the status of each element at the various time planes.Combining multiple exodusII files arising from a restarted analysis or combining multiple exodusII files arising from a finite element analysis with dynamic topology changes.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "Conjoin", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ConnectIt:_A_Framework_for_Static_and_Incremental_Parallel_Graph_Connectivity_Algorithms.json b/agency-indexes/DoE/ConnectIt:_A_Framework_for_Static_and_Incremental_Parallel_Graph_Connectivity_Algorithms.json new file mode 100644 index 00000000..bb489085 --- /dev/null +++ b/agency-indexes/DoE/ConnectIt:_A_Framework_for_Static_and_Incremental_Parallel_Graph_Connectivity_Algorithms.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nLaxman Dhulipala, Changwan Hong, and Julian Shun.\nConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms.\nProceedings of the VLDB Endowment, 14(4), pp. 653-667, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "ConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Connectivity:_Performance_Portable_Algorithms_for_graph_connectivity_v._0.1.json b/agency-indexes/DoE/Connectivity:_Performance_Portable_Algorithms_for_graph_connectivity_v._0.1.json new file mode 100644 index 00000000..adf93c42 --- /dev/null +++ b/agency-indexes/DoE/Connectivity:_Performance_Portable_Algorithms_for_graph_connectivity_v._0.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Graphs occur in several places in real world from road networks, social networks and scientific simulations. Connectivity is a graph analysis software to graph connectivity in modern architectures like multicore CPUs, Xeon Phi and GPUs.", + "laborHours": 2796.8, + "languages": [ + "C++" + ], + "name": "Connectivity: Performance Portable Algorithms for graph connectivity v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Connectivity", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Conservative_Remapper.json b/agency-indexes/DoE/Conservative_Remapper.json new file mode 100644 index 00000000..dac7a2c1 --- /dev/null +++ b/agency-indexes/DoE/Conservative_Remapper.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Conservative Remapper (CORE) is a C++ language software library for remapping cell masses and cell-averaged densities on unstructured two dimensional grids, maintaining conservation of total mass in the process. CORE contains implementation of two remapping algorithms: a new, efficient \"swept region\" algorithm, and a more traditional algorithm basedon the computation of cell intersections. Grids may be Cartesian or cylindrical, and cells may have three or more vertices, with no upper limit. CORE can run in serial and in parallel, but in order to achieve wide applicability, CORE used no particular parallel communication library. Instead it achieves parallel communication through strategically placed, user defined callbacks. Users can also provide callbacks to redefine different parts or subcomponents of the remapping process. CORE allows the use of different data types, e.g. single-, double-, and quadruple- precision floating-point numbers, through the use of C++ templates. Using CORE is simple, and requires no configuration scripts or makefiles.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "Any ANSI-compliant C++ compiler" + ], + "name": "Conservative Remapper", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Consistent_Space_Runtime__CSPACER__v1.0.json b/agency-indexes/DoE/Consistent_Space_Runtime__CSPACER__v1.0.json new file mode 100644 index 00000000..252e4fb3 --- /dev/null +++ b/agency-indexes/DoE/Consistent_Space_Runtime__CSPACER__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-29", + "metadataLastUpdated": "2021-03-31" + }, + "description": "This software provides a runtime for communication-bound applications, especially with irregular communication patterns. The target programming abstraction for the runtime is the space consistency model, which defines consistency guarantees at the granularity of memory spaces. This model has relaxed consistency semantics that enables a wide range of runtime optimizations. The runtime leverages threading to accelerate communication primitives, especially collective operations. It also allows efficient pipelining of communication operations and enable constructing a consistent state of multiple unordered communication activities targeting a memory space. The runtime uses a reduced API design that decomposes complex communication primitives in traditional general-purpose runtime into a sequence of simpler steps.\n\nTo improve the productivity of using this runtime, we provide communication patterns commonly used for regular scientific computing applications and irregular data analytics. These communication patterns offer skeletons for the integration with application computation to allow efficient overlap.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Consistent Space Runtime (CSPACER) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Constitutive_Models_via_Automatic_Differentiation_v.1.0.0.json b/agency-indexes/DoE/Constitutive_Models_via_Automatic_Differentiation_v.1.0.0.json new file mode 100644 index 00000000..fc710aa4 --- /dev/null +++ b/agency-indexes/DoE/Constitutive_Models_via_Automatic_Differentiation_v.1.0.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-06", + "metadataLastUpdated": "2024-06-06" + }, + "description": "SAND2024-00905O\nConstitutive Models via Automatic Differentiation (CMAD) provides a software framework for solving constitutive or material model calibration problems. It relies on JAX's automatic differentiation capabilities to compute the derivatives needed for both forward and adjoint sensitivity analyses. The software can be used to implement constitutive models and calibrate the parameters from experimental data. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1550.4, + "languages": [ + "Python" + ], + "name": "Constitutive Models via Automatic Differentiation v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cmad", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Constructing_Hardware_in_a_Scale_Embedded_Language.json b/agency-indexes/DoE/Constructing_Hardware_in_a_Scale_Embedded_Language.json new file mode 100644 index 00000000..10b31c70 --- /dev/null +++ b/agency-indexes/DoE/Constructing_Hardware_in_a_Scale_Embedded_Language.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Chisel is a new open-source hardware construction language developed at UC Berkeley that supports advanced hardware design using highly parameterized generators and layered domain-specific hardware languages. Chisel is embedded in the Scala programming language, which raises the level of hardware design abstraction by providing concepts including object orientation, functional programming, parameterized types, and type inference. From the same source, Chisel can generate a high-speed C++-based cycle-accurate software simulator, or low-level Verilog designed to pass on to standard ASIC or FPGA tools for synthesis and place and route.", + "laborHours": 16233.6, + "name": "Constructing Hardware in a Scale Embedded Language", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ucb-bar/chisel/blob/master/src/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ucb-bar/chisel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Contact_Control,_Version_1.json b/agency-indexes/DoE/Contact_Control,_Version_1.json new file mode 100644 index 00000000..cbf5d633 --- /dev/null +++ b/agency-indexes/DoE/Contact_Control,_Version_1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The contact control code is a generalized force control scheme meant to interface with a robotic arm being controlled using the Robot Operating System (ROS). The code allows the user to specify a control scheme for each control dimension in a way that many different control task controllers could be built from the same generalized controller. The input to the code includes maximum velocity, maximum force, maximum displacement, and a control law assigned to each direction and the output is a 6 degree of freedom velocity command that is sent to the robot controller.", + "laborHours": 7174.4, + "name": "Contact Control, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/UTNuclearRoboticsPublic/contact_control/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/UTNuclearRoboticsPublic/contact_control", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ContainerRunner.json b/agency-indexes/DoE/ContainerRunner.json new file mode 100644 index 00000000..2f5d56f7 --- /dev/null +++ b/agency-indexes/DoE/ContainerRunner.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "Unittest based module that runs docker containers and examines the output/exit codes to determine success or failure.", + "laborHours": 152.0, + "languages": [], + "name": "ContainerRunner", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/ContainerRunner", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Container_Security_-_part_of_the_CORE_system.json b/agency-indexes/DoE/Container_Security_-_part_of_the_CORE_system.json new file mode 100644 index 00000000..b3d77b34 --- /dev/null +++ b/agency-indexes/DoE/Container_Security_-_part_of_the_CORE_system.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "A data integration system to support the US Customs and Border Protection Officers to supervise and make decisions for container inspections. CORE is designed to act as a framework to bridge the gaps between disparate data integration and delivery of disparate information visualization.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Container Security - part of the CORE system", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Content_Model_Guidelines.json b/agency-indexes/DoE/Content_Model_Guidelines.json new file mode 100644 index 00000000..c07b0d2b --- /dev/null +++ b/agency-indexes/DoE/Content_Model_Guidelines.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This wiki page provides the public with all specifications needed to create a new spreadsheet (workbook) implementation of an information exchange, so that it conforms and functions properly with NGDS validation tools.", + "laborHours": 4636.0, + "name": "Content Model Guidelines", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/ContentModelCMS/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/ContentModelCMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Content_Model_Validator.json b/agency-indexes/DoE/Content_Model_Validator.json new file mode 100644 index 00000000..ce567154 --- /dev/null +++ b/agency-indexes/DoE/Content_Model_Validator.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is a Python API for interacting with USGIN Content Models.", + "laborHours": 4636.0, + "name": "Content Model Validator", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/ContentModelCMS/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/ContentModelCMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ContigFilter.json b/agency-indexes/DoE/ContigFilter.json new file mode 100644 index 00000000..d4d31535 --- /dev/null +++ b/agency-indexes/DoE/ContigFilter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "An example app that filters out contigs that are smaller than a minimum length from an assembly.", + "laborHours": 699.2, + "languages": [], + "name": "ContigFilter", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ContigFilter", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Contingency_Base_Energy_Management_System.json b/agency-indexes/DoE/Contingency_Base_Energy_Management_System.json new file mode 100644 index 00000000..167f360b --- /dev/null +++ b/agency-indexes/DoE/Contingency_Base_Energy_Management_System.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "CB-EMS is the latest implementation of DSOM (Decision Support for Operations and Maintenance), which was previously patented by PNNL. CB-EMS WAS specifically designed for contingency bases for the US Army. It is a software package that is designed to monitor energy consumption at an Army contingency base to alert the camp manager when the systems are wasting energy. It's main feature that separates it from DSOM is it's ability to add systems using a plug and play menu system.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Contingency Base Energy Management System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Continous_Improvement_testbot__CI-bot_.json b/agency-indexes/DoE/Continous_Improvement_testbot__CI-bot_.json new file mode 100644 index 00000000..631d0848 --- /dev/null +++ b/agency-indexes/DoE/Continous_Improvement_testbot__CI-bot_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "This repository contains all the code necessary to create a new CI service. It has support for GitHub statuses and uses GitHub wiki for commit test logs.", + "laborHours": 304.0, + "languages": [], + "name": "Continous Improvement testbot (CI-bot)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/ci-bots", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Continous_Representation_Learning_via_User_Feedback.json b/agency-indexes/DoE/Continous_Representation_Learning_via_User_Feedback.json new file mode 100644 index 00000000..d92c96bf --- /dev/null +++ b/agency-indexes/DoE/Continous_Representation_Learning_via_User_Feedback.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Representation learning is a deep-learning based technique for extracting features from data for the purpose of machine learning. This requires a large amount of data, on order tens of thousands to millions of samples, to properly teach the deep neural network. This a system for continuous representation learning, where the system may be improved with a small number of additional samples (order 10-100). The unique characteristics of this invention include a human-computer feedback component, where assess the quality of the current representation and then provides a better representation to the system. The system then mixes the new data with old training examples to avoid overfitting and improve overall performance of the system. The model can be exported and shared with other users, and it may be applied to additional images the system hasn't seen before.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "multi" + ], + "name": "Continous Representation Learning via User Feedback", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Continual_Load_Modelling.json b/agency-indexes/DoE/Continual_Load_Modelling.json new file mode 100644 index 00000000..1852888e --- /dev/null +++ b/agency-indexes/DoE/Continual_Load_Modelling.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-07-29", + "metadataLastUpdated": "2024-07-29" + }, + "description": "Lack of harmonic rich datasets limits the ability to have fine grained load models at grid edge. We aim to develop\nmathematical models for power electronic based load combinations at grid edge to help replicate current and future\nevolving load conditions", + "laborHours": 30.4, + "languages": [], + "name": "Continual Load Modelling", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Continual-Load-Modelling-HELM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Continuous-Time_Models_for_Longitudinal_Data.json b/agency-indexes/DoE/Continuous-Time_Models_for_Longitudinal_Data.json new file mode 100644 index 00000000..22344a99 --- /dev/null +++ b/agency-indexes/DoE/Continuous-Time_Models_for_Longitudinal_Data.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-06-20", + "metadataLastUpdated": "2023-06-20" + }, + "description": "This software is used to estimate a probabilistic continuous-time model from data. The models capture\nnonlinear associations between variables that change over time. They can be used to infer future values\nof variables. These tools were used in the manuscript entitled \"Continuous-Time Probabilistic Models for\nLongitudinal Electronic Health Records.\"", + "laborHours": 0.0, + "languages": [], + "name": "Continuous-Time Models for Longitudinal Data", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/alankaplan/CTMLD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Continuum_Gyrokinetic_Edge_New_Technology.json b/agency-indexes/DoE/Continuum_Gyrokinetic_Edge_New_Technology.json new file mode 100644 index 00000000..a551bc45 --- /dev/null +++ b/agency-indexes/DoE/Continuum_Gyrokinetic_Edge_New_Technology.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "COGENT is a simulation code that models the plasma evolution in the edge region of a tokamak fusion reactor, from the open field line scrape-off layer, across the separatrix, and into the core. The model is based on the 4D gyrokinetic closure of the kinetic equations for a plasma coupled to an electrostatic potential field. The background magnetic field is prescribed either analytically or generated from experimental data, and the grid is aligned with magnetic flux surfaces. Multiple collision operator options are provided, from Krook to fully nonlinear Fokker-Planck.", + "laborHours": 1019479.2, + "name": "Continuum Gyrokinetic Edge New Technology", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/COGENT/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/cogent", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Contra.json b/agency-indexes/DoE/Contra.json new file mode 100644 index 00000000..2e66cce2 --- /dev/null +++ b/agency-indexes/DoE/Contra.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-05-10", + "metadataLastUpdated": "2022-05-10" + }, + "description": "written in Contra can run without modification on a variety of parallel runtimes. Currently supported parallel runtimes include: MPI, Legion, CUDA, AMD ROCm/HIP, and PThreads.", + "laborHours": 0.0, + "languages": [], + "name": "Contra", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/contra", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Contraction_Optimizer_v1.0.json b/agency-indexes/DoE/Contraction_Optimizer_v1.0.json new file mode 100644 index 00000000..d9509d03 --- /dev/null +++ b/agency-indexes/DoE/Contraction_Optimizer_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-15", + "metadataLastUpdated": "2019-10-15" + }, + "description": "Code to perform operation count minimization for the evaluation of a large number of tensor contractions. A possible application is the efficient evaluation of correlation functions in lattice QCD calculations, where a reduction of computational complexity by an order of magnitude is achieved", + "laborHours": 364.8, + "languages": [], + "name": "Contraction Optimizer v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laphnn/contraction_optimizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Contribute_to_VOTCA_package.json b/agency-indexes/DoE/Contribute_to_VOTCA_package.json new file mode 100644 index 00000000..afb54f60 --- /dev/null +++ b/agency-indexes/DoE/Contribute_to_VOTCA_package.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-06" + }, + "description": "Versatile Object-oriented Toolkit for Coarse-graining Applications (VOTCA) is a Coarse-grained modeling package, which focuses on the analysis of molecular dynamics data, the development of systematic coarse-graining techniques as well as methods used for simulating microscopic charge (and exciton) transport in disordered semiconductors. It was originally developed at the Max Planck Institute for Polymer Research. VOTCA has 2 major parts, the Coarse-graining toolkit (VOTCA-CSG) and the Excitation Transport Toolkit (VOTCA-XTP). All of them are based on the VOTCA Tools library, which implements shared procedures. Coarse-graining toolkit (VOTCA-CSG) VOTCA-CSG supports a variety of different coarse-graining methods, incl. (iterative) Boltzmann Inversion, Inverse Monte Carlo, Force Matching (also known as the multiscale coarse-graining method) and the Relative entropy method and hybrid combinations of those as well as optimization-driven approaches, like simplex and CMA. To gather statistics VOTCA-CSG can use multiple molecular dynamics package incl. GROMACS, DL_POLY, ESPResSo, ESPResSo++, LAMMPS and HOOMD-blue for sampling. Excitation Transport toolkit (VOTCA-XTP) VOTCA-XTP allows to simulate excitation transport and properties. Therefore, it provides its own implementation of GW-BSE and a basic DFT implementation, employing localized basis sets. Polarized QM/MM calculations for excited states are provided in the Thole framework. It features interfaces to more external Quantum Chemistry packages (Gaussian, NWChem and ORCA) for large scale production runs.", + "laborHours": 0.0, + "languages": [], + "name": "Contribute to VOTCA package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/votca/votca", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Contributing_to_Sunny_open_source_code.json b/agency-indexes/DoE/Contributing_to_Sunny_open_source_code.json new file mode 100644 index 00000000..08adcf8c --- /dev/null +++ b/agency-indexes/DoE/Contributing_to_Sunny_open_source_code.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2022-07-15" + }, + "description": "The Sunny package is an existing open source software to support the simulation of magnetic spin systems. It is available online under the MIT license here: https://github.com/SunnySuite/Sunny.jl The package aims to include the following features: - Analysis for symmetry-allowed interactions - Monte Carlo algorithms for simulating equilibrium configurations. - Schemes for integrating spin dynamics. - Inference of model Hamiltonians - Support for generalized SU(N) spins - Tools for interpreting experimental data, such as diffraction data, magnetization curves, and heat capacity data", + "laborHours": 0.0, + "languages": [], + "name": "Contributing to Sunny open source code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SunnySuite/Sunny.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Contribution_to_Open_Source_Software_BdNMC.json b/agency-indexes/DoE/Contribution_to_Open_Source_Software_BdNMC.json new file mode 100644 index 00000000..e24e7f62 --- /dev/null +++ b/agency-indexes/DoE/Contribution_to_Open_Source_Software_BdNMC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-19" + }, + "description": "BdNMC is a Monte Carlo that simulates the creation, propagation and detection of dark sector particles in particle physics experiments. Dark sector particles are defined as any particles which are weakly coupled to matter and are expected to travel large distances in matter without interaction. The code takes input from some initial distribution or list of Standard Model particles and generates a list of dark sector particles. The generated dark sector particles are propagated to a defined detector volume, where they are then checked for their probability to interact with the detector through either decay or scattering. The code outputs an expected number of interaction events to the user, and may optionally produce an additional output file of all of the particles simulated by the code for each interaction event. This contribution makes corrections and updates to several of the physics formulas and functions implemented in the BdNMC simulation code related to Coherent Captain Mills experiment's physics analyses.", + "laborHours": 0.0, + "languages": [], + "name": "Contribution to Open Source Software BdNMC", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/BdNMC_LANL", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Contributions_to_MoDELib_SOFTWARE.json b/agency-indexes/DoE/Contributions_to_MoDELib_SOFTWARE.json new file mode 100644 index 00000000..62f5288a --- /dev/null +++ b/agency-indexes/DoE/Contributions_to_MoDELib_SOFTWARE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-05" + }, + "description": "The purpose of the current request is to enable LANL employees to contribute computer source code to the existing public repository of the MoDELib software package. This software implements discrete dislocation dynamics (DDD) and finite element (FEM) methods and is currently a vital component of an ongoing DR project at LANL, in collaboration with its original author and maintainer Giacomo Po. Contributions from LANL employees would aim to enhance the reliability, accuracy, and performance of MoDELib simulations using LANL's high performance computing platforms through bug fixes, algorithmic refinements, and parallelization.", + "laborHours": 0.0, + "languages": [], + "name": "Contributions to MoDELib SOFTWARE", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nickjulian-LANL/MoDELib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Contributions_to_pFUnit.json b/agency-indexes/DoE/Contributions_to_pFUnit.json new file mode 100644 index 00000000..4a196a6f --- /dev/null +++ b/agency-indexes/DoE/Contributions_to_pFUnit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This software consists of LANL contributions to the pFUnit unit testing framework, developed and copyrighted by NASA/Goddard Space Flight Center.\n\npFUnit is a unit testing framework enabling JUnit-like testing of serial and MPI-parallel software written in Fortran. The LANL contributions will consist of adding support for new platforms/compilers not currently supported (including IBM XL and Cray), and fixing bugs found in the process.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Contributions to pFUnit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/NASA-1.3", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Control_Algorithms_for_Multi-Wavefront_Sensor_Adaptive_Optics_for_Astronomical_Exoplanet_Imaging.json b/agency-indexes/DoE/Control_Algorithms_for_Multi-Wavefront_Sensor_Adaptive_Optics_for_Astronomical_Exoplanet_Imaging.json new file mode 100644 index 00000000..9ebacbf5 --- /dev/null +++ b/agency-indexes/DoE/Control_Algorithms_for_Multi-Wavefront_Sensor_Adaptive_Optics_for_Astronomical_Exoplanet_Imaging.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-10-16", + "metadataLastUpdated": "2024-10-16" + }, + "description": "This package consists of simulations of control algorithms being proposed for upcoming adaptive optics\nprojects for exoplanet direct imaging, in which one wavefront affector (deformable mirror) is controlled by\ntwo wavefront sensors. Simulations include time-domain behavior under various assumed conditions,\nparameter optimization routines for the controllers, and stability analysis.", + "laborHours": 2295.2, + "languages": [], + "name": "Control Algorithms for Multi-Wavefront Sensor Adaptive Optics for Astronomical Exoplanet Imaging", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/multiwfs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Conversion_Helper_4_Easy_Serialization_Of_Exi__ch4ese_.json b/agency-indexes/DoE/Conversion_Helper_4_Easy_Serialization_Of_Exi__ch4ese_.json new file mode 100644 index 00000000..7c28f8c2 --- /dev/null +++ b/agency-indexes/DoE/Conversion_Helper_4_Easy_Serialization_Of_Exi__ch4ese_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-11-06", + "metadataLastUpdated": "2024-11-06" + }, + "description": "CH4ESE is an EXI conversion tool developed in Python3 that utilizes the open-source EXIficient implementation of the W3C EXI format specification. CH4ESE can be used to translate to and from EXI format using the command line with input data or using the web server for live-translation.", + "laborHours": 1580.8, + "languages": [ + "Python" + ], + "name": "Conversion Helper 4 Easy Serialization Of Exi (ch4ese)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/CH4ESE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Convert_XML_to_VTK.json b/agency-indexes/DoE/Convert_XML_to_VTK.json new file mode 100644 index 00000000..52a29aee --- /dev/null +++ b/agency-indexes/DoE/Convert_XML_to_VTK.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-01-05", + "metadataLastUpdated": "2022-01-05" + }, + "description": "Converts XML format files to VTK format files for visualization of 3D printing.", + "laborHours": 0.0, + "languages": [], + "name": "Convert XML to VTK", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CLDruzgalski/AM_fileConverters", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "000" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Convex_methods_for_physics.json b/agency-indexes/DoE/Convex_methods_for_physics.json new file mode 100644 index 00000000..6ad1002b --- /dev/null +++ b/agency-indexes/DoE/Convex_methods_for_physics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "Software for performing calculations of physical systems, both equilibrium and dynamical, using convex constraints.", + "laborHours": 425.6, + "languages": [], + "name": "Convex methods for physics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/concave", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Conveyor_LC.json b/agency-indexes/DoE/Conveyor_LC.json new file mode 100644 index 00000000..94083cf9 --- /dev/null +++ b/agency-indexes/DoE/Conveyor_LC.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-07", + "metadataLastUpdated": "2018-03-20" + }, + "description": "ConveyorLC is a high throughput virtual screening pipeline for in-silico screening of virtual compound databases using high performance computing. The pipeline mainly includes four modules: receptor/target preparation, ligand preparation, VinaLC docking calculation, and molecular mechanics/generalized Born surface area rescoring.", + "laborHours": 68932.0, + "name": "Conveyor LC", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/XiaohuaZhangLLNL/conveyorlc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Convolution_Neural_Network_for_Fault_Identification_in_Distribution_Feeder_with_High_Penetration_Solar_PV.json b/agency-indexes/DoE/Convolution_Neural_Network_for_Fault_Identification_in_Distribution_Feeder_with_High_Penetration_Solar_PV.json new file mode 100644 index 00000000..58cf7197 --- /dev/null +++ b/agency-indexes/DoE/Convolution_Neural_Network_for_Fault_Identification_in_Distribution_Feeder_with_High_Penetration_Solar_PV.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Identification and zonal classification of the faults is a decisive factor in the relay\u2019s decision to trip or not. Different types of\nfault like three-phase, line-to-line-to-ground and single-line-to-ground can occur at various locations in the feeder. These\nfaults are seen as the variation in the instantaneous values of three-phase voltages and currents, i.e., waveforms, that are\nmeasured at the relay location. The objective of this work is to develop a machine learning model that can\nidentify a fault and classify it to various protection zones based on measured waveforms. In this work, a data-driven relay\nbased on Convolutional Neural Network (CNN) is proposed for fault identification in distribution feeders with high\npenetration solar PV. The proposed CNN model takes local current and voltage waveforms as input and classify it into\nfault, no-fault or a capacitor switching. Further, the CNN also attempts to identify fault zones based on the images of\nwaveforms. The overall testing accuracy of the trained model exceeds 95%.", + "laborHours": 60.8, + "languages": [], + "name": "Convolution Neural Network for Fault Identification in Distribution Feeder with High Penetration Solar PV", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/DPVCNN", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CoolCalc_[SWR-09-39].json b/agency-indexes/DoE/CoolCalc_[SWR-09-39].json new file mode 100644 index 00000000..5a936854 --- /dev/null +++ b/agency-indexes/DoE/CoolCalc_[SWR-09-39].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-12-19" + }, + "description": "CoolCalc simulates energy used for climate control in truck cabs and assesses the impact of thermal load-reduction technologies. Researchers can calculate the potential benefits of thermal load reduction options in a range of use and weather scenarios. CoolCalc is built on NREL's original OpenStudio development and is a plug-in extension of Trimble's SketchUp software. DOE's EnergyPlus program is used as the heat transfer equation solver. The tool's graphical user interface makes it possible for industry partners to quickly determine the impact of thermal load-reduction strategies. CoolCalc allows parametric trade-off studies to rapidly evaluate the impact of design factors (such as insulation thickness, material properties, and geometries) on HVAC loads. For more information on how to become a CoolCalc partner and access the tool download, contact Jason Lustbader.", + "homepageURL": "https://www.nrel.gov/transportation/vtm-models-tools.html", + "laborHours": 0.0, + "languages": [], + "name": "CoolCalc [SWR-09-39]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/transportation/vtm-models-tools.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/transportation/vtm-models-tools.html", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Coopr_Forum_v_1.0.json b/agency-indexes/DoE/Coopr_Forum_v_1.0.json new file mode 100644 index 00000000..88788f2d --- /dev/null +++ b/agency-indexes/DoE/Coopr_Forum_v_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SNL Coopr Forum is a set of Python routines that provide extensions to the Coopr optimization software. This software augments the open-source Coopr project to provide a more comprehensive capability for formulating and solving optimization applications.Optimization is a common analysis tool used in engineering design and scientific discovery. The SNL Coopr Forum software augments the Coopr Forum open source project to provide extensions of the Coopr optimization framework. Specifically, Coopr Forum provides plugin tools that allow Coopr to apply different optimization solvers, manage optimization solvers in a distributed manner, and to process input and output files. Thus, Coopr Forum is comprised of a variety of distinct software components, each of which provides a different capability that can be used within Coopr.", + "laborHours": 314837.6, + "name": "Coopr Forum v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pyomo/pyomo", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Coordinate_Projection-based_Solver_for_ODE_with_Invariants.json b/agency-indexes/DoE/Coordinate_Projection-based_Solver_for_ODE_with_Invariants.json new file mode 100644 index 00000000..c2767fac --- /dev/null +++ b/agency-indexes/DoE/Coordinate_Projection-based_Solver_for_ODE_with_Invariants.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "CPODES is a general purpose (serial and parallel) solver for systems of ordinary differential equation (ODE) with invariants. It implements a coordinate projection approach using different types of projection (orthogonal or oblique) and one of several methods for the decomposition of the Jacobian of the invariant equations.", + "homepageURL": "https://simtk.org/projects/cpodes", + "laborHours": 0.0, + "languages": [], + "name": "Coordinate Projection-based Solver for ODE with Invariants", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://simtk.org/projects/cpodes", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Copson_Expansion_Solution.json b/agency-indexes/DoE/Copson_Expansion_Solution.json new file mode 100644 index 00000000..75c69750 --- /dev/null +++ b/agency-indexes/DoE/Copson_Expansion_Solution.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-31", + "metadataLastUpdated": "2020-01-31" + }, + "description": "Evaluate Copson's solution for the free expansion of an ideal gas into vacuum. \n\nThe solution for streamlines and characteristics are given along with a way to evaluate the solution for any (x,t) location.", + "laborHours": 334.4, + "languages": [], + "name": "Copson Expansion Solution", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/copson_expansion_solution", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Coramin_v._0.1_Beta.json b/agency-indexes/DoE/Coramin_v._0.1_Beta.json new file mode 100644 index 00000000..d3f42af2 --- /dev/null +++ b/agency-indexes/DoE/Coramin_v._0.1_Beta.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-11", + "metadataLastUpdated": "2019-03-12" + }, + "description": "Coramin is a package that provides tools for developing tailored algorithms for mixed-integer nonlinear programming problems. This software includes the ability to:\n- Generate convex or piecewise relaxations of nonlinear optimization problems, addressing bilinear, quadratic, and convex/concave univariate functions\n- Perform optimization-based bounds tightening on all or subsets of the problem variables\n- Generate polyhedral envelopes for multi-linear functions", + "laborHours": 2006.4, + "languages": [ + "Python" + ], + "name": "Coramin v. 0.1 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Coramin/Coramin", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Core-Collapse_Supernova_Code_with_New_Convection_Algorithms.json b/agency-indexes/DoE/Core-Collapse_Supernova_Code_with_New_Convection_Algorithms.json new file mode 100644 index 00000000..3118353b --- /dev/null +++ b/agency-indexes/DoE/Core-Collapse_Supernova_Code_with_New_Convection_Algorithms.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The software in development is a model of convection to be added to a public domain 1-dimensional supernova code. The supernova code models the collapse and explosion of stars. Without a convection module, the 1-dimensional code does not include the effects of convection under an entropy gradient. The modules that will be integrated into this code will calculate this convection.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Core-Collapse Supernova Code with New Convection Algorithms", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CoreServicesIntegrationTests.json b/agency-indexes/DoE/CoreServicesIntegrationTests.json new file mode 100644 index 00000000..a0674e0c --- /dev/null +++ b/agency-indexes/DoE/CoreServicesIntegrationTests.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This is the repository for \"CoreServicesIntegrationTests\" developed by KBase. A KBase module generated by the KBase SDK.", + "laborHours": 349.6, + "languages": [], + "name": "CoreServicesIntegrationTests", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/CoreServicesIntegrationTests", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Correcting_for_reporting_delay:_an_example_using_dengue_fever_data.json b/agency-indexes/DoE/Correcting_for_reporting_delay:_an_example_using_dengue_fever_data.json new file mode 100644 index 00000000..c426a2a7 --- /dev/null +++ b/agency-indexes/DoE/Correcting_for_reporting_delay:_an_example_using_dengue_fever_data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "One complication to infectious disease forecasting efforts is delay in reporting of cases, where real-time data often under-report the true disease burden. This pair of R scripts (1) provides example code demonstrating several strategies to account for the reporting delay and improve disease forecasts and (2) applies these methods using publicly-available data on dengue fever case reporting in Puerto Rico from 1990 to 2009.", + "laborHours": 0.0, + "languages": [], + "name": "Correcting for reporting delay: an example using dengue fever data", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbeesleyBIOSTAT/Reporting_Delay_Example_Code", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Correlation_Algorithm_Library.json b/agency-indexes/DoE/Correlation_Algorithm_Library.json new file mode 100644 index 00000000..33892343 --- /dev/null +++ b/agency-indexes/DoE/Correlation_Algorithm_Library.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "CorAL is a software Library designed to aid in the analysis of femtoscipic data. Femtoscopic data are a class of measured quantities used in heavy-ion collisions to characterize particle emitting source sizes. The most common type of this data is two-particle correleations induced by the Hanbury-Brown/Twiss (HBT) Effect, but can also include correlations induced by final-state interactions between pairs of emitted particles in a heavy-ion collision. Because heavy-ion collisions are complex many particle systems, modeling hydrodynamical models or hybrid techniques. Using the CRAB module, CorAL can turn the output from these models into something that can be directley compared to experimental data. CorAL can also take the raw experimentally measured correlation functions and image them by inverting the Koonin-Pratt equation to extract the space-time emission profile of the particle emitting source. This source function can be further analyzed or directly compared to theoretical calculations.", + "homepageURL": "https://asc.llnl.gov/CORAL-benchmarks", + "laborHours": 0.0, + "languages": [ + "C++, Python" + ], + "name": "Correlation Algorithm Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://asc.llnl.gov/CORAL-benchmarks", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://asc.llnl.gov/CORAL-benchmarks", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Correlation_Layers_for_Information_Query_and_Exploration.json b/agency-indexes/DoE/Correlation_Layers_for_Information_Query_and_Exploration.json new file mode 100644 index 00000000..bcfb3593 --- /dev/null +++ b/agency-indexes/DoE/Correlation_Layers_for_Information_Query_and_Exploration.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-21", + "metadataLastUpdated": "2025-04-21" + }, + "description": "CLIQUE provides insight into the nature of current activity on network infrastructure through visual representations of typical and atypical patterns.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 76927.2, + "languages": [], + "name": "Correlation Layers for Information Query and Exploration", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cortexsys_v._3.0.json b/agency-indexes/DoE/Cortexsys_v._3.0.json new file mode 100644 index 00000000..bcbcbd1a --- /dev/null +++ b/agency-indexes/DoE/Cortexsys_v._3.0.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This code implements a variety of \"deep learning\" algorithms from openly published academic journals. These deep learning algorithms allow the user to train neural networks to do various tasks. Such tasks include predicting future values in a time sequence, categorizing images or compressing information. The code is mostly written in the easy to understand Matlab / GNU Octave language, which enables rapid prototyping and understanding for research and educational purposes.", + "laborHours": 2933.6, + "languages": [ + "C++", + "C", + "MATLAB", + "M", + "Cuda" + ], + "name": "Cortexsys v. 3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Cortexsys", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cortext_v._1.0.json b/agency-indexes/DoE/Cortext_v._1.0.json new file mode 100644 index 00000000..47c46f01 --- /dev/null +++ b/agency-indexes/DoE/Cortext_v._1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-29" + }, + "description": "Cortext provides generalized text processing and document analytics capabilities", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Cortext v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/CosmicEmu,_Version_2.0.json b/agency-indexes/DoE/CosmicEmu,_Version_2.0.json new file mode 100644 index 00000000..1b8494a9 --- /dev/null +++ b/agency-indexes/DoE/CosmicEmu,_Version_2.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The CosmicEmu implements a Gaussian process emulation scheme to predict the dark matter and dark matter + neutrino power spectra over a range of physical parameters that describe the composition and evolution of the Universe. The procedure can produce thousands of spectra per second, much faster than the complex n-body simulations used to produce the training set, which can take weeks per simulation. The training simulations, their design, and the general scheme is described in Lawrence et al. (2010), Heitmann et al. (2014), Heitmann et al. (2016), and an upcoming paper.", + "laborHours": 159311.2, + "name": "CosmicEmu, Version 2.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/CosmicEmu/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/CosmicEmu", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cost_Optimized_Risk_and_Reliability_Assessment_Tool_v.0.1.0.json b/agency-indexes/DoE/Cost_Optimized_Risk_and_Reliability_Assessment_Tool_v.0.1.0.json new file mode 100644 index 00000000..a37f595c --- /dev/null +++ b/agency-indexes/DoE/Cost_Optimized_Risk_and_Reliability_Assessment_Tool_v.0.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00927O\nCORRA is a software tool that helps evaluate the costs and benefits of inspecting and repairing wind turbine blades. It combines probabilistic analysis of blade damage with economic analysis to calculate the overall cost of energy production. CORRA can compare different maintenance strategies and their impact on energy costs, which aids in the optimization of wind turbine operations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Cost Optimized Risk and Reliability Assessment Tool v.0.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Coulomb_Logarithm,_Version_1.0.json b/agency-indexes/DoE/Coulomb_Logarithm,_Version_1.0.json new file mode 100644 index 00000000..8abb71c1 --- /dev/null +++ b/agency-indexes/DoE/Coulomb_Logarithm,_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Clog is a library of charged particle stopping powers and related Coulomb logarithm processes in a plasma. The stopping power is a particularly useful quantity for plasma physics, as it measures the energy loss of per unit length of charged particle as it traverses a plasma. Clog's primary stopping power is the BPS (Brown-Preston-Singleton) theory.", + "laborHours": 5532.8, + "name": "Coulomb Logarithm, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/clog/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/clog", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Counting_Occupants_Using_Network_Technology__COUNT__v0.1.json b/agency-indexes/DoE/Counting_Occupants_Using_Network_Technology__COUNT__v0.1.json new file mode 100644 index 00000000..b64cba0d --- /dev/null +++ b/agency-indexes/DoE/Counting_Occupants_Using_Network_Technology__COUNT__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-02-24", + "metadataLastUpdated": "2021-03-05" + }, + "description": "With this COUNT software, we can run a simple query on a campus's Wireless Local Area Network controller (WLAN controller) to obtain the number of connected devices per access point across the whole campus and this can be used as a proxy for the actual number of occupants in the campus. The software supports user defined functions to parse access point names to retrieve more information (e.g.: building names, room numbers etc.) and also allows post-processing of the data.", + "laborHours": 349.6, + "languages": [], + "name": "Counting Occupants Using Network Technology (COUNT) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/COUNT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CoverageTools.json b/agency-indexes/DoE/CoverageTools.json new file mode 100644 index 00000000..8d40ce64 --- /dev/null +++ b/agency-indexes/DoE/CoverageTools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "This is the repository for \"CoverageTools\" developed by KBase.", + "laborHours": 380.0, + "languages": [], + "name": "CoverageTools", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/CoverageTools", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cram.json b/agency-indexes/DoE/Cram.json new file mode 100644 index 00000000..9f419873 --- /dev/null +++ b/agency-indexes/DoE/Cram.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Tool to run many small MPI jobs inside of one large MPI job.\n", + "laborHours": 1824.0, + "languages": [], + "name": "Cram", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/cram", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Credibility_Framework__CF__v.1.0.json b/agency-indexes/DoE/Credibility_Framework__CF__v.1.0.json new file mode 100644 index 00000000..2a50d471 --- /dev/null +++ b/agency-indexes/DoE/Credibility_Framework__CF__v.1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-10-13", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Credibility Framework provides tools such as PIRT (Phenomena Identification and Ranking Table) and PCMM (Predictive Capability Maturity Model) configurable by non-programmers through simple Excel spreadsheets for tailoring the credibility process to meet the needs of the analysis provider organizations, customers and regulatory agencies. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2020-10230 M", + "laborHours": 109728.8, + "languages": [ + "Java", + "Java" + ], + "name": "Credibility Framework (CF) v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/cf?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cf", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Crescendo.json b/agency-indexes/DoE/Crescendo.json new file mode 100644 index 00000000..18f235f6 --- /dev/null +++ b/agency-indexes/DoE/Crescendo.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "mcarbone@bnl.gov" + }, + "date": { + "created": "2023-10-01", + "metadataLastUpdated": "2023-10-01" + }, + "description": "A greatly abstracted machine learning suite built for ease of use, powered by Hydra + Lightning", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Crescendo", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://GitHub.com/matthewcarbone/crescendo", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Critical_Infrastructure_Consequence_Modeler_v_0.5.0_Beta.json b/agency-indexes/DoE/Critical_Infrastructure_Consequence_Modeler_v_0.5.0_Beta.json new file mode 100644 index 00000000..c5d263a6 --- /dev/null +++ b/agency-indexes/DoE/Critical_Infrastructure_Consequence_Modeler_v_0.5.0_Beta.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "Implements previously developed methodology to calculate total disutility to an organization caused by impacts imposed upon the physical system in question (electric power transmission system, water system, etc).Critical infrastructure utility personnel will use this as a planning tool to determine where system weaknesses are and where improvements should be made such that the consequence of some impact is no longer higher than acceptable.", + "laborHours": 5745.6, + "languages": [ + "Java", + "CSS" + ], + "name": "Critical Infrastructure Consequence Modeler v 0.5.0 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cicm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.5.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cross-instrument_Analysis_Correlation_Software.json b/agency-indexes/DoE/Cross-instrument_Analysis_Correlation_Software.json new file mode 100644 index 00000000..f5149b8c --- /dev/null +++ b/agency-indexes/DoE/Cross-instrument_Analysis_Correlation_Software.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "This program has been designed to assist with the tracking of a sample from one analytical instrument to another such as SEM, microscopes, micro x-ray diffraction and other instruments where particular positions/locations on the sample are examined, photographed, etc. The software is designed to easily enter the position of fiducials and locations of interest such that in a future session in the same of different instrument the positions of interest can be re-found through using the known location fiducials in the current and reference session to transform the point into the current sessions coordinate system. The software is dialog box driven guiding the user through the necessary data entry and program choices. Information is stored in a series of text based extensible markup language (XML) files.", + "laborHours": 0.0, + "languages": [], + "name": "Cross-instrument Analysis Correlation Software", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/CIACS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CrossSim.json b/agency-indexes/DoE/CrossSim.json new file mode 100644 index 00000000..ea0a4d11 --- /dev/null +++ b/agency-indexes/DoE/CrossSim.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-26" + }, + "description": "CrossSim is a simulator for modeling neural-inspired machine learning algorithms on analog hardware, such as resistive memory crossbars. It includes noise models for reading and updating the resistances, which can be based on idealized equations or experimental data. It can also introduce noise and finite precision effects when converting values from digital to analog and vice versa. All of these effects can be turned on or off as an algorithm processes a data set and attempts to learn its salient attributes so that it can be categorized in the machine learning training/classification context. CrossSim thus allows the robustness, accuracy, and energy usage of a machine learning algorithm to be tested on simulated hardware.", + "laborHours": 7904.0, + "languages": [ + "Python.", + "Jupyter Notebook", + "MATLAB" + ], + "name": "CrossSim", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cross-sim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Crosslinking_IMS.json b/agency-indexes/DoE/Crosslinking_IMS.json new file mode 100644 index 00000000..261b5690 --- /dev/null +++ b/agency-indexes/DoE/Crosslinking_IMS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Given a list of proteins, finds all cross-linked peptides in the given Ion Mobility MS dataset. This application attempts to find all cross-linked peptides in the given Ion Mobility MS dataset. First, the FASTA file is read in and possible peptides are generated by digesting the protein(s) and assuming 1 max missed cleavage. The possible peptides are searched for in the given features by matching up the monoisotopic mass of the feature to the mass of the peptides. The mass ppm tolerance is an input parameter of the application. All possible cross-links of the unmodified peptides are then calculated and searched for in the Isotopic Peak data. A detailed csv results file is created at the end.", + "laborHours": 684.0, + "languages": [], + "name": "Crosslinking IMS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/CrossLinkingIMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CryoModule_On_Chip__CMOC__v1.0.json b/agency-indexes/DoE/CryoModule_On_Chip__CMOC__v1.0.json new file mode 100644 index 00000000..b18b9862 --- /dev/null +++ b/agency-indexes/DoE/CryoModule_On_Chip__CMOC__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-26", + "metadataLastUpdated": "2018-07-27" + }, + "description": "The software, titled Cryomodule-On-Chip (CMOC), simulates a cryomodule used for low-level RF acceleration in superconducting cavities. The model includes a state-space model of the accelerating fields inside the cavity, the mechanical resonances inside a cryomodule, and their interactions.", + "laborHours": 21690.4, + "languages": [], + "name": "CryoModule On Chip (CMOC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/CMOC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cryo_electron_microscopy_fitting_.json b/agency-indexes/DoE/Cryo_electron_microscopy_fitting_.json new file mode 100644 index 00000000..68775129 --- /dev/null +++ b/agency-indexes/DoE/Cryo_electron_microscopy_fitting_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "The tool inputs cryo electron microscopy (cryo-EM) 3-D reconstructions and an accompanying 3-D atomistic model of a molecular complex. It uses molecular simulation to guide the atomistic model into the 3-D reconstruction, making the atomistic model more consistent with the 3-D reconstruction. This will not be distributed by LANL. This was designed with the intention of being open to the public.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Cryo electron microscopy fitting ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cryogenic_H2_vehicle_simulation.json b/agency-indexes/DoE/Cryogenic_H2_vehicle_simulation.json new file mode 100644 index 00000000..373f0f4e --- /dev/null +++ b/agency-indexes/DoE/Cryogenic_H2_vehicle_simulation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-20" + }, + "description": "CryoH2Vehicle enables to simulate the variations of the thermodynamic states of H2 inside nn onboard vessel, that undergoes n given duty cycle (park/drive/fill). Typical states of charge and boil-off losses can thus be estimated. ", + "laborHours": 380.0, + "languages": [], + "name": "Cryogenic H2 vehicle simulation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/cryoH2vehicle", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CryptoConfig__ITS_Data_Management_.json b/agency-indexes/DoE/CryptoConfig__ITS_Data_Management_.json new file mode 100644 index 00000000..ba35e8ce --- /dev/null +++ b/agency-indexes/DoE/CryptoConfig__ITS_Data_Management_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "Python class for handling encrypted elements in a config file. Extension of ConfigParser. This class overides the 'get' method of ConfigParser replacing it with Fernet symmetric encryption so that you can safely store encrypted passwords in an ini file.", + "laborHours": 152.0, + "languages": [ + "Python" + ], + "name": "CryptoConfig (ITS Data Management)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/CryptoConfig", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CrystalVR.json b/agency-indexes/DoE/CrystalVR.json new file mode 100644 index 00000000..a3109cc6 --- /dev/null +++ b/agency-indexes/DoE/CrystalVR.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2023-01-12" + }, + "description": "SAND2022-14694 O CrystalVR is a CAD2VR plugin which enables the import of crystallographic information files (CIF) into a virtual reality (VR) environment for visualization and interaction. Crystallographic data is incredibly complex and difficult to navigate and visualize on a two-dimensional or 2D screen. CrystalVR empowers users to step inside their crystals, allowing them to intuitively grow, shrink, and scale the crystal structure. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "CrystalVR", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "2022.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Curifactory.json b/agency-indexes/DoE/Curifactory.json new file mode 100644 index 00000000..d66bcf21 --- /dev/null +++ b/agency-indexes/DoE/Curifactory.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "stewartsl@ornl.gov" + }, + "date": { + "created": "2022-02-08", + "metadataLastUpdated": "2022-02-22" + }, + "description": "Curifactory is a library and CLI tool designed to help organize and manage research experiments in Python. Experiment management requires several aspects, including experiment orchestration, parameterization, caching, reproducibility, reporting, and parallelization. Existing projects such as MLFlow, MetaFlow, Luigi, and Pachyderm support these aspects in several different ways and to various degrees. Curifactory provides a different opinion to these, with a heavier focus on supporting general research experiment workflows for individuals or small teams working primarily in Python.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Curifactory", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/curifactory", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Current-Voltage_Analysis_Tool_for_Solar_Fuel_Production__CATS__v0.1.json b/agency-indexes/DoE/Current-Voltage_Analysis_Tool_for_Solar_Fuel_Production__CATS__v0.1.json new file mode 100644 index 00000000..fea8325e --- /dev/null +++ b/agency-indexes/DoE/Current-Voltage_Analysis_Tool_for_Solar_Fuel_Production__CATS__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The program is expected to be a useful tool during operation of a range of solar-driven electrochemical devices, such as PV-electrolyzers and photoelectrochemical (PEC) devices. It makes use of current-voltage data collected during operation, operation parameters that are easily accessible for many devices of interest. The program captures the time-dependence of loss mechanisms at play during PEC device operation and opens the door for real-time optimizations of operational parameters like the feed humidity to minimize performance losses. Currently, the program is useful for applications where the current-voltage polarization response of the photoabsorber and electrolyzer are pre-recorded, and changes over time can be estimated based on the pre-recorded current-voltage scans. More complicated scenarios that involve permanent degradation of the PV component or complex calculations of the electrolyzer current-voltage characteristics may be included in future versions of this software. Aside from the possibility of deconvoluting loss mechanisms, this software can also reveal possible performance benefits by convective PV cooling when the photoabsorber is integrated into the electrolysis cell. The latter can highlight why certain device architectures may be beneficial over others. No similar technologies are known to the developer.", + "laborHours": 927.2, + "languages": [], + "name": "Current-Voltage Analysis Tool for Solar Fuel Production (CATS) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MEG-LBNL/Current-Voltage-Analysis-Tool-for-Solar-Fuel-Production-CATS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Curvallis.json b/agency-indexes/DoE/Curvallis.json new file mode 100644 index 00000000..0600ca4e --- /dev/null +++ b/agency-indexes/DoE/Curvallis.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2023-01-26" + }, + "description": "Curvallis is a plotting program written in Python using MatPlotLib to visualize and modify experimental equation of state data. It does this by plotting individual isotherms as lines. Data can be either 1d or 2d, meaning there can be 1 or many isotherms plotted at once. Data points on these lines can be moved around, and new points can be added or removed. 1d data can have different equations fitted to them, which best fit the data. These equations are currently only Nth degree polynomials and Equations of State, but any equation can be added. Manipulating data points causes this fitted line to be recalculated and redisplayed. The manipulated data points, as well as the fitted line, can be written to a file.", + "laborHours": 2614.4, + "languages": [ + "Python" + ], + "name": "Curvallis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Curvallis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Custom_script_used_in_'Updated_virophage_taxonomy_and_distinction_from_polinton-like_viruses'__Virophage_Scripts__v1.json b/agency-indexes/DoE/Custom_script_used_in_'Updated_virophage_taxonomy_and_distinction_from_polinton-like_viruses'__Virophage_Scripts__v1.json new file mode 100644 index 00000000..c27752fd --- /dev/null +++ b/agency-indexes/DoE/Custom_script_used_in_'Updated_virophage_taxonomy_and_distinction_from_polinton-like_viruses'__Virophage_Scripts__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-28", + "metadataLastUpdated": "2023-06-30" + }, + "description": "This is a script and the associated test input/output that will accompany a new manuscript (soon to be submitted for publication). It can be used to detect and classify virophage, a specific group of viruses. This script is released as documentation for the manuscript, but there is no specific invention, and most bioinformaticians would be able to recreate a comparable script in a matter of days (if not hours) based on the description in the manuscript.", + "laborHours": 0.0, + "languages": [], + "name": "Custom script used in 'Updated virophage taxonomy and distinction from polinton-like viruses' (Virophage_Scripts) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/simroux/ICTV_VirophageSG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Custom_scripts_used_in_\"Distribution_and_activity_patterns_of_targeted_hypermutation_in_the_global_microbiome\"__Scripts_DGR__v1.json" "b/agency-indexes/DoE/Custom_scripts_used_in_\"Distribution_and_activity_patterns_of_targeted_hypermutation_in_the_global_microbiome\"__Scripts_DGR__v1.json" new file mode 100644 index 00000000..5df754a5 --- /dev/null +++ "b/agency-indexes/DoE/Custom_scripts_used_in_\"Distribution_and_activity_patterns_of_targeted_hypermutation_in_the_global_microbiome\"__Scripts_DGR__v1.json" @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-06-10", + "metadataLastUpdated": "2020-06-10" + }, + "description": "Set of scripts used to identify and analyze DGR loci in metagenomes.", + "laborHours": 2325.6, + "languages": [], + "name": "Custom scripts used in \"Distribution and activity patterns of targeted hypermutation in the global microbiome\" (Scripts_DGR) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/srouxjgi/dgr_scripts/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Customs:_Inspect_and_Report_Python_Imports__customs__v1.0.0.json b/agency-indexes/DoE/Customs:_Inspect_and_Report_Python_Imports__customs__v1.0.0.json new file mode 100644 index 00000000..db662f53 --- /dev/null +++ b/agency-indexes/DoE/Customs:_Inspect_and_Report_Python_Imports__customs__v1.0.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-05-06", + "metadataLastUpdated": "2021-06-15" + }, + "description": "We have developed a simple, minimally invasive monitoring framework that enables us to capture key metrics from Python user processes. This is part of a larger effort to collect data across our entire data-intensive science workload at NERSC. The approach for Python is inspired by a similar framework developed for Blue Waters at NCSA. Both frameworks leverage standard Python features, sitecustomize and atexit, to capture Python imports of interest and other job data. The customs package decomposes the information capture into separate inspection and reporting interfaces.", + "laborHours": 0.0, + "languages": [], + "name": "Customs: Inspect and Report Python Imports (customs) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/customs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CyGutz.json b/agency-indexes/DoE/CyGutz.json new file mode 100644 index 00000000..ff033e38 --- /dev/null +++ b/agency-indexes/DoE/CyGutz.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "joiner@ameslab.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This software is an efficient computational package of the Gutzwiller variational method. It solves the Gutzwiller variational problem for general multiband models with arbitrary on-site interaction in a fully self-consistent numerical approach. The underlying algorithm drastically reduces the problem of the high-dimensional Gutzwiller minimization by mapping it to a minimization only in the variational density matrix. For fixed density the Gutzwiller renormalization matrix is determined as a fix-point of a proper functional, whose evaluation requires only ground-state calculations of matrices defined in the Gutzwiller variational space. Furthermore, the package is able to account for the symmetries of the variational function in a controlled way, reducing the number of variational parameters. The software is highly efficient and robust, and is particularly suitable for first-principles studies (e.g., in combination with DFT) of many complex real materials, where the full intra-atomic interaction is important to obtain correct results.", + "laborHours": 167412.8, + "name": "CyGutz", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yaoyongxin/CyGutz", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CyMEpy_[SWR-21-20].json b/agency-indexes/DoE/CyMEpy_[SWR-21-20].json new file mode 100644 index 00000000..ac1936b9 --- /dev/null +++ b/agency-indexes/DoE/CyMEpy_[SWR-21-20].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-09-19", + "metadataLastUpdated": "2023-04-24" + }, + "description": "CYMEpy is a high-level Python package that provides users HELICS bindings for CYMEDIST, CYME\u2019s distribution system simulator.", + "laborHours": 0.0, + "languages": [], + "name": "CyMEpy [SWR-21-20]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GMLC-TDC/cymepy", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/CyPhyTown.json b/agency-indexes/DoE/CyPhyTown.json new file mode 100644 index 00000000..898974c3 --- /dev/null +++ b/agency-indexes/DoE/CyPhyTown.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A series of software programs that enables students to progress from completely unsecured control of devices to control that protects network commands with authentication, integrity and confidentiality. The working example provided is for turning LED lights on and off on a Raspberry Pi computer.", + "laborHours": 304.0, + "name": "CyPhyTown", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNLgov/cyPhyTown/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNLgov/cyPhyTown", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cyber-Physical_Security_Assessment__CyPSA__Toolset.json b/agency-indexes/DoE/Cyber-Physical_Security_Assessment__CyPSA__Toolset.json new file mode 100644 index 00000000..f9fb46b3 --- /dev/null +++ b/agency-indexes/DoE/Cyber-Physical_Security_Assessment__CyPSA__Toolset.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "CyPSA seeks to organize and gain insight into the diverse sets of data that a critical infrastructure provider must manage. Specifically CyPSA inventories, manages, and analyzes assets and relations among those assets. A variety of interfaces are provided. CyPSA inventories assets (both cyber and physical). This may include the cataloging of assets through a common interface. Data sources used to generate a catalogue of assets include PowerWorld, NPView, NMap Scans, and device configurations. Depending upon the role of the person using the tool the types of assets accessed as well as the data sources through which asset information is accessed may vary. CyPSA allows practitioners to catalogue relations among assets and these may either be manually or programmatically generated. For example, some common relations among assets include the following: Topological Network Data: Which devices and assets are connected and how? Data sources for this kind of information include NMap scans, NPView topologies (via Firewall rule analysis). Security Metrics Outputs: The output of various security metrics such as overall exposure. Configure Assets:CyPSA may eventually include the ability to configure assets including relays and switches. For example, a system administrator would be able to configure and alter the state of a relay via the CyPSA interface. Annotate Assets: CyPSA also allows practitioners to manually and programmatically annotate assets. Sources of information with which to annotate assets include provenance metadata regarding the data source from which the asset was loaded, vulnerability information from vulnerability databases, configuration information, and the output of an analysis in general.", + "laborHours": 0.0, + "languages": [ + "Java, Python" + ], + "name": "Cyber-Physical Security Assessment (CyPSA) Toolset", + "organization": "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/bigezy/Armadillo/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bigezy/Armadillo", + "status": "Production", + "tags": [ + "DOE CODE", + "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cyber-informed_Engineering_Battery_Analysis_Tool.json b/agency-indexes/DoE/Cyber-informed_Engineering_Battery_Analysis_Tool.json new file mode 100644 index 00000000..c4554252 --- /dev/null +++ b/agency-indexes/DoE/Cyber-informed_Engineering_Battery_Analysis_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-01-17", + "metadataLastUpdated": "2025-01-17" + }, + "description": "The Cyber-Informed Engineering Battery Analysis Tool (CIEBAT) leverages the Department of Energy\u2019s Cyber-Informed Engineering to prompt engineering designers and operators through an analysis of the critical functions to be supported by a BESS installation, the criticality of those functions, the impacts of denial, disruption or misuse of those functions within the BESS system, and the mitigations which could best prevent impacts to those functions resulting from cyber attack. Through use of this tool, BESS designers and operators can quickly identify appropriate engineering mitigation opportunities to limit impacts from cyber attack and functions where engineering and operational staff can prioritize and guide the application of cybersecurity protections to best support the resiliency of the system.", + "laborHours": 0.0, + "languages": [], + "name": "Cyber-informed Engineering Battery Analysis Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/CIEBAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cyber-informed_Engineering_Microgrid_Analysis_Tool.json b/agency-indexes/DoE/Cyber-informed_Engineering_Microgrid_Analysis_Tool.json new file mode 100644 index 00000000..10056919 --- /dev/null +++ b/agency-indexes/DoE/Cyber-informed_Engineering_Microgrid_Analysis_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "The Cyber-Informed Engineering Microgrid Analysis Tool (CIEMAT) leverages the Department of Energy\u2019s Cyber-Informed Engineering to prompt engineering designers and operators through an analysis of the critical functions to be supported by a microgrid installations, the criticality of those functions, the impacts of denial, disruption or misuse of those functions on the microgrid and dependent functions, and the mitigations which could best prevent impacts to those functions resulting from cyber attack. Through use of this tool, microgrid designers and operators can quickly identify appropriate engineering mitigations to limit impacts from cyber attack and functions where engineering and operational staff can prioritize and guide the application of cybersecurity protections to best support the resiliency of the system.", + "laborHours": 0.0, + "languages": [], + "name": "Cyber-informed Engineering Microgrid Analysis Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/CIEMAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cyber_Contingency_Analysis_version_1.x.json b/agency-indexes/DoE/Cyber_Contingency_Analysis_version_1.x.json new file mode 100644 index 00000000..a91ffcb6 --- /dev/null +++ b/agency-indexes/DoE/Cyber_Contingency_Analysis_version_1.x.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Contingency analysis based approach for quantifying and examining the resiliency of a cyber system in respect to confidentiality, integrity and availability. A graph representing an organization's cyber system and related resources is used for the availability contingency analysis. The mission critical paths associated with an organization are used to determine the consequences of a potential contingency. A node (or combination of nodes) are removed from the graph to analyze a particular contingency. The value of all mission critical paths that are disrupted by that contingency are used to quantify its severity. A total severity score can be calculated based on the complete list of all these contingencies. A simple n1 analysis can be done in which only one node is removed at a time for the analysis. We can also compute nk analysis, where k is the number of nodes to simultaneously remove for analysis. A contingency risk score can also be computed, which takes the probability of the contingencies into account. In addition to availability, we can also quantify confidentiality and integrity scores for the system. These treat user accounts as potential contingencies. The amount (and type) of files that an account can read to is used to compute the confidentiality score. The amount (and type) of files that an account can write to is used to compute the integrity score. As with availability analysis, we can use this information to compute total severity scores in regards to confidentiality and integrity. We can also take probability into account to compute associated risk scores.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++11 QtCreator 5.3" + ], + "name": "Cyber Contingency Analysis version 1.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cyber_Defense_Competition_Code_.json b/agency-indexes/DoE/Cyber_Defense_Competition_Code_.json new file mode 100644 index 00000000..b62247b8 --- /dev/null +++ b/agency-indexes/DoE/Cyber_Defense_Competition_Code_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-19", + "metadataLastUpdated": "2020-04-20" + }, + "description": "As a part of the annual Argonne Cyber Defense Competition, we develop 3 general categories of software: 1. Mock infrastructure components including ICS systems, web properties, etc.; 2. Visualization, monitoring, and network administration software; 3. Software to assist in the development of puzzles and challenges. We would like to use this disclosure to notify of the existence of this code and allow us to open source portions of the code that would be useful to our community building and education efforts associated with the Cyber Defense Competition. Software will only be released after each year's competition when it won't give a competitive advantage to future competitors. ", + "laborHours": 17084.8, + "languages": [], + "name": "Cyber Defense Competition Code ", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/cyber-defense-competition", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cyber_Dynamic_Impact_Modeling_Engine.json b/agency-indexes/DoE/Cyber_Dynamic_Impact_Modeling_Engine.json new file mode 100644 index 00000000..d2b0b391 --- /dev/null +++ b/agency-indexes/DoE/Cyber_Dynamic_Impact_Modeling_Engine.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "joiner@ameslab.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "As the rate, sophistication, and potential damage of cyber attacks continue to grow, the latency of human-speed analysis and response is becoming increasingly costly. Intelligent response to detected attacks and other malicious activity requires both knowledge of the characteristics of the attack as well as how resources involved in the attack related to the mission of the organization. Cydime fills this need by estimating a key component of intrusion detection and response automation: the relationship type and strength between the target organization and the potential attacker.", + "laborHours": 15762.4, + "name": "Cyber Dynamic Impact Modeling Engine", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Ames-Laboratory-Cyber-Group/Cydime", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cyber_Knowledge_Alignment.json b/agency-indexes/DoE/Cyber_Knowledge_Alignment.json new file mode 100644 index 00000000..dbc704eb --- /dev/null +++ b/agency-indexes/DoE/Cyber_Knowledge_Alignment.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-20", + "metadataLastUpdated": "2025-02-20" + }, + "description": "An automated workflow and introduces new approaches to curate existing cybersecurity\nknowledge from multiple sources. It also proposes AI/ML-based methods to infer knowledge alignments across different\nrepositories.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 608.0, + "languages": [], + "name": "Cyber Knowledge Alignment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cybersecurity-Tools_V2W-BERT.json b/agency-indexes/DoE/Cybersecurity-Tools_V2W-BERT.json new file mode 100644 index 00000000..617c8a47 --- /dev/null +++ b/agency-indexes/DoE/Cybersecurity-Tools_V2W-BERT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-02-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Software Vulnerabilities to Weakness Mapping. V2W-BERT optimizes the learnable parameters \u03b8 of F\u03b8 in two steps. In the first step, the pre-trained BERT language model is further fine-tuned with CVE/CWE descriptions specific to cyber security. In the second step, the trained BERT model is employed in a Siamese network architecture to establish links between CVEs and CWEs. The architecture takes a specific CVE-CWE pair as input and predicts whether the CVE belongs to the CWE or not, with a confidence value. V2W-BERT includes a Mask Language Model (LM) based Reconstruction Decoder to ensure that the descriptions\u2019 contexts are not changed too much during the training process.", + "laborHours": 0.0, + "languages": [], + "name": "Cybersecurity-Tools/V2W-BERT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Cybersecurity-Tools/V2W-BERT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cybersecurity_Framework_Tool.json b/agency-indexes/DoE/Cybersecurity_Framework_Tool.json new file mode 100644 index 00000000..50208a05 --- /dev/null +++ b/agency-indexes/DoE/Cybersecurity_Framework_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-11-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Cybersecurity Framework Tool is a web-based tool that provides five (5) concurrent and continuous functions to identify, detect, protect, respond and recover from cyber security threats to critical infrastructure.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Cybersecurity Framework Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cybersecurity_Visualization_Tool.json b/agency-indexes/DoE/Cybersecurity_Visualization_Tool.json new file mode 100644 index 00000000..fa80ff56 --- /dev/null +++ b/agency-indexes/DoE/Cybersecurity_Visualization_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-09-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL created a visualization tool that was tested with real control room operators and IT cybersecurity professionals. The tool enabled adequate communications between the two parties such that they were able to adequately address OT cybersecurity issues. The visualization tool was developed based on an iterative design process, factoring in observations and interviews with the end users, and considering the cognitive workload of the operations staff.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Cybersecurity Visualization Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cyberwheel.json b/agency-indexes/DoE/Cyberwheel.json new file mode 100644 index 00000000..8c2f002a --- /dev/null +++ b/agency-indexes/DoE/Cyberwheel.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "weberb@ornl.gov" + }, + "date": { + "created": "2024-07-15", + "metadataLastUpdated": "2024-07-15" + }, + "description": "Cyberwheel is a high fidelity training environment for autonomous cyber defense agents that includes both simulation and emulation capabilities. Cyberwheel simplifies customization of the training network and easily allows redefining the agent\u2019s reward function, observation space, and action space to support rapid experimentation of novel approaches to agent design. It also provides visibility into agent behaviors necessary for agent evaluation and sufficient documentation and examples to lower the barrier to entry.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Cyberwheel", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl/cyberwheel", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cycle_Consistent_Surrogate_for_Inertial_Confinement_Fusion.json b/agency-indexes/DoE/Cycle_Consistent_Surrogate_for_Inertial_Confinement_Fusion.json new file mode 100644 index 00000000..fd79e83a --- /dev/null +++ b/agency-indexes/DoE/Cycle_Consistent_Surrogate_for_Inertial_Confinement_Fusion.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-03", + "metadataLastUpdated": "2019-05-06" + }, + "description": "We provide a self-contained package to load, process, and test the ICF JAG dataset. In particular, we include a Neural Network designed to act as a surrogate for the JAG 1D Simulator. The neural network is implemented in Tensorflow.\nWe include a Jupyter notebook which allows a user to load the dataset, load the neural network and train it such that given just the 5 input parameters, it predicts the scalars and images accurately. This can be done directly in the notebook, without any additional modifications. During training, intermediate predictions are also saved to disk (as specified by the user). We hope this serves as a starting point to build, test and play with the ICF-JAG simulation dataset.", + "laborHours": 532.0, + "languages": [], + "name": "Cycle Consistent Surrogate for Inertial Confinement Fusion", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rushilanirudh/icf-jag-cycleGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cygnus.json b/agency-indexes/DoE/Cygnus.json new file mode 100644 index 00000000..b185dd16 --- /dev/null +++ b/agency-indexes/DoE/Cygnus.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-08", + "metadataLastUpdated": "2019-04-08" + }, + "description": "Cygnus is a C++ code which is used to analyze Coulomb excitation experiments. In these experiments, the structure of nuclei is probed at low energy, so that only the electromagnetic interaction is involved. The excitation can then be solved semi-classically. Cygnus fits calculated yields to experimental data, allowing the extraction of transition matrix elements, which are important probes of nuclear structure.", + "laborHours": 49172.0, + "languages": [], + "name": "Cygnus", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jhenderson88/Cygnus", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cylindrical_Fast_Backprojection.json b/agency-indexes/DoE/Cylindrical_Fast_Backprojection.json new file mode 100644 index 00000000..633aba15 --- /dev/null +++ b/agency-indexes/DoE/Cylindrical_Fast_Backprojection.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Cylindrical Fast Backprojection (CFBP) is a novel image reconstruction algorithm developed at PNNL that radically\nincreases the efficiency of normal backprojection techniques and is ideally suited to microwave and millimeter-wave\nimaging systems based on scanned linear arrays such as current and next-generation cylindrical body scanners in\ncommon use for aviation security screening. T", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Cylindrical Fast Backprojection", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cylindrical_Scanner.json b/agency-indexes/DoE/Cylindrical_Scanner.json new file mode 100644 index 00000000..fe719248 --- /dev/null +++ b/agency-indexes/DoE/Cylindrical_Scanner.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The CS system is designed to provide a very fast imaging system in order to search for weapons on persons in an airport environment. The Cylindrical Scanner moves a vertical transceiver array rapidly around a person standing stationary. The software can be segmented in to three specific tasks. The first task is data acquisition and scanner control. At the operator's request, this task commands the scanner to move and the radar transceiver array to send data to the computer system in a known and well-ordered manner. The array is moved over the complete aperture in 10 to 12 seconds. At the completion of the array movement the second software task automatically reconstructs the high-resolution image from the radar data utilizing the integrated DSP boards. The third task displays the resulting images, as they become available, to the computer screen for user review and analysis.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Cylindrical Scanner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cylindrical_battery_design_app.json b/agency-indexes/DoE/Cylindrical_battery_design_app.json new file mode 100644 index 00000000..0289a9e8 --- /dev/null +++ b/agency-indexes/DoE/Cylindrical_battery_design_app.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-09-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Software that delivers optimal design parameters and performance predictions for cylindrical cells, which can range in size from microbatteries to EV batteries, is developed. The software utilizes machine learning and includes a graphical user interface to enable rapid prototyping and to accelerate energy storage research, development, and manufacturing. The Cylindrical battery design V1.0 comprises of three types of cylindrical batteries, Microbattery (Primary), Microbattery (Secondary) and 18650/21700/xxxxx Cylindrical battery. The software was developed in MATLAB. The software has the capability to output the cell design with the capacity ranges from several mAh to several million Ah.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Cylindrical battery design app", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DAAP__Data_Analytics_Application_Profiling_.json b/agency-indexes/DoE/DAAP__Data_Analytics_Application_Profiling_.json new file mode 100644 index 00000000..c8b3417e --- /dev/null +++ b/agency-indexes/DoE/DAAP__Data_Analytics_Application_Profiling_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-09-15", + "metadataLastUpdated": "2022-09-15" + }, + "description": "The Data Analytics Application Profiling (DAAP) utility is a software program comprised of a library and scripts to provide basic instrumenting of parallel scientific software applications while they are running on an HPC cluster, and transmit this data over a secure connection as individual records to aggregators. When used in conjunction with additional open source software components (Telegraf, FluentD, and RabbitMQ), the data collected by DAAP can be transmitted off-cluster to an analytics system of the user\u2019s choice for further analysis.", + "laborHours": 0.0, + "languages": [], + "name": "DAAP (Data Analytics Application Profiling)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/daap-log", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DAKOTA_Design_Analysis_Kit_for_Optimization_and_Terascale.json b/agency-indexes/DoE/DAKOTA_Design_Analysis_Kit_for_Optimization_and_Terascale.json new file mode 100644 index 00000000..d201861b --- /dev/null +++ b/agency-indexes/DoE/DAKOTA_Design_Analysis_Kit_for_Optimization_and_Terascale.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-09" + }, + "description": "The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes (computational models) and iterative analysis methods. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and analysis of computational models on high performance computers.A user provides a set of DAKOTA commands in an input file and launches DAKOTA. DAKOTA invokes instances of the computational models, collects their results, and performs systems analyses. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, polynomial chaos, stochastic collocation, and epistemic methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as hybrid optimization, surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. Services for parallel computing, simulation interfacing, approximation modeling, fault tolerance, restart, and graphics are also included.", + "homepageURL": "https://dakota.sandia.gov/sites/default/files/docs/6.0/html-dev/files.html", + "laborHours": 3812676.8, + "languages": [], + "name": "DAKOTA Design Analysis Kit for Optimization and Terascale", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/sites/default/files/docs/6.0/html-dev/files.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/DAKOTA_Driver__WISDEM\302\256__[SWR-13-16].json" "b/agency-indexes/DoE/DAKOTA_Driver__WISDEM\302\256__[SWR-13-16].json" new file mode 100644 index 00000000..211aa684 --- /dev/null +++ "b/agency-indexes/DoE/DAKOTA_Driver__WISDEM\302\256__[SWR-13-16].json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-11", + "metadataLastUpdated": "2024-10-25" + }, + "description": "OpenMDAO driver for DAKOTA (Design Analysis Kit for Optimization and Terascale Applications). This code connects the SANDIA National Laboratory's C++-based DAKOTA optimization and analysis tool with NASA\u2019s python-based openMDAO systems engineering framework. It allows DAKOTA to be used as an openMDAO \u201cDriver\u201d. DAKOTA contains a wide array of advanced sensitivity, uncertainty quantification, and optimization methods. These are now available in a \u201cpluggable\u201d way to any openMDAO based workflow.", + "laborHours": 684.0, + "languages": [ + "Python" + ], + "name": "DAKOTA Driver (WISDEM\u00ae) [SWR-13-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/dakota_driver", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DAKOTA__Design_Analysis_Kit_for_Optimization_and_Terascale__v.6.14.json b/agency-indexes/DoE/DAKOTA__Design_Analysis_Kit_for_Optimization_and_Terascale__v.6.14.json new file mode 100644 index 00000000..056a171e --- /dev/null +++ b/agency-indexes/DoE/DAKOTA__Design_Analysis_Kit_for_Optimization_and_Terascale__v.6.14.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2021-08-30" + }, + "description": "Sandia's Dakota software supports science and engineering transformation through advanced exploration of simulations. Specifically, Dakota manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to: (1) enhance understanding of risk, (2) improve products, and (3) assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a computational model. Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. The algorithms implemented in Dakota aim to address challenges in performing these analyses with complex science and engineering models from desktop to high performance computers. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-10468 O", + "homepageURL": "https://dakota.sandia.gov/download.html", + "laborHours": 0.0, + "languages": [ + "C++", + "C++" + ], + "name": "DAKOTA (Design Analysis Kit for Optimization and Terascale) v.6.14", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "6.14" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DAKOTA__Design_Analysis_Kit_for_Optimization_and_Terascale__v.6.16.json b/agency-indexes/DoE/DAKOTA__Design_Analysis_Kit_for_Optimization_and_Terascale__v.6.16.json new file mode 100644 index 00000000..8f78b111 --- /dev/null +++ b/agency-indexes/DoE/DAKOTA__Design_Analysis_Kit_for_Optimization_and_Terascale__v.6.16.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-09-30", + "metadataLastUpdated": "2022-09-30" + }, + "description": "Sandia's Dakota software supports science and engineering transformation through advanced exploration of simulations. Specifically, Dakota manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to: (1) enhance understanding of risk, (2) improve products, and (3) assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a computational model. Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. The algorithms implemented in Dakota aim to address challenges in performing these analyses with complex science and engineering models from desktop to high performance computers. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-10468 O", + "homepageURL": "https://dakota.sandia.gov", + "laborHours": 0.0, + "languages": [ + "C++", + "C++" + ], + "name": "DAKOTA (Design Analysis Kit for Optimization and Terascale) v.6.16", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "6.16" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DAKOTA_plugin,_dakota_driver__pydakdriver__[SWR-13-16].json b/agency-indexes/DoE/DAKOTA_plugin,_dakota_driver__pydakdriver__[SWR-13-16].json new file mode 100644 index 00000000..5929f39c --- /dev/null +++ b/agency-indexes/DoE/DAKOTA_plugin,_dakota_driver__pydakdriver__[SWR-13-16].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This directory tree contains the materials for the initial version of an openMDAO \"Driver\" object that wraps Sandia Lab's \"DAKOTA\" optimization and analysis code.", + "laborHours": 1048.8, + "languages": [ + "Python" + ], + "name": "DAKOTA_plugin, dakota_driver (pydakdriver) [SWR-13-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DAKOTA_plugin", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DAQMAN_-_A_flexible_configurable_data_acquisition_system.json b/agency-indexes/DoE/DAQMAN_-_A_flexible_configurable_data_acquisition_system.json new file mode 100644 index 00000000..9a6054b3 --- /dev/null +++ b/agency-indexes/DoE/DAQMAN_-_A_flexible_configurable_data_acquisition_system.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DAQMAN is a flexible configurable interface that allows the user to build and operate a VME-based data acquisition system on a Linux workstation. It consists of two parts: a Java-based Graphical User Interface to configure the system, and a C-based utility that reads out the data and creates the output ASCII data file, with two levels of diagnostic tools. The data acquisition system requires a CAEN CONET-VME Bridge to communicate between the hardware in the VME crate and the Linux workstation. Data acquisition modules, such as ADCs, TDC, Scalers, can be loaded into the system, or removed easily. The GUI allows users to activate modules, and channels within modules by clicking on icons. Running configurations are stored; data are collected and can be viewed either as raw numbers, or by charts and histograms that update as the data are accumulated. Data files are written to disk in ASCII format, with a date and time stamp.", + "homepageURL": "https://www.bnl.gov/nsrl/userguide/data-aquisition.php", + "laborHours": 0.0, + "name": "DAQMAN - A flexible configurable data acquisition system", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.bnl.gov/nsrl/userguide/data-aquisition.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.bnl.gov/nsrl/userguide/data-aquisition.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DARMA-tasking_detector.json b/agency-indexes/DoE/DARMA-tasking_detector.json new file mode 100644 index 00000000..2e70f285 --- /dev/null +++ b/agency-indexes/DoE/DARMA-tasking_detector.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "DARMA/detector => Minimal C++ detection idiom. detector is a small library that implements static/compile-time type introspection in C++. With this code, we can check if a type has methods, type aliases, or members that are exactly matching or convertible to a particular interface. Because this library requires C++-14, it is separated from the other DARMA/* libraries.", + "laborHours": 212.8, + "languages": [], + "name": "DARMA-tasking/detector", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/DARMA-tasking/detector/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DARMA-tasking/detector", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/DARMA_checkpoint\302\240.json" "b/agency-indexes/DoE/DARMA_checkpoint\302\240.json" new file mode 100644 index 00000000..ea7a2f6b --- /dev/null +++ "b/agency-indexes/DoE/DARMA_checkpoint\302\240.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "Serialization and checkpointing library.", + "laborHours": 7052.8, + "languages": [], + "name": "DARMA/checkpoint\u00a0", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/DARMA-tasking/checkpoint/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DARMA-tasking/checkpoint", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DARMA_vt.json b/agency-indexes/DoE/DARMA_vt.json new file mode 100644 index 00000000..e7e86367 --- /dev/null +++ b/agency-indexes/DoE/DARMA_vt.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "DARMA/vt => Virtual Transport. vt is an active messaging layer that utilizes C++ object virtualization to manage virtual endpoints with automatic location management. vt is directly built on top of MPI to provide efficient portability across different machine architectures. Empowered with virtualization, vt can automatically perform dynamic load balancing to schedule scientific applications across diverse platforms with minimal user input.", + "laborHours": 155085.6, + "languages": [], + "name": "DARMA/vt", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/DARMA-tasking/vt/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DARMA-tasking/vt", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DASSA_v0.0.1.json b/agency-indexes/DoE/DASSA_v0.0.1.json new file mode 100644 index 00000000..9e503e11 --- /dev/null +++ b/agency-indexes/DoE/DASSA_v0.0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-20" + }, + "description": "DASSA (Parallel DAS Data Storage and Analysis) provides a data storage engine and analysis engine for data from distributed acoustic sensing and other methods. It supports various data analysis operations, from FFT , signal filter, cross-correlation, compression, stacking etc.", + "laborHours": 0.0, + "languages": [], + "name": "DASSA v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/dbin_sdm/dassa/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DATA-DRIVEN_DISCOVERY_OF_DYNAMICS_FROM_TIME-RESOLVED_COHERENT_SCATTERING.json b/agency-indexes/DoE/DATA-DRIVEN_DISCOVERY_OF_DYNAMICS_FROM_TIME-RESOLVED_COHERENT_SCATTERING.json new file mode 100644 index 00000000..0b9e7ca1 --- /dev/null +++ b/agency-indexes/DoE/DATA-DRIVEN_DISCOVERY_OF_DYNAMICS_FROM_TIME-RESOLVED_COHERENT_SCATTERING.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-09", + "metadataLastUpdated": "2024-03-20" + }, + "description": "This software implements a data-driven framework to uncover mechanistic models of dynamics directly from time-resolved coherent X-ray scattering measurements. It employs neural differential equations to parameterize unknown real-space dynamics and incorporates a computational scattering forward model to relate real-space predictions to reciprocal-space observations.", + "laborHours": 0.0, + "languages": [], + "name": "DATA-DRIVEN DISCOVERY OF DYNAMICS FROM TIME-RESOLVED COHERENT SCATTERING", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ninarina12/dynamiCXS", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DBSchema_DMS.json b/agency-indexes/DoE/DBSchema_DMS.json new file mode 100644 index 00000000..357aabac --- /dev/null +++ b/agency-indexes/DoE/DBSchema_DMS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PRISM Data Management System database schema. This is a collection of DDL files that define the database schema used by the Data Management System (DMS) component of the Pan-Omics Research Information Storage and Management system (PRISM) at the Pacific Northwest National Laboratory (PNNL). PRISM incorporates a diverse set of analysis tools and allows a wide range of operations to be incorporated, leveraing a state machine that is accessible to independent, distributed computational nodes. The system has scaled well as data volume has increased since 2002, while allowing adaptability for incorporating new and improved data analysis tools for more effective proteomics research.", + "laborHours": 462475.2, + "languages": [], + "name": "DBSchema_DMS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DBSchema_DMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DBSchema_MTS.json b/agency-indexes/DoE/DBSchema_MTS.json new file mode 100644 index 00000000..2d75ab15 --- /dev/null +++ b/agency-indexes/DoE/DBSchema_MTS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a collection of DDL files that define the database schema used by the Mass and Time Tag System (MTS) component of the Pan-Omics Research Information Storage and Management system (PRISM) at the Pacific Northwest National Laboratory (PNNL). MTS is used to track and quantify peptides and proteins identified in proteomics and related samples.", + "laborHours": 116112.8, + "languages": [], + "name": "DBSchema_MTS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DBSchema_MTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DB_Schema_Export_Tool.json b/agency-indexes/DoE/DB_Schema_Export_Tool.json new file mode 100644 index 00000000..e41ecdc7 --- /dev/null +++ b/agency-indexes/DoE/DB_Schema_Export_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Exports Sql Server database objects as schema files. Exported objects include tables, views, stored procedures, and functions,plus also database properties including database roles and logins. The program can also export table data to create SQL files with an Insert Into statement for each row.", + "laborHours": 4620.8, + "languages": [], + "name": "DB Schema Export Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DB-Schema-Export-Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DCA++.json b/agency-indexes/DoE/DCA++.json new file mode 100644 index 00000000..8329c00b --- /dev/null +++ b/agency-indexes/DoE/DCA++.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "doakpw@ornl.gov" + }, + "date": { + "created": "2019-06-03", + "metadataLastUpdated": "2020-09-25" + }, + "description": "With the DCA++ project, we aim to gain insight into the fascinating physics of strongly correlated electron systems by employing modern quantum cluster methods. The DCA++ code provides a state of the art implementation of the dynamical cluster approximation (DCA) and its DCA+ extension. High scalability and portable performance allow to exploit today's leadership computing systems.", + "laborHours": 113255.2, + "languages": [ + "C++" + ], + "name": "DCA++", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CompFUSE/DCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DD-AADL.json b/agency-indexes/DoE/DD-AADL.json new file mode 100644 index 00000000..927cc880 --- /dev/null +++ b/agency-indexes/DoE/DD-AADL.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2022-03-03", + "metadataLastUpdated": "2022-03-03" + }, + "description": "Data Driven Anderson Acceleration for Physics Informed Neural Networks to solve high dimensional partial differential equations", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "DD-AADL", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/DD-AADL", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DDNTool.json b/agency-indexes/DoE/DDNTool.json new file mode 100644 index 00000000..49492274 --- /dev/null +++ b/agency-indexes/DoE/DDNTool.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OLCF's ATlas 1 & 2 filesystems use disk drive controllers from a company named Data Direct Networks. The vendor-provided monitoring software is sufficient for a small number of controllers, but is ill-suited for simultaneous monitoring of all the controllers used by OLCF. This tool provides a means of gathering performance data from multiple controllers, collating it and storing it in a database for querying by other tools.", + "laborHours": 577.6, + "name": "DDNTool", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-TechInt/DDNTool_v2/blob/master/License.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-TechInt/DDNTool_v2", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DDStore.json b/agency-indexes/DoE/DDStore.json new file mode 100644 index 00000000..f7c8e589 --- /dev/null +++ b/agency-indexes/DoE/DDStore.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "choij@ornl.gov" + }, + "date": { + "created": "2024-02-09", + "metadataLastUpdated": "2024-02-12" + }, + "description": "DDStore is designed to addresses random, read-oriented, global shuffle operations for data-intensive deep learning applications. By preserving global shuffling, DDStore ensures that deep learning model maintains high accuracy and generalizability when it is trained with large volume of data using HPC facilities.", + "laborHours": 0.0, + "languages": [], + "name": "DDStore", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/DDStore", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DEBS_MHD_Code.json b/agency-indexes/DoE/DEBS_MHD_Code.json new file mode 100644 index 00000000..6d87ed9f --- /dev/null +++ b/agency-indexes/DoE/DEBS_MHD_Code.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-12-09" + }, + "description": "DEBS advances the resistive MHD equations via a combination of the explicit leapfrop method and the semi-implicit method. In this way the time step is limited by the CFL condition v*kmax*dt < 1, where v is the local flow velocity, NOT the wave propagation (sound plus Alfven) velocity. The code is thus able to take timesteps that are much larger than allowed by purely explicit codes. For the spatial discretization, DEBS uses a finite difference approximation for the radial variation and a Fourier representation for the variation of the fields in the poloidal and axial directions, i.e it assumes a doubly-periodic geometry. It advances the vector potential in lieu of the magnetic field and uses the Weyl gauge which assumes the electrostatic potential is zero", + "homepageURL": "http://www.tibbartech.com", + "laborHours": 7128.8, + "languages": [ + "fortran 77" + ], + "name": "DEBS MHD Code", + "organization": "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.tibbartech.com/contact", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.tibbartech.com", + "status": "Production", + "tags": [ + "DOE CODE", + "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DECARBONIZATION_SCENARIO_ANALYSIS_MODEL.json b/agency-indexes/DoE/DECARBONIZATION_SCENARIO_ANALYSIS_MODEL.json new file mode 100644 index 00000000..84e4e65e --- /dev/null +++ b/agency-indexes/DoE/DECARBONIZATION_SCENARIO_ANALYSIS_MODEL.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-24", + "metadataLastUpdated": "2022-09-27" + }, + "description": "Achieving the U.S. government's target of net-zero greenhouse gas (GHG) emissions by 2050 will require technological transformations and energy sector migration towards low-carbon or carbon-negative options. To understand the role of technologies, identify synergies and dissonance and the effect of allocating limited low-carbon biomass resources, we developed the Decarbonization Tool to evaluate scenarios from 2020 through 2050. The tool employs an LCA framework considering the U.S. economy as the functional unit and assessing GHG emissions reduction from the 2020 level of 5.4 billion tones CO2e. The tool employs a lifecycle analysis framework to capture both the direct and supply-chain emissions resulting from changes in patterns of energy generation and consumption, technology breakthroughs, and reductions in fugitive emissions over time at the granularity of economic sectors, sub-sectors, and end use applications. A reference scenario is developed using Energy Information Administration (EIA AEO) projection of economic activities for 2020-2050, GHG emissions data from Environmental Protection Agency's (EPA) inventory of GHG sources and sinks for 2019, and emission factors from Argonne's Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model (GREET\u00ae) tool. We consider several carbon reduction approaches including replacement and scale-up of electricity generation with renewables, partial electrification of the transportation sector complimented with biofuels, improvements in building energy efficiency, replacement of natural gas with renewable hydrogen, mitigation of methane emissions from waste and natural gas, agricultural decarbonization, and carbon dioxide removal pathways. The scenario we analyze indicates the potential to achieve 80-90% decarbonization economy-wide relative to a 200X baseline.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "DECARBONIZATION SCENARIO ANALYSIS MODEL", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DEGAS_2.json b/agency-indexes/DoE/DEGAS_2.json new file mode 100644 index 00000000..52286ee6 --- /dev/null +++ b/agency-indexes/DoE/DEGAS_2.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "dstotler@pppl.gov" + }, + "date": { + "created": "2019-05-22", + "metadataLastUpdated": "2019-05-22" + }, + "description": "DEGAS 2 [1], like its predecessor, DEGAS [2], uses the Monte Carlo approach to integrating the Boltzmann equation, allowing the treatment of complex geometries, atomic physics, and wall interactions. DEGAS 2 is written in a \"macro-enhanced'' version of FORTRAN via the FWEB library, providing an object oriented capability and simplifying tedious tasks, such as dynamic memory allocation and the reading and written of self-describing binary files. As a result, the code is extremely flexible and can be readily adapted to problems seemingly far removed from tokamak divertor physics, e.g., its use in simulating the diffusive evaporation of lithium in NSTX [3] and LTX [4]. DEGAS 2 has been extensively verified, as is documented in its User's Manual [5]. Experimental validation has been largely centered on the Gas Puff Imaging (GPI) technique for visualizing plasma turbulence in the tokamak edge. The validation against deuterium gas puff data from NSTX is described in the paper by B. Cao et al. [6] Analogous work with both deuterium and helium has been carried out on Alcator C-Mod. A related application of DEGAS 2 is in the interpretation of data from the Edge Neutral Density Diagnostic on NSTX [7] and NSTX-U. DEGAS 2 has been applied to many other devices, including JT-60U [8], ADITYA [9], and FRC experiments at Tri-Alpha Energy [10]. Neutral transport codes are frequently coupled to plasma simulation codes to allow a self-consistent plasma-neutral solution to be computed. Initially, DEGAS 2 was coupled to UEDGE [11]. More recently, DEGAS 2 has been coupled to the drift-kinetic XGC0 [12], and has been used in the development and testing of the simplified built-in neutral transport module in XGC1 [13]. A related project is a DEGAS 2-based synthetic GPI diagnostic for XGC1 [14].\n\n[1] D. P. Stotler & C. F. F. Karney, Contrib. Plasma Phys. 34, 392 (1994)\n[2] D. Heifetz, D. Post et al., J. Comp. Phys. 46, 309 (1982)\n[3] D. P. Stotler et al., J. Nucl. Mater. 415, S1058 (2011)\n[4] J. C. Schmitt et al., J. Nucl. Mater. 438, S1096 (2013)\n[5] DEGAS 2 Home Page\n[6] B. Cao et al., Fusion Sci. Tech. 64, 29 (2013)\n[7] D. P. Stotler et al., Phys. Plasmas 22, 082506 (2015)\n[8] H. Takenaga et al., Nucl. Fusion 41, 1777 (2001)\n[9] R. Dey et al., Nucl. Fusion 57, 086003 (2017)\n[10] E. M. Granstedt et al., Presented at 60th Annual Meeting of the APS Division of Plasma Physics\n[11] D. P. Stotler et al., Contrib. Plasma Phys. 40, 221 (2000)[\n[12] D. P. Stotler et al., Comput. Sci. Disc. 6, 015006 (2013)\n[13] D. P. Stotler et al., Nucl. Fusion 57, 086028 (2017)\n[14] D. P. Stotler et al., Nucl. Mater. Energy 19, 113 (2019)\n\n", + "homepageURL": "https://theory.pppl.gov/research/research.php?rid=10#h52", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "DEGAS 2", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://theory.pppl.gov/research/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://theory.pppl.gov/research/research.php?rid=10#h52", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DELSOL_v._3.json b/agency-indexes/DoE/DELSOL_v._3.json new file mode 100644 index 00000000..9a332afd --- /dev/null +++ b/agency-indexes/DoE/DELSOL_v._3.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "DELSOL calculates collector field performance and layout and optimal system design for solar thermal central receiver plants. The code consists of a detailed model of the optical performance, a simpler model of the non-optical performance, an algorithm for field layout, and a searching algorithm to find the best system design based on energy cost. The latter two features are coupled to a cost model of central receiver components and an economic model for calculating energy costs. The program optimizes the tower height, receiver size, field layout, heliostat spacings, and tower position at user specified power levels.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "DELSOL v. 3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/delsol", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DENSS-Multiple.json b/agency-indexes/DoE/DENSS-Multiple.json new file mode 100644 index 00000000..201da8c7 --- /dev/null +++ b/agency-indexes/DoE/DENSS-Multiple.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "qians@ornl.gov" + }, + "date": { + "created": "2022-03-28", + "metadataLastUpdated": "2022-03-29" + }, + "description": "It takes multiple data sets from small-angle neutron scattering experiment at different contrast conditions to synthetically use DENSS algorithm (https://www.nature.com/articles/nmeth.4581) to combine all the information from each data set. As the multiple data set contains more information than a single data, all information in the multiple data set are collectively contribute to the final single synthetic structure that represents a molecular particle structure.", + "laborHours": 0.0, + "languages": [], + "name": "DENSS-Multiple", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/q3n/denss-multiple", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DEPDOSE.json b/agency-indexes/DoE/DEPDOSE.json new file mode 100644 index 00000000..ec1b98e9 --- /dev/null +++ b/agency-indexes/DoE/DEPDOSE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "DEPDOSE is an open-source computer application which combines the KDEP respiratory tract deposition software with committed equivalent dose coefficient tables from the DC_PAK internal dosimetry package. DEPDOSE allows the user to rapidly produce tables of dose coefficients to workers and members of the public inhaling a precisely defined, user-specified aerosols using the ICRP 60 series methodology. Combined with a plume dispersion modeling system such as QUIC, this makes it possible to predict radiation doses downstream from an accidental or intentional release of radioactive materials. For this work, a radioactive plume was calculated to members of the public downstream from a plausible release of radionuclides into the atmosphere.", + "laborHours": 0.0, + "languages": [], + "name": "DEPDOSE", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/DEPDOSE", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DERCF__Distributed_Energy_Resource_Cybersecurity_Framework_.json b/agency-indexes/DoE/DERCF__Distributed_Energy_Resource_Cybersecurity_Framework_.json new file mode 100644 index 00000000..c4466c71 --- /dev/null +++ b/agency-indexes/DoE/DERCF__Distributed_Energy_Resource_Cybersecurity_Framework_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2021-06-24" + }, + "description": "The Distributed Energy Resource Cybersecurity Framework (DERCF) provides U.S. federal government sites with a tool to assess the cybersecurity posture\u2014or health\u2014of their distributed energy resource (DER) systems.", + "homepageURL": "https://dercf.nrel.gov", + "laborHours": 0.0, + "languages": [], + "name": "DERCF (Distributed Energy Resource Cybersecurity Framework)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://dercf.nrel.gov/auth/#/register", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://dercf.nrel.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DERHCAT__Distributed_Energy_Resource_Hosting_Capacity_Analysis_Tool__[SWR-16-32].json b/agency-indexes/DoE/DERHCAT__Distributed_Energy_Resource_Hosting_Capacity_Analysis_Tool__[SWR-16-32].json new file mode 100644 index 00000000..67602e62 --- /dev/null +++ b/agency-indexes/DoE/DERHCAT__Distributed_Energy_Resource_Hosting_Capacity_Analysis_Tool__[SWR-16-32].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2023-08-09" + }, + "description": "NREL's advanced hosting capacity analysis and System Analysis Reports can help utilities, policymakers, and solar developers better understand the impact of adding new distributed photovoltaic (DPV) systems to the electrical distribution system.\nAdvanced hosting capacity analysis considers the thresholds at which new DPV systems will trigger upgrades or changes to the electrical distribution system and evaluates the cost of different options for expanding the hosting capacity.\n\nIt is one part of NREL's work to help stakeholders better understand the distribution system costs associated with integrating new DPV systems at different penetration levels.\n\nNREL's analysis uses a bottom-up methodology that involves simulating distribution systems. The analysis considers sequential increases in hosting capacity and corresponding upgrade costs from a baseline scenario with no DPV up to penetration levels greater than 100% of peak load.", + "laborHours": 0.0, + "languages": [], + "name": "DERHCAT (Distributed Energy Resource Hosting Capacity Analysis Tool) [SWR-16-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SystemsAnalysisReports", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DESS__Differential_Equation_System_Solver__[SWR-24-48].json b/agency-indexes/DoE/DESS__Differential_Equation_System_Solver__[SWR-24-48].json new file mode 100644 index 00000000..fa1aa4f7 --- /dev/null +++ b/agency-indexes/DoE/DESS__Differential_Equation_System_Solver__[SWR-24-48].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-01", + "metadataLastUpdated": "2024-06-28" + }, + "description": "The Differential Equation System Solver (DESS) is a Rust crate implementing fixed-step and adaptive-step solvers and designed especially for modeling physical systems. Seven explicit ordinary differential equation (ODE) solver methods have been added so far: Euler\u2019s, Heun\u2019s, Midpoint, Ralston\u2019s, Classic Runge-Kutta, Bogacki-Shampine, and Cash-Karp. These comprise five fixed-step methods and two adaptive-step methods. Few solver packages are implemented in the Rust ecosystem and none are intended specifically for physical system modeling, so the goal of DESS is to create a Rust ODE solver crate designed to easily specify and model physical systems with modular, configurable solver options. In addition to allowing users to directly input equations to solve, DESS allows users to optionally specify and define relationships between nodes in their system, which the package then translates into a system of equations via the Rust macro system, leading to simpler and more intuitive code.", + "laborHours": 5791.2, + "languages": [ + "Rust", + "Python" + ], + "name": "DESS (Differential Equation System Solver) [SWR-24-48]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/de-system-solver", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DESTINY.json b/agency-indexes/DoE/DESTINY.json new file mode 100644 index 00000000..61ae3179 --- /dev/null +++ b/agency-indexes/DoE/DESTINY.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DESTINY is a comprehensive tool for modeling 3D and 2D cache designs using SRAM,embedded DRAM (eDRAM), spin transfer torque RAM (STT-RAM), resistive RAM (ReRAM), and phase change RAM (PCN). In its purpose, it is similar to CACTI, CACTI-3DD or NVSim. DESTINY is very useful for performing design-space exploration across several dimensions, such as optimizing for a target (e.g. latency, area or energy-delay product) for agiven memory technology, choosing the suitable memory technology or fabrication method (i.e. 2D v/s 3D) for a given optimization target, etc. DESTINY has been validated against several cache prototypes. DESTINY is expected to boost studies of next-generation memory architectures used in systems ranging from mobile devices to extreme-scale supercomputers.", + "laborHours": 6292.8, + "name": "DESTINY", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/3d_cache_modeling_tool/destiny/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/3d_cache_modeling_tool/destiny", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DGTile.json b/agency-indexes/DoE/DGTile.json new file mode 100644 index 00000000..69c27bd4 --- /dev/null +++ b/agency-indexes/DoE/DGTile.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "SAND2022-12898 O\nDGTile is a lightweight C++17 adaptive mesh library meant to support explicit discontinuous Galerkin applications on high performance computing machines. DGTile uses a block-based adaptive mesh refinement approach, where the underlying mesh data structure is an octree in three dimensions, where each leaf node of the tree represents a Cartesian grid. Over each grid, DGTile provides modal discontinuous Galerkin basis functions to facilitate simulations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++17" + ], + "name": "DGTile", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DGTile", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DIGITAL_MODULAR_MATERIALS_ROBOTIC_PLATFORM_SOFTWARE.json b/agency-indexes/DoE/DIGITAL_MODULAR_MATERIALS_ROBOTIC_PLATFORM_SOFTWARE.json new file mode 100644 index 00000000..762ef007 --- /dev/null +++ b/agency-indexes/DoE/DIGITAL_MODULAR_MATERIALS_ROBOTIC_PLATFORM_SOFTWARE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-09-12", + "metadataLastUpdated": "2022-01-05" + }, + "description": "This software provides the implementation and operation of a network based mixed-reality platform for Digital prototyping of scientific and materials discovery process. It provides human-in-the-loop approach for materials/process design, synthesis automation, and intelligent methods of feedback optimization. The software is accomplished through network-distributed integration based on robot operating system (ROS) of virtual-reality modeling and simulation, real-time 3D environmental sensing, tracking, and reconstruction, augmented-reality, process automation based on machine learning", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "DIGITAL MODULAR MATERIALS ROBOTIC PLATFORM SOFTWARE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DISCO_GUI_v.1.json b/agency-indexes/DoE/DISCO_GUI_v.1.json new file mode 100644 index 00000000..25885b52 --- /dev/null +++ b/agency-indexes/DoE/DISCO_GUI_v.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08619O\nThe DISCO GUI software, written in MATLAB, allows for data calibration for X-ray diffraction work at Sandia National Labs\u2019 Z Machine. The program manually identifies and manipulates images from seven fiber bundles based on a calibration reticle. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 212.8, + "languages": [ + "MATLAB" + ], + "name": "DISCO GUI v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DISCO_GUI", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DISCO__Distribution_Integration_Solution_Cost_Options__[SWR-20-02].json b/agency-indexes/DoE/DISCO__Distribution_Integration_Solution_Cost_Options__[SWR-20-02].json new file mode 100644 index 00000000..427437da --- /dev/null +++ b/agency-indexes/DoE/DISCO__Distribution_Integration_Solution_Cost_Options__[SWR-20-02].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-03-10", + "metadataLastUpdated": "2024-01-04" + }, + "description": "DISCO is a suite of software for configuring and parallelizing large numbers of distribution power flow simulations and analyzing the results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DISCO (Distribution Integration Solution Cost Options) [SWR-20-02]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/disco", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.2.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DISCO__Distribution_Integration_Solution_Cost_Options__v0.5.0_[SWR-20-02].json b/agency-indexes/DoE/DISCO__Distribution_Integration_Solution_Cost_Options__v0.5.0_[SWR-20-02].json new file mode 100644 index 00000000..262e19eb --- /dev/null +++ b/agency-indexes/DoE/DISCO__Distribution_Integration_Solution_Cost_Options__v0.5.0_[SWR-20-02].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-01-04", + "metadataLastUpdated": "2024-01-04" + }, + "description": "DISCO is a suite of software for configuring and parallelizing large numbers of distribution power flow simulations and analyzing the results.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook", + "Mustache" + ], + "name": "DISCO (Distribution Integration Solution Cost Options) v0.5.0 [SWR-20-02]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/disco", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.5.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DISCOverflow.json b/agency-indexes/DoE/DISCOverflow.json new file mode 100644 index 00000000..e6163ec1 --- /dev/null +++ b/agency-indexes/DoE/DISCOverflow.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Procedure for reverse engineering binary files and storing the result in a graph database structure for later analysis. This is achieved through the use of Python, angr, and OrientDB Community Edition.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DISCOverflow", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/idaholab/DISCOverflow/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DISCOverflow", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "3.6 and up" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DISSIDE:_Dynamic_In_Silico_Sample_Identification_for_Discrete_Evaluation.json b/agency-indexes/DoE/DISSIDE:_Dynamic_In_Silico_Sample_Identification_for_Discrete_Evaluation.json new file mode 100644 index 00000000..ab3039fc --- /dev/null +++ b/agency-indexes/DoE/DISSIDE:_Dynamic_In_Silico_Sample_Identification_for_Discrete_Evaluation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "DISSIDE uses novel unsupervised learning to select samples that best represent the strongest a\npriori discrete pattern in a given data set. It further removes major outliers and \"noisy\" samples\nthat do not fit discrete patterns well or represent outliers in groups below a defined n value. It\nthen estimates the fit and strength of the a priori discrete pattern using both unconstrained and\nconstrained methods for raw and cleaned data", + "laborHours": 744.8, + "languages": [], + "name": "DISSIDE: Dynamic In Silico Sample Identification for Discrete Evaluation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lebrun-LANL/DISSIDE-Dynamic-In-Silico-Sample-Identification-for-Discrete-Evaluation", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DIVA_DeviceEditor__DIVA__v5.1.json b/agency-indexes/DoE/DIVA_DeviceEditor__DIVA__v5.1.json new file mode 100644 index 00000000..9cc4124a --- /dev/null +++ b/agency-indexes/DoE/DIVA_DeviceEditor__DIVA__v5.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2021-06-24" + }, + "description": "The DIVA software interfaces a process in which researchers design their DNA with a web-based graphical user interface (DeviceEditor), submit their designs to a central queue, and a few weeks later receive their sequence-verified clonal constructs. Each researcher independently designs the DNA to be constructed with a web-based BioCAD tool, and presses a button to submit their designs to a central queue. Researchers have web-based access to their DNA design queues, and can track the progress of their submitted designs as they progress from \"evaluation\", to \"waiting for reagents\", to \"in progress\", to \"complete\". Researchers access their completed constructs through the central DNA repository. Along the way, all DNA construction success/failure rates are captured in a central database. his success/failure rate data can be leveraged to refine the DNA assembly design process.", + "homepageURL": "https://agilebiofoundry.org/capabilities/diva-biocad", + "laborHours": 0.0, + "languages": [], + "name": "DIVA/DeviceEditor (DIVA) v5.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://agilebiofoundry.org/capabilities/diva-biocad", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://agilebiofoundry.org/capabilities/diva-biocad", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DLIO:_A_DATA-CENTRIC_BENCHMARK_FOR_DEEP_LEARNING_APPLICATIONS.json b/agency-indexes/DoE/DLIO:_A_DATA-CENTRIC_BENCHMARK_FOR_DEEP_LEARNING_APPLICATIONS.json new file mode 100644 index 00000000..47bbd403 --- /dev/null +++ b/agency-indexes/DoE/DLIO:_A_DATA-CENTRIC_BENCHMARK_FOR_DEEP_LEARNING_APPLICATIONS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2023-03-14" + }, + "description": "SF-22-136 Deep learning has been shown as a successful method for various tasks, and its popularity results in numerous open-source deep learning software tools. Deep learning has been applied to a broad spectrum of scientific domains such as cosmology, particle physics, computer vision, fusion, and astrophysics. Scientists have performed a great deal of work to optimize the computational performance of deep learning frameworks. However, the same cannot be said for I/O performance. As deep learning algorithms rely on big-data volume and variety to effectively train neural networks accurately, I/O is a significant bottleneck on large-scale distributed deep learning training. DLIO, is a novel representative benchmark suite built based on the I/O profiling of the selected workloads. DLIO can be utilized to accurately emulate the I/O behavior of modern deep learning applications. Using DLIO, application developers and system software solution architects can identify potential I/O bottlenecks in their applications and guide optimizations to boost the I/O performance leading to lower training times. The storage vendor can also use DLIO as a guide for designing and optimize the storage and filesystem targeting at deep learning application.", + "laborHours": 0.0, + "languages": [], + "name": "DLIO: A DATA-CENTRIC BENCHMARK FOR DEEP LEARNING APPLICATIONS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/argonne-lcf/dlio_benchmark", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DLLExternalCode.json b/agency-indexes/DoE/DLLExternalCode.json new file mode 100644 index 00000000..19545b2d --- /dev/null +++ b/agency-indexes/DoE/DLLExternalCode.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "bobby.kitchens@srnl.doe.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "DLLExternalCode is the a general dynamic-link library (DLL) interface for linking GoldSim (www.goldsim.com) with external codes. The overall concept is to use GoldSim as top level modeling software with interfaces to external codes for specific calculations. The DLLExternalCode DLL that performs the linking function is designed to take a list of code inputs from GoldSim, create an input file for the external application, run the external code, and return a list of outputs, read from files created by the external application, back to GoldSim. Instructions for creating the input file, running the external code, and reading the output are contained in an instructions file that is read and interpreted by the DLL.", + "homepageURL": "http://srnl.doe.gov/downloads/DllExternalCode_distribution.zip", + "laborHours": 0.0, + "languages": [ + "Fortran90 compiler" + ], + "name": "DLLExternalCode", + "organization": "Savannah River Site (SRS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://srnl.doe.gov/downloads/DllExternalCode_distribution.zip", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://srnl.doe.gov/downloads/DllExternalCode_distribution.zip", + "status": "Production", + "tags": [ + "DOE CODE", + "Savannah River Site (SRS)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DMS_Analysis_Tool_Manager.json b/agency-indexes/DoE/DMS_Analysis_Tool_Manager.json new file mode 100644 index 00000000..d8dfc4d0 --- /dev/null +++ b/agency-indexes/DoE/DMS_Analysis_Tool_Manager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Analysis Tool Manager is a part of PRISM, the Proteomics Research Information and Management System. The analysis manager performs automated processing of available job steps, tracked by the in the DMS_Pipeline database. Plugin DLLs implement the processing details for each analysis tool.", + "laborHours": 188297.6, + "languages": [], + "name": "DMS Analysis Tool Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Analysis-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DMS_Capture_Task_Manager.json b/agency-indexes/DoE/DMS_Capture_Task_Manager.json new file mode 100644 index 00000000..3f2a46b5 --- /dev/null +++ b/agency-indexes/DoE/DMS_Capture_Task_Manager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Capture Task Manager is a part of PRISM, the Proteomics Research Information and Management System. The capture manager processes instrument data files, copying them from the instrument to storage servers, validating the data, creating QC graphics, and pushing the data into MyEMSL. Plugin DLLs implement the processing details for each tool.", + "laborHours": 110990.4, + "languages": [], + "name": "DMS Capture Task Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Capture-Task-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DMS_EMail_Manager.json b/agency-indexes/DoE/DMS_EMail_Manager.json new file mode 100644 index 00000000..d985adfb --- /dev/null +++ b/agency-indexes/DoE/DMS_EMail_Manager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Email Manager obtains data from a SQL Server database using queries defined in a settings file, e-mailing the results of the queries to one or more people. Reports can be e-mailed daily or only on certain days. It also supports calling a stored procedure or querying WMI.", + "laborHours": 2143.2, + "languages": [], + "name": "DMS EMail Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-EMail-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DMS_Instrument_Directory_Scanner.json b/agency-indexes/DoE/DMS_Instrument_Directory_Scanner.json new file mode 100644 index 00000000..5744b8a8 --- /dev/null +++ b/agency-indexes/DoE/DMS_Instrument_Directory_Scanner.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This program examines the source folder on instrument computers to find files and folders. It creates a tab-delimited text file for each instrument, listing the names of the files and folders found. The text files for the instruments are stored in a central location, and are made made visible via the DMS website to allow instrument operators to see the instrument data files on the instrument computer.", + "laborHours": 760.0, + "languages": [], + "name": "DMS Instrument Directory Scanner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Instrument-Directory-Scanner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DMS_Organism_Database_Handler.json b/agency-indexes/DoE/DMS_Organism_Database_Handler.json new file mode 100644 index 00000000..4d5703d3 --- /dev/null +++ b/agency-indexes/DoE/DMS_Organism_Database_Handler.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Organism Database (FASTA file) programs, including PRISMSeq Uploader and the FastaFileMaker console application. This repository includes several software utilities for working with Protein Collections stored in PRISM, the Proteomics Research Information and Management System.", + "laborHours": 10883.2, + "languages": [], + "name": "DMS Organism Database Handler", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Organism-Database-Handler", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DMS_Program_Runner_Service.json b/agency-indexes/DoE/DMS_Program_Runner_Service.json new file mode 100644 index 00000000..c35a5df2 --- /dev/null +++ b/agency-indexes/DoE/DMS_Program_Runner_Service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Program Runner (MultiProgRunner) is a Windows Service that can be configured to start specific programs on a regular interval. In the Proteomics Research Information and Management System (PRISM) the DMS Program runner Service is used to run manager programs at regular intervals.", + "laborHours": 957.6, + "languages": [], + "name": "DMS Program Runner Service", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Program-Runner-Service", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DMS_Space_Manager.json b/agency-indexes/DoE/DMS_Space_Manager.json new file mode 100644 index 00000000..c5bba238 --- /dev/null +++ b/agency-indexes/DoE/DMS_Space_Manager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Space Manager is a part of PRISM, the Proteomics Research Information and Management System. The space manager monitors the free space on Proto-x storage servers, purging old dataset files to free up space if the available space drops below a threshold.", + "laborHours": 1656.8, + "languages": [], + "name": "DMS Space Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Space-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DMS_Update_Manager.json b/agency-indexes/DoE/DMS_Update_Manager.json new file mode 100644 index 00000000..f2ebe17f --- /dev/null +++ b/agency-indexes/DoE/DMS_Update_Manager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DMS Update Manager is used to keep automated processing manager software up-to-date. Although it is part of PRISM (the Proteomics Research Information and Management System), it is a standalone program and does not contact any databases. The program compares the files on a central distribution share to files on the local computer, updating any files that are out of date. It supports rolling back local files to an older version and auto-deleting extra files.", + "laborHours": 2006.4, + "languages": [], + "name": "DMS Update Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Update-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DMS_Website.json b/agency-indexes/DoE/DMS_Website.json new file mode 100644 index 00000000..dced95cf --- /dev/null +++ b/agency-indexes/DoE/DMS_Website.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PNNL Data Management System (DMS) is composed of a SQL Server backend and website front end to allow PNNL staff to track biomaterial, samples, instrument data, and result files from automated software analyses. This repository tracks the files behind the DMS website.", + "laborHours": 108132.8, + "languages": [], + "name": "DMS Website", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DMS-Website", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DNA_Sequencing_Optimizer_v0.1.json b/agency-indexes/DoE/DNA_Sequencing_Optimizer_v0.1.json new file mode 100644 index 00000000..73ecd411 --- /dev/null +++ b/agency-indexes/DoE/DNA_Sequencing_Optimizer_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2021-03-11" + }, + "description": "This is a software utility used to maximize next-generation sequencing data output without compromising quality values. The DNA Sequencing Optimizer is used to determine the optimal amount of library to load. To do this a supervised machine learning model predicts cluster density, a measure of how much DNA is bound to the sequence, from the concentration of DNA loaded. The output is a plot that is used by experimentalists to determine the best DNA library concentration to load onto the sequencer.", + "laborHours": 0.0, + "languages": [], + "name": "DNA Sequencing Optimizer v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/library_loading_concentration_prediction", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DNSViz.json b/agency-indexes/DoE/DNSViz.json new file mode 100644 index 00000000..b94c69d1 --- /dev/null +++ b/agency-indexes/DoE/DNSViz.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Domain Name System Security Extensions (DNSSEC) add authentication to the DNS. However, analyzing and troubleshooting a DNSSEC deployment is difficult in part because of the protocol complexity and in part because authentication involves retrieving dependent components from a number of different Internet locations. DNSViz was written to bring all these DNSSEC components together into a single graph, so they can be represented visually, and nuances can be highlighted for easy identification. DNSViz includes functionality for both analyzing a domain name using active probing and visual representation of the domain name, available currently through a Web interface.", + "laborHours": 11445.6, + "name": "DNSViz", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dnsviz/dnsviz", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DNTTD__Distributed_Non-Negative_Tensor_Train_Decomposition_.json b/agency-indexes/DoE/DNTTD__Distributed_Non-Negative_Tensor_Train_Decomposition_.json new file mode 100644 index 00000000..90934c08 --- /dev/null +++ b/agency-indexes/DoE/DNTTD__Distributed_Non-Negative_Tensor_Train_Decomposition_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "The era of exascale computing opens new venues for innovations and discoveries in many scientific, engineering, and commercial fields. However, with the exa flops also come the extra-large high-dimensional data generated by high performance computing. High-dimensional data is presented as multidimensional arrays, aka tensors. The presence of latent (not directly observable) structures in the tensor allows a unique representation and compression of the data by classical tensor factorization techniques. However, the classical tensor methods are not always stable or they can be exponential in their memory requirements, which makes them not suitable for high-dimensional tensors. Tensor train (TT) is a state-of-the-art tensor network introduced for factorization of high-dimensional tensors. TT transforms the initial high-dimensional tensor in a network of three-dimensional tensors that requires only a linear storage. Many real-world data, such as, density, temperature, population, probability, etc., are non-negative and for an easy interpretation, the algorithms preserving non-negativity are preferred. Here, we introduce a distributed non-negative tensor-train and demonstrate its scalability and the compression on synthetic and real world big datasets.", + "laborHours": 0.0, + "languages": [], + "name": "DNTTD (Distributed Non-Negative Tensor Train Decomposition)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyDNTNK", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DOE-ICoM_Torrent.jl.json b/agency-indexes/DoE/DOE-ICoM_Torrent.jl.json new file mode 100644 index 00000000..95d1bb4f --- /dev/null +++ b/agency-indexes/DoE/DOE-ICoM_Torrent.jl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-23", + "metadataLastUpdated": "2025-04-23" + }, + "description": "Computationally efficient flood simulation using Lagrangian rivulets.", + "laborHours": 1383.2, + "languages": [], + "name": "DOE-ICoM/Torrent.jl", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DOE-ICoM/Torrent.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DOE_CODE.json b/agency-indexes/DoE/DOE_CODE.json new file mode 100644 index 00000000..6a8e88c5 --- /dev/null +++ b/agency-indexes/DoE/DOE_CODE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "westm@osti.gov" + }, + "date": { + "created": "2017-10-31", + "metadataLastUpdated": "2019-08-09" + }, + "description": "Main repo for managing the new DOE CODE site from the DOE Office of Scientific and Technical Information (OSTI).", + "laborHours": 2219.2, + "languages": [], + "name": "DOE CODE", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/doecode/doecode", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DOLCE:_A_Model-Based_Probabilistic_Diffusion_Framework_for_Limited-Angle_CT_Reconstruction.json b/agency-indexes/DoE/DOLCE:_A_Model-Based_Probabilistic_Diffusion_Framework_for_Limited-Angle_CT_Reconstruction.json new file mode 100644 index 00000000..1530ef59 --- /dev/null +++ b/agency-indexes/DoE/DOLCE:_A_Model-Based_Probabilistic_Diffusion_Framework_for_Limited-Angle_CT_Reconstruction.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-10-09", + "metadataLastUpdated": "2023-10-09" + }, + "description": "Limited-Angle Computed Tomography (LACT) is a non-destructive evaluation technique used in a variety\nof applications ranging from security to medicine. The limited angle coverage in LACT is often a dominant\nsource of severe artifacts in the reconstructed images, making it a challenging inverse problem. We\npresent DOLCE, a new deep model-based framework for LACT that uses a conditional diffusion model as\nan image prior. Diffusion models are a recent class of deep generative models that are relatively easy to\ntrain due to their implementation as image denoisers. DOLCE can form high-quality images from severely\nunder-sampled data by integrating data-consistency updates with the sampling updates of a diffusion\nmodel, which is conditioned on the transformed limited-angle data. We show through extensive\nexperimentation on several challenging real LACT datasets that, the same pre-trained DOLCE model\nachieves the SOTA performance on drastically different types of images. Additionally, we show that,\nunlike standard LACT reconstruction methods, DOLCE naturally enables the quantification of the\nreconstruction uncertainty by generating multiple samples consistent with the measured data.", + "laborHours": 0.0, + "languages": [], + "name": "DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wustl-cig/DOLCE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DQL__Django_Query_Logger__[SWR-24-96].json b/agency-indexes/DoE/DQL__Django_Query_Logger__[SWR-24-96].json new file mode 100644 index 00000000..0d146427 --- /dev/null +++ b/agency-indexes/DoE/DQL__Django_Query_Logger__[SWR-24-96].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-08-08", + "metadataLastUpdated": "2024-08-26" + }, + "description": "The Django Query Logger (DQL) is a tool that allows developers of Django web applications to stream the raw database queries that are being executed in real-time from any Django application for review, profiling, filtering, formatting, and analysis.\n\nReference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or Alliance for Sustainable Energy, LLC. The views and opinions of authors expressed in the available or referenced documents do not necessarily state or reflect those of the United States Government or Alliance.", + "laborHours": 562.4, + "languages": [ + "TypeScript", + "SCSS", + "HTML" + ], + "name": "DQL (Django Query Logger) [SWR-24-96]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/django-query-logger", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DR-Path.json b/agency-indexes/DoE/DR-Path.json new file mode 100644 index 00000000..61790715 --- /dev/null +++ b/agency-indexes/DoE/DR-Path.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-19", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This package estimates future potential for utility customers to provide various forms of demand response (DR) based on granular forecasts of energy demand by customer type and a database of DR-enabling technologies.", + "homepageURL": "https://buildings.lbl.gov/download-phase-3-dr-potential-study", + "laborHours": 0.0, + "languages": [], + "name": "DR-Path", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://buildings.lbl.gov/download-phase-3-dr-potential-study", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DREAM.json b/agency-indexes/DoE/DREAM.json new file mode 100644 index 00000000..58daef32 --- /dev/null +++ b/agency-indexes/DoE/DREAM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "DREAM: Distributed Resources for the Earth System Grid Federation (ESGF) Advanced Management\n", + "laborHours": 8025.6, + "languages": [], + "name": "DREAM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/dream", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DREEM.json b/agency-indexes/DoE/DREEM.json new file mode 100644 index 00000000..bdf33423 --- /dev/null +++ b/agency-indexes/DoE/DREEM.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2023-03-15" + }, + "description": "A System Dynamics Model for Assessing Dynamic Rare Earth Production, Demand and U.S. Wind Energy Demand", + "laborHours": 15.2, + "languages": [ + "Powersim Studio" + ], + "name": "DREEM", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/DREEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DSGAN.json b/agency-indexes/DoE/DSGAN.json new file mode 100644 index 00000000..09a7c3ac --- /dev/null +++ b/agency-indexes/DoE/DSGAN.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2021-08-20" + }, + "description": "This study develops a neural network-based approach for emulating high-resolution modeled precipitation data with comparable statistical properties but at greatly reduced computational cost. The key idea is to use combination of low-and high- resolution simulations to train a neural network to map from the former to the latter. Specifically, we define two types of CNNs, one that stacks variables directly and one that encodes each variable before stacking, and we train each CNN type both with a conventional loss function, such as mean square error (MSE), and with a conditional generative adversarial network (CGAN), for a total of four CNN variants. We compare the four new CNN-derived high-resolution precipitation results with precipitation generated from original high resolution simulations, a bilinear interpolater and the state-of-the-art CNN-based super-resolution (SR) technique. Results show that the SR technique produces results similar to those of the bilinear interpolator with smoother spatial and temporal distributions and smaller data variabilities and extremes than the original high resolution simulations. While the new CNNs trained by MSE generate better results over some regions than the interpolator and SR technique do, their predictions are still not as close as the original high resolution simulations. The CNNs trained by CGAN generate more realistic and physically reasonable results, better capturing not only data variability in time and space but also extremes such as intense and long-lasting storms. The new proposed CNN-based downscaling approach can downscale precipitation from 50~km to 12~km in 14~min for 30~years", + "laborHours": 0.0, + "languages": [], + "name": "DSGAN", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lzhengchun/DSGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DSS-SimPy-RL__Open-DSS_and_SimPy_based_Cyber-Physical_RL_environment__[SWR-23-29].json b/agency-indexes/DoE/DSS-SimPy-RL__Open-DSS_and_SimPy_based_Cyber-Physical_RL_environment__[SWR-23-29].json new file mode 100644 index 00000000..9cc45e07 --- /dev/null +++ b/agency-indexes/DoE/DSS-SimPy-RL__Open-DSS_and_SimPy_based_Cyber-Physical_RL_environment__[SWR-23-29].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-03-30", + "metadataLastUpdated": "2023-05-08" + }, + "description": "Recently, numerous data-driven approaches to control an electric grid using machine learning techniques have been investigated. With the advancement of reinforcement learning (RL) based techniques, gradually the conventional optimization based solvers are being replaced with RL approach where there is uncertainty in the environment such as renewable generation or cyber system emulation. However, to train an agent efficiently, it requires numerous interactions with an environment to learn the best policies. There are numerous RL environments for the power systems based on some well-known simulators, similarly there are environment for communication domains. While majority of the cyber emulators are based in an UNIX environment, the power simulators are based in the Windows-based operating system, the generation of cyber-physical mixed domain RL environment has been challenging. Existing co-simulation methods are efficient but resource and time intensive to generate large scale data set for training RL agents. Hence, this software focuses on development and validation of a mixed domain RL environment using Open DSS for the physical side and leverages a discrete event simulator python package, SimPy, for cyber-side emulation which is Operating Systems agnostic. Further utilizing this software co-simulation and training RL agents for re-routing based resilient control for network reconfiguration and volt-var control in power distribution feeder are performed.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DSS-SimPy-RL (Open-DSS and SimPy based Cyber-Physical RL environment) [SWR-23-29]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DSS-SimPy-RL", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/DSS2ePHASOR__\"OpenDSS\"_files_to_\"ePHASORSIM\"_interface_files_converter_.json" "b/agency-indexes/DoE/DSS2ePHASOR__\"OpenDSS\"_files_to_\"ePHASORSIM\"_interface_files_converter_.json" new file mode 100644 index 00000000..7aeb7a58 --- /dev/null +++ "b/agency-indexes/DoE/DSS2ePHASOR__\"OpenDSS\"_files_to_\"ePHASORSIM\"_interface_files_converter_.json" @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-01-15", + "metadataLastUpdated": "2018-01-16" + }, + "description": "The converter extracts all the required feeder data information from \u201cOpendss format\u201d files also known as \u201c.dss\u201d files to construct the feeder data spreadsheets to be interfaced with the \u201cePHASORSIM\u201d simulator.", + "laborHours": 8664.0, + "name": "DSS2ePHASOR (\"OpenDSS\" files to \"ePHASORSIM\" interface files converter)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/DSS2ePHASOR/blob/master/README.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DSS2ePHASOR", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DT-HYDRO.json b/agency-indexes/DoE/DT-HYDRO.json new file mode 100644 index 00000000..e004325a --- /dev/null +++ b/agency-indexes/DoE/DT-HYDRO.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "gureckywl@ornl.gov" + }, + "date": { + "created": "2023-06-29", + "metadataLastUpdated": "2023-06-29" + }, + "description": "The software solves the time dependent, one dimensional (1D) coupled mass and momentum balance equations governing the elastic flow of water through the penstock, turbine and draft tube in a hydroelectric facility using a high order finite volume based method. The numerical method is based on the Kurganov-Tadmor central method paired with the Monotonic Upstream-centered Scheme for Conservation Laws (MUSCL). This solution method accurately resolves the fast transient behavior of the flow, including water hammer. Additionally, the software estimates the full 3D flow field within the turbine chamber in real time, a feat that is made possible by leveraging pre-computed CFD results by utilizing a reduced order modeling method based on an efficient randomized singular value decomposition (SVD) driven proper orthogonal decomposition (POD) with POD-mode weight regression. The reduced order model of the 3D flow is directly coupled to the 1D elastic flow model so the entire flow field through the penstock and turbine system is resolved quickly and with high fidelity.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DT-HYDRO", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/dt-hydro/dt-hydro-cfd", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DTCMP.json b/agency-indexes/DoE/DTCMP.json new file mode 100644 index 00000000..89c73cd7 --- /dev/null +++ b/agency-indexes/DoE/DTCMP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Datatype Compare (DTCMP) Library for sorting and ranking distributed data using MPI.", + "laborHours": 10047.2, + "languages": [], + "name": "DTCMP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/dtcmp", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DTKData.json b/agency-indexes/DoE/DTKData.json new file mode 100644 index 00000000..79cb1346 --- /dev/null +++ b/agency-indexes/DoE/DTKData.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "DTKData contains large files for DataTransferKit testing and examples.\n", + "laborHours": 0.0, + "name": "DTKData", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-CEES/DTKData", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DUCTED_ASSEMBLY_STEADY_STATE_HEAT_TRANSFER_SOFTWARE.json b/agency-indexes/DoE/DUCTED_ASSEMBLY_STEADY_STATE_HEAT_TRANSFER_SOFTWARE.json new file mode 100644 index 00000000..633342f0 --- /dev/null +++ b/agency-indexes/DoE/DUCTED_ASSEMBLY_STEADY_STATE_HEAT_TRANSFER_SOFTWARE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-23", + "metadataLastUpdated": "2021-08-23" + }, + "description": "The Ducted Assembly Steady State Heat transfer software (DASSH) performs full core, steady state, subchannel temperature calculations for hexagonal, ducted assemblies. DASSH is targeted for use in the early stages of the reactor design process when assembly characteristics may not be defined or are undergoing considerable changes. DASSH provides a relatively rapid assessment of the temperature and flow distribution to inform reactor design updates and analysis.", + "laborHours": 0.0, + "languages": [], + "name": "DUCTED ASSEMBLY STEADY STATE HEAT TRANSFER SOFTWARE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dassh-dev/dassh", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DVCalc.json b/agency-indexes/DoE/DVCalc.json new file mode 100644 index 00000000..7555fae2 --- /dev/null +++ b/agency-indexes/DoE/DVCalc.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-11-09", + "metadataLastUpdated": "2022-01-05" + }, + "description": "A methodology and tool for computing the benefits and costs of Advanced Distribution Management Systems (DMS) for Grid Modernization. It suggests an approach for monetizing the \"functional\" benefits, expressed in non-monetary terms, such as System Average Interruption Duration Index/System Average Interruption Frequency Index (SAIDI/SAIFI) reduction and improved efficiency, using commonly available technical and financial parameters. It offers a model for individual utilities to determine the estimated costs and benefits using their own specific data. Where actual utility-specific data is not available, industry default values are offered. The model uses discounted cash flow (DCF) analysis to evaluate the economic justification for an investment in DMS.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "DVCalc", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DVIEW.json b/agency-indexes/DoE/DVIEW.json new file mode 100644 index 00000000..d8ecec54 --- /dev/null +++ b/agency-indexes/DoE/DVIEW.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DView is a time series data visualization tool that provides several different ways to plot time series datasets. 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Its goal is to provide an easy and interactive way for researchers and developers to explore their application's I/O behavior and detect possible I/O bottlenecks that are impacting performance.", + "laborHours": 0.0, + "languages": [], + "name": "DXT Explorer v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/dxt-explorer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DXT_Explorer_v2.0.json b/agency-indexes/DoE/DXT_Explorer_v2.0.json new file mode 100644 index 00000000..2a59da8e --- /dev/null +++ b/agency-indexes/DoE/DXT_Explorer_v2.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-13", + "metadataLastUpdated": "2024-06-13" + }, + "description": "DTX Explorer is a tool to generate interactive data visualizations of Darshan I/O traces collected from HPC applications. 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The problem to be solved is to simulate certain networks of nonlinearly-interacting dynamical variables, and collect statistics on their behavior, to show that they can reliably perform useful computations. 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With data-centric parallel programming, we enable direct knowledge transfer of performance optimization, regardless of the application or the target processor.", + "laborHours": 0.0, + "languages": [], + "name": "DaCe - Data Centric Parallel Programming", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/dace", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dakota_Graphical_User_Interface.json b/agency-indexes/DoE/Dakota_Graphical_User_Interface.json new file mode 100644 index 00000000..58661453 --- /dev/null +++ b/agency-indexes/DoE/Dakota_Graphical_User_Interface.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-10", + "metadataLastUpdated": "2021-08-30" + }, + "description": "The Dakota GUI is an interactive graphical analysis environment for creating, running, and interpreting Dakota optimization and uncertainty quantification studies. It includes problem (Dakota study) set-up, option specification, simulation interfacing, analysis execution, and results visualization. Through the use of wizards, templates, and views, Dakota GUI helps uses navigate Dakota\u2019s complex capability landscape.", + "homepageURL": "https://dakota.sandia.gov", + "laborHours": 3988282.4, + "languages": [ + "Java" + ], + "name": "Dakota Graphical User Interface", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v.6.12" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dakota_Graphical_User_Interface_v.6.14.json b/agency-indexes/DoE/Dakota_Graphical_User_Interface_v.6.14.json new file mode 100644 index 00000000..932d8751 --- /dev/null +++ b/agency-indexes/DoE/Dakota_Graphical_User_Interface_v.6.14.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2021-08-30" + }, + "description": "Dakota GUI is a graphical analysis environment for Sandia\u2019s Dakota software for optimization and uncertainty quantification. This version of the Dakota GUI includes new functionality such as plotting capabilities, Eclipse-based resource management, and integration with the SAW-IF Next Gen Workflow editor. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10629 O", + "homepageURL": "https://dakota.sandia.gov/download.html", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Dakota Graphical User Interface v.6.14", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v.6.14" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Damselfly_Network_Simulator.json b/agency-indexes/DoE/Damselfly_Network_Simulator.json new file mode 100644 index 00000000..da9dbbae --- /dev/null +++ b/agency-indexes/DoE/Damselfly_Network_Simulator.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Damselfly is a model-based parallel network simulator. It can simulate communication patterns of High Performance Computing applications on different network topologies. It outputs steady-state network traffic for a communication pattern, which can help in studying network congestion and its impact on performance.", + "laborHours": 2401.6, + "name": "Damselfly Network Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/damselfly", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dante.json b/agency-indexes/DoE/Dante.json new file mode 100644 index 00000000..20c194ea --- /dev/null +++ b/agency-indexes/DoE/Dante.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "Dante is a probabilistic flu forecasting model. The methodology was developed to produce real-time flu forecasts in the U.S. The software to execute Dante is a collection of R scripts and JAGS files. It takes publicly available data from the US Centers for Disease Control and Prevention (CDC) as input. It runs R scrips and JAGS code to produce model output. ", + "laborHours": 0.0, + "languages": [], + "name": "Dante", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Dante", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dark_Subtraction_Demo.json b/agency-indexes/DoE/Dark_Subtraction_Demo.json new file mode 100644 index 00000000..194617d9 --- /dev/null +++ b/agency-indexes/DoE/Dark_Subtraction_Demo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "This is a demonstration using bluesky to acquire light frames and dark frames and to export dark-subtracted images as TIFF.", + "laborHours": 121.6, + "languages": [], + "name": "Dark Subtraction Demo", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/dark-subtraction-demo", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Darshan.json b/agency-indexes/DoE/Darshan.json new file mode 100644 index 00000000..b107158d --- /dev/null +++ b/agency-indexes/DoE/Darshan.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "Darshan is a lightweight I/O characterization tool that transparently captures I/O access pattern information from HPC applications. Darshan can be used to tune applications for increased scientific productivity or to gain insight into trends in large-scale computing systems.", + "laborHours": 29244.8, + "languages": [], + "name": "Darshan", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://xgitlab.cels.anl.gov/darshan/darshan/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://xgitlab.cels.anl.gov/darshan/darshan", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dashboard_for_Visualizing_Molecular_Property_Prediction_Machine_Learning_Results.json b/agency-indexes/DoE/Dashboard_for_Visualizing_Molecular_Property_Prediction_Machine_Learning_Results.json new file mode 100644 index 00000000..e032f5df --- /dev/null +++ b/agency-indexes/DoE/Dashboard_for_Visualizing_Molecular_Property_Prediction_Machine_Learning_Results.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-05-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a dashboard for exploring the results of machine learning models for predicting molecular properties from\nmolecular structure. It includes tools for:\n1. Modifying molecules to observe the change in predicted properties\n2. Exploring the relationship between molecular structure and predicted properties\n3. Recommending structurally similar molecules with improved properties\n4. Exploring the impact of data subsampling on model performance metrics", + "laborHours": 532.0, + "languages": [], + "name": "Dashboard for Visualizing Molecular Property Prediction Machine Learning Results", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mol-ml-dashboard", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data-Driven_Protection_Software_to_classify_fault_locations_by_protective_zone_in_distribution_systems_with_high_PV_penetration.json b/agency-indexes/DoE/Data-Driven_Protection_Software_to_classify_fault_locations_by_protective_zone_in_distribution_systems_with_high_PV_penetration.json new file mode 100644 index 00000000..4c9fce04 --- /dev/null +++ b/agency-indexes/DoE/Data-Driven_Protection_Software_to_classify_fault_locations_by_protective_zone_in_distribution_systems_with_high_PV_penetration.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-07-18", + "metadataLastUpdated": "2024-07-18" + }, + "description": "The software contains\n(a) the source codes to generate Point-on-Wave (PoW) transient data for any feeder model in Alternative Transient Program\n(ATP) format. Codes provide options to change different steady state settings, including the loading condition and PV\ncapacity and transient state setting like faults type, location and initiation time\n(b) data post-processing source code to converted data from native format to COMTRADE, csv, HDF5\n(c) Docker container to train CNN to classify fault locations by protective zone. The container takes dataset and other\ntraining parameters (sampling rate, training epochs, batch size etc) as input to train CNN. The container writes back the\ntrained CNN model, training and testing metrics and plots to the local workstation", + "laborHours": 501.6, + "languages": [], + "name": "Data-Driven Protection Software to classify fault locations by protective zone in distribution systems with high PV penetration", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/oedisi_transients", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data-Intensive_Benchmarking_Suite.json b/agency-indexes/DoE/Data-Intensive_Benchmarking_Suite.json new file mode 100644 index 00000000..a12a4983 --- /dev/null +++ b/agency-indexes/DoE/Data-Intensive_Benchmarking_Suite.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "The Data-Intensive Benchmark Suite is a set of programs written for the study of data-or storage-intensive science and engineering problems, The benchmark sets cover: general graph searching (basic and Hadoop Map/Reduce breadth-first search), genome sequence searching, HTTP request classification (basic and Hadoop Map/Reduce), low-level data communication, and storage device micro-benchmarking.", + "homepageURL": "https://computing.llnl.gov/projects/memory-centric-architectures/software", + "laborHours": 0.0, + "languages": [], + "name": "Data-Intensive Benchmarking Suite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://computing.llnl.gov/projects/memory-centric-architectures/software", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data-Intensive_Memory-Map_simulator_and_runtime.json b/agency-indexes/DoE/Data-Intensive_Memory-Map_simulator_and_runtime.json new file mode 100644 index 00000000..79137b1c --- /dev/null +++ b/agency-indexes/DoE/Data-Intensive_Memory-Map_simulator_and_runtime.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DI-MMAP is a simulator for modeling the performance of next generation non-volatile random access memory technologies (NVRAM) and a high-perfromance memory-map runtime for the Linux operating system. It is implemented as a device driver for the Linux operating system. It will be used by algorithm designers to unserstand the impact of future NVRAM on their algorithms and will be used by application developers for high-performance access to NVRAM storage.", + "laborHours": 4894.4, + "name": "Data-Intensive Memory-Map simulator and runtime", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/vanessen/di-mmap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DataFed.json b/agency-indexes/DoE/DataFed.json new file mode 100644 index 00000000..37d1be9a --- /dev/null +++ b/agency-indexes/DoE/DataFed.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "There is a need to easily and uniformly capture, access, enrich, organize, search, and collaborate on working scientific data sets across geographically distributed experiment, computation, and data analytics facilities. DataFed provides a set of services and applications enabling simple and uniform cross-facility scientific data management with federated (distributed) data repositories. This solution greatly reduces effort required by scientist to organize and/or move data between facilities/institutes, Reduces likelihood of misidentification and subsequent misuse of data, and improves scientific reproducibility through deep, domain-specific context and provenance capture.", + "laborHours": 83797.6, + "languages": [ + "C++11 GCC 5.x or grerater; Python 3" + ], + "name": "DataFed", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/DataFed", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DataFileUtil.json b/agency-indexes/DoE/DataFileUtil.json new file mode 100644 index 00000000..deb4a527 --- /dev/null +++ b/agency-indexes/DoE/DataFileUtil.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "Utility functions for operating on files and data objects in KBase data stores like Shock and the Workspace.", + "laborHours": 2204.0, + "languages": [], + "name": "DataFileUtil", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/DataFileUtil", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DataMover-Lite.json b/agency-indexes/DoE/DataMover-Lite.json new file mode 100644 index 00000000..7b5dc082 --- /dev/null +++ b/agency-indexes/DoE/DataMover-Lite.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "DataMover-Lite (DML) is a client program whose purpose is to automatically manage multi-file transfers to clients. It expects as its input a transfer-instruction file, and a local target directory where the files will be moved to. The input file contains the Logical File Names (LFNs) and the transfer URLs (TURLs) of files that need to be transferred. The TURLs can have various protocols depending on the server that manages the files, including gridftp, ftp, https, and srm. Given a multi-file request for a large number of files, the DML can issue concurrently a number of transfers in order to get the files. The number of transfers it can issue is set as a parameter and is usually less than 10. For example, if the multi-file is for 100 files, the DML may keep active only 5 transfers at any one time. When any of the 5 transfers completes it will initiate another transfer. It is not necessary for a single request to contain files whose TURLs have same protocol. If the request to the DML contains TURLs with various protocols, the DML will contact the various servers on different threads according to each TURL's protocol. The DMK take care if scheduling the transfers, monitoring their progress, releasing the files, and getting the authorization for each file to be transferred.", + "homepageURL": "https://sdm.lbl.gov/dml", + "laborHours": 0.0, + "languages": [ + "java 1.5.0{sub minus}x or above" + ], + "name": "DataMover-Lite", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sdm.lbl.gov/dml/DMLLicense.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sdm.lbl.gov/dml", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DataPaletteService.json b/agency-indexes/DoE/DataPaletteService.json new file mode 100644 index 00000000..41d2d175 --- /dev/null +++ b/agency-indexes/DoE/DataPaletteService.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This is the repository for \"DataPaletteService\" developed by KBase. ", + "laborHours": 1763.2, + "languages": [], + "name": "DataPaletteService", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/DataPaletteService", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DataRaceBench.json b/agency-indexes/DoE/DataRaceBench.json new file mode 100644 index 00000000..acd3c1e5 --- /dev/null +++ b/agency-indexes/DoE/DataRaceBench.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "DataRaceBench is a benchmark suite designed to systematically and quantitatively evaluate the effectiveness of data race detection tools. It includes a set of microbenchmarks with and without data races. Parallelism is represented by OpenMP directives. OpenMP is a popular parallel programming model for multi-threaded applications.\n", + "laborHours": 4164.8, + "languages": [], + "name": "DataRaceBench", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/dataracebench", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DataXray.json b/agency-indexes/DoE/DataXray.json new file mode 100644 index 00000000..f225d2a7 --- /dev/null +++ b/agency-indexes/DoE/DataXray.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Lab experiments involving digital signal processing tend to capture heterogeneous data that is binned into individual files. The structure of the whole experiment tends to get lost in this process, generating a \"mess\" of data that is difficult to summarize, and even more difficult to analyze in a consistent way. DataXray is a set of python routines that wraps publicly available open-source codes to create a consistent workflow for data and experiments, involving imaging, spectral and hyperspectral data. Routines are provided for data translation, slicing, visualization, multivariate statistics, integral transforms, feature extraction and reporting in the form of publication-grade figures.", + "laborHours": 2173.6, + "languages": [ + "Python 3.5" + ], + "name": "DataXray", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/glacio/data-xray/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_API_Dataview_Widgets.json b/agency-indexes/DoE/Data_API_Dataview_Widgets.json new file mode 100644 index 00000000..9b3df8d9 --- /dev/null +++ b/agency-indexes/DoE/Data_API_Dataview_Widgets.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-13", + "metadataLastUpdated": "2020-08-13" + }, + "description": "Javascript code and supporting content for KBase data landing pages.", + "laborHours": 1413.6, + "languages": [], + "name": "Data API Dataview Widgets", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-data-landing-pages", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Assimilation_Library.json b/agency-indexes/DoE/Data_Assimilation_Library.json new file mode 100644 index 00000000..b82d12d0 --- /dev/null +++ b/agency-indexes/DoE/Data_Assimilation_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "Data assimilation methods are algorithms that incorporate observational data into models in order to improve their forecast and predictability. This library contains a number of version of the Kalman filter methods, such as the ensemble Kalman filter, transform Kalman filter, and the localized transformed Kalman filter. It is meant to be easy to use and flexible for implementation into toy problems, as well as large-scale problems. There are a number of toy problem examples for the use of some of the Kalman filter methods. The code is written in Fortran and includes Python wrappers.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Data Assimilation Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Broker_Search_App.json b/agency-indexes/DoE/Data_Broker_Search_App.json new file mode 100644 index 00000000..b8bdce84 --- /dev/null +++ b/agency-indexes/DoE/Data_Broker_Search_App.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "A web app for searching the data broker. This is a proof-of-concept of the idea that metadatastore will empower scientists to \"Google their data.\" In this demo implementation, the results come back as a truncated list of uids, each with a convenience \"Copy to clipboard\" button. The HTML of each result is pluggable and can be customized on a result-by-result basis.", + "laborHours": 30.4, + "languages": [], + "name": "Data Broker Search App", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/broker-search", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Broker_Tutorial_Materials.json b/agency-indexes/DoE/Data_Broker_Tutorial_Materials.json new file mode 100644 index 00000000..d50f919d --- /dev/null +++ b/agency-indexes/DoE/Data_Broker_Tutorial_Materials.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "Teaching material for databroker.", + "laborHours": 30.4, + "languages": [], + "name": "Data Broker Tutorial Materials", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/broker-tutorial", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Change_Management_for_Scientific_Datasets_on_HPC_systems.json b/agency-indexes/DoE/Data_Change_Management_for_Scientific_Datasets_on_HPC_systems.json new file mode 100644 index 00000000..899b976c --- /dev/null +++ b/agency-indexes/DoE/Data_Change_Management_for_Scientific_Datasets_on_HPC_systems.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-31", + "metadataLastUpdated": "2019-09-23" + }, + "description": "The Dac-Man framework identifies, captures and manages change in large scientific datasets, and enables plug-in of domain-specific change analysis with minimal user effort.", + "laborHours": 4316.8, + "languages": [], + "name": "Data Change Management for Scientific Datasets on HPC systems", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dghoshal-lbl/dac-man", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Citation_Explorer__DCE__v1.0.json b/agency-indexes/DoE/Data_Citation_Explorer__DCE__v1.0.json new file mode 100644 index 00000000..b271a6a3 --- /dev/null +++ b/agency-indexes/DoE/Data_Citation_Explorer__DCE__v1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-28", + "metadataLastUpdated": "2024-06-28" + }, + "description": "Increases in sequencing capacity, combined with rapid accumulation of publications and associated data resources, have increased the complexity of maintaining associations between literature and genomic data. As the volume of literature and data have exceeded the capacity of manual curation, automated approaches to maintaining and confirming associations among these resources have become necessary. Here we present the Data Citation Explorer (DCE), which discovers literature incorporating genomic data whether or not provenance was clearly indicated. This service provides advantages over manual curation methods including consistent resource coverage, metadata enrichment, documentation of new use cases, and identification of conflicting metadata. The service reduces labor costs associated with manual review, improves the quality of genome metadata maintained by the U.S. Department of Energy Joint Genome Institute (JGI), and increases the number of known publications that incorporate its data products. The DCE facilitates an understanding of JGI impact, improves credit attribution for data generators, and can encourage data sharing by allowing scientists to see how reuse amplifies the impact of their original studies.", + "laborHours": 16036.0, + "languages": [ + "ABAP" + ], + "name": "Data Citation Explorer (DCE) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/data-citation-explorer/data-citation-explorer-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Cleaning_and_Analysis_Scripts_for_Individual_Traits_in_the_Dunning-Kruger_Effect_Study.json b/agency-indexes/DoE/Data_Cleaning_and_Analysis_Scripts_for_Individual_Traits_in_the_Dunning-Kruger_Effect_Study.json new file mode 100644 index 00000000..53f89a7d --- /dev/null +++ b/agency-indexes/DoE/Data_Cleaning_and_Analysis_Scripts_for_Individual_Traits_in_the_Dunning-Kruger_Effect_Study.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-01", + "metadataLastUpdated": "2024-09-10" + }, + "description": "This code was built to recode and analyze survey data. The recoding script was built in Python while the data analysis script was built in R. The recoding script takes the raw survey data text and converts it to a numeric coding scheme. The data analysis script conducts analyses recommended by the American Psychological Association (APA) for data of this type. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-3178 O", + "laborHours": 1322.4, + "languages": [ + "Python" + ], + "name": "Data Cleaning and Analysis Scripts for Individual Traits in the Dunning-Kruger Effect Study", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/DKE125/DKE-Scripts/blob/main/Copyright_Notice.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DKE-Scripts", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Elevator.json b/agency-indexes/DoE/Data_Elevator.json new file mode 100644 index 00000000..cd321d17 --- /dev/null +++ b/agency-indexes/DoE/Data_Elevator.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2019-09-23" + }, + "description": "Data Elavator allows extensive optimizations, such as overlapping read and write operations, choosing I/O modes, and aligning buffer boundaries. Is as much as 4.2X faster than Cray DataWarp, the start-of-art software for burst buffer, and 4X faster than directly writing to PFS.", + "laborHours": 53473.6, + "languages": [], + "name": "Data Elevator", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/sbyna/dataelevator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Feature_Extraction_for_High-Rate_3-Phase_Data.json b/agency-indexes/DoE/Data_Feature_Extraction_for_High-Rate_3-Phase_Data.json new file mode 100644 index 00000000..39669f87 --- /dev/null +++ b/agency-indexes/DoE/Data_Feature_Extraction_for_High-Rate_3-Phase_Data.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "This algorithm processes high-rate 3-phase signals to identify the start time of each signal and estimate its envelope as data features. The start time and magnitude of each signal during the steady state is also extracted. The features can be used to detect abnormal signals. This algorithm is developed to analyze Exxeno's 3-phase voltage and current data recorded from refrigeration systems to detect device failure or degradation.", + "homepageURL": "https://store.pnnl.gov/content/data-feature-extraction-high-rate-3-phase-data", + "laborHours": 0.0, + "languages": [ + "Algorithm" + ], + "name": "Data Feature Extraction for High-Rate 3-Phase Data", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/data-feature-extraction-high-rate-3-phase-data", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Import_Export_Service.json b/agency-indexes/DoE/Data_Import_Export_Service.json new file mode 100644 index 00000000..9c25d015 --- /dev/null +++ b/agency-indexes/DoE/Data_Import_Export_Service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "The data import export service provides interfaces to enable the narrative to download data.\n", + "laborHours": 1276.8, + "languages": [], + "name": "Data Import Export Service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/data_import_export", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Import_Manager.json b/agency-indexes/DoE/Data_Import_Manager.json new file mode 100644 index 00000000..0490a220 --- /dev/null +++ b/agency-indexes/DoE/Data_Import_Manager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Data Import Manager is a part of PRISM, the Proteomics Research Information and Management System. The Data Import Manager monitors a central folder for new dataset trigger files, which are XML files that specify metadata for new datasets to import into the Data Management System (DMS). The Data Import Manager validates the metadata in the XML trigger file, notifying the instrument operator by e-mail if invalid metadata is encountered. After processing each XML trigger file, the file is moved into either a success or failure folder.", + "laborHours": 1641.6, + "languages": [], + "name": "Data Import Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Data-Import-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Integration_Aggregated_Model_For_Nuclear_Deployment.json b/agency-indexes/DoE/Data_Integration_Aggregated_Model_For_Nuclear_Deployment.json new file mode 100644 index 00000000..67ec03b0 --- /dev/null +++ b/agency-indexes/DoE/Data_Integration_Aggregated_Model_For_Nuclear_Deployment.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-05-01", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The data of a nuclear utility or plant are stored in various isolated forms in different systems. These data have different structures and tools and are, therefore, used independently. The integration of data sources is often needed and is performed manually and on an as-needed basis. The integration of the data would enable creating a data warehouse for a single nuclear power plant (NPP) or multiple plants. A data model contains objects that make up a given domain along with their attributes and relationships and could be used as a standard for exchange between applications for simple integration and data aggregation. After a survey of existing models, it was determined that a new model was required to meet the scope of this problem. DIAMOND has been developed in the form of an ontology to meet these needs. An ontology is simply a data model that also acts as a taxonomy for the domain, organizing the objects in a hierarchy with the most general objects at the top.", + "laborHours": 30.4, + "languages": [], + "name": "Data Integration Aggregated Model For Nuclear Deployment", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DIAMOND", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Muxer.json b/agency-indexes/DoE/Data_Muxer.json new file mode 100644 index 00000000..1a9b4994 --- /dev/null +++ b/agency-indexes/DoE/Data_Muxer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "Tools for acccessing data in a convenient, workable format. Data Muxer is a tool for interleaving (\u201cmuxing\u201d) separate streams of data based on time. For example, readings taking asynchronously must be aligned \u2013 that is, assigned common bins in time \u2013 before they can be plotted against each other.", + "laborHours": 456.0, + "languages": [], + "name": "Data Muxer", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/datamuxer/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/datamuxer", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Package_Archive_Manager.json b/agency-indexes/DoE/Data_Package_Archive_Manager.json new file mode 100644 index 00000000..7c68b52d --- /dev/null +++ b/agency-indexes/DoE/Data_Package_Archive_Manager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Data Package Archive Manager is a part of PRISM, the Proteomics Research Information and Management System. The software scans data package folders and files, pushing new or changed files into MyEMSL.", + "laborHours": 760.0, + "languages": [], + "name": "Data Package Archive Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DataPackage-Archive-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Processing_Unit_Services_Module.json b/agency-indexes/DoE/Data_Processing_Unit_Services_Module.json new file mode 100644 index 00000000..079512fa --- /dev/null +++ b/agency-indexes/DoE/Data_Processing_Unit_Services_Module.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-24" + }, + "description": "The Data Processing Services Module (DPUSM) provides the ability to perform pluggable compression, erasure coding, checksuming and other important file system operations within the Linux kernel. The pluggable provider interface allows for the use of hardware acceleration of those services. In-kernel file systems are then able to use these functions to use these accelerators to perform operations that are normally run on the processor, resulting in improved file system performance. Third parties will register \"providers\" with the DPUSM to communicate with their respective accelerators. Providers will implement functions with DPUSM API signatures so that the DPUSM can translate the data inputted by users of the DPUSM into data that providers recognize.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Data Processing Unit Services Module", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Quality_Reporting.json b/agency-indexes/DoE/Data_Quality_Reporting.json new file mode 100644 index 00000000..4ff28208 --- /dev/null +++ b/agency-indexes/DoE/Data_Quality_Reporting.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is a repository for tracking issues with metadata in the National Geothermal Data System. Each page representing a resource in NGDS has a link for the user to report issues with the metadata. NGDS teams also use this issue tracker to indicate problems and manage their resolution.", + "laborHours": 0.0, + "name": "Data Quality Reporting", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ngds/metadata-issues/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ngds/metadata-issues", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Science_Infrastructure_SOFTWARE.json b/agency-indexes/DoE/Data_Science_Infrastructure_SOFTWARE.json new file mode 100644 index 00000000..79195ac1 --- /dev/null +++ b/agency-indexes/DoE/Data_Science_Infrastructure_SOFTWARE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "LANL science workflows generate complex data sets and ensembles of data requiring significant compute and storage resources. The Data Science Infrastructure (DSI) project focuses on data-driven approaches to make data more readily available to LANL projects. DSI workflows leverage metadata stored in data-agnostic databases, supported by an abstraction layer API to simplify searching and accessing data across simulation runs, experimental runs, filesystems and environments. The abstraction layer API allows the user to query a range of data types: raw output, processed data, configuration data, machine learning models, performance data, etc. In addition to the abstraction backend API, the DSI project is developing client-driven query APIs and UIs to support specific user workflows.", + "laborHours": 0.0, + "languages": [], + "name": "Data Science Infrastructure SOFTWARE", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/dsi", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Transfer_Kit__DTK_.json b/agency-indexes/DoE/Data_Transfer_Kit__DTK_.json new file mode 100644 index 00000000..fd998286 --- /dev/null +++ b/agency-indexes/DoE/Data_Transfer_Kit__DTK_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2020-06-01" + }, + "description": "A library for multiphysics solution transfer.\n", + "laborHours": 9287.2, + "languages": [], + "name": "Data Transfer Kit (DTK)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-CEES/DataTransferKit", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_Visualization_Saliency_v._1.0.json b/agency-indexes/DoE/Data_Visualization_Saliency_v._1.0.json new file mode 100644 index 00000000..e97ed15f --- /dev/null +++ b/agency-indexes/DoE/Data_Visualization_Saliency_v._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2019-03-12" + }, + "description": "Evaluating the effectiveness of data visualizations is a challenging undertaking and often relies on one-off human subject studies that test a visualization in the context of one specific task. Researchers across the fields of data science, visualization, and human-computer interaction are calling for foundational tools and principles that could be applied to assessing the effectiveness of data visualizations in a more rapid and generalizable manner. The visual saliency model for data visualizations described here addresses this need for evaluation tools. Visual saliency models assess the visual features (e.g. color, contrast, edges) of an image to predict which areas of that image will draw a viewer\u2019s attention. Providing predictions of where viewers will look in a visualization based on the saliency of the various regions and elements in that image could help designers to assess whether or not their design will draw the viewer\u2019s attention as intended. The Data Visualization Saliency model, a saliency model for data visualizations, consists of two parts: a text saliency map and a modified version of the Itti, Koch and Niebur model [1]. The final saliency map is a linear combination of the two. The text saliency map is created from an algorithm that computes the likelihood of belonging to a text region for each pixel of an input visualization image. The modified Itti model transforms the original input image to a representation in CIE LAB color space, which provides an accurate representation of perceptual color opponency.\n\nFor a given input data visualization image, the Data Visualization Saliency model computes and returns the visualization saliency map highlighting areas of the data visualization that will draw a viewer\u2019s attention. It also returns the lower level saliency maps for text and the modified Itti model.\n\n", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 1869.6, + "languages": [ + "MATLAB" + ], + "name": "Data Visualization Saliency v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_import_scripts_for_the_Relation_Engine__KBase_.json b/agency-indexes/DoE/Data_import_scripts_for_the_Relation_Engine__KBase_.json new file mode 100644 index 00000000..65aa6b29 --- /dev/null +++ b/agency-indexes/DoE/Data_import_scripts_for_the_Relation_Engine__KBase_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "Utilities for reproducible imports into the Relation Engine from various data sources.", + "laborHours": 3891.2, + "languages": [], + "name": "Data import scripts for the Relation Engine (KBase)", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/relation_engine_importers", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Data_on_temporal_complementarity_of_hybrid_renewable_energy_systems_[SWR-23-09].json b/agency-indexes/DoE/Data_on_temporal_complementarity_of_hybrid_renewable_energy_systems_[SWR-23-09].json new file mode 100644 index 00000000..7f18a18d --- /dev/null +++ b/agency-indexes/DoE/Data_on_temporal_complementarity_of_hybrid_renewable_energy_systems_[SWR-23-09].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-01-24", + "metadataLastUpdated": "2023-04-05" + }, + "description": "These datasets describe multiple facets of the temporal complementarity of co-located hybrid renewable energy systems throughout the United States. Several metrics characterizing the complementarity of generation profiles are provided on an annual and monthly basis (for both hourly and daily aggregations). These generation profiles are underpinned by hourly resource data (e.g., the WIND Toolkit and National Solar Radiation Database (NSRDB)) spanning the multi-year period 2007-2013. The data include complementarity results for greater than 1.76 million individual locations within the continental United States (CONUS). The data are intended to accompany two publications on the topic of temporal complementarity: 1) Harrison-Atlas, Dylan, Caitlin Murphy, Anna Schleifer, and Nicholas Grue. \"Temporal complementarity and value of wind-PV hybrid systems across the United States.\" Renewable Energy 201 (2022): 111-123, doi:10.1016/j.renene.2022.10.060; and 2) Murphy, Caitlin, Harrison-Atlas, Dylan, Nicholas Grue, Vahan Gevorgian, Juan Gallego-Calderon, Shiloh Elliot and Thomas Mosier. \u201cA Resource Assessment for FlexPower\u201d. NREL Technical Report.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "Data on temporal complementarity of hybrid renewable energy systems [SWR-23-09]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Renewable-Complementarity", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Database_Comm.json b/agency-indexes/DoE/Database_Comm.json new file mode 100644 index 00000000..20ae3f3f --- /dev/null +++ b/agency-indexes/DoE/Database_Comm.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-16", + "metadataLastUpdated": "2023-02-16" + }, + "description": "dbComm is a module for integrating a Python codebase with MongoDB using the PyMongo library. The\nmethods contained are used to connect to a Mongo database and push/pull data.", + "laborHours": 0.0, + "languages": [], + "name": "Database Comm", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/license/pythonsoftfoundation-php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/dbComm", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Database_Manager_for_use_with_PLEXOS_XML_files_[SWR-24-90].json b/agency-indexes/DoE/Database_Manager_for_use_with_PLEXOS_XML_files_[SWR-24-90].json new file mode 100644 index 00000000..24032d68 --- /dev/null +++ b/agency-indexes/DoE/Database_Manager_for_use_with_PLEXOS_XML_files_[SWR-24-90].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-09-04", + "metadataLastUpdated": "2024-09-06" + }, + "description": "This software is an API for create and modify XML that are used for Plexos.\n\nDISCLAIMER: PLEXOS is a registered trademark of Energy Exemplar Pty Ltd (\"Owner\"). Owner has no affiliation to or participation in this software. Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or Alliance for Sustainable Energy, LLC (\"Alliance\"). The views and opinions of authors expressed in the available or referenced documents do not necessarily state or reflect those of the United States Government or Alliance.", + "laborHours": 1246.4, + "languages": [ + "Python" + ], + "name": "Database Manager for use with PLEXOS XML files [SWR-24-90]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/plexosdb", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.0.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Database_and_training_set_enabling_real-time,_on-line_process_monitoring.json b/agency-indexes/DoE/Database_and_training_set_enabling_real-time,_on-line_process_monitoring.json new file mode 100644 index 00000000..b0248eb6 --- /dev/null +++ b/agency-indexes/DoE/Database_and_training_set_enabling_real-time,_on-line_process_monitoring.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a database and associated data treatment that enables software for real-time Raman spectral analysis of sample streams in traditional flow and static solution cells and microfluidic devices. It will enable a chemometric approach to identify and quantify species of interest, including UO22+, nitric acid, and total nitrate. \nLicensed with right to sublicense.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Database and training set enabling real-time, on-line process monitoring", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Datacat.json b/agency-indexes/DoE/Datacat.json new file mode 100644 index 00000000..e51b97ef --- /dev/null +++ b/agency-indexes/DoE/Datacat.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Datacat is a system for the tracking and organization of files, their replicas, and user-defined metadata across heterogeneous storage systems.", + "laborHours": 32680.0, + "name": "Datacat", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/datacat/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/datacat", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dax_v._1.0.json b/agency-indexes/DoE/Dax_v._1.0.json new file mode 100644 index 00000000..701977f2 --- /dev/null +++ b/agency-indexes/DoE/Dax_v._1.0.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The Dax Toolkit enables the fine-grained concurrency for data analysis and visualization required to drive multi-core processors, many-core GPU accelerators, and emerging architectures for exascale computing. Dax simplifies the design of finely threaded algorithms by characterizing them in per element operations, which we call worklets. Worklets simplify design because they can behave as serial processes without the complications of memory clashes or other race conditions. Yet worklets can be scheduled on a practically unlimited number of threads, thereby making effective utilization of many processing cores. Operations coordinated across elements are encapsulated in a few versatile communicative operations that are adapted to the specifics of computing devices.", + "laborHours": 24396.0, + "languages": [ + "C++", + "C", + "CMake", + "Cuda" + ], + "name": "Dax v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DaxToolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DeBoinR:_Density_Boxplots_in_R.json b/agency-indexes/DoE/DeBoinR:_Density_Boxplots_in_R.json new file mode 100644 index 00000000..c45172fd --- /dev/null +++ b/agency-indexes/DoE/DeBoinR:_Density_Boxplots_in_R.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-29" + }, + "description": "DeBoinR (Density Boxplots in R) takes in a set of Probability Density Functions (PDFs), calculates outliers based on several notions of distance, and visualizes these outliers via functional boxplots. This code is written as a stand-along R package with the hopes of eventually submitting it to CRAN. The package is written in generality; it would be useful to any researching looking to analyze a general ensemble of PDFs.", + "laborHours": 0.0, + "languages": [], + "name": "DeBoinR: Density Boxplots in R", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/deboinr", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DecLib_v.1.0.json b/agency-indexes/DoE/DecLib_v.1.0.json new file mode 100644 index 00000000..f2e739ff --- /dev/null +++ b/agency-indexes/DoE/DecLib_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00852O\nDecLib is a software library that aids in the study and application of discrete exterior calculus (DEC) in physical systems. It offers a range of models in fluid and solid mechanics that help users understand complex dynamics like shallow water and compressible Euler equations. DecLib preserves the inherent structures of these systems to ensure accurate and reliable simulations. It is a user-friendly application for exploring geometric mechanics and enhancing the study of physical phenomena. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DecLib v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Decaf.json b/agency-indexes/DoE/Decaf.json new file mode 100644 index 00000000..cfc7b904 --- /dev/null +++ b/agency-indexes/DoE/Decaf.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "Decaf is a dataflow system for the parallel communication of coupled tasks in an HPC workflow and allows the user to allocate resources and execute custom code in the dataflow. The runtime for calling tasks is entirely message-driven. Such a message-driven runtime allows cyclic task dependencies in the workflow graph, for example, to enact computational steering based on the result of downstream tasks. Decaf can stand alone as a complete workflow system, or Decaf can also be used as the dataflow layer by one or more other workflow systems to form a heterogeneous task-based computing environment.", + "laborHours": 45372.0, + "languages": [], + "name": "Decaf", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tpeterka/decaf", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Decision-support_and_Emissions_Prediction_Interactive_Cities_Tool.json b/agency-indexes/DoE/Decision-support_and_Emissions_Prediction_Interactive_Cities_Tool.json new file mode 100644 index 00000000..aaf2b01a --- /dev/null +++ b/agency-indexes/DoE/Decision-support_and_Emissions_Prediction_Interactive_Cities_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-22", + "metadataLastUpdated": "2021-07-22" + }, + "description": "The Decision-support and Emissions Prediction Interactive Cities Tool (DEPICT) aims at predicting the cross-sectoral (building construction, operation and vehicles) energy consumption and greenhouse gases emissions at campus and urban scale. It leverages capabilities of multiple modeling tools: EnergyPlus for building operation, CalEEMod for building construction and gas vehicle, BEAM for electric vehicles and SAM for building\u2013integrated photovoltaics. It distinguishes from other cross-sectoral model such as CalEEMod or BEST in that it uses physical models, rather than empirical models, for all sectors, which allows for a more accurate and customizable quantification. It is relevant for short-term multi-sectoral decision making by developers and city planners and long-term policy making by municipal and state officials. Information about all the developers", + "homepageURL": "https://buildings.lbl.gov/impel/people/lit/lit5", + "laborHours": 0.0, + "languages": [], + "name": "Decision-support and Emissions Prediction Interactive Cities Tool", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://buildings.lbl.gov/impel/people/lit/lit5", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://buildings.lbl.gov/impel/people/lit/lit5", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Decision_Support_For_Digester_Algae_Integration_For_Improved_Environmental_And_Economic_Sustainability.json b/agency-indexes/DoE/Decision_Support_For_Digester_Algae_Integration_For_Improved_Environmental_And_Economic_Sustainability.json new file mode 100644 index 00000000..6ab10105 --- /dev/null +++ b/agency-indexes/DoE/Decision_Support_For_Digester_Algae_Integration_For_Improved_Environmental_And_Economic_Sustainability.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The Idaho National Laboratory (INL) has teamed with University of Idaho and Boise State University to make the use of ADs more attractive by implementing a two-stage AD and coupling additional processes to the system. The addition of a polyhydroxyalkanoate (PHA) reactor, algae cultivation system, and a biomass treatment system such as fast-pyrolysis or hydrothermal liquefaction (HTL) would further sequester carbon and nutrients, as well as add valuable products that can be sold or used on-site to mitigate costs. The Decision-support for Digester-Algae IntegRation for Improved Environmental and Economic Sustainability (DAIRIEES) technoeconomic model will play a key role in evaluating the effectiveness and viability of this system to achieve economic and environmental sustainability by the dairy industry.", + "laborHours": 0.0, + "languages": [], + "name": "Decision Support For Digester Algae Integration For Improved Environmental And Economic Sustainability", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/DAIRIEES", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Decision_Support_for_Operations_and_Maintenance_IV.json b/agency-indexes/DoE/Decision_Support_for_Operations_and_Maintenance_IV.json new file mode 100644 index 00000000..8e4ccb47 --- /dev/null +++ b/agency-indexes/DoE/Decision_Support_for_Operations_and_Maintenance_IV.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "DSOM (Decision Support for Operations and Maintenance) is an expert operations and maintenance system that integrates plant operations, fuel management, and maintenance processes. The DSOM package provides operators with the information they need for cost-effective operating decisions creating savings in fuel, personnel, maintenance, and plant life extension. DSOM provides operators real-time system performance information to allow them to determine if the plant is malfunctioning or running below expectations. By catching potential problems, DSOM enables plants to operate safely at peak efficiency, while providing a higher level of reliability and safety.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++", + "Java", + "PHP" + ], + "name": "Decision Support for Operations and Maintenance IV", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Decomposition_Algorithms_for_Scalable_Quantum_Annealing.json b/agency-indexes/DoE/Decomposition_Algorithms_for_Scalable_Quantum_Annealing.json new file mode 100644 index 00000000..7f6662b0 --- /dev/null +++ b/agency-indexes/DoE/Decomposition_Algorithms_for_Scalable_Quantum_Annealing.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-19", + "metadataLastUpdated": "2021-11-19" + }, + "description": "The presented python code provides wrapper functions for two decomposition algorithms: One algorithm to decompose Maximum Clique problems and one to decompose Minimum Vertex Cover problems. The functions take as input a networkx graph object, and decompose either problem on the input graph recursively into subproblems such that the optimal solution can be constructed from the optimal solutions of both subproblems. The recursion ends as soon as the subproblems reach a pre-specified size limit by the user, and they can be solved using any method provided in advance by the user as external function. This includes exact solvers or an adiabatic quantum annealer.", + "laborHours": 0.0, + "languages": [], + "name": "Decomposition Algorithms for Scalable Quantum Annealing", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Decomposition-Algorithms-for-Scalable-Quantum-Annealing", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DeconEngineV2.json b/agency-indexes/DoE/DeconEngineV2.json new file mode 100644 index 00000000..3fc7a727 --- /dev/null +++ b/agency-indexes/DoE/DeconEngineV2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DeconEngine includes routines for deconvoluting (deisotoping) observed isotopic signatures in mass spectrometry data to detect features.", + "laborHours": 91017.6, + "languages": [], + "name": "DeconEngineV2", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DeconEngineV2", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DeconMSn.json b/agency-indexes/DoE/DeconMSn.json new file mode 100644 index 00000000..339837e4 --- /dev/null +++ b/agency-indexes/DoE/DeconMSn.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "DeconMSn converts mass spectrometry instrument data to text files, including determining the charge state for each parent ion.", + "laborHours": 74692.8, + "languages": [], + "name": "DeconMSn", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DeconMSn", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DeconTools.json b/agency-indexes/DoE/DeconTools.json new file mode 100644 index 00000000..43b83faa --- /dev/null +++ b/agency-indexes/DoE/DeconTools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "DeconTools is a software package used for detecting features in MS data by using the isotopic signatures of expected components. The tool uses different algorithms for different parts of the deconvolution process: noise reduction, peak detection, prediction of theoretical isotopic envelope and scoring functions that quantitate the quality of signature observed in the data.", + "laborHours": 306447.2, + "languages": [], + "name": "DeconTools", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/DeconTools", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deep-Lynx-ML-Adapter.json b/agency-indexes/DoE/Deep-Lynx-ML-Adapter.json new file mode 100644 index 00000000..ef43cb38 --- /dev/null +++ b/agency-indexes/DoE/Deep-Lynx-ML-Adapter.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-10-28", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The Deep Lynx Machine Learning (ML) Adapter is a generic adapter that programmatically runs the ML as continuous data is received. Then, Jupyter Notebooks can be customized according to the project for pre-processing the data, building the machine learning models, prediction analysis of incoming data using an existing model, and forecasting anomalies / failures of the physical asset.", + "laborHours": 0.0, + "languages": [ + "Python", + "R" + ], + "name": "Deep-Lynx-ML-Adapter", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-ML-Adapter", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deep-Lynx-Python-Package.json b/agency-indexes/DoE/Deep-Lynx-Python-Package.json new file mode 100644 index 00000000..63fcdf7c --- /dev/null +++ b/agency-indexes/DoE/Deep-Lynx-Python-Package.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-06-29", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This software is a python package that interacts with the Application Programming Interface (API) suite provided by Deep Lynx. A python codebase may import this package in order to have access to these methods for communicating with a Deep Lynx instance.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deep-Lynx-Python-Package", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-Python-Package", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DeepAnnotator.json b/agency-indexes/DoE/DeepAnnotator.json new file mode 100644 index 00000000..805e635a --- /dev/null +++ b/agency-indexes/DoE/DeepAnnotator.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-22", + "metadataLastUpdated": "2020-11-30" + }, + "description": "Given a collection of pairs ((A) written material such as reports, phrases, bulleted lists, etc., (B) structured labels called annotations) called the training data, we want to create software to take future written material (A) and correctly predict (B). In this case we have used medical reports and medical coder's structured labels as our training data. The software builds a machine learning model of type deep learning, specifically a convolutional neural network (CNN) using the training data so that when new data arrives in the future the annotations can be predicted.", + "laborHours": 273.6, + "languages": [ + "python/none/3.6" + ], + "name": "DeepAnnotator", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CBIIT/pilot3_MT-CNN_ORNL", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DeepHyper:_Scalable_Asynchronous_Neural_Architecture_and_Hyperparameter_Search_for_Deep_Neural_Networks.json b/agency-indexes/DoE/DeepHyper:_Scalable_Asynchronous_Neural_Architecture_and_Hyperparameter_Search_for_Deep_Neural_Networks.json new file mode 100644 index 00000000..4f61c64c --- /dev/null +++ b/agency-indexes/DoE/DeepHyper:_Scalable_Asynchronous_Neural_Architecture_and_Hyperparameter_Search_for_Deep_Neural_Networks.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "DeepHyper is a Python package and infrastructure that targets experimental research in DL search methods, scalability, and portability across high performance computing (HPC) systems. It comprises three modules: benchmarks, a collection of extensible and diverse DL hyperparameter search problems; search, a set of search algorithms for DL hyperparameter search; and evaluators, a common interface for evaluating hyperparameter configurations on HPC platforms. ", + "laborHours": 12388.0, + "languages": [], + "name": "DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/deephyper/deephyper", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deep_Center_Analytical_Foundations_v._1.0.json b/agency-indexes/DoE/Deep_Center_Analytical_Foundations_v._1.0.json new file mode 100644 index 00000000..ea741d5a --- /dev/null +++ b/agency-indexes/DoE/Deep_Center_Analytical_Foundations_v._1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "DCAF is a software library containing analytic functions for encoding, mapping, structuring, and providing access to relations among a collection of entities and deriving attribute and structural features for the purposes of providing an interpretable representation of the information within a collection.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Deep Center Analytical Foundations v. 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deep_Jointly-Informed_neural_networks.json b/agency-indexes/DoE/Deep_Jointly-Informed_neural_networks.json new file mode 100644 index 00000000..7565f1c7 --- /dev/null +++ b/agency-indexes/DoE/Deep_Jointly-Informed_neural_networks.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-07-24", + "metadataLastUpdated": "2018-07-24" + }, + "description": "OJINN Is an easy-to-use deep neural network model that requires fewer user-specified hyper-parameters than traditional neural networks. The algorithm leverages decision trees trained on the data to determine an appropriate deep neural network architectures and weight Initializations. Optional functions also select the learning rate, batch size. and number of training Iterations necessary to create an accurate model.", + "laborHours": 562.4, + "languages": [], + "name": "Deep Jointly-Informed neural networks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DJINN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deep_Learning-based_Non-Stationary_Bias_Correction__NSBC_.json b/agency-indexes/DoE/Deep_Learning-based_Non-Stationary_Bias_Correction__NSBC_.json new file mode 100644 index 00000000..633cb3ce --- /dev/null +++ b/agency-indexes/DoE/Deep_Learning-based_Non-Stationary_Bias_Correction__NSBC_.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2025-02-10", + "metadataLastUpdated": "2025-02-10" + }, + "description": "This work develops the NSBC (non-stationary bias correction) methodology to correct temperature\nprojection bias from E3SM.\nThe NSBC deep learning framework consists of a three-part architecture: an auto-encoder for\ncompressing the spatial information, an LSTM for predicting annual temperature mean, and a U-Net for\ncapturing the residual bias in temperature. The non-stationary bias correction (NSBC) framework can\ncorrect the non-stationarity of the biases of the climate models, which significantly improves the accuracy\nof future temperature prediction and improves the overestimation of extreme high temperatures that many\nexisting bias correction methods suffer from.\nGetting started\n1. Obtain the historical climate simulation and observation data.\nThe E3SM simulation data are available through https://aims2.llnl.gov/search/cmip6/.\nThe pseudo observations, the Geophysical Fluid Dynamics Laboratory (GFDL)-ESM4 model (Krasting et\nal., 2018) are available through https://aims2.llnl.gov/search/cmip6/.\nThe spatial resolution of E3SM and pseudo observation datasets are both regridded to a common 1\u00b0\nresolution grid using conservative interpolation. The regridded E3SM and pseudo observation with 1\u00b0\nresolution can be found throught ./data/.\n2. Train the Auto-encoder model.\nPython 0-autoencoder.py\n3. Train the LSTM\nPython 1-LSTM.py\n4. Generate the annual mean temperature based on trained LSTM\nPython 2-generate_annual_mean_LSTM.py\n5. Train the U-Net.\nPython 3-unet.py\n6. Evaluation and compared with the baseline\nPython 4_evaluation.py\nIs there a deadline approaching that requires the release of yo", + "laborHours": 684.0, + "languages": [], + "name": "Deep Learning-based Non-Stationary Bias Correction (NSBC)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/NSBC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deep_Learning_Denoiser.json b/agency-indexes/DoE/Deep_Learning_Denoiser.json new file mode 100644 index 00000000..74368b71 --- /dev/null +++ b/agency-indexes/DoE/Deep_Learning_Denoiser.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2023-06-22" + }, + "description": "SAND2022-14744 O The Deep Learning Denoiser uses a trained deep convolutional neural network (CNN) model to decompose an input waveform into a signal and noise waveform. In the approach, the CNN provides a signal mask and a noise mask for an input signal. The Short-Time Fourier Transform (STFT) of the estimated signal is obtained by multiplying the signal mask with the STFT of the input signal. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deep Learning Denoiser", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Deep-Learning-Denoiser", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deep_Learning_for_Automated_Fish_Detection_from_Sonar_Images.json b/agency-indexes/DoE/Deep_Learning_for_Automated_Fish_Detection_from_Sonar_Images.json new file mode 100644 index 00000000..dcac082d --- /dev/null +++ b/agency-indexes/DoE/Deep_Learning_for_Automated_Fish_Detection_from_Sonar_Images.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2025-02-24" + }, + "description": "Sonar image classification with Convolution\nNeural Network (CNN)", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 42073.6, + "languages": [], + "name": "Deep Learning for Automated Fish Detection from Sonar Images", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deep_Lynx:_Digital_Engineering_Integration_Hub.json b/agency-indexes/DoE/Deep_Lynx:_Digital_Engineering_Integration_Hub.json new file mode 100644 index 00000000..90e16905 --- /dev/null +++ b/agency-indexes/DoE/Deep_Lynx:_Digital_Engineering_Integration_Hub.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The construction of megaprojects has consistently demonstrated challenges for project managers in regard to meeting cost, schedule, and performance requirements. Megaproject construction challenges are common place within megaprojects with many active projects in the United States failing to meet cost and schedule efforts by significant margins. Currently, engineering teams operate in siloed tools and disparate teams where connections across design, procurement, and construction systems are translated manually or over brittle point-to-point integrations. The manual nature of data exchange increases the risk of silent errors in the reactor design, with each silent error cascading across the design. These cascading errors lead to uncontrollable risk during construction, resulting in significant delays and cost overruns. Deep Lynx allows for an integrated platform during design and operations of mega projects.", + "laborHours": 119244.0, + "languages": [ + "JavaScript" + ], + "name": "Deep Lynx: Digital Engineering Integration Hub", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deep_Lynx_Data_Historian.json b/agency-indexes/DoE/Deep_Lynx_Data_Historian.json new file mode 100644 index 00000000..35d8d419 --- /dev/null +++ b/agency-indexes/DoE/Deep_Lynx_Data_Historian.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-07-22", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This software is intended to facilitate the ingestion of data from some data historian into Deep Lynx. A data historian in this instance is any location where sensor and operational data from some live asset is gathered. The data can be either manual retrieved by this software or the data historian source can push to a listening endpoint provided by this software.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deep Lynx Data Historian", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-Data-Historian", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deep_Lynx_Javascript_Package.json b/agency-indexes/DoE/Deep_Lynx_Javascript_Package.json new file mode 100644 index 00000000..fa8d1127 --- /dev/null +++ b/agency-indexes/DoE/Deep_Lynx_Javascript_Package.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-10-28", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This software is a JavaScript package that interacts with the Application Programming Interface (API) suite provided by Deep Lynx. A JavaScript or TypeScript codebase may import this package in order to have access to these methods for communicating with a Deep Lynx instance.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "TypeScript" + ], + "name": "Deep Lynx Javascript Package", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep_Lynx_JS_SDK", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deep_Lynx_MOOSE_Adapter.json b/agency-indexes/DoE/Deep_Lynx_MOOSE_Adapter.json new file mode 100644 index 00000000..6880dbaf --- /dev/null +++ b/agency-indexes/DoE/Deep_Lynx_MOOSE_Adapter.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-24", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The Deep Lynx MOOSE Adapter connects the Deep Lynx data warehouse with any MOOSE executable. The Adapter can receive events from Deep Lynx and will take incoming data to format a template input file for the MOOSE executable. Returns from the MOOSE run are sent back to Deep Lynx for use by other applications.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deep Lynx MOOSE Adapter", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-MOOSE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deep_Lynx_Matlab_Adapter.json b/agency-indexes/DoE/Deep_Lynx_Matlab_Adapter.json new file mode 100644 index 00000000..d69cb4ba --- /dev/null +++ b/agency-indexes/DoE/Deep_Lynx_Matlab_Adapter.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-07-12", + "metadataLastUpdated": "2023-07-12" + }, + "description": "The Deep Lynx MATLAB Adapter is a Python application that connects the Deep Lynx data warehouse with any MATLAB simulation.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python" + ], + "name": "Deep Lynx Matlab Adapter", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-MATLAB", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deep_Lynx_Unidirectional_Network_Connector.json b/agency-indexes/DoE/Deep_Lynx_Unidirectional_Network_Connector.json new file mode 100644 index 00000000..98185c27 --- /dev/null +++ b/agency-indexes/DoE/Deep_Lynx_Unidirectional_Network_Connector.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-01-21", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The Deep Lynx UNC is a small utility written in Python that uses only basic Python libraries and the Deep Lynx Python Software Development Kit (SDK). It queries Deep Lynx for tasks that indicate some data to be run in the UNC's environment. Once a task is acquired, the UNC retrieves the associated data and provides it to some other application for processing, waits for output, and sends the output from the other application to Deep Lynx. As data flows only from the UNC to Deep Lynx, this software solves the problem of connecting Deep Lynx with applications and resources that exist in a network where the network can reach Deep Lynx, but Deep Lynx cannot reach that network (unidirectional network).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deep Lynx Unidirectional Network Connector", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-UNC", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deep_Symbolic_Regression.json b/agency-indexes/DoE/Deep_Symbolic_Regression.json new file mode 100644 index 00000000..f10140af --- /dev/null +++ b/agency-indexes/DoE/Deep_Symbolic_Regression.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-20", + "metadataLastUpdated": "2020-02-20" + }, + "description": "Symbolic regression is the task of finding tractable mathematical expressions that best fit an input\ndataset. \n\nDeep symbolic regression (DSR) searches the space of tractable mathematical expressions by using a recurrent neural network that generates mathematical expressions. \n\nThe network is trained using reinforcement learning.", + "laborHours": 4985.6, + "languages": [], + "name": "Deep Symbolic Regression", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/brendenpetersen/deep-symbolic-regression", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deeper_Fluids.json b/agency-indexes/DoE/Deeper_Fluids.json new file mode 100644 index 00000000..f42503a1 --- /dev/null +++ b/agency-indexes/DoE/Deeper_Fluids.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "A framework for building and training neural network surrogates for CFD simulation, with a focus on quickly simulating volume fraction dynamics for carbon capture efficiency prediction. Augments the Deep Fluids (Kim et al., 2019) approach as described in our paper \"Latent Space Simulation for Carbon Capture Design Optimization\" (Bartoldson et al., 2021).", + "laborHours": 0.0, + "languages": [], + "name": "Deeper Fluids", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CCSI-Toolset/DeeperFluids", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deeplynx-loader.json b/agency-indexes/DoE/Deeplynx-loader.json new file mode 100644 index 00000000..a26c6695 --- /dev/null +++ b/agency-indexes/DoE/Deeplynx-loader.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-07-17", + "metadataLastUpdated": "2023-07-17" + }, + "description": "'deeplynx-timeseries-loader' is a library designed to make it as easy as possible for users to download and access timeseries or tabular data from DeepLynx.", + "laborHours": 0.0, + "languages": [ + "Rust" + ], + "name": "Deeplynx-loader", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-Timeseries-Loader", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deeplynx_Airflow_Provider_Package.json b/agency-indexes/DoE/Deeplynx_Airflow_Provider_Package.json new file mode 100644 index 00000000..41ac3ce9 --- /dev/null +++ b/agency-indexes/DoE/Deeplynx_Airflow_Provider_Package.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-07-22", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The DeepLynx Airflow Provider Package is a python package used to interact with the data warehouse DeepLynx when using the workflow orchestration tool Apache Airflow. This python package is packaged together using the airflow package standard so that it can be easily installed and used in any Apache Airflow environment. This package is meant to encapsulate the DeepLynx API for use in Airflow so that any interactions with DeepLynx that a user may want to use in their Airflow workflow can be easily accomplished using this provider package. This allows us to develop, implement, and test our DeepLynx-Airflow interactions in one provider package repository, and then easily install and use this package in any airflow instance. This DeepLynx Airflow Provider Package will be used extensively by the DeepLynx DAG repository.", + "laborHours": 1079.2, + "languages": [ + "Python" + ], + "name": "Deeplynx Airflow Provider Package", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/airflow-provider-deeplynx", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deeplynx_Dag_Repository.json b/agency-indexes/DoE/Deeplynx_Dag_Repository.json new file mode 100644 index 00000000..92530ebb --- /dev/null +++ b/agency-indexes/DoE/Deeplynx_Dag_Repository.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2024-10-07" + }, + "description": "The DeepLynx DAG repository will contain several Airflow DAGs (Directed Acyclic Graphs) which will be used in the context of DeepLynx's deployed Apache Airflow instance. These DAGs will be used for multiple data management tasks for DeepLynx data, including but not limited to:\n- bringing data from various sources and tools into DeepLynx\n- managing sequential data workflows, such as running Python scripts on data to perform analysis and returning the results to DeepLynx\n- performing any necessary transformation or pre-processing on data coming into DeepLynx from external sources or out of DeepLynx to go to external applications", + "laborHours": 258.4, + "languages": [ + "Python" + ], + "name": "Deeplynx Dag Repository", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DLDAGS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deeplynx_Rust_Sdk.json b/agency-indexes/DoE/Deeplynx_Rust_Sdk.json new file mode 100644 index 00000000..912c49f4 --- /dev/null +++ b/agency-indexes/DoE/Deeplynx_Rust_Sdk.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-18" + }, + "description": "This software is a Rust package that interacts with the Application Programming Interface (API) suite provided by DeepLynx. A Rust codebase may import this package in order to have access to these methods for communicating with a DeepLynx instance.", + "laborHours": 0.0, + "languages": [ + "Rust" + ], + "name": "Deeplynx Rust Sdk", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-Rust_SDK", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deeplynx_Supervisory_Control_Adapter.json b/agency-indexes/DoE/Deeplynx_Supervisory_Control_Adapter.json new file mode 100644 index 00000000..4b51e9ae --- /dev/null +++ b/agency-indexes/DoE/Deeplynx_Supervisory_Control_Adapter.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-06-19", + "metadataLastUpdated": "2023-06-19" + }, + "description": "This software is intended to facilitate the sending of data from DeepLynx to some human machine interface (HMI). The HMI would read the data generated by this software and potentially make a physical change on a process which the HMI controls. This software enables a digital twin using DeepLynx to talk to an HMI, thereby making autonomous updates to the physical asset which is being twinned.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Deeplynx Supervisory Control Adapter", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Deep-Lynx-Supervisory-Control", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DefectSegNet.json b/agency-indexes/DoE/DefectSegNet.json new file mode 100644 index 00000000..ebf9001c --- /dev/null +++ b/agency-indexes/DoE/DefectSegNet.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2024-06-18" + }, + "description": "DefectSegNet for semantic segmentation of defects in Steels\nThe first and most important step of automating defect analysis is perceptual defect identification. In terms of digital image processing, semantic segmentation best emulates human recognition of defect features \u2013 it identifies the crystallographic defects and where they are located in a TEM micrograph. We solved this problem by developing DefectSegNet, a novel hybrid CNN algorithm for robust and automated semantic segmentation of three crystallographic defects, including line dislocations, precipitates and voids, that are commonly observed in structural metals and alloys.", + "laborHours": 1033.6, + "languages": [], + "name": "DefectSegNet", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ZEMG-UCONN/DefectSegNet", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Defining_a_new_information_exchange.json b/agency-indexes/DoE/Defining_a_new_information_exchange.json new file mode 100644 index 00000000..dc60aed6 --- /dev/null +++ b/agency-indexes/DoE/Defining_a_new_information_exchange.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This wiki page provides the public with all specifications needed to create a new information exchange (content model package).", + "laborHours": 243.2, + "name": "Defining a new information exchange", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/usginmodels/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/usginmodels", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DelPlasmid:_Finding_Plasmids_with_Deep_Learning_and_Machine_Learning_v1.json b/agency-indexes/DoE/DelPlasmid:_Finding_Plasmids_with_Deep_Learning_and_Machine_Learning_v1.json new file mode 100644 index 00000000..8e4bdfea --- /dev/null +++ b/agency-indexes/DoE/DelPlasmid:_Finding_Plasmids_with_Deep_Learning_and_Machine_Learning_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-03", + "metadataLastUpdated": "2021-09-03" + }, + "description": "Extrachromosomal genetic elements or plasmids are an important driver of DNA exchange and genetic innovation in prokaryotes. The success of plasmids has been attributed to their independent replication from host cell chromosomes and their frequent self-transfer. In recent years, the Department of Energy has recognized the importance of plasmid DNA to the viability and success of microbial communities and JGI has responded with funding to support the research and development of new methods and tools for the efficient sequencing of plasmid DNA. LBNL #2019-037 is responsive to this call.", + "laborHours": 0.0, + "languages": [], + "name": "DelPlasmid: Finding Plasmids with Deep Learning and Machine Learning v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wandreopoulos/deeplasmid.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Delaunay_density_diagnostic.json b/agency-indexes/DoE/Delaunay_density_diagnostic.json new file mode 100644 index 00000000..acb9f695 --- /dev/null +++ b/agency-indexes/DoE/Delaunay_density_diagnostic.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2022-03-24" + }, + "description": "The Delaunay density diagnostic helps detect and assess geometric scales within unstructured numerical data sets. The algorithm was first introduced in the paper \"Data-driven geometric scale detection via Delaunay interpolation\" by Andrew Gillette and Eugene Kur, 2022. More details can be found in that paper, as well as the included README file.", + "laborHours": 0.0, + "languages": [], + "name": "Delaunay density diagnostic", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ddd", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Delft3D_turbine_turbulence_module.json b/agency-indexes/DoE/Delft3D_turbine_turbulence_module.json new file mode 100644 index 00000000..67413a2e --- /dev/null +++ b/agency-indexes/DoE/Delft3D_turbine_turbulence_module.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The DOE has funded Sandia National Labs (SNL) to develop an open-source modeling tool to guide the design and layout of marine hydrokinetic (MHK) arrays to maximize power production while minimizing environmental effects. This modeling framework simulates flows through and around a MHK arrays while quantifying environmental responses. As an augmented version of the Dutch company, Deltares\u2019s, environmental hydrodynamics code, Delft3D, SNL-Delft3D includes a new module that simulates energy conversion (momentum withdrawal) by MHK devices with commensurate changes in the turbulent kinetic energy and its dissipation rate.", + "laborHours": 801480.8, + "languages": [ + "C++", + "Shell", + "HTML", + "C", + "MATLAB", + "Fortran" + ], + "name": "Delft3D turbine turbulence module", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SNL-Delft3D-CEC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Demand_Flexibility_Controls_Library_using_Semantics__DFLEXLIBS__v0.1.json b/agency-indexes/DoE/Demand_Flexibility_Controls_Library_using_Semantics__DFLEXLIBS__v0.1.json new file mode 100644 index 00000000..a35241d4 --- /dev/null +++ b/agency-indexes/DoE/Demand_Flexibility_Controls_Library_using_Semantics__DFLEXLIBS__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-10-02", + "metadataLastUpdated": "2023-10-05" + }, + "description": "DFLEXLIBS is a library/repository of HVAC-based demand flexibility control applications developed using Python. The library is based on portable control applications that exclusively contain control logic and are abstract to building details, such as point names and communication protocols. The library leverages semantic models and control platform-oriented interfaces to configure and run the controls in specific buildings. To date, the library contains two applications and two interfaces (for BOPTEST and VOLTTRON) and has been demonstrated in five heterogeneous buildings.", + "laborHours": 0.0, + "languages": [], + "name": "Demand Flexibility Controls Library using Semantics (DFLEXLIBS) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/DFLEXLIBS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Demand_Response_Dispatch_Tool.json b/agency-indexes/DoE/Demand_Response_Dispatch_Tool.json new file mode 100644 index 00000000..a69ba388 --- /dev/null +++ b/agency-indexes/DoE/Demand_Response_Dispatch_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-24", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The Demand Response (DR) Dispatch Tool uses price profiles to dispatch demand response resources and create load modifying profiles. These annual profiles are used as inputs to production cost models and regional planning tools (e.g., PROMOD). The tool has been effectively implemented in transmission planning studies conducted by the Western Electricity Coordinating Council via its Transmission Expansion Planning and Policy Committee. The DR Dispatch Tool can properly model the dispatch of DR resources for both reliability and economic conditions.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Demand Response Dispatch Tool", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Demand_Response_Quick_Assessment_Tool.json b/agency-indexes/DoE/Demand_Response_Quick_Assessment_Tool.json new file mode 100644 index 00000000..c1d4e871 --- /dev/null +++ b/agency-indexes/DoE/Demand_Response_Quick_Assessment_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "DRQAT (Demand Response Quick Assessment Tool) is the tool for assessing demand response saving potentials for large commercial buildings. This tool is based on EnergyPlus simulations of prototypical buildings and HVAC equipment. The opportunities for demand reduction and cost savings with building demand responsive controls vary tremendously with building type and location. The assessment tools will predict the energy and demand savings, the economic savings, and the thermal comfort impact for various demand responsive strategies. Users of the tools will be asked to enter the basic building information such as types, square footage, building envelope, orientation, utility schedule, etc. The assessment tools will then use the prototypical simulation models to calculate the energy and demand reduction potential under certain demand responsive strategies, such as precooling, zonal temperature set up, and chilled water loop and air loop set points adjustment.", + "homepageURL": "https://buildings.lbl.gov/demand-response-quick-assessment-tool-drqat", + "laborHours": 0.0, + "languages": [], + "name": "Demand Response Quick Assessment Tool", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://buildings.lbl.gov/demand-response-quick-assessment-tool-drqat", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://buildings.lbl.gov/demand-response-quick-assessment-tool-drqat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Demeter-W.json b/agency-indexes/DoE/Demeter-W.json new file mode 100644 index 00000000..75ac0e68 --- /dev/null +++ b/agency-indexes/DoE/Demeter-W.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Demeter-W, an open-access software written in Python, consists of extensible module packages. It is developed with statistical downscaling algorithms, to spatially and temporally downscale water demand data into finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. For better understanding of the driving forces and patterns for global water withdrawal, the researchers is able to utilize Demeter-W to reconstruct the data sets to examine the issues related to water withdrawals at fine spatial and temporal scales.", + "laborHours": 1124.8, + "name": "Demeter-W", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/demeter-w", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Demeter.json b/agency-indexes/DoE/Demeter.json new file mode 100644 index 00000000..7e65d372 --- /dev/null +++ b/agency-indexes/DoE/Demeter.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Demeter is a fully extensible, community-based land use land cover (LULC) downscaling and change detection model that allows for customization and/or additions from its user base.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Demeter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/demeter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dencity_Gem.json b/agency-indexes/DoE/Dencity_Gem.json new file mode 100644 index 00000000..2e1c5b78 --- /dev/null +++ b/agency-indexes/DoE/Dencity_Gem.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "This gem is an API client for DEnCity.org.", + "laborHours": 425.6, + "languages": [], + "name": "Dencity Gem", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/dencity-gem/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dencity-gem", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dendro-GRCA_ver._2.x.json b/agency-indexes/DoE/Dendro-GRCA_ver._2.x.json new file mode 100644 index 00000000..74c7031d --- /dev/null +++ b/agency-indexes/DoE/Dendro-GRCA_ver._2.x.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "Dendro-GRCA is a parallel and distributed partial differential equation solver to perform large scale simulations in general relativistic computational astrophysics problems such as merging black holes and neutron stars and also many other problems in computational astrophysics. This toolkit, the Dendro library is a large scale distributed memory adaptive octree framework. Dendro consists of efficient parallel data structures and algorithms to perform finite element methods and finite difference methods on 2:1 balanced arbitrary adaptive octrees. ", + "laborHours": 0.0, + "languages": [], + "name": "Dendro-GRCA ver. 2.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Dendro-GRCA", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dependency_Analysis_Project.json b/agency-indexes/DoE/Dependency_Analysis_Project.json new file mode 100644 index 00000000..22c8cf73 --- /dev/null +++ b/agency-indexes/DoE/Dependency_Analysis_Project.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-11-25", + "metadataLastUpdated": "2024-11-25" + }, + "description": "The Dependency Analysis Project creates datasets from package management ecosystems to determine\nwhat package a file was likely installed by, and provides tools to recognize implicit dependencies when\nsource code is available for a variety of language ecosystems. The overarching goal is to help answer the\nquestion: what software does a system use?", + "laborHours": 182.4, + "languages": [], + "name": "Dependency Analysis Project", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/dapper", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deploy_Tools.json b/agency-indexes/DoE/Deploy_Tools.json new file mode 100644 index 00000000..d9b0d709 --- /dev/null +++ b/agency-indexes/DoE/Deploy_Tools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "This repo contains tools to aid in the deployment of KBase software. The main script is deploy_cluster. It reads a config file which is typically named cluster.ini.", + "laborHours": 3465.6, + "languages": [], + "name": "Deploy Tools", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/deploy_tools", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deployment_Optimization_Tool__DOT_.json b/agency-indexes/DoE/Deployment_Optimization_Tool__DOT_.json new file mode 100644 index 00000000..556902fe --- /dev/null +++ b/agency-indexes/DoE/Deployment_Optimization_Tool__DOT_.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-08-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This tool was developed to assist in the design of in-place RF monitoring systems. This tool uses a brute force method to find the optimal location for RF receivers in a location of interest. This tool\ncurrently depends on the commercial Wireless InSite software from Remcom. Currently available to US Government users only.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Deployment Optimization Tool (DOT)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Depth-First_Atmospheric_River_lifecycle_Tracking__DART__v1.json b/agency-indexes/DoE/Depth-First_Atmospheric_River_lifecycle_Tracking__DART__v1.json new file mode 100644 index 00000000..709b0cc4 --- /dev/null +++ b/agency-indexes/DoE/Depth-First_Atmospheric_River_lifecycle_Tracking__DART__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "This algorithm will identify the genesis and track the lifecycle of atmospheric rivers. It can be applied in different global atmospheric river detection algorithms. It is one of the earliest atmospheric river lifecycle tracking algorithms.", + "laborHours": 60.8, + "languages": [], + "name": "Depth-First Atmospheric River lifecycle Tracking (DART) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-EESA/DART", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dereplication,_Aggregation_and_Scoring_Tool__DAS_Tool__v1.0.json b/agency-indexes/DoE/Dereplication,_Aggregation_and_Scoring_Tool__DAS_Tool__v1.0.json new file mode 100644 index 00000000..2a4df1b9 --- /dev/null +++ b/agency-indexes/DoE/Dereplication,_Aggregation_and_Scoring_Tool__DAS_Tool__v1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Communities of uncultivated microbes are critical to ecosystem function and microorganism health, and a key objective of metagenomic studies is to analyze organism-specific metabolic pathways and reconstruct community interaction networks. This requires accurate assignment of genes to genomes, yet existing binning methods often fail to predict a reasonable number of genomes and report many bins of low quality and completeness. Furthermore, the performance of existing algorithms varies between samples and biotypes. Here, we present a dereplication, aggregation and scoring strategy, DAS Tool, that combines the strengths of a flexible set of established binning algorithms. DAS Tools applied to a constructed community generated more accurate bins than any automated method. Further, when applied to samples of different complexity, including soil, natural oil seeps, and the human gut, DAS Tool recovered substantially more near-complete genomes than any single binning method alone. Included were three genomes from a novel lineage . The ability to reconstruct many near-complete genomes from metagenomics data will greatly advance genome-centric analyses of ecosystems.", + "laborHours": 3344.0, + "languages": [ + "NA" + ], + "name": "Dereplication, Aggregation and Scoring Tool (DAS Tool) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cmks/DAS_Tool/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmks/DAS_Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Design,_Analysis,_and_Operations_Toolkit__DAO-Tk_.json b/agency-indexes/DoE/Design,_Analysis,_and_Operations_Toolkit__DAO-Tk_.json new file mode 100644 index 00000000..d7822f5b --- /dev/null +++ b/agency-indexes/DoE/Design,_Analysis,_and_Operations_Toolkit__DAO-Tk_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-06", + "metadataLastUpdated": "2019-05-13" + }, + "description": "The Design, Analysis, and Operations Toolkit (DAO-Tk) is a software package that allows users to explore design optimization, operations decision, and performance characterization of concentrating solar power tower plants. Users interface with the tool through a scripting language, and results are reported in time series tables, plots, runtime logs, and design outputs. Users choose from a list of variables such as tower height, solar multiple, design-point irradiance, thermal storage size, etc., and specify information about the system using a list of parameters. The software can then optimize the specified variables to reduce the cost of energy produced by the system while meeting certain production requirements, accounting for uncertain weather and electricity price forecasts, and correcting for equipment failures or repair time. The DAO-Tk software is the first comprehensive design tool of it's kind to incorporate all of these aspects while being deployed as open source. ", + "laborHours": 106536.8, + "languages": [], + "name": "Design, Analysis, and Operations Toolkit (DAO-Tk)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dao-tk", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Design,_Integration_and_Synthesis_Platform_to_Advance_Tightly_Coupled_Hybrid_Energy_Systems__DISPATCHES__v0.1.0.json b/agency-indexes/DoE/Design,_Integration_and_Synthesis_Platform_to_Advance_Tightly_Coupled_Hybrid_Energy_Systems__DISPATCHES__v0.1.0.json new file mode 100644 index 00000000..ad0c7abc --- /dev/null +++ b/agency-indexes/DoE/Design,_Integration_and_Synthesis_Platform_to_Advance_Tightly_Coupled_Hybrid_Energy_Systems__DISPATCHES__v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-28", + "metadataLastUpdated": "2021-10-28" + }, + "description": "The DISPATCHES software will enable the design and optimization of Integrated Energy Systems (IES). The platform will support hybridizing existing generation facilities (such as nuclear and coal plants) as well as greenfield hybrid designs that incorporate advanced technologies (such as Advanced Modular Reactors and Coal FIRST), and it will enable the consideration of multiple technology options with different time constants. The design of the IES will be optimized for operation within the bulk power system via energy market signals (day ahead, real-time, and ancillary services) obtained from a production cost model. The goal of DISPATCHES is to identify flexible, dynamic designs that are responsive to grid market signals resulting in highly efficient, cost effective tightly coupled hybrid energy systems that can act as a \"black box\" to the grid to provide increased flexibility and resiliency.", + "laborHours": 0.0, + "languages": [], + "name": "Design, Integration and Synthesis Platform to Advance Tightly Coupled Hybrid Energy Systems (DISPATCHES) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gmlc-dispatches/dispatches", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Design_Analysis_Kit_for_Optimization_and_Terascale_Applications_6.0.json b/agency-indexes/DoE/Design_Analysis_Kit_for_Optimization_and_Terascale_Applications_6.0.json new file mode 100644 index 00000000..9ee85fa8 --- /dev/null +++ b/agency-indexes/DoE/Design_Analysis_Kit_for_Optimization_and_Terascale_Applications_6.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-09" + }, + "description": "Sandia's Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to: (1) enhance understanding of risk, (2) improve products, and (3) assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a computational model. However, Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. The algorithms implemented in Dakota aim to address challenges in performing these analyses with complex science and engineering models from desktop to high performance computers.", + "homepageURL": "https://dakota.sandia.gov/sites/default/files/docs/6.0/html-dev/files.html", + "laborHours": 3812676.8, + "languages": [], + "name": "Design Analysis Kit for Optimization and Terascale Applications 6.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/sites/default/files/docs/6.0/html-dev/files.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Designs_for_Risk_Evaluation_and_Management.json b/agency-indexes/DoE/Designs_for_Risk_Evaluation_and_Management.json new file mode 100644 index 00000000..a6f2fa34 --- /dev/null +++ b/agency-indexes/DoE/Designs_for_Risk_Evaluation_and_Management.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The Designs for Risk Evaluation and Management (DREAM) tool was developed as part of the effort to quantify the risk of geologic storage of carbon dioxide (CO2) under the U.S. Department of Energy's National Risk Assessment Partnership (NRAP). DREAM is an optimization tool created to identify optimal monitoring schemes that minimize the time to first detection of CO2 leakage from a subsurface storage formation. DREAM acts as a post-processer on user-provided output from subsurface leakage simulations. While DREAM was developed for CO2 leakage scenarios, it is applicable to any subsurface leakage simulation of the same output format. The DREAM tool is comprised of three main components: (1) a Java wizard used to configure and execute the simulations, (2) a visualization tool to view the domain space and optimization results, and (3) a plotting tool used to analyze the results. A secondary Java application is provided to aid users in converting common American Standard Code for Information Interchange (ASCII) output data to the standard DREAM hierarchical data format (HDF5). DREAM employs a simulated annealing approach that searches the solution space by iteratively mutating potential monitoring schemes built of various configurations of monitoring locations and leak detection parameters. This approach has proven to be orders of magnitude faster than an exhaustive search of the entire solution space. The user's manual illustrates the program graphical user interface (GUI), describes the tool inputs, and includes an example application.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Designs for Risk Evaluation and Management", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Detection_Framework_Testbed_and_Toolkit.json b/agency-indexes/DoE/Detection_Framework_Testbed_and_Toolkit.json new file mode 100644 index 00000000..7b27f378 --- /dev/null +++ b/agency-indexes/DoE/Detection_Framework_Testbed_and_Toolkit.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "The Detection Framework Testbed and Toolkit \n(DFTT) is a signal detection system that uses\nautomatically generated subspace and correlation detectors. \n\nDFTT is intended to facilitate the development and testing of algorithms for operating suites of such detectors. \n\nThe software is a generalization of the system described in Harris and Dodge (2011) and has been applied in contexts ranging from local borehole induced seismicity to large-scale teleseismic observations. \n\nThe software includes interactive applications for creating detection configurations, inspecting and \nediting templates, viewing detection statistics, viewing detected signals, classifying detectors and more.", + "laborHours": 102448.0, + "languages": [], + "name": "Detection Framework Testbed and Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DFTT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Detection_of_homologous_horizontal_gene_transfer_in_SNP_data.json b/agency-indexes/DoE/Detection_of_homologous_horizontal_gene_transfer_in_SNP_data.json new file mode 100644 index 00000000..3de7dd19 --- /dev/null +++ b/agency-indexes/DoE/Detection_of_homologous_horizontal_gene_transfer_in_SNP_data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "We study the detection of mutations, sequencing errors, and homologous horizontal gene transfers (HGT) in a set of closely related microbial genomes. We base the model on single nucleotide polymorphisms (SNP's) and break the genomes into blocks to handle the rearrangement problem. Then we apply a synamic programming algorithm to model whether changes within each block are likely a result of mutations, sequencing errors, or HGT.", + "homepageURL": "https://sourceforge.net/projects/hgtfinder", + "laborHours": 0.0, + "languages": [], + "name": "Detection of homologous horizontal gene transfer in SNP data", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sourceforge.net/projects/hgtfinder/files", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/hgtfinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Deterministic_Arrival_Time_Monitor.json b/agency-indexes/DoE/Deterministic_Arrival_Time_Monitor.json new file mode 100644 index 00000000..2e8554b4 --- /dev/null +++ b/agency-indexes/DoE/Deterministic_Arrival_Time_Monitor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-25", + "metadataLastUpdated": "2022-08-25" + }, + "description": "Repo for the deterministic approach for the arrival time monitor.", + "laborHours": 0.0, + "languages": [], + "name": "Deterministic Arrival Time Monitor", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/datm/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/datm", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DevOps_Cloud_on_the_fly.json b/agency-indexes/DoE/DevOps_Cloud_on_the_fly.json new file mode 100644 index 00000000..3d0d7008 --- /dev/null +++ b/agency-indexes/DoE/DevOps_Cloud_on_the_fly.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "DevOps cloud on the fly provides automated virtual machine creation on demand. This is accomplished using two very powerful software tools: Packer and Vagrant.", + "laborHours": 0.0, + "languages": [], + "name": "DevOps Cloud on the fly", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/devOpsCloudOnTheFly", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Devastator_Parallel_Discrete_Event_Simulation_Runtime__Devastator__v1.0.json b/agency-indexes/DoE/Devastator_Parallel_Discrete_Event_Simulation_Runtime__Devastator__v1.0.json new file mode 100644 index 00000000..af227053 --- /dev/null +++ b/agency-indexes/DoE/Devastator_Parallel_Discrete_Event_Simulation_Runtime__Devastator__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-17" + }, + "description": "The Devastator runtime is a modern C++ implementation of optimistic parallel discrete event simulation methods. Devastator allows simulation application code to productively specify their component and event functionality with C++14 constructs. It utilizes GASNet-EX for distributed memory communication and includes parallel performance optimizations such as light-weight thread message queues and asynchronous GVT. Furthermore, it supports efficient event broadcasts and pause-rewind-resume functionality to support periodic load balancing and outer loop optimization algorithms.", + "laborHours": 0.0, + "languages": [], + "name": "Devastator Parallel Discrete Event Simulation Runtime (Devastator) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cychan-lbnl/devastator.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Developer_Network.json b/agency-indexes/DoE/Developer_Network.json new file mode 100644 index 00000000..b054e1fb --- /dev/null +++ b/agency-indexes/DoE/Developer_Network.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "NREL's Developer Network, developer.nrel.gov, provides data that users can access to provide data to their own analyses, mobile and web applications. Developers can retrieve the data through a Web services API (application programming interface). The Developer Network handles overhead of serving up web services such as key management, authentication, analytics, reporting, documentation standards, and throttling in a common architecture, while allowing web services and APIs to be maintained and managed independently.", + "laborHours": 64736.8, + "name": "Developer Network", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/developer.nrel.gov/blob/master/source/terms.html.erb", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/developer.nrel.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Development_Container.json b/agency-indexes/DoE/Development_Container.json new file mode 100644 index 00000000..42a6f581 --- /dev/null +++ b/agency-indexes/DoE/Development_Container.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "This repository is a container for developing and deploying KBase modules. To use this, you must already have a \"runtime\" directory, which contains the neccesary binaries and libraries. For an idea of what is expected to be in this runtime, consult the bootstrap repository.", + "laborHours": 349.6, + "languages": [], + "name": "Development Container", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/dev_container", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Devil_Ray.json b/agency-indexes/DoE/Devil_Ray.json new file mode 100644 index 00000000..30cc538a --- /dev/null +++ b/agency-indexes/DoE/Devil_Ray.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "Devil Ray is a ray tracing library for high-order elements", + "laborHours": 38258.4, + "languages": [], + "name": "Devil Ray", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/devil_ray", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DiHydrogen.json b/agency-indexes/DoE/DiHydrogen.json new file mode 100644 index 00000000..1fc8ee39 --- /dev/null +++ b/agency-indexes/DoE/DiHydrogen.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-06", + "metadataLastUpdated": "2020-01-06" + }, + "description": "DiHydrogen is the second version of the Hydrogen fork of the well-known distributed linear algebra library, Elemental. \n\nDiHydrogen is a GPU-accelerated distributed multilinear algebra interface with a particular emphasis on the needs of the scalable distributed deep learning training and inference. \n\nDiHydrogen is part of the Livermore Big Artificial Neural Network (LBANN) software stack.", + "laborHours": 38456.0, + "languages": [], + "name": "DiHydrogen", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/dihydrogen", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DiTTo__Distribution_Transformation_Tool_.json b/agency-indexes/DoE/DiTTo__Distribution_Transformation_Tool_.json new file mode 100644 index 00000000..5353d8db --- /dev/null +++ b/agency-indexes/DoE/DiTTo__Distribution_Transformation_Tool_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2019-07-10" + }, + "description": "The Distribution Transformation Tool (DiTTo) provides a framework for converting between and modifying several different types of distribution model formats . These include commercial formats such as CYME, Synergi, DEW, ePHASORSIM as well as open source formats such as OpenDSS and GridLAB-D. DiTTo consists of an API which represents electrical equipment, configurations, settings and timeseries data. This API acts as an intermediary between different distribution model formats. Several modules for reading and writing the models connect to this API to facilitate easy conversion between formats. Once feeder models are converted into the intermediate API, analysis can be done on the feeder using a network module. The modification module allows changes to be made to the model in the intermediate API. This allows a clear workflow that supports reading a model from one format, performing analysis, making modifications and writing the model to a different format.", + "laborHours": 62639.2, + "languages": [ + "Python", + "Python" + ], + "name": "DiTTo (Distribution Transformation Tool)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ditto", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DiTour_OSS.json b/agency-indexes/DoE/DiTour_OSS.json new file mode 100644 index 00000000..2e872173 --- /dev/null +++ b/agency-indexes/DoE/DiTour_OSS.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Mobile digital signage software optimized for giving tours and trade shows.", + "laborHours": 2690.4, + "name": "DiTour OSS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ditour/ditour/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ditour/ditour", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DiagnosticsViewer.json b/agency-indexes/DoE/DiagnosticsViewer.json new file mode 100644 index 00000000..d37b7bf7 --- /dev/null +++ b/agency-indexes/DoE/DiagnosticsViewer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "The DiagnosticsViewer is a Django web application for uploading, sharing, and distributing any kind of structured output. The\u00a0output_viewer\u00a0project provides a convenient set of scripts for interacting with the app (it builds a JSON, uploads the relevant files, and manages account information on the client).\n", + "laborHours": 1079.2, + "languages": [], + "name": "DiagnosticsViewer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/DiagnosticsViewer", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dial.json b/agency-indexes/DoE/Dial.json new file mode 100644 index 00000000..6c0dc45e --- /dev/null +++ b/agency-indexes/DoE/Dial.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "dewittsj@ornl.gov" + }, + "date": { + "created": "2025-02-14", + "metadataLastUpdated": "2025-02-14" + }, + "description": "A key step in almost all scientific endeavors is answering the question: Given this data I already collected, what new data do I expect will yield the most useful information toward my scientific objective? The area of (sequential) experimental design has long been investigating answers to this question, but in recent years techniques from the machine learning subfield of active learning are increasingly applied. Researchers need a simple software tool for active learning applied to experimental design that can easily integrate into their existing workflows.\n\nThis computer code, Dial, provides a microservice in ORNL's INTERSECT ecosystem for active learning applied to experimental design. By being part of the INTERSECT ecosystem, Dial is simple to integrate into any INTERSECT-based workflow. Dial provides multiple backend options, where a backend is an implementation of a specific active learning method. Users can select the backend that performs best for their application. Developers can also add new backends as needed.\n\nAt its core, Dial receives a set of pre-existing measurements and input parameter bounds and then recommends one or more new sets of parameters to measure. Dial also includes interfaces to other microservices in the INTERSECT ecosystem so that it can be incorporated into INTERSECT campaigns.\n\nDial provides a simple, yet powerful interface to convert automated INTERSECT workflows into autonomous workflows that adapt based on the results that are obtained. A shared microservice for active learning prevents duplicated effort by each application team implementing its own adaptive design of experiments tool.", + "laborHours": 668.8, + "languages": [ + "Python" + ], + "name": "Dial", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/INTERSECT-DIAL/dial", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DiffPy-CMI-Python_libraries_for_Complex_Modeling_Initiative.json b/agency-indexes/DoE/DiffPy-CMI-Python_libraries_for_Complex_Modeling_Initiative.json new file mode 100644 index 00000000..19b2baa4 --- /dev/null +++ b/agency-indexes/DoE/DiffPy-CMI-Python_libraries_for_Complex_Modeling_Initiative.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Software to manipulate and describe crystal and molecular structures and set up structural refinements from multiple experimental inputs. Calculation and simulation of structure derived physical quantities. Library for creating customized refinements of atomic structures from available experimental and theoretical inputs.", + "homepageURL": "http://www.diffpy.org", + "laborHours": 0.0, + "name": "DiffPy-CMI-Python libraries for Complex Modeling Initiative", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.diffpy.org/products/diffpycmi/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.diffpy.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/DifferentialExpressionUtils.json b/agency-indexes/DoE/DifferentialExpressionUtils.json new file mode 100644 index 00000000..89596645 --- /dev/null +++ b/agency-indexes/DoE/DifferentialExpressionUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "Module to upload/download/export differential expression object.", + "laborHours": 66880.0, + "languages": [], + "name": "DifferentialExpressionUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/DifferentialExpressionUtils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Differentially_Private_DBSCAN.json b/agency-indexes/DoE/Differentially_Private_DBSCAN.json new file mode 100644 index 00000000..f0f8734c --- /dev/null +++ b/agency-indexes/DoE/Differentially_Private_DBSCAN.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-15185 O Differentially Private DBSCAN is a differential private clustering algorithm used for running experiments and conducting data analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 76.0, + "languages": [ + "Python3" + ], + "name": "Differentially Private DBSCAN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DP_DBSCAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Digital_Analytics,_Causal_Knowledge_Acquisition_and_Reasoning_for_Technical_Language_Processing.json b/agency-indexes/DoE/Digital_Analytics,_Causal_Knowledge_Acquisition_and_Reasoning_for_Technical_Language_Processing.json new file mode 100644 index 00000000..4f1780a0 --- /dev/null +++ b/agency-indexes/DoE/Digital_Analytics,_Causal_Knowledge_Acquisition_and_Reasoning_for_Technical_Language_Processing.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-26" + }, + "description": "Complex engineering systems such as nuclear power plants (NPPs) generate and collect large amounts of equipment reliability (ER) data elements that contain information on the status of components, assets, and systems. Some of this information is textual in form and can be found in documents such as incident reports (IRs) and work orders (WOs). Analyses of textual data in current NPPs-using natural language processing (NLP) methods-have been expanded over the last decade, and it is only recently that the true potential of such analyses has emerged. So far, applications of NLP methods have mostly been limited to classification and prediction, the goal being to identify the nature of the textual element (e.g., safety or non-safety related). Here, we target a more complex problem: automatically extracting knowledge from a textual element in order to assist system engineers in conducting system health assessments. Knowledge extraction is a very broad concept, and its definition may vary depending on the application context. Our methods are a blend of both rule-based and machine learning (ML) algorithms. For our purposes, knowledge extraction means identifying the systems or assets mentioned in a given textual element, as well as the type of event described (e.g., component failure or maintenance activity). In addition, we want to capture details such as measured quantities and the temporal/cause-effect relations between events. In this tool, we also demonstrate how textual data elements are preprocessed in order to handle typos, acronyms, and abbreviations. One main feature of these methods is that they are not based solely on data, but are in fact model-based. In other words, they also rely on MBSE models that are designed to capture-from a functional point of view-the architecture of the systems/assets under consideration. The main purpose of such models is to digitally emulate system engineers' knowledge of system and asset architecture and to identify dependencies among systems, assets, and components. Provided these models, analyses of textual and numeric ER data can be performed by first identifying the OPM model elements to which the ER data elements are referring. The relationships between ER data elements are then identified by checking for any temporal or logical dependencies.", + "laborHours": 7265.6, + "languages": [ + "Python" + ], + "name": "Digital Analytics, Causal Knowledge Acquisition and Reasoning for Technical Language Processing", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DACKAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Digital_Image_Correlation_Engine_v.2.0.json b/agency-indexes/DoE/Digital_Image_Correlation_Engine_v.2.0.json new file mode 100644 index 00000000..71302963 --- /dev/null +++ b/agency-indexes/DoE/Digital_Image_Correlation_Engine_v.2.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "DICe is a 2D and stereo image correlation software package that determines motion and deformation of objects from sequences of digital images.", + "laborHours": 0.0, + "languages": [ + "C++, Javascript" + ], + "name": "Digital Image Correlation Engine v.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dicengine/dice/releases/tag/v2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Digital_Image_Correlation_Engine_v.3.0.json b/agency-indexes/DoE/Digital_Image_Correlation_Engine_v.3.0.json new file mode 100644 index 00000000..2183c4c5 --- /dev/null +++ b/agency-indexes/DoE/Digital_Image_Correlation_Engine_v.3.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-08-16" + }, + "description": "DICe is an open source digital image correlation (DIC) tool intended for use as a module in an external application or as a standalone analysis code. It's primary capability is computing full-field displacements and strains from sequences of digital These images are typically of a material sample undergoing a materials characterization experiment, but DICe is also useful for other applications (for example, trajectory tracking). DICe is machine portable (Windows, Linux and Mac) and can be effectively deployed on a high performance computing platform. Capabilities from DICe can be invoked through a library interface, via source code integration of DICe classes or through a graphical user interface.", + "laborHours": 45128.8, + "languages": [], + "name": "Digital Image Correlation Engine v.3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dicengine/dice", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Digital_Twin_Analytics_Search.json b/agency-indexes/DoE/Digital_Twin_Analytics_Search.json new file mode 100644 index 00000000..a72d14ab --- /dev/null +++ b/agency-indexes/DoE/Digital_Twin_Analytics_Search.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-11-08", + "metadataLastUpdated": "2023-11-08" + }, + "description": "The purpose of the software is to provide initial machine learning results to an unknown data set.", + "laborHours": 0.0, + "languages": [ + "Python", + "R" + ], + "name": "Digital Twin Analytics Search", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Digital-Twin-Analytics-SEARCH", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dimensionality_Reduction_Library_v_0.2.json b/agency-indexes/DoE/Dimensionality_Reduction_Library_v_0.2.json new file mode 100644 index 00000000..c5ebffcf --- /dev/null +++ b/agency-indexes/DoE/Dimensionality_Reduction_Library_v_0.2.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Dimensionality Reduction Library is a C++ library for dimensionality reduction. In the context of this library, dimensionality reduction is considered to consist of 1)estimation of the intrinsic dimensionality using sampled data, 2) Finding maps that reduce the dimensionality of data (forward map) or increase the dimensionality of data (reverse map) and 3) mapping arbitray coordinates to high and low dimensionalities. The library is intended to provide a consistent interface to multiple dimensionality reduction algorithms with an efficient C++ interface that runs efficiently on multicore architectures. A few routines have been optimized with an option for GPU acceleration or distributed computation. Currently the library offers intrinsic dimensionality estimation using point-PCA reconstruction error and/ residual variance. The following dimensionality reduction methods have been implemented: Principal Component Analysis Multidimensional Scaling Locally Linear Embedding IsoMap Autoencoder Neutral Networks An executable is also supplied that can be built to allow for command-line access to the library routines. A description for an application of the library for molecular structure analysis has been published.", + "laborHours": 6976.8, + "languages": [ + "JavaScript" + ], + "name": "Dimensionality Reduction Library v 0.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/dimensionality-reduction-library", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dimensionally_Aligned_Signal_Processing_Algorithms.json b/agency-indexes/DoE/Dimensionally_Aligned_Signal_Processing_Algorithms.json new file mode 100644 index 00000000..ba9e76a1 --- /dev/null +++ b/agency-indexes/DoE/Dimensionally_Aligned_Signal_Processing_Algorithms.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "stewartsl@ornl.gov" + }, + "date": { + "created": "2024-01-12", + "metadataLastUpdated": "2024-01-12" + }, + "description": "Dimensionally aligned signal projection (DASP) algorithms are used to analyze fast Fourier transforms (FFTs) and generate visualizations that help focus on the harmonics for specific signals. At a high level, these algorithms extract the FFT segments around each harmonic frequency center, and then align them in equally sized arrays ordered by increasing distance from the base frequency. This allows for a focused view of the harmonic frequencies, which, among other use cases, can enable machine learning algorithms to more easily identify salient patterns. \n \nThe DASP library is implemented in Python and contains four types of algorithms for implementing these feature engineering techniques: fixed harmonically aligned signal projection (HASP), decimating HASP, interpolating HASP, and frequency aligned signal projection (FASP). Each algorithm returns a numerical array, which can be visualized as an image. For consistency FASP, which is the terminology used for the short-time Fourier transform, has been implemented as part of the library to provide a similar interface to the STFT of the raw signal. Additionally, the library contains an algorithm to generate artificial signals with basic customizations such as the base frequency, sample rate, duration, number of harmonics, noise, and number of signals.\n \nFinally, the library provides multiple interactive visualizations, each implemented using IPyWidgets and work in a Jupyter environment. A dashboard-style visualization is provided, which contains some common signal-processing visual components (signal, FFT, spectrogram) updating in unison with the HASP functions (see Figure 1 below). Separate from the dashboard, an independent visualization is provided for each of the DASP algorithms as well as the artificial signal generator. These visualizations are included in the library to aid in developing an intuitive understanding how the algorithms are affected by different input signals and parameter selections.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Dimensionally Aligned Signal Processing Algorithms", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/dasp-stacker", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Direct-FUSE.json b/agency-indexes/DoE/Direct-FUSE.json new file mode 100644 index 00000000..d4ce0bdf --- /dev/null +++ b/agency-indexes/DoE/Direct-FUSE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-08", + "metadataLastUpdated": "2020-05-08" + }, + "description": "The Direct-FUSE framework supports multiple FUSE file systems as well as other, custom user-level file\nsystems in user space without the need to cross the user/kernel boundary into the FUSE kernel module.\nAll layers of Direct-FUSE are in user space, and applications can directly use pre-defined unified file\nsystem calls to interact with different user-defined file systems. Our performance results show that Direct-\nFUSE can outperform some native FUSE file systems by 11.9% on average and does not add significant\noverhead over backend file systems.\n", + "laborHours": 13588.8, + "languages": [], + "name": "Direct-FUSE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/direct-fuse", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Direct-Sampling_Beam_Position_Monitor__dsbpm__v1.0.json b/agency-indexes/DoE/Direct-Sampling_Beam_Position_Monitor__dsbpm__v1.0.json new file mode 100644 index 00000000..a210836e --- /dev/null +++ b/agency-indexes/DoE/Direct-Sampling_Beam_Position_Monitor__dsbpm__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "Direct-Sampling Beam Position Monitor is an FPGA gateware and embedded firmware that run on evaluation kits (either Xilinx ZCU111 or Xilinx ZCU208 ) that digitizes signals up to 4GSPS and 4GHz analog bandwidth, which can be synchronized to the accelerator timing system, providing synchronous sampling frequency/phase digitization. In addition to these capabilities, a proof of concept for a beam position monitor is also present, providing an envelope detection algorithm capable of determining the transverse beam position for an electron circular accelerator, such as ALS/ALS-U.", + "laborHours": 0.0, + "languages": [], + "name": "Direct-Sampling Beam Position Monitor (dsbpm) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/LBNL-DSBPM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DiscoFluxM_version_1.x.json b/agency-indexes/DoE/DiscoFluxM_version_1.x.json new file mode 100644 index 00000000..71a52371 --- /dev/null +++ b/agency-indexes/DoE/DiscoFluxM_version_1.x.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-22" + }, + "description": "DiscoFluxM is software for modeling the deformation behavior of crystalline materials within the third-party finite-element based software, MOOSE. The software enables full-field crystal plasticity finite element simulations of deformation processes of metals and other crystalline materials. DiscoFluxM is an implementation of the DiscoFlux theoretical and algorithmic framework for coupling single-crystal plasticity with dislocation transport. The \ncontinuum mesoscale modeling framework is founded upon a nonlocal dislocation-density based crystal plasticity theory. The nonlocal theory couples continuum dislocation transport with an otherwise spatially-local single-crystal model employing nonlinear thermoelasticity and crystallographic plasticity. Dislocation transport is modeled by enforcing dislocation conservation at a slip-system level through the solution of advection-diffusion equations. The configuration of geometrically necessary dislocation density gives rise to a back-stress that inhibits or accentuates the flow of dislocations.", + "laborHours": 1778.4, + "languages": [], + "name": "DiscoFluxM version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/subhendu-LANL/DiscoFluxM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dispatch_Optimization_Variable_Engine.json b/agency-indexes/DoE/Dispatch_Optimization_Variable_Engine.json new file mode 100644 index 00000000..a2669c2d --- /dev/null +++ b/agency-indexes/DoE/Dispatch_Optimization_Variable_Engine.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "The Dispatch Optimization Variable Engine (DOVE) is software tool written in python, developed at Idaho National Laboratory (INL) that provides an easily accessible application-programming-interface (API) to performing resource dispatch optimization analysis for integrated energy system (IES) configurations. DOVE is an integral part of the Framework for Optimization of Resources and Economics (FORCE) software suite and is leveraged by codes such as the Holistic Energy Resource Optimization Network (HERON) and the Optimization of Real-Time Capacity Allocation (ORCA). The philosophy behind DOVE is to provide a modular software solution to IES planning and operation by utilizing state-of-the-art algorithms and machine learning. The goal is to accurately capture the dispatching behavior of a complex energy system given varying time-dependent signals for demand and commodity pricing.", + "laborHours": 1535.2, + "languages": [ + "Python" + ], + "name": "Dispatch Optimization Variable Engine", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DOVE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dispatch_Table.json b/agency-indexes/DoE/Dispatch_Table.json new file mode 100644 index 00000000..508e87ad --- /dev/null +++ b/agency-indexes/DoE/Dispatch_Table.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-09-19", + "metadataLastUpdated": "2018-10-23" + }, + "description": "The Energy Market Price Response (EMPR) service is provided by the device, which shifts demand from high price periods in the day to low price periods. The device would consume energy when prices are low and release energy (or defer consumption) when prices are high. This load shifting benefits the individual consumers and society in general by shifting consumption to periods when production resources are available at lower costs. The service could be driven by price forecasts of the day-ahead market or shorter time periods. The service could be facilitated by demand response aggregators, utilities, or other load serving entities.", + "laborHours": 76.0, + "languages": [], + "name": "Dispatch Table", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/TomEdmunds/DispatchTable", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Display_Builder_Web_Runtime.json b/agency-indexes/DoE/Display_Builder_Web_Runtime.json new file mode 100644 index 00000000..e719da50 --- /dev/null +++ b/agency-indexes/DoE/Display_Builder_Web_Runtime.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "kasemirk@ornl.gov" + }, + "date": { + "created": "2021-10-12", + "metadataLastUpdated": "2021-10-12" + }, + "description": "A Web Runtime for the Display Builder. Can load and display most control system operator screens that have been created with the desktop version of the Control System Studio Display Builder, but presents them in a web browser without requiring any setup on the end-user's computer. Part of ORNL-EPICS.", + "laborHours": 0.0, + "languages": [ + "Java", + "Java", + "Java", + "CSS", + "HTML", + "JavaScript" + ], + "name": "Display Builder Web Runtime", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-epics/dbwr", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Disruption_Tolerant_Key_Management_Monitoring_for_Stream-Processing_Architecture_for_Real-time_Cyber-physical_Security__DTKM-SPARCS__v0.9.json b/agency-indexes/DoE/Disruption_Tolerant_Key_Management_Monitoring_for_Stream-Processing_Architecture_for_Real-time_Cyber-physical_Security__DTKM-SPARCS__v0.9.json new file mode 100644 index 00000000..7ce2268e --- /dev/null +++ b/agency-indexes/DoE/Disruption_Tolerant_Key_Management_Monitoring_for_Stream-Processing_Architecture_for_Real-time_Cyber-physical_Security__DTKM-SPARCS__v0.9.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-08-15", + "metadataLastUpdated": "2019-06-25" + }, + "description": "This code is a set of modules designed to monitor key exchange protocols used to securely communicate with equipment in the power grid and alert on deviations from the expected protocol, including both attacks and failures.", + "laborHours": 60.8, + "languages": [], + "name": "Disruption Tolerant Key Management Monitoring for Stream-Processing Architecture for Real-time Cyber-physical Security (DTKM-SPARCS) v0.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/dtkm-sparcs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DistGANS-_Distributed_Generative_Adversarial_Neural_Networks.json b/agency-indexes/DoE/DistGANS-_Distributed_Generative_Adversarial_Neural_Networks.json new file mode 100644 index 00000000..418b18db --- /dev/null +++ b/agency-indexes/DoE/DistGANS-_Distributed_Generative_Adversarial_Neural_Networks.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "DistGANs is a Python package to perform distributed training of conditional generative adversarial neural networks for multi-class labeled image data.\nDistGANs partitionins the training data according to data labels, and enhances scalability by performing a parallel training where multiple generators are concurrently trained, each one of them focusing on a single data label.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "DistGANS- Distributed Generative Adversarial Neural Networks", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/DistGANs", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Distributed_Berkeley_Efficient_Long-Read_to_Long-Read_Aligner_and_Overlapper__DiBELLA__v1.0.0.json b/agency-indexes/DoE/Distributed_Berkeley_Efficient_Long-Read_to_Long-Read_Aligner_and_Overlapper__DiBELLA__v1.0.0.json new file mode 100644 index 00000000..66e32d5a --- /dev/null +++ b/agency-indexes/DoE/Distributed_Berkeley_Efficient_Long-Read_to_Long-Read_Aligner_and_Overlapper__DiBELLA__v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-16", + "metadataLastUpdated": "2021-03-16" + }, + "description": "We present a parallel algorithm and scalable implementation for genome analysis, specifically the problem of finding overlaps and alignments for data from \"third generation\" long read sequencers. While long sequences of DNA offer enormous advantages for biological analysis and insight, current long read sequencing instruments have high error rates and therefore require different approaches to analysis than their short read counterparts. Our work focuses on an efficient distributed-memory parallelization of an accurate single-node algorithm for overlapping and aligning long reads. We achieve scalability of this irregular algorithm by addressing the competing issues of increasing parallelism, minimizing communication, constraining the memory footprint, and ensuring good load balance. The resulting application, DiBELLA, is the first distributed memory overlapper and aligner specifically designed for long reads and parallel scalability.", + "homepageURL": "https://sourceforge.net/projects/dibella", + "laborHours": 0.0, + "languages": [], + "name": "Distributed Berkeley Efficient Long-Read to Long-Read Aligner and Overlapper (DiBELLA) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/dibella", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Distributed_Energy_Resources_Customer_Adoption_Model__DER-CAM__v5.9.json b/agency-indexes/DoE/Distributed_Energy_Resources_Customer_Adoption_Model__DER-CAM__v5.9.json new file mode 100644 index 00000000..ebf788f1 --- /dev/null +++ b/agency-indexes/DoE/Distributed_Energy_Resources_Customer_Adoption_Model__DER-CAM__v5.9.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-16", + "metadataLastUpdated": "2018-10-17" + }, + "description": "The Distributed Energy Resources Customer Adoption Model (DER-CAM) is a powerful and comprehensive decision support tool that primarily serves the purpose of finding optimal distributed energy resource (DER) investments in the context of either buildings or multi-energy microgrids. \n\nVersion 5.9 introduces significant advancements to DER-CAM, including support for wholesale market integration (ancillary services), storage aging effects, improved solar thermal collector modeling, improved part-load efficiency modeling for conventional generators, added support for hydro generation, among others.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 5335.2, + "languages": [], + "name": "Distributed Energy Resources Customer Adoption Model (DER-CAM) v5.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Distributed_File_System_Test_Using_Small_FilesV1.1.json b/agency-indexes/DoE/Distributed_File_System_Test_Using_Small_FilesV1.1.json new file mode 100644 index 00000000..af194855 --- /dev/null +++ b/agency-indexes/DoE/Distributed_File_System_Test_Using_Small_FilesV1.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "This program tests distributed filesystems using small files for lock and metadata contention. It is useful for debugging.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Distributed File System Test Using Small FilesV1.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Distributed_File_System_Utilities_to_Manage_Large_DatasetsVersion_0.5.json b/agency-indexes/DoE/Distributed_File_System_Utilities_to_Manage_Large_DatasetsVersion_0.5.json new file mode 100644 index 00000000..1fb0ece7 --- /dev/null +++ b/agency-indexes/DoE/Distributed_File_System_Utilities_to_Manage_Large_DatasetsVersion_0.5.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "FileUtils provides a suite of tools to manage large datasets typically created by large parallel MPI applications. They are written in C and use standard POSIX I/Ocalls. The current suite consists of tools to copy, compare, remove, and list. The tools provide dramatic speedup over existing Linux tools, which often run as a single process.", + "laborHours": 18194.4, + "languages": [], + "name": "Distributed File System Utilities to Manage Large DatasetsVersion 0.5", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/hpc/mpifileutils/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/fileutils", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Distributed_Optimal_and_Predictive_Energy_Resources__DOPER__v1.0.json b/agency-indexes/DoE/Distributed_Optimal_and_Predictive_Energy_Resources__DOPER__v1.0.json new file mode 100644 index 00000000..9088bd51 --- /dev/null +++ b/agency-indexes/DoE/Distributed_Optimal_and_Predictive_Energy_Resources__DOPER__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-15", + "metadataLastUpdated": "2019-10-15" + }, + "description": "This is a controller for distributed energy resources (i.e. photovoltaics, storage,..) based on model predictive control. It is written in Python.", + "laborHours": 4453.6, + "languages": [], + "name": "Distributed Optimal and Predictive Energy Resources (DOPER) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/DOPER", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Distribution_System_Dataset_Generator_for_AI_Applications_[SWR-24-75].json b/agency-indexes/DoE/Distribution_System_Dataset_Generator_for_AI_Applications_[SWR-24-75].json new file mode 100644 index 00000000..a85f8e56 --- /dev/null +++ b/agency-indexes/DoE/Distribution_System_Dataset_Generator_for_AI_Applications_[SWR-24-75].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-19", + "metadataLastUpdated": "2024-11-19" + }, + "description": "This software is a simple, light-weight python package to generate pytorch compatible machine learning graph dataset representing electric power distribution system. User is able to use these graph datasets to test their graph generation artificial intelligence (AI) models, link prediction AI models, graph classification AI models and so much more. This package uses grid-data-models (https://github.com/NREL-Distribution-Suites/grid-data-models) as input data format for power distribution system. NREL-Ditto (https://github.com/NREL-Distribution-Suites/ditto) tool can be leveraged to transform popular distribution system file formats such as opendss, cyme and synergi to grid-data-models.", + "laborHours": 187963.2, + "languages": [ + "Python" + ], + "name": "Distribution System Dataset Generator for AI Applications [SWR-24-75]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-Distribution-Suites/gridai", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Distribution_System_Model_Calibration_Algorithms.json b/agency-indexes/DoE/Distribution_System_Model_Calibration_Algorithms.json new file mode 100644 index 00000000..cdfc326b --- /dev/null +++ b/agency-indexes/DoE/Distribution_System_Model_Calibration_Algorithms.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2022-10-05" + }, + "description": "SAND2021-15065 O This release contains Python code for two distribution system model calibration algorithms as well as some sample data and documentation for the algorithms and code. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python 3.7.3" + ], + "name": "Distribution System Model Calibration Algorithms", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/distribution-system-model-calibration", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/District_EnErgy_Planner__DEEP__v2.json b/agency-indexes/DoE/District_EnErgy_Planner__DEEP__v2.json new file mode 100644 index 00000000..fbd99d1b --- /dev/null +++ b/agency-indexes/DoE/District_EnErgy_Planner__DEEP__v2.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-11" + }, + "description": "The District EnErgy Planner - DEEP is an Mixed Integer Linear Programming (MILP) optimization software tool to solve district energy system, technology configuration, operation strategies, and energy retail business schemes. DEEP takes user input energy demand on heating, cooling and electricity demand. Energy loss through pipeline is calculated for heating and cooling from central plants. The optimal system configuration to minimize the district energy system life cycle cost or minimize CO2 emission is calculated based on energy balance equations and various constraints. The recent update on DEEP include a feature of waste heat utilization energy balance based optimization to take into accounts of different temperature bands of heat into account to maximize system efficiency. Another feature is to optimize district energy retail by provide optimal pricing scheme for heating, cooling and electricity to end users to incorporate district to grid demand response.", + "laborHours": 0.0, + "languages": [], + "name": "District EnErgy Planner (DEEP) v2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/deep_ceg_lbl/deep_ceg_lbl/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Diventi.json b/agency-indexes/DoE/Diventi.json new file mode 100644 index 00000000..8cc47b24 --- /dev/null +++ b/agency-indexes/DoE/Diventi.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-09-18" + }, + "description": "Diventi provides a write optimized index of network logs such as netflow or zeek. The program will ingest various network traffic logs (zeek connection logs or NetflowV5, v9 or IPFix logs) and index each IP address and time of its activity. This database can then be queried for timely tracking of network activity. It currently uses the ft-index library from Percona but is adaptable to any key-value store that supports the Berkeley DB api.SAND2019-15037 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 6642.4, + "languages": [ + "C++", + "Makefile", + "Python" + ], + "name": "Diventi", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/opendiventi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Diverse_Super-Resolution__diversity_SR_.json b/agency-indexes/DoE/Diverse_Super-Resolution__diversity_SR_.json new file mode 100644 index 00000000..22a3cb0e --- /dev/null +++ b/agency-indexes/DoE/Diverse_Super-Resolution__diversity_SR_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-04-23", + "metadataLastUpdated": "2021-04-23" + }, + "description": "Deep learning tools for enhancing the spatial resolution of wind data. The software is developed in Python using the TensorFlow deep learning package. Models for diversity super-resolution is provided. Included in the package are pretrained models with example code/data to perform the super-resolution as well as tools of training models for different enhancement- or data-types. The super-resolution is an inherently ill-conditioned problem, with multiple high-resolution fields plausibly mapping to the same coarse field. Considitional GANs provide a framework for generating a distribution of high-resolution realizations from a given low-resolution input. Stochastic estimation is used to inform the network of the expected degree and location of sub-grid diversity. The package includes a pretrained network to generate distributions of 10x-enhanced fields of wind data.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Diverse Super-Resolution (diversity_SR)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/diversity_SR", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DnMFk_.json b/agency-indexes/DoE/DnMFk_.json new file mode 100644 index 00000000..10e45f80 --- /dev/null +++ b/agency-indexes/DoE/DnMFk_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The holistic analysis and understanding of the latent (that is, not-directly observable) variables and patterns buried in large datasets is crucial for data-driven science, decision making and emergency response. Such exploratory analyses require devising unsupervised learning methods for data mining and extraction of the latent features, and non-negative matrix factorization (NMF) is one of the prominent such methods. % to extract interpretable latent features, with dimensionality reduction for data mining and blind source separation. NMF is based on compute-intense non-convex constrained minimization, which, for large datasets requires fast and distributed algorithms. However, current parallel implementations of NMF fail to estimate the number of latent features. In practice, identifying these features is both difficult and significant for pattern recognition and latent feature analysis, especially for large dense matrices. In this paper, we introduce a distributed NMF algorithm coupled with distributed custom clustering followed by a stability analysis on dense data, which we call DnMFk, to determine the number of latent variables. The results on synthetic data and the classical Swimmer data set demonstrate the accuracy of model determination while scaling nearly linearly across multiple processors for large data. Further, we employ DnMFk to determine the number of hidden features from a tera byte (TB) matrix.", + "laborHours": 0.0, + "languages": [], + "name": "DnMFk ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/DnMFkCPP", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Domain-decomposition_nonlinear_manifold_reduced_order_model.json b/agency-indexes/DoE/Domain-decomposition_nonlinear_manifold_reduced_order_model.json new file mode 100644 index 00000000..f991c830 --- /dev/null +++ b/agency-indexes/DoE/Domain-decomposition_nonlinear_manifold_reduced_order_model.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-27", + "metadataLastUpdated": "2024-08-27" + }, + "description": "This software combines nonlinear-manifold reduced order models (NM-ROMs) with domain\ndecomposition (DD) techniques. NM-ROMs, which utilize a shallow, sparse autoencoder trained with full\norder model (FOM) snapshot data, approximate the FOM state on a nonlinear manifold. These models\noffer advantages over linear-subspace ROMs (LS-ROMs) particularly in scenarios with slowly decaying\nKolmogorov n-width. However, the training of NM-ROMs involves a number of parameters that scale with\nthe size of the FOM, and storing high-dimensional FOM snapshots can significantly increase the cost of\nROM training for extreme-scale problems.\nTo mitigate these costs, the software employs DD to partition the FOM into smaller subdomains,\ncomputes NM-ROMs for each, and then integrates these to form a global NM-ROM. This strategy offers\nmultiple benefits: it enables parallel training of subdomain NM-ROMs, reduces the number of parameters\nneeded, decreases the dimensional requirements of subdomain FOM training data, and allows for\ncustomization to the unique characteristics of each FOM subdomain. The use of a shallow, sparse\nautoencoder architecture in each subdomain NM-ROM facilitates the application of hyper-reduction (HR),\nsimplifying the nonlinear complexities and enhancing computational speed.\nThis software marks the inaugural application of NM-ROM combined with HR to a DD problem. It features\nan algebraic DD reformulation of the FOM, training of NM-ROMs with HR for each subdomain, and\nemploys a sequential quadratic programming (SQP) solver for the evaluation of the coupled global NMROM.\nThe effectiveness of the DD NM-ROM with HR is numerically demonstrated on the 2D steady-state\nBurgers' equation, showing an order of magnitude improvement in accuracy over the DD LS-ROM with\nHR.", + "laborHours": 3055.2, + "languages": [], + "name": "Domain-decomposition nonlinear manifold reduced order model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DD-NM-ROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DomainAnnotation.json b/agency-indexes/DoE/DomainAnnotation.json new file mode 100644 index 00000000..b1f38ff3 --- /dev/null +++ b/agency-indexes/DoE/DomainAnnotation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "DomainAnnotation is a SDK port of the old Gene Families service, which finds domains (from public protein domain libraries such as COGs and Pfam) in proteins in a user-supplied genome.", + "laborHours": 10564.0, + "languages": [], + "name": "DomainAnnotation", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/DomainAnnotation", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Domain_Reconniassance_Robot__DR._ROBOT__Beta_0.1.json b/agency-indexes/DoE/Domain_Reconniassance_Robot__DR._ROBOT__Beta_0.1.json new file mode 100644 index 00000000..26f7507c --- /dev/null +++ b/agency-indexes/DoE/Domain_Reconniassance_Robot__DR._ROBOT__Beta_0.1.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "This tool can be used to enumerate the subdomains associated with a company by aggregating the results of multiple OSINT (Open Source Intelligence) tools.", + "laborHours": 1459.2, + "languages": [ + "Bash", + "Perl", + "Python", + "Ruby" + ], + "name": "Domain Reconniassance Robot (DR. ROBOT) Beta 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/dr_robot", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "Beta 0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Domi.json b/agency-indexes/DoE/Domi.json new file mode 100644 index 00000000..3b4635b1 --- /dev/null +++ b/agency-indexes/DoE/Domi.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Domi (Greek for \"structure\") is a Trilinos package that provides support for multi-dimensional data arrays distributed over multiple processors of a high performance computing system. The software supports data arrays of arbitrary number of dimensions mapped to a multi-dimensional grid of processors. Domi provides local access to the data, as well as the ability to compute global quantities such as norms, maxima and minima. Data arrays can be constructed with boundary and communication padding, necessary for finite difference algorithms, and provides high-level methods for communicating data between processors to update these buffers. The distributed maps and vectors in Domi can be converted to the equivalent data structures in Epetra and Tpetra (both of which assume unstructured data), using view semantics when appropriate, for use with other Trilinos solvers.", + "laborHours": 10336.0, + "languages": [ + "CMake", + "C++" + ], + "name": "Domi", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Domi/blob/main/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Domi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Double_Visual_Defense.json b/agency-indexes/DoE/Double_Visual_Defense.json new file mode 100644 index 00000000..363b0bf8 --- /dev/null +++ b/agency-indexes/DoE/Double_Visual_Defense.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2025-04-16", + "metadataLastUpdated": "2025-04-16" + }, + "description": "This is the official code for the paper \"Double Visual Defense: Adversarial Pre-training and Instruction\nTuning for Improving Vision-Language Model Robustness\". This code can be used to produce vision\nlanguage models (VLMs), like LLaVA, with enhanced robustness to adversarial attacks (e.g. jailbreaks).", + "laborHours": 225188.0, + "languages": [], + "name": "Double Visual Defense", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zw615/Double_Visual_Defense", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Doubly_Distributed_Transactions.json b/agency-indexes/DoE/Doubly_Distributed_Transactions.json new file mode 100644 index 00000000..5e88d124 --- /dev/null +++ b/agency-indexes/DoE/Doubly_Distributed_Transactions.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Doubly Distributed Transactions (D2T) offers a technique for managing operations from a set of parallel clients with a collection of distributed services. It detects and manages faults. Example code with a test harness is also provided", + "laborHours": 61651.2, + "languages": [ + "C++", + "C" + ], + "name": "Doubly Distributed Transactions", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/d2t", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Downscaled_Climate_Data_Dashboard.json b/agency-indexes/DoE/Downscaled_Climate_Data_Dashboard.json new file mode 100644 index 00000000..f5c84e8a --- /dev/null +++ b/agency-indexes/DoE/Downscaled_Climate_Data_Dashboard.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-07-03", + "metadataLastUpdated": "2023-07-03" + }, + "description": "Provides a central location for viewing and comparing different methods for downscaling coarse resolution\nclimate model output.", + "laborHours": 0.0, + "languages": [], + "name": "Downscaled Climate Data Dashboard", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Downscaled-Climate-Data-Dashboard", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dr.L:_Distributed_Recursive__Graph__Layout.json b/agency-indexes/DoE/Dr.L:_Distributed_Recursive__Graph__Layout.json new file mode 100644 index 00000000..b211cbab --- /dev/null +++ b/agency-indexes/DoE/Dr.L:_Distributed_Recursive__Graph__Layout.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Dr. L provides two-dimensional visualizations of very large abstract graph structures. it can be used for data mining applications including biology, scientific literature, and social network analysis. Dr. L is a graph layout program that uses a multilevel force-directed algorithm. A graph is input and drawn using a force-directed algorithm based on simulated annealing. The resulting layout is clustered using a single link algorithm. This clustering is used to produce a coarsened graph (fewer nodes) which is then re-drawn. this process is repeated until a sufficiently small graph is produced. The smallest graph is drawn and then used as a basis for drawing the original graph by refining the series of coarsened graphs that were produced. The layout engine can be run in serial or in parallel.", + "homepageURL": "https://www.sandia.gov/smartin/software.html", + "laborHours": 0.0, + "languages": [ + "g++ and bash" + ], + "name": "Dr.L: Distributed Recursive (Graph) Layout", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.sandia.gov/smartin/software.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Draco,Version_6.x.x.json b/agency-indexes/DoE/Draco,Version_6.x.x.json new file mode 100644 index 00000000..56630ae9 --- /dev/null +++ b/agency-indexes/DoE/Draco,Version_6.x.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Draco is an object-oriented component library geared towards numerically intensive, radiation (particle) transport applications built for parallel computing hardware. It consists of semi-independent packages and a robust build system. The packages in Draco provide a set of components that can be used by multiple clients to build transport codes. The build system can also be extracted for use in clients. Software includes smart pointers, Design-by-Contract assertions, unit test framework, wrapped MPI functions, a file parser, unstructured mesh data structures, a random number generator, root finders and an angular quadrature component.", + "laborHours": 67214.4, + "name": "Draco,Version 6.x.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/Draco/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/Draco", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dragonview.json b/agency-indexes/DoE/Dragonview.json new file mode 100644 index 00000000..13499a0a --- /dev/null +++ b/agency-indexes/DoE/Dragonview.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Dragonview is an interactive visual analytics tool to visualize the nodes and links of a supercomputer that uses the dragonfly topology for its interconnection network. It can be used to map different data such as number of packets or bytes or stalls on the network links and job IDs or other on-node metrics on the router or node.", + "laborHours": 3085.6, + "name": "Dragonview", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DragonView", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Drainage_Algorithm_for_Geospatial_Knowledge.json b/agency-indexes/DoE/Drainage_Algorithm_for_Geospatial_Knowledge.json new file mode 100644 index 00000000..432c4d7e --- /dev/null +++ b/agency-indexes/DoE/Drainage_Algorithm_for_Geospatial_Knowledge.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Pacific Northwest National Laboratory (PNNL) has developed a prototype stream extraction algorithm that semi-automatically extracts and characterizes streams using a variety of multisensor imagery and digital terrain elevation data. The system is currently optimized for three types of single-band imagery: radar, visible, and thermal. Method of Solution: DRAGON: (1) classifies pixels into clumps of water objects based on the classification of water pixels by spectral signatures and neighborhood relationships, (2) uses the morphology operations (erosion and dilation) to separate out large lakes (or embayment), isolated lakes, ponds, wide rivers and narrow rivers, and (3) translates the river objects into vector objects. In detail, the process can be broken down into the following steps. A. Water pixels are initially identified using on the extend range and slope values (if an optional DEM file is available). B. Erode to the distance that defines a large water body and then dilate back. The resulting mask can be used to identify large lake and embayment objects that are then removed from the image. Since this operation be time consuming it is only performed if a simple test (i.e. a large box can be found somewhere in the image that contains only water pixels) that indicates a large water body is present. C. All water pixels are clumped (in Imagine terminology clumping is when pixels of a common classification that touch are connected) and clumps which do not contain pure water pixels (e.g. dark cloud shadows) are removed D. The resulting true water pixels are clumped and water objects which are too small (e.g. ponds) or isolated lakes (i.e. isolated objects with a small compactness ratio) are removed. Note that at this point lakes have been identified has a byproduct of the filtering process and can be output has vector layers if needed. E. At this point only river pixels are left in the image. To separate out wide rivers all objects in the image are eroded by the half width of narrow rivers. This causes all narrow rivers to be removed and leaves only the core of wide rivers. This core is dilated out by the same distance to create a mask that is used with the original river image to separate out rivers into two separate images of narrow rivers and wide rivers F. If in the image that contains wide rivers there are small isolated short (less than 300 meters if NGA criteria is used) segments these segments are transferred to the narrow river file in order to be treated has parts of single line rivers G. The narrow river file is optionally dilated and eroded. This closing has the effect of removing small islands, filling small gaps, and smoothing the outline. H. The user also has the option of closing objects in the wide river file. However, this depends on the degree to which the user wants to remove small islands in the large rivers. I. To make the translation from raster to single vector easier the objects in the narrow river image are reduced to a single center line (i.e. thinned) with binary morphology operations.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Drainage Algorithm for Geospatial Knowledge", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Drekar.json b/agency-indexes/DoE/Drekar.json new file mode 100644 index 00000000..845b6279 --- /dev/null +++ b/agency-indexes/DoE/Drekar.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Drekar is a code written for solving the low-mach incompressible Navier-Stokes and magnetohydrodynamics equations. It implements a stabilized Galerkin finite element discretization of the incompressible Navier-Stokes equations and a variational multiscale stabilized formulation for magnetohydrodynamics published by Codina. Drekar contains the front end physics description of the problem and then leverages 30 open source Trilinos packages to solve the problem. It relies on Trilinos for all parallel capabilities. The code will be released open source under the LGPL license. The code will be used by the partners of the Consortium for Advanced Simulation of Light Water Reactors (CASL), an Energy Innovation Hub funded by DOE to simulate fluid flow and heat transfer inside nuclear reactors. Additionally the code will be used for fundamental research collaborations in magnetohydrodynamics and computational fluid dynamics.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++ / various compilers" + ], + "name": "Drekar", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Drekar_v.2.0.json b/agency-indexes/DoE/Drekar_v.2.0.json new file mode 100644 index 00000000..fea18785 --- /dev/null +++ b/agency-indexes/DoE/Drekar_v.2.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "Drekar is an application code that solves partial differential equations for fluids that can be optionally coupled to electromagnetics. Drekar solves low-mach compressible and incompressible computational fluid dynamics (CFD), compressible and incompressible resistive magnetohydrodynamics (MHD), and multiple species plasmas interacting with electromagnetic fields. Drekar discretization technology includes continuous and discontinuous finite element formulations, stabilized finite element formulations, mixed integration finite element bases (nodal, edge, face, volume) and an initial arbitrary Lagrangian Eulerian (ALE) capability. Drekar contains the implementation of the discretized physics and leverages the open source Trilinos project for both parallel solver capabilities and general finite element discretization tools. The code will be released open source under a BSD license. The code is used for fundamental research for simulation of fluids and plasmas on high performance computing environments.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Drekar v.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Drifty_shifty_deluxe.m.json b/agency-indexes/DoE/Drifty_shifty_deluxe.m.json new file mode 100644 index 00000000..39d76050 --- /dev/null +++ b/agency-indexes/DoE/Drifty_shifty_deluxe.m.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Performs a cross-correlation calculation to align images. This is particularly useful for aligning frames of a movie so that an object of interest does not spatially drift. For in situ microscopy experiments. Movies are collected where an object changes with time. At the same time, the object usually drifts too. This shifts the movie frames so that the object is aligned from frame to frame. Then it is easy to see the object changes without the added complication of it moving too.", + "homepageURL": "http://freesourcecode.net/matlabprojects/57416/drifty-shifty-deluxe-in-matlab#.Wczt52hyKUk", + "laborHours": 0.0, + "name": "Drifty shifty deluxe.m", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://freesourcecode.net/matlabprojects/57416/drifty-shifty-deluxe-in-matlab#.Wczt52hyKUk", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Drink_From_The_Firehose.json b/agency-indexes/DoE/Drink_From_The_Firehose.json new file mode 100644 index 00000000..60cc7a38 --- /dev/null +++ b/agency-indexes/DoE/Drink_From_The_Firehose.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-31", + "metadataLastUpdated": "2023-05-31" + }, + "description": "DFTF converts Redfish events to messages on a Kafka bus. DFTF subscribes to events in Redfish,\nspecifically Alerts and CrayTelemetry. It listens for HTTP POST requests containing event data, reduces\nthe data, serializes the reduced data using Avro, and publishes the data to topics in Kafka.", + "laborHours": 0.0, + "languages": [], + "name": "Drink From The Firehose", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/dftf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Drinking_Water_System_Energy_Resilience_Value_Estimator.json b/agency-indexes/DoE/Drinking_Water_System_Energy_Resilience_Value_Estimator.json new file mode 100644 index 00000000..86acc314 --- /dev/null +++ b/agency-indexes/DoE/Drinking_Water_System_Energy_Resilience_Value_Estimator.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-02-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Tool for water system owners to estimate the cost of system interruption or loss. Publicly available for download (.zip file) at https://www.pnnl.gov/media/24681", + "homepageURL": "https://www.pnnl.gov/media/24681", + "laborHours": 0.0, + "languages": [], + "name": "Drinking Water System Energy Resilience Value Estimator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://creativecommons.org/publicdomain/zero/1.0/legalcode", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/media/24681", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Drishti_v0.3.json b/agency-indexes/DoE/Drishti_v0.3.json new file mode 100644 index 00000000..58b8a81c --- /dev/null +++ b/agency-indexes/DoE/Drishti_v0.3.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-18" + }, + "description": "Drishti is a command-line tool to guide end-users in optimizing I/O in their applications by detecting typical I/O performance pitfalls and providing a set of recommendations.", + "laborHours": 1170.4, + "languages": [], + "name": "Drishti v0.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/drishti", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DrivePy.json b/agency-indexes/DoE/DrivePy.json new file mode 100644 index 00000000..830ba082 --- /dev/null +++ b/agency-indexes/DoE/DrivePy.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DrivePy is physics-based drivetrain model that sizes drivetrain components based on aerodynamic and operational loads for use in a systems engineering model. It also calculates costs based on empirical data collected by NREL's National Wind Technology Center.", + "laborHours": 3070.4, + "name": "DrivePy", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/DriveSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Droplet_Number_Concentration_Value_Added_Product.json b/agency-indexes/DoE/Droplet_Number_Concentration_Value_Added_Product.json new file mode 100644 index 00000000..894972e0 --- /dev/null +++ b/agency-indexes/DoE/Droplet_Number_Concentration_Value_Added_Product.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Cloud droplet number concentration is an important factor in understanding aerosol-cloud interactions. As aerosol concentration increases, it is expected that droplet number concentration (Nd) will increase and droplet size will decrease, for a given liquid water path. This will greatly affect cloud albedo as smaller droplets reflect more shortwave radiation; however, the magnitude and variability of these processes under different environmental conditions is still uncertain.McComiskey et al. (2009) have implemented a method, based onBoers and Mitchell (1994), for calculating Nd from ground-based remote sensing measurements of optical depth and liquid water path. They show that the magnitude of the aerosol-cloud interactions (ACI) varies with a range of factors, including the relative value of the cloud liquid water path (LWP), the aerosol size distribution, and the cloud updraft velocity. Estimates of Nd under a range of cloud types and conditions and at a variety of sites are needed to further quantify the impacts of aerosol cloud interactions. In order to provide data sets for studying aerosol-cloud interactions, the McComiskey et al. (2009) method was implemented as the Droplet Number Concentration (NDROP) value-added product (VAP).", + "laborHours": 532.0, + "name": "Droplet Number Concentration Value Added Product", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ARM-DOE/adi-vap-ndrop", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/adi-vap-ndrop", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Drug_Target_and_Chemotype_Identification_Pipeline.json b/agency-indexes/DoE/Drug_Target_and_Chemotype_Identification_Pipeline.json new file mode 100644 index 00000000..fc30df44 --- /dev/null +++ b/agency-indexes/DoE/Drug_Target_and_Chemotype_Identification_Pipeline.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "The TargetID pipeline enables rapid identification and characterization of binding sites in SARS-CoV-2 proteins as well as the core chemical components with which these sites interact.", + "laborHours": 0.0, + "languages": [], + "name": "Drug Target and Chemotype Identification Pipeline", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TargetID", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Drupal_Contributed_Modules.json b/agency-indexes/DoE/Drupal_Contributed_Modules.json new file mode 100644 index 00000000..35eb6d63 --- /dev/null +++ b/agency-indexes/DoE/Drupal_Contributed_Modules.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "These Drupal Modules extend the functionality of Drupal by including specific styles for dates and tabs, publishing options for scheduled and immediate publication of content modes, field visibility in content forms, keyword block filters (taxonomy based), adding content nodes to a specified queue for display in views, and status display of workflow settings.", + "laborHours": 0.0, + "languages": [ + "PHP (99%)", + "JavaScript (1%)" + ], + "name": "Drupal Contributed Modules", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.drupalcode.org/project/field_visibility", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Drupal_Contributed_Modules_Date_AP_Style.json b/agency-indexes/DoE/Drupal_Contributed_Modules_Date_AP_Style.json new file mode 100644 index 00000000..7499db04 --- /dev/null +++ b/agency-indexes/DoE/Drupal_Contributed_Modules_Date_AP_Style.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This Drupal Module extend the functionality of Drupal by modifying the output of dates to comply to the format of AP Style guide.", + "homepageURL": "https://www.drupal.org/project/date_ap_style", + "laborHours": 380.0, + "languages": [ + "PHP (99%)", + "JavaScript (1%)" + ], + "name": "Drupal Contributed Modules Date AP Style", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.drupal.org/project/date_ap_style", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Drupal_Installer.json b/agency-indexes/DoE/Drupal_Installer.json new file mode 100644 index 00000000..03b6a8cf --- /dev/null +++ b/agency-indexes/DoE/Drupal_Installer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-11-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software is a plugin/installer for existing software. Composer (https://getcomposer.org) is a dependency manager for\nPHP. Installer plugins can be created through Composer's plugin API (https://getcomposer.org/doc/articles/custominstallers.\nmd) allowing certain types of packages to be automatically installed to specific paths. Plugins like this exist for\nseveral different frameworks: https://packagist.org/search/?q=installer&type=composer-plugin\nThis software is a plugin to install Drupal modules (https://www.drupal.org/). Drupal has begun supporting Composer as a means of installing and maintaining modules, but requires specific paths for it's various components. These paths can be\nmanually specified in the \"composer.json\" file, or can be automatically determined with a plugin. Currently an installer\nplugin does not exist for Drupal.", + "laborHours": 273.6, + "languages": [], + "name": "Drupal Installer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/drupal-installer", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Drupal_VM.json b/agency-indexes/DoE/Drupal_VM.json new file mode 100644 index 00000000..ff8ba785 --- /dev/null +++ b/agency-indexes/DoE/Drupal_VM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "Drupal VM\u00a0is a VM for Drupal, built with Ansible. Drupal VM makes building Drupal development environments quick and easy, and introduces developers to the wonderful world of Drupal development on virtual machines or Docker containers.", + "laborHours": 9576.0, + "languages": [], + "name": "Drupal VM", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/drupal-vm", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DualSPHysics-INL.json b/agency-indexes/DoE/DualSPHysics-INL.json new file mode 100644 index 00000000..ee7b84ac --- /dev/null +++ b/agency-indexes/DoE/DualSPHysics-INL.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-01-17", + "metadataLastUpdated": "2025-01-17" + }, + "description": "Funded by the DOE's Bioenergy Technology Office through the Feedstock-Conversion Interface Consortium, INL researchers developed this code to model biomass freestock flow in various handling equipment, such as hoppers and augers. Built on top of an existing open-source code DualSPHysics (https://dual.sphysics.org/) , the enrichment includes modification of the mass conservation equation that switching tracking density to void ratio, adding a hypoplastic constitutive law to better capture the flow physics of this type of material and implementing a novel boundary condition that can handle the dynamic contact between material and equipment. All implementation were realized via Nvidia CUDA, so GPU accelaration can be leveraged to signifiantly speed up the computational process.", + "laborHours": 44338.4, + "languages": [ + "C++" + ], + "name": "DualSPHysics-INL", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/DualSPHysics-INL", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dual_Event_Generator__dual-evg__v1.0.json b/agency-indexes/DoE/Dual_Event_Generator__dual-evg__v1.0.json new file mode 100644 index 00000000..3c7915d1 --- /dev/null +++ b/agency-indexes/DoE/Dual_Event_Generator__dual-evg__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "The dual event generator is a event-based timing system implementation capable of synchronizing (with respect to clock, events and triggers) hundreds of downstreams devices. This has been in use by ALS for many years and this is a similar implementation, but with a synchronized dual-master frequency , as opposed to just one in a more conventional approach.", + "laborHours": 0.0, + "languages": [], + "name": "Dual Event Generator (dual-evg) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/LBNL-Dual-EVG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dual_Panal_Planar_Portal.json b/agency-indexes/DoE/Dual_Panal_Planar_Portal.json new file mode 100644 index 00000000..122f9c59 --- /dev/null +++ b/agency-indexes/DoE/Dual_Panal_Planar_Portal.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The D3P system is designed to provide a very fast imaging system in order to search for weapons on persons in an airport environment. The complete vision of the D3P system is to have two array systems facing each other. Version 2.3 of the software is designed to control and process data from a single panel. A second panel is expected to be added at a future date and the software will be modified at that time to integrate the images from two panels at one time. The D3P software can be segmented into three specific tasks. The first task is data acquisition and scanner control. At the operator's request, this task commands the scanner to move and the radar transceiver-array to send data to the computer system in a known and well-ordered manner. The array is moved over the complete aperture in 1 to 2 seconds. At the completion of the array movement the second software task reconstructs the high-resolution image from the radar data utilizing the integrated DSP board. The third task displays the result to the computer screen for user review and analysis.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Dual Panal Planar Portal", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Duluth_Shines!_Solar_Map_Application.json b/agency-indexes/DoE/Duluth_Shines!_Solar_Map_Application.json new file mode 100644 index 00000000..a5cdaa3b --- /dev/null +++ b/agency-indexes/DoE/Duluth_Shines!_Solar_Map_Application.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jodi@ecolibrium3.org" + }, + "date": { + "created": "2018-03-30", + "metadataLastUpdated": "2018-05-15" + }, + "description": "The Duluth Shines! application is an online solar map developed in partnership with the University of Minnesota-Duluth to allow the public to compute solar resources available on the rooftops of properties within the Duluth City Limits. The map links to a Minnesota DNR solar cost calculator.", + "homepageURL": "http://umd-cla-gis04.d.umn.edu/duluthshines", + "laborHours": 1945.6, + "languages": [], + "name": "Duluth Shines! Solar Map Application", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://solar.maps.umn.edu/products.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://umd-cla-gis04.d.umn.edu/duluthshines", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dwave_compatible_C_to_Verilog_converter_.json b/agency-indexes/DoE/Dwave_compatible_C_to_Verilog_converter_.json new file mode 100644 index 00000000..09c82cbe --- /dev/null +++ b/agency-indexes/DoE/Dwave_compatible_C_to_Verilog_converter_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-11-13", + "metadataLastUpdated": "2018-11-13" + }, + "description": "This software is a C to Verilog converter. However it doesn't just generate any Verilog code, it is intended to generate Verilog code compatible with execution over quantum based D-Wave systems. ", + "laborHours": 410.4, + "languages": [], + "name": "Dwave compatible C to Verilog converter ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/c2verilog", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DynamicSimCCS.json b/agency-indexes/DoE/DynamicSimCCS.json new file mode 100644 index 00000000..01674a72 --- /dev/null +++ b/agency-indexes/DoE/DynamicSimCCS.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-29", + "metadataLastUpdated": "2024-04-29" + }, + "description": "This code solves for the one-dimensional concentration and temperature distribution within a carbon\ncapture column using a homogenized absorber model. These solutions are compared to experimental\ndata.", + "laborHours": 927.2, + "languages": [], + "name": "DynamicSimCCS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DynamicSimCCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.01" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dynamic_Contingency_Analysis_Tool.json b/agency-indexes/DoE/Dynamic_Contingency_Analysis_Tool.json new file mode 100644 index 00000000..4d75f2cb --- /dev/null +++ b/agency-indexes/DoE/Dynamic_Contingency_Analysis_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The Dynamic Contingency Analysis Tool (DCAT) is an open-platform and publicly available methodology to help develop applications that aim to improve the capabilities of power system planning engineers to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. Outputs from the DCAT will help find mitigation solutions to reduce the risk of cascading outages in technically sound and effective ways. The current prototype DCAT implementation has been developed as a Python code that accesses the simulation functions of the Siemens PSS/E planning tool (PSS/E). It has the following features: It uses a hybrid dynamic and steady-state approach to simulating the cascading outage sequences that includes fast dynamic and slower steady-state events. It integrates dynamic models with protection scheme models for generation, transmission, and load. It models special protection systems (SPSs)/remedial action schemes (RASs) and automatic and manual corrective actions. Overall, the DCAT attempts to bridge multiple gaps in cascading-outage analysis in a single, unique prototype tool capable of automatically simulating and analyzing cascading sequences in real systems using multiprocessor computers. While the DCAT has been implemented using PSS/E in Phase I of the study, other commercial software packages with similar capabilities can be used within the DCAT framework.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Dynamic Contingency Analysis Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dynamic_Importance_Sampling.json b/agency-indexes/DoE/Dynamic_Importance_Sampling.json new file mode 100644 index 00000000..ae0550d5 --- /dev/null +++ b/agency-indexes/DoE/Dynamic_Importance_Sampling.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "Dynamic Importance (DynIm) Sampling is a new approach for importance sampling in high-dimensional space. DynIm has two key characteristics. (1) Importance sampling: The notion of importance of candidate samples is used to guide the sampling, where importance is defined based on the (dis)similarity from previously selected samples (via Euclidean distance metric). (2) Dynamic sampling: The sampling can be performed dynamically, as new candidates are generated and new samples must be selected.\nDynIm was developed as part of a machine learning based coupling of scales in large multiscale simulations and can be used for a variety of applications.", + "laborHours": 0.0, + "languages": [], + "name": "Dynamic Importance Sampling", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/dynim", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dynamic_Power_Grid_Simulation.json b/agency-indexes/DoE/Dynamic_Power_Grid_Simulation.json new file mode 100644 index 00000000..29db8c76 --- /dev/null +++ b/agency-indexes/DoE/Dynamic_Power_Grid_Simulation.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GridDyn is a part of power grid simulation toolkit. The code is designed using modern object oriented C++ methods utilizing C++11 and recent Boost libraries to ensure compatibility with multiple operating systems and environments.", + "laborHours": 493620.0, + "name": "Dynamic Power Grid Simulation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/GridDyn/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GridDyn", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dynamic_Scalable_Event_Chain_Tracing_API.json b/agency-indexes/DoE/Dynamic_Scalable_Event_Chain_Tracing_API.json new file mode 100644 index 00000000..cf918149 --- /dev/null +++ b/agency-indexes/DoE/Dynamic_Scalable_Event_Chain_Tracing_API.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "An API and implementation to install debug probes into a parallel application", + "laborHours": 5517.6, + "name": "Dynamic Scalable Event Chain Tracing API", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/dysectapi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Dynamical_Components_Analysis__DCA__v1.0.0.json b/agency-indexes/DoE/Dynamical_Components_Analysis__DCA__v1.0.0.json new file mode 100644 index 00000000..c5c78996 --- /dev/null +++ b/agency-indexes/DoE/Dynamical_Components_Analysis__DCA__v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2021-03-12" + }, + "description": "Dynamical Components Analysis is a Python implementation of the method described in \"Unsupervised discovery of temporal structure in noisy data with dynamical components analysis\". It implements the method as well as related data analysis functions.", + "laborHours": 0.0, + "languages": [], + "name": "Dynamical Components Analysis (DCA) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BouchardLab/DynamicalComponentsAnalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DynamiteNSM.json b/agency-indexes/DoE/DynamiteNSM.json new file mode 100644 index 00000000..f3f72a75 --- /dev/null +++ b/agency-indexes/DoE/DynamiteNSM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "oleg@dynamite.ai" + }, + "date": { + "created": "2019-12-04", + "metadataLastUpdated": "2021-12-02" + }, + "description": "DynamiteNSM is a free Network Security Monitor (NSM), built on top of several leading, enterprise-grade technologies. The tool provides network and cybersecurity operators with holistic insights into their networks while giving them the ability to deep-dive into lower-level activities. The solution presents powerful dashboards, giving comprehensive view into performance and threat-based metrics. Dynamite-NSM can be easily deployed in different environments including high-speed data centers, small-to-large enterprises, IoT & industrial networks, and even at home.\n\nDynamite-NSM handles massive volumes of network traffic through scalable ingestion and optimized network sensors. The solution includes two key components: the agent and the monitor. The agent analyzes and forwards network events, while the monitor processes incoming events and displays analytic information. The monitor component builds upon the OpenSearch stack and is coupled with network packet inspection by Zeek and Suricata. \n\nDynamite-NSM is designed to be deployed very quickly with minimal configuration. Unlike many other tools, it can be installed and managed with a standalone command-line utility. The system is inherently passive without disruption to the network. There is no need to install agents on every computer, perform network scans, or directly interact with network assets.", + "laborHours": 4620.8, + "languages": [], + "name": "DynamiteNSM", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DynamiteAI/dynamite-nsm", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/DyninstAPI_Patches.json b/agency-indexes/DoE/DyninstAPI_Patches.json new file mode 100644 index 00000000..7a15b43d --- /dev/null +++ b/agency-indexes/DoE/DyninstAPI_Patches.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "We are seeking a code review of patches against DyninstAPI 8.0. DyninstAPI is an open source binary instrumentation library from the University of Wisconsin and University of Maryland. Our patches port DyninstAPI to the BlueGene/P and BlueGene/Q systems, as well as fix DyninstAPI bugs and implement minor new features in DyninstAPI.", + "laborHours": 290867.2, + "languages": [], + "name": "DyninstAPI Patches", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dyninst/dyninst", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/E3SMFC.json b/agency-indexes/DoE/E3SMFC.json new file mode 100644 index 00000000..532e237e --- /dev/null +++ b/agency-indexes/DoE/E3SMFC.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-06", + "metadataLastUpdated": "2025-02-06" + }, + "description": "SAND2025-01123O\nE3SMFC is a software tool that integrates a feedback controller algorithm into the E3SM climate model to regulate sulfur dioxide injection, aiming to achieve specific climate outcomes. The program uses proportional-integral-derivative feedback control to adjusts sulfur dioxide levels in both spatial and temporal dimensions. It will only operate on computers that can run the DOE climate model E3SM. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1769751.2, + "languages": [ + "Fortran", + "Python" + ], + "name": "E3SMFC", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/E3SMFC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/E3SM_Co-design_Kernels.json b/agency-indexes/DoE/E3SM_Co-design_Kernels.json new file mode 100644 index 00000000..397e6c9c --- /dev/null +++ b/agency-indexes/DoE/E3SM_Co-design_Kernels.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "sarat@ornl.gov" + }, + "date": { + "created": "2021-08-06", + "metadataLastUpdated": "2021-08-06" + }, + "description": "Climate kernels for Co-design These kernels originate from the Energy Exascale Earth System Model (E3SM). They are intended for sharing with interested parties for co-design purposes.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "E3SM Co-design Kernels", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/codesign-kernels", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/E4D_RT.json b/agency-indexes/DoE/E4D_RT.json new file mode 100644 index 00000000..3e51ce7d --- /dev/null +++ b/agency-indexes/DoE/E4D_RT.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Time-lapse ERT imaging for monitoring both natural and engineered subsurface processes has advanced rapidly over the past 15-20 years. However, imaging results generally required a significant amount of manual and computational effort, and therefore were not available while the process was occurring. Although the value of real-time imaging was recognized, several obstacles prevented it's implementation. E4D_RT addresses these obstacles by 1) providing specialized algorithms that negate the need for user intervention, thereby automating the time-lapse data processing steps, 2) linking field data collection systems with parallel supercomputing systems via wireless data transfer link, and 3) addressing the computational burdens by utilizing distributed memory supercomputing resources, thereby enabling rapid data processing and imaging results.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "E4D_RT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/E4D/blob/master/E4D_LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/E4D", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/E4D_Simulator_with_Joint_Inversion_Capability.json b/agency-indexes/DoE/E4D_Simulator_with_Joint_Inversion_Capability.json new file mode 100644 index 00000000..03858698 --- /dev/null +++ b/agency-indexes/DoE/E4D_Simulator_with_Joint_Inversion_Capability.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A joint inverse module was developed by imposing structural similarities between different physical parameters and\nincorporated into the E4D geophysical simulator, a parallel multi-physics modeling and inversion code with unstructured\ntetrahedral mesh. The inversion capability of E4D can accommodate joint inversions of data from two or more geophysical\nmethods that are available in E4D and is suitable for large scale three-dimensional subsurface characterization or\nmonitoring. The joint inversion capability were tested using synthetic data from borehole electrical resistivity tomography\nand seismic survey.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "E4D Simulator with Joint Inversion Capability", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/EAM-X_Potential_Generator.json b/agency-indexes/DoE/EAM-X_Potential_Generator.json new file mode 100644 index 00000000..fb5f3976 --- /dev/null +++ b/agency-indexes/DoE/EAM-X_Potential_Generator.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-13", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-06608O\nThe EAM-X Potential Generator code establishes parameters that describe interactions between atoms in pure metals and alloys. The open-source software allows for the understanding of the relationship between general properties of atoms and macroscopic properties of metals. The code reads in values for the parameters of the model and outputs a table that describes the interactions. This code will be published by Acta Materialia along with two papers describing the method. The output of this code is meant for use by the LAMMPS simulation code created by Sandia. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [], + "name": "EAM-X Potential Generator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/EAM-X-Potential-Generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EAP_Patterns.json b/agency-indexes/DoE/EAP_Patterns.json new file mode 100644 index 00000000..fc722a6e --- /dev/null +++ b/agency-indexes/DoE/EAP_Patterns.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-04", + "metadataLastUpdated": "2023-01-04" + }, + "description": "EAP Patterns: Memory access and iteration patterns from the EAP code base with the physics removed. This is intended to be a serial app representing memory access patterns. We will populate the data structures from EAP output files to provide representative patterns of face and cell loops within the EAP code base The arguments to the program are the EAP output file and the number of MPI processors to emulate. Currently there is no MPI in the application and the number of processors represents a means of emulating the halo (clone) cells around the domain of the given processor. An optional argument `processor_ID` can be provided to specify the processor to emulate. In the future we plan to include the ability to run multiple MPI ranks to more accurately represent the on-node demands on memory bandwidth.", + "laborHours": 0.0, + "languages": [], + "name": "EAP Patterns", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/eap-patterns", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EASE.json b/agency-indexes/DoE/EASE.json new file mode 100644 index 00000000..57a60a8f --- /dev/null +++ b/agency-indexes/DoE/EASE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2018-05-30" + }, + "description": "Easiest Alert System Ever (EPICS alert and reaction system)\n", + "laborHours": 3936.8, + "languages": [], + "name": "EASE", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/ease/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ease", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EASEE:_Edge_Advertisements_into_Snapshots_using_Evolving_Expectations.json b/agency-indexes/DoE/EASEE:_Edge_Advertisements_into_Snapshots_using_Evolving_Expectations.json new file mode 100644 index 00000000..837bfc61 --- /dev/null +++ b/agency-indexes/DoE/EASEE:_Edge_Advertisements_into_Snapshots_using_Evolving_Expectations.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-07-29" + }, + "description": "Code developed in conjunction with a research paper. This code demonstrates how to identify static graph snapshots from a stream of communication events. A second, related code generates simulated communication events with known split moments for accuracy testing.SAND2020-12245 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 653.6, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "EASEE: Edge Advertisements into Snapshots using Evolving Expectations", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Easee", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EB_Profiler.json b/agency-indexes/DoE/EB_Profiler.json new file mode 100644 index 00000000..13bc30cb --- /dev/null +++ b/agency-indexes/DoE/EB_Profiler.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-20" + }, + "description": "EB_Profiler, v2.2 is a LabVIEW program which uses computed tomography to determine the power\ndistribution in the beams of electron beam welders. It requires that the National Instruments LabVIEW\nRun-Time Engine be installed. The program takes in beam profile data from a data acquisition device or\nfrom a data file. Beam parameters necessary for calculations are entered by the user or automatically\nextracted from header information in the data file. The result is a two-dimensional reconstruction of the\npower distribution in the beam.", + "homepageURL": "https://softwarelicensing.llnl.gov/product/ebprofiler-v22", + "laborHours": 0.0, + "languages": [], + "name": "EB_Profiler", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://softwarelicensing.llnl.gov/product/ebprofiler-v22", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "2.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ECP-ExaGraph_Submodular-b-matching.json b/agency-indexes/DoE/ECP-ExaGraph_Submodular-b-matching.json new file mode 100644 index 00000000..75914ffa --- /dev/null +++ b/agency-indexes/DoE/ECP-ExaGraph_Submodular-b-matching.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A b-MATCHING is a subset of edges M such that at most b(v) edges in M are incident on each vertex v, where b(v) is specified. We present a distributed-memory parallel algorithm, b-SUITOR, that computes a b-MATCHING with more than half the maximum weight in a graph with weights on the edges", + "laborHours": 0.0, + "languages": [], + "name": "ECP-ExaGraph/Submodular-b-matching", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-ExaGraph/Submodular-b-matching", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ECP-ExaGraph_netAlign.json b/agency-indexes/DoE/ECP-ExaGraph_netAlign.json new file mode 100644 index 00000000..7b993d84 --- /dev/null +++ b/agency-indexes/DoE/ECP-ExaGraph_netAlign.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "We investigate substituting a parallel, half-approximation for maximum weight matching instead of an exact computation. Our experiments show that the resulting difference in solution quality is negligible. We demonstrate almost a 20-fold speedup using 40 threads on an 8 processor Intel Xeon E7-8870 system and now solve real-world problems in 36 seconds instead of 10 minutes", + "laborHours": 0.0, + "languages": [], + "name": "ECP-ExaGraph/netAlign", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-ExaGraph/netAlign", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ECP-copa_ExaMiniMD.json b/agency-indexes/DoE/ECP-copa_ExaMiniMD.json new file mode 100644 index 00000000..4d4f03f6 --- /dev/null +++ b/agency-indexes/DoE/ECP-copa_ExaMiniMD.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-04-12", + "metadataLastUpdated": "2020-11-02" + }, + "description": "ExaMiniMD is a proxy application for Molecular Dynamics (MD) codes such as LAMMPS. Its intend is to facilitate research and development on MD algorithms in particular in the context of CoDesign efforts with hardware vendors. Currently, ExaMiniMD implements a basic Lennard Jones two body potential as well as the SNAP many body potential, both of which are available in LAMMPS. It also includes basic neighbor list builds as well as constant energy integration as found in LAMMPS and other MD codes. A feature not generally available in other MD codes is a set of statistical correctness checks which will help other developers judge whether changes to the code still give correct answers. ExaMiniMD is using the Kokkos programming model to achieve performance portability and is able to run across all major HPC platforms (GPUs, ManyCore, CPUs).", + "laborHours": 3389.6, + "languages": [], + "name": "ECP-copa/ExaMiniMD", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ecp-copa/examinimd", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ECP_Collaborative_Software_Development_for_In_Situ_Data_Analysis_and_Visualization.json b/agency-indexes/DoE/ECP_Collaborative_Software_Development_for_In_Situ_Data_Analysis_and_Visualization.json new file mode 100644 index 00000000..e332c83d --- /dev/null +++ b/agency-indexes/DoE/ECP_Collaborative_Software_Development_for_In_Situ_Data_Analysis_and_Visualization.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-07" + }, + "description": "As high-performance computing reaches exascale, data analysis and visualization will need to shift from a predominantly post hoc approach to an in situ paradigm \u2013 running while the simulation is running. Memory and I/O bandwidth growth is expected to lag behind concurrency growth by orders of magnitude. This will require new in situ algorithms and tools that can leverage emerging accelerator technology to sufficiently decrease the volume of data moved on the machine and amount saved to persistent storage. As part of the Department of Energy\u2019s Exascale Computing Project (ECP), the ALPINE and team at Los Alamos National Laboratory (LANL) is collaboratively developing open source solutions with DOE leadership laboratories, universities, and industry partners to address these challenges. The ECP ALPINE project is developing filters and algorithms to support the in situ analysis and visualization goals of ECP application codes. Prototypes of the filters and algorithms are written in C++ and Python while production versions are written in VTK or VTK-m. These filters and algorithms will be available in commonly used visualization tools and infrastructures such as ParaView, VisIt, and Ascent and will be deployed on exascale machines at the DOE Leadership Computing Facilities. The primary users of these projects will be both at Los Alamos National Laboratory and will include application codes at institutions across the Exascale Computing Project (https://www.exascaleproject.org/).", + "laborHours": 0.0, + "languages": [], + "name": "ECP Collaborative Software Development for In Situ Data Analysis and Visualization", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/alpine-lanl", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ECoG_Cluster_Flow_v1.0.json b/agency-indexes/DoE/ECoG_Cluster_Flow_v1.0.json new file mode 100644 index 00000000..406f8ae4 --- /dev/null +++ b/agency-indexes/DoE/ECoG_Cluster_Flow_v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ECoG ClusterFlow is a novel multi-scale visual analysis system for the detailed exploration of dynamic functional connectivity graphs obtained through electrocorticography.", + "laborHours": 576718.4, + "name": "ECoG Cluster Flow v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sugeerth/ECoG-ClusterFlow/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sugeerth/ECoG-ClusterFlow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ED-LPD,_MATLAB_standalone.json b/agency-indexes/DoE/ED-LPD,_MATLAB_standalone.json new file mode 100644 index 00000000..fb4c10e4 --- /dev/null +++ b/agency-indexes/DoE/ED-LPD,_MATLAB_standalone.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-23", + "metadataLastUpdated": "2019-01-25" + }, + "description": "This computer software is a MATLAB standalone code for implementation of the Lumped Particle Domain model. The model solves charge transfer kinetics, lithium diffusion dynamics, charge conservation and energy conservation occurring across the porous electrode pair unit cell sandwich to predict electrical and thermal response of a battery. Physico-chemical states of batteries are also evaluated by the model.", + "homepageURL": "https://www.nrel.gov/workingwithus/licensing.html", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "ED-LPD, MATLAB standalone", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrel.gov/workingwithus/licensing.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrel.gov/workingwithus/licensing.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/EDAT.json b/agency-indexes/DoE/EDAT.json new file mode 100644 index 00000000..45ae8b66 --- /dev/null +++ b/agency-indexes/DoE/EDAT.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-14", + "metadataLastUpdated": "2022-10-14" + }, + "description": "SAND2022-13281 O\nEDAT is a suite of tools for analyzing time-dependent electron densities produced by time-dependent density functional theory (TDDFT) simulations of ion-irradiated materials and surfaces. The code\u2019s key capabilities include various routines to extract the number of electrons emitted from a surface, the energy spectrum of these emitted electrons, and the number of electrons captured by the ion. The code is written in Python and can interface with multiple TDDFT codes.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "EDAT", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EDD_Basic_Stats_and_Graphs_Notebook_analysis__EDD_BSG_Notebook__v1.0.json b/agency-indexes/DoE/EDD_Basic_Stats_and_Graphs_Notebook_analysis__EDD_BSG_Notebook__v1.0.json new file mode 100644 index 00000000..c38d99c7 --- /dev/null +++ b/agency-indexes/DoE/EDD_Basic_Stats_and_Graphs_Notebook_analysis__EDD_BSG_Notebook__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "This jupyter notebook calculates basic statistics (e.g., mean, standard deviation, coefficient of variation) and simple graphs (e.g., bar graphs, line plots) for data from the Experiment Data Depot (EDD) to provide rapid and reproducible assessment of data quality to aid research efforts across the JBEI and ABF projects. It rapidly and reproducibly calculates basic statistical values for data stored in the EDD which aids researchers and strengthens comparisons across different experiments and projects.", + "laborHours": 288.8, + "languages": [], + "name": "EDD Basic Stats and Graphs Notebook analysis (EDD BSG Notebook) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/Omics-Data-QA-QC-tool", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EDIPIC-2D.json b/agency-indexes/DoE/EDIPIC-2D.json new file mode 100644 index 00000000..e1a32b0e --- /dev/null +++ b/agency-indexes/DoE/EDIPIC-2D.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "apritch@pppl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-21" + }, + "description": "EDIPIC codes were developed for simulation of kinetic effects in low-temperature plasmas. They can be used for simulation of plasmas in electrostatic approximation and include many atomistic and plasma-surface interaction processes needed for simulations of low temperature plasmas. These codes include a detailed model of secondary electron emission induced by electrons and ions. The Monte-Carlo model of electron-neutral collisions and the Langevin model of Coulomb collisions for electrons are also implemented.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "EDIPIC-2D", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PrincetonUniversity/EDIPIC-2D", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EDRB_Service.json b/agency-indexes/DoE/EDRB_Service.json new file mode 100644 index 00000000..c5e067bf --- /dev/null +++ b/agency-indexes/DoE/EDRB_Service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This service wraps the ERDB software and allows querying the CDS via the ERDB using typecompiler generated clients rather than direct Perl imports of the ERDB code.", + "laborHours": 136.8, + "languages": [], + "name": "EDRB Service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/erdb_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EDS_Montage.json b/agency-indexes/DoE/EDS_Montage.json new file mode 100644 index 00000000..5ab86fd0 --- /dev/null +++ b/agency-indexes/DoE/EDS_Montage.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "parishcm@ornl.gov" + }, + "date": { + "created": "2021-08-17", + "metadataLastUpdated": "2021-08-17" + }, + "description": "Applies machine learning to analyze individual or sets of X-ray energy dispersive spectroscopy spectrum images acquired in the electron microscope.", + "laborHours": 0.0, + "languages": [], + "name": "EDS Montage", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/nmp/eds_montage", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/EFFORT__EFFectiveness_Of_Rate_sTructure_for_enabling_demand_response_.json b/agency-indexes/DoE/EFFORT__EFFectiveness_Of_Rate_sTructure_for_enabling_demand_response_.json new file mode 100644 index 00000000..97f843b5 --- /dev/null +++ b/agency-indexes/DoE/EFFORT__EFFectiveness_Of_Rate_sTructure_for_enabling_demand_response_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-05-26", + "metadataLastUpdated": "2021-09-13" + }, + "description": "This tool helps utilities evaluate potential time of use price-plans and find effective hours for price plan on peak periods and the potential price-elastic demand response. An optimization model can be used to find tiered prices for the time of use tariffs and analyze the impact on load profiles, energy consumption, utility, and customer savings. The tool is equipped with an optimization model to determine the energy consumption of electric appliances that can leverage survey data containing information on the number of appliances owned by customers. Lastly, a statistical model can be used to predict system-level load based on exogenous parameters such as weather, time of day, month, type of day, and year. The tool is scripted in Python and uses the Pyomo python optimization language.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "EFFORT (EFFectiveness Of Rate sTructure for enabling demand response)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EFFORT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EGSim_v1.0.json b/agency-indexes/DoE/EGSim_v1.0.json new file mode 100644 index 00000000..c96e0737 --- /dev/null +++ b/agency-indexes/DoE/EGSim_v1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-06-03", + "metadataLastUpdated": "2024-08-07" + }, + "description": "EGSim contains tools aimed at simulating static load flow solutions for power grids. It implements models for loads, generators, and transmission lines. The static load flow solution is computed via gradient descent. \n\nSAND20019-4672 M", + "laborHours": 13968.8, + "languages": [ + "C++", + "Fortran" + ], + "name": "EGSim v1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/EGSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EI_MS_ML.json b/agency-indexes/DoE/EI_MS_ML.json new file mode 100644 index 00000000..c37e59bb --- /dev/null +++ b/agency-indexes/DoE/EI_MS_ML.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-03" + }, + "description": "The unambiguous identification of compounds from their electron ionization mass (EI-MS) spectra remains a significant unsolved problem in the field of metabolomics and analytical chemistry as a whole. Typically EI-MS spectra are compared using various mathematical operations that convert the spectral similarity or differences into a distance-like metric that roughly approximates the similarity of any two spectra. A commonly used metric for this is the cosine similarity metric which has values close to one for very similar spectra and a value of zero for very dissimilar spectra; however, no metric is perfect. Due to the prevalence of structurally-similar compounds such as isomers and the prevalence of certain fragmentation patterns across structurally-dissimilar compounds, the unambiguous assignment of EI-MS spectra compounds remains difficult. Frequently, querying an observed EI-MS spectrum against a large database such as the NIST17 library yields multiple possible assignments requiring the end user to distinguish between multiple high scoring hits, or multiple low scoring hits while keeping in mind that the correct hit may not be in the database at all. Although techniques such as orthogonal information from techniques such as chromatography can greatly aid in unambiguous assignment, this also requires more complicated experimental designs and access to more complicated analytical instrumentation.\nSubstructures can be trivially detected and represented as strings using a previously published technique called node coloring from a known chemical structure. However, for experimentally-derived EI-MS spectra this information must be derived from the spectra itself (i.e., because we do not know what compound it represents). To achieve this, the software uses techniques from the field of machine learning and a large training dataset of EI-MS spectra corresponding to known structures annotated with substructure strings, to build models that can predict the presence of a given chemical substructure from an EI-MS spectrum directly.If these predictions are of high-quality (i.e., are unlikely to be false positives), the presence of one or more predicted substructures can be used to constrain the number of possible hits for a query spectrum. Mathematically, this restriction could be expressed in many forms, but the most straight-forward implementation is to weight the cosine similarity of a query spectrum and a plausible database match with a Tanimoto-like coefficient based on the ratio of the number of substructures predicted to the number of substructures present in the potential database hit.\nDetermining which combination of models best reduces assignment ambiguity will be achieved using a combination of manual curation and optimization techniques such as genetic algorithms. This software will perform all the steps necessary to construct said models from a training dataset and evaluate them using a holdout dataset. Various statistical analyses can be performed to determine if this approach does decrease assignment ambiguity. For example, if this approach works, on average, the rank-order of the correct assignment for the holdout set of EI-MS spectra should decrease and the weighted cosine similarities for most of the possible matches in the database should be better than the unweighted cosine similarities. Furthermore, this same pipeline can be used on real experimental data to generate less ambiguous assignments.", + "laborHours": 0.0, + "languages": [], + "name": "EI_MS_ML", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EI_MS_ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EKAT_v.1.0.json b/agency-indexes/DoE/EKAT_v.1.0.json new file mode 100644 index 00000000..85011538 --- /dev/null +++ b/agency-indexes/DoE/EKAT_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-02-08", + "metadataLastUpdated": "2022-02-08" + }, + "description": "E3SM Kokkos Application Toolkit (EKAT) is a collection of C++, Fortran, and CMake utilities for providing a single implementation of common kernels based on the Kokkos programming model. The library contains utilities for vectorization, tridiagonal linear system solvers, and linear interpolation as well as some general-purpose utilities such as testing utilities, parameter lists, representation of physical units, and additional interfaces. The goal is to provide a centralized implementation for high-performance computing structures and common utilities that reduce code duplication and streamline maintenance efforts. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2022-1327 O", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "EKAT v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/E3SM-Project/EKAT/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/EKAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ELASTEMP.json b/agency-indexes/DoE/ELASTEMP.json new file mode 100644 index 00000000..83308143 --- /dev/null +++ b/agency-indexes/DoE/ELASTEMP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-13", + "metadataLastUpdated": "2023-03-14" + }, + "description": "SF-22-160 Elastemp is a software to obtain the quasi-harmonic temperature dependent elastic constants of material. Elastemp integrates with VASP quantum-mechanical simulation package and with Phonopy package to perform dynamic calculations. Elastemp is capable of creating symmetry dependent deformations, run static and dynamic calculations to obtain the helmholtz energies from which quasi-harmonic temperature dependent elastic constants are obtained.", + "laborHours": 0.0, + "languages": [], + "name": "ELASTEMP", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Karthik-Balas/elastemp", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ELEMENTS.json b/agency-indexes/DoE/ELEMENTS.json new file mode 100644 index 00000000..1a86da4b --- /dev/null +++ b/agency-indexes/DoE/ELEMENTS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "ELEMENTS is a C++ library of mathematical functions and computer routines to support a broad range of numerical methods on diverse element types including: a) serendipity linear, quadratic, and cubic elements; b) arbitrary order tensor-product space elements b) high-order spectral elements; and d) a linear space-time element. The ELEMENTS library can be used for research and development of both continuous and discontinuous finite element methods for solving a diverse range of partial differential equations. The library has functions for calculating quantities that are commonly used in continuous and discontinuous finite element methods such as the gradient of a basis function, the Jacobi matrix, the inverse Jacobi matrix, the determinant of the Jacobi matrix, and a physical position inside the element, to name a few examples. The library supports both Gauss\u2013Legendre and Gauss\u2013Lobatto quadrature rules up to 8 quadrature points in each coordinate direction. The library has a mesh class designed for unstructured meshes and supports sub-cell decomposition that is used with advanced discontinuous numerical methods. Novel routines exist in the mesh class for connectivity across various mesh entities including: nodes, vertices, quadrature points, surfaces, elements, subcells, subcell-corners, and subcell-faces. These routines have simple interfaces and are cleverly designed for computational performance. The mesh class is designed to minimize memory usage.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "ELEMENTS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ELM__Energy_Language_Model__[SWR-23-94].json b/agency-indexes/DoE/ELM__Energy_Language_Model__[SWR-23-94].json new file mode 100644 index 00000000..402b4bed --- /dev/null +++ b/agency-indexes/DoE/ELM__Energy_Language_Model__[SWR-23-94].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-11", + "metadataLastUpdated": "2023-10-17" + }, + "description": "The Energy Language Model (ELM) software provides interfaces to apply Large Language Models (LLMs) like ChatGPT and GPT-4 to energy research.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ELM (Energy Language Model) [SWR-23-94]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/elm", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMBODY_Environmental_Modules_Build_System_Software_.json b/agency-indexes/DoE/EMBODY_Environmental_Modules_Build_System_Software_.json new file mode 100644 index 00000000..adb5c21b --- /dev/null +++ b/agency-indexes/DoE/EMBODY_Environmental_Modules_Build_System_Software_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-03-27" + }, + "description": "Embody (Environment Modules Build) is a software build tool with integrated support for the environment-modules package. The tool eases and automates the task of building and installing software packages from source or binary distributions, as well as the management of associated module files. An administrator or software pool maintainer has to write a brief script for the installation process. These steps are usually described for manual execution, in a package's README or INSTALL file. It would be up to the site administrator to work out a procedure to capture the steps taken. This tool: streamlines and codifies the installation tasks in a common framework; it provides a self-documenting and unified way for maintaining package installations; uses bash shell variables and functions for portability; keeps log files of the proceedings. It is similar in intent and function to other existing tools, such as RPM, but has several novel features tailored for High Performance Computing (HPC) software deployments. The design goal is simplicity and decoupling from RPM's dependencies and its database, which enables coexistence of several builds. Useful on HPC systems, new builds can be deployed centrally to shared file systems and without affecting running jobs.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "EMBODY(Environmental Modules Build System Software)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMCCD_Calibration.json b/agency-indexes/DoE/EMCCD_Calibration.json new file mode 100644 index 00000000..350f9e1c --- /dev/null +++ b/agency-indexes/DoE/EMCCD_Calibration.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The program \u201cEMCCD Calibration\u201d is software to provide accurate calibration of the gain and analogue-to-digital conversation factor for a variety of scientific imaging devices, such as electron-multiplying charge-coupled device (EMCCD) cameras, complementary metal-oxide semiconductor (sCMOS), and intensified charge coupled device (ICCD) cameras. The software implements new calibration methods that are described in a manuscript intended for publication under the title \u201cFrom Noise to Harmony: Calibration Methods for Electron Multiplying CCD Cameras\u201d. The software provides ready-to-use tools for researchers using EMCCD, sCMOS, or ICCD cameras.", + "laborHours": 0.0, + "languages": [], + "name": "EMCCD Calibration", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ryand-LANL/EMCCD-calibration", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMF_Biomass_Data_Interpreter_[SWR-23-06].json b/agency-indexes/DoE/EMF_Biomass_Data_Interpreter_[SWR-23-06].json new file mode 100644 index 00000000..0495dfdf --- /dev/null +++ b/agency-indexes/DoE/EMF_Biomass_Data_Interpreter_[SWR-23-06].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-04-05", + "metadataLastUpdated": "2023-11-27" + }, + "description": "EMF Biomass Data Interpreter was developed for the transportation team of the Energy Modeling Forum (EMF) 37: Deep Decarbonization and High Electrification Scenarios for North America project. It parses results from different modeling groups to show how biomass might be employed under electrification.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "EMF Biomass Data Interpreter [SWR-23-06]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMF_Data_Interpreter", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMIS-CompetitiveEquilibrium.jl_[SWR-19-56].json b/agency-indexes/DoE/EMIS-CompetitiveEquilibrium.jl_[SWR-19-56].json new file mode 100644 index 00000000..80dc4e6f --- /dev/null +++ b/agency-indexes/DoE/EMIS-CompetitiveEquilibrium.jl_[SWR-19-56].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "gord.stephen@nrel.gov" + }, + "date": { + "created": "2020-09-28", + "metadataLastUpdated": "2023-04-24" + }, + "description": "The Electricity Markets Investment Suite - Competitive Equilibrium (EMIS-CE) model is an optimization-based power system investment model developed at NREL. It attempts to approximate a market-driven investment equilibrium outcome under the assumption of idealized or perfect competition (e.g. no participants are able to exert market power or leverage exclusive cost advantages) and uncertain future conditions.", + "laborHours": 1079.2, + "languages": [ + "Julia" + ], + "name": "EMIS-CompetitiveEquilibrium.jl [SWR-19-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMIS-CompetitiveEquilibrium.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMIS-Data_[SWR-19-56].json b/agency-indexes/DoE/EMIS-Data_[SWR-19-56].json new file mode 100644 index 00000000..ec073481 --- /dev/null +++ b/agency-indexes/DoE/EMIS-Data_[SWR-19-56].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-10-26", + "metadataLastUpdated": "2023-04-24" + }, + "description": "In support of the Electricity Markets and Investment Suite, this repository hold data set used in the following julia packages EMISApproximateEquilibrium.jl, EMISCompetitiveEquilibrium.jl, and EMISAgentSimulation.jl.", + "laborHours": 137073.6, + "languages": [ + "HTML" + ], + "name": "EMIS-Data [SWR-19-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMIS-Data", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMISApproximateEquilibrium.jl_[SWR-19-56].json b/agency-indexes/DoE/EMISApproximateEquilibrium.jl_[SWR-19-56].json new file mode 100644 index 00000000..434e044b --- /dev/null +++ b/agency-indexes/DoE/EMISApproximateEquilibrium.jl_[SWR-19-56].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-10-26", + "metadataLastUpdated": "2023-04-24" + }, + "description": "The Electricity Markets Investment Suite Approximate Equilibrium (EMIS-AE) package is developed at NREL and provides a solution capability to solve generation expansion equilibrium problems in the electricity markets. EMIS-AE is designed to capture the evolution of the electricity generation portfolio resulting from the interactions of heterogeneous investors under different policy and market designs. The investment problem for each generation company (GENCO) is a bi-level problem with the investment decision made in the upper level and market clearing condition in the lower level, which traditionally is represented as a Mathematical Program with Equilibrium Constraint (MPEC). EMIS-AE provides a predictive model to be trained for estimating the system-wide revenues for each technology type across energy, ancillary services and capacity markets given the amount of installed capacity on the grid. The profit maximization investment problem for each GENCO is solved using a global search algorithm, which uses the predictive model to evaluate the objective function. To solve for the strategic equilibrium, each GENCO\u2019s problem is plugged into a diagonalization algorithm that is generally used in multi-leader, single-follower bi-level problems.", + "laborHours": 1520.0, + "languages": [ + "Julia", + "Python" + ], + "name": "EMISApproximateEquilibrium.jl [SWR-19-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMISApproximateEquilibrium.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMIS_Agent_Simulation_Model__Electricity_Markets_Investment_Suite__[SWR-19-56].json b/agency-indexes/DoE/EMIS_Agent_Simulation_Model__Electricity_Markets_Investment_Suite__[SWR-19-56].json new file mode 100644 index 00000000..aabe4686 --- /dev/null +++ b/agency-indexes/DoE/EMIS_Agent_Simulation_Model__Electricity_Markets_Investment_Suite__[SWR-19-56].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-10-26", + "metadataLastUpdated": "2023-04-24" + }, + "description": "The Electricity Markets Investment Suite Agent-based Simulation (EMIS-AS) model is an agent-based model developed at NREL for simulating annual investment and retirement decisions of heterogeneous investors in the electricity sector. EMIS-AS is designed to capture the evolution of the electricity generation portfolio resulting from the interactions of heterogeneous investors under different policy and market designs. EMIS-AS not only allows end-users to customize market products and rules, but also to capture investors' heterogeneous financing parameters, technology preferences, beliefs about the future (forecasts), ability to update those forecasts, and risk preferences under uncertainty.", + "laborHours": 5046.4, + "languages": [ + "Julia" + ], + "name": "EMIS Agent Simulation Model (Electricity Markets Investment Suite) [SWR-19-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMISAgentSimulation.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMPRESSA_v.0.01.json b/agency-indexes/DoE/EMPRESSA_v.0.01.json new file mode 100644 index 00000000..0ac4ecf9 --- /dev/null +++ b/agency-indexes/DoE/EMPRESSA_v.0.01.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2022-10-06" + }, + "description": "SAND2021-13992 O EMPRESSA is a descriptive metadata management service for large-scale HPC applications that use any mesh type. EMPRESSA uses an RDBMS storage backend and provides mesh indexing capabilities which allows scientists to efficiently store descriptive metadata attributes that describe identified features of interest and then later search these attributes to determine what data contains these features. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "EMPRESSA v.0.01", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.01" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMPRESS_v.2.0.json b/agency-indexes/DoE/EMPRESS_v.2.0.json new file mode 100644 index 00000000..e03d8909 --- /dev/null +++ b/agency-indexes/DoE/EMPRESS_v.2.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "EMPRESS is a metadata management system designed to offer rapid access to annotated data at a data-region level, rather than on a whole data set or variable level. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-4637 O", + "laborHours": 112358.4, + "languages": [ + "CMake", + "C++", + "C" + ], + "name": "EMPRESS v.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/empress", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMPaSE:_an_Extensible_Multi-Paradigm_Simulation_Environment.json b/agency-indexes/DoE/EMPaSE:_an_Extensible_Multi-Paradigm_Simulation_Environment.json new file mode 100644 index 00000000..95f3cba5 --- /dev/null +++ b/agency-indexes/DoE/EMPaSE:_an_Extensible_Multi-Paradigm_Simulation_Environment.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "EMPaSE is a hierarchical, extensible, modular modeling environment for developing and running hybrid simulations of sequential-modular, systems dynamics, discrete-event, and agent-based paradigms. It contains two principle components: a multi-paradigm simulation engine and a graphical user interface. EMPaSE models are defined through a hierarchically-defined set of computational modules that define the simulation logic. Inter-module communication occurs through two complimentary systems: pull-based \"ports\" for general computation patterns and push-based \"plugs\" for event processing. Entities (i.e. agents) within the simulation operate within an abstract multi-network environment. The EMPaSE simulation engine is designed around a flexible plug-in architecture, allowing simulations to import computational modules, engine customizations, and interfaces to external applications from independent plug-in libraries. The EMPaSE GUI environment provides an environment for graphically constructing, executing, and debugging EMPaSE models. As with the simulation engine, the GUI is constructed on top of an extensible architecture that supports rapid customization of the user experience through external plug-in libraries.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "gcc>=3.4.2 or Microsfot Visual Studio 2005" + ], + "name": "EMPaSE: an Extensible Multi-Paradigm Simulation Environment", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMSL-Computing_CoreMS-Portal.json b/agency-indexes/DoE/EMSL-Computing_CoreMS-Portal.json new file mode 100644 index 00000000..03d5edff --- /dev/null +++ b/agency-indexes/DoE/EMSL-Computing_CoreMS-Portal.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Software that orchestrate data processing and management for mass spectrometry workflows and data products. Stack presented contains a web application, data processing job scheduling, and data processing workers for data processing and management.", + "laborHours": 0.0, + "languages": [], + "name": "EMSL-Computing/CoreMS-Portal", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-Computing/CoreMS-Portal", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMSL-Computing_PeakDecoder.json b/agency-indexes/DoE/EMSL-Computing_PeakDecoder.json new file mode 100644 index 00000000..f4bd3c16 --- /dev/null +++ b/agency-indexes/DoE/EMSL-Computing_PeakDecoder.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-09-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PeakDecoder is a machine learning (ML)-based metabolite identification algorithm for multidimensional mass spectrometry measurements incorporating liquid chromatography (LC) and ion mobility spectrometry (IM) separations, and collecting extensive fragmentation spectra with data-independent acquisition (DIA) methods: LC-IM-DIA-MS. The algorithm learns to distinguish true co-elution and co-mobility from raw data and calculates metabolite identification error rates.", + "laborHours": 0.0, + "languages": [], + "name": "EMSL-Computing/PeakDecoder", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-Computing/PeakDecoder", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMSL-Computing_fticRanalysis.json b/agency-indexes/DoE/EMSL-Computing_fticRanalysis.json new file mode 100644 index 00000000..3fa05b43 --- /dev/null +++ b/agency-indexes/DoE/EMSL-Computing_fticRanalysis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-01-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "fticRanalysis - a package to hand data formatting and storage of Fourier-transform ion cyclotron resonance (FTICR) data in a generalizable way. Additional functionality is available for manipulating and transforming the data, filtering the data based on different criteria, creating summary plots (e.g. Van Krevelen plots, Kendrick plots, etc.), summarizing group-level data, comparing treatment groups, and making complementary plotting functionality", + "laborHours": 38288.8, + "languages": [], + "name": "EMSL-Computing/fticRanalysis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-Computing/fticRanalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMSL-Computing_nmRanalysis.json b/agency-indexes/DoE/EMSL-Computing_nmRanalysis.json new file mode 100644 index 00000000..ab919c07 --- /dev/null +++ b/agency-indexes/DoE/EMSL-Computing_nmRanalysis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "R package that serves as wrapper for rDolphin, an open-source R package that performs semiautomated quantification of metabolites represented within Nuclear Magnetic Resonance (NMR) spectral data", + "laborHours": 0.0, + "languages": [], + "name": "EMSL-Computing/nmRanalysis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-Computing/nmRanalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMSL-MSC_MscClusterMgmt.json b/agency-indexes/DoE/EMSL-MSC_MscClusterMgmt.json new file mode 100644 index 00000000..990be064 --- /dev/null +++ b/agency-indexes/DoE/EMSL-MSC_MscClusterMgmt.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-09-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a suite of automation tools used to manage large HPC clusters using xCAT", + "laborHours": 562.4, + "languages": [], + "name": "EMSL-MSC/MscClusterMgmt", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/MscClusterMgmt", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMTA-NLA.json b/agency-indexes/DoE/EMTA-NLA.json new file mode 100644 index 00000000..298d0d27 --- /dev/null +++ b/agency-indexes/DoE/EMTA-NLA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "EMTA-NLA is a computer program for analyzing the nonlinear stiffness, strength, and thermo-elastic properties of discontinuous fiber composite materials. Discontinuous fiber composites are chopped-fiber reinforced polymer materials that are formed by injection molding or compression molding techniques. The fibers tend to align during forming as the composite flows and fills the mold. EMTA-NLA can read the fiber orientation data from the molding software, Autodesk Moldflow Plastics Insight, and calculate the local material properties for accurately analyzing the warpage, stiffness, and strength of the as-formed composite part using the commercial NLA software. Therefore, EMTA-NLA is a unique assembly of mathematical algorithms that provide a one-of-a-kind composites constitutive model that links these two powerful commercial software packages.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "EMTA-NLA", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/EMeRGE__Emerging_technologies_Management_and_Risk_evaluation_on_distribution_Grids_Evolution_.json b/agency-indexes/DoE/EMeRGE__Emerging_technologies_Management_and_Risk_evaluation_on_distribution_Grids_Evolution_.json new file mode 100644 index 00000000..ca0fc920 --- /dev/null +++ b/agency-indexes/DoE/EMeRGE__Emerging_technologies_Management_and_Risk_evaluation_on_distribution_Grids_Evolution_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "EMeRGE (Emerging technologies Management and Risk evaluation on distribution Grids Evolution) is a collection of mini-tools to help users develop openDSS feeder model from GIS (.shp) file and perform risk analysis at various PV scenarios and visulize results in an interactive dashboard made using Dash.", + "laborHours": 11172.0, + "languages": [], + "name": "EMeRGE (Emerging technologies Management and Risk evaluation on distribution Grids Evolution)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EMeRGE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ENIGMA_Metal_Metabolism_Campaign.json b/agency-indexes/DoE/ENIGMA_Metal_Metabolism_Campaign.json new file mode 100644 index 00000000..e0f84101 --- /dev/null +++ b/agency-indexes/DoE/ENIGMA_Metal_Metabolism_Campaign.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "ENIGMA Metal Metabolism Campaign generates various types of biological data. This repository contains KBase data models, data uploaders/downloaders, etc to enable modeling of a collaborative research of several ENIMGA Metal Campaign teams in the KBase environment.", + "laborHours": 1717.6, + "languages": [], + "name": "ENIGMA Metal Metabolism Campaign", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/enigma_metal_campaign", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ENRICO:_Exascale_Nuclear_Reactor_Investigative_Code_.json b/agency-indexes/DoE/ENRICO:_Exascale_Nuclear_Reactor_Investigative_Code_.json new file mode 100644 index 00000000..ec365cbb --- /dev/null +++ b/agency-indexes/DoE/ENRICO:_Exascale_Nuclear_Reactor_Investigative_Code_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-31", + "metadataLastUpdated": "2019-07-31" + }, + "description": "ENRICO is a code to automate the workflow for iteratively solving neutral particle transport via the OpenMC code and fluid dynamics via the Nek5000 code. It establishes a mapping between the geometry representation of a model in OpenMC and the spectral element mesh used by Nek5000 so that the output of each code can be used as the input of the other. Heat generation rates as solved by OpenMC are used as heat sources in a Nek5000 simulation, and the temperature/density fields from Nek5000 are used as inputs for the OpenMC model. Both OpenMC and Nek5000 are open-source, community-developed, simulation codes. ", + "laborHours": 34245.6, + "languages": [], + "name": "ENRICO: Exascale Nuclear Reactor Investigative Code ", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/enrico-dev/enrico", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EOS7C-ECBM_Version_1.0.json b/agency-indexes/DoE/EOS7C-ECBM_Version_1.0.json new file mode 100644 index 00000000..58681640 --- /dev/null +++ b/agency-indexes/DoE/EOS7C-ECBM_Version_1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-26", + "metadataLastUpdated": "2019-09-24" + }, + "description": "EOS7C is an equation of state module for the TOUGH2 program for CO2 or N2 in Methane (CH4) Reservoirs. In the present work, additions have been made to the EOS7C Version 1.0 module to include the Enhanced Coal Bed Methane (ECBM) modifications developed by Webb (2003). In addition, the Dusty Gas Model for gas-phase diffusion (Webb 2001) has been included. The ECBM modification to the EOS7C equation of state incorporate the extended Langmuir isothem for sorbing gases, including the change in porosity associated with the sorbed gas mass. Comparison to hand calculations for pure gas and binary mixture shows very good agreement. Application to a CO2 well injection problem by Law et al. (2002). The Dusty Model modification add options to calculate gas diffusion using the Dusty-Gas Model including separate and coupled approaches. Comparison to low-permeability pure gas diffusion data shows excellent agreement. The results from the DGM are compared to the Fick's Law behavior for diffusion across a capillary fringe. The differences between the models are small due to the relatively high permeability (10-11 m2) of the problem.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "EOS7C-ECBM Version 1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/EOS7CA_Version_1.0:_TOUGH2_Module_for_Gas_Migration_in_Shallow_Subsurface_Porous_Media_Systems.json b/agency-indexes/DoE/EOS7CA_Version_1.0:_TOUGH2_Module_for_Gas_Migration_in_Shallow_Subsurface_Porous_Media_Systems.json new file mode 100644 index 00000000..44860ab5 --- /dev/null +++ b/agency-indexes/DoE/EOS7CA_Version_1.0:_TOUGH2_Module_for_Gas_Migration_in_Shallow_Subsurface_Porous_Media_Systems.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-28", + "metadataLastUpdated": "2018-10-01" + }, + "description": "EOS7CA is a TOUGH2 module for mixtures of a non-condensible gas (NCG) and air (with or without a gas tracer), an aqueous phase, and water vapor. The user can select the NCG as being CO2, N2, or CH4. EOS7CA uses a cubic equation of state with a multiphase version of Darcy's Law to model flow and transport of gas and aqueous phase mixtures over a range of pressures and temperatures appropriate to shallow subsurface porous media systems. The limitation to shallow systems arises from the use of Henry's Law for gas solubility which is appropriate for low pressures but begins to over-predict solubility starting at pressures greater than approximately 1 MPa (10 bar). The components modeled in EOS7CA are water, brine, NCG, gas tracer, air, and optional heat.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 7706.4, + "languages": [], + "name": "EOS7CA Version 1.0: TOUGH2 Module for Gas Migration in Shallow Subsurface Porous Media Systems", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/EOS7C_Version_1.0.json b/agency-indexes/DoE/EOS7C_Version_1.0.json new file mode 100644 index 00000000..9369476a --- /dev/null +++ b/agency-indexes/DoE/EOS7C_Version_1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-27", + "metadataLastUpdated": "2019-09-24" + }, + "description": "EOS7C allows the user to model CO2 injection into natural gas reservoirs that contain methane. There are numerous natural gas modeling codes that can be easily modified to handle CO2, but the developer is not aware of any direct competitors. The current use of the code would be research on carbon sequestration or enhanced natural gas recovery (something the industry is not yet motivated to do). The code development was fully funded by DOE, contains no third party code as the developer has removed MA 28 from the manual, and fully written by LBNL employees. \n\nThe code will be distributed via the TOUGH website and requires the use of TOUGH 2 v2, with which it will be bundled. ", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 7159.2, + "languages": [], + "name": "EOS7C Version 1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/EOS9nT_V2.0_and_User's_Manual_-_A_FORTRAN_90_Simulator_of_Water_Flow_and_Solute_Colloid_Transport_in_the_Subsurface.json b/agency-indexes/DoE/EOS9nT_V2.0_and_User's_Manual_-_A_FORTRAN_90_Simulator_of_Water_Flow_and_Solute_Colloid_Transport_in_the_Subsurface.json new file mode 100644 index 00000000..52de53e0 --- /dev/null +++ b/agency-indexes/DoE/EOS9nT_V2.0_and_User's_Manual_-_A_FORTRAN_90_Simulator_of_Water_Flow_and_Solute_Colloid_Transport_in_the_Subsurface.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-07-01", + "metadataLastUpdated": "2019-07-02" + }, + "description": "Geophysics and Flows", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "EOS9nT V2.0 and User's Manual - A FORTRAN 90 Simulator of Water Flow and Solute/Colloid Transport in the Subsurface", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/EOSlib,_Version_3.json b/agency-indexes/DoE/EOSlib,_Version_3.json new file mode 100644 index 00000000..04240176 --- /dev/null +++ b/agency-indexes/DoE/EOSlib,_Version_3.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Equilibrium thermodynamics underpins many of the technologies used throughout theoretical physics, yet verification of the various theoretical models in the open literature remains challenging. EOSlib provides a single, consistent, verifiable implementation of these models, in a single, easy-to-use software package. It consists of three parts: a software library implementing various published equation-of-state (EOS) models; a database of fitting parameters for various materials for these models; and a number of useful utility functions for simplifying thermodynamic calculations such as computing Hugoniot curves or Riemann problem solutions. Ready availability of this library will enable reliable code-to- code testing of equation-of-state implementations, as well as a starting point for more rigorous verification work. EOSlib also provides a single, consistent API for its analytic and tabular EOS models, which simplifies the process of comparing models for a particular application.", + "laborHours": 55753.6, + "name": "EOSlib, Version 3", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/EOSlib/blob/github/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EOSlib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EPANET-BAM.json b/agency-indexes/DoE/EPANET-BAM.json new file mode 100644 index 00000000..0759e13e --- /dev/null +++ b/agency-indexes/DoE/EPANET-BAM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "EPANET-BAM 1.0 is an augmented version of EPANET 2.00.10, open-source software distributed by the US Environmental Protection Agency that models flow and contaminant transport through water distribution pipe networks. EPANET-BAM uses a new Bulk advective Mixing (BAM) model to predict concentrations of an aqueous solute at the outlets of cross junctions in a water quality simulation.", + "laborHours": 0.0, + "languages": [], + "name": "EPANET-BAM", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/EPANET-BAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EPBD-BERT.json b/agency-indexes/DoE/EPBD-BERT.json new file mode 100644 index 00000000..6ebd031b --- /dev/null +++ b/agency-indexes/DoE/EPBD-BERT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This framework aids in Transcription factor binding site prediction given DNA sequence information and DNA biophysical characteristics computed by pyDNA-EPBD. This framework utilizes a large language model for binding site prediction.", + "laborHours": 10564.0, + "languages": [], + "name": "EPBD-BERT", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EPBD-BERT", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EPICS_Channel_Access_Server_for_LabVIEW.json b/agency-indexes/DoE/EPICS_Channel_Access_Server_for_LabVIEW.json new file mode 100644 index 00000000..1837f387 --- /dev/null +++ b/agency-indexes/DoE/EPICS_Channel_Access_Server_for_LabVIEW.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "It can be challenging to interface National Instruments LabVIEW (http://www.ni.com/labview/) with EPICS (http://www.aps.anl.gov/epics/). Such interface is required when an instrument control program was developed in LabVIEW but it also has to be part of global control system. This is frequently useful in big accelerator facilities. The Channel Access Server is written in LabVIEW, so it works on any hardware/software platform where LabVIEW is available. It provides full server functionality, so any EPICS client can communicate with it.", + "laborHours": 243.2, + "name": "EPICS Channel Access Server for LabVIEW", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/az9/LVCA/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/az9/LVCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/EPICS_Core_Java_Libraries_Supermodule.json b/agency-indexes/DoE/EPICS_Core_Java_Libraries_Supermodule.json new file mode 100644 index 00000000..ca4dce4e --- /dev/null +++ b/agency-indexes/DoE/EPICS_Core_Java_Libraries_Supermodule.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2022-08-02" + }, + "description": "This is a supermodule to build, test, bundle and deploy all Java/Maven modules of the EPICS Core Libraries. It also contains the EPICS parent POM that is inherited by all modules, and provides a convenience dependency POM that can be used by other projects to depend on a matching set of the EPICS Core libraries.", + "laborHours": 0.0, + "languages": [], + "name": "EPICS Core Java Libraries Supermodule", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/epics-core-java-backport-1.5/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/epics-core-java-backport-1.5", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EPICS_Support_For_Beckhoff_EK9000.json b/agency-indexes/DoE/EPICS_Support_For_Beckhoff_EK9000.json new file mode 100644 index 00000000..719cb369 --- /dev/null +++ b/agency-indexes/DoE/EPICS_Support_For_Beckhoff_EK9000.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-07", + "metadataLastUpdated": "2022-07-07" + }, + "description": "This is a device support module for the EK9000, which couples EtherCAT terminals (specifically the ELXXXX terminals from Beckhoff) to a modbus network. Because it uses modbus, it's runnable on any IOC without needing a kernel module or other support software.", + "laborHours": 0.0, + "languages": [], + "name": "EPICS Support For Beckhoff EK9000", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/epics-ek9000/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/epics-ek9000", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EPOXY.json b/agency-indexes/DoE/EPOXY.json new file mode 100644 index 00000000..4f14b661 --- /dev/null +++ b/agency-indexes/DoE/EPOXY.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2024-07-19" + }, + "description": "EPOXY is a LLVM base compiler that applies security protections to bare-metal programs on ARM Cortex-M series micro-controllers. This includes privilege overlaying, wherein operations requiring privileged execution are identified and only these operations execute in privileged mode. It also applies code integrity, control-flow hijacking defenses, stack protections, and fine-grained randomization schemes. All of its protections work within the constraints of bare-metal systems.", + "laborHours": 263081.6, + "languages": [ + "C++", + "HTML", + "C", + "Makefile", + "Assembly", + "Rich Text Format" + ], + "name": "EPOXY", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/EPOXY?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/EPOXY", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EPU_v.3.0.08.json b/agency-indexes/DoE/EPU_v.3.0.08.json new file mode 100644 index 00000000..e3cd2c2d --- /dev/null +++ b/agency-indexes/DoE/EPU_v.3.0.08.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "EPU recombines multiple results exodus II database files into a single exodus II database. The multiple databases are the results of parallel finite element analysis runs where each processor writes its own portion of the solution to a single file. EPU will then put the pieces back together in the correct order. It allows sub-setting of the data to reduce the size of the final database.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "EPU v.3.0.08", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0.08" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EPXMLPreprocessor.json b/agency-indexes/DoE/EPXMLPreprocessor.json new file mode 100644 index 00000000..debfefec --- /dev/null +++ b/agency-indexes/DoE/EPXMLPreprocessor.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-07-09", + "metadataLastUpdated": "2022-08-08" + }, + "description": "The EPXMLPreprocessor is a computer program that reads an abstract description of a building and writes a complete, fully-functional EnergyPlus\u2122 input file. The building xml model is the text input file to the Preprocessor which contains a minimal set of high-level parameters to describe the building type, geometry, loads, and systems. The Preprocessor constructs the resulting EnergyPlus building model by automatically generating and connecting all of the required EnergyPlus objects based on a set of built-in modeling assumptions. This software is no longer supported and users may use at their own risk.", + "laborHours": 90972.0, + "languages": [ + "Pascal" + ], + "name": "EPXMLPreprocessor", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EPXMLPreprocessor", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EQ3_6_A_Software_Package_for_Geochemical_Modeling.json b/agency-indexes/DoE/EQ3_6_A_Software_Package_for_Geochemical_Modeling.json new file mode 100644 index 00000000..05b1a589 --- /dev/null +++ b/agency-indexes/DoE/EQ3_6_A_Software_Package_for_Geochemical_Modeling.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2022-11-16" + }, + "description": "EQ3/6 is a software package for modeling geochemical interactions between aqueous solution, solids, and gases, following principles of chemical thermodynamics and chemical kinetics. It is useful for interpreting aqueous solution chemical compositions and for calculating the consequences of reaction of such solutions with minerals, other solids, and gases. It is designed to run in a command line environment. EQPT is a thermodynamic data file preprocessor. EQ3NR is a speciation-solubility code. EQ6 is a reaction path code.", + "laborHours": 0.0, + "languages": [], + "name": "EQ3/6 A Software Package for Geochemical Modeling", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/eq3_6", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ERAD__Equitable_Resiliency_Analysis_tool_for_Distribution_System__[SWR-22-75].json b/agency-indexes/DoE/ERAD__Equitable_Resiliency_Analysis_tool_for_Distribution_System__[SWR-22-75].json new file mode 100644 index 00000000..2013d60a --- /dev/null +++ b/agency-indexes/DoE/ERAD__Equitable_Resiliency_Analysis_tool_for_Distribution_System__[SWR-22-75].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-10-18", + "metadataLastUpdated": "2023-02-07" + }, + "description": "ERAD is a software product for computing resiliency and equity metrics in power distribution system. It uses graph database technology to store, query and compute metrics making it highly scalable and available. Metrics can be computed for various resiliency scenarios such as fire, flooding, earthquake.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "ERAD (Equitable Resiliency Analysis tool for Distribution System) [SWR-22-75]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/erad", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESAMS_Anomaly_Detection_Tool.json b/agency-indexes/DoE/ESAMS_Anomaly_Detection_Tool.json new file mode 100644 index 00000000..17e5a598 --- /dev/null +++ b/agency-indexes/DoE/ESAMS_Anomaly_Detection_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software reads PMU (phasor measurement unit) data and creates features from the data that are used in analyses. It\nthen takes the past features from previous days of data and builds a baseline to understand the typical behavior of the\npower grid. This baseline is used by employing multivariate statistical algorithms like PCA (Principal Component Analysis),\nclustering (unsupervised learning), and classification (supervised learning). This baseline is then applied to new data to\ndetermine the state of the power grid, whether the behavior is typical or atypical, compared to what has been seen\npreviously. At the end of the day, the baseline is updated and the new baseline is used on the next day. When a time period\nis determined to be atypical, then drill down analyses are performed to help the user understand why the time period is\natypical. Plots and tables are used to show atypicality, including a performance envelope plot. This plot shows the typical\nbehavior of the variable or feature of interest, by plotting in the background the values of the variable from past days using\ncontour shading over time and then the new data over time. This allows the user to see how the new data differs from past\ndata at the same time.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "ESAMS Anomaly Detection Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_Compute_WPS.json b/agency-indexes/DoE/ESGF_Compute_WPS.json new file mode 100644 index 00000000..6e98c901 --- /dev/null +++ b/agency-indexes/DoE/ESGF_Compute_WPS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "ESGF Compute is a Django application capable of providing compute resources to the ESGF data stack. It leverages the 1.0.0 version of the\u00a0Web Processing Service\u00a0(WPS) standard to process compute requests.\n", + "laborHours": 21325.6, + "languages": [], + "name": "ESGF Compute WPS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-compute-wps", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_Compute_end-user_API.json b/agency-indexes/DoE/ESGF_Compute_end-user_API.json new file mode 100644 index 00000000..015448bb --- /dev/null +++ b/agency-indexes/DoE/ESGF_Compute_end-user_API.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "The ESGF Compute end-user API provides an object-oriented climatology package to access large scale computational resources through the Web Processing Service interface standard.\n", + "laborHours": 1307.2, + "languages": [], + "name": "ESGF Compute end-user API", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-compute-api", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_Dashboard.json b/agency-indexes/DoE/ESGF_Dashboard.json new file mode 100644 index 00000000..44b5cece --- /dev/null +++ b/agency-indexes/DoE/ESGF_Dashboard.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This is the repository for the ESFG Dashboard developed at Lawrence Livermore National Laboratory. \n", + "laborHours": 51269.6, + "languages": [], + "name": "ESGF Dashboard", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-dashboard", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_Fetcher.json b/agency-indexes/DoE/ESGF_Fetcher.json new file mode 100644 index 00000000..3cc4abdb --- /dev/null +++ b/agency-indexes/DoE/ESGF_Fetcher.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "ESGF Fetcher - Keeps fetched files sync'ed\u00a0http://esgf.org/esgf-fetcher/\n", + "laborHours": 380.0, + "languages": [], + "name": "ESGF Fetcher", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-fetcher", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_IDP.json b/agency-indexes/DoE/ESGF_IDP.json new file mode 100644 index 00000000..ab5e2bee --- /dev/null +++ b/agency-indexes/DoE/ESGF_IDP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-17" + }, + "description": "The Yadis discovery service is a simple web application that returns XML documents containing URLs for user services. It has no significant library dependencies. The Openid Server functionality is based on the openid4java library, currently the version modified by ESGF to support attribute providers. It uses Spring for managing the application configuration through dependency injection, but it does not use any Spring Security (except for enforcing HTTPS connections), since Spring Security does not support the server-side functionality of the openid exchange. The Openid Client package is a small application provided as a facility to test the Openid Server. It relies on Spring Security support for the client-side openid, which is in turn based on the openid4java library also.\n", + "laborHours": 2188.8, + "languages": [], + "name": "ESGF IDP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-idp", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_Installer.json b/agency-indexes/DoE/ESGF_Installer.json new file mode 100644 index 00000000..dd0d537f --- /dev/null +++ b/agency-indexes/DoE/ESGF_Installer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "The ESGF Installer is a command line tool for installing the ESGF Software Stack. The software stack is comprised of: Tomcat, Thredds, CDAT & CDMS, PostgreSQL, MyProxy, and several ESGF.org custom software applications running on a LINUX (RedHat/CentOS) operating system.\n", + "laborHours": 6748.8, + "languages": [], + "name": "ESGF Installer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-installer", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_Node_Manager.json b/agency-indexes/DoE/ESGF_Node_Manager.json new file mode 100644 index 00000000..f05c5c62 --- /dev/null +++ b/agency-indexes/DoE/ESGF_Node_Manager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-17" + }, + "description": "The ESGF Node Manager is transitioning. We are repurposing this repo to contain the material essential for installing the new node manager while keeping the original parts of the previous version. 1) java source needed for access logging filter only - future work is to migrate this to another module within ESGF. 2) python sources: for database table creation, for node manager request and worker daemon and django REST service API 3) bash control scripts\n", + "laborHours": 7828.0, + "languages": [], + "name": "ESGF Node Manager", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-node-manager", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_Openid_Relying_Party__ORP_.json b/agency-indexes/DoE/ESGF_Openid_Relying_Party__ORP_.json new file mode 100644 index 00000000..6465182b --- /dev/null +++ b/agency-indexes/DoE/ESGF_Openid_Relying_Party__ORP_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This package contains the ESG OpenidRelyingParty (ORP) web application, which can be used to secure a generic data application server running in a Tomcat container in conjunction with the ESG access control filters, and any Openid Identity Provider.\n", + "laborHours": 2599.2, + "languages": [], + "name": "ESGF Openid Relying Party (ORP)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esg-orp", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_Publisher.json b/agency-indexes/DoE/ESGF_Publisher.json new file mode 100644 index 00000000..51a458d8 --- /dev/null +++ b/agency-indexes/DoE/ESGF_Publisher.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This repository contains a basic description and layout of the ESFG Publisher, with the latest version including the following updates: Support for CMIP6, integration of PrePARE, PID creation via RabbitMQ, cdf2cim included, and handler for non-netCDF and skip variable scan for multiple cases. http://esgf.github.io/esg-publisher/\n", + "laborHours": 24806.4, + "languages": [], + "name": "ESGF Publisher", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esg-publisher", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_Search_Component.json b/agency-indexes/DoE/ESGF_Search_Component.json new file mode 100644 index 00000000..474595af --- /dev/null +++ b/agency-indexes/DoE/ESGF_Search_Component.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This module contains the next generation search functionality for the Earth System Grid Federation, built upon the Apache Solr search engine. The package contains functionality for: - Publishing and unpublishing search metadata records into and from a Solr server. Metadata records are generated by harvesting a remote metadata source (a hierarchy of THREDDS catalogs, a OAI repository, a CAS metadata catalog). - Searching the Solr engine content via a free text or faceted search.\n", + "laborHours": 12828.8, + "languages": [], + "name": "ESGF Search Component", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esg-search", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_Security.json b/agency-indexes/DoE/ESGF_Security.json new file mode 100644 index 00000000..a4c23d2c --- /dev/null +++ b/agency-indexes/DoE/ESGF_Security.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This project contains a web application that can be used to deploy an ESG Attribute Service and/or an ESG Authorization service. Additionally, the packaged jar contains ESG utilities for parsing and producing SAML statements that can be used in other ESG SAML-aware projects.\n", + "laborHours": 9880.0, + "languages": [], + "name": "ESGF Security", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-security", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_Toolbox.json b/agency-indexes/DoE/ESGF_Toolbox.json new file mode 100644 index 00000000..92faf0b2 --- /dev/null +++ b/agency-indexes/DoE/ESGF_Toolbox.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This is the repository for the ESFG Toolbox developed at Lawrence Livermore National Laboratory.", + "laborHours": 380.0, + "languages": [], + "name": "ESGF Toolbox", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-toolbox", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_apache-frontend.json b/agency-indexes/DoE/ESGF_apache-frontend.json new file mode 100644 index 00000000..8ad95fff --- /dev/null +++ b/agency-indexes/DoE/ESGF_apache-frontend.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This is the repository for apache-frontend, Earth System Grid Federation (ESGF) developed at Lawrence Livermore National Laboratory.\n", + "laborHours": 91.2, + "languages": [], + "name": "ESGF/apache-frontend", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/apache-frontend", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_compute.json b/agency-indexes/DoE/ESGF_compute.json new file mode 100644 index 00000000..db9a449b --- /dev/null +++ b/agency-indexes/DoE/ESGF_compute.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This is the repository for compute developed at Lawrence Livermore National Laboratory. \n", + "laborHours": 91.2, + "languages": [], + "name": "ESGF/compute", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/compute", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESGF_config.json b/agency-indexes/DoE/ESGF_config.json new file mode 100644 index 00000000..e79fc960 --- /dev/null +++ b/agency-indexes/DoE/ESGF_config.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "ESGF repository containing global registries and configuration files.\n", + "laborHours": 2796.8, + "languages": [], + "name": "ESGF/config", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/config", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESS-DIVE_File_Level_Metadata_Extractor.json b/agency-indexes/DoE/ESS-DIVE_File_Level_Metadata_Extractor.json new file mode 100644 index 00000000..5cb94dff --- /dev/null +++ b/agency-indexes/DoE/ESS-DIVE_File_Level_Metadata_Extractor.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "velliquettet@ornl.gov" + }, + "date": { + "created": "2020-11-03", + "metadataLastUpdated": "2021-02-08" + }, + "description": "The File-level Metadata (FLMD) parser is a lightweight python script that can produce a summary of fields based on column headers within a Comma-separated Values (CSV) file. The script enables a way to extract certain metadata fields from CSV data files. An optional configuration file can be used to select specific column headers to extract a smaller subset of values. The script can be used on a single file, or it can be given a directory to process groups of files in bulk. The FLMD parser outputs the metadata as a JSON and can be configured to updated the source file or produce an external companion file.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ESS-DIVE File Level Metadata Extractor", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/ngee-arctic/ess-dive-meta", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/ngee-arctic/ess-dive-meta", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESTEEM.json b/agency-indexes/DoE/ESTEEM.json new file mode 100644 index 00000000..0ef89269 --- /dev/null +++ b/agency-indexes/DoE/ESTEEM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ESTEEM is an interactive web-based prototype visualization tool to allow you to explore dynamic word embeddings across regions using siple keyword queries.", + "laborHours": 7995.2, + "languages": [], + "name": "ESTEEM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/esteem", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESnet_Network_Operating_System__ENOS_.json b/agency-indexes/DoE/ESnet_Network_Operating_System__ENOS_.json new file mode 100644 index 00000000..3fdbac0b --- /dev/null +++ b/agency-indexes/DoE/ESnet_Network_Operating_System__ENOS_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2020-09-08" + }, + "description": "ENOS is a prototype next-generation ESnet architecture for handling data-intensive science workflows. The concept of a 'network operating system', a software layer that enables applications to get information about the network and to program it to meet its needs, has been around in academic papers for a while but appears to be feasible now due to the wide adoption of the Software-Defined Networking (SDN) paradigm. The SDN paradigm constitutes a network architecture that separates the control plane from the distributed data plane and provides logical centralization of the network control and state. These logical central control plane capabilities can be evolved to become the operating system through which the network policies are implemented across the entire network and applications can program network behavior.", + "laborHours": 10138.4, + "languages": [], + "name": "ESnet Network Operating System (ENOS)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/enos/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/enos", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESnet_React_Base.json b/agency-indexes/DoE/ESnet_React_Base.json new file mode 100644 index 00000000..977984d8 --- /dev/null +++ b/agency-indexes/DoE/ESnet_React_Base.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "Common React components for ESnet tools.", + "laborHours": 1368.0, + "languages": [], + "name": "ESnet React Base", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/esnet-react-base/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/esnet-react-base", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESnet_Secure_Copy__EScp__v0.6.json b/agency-indexes/DoE/ESnet_Secure_Copy__EScp__v0.6.json new file mode 100644 index 00000000..4ef3de9a --- /dev/null +++ b/agency-indexes/DoE/ESnet_Secure_Copy__EScp__v0.6.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-11", + "metadataLastUpdated": "2021-08-11" + }, + "description": "EScp is a high speed transfer tool with a similar command line syntax to scp. Unlike SCP it is designed to transfer files at high speed, thus far we have been able to show 100gbit/s transfers, although I expect that the throughput should scale in proportion to the network interface, i.e. I expect 400gbit/s performance on our 400gbit/s test bed. EScp achieves good performance through an innovative design (multithreaded, zero copy transfers), along with pluggable filters and I/O engines. As an example, you can switch from POSIX i/O to UIO by checking a different engine. It also natively supports encryption, and cheksums for file verification and transport security. AAA is through standard SSH (same as SCP). By taking advantage of filters, EScp supports transferring unstructured data and/or I/O to non-posix data sources. Examples include streaming data (i.e. from equipment), transferring data to the cloud, and/or supporting non-posix file systems (like HPSS).", + "laborHours": 0.0, + "languages": [], + "name": "ESnet Secure Copy (EScp) v0.6", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/EScp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESnet_SmartNIC_v1.0.json b/agency-indexes/DoE/ESnet_SmartNIC_v1.0.json new file mode 100644 index 00000000..f0612918 --- /dev/null +++ b/agency-indexes/DoE/ESnet_SmartNIC_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The ESnet SmartNIC is a collection of Verilog based FPGA design software, as well as drivers to interact with the FPGA. It provides an infrastructure framework for FPGA based hardware acceleration of network packet use cases. Different research and production applications can be easily written for the SmartNIC. Its advantage is that it reduces the development time for new applications by providing a pre-existing shell library for common functions.", + "laborHours": 15838.4, + "languages": [], + "name": "ESnet SmartNIC v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/esnet-smartnic-hw", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ESnet_docker.json b/agency-indexes/DoE/ESnet_docker.json new file mode 100644 index 00000000..f9ad0334 --- /dev/null +++ b/agency-indexes/DoE/ESnet_docker.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "Files for various Science DMZ use cases. ", + "laborHours": 76.0, + "languages": [], + "name": "ESnet docker", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/docker", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EUForia.json b/agency-indexes/DoE/EUForia.json new file mode 100644 index 00000000..d4a88f43 --- /dev/null +++ b/agency-indexes/DoE/EUForia.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-09", + "metadataLastUpdated": "2024-07-23" + }, + "description": "EUForia is a general-purpose model checker that solves reachability problems in dynamical systems. It implements an abstraction-refinement process in which the system is iteratively approximated until it can prove or disprove that a system state is reachable. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-3020 O", + "laborHours": 23499.2, + "languages": [ + "C++", + "Shell", + "Nix", + "CMake", + "Makefile", + "Python" + ], + "name": "EUForia", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/euforia", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EVI-OnDemand_[SWR-21-115].json b/agency-indexes/DoE/EVI-OnDemand_[SWR-21-115].json new file mode 100644 index 00000000..1cf7b182 --- /dev/null +++ b/agency-indexes/DoE/EVI-OnDemand_[SWR-21-115].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-06-28", + "metadataLastUpdated": "2024-07-15" + }, + "description": "EVI-OnDemand is a simulation platform which estimates fast-charging infrastructure requirements necessary to support ride-hailing electrification. The tool belongs to the broader EVI-X family, a consortium of infrastructure modeling tools created by researchers at the National Renewable Energy Laboratory (NREL).", + "laborHours": 228.0, + "languages": [ + "Python" + ], + "name": "EVI-OnDemand [SWR-21-115]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EVI-OnDemand", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EVOLVE.json b/agency-indexes/DoE/EVOLVE.json new file mode 100644 index 00000000..f93cba95 --- /dev/null +++ b/agency-indexes/DoE/EVOLVE.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "EVOLVE is a combination of a dashboard developed in React, which enables user to visualize the net load evolution with emerging technologies such as PV, energy storage, and electric vehicles, and a Python backend processes data. A user can choose settings for solar, energy storage, and electric vehicles in the dashboard. Modules that are developed to model the impact of these DERs can also be used independently without being integrated into the dashboard. We used a RESTful API to expose these modules to the React front-end. ", + "laborHours": 30749.6, + "languages": [ + "Python", + "Python" + ], + "name": "EVOLVE", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/evolve", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EXACT_Software_Repository_v_1.1.json b/agency-indexes/DoE/EXACT_Software_Repository_v_1.1.json new file mode 100644 index 00000000..818c84f7 --- /dev/null +++ b/agency-indexes/DoE/EXACT_Software_Repository_v_1.1.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-30" + }, + "description": "The EXACT Software Repository contains a variety of software packages for describing, controlling, and analyzing computer experiments. The EXACT Python framework provides the experimentalist with convenient software tools to ease and organize the entire experimental process, including the description of factors and levels, the design of experiments, the control of experimental runs, the archiving of results, and analysis of results. The FAST package provides a Framework for Agile Software Testing. FAST manage the distributed execution of EXACT, as well as summaries of test results.", + "laborHours": 0.0, + "languages": [ + "Perl", + "Python" + ], + "name": "EXACT Software Repository v 1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/exact", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EXARL-Easily_eXtendable_Architecture_for_Reinforcement_Learning.json b/agency-indexes/DoE/EXARL-Easily_eXtendable_Architecture_for_Reinforcement_Learning.json new file mode 100644 index 00000000..d4e89753 --- /dev/null +++ b/agency-indexes/DoE/EXARL-Easily_eXtendable_Architecture_for_Reinforcement_Learning.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-14", + "metadataLastUpdated": "2022-01-14" + }, + "description": "A scalable software framework for reinforcement learning environments and agents/policies used for the Design and Control applications", + "laborHours": 0.0, + "languages": [], + "name": "EXARL-Easily eXtendable Architecture for Reinforcement Learning", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exalearn/exarl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EXSCLAIM!.json b/agency-indexes/DoE/EXSCLAIM!.json new file mode 100644 index 00000000..46562867 --- /dev/null +++ b/agency-indexes/DoE/EXSCLAIM!.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-08", + "metadataLastUpdated": "2022-04-08" + }, + "description": "Due to recent improvements in image resolution and acquisition speed, materials microscopy is experiencing an explosion of published imaging data. The standard publication format, while sufficient for traditional data ingestion scenarios where a select number of images can be critically examined and curated manually, is not conducive tolarge-scale data aggregation or analysis, hindering data sharing and reuse. Most images in publications are presented as components of a larger figure with their explicit context buried in the main body or caption text, so even if aggregated, collections of images with weak or no digitized contextual labels have limited value. To solve the problem of curating labeled microscopy data from literature, we introduce the EXSCLAIM! Python toolkit for the automatic EXtraction, Separation, and Caption-based natural Language Annotation of IMages from scientific literature. The software is implemented through a three part pipeline: the JournalScraper, which searches the web and downloads figures and captions based on a user provided query, the CaptionDistributor, which separates caption text based on the subfigure each portion of the caption refers to, and the FigueSeparator, which separates figures into component subfigures and extracts other visual information. Also included is a Django user interface for exploring the resulting dataset.", + "laborHours": 0.0, + "languages": [], + "name": "EXSCLAIM!", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MaterialEyes/exsclaim", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EXTENDED_VERSION_OF_SOFTWARE_POLYLAUE.json b/agency-indexes/DoE/EXTENDED_VERSION_OF_SOFTWARE_POLYLAUE.json new file mode 100644 index 00000000..18ea1bc8 --- /dev/null +++ b/agency-indexes/DoE/EXTENDED_VERSION_OF_SOFTWARE_POLYLAUE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-08-28", + "metadataLastUpdated": "2024-08-28" + }, + "description": "(SF-24-031) Software PolyLaue, having ANL OPEN SOURCE LICENSE, will be extended by KITWARE, INC. New functionality, including file manager, visualizer and mapping routine will substantially improve the procedure to identify single-crystals across compression with Laue diffraction technique.", + "laborHours": 1565.6, + "languages": [], + "name": "EXTENDED VERSION OF SOFTWARE POLYLAUE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PolyLaue/PolyLaue", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Earth's_Field_NMR_SPINACH_Simulation_Code.json b/agency-indexes/DoE/Earth's_Field_NMR_SPINACH_Simulation_Code.json new file mode 100644 index 00000000..961d71e4 --- /dev/null +++ b/agency-indexes/DoE/Earth's_Field_NMR_SPINACH_Simulation_Code.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "MATLAB code that executes a numerical simulation in the open-source software, SPINACH, which is written for MATLAB. The simulation was used as data in our published paper (https://doi.org/10.1016/j.jmr.2023.107540).", + "laborHours": 0.0, + "languages": [], + "name": "Earth's Field NMR SPINACH Simulation Code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EFNMR_LANL", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Earth_System_Grid__ESG__Data_Node_Software_Stack.json b/agency-indexes/DoE/Earth_System_Grid__ESG__Data_Node_Software_Stack.json new file mode 100644 index 00000000..f44f1ac3 --- /dev/null +++ b/agency-indexes/DoE/Earth_System_Grid__ESG__Data_Node_Software_Stack.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The ESG-CET system consist of two major components: 1) Gateways that support portal services, which serve as interfaces to end-users who can search, discover, and request data and data products, and 2) Data Nodes where the data actually resides. The Data is \"published\" to the Data Node, which makes the data visible to a Gateway and enables its delivery to end-users. It is expected that Gateways will only be installed by a small number of centers devoted to serving data (e.g., LLNL/PCMDI, NCAR, GFDL, DADC, DKRZ, ANU, JAMSTEC), whereas it is hoped that most climate modeling centers will install the Data Node software through which they can serve their model output.", + "laborHours": 0.0, + "languages": [], + "name": "Earth System Grid (ESG) Data Node Software Stack", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/earth-system-grid-esg-data-node-software-stack", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Earthdata_Pub.json b/agency-indexes/DoE/Earthdata_Pub.json new file mode 100644 index 00000000..a46d48b9 --- /dev/null +++ b/agency-indexes/DoE/Earthdata_Pub.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "wilsonbe@ornl.gov" + }, + "date": { + "created": "2023-11-08", + "metadataLastUpdated": "2023-11-08" + }, + "description": "Earthdata Pub is a toolset that provides forms and workflows so that a data producer can request archival of their NASA-funded data, NASA can determine which (if any) DAAC is appropriate to that data, and the selected DAAC can work with the data producer to get the data and metadata necessary for publication.", + "laborHours": 0.0, + "languages": [], + "name": "Earthdata Pub", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eosdis-nasa/earthdata-pub", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EastCoast_v1.0.0.json b/agency-indexes/DoE/EastCoast_v1.0.0.json new file mode 100644 index 00000000..573fc50d --- /dev/null +++ b/agency-indexes/DoE/EastCoast_v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "This repository contains data and code for statistically comparing soil microbial communities across four different wetland sites and making publication quality figures. It is similar to other microbiome analysis but is specific for this project.", + "laborHours": 834145.6, + "languages": [], + "name": "EastCoast v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cliffbueno/EastCoast", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Eastern_Interconnection_Situational_Awareness_Monitoring_System__ESAMS__Oscillation_Tool.json b/agency-indexes/DoE/Eastern_Interconnection_Situational_Awareness_Monitoring_System__ESAMS__Oscillation_Tool.json new file mode 100644 index 00000000..20ff05b1 --- /dev/null +++ b/agency-indexes/DoE/Eastern_Interconnection_Situational_Awareness_Monitoring_System__ESAMS__Oscillation_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The tool is designed to read, process, analyze, and report on data produced by phasor measurement units (PMUs). It has\nthree main functions:\nData ingestion and processing\nForced oscillation detection\nEvent tracking\nResult writing\nAmbient oscillation baselining\nSpectral analysis and event detection\nDominant mode identification\nResult writing\nData ingestion involves reading PMU data from CSV files, concatenating it, and applying standard signal processing\ntechniques to prepare the data for analysis.\nThe forced oscillation detection portion of the tool examines the data for evidence of a particular dynamic phenomenon in\npower systems known as forced oscillations. It is implemented with a periodogram-based method that was developed at\nPNNL. Forced oscillation events are tracked across time. Results are written to CSV files.\nThe ambient oscillation baselining portion of the tool is based on the Robust Modified Daniell-Welch (RMDW) spectral\nestimator, which was developed at PNNL. It produces estimates of the signal's ambient spectrum while detecting large\npower system events. The ambient spectrum is analyzed to identify the most observable (dominant) mode frequency. At\nthe end of each day, the tool applies the k-means clustering algorithm to distinguish between dominant system modes.\nResults are written to CSV files.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "Eastern Interconnection Situational Awareness Monitoring System (ESAMS) Oscillation Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/EasyBO.json b/agency-indexes/DoE/EasyBO.json new file mode 100644 index 00000000..7c8a10be --- /dev/null +++ b/agency-indexes/DoE/EasyBO.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "mcarbone@bnl.gov" + }, + "date": { + "created": "2022-10-12", + "metadataLastUpdated": "2022-12-07" + }, + "description": "All things Gaussian Process and Bayesian optimization, made easy", + "laborHours": 0.0, + "languages": [], + "name": "EasyBO", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/matthewcarbone/EasyBO", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EchemAMR__electro-chemical_microsctructure_scale_models_with_adaptive_meshing__[SWR-23-111].json b/agency-indexes/DoE/EchemAMR__electro-chemical_microsctructure_scale_models_with_adaptive_meshing__[SWR-23-111].json new file mode 100644 index 00000000..242ecd03 --- /dev/null +++ b/agency-indexes/DoE/EchemAMR__electro-chemical_microsctructure_scale_models_with_adaptive_meshing__[SWR-23-111].json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-07-15", + "metadataLastUpdated": "2024-08-26" + }, + "description": "A 3D microstructure resolving electrochemical transport and interfacial chemistry solver. \n\nElectrode microstructure plays an important role in determining the performance of an electrochemical system, e.g. lithium ion battery. EchemAMR is a microstructure scale model that solves the governing equations for ion transport, electrical current continuity, interfacial chemistry and structural mechanics. Complex microstructure geometries from imaging can be directly imported into EchemAMR. A volume fraction based description of the geometry on Cartesian grid with an immersed interface formulation enables simplified meshing and large-scale simulations with millions of degrees of freedom. EchemAMR has been tested against systems with analytic solutions for numerical convergence and highly resolved lithium ion battery microstructures. EchemAMR demonstrates excellent mass conversation and efficient scaling on heterogenous High-Performance Computing (HPC) with central and graphics processing units.", + "laborHours": 8253.6, + "languages": [ + "C++", + "HTML", + "C", + "Jupyter Notebook", + "MATLAB", + "Python" + ], + "name": "EchemAMR (electro-chemical microsctructure scale models with adaptive meshing) [SWR-23-111]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/echemAMR", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Eclipse_Parallel_Tools_Platform.json b/agency-indexes/DoE/Eclipse_Parallel_Tools_Platform.json new file mode 100644 index 00000000..4fb7b0fe --- /dev/null +++ b/agency-indexes/DoE/Eclipse_Parallel_Tools_Platform.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "watsongr@ornl.gov" + }, + "date": { + "created": "2017-11-15", + "metadataLastUpdated": "2020-08-12" + }, + "description": "The PTP project provides an integrated development environment to support the development of parallel applications written in C, C++, and Fortran. This include support for the MPI, OpenMP and UPC programming models, as well as OpenSHMEM and OpenACC, support for a wide range of batch systems and runtime systems, including PBS/Torque, LoadLeveler, GridEngine, Parallel Environment, Open MPI, and MPICH2. A scalable parallel debugger and support for the integration of a wide range of parallel tools is also included.", + "homepageURL": "https://git.eclipse.org/c/ptp/org.eclipse.ptp.git", + "laborHours": 548841.6, + "languages": [], + "name": "Eclipse Parallel Tools Platform", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.eclipse.org/c/ptp/org.eclipse.ptp.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Eddy_covariance_towers_as_sentinels_of_abnormal_radioactive_material_releases.json b/agency-indexes/DoE/Eddy_covariance_towers_as_sentinels_of_abnormal_radioactive_material_releases.json new file mode 100644 index 00000000..ade4cf38 --- /dev/null +++ b/agency-indexes/DoE/Eddy_covariance_towers_as_sentinels_of_abnormal_radioactive_material_releases.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2025-01-08" + }, + "description": "Ensuring accurate detection and attribution of abnormal releases of radioactive material is critical for protecting human health and safety. Most commonly, such detection is accomplished via active monitoring approaches involving the collection of physical samples. This is labor intensive and limits the temporal and spatial resolution of any detected events to a relatively coarse level. As an alternative first step towards passive monitoring, we developed an approach using eddy flux tower data records to identify signals from a known abnormal release and quantify the extent to which that signal also occurs at other times in the data record. Through two case-studies, one of which targeted the Fukushima nuclear disaster and the other targeting an abnormal release event at a radioisotope production facility in Fleurus Belgium, we tested our approach and identified several potential heretofore unidentified abnormal releases that were consistent with atmospheric circulation patterns and/or wind direction from known release sites. Because our approach is relatively simple and is resistant to systematic errors in the observational record, it has broad applicability beyond specific constituents and ecosystem types to identify a wide variety of limited-duration anomalies in flux tower data to ensure human health and industrial safety.", + "laborHours": 2872.8, + "languages": [], + "name": "Eddy covariance towers as sentinels of abnormal radioactive material releases", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/fluxnet-sentinels", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Edge_Bioinformatics.json b/agency-indexes/DoE/Edge_Bioinformatics.json new file mode 100644 index 00000000..ca51f7fa --- /dev/null +++ b/agency-indexes/DoE/Edge_Bioinformatics.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Edge Bioinformatics is a developmental bioinformatics and data management platform which seeks to supply laboratories with bioinformatics pipelines for analyzing data associated with common samples case goals. Edge Bioinformatics enables sequencing as a solution and forward-deployed situations where human-resources, space, bandwidth, and time are limited. The Edge bioinformatics pipeline was designed based on following USE CASES and specific to illumina sequencing reads. 1. Assay performance adjudication (PCR): Analysis of an existing PCR assay in a genomic context, and automated design of a new assay to resolve conflicting results; 2. Clinical presentation with extreme symptoms: Characterization of a known pathogen or co-infection with a. Novel emerging disease outbreak or b. Environmental surveillance", + "laborHours": 155587.2, + "name": "Edge Bioinformatics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/edge", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EditorApps.json b/agency-indexes/DoE/EditorApps.json new file mode 100644 index 00000000..f75b78cc --- /dev/null +++ b/agency-indexes/DoE/EditorApps.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "Repository for specifications for Narrative Editor Apps.", + "laborHours": 592.8, + "languages": [], + "name": "EditorApps", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/EditorApps", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Efficent_XAI_Information_Saliency_Tool.json b/agency-indexes/DoE/Efficent_XAI_Information_Saliency_Tool.json new file mode 100644 index 00000000..4756bb93 --- /dev/null +++ b/agency-indexes/DoE/Efficent_XAI_Information_Saliency_Tool.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2020-05-13" + }, + "description": "This software is an implementation which is described in: \"Efficient Saliency Maps for Explainable AI\"\n(https://openreview.net/forum?id=ryxf9CEKDr). The toolkit is located in:\nhttps://mybitbucket.llnl.gov/projects/SAL/repos/smoe_lovi/browse. It is a set of of PyTorch related python\nscripts for extracting the what parts of an image are most salient to a deep neural network in an efficient\nmanner. This source will allow one to replicate the results in the paper referenced above.\nIs there", + "laborHours": 1170.4, + "languages": [], + "name": "Efficent XAI Information Saliency Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/fastcam", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Efficient_Algorithms_for_Parallel_Bi-core_Decomposition.json b/agency-indexes/DoE/Efficient_Algorithms_for_Parallel_Bi-core_Decomposition.json new file mode 100644 index 00000000..e5a8c66b --- /dev/null +++ b/agency-indexes/DoE/Efficient_Algorithms_for_Parallel_Bi-core_Decomposition.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper:\n\nYihao Huang, Claire Wang, Jessica Shi, and Julian Shun.\nEfficient Algorithms for Parallel Bi-core Decomposition.\nProceedings of the SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS), pp. 17-32, 2023.", + "laborHours": 0.0, + "languages": [], + "name": "Efficient Algorithms for Parallel Bi-core Decomposition", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/clairebookworm/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Efficient_training_of_physics-informed_neural_networks.json b/agency-indexes/DoE/Efficient_training_of_physics-informed_neural_networks.json new file mode 100644 index 00000000..5ef2fe7b --- /dev/null +++ b/agency-indexes/DoE/Efficient_training_of_physics-informed_neural_networks.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-17", + "metadataLastUpdated": "2025-01-08" + }, + "description": "Open-source software package designed for the efficient training of Physics-Informed Neural Networks\n(PINNs) and their variants, integrating advanced methodologies such as adaptive weighting and adaptive sampling", + "laborHours": 3192.0, + "languages": [], + "name": "Efficient training of physics-informed neural networks", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ET-PINN", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Egret_v._0.1__beta_.json b/agency-indexes/DoE/Egret_v._0.1__beta_.json new file mode 100644 index 00000000..b6c9415c --- /dev/null +++ b/agency-indexes/DoE/Egret_v._0.1__beta_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-11", + "metadataLastUpdated": "2019-03-12" + }, + "description": "Egret is a package that provides tools for building electric grid optimization models. This software includes objects and functions for parsing, storing, and managing electric grid data. Egret also includes the following electric grid models:\n- ACOPF (alternating current optimal power flow)\n- DCOPF \u2013 a linearized transmission model\n- ACOPF relaxations\n- Unit commitment\n- Economic dispatch", + "laborHours": 7174.4, + "languages": [ + "Python" + ], + "name": "Egret v. 0.1 (beta)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/grid-parity-exchange/Egret", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.1 (beta)" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ejoin.json b/agency-indexes/DoE/Ejoin.json new file mode 100644 index 00000000..e4c57107 --- /dev/null +++ b/agency-indexes/DoE/Ejoin.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "ejoin is a three-dimensional mesh combination program. ejoin combines two or more meshes written in the exodusII mesh database format into a single exodusII mesh. Selected nodes in the wo meshes that are closer than a specified distance can be combined The geometry of the mesh databases an be modified by offsetting. Any results data on one or more of the input mesh files will be copied to the appropriate nodes/elements/nodesets/sidesets on the output file.Preparation of input mesh files for finite element analysis programs using the exodusII format.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "Ejoin", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Elastic_Stacker.json b/agency-indexes/DoE/Elastic_Stacker.json new file mode 100644 index 00000000..255c8998 --- /dev/null +++ b/agency-indexes/DoE/Elastic_Stacker.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-21", + "metadataLastUpdated": "2023-06-21" + }, + "description": "Stacker is a library and command-line tool for interacting with components of the Elastic Stack remotely\nusing their APIs. For example, Stacker allows the user to persist API resources to disk and re-create them\nusing the same APIs, potentially allowing configuration to be kept in sync across multiple Elastic Stack\ninstances.", + "laborHours": 0.0, + "languages": [], + "name": "Elastic Stacker", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/elastic-stacker", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Electric_Grid_Simulator_For_Human_Factor_Research.json b/agency-indexes/DoE/Electric_Grid_Simulator_For_Human_Factor_Research.json new file mode 100644 index 00000000..0f8237b1 --- /dev/null +++ b/agency-indexes/DoE/Electric_Grid_Simulator_For_Human_Factor_Research.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-02-18", + "metadataLastUpdated": "2025-02-18" + }, + "description": "The developed code simulates real-time monitor and control for west area of IEEE 118-bus system. The 24-hour load profile for each bus is derived by scaling the system\u2019s rated load in the PSSE sav file according to the California Independent System Operator\u2019s Day-ahead load forecast for May 1, 2024. This simulator performs several critical functions: (1) Calculating time-series power flow every 4 seconds; (2) Updating and dispatching AGC signals every minute; (3) Conducting N-1 contingency analysis every 5 minutes. Additionally, the simulator can trip lines and subsequently update and dispatch AGC signals, running power flow analysis after each tripping event.", + "laborHours": 197.6, + "languages": [ + "Python" + ], + "name": "Electric Grid Simulator For Human Factor Research", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/PSSE_for_Human_factor_research", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Electric_System_Intra-hour_Operation_Simulator.json b/agency-indexes/DoE/Electric_System_Intra-hour_Operation_Simulator.json new file mode 100644 index 00000000..754a1a04 --- /dev/null +++ b/agency-indexes/DoE/Electric_System_Intra-hour_Operation_Simulator.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "ESIOS is a software program developed at Pacific Northwest National Laboratory (PNNL) that performs intra-hour dispatch and automatic generation control (AGC) simulations for electric power system frequency regulation and load/variable generation following. The program dispatches generation resources at minute interval to meet control performance requirements, while incorporating stochastic models of forecast errors and variability with generation, load, interchange and market behaviors. The simulator also contains an operator model that mimics manual actions to adjust resource dispatch and maintain system reserves. Besides simulating generation fleet intra-hour dispatch, ESIOS can also be used as a test platform for the design and verification of energy storage, demand response, and other technologies helping to accommodate variable generation.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Python, Java" + ], + "name": "Electric System Intra-hour Operation Simulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Electricity_Bill_Calculator__elecprice__v0.1.0.json b/agency-indexes/DoE/Electricity_Bill_Calculator__elecprice__v0.1.0.json new file mode 100644 index 00000000..8c16d75f --- /dev/null +++ b/agency-indexes/DoE/Electricity_Bill_Calculator__elecprice__v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-14" + }, + "description": "The Electricity Bill Calculator Library is a generic tool for manipulating the tariffs of electricity, with an emphasis on commercial Time-Of-Use (TOU) rates in the U.S. and residential Net Energy Metering tariffs in CA. Typical uses of the package are price signal generation and bill computation. To generate price signals from a specific tariff and given a time window, the tool creates a pandas dataframes containing the various components of the electricity charges, at each time step. This is particularly useful for Demand Response (DR) applications, such as price-based optimization of energy in buildings. The tool also computes bills given a building's power consumption and a specific tariff and returning the corresponding cost of electricity, as well as a breakdown per type of rate.", + "laborHours": 0.0, + "languages": [], + "name": "Electricity Bill Calculator (elecprice) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/elecprice", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Electrode_Cage_for_Hydrogen_Production.json b/agency-indexes/DoE/Electrode_Cage_for_Hydrogen_Production.json new file mode 100644 index 00000000..fcfdbfea --- /dev/null +++ b/agency-indexes/DoE/Electrode_Cage_for_Hydrogen_Production.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-06-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "3D design documents for 3D printing. The holes in the electrode cage are designed to condense hydrogen into progressively larger\nbubbles, and to direct the flow of hydrogen from the cathode up and out of the bioreactor so it is kept away from the anode\nand collected as nearly pure hydrogen.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Electrode Cage for Hydrogen Production", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Electron-phonon_dynamics_for_LAMMPS_.json b/agency-indexes/DoE/Electron-phonon_dynamics_for_LAMMPS_.json new file mode 100644 index 00000000..b4b7dd0b --- /dev/null +++ b/agency-indexes/DoE/Electron-phonon_dynamics_for_LAMMPS_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-20" + }, + "description": "4.Brief Description:\nThis is a LAMMPS extension (LAMMPS \"fix\") to capture electron-ion interaction. We use this extension mechanism to generalize the two\u00ad\ntemperature model to include electron-phonon coupling. The extension is flexible enough to represent cascades, laser heating and equilibration and study energy transport with realistic electron-phonon coupling. ", + "laborHours": 1444.0, + "languages": [], + "name": "Electron-phonon dynamics for LAMMPS ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/USER-EPH", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Electron_Beam_Longitudinal_Tracking__EBLT__v1.0.json b/agency-indexes/DoE/Electron_Beam_Longitudinal_Tracking__EBLT__v1.0.json new file mode 100644 index 00000000..09a66f29 --- /dev/null +++ b/agency-indexes/DoE/Electron_Beam_Longitudinal_Tracking__EBLT__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-25", + "metadataLastUpdated": "2024-06-25" + }, + "description": "It is a serial/parallel code for fast electron beam longitudinal\nforward or backward tracking through an electron linear accelerator.\n\nThis codes includes longitudinal space-charge effect, structure\nand resistive wall wakefields, and longitudinal coherent synchrotron radiation effect.\n\nTo use it as a parallel code, please comment out the \"use mpistub\" in BeamBunch.f90, rename mpif.h as mpif.hh,\nand use the Makefile_parallel as Makefile.", + "laborHours": 942.4, + "languages": [], + "name": "Electron Beam Longitudinal Tracking (EBLT) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qianglbl/EBLT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Electronic_Structure_Engine.json b/agency-indexes/DoE/Electronic_Structure_Engine.json new file mode 100644 index 00000000..c286d032 --- /dev/null +++ b/agency-indexes/DoE/Electronic_Structure_Engine.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "INQ is an engine for electronic structure calculations. INQ is implemented as a C++ library of components\ndesigned to build a parallel, portable code for electronic structure calculations, including ground state and\nexcited states. INQ is based on density functional theory (DFT). It can calculate ground state properties in\nDFT, and also excited states using time-dependent DFT (TDDFT) in real-time and linear-response. It\nimplements different approximations for the exchange and correlation part: semi-local functionals like\nLDAs, GGAs and metaGGAs, and hybrid functionals that are implemented through the ACE approach for\nfast execution.", + "laborHours": 92644.0, + "languages": [], + "name": "Electronic Structure Engine", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/inq", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Electrostatics_apbs-rest.json b/agency-indexes/DoE/Electrostatics_apbs-rest.json new file mode 100644 index 00000000..02f53b6f --- /dev/null +++ b/agency-indexes/DoE/Electrostatics_apbs-rest.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Web server and RESTful backend services for APBS and PDB2PQR\nThis software was developed to deploy APBS (https://github.com/Electrostatics/apbs) and PDB2PQR\n(https://github.com/Electrostatics/pdb2pqr) on Azure to address a gap left by the closing of the previous hosting service at\nUCSD", + "laborHours": 0.0, + "languages": [], + "name": "Electrostatics/apbs-rest", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://creativecommons.org/publicdomain/zero/1.0", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electrostatics/apbs-rest", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Electrostatics_go2pdb.json b/agency-indexes/DoE/Electrostatics_go2pdb.json new file mode 100644 index 00000000..e84397da --- /dev/null +++ b/agency-indexes/DoE/Electrostatics_go2pdb.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-03-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Extract PDB entries annotated with specific GO codes", + "laborHours": 0.0, + "languages": [], + "name": "Electrostatics/go2pdb", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electrostatics/go2pdb", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Elga_v.1.json b/agency-indexes/DoE/Elga_v.1.json new file mode 100644 index 00000000..4ec66b4b --- /dev/null +++ b/agency-indexes/DoE/Elga_v.1.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SAND2021-4635 O Elga is a software system that provides distributed and elastic computation for temporal graph algorithms. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 4073.6, + "languages": [ + "Dockerfile", + "C++", + "Shell", + "CMake", + "Python" + ], + "name": "Elga v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GT-TDAlab/ElGA/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Elga", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Empirical_Roofline_Tool__ERT__v1.1.0.json b/agency-indexes/DoE/Empirical_Roofline_Tool__ERT__v1.1.0.json new file mode 100644 index 00000000..0ab7c3b8 --- /dev/null +++ b/agency-indexes/DoE/Empirical_Roofline_Tool__ERT__v1.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-04-23", + "metadataLastUpdated": "2021-06-15" + }, + "description": "The Empirical Roofline Tool (ERT) empirically determines the machine characteristics (CPU or GPU-accelerated) that are needed to generate the machine characteristics for the roofline model.", + "laborHours": 0.0, + "languages": [], + "name": "Empirical Roofline Tool (ERT) v1.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/cs-roofline-toolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "version": "v1.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Emu_v1.1.json b/agency-indexes/DoE/Emu_v1.1.json new file mode 100644 index 00000000..da7ec34a --- /dev/null +++ b/agency-indexes/DoE/Emu_v1.1.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-25", + "metadataLastUpdated": "2021-03-31" + }, + "description": "Emu is a particle-in-cell code for solving the neutrino quantum kinetic equations in 1, 2, or 3 spatial dimensions with arbitrary angular resolution in order to simulate neutrino flavor transformation in neutron star merger and core collapse supernova environments. Emu represents the neutrino distribution function as a set of particles, each of which represent a collection of neutrinos and antineutrinos with unique position and momentum. Each particle carries two density matrices to define the flavor state of the neutrinos and antineutrinos it represents. Emu includes the vacuum, matter, and neutrino self-interaction potentials. Emu calculates the self-interaction potential using PIC deposition and interpolation algorithms that efficiently compute the local number density and flux at particle locations. Emu is implemented in C++ and is based on the AMReX library for high-performance, block-structured adaptive mesh refinement. Emu is parallelized with MPI + OpenMP for CPUs and MPI + CUDA for GPUs.", + "laborHours": 0.0, + "languages": [], + "name": "Emu v1.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Astro/Emu", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Emulator_Generation_Gadget.json b/agency-indexes/DoE/Emulator_Generation_Gadget.json new file mode 100644 index 00000000..706baa75 --- /dev/null +++ b/agency-indexes/DoE/Emulator_Generation_Gadget.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-04-19", + "metadataLastUpdated": "2018-04-19" + }, + "description": "This software automates the production of standalone emulators for complex computer models. The end result of running the software is a piece of code called an emulator, a statistical approximation which predicts the output of complex computer simulation, but at a much faster speed. The emulator is built using a training set of inputs and outputs from the simulations. The input-output pairs are used in a Bayesian scheme to estimate the parameters of a Gaussian process based regression model that learns the input-output relationship. The estimated parameters are combined with a generic C skeleton to produce a compile-able instantiation of the emulator.", + "laborHours": 1854.4, + "name": "Emulator Generation Gadget", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/EGG", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EnGAGE.json b/agency-indexes/DoE/EnGAGE.json new file mode 100644 index 00000000..1d5ad5e9 --- /dev/null +++ b/agency-indexes/DoE/EnGAGE.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-09-04", + "metadataLastUpdated": "2020-09-18" + }, + "description": "EnGAGE is a tool that enables complex queries of geospatial-temporal data. Disparate data sources are loaded into a geospatial-temporal semantic graph, where nodes have positions and times, and edges represent relationships between the nodes. Analysts can then design complex search templates to apply to the semantic graph, resulting in a set of matches. SAND2019-11999 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of ", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "EnGAGE", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v.2.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Enabling_the_democratization_of_the_genomics_revolution_with_a_fully_integrated_web-based_bioinformatics_platform,_Version_1.5_and_1.x..json b/agency-indexes/DoE/Enabling_the_democratization_of_the_genomics_revolution_with_a_fully_integrated_web-based_bioinformatics_platform,_Version_1.5_and_1.x..json new file mode 100644 index 00000000..e4558c5d --- /dev/null +++ b/agency-indexes/DoE/Enabling_the_democratization_of_the_genomics_revolution_with_a_fully_integrated_web-based_bioinformatics_platform,_Version_1.5_and_1.x..json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "EDGE bioinformatics was developed to help biologists process Next Generation Sequencing data (in the form of raw FASTQ files), even if they have little to no bioinformatics expertise. EDGE is a highly integrated and interactive web-based platform that is capable of running many of the standard analyses that biologists require for viral, bacterial/archaeal, and metagenomic samples. EDGE provides the following analytical workflows: quality trimming and host removal, assembly and annotation, comparisons against known references, taxonomy classification of reads and contigs, whole genome SNP-based phylogenetic analysis, and PCR analysis. EDGE provides an intuitive web-based interface for user input, allows users to visualize and interact with selected results (e.g. JBrowse genome browser), and generates a final detailed PDF report. Results in the form of tables, text files, graphic files, and PDFs can be downloaded. A user management system allows tracking of an individual\u2019s EDGE runs, along with the ability to share, post publicly, delete, or archive their results.", + "laborHours": 155587.2, + "name": "Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform, Version 1.5 and 1.x.", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Bioinformatics/EDGE.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Encoding_Initial_Solutions_using_the_HGain_feature_on_D-Wave_Quantum_Annealers.json b/agency-indexes/DoE/Encoding_Initial_Solutions_using_the_HGain_feature_on_D-Wave_Quantum_Annealers.json new file mode 100644 index 00000000..2e473598 --- /dev/null +++ b/agency-indexes/DoE/Encoding_Initial_Solutions_using_the_HGain_feature_on_D-Wave_Quantum_Annealers.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "We developed software which finds HGain schedules that can be used to encode initial solutions into a quantum annealer in a similar manner to the reveres annealing feature on the D-Wave 2000Q. With the newer generations of the D-Wave annealer, more advanced features are available which allow the user to have greater control of the anneal process. We study how such features can help in improving the quality of the solutions returned by the annealer. Specifically, we focus on two of these features: reverse annealing and h-gain. Reverse annealing (RA) was designed to allow refining a known solution by backward annealing from a classical state representing the solution to a mid-anneal point where a transverse field is present, followed by an ordinary forward anneal, which is hoped to improve on the previous solution.The h-gain (HG) feature stands for time-dependent gain in Hamiltonian linear ($h$) biases and was originally developed to help study freezeout times and phase transitions in spin glasses. Here we apply HG to bias the quantum state in the beginning of the annealing process towards the known solution as in the RA case, but using a different apparatus. We also investigate a hybrid reverse annealing/h-gain schedule, which has a backward phase resembling an RA step and whose forward phase uses the HG idea. To optimize the parameters of the schedules, we employ a Bayesian optimization framework. We test all techniques on a variety of input problems including the weighted Maximum Cut problem and the weighted Maximum Clique problem. Our results show that each technique may dominate the others depending on the input instance, and that the HG technique is a viable alternative to RA for some problems.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Encoding Initial Solutions using the HGain feature on D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/EnergyPlus.json b/agency-indexes/DoE/EnergyPlus.json new file mode 100644 index 00000000..11606629 --- /dev/null +++ b/agency-indexes/DoE/EnergyPlus.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "EnergyPlus(TM) is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption - for heating, cooling, ventilation, lighting and plus and process loads - and water use in buildings.", + "laborHours": 2335920.8, + "name": "EnergyPlus", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/EnergyPlus/blob/develop/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlus", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EnergyPlus_Version_7.json b/agency-indexes/DoE/EnergyPlus_Version_7.json new file mode 100644 index 00000000..f799b8c2 --- /dev/null +++ b/agency-indexes/DoE/EnergyPlus_Version_7.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "EnergyPlus is a whole building energy simulation program that engineers, architects and researchers use to model energy and water use in buildings. Modeling the performance of a building with EnergyPlus enables building professionals to optimize the building design to use less energy and water. Each version of EnergyPlus is tested extensively before release. EnergyPlus models heating, cooling, lighting, ventilation, other energy flows, and water use. EnergyPlus includes many innovation simulation capabilities: time-steps less than an hour, modular systems and plant integrated with heat balance-based zone simulation, multizone air flow, thermal comfort, water use, natural ventilation, and photovoltaic systems. EnergyPlus runs on the Windows, Macintosh, and Linux platforms. Free add-ons and other third party software products are available for use with EnergyPlus.", + "laborHours": 0.0, + "languages": [ + "Intel Fortran V11" + ], + "name": "EnergyPlus Version 7", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://energyplus.net/licensing", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlusRelease/releases/tag/7.0.0.036", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "7.0.0.036" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/EnergyPlus\302\256_Regression_Tool__EPRT_.json" "b/agency-indexes/DoE/EnergyPlus\302\256_Regression_Tool__EPRT_.json" new file mode 100644 index 00000000..0957adf2 --- /dev/null +++ "b/agency-indexes/DoE/EnergyPlus\302\256_Regression_Tool__EPRT_.json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-08-14", + "metadataLastUpdated": "2019-08-15" + }, + "description": "A Python library and GUI for doing comparisons of EnergyPlus\u00ae builds. EPRT is almost exclusively a developer tool for members of the EnergyPlus\u00ae development team to ensure that code changes are not impacting the test suite.", + "laborHours": 16856.8, + "languages": [ + "Python" + ], + "name": "EnergyPlus\u00ae Regression Tool (EPRT)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlusRegressionTool", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/EnergyPlus\342\204\242__SWR-17-23_.json" "b/agency-indexes/DoE/EnergyPlus\342\204\242__SWR-17-23_.json" new file mode 100644 index 00000000..56c4b97f --- /dev/null +++ "b/agency-indexes/DoE/EnergyPlus\342\204\242__SWR-17-23_.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-02-27" + }, + "description": "Originally developed in 1999, an updated version 8.8.0 with bug fixes was released on September 30th, 2017. EnergyPlus\u2122 is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption\u2014for heating, cooling, ventilation, lighting and plug and process loads\u2014and water use in buildings. EnergyPlus is a console-based program that reads input and writes output to text files. It ships with a number of utilities including IDF-Editor for creating input files using a simple spreadsheet-like interface, EP-Launch for managing input and output files and performing batch simulations, and EP-Compare for graphically comparing the results of two or more simulations. Several comprehensive graphical interfaces for EnergyPlus are also available. DOE does most of its work with EnergyPlus using the OpenStudio\u00ae software development kit and suite of applications. DOE releases major updates to EnergyPlus twice annually.", + "laborHours": 2335920.8, + "languages": [], + "name": "EnergyPlus\u2122 (SWR-17-23)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/EnergyPlus/blob/develop/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlus", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/EnergyPlus\342\204\242_v.23.2.0_2023_[SWR-17-23].json" "b/agency-indexes/DoE/EnergyPlus\342\204\242_v.23.2.0_2023_[SWR-17-23].json" new file mode 100644 index 00000000..6a56e4e9 --- /dev/null +++ "b/agency-indexes/DoE/EnergyPlus\342\204\242_v.23.2.0_2023_[SWR-17-23].json" @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-02-27", + "metadataLastUpdated": "2024-06-05" + }, + "description": "EnergyPlus\u2122 is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption and water use in buildings.\n\nThis is the EnergyPlus Development Repository.\n\nThe Department of Energy maintains a public website for EnergyPlus where you can find much more information about the program. https://energyplus.net/\n\nFor detailed developer information, consult the wiki. https://github.com/NREL/EnergyPlus/wiki\n\nMany users (and developers) of EnergyPlus are active on Unmet Hours, so that's a great place to start if you have a question about EnergyPlus or building simulation. https://unmethours.com/questions/\n\nFor more in-depth, developer-driven support, please utilize the EnergyPlus Helpdesk. https://energyplushelp.freshdesk.com/support/home", + "laborHours": 2335920.8, + "languages": [ + "C++", + "Fortran", + "Python", + "Jupyter Notebook", + "Visual Basic 6.0", + "CMake" + ], + "name": "EnergyPlus\u2122 v.23.2.0 2023 [SWR-17-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/EnergyPlus?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyPlus", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "23.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.0.json b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.0.json new file mode 100644 index 00000000..d52012f2 --- /dev/null +++ b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2020-08-25" + }, + "description": "\nE3SM is a state-of-the-art fully coupled model of the Earth's climate including important biogeochemical and cryospheric processes. It is intended to address the most challenging and demanding climate-change research problems and DOE mission needs while efficiently using DOE Leadership Computing Facilities. ", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v1.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v1.0.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.1.1.json b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.1.1.json new file mode 100644 index 00000000..0d9f34e0 --- /dev/null +++ b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.1.1.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2020-08-25", + "metadataLastUpdated": "2020-08-25" + }, + "description": "Second release of E3SM v1.1\n\nThis update to v1.1.0 includes additional output variables and small changes to the\nECA configurations. In particular, the following changes/additions are included:\n\nELM: add new diagnostic variables, Add diagnostic CNP flux from plant to CWD,\nUpdate land use case file for CBGC 20TR compsets, Update the constant CO2\noverride value to be CMIP6-compliant\n\nall: fix bug preventing reading of v1.0 restarts, update BGC compset names in tests,\nadd short names for ECA compsets with ocean BGC off, Change the names of PI control\ncases to use the string \"CNTL\", Fix 20th-century transient BGC use case specification\n\nThis tag is used for the E3SM v1 BGC simulations using the ECA biogeochemistry configuration.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v1.1.1", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v1.1.1", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v1.1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.1.json b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.1.json new file mode 100644 index 00000000..1065afe3 --- /dev/null +++ b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.1.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2020-08-25", + "metadataLastUpdated": "2020-08-25" + }, + "description": "First release of E3SM v1.1\n\nThis release includes scientifically-validated tunings of the E3SM Land Model (ELM) and E3SM Atmosphere Model (EAM) for coupled simulations with active land, ocean, and sea ice biogeochemistry, for ELM configurations using the CTC approach to representing nutrient competition.\n\nAdditional diagnostic variables have been made available as history variables from the ELM,\nand from the MPAS-Ocean and MPAS-Seaice biogeochemistry modules, in order to improve consistency with the output variable requests of the Coupled Climate Carbon Cycle Model Intercomparison\nProject (C4MIP), and to support improved analysis of the land, ocean, and sea ice carbon cycles.\n\nThe atmosphere models prognostic CO2 code has been updated to enable regridding of anthropogenic\nCO2 emission files to the E3SMs native spectral element grid. Note that (1) the prognostic CO2\nconfiguration of E3SM has not been scientifically validated, and (2) the regridding of emission\nfiles as currently implemented is not mass-conserving and is intended as a temporary workaround.\nWe do not advise using E3SMv1.1 for fully-coupled carbon cycle simulations where mass conservation\nis critical, but it is suitable for enabling use of the 3D CO2 tracer for diagnostic and testing purposes.\n\nSeveral bugs found after v1.0 have been fixed in this tag and changes made to default settings, including:\n EAM: adding limiters to avoid bad extrapolation in RRTMG, fixing an error in the calculation of NIR\n reflectance that affects cloud fields derived from MODIS simulator.\n ELM: fixing surface water and lakes, increasing the land field name size, fixing a memory leak in\n ELM CNStateType, fixing a snow compaction bug that was resulting in sporadic unphysical snow depths,\n adding a water budget in the land model (and fixing a water conservation error)\n MPAS-O: preventing thermo energy conservation errors by lowering the permitted surface flux error\n in the mushy layer picard iteration to 0.9*ferrmax, fixing a small bug in marine BGC,\n MPAS-SeaIce: Turning off mpas-seaice history files by default\n MOSART: Replacing the low-res (half-degree) MOSART file\n\nIn addition, the budget output has been turned on by default for any fully coupled case, and CIME was\nmodified to remove a bad term from E3SM water budgets. The CCSM_CO2_PPMV is now set correctly in BGC cases. A bugfix for the IEFLX output is included and the timestep for the EC60to30 mesh has been\nupdated. Finally, a number of minor bugfixes and technical improvements have been introduced in the\nEAM, ELM and MPAS-Ocean models.\n\nMachine updates for cascade, edison, eos, cori are included.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v1.1", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v1.1.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v1.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.2.0.json b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.2.0.json new file mode 100644 index 00000000..6ec3066e --- /dev/null +++ b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.2.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2021-03-08", + "metadataLastUpdated": "2021-03-09" + }, + "description": "v1.2.0 used for v1 Cryosphere Science Campaign\n\nThis release is on the maint-1.2 branch which was branched from master on Feb 25, 2019 (7a3e32d6a), and is the code base for the Cryosphere Science Campaign\nv1 simulations. This includes modified v1 versions of the atmosphere (EAM), land model (ELM), ocean (MPAS-Ocean), sea ice (MPAS-Seaice), and land ice (MALI). A key feature of the E3SM v1 Cryosphere simulations is the inclusion of Antarctic ice shelf cavities in the ocean domain. This allows the calculation of ice shelf basal melt rates, with a static ice shelf geometry. Another distinction between standard E3SM configurations and Cryosphere configurations is the inclusion of prescribed iceberg fluxes (using gridded monthly climatology data from Merino et al 2016). To account for the explicit representation of Antarctic mass fluxes to the ocean through prognostic basal melting and prescribed icebergs, standard representations of runoff from Antarctica, both solid and liquid, are disabled.\n\nDifferences from v1.0 DECK simulations include all of those listed in the v1.1.0-beta tag. Additional differences from the v1.1 BGC simulations are listed in the v1.2.0-beta tag.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v1.2.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v1.2.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v1.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.2.1.json b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.2.1.json new file mode 100644 index 00000000..8807ac2a --- /dev/null +++ b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.2.1.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2021-03-09", + "metadataLastUpdated": "2021-03-09" + }, + "description": "v1.2.1 with 3D GM in ocean used for v1 Cryosphere campaign\n\nThis update to v1.2.0 does the following: Add ne30_oARRM60to10 grid resolution. Add options for 3D varying GM bolus and 2d varying phase speed, Add GM bolus eddy stats, turn 3DGM on by default, add 3DGM namelist options, compute landIceMask using geometric_features, bug fixes for nonlocal source term in KPP, change all output to single precision and fix threading issue in GM.\n\nUpdate machine files on cori, anvil, and LANL machines.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v1.2.1", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v1.2.1", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v1.2.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.3.json b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.3.json new file mode 100644 index 00000000..f306d1d5 --- /dev/null +++ b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v1.3.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "This version used only for additional G-cases in the v1 Cryosphere campaign. MPAS-Ocean: Update MPAS-source to GM varying, add namelist options for 3D varying GM bolus Kappa Flags are added to enable the 3D varying GM bolus Kappa, it is enabled by default and is on whenever the GM parameterization is on. Output of kappaGM3D and the phase speed are added to monthly history as well Differences from v1.2 simulations include above and all of those listed in the v1.3.0-beta tag.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v1.3", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v1.3.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v1.3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v2.0.1.json b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v2.0.1.json new file mode 100644 index 00000000..55d8060e --- /dev/null +++ b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v2.0.1.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2022-11-16", + "metadataLastUpdated": "2022-11-16" + }, + "description": "First patch release of v2.0.0 Changes since v2.0.0 [Important change] Fix ocean threading bug seen in debug cases on Chrysalis with Intel 20.0.4. Was introduced around time of v2.0.0 tag. Does not change v2.0.0 answers on Chrysalis because those didn't use threading or debugging. [EAM] Add semi-lagrangian tracer transport for theta-l (F90 and C++), add new algorithm for finding tropopause, add DSCREAM to allow v2 and SCREAM settings in same code such as adjust_ps [EAM-MMF] 60L default, allow C++ back end of RRTMGP (EAM too). [EAMxx] add nu-top functionality, fix forcing functor, add ttype9 and dcmip2012 tests 2.1, 2.2, and 3 HOMME: remove obsolete remap algs, option to specify dynamics alg indep of tracer, new sponge layer, add imex tests [ELM] Add topography-based subgrid (topounits), add FATES-ELM Nitro., Phos. and CH4 coupling, add land-use ts for NARRM, add lulc for SSP3 RCP7, Fix nutrient fertilization exp test and carbon isotope flux, Fix xactive lnd dry deposition, add lake water storage option, fix plant hydraulics 2d params, fix carbon budget calc, fix soil nutrient conc. bug, fix mosart dam bug, add test for new ELM, MOSART features, fix bug in O3 dry dep stomatal resistances, fix plant hydraulics restart BFB error, update mkmapdata. [MOSART] fix bug for reading the latitude from an unstructured input file, fix oversat in bubble test. [MPAS-ocean] Add CFC11, CFC12 tracers, add 2D spherical transport tests, fix del4 tracer mixing, add MARBL ocean tracer mixing, modify harmonic analysis options, add GPU port of vmix routines, fix calc of ML-averaged BV freq. [MPAS-seaice] Change extents of initial polar disks for oRRS18to6v3 grid, fix ice BGC with MARBL, update spherical test cases, fix DON coupling, Remove Cf from sea ice constants. [MPAS-landice] add CRYO1850-4xCO2 compset [CIME] add GCP, ANL GCE, Spock, Perlmutter, deprecate config_compilers.xml, fix and clean-up cmake macros, fix slurm bindings, refactor CIME internal testing, cleanup SCORPIO perf data, allow position independent compset naming, [also] update v2 benchmarking suite, extend e3sm_prod with throughput and memory checks", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v2.0.1", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v2.0.1", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v2.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v2.0.2.json b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v2.0.2.json new file mode 100644 index 00000000..c470f65c --- /dev/null +++ b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v2.0.2.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2022-11-18", + "metadataLastUpdated": "2022-12-23" + }, + "description": "Second patch release of v2.0.0 Changes since v2.0.1 [Important change] Add and update SSP370 and SSP585 cases, add tests, fix use-case files, Change ocean and sea-ice IC for ARRM60to10. [EAM] allow thetaxx as a CAM_TARGET, enable northamericax4v1pg2_WC14to60E2r3 for AMIP, fix ndrop initialization, allow up to 15 history files. [EAMxx] allow use of readnl [EAM-MMF] allow transient SST case for C++ MMF, remove specific task/thread count for ESMT test, modify the variance transport diagnostic, reorg tests, [HOMME] Allow optional sponge layer. [ELM] add 2 land-atm compsets, update FATES to API 17.0.0, allow FATES sp mode, allow ELM harvest to drive FATES harvest, fix memleaks, reduce test build times, modified parameters for miscanthus and switchgrass based on calibration [MPAS-Ocean] turn on ocean BGC in BGC cases, fix interface locations for 60L PHC grid, add mode spec to conservation check streams, allow oRRS18to6v3 grid to run with JRA, update ocean and sea ice ICs for ARRM60to10 (needed for v2), GPU port of thickness tendency, add CMPASO-JRA1p4, [MPAS framework] Add new reproducible global sum module for MPAS components, Add mostRecentAccessTime attribute to streams [MPAS-landice] Update MALI version and Greenland mesh [MPAS-seaice] add single-cell test case, fix BGC restart, Adds omp critical directives for ice warnings seen on cori. [CIME] Fix component namelist creation bugs when NINST>1, add OpenACC, OpenMP and CXX GPU tests, fix nonBFB tests, stop using config_compilers, reduce ELM test build times with shared executable, update OpenMPI on Chrysalis. fix baseline handling, provenance handling with update to cime6.0.33, also use component-specific config_pes files and add the ones from master [Machine updates] cori modules after maint, Chrysalis to OpenMPI-4.1.3 [run_e3sm] replace default case name and group. [Externals] update SCORPIO to 1.3.2", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v2.0.2", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v2.0.2", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v2.0.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v2.0.json b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v2.0.json new file mode 100644 index 00000000..58edbfd8 --- /dev/null +++ b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v2.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2021-09-27", + "metadataLastUpdated": "2022-11-18" + }, + "description": "First release of version 2 of the Energy Exascale Earth System Model. The atmosphere component remains EAM. Major changes since version 1 include: all column-physics parameterizations are computed on a separate grid that has approximately half the number of points of the dynamics grid, a new nonhydrostatic dynamical core (running in hydrostatic mode) with semi-Lagrangian tracer transport, CLUBB updated from v1 to v2, a new convective trigger (dCAPE/ULL) based on the dynamic Convective Available Potential Energy (CAPE) (dCAPE) and the Unrestricted Launch Level (ULL) concepts is used in ZM. minimum cloud droplet number changed, gravity wave drag energy conservation fixed and new tunings used, dust emission size distribution changed to emit more coarse dust particles The land component is still ELM. Major changes since version 1 include: using SNICAR-AD for radiation in snow to match the sea-ice model and fixing bugs in snow compaction and water state calculation. The ocean component remains MPAS-ocean. Major change since version 1 include: Redi isopycnal mixing has been updated, tested, and tuned in combination with the Gent-McWilliams parameterization, a sign error was fixed in the 3rd-order flux routines, the mesh used in low-resolution coupled cases was modified and the time steps adjusted, new regionally refined meshes were created, one focused on North America and another on the Southern Ocean, including ice shelf cavities. The sea-ice component remains MPAS-seaice. Major changes since version 1 include: A new heat- and freshwater-conserving coupling of frazil ice, turning off of SSH filtering, addition of SNICAR-AD and snow grain aging. The land-ice component remains MPAS-Albany-landIce (MALI) and is a static ice sheet. There is more out-of-the-box support for cryosphere configurations including the new regionally refined configuration around Antarctica with ice shelf cavities. The river model is MOSART. The half-degree river mesh was redone so it no longer treats Black and Caspian seas as ocean. The coupler remains cpl7/MCT. Major changes since version 1 include handling of ice shelf melt fluxes (heat / freshwater exchange with the ocean), and data icebergs. All components allow regional refinement of their meshes and two separate example of refinement, one in and around North America and one around Antarctica and the Southern Ocean, are provided.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v2.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v2.0.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v2.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v2.1.0.json b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v2.1.0.json new file mode 100644 index 00000000..2fe6c525 --- /dev/null +++ b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v2.1.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2023-01-12" + }, + "description": "First release of version 2.1 of the Energy Exascale Earth System Model. [ATM] The atmosphere component remains EAM. There are no major changes in the default configuration since 2.0. New features include: A semi-lagrangian tracer transport for theta-l dycore, a new algorithm for finding the tropopause, new RRM mesh configurations. Add and update SSP370 and SSP585 cases. Restore the FIDEAL case. [LAND] The land component is ELM. There are no major changes in the default configuration since 2.0. Several option features have been added including: implementation of topography-based subgrid structure (topounits) and accompanying parameterizations and atmospheric forcing downscaling methods; a new plant hydraulics scheme; two-way land-river hydrological coupling through the infiltration of floodplain water; an implementation of perennial crops; updates to the SNICAR-AD snow radiative transfer model; and implementation of soil erosion and sediment yield in ELM-Erosion. Each of these new changes is modular in design and can be turned on or off as the user specifies; they are currently being tested in different \u201cBGC\u201d configurations. [OCEAN] The ocean component remains MPAS-Ocean. Major change since version 2.0 include the addition of the Fox-Kemper et al. 2011 parameterization for submesocale eddies, a correction for barotropic thickness consistency that reduces divergence noise, and the addition of an ocean carbon conservation analysis member. [SEAICE] The sea-ice component remains MPAS-Seaice. Major changes since version 2.0 include: A correction to how shortwave parameters are interpolated in the snicar-ad 5-band radiation scheme, the addition of a sea ice carbon conservation analysis member, updates to the default sea ice biogeochemistry namelist parameters to be consistent with version 2.0 improvements to nitrogen cycling and a correction in the ice-ocean dissolved organic nitrogen coupling. [LAND ICE] The land-ice component remains MPAS-Albany-landIce (MALI). Major changes since 2.0 include an update to the MALI version and the Greenland mesh.[RIVER] The river model is MOSART. There are no major changes in the default configuration since 2.0. A major new optional feature is two-way river-ocean hydrological coupling between MOSART and MPAS-O. This change can be turned on or off as the user specifies, and is being tested in different configurations. [COUPLER] The coupler remains cpl7/MCT. Major changes since version 2.0 include: Carbon budget calculated when heat/water budgets active. Fix a bug in land-atm fluxes for tri-grid configurations. [OTHER] a small bug in the zenith angle calculation was fixed in the data models.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v2.1.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v2.1.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v2.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v3.0.0.json b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v3.0.0.json new file mode 100644 index 00000000..51bdf61c --- /dev/null +++ b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v3.0.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2024-03-01", + "metadataLastUpdated": "2024-03-04" + }, + "description": "First release of version 3.0 of the Energy Exascale Earth System Model. \nThe fully coupled cases now run by default in a \u201ctri-grid\u201d configuration where the land and river model share a higher-resolution (0.5 degree) lat-lon grid while the atmosphere and ocean are on their own grids. [ATM] component is EAM. Vertical res. has been increased from 72 to 80 layers; horizontal res. remains ne30pg2. Atmospheric physics have had significant additions and changes since version 2. Added: interactive gas chemistry in stratosphere and troposphere; size mode for prognostic treatment of stratospheric sulfate aerosol; explicit representation of secondary organic aerosols (SOA) sources; a new dust emission scheme; Predicted Particle Properties (P3) for stratiform clouds; cloud microphysics for convective clouds; MCSP to represent the effects of organized mesoscale convective systems; rougher topography. Improved: aerosol wet removal processes to reduce the overestimation of aerosols and thus aerosol forcing; numerical coupling of aerosol emission, vertical mixing and dry deposition; cloud base mass flux adjustment in ZM; lower stratospheric vertical grid and surrogate-accelerated parameter optimization. Re-tuned: Dimethyl sulfide (DMS) emission, number of monolayers for black carbon (BC) aging, and hygroscopicity of particulate organic matter (kPOM). [LAND] component is ELM. The default configuration for ELM has been switched from vegetation leaf area specified as a static monthly time series based on satellite data to a dynamic vegetation growth model. This implementation uses prognostic coupled carbon, nitrogen, and phosphorus cycles (C-N-P) for vegetation and soil biogeochemistry; the relative demand (RD) approach to resolve competition between plants and soil microbes for available nutrients; the converging trophic cascade (CTC) model for organization of plant litter and soil organic matter pools. The model also includes: A computationally efficient radiative transfer parameterization (TOP), which is based on the Monte Carlo simulations, accounts for subgrid topographic effects on solar radiation; Changed the order of sublimation and dew on snow depth calculation to ensure that snow depth is not accidentally set to a negative value. [RIVER] model is still MOSART. [OCEAN] component remains MPAS-Ocean. Major change since version 2.1 include: Using a new Icosahedral 30 km mesh with Ice Shelf Cavities (IcoswISC30E3r5) for low-resolution coupled simulations. Switched coupled surface pressure to pressure at mean sea level which reduces errors in gradient term for sea ice. Improvements to the Redi isopycnal mixing scheme; Improved computational efficiency of the ocean component by changing the baroclinic time stepping method. [SEA-ICE] component is MPAS-Seaice and has had many improvements since 2.1; Added Icepack as the default sea ice column physics; Switched to high-frequency sea ice coupling as the default surface stress flux option for all meshes; Reduced the maximum number of sea ice atmospheric turbulent flux iterations; Decreased the dynamics minimum concentration sea ice and the ice mass per unit area cutoff; Reduced standard monthly sea ice output by removing sea ice age, first year ice tracers, and level ice volume and area; Added or updated checks on configuration settings. [LAND-ICE] component remains MPAS-Albany-landIce (MALI). The version of MALI has been updated to include higher-order advection and time integration. The land-ice component is not yet supported in production configurations with v3. [COUPLER] remains cpl7/MCT. A new property-preserving map procedure enables high-order flux maps between components for selected fields. In v3 LR cases, applied to all atmosphere-to-surface fluxes except precip. Calculation of gustiness between atmosphere, ocean and land was rationalized. Default processor layouts for the low-resolution configuration are available on Perlmutter and other DOE platforms.", + "laborHours": 0.0, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v3.0.0", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v3.0.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v3.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v3.0.1.json b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v3.0.1.json new file mode 100644 index 00000000..aef70acf --- /dev/null +++ b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v3.0.1.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2024-09-30", + "metadataLastUpdated": "2024-10-02" + }, + "description": "E3SM v3.0.1. First patch release of v3.0. The main purpose of this release is to introduce additional compsets used in v3 simulations and also fix some bugs found in compsets released with 3.0.0. [BUG FIXES] WCYCL20TR and F20TR have an updated landuse timeseries file. Those compsets and F2010 also have corrected nitrogen deposition and population density files for years after 1990. Except for those compsets, the simulated climate is identical for compsets released in v3.0.0. [NEW COMPSETS] New fully coupled compsets, including WCYCLSSP245, WCYCLSSP370, and WCYCLSSP585, which simulate future climate scenarios based on different socio-economic pathways. New single-forcing compsets like WCYCL20TR-GHG (greenhouse gases), and WCYCL20TR-aer (aerosols), allow simulations focusing on specific climate drivers. Two fully coupled compsets with dynamic ice sheets are also available. [GENERAL] Documentation for all components has been created at https://docs.e3sm.org/E3SM/ . All components have new optional features but the defaults have not changed for v3.0.0 supported compsets. The supported resolution is still a \"tri-grid\" as described in v3.0.0. [ATM] Add ability to calculate zonal mean quantities for QBO. Add new diagnostic to output CCN fields per mass of air. Add four new joint histograms to the MODIS simulator. Add alternative data stream control for SO2 species. Fix diagnostic output of in-cloud qc, nc, qi, and ni in P3. Created new User and Technical guide for EAM. Restore ability to output variable along ship/flight tracks Major update to PAM in EAM-MMF: Add adaptive subcycling in driver and enable variance transport by default. Add compsets to facilitate the E3SM-MMF (and E3SM) contributions to phase 1 & 2 of the radiative-convective equilibrium model inter-comparison project (RCEMIP). [LAND] Several fixes to C,N, P balance checks. Optionally modify the ELM snowcapping routing scheme along with the snow and firn compaction schemes to include changes made by Schneider et al. (2022); optionally implement the new snow thermal conductivity calculation method introduced in Fourteau et al. (2021); introduce a new optional format for PFT physiology files (paramfile) that allows user to specify a flexible number of PFTs. Add a LULC file for 1850-2015 at r025; allow output of land fraction used in dust mobilization. [OCEAN] Modify SSS restoring to include under sea ice by default. Fix GOTM interface for vertical mixing. Assign alkalinity equals DIC in sea ice melt, switch ice-shelf melt fluxes to Paolo 2023. Add frazil to ice-shelf melt rates, add distinct passive tracer background vert diffusivity, add parametrized tidal mixing effects to ice shelf basal melt, and add subglacial discharge at grounding line. Improve checks for ocean conservation. [LAND-ICE] Add support for dynamic Greenland Ice sheet and Antarctic Ice Sheet meshes for MALI. Add MALI thermal solver bug fix and improved iceberg handling. Activate MALI thermal solver and update configuration to be relevant to both AIS and GIS grids. [SEA-ICE] Merged vertically resolved biogeochemistry and aerosols from the standard MPAS-Seaice column package into the Icepack library, enabling the option to use Icepack for active biogeochemistry and aerosol simulations. Added a namelist option to use a spatial field for dust-iron solubility rather than a constant. Added capability to read atmospheric dust fluxes and dust-iron solubility maps from an input file. \n[COUPLER] Add ability to robustly recover from failures during restart-file writing, and cryo fields to coupler budget accounting. [Included libraries] update SCORPIO to v1.6.5, Kokkos to 4.2, CIME to 6.1.18. SCORPIO 1.6.5 includes improved support for Perlmutter and Frontier. A new rearranger, PIO_REARR_ANY, was added that lets the library choose the appropriate data rearranger to use.The default I/O NetCDF format (for reading and writing) is changed from \"64-bit offset\" (NetCDF CDF2) to \"64bit-data\" (NetCDF CDF5).", + "laborHours": 1762470.4, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v3.0.1", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v3.0.1", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v3.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v3.0.2.json b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v3.0.2.json new file mode 100644 index 00000000..cd326c97 --- /dev/null +++ b/agency-indexes/DoE/Energy_Exascale_Earth_System_Model_v3.0.2.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2024-12-16", + "metadataLastUpdated": "2024-12-18" + }, + "description": "E3SM v3.0.2. Second patch release of v3.0. The main purpose of this release is to fix the forcing specifications of single-forcing compsets introduced in v3.0.1\n[BUG FIXES] These compsets are changed: WCYCL20TR-GHG, WCYCL20TR-aer, WCYCL20TR-xGHG-xaer, WCYCL20TR-xaer. Core to the changes is to separate the transient aerosol and chemical precursors for different single forcing compsets. New virtually transient forcing files are introduced to satisfy the unified data stream control for surface and elevated emissions. Historical evolution of stratospheric ozone is moved from the all-else configuration to the GHG only configuration. Except for those compsets, the simulated climate is identical for compsets released in v3.0.0 and released/updated in v3.0.1.\n[ATM] fix output of r_lch4 and r_lco_h reaction rates. Downstream merge from SCREAM repo.\n[LND] The precision of a few real variables is fixed during model initialization. New parameterizations are added for the burial of shrubs by snow; however, these parameterizations are not on by default.\n[OCEAN] fix bug in data sub-glacial runoff. Add new SOwISC12to30E3r3 mesh.\n[SEA-ICE] Update BGC history fields.\n[LAND-ICE] Add ERA5r025 configurations for new IGERA5ELM_MLI compsets\n[WAVES] Change location of WW3 compilation, update wave developer test suite.\n[DATA-MODEL] Add support for new JRA forcing through year 2023.", + "laborHours": 1769751.2, + "languages": [ + "C", + "C", + "Fortran" + ], + "name": "Energy Exascale Earth System Model v3.0.2", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM/releases/tag/v3.0.2", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v3.0.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Operation_Model.json b/agency-indexes/DoE/Energy_Operation_Model.json new file mode 100644 index 00000000..ca7291b9 --- /dev/null +++ b/agency-indexes/DoE/Energy_Operation_Model.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Energy Operation Model (EOM) simulates the operation of the electric grid at the zonal scale, including inter-zonal transmission constraints. It generates the production cost, power generation by plant and category, fuel usage, and locational marginal price (LMP) with a flexible way to constrain the power production by environmental constraints, e.g. heat waves, drought conditions). Different from commercial software such as PROMOD IV where generator capacity and heat rate efficiency can only be adjusted on a monthly basis, EOM calculates capacity impacts and plant efficiencies based on hourly ambient conditions (air temperature and humidity) and cooling water availability for thermal plants. What is missing is a hydro power dispatch.", + "homepageURL": "https://store.pnnl.gov/content/energy-operation-model-eom", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Energy Operation Model", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/energy-operation-model-eom", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/energy-operation-model-eom", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Research_and_Forecasting__ERF__v1.json b/agency-indexes/DoE/Energy_Research_and_Forecasting__ERF__v1.json new file mode 100644 index 00000000..daf75495 --- /dev/null +++ b/agency-indexes/DoE/Energy_Research_and_Forecasting__ERF__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "ERF is a next-generation regional atmospheric modeling code for simulation mesoscale atmospheric flows. Its capabilities include the ability to model advection, diffusion, turbulence, terrain and moisture physics.", + "laborHours": 0.0, + "languages": [], + "name": "Energy Research and Forecasting (ERF) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/erf-model/ERF", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Energy_Storage_Sizing,_Placement_and_Valuation_for_Distribution_Networks.json b/agency-indexes/DoE/Energy_Storage_Sizing,_Placement_and_Valuation_for_Distribution_Networks.json new file mode 100644 index 00000000..ea1ead12 --- /dev/null +++ b/agency-indexes/DoE/Energy_Storage_Sizing,_Placement_and_Valuation_for_Distribution_Networks.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2024-07-30" + }, + "description": "SAND2023-05682O\nThe Energy Storage Sizing, Placement, and Valuation for Distribution software allows a user to simulate sizing, placement, and operation of one or more storage assets on a distribution grid. Among its features are measuring differences to determine the best combinations, and options for configuring and comparing results. This new simulation capability leverages the Open Distribution System Simulator and the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS).\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 6840.0, + "languages": [ + "Python", + "kvlang" + ], + "name": "Energy Storage Sizing, Placement and Valuation for Distribution Networks", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/quest-ssim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Engage\342\204\242:_A_Calliope_Web_Environment_for_Collaborative_Energy_Systems_Modeling_and_Planning.json" "b/agency-indexes/DoE/Engage\342\204\242:_A_Calliope_Web_Environment_for_Collaborative_Energy_Systems_Modeling_and_Planning.json" new file mode 100644 index 00000000..f2aa553a --- /dev/null +++ "b/agency-indexes/DoE/Engage\342\204\242:_A_Calliope_Web_Environment_for_Collaborative_Energy_Systems_Modeling_and_Planning.json" @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-02-16", + "metadataLastUpdated": "2023-04-24" + }, + "description": "Engage\u2122 is a free, open-access energy system planning tool that allows multiple users/stakeholders to develop and collaborate on capacity expansion models. The tool, developed at the National Renewable Energy Laboratory (NREL), provides a collaborative and easy-to-use interface built on Calliope, a multi-scale energy systems modeling framework. Visit the NREL hosted webtool at https://engage.nrel.gov/", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python", + "SCSS", + "CSS", + "HTML" + ], + "name": "Engage\u2122: A Calliope Web Environment for Collaborative Energy Systems Modeling and Planning", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/engage", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Enhanced_STIX_Elevator.json b/agency-indexes/DoE/Enhanced_STIX_Elevator.json new file mode 100644 index 00000000..5f08192a --- /dev/null +++ b/agency-indexes/DoE/Enhanced_STIX_Elevator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-02-09", + "metadataLastUpdated": "2023-03-08" + }, + "description": "To more effectively and completely convert STIX1 data to STIX2.", + "laborHours": 0.0, + "languages": [], + "name": "Enhanced_STIX_Elevator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/idaholab/Enhanced_STIX_Elevator/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Enhanced_STIX_Elevator", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ensemble_Data_Analysis_ENvironment__EDEN_.json b/agency-indexes/DoE/Ensemble_Data_Analysis_ENvironment__EDEN_.json new file mode 100644 index 00000000..a652b2a2 --- /dev/null +++ b/agency-indexes/DoE/Ensemble_Data_Analysis_ENvironment__EDEN_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The EDEN toolkit facilitates exploratory data analysis and visualization of global climate model simulation datasets. EDEN provides an interactive graphical user interface (GUI) that helps the user visually construct dynamic queries of the characteristically large climate datasets using temporal ranges, variable selections, and geographic areas of interest. EDEN reads the selected data into a multivariate visualization panel which features an extended implementation of parallel coordinates plots as well as interactive scatterplots. The user can query data in the visualization panel using mouse gestures to analyze different ranges of data. The visualization panel provides coordinated multiple views whereby selections made in one plot are propagated to the other plots.", + "laborHours": 0.0, + "languages": [ + "Java 1.6 or higher" + ], + "name": "Ensemble Data Analysis ENvironment (EDEN)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/csteed/eden/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csteed/eden", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Environmental_and_Molecular_Science_Laboratory_Arrow.json b/agency-indexes/DoE/Environmental_and_Molecular_Science_Laboratory_Arrow.json new file mode 100644 index 00000000..81d999dc --- /dev/null +++ b/agency-indexes/DoE/Environmental_and_Molecular_Science_Laboratory_Arrow.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Arrows is a software package that combines NWChem, SQL and NOSQL databases, email, and social networks (e.g. Twitter, Tumblr) that simplifies molecular and materials modeling and makes these modeling capabilities accessible to all scientists and engineers. EMSL Arrows is very simple to use. The user just emails chemical reactions to arrows@emsl.pnnl.gov and then an email is sent back with thermodynamic, reaction pathway (kinetic), spectroscopy, and other results. EMSL Arrows parses the email and then searches the database for the compounds in the reactions. If a compound isn't there, an NWChem calculation is setup and submitted to calculate it. Once the calculation is finished the results are entered into the database and then results are emailed back.", + "homepageURL": "https://store.pnnl.gov/content/emsl-arrows", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Environmental and Molecular Science Laboratory Arrow", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/emsl-arrows", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/emsl-arrows", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/EpetraExt__Epetra_Extended__-_Linear_Algebra_Services.json b/agency-indexes/DoE/EpetraExt__Epetra_Extended__-_Linear_Algebra_Services.json new file mode 100644 index 00000000..7e4259d0 --- /dev/null +++ b/agency-indexes/DoE/EpetraExt__Epetra_Extended__-_Linear_Algebra_Services.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "EpetraExt is a set of extensions to Epetra. To allow Epetra to remain focused on its primary functionality as a Linear Algebra object support, EpetraExt was created to maintain additional support for such capabilities as transformations (permutations, subblock views, etc.), coloring support, partitioning (Zoltan), and I/O.", + "laborHours": 8344830.4, + "languages": [], + "name": "EpetraExt (Epetra Extended) - Linear Algebra Services", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Epetra_Linear_Algebra_Services_Package.json b/agency-indexes/DoE/Epetra_Linear_Algebra_Services_Package.json new file mode 100644 index 00000000..42e517a0 --- /dev/null +++ b/agency-indexes/DoE/Epetra_Linear_Algebra_Services_Package.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Epetra provides the fundamental construction routines and service functions that are required for serial and paraliellinear algebra libraries using double precision scalar values and int ordinal values.", + "laborHours": 8344830.4, + "languages": [], + "name": "Epetra Linear Algebra Services Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EpicsBuildAnalysis.json b/agency-indexes/DoE/EpicsBuildAnalysis.json new file mode 100644 index 00000000..a9b337f8 --- /dev/null +++ b/agency-indexes/DoE/EpicsBuildAnalysis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-24", + "metadataLastUpdated": "2022-08-24" + }, + "description": "EpicsBuildAnalyis is a program that analyzes EPICS builds to produce a text file describing the dependencies of each module in the EPICS build; produce a dependency graph for each build of each EPICS module in the build, and, optionally, the complete dependency graph for the entire module set; produce a list of EPICS modules that are present in one EPICS local release but are not in another EPICS local release.", + "laborHours": 0.0, + "languages": [], + "name": "EpicsBuildAnalysis", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/EpicsBuildAnalysis/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/EpicsBuildAnalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Equilipy.json b/agency-indexes/DoE/Equilipy.json new file mode 100644 index 00000000..85f09dd5 --- /dev/null +++ b/agency-indexes/DoE/Equilipy.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "kwons@ornl.gov" + }, + "date": { + "created": "2024-03-12", + "metadataLastUpdated": "2024-03-13" + }, + "description": "There is high demand for high-throughput calculations of phase equilibria based on the CALPHAD method (CALculation of PHAse Diagram). High-throughput calculations are possible through HPC, currently by a commercial program called Thermo-Calc. However, the number of nodes/processors are limited to the number of purchased license (16 processors per license). This program provides a toolkit for high-throughput calculations of phase equilibria by the CALPHAD method. The program is prepared for Python environment, so that it can be easily installed and used together with other open-source programs. The program can be run in supercomputer.", + "laborHours": 0.0, + "languages": [ + "Fortran", + "Python" + ], + "name": "Equilipy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/Equilipy", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Equipment_Cost_Estimator.json b/agency-indexes/DoE/Equipment_Cost_Estimator.json new file mode 100644 index 00000000..b458e1cd --- /dev/null +++ b/agency-indexes/DoE/Equipment_Cost_Estimator.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The ECE application forecasts annual costs of preventive and corrective maintenance for budgeting purposes. Features within the application enable the user to change the specifications of the model to customize your forecast to best fit their needs and support \u201cwhat if\u201d analysis. Based on the user's selections, the ECE model forecasts annual maintenance costs. Preventive maintenance costs include the cost of labor to perform preventive maintenance activities at the specific frequency and labor rate. Corrective maintenance costs include the cost of labor and the cost of replacement parts. The application presents forecasted maintenance costs for the next five years in two tables: costs by year and costs by site.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++, other" + ], + "name": "Equipment Cost Estimator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ergonomics_Education,_Awareness_System_Evaluation_and_Recording.json b/agency-indexes/DoE/Ergonomics_Education,_Awareness_System_Evaluation_and_Recording.json new file mode 100644 index 00000000..153c158b --- /dev/null +++ b/agency-indexes/DoE/Ergonomics_Education,_Awareness_System_Evaluation_and_Recording.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-07-03", + "metadataLastUpdated": "2022-08-09" + }, + "description": "ErgoEASER is a computer based program that provides training and analysis tools on potential ergonomic hazards in the workplace. This version incorporates training on ergonomic issues in office environments and those associated with hand tool design and use. These training modules complement the ergonomic analysis tools (for lifting tasks and Video Display Terminal workstations comprising Version 1 (copyrighted under the name, ErgoAnalyze) ErgoEASER2.0 includes the entire analysis tool/training package. It provides multiple levels of support through its interactive components. Getting started reviews background information on occupational ergonomics. Awareness and reporting presents examples and photographs of potentially hazardous postures and practices, enabling users to assess their work environments. This component provides a modest level of education and training on occupational ergonomics. Lifting analysis this component enables users to input key dimensions and variables that apply to lifting tasks, then adjust the values and view results in a simulated display depicting the human postures, practices, and associated strains. VDT analysis this component enables users to input key dimensions and variables that apply to video display terminal workstation tasks, then adjust the values and view results in a simulated display depicting the human postures, practices, and associated strains. Ergonomics computer based training this component presents two computer based training lessons, one on office ergonomics and the other on hand tools. Each lesson includes four topics: ergonomics, risk factors, symptoms and signs, and a mastery exercise that assesses the students overall comprehension of the material and preparedness to use ErgoEASER's analysis components.", + "laborHours": 0.0, + "languages": [], + "name": "Ergonomics Education, Awareness System Evaluation and Recording", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://creativecommons.org/publicdomain/zero/1.0/legalcode", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/ergoeaser2", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ErrFilter.json b/agency-indexes/DoE/ErrFilter.json new file mode 100644 index 00000000..a47338e9 --- /dev/null +++ b/agency-indexes/DoE/ErrFilter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-09-04", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ErrFilter is a tool that allows an analyst to explore data by defining simple Boolean filters on data. The tool also allows the user to sort the results by any attribute. The user sees both the distribution of filtered data as well as selected examples. The tool was designed to be applied generally to multivariate data associated with machine learning models.", + "laborHours": 65770.4, + "languages": [], + "name": "ErrFilter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/errfilter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Error_Detection_and_Correction_LDMS_Plugin_Version_1.0.json b/agency-indexes/DoE/Error_Detection_and_Correction_LDMS_Plugin_Version_1.0.json new file mode 100644 index 00000000..d72a302a --- /dev/null +++ b/agency-indexes/DoE/Error_Detection_and_Correction_LDMS_Plugin_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Sandia's Lightweight Distributed Metric Service (LDMS) is a data collection and transport system used at Livermore Computing to gather performance data across the center. While Sandia has a set of plugins available, they do not include all the data we need to capture. The ECAC plugin that we have developed enables collection of the Error Detection and Correction (EDAC) counters.", + "laborHours": 98252.8, + "name": "Error Detection and Correction LDMS Plugin Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ovis-hpc/ovis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Eshelby-Mori-Tanaka_Approach.json b/agency-indexes/DoE/Eshelby-Mori-Tanaka_Approach.json new file mode 100644 index 00000000..3404e5fc --- /dev/null +++ b/agency-indexes/DoE/Eshelby-Mori-Tanaka_Approach.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "EMTA is a stand-alone computer program that has been developed for the computation of elastic properties and thermal expansion coefficients (thermoelastic properties) of discontinuous fiber composites. EMTA stands for the Eshelby-Mori-Tanaka approach. It implements the standard and modified Mori-Tanaka models that use the Eshelby's equivalent inclusion method. EMTA carries out the Eshelby-Mori-Tanaka homogenization procedure accounting for the constituents (fiber and matrix) properties such as the elastic properties and thermal expansion coefficients (CTEs) of the fibers and of the matrix. It also accounts for the constituents features such as fiber length and orientation distributions, fiber curvature, and imperfect fiber/matrix interfaces. The outputs of an EMTA execution are the elastic properties (engineering constants) and CTEs of the as-formed composite in the defined material coordinate system. These results can readily be used in engineering applications and designs that require these properties.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Eshelby-Mori-Tanaka Approach", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Essential_Signal_Simulation_Enabled_by_Netlist_Transforms__ESSENT__v1.0.json b/agency-indexes/DoE/Essential_Signal_Simulation_Enabled_by_Netlist_Transforms__ESSENT__v1.0.json new file mode 100644 index 00000000..5362bd8f --- /dev/null +++ b/agency-indexes/DoE/Essential_Signal_Simulation_Enabled_by_Netlist_Transforms__ESSENT__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-29", + "metadataLastUpdated": "2019-10-29" + }, + "description": "Hardware simulation is an indispensable tool for designing chips as well as researching future architectures. Unfortunately, the slow rate of simulation can often bottleneck the design process, as designers must wait to see the results of a simulation before changing the design and starting a new simulation. The Essential Signal Simulation Enabled by Netlist Transforms (ESSENT) is a tool designed to accelerate hardware simulations. ESSENT takes in a design, uses graph algorithms to identify opportunities for conditional execution, and generates a simulator that leverages these opportunities. The generated simulator produces the exact same simulation results that would be returned by an unoptimized simulator, but in substantially less time. For input, ESSENT takes in designs formatted in FIRRTL (an open format).", + "laborHours": 1717.6, + "languages": [], + "name": "Essential Signal Simulation Enabled by Netlist Transforms (ESSENT) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ucsc-vama/essent", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EtherNet_IP_Client_Library.json b/agency-indexes/DoE/EtherNet_IP_Client_Library.json new file mode 100644 index 00000000..65085b6c --- /dev/null +++ b/agency-indexes/DoE/EtherNet_IP_Client_Library.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "kasemirk@ornl.gov" + }, + "date": { + "created": "2021-10-12", + "metadataLastUpdated": "2021-10-12" + }, + "description": "Java library for reading and writing tags via the Ethernet/IP network protocol as used by AllenBradley ControlLogix and Compact Logix PLCs.\n\nPart of ORNL-EPICS. ", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "EtherNet IP Client Library", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-epics/etherip", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ethon.json b/agency-indexes/DoE/Ethon.json new file mode 100644 index 00000000..0e3108b4 --- /dev/null +++ b/agency-indexes/DoE/Ethon.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Ethon is a research code that implements well-known hydrodynamics methods (finite-volume and Discontinuous Galerkin) to solve the compressible Euler equations with a simple ideal gas equation of state and no additional physics using a block-based adaptive mesh refinement (AMR) infrastructure. Ethon uses the publicly available Kokkos library for performance portability between CPUs and GPUs. The purpose of Ethon is to evaluate the hydrodynamics methods using block-based AMR on different computing infrastructures.", + "laborHours": 0.0, + "languages": [], + "name": "Ethon", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ethon", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Euclidean_neural_networks__e3nn__v1.0.json b/agency-indexes/DoE/Euclidean_neural_networks__e3nn__v1.0.json new file mode 100644 index 00000000..70f26868 --- /dev/null +++ b/agency-indexes/DoE/Euclidean_neural_networks__e3nn__v1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-03", + "metadataLastUpdated": "2021-06-15" + }, + "description": "E(3) is the Euclidean group in dimension 3. That is the group of rotations, translations and mirror. e3nn is a pytorch library that aims to create E(3) equivariant neural networks.", + "laborHours": 0.0, + "languages": [], + "name": "Euclidean neural networks (e3nn) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/e3nn/e3nn", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ev_Info_And_Incident_Response_Solutions.json b/agency-indexes/DoE/Ev_Info_And_Incident_Response_Solutions.json new file mode 100644 index 00000000..3c406f90 --- /dev/null +++ b/agency-indexes/DoE/Ev_Info_And_Incident_Response_Solutions.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-10-19", + "metadataLastUpdated": "2023-10-19" + }, + "description": "In post-crash situations, passengers, bystanders, and first responders are exposed to the immediate safety risks of stranded energy in electric vehicle (EV) batteries. A potentially damaged battery with an unknown state of safety might go into a thermal runaway without proper handling, leading to potential loss of life and property damage. Therefore, it is imperative to develop methods, guidelines and tools to handle the post-crash EVs appropriately and minimize safety risks from immediately after an EV accident to final disposal or re-entry to the road. \nThis software tool:\n(1) provides quick access to EV specification, \n(2) estimate stranded energy left in an EV after a crash specific to EVs in a user-friendly way, \n(3) inform EV structure/disconnect for appropriate quick post-crash handling,\n(4) perform the calculation for the first responder to decide on onsite or offsite discharge, and\n(5) feature appropriate battery disposal and education/lessons learned.\nThis software tool will directly help the emergency responders to handle EV post-crash situations effectively and safely.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python", + "SQL" + ], + "name": "Ev Info And Incident Response Solutions", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/EVIRS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Evaluating_Physics_Informed_Neural_Network_Performance_for_Seismic_Discrimination_Between_Earthquake.json b/agency-indexes/DoE/Evaluating_Physics_Informed_Neural_Network_Performance_for_Seismic_Discrimination_Between_Earthquake.json new file mode 100644 index 00000000..5d139ef7 --- /dev/null +++ b/agency-indexes/DoE/Evaluating_Physics_Informed_Neural_Network_Performance_for_Seismic_Discrimination_Between_Earthquake.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "This package contains the code for the paper Evaluating Physics Informed Neural Network Performance\nfor Seismic Discrimination Between Earthquake published at Seismological Research Letters. There are\none Jupyter notebook and demo data so that the audience can run build a machine learning model with\nthe P/S ratios as a physics loss in addition to the data driven loss.t", + "laborHours": 106.4, + "languages": [], + "name": "Evaluating Physics Informed Neural Network Performance for Seismic Discrimination Between Earthquake", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qingkaikong/PhysicsML-PINN-EmpiricalRelationship", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Event-by-event_fission_simulation_code,_generates_complete_fission_events.json b/agency-indexes/DoE/Event-by-event_fission_simulation_code,_generates_complete_fission_events.json new file mode 100644 index 00000000..b09f65e7 --- /dev/null +++ b/agency-indexes/DoE/Event-by-event_fission_simulation_code,_generates_complete_fission_events.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "FREYA is a computer code that generates complete fission events. The output includes the energy and momentum of these final state particles: fission products, prompt neutrons and prompt photons. The version of FREYA that is to be released is a module for MCNP6.", + "homepageURL": "http://nuclear.llnl.gov/simulations", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Event-by-event fission simulation code, generates complete fission events", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://nuclear.llnl.gov/simulations", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://nuclear.llnl.gov/simulations", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Event-modeled_Risk_Assessment_Using_Linked_Diagrams.json b/agency-indexes/DoE/Event-modeled_Risk_Assessment_Using_Linked_Diagrams.json new file mode 100644 index 00000000..417a7fc0 --- /dev/null +++ b/agency-indexes/DoE/Event-modeled_Risk_Assessment_Using_Linked_Diagrams.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-04-02", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Event Modeling Risk Assessment using Linked Diagrams (EMRALD) is a software tool developed at INL for researching the capabilities of dynamic PRA (Probabilistic Risk Assessment). In order to promote the effective use of dynamic PRA by the general community, EMRALD focuses on the following key aspects: Simplifying the modeling process by providing a structure that corresponds to traditional PRA modeling methods Providing a user interface (UI) that makes it easy for the user to model and visualize complex interactions Allowing the user to couple with other analysis applications such as physics based simulations. This includes one-way communication for most applications and two-way loose coupling for customizable applications Providing the sequence and timing of events that lead to the specified outcomes when calculating results Traditional aspects of components with basic events, fault trees, and event trees are all captured in a dynamic framework of state diagrams, which are displayed.", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Event-modeled Risk Assessment Using Linked Diagrams", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/EMRALD", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Event_Fanout_Receiver__evfr__v1.0.json b/agency-indexes/DoE/Event_Fanout_Receiver__evfr__v1.0.json new file mode 100644 index 00000000..1371be6d --- /dev/null +++ b/agency-indexes/DoE/Event_Fanout_Receiver__evfr__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The event fanout-receiver is an event-based timing system implementation capable of synchronizing (with respect to clock, events and triggers) to an upstream event generator. This can be used in 2 modes: fanout or receiver. the first one receives 1 upstream timing streams and fanouts it to 36. The second one receives and decodes the stream. This has been in use by ALS for many years and this is a similar implementation, but providing a more flexible configuration", + "laborHours": 8618.4, + "languages": [], + "name": "Event Fanout/Receiver (evfr) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/LBNL-EVFR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EvoProtGrad__Directed_Evolution_for_Proteins_with_Gradients__[SWR-23-48].json b/agency-indexes/DoE/EvoProtGrad__Directed_Evolution_for_Proteins_with_Gradients__[SWR-23-48].json new file mode 100644 index 00000000..1bf3945a --- /dev/null +++ b/agency-indexes/DoE/EvoProtGrad__Directed_Evolution_for_Proteins_with_Gradients__[SWR-23-48].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2024-06-05" + }, + "description": "A Python package for directed evolution on a protein sequence with gradient-based discrete Markov chain monte carlo (MCMC). Users are able to compose custom models that map sequence to function with pretrained models, including protein language models (PLMs), to guide and constrain search. Our package natively integrates with the HuggingFace platform and supports PLMs from transformers.\n\nOur MCMC sampler identifies promising amino acids to mutate via model gradients taken with respect to the input (i.e., sensitivity analysis). We allow users to compose their own custom target function for MCMC by leveraging the Product of Experts MCMC paradigm. Each model is an \"expert\" that contributes its own knowledge about the protein's fitness landscape to the overall target function. The sampler is designed to be more efficient and effective than brute force and random search while maintaining most of the generality and flexibility.\n\nAdditional information can be found in the related publication: https://iopscience.iop.org/article/10.1088/2632-2153/accacd", + "laborHours": 820.8, + "languages": [ + "PYTHON", + "Jupyter Notebook" + ], + "name": "EvoProtGrad (Directed Evolution for Proteins with Gradients) [SWR-23-48]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EvoProtGrad", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Evolution_of_mechanisms_that_control_mating_in_Drosophila_males_-_\"Supplemental_Folder_1\".json" "b/agency-indexes/DoE/Evolution_of_mechanisms_that_control_mating_in_Drosophila_males_-_\"Supplemental_Folder_1\".json" new file mode 100644 index 00000000..e70abbd2 --- /dev/null +++ "b/agency-indexes/DoE/Evolution_of_mechanisms_that_control_mating_in_Drosophila_males_-_\"Supplemental_Folder_1\".json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-02", + "metadataLastUpdated": "2019-05-03" + }, + "description": "Supplementary Folder 1\" is documentation with embedded code. It is a supplement to a manuscript communicating results for a collaborative research project on the evolutionary mechanisms of fruit fly mating.", + "laborHours": 6049.6, + "languages": [], + "name": "Evolution of mechanisms that control mating in Drosophila males - \"Supplemental Folder 1\"", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aavilaherrera/flymating", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ex_Situ_and_In_Situ_Catalytic_Fast_Pyrolysis_Models__ASPEN_PLUS_MODELS__[SWR-16-12].json b/agency-indexes/DoE/Ex_Situ_and_In_Situ_Catalytic_Fast_Pyrolysis_Models__ASPEN_PLUS_MODELS__[SWR-16-12].json new file mode 100644 index 00000000..59432f09 --- /dev/null +++ b/agency-indexes/DoE/Ex_Situ_and_In_Situ_Catalytic_Fast_Pyrolysis_Models__ASPEN_PLUS_MODELS__[SWR-16-12].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2025-03-26" + }, + "description": "These models are based on the 2015 Design Report of Dutta et al. found here: https://www.nrel.gov/docs/fy15osti/62455.pdf The models are distributed under the GNU General Public License. You will need a separate license to use the Aspen Plus and Microsoft Excel software packages in order to run the models. These models relate to an Aspen Plus process model for in situ and ex situ upgrading of fast pyrolysis vapors for the conversion of biomass to hydrocarbon fuels. It is based on conceptual designs that allow projections of future commercial implementations of the technologies based on a combination of research and existing commercial technologies. Results from the model are documented in a detailed design report NREL/TP-5100-62455 (available at http://www.nrel.gov/docs/fy15osti/62455.pdf). The model consists of the following key operations: (a) fast pyrolysis and vapor upgrading, (b) vapor condensation and recovery of an organic liquid and an aqueous phase, (c) hydroprocessing of the liquid organic phase to produce a fuel blendstock, (d) hydrogen production from off gases, (e) electricity production from excess heat, (f) other utilities such as cooling water, (g) wastewater utilization and treatment.", + "homepageURL": "https://www.nrel.gov/extranet/biorefinery/aspen-models", + "laborHours": 0.0, + "languages": [], + "name": "Ex Situ and In Situ Catalytic Fast Pyrolysis Models (ASPEN PLUS MODELS) [SWR-16-12]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/extranet/biorefinery/aspen-models", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Exa-Graph_mel.json b/agency-indexes/DoE/Exa-Graph_mel.json new file mode 100644 index 00000000..98c0236f --- /dev/null +++ b/agency-indexes/DoE/Exa-Graph_mel.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-07-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MPI implementation of Half-approximate Graph Matching", + "laborHours": 2568.8, + "languages": [], + "name": "Exa-Graph/mel", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exa-Graph/mel", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Exa-Graph_neve.json b/agency-indexes/DoE/Exa-Graph_neve.json new file mode 100644 index 00000000..02f57e98 --- /dev/null +++ b/agency-indexes/DoE/Exa-Graph_neve.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-03-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Microbenchmark to study communication and memory-access performance of graphs.", + "laborHours": 0.0, + "languages": [], + "name": "Exa-Graph/neve", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exa-Graph/neve", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Exa-Graph_vite.json b/agency-indexes/DoE/Exa-Graph_vite.json new file mode 100644 index 00000000..1521795d --- /dev/null +++ b/agency-indexes/DoE/Exa-Graph_vite.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-09-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MPI+OpenMP implementation of Louvain method for Graph Community Detection, with a number of parallel heuristics/approximate computing techniques\nAlso called \"CuVite\"", + "laborHours": 4043.2, + "languages": [], + "name": "Exa-Graph/vite", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exa-Graph/vite", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExaChem_exachem.json b/agency-indexes/DoE/ExaChem_exachem.json new file mode 100644 index 00000000..e23b2e1d --- /dev/null +++ b/agency-indexes/DoE/ExaChem_exachem.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-06-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Open Source Exascale Computational Chemistry Software", + "laborHours": 0.0, + "languages": [], + "name": "ExaChem/exachem", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ExaChem/exachem", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExaConstit.json b/agency-indexes/DoE/ExaConstit.json new file mode 100644 index 00000000..14d2007c --- /dev/null +++ b/agency-indexes/DoE/ExaConstit.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-10-24", + "metadataLastUpdated": "2019-10-24" + }, + "description": "The principal purpose of this code is to determine bulk constitutive properties and response of polycrystalline materials. \n\nThis is a nonlinear quasi-static, implicit solid mechanics code built on the MFEM library based on an updated Lagrangian formulation (velocity based).\n\nWithin this context, there is flexibility in the type of constitutive model employed, with the code allowing for various UMATs to be interfaced within the code framework or for the use of the ExaCMech library.\n\nUsing crystal-mechanics-based constitutive models, the code can be used, for example, to compute homogenized response behavior over a polycrystal.\n", + "laborHours": 4180.0, + "languages": [], + "name": "ExaConstit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ExaConstit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExaDigiT_RAPS.json b/agency-indexes/DoE/ExaDigiT_RAPS.json new file mode 100644 index 00000000..5f2cf652 --- /dev/null +++ b/agency-indexes/DoE/ExaDigiT_RAPS.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "brewerwh@ornl.gov" + }, + "date": { + "created": "2024-06-04", + "metadataLastUpdated": "2024-06-28" + }, + "description": "ExaDigiT is a framework for developing comprehensive digital twins of liquid-cooled supercomputers, which has three main modules: (1) a python-based Resource Allocator and Power Simulator (RAPS), (2) a Modelica-based Thermo-Fluidic cooling model, and (3) a C++-based augmented reality model built on Unreal Engine 5. RAPS either simulates workloads or replays historical workloads from system telemetry, and is able to predict dynamic energy consumption, as well as interact with the cooling model to predict cooling system behavior. Such a tool can be used together with reinforcement learning algorithms to provide an end-to-end optimization tool for data centers.", + "laborHours": 775.2, + "languages": [ + "Python" + ], + "name": "ExaDigiT/RAPS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/exadigit/raps", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExaGAN_v1.0.json b/agency-indexes/DoE/ExaGAN_v1.0.json new file mode 100644 index 00000000..d115c042 --- /dev/null +++ b/agency-indexes/DoE/ExaGAN_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-10-04" + }, + "description": "This software provides a basic Generative Adversarial Network (GAN) template for modeling 2D slices of N-body dark matter simulations, as part of the Exalearn project. The underlying design is a standard deep convolutional GAN, but we augment it with a technique we are calling multi-channel rescaling. This technique adds a second image channel to the output of the GAN, which represents the data in a different normalization in order to improve the quality of the results.", + "laborHours": 349.6, + "languages": [], + "name": "ExaGAN v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pzharrington/ExaGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExaGo.json b/agency-indexes/DoE/ExaGo.json new file mode 100644 index 00000000..38ee7634 --- /dev/null +++ b/agency-indexes/DoE/ExaGo.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2021-09-22" + }, + "description": "A library for solving large scale power system stochastic multi-period security-constrained optimization problems on next generation exascale architectures", + "laborHours": 0.0, + "languages": [], + "name": "ExaGo", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/exasgd/frameworks/exago", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExaMPM.json b/agency-indexes/DoE/ExaMPM.json new file mode 100644 index 00000000..b4ebb5d2 --- /dev/null +++ b/agency-indexes/DoE/ExaMPM.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "ExaMPM is a mini-application for the Material Point Method (MPM) for studying the application of MPM to future exascale computing systems. MPM is a general method for computational mechanics and fluids and is used in a wide variety of science and engineering disciplines to study problems with large deformations, phase change, fracture, and other phenomena. ExaMPM provides a reference implementation of MPM as described in the 1994 work of Sulsky et.al. (Sulsky, Deborah, Zhen Chen, and Howard L. Schreyer. \"A particle method for history-dependent materials.\" Computer methods in applied mechanics and engineering 118.1-2 (1994): 179-196.). The software can solve basic MPM problems in solid mechanics using the original algorithm of Sulsky with explicit time integration, basic geometries, and free-slip and no-slip boundary conditions as described in the reference. ExaMPM is intended to be used as a starting point to design new parallel algorithms for the next generation of DOE supercomputers.", + "laborHours": 33911.2, + "name": "ExaMPM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ECP-copa/ExaMPM", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-copa/ExaMPM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExaPF.json b/agency-indexes/DoE/ExaPF.json new file mode 100644 index 00000000..4083bac5 --- /dev/null +++ b/agency-indexes/DoE/ExaPF.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-10-13", + "metadataLastUpdated": "2020-10-19" + }, + "description": "ExaPF is a HPC package in Julia for solving power flow (PF) on a GPU. It currently solves PF using the Newton-Raphson algorithm on NVIDA GPUs.", + "laborHours": 6080.0, + "languages": [], + "name": "ExaPF", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exanauts/EXaPF.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExaSP2.json b/agency-indexes/DoE/ExaSP2.json new file mode 100644 index 00000000..1f5ec52e --- /dev/null +++ b/agency-indexes/DoE/ExaSP2.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "ExaSP2 is a reference implementation of typical linear algebra algorithms and workloads for a quantum molecular dynamics (QMD) electronic structure code. The algorithm is based on a recursive second-order Fermi-Operator expansion method (SP2) and is tailored for density functional based tight-binding calculations of material systems.", + "laborHours": 1048.8, + "languages": [ + "C" + ], + "name": "ExaSP2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ECP-copa/ExaSP2/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-copa/ExaSP2", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExaSat:_An_Exascale_Static_Analysis_Tool__ExaSat__v1.0.json b/agency-indexes/DoE/ExaSat:_An_Exascale_Static_Analysis_Tool__ExaSat__v1.0.json new file mode 100644 index 00000000..94ee9537 --- /dev/null +++ b/agency-indexes/DoE/ExaSat:_An_Exascale_Static_Analysis_Tool__ExaSat__v1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "The ExaSAT framework automates the extraction of parameterized performance models directly from source code using compiler analysis. Its parameterized analytic model enables quantitative evaluation of a broad range of hardware design trade-offs and software optimizations on a variety of different performance metrics, with a primary focus on data movement as a metric. ExaSAT analysis provides insights in the hardware and software tradeoffs and lays the groundwork for exploring a more targeted set of design points using cycle-accurate architectural simulators and emulators.", + "laborHours": 0.0, + "languages": [ + "NA" + ], + "name": "ExaSat: An Exascale Static Analysis Tool (ExaSat) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LBL-CoDEx/exasat/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-CoDEx/exasat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExaTENSOR.json b/agency-indexes/DoE/ExaTENSOR.json new file mode 100644 index 00000000..d6209390 --- /dev/null +++ b/agency-indexes/DoE/ExaTENSOR.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "ExaTENSOR is a software math library for performing basic numerical tensor algebra operations on distributed heterogeneous HPC platforms. The library provides the following basic numerical tensor algebra primitives: tensor contraction, tensor product, tensor addition, tensor scaling by a scalar, etc. ExaTENSOR supports dense, block-sparse and hierarchical block-sparse tensors stored and processed across many heterogeneous HPC nodes (node equipped with NVIDIA GPU and Intel Xeon Phi have been considered so far). The architecture of ExaTENSOR is based on the concept of domain-specific virtual processor (DSVP), that is, an intermediate software layer capable of processing domain-specific instructions, in this case, numerical tensor algebra instructions. In this way, a separation of the domain-specific algorithm expression and hardware-agnostic algorithm execution is achieved, thus ensuring portability of the applications which use ExaTENSOR as a numerical backend.", + "laborHours": 85591.2, + "languages": [ + "Fortran 2003", + "C/C++", + "gcc-8.1", + "intel-1.8", + "xl-16.1.1" + ], + "name": "ExaTENSOR", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/ExaTENSOR", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExaTN.json b/agency-indexes/DoE/ExaTN.json new file mode 100644 index 00000000..b027bda7 --- /dev/null +++ b/agency-indexes/DoE/ExaTN.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "A challenging scientific problem that will benefit from exascale computing is predictive simulation of two- and three-dimensional quantum many-body Hamiltonians in condensed matter physics, together with the related strong entanglement problems in quantum chemistry and quantum computing. Efficient numerical simulations will require new insights into wavefunction compression algorithms that scale on extremely heterogeneous HPC architectures. To address this need, we propose to develop a scalable math library of parallel multi-linear algebraic numerical primitives for hierarchical tensor compression. Our library will subsequently be used for building an efficient, performance-portable HPC framework for simulating strongly correlated quantum systems. In particular, our will will be the first to deliver a massively parallel implementation of the multiscale entanglement renormalization ansatz (MERA), a hierarchical tensor decomposition quantum scheme capable of expressing local expectation values of strongly entangled higher-dimensional quantum systems efficiently. To address the extreme complexity and high computational cost of such schemes, we will automate their parallel implementation by delivering an integrated software framework, ExaTN (Exascale Tensor Networks), that will process hierarchical tensor representations on exascale HPC systems via an asymchronous task-based programming model. As a specific application, our framework will provide scientists with a capability of simulating strongly entangled quantum systems, thus positioning ORNL as a strategic leader in modeling of strongly correlated materials.", + "laborHours": 173097.6, + "languages": [ + "C++ using clang and/or gcc versions compliant with C++11" + ], + "name": "ExaTN", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-qci/exatn", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExactPack.json b/agency-indexes/DoE/ExactPack.json new file mode 100644 index 00000000..9edd3fe1 --- /dev/null +++ b/agency-indexes/DoE/ExactPack.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "A new version of the verification tool ExactPack, 1.7.0, includes three new solvers: A Radshocks solver, Riemann solver and an Elastic-Plastic Piston problem solver. The code has been refactored to work with Python 3. All Fortran code has been removed and solvers implemented in Fortran have been re-implemented in Python where necessary. All unit tests have been converted to use the Pytest format and all the GUI, CLI and verification analysis code has been removed.", + "laborHours": 0.0, + "languages": [], + "name": "ExactPack", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ExactPack", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExampleWDL.json b/agency-indexes/DoE/ExampleWDL.json new file mode 100644 index 00000000..a8740e3e --- /dev/null +++ b/agency-indexes/DoE/ExampleWDL.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "Example WDL app developed by KBase. ", + "laborHours": 729.6, + "languages": [], + "name": "ExampleWDL", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ExampleWDL", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Example_CIVET_recipes.json b/agency-indexes/DoE/Example_CIVET_recipes.json new file mode 100644 index 00000000..6182768a --- /dev/null +++ b/agency-indexes/DoE/Example_CIVET_recipes.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2023-03-07" + }, + "description": "Example recipes and scripts for use with CIVET (Continuous Integration, Verification, Enhancement, and Testing).", + "laborHours": 136.8, + "languages": [], + "name": "Example CIVET recipes", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/civet_example_recipes", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Example_Drops_8_Composer.json b/agency-indexes/DoE/Example_Drops_8_Composer.json new file mode 100644 index 00000000..1fe2509d --- /dev/null +++ b/agency-indexes/DoE/Example_Drops_8_Composer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "This repository can be used to set up a Composer-Managed Drupal 8 site on\u00a0Pantheon.", + "laborHours": 288.8, + "languages": [], + "name": "Example Drops 8 Composer", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/example-drops-8-composer", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Exascale-Enabled_Models_and_Algorithms_for_Microelectronics_Applications__MicroEleX__v1.json b/agency-indexes/DoE/Exascale-Enabled_Models_and_Algorithms_for_Microelectronics_Applications__MicroEleX__v1.json new file mode 100644 index 00000000..c16a6cb3 --- /dev/null +++ b/agency-indexes/DoE/Exascale-Enabled_Models_and_Algorithms_for_Microelectronics_Applications__MicroEleX__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-20", + "metadataLastUpdated": "2024-08-21" + }, + "description": "The MicroEleX code package contains a variety of models and algorithms for physical modeling of microelectronic circuitry, including electrostatics, electrodynamics, superconducting physics, micromagnetics, multi-ferroic systems, and quantum transport. MicroEleX leverages the AMReX software framework to provide scalability on GPU-based supercomputing architectures. The code is open source and designed to be algorithmically flexible so developers can incorporate enhanced or customized physics.", + "laborHours": 81669.6, + "languages": [], + "name": "Exascale-Enabled Models and Algorithms for Microelectronics Applications (MicroEleX) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Microelectronics/artemis.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Exascale-capable_cellular_automaton_for_nucleation_and_grain_growth.json b/agency-indexes/DoE/Exascale-capable_cellular_automaton_for_nucleation_and_grain_growth.json new file mode 100644 index 00000000..bef59021 --- /dev/null +++ b/agency-indexes/DoE/Exascale-capable_cellular_automaton_for_nucleation_and_grain_growth.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "This model is a cellular automata-based algorithm used to predict grain-scale microstructure development. Nucleation and growth of existing grains are considered in an initially liquid domain, where the temperature field evolution is either driven through heat transport simulation data or a frozen temperature approximation (i.e., a constant cooling rate and a fixed thermal gradient). The growth of grains is based on the decentered octahedron algorithm published by Gandin and Rappaz (https://doi.org/10.1016/S1359-6454(96)00303-5), where the grain envelopes are tracked as approximations of the evolving dendritic growth front. The input heat transport data, which can come from simulation of an arbitrary processing technique, consists of coordinates and times at which said coordinates fall below the liquidus and solidus temperatures for the final time. As a result, only the final solidification of a given region is modeled (no remelting). The code is designed to be compatible with pre-Exascale architectures, and uses MPI and the Kokkos library to decompose the computational domain and offload solidification calculations to GPUs.", + "laborHours": 0.0, + "languages": [], + "name": "Exascale-capable cellular automaton for nucleation and grain growth", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ExaCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Exascale_Dislocation_Simulator.json b/agency-indexes/DoE/Exascale_Dislocation_Simulator.json new file mode 100644 index 00000000..e23e4485 --- /dev/null +++ b/agency-indexes/DoE/Exascale_Dislocation_Simulator.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-22", + "metadataLastUpdated": "2024-04-22" + }, + "description": "ExaDiS, or Exascale Dislocation Simulator, is a set of software modules written to enable numerical\nsimulations of large groups of moving and interacting dislocations, line defects in crystals responsible for\ncrystal plasticity. By tracking time evolution of sufficiently large dislocation ensembles, ExaDiS predicts\nplasticity response and plastic strength of crystalline materials. ExaDiS is built around a library of core\nfunctions for Discrete Dislocation Dynamics method specifically written to perform efficient computations\non GPUs.", + "laborHours": 8040.8, + "languages": [], + "name": "Exascale Dislocation Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/exadis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Exascale_Julia_Grid_Optimization.json b/agency-indexes/DoE/Exascale_Julia_Grid_Optimization.json new file mode 100644 index 00000000..b5a8ca29 --- /dev/null +++ b/agency-indexes/DoE/Exascale_Julia_Grid_Optimization.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2025-02-27", + "metadataLastUpdated": "2025-02-27" + }, + "description": "Simple Julia scrips for solving AC power flow, AC optimal power flow, and security-constrained AC\noptimal power flow.\nThese scripts are intended for experimentation with different (possibly, new) methods, formulations, and\nsettings for solving these power system problem. Their implementation, therefore, intentionally avoids\nexcessive encapsulation, which makes other packages difficult to modify by non-developers.", + "laborHours": 1307.2, + "languages": [], + "name": "Exascale Julia Grid Optimization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/exajugo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Excel_to_NGDS_Services_Tool.json b/agency-indexes/DoE/Excel_to_NGDS_Services_Tool.json new file mode 100644 index 00000000..9e7f2262 --- /dev/null +++ b/agency-indexes/DoE/Excel_to_NGDS_Services_Tool.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This site allows state data contributors to standardize their data in a USIGN content model, ensure that it meets all specifications, reprojects spatial data, and creates a geodatabase that is ready for web services deployment for tier 3 data.", + "laborHours": 5608.8, + "name": "Excel to NGDS Services Tool", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/ExcelToNGDSServiceTool", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Exceptional.json b/agency-indexes/DoE/Exceptional.json new file mode 100644 index 00000000..3b9e0ffd --- /dev/null +++ b/agency-indexes/DoE/Exceptional.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "A client and server to post tracebacks to the NSLS2 DAMA slack chat.", + "laborHours": 501.6, + "languages": [], + "name": "Exceptional", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/exceptional", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExchCXX_v0.1.0.json b/agency-indexes/DoE/ExchCXX_v0.1.0.json new file mode 100644 index 00000000..33f502fd --- /dev/null +++ b/agency-indexes/DoE/ExchCXX_v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-01", + "metadataLastUpdated": "2021-03-01" + }, + "description": "ExchCXX is a modern C++ library for the evaluation of exchange-correlation (XC) functionals required for density functional theory (DFT) calculations. In addition to providing high-level wrappers for the ubiquitous Libxc library for the CPU evaluation of XC functionals, ExchCXX also provides locally developed implementations of a small subset of XC functionals which may be evaluated either on the host (CPU) or device (GPU, FPGA, etc).", + "laborHours": 0.0, + "languages": [], + "name": "ExchCXX v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wavefunction91/ExchCXX", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExoToComsol_v.0.1.json b/agency-indexes/DoE/ExoToComsol_v.0.1.json new file mode 100644 index 00000000..d6b413c5 --- /dev/null +++ b/agency-indexes/DoE/ExoToComsol_v.0.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08641O\nExoToComsol models capability-sharing. For example, the software can develop a multiphysics modeling chain using physics modeling capabilities from different research institutions using either SIERRA or COMSOL. The converter program allows exporting user-defined, region-of-interest from a large FE model, which results in a finer mesh of the submodel that can be used for subsequent analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 152.0, + "languages": [ + "python" + ], + "name": "ExoToComsol v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ExoToComsol", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Exodiff_v._2.09.json b/agency-indexes/DoE/Exodiff_v._2.09.json new file mode 100644 index 00000000..e0eee1e7 --- /dev/null +++ b/agency-indexes/DoE/Exodiff_v._2.09.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-11" + }, + "description": "Exodiff compares the results data from two Exodus II files. By defult, a relative difference is used with a tolerance of 1.-6 (about 6 significant digits). The nodal locations are also compared using an absolute difference with a tolerance of 1.e-6. Time step values are compared using a relative difference with a tolerance of 1.e-6 and a floor of 1.e-15. If a third file [diffile.exo] is given, then it is overwritten with the difference of the two files.", + "laborHours": 692284.0, + "languages": [], + "name": "Exodiff v. 2.09", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Exomerge_v._8.0.json b/agency-indexes/DoE/Exomerge_v._8.0.json new file mode 100644 index 00000000..e899cc34 --- /dev/null +++ b/agency-indexes/DoE/Exomerge_v._8.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Exomerge is a lightweight Python interface for manipulating ExodusII files.", + "laborHours": 4377.6, + "languages": [ + "Shell", + "Python" + ], + "name": "Exomerge v. 8.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/exomerge", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "8.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExpM+NF_MIMIC_III_experiments.json b/agency-indexes/DoE/ExpM+NF_MIMIC_III_experiments.json new file mode 100644 index 00000000..a5365bac --- /dev/null +++ b/agency-indexes/DoE/ExpM+NF_MIMIC_III_experiments.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bridgesra@ornl.gov" + }, + "date": { + "created": "2024-06-11", + "metadataLastUpdated": "2024-06-11" + }, + "description": "This code allows reproduction of results in the paper\n\n\"Are Normalizing Flows the Key to Unlocking the Exponential Mechanism? \" https://arxiv.org/abs/2311.09200\n\nThe code here provides implementation of our experiments where we test if we can training models with ExpM+NF alongside and in comparison with DPSGD and non-private training.", + "laborHours": 21994.4, + "languages": [], + "name": "ExpM+NF MIMIC III experiments", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bridgesra/expm_nf_mimic3_results_code", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Experimental_Physics_and_Industrial_Control_System_BASE.json b/agency-indexes/DoE/Experimental_Physics_and_Industrial_Control_System_BASE.json new file mode 100644 index 00000000..42d0ab96 --- /dev/null +++ b/agency-indexes/DoE/Experimental_Physics_and_Industrial_Control_System_BASE.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "EPICS is a set of software tools and applications developed initially by the Los Alamos National Laboratories for the control of large accelerators, enhanced by contributions from users worldwide and continuing development for application to other large scientific experimental equipment, such as telescopes and detectors. EPICS consists of EPICS BASE, Extensions, and other unbundled modules. EPICS BASE marks a change in the handling of the distribution of the software starting with the EPICS BASE 3.13.7 AND 3.140beta2 software.", + "laborHours": 138928.0, + "name": "Experimental Physics and Industrial Control System BASE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/epics-base/epics-base/blob/3.16/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/epics-base/epics-base", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Explainable_Neural_Architecture_Search__XNAS_.json b/agency-indexes/DoE/Explainable_Neural_Architecture_Search__XNAS_.json new file mode 100644 index 00000000..51a174e6 --- /dev/null +++ b/agency-indexes/DoE/Explainable_Neural_Architecture_Search__XNAS_.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-03", + "metadataLastUpdated": "2022-03-03" + }, + "description": "Code for the paper Learning Interpretable Models Through Multi-Objective Neural Architecture Search by Zachariah Carmichael, Tim Moon, and Sam Ade Jacobs. Monumental advances in deep learning have led to unprecedented achievements across a multitude of domains. While the performance of deep neural networks is indubitable, the architectural design and interpretability of such models are nontrivial. Research has been introduced to automate the design of neural network architectures through neural architecture search (NAS). Recent progress has made these methods more pragmatic by exploiting distributed computation and novel optimization algorithms. However, there is little work in optimizing architectures for interpretability. To this end, we propose a multiobjective distributed NAS framework that optimizes for both task performance and introspection. We leverage the non-dominated sorting genetic algorithm (NSGA-II) and explainable AI (XAI) techniques to reward architectures that can be better comprehended by humans. The framework is evaluated on several image classification datasets. We demonstrate that jointly optimizing for introspection ability and task error leads to more disentangled architectures that perform within tolerable error.", + "laborHours": 0.0, + "languages": [], + "name": "Explainable Neural Architecture Search (XNAS)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/XNAS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Exploit,_Malware_And_Vulnerability_Scoring_Application.json b/agency-indexes/DoE/Exploit,_Malware_And_Vulnerability_Scoring_Application.json new file mode 100644 index 00000000..cf72d5cf --- /dev/null +++ b/agency-indexes/DoE/Exploit,_Malware_And_Vulnerability_Scoring_Application.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-07-09", + "metadataLastUpdated": "2023-03-08" + }, + "description": "Exploit, Malware and Vulnerability (EMV) is a way for users to create and use their own scoring schema against various configurations they might be scoring cyber issues against. This application was created to take the EMV process and develop a GUI to accomplish this task. EMV application is customizable and configurable, interfaces with STIX objects and allows exporting scored objects.", + "laborHours": 2903.2, + "languages": [ + "TypeScript" + ], + "name": "Exploit, Malware And Vulnerability Scoring Application", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/EMV", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Exploration_ToolKit__ExTK_.json b/agency-indexes/DoE/Exploration_ToolKit__ExTK_.json new file mode 100644 index 00000000..35d8fa64 --- /dev/null +++ b/agency-indexes/DoE/Exploration_ToolKit__ExTK_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-06", + "metadataLastUpdated": "2021-09-21" + }, + "description": "The Exploration Toolkit (ExTK) is a reusable Extended Reality (XR) system developed for incorporating and exploring 3-Dimensional (3-D) computer aided design (CAD) models in XR, with a primary focus on Augmented Reality (AR). The ExTK consists of a Developer Mode and a User Mode. In Developer Mode, ExTK provides developers with the ability to easily import 3-D CAD models and activate desired exploration functionality and layout. Multiple models can be added to a single instantiation of the ExTK using Unity's Scene capability. Exploration functions include scaling, rotating, explode/contract, animations, hiding parts, submodules, and measurement functions. In User Mode, ExTK provides a menu system that allows users to select models and initiate exploration functions. ExTK is architected for reusability and developers can customize the ExTK layout and functions according to application needs. ExTK is designed to be hardware agnostic, although initial development focused on the Microsoft HoloLens as the primary deployment platform. The ExTK is developed using the Unity Game Engine Development Platform. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1506 O", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Exploration ToolKit (ExTK)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ExTK", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Exploring_the_Design_Space_of_Static_and_Incremental_Graph_Connectivity_Algorithms_on_GPUs.json b/agency-indexes/DoE/Exploring_the_Design_Space_of_Static_and_Incremental_Graph_Connectivity_Algorithms_on_GPUs.json new file mode 100644 index 00000000..c1c880ed --- /dev/null +++ b/agency-indexes/DoE/Exploring_the_Design_Space_of_Static_and_Incremental_Graph_Connectivity_Algorithms_on_GPUs.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nChangwan Hong, Laxman Dhulipala, and Julian Shun.\nExploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs.\nProceedings of International Conference on Parallel Architectures and Compilation Techniques (PACT), pp. 55-69, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "Exploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hochawa/gconn", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExpressionAPI.json b/agency-indexes/DoE/ExpressionAPI.json new file mode 100644 index 00000000..53c8ea89 --- /dev/null +++ b/agency-indexes/DoE/ExpressionAPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "To get ExpressionMatrix object from Expressionset object.", + "laborHours": 532015.2, + "languages": [], + "name": "ExpressionAPI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ExpressionAPI", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ExpressionUtils.json b/agency-indexes/DoE/ExpressionUtils.json new file mode 100644 index 00000000..ffd6b5c5 --- /dev/null +++ b/agency-indexes/DoE/ExpressionUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "Functions for uploading and downloading KBase expression files. A module to upload, download and export RNASeq Expression data obtained by either StringTie or Cufflinks Apps.", + "laborHours": 24000.8, + "languages": [], + "name": "ExpressionUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ExpressionUtils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Expression_Services.json b/agency-indexes/DoE/Expression_Services.json new file mode 100644 index 00000000..f402ef68 --- /dev/null +++ b/agency-indexes/DoE/Expression_Services.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This service has methods to retrieve data and metadata for expression samples.\nThere are also methods to do comparisons (custom, vs default, vs average of samples), get top changers and get on off calls. There are at least 30 functions.", + "laborHours": 18756.8, + "languages": [], + "name": "Expression Services", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/expression", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Extensible_Computational_Chemistry_Environment.json b/agency-indexes/DoE/Extensible_Computational_Chemistry_Environment.json new file mode 100644 index 00000000..be2a89d0 --- /dev/null +++ b/agency-indexes/DoE/Extensible_Computational_Chemistry_Environment.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ECCE provides a sophisticated graphical user interface, scientific visualization tools, and the underlying data management framework enabling scientists to efficiently set up calculations and store, retrieve, and analyze the rapidly growing volumes of data produced by computational chemistry studies. ECCE was conceived as part of the Environmental Molecular Sciences Laboratory construction to solve the problem of researchers being able to effectively utilize complex computational chemistry codes and massively parallel high performance compute resources. Bringing the power of these codes and resources to the desktops of researcher and thus enabling world class research without users needing a detailed understanding of the inner workings of either the theoretical codes or the supercomputers needed to run them was a grand challenge problem in the original version of the EMSL. ECCE allows collaboration among researchers using a web-based data repository where the inputs and results for all calculations done within ECCE are organized. ECCE is a first of kind end-to-end problem solving environment for all phases of computational chemistry research: setting up calculations with sophisticated GUI and direct manipulation visualization tools, submitting and monitoring calculations on remote high performance supercomputers without having to be familiar with the details of using these compute resources, and performing results visualization and analysis including creating publication quality images. ECCE is a suite of tightly integrated applications that are employed as the user moves through the modeling process.", + "laborHours": 450421.6, + "name": "Extensible Computational Chemistry Environment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mattbernst/ECCE/blob/master/ecce-v7.0/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mattbernst/ECCE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Extract_Bandwidth_Statistical_Properties.json b/agency-indexes/DoE/Extract_Bandwidth_Statistical_Properties.json new file mode 100644 index 00000000..417f1627 --- /dev/null +++ b/agency-indexes/DoE/Extract_Bandwidth_Statistical_Properties.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "This is the script to calculate higher-order spectral densities.", + "laborHours": 0.0, + "languages": [], + "name": "Extract Bandwidth Statistical Properties", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SpectralDensities", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Extreme_SeaState_Contour_v1.json b/agency-indexes/DoE/Extreme_SeaState_Contour_v1.json new file mode 100644 index 00000000..35103367 --- /dev/null +++ b/agency-indexes/DoE/Extreme_SeaState_Contour_v1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "This software generates environmental contours of extreme sea states using buoy observations of significant wave height and energy period or peak period. The code transforms these observations using principal component analysis (PCA) to create an uncorrelated representation of the data. The subsequent components are modeled using probability distributions and parameter fitting functions. The inverse first-order reliability method (I-FORM) is then applied to these models in order to generate an extreme event contour based on a given return period (i.e., 100 years).The subsequent contour is then transformed back into the original input space defined by the variables of interest in order to create an environmental contour of extreme sea states.", + "laborHours": 197.6, + "languages": [ + "MATLAB" + ], + "name": "Extreme_SeaState_Contour_v1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SNL-ESSC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Extremum_Seeking_Library__ESL__v1.0.json b/agency-indexes/DoE/Extremum_Seeking_Library__ESL__v1.0.json new file mode 100644 index 00000000..91e4f2ac --- /dev/null +++ b/agency-indexes/DoE/Extremum_Seeking_Library__ESL__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-16", + "metadataLastUpdated": "2019-12-16" + }, + "description": "The software developed is a library for the Modelica language. The library includes different extremum seeking control algorithms and examples of possible usecases. It is also intended to export the models as so called Functional Mock-up Units, which are models supported by any kind of software which supports the Functional Mock-up Interface standard.", + "laborHours": 15.2, + "languages": [], + "name": "Extremum Seeking Library (ESL) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/ESL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EyeON.json b/agency-indexes/DoE/EyeON.json new file mode 100644 index 00000000..a62c04f0 --- /dev/null +++ b/agency-indexes/DoE/EyeON.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-12-23", + "metadataLastUpdated": "2024-12-23" + }, + "description": "EyeON: Eye on Operational technology\nSoftware Supply Chain attacks have risen drastically over the past few years, none more well-known and\nimpactful than the SolarWinds compromise. Criminal organizations inserted an attack vector into a\nspecific version of the source code, giving themselves an air of credibility. Once news broke on\nSolarWinds, identifying compromised sites was very difficult, even knowing the culprit update.\nSoftware Bills of Materials (SBOM) have been touted as the solution to reclaiming control of your software\nsupply chain. Deployment of SBOMs has been slow, however, due to conflicting standards, opaque\nstorage requirements, and vendor adoption. Additionally, the path from obtaining an SBOM and securing\nyour supply chain is unclear; how can an SBOM library be leveraged to provide insight to your attack\nsurface? The EyeON tool, sponsored by Department of Energy Cybersecurity, Energy Security, and\nEmergency Response (DoE CESER), aims to address these gaps by providing an encapsulated solution\nto tracking which updates have been installed in an enterprise, and alerting system administrators to\nvulnerabilities as they become known.\nSimilar to a virus scanner, EyeON is a command line tool to parse either a single file, nested directory\nstructure, or filesystem. It collects data such as signature (hashes), version information, VirusTotal tags,\ncompiler, compilation date, and code signing information. Users will anonymously submit scan data\nperiodically to DoE CESER, who will then compile a database of known software products employed by\nCritical Infrastructure and broadcast alerts based on discovered flaws as they arise.", + "laborHours": 1580.8, + "languages": [], + "name": "EyeON", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pEyeON", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/EzGet.json b/agency-indexes/DoE/EzGet.json new file mode 100644 index 00000000..b473328c --- /dev/null +++ b/agency-indexes/DoE/EzGet.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "EzGet facilitates retrieval of data stored in popular formats (including DRS, netCDF, GrADS, and if a control file is supplied, GRIB). EzGET (pronounced\neasy-get) is specifically designed to access climate data and climate model output. You can specify how the data should be structured and whether it should undergo a grid transformation before you receive it, even when you know little about the structure of the stored data (i.e., its dimension order, grid, and domain).", + "laborHours": 9484.8, + "languages": [], + "name": "EzGet", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/EzGet", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/F-ANOVA.json b/agency-indexes/DoE/F-ANOVA.json new file mode 100644 index 00000000..a0cc3474 --- /dev/null +++ b/agency-indexes/DoE/F-ANOVA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-12-15", + "metadataLastUpdated": "2023-12-15" + }, + "description": "Class and supporting functions to utilize an object oriented approach to F-ANOVA", + "laborHours": 0.0, + "languages": [], + "name": "F-ANOVA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/F-ANOVA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/F3C++_v0.1.json b/agency-indexes/DoE/F3C++_v0.1.json new file mode 100644 index 00000000..b65ea3fb --- /dev/null +++ b/agency-indexes/DoE/F3C++_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-06" + }, + "description": "Fast Free Fermion Compiler (F3C) is an application-specific quantum circuit compiler for time-evolution circuits of spin Hamiltonian systems that can be mapped to free fermions.", + "laborHours": 0.0, + "languages": [], + "name": "F3C++ v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QuantumComputingLab/f3cpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/F3C_v0.1.json b/agency-indexes/DoE/F3C_v0.1.json new file mode 100644 index 00000000..7c186eb3 --- /dev/null +++ b/agency-indexes/DoE/F3C_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-06" + }, + "description": "Fast Free Fermion Compiler (F3C) is an application-specific quantum circuit compiler for time-evolution circuits of spin Hamiltonian systems that can be mapped to free fermions. F3C is the Matlab software version and the related F3C++ is the C++ software version.", + "laborHours": 0.0, + "languages": [], + "name": "F3C v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QuantumComputingLab/f3c", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/F3D_Image_Processing_and_Analysis_for_Many_-_and_Multi-core_Platforms.json b/agency-indexes/DoE/F3D_Image_Processing_and_Analysis_for_Many_-_and_Multi-core_Platforms.json new file mode 100644 index 00000000..e8e46c30 --- /dev/null +++ b/agency-indexes/DoE/F3D_Image_Processing_and_Analysis_for_Many_-_and_Multi-core_Platforms.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "F3D is written in OpenCL, so it achieve[sic] platform-portable parallelism on modern mutli-core CPUs and many-core GPUs. The interface and mechanims to access F3D core are written in Java as a plugin for Fiji/ImageJ to deliver several key image-processing algorithms necessary to remove artifacts from micro-tomography data. The algorithms consist of data parallel aware filters that can efficiently utilizes[sic] resources and can work on out of core datasets and scale efficiently across multiple accelerators. Optimizing for data parallel filters, streaming out of core datasets, and efficient resource and memory and data managements over complex execution sequence of filters greatly expedites any scientific workflow with image processing requirements. F3D performs several different types of 3D image processing operations, such as non-linear filtering using bilateral filtering and/or median filtering and/or morphological operators (MM). F3D gray-level MM operators are one-pass constant time methods that can perform morphological transformations with a line-structuring element oriented in discrete directions. Additionally, MM operators can be applied to gray-scale images, and consist of two parts: (a) a reference shape or structuring element, which is translated over the image, and (b) a mechanism, or operation, that defines the comparisons to be performed between the image and the structuring element. This tool provides a critical component within many complex pipelines such as those for performing automated segmentation of image stacks. F3D is also called a \"descendent\" of Quant-CT, another software we developed in the past. These two modules are to be integrated in a next version. Further details were reported in: D.M. Ushizima, T. Perciano, H. Krishnan, B. Loring, H. Bale, D. Parkinson, and J. Sethian. Structure recognition from high-resolution images of ceramic composites. IEEE International Conference on Big Data, October 2014.", + "laborHours": 1869.6, + "name": "F3D Image Processing and Analysis for Many - and Multi-core Platforms", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/CameraIA/F3D/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CameraIA/F3D", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FABLE_-_automatic_Fortran_to_C++_conversion.json b/agency-indexes/DoE/FABLE_-_automatic_Fortran_to_C++_conversion.json new file mode 100644 index 00000000..8df57296 --- /dev/null +++ b/agency-indexes/DoE/FABLE_-_automatic_Fortran_to_C++_conversion.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "FABLE is a Fortran to C++ source-to-source conversion tool. This enables the continued development of new methods even while switching programming languages. FABLE is available under a nonrestrictive open source license. In FABLE the analysis of the Fortran source is separated from the generation of the C++ source. Therefore parts of FABLE could be reused for other target languages. Hardware req.: Multi-platform; types of files: source code, sample problem Input data, sample problem output, installation instructions, user guide.", + "laborHours": 0.0, + "languages": [ + "fortran" + ], + "name": "FABLE - automatic Fortran to C++ conversion", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cctbx/cctbx_project/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cctbx/cctbx_project", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FABLE_v0.1.json b/agency-indexes/DoE/FABLE_v0.1.json new file mode 100644 index 00000000..11974598 --- /dev/null +++ b/agency-indexes/DoE/FABLE_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "FABLE is a s light-weight software package for easy generation of quantum circuits that block encode arbitrary matrices.", + "laborHours": 0.0, + "languages": [], + "name": "FABLE v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QuantumComputingLab/fable", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FAODEL.json b/agency-indexes/DoE/FAODEL.json new file mode 100644 index 00000000..aea21105 --- /dev/null +++ b/agency-indexes/DoE/FAODEL.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-04-12", + "metadataLastUpdated": "2021-08-16" + }, + "description": "FAODEL is a collection of libraries for implementing data management services on high-performance computing (HPC) platforms. It is composed of several components: (1) an RDMA portability library called NNTI for transporting data, (2) an in-application, restful API service, (3) a memory management library for network memory named Lunasa, (4) an asynchronous communication engine, and (5) a distributed key/blob service names Kelpie. Application developers may use these libraries to move data between the distributed nodes of one job to another, as well as to distributed storage resources. FAODEL is different than other communication libraries in that it supports both intra- and inter-job communication, features event-driven mechanisms, and provides high-level primitives for developers to reason about a platform\u2019s distributed resources.", + "laborHours": 108558.4, + "languages": [], + "name": "FAODEL", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/faodel/faodel", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2108.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FAR3d.json b/agency-indexes/DoE/FAR3d.json new file mode 100644 index 00000000..dacf4b38 --- /dev/null +++ b/agency-indexes/DoE/FAR3d.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "spongda@ornl.gov" + }, + "date": { + "created": "2024-09-24", + "metadataLastUpdated": "2024-10-18" + }, + "description": "The FAR3d model calculates the linear and nonlinear stability properties of energetic particle driven Alfven instabilities for both\ntokamak and stellarator plasma confinement devices using gyro-landau closure methods. This is an important fundamental\nphysics problem for existing fusion energy experiments and for future fusion reactors.", + "laborHours": 16492.0, + "languages": [ + "Fortran" + ], + "name": "FAR3d", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DSfusion/FAR3d", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FAST.Farm_[SWR-17-56].json b/agency-indexes/DoE/FAST.Farm_[SWR-17-56].json new file mode 100644 index 00000000..ca560579 --- /dev/null +++ b/agency-indexes/DoE/FAST.Farm_[SWR-17-56].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-09-29" + }, + "description": "FAST.Farm is a multi-physics engineering tool for predicting the performance and loads of wind turbines within a wind farm. FAST.Farm uses FAST to solve the aero-hydro-servo-elastic dynamics of an individual turbine, but adds additional physics for wind farm-wide ambient wind in the atmospheric boundary layer; a wind-farm super controller; and wake deficits, advection, deflection, meandering, and merging. FAST.Farm is based on the principles of the Dynamic Wake Meandering (DWM) model\u2014including passive tracer modeling of wake meandering\u2014but addresses many of the limitations of previous DWM limitations. FAST.Farm maintains a low computational cost to the often highly iterative and probabilistic design process. Applications of FAST.Farm include reducing wind farm underperformance and loads uncertainty, developing wind farm controls to enhance operation, optimizing wind farm siting and topology, and innovating the design of wind turbines for the wind-farm environment.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "FAST.Farm [SWR-17-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/farms", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FASTQ_quality_control_dashboard.json b/agency-indexes/DoE/FASTQ_quality_control_dashboard.json new file mode 100644 index 00000000..6322218d --- /dev/null +++ b/agency-indexes/DoE/FASTQ_quality_control_dashboard.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "FQCDB builds up existing open source software, FastQC, implementing a modern web interface for across parsed output of FastQC. In addition, FQCDB is extensible as a web service to include additional plots of type line, boxplot, or heatmap, across data formatted according to guidelines. The interface is also configurable via more readable JSON format, enabling customization by non-web programmers.", + "laborHours": 56376.8, + "name": "FASTQ quality control dashboard", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/brwnj/fqc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FAST_-_A_Framework_for_Agile_Software_Testing_v._2.0.json b/agency-indexes/DoE/FAST_-_A_Framework_for_Agile_Software_Testing_v._2.0.json new file mode 100644 index 00000000..d5516943 --- /dev/null +++ b/agency-indexes/DoE/FAST_-_A_Framework_for_Agile_Software_Testing_v._2.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The FAST software package contains a variety of Python packages for applying and managing software tests. In version 2.0, FAST includes (1) the EXACT package, which supports the definition and execution of computational experiments, (2) the FAST package, which manages the distributed execution of software builds, and (3) general tools related to the PyUnit testing framework.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "FAST - A Framework for Agile Software Testing v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://software.sandia.gov/trac/fast/wiki/Licensing", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fast", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FAST_Simulation_Tool_Containing_Methods_for_Predicting_the_Dynamic_Response_of_Wind_Turbines.json b/agency-indexes/DoE/FAST_Simulation_Tool_Containing_Methods_for_Predicting_the_Dynamic_Response_of_Wind_Turbines.json new file mode 100644 index 00000000..0e6a2ba5 --- /dev/null +++ b/agency-indexes/DoE/FAST_Simulation_Tool_Containing_Methods_for_Predicting_the_Dynamic_Response_of_Wind_Turbines.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "FAST is a simulation tool (computer software) for modeling tlie dynamic response of horizontal-axis wind turbines. FAST employs a combined modal and multibody structural-dynamics formulation in the time domain.", + "laborHours": 0.0, + "languages": [ + "Fortran", + "C", + "MATLAB (for Simulink interface)" + ], + "name": "FAST Simulation Tool Containing Methods for Predicting the Dynamic Response of Wind Turbines", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/OpenFAST/openfast", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FAST__FAST_AUTONOMOUS_SCANNING_TOOLKIT_.json b/agency-indexes/DoE/FAST__FAST_AUTONOMOUS_SCANNING_TOOLKIT_.json new file mode 100644 index 00000000..e5df0085 --- /dev/null +++ b/agency-indexes/DoE/FAST__FAST_AUTONOMOUS_SCANNING_TOOLKIT_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-18" + }, + "description": "SF-23-006 FAST (FAST AUTONOMOUS SCANNING TOOLKIT)The software is deployed on an edge computing device at the beamline computer attached to a \nscanning microscope. It iteratively analyzes the data collected, then identifies new scan positions \nto scan next and directs the positioners that move the sample (or probe beam) to these positions. \nOverall, it identifies a sparse set of scan positions that are sufficient to image the full sample. \nThis can reduce the scan time by >60%.\n\n", + "laborHours": 0.0, + "languages": [], + "name": "FAST (FAST AUTONOMOUS SCANNING TOOLKIT)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/saugatkandel/fast_smart_scanning", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FBAFileUtil.json b/agency-indexes/DoE/FBAFileUtil.json new file mode 100644 index 00000000..914f19e2 --- /dev/null +++ b/agency-indexes/DoE/FBAFileUtil.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "Functions for accessing and saving KBase FBA related data as files.", + "laborHours": 31524.8, + "languages": [], + "name": "FBAFileUtil", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/FBAFileUtil", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FBMPI.json b/agency-indexes/DoE/FBMPI.json new file mode 100644 index 00000000..42aef789 --- /dev/null +++ b/agency-indexes/DoE/FBMPI.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-09", + "metadataLastUpdated": "2022-10-09" + }, + "description": "SAND2022-3387 O FallBack MPI (FBMPI) is a fallback implementation of the Message Passing Interface (MPI) which is used in high performance computing software. FBMPI ensures that MPI is always present so that high performance computing software does not need to spend funding on the use case where MPI is not present. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "FBMPI", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fbmpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FEASTPACK_v._1.0.json b/agency-indexes/DoE/FEASTPACK_v._1.0.json new file mode 100644 index 00000000..31b4ef46 --- /dev/null +++ b/agency-indexes/DoE/FEASTPACK_v._1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software implements the generative graph algorithm described in the following reference: T. G. Kolda, A. Pinar, T. Plantenga and C. Seshadhri. A Scalable Generative Graph Model with Community Structure, arXiv:1302.6636, March 2013, http:l/arxiv.org/abs/1302.6636. The software also implements the clustering coefficient algorithms described in C. Seshadhri, A. Pinar and T. G. Kolda. Triadic Measures on Graphs: The Power of Wedge Sampling, in Proc. 2013 SIAM International Conference on Data Mining {SDM), May 2013.", + "laborHours": 0.0, + "languages": [], + "name": "FEASTPACK v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/feastpack", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/FEDIS__The_\342\200\234Fresnel_Equations\342\200\235_for_Diffuse_radiation_on_Inclined_photovoltaic_Surfaces__[SWR-22-64].json" "b/agency-indexes/DoE/FEDIS__The_\342\200\234Fresnel_Equations\342\200\235_for_Diffuse_radiation_on_Inclined_photovoltaic_Surfaces__[SWR-22-64].json" new file mode 100644 index 00000000..f5133820 --- /dev/null +++ "b/agency-indexes/DoE/FEDIS__The_\342\200\234Fresnel_Equations\342\200\235_for_Diffuse_radiation_on_Inclined_photovoltaic_Surfaces__[SWR-22-64].json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-08-24", + "metadataLastUpdated": "2023-04-24" + }, + "description": "The well-known Fresnel equations solve for the reflection and transmission of light for precise incident angles. The transmission of diffuse radiation incident on a planar or domed surface is often needed for real-world applications. Due to the complexity of the Fresnel equations, the analytical solution of the integration has hitherto been unobtainable over the last centuries. Therefore, this problem was numerically solved by integrating the angular transmittances in space often leading to substantial computing burden and bias in the results. To efficiently estimate the solar energy resource for a glass-covered photovoltaic (PV) module, we derive an analytical solution of diffuse transmission based on the rigorous integration of an alternate form of the Fresnel equations. The approach leads to a simple yet accurate relative transmittance model that reconciles the solar energy sensed by pyranometers and PV panels. With limited and clearly stated approximations, the complex mathematical derivation resulted in an elegant solution.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "FEDIS (The \u201cFresnel Equations\u201d for Diffuse radiation on Inclined photovoltaic Surfaces) [SWR-22-64]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/FEDIS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FEDS.json b/agency-indexes/DoE/FEDS.json new file mode 100644 index 00000000..b016bb9d --- /dev/null +++ b/agency-indexes/DoE/FEDS.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-06-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An easy to use tool for identifying energy saving retrofits for buildings.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "FEDS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "8" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FEHM_V3.0_-_V3.X.json b/agency-indexes/DoE/FEHM_V3.0_-_V3.X.json new file mode 100644 index 00000000..64b18d2c --- /dev/null +++ b/agency-indexes/DoE/FEHM_V3.0_-_V3.X.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-03-30", + "metadataLastUpdated": "2018-04-06" + }, + "description": "The numerical background of the FEHM computer code can be traced to the early 1970s when it was used to simulate geothermal and hot dry rock reservoirs. The primary use over a number of years was to assist in the understanding of flow fields and mass transport in the saturated and unsaturated zones below the potential Yucca Mountain repository. Today FEHM is used to simulate groundwater and contaminant flow and transport in deep and shallow, fractured and un-fractured porous media throughout the US DOE complex. FEHM has proved to be a valuable asset on a variety of projects of national interest including Environmental Remediation of the Nevada Test Site, the LANL Groundwater Protection Program, geologic CO2 sequestration, Enhanced Geothermal Energy (EGS) programs, Oil and Gas production, Nuclear Waste Isolation, and Arctic Permafrost. Subsurface physics has ranged from single fluid/single phase fluid flow when simulating basin scale groundwater aquifers to complex multifluid/ multi-phase fluid flow that includes phase change with boiling and condensing in applications such as unsaturated zone surrounding nuclear waste storage facility or leakage of CO2/brine through faults or wellbores. The numerical method used in FEHM is the control volume method (CV) for fluid flow and heat transfer equations which allows FEHM to exactly enforce energy/mass conservation; while an option is available to use the finite element (FE) method for displacement equations to obtain more accurate stress calculations. In addition to these standard methods, an option to use FE for flow is available, as well as a simple Finite Difference scheme.", + "laborHours": 1601304.8, + "name": "FEHM V3.0 - V3.X", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/FEHM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FEMP_Cyber_Security_Arsenal.json b/agency-indexes/DoE/FEMP_Cyber_Security_Arsenal.json new file mode 100644 index 00000000..cf819fa4 --- /dev/null +++ b/agency-indexes/DoE/FEMP_Cyber_Security_Arsenal.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The FEMP Cyber Security Arsenal is a family of cyber security tools for the federal facility owners and operators. Using these tools, facility owners can evaluate their overall cybersecurity posture. These tools are web-based front-end tools. This is an upgrade of the tools available from the earlier version in DOE CODE ID: #41457", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "FEMP Cyber Security Arsenal", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FEMP_Cybersecurity_Arsenal.json b/agency-indexes/DoE/FEMP_Cybersecurity_Arsenal.json new file mode 100644 index 00000000..dddf220b --- /dev/null +++ b/agency-indexes/DoE/FEMP_Cybersecurity_Arsenal.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-25", + "metadataLastUpdated": "2025-02-25" + }, + "description": "The FEMP Cyber Security Arsenal is a family of cyber security tools for the federal facility owners and operators. Using these tools, facility owners can evaluate their overall cybersecurity posture. These tools are web-based front-end tools. The tools are meant to help federal owners and operators to evaluate their overall cybersecurity posture. These tools are developed based on the NIST Cybersecurity framework, risk management framework, and DOE C2M2 architectures. Version 3 provides significant updates and features in ten areas", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 126038.4, + "languages": [], + "name": "FEMP Cybersecurity Arsenal", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FENATE.json b/agency-indexes/DoE/FENATE.json new file mode 100644 index 00000000..b2bf2fe6 --- /dev/null +++ b/agency-indexes/DoE/FENATE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "FENATE: Fast Evaluation of Network Architecture -- Toolchain and Environment. Our framework is comprised of scalable\ntools to both skeletonize and simulate MPI communication patterns providing a functional view of the network under\ninvestigation (trading off accuracy for speed)", + "laborHours": 0.0, + "languages": [], + "name": "FENATE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/FENATE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FESTIV__Flexible_Energy_Scheduling_Tool_for_Integrating_Variable_generation_.json b/agency-indexes/DoE/FESTIV__Flexible_Energy_Scheduling_Tool_for_Integrating_Variable_generation_.json new file mode 100644 index 00000000..0125f2df --- /dev/null +++ b/agency-indexes/DoE/FESTIV__Flexible_Energy_Scheduling_Tool_for_Integrating_Variable_generation_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-04-03", + "metadataLastUpdated": "2019-04-03" + }, + "description": "Flexible Energy Scheduling Tool for Integrating Variable generation (FESTIV) is a tool that simulates the realistic representation of steady-state power system operations and scheduling performed by an independent system operator, regional transmission organization, or a vertically integrated regulated utility. The tool integrates security-constrained unit commitment (SCUC), security-constrained economic dispatch (SCED), and automatic generation control (AGC) into one model. These are the three modes of power system scheduling that are used to meet the changing net demand. Each of these submodels have different time characteristics and are used to meet the changing demand at different time resolutions and horizons. This allows multiple timescales to be studied where FESTIV accounts for intertemporal coupling between each submodel and the submodels themselves. It does this while having different objectives between the submodels; commitment of resources, dispatch and reserve commitment, and finally control.", + "laborHours": 10488.0, + "languages": [], + "name": "FESTIV (Flexible Energy Scheduling Tool for Integrating Variable generation)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/FESTIV_MODEL", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FESTR,_Version_0.x.json b/agency-indexes/DoE/FESTR,_Version_0.x.json new file mode 100644 index 00000000..14bfb2a1 --- /dev/null +++ b/agency-indexes/DoE/FESTR,_Version_0.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "FESTR is a modeling tool for calculating spectroscopic-quality synthetic outputs (e.g., spectra and images) based on (in general) the time evolutions of 3-D spatial distributions of materials characterized by their chemical composition, temperature, and density conditions. FESTR performs raytracing across unstructured meshes, builds intrinsic optical properties of mixed materials by performing equation-of-state lookups in external data, and then solves the radiation-transport equation along rays to obtain emergent time and space resolved synthetic spectra. These results can be further processed into time and/or space integrated spectra, as well as into spectral-band-integrated synthetic images, radiated power histories, and total radiated energy values. FESTR is also applicable to spatial reconstructions of material properties via the analysis of experimental data.", + "laborHours": 70376.0, + "name": "FESTR, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LANLhakel/FESTR/blob/d5a8941f2e74fb0adc8b12a90180b299b95dc93e/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANLhakel/FESTR", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FEVER_Probe_Design_Algorithm.json b/agency-indexes/DoE/FEVER_Probe_Design_Algorithm.json new file mode 100644 index 00000000..cbd9afaf --- /dev/null +++ b/agency-indexes/DoE/FEVER_Probe_Design_Algorithm.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Here we have developed a pipeline for the fast evaluation of viral emerging risks (FEVER) that generates primer and probe sets for genetically diverse viruses. The goal of probe design is to produce a short nucleotide sequence (called a K-mer, as it is of length K) that reacts with SARS-CoV-2 without also reacting to background material that may be present in the sample that is being tested. Other desirable properties of the probe, making it more effective in the experimental setup, include maintaining a high G/C content and reducing the \"hairpin propensity\" (ie, the tendency of the probe string to fold over on itself) by ensuring that any self-complementary pairs of sub-strings in the probe are sufficiently short. The mathematical formalization of the problem is expressed in terms of a constrained optimization, with G/C content and length of self-complementary sub-strings taken as constraints, while maximizing coverage of the probe. A probe is said to \"cover\" a SARS-CoV-2 sequence if the probe's K-mer appears as a sub-sequence of that sequence. Thus, coverage is defined as the number of sequences in the database that are covered by the probe. \"Exact\" coverage corresponds to an exact match of probe and sub-sequence; \"off-by-m\" coverage corresponds to an approximate match in which all but m nucleotides agree. Given a database of SARS-CoV-2 sequences, the single probe design problem is to find a string of length K, subject to the constraints of G/C content and hairpin aversion, which covers as many SARS-CoV-2 sequences as possible. For the multi-probe design problem, we seek P probes instead of just one, and a P-probe design is said to cover a SARS-CoV-2 sequence if any one of the probes cover it. Selection of K=31 was used because it was short enough that a single probe can cover a large fraction of the sequences in the SARS-CoV-2 database, but long enough that it won't accidentally cover potential background sequences. ", + "laborHours": 0.0, + "languages": [], + "name": "FEVER Probe Design Algorithm", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jt-lanl/fever-probes", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FFTX.json b/agency-indexes/DoE/FFTX.json new file mode 100644 index 00000000..c1848b8b --- /dev/null +++ b/agency-indexes/DoE/FFTX.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2021-08-20" + }, + "description": "This is the repository for the FFTX Project developed by the Exascale Computing Project (ECP) and Lawrence Berkeley National Laboratory (LBNL).", + "laborHours": 0.0, + "languages": [], + "name": "FFTX", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/spiral-software/fftx/blob/main/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spiral-software/fftx", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FIDO.json b/agency-indexes/DoE/FIDO.json new file mode 100644 index 00000000..daef6901 --- /dev/null +++ b/agency-indexes/DoE/FIDO.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "The finite difference optimizer (FIDO), is a tool for optimizing finite difference discretization stencils for stability. It supports uniform Cartesian meshes as well as cut-cell meshes. FIDO is a driver program with a configurable objective function that is meant to be coupled with a solver.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "FIDO", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/FIERRO_V.X.json b/agency-indexes/DoE/FIERRO_V.X.json new file mode 100644 index 00000000..59c01cf3 --- /dev/null +++ b/agency-indexes/DoE/FIERRO_V.X.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-08-03" + }, + "description": "FIERRO is a modern C++ code intended to simulate quasi-static solid mechanics problems and transient, compressible material dynamic problems with Lagrangian methods, which have meshes with constant mass elements that move with the material. FIERRO is designed to aid a) material model research that has historically been done using commercial implicit and explicit finite element codes, b) numerical methods research, and c) computer science research. FIERRO supports user developed material models that adhere to several industry standard formats by using a C++ to Fortran interface to couple the model to the numerical solvers. FIERRO is built on the ELEMENTS library that supports a diverse suite of element types, including high-order elements, and quadrature rules. The mesh class within the ELEMENTS library is designed for efficient calculations on unstructured meshes and to minimize memory usage. FIERRO is designed to readily accommodate a range of numerical methods including continuous finite element, finite volume, and discontinuous Galerkin methods. FIERRO is designed to support explicit and implicit time integration methods. FIERRO only supports a single material in an element. No physical data exists within the code.", + "laborHours": 0.0, + "languages": [], + "name": "FIERRO V.X", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Fierro", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FIEXTA__FIeld_EXperiments_Tool_Arsenal__[SWR-24-129].json b/agency-indexes/DoE/FIEXTA__FIeld_EXperiments_Tool_Arsenal__[SWR-24-129].json new file mode 100644 index 00000000..381c011b --- /dev/null +++ b/agency-indexes/DoE/FIEXTA__FIeld_EXperiments_Tool_Arsenal__[SWR-24-129].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-22", + "metadataLastUpdated": "2025-04-22" + }, + "description": "Code repository to assist the planning, management, and data analysis of experiment field campaigns including atmospheric sensors, remote sensing devices, and renewable energy plants.", + "laborHours": 1839.2, + "languages": [ + "Python" + ], + "name": "FIEXTA (FIeld EXperiments Tool Arsenal) [SWR-24-129]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/FIEXTA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FINITE-ELEMENT_DISTORED_WAVE_BORN_APPROXIMATION_FOR_SURFACE_SCATTERING.json b/agency-indexes/DoE/FINITE-ELEMENT_DISTORED_WAVE_BORN_APPROXIMATION_FOR_SURFACE_SCATTERING.json new file mode 100644 index 00000000..5ccf5a03 --- /dev/null +++ b/agency-indexes/DoE/FINITE-ELEMENT_DISTORED_WAVE_BORN_APPROXIMATION_FOR_SURFACE_SCATTERING.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-23" + }, + "description": "FE-DWBA is a software package that computes the x-ray scattering patterns of objects that locate on \na surface or buried next to a surface, such as the nano-circuits and nano-patterns of the mask used \nin the extreme ultraviolet lithography. It can incorporate the dynamical scattering effect (photons \nscattered multiple times), which is predominant in surface scattering and yield high-fidelity \nscattering patterns. The application includes surface imaging using x-rays, and critical dimension \ndetermination for semiconductor manufacturing.\n\n", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "FINITE-ELEMENT DISTORED WAVE BORN APPROXIMATION FOR SURFACE SCATTERING", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/FLAMINGo:_Few_shot_Learning_Analysis_of_Multi-modal_Inference_Network_Graphs.json b/agency-indexes/DoE/FLAMINGo:_Few_shot_Learning_Analysis_of_Multi-modal_Inference_Network_Graphs.json new file mode 100644 index 00000000..2b9e8ece --- /dev/null +++ b/agency-indexes/DoE/FLAMINGo:_Few_shot_Learning_Analysis_of_Multi-modal_Inference_Network_Graphs.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-05-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A multi-modal few-shot learning approach is used to identify similarities between particles obtained from environmental samples. The inferred similarities are then used in a similarity graph to identify groupings and outliers in the sample", + "laborHours": 668.8, + "languages": [], + "name": "FLAMINGo: Few shot Learning Analysis of Multi-modal Inference Network Graphs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/particlefsl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FLASC__FLORIS-based_Analysis_for_SCADA_data_.json b/agency-indexes/DoE/FLASC__FLORIS-based_Analysis_for_SCADA_data_.json new file mode 100644 index 00000000..1c54bc7f --- /dev/null +++ b/agency-indexes/DoE/FLASC__FLORIS-based_Analysis_for_SCADA_data_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-05-04", + "metadataLastUpdated": "2022-05-11" + }, + "description": "FLASC provides a rich suite of analysis tools for SCADA data filtering & analysis, wind farm model validation, field experiment design, and field experiment monitoring. The repository is centrally built around NRELs in-house floris wind farm model, available at https://github.com/nrel/floris. FLASC also largely relies on the energy ratio to, among others, quantify wake losses in synthetic and historical data, to perform turbine northing calibrations, and for model parameter estimation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "FLASC (FLORIS-based Analysis for SCADA data)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/flasc", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FLIT:_A_Generic_Fortran_Library_based_on_Interfaces_and_Templates.json b/agency-indexes/DoE/FLIT:_A_Generic_Fortran_Library_based_on_Interfaces_and_Templates.json new file mode 100644 index 00000000..d1c1410e --- /dev/null +++ b/agency-indexes/DoE/FLIT:_A_Generic_Fortran_Library_based_on_Interfaces_and_Templates.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This Fortran code consists of multiple modules with a focus on simplifying array operations, image processing, and numerical computation especially for computational geophysics applications. We intend to use this code to demonstrate the application and usefulness of Fortran interface and templates for generic programming, especially for computational geophysics and seismology applications. The code has several notable features. Firstly, it is based on a modularized structure, where each module contains multiple functions but with a focus of functionality. Secondly, it heavily uses interfaces and templates for improving the genericness and convenience of the resulting code, where a same function interface can enclose a group of functions that perform the same functionality but with inputs/output variables of different data types. Thirdly, it includes a variety of generic functions with an emphasis on array operations, such as rotation, flipping, cropping, padding, fast Fourier transform, Gaussian blurring, interpolation, and so on. We name this package FLIP \u2013 a generic Fortran Library based on Interfaces and Templates.", + "laborHours": 33105.6, + "languages": [], + "name": "FLIT: A Generic Fortran Library based on Interfaces and Templates", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/flit", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FLORIS_[SWR-14-20].json b/agency-indexes/DoE/FLORIS_[SWR-14-20].json new file mode 100644 index 00000000..fb457b9c --- /dev/null +++ b/agency-indexes/DoE/FLORIS_[SWR-14-20].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-08-07" + }, + "description": "*** PUBLIC ARCHIVE*** THIS IS A READ-ONLY VERSION OF THE DEPRECATED VERSION. FOR THE CURRENT VERSION OF THE FLORIS SOFTWARE, SEE WWW.GITHUB.COM/NREL/FLORIS\n\nFLORIS is an engineering model of wind turbine wake interactions which accounts for the effects of turbines on the flow through the creation of wakes an accounting for both velocity deficit and wake redirection through yaw", + "laborHours": 1003.2, + "languages": [ + "OpenEdge ABL", + "Python" + ], + "name": "FLORIS [SWR-14-20]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/FLORISSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FLORIS_v3.5_Wake_Modeling_and_Wind_Farm_Controls_Software_[SWR-17-43_and_SWR-14-20].json b/agency-indexes/DoE/FLORIS_v3.5_Wake_Modeling_and_Wind_Farm_Controls_Software_[SWR-17-43_and_SWR-14-20].json new file mode 100644 index 00000000..e4d27eb9 --- /dev/null +++ b/agency-indexes/DoE/FLORIS_v3.5_Wake_Modeling_and_Wind_Farm_Controls_Software_[SWR-17-43_and_SWR-14-20].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2024-01-05" + }, + "description": "FLORIS is a controls-focused wind farm simulation software incorporating steady-state engineering wake models into a performance-focused Python framework. It has been in active development at NREL since 2013 and the latest release is FLORIS v3.5.Online documentation is available at https://nrel.github.io/floris.\n\nThe software is in active development and engagement with the development team is highly encouraged. If you are interested in using FLORIS to conduct studies of a wind farm or extending FLORIS to include your own wake model, please join the conversation in GitHub Discussions!\n\nhttps://www.nrel.gov/wind/floris.html", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "FLORIS v3.5 Wake Modeling and Wind Farm Controls Software [SWR-17-43 and SWR-14-20]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/floris", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FLOWER_IPv4_IPv6_Network_Flow_Summarization_software.json b/agency-indexes/DoE/FLOWER_IPv4_IPv6_Network_Flow_Summarization_software.json new file mode 100644 index 00000000..79a93eb2 --- /dev/null +++ b/agency-indexes/DoE/FLOWER_IPv4_IPv6_Network_Flow_Summarization_software.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "FLOWER was written as a refactoring/reimplementation of the existing Flo software used by the Cooperative Protection Program (CPP) to provide network flow summaries for analysis by the Operational Analysis Center (OAC) and other US Department of Energy cyber security elements. FLOWER is designed and tested to operate at 10 gigabits/second, nearly 10 times faster than competing solutions. FLOWER output is optimized for importation into SQL databases for categorization and analysis. FLOWER is written in C++ using current best software engineering practices.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "FLOWER IPv4/IPv6 Network Flow Summarization software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/FLUXNET_v._1.0.json b/agency-indexes/DoE/FLUXNET_v._1.0.json new file mode 100644 index 00000000..24e1664f --- /dev/null +++ b/agency-indexes/DoE/FLUXNET_v._1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-30" + }, + "description": "Solves the Poisson equation on three-dimensional network of line segments, each of uniform material properties, subject to boundary condition forcing.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 121.6, + "languages": [], + "name": "FLUXNET v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FL_V1.3.json b/agency-indexes/DoE/FL_V1.3.json new file mode 100644 index 00000000..ad7e5665 --- /dev/null +++ b/agency-indexes/DoE/FL_V1.3.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "A library of utility classes for computer vision. Contains implementations of various well-known image processing techniques, such as interest point operators and region descriptors. Includes interfaces to various libraries for image and video I/O, as well as an interface to LAPACK/BLAS. FL was developed at the University of Illinois, Urbana-Champaign (UIUC) and released under an open source license. Version 1.2 was a maintenance release provided by SNL under the LGPL license. Version 1.3 is a maintenance release, containing the following changes: - Improved image format handling. Now handles strided and planar memory layouts and a wider range of pixel formats. - Improved image file I/O, including better support for metadata, a wider range of stored pixel types, and a couple of new file formats. - Improvements to DOG and SIFT, and efficiency improvements in low-level convolution. - Improvements to networking, including a generic TCP listener. - Various improvements to numerical processing. The HISTORY file included in the distribution contains a more detailed description of the changes.", + "laborHours": 35978.4, + "languages": [ + "CMake", + "C++" + ], + "name": "FL V1.3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FL_V1.4.json b/agency-indexes/DoE/FL_V1.4.json new file mode 100644 index 00000000..ee10b7ed --- /dev/null +++ b/agency-indexes/DoE/FL_V1.4.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2019-12-19" + }, + "description": "A library of utility classes for computer vision. Contains implementations of various well-known image processing techniques, such as interest point operators and region descriptors. Includes interfaces to various libraries for image and video I/O, as well as an interface to LAPACK/BLAS. FL was developed at the University of Illinois, Urbana-Champaign (UIUC) and released under an open source license. Version 1.2 was a maintenance release provided by SNL under the LGPL license. Version 1.3 is a maintenance release, containing the following changes: - Improved image format handling. Now handles strided and planar memory layouts and a wider range of pixel formats. - Improved image file I/O, including better support for metadata, a wider range of stored pixel types, and a couple of new file formats. - Improvements to DOG and SIFT, and efficiency improvements in low-level convolution. - Improvements to networking, including a generic TCP listener. - Various improvements to numerical processing. The HISTORY file included in the distribution contains a more detailed description of the changes.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "FL V1.4", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.4" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FLiT.json b/agency-indexes/DoE/FLiT.json new file mode 100644 index 00000000..dd5112aa --- /dev/null +++ b/agency-indexes/DoE/FLiT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Floating-point Litmus Tests (FLiT) is a C++ test infrastructure for detecting variability in floating-point code caused by variations in compiler code generation, hardware and execution environments.", + "laborHours": 10336.0, + "languages": [], + "name": "FLiT", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PRUNERS/FLiT", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FNCL_Analysis_and_Simulation.json b/agency-indexes/DoE/FNCL_Analysis_and_Simulation.json new file mode 100644 index 00000000..5fd11a58 --- /dev/null +++ b/agency-indexes/DoE/FNCL_Analysis_and_Simulation.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "obriense@ornl.gov" + }, + "date": { + "created": "2022-02-16", + "metadataLastUpdated": "2022-02-16" + }, + "description": "Analyzes list mode data in a common frame work from both measured waveform data and Monte Carlo simulated pulse history data. Allows for filtering, such as pulse shape discrimination, pile up rejection, and crosstalk removal, to be applied before analyzing the pulse stream for quantities such as multiplicity counting rates, die-away times, and detection efficiency. Several FNCL MCNP models, Am(Li) source holders, and neutron generators, are created in the GUI for several sources, including fuel assemblies, and ran to produce synthetic list mode data. The package unifies the analysis and simulation of the FNCL, from simulation and measurement, into one framework to ensure consistency. Implemented as a GUI for ease of use but also as an application program interface (API) for use in other software packages.", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "FNCL Analysis and Simulation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/multTMU/FNCL", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FPChecker.json b/agency-indexes/DoE/FPChecker.json new file mode 100644 index 00000000..772b32e3 --- /dev/null +++ b/agency-indexes/DoE/FPChecker.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-08", + "metadataLastUpdated": "2019-04-08" + }, + "description": "CUDA is the programming model used to program NVIDIA GPUs, which are widely used in DOE supercomputers. FPChecker allows programmers to detect and fix hidden exceptions in the floating-point computations that CUDA executes. When a floating-point exception occurs (e.g., division by zero), GPUs cannot catch these errors. FPChecker intercepts each floating-point operations (addition, subtraction, multiplication and division) and reports to users where exceptions occur (file and line of code).", + "laborHours": 2280.0, + "languages": [], + "name": "FPChecker", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FPChecker", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FPEAM__Feedstock_Production_to_Air_Emissions_Model_.json b/agency-indexes/DoE/FPEAM__Feedstock_Production_to_Air_Emissions_Model_.json new file mode 100644 index 00000000..66bc2b32 --- /dev/null +++ b/agency-indexes/DoE/FPEAM__Feedstock_Production_to_Air_Emissions_Model_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-16", + "metadataLastUpdated": "2019-10-17" + }, + "description": "FPEAM is a modeling framework that integrates agricultural and forestry production, supply data, and equipment budgets for those activities with methodologies for estimating air pollutant emissions.", + "laborHours": 4408.0, + "languages": [ + "Python" + ], + "name": "FPEAM (Feedstock Production to Air Emissions Model)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/fpeam", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FPZIP.json b/agency-indexes/DoE/FPZIP.json new file mode 100644 index 00000000..2a6c9201 --- /dev/null +++ b/agency-indexes/DoE/FPZIP.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2019-12-19" + }, + "description": "fpzip is a C/C++ library for lossless and lossy compression of 1D, 2D, and 3D single- and double-precision floating-point arrays. \n\nAlthough designed for lossless compression, the user may optionally request lossy compression by specifying how many bits of precision per floating-point value to retain.\n\nFpzip supports streaming compression and decompression with either a memory buffer or a file as source or destination. \n\nIn addition to a simple C interface, fpzip comes with an executable for (de)compressing binary files.", + "laborHours": 1322.4, + "languages": [], + "name": "FPZIP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/fpzip", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FPcompress.json b/agency-indexes/DoE/FPcompress.json new file mode 100644 index 00000000..d3e22f67 --- /dev/null +++ b/agency-indexes/DoE/FPcompress.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "burtscher@txstate.edu" + }, + "date": { + "created": "2025-03-14", + "metadataLastUpdated": "2025-03-14" + }, + "description": "This repository contains the code and related scripts for 4 high-performance lossless compression algorithms for single- and double-precision floating-point data. They are named SPratio, SPspeed, DPratio, and DPspeed. The compressors work on CPUs and GPUs and deliver state-of-the-art throughputs and compression ratios.", + "laborHours": 4453.6, + "languages": [], + "name": "FPcompress", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/burtscher/FPcompress", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FQC.json b/agency-indexes/DoE/FQC.json new file mode 100644 index 00000000..ab446f71 --- /dev/null +++ b/agency-indexes/DoE/FQC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Extensible quality control dashboard built around FASTQ assessment. FQC is designed to better group FastQC result data across groups where each group is comprised of FASTQs related to an experiment or sequencing batch. Individual samples are grouped into paired-end sets when available and the dashboard's extensibility allows a user to add plots or tables as desired.", + "laborHours": 125795.2, + "languages": [], + "name": "FQC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/fqc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FRACHELM_v.1.0.json b/agency-indexes/DoE/FRACHELM_v.1.0.json new file mode 100644 index 00000000..92337bdd --- /dev/null +++ b/agency-indexes/DoE/FRACHELM_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2024-06-11" + }, + "description": "Program uses linear, nodal finite elements to solve the space-fractional Helmholtz equation over segments of an arbitrary 3D graph.SAND2019-11082 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 1124.8, + "languages": [ + "Fortran" + ], + "name": "FRACHELM v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FRHODO.json b/agency-indexes/DoE/FRHODO.json new file mode 100644 index 00000000..d4352232 --- /dev/null +++ b/agency-indexes/DoE/FRHODO.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-05-28", + "metadataLastUpdated": "2020-05-28" + }, + "description": "Frhodo is an open-source Python application to optimize chemical kinetics mechanisms using Cantera as its chemistry\nsolver. Frhodo is built on an easy-to-use GUI that provides immediate graphical feedback when changes are made to a\nmechanism. This feedback is used to optimize kinetics mechanisms based on experimental observables. Optimization\ncan be performed either by hand or built-in optimization routines. There is currently support for high-temperature\nchemical kinetics experiments that can be simulated using a 0d reactor or using a custom reactor built for\nmeasurements taken behind incident shock waves. Such experiments include shock tubes, idealized rapid compression\nmachines, etc. Additional tools for exploring chemical kinetics mechanisms are provided such as the simulation\nexplorer, which can graph an extensive list of combustion relevant variables. The guiding principle of Frhodo is to\nelevate researcher capabilities by minimizing repetitive tasks.\n", + "laborHours": 25308.0, + "languages": [], + "name": "FRHODO", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/Frhodo", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FRISM__FReight_Integrated_Simulation_Model__[SWR-24-40].json b/agency-indexes/DoE/FRISM__FReight_Integrated_Simulation_Model__[SWR-24-40].json new file mode 100644 index 00000000..186b4f8f --- /dev/null +++ b/agency-indexes/DoE/FRISM__FReight_Integrated_Simulation_Model__[SWR-24-40].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-08-27", + "metadataLastUpdated": "2024-09-10" + }, + "description": "FRISM simulates day-to-day freight activities including end-consumer shopping, distribution channel, and carrier operation with e-commerce dynamics between passenger and freight travel. It outputs an assignment of different shipments to carriers and tour plans of the carriers' vehicles to transport shipments from their origins to their destinations.", + "laborHours": 6171.2, + "languages": [ + "Python", + "Shell" + ], + "name": "FRISM (FReight Integrated Simulation Model) [SWR-24-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/FRISM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FTL:_Transfer_Learning_Nonlinear_Plasma_Dynamic_Transitions_in_Low_Dimensional_Embeddings__FTL__v1.0.json b/agency-indexes/DoE/FTL:_Transfer_Learning_Nonlinear_Plasma_Dynamic_Transitions_in_Low_Dimensional_Embeddings__FTL__v1.0.json new file mode 100644 index 00000000..caf1d9d2 --- /dev/null +++ b/agency-indexes/DoE/FTL:_Transfer_Learning_Nonlinear_Plasma_Dynamic_Transitions_in_Low_Dimensional_Embeddings__FTL__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "Fusion Transfer Learning (FTL) model provides a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. The knowledge transfer process leverages a pre-trained neural encoder-decoder network, initially trained on linear simulations, to effectively capture nonlinear dynamics. The low-dimensional embeddings extract the coherent structures of interest, while preserving the inherent dynamics of the complex system. Experimental results highlight FTL's capacity to capture transitional behaviors and dynamical features in plasma dynamics -- a task often challenging for conventional methods. The model developed in this study is generalizable and can be extended broadly through transfer learning to address various magnetohydrodynamics (MHD) modes.", + "laborHours": 91.2, + "languages": [], + "name": "FTL: Transfer Learning Nonlinear Plasma Dynamic Transitions in Low Dimensional Embeddings (FTL) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zhbai/FTL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FTTN:_Feature-Targeted_Testing_for_Numerical_Properties_of_NVIDIA_&_AMD_Matrix_Accelerators.json b/agency-indexes/DoE/FTTN:_Feature-Targeted_Testing_for_Numerical_Properties_of_NVIDIA_&_AMD_Matrix_Accelerators.json new file mode 100644 index 00000000..ad683621 --- /dev/null +++ b/agency-indexes/DoE/FTTN:_Feature-Targeted_Testing_for_Numerical_Properties_of_NVIDIA_&_AMD_Matrix_Accelerators.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-10-18", + "metadataLastUpdated": "2024-10-18" + }, + "description": "FTTN is a test suite to evaluate the numerical behaviors of matrix accelerators of GPUs (NVIDIA Tensor\nCores and AMD Matrix Cores) in a quick and simple setting. Matrix accelerators are heavily used in\ntoday's computationally intense applications to speed up matrix multiplications. This test suite provides a\ncomprehensive study on the numerical behaviors of these accelerators, including support for subnormals,\nrounding modes, extra precision bits and FMA features.\nIs there", + "laborHours": 1474.4, + "languages": [], + "name": "FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FTTN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FVCOM-ICM4.0.json b/agency-indexes/DoE/FVCOM-ICM4.0.json new file mode 100644 index 00000000..17e4ab37 --- /dev/null +++ b/agency-indexes/DoE/FVCOM-ICM4.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "FVCOM-ICM is a water quality model that simulates the influence of nutrients and carbon pollution on biogeochemical oceanographic processes such as phytoplankton primary productivity, nutrient consumption, mineralization, decay and settling of particulate organic matter and computes resulting dissolved oxygen (DO) concentrations and pH levels. An \u201coffline\u201d approach of coupling Finite Volume Coastal Ocean Model (FVCOM) hydrodynamic solutions to CE-QUAL-ICM biogeochemical model was used. FVCOM and CE-QUAL-ICM are public domain Fortran Codes that were developed independently by US Army Corps of Engineers and University of Massachusetts. PNNL developed FVCOM-ICM that has the ability to conduct water quality calculations using a previously computed hydrodynamic solution. The biogeochemical calculations using CE-QUAL-ICM kinetics are conducted over the same finite-volume mesh and in the FVCOM framework.", + "laborHours": 0.0, + "languages": [], + "name": "FVCOM-ICM4.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ssmc/fvcom-icm4.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Face_Recognition_from_Oak_Ridge__FaRO_.json b/agency-indexes/DoE/Face_Recognition_from_Oak_Ridge__FaRO_.json new file mode 100644 index 00000000..d99dc6ca --- /dev/null +++ b/agency-indexes/DoE/Face_Recognition_from_Oak_Ridge__FaRO_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Many universities have published highly accurate open source face recognition algorithms, but configuring and using those algorithms can be very difficult due to poor documentation and challenges with installing the right software and libraries. Comparing research results is also a problem due to uncontrolled research methods. Provide baseline face recognition implementations that can be used for evaluating algorithm accuracy. The software provides a consistent web service interface to face recognition algorithms that can be used to support research in biometrics. The software uses protobuf and grpc services to publish standardized interfaces to the algorithms. The software also provides Docker container support which allows services to be easily started and configured on new machines. Reproducible baseline configurations are provided to serve as bench marks for publications in this area.", + "laborHours": 35613.6, + "languages": [ + "Python 3" + ], + "name": "Face Recognition from Oak Ridge (FaRO)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/faro", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Facility_CO2_Flow_Tool__FCFT__v0.9.json b/agency-indexes/DoE/Facility_CO2_Flow_Tool__FCFT__v0.9.json new file mode 100644 index 00000000..dd94239c --- /dev/null +++ b/agency-indexes/DoE/Facility_CO2_Flow_Tool__FCFT__v0.9.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-06", + "metadataLastUpdated": "2024-08-13" + }, + "description": "Facility CO2 Flow Tool assists facilities and entities to visualize their CO2 flows for accounting and decarbonization purposes. To do so, the suite offers two components \u2013 an MS Excel-based input workbook and a web-based visualization tool. The workbook serves as the input sheet, utilizing the user-provided process and equipment-level energy consumption data to calculate the corresponding CO2 emissions. The web-based tool utilizes the data from this workbook to generate a Sankey diagram. This diagram visually represents the CO2 flow originating from the fuel and electricity consumption within the facility/entity boundary.", + "laborHours": 881.6, + "languages": [], + "name": "Facility CO2 Flow Tool (FCFT) v0.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IACDecarb/IAC-Decarb-Tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Facility_Energy_Decision_System__FEDS__version_7.0.json b/agency-indexes/DoE/Facility_Energy_Decision_System__FEDS__version_7.0.json new file mode 100644 index 00000000..32c14a60 --- /dev/null +++ b/agency-indexes/DoE/Facility_Energy_Decision_System__FEDS__version_7.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Designed for building energy managers, utilities and firms providing energy services, FEDS provides a comprehensive and user-friendly method for users to quickly and accurately identifying energy conversion and end-use technology improvements that offer maximum savings in energy usage and cost. FEDS enables the user to assess energy efficiency and consumption, identify retrofit opportunities, select minimum life cycle costs, determine payback, and prioritize investments in energy efficiency retrofit projects for multiple or single buildings across a particular site. As part of the life-cycle cost optimization it also considers several options for partial or complete abandonment of central energy plants including: individual technologies dropping off a thermal loop, a loop and all technologies dropping off a central plant, and all technologies and loops dropping off a central plant resulting in its complete abandonment. Improvements in release 7.0 include: FEDS 7.0 is now a full hourly simulation model (runs every hour of the year as opposed to the previous simplified hourly approach which ran 9 24-hour periods to represent each month). Enhanced building operation and occupancy modeling; New HVAC technology options (VAV, Economizers, Demand Controlled Ventilation, Terminal Reheat, Subcool Dehumidification); Additional chiller types; New lighting technologies (LED, Halogen, Induction, additional fluorescent options); Completely updated retrofit cost and performance data; Regional cost data tied to zip code (previously applied state level averages); Updated and enhanced reporting capabilities; and New pier floor model", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++, Microsoft Visual Studio" + ], + "name": "Facility Energy Decision System (FEDS) version 7.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fair_Bagging_Boosting_Models_[SWR-24-38].json b/agency-indexes/DoE/Fair_Bagging_Boosting_Models_[SWR-24-38].json new file mode 100644 index 00000000..2a3da47d --- /dev/null +++ b/agency-indexes/DoE/Fair_Bagging_Boosting_Models_[SWR-24-38].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Fair Bagging Boosting Models is a software implementation of a framework for building, measuring bias and correcting bias in 3 popular forest machine learning models: gradient boosted trees (GBT), random forest (RF), and XGBoost models, using the XGBoost library. The framework takes advantage of the flexibility in XGBoost library to represent gradient boosted tree and random forest models, as well as the ability to use custom loss function.", + "laborHours": 1216.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "Fair Bagging Boosting Models [SWR-24-38]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Fair_Bagging_Boosting_Models", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FakeADFS.json b/agency-indexes/DoE/FakeADFS.json new file mode 100644 index 00000000..b34b655e --- /dev/null +++ b/agency-indexes/DoE/FakeADFS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2023-03-15" + }, + "description": "When developing Asp.Net Core applications for deployment in Linux or Docker environments, applications are no longer able to be configured to use Windows Authentication. Many organizations have an ADFS implementation that applications can authenticate off of, but during development there are issues with ADFS. This is a small set of applications that represent a dummy ADFS implementation that removes restrictions while developing locally.", + "laborHours": 0.0, + "languages": [], + "name": "FakeADFS", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/FakeADFS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FakeObjectsForTests.json b/agency-indexes/DoE/FakeObjectsForTests.json new file mode 100644 index 00000000..977c4992 --- /dev/null +++ b/agency-indexes/DoE/FakeObjectsForTests.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "This is the repository for \"FakeObjectsForTests\" developed by KBase. ", + "laborHours": 2356.0, + "languages": [], + "name": "FakeObjectsForTests", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/FakeObjectsForTests", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Falcon:_A_Temporal_Visual_Analysis_System.json b/agency-indexes/DoE/Falcon:_A_Temporal_Visual_Analysis_System.json new file mode 100644 index 00000000..c60fea36 --- /dev/null +++ b/agency-indexes/DoE/Falcon:_A_Temporal_Visual_Analysis_System.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Flexible visible exploration of long, high-resolution time series from multiple sensor streams is a challenge in several domains. Falcon is a visual analytics approach that helps researchers acquire a deep understanding of patterns in log and imagery data. Falcon allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations with multiple levels of detail. These capabilities are applicable to the analysis of any quantitative time series.", + "laborHours": 0.0, + "name": "Falcon: A Temporal Visual Analysis System", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csteed/falcon", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Falkor_'Rust'_Acquisition_Module.json b/agency-indexes/DoE/Falkor_'Rust'_Acquisition_Module.json new file mode 100644 index 00000000..f8764b8c --- /dev/null +++ b/agency-indexes/DoE/Falkor_'Rust'_Acquisition_Module.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-02-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The acquisition of analog signal from a time of flight mass spectrometer requires robust, efficient, and fast software. Writing multi-threaded applications is inherently more challenging due to the potential for livelocks, deadlocks, and race conditions. Rust was identified as a \"safe\" language that has a compiler that statically checks the code for these potential problems and prevents compilation entirely if detected. Rust is a systems level language, on par with C / C++. However, it supports a thriving package management system similar to npm or NuGet and has other modern features which make it accessible for rapid prototyping and simplifies compilation procedures.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Falkor 'Rust' Acquisition Module", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/business/default.aspx?topic=Licensing_Guidelines", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Falkor_Data_Station.json b/agency-indexes/DoE/Falkor_Data_Station.json new file mode 100644 index 00000000..521704d3 --- /dev/null +++ b/agency-indexes/DoE/Falkor_Data_Station.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-02-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "In order to support different hardware configurations, an extensible and modular software architecture was developed that could adapt to new requirements in an agile manner. This led to the design of an application programming interface or software development kit that would allow for the rapid integration of new hardware plugins, including AMPS, MIPS, and National Instruments, along with support for digitizers from vendors such as Acqiris. The use of ZeroMQ and a simple communication protocol allows for real time data display and analysis. This is achieved via a separate application simply called the AgMD1 Console. This application allows for low level foreign function interface (FFI) calls to the AGMD1 libraries to operate the U1084A analog-to-digital converter.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Falkor Data Station", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/business/default.aspx?topic=Licensing_Guidelines", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Faraday:_A_High-temperature_Electrolysis_Data_Explorer.json b/agency-indexes/DoE/Faraday:_A_High-temperature_Electrolysis_Data_Explorer.json new file mode 100644 index 00000000..9d0b121f --- /dev/null +++ b/agency-indexes/DoE/Faraday:_A_High-temperature_Electrolysis_Data_Explorer.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-11-18", + "metadataLastUpdated": "2024-11-18" + }, + "description": "Faraday is a high-temperature electrolysis data visualization tool, which reveals the performance of various button cells under test conditions. These tests and the resulting analytics on their data constitute a state of the industry as the US Department of Energy pushes for the production of hydrogen.\n\nFaraday leverages the Idaho National Laboratory's DeepLynx data warehouse to standardize and query button cell data. Faraday programmatically accesses this data in DeepLynx by traversing the schema, represented by a custom ontology.\n\nThe user interface queries DeepLynx for timeseries data associated with specific button cells in the warehouse, and renders them using JavaScript charts. Additional charting and data analysis techniques are made possible by an auxiliary Python server.", + "laborHours": 4712.0, + "languages": [ + "Python", + "TypeScript" + ], + "name": "Faraday: A High-temperature Electrolysis Data Explorer", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholabresearch/faraday", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FasTensor__FT__v0.0.1.json b/agency-indexes/DoE/FasTensor__FT__v0.0.1.json new file mode 100644 index 00000000..243310bd --- /dev/null +++ b/agency-indexes/DoE/FasTensor__FT__v0.0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-04-17", + "metadataLastUpdated": "2021-06-15" + }, + "description": "The FasTensor implements the native array data programming mode namely SLOPE for modern data analysis tasks. It is designed to work in parallel on supercomputer and can handle terabyte data analysis tasks. It is thousand times faster than other data analysis systems such as Apache Spark and 38% faster than TensorFlow in dealing with large scale scientific data analysis. It has wide applications in image data analysis and mesh data analysis tasks in physical simulations and other fields.", + "laborHours": 0.0, + "languages": [], + "name": "FasTensor (FT) v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/fastensor/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/FastANI_for_KBase.json b/agency-indexes/DoE/FastANI_for_KBase.json new file mode 100644 index 00000000..b50395e5 --- /dev/null +++ b/agency-indexes/DoE/FastANI_for_KBase.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "FastANI wrapper for the KBase SDK. FastANI is a whole-genome similarity estimation utility. Refer to its documentation for more details about the algorithm.", + "laborHours": 972.8, + "languages": [], + "name": "FastANI for KBase", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/FastANI", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FastBit.json b/agency-indexes/DoE/FastBit.json new file mode 100644 index 00000000..9946e5c0 --- /dev/null +++ b/agency-indexes/DoE/FastBit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-02", + "metadataLastUpdated": "2018-07-02" + }, + "description": "FastBit is a library of search functions supported by compressed bitmap indexes. Similarly to other database management systems, Fastbit treats user data in a column-oriented manner but it is designed to accelerate user's data selection tasks. ", + "homepageURL": "https://sdm.lbl.gov/fastbit", + "laborHours": 0.0, + "languages": [], + "name": "FastBit", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sdm.lbl.gov/fastbit/src/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sdm.lbl.gov/fastbit", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fast_All-sky_Radiation_Model_for_Solar_applications__FARMS__2023_[SWR-16-18].json b/agency-indexes/DoE/Fast_All-sky_Radiation_Model_for_Solar_applications__FARMS__2023_[SWR-16-18].json new file mode 100644 index 00000000..d2974a58 --- /dev/null +++ b/agency-indexes/DoE/Fast_All-sky_Radiation_Model_for_Solar_applications__FARMS__2023_[SWR-16-18].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-07-01", + "metadataLastUpdated": "2024-07-01" + }, + "description": "The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.", + "laborHours": 0.0, + "languages": [ + "Python", + "Shell" + ], + "name": "Fast All-sky Radiation Model for Solar applications (FARMS) 2023 [SWR-16-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/farms", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fast_All-sky_Radiation_Model_for_Solar_applications__FARMS__[SWR-16-18].json b/agency-indexes/DoE/Fast_All-sky_Radiation_Model_for_Solar_applications__FARMS__[SWR-16-18].json new file mode 100644 index 00000000..e59ca775 --- /dev/null +++ b/agency-indexes/DoE/Fast_All-sky_Radiation_Model_for_Solar_applications__FARMS__[SWR-16-18].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-04-19", + "metadataLastUpdated": "2024-07-01" + }, + "description": "The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "Fast All-sky Radiation Model for Solar applications (FARMS) [SWR-16-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/farms", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fast_Combinatorial_Nonnegative_Least_Squares_v_1.0.json b/agency-indexes/DoE/Fast_Combinatorial_Nonnegative_Least_Squares_v_1.0.json new file mode 100644 index 00000000..57b8a971 --- /dev/null +++ b/agency-indexes/DoE/Fast_Combinatorial_Nonnegative_Least_Squares_v_1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2024-08-07" + }, + "description": "Software that employs an algorithm that rapidly and rigorously solves nonnegative least squares problems with many right hand sides. This is the latest internal version of MATLAB pseudocode that was described in a published in M. H. Van Benthem and M. R. Keenan, \"Fast algorithm for the solution of largescale non-negativity-constrained least squares problems,\" J. Chemom. 18(10), 441-450 (2004). Example code of this algorithm was included in the publication. This algorithm was also patented in M. H. Van Benthem and M. R. Keenan, \"Fast combinatorial algorithm for the solution of linearly constrained least squares problems,\"USPTO, Ed., Sandia Corporation, USA (2008). SAND2019-10098 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 45.6, + "languages": [ + "MATLAB" + ], + "name": "Fast Combinatorial Nonnegative Least Squares v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fcnnls", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fast_Equilibration_of_Ocean_Tracers_Software.json b/agency-indexes/DoE/Fast_Equilibration_of_Ocean_Tracers_Software.json new file mode 100644 index 00000000..039415e7 --- /dev/null +++ b/agency-indexes/DoE/Fast_Equilibration_of_Ocean_Tracers_Software.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-01-29", + "metadataLastUpdated": "2018-01-29" + }, + "description": "The Fast Equilibration of Ocean Tracers Software (FEOTS) is a set of Fortran modules and programs for post-processing output from LANL's Parallel Ocean Program (POP). However, it is written so that it can be extended for use with other General Circulation Models. Tools are provided for aiding in the diagnosis of sparse matrices that capture advection and diffusion operators that are consistent with General Circulation Model discretizations. FEOTS additionally offers tools to make use of the diagnosed operators to run offline tracer models in forward or equilibration modes.", + "laborHours": 4119.2, + "name": "Fast Equilibration of Ocean Tracers Software", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/FEOTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fast_Gaussian_Process_Prediction_with_MuyGPs.json b/agency-indexes/DoE/Fast_Gaussian_Process_Prediction_with_MuyGPs.json new file mode 100644 index 00000000..86cdf236 --- /dev/null +++ b/agency-indexes/DoE/Fast_Gaussian_Process_Prediction_with_MuyGPs.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-01", + "metadataLastUpdated": "2023-03-01" + }, + "description": "This code provides fast Gaussian process prediction algorithms based on the MuyGPs scalable hyperparameter optimization algorithm. This code is the companion to a research paper preprint soon to be made publicly available.", + "laborHours": 0.0, + "languages": [], + "name": "Fast Gaussian Process Prediction with MuyGPs", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MuyGPyS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fast_Global_File_Status.json b/agency-indexes/DoE/Fast_Global_File_Status.json new file mode 100644 index 00000000..8023f2e6 --- /dev/null +++ b/agency-indexes/DoE/Fast_Global_File_Status.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Fast Global File Status (FGFS) is a system software package that implimints a scalable mechanism to retrieve file information, such as its degree of distribution or replication and consistency.", + "laborHours": 6186.4, + "name": "Fast Global File Status", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/fastglobalfilestatus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fast_Model_Generalized_Pseudopotential_Theory_Interatomic_Potential_Routine.json b/agency-indexes/DoE/Fast_Model_Generalized_Pseudopotential_Theory_Interatomic_Potential_Routine.json new file mode 100644 index 00000000..b3c0c1e7 --- /dev/null +++ b/agency-indexes/DoE/Fast_Model_Generalized_Pseudopotential_Theory_Interatomic_Potential_Routine.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MGPT is an unclassified source code for the fast evaluation and application of quantum-based MGPT interatomic potentials for mrtals. The present version of MGPT has been developed entirely at LLNL, but is specifically designed for implementation in the open-source molecular0dynamics code LAMMPS maintained by Sandia National Laboratories. Using MGPT in LAMMPS, with separate input potential data, one can perform large-scale atomistic simulations of the structural, thermodynamic, defeat and mechanical properties of transition metals with quantum-mechanical realism.", + "homepageURL": "http://lammps.sandia.gov/download.html", + "laborHours": 0.0, + "name": "Fast Model Generalized Pseudopotential Theory Interatomic Potential Routine", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://lammps.sandia.gov/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fast_Parallel_Algorithms_for_Euclidean_Minimum_Spanning_Tree_and_Hierarchical_Spatial_Clustering.json b/agency-indexes/DoE/Fast_Parallel_Algorithms_for_Euclidean_Minimum_Spanning_Tree_and_Hierarchical_Spatial_Clustering.json new file mode 100644 index 00000000..9e02093d --- /dev/null +++ b/agency-indexes/DoE/Fast_Parallel_Algorithms_for_Euclidean_Minimum_Spanning_Tree_and_Hierarchical_Spatial_Clustering.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nYiqiu Wang, Shangdi Yu, Yan Gu, and Julian Shun.\nFast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering.\nProceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pp. 1982-1995, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wangyiqiu/hdbscan", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fast_Sparse-Vector_Cosine_Similarity_in_Go.json b/agency-indexes/DoE/Fast_Sparse-Vector_Cosine_Similarity_in_Go.json new file mode 100644 index 00000000..e344abe4 --- /dev/null +++ b/agency-indexes/DoE/Fast_Sparse-Vector_Cosine_Similarity_in_Go.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "shiversrm@ornl.gov" + }, + "date": { + "created": "2022-09-27", + "metadataLastUpdated": "2022-09-28" + }, + "description": "This software provides a fast way to perform efficient sparse matrix multiplication followed by top-n multiplication result selection. Functionality for performing matrix multiplication / cosine similarity separately is included in this package as well. This package is a pure Go port of a Python package developed by ING Bank (https://github.com/ing-bank/sparse_dot_topn) which uses Cython to execute the matrix multiplication in C++. Instructions for compiling bindings which can be called from Python are included with this package as well.", + "laborHours": 0.0, + "languages": [ + "Go", + "Python" + ], + "name": "Fast Sparse-Vector Cosine Similarity in Go", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/sparse-gosine-similarity", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FastaManager.json b/agency-indexes/DoE/FastaManager.json new file mode 100644 index 00000000..e23ed44b --- /dev/null +++ b/agency-indexes/DoE/FastaManager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "A KBase module generated by the KBase SDK to build and managage reference fasta data used for things like BLAST and other aligners and comparison tools.", + "laborHours": 1246.4, + "languages": [], + "name": "FastaManager", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/FastaManager", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fasta_File_Splitter.json b/agency-indexes/DoE/Fasta_File_Splitter.json new file mode 100644 index 00000000..5431ebaf --- /dev/null +++ b/agency-indexes/DoE/Fasta_File_Splitter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The FASTA File Splitter program can be used to split apart a protein FASTA file into a number of sections. Although the splitting is random, each section will have a nearly identical number of residues.", + "laborHours": 440.8, + "languages": [], + "name": "Fasta File Splitter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Fasta-File-Splitter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fasta_Organism_Filter.json b/agency-indexes/DoE/Fasta_Organism_Filter.json new file mode 100644 index 00000000..1b62a97c --- /dev/null +++ b/agency-indexes/DoE/Fasta_Organism_Filter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Reads a protein FASTA file and filters the proteins by either organism name or protein name to create a new, filtered file.", + "laborHours": 501.6, + "languages": [], + "name": "Fasta Organism Filter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Fasta-Organism-Filter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Faster_Parallel_Exact_Density_Peaks_Clustering.json b/agency-indexes/DoE/Faster_Parallel_Exact_Density_Peaks_Clustering.json new file mode 100644 index 00000000..aeb2779c --- /dev/null +++ b/agency-indexes/DoE/Faster_Parallel_Exact_Density_Peaks_Clustering.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for \"Faster Parallel Exact Density Peaks Clustering\" paper.\n\nHuang, Yihao, Shangdi Yu, and Julian Shun. \"Faster Parallel Exact Density Peaks Clustering.\"\u00a0SIAM Conference on Applied and Computational Discrete Algorithms (ACDA23). Society for Industrial and Applied Mathematics, 2023.\n", + "laborHours": 0.0, + "languages": [], + "name": "Faster Parallel Exact Density Peaks Clustering", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/michaelyhuang23/ParCluster", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fat_Crayon_Toolkit.json b/agency-indexes/DoE/Fat_Crayon_Toolkit.json new file mode 100644 index 00000000..e99e9b50 --- /dev/null +++ b/agency-indexes/DoE/Fat_Crayon_Toolkit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-08", + "metadataLastUpdated": "2021-02-08" + }, + "description": "The Fat Crayon Toolkit (FCT) provides python modules for assisting in the design and visualization of\nboreholes and tunnels and their relationship with natural features such as fractures. Distances of closest\napproach among the boreholes can be calculated, along with other key design metrics. Additionally, the shear propensity of natural fractures (either deterministic or stochastic) can be visualized in either 3D (as\nVTK files) or in 2D (stereonets). The example provided demonstrates a test bed developed for the\nEnhanced Geothermal Systems (EGS) Collab project. This material is based upon work supported by the\nGeothermal Office of the Department of Energy and the Sanford Underground Research Facility and was\nprepared by LLNL under Contract DE-AC52-07NA27344.", + "laborHours": 0.0, + "languages": [], + "name": "Fat Crayon Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/joepmorris/FatCrayonToolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fault_Graph__fg_.json b/agency-indexes/DoE/Fault_Graph__fg_.json new file mode 100644 index 00000000..f95aa835 --- /dev/null +++ b/agency-indexes/DoE/Fault_Graph__fg_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "nutarojj@ornl.gov" + }, + "date": { + "created": "2022-01-28", + "metadataLastUpdated": "2022-02-03" + }, + "description": "This software package offers a novel fault graph modeling language and a simulation tool for executing models specified in the language. The modeling language has three primary features that distinguish it from similar reliability analysis tools. These are (1) a random variable modeling several distinct outcomes of a single fault; (2) chains of faults in which one fault triggers another; and (3) time to fail sampled from probability distributions including positive normal, exponential, Weibull with a minimum, or immediate.", + "laborHours": 0.0, + "languages": [], + "name": "Fault Graph (fg)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/1qn/fault-graph", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fayda.json b/agency-indexes/DoE/Fayda.json new file mode 100644 index 00000000..b38bf88d --- /dev/null +++ b/agency-indexes/DoE/Fayda.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Fayda application developed as a part of the Reaction Roulette m/q LDRD project (76006) primarily exists as a data\nvisualization, analysis and predictive platform for data collected using atomic tandem inductively coupled plasma mass\nspectrometry (ICP-MS/MS)", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Fayda", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Feature-based_Anomaly_Detection_System.json b/agency-indexes/DoE/Feature-based_Anomaly_Detection_System.json new file mode 100644 index 00000000..d0b637f8 --- /dev/null +++ b/agency-indexes/DoE/Feature-based_Anomaly_Detection_System.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-10", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SAND2022-7963 O\nThe Feature-Based Anomaly Detection System detects anomalies in video data based on features derived from pre-trained image models to avoid the need for training. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1033.6, + "languages": [ + "Python", + "Dockerfile", + "Shell" + ], + "name": "Feature-based Anomaly Detection System", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Feature-based-Anomaly-Detection", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FeatureCreature.json b/agency-indexes/DoE/FeatureCreature.json new file mode 100644 index 00000000..dd1bee4d --- /dev/null +++ b/agency-indexes/DoE/FeatureCreature.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2018-09-07" + }, + "description": "This software provides mechanical/structural explanations for machine learning in chemistry.", + "laborHours": 2097.6, + "languages": [ + "Python" + ], + "name": "FeatureCreature", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/FeatureCreature", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FeatureSetUtils.json b/agency-indexes/DoE/FeatureSetUtils.json new file mode 100644 index 00000000..239d1c94 --- /dev/null +++ b/agency-indexes/DoE/FeatureSetUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "This is the repository for \"FeatureSetUtils\" developed by KBase. A KBase module generated by the KBase SDK.", + "laborHours": 1976.0, + "languages": [], + "name": "FeatureSetUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/FeatureSetUtils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Feature_Interpretability.json b/agency-indexes/DoE/Feature_Interpretability.json new file mode 100644 index 00000000..c6333fe7 --- /dev/null +++ b/agency-indexes/DoE/Feature_Interpretability.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "The feature interpretability code is a python module that interprets and analyzes neural networks trained on hydrodynamic simulation output in the form of numpy arrays. The code takes trained neural networks and extracts internal model states in the form of images. Additionally, tools for covariance analysis of network weights and predictions are provided. This code is built on the TensorFlow and PyTorch python libraries, and includes trained networks and example input data for demonstration purposes.", + "laborHours": 0.0, + "languages": [], + "name": "Feature Interpretability", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/feature_interpretability", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Feature_Values_Service.json b/agency-indexes/DoE/Feature_Values_Service.json new file mode 100644 index 00000000..b7dad121 --- /dev/null +++ b/agency-indexes/DoE/Feature_Values_Service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-31", + "metadataLastUpdated": "2020-08-31" + }, + "description": "This KBase service provides a set of methods for manipulation and visualization of expression values organized as two-dimentional matrix and assigned to genome features on one dimention and to different sorts conditions on second dimention.", + "laborHours": 10579.2, + "languages": [], + "name": "Feature Values Service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/feature_values", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Federally_Funded_Research_and_Development_Centers-as-Code_V.1.0.json b/agency-indexes/DoE/Federally_Funded_Research_and_Development_Centers-as-Code_V.1.0.json new file mode 100644 index 00000000..98361c4f --- /dev/null +++ b/agency-indexes/DoE/Federally_Funded_Research_and_Development_Centers-as-Code_V.1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The functionality of the software is to expand upon the concept of software defined anything/everything (SDX) and apply it to Federally Funded Research and Development Centers (FFRDCs).", + "laborHours": 60.8, + "languages": [ + "Dockerfile", + "Shell" + ], + "name": "Federally Funded Research and Development Centers-as-Code V.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fac", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Federation_of_UML_models_for_cyber_physical_use_cases.json b/agency-indexes/DoE/Federation_of_UML_models_for_cyber_physical_use_cases.json new file mode 100644 index 00000000..cfc23272 --- /dev/null +++ b/agency-indexes/DoE/Federation_of_UML_models_for_cyber_physical_use_cases.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This method employs the concept of federation, which is defined as the use of existing models that represent aspects of a system in specific domains (such as physical and cyber security domains) and building interfaces to link all of domain models. Federation seeks to build on existing bodies of work. Some examples include the Common Information Models (CIM) maintained by the International Electrotechnical Commission Technical Committee 57 (IEC TC 57) for the electric power industry. Another relevant model is the CIM maintained by the Distributed Management Task Force (DMTF)? this CIM defines a representation of the managed elements in an Information Technology (IT) environment. The power system is an example of a cyber-physical system, where the cyber systems, consisting of computing infrastructure such as networks and devices, play a critical role in the operation of the underlying physical electricity delivery system. Measurements from remote field devices are relayed to control centers through computer networks, and the data is processed to determine suitable control actions. Control decisions are then relayed back to field devices. It has been observed that threat actors may be able to successfully compromise this cyber layer in order to impact power system operation. Therefore, future control center applications must be wary of potentially compromised measurements coming from field devices. In order to ensure the integrity of the field measurements, these applications could make use of compromise indicators from alternate sources of information such as cyber security. Thus, modern control applications may require access to data from sources that are not defined in the local information model. In such cases, software application interfaces will require integration of data objects from cross-domain data models. When incorporating or federating different domains, it is important to have subject matter experts work together, recognizing that not everyone has the same knowledge, responsibilities, focus, or skill set.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Federation of UML models for cyber physical use cases", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Feeds.json b/agency-indexes/DoE/Feeds.json new file mode 100644 index 00000000..8a81f28f --- /dev/null +++ b/agency-indexes/DoE/Feeds.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-18", + "metadataLastUpdated": "2020-08-18" + }, + "description": "A service to manage event feeds that will get served to KBase users.", + "laborHours": 4377.6, + "languages": [], + "name": "Feeds", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/feeds", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Feedstock_to_Function__F2F__v1.json b/agency-indexes/DoE/Feedstock_to_Function__F2F__v1.json new file mode 100644 index 00000000..b830fbab --- /dev/null +++ b/agency-indexes/DoE/Feedstock_to_Function__F2F__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "\tThe Feedstock to Function (F2F) tool was designed to help scientists and companies explore viable biofuels and bioproducts early in the R&D cycle to support more productive experimentation, while reducing early-stage exploration from months/years to days/weeks (feedstock-to-function.lbl.gov). The tool focuses on using machine learning to predict biomass-derived molecule properties, while evaluating the cost, benefits, and risks of promising molecules for sustainable aviation fuels. The tool successfully predicts (within 15% of experimental values) high-throughput aviation properties for over 10,000 molecules while enabling users to explore new possibilities and opportunities rapidly and effortlessly. It also links to lightweight life-cycle analysis and techno-economic tools for cost and emissions analyses. Predicted molecule properties include melting point, boiling point, flash point, yield sooting index, and heat of combustion.\n\nTo date, F2F is more expansive and outperforms several other molecule property prediction models while enabling users (scientists, companies, and policy makers) to explore new possibilities and opportunities rapidly and effortlessly. F2F provides the foundation for developing an adaptive computational tool that predicts properties, cost, benefits, and risk of promising new and uncertified alternative jet fuel pathways and their blending effects.", + "laborHours": 0.0, + "languages": [], + "name": "Feedstock to Function (F2F) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tylerhuntington/feedstock-to-function", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fenix,_A_Fault_Tolerant_Programming_Framework_for_MPI_Applications.json b/agency-indexes/DoE/Fenix,_A_Fault_Tolerant_Programming_Framework_for_MPI_Applications.json new file mode 100644 index 00000000..8510d8b8 --- /dev/null +++ b/agency-indexes/DoE/Fenix,_A_Fault_Tolerant_Programming_Framework_for_MPI_Applications.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Fenix provides APIs to allow the users to add fault tolerance capability to MPI-based parallel programs in a transparent manner. Fenix-enabled programs can run through process failures during program execution using a pool of spare processes accommodated by Fenix.", + "laborHours": 3070.4, + "languages": [ + "CMake", + "C" + ], + "name": "Fenix, A Fault Tolerant Programming Framework for MPI Applications", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/epizon-project/Fenix", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ferdinand.json b/agency-indexes/DoE/Ferdinand.json new file mode 100644 index 00000000..b084f000 --- /dev/null +++ b/agency-indexes/DoE/Ferdinand.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-02-09", + "metadataLastUpdated": "2022-02-09" + }, + "description": "A code to read, translate and output parameters of R-matrix fits to nuclear resonance data.", + "laborHours": 0.0, + "languages": [], + "name": "Ferdinand", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ferdinand", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.40" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fermi-Hubbard_Transport_Solver_v._1.0.json b/agency-indexes/DoE/Fermi-Hubbard_Transport_Solver_v._1.0.json new file mode 100644 index 00000000..d1596ddf --- /dev/null +++ b/agency-indexes/DoE/Fermi-Hubbard_Transport_Solver_v._1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2021-1511 O. The code takes a description of a system comprised of two leads that are sources and sinks of electrons, a set of abstract sites that those electrons can occupy, and their connectivity. It then predicts the current passing between the two leads through the set of abstract sites. There are numerical parameters that define the rate at which electrons tunnel between sites and another parameter that determines the energy of having two electrons on the same site. When the ratio of these energies and biases are set just right, they can be used to predict the existence of Coulomb blockade in which no current flows because the energetic penalty would be too high. That is, the code predicts a current and the absence of a current which is predictive of Coulomb blockade. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 182.4, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "Fermi-Hubbard Transport Solver v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/FermiHubbardTransport", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FermiLib_v0.1.json b/agency-indexes/DoE/FermiLib_v0.1.json new file mode 100644 index 00000000..c7c4b4b8 --- /dev/null +++ b/agency-indexes/DoE/FermiLib_v0.1.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "FermiLib is an open source software package designed to facilitate the development and testing of algorithms for simulations of fermionic systems on quantum computers. Fermionic simulations represent an important application of early quantum devices with a lot of potential high value targets, such as quantum chemistry for the development of new catalysts. This software strives to provide a link between the required domain expertise in specific fermionic applications and quantum computing to enable more users to directly interface with, and develop for, these applications. It is an extensible Python library designed to interface with the high performance quantum simulator, ProjectQ, as well as application specific software such as PSI4 from the domain of quantum chemistry. Such software is key to enabling effective user facilities in quantum computation research.", + "laborHours": 0.0, + "languages": [ + "PYTHON 2.7" + ], + "name": "FermiLib v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ProjectQ-Framework/FermiLib", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Few-shot_leaf_segmentation.json b/agency-indexes/DoE/Few-shot_leaf_segmentation.json new file mode 100644 index 00000000..b12b745e --- /dev/null +++ b/agency-indexes/DoE/Few-shot_leaf_segmentation.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "lagergrenjh@ornl.gov" + }, + "date": { + "created": "2023-03-20", + "metadataLastUpdated": "2023-03-21" + }, + "description": "In this work, we use few-shot learning to segment the body and vein architecture of Populus trichocarpa leaves from high-resolution scans obtained in the UC Davis common garden. Leaf and vein segmentation are formulated as separate tasks, in which convolutional neural networks (CNNs) are used to iteratively expand partial segmentations until reaching stopping criteria. Our leaf and vein segmentation approaches use just 50 and 8 manually traced images for training, respectively, and are applied to a set of 2,634 top and bottom leaf scans. We show that both methods achieve high segmentation accuracy, in some cases exceeding even human-level segmentation. The leaf and vein segmentations are subsequently used to extract 68 morphological traits using traditional open-source image processing tools, which are validated using real-world physical measurements. For a biological perspective, we perform a genome-wide association study using the \"vein density\" trait to discover novel genetic architectures associated with multiple physiological processes relating to leaf development and function. In addition to sharing all of the few-shot learning code, we are releasing all images, manual segmentations, model predictions, 68 extracted leaf phenotypes, and a new set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Few-shot leaf segmentation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jlager/few-shot-leaf-segmentation", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fiducia.json b/agency-indexes/DoE/Fiducia.json new file mode 100644 index 00000000..475d0d8a --- /dev/null +++ b/agency-indexes/DoE/Fiducia.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2022-09-15" + }, + "description": "FIDUCIA: Filtered Diode Unfolder (using) Cubic-spline Algorithm Fiducia is a DANTE signal deconvolver based on the cubic splines method. Given time-resolved DANTE data across a number of K-edge filtered channels, this code can produce time-resolved x-ray spectra with coarse spectral resolution, as well as time-resolved x-ray flux and radiation temperature for a given source. The main application for this code is for diagnosing and constraining hohlraum drives on high energy density plasma physics experiments at the OMEGA Laser Facility and the National Ignition Facility. Spectral unfolds are created by assuming each DANTE channel provides information on the x-ray intensity in a particular photon energy band defined by its K-edge filter. The combination of multiple DANTE channels sensitive to different photon energies then provides coarse spectral information. The overall x-ray spectrum is approximated as a series of cubic splines corresponding to each energy band, which reduces the process of unfolding x-ray spectra from time-resolved DANTE channel data to a series of matrix operations folded with the DANTE response functions. By reducing the spectral deconvolution to a series of matrix operations, DANTE analysis is accelerated to the point where it could be feasibly used for on-the-fly characterization of hohlraum drives during experiments, with no additional assumptions about the shape of the x-ray spectrum.", + "laborHours": 0.0, + "languages": [], + "name": "Fiducia", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/fiducia", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FieLDS.json b/agency-indexes/DoE/FieLDS.json new file mode 100644 index 00000000..d72773d7 --- /dev/null +++ b/agency-indexes/DoE/FieLDS.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Field Landscape Decision Support (FieLDS) is a decision support tool that assists agricultural producers and farm managers in selecting parts of the field that can be converted to bioenergy plants, like perennial grasses, from the conventional use, like corn or soybean growth. That conversion of parts of the field is done based on the specific landscape properties and the agricultural producer\u2019s priorities. The decision support tool generates a map of the field layout and spatially marks where to place each plant based on the spatial input from the user. Also, the user selects which priorities (sustainability indicators) are most relevant to them in their decision-making. By allowing the user to set the weights among the priorities, the tool empowers the user to generate field designs specific to their needs instead of imposing the developer\u2019s set of priorities, and increases the transparency of the decision process.", + "laborHours": 152.0, + "languages": [ + "Python" + ], + "name": "FieLDS", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/FieLDS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Field_To_Farm_Aggregation_For_Agricultural_Systems.json b/agency-indexes/DoE/Field_To_Farm_Aggregation_For_Agricultural_Systems.json new file mode 100644 index 00000000..8c942805 --- /dev/null +++ b/agency-indexes/DoE/Field_To_Farm_Aggregation_For_Agricultural_Systems.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2024-10-07" + }, + "description": "The Fields to Farms methodology illustrates the generation of farm parcels from the Crop Data Layer (CDL), a raster dataset containing 133 categories representing various crop types and land uses. This methodology involves two primary steps: Field Delineation and Farm Aggregation. The code specifically addresses the aggregation of pre-delineated fields within a county to form farms, adhering to predefined criteria for farm size categories. It is assumed that the field delineation process, which involves creating vector polygons from CDL raster, has been completed beforehand, possibly through external tools or methods. Upon initialization, the script processes county-level fields, preparing them for farm aggregation. In the Farm Aggregation phase, the code iteratively combines delineated fields into farms based on specified criteria, continuing until the aggregated farm size meets predefined thresholds derived from data from the 2017 National Agricultural Statistics Service (NASS) census. Throughout this iterative process, the script dynamically adjusts the aggregation to ensure alignment with the desired distribution reported by NASS. The resulting output of the script is a GeoDataFrame containing classified farms, which are subsequently saved as GeoPackage files. These files enable further analysis and visualization, facilitating comprehensive exploration of the farm landscape generated through the methodology.", + "laborHours": 76.0, + "languages": [ + "Python" + ], + "name": "Field To Farm Aggregation For Agricultural Systems", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Field2Farm", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fierro_Version_2.x.json b/agency-indexes/DoE/Fierro_Version_2.x.json new file mode 100644 index 00000000..3febfbf1 --- /dev/null +++ b/agency-indexes/DoE/Fierro_Version_2.x.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-05-03" + }, + "description": "FIERRO is a parallel C++ code designed to simulate fluid mechanics, heat transfer, and solid mechanics in two- and three-dimensional space. FIERRO is written to run on homogeneous (CPU) and heterogeneous (CPU+GPU) high performance computing machines. Fierro can aid a) modeling and design efforts that have historically relied on commercial implicit and explicit finite element codes, b) numerical methods research, c) manufacturing research, and d) computer science research. The code contains diverse numerical methods to solve the governing physics equations for both quasi-static and dynamic problems. Mathematical optimization solvers are coupled to the numerical methods to research topology and shape optimization that has application to additive manufacturing, and to create novel numerical approaches. Phase-field methods with micromechanical solvers are provided to simulate microstructure formation and evolution in manufacturing processes. The micromechanical solvers can also help research efforts create continuum-scale constitutive models for solids, as a function of the microstructure, in situ in a calculation or in a stand-alone manner. No physical data exists within the code.", + "laborHours": 0.0, + "languages": [], + "name": "Fierro Version 2.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Fierro", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "2.x" +} \ No newline at end of file diff --git a/agency-indexes/DoE/File_Comparison_Sampler.json b/agency-indexes/DoE/File_Comparison_Sampler.json new file mode 100644 index 00000000..698cadae --- /dev/null +++ b/agency-indexes/DoE/File_Comparison_Sampler.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The file Comparison Sampler console application compares two or more files (typically in separate folders) to check whether the start of the files match, the end of the files match, and selected sections inside the files also match. It is useful for comparing large files without reading the entire file. Alternatively, you can provide two folder paths and the program will compare all of the files in the first folder to the identically named files in the second folder.", + "laborHours": 532.0, + "languages": [], + "name": "File Comparison Sampler", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/File-Comparison-Sampler", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/File_and_Directory_Management_Tool:_view,_organize,_transfer_files.json b/agency-indexes/DoE/File_and_Directory_Management_Tool:_view,_organize,_transfer_files.json new file mode 100644 index 00000000..9c51efec --- /dev/null +++ b/agency-indexes/DoE/File_and_Directory_Management_Tool:_view,_organize,_transfer_files.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "Hopper is a powerful interactive tool that allows users to graphically move, copy, find, delete, and otherwise operate on files. Users can connect to and manipulate resources using ftp, ssh, sftp, htar, Endeavor (nft), and other protocols. Operations include changing permissions, checking access, searching using wildcards, synchronizing directories, and many others.", + "homepageURL": "https://hpc.llnl.gov/software/data-management-tools/using-hopper", + "laborHours": 0.0, + "languages": [], + "name": "File and Directory Management Tool: view, organize, transfer files", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://hpc.llnl.gov/software/data-management-tools/using-hopper", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Filebench.json b/agency-indexes/DoE/Filebench.json new file mode 100644 index 00000000..b83fc93c --- /dev/null +++ b/agency-indexes/DoE/Filebench.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-31", + "metadataLastUpdated": "2018-07-31" + }, + "description": "Filebench is a file system and storage benchmark that allows to generate a high variety of workloads. It employs extensive Workload Model Language (WML) for detailed workload specification.", + "laborHours": 22860.8, + "languages": [], + "name": "Filebench", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/zfsonlinux/filebench/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zfsonlinux/filebench", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Finch.json b/agency-indexes/DoE/Finch.json new file mode 100644 index 00000000..46e17076 --- /dev/null +++ b/agency-indexes/DoE/Finch.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "reevest@ornl.gov" + }, + "date": { + "created": "2024-02-23", + "metadataLastUpdated": "2024-02-23" + }, + "description": "Finite difference heat transfer using Cabana for additive manufacturing", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Finch", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-MDF/Finch", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Finite_Element_Analysis_Code_-_CONEX.json b/agency-indexes/DoE/Finite_Element_Analysis_Code_-_CONEX.json new file mode 100644 index 00000000..a210ccca --- /dev/null +++ b/agency-indexes/DoE/Finite_Element_Analysis_Code_-_CONEX.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-03-20" + }, + "description": "CONEX is a code for joining sequentially in time multiple exodusll database files which all represent the same base mesh topology and geometry. It is used to create a single results or restart file from multiple results or restart files which typically arise as the result of multiple restarted analyses. CONEX is used to postprocess the results from a series of finite element analyses. It can join sequentially the data from multiple results databases into a single database which makes it easier to postprocess the results data.", + "laborHours": 2002235.2, + "languages": [], + "name": "Finite Element Analysis Code - CONEX", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gsjaardema/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Finite_Element_Analysis_Code_-_Exotxt.json b/agency-indexes/DoE/Finite_Element_Analysis_Code_-_Exotxt.json new file mode 100644 index 00000000..b204a3ea --- /dev/null +++ b/agency-indexes/DoE/Finite_Element_Analysis_Code_-_Exotxt.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-18" + }, + "description": "Exotxt is an analysis code that reads finite element results data stored in an exodusII file and generates a file in a structured text format. The text file can be edited or modified via a number of text formatting tools. Exotxt is used by analysis to translate data from the binary exodusII format into a structured text format which can then be edited or modified and then either translated back to exodusII format or to another format.", + "laborHours": 692284.0, + "languages": [], + "name": "Finite Element Analysis Code - Exotxt", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Finite_Element_Analysis_Code_-_MAPVAR-KD.json b/agency-indexes/DoE/Finite_Element_Analysis_Code_-_MAPVAR-KD.json new file mode 100644 index 00000000..7b61953b --- /dev/null +++ b/agency-indexes/DoE/Finite_Element_Analysis_Code_-_MAPVAR-KD.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-03-20" + }, + "description": "MAPVAR-KD is designed to transfer solution results from one finite element mesh to another. MAPVAR-KD draws heavily from the structure and coding of MERLIN II, but it employs a new finite element data base, EXODUS II, and offers enhanced speed and new capabilities not available in MERLIN II. In keeping with the MERLIN II documentation, the computational algorithms used in MAPVAR-KD are described. User instructions are presented. Example problems are included to demonstrate the operation of the code and the effects of various input options. MAPVAR-KD is a modification of MAPVAR in which the search algorithm was replaced by a kd-tree-based search for better performance on large problems.", + "laborHours": 2002235.2, + "languages": [], + "name": "Finite Element Analysis Code - MAPVAR-KD", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gsjaardema/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Finite_Element_Method_for_Electrochemical_Transport.json b/agency-indexes/DoE/Finite_Element_Method_for_Electrochemical_Transport.json new file mode 100644 index 00000000..cb409062 --- /dev/null +++ b/agency-indexes/DoE/Finite_Element_Method_for_Electrochemical_Transport.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-09-27", + "metadataLastUpdated": "2022-09-27" + }, + "description": "This code provides Finite Element solvers for Electrochemical Transport. A few examples from the literature are reproduced, with a focus on CO2 electrolysis. The Discontinuous Galerkin scheme for the electroneutral Nernst-Planck equations is from Roy, T., Andrej, J. and Beck, V.A., 2021. A scalable DG solver for the electroneutral Nernst-Planck equations. arXiv preprint arXiv:2112.09271. This work also includes a scalable preconditioner.", + "laborHours": 0.0, + "languages": [], + "name": "Finite Element Method for Electrochemical Transport", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/echemfem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Finite_Element_Solver_for_Fission_Dynamics.json b/agency-indexes/DoE/Finite_Element_Solver_for_Fission_Dynamics.json new file mode 100644 index 00000000..2a530b86 --- /dev/null +++ b/agency-indexes/DoE/Finite_Element_Solver_for_Fission_Dynamics.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "FELIX is a physics computer code used to model fission fragment mass distributions in a fully quantum-mechanical, microscopic framework that only relies on our current knowledge of nuclear forces. It is an implementation of the time-dependent generator coordinate method (TDGCM), which simulates the dynamics of a collective quantum wave-packet assuming the motion is adiabatic. In typical applications of the TDGCM, the nuclear collective wavepacket is obtained as a superposition of wavefunctions obtained by solving the Hartree-Fock-Bogoliubov equations of nuclear density functional theory (DFT). The program calculates at each time step the coefficients of that superposition.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Finite Element Solver for Fission Dynamics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/finite-element-solver-for-fission-dynamics", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/FireCat.json b/agency-indexes/DoE/FireCat.json new file mode 100644 index 00000000..5eb6f23f --- /dev/null +++ b/agency-indexes/DoE/FireCat.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-23" + }, + "description": "FireCat performs multiscale simulations by coupling ab initio microkinetic simulations from CatMAP with two-dimensional continuum transport simulations from EchemFEM (Firedrake). This coupling is performed in an iterative fashion. The examples provided here are specific to electrochemical CO2 reduction to CO on Au electrodes.\n", + "laborHours": 0.0, + "languages": [], + "name": "FireCat", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/firecat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.01" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FireHose_Streaming_Benchmarks.json b/agency-indexes/DoE/FireHose_Streaming_Benchmarks.json new file mode 100644 index 00000000..b68fee9c --- /dev/null +++ b/agency-indexes/DoE/FireHose_Streaming_Benchmarks.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The FireHose Streaming Benchmarks are a suite of stream-processing benchmarks defined to enable comparison of streaming software and hardware, both quantitatively vis-a-vis the rate at which they can process data, and qualitatively by judging the effort involved to implement and run the benchmarks. Each benchmark has two parts. The first is a generator which produces and outputs datums at a high rate in a specific format. The second is an analytic which reads the stream of datums and is required to perform a well-defined calculation on the collection of datums, typically to find anomalous datums that have been created in the stream by the generator. The FireHose suite provides code for the generators, sample code for the analytics (which users are free to re-implement in their own custom frameworks), and a precise definition of each benchmark calculation.", + "laborHours": 2964.0, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "Python" + ], + "name": "FireHose Streaming Benchmarks", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/firehose", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Firm_Synthesizer_and_Supply-chain_Simulator__SynthFirm__v1.0.json b/agency-indexes/DoE/Firm_Synthesizer_and_Supply-chain_Simulator__SynthFirm__v1.0.json new file mode 100644 index 00000000..fb4eb5af --- /dev/null +++ b/agency-indexes/DoE/Firm_Synthesizer_and_Supply-chain_Simulator__SynthFirm__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "SynthFirm is a large-scale agent-based freight demand model which generates a complete synthetic population of firms in the U.S. and the business-to-business commodity flows between them. Using publicly available data sources as inputs, SynthFirm simulates detailed firm and fleet characteristics, commodity production and consumption, formation of supply chains, and selection of shipping modes, all of which are essential drivers of commodity flow at a disaggregate level.", + "laborHours": 19456.0, + "languages": [], + "name": "Firm Synthesizer and Supply-chain Simulator (SynthFirm) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-UCB-STI/SynthFirm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FitIsoAndDeff_and_DeffCalculator_Matlab_Codes.json b/agency-indexes/DoE/FitIsoAndDeff_and_DeffCalculator_Matlab_Codes.json new file mode 100644 index 00000000..9f6dc6ed --- /dev/null +++ b/agency-indexes/DoE/FitIsoAndDeff_and_DeffCalculator_Matlab_Codes.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2024-06-14" + }, + "description": "These codes estimate effective diffusivity for species transport in materials and simultaneously fit multiple temperatures of measured isotherm and effective diffusivities for sorption transport of species through materials. Assumes triple-mode type sorption thermodynamics with mobile and immobile species in quasi-equilibrium.", + "laborHours": 349.6, + "languages": [], + "name": "FitIsoAndDeff and DeffCalculator Matlab Codes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/foley352/polymer-diffusion", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "01" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fitting_program_for_linear_regressions_according_to_Mahon__1996_.json b/agency-indexes/DoE/Fitting_program_for_linear_regressions_according_to_Mahon__1996_.json new file mode 100644 index 00000000..c523b77f --- /dev/null +++ b/agency-indexes/DoE/Fitting_program_for_linear_regressions_according_to_Mahon__1996_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This program takes the users' Input data and fits a linear regression to it using the prescription presented by Mahon (1996). Compared to the commonly used York fit, this method has the correct prescription for measurement error \r\npropagation. This software should facilitate the proper fitting of measurements with a simple Interface.", + "laborHours": 304.0, + "languages": [ + "Python 2.7 (100%)" + ], + "name": "Fitting program for linear regressions according to Mahon (1996)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MahonFitting", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fixed-rate_compressed_floating-point_arrays.json b/agency-indexes/DoE/Fixed-rate_compressed_floating-point_arrays.json new file mode 100644 index 00000000..172291f4 --- /dev/null +++ b/agency-indexes/DoE/Fixed-rate_compressed_floating-point_arrays.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "ZFP is a library for lossy compression of single- and double-precision floating-point data. One of the unique features of ZFP is its support for fixed-rate compression, which enables random read and write access at the granularity of small blocks of values. Using a C++ interface, this allows declaring compressed arrays (1D, 2D, and 3D arrays are supported) that through operator overloading can be treated just like conventional, uncompressed arrays, but which allow the user to specify the exact number of bits to allocate to the array. ZFP also has variable-rate fixed-precision and fixed-accuracy modes, which allow the user to specify a tolerance on the relative or absolute error.", + "laborHours": 9272.0, + "languages": [], + "name": "Fixed-rate compressed floating-point arrays", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/zfp/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ZFP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Flang_LLVM_Fortran_compiler.json b/agency-indexes/DoE/Flang_LLVM_Fortran_compiler.json new file mode 100644 index 00000000..f64d7f9d --- /dev/null +++ b/agency-indexes/DoE/Flang_LLVM_Fortran_compiler.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "Flang is a Fortran language front-end designed for integration with LLVM.", + "laborHours": 607939.2, + "languages": [], + "name": "Flang/LLVM Fortran compiler", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/flang-compiler/flang", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Flash-X.json b/agency-indexes/DoE/Flash-X.json new file mode 100644 index 00000000..d9c42f9b --- /dev/null +++ b/agency-indexes/DoE/Flash-X.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-03-17", + "metadataLastUpdated": "2024-02-26" + }, + "description": "Flash-X is a highly composable multiphysics software system that can be used to simulate physical phenomena in several scientific domains. It is derived from FLASH, which has been a community code for several communities over the last 20 years. The Flash-X architecture has been redesigned to be compatible with increasingly heterogeneous hardware platforms. A part of the redesign is a utilizing a newly designed performance portability layer that is language agnostic.", + "homepageURL": "https://flash-x.org", + "laborHours": 0.0, + "languages": [ + "C++", + "C", + "Fortran", + "Python" + ], + "name": "Flash-X", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://flash-x.org", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Flaviolin_Media_Optimization_C1_v1.0.json b/agency-indexes/DoE/Flaviolin_Media_Optimization_C1_v1.0.json new file mode 100644 index 00000000..0e6a3f08 --- /dev/null +++ b/agency-indexes/DoE/Flaviolin_Media_Optimization_C1_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-09-03", + "metadataLastUpdated": "2024-09-03" + }, + "description": "Use of media compiler and ART to perform media optimization", + "laborHours": 153976.0, + "languages": [], + "name": "Flaviolin_Media_Optimization_C1 v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/Flaviolin_media_opt_C1", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Flaviolin_Media_Optimization_C2_v1.0.json b/agency-indexes/DoE/Flaviolin_Media_Optimization_C2_v1.0.json new file mode 100644 index 00000000..ff940aa7 --- /dev/null +++ b/agency-indexes/DoE/Flaviolin_Media_Optimization_C2_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-09-03", + "metadataLastUpdated": "2024-09-03" + }, + "description": "Use of media compiler and ART to perform media optimization for titer maximization in flaviolin producing P. putida", + "laborHours": 3754.4, + "languages": [], + "name": "Flaviolin_Media_Optimization_C2 v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/Flaviolin_media_opt_C2", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FleCSPH_-_a_parallel_and_distributed_SPH_implementation_based_on_the_FleCSI_framework.json b/agency-indexes/DoE/FleCSPH_-_a_parallel_and_distributed_SPH_implementation_based_on_the_FleCSI_framework.json new file mode 100644 index 00000000..49d98a2c --- /dev/null +++ b/agency-indexes/DoE/FleCSPH_-_a_parallel_and_distributed_SPH_implementation_based_on_the_FleCSI_framework.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "FleCSPH is a multi-physics compact application that exercises FleCSI parallel data structures for tree-based particle methods. In particular, FleCSPH implements a smoothed-particle hydrodynamics (SPH) solver for the solution of Lagrangian problems in astrophysics and cosmology. FleCSPH includes support for gravitational forces using the fast multipole method (FMM).", + "laborHours": 10001.6, + "name": "FleCSPH - a parallel and distributed SPH implementation based on the FleCSI framework", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laristra/flecsph", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FlexDRL_v1.0.json b/agency-indexes/DoE/FlexDRL_v1.0.json new file mode 100644 index 00000000..e5da074c --- /dev/null +++ b/agency-indexes/DoE/FlexDRL_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2021-03-12" + }, + "description": "FlexDRL is a framework that can be used as a benchmarking tool to evaluate different Deep Reinforcement Learning algorithms in a building energy management setting. OpenAI Gym was used as wrapper to the co-simulation environment (EnergyPlus for envelope and HVAC and Modelica for battery and PV) to interface with DRL algorithms, which are developed in PyTorch. In order to facilitate the usage of FlexDRL, all the required dependencies have been packaged into a Docker container.", + "laborHours": 0.0, + "languages": [], + "name": "FlexDRL v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/FlexDRL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FlexFlow_.json b/agency-indexes/DoE/FlexFlow_.json new file mode 100644 index 00000000..7a20301b --- /dev/null +++ b/agency-indexes/DoE/FlexFlow_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "FlexFlow is a deep learning framework and engine, built using the Legion Programming System, that accelerates distributed deep neural network training by automatically discovering fast parallelization strategies. This is achieved by using a guided randomized search to find a fast parallelization strategy for a specific parallel machine architecture. To accelerate this search, FlexFlow introduces a novel execution simulator that can accurately predict a parallelization strategy\u2019s performance and is three orders of magnitude faster than prior approaches that execute each strategy. FlexFlow currently out-performs common industry software frameworks like Google's TensorFlow/Keras and Facebook's PyTorch by factors ranging from 3 to 15 times.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "FlexFlow ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Flexible_Computer_Science_Infrastructure__FleCSI_.json b/agency-indexes/DoE/Flexible_Computer_Science_Infrastructure__FleCSI_.json new file mode 100644 index 00000000..4727d078 --- /dev/null +++ b/agency-indexes/DoE/Flexible_Computer_Science_Infrastructure__FleCSI_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "FleCSI is a compile-time configurable framework designed to support multi-physics application development. As such, FleCSI attempts to provide a very general set of infrastructure design patterns that can be specialized and extended to suit the needs of a broad variety of solver and data requirements. Current support includes multi-dimensional mesh topology, mesh geometry, and mesh adjacency information, n-dimensional hashed-tree data structures, graph partitioning interfaces, and dependency closures. FleCSI also introduces a functional programming model with control, execution, and data abstractions that are consistent with both MPI and state-of-the-art task-based runtimes such as Legion and Charm++. The FleCSI abstraction layer provides the developer with insulation from the underlying runtime, while allowing support for multiple runtime systems, including conventional models like asynchronous MPI. The intent is to give developers a concrete set of user-friendly programming tools that can be used now, while allowing flexibility in choosing runtime implementations and optimizations that can be applied to architectures and runtimes that arise in the future. The control and execution models in FleCSI also provide formal nomenclature for describing poorly understood concepts like kernels and tasks.", + "laborHours": 334.4, + "name": "Flexible Computer Science Infrastructure (FleCSI)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/laristra/flecsi-third-party", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/flecsi-third-party", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Flexible_File_Sort_Utility.json b/agency-indexes/DoE/Flexible_File_Sort_Utility.json new file mode 100644 index 00000000..3a7bb972 --- /dev/null +++ b/agency-indexes/DoE/Flexible_File_Sort_Utility.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This program sorts a text file alphabetically (forward or reverse). It supports both in-memory sorts for smaller files and use of temporary swap files for large files. It can alternatively sort on a column in a tab-delimited or comma-separated file. The column sort mode also supports numeric sorting.", + "laborHours": 1763.2, + "languages": [], + "name": "Flexible File Sort Utility", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/FlexibleFileSortUtility", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Flexible_Optimized_Coils_Using_Space_curves__FOCUS_.json b/agency-indexes/DoE/Flexible_Optimized_Coils_Using_Space_curves__FOCUS_.json new file mode 100644 index 00000000..d73dca0e --- /dev/null +++ b/agency-indexes/DoE/Flexible_Optimized_Coils_Using_Space_curves__FOCUS_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "czhu@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2018-06-27" + }, + "description": "FOCUS uses 3D curves to represent coils in fusion devices, mainly for toroidal devices including stellarators and tokamaks. For a given configuration, FOCUS can find optimal coils, which can produced the required magnetic field for confining the plasma meeting the user-specified physics and engineering constraints.", + "homepageURL": "https://princetonuniversity.github.io/FOCUS", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Flexible Optimized Coils Using Space curves (FOCUS)", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://princetonuniversity.github.io/FOCUS", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "version": "0.3.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Flexible_configuration-interaction_shell-model_many-body_solver.json b/agency-indexes/DoE/Flexible_configuration-interaction_shell-model_many-body_solver.json new file mode 100644 index 00000000..18ac6246 --- /dev/null +++ b/agency-indexes/DoE/Flexible_configuration-interaction_shell-model_many-body_solver.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "BIGSTICK Is a flexible configuration-Interaction open-source shell-model code for the many-fermion problem In a shell model (occupation representation) framework. BIGSTICK can generate energy spectra, static and transition one-body densities, and expectation values of scalar operators. Using the built-in Lanczos algorithm one can compute transition probabflity distributions and decompose wave functions into components defined by group theory.", + "laborHours": 40690.4, + "languages": [ + "Fortran 90" + ], + "name": "Flexible configuration-interaction shell-model many-body solver", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cwjsdsu/BigstickPublick", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Flibcpp.json b/agency-indexes/DoE/Flibcpp.json new file mode 100644 index 00000000..e2b49955 --- /dev/null +++ b/agency-indexes/DoE/Flibcpp.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "johnsonsr@ornl.gov" + }, + "date": { + "created": "2021-01-31", + "metadataLastUpdated": "2021-02-01" + }, + "description": "Flibcpp is a library for use by application developers that provides native Fortran interfaces to existing high-quality algorithms and containers implemented in C++ and available on all modern computer systems.", + "laborHours": 0.0, + "languages": [ + "C++", + "Fortran", + "SWIG" + ], + "name": "Flibcpp", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/swig-fortran/flibcpp", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/FloatingSE__WISDEM\302\256__[SWR-15-33].json" "b/agency-indexes/DoE/FloatingSE__WISDEM\302\256__[SWR-15-33].json" new file mode 100644 index 00000000..5ef4f2e1 --- /dev/null +++ "b/agency-indexes/DoE/FloatingSE__WISDEM\302\256__[SWR-15-33].json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-10-25" + }, + "description": "***THIS REPOSITORY HAS BEEN ARCHIVED BY THE OWNER ON JUNE 19, 2020. IT IS NOW READ ONLY. ***DEPRECATED: Python version of floating sizing tools compatible with WISDEM FloatingSE is a set of models for analyzing the floating support structures for offshore wind plants. Author: NREL WISDEM Team", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "FloatingSE (WISDEM\u00ae) [SWR-15-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/FloatingSE", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Floorspace.js.json b/agency-indexes/DoE/Floorspace.js.json new file mode 100644 index 00000000..44afe08e --- /dev/null +++ b/agency-indexes/DoE/Floorspace.js.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "Floorspace.js is a 2D geometry editor. Users can define an explicit floor plan for each story of a building. A story-by-story interface makes it easy to develop space geometry and assign properties. Referencing satellite imagery or floor plan images, when available, speeds up geometry entry. Conversion of 2D to 3D geometry is currently out of scope for Floorspace.js, a reference implementation is available in the OpenStudio\u00ae SDK. Explicit floor plans allow more building-specific information than parameterized shoe-boxes but less information than a full 3D BIM model. Sloped walls, complex roofs, detailed shading structures, and other complex 3D structures are out of FloorspaceJS's scope. In general, if users have a 3D BIM model in a tool that can export a useful BEM representation then it is better to use that export than to recreate a new model using FloorspaceJS. Re-usability and minimal dependencies were key design considerations for software developers. Web technologies can be used in both online and desktop applications. The editor was written in pure JavaScript for maximum portability and re-usability. A custom JavaScript Object Notation (JSON) file format was developed to ease integration with other applications. Custom JSON schema design was a key part of FloorspaceJS development.", + "laborHours": 0.0, + "languages": [ + "C++", + "JavaScript", + "Vue" + ], + "name": "Floorspace.js", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/floorspace.js", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "V0.8.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FloorspaceJS.json b/agency-indexes/DoE/FloorspaceJS.json new file mode 100644 index 00000000..4e111c5a --- /dev/null +++ b/agency-indexes/DoE/FloorspaceJS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "A widget for creating 2d geometry for building energy models.\n", + "laborHours": 19167.2, + "languages": [], + "name": "FloorspaceJS", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/openstudio-geometry-editor/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/openstudio-geometry-editor", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Flow-Bench:_A_Dataset_for_Computational_Workflow_Anomaly_Detection.json b/agency-indexes/DoE/Flow-Bench:_A_Dataset_for_Computational_Workflow_Anomaly_Detection.json new file mode 100644 index 00000000..b085eb96 --- /dev/null +++ b/agency-indexes/DoE/Flow-Bench:_A_Dataset_for_Computational_Workflow_Anomaly_Detection.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-18", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Flow-Bench is a benchmark dataset for anomaly detection techniques in computational workflows. Flow-Bench contains workflow execution traces, executed on distributed infrastructure, that include systematically injected anomalies (labeled), and offers both the raw execution logs and a more compact parsed version. In this GitHub repository, apart from the logs and traces, you will find sample code to load and process the parsed data using pytorch, as well as, the code used to parse the raw logs and events.", + "laborHours": 14272.8, + "languages": [], + "name": "Flow-Bench: A Dataset for Computational Workflow Anomaly Detection", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/FlowBench", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FlowBench_Raw_Data_Archive.json b/agency-indexes/DoE/FlowBench_Raw_Data_Archive.json new file mode 100644 index 00000000..f427f425 --- /dev/null +++ b/agency-indexes/DoE/FlowBench_Raw_Data_Archive.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-18", + "metadataLastUpdated": "2024-08-20" + }, + "description": "The repo that provides data archive for DOE PoSeiDon project. It also contains scripts and instructions to parse the data.", + "laborHours": 349.6, + "languages": [], + "name": "FlowBench Raw Data Archive", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/FlowBench-Raw-Workflow-Data", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fluorescent_Amplification_of_Next_Generation_Sequencing_Libraries_Tools__FA-NGS_tools__v1.json b/agency-indexes/DoE/Fluorescent_Amplification_of_Next_Generation_Sequencing_Libraries_Tools__FA-NGS_tools__v1.json new file mode 100644 index 00000000..9962b63f --- /dev/null +++ b/agency-indexes/DoE/Fluorescent_Amplification_of_Next_Generation_Sequencing_Libraries_Tools__FA-NGS_tools__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-21", + "metadataLastUpdated": "2019-10-21" + }, + "description": "This is a software utility for calculating pooling volumes and graphing quality control data of next generation sequencing libraries amplified with fluorescent intercalating agents and monitored by real-time quantitative PCR (qPCR). The tool is used to calculate pooling volumes of individual next generation sequencing libraries based on experimentally determined fluorescence values. To do this, fluorescent values are used as a proxy for relative concentration to determine the ratio of transfer volumes. The output is a \"transfer file\" that specifies the transfer volume and destination well of a given library. The tool can also be used to assess the quality of individual next generation sequencing libraries by melting curve analysis. The output are small-multiples graphs of the melting curves of individual sequencing libraries according to the specified plate layout.", + "laborHours": 152.0, + "languages": [], + "name": "Fluorescent Amplification of Next Generation Sequencing Libraries Tools (FA-NGS tools) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AgileBioFoundry/FA-NGS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Flux_Resource_Manager_Framework.json b/agency-indexes/DoE/Flux_Resource_Manager_Framework.json new file mode 100644 index 00000000..6219424f --- /dev/null +++ b/agency-indexes/DoE/Flux_Resource_Manager_Framework.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-01-31", + "metadataLastUpdated": "2019-02-04" + }, + "description": "First, note: flux framework, and the flux framework projects, are already released under GPLv2 and LGPLv2 for linkable components since roughly 2014. This request is to re-license the flux framework in full to LGPLv3 to better support vendor collaboration and allow use of external apache2 and similarly licensed libraries.\nflux is a framework for writing resource managers as well as a resource manager for HPC systems. It allows for hierarchical nesting and providing a portable interface for job scheduling across systems.", + "laborHours": 118028.0, + "languages": [], + "name": "Flux Resource Manager Framework", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/flux-framework/flux-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Flux_wrapper_scripts.json b/agency-indexes/DoE/Flux_wrapper_scripts.json new file mode 100644 index 00000000..b5936b0c --- /dev/null +++ b/agency-indexes/DoE/Flux_wrapper_scripts.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-10-29", + "metadataLastUpdated": "2021-10-29" + }, + "description": "The Flux Wrapper Scripts translate the commands used by other HPC resource / workload management tools to Flux commands in order to provide a bridge for HPC users between other HPC resource / workload management tools and the Flux resource manager.", + "laborHours": 0.0, + "languages": [], + "name": "Flux wrapper scripts", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/flux-wrappers", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Foldy_v1.json b/agency-indexes/DoE/Foldy_v1.json new file mode 100644 index 00000000..c220cd92 --- /dev/null +++ b/agency-indexes/DoE/Foldy_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "We created a cloud-based application for running AlphaFold2 and related structural programs called Foldy. Foldy is built on Helm / Kubernetes, which enables a facile production deployment and a scalable backend. Once set up by an institution, Foldy requires no software expertise from its users. It can be used to predict the structure of large proteins (up to 3000 amino acids), to visualize Pfam and antiSMASH annotations, and to perform ligand docking with Autodock Vina.", + "laborHours": 32224.0, + "languages": [], + "name": "Foldy v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/foldy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Foobug.json b/agency-indexes/DoE/Foobug.json new file mode 100644 index 00000000..af6d7668 --- /dev/null +++ b/agency-indexes/DoE/Foobug.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Foobug is an application to assist a group of developers in keeping track of issues relevant to their shared interests. These are sometimes called \"bug-tracking\" or \"ticket-tracking\" systems.", + "homepageURL": "http://sourceforge.net/projects/foobug", + "laborHours": 0.0, + "name": "Foobug", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://sourceforge.net/projects/foobug", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ForQint.json b/agency-indexes/DoE/ForQint.json new file mode 100644 index 00000000..06625944 --- /dev/null +++ b/agency-indexes/DoE/ForQint.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "ForQint is a Fortran software library to adaptively integrate multivariable functions versus well known probability distributions (e.g. normal, lognormal, etc.) using quadrature rules. Such integration is known to be more efficient and accurate especially when the function evaluation is expensive. The library also FQint enables the creation of both full and sparse anisotropic multi-dimensional quadrature rules. These latter encompass different such as Gauss-Hermite, Gauss-Legendre, etc. The functions Maher Salloum, Bert Debusschere, Kenny Chowdhary and subroutines rely on the C++ Stokhos package of Trilinos (trilinos.sandia.gov) where the appropriate classes were wrapped into Fortran.", + "laborHours": 699.2, + "languages": [ + "Makefile", + "Fortran" + ], + "name": "ForQint", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ForQint", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ForTrilinos.json b/agency-indexes/DoE/ForTrilinos.json new file mode 100644 index 00000000..d9c3b4b5 --- /dev/null +++ b/agency-indexes/DoE/ForTrilinos.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-10-29" + }, + "description": "'ForTrilinos' is related to The Trilinos Project, which contains a large and growing collection of solver capabilities that can utilize next-generation platforms, in particular scalable multicore, manycore, accelerator and heterogeneous systems. Trilinos is primarily written in C++, including its user interfaces. While C++ is advantageous for gaining access to the latest programming environments, it limits Trilinos usage via Fortran. Sever ad hoc translation interfaces exist to enable Fortran usage of Trilinos, but none of these interfaces is general-purpose or written for reusable and sustainable external use. 'ForTrilinos' provides a seamless pathway for large and complex Fortran-based codes to access Trilinos without C/C++ interface code. This access includes Fortran versions of Kokkos abstractions for code execution and data management. ", + "laborHours": 165087.2, + "languages": [ + "C++", + "Fortran" + ], + "name": "ForTrilinos", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/ForTrilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ForTrilinos_v_10.1.json b/agency-indexes/DoE/ForTrilinos_v_10.1.json new file mode 100644 index 00000000..7cb3c38a --- /dev/null +++ b/agency-indexes/DoE/ForTrilinos_v_10.1.json @@ -0,0 +1,40 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "ForTrilinos stands for interfaces to Trilinos. It effectively replaces common practices for interfacing Fortran codes with Trilinos C++ packages. Common practices include writing user-specific drivers and exploiting the name-mangling schemes of specific compilers. ForTrilinos improves portability and robustness by exploiting the C interoperability constructs of Fortran 2003. These constructs facilitate binding Fortran interface bodies to their equivalent C function prototypes, providing for name resolution independent of the compiler\u2122s underlying mangling scheme and guaranteeing compatible type bit representations. Furthermore, ForTrilinos maintains the overall design philosophy and architecture of Trilinos by creating a derived type structure in Fortran similar to the class hierarchy in the underlying C++.ForTrilinos can be applied wherever the underlying Trilinos packages can be applied.", + "laborHours": 165087.2, + "languages": [ + "Dockerfile", + "C++", + "Shell", + "SWIG", + "CMake", + "Fortran", + "Python" + ], + "name": "ForTrilinos v 10.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/ForTrilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "10.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Force-Field_Parameter_Fitter.json b/agency-indexes/DoE/Force-Field_Parameter_Fitter.json new file mode 100644 index 00000000..6359c7ad --- /dev/null +++ b/agency-indexes/DoE/Force-Field_Parameter_Fitter.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "joiner@ameslab.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ParFit is a flexible and extendable framework and library of classes for fitting force-field parameters to data from high-level ab-initio calculations on the basis of deterministic and stochastic algorithms. Currently, the code is fitting MM3 and Merck force-field parameters but could easily extend to other force-field types.", + "laborHours": 31874.4, + "name": "Force-Field Parameter Fitter", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fzahari/ParFit", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fork_of_Reflow_v.1.0.2.json b/agency-indexes/DoE/Fork_of_Reflow_v.1.0.2.json new file mode 100644 index 00000000..452d6bb8 --- /dev/null +++ b/agency-indexes/DoE/Fork_of_Reflow_v.1.0.2.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00898O\nFork of Reflow is a software tool that extends the functionality of NASA Reflow to support relevant projects. It provides automated reasoning support for floating-point roundoff error in numerical computer programs. The tool integrates with Frama-C and the PVS theorem prover to specify and verify program properties, ensuring compliance with specifications through weakest-precondition style analysis. This fork enhances automated reasoning features and enables direct analysis of C code, making it suitable for applications involving small programs with floating-point computations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Haskell", + "PVS", + "C" + ], + "name": "Fork of Reflow v.1.0.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fortran_Language_Compatibility_Layer__FLCL_.json b/agency-indexes/DoE/Fortran_Language_Compatibility_Layer__FLCL_.json new file mode 100644 index 00000000..16c3e910 --- /dev/null +++ b/agency-indexes/DoE/Fortran_Language_Compatibility_Layer__FLCL_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "The Kokkos Fortran Interop repository contains tools and interfaces which help interactions between Fortran portions of an applications and C++ portions using Kokkos.", + "laborHours": 20702.4, + "languages": [], + "name": "Fortran Language Compatibility Layer (FLCL)", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/kokkos-fortran-interop", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fourier-Bessel_Particle-In-Cell__FBPIC__v0.1.0.json b/agency-indexes/DoE/Fourier-Bessel_Particle-In-Cell__FBPIC__v0.1.0.json new file mode 100644 index 00000000..a7e9e3e1 --- /dev/null +++ b/agency-indexes/DoE/Fourier-Bessel_Particle-In-Cell__FBPIC__v0.1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The Fourier-Bessel Particle-In-Cell code is a scientific simulation software for relativistic plasma physics. It is a Particle-In-Cell code whose distinctive feature is to use a spectral decomposition in cylindrical geometry.\r\n\r\nThis decomposition allows to combine the advantages of spectral 3D Cartesian PIC codes (high accuracy and stability) and those of finite-difference cylindrical PIC codes with azimuthal decomposition (orders-of-magnitude speedup when compared to 3D simulations).\r\n\r\nThe code is built on Python and can run both on CPU and GPU (the GPU runs being typically 1 or 2 orders of magnitude faster than the corresponding CPU runs.)\r\n\r\nThe code has the exact same output format as the open-source PIC codes Warp and PIConGPU (openPMD format: openpmd.org) and has a very similar input format as Warp (Python script with many similarities). There is therefore tight interoperability between Warp and FBPIC, and this interoperability will increase even more in the future.", + "laborHours": 16233.6, + "languages": [ + "None" + ], + "name": "Fourier-Bessel Particle-In-Cell (FBPIC) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fbpic/fbpic", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FrESCO.json b/agency-indexes/DoE/FrESCO.json new file mode 100644 index 00000000..89e9d080 --- /dev/null +++ b/agency-indexes/DoE/FrESCO.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "spannausat@ornl.gov" + }, + "date": { + "created": "2023-02-08", + "metadataLastUpdated": "2023-08-22" + }, + "description": "The National Cancer Institute (NCI) monitors population level cancer trends as part of its Surveillance, Epidemiology, and End Results (SEER) program. This program consists of state or regional level cancer registries which collect, analyze, and annotate cancer pathology reports. From these annotated pathology reports, each individual registry aggregates cancer phenotype information and summary statistics about cancer prevalence to facilitate population level monitoring of cancer incidence. Extracting cancer phenotype from these reports is a labor intensive task, requiring specialized knowledge about the reports and cancer. Automating this information extraction process from cancer pathology reports has the potential to improve not only the quality of the data by extracting information in a consistent manner across registries, but to improve the quality of patient outcomes by reducing the time to assimilate new data and enabling time-sensitive applications such as precision medicine. Here we present FrESCO: Framework for Exploring Scalable Computational Oncology, a modular deep-learning natural language processing (NLP) library for extracting pathology information from clinical text documents.", + "laborHours": 0.0, + "languages": [], + "name": "FrESCO", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DOE-NCI-MOSSAIC/FrESCO", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v0.2.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fracturing_And_Liquid_CONvection.json b/agency-indexes/DoE/Fracturing_And_Liquid_CONvection.json new file mode 100644 index 00000000..d0d0681e --- /dev/null +++ b/agency-indexes/DoE/Fracturing_And_Liquid_CONvection.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "FALCON has been developed to enable simulation of the tightly coupled fluid-rock behavior in hydrothermal and engineered geothermal system (EGS) reservoirs, targeting the dynamics of fracture stimulation, fluid flow, rock deformation, and heat transport in a single integrated code, with the ultimate goal of providing a tool that can be used to test the viability of EGS in the United States and worldwide. Reliable reservoir performance predictions of EGS systems require accurate and robust modeling for the coupled thermal\u00adhydrological\u00admechanical processes.", + "laborHours": 23043.2, + "languages": [], + "name": "Fracturing And Liquid CONvection", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/falcon", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Framework_For_Optimization_Of_Resources_And_Economics_Ecosystem.json b/agency-indexes/DoE/Framework_For_Optimization_Of_Resources_And_Economics_Ecosystem.json new file mode 100644 index 00000000..b024b1e8 --- /dev/null +++ b/agency-indexes/DoE/Framework_For_Optimization_Of_Resources_And_Economics_Ecosystem.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-05-11", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The Framework for Optimization of ResourCes and Economics is a collection of software tools, models, and datasets acquired and developed under the Integrated Energy Systems (IES) program to enable analysis of technical and economic viability of myriad IES configurations. FORCE is the consolidating interface and data repository for all the IES toolsets ranging from macro technoeconomic analysis to transient process modeling and experimental validation for integrated energy systems.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Framework For Optimization Of Resources And Economics Ecosystem", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/FORCE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "XML, Python, Modelica" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Framework_For_Performing_Time-dependent_Pebble_Bed_Reactor_Simulations.json b/agency-indexes/DoE/Framework_For_Performing_Time-dependent_Pebble_Bed_Reactor_Simulations.json new file mode 100644 index 00000000..50b64bd2 --- /dev/null +++ b/agency-indexes/DoE/Framework_For_Performing_Time-dependent_Pebble_Bed_Reactor_Simulations.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-08-05", + "metadataLastUpdated": "2024-08-05" + }, + "description": "The present work details the creation of a high-fidelity Monte Carlo methodology for analyzing the run-in and subsequent approach to equilibrium for PBRs. The methodology entails a Python module wrapped around Serpent so as to perform neutronics calculations, move pebbles, refuel the core, and discharge pebbles, thereby modeling the explicit behavior of the PBR run-in. The code kugelpy is within the GitHub repository `pyrates`.", + "laborHours": 3116.0, + "languages": [ + "Python" + ], + "name": "Framework For Performing Time-dependent Pebble Bed Reactor Simulations", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/kugelpy", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Framework_for_Analysis_and_Visualization_of_Simulation_Data__VizAly_.json b/agency-indexes/DoE/Framework_for_Analysis_and_Visualization_of_Simulation_Data__VizAly_.json new file mode 100644 index 00000000..d7c8d05f --- /dev/null +++ b/agency-indexes/DoE/Framework_for_Analysis_and_Visualization_of_Simulation_Data__VizAly_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2017-12-11", + "metadataLastUpdated": "2018-01-10" + }, + "description": "As supercomputing resources increase, cosmological scientists are able to run more detailed and larger simulations generating massive amounts of data. Analyzing these simulations with an available open-source toolkit is important for collaborative Department of Energy scientific discovery across labs, universities, and other partners. Developed software as a part of this collection include: comparing data with other existing simulations, verifying and validating results with observation databases, new halo finder algorithms, and using analytical tools to get insights into the physics of the\ncosmological universe. The goal of this software project is to provide a set of open-source libraries, tools, and packages for large-scale cosmology that allows scientists to visualize, analyze, and compare large-scale simulation and observational\ndata sets. Developed software will provide a variety of methods for processing, visualization, and analysis of astronomical observation and cosmological simulation data. These tools are intended for deployment on multiple scientific computing\nplatforms, including but not limited to personal computers, cloud computing, experimental sites (telescopes) and high performance supercomputers.", + "laborHours": 101308.0, + "name": "Framework for Analysis and Visualization of Simulation Data (VizAly)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/VizAly", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Framework_for_Multi_Layer_Control_in_Python__FMLC__v1.0.json b/agency-indexes/DoE/Framework_for_Multi_Layer_Control_in_Python__FMLC__v1.0.json new file mode 100644 index 00000000..8e619c2d --- /dev/null +++ b/agency-indexes/DoE/Framework_for_Multi_Layer_Control_in_Python__FMLC__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-29", + "metadataLastUpdated": "2019-10-29" + }, + "description": "This package is developed as a backend for multi-layer and multi-time domain controller. One example are controller based on [Model Predictive Control] (MPC) where different modules with different time constants have to be coordinated to allow optimal control. In a simple example, the Weather Forecast must be acquired and processed, the MPC is computed, and finally the control is applied. All these modules typically run on the same time step (Time step: 5 minutes), but are different instances within the framework. The framework allows parallelization using the `multiprocessing` module. However, another real-time controller (Time step: 1 second) must be applied to react on instant system disturbances beyond the MPC time step. Last, a supervisory MPC controller (Time step: 1 hour) might be added to ensure global optimality.", + "laborHours": 501.6, + "languages": [], + "name": "Framework for Multi Layer Control in Python (FMLC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/FMLC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Framework_for_Network_Co-Simulation.json b/agency-indexes/DoE/Framework_for_Network_Co-Simulation.json new file mode 100644 index 00000000..b0724ef7 --- /dev/null +++ b/agency-indexes/DoE/Framework_for_Network_Co-Simulation.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Framework for Network Co-Simulation (FNCS) uses a federated approach to integrate simulations which may have differing time scales. Special consideration is given to integration with a communication network simulation such that inter-simulation messages may be optionally routed through and delayed by such a simulation. In addition, FNCS uses novel time synchronization algorithms to accelerate co-simulation including the application of speculative multithreading. FNCS accomplishes all of these improvements with minimal end user intervention. Simulations can be integrated using FNCS while maintaining their original model input files simply by linking with the FNCS library and making appropriate calls into the FNCS API.", + "laborHours": 38592.8, + "name": "Framework for Network Co-Simulation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/FNCS/fncs/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FNCS/fncs", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Framework_for_Network_Co-simulation_v._2.x.json b/agency-indexes/DoE/Framework_for_Network_Co-simulation_v._2.x.json new file mode 100644 index 00000000..7fda07a3 --- /dev/null +++ b/agency-indexes/DoE/Framework_for_Network_Co-simulation_v._2.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Not Specified", + "laborHours": 39793.6, + "name": "Framework for Network Co-simulation v. 2.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GridOPTICS/FNCS/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GridOPTICS/FNCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Framework_for_Radiance_Simulation_Control__Frads__v1.0.json b/agency-indexes/DoE/Framework_for_Radiance_Simulation_Control__Frads__v1.0.json new file mode 100644 index 00000000..b2ae2c83 --- /dev/null +++ b/agency-indexes/DoE/Framework_for_Radiance_Simulation_Control__Frads__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-11-13", + "metadataLastUpdated": "2019-11-13" + }, + "description": "Radiance matrix algebraic methods enable efficient annual daylight simulation while preserving accuracy. The five sub-methods, 2 to 6 phase methods, enable scene components parameterization and separation of direct and diffuse flux transfer based on the user's need. However, the burden is on the user to figure out the which method, matrix basis, matrix resolution, simulation parameters to use to achieve the desired efficiency and accuracy to the end application. Several utility programs and an executive program (in-progress) were created to lower the entry barrier and to reduce human error when executing the simulation. This suite of programs should also reduce the burden of adopting Radiance matrix methods for third party software.", + "laborHours": 729.6, + "languages": [], + "name": "Framework for Radiance Simulation Control (Frads) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/frads", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Framework_for_Research_in_Nuclear_Science_and_Engineering_v._0.3.0.json b/agency-indexes/DoE/Framework_for_Research_in_Nuclear_Science_and_Engineering_v._0.3.0.json new file mode 100644 index 00000000..f01cd824 --- /dev/null +++ b/agency-indexes/DoE/Framework_for_Research_in_Nuclear_Science_and_Engineering_v._0.3.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "FRENSIE (the Framework for Research in Nuclear Science and Engineering) is a Monte Carlo code for solving linear particle transport problems with neutron, photon, and electron particles.", + "laborHours": 228927.2, + "languages": [ + "C++" + ], + "name": "Framework for Research in Nuclear Science and Engineering v. 0.3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lkersting/SCR-2123", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Framework_for_Unified_Systems_Engineering_and_Design_of_Wind_Plants__FUSED-Wind__cost_models_and_case_analyzer_[SWR-14-25].json b/agency-indexes/DoE/Framework_for_Unified_Systems_Engineering_and_Design_of_Wind_Plants__FUSED-Wind__cost_models_and_case_analyzer_[SWR-14-25].json new file mode 100644 index 00000000..2ba429f2 --- /dev/null +++ b/agency-indexes/DoE/Framework_for_Unified_Systems_Engineering_and_Design_of_Wind_Plants__FUSED-Wind__cost_models_and_case_analyzer_[SWR-14-25].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Framework for Unified Systems Engineering and Design of Wind Plants ( FUSED-Wind) is an open-source framework for multi-disciplinary optimisation and analysis (MDAO) of wind energy systems, developed jointly by DTU and NREL. The framework is designed as an extension to the NASA developed OpenMDAO, and defines key I/O elements and methods necessary for wiring together different simulation codes in order to achieve a system level analysis capability of wind turbine plants with multiple levels of fidelity. NREL and DTU have developed independent interfaces to their respective simulation codes and cost models (e.g. FAST/CCBlade, HAWC2/BECAS) with the aim of offering an environment where these codes can be used interchangeably. The open source nature of the framework enables third parties to develop interfaces to their own tools, either replacing or extending those offered by DTU and NREL.", + "laborHours": 12935.2, + "languages": [ + "Python" + ], + "name": "Framework for Unified Systems Engineering and Design of Wind Plants (FUSED-Wind) cost models and case analyzer [SWR-14-25]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FUSED-Wind/fusedwind", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Framework_for_an_Information_Visualization_System.json b/agency-indexes/DoE/Framework_for_an_Information_Visualization_System.json new file mode 100644 index 00000000..69cfc354 --- /dev/null +++ b/agency-indexes/DoE/Framework_for_an_Information_Visualization_System.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Program is a suite of Windows-based software applications and services for ingesting, storing, and analyzing large quantities of disparate information. The software supports the ingestion and storage of any information that can be represented in eXtensible Markup Language (XML) format. Stored information can be subsequently retrieved via search operations, then \"visualized\" in multiple ways using a client application that supports a variety of analytical functions. Visualization capabilities include tools for depicting a variety of relationships that may be present in the information, including geospatial, temporal, topical, categorical, and network relationships.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++, Microsoft.net2003 7.1" + ], + "name": "Framework for an Information Visualization System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Frequency_Response_Tool.json b/agency-indexes/DoE/Frequency_Response_Tool.json new file mode 100644 index 00000000..32a0f585 --- /dev/null +++ b/agency-indexes/DoE/Frequency_Response_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-24", + "metadataLastUpdated": "2021-06-10" + }, + "description": "According to the North American Electric Reliability Corporation (NERC) definition: \"Frequency response is a measure of an Interconnection's ability to stabilize frequency immediately following the sudden loss of generation or load, and is a critical component of the reliable operation of the Bulk-Power System, particularly during disturbances and recoveries. Failure to maintain frequency can disrupt the operation of equipment and initiate disconnection of power plant equipment to prevent it from being damaged, which could lead to wide-spread blackouts.\" Frequency Response Tool automates the power system frequency response analysis process. The tool performs initial estimation of the system frequency parameters (initial frequency, minimum frequency, settling point). User can visually inspect and adjust these parameters. The tool also calculates the frequency response performance metrics of the system, archives the historic events and baselines the system performance. Frequency response performance characteristics of the system are calculated using phasor measurement unit (PMU) information. Methodology of the frequency response performance assessment implemented in the tool complies with the NERC Frequency response standard.", + "homepageURL": "https://svn.pnl.gov/FRTool", + "laborHours": 0.0, + "languages": [ + "VB.NET" + ], + "name": "Frequency Response Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://svn.pnl.gov/FRTool#License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.pnl.gov/FRTool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Frescox.json b/agency-indexes/DoE/Frescox.json new file mode 100644 index 00000000..04eb3ee1 --- /dev/null +++ b/agency-indexes/DoE/Frescox.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-24", + "metadataLastUpdated": "2020-06-24" + }, + "description": "FRESCOX is a flexible, science-oriented, and general-purpose computer code that models direct\nreactions during the interaction of two atomic nuclei. FRESCOX is a coupled-channels program that can\nhave finite-range transfer interactions among any number of mass partitions, and any number of nuclear\nexcitations in each partition.", + "laborHours": 43532.8, + "languages": [], + "name": "Frescox", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Frescox", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FriendlyNets.json b/agency-indexes/DoE/FriendlyNets.json new file mode 100644 index 00000000..9b0b9560 --- /dev/null +++ b/agency-indexes/DoE/FriendlyNets.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "FriendlyNets provides a method for assessing the promotion/inhibition effect on a microbe of a microbial community using a network of community interactions. At its core, FriendlyNets judges how much a network promotes or inhibits one of its nodes. It does this by assuming a set of dynamical systems represented by the network and using the resulting dynamics. FriendlyNets is also packaged with functions for generating a network from a set of genome-scale metabolic models (commonly called GSMs or GEMs) by simulating pairwise growth.", + "laborHours": 0.0, + "languages": [], + "name": "FriendlyNets", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/friendlyNets", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Front-end_Only_Chatbot_Interface.json b/agency-indexes/DoE/Front-end_Only_Chatbot_Interface.json new file mode 100644 index 00000000..efe4b183 --- /dev/null +++ b/agency-indexes/DoE/Front-end_Only_Chatbot_Interface.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "This code is a web-based front-end only (HTML, CSS, JS) chatbot interface for any OpenAI compatible text completion API.", + "laborHours": 638.4, + "languages": [ + "JavaScript", + "HTML", + "CSS" + ], + "name": "Front-end Only Chatbot Interface", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HPC_OOD_Chat", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FuelLib__Fuel_Library__[SWR-25-26].json b/agency-indexes/DoE/FuelLib__Fuel_Library__[SWR-25-26].json new file mode 100644 index 00000000..31728347 --- /dev/null +++ b/agency-indexes/DoE/FuelLib__Fuel_Library__[SWR-25-26].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-03-17", + "metadataLastUpdated": "2025-03-17" + }, + "description": "FuelLib is a library that utilizes the group contribution method (GCM) for calculating thermodynamic properties of hydro-carbon jet fuels.\n\nFuelLib utilizes the tables and functions of the GCM as proposed by Constantinou and Gani (1994) and Constantinou, Gani and O'Connel (1995), with additional physical properties discussed in Govindaraju & Ihme (2016). The code is based on Pavan B. Govindaraju's Matlab implementation of the GCM, and has been expanded to include additional thermodynamic properties and mixture properties. The fuel library contains gas chromatography (GC x GC) data for a variety of fuels ranging from simple single component fuels to complex jet fuels. The GC x GC data for POSF jet fuels comes from Edwards (2020).", + "laborHours": 532.0, + "languages": [ + "Python" + ], + "name": "FuelLib (Fuel Library) [SWR-25-26]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/FuelLib", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fuel_Cycle_Services_Needs_Estimator_v.2.0.json b/agency-indexes/DoE/Fuel_Cycle_Services_Needs_Estimator_v.2.0.json new file mode 100644 index 00000000..387edbd5 --- /dev/null +++ b/agency-indexes/DoE/Fuel_Cycle_Services_Needs_Estimator_v.2.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The \"Fuel Cycle Services Needs Estimator\", Version 2.0 allows users to estimate the amount of uranium enrichment services needed and amount of spent nuclear fuel produced by a given fleet of nuclear power reactors through 2050 based on user-determined information about the size of a reactor fleet and average characteristics of reactors in that fleet. The program helps users evaluate the current and future supply of nuclear fuel cycle services. The program also allows users to compare the enrichment needs and spent fuel production of more up to seven defined nuclear power reactor fleets and to aggregate estimated needs. Version 2.0 of the program has an additions of new graphs to show results of calculations (calculation capabilities and other graphing tools included in version 1.o), maps showing flows of material based on calculation results, and additional calculation capabilities that allow the user to compare supply to demand (demand calculations included in version 1.0). Default values for seven selected nuclear energy programs in East Asia are included for reference and comparison. The program was designed using the dynamic simulation software, Powersim.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "Fuel Cycle Services Needs Estimator v.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/FuelsGen.json b/agency-indexes/DoE/FuelsGen.json new file mode 100644 index 00000000..9f59fcd5 --- /dev/null +++ b/agency-indexes/DoE/FuelsGen.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-23", + "metadataLastUpdated": "2023-06-30" + }, + "description": "This toolset generates heterogeneous spatial layouts, aimed at representing forest fuels applicable to wildland fire modeling. Methods are included for calibrating (fitting) this model to data extracted from plot survey information.", + "laborHours": 0.0, + "languages": [], + "name": "FuelsGen", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/FuelsGen", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fugu_v.0.1.json b/agency-indexes/DoE/Fugu_v.0.1.json new file mode 100644 index 00000000..03f72d5e --- /dev/null +++ b/agency-indexes/DoE/Fugu_v.0.1.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SAND2021-15052 O Fugu provides a common software framework for designing and prototyping algorithms for spiking neuromorphic hardware and compiling to multiple hardware platforms. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 3906.4, + "languages": [ + "CSS", + "Python" + ], + "name": "Fugu v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Fugu", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Full_TIE_Reconstruction.json b/agency-indexes/DoE/Full_TIE_Reconstruction.json new file mode 100644 index 00000000..d83f7c7d --- /dev/null +++ b/agency-indexes/DoE/Full_TIE_Reconstruction.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "This IDL based GUI interface is for complete phase retrieval based on transport of intensity formalism. It provides routines for alignment of images, alignment of unflipped and flippped image stacks and finally various options for phase retrieval algorithm. ", + "laborHours": 1140.0, + "languages": [], + "name": "Full TIE Reconstruction", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cphatak/full_tie", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FunFact_v0.6.json b/agency-indexes/DoE/FunFact_v0.6.json new file mode 100644 index 00000000..0c1cfcc1 --- /dev/null +++ b/agency-indexes/DoE/FunFact_v0.6.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2021-09-22" + }, + "description": "FunFact is a Python package for functional factorization of matrices and higher-order tensors", + "laborHours": 0.0, + "languages": [], + "name": "FunFact v0.6", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yhtang/FunFact.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Function_Preserving_Projection.json b/agency-indexes/DoE/Function_Preserving_Projection.json new file mode 100644 index 00000000..2601710a --- /dev/null +++ b/agency-indexes/DoE/Function_Preserving_Projection.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "With function preserving projection (FPP), we aim to address high-dimensional data exploration\nchallenges common in many scientific applications. Instead of preserving the global or local geometric\nstructure of a dataset like traditional dimensionality reduction methods (e.g., principal component\nanalysis, t-stochastic neighborhood embedding), the proposed approach finds a linear projection that\nreveal interpretable (yet potentially nonlinear) pattern of the properties of interests defined on a highdimensional\ndomain (e.g., simulation yield defined on the input parameter space).\nThe key insight driving FPP is the fact that while non-linear embeddings are difficult to interpret, humans\nare highly skilled in understanding complex visual patterns. FPP lets users select the complexity of a\npattern they consider interpretable, allows to find a joint projection that explains multiple functions, and\nprovides a confidence statistic (akin to a p-value) indicating how salient the resulting pattern is. We\ndemonstrate the efficacy of the proposed method on several synthetic and scientific datasets for both\ncontinuous (regression) and discrete (classification) problems of interests and illustrate the scalability of\nFPP by finding an optimal projection for close to 40 gigabytes in around 10 minutes.\n", + "laborHours": 182.4, + "languages": [], + "name": "Function Preserving Projection", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/fpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FunctionalProfileUtil.json b/agency-indexes/DoE/FunctionalProfileUtil.json new file mode 100644 index 00000000..bbc02d40 --- /dev/null +++ b/agency-indexes/DoE/FunctionalProfileUtil.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-08", + "metadataLastUpdated": "2020-09-08" + }, + "description": "This is the repository for \"FunctionalProfileUtil\" developed by KBase. ", + "laborHours": 1428.8, + "languages": [], + "name": "FunctionalProfileUtil", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/FunctionalProfileUtil", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Functional_Mock-up_Interface_-_Machine_Learning_Center__FMI-MLC__v1.json b/agency-indexes/DoE/Functional_Mock-up_Interface_-_Machine_Learning_Center__FMI-MLC__v1.json new file mode 100644 index 00000000..98a887dc --- /dev/null +++ b/agency-indexes/DoE/Functional_Mock-up_Interface_-_Machine_Learning_Center__FMI-MLC__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2021-05-27" + }, + "description": "The Functional Mock-up Interface - Machine Learning Center is a tool to interface the Python-Tensorflow library with building simulation models, to develop and train machine learning-based controls. In particular, this framework allows the use of reinforcement learning through the standardized Functional Mock-up Interface, an open industry standard for co-simulation. First application was the development of a controller for dynamic fa\u00e7ade and heating ventilation and air conditioning (HVAC) systems.", + "laborHours": 0.0, + "languages": [], + "name": "Functional Mock-up Interface - Machine Learning Center (FMI-MLC) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/FMI-MLC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fusion_Neutron_Generator.json b/agency-indexes/DoE/Fusion_Neutron_Generator.json new file mode 100644 index 00000000..7a03844c --- /dev/null +++ b/agency-indexes/DoE/Fusion_Neutron_Generator.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-07", + "metadataLastUpdated": "2024-06-07" + }, + "description": "The proposed code, named FROG (Fusion neutron Generator) is built upon the open-source particle transport Monte Carlo toolkit Geant4. Geant4 provides C++ classes that can be leveraged to build application-specific codes dealing with the transport of particles through matter. Geant4-based codes are applied in high-energy particle physics experiments, medical applications, shielding, and space applications for example.\n\nThe FROG code allows the user to define the geometry of a neutron converter device shaped as a hollow cylinder, where a neutron breeding material such as lithium deuteride (LiD) is cladded by two concentric cylinders. Such neutron converter is then placed inside a regular nuclear fission reactor, where thermal neutrons will react with the neutron breeder material (typically, Lithium 6), and through a series of reactions, will generate high-energy neutrons \u2013 neutrons whose kinetic energy are around 14 MeV. The hollowed central portion can hold a specimen that will be bombarded by high-energy neutrons created inside the neutron breeding material. Figuratively speaking, this type of device transforms neutrons from thermal (~0.625 eV) to fusion (~14 MeV) energies and is sometimes termed \u201cfusion-to-thermal neutron converters\u201d in the literature. \n\nThe code consists of C++ source file compiled and linked to generate an executable. The user can select the dimensions of the converter (radius, length, and thickness of the breeder material), the breeder material type, the cladding material, and the specimen material that will be activated or irradiated. As input, the neutron flux for a specific location inside a reactor, for instance, positions in ATR, is required. As output, the code predicts the number of high-energy neutrons produced, the total neutron flux and fluence as well as its detailed spectrum. \n\nThe physics involved in such device is very complex, as it requires modeling neutron transport, light-ion (tritons) transport, as well as fusion reactions. The Geant4 toolkit provides the required physical models.", + "laborHours": 1489.6, + "languages": [ + "C++" + ], + "name": "Fusion Neutron Generator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/thermal_to_fusion_converter", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fusion_RF_Modeling_Machine_Learning__FusionML_RF__v1.0.json b/agency-indexes/DoE/Fusion_RF_Modeling_Machine_Learning__FusionML_RF__v1.0.json new file mode 100644 index 00000000..4f7eb843 --- /dev/null +++ b/agency-indexes/DoE/Fusion_RF_Modeling_Machine_Learning__FusionML_RF__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "\tFusionML_RF consists of multiple codes and trained machine learning (ML) models that perform low-cost output modeling from the Genray-CQL3D. Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. For example, completing a single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time. On the other hand, these ML models achieve ~ms of inference time with high accuracy across the input parameter space. This software collection consists of multiple components. (1) codes that use ML methods and precomputed Genray-CQL3D simulation output to build regression models that enable approximate computations of Genray-CLQ3D outputs from arbitrary but physically meaningful input parameters (surrogate modeling); (2) three trained models created by the team, using a database of 16,000+ GENRAY/CQL3D simulations, to study the performance of ML models for surrogate modeling; (3) codes that load the trained models and simulation data, and then compute mean squared error between the models' predictions and the ground truth of simulation output data. This collection is being made available in conjunction with a scientific publication about the work to promote reusability and provide an artifact of the scientific work.", + "laborHours": 0.0, + "languages": [], + "name": "Fusion RF Modeling Machine Learning (FusionML_RF) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FusionRFModelingMachineLearning/genray-cql3d-ml", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Fusion_models_for_Atomic_and_molecular_STructures.json b/agency-indexes/DoE/Fusion_models_for_Atomic_and_molecular_STructures.json new file mode 100644 index 00000000..27578b90 --- /dev/null +++ b/agency-indexes/DoE/Fusion_models_for_Atomic_and_molecular_STructures.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2020-05-13" + }, + "description": "Prediction of ligand-protein binding affinity from 3D atomic structures", + "laborHours": 2538.4, + "languages": [], + "name": "Fusion models for Atomic and molecular STructures", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FAST", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Futility.json b/agency-indexes/DoE/Futility.json new file mode 100644 index 00000000..3876d33a --- /dev/null +++ b/agency-indexes/DoE/Futility.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Futility package contains the following: 1) Definition of the size of integers and real numbers; 2) A generic Unit test harness; 3) Definitions for some basic extensions to the Fortran language: arbitrary length strings, a parameter list construct, exception handlers, command line processor, timers; 4) Geometry definitions: point, line, plane, box, cylinder, polyhedron; 5) File wrapper functions: standard Fortran input/output files, Fortran binary files, HDF5 files; 6) Parallel wrapper functions: MPI, and Open MP abstraction layers, partitioning algorithms; 7) Math utilities: BLAS, Matrix and Vector definitions, Linear Solver methods and wrappers for other TPLs (PETSC, MKL, etc), preconditioner classes; 8) Misc: random number generator, water saturation properties, sorting algorithms.", + "laborHours": 99727.2, + "name": "Futility", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CASL/Futility", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/FutureTense.json b/agency-indexes/DoE/FutureTense.json new file mode 100644 index 00000000..be890650 --- /dev/null +++ b/agency-indexes/DoE/FutureTense.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "Protective vaccines and reliable diagnostics are essential tools for controlling viral diseases. However, the efficacy of these tools can be diminished by mutations in viral genomes. The delay between the emergence of new viral strains and the redesign of vaccines and diagnostics allows for continued viral transmission. Is it possible to address this challenge by computationally predicting viral genome sequence evolution? Can we \u201cfuture-proof\u201d vaccines and diagnostics by targeting both current and anticipated future sequence variants? While predicting viral evolution is still an unsolved, \u201cgrand challenge\u201d problem in biology, the large, and rapidly growing, number of SARS-CoV-2 genome sequences provide an opportunity to quantify the ability of machine learning to predict viral genome sequence evolution. Towards this end, we have developed a simple computational model for predicting viral evolution at the level of individual nucleotides. The key metric for quantifying the per-base, prediction accuracy for viral evolution is the Mann-Whitney U statistic (or, equivalently, the area under the receiver operator curve). Since the Mann-Whitney U statistic is not a differentiable function, existing deep leaning packages (like Pytorch and Keras/TensorFlow) are not useful, as they require that the accuracy metric/objective function be analytically differentiable with respect to the model parameters. To overcome this challenge, we have implemented custom software, \u201cFutureTense\u201d, that can train a machine learning model by maximizing the non-differentiable Mann-Whitney U statistic. This software trains a machine learning model by exploring along the direction of the discrete gradient of the Mann-Whitney U statistic in the model parameter space. Parallel computing and genome sequence-specific optimizations are used to accelerate model training. The resulting machine learning model learns the observed high C->U mutation rates in the SARS-CoV-2 genome (which are potentially induced by host defenses) and provides prediction accuracies that are significantly better than one would expect from random chance. While predicting viral evolution is still quite far from a solved problem, the surprising performance of this simple model gives hope that the accuracy of predicting viral genome evolution can be further increased by more sophisticated approaches.", + "laborHours": 0.0, + "languages": [], + "name": "FutureTense", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/FutureTense", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/G-PST_Inertia_Monitoring_Tool_[SWR-23-54].json b/agency-indexes/DoE/G-PST_Inertia_Monitoring_Tool_[SWR-23-54].json new file mode 100644 index 00000000..227dbb15 --- /dev/null +++ b/agency-indexes/DoE/G-PST_Inertia_Monitoring_Tool_[SWR-23-54].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-05", + "metadataLastUpdated": "2023-07-31" + }, + "description": "This tool provides interfaces for ingesting real-time unit commitment data (e.g., from a grid operator's control room energy management system) and calculating system inertia estimates based on the H-constant method, before relaying those estimates to customizable visualization or logging outputs.", + "laborHours": 0.0, + "languages": [ + "Go", + "CSS", + "HTML", + "JavaScript" + ], + "name": "G-PST Inertia Monitoring Tool [SWR-23-54]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/G-PST/inertia", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/G2Aero__Separable_shape_tensors_for_aerodynamic_design__[SWR-22-44].json b/agency-indexes/DoE/G2Aero__Separable_shape_tensors_for_aerodynamic_design__[SWR-22-44].json new file mode 100644 index 00000000..93bf9208 --- /dev/null +++ b/agency-indexes/DoE/G2Aero__Separable_shape_tensors_for_aerodynamic_design__[SWR-22-44].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-04-21", + "metadataLastUpdated": "2024-01-03" + }, + "description": "G2Aero is a flexible and practical tool for design and deformation of 2D airfoils and 3D blades using data-driven approaches. G2Aero utilizes the geometry of matrix manifolds\u2014specifically the Grassmannian\u2014to build a novel framework for representing physics-based separable deformations of shapes. G2Aero offers the flexibility to generate perturbations in a customizable way over any portion of the blade. The G2Aero framework utilizes data-driven methods based on a curated database of physically relevant airfoils. Specific tools include:\n- principal geodesic analysis over normal coordinate neighborhoods of matrix manifolds;\n- a variety of data-regularized deformations to nominal 2D airfoil shapes;\n- Riemannian interpolation connecting a sequence of airfoil cross-sections to build 3D blades from 2D data;\n- consistent perturbations over the span of interpolated 3D blades based on dominant modes from the data-driven analysis.", + "laborHours": 0.0, + "languages": [ + "HTML", + "Python" + ], + "name": "G2Aero (Separable shape tensors for aerodynamic design) [SWR-22-44]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/G2Aero", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/G4beamline.json b/agency-indexes/DoE/G4beamline.json new file mode 100644 index 00000000..6894f907 --- /dev/null +++ b/agency-indexes/DoE/G4beamline.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "G4beamline is a single-particle-tracking simulation code based on the Geant4 toolkit. It is specifically optimized for the realistic evaluation of beam lines. It is especially useful for evaluating future muon facilities.", + "homepageURL": "http://g4beamline.muonsinc.com", + "laborHours": 0.0, + "name": "G4beamline", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://g4beamline.muonsinc.com", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GABLE_contract_source_code.json b/agency-indexes/DoE/GABLE_contract_source_code.json new file mode 100644 index 00000000..525dd3b4 --- /dev/null +++ b/agency-indexes/DoE/GABLE_contract_source_code.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-06-01", + "metadataLastUpdated": "2022-06-01" + }, + "description": "Garbled Autonomous Bots Leveraging Ethereum (GABLE) uses simple but effective algorithms to permit secure private execution of garbled state machines and garbled circuits on public computing resources. This release consists of two Solidity smart contracts illustrating the GABLE approach. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2022-7215 O", + "laborHours": 0.0, + "languages": [ + "Solidity" + ], + "name": "GABLE contract source code", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gable", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GALATIC:_GPU_Accelerated_Sparse_Matrix_Multiplication_over_Arbitrary_Semirings__GALATIC__v1.0.json b/agency-indexes/DoE/GALATIC:_GPU_Accelerated_Sparse_Matrix_Multiplication_over_Arbitrary_Semirings__GALATIC__v1.0.json new file mode 100644 index 00000000..394c1d5c --- /dev/null +++ b/agency-indexes/DoE/GALATIC:_GPU_Accelerated_Sparse_Matrix_Multiplication_over_Arbitrary_Semirings__GALATIC__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-02", + "metadataLastUpdated": "2021-09-02" + }, + "description": "GALATIC is a CUDA template library for performing Sparse Matrix - Sparse Matrix multiplication (SpGEMM) over arbitrary semirings on the GPU. This work generalizes AC-SpGEMM, a modern GPU accelerated SpGEMM implementation that supports single and double-precision floating-point formats.", + "laborHours": 0.0, + "languages": [], + "name": "GALATIC: GPU Accelerated Sparse Matrix Multiplication over Arbitrary Semirings (GALATIC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/richardlett/GALATIC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GAMESS_RI-MP2_MiniApp.json b/agency-indexes/DoE/GAMESS_RI-MP2_MiniApp.json new file mode 100644 index 00000000..b4f6c19b --- /dev/null +++ b/agency-indexes/DoE/GAMESS_RI-MP2_MiniApp.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-02-10", + "metadataLastUpdated": "2020-02-10" + }, + "description": "This mini app is to measure performance of a kernel for computing the correlation energy of GAMESS (General Atomic and Molecular Electronic Structure System) application on multiple processor architectures.", + "laborHours": 760.0, + "languages": [], + "name": "GAMESS RI-MP2 MiniApp", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/NCSA", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jkwack/GAMESS_RI-MP2_MiniApp", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GAM_GAMV_GUI.json b/agency-indexes/DoE/GAM_GAMV_GUI.json new file mode 100644 index 00000000..786553b7 --- /dev/null +++ b/agency-indexes/DoE/GAM_GAMV_GUI.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The GAM/GAMV GUI provides a graphic user interface to public domain FORTRAN codes (gam, version 2.0 and gamv, version 2.0) that were developed at Stanford University in 1998 (see Deutsch and Journel, 1998). The gam and gamv codes allow for calculation of different measures of spatial variability and spatial correction from a set of available data. The GAM/GAMV GUI accesses the executable versions of the gam and gamv software, initiates the calculations by the executables and manages the outputs of the executables in a user friendly graphical manner. Additionally, the GAM/GAMV GUI code then provides the user with both automatic and interactive tools in a graphical interface to fit models to the calculations of the spatial variation/correlation of the data. The GAM/GAMV GUI software allows the user to get various parameters for the gam and gamv executables that do the actual calculations by using dialog boxes, it provides some error checking as these parameters are set and then allows the user to run the calculation by calling the executable compiled from the previously developed FORTRAN software. The resulting output of the gam or gamv codes can be visualized in the GAM/GAMV GUI interface. The visualization portion of GAM/GAMV allows for both automatic and manual fitting of the model of spatial variation/correlation. GAM/GAMV GUI can be run in batch mode from the command line without invoking the graphical interface.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "GAM/GAMV GUI", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/GAM-GAMV-GUI-AND-K3TD?tab=readme-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GAM-GAMV-GUI-AND-K3TD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GANISP__GAN-assisted_Importance_SPlitting_.json b/agency-indexes/DoE/GANISP__GAN-assisted_Importance_SPlitting_.json new file mode 100644 index 00000000..89c1783f --- /dev/null +++ b/agency-indexes/DoE/GANISP__GAN-assisted_Importance_SPlitting_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-11-16", + "metadataLastUpdated": "2021-11-16" + }, + "description": "Genealogical importance splitting marches towards a rare event by iteratively selecting and replicating realizations that are headed towards a rare event. The replication step is made difficult when applied to deterministic systems as the initial conditions of the offspring realizations need to be adjusted. Typically, a random perturbation is applied to the offspring. For some cases, this cloning technique may not be adequate and prevent variance reduction in the probability estimate. A GAN-based replication process is proposed to address this limitation. The perturbations applied to the clones are physically consistent instead of being randomly chosen. The proposed method allows reducing the variance in the probability estimation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "GANISP (GAN-assisted Importance SPlitting)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GANISP", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GAPs__Geospatial_Analysis_Pipelines_.json b/agency-indexes/DoE/GAPs__Geospatial_Analysis_Pipelines_.json new file mode 100644 index 00000000..3da4e7cb --- /dev/null +++ b/agency-indexes/DoE/GAPs__Geospatial_Analysis_Pipelines_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "Geospatial Analysis Pipelines (GAPs) is a framework designed to scale single-location geospatial models to a High-Performance Computing (HPC) environment.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "GAPs (Geospatial Analysis Pipelines)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/gaps", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GAUSS.json b/agency-indexes/DoE/GAUSS.json new file mode 100644 index 00000000..f202c03b --- /dev/null +++ b/agency-indexes/DoE/GAUSS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "This project is intended to take a graph and build a smaller (upscaled) graph that is representative of the original in some way. We represent the graph Laplacian in a mixed form, solve some local eigenvalue problems to uncover near-nullspace modes, and use those modes as coarse degrees of freedom.", + "laborHours": 7584.8, + "languages": [], + "name": "GAUSS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gelever/GAUSS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GBASS_SOFTWARE.json b/agency-indexes/DoE/GBASS_SOFTWARE.json new file mode 100644 index 00000000..c1f7cbe9 --- /dev/null +++ b/agency-indexes/DoE/GBASS_SOFTWARE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "R code to fit generalized Bayesian Adaptive Smoothing Spline (GBASS) models for nonlinear regression. The approach is similar to the Bayesian MARS approach of Francom & Sanso (2020), but allows for non-Gaussian likelihoods. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "GBASS SOFTWARE", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GCMAT,_GLOBAL_CRITICAL_MATERIALS_MODEL.json b/agency-indexes/DoE/GCMAT,_GLOBAL_CRITICAL_MATERIALS_MODEL.json new file mode 100644 index 00000000..d318427b --- /dev/null +++ b/agency-indexes/DoE/GCMAT,_GLOBAL_CRITICAL_MATERIALS_MODEL.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-09-12", + "metadataLastUpdated": "2022-01-05" + }, + "description": "Argonne's GCMat is an agent-based market model of critical material supply chains using Repast Simphony with Java. It provides capabilities to explore supply chain dynamics and uncertainty under scenarios of demand growth or shrinkage, technology adoption, supply disruptions, and trade policies, and mitigation strategies of new supply sources, product substitution, consumer thrifting, and stockpiling. Supply chain participants from mining through final demand are modeled as interacting agents who make market decisions independently as time progresses. The copyright would cover the code that defines the agent behaviors and how they interact, but not the input data that is used to run the model.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "GCMAT, GLOBAL CRITICAL MATERIALS MODEL", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GDM__Grid_Data_Models__[SWR-24-31].json b/agency-indexes/DoE/GDM__Grid_Data_Models__[SWR-24-31].json new file mode 100644 index 00000000..ab3df370 --- /dev/null +++ b/agency-indexes/DoE/GDM__Grid_Data_Models__[SWR-24-31].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-04-25" + }, + "description": "Grid Data Models (GDM) is a collection of pydantic data models for power distribution and transmission system components. These data models can be easily serialized and deserialized. GDM provides a standard interface for accessing power system component data with built in validation.\n\nSee also: https://pypi.org/project/grid-data-models/", + "laborHours": 1976.0, + "languages": [ + "Python" + ], + "name": "GDM (Grid Data Models) [SWR-24-31]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-Distribution-Suites/grid-data-models", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.1.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GDX-pandas_[SWR_15-21].json b/agency-indexes/DoE/GDX-pandas_[SWR_15-21].json new file mode 100644 index 00000000..0d3f885c --- /dev/null +++ b/agency-indexes/DoE/GDX-pandas_[SWR_15-21].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This is a Python package to translate between gdx (GAMS data) and pandas. \n\nThere are two main ways to use gdxpds. The first use case is the one that was initially supported: direct conversion between GDX files on disk and pandas DataFrames or a csv version thereof. Starting with the Version 1.0.0 rewrite, there is now a second style of use which involves interfacing with GDX files and symbols via the `gdxpds.gdx.GdxFile` and `gdxpds.gdx.GdxSymbol` classes.\n\nPlease visit https://nrel.github.io/gdx-pandas for the latest documentation.", + "laborHours": 972.8, + "languages": [ + "Python" + ], + "name": "GDX-pandas [SWR 15-21]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/gdx-pandas", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GEECS__Generalized_Equipment_and_Experiment_Control_System_.json b/agency-indexes/DoE/GEECS__Generalized_Equipment_and_Experiment_Control_System_.json new file mode 100644 index 00000000..03e47f55 --- /dev/null +++ b/agency-indexes/DoE/GEECS__Generalized_Equipment_and_Experiment_Control_System_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "GEECS (Generalized Equipment and Experiment Control System) monitors and controls equipment distributed across a network, performs experiments by scanning input variables, and collects and stores various types of data synchronously from devices. Examples of devices include cameras, motors and pressure gauges. GEEKS is based upon LabView graphical object oriented programming (GOOP), allowing for a modular and scalable framework. Data is published for subscription of an arbitrary number of variables over TCP. A secondary framework allows easy development of graphical user interfaces for a combined control of any available devices on the control system without the need of programming knowledge. This allows for rapid integration of GEECS into a wide variety of systems. A database interface provides for devise and process configuration while allowing the user to save large quantities of data to local or network drives.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "LABVIEW 2011 OR LATER" + ], + "name": "GEECS (Generalized Equipment and Experiment Control System)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GEMMA_GWAS.json b/agency-indexes/DoE/GEMMA_GWAS.json new file mode 100644 index 00000000..9a826c93 --- /dev/null +++ b/agency-indexes/DoE/GEMMA_GWAS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "KBase module for genome-wide association studies, using the genome-wide efficient mixed model association algorithm (GEMMA).", + "laborHours": 5046.4, + "languages": [], + "name": "GEMMA_GWAS", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/GEMMA_GWAS", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GEN3D_Ver._1.37.json b/agency-indexes/DoE/GEN3D_Ver._1.37.json new file mode 100644 index 00000000..d3f6689c --- /dev/null +++ b/agency-indexes/DoE/GEN3D_Ver._1.37.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GEN3D is a three-dimensional mesh generation program. The three-dimensional mesh is generated by mapping a two-dimensional mesh into three-dimensions according to one of four types of transformations: translating, rotating, mapping onto a spherical surface, and mapping onto a cylindrical surface. The generated three-dimensional mesh can then be reoriented by offsetting, reflecting about an axis, and revolving about an axis. GEN3D can be used to mesh geometries that are axisymmetric or planar, but, due to three-dimensional loading or boundary conditions, require a three-dimensional finite element mesh and analysis. More importantly, it can be used to mesh complex three-dimensional geometries composed of several sections when the sections can be defined in terms of transformations of two dimensional geometries. The code GJOIN is then used to join the separate sections into a single body. GEN3D reads and writes two-dimensional and three-dimensional mesh databases in the GENESIS database format; therefore, it is compatible with the preprocessing, postprocessing, and analysis codes used by the Engineering Analysis Department at Sandia National Laboratories, Albuquerque, NM.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "GEN3D Ver. 1.37", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.37" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GENESPACE_R_Package__GENESPACE__v1.0.json b/agency-indexes/DoE/GENESPACE_R_Package__GENESPACE__v1.0.json new file mode 100644 index 00000000..2c4f91e0 --- /dev/null +++ b/agency-indexes/DoE/GENESPACE_R_Package__GENESPACE__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-10", + "metadataLastUpdated": "2021-06-11" + }, + "description": "In short, the GENESPACE pipeline conducts analysis of orthology networks, constrained within syntenic regions. Since analyses are limited to local tests conducted within syntenic blocks, GENESPACE is agnostic to ploidy, duplicated regions, inversions or other whole-genome chromosomal complexities that are common across many evolutionary lineages. This advantage allows for evolutionary tests in polyploids (e.g. switchgrass, manuscript in review), species with ancient, but retained whole-genome duplications (e.g. pecan, manuscript in prep), high levels of tandem array proliferation (e.g. eukalypts, manuscript in review) and many other factors that can confound comparative genomic analyses. The major advances of GENESPACE are three-fold: First, this is the first R package to integrate visualization and analysis of large-scale comparative genomics. R, which offers a high-level environment for graphical and statistical exploration of data, is often speed- and memory-limited and not used for computationally intensive tasks such as comparative genomics. The highly efficient C++ scripts used in GENESPACE (via data.table) permit a much faster and computationally lightweight implementation of comparative genomics than is currently available. Second, the pipeline itself is novel. To the best of our knowledge, no other program accomplishes synteny-constrained and ploidy-agnostic comparative genomics. Since nearly all plants and many animals have a history of whole-genome duplications, this is a major and necessary advance to the field. Third, GENESPACE offers high-level and intuitive multi-genome graphical outputs. The dotplots and 'riparian' plots produced herein, which are produced entirely through original R code, are publication-ready and easily customizable.", + "laborHours": 0.0, + "languages": [], + "name": "GENESPACE R Package (GENESPACE) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/plant/genespace-r", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GEOPHIRES_v2.0.json b/agency-indexes/DoE/GEOPHIRES_v2.0.json new file mode 100644 index 00000000..aaaee604 --- /dev/null +++ b/agency-indexes/DoE/GEOPHIRES_v2.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-02-12", + "metadataLastUpdated": "2020-02-17" + }, + "description": "GEOPHIRES v2.0 is a geothermal techno-economic simulation tool upgraded from GEOPHIRES v1.2. The name stands for \"GEOthermal energy for Production of Heat and electricity (\u201cIR\u201d) Economically Simulated\". GEOPHIRES combines reservoir, wellbore, and surface plant technical models with cost correlations and levelized cost models to estimate the capital and operation and maintenance costs, instantaneous and lifetime energy production, and overall levelized cost of energy of a geothermal plant. In addition to electricity generation, direct-use heat applications and combined heat and power or cogeneration can be modeled. Various upgrades have been implemented to develop GEOPHIRES v2.0, including: updating the built-in cost correlations, coupling to the external reservoir simulator TOUGH2, enhancing the built-in wellbore simulator, converting the programming language to Python, and making the code open-source. Users are encouraged to build upon the tool, e.g. by implementing their own correlations or coupling to other simulators. ", + "laborHours": 1140.0, + "languages": [ + "Python" + ], + "name": "GEOPHIRES v2.0", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GEOPHIRES-v2", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/GEOPM\302\240.json" "b/agency-indexes/DoE/GEOPM\302\240.json" new file mode 100644 index 00000000..49d0265f --- /dev/null +++ "b/agency-indexes/DoE/GEOPM\302\240.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "The Global Extensible Open Power Manager (GEOPM) is a framework for exploring power and energy optimizations targeting high performance computing. ", + "laborHours": 99058.4, + "languages": [], + "name": "GEOPM\u00a0", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/geopm/geopm", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GEOSX_Simulation_Framework.json b/agency-indexes/DoE/GEOSX_Simulation_Framework.json new file mode 100644 index 00000000..6c81e837 --- /dev/null +++ b/agency-indexes/DoE/GEOSX_Simulation_Framework.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-28", + "metadataLastUpdated": "2020-10-29" + }, + "description": "General multi-physics simulation framework targeting exascale computing platforms.", + "laborHours": 337546.4, + "languages": [ + "C++", + "Python" + ], + "name": "GEOSX Simulation Framework", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GEOSX/GEOSX", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GHEDesigner_[SWR-23-33].json b/agency-indexes/DoE/GHEDesigner_[SWR-23-33].json new file mode 100644 index 00000000..09519035 --- /dev/null +++ b/agency-indexes/DoE/GHEDesigner_[SWR-23-33].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-04-06", + "metadataLastUpdated": "2023-04-06" + }, + "description": "GHEDesigner is a Python package for designing ground heat exchangers (GHE) used with ground source heat pump (GSHP) systems.", + "laborHours": 0.0, + "languages": [ + "PYTHON" + ], + "name": "GHEDesigner [SWR-23-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BETSRG/GHEDesigner", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GHEP_WIBT__Guidelines_for_Home_Energy_Professionals_Weatherization_Installer_Badges_Toolkit__[SWR-20-69].json b/agency-indexes/DoE/GHEP_WIBT__Guidelines_for_Home_Energy_Professionals_Weatherization_Installer_Badges_Toolkit__[SWR-20-69].json new file mode 100644 index 00000000..7a308990 --- /dev/null +++ b/agency-indexes/DoE/GHEP_WIBT__Guidelines_for_Home_Energy_Professionals_Weatherization_Installer_Badges_Toolkit__[SWR-20-69].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-02-15", + "metadataLastUpdated": "2024-02-21" + }, + "description": "The National Renewable Energy Laboratory (NREL) and the U.S. Department of Energy's (DOE) Weatherization Assistance Program (WAP) are collaborating with the home energy retrofit industry to support the development of skilled workers. The Installer Badges Toolkit provides a flexible, customizable, and voluntary approach to training and skills recognition for WAP implementers, utility programs, private-sector workers, and contractors.\n\nIn Fiscal Year 2018, DOE, along with the Crew Leader scheme committee, determined the Retrofit Installer Technician (RIT) Job Task Analysis (JTA) could be eliminated and its tasks inserted in the Crew Leader JTA. The RIT tasks became the basis of the Installer Badges.\n\nThe Badges Toolkit was updated in 2020 to add licensing and copyright agreements. Users must cite the copyright information when using or distributing copies of the Badges Toolkit in any way. The technical content has remained unchanged from previous versions of the Badges Toolkit.\n\nThe Toolkit for home retrofits consists of 25 Badges, each representing different energy efficiency tasks that an installer could perform on a home. Each Badge defines the desired outcome, criteria to verify, applicable material requirements, and references to Standard Work Specifications (SWS) or other relevant standards.\n\nThe Badges provide a consistent approach to training by ensuring that installers in different regions are learning the same skills nationwide. Organizations can also customize the Toolkit by choosing only those Badges that are relevant to their program.\n\nThe Badges Toolkit includes five pieces:\n\n\"How to Use the Badges Toolkit\" provides a brief overview of how a Grantee, Subgrantee, or training provider may approach using the toolkit.\nThe \"Badges Toolkit: Worksheet\" includes what to consider when determining whether and how to best incorporate the Badges into a weatherization assistance program.\nThe \"Crew Leader Job Task Analysis Spreadsheet\" indicates how the Badges align with specific areas of the JTA.\nThe \"Installer Badges Passport\" features separate pages for each Badge, which include places for the installer and the supervisor/trainer to record the number of times a task has been successfully completed.\nThe \"Installer Badges Verification Criteria\" includes sample inspection checklists for each Badge. These can be modified as needed based on approved variance requests or more stringent requirements. They also provide a basis for consistent inspections and awarding of Badges.\n \n\nNote: All elements of the Badges Toolkit are designed for use by potential program implementers. They are not off-the-shelf products intended for immediate deployment. Program implementers must review and modify as needed, revise verification criteria to match local requirements, complete worksheets, and otherwise define the parameters of their own badging program.", + "homepageURL": "https://sws.nrel.gov/installerbadges", + "laborHours": 0.0, + "languages": [], + "name": "GHEP WIBT (Guidelines for Home Energy Professionals Weatherization Installer Badges Toolkit) [SWR-20-69]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://creativecommons.org/licenses/by-nc/4.0/deed.en", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sws.nrel.gov/installerbadges", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GHOST__Grid_Hardware_Open_Source_Testbed__[SWR-18-32].json b/agency-indexes/DoE/GHOST__Grid_Hardware_Open_Source_Testbed__[SWR-18-32].json new file mode 100644 index 00000000..cc9716d7 --- /dev/null +++ b/agency-indexes/DoE/GHOST__Grid_Hardware_Open_Source_Testbed__[SWR-18-32].json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-05-22", + "metadataLastUpdated": "2025-03-26" + }, + "description": "The software was developed for the purpose of Microgrid Controller Procurement where multiple Microgrid Controller vendors were competing to prove the best performance. Each microgrid controller was connected to Real-Time Simulator (Opal-RT) where the Real-Time model of microgrid was simulated. Microgrid controllers were able to control most of the assets in the model. To be able to fairly compare controller's performance each controller was evaluated using exactly the same model, with the same initial conditions and exactly the same test sequence.\n\nThe microgrid evaluation test sequence lasted 100 minutes and consist of various grid disturbances to which a microgrid controller must respond. The microgrid and power system will experience multiple types of disturbances while performing dispatch functions. Many functions are tested in grid-connected and islanded modes such as unexpended failures of generators, energy storage trip events, and large load fluctuations. The test sequence focuses on fault scenarios that cause the highest short-circuit fault current contribution; force a swing bus or generator capable of being a swing bus offline; cause the most reconfigurations; and cause conflicting objectives for the microgrid controller. \n\nDuring the test sequence execution multiple datapoints are being recorded and stored. During data postprocessing key performance parameters are extracted allowing quantitative comparison of performance on multiple aspects including: resiliency, fuel utilization, grid interconnection, ancillary services and power quality and eventually after summing all key performance parameters by comparing the overall result.\n\nTo be able to perform such testing multiple tools had to be developed included in this repository including:\n- Real time model of microgrid (Urban-Banshee, Remote-smaller model)\n- Test sequence configuration tools\n- Test execution real-time scripts\n- Post processing scripts\n- Human Machine Interface software", + "homepageURL": "https://github.com/PowerSystemsHIL/EPHCC/tree/NREL_merge", + "laborHours": 242196.8, + "languages": [], + "name": "GHOST (Grid Hardware Open Source Testbed) [SWR-18-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PowerSystemsHIL/EPHCC/tree/NREL_merge", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GIIP__Gaussian_Integral_Inner_Products_.json b/agency-indexes/DoE/GIIP__Gaussian_Integral_Inner_Products_.json new file mode 100644 index 00000000..d05cd951 --- /dev/null +++ b/agency-indexes/DoE/GIIP__Gaussian_Integral_Inner_Products_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-17", + "metadataLastUpdated": "2024-10-17" + }, + "description": "SAND2024-08692O\nThe Gaussian Integral Inner Products (GIIP) calculates the integral of squared difference of atomic density functions minimized over the orthogonal group. It uses the hyper-spherical coverings library to sample orthogonal group.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 17069.6, + "languages": [ + "Python 3" + ], + "name": "GIIP (Gaussian Integral Inner Products)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/giip", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GISMo_Docs_Browser.json b/agency-indexes/DoE/GISMo_Docs_Browser.json new file mode 100644 index 00000000..cf6a7d97 --- /dev/null +++ b/agency-indexes/DoE/GISMo_Docs_Browser.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-13", + "metadataLastUpdated": "2022-09-13" + }, + "description": "This project allows GitHub projects to publish the docs folder to a server other than github.io and support more advanced documentation navigation. This is accomplished using a simple client-side implementation that does not require anything more than delivery of the required files themselves by the server. There is no need for any server side processing, which eliminates the need for a server instance.", + "laborHours": 0.0, + "languages": [], + "name": "GISMo Docs Browser", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/docs-browser", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GJOIN.json b/agency-indexes/DoE/GJOIN.json new file mode 100644 index 00000000..3f29c13e --- /dev/null +++ b/agency-indexes/DoE/GJOIN.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-15" + }, + "description": "GJOIN is a two- or three-dimensional mesh combination program. GJOIN combines two or more meshes written in the GENESIS mesh database format into a single GENESIS mesh. Selected nodes in the two meshes that are closer than a specified distance can be combined. The geometry of the mesh databases can be modified by scaling, offsetting, revolving, nd mirroring. The combined meshes can be further modified by deleting, renaming, or combining material blocks, sideset identifications, or nodeset identifications.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "GJOIN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GLVis.json b/agency-indexes/DoE/GLVis.json new file mode 100644 index 00000000..f1cf12f0 --- /dev/null +++ b/agency-indexes/DoE/GLVis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2019-07-11" + }, + "description": "Mirror of GLVis - a lightweight OpenGL tool for accurate and flexible finite element visualization. GLVis is an OpenGL tool for visualization of finite element meshes and functions.\n", + "homepageURL": "https://glvis.org", + "laborHours": 0.0, + "languages": [], + "name": "GLVis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://glvis.org", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GLVis:_OpenGL_Finite_Element_Visualization_Tool.json b/agency-indexes/DoE/GLVis:_OpenGL_Finite_Element_Visualization_Tool.json new file mode 100644 index 00000000..f39be47f --- /dev/null +++ b/agency-indexes/DoE/GLVis:_OpenGL_Finite_Element_Visualization_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-01-22" + }, + "description": "GLVis is an OpenGL tool for visualization of finite element meshes and functions. When started without any options, GLVis starts a server, which waits for a socket connections and visualizes any recieved data. This way the results of simulations on a remote (parallel) machine can be visualized on the lical user desktop. GLVis can also be used to visualize a mesh with or without a finite element function (solution). It can run a batch sequence of commands (GLVis scripts), or display previously saved socket streams. For more information, see the project website: http://glvis.org/.", + "laborHours": 17343.2, + "languages": [], + "name": "GLVis: OpenGL Finite Element Visualization Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/glvis/glvis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GLVis_doxygen.json b/agency-indexes/DoE/GLVis_doxygen.json new file mode 100644 index 00000000..00189f44 --- /dev/null +++ b/agency-indexes/DoE/GLVis_doxygen.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This is the repository for doxygen, GLVis - a lightweight OpenGL tool for accurate and flexible finite element visualization developed at Lawrence Livermore National Laboratory. 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GLVis uses OpenGL with interactive refinement to accurately represent curved high-order meshes and a wide variety of finite element grid functions defined on them.", + "laborHours": 17343.2, + "languages": [], + "name": "GL Visualization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/glvis/glvis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "4.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GNATFinder.json b/agency-indexes/DoE/GNATFinder.json new file mode 100644 index 00000000..4ba5e718 --- /dev/null +++ b/agency-indexes/DoE/GNATFinder.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-13", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-05510O\nGNATFinder is a software tool for extracting graphical neural activity threads (GNATs) from spiking neural networks. GNATFinder efficiently extracts GNATs from spiking neural network data. A GNAT is a graph that represents the causal relationships between individual spikes in a spiking network using a combination of the network connectivity structure and the timing of individual spikes. The software allows for identifying similar, repeating threads that often reappear in a dataset. Using quadtree data structures to recursively subdivide the time interval over which spikes were produced by the spiking network, GNATFinder allows for efficient pairwise comparisons of spike times to determine the degree of causal relatedness among all pairs of spikes in a dataset. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 440.8, + "languages": [ + "C", + "C++" + ], + "name": "GNATFinder", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GNATFinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GNN_Parameterized_Differential_Operators_v.0.9.json b/agency-indexes/DoE/GNN_Parameterized_Differential_Operators_v.0.9.json new file mode 100644 index 00000000..1406b569 --- /dev/null +++ b/agency-indexes/DoE/GNN_Parameterized_Differential_Operators_v.0.9.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-03-21", + "metadataLastUpdated": "2024-09-10" + }, + "description": "GNN Parametrized Differential Operators is an example code and layer implementation for using the parameterized differential operator used in conference submissions. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.\nSAND2021-2984 O", + "laborHours": 395.2, + "languages": [], + "name": "GNN Parameterized Differential Operators v.0.9", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PDONet", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.6.9" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GNU_Radio_Sandia_Utilities_v._1.6.json b/agency-indexes/DoE/GNU_Radio_Sandia_Utilities_v._1.6.json new file mode 100644 index 00000000..1f8ad2e8 --- /dev/null +++ b/agency-indexes/DoE/GNU_Radio_Sandia_Utilities_v._1.6.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2019-07-30" + }, + "description": "This software adds a data handling module to the GNU Radio (GR) software defined radio (SDR) framework as well as some general-purpose function blocks (filters, metadata control, etc). This software is useful for processing bursty RF transmissions with GR, and serves as a base for applying SDR signal processing techniques to a whole burst of data at a time, as opposed to streaming data which GR.", + "laborHours": 11536.8, + "languages": [ + "C++", + "Python" + ], + "name": "GNU Radio Sandia Utilities v. 1.6", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gr-pdu_utils", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.6" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GOAT._jl.json b/agency-indexes/DoE/GOAT._jl.json new file mode 100644 index 00000000..43e10059 --- /dev/null +++ b/agency-indexes/DoE/GOAT._jl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-17" + }, + "description": "SF-23-008 This project is a Julia implementation of the Gradient Optimization of Analytic conTrols (GOAT) \noptimal control\nmethodology. It integrates with other packages in Julia's ecosystem to provide memory-efficient, \nparallelized solutions to quantum optimal control tasks. A prototype implementation of some of these algorithms was initially developed and funded by the \nASCR Early Career Research Award program under PI Travis Humble at Oak Ridge National Laboratory. \nThe current version was funded under the ASCR AIDE-QC Program under PI Paul Hovland. The current \npackage to be released has a novel implementation, syntax, and structure making it substantially \ndifferent than the original prototype (which was not released under copyright to the best of my \nknowledge).\n", + "laborHours": 0.0, + "languages": [], + "name": "GOAT. jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MCS-Quantum/GOAT.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GOMA_Ver._6.0.json b/agency-indexes/DoE/GOMA_Ver._6.0.json new file mode 100644 index 00000000..64ecca99 --- /dev/null +++ b/agency-indexes/DoE/GOMA_Ver._6.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Not Specified", + "laborHours": 222254.4, + "name": "GOMA Ver. 6.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/goma/goma", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GOOSE__GRAPHITE_OBJECT-ORIENTED_SIMULATION_ENVIRONMENT_.json b/agency-indexes/DoE/GOOSE__GRAPHITE_OBJECT-ORIENTED_SIMULATION_ENVIRONMENT_.json new file mode 100644 index 00000000..f634341f --- /dev/null +++ b/agency-indexes/DoE/GOOSE__GRAPHITE_OBJECT-ORIENTED_SIMULATION_ENVIRONMENT_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This package is a set of extensions to MOOSE (https://moose.inl.gov) adding anisotropic graphite material models for irradiation creep and swelling. The goal of the package is to provide a framework to model graphite components for use in future high temperature nuclear reactors.", + "laborHours": 0.0, + "languages": [], + "name": "GOOSE (GRAPHITE OBJECT-ORIENTED SIMULATION ENVIRONMENT)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/goose", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GOTCHA.json b/agency-indexes/DoE/GOTCHA.json new file mode 100644 index 00000000..477da524 --- /dev/null +++ b/agency-indexes/DoE/GOTCHA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2020-05-27" + }, + "description": "Gotcha is a library that wraps functions. Tools can use gotcha to install hooks into other libraries, for example putting a wrapper function around libc's malloc.\n", + "laborHours": 2204.0, + "languages": [], + "name": "GOTCHA", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GOTCHA", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GOTCHA_Tracer.json b/agency-indexes/DoE/GOTCHA_Tracer.json new file mode 100644 index 00000000..e9e04c08 --- /dev/null +++ b/agency-indexes/DoE/GOTCHA_Tracer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This is a simple example for how to create a tracer using\u00a0GOTCHA. It is also shows how a CMake project would integrate Gotcha. This includes testing Gotcha via direct invocation and using\u00a0LD_PRELOAD.\n", + "laborHours": 258.4, + "languages": [], + "name": "GOTCHA Tracer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GOTCHA-tracer", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GOTTCHA,_Version_1.json b/agency-indexes/DoE/GOTTCHA,_Version_1.json new file mode 100644 index 00000000..f811a183 --- /dev/null +++ b/agency-indexes/DoE/GOTTCHA,_Version_1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "One major challenge in the field of shotgun metagenomics is the accurate identification of the organisms present within the community, based on classification of short sequence reads. Though microbial community profiling methods have emerged to attempt to rapidly classify the millions of reads output from contemporary sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling tool with significantly smaller FDR, which is also capable of classifying never-before seen genomes into the appropriate parent taxa.The algorithm is based upon three primary computational phases: (I) genomic decomposition into bit vectors, (II) bit vector intersections to identify shared regions, and (III) bit vector subtractions to remove shared regions and reveal unique, signature regions. In the Decomposition phase, genomic data is first masked to highlight only the valid (non-ambiguous) regions and then decomposed into overlapping 24-mers. The k-mers are sorted along with their start positions, de-replicated, and then prefixed, to minimize data duplication. The prefixes are indexed and an identical data structure is created for the start positions to mimic that of the k-mer data structure. During the Intersection phase -- which is the most computationally intensive phase -- as an all-vs-all comparison is made, the number of comparisons is first reduced by four methods: (a) Prefix restriction, (b) Overlap detection, (c) Overlap restriction, and (d) Result recording. In Prefix restriction, only k-mers of the same prefix are compared. Within that group, potential overlap of k-mer suffixes that would result in a non-empty set intersection are screened for. If such an overlap exists, the region which intersects is first reduced by performing a binary search of the boundary suffixes of the smaller set into the larger set, which defines the limits of the zipper-based intersection process. Rather than recording the actual k-mers of the intersection, another data structure of identical \"shape\" is created which consists of only bit vectors so that only a 1 or 0 will be stored in the location of the k-mer suffix that was found in the intersection. This reduces the amount of data generated and stored considerably. During the Subtraction phase, relevant intersection bitmasks are first unionized together to form a single bitmask which is then applied over the original genome to reveal only those regions of the genome that are unique. These regions are then exported to disk in FASTA format and used in the application of determining the constituents of an unknown metagenomic community.", + "laborHours": 5168.0, + "name": "GOTTCHA, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/GOTTCHA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GOTTCHA_Database,_Version_1.json b/agency-indexes/DoE/GOTTCHA_Database,_Version_1.json new file mode 100644 index 00000000..c26ee1c7 --- /dev/null +++ b/agency-indexes/DoE/GOTTCHA_Database,_Version_1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "One major challenge in the field of shotgun metagenomics is the accurate identification of the organisms present within the community, based on classification of short sequence reads. Though microbial community profiling methods have emerged to attempt to rapidly classify the millions of reads output from contemporary sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling tool with significantly smaller FDR, which is also capable of classifying never-before seen genomes into the appropriate parent taxa.The algorithm is based upon three primary computational phases: (I) genomic decomposition into bit vectors, (II) bit vector intersections to identify shared regions, and (III) bit vector subtractions to remove shared regions and reveal unique, signature regions.In the Decomposition phase, genomic data is first masked to highlight only the valid (non-ambiguous) regions and then decomposed into overlapping 24-mers. The k-mers are sorted along with their start positions, de-replicated, and then prefixed, to minimize data duplication. The prefixes are indexed and an identical data structure is created for the start positions to mimic that of the k-mer data structure.During the Intersection phase -- which is the most computationally intensive phase -- as an all-vs-all comparison is made, the number of comparisons is first reduced by four methods: (a) Prefix restriction, (b) Overlap detection, (c) Overlap restriction, and (d) Result recording. In Prefix restriction, only k-mers of the same prefix are compared. Within that group, potential overlap of k-mer suffixes that would result in a non-empty set intersection are screened for. If such an overlap exists, the region which intersects is first reduced by performing a binary search of the boundary suffixes of the smaller set into the larger set, which defines the limits of the zipper-based intersection process. Rather than recording the actual k-mers of the intersection, another data structure of identical \"shape\" is created which consists of only bit vectors so that only a 1 or 0 will be stored in the location of the k-mer suffix that was found in the intersection. This reduces the amount of data generated and stored considerably.During the Subtraction phase, relevant intersection bitmasks are first unionized together to form a single bitmask which is then applied over the original genome to reveal only those regions of the genome that are unique. These regions are then exported to disk in FASTA format and used in the application of determining the constituents of an unknown metagenomic community.The DATABASE provided is the result of the algorithm described.", + "laborHours": 5168.0, + "name": "GOTTCHA Database, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/GOTTCHA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GPLaSDI:_Gaussian_Process_Latent_Space_Dynamics_Identification.json b/agency-indexes/DoE/GPLaSDI:_Gaussian_Process_Latent_Space_Dynamics_Identification.json new file mode 100644 index 00000000..a56d58b8 --- /dev/null +++ b/agency-indexes/DoE/GPLaSDI:_Gaussian_Process_Latent_Space_Dynamics_Identification.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-07-31", + "metadataLastUpdated": "2023-07-31" + }, + "description": "GPLaSDI is a software that introduces GPLaSDI, a novel LaSDI-based framework that relies on Gaussian\nprocess (GP) for latent space ODE interpolations. Using GPs offers two significant advantages. First, it\nenables the quantification of uncertainty over the reduced order model (ROM) predictions. Second,\nleveraging this prediction uncertainty allows for efficient adaptive training through a greedy selection of\nadditional training data points. This approach does not require prior knowledge of the underlying PDEs.\nConsequently, GPLaSDI is inherently non-intrusive and can be applied to problems without a known PDE\nor its residual. We demonstrate the effectiveness of our approach on the Burgers equation, Vlasov\nequation for plasma physics, and a rising thermal bubble problem. Our proposed method achieves\nbetween 200 and 100,000 times speed-up, with up to 7% relative error.", + "laborHours": 0.0, + "languages": [], + "name": "GPLaSDI: Gaussian Process Latent Space Dynamics Identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GPLaSDI", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GPTune_v.1.json b/agency-indexes/DoE/GPTune_v.1.json new file mode 100644 index 00000000..38092a87 --- /dev/null +++ b/agency-indexes/DoE/GPTune_v.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-08-07", + "metadataLastUpdated": "2020-09-08" + }, + "description": "GPTune is an autotuning framework for exascale applications. Given an application with a set of parameters controlling its performance (e.g. runtime, memory and/or energy consumption, numerical accuracy, ...), GPTune aims at finding a combination of the parameters that yields the best possible performance. Although general enough, GPTune specializes in the tunning of expensive-to-run applications, where the cost of running the application is very expensive (in terms of computing power requirement and/or runtime).", + "laborHours": 38471.2, + "languages": [], + "name": "GPTune v.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gptune/GPTune", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GPU-Accelerated_Denoising_in_3D__GD3D_.json b/agency-indexes/DoE/GPU-Accelerated_Denoising_in_3D__GD3D_.json new file mode 100644 index 00000000..3c2ff67f --- /dev/null +++ b/agency-indexes/DoE/GPU-Accelerated_Denoising_in_3D__GD3D_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The raw computational power GPU Accelerators enables fast denoising of 3D MR images using bilateral filtering, anisotropic diffusion, and non-local means. This software addresses two facets of this promising application: what tuning is necessary to achieve optimal performance on a modern GPU? And what parameters yield the best denoising results in practice? To answer the first question, the software performs an autotuning step to empirically determine optimal memory blocking on the GPU. To answer the second, it performs a sweep of algorithm parameters to determine the combination that best reduces the mean squared error relative to a noiseless reference image.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "GPU-Accelerated Denoising in 3D (GD3D)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GPU-FPX.json b/agency-indexes/DoE/GPU-FPX.json new file mode 100644 index 00000000..b224c76e --- /dev/null +++ b/agency-indexes/DoE/GPU-FPX.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "GPU-FPX is a tool based on NVBit that detects and analyzes floating-point exceptions on NVIDIA GPUs through binary instrumentation. Its purpose is to detect and report the occurrences of floating-point exceptions during numerical computations, offering efficient location detections and exception flow. GPUFPX achieves exceptional performance, being 16x faster than comparable prior tools, such as BinFPE.", + "laborHours": 0.0, + "languages": [], + "name": "GPU-FPX", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GPU-FPX", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GPULife.json b/agency-indexes/DoE/GPULife.json new file mode 100644 index 00000000..aa8526f1 --- /dev/null +++ b/agency-indexes/DoE/GPULife.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The code runs the Game of Life among several processors. Each processor uses CUDA to set up the grid's buffer on the GPU, and that buffer is fed to other GPU languages to apply the rules of the game of life. Only the halo is copied off the buffer and exchanged using MPI. This code looks at the interoperability of GPU languages among current platforms.", + "laborHours": 1185.6, + "name": "GPULife", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnkelly/GPULife", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GPU_Accelerated_Singular_Binarized_Neural_Network_Inference_Framework.json b/agency-indexes/DoE/GPU_Accelerated_Singular_Binarized_Neural_Network_Inference_Framework.json new file mode 100644 index 00000000..195b62ca --- /dev/null +++ b/agency-indexes/DoE/GPU_Accelerated_Singular_Binarized_Neural_Network_Inference_Framework.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Singular Binarized Neural Network based on GPU Bit Operations.", + "laborHours": 3024.8, + "languages": [], + "name": "GPU Accelerated Singular Binarized Neural Network Inference Framework", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/uuudown/SBNN", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GRAF-Plan.json b/agency-indexes/DoE/GRAF-Plan.json new file mode 100644 index 00000000..a9dcdcfa --- /dev/null +++ b/agency-indexes/DoE/GRAF-Plan.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Wind and solar generation is increasing rapidly in the USA and around the world and has the potential to replace carbon emitting generation. However, at high penetration, intermittent generation can present significant challenges because of increasing system variability and uncertainty. To manage these challenges, operation and planning procedures should incorporate additional analysis tools and methodologies. Particularly, tools are needed to help plan and operate the power system for maintaining intra\u2010day and intra\u2010hour balance between generation and load in power system\u2019s balancing authorities. This tool addresses this problem by providing a way to plan for adequate amounts of balancing reserves for future years or seasons for expected wind and solar generation. This is a user friendly tool to calculate ahead monthly required balancing reserves and the flexibility of scheduled\ngeneration to meet such requirements. This tool calculates reserves requirements of various types, such as day\u2010ahead, load following and regulation, as well as estimates the capacity of the generation fleet to provide the required reserves. The estimations are based on utilities\u2019 operational practices (such as forecasting, timeframe of reserve deployment), and it incorporates detailed synchronized variable and uncertain data from renewable generation and load. This tool uses a methodology that has been previously tested and applied to several systems: California Independent System Operator Corp., Columbia Grid, Northwest Power Pool, the Western Interconnection of the United States, and internationally in Honduras, Guatemala, El Salvador, Nicaragua, Costa Rica, and Panama.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "GRAF-Plan", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GRAF-Plan_for_Vietnam.json b/agency-indexes/DoE/GRAF-Plan_for_Vietnam.json new file mode 100644 index 00000000..c7a2bb92 --- /dev/null +++ b/agency-indexes/DoE/GRAF-Plan_for_Vietnam.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Evaluates the reserve requirements for power system balancing areas based on variability and uncertainty of load as well as wind and solar generation scenarios. The tool uses minute\u2010by\u2010minute site\u2010specific generation and load information, as well as information from generation and load forecasting algorithms used in the balancing areas. The Balancing\u2010Plan Tool can be used directly by utility planners and operators to aid in the integration of intermittent renewable resources. The tool provides reserve requirements of various kinds, such as day\u2010ahead, load following and regulation, as well as estimates the capacity of the generation fleet to provide the require reserves.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "GRAF-Plan for Vietnam", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GRAPH_CONVOLUTIONAL_NEURAL_NETWORK__GCNN_FOR_POLYMER_PROPERTY_PREDICTION.json b/agency-indexes/DoE/GRAPH_CONVOLUTIONAL_NEURAL_NETWORK__GCNN_FOR_POLYMER_PROPERTY_PREDICTION.json new file mode 100644 index 00000000..758a5e96 --- /dev/null +++ b/agency-indexes/DoE/GRAPH_CONVOLUTIONAL_NEURAL_NETWORK__GCNN_FOR_POLYMER_PROPERTY_PREDICTION.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2023-03-14" + }, + "description": "SF-22-121 Graph convolutional neural networks (GCNN) are powerful machine learning models that apply a message-passing algorithm on adjacent nodes in a graph. Due to the natural representation of molecules via discrete graphs (where nodes encode atoms and edges encode bonds), GCNNs are an intuitive machine learning model chemical space informatics, including the prediction of polymer properties. Here, molecules are represented in feature and adjacency matrices where they are directly used as inputs to a GCNN.", + "laborHours": 0.0, + "languages": [], + "name": "GRAPH CONVOLUTIONAL NEURAL NETWORK (GCNN)FOR POLYMER PROPERTY PREDICTION", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AI4Plastics/AI4Plastics", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GRChombo.json b/agency-indexes/DoE/GRChombo.json new file mode 100644 index 00000000..739c857b --- /dev/null +++ b/agency-indexes/DoE/GRChombo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "GRChombo is a new numerical relativity code written to take full advantage of modern parallel computing techniques. GRChombo's features include full adaptive mesh refinement (AMR) with block structured Berger-Rigoutsos grid generation which supports non-trivial \"many-boxes-in-many-boxes\" meshing hierarchies, and massive parallelism through the Message Passing Interface (MPI). GRChombo evolves the Einstein equation with the standard BSSN formalism, with an option to turn on CCZ4 constraint damping if required. It can stably and accurately evolve vacuum black hole spacetimes such as binary black hole mergers, and non-vacuum spacetimes such as scalar collapses into black holes. ", + "laborHours": 6551.2, + "languages": [], + "name": "GRChombo", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GRChombo/GRChombo", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GREET+_Model_2024.json b/agency-indexes/DoE/GREET+_Model_2024.json new file mode 100644 index 00000000..23090d8f --- /dev/null +++ b/agency-indexes/DoE/GREET+_Model_2024.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2024-11-05", + "metadataLastUpdated": "2024-11-05" + }, + "description": "Based on the well-established GREET model mainly for the United States (U.S.), Argonne National Laboratory (ANL), with the support of the U.S. Department of Energy (DOE), has collaborated with the International Energy Agency (IEA) to develop a global version of the R&D GREET model, referred to as GREET+. GREET+ is a consistent and comparable life cycle analysis (LCA) modeling platform to evaluate life-cycle energy use and greenhouse gas (GHG) emissions of vehicle/fuel systems and technologies. It examines the energy and GHG impacts of technological advancements in different world regions through 2050.\n\nThe GREET+ model builds upon the Excel platform of the R&D GREET\u00ae 2022 rev1 model and ANL\u2019s previous efforts on two regionalized GREET versions, i.e., China-GREET for China and MENA-GREET for Middle East and North Africa (MENA). GREET+ covers 16 regions and countries, including Canada, the USA, Mexico, Brazil, Central and South America region A, Central and South America region B, the European Union, China, India, Japan, South Korea, Southeast Asia and Oceania, MENA, Central and South Africa, the UK, and Norway. The current version of GREET+ focuses on the background data of the fuel cycle (or well-to-wheels, WTW), enabling the generation of region-specific WTW results for fuels and vehicles technologies of interest.", + "homepageURL": "https://greet.anl.gov/greet_plus", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "GREET+ Model 2024", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.anl.gov/greet_plus", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "2024" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GREPOS.json b/agency-indexes/DoE/GREPOS.json new file mode 100644 index 00000000..8310b8bc --- /dev/null +++ b/agency-indexes/DoE/GREPOS.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GREPOS is a mesh utility program that repositions or modifies the configuration of a two- dimensional or three-dimensional mesh. GREPOS can be used to change the orientation and size of a two- dimensional or three-dimensional mesh; change the material block, nodeset, and sideset IDs; or \"explode\" the mesh to facilitate viewing of the various parts of the model, and several other mesh modification utilities.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "GREPOS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.61" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GRIDAPPSD_GOSS-GridAPPS-D.json b/agency-indexes/DoE/GRIDAPPSD_GOSS-GridAPPS-D.json new file mode 100644 index 00000000..ee6ce367 --- /dev/null +++ b/agency-indexes/DoE/GRIDAPPSD_GOSS-GridAPPS-D.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2020-10-29" + }, + "description": "GridAPPS-D provides a method for developers to run their new applications on a real-time simulator with extensive modeling and tool support. GridAPPS-D is built around standard data models like the CIM. It readily interfaces to existing software products, which may also 1) use components of GridAPPS-D and 2) supplement or replace the built-in distribution simulator, facilitating the deployment of new ADMS applications to existing software products.", + "laborHours": 70862.4, + "languages": [], + "name": "GRIDAPPSD/GOSS-GridAPPS-D", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GRIDAPPSD/GOSS-GridAPPS-D", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GROK.json b/agency-indexes/DoE/GROK.json new file mode 100644 index 00000000..bfc64142 --- /dev/null +++ b/agency-indexes/DoE/GROK.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "GROK is web based Internet Protocol (IP) search tool designed to help the user find and analyze network sessions in close to real time (5 minute). It relies on the output generated by a packet capture and session summary tool called BAG. The bag program runs on a linux system, and continuously generates 5 minute full packet capture ILIBPCAP files, Internet session summary files, and interface statistic files, round-robin, over a period limited to the amount of disc storage available to the system. In the LANL case, an 8 terabyte file system accommodates seven days of data (most of the time). Summary information, such as top 20 outgoing and incoming network services (such as www/tcp or 161/udp) along with network interface statistics which indicate the health of the capture system are plotted every 5 minutes for display by the GROK web server. The grok home page presents the analyst with a set of search criteria used to query the information being collected by the bag program. Since the information ultimately resides in \"pcap\" files, other pcap aware programs such as bro ethereal, nosehair, smacqq, snort, and tcpdump have been incorporated into groks web interface. Clickable documentation is available for each search criteria.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [], + "name": "GROK", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GRid_Analysis_and_Visualization_Interface__GRAVI__[SWR-24-16].json b/agency-indexes/DoE/GRid_Analysis_and_Visualization_Interface__GRAVI__[SWR-24-16].json new file mode 100644 index 00000000..df693402 --- /dev/null +++ b/agency-indexes/DoE/GRid_Analysis_and_Visualization_Interface__GRAVI__[SWR-24-16].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-07", + "metadataLastUpdated": "2024-04-16" + }, + "description": "GRAVI (GRid Analysis and Visualization Interface) is a web application for viewing and analyzing nodal Production Cost Model (PCM) and Capacity Expansion Model (CEM) simulations. The web application provides the ability to animate geospatially coupled timeseries data in an agnostic way regardless of the underlying simulation tool used to generate the data. GRAVI also provides capabilities to animate non-geospatial data relevant to a PCM or CEM model. Furthermore, this web application can be tailored as an real-time operational tool to better understand a live grid.", + "laborHours": 1535.2, + "languages": [ + "TypeScript", + "CSS", + "JavaScript", + "Python" + ], + "name": "GRid Analysis and Visualization Interface (GRAVI) [SWR-24-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GRAVI", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GSAS-II__GENERAL_STRUCTURE_AND_ALAYSIS_SYSTEM-II_.json b/agency-indexes/DoE/GSAS-II__GENERAL_STRUCTURE_AND_ALAYSIS_SYSTEM-II_.json new file mode 100644 index 00000000..ac0cb65f --- /dev/null +++ b/agency-indexes/DoE/GSAS-II__GENERAL_STRUCTURE_AND_ALAYSIS_SYSTEM-II_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2023-03-14" + }, + "description": "GSAS-II is a comprehensive data analysis and simulation software package for determining atomistic structures from single-crystal and powder diffraction data. X-ray, neutron and electron data may be used. Constant-wavelength, time-of-flight and pink-beam sources may be employed and analyses may combine different types of data. The package is oriented towards materials characterization problems, but protein crystallography, pair-distribution function analysis, small-angle scattering and reflectometry analysis are all included. GSAS-II provides tools for indexing and solving structures from powder diffraction data, in addition to structure, data and results visualization tools", + "laborHours": 0.0, + "languages": [], + "name": "GSAS-II (GENERAL STRUCTURE AND ALAYSIS SYSTEM-II)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://subversion.xray.aps.anl.gov/pyGSAS/trunk", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GWASTool.json b/agency-indexes/DoE/GWASTool.json new file mode 100644 index 00000000..06819feb --- /dev/null +++ b/agency-indexes/DoE/GWASTool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "Working repository for the TNTech student Software Engineering team.", + "laborHours": 3298.4, + "languages": [], + "name": "GWASTool", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/EMMAX_GWAS", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gafaelfawr.json b/agency-indexes/DoE/Gafaelfawr.json new file mode 100644 index 00000000..bcf8df0a --- /dev/null +++ b/agency-indexes/DoE/Gafaelfawr.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "Gafaelfawr is a FastAPI application for the authorization and management of tokens, including their issuance and revocation.", + "laborHours": 0.0, + "languages": [], + "name": "Gafaelfawr", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/gafaelfawr", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Galacticus_HDF5_Example,_Version_1.0.json b/agency-indexes/DoE/Galacticus_HDF5_Example,_Version_1.0.json new file mode 100644 index 00000000..abf557bb --- /dev/null +++ b/agency-indexes/DoE/Galacticus_HDF5_Example,_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "An example of reading the Galacticus HDF5 file in R and a demonstration of some of the features of the data.", + "laborHours": 15.2, + "name": "Galacticus HDF5 Example, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/Galacticus-HDF5-Example/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/Galacticus-HDF5-Example", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Galen_View.json b/agency-indexes/DoE/Galen_View.json new file mode 100644 index 00000000..81d5a7ac --- /dev/null +++ b/agency-indexes/DoE/Galen_View.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-03" + }, + "description": "This is software lets one explore the data released as part of the COVID-19 Open Research Dataset Challenge. It downloads and analyzes the natural language text of the data set and then creates a 2D visualization that can be used to explore it. SAND2020-12185 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 152.0, + "languages": [], + "name": "Galen View", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/galen-view/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/galen-view", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Galeri_Matrix_Generation_Package.json b/agency-indexes/DoE/Galeri_Matrix_Generation_Package.json new file mode 100644 index 00000000..1d77ec8f --- /dev/null +++ b/agency-indexes/DoE/Galeri_Matrix_Generation_Package.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-12" + }, + "description": "The Galeri package defines a collection of serial and distributed linear algebra objects to be used for software verification and validation. Galeri is used in several of the examples of the Amesos, IFPACK and ML packages, and in the Trilinos tutorial, Didasko. Galeri can be used for the generation of linear system with known propeties and data distribution for convergence analysis of interative solvers of Krylov type and domain decomposition and multigrid preconditioners.", + "laborHours": 8344830.4, + "languages": [], + "name": "Galeri Matrix Generation Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gap_Resolution.json b/agency-indexes/DoE/Gap_Resolution.json new file mode 100644 index 00000000..575f8ee3 --- /dev/null +++ b/agency-indexes/DoE/Gap_Resolution.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Gap Resolution is a software package that was developed to improve Newbler genome assemblies by automating the closure of sequence gaps caused by repetitive regions in the DNA. This is done by performing the follow steps:1) Identify and distribute the data for each gap in sub-projects. 2) Assemble the data associated with each sub-project using a secondary assembler, such as Newbler or PGA. 3) Determine if any gaps are closed after reassembly, and either design fakes (consensus of closed gap) for those that closed or lab experiments for those that require additional data. The software requires as input a genome assembly produce by the Newbler assembler provided by Roche and 454 data containing paired-end reads.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Gap Resolution", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gas_Reliability_Analysis_Integrated_Library__GRAIL_.json b/agency-indexes/DoE/Gas_Reliability_Analysis_Integrated_Library__GRAIL_.json new file mode 100644 index 00000000..9c3b0b7d --- /dev/null +++ b/agency-indexes/DoE/Gas_Reliability_Analysis_Integrated_Library__GRAIL_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-17", + "metadataLastUpdated": "2018-09-17" + }, + "description": "The Gas Reliability Analysis Integrated Library (GRAIL) is a prototype computational tool for solving a class of intra-day model-predictive control problems for a simplified network model of midstream natural gas pipeline systems. The model accurately resolves dynamic gas flows through long pipes using a non-ideal gas equation of state. It can be used to provide optimal intra-day flow schedules as well as spatiotemporal economic values of natural gas while ensuring that pipeline hydraulic limitations, compressor station constraints, operational factors, and pre-existing shipping contracts are satisfied. The inputs to the code are a model of the pipeline system as well as time-series data that specify boundary conditions on the network and time-dependent constraints on the optimal control problem. The outputs are time-series data that provide an approximately optimal solution of flows, pressures, compressor settings, and sensitivities to the objective function.", + "laborHours": 1976.0, + "languages": [], + "name": "Gas Reliability Analysis Integrated Library (GRAIL)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/grail", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GauXC_v0.1.0.json b/agency-indexes/DoE/GauXC_v0.1.0.json new file mode 100644 index 00000000..ba085cde --- /dev/null +++ b/agency-indexes/DoE/GauXC_v0.1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-03", + "metadataLastUpdated": "2021-03-03" + }, + "description": "GauXC is a modern, modular C++ library for the numerical exchange-correlation (XC) integration required for the Gaussian basis set discretization of Kohn-Sham density functional theory (DFT). The modular nature of GauXC allows for an extensible software design which enables performance portability on an array of CPU and GPU architectures.", + "laborHours": 0.0, + "languages": [], + "name": "GauXC v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wavefunction91/GauXC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gauss_Sum_Strong_Simulation_v.0.1.json b/agency-indexes/DoE/Gauss_Sum_Strong_Simulation_v.0.1.json new file mode 100644 index 00000000..f85f6db7 --- /dev/null +++ b/agency-indexes/DoE/Gauss_Sum_Strong_Simulation_v.0.1.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2024-09-19" + }, + "description": "Universal quantum circuits can be formulated in the Pauli measurement-based formalism as input T gate magic states, Clifford gates, and then multi-Pauli measurements. This code simulates single-Pauli measurements to show some theoretical bounds on the cost of full multi-Pauli measurements. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2020-14080 O", + "laborHours": 0.0, + "languages": [], + "name": "Gauss Sum Strong Simulation v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Gauss-Sum-Strong-Simulation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GeRM.json b/agency-indexes/DoE/GeRM.json new file mode 100644 index 00000000..8ffbe0fe --- /dev/null +++ b/agency-indexes/DoE/GeRM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "Software for Germanium Readout Module.", + "laborHours": 1702.4, + "languages": [], + "name": "GeRM", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/GeRM", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Geant4_based_positron_beam_source__GPos__v1.0.json b/agency-indexes/DoE/Geant4_based_positron_beam_source__GPos__v1.0.json new file mode 100644 index 00000000..00d571e9 --- /dev/null +++ b/agency-indexes/DoE/Geant4_based_positron_beam_source__GPos__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-05" + }, + "description": "GPos is a software that was created to determine the properties of positron beams resulting from the interaction of the LBNL BELLA center PetaWatt laser-driven plasma-capillary accelerated electron beam and the atoms of a thin solid target. GPos is written in C++, easily compiled with cmake and the spack package manager, which allows for multi-thread and MPI parallel computing. Its functions expand on the Geant4 toolkit library and allow for propagation of the modelled particles through vacuum drift distances with a focusing element (thin lens approximation). Users can change beam-foil-drift-lens parameters - to adapt GPos to other particle sources and infrastructures - in a simple input file. The code particle data output format, openPMD, which is compatible, for example, with the input of the ECP WarpX project code used to explore the physics of particle acceleration in plasmas. Using GPos in conjunction to WarpX allowed us to test various configurations for designing a high-quality and high-energy positron source at BELLA -required for us to address positron acceleration challenges in the development of future linear colliders. GPos can also be advantageous when tackling the physics of muon sources for future muon colliders as well as for the investigation of positron sources in lower energy regimes for applications like annihilation spectroscopy and astrophysical gamma-ray-bursts.", + "laborHours": 0.0, + "languages": [], + "name": "Geant4 based positron beam source (GPos) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LDAmorim/GPos", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gear-SCouP.json b/agency-indexes/DoE/Gear-SCouP.json new file mode 100644 index 00000000..a8fe29b7 --- /dev/null +++ b/agency-indexes/DoE/Gear-SCouP.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-06", + "metadataLastUpdated": "2021-04-27" + }, + "description": "Gear-SCouP is an analytical model for the rating analysis of articulated spline coupling designs. Articulated splines are commonly used in the planetary stage of wind turbine gearboxes as the means of transmitting the driving torque while also improving load sharing. Direct measurement of spline loads and performance is extremely challenging because of limited accessibility and spline design standards are limited. For a given torque and shaft misalignment, Gear-SCouP quickly yields physical insights into relationships between the spline design parameters and resulting loads, bending, contact, and shear stresses, and safety factors considering various heat treatment methods. Results of this analytical model are compared well against several computational approaches under moderate misalignment. The computational time of Gear-SCouP is significantly less than other FE-based tools.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Gear-SCouP", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GEAR-SCouP", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Genders.json b/agency-indexes/DoE/Genders.json new file mode 100644 index 00000000..bd25ab5d --- /dev/null +++ b/agency-indexes/DoE/Genders.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Genders is a static cluster configuration database used for cluster configuration management. It is used by a variety of tools and scripts for management of large clusters.", + "laborHours": 88722.4, + "languages": [], + "name": "Genders", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/genders", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gendersllnl.json b/agency-indexes/DoE/Gendersllnl.json new file mode 100644 index 00000000..403cc457 --- /dev/null +++ b/agency-indexes/DoE/Gendersllnl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "The Gendersllnl package is a local genders package that contains libraries with extra helper functions for Lawrence Livermore National Laboratory (LLNL) specific needs. They illustrate how local APIs can be developed on top of the genders base API. The LLNL tool dist2 is also included in the Gendersllnl package. A number of the libraries and tools in this package may be useful for clusters outside of Lawrence Livermore, but they may need to be modified for use on your particular systems. They are perhaps best used as an illustration of how libraries and tools can be built on top of the base genders libraries and tools.\n", + "laborHours": 21432.0, + "languages": [], + "name": "Gendersllnl", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/gendersllnl", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GeneDrugRepo.sol.json b/agency-indexes/DoE/GeneDrugRepo.sol.json new file mode 100644 index 00000000..c71df711 --- /dev/null +++ b/agency-indexes/DoE/GeneDrugRepo.sol.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-05" + }, + "description": "An entry to the IDASH PRIVACY & SECURITY WORKSHOP 2019 - secure genome analysis competition, Track I: Distributed Gene-Drug Interaction Data Sharing based on Blockchain and Smart Contracts. The entire codebase is comprised of a single solidity file, GeneDrugRepo.sol. Solidity is a smart contract language for the Ethereum blockchain platform. SAND2019-13419 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 106.4, + "languages": [ + "Solidity" + ], + "name": "GeneDrugRepo.sol", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/iDASH2019GeneDrug", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GeneOntologyDecorator.json b/agency-indexes/DoE/GeneOntologyDecorator.json new file mode 100644 index 00000000..ca92bc68 --- /dev/null +++ b/agency-indexes/DoE/GeneOntologyDecorator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This is the repository for \"GeneOntologyDecorator\" developed by KBase. A KBase module generated by the KBase SDK.", + "laborHours": 4392.8, + "languages": [], + "name": "GeneOntologyDecorator", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/GeneOntologyDecorator", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GeneSet_Enrichment.json b/agency-indexes/DoE/GeneSet_Enrichment.json new file mode 100644 index 00000000..501c14b8 --- /dev/null +++ b/agency-indexes/DoE/GeneSet_Enrichment.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"GeneSet_Enrichment\" developed by KBase. This is a KBase module generated by the KBase Software Development Kit (SDK).", + "laborHours": 1550.4, + "languages": [], + "name": "GeneSet_Enrichment", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/GeneSet_Enrichment", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gene_Tuples_ArraNGed_in_overLapping_Elements.json b/agency-indexes/DoE/Gene_Tuples_ArraNGed_in_overLapping_Elements.json new file mode 100644 index 00000000..0d4603ec --- /dev/null +++ b/agency-indexes/DoE/Gene_Tuples_ArraNGed_in_overLapping_Elements.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-07", + "metadataLastUpdated": "2023-06-23" + }, + "description": "GENTANGLE is a high performance containerized pipeline for the computational design of two overlapping genes translated in different reading frames of the genome that can be used to design and test gene entanglements for new microbial engineering projects using arbitrary sets of user specified gene pairs.", + "laborHours": 0.0, + "languages": [], + "name": "Gene Tuples ArraNGed in overLapping Elements", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BiosecSFA/gentangle", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/General-Simulator-Intermediary.json b/agency-indexes/DoE/General-Simulator-Intermediary.json new file mode 100644 index 00000000..996c474d --- /dev/null +++ b/agency-indexes/DoE/General-Simulator-Intermediary.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-01-03", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This application allows parallel development of simulator screens for the Human System Simulation Laboratory and connection of the backend simulators for various power plants", + "laborHours": 0.0, + "languages": [], + "name": "General-Simulator-Intermediary", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/General-Simulator-Intermediary", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/General_Entity_Model.json b/agency-indexes/DoE/General_Entity_Model.json new file mode 100644 index 00000000..df3f1a2c --- /dev/null +++ b/agency-indexes/DoE/General_Entity_Model.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2022-10-10", + "metadataLastUpdated": "2023-03-08" + }, + "description": "General Entity Model (GEM) is an extensible, upper-level ontology. An ontology is simply a collection of concepts and their relationships and properties and can be used as a schema or data model to describe some domain. As an upper-level ontology, GEM is intended to be used as a foundation for building domain-specific ontologies (such as energy, manufacturing, etc).", + "laborHours": 0.0, + "languages": [], + "name": "General Entity Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/GEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/General_Interaction_Data_Interface.json b/agency-indexes/DoE/General_Interaction_Data_Interface.json new file mode 100644 index 00000000..d9bf90a9 --- /dev/null +++ b/agency-indexes/DoE/General_Interaction_Data_Interface.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "The General Interaction Data Interface (GIDI) is a C++ API that reads and writes nuclear reaction data stored in the General Nuclear Data Structure (GNDS). GNDS is a new \"format\" for storing nuclear reaction data developed by the Working Party on Evaluation Co-operation (OECD/NEA/WPEC) Subgroup 38. \n\nGNDS can store evaluated nuclear data as well as nuclear data processed for deterministic (multi-group) and Monte Carlo transport. GIDI handles and provides accesses to all forms of the GNDS nuclear data.\n\nFor multi-group data, GIDI provides functions to sum the data over all reactions. It also has functions for collapsing multi-group data to a small subset of groups and can transport correct multi-group data using the Pendlebury/Underhill formalism.\n\nThe GNDS definition supports data for a PROjectile hitting a TARget for a given Evaluation. In GIDI this is called a PROTARE. For example, a neutron hitting O-16 from the ENDF/B-VIII.0 evaluation.\n\nTo support a collection of protares, GIDI adds a Map class. The map class reads in a \"map\" file which specifies a list of projectile/target/evalaution's and their associated protare files. \n\nWith a map instance, a user can request a specific projectile/target/evaluation and the map instance will return the requested protare.", + "laborHours": 60359.2, + "languages": [ + "C++" + ], + "name": "General Interaction Data Interface", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.17" +} \ No newline at end of file diff --git a/agency-indexes/DoE/General_Nonlinear_Ferroelectric_Model_v._Beta.json b/agency-indexes/DoE/General_Nonlinear_Ferroelectric_Model_v._Beta.json new file mode 100644 index 00000000..63187c54 --- /dev/null +++ b/agency-indexes/DoE/General_Nonlinear_Ferroelectric_Model_v._Beta.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The purpose of this software is to function as a generalized ferroelectric material model. The material model is designed to work with existing finite element packages by providing updated information on material properties that are nonlinear and dependent on loading history. The two major nonlinear phenomena this model captures are domain-switching and phase transformation. The software itself does not contain potentially sensitive material information and instead provides a framework for different physical phenomena observed within ferroelectric materials. The model is calibrated to a specific ferroelectric material through input parameters provided by the user.", + "laborHours": 1079.2, + "languages": [ + "C++", + "C" + ], + "name": "General Nonlinear Ferroelectric Model v. Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/gnom3-fe?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gnom3-fe", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/General_Nuclear_Date.json b/agency-indexes/DoE/General_Nuclear_Date.json new file mode 100644 index 00000000..a96e7844 --- /dev/null +++ b/agency-indexes/DoE/General_Nuclear_Date.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Provides python rountines to convert ENDF-6 formatted nuclear data (4) into the new GND structure. Includes sample published ENDF-6 formatted data as well as published ENSL (5) and HDF5 file.", + "homepageURL": "https://ndclx4.bnl.gov/gf/project/gnd/frs/?action=FrsReleaseBrowse&frs_package_id=26", + "laborHours": 0.0, + "name": "General Nuclear Date", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ndclx4.bnl.gov/gf/project/gnd/frs/?action=FrsReleaseBrowse&frs_package_id=26", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/General_purpose_nonlinear_system_solver_based_on_Newton-Krylov_method.json b/agency-indexes/DoE/General_purpose_nonlinear_system_solver_based_on_Newton-Krylov_method.json new file mode 100644 index 00000000..99fa74bf --- /dev/null +++ b/agency-indexes/DoE/General_purpose_nonlinear_system_solver_based_on_Newton-Krylov_method.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-07-13" + }, + "description": "KINSOL is part of a software family called SUNDIALS: SUite of Nonlinear and Differential/Algebraic equation Solvers [1]. KINSOL is a general-purpose nonlinear system solver based on Newton-Krylov and fixed-point solver technologies [2].", + "laborHours": 213088.8, + "languages": [], + "name": "General purpose nonlinear system solver based on Newton-Krylov method", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generalized_Interaction_Data_Interface_and_associated_packages.json b/agency-indexes/DoE/Generalized_Interaction_Data_Interface_and_associated_packages.json new file mode 100644 index 00000000..a19432b9 --- /dev/null +++ b/agency-indexes/DoE/Generalized_Interaction_Data_Interface_and_associated_packages.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "GIDIplus contains libraries for reading and using GNDS-formatted nuclear data.\n\nIt includes sub-packages\nGIDI, MCGIDI, PoPs, numerical Functions and status Message Reporting along with scripts for building and installing the entire library.", + "laborHours": 60359.2, + "languages": [], + "name": "Generalized Interaction Data Interface and associated packages", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generalized_Nuclear_Data_-_Mim.json b/agency-indexes/DoE/Generalized_Nuclear_Data_-_Mim.json new file mode 100644 index 00000000..471d2254 --- /dev/null +++ b/agency-indexes/DoE/Generalized_Nuclear_Data_-_Mim.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-03-15", + "metadataLastUpdated": "2021-03-15" + }, + "description": "Flexible API for combinating and generating parsers given a JSON schema.", + "laborHours": 0.0, + "languages": [], + "name": "Generalized Nuclear Data - Mim", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GeneralizedNuclearData/Mim/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GeneralizedNuclearData/Mim", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generalized_Nuclear_Data_-_WPEC_Subgroup_43.json b/agency-indexes/DoE/Generalized_Nuclear_Data_-_WPEC_Subgroup_43.json new file mode 100644 index 00000000..a1c00cb7 --- /dev/null +++ b/agency-indexes/DoE/Generalized_Nuclear_Data_-_WPEC_Subgroup_43.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-03-15", + "metadataLastUpdated": "2021-03-15" + }, + "description": "This repository describes the goals and governance of WPEC Subgroup 43 (SG43). This subgroup is tasked with creating infrastructure for the Generalized Nuclear Data (GND) format.", + "laborHours": 0.0, + "languages": [], + "name": "Generalized Nuclear Data - WPEC Subgroup 43", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GeneralizedNuclearData/SG43/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GeneralizedNuclearData/SG43", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generalized_Nuclear_Data_-_schemas_.json b/agency-indexes/DoE/Generalized_Nuclear_Data_-_schemas_.json new file mode 100644 index 00000000..7758fb05 --- /dev/null +++ b/agency-indexes/DoE/Generalized_Nuclear_Data_-_schemas_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-03-15", + "metadataLastUpdated": "2021-03-15" + }, + "description": "Schemas defining the GNDS format. Hosting the schemas in a public place allows anyone to refer to them and a common place to store them.", + "laborHours": 0.0, + "languages": [], + "name": "Generalized Nuclear Data - schemas ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GeneralizedNuclearData/schemas/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GeneralizedNuclearData/schemas", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generalized_Perturbed_Equilibrium_Code.json b/agency-indexes/DoE/Generalized_Perturbed_Equilibrium_Code.json new file mode 100644 index 00000000..f56ba5f4 --- /dev/null +++ b/agency-indexes/DoE/Generalized_Perturbed_Equilibrium_Code.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "nlogan@pppl.gov" + }, + "date": { + "created": "2019-02-07", + "metadataLastUpdated": "2019-02-12" + }, + "description": "The Generalized Perturbed Equilibrium Code (GPEC) package contains a suite of non-axisymmetric stability and perturbed equilibrium force balance codes including DCON/RDCON/STRIDE (stability), GPEC (driven plasma response), and PENTRC (NTV torque). The perturbation calculations can optionally use ideal MHD throughout, kinetic MHD throughout, or a mix of ideal MHD outer layer and resistive MHD inner layer physics at the rational surfaces. \n\nEarlier versions of this software contained only the ideal MHD model, and results were published under the name of the Ideal Perturbed Equilibrium Code (IPEC).\n\nPrimary journal citations can be found on the landing page.", + "homepageURL": "http://princetonuniversity.github.io/GPEC", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Generalized Perturbed Equilibrium Code", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://princetonuniversity.github.io/GPEC", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://princetonuniversity.github.io/GPEC", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "version": "1.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generalized_Preconditioned_Locally_Harmonic_Residual_Eigensolver__GPLHR__v0.1.json b/agency-indexes/DoE/Generalized_Preconditioned_Locally_Harmonic_Residual_Eigensolver__GPLHR__v0.1.json new file mode 100644 index 00000000..bc19e0f4 --- /dev/null +++ b/agency-indexes/DoE/Generalized_Preconditioned_Locally_Harmonic_Residual_Eigensolver__GPLHR__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The software contains a MATLAB implementation of the Generalized Preconditioned Locally Harmonic Residual (GPLHR) method for solving standard and generalized non-Hermitian eigenproblems. The method is particularly useful for computing a subset of eigenvalues, and their eigen- or Schur vectors, closest to a given shift. The proposed method is based on block iterations and can take advantage of a preconditioner if it is available. It does not need to perform exact shift-and-invert transformation. Standard and generalized eigenproblems are handled in a unified framework.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Generalized Preconditioned Locally Harmonic Residual Eigensolver (GPLHR) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generalized_defect_dynamics.json b/agency-indexes/DoE/Generalized_defect_dynamics.json new file mode 100644 index 00000000..0b43fdf2 --- /dev/null +++ b/agency-indexes/DoE/Generalized_defect_dynamics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "The micron level generalized defect dynamics code is a numerical tool predicting the overall mechanical response and microstructure evolutions of metals deforming by dislocation glide, cross slip and climb and point defect diffusion and clustering. The tool relies on the use of a Fast Fourier Transform mechanical solver allowing for the computation of mechanical fields resulting from the presence of dislocations, grain boundaries and second phases. The code leverages both field defect mechanics and cluster dynamics modeling framework.\n\n\tThe primary intent of this tool is to validate and calibrate mathematical constitutive models used to describe the mechanical response and microstructure evolutions of metals. This is achieved by tracking the evolution of an ensemble of dislocations and of points defects subjected to mechanical loading. The code can simulate complex microstructures and physical phenomena associated with plasticity. As such, it can be applied to metals with any crystal symmetry (face centered cubic, body centered cubic, hexagonal closed packed). Further, the model can be applied to single crystalline and to polycrystalline aggregates. Simulation volumes can be subjected to mixed boundary conditions (i.e. stress and strain) and the effect of free surfaces can also be accounted for such as to mimic plasticity in thin films and in micropillars.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Generalized defect dynamics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generate_reveal.js_slfdeshow_from_reStructuredText.json b/agency-indexes/DoE/Generate_reveal.js_slfdeshow_from_reStructuredText.json new file mode 100644 index 00000000..d14e5f0c --- /dev/null +++ b/agency-indexes/DoE/Generate_reveal.js_slfdeshow_from_reStructuredText.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-07-20", + "metadataLastUpdated": "2018-07-20" + }, + "description": "Rst2slldes Is a python extension package for the standard docuti!s documentation generation system. Docutlls translates a simple text markup language called reStructuredText Into a variety of formals, Including HTML and PDF. The reveal.Js presentation framework is a popular syslem klr displaying a specially prepared HTML file as a slldeshow. Because reStructuredText is far simpler to compose end read than HTML, rst2slldes is a useful tool for creating and maintaining technical presentations, which can be delivered to the audience using any web browser. Most of the functionality of rst2slldes, Including lhe ability to display equations written In LaTeX and to embed Images, Is Inherited from docutlls. Besides slightly modifying Ule HTML output to work with reveal.js, the features added by rst2slldes are the ability to embed video, and to set reveal.js configuration options.", + "laborHours": 456.0, + "languages": [], + "name": "Generate reveal.js slfdeshow from reStructuredText", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/rst2slides", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generator_Scorecard.json b/agency-indexes/DoE/Generator_Scorecard.json new file mode 100644 index 00000000..145cf299 --- /dev/null +++ b/agency-indexes/DoE/Generator_Scorecard.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2025-02-24" + }, + "description": "Code built on Archive Walker. The Generator Scorecard analyzes power grid measurements to automate the process of evaluating the performance of generators. The tool includes three aspects: frequency response, voltage response, and voltage schedule tracking.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 201217.6, + "languages": [], + "name": "Generator Scorecard", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generic_Cron_Server.json b/agency-indexes/DoE/Generic_Cron_Server.json new file mode 100644 index 00000000..dc3fe721 --- /dev/null +++ b/agency-indexes/DoE/Generic_Cron_Server.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "This server sends requests to other servers on a pre-defined schedule. Those requests can be optionally authenticated.", + "laborHours": 60.8, + "languages": [], + "name": "Generic Cron Server", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/cron_server", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generic_Data_Display__GD2_.json b/agency-indexes/DoE/Generic_Data_Display__GD2_.json new file mode 100644 index 00000000..ee9e65b4 --- /dev/null +++ b/agency-indexes/DoE/Generic_Data_Display__GD2_.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-08", + "metadataLastUpdated": "2023-08-08" + }, + "description": "SAND2023-11967O\nGeneric Data Display (GD2) is a real-time data visualization application that can display user-defined input data. The open-source software is comprised of a back end system written in Python, and a front end user interface written in JavaScript. The back end system collects data from a variety of input sources, such as message queue, HTTP, XML, JSON, and others. The front end displays data in an Open MCT web interface, and users can configure the system by providing JSON formatted configuration files. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "python" + ], + "name": "Generic Data Display (GD2)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/generic-data-display", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generic_Fortran_Containers__GFC_.json b/agency-indexes/DoE/Generic_Fortran_Containers__GFC_.json new file mode 100644 index 00000000..3b2a86b4 --- /dev/null +++ b/agency-indexes/DoE/Generic_Fortran_Containers__GFC_.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Fortran language does not provide a standard library that implements generic containers, like linked lists, trees, dictionaries, etc. The GFC software provides an implementation of generic Fortran containers natively written in Fortran 2003/2008 language. The following containers are either already implemented or planned: Stack (done), Linked list (done), Tree (done), Dictionary (done), Queue (planned), Priority queue (planned).", + "laborHours": 8268.8, + "name": "Generic Fortran Containers (GFC)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/DmitryLyakh/GFC", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generic_Learning_User_Enablement_Code__GLUE_Code_.json b/agency-indexes/DoE/Generic_Learning_User_Enablement_Code__GLUE_Code_.json new file mode 100644 index 00000000..243d286a --- /dev/null +++ b/agency-indexes/DoE/Generic_Learning_User_Enablement_Code__GLUE_Code_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "The Generic Learning User Enablement Code (GLUE Code) is a modular framework designed to couple different scientific\napplications to support use cases including multiscale methods and various forms of machine learning. The workflow was\ninitially designed around supporting active learning as an alternative to coupled applications to support multiscale\nmethods but has been written in a sufficiently modular way that different machine learning methods can be utilized.\nApplication programming interfaces (API) are available for C, C++, Fortran, and Python with support for various storage\nformats including SQL databases and HDF5. The code also provides direct coupling with high performance computing job\nschedulers such as Slurm and Flux. The associated open source repository will include source code, build infrastructure,\ndocumentations, and examples demonstrating how to use the GLUE Code with oopen source ICF and Porous Media\napplications", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Generic Learning User Enablement Code (GLUE Code)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generic_Optimization_Program.json b/agency-indexes/DoE/Generic_Optimization_Program.json new file mode 100644 index 00000000..c3e98fc8 --- /dev/null +++ b/agency-indexes/DoE/Generic_Optimization_Program.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "GenOpt is a generic optimization program for nonlinear, constrained optimization. For evaluating the objective function, any simulation program that communicates over text files can be coupled to GenOpt without code modification. No analytic properties of the objective function are used by GenOpt. Optimization algorithms and numerical methods can be implemented in a library and shared among users. GenOpt offers an interlace between the optimization algorithm and its kernel to make the implementation of new algorithms fast and easy. Different algorithms of constrained and unconstrained minimization can be added to a library. Algorithms for approximation derivatives and performing line-search will be implemented. The objective function is evaluated as a black-box function by an external simulation program. The kernel of GenOpt deals with the data I/O, result storage and report, interlace to the external simulation program, and error handling. An abstract optimization class offers methods to interface the GenOpt kernel and the optimization algorithm library.", + "homepageURL": "http://simulationresearch.lbl.gov/GO", + "laborHours": 0.0, + "languages": [], + "name": "Generic Optimization Program", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://simulationresearch.lbl.gov/GO/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://simulationresearch.lbl.gov/GO", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generic_Overlay_Framework.json b/agency-indexes/DoE/Generic_Overlay_Framework.json new file mode 100644 index 00000000..0ad9efb8 --- /dev/null +++ b/agency-indexes/DoE/Generic_Overlay_Framework.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "This software provides a framework for building application layter overlay networks. It includes example overlays that can be used without modification. Also provided are example multicast and routing protocols that can be used with the overlays.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Generic Overlay Framework", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Generic_Semi-Analytical_Simulation_Tool__GenSAS_.json b/agency-indexes/DoE/Generic_Semi-Analytical_Simulation_Tool__GenSAS_.json new file mode 100644 index 00000000..93afe113 --- /dev/null +++ b/agency-indexes/DoE/Generic_Semi-Analytical_Simulation_Tool__GenSAS_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2023-03-16" + }, + "description": "A generic simulation tool for power grid and general dynamic systems based on semi-analytical solutions (SAS) technology.", + "laborHours": 0.0, + "languages": [], + "name": "Generic Semi-Analytical Simulation Tool (GenSAS)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-CEEESA/gensas", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GenericsAPI.json b/agency-indexes/DoE/GenericsAPI.json new file mode 100644 index 00000000..35557762 --- /dev/null +++ b/agency-indexes/DoE/GenericsAPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-08", + "metadataLastUpdated": "2020-09-08" + }, + "description": "This is the repository for \"GenericsAPI\" developed by KBase. A KBase module generated by the KBase SDK.", + "laborHours": 12388.0, + "languages": [], + "name": "GenericsAPI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/GenericsAPI", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GenericsIndexer.json b/agency-indexes/DoE/GenericsIndexer.json new file mode 100644 index 00000000..26a1c433 --- /dev/null +++ b/agency-indexes/DoE/GenericsIndexer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "This is the repository for \"GenericsIndexer\" developed by KBase. ", + "laborHours": 1474.4, + "languages": [], + "name": "GenericsIndexer", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/GenericsIndexer", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GenericsService.json b/agency-indexes/DoE/GenericsService.json new file mode 100644 index 00000000..e4637c0e --- /dev/null +++ b/agency-indexes/DoE/GenericsService.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "A dynamic service with fetch methods for Generics objects.", + "laborHours": 972.8, + "languages": [], + "name": "GenericsService", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/GenericsService", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GenericsUtil.json b/agency-indexes/DoE/GenericsUtil.json new file mode 100644 index 00000000..b28fa1bf --- /dev/null +++ b/agency-indexes/DoE/GenericsUtil.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "Utilities to import and map KBase Generic objects.", + "laborHours": 7341.6, + "languages": [], + "name": "GenericsUtil", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/GenericsUtil", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Genesearch:_a_Gene_Homology_Search_Service__Genesearch__v1.0.json b/agency-indexes/DoE/Genesearch:_a_Gene_Homology_Search_Service__Genesearch__v1.0.json new file mode 100644 index 00000000..ac277dae --- /dev/null +++ b/agency-indexes/DoE/Genesearch:_a_Gene_Homology_Search_Service__Genesearch__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-03", + "metadataLastUpdated": "2021-03-03" + }, + "description": "This is a web service that allows users to query a set of genome databases to find matches for specific genes.\n\nGenesearch provides endpoints for interactive and batch homology searches that identify alignments between a query sequence and the sequences in a genomics database.", + "laborHours": 0.0, + "languages": [], + "name": "Genesearch: a Gene Homology Search Service (Genesearch) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/jgi-kbase/genesearch", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "version": "v1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Geneset.json b/agency-indexes/DoE/Geneset.json new file mode 100644 index 00000000..9a552a48 --- /dev/null +++ b/agency-indexes/DoE/Geneset.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"Geneset\" developed by KBase. \n", + "laborHours": 60.8, + "languages": [], + "name": "Geneset", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/Geneset", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Genetic_Algorithms_for_Optimizing_Spin_Reversals_on_D-Wave_Quantum_Annealers.json b/agency-indexes/DoE/Genetic_Algorithms_for_Optimizing_Spin_Reversals_on_D-Wave_Quantum_Annealers.json new file mode 100644 index 00000000..29ad7334 --- /dev/null +++ b/agency-indexes/DoE/Genetic_Algorithms_for_Optimizing_Spin_Reversals_on_D-Wave_Quantum_Annealers.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "We developed software which optimizes the selection of spin reversal's on the D-Wave 2000Q for individual problems. Commercial quantum annealers from D-Wave Systems make it possible to obtain approximate solutions of high quality for certain NP-hard problems in nearly constant time. Before solving a problem on D-Wave, several pre-processing methods can be applied, one of them being the so-called spin reversal or gauge transform. The spin reversal transform flips the sign of selected variables and coefficients of the Ising or QUBO (quadratic unconstrained binary optimization) representation of the problem that D-Wave minimizes. The spin reversal transform leaves the ground state of the Ising model invariant, but can average out the biases induced through analog and systematic errors on the device, thus improving the quality of the solution that D-Wave returns. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Genetic Algorithms for Optimizing Spin Reversals on D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GenomeAnnotationAPI.json b/agency-indexes/DoE/GenomeAnnotationAPI.json new file mode 100644 index 00000000..0c0132bd --- /dev/null +++ b/agency-indexes/DoE/GenomeAnnotationAPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-18", + "metadataLastUpdated": "2020-08-18" + }, + "description": "Data API for Genome Annotation Objects.", + "laborHours": 817167.2, + "languages": [], + "name": "GenomeAnnotationAPI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/genome_annotation_api", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GenomeAnnotationFileUtil.json b/agency-indexes/DoE/GenomeAnnotationFileUtil.json new file mode 100644 index 00000000..7743b0ea --- /dev/null +++ b/agency-indexes/DoE/GenomeAnnotationFileUtil.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "Narrative uploader/downloader apps and local functions for GenomeAnnotation objects.", + "laborHours": 1124.8, + "languages": [], + "name": "GenomeAnnotationFileUtil", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/GenomeAnnotationFileUtil", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GenomeBrowser.json b/agency-indexes/DoE/GenomeBrowser.json new file mode 100644 index 00000000..7b391372 --- /dev/null +++ b/agency-indexes/DoE/GenomeBrowser.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This module implements apps and utilities to enable browsing genomes with JBrowse.", + "laborHours": 1702.4, + "languages": [], + "name": "GenomeBrowser", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/kb_GenomeBrowser", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GenomeComparison.json b/agency-indexes/DoE/GenomeComparison.json new file mode 100644 index 00000000..46bb5a65 --- /dev/null +++ b/agency-indexes/DoE/GenomeComparison.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "This module contains the code for some comparative genomics functions in KBase.", + "laborHours": 8770.4, + "languages": [], + "name": "GenomeComparison", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/GenomeComparison", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GenomeFileUtil.json b/agency-indexes/DoE/GenomeFileUtil.json new file mode 100644 index 00000000..5383eb85 --- /dev/null +++ b/agency-indexes/DoE/GenomeFileUtil.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-08", + "metadataLastUpdated": "2020-09-08" + }, + "description": "This is the repository for \"GenomeFileUtil\" developed by KBase. ", + "laborHours": 2516846.4, + "languages": [], + "name": "GenomeFileUtil", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/GenomeFileUtil", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GenomeProteomeComparison.json b/agency-indexes/DoE/GenomeProteomeComparison.json new file mode 100644 index 00000000..4c1cec5a --- /dev/null +++ b/agency-indexes/DoE/GenomeProteomeComparison.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "This is the repository for \"GenomeProteomeComparison\" developed by KBase. ", + "laborHours": 6551.2, + "languages": [], + "name": "GenomeProteomeComparison", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/GenomeProteomeComparison", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GenomeReport.json b/agency-indexes/DoE/GenomeReport.json new file mode 100644 index 00000000..16279154 --- /dev/null +++ b/agency-indexes/DoE/GenomeReport.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "A module with tools to generate different reports on a genome or a set of genomes.", + "laborHours": 1140.0, + "languages": [], + "name": "GenomeReport", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/GenomeReport", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GenomeSearchUtil.json b/agency-indexes/DoE/GenomeSearchUtil.json new file mode 100644 index 00000000..6130cb60 --- /dev/null +++ b/agency-indexes/DoE/GenomeSearchUtil.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "This is the repository for \"GenomeSearchUtil\" developed by KBase. ", + "laborHours": 602740.8, + "languages": [], + "name": "GenomeSearchUtil", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/GenomeSearchUtil", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Genome_Utilities.json b/agency-indexes/DoE/Genome_Utilities.json new file mode 100644 index 00000000..54814d3e --- /dev/null +++ b/agency-indexes/DoE/Genome_Utilities.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "Exposes core KBase genome and feature utility methods, such as running Blast against a genome.", + "laborHours": 425.6, + "languages": [], + "name": "Genome Utilities", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/genome_util", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Genomic_Island_Identification_Software_v_1.0.json b/agency-indexes/DoE/Genomic_Island_Identification_Software_v_1.0.json new file mode 100644 index 00000000..f779de0e --- /dev/null +++ b/agency-indexes/DoE/Genomic_Island_Identification_Software_v_1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-19" + }, + "description": "Genomic islands are key mobile DNA elements in bacterial evolution, that can distinguish pathogenic strains from each other, or distinguish pathogenic strains from non-pathogenic strains. Their detection in genomes is a challenging problem. We present 3 main software components that attack the island detection problem on two different bases: 1) the preference of islands to insert in chromosomal tRNA or tmRNA genes (islander.pl), and 2) islands' sporadic occurrence among closely related strains. The latter principle is employed in both an algorithm (learnedPhyloblocks.pl) and a visualization method (panGenome.pl). Component islander.pl finds islands based on their preference for a particular target gene type. We annotate each tRNA and tmRNA gene, find fragments of each such gene as candidates for the distal ends of islands, and filter candidates to remove false positives. Component learnedPhyloblocks.pl uses islands found by islander.pl and other methods as a training set to find new islands. Reference genomes are aligned using mugsy, then the \"phylotypes\" or patterns of occurrence in the reference set are determined for each position in the target genome, and those phylotypes most enriched in the training set of islands are followed to detect yet more islands. Component panGenome.pl produces a big-data visualization of the chromosomally-ordered \"pan-genome\", that includes every gene of every reference genome (x-axis, pan-genome order; y-axis, reference genomes; color-coding, gene presence/absence etc.), islands appearing as dark patches.", + "laborHours": 18027.2, + "languages": [ + "Perl", + "C", + "Python" + ], + "name": "Genomic Island Identification Software v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TIGER", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Genten:_Software_for_Generalized_Tensor_Decompositions_v._1.0.0.json b/agency-indexes/DoE/Genten:_Software_for_Generalized_Tensor_Decompositions_v._1.0.0.json new file mode 100644 index 00000000..e6177d0c --- /dev/null +++ b/agency-indexes/DoE/Genten:_Software_for_Generalized_Tensor_Decompositions_v._1.0.0.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Tensors, or multidimensional arrays, are a powerful mathematical means of describing multiway data. This software provides computational means for decomposing or approximating a given tensor in terms of smaller tensors of lower dimension, focusing on decomposition of large, sparse tensors. These techniques have applications in many scientific areas, including signal processing, linear algebra, computer vision, numerical analysis, data mining, graph analysis, neuroscience and more. The software is designed to take advantage of parallelism present emerging computer architectures such has multi-core CPUs, many-core accelerators such as the Intel Xeon Phi, and computation-oriented GPUs to enable efficient processing of large tensors.", + "laborHours": 606784.0, + "languages": [ + "C++", + "Shell", + "C", + "CMake", + "Makefile", + "Python" + ], + "name": "Genten: Software for Generalized Tensor Decompositions v. 1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/GenTen?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GenTen", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GentenMPI.json b/agency-indexes/DoE/GentenMPI.json new file mode 100644 index 00000000..47169c78 --- /dev/null +++ b/agency-indexes/DoE/GentenMPI.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2025-02-13" + }, + "description": "GentenMPI is software to compute low-rank approximations of sparse data tensors. These methods are often used for unsupervised machine learning to find significant properties of sparse, unstructured data sets. GentenMPI uses the same algorithms that are available in Sandia's open-source codes TensorToolbox and Genten, but GentenMPI provides distributed memory implementations of these algorithms using infrastructure from Sandia's open-source Trilinos framework. GentenMPI includes an implementation CP-ALS (canonical polyadic decomposition via alternating least squares optimization, first published in 1970 by Carroll & Chang and Harshman); its distributed memory implementation uses Trilinos' Map-based distribution of data to processors and Trilinos' communication operations designed for sparse matrix-vector multiplication. Its performance is comparable to other open-source CP-ALS implementations (e.g., the SPLATT tool of Smith and Karypis). GentenMPI also include a distributed memory implementation of GCP-SGD (generalized canonical polyadic decomposition via stochastic gradient descent, first published in 2019 by Hong, Kolda and Deursch); the implementation closely follows that in TensorToolbox, and exploits a block-based data distribution to perform sampling in parallel. GentenMPI is written in C++ and relies on the MPI (Message Passing Interface) library available on most distributed memory computers. SAND2020-12648 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 12448.8, + "languages": [ + "C++", + "Cmake" + ], + "name": "GentenMPI", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GentenMPI", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GeoGraph:_A_Framework_for_Graph_Processing_on_Geometric_Data.json b/agency-indexes/DoE/GeoGraph:_A_Framework_for_Graph_Processing_on_Geometric_Data.json new file mode 100644 index 00000000..9f7cea11 --- /dev/null +++ b/agency-indexes/DoE/GeoGraph:_A_Framework_for_Graph_Processing_on_Geometric_Data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nYiqiu Wang, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun.\nGeoGraph: A Framework for Graph Processing on Geometric Data.\nACM SIGOPS Operating Systems Review, Vol. 55 Issue 1, pp. 38-46, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "GeoGraph: A Framework for Graph Processing on Geometric Data", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/GeoGraph", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/GeoGridFusion__Open-Source_Geospatial_Toolkit_for_Solar_Data_Integration\342\200\213__[SWR-25-19].json" "b/agency-indexes/DoE/GeoGridFusion__Open-Source_Geospatial_Toolkit_for_Solar_Data_Integration\342\200\213__[SWR-25-19].json" new file mode 100644 index 00000000..0f58223a --- /dev/null +++ "b/agency-indexes/DoE/GeoGridFusion__Open-Source_Geospatial_Toolkit_for_Solar_Data_Integration\342\200\213__[SWR-25-19].json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-02-24", + "metadataLastUpdated": "2025-03-11" + }, + "description": "GeoGridFusion facilitates the usage and storage of gridded geospatial satellite data by users outside of the National Renewable Lab (NREL), particularly those without access to high-performance computing (HPC) resources. This tool builds on work done by the PVDegradationTools project for DuraMAT, with the goal of making our advancements from this project widely accessible.\n\nThis repo contains utilities to allow for the storage of user downloaded geospatial weather data by providing a local datastore for storage and spatial queries, supporting large-scale analyses without the need for HPC resources.", + "laborHours": 9393.6, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "GeoGridFusion (Open-Source Geospatial Toolkit for Solar Data Integration\u200b) [SWR-25-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/GeoGridFusion", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GeoMatTool,_Version_1.0.json b/agency-indexes/DoE/GeoMatTool,_Version_1.0.json new file mode 100644 index 00000000..63542463 --- /dev/null +++ b/agency-indexes/DoE/GeoMatTool,_Version_1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-06-15", + "metadataLastUpdated": "2018-06-18" + }, + "description": "GeoMatTool support the estimation of parameter values for certain models of use in geomechanics modeling and simulation. The tool itself is a Java language script that functions principally as a database manager for data from certain geomechanical tests. The tool as a database manager allows the user to access, review and modify in limited ways the data. The tool then serves as an interface to plotting and statistical software packages to facilitate the evaluation of the data and parameter estimation.", + "homepageURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [], + "name": "GeoMatTool, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GeoPlace_v._1.0.json b/agency-indexes/DoE/GeoPlace_v._1.0.json new file mode 100644 index 00000000..342d65c0 --- /dev/null +++ b/agency-indexes/DoE/GeoPlace_v._1.0.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-19" + }, + "description": "GeoPlace software solves several problems related to efficient sensor placement for remote sensing. It consists of several components. \u201cGeoFoot\u201d finds efficient locations for centering a set of camera images, in order to ensure that the collection of images contains an entire region. It is built on a modified version of \u201cSimple MPS\u201d. GeoSubFoot selects non-overlapping rectangular subregions of a single camera image, in order to devote more resources for higher-fidelity sub-images of those regions. The goal is for the rectangular subregions to contain many user-specified pixels of interest. Simple MPS is a generic program that produces point-sample distributions with blue noise characteristics over arbitrary-dimensional squares. GeoFoot includes an extension of it to sampling from polygons in 2d, including both the inside of the polygon and slightly outside it.", + "laborHours": 2280.0, + "languages": [ + "C++", + "Shell", + "Makefile", + "Python" + ], + "name": "GeoPlace v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/GeoPlace?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cgvalic/GeoPlace", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GeoT_V1.3.json b/agency-indexes/DoE/GeoT_V1.3.json new file mode 100644 index 00000000..07f2b1b5 --- /dev/null +++ b/agency-indexes/DoE/GeoT_V1.3.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-13", + "metadataLastUpdated": "2019-06-17" + }, + "description": "Geo T automates into a stand-alone computer program the multicomponent chemical geothermometry method previously developed by Reed and Spycher (1984). Geo T allows for simultaneous regression of multiple water chemical analyses, automatic reconstitution of deep fluids, and estimation of reservoir temperature from statistical evaluation of computed mineral saturation indices. The temperature estimation includes a \"best\" estimated temperature with its range of uncertainity. The computer program also outputs temperatures predicted using classical geothermometers. Input parameters include water composition and optionally, gas composition, dilution/evaporation factor (in case of boiling or mixing with dilute waters), and end-member water composition (in case of mixing with other non-dilute waters). This program was designed for geothermal applications but is also useful as a tool to quickly speciate a large number of water analyses.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "GeoT V1.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GeoTess_v._2.6.8.json b/agency-indexes/DoE/GeoTess_v._2.6.8.json new file mode 100644 index 00000000..27136937 --- /dev/null +++ b/agency-indexes/DoE/GeoTess_v._2.6.8.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GeoTess facilitates access to a multi-level triangular tessellation of a unit sphere, including find the index of the triangle in which an arbitrary position on the sphere resides and computing the interpolation coefficients that should be applied to data stored on the nodes of the tessellation that defines the triangle. It is very common for Earth scientists to store values of various Earth properties on a grid that spans the globe. For convenience, they almost always choose a grid which is evenly spaced in both latitude and longitude over the surface of the globe. While these grids are evenly spaced in latitude-longitude coordinates, they are in reality very unevenly spaced when cell size is evaluated in square km since lines of longitude converge at the poles. Tessellations consisting of a set of approximately equal area triangles that span the globe are much more efficient way to impose a grid onto the surface of a sphere. The GeoTess software facilitates interacting with a triangular tessellation of a sphere and could significantly increase the efficiency of Earth science software codes. The code can construct variable resolution triangular tessellations. It can also load a previously constructed tessellation from an input file and implements a \"walking triangle\" search algorithm to find the index of the triangle on the tessellation that contains a user specified point of interest. It also computes the interpolation coefficients that should be applied to data stored on the nodes of the containing triangle", + "laborHours": 135918.4, + "languages": [ + "Java", + "HTML" + ], + "name": "GeoTess v. 2.6.8", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GeoTessJava", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.6.8" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Geodesic_IO_Library.json b/agency-indexes/DoE/Geodesic_IO_Library.json new file mode 100644 index 00000000..db3be62e --- /dev/null +++ b/agency-indexes/DoE/Geodesic_IO_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "GIO is an application programmer interface (API) or library for high performance IO that is designed for climate models that operate on a geodesic grid. GIO uses a combination of configuration files and API calls to define the mapping of internal model data to output variables in standard climate data formats. The mapping from model data to model output includes method of data slicing, aggregation, and linearization using a morton ordering approach. The data is then persisted through a standard interface that can be implemented using several different high level parallel libraries. Both Parallel NetCDF and NetCDF4 interfaces are provided. GIO is designed to run on supercomputing systems or multi-processor clusters with parallel file systems.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Geodesic IO Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Geographic_Visualization_of_Power-Grid_Dynamics.json b/agency-indexes/DoE/Geographic_Visualization_of_Power-Grid_Dynamics.json new file mode 100644 index 00000000..fedcba41 --- /dev/null +++ b/agency-indexes/DoE/Geographic_Visualization_of_Power-Grid_Dynamics.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The visualization enables the simulation analyst to see changes in the frequency through time and space. With this technology, the analyst has a bird's eye view of the frequency at loads and generators as the simulated power system responds to the loss of a generator, spikes in load, and other contingencies. The significance of a contingency to the operation of an electrical power system depends critically on how the resulting tansients evolve in time and space. Consequently, these dynamic events can only be understood when seen in their proper geographic context. this understanding is indispensable to engineers working on the next generation of distributed sensing and control systems for the smart grid. By making possible a natural and intuitive presentation of dynamic behavior, our new visualization technology is a situational-awareness tool for power-system engineers.", + "laborHours": 773132.8, + "name": "Geographic Visualization of Power-Grid Dynamics", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ssrangan/VizPower/blob/master/Open%20Source%20Software%20License%20(Permissive).pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ssrangan/VizPower", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Geographically_aware_estimates_of_remotely_sensed_water_properties_for_Chesapeake_Bay.json b/agency-indexes/DoE/Geographically_aware_estimates_of_remotely_sensed_water_properties_for_Chesapeake_Bay.json new file mode 100644 index 00000000..a591b239 --- /dev/null +++ b/agency-indexes/DoE/Geographically_aware_estimates_of_remotely_sensed_water_properties_for_Chesapeake_Bay.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-04", + "metadataLastUpdated": "2023-01-04" + }, + "description": "This software contains the code for a data-driven model to produce high-resolution (< 1 km2) estimates of temperature, salinity, and turbidity over decadal time scales as required by next-generation Earth Systems Models. Our model fits daily MODIS Aqua reflectance data to surface observations (< 1 m depth) from 2000-2021 in Chesapeake Bay, USA.", + "laborHours": 0.0, + "languages": [], + "name": "Geographically aware estimates of remotely sensed water properties for Chesapeake Bay", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DOE-ICoM/geowq-chesapeake", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Geometry_Description_Markup_Language__GDML_.json b/agency-indexes/DoE/Geometry_Description_Markup_Language__GDML_.json new file mode 100644 index 00000000..4b520dca --- /dev/null +++ b/agency-indexes/DoE/Geometry_Description_Markup_Language__GDML_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "Geometry Description Markup Language (GDML) version 3.1.2 (deprecated but used by SLIC).\n", + "laborHours": 19167.2, + "languages": [], + "name": "Geometry Description Markup Language (GDML)", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/gdml/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/gdml", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Geospatial_Toolkit.json b/agency-indexes/DoE/Geospatial_Toolkit.json new file mode 100644 index 00000000..319fffc0 --- /dev/null +++ b/agency-indexes/DoE/Geospatial_Toolkit.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Geospatial Toolkit is an NREL-developed map-based software application that integrates resource data and other geographic information systems (GIS) data for integrated resource assessment. The non-resource, country-specific data for each toolkit comes from a variety of agencies within each country as well as from global datasets. Originally developed in 2005, the Geospatial Toolkit was completely redesigned and re-released in November 2010 to provide a more modern, easier-to-use interface with considerably faster analytical querying capabilities. The revised version of the Geospatial Toolkit has been released for all original toolkit countries/regions and each software package is made available on NREL's website,", + "homepageURL": "http://www.nrel.gov/international/geospatial_toolkits.html", + "laborHours": 281245.6, + "name": "Geospatial Toolkit", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.nrel.gov/international/geospatial_toolkits.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Geothermal_Design_Tool__GeoDT_.json b/agency-indexes/DoE/Geothermal_Design_Tool__GeoDT_.json new file mode 100644 index 00000000..fd99c481 --- /dev/null +++ b/agency-indexes/DoE/Geothermal_Design_Tool__GeoDT_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "Advanced high-fidelity modelling capabilities are available to evaluate hydraulic fracture growth, fluid flow in fracture networks, fluid-rock heat and mass transfer, geomechanical coupling, geochemical coupling, and electrical power production. While all these components must be considered to design geothermal wells and well fields, as of yet, no models couple all these processes efficiently enough for timely making during ongoing projects. Here we present a new modelling tool to inform rapid decision making for well design, drilling, and operation in fracture-dominated geothermal systems. This new tool, which we call the Geothermal Design Tool (GeoDT), evaluates 3D well placement, natural and hydraulic fracture stimulation by fluid injection, induced seismicity risk, long term flow behavior, heat transfer to flowing fluid over time, and transient electrical power production. Instead of using only first-principles and the common simplifying assumptions that are typical of high-fidelity models, this model is based more on experiment derived scaling relations that, by their nature, include the effect of multi-scale complex effects. This approach helps to avoid misleading simplifications while, at the same time, including small-scale complexities that are often too cumbersome or ill-defined to directly include in higher-fidelity models. The final product is a tool that can model 20 years of dynamic geothermal fluid production from a stimulated fracture dominated systems in seconds using a desktop computer.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Geothermal Design Tool (GeoDT)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Geothermal_District_Heating_Economics.json b/agency-indexes/DoE/Geothermal_District_Heating_Economics.json new file mode 100644 index 00000000..e6ea5c74 --- /dev/null +++ b/agency-indexes/DoE/Geothermal_District_Heating_Economics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2023-01-17" + }, + "description": "GEOCITY is a large-scale simulation model which combines both engineering and economic submodels to systematically calculate the cost of geothermal district heating systems for space heating, hot-water heating, and process heating based upon hydrothermal geothermal resources. The GEOCITY program simulates the entire production, distribution, and waste disposal process for geothermal district heating systems, but does not include the cost of radiators, convectors, or other in-house heating systems. GEOCITY calculates the cost of district heating based on the climate, population, and heat demand of the district; characteristics of the geothermal resource and distance from the distribution center; well-drilling costs; design of the distribution system; tax rates; and financial conditions.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Geothermal District Heating Economics", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Geppetto_User_Interface__UI_.json b/agency-indexes/DoE/Geppetto_User_Interface__UI_.json new file mode 100644 index 00000000..217808a3 --- /dev/null +++ b/agency-indexes/DoE/Geppetto_User_Interface__UI_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The Geppetto application, developed in collaboration between Los Alamos National Laboratory and the DARPA MediFor program, provides an analysis platform for deepfake video detection. Geppetto provides a web interface and backend software that orchestrates the upload and analysis processes for a set of videos. This disclosure covers the user interface for Geppetto. ", + "laborHours": 0.0, + "languages": [], + "name": "Geppetto User Interface (UI)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/geppetto-ui", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Git_Replacement_for_the.json b/agency-indexes/DoE/Git_Replacement_for_the.json new file mode 100644 index 00000000..b86dbee2 --- /dev/null +++ b/agency-indexes/DoE/Git_Replacement_for_the.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GRAPE is a tool for managing software project workflows for the Git version control system. It provides a suite of tools to simplify and configure branch based development, integration with a project's testing suite, and integration with the Atlassian Stash repository hosting tool.", + "laborHours": 15139.2, + "name": "Git Replacement for the", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/GRAPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gitlab_Runner_Auth.json b/agency-indexes/DoE/Gitlab_Runner_Auth.json new file mode 100644 index 00000000..57aa7a95 --- /dev/null +++ b/agency-indexes/DoE/Gitlab_Runner_Auth.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-11-11", + "metadataLastUpdated": "2019-11-11" + }, + "description": "This project simplifies the registration and authentication of a Gitlab runner. \n\nThis allows administrators to create a set of static configuration files from which this script will build the appropriate, host-specific config needed to communicate with and accept jobs from Gitlab.", + "laborHours": 182.4, + "languages": [], + "name": "Gitlab Runner Auth", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/gitlab-runner-auth", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Give_Take.json b/agency-indexes/DoE/Give_Take.json new file mode 100644 index 00000000..8a2f8bb7 --- /dev/null +++ b/agency-indexes/DoE/Give_Take.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Give and Take are set of companion utilities that allow a secure transfer of files from one user to another without exposing the files to third parties. The named files are copied to a spool area. The reciever can retrieve the files by running the \"take\" program. Ownership of the files remains with the giver until they are taken. Certain users may be limited to take files only from specific givers. For these users, files may only be taken from givers who are members of the gt-uid-group where uid is the UNIX id of the limited user.", + "laborHours": 26934.4, + "name": "Give/Take", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/give", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gkeyll_2.0.json b/agency-indexes/DoE/Gkeyll_2.0.json new file mode 100644 index 00000000..ad998ab8 --- /dev/null +++ b/agency-indexes/DoE/Gkeyll_2.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "ahakim@pppl.gov" + }, + "date": { + "created": "2018-07-26", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Gkeyll v2.0 (also known as Gkyl, or G2) is a computational plasma physics code mostly written in LuaJIT, with time-critical parts written in C++. Gkyl contains solvers for gyrokinetic equations, Vlasov-Maxwell equations, and multi-fluid equations. Gkeyll contains ab-initio and novel implementations of a number of algorithms, and perhaps is unique in using a JIT compiled typeless dynamic language for its implementation.\n\nOne of the main innovations in Gkeyll is the blurring of boundaries between user written code (i.e. input files) and backend solver code. In fact, there is no difference: the front-end and back-end are written in the same programming language, opening up a very powerful way of composing simulations. All solver objects (grids, data-structures, updaters) can be queried, modified and controlled by the user, allowing complete control over the full simulation cycle. The use of the highly optimized Just-in-Time (JIT) compiled LuaJIT as the main programming language ensures that user written code remains highly efficient. Of course, core kernels can always be written in C/C++ and hooked in via LuaJIT\u2019s powerful FFI facilities.", + "homepageURL": "https://theory.pppl.gov/research/research.php?rid=10#h44", + "laborHours": 0.0, + "languages": [ + "C++", + "C++", + "Lua" + ], + "name": "Gkeyll 2.0", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://theory.pppl.gov/research/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://theory.pppl.gov/research/research.php?rid=10#h44", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GlideinMonitor.json b/agency-indexes/DoE/GlideinMonitor.json new file mode 100644 index 00000000..063449b6 --- /dev/null +++ b/agency-indexes/DoE/GlideinMonitor.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2020-03-12", + "metadataLastUpdated": "2020-03-12" + }, + "description": "GlideinMonitor is a Web application that allows to view GlideinWMS\u2019s Glidein log files: it provides a user interface, tools to do quick searches and to decode the log content; it provides an efficient managed archive of the log files and a framework to add log processing, e.g. log sanitation.\nhttps://docs.google.com/document/d/1PqmQ_-_JtqK472DT-Y0D08yU1m-lPeFvrp8n4x9f5QE/edit?usp=sharing", + "homepageURL": "https://cdcvs.fnal.gov/redmine/projects/glideinwms/repository/glideinmonitor", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "GlideinMonitor", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cdcvs.fnal.gov/redmine/projects/glideinwms/repository/glideinmonitor", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GloVe_C++_v._1.0.json b/agency-indexes/DoE/GloVe_C++_v._1.0.json new file mode 100644 index 00000000..2a2aa8b3 --- /dev/null +++ b/agency-indexes/DoE/GloVe_C++_v._1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This code implements the GloVe algorithm for learning word vectors from a text corpus. It uses a modern C++ approach. This algorithm is described in the open literature in the referenced paper by Pennington, Jeffrey, Richard Socher, and Christopher D. Manning.", + "laborHours": 486.4, + "languages": [ + "C++", + "Makefile" + ], + "name": "GloVe C++ v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GloveCpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Global-Address_Networking__GASNet-1__Library.json b/agency-indexes/DoE/Global-Address_Networking__GASNet-1__Library.json new file mode 100644 index 00000000..5fe88920 --- /dev/null +++ b/agency-indexes/DoE/Global-Address_Networking__GASNet-1__Library.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2018-09-05" + }, + "description": "GASNet is a language-independent, networking middleware layer that provides network-independent, high-performance communication primitives including Remote Memory Access (RMA) and Active Messages (AM). It has been used to implement parallel programming models and libraries such as UPC, Co-Array Fortran, Titanium, Legion, Chapel, and many others. The interface is primarily intended as a compilation target and for use by runtime library writers (as opposed to end users), and the primary goals are high performance, interface portability, and expressiveness. GASNet stands for \"Global-Address Space Networking\". \n\n", + "laborHours": 93632.0, + "languages": [], + "name": "Global-Address Networking (GASNet-1) Library", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/gasnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Global-Address_Space_Networking_for_Exascale.json b/agency-indexes/DoE/Global-Address_Space_Networking_for_Exascale.json new file mode 100644 index 00000000..093d0648 --- /dev/null +++ b/agency-indexes/DoE/Global-Address_Space_Networking_for_Exascale.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2020-06-01" + }, + "description": "GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of Partitioned Global Address Space (PGAS) runtime systems and other alternative models in future exascale machines. The library is an evolution of the popular GASNet communication system, building upon over 15 years of lessons learned. \n\nGASNet is a language-independent, networking middleware layer that provides network-independent, high-performance communication primitives including Remote Memory Access (RMA) and Active Messages (AM). It has been used to implement parallel programming models and libraries such as UPC, Co-Array Fortran, Titanium, Legion, Chapel, and many others. The interface is primarily intended as a compilation target and for use by runtime library writers (as opposed to end users), and the primary goals are high performance, interface portability, and expressiveness. GASNet stands for \"Global-Address Space Networking\". \n", + "homepageURL": "http://gasnet.lbl.gov", + "laborHours": 235858.4, + "languages": [], + "name": "Global-Address Space Networking for Exascale", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://gasnet.lbl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GlobalSums,_Version_1.x.json b/agency-indexes/DoE/GlobalSums,_Version_1.x.json new file mode 100644 index 00000000..56e89810 --- /dev/null +++ b/agency-indexes/DoE/GlobalSums,_Version_1.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code is a set of global sums to support the paper \"Computational Reproducibility for Production Physics Applications\" submitted to the Numerical Reproducibility at Exascale (NRE 2015) workshop at the 2015 Supercomputing conference, Nov. 20, 2015", + "laborHours": 851.2, + "name": "GlobalSums, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/GlobalSums", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Global_Arrays.json b/agency-indexes/DoE/Global_Arrays.json new file mode 100644 index 00000000..1a443e54 --- /dev/null +++ b/agency-indexes/DoE/Global_Arrays.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-09-01" + }, + "description": "Global Arrays (GA) is a Partitioned Global Address Space (PGAS) programming model. It provides primitives for one-sided communication (Get, Put, Accumulate) and Atomic Operations (read increment). It supports blocking and non-blocking primtives, and supports location consistency.", + "laborHours": 311478.4, + "languages": [], + "name": "Global Arrays", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GlobalArrays/ga/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GlobalArrays/ga", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Global_Feedback_Simulator.json b/agency-indexes/DoE/Global_Feedback_Simulator.json new file mode 100644 index 00000000..fe0b1e99 --- /dev/null +++ b/agency-indexes/DoE/Global_Feedback_Simulator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "GFS is a simulation engine that is used for the characterization of Accelerator performance parameters based on the machine layout, configuration and noise sources. It combines extensively tested Feedback models with a longitudinal phase space tracking simulator along with the interaction between the two via beam-based feedback using a computationally efficient simulation engine. The models include beam instrumentation, considerations on loop delays for in both the R and beam-based feedback loops, as well as the ability to inject noise (both correlated and uncorrelated) at different points of the machine including a full characterization of the electron gun performance parameters.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Global Feedback Simulator", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Global_Pathway_Selection_with_Zero-RK.json b/agency-indexes/DoE/Global_Pathway_Selection_with_Zero-RK.json new file mode 100644 index 00000000..9c21b11e --- /dev/null +++ b/agency-indexes/DoE/Global_Pathway_Selection_with_Zero-RK.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-08", + "metadataLastUpdated": "2024-08-08" + }, + "description": "Global Pathway Selection (GPS) is an algorithm to effectively generates reduced (skeletal) chemistry\nmechanisms, which speeds up simulations and can be used as a systematic analytics tool to extract\ninsights from complex reacting system. This release is an extension of the original code to run in parallel\nand to use LLNL's Zero-RK solver for fast solution of chemical problems.", + "laborHours": 10351.2, + "languages": [], + "name": "Global Pathway Selection with Zero-RK", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GPS-Z", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.4" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GlobiPack_v._1.0.json b/agency-indexes/DoE/GlobiPack_v._1.0.json new file mode 100644 index 00000000..48b3c84e --- /dev/null +++ b/agency-indexes/DoE/GlobiPack_v._1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GlobiPack contains a small collection of optimization globalization algorithms. These algorithms are used by optimization and various nonlinear equation solver algorithms.Used as the line-search procedure with Newton and Quasi-Newton optimization and nonlinear equation solver methods. These are standard published 1-D line search algorithms such as are described in the book Nocedal and Wright Numerical Optimization: 2nd edition, 2006. One set of algorithms were copied and refactored from the existing open-source Trilinos package MOOCHO where the linear search code is used to globalize SQP methods. This software is generic to any mathematical optimization problem where smooth derivatives exist. There is no specific connection or mention whatsoever to any specific application, period. You cannot find more general mathematical software.", + "laborHours": 8344830.4, + "name": "GlobiPack v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/globipack/copyright_header.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Globus.json b/agency-indexes/DoE/Globus.json new file mode 100644 index 00000000..b89b9e23 --- /dev/null +++ b/agency-indexes/DoE/Globus.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-13", + "metadataLastUpdated": "2021-11-23" + }, + "description": "Globus is a platform for research data management. The Globus service, operated by the University of Chicago, enables secure, reliable file transfer, sharing and data automation. The service is integrated into data portals, science gateways, and other web applications that manage data distribution from instruments and provide access to reference datasets.", + "homepageURL": "https://globus.org", + "laborHours": 0.0, + "languages": [], + "name": "Globus", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.globus.org/legal", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://globus.org", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GlyQ-IQ.json b/agency-indexes/DoE/GlyQ-IQ.json new file mode 100644 index 00000000..0053ab70 --- /dev/null +++ b/agency-indexes/DoE/GlyQ-IQ.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "GlyQ-IQ is a program that performs a targeted, chromatographic centric search of mass spectral data for glycans. It is designed for high resolution LC-MS datasets. The software uses a list of glycan targets to search for expected features in MS1 spectra. Features are characterized by monoisotopic mass, elution time, and isotopic fit score. Features are annotated by glycan family relationships and optionally by in-source fragmentation patterns.", + "laborHours": 321601.6, + "languages": [], + "name": "GlyQ-IQ", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/GlyQ-IQ", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gnawts.json b/agency-indexes/DoE/Gnawts.json new file mode 100644 index 00000000..f4fcafb7 --- /dev/null +++ b/agency-indexes/DoE/Gnawts.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "High Performance Computing (HPC) systems generate millions of inter-related event log lines per day from thousands of computers, providing feedback on both successful and unsuccessful operations within the system. Thorough analysis of these logs is often required for root cause analysis of problems and tuning for greatest performance. This \"app\" for the \"Gnawts\" log analysis software (http://www.gnawts.com) facilitates faster and deeper insights into HPC system logs.", + "laborHours": 4301.6, + "languages": [ + "CSS", + "Perl", + "HTML", + "Korn shell", + "JavaScript", + "Python" + ], + "name": "Gnawts", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gnawts", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GnuForPlot_Graphics.json b/agency-indexes/DoE/GnuForPlot_Graphics.json new file mode 100644 index 00000000..5d5b64f4 --- /dev/null +++ b/agency-indexes/DoE/GnuForPlot_Graphics.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "bobby.kitchens@srnl.doe.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Gnuforplot Graphics is a Fortran90 program designed to generate two and three dimensional plots of data on a personal computer. The program uses calls to the open source code Gnuplot to generate the plots. Two Fortran90 programs have been written to use the Gnuplot graphics capabilities. The first program, named Plotsetup.f90 reads data from output files created by either the Stadium or LeachXS/Orchestra modeling codes and saves the data in arrays for plotting. This program then calls Gnuforplot which takes the data array along with user specified parameters to set plot specifications and issues Gnuplot commands that generate the screen plots. The user can view the plots and optionally save copies in jpeg format.", + "homepageURL": "http://sti.srs.gov/fulltext/Software/gnuforplot_rev_11-4-15.zip", + "laborHours": 0.0, + "languages": [ + "Fortran90" + ], + "name": "GnuForPlot Graphics", + "organization": "Savannah River Site (SRS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://sti.srs.gov/fulltext/Software/gnuforplot_rev_11-4-15.zip", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://sti.srs.gov/fulltext/Software/gnuforplot_rev_11-4-15.zip", + "status": "Production", + "tags": [ + "DOE CODE", + "Savannah River Site (SRS)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GoFigure.json b/agency-indexes/DoE/GoFigure.json new file mode 100644 index 00000000..d8041183 --- /dev/null +++ b/agency-indexes/DoE/GoFigure.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-07", + "metadataLastUpdated": "2021-07-07" + }, + "description": "GoFigure is a code repository for a set of tools for the analysis and retrieval of technical images, or figures, such as drawings and plots. The goal of these tools is to automate the understanding of technical content contained in scientific images. Computer vision algorithms are automating the analysis of content in images and these tools will extend these innovations for images of scientific content. GoFigure includes tools for analyzing the context, topology and shape information in images, as well as graph-based matching algorithms for fast retrieval of similar images. These components are written in Python, a high-level programming language that takes advantage of the Python eco-system of high-quality open-source packages for computer vision, graph algorithms and machine learning.", + "laborHours": 0.0, + "languages": [], + "name": "GoFigure", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GoFigure-LANL/GoFigure", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Go_oVirt_API.json b/agency-indexes/DoE/Go_oVirt_API.json new file mode 100644 index 00000000..e571b500 --- /dev/null +++ b/agency-indexes/DoE/Go_oVirt_API.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An API library that allows communication with oVirt using the Go language.", + "laborHours": 1033.6, + "languages": [], + "name": "Go oVirt API", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/ovirtapi", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GradeIT__Road_Grade_Inference_Tool_.json b/agency-indexes/DoE/GradeIT__Road_Grade_Inference_Tool_.json new file mode 100644 index 00000000..d320f529 --- /dev/null +++ b/agency-indexes/DoE/GradeIT__Road_Grade_Inference_Tool_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-17" + }, + "description": "The National Renewable Energy Laboratory (NREL) has developed the Road Grade Inference Tool, \"GradeIT\". This tool is a modular Python package the leverages the United States Geological Survey\u2019s (USGS) 1/3 arc-second Digital Elevation Model (DEM), an open and free public dataset. Roadway gradient (slope) has a strong influence on vehicle energy consumption behavior and longitudinal dynamics. Therefore, any tools, models, or analyses that consider vehicle energy consumption or driving profiles is incomplete without accurate elevation and grade information. Despite the acute need for this data, it is rarely collected alongside GPS (latitude and longitude) data, and tools to post-process GPS data to append elevation and grade are difficult to come by. GradeIT satisfies this significant need in the research community. \n\nUtilization of the USGS DEM makes the underlying data available to any potential user and ensures continuous data anywhere in the continental United States. The USGS DEM is a great resource; however, in order to be useful for automotive and traffic engineering applications, significant interpolation and filtering is required to achieve an accurate representation of gradient on the roadway. GradeIT employs a two-dimensional interpolation to approximate elevation at a point on the road from the nearest nodes in the DEM. Then, GradeIT applies multiple filtering techniques to smooth the elevation profile to a realistic road topology. Finally, road grade is derived from the elevation profile and returned as the primary output.", + "laborHours": 288.8, + "languages": [ + "Python" + ], + "name": "GradeIT (Road Grade Inference Tool)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/gradeit", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Grand_Unified_File-Index__GUFI_.json b/agency-indexes/DoE/Grand_Unified_File-Index__GUFI_.json new file mode 100644 index 00000000..0d0199de --- /dev/null +++ b/agency-indexes/DoE/Grand_Unified_File-Index__GUFI_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "The Grand Unified File Index (GUFI) is an index that holds file-system metadata (i.e. filenames, access and creation dates, file attributes, extended attributes, etc.) pulled from huge file/data storage-systems using full and incremental index update, allowing rapid searches that don\u2019t have to impact the file-systems themselves, supporting both users and system/data managers. GUFI is a very fast software solution that offers speed and security, while minimizing impact on supercomputing resources. ", + "laborHours": 18787.2, + "languages": [], + "name": "Grand Unified File-Index (GUFI)", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mar-file-system/GUFI/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mar-file-system/GUFI", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Granular_Flow.json b/agency-indexes/DoE/Granular_Flow.json new file mode 100644 index 00000000..71efaae6 --- /dev/null +++ b/agency-indexes/DoE/Granular_Flow.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2023-03-08" + }, + "description": "LIGGGHTS-INL is a capability-extended version of LIGGGHTS. LIGGGHTS is an Open Source Discrete Element Method Particle Simulation Software (https://www.cfdem.com/media/DEM/docu/Manual.html). LIGGGHTS stands for LAMMPS improved for general granular and granular heat transfer simulations. LAMMPS is a classical molecular dynamics simulator. It is widely used in the field of Molecular Dynamics (https://lammps.sandia.gov/doc/Manual.html). Thanks to physical and algorithmic analogies, LAMMPS is a very good platform for DEM simulations. LAMMPS offers a GRANULAR package to perform these kinds of simulations. LIGGGHTS aims to improve those capability with the goal to apply it to industrial applications.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Granular Flow", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/LIGGGHTS-INL", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Granular_Flow_Constitutive_Model_Add-ons_For_Abaqus.json b/agency-indexes/DoE/Granular_Flow_Constitutive_Model_Add-ons_For_Abaqus.json new file mode 100644 index 00000000..bc009d33 --- /dev/null +++ b/agency-indexes/DoE/Granular_Flow_Constitutive_Model_Add-ons_For_Abaqus.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-02-19", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The software is a list of Abaqus User MATerial subroutines (VUMAT) for modeling granular flow physics. It includes (1) density dependent Mohr-Coulomb model, (2) density dependent Drager-Prager\\Cap model, (3)Gudehus-Bauer hypoplastic model, and (4) critical state-based NorSand model.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Granular Flow Constitutive Model Add-ons For Abaqus", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/GranularFlowModels", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Graph-Env.json b/agency-indexes/DoE/Graph-Env.json new file mode 100644 index 00000000..a7f16a93 --- /dev/null +++ b/agency-indexes/DoE/Graph-Env.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-04-22", + "metadataLastUpdated": "2022-06-22" + }, + "description": "The Graph-Env library provides a framework for adapting graph search problems into OpenAI Gym environments for reinforcement learning. In other words, Graph-Env enables reinforcement learning algorithms to be applied to graph search problems. Graph search problems include molecule and crystal structure design problems; route planning problems, including traveling salesperson problem; puzzles and games, such as chess and go; shortest path problems; minimum spanning tree; vehicle path generation; and others.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Graph-Env", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/graph-env", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GraphBench.json b/agency-indexes/DoE/GraphBench.json new file mode 100644 index 00000000..d759fd95 --- /dev/null +++ b/agency-indexes/DoE/GraphBench.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "GraphBench is a benchmark suite for graph pattern mining and graph analysis systems. The benchmark suite is a significant addition to conducting apples-apples comparison of graph analysis software (databases, in-memory tools, triple stores, etc.)", + "laborHours": 19121.6, + "name": "GraphBench", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ssrangan/GraphBench/blob/master/Open%20Source%20Software%20License%20(Permissive%20May%202015)%20for%20GM-SPARQL.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ssrangan/GraphBench", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GraphDot_v0.1.json b/agency-indexes/DoE/GraphDot_v0.1.json new file mode 100644 index 00000000..4cb5b2c8 --- /dev/null +++ b/agency-indexes/DoE/GraphDot_v0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-15", + "metadataLastUpdated": "2019-10-15" + }, + "description": "GraphDot is a scikit-learn compatible library that implements GPU-accelerated graph kernels for similarity comparison between graphs.", + "laborHours": 1126912.8, + "languages": [], + "name": "GraphDot v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/yhtang/graphdot", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GraphEM.json b/agency-indexes/DoE/GraphEM.json new file mode 100644 index 00000000..b3d87126 --- /dev/null +++ b/agency-indexes/DoE/GraphEM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-06-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An unsupervised segmentation method for structural analysis of Scanning Transmission\nElectron Microscopy (STEM) images", + "laborHours": 212.8, + "languages": [], + "name": "GraphEM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/GraphEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GraphIt:_A_high-performance_graph_domain_specific_language.json b/agency-indexes/DoE/GraphIt:_A_high-performance_graph_domain_specific_language.json new file mode 100644 index 00000000..bf6efd18 --- /dev/null +++ b/agency-indexes/DoE/GraphIt:_A_high-performance_graph_domain_specific_language.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for GraphIt DSL. See https://graphit-lang.org/ for more info.", + "laborHours": 0.0, + "languages": [], + "name": "GraphIt: A high-performance graph domain specific language", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GraphIt-DSL/graphit", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GraphSAGE-Sparse_v.0.2.0.json b/agency-indexes/DoE/GraphSAGE-Sparse_v.0.2.0.json new file mode 100644 index 00000000..02809638 --- /dev/null +++ b/agency-indexes/DoE/GraphSAGE-Sparse_v.0.2.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-14", + "metadataLastUpdated": "2022-10-21" + }, + "description": "SAND2022-12899 O GraphSAGE-Sparse is an implementation of the GraphSAGE Graph Neural Network that adds support for sparse data structures, as well as improved functionality through the Tensorflow 2 functional API. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Bash", + "Python" + ], + "name": "GraphSAGE-Sparse v.0.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/graphsage-sparse/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/graphsage-sparse", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Graph_Learning_in_Physical-informed_Mesh-reduced_Space_for_Real-world_Dynamic_Systems.json b/agency-indexes/DoE/Graph_Learning_in_Physical-informed_Mesh-reduced_Space_for_Real-world_Dynamic_Systems.json new file mode 100644 index 00000000..2b6090bc --- /dev/null +++ b/agency-indexes/DoE/Graph_Learning_in_Physical-informed_Mesh-reduced_Space_for_Real-world_Dynamic_Systems.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-03", + "metadataLastUpdated": "2023-08-08" + }, + "description": "This Git repository contains codes for the 'Graph Learning in Physical-informed Mesh-reduced Space for Real-world Dynamic Systems' paper that will be published in 2023 SIGKDD. This work uses physical-informed prior (PiP) information to learn and predict fluid dynamics in a reduced mesh space. We propose a two-stage graph-based model for fluid velocity field reconstruction and prediction. In the first stage, we learn a subgraph autoencoder to summarize the information in a mesh-reduced space using physical-informed priors. In the second stage, we learn a dynamics predictor to predict subgraph evolution. We demonstrate the effectiveness of our model on two fluid flow datasets: lid-driven cavity flow data and cylinder flow data. This code is also applicable for any other dynamic systems with corresponding data.", + "laborHours": 0.0, + "languages": [], + "name": "Graph Learning in Physical-informed Mesh-reduced Space for Real-world Dynamic Systems", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Yeping-Hu/MeshGraph-RealDynSys", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Graph_Library.json b/agency-indexes/DoE/Graph_Library.json new file mode 100644 index 00000000..aa98bf2d --- /dev/null +++ b/agency-indexes/DoE/Graph_Library.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GraphLib is a support library used by other tools to create, manipulate, store, and export graphs. It provides a simple interface to specifS' arbitrary directed and undirected graphs by adding nodes and edges. Each node and edge can be associated with a set of attributes describing size, color, and shape. Once created, graphs can be manipulated using a set of graph analysis algorithms, including merge, prune, and path coloring operations. GraphLib also has the ability to export graphs into various open formats such as DOT and GML.", + "laborHours": 2340.8, + "name": "Graph Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/graphlib", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Graph_Neural_Network_for_Anomaly_Detection_and_Classification_in_Scientific_Workflows.json b/agency-indexes/DoE/Graph_Neural_Network_for_Anomaly_Detection_and_Classification_in_Scientific_Workflows.json new file mode 100644 index 00000000..8c85402d --- /dev/null +++ b/agency-indexes/DoE/Graph_Neural_Network_for_Anomaly_Detection_and_Classification_in_Scientific_Workflows.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-20", + "metadataLastUpdated": "2024-08-20" + }, + "description": "Repo that contains code and example data for workflow anomaly detection with graph neural networks", + "laborHours": 13832.0, + "languages": [], + "name": "Graph Neural Network for Anomaly Detection and Classification in Scientific Workflows", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/FlowGAD", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Graph_Neural_Networks_and_Applied_Linear_Algebra_v.1.0.json b/agency-indexes/DoE/Graph_Neural_Networks_and_Applied_Linear_Algebra_v.1.0.json new file mode 100644 index 00000000..c459c31e --- /dev/null +++ b/agency-indexes/DoE/Graph_Neural_Networks_and_Applied_Linear_Algebra_v.1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-20" + }, + "description": "SAND2024-01365O\nThe Graph Neural Networks and Applied Linear Algebra is companion software for the educational article with the same title. The software provides illustrative examples of graph neural networks in Matlab and Python. These stand-alone algorithms are for educational purposes. \n\nThe software also includes graph neural network-based algorithms for a trainable Jacobi iteration as well as diffusion coefficient estimation. The software provides human-interpretable implementations of Graph Neural Networks in Matlab and Python. These implementations are not optimized for performance and instead emphasize readability. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python" + ], + "name": "Graph Neural Networks and Applied Linear Algebra v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gnn-applied-linear-algebra", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Graph_Partitioning_Bias_Reduction_for_D-Wave_Quantum_Annealers.json b/agency-indexes/DoE/Graph_Partitioning_Bias_Reduction_for_D-Wave_Quantum_Annealers.json new file mode 100644 index 00000000..bc7f1c9e --- /dev/null +++ b/agency-indexes/DoE/Graph_Partitioning_Bias_Reduction_for_D-Wave_Quantum_Annealers.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "Quantum annealers offer an efficient way to compute high quality solutions of NP-hard problems when expressed in a QUBO (quadratic unconstrained binary optimization) or an Ising form. This is done by mapping a problem onto the physical qubits and couplers of the quantum chip, from which a solution is read after a process called quantum annealing. However, this process is subject to multiple sources of biases, including poor calibration, leakage between adjacent qubits, control biases, etc., which might negatively influence the quality of the annealing results. In this software, we aim at mitigating the effect of such biases for solving constrained optimization problems, by offering a two-step method, and apply it to Graph Partitioning. In the first step, we measure and reduce any biases that result from implementing the constraints of the problem. In the second, we add the objective function to the resulting bias-corrected implementation of the constraints, and send the problem to the quantum annealer. We apply this concept to Graph Partitioning, an important NP-hard problem, which asks to find a partition of the vertices of a graph that is balanced (the constraint) and minimizes the cut size (the objective). We develop methods for an iterative method to correct any such biases. We demonstrate that, after adding the objective, solving the resulting bias-corrected Ising problem on the quantum annealer results in a higher solution accuracy.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Graph Partitioning Bias Reduction for D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Graph_neural_network_tutorial_for_digital_twin_application.json b/agency-indexes/DoE/Graph_neural_network_tutorial_for_digital_twin_application.json new file mode 100644 index 00000000..5f93ee43 --- /dev/null +++ b/agency-indexes/DoE/Graph_neural_network_tutorial_for_digital_twin_application.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zhangc@ornl.gov" + }, + "date": { + "created": "2024-01-08", + "metadataLastUpdated": "2024-01-09" + }, + "description": "Tutorial on graph neural network (GNN) for the digital twin (DT) team at ORNL.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Graph neural network tutorial for digital twin application", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/KedoKudo/DT_GNN_Tutorial", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Graph_theory_approach_to_estimate_the_rate_of_SARS-CoV-2_lineage_spread_from_early_genetic_sequence_data.json b/agency-indexes/DoE/Graph_theory_approach_to_estimate_the_rate_of_SARS-CoV-2_lineage_spread_from_early_genetic_sequence_data.json new file mode 100644 index 00000000..81610a83 --- /dev/null +++ b/agency-indexes/DoE/Graph_theory_approach_to_estimate_the_rate_of_SARS-CoV-2_lineage_spread_from_early_genetic_sequence_data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Analyze virus genetic sequences to identify lineages that are spreading especially rapidly.", + "laborHours": 121.6, + "languages": [], + "name": "Graph theory approach to estimate the rate of SARS-CoV-2 lineage spread from early genetic sequence data", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ruianke/CoV2-GenomicGraphTheory-PCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Graphene_U-Net_v1.json b/agency-indexes/DoE/Graphene_U-Net_v1.json new file mode 100644 index 00000000..84b850eb --- /dev/null +++ b/agency-indexes/DoE/Graphene_U-Net_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-01", + "metadataLastUpdated": "2021-07-01" + }, + "description": "Graphene U-Net is a library that provides a simplified platform for training deep neural networks for the task of microscopy image segmentation. It contains functions and classes that make the process of training a neural network simple such that non-ML experts can train and evaluate models on their own datasets. It uses Pytorch as a backend and can run on both CUDA-enable GPUs and CPUs. It contains the main library file Microscopy_Unet.py as well as unet.py which contains the UNET model used for this software. This can be replaced with any other fully convolutional deep learning architecture with relative ease.", + "laborHours": 0.0, + "languages": [], + "name": "Graphene U-Net v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnlcomputerarch/graphene-u-net", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Graphical_Contingency_Analysis_Tool.json b/agency-indexes/DoE/Graphical_Contingency_Analysis_Tool.json new file mode 100644 index 00000000..342fec8b --- /dev/null +++ b/agency-indexes/DoE/Graphical_Contingency_Analysis_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "GCA is a visual analytic tool for power grid contingency analysis to provide more decision support for power grid operations. GCA allows power grid operators to quickly gain situational awareness of power grid by converting large amounts of operational data to graphic domain with a color contoured map; identify system trend and foresee and discern emergencies by performing trending analysis; identify the relationships between system configurations and affected assets by conducting clustering analysis; and identify the best action by interactively evaluate candidate actions.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Graphical Contingency Analysis Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Graphical_Data_Broker_Browsers.json b/agency-indexes/DoE/Graphical_Data_Broker_Browsers.json new file mode 100644 index 00000000..ee3da8d5 --- /dev/null +++ b/agency-indexes/DoE/Graphical_Data_Broker_Browsers.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "This is GUI for browsing runs that are stored in the databroker. It is intended as read-only browser, not a full-fledged data analysis framework. There is limited support for interactivity and data export. This project has been superceded by bluesky-browser.", + "laborHours": 684.0, + "languages": [], + "name": "Graphical Data Broker Browsers", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/databroker-browser", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Grappolo.json b/agency-indexes/DoE/Grappolo.json new file mode 100644 index 00000000..58a48fe7 --- /dev/null +++ b/agency-indexes/DoE/Grappolo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Community detection has become a fundamental operation in numerous graph-theoretic applications. It is used to reveal natural divisions that exist within real world networks without imposing prior size or cardinality constraints on the set of communities. Despite its potential for application, there is only limited support for community detection on large-scale parallel computers, largely owing to the irregular and inherently sequential nature of the underlying heuristics. In this paper, we present parallelization heuristics for fast community detection using the Louvain method as the serial template. The Louvain method is an iterative heuristic for modularity optimization. Originally developed by Blondel et al. in 2008, the method has become increasingly popular owing to its ability to detect high modularity community partitions in a fast and memory-efficient manner. However, the method is also inherently sequential, thereby limiting its scalability. Here, we observe certain key properties of this method that present challenges for its parallelization, and consequently propose heuristics that are designed to break the sequential barrier. For evaluation purposes, we implemented our heuristics using OpenMP multithreading, and tested them over real world graphs derived from multiple application domains (e.g., internet, citation, biological). Compared to the serial Louvain implementation, our parallel implementation is able to produce community outputs with a higher modularity for most of the inputs tested, in comparable number of iterations, while providing real speedups of up to 8x using 32 threads. In addition, our parallel implementation was able to exhibit weak scaling properties on up to 32 threads.", + "laborHours": 0.0, + "languages": [], + "name": "Grappolo", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exa-Graph/grappolo", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gravitation_and_Mesh_Adaption.json b/agency-indexes/DoE/Gravitation_and_Mesh_Adaption.json new file mode 100644 index 00000000..3bb5e0d6 --- /dev/null +++ b/agency-indexes/DoE/Gravitation_and_Mesh_Adaption.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-01-19", + "metadataLastUpdated": "2022-01-19" + }, + "description": "The Gravitation and Mesh Adaptation (GaMA) toolbox consists of a set of Matlab classes for modeling the environment around asteroids and comets. A variety of gravitational models and supporting algorithms from are consolidated alongside a custom meshing utility tailored for the application. This allows the user to work within a single streamlined environment to import and manipulate surface definitions, probe the dynamical environment, integrate trajectories, and post-process results. For other applications, modified surface meshes can be exported. Gravity Models: 1) Werner's analytic polyhedron model 2) Mascon model 3) Gottlieb's spherical harmonic model 4) Approximate polyhedron models 5) Curvilinear surface models 6) Custom composite models Meshing Features: 1) Array-based half-edge data structure 2) Supports curvilinear surface definitions up to degree 4 3) Ray-tracing 4) Coarsening 5) Feature-based refinement 6) Projection 7) Smoothing 8) Mesh quality validity tests 9) Mesh repair Additional Features: 1) Solar radiation pressure model 2) Distant 3rd body model 3) Collision detection 4) Trajectory integration and post-processing 5) Visualization of surface fields", + "laborHours": 0.0, + "languages": [], + "name": "Gravitation and Mesh Adaption", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmpearl/GaMA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Greedy_Latent_Space_Dynamics_Identification.json b/agency-indexes/DoE/Greedy_Latent_Space_Dynamics_Identification.json new file mode 100644 index 00000000..095cf6d4 --- /dev/null +++ b/agency-indexes/DoE/Greedy_Latent_Space_Dynamics_Identification.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-21", + "metadataLastUpdated": "2023-03-21" + }, + "description": "This is a variant of LaSDI where it minimizes both reconstruction loss terms of auto encoder and dynamics regression loss terms simultaneously. Plus, an active learning framework is adopted so that a physics-informed greedy sampling point can be added to enhance the performance of gLaSDI. It is written in python and several examples are included in this software.", + "laborHours": 0.0, + "languages": [], + "name": "Greedy Latent Space Dynamics Identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gLaSDI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GreenArrow_version_1.0.json b/agency-indexes/DoE/GreenArrow_version_1.0.json new file mode 100644 index 00000000..ee7947bf --- /dev/null +++ b/agency-indexes/DoE/GreenArrow_version_1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "GreenArrow is a visualization program for displaying directed graphs that can use text in place of lines to represent the edges between nodes. This text can be animated to show the link direction, and allow for more text to be displayed then would normally be allowed. The text is also tapered and arced to show direction. The node labels can be wrapped around the node to avoid label crossing as well. The program is interactive, and allows the user to zoom, pan and rotate a graph, as well as manipulate the individual nodes.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "GreenArrow version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2020_.Net_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2020_.Net_.json" new file mode 100644 index 00000000..d4934317 --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2020_.Net_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-10-07" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model \u00ae (2020 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2020 (v1.3.0.13656)" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2020_Excel_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2020_Excel_.json" new file mode 100644 index 00000000..e9b78e78 --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2020_Excel_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-12" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model \u00ae (2020 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2020" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2021_.Net_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2021_.Net_.json" new file mode 100644 index 00000000..eed9c0fe --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2021_.Net_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2021-09-02", + "metadataLastUpdated": "2021-10-16" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model \u00ae (2021 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2021 (v1.3.0.13857)" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2021_Excel_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2021_Excel_.json" new file mode 100644 index 00000000..fff0c11c --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2021_Excel_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2021-09-01", + "metadataLastUpdated": "2021-10-16" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model \u00ae (2021 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2021" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2022_.Net_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2022_.Net_.json" new file mode 100644 index 00000000..1057b8c7 --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2022_.Net_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2022-09-07", + "metadataLastUpdated": "2022-10-18" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model \u00ae (2022 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2022 (v1.3.0.13991)" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2022_Excel_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2022_Excel_.json" new file mode 100644 index 00000000..f1cf8bc7 --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2022_Excel_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2022-09-07", + "metadataLastUpdated": "2022-10-18" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet_excel_model.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model \u00ae (2022 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet_excel_model.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2022" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2023_.Net_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2023_.Net_.json" new file mode 100644 index 00000000..08624ecd --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2023_.Net_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2023-09-07", + "metadataLastUpdated": "2023-09-15" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model \u00ae (2023 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2023 (v1.3.0.14xxx)" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2023_Excel_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2023_Excel_.json" new file mode 100644 index 00000000..1361377b --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2023_Excel_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2023-09-07", + "metadataLastUpdated": "2023-09-15" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model \u00ae (2023 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2023" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2024_.Net_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2024_.Net_.json" new file mode 100644 index 00000000..40b8d71f --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2024_.Net_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2024-12-03", + "metadataLastUpdated": "2024-12-04" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model \u00ae (2024 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2024 (v1.3.0.14xxx)" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2024_Excel_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2024_Excel_.json" new file mode 100644 index 00000000..0e91772f --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Technologies_Model_\302\256__2024_Excel_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2024-12-03", + "metadataLastUpdated": "2024-12-04" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model \u00ae (2024 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2024" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2012_Excel_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2012_Excel_.json" new file mode 100644 index 00000000..96bbb3fa --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2012_Excel_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2012 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2012" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2013_.Net_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2013_.Net_.json" new file mode 100644 index 00000000..e3ae0e21 --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2013_.Net_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2013 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2013 (v1.1.0.9021)" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2013_Excel_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2013_Excel_.json" new file mode 100644 index 00000000..669cf228 --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2013_Excel_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2013 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2013" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2014_.Net_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2014_.Net_.json" new file mode 100644 index 00000000..2bed6792 --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2014_.Net_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2014 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2014 (v1.2.0.10728)" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2014_Excel_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2014_Excel_.json" new file mode 100644 index 00000000..cd64ee8d --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2014_Excel_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2014 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2014" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2015_.Net_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2015_.Net_.json" new file mode 100644 index 00000000..4f24d13b --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2015_.Net_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2015 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2015 (v1.3.0.12309)" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2015_Excel_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2015_Excel_.json" new file mode 100644 index 00000000..8eb16098 --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2015_Excel_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2015 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2015" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2016_.Net_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2016_.Net_.json" new file mode 100644 index 00000000..51bb1cd3 --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2016_.Net_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2016 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2016 (v1.3.0.13081)" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2016_Excel_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2016_Excel_.json" new file mode 100644 index 00000000..9ca31056 --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2016_Excel_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2016 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2016" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2017_.Net_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2017_.Net_.json" new file mode 100644 index 00000000..8492335d --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2017_.Net_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2017 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2017 (v1.3.0.13239)" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2017_Excel_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2017_Excel_.json" new file mode 100644 index 00000000..4482b3d6 --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2017_Excel_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2017 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2017" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2018_.Net_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2018_.Net_.json" new file mode 100644 index 00000000..34a57bff --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2018_.Net_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2018 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2018 (v1.3.0.13395)" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2018_Excel_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2018_Excel_.json" new file mode 100644 index 00000000..1cccccfd --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2018_Excel_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-08-03", + "metadataLastUpdated": "2020-08-03" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2018 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2018" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2019_.Net_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2019_.Net_.json" new file mode 100644 index 00000000..76899c34 --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2019_.Net_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-07-06", + "metadataLastUpdated": "2020-07-06" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2019 .Net)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/index.php?content=greetdotnet", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Net 2019 (v1.3.0.13520)" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2019_Excel_.json" "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2019_Excel_.json" new file mode 100644 index 00000000..9cf46be8 --- /dev/null +++ "b/agency-indexes/DoE/Greenhouse_gases,_Regulated_Emissions,_and_Energy_use_in_Transportation_Model_\302\256__2019_Excel_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zlu@anl.gov" + }, + "date": { + "created": "2020-07-06", + "metadataLastUpdated": "2020-07-06" + }, + "description": "To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. \n\nThe first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.", + "homepageURL": "https://greet.es.anl.gov/greet.models", + "laborHours": 0.0, + "languages": [ + "Microsoft Excel" + ], + "name": "Greenhouse gases, Regulated Emissions, and Energy use in Transportation Model \u00ae (2019 Excel)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://greet.es.anl.gov/copyright", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://greet.es.anl.gov/greet.models", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "version": "Excel 2019" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Greggd.json b/agency-indexes/DoE/Greggd.json new file mode 100644 index 00000000..2dfb886c --- /dev/null +++ b/agency-indexes/DoE/Greggd.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "vossjm@ornl.gov" + }, + "date": { + "created": "2020-08-07", + "metadataLastUpdated": "2020-09-08" + }, + "description": "greg(g)d - Global runtime for eBPF-enabled gathering (w/ gumption) daemon\n\nRecently the linux kernel has added support for low-level kernel monitoring and\nprofiling through a in-kernel virtual machine. The tooling around these new\nfeatures (the extended Berkley Packet Filter or eBPF for short) is not mature\nand is difficult to use. Benefits from eBPF are especially hard to realize\nwhile trying to do large scale deployments and integrate with existing metric\nanalysis stacks. A tool was needed to enable loading and collecting data from\neBPF programs on large scale HPC systems.\n\nGiven the problems above it was obvious we needed some wrapper program to\ncompile, load, and collect data from eBPF programs running in the kernel. This\ntool needed to be lightweight without a heavy set of dependencies, relatively\nstable between different kernel versions, and integrate nicely with existing\nwidely used metric collection tools.\n\nWe wrote a program that wraps the eBPF tooling and sends data to our metric\ngathering tool. eBPF programs are either compiled using the host compiler\nstack, or loaded in the kernel directly from an object file. These programs are\nthen attached to the system calls that we want to profile. Whenever these\nsystem calls are run, the eBPF program collects information of interest and\nwrites that to memory. Our wrapper program polls these memory locations, reads\nand formats the data, then sends the information to a local unix socket. Our\nother monitoring tools are configured to read from that socket and send it to\nthe rest of our metric monitoring stack for analysis.", + "laborHours": 1033.6, + "languages": [ + "Go" + ], + "name": "Greggd", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/greggd", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gremlin.json b/agency-indexes/DoE/Gremlin.json new file mode 100644 index 00000000..0ce78699 --- /dev/null +++ b/agency-indexes/DoE/Gremlin.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "colettima@ornl.gov" + }, + "date": { + "created": "2022-03-31", + "metadataLastUpdated": "2022-03-31" + }, + "description": "Gremlin is an evolutionary algorithm that discovers weaknesses in machine learning models.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Gremlin", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/markcoletti/gremlin", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v0.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gremlins.json b/agency-indexes/DoE/Gremlins.json new file mode 100644 index 00000000..d878cbdc --- /dev/null +++ b/agency-indexes/DoE/Gremlins.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "Flexible and extensible framework to emulate expected exascale architecture characteristics.\n", + "laborHours": 6232.0, + "languages": [], + "name": "Gremlins", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Gremlins", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Grid-Integrated_Electric_Mobility_Model__GEM__v1.0.json b/agency-indexes/DoE/Grid-Integrated_Electric_Mobility_Model__GEM__v1.0.json new file mode 100644 index 00000000..7cd0e35b --- /dev/null +++ b/agency-indexes/DoE/Grid-Integrated_Electric_Mobility_Model__GEM__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-02-17", + "metadataLastUpdated": "2021-02-17" + }, + "description": "\tTransportation is the fastest-growing source of greenhouse gas (GHG) emissions and energy consumption globally. The convergence of shared mobility, vehicle automation, and electrification has the potential to drastically reduce transportation impacts, but requires careful integration with rapidly evolving electricity systems. We have developed the GEM Model (Grid-Integrated Electric Mobility) to examine these interactions with a U.S.-wide simulation framework encompassing private electric vehicles (EVs); shared automated EVs (SAEVs); charging infrastructure; controlled EV charging; and a grid economic dispatch model to simulate mobility futures exclusively using EVs. We find that an SAEV fleet 9% the size of today's active vehicles can satisfy trip demand with only 2.6 million chargers (0.2 per EV). Controlled EV charging can also reduce electricity demand variability, significantly reducing GHG emissions and decreasing solar curtailment by about one-third. While private EVs with uncontrolled charging would reduce GHG emissions by 53% compared to gasoline vehicles, SAEVs could achieve a 70% reduction.", + "laborHours": 0.0, + "languages": [], + "name": "Grid-Integrated Electric Mobility Model (GEM) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-UCB-STI/gem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GridDS:_Data_Science_Toolkit_for_Energy_Grid_Data.json b/agency-indexes/DoE/GridDS:_Data_Science_Toolkit_for_Energy_Grid_Data.json new file mode 100644 index 00000000..2fe7fba1 --- /dev/null +++ b/agency-indexes/DoE/GridDS:_Data_Science_Toolkit_for_Energy_Grid_Data.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-07-05", + "metadataLastUpdated": "2022-11-04" + }, + "description": "According to the U.S. Energy Information Administration (EIA), the demand for energy is expected to increase 50% by the year 20501. While energy standards, such as the Institute of Electrical and Electronics Engineers (IEEE) Standard 1547, (Basso 2015) and monitoring with wide area management systems (WAMS) (Liu 2017, Zhou 2016) have enabled large scale data collection and storage, the application of this data in mitigating costs associated with increased consumer demand is an ongoing focus for energy research. This ubiquitous data collection presents a promising opportunity for machine learning and data science to improve efficiency of distributed energy resources (DERs). The GridDS software toolkit is designed to leverage advanced metering infrastructure (AMI), outage management systems data (OMS), Supervisory control Data Acquisition (SCADA), and geographic information systems (GIS) to forecast future energy demands and detect incipient grid failures. GridDS is a python software library designed to be modular and generalizable to data recorded by DERs. In adapting to disparate datasets recorded by various WAMS, GridDS provides a range of unique functionality not presently implemented in current WAMS which have highly specific software infrastructure by design. GridDS functionality ranges from data specification and preparation, to training and validation for state of the art machine learning, to interactive data visualization. For data intake, GridDS combines: Pandera: a library for creating data specifications. TimeScaleDB: a postgresSQL database infrastructure for efficient storage of timeseries data. Dataset class: A custom dataset class / interface that ensures modularity between a range of synthetic and live recorded datasets. Is", + "laborHours": 0.0, + "languages": [], + "name": "GridDS: Data Science Toolkit for Energy Grid Data", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/gridds", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GridKit.json b/agency-indexes/DoE/GridKit.json new file mode 100644 index 00000000..909f6df5 --- /dev/null +++ b/agency-indexes/DoE/GridKit.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "peless@ornl.gov" + }, + "date": { + "created": "2025-03-10", + "metadataLastUpdated": "2025-03-10" + }, + "description": "Modeling framework for power systems simulations and analysis.", + "laborHours": 10320.8, + "languages": [ + "C++" + ], + "name": "GridKit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/GridKit", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GridLAB-D_SG.json b/agency-indexes/DoE/GridLAB-D_SG.json new file mode 100644 index 00000000..6717eff2 --- /dev/null +++ b/agency-indexes/DoE/GridLAB-D_SG.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "GridLAB-D is a new power system simulation tool that provides valuable information to users who design and operate electric power transmission and distribution systems, and to utilities that wish to take advantage of the latest smart grid technology. This special release of GridLAB-D was developed to study the proposed Smart Grid technology that is used by Battelle Memorial Institute in the AEP gridSMART demonstration project in Northeast Columbus, Ohio.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C, C++, Java" + ], + "name": "GridLAB-D/SG", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GridLab-D.json b/agency-indexes/DoE/GridLab-D.json new file mode 100644 index 00000000..db8ab8f6 --- /dev/null +++ b/agency-indexes/DoE/GridLab-D.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A power system simulation that runs on all major platforms, provides open access to all functionality, and supports extended modeling of non-traditional components of the electric power system, such as buildings, distributed resources, and markets.", + "laborHours": 252776.0, + "name": "GridLab-D", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/gridlab-d/gridlab-d/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gridlab-d/gridlab-d", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GridLab-D_version_1.0.json b/agency-indexes/DoE/GridLab-D_version_1.0.json new file mode 100644 index 00000000..3301b90b --- /dev/null +++ b/agency-indexes/DoE/GridLab-D_version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A power system simulation that runs on all major platforms, provides open access to all functionality, and supports extended modeling of non-traditional components of the electric power system, such as buildings, distributed resources, and markets. GridLAB-D solution engine can determine the simultaneous state of millions of independent devices, each of which is described by multiple differential equations solved only locally for both state and time. The advantages of this algorithm over traditional finite difference-based simulators are: (1) it is much more accurate; (2) it can handle widely disparate time scales, ranging from sub-seconds to many years; and 3) it is easy to integrate with new modules and third-party systems. The advantage over traditional differential-based solvers is that it is not necessary to integrate all the device's behaviors into a single set of equations that must be solved.", + "laborHours": 252776.0, + "name": "GridLab-D version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/gridlab-d/gridlab-d/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gridlab-d/gridlab-d", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GridOPTICS_GridPACK.json b/agency-indexes/DoE/GridOPTICS_GridPACK.json new file mode 100644 index 00000000..cd02ccf0 --- /dev/null +++ b/agency-indexes/DoE/GridOPTICS_GridPACK.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "GridPACK is a software framework consisting of a set of modules designed to simplify the development of programs that model the power grid and run on parallel, high performance computing platforms. It also contains several fully developed applications, including powerflow, dynamic simulation, state estimation, Kalman filter analysis (dynamic state estimation), contingency analysis and real time path rating. These applications can be used either standalone or as components in more complicated workflows that combine several different types of application together. The framework modules are available as a combination of libraries and software templates and consist of components for setting up and distributing power grid networks, support for modeling the behavior of individual buses and branches in the network, converting the network models to the corresponding algebraic equations, and parallel routines for manipulating and solving large algebraic systems. The framework also contains a module for distributing tasks evenly amongst computing resources, even if individual tasks vary widely in their execution times. Additional modules support input and output, basic statistical analysis of contingency based calculations, distributed data structures, as well as basic profiling and error management.", + "laborHours": 217861.6, + "languages": [], + "name": "GridOPTICS/GridPACK", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GridOPTICS/GridPACK", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GridOPTICS_Software_System.json b/agency-indexes/DoE/GridOPTICS_Software_System.json new file mode 100644 index 00000000..b6042d23 --- /dev/null +++ b/agency-indexes/DoE/GridOPTICS_Software_System.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GridOPTICS Software System (GOSS) is a middleware that facilitates creation of new, modular and flexible operational and planning platforms that can meet the challenges of the next generation power grid. GOSS enables Department of Energy, power system utilities, and vendors to build better tools faster. GOSS makes it possible to integrate Future Power Grid Initiative software products/prototypes into existing power grid software systems, including the PNNL PowerNet and EIOC environments. GOSS is designed to allow power grid applications developed for different underlying software platforms installed in different utilities to communicate with ease. This can be done in compliance with existing security and data sharing policies between the utilities. GOSS not only supports one-to-one data transfer between applications, but also publisher/subscriber scheme. To support interoperability requirements of future EMS, GOSS is designed for CIM compliance. In addition to this, it supports authentication and authorization capabilities to protect the system from cyber threats. In summary, the contributions of the GOSS middleware are as follows: A platform to support future EMS development. A middleware that promotes interoperability between power grid applications. A distributed architecture that separates data sources from power grid applications. Support for data exchange with either one-to-one or publisher/subscriber interfaces. An authentication and authorization scheme for limiting the access to data between utilities.", + "laborHours": 27724.8, + "name": "GridOPTICS Software System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/craig8/GOSS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GridPV_Toolbox.json b/agency-indexes/DoE/GridPV_Toolbox.json new file mode 100644 index 00000000..ff4bef0f --- /dev/null +++ b/agency-indexes/DoE/GridPV_Toolbox.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "Matlab Toolbox for simulating the impact of solar energy on the distribution grid. The majority of the functions are useful for interfacing OpenDSS and MATLAB, and they are of generic use for commanding OpenDSS from MATLAB and retrieving GridPV Toolbox information from simulations. A set of functions is also included for modeling PV plant output and setting up the PV plant in the OpenDSS simulation. The toolbox contains functions for modeling the OpenDSS distribution feeder on satellite images with GPS coordinates. Finally, example simulations functions are included to show potential uses of the toolbox functions.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "OpenDSS" + ], + "name": "GridPV Toolbox", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gridpv", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GridSTAGE__aka_PowerDrone_.json b/agency-indexes/DoE/GridSTAGE__aka_PowerDrone_.json new file mode 100644 index 00000000..264f99c4 --- /dev/null +++ b/agency-indexes/DoE/GridSTAGE__aka_PowerDrone_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Simulation tool for electrical grid security. It is possible to select from pre-loaded power system topologies, enable different grid controls\n(like AGC, power system stabilizer), add faults, tweak different parameters, add pre-modeled attack scenarios, and run\nbatch simulations to generate data needed for research.", + "laborHours": 0.0, + "languages": [], + "name": "GridSTAGE (aka PowerDrone)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/GridSTAGE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GridSweep_Processing_and_Graphing_Software_v1.0.json b/agency-indexes/DoE/GridSweep_Processing_and_Graphing_Software_v1.0.json new file mode 100644 index 00000000..15fc9c96 --- /dev/null +++ b/agency-indexes/DoE/GridSweep_Processing_and_Graphing_Software_v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-09-28", + "metadataLastUpdated": "2023-09-28" + }, + "description": "This software is used to process the raw data from the GridSweep instrument, a device developed under subcontract by McEachern Laboroatories for a DOE GMLC project. The software scrubbs, demodulates, and transforms point on wave voltage timeseries data into frequency/voltage amplitude/time data. It also has a GUI that allows for user selection of processed experimental data and graphing in heatmaps or 3-D plots. It was created alongside the GridSweep instrument as a part of the same project and is required to be open-source.", + "laborHours": 0.0, + "languages": [], + "name": "GridSweep Processing and Graphing Software v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/jsmacdonald/gridsweep-processing/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/GridTrust.json b/agency-indexes/DoE/GridTrust.json new file mode 100644 index 00000000..65c6d2c3 --- /dev/null +++ b/agency-indexes/DoE/GridTrust.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "khutto30@gatech.edu" + }, + "date": { + "created": "2023-09-29", + "metadataLastUpdated": "2023-09-29" + }, + "description": "Hardware/software co-designed systems are increasingly prevalent due to trends such as the adoption of hardware accelerators and the availability of heterogeneous system-on-chip (SoC) architectures. A potential security concern arising from hardware/software interaction in heterogeneous computing architectures is the possibility of software-based attacks on reconfigurable hardware, and vice versa. This is especially important when considering remote updates of the software, hardware, or both combined. In this work, we have created a remote update scheme that relies on a physical unclonable function (PUF) and multiple updating parties to deliver hardware/software updates in a secure fashion. The scheme, GridTrust, provides a high level of assurance that the system only accepts updates from approved entities while also preventing common remote attacks from compromising the security of the update process. As shown above, an attacker has multiple opportunities to attack. GridTrust\u2019s protection features help to prevent any single attack from the locations shown in Figure 1 from succeeding.\n\nThe GridTrust scheme follows a few key tenets; (1) the usage of auditable open-source software, (2) software update authorization via two distinct entities, (3) and device authentication via a hardware fingerprinting technique known as a PUF. Used together, these techniques harden cybersecurity defenses in the electric grid supply chain against both a third-party actor and a malicious lone-wolf insider.", + "laborHours": 0.0, + "languages": [ + "Rust" + ], + "name": "GridTrust", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/huttokd/GridTrust", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Grid_Modeling_and_Hosting_Capacity_Analysis.json b/agency-indexes/DoE/Grid_Modeling_and_Hosting_Capacity_Analysis.json new file mode 100644 index 00000000..a4d59d14 --- /dev/null +++ b/agency-indexes/DoE/Grid_Modeling_and_Hosting_Capacity_Analysis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An interface with the OpenDSS distribution grid simulator, facilitating users in\ncalibrating and validating models. Additionally, three distinct tools have been developed:\nPV Hosting Capacity: This tool allows users to determine the additional amount of photovoltaic (PV) generation that can be\nintegrated into the system without breaching operational constraints.\nEV Hosting Capacity: This tool focuses on identifying the capacity for incorporating extra electric vehicle (EV) load into the\nsystem without surpassing operational limitations.\nProject Impact Analysis Tool: This tool is designed to assess and report all potential grid violations associated with a\nspecific project, providing valuable insights into its impact on the distribution grid.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Grid Modeling and Hosting Capacity Analysis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Grid_Optimization_Lawrence_Livermore_Nonlinear_Programming.json b/agency-indexes/DoE/Grid_Optimization_Lawrence_Livermore_Nonlinear_Programming.json new file mode 100644 index 00000000..ebf64aa8 --- /dev/null +++ b/agency-indexes/DoE/Grid_Optimization_Lawrence_Livermore_Nonlinear_Programming.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "Modelling and solution library for security-constrained AC optimal power flow problems that uses nonlinear programming methods (interior-point methods) and solvers (Ipopt, HiOp). The code is written in C++ and provides parallel computing capabilities in the form of task parallelism (solving contingency problems in parallel). Code can run on a variety of commodity high-performance computing.", + "laborHours": 11886.4, + "languages": [], + "name": "Grid Optimization Lawrence Livermore Nonlinear Programming", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gollnlp/gollnlp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Grid_Optimization__GO__Competition_Platform.json b/agency-indexes/DoE/Grid_Optimization__GO__Competition_Platform.json new file mode 100644 index 00000000..e57ad8ae --- /dev/null +++ b/agency-indexes/DoE/Grid_Optimization__GO__Competition_Platform.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A software for a multi-challenge power-flow grid optimization competition was developed. The platform brings together high performance computing clusters, webservers, databases, competition datasets, schedulers, evaluation codes, and a multitude of language compilers and optimization solvers to host the competition. The original video announcing the competition, from former Secretary Perry, at: https://www.youtube.com/watch?v=hZwX3P9vS8M", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Grid Optimization (GO) Competition Platform", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Grid_Reliability_Statistics_[SWR-25-45].json b/agency-indexes/DoE/Grid_Reliability_Statistics_[SWR-25-45].json new file mode 100644 index 00000000..57e07676 --- /dev/null +++ b/agency-indexes/DoE/Grid_Reliability_Statistics_[SWR-25-45].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-03", + "metadataLastUpdated": "2025-04-03" + }, + "description": "This codebase houses a suite of statistical and descriptive analyses of NERC GADS data of interest to grid modelers and planners. This repository is envisioned to house a collection of statistical and descriptive summaries of NERC GADS data, particularly summaries that on their own might be insufficient to warrant publication. In addition, it is intended to disseminate results rather than to enable reproduction as GADS is non-public.", + "laborHours": 15.2, + "languages": [ + "Jupyter Notebook" + ], + "name": "Grid Reliability Statistics [SWR-25-45]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/grid-reliability-statistics", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Grid_Research_for_Good_Software_Tools.json b/agency-indexes/DoE/Grid_Research_for_Good_Software_Tools.json new file mode 100644 index 00000000..93a9c728 --- /dev/null +++ b/agency-indexes/DoE/Grid_Research_for_Good_Software_Tools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-10-28", + "metadataLastUpdated": "2021-10-28" + }, + "description": "The Grid Research for Good Software Tools includes a variety of software packages for working with electric power systems data. It includes: parsers for Matpower, PSS/E, and GRG data files; translators between these formats; and validation routines for network structure and component parameters.", + "laborHours": 0.0, + "languages": [], + "name": "Grid Research for Good Software Tools", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/grg-grgdata", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Grid_Services_Load_Shift_Baseline_Degradation_Analysis_Methodology_v1.json b/agency-indexes/DoE/Grid_Services_Load_Shift_Baseline_Degradation_Analysis_Methodology_v1.json new file mode 100644 index 00000000..fe381fae --- /dev/null +++ b/agency-indexes/DoE/Grid_Services_Load_Shift_Baseline_Degradation_Analysis_Methodology_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-18", + "metadataLastUpdated": "2024-07-18" + }, + "description": "As demand flexibility becomes more common, the mix and frequency of a range of demand flexibility strategies will introduce potential biases into baselines, i.e., the time period immediately prior to a LS event may include other LS or DF events. Baseline degradation assessment provides an approach to quantify how these biases begin to compromise predictive accuracy. Heatmaps, based on each month of the year provides a granular view of a given model's predictive capability. However, for comparing multiple algorithms, separately for weekdays and weekends, aggregating results to seasons provides a simpler means of comparison while still allowing for review of variations by time of day and time of year", + "laborHours": 1398.4, + "languages": [], + "name": "Grid Services Load Shift Baseline Degradation Analysis Methodology v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sgfernandes/Loadshift", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Grid_State_Estimation_Tool.json b/agency-indexes/DoE/Grid_State_Estimation_Tool.json new file mode 100644 index 00000000..ebfad97d --- /dev/null +++ b/agency-indexes/DoE/Grid_State_Estimation_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "This software code is designed to track generator state variables in real time using the Ensemble Kalman Filter method with the aid of PMU measurements. This code can also be used to calibrate dynamic model parameters by augmenting parameters in the state variable vector.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab" + ], + "name": "Grid State Estimation Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gridder,_Version_3.json b/agency-indexes/DoE/Gridder,_Version_3.json new file mode 100644 index 00000000..67d85828 --- /dev/null +++ b/agency-indexes/DoE/Gridder,_Version_3.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "GRIDDER is a simple interactive grid generation tool for creating orthogonal, 2D quadrilateral or 3D hexahedral grids. Grid spacing can be even, logarithmic, or geometric. Gridder creates orthogonal one-dimensional, two-dimensional, or three- dimensional grids. Each dimension can have multiple regions, each with different nodal spacing. This spacing can be equal spacing, geometric spacing, or logarithmic spacing. The resulting grid can be output in AVS (Advanced Visualization Systems) format, Tracer 30, Vectors, or FEHM format. Coordinate and connectivity data are output for AVS, but only coordinate data is output for Tracer30. As it runs, Gridder prompts the user for input such as number of dimensions, number of regions in each dimension, coordinates of region borders, number of divisions in each region, spacing specifications of each region, and output format. The Gridder can also accept the necessary information from a file, bypassing the interactive interface. Every time the interactive interface is used, the input parameters are saved to a file so that the same grid can be regenerated from that file.", + "laborHours": 0.0, + "languages": [ + "c", + "gcc version 4.8.2" + ], + "name": "Gridder, Version 3", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/gridder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Grope_Ver._1.38.json b/agency-indexes/DoE/Grope_Ver._1.38.json new file mode 100644 index 00000000..4a68329f --- /dev/null +++ b/agency-indexes/DoE/Grope_Ver._1.38.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GROPE is a program that examines the input to a finite element analysis (which is in the GENESIS database format) or the output from an analysis (in the EXODUS database format). GROPE allows the user to examine any value in the database. The display can be directed to the user's terminal or to a print file.", + "laborHours": 3063438.4, + "languages": [ + "CSS", + "HTML", + "TeX", + "Makefile", + "JavaScript", + "PostScript" + ], + "name": "Grope Ver. 1.38", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas-docs", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.38" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ground_Water_Age_Predictor.json b/agency-indexes/DoE/Ground_Water_Age_Predictor.json new file mode 100644 index 00000000..f574cca0 --- /dev/null +++ b/agency-indexes/DoE/Ground_Water_Age_Predictor.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-05-28", + "metadataLastUpdated": "2024-05-28" + }, + "description": "Machine Learning script to predict groundwater ages based on auxiliary features in a publicly available\ndataset, based on publicly available software libraries. Code applied to data from the Groundwater\nAmbient Monitoring and Assessment (GAMA) program in California, including well location and\nconstruction information, chemical constituents and isotopic tracers, and land use metrics.", + "laborHours": 577.6, + "languages": [], + "name": "Ground Water Age Predictor", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/GWAP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GroupAPI.json b/agency-indexes/DoE/GroupAPI.json new file mode 100644 index 00000000..3a28e6a2 --- /dev/null +++ b/agency-indexes/DoE/GroupAPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "This is the repository for \"GroupAPI\" developed by KBase. ", + "laborHours": 942.4, + "languages": [], + "name": "GroupAPI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/GroupAPI", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GroupTheoretical.json b/agency-indexes/DoE/GroupTheoretical.json new file mode 100644 index 00000000..5b44141e --- /dev/null +++ b/agency-indexes/DoE/GroupTheoretical.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "GAP codes for computing (pre)modular data from finite groups.", + "laborHours": 167.2, + "languages": [], + "name": "GroupTheoretical", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/GroupTheoretical", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/GrumPHP_Editor_Config.json b/agency-indexes/DoE/GrumPHP_Editor_Config.json new file mode 100644 index 00000000..f88c1b73 --- /dev/null +++ b/agency-indexes/DoE/GrumPHP_Editor_Config.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Use GrumPHP to ensure your files conform to the standards setup in your projects .editorconfig file. This plugin allows your Git pre-commit hooks to check your files for the proper file standards and reject a commit if any of your files don't conform.", + "laborHours": 136.8, + "languages": [], + "name": "GrumPHP Editor Config", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/editorconfig", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Guideline_36_Savings_Calculator_v0.1.json b/agency-indexes/DoE/Guideline_36_Savings_Calculator_v0.1.json new file mode 100644 index 00000000..9dbf3f39 --- /dev/null +++ b/agency-indexes/DoE/Guideline_36_Savings_Calculator_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-10", + "metadataLastUpdated": "2021-06-11" + }, + "description": "This software package contains a simple calculator that can be used to estimate savings from implementing a retrofit of HVAC controls to ASHRAE Guideline 36 in a multi-zone office building. Implemented in Excel, the calculator has a user-interface front-end to configure parameters of the case study, such as location, building size, and existing control strategies, and a back-end containing results from a large number of pre-run annual energy simulations. The software package also contains the simulation models and associated pre- and post-processing scripts to generate these results.", + "laborHours": 0.0, + "languages": [], + "name": "Guideline 36 Savings Calculator v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/G36SavingsCalculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gulliver.json b/agency-indexes/DoE/Gulliver.json new file mode 100644 index 00000000..36435d9d --- /dev/null +++ b/agency-indexes/DoE/Gulliver.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2020-11-11" + }, + "description": "Gulliver is a C# utility package and library engineered for the manipulation of arbitrary sized byte arrays accounting for appropriate endianness and jagged byte length. Functionality includes the as previously unsupported standard set of boolean algebraic operations, bitwise shifting, and unsigned endian aware mathematical addition, subtraction, and comparison. Gulliver exists to free developers from managing byte ordering and operations and the low level as was previously required by the standard C# language distributions.SAND2019-8990 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.\n", + "laborHours": 3724.0, + "languages": [ + "C++" + ], + "name": "Gulliver", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Gulliver", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Gyrokinetic_Tokamak_Simulation_code__GTS_.json b/agency-indexes/DoE/Gyrokinetic_Tokamak_Simulation_code__GTS_.json new file mode 100644 index 00000000..7ec031ad --- /dev/null +++ b/agency-indexes/DoE/Gyrokinetic_Tokamak_Simulation_code__GTS_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "ethier@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2018-07-26" + }, + "description": "Global, gyrokinetic PIC code in full general geometry used for studying core microturbulent transport in experimental tokamaks.", + "homepageURL": "https://theory.pppl.gov/research/research.php?rid=10#h47", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Gyrokinetic Tokamak Simulation code (GTS)", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://theorycodes.pppl.wikispaces.net/file/detail/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://theory.pppl.gov/research/research.php?rid=10#h47", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/H2FAST:_Hydrogen_Financial_Analysis_Scenario_Tool_[SWR_15-06].json b/agency-indexes/DoE/H2FAST:_Hydrogen_Financial_Analysis_Scenario_Tool_[SWR_15-06].json new file mode 100644 index 00000000..f140bfae --- /dev/null +++ b/agency-indexes/DoE/H2FAST:_Hydrogen_Financial_Analysis_Scenario_Tool_[SWR_15-06].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-05-11", + "metadataLastUpdated": "2023-05-22" + }, + "description": "The Hydrogen Financial Analysis Scenario Tool, H2FAST, provides a quick and convenient in-depth financial analysis for hydrogen and nonhydrogen systems and services.\n\nH2FAST is available as a downloadable Excel spreadsheet. The model uses a generally accepted accounting principles analysis framework and provides annual projections of income statements, cash flow statements, and balance sheets. H2FAST allows users to generate a side-by-side scenario analysis, where a base system can be tested by varying key operating or financing parameters. Detailed capital structure, taxation, and incentives are included. The model has built-in risk analysis allowing impact assessment of parameters bearing user-specified uncertainty ranges. Financial articulation is presented in graphical and tabular format for the user-specified analysis period. The model is self-documented, with embedded help functions and annotation of input parameters.\n\nNote: The model is also flexible for providing analysis for International Financial Reporting Standards by adjusting inputs for compliance with their rules.\n\nThe H2FAST framework has been used for analysis of a variety of systems, e.g., retail hydrogen refueling stations with incentives analysis, ammonia production, methane pyrolysis, seasonal energy storage, hydrogen fleet operations, electric vehicle charging with time of use rate structures, combined heat and power systems, hydrogen production pathways, and hydrogen transmission and distribution. The example cases available for download are intended to demonstrate model functionality and should be populated with user-specific analysis values such as CapEx, OpEx, and capital structure.", + "homepageURL": "https://www.nrel.gov/hydrogen/h2fast.html", + "laborHours": 0.0, + "languages": [ + "Excel" + ], + "name": "H2FAST: Hydrogen Financial Analysis Scenario Tool [SWR 15-06]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/hydrogen/assets/pdfs/h2fast_spreadsheet_user_manual.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/hydrogen/h2fast.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/H2Fills\342\204\242.json" "b/agency-indexes/DoE/H2Fills\342\204\242.json" new file mode 100644 index 00000000..ccf7ed57 --- /dev/null +++ "b/agency-indexes/DoE/H2Fills\342\204\242.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-02-24", + "metadataLastUpdated": "2021-02-24" + }, + "description": "H2FillS: Hydrogen Filling Simulation\nThe Hydrogen Filling Simulation (H2FillS) software is a thermodynamic model designed to track and report on the transient change in hydrogen temperature, pressure, and mass flow when filling a fuel cell electric vehicle (FCEV).\n\nH2FillS simulates gas flow from the hydrogen station to the FCEV storage system. Using empirical fueling data sets, the model has been validated over a range of fueling conditions to match common light-duty FCEV fill profiles. Overall, it provides significant benefits to the light-duty fueling market and fill knowledge gaps of the interaction between a hydrogen station and an FCEV.\n\nCapabilities\nUse the comprehensive H2FillS model to:\n\nSafely design and operate a hydrogen fueling station\nSupport code refinement with readily available data\nDevelop system and operational improvements to reduce capital or operating costs at hydrogen stations or on-board FCEVs.\nHow It Works\nH2FillS uses a \"drag-and-drop\" graphical user interface to simulate station and vehicle systems with preset parameters for common hydrogen station components as default values. When needed, users can define their own parameters to create their own station or vehicle components.\n\nDownload H2FillS in Two Steps\nRead the terms of the end user software license agreement.\nRegister to download the software.\nThere are two versions of the model:\n\nA full-station model starts the simulation at high-pressure ground storage, runs through a dispenser, and ends at a vehicle storage system.\nA partial-station model starts at the dispenser breakaway and consists solely of the dispenser components and the vehicle storage system.\nH2FillS will automatically output fill performance data from the vehicle by tracking pressure and temperature throughout the fill. Users can input their own fill profiles into the model to run a variety of simulations.", + "homepageURL": "https://www.nrel.gov/hydrogen/h2fills.html", + "laborHours": 0.0, + "languages": [], + "name": "H2Fills\u2122", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrel.gov/hydrogen/h2fills-agreement-registration.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrel.gov/hydrogen/h2fills.html", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/H2OI95:_A_Stand-Alone_Fortran_Code_for_Evaluating_the_IAPWS-95_Equation-of-State_Model_for_Water.json b/agency-indexes/DoE/H2OI95:_A_Stand-Alone_Fortran_Code_for_Evaluating_the_IAPWS-95_Equation-of-State_Model_for_Water.json new file mode 100644 index 00000000..db9b872a --- /dev/null +++ b/agency-indexes/DoE/H2OI95:_A_Stand-Alone_Fortran_Code_for_Evaluating_the_IAPWS-95_Equation-of-State_Model_for_Water.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-08", + "metadataLastUpdated": "2019-04-08" + }, + "description": "H2OI95 is a stand-alone Fortran code for evaluating the IAPWS-95 equation-of-state model (Wagner and Pruss, 2002) for the thermodynamic properties of water. It further evaluates the corresponding thermochemical properties of water consistent with the CODATA recommendations (Cox et al., 1989). The IAPWS-95 model is based on a model equation for the dimensionless Helmholtz energy for which the primary variables are the inverse reduced temperature and reduced density. Here is the absolute temperature (K), is density (kg/m3), and the subscript refers to the critical point of water (647.096 K and 22.064 MPa pressure in this model, for which is 322 kg/m3). The code solves four basic types of problems, distinguished by the specified inputs: \n1, Temperature (K) and density (kg/m3) or reduced density\n2. Temperature (K) and pressure (MPa). \n3. Temperature (K) on the saturation (liquid-vapor equilibrium) curve \n4. Pressure (MPa) on the saturation curve\nEach type of problem is run using a corresponding input (text) file. All but the first type of problem require iteration. For example, to solve for desired temperature and pressure, the reduced density must be adjusted to give the desired pressure. Iteration is accomplished using the Newton-Raphson method, though the secant method is also used in solving the fourth type of problem. H2OI95 has been used to conduct numerical studies of convergence and the problem of multiple numerical solutions, only some of which correspond to valid results. Obtaining valid results depends mainly on appropriate choice of starting values. The default values in H2OI95 appear to consistently lead to generally desired results. With modification (not addressed here), H2OI95 can be used to support SUPCRT92 (Johnson et al., 1992) and similar codes that compute chemical thermodynamic properties of species and reactions over a wide range of temperature and pressure (273.16-1273K and 0-1000 MPa).\n", + "laborHours": 15.2, + "languages": [], + "name": "H2OI95: A Stand-Alone Fortran Code for Evaluating the IAPWS-95 Equation-of-State Model for Water", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/H2OI95", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/H3D_Data_Acquisition_Software__H3DDAQ__v1.0.json b/agency-indexes/DoE/H3D_Data_Acquisition_Software__H3DDAQ__v1.0.json new file mode 100644 index 00000000..cbe13de0 --- /dev/null +++ b/agency-indexes/DoE/H3D_Data_Acquisition_Software__H3DDAQ__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-11-03", + "metadataLastUpdated": "2024-11-03" + }, + "description": "A python library to enable readout of data from commercial H3D gamma-ray detectors. This software perform readout of data and system status, as well as starting and stopping measurements, with either WebREST (HTTP), XML (N42.42), or Binary (FlatBuffers) interfaces.", + "laborHours": 1550.4, + "languages": [], + "name": "H3D Data Acquisition Software (H3DDAQ) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/lbl-anp/h3d_tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/H5TurboPFor_v0.0.1.json b/agency-indexes/DoE/H5TurboPFor_v0.0.1.json new file mode 100644 index 00000000..f10fe7c7 --- /dev/null +++ b/agency-indexes/DoE/H5TurboPFor_v0.0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-17" + }, + "description": "H5TurboPFor is a wrapper for the TurboPFor-Integer-Compression for HDF5 library. Basically, it enables the HDF5 library to compress integer data using the TurboPFor.", + "laborHours": 0.0, + "languages": [], + "name": "H5TurboPFor v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/berkeleysdm/H5TurboPFor.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/H5Z-ZFP.json b/agency-indexes/DoE/H5Z-ZFP.json new file mode 100644 index 00000000..8dced9ab --- /dev/null +++ b/agency-indexes/DoE/H5Z-ZFP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "A highly flexible floating point and integer compression plugin for the HDF5 library using ZFP compression.\n", + "laborHours": 1504.8, + "languages": [], + "name": "H5Z-ZFP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/H5Z-ZFP", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/H5bench:_a_benchmark_suite_for_parallel_HDF5__H5bench__v0.1.json b/agency-indexes/DoE/H5bench:_a_benchmark_suite_for_parallel_HDF5__H5bench__v0.1.json new file mode 100644 index 00000000..641e532c --- /dev/null +++ b/agency-indexes/DoE/H5bench:_a_benchmark_suite_for_parallel_HDF5__H5bench__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-21", + "metadataLastUpdated": "2021-04-21" + }, + "description": "H5bench benchmark suite contains a list of applications that are used to measure the HDF5 I/O performance from various aspects.", + "laborHours": 0.0, + "languages": [], + "name": "H5bench: a benchmark suite for parallel HDF5 (H5bench) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/h5bench", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/H5bench:_a_benchmark_suite_for_parallel_HDF5__H5bench__v0.6.json b/agency-indexes/DoE/H5bench:_a_benchmark_suite_for_parallel_HDF5__H5bench__v0.6.json new file mode 100644 index 00000000..383fbc6f --- /dev/null +++ b/agency-indexes/DoE/H5bench:_a_benchmark_suite_for_parallel_HDF5__H5bench__v0.6.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2021-06-24" + }, + "description": "H5bench benchmark suite contains a list of applications that are used to measure the HDF5 I/O performance from various aspects.", + "laborHours": 0.0, + "languages": [], + "name": "H5bench: a benchmark suite for parallel HDF5 (H5bench) v0.6", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/h5bench", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HAERO:_High-performance_aerosols.json b/agency-indexes/DoE/HAERO:_High-performance_aerosols.json new file mode 100644 index 00000000..961a1385 --- /dev/null +++ b/agency-indexes/DoE/HAERO:_High-performance_aerosols.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-09", + "metadataLastUpdated": "2023-02-21" + }, + "description": "SAND2021-15059 O Haero is a software library for representing aerosol size distributions, chemical species, and parameterized processes to use with a coupled atmospheric dynamics model or as a standalone tool. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1450475.2, + "languages": [ + "C++", + "Fortran" + ], + "name": "HAERO: High-performance aerosols", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/E3SM", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HALA:_Handy_Accelerated_Linear_Algebra.json b/agency-indexes/DoE/HALA:_Handy_Accelerated_Linear_Algebra.json new file mode 100644 index 00000000..6959e3d2 --- /dev/null +++ b/agency-indexes/DoE/HALA:_Handy_Accelerated_Linear_Algebra.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Accelerated linear algebra libraries often come with C-style of interfaces or even older Fortran77 standards, which makes it difficult to use within generic template programming environment of modern C++. For example, the BLAS and derived standards such as cuBLAS do not accept overloads and a different functions have to be called for each input type, thus it is very challenging to write a single template that handles multiple precision modes and works well with different C++ containers. HALA offers a series of templates that wrap around the BLAS/cuBLAS and other similar methods, automatically infer the relevant types and call the appropriate back-end. The templates work out-of-the-box with all C++ standard vector-like containers and can be easily extended (with template specializations) to handle user-provided containers. The HALA API is also overloaded to handle both GPU and CPU cases with a single \"engine\" class, thus a single high-level algorithms can utilize both CPU or GPU backends, i.e., the HALA API is unified and handles the variations between cuBLAS and BLAS. In addition to BLAS and cuBLAS, wrapper templates are provided for subset of LAPACK, cuSparse, and Cholmod methods. Work is in progress to complete as many of these standards as possible. HALA also includes a module for low-level extended register vectorization for complex number arithmetic and several simple solvers that build on the basic linear algebra capabilities. A single unified C++ API will benefit fast prototyping and easily writing code that is portable across GPU/CPU platforms as well as precision types and user containers. Note that HALA does not provide any accelerated algorithms, it simply serves as a \"handy\" front-end to other standards.", + "laborHours": 0.0, + "languages": [ + "C++ (gcc6 and 7 or clang 5 and 6)" + ], + "name": "HALA: Handy Accelerated Linear Algebra", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LIBHALA/hala", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HALOS__Heliostat_Aimpoint_and_Layout_Optimization_Software_.json b/agency-indexes/DoE/HALOS__Heliostat_Aimpoint_and_Layout_Optimization_Software_.json new file mode 100644 index 00000000..1e5f9429 --- /dev/null +++ b/agency-indexes/DoE/HALOS__Heliostat_Aimpoint_and_Layout_Optimization_Software_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-15", + "metadataLastUpdated": "2021-06-16" + }, + "description": "Heliostat Aimpoint and Layout Optimization Software (HALOS) is an open-source software package that allows users to explore solar field layout optimization, aimpoint strategy optimization, and performance characterization of concentrating solar power tower plants. Users interface with the tool through python, and results are reported in time series tables, plots, runtime logs, and flat-file outputs. Users choose from a list of variables such as tower height, receiver capacity, flux limits, design-point irradiance, etc., and specify information about the system using a small collection of flat files. The software can then optimize the specified variables (e.g., aimpoints for each heliostat) to maximize the thermal energy delivered to the receiver while adhering to flux limits. HALOS is implemented to be flexible with respect to flux characterization methods, but includes a direct connection to NREL's SolarPILOT\u2122 software via its python API so that users can utilize high-fidelity flux simulation methods that have already been developed.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HALOS (Heliostat Aimpoint and Layout Optimization Software)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HALOS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HALucinator_v._0.1_Beta.json b/agency-indexes/DoE/HALucinator_v._0.1_Beta.json new file mode 100644 index 00000000..977b8078 --- /dev/null +++ b/agency-indexes/DoE/HALucinator_v._0.1_Beta.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2018-10-23" + }, + "description": "HALucinator enables execution of firmware on a generic system emulation through interception of hardware abstraction library functions. This enables it to intercept the execution of functions that would interact with external hardware and to model the external hardware at a high-level of abstraction while maintaining correct firmware behavior. ", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HALucinator v. 0.1 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/HALucinator_v._1.0.json b/agency-indexes/DoE/HALucinator_v._1.0.json new file mode 100644 index 00000000..fa324e63 --- /dev/null +++ b/agency-indexes/DoE/HALucinator_v._1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2019-07-22" + }, + "description": "Scripts that enable emulating firmware by intercepting low-level hardware abstraction function calls and replacing their execution with abstractions of the hardware the intercepted functions are intended to interact with.", + "laborHours": 4316.8, + "languages": [], + "name": "HALucinator v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/embedded-sec/halucinator", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HAMR_-_Heterogeneous_Accelerator_Memory_Resource__HAMR__v1.0.json b/agency-indexes/DoE/HAMR_-_Heterogeneous_Accelerator_Memory_Resource__HAMR__v1.0.json new file mode 100644 index 00000000..bb93f8cc --- /dev/null +++ b/agency-indexes/DoE/HAMR_-_Heterogeneous_Accelerator_Memory_Resource__HAMR__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "HAMR is a library defining an accelerator technology agnostic memory model that bridges between accelerator technologies (CUDA, HIP, ROCm, OpenMP, Sycl, OpenCL, Kokos, etc) and traditional CPUs in heterogeneous computing environments. HAMR is light weight and implemented in modern C++. HAMR can be used to manage memory with in a single code or as a data model for coupling codes in a technologically agnostic way. HAMR provides a Python module for coupling C++ and Python codes which implements zero-copy data transfers to and from Python using the Numpy array interface and Numba CUDA array interface protocols.", + "laborHours": 0.0, + "languages": [], + "name": "HAMR - Heterogeneous Accelerator Memory Resource (HAMR) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-EESA/HAMR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HARD.json b/agency-indexes/DoE/HARD.json new file mode 100644 index 00000000..82055448 --- /dev/null +++ b/agency-indexes/DoE/HARD.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "Hydrodynamics And Radiative Diffusion Solver based on FleCSI framework", + "laborHours": 6475.2, + "languages": [], + "name": "HARD", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/HARD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HARP_Opt:_Horizontal_Axis_Rotor_Performance_Optimization.json b/agency-indexes/DoE/HARP_Opt:_Horizontal_Axis_Rotor_Performance_Optimization.json new file mode 100644 index 00000000..4faa5af7 --- /dev/null +++ b/agency-indexes/DoE/HARP_Opt:_Horizontal_Axis_Rotor_Performance_Optimization.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2018-09-12" + }, + "description": "HARP_Opt (Horizontal Axis Rotor Performance Optimization) utilizes MATLAB's optimization algorithms and the National Renewable Energy Laboratory's (NREL) WT-Perf blade element momentum (BEM) code to design axial-flow wind and water (i.e. hydrokinetic) turbine rotors. The code optimizes a rotor's performance for steady and uniform flows (no sheared or yawed flows). A variety of rotor control configurations can be designed using HARP_Opt, including fixed or variable rotor speed and fixed or variable blade pitch configuration. Blades with circular or non-circular roots are also supported.\n", + "laborHours": 5396.0, + "languages": [], + "name": "HARP_Opt: Horizontal Axis Rotor Performance Optimization", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HARP_Opt", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HC-NIDS:_signatures_and_simulations_for_detecting_cyber-attacks_aiming_to_cause_damage_against_cyber-physical_energy_systems.json b/agency-indexes/DoE/HC-NIDS:_signatures_and_simulations_for_detecting_cyber-attacks_aiming_to_cause_damage_against_cyber-physical_energy_systems.json new file mode 100644 index 00000000..7b4c8ccd --- /dev/null +++ b/agency-indexes/DoE/HC-NIDS:_signatures_and_simulations_for_detecting_cyber-attacks_aiming_to_cause_damage_against_cyber-physical_energy_systems.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Physical device safety is typically implemented locally using embedded controllers, while operations safety is primarily performed in control centers. Safe operations can be enhanced by correct design of device-level control algorithms, and protocols, procedures and operator training at the control-room level, but all can fail. Moreover, these elements exchange data and issue commands via vulnerable communication layers. In order to secure these gaps and enhance operational safety, we believe monitoring of command sequences must be combined with an awareness of physical device limitations and automata models that capture safety mechanisms. One way of doing this is by leveraging specification-based intrusion detection to monitor for physical constraint violations. The method can also verify that physical infrastructure state is consistent with monitoring information and control commands exchanged between field devices and control centers. This additional security layer enhances protection from both outsider attacks and insider mistakes. We implemented specification-based SCADA command analyzers using physical constraint algorithms directly in the Bro framework and Broccoli APIs for three separate scenarios: a water heater, an automated distribution system, and an over-current protection scheme. To accomplish this, we added low-level analyzers capable of examining control system-specific protocol packets for both Modbus TCP and DNP3, and also higher-level analyzers able to interpret device command and data streams within the context of each device's physical capabilities and present operational state. Thus the software that we are making available includes the Bro/Broccoli scripts for these three scenarios, as well as simulators, written in C, of those scenarios that generate sample traffic that is monitored by the Bro/Broccoli scripts. In addition, we have also implemented systems to directly pull cyber-physical information from the OSIsoft PI historian system. We have included the Python scripts used to perform that monitoring.", + "laborHours": 43487.2, + "name": "HC-NIDS: signatures and simulations for detecting cyber-attacks aiming to cause damage against cyber-physical energy systems", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lbnl-cybersecurity/LBNL_Physics_Based_IDS/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/LBNL_Physics_Based_IDS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HD-Bind:_Encoding_of_Molecular_Structure_with_Low_Precision,_Hyperdimensional_Binary_Representations.json b/agency-indexes/DoE/HD-Bind:_Encoding_of_Molecular_Structure_with_Low_Precision,_Hyperdimensional_Binary_Representations.json new file mode 100644 index 00000000..ec0fb195 --- /dev/null +++ b/agency-indexes/DoE/HD-Bind:_Encoding_of_Molecular_Structure_with_Low_Precision,_Hyperdimensional_Binary_Representations.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-08-01", + "metadataLastUpdated": "2024-09-12" + }, + "description": "Publicly available collections of drug-like molecules have grown to comprise tens of billions of compounds\ndue to advances in combinatorial chemistry. Traditional methods for identifying \"hit\" molecules from a\nlarge collection of potential drug-like candidates have relied on biophysical theory to compute\napproximations to the Gibbs free energy of the binding interaction between the drug and its protein target.\nThese approaches have the major drawback that they require exceptional computing capabilities for\neven relatively small collections of molecules.\nHyperdimensional Computing (HDC) is a recently-proposed learning paradigm that represents data with\nhigh-dimension binary vectors; this allows the use of low-precision binary vector arithmetic to create\nmodels of the data that can be learned without the need for the gradient-based optimization required in\nmany conventional machine learning and deep learning methods. This algorithmic simplicity allows for\nacceleration in hardware that has been previously demonstrated in a range of application areas. We\nconsider existing HDC approaches for molecular property classification and introduce two novel\nencodings of a commonly-used molecular representation, the extended connectivity fingerprint (ECFP).\nWe show that HDC-based inference methods are as much as 91 times more efficient than traditional\nmachine learning methods, and achieve an acceleration of nearly nine orders of magnitude compared to\nmolecular docking. Our results show that HDC accelerated methods retain competitive accuracy on a\nnumber of well-studied tasks such as molecular property predictions using the MoleculeNet dataset, and\nbind/no-bind activity classification using the DUD-E and LIT-PCBA datasets.\nOur work thus motivates further investigation into molecular representation learning to develop ultraefficient\npre-screening tools.", + "laborHours": 6064.8, + "languages": [], + "name": "HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/hdbind", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HDEV_Depot_Load_Profile_Generation_Code__Code_to_Generate_Heavy-Duty_Electric_Truck_Depot_Load_Profiles__[SWR-21-72].json b/agency-indexes/DoE/HDEV_Depot_Load_Profile_Generation_Code__Code_to_Generate_Heavy-Duty_Electric_Truck_Depot_Load_Profiles__[SWR-21-72].json new file mode 100644 index 00000000..a847fe18 --- /dev/null +++ b/agency-indexes/DoE/HDEV_Depot_Load_Profile_Generation_Code__Code_to_Generate_Heavy-Duty_Electric_Truck_Depot_Load_Profiles__[SWR-21-72].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-08-23", + "metadataLastUpdated": "2023-04-24" + }, + "description": "Code developed to generate heavy-duty electric truck depot load profiles for the study, \"Heavy-Duty Truck Electrification and the Impacts of Depot Charging on Electricity Distribution Systems\", by Borlaug et al., published in 2021. This software is provided as-is without dedicated support. The programming environment for this study may be reproduced with conda (installed via the Anaconda website): conda env create -f environment.yml To activate the environment: conda activate hdev-depot-charging-2021", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "HDEV Depot Load Profile Generation Code (Code to Generate Heavy-Duty Electric Truck Depot Load Profiles) [SWR-21-72]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hdev-depot-charging-2021", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HDF5-Version_1.12.0.json b/agency-indexes/DoE/HDF5-Version_1.12.0.json new file mode 100644 index 00000000..58b1bd44 --- /dev/null +++ b/agency-indexes/DoE/HDF5-Version_1.12.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "koziol@lbl.gov" + }, + "date": { + "created": "2018-03-30", + "metadataLastUpdated": "2023-05-16" + }, + "description": "The HDF5 library and file format implement the HDF5 data model for storing and managing data. This implementation supports an unlimited variety of datatypes and is designed for flexible and efficient I/O and for high volume and complex data. It is highly portable and extensible, allowing applications to evolve in their use of HDF5. The HDF5 Technology suite includes tools and applications for managing, manipulating, viewing, and analyzing data in the HDF5 format and other implementations.", + "laborHours": 0.0, + "languages": [], + "name": "HDF5-Version 1.12.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HDFGroup/hdf5", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HDTADA.json b/agency-indexes/DoE/HDTADA.json new file mode 100644 index 00000000..07755537 --- /dev/null +++ b/agency-indexes/DoE/HDTADA.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-02-04", + "metadataLastUpdated": "2019-02-05" + }, + "description": "The Hydrogen Dispenser Test Apparatus (HDTA) is used to validate hydrogen fueling station performance. This software takes the data generated from HDTA and compares it to fueling standards CSA HGV4.3 and SAE J2601. The software generates plots and metrics for pressure, temperature and IR communications from the HDTA.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "HDTADA", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HDTADA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HDTHe_calorimetry_v.1.0.json b/agency-indexes/DoE/HDTHe_calorimetry_v.1.0.json new file mode 100644 index 00000000..b549b84d --- /dev/null +++ b/agency-indexes/DoE/HDTHe_calorimetry_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software generates predicted results of differential scanning calorimetry experiments for samples of palladium in a perforated capsule in an atmosphere containing a mixture of hydrogen isotopologues and helium. It can also be used to predict the results of absorption-desorption experiments at constant temperature and solid-phase isotopic ratio.", + "laborHours": 0.0, + "languages": [ + "GNU Octave 3.6.4 or later" + ], + "name": "HDTHe calorimetry v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HDTHe", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HEAT_STRESS_TIME_WEIGHTED_AVERAGE_CALCULATOR.json b/agency-indexes/DoE/HEAT_STRESS_TIME_WEIGHTED_AVERAGE_CALCULATOR.json new file mode 100644 index 00000000..d93ded7a --- /dev/null +++ b/agency-indexes/DoE/HEAT_STRESS_TIME_WEIGHTED_AVERAGE_CALCULATOR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "This software organizes the collection of information necessary to evaluate heat stress and compare it to the exposure limits of the American Conference of Industrial Hygienists.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "HEAT STRESS TIME WEIGHTED AVERAGE CALCULATOR", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/HELICS-HLA.json b/agency-indexes/DoE/HELICS-HLA.json new file mode 100644 index 00000000..b08969a3 --- /dev/null +++ b/agency-indexes/DoE/HELICS-HLA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "The Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS) is a co-simulation platform that is currently under development as part of a GMLC project. The High Level Architecture (HLA) is a co-simulation standard, various implementations of which have been widely used for co-simulations for several years, particularly in the defense community. The objective of developing the HELICS-HLA interface is to provide the ability of making software connected with HLA implementations to work with software connected with HELICS. Since each HLA federation is dependent on the RTI being used, the HELICS-HLA interface developed here uses an implementation of the HLA, the Universal CPS Environment for Federation (UCEF), to create this interface. Both HELICS and UCEF are open source software. UCEF-gateway that enables the integration of HELICS and UCEF is also an open source software.", + "laborHours": 1109.6, + "languages": [], + "name": "HELICS-HLA", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GMLC-TDC/HELICS-HLA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HEMLOCK.json b/agency-indexes/DoE/HEMLOCK.json new file mode 100644 index 00000000..23e96ea3 --- /dev/null +++ b/agency-indexes/DoE/HEMLOCK.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-22" + }, + "description": "HEMLOCK (Heterogeneous Ensemble Machine Learning Open Classification Kit) is a software tool for constructing, evaluating, and applying heterogeneous ensemble data models for use in solving supervised machine learning problems. Specifically, the main class of problems targeted by HEMLOCK is the problem of multiple-class classification (also called labeling or categorization) of data with continuous or discrete features. HEMLOCK consists of various data readers, machine learning algorithms, model combination and comparison routines, evaluation methods for model performance testing, and interfaces to external, state-of-the-art machine learning software libraries.", + "laborHours": 2720.8, + "languages": [ + "Java" + ], + "name": "HEMLOCK", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/HEMLOCK?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HEMLOCK", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HEM__HolisticElectricityModel.jl__[SWR-21-62].json b/agency-indexes/DoE/HEM__HolisticElectricityModel.jl__[SWR-21-62].json new file mode 100644 index 00000000..3bc833b0 --- /dev/null +++ b/agency-indexes/DoE/HEM__HolisticElectricityModel.jl__[SWR-21-62].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-02-14", + "metadataLastUpdated": "2024-04-30" + }, + "description": "The Holistic Electricity Model (HEM) is a computational framework for analyzing electricity systems in their entirety, from the points of view of all key stakeholders.\n\nRelated publication: https://ieeexplore.ieee.org/document/10128887", + "laborHours": 7159.2, + "languages": [ + "Julia" + ], + "name": "HEM (HolisticElectricityModel.jl) [SWR-21-62]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel-hem/HolisticElectricityModel.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HERMES.json b/agency-indexes/DoE/HERMES.json new file mode 100644 index 00000000..a96bb82d --- /dev/null +++ b/agency-indexes/DoE/HERMES.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "HERMES - High-speed Event Retrieval and Management for Enhanced Spectral imaging code. \nThis code is meant to unpack and process neutron imaging data from the TPX3Cam made by Amsterdam Scientific Instruments. The TPX3Cam utilizes the Timepix3 chip in a single photon counting mode of image acquisition. The photon counting data streaming off the TPX3Cam needs to be process and analyzed in order to create final images. Therefore we are developing both python and cpp codes to allow for users of the TPX3Cam to efficiently analyze data and create images.", + "laborHours": 1261.6, + "languages": [], + "name": "HERMES", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/hermes", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HERON.json b/agency-indexes/DoE/HERON.json new file mode 100644 index 00000000..26089e1b --- /dev/null +++ b/agency-indexes/DoE/HERON.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2024-06-04" + }, + "description": "HERON is a modeling toolset and plugin for RAVEN to accelerate stochastic technoeconomic assessment of the economic viability of various grid-energy system configurations, especially with application to electrical grids and integrated energy systems (IES). The frameworks enabling this toolset are INL's RAVEN and its TEAL plugin. The toolset includes automated RAVEN workflow generation tools for performing stochastic analysis and optimization driven by technoeconomic factors. The workflows generated employ RAVEN for parametric or optimizing study of grid component characteristics, and again for stochastic sampling of regulated and deregulated markets, load, and weather histories. The toolset further provides methods for economically-optimal dispatch of system components given the stochastic samples of market, load, and weather histories. The toolset allows assembling of existing and new models through the RAVEN interface to the Modelica process modeling language.", + "laborHours": 14272.8, + "languages": [ + "Python" + ], + "name": "HERON", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HERON", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HFBTHO.json b/agency-indexes/DoE/HFBTHO.json new file mode 100644 index 00000000..bddad16a --- /dev/null +++ b/agency-indexes/DoE/HFBTHO.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HFBRHO is a physics computer code that is used to model the structure of the nucleus. It is an implementation of the nuclear energy Density Functional Theory (DFT), where the energy of the nucleus is obtained by integration over space of some phenomenological energy density, which is itself a functional of the neutron and proton densities. In HFBTHO, the energy density derives from the Skyrme effective two-body interaction between nucleons, nuclear superfluidity is treated at the Hartree-Fock-Bogoliubov (HFB) approximation, and axial-symmetry of the nuclear shape is assumed This version is the 2nd release of the program; the previous version has been published in Computer Physics Communications (1). It is the first version that has been partly developed at Lawrence Livermore National Laboratory.", + "homepageURL": "http://cpc.cs.qub.ac.uk/summaries/ADUI_v2_0.html", + "laborHours": 0.0, + "name": "HFBTHO", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://cpc.cs.qub.ac.uk/summaries/ADUI_v2_0.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/HFVT.json b/agency-indexes/DoE/HFVT.json new file mode 100644 index 00000000..b95ea834 --- /dev/null +++ b/agency-indexes/DoE/HFVT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2022-10-26", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The optimization tool denoted as the \u201cHydropower Flexibility Valuation Tool\u201d aims to maximize the revenue from market participation after satisfying flow requirements, considering a range of power market price signals and water availability scenarios.", + "laborHours": 0.0, + "languages": [], + "name": "HFVT", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HFVT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HGDL_v1.json b/agency-indexes/DoE/HGDL_v1.json new file mode 100644 index 00000000..5560aa0f --- /dev/null +++ b/agency-indexes/DoE/HGDL_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-15", + "metadataLastUpdated": "2021-03-15" + }, + "description": "The software is a general optimizer, simliar to scipy.minimize, but using advanced methods and it is HPC ready.", + "laborHours": 0.0, + "languages": [], + "name": "HGDL v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/hgdl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "version": "v1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HIPPO_Software.json b/agency-indexes/DoE/HIPPO_Software.json new file mode 100644 index 00000000..69fffd7a --- /dev/null +++ b/agency-indexes/DoE/HIPPO_Software.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-08-31", + "metadataLastUpdated": "2024-06-18" + }, + "description": "HIPPO software is a Python implementation of the HIPPO technology. The HIPPO technology provides the computational and modeling capabilities for managing electricity market operations and for designing and prototyping future markets. The current software can solve the day-ahead unit commitment problem and perform simultaneous feasibility test. It can be used to handle industry scale electricity market.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "HIPPO Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/HIPPO_Unit_Commitment_Version_1.json b/agency-indexes/DoE/HIPPO_Unit_Commitment_Version_1.json new file mode 100644 index 00000000..2ced07ba --- /dev/null +++ b/agency-indexes/DoE/HIPPO_Unit_Commitment_Version_1.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Developed for the Midcontinent Independent System Operator, Inc. (MISO), HIPPO-Unit Commitment Version 1 is for solving security constrained unit commitment problem. The model was developed to solve MISO's cases. This version of codes includes I/O module to read in MISO's csv files, modules to create a state-based mixed integer programming formulation for solving MIP, and modules to test basic procedures to solve MIP via HPC.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Python 2.7.7" + ], + "name": "HIPPO Unit Commitment Version 1", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/HIPSTER__Harmonized_Impacts_across_Products,_Scenarios,_and_Technologies_for_Environmental_and_Resource_metrics__[SWR-24-17].json b/agency-indexes/DoE/HIPSTER__Harmonized_Impacts_across_Products,_Scenarios,_and_Technologies_for_Environmental_and_Resource_metrics__[SWR-24-17].json new file mode 100644 index 00000000..3a2891cd --- /dev/null +++ b/agency-indexes/DoE/HIPSTER__Harmonized_Impacts_across_Products,_Scenarios,_and_Technologies_for_Environmental_and_Resource_metrics__[SWR-24-17].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-02-29" + }, + "description": "Development of a prototype, code-based life cycle assessment framework, the Harmonized Impacts across Products, Scenarios, and Technologies for Environmental and Resource metrics (HIPSTER), to coherently assess outputs of prospective NREL models across environmental and resource use metrics. Eventually, HIPSTER is aimed to also cover socioeconomic and justice metrics. At present, NREL model scenario impact assessments are performed incoherently, as they as based on varying assumptions and inputs, specifically life cycle inventories, and cover different system boundaries. HIPSTER was created to align the assumptions and boundaries with those of cradle-to-grave life cycle assessment. In FY22, HIPSTER was successfully applied using scenarios from the ReEDS\u2122 model, NREL's flagship capacity expansion model resulting in cradle-to-grace time-series life cycle impacts across LCA midpoints and resource use metrics.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HIPSTER (Harmonized Impacts across Products, Scenarios, and Technologies for Environmental and Resource metrics) [SWR-24-17]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HIPSTER", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.0.1 beta" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/HIVE\342\204\242_[SWR-19-36].json" "b/agency-indexes/DoE/HIVE\342\204\242_[SWR-19-36].json" new file mode 100644 index 00000000..2d5dd8fd --- /dev/null +++ "b/agency-indexes/DoE/HIVE\342\204\242_[SWR-19-36].json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-09-27", + "metadataLastUpdated": "2022-11-02" + }, + "description": "The HIVE\u2122 platform is a mobility services simulation platform developed to provide insight on the energy, infrastructure, service, and economic outcomes of various mobility as a service (MaaS) options. The HIVE platform takes a set of spatiotemporal travel origin-destination pairs and simulates the operation of a predefined mobility service fleet, incorporating request pooling, and various operational and charging behaviors. Hive specializes at modeling fleets of automated electric vehicles (AEVs) and can be used to site and size direct current fast charge (DCFC) stations and measure grid impacts of large-scale AEV fleets serving real-world MaaS trip demand (similar to taxis, Uber, Lyft, etc.). Potential outcomes from a Hive simulation include level of service, total vehicle miles traveled (VMT), deadheading (zero passenger) miles, simultaneous and total energy loads, average occupancy, and more. Hive is developed to generalize to new regions and can be customized to handle many scenarios and operating conditions.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HIVE\u2122 [SWR-19-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hive", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HMHD.json b/agency-indexes/DoE/HMHD.json new file mode 100644 index 00000000..52107010 --- /dev/null +++ b/agency-indexes/DoE/HMHD.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "yhuang@pppl.gov" + }, + "date": { + "created": "2018-08-10", + "metadataLastUpdated": "2018-08-14" + }, + "description": "HMHD is a massively parallel, general purpose 3D extended MHD code. HMHD is written in Fortran 90 and parallelized with MPI for domain decomposition, augmented with OpenMP for multi-threading in each domain.", + "homepageURL": "https://theory.pppl.gov/research/research.php?rid=10#h48", + "laborHours": 0.0, + "languages": [], + "name": "HMHD", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://theory.pppl.gov/research/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://theory.pppl.gov/research/research.php?rid=10#h48", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/HNQ_Version_0.1.json b/agency-indexes/DoE/HNQ_Version_0.1.json new file mode 100644 index 00000000..c12282ef --- /dev/null +++ b/agency-indexes/DoE/HNQ_Version_0.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-22" + }, + "description": "HNQ is a low level benchmark code used to characterize storage hardware performance.", + "laborHours": 334.4, + "languages": [ + "C" + ], + "name": "HNQ Version 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hnq", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HODIF:_High-Order_Discretizations,_Interpolations_and_Filters_for_AMR.json b/agency-indexes/DoE/HODIF:_High-Order_Discretizations,_Interpolations_and_Filters_for_AMR.json new file mode 100644 index 00000000..2f22f388 --- /dev/null +++ b/agency-indexes/DoE/HODIF:_High-Order_Discretizations,_Interpolations_and_Filters_for_AMR.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "This software, a library, contains FORTRAN77 subroutines to calculate first and second derivatives up to 8th order, interpolations (1D and 2D) up to 10th order and filters up to 14th order. Only even orders are addressed and finite-difference stencils are implemented on a vertex-centered mesh. The primary aim of this library is to be used in block-structured adaptive mesh simulations where high order is desired. The interpolants in this library are essentially designed to do prolongations and restrictions between levels of rfinement - however, they assume that the refinement ratio is 2. The filters are provided to remove high wavenumber content from solutions in case Runge phenomenon occurs - a common occurrence in case of marginal resolution of the solution. Details of the derivation and use are to be found in \"Using high-order methods on adaptively refined block-structured meshes - discretizations, interpolations and filters\", by J. Ray, C.A. Kennedy, S. Lefantzi and H.N. Najm, Sandia Technical Report, SAND2005-7981. The software comes with a User's Guide and examples how to use it.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "HODIF: High-Order Discretizations, Interpolations and Filters for AMR", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HODIF", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HOMMEXX.json b/agency-indexes/DoE/HOMMEXX.json new file mode 100644 index 00000000..9c55c40f --- /dev/null +++ b/agency-indexes/DoE/HOMMEXX.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "HOMMEXX is a global atmosphere dynamics and transport solver that uses a spectral element method, and is now written to be performance portable to many new computer architectures.", + "laborHours": 93723.2, + "languages": [ + "C++" + ], + "name": "HOMMEXX", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/E3SM-Project/HOMMEXX/blob/master/src/share/cxx/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/HOMMEXX", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HOMP__Hybrid_Operation_and_Maintenance_Platform__[SWR-22-81].json b/agency-indexes/DoE/HOMP__Hybrid_Operation_and_Maintenance_Platform__[SWR-22-81].json new file mode 100644 index 00000000..5a9eb42f --- /dev/null +++ b/agency-indexes/DoE/HOMP__Hybrid_Operation_and_Maintenance_Platform__[SWR-22-81].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2023-05-16" + }, + "description": "The HOMP software module is contained within NREL's Hybrid Optimization and Performance Platform (HOPP) at this URL: https://github.com/NREL/HOPP/tree/feature/HOMP. HOMP is a python-based software module which can be used concurrently with the Hybrid Optimization and Performance Platform (HOPP) to model, simulate, and optimize degradation, reliability, and operations and maintenance of hybrid power plant components. The program currently models lithium ion battery, PEM electrolyzer, wind turbine, and solar PV array components, which enables users to understand the design and operation tradeoffs of hybrid power plants. For instance, HOMP enables users to answer questions like: how large does a battery bank need to be to achieve optimal charge/discharge rates for performance and reliability? How does plant design change for different objectives (e.g., profit versus resilience)? Under what conditions is it better to produce electricity versus hydrogen? How do we optimally control hybrid power plants to reduce downtime and increase performance?", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "PowerBuilder", + "Python" + ], + "name": "HOMP (Hybrid Operation and Maintenance Platform) [SWR-22-81]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HOPP", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HONE_Sensor_Wireshark_Shim.json b/agency-indexes/DoE/HONE_Sensor_Wireshark_Shim.json new file mode 100644 index 00000000..df37efa4 --- /dev/null +++ b/agency-indexes/DoE/HONE_Sensor_Wireshark_Shim.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Hone sensors are packet-process correlation engines that log the relationships between applications and the communications they are responsible for. Hone sensors are available for a variety of platforms including Linux, Windows, and MacOSX", + "laborHours": 0.0, + "languages": [], + "name": "HONE Sensor Wireshark Shim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HoneProject/Wireshark-Shim", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HP-CONCORD_v0.1.json b/agency-indexes/DoE/HP-CONCORD_v0.1.json new file mode 100644 index 00000000..5153adee --- /dev/null +++ b/agency-indexes/DoE/HP-CONCORD_v0.1.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "High performance parallel computation of sparse inverse covariance matrix estimation.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "MPI C++ COMPLIER WITH OPENmp SUPPORT" + ], + "name": "HP-CONCORD v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/HPC-NMF:_A_High-Performance_Parallel_Algorithm_for_Nonnegative_Matrix_Factorization.json b/agency-indexes/DoE/HPC-NMF:_A_High-Performance_Parallel_Algorithm_for_Nonnegative_Matrix_Factorization.json new file mode 100644 index 00000000..99f18f6c --- /dev/null +++ b/agency-indexes/DoE/HPC-NMF:_A_High-Performance_Parallel_Algorithm_for_Nonnegative_Matrix_Factorization.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient distributed algorithms to solve the problem for big data sets. We propose a high-performance distributed-memory parallel algorithm that computes the factorization by iteratively solving alternating non-negative least squares (NLS) subproblems for $\\WW$ and $\\HH$. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). As opposed to previous implementation, our algorithm is also flexible: It performs well for both dense and sparse matrices, and allows the user to choose any one of the multiple algorithms for solving the updates to low rank factors $\\WW$ and $\\HH$ within the alternating iterations.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "HPC-NMF: A High-Performance Parallel Algorithm for Nonnegative Matrix Factorization", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ramkikannan/planc/blob/master/license.dat", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ramkikannan/planc", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HPC-PATTERNS.json b/agency-indexes/DoE/HPC-PATTERNS.json new file mode 100644 index 00000000..fd17700f --- /dev/null +++ b/agency-indexes/DoE/HPC-PATTERNS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "This repository consists of various code examples demonstrating common patterns used in High-Performance Computing (HPC). Indeed, examples showcasing innovative usage of newly developed capabilities of HPC libraries are highly demanded by the HPC community. This repository's goal is to fulfill those requests.", + "laborHours": 0.0, + "languages": [], + "name": "HPC-PATTERNS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/argonne-lcf/HPC-Patterns", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HPCCG_Solver_Package.json b/agency-indexes/DoE/HPCCG_Solver_Package.json new file mode 100644 index 00000000..b426e207 --- /dev/null +++ b/agency-indexes/DoE/HPCCG_Solver_Package.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "HPCCG is a simple PDE application and preconditioned conjugate gradient solver that solves a linear system on a beam-shaped domain. Although it does not address many performance issues present in real engineering applications, such as load imbalance and preconditioner scalability, it can serve as a first \"sanity test\" of new processor design choices, inter-connect network design choices and the scalability of a new computer system. Because it is self-contained, easy to compile and easily scaled to 100s or 1000s of porcessors, it can be an attractive study code for computer system designers.", + "laborHours": 775.2, + "languages": [ + "C++", + "Makefile" + ], + "name": "HPCCG Solver Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HPCCG", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HPCGraph_v._0.1.json b/agency-indexes/DoE/HPCGraph_v._0.1.json new file mode 100644 index 00000000..4f72819f --- /dev/null +++ b/agency-indexes/DoE/HPCGraph_v._0.1.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Graphs occur in several places in real world from road networks, social networks and scientific simulations. HPC Graph is a graph analysis software to analyze the properties such as connectivity, communities etc in extreme scale graphs.", + "laborHours": 2295.2, + "languages": [ + "C++", + "Makefile", + "C" + ], + "name": "HPCGraph v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HPCGraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HPC_Cluster_Modeler_and_CoLaboration_Platform.json b/agency-indexes/DoE/HPC_Cluster_Modeler_and_CoLaboration_Platform.json new file mode 100644 index 00000000..8d98c550 --- /dev/null +++ b/agency-indexes/DoE/HPC_Cluster_Modeler_and_CoLaboration_Platform.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The developed software is an HPC cluster model and collaboration tool which provides the\nfollowing features:\n- Construction of HPC cluster nodes\n- Complex interaction and dependency between HPC cluster nodes\n- Construction of fully software stacks (OS, data base, scheduler, libraries) internal to the\ncluster environment\n- Cluster nodes may be implemented via arbitrary providers (virtual machines, containers)\n- Complex interaction and dependency between HPC node\u2019s software stacks\n- Verification test framework between nodes and their software stacks\nThis is being used for active projects. This is intended to be used to provide consistent, coordinated scenario measurements,\nconfiguration and collaboration among the DoE TriLabs and other USG HPC sites in the\nforeseeable future, to accomplish DoE HPC CCE goals.", + "laborHours": 0.0, + "languages": [], + "name": "HPC Cluster Modeler and CoLaboration Platform", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/hpc-collab", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HPC_Job_Tracker.json b/agency-indexes/DoE/HPC_Job_Tracker.json new file mode 100644 index 00000000..2a4934ee --- /dev/null +++ b/agency-indexes/DoE/HPC_Job_Tracker.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-04-24", + "metadataLastUpdated": "2023-03-15" + }, + "description": "HPC job tracker is a wrapper script which will allow some of the resources a HPC application consumes to be tracked for the duration of the job.", + "laborHours": 456.0, + "languages": [], + "name": "HPC_Job_Tracker", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HPC_Job_Tracker", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HPDM-STD205.json b/agency-indexes/DoE/HPDM-STD205.json new file mode 100644 index 00000000..f720bde1 --- /dev/null +++ b/agency-indexes/DoE/HPDM-STD205.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "wanh@ornl.gov" + }, + "date": { + "created": "2023-02-13", + "metadataLastUpdated": "2023-02-13" + }, + "description": "ASHRAE Standard 205 - Heat Pump Design Model supply; This package helps OEMs to convert HPDM output files to STD 205 format; it also provides some RS sample tables.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HPDM-STD205", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/HPDM-STD205", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HPS-RL:_Hyperparameter_tuning_for_deep_RL_applications__HPS-RL__v1.json b/agency-indexes/DoE/HPS-RL:_Hyperparameter_tuning_for_deep_RL_applications__HPS-RL__v1.json new file mode 100644 index 00000000..21e3e55d --- /dev/null +++ b/agency-indexes/DoE/HPS-RL:_Hyperparameter_tuning_for_deep_RL_applications__HPS-RL__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-23", + "metadataLastUpdated": "2024-08-23" + }, + "description": "Genetic Algorithms meets Deep RL for Hyperparameters Hyperparameter optimization and architecture search can easily become cumbersome and finding the right hyperparameters can seriously impact the robustness of the deep RL application being developed.\n\nWe use genetic algorithms to evolve optimum deep RL architectures in a scalable manner.\n\nHPS-RL is designed to work with multiple gym enviornments, allow users to test their own optimization functions and tune multi-objective parameters in multiple deep RL algorithms. HPS-RL uses multi-threading and is being extended with mpipy for distributed processing on HPC.\n\nhttps://arxiv.org/abs/2201.11182", + "laborHours": 1915.2, + "languages": [], + "name": "HPS-RL: Hyperparameter tuning for deep RL applications (HPS-RL) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SelfDrivingNetworkLab/hps-rl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HPS__HydroPowerSimulations.jl__[SWR-23-110].json b/agency-indexes/DoE/HPS__HydroPowerSimulations.jl__[SWR-23-110].json new file mode 100644 index 00000000..0802592d --- /dev/null +++ b/agency-indexes/DoE/HPS__HydroPowerSimulations.jl__[SWR-23-110].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-02-06" + }, + "description": "HydroPowerSimulations is an extension to NREL's PowerSimulations.jl software that enables the modeling and analysis of hydropower systems.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "HPS (HydroPowerSimulations.jl) [SWR-23-110]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-Sienna/HydroPowerSimulations.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.8.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HPSim,_Version_1.0.json b/agency-indexes/DoE/HPSim,_Version_1.0.json new file mode 100644 index 00000000..156d1d78 --- /dev/null +++ b/agency-indexes/DoE/HPSim,_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HPSim is a GPU-accelerated online multi-particle beam dynamics simulation tool for ion linacs. It was originally developed for use on the Los Alamos 800-MeV proton linac. It is a \u201cz-code\u201d that contains typical linac beam transport elements. The linac RF-gap transformation utilizes transit-time-factors to calculate the beam acceleration therein. The space-charge effects are computed using the 2D SCHEFF (Space CHarge EFFect) algorithm, which calculates the radial and longitudinal space charge forces for cylindrically symmetric beam distributions. Other space- charge routines to be incorporated include the 3D PICNIC and a 3D Poisson solver. HPSim can simulate beam dynamics in drift tube linacs (DTLs) and coupled cavity linacs (CCLs). Elliptical superconducting cavity (SC) structures will also be incorporated into the code. The computational core of the code is written in C++ and accelerated using the NVIDIA CUDA technology. Users access the core code, which is wrapped in Python/C APIs, via Pythons scripts that enable ease-of-use and automation of the simulations. The overall linac description including the EPICS PV machine control parameters is kept in an SQLite database that also contains calibration and conversion factors required to transform the machine set points into model values used in the simulation.", + "laborHours": 31661.6, + "name": "HPSim, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/apphys/hpsim/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/apphys/hpsim", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HPXML2RESO__Home_Performance_XML_to_Real_Estate_Standards_Organization_Data_Dictionary_Translator_.json b/agency-indexes/DoE/HPXML2RESO__Home_Performance_XML_to_Real_Estate_Standards_Organization_Data_Dictionary_Translator_.json new file mode 100644 index 00000000..034bd765 --- /dev/null +++ b/agency-indexes/DoE/HPXML2RESO__Home_Performance_XML_to_Real_Estate_Standards_Organization_Data_Dictionary_Translator_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-07-07" + }, + "description": "This translator takes fields from the HPXML and translates them into RESO\u2019s Data Dictionary, which is used in MLS systems for real estate transactions across the country. The purpose is to get energy efficiency data into the real estate transaction.", + "laborHours": 167.2, + "languages": [], + "name": "HPXML2RESO (Home Performance XML to Real Estate Standards Organization Data Dictionary Translator)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hpxml2reso", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HPXML_Version_Translator.json b/agency-indexes/DoE/HPXML_Version_Translator.json new file mode 100644 index 00000000..3e28e7a7 --- /dev/null +++ b/agency-indexes/DoE/HPXML_Version_Translator.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "HPXML is a consensus data transfer standard for residential buildings. Over several years, multiple versions of the standard have been released. This tool accepts an HPXML file in an older version and translates it to a newer version.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HPXML Version Translator", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hpxml_version_translator", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HPXML_to_Home_Energy_Score_Translator__hescore-hpxml__[SWR-14-30].json b/agency-indexes/DoE/HPXML_to_Home_Energy_Score_Translator__hescore-hpxml__[SWR-14-30].json new file mode 100644 index 00000000..cd202f93 --- /dev/null +++ b/agency-indexes/DoE/HPXML_to_Home_Energy_Score_Translator__hescore-hpxml__[SWR-14-30].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This repository has been archived by the owner on Mar 6, 2024. It is now read-only.\n\nHome Energy Score is a simulation-based rating method for existing homes. Home Performance XML (HPXML) is a data transfer standard for home energy audit and retrofit data used throughout the industry. This software receives an HPXML document and translates the building characteristics into HEScore inputs compliant with their API.", + "laborHours": 23119.2, + "languages": [ + "Python" + ], + "name": "HPXML to Home Energy Score Translator (hescore-hpxml) [SWR-14-30]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hescore-hpxml", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v2023.05.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HPXr,_HPX_with_Resilience_Extension.json b/agency-indexes/DoE/HPXr,_HPX_with_Resilience_Extension.json new file mode 100644 index 00000000..607de4cc --- /dev/null +++ b/agency-indexes/DoE/HPXr,_HPX_with_Resilience_Extension.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2021-02-09" + }, + "description": "This software is extended from HPX, open source software (the copyright belongs to Louisiana State University). SAND2019-5457 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.\n", + "laborHours": 696965.6, + "languages": [], + "name": "HPXr, HPX with Resilience Extension", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/STEllAR-GROUP/hpx/blob/master/LICENSE_1_0.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/STEllAR-GROUP/hpx", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HQ-Tracer.json b/agency-indexes/DoE/HQ-Tracer.json new file mode 100644 index 00000000..3549d93a --- /dev/null +++ b/agency-indexes/DoE/HQ-Tracer.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-09-30", + "metadataLastUpdated": "2024-07-23" + }, + "description": "HQ-Tracer is a software plugin related to the open-source project Ghidra. It is used for taking an emulation instruction trace from open source platforms and displaying inside of Ghidra. It allows for software debugging, reverse engineering, and enables interactive forward and backward stepping and searching through the execution traces. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-4552 O", + "laborHours": 2568.8, + "languages": [ + "Python" + ], + "name": "HQ-Tracer", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/halucinator_hq-tracer", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HSE12_implementation_in_libxc.json b/agency-indexes/DoE/HSE12_implementation_in_libxc.json new file mode 100644 index 00000000..81e88e5c --- /dev/null +++ b/agency-indexes/DoE/HSE12_implementation_in_libxc.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "This piece of software is a new feature implemented inside an existing open-source library. Specifically, it is a new implementation of a density functional (HSE, short for Heyd-Scuseria-Ernzerhof) for a repository of density functionals, the libxc library. It fixes some numerical problems with existing implementations, as outlined in a scientific paper recently submitted for publication. Density functionals are components of electronic structure simulations, which model properties of electrons inside molecules and crystals.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C, any up-to-date compiler should suffice" + ], + "name": "HSE12 implementation in libxc", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/HSNMon:_High-Speed_Monitoring_Software_for_Omni-Path.json b/agency-indexes/DoE/HSNMon:_High-Speed_Monitoring_Software_for_Omni-Path.json new file mode 100644 index 00000000..461d1c79 --- /dev/null +++ b/agency-indexes/DoE/HSNMon:_High-Speed_Monitoring_Software_for_Omni-Path.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-19", + "metadataLastUpdated": "2021-11-19" + }, + "description": "HSNMon is a robust high speed network monitoring daemon that provides insight into network availability, hardware failure, and network performance for switches and network cards. HSNMon collects counters, forwarding tables, and error information at high resolution using publicly available Omni-Path Management APIs. The collected data can be forwarded into multiple logging infrastructures including syslog and message queuing systems. HSNMon is only the infrastructure for collecting the network data. It does not include any collected data or proprietary LANL information", + "laborHours": 0.0, + "languages": [], + "name": "HSNMon: High-Speed Monitoring Software for Omni-Path", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/hsnmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HSolo_v.1.0.json b/agency-indexes/DoE/HSolo_v.1.0.json new file mode 100644 index 00000000..03f18092 --- /dev/null +++ b/agency-indexes/DoE/HSolo_v.1.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-08-03", + "metadataLastUpdated": "2022-08-03" + }, + "description": "SAND2021-11023 O HSolo is a library for estimating similarity, affine, projective homographies from matches produced by image feature detectors such as SURF and SIFT. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python", + "C++" + ], + "name": "HSolo v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hsolo", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HTEM-DB_API_Examples.json b/agency-indexes/DoE/HTEM-DB_API_Examples.json new file mode 100644 index 00000000..b46e3ec8 --- /dev/null +++ b/agency-indexes/DoE/HTEM-DB_API_Examples.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-19", + "metadataLastUpdated": "2018-04-19" + }, + "description": "The HTEM DB is a public database and web application containing measurements of thin film materials collected using \"high throughput\" (combinatorial) synthesis and measurement processes. This software provides examples of utilizing the HTEM-DB API to access, plot and analyze the data contained therein.", + "laborHours": 364.8, + "name": "HTEM-DB API Examples", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/htem-api-examples", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HTMLFileSetServ.json b/agency-indexes/DoE/HTMLFileSetServ.json new file mode 100644 index 00000000..6dbc8f2b --- /dev/null +++ b/agency-indexes/DoE/HTMLFileSetServ.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "Dynamic HTTP service that serves up the contents of HTMLFileSets.", + "laborHours": 1611.2, + "languages": [], + "name": "HTMLFileSetServ", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/HTMLFileSetServ", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HTMLFileSetUtils.json b/agency-indexes/DoE/HTMLFileSetUtils.json new file mode 100644 index 00000000..e4e085e1 --- /dev/null +++ b/agency-indexes/DoE/HTMLFileSetUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "Utility function for saving a set of html files to the KBase data stores.", + "laborHours": 1216.0, + "languages": [], + "name": "HTMLFileSetUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/HTMLFileSetUtils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HTTPS_Servers_Cheat_Sheet.json b/agency-indexes/DoE/HTTPS_Servers_Cheat_Sheet.json new file mode 100644 index 00000000..c5379218 --- /dev/null +++ b/agency-indexes/DoE/HTTPS_Servers_Cheat_Sheet.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Repository containing vagrant configurations for how to properly install and harden common web servers, as well as configuration for meeting requirements for (e.g.) HTTPS and HSTS, as laid out in\u00a0OMB M-15-13\u00a0/\u00a0The HTTPS-Only Standard.\n", + "laborHours": 30.4, + "languages": [], + "name": "HTTPS Servers Cheat Sheet", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/hscs", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HUNTRESS:_a_fast_heuristic_for_reconstructing_phylogenetic_trees_of_tumor_evolution__HUNTRESS__v0.1.json b/agency-indexes/DoE/HUNTRESS:_a_fast_heuristic_for_reconstructing_phylogenetic_trees_of_tumor_evolution__HUNTRESS__v0.1.json new file mode 100644 index 00000000..c4de5d39 --- /dev/null +++ b/agency-indexes/DoE/HUNTRESS:_a_fast_heuristic_for_reconstructing_phylogenetic_trees_of_tumor_evolution__HUNTRESS__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-16" + }, + "description": "We introduce HUNTRESS (Histogrammed UNion Tree REconStruction heuriStic), a computational method for tumor phylogeny reconstruction from noisy genotype matrices derived from single-cell sequencing data, whose running time is linear with the number of cells and quadratic with the number of mutations. Provided that the input genotype matrix includes no false positives, each cellular subpopulation is at least a user defined fraction of the total number of cells, and the number of cells are much bigger than the number of mutations considered, HUNTRESS computes the ground truth tumor phylogeny with high probability. On simulated data HUNTRESS is faster than available alternatives with comparable or better accuracy. Additionally, the phylogenies reconstructed by HUNTRESS on two single-cell sequencing data sets agree with the best known evolutionary scenarios for the associated tumors.", + "laborHours": 0.0, + "languages": [], + "name": "HUNTRESS: a fast heuristic for reconstructing phylogenetic trees of tumor evolution (HUNTRESS) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PASSIONLab/HUNTRESS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HVAC_Fault_Detection_and_Diagnosis_Toolkit.json b/agency-indexes/DoE/HVAC_Fault_Detection_and_Diagnosis_Toolkit.json new file mode 100644 index 00000000..f51334ee --- /dev/null +++ b/agency-indexes/DoE/HVAC_Fault_Detection_and_Diagnosis_Toolkit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "This toolkit supports component-level model-based fault detection methods in commercial building HVAC systems. The toolbox consists of five basic modules: a parameter estimator for model calibration, a preprocessor, an AHU model simulator, a steady-state detector, and a comparator. Each of these modules and the fuzzy logic rules for fault diagnosis are described in detail. The toolbox is written in C++ and also invokes the SPARK simulation program.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "HVAC Fault Detection and Diagnosis Toolkit", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/HXHIM:_The_Hexa-dimensional_Hashing_Indexing_Middleware.json b/agency-indexes/DoE/HXHIM:_The_Hexa-dimensional_Hashing_Indexing_Middleware.json new file mode 100644 index 00000000..db0de6b2 --- /dev/null +++ b/agency-indexes/DoE/HXHIM:_The_Hexa-dimensional_Hashing_Indexing_Middleware.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "As HPC physics simulations grow ever larger in size, accessing the data generated by them becomes an increasingly difficult challenge. Searching for individual pieces of data or ranges of data in storage takes significant amounts of time that could be better spent elsewhere. In order to reduce the cost of pulling data from storage, we have developed the Hexadimensional Hashing Indexing Middleware (HXHIM). HXHIM is a distributed key-value store library written in C++ with a C api with networking performed by MPI and Thallium, and with LevelDB as the storage backend. Data is stored as Subject-Predicate-Object triples that can be searched for in any combination and can return ranges of data instead of just a single data point, allowing for fast, parallel extraction of large amounts of data from storage in significantly less time than existing methods are able to obtain the same data.", + "laborHours": 0.0, + "languages": [], + "name": "HXHIM: The Hexa-dimensional Hashing Indexing Middleware", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/hxhim", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HYBRED__HYbrid_Battery_Robust_Energy_Design_Tool_.json b/agency-indexes/DoE/HYBRED__HYbrid_Battery_Robust_Energy_Design_Tool_.json new file mode 100644 index 00000000..f28d049a --- /dev/null +++ b/agency-indexes/DoE/HYBRED__HYbrid_Battery_Robust_Energy_Design_Tool_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-12-02", + "metadataLastUpdated": "2021-09-07" + }, + "description": "HYbrid Battery Robust Energy Design (HYBRED) Tool is formulated as a mixed integer linear programming (MILP) model where discrete decisions are taken as of size of battery per type, choice of service each battery type can provide at a specific time (grid or dynamic regulatory service), and times of charging and discharging each battery. The potential charging sources are grid and renewables while the end users are commercial and industrial building loads, and electrical vehicles. The objective of the model is to maximize the batteries profit or in other words, to minimize the total battery cost. Major inputs to the model are solar irradiation profiles, time of use tariffs, buildings loads, dynamic regulatory service signal, various battery parameters, etc. Major outputs of the tool include battery sizes, costs and revenues, temporal profiles, and duration curves.", + "homepageURL": "https://www.labpartnering.org/p/lab-technologies/02761bf5-e886-43b9-b506-5be4b0416b99", + "laborHours": 0.0, + "languages": [], + "name": "HYBRED (HYbrid Battery Robust Energy Design Tool)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.labpartnering.org/p/lab-technologies/02761bf5-e886-43b9-b506-5be4b0416b99", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.labpartnering.org/p/lab-technologies/02761bf5-e886-43b9-b506-5be4b0416b99", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/HYDRATE_v1.5_OPTION_OF_TOUGH+_v1.5.json b/agency-indexes/DoE/HYDRATE_v1.5_OPTION_OF_TOUGH+_v1.5.json new file mode 100644 index 00000000..aff85ab5 --- /dev/null +++ b/agency-indexes/DoE/HYDRATE_v1.5_OPTION_OF_TOUGH+_v1.5.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-10", + "metadataLastUpdated": "2019-09-24" + }, + "description": "HYDRATE v1.5 is a numerical code that for the simulation of the behavior of hydrate-bearing geologic systems, and represents the third update of the code since its first release [Moridis et al., 2008]. It is an option of TOUGH+ v1.5 [Moridis and Pruess, 2014], a successor to the TOUGH2 [Pruess et al., 1999, 2012] family of codes for multi-component, multiphase fluid and heat flow developed at the Lawrence Berkeley National Laboratory. HYDRATE v1.5 needs the TOUGH+ v1.5 core code in order to compile and execute. It is written in standard FORTRAN 95/2003, and can be run on any computational platform (workstation, PC, Macintosh) for which such compilers are available. \nBy solving the coupled equations of mass and heat balance, the fully operational TOUGH+HYDRATE code can model the non-isothermal gas release, phase behavior and flow of fluids and heat under conditions typical of common natural CH4-hydrate deposits (i.e., in the permafrost and in deep ocean sediments) in complex geological media at any scale (from laboratory to reservoir) at which Darcy's law is valid. \nTOUGH+HYDRATE v1.5 includes both an equilibrium and a kinetic model of hydrate formation and dissociation. The model accounts for heat and up to four mass components, i.e., water, CH4, hydrate, and water-soluble inhibitors such as salts or alcohols. These are partitioned among four possible phases (gas phase, liquid phase, ice phase and hydrate phase). Hydrate dissociation or formation, phase changes and the corresponding thermal effects are fully described, as are the effects of inhibitors. The model can describe all possible hydrate dissociation mechanisms, i.e., depressurization, thermal stimulation, salting-out effects and inhibitor-induced effects.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 9408.8, + "languages": [], + "name": "HYDRATE v1.5 OPTION OF TOUGH+ v1.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/HYPPO_v1.0.0.json b/agency-indexes/DoE/HYPPO_v1.0.0.json new file mode 100644 index 00000000..3b9bb7eb --- /dev/null +++ b/agency-indexes/DoE/HYPPO_v1.0.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "HYPPO is a hyperparameter optimization (HPO) software that uses surrogate modeling and uncertainty quantification to provide reliable neural network architectures. Similar state-of-the-art HPO technologies do not use such features and mostly perform random searches to explore the parameter space, which can easily become computationally expensive. Using HYPPO, the user is able to reduce by an order of magnitude the number of evaluations necessary to identify the most optimal region in the hyperparameter space. Finally, using asynchronous nested parallelism, we are able to decrease by two orders of magnitude the amount of time required to complete the HPO process.", + "laborHours": 0.0, + "languages": [], + "name": "HYPPO v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/hpo-uq/hyppo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/HYPSTAT__Hydrogen_Production,_Storage,_and_Transmission_Analysis_Tool__[SWR-23-04].json b/agency-indexes/DoE/HYPSTAT__Hydrogen_Production,_Storage,_and_Transmission_Analysis_Tool__[SWR-23-04].json new file mode 100644 index 00000000..3f854e2f --- /dev/null +++ b/agency-indexes/DoE/HYPSTAT__Hydrogen_Production,_Storage,_and_Transmission_Analysis_Tool__[SWR-23-04].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-07", + "metadataLastUpdated": "2025-04-07" + }, + "description": "The Hydrogen Production, Storage, and Transmission Analysis Tool (HYPSTAT) is a modeling framework developed by the National Renewable Energy Laboratory (NREL) to support the analysis of hydrogen systems. HYPSTAT focuses on key components of hydrogen infrastructure, particularly electrolytic hydrogen production, hydrogen storage, and hydrogen transmission, as part of the transition to decarbonized energy systems\n\nHYPSTAT operates as a supply-to-demand model, taking a fixed exogenous demand as input and optimizing the design and operation of the hydrogen system to meet that demand. It determines cost-optimal configurations based on specified technology options and system constraints.", + "laborHours": 304.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "HYPSTAT (Hydrogen Production, Storage, and Transmission Analysis Tool) [SWR-23-04]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HYPSTAT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Handheld_Assessment_Tool_-_Data_Viewers__HATS_.json b/agency-indexes/DoE/Handheld_Assessment_Tool_-_Data_Viewers__HATS_.json new file mode 100644 index 00000000..e7ca2bd4 --- /dev/null +++ b/agency-indexes/DoE/Handheld_Assessment_Tool_-_Data_Viewers__HATS_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "HATS\u00a0allows\u00a0partner\u00a0countries\u00a0to\u00a0collect\u00a0data\u00a0on\u00a0all\u00a0of\u00a0their\u00a0handheld\u00a0radiation\u00a0detectors.\u00a0The\u00a0DataViewer\u00a0then\u00a0allows\u00a0them to\u00a0get\u00a0summaries\u00a0of\u00a0how\u00a0all\u00a0the\u00a0devices\u00a0are\u00a0performing\u00a0over\u00a0time,\u00a0pick\u00a0outliers\u00a0in\u00a0performance\u00a0so\u00a0they\u00a0can\u00a0be\u00a0fixed,\u00a0trend how\u00a0individual\u00a0devices\u00a0perform\u00a0over\u00a0time,\u00a0and\u00a0provide\u00a0reports\u00a0on\u00a0the\u00a0state\u00a0of\u00a0health\u00a0of\u00a0devices\u00a0they\u00a0service. 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We provide scripts to render each block and font into an image and store them together in an HDF5 file for each font and fontsize specified. Each font has 11,172 possible blocks and we have curated 35 fonts for a total of 391,020 possible images. The spoken consonants and vowel correspond to a set of \"initial\", \"medial\", and \"final\" labels for each block with 19, 21, and 28 classes respectively. In addition, each block can also be assigned a hierarchy label based on the block geometry. Finally, the individual glyphs (atoms) are composed across the initial, medial, and final locations along with potential scalings, translations, or rotations. These features of the data set make it uniquely positioned in the deep representation learning field because of its compositionally and hierarchical organization, while retaining diverse types of variation in the realizations.", + "laborHours": 0.0, + "languages": [], + "name": "HangulFonts v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BouchardLab/HangulFontsDatasetGenerator.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hard_X-Ray_Split_and_Delay_Automated_Controls_System.json b/agency-indexes/DoE/Hard_X-Ray_Split_and_Delay_Automated_Controls_System.json new file mode 100644 index 00000000..82daa075 --- /dev/null +++ b/agency-indexes/DoE/Hard_X-Ray_Split_and_Delay_Automated_Controls_System.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Controls automation module for the hard x-ray split and delay instrument.", + "laborHours": 3161.6, + "name": "Hard X-Ray Split and Delay Automated Controls System", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/HXRSnD/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/HXRSnD", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hardware-control_v1.json b/agency-indexes/DoE/Hardware-control_v1.json new file mode 100644 index 00000000..8e9f2dea --- /dev/null +++ b/agency-indexes/DoE/Hardware-control_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-05-02", + "metadataLastUpdated": "2021-06-15" + }, + "description": "The software is a python module that makes it easy to create reusable interfaces to control common hardware used in experiments.", + "laborHours": 0.0, + "languages": [], + "name": "Hardware-control v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/hardware-control", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hardware_In_the_Loop_for_Demand_Flexibility__HIL4DF__v1.0.json b/agency-indexes/DoE/Hardware_In_the_Loop_for_Demand_Flexibility__HIL4DF__v1.0.json new file mode 100644 index 00000000..8601dab9 --- /dev/null +++ b/agency-indexes/DoE/Hardware_In_the_Loop_for_Demand_Flexibility__HIL4DF__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-24", + "metadataLastUpdated": "2024-06-27" + }, + "description": "The software package in question is a collection of simulation models in the Modelica language, representing a variety of mechanical system designs and envelope conditions related to LBL's FLEXLAB facility. The collection of models also features multiple controls sequences that can be simulated with the FLEXLAB model to simulate different demand flexibility scenarios. Additionally, this package will feature datasets from 3 experimental tests, used for calibration, validation and comparison against the Modelica models, this includes weather data that can be used to replicate different scenarios in simulation across the same weather conditions experienced in real experiments. Given FLEXLAB high level of instrumentation and available data, the models are calibrated across multiple measurement points, and thus results from the extension of this model to other climate zones or control sequences, would provide high level of confidence.", + "laborHours": 0.0, + "languages": [], + "name": "Hardware In the Loop for Demand Flexibility (HIL4DF) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/HIL4DF", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Harmony_code.json b/agency-indexes/DoE/Harmony_code.json new file mode 100644 index 00000000..c2c2b60b --- /dev/null +++ b/agency-indexes/DoE/Harmony_code.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "Harmony is a finite element ALE code for solving the equations of fluid dynamics for single-material flows with arbitrary mesh motion in three dimensional geometry. ", + "laborHours": 0.0, + "languages": [], + "name": "Harmony code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Harmony", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hasty.json b/agency-indexes/DoE/Hasty.json new file mode 100644 index 00000000..e53e3c6d --- /dev/null +++ b/agency-indexes/DoE/Hasty.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-08-12", + "metadataLastUpdated": "2021-06-28" + }, + "description": "The software is a web app to create semantic metadata models, namely, Haystack and Brick. The purpose of Hasty is to assist in the auditing of building mechanical systems and controls. The software is designed to capture mechanical system topology and important information regarding real world controls implementations. The tool is intended to output Brick / Haystack / ASHRAE 223 compliant models.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python", + "CSS", + "HTML" + ], + "name": "Hasty", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hasty", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hatchet.json b/agency-indexes/DoE/Hatchet.json new file mode 100644 index 00000000..cb56936b --- /dev/null +++ b/agency-indexes/DoE/Hatchet.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "Hatchet is a Python-based library to analyze performance data that has a tree hierarchy (calling context\ntrees, call graphs, callpath traces, nested regions' timers, etc.).", + "laborHours": 29062.4, + "languages": [], + "name": "Hatchet", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/hatchet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Haven_beamline_control_software.json b/agency-indexes/DoE/Haven_beamline_control_software.json new file mode 100644 index 00000000..d27dbe95 --- /dev/null +++ b/agency-indexes/DoE/Haven_beamline_control_software.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-17", + "metadataLastUpdated": "2024-10-17" + }, + "description": "A suite of beamline controls software based on the Bluesky framework. SF-23-122", + "laborHours": 58854.4, + "languages": [], + "name": "Haven beamline control software", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spc-group/haven", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HawaiiCoast_GT_Code_Generation.json b/agency-indexes/DoE/HawaiiCoast_GT_Code_Generation.json new file mode 100644 index 00000000..dfe211c1 --- /dev/null +++ b/agency-indexes/DoE/HawaiiCoast_GT_Code_Generation.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-15" + }, + "description": "SAND2024-01823O\nThe HawaiiCoast_GT dataset validates anomaly detection algorithms on marine vessel tracks. The software also curates the dataset by extracting, filtering, cleaning, correlating, and computing. The codebase demonstrates the overarching methodology for deriving datasets like HawaiiCoast_GT. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HawaiiCoast_GT Code Generation", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HawaiiCoast_GT_Code_Generation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Haxall-based__Axon__fault_auto-correction_package_for_building_HVAC_system__Haxall-based_Fault_Correction__v1.0.json b/agency-indexes/DoE/Haxall-based__Axon__fault_auto-correction_package_for_building_HVAC_system__Haxall-based_Fault_Correction__v1.0.json new file mode 100644 index 00000000..a8093650 --- /dev/null +++ b/agency-indexes/DoE/Haxall-based__Axon__fault_auto-correction_package_for_building_HVAC_system__Haxall-based_Fault_Correction__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-28", + "metadataLastUpdated": "2023-06-28" + }, + "description": "\tHaxall-based Fault Correction is a set of fault auto-correction algorithms implemented using the Axon language. These algorithms can automatically fix equipment and control problems as they arise and improve the operation of building Heating, Ventilation, and Air Conditioning (HVAC) systems. The coded auto-correction algorithms include mitigation of rogue zones, ASHRAE Guideline 36 static pressure and supply air reset, resolution of control hunting due to improper settings in a proportional-integral-derivative controller, correction of biased temperature sensors, etc. FDD tools with enhanced auto-correction capability can resolve control problems as they are detected, increasing energy savings and emissions reductions while freeing up operational staff expertise for the hardest facility problems.", + "laborHours": 0.0, + "languages": [], + "name": "Haxall-based (Axon) fault auto-correction package for building HVAC system (Haxall-based Fault Correction) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/haxall-based-fault-correction", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Haxall_and_Haystack_Data_Analysis_for_Building_Operations__Data_Analysis_for_Operations__v1.0.json b/agency-indexes/DoE/Haxall_and_Haystack_Data_Analysis_for_Building_Operations__Data_Analysis_for_Operations__v1.0.json new file mode 100644 index 00000000..3f0e1c39 --- /dev/null +++ b/agency-indexes/DoE/Haxall_and_Haystack_Data_Analysis_for_Building_Operations__Data_Analysis_for_Operations__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-14", + "metadataLastUpdated": "2024-08-14" + }, + "description": "A library of Axon code and Trio files in active use at LBNL to analyze and display data related to the operation of buildings in the Haxall or SkySpark environment.", + "laborHours": 15.2, + "languages": [], + "name": "Haxall and Haystack Data Analysis for Building Operations (Data Analysis for Operations) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ralphou/data-analysis-operations", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Haystack-Ruby.json b/agency-indexes/DoE/Haystack-Ruby.json new file mode 100644 index 00000000..98ef0298 --- /dev/null +++ b/agency-indexes/DoE/Haystack-Ruby.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The open source Project Haystack initiative defines meta data and communication standards related to data from buildings and intelligent devices. The Project Haystack REST API defines standard formats and operations for exchanging Haystack tagged data over HTTP. The HaystackRuby gem wraps calls to this REST API to enable Ruby application to easily integrate data hosted on a Project Haystack compliant server. The HaystackRuby gem was developed at the National Renewable Energy Lab to support applications related to campus energy. We hope that this tool may be useful to others.", + "laborHours": 425.6, + "name": "Haystack-Ruby", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/haystack_ruby", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Haystack.json b/agency-indexes/DoE/Haystack.json new file mode 100644 index 00000000..ea4ac334 --- /dev/null +++ b/agency-indexes/DoE/Haystack.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Haystack is a software agent platform for user emulation. We are leveraging python and the SPADE software packages to develop an architecture and platform where software agents can be sent actuation behaviors, configured with different behavior profiles (time based, event based, probability based, etc.), and controlled/monitored from a central control unit. The haystack agent platform provides the ability to model and simulate user behavior in cyber systems. This eliminates the need to fund real users to provide this interaction, provides control such that researchers can randomize, hold-steady, or model whatever behavior that want to study without running afoul of IRB requirements, and provides a documented truth that enables understanding what happened in and experiment and provides for repeatability.", + "laborHours": 364.8, + "name": "Haystack", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/haystack", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Heat_Equation_Neural_Simulation.json b/agency-indexes/DoE/Heat_Equation_Neural_Simulation.json new file mode 100644 index 00000000..46f42800 --- /dev/null +++ b/agency-indexes/DoE/Heat_Equation_Neural_Simulation.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-04", + "metadataLastUpdated": "2024-09-18" + }, + "description": "This code solves a steady state heat equation problem on a wire with random walks implemented using a spiking neural algorithm. SAND2020-12194 M", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "Heat Equation Neural Simulation", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HeatEquationNeuralSimulation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Helium_Fluid_Properties.json b/agency-indexes/DoE/Helium_Fluid_Properties.json new file mode 100644 index 00000000..b05839b0 --- /dev/null +++ b/agency-indexes/DoE/Helium_Fluid_Properties.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-08-30" + }, + "description": "This software is used to compute numerous properties for helium.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Helium Fluid Properties", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/helium", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Henson_v1.0.json b/agency-indexes/DoE/Henson_v1.0.json new file mode 100644 index 00000000..d0946e7e --- /dev/null +++ b/agency-indexes/DoE/Henson_v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Modern scientific and engineering simulations track the time evolution of billions of elements. For such large runs, storing most time steps for later analysis is not a viable strategy. It is far more efficient to analyze the simulation data while it is still in memory. The developers present a novel design for running multiple codes in situ: using coroutines and position-independent executables they enable cooperative multitasking between simulation and analysis, allowing the same executables to post-process simulation output, as well as to process it on the fly, both in situ and in transit. They present Henson, an implementation of our design, and illustrate its versatility by tackling analysis tasks with different computational requirements. Our design differs significantly from the existing frameworks and offers an efficient and robust approach to integrating multiple codes on modern supercomputers. The presented techniques can also be integrated into other in situ frameworks.", + "laborHours": 29928.8, + "name": "Henson v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mrzv/henson/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mrzv/henson", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hermes-3.json b/agency-indexes/DoE/Hermes-3.json new file mode 100644 index 00000000..a9351ad3 --- /dev/null +++ b/agency-indexes/DoE/Hermes-3.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-15", + "metadataLastUpdated": "2023-02-15" + }, + "description": "Hermes-3 is a plasma simulation model built on BOUT++, developed as part of research studies of the edge and divertor regions of magnetically confined fusion plasmas such as tokamaks. The main purpose of this model is multi-species simulation of plasmas containing a mixture of deuterium, tritium, helium and other plasma and neutral gas species.", + "laborHours": 0.0, + "languages": [], + "name": "Hermes-3", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bendudson/hermes-3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hermes_Utility_Libraries_and_Tools.json b/agency-indexes/DoE/Hermes_Utility_Libraries_and_Tools.json new file mode 100644 index 00000000..53cc81b8 --- /dev/null +++ b/agency-indexes/DoE/Hermes_Utility_Libraries_and_Tools.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-22" + }, + "description": "This software is a set of utility libraries and tools developed in support of multiple scientific simulation projects. These libraries provide many general-purpose capabilities, such as a compact, extensible, machine-independent binary file format for various forms of scientific data, a Fortran-callable command parser that supports symbolic variables, looping, and conditional constructs, a Fortran-callable interface to ITT Corporation's callable IDL graphics and data analysis, a multi-block, 2D electrostatic solver, a machine-independent Fortran interface to standard system services, and various Fortran-callable dynamic memory services. In some cases, C interfaces are also provided. In addition, some tools that use these various libraries are available. A brief description of each library/tool follows: PFF library - PFF is a compact, extensible, machine-independent binary file format for various forms of scientific data. Two libraries are provided: one designed to be called from Fortran 77, and the other designed to be called from C or C++. Dataset types for several varieties of scientific data are built into the library, and new dataset types can be added. The libraries provide support for reading/writing these datasets from/to PFF files, as well as functionality for interactive processing of PFF files and the data they contain. Tools for manipulating, converting, and comparing PFF data are also available.", + "laborHours": 42043.2, + "languages": [ + "C++", + "C", + "Fortran", + "Python" + ], + "name": "Hermes Utility Libraries and Tools", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hermes-util", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Heterogeneous_Data_Type_Mixture_Model.json b/agency-indexes/DoE/Heterogeneous_Data_Type_Mixture_Model.json new file mode 100644 index 00000000..59ce7d42 --- /dev/null +++ b/agency-indexes/DoE/Heterogeneous_Data_Type_Mixture_Model.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-01", + "metadataLastUpdated": "2024-04-01" + }, + "description": "This code performs estimation of a mixture model involving heterogeneous data types. The resulting\nmodel can be used to calculate likelihoods of underlying model components.", + "laborHours": 273.6, + "languages": [], + "name": "Heterogeneous Data Type Mixture Model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/alankaplan/HDTMM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Heuristic_Access_to_Positions_of_Photon_Instruments__HAPPI_.json b/agency-indexes/DoE/Heuristic_Access_to_Positions_of_Photon_Instruments__HAPPI_.json new file mode 100644 index 00000000..0c226816 --- /dev/null +++ b/agency-indexes/DoE/Heuristic_Access_to_Positions_of_Photon_Instruments__HAPPI_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Happi is a database to hold generic information for devices along the LCLS photon beamline. LCLS endstations deal with dynamic sets of instrumentation. Information like ports, triggers and aliases are all important for operation, but hard to manage when spread across a multitude of applications.\u00a0Happi\u00a0solves this problem by creating a single access point for all the metadata required to interface with LCLS instrumentation. Using a flexible\u00a0container\u00a0based system Happi allows the enforcement of specific conventions while still permitting flexible data entry where required.", + "laborHours": 1641.6, + "name": "Heuristic Access to Positions of Photon Instruments (HAPPI)", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/happi/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/happi", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HexFinder.json b/agency-indexes/DoE/HexFinder.json new file mode 100644 index 00000000..498e7dae --- /dev/null +++ b/agency-indexes/DoE/HexFinder.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "Simulations and analyses of data from hexagonally pixelated detectors require conversions from a Cartesian coordinate system to and from a hexagonal pixel index. This software builds and indexes the detector geometry, calculates neighbors and coordinate system conversions, and provides a framework for plotting analysis results.", + "laborHours": 440.8, + "languages": [ + "C++;gcc;4.8.4" + ], + "name": "HexFinder", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/leahbroussard/HexFinder/-/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/leahbroussard/HexFinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/HiFiPDV2_v._2.json b/agency-indexes/DoE/HiFiPDV2_v._2.json new file mode 100644 index 00000000..e3a7a2eb --- /dev/null +++ b/agency-indexes/DoE/HiFiPDV2_v._2.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-20" + }, + "description": "SAND2024-01061O\nThe HiFiPDV-2 software is similar to other photonic Doppler velocimetry (PDV) analysis codes in that it converts signals from intensity-time space to frequency-time space using a short-time Fourier transform (STFT). It then analyzes peaks of the resulting power spectral density information to extract the velocity-time history. \n\nThe unique aspects of HiFiPDV and HiFiPDV-2 are that this reduction process is repeated for an array of reasonable STFT input variables. The resulting population distribution of output velocity-time histories is evaluated to determine the most likely velocity history and its associated uncertainty. This uncertainty is defined as the systematic uncertainty of the PDV signal as it is a function of input values to the reduction process. The HiFiPDV-2 program brings new functionality and efficiency to these calculations\u2014most notably significant reductions in memory usage and calculation times, the ability to evaluate frequency-shifted signals, and the ability to filter out baseline signals. \n\nDevelopers recommend that users have at least 2 GB of RAM per CPU core in their system. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "HiFiPDV2 v. 2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HiFiPDV2", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HiPACE++_v0.1.json b/agency-indexes/DoE/HiPACE++_v0.1.json new file mode 100644 index 00000000..581063e5 --- /dev/null +++ b/agency-indexes/DoE/HiPACE++_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-21" + }, + "description": "Hipace++ is the new implementation of the DESY-LBNL code Hipace (not distributed nor licensed) for plasma acceleration, relying on the quasi-static particle-in-cell (PIC) method, enabling fast and accurate simulations of plasma accelerators for problems satisfying the quasi-static approximation. Plasma acceleration is a priority in the ATAP division, and such problems represent a wide range of parameters. Hipace++ is an HPC (high-performance computing) code running on supercomputers and it provides the first efficient implementation of the quasi-static PIC method on Graphic Processing Units (GPU), showing 10x speedup and using much less resources than CPU implementations for production simulations. It currently runs on Nvidia GPUs and will ultimately be portable to more accelerated HPC platforms. The porting strategy is novel, and can be adapted to other flavors of quasi-static PIC. Besides, Hipace++ aims at using mesh refinement for higher efficiency, thus enabling simulations unfeasible today. For this purpose, Hipace++ depends on the open-source library AMReX (Adaptive Mesh Refinement at EXascale) developed at LBNL.", + "laborHours": 0.0, + "languages": [], + "name": "HiPACE++ v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Hi-PACE/hipace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HiPAS_Converters.json b/agency-indexes/DoE/HiPAS_Converters.json new file mode 100644 index 00000000..da6d1b45 --- /dev/null +++ b/agency-indexes/DoE/HiPAS_Converters.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-13", + "metadataLastUpdated": "2022-09-13" + }, + "description": "This is the repository for \"HiPAS Converters\" developed by SLAC National Accelerator Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "HiPAS Converters", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/gridlabd-converters", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HiPAS_GridLAB-D.json b/agency-indexes/DoE/HiPAS_GridLAB-D.json new file mode 100644 index 00000000..c3c526b7 --- /dev/null +++ b/agency-indexes/DoE/HiPAS_GridLAB-D.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-07", + "metadataLastUpdated": "2022-09-07" + }, + "description": "HiPAS GridLAB-D is the California Energy Commission (CEC) version of GridLAB-D.", + "laborHours": 0.0, + "languages": [], + "name": "HiPAS GridLAB-D", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/gridlabd", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HiPerSBTK_[SWR-08-64].json b/agency-indexes/DoE/HiPerSBTK_[SWR-08-64].json new file mode 100644 index 00000000..73d4cbdf --- /dev/null +++ b/agency-indexes/DoE/HiPerSBTK_[SWR-08-64].json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-07-25" + }, + "description": "HiPerSBTK consists of software which integrates equation solving, optimization and graphical interface functions to perform large-scale systems biology modeling.\n\nsee: https://www.nrel.gov/docs/fy11osti/51558.pdf", + "laborHours": 3149576.8, + "languages": [], + "name": "HiPerSBTK [SWR-08-64]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hiearchical_Engine_for_Large_Scale_Infrastructure_Simulation.json b/agency-indexes/DoE/Hiearchical_Engine_for_Large_Scale_Infrastructure_Simulation.json new file mode 100644 index 00000000..67fb6b84 --- /dev/null +++ b/agency-indexes/DoE/Hiearchical_Engine_for_Large_Scale_Infrastructure_Simulation.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HELICS ls a new open-source, cyber-physlcal-energy co-simulation framework for electric power systems. HELICS Is designed to support very-large-scale (100,000+ federates) co\u00adsimulations with off-the-shelf power-system, communication, market, and end-use tools. Other key features Include cross platform operating system support, the integration of both eventdrlven (e.g., packetlzed communication) and time-series (e.g.,power flow) simulations, and the ability to co-Iterate among federates to ensure physical model convergence at each time step.", + "laborHours": 265848.0, + "name": "Hiearchical Engine for Large Scale Infrastructure Simulation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GMLC-TDC/HELICS-src/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GMLC-Tdc/HELICS-src", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hierarchical_Engine_for_Large-scale_Infrastructure_Co-Simulation.json b/agency-indexes/DoE/Hierarchical_Engine_for_Large-scale_Infrastructure_Co-Simulation.json new file mode 100644 index 00000000..c7b6b3ca --- /dev/null +++ b/agency-indexes/DoE/Hierarchical_Engine_for_Large-scale_Infrastructure_Co-Simulation.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HELICS is designed to support very-large-scale (100,000+ federates) cosimulations with off-the-shelf power-system, communication, market, and end-use tools. Other key features include cross platform operating system support, the integration of both event driven (e.g., packetized communication) and time-series (e.g., power flow) simulations, and the ability to co-iterate among federates to ensure physical model convergence at each time step.", + "laborHours": 265848.0, + "name": "Hierarchical Engine for Large-scale Infrastructure Co-Simulation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GMLC-TDC/HELICS-src/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GMLC-TDC/HELICS-src", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hierarchical_Model-Free_Transactional_Control_of_Building_Loads_to_Support_Grid_Services.json b/agency-indexes/DoE/Hierarchical_Model-Free_Transactional_Control_of_Building_Loads_to_Support_Grid_Services.json new file mode 100644 index 00000000..2978757d --- /dev/null +++ b/agency-indexes/DoE/Hierarchical_Model-Free_Transactional_Control_of_Building_Loads_to_Support_Grid_Services.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "olamahussemm@ornl.gov" + }, + "date": { + "created": "2022-11-21", + "metadataLastUpdated": "2022-11-21" + }, + "description": "A transition from generation on demand to consumption on demand is one of the solutions to overcome the many limitations associated with the higher penetration of renewable energy sources. Such a transition, however, requires a considerable amount of load flexibility in the demand side. Demand response (DR) programs can reveal and utilize this demand flexibility by enabling the participation of a large number of grid-interactive efficient buildings (GEB). Existing approaches on DR require significant modelling or training efforts, are computationally expensive, and do not guarantee the satisfaction of end users. To address the aforementioned limitations, this software code considers a scalable hierarchical model-free transactional control approach that incorporates elements of virtual battery, game theory, and model-free control (MFC) mechanisms. The developed approach separates the control mechanism into upper and lower levels. The MFC modulates the flexible GEB in the lower level with guaranteed thermal comfort of end users in response to the optimal pricing and power signals determined in the upper layer using a Stackelberg game integrated with aggregate virtual battery constraints. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable even on small, embedded devices. This software code enables the use of residential and small-size commercial buildings to offer a potentially substantial source of ancillary grid services that are currently underutilized. A hierarchical, model-free transactive building control provides a smooth interface between the grid service requests of utilities and the reliable control required by participating buildings. Model-free control, which supports distributed control architecture, will be a more scalable solution that can be deployed in neighborhood-size systems as well as individual buildings. The proposed approach contributes to the body of knowledge on two main aspects. First, it couples the MFC with the game-theoretic control and proposes a scalable model-free transactive control approach. MFC does not require any modeling effort or model training for the various building loads. This is very beneficial since deriving an accurate model for every single unit participating in DR programs and obtaining all the parameters about the units (e.g., thermal coefficients, standby losses) are infeasible. Also, MFC is computationally efficient, easily deployable even on small, embedded devices, and can be implemented in real time. Second, it integrates the concept of virtual battery into DR via the Stackelberg game. The concept of virtual battery enables efficient coordination and aggregation of a large number of flexible GEB with guaranteed thermal comfort of end users.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Hierarchical Model-Free Transactional Control of Building Loads to Support Grid Services", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aulama2000/HMFC", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High-Energy_X-Ray_Diffraction_Analysis_Tool.json b/agency-indexes/DoE/High-Energy_X-Ray_Diffraction_Analysis_Tool.json new file mode 100644 index 00000000..65ed85a7 --- /dev/null +++ b/agency-indexes/DoE/High-Energy_X-Ray_Diffraction_Analysis_Tool.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The functionality of heRXD includes the following: distance and angular calibration and viewing flat-panel detector images used for X-ray diffraction; image (polar) rebinning or \"caking\"; line position fitting in powder diffraction images; image segmentation or \"blob finding\"; crystal orentation indesing; and lattice vector refinement. These functionalities encompass a critical set analyzing teh data for high-energy diffraction measurements that are currently performed at synchrotron sources such as the Advanced Photon Source (APS). The software design modular and open source under LGPL. The intent is to provide a common framework and graphical user interface that has the ability to utillize internal as well as external subroutines to provide various optins for performing the fuctionalities listed above. The software will initially be deployed at several national user facilities--including APS, ALS, and CHESS--and then made available for download using a hosting service such as sourceforge.", + "laborHours": 33865.6, + "name": "High-Energy X-Ray Diffraction Analysis Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/praxes/hexrd", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High-Performance_GMRES_Mixed-Precision__HPG-MxP__Benchmark.json b/agency-indexes/DoE/High-Performance_GMRES_Mixed-Precision__HPG-MxP__Benchmark.json new file mode 100644 index 00000000..364b4b0d --- /dev/null +++ b/agency-indexes/DoE/High-Performance_GMRES_Mixed-Precision__HPG-MxP__Benchmark.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-11-05" + }, + "description": "SAND2024-08539O\nThe High Performance GMRES Mixed-Precision (HPG-MxP) is a benchmark for ranking high-performance supercomputers, allowing use of mixed-precision. Similar to HPCG benchmark, it is designed to profile the computers' capabilities to perform the computational and communication tasks that are commonly found in important classes of real-world applications. At the same time, like HPL-MxP benchmark, it allows the use of mixed-precision arithmetic, while ensuring the double-precision accuracy of the computed solution.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 2888.0, + "languages": [ + "C++" + ], + "name": "High-Performance GMRES Mixed-Precision (HPG-MxP) Benchmark", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/iyamazaki/hpcg", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High-performance_optimization_solver.json b/agency-indexes/DoE/High-performance_optimization_solver.json new file mode 100644 index 00000000..4d2247fe --- /dev/null +++ b/agency-indexes/DoE/High-performance_optimization_solver.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "HIOP is a HPC solver for solving certain optimization problems arising in mathematical optimization of systems described by partial-differential equations (POEs).", + "laborHours": 51573.6, + "languages": [ + "C++ (95%), CMake (5%)" + ], + "name": "High-performance optimization solver", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/hiop/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/hiop", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High-throughput_electronic_structure_package.json b/agency-indexes/DoE/High-throughput_electronic_structure_package.json new file mode 100644 index 00000000..5e9426de --- /dev/null +++ b/agency-indexes/DoE/High-throughput_electronic_structure_package.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2024-06-19", + "metadataLastUpdated": "2024-06-19" + }, + "description": "We introduce HTESP (High-Throughput Electronic Structure Package), an automated tool designed for high-throughput ab initio calculations. HTESP simplifies the entire workflow, including data extraction, input files generation, calculation submission, result collection, and plotting. The package is implemented in Python and Bash languages. In this paper, we provide detailed information about the package, its installation process and some illustrative examples to demonstrate its usage. Additionally, the package includes comprehensive online documentation on input parameters and tutorials to assist users.", + "laborHours": 14060.0, + "languages": [ + "Bash", + "Python" + ], + "name": "High-throughput electronic structure package", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Neraaz/HTESP", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HighIQ.json b/agency-indexes/DoE/HighIQ.json new file mode 100644 index 00000000..8d457a1e --- /dev/null +++ b/agency-indexes/DoE/HighIQ.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-05-27", + "metadataLastUpdated": "2020-09-18" + }, + "description": "This software is for the processing of raw IQ data from radars and lidars that uses CUDA-compatible GPUs such as those in the Array of Things.", + "laborHours": 410.4, + "languages": [], + "name": "HighIQ", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openradar/HighIQ", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High_Entropy_Analysis_Code.json b/agency-indexes/DoE/High_Entropy_Analysis_Code.json new file mode 100644 index 00000000..1d6c1f9a --- /dev/null +++ b/agency-indexes/DoE/High_Entropy_Analysis_Code.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-05-28", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This code describes the process to estimate material properties using elemental properties and machine learning.", + "laborHours": 0.0, + "languages": [ + "R" + ], + "name": "High Entropy Analysis Code", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HEA_Code", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High_Magnetic_Field_Science_Toolset.json b/agency-indexes/DoE/High_Magnetic_Field_Science_Toolset.json new file mode 100644 index 00000000..b3a71f11 --- /dev/null +++ b/agency-indexes/DoE/High_Magnetic_Field_Science_Toolset.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-13" + }, + "description": "High Magnetic Field Science Toolset is designed to acquire and analyze experimental data at high magnetic fields. The software toolset is developed at Los Alamos National Laboratory for the National High Magnetic Field Laboratory user program within the scope of the High Magnetic Field Science Designated Unclassified Subject Area.", + "homepageURL": "https://github.com/ffb-LANL/High-Magnetic-Field-Science-Toolset", + "laborHours": 0.0, + "languages": [], + "name": "High Magnetic Field Science Toolset", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ffb-LANL/High-Magnetic-Field-Science-Toolset", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "v1.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High_Performance_Approximate_Computing.json b/agency-indexes/DoE/High_Performance_Approximate_Computing.json new file mode 100644 index 00000000..95acfbda --- /dev/null +++ b/agency-indexes/DoE/High_Performance_Approximate_Computing.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "This code repository contains the implementation of the \"High-Performance Approximate Computing\" (HPAC) toolkit. The toolkit allows you to approximate your own C/C++. The developer uses \"pragma's\" to annotate code regions as approximate. The compiler extensions lower these pragmas to either compiletime approximate techniques or runtime approximation techniques. At execution time, the implemented runtime system decides which annotated regions it should approximate. HPAC also provides a set of script utilities. The utilities perform a grid search within approximation parameters and performance. The user can analyze the raw data to identify optimal approximation techniques for the application.", + "laborHours": 0.0, + "languages": [], + "name": "High Performance Approximate Computing", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/HPAC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High_Performance_Computing_Cluster_Engineering_Academy.json b/agency-indexes/DoE/High_Performance_Computing_Cluster_Engineering_Academy.json new file mode 100644 index 00000000..8b8e44bf --- /dev/null +++ b/agency-indexes/DoE/High_Performance_Computing_Cluster_Engineering_Academy.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-03", + "metadataLastUpdated": "2019-05-06" + }, + "description": "Collection of tools and code for evaluation testing of HPC orchestration solutions by HPCCEA summer students. These scripts and configuration files were written by HPCCEA summer students as part of their summer internship where they explore alternative solutions to our current HPC cluster management software. These scripts/configuration files range from using configuration management tools (Puppet, Chef, Ansible, Fabric, etc.) to scripting languages (Phython, BASH, Perl, etc.). Each year, new students will be added to the project and expand on previous years work.", + "laborHours": 1474.4, + "languages": [], + "name": "High Performance Computing Cluster Engineering Academy", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/HPCCEA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High_Performance_Computing_Innovation_Center_Open_Source_Developer_Tools.json b/agency-indexes/DoE/High_Performance_Computing_Innovation_Center_Open_Source_Developer_Tools.json new file mode 100644 index 00000000..ba734967 --- /dev/null +++ b/agency-indexes/DoE/High_Performance_Computing_Innovation_Center_Open_Source_Developer_Tools.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-02", + "metadataLastUpdated": "2023-03-03" + }, + "description": "The High Performance Computing Innovation Center (HPCIC) aims to ease the transition for developers to use open source software provided by the lab. HPCIC Developer Tools is a collection of software, containers, cloud configurations, and associated documentation that make it easy to deploy tutorials or small apps to demonstrate lab-developed software. For example, building a tutorial container that includes lab software and interactive interfaces; a command line or web-based tool that accepts user preferences for the tutorial; supporting tools and software development kits (SDKs) for developer interactions or productivity in different languages embraced by the larger developer community such as Go, Rust, and Python; and automation in version control to support continued update of software and associated resources. These tools are best developed in an open source environment such as GitHub, not only to champion the lab's open source software, but for purposes of branding and demonstrating the lab's leadership in open source. Such an effort that brings in more developers to use and contribute to lab software can further improve the quality of the software, and developer experience at the lab. ", + "laborHours": 0.0, + "languages": [], + "name": "High Performance Computing Innovation Center Open Source Developer Tools", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/converged-computing/playground", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High_Performance_Computing_tutorials.json b/agency-indexes/DoE/High_Performance_Computing_tutorials.json new file mode 100644 index 00000000..2da730eb --- /dev/null +++ b/agency-indexes/DoE/High_Performance_Computing_tutorials.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-24", + "metadataLastUpdated": "2021-02-24" + }, + "description": "This source code includes tutorials targeting a general audience that will help users to use high performance computing environments and systems at Livermore Computing and beyond. Examples of HPC tools covered include mpi and posix. Tutorials may include source code demonstrating usage.", + "laborHours": 0.0, + "languages": [], + "name": "High Performance Computing tutorials", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/HPC-Tutorials", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High_Performance_Conjugate_Gradient_Benchmark__HPCG_.json b/agency-indexes/DoE/High_Performance_Conjugate_Gradient_Benchmark__HPCG_.json new file mode 100644 index 00000000..838db6d8 --- /dev/null +++ b/agency-indexes/DoE/High_Performance_Conjugate_Gradient_Benchmark__HPCG_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "HPCG is a software package that performs a fixed number of multigrid preconditioned (using a symmetric Gauss-Seidel smoother) conjugate gradient (PCG) iterations using double precision (64 bit) floating point values.", + "laborHours": 2629.6, + "languages": [], + "name": "High Performance Conjugate Gradient Benchmark (HPCG)", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/kokkos/hpcg/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/hpcg", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High_Performance_Simulator__HPSim.json b/agency-indexes/DoE/High_Performance_Simulator__HPSim.json new file mode 100644 index 00000000..8cdd00d7 --- /dev/null +++ b/agency-indexes/DoE/High_Performance_Simulator__HPSim.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "HPSim is a GPU-accelerated online multi-particle beam dynamics simulation tool for ion linacs. It was originally developed for use on the Los Alamos 800-MeV proton linac with the goal of providing a fast and accurate tool for realistic beam simulations of the actual operating linac. It runs on a GPU equipped workstation. The simulation parameters mirror those of the actual accelerator and can be manipulated through Python scripts in an offline mode or track them\nwhen connected via EPICS in an online mode.", + "laborHours": 33272.8, + "languages": [], + "name": "High Performance Simulator (HPSim", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/enchuanhuang/hpsim", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High_Speed_Digitizer_Firmware__HSD__v1.0.json b/agency-indexes/DoE/High_Speed_Digitizer_Firmware__HSD__v1.0.json new file mode 100644 index 00000000..3817df5b --- /dev/null +++ b/agency-indexes/DoE/High_Speed_Digitizer_Firmware__HSD__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-06", + "metadataLastUpdated": "2023-07-06" + }, + "description": "The High Speed Digitizer firmware is an FPGA gateware and embedded firmware that run on evaluation kits (either Xilinx ZCU111 or Xilinx ZCU208 ) that digitizes signals up to 4GSPS and 4GHz analog bandwidth, which can be synchronized to the accelerator timing system, providing synchronous sampling frequency/phase digitization. In addition to these capabilities, a proof of concept for a beam position monitor is also present, providing an envelope detection algorithm capable of determining the transverse beam position for an electron circular accelerator, such as ALS/ALS-U.", + "laborHours": 0.0, + "languages": [], + "name": "High Speed Digitizer Firmware (HSD) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/LBNL-Digitizers", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High_Velocity_AI_Cache__HVAC_.json b/agency-indexes/DoE/High_Velocity_AI_Cache__HVAC_.json new file mode 100644 index 00000000..4389e63a --- /dev/null +++ b/agency-indexes/DoE/High_Velocity_AI_Cache__HVAC_.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "khana@ornl.gov" + }, + "date": { + "created": "2025-03-06", + "metadataLastUpdated": "2025-03-07" + }, + "description": "HVAC is a high-performance caching system designed for large-scale AI training workloads.", + "laborHours": 684.0, + "languages": [ + "C++", + "C" + ], + "name": "High Velocity AI Cache (HVAC)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/akhanaornl/hvac.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/High_fidelity_OT_Decoy_Profiles_Services.json b/agency-indexes/DoE/High_fidelity_OT_Decoy_Profiles_Services.json new file mode 100644 index 00000000..2db6abd0 --- /dev/null +++ b/agency-indexes/DoE/High_fidelity_OT_Decoy_Profiles_Services.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-04-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A creation of packages of metadata, data, and communication networks services that are designed to highly accurately mimic the behavior of specific models of control system devices such as relays, PLCs, RTUs, etc. The inventive nature is the packaging of these features together such that they mimic specific models of equipment where existing approaches\nfocus on generalized control devices.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "High fidelity OT Decoy Profiles/Services", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/High_resolution_hydrologic_routing_with_machine_learning_assisted_waterbody_classification.json b/agency-indexes/DoE/High_resolution_hydrologic_routing_with_machine_learning_assisted_waterbody_classification.json new file mode 100644 index 00000000..044c07a3 --- /dev/null +++ b/agency-indexes/DoE/High_resolution_hydrologic_routing_with_machine_learning_assisted_waterbody_classification.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This software contains the code for a machine learning-based pipeline for creating persistent waterbody databases used in hydrologic routing. It consists of three components, 1) a PyTorch library (TorchWBType) for classifying/labeling arbitrary waterbodies into lakes and non-lakes, 2) a batch processing orchestrator (wbextractor) for delineating waterbodies from remote sensing imagery, and 3) graphing/analysis scripts for reproducing the plots in an associated journal article (LA-UR-24-22590).", + "laborHours": 1140.0, + "languages": [], + "name": "High resolution hydrologic routing with machine learning assisted waterbody classification", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VeinsOfTheEarth/waterbody_classification_ms", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Highly_Asynchronous_VisitOr_Queue_Graph_Toolkit.json b/agency-indexes/DoE/Highly_Asynchronous_VisitOr_Queue_Graph_Toolkit.json new file mode 100644 index 00000000..f70943e8 --- /dev/null +++ b/agency-indexes/DoE/Highly_Asynchronous_VisitOr_Queue_Graph_Toolkit.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "HavoqGT (Highly Asynchronous Visitor Queue Graph Toolkit) is a framework for expressing\nasynchronous vertex-centric graph algorithms, and executing them on High Performance Computing (HPC) systems. It provides a vertex 'visitor' interface, where actions are defined at an individual vertex level, and contains a suite of classic graph algorithms. HavoqGT is capable of processing large graphs stored in NVRAM (SSDs) using a memory mapped interface.\n", + "laborHours": 15139.2, + "languages": [], + "name": "Highly Asynchronous Visitor Queue Graph Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/havoqgt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Highly_Extensible_X-ray_Diffraction_Toolkit.json b/agency-indexes/DoE/Highly_Extensible_X-ray_Diffraction_Toolkit.json new file mode 100644 index 00000000..79ba6647 --- /dev/null +++ b/agency-indexes/DoE/Highly_Extensible_X-ray_Diffraction_Toolkit.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-14", + "metadataLastUpdated": "2021-12-14" + }, + "description": "This code has been previous released as open source under LLNL-CODE-529294. The HEXRD program comprises a library of X-ray diffraction analysis tools and a stand-alone GUI application. While there are many software packages that provide similar capabilities, HEXRD was designed to provide an extremely flexible and extensible basis for describing a broad array of X-ray diffraction instruments; this includes both mono- and poly-chromatic modalities as well as poly- and single-crystal samples. The high-level objects include Material: an abstraction for defining crystalline materials, including unit cell parameters and anisotropic elastic moduli Imageseries: an interface for series of diffraction images containing one or more frames, including provisions for metadata. Instrument: an abstraction of an X-ray diffraction instrument including support for the definition of multiple detector elements as well as powder, Laue, and mono-chromatic single/multi-grain diffraction analysis modalities (including attendant calibration routines). The hexrdgui package is a standalone PySide2/Qt5 GUI built on top of hexrd. The 0.8.1 release includes various bug fixes as well as some new functionality in the GUI, including: o Enhancements to the import tools for LLNL diffraction instruemtns (PXRDIP and TARDIS) o The ability to save 1-d LeBail fits of integrated diffraction spectra.", + "laborHours": 0.0, + "languages": [], + "name": "Highly Extensible X-ray Diffraction Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HEXRD/hexrd", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.8.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HipGISAXS.json b/agency-indexes/DoE/HipGISAXS.json new file mode 100644 index 00000000..ba9bedbb --- /dev/null +++ b/agency-indexes/DoE/HipGISAXS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-08", + "metadataLastUpdated": "2019-09-23" + }, + "description": "Implementation of a flexible Grazing Incidence Small-Angle Scattering (GISAXS). Simulation code based on the Distorted Wave Born Approximation (DWBA) theory that effectively utilizes the parallel processing power provided by graphic processors and multicore processors. This constitutes a handy tool for experimentalists facing a massive flux of data, allowing them to accurately simulate the GISAXS process and analyze the produced data. The software computes the diffraction image for any given super position of custom shapes or morphologies in a user-defined region of the reciprocal space for all possible grazing incidence angles and in-plane sample rotations. This flexibility then allows to easily tackle a wide range of possible sample structures such as nanoparticles o top of or embedded in a substrate or a multilayered structure. In cases where the sample displays regions of significant refractive index contrast, an algorithm has been implemented to perform a slicing of the sample along the vertical direction and compute the averaging refractive index profile to be used as the reference geometry of the unpertubed system. Preliminary tests show good agreement with experimental data for a variety of commonly encountered nanostructures.", + "laborHours": 20033.6, + "languages": [], + "name": "HipGISAXS", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/hipgisaxs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HistogramFreeMUCA.json b/agency-indexes/DoE/HistogramFreeMUCA.json new file mode 100644 index 00000000..fc16fc5d --- /dev/null +++ b/agency-indexes/DoE/HistogramFreeMUCA.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This program implements a novel algorithm to obtain the density of state of a physical system, expanded in a chosen basis set. Unlike existing algorithms that return the density of states as a numerical array, this algorithm avoids binning of a continuous variable and is able to express the density of states in an analytical form. It is thus suitable for the study of the statistical mechanics and thermodynamic properties of physical systems where the density of a continuous state variable is of interest. The new algorithm presented here is a special reweighting method in classical Monte Carlo approaches. In particular, it can be regarded as a descendant and a hybrid method closely related to the multicanonical method and Wang--Landau sampling.", + "laborHours": 106.4, + "languages": [ + "Python3" + ], + "name": "HistogramFreeMUCA", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yingwaili/HistogramFreeMUCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hod_Carrier_.json b/agency-indexes/DoE/Hod_Carrier_.json new file mode 100644 index 00000000..0c3d7ff1 --- /dev/null +++ b/agency-indexes/DoE/Hod_Carrier_.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2023-08-14" + }, + "description": "SAND2023-06720O\nHod Carrier is a simple proof-of-concept library for moving data from host to NVIDIA BlueField device memory using remote direct memory access. The Hod Carrier software also facilitates research activities related to the potential uses of NVIDIA BlueField data processing unit devices. Using well-established technologies (e.g., RDMA over Infiniband), it will move data from the host to the data processing unit\u2019s memory. This software is a middleware utility for moving data without regard to its semantic meaning. Its operation is fundamentally unaffected by storage allocation. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python", + "bash shell scripts" + ], + "name": "Hod Carrier ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hod-carrier", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Holotomography_Phase-Retrieval.json b/agency-indexes/DoE/Holotomography_Phase-Retrieval.json new file mode 100644 index 00000000..c7a14d69 --- /dev/null +++ b/agency-indexes/DoE/Holotomography_Phase-Retrieval.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-13", + "metadataLastUpdated": "2021-10-05" + }, + "description": "Holotomography is a non-destructive x-ray imaging technique which allows to visualize the interior morphology of object without damaging them. It is similar to x-ray computed tomography (CT), but unlike conventional CT, which is based on the attenuation of x-rays passing through the object, holotomography exploits the phase shift caused by the sample. This phase-contrast imaging allows to increase image contrast by recovering refractive index of materials and is proven to be more sensitive to density variations than conventional absorption-based X-ray imaging when applied to low-Z materials. In holotomography, the phase is retrieved by measuring the variations in intensity of the object at different sample to detector distances. Several algorithms exist to perform this task such as, contrast transfer function (CTF), transport of intensity equation (TIE), and a mixed approach which combine both TIE and CTF.", + "laborHours": 349.6, + "languages": [], + "name": "Holotomography Phase-Retrieval", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jbforien/phaseCT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Home_Energy_Management_System_-_VOLTTRON_Integration.json b/agency-indexes/DoE/Home_Energy_Management_System_-_VOLTTRON_Integration.json new file mode 100644 index 00000000..5b765253 --- /dev/null +++ b/agency-indexes/DoE/Home_Energy_Management_System_-_VOLTTRON_Integration.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "In most Home Energy Management Systems (HEMS) available in the market, different devices running different communication protocols cannot interact with each other and exchange information. As a result of this integration, the information about different devices running different communication protocol can be accessible by other agents and devices running on VOLTTRON platform. The integration process can be used by any HEMS available in the market regardless of the programming language they use. If the existing HEMS provides an Application Programming Interface (API) based on the RESTFul architecture, that API can be used for integration. Our candidate HEMS in this project is home-assistant (Hass). An agent is implemented which can communicate with the Hass API and receives information about the devices loaded on the API. The agent publishes the information it receives on the VOLTTRON message bus so other agents can have access to this information. On the other side, for each type of devices, an agent is implemented such as Climate Agent, Lock Agent, Switch Agent, Light Agent, etc. Each of these agents is subscribed to the messages published on the message bus about their associated devices. These agents can also change the status of the devices by sending appropriate service calls to the API. Other agents and services on the platform can also access this information and coordinate their decision-making process based on this information.", + "laborHours": 109880.8, + "name": "Home Energy Management System - VOLTTRON Integration", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/VOLTTRON/volttron-applications/blob/master/ornl/HomeAssistant-VOLTTRON-Integration-Agents/License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron-applications", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Home_Energy_Saver_v3__website__and_APIs.json b/agency-indexes/DoE/Home_Energy_Saver_v3__website__and_APIs.json new file mode 100644 index 00000000..ee76519b --- /dev/null +++ b/agency-indexes/DoE/Home_Energy_Saver_v3__website__and_APIs.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2019-04-22" + }, + "description": "A web-based residential energy calculator with APIs that run two LBNL websites: http://hes.lbl.gov and http://hespro.lbl.gov. Provide customized estimates of residential energy use, energy bills, and CO2 emissions, based on building description information provided by the user. Energy use is estimated by end-use and device, using engineering models developed at LBNL. Space heating and cooling use is based on the DOE-2.1 E building simulation model. Other end-uses (water heating, appliances, lighting, and miscellaneous equipment) are based on engineering models developed by LBNL. Users can estimate their household carbon footprint and compare it to average values for their neighborhood and other regions, displayed using the Google Maps API. Energy bills can be calculated using either average energy price data or actual utility tariffs. The HES software also includes extensive default input for required user inputs. Hardware req.: Multi-platform; Type of files: Source code, installation instructions other; programmer documentation; user manual; electronic format.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 181138.4, + "languages": [], + "name": "Home Energy Saver v3 (website) and APIs", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Homogeneous_models_for_biomass_pyrolysis.json b/agency-indexes/DoE/Homogeneous_models_for_biomass_pyrolysis.json new file mode 100644 index 00000000..95136e35 --- /dev/null +++ b/agency-indexes/DoE/Homogeneous_models_for_biomass_pyrolysis.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "albertop@iastate.edu" + }, + "date": { + "created": "2022-03-30", + "metadataLastUpdated": "2022-03-31" + }, + "description": "Implementation of homogeneous models (PFR and PaSR for applications to biomass pyrolysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Homogeneous models for biomass pyrolysis", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Biomass-Autothermal-Pyrolysis/HomogeneousModels", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HoneProject_Linux-Sensor.json b/agency-indexes/DoE/HoneProject_Linux-Sensor.json new file mode 100644 index 00000000..5bf3445c --- /dev/null +++ b/agency-indexes/DoE/HoneProject_Linux-Sensor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Correlate packets to the responsible processes in Linux systems. Diagnose connections by adding process information.", + "laborHours": 0.0, + "languages": [], + "name": "HoneProject/Linux-Sensor", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HoneProject/Linux-Sensor", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HopPyBar.json b/agency-indexes/DoE/HopPyBar.json new file mode 100644 index 00000000..6e7efe61 --- /dev/null +++ b/agency-indexes/DoE/HopPyBar.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "HopPyBar is a python program to import, analyze, and export split-Hopkinson pressure bar (SHPB, also known as Kolsky bar) data. Traditional analysis offers a black box approach, where input data is converted to analyzed output by performing a series of calculations without user involvement. This program serves as a developmental platform to \"white box\" the data analysis process. Data streams can be captured (in-situ) to enable advanced or unconventional analyses, statistics, and comparisons. Additionally, the program is geared towards the standardized forms of input and output used at LANL to streamline analysis, but the open nature of the program makes additional input/output schemes straightforward to add. General workflow will import SHPB data in one of a number of formats, identify relevant portions of data signals, and convert to stress-strain-strain rate to show material behavior as a function of dynamic testing.", + "laborHours": 0.0, + "languages": [], + "name": "HopPyBar", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/HopPyBar", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hop_Decorate.json b/agency-indexes/DoE/Hop_Decorate.json new file mode 100644 index 00000000..b9ee4322 --- /dev/null +++ b/agency-indexes/DoE/Hop_Decorate.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "Hop-Decorate is a python code developed as part of the LDRD funded project: 20220063DR: Accelerated Dynamics Across Computational and Physical Scales with the aim of using molecular dynamics and statics techniques to generate atomistic databases of defect transport in chemically complex materials using automated energy barrier calculations.", + "laborHours": 1109.6, + "languages": [], + "name": "Hop Decorate", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Hop-Decorate", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HostDesigner,_Version_3.json b/agency-indexes/DoE/HostDesigner,_Version_3.json new file mode 100644 index 00000000..42881a47 --- /dev/null +++ b/agency-indexes/DoE/HostDesigner,_Version_3.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "joiner@ameslab.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "HostDesigner is a computer-aided molecular design code that enables the general application of de novo structure-based methods to problems in chemistry and material science. Its purpose is to identify organic molecules with 3D structures that match user-input specifications. To accomplish this, the code connects chemical fragments to build millions of potential molecules, evaluates the resulting structures based on geometric constraints, and outputs a rank-ordered list of candidates. Example applications include the design of metal ion sequestering agents for use in separations processes, molecules that form self-assembled nanoscale containers, and molecular building blocks for metal-organic frameworks.", + "homepageURL": "http://sourceforge.net/projects/hostdesigner-v3-0", + "laborHours": 0.0, + "name": "HostDesigner, Version 3", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://sourceforge.net/projects/hostdesigner-v3-0", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hot,_Cold,_or_Just_Right?_Model_Predictive_Controller__HCJR_MPC__v0.1.0.json b/agency-indexes/DoE/Hot,_Cold,_or_Just_Right?_Model_Predictive_Controller__HCJR_MPC__v0.1.0.json new file mode 100644 index 00000000..99f4c736 --- /dev/null +++ b/agency-indexes/DoE/Hot,_Cold,_or_Just_Right?_Model_Predictive_Controller__HCJR_MPC__v0.1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-02-25", + "metadataLastUpdated": "2021-02-25" + }, + "description": "The project seeks to develop new sensor and control technologies that will improve occupant thermal comfort and reduce cooling energy consumption in commercial buildings by minimizing overcooling.", + "laborHours": 0.0, + "languages": [], + "name": "Hot, Cold, or Just Right? Model Predictive Controller (HCJR MPC) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/hcjr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hpc_Natural_Language_Understanding__nlu__Dataset.json b/agency-indexes/DoE/Hpc_Natural_Language_Understanding__nlu__Dataset.json new file mode 100644 index 00000000..9c6e0744 --- /dev/null +++ b/agency-indexes/DoE/Hpc_Natural_Language_Understanding__nlu__Dataset.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-07-12", + "metadataLastUpdated": "2023-07-12" + }, + "description": "This code provides natural language annotation and labels for multiple activities in high performance. The purpose is to enable machine learning for natural language processing algorithms with high performance computing systems. ", + "laborHours": 0.0, + "languages": [ + "python3", + "yml" + ], + "name": "Hpc Natural Language Understanding (nlu) Dataset", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HPC_Natural_Language_Understanding_-NLU-_Dataset", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Human_metrics_exploration__HCTPM:_Human_Centered_Transportation_Performance_Metrics__.json b/agency-indexes/DoE/Human_metrics_exploration__HCTPM:_Human_Centered_Transportation_Performance_Metrics__.json new file mode 100644 index 00000000..aa75192b --- /dev/null +++ b/agency-indexes/DoE/Human_metrics_exploration__HCTPM:_Human_Centered_Transportation_Performance_Metrics__.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-02-16", + "metadataLastUpdated": "2022-02-16" + }, + "description": "This is a set of notebooks to support exploring human centered metrics. You can explore the metrics interactively using the Interactive_Metrics juypter notebook.", + "laborHours": 0.0, + "languages": [ + "Python", + "JUPYTER" + ], + "name": "Human metrics exploration (HCTPM: Human Centered Transportation Performance Metrics) ", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/human-metrics-explore", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HunStat_v4.10.json b/agency-indexes/DoE/HunStat_v4.10.json new file mode 100644 index 00000000..81289ffc --- /dev/null +++ b/agency-indexes/DoE/HunStat_v4.10.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "kerteszv@ornl.gov" + }, + "date": { + "created": "2023-04-19", + "metadataLastUpdated": "2023-04-19" + }, + "description": "Support for the following electrochemical techniques: \u00b7 cyclic voltammogram (CV) \u00b7 linear sweep voltammogram (LSV) \u00b7 differential pulse voltammogram (DPV) \u00b7 chronoamperometry (CA) Specific application: low-cost DIY potentiostat, demonstrating electrochemistry in the educational sector", + "homepageURL": "https://u.pcloud.link/publink/show?code=XZyeQqVZWfpzv3qm0HJ40WFUBDEmzhUcJfP7", + "laborHours": 0.0, + "languages": [ + "Delphi/Object Pascal" + ], + "name": "HunStat v4.10", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://u.pcloud.link/publink/show?code=XZyeQqVZWfpzv3qm0HJ40WFUBDEmzhUcJfP7", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "4.10" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Huntsman.json b/agency-indexes/DoE/Huntsman.json new file mode 100644 index 00000000..69b46323 --- /dev/null +++ b/agency-indexes/DoE/Huntsman.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2022-10-05" + }, + "description": "SAND2021-15137 O\nThe Huntsman library includes two main components: WebComms, which enhances Apache's HTTP Client by providing commonly needed capabilities in this domain to simplify web access as well as TwitterComms, which provides enhancements to the Twitter4J library for Twitter access. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Huntsman", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hy2.0-eos-lasso_v.0.0.0.json b/agency-indexes/DoE/Hy2.0-eos-lasso_v.0.0.0.json new file mode 100644 index 00000000..470a1063 --- /dev/null +++ b/agency-indexes/DoE/Hy2.0-eos-lasso_v.0.0.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00777O\nHy2.0-eos-lasso is a software tool that derives an equation of state (EOS) using the compound energy formalism (CEF) with LASSO-based parameter fitting. It uses experimental and density functional theory (DFT) data to derive accurate EOS parameters. This tool is designed for users familiar with CEF and aims to facilitate reproducibility in academic research by meeting open-sourcing requirements. Hy2.0-eos-lasso addresses fundamental materials modeling challenges by providing a robust method for EOS parameter fitting. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Hy2.0-eos-lasso v.0.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HyKKT.json b/agency-indexes/DoE/HyKKT.json new file mode 100644 index 00000000..0641d5fd --- /dev/null +++ b/agency-indexes/DoE/HyKKT.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "peless@ornl.gov" + }, + "date": { + "created": "2022-12-05", + "metadataLastUpdated": "2023-02-16" + }, + "description": "HyKKT (pronounced as \"hiked\") is a package for solving systems of linear equations of Karush-Kuhn-Tucker (KKT) form, which typically arise in optimization problems, such as optimal power flow analysis. HyKKT uses Cholesky instead of LDL^T factorization and solves the general KKT system to a desired numerical precision via block reduction and conjugate gradient on the Schur complement. Such implementation is more suitable for implementation on graphic processing units (GPUs).", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "HyKKT", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/hykkt", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HyRAM+__Hydrogen_Plus_Other_Alternative_Fuels_Risk_Assessment_Models__v.4.0.json b/agency-indexes/DoE/HyRAM+__Hydrogen_Plus_Other_Alternative_Fuels_Risk_Assessment_Models__v.4.0.json new file mode 100644 index 00000000..d7da21d0 --- /dev/null +++ b/agency-indexes/DoE/HyRAM+__Hydrogen_Plus_Other_Alternative_Fuels_Risk_Assessment_Models__v.4.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-11-03", + "metadataLastUpdated": "2021-11-03" + }, + "description": "HyRAM+ is a software toolkit for conducting quantitative risk assessment (QRA) and consequence modeling for hydrogen and other alternative fuels infrastructure and transportation systems. HyRAM+ contains validated, simplified release behavior models, a standardized QRA approach, and engineering models and generic data relevant to hydrogen installations. HyRAM (hydrogen-only) versions 1.0 to 3.1 were developed by Sandia for the U.S. Department of Energy (DOE) Hydrogen and Fuel Cell Technologies Office (HFTO). The U.S. DOE Vehicle Technologies Office (VTO) and U.S. Department of Transportation (DOT) Pipeline and Hazardous Material Safety Administration (PHMSA) contributed to the development of HyRAM+ version 4.0 regarding the addition of methane (natural gas) and propane models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10862 O", + "laborHours": 21508.0, + "languages": [], + "name": "HyRAM+ (Hydrogen Plus Other Alternative Fuels Risk Assessment Models) v.4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hyram", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 4.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HyRAM+__Hydrogen_Plus_Other_Alternative_Fuels_Risk_Assessment_Models__v.4.1.1.json b/agency-indexes/DoE/HyRAM+__Hydrogen_Plus_Other_Alternative_Fuels_Risk_Assessment_Models__v.4.1.1.json new file mode 100644 index 00000000..7690a5b7 --- /dev/null +++ b/agency-indexes/DoE/HyRAM+__Hydrogen_Plus_Other_Alternative_Fuels_Risk_Assessment_Models__v.4.1.1.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-09-30", + "metadataLastUpdated": "2022-09-30" + }, + "description": "HyRAM+ is a software toolkit for conducting quantitative risk assessment (QRA) and consequence modeling for hydrogen and other alternative fuels infrastructure and transportation systems. HyRAM+ contains validated, simplified release behavior models, a standardized QRA approach, and engineering models and generic data relevant to hydrogen installations. HyRAM (hydrogen-only) versions 1.0 to 3.1 were developed by Sandia for the U.S. Department of Energy (DOE) Hydrogen and Fuel Cell Technologies Office (HFTO). The U.S. DOE Vehicle Technologies Office (VTO) and U.S. Department of Transportation (DOT) Pipeline and Hazardous Material Safety Administration (PHMSA) contributed to the development of HyRAM+ version 4.0 regarding the addition of methane (natural gas) and propane models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10862 O", + "laborHours": 21508.0, + "languages": [ + "C#", + "Python" + ], + "name": "HyRAM+ (Hydrogen Plus Other Alternative Fuels Risk Assessment Models) v.4.1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hyram", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 4.1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HyRAM__Hydrogen_Risk_Assessment_Models__v._2.0.json b/agency-indexes/DoE/HyRAM__Hydrogen_Risk_Assessment_Models__v._2.0.json new file mode 100644 index 00000000..a54bdd59 --- /dev/null +++ b/agency-indexes/DoE/HyRAM__Hydrogen_Risk_Assessment_Models__v._2.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2020-06-15" + }, + "description": "HyRAM is a software toolkit for conducting quantitative risk assessment (QRA) and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM contains validated, simplified hydrogen behavior models, a standardized QRA approach, and engineering models and generic data relevant to hydrogen installations. HyRAM 1.0 was developed by Sandia National Laboratories for the U. S. Department of Energy.\nSAND2019-5270 M", + "laborHours": 21508.0, + "languages": [], + "name": "HyRAM (Hydrogen Risk Assessment Models) v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hyram", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hybrid-RL-MPC4CLR__Hybird-Reinforcement-Learning-Model-Predictive-Control-for-Reserve-Policy-Assisted-Critical-Load-Restoration-in-Distribution-Grids_.json b/agency-indexes/DoE/Hybrid-RL-MPC4CLR__Hybird-Reinforcement-Learning-Model-Predictive-Control-for-Reserve-Policy-Assisted-Critical-Load-Restoration-in-Distribution-Grids_.json new file mode 100644 index 00000000..3076ffa6 --- /dev/null +++ b/agency-indexes/DoE/Hybrid-RL-MPC4CLR__Hybird-Reinforcement-Learning-Model-Predictive-Control-for-Reserve-Policy-Assisted-Critical-Load-Restoration-in-Distribution-Grids_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-09-19" + }, + "description": "Hybrid-RL-MPC4CLR was developed as a hybrid controller for active distribution grid critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. The RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while the MPC models grid operations incorporating the RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. The developers formulated the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The software is developed using various software packages in Python. The MPC's optimal power flow (OPF) model is implemented using the Pyomo package, the RL simulation environment is implemented using the MPC simulation with various scenarios of renewable energy and load demand profiles and power outage beginning times, based on the OpenAI Gym framework. The RL agent training is performed using the RLlib Ray package. The RL algorithm is trained offline using historical forecasts of renewable generation and load demand profiles. Simulation analysis and performance tests are conducted using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "python" + ], + "name": "Hybrid-RL-MPC4CLR (Hybird-Reinforcement-Learning-Model-Predictive-Control-for-Reserve-Policy-Assisted-Critical-Load-Restoration-in-Distribution-Grids)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/hybrid-rl-mpc4clr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HybridBOSSE__Hybrid_Balance-of-System__BOS__Systems_Engineering_Model_.json b/agency-indexes/DoE/HybridBOSSE__Hybrid_Balance-of-System__BOS__Systems_Engineering_Model_.json new file mode 100644 index 00000000..66ca8f4a --- /dev/null +++ b/agency-indexes/DoE/HybridBOSSE__Hybrid_Balance-of-System__BOS__Systems_Engineering_Model_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-28", + "metadataLastUpdated": "2021-06-28" + }, + "description": "Hybrid Power Plants (HPPs) have the potential to increase the value of renewable energy systems and decrease their costs through shared development (e.g., permitting) and infrastructure (e.g., collection system). Prior work has identified potential cost savings and technical and economic performance improvements for solar plus storage plants. However, additional research is needed to understand cost drivers that are specific to hybrid wind plants. Here we analyze the potential for shared infrastructure cost savings at one type of hybrid plant: wind plus solar photovoltaic (PV). To perform this analysis, we developed a new open-source, Python-based cost modeling tool: the Hybrid Balance-of-System (BOS) Systems Engineering model (HybridBOSSE). HybridBOSSE is an extension of NREL's LandBOSSE tool.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HybridBOSSE (Hybrid Balance-of-System (BOS) Systems Engineering Model)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HybridBOSSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hybrid_Bioreactor_for_Enhanced_Mixing_Efficiency.json b/agency-indexes/DoE/Hybrid_Bioreactor_for_Enhanced_Mixing_Efficiency.json new file mode 100644 index 00000000..715b3113 --- /dev/null +++ b/agency-indexes/DoE/Hybrid_Bioreactor_for_Enhanced_Mixing_Efficiency.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-06-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "3D printable reactor base provides all of the mixing innovations needed to make excellent mixing reactors at any scale", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Hybrid Bioreactor for Enhanced Mixing Efficiency", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hybrid_Optimization_Parallel_Search_PACKage.json b/agency-indexes/DoE/Hybrid_Optimization_Parallel_Search_PACKage.json new file mode 100644 index 00000000..87d8852c --- /dev/null +++ b/agency-indexes/DoE/Hybrid_Optimization_Parallel_Search_PACKage.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "HOPSPACK is open source software for solving optimization problems without derivatives. Application problems may have a fully nonlinear objective function, bound constraints, and linear and nonlinear constraints. Problem variables may be continuous, integer-valued, or a mixture of both. The software provides a framework that supports any derivative-free type of solver algorithm. Through the framework, solvers request parallel function evaluation, which may use MPI (multiple machines) or multithreading (multiple processors/cores on one machine). The framework provides a Cache and Pending Cache of saved evaluations that reduces execution time and facilitates restarts. Solvers can dynamically create other algorithms to solve subproblems, a useful technique for handling multiple start points and integer-valued variables. HOPSPACK ships with the Generating Set Search (GSS) algorithm, developed at Sandia as part of the APPSPACK open source software project.", + "laborHours": 0.0, + "languages": [], + "name": "Hybrid Optimization Parallel Search PACKage", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hopspack", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hybrid_Optimization_and_Performance_Platform__HOPP_.json b/agency-indexes/DoE/Hybrid_Optimization_and_Performance_Platform__HOPP_.json new file mode 100644 index 00000000..7d8f3bdd --- /dev/null +++ b/agency-indexes/DoE/Hybrid_Optimization_and_Performance_Platform__HOPP_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "charles.tripp@nrel.gov" + }, + "date": { + "created": "2021-03-26", + "metadataLastUpdated": "2022-08-22" + }, + "description": "As part of NREL's Hybrid Energy Systems Research, this software assesses optimal designs for the deployment of utility-scale hybrid energy plants, particularly considering wind, solar and storage.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Hybrid Optimization and Performance Platform (HOPP)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/HOPP", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.0.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hybrid_Parallel_Contour_Trees,_Version_1.0.json b/agency-indexes/DoE/Hybrid_Parallel_Contour_Trees,_Version_1.0.json new file mode 100644 index 00000000..661ee834 --- /dev/null +++ b/agency-indexes/DoE/Hybrid_Parallel_Contour_Trees,_Version_1.0.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A common operation in scientific visualization is to compute and render a contour of a data set. Given a function of the form f : R^d -> R, a level set is defined as an inverse image f^-1(h) for an isovalue h, and a contour is a single connected component of a level set. The Reeb graph can then be defined to be the result of contracting each contour to a single point, and is well defined for Euclidean spaces or for general manifolds. For simple domains, the graph is guaranteed to be a tree, and is called the contour tree. Analysis can then be performed on the contour tree in order to identify isovalues of particular interest, based on various metrics, and render the corresponding contours, without having to know such isovalues a priori. This code is intended to be the first data-parallel algorithm for computing contour trees. Our implementation will use the portable data-parallel primitives provided by Nvidia\u2019s Thrust library, allowing us to compile our same code for both GPUs and multi-core CPUs. Native OpenMP and purely serial versions of the code will likely also be included. It will also be extended to provide a hybrid data-parallel / distributed algorithm, allowing scaling beyond a single GPU or CPU.", + "laborHours": 204652.8, + "name": "Hybrid Parallel Contour Trees, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.kitware.com/vtk/vtk-m/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk-m", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hybrid_Simulation_Framework.json b/agency-indexes/DoE/Hybrid_Simulation_Framework.json new file mode 100644 index 00000000..859a7a31 --- /dev/null +++ b/agency-indexes/DoE/Hybrid_Simulation_Framework.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-04-02", + "metadataLastUpdated": "2023-03-08" + }, + "description": "HYBRID is a modeling toolset to assess the economic viability of Nuclear-Renewable Integrated Energy Systems (N-R IES). The frameworks enabling this toolset are INL\u2019s RAVEN, its CashFlow plugin and the Modelica language. The toolset includes sample RAVEN workflows performing economic assessments. These workflows consist of: generation of stochastic time series and application of probabilistic analysis and optimization algorithms (RAVEN); a library of Modelica models representing the physical behavior of N-R IES; and the CashFlow plugin mapping physical performance to economic performance. The toolset allows assembling existing and new models such as nuclear reactors, renewable energy sources, energy storage, gas turbines, industrial processes, etc. into an N-R IES. The toolset workflows evaluate the dynamics of the N-R IES responding to stochastic conditions (electricity demand, price, etc.) and optimize the dispatch economics as well as N-R IES capacity planning.", + "laborHours": 0.0, + "languages": [], + "name": "Hybrid Simulation Framework", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HYBRID", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HydraGNN.json b/agency-indexes/DoE/HydraGNN.json new file mode 100644 index 00000000..18a6b012 --- /dev/null +++ b/agency-indexes/DoE/HydraGNN.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2021-10-19", + "metadataLastUpdated": "2021-10-19" + }, + "description": "Distributed PyTorch implementation of multi-headed graph convolutional neural networks", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HydraGNN", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/HydraGNN", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HydraGNN_2.0.json b/agency-indexes/DoE/HydraGNN_2.0.json new file mode 100644 index 00000000..7883d53b --- /dev/null +++ b/agency-indexes/DoE/HydraGNN_2.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2023-05-01", + "metadataLastUpdated": "2023-05-01" + }, + "description": "HydraGNN is an Oak Ridge National Laboratory (ORNL)-branded implementation of distributed multi-tasking graph neural networks that supports several scientific applications within the ORNL portfolio to support the US-DOE mission.\n\nNew or improved capabilities included in v2.0.0 release are as follows:\n\n1) Enhancement in message passing layers through class inheritance\n2) Adding transformation to ensure translation and rotation invariance\n3) Supporting various optimizers\n4) Atomic descriptors\n5) Integration with continuous CI test\n6) Distributed printouts and timers\n7) Profiling\n8) Support of ADIOS2 for scalable data loading\n9) Large-scale system support, including Summit (ORNL) and Perlmutter (NERSC)", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HydraGNN 2.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/HydraGNN/releases/tag/v2.0.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v2.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HydraGNN_v3.0.json b/agency-indexes/DoE/HydraGNN_v3.0.json new file mode 100644 index 00000000..d078e75b --- /dev/null +++ b/agency-indexes/DoE/HydraGNN_v3.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2024-01-31", + "metadataLastUpdated": "2024-01-31" + }, + "description": "New or improved capabilities included in v3.0 release are as follows:\n\n1. Enhancement in message passing layers through generalization of the class inheritance to enable the inclusion of a broader set of message passing policies\nInclusion of equivariant message passing layers from the original implementations of:\nSchNet (https://pubs.aip.org/aip/jcp/article/148/24/241722/962591/SchNet-A-deep-learning-architecture-for-molecules); DimeNet++ (https://arxiv.org/abs/2011.14115); EGNN models (https://arxiv.org/pdf/2102.09844.pdf)\n2. Restructuring of class inheritance for data management\n3. Support of DDStore https://github.com/ORNL/DDStore capabilities for improved distributed data parallelism on large volumes of data that cannot fit on intra-node memory capacities\n4. Large-scale system support for OLCF-Crusher and OLCF-Frontier", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "HydraGNN v3.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/HydraGNN/releases/tag/v3.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hydra_Network_Automatic_Configuration__Hydra_Autoconfig__v1.json b/agency-indexes/DoE/Hydra_Network_Automatic_Configuration__Hydra_Autoconfig__v1.json new file mode 100644 index 00000000..4d9f2d0d --- /dev/null +++ b/agency-indexes/DoE/Hydra_Network_Automatic_Configuration__Hydra_Autoconfig__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-08", + "metadataLastUpdated": "2021-05-13" + }, + "description": "Hydra Autoconfig is an algorithm and software program to automatically configure a resilient network of independent ASICs that are capable of being connected as a Hydra network. The Hydra network itself is described in an invention disclosure titled: \"Ad-Hoc Networks of Readout ASICs for Reliable Detector Instrumentation\" (2020-091). The Hydra Autoconfig software works by first configuring a Hydra node. Then it recursively builds a Hydra network by attempting to link to each available upstream node in succession, keeping links that are verified. It then repeats on each newly generated node until no possible links remain. Once it is so configured, a reliable Hydra network of ASICs remains that can be reconfigured later to respond to damage or malfunction of one or more of the constituent ASICs.", + "homepageURL": "https://sites.google.com/lbl.gov/hydra2020-132/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Hydra Network Automatic Configuration (Hydra Autoconfig) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/hydra2020-132/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/HydroWIRES-PNNL_fisch.json b/agency-indexes/DoE/HydroWIRES-PNNL_fisch.json new file mode 100644 index 00000000..61f3739d --- /dev/null +++ b/agency-indexes/DoE/HydroWIRES-PNNL_fisch.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-01-30", + "metadataLastUpdated": "2025-01-30" + }, + "description": "Forecast Informed Scheduler for Hydropower (FIScH)", + "laborHours": 304.0, + "languages": [], + "name": "HydroWIRES-PNNL/fisch", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HydroWIRES-PNNL/fisch", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hydro_+_Storage_Sizing_Tool.json b/agency-indexes/DoE/Hydro_+_Storage_Sizing_Tool.json new file mode 100644 index 00000000..7a75cb49 --- /dev/null +++ b/agency-indexes/DoE/Hydro_+_Storage_Sizing_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-02-18", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The Hydro + Storage Sizing Tool recommends battery sizes and configurations to maximize financial performance of a battery investment that is integrated with a hydropower plant for a facility participating in a competitive electricity market. While the tool is primarily designed for hydropower facilities, it also works with other forms of baseload and peaking generation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Hydro + Storage Sizing Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Hydro_Hybrids", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hydroboost.json b/agency-indexes/DoE/Hydroboost.json new file mode 100644 index 00000000..ecd6537e --- /dev/null +++ b/agency-indexes/DoE/Hydroboost.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-03-05", + "metadataLastUpdated": "2025-03-05" + }, + "description": "HydroBoost is the most realistic revenue optimization tool for the hybridization of hydropower and battery energy storage systems to date. The innovative representation of how operators actually schedule hydropower in practice results in more realistic predictions of revenue and operations. Unlike other optimization tools, HydroBoost generates forecast energy prices with uncertainty to use in the optimization. This allows HydroBoost to give users a range of potential revenue with an upper bound using the perfect foresight pricing and a lower bound using a naive persistence forecast model. Additional forecast can be generated and used in the optimization, such as additive models, random forest, and neural networks to give further insight into potential revenue. \n\nHydroBoost has been designed to be applicable for both run-of-river and reservoir storage sites. The primary focus is on the day-ahead market and requires year-long data with an hour time-step. All time-series input and constraints are contained in an Excel worksheet for convince. The user will run the forecasting generation first with a Python script to give the optimization model the necessary requirements. Next the optimization is ran using Julia and results are generated and stored into a directory as csv files.\n\nHydroBoost includes an additional module to generate figures based on the results of the optimization simulation. The results help analyze the results and users to draw insights into how the hydro and battery systems are operated and the revenue each is producing. Additionally, the difference between the perfect foresight model and models that include forecast can easily be inspected.", + "laborHours": 1322.4, + "languages": [ + "Julia", + "Python" + ], + "name": "Hydroboost", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HydroBoost", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hydrogen_Extremely_Low_Probability_of_Rupture_Version_1.json b/agency-indexes/DoE/Hydrogen_Extremely_Low_Probability_of_Rupture_Version_1.json new file mode 100644 index 00000000..6085ed59 --- /dev/null +++ b/agency-indexes/DoE/Hydrogen_Extremely_Low_Probability_of_Rupture_Version_1.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08511O\nThe Hydrogen Extremely Low Probability of Rupture (HELPR) software toolkit provides probabilistic fracture assessments of natural gas infrastructure for transporting hydrogen. Using probabilistic sampling and sensitivity analysis\u2014along with engineering fatigue and fracture mechanics\u2014 the software develops models that can predict structural integrity measures for natural gas pipelines under stress. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 7630.4, + "languages": [ + "Python", + "QML" + ], + "name": "Hydrogen Extremely Low Probability of Rupture Version 1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/helpr", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hydrogen_Hub_Systems_Analysis_and_Mapping_Tool__ParaCraft__v1.json b/agency-indexes/DoE/Hydrogen_Hub_Systems_Analysis_and_Mapping_Tool__ParaCraft__v1.json new file mode 100644 index 00000000..7e340af1 --- /dev/null +++ b/agency-indexes/DoE/Hydrogen_Hub_Systems_Analysis_and_Mapping_Tool__ParaCraft__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2025-02-05", + "metadataLastUpdated": "2025-02-05" + }, + "description": "A plug and play techno-economic analysis (TEA) and lifecycle assessment (LCA) tool was built that could incorporate new projects into the California ARCHES LLC Hydrogen hub, and generate results for the project, as well as the overall hub on an annual basis. The model was first constructed in Microsoft Excel and ArcGIS, but required labor intensive updating and manual decision making regarding the matching of hydrogen supplier and offtaker and estimation of transportation distances and utility sources. The project team converted the Excel model used for the ARCHES LLC hub conceptualization into a highly flexible and nearly completely automated R code. The R code runs the TEA and LCA, as well as provides mapping capabilities that automatically link projects by latitude and longitude to nearby utilities.", + "laborHours": 4484.0, + "languages": [], + "name": "Hydrogen Hub Systems Analysis and Mapping Tool (ParaCraft) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/calgem/Paracraft", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hydrogen_Permeation_Analysis_Tool.json b/agency-indexes/DoE/Hydrogen_Permeation_Analysis_Tool.json new file mode 100644 index 00000000..db6eb2f7 --- /dev/null +++ b/agency-indexes/DoE/Hydrogen_Permeation_Analysis_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-01-12", + "metadataLastUpdated": "2023-03-08" + }, + "description": "There is a rising need for the measurement and understanding of hydrogen transport properties in materials for the energy and transportation industries. The Hydrogen Permeation Analysis Tool (HyPAT) provides a user friendly interface for batch analysis of dynamic hydrogen permeation data to calculate the transport properties permeability, solubility, and diffusivity. A built in literature database provides an easy comparison to known values. A common method for measuring these hydrogen transport properties is dynamic pressure rise permeation experiments, for example, those done in the Static Gas Absorption and Permeation (SGAP) experiment at INL. Most laboratories develop individual, in-house codes for data analysis. HyPAT provides a platform that can be adopted by other user groups for such experimental analysis and significantly reduce personnel time spent performing data analysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Hydrogen Permeation Analysis Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HyPAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hydrogenerate:_Open_Source_Python_Tool_To_Estimate_Hydropower_Generation_Time-series.json b/agency-indexes/DoE/Hydrogenerate:_Open_Source_Python_Tool_To_Estimate_Hydropower_Generation_Time-series.json new file mode 100644 index 00000000..8c3bfa6b --- /dev/null +++ b/agency-indexes/DoE/Hydrogenerate:_Open_Source_Python_Tool_To_Estimate_Hydropower_Generation_Time-series.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-11-12", + "metadataLastUpdated": "2023-05-25" + }, + "description": "Hydropower is one of the most mature forms of renewable energy generation. The United States (US) has almost 103 GW of installed, with 80 GW of conventional generation and 23 GW of pumped hydropower [1]. Moreover, the potential for future development on Non-Powered Dams is up to 10 GW. With the US setting its goals to become carbon neutral [2], more renewable energy in the form of hydropower needs to be integrated with the grid. Currently, there are no publicly available tool that can estimate the hydropower potential for existing hydropower dams or other non-powered dams. The HydroGenerate is an open-source python library that has the capability of estimating hydropower generation based on flow rate either provided by the user or received from United States Geological Survey (USGS) water data services. The tool calculates the efficiency as a function of flow based on the turbine type either selected by the user or estimated based on the \u201chead\u201d provided by the user.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Hydrogenerate: Open Source Python Tool To Estimate Hydropower Generation Time-series", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/HydroGenerate", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "3.6 or newer" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hydropower_Biological_Evaluation_Tools.json b/agency-indexes/DoE/Hydropower_Biological_Evaluation_Tools.json new file mode 100644 index 00000000..96cd72e5 --- /dev/null +++ b/agency-indexes/DoE/Hydropower_Biological_Evaluation_Tools.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "This software is a set of analytical tools to evaluate the physical and biological performance of existing, refurbished, or newly installed conventional hydro-turbines nationwide where fish passage is a regulatory concern. The current version is based on information collected by the Sensor Fish. Future version will include other technologies. The tool set includes data acquisition, data processing, and biological response tools with applications to various turbine designs and other passage alternatives. The associated database is centralized, and can be accessed remotely. We have demonstrated its use for various applications including both turbines and spillways.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "MS" + ], + "name": "Hydropower Biological Evaluation Tools", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hydropower_Fleet_Intelligence.json b/agency-indexes/DoE/Hydropower_Fleet_Intelligence.json new file mode 100644 index 00000000..76b39fa5 --- /dev/null +++ b/agency-indexes/DoE/Hydropower_Fleet_Intelligence.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "foleymk@ornl.gov" + }, + "date": { + "created": "2024-03-07", + "metadataLastUpdated": "2024-03-12" + }, + "description": "The Hydropower Fleet Intelligence application can integrate hydropower facilities data sources to perform analyses on asset age, reliability and costs, as well as produce visualizations that combine time series data collected by mechanical component sensors with event history.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python", + "TypeScript" + ], + "name": "Hydropower Fleet Intelligence", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/HydroFleetIntel/blob/main/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/HydroFleetIntel", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hydropower_Modeling_Gap_Tools.json b/agency-indexes/DoE/Hydropower_Modeling_Gap_Tools.json new file mode 100644 index 00000000..fc4054cb --- /dev/null +++ b/agency-indexes/DoE/Hydropower_Modeling_Gap_Tools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The software manages a database of historical hydrology and power systems operations data and based on some newly developed algorithms helps generate and\ntranslate historical hydrology data into estimations of steady-state and dynamic model parameters based on user inputs of hydro conditions which can be imported to\nexisting power system simulators.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Hydropower Modeling Gap Tools", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hylia:_Time-Series_Library_for_Network_Operations__Hylia__v1.json b/agency-indexes/DoE/Hylia:_Time-Series_Library_for_Network_Operations__Hylia__v1.json new file mode 100644 index 00000000..17e461c9 --- /dev/null +++ b/agency-indexes/DoE/Hylia:_Time-Series_Library_for_Network_Operations__Hylia__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-02-25", + "metadataLastUpdated": "2021-05-17" + }, + "description": "The ability to analyze time-series data in network operations is critical to ensure optimal operations and management in wide area networks, sensor networks, and cloud networks. Hylia is a collection of multiple time-series prediction algorithms designed specifically to work with network monitoring data sets such as SNMP, NETFLOW and other monitoring data. It is designed to recognize these features and perform the extrapolation of the data.", + "laborHours": 0.0, + "languages": [], + "name": "Hylia: Time-Series Library for Network Operations (Hylia) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/hylia_networkprediction", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HypeEmb4Py.json b/agency-indexes/DoE/HypeEmb4Py.json new file mode 100644 index 00000000..3cfe805b --- /dev/null +++ b/agency-indexes/DoE/HypeEmb4Py.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-09-04", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This software performs parallel hyperbolic coordinate embedding of large scale undirected, fully connected graphs for quick and accurate computation of node pair distances. Each node on the graph is mapped to a coordinate in hyperbolic space, after which node pair distances can be computed almost instantaneously. The embedding requires a training set of node pair distances between a small set of fixed landmark nodes (nodes with the highest degree) and all other nodes. An LBFGS quasi-newton optimization is performed to create the embedding. LBFGS quasi-newton optimization is performed to create the embedding.SAND2019-12114 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 760.0, + "languages": [ + "Python", + "Shell" + ], + "name": "HypeEmb4Py", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HypeEmb4Py", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HyperHeadTail_v._1.0.json b/agency-indexes/DoE/HyperHeadTail_v._1.0.json new file mode 100644 index 00000000..9d5e93e4 --- /dev/null +++ b/agency-indexes/DoE/HyperHeadTail_v._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "HyperHeadTail is a streaming algorithm for estimating the degree distribution of a graph from a stream of edges using very small storage space. Our algorithm builds upon the HeadTail algorithm of Simpson, Comandur, and McGregor [14], but extends it to handle repeat edges and variable-length sliding time windows, making it suitable for application to real-world streams such as those generated by network traffic or other communication networks.", + "laborHours": 684.0, + "languages": [ + "C++, Python" + ], + "name": "HyperHeadTail v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/HyperHeadTail?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/HyperHeadTail", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HyperKube.json b/agency-indexes/DoE/HyperKube.json new file mode 100644 index 00000000..05449e75 --- /dev/null +++ b/agency-indexes/DoE/HyperKube.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "martins@ornl.gov" + }, + "date": { + "created": "2023-11-01", + "metadataLastUpdated": "2024-01-30" + }, + "description": "A kubernetes based pipeline for analyzing hyperspectral data", + "laborHours": 0.0, + "languages": [], + "name": "HyperKube", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/StantonMartin/hyperkube", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/HyperSpace.json b/agency-indexes/DoE/HyperSpace.json new file mode 100644 index 00000000..e5821054 --- /dev/null +++ b/agency-indexes/DoE/HyperSpace.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "Machine learning (ML) models often contain numerous hyperparameters, free parameters that must be set before the models can be trained. As the number of model hyperparameters increases, their optimization becomes significantly more challenging as we face a combinatorial increase in potential model configurations. Similarly, there is an increased chance that our models\u2019 hyperparameters interact in complex ways. HyperSpace allows a user to optimize complex machine learning algorithms based on their hyperparameters. HyperSpace works by parallelizing parameter search spaces, running Bayesian model based optimization (SMBO) over each of these spaces in parallel. It was designed to be as minimally invasive as possible such that very little change to existing code will be needed to get a user started.", + "laborHours": 1717.6, + "languages": [ + "Python 3" + ], + "name": "HyperSpace", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yngtodd/hyperspace", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hypercane.json b/agency-indexes/DoE/Hypercane.json new file mode 100644 index 00000000..22dbc578 --- /dev/null +++ b/agency-indexes/DoE/Hypercane.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-17", + "metadataLastUpdated": "2023-11-21" + }, + "description": "Automatically summarizing a collection of documents requires analyzing their features using various operations. Hypercane is a framework for building algorithms for sampling files from a collection. Sampling is a vital part of automatic summarization. Hypercane ties together many existing third-party libraries. These libraries include those for processing web resources, natural language processing for analyzing text and filtering documents, and machine learning for clustering summarization candidates. A user can run up to more than 70 operations on a corpus in the order of their choosing. Through these operations, they can create custom automatic summarization algorithms to help them process the corpus of their choice. Details of the algorithms possible with Hypercane are available in Jones 2021. Details of running Hypercane are available in Jones et al.; 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Hypercane", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/hypercane", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hyperparameter_Studies_for_Vision_Transformers_Trained_on_High-Fidelity_Simulations.json b/agency-indexes/DoE/Hyperparameter_Studies_for_Vision_Transformers_Trained_on_High-Fidelity_Simulations.json new file mode 100644 index 00000000..b4aa7215 --- /dev/null +++ b/agency-indexes/DoE/Hyperparameter_Studies_for_Vision_Transformers_Trained_on_High-Fidelity_Simulations.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This library is a collection of python modules that define, train, and analyze vision-transformer (ViT) machine learning models. The code implements, with mild modifications, ViT models that have been made publicly available through publication and GitHub code. The training data for these models is hydrodynamic simulation output in the form of numpy arrays. This library contains code to train these ViT models on the hydrodynamic simulation output with a variety of hyperparameters, and to compare the results of such models. Furthermore, the library contains definitions of simple convolutional neural network (CNN) machine learning architectures which can be trained on the same hydrodynamic simulation output. These are included as a reference point to compare the ViT models to. Additionally, the library includes trained ViT and CNN models and example input data for demonstration purposes. The code is based on the PyTorch python library.", + "laborHours": 2006.4, + "languages": [], + "name": "Hyperparameter Studies for Vision Transformers Trained on High-Fidelity Simulations", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/CNN-T2TViT-comparison", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Hyperspectral_Data_Approximation_by_Gaussian_Sigmoids.json b/agency-indexes/DoE/Hyperspectral_Data_Approximation_by_Gaussian_Sigmoids.json new file mode 100644 index 00000000..9ab1cb0c --- /dev/null +++ b/agency-indexes/DoE/Hyperspectral_Data_Approximation_by_Gaussian_Sigmoids.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-08-26", + "metadataLastUpdated": "2019-08-27" + }, + "description": "Finds LASSO fit coefficient values of hyperspectral data for a Gaussian sigmoid basis function collection using LARS (least angle regression) methodology on a provided vector of sensor wavelength bins.", + "laborHours": 212.8, + "languages": [], + "name": "Hyperspectral Data Approximation by Gaussian Sigmoids", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/hydags", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/I-JEDI__International_Jobs_and_Economic_Development_Impacts__[SWR-19-20].json b/agency-indexes/DoE/I-JEDI__International_Jobs_and_Economic_Development_Impacts__[SWR-19-20].json new file mode 100644 index 00000000..e878d631 --- /dev/null +++ b/agency-indexes/DoE/I-JEDI__International_Jobs_and_Economic_Development_Impacts__[SWR-19-20].json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-08-31", + "metadataLastUpdated": "2025-03-26" + }, + "description": "The International Jobs and Economic Development Impacts (I-JEDI) model is a free, online tool for analyzing the economic impacts of renewable energy development. The tool estimates the potential gross economic impacts of wind, solar, biomass and geothermal energy projects for a specific country.\n\nI-JEDI estimates the employment, earnings, gross domestic product, and output from the construction and operation of renewable energy projects and across the domestic supply chain. The model results include total economic impacts as well as impacts by industry (e.g., construction, manufacturing, banking services, etc.). This information helps align renewable energy action with key economic development goals. I-JEDI was developed through the USAID-NREL Partnership to support informed renewable energy decisions.", + "homepageURL": "https://www.i-jedi.org/scenario/start", + "laborHours": 0.0, + "languages": [], + "name": "I-JEDI (International Jobs and Economic Development Impacts) [SWR-19-20]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/disclaimer.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.i-jedi.org/scenario/start", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "version": "v.10" +} \ No newline at end of file diff --git a/agency-indexes/DoE/I-V_characterization_and_parameter_extraction_tool_[SWR-24-59].json b/agency-indexes/DoE/I-V_characterization_and_parameter_extraction_tool_[SWR-24-59].json new file mode 100644 index 00000000..cff95edd --- /dev/null +++ b/agency-indexes/DoE/I-V_characterization_and_parameter_extraction_tool_[SWR-24-59].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-05-29", + "metadataLastUpdated": "2024-05-29" + }, + "description": "GPT-crafted control software and graphical user interface for Keithley 2400 Source Measure Units and global optimization algorithm. It contains Numba-compatible self-adaptive differential evolution algorithm for optimization tasks.\n\nThis software is comprised of two repositories: \nhttps://github.com/NREL/Keithley_GPT\nhttps://github.com/NREL/DE", + "laborHours": 288.8, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "I-V characterization and parameter extraction tool [SWR-24-59]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IBSL__Interface_between_source_and_load__[SWR-21-81].json b/agency-indexes/DoE/IBSL__Interface_between_source_and_load__[SWR-21-81].json new file mode 100644 index 00000000..c67c4481 --- /dev/null +++ b/agency-indexes/DoE/IBSL__Interface_between_source_and_load__[SWR-21-81].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2023-07-07" + }, + "description": "Interfacing voltage source with a load and a current source with a sink are challenging. The model developed under this software is used to interface voltage source with a sink and a current source with the sink.", + "laborHours": 0.0, + "languages": [], + "name": "IBSL (Interface between source and load) [SWR-21-81]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/IBSL", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IBTopo.json b/agency-indexes/DoE/IBTopo.json new file mode 100644 index 00000000..cb2916de --- /dev/null +++ b/agency-indexes/DoE/IBTopo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "The IBTopo package contains a set of perl modules and a script that uses the modules to process network connectivity information.\n", + "laborHours": 304.0, + "languages": [], + "name": "IBTopo", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ibtopo", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ICITools_v1.0.json b/agency-indexes/DoE/ICITools_v1.0.json new file mode 100644 index 00000000..1da715ee --- /dev/null +++ b/agency-indexes/DoE/ICITools_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "Identification of cell state based on objective metrics is a fundamental problem in developmental biology. With the advent of fluorescent activated cell sorting (FACS), transcriptomics, and (more recently) single-cell RNA sequencing, it has become possible to profile mRNA abundance of all genes in individual cells or cell types. This transcriptomic information for cell types is often characteristic, and can be used to classify cell types for cells with unknown identity. Previously, an algorithm was developed using a Bayesian method to derive specificity scores for all genes across all known cell types, and then to use these scores to assign the most likely cell type for a new transcriptomic profile. ICITools implements this Index of Cell Identity algorithm as an R package, making the method more easily distributed. In addition, this package implements slight improvements on the previous implementation by adding parallelization, small enhancements in speed, and the ability to customize some aspects of the specificity score computation method. The package does not alter the underlying algorithm, nor the overall functionality of the original methods.", + "laborHours": 380.0, + "languages": [], + "name": "ICITools v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/b-coli/ICITools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IDB_Loader.json b/agency-indexes/DoE/IDB_Loader.json new file mode 100644 index 00000000..a600cf57 --- /dev/null +++ b/agency-indexes/DoE/IDB_Loader.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-31", + "metadataLastUpdated": "2024-07-31" + }, + "description": "SAND2024-08428O\nThe IDB Loader is a database designed to hold gamma spectra. IDB is a web-accessible database of reference gamma spectra for measuring uranium (U) and plutonium (Pu) isotopic composition. The database, developed by the International Atomic Energy Agency (IAEA), provides access to well-characterized groups of gamma spectra curated by international experts in gamma spectroscopy. It was created to promote sustainability and maintenance of software used to determine the isotopic abundances of U and Pu. The IDB Loader works by uploading one set of spectral data into an existing IDB. The Data Loader package includes documentation describing the IDB's table, the format of the spectral data, and a description of the loader program. The IDB is currently hosted by the IAEA at: https://nds.iaea.org/idb \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 4104.0, + "languages": [ + "Java" + ], + "name": "IDB Loader", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IDB_Loader", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IEEE_Short_Course_4:_Introduction_to_Machine_Learning.json b/agency-indexes/DoE/IEEE_Short_Course_4:_Introduction_to_Machine_Learning.json new file mode 100644 index 00000000..e003893f --- /dev/null +++ b/agency-indexes/DoE/IEEE_Short_Course_4:_Introduction_to_Machine_Learning.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "ghawalyjm@ornl.gov" + }, + "date": { + "created": "2023-01-18", + "metadataLastUpdated": "2023-01-18" + }, + "description": "Code accompanying the \"Introduction to Machine Learning\" short course for the 2022 IEEE NSS MIC RTSD conference.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "IEEE Short Course 4: Introduction to Machine Learning", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jghawaly/IEEE_Intro2ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IGCAPT.json b/agency-indexes/DoE/IGCAPT.json new file mode 100644 index 00000000..a8bcf003 --- /dev/null +++ b/agency-indexes/DoE/IGCAPT.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-07-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The IGCAPT allows electric utility personnel to perform a static analysis of their communications network supporting smart grid architectures from a network utilization and performance standpoint. IGCAPT is meant to be a \"first order\" planning tool - the tool will accommodate estimates and best available data alongside default settings, which the user can then improve over time.", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "IGCAPT", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/IGCAPT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IHT:_Tools_for_Computing_Insolation_Absorption_by_Particle_Laden_Flows.json b/agency-indexes/DoE/IHT:_Tools_for_Computing_Insolation_Absorption_by_Particle_Laden_Flows.json new file mode 100644 index 00000000..d3fdff08 --- /dev/null +++ b/agency-indexes/DoE/IHT:_Tools_for_Computing_Insolation_Absorption_by_Particle_Laden_Flows.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "INT is a toolkit for computing radiative heat exchange between particles. The algorithm is based on the the 'Photon Monte Carlo\" approach described by Wang and Modest and implemented as a library that can be interfaced with a variety of CFD codes to analyze radiative heat transfer in particle laden flows.", + "homepageURL": "https://www.nrel.gov/workingwithus/licensing.html", + "laborHours": 0.0, + "languages": [ + "FORTRAN" + ], + "name": "IHT: Tools for Computing Insolation Absorption by Particle Laden Flows", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/workingwithus/licensing.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/workingwithus/licensing.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/IIA_Incremental_Interval_Assignment.json b/agency-indexes/DoE/IIA_Incremental_Interval_Assignment.json new file mode 100644 index 00000000..0d5c75be --- /dev/null +++ b/agency-indexes/DoE/IIA_Incremental_Interval_Assignment.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2024-08-07" + }, + "description": "IIA is a solver for optimizing integer matrix problems Ax=b. It was developed to decide the number of mesh edges on model curves (intervals) for quad and hex meshing. Meshing schemes impose constraints ranging from the mild requirement (i.e. that any quad mesh must have an even number of edges on its boundary) to structured mapped patches where opposite sides of a rectangle must have exactly equal numbers of edges. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.\nSAND2020-13618 M", + "laborHours": 2004074.4, + "languages": [ + "C++" + ], + "name": "IIA Incremental Interval Assignment", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IntervalAssignment", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ILI_Code.json b/agency-indexes/DoE/ILI_Code.json new file mode 100644 index 00000000..cd53e017 --- /dev/null +++ b/agency-indexes/DoE/ILI_Code.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-10-27", + "metadataLastUpdated": "2022-10-27" + }, + "description": "This R code consists of three scripts, described below.\n1. ILI_LHC_sample.R The first script generate 10,000 samples from the total\nparameter space formed by the ranges of the following five parameters inputted\ninto the ILI model: transmission rate (beta), per capita rate of progress from\nexposed to infectious state (gamma_1), per capita rate of progress through initial\ninfectious state (gamma_2), per capita rate of progress through hospitalized state\n(gamma_3), and per capita rate of progress through non-hospitalized infectious\nstate (gamma_4). The output is LHS_samples.csv, for input into the global\nsensitivity script, ILI_SEIR.\n2. ILI_SEIR.R The second script solves a standard Susceptible-Exposed-Infected-\nRecovered (SEIR) model (a system of Ordinary Differential Equations (ODEs)),\nruns global sensitivity analyses, and generates plots showing the impact of the\ninput variables on the response variables for each virus.\n3. virus_sims.R The third script solves a standard Susceptible-Exposed-Infected-\nRecovered (SEIR) model (a system of Ordinary Differential Equations (ODEs)),\naimed at modeling outbreaks for five common upper respiratory viruses within a\ncontained population. The output of this code is an epidemic curve to show\ntiming and magnitude of the epidemic peak for each virus.\nNote: for all three scripts, the parameter values must be hard-coded by the user or the\noutput will not be accurate.", + "laborHours": 0.0, + "languages": [], + "name": "ILI Code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ILI", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IMG_Annotation_Pipeline__IMGAP__v5.1.13.json b/agency-indexes/DoE/IMG_Annotation_Pipeline__IMGAP__v5.1.13.json new file mode 100644 index 00000000..8c72b0f2 --- /dev/null +++ b/agency-indexes/DoE/IMG_Annotation_Pipeline__IMGAP__v5.1.13.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "The IMG Annotation Pipeline is a collection of Bash and Python scripts to control a workflow for structural and functional annotation of prokaryotic genomes, metagenomes, and metatranscriptomes. The bash scripts in general control the overall workflow and are wrappers around 3rd party executables (not included in repo) that predict features or functions. Whereas the Python scripts do post-processing of raw output in terms of filtering or format transformation and in some cases contain some logic for picking the correct predictions or resolving overlaps. The pipeline is tailored to produce results required by IMG (https://img.jgi.doe.gov/) and is executed on every dataset submitted to IMG via https://img.jgi.doe.gov/submit. These consist of internal genomes, metagenomes and metatranscriptomes sequenced and assembled at the JGI, as well as datasets submitted by external users (non-lab/JGI affiliates).", + "laborHours": 3556.8, + "languages": [], + "name": "IMG Annotation Pipeline (IMGAP) v5.1.13", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/img/img-pipelines/img-annotation-pipeline", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/IMIGO_Software_for_Lattice_Element_Error_Modeling_in_Accelerators.json b/agency-indexes/DoE/IMIGO_Software_for_Lattice_Element_Error_Modeling_in_Accelerators.json new file mode 100644 index 00000000..3e26bb3f --- /dev/null +++ b/agency-indexes/DoE/IMIGO_Software_for_Lattice_Element_Error_Modeling_in_Accelerators.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-09-21", + "metadataLastUpdated": "2018-09-21" + }, + "description": "This nonlinear program was developed from a nonlinear solver (called OASIS). During Phase I work, it was applied on a number of nonlinear-solver benchmarking problems and a few SLAC accelerator problems. By searching over only two optimization-control parameters, this Phase I work has enabled the development of a systematic procedure to facilitate the finding of a \"best-guessed\" global minimum solution for various types of problems with different size and complexity. This set of rules has been codified and has led to a versatile nonlinear program IMIGO.", + "homepageURL": "http://www.slac.stanford.edu/doecode/IMIGO_2011", + "laborHours": 167.2, + "languages": [], + "name": "IMIGO Software for Lattice Element Error Modeling in Accelerators", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.slac.stanford.edu/doecode/IMIGO_2011", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.slac.stanford.edu/doecode/IMIGO_2011", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/IMMM-SFA_cerf.json b/agency-indexes/DoE/IMMM-SFA_cerf.json new file mode 100644 index 00000000..c77f493b --- /dev/null +++ b/agency-indexes/DoE/IMMM-SFA_cerf.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Capacity Expansion Regional Feasibility (CERF) model", + "laborHours": 2538.4, + "languages": [], + "name": "IMMM-SFA/cerf", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/immm-sfa/cerf", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IMMM-SFA_gamut.json b/agency-indexes/DoE/IMMM-SFA_gamut.json new file mode 100644 index 00000000..0cb3eff2 --- /dev/null +++ b/agency-indexes/DoE/IMMM-SFA_gamut.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-03-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An R package to identify multi-sector teleconnection complexity", + "laborHours": 0.0, + "languages": [], + "name": "IMMM-SFA/gamut", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/gamut", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IMMM-SFA_horizon.json b/agency-indexes/DoE/IMMM-SFA_horizon.json new file mode 100644 index 00000000..0e41fe81 --- /dev/null +++ b/agency-indexes/DoE/IMMM-SFA_horizon.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-02-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A tool for inferring and analyzing forecast-guided dam and reservoir operations", + "laborHours": 410.4, + "languages": [], + "name": "IMMM-SFA/horizon", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/horizon", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IMMM-SFA_im3py.json b/agency-indexes/DoE/IMMM-SFA_im3py.json new file mode 100644 index 00000000..89f17bef --- /dev/null +++ b/agency-indexes/DoE/IMMM-SFA_im3py.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-05-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An IM3 template repository for Python projects that have time-steps", + "laborHours": 273.6, + "languages": [ + "Python" + ], + "name": "IMMM-SFA/im3py", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/im3py", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IMMM-SFA_proxymod.json b/agency-indexes/DoE/IMMM-SFA_proxymod.json new file mode 100644 index 00000000..d0bc82ed --- /dev/null +++ b/agency-indexes/DoE/IMMM-SFA_proxymod.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": 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"metadataLastUpdated": "2024-06-18" + }, + "description": "Generates new temperature set point schedules from base schedules. The software provides a systematic, automatic method to generate temperature setpoint schedules from a base schedule and a small set of modeling parameters. The software will be open-sourced, and can easily be accessed by energy modelers.", + "laborHours": 0.0, + "languages": [], + "name": "IMMM-SFA/tempset", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/tempset", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IMMM-SFA_wm.json b/agency-indexes/DoE/IMMM-SFA_wm.json new file mode 100644 index 00000000..ba5b536b --- /dev/null +++ b/agency-indexes/DoE/IMMM-SFA_wm.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MOSART-WM - a large scale water management model", + "laborHours": 1322.4, + "languages": [], + "name": "IMMM-SFA/wm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/wm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IMS_-_MS_Data_Extractor.json b/agency-indexes/DoE/IMS_-_MS_Data_Extractor.json new file mode 100644 index 00000000..84a83ad0 --- /dev/null +++ b/agency-indexes/DoE/IMS_-_MS_Data_Extractor.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "An automated drift time extraction and computed associated collision cross section software tool for small molecule analysis with ion mobility spectrometry-mass spectrometry (IMS-MS). The software automatically extracts drift times and computes associated collision cross sections for small molecules analyzed using ion mobility spectrometry-mass spectrometry (IMS-MS) based on a target list of expected ions provided by the user.", + "laborHours": 83235.2, + "name": "IMS - MS Data Extractor", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/PIXIE/blob/master/PNNL%20OSS%20License_citation.doc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PIXIE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IMS_Drift_Time_Aligner.json b/agency-indexes/DoE/IMS_Drift_Time_Aligner.json new file mode 100644 index 00000000..db5f0386 --- /dev/null +++ b/agency-indexes/DoE/IMS_Drift_Time_Aligner.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This program processes IMS data in a UIMF file to align all frames to a base frame, adjusting the observed drift times of each frame to align with the base frame.", + "laborHours": 775.2, + "languages": [], + "name": "IMS Drift Time Aligner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/IMS-Drift-Time-Aligner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IN-SPIRE.json b/agency-indexes/DoE/IN-SPIRE.json new file mode 100644 index 00000000..ab52e84d --- /dev/null +++ b/agency-indexes/DoE/IN-SPIRE.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-15", + "metadataLastUpdated": "2025-04-15" + }, + "description": "IN-SPIRE\u2122 can quickly and automatically convey the gist of large sets of unformatted text documents such as technical reports, web data, newswire feeds and message traffic. By clustering similar documents together, this Windows-based software unveils common themes and reveals hidden relationships within the collection. IN-SPIRE\u2122 allows analysts to spend more time exploring the information they find most relevant and less time sifting through the masses of irrelevant documents.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 3747666.4, + "languages": [], + "name": "IN-SPIRE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/INFRA-COMPASS__Infrastructure_Continuous_Ordinance_Mapping_for_Planning_and_Siting_Systems__[SWR-25-62].json b/agency-indexes/DoE/INFRA-COMPASS__Infrastructure_Continuous_Ordinance_Mapping_for_Planning_and_Siting_Systems__[SWR-25-62].json new file mode 100644 index 00000000..51752d92 --- /dev/null +++ b/agency-indexes/DoE/INFRA-COMPASS__Infrastructure_Continuous_Ordinance_Mapping_for_Planning_and_Siting_Systems__[SWR-25-62].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-15", + "metadataLastUpdated": "2025-04-15" + }, + "description": "INFRA-COMPASS is an innovative software tool that harnesses the power of Large Language Models (LLMs) to automate the compilation and continued maintenance of an inventory of state and local codes and ordinances pertaining to energy infrastructure.", + "laborHours": 5274.4, + "languages": [ + "Python", + "Rust" + ], + "name": "INFRA-COMPASS (Infrastructure Continuous Ordinance Mapping for Planning and Siting Systems) [SWR-25-62]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/COMPASS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v.0.3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/INN_Airfoil_Tools.json b/agency-indexes/DoE/INN_Airfoil_Tools.json new file mode 100644 index 00000000..ea105265 --- /dev/null +++ b/agency-indexes/DoE/INN_Airfoil_Tools.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-05-18", + "metadataLastUpdated": "2022-06-22" + }, + "description": "This software package contains code to perform airfoil inverse shape design using a sparsified invertible neural network model. This is a specialized deep learning architecture that enables both network weights to be shared to evaluate forward or inverse passes through the network. As a design tool, this network allows practitioners to specify desired aerodynamic and structural properties and generate shapes that satisfy those properties. The invertible neural network is accompanied with tuned parameters as well as software tools to train new models as needed.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "INN Airfoil Tools", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/INN-interface", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/INPAGN_Launcher_V3.DLL.json b/agency-indexes/DoE/INPAGN_Launcher_V3.DLL.json new file mode 100644 index 00000000..f653d87c --- /dev/null +++ b/agency-indexes/DoE/INPAGN_Launcher_V3.DLL.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-22" + }, + "description": "INPAGN_Launcher_v3.DLL is a preprocessor and postprocessor used to integrate the INPAG-N code (Monitor Scientific, LLC) with the GoldSim\u00e2\u201e\u00a2 code (GoldSim Technology Group, LLC). 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This software is used as part of a modeling package that consists of INPAGN.EXE, INPAGNH.EXE, INPAGNHI.EXE, INPAGNV2.EXE, INPAGNV21.EXE, GoldSim\u00e2\u201e\u00a2, and INPAGN_Launcher_v3.DLL.", + "laborHours": 0.0, + "languages": [ + "FORTRAN/DIGITAL Visual FORTRAN 6.0" + ], + "name": "INPAGN_Launcher_V3.DLL", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/INPAGN_Launcher", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/INTERSECT-SDK__Python_.json b/agency-indexes/DoE/INTERSECT-SDK__Python_.json new file mode 100644 index 00000000..b967e00b --- /dev/null +++ b/agency-indexes/DoE/INTERSECT-SDK__Python_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "mcdonnellmt@ornl.gov" + }, + "date": { + "created": "2024-09-27", + "metadataLastUpdated": "2024-10-15" + }, + "description": "Interconnected Science Ecosystem - Software Development Kit (INTERSECT-SDK)", + "laborHours": 6064.8, + "languages": [ + "Python" + ], + "name": "INTERSECT-SDK (Python)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/INTERSECT-SDK/python-sdk", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/INteroperable_Tools_for_Rapid_dEveloPment_of_compatible_Discretizations.json b/agency-indexes/DoE/INteroperable_Tools_for_Rapid_dEveloPment_of_compatible_Discretizations.json new file mode 100644 index 00000000..5499f32e --- /dev/null +++ b/agency-indexes/DoE/INteroperable_Tools_for_Rapid_dEveloPment_of_compatible_Discretizations.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Intrepid is a library of interoperable tools for compatible discretizations of Partial Differential Equations (PDEs).Current version is intended primarily for application developers who want to reuse large parts of their existing code frameworks such as I/O, data structures, assembly routines, etc. while gaining access to advanced discretization capabilities provided by Intrepid. Intrepid2 is a performance portable version of Intrepid, that requires all input data types be Kokkos (performance-portability library from Trillions) multidimentional arrays. this restriction is needed for providing performance portability in Intrepid2 and break backward-compatibility of Intrepid.", + "laborHours": 8344830.4, + "name": "INteroperable Tools for Rapid dEveloPment of compatible Discretizations", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/intrepid/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IOMiner_v0.3.json b/agency-indexes/DoE/IOMiner_v0.3.json new file mode 100644 index 00000000..3876eb54 --- /dev/null +++ b/agency-indexes/DoE/IOMiner_v0.3.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-30", + "metadataLastUpdated": "2021-03-30" + }, + "description": "Modern HPC systems are collecting large amounts of I/O performance data. The massive volume and heterogeneity of this data, however, have made timely performance of in-depth integrated analysis difficult. To overcome this difficulty and to allow users to identify the root causes of poor application I/O performance, we developed IOMiner, an I/O log analytics framework.", + "laborHours": 0.0, + "languages": [], + "name": "IOMiner v0.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/iominer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/IOR.json b/agency-indexes/DoE/IOR.json new file mode 100644 index 00000000..9239d748 --- /dev/null +++ b/agency-indexes/DoE/IOR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Parallel filesystem I/O benchmark.\n", + "laborHours": 3845.6, + "languages": [], + "name": "IOR", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ior", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IOSS.json b/agency-indexes/DoE/IOSS.json new file mode 100644 index 00000000..24846a2d --- /dev/null +++ b/agency-indexes/DoE/IOSS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-22", + "metadataLastUpdated": "2020-05-22" + }, + "description": "This is the repository for the IO System (IOSS) library developed at Sandia National Lab. ", + "laborHours": 2002235.2, + "languages": [], + "name": "IOSS", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/gsjaardema/seacas/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gsjaardema/seacas", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IPS_Framework.json b/agency-indexes/DoE/IPS_Framework.json new file mode 100644 index 00000000..9d51d23d --- /dev/null +++ b/agency-indexes/DoE/IPS_Framework.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "bernholdtde@ornl.gov" + }, + "date": { + "created": "2021-09-26", + "metadataLastUpdated": "2021-09-28" + }, + "description": "IPS is an environment to orchestrate complex coupled simulation workflows on parallel computers. The IPS is designed primarily for use in abatch-processing environment, with a batch job typically comprising a single invocation of the framework, calling the individual physics codesmany times as the simulation progresses.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "IPS Framework", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HPC-SimTools/IPS-framework", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IPyOverlay.json b/agency-indexes/DoE/IPyOverlay.json new file mode 100644 index 00000000..0a51c6a3 --- /dev/null +++ b/agency-indexes/DoE/IPyOverlay.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "martindalena@ornl.gov" + }, + "date": { + "created": "2024-05-30", + "metadataLastUpdated": "2024-05-30" + }, + "description": "IPyOverlay is a Python library that provides several IPyWidget components for use within the Jupyter software ecosystem. These components add novel UI capabilities to enable details-on-demand interaction paradigms by providing the ability to render widgets on top of other widgets with arbitrary and controllable positioning. This capability enables adding click-and-draggable overlay windows containing other widgets, right-click context menus, and more complex tooltip functionality.", + "laborHours": 820.8, + "languages": [ + "Python" + ], + "name": "IPyOverlay", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl/ipyoverlay", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IRAD.json b/agency-indexes/DoE/IRAD.json new file mode 100644 index 00000000..7f2a73a7 --- /dev/null +++ b/agency-indexes/DoE/IRAD.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "liny@ornl.gov" + }, + "date": { + "created": "2024-03-04", + "metadataLastUpdated": "2024-03-04" + }, + "description": "IRAD (Ion Irradiation and Radiation Damage) is an open-source GUI for SRIM-like vacancy production and implanted ion profile calculations. Using updated databases, IRAD is accessible at https://code.ornl.gov/liny/irad for Windows systems. It performs energy-corrected Iradina calculations, automatically determining dpa and implanted ion concentration, considering total ion fluence. Additional results like ion trajectories, final positions, stopping power distribution, etc., are available. Advanced settings permit customization of parameters such as stopping power database, incident ion angle, and 3D target simulations.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "IRAD", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/liny/irad", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IREP.json b/agency-indexes/DoE/IREP.json new file mode 100644 index 00000000..d35de968 --- /dev/null +++ b/agency-indexes/DoE/IREP.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2022-10-27" + }, + "description": "A tool for filling C/C++ or Fortran data structures from Lua input tables. IREP reads external program input using the Lua C Library, organizes the input into native language structures, and shares those structures among compiled program objects written in either (or both) C/C++ or Fortran.", + "laborHours": 927.2, + "languages": [ + "C, C++, Fortran, Lua version 5.1" + ], + "name": "IREP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/irep", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IRIS.json b/agency-indexes/DoE/IRIS.json new file mode 100644 index 00000000..828cde4a --- /dev/null +++ b/agency-indexes/DoE/IRIS.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "kimj@ornl.gov" + }, + "date": { + "created": "2021-10-20", + "metadataLastUpdated": "2021-10-27" + }, + "description": "A unified framework across multiple programming platforms", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Fortran", + "Python" + ], + "name": "IRIS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/iris", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IRViz_v0.0.5.json b/agency-indexes/DoE/IRViz_v0.0.5.json new file mode 100644 index 00000000..fba96ef7 --- /dev/null +++ b/agency-indexes/DoE/IRViz_v0.0.5.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-11-07" + }, + "description": "The IRViz package provides easy to use graphical user interface for the analysis of IR data.", + "laborHours": 3222.4, + "languages": [], + "name": "IRViz v0.0.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/irviz", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ISDDD.json b/agency-indexes/DoE/ISDDD.json new file mode 100644 index 00000000..ca3dd0a6 --- /dev/null +++ b/agency-indexes/DoE/ISDDD.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-11-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The ISDDD software program simulates a mathematical model, named ISD3 (\"ISDDD\"), developed for describing the time-, concentration- and particle size- dependent dissolution of particles, their delivery to cells, and the delivery and uptake of ions to cells in in vitro liquid test systems. The model is based on a specific formulation of the Population Balance Equation, derived for soluble particles. ISD3 solves for the size and spatial distribution of particle numbers, represented together as a particle number density (that is a function of particle location and diameter). From the number density, all other quantities, such as mass, concentration, size distribution and surface areas are derived. The model can be applied for any initial particle size distribution data by representing the data in terms of the number density. As a result, time dependent solutions can be obtained for all size ranges in a single run of the ISD3 simulation for a given particle type and\nmedia conditions. In the current implementation, particles are treated as spherical in shape and can be modeled as primary particles, agglomerates, or as primary particles coated with proteins. Ions are modeled as a lumped system with a uniform concentration in the liquid media. Particle transport is assumed to occur down the liquid column via diffusion and sedimentation (no fluid convection), and no aggregation/agglomeration, coagulation and break-up of the particles occur during transport. Cellular uptake kinetics of ions and particle dissolution kinetics are currently implemented using empirical models that were developed and calibrated for silver nanoparticles and ions. The ISD3 code is modular, allowing use of the existing equations for the dissolution model and ion uptake, but can be modified to include alternate models developed by the user. Application of ISD3 to another particle system would involve inputting parameters appropriate for the particles and model system. For particle uptake by cells, users have the option to use a no-flux or a perfectly absorbing \u2018sticky\u2019 boundary condition. For reactive boundary conditions, the user needs to modify a few lines of the code to express the desired form of the boundary condition (e.g., Robin type of boundary condition).", + "homepageURL": "http://nanodose.pnnl.gov/ModelDownload.aspx", + "laborHours": 0.0, + "languages": [], + "name": "ISDDD", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://nanodose.pnnl.gov/ModelDownload.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ISOCELES__Iterative_Self-Organizing_Scene-Level_Sampling_.json b/agency-indexes/DoE/ISOCELES__Iterative_Self-Organizing_Scene-Level_Sampling_.json new file mode 100644 index 00000000..c645a2a9 --- /dev/null +++ b/agency-indexes/DoE/ISOCELES__Iterative_Self-Organizing_Scene-Level_Sampling_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "swanbt@ornl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "ISOSCLES (Iterative Self-Organizing SCene LEvel Sampling) is a hierarchical, unsupervised method for obtaining a set of image chips for training convolutional neural networks. ISOSCELES operates at two levels, first selecting representative images from a full image domain and then performing unsupervised clustering of potential samples from each of those scenes to obtain a final set of sample chips that then can be labelled or used for unsupervised training. This technique was first designed to support building extraction tasks using Maxar 4-band imagery from WorldView-2, WorldView-3, Quickbird-2, or GeoEye, but can be modified to work with other image sources.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ISOCELES (Iterative Self-Organizing Scene-Level Sampling)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/btswan87/isosceles", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ISO_15118_Node-Red_Dashboard.json b/agency-indexes/DoE/ISO_15118_Node-Red_Dashboard.json new file mode 100644 index 00000000..5cd6e2d9 --- /dev/null +++ b/agency-indexes/DoE/ISO_15118_Node-Red_Dashboard.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-09", + "metadataLastUpdated": "2024-03-13" + }, + "description": "This is a graphical user interface (GUI) that can be deployed in a Node-RED environment and be configured to provide monitoring and control of an ISO 15118 EV Charger (DC or AC).", + "laborHours": 0.0, + "languages": [], + "name": "ISO 15118 Node-Red Dashboard", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/node-red/node-red", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ISO_Data_Automated_Request_Tool.json b/agency-indexes/DoE/ISO_Data_Automated_Request_Tool.json new file mode 100644 index 00000000..f47c0536 --- /dev/null +++ b/agency-indexes/DoE/ISO_Data_Automated_Request_Tool.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "Very early stages of a simple tool able to create multiple automated requests of different Independent System Operators (ISOs) data, and download it in comma separated value (.csv) files.\n", + "laborHours": 0.0, + "languages": [], + "name": "ISO Data Automated Request Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ISO-DART", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ISO_Fortran_binding_m_v0.1.0.json b/agency-indexes/DoE/ISO_Fortran_binding_m_v0.1.0.json new file mode 100644 index 00000000..226c1894 --- /dev/null +++ b/agency-indexes/DoE/ISO_Fortran_binding_m_v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-06", + "metadataLastUpdated": "2024-09-12" + }, + "description": "The Fortran programming language standard defines a broad feature set supporting the interoperability of Fortran programs with program written according to the C programming language standard. Among Fortran's C-interoperability features is a a C header file \"ISO_Fortran_binding.h\" This header file defines the interface to various C data structures and functions that C programs may use to access Fortran data entities. The ISO_Fortran_binding_m software defines a native Fortran module that presents an interface to these same data structures and functions. ISO_Fortran_bind_m thus enables Fortran programs to access and manipulate Fortran entities in ways that precisely mirror what C programs can do using ISO_Fortran_binding.h. ISO_Fortran_binding_m facilitates writing portable standard-conforming Fortran programs that emulate non-interoperable features, e.g., dynamic polymorphism, in a standard-conforming interoperable way similar but broader than what is demonstrated in Berkeley Lab's Caffeine software [1]. ISO_Fortran_binding_m also enables a Fortran programmer to extend Fortran's capabilities to emulate certain C functionality such as memory address arithmetic or computing C's \"sizeof\" function.\n\n[1] https://github.com/BerkeleyLab/caffeine/blob/213e3df1c319f0663306354414f352acda42a24f/src/caffeine/collective_subroutines/co_reduce_s.f90#L88\n[2] https://github.com/BerkeleyLab/ISO_Fortran_binding_m/blob/0c585362bb4f2c72cf9049c800a7115b529ec533/src/iso_fortran_binding_m.F90#L196", + "laborHours": 167.2, + "languages": [], + "name": "ISO_Fortran_binding_m v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/ISO_Fortran_binding_m", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ITL__InterfaceLimits.jl__[SWR-23-56].json b/agency-indexes/DoE/ITL__InterfaceLimits.jl__[SWR-23-56].json new file mode 100644 index 00000000..c3fafc48 --- /dev/null +++ b/agency-indexes/DoE/ITL__InterfaceLimits.jl__[SWR-23-56].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-21", + "metadataLastUpdated": "2023-07-06" + }, + "description": "Network flow of electrical power is governed by Kirchhoff's laws which make calculating the power transfer capacity across interfaces connecting groups of nodes complex. This package leverages the capabilities of Sienna\\Data to build and solve interface limit calculation problems.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "ITL (InterfaceLimits.jl) [SWR-23-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel-sienna/InterfaceLimits.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Icypaw.json b/agency-indexes/DoE/Icypaw.json new file mode 100644 index 00000000..6829e4c9 --- /dev/null +++ b/agency-indexes/DoE/Icypaw.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-16", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The Intermode Communication Protocol Wrapper, or Icypaw, structures and facilitates communication between endpoints in a network. It is used to connect various independent software and hardware components into one loosely organized system controllable from one or more locations. The code uses the MQTT protocol to communicate and enhances it with a useful framework. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8293 O", + "laborHours": 4909.6, + "languages": [ + "Python" + ], + "name": "Icypaw", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IcyPaw", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IdahoLabResearch_INLIDD.json b/agency-indexes/DoE/IdahoLabResearch_INLIDD.json new file mode 100644 index 00000000..80590167 --- /dev/null +++ b/agency-indexes/DoE/IdahoLabResearch_INLIDD.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-04-13", + "metadataLastUpdated": "2023-04-13" + }, + "description": "This code along with the included data allows users to train machine learning models on network packet data.", + "laborHours": 0.0, + "languages": [], + "name": "IdahoLabResearch/INLIDD", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/INLIDD", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Igor.json b/agency-indexes/DoE/Igor.json new file mode 100644 index 00000000..91a7034f --- /dev/null +++ b/agency-indexes/DoE/Igor.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-13", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-05551O\nIgor, an open-source software, manages large clusters of users in a high-performance computing community. The systems allows users to choose an operating system and reserve and request hosts. The administrative side sets up and executes requests from users while simultaneously giving them tools to manage and enforce reservation policies and user access to the hosts.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 20930.4, + "languages": [ + "Go", + "Shell", + "JavaScript", + "Vue" + ], + "name": "Igor", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/igor", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Igor_Pro_procedures_for_ARPES_analysis__ARPES_Igor_procedures__v21.0.json b/agency-indexes/DoE/Igor_Pro_procedures_for_ARPES_analysis__ARPES_Igor_procedures__v21.0.json new file mode 100644 index 00000000..381679ff --- /dev/null +++ b/agency-indexes/DoE/Igor_Pro_procedures_for_ARPES_analysis__ARPES_Igor_procedures__v21.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-21" + }, + "description": "A suite of non-proprietary C-like procedures (code) that compile and run within the commercial Igor Pro data analysis program (wavemetrics.com) have been developed for the data file loading, plotting and analysis of Angle-Resolved Photoemission Spectroscopy (ARPES) data. The data file loading procedures are more specific to ARPES data acquisition and file formats at Advanced Light Source (ALS) beamlines, while plotting and analysis procedures are more generic to processing of 1D, 2D and higher dimensional dataset arrays with some specific tools tailored to the ARPES technique.", + "homepageURL": "https://sites.google.com/lbl.gov/2021-158/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Igor Pro procedures for ARPES analysis (ARPES Igor procedures) v21.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-158/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ImageVis3D.json b/agency-indexes/DoE/ImageVis3D.json new file mode 100644 index 00000000..2654723a --- /dev/null +++ b/agency-indexes/DoE/ImageVis3D.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-06", + "metadataLastUpdated": "2018-07-06" + }, + "description": "ImageVis3D is a volume rendering program developed by the NIH/NCRR Center for Integrative Biomedical Computing with main design goals of simplicity, scalability, and interactivity. ", + "laborHours": 31980.8, + "languages": [], + "name": "ImageVis3D", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SCIInstitute/ImageVis3D", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Image_Composition_Engine_for_Tiles.json b/agency-indexes/DoE/Image_Composition_Engine_for_Tiles.json new file mode 100644 index 00000000..c2c9313f --- /dev/null +++ b/agency-indexes/DoE/Image_Composition_Engine_for_Tiles.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The Image Composition Engine for Tiles (lceT) is a high-performance sort-last parallel rendering library. It is designed to be used in parallel applications requiring rendering. The primary purpose of IceT is to be integrated into parallel visualization applications such as ParaView to provide parallel rendering capabilities. The Image Composition Engine for Tiles (lceT) is a high-performance sort-last parallel rendering library. IceT uses a \"sort-Iasf' approach to rendering. Each process in a parallel application independently renders a local piece of geometry. The resulting images are given to IceT, and IceT combines the images together to form a single cohesive image. Ice T is also capable of driving tiled displays, largeformat displays comprising an array of smaller displays. To this end IceT can collect the smaller tile images and organize them such that the entire tiled display can be driven. Ice T takes advantage of spatial coherence in geometry by identifying empty regions of the display and reducing the overall required work.", + "laborHours": 8709.6, + "languages": [ + "C" + ], + "name": "Image Composition Engine for Tiles", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IceT", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ImagingSIMS_ImagingSIMS.json b/agency-indexes/DoE/ImagingSIMS_ImagingSIMS.json new file mode 100644 index 00000000..8888c323 --- /dev/null +++ b/agency-indexes/DoE/ImagingSIMS_ImagingSIMS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2020-09-01" + }, + "description": "ImagingSIMS is an open-source project for loading, analyzing, and visualizing secondary ion mass spectrometry (SIMS) data.", + "laborHours": 111887.2, + "languages": [], + "name": "ImagingSIMS/ImagingSIMS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ImagingSIMS/ImagingSIMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Imaging_Bragg_Edge_Analysis_TooLs_for_Engineering_Structures__iBeatles_.json b/agency-indexes/DoE/Imaging_Bragg_Edge_Analysis_TooLs_for_Engineering_Structures__iBeatles_.json new file mode 100644 index 00000000..315ca05e --- /dev/null +++ b/agency-indexes/DoE/Imaging_Bragg_Edge_Analysis_TooLs_for_Engineering_Structures__iBeatles_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "bilheuxjm@ornl.gov" + }, + "date": { + "created": "2024-12-09", + "metadataLastUpdated": "2024-12-09" + }, + "description": "The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) provides pulsed neutrons with energies varying from epithermal to cold. In preparation for VENUS, the neutron imaging beamline to be located at beam port 10, we have performed a series of experiments focused on wavelength-dependent radiography and computed tomography for a broad range of applications, from materials science to biological tissues.One of the time-of-flight (TOF) techniques that is of interest to the scientific community is the 2-dimensional mapping of phases and average crystalline plane orientation in samples both ex-situ and during applied stresses such as tensile loading and heating. This technique is known as Bragg edgeimaging and relies on the identification of changes of transmission values, fitting of the edge to measure its displacement, and thus identify the shift in lattice parameter due to stresses. One of the challenges of TOF imaging measurements is the amount of data and the inability to observe Bragg edge shifts in real time during an experiment. Thus, we have been focusing on creating a Python-based interface that allows fast data processing and instantaneous mapping and fitting of the Bragg edges, and their evolution through time. Python libraries and Jupyter notebooks have been implemented to facilitate decision making during an experiment. The advantage of the notebooks is the possibility to guide an experiment as they can quickly process and display Bragg edge data. These notebooks can be used independently, or can be combined in a Python Graphical User Interface (GUI) tool called iBeatles. This interface permits visualization and fitting of the Bragg edges, and ultimately back-projects the fitting results onto the radiographs to display a strain map. Assuming data collection has sufficient statistics, the strain mapping analysis can be performed on a pixel-by-pixel basis. This development is a step forward toward a better user experience at the future VENUS beamline in terms of live feedback and productivity. Analysis that used to take days of switching between different applications can now be done in minutes within the", + "laborHours": 36449.6, + "languages": [ + "Python" + ], + "name": "Imaging Bragg Edge Analysis TooLs for Engineering Structures (iBeatles)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornlneutronimaging/iBeatles", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Impact-Z.json b/agency-indexes/DoE/Impact-Z.json new file mode 100644 index 00000000..e127a1c8 --- /dev/null +++ b/agency-indexes/DoE/Impact-Z.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "IMPACT-Z is a parallel particle-in-cell code whose primary purpose is to model the dynamics of charged particle beams in linear accelerators. The code includes the effects of externally applied fields from magnets and accelerating cavities as well as the effect of self-fields (space charge fields). Mathematically, the code solves the Vlasov/Poisson equations using a particle-based technique. The code, which is written in Fortran90 with MPI, runs on both single-processor and multi-processor systems.", + "laborHours": 0.0, + "languages": [ + "Fortran90 with MPI" + ], + "name": "Impact-Z", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/impact-lbl/IMPACT-Z/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/impact-lbl/IMPACT-Z", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ImpactX_v0.1.json b/agency-indexes/DoE/ImpactX_v0.1.json new file mode 100644 index 00000000..733d3fe1 --- /dev/null +++ b/agency-indexes/DoE/ImpactX_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "ImpactX is the next generation of the IMPACT-Z code. It is a s-based simulation code for modeling intense beams in particle accelerators using symplectic tracking methods and includes collective effects. It is multi-node parallel and supports modern compute hardware such as GPUs, modern algorithms such as mesh-refinement and realistic geometries (embedded boundaries).", + "laborHours": 0.0, + "languages": [], + "name": "ImpactX v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-WarpX/impactx", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Implement_the_size_statistics_Parquet_standard_in_the_Rust_implementation_of_Arrow_and_Parquet..json b/agency-indexes/DoE/Implement_the_size_statistics_Parquet_standard_in_the_Rust_implementation_of_Arrow_and_Parquet..json new file mode 100644 index 00000000..183f0b15 --- /dev/null +++ b/agency-indexes/DoE/Implement_the_size_statistics_Parquet_standard_in_the_Rust_implementation_of_Arrow_and_Parquet..json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-03-11", + "metadataLastUpdated": "2024-03-11" + }, + "description": "This patch will implement the new size statistics standard in the Rust implementation of Apache Arrow\nand Parquet (https://github.com/apache/arrow-rs/). This allows an uncompressed and unencoded size to\nbe known prior to uncompressing and unencoding data stored in parquet files.", + "laborHours": 0.0, + "languages": [], + "name": "Implement the size statistics Parquet standard in the Rust implementation of Arrow and Parquet.", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/apache/arrow-rs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Implicit_SPH_v._1.0.json b/agency-indexes/DoE/Implicit_SPH_v._1.0.json new file mode 100644 index 00000000..0988a138 --- /dev/null +++ b/agency-indexes/DoE/Implicit_SPH_v._1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "ISPH code is developed to solve multi-physics meso-scale flow problems using implicit SPH method. In particular, the code can provides solutions for incompressible, multi phase flow and electro-kinetic flows.", + "laborHours": 19425.6, + "languages": [ + "C++", + "MATLAB" + ], + "name": "Implicit SPH v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/implicit-sph", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Improv_Dynamic_Workflows.json b/agency-indexes/DoE/Improv_Dynamic_Workflows.json new file mode 100644 index 00000000..7f4eab1f --- /dev/null +++ b/agency-indexes/DoE/Improv_Dynamic_Workflows.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-11", + "metadataLastUpdated": "2024-04-11" + }, + "description": "A workflow is a series of dependent computations which are executed to\nyield an experimental result, much like sheet music describes a musical\nperformance. Dynamic workflows are like improvisational jazz, in which\nthe musicians create unique, situation-driven, collaborative variations\non themes. Dynamic workflows can potentially yield better results, save\ncomputation, and/or save human decision-making effort versus pre-specified\nor manual workflows, as they need not run the exhaustive set of studies\nwhich might be required in a pre-specified set, and they make their own\nexperimental design decisions at run time. If you have an existing\nMaestro study where you would like to save computation and/or human time,\nImprov is for you.\nImprov provides core capabilities for creating a simple, hierarchical structure over Maestro studies,\nallowing you to connect ``experimental'' Maestro strudies with decision-making code to select parameters\nand run corresponding studies.", + "laborHours": 2492.8, + "languages": [], + "name": "Improv Dynamic Workflows", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/improvwf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ImsInformed_Library.json b/agency-indexes/DoE/ImsInformed_Library.json new file mode 100644 index 00000000..538d4372 --- /dev/null +++ b/agency-indexes/DoE/ImsInformed_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ImsInformed is a .NET class library that provides target identification workflows for peptides and metabolites alike in IMS experiment runs.", + "laborHours": 127345.6, + "languages": [], + "name": "ImsInformed Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/IMS-Informed-Library", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/IMS-Informed-Library", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/In-Situ_Machine_Learning__ISML_.json b/agency-indexes/DoE/In-Situ_Machine_Learning__ISML_.json new file mode 100644 index 00000000..b501ed72 --- /dev/null +++ b/agency-indexes/DoE/In-Situ_Machine_Learning__ISML_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-02-24", + "metadataLastUpdated": "2022-02-25" + }, + "description": "SAND2022-1478 O In-Situ Machine Learning (ISML) is a library of functions that can be combined to create algorithms for in-situ event detection. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "In-Situ Machine Learning (ISML)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/isml", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/In-situ_FTIR_Spectral_Deconvolution_[SWR-24-60].json b/agency-indexes/DoE/In-situ_FTIR_Spectral_Deconvolution_[SWR-24-60].json new file mode 100644 index 00000000..1283ff50 --- /dev/null +++ b/agency-indexes/DoE/In-situ_FTIR_Spectral_Deconvolution_[SWR-24-60].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-05-30", + "metadataLastUpdated": "2024-09-24" + }, + "description": "In-situ FTIR Spectral Deconvolution contains scripts for the fitting of gaussians to convoluted FTIR spectra. It was specifically developed to handle a time-series of in situ ATR-FTIR spectra, split the spectra into its individual gaussians, and track those peaks as they shift in intensity and energy. Along with the actual fitting script, this repository contains several support scripts for data analysis and recall of prior fit results.", + "laborHours": 532.0, + "languages": [ + "Python" + ], + "name": "In-situ FTIR Spectral Deconvolution [SWR-24-60]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/In-Situ-FTIR-SpectralDeconvolution", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/In_silico_evolution_of_oscillatory_gene_dynamics_formerly_Code_sharing_for_a_manuscript_to_be_submitted_to_the_journal_iScience.json b/agency-indexes/DoE/In_silico_evolution_of_oscillatory_gene_dynamics_formerly_Code_sharing_for_a_manuscript_to_be_submitted_to_the_journal_iScience.json new file mode 100644 index 00000000..8cfa238d --- /dev/null +++ b/agency-indexes/DoE/In_silico_evolution_of_oscillatory_gene_dynamics_formerly_Code_sharing_for_a_manuscript_to_be_submitted_to_the_journal_iScience.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-05-09", + "metadataLastUpdated": "2022-05-09" + }, + "description": "The disclosure is about the numerical simulations and visualization implemented in general-purpose language Python and C++. The simulations were in-silico evolution of hypothetical gene circuits that potentially admit oscillatory dynamics. The aim of the study, which was invited to be submitted to a special issue \"Timekeeping, noise and development across kingdoms\" in the journal iScience, is to demonstrate that in contrast to common belief, noise in gene expression dynamics could significantly facilitate the evolutionary process for searching oscillatory dynamics, which are essential for developing circadian rhythm in living organisms.", + "laborHours": 0.0, + "languages": [], + "name": "In silico evolution of oscillatory gene dynamics formerly Code sharing for a manuscript to be submitted to the journal iScience", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/In-Silico-Evolution-of-oscillatory-gene-dynamics", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Incomplete_Interior_Penalty_Galerkin_Method_For_Modeling_Brittle_Fracture_Propagation.json b/agency-indexes/DoE/Incomplete_Interior_Penalty_Galerkin_Method_For_Modeling_Brittle_Fracture_Propagation.json new file mode 100644 index 00000000..d318088d --- /dev/null +++ b/agency-indexes/DoE/Incomplete_Interior_Penalty_Galerkin_Method_For_Modeling_Brittle_Fracture_Propagation.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-09-12", + "metadataLastUpdated": "2023-09-12" + }, + "description": "IIPG_Fracture is to provide a numerical tool to model crack propagation in brittle solid media by implementing the Incomplete Interior Penalty Galerkin (IIPG) as well as an extrinsic cohesive law for modeling crack nucleation and propagation in the MOOSE framework.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Incomplete Interior Penalty Galerkin Method For Modeling Brittle Fracture Propagation", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/IIPG_Crack", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IndexRunner.json b/agency-indexes/DoE/IndexRunner.json new file mode 100644 index 00000000..6c691e77 --- /dev/null +++ b/agency-indexes/DoE/IndexRunner.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-18", + "metadataLastUpdated": "2020-08-18" + }, + "description": "This is an index runner. It watches a Kafka topic and can trigger indexing using indexers written with the SDK. The results go into ElasticSearch.", + "laborHours": 2401.6, + "languages": [], + "name": "IndexRunner", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/IndexRunner", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Indira:_intent-based_networking_and_rendering_for_networks__Indira__v1.json b/agency-indexes/DoE/Indira:_intent-based_networking_and_rendering_for_networks__Indira__v1.json new file mode 100644 index 00000000..7f8fbed8 --- /dev/null +++ b/agency-indexes/DoE/Indira:_intent-based_networking_and_rendering_for_networks__Indira__v1.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-03", + "metadataLastUpdated": "2021-03-03" + }, + "description": "Intelligent Network Deployment Intent Renderer Application an interactive network assistant that will help us configure a data path between two scientific end-point groups (EPGs) to optimize the transfer of elephant data flows. This tool is able to talk to scientists gather network requirements and then convert to network programming code and automate the end-to-end provisioning.", + "laborHours": 0.0, + "languages": [], + "name": "Indira: intent-based networking and rendering for networks (Indira) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/indira_networkIntent.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Industrial_Control_Systems_Network_Protocol_Parsers.json b/agency-indexes/DoE/Industrial_Control_Systems_Network_Protocol_Parsers.json new file mode 100644 index 00000000..a119a7dc --- /dev/null +++ b/agency-indexes/DoE/Industrial_Control_Systems_Network_Protocol_Parsers.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-12", + "metadataLastUpdated": "2024-02-27" + }, + "description": "Industrial Control Systems protocol parsers plugins for the Zeek network security monitoring framework. Currently we have four fully developed protocol parsers but we plan on adding more in the future. The protocol parsers we currently have developed are for BACnet, DNP3, Ethernet/IP, and Modbus.", + "laborHours": 0.0, + "languages": [], + "name": "Industrial Control Systems Network Protocol Parsers", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/cisagov/ICSNPP", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Industrial_Radiography_Mobile_Source_Transit_Security_Software_and_Firmware.json b/agency-indexes/DoE/Industrial_Radiography_Mobile_Source_Transit_Security_Software_and_Firmware.json new file mode 100644 index 00000000..6fd4b50f --- /dev/null +++ b/agency-indexes/DoE/Industrial_Radiography_Mobile_Source_Transit_Security_Software_and_Firmware.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Industrial Radiography Mobile Source Transit Security (IR-MSTS) Software and Firmware Applications and Components described here are part of a system developed under NNSA funding to track mobile radioactive sources used in the industrial radiography service industry. The individual software applications and libraries, and firmware executables work together and in conjunction with the electronic hardware components to provide situational awareness of the radioactive sources as they are transported from the home base of operations to a job site and back again. Industrial radiography devices are equipped with IR-MSTS components to provide near real time source location information. A Global Positioning System (GPS) is used to track the geographic location of the transport vehicle. Various sensors are used to detect and report tamper of the IR-MSTS components. Base Station application software, IR Dashboard, allows qualified personnel to track alarms, device information and locations and provides contact info of individuals that need to be notified should anomalous conditions be detected. Firmware for Industrial Radiography 31602 IR Cloud Services for Industrial Radiography 31600 PM-Mat Firmware for Industrial Radiography 31599 IR Dashboard for Industrial Radiography 31598 PM-Box Firmware for Industrial Radiography 31597 PM-Tag Firmware for Industrial Radiography 31596 VCU Firmware for Industrial Radiography 31595", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Industrial Radiography Mobile Source Transit Security Software and Firmware", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Industry_Energy_Tool.json b/agency-indexes/DoE/Industry_Energy_Tool.json new file mode 100644 index 00000000..9bb77d44 --- /dev/null +++ b/agency-indexes/DoE/Industry_Energy_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2019-11-04" + }, + "description": "The Industry Energy Tool (IET) is an open-source calculator tool designed for projecting energy and emissions impacts of industrial sector energy efficiency, material efficiency, and fuel switching. Projections are available at the county and Census Region levels. The IET is based on a detailed county-level energy data set for agriculture, mining, construction, and manufacturing industries. End use energy disaggregation is provided for manufacturing industries, and some agriculture and mining industries. Process temperature disaggregation is provided for most manufacturing industries.", + "laborHours": 2416.8, + "languages": [], + "name": "Industry Energy Tool", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Industry-Energy-Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Inference-Engine_v0.1.0.json b/agency-indexes/DoE/Inference-Engine_v0.1.0.json new file mode 100644 index 00000000..6687663b --- /dev/null +++ b/agency-indexes/DoE/Inference-Engine_v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-13", + "metadataLastUpdated": "2023-07-13" + }, + "description": "Given a pre-trained neural network, Inference-Engine performs maps network inputs to outputs by executing the forward pass through the provided network. Although the predominant programming language for machine-learning is Python, most high-performance computing (HPC) applications are written in Fortran, C, or C++. Inference-Engine aims to support HPC programs and is written in Fortran, a language with a large feature set supporting interoperability with C. This software exposes concurrency in a portable way by using standard language features that some modern Fortran compilers can exploit with various optimizations, including offloading computation to a Graphics Processing Unit (GPU). In particular, this software makes extensive use of Fortran's \"do concurrent\" parallel loop construct, implicitly parallel array statements, and pure procedures that can be invoked inside \"do concurrent\" blocks. Inference-Engine also supports dynamic choice of inference methods at runtime. Two current options include one method that uses Fortran's \"dot_product\" intrinsic function inside \"do concurrent\" blocks and another method that instead uses Fortran' \"matmul\" array intrinsic function. We plan to investigate automatic compiler offloading of \"do concurrent\" calculations to GPUs and compile-time substitution of optimized libraries such as the Basic Linear Algebra Library (BLAS) for \"matmul\" invocations. We also envision the potential for the choice of which method to use could happen at program launch based on in situ performance measurements on any given platform.", + "laborHours": 0.0, + "languages": [], + "name": "Inference-Engine v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/Inference-Engine", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/InfernoRDN.json b/agency-indexes/DoE/InfernoRDN.json new file mode 100644 index 00000000..f93830d6 --- /dev/null +++ b/agency-indexes/DoE/InfernoRDN.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "InfernoRDN can perform various downstream analyses on large scale datasets from proteomics and microarrays.", + "laborHours": 63353.6, + "languages": [], + "name": "InfernoRDN", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/InfernoRDN", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Inferring_trees_from_limited_data.json b/agency-indexes/DoE/Inferring_trees_from_limited_data.json new file mode 100644 index 00000000..1aa38091 --- /dev/null +++ b/agency-indexes/DoE/Inferring_trees_from_limited_data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "Algorithms for phylogenetic tree inference.", + "laborHours": 456.0, + "languages": [], + "name": "Inferring trees from limited data", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/distphylo", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Information_Exchange_development_forums.json b/agency-indexes/DoE/Information_Exchange_development_forums.json new file mode 100644 index 00000000..faa1f77a --- /dev/null +++ b/agency-indexes/DoE/Information_Exchange_development_forums.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "GitHub repositories for creating and managing information exchanges (content models) for use in the NGDS and larger USGIN systems.", + "laborHours": 243.2, + "name": "Information Exchange development forums", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/usginmodels/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/usginmodels", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Information_Exchange_management_site.json b/agency-indexes/DoE/Information_Exchange_management_site.json new file mode 100644 index 00000000..bbfcdae1 --- /dev/null +++ b/agency-indexes/DoE/Information_Exchange_management_site.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Django site used to manage the approved information exchanges (content models) after creation and public comment at https://github.com/usgin-models.", + "laborHours": 14394.4, + "name": "Information Exchange management site", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/modelmanager", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Informed_Proteomics.json b/agency-indexes/DoE/Informed_Proteomics.json new file mode 100644 index 00000000..59628b47 --- /dev/null +++ b/agency-indexes/DoE/Informed_Proteomics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Informed Proteomics project includes algorithms for proteomic mass spectrometry data analysis. Although the back-end data access and some of the scoring routines are general purpose, this repository is currently maintained for top down MS/MS datasets.", + "laborHours": 335874.4, + "languages": [], + "name": "Informed Proteomics", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Informed-Proteomics", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/InfraSys__Infrastructure_Systems__[SWR-24-42].json b/agency-indexes/DoE/InfraSys__Infrastructure_Systems__[SWR-24-42].json new file mode 100644 index 00000000..5e0fb15c --- /dev/null +++ b/agency-indexes/DoE/InfraSys__Infrastructure_Systems__[SWR-24-42].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-04-25" + }, + "description": "This package implements a data store for components and time series in support of Python-based modeling packages. While it is designed to support teams modeling transmission and distribution systems for electrical grids, it can be used by any package that needs to store components (e.g., generators and buses) that have quantities (e.g., power and voltage) which may vary over time.\n\nThe package was inspired by InfrastructureSystems.jl (https://github.com/NREL-Sienna/InfrastructureSystems.jl).", + "laborHours": 2021.6, + "languages": [ + "Python" + ], + "name": "InfraSys (Infrastructure Systems) [SWR-24-42]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/infrasys", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.0.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Infrastructure_Expression:_Discovery_Tools.json b/agency-indexes/DoE/Infrastructure_Expression:_Discovery_Tools.json new file mode 100644 index 00000000..5e133bd5 --- /dev/null +++ b/agency-indexes/DoE/Infrastructure_Expression:_Discovery_Tools.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The Infrastructure Expression: Discovery Tools is a toolset that allows for the automated collection of various network, hardware, and software vulnerabilities and details to be collected from systems on a given network. These details are then converted into a STIX 2.1 format, allowing for easy viewing in existing applications as well as sharing and interfacing with tools that already use the STIX 2.1 format.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Infrastructure Expression: Discovery Tools", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/IX-DiscoveryTools", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ingest.json b/agency-indexes/DoE/Ingest.json new file mode 100644 index 00000000..00614ff3 --- /dev/null +++ b/agency-indexes/DoE/Ingest.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-05-21", + "metadataLastUpdated": "2024-05-21" + }, + "description": "Ingest is an application that allows project owners to solicit data from users and require them to fill out metadata along with those uploads. It is an application developed in Elixir/Phoenix and is a web based platform.", + "laborHours": 11491.2, + "languages": [ + "Elixir", + "Erlang" + ], + "name": "Ingest", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Ingest", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Inl-azure-devops-tasks.json b/agency-indexes/DoE/Inl-azure-devops-tasks.json new file mode 100644 index 00000000..b106b52f --- /dev/null +++ b/agency-indexes/DoE/Inl-azure-devops-tasks.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2019-09-30", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Contains pipeline tasks for Azure DevOps", + "laborHours": 0.0, + "languages": [], + "name": "Inl-azure-devops-tasks", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/inl-azure-devops-tasks", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Inl_Open_Ondemand_Applications.json b/agency-indexes/DoE/Inl_Open_Ondemand_Applications.json new file mode 100644 index 00000000..cbd240fa --- /dev/null +++ b/agency-indexes/DoE/Inl_Open_Ondemand_Applications.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-11-15", + "metadataLastUpdated": "2023-11-15" + }, + "description": "Open OnDemand is a software tool that is used to access HPC resources. It provides a framework for organizations to create apps and other additional functionality that may be useful to the organization. This code expands upon the pre-existing INL applications, including the NEAMS Workbench application, MOOSE Herd applications, and others. These changes significantly expand upon the functionality originally provided. Due to the extensive functionality that we added, these changes would not be added to the original application but would function as a standalone application that other organizations would be able to utilize on their own systems.", + "laborHours": 0.0, + "languages": [ + "Bash", + "JavaScript", + "Ruby", + "HTML", + "CSS", + "yml" + ], + "name": "Inl Open Ondemand Applications", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/HPC_OOD", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Inline_System.json b/agency-indexes/DoE/Inline_System.json new file mode 100644 index 00000000..877549f4 --- /dev/null +++ b/agency-indexes/DoE/Inline_System.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Inline_System replaces a small subset of file query and manipulation commands, on computing platforms that do not offer a complete standard POSIX environment.", + "homepageURL": "https://sourceforge.net/projects/inlinesystem", + "laborHours": 0.0, + "name": "Inline_System", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/inlinesystem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Innate_Immune_Response_Agent-based_Model.json b/agency-indexes/DoE/Innate_Immune_Response_Agent-based_Model.json new file mode 100644 index 00000000..5f0513c2 --- /dev/null +++ b/agency-indexes/DoE/Innate_Immune_Response_Agent-based_Model.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-19" + }, + "description": "An agent-based simulation of the innate immune response to bacterial infection.", + "laborHours": 1124.8, + "languages": [], + "name": "Innate Immune Response Agent-based Model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/iirabm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Institute_for_the_Design_of_Advanced_Energy_Systems_Integrated_Platform.json b/agency-indexes/DoE/Institute_for_the_Design_of_Advanced_Energy_Systems_Integrated_Platform.json new file mode 100644 index 00000000..03fef1be --- /dev/null +++ b/agency-indexes/DoE/Institute_for_the_Design_of_Advanced_Energy_Systems_Integrated_Platform.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christy.pecyna@netl.doe.gov" + }, + "date": { + "created": "2022-08-16", + "metadataLastUpdated": "2022-08-16" + }, + "description": "The IDAES Toolkit aims to provide multi-scale, simulation-based, open source computational tools and models to support the design, analysis, optimization, scale-up, operation and troubleshooting of innovative, advanced energy systems.\n\nThe ARPA-E FLECCS project extended existing models and optimization frameworks within the previously released open source IDAES Integrated Platform. These extensions are part of most recent 2022 release.", + "laborHours": 99788.0, + "languages": [], + "name": "Institute for the Design of Advanced Energy Systems Integrated Platform", + "organization": "National Energy Technology Laboratory (NETL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/IDAES/idaes-pse", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IDAES/idaes-pse", + "status": "Development", + "tags": [ + "DOE CODE", + "National Energy Technology Laboratory (NETL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Institute_for_the_Design_of_Advanced_Energy_Systems_Process_Systems_Engineering_Framework__IDAES_PSE_Framework__.json b/agency-indexes/DoE/Institute_for_the_Design_of_Advanced_Energy_Systems_Process_Systems_Engineering_Framework__IDAES_PSE_Framework__.json new file mode 100644 index 00000000..c5f63336 --- /dev/null +++ b/agency-indexes/DoE/Institute_for_the_Design_of_Advanced_Energy_Systems_Process_Systems_Engineering_Framework__IDAES_PSE_Framework__.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-30", + "metadataLastUpdated": "2019-09-24" + }, + "description": "IDAES PSE capabilities support the design and optimization of innovative new advanced Process Systems Engineering (PSE) capabilities to improve the efficiency and reliability of the existing fleet of coal-fired power plants while accelerating the development of a broad range of advanced fossil energy systems.", + "laborHours": 99788.0, + "languages": [], + "name": "Institute for the Design of Advanced Energy Systems Process Systems Engineering Framework (IDAES PSE Framework) ", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/IDAES/idaes-pse/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaes/idaes-pse", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Institutional_Transformation_v._2.6.json b/agency-indexes/DoE/Institutional_Transformation_v._2.6.json new file mode 100644 index 00000000..e00db4f0 --- /dev/null +++ b/agency-indexes/DoE/Institutional_Transformation_v._2.6.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-06-03", + "metadataLastUpdated": "2019-06-04" + }, + "description": " IX uses whole building analysis, and solar power cost algorithms to evaluate tradeoffs associated with alternative large-scale, long term facilities energy conservation strategies. It is designed to use existing energy simulation tools such as doe2.2 and SAMS to produce detailed results which are then processed at a higher level. 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The human aspect of the simulation code is focused in particular on the effects of human activities on land use and land cover change, but also includes aspects such as energy economies. The time frame for predictions with iESM is approximately 1970 through 2100.", + "laborHours": 6406374.4, + "name": "Integrated Earth System Model (iESM)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ACME-Climate/iESM/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ACME-Climate/iESM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Integrated_Network_Decompositions_and_Dynamic_Programming_for_Graph_Optimization__INDDGO_.json b/agency-indexes/DoE/Integrated_Network_Decompositions_and_Dynamic_Programming_for_Graph_Optimization__INDDGO_.json new file mode 100644 index 00000000..3ee107ef --- /dev/null +++ b/agency-indexes/DoE/Integrated_Network_Decompositions_and_Dynamic_Programming_for_Graph_Optimization__INDDGO_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. 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Existing technologies typically rely on a single method, and the main advantage of iPHoP is its ability to integrate the results from multiple methods into a single prediction. 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The InterGroup suite of protocols is a scalable group communication system that introduces an unusual approach to handling group membership, and supports a receiver-oriented selection of service. The protocols are intended for a wide-area network, with a large number of nodes, that has highly variable delays and a high message loss rate, such as the Internet. The levels of the message delivery service range from unreliable unordered to reliable timestamp ordered.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "InterGroup Protocols", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/InterProScan_SDK.json b/agency-indexes/DoE/InterProScan_SDK.json new file mode 100644 index 00000000..fc55a3e1 --- /dev/null +++ b/agency-indexes/DoE/InterProScan_SDK.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "This module contains the SDK wrap of the InterProScan annotation pipeline.", + "laborHours": 3708.8, + "languages": [], + "name": "InterProScan_SDK", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/InterProScan_SDK", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/InterSpec_v._1.0.8.json b/agency-indexes/DoE/InterSpec_v._1.0.8.json new file mode 100644 index 00000000..13ecefbb --- /dev/null +++ b/agency-indexes/DoE/InterSpec_v._1.0.8.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2024-07-26" + }, + "description": "SAND2021-4823 O InterSpec decodes and displays gamma radiation data from a variety of handheld, laboratory, and fixed installation detector types. Once loaded, InterSpec provides a means to interactively analyze the data via a peak-based methodology. InterSpec assists with isotope identification and determines the source strength and shielding characteristics of the measured item. 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Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++", + "JavaScript", + "C++", + "HTML" + ], + "name": "InterSpec v. 1.0.9", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/InterSpec", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.9" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Interactive_Corpus_Analysis_Tool.json b/agency-indexes/DoE/Interactive_Corpus_Analysis_Tool.json new file mode 100644 index 00000000..7e7836cd --- /dev/null +++ b/agency-indexes/DoE/Interactive_Corpus_Analysis_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "stewartsl@ornl.gov" + }, + "date": { + "created": "2023-04-27", + "metadataLastUpdated": "2023-04-27" + }, + "description": "The Interactive Corpus Analysis Tool (ICAT) is an interactive machine learning dashboard for unlabeled text/natural language processing datasets that allows a user to iteratively and visually define features, explore and label instances of their dataset, and simultaneously train a logistic regression model. 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It has been built by the National Renewable Energy Laboratory's (NREL) Mobility, Behavior, and Advanced Powertrains (MBAP) research group.\n\nThe software for the interactive landscape is located at https://github.com/NREL/mobility_landscapeapp\nThis repo includes all of the data and images specific to the Interactive Mobility \nData Landscape.", + "laborHours": 0.0, + "languages": [], + "name": "Interactive Mobility Data Landscape", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mobility_landscape", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Interactive_Mobility_Landscape_App.json b/agency-indexes/DoE/Interactive_Mobility_Landscape_App.json new file mode 100644 index 00000000..c2bef57d --- /dev/null +++ b/agency-indexes/DoE/Interactive_Mobility_Landscape_App.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-28", + "metadataLastUpdated": "2021-09-13" + }, + "description": "This is the companion repository to NREL's Interactive Mobility Data Landscape (SEE: DOE Code ID 61284. NREL SWR-21-09). \n\nThe landscapeapp is an upstream NPM module that supports building interactive landscape websites such as the CNCF Cloud Native Landscape (source) and the LF Artificial Intelligence Landscape (source). The application is managed by Dan Kohn of CNCF and is under active development by Andrey Kozlov (who did most of the development to date, 9/13/2021) and Jordi Noguera.", + "laborHours": 0.0, + "languages": [ + "JavaScript" + ], + "name": "Interactive Mobility Landscape App", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mobility_landscapeapp", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Interactive_Web_Mapping_Tools_And_Custom_Subsurface_Cross-sections_For_Interdisciplinary_Geologic_Investigation.json b/agency-indexes/DoE/Interactive_Web_Mapping_Tools_And_Custom_Subsurface_Cross-sections_For_Interdisciplinary_Geologic_Investigation.json new file mode 100644 index 00000000..031725c6 --- /dev/null +++ b/agency-indexes/DoE/Interactive_Web_Mapping_Tools_And_Custom_Subsurface_Cross-sections_For_Interdisciplinary_Geologic_Investigation.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2023-03-13" + }, + "description": "This code allows for a geologic cross-sectional profile to be obtained from a user-drawn profile line within a web map application.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Interactive Web Mapping Tools And Custom Subsurface Cross-sections For Interdisciplinary Geologic Investigation", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/SFWDSubsurface", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Interdependent_Water_And_Power_Infrastructure_Model.json b/agency-indexes/DoE/Interdependent_Water_And_Power_Infrastructure_Model.json new file mode 100644 index 00000000..36551cfb --- /dev/null +++ b/agency-indexes/DoE/Interdependent_Water_And_Power_Infrastructure_Model.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-01-31", + "metadataLastUpdated": "2025-01-31" + }, + "description": "The approach used is the Multi-Agent System (MAS) paradigms, where systems components are represented as agents, interacting both with each other, and with the environment in which they evolved. Agents behaviors correspond to components in the real Integrated Water-Power System. The model simulate actions and interactions of these (autonomous) agents to analyze their effects on the overall system. \nAgents in the water system capture components of water collection, treatment, transportation, distribution and use (e.g. pipe, canal, pump, water demands for agriculture, etc.). Agents in the power system capture components of power generation, transportation, distribution and use (electricity demands, sources, etc.).", + "laborHours": 744.8, + "languages": [ + "Python" + ], + "name": "Interdependent Water And Power Infrastructure Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Integrated_Water_Power_System", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Interpolating_Low_Time-Resolution_Forecast_Data.json b/agency-indexes/DoE/Interpolating_Low_Time-Resolution_Forecast_Data.json new file mode 100644 index 00000000..e95de120 --- /dev/null +++ b/agency-indexes/DoE/Interpolating_Low_Time-Resolution_Forecast_Data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Methodology that interpolates low time-resolution data (e.g., hourly) to high time-resolution (e.g., minutely) with variability patterns extracted from historical records. Magnitude of the variability inserted into the low time resolution data can be adjusted according to the installed capacity represented by the low time-resolution data compared to that by historical records. This approach enables detailed analysis of the impacts from wind and solar on power system intra-hour operations and balancing reserve requirements even with only hourly data. It also allows convenient creation of high resolution wind or solar generation data with various degree of variability to investigate their operational impacts. The methodology comprises of the following steps: 1. Smooth the historical data (set A) with an appropriate window length l to get its trend (set B); l can be a fraction of an hour (e.g., 15 minutes) or longer than an hour, of which the length of the variability patterns will be; 2. Extract the variable component (set C) of historical data by subtracting the smooth trend from it, i.e. set C = set A - set B 3. For each window length l of the variable component data set, find the average value x (will call it base component) of the corresponding window of the historical data set; 4. Define a series of segments (set D) that the values of data will be grouped into, e.g. (0, 0.1), (0.1, 0.2), ..., (0.9, 1.0) after normalization; Link each variability pattern to a data segment based on its corresponding base component x; after this step, each data segment should be linked to multiple variability patterns after this step; 5. Use spline function to interpolate the low time-resolution forecast data (set E) to become a high time-resolution smooth curve (set F); 6. Based on the window length l , calculate the average value y in each window length of set F; find the data segment that y belongs to; then randomly select one of the variability patterns linked to this data segment; 7. Add the selected variability pattern in each window to set F to get the high time-resolution data (set G) with variability observed from historical data set A; a coefficient k can be multiplied to the selected variability pattern to reflect the potential difference in variability between forecast set E and historical data set A caused by installation capacity and other factors. 8. After set G is constructed, variability statistics can be checked for set A and set G for comparison. Adjust the coefficient k if necessary to achieve desired variability in the reconstructed data.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Interpolating Low Time-Resolution Forecast Data", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Interpolation-Based_Composite_Derivative-Free_Optimization__IBCDFO__v0.01.json b/agency-indexes/DoE/Interpolation-Based_Composite_Derivative-Free_Optimization__IBCDFO__v0.01.json new file mode 100644 index 00000000..75c2972d --- /dev/null +++ b/agency-indexes/DoE/Interpolation-Based_Composite_Derivative-Free_Optimization__IBCDFO__v0.01.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-27", + "metadataLastUpdated": "2024-06-27" + }, + "description": "ICDFO is python and matlab/octave code for a set of for interpolation-based optimization methods for composite derivative-free optimization. These methods are applicable when a user wishes to maximize or minimize a function that depends on some blackbox component/simulation for which derivatives with respect to the decision variables are not available. The methods include pounders and goombah.", + "laborHours": 3040.0, + "languages": [], + "name": "Interpolation-Based Composite Derivative-Free Optimization (IBCDFO) v0.01", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/POptUS/IBCDFO", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Interpolation_Models_and_Error_Bounds_for_Verifiable_Scientific_Machine_Learning.json b/agency-indexes/DoE/Interpolation_Models_and_Error_Bounds_for_Verifiable_Scientific_Machine_Learning.json new file mode 100644 index 00000000..973604ae --- /dev/null +++ b/agency-indexes/DoE/Interpolation_Models_and_Error_Bounds_for_Verifiable_Scientific_Machine_Learning.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-01", + "metadataLastUpdated": "2024-04-11" + }, + "description": "This repository contains python scripts and numerical data accompanying the paper:\n\"Leveraging Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning,\" Tyler Chang, Andrew Gillette, Romit Maulik, 2024. The following subdirectories are included:\n- \"interpolants\" contains our interpolation scripts used for all studies\n- \"experiments\" contains scripts demonstrating our experiments with synthetic data\n- \"airfoil\" contains scripts demonstrating our experiments with the publicly available UIUC airfoil dataset. Further instructions are provided in READMEs within the sub-directories.", + "laborHours": 0.0, + "languages": [], + "name": "Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/interpML", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Interpretable,_Extensible_Linear_Regression_Model_for_Electron_Density_Prediction.json b/agency-indexes/DoE/Interpretable,_Extensible_Linear_Regression_Model_for_Electron_Density_Prediction.json new file mode 100644 index 00000000..1859d640 --- /dev/null +++ b/agency-indexes/DoE/Interpretable,_Extensible_Linear_Regression_Model_for_Electron_Density_Prediction.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-05-28", + "metadataLastUpdated": "2024-05-28" + }, + "description": "This code allows us to generate a model to predict ground state electron densities directly from atomic\nstructure thereby bypassing the need to perform direct DFT calculations. It is based on many body\ncorrelation descriptors defined in https://arxiv.org/abs/2004.14442 (IM release numbers: LLNL-JRNL-\n808791 and LLNL-JRNL-840698). The code reads in electron densities, in CHGCAR format used by the\nDFT code VASP, calculates many-body correlation descriptors based on atoms surrounding a grid point\nand then uses linear regression to obtain the fitting parameters.", + "laborHours": 2508.0, + "languages": [], + "name": "Interpretable, Extensible Linear Regression Model for Electron Density Prediction", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gopal-iyer/interpretable_ML_charge_density", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/InvenioRDM_Memento_Proxy.json b/agency-indexes/DoE/InvenioRDM_Memento_Proxy.json new file mode 100644 index 00000000..0b484453 --- /dev/null +++ b/agency-indexes/DoE/InvenioRDM_Memento_Proxy.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-22" + }, + "description": "The Memento Proxy software transforms Invenio systems on the web into repositories that are compliant with the Memento protocol.", + "laborHours": 425.6, + "languages": [], + "name": "InvenioRDM Memento Proxy", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/invenio-memento-proxy", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Inventory_of_Composable_Elements__ICE__v6.0.0.json b/agency-indexes/DoE/Inventory_of_Composable_Elements__ICE__v6.0.0.json new file mode 100644 index 00000000..92c9f3ba --- /dev/null +++ b/agency-indexes/DoE/Inventory_of_Composable_Elements__ICE__v6.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-26" + }, + "description": "The Inventory of Composable Elements (ICE) is an open source registry software platform for managing information about biological parts. It is capable of recording information about plasmids, microbial host strains and seeds, as well as DNA parts. Includes features such as DNA sequence visualization, editing and annotation, auto-aligning sequencing trace files against reference templates, SBOL XML/RDF support, and web-of-registries functionality. The web of registries functionality provides strong support for distributed interconnected use and enables sharing and transfer of biological parts across various independent ICE instances. ICE adopts modern software development principles, leveraging component-base frameworks, offering a REST API for convenient third-party integration and emphasizing scalability, security, and service integrations for dynamic content availability. The source code is hosted at https://github.com/JBEI/ice. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects.", + "laborHours": 45037.6, + "languages": [], + "name": "Inventory of Composable Elements (ICE) v6.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/ice", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/InversionNet.json b/agency-indexes/DoE/InversionNet.json new file mode 100644 index 00000000..5ea75f34 --- /dev/null +++ b/agency-indexes/DoE/InversionNet.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-09-15", + "metadataLastUpdated": "2022-09-15" + }, + "description": "InversionNet is a software to solve subsurface imaging problems. It leverages a convolutional neural network with an encoder-decoder structure to model the correspondence from seismic data to subsurface velocity structures.", + "laborHours": 0.0, + "languages": [], + "name": "InversionNet", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/OpenFWI", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Invocation_Service.json b/agency-indexes/DoE/Invocation_Service.json new file mode 100644 index 00000000..46eeebad --- /dev/null +++ b/agency-indexes/DoE/Invocation_Service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "The invocation service provides remote invocation of commands. A java script browser client for interactive remote invocation (IRIS) is included. This deploys the client, service and javascript web application.", + "laborHours": 4423.2, + "languages": [], + "name": "Invocation Service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/invocation", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IonControl_v._1.0.json b/agency-indexes/DoE/IonControl_v._1.0.json new file mode 100644 index 00000000..4d5de930 --- /dev/null +++ b/agency-indexes/DoE/IonControl_v._1.0.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "The IonControl software is a set of python scripts and Field-Programmable-Gate-Array (FPGA) code designed to control a trapped ion research experiment. It enables one to generate the pulses (time resolution: 20ns) necessary to control the quantum states of trapped ions and allows one to collect and analyze measurement results from trapped ion systems.", + "laborHours": 228410.4, + "languages": [ + "CSS", + "HTML", + "TeX", + "JavaScript", + "PostScript", + "Python" + ], + "name": "IonControl v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/IonControl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ion_Beam_Simulator.json b/agency-indexes/DoE/Ion_Beam_Simulator.json new file mode 100644 index 00000000..7c455dd8 --- /dev/null +++ b/agency-indexes/DoE/Ion_Beam_Simulator.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "IBSimu(Ion Beam Simulator) is a computer program for making two and three dimensional ion optical simulations. The program can solve electrostatic field in a rectangular mesh using Poisson equation using Finite Difference method (FDM). The mesh can consist of a coarse and a fine part so that the calculation accuracy can be increased in critical areas of the geometry, while most of the calculation is done quickly using the coarse mesh. IBSimu can launch ion beam trajectories into the simulation from an injection surface or fomo plasma. Ion beam space charge of time independent simulations can be taken in account using Viasov iteration. Plasma is calculated by compensating space charge with electrons having Boltzmann energy distribution. The simulation software can also be used to calculate time dependent cases if the space charge is not calculated. Software includes diagnostic tools for plotting the geometry, electric field, space charge map, ion beam trajectories, emittance data and beam profiles.", + "homepageURL": "https://sourceforge.net/projects/ibsimu", + "laborHours": 0.0, + "name": "Ion Beam Simulator", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/ibsimu", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ion_mobility_control_software__Ion_Trap_coupled_.json b/agency-indexes/DoE/Ion_mobility_control_software__Ion_Trap_coupled_.json new file mode 100644 index 00000000..b09887e5 --- /dev/null +++ b/agency-indexes/DoE/Ion_mobility_control_software__Ion_Trap_coupled_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Ion Mobility control software designed to work specifically with Thermo Fisher Scientific ion trap (specifically the Exactive / Q Exactive)", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Ion mobility control software (Ion Trap coupled)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ipmiping_V1.0.json b/agency-indexes/DoE/Ipmiping_V1.0.json new file mode 100644 index 00000000..266917c4 --- /dev/null +++ b/agency-indexes/DoE/Ipmiping_V1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Ipmiping is a collection of two programs, impiping and rmcpping. Both ipmiping and rmcpping are similar to the Unix/Linux ping utility, except they use a different network protocol. Ipmiping uses Intelligent Platform Management Interface (IPMI) messages to discover if a remote destination supports IPMI. Rmcpping uses remote management control protocol (RMCP) messages to discover if a remote destination supports RMCP.", + "homepageURL": "https://www.gnu.org/software/freeipmi", + "laborHours": 0.0, + "languages": [], + "name": "Ipmiping V1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ipopt_Interface_to_Re::Solve_Linear_Solver.json b/agency-indexes/DoE/Ipopt_Interface_to_Re::Solve_Linear_Solver.json new file mode 100644 index 00000000..92ef5104 --- /dev/null +++ b/agency-indexes/DoE/Ipopt_Interface_to_Re::Solve_Linear_Solver.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "peless@ornl.gov" + }, + "date": { + "created": "2025-04-25", + "metadataLastUpdated": "2025-04-25" + }, + "description": "The software provides Ipopt optimization package an interface to the Re::Solve linear solver library. Re::Solve features GPU-resident direct and iterative linear solvers that could be used to accelerate optimization computations.", + "laborHours": 106688.8, + "languages": [], + "name": "Ipopt Interface to Re::Solve Linear Solver", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/Ipopt", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Irrigation_Monitor.json b/agency-indexes/DoE/Irrigation_Monitor.json new file mode 100644 index 00000000..eea0be1d --- /dev/null +++ b/agency-indexes/DoE/Irrigation_Monitor.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-10-11", + "metadataLastUpdated": "2023-10-11" + }, + "description": "This software gathers irrigation data as well as evapotranspiration rates to understand the on field water balances and track water usage.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Irrigation Monitor", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/irrmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/IsoMatchMS.json b/agency-indexes/DoE/IsoMatchMS.json new file mode 100644 index 00000000..0a2afb2f --- /dev/null +++ b/agency-indexes/DoE/IsoMatchMS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-05", + "metadataLastUpdated": "2024-08-05" + }, + "description": "An R package built to match proteoform isotoping distributions to mass spectrum, quantitatively select\nmatches of high quality, and visualize those matches in a trelliscope display.", + "laborHours": 3085.6, + "languages": [], + "name": "IsoMatchMS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-HubMAP-Proteoform-Suite/IsoMatchMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Isopod__inverse_Optimization_And_Design_:_Moose-based_Application_For_Performing_Inverse_Optimization_On_Multiphysics_Modeling_And_Simulation.json b/agency-indexes/DoE/Isopod__inverse_Optimization_And_Design_:_Moose-based_Application_For_Performing_Inverse_Optimization_On_Multiphysics_Modeling_And_Simulation.json new file mode 100644 index 00000000..2ae57aba --- /dev/null +++ b/agency-indexes/DoE/Isopod__inverse_Optimization_And_Design_:_Moose-based_Application_For_Performing_Inverse_Optimization_On_Multiphysics_Modeling_And_Simulation.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-01-13", + "metadataLastUpdated": "2023-03-08" + }, + "description": "ISOPOD (InverSe OPtimizatiOn and Design) will be a MOOSE (Multiphysics Object Oriented Simulation Environment)-based framework which will iteratively estimate the parameters by minimizing the difference between simulated and experimental observables. While inverse optimization has long been used for parameter estimation, the unique feature of ISOPOD is rapid solution of new inverse problems, leading to accelerated Research, Development and Demonstration (RD&D) for complex parameter estimation problems. This will be achieved by extending the software structure of MOOSE to inverse optimization, as well as building on the unique automatic differentiation feature of MOOSE.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Isopod (inverse Optimization And Design): Moose-based Application For Performing Inverse Optimization On Multiphysics Modeling And Simulation", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/isopod", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Iterative_multi-task_learning_and_inference_from_seismic_images.json b/agency-indexes/DoE/Iterative_multi-task_learning_and_inference_from_seismic_images.json new file mode 100644 index 00000000..b11f9a9d --- /dev/null +++ b/agency-indexes/DoE/Iterative_multi-task_learning_and_inference_from_seismic_images.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "Seismic interpretation aims to extract quantitative and interpretable attributes from a seismic image produced using some migration method to inform characteristics of a subsurface reservoir or target of interest. Current paradigms for computing seismic attributes mostly rely on single-task algorithms. We develop an iterative, multi-task machine learning method to learn and infer multiple attributes from a seismic image. This method is composed of two stages: a multi-task inference stage and a multi-modal, multi-task refinement stage. The basic mechanism of this method is that we train a multi-task inference neural network (NN) to estimate a set of attributes, including a relative geological time (RGT), a denoised higher-resolution (DHR) seismic image, and multiple fault attributes (including probability, dip, and strike), from a low-resolution, noisy seismic image; then we input the inferred attributes to a multi-task refinement NN to enhance the raw inference results iteratively. The two multi-task NNs are trained separately based on synthetic seismic images and associated attributes generated by a geological modeling algorithm. The software we intend to release is a PyTorch implementation of this multi-task learning method for both 2D and 3D cases along with scripts to run the training/validation. The algorithm and software can be a useful tool for automatic seismic interpretation.", + "laborHours": 0.0, + "languages": [], + "name": "Iterative multi-task learning and inference from seismic images", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/mtl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/J1939_Decoder.json b/agency-indexes/DoE/J1939_Decoder.json new file mode 100644 index 00000000..72b2aeb9 --- /dev/null +++ b/agency-indexes/DoE/J1939_Decoder.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "olattjv@ornl.gov" + }, + "date": { + "created": "2024-08-20", + "metadataLastUpdated": "2024-08-20" + }, + "description": "The J1939 Decoder package is a set of scripts that will allow one to decode J1939 messages.", + "laborHours": 15.2, + "languages": [], + "name": "J1939 Decoder", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/joornl/J1939-Decoder", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JA3.json b/agency-indexes/DoE/JA3.json new file mode 100644 index 00000000..c95a6635 --- /dev/null +++ b/agency-indexes/DoE/JA3.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "JA3 is a method for creating SSL/TLS client fingerprints that are easy to produce and can be easily shared for threat intelligence.", + "laborHours": 304.0, + "languages": [], + "name": "JA3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/ja3", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JA3_for_Bro.json b/agency-indexes/DoE/JA3_for_Bro.json new file mode 100644 index 00000000..f2a1a0cc --- /dev/null +++ b/agency-indexes/DoE/JA3_for_Bro.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "This module adds support for JA3 ssl fingerprinting for Bro IDS.", + "laborHours": 0.0, + "languages": [], + "name": "JA3 for Bro", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/bro-ja3", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JADE.json b/agency-indexes/DoE/JADE.json new file mode 100644 index 00000000..6fe65400 --- /dev/null +++ b/agency-indexes/DoE/JADE.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-04-05", + "metadataLastUpdated": "2022-07-26" + }, + "description": "JADE provides a simple, flexible interface to submit jobs to an HPC. JADE is an HPC workflow management system that enables researchers to run simulations efficiently. It provides a simple, flexible interface to define jobs, as well as dependencies between jobs, and then dispatch them to an HPC with maximized parallelization. It also provides detailed error reporting and resource utilization statistics to aid in debugging problems.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "JADE", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/jade", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JAT-Box.json b/agency-indexes/DoE/JAT-Box.json new file mode 100644 index 00000000..36db996a --- /dev/null +++ b/agency-indexes/DoE/JAT-Box.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The JAT (Just Add Tests) Box is a preconfigured Behat Vagrant virtual machine.", + "laborHours": 152.0, + "languages": [], + "name": "JAT-Box", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/jatbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JAva_GUi_for_Applied_Research__JAGUAR__v_3.0.json b/agency-indexes/DoE/JAva_GUi_for_Applied_Research__JAGUAR__v_3.0.json new file mode 100644 index 00000000..007b1f6c --- /dev/null +++ b/agency-indexes/DoE/JAva_GUi_for_Applied_Research__JAGUAR__v_3.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-24" + }, + "description": "JAGUAR is a Java software tool for automatically rendering a graphical user interface (GUI) from a structured input specification. It is designed as a plug-in to the Eclipse workbench to enable users to create, edit, and externally execute analysis application input decks and then view the results. JAGUAR serves as a GUI for Sandia's DAKOTA software toolkit for optimization and uncertainty quantification. It will include problem (input deck)set-up, option specification, analysis execution, and results visualization. Through the use of wizards, templates, and views, JAGUAR helps uses navigate the complexity of DAKOTA's complete input specification. JAGUAR is implemented in Java, leveraging Eclipse extension points and Eclipse user interface. JAGUAR parses a DAKOTA NIDR input specification and presents the user with linked graphical and plain text representations of problem set-up and option specification for DAKOTA studies. After the data has been input by the user, JAGUAR generates one or more input files for DAKOTA, executes DAKOTA, and captures and interprets the results", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "JAva GUi for Applied Research (JAGUAR) v 3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/jaguar", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JBEI_Registry.json b/agency-indexes/DoE/JBEI_Registry.json new file mode 100644 index 00000000..42f25d38 --- /dev/null +++ b/agency-indexes/DoE/JBEI_Registry.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "The JBEI Registry is a software to store and manage to a database of biological parts. It is intended to be used as a web service that is accessed via a web browser. It is also capable of running as a desktop program for a single user. The registry software stores, indexes, categories, and allows users to enter, search, retrieve, and construct biological constructs in silico. It is also able to communicate with other Registries for data sharing and exchange.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "JBEI Registry", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/JBlulce_Data_Acquisition_Software_for_Macromolecular_Crystallography.json b/agency-indexes/DoE/JBlulce_Data_Acquisition_Software_for_Macromolecular_Crystallography.json new file mode 100644 index 00000000..4e0d6457 --- /dev/null +++ b/agency-indexes/DoE/JBlulce_Data_Acquisition_Software_for_Macromolecular_Crystallography.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "JBlulce (Java Beam Line Universal Integrated Configuration Environment is a data acquisition software for macromolecular crystallography conforming user interface of the SSRL Blulce that has become a de-factor standard in the field. Besides this interface conformity, JBlulce is a unique system in terms of architecture, spec, capability and software implementation. It features only two software layers, the JBlulce clients and the EPICS servers, as compared to three layers present in Blulce and most of similar systems. This layers reduction provides a faster communication with hardware and an easier access to advanced hardware capabilities like on-the-fly scanning. Then JBlulce clients are designed to operate in parallel with the other beamline controls which streamlines the tasks performed by staff such as beamline preparation, maintenance, auditing and user assistance. Another distinction is the deployment of multiple plugins that can be written in any programming language thus involving more staff into the development. further on, JBlulce makes use of unified motion controls allowing for easy scanning and optimizing of any beamline component. Finally, the graphic interface is implemented in Java making full use of rich Java libraries and Jave IDE for debugging. to compare, Blulce user interface is implemented with aging Tcl/tk language providing very restricted capabilities. JBlulce makes full use of the industrial power and wide drivers selection of EPICS in controlling hardware; all hardware communication is routed via multiple EPICS servers residing on local area network. JBlulce also includes several EPICS State Notation servers aimed at making hardware communication more robust. Besides using EPICS for controlling hardware, JBlulce extensively uses EPICS databases for efficient communications between multiple instances of JBlulce clients and JBlulce plugins that can run in parallel on different computers. All of the above makes JBlulce one of the biggest and most sophisticated EPICS client projects to date. JBlulce configuration is stored in my SQL database which provides flexibility in tuning the system. The database is also accessible by the plugins. From the users perspective JBlulce provides all standard features of data acquisition software for macromolecular crystallography plus such unique capabilities as one click beamline energy change that may involve switching undulator harmonics, mirrors lanes and beam realignment, automated diffraction rtastering for finding small crystals and sweet spots on poorly diffracting crystals with automated scoring of raster cells by the number of reflections; data collection along a vector; automated on-the-fly fluorescent tastering, a faster and lower-irradiation compliment to the diffraction raster; fully automated fluorescence measurements for MAD that include signal optimization, fast on the fly energy scanning and automated adapting of scan range to chemical shifts; fly-scan minibeam realignment; automated loop and crystal centering, controls for sample automounter, automated screening, data collection auditing, remote access and a lot more.", + "homepageURL": "https://www.gmca.aps.anl.gov/jbluice-epics", + "laborHours": 0.0, + "languages": [ + "SUN JDK 1.6, Perl 5, EPICS 3.14, SNL 2.0" + ], + "name": "JBlulce Data Acquisition Software for Macromolecular Crystallography", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.gmca.aps.anl.gov/jbluice-epics/jbluice-license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gmca.aps.anl.gov/jbluice-epics", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/JChristopherEllis_P-Finder.json b/agency-indexes/DoE/JChristopherEllis_P-Finder.json new file mode 100644 index 00000000..0f0893aa --- /dev/null +++ b/agency-indexes/DoE/JChristopherEllis_P-Finder.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ellisjc@ornl.gov" + }, + "date": { + "created": "2019-10-30", + "metadataLastUpdated": "2019-10-30" + }, + "description": "P Finder is a GUI software application for the fast identification of the rnpB gene in prokaryote genomes", + "laborHours": 0.0, + "languages": [], + "name": "JChristopherEllis/P-Finder", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JChristopherEllis/P-Finder", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JEGA_V_2.3.json b/agency-indexes/DoE/JEGA_V_2.3.json new file mode 100644 index 00000000..d9e0bdb9 --- /dev/null +++ b/agency-indexes/DoE/JEGA_V_2.3.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-11-05" + }, + "description": "JEGA is a software package that implements a multi-objective genetic algorithm (MOGA) for solution to multi-objective optimization problems (MOPS) and a single objective genetic algorithm (SOGA) for solution to single objective optimization problems (SOPS). JEGA is highly configurable and provides a rich set of algorithmic components for tailored optimization. It has been used successfully on many problems by users both internal and external to Sandia. By employing object-oriented design to implement abstractions of the key components making up the algorithms, JEGA provides a flexible and extensible problem-solving environment for design and performance analysis of computational models.", + "homepageURL": "https://dakota.sandia.gov", + "laborHours": 3988282.4, + "languages": [ + "C++ compiler" + ], + "name": "JEGA V 2.3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://dakota.sandia.gov/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/JGCRI_fldgen.json b/agency-indexes/DoE/JGCRI_fldgen.json new file mode 100644 index 00000000..6cc0c354 --- /dev/null +++ b/agency-indexes/DoE/JGCRI_fldgen.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-01-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Generate random global temperature fields with spatial and temporal correlation derived from an ESM\nAs of version 2.0, fldgen allows to emulate any climate variable, not just ones that are approximately normally distributed, and it allows us to emulate climate variables in combinations, such as temperature and precipitation. These new capabilities can be used for risk modeling in areas such as drought and it agricultural impacts, where both temperature and moisture play a role.", + "laborHours": 988.0, + "languages": [], + "name": "JGCRI/fldgen", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/fldgen", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JGCRI_gcamfaostat.json b/agency-indexes/DoE/JGCRI_gcamfaostat.json new file mode 100644 index 00000000..01838fb1 --- /dev/null +++ b/agency-indexes/DoE/JGCRI_gcamfaostat.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-03-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An R package to prepare, process, and synthesize FAOSTAT data for global agroeconomic and multisector dynamic modeling", + "laborHours": 0.0, + "languages": [], + "name": "JGCRI/gcamfaostat", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/gcamfaostat", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JGCRI_hectordata.json b/agency-indexes/DoE/JGCRI_hectordata.json new file mode 100644 index 00000000..83e4a1d9 --- /dev/null +++ b/agency-indexes/DoE/JGCRI_hectordata.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Prepare and format the inputs for Hector. This software was developed out of a need to help support Hector, PNNL\u2019s simple climate model continue to grow", + "laborHours": 0.0, + "languages": [], + "name": "JGCRI/hectordata", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jgcri/hectordata", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JGCRI_hydro-emulator.json b/agency-indexes/DoE/JGCRI_hydro-emulator.json new file mode 100644 index 00000000..a655961f --- /dev/null +++ b/agency-indexes/DoE/JGCRI_hydro-emulator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-05-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The hydrological emulator (HE) was built to mimic complex global hydrological models (GHMs) at a range of spatial scales. The HE was written in MATLAB and utilizes a genetic algorithm to calibrate the a, b, c, d, m parameters from the ABCD runoff algorithm to observed runoff from GHMs when forced by the same climate data. The HE employs two methods to choose from when processing basin data: lumped (by basin) and distributed (gridded). Both methods can be evaluated using the built-in Kling-Gupta efficiency as a measure of model performance when compared to the outputs from the more complex GHM. Testing shows that the HE is 7 orders of magnitude faster then the widely used Variable Infiltration Capacity (VIC) GHM.", + "laborHours": 2067.2, + "languages": [], + "name": "JGCRI/hydro-emulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/hydro-emulator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JGCRI_metis.json b/agency-indexes/DoE/JGCRI_metis.json new file mode 100644 index 00000000..bb34c8be --- /dev/null +++ b/agency-indexes/DoE/JGCRI_metis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Sub-Regional Nexus Modeling\nMetis provides a framework allowing analysis of dynamics across multiple sectors including energy, water, land and socioeconomics at variable spatial and temporal scales. It is designed to be a flexible tool which can take inputs from both global integrated assessment models (IAMs) which capture global dynamics as well as more detailed models which capture specific sub-regional and sectoral details at finer resolutions. Metis integrates across tools by sharing data in standardized formats.", + "laborHours": 14348.8, + "languages": [], + "name": "JGCRI/metis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/metis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JGCRI_persephone.json b/agency-indexes/DoE/JGCRI_persephone.json new file mode 100644 index 00000000..29b7c48c --- /dev/null +++ b/agency-indexes/DoE/JGCRI_persephone.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "crop model yield change emulation", + "laborHours": 1748.0, + "languages": [], + "name": "JGCRI/persephone", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/persephone", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JGCRI_rmap.json b/agency-indexes/DoE/JGCRI_rmap.json new file mode 100644 index 00000000..2cb107fb --- /dev/null +++ b/agency-indexes/DoE/JGCRI_rmap.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Mapping software with pre-loaded global and local maps", + "laborHours": 0.0, + "languages": [], + "name": "JGCRI/rmap", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/rmap", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JGCRI_stitches.json b/agency-indexes/DoE/JGCRI_stitches.json new file mode 100644 index 00000000..91a28be4 --- /dev/null +++ b/agency-indexes/DoE/JGCRI_stitches.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Amalgamate existing climate data to create monthly climate variable fields. The STITCHES python library provides a user-friendly interface to top-down climate emulation.", + "laborHours": 0.0, + "languages": [], + "name": "JGCRI/stitches", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jgcri/stitches", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JGI_Import_Tool.json b/agency-indexes/DoE/JGI_Import_Tool.json new file mode 100644 index 00000000..96952289 --- /dev/null +++ b/agency-indexes/DoE/JGI_Import_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-25", + "metadataLastUpdated": "2020-08-25" + }, + "description": "This is a tool for incorporating an object imported via the JGI-to-KBase, aka \"Push to KBase\" service into a user's existing or new narrative. This was originally a component of the dataview plugin, but now lives separately.", + "laborHours": 258.4, + "languages": [], + "name": "JGI Import Tool", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-jgi-import", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JGI_Metagenome_Assembly_in_KBase.json b/agency-indexes/DoE/JGI_Metagenome_Assembly_in_KBase.json new file mode 100644 index 00000000..ee767748 --- /dev/null +++ b/agency-indexes/DoE/JGI_Metagenome_Assembly_in_KBase.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "Contains apps for running the JGI metagenome assembly pipeline.", + "laborHours": 2097.6, + "languages": [], + "name": "JGI Metagenome Assembly in KBase", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/jgi_mg_assembly", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JGI_Search_Plugin.json b/agency-indexes/DoE/JGI_Search_Plugin.json new file mode 100644 index 00000000..9ca5ad69 --- /dev/null +++ b/agency-indexes/DoE/JGI_Search_Plugin.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "A kbase ui plugin for searching JGI JAMO data and copying it to a user's KBase staging area.", + "laborHours": 12296.8, + "languages": [], + "name": "JGI Search Plugin", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-jgi-search", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JOBS_EV.json b/agency-indexes/DoE/JOBS_EV.json new file mode 100644 index 00000000..1518321b --- /dev/null +++ b/agency-indexes/DoE/JOBS_EV.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-12-30", + "metadataLastUpdated": "2021-12-30" + }, + "description": "JOBS EV estimates economic impact associated with deploying electric vehicle supply equipment. It is a derivative of the other JOBS models available at the ES website.", + "homepageURL": "https://jobsfc.es.anl.gov", + "laborHours": 0.0, + "languages": [], + "name": "JOBS EV", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://jobsfc.es.anl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/JPype.json b/agency-indexes/DoE/JPype.json new file mode 100644 index 00000000..623ee8f2 --- /dev/null +++ b/agency-indexes/DoE/JPype.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-10-21", + "metadataLastUpdated": "2020-10-21" + }, + "description": "JPype is a Python module to provide full access to Java from within Python. It allows Python to make use of Java only libraries, exploring and visualization of Java structures, development and testing of Java libraries, scientific computing, and much more. By gaining the best of both worlds using Python for rapid prototyping and Java for strong typed production code, JPype provides a powerful environment for engineering and code development. This is achieved not through re-implementing Python, as Jython has done, but rather through interfacing at the native level in both virtual machines. This shared memory based approach achieves decent computing performance, while providing the access to the entirety of CPython and Java libraries.", + "laborHours": 34656.0, + "languages": [], + "name": "JPype", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Thrameos/jpype", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JSAC.json b/agency-indexes/DoE/JSAC.json new file mode 100644 index 00000000..3d076091 --- /dev/null +++ b/agency-indexes/DoE/JSAC.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-10-30", + "metadataLastUpdated": "2023-10-30" + }, + "description": "JSAC is a Java implementation of the Seismic Analysis Code (SAC2000,\nhttps://github.com/LLNL/SAC2000). It is intended to bring the most commonly used features of SAC2000\nup to date with modern standards, support parallelized computation where possible, and implement\nimprovements in algorithms and numerics.", + "laborHours": 0.0, + "languages": [], + "name": "JSAC", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/JSAC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JSONRPCBase.json b/agency-indexes/DoE/JSONRPCBase.json new file mode 100644 index 00000000..7324af0d --- /dev/null +++ b/agency-indexes/DoE/JSONRPCBase.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-02", + "metadataLastUpdated": "2020-09-02" + }, + "description": "Simple JSON-RPC service without transport layer. This library is intended as an auxiliary library for easy an implementation of JSON-RPC services with Unix/TCP socket like transport protocols that do not have complex special requirements. You need to utilize some suitable transport protocol with this library to actually provide a working JSON-RPC service.", + "laborHours": 395.2, + "languages": [], + "name": "JSONRPCBase", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/jsonrpcbase", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JacketSE_[SWR-14-23].json b/agency-indexes/DoE/JacketSE_[SWR-14-23].json new file mode 100644 index 00000000..f29e4520 --- /dev/null +++ b/agency-indexes/DoE/JacketSE_[SWR-14-23].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "THIS REPOSITORY IS DEPRECATED AND WAS ARCHIVED (READ-ONLY) on June 19, 2020.\n\nWISDEM has moved to a single, integrated repository at https://github.com/wisdem/wisdem\n\nJacketSE is a systems engineering model for 3 and 4-legged lattice structures (jackets) supporting tubular steel towers for offshore wind turbines. A module for static hydrodynamic, aerodynamic, and structural design and analysis of wind turbine jacket and towers within the Systems Engineering toolbox.", + "laborHours": 27861.6, + "languages": [ + "Fortran", + "Python" + ], + "name": "JacketSE [SWR-14-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/JacketSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Jali_-_Unstructured_Mesh_Infrastructure_for_Multi-Physics_Applications.json b/agency-indexes/DoE/Jali_-_Unstructured_Mesh_Infrastructure_for_Multi-Physics_Applications.json new file mode 100644 index 00000000..42438404 --- /dev/null +++ b/agency-indexes/DoE/Jali_-_Unstructured_Mesh_Infrastructure_for_Multi-Physics_Applications.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Jali is a parallel unstructured mesh infrastructure library designed for use by multi-physics simulations. It supports 2D and 3D arbitrary polyhedral meshes distributed over hundreds to thousands of nodes. Jali can read write Exodus II meshes along with fields and sets on the mesh and support for other formats is partially implemented or is (https://github.com/MeshToolkit/MSTK), an open source general purpose unstructured mesh infrastructure library from Los Alamos National Laboratory. While it has been made to work with other mesh frameworks such as MOAB and STKmesh in the past, support for maintaining the interface to these frameworks has been suspended for now. Jali supports distributed as well as on-node parallelism. Support of on-node parallelism is through direct use of the the mesh in multi-threaded constructs or through the use of \"tiles\" which are submeshes or sub-partitions of a partition destined for a compute node.", + "laborHours": 16841.6, + "name": "Jali - Unstructured Mesh Infrastructure for Multi-Physics Applications", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/jali", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Jammy.json b/agency-indexes/DoE/Jammy.json new file mode 100644 index 00000000..d47ddad5 --- /dev/null +++ b/agency-indexes/DoE/Jammy.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "brownjm@ornl.gov" + }, + "date": { + "created": "2023-04-27", + "metadataLastUpdated": "2023-04-27" + }, + "description": "Julia language version of the SAMMY R-matrix code", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "Jammy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/brownjm1968/Jammy", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JaqalPaq_v.1.1.json b/agency-indexes/DoE/JaqalPaq_v.1.1.json new file mode 100644 index 00000000..f6906f45 --- /dev/null +++ b/agency-indexes/DoE/JaqalPaq_v.1.1.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-07-29" + }, + "description": "Jaqal-pup (Jaqal Programming Utilities Project) is a high-level Python metaprogramming interface for Jaqal, a quantum programming language for near-term quantum hardware (see https://arxiv.org/abs/2003.09382 for a description of Jaqal). In addition to parsing and writing out Jaqal programs, it includes the ability to read in and write out quantum programs in other languages and frameworks, e.g. Qiskit (IBM), Quil (Rigetti), Cirq (Google), Q# (Microsoft), ProjectQ (ETH Zurich), and tket (Cambridge Quantum Computing). It implements a gate scheduler, an emulator of a small-scale quantum computer programmed using Jaqal, and tie-ins for other simulation back-ends. 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It can be used with any data acquisition system, providing that an appropriate data access interface is developed. 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It primarily reads .csv files and then sends those via HTTP or Websocket requests to an external instance of DeepLynx. 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The software was designed to allow scientists to enqueue, run, and accumulate results from computational experiments in an efficient, manageable manner. 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Organization details of a directory\ntree are encoded in Jobfiles which serve as an index of files/scripts, and indicate their purpose when deploying or\nsetting up a job. 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The purpose of JAWS is to improve the reusability and robustness of bioinformatic (or any) workflows in evolving and/or diverse high-performance computing (HPC), large cluster, and cloud environments. JAWS moves data and code to user-specified compute resources, executes computation, and returns results. JAWS implements Cromwell, developed at the Broad Institute, to make use of Workflow Description Language (WDL). Additionally, JAWS implements containers (compatible with Docker, Shifter, and Singularity) to ensure use of well-defined compute environments and workflow task codebases. 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Juqbox.jl is written in the Julia programming language which, among many other features, provides a convenient interface to the Ipopt library.", + "laborHours": 0.0, + "languages": [], + "name": "Juqbox.jl", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Juqbox.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Justice_40_Tool__J40_Tool__v1.0.json b/agency-indexes/DoE/Justice_40_Tool__J40_Tool__v1.0.json new file mode 100644 index 00000000..1cfe26fc --- /dev/null +++ b/agency-indexes/DoE/Justice_40_Tool__J40_Tool__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-10-03", + "metadataLastUpdated": "2023-10-03" + }, + "description": "The Justice 40 tool provides a quantitative framework to support decision-making around equitable energy interventions at the community level. 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Mathematically, this problem is formalized as an optimization model and formulated as a linear program.", + "laborHours": 0.0, + "languages": [], + "name": "Justice 40 Tool (J40 Tool) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNLgrid/j40model", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Juxtaposer_v._1.0.json b/agency-indexes/DoE/Juxtaposer_v._1.0.json new file mode 100644 index 00000000..17755a9f --- /dev/null +++ b/agency-indexes/DoE/Juxtaposer_v._1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This software collects sequence reads from Illumina next-generation sequencing to identify the counts of reads that support the mobilization of DNA.", + "laborHours": 1337.6, + "languages": [ + "Perl" + ], + "name": "Juxtaposer v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Juxtaposer", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/K-anonymization.json b/agency-indexes/DoE/K-anonymization.json new file mode 100644 index 00000000..24682de5 --- /dev/null +++ b/agency-indexes/DoE/K-anonymization.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-09-07", + "metadataLastUpdated": "2025-04-14" + }, + "description": "New algorithms to de-identify geolocations.\nA unique feature of our algorithms is the ability to compare de-identified values that are similar but not the same", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 27360.0, + "languages": [], + "name": "K-anonymization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KARMA4.json b/agency-indexes/DoE/KARMA4.json new file mode 100644 index 00000000..5f45ea12 --- /dev/null +++ b/agency-indexes/DoE/KARMA4.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-05", + "metadataLastUpdated": "2024-07-19" + }, + "description": "KARMA4 is a C++ library for autoregressive moving average (ARMA) modeling and forecasting of time-series data while incorporating both process and observation error. 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end of file diff --git a/agency-indexes/DoE/KBase_SDK.json b/agency-indexes/DoE/KBase_SDK.json new file mode 100644 index 00000000..a2788312 --- /dev/null +++ b/agency-indexes/DoE/KBase_SDK.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "The KBase SDK is a set of tools for developing KBase Apps that can be dynamically registered and run on the KBase platform. 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This is specifically designed to run on HPC-class resources and is currently designed to specifically for systems at NERSC (www.nersc.gov).", + "laborHours": 1976.0, + "languages": [], + "name": "KBase SDK version of HipMer", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/kbase_hipmer", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KBase_Search.json b/agency-indexes/DoE/KBase_Search.json new file mode 100644 index 00000000..172a4995 --- /dev/null +++ b/agency-indexes/DoE/KBase_Search.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "The KBase Search module is responsible for providing a search capability that guides users to KBase data of interest. ", + "laborHours": 11476.0, + "languages": [], + "name": "KBase Search", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/search", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KBase_Static_Assets_for_UI.json b/agency-indexes/DoE/KBase_Static_Assets_for_UI.json new file mode 100644 index 00000000..3a1ac9f8 --- /dev/null +++ b/agency-indexes/DoE/KBase_Static_Assets_for_UI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-10", + "metadataLastUpdated": "2020-08-10" + }, + "description": "Store and serve static assets for KBase frontends.", + "laborHours": 106.4, + "languages": [], + "name": "KBase Static Assets for UI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/ui-assets", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KBase_System_Metrics.json b/agency-indexes/DoE/KBase_System_Metrics.json new file mode 100644 index 00000000..698d339c --- /dev/null +++ b/agency-indexes/DoE/KBase_System_Metrics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This repository contains code for gathering and uploading KBase system metrics from Condor API such as memory, disk and cpu usage, as well as job and queue information. 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", + "laborHours": 2948.8, + "languages": [], + "name": "KBase UI ES6 Library", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-common-es6", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KBase_UI_Feeds_Plugin.json b/agency-indexes/DoE/KBase_UI_Feeds_Plugin.json new file mode 100644 index 00000000..578f6a1d --- /dev/null +++ b/agency-indexes/DoE/KBase_UI_Feeds_Plugin.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "A kbase-ui plugin which provides a view of a user's 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for viewing legacy methods and apps.", + "laborHours": 228.0, + "languages": [], + "name": "KBase UI Method View", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-methodview", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KBase_UI_Plugin:_Ontology.json b/agency-indexes/DoE/KBase_UI_Plugin:_Ontology.json new file mode 100644 index 00000000..ae398d03 --- /dev/null +++ b/agency-indexes/DoE/KBase_UI_Plugin:_Ontology.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-02", + "metadataLastUpdated": "2020-09-02" + }, + "description": "This is a plugin for kbase-ui, which allows a KBase user to view individual ontological terms, and navigate within the ontology to which that term belongs.", + "laborHours": 17328.0, + "languages": [], + "name": "KBase UI Plugin: Ontology", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/kbase-ui-plugin-ontology", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KBase_UI_Plugin:_Organizations.json b/agency-indexes/DoE/KBase_UI_Plugin:_Organizations.json new file mode 100644 index 00000000..733035e5 --- /dev/null +++ b/agency-indexes/DoE/KBase_UI_Plugin:_Organizations.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is a plugin for kbase-ui, which allows a KBase user to browse, view, and manage Organizations.", + "laborHours": 27785.6, + "languages": [], + "name": "KBase UI Plugin: Organizations", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-organizations", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KBase_UI_Plugin:_Relation_Engine_Landing_Pages.json b/agency-indexes/DoE/KBase_UI_Plugin:_Relation_Engine_Landing_Pages.json new file mode 100644 index 00000000..dbff9812 --- /dev/null +++ b/agency-indexes/DoE/KBase_UI_Plugin:_Relation_Engine_Landing_Pages.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-02", + "metadataLastUpdated": "2020-09-02" + }, + "description": "A kbase-ui plugin to provide Relation Engine landing pages.", + "laborHours": 5183.2, + "languages": [], + "name": "KBase UI Plugin: Relation Engine Landing Pages", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/kbase-ui-plugin-re-landing-pages", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KBase_UI_Plugin:_Taxonomy_Support.json b/agency-indexes/DoE/KBase_UI_Plugin:_Taxonomy_Support.json new file mode 100644 index 00000000..e805cfa6 --- /dev/null +++ b/agency-indexes/DoE/KBase_UI_Plugin:_Taxonomy_Support.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-02", + "metadataLastUpdated": "2020-09-02" + }, + "description": "This is a plugin for kbase-ui, which allows a KBase user to view individual taxons, and navigate within the taxonomy to which that taxon belongs.", + "laborHours": 3024.8, + "languages": [], + "name": "KBase UI Plugin: Taxonomy Support", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/kbase-ui-plugin-taxonomy", + "status": 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It uses a left looking LU factorization method.", + "laborHours": 8344830.4, + "languages": [], + "name": "KLU2 Direct Linear Solver Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KO_by_taxa_v1.json b/agency-indexes/DoE/KO_by_taxa_v1.json new file mode 100644 index 00000000..14e2bfe2 --- /dev/null +++ b/agency-indexes/DoE/KO_by_taxa_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-25", + "metadataLastUpdated": "2024-07-03" + }, + "description": "This program is used to subset metagenomic functional profiles to a list of desired taxa.", + "laborHours": 15.2, + "languages": [], + "name": "KO_by_taxa v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cliffbueno/KO_by_taxa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KSpaceNavigator__KSN_.json b/agency-indexes/DoE/KSpaceNavigator__KSN_.json new file mode 100644 index 00000000..a41169f7 --- /dev/null +++ b/agency-indexes/DoE/KSpaceNavigator__KSN_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-14", + "metadataLastUpdated": "2021-07-14" + }, + "description": "Intuitive GUI for manipulating microscope stages, allowing to align crystallographic data with stages, allowing to align crystallographic data with stage coordinates and microscope images. Simulates kinematic diffraction patterns and Kikuchi line patterns. Simulated patterns can be displayed as overlay to actually measured data, allowing manual fingerprinting and angular alignment. Crystallographic data is fed to the program in form of CIF (crystallographic information file) files, which are available from many databases and cover virtually all crystal structure ever reported in any journal. Actual goniometer scales can be linearized by lookup tables, program can be used with any microscope goniometer, double tilt and tilt-rotation type. Software requirements: Win32 platform (XP); Compiler/Version: Borland C++ Builder 5; Type of files: Executable modules; Hardware requirement: PC", + "laborHours": 0.0, + "languages": [], + "name": "KSpaceNavigator (KSN)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/kspacenavigator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/KT3D_GUI.json b/agency-indexes/DoE/KT3D_GUI.json new file mode 100644 index 00000000..12e029dd --- /dev/null +++ b/agency-indexes/DoE/KT3D_GUI.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The KT3D GUI provides a graphic user interface to a public domain FORTRAN code (kt3d) that was developed at Stanford University in 1998 (see Deutsch and Journel, 1998). The kt3d software contains the implementation of several kriging algorithms that complete spatial estimation onto a grid or a set of points from a set of available data and using a variogram model to describe the spatial variation of the data. The variogram model is calculated and modeled using the GAM/GAMV GUI software described separately. The KT3D GUI software allows the user to set various parameters for the FORTRAN code by using dialog boxes, it provides some error checking as these parameters are set and then allows the user to run the calculation by calling the executable compiled from the previously developed FORTRAN software. The resulting output of the kt3d code can be visualized in the KT3D GUI in several ways. If a gridded estimation problem is selected, color maps of the estimated values and the kriging variance are displayed in side by side images. If either jackknifing or cross-validation options are selected, then a series of user-defined X-Y plots can be created.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "KT3D GUI", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/GAM-GAMV-GUI-AND-K3TD?tab=readme-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/GAM-GAMV-GUI-AND-K3TD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KVTree.json b/agency-indexes/DoE/KVTree.json new file mode 100644 index 00000000..633b9cda --- /dev/null +++ b/agency-indexes/DoE/KVTree.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "KVTree is a hierarchical, tree-structured, key-value data structure library that can be used and re-used by other tools.", + "laborHours": 3131.2, + "languages": [ + "C" + ], + "name": "KVTree", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/KVTree", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KWAGE__FORMERLY_BIGSI++_.json b/agency-indexes/DoE/KWAGE__FORMERLY_BIGSI++_.json new file mode 100644 index 00000000..9d66bccb --- /dev/null +++ b/agency-indexes/DoE/KWAGE__FORMERLY_BIGSI++_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "The number of nucleic acid sequences in GenBank has been growing exponentially for almost 40 years. With the rapid adoption of high throughput, relatively inexpensive sequencing devices, the amount of available \u201craw\u201d, unassembled sequence in the Sequence Read Archive (SRA) is significantly greater than the traditional GenBank \u201ccomplete\u201d and \u201cWGS\u201d sequence categories combined. The SRA is an invaluable data trove that contains sequence reads that reflect the enormous diversity of modern genomic science from \u201cA\u201d (aardvark gut metagenome) to \u201cZ\u201d (zebra finch auditory lobule RNA-seq). \n\nHowever, as a result of the explosive growth of the SRA traditional methods for querying sequence databases (e.g. BLAST) can no longer keep up. Instead of finding the list of best matching database sequences for a given search query (usually accompanied by pairwise sequence alignments), new search algorithms have been developed to identify the \u201csamples\u201d (i.e. collections of short, sequenced reads from a single biological sample) that are most \u201csimilar\u201d to the query sequence. These search algorithms represent collections of sequences (both the query and the database entries) as mathematical sets of short, fixed-length sequences (\u201ck-mers\u201d) and then rank potential matches between the query set and each of the database sets using the fraction of k-mers that are shared between each pair of sets (e.g. the Jaccard distance).\n\nDue to the large amount of sequence data stored in the SRA, a na\u00efve, \u201cbrute-force\u201d approach that attempts to enumerate and store the k-mers associated with each biological sample in the SRA will quickly exhaust the available storage of most high-performance computing centers. Instead, the primary innovation of the new search algorithms is the application Bloom filters (and related computer science data structures) to the massive sequence search problem. A Bloom filter provides a pragmatic trade-off between \u201cset size\u201d and \u201cmatch certainty\u201d. By using one or more hash functions to map k-mers to a smaller set of numbers, the size of k-mers used to represent a collection of sequence reads can be dramatically reduced. This brings the added benefit that smaller set sizes can be computationally compared more quickly. However, there is no bioinformatic \u201cfree-lunch\u201d \u2013 the similarity between two Bloom filters now only approximates the similarity between the underlying k-mer sets. Thanks to the properties of the hash functions used to build the Bloom filters, the approximation is \u201cone-sided\u201d \u2013 the Bloom filter-based similarity can be greater, but never less, than the true k-mer set similarity. This leads to a non-zero probability of false discovery, where a predicted database match to a query sequence is not actually similar to the query. Thankfully, the probability of a false negative (i.e. failing to report a database match that is actually similar to the query) is zero. In addition, there is practical statistics-based guidance that enables implementing a Bloom filter with a known, user-specified false discovery rate.", + "laborHours": 0.0, + "languages": [], + "name": "KWAGE (FORMERLY BIGSI++)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Bioinformatics/KWAGE", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/K_Road__KRoad_.json b/agency-indexes/DoE/K_Road__KRoad_.json new file mode 100644 index 00000000..0f76deee --- /dev/null +++ b/agency-indexes/DoE/K_Road__KRoad_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "charles.tripp@nrel.gov" + }, + "date": { + "created": "2021-04-20", + "metadataLastUpdated": "2021-04-26" + }, + "description": "KRoad is a 2-dimensional, lightweight, vehicle driver simulator that uses 3-dimensional vehicle driving model considerations, i.e. state-of-the-art friction models, and enables the driver to make control decisions with less computation time and programmer effort required than is with full-fidelity 3d simulators. KRoad is fully compatible with OpenAI gym, and contains a factored gym framework for composing gyms from various components (process, reward function, observation function, termination conditions, etc.). KRoad is additionally compatible with the RLlib distributed reinforcement learning environment, running under the Ray distributed python framework.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "K_Road (KRoad)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/K_Road", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kbasecollaborations.github.io.json b/agency-indexes/DoE/Kbasecollaborations.github.io.json new file mode 100644 index 00000000..18751de7 --- /dev/null +++ b/agency-indexes/DoE/Kbasecollaborations.github.io.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"Kbasecollaborations.github.io\" developed by KBase. ", + "laborHours": 324261.6, + "languages": [], + "name": "Kbasecollaborations.github.io", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/Kbasecollaborations.github.io", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KeNary.json b/agency-indexes/DoE/KeNary.json new file mode 100644 index 00000000..ed59f97f --- /dev/null +++ b/agency-indexes/DoE/KeNary.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-04-18", + "metadataLastUpdated": "2025-04-18" + }, + "description": "A Probabilistic Kernel-Based n-ary Classification Method for Sets of Observations", + "laborHours": 334.4, + "languages": [], + "name": "KeNary", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/KeNary", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kelvin.json b/agency-indexes/DoE/Kelvin.json new file mode 100644 index 00000000..487eb247 --- /dev/null +++ b/agency-indexes/DoE/Kelvin.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Kelvin is a multiphysics sintering simulation software that uses the material point method to simulate the thermomechanical behavior of metal parts.", + "laborHours": 2264.8, + "languages": [ + "C++, gcc 8.x" + ], + "name": "Kelvin", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/kelvin/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/kelvin", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kepler.json b/agency-indexes/DoE/Kepler.json new file mode 100644 index 00000000..117c9b99 --- /dev/null +++ b/agency-indexes/DoE/Kepler.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "Kepler is a problem-solving environment for the analysis and modeling of scientific data. It simplifies the creation of executable models by using a visual representation of processes, or \u201cscientific workflows\u201d, which display the flow of data among discrete analysis and modeling components. ", + "laborHours": 8320267.2, + "languages": [], + "name": "Kepler", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.kepler-project.org/code/kepler/trunk/licenses.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.kepler-project.org/code/kepler", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Keras_CT_Segmentation_v.1.json b/agency-indexes/DoE/Keras_CT_Segmentation_v.1.json new file mode 100644 index 00000000..0331dbbd --- /dev/null +++ b/agency-indexes/DoE/Keras_CT_Segmentation_v.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2022-08-02" + }, + "description": "SAND2020-14119 O A Tensorflow and Keras-backed framework for learned segmentation methods of 3D CT scan volumes. Supported functionality includes training models, running inference and quantifying uncertainty. The main underlying model architecture is V-Net. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Keras CT Segmentation v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mcdn-3d-seg", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": ".1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KernelMatrices.jl.json b/agency-indexes/DoE/KernelMatrices.jl.json new file mode 100644 index 00000000..a618e2db --- /dev/null +++ b/agency-indexes/DoE/KernelMatrices.jl.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2018-08-27", + "metadataLastUpdated": "2018-08-27" + }, + "description": "A software suite for applying hierarchical matrices, specifically the \"hierarchically off-diagonal low rank\" (HODLR) format, to Gaussian process computing", + "laborHours": 1717.6, + "languages": [], + "name": "KernelMatrices.jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/cgeoga/kernelmatrices.jl", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/KinBot.json b/agency-indexes/DoE/KinBot.json new file mode 100644 index 00000000..a6a6c3ab --- /dev/null +++ b/agency-indexes/DoE/KinBot.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2018-09-06" + }, + "description": "KinBot 2.0 searches for chemical reaction pathways for gas-phase systems containing C, H, and O atoms. It determines the structure of key intermediates and products, characterizes their molecular structure and related properties, and creates an output that can be conveniently used to calculate rate coefficients by other codes.", + "laborHours": 6961.6, + "languages": [ + "Python" + ], + "name": "KinBot", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zadorlab/KinBot", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KinCat_v.1.0.json b/agency-indexes/DoE/KinCat_v.1.0.json new file mode 100644 index 00000000..71a5346b --- /dev/null +++ b/agency-indexes/DoE/KinCat_v.1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-15" + }, + "description": "SAND2024-02099O\nThe software is designed to allow researchers to perform kinetic Monte Carlo (KMC) simulations of catalytic reactions on a 2D lattice. The code is written efficiently to run on a variety of shared memory computing architectures (e.g. GPU, multi-core) and to natively express the full complexity of lateral interactions on reaction rates. The software allows researchers to perform KMC simulations of catalytic reactions on a 2D lattice. It uses parallel shared-memory computing architectures to reduce run-times and allows for simultaneous simulation of multiple independent runs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python", + "C++" + ], + "name": "KinCat v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/KinCat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kinetic_Learning_vo.1.json b/agency-indexes/DoE/Kinetic_Learning_vo.1.json new file mode 100644 index 00000000..f5540b50 --- /dev/null +++ b/agency-indexes/DoE/Kinetic_Learning_vo.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2021-07-06" + }, + "description": "New synthetic biology capabilities hold the promise of dramatically improving our ability to engineer biological systems. However, a fundamental hurdle in realizing this potential is our inability to accurately predict biological behavior after modifying the corresponding genotype. Kinetic models have traditionally been used to predict pathway dynamics in bioengineered systems, but they take significant time to develop, and rely heavily on domain expertise. This software implements a method to effectively predict pathway dynamics in an automated fashion using a combination of machine learning and abundant multiomics data (proteomics and metabolomics). The new method outperforms a classical kinetic model, and produces qualitative and quantitative predictions that can be used to productively guide bioengineering efforts. This method systematically leverages arbitrary amounts of new data to improve predictions, and does not assume any particular interactions, but rather implicitly chooses the most predictive ones.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Kinetic Learning vo.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kinetic_Monte_Carlo_for_semiconductor_surface_science_v.1.json b/agency-indexes/DoE/Kinetic_Monte_Carlo_for_semiconductor_surface_science_v.1.json new file mode 100644 index 00000000..def82f45 --- /dev/null +++ b/agency-indexes/DoE/Kinetic_Monte_Carlo_for_semiconductor_surface_science_v.1.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SAND2020-14229 O This software builds on an open source Kinetic Monte Carlo library to evaluate the incorporation rate of semiconductor dopant atoms in an Atomic Precision Advanced Manufacturing (APAM) process. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525", + "laborHours": 6779.2, + "languages": [ + "Python" + ], + "name": "Kinetic Monte Carlo for semiconductor surface science v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/apam-kmc", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kinetic_Simulations_of_Microstructural_Evolution__KSOME_.json b/agency-indexes/DoE/Kinetic_Simulations_of_Microstructural_Evolution__KSOME_.json new file mode 100644 index 00000000..84ad5f57 --- /dev/null +++ b/agency-indexes/DoE/Kinetic_Simulations_of_Microstructural_Evolution__KSOME_.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "giridhar.nandipati@pnnl.gov" + }, + "date": { + "created": "2020-08-25", + "metadataLastUpdated": "2020-08-26" + }, + "description": "\"Kinetic simulations of microstructural evolution\" (KSOME) is an object Kinetic Monte Carlo (OMKC) simulation code. It is developed to simulate microstructural evolution in materials during irradiation. KSOME is developed from ground up with priority given to the flexibility, ease of upgradability, and computation efficiency, in that order. With previously developed simulation codes, various processes (more precisely, the diffusion-reaction processes) that can occur in a system were hardwired into the code. Hence, to perform higher fidelity simulations, a significant coding effort was required every time to incorporate either a more accurate description of existing processes or new processes. With KSOME, the necessity for frequent code upgrades whenever there is a need to perform higher fidelity simulations is either eliminated or reduced significantly. In KSOME, the categories of various diffusion-reaction processes and the data-management system are hardwired, while the execution of the diffusion-reaction processes specific to a system is specified via input files. In the present version of KSOME, the analytical expression required to calculate defect interaction radii are inputted via a text file. However, the ability to parse mathematical expressions from a text file can be extended to input the analytical expression to calculate other defect properties; including the expressions to calculate the change in the migration barriers of mobile defects due to long-range interaction with extended defects ", + "laborHours": 8968.0, + "languages": [ + "C++" + ], + "name": "Kinetic Simulations of Microstructural Evolution (KSOME)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/giridharnandipati/ksome", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kinetics05_OSS.json b/agency-indexes/DoE/Kinetics05_OSS.json new file mode 100644 index 00000000..c0dd85d8 --- /dev/null +++ b/agency-indexes/DoE/Kinetics05_OSS.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "Kinetics05 uses a variety of linear and nonlinear regression methods, depending on the model to be fitted.\nIsoconversional methods use linear regression, supplemented by empirical correlations between model\nparameters and reaction profile characteristics. Distributed activation energy and nucleation-growth\nmodels use nonlinear regression, with the exception of the discrete distribution model, which uses a\nnested constrained linear-nonlinear regression method.", + "homepageURL": "https://softwarelicensing.llnl.gov/product/kinetics05oss", + "laborHours": 6688.0, + "languages": [], + "name": "Kinetics05_OSS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://softwarelicensing.llnl.gov/product/kinetics05oss", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kip,_Version_1.0.json b/agency-indexes/DoE/Kip,_Version_1.0.json new file mode 100644 index 00000000..63c570eb --- /dev/null +++ b/agency-indexes/DoE/Kip,_Version_1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-04" + }, + "description": "This high-performance ray tracing library provides very fast rendering, compact code, type flexibility via C++ 'generic programming' techniques, and ease of use through an application programming interface (API) that functions independently of any GUI, on-screen display, or other enclosing application. Kip supports constructive solid geometry models based on any of several built-in shapes and operators and allows for new, user-defined shapes and operators. Additional features include basic texturing, input/output of models using a simple human-readable file format with full error checking and detailed diagnostics, and support for shared data parallelism. Kip is written in pure, ANSI Standard C++, is entirely platform independent, and is very easy to use, as it requires no build system, configuration or installation scripts, wizards, special preprocessing, makefiles, or external libraries.", + "laborHours": 10001.6, + "languages": [], + "name": "Kip, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/staleyLANL/kip", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KiteFAST.json b/agency-indexes/DoE/KiteFAST.json new file mode 100644 index 00000000..837ef441 --- /dev/null +++ b/agency-indexes/DoE/KiteFAST.json @@ -0,0 +1,40 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-06-07", + "metadataLastUpdated": "2022-09-13" + }, + "description": "KiteFAST is a simulator for airborne wind energy systems based on NREL's OpenFAST whole turbine simulator. KiteFAST is a multi-physics engineering tool for modeling the coupled aero-servo-elastic dynamics of airborne wind energy systems i.e. a wind-energy kite. The engineering model is like NREL's OpenFAST tool for land-based or offshore horizontal-axis wind turbines atop towers, in that KiteFAST models the important physical phenomena and system couplings, including the wind/aerodynamic excitation and full-system dynamics response (fuselage, wings, tail, stabilizers, pylons, nacelles, rotors, tether, ground station, control surfaces, and controller) under both normal (for fatigue) and extreme (for ultimate) loading conditions. The configuration of the wind-energy kite is assumed to have one fuselage; two wings (starboard, port) attached to the fuselage; one vertical stabilizer attached the fuselage; two horizontal stabilizers (starboard, port) attached to the vertical stabilizer; one or more pylons per wing, each with two rotors (top, bottom); one ground-station-fixed tether with a bridal connection to the wings, and nominal circular motion of the energy kite in the port (left) direction. The general configuration of the control surfaces assumes one or more flaps per wing, two rudders on the vertical stabilizer, two elevators per horizontal stabilizer, and rotors with variable speed and rotor-collective blade pitch. KiteFAST was developed from (1) the existing MBDyn open-source multi-body dynamics code; (2) the existing/modified OpenFAST modules NWTC Subroutine Library, AirfoilInfo, InflowWind, MoorDyn, and TurbSim; and (3) new source code for a) generating MBDyn models of the energy kite (KiteMBDyn Preprocessor), b) computing quasi-steady energy-kite aerodynamics (KiteAeroDyn, KiteAeroDyn Driver, KiteVSM, ActuatorDisk), c) interfacing an energy-kite controller, and d) coupling the various KiteFAST modules together (KiteFASTMBD).", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Fortran", + "Python", + "Jupyter Notebook", + "Roff", + "C", + "C++" + ], + "name": "KiteFAST", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/OpenFAST/KiteFAST", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Klipper_Firmware_Tools.json b/agency-indexes/DoE/Klipper_Firmware_Tools.json new file mode 100644 index 00000000..3e8c0aa2 --- /dev/null +++ b/agency-indexes/DoE/Klipper_Firmware_Tools.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "haunab@ornl.gov" + }, + "date": { + "created": "2023-07-25", + "metadataLastUpdated": "2023-08-02" + }, + "description": "Tools for building containers to ease building Klipper and CanBoot for multiple targets.\n\nNote: This is being submitted to DOECODE as per instructions received after providing notification of creation of IP outside of work as part of a site-specific IP assignment agreement. This work was not funded by, nor was any work performed under any DOE contract.", + "laborHours": 0.0, + "languages": [ + "Bash", + "C", + "Z shell" + ], + "name": "Klipper Firmware Tools", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laikulo/Klipper-firmware.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Klipper_Quick_Flash.json b/agency-indexes/DoE/Klipper_Quick_Flash.json new file mode 100644 index 00000000..0689d12b --- /dev/null +++ b/agency-indexes/DoE/Klipper_Quick_Flash.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "haunab@ornl.gov" + }, + "date": { + "created": "2024-03-18", + "metadataLastUpdated": "2024-03-18" + }, + "description": "A tool to compile firmware and flash same to Klipper MCUs\n\nNote: This is a personal project being submitted to DOE CODE as per instruction from ORNL's TTS office.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Klipper Quick Flash", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laikulo/klipper-quickflash.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Klippy.json b/agency-indexes/DoE/Klippy.json new file mode 100644 index 00000000..35a3b0c6 --- /dev/null +++ b/agency-indexes/DoE/Klippy.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "haunab@ornl.gov" + }, + "date": { + "created": "2023-03-06", + "metadataLastUpdated": "2023-10-27" + }, + "description": "Tools and scripts created to ease the packaging of Klippy (A component of Klipper, a GPL3 licensed project). // Note: This project interacts with/is based on Klipper; Klipper contributors are listed here: https://github.com/Klipper3d/klipper/graphs/contributors. // Note: This is being submitted to DOECODE as per instructions received after providing notification of creation of IP outside of work as part of a site-specific IP assignment agreement. This work was not funded by, nor was any work performed under any DOE contract.", + "laborHours": 0.0, + "languages": [ + "Bash", + "C", + "Python" + ], + "name": "Klippy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Laikulo/klippy-tooling", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.11.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Knife-ovirt.json b/agency-indexes/DoE/Knife-ovirt.json new file mode 100644 index 00000000..13b8c737 --- /dev/null +++ b/agency-indexes/DoE/Knife-ovirt.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Knife-ovirt is code building on the chef, knife-cloud, fog, rbovirt projects that allows deployment of virtual machines on an ovirt cluster, and immediately bootstrap them into a chef managed infrastructure. (similar to knife-openstack project).", + "laborHours": 258.4, + "name": "Knife-ovirt", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/knife-ovirt", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Know_Your_Space:_Inlier_and_Outlier_Construction_for_Calibrating_Medical_OOD_Detectors.json b/agency-indexes/DoE/Know_Your_Space:_Inlier_and_Outlier_Construction_for_Calibrating_Medical_OOD_Detectors.json new file mode 100644 index 00000000..41999bf7 --- /dev/null +++ b/agency-indexes/DoE/Know_Your_Space:_Inlier_and_Outlier_Construction_for_Calibrating_Medical_OOD_Detectors.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-27", + "metadataLastUpdated": "2023-06-27" + }, + "description": "This software offers methods and functions for training calibrated out-of-distribution detectors for medical\nimage classification tasks. It includes functionalities for training, synthesizing data augmentations,\ncalibration, and out-of-distribution detection. Developed using PyTorch, this software is compatible with\nstandard neural network architectures used for imaging data. Additionally, it provides capabilities to compute evaluation metrics for assessing the performance and quality of the detectors.", + "laborHours": 0.0, + "languages": [], + "name": "Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/OODmedic", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/KnowledgeEnginePrototype.json b/agency-indexes/DoE/KnowledgeEnginePrototype.json new file mode 100644 index 00000000..585545c3 --- /dev/null +++ b/agency-indexes/DoE/KnowledgeEnginePrototype.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This is the repository for \"KnowledgeEnginePrototype\" developed by KBase. A KBase module generated by the KBase SDK.", + "laborHours": 77626.4, + "languages": [], + "name": "KnowledgeEnginePrototype", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/KnowledgeEnginePrototype", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kohn-Sham_Solver__KSSOLV__v2.0.json b/agency-indexes/DoE/Kohn-Sham_Solver__KSSOLV__v2.0.json new file mode 100644 index 00000000..32b01c00 --- /dev/null +++ b/agency-indexes/DoE/Kohn-Sham_Solver__KSSOLV__v2.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2021-06-24" + }, + "description": "KSSOLV is a MATLAB toolbox for solving Kohn-Sham density functional theory based electronic structure eigenvalue problems. It uses an object oriented features of MATLAB to represent atom, molecules, wavefunctions and Hamiltonians and their operations. It is designed to make it easier for users to prototype and test new algorithms for solving the Kohn-Sham problem. KSSOLV2.0 contains significant improvement over the original KSSOLV described in a paper published in ACM Transaction on Mathematical Software (attached). In addition to performing ground state calculation for small molecules, it can also perform geometry optimization for both molecules and solids. It uses standard pseudopotentials and implements local density approximation, generalized gradient approximation and hybrid functionals. Future releases will also include time-dependent DFT and post DFT calculations such as the GW quasi-particle energy calculation and Bethe-Salpeter equation solver for optical absorption.", + "laborHours": 0.0, + "languages": [], + "name": "Kohn-Sham Solver (KSSOLV) v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/kssolv2.0/src/release", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/KokkosP_Profiling_Tools.json b/agency-indexes/DoE/KokkosP_Profiling_Tools.json new file mode 100644 index 00000000..8060a4a3 --- /dev/null +++ b/agency-indexes/DoE/KokkosP_Profiling_Tools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "Kokkos C++ Performance Portability Programming EcoSystem: Profiling and Debugging Tools. Performance profiling tools that can be optionally integrated into Kokkos-based applications and libraries.\n", + "laborHours": 115292.0, + "languages": [], + "name": "KokkosP Profiling Tools", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/kokkos/kokkos-tools/blob/master/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/kokkos-tools", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kokkos_Array.json b/agency-indexes/DoE/Kokkos_Array.json new file mode 100644 index 00000000..b4f60e1e --- /dev/null +++ b/agency-indexes/DoE/Kokkos_Array.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Kokkos Array library implements shared-memory array data structures and parallel task dispatch interfaces for data-parallel computational kernels that are performance-portable to multicore-CPU and manycore-accelerator (e.g., GPGPU) devices.", + "laborHours": 8344830.4, + "name": "Kokkos Array", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kokkos_Clang.json b/agency-indexes/DoE/Kokkos_Clang.json new file mode 100644 index 00000000..7bd31996 --- /dev/null +++ b/agency-indexes/DoE/Kokkos_Clang.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-09" + }, + "description": "This will be a fork of the LLVM project which will contain enhancements to help Kokkos users. It will also wrap in contributions from LANL and Argonne, that we might also give our users access to that work. We will eventually try to upstream (give back to LLVM) any changes we make, if possible. SAND2020-12447 O\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 12563271.2, + "languages": [ + "C++" + ], + "name": "Kokkos Clang", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/llvm-project", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "9.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kokkos_GPU_Compiler.json b/agency-indexes/DoE/Kokkos_GPU_Compiler.json new file mode 100644 index 00000000..951474bf --- /dev/null +++ b/agency-indexes/DoE/Kokkos_GPU_Compiler.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Kokkos Clang compiler is a version of the Clang C++ compiler that has been modified to perform targeted code generation for Kokkos constructs in the goal of generating highly optimized code and to provide semantic (domain) awareness throughout the compilation toolchain of these constructs such as parallel for and parallel reduce. This approach is taken to explore the possibilities of exposing the developer\u2019s intentions to the underlying compiler infrastructure (e.g. optimization and analysis passes within the middle stages of the compiler) instead of relying solely on the restricted capabilities of C++ template metaprogramming. To date our current activities have focused on correct GPU code generation and thus we have not yet focused on improving overall performance. The compiler is implemented by recognizing specific (syntactic) Kokkos constructs in order to bypass normal template expansion mechanisms and instead use the semantic knowledge of Kokkos to directly generate code in the compiler\u2019s intermediate representation (IR); which is then translated into an NVIDIA-centric GPU program and supporting runtime calls. In addition, by capturing and maintaining the higher-level semantics of Kokkos directly within the lower levels of the compiler has the potential for significantly improving the ability of the compiler to communicate with the developer in the terms of their original programming model/semantics.", + "laborHours": 2076198.4, + "name": "Kokkos GPU Compiler", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/kokkos-clang/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/kokkos-clang", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kokkos_Kernels_v._0.9.json b/agency-indexes/DoE/Kokkos_Kernels_v._0.9.json new file mode 100644 index 00000000..4df66b53 --- /dev/null +++ b/agency-indexes/DoE/Kokkos_Kernels_v._0.9.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-09-01" + }, + "description": "Linear Algebra Kernels and Graph Kernels are foundational technologies for scientific simulations. These foundational kernels need to run on several computer platforms that are popular for scientific simulations. KokkosKernels provides an implementation of different kernels that is portable to different architectures.", + "laborHours": 187370.4, + "languages": [], + "name": "Kokkos Kernels v. 0.9", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/kokkos-kernels", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kokkos_Spack.json b/agency-indexes/DoE/Kokkos_Spack.json new file mode 100644 index 00000000..ab5640f8 --- /dev/null +++ b/agency-indexes/DoE/Kokkos_Spack.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "A flexible package manager that supports multiple versions, configurations, platforms, and compilers.", + "laborHours": 133364.8, + "languages": [], + "name": "kokkos/spack", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/kokkos/spack/blob/develop/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/spack", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kokkos_Version_2.0.json b/agency-indexes/DoE/Kokkos_Version_2.0.json new file mode 100644 index 00000000..b19896e9 --- /dev/null +++ b/agency-indexes/DoE/Kokkos_Version_2.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-01" + }, + "description": "The Kokkos library implements thread-parallel execution policies and shared-memory multidimensional array data structures that enable applications and domain libraries to develop computational kernels that are performance portable across multicore-CPU and manycore-accelerator (e.g. GPU) computing architectures.", + "laborHours": 119700.0, + "languages": [], + "name": "Kokkos Version 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/kokkos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kokkos_v.4.0.json b/agency-indexes/DoE/Kokkos_v.4.0.json new file mode 100644 index 00000000..cc43b3b8 --- /dev/null +++ b/agency-indexes/DoE/Kokkos_v.4.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-07", + "metadataLastUpdated": "2024-06-13" + }, + "description": "SAND2023-07883O\nKokkos software implements C++ performance portability programming models, tools and math libraries, which enables science and engineering software developers to use single-source codes for a wide range of computer architectures. Kokkos also provides implementations of existing and proposed C++ standard features that support programming model and math libraries that are used for implementing performance-portable scientific and engineering applications. The Kokkos libraries provide algorithms, data structures, and tools to enable high-performance computing developers to write performance-portable code. Capabilities fall into three broad categories: Kokkos Core, Kokkos Kernels, and Kokkos Tools.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 119700.0, + "languages": [ + "C++" + ], + "name": "Kokkos v.4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/kokkos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "4.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kona.json b/agency-indexes/DoE/Kona.json new file mode 100644 index 00000000..53a246ee --- /dev/null +++ b/agency-indexes/DoE/Kona.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Script to create operating system images in a directory from RPMs using the commands rpm or YUM.", + "laborHours": 136.8, + "name": "Kona", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trentdhooge/kona.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kosh.json b/agency-indexes/DoE/Kosh.json new file mode 100644 index 00000000..77004d40 --- /dev/null +++ b/agency-indexes/DoE/Kosh.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-10-25", + "metadataLastUpdated": "2021-10-25" + }, + "description": "Kosh allows codes to store, query, share data via an easy-to-use Python API. Kosh lies on top of Sina and as a result can use any database backend supported by Sina. In adition Kosh aims to make data access and sharing as simple as possible. Via \"loaders\" kosh can open files associated with datasets in a seemless fashion independently of the actual file format. Kosh's loader can also load data in different format, although numpy is the most usual output type. Once loaded data from sources, data can be further processed via \"transformers\"", + "laborHours": 0.0, + "languages": [], + "name": "Kosh", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/kosh", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Kubernetes_Bindings_for_the_Flux_Workload_Manager.json b/agency-indexes/DoE/Kubernetes_Bindings_for_the_Flux_Workload_Manager.json new file mode 100644 index 00000000..8a1a090f --- /dev/null +++ b/agency-indexes/DoE/Kubernetes_Bindings_for_the_Flux_Workload_Manager.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-09-30", + "metadataLastUpdated": "2022-09-30" + }, + "description": "Flux is a framework for writing resource managers as well as a resource manager for HPC systems. It allows for hierarchical nesting and providing a portable interface for job scheduling across systems. The flux-k8s software provides an interface between Flux and Kubernetes so the two frameworks can use each other's functionality. The code is currently licensed under the LGPL-3.0 License, but we request to re-license the code to promote outside collaboration and community adoption.", + "laborHours": 0.0, + "languages": [], + "name": "Kubernetes Bindings for the Flux Workload Manager", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/flux-framework/flux-k8s", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/L-TERRA.json b/agency-indexes/DoE/L-TERRA.json new file mode 100644 index 00000000..ec54435a --- /dev/null +++ b/agency-indexes/DoE/L-TERRA.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-04", + "metadataLastUpdated": "2022-02-16" + }, + "description": "Lidar (light detection and ranging) instruments are often used in wind energy studies in place of meteorological towers, as they can collect measurements at higher heights than met towers and are more easily moved to different parts of a site. While lidars can accurately measure mean wind speeds, they frequently measure different values of turbulence intensity (TI) than would be measured by a cup anemometer on a tower. Discrepancies in TI values are caused by several factors, including instrument noise and volume averaging. The inability of lidars to accurately measure turbulence is a significant barrier to replacing met towers with lidars in the future. There is currently no accepted standard process for quantifying and removing these errors in lidar TI measurements. The Software is an error reduction algorithm for lidar-measured turbulence. The algorithm is trained using co-located lidar and meteorological tower data. Lidar-measured parameters, such as wind speed, shear, and TI, will be used to predict the difference between the lidar- and tower-measured TI. The algorithm will be disseminated as a set of computer code that can be used by lidar users and manufacturers to correct lidar TI data in real time or in post-processing.", + "laborHours": 684.0, + "languages": [ + "Python" + ], + "name": "L-TERRA", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/L-TERRA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/L3_Interactive_Data_Language.json b/agency-indexes/DoE/L3_Interactive_Data_Language.json new file mode 100644 index 00000000..d0126300 --- /dev/null +++ b/agency-indexes/DoE/L3_Interactive_Data_Language.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "The L3 system is a computational steering environment for image processing and scientific computing. It consists of an interactive graphical language and interface. Its purpose is to help advanced users in controlling their computational software and assist in the management of data accumulated during numerical experiments. L3 provides a combination of features not found in other environments; these are: - textual and graphical construction of programs - persistence of programs and associated data - direct mapping between the scripts, the parameters, and the produced data - implicit hierarchial data organization - full programmability, including conditionals and functions - incremental execution of programs The software includes the l3 language and the graphical environment. The language is a single-assignment functional language; the implementation consists of lexer, parser, interpreter, storage handler, and editing support, The graphical environment is an event-driven nested list viewer/editor providing graphical elements corresponding to the language. These elements are both the representation of a users program and active interfaces to the values computed by that program.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "L3 Interactive Data Language", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/LANL-contributed_enhancements_to_BatSim_toolstack,_including_VizUtil,_derivative_of_and_enhancement_of_Evalys.json b/agency-indexes/DoE/LANL-contributed_enhancements_to_BatSim_toolstack,_including_VizUtil,_derivative_of_and_enhancement_of_Evalys.json new file mode 100644 index 00000000..77ef8471 --- /dev/null +++ b/agency-indexes/DoE/LANL-contributed_enhancements_to_BatSim_toolstack,_including_VizUtil,_derivative_of_and_enhancement_of_Evalys.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "The tools used are the modified, enhanced and extended versions of the open source BatSim and BatSched suite, including visualization tools (Evalys) derived from those toolstacks.", + "laborHours": 562.4, + "languages": [], + "name": "LANL-contributed enhancements to BatSim toolstack, including VizUtil, derivative of and enhancement of Evalys", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/BatsimGantt-LANL", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LANL_Contribution_to_NRAP-Open-IAM.json b/agency-indexes/DoE/LANL_Contribution_to_NRAP-Open-IAM.json new file mode 100644 index 00000000..f123c025 --- /dev/null +++ b/agency-indexes/DoE/LANL_Contribution_to_NRAP-Open-IAM.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "NRAP-Open-IAM is an open-source software product that enables quantification of containment effectiveness and leakage risk at storage sites in the context of system uncertainties and variability.", + "laborHours": 114197.6, + "languages": [], + "name": "LANL Contribution to NRAP-Open-IAM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NRAP/OpenIAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/LANL_Contributions_to_Parallelized_large-Eddy_Simulation_Model_Formerly_PALM-LANL.json b/agency-indexes/DoE/LANL_Contributions_to_Parallelized_large-Eddy_Simulation_Model_Formerly_PALM-LANL.json new file mode 100644 index 00000000..1df328f5 --- /dev/null +++ b/agency-indexes/DoE/LANL_Contributions_to_Parallelized_large-Eddy_Simulation_Model_Formerly_PALM-LANL.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "PALM-LANL is a model system for conducting large-eddy simulations, that is, simulations of turbulence that only resolve the largest turbulent eddies and rely on a turbulence closure scheme to represent the smallest turbulent eddies. PALM-LANL is based on PALM version 5.0 but it contains numerous modifications by LANL authors to add research capabilities. PALM is written for atmosphere and ocean turbulence; PALM-LANL includes modifications and additions to the ocean turbulence components, analysis, and data output capabilities. ", + "laborHours": 0.0, + "languages": [], + "name": "LANL Contributions to Parallelized large-Eddy Simulation Model Formerly PALM-LANL", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/palm_lanl", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LANL_Contributions_to_pyiron:_An_integrated_development_environment_for_computational_materials_science.json b/agency-indexes/DoE/LANL_Contributions_to_pyiron:_An_integrated_development_environment_for_computational_materials_science.json new file mode 100644 index 00000000..d4e15453 --- /dev/null +++ b/agency-indexes/DoE/LANL_Contributions_to_pyiron:_An_integrated_development_environment_for_computational_materials_science.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "To support and accelerate the development of simulation protocols in atomistic modelling, we introduce an integrated development environment (IDE) for computational materials science called pyiron (http://pyiron.org). The pyiron IDE combines a web based source code editor, a job management system for build automation, and a hierarchical data management solution. The core components of the pyiron IDE are pyiron objects based on an abstract class, which links application structures such as atomistic structures, projects, jobs, simulation protocols and computing resources with persistent storage and an interactive user environment. The simulation protocols within the pyiron IDE are constructed using the Python programming language. To highlight key concepts of this tool as well as to demonstrate its ability to simplify the implementation and testing of simulation protocols we discuss two applications. In these examples we show how pyiron supports the whole life cycle of a typical simulation, seamlessly combines ab initio with empirical potential calculations, and how complex feedback loops can be implemented. While originally developed with focus on ab initio thermodynamics simulations, the concepts and implementation of pyiron are general thus allowing to employ it for a wide range of simulation topics.", + "laborHours": 0.0, + "languages": [], + "name": "LANL Contributions to pyiron: An integrated development environment for computational materials science", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pyiron/pyiron_contrib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LANL_Crystal_Cut__LCC_.json b/agency-indexes/DoE/LANL_Crystal_Cut__LCC_.json new file mode 100644 index 00000000..6dd02d99 --- /dev/null +++ b/agency-indexes/DoE/LANL_Crystal_Cut__LCC_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "Computes the atomic positions in cleaved crystal lattices. The current version of the code allows to cleave the lattices with different planes that are readily available. The cleavages can be performed on any type of lattices. The code constructs a slab that can be used to study surface properties.", + "laborHours": 0.0, + "languages": [], + "name": "LANL Crystal Cut (LCC)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/LCC", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LANL_contribution_to_ryujin,_an_open_source_finite_element_solver.json b/agency-indexes/DoE/LANL_contribution_to_ryujin,_an_open_source_finite_element_solver.json new file mode 100644 index 00000000..2b69e639 --- /dev/null +++ b/agency-indexes/DoE/LANL_contribution_to_ryujin,_an_open_source_finite_element_solver.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-12-15", + "metadataLastUpdated": "2024-04-19" + }, + "description": "Ryujin (https://github.com/conservation-laws/ryujin) is a high-performance finite-element software for solving mathematical partial differential equations (PDEs) with dominant hyperbolic structures. The author of this request, Eric Tovar, is using Ryujin as a high-performance tool for his Mark Kac postdoctoral fellowship research at LANL. Eric would like to contribute openly to the ryujin software without changing its core functionality. This includes: (i) bug fixes; (ii) re-organization of code for performance and syntactic updates including documentation; (iii) implementation of new PDE numerical methods that align with the core solver; (iv) implementation of new initial state configurations for target applications.", + "laborHours": 0.0, + "languages": [], + "name": "LANL contribution to ryujin, an open source finite element solver", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EricTovar-LANL/ryujin-contribution.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LANL_contributions_to_PLEIADES.json b/agency-indexes/DoE/LANL_contributions_to_PLEIADES.json new file mode 100644 index 00000000..bb567171 --- /dev/null +++ b/agency-indexes/DoE/LANL_contributions_to_PLEIADES.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "PLEIADES: Python Libraries Extensions for Isotopic Analysis via Detailed Extraction of SAMMY. \n\nThis is a Python package that configures and executes the code SAMMY, which is an open sourced R-Matrix fitting code from ORNL. Additionally, PLEIADES includes python packages to analyze SAMMY results and process them into isotopic images.", + "laborHours": 1504.8, + "languages": [], + "name": "LANL contributions to PLEIADES", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PLEIADES", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LANL_contributions_to_Rayleigh.json b/agency-indexes/DoE/LANL_contributions_to_Rayleigh.json new file mode 100644 index 00000000..8014bf26 --- /dev/null +++ b/agency-indexes/DoE/LANL_contributions_to_Rayleigh.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Rayleigh is a 3-D convection code designed for the study of dynamo behavior in spherical geometry. It evolves the incompressible and anelastic MHD equations in spherical geometry using a pseudo-spectral approach.", + "laborHours": 34169.6, + "languages": [], + "name": "LANL contributions to Rayleigh", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/geodynamics/Rayleigh", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LANL_contributions_to_isoWater_R_package.json b/agency-indexes/DoE/LANL_contributions_to_isoWater_R_package.json new file mode 100644 index 00000000..35f75312 --- /dev/null +++ b/agency-indexes/DoE/LANL_contributions_to_isoWater_R_package.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-07" + }, + "description": "The ratio of heavy-to-light stable isotope abundance in water vapor is a tracer of atmospheric processes including evapotranspiration, condensation, mixing, and transport. Measurements of these isotope ratios at the surface, in the atmospheric column, or from satellites provide insights into atmospheric processes that cannot be gained from measurements of water vapor mixing ratios alone. A number of theoretical models for how water vapor isotope ratios should vary in response to atmospheric processes have been developed, and LANL contributions to the isoWater R package provides a simplified interface for calculating expected vapor isotope ratios based on these models and adding them to plots of water vapor isotope ratios.", + "laborHours": 0.0, + "languages": [], + "name": "LANL contributions to isoWater R package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/isoWater", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LATTE:_Los_Alamos_TravelTime_package_based_on_Eikonal_equation.json b/agency-indexes/DoE/LATTE:_Los_Alamos_TravelTime_package_based_on_Eikonal_equation.json new file mode 100644 index 00000000..12f65993 --- /dev/null +++ b/agency-indexes/DoE/LATTE:_Los_Alamos_TravelTime_package_based_on_Eikonal_equation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This Fortran code focuses on traveltime computation and tomography based on eikonal equation. Specifically, the package provides three major functionalities: (1) forward modeling of traveltime from single-point or ensemble source based on factorized eikonal equation, (2) adjoint-state first-arrival traveltime tomography based on picked first arrival traveltime using steepest descent, conjugate gradient, or limited-memory BFGS inversion scheme, and (3) adjoint-state joint transmission-reflection tomography based on picked first-arrival and reflection traveltimes. The package applies to forward modeling and tomography based on traveltime in 2D and 3D isotropic regular-grid models. We name this package LATTE \u2013 Los Alamos TravelTime package based on Eikonal equation. \n\n* The code is for accompanying a journal paper under preparation. The paper will be submitted via LA-UR separately later.", + "laborHours": 7949.6, + "languages": [], + "name": "LATTE: Los Alamos TravelTime package based on Eikonal equation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/latte_traveltime", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LAVA.json b/agency-indexes/DoE/LAVA.json new file mode 100644 index 00000000..1a20e776 --- /dev/null +++ b/agency-indexes/DoE/LAVA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-06-15", + "metadataLastUpdated": "2022-06-15" + }, + "description": "We introduce LAVA, a general-purpose python toolkit to provide user-friendly and high throughput calculations for material properties using both LAMMPS and VASP. It contains a set of classes as well as pre-processing and post-processing functions to prepare, execute and extract information from LAMMPS/VASP simulations. An overview of the program structure is provided. The current version contains modules to calculate elastic and mechanical properties such as lattice constant, cohesive energy, cold curve, elastic constants, bulk and shear modulus, volume conserving/non-conserving deformation path, vacancy/interstitial formation energy, surface energy, stacking fault energy, melting point, radial distribution function, and thermal expansion.", + "laborHours": 0.0, + "languages": [], + "name": "LAVA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/LAVA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LB-analysis-framework.json b/agency-indexes/DoE/LB-analysis-framework.json new file mode 100644 index 00000000..253a237c --- /dev/null +++ b/agency-indexes/DoE/LB-analysis-framework.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "Analysis framework for exploring, testing, and comparing load balancing strategies.", + "laborHours": 10229.6, + "languages": [], + "name": "LB-analysis-framework", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/DARMA-tasking/LB-analysis-framework/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DARMA-tasking/LB-analysis-framework", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LBC__Learning_Building_Control_.json b/agency-indexes/DoE/LBC__Learning_Building_Control_.json new file mode 100644 index 00000000..681f26ae --- /dev/null +++ b/agency-indexes/DoE/LBC__Learning_Building_Control_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-18" + }, + "description": "LBC encompasses the source code and data to reproduce and extend results for a manuscript that compares demand responsive control schemes for multi-zone buildings. It includes examples of model predictive control (MPC), value function approximation via CVXPYLAYERS, and differentiable predictive control (DPC). The goal of the study is to evaluate state-of-the-art controllers and establish the efficacy (if any) of learning-based approaches that leverage deep neural networks in one way or another.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter" + ], + "name": "LBC (Learning Building Control)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/learning-building-control", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LBNL-Load.json b/agency-indexes/DoE/LBNL-Load.json new file mode 100644 index 00000000..50cdad20 --- /dev/null +++ b/agency-indexes/DoE/LBNL-Load.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-22", + "metadataLastUpdated": "2021-04-22" + }, + "description": "This software package is a set of Python-based tools for forecasting future time series of electrical power demand for a granular set of customer types in California, based on historical data on individual customers' demand, combined with aggregate forecasts of demand growth.", + "homepageURL": "https://buildings.lbl.gov/download-phase-3-dr-potential-study", + "laborHours": 0.0, + "languages": [], + "name": "LBNL-Load", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://buildings.lbl.gov/download-phase-3-dr-potential-study", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/LBNL_BPM_Firmware__CAL-BPM__v1.0.json b/agency-indexes/DoE/LBNL_BPM_Firmware__CAL-BPM__v1.0.json new file mode 100644 index 00000000..485ade57 --- /dev/null +++ b/agency-indexes/DoE/LBNL_BPM_Firmware__CAL-BPM__v1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-06", + "metadataLastUpdated": "2021-10-06" + }, + "description": "CAL-BPM is the firmware code base of the Advanced Light Source (ALS) Beam Position Monitor (BPM) Field Programmable Gate Array (FPGA) based electronics.", + "homepageURL": "https://github.com/BerkeleyLab/CAL-BPM", + "laborHours": 0.0, + "languages": [], + "name": "LBNL BPM Firmware (CAL-BPM) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/BerkeleyLab/CAL-BPM/blob/main/LICENSE_firmware.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/CAL-BPM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LBNL_BPM_Firmware__CAL-BPM__v1.0:_software.json b/agency-indexes/DoE/LBNL_BPM_Firmware__CAL-BPM__v1.0:_software.json new file mode 100644 index 00000000..416ecdd3 --- /dev/null +++ b/agency-indexes/DoE/LBNL_BPM_Firmware__CAL-BPM__v1.0:_software.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-03", + "metadataLastUpdated": "2021-09-08" + }, + "description": "CAL-BPM is the firmware code base of the Advanced Light Source (ALS) Beam Position Monitor (BPM) Field Programmable Gate Array (FPGA) based electronics.", + "laborHours": 0.0, + "languages": [], + "name": "LBNL BPM Firmware (CAL-BPM) v1.0: software", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/CAL-BPM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LBNL_Cell_controller_v1.0.json b/agency-indexes/DoE/LBNL_Cell_controller_v1.0.json new file mode 100644 index 00000000..980f89ec --- /dev/null +++ b/agency-indexes/DoE/LBNL_Cell_controller_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-03", + "metadataLastUpdated": "2021-09-03" + }, + "description": "Firmware and software of LBNL's Cell controller logic. Cell logic forms a high-speed data distribution network of FPGAs, transmitting data in a ring topology. This logic is used at ALS for the distribution of BPM data as part of the fast orbit feedback system.", + "laborHours": 0.0, + "languages": [], + "name": "LBNL Cell controller v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/LBNL-Cell-controller", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LBNL_DDoS_Detection_on_Science_Networks_v0.1.json b/agency-indexes/DoE/LBNL_DDoS_Detection_on_Science_Networks_v0.1.json new file mode 100644 index 00000000..50325812 --- /dev/null +++ b/agency-indexes/DoE/LBNL_DDoS_Detection_on_Science_Networks_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-31" + }, + "description": "This software contains a set of analysis tools to identify certain types of DDoS attacks and disambiguate those attacks from large scientific data transfers over networks as well as ordinary Internet network traffic. It also contains a piece of \"driver\" code that allows individual scripts that detect certain types of attacks to selectively be run.", + "laborHours": 5274.4, + "languages": [], + "name": "LBNL DDoS Detection on Science Networks v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lbnl-cybersecurity/ddos-detection/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/ddos-detection", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LBNL_SecureMessaging.json b/agency-indexes/DoE/LBNL_SecureMessaging.json new file mode 100644 index 00000000..71a22511 --- /dev/null +++ b/agency-indexes/DoE/LBNL_SecureMessaging.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The LBNLSecureMessaging application enables collaboration among colocated or geograhically dispersed users by supporting secure synchronous and asynchronous communication. This application is the graphical user interface client that is meant to be used in conjunction with servers (LBNL's PCCEServer and a customized IRC server) to allow group and one-to-one conversations via text-based instant messaging. Conversations may be private (by invitation only) or public (open to any member of a collaboratory group_ and they may be permanent and on-going or temporary and ad hoc. Users may leave notes for other people who are online or offline. By providing presence and awareness information, collaborators can easily locate each other and rendezvous. Written in Java/Swing, this application is cross-platform. To gain access to functionality, users have to be registered with an authorization server (PCCEServer) that maintains an access control list. Thus a collaboration group is comprised of a set of PCCE-registered users. Registered users can log in via either X.509 certificate or a username and password combination. PKI and SSL are used to authenticate servers and clients and to encrypt messages sent over the network. The LBNLSecureMessaging application offers instant messaging capabilities in a secure environment that provides data integrity, privacy authorization, and authentication.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "LBNL SecureMessaging", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/LC-IM-TOF_Instrument_Control_&_Data_Visualization_Software.json b/agency-indexes/DoE/LC-IM-TOF_Instrument_Control_&_Data_Visualization_Software.json new file mode 100644 index 00000000..1d7a4d34 --- /dev/null +++ b/agency-indexes/DoE/LC-IM-TOF_Instrument_Control_&_Data_Visualization_Software.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Liquid Chromatography-Ion Mobility-time of Flight Instrument Control and Data Visualization software is designed to control instrument voltages for the Ion Mobility drift tube. It collects and stores information collected from the Agilent TOF instrument and analyses/displays the ion intensity information acquired. The software interface can be split into 3 categories -- Instrument Settings/Controls, Data Acquisition, and Viewer. The Instrument Settings/Controls prepares the instrument for Data Acquisition. The Viewer contains common objects that are used by Instrument Settings/Controls and Data Acquisition. Intensity information is collected in 1 nanosec bins and separated by TOF pulses called scans. A collection of scans are stored side by side making up an accumulation. In order for the computer to keep up with the stream of data, 30-50 accumulations are commonly summed into a single frame. A collection of frames makes up an experiment. The Viewer software then takes the experiment and presents the data in several possible ways, each frame can be viewed in TOF bins or m/z (mass to charge ratio). The experiment can be viewed frame by frame, merging several frames, or by viewing the peak chromatogram. The user can zoom into the data, export data, and/or animate frames. Additional features include calibration of the data and even post-processing multiplexed data.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C#, C++" + ], + "name": "LC-IM-TOF Instrument Control & Data Visualization Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/LC-IMS-MS_Feature_Finder.json b/agency-indexes/DoE/LC-IMS-MS_Feature_Finder.json new file mode 100644 index 00000000..37a9328b --- /dev/null +++ b/agency-indexes/DoE/LC-IMS-MS_Feature_Finder.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "LC-IMS-MS Feature Finder is a command line software application which searches for possible molecular ion signatures in multidimensional liquid chromatography, ion mobility spectrometry, and mass spectrometry data by clustering deisotoped peaks with similar monoisotopic mass values, charge states, elution times, and drift times. The software application includes an algorithm for detecting multiple conformations and co-eluting species in the ion mobility dimension. LC-IMS-MS Feature Finder is designed to create an output file with detected features that includes associated information about the detected features.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "LC-IMS-MS Feature Finder", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCA-PyTorch.json b/agency-indexes/DoE/LCA-PyTorch.json new file mode 100644 index 00000000..00c60037 --- /dev/null +++ b/agency-indexes/DoE/LCA-PyTorch.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "LCA-PyTorch is a code repository which contains PyTorch implementations of the Locally Competitive Algorithm (LCA), which is a biologically-plausible sparse coding model. LCA-PyTorch allows for the training, testing, and analysis of single layer LCA networks, multi-layer LCA networks, and hybrid LCA-based deep neural network models on a wide variety of applications and data types. LCA-PyTorch was developed in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning. LCA-PyTorch interfaces heavily with the open-source PyTorch Python package. ", + "laborHours": 0.0, + "languages": [], + "name": "LCA-PyTorch", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/lca-pytorch", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCA.json b/agency-indexes/DoE/LCA.json new file mode 100644 index 00000000..0390f143 --- /dev/null +++ b/agency-indexes/DoE/LCA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-03-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Locally Competitive Algorithm (LCA) is a dynamical sparse solver that uses only local computations, allowing for massively parallel implementations on compatible neuromorphic architectures such as Intel's Loihi research chip. In this invention, we show how unsupervised dictionary learning with spiking LCA can be implemented on GPUs and Intel's Loihi research chip.", + "laborHours": 0.0, + "languages": [], + "name": "LCA", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/LCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCIO.json b/agency-indexes/DoE/LCIO.json new file mode 100644 index 00000000..6132865b --- /dev/null +++ b/agency-indexes/DoE/LCIO.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "georgea@ornl.gov" + }, + "date": { + "created": "2023-08-29", + "metadataLastUpdated": "2023-08-30" + }, + "description": "Performance of file systems shift during their life cycles. Evaluating this performance change over time is not trivial. Complexity arises in the interplay between external (i.e. application I/O workloads) and internal (i.e. the filesystem state) factors. Many benchmarks can test how a filesystem performs at the current snapshot state, but to observe the change over time necessitates that the filesystem state mutate (age) between benchmark runs. For a large-scale HPC parallel filesystem, the sheer scale and amount of interacting components during I/O operations magnify these challenges. LCIO addresses the question - how will the filesystem perform at different stages of its life cycle? LCIO is a synthetic benchmark, which provides the file system aging process to increase the amount of information that existing benchmarks like IOR and MDTest yield, as well as provide additional points of data that will be useful to system architects and engineers.", + "laborHours": 0.0, + "languages": [ + "C", + "Python" + ], + "name": "LCIO", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/olcf/lcio/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/lcio", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCIO_Julia_Bindings.json b/agency-indexes/DoE/LCIO_Julia_Bindings.json new file mode 100644 index 00000000..5d9c6b13 --- /dev/null +++ b/agency-indexes/DoE/LCIO_Julia_Bindings.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software is the interface between LCIO (lcio.desy.de) and Julia (julialang.org), such that event records in the LCIO format can be analyzed with Julia and its libraries.", + "laborHours": 243.2, + "name": "LCIO Julia Bindings", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jstrube/LCIO.jl/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jstrube/LCIO.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCLS-II_MPS_Application_Node.json b/agency-indexes/DoE/LCLS-II_MPS_Application_Node.json new file mode 100644 index 00000000..e6191694 --- /dev/null +++ b/agency-indexes/DoE/LCLS-II_MPS_Application_Node.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-16", + "metadataLastUpdated": "2022-08-16" + }, + "description": "This is the LCLS-II MPS Application Node developed by SLAC National Accelerator Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "LCLS-II MPS Application Node", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/l2MpsAN/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/l2MpsAN", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCLS-II_MPS_Database.json b/agency-indexes/DoE/LCLS-II_MPS_Database.json new file mode 100644 index 00000000..5baec8ab --- /dev/null +++ b/agency-indexes/DoE/LCLS-II_MPS_Database.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "This package contains SQLAlchemy python classes that provide access to the MPS sqlite3 database.\n", + "laborHours": 6064.8, + "languages": [], + "name": "LCLS-II MPS Database", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/mps_database/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/mps_database", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCLS-II_MPS_Link_Node.json b/agency-indexes/DoE/LCLS-II_MPS_Link_Node.json new file mode 100644 index 00000000..082f981b --- /dev/null +++ b/agency-indexes/DoE/LCLS-II_MPS_Link_Node.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-11", + "metadataLastUpdated": "2022-07-11" + }, + "description": "LCLS-II MPS Link Node EPICS IOC developed by SLAC National Accelerator Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "LCLS-II MPS Link Node", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/l2MpsLN/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/l2MpsLN", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCLS-Live.json b/agency-indexes/DoE/LCLS-Live.json new file mode 100644 index 00000000..c773fea6 --- /dev/null +++ b/agency-indexes/DoE/LCLS-Live.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-11", + "metadataLastUpdated": "2022-07-11" + }, + "description": "The LCLS accelerator complex consists of multiple electron sources and multiple beam paths. Live models are computer simulation programs that continuously execute with inputs taken from the machine, and serve physics predictions of the beam behavior. LCLS-Live is a Python package with related tools and data to help in translating machine settings to simulation models.", + "laborHours": 0.0, + "languages": [], + "name": "LCLS-Live", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/lcls-live", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCLS2.json b/agency-indexes/DoE/LCLS2.json new file mode 100644 index 00000000..1372b1e5 --- /dev/null +++ b/agency-indexes/DoE/LCLS2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-06-14", + "metadataLastUpdated": "2022-06-14" + }, + "description": "This is the LCLS II development repository developed at SLAC National Accelerator Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "LCLS2", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slac-lcls/lcls2/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slac-lcls/lcls2", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCLS2_MPS_RTM_Tester.json b/agency-indexes/DoE/LCLS2_MPS_RTM_Tester.json new file mode 100644 index 00000000..45e90713 --- /dev/null +++ b/agency-indexes/DoE/LCLS2_MPS_RTM_Tester.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-10", + "metadataLastUpdated": "2022-08-10" + }, + "description": "This repository contains tools and applications for testing the RTM boards used by the LCLS2 MPS project.", + "laborHours": 0.0, + "languages": [], + "name": "LCLS2 MPS RTM Tester", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/lcls2-mps-rtm-tester/blob/main/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/lcls2-mps-rtm-tester", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCLS_Lightpath.json b/agency-indexes/DoE/LCLS_Lightpath.json new file mode 100644 index 00000000..92748a28 --- /dev/null +++ b/agency-indexes/DoE/LCLS_Lightpath.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2018-05-30" + }, + "description": "Python module for control of LCLS beamlines-By abstracting individual devices into larger collections of paths, operators can quickly guide beam to experimental end stations. Instead of dealing with the individual interfaces for each device, devices are summarized in states. This allows operators to quickly view and manipulate large sections of the beamline when the goal is to simply handle beam delivery.\n", + "laborHours": 1915.2, + "languages": [], + "name": "LCLS Lightpath", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pcdshub/lightpath/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/lightpath", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCLS_Orbit_Server.json b/agency-indexes/DoE/LCLS_Orbit_Server.json new file mode 100644 index 00000000..b14a1b7b --- /dev/null +++ b/agency-indexes/DoE/LCLS_Orbit_Server.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2022-08-02" + }, + "description": "This application monitors all LCLS BPMs, and emits a PV Access table of synchronized orbit data.", + "laborHours": 0.0, + "languages": [], + "name": "LCLS Orbit Server", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/orbit_server/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/orbit_server", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCMS-Spectator.json b/agency-indexes/DoE/LCMS-Spectator.json new file mode 100644 index 00000000..8fb2d5db --- /dev/null +++ b/agency-indexes/DoE/LCMS-Spectator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "LCMS raw data and MSGF+ results viewer. LcmsSpectator is a standalone Windows graphical user interface tool for viewing LC-MS data and identifications.", + "laborHours": 114304.0, + "languages": [], + "name": "LCMS-Spectator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/LCMS-Spectator/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LCMS-Spectator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCMSNet_v._3.0.json b/agency-indexes/DoE/LCMSNet_v._3.0.json new file mode 100644 index 00000000..3b10f99f --- /dev/null +++ b/agency-indexes/DoE/LCMSNet_v._3.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "LCMSnet communicates with, controls and orchestrates devices for high pressure liquid chromatography. In developing cutting edge chromatographic methods it was apparent that components from different manufacturers were required. Autosamplers, valves, and pumps all had to be controlled and configured to run unattended and in the highest throughput possible. The power of LCMSnet is the ability so build methods in a simple step by step fashion and then the software uses a scheduling algorithm to run the devices as efficiently as possible without crashing critical functions. This latest iteration of the software allows for modeling of the valves and incorporates logic that will report if a fluid path is undesirable. LCMSnet has reduced method development time from days to minutes and allows the ability to check configurations before any valves or pumps are connected.", + "laborHours": 70239.2, + "name": "LCMSNet v. 3.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/LCMSNet", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LCMSNet", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LCOC__Levelized_Cost_of_Light-Duty_EV_Charging_Calculator_.json b/agency-indexes/DoE/LCOC__Levelized_Cost_of_Light-Duty_EV_Charging_Calculator_.json new file mode 100644 index 00000000..19e86dd4 --- /dev/null +++ b/agency-indexes/DoE/LCOC__Levelized_Cost_of_Light-Duty_EV_Charging_Calculator_.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-02-22", + "metadataLastUpdated": "2022-02-22" + }, + "description": "This code was developed to calculate the levelized cost of light-duty electric vehicle (EV) charging (LCOC) for the paper \"Levelized Cost of Charging Electric Vehicles in the United States\" by Borlaug et al.(https://doi.org/10.1016/j.joule.2020.05.013). The calculation takes inputs from a variety of publicly available data sources (e.g., utility tariffs from the Utility Rate Database; EV charging station locations from the Alternative Fuels Data Center; energy price forecasts from the Energy Information Administration) and produces the current LCOC, considering when, where, and how light-duty EVs are recharged. In addition, the lifetime fuel cost savings (LFCS) calculation estimates the discounted fuel cost savings for a new battery EV (BEV) or plug-in hybrid EV (PHEV) over a 15-year time horizon using state-level gasoline price and LCOC projections.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook", + "Python" + ], + "name": "LCOC (Levelized Cost of Light-Duty EV Charging Calculator)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/lcoc-ldevs", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LDES-Sizing-and-siting-model__Power_grid_test_cases_for_long-duration_energy_storage__LDES__siting__[SWR-25-75].json b/agency-indexes/DoE/LDES-Sizing-and-siting-model__Power_grid_test_cases_for_long-duration_energy_storage__LDES__siting__[SWR-25-75].json new file mode 100644 index 00000000..fe0b6da4 --- /dev/null +++ b/agency-indexes/DoE/LDES-Sizing-and-siting-model__Power_grid_test_cases_for_long-duration_energy_storage__LDES__siting__[SWR-25-75].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-02", + "metadataLastUpdated": "2025-04-15" + }, + "description": "This repository contains code and data for performing a siting analysis of long-duration energy storage (LDES) in the 5-bus and RTS systems using the Sienna suite developed by the National Renewable Energy Laboratory for production cost modeling (PCM). This analysis involves moving the LDES component to different buses in the system, running a simulation, and considering the production cost of the simulation. Different system configurations are also analyzed with these scripts (such as moving load or renewable dispatch generators to different buses) to observe the impacts the system configuration has on optimal siting. This repository contains three sub directories discussed below. Both the 5-bus and RTS systems have two different initial configurations for the renewable energy components in them, one that is predominantly PV-driven and one that is predominantly wind-driven.\n\nSienna suite can be found here: https://github.com/NREL-Sienna", + "laborHours": 30536.8, + "languages": [ + "Julia" + ], + "name": "LDES-Sizing-and-siting-model (Power grid test cases for long-duration energy storage (LDES) siting) [SWR-25-75]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/LDES-Sizing-and-siting-model", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LEAD_-_LEArning_Damage.json b/agency-indexes/DoE/LEAD_-_LEArning_Damage.json new file mode 100644 index 00000000..c4f3820e --- /dev/null +++ b/agency-indexes/DoE/LEAD_-_LEArning_Damage.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "LEAD is a suite of scripts to enable rapid estimation of model parameters for damage models for ductile materials using machine learning. In its current version, the only supported damage model is TEPLA, though others are planned. The data we train on are comprised of free surface velocity data as well as porosity data. Some details about our method can be found in the preprint LA-UR-23-20468 (arxiv.org/abs/2301.07790)", + "laborHours": 0.0, + "languages": [], + "name": "LEAD - LEArning Damage", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dblaschke-LANL/LEAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LEMD.json b/agency-indexes/DoE/LEMD.json new file mode 100644 index 00000000..f9796f89 --- /dev/null +++ b/agency-indexes/DoE/LEMD.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "nsu@lifeeusa.com" + }, + "date": { + "created": "2020-02-18", + "metadataLastUpdated": "2020-09-09" + }, + "description": "Deep neural network-based force field enables researchers to study materials systems of large size and/or time scale efficiently with comparable accuracy to DFT-based methods. However, such force fields, if improperly trained or mistakenly selected, could result in ill-conditioned results. This SBIR Phase I project has explored the possibility to characterize and index force fields in Deep potential theme by quantizing local atomic environments of atoms in a simulation system. This project has also demonstrated the feasibility of building a public accessible web infrastructure providing high quality machine learning algorithm-based force field for next generation materials modeling and simulation to accelerate the study and discovery of new energy-related materials.", + "laborHours": 638.4, + "languages": [ + "Python" + ], + "name": "LEMD", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mogudaxia/LEMD.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LFIS.json b/agency-indexes/DoE/LFIS.json new file mode 100644 index 00000000..6d36a72b --- /dev/null +++ b/agency-indexes/DoE/LFIS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Repository of the codes developed for the paper titled \"Liouville Flow Importance Sampler\"", + "laborHours": 775.2, + "languages": [], + "name": "LFIS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/LFIS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LGR.json b/agency-indexes/DoE/LGR.json new file mode 100644 index 00000000..cb3bdd75 --- /dev/null +++ b/agency-indexes/DoE/LGR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2020-03-04" + }, + "description": "Provides test-bed for physics on heterogeneous supercomputers.", + "laborHours": 15716.8, + "languages": [], + "name": "LGR", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SNLComputation/lgrtk", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LH2_Transfer_Simulation_.json b/agency-indexes/DoE/LH2_Transfer_Simulation_.json new file mode 100644 index 00000000..97ebc0e6 --- /dev/null +++ b/agency-indexes/DoE/LH2_Transfer_Simulation_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-04-09", + "metadataLastUpdated": "2018-04-09" + }, + "description": "LH2TS enables to calculate the wasted H2 due to transfer and boil-off while using LH2 as a fuel for transportation. The supply chain from the liquefaction plant to the station can be modeled using real gas equations of state from REFPROP and heat transfer models. ", + "laborHours": 532.0, + "name": "LH2 Transfer Simulation ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/NASA-1.3", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LH2Transfer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LIB_Design_Module_for_Grid_Energy_System_Application.json b/agency-indexes/DoE/LIB_Design_Module_for_Grid_Energy_System_Application.json new file mode 100644 index 00000000..22293280 --- /dev/null +++ b/agency-indexes/DoE/LIB_Design_Module_for_Grid_Energy_System_Application.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-10", + "metadataLastUpdated": "2025-02-24" + }, + "description": "We will employ a machine learning approach with intelligent data mining and\ndatabase construction to analyze enormous data repositories for identifying and\nextracting geographic-dependent cell design specifications from publicly accessible\ngrid-scale energy storage usage databases in an automated way at scale.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 53169.6, + "languages": [], + "name": "LIB Design Module for Grid Energy System Application", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/LIBlib_v0.1.0.json b/agency-indexes/DoE/LIBlib_v0.1.0.json new file mode 100644 index 00000000..b36cc6d2 --- /dev/null +++ b/agency-indexes/DoE/LIBlib_v0.1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-28", + "metadataLastUpdated": "2021-10-28" + }, + "description": "LIBlib is a Python 2 / Python 3 software package (library), built on top of the PyGDH package, for relatively simple and highly flexible implementation of macrohomogenous lithium ion battery models.", + "laborHours": 0.0, + "languages": [], + "name": "LIBlib v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/esdr-liblib/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/LIME_0.5.json b/agency-indexes/DoE/LIME_0.5.json new file mode 100644 index 00000000..4ceaefee --- /dev/null +++ b/agency-indexes/DoE/LIME_0.5.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "LIME 0.5 is an initial version of a Lightweight Integrating Multi-physics Environment for coupling codes. LIME by itself is not a code for doing multiphysics simulations. Instead, LIME provides the key high-level software, a flexible but defined approach, and interface requirements for a collection of (potentially disparate) physics codes to be combined with strong coupling (when needed) though non-linear solution methods (e.g. JFNK, fixed point), thus creating a new multi-physics simulation capability customized for a particular need. The approach taken is designed to; preserve and leverage any important specialized algorithms and/or functionality an existing application may provide; minimize the requirements barrier for an application to participate; and work within advanced solver frameworks (e.g. as extensions to the Trilinos/NOX nonlinear solver libraries, PETSc, . . .). Of note is that components/physics codes that can be coupled within LIME are NOT limited to: components written in one particular language; a particular numerical discretization approach ( e.g. Finite Element); or physical models expressed as PDE's.", + "laborHours": 7326.4, + "languages": [ + "CMake", + "C++", + "Fortran" + ], + "name": "LIME 0.5", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/limeext", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LIQUID.json b/agency-indexes/DoE/LIQUID.json new file mode 100644 index 00000000..2bafe41b --- /dev/null +++ b/agency-indexes/DoE/LIQUID.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "LIQUID is a software tool for identifying lipids in LC-MS/MS-based lipidomics data. It is described in publication\u00a0LIQUID: an-open source software for identifying lipids in LC-MS/MS-based lipidomics data\u00a0(doi: 10.1093/bioinformatics/btx046). LIQUID provides users with the capability to process high throughput data and contains a customizable target library and scoring model per project needs. The graphical user interface provides visualization of multiple lines of spectral evidence for each lipid identification, allowing rapid examination of data for making confident identifications of lipid molecular species.", + "laborHours": 76015.2, + "languages": [], + "name": "LIQUID", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LIQUID", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LIvermore_SEM_image_Tools.json b/agency-indexes/DoE/LIvermore_SEM_image_Tools.json new file mode 100644 index 00000000..03b57d1e --- /dev/null +++ b/agency-indexes/DoE/LIvermore_SEM_image_Tools.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2020-05-11" + }, + "description": "Scanning Electron Microscopy (SEM) images provide a variety of structural and morphological\ninformation for the characterization of the nanomaterials. This code offers automatic recognition and\nquantitative analysis of SEM images in a high-throughput manner using computer vision and machine\nlearning techniques. The main function of this application is to extract particle size and morphology\ninformation of overlapping nanoparticles and core-shell nanostructures in a user friendly interface. The\ncode is written in C++ with QT environment, and has been tested on MacOSX.", + "laborHours": 3192.0, + "languages": [], + "name": "LIvermore SEM image Tools", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LIST", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LK_Scripting_Language.json b/agency-indexes/DoE/LK_Scripting_Language.json new file mode 100644 index 00000000..597ade5f --- /dev/null +++ b/agency-indexes/DoE/LK_Scripting_Language.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The LK scripting language is a simple and fast computer programming language designed for easy integration with existing software to enable automation of tasks. The LK language is used by NREL\u2019s System Advisor Model (SAM), the SAM Software Development Kit (SDK), and SolTrace products. LK is easy extensible and adaptable to new software due to its small footprint and is designed to be statically linked into other software. It is written in standard C++, is cross-platform (Windows, Linux, and OSX), and includes optional portions that enable direct integration with graphical user interfaces written in the open source C++ wxWidgets Version 3.0+ toolkit.", + "laborHours": 111248.8, + "name": "LK Scripting Language", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/lk/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/lk", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLEPE.json b/agency-indexes/DoE/LLEPE.json new file mode 100644 index 00000000..18610679 --- /dev/null +++ b/agency-indexes/DoE/LLEPE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-10-19", + "metadataLastUpdated": "2021-10-19" + }, + "description": "LLEPE (liquid-liquid equilibrium parameter estimator) is a tool for estimating thermodynamic parameters like standard enthalpies, standard molar volumes and Pitzer coefficients, by combining Gibbs minimization with regression to multiphase equilibrium isotherm data. It also includes visualization tools to access data quality and prediction model performance.", + "laborHours": 0.0, + "languages": [], + "name": "LLEPE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-CEEESA/LLEPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_Admiral.json b/agency-indexes/DoE/LLNL_Admiral.json new file mode 100644 index 00000000..e5122c0c --- /dev/null +++ b/agency-indexes/DoE/LLNL_Admiral.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "rusu1@llnl.gov" + }, + "date": { + "created": "2020-11-04", + "metadataLastUpdated": "2020-11-04" + }, + "description": "Agent Based Modeling and Reinforcement Learning", + "laborHours": 10138.4, + "languages": [ + "Python" + ], + "name": "LLNL/Admiral", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Admiral", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_Automized_Surface_Titration_Model.json b/agency-indexes/DoE/LLNL_Automized_Surface_Titration_Model.json new file mode 100644 index 00000000..e0d942b0 --- /dev/null +++ b/agency-indexes/DoE/LLNL_Automized_Surface_Titration_Model.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-10-30", + "metadataLastUpdated": "2023-10-30" + }, + "description": "The LLNL Automized Surface Titration Model (L-ASTM) is a community data-driven surface complexation\nmodeling workflow for simulating potentiometric titration of mineral surfaces. The model accepts raw\nexperimental potentiometric titration data formatted in a findable, accessible, interoperable, and reusable\n(FAIR) structure. The workflow was coded in Python and coupled to PHREEQC for surface complexation\nmodeling and PEST for data fitting and parameter estimation.", + "laborHours": 0.0, + "languages": [], + "name": "LLNL Automized Surface Titration Model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LLNL-ASTM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_ExaCMech.json b/agency-indexes/DoE/LLNL_ExaCMech.json new file mode 100644 index 00000000..8b064b30 --- /dev/null +++ b/agency-indexes/DoE/LLNL_ExaCMech.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-08-09", + "metadataLastUpdated": "2019-08-12" + }, + "description": "ExaCMech is a GPU-friendly library of constitutive models. Crystal-mechanics-based and porositymechanics-\nbased models are a principal focus.", + "laborHours": 1900.0, + "languages": [], + "name": "LLNL/ExaCMech", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/exacmech", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_MaPPeRTrac.json b/agency-indexes/DoE/LLNL_MaPPeRTrac.json new file mode 100644 index 00000000..c2305866 --- /dev/null +++ b/agency-indexes/DoE/LLNL_MaPPeRTrac.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "moon15@llnl.gov" + }, + "date": { + "created": "2021-04-06", + "metadataLastUpdated": "2021-04-06" + }, + "description": "Massively Parallel, Portable, and Reproducible Tractography", + "laborHours": 0.0, + "languages": [], + "name": "LLNL/MaPPeRTrac", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MaPPeRTrac", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_Rescal-snow.json b/agency-indexes/DoE/LLNL_Rescal-snow.json new file mode 100644 index 00000000..2be26f00 --- /dev/null +++ b/agency-indexes/DoE/LLNL_Rescal-snow.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-08-09", + "metadataLastUpdated": "2019-10-11" + }, + "description": "When wind blows over snow, it self-organizes. This forms surface features, such as ripples and dunes, that alter the reflectivity and thermal conductivity of the snow.\n\nThese features have just begun to be studied by the snow and climate science communities (see 1, 2, 3 for recent work).\n\nWe created rescal-snow to provide a highly capable snow dune modelling toolkit, to enable snow scientists to study snow features in controlled numerical experiments, and produce high-quality quantitative output. \n\nWe hope that this model will be useful to researchers in snow science, geomorphology, and polar climate.", + "laborHours": 81836.8, + "languages": [], + "name": "LLNL/Rescal-snow", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Rescal-snow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_S-,_P-,_Rayleigh,_Love_wave_model_implementation_into_SPECFEM3D_Globe.json b/agency-indexes/DoE/LLNL_S-,_P-,_Rayleigh,_Love_wave_model_implementation_into_SPECFEM3D_Globe.json new file mode 100644 index 00000000..81ea4f76 --- /dev/null +++ b/agency-indexes/DoE/LLNL_S-,_P-,_Rayleigh,_Love_wave_model_implementation_into_SPECFEM3D_Globe.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-01-07" + }, + "description": "This routine is to be used with the open source package for seismic wave propagation\nSPECFEM3D_Globe version v7.0.2-111-gf469578\n(https://geodynamics.org/cig/software/specfem3d_globe/) to implement the LLNL S-, P-, Rayleigh, Love wave model (SPiRaL). It handles 3D radial isotropic crustal and mantle properties, as well as 410-660 topography.", + "laborHours": 0.0, + "languages": [], + "name": "LLNL S-, P-, Rayleigh, Love wave model implementation into SPECFEM3D_Globe", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/geodynamics/specfem3d_globe.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_SAC2000.json b/agency-indexes/DoE/LLNL_SAC2000.json new file mode 100644 index 00000000..08ad30de --- /dev/null +++ b/agency-indexes/DoE/LLNL_SAC2000.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "barno1@llnl.gov" + }, + "date": { + "created": "2022-07-05", + "metadataLastUpdated": "2022-07-06" + }, + "description": "SAC2000 (Seismic Analysis Code for the third millennium) is a general purpose interactive program designed for the study of sequential signals, especially time-series data.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "LLNL/SAC2000", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SAC2000", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_Software_Catalog.json b/agency-indexes/DoE/LLNL_Software_Catalog.json new file mode 100644 index 00000000..527b1f05 --- /dev/null +++ b/agency-indexes/DoE/LLNL_Software_Catalog.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "The public home for LLNL software catalog\u00a0https://software.llnl.gov. The purpose of this software portal is to serve as a hub for open source software that is produced by Lawrence Livermore National Laboratory.\n", + "laborHours": 198892.0, + "languages": [], + "name": "LLNL Software Catalog", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/llnl.github.io", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_Thomson-Scattering-Cross-Section-Calculator.json b/agency-indexes/DoE/LLNL_Thomson-Scattering-Cross-Section-Calculator.json new file mode 100644 index 00000000..7ea6cf43 --- /dev/null +++ b/agency-indexes/DoE/LLNL_Thomson-Scattering-Cross-Section-Calculator.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "swadling1@llnl.gov" + }, + "date": { + "created": "2021-12-13", + "metadataLastUpdated": "2021-12-20" + }, + "description": "MATLAB Functions for calculating the Thomson scattering cross-section", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "LLNL/Thomson-Scattering-Cross-Section-Calculator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Thomson-Scattering-Cross-Section-Calculator", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_Wemul.json b/agency-indexes/DoE/LLNL_Wemul.json new file mode 100644 index 00000000..5c335efd --- /dev/null +++ b/agency-indexes/DoE/LLNL_Wemul.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "mohror1@llnl.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-01" + }, + "description": "Workflow I/O Emulation Framework", + "laborHours": 4529.6, + "languages": [ + "C", + "C++", + "Perl", + "C", + "python" + ], + "name": "LLNL/Wemul", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/wemul", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_benchpark.json b/agency-indexes/DoE/LLNL_benchpark.json new file mode 100644 index 00000000..27d37f0f --- /dev/null +++ b/agency-indexes/DoE/LLNL_benchpark.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "pearce8@llnl.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "An open collaborative repository for reproducible specifications of HPC benchmarks and cross site benchmarking environments", + "laborHours": 7280.8, + "languages": [ + "Python" + ], + "name": "LLNL/benchpark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/benchpark", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_coda-calibration-tool.json b/agency-indexes/DoE/LLNL_coda-calibration-tool.json new file mode 100644 index 00000000..2860a615 --- /dev/null +++ b/agency-indexes/DoE/LLNL_coda-calibration-tool.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "barno1@llnl.gov" + }, + "date": { + "created": "2018-03-06", + "metadataLastUpdated": "2018-03-06" + }, + "description": "Tool for calibrating 1D coda seismic models", + "laborHours": 47712.8, + "name": "LLNL/coda-calibration-tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/coda-calibration-tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_cyme-launcher.json b/agency-indexes/DoE/LLNL_cyme-launcher.json new file mode 100644 index 00000000..dc5c4ecc --- /dev/null +++ b/agency-indexes/DoE/LLNL_cyme-launcher.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "mast9@llnl.gov" + }, + "date": { + "created": "2022-08-22", + "metadataLastUpdated": "2022-08-22" + }, + "description": "Utility to help run CYME in an HPC environment. Ensures sufficient licenses are available for running CYME in as part of a batch job, and helps start CYME running under WINE on Linux.", + "laborHours": 0.0, + "languages": [ + "Go", + "Go" + ], + "name": "LLNL/cyme-launcher", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/cyme-launcher", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_ddd.json b/agency-indexes/DoE/LLNL_ddd.json new file mode 100644 index 00000000..e19ce944 --- /dev/null +++ b/agency-indexes/DoE/LLNL_ddd.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "gillette7@llnl.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-30" + }, + "description": "This code implements algorithms described in: \"Data-driven geometric scale detection via Delaunay interpolation\" Andrew Gillette and Eugene Kur, 2022 https://arxiv.org/abs/2203.05685", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "LLNL/ddd", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ddd", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_hires-timers.json b/agency-indexes/DoE/LLNL_hires-timers.json new file mode 100644 index 00000000..46ca3b1f --- /dev/null +++ b/agency-indexes/DoE/LLNL_hires-timers.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "C library containing high resolution timer implementation for several platforms.", + "laborHours": 136.8, + "languages": [], + "name": "LLNL hires-timers", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/llnl-hires-timers", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_mgmol.json b/agency-indexes/DoE/LLNL_mgmol.json new file mode 100644 index 00000000..9dc2fdd6 --- /dev/null +++ b/agency-indexes/DoE/LLNL_mgmol.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "fattebertj@ornl.gov" + }, + "date": { + "created": "2018-04-20", + "metadataLastUpdated": "2018-04-20" + }, + "description": "MGmol is a scalable O(N) First-Principles Molecular Dynamics code that is capable of performing large-scale electronics structure calculations and molecular dynamics simulations of atomistic systems.", + "laborHours": 62760.8, + "name": "LLNL/mgmol", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mgmol", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLNL_thicket.json b/agency-indexes/DoE/LLNL_thicket.json new file mode 100644 index 00000000..72548a90 --- /dev/null +++ b/agency-indexes/DoE/LLNL_thicket.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "pearce8@llnl.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "Thicket is a python-based toolkit for Exploratory Data Analysis (EDA) of parallel performance data that enables performance optimization and understanding of applications\u2019 performance on supercomputers. It bridges the performance tool gap between being able to consider only a single instance of a simulation run (e.g., single platform, single measurement tool, or single scale) and finding actionable insights in multi-dimensional, multi-scale, multi-architecture, and multi-tool performance datasets.", + "laborHours": 18452.8, + "languages": [ + "Python" + ], + "name": "LLNL/thicket", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/thicket", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLRF_AMC_Card_Low_Level_Driver.json b/agency-indexes/DoE/LLRF_AMC_Card_Low_Level_Driver.json new file mode 100644 index 00000000..b3b50887 --- /dev/null +++ b/agency-indexes/DoE/LLRF_AMC_Card_Low_Level_Driver.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-10", + "metadataLastUpdated": "2022-08-10" + }, + "description": "This is a low level driver for the LLRF AMC cards. The driver is based on CPSW and implement low level routines to configure the different LLRF AMC cards: Gen1 UpConverter, Gen2 UpConverter, and DownConverter. The driver also implements health checks to verify that the different JESD links are locked and stable.", + "laborHours": 0.0, + "languages": [], + "name": "LLRF AMC Card Low Level Driver", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/llrfAmc/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/llrfAmc", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLUDA__Low-cost_Logging_for_Ubiquitous_Decarbonization_and_Analysis__[SWR-24-131].json b/agency-indexes/DoE/LLUDA__Low-cost_Logging_for_Ubiquitous_Decarbonization_and_Analysis__[SWR-24-131].json new file mode 100644 index 00000000..6c7595e7 --- /dev/null +++ b/agency-indexes/DoE/LLUDA__Low-cost_Logging_for_Ubiquitous_Decarbonization_and_Analysis__[SWR-24-131].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-01-27", + "metadataLastUpdated": "2025-03-11" + }, + "description": "This repository features an Arduino-based GPS logger, called LLUDA, which uses the Adafruit Ultimate GPS FeatherWing with the Adafruit Feather M0 Adalogger, designed to capture and log GPS data in CSV format onto an SD card (embedded inside the Feather M0 Adalogger). The FeatherWing is powered through the vehicle's auxiliary power (from cigarette lighter) socket via a micro USB cable. The data it collects can be used to analyze vehicle operations and support vehicle modeling applications, helping to assess the potential for electrification.", + "laborHours": 136.8, + "languages": [ + "C++" + ], + "name": "LLUDA (Low-cost Logging for Ubiquitous Decarbonization and Analysis) [SWR-24-131]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Low-cost-Logging-for-Ubiquitous-Decarbonization-and-Analysis-LLUDA-", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LLVM.json b/agency-indexes/DoE/LLVM.json new file mode 100644 index 00000000..b8e30a3d --- /dev/null +++ b/agency-indexes/DoE/LLVM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "This disclosure is related to code contributions to the LLVM compiler infrastructure (see http://llvm.org). This includes all the projects encompassed in LLVM as well as a new addition that supports the Fortran programming language. In quick summary, the LLVM Project is a collection of modular and reusable compiler and toolchain technologies. This includes C/C++, Go, runtime systems for OpenMP, and various other supporting pieces such as a debugger and linker. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "LLVM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/LLVM_\"test-suite\".json" "b/agency-indexes/DoE/LLVM_\"test-suite\".json" new file mode 100644 index 00000000..3cb7b49d --- /dev/null +++ "b/agency-indexes/DoE/LLVM_\"test-suite\".json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "This is the LLVM \"test-suite\" repository developed by the Exascale Computing Project (ECP). ", + "laborHours": 1644123.2, + "languages": [], + "name": "LLVM \"test-suite\"", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SOLLVE/llvm-test-suite", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LMT__Lustre_Monitoring_Tool_.json b/agency-indexes/DoE/LMT__Lustre_Monitoring_Tool_.json new file mode 100644 index 00000000..c06339ee --- /dev/null +++ b/agency-indexes/DoE/LMT__Lustre_Monitoring_Tool_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "LMT is a distributed system that provides a \"top\"-like display of the activity levels of the server-side (MDS, OSSes, and LNET routers) nodes of one or more Lustre-based filesystems. It is possible to watch server metrics in real time, and to graph past behavior. The clients provide this capability, but it is also possible to directly mine the MySQL database, e.g. with SQL scripts and GNU plot.\n", + "laborHours": 8253.6, + "languages": [], + "name": "LMT (Lustre Monitoring Tool)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lmt", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LOGAN:_High-Performance_X-Drop_Pairwise_Alignment_on_GPU__LOGAN__v1.0.json b/agency-indexes/DoE/LOGAN:_High-Performance_X-Drop_Pairwise_Alignment_on_GPU__LOGAN__v1.0.json new file mode 100644 index 00000000..e969fedd --- /dev/null +++ b/agency-indexes/DoE/LOGAN:_High-Performance_X-Drop_Pairwise_Alignment_on_GPU__LOGAN__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-11-13", + "metadataLastUpdated": "2019-11-13" + }, + "description": "Pairwise sequence alignment is one of the most computationally intensive kernels in genomic data analysis, accounting for more than 90% of the run time for key bioinformatics applications. This method is particularly expensive for third-generation sequences due to the high computational expense of analyzing these long read lengths (1Kb-1Mb). Given the quadratic overhead of exact pairwise algorithms such as Smith-Waterman, for long alignments, the community primarily relies on approximate algorithms that search only for high-quality alignments and stop early when one is not found. In this work, we present the first GPU optimization of the popular X-drop alignment algorithm, named LOGAN. Results show that our high-performance multi-GPU LOGAN implementation achieves up to 181.6 GCUPS and speed-ups up to 6.6x and 30.7x using 1 and 6 NVIDIA Tesla V100, respectively, over the state-of-the-art software running on two IBM Power9 processors using 168 threads, with equivalent accuracy. We also demonstrate a 2.3x LOGAN speed-up versus ksw2, a state-of-art vectorized algorithm for sequence alignment implemented in minimap2. To highlight the impact of our work on a real-world application, we couple the LOGAN aligner with a many-to-many long-read alignment software called BELLA, and demonstrate that our implementation improves the overall BELLA runtime by up to 10.6x. Finally, we adapt the Roofline model for our optimized kernel and demonstrate that our implementation is near-optimal on the NVIDIA Tesla V100s.", + "laborHours": 133851.2, + "languages": [], + "name": "LOGAN: High-Performance X-Drop Pairwise Alignment on GPU (LOGAN) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/albertozeni/LOGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LOGOS.json b/agency-indexes/DoE/LOGOS.json new file mode 100644 index 00000000..3ca2e100 --- /dev/null +++ b/agency-indexes/DoE/LOGOS.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-19", + "metadataLastUpdated": "2023-03-08" + }, + "description": "LOGOS is a software package which contains a set of discrete optimization models that can be employed for capital budgeting optimization problems. More specifically, provided a set of items (characterized by cost and reward values) and constraints, these models select the best combination of items which maximizes overall reward and satisfies the provided constraints. The developed models are based on different versions of the knapsack optimization algorithms. Two main classes of optimization models have been initially developed: deterministic and stochastic. Stochastic optimization models evolve deterministic models by explicitly considering data uncertainties (associated to constraints or item cost and reward). These models can be employed as stand-alone models or interfaced with the INL developed RAVEN code to propagate data uncertainties and analyze the generated data (i.e., sensitivity analysis).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "LOGOS", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/LOGOS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LOKI.json b/agency-indexes/DoE/LOKI.json new file mode 100644 index 00000000..8f57389e --- /dev/null +++ b/agency-indexes/DoE/LOKI.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-11-10", + "metadataLastUpdated": "2022-11-10" + }, + "description": "LOKI is a simulation code that models weakly-coupled plasma evolution using Eulerian kinetic models in four phase space dimensions. The code is useful to understand basic plasma nonlinear plasma physics phenomena - in particular, wave-particle and wave-wave resonances that occur in laser plasma interactions. LOKI can simulate fundamental physical process in low-density plasmas on a scale of hundreds of light wavelengths. It does so by solving the relativistic Vlasov and Valsov-Fokker-Planck differential transport equations describing the collision less and low-collisionality evolution of charged particles in electromagnetic fields in two configuration space and two velocity space dimensions. Two principle electromagnetic models are provided: electrostatic (Poisson's Equation) and electromagnetic (Maxwell's equations).", + "laborHours": 0.0, + "languages": [], + "name": "LOKI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LOKI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LOOP-LESS_CODE_GENERATOR_FOR_WELL-DEFINED_COMPUTATIONAL_TASKS.json b/agency-indexes/DoE/LOOP-LESS_CODE_GENERATOR_FOR_WELL-DEFINED_COMPUTATIONAL_TASKS.json new file mode 100644 index 00000000..9b6283e6 --- /dev/null +++ b/agency-indexes/DoE/LOOP-LESS_CODE_GENERATOR_FOR_WELL-DEFINED_COMPUTATIONAL_TASKS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2018-09-06" + }, + "description": "Loop-Less Coe Generator for small even size matrices multiplication for AMD processor systems. Matrices are stored in double precision row-wise. Defining the sizes of double precision matrices required. Output is an assembly listing file. Stored as a text file. ", + "laborHours": 0.0, + "languages": [], + "name": "LOOP-LESS CODE GENERATOR FOR WELL-DEFINED COMPUTATIONAL TASKS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jesseYhWang/LLCGX", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LTAU-FF:_Loss_Trajectory_Analysis_for_Uncertainty_in_atomistic_Force_Fields.json b/agency-indexes/DoE/LTAU-FF:_Loss_Trajectory_Analysis_for_Uncertainty_in_atomistic_Force_Fields.json new file mode 100644 index 00000000..8db1f2d5 --- /dev/null +++ b/agency-indexes/DoE/LTAU-FF:_Loss_Trajectory_Analysis_for_Uncertainty_in_atomistic_Force_Fields.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-08", + "metadataLastUpdated": "2024-09-12" + }, + "description": "LTAU (Loss Trajectory Analysis for Uncertainty) is a technique for estimating the uncertainty in a model's\npredictions for any regression task by approximating the cumulative distribution function (CDF) of the\nmodel's errors over the course of training. The approximated CDF, combined with a similarity search\nalgorithm in the model's descriptor space, can then be used to estimate the likelihood that the model's\npredictions on any given test point will fall below a chosen threshold. LTAU-FF (LTAU in atomistic Force\nFields) is the application of LTAU specifically for use with atomistic force fields.", + "laborHours": 896.8, + "languages": [], + "name": "LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ltau-ff", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LUNA.json b/agency-indexes/DoE/LUNA.json new file mode 100644 index 00000000..0c0b5bac --- /dev/null +++ b/agency-indexes/DoE/LUNA.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2022-10-05" + }, + "description": "SAND2021-15051 O\nLuna is an experimental cognitive architecture that seeks to enable continuous learning in an embodied agent. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Python3" + ], + "name": "Luna", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LUNUS,_Version_0.1a.json b/agency-indexes/DoE/LUNUS,_Version_0.1a.json new file mode 100644 index 00000000..2885bd0e --- /dev/null +++ b/agency-indexes/DoE/LUNUS,_Version_0.1a.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "LUNUS software for generating 3D maps of diffuse scattering from macromolecular X-ray crystallography diffraction images. A set of tools needed for advanced refinement of crystal structures and crystallographic charge density models. Includes tools for processing X--ray diffraction images, charge density maps, and structure factors for analysis of diffuse X-ray scattering and charge density variations in crystallography. Specific methods include: elementary algebraic operations on images and 3D lattices; fourier transform of images and 3D lattices; image processing to measure diffuse intensity; crystallographic refinement; and 3D integration of diffuse intensity.", + "laborHours": 25353.6, + "name": "LUNUS, Version 0.1a", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mewall/lunus/blob/master/00LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mewall/lunus", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LUNUS,_Version_0.2a.json b/agency-indexes/DoE/LUNUS,_Version_0.2a.json new file mode 100644 index 00000000..7aa15f4c --- /dev/null +++ b/agency-indexes/DoE/LUNUS,_Version_0.2a.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-06-15", + "metadataLastUpdated": "2022-06-15" + }, + "description": "Software for diffuse X-ray scattering from protein crystals", + "laborHours": 0.0, + "languages": [], + "name": "LUNUS, Version 0.2a", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/lunus", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LW3D_v1.json b/agency-indexes/DoE/LW3D_v1.json new file mode 100644 index 00000000..873cc4d5 --- /dev/null +++ b/agency-indexes/DoE/LW3D_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2021-09-17" + }, + "description": "LW3D is code for modeling beam dynamics in particle accelerators including Lienard-Wiechert self-fields. It is similar to codes like IMPACT-T except that the Poisson solver is replaced by a Lienard-Wiechert solver. Along with space-charge effects, the code can model effects like coherent synchrotron radiation.", + "laborHours": 0.0, + "languages": [], + "name": "LW3D v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LienardWiechert/LW3D", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/LaDa\342\204\242.json" "b/agency-indexes/DoE/LaDa\342\204\242.json" new file mode 100644 index 00000000..7dbc1374 --- /dev/null +++ "b/agency-indexes/DoE/LaDa\342\204\242.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-10-13" + }, + "description": "High-Throughput software platform to create/launch/analyze physics-related calculations. The front-end is a python API which allows the user to create any conceivable first-principles physics calculation. Is is coupled to an ipython interface to launch and retrieve large number of calculations. It was successfully used in high-throughput calculations of point defect formation enthalpies, compound formation enthalpies, and a genetic algorithm search of direct-gap silicon/germanium structures.", + "laborHours": 49506.4, + "languages": [ + "C++", + "Python" + ], + "name": "LaDa\u2122", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://pylada.github.io/pylada", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mdavezac/LaDa", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LaFA.json b/agency-indexes/DoE/LaFA.json new file mode 100644 index 00000000..b21cecfc --- /dev/null +++ b/agency-indexes/DoE/LaFA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Latent Feature Attacks on Non-negative Matrix Factorization", + "laborHours": 1003.2, + "languages": [], + "name": "LaFA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/LaFA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LabVIEW_Task_Manager_v._1.10.0.json b/agency-indexes/DoE/LabVIEW_Task_Manager_v._1.10.0.json new file mode 100644 index 00000000..683c0231 --- /dev/null +++ b/agency-indexes/DoE/LabVIEW_Task_Manager_v._1.10.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "LabVIEW Task Manager is a debugging tool for use during code development in the National Instruments (NI) LabVIEW\u00ae IDE. While providing a dynamic & big-picture view of running code, an expandable/collapsible tree diagram displays detailed information (both static and dynamic) on all VIs in memory, belonging to a selected project/target. It allows for interacting with single or multiple selected VIs at a time, providing significant benefits while troubleshooting, and has the following features: Look & Feel similar to Windows\u00ae Task Manager; Selection of project/target; Lists all VIs in memory, grouped by class/library; Searches for and enumerates clones in memory; DropIn VI for including dynamically referenced clones (Clone Beacon); 'Refresh Now' (F5) re-reads all VIs in memory and adds new ones to the tree; Displays VI name, owning class/library, state, path, data size & code size; Displays VI FP Behavior, Reentrant?, Reentrancy Type, Paused? & Highlight?; Sort by any column, including by library name; Filter by item types vi, ctl, and vit/ctt; Filter out vi.lib and global VIs; Tracking of, and ability to toggle, execution highlighting on multiple selected VIs; Tracking of paused VIs with ability to Pause/Resume/TogglePause multiple selected VIs; DropIn VI for pausing on a condition; If a clone initiates a pause, a different pause symbol is used for all clones of that same reentrant original VI; Select multiple VIs and open or close their FPs or BDs; Double Click a VI from the tree to bring the BD (first choice) or FP to front, if already open; and Select multiple top-level VIs and Abort them.", + "laborHours": 1596.0, + "languages": [ + "National Instruments (NI) LabVIEW\u00ae, versions 2010 through 2016", + "LABVIEW", + "HTML" + ], + "name": "LabVIEW Task Manager v. 1.10.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/lavag/labview-task-manager/src/master/Documentation/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/LVTM", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.10" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Labelme.json b/agency-indexes/DoE/Labelme.json new file mode 100644 index 00000000..9103c832 --- /dev/null +++ b/agency-indexes/DoE/Labelme.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-07", + "metadataLastUpdated": "2022-09-07" + }, + "description": "Labelme is a graphical image annotation tool. It is written in Python and uses Qt for its graphical interface.", + "laborHours": 0.0, + "languages": [], + "name": "Labelme", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/PyLabelMe", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Labor_Planner.json b/agency-indexes/DoE/Labor_Planner.json new file mode 100644 index 00000000..07e06c34 --- /dev/null +++ b/agency-indexes/DoE/Labor_Planner.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Plan and visualize staff labor allocation. This package produces outputs in spreadsheet form that are easily navigable and informative. Outputs include staff-level individual summaries detailing project commitment monthly, project-level summaries highlighting the number of staff and hours per project within an organization, a staff overview summary containing funding probability considerations and visualization, all staff rundown of monthly commitments tied to visual indicators for over- and under-commitment, and overall summary charts and data for all staff and all project and their interrelation. labor_planner was designed for extension and reuse and the authors encourage continued community development.", + "laborHours": 668.8, + "languages": [], + "name": "Labor_Planner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/crvernon/labor_planner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Laboratory_Review_System_Scientific_OSTI_Release_Tool.json b/agency-indexes/DoE/Laboratory_Review_System_Scientific_OSTI_Release_Tool.json new file mode 100644 index 00000000..8b3d99e7 --- /dev/null +++ b/agency-indexes/DoE/Laboratory_Review_System_Scientific_OSTI_Release_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2019-09-30", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Software is a workflow management system designed to capture documents and route for compliance and peer reviews. Software does not in itself contain any technical information but is used as a business system to manage and release information from a research organization.", + "laborHours": 0.0, + "languages": [], + "name": "Laboratory Review System/Scientific OSTI Release Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/LRS_SORT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Labview_utilities.json b/agency-indexes/DoE/Labview_utilities.json new file mode 100644 index 00000000..3744de1d --- /dev/null +++ b/agency-indexes/DoE/Labview_utilities.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-07-23", + "metadataLastUpdated": "2023-03-02" + }, + "description": "The software package provides several utilities written in LabView. These utilities don't form independent programs, but rather can be used as a library or controls in other labview programs. The utilities include several new controls (xcontrols), VIs for input and output routines, as well as other 'helper'-functions not provided in the standard LabView environment.", + "laborHours": 0.0, + "languages": [], + "name": "Labview utilities", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/atap-ibt-labview-utilities", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ladybug_Tools_IN2_Measures.json b/agency-indexes/DoE/Ladybug_Tools_IN2_Measures.json new file mode 100644 index 00000000..84f08dc5 --- /dev/null +++ b/agency-indexes/DoE/Ladybug_Tools_IN2_Measures.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-06", + "metadataLastUpdated": "2019-03-06" + }, + "description": "Ladybug Tools IN2 Measures is a collection of OpenStudio\u00ae measures, file formats, scripts, and related tools for integrating Ladybug Tools with energy modeling via OpenStudio. ", + "laborHours": 0.0, + "languages": [], + "name": "Ladybug Tools IN2 Measures", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ladybug-tools-in2/standards-measure", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lag2D.json b/agency-indexes/DoE/Lag2D.json new file mode 100644 index 00000000..29e80502 --- /dev/null +++ b/agency-indexes/DoE/Lag2D.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2021-09-10" + }, + "description": "This is a 2D Lagrangian discontinuous Galerkin research code written with Fortran. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Lag2D", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lagomorph.json b/agency-indexes/DoE/Lagomorph.json new file mode 100644 index 00000000..a1d753f5 --- /dev/null +++ b/agency-indexes/DoE/Lagomorph.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Existing tools for computational anatomy and image registration are not aimed at HPC environments. As such they are not easily adapted to multimode platforms and contain inefficient batch processing modes. Lagomorph addresses this by providing an easy to install and use pure python implementation of very efficient image registration and atlas building which is aimed at extreme-scale anatomical studies using modern HPC and GPU resources.", + "laborHours": 3192.0, + "languages": [ + "Python 3.6" + ], + "name": "Lagomorph", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jacobhinkle/lagomorph/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jacobhinkle/lagomorph", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Laika_BOSS__Binary_Object_Scanning_System_.json b/agency-indexes/DoE/Laika_BOSS__Binary_Object_Scanning_System_.json new file mode 100644 index 00000000..6677442f --- /dev/null +++ b/agency-indexes/DoE/Laika_BOSS__Binary_Object_Scanning_System_.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-01-22", + "metadataLastUpdated": "2024-09-23" + }, + "description": "Laika BOSS (Binary Object Scanning System), often written as \"Laikaboss\", is an object scanner and intrusion detection system that strives to be scalable, flexible, and verbose. Its goal is to take arbitrary file input and extract all relevant subfiles and metadata for use in helping analysts determine the function and maliciousness of a file at a glance. This is an extension to the original code developed by Lockheed Martin.", + "laborHours": 11901.6, + "languages": [ + "Dockerfile", + "Shell", + "YARA", + "JavaScript", + "Vue", + "Python" + ], + "name": "Laika BOSS (Binary Object Scanning System)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/laikaboss", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.00+2821.g2403134" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lamellar.json b/agency-indexes/DoE/Lamellar.json new file mode 100644 index 00000000..f0581fa2 --- /dev/null +++ b/agency-indexes/DoE/Lamellar.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "asynchronous task based runtime developed using the Rust programming language for HPC", + "laborHours": 0.0, + "languages": [], + "name": "Lamellar", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/lamellar-runtime", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LandBOSSE__Land-Based_Balance_Of_System__2023_[SWR-18-43].json b/agency-indexes/DoE/LandBOSSE__Land-Based_Balance_Of_System__2023_[SWR-18-43].json new file mode 100644 index 00000000..f6d1dc04 --- /dev/null +++ b/agency-indexes/DoE/LandBOSSE__Land-Based_Balance_Of_System__2023_[SWR-18-43].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-19" + }, + "description": "The Land-based Balance-of-System Systems Engineering (LandBOSSE) model is a systems engineering tool that estimates the balance-of-system (BOS) costs associated with installing utility scale wind plants (10, 1.5 MW turbines or larger). It can execute on macOS and Windows. At this time, for both platforms, it is a command line tool that needs to be accessed from the command line.\n\nThe methods used to develop this model (specifically, LandBOSSE Version 2.1.0) are described in greater detail the following report:\n\nEberle, Annika, Owen Roberts, Alicia Key, Parangat Bhaskar, and Katherine Dykes. 2019. NREL\u2019s Balance-of-System Cost Model for Land-Based Wind. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-72201. https://www.nrel.gov/docs/fy19osti/72201.pdf.", + "laborHours": 1884.8, + "languages": [ + "Python" + ], + "name": "LandBOSSE (Land-Based Balance Of System) 2023 [SWR-18-43]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/LandBOSSE", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.5.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LandBOSSE__Land-Based_Balance_Of_System__[SWR-18-43].json b/agency-indexes/DoE/LandBOSSE__Land-Based_Balance_Of_System__[SWR-18-43].json new file mode 100644 index 00000000..5540b99c --- /dev/null +++ b/agency-indexes/DoE/LandBOSSE__Land-Based_Balance_Of_System__[SWR-18-43].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Cost model for Land-Based BOS for wind turbines.", + "laborHours": 1884.8, + "languages": [], + "name": "LandBOSSE (Land-Based Balance Of System) [SWR-18-43]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/WISDEM/LandBOSSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/LandBOSSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LandOpExSE__Land-Based_Operational_Expenditures_SE__[SWR-14-31].json b/agency-indexes/DoE/LandOpExSE__Land-Based_Operational_Expenditures_SE__[SWR-14-31].json new file mode 100644 index 00000000..ec717e27 --- /dev/null +++ b/agency-indexes/DoE/LandOpExSE__Land-Based_Operational_Expenditures_SE__[SWR-14-31].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "A cost model for operational expenditures for land-based wind plants.", + "laborHours": 6733.6, + "languages": [], + "name": "LandOpExSE (Land-Based Operational Expenditures SE) [SWR-14-31]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/Plant_CostsSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Land_Ice_Verification_and_Validation_Kit.json b/agency-indexes/DoE/Land_Ice_Verification_and_Validation_Kit.json new file mode 100644 index 00000000..71f3153c --- /dev/null +++ b/agency-indexes/DoE/Land_Ice_Verification_and_Validation_Kit.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "To address a pressing need to better understand the behavior and complex interaction of ice sheets within the global Earth system, significant development of continental-scale, dynamical ice-sheet models is underway. The associated verification and validation process of these models is being coordinated through a new, robust, python-based extensible software package, the Land Ice Verification and Validation toolkit (LIVV). This release provides robust and automated verification and a performance evaluation on LCF platforms. The performance V&V involves a comprehensive comparison of model performance relative to expected behavior on a given computing platform. LIVV operates on a set of benchmark and test data, and provides comparisons for a suite of community prioritized tests, including configuration and parameter variations, bit-4-bit evaluation, and plots of tests where differences occur.", + "laborHours": 4772.8, + "name": "Land Ice Verification and Validation Kit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LIVVkit/LIVVkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Landscape_Environmental_Assessment_Framework.json b/agency-indexes/DoE/Landscape_Environmental_Assessment_Framework.json new file mode 100644 index 00000000..8f3c1160 --- /dev/null +++ b/agency-indexes/DoE/Landscape_Environmental_Assessment_Framework.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "LEAF Version 2.0 is a framework comprising of three models RUSLE2, WEPS, and AGNPS. The framework can predict row crop, crop residue, and energy crop yields at a sub-field resolutions for various combinations of soil, climate and crop management and residue harvesting practices. It estimates the loss of soil, carbon, and nutrients to the atmosphere, to the groundwater, and to runoff. It also models the overland flow of water and washed-off sediments, nutrients and other chemicals to provide estimates of sediment, nutrient, and chemical loadings to water bodies within a watershed. AGNPS model and wash-off calculations are the new additions to this version of LEAF. Development of LEAF software is supported by DOE's BETO program.", + "laborHours": 0.0, + "languages": [], + "name": "Landscape Environmental Assessment Framework", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/LEAF", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LaplaceInterpolation.jl.json b/agency-indexes/DoE/LaplaceInterpolation.jl.json new file mode 100644 index 00000000..86d474ea --- /dev/null +++ b/agency-indexes/DoE/LaplaceInterpolation.jl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-03" + }, + "description": "This code performs fast interpolation for volume datasets, specifically, Laplace and Matern interpolation where missing data are on a grid of arbitrary dimension.", + "laborHours": 0.0, + "languages": [], + "name": "LaplaceInterpolation.jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/vishwas1984/LaplaceInterpolation.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Large_Language_Model_Output_Evaluator.json b/agency-indexes/DoE/Large_Language_Model_Output_Evaluator.json new file mode 100644 index 00000000..cf93e802 --- /dev/null +++ b/agency-indexes/DoE/Large_Language_Model_Output_Evaluator.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "klaskyhb@ornl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "Given the text files of LLM outputs for specific variables about numerous databases and the reference Excel sheets to compare the LLM outputs to, this program will generate Excel sheets and CSV files of evaluations to describe the LLMs' performances. When the program is executed, these files can be located in ./evals. All folders within ./evals are named by the time which the program finished.\nThe main focus of this pipeline is to evaluate the database descriptions using BERTScore, SacreBLEU, and MoverScore. However, multiple different types of metadata aside from descriptions.", + "laborHours": 410.4, + "languages": [ + "Python" + ], + "name": "Large Language Model Output Evaluator", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/summer_2024/llm_output_evaluation", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "Summer 2024" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Large_Language_Models_for_Anomaly_Detection_in_Computational_Workflows:_from_Supervised_Fine-Tuning_to_In-Context_Learning.json b/agency-indexes/DoE/Large_Language_Models_for_Anomaly_Detection_in_Computational_Workflows:_from_Supervised_Fine-Tuning_to_In-Context_Learning.json new file mode 100644 index 00000000..bc9251dc --- /dev/null +++ b/agency-indexes/DoE/Large_Language_Models_for_Anomaly_Detection_in_Computational_Workflows:_from_Supervised_Fine-Tuning_to_In-Context_Learning.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-19" + }, + "description": "Repo for running Large Language Models for Anomaly Detection in Computational Workflows. Include datasets for 1000Genome, Montage, and Predict Future Sales workflows.", + "laborHours": 3617.6, + "languages": [], + "name": "Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context Learning", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/LLM_AD", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Latent_Space_Dynamics_Identification.json b/agency-indexes/DoE/Latent_Space_Dynamics_Identification.json new file mode 100644 index 00000000..9f897b92 --- /dev/null +++ b/agency-indexes/DoE/Latent_Space_Dynamics_Identification.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-07", + "metadataLastUpdated": "2023-03-07" + }, + "description": "LaSDI is a data-driven physical simulation software that forms a latent space for a given high-fidelity model and discovers a set of ordinary differential equations for the latent space dynamics. It allows a fast and accurate solution process, which is useful for multi-query decision making applications, such as design optimization and uncertainty quantification. The performance of the LaSDI framework is demonstrated on four different problems, i.e., 1D and 2D Burgers equations, nonlinear heat conduction, and radial advection problems. Both linear and nonlinear compression techniques, such as neural network and proper orthogonal decomposition, are used to form a latent space. A concept of local dynamics identification procedure is introduced to enable a parametric model, which enhances the accuracy level over a given parameter space.", + "laborHours": 0.0, + "languages": [], + "name": "Latent Space Dynamics Identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LaSDI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Latent_Variable_Network_Modeling.json b/agency-indexes/DoE/Latent_Variable_Network_Modeling.json new file mode 100644 index 00000000..c8075c87 --- /dev/null +++ b/agency-indexes/DoE/Latent_Variable_Network_Modeling.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-05-05", + "metadataLastUpdated": "2022-05-05" + }, + "description": "lvnm Is a library for fitting latent variable network models within the R programming language. The code focuses on the Stochastic Block Model, Weighted Stochastic Block Model, and Dynamic Stochastic Block Model. Features include simulation methods, estimation methods, diagnostic plots and anomaly detection routines for network data.", + "laborHours": 0.0, + "languages": [ + "R (55%), C++ (40%), Rmarkdown (5%)" + ], + "name": "Latent Variable Network Modeling", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bdabbs13/lvnm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lattice_Optimization_for_Porous_Electrode.json b/agency-indexes/DoE/Lattice_Optimization_for_Porous_Electrode.json new file mode 100644 index 00000000..bf301ca2 --- /dev/null +++ b/agency-indexes/DoE/Lattice_Optimization_for_Porous_Electrode.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-04-13", + "metadataLastUpdated": "2022-04-13" + }, + "description": "This code performs an optimization over the structure of a porous electrode formed from a lattice of unit cells. This is a steepest descent version of the code used in: V. A. Beck, J. J. Wong, C. F. Jekel, D. A. Tortorelli, S. E. Baker, E. B. Duoss and M. A. Worsley, Computational design of microarchitected porous electrodes for redox flow batteries, J. Power Sources, 2021, 512, 230453.", + "laborHours": 0.0, + "languages": [], + "name": "Lattice Optimization for Porous Electrode", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LOPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LaunchMON:_An_Infrastructue_for_Large_Scale_Tool_Daemon_Launching.json b/agency-indexes/DoE/LaunchMON:_An_Infrastructue_for_Large_Scale_Tool_Daemon_Launching.json new file mode 100644 index 00000000..c6fb62fc --- /dev/null +++ b/agency-indexes/DoE/LaunchMON:_An_Infrastructue_for_Large_Scale_Tool_Daemon_Launching.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "LaunchMON is a tool infrastructure that allows a HPC tool to deploy tool daemons into the right remote nodes. It makes use of a target resource manager (RM)'s Automatic Process Acquisition Interface (APAI) to identify the remote nodes and processes of a parallel program, and also exploits the same RM's efficient MPI job launching capability on co-locating daemons with the job. To support a wide range of HPC tools that are inherently distributed software, LaunchMON provides the tool with distributed application programming interface sets: the front end (FE) API, the back end (BE) API and the middleware (MW) API. They each support a tool's front end, back end daemons and middleware communication daemons, respectively. Using those API sets, the tool can launch and initialize their remote daemons scalably.", + "laborHours": 17449.6, + "name": "LaunchMON: An Infrastructue for Large Scale Tool Daemon Launching", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/launchmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lbl_bctc_Ldrd_Graphical_User_Interface.json b/agency-indexes/DoE/Lbl_bctc_Ldrd_Graphical_User_Interface.json new file mode 100644 index 00000000..e775d628 --- /dev/null +++ b/agency-indexes/DoE/Lbl_bctc_Ldrd_Graphical_User_Interface.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-03-05", + "metadataLastUpdated": "2025-03-05" + }, + "description": "This was written in React, using Typescript, Vite, and Material UI", + "laborHours": 10336.0, + "languages": [ + "JavaScript", + "TypeScript" + ], + "name": "Lbl/bctc Ldrd Graphical User Interface", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Solvent_Extraction_Experiment_GUI", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Learning_Planar_Ising_Models_Software.json b/agency-indexes/DoE/Learning_Planar_Ising_Models_Software.json new file mode 100644 index 00000000..d1f9124b --- /dev/null +++ b/agency-indexes/DoE/Learning_Planar_Ising_Models_Software.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-09-15", + "metadataLastUpdated": "2022-09-15" + }, + "description": "Learning Planar Ising Models is a software package written in Matlab for learning relationships among variable in a dataset using graphical models. The software package implements a generally-applicable algorithm for learning planar Ising models from any multivariate dataset. The code provides an algorithm for learning the best planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. The software includes demonstrations of the algorithm in simulations and for applications on publicly available datasets. Details of the algorithm, demonstration simulations, and applications are given in Johnson, et al; 2016. Reference: Johnson, J. K., Oyen, D., Chertkov, M., and Netrapalli, P. (2016). Learning planar Ising models. Journal of Machine Learning Research.", + "laborHours": 0.0, + "languages": [], + "name": "Learning Planar Ising Models Software", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/planar-ising", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Learning_Universal_Authorship_Representations.json b/agency-indexes/DoE/Learning_Universal_Authorship_Representations.json new file mode 100644 index 00000000..86bfffbe --- /dev/null +++ b/agency-indexes/DoE/Learning_Universal_Authorship_Representations.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-02-16", + "metadataLastUpdated": "2023-02-16" + }, + "description": "This code contains all the utilities required to reproduce the results of our EMNLP 2021 paper \"Learning Universal Authorship Representations\". It contains the utilities required for download the datasets, training our model, and performing all evaluations necessary for reproducing the results in the paper. Here's the abstract of our work: Determining whether two documents were composed by the same author, also known as authorship verification, has traditionally been tackled using statistical methods. Recently, authorship representations learned using neural networks have been found to outperform alternatives, particularly in large-scale settings involving hundreds of thousands of authors. But do such representations learned in a particular domain transfer to other domains? Or are these representations inherently entangled with domain-specific features? To study these questions, we conduct the first large-scale study of cross-domain transfer for authorship verification considering zero-shot transfers involving three disparate domains: Amazon reviews, fanfiction short stories, and Reddit comments. We find that although a surprising degree of transfer is possible between certain do- mains, it is not so successful between others. We examine properties of these domains that influence generalization and propose simple but effective methods to improve transfer.", + "laborHours": 0.0, + "languages": [], + "name": "Learning Universal Authorship Representations", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LUAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Learning_in_Emerging_Energy_Industries.json b/agency-indexes/DoE/Learning_in_Emerging_Energy_Industries.json new file mode 100644 index 00000000..36b6b13b --- /dev/null +++ b/agency-indexes/DoE/Learning_in_Emerging_Energy_Industries.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This software is a learning model excerpted from the BSM that can be used to examine effects of different learning rates and different techno-economics on industry evolution.", + "laborHours": 15.2, + "name": "Learning in Emerging Energy Industries", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/bsm-learning/blob/master/ReadMe.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bsm-learning", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Legacy_OpenStudio\302\256_SketchUp_Plug-in_[SWR-07-40].json" "b/agency-indexes/DoE/Legacy_OpenStudio\302\256_SketchUp_Plug-in_[SWR-07-40].json" new file mode 100644 index 00000000..beac2c71 --- /dev/null +++ "b/agency-indexes/DoE/Legacy_OpenStudio\302\256_SketchUp_Plug-in_[SWR-07-40].json" @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2024-02-09" + }, + "description": "The Legacy OpenStudio\u00ae SketchUp Plug-in makes it easy to create and edit the building geometry in EnergyPlus\u00ae input files. This free plug-in also allows you to launch EnergyPlus simulations and view the results without leaving the SketchUp 3D drawing program.\n\nNote that active OpenStudio development has moved from the Legacy OpenStudio Plug-in to the more comprehensive OpenStudio suite of tools and libraries found here: https://github.com/NREL/OpenStudio. More information can be found at http://openstudio.net.\n\nThe OpenStudio Legacy Plug-in has been relaunched as Euclid by Big Ladder Software, the project's new homepage is http://bigladdersoftware.com/projects/euclid/.\n\nThe Legacy OpenStudio Plug-in was created by the National Renewable Energy Laboratory for the U.S. Department of Energy as an interface to the EnergyPlus simulation engine. Refer to the EnergyPlus webpage at energyplus.gov for an overview of the concept and features.\n\nUser support is available via the community moderated question and answer resource unmethours.com.", + "laborHours": 17571.2, + "languages": [ + "Ruby", + "HTML", + "JavaScript" + ], + "name": "Legacy OpenStudio\u00ae SketchUp Plug-in [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/legacy-openstudio", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.14" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Legion.json b/agency-indexes/DoE/Legion.json new file mode 100644 index 00000000..15c4af5f --- /dev/null +++ b/agency-indexes/DoE/Legion.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "Legion is a parallel programming model for distributed, heterogeneous machines.", + "laborHours": 433853.6, + "languages": [], + "name": "Legion", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/StanfordLegion/legion", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lester,_the_Lustre_Lister.json b/agency-indexes/DoE/Lester,_the_Lustre_Lister.json new file mode 100644 index 00000000..ef6bc0ab --- /dev/null +++ b/agency-indexes/DoE/Lester,_the_Lustre_Lister.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Lestre performs a high-speed scan of the Lustre metadata target, and provides a listing of files that match a user-specified criteria, such as modification time, inode number, or if its data resides on specific OSTs. The output format is configurable, as is the parameters it uses to perform IO.", + "laborHours": 2492.8, + "name": "Lester, the Lustre Lister", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-TechInt/lester", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Level_set_topology_optimization_in_Firedrake.json b/agency-indexes/DoE/Level_set_topology_optimization_in_Firedrake.json new file mode 100644 index 00000000..c406c0f3 --- /dev/null +++ b/agency-indexes/DoE/Level_set_topology_optimization_in_Firedrake.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-05-12", + "metadataLastUpdated": "2021-05-12" + }, + "description": "Lestofire is an academic software for the automated design of engineering components. It finds the optimal geometry of a system to minimize a given cost function while constrained by a given set of physics equations. Using a level set function to describe the geometry, lestofire uses shapes derivative to evolve the system until its optimal shape. It leverages the compilation of variational forms in Firedrake (https://www.firedrakeproject.org/) and the automated calculation of shape derivatives via pyadjoint (http://www.dolfin-adjoint.or/en/latest/) to allow fast prototyping of different physics, cost functions and design parametrizations.", + "laborHours": 0.0, + "languages": [], + "name": "Level set topology optimization in Firedrake", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lestofire", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Levelized_Cost_of_Avoided_CO2_tool__LCAC_tool__v0.9.json b/agency-indexes/DoE/Levelized_Cost_of_Avoided_CO2_tool__LCAC_tool__v0.9.json new file mode 100644 index 00000000..adf99142 --- /dev/null +++ b/agency-indexes/DoE/Levelized_Cost_of_Avoided_CO2_tool__LCAC_tool__v0.9.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-06", + "metadataLastUpdated": "2024-08-07" + }, + "description": "The levelized cost of avoided CO2 (LCAC) tool facilitates techno-economic calculations for various decarbonization technologies. It comprises two components to accomplish this: an input workbook based on MS Excel and a web-based output tool. The workbook acts as the input sheet, using the user-provided decarbonization measures and their impacts on lifetime energy consumption, energy costs, and CO2 emissions to compute LCAC (expressed in $/metric ton of avoided CO2). The workbook is uploaded to a web-based tool to generate an LCAC curve. This graphical representation illustrates the economic comparison of all decarbonization measures for purposes such as implementation prioritization. We are unaware of any publicly available tools with similar capabilities.", + "laborHours": 881.6, + "languages": [], + "name": "Levelized Cost of Avoided CO2 tool (LCAC tool) v0.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IACDecarb/IAC-Decarb-Tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Levenberg-Marquardt_Minimization_for_Poisson_Distributed_Data.json b/agency-indexes/DoE/Levenberg-Marquardt_Minimization_for_Poisson_Distributed_Data.json new file mode 100644 index 00000000..0aeab836 --- /dev/null +++ b/agency-indexes/DoE/Levenberg-Marquardt_Minimization_for_Poisson_Distributed_Data.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Fit event counting histograms.", + "laborHours": 0.0, + "languages": [], + "name": "Levenberg-Marquardt Minimization for Poisson Distributed Data", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/levenberg-marquardt-minimization-for-poisson-distributed-data", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/LiAISON__Life-cycle_Assessment_Integration_into_Scalable_Open-source_Numerical_models__[SWR-24-01].json b/agency-indexes/DoE/LiAISON__Life-cycle_Assessment_Integration_into_Scalable_Open-source_Numerical_models__[SWR-24-01].json new file mode 100644 index 00000000..7d9c7fdd --- /dev/null +++ b/agency-indexes/DoE/LiAISON__Life-cycle_Assessment_Integration_into_Scalable_Open-source_Numerical_models__[SWR-24-01].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-12", + "metadataLastUpdated": "2024-01-22" + }, + "description": "We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE)7. We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.\n\nScientific publication available here: https://pubs.acs.org/doi/full/10.1021/acs.est.2c04246", + "laborHours": 0.0, + "languages": [ + "Python", + "Shell" + ], + "name": "LiAISON (Life-cycle Assessment Integration into Scalable Open-source Numerical models) [SWR-24-01]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/LiAISON", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LiTM:_A_Lightweight_Deterministic_Software_Transactional_Memory_System.json b/agency-indexes/DoE/LiTM:_A_Lightweight_Deterministic_Software_Transactional_Memory_System.json new file mode 100644 index 00000000..2755b8b9 --- /dev/null +++ b/agency-indexes/DoE/LiTM:_A_Lightweight_Deterministic_Software_Transactional_Memory_System.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nYu Xia, Xiangyao Yu, William Moses, Julian Shun, and Srini Devadas.\nLiTM: A Lightweight Deterministic Software Transactional Memory System.\nProceedings of the International Workshop on Programming Models and Applications for Multicores and Manycores (PMAM), pp. 1-10, 2019.", + "laborHours": 0.0, + "languages": [], + "name": "LiTM: A Lightweight Deterministic Software Transactional Memory System", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yuxiamit/LiTM", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LiTrack.json b/agency-indexes/DoE/LiTrack.json new file mode 100644 index 00000000..bbe699a6 --- /dev/null +++ b/agency-indexes/DoE/LiTrack.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-14", + "metadataLastUpdated": "2022-07-14" + }, + "description": "LiTrack is a fast 1D longitudinal phase-space tracking code written in MATLAB, which includes standard cavities, chicanes, wakefields, steady-state CSR, and longitudinal space charge.", + "laborHours": 0.0, + "languages": [], + "name": "LiTrack", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/LiTrack", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LibEnsemble.json b/agency-indexes/DoE/LibEnsemble.json new file mode 100644 index 00000000..954b27b5 --- /dev/null +++ b/agency-indexes/DoE/LibEnsemble.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2020-06-01" + }, + "description": "Library for managing ensemble-like collections of computations", + "laborHours": 7311.2, + "languages": [], + "name": "LibEnsemble", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Libensemble/libensemble", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LibIsopach.json b/agency-indexes/DoE/LibIsopach.json new file mode 100644 index 00000000..9b85a389 --- /dev/null +++ b/agency-indexes/DoE/LibIsopach.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "LibIsopach is a toolkit for high performance distributed immersive visualization, leveraging modern OpenGL. It features a multi-process scenegraph, explicit instance rendering, mesh generation, and three-dimensional user interaction event processing.", + "homepageURL": "https://www.nrel.gov/workingwithus/licensing.html", + "laborHours": 11126.4, + "languages": [ + "C++14" + ], + "name": "LibIsopach", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/workingwithus/licensing.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/workingwithus/licensing.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/LibPowerMon:_A_vendor-neutral_system_monitoring_library.json b/agency-indexes/DoE/LibPowerMon:_A_vendor-neutral_system_monitoring_library.json new file mode 100644 index 00000000..b05cc444 --- /dev/null +++ b/agency-indexes/DoE/LibPowerMon:_A_vendor-neutral_system_monitoring_library.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2020-05-13" + }, + "description": "As power becomes an important resource to provision for modern HPC systems it becomes crucial to\nobtain deeper insights into application's power and thermal characteristics and to correlate application\ncontext with important system-level measurements. Existing profiling tools to monitor power and thermal\nmeasurements either operate at a granularity that is not fine enough to correlate with application-level\nevents that describe application context or are not equipped to sample application-level events\ntransparently. We introduce LibPowerMon, a lightweight, vendor-neutral user-level profiling framework to\nsimultaneously sample user-specified application events and system-level metrics at up to 1 kHz\nsampling intervals. At the application level, LibPowerMon provides a source-level phase markup interface\nto capture application context. At runtime level, LibPowerMon records MPI and OpenMP events and can\nbe extended to include other runtimes. At the system level, LibPowerMon samples power, thermal and\nrelevant metrics, and provides an extensible interface to system's control capabilities. In this release,\nLibPowerMon supports monitoring and control functionalities on the Intel, IBM Power9 and Nvidia Volta architectures.\n", + "laborHours": 0.0, + "languages": [], + "name": "LibPowerMon: A vendor-neutral system monitoring library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LibPowerMon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LibPressio-Opt.json b/agency-indexes/DoE/LibPressio-Opt.json new file mode 100644 index 00000000..1af58bad --- /dev/null +++ b/agency-indexes/DoE/LibPressio-Opt.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-29", + "metadataLastUpdated": "2021-09-29" + }, + "description": "LibPressioOpt provides a plugin for libpressio that provides optimization routines to configure compressors", + "laborHours": 0.0, + "languages": [], + "name": "LibPressio-Opt", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/robertu94/libpressio_opt/blob/develop/COPYRIGHT.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/robertu94/libpressio_opt", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LibVMI.json b/agency-indexes/DoE/LibVMI.json new file mode 100644 index 00000000..effb92fe --- /dev/null +++ b/agency-indexes/DoE/LibVMI.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "LibVMI is an introspection library focused on reading and writing memory from virtual machines (VMs). For convenience, LibVMI also provides functions for accessing CPU registers, pausing and unpausing a VM, printing binary data, and more. LibVMI is designed to work across multiple virtualization platforms. LibVMI currently supports VMs running in either Xen or KVM. LibVMI also supports reading physical memory snapshots when saved as a file.", + "laborHours": 59097.6, + "languages": [ + "Yacc", + "C++", + "C", + "CMake", + "M4", + "Python" + ], + "name": "LibVMI", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/libvmi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.6" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Libparty,_Version_1.x.json b/agency-indexes/DoE/Libparty,_Version_1.x.json new file mode 100644 index 00000000..dc3c709d --- /dev/null +++ b/agency-indexes/DoE/Libparty,_Version_1.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A general particle library designed to run on next-generation hardware such as MICs and GPUs.", + "laborHours": 31342.4, + "name": "Libparty, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/libparty", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Libra.json b/agency-indexes/DoE/Libra.json new file mode 100644 index 00000000..b5c89f18 --- /dev/null +++ b/agency-indexes/DoE/Libra.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "Libra is a Python package that extends support of its parent package, SQLAlchemy. Libra\u2019s primary functionality supports the dynamic creation of object-oriented analogs of SQL tables from a variety of user-defined, text-based schema definition formats and provides quality control and analysis tools and methods", + "laborHours": 501.6, + "languages": [], + "name": "Libra", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Seismoacoustics/libra", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Libra:_Scalable_Load_Balance_Analysis.json b/agency-indexes/DoE/Libra:_Scalable_Load_Balance_Analysis.json new file mode 100644 index 00000000..ed732270 --- /dev/null +++ b/agency-indexes/DoE/Libra:_Scalable_Load_Balance_Analysis.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Libra is a tool for scalable analysis of load balance data from all processes in a parallel application. Libra contains an instrumentation module that collects model data from parallel applications and a parallel compression mechanism that uses distributed wavelet transforms to gather load balance model data in a scalable fashion. Data is output to files, and these files can be viewed in a GUI tool by Libra users. The GUI tool associates particular load balance data with regions for code, emabling users to view the load balance properties of distributed \"slices\" of their application code.", + "laborHours": 36723.2, + "name": "Libra: Scalable Load Balance Analysis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/tgamblin/libra/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tgamblin/libra", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Library-AI-Toolset.json b/agency-indexes/DoE/Library-AI-Toolset.json new file mode 100644 index 00000000..2bba83dd --- /dev/null +++ b/agency-indexes/DoE/Library-AI-Toolset.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Collection of tools designed to parse documents, such as PDFs, and extract structured elements including URLs, citation contexts, tables, formulas, and figures. This toolset leverages AI-based text extraction and classification methods, providing robust solutions for various scholarly resources processing needs.", + "laborHours": 1520.0, + "languages": [], + "name": "Library-AI-Toolset", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Library-AI-Toolset", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Light_Transport_with_Weak_Angular_Dependence_in_Fog:_Supplemental_Code.json b/agency-indexes/DoE/Light_Transport_with_Weak_Angular_Dependence_in_Fog:_Supplemental_Code.json new file mode 100644 index 00000000..241b93fd --- /dev/null +++ b/agency-indexes/DoE/Light_Transport_with_Weak_Angular_Dependence_in_Fog:_Supplemental_Code.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-09-30", + "metadataLastUpdated": "2024-07-23" + }, + "description": "A MATLAB script for calculating the optical properties of different fog types. This is a supplemental code intended to be published along with a journal paper. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1504 O", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Light Transport with Weak Angular Dependence in Fog: Supplemental Code", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ltwwadif", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lightshow.json b/agency-indexes/DoE/Lightshow.json new file mode 100644 index 00000000..395c54ac --- /dev/null +++ b/agency-indexes/DoE/Lightshow.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "mcarbone@bnl.gov" + }, + "date": { + "created": "2022-10-12", + "metadataLastUpdated": "2022-10-12" + }, + "description": "A one-stop-shop for writing computational spectroscopy input files.", + "laborHours": 0.0, + "languages": [], + "name": "Lightshow", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AI-multimodal/Lightshow", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lightweight_Distributed_Metric_Service__LDMS__v._4.0.json b/agency-indexes/DoE/Lightweight_Distributed_Metric_Service__LDMS__v._4.0.json new file mode 100644 index 00000000..83697c04 --- /dev/null +++ b/agency-indexes/DoE/Lightweight_Distributed_Metric_Service__LDMS__v._4.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-01-14" + }, + "description": "LDMS is a framework for collection and transport of system monitoring data from computational clusters. It utilizes existing data sources on the cluster (e.g., temperature sensors, network traffic counters). The collection and transport mechanisms of LDMS are lightweight and do not significantly adversely impact the performance of concurrently running applications.", + "laborHours": 98252.8, + "languages": [ + "Perl", + "C", + "Python" + ], + "name": "Lightweight Distributed Metric Service (LDMS) v. 4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ovis-hpc/ovis", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 4.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lightweight_File_System__LWFS__v._1.0.json b/agency-indexes/DoE/Lightweight_File_System__LWFS__v._1.0.json new file mode 100644 index 00000000..d4643278 --- /dev/null +++ b/agency-indexes/DoE/Lightweight_File_System__LWFS__v._1.0.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The Lightweight File System (LWFS) is a storage system that provides a minimal set of I/O-system functionality required by file system and/or I/O library implementations for massively parallel machines. In particular, the LWFS-core consists of a scalable security model, an efficient data-movement protocol, and a direct interface to object-based storage devices. Higher-level services such as namespace management, consistency semantics, reliability, and so forth are layered on top of the core services to provide application-specific functionality as needed. The LWFS code contains implementations of the core services and reference implementations of a number of supplemental services for namespace management and transaction support.", + "laborHours": 230538.4, + "languages": [ + "Shell", + "Perl", + "C", + "Roff", + "Makefile", + "M4" + ], + "name": "Lightweight File System (LWFS) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/lwfs", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lightweight_Threading_and_Communication_Shims_for_Chapel_v._1.0_Beta.json b/agency-indexes/DoE/Lightweight_Threading_and_Communication_Shims_for_Chapel_v._1.0_Beta.json new file mode 100644 index 00000000..fead15de --- /dev/null +++ b/agency-indexes/DoE/Lightweight_Threading_and_Communication_Shims_for_Chapel_v._1.0_Beta.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This software extends the Cray Chapel runtime to use directly Sandia's Qthreads lightweight threading library and Sandia's Portals4 lightweight communication reference library.", + "laborHours": 4298453.6, + "name": "Lightweight Threading and Communication Shims for Chapel v. 1.0 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/chapel-lang/chapel/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chapel-lang/chapel", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Likeness-Vitals.json b/agency-indexes/DoE/Likeness-Vitals.json new file mode 100644 index 00000000..045ad519 --- /dev/null +++ b/agency-indexes/DoE/Likeness-Vitals.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "This package is part of the Likeness Python toolkit, which generates high-fidelity synthetic populations for human dynamics modeling.", + "laborHours": 577.6, + "languages": [ + "Python" + ], + "name": "Likeness-Vitals", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/likeness-vitals/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/likeness-vitals", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.4.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Limbo.json b/agency-indexes/DoE/Limbo.json new file mode 100644 index 00000000..4fa66167 --- /dev/null +++ b/agency-indexes/DoE/Limbo.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "SAND2021-15055 O Limbo provides a programmatic interface for accessing computer vision training data. It is organized in the Limbo format. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://limbo-ml.readthedocs.io/en/latest", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "Limbo", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://limbo-ml.readthedocs.io/en/latest", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Linear_Grains.json b/agency-indexes/DoE/Linear_Grains.json new file mode 100644 index 00000000..c911cd6f --- /dev/null +++ b/agency-indexes/DoE/Linear_Grains.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-14" + }, + "description": "LIGR (Linear Grains) implements a linear (Fourier mode) analysis of a shock propagating through density perturbations. It has two primary capabilities. First, it calculates the shock front distortion and post-shock flow variables (density, velocity, pressure) for single Fourier mode pairs in two dimensions (a pair of x and y modes). Second, it calculates these same quantities for a grains-like pre-shock density perturbation, which consists of a sum of many Fourier modes. This grains-like perturbation is a periodic grid of rectangles at a specifiable density and size (the grains), separated by regions of a different specifiable size and density (interstitial spaces between the grains). The single-mode analysis is based on the work of Velikovich et al., Phys. Plasmas 14 072706 (2007).", + "laborHours": 0.0, + "languages": [], + "name": "Linear Grains", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LIGR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Linear_Scaling_3_Dimensional_Fragment_Method_v1.json b/agency-indexes/DoE/Linear_Scaling_3_Dimensional_Fragment_Method_v1.json new file mode 100644 index 00000000..d2ca63e1 --- /dev/null +++ b/agency-indexes/DoE/Linear_Scaling_3_Dimensional_Fragment_Method_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-16", + "metadataLastUpdated": "2019-01-31" + }, + "description": "The software is a divide-and-conquer method to calculate the material properties using density functional theory (DFT) that scales linearly. Local effects (e.g., quantum) are calculated in small domains while macro effects (e.g., electrostatic) are calculated globally.", + "laborHours": 0.0, + "languages": [], + "name": "Linear Scaling 3 Dimensional Fragment Method v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Lin-Wang/LS3DF", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LinkShop_v.1.0.0.json b/agency-indexes/DoE/LinkShop_v.1.0.0.json new file mode 100644 index 00000000..8459afef --- /dev/null +++ b/agency-indexes/DoE/LinkShop_v.1.0.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "LinkShop is a software tool for applying the method of Linkography to the analysis time-sequence data. LinkShop provides command line, web, and application programming interfaces (API) for input and processing of time-sequence data, abstraction models, and ontologies. The software creates graph representations of the abstraction model, ontology, and derived linkograph. Finally, the tool allows the user to perform statistical measurements of the linkograph and refine the ontology through direct manipulation of the linkograph.", + "laborHours": 10503.2, + "languages": [ + "Python 3, Javascript, C++" + ], + "name": "LinkShop v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/linkshop", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Link_Parser_Library.json b/agency-indexes/DoE/Link_Parser_Library.json new file mode 100644 index 00000000..751ce506 --- /dev/null +++ b/agency-indexes/DoE/Link_Parser_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "Link Parser Library is a Python library for parsing HTTP Link header format. Link Parser extracts information about relationships to other resources from Link Header and translates it into an easy to use Json structure.", + "laborHours": 0.0, + "languages": [], + "name": "Link Parser Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/link-parse", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LinuxSA.json b/agency-indexes/DoE/LinuxSA.json new file mode 100644 index 00000000..84c4e19e --- /dev/null +++ b/agency-indexes/DoE/LinuxSA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Collection of Linux scripts and libraries to aid in common administration tasks and automation. Scripts are for LDAP, nagios, ansible, automatic emailing, license managers, and supporting functions", + "laborHours": 0.0, + "languages": [], + "name": "LinuxSA", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholabUnsupported/LinuxSA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Linux_Kernel_Role.json b/agency-indexes/DoE/Linux_Kernel_Role.json new file mode 100644 index 00000000..ef20e2df --- /dev/null +++ b/agency-indexes/DoE/Linux_Kernel_Role.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-14", + "metadataLastUpdated": "2022-07-14" + }, + "description": "This Ansible role install and enable a specific kernel version from OS repositories and to ensure matching kernel headers are installed.", + "laborHours": 0.0, + "languages": [], + "name": "Linux Kernel Role", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ansible-role-linux-kernel", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Linux_kernel_driver_for_Cray_ClusterStor_E1000_NVMe_slot_LEDs.json b/agency-indexes/DoE/Linux_kernel_driver_for_Cray_ClusterStor_E1000_NVMe_slot_LEDs.json new file mode 100644 index 00000000..f1bb4bbc --- /dev/null +++ b/agency-indexes/DoE/Linux_kernel_driver_for_Cray_ClusterStor_E1000_NVMe_slot_LEDs.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-29", + "metadataLastUpdated": "2023-03-29" + }, + "description": "Linux kernel driver for the Cray ClusterStor E1000 NVMe slot LEDs. This driver allows us to set the 'fault' and 'locate' LEDs on a CrayE1000 slot to indicate which drive has failed. Is there", + "laborHours": 0.0, + "languages": [], + "name": "Linux kernel driver for Cray ClusterStor E1000 NVMe slot LEDs", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tonyhutter/e1000_nvme_led", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LipidFDR.json b/agency-indexes/DoE/LipidFDR.json new file mode 100644 index 00000000..fc1f2049 --- /dev/null +++ b/agency-indexes/DoE/LipidFDR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python scripts of SVM model training and testing used in a publication entitled 'A generalizable method for false-discovery rate estimation in mass spectrometry-based lipidomics'.", + "laborHours": 121.6, + "languages": [], + "name": "LipidFDR", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LipidFDR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lipid_Informed_Quantitation_and_Identification.json b/agency-indexes/DoE/Lipid_Informed_Quantitation_and_Identification.json new file mode 100644 index 00000000..83389675 --- /dev/null +++ b/agency-indexes/DoE/Lipid_Informed_Quantitation_and_Identification.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "LIQUID (Lipid Informed Quantitation and Identification) is a software program that has been developed to enable users to conduct both informed and high-throughput global liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based lipidomics analysis. This newly designed desktop application can quickly identify and quantify lipids from LC-MS/MS datasets while providing a friendly graphical user interface for users to fully explore the data. Informed data analysis simply involves the user specifying an electrospray ionization mode, lipid common name (i.e. PE(16:0/18:2)), and associated charge carrier. A stemplot of the isotopic profile and a line plot of the extracted ion chromatogram are also provided to show the MS-level evidence of the identified lipid. In addition to plots, other information such as intensity, mass measurement error, and elution time are also provided. Typically, a global analysis for 15,000 lipid targets.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Lipid Informed Quantitation and Identification", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ListWindowsShares.json b/agency-indexes/DoE/ListWindowsShares.json new file mode 100644 index 00000000..f4069cfa --- /dev/null +++ b/agency-indexes/DoE/ListWindowsShares.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Utility to show the shared folders on the local computer, or on a remote computer", + "laborHours": 212.8, + "languages": [], + "name": "ListWindowsShares", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/List-Windows-Shares", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lithium-Ion_Modeling_with_1-D_Thermal_Runaway__LIM1TR_.json b/agency-indexes/DoE/Lithium-Ion_Modeling_with_1-D_Thermal_Runaway__LIM1TR_.json new file mode 100644 index 00000000..77458452 --- /dev/null +++ b/agency-indexes/DoE/Lithium-Ion_Modeling_with_1-D_Thermal_Runaway__LIM1TR_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-09-04", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Lithium ion battery technology presents a great opportunity for addressing the need for energy storage. However, in the event of a damaging accident, battery misuse, or manufacturing defect a battery can go in to thermal runaway. This event can be hazardous to nearby humans, flammable materials, and other batteries. When multiple batteries are packed close to one another such as in an energy storage system or electric vehicle, a thermal runaway event in a single can lead to a cascading failure that propagates through neighboring cells. \nA model of cascading failure in a stack of batteries that requires less computational time than a fully resolved system model would be valuable to battery pack designers, fire protection engineers looking at hazards, and researchers developing kinetic and thermal models. A 1-D approximation is reasonable for a stack of pouch/prismatic cells as the thermal conductivity along the electrode materials is significantly higher that the thermal conductivity between layers. This approximation allows for quick testing of chemistry models in cascading failure or single battery/component situations. \nThe primary outputs of this model are the propagation speed and temperature in the battery stack as well as the heat transferred to surrounding materials. The package also aims to provide methods for simulating accelerating rate calorimetry (ARC) and differential scanning calorimetry (DSC) experiments which are commonly used for developing kinetic models for thermal runaway. Simulation of ARC and DSC experiments may not be included in the initial release of the software.\nSandia has been tasked with providing an ability to predict thermal runaway. This tool serves this purpose by providing a platform to communicate the results of this research in a format that allows interaction with the external community. Internal Sandia codes exist with similar capabilities for higher fidelity models and a greater range of customizable physics models. However, these codes are generally not available to designers or fire protection engineers in industry. Additionally, constructing a 1-D approximation in these codes is not a trivial exercise. Commercial codes such as Comsol are also available, but these codes require a license and are not open source. These particular models for thermal runaway are not necessarily available in Comsol and Sandia does not plan to develop in Comsol. No open source finite volume code tailored to battery thermal runaway is known to the authors at this time.\nWe propose the inclusion of the following physics in the model: heat conduction, heat transfer to surroundings/enclosure via convection and radiation, chemical kinetics based on common models from literature with a limited set of options for modifying the kinetic equations, short circuit heating, and conduction between spacer materials. Future versions of the code may include models for gas venting and the associated heat released from the combustion of these gases. The code is written in Python 2.7 with a small number of required packages commonly used for scientific computing. The code also includes a set of unit tests and verification tests. The implementation of this framework with our models allows interaction with other researchers to investigate design variables such as the kinetic parameters and material thermal properties of Li-ion batteries.SAND2019-8934 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1884.8, + "languages": [ + "Python", + "Cython" + ], + "name": "Lithium-Ion Modeling with 1-D Thermal Runaway (LIM1TR)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/lim1tr", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lithium_Supply_Analysis_Model.json b/agency-indexes/DoE/Lithium_Supply_Analysis_Model.json new file mode 100644 index 00000000..bfd2b66e --- /dev/null +++ b/agency-indexes/DoE/Lithium_Supply_Analysis_Model.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-07-21", + "metadataLastUpdated": "2023-03-08" + }, + "description": "This model was developed to assess the viability of US Lithium supply from geothermal brine and the potential supply chain impact of extracting Lithium from this source. This model links global demand and supply of lithium (Li) considering different electric vehicle (EV) demand scenarios. We seek to answer the following questions: \u2022 What is the economic potential of Li extraction from US geothermal sources? \u2022 Is geothermal Li extraction technology a viable investment in the US? \u2022 What is the potential supply chain impact of Li supply from US geothermal sources?", + "laborHours": 0.0, + "languages": [], + "name": "Lithium Supply Analysis Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/LISA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LiveLike.json b/agency-indexes/DoE/LiveLike.json new file mode 100644 index 00000000..d1bc0f4d --- /dev/null +++ b/agency-indexes/DoE/LiveLike.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "This package is part of the Likeness Python toolkit, which generates high-fidelity synthetic populations for human dynamics modeling. The LiveLike package provides a high-level wrapper for generating synthetic populations via Census APIs based on the American Community Survey (ACS) 5-Year Estimates. Synthetic populations are virtual representations of people and households produced for small census areas (block groups, tracts) and can be attributed by a variety of demographic, economic, social, worker, student, mobility, housing, health, and communication characteristics found in the ACS.", + "laborHours": 4636.0, + "languages": [ + "Python" + ], + "name": "LiveLike", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/livelike/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/livelike", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.4.7" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LivermorE_Al_Projector_for_Computed_Tomography_Tasks_.json b/agency-indexes/DoE/LivermorE_Al_Projector_for_Computed_Tomography_Tasks_.json new file mode 100644 index 00000000..edffef6b --- /dev/null +++ b/agency-indexes/DoE/LivermorE_Al_Projector_for_Computed_Tomography_Tasks_.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-22", + "metadataLastUpdated": "2023-06-22" + }, + "description": "With recent computed tomography (CT) efforts using Artificial Intelligence (AI) and Deep Learning (DL)techniques, there is a strong need for differentiable forward projection models that can be integrated into existing DL frameworks. We developed a pytorch-based package library providing differentiable forward and back projection functions and classes to facilitate forward and back propagation of CT operations in\nthe training procedure. This forward projectors support three CT projection geometries: cone, parallel and modular beams. This package can be used with both CPU and GPU with CUDA.", + "laborHours": 0.0, + "languages": [], + "name": "LivermorE Al Projector for Computed Tomography Tasks ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/leap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Livermore_Big_Artificial_Neural_Network_Toolkit.json b/agency-indexes/DoE/Livermore_Big_Artificial_Neural_Network_Toolkit.json new file mode 100644 index 00000000..3acdb9ce --- /dev/null +++ b/agency-indexes/DoE/Livermore_Big_Artificial_Neural_Network_Toolkit.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "LBANN is a toolkit that is designed to train artificial neural networks efficiently on high performance computing architectures. It is optimized to take advantages of key High Performance Computing features to accelerate neural network training. Specifically it is optimized for low-latency, high bandwidth interconnects, node-local NVRAM, node-local GPU accelerators, and high bandwidth parallel file systems. It is built on top of the open source Elemental distributed-memory dense and spars-direct linear algebra and optimization library that is released under the BSD license. The algorithms contained within LBANN are drawn from the academic literature and implemented to work within a distributed-memory framework.", + "laborHours": 64919.2, + "name": "Livermore Big Artificial Neural Network Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LBANN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Livermore_Computing_User_and_System_Scripts.json b/agency-indexes/DoE/Livermore_Computing_User_and_System_Scripts.json new file mode 100644 index 00000000..c7affb3c --- /dev/null +++ b/agency-indexes/DoE/Livermore_Computing_User_and_System_Scripts.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-07-11", + "metadataLastUpdated": "2024-07-11" + }, + "description": "LCUSS is a collection of scripts used to improve productivity on HPC systems for both administrators and\ngeneral users. It will include general scripts for user management, scripts for helping users interact with\nLC resource management software (e.g. SLURM and Flux), and scripts to automate common user\ncommand-line tasks on LC and other HPC machines. These scripts are intended to be made available to\nall LC users. Hosting them on GitHub will allow LC staff, users, and collaborators to work on them\ntogether.", + "laborHours": 60.8, + "languages": [], + "name": "Livermore Computing User and System Scripts", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/LCUSS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Livermore_Metagenomics_Analysis_Toolkit.json b/agency-indexes/DoE/Livermore_Metagenomics_Analysis_Toolkit.json new file mode 100644 index 00000000..8fca80db --- /dev/null +++ b/agency-indexes/DoE/Livermore_Metagenomics_Analysis_Toolkit.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "LMAT is designed to take as input a collection of raw metagenomic sequencer reads, and search each read against a reference genome database and assign a taxonomic label and confidence value to each read and report a summary of the predicted taxonomic contents of the metagenomic sample.", + "homepageURL": "https://sourceforge.net/projects/lmat", + "laborHours": 0.0, + "name": "Livermore Metagenomics Analysis Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/lmat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Livermore_Random_I_O_Testbench.json b/agency-indexes/DoE/Livermore_Random_I_O_Testbench.json new file mode 100644 index 00000000..92643f01 --- /dev/null +++ b/agency-indexes/DoE/Livermore_Random_I_O_Testbench.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-10-08" + }, + "description": "LRIOT is a test bench framework that is designed to generate sophisticated I/O rates that can stress high-performance memory and storage systems, such as non-volatile random access memories (NVRAM)and storage class memory. Furthermore, LRIOT provides the capabilities to mix multiple types of concurrency, namely threading and task parallelism, as well as distributed execution using Message Passing Interface (MPI) libraries. It will be used by algorithm designers to generate access patterns that mimic their application's behavior, and by system designers to test high-performance NVRAM storage.", + "laborHours": 760.0, + "languages": [ + "None" + ], + "name": "Livermore Random I/O Testbench", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/vanessen/lriot/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Livermore_Unstructured_Lagrange_Explicit_Shock_Hydrodynamics.json b/agency-indexes/DoE/Livermore_Unstructured_Lagrange_Explicit_Shock_Hydrodynamics.json new file mode 100644 index 00000000..3284b019 --- /dev/null +++ b/agency-indexes/DoE/Livermore_Unstructured_Lagrange_Explicit_Shock_Hydrodynamics.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-09-30" + }, + "description": "LULESH v1.0 is a 3D unstructured Lagrange hydrodynamics simulation written specifically to solve a standard analytical test problem, known as the Sedov problem. In this problem, a quantum of energy is deposited into a gas and propagates through the gas over time.", + "laborHours": 2933.6, + "languages": [ + "None" + ], + "name": "Livermore Unstructured Lagrange Explicit Shock Hydrodynamics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/lulesh", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LoTToR:_An_Algorithm_for_Missing-Wedge_Correction_of_the_Low-Tilt_Tomographic_3D_Reconstruction_of_a_Single-Molecule_Structure__LoTToR__v1.0.json b/agency-indexes/DoE/LoTToR:_An_Algorithm_for_Missing-Wedge_Correction_of_the_Low-Tilt_Tomographic_3D_Reconstruction_of_a_Single-Molecule_Structure__LoTToR__v1.0.json new file mode 100644 index 00000000..a1cdca38 --- /dev/null +++ b/agency-indexes/DoE/LoTToR:_An_Algorithm_for_Missing-Wedge_Correction_of_the_Low-Tilt_Tomographic_3D_Reconstruction_of_a_Single-Molecule_Structure__LoTToR__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-22", + "metadataLastUpdated": "2021-11-22" + }, + "description": "The low-tilt tomographic reconstruction (LoTToR) method is a post-processing method to correct the missing-wedge artifact, which contains a model-free iteration process under a set of constraints in real and reciprocal spaces. A proof of concept is conducted by using the LoTToR on a phantom, i.e., a simulated 3D reconstruction from a low-tilt series of images, including that within a tilt range of \u00b115\u00b0. The method is validated by using both negative-staining (NS) and cryo-electron tomography (cryo-ET) experimental data. A significantly reduced missing-wedge artifact verifies the capability of LoTToR, suggesting a new tool to support the future study of macromolecular dynamics, fluctuation and chemical activity from the viewpoint of single-molecule 3D structure determination. Moreover, the software can be used for hospital computer tomography (CT) to reduce the radiation damage to patients without reducing the CT image quality.", + "homepageURL": "https://rengroup.lbl.gov/page6/page6-LoTToR-download.html", + "laborHours": 0.0, + "languages": [], + "name": "LoTToR: An Algorithm for Missing-Wedge Correction of the Low-Tilt Tomographic 3D Reconstruction of a Single-Molecule Structure (LoTToR) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://rengroup.lbl.gov/page6/page6-LoTToR-download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Load_Composition_Analysis_Tools.json b/agency-indexes/DoE/Load_Composition_Analysis_Tools.json new file mode 100644 index 00000000..ba69b133 --- /dev/null +++ b/agency-indexes/DoE/Load_Composition_Analysis_Tools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-13", + "metadataLastUpdated": "2022-09-13" + }, + "description": "Methods and tools to support load composition analysis for bulk electric power systems.", + "laborHours": 0.0, + "languages": [], + "name": "Load Composition Analysis Tools", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/load_composition_analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Load_Decomposition_Analysis_Tool.json b/agency-indexes/DoE/Load_Decomposition_Analysis_Tool.json new file mode 100644 index 00000000..b9f1d070 --- /dev/null +++ b/agency-indexes/DoE/Load_Decomposition_Analysis_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-13", + "metadataLastUpdated": "2022-09-13" + }, + "description": "This project tests the application of Bennet Meyers' signal decomposition to the residential end-use load decomposition problem.", + "laborHours": 0.0, + "languages": [], + "name": "Load Decomposition Analysis Tool", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/load_decomposition", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Load_Leveling_Battery_System_Costs.json b/agency-indexes/DoE/Load_Leveling_Battery_System_Costs.json new file mode 100644 index 00000000..8caa44bd --- /dev/null +++ b/agency-indexes/DoE/Load_Leveling_Battery_System_Costs.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-22", + "metadataLastUpdated": "2022-12-07" + }, + "description": "SYSPLAN evaluates capital investment in customer side of the meter load leveling battery systems. Such systems reduce the customer's monthly electrical demand charge by reducing the maximum power load supplied by the utility during the customer's peak demand. System equipment consists of a large array of batteries, a current converter, and balance of plant equipment and facilities required to support the battery and converter system. The system is installed on the customer's side of the meter and controlled and operated by the customer. Its economic feasibility depends largely on the customer's load profile. Load shape requirements, utility rate structures, and battery equipment cost and performance data serve as bases for determining whether a load leveling battery system is economically feasible for a particular installation. Life-cycle costs for system hardware include all costs associated with the purchase, installation, and operation of battery, converter, and balance of plant facilities and equipment. The SYSPLAN spreadsheet software is specifically designed to evaluate these costs and the reduced demand charge benefits; it completes a 20 year period life cycle cost analysis based on the battery system description and cost data. A built-in sensitivity analysis routine is also included for key battery cost parameters. The life cycle cost analysis spreadsheet is augmented by a system sizing routine to help users identify load leveling system size requirements for their facilities. The optional XSIZE system sizing spreadsheet which is included can be used to identify a range of battery system sizes that might be economically attractive. XSIZE output consisting of system operating requirements can then be passed by the temporary file SIZE to the main SYSPLAN spreadsheet.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Load Leveling Battery System Costs", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Load_Model_Data_Tool.json b/agency-indexes/DoE/Load_Model_Data_Tool.json new file mode 100644 index 00000000..41730dd0 --- /dev/null +++ b/agency-indexes/DoE/Load_Model_Data_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The LMDT software automates the process of the load composite model data preparation in the format supported by the major power system software vendors (GE and Siemens). Proper representation of the load composite model in power system dynamic analysis is very important. Software tools for power system simulation like GE PSLF and Siemens PSSE already include algorithms for the load composite modeling. However, these tools require that the input information on composite load to be provided in custom formats. Preparation of this data is time consuming and requires multiple manual operations. The LMDT software enables to automate this process. Software is designed to generate composite load model data. It uses the default load composition data, motor information, and bus information as an input. Software processes the input information and produces load composition model. Generated model can be stored in .dyd format supported by GE PSLF package or .dyr format supported by Siemens PSSE package.", + "homepageURL": "https://svn.pnl.gov/LoadTool", + "laborHours": 0.0, + "languages": [], + "name": "Load Model Data Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://svn.pnl.gov/LoadTool#License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.pnl.gov/LoadTool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/LocOO3d_v.1.1.1.json b/agency-indexes/DoE/LocOO3d_v.1.1.1.json new file mode 100644 index 00000000..92a8a52e --- /dev/null +++ b/agency-indexes/DoE/LocOO3d_v.1.1.1.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-27", + "metadataLastUpdated": "2024-07-27" + }, + "description": "SAND2022-4247 O\nLocOO3d is used to estimate the location of seismic events by comparing estimates of the arrival time for seismic waves from hypothesized locations to observed arrival times. LocOO3d also computes errors in estimated locations through the computation of an \u201cerror ellipsoid\u201d around the optimal event location.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 291095.2, + "languages": [], + "name": "LocOO3d v.1.1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Salsa3DSoftware", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Localization_and_Mapping_Platform_Software__LAMP_Software__v1.json b/agency-indexes/DoE/Localization_and_Mapping_Platform_Software__LAMP_Software__v1.json new file mode 100644 index 00000000..9f4281b9 --- /dev/null +++ b/agency-indexes/DoE/Localization_and_Mapping_Platform_Software__LAMP_Software__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-21", + "metadataLastUpdated": "2021-09-21" + }, + "description": "The Localization and Mapping Platform (LAMP) software fuses radiation and contextual data to produce 3-D maps that locate and identify gamma-ray emitting sources in complex environments. It enables data collection, fusion, and processing in near-real-time and on-board in several configurations, including handheld and unmanned aerial system (UAS) form factors.", + "homepageURL": "https://sites.google.com/lbl.gov/2018-041/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Localization and Mapping Platform Software (LAMP Software) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2018-041/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2018-041/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Localization_and_Mapping_Platform_Software__LAMP__v3.json b/agency-indexes/DoE/Localization_and_Mapping_Platform_Software__LAMP__v3.json new file mode 100644 index 00000000..d8f72639 --- /dev/null +++ b/agency-indexes/DoE/Localization_and_Mapping_Platform_Software__LAMP__v3.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2021-05-27" + }, + "description": "The Localization and Mapping Platform (LAMP) software fuses radiation and contextual data to produce 3-D maps that locate and identify gamma-ray emitting sources in complex environments. It enables data collection, fusion, and processing onboard the LAMP system in handheld configurations, and enables near-real-time 3-D mapping from onboard an unmanned aerial system (UAS). This software enables a real-time 3-D gamma-ray mapping capability that is not available commercially.", + "homepageURL": "https://gitlab.com/lbl-anp/ipo/lamp", + "laborHours": 0.0, + "languages": [], + "name": "Localization and Mapping Platform Software (LAMP) v3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://gitlab.com/lbl-anp/ipo/lamp", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://gitlab.com/lbl-anp/ipo/lamp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Locating_Luna.json b/agency-indexes/DoE/Locating_Luna.json new file mode 100644 index 00000000..f2d92d03 --- /dev/null +++ b/agency-indexes/DoE/Locating_Luna.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-12-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Locating Luna is a STEM Education virtual reality game for grade 6-12 students. Users search for a lost dog in a dark swamp, calling out to the dog and lighting torches as they search. The app collects data on all user actions which are saved in a file for download. Teachers then have students use various tools to represent and analyze their data. This provides a common interactive experience for teachers to use in addressing computer science learning standards. Locations of key points of interest in the app (such as the dog) are randomly generated when the game is restarted\u037e however, replay without a restart of the game allows users to try the same scenario again with a different search strategy. This allows users to compare strategies using data. A teacher's guide supports use by teachers in the classroom.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Locating Luna", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Location_Generalizer.json b/agency-indexes/DoE/Location_Generalizer.json new file mode 100644 index 00000000..3f965e1c --- /dev/null +++ b/agency-indexes/DoE/Location_Generalizer.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2023-03-15" + }, + "description": "This software produces general location descriptions from time-series location data collected from mobile devices that record global positioning system (GPS) coordinates over time. The purpose of this software is to convert detailed location history data, which is considered personally identifiable information (PII), into non-traceable, anonymized, generic information that is useful to researchers but does not contain PII. The software is specifically designed for use with trigger-based data that describe the parked locations and dwell times of automobiles.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Location Generalizer", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Location-Generalizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lock_In_Spectrometer_v0.1.json b/agency-indexes/DoE/Lock_In_Spectrometer_v0.1.json new file mode 100644 index 00000000..0709cc20 --- /dev/null +++ b/agency-indexes/DoE/Lock_In_Spectrometer_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-31", + "metadataLastUpdated": "2021-06-03" + }, + "description": "A method that uses a spectrometer to run a lock in amplifier process on multiple frequencies simultaneously.", + "laborHours": 0.0, + "languages": [], + "name": "Lock In Spectrometer v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMOS-experiment/SILIA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Log-tool.json b/agency-indexes/DoE/Log-tool.json new file mode 100644 index 00000000..f834b3e8 --- /dev/null +++ b/agency-indexes/DoE/Log-tool.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Log-tool is a framework for connecting and processing streams of data. It has a simple modular architecture, consisting of input streams, output streams, and \"parsers\". The \"parsers\" are both input and output streams, and they (generally) perform some operation on that data that passes through them. Many of these parsers can be combined in series to perform more complex operations.\n", + "laborHours": 40036.8, + "name": "Log-tool", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/log-tool", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LogBookClient.json b/agency-indexes/DoE/LogBookClient.json new file mode 100644 index 00000000..2a91d974 --- /dev/null +++ b/agency-indexes/DoE/LogBookClient.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "A python client that talks to the PCDS logbook using the logbook webservice.\n", + "laborHours": 1352.8, + "languages": [], + "name": "LogBookClient", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/LogBookClient", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LogJam.json b/agency-indexes/DoE/LogJam.json new file mode 100644 index 00000000..b54a561c --- /dev/null +++ b/agency-indexes/DoE/LogJam.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "A log viewing and filtering tool.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "LogJam", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/logjam", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Logic_in_Memory_Emulator.json b/agency-indexes/DoE/Logic_in_Memory_Emulator.json new file mode 100644 index 00000000..778fe6d2 --- /dev/null +++ b/agency-indexes/DoE/Logic_in_Memory_Emulator.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-28", + "metadataLastUpdated": "2020-07-28" + }, + "description": "Logic in Memory Emulator (LiME) is a hardware/software tool specially designed for memory system evaluation and experiment. Emerging memories display a wide range of bandwidths, latencies, and capacities, making it challenging for the computer architect to navigate the design space of potential memory configurations, and for the application developer to assess performance implications of using such memories. With the LiME framework, architectural ideas can be prototyped in great detail yet with sufficient performance to support realistic evaluation on long running applications. LiME consists of two fundamental components: 1) the hardware and OS infrastructure for the emulator, and 2) a suite of benchmark applications to assist in characterizing the performance of current and future computer architectures. Some of the applications have been collected from other open source projects.\nUses:\nLogging, replay and analysis of an application's memory behavior Evaluate impact of emerging memory technology on application performance. Emulate complex memory interactions in whole applications orders of magnitude faster than software\nsimulation. Emulate acceleration hardware co-located with the memory subsystem.\nFeatures:\nCapture and log external memory accesses to a separate off-chip memory device without affecting application execution.\nMemory traces include the address, length, timestamp, and optionally the data for each transaction. Captured trace data can be saved to an SD card for off-line analysis.\nConfigure a wide range of memory latencies in sub-nanosecond increments that encompass highbandwidth and storage class memories.\nSpecify regions of interest (ROI) in applications to reduce the amount of trace data captured for analysis. Currently supports execution on Xilinx Zynq SoC which integrates an ARM processor with FPGA logic on a single device.\nApplications can be run under Linux or in bare metal mode on the ARM cores.", + "laborHours": 32041.6, + "languages": [], + "name": "Logic in Memory Emulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lime.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Logical_Activation_Functions_v.1.1.json b/agency-indexes/DoE/Logical_Activation_Functions_v.1.1.json new file mode 100644 index 00000000..aaad269c --- /dev/null +++ b/agency-indexes/DoE/Logical_Activation_Functions_v.1.1.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2024-01501O\nLogical Activation Functions software is a PyTorch implementation from the paper, \"Logical Activation Functions for Training Arbitrary Probabilistic Boolean Logic.\" The activation functions approximate logit-space marginalization of probabilistic truth tables from probabilistic interpretations of inputs. They also provide a general methodology to approximate logical relationships between abstract antecedents and consequents for machine learning architectures. They do not target any specific application or use-case. By training probabilistic truth tables, these activation functions can capture more expressive relationships in a neural network than typical elementwise activation functions. \n\nThis code is only designed for a single compute node with a GPU and is limited to machine learning architectures than can fit within the memory of a single GPU. \n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 608.0, + "languages": [ + "C++", + "Python", + "Cuda", + "Shell" + ], + "name": "Logical Activation Functions v.1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/logic-act", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Look-ahead_Dynamic_Simulation.json b/agency-indexes/DoE/Look-ahead_Dynamic_Simulation.json new file mode 100644 index 00000000..730d231f --- /dev/null +++ b/agency-indexes/DoE/Look-ahead_Dynamic_Simulation.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Look-ahead dynamic simulation software system incorporates the high performance parallel computing technologies, significantly reduces the solution time for each transient simulation case, and brings the dynamic simulation analysis into on-line applications to enable more transparency for better reliability and asset utilization. It takes the snapshot of the current power grid status, functions in parallel computing the system dynamic simulation, and outputs the transient response of the power system in real time.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Linux" + ], + "name": "Look-ahead Dynamic Simulation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lookup_Service_WebUI.json b/agency-indexes/DoE/Lookup_Service_WebUI.json new file mode 100644 index 00000000..0f9dba83 --- /dev/null +++ b/agency-indexes/DoE/Lookup_Service_WebUI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "Lookup Service WebUI (aka. Services Directory) is a Django based web application that presents data from the Simple Lookup Service (sLS) visually in a service oriented fashion.", + "laborHours": 119152.8, + "languages": [], + "name": "Lookup Service WebUI", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/lookup-service-webui/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/lookup-service-webui", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Los_Alamos_Transferable_Tight-binding_for_Energetics__LATTE_,_Version_1.0.json b/agency-indexes/DoE/Los_Alamos_Transferable_Tight-binding_for_Energetics__LATTE_,_Version_1.0.json new file mode 100644 index 00000000..7334a3ff --- /dev/null +++ b/agency-indexes/DoE/Los_Alamos_Transferable_Tight-binding_for_Energetics__LATTE_,_Version_1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2019-06-18", + "metadataLastUpdated": "2019-06-19" + }, + "description": "LATTE is a code used for computing the energy of, and forces acting on atoms in molecular materials using an implementation of the self-consistent charge tranfer tight-binding approximation. Advanced algorithms allow computational cost to scale linearly with the number of atoms, facilitating large-scale, long-duration molecular dynamics simulations of dynamic phenomena using an explicitly quantum mechanical method. Furthermore, these algorithms offer a straightforward path toward parallelization on multi-core/multi-processor and hybrid hardware architectures. Precise energy conservation in quantum-molecular dynamics is made possible via the extended Lagrangian Born-Oppenheimer molecular dynamics formalism. Medium and long-range interactions in molecular materials are described and bond-making and breaking events are tolerated via spin polarization. LATTE facilitates high-fidelity atomistic simulations of static and dynamic phenomena in condensed and gas phases where interatomic interactions are some combination of covalent, electrostatic, and van der Waals bonding. The main features of LATTE are implementation of concepts discussed in the scientific literature.", + "laborHours": 20839.2, + "languages": [], + "name": "Los Alamos Transferable Tight-binding for Energetics (LATTE), Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/LATTE", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Low-Latency_Graph_Streaming_Using_Compressed_Purely-Functional_Trees.json b/agency-indexes/DoE/Low-Latency_Graph_Streaming_Using_Compressed_Purely-Functional_Trees.json new file mode 100644 index 00000000..331c7adf --- /dev/null +++ b/agency-indexes/DoE/Low-Latency_Graph_Streaming_Using_Compressed_Purely-Functional_Trees.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nLaxman Dhulipala, Guy Blelloch, and Julian Shun.\nLow-Latency Graph Streaming Using Compressed Purely-Functional Trees.\nProceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), pp. 918-934, 2019.", + "laborHours": 0.0, + "languages": [], + "name": "Low-Latency Graph Streaming Using Compressed Purely-Functional Trees", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ldhulipala/aspen", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LowFive_v1.0.json b/agency-indexes/DoE/LowFive_v1.0.json new file mode 100644 index 00000000..360dd9b7 --- /dev/null +++ b/agency-indexes/DoE/LowFive_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "LowFive is a new data transport layer based on the HDF5 data model, for in situ workflows. Executables using LowFive can communicate in situ (using in-memory data and MPI message passing), reading and writing traditional HDF5 files to physical storage, and combining the two modes. Minimal and often no source-code modification is needed for programs that already use HDF5. LowFive maintains deep copies or shallow references of datasets, configurable by the user. More than one task can produce (write) data, and more than one task can consume (read) data, accommodating fan-in and fan-out in the workflow task graph. LowFive supports data redistribution from n producer processes to m consumer processes.", + "laborHours": 212161.6, + "languages": [], + "name": "LowFive v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/diatomic/LowFive", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Low_Energy_Analysis_of_NuclEar_Reactions_v0.0.1.json b/agency-indexes/DoE/Low_Energy_Analysis_of_NuclEar_Reactions_v0.0.1.json new file mode 100644 index 00000000..a371d899 --- /dev/null +++ b/agency-indexes/DoE/Low_Energy_Analysis_of_NuclEar_Reactions_v0.0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-05-17", + "metadataLastUpdated": "2023-05-17" + }, + "description": "This is a lightweight, easy to use Python analysis package for analyzing public low-energy nuclear reaction data relevant to understanding basic nuclear processes, often of relevance to Solar Fusion, to improve our theoretical understanding of them, and enable connections with input from lattice QCD. It performs the analysis in a Bayesian Framework and supports Bayesian Model Averaging to provide a robust uncertainty quantification.", + "laborHours": 0.0, + "languages": [], + "name": "Low Energy Analysis of NuclEar Reactions v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrp-g/leaner", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/LsstPsProdTop.json b/agency-indexes/DoE/LsstPsProdTop.json new file mode 100644 index 00000000..66f074ea --- /dev/null +++ b/agency-indexes/DoE/LsstPsProdTop.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-10", + "metadataLastUpdated": "2022-08-10" + }, + "description": "This is the repository for \"LsstPsProdTop\" developed by SLAC National Accelerator Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "LsstPsProdTop", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/LsstPsProdTop/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/LsstPsProdTop", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lua-CLR_Bridge.json b/agency-indexes/DoE/Lua-CLR_Bridge.json new file mode 100644 index 00000000..b07ed7b1 --- /dev/null +++ b/agency-indexes/DoE/Lua-CLR_Bridge.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "creinke@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-01-18" + }, + "description": "LuaCLRBridge is a library which provides an interface for hosting Lua within .NET applications and facilitating interoperability between the two runtimes.", + "homepageURL": "https://bitbucket.org/luaclrbridge/luaclrbridge/src", + "laborHours": 20748.0, + "languages": [ + "C#", + "C++/CLI" + ], + "name": "Lua-CLR Bridge", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/luaclrbridge/luaclrbridge/src", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lua_modules_for_linux_containers.json b/agency-indexes/DoE/Lua_modules_for_linux_containers.json new file mode 100644 index 00000000..e0d32b30 --- /dev/null +++ b/agency-indexes/DoE/Lua_modules_for_linux_containers.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This package inplements a Lua interface to linux containers system calls, such as unshare(2) and chroot(2)", + "laborHours": 0.0, + "name": "Lua modules for linux containers", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/grondo/lua-containers", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lume-model.json b/agency-indexes/DoE/Lume-model.json new file mode 100644 index 00000000..e18bfd3e --- /dev/null +++ b/agency-indexes/DoE/Lume-model.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-14", + "metadataLastUpdated": "2022-07-14" + }, + "description": "Lume-model defines data structures used in the LUME modeling tool set.", + "laborHours": 0.0, + "languages": [], + "name": "Lume-model", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/lume-model/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/lume-model", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Luna_Hostlist_Library.json b/agency-indexes/DoE/Luna_Hostlist_Library.json new file mode 100644 index 00000000..9a4fae12 --- /dev/null +++ b/agency-indexes/DoE/Luna_Hostlist_Library.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This package implements a Lua interface to the LLNL hostlist routines, and includes a hostlist command oine utility based on the lua hostlist library.", + "laborHours": 1930.4, + "name": "Luna Hostlist Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/grondo/lua-hostlist", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Lustre_Administrative_Tool.json b/agency-indexes/DoE/Lustre_Administrative_Tool.json new file mode 100644 index 00000000..90325a81 --- /dev/null +++ b/agency-indexes/DoE/Lustre_Administrative_Tool.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Lustre Administrative Tools (LAT) is a set of programs and utilities designed to facilitate management of the Lustre File System by System Administrators.", + "laborHours": 5639.2, + "name": "Lustre Administrative Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cea-hpc/shine", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/M&V_Tool_Testing_Portal_v1.json b/agency-indexes/DoE/M&V_Tool_Testing_Portal_v1.json new file mode 100644 index 00000000..139acc26 --- /dev/null +++ b/agency-indexes/DoE/M&V_Tool_Testing_Portal_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-10", + "metadataLastUpdated": "2018-09-13" + }, + "description": "Software is an online self-service portal for testing M&V methods/tools using buildings' interval meter data. After registering as a user in the portal, that user can download test data files, run those test data files through their own M&V software, and then upload software modeling results to the online portal as a csv file. After the user has uploaded their modeling results the portal will develop statistical accuracy metrics for that M&V tool. The online portal will summarize test results for some or all of the submitted tests. This online portal has been developed by LBNL, and we have been collaborating with the Efficiency Valuation Organization (EVO) with the objective of EVO managing the portal as an ongoing service. Portal is currently posted at http://mvportal.evo-world.org/", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 3237.6, + "languages": [], + "name": "M&V Tool Testing Portal v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/M3D-C1.json b/agency-indexes/DoE/M3D-C1.json new file mode 100644 index 00000000..fc214e35 --- /dev/null +++ b/agency-indexes/DoE/M3D-C1.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "nferraro@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2018-07-02" + }, + "description": "M3D-C1 is a code for simulating magnetized plasmas using an extended-MHD model", + "homepageURL": "https://w3.pppl.gov/~nferraro/m3dc1.html", + "laborHours": 0.0, + "languages": [ + "C++", + "Fortran", + "IDL" + ], + "name": "M3D-C1", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://w3.pppl.gov/~nferraro/m3dc1.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MACAW_v1.0.json b/agency-indexes/DoE/MACAW_v1.0.json new file mode 100644 index 00000000..7259da29 --- /dev/null +++ b/agency-indexes/DoE/MACAW_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-21" + }, + "description": "The ability to embed molecules in a numeric space is essential in order to build mathematical and machine-learning models describing molecular properties or other processes affected by molecules. MACAW is a cheminformatic tool that allows embedding small molecules into a multidimensional numeric space. In the embedding, each molecule is assigned a numeric vector that captures information of the molecule in relation to other molecules, and that vector can be used as input to mathematical models. Molecules that are more similar to each other are embedded closer in this numeric space, whereas molecules that are more different are embedded further away. One advantage of the MACAW embedding technology compared to established alterantives is that it is fast and does not require extensive computational resources or expertise. In particular, MACAW embeddings can be used as input to mathematical models without the need for variable cleaning or feature selection, saving time and simplifying their use. On the other hand, MACAW also contains methods to generate new molecules and to recommend new molecules satisfying a desired molecular property. The generation of new molecules can be biased based on an input set of molecules, effectively generating molecular diversity around it. In its turn, MACAW's molecular recommendation tool is a novel method for evolving molecules in silico towards a desired molecular specification. In this method, the biased molecular generator tool is applied iteratively in combination with a molecular selection step. As a result, in each iteration the molecules selected by the software are increasingly closer to the desired specification. Both the molecular generation and the molecular recommendation tools are very fast, efficient, and intuitive to use.", + "homepageURL": "https://sites.google.com/lbl.gov/2021-187/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "MACAW v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2021-187/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-187/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MADSpython_1.x.json b/agency-indexes/DoE/MADSpython_1.x.json new file mode 100644 index 00000000..f7efeb9e --- /dev/null +++ b/agency-indexes/DoE/MADSpython_1.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MADSpython (Model analysis and decision support tools in Python) is a code in Python that streamlines the process of using data and models for analysis and decision support using the code MADS. MADS is open-source code developed at LANL and written in C/C++ (MADS; http://mads.lanl.gov; LA-CC-11-035). MADS can work with external models of arbitrary complexity as well as built-in models of flow and transport in porous media. The Python scripts in MADSpython facilitate the generation of input and output file needed by MADS as wells as the external simulators which include FEHM and PFLOTRAN. MADSpython enables a number of data- and model-based analyses including model calibration, sensitivity analysis, uncertainty quantification, and decision analysis. MADSpython will be released under GPL V3 license. MADSpython will be distributed as a Git repo at gitlab.com and github.com. MADSpython manual and documentation will be posted at http://madspy.lanl.gov.", + "laborHours": 182.4, + "name": "MADSpython 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/madspython", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MAESTROeX.json b/agency-indexes/DoE/MAESTROeX.json new file mode 100644 index 00000000..a37f540a --- /dev/null +++ b/agency-indexes/DoE/MAESTROeX.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "ajnonaka@lbl.gov" + }, + "date": { + "created": "2021-04-15", + "metadataLastUpdated": "2021-04-15" + }, + "description": "MAESTROeX is a massively parallel, finite-volume C++/F90 solver for low Mach number astrophysical flows. The code utilizes a low Mach number equation set allowing for more efficient, long-time integration of highly subsonic flows compared to compressible approaches. The recommended range of applicability is for flows where the Mach number does not exceed~0.1.", + "laborHours": 0.0, + "languages": [ + "C++", + "Fortran" + ], + "name": "MAESTROeX", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Astro/MAESTROeX", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "20.11" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MAFRIT__Multi-Area_Frequency_Response_Integration_Tool_.json b/agency-indexes/DoE/MAFRIT__Multi-Area_Frequency_Response_Integration_Tool_.json new file mode 100644 index 00000000..8fce0e35 --- /dev/null +++ b/agency-indexes/DoE/MAFRIT__Multi-Area_Frequency_Response_Integration_Tool_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-03-18", + "metadataLastUpdated": "2020-04-03" + }, + "description": "The Multi-Area Frequency Response Integration Tool (MAFRIT) is the only software tool of its kind that integrates primary frequency response (turbine governor control) with secondary frequency response (automatic generation control). It simulates the power system dynamic response in full time spectrum with variable time steps from millisecond to minutes to hours and days. Capable of simulating both normal and event conditions, this tool can represent real power system operations and thus evaluate the primary and secondary reserves adequacy. This unique interaction of a turbine governor model and a novel automatic generation control model places special emphasis on electric power systems with high penetrations of renewable generation.", + "laborHours": 3967.2, + "languages": [ + "MATLAB" + ], + "name": "MAFRIT (Multi-Area Frequency Response Integration Tool)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MAFRIT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MAGMA.json b/agency-indexes/DoE/MAGMA.json new file mode 100644 index 00000000..f51aafec --- /dev/null +++ b/agency-indexes/DoE/MAGMA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "The MAGMA (Matrix Algebra on GPU and Multicore Architectures) project aims to develop a dense linear algebra library similar to LAPACK but for heterogeneous/hybrid architectures, starting with current \"Multicore+GPU\" systems.", + "homepageURL": "https://bitbucket.org/icl/magma/src/default", + "laborHours": 303969.6, + "languages": [], + "name": "MAGMA", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/icl/magma/src/default/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/icl/magma/src/default", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MAGMAFortranModule.json b/agency-indexes/DoE/MAGMAFortranModule.json new file mode 100644 index 00000000..21cea1e3 --- /dev/null +++ b/agency-indexes/DoE/MAGMAFortranModule.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Module file to be used with Fortran (90) to gain access to MAGMA's C routines\n", + "laborHours": 501.6, + "name": "MAGMAFortranModule", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/MAGMAFortranModule", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MAK.json b/agency-indexes/DoE/MAK.json new file mode 100644 index 00000000..be771f5e --- /dev/null +++ b/agency-indexes/DoE/MAK.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "This is the repository for \"MAK\" developed by KBase. ", + "laborHours": 6536.0, + "languages": [], + "name": "MAK", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/MAK", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MAM4xx.json b/agency-indexes/DoE/MAM4xx.json new file mode 100644 index 00000000..9853cb85 --- /dev/null +++ b/agency-indexes/DoE/MAM4xx.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2023-08-10" + }, + "description": "SAND2023-05377O\nThe Modal Aerosol Model with 4 fixed modes (MAM4xx) is a performance-portable, C++ implementation for modeling the chemical reactions of aerosols in the atmosphere. MAM4xx is part of the Energy Exascale Earth System Model (E3SM). The E3SM project is an ongoing Earth system modeling, simulation, and prediction project that optimizes the use of DOE laboratory resources to meet the science needs of the nation and the mission needs of DOE. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "MAM4xx", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eagles-project/mam4xx", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MAMA_Plugin_API.json b/agency-indexes/DoE/MAMA_Plugin_API.json new file mode 100644 index 00000000..bde457d6 --- /dev/null +++ b/agency-indexes/DoE/MAMA_Plugin_API.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-03-16", + "metadataLastUpdated": "2018-03-16" + }, + "description": "Plugin API for the LANL Mama (Morphological Analysis of Materials) application.", + "laborHours": 136.8, + "name": "MAMA Plugin API", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/mama-plugin-api", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MAPLE_v.1.0.json b/agency-indexes/DoE/MAPLE_v.1.0.json new file mode 100644 index 00000000..6b5d4e99 --- /dev/null +++ b/agency-indexes/DoE/MAPLE_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-27", + "metadataLastUpdated": "2025-03-04" + }, + "description": "SAND2025-00659O\nMAPLE is a software tool that uses epigenomic data to predict gene expression. MAPLE uses a set of epigenomic modifications to determine the effect on gene expression in a specific subset of species. The algorithm can be trained on additional species and epigenomic modifications, enhancing its predictive capabilities. EAGLE employs a hybrid neural network architecture, featuring a convolutional front-end and a multi-head attention layer, to process pre-processed signal data as input. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 243.2, + "languages": [ + "Python" + ], + "name": "MAPLE v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MAPLE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MAPSToTomoPy.json b/agency-indexes/DoE/MAPSToTomoPy.json new file mode 100644 index 00000000..6485298c --- /dev/null +++ b/agency-indexes/DoE/MAPSToTomoPy.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-16", + "metadataLastUpdated": "2019-08-16" + }, + "description": "MAPSToTomoPy provides a graphical user interface (GUI) to control a work flow between MAPS and TomoPy, with tools for visualizing the sinograms of projection image sequences from particular elements and to use these to help correct misalignments of the rotation axis. The program also provides an integrated output of the 3D distribution of the detected elements for subsequent 3D visualization packages.", + "laborHours": 1535.2, + "languages": [], + "name": "MAPSToTomoPy", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdvancedPhotonSource/MAPSToTomoPy", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MAPVAR_V1.9.json b/agency-indexes/DoE/MAPVAR_V1.9.json new file mode 100644 index 00000000..85128306 --- /dev/null +++ b/agency-indexes/DoE/MAPVAR_V1.9.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "Mapvar is designed to transfer solution results from one finite element mesh to another. Mapvar draws heavily from the structure and coding of MERLIN II, but it employs a new finite element data base. Exodus II, and offers enhanced speed and new capabilities not available in MERLIN II.", + "laborHours": 692284.0, + "languages": [ + "Fortran" + ], + "name": "MAPVAR V1.9", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MAQ:_Machine_Learning_on_Adiabatic_Quantum_Computers.json b/agency-indexes/DoE/MAQ:_Machine_Learning_on_Adiabatic_Quantum_Computers.json new file mode 100644 index 00000000..abc53a80 --- /dev/null +++ b/agency-indexes/DoE/MAQ:_Machine_Learning_on_Adiabatic_Quantum_Computers.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "datepa@ornl.gov" + }, + "date": { + "created": "2024-03-07", + "metadataLastUpdated": "2024-03-07" + }, + "description": "Machine Learning on Adiabatic Quantum Computers (MAQ) is a library of algorithms used to train machine learning models on adiabatic quantum computers.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "MAQ: Machine Learning on Adiabatic Quantum Computers", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/prasannadate/maq", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MARBLES__Multi-scale_Adaptively_Refined_Boltzmann_LatticE_Solver__[SWR-23-37].json b/agency-indexes/DoE/MARBLES__Multi-scale_Adaptively_Refined_Boltzmann_LatticE_Solver__[SWR-23-37].json new file mode 100644 index 00000000..34eae50a --- /dev/null +++ b/agency-indexes/DoE/MARBLES__Multi-scale_Adaptively_Refined_Boltzmann_LatticE_Solver__[SWR-23-37].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-09", + "metadataLastUpdated": "2023-10-09" + }, + "description": "MARBLES (Multi-scale Adaptively Refined Boltzmann LatticE Solver) is an open-source computational fluid dynamics package powered by the lattice Boltzmann equations and built on AMReX. In the lattice Boltzmann method, local collisions between meso-scale fictitious particles drive the governing equations which enables MARBLES to easily simulate flow around complex and/or moving geometry without the generation of a body-conforming mesh. Using AMReX data structures and operations ensures a high level of computational performance and parallel scaling on heterogenous architectures while also naturally supporting locally enhanced grid resolution and fidelity through automatic mesh refinement. New domains and problem definitions are easily specified through an input file with examples and guidance on all options and variables provided in the MARBLES documentation.", + "laborHours": 0.0, + "languages": [ + "C++", + "CMake" + ], + "name": "MARBLES (Multi-scale Adaptively Refined Boltzmann LatticE Solver) [SWR-23-37]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/marbles", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MATBOX__Microstructure_Analysis_Toolbox__[SWR-20-76].json b/agency-indexes/DoE/MATBOX__Microstructure_Analysis_Toolbox__[SWR-20-76].json new file mode 100644 index 00000000..3d281ba7 --- /dev/null +++ b/agency-indexes/DoE/MATBOX__Microstructure_Analysis_Toolbox__[SWR-20-76].json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-07-02", + "metadataLastUpdated": "2023-12-18" + }, + "description": "MATBOX is a MATLAB application for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization, result three-dimensional visualization and result correlation, and microstructure meshing. MATBOX was originally developed to analyze electrode microstructures for lithium ion batteries; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphic-User Interface.", + "laborHours": 28059.2, + "languages": [ + "MATLAB" + ], + "name": "MATBOX (Microstructure Analysis Toolbox) [SWR-20-76]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/MATBOX_Microstructure_analysis_toolbox", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MATBOX_Microstructure_analysis_toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "Matbox2021c" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MATMULT_Version1.0.json b/agency-indexes/DoE/MATMULT_Version1.0.json new file mode 100644 index 00000000..5a2a4665 --- /dev/null +++ b/agency-indexes/DoE/MATMULT_Version1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "MATMULT is a benchmark computes the dense matrix multiply, C=A*B using the DotProd and column methods with various levels of inner loop unrolling. The performance is measured and result correctness is checked.", + "laborHours": 0.0, + "languages": [ + "Fortran (48%), C(52%)" + ], + "name": "MATMULT Version1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/matmult-version1.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MAUD_Interface_Tool_Kit__MILK_.json b/agency-indexes/DoE/MAUD_Interface_Tool_Kit__MILK_.json new file mode 100644 index 00000000..caa96ab3 --- /dev/null +++ b/agency-indexes/DoE/MAUD_Interface_Tool_Kit__MILK_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "Materials Analysis Using Diffraction (MAUD) is an open source Rietveld refinement program which fits diffraction models to\ndiffraction spectra allowing quantitative diffraction analysis. The scripting interface developed here using python facilitates the\nchoice of parameters to refine during the Rietveld fitting process and provides a simple MPI framework for running MAUD\ninstances in parallel. The scripting language facilitates batch, custom, and reproducible Rietveld refinements of large datasets.", + "laborHours": 0.0, + "languages": [], + "name": "MAUD Interface Tool Kit (MILK)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MILK", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MBMS1.0:_An_Open-Source_Code_for_Modeling_and_Simulation_of_Membrane-Based_Dehumidification_and_Energy_Recovery.json b/agency-indexes/DoE/MBMS1.0:_An_Open-Source_Code_for_Modeling_and_Simulation_of_Membrane-Based_Dehumidification_and_Energy_Recovery.json new file mode 100644 index 00000000..d9abf145 --- /dev/null +++ b/agency-indexes/DoE/MBMS1.0:_An_Open-Source_Code_for_Modeling_and_Simulation_of_Membrane-Based_Dehumidification_and_Energy_Recovery.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2021-03-05" + }, + "description": "Air dehumidification processes are important and significantly impact both the performance of building ventilation and air conditioning systems, and the health of occupants. In a membrane-based dehumidifier, a permselective membrane is adopted to separate the two flow streams at feed and permeate sides. The feed side is continuously supplied with humid air at atmospheric pressure, while the permeate side is connected to a vacuum pump to produce vacuum or a low permeate vapor pressure as a driving force for water vapor permeation. The software MBMS 1.0 enables modeling and simulation of the design and configuration optimization of a membrane-based air-to-air (A2A) or air-to-vapor (A2V) device. A first-order physical-constant model was developed to reasonably account for the fundamental heat and mass transfer processes involved.", + "laborHours": 1200.8, + "languages": [ + "C", + "C++" + ], + "name": "MBMS1.0: An Open-Source Code for Modeling and Simulation of Membrane-Based Dehumidification and Energy Recovery", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MBMS/C-CODE_FOR_MEMBRANE_BASED_MODEL", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "MBMS. 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MC-ASI.json b/agency-indexes/DoE/MC-ASI.json new file mode 100644 index 00000000..f03c97a8 --- /dev/null +++ b/agency-indexes/DoE/MC-ASI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-30" + }, + "description": "The software performs Monte Carlo simulations for artificial spin ice (ASI) structures. ASIs are composed of magnetic nano islands on varying lattice geometries. The software computes the dipolar energy of the neighboring islands and determines their ground state configuration. Various thermodynamic parameters are also calculated during the simulations. Flexibility is provided in terms of input of various types of lattice geometries.", + "laborHours": 0.0, + "languages": [], + "name": "MC-ASI", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cphatak/mc_asi", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MC3,_Version_1.json b/agency-indexes/DoE/MC3,_Version_1.json new file mode 100644 index 00000000..58064447 --- /dev/null +++ b/agency-indexes/DoE/MC3,_Version_1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The MC3 code is used to perform Monte Carlo simulations in the isothermal-isobaric ensemble (constant number of particles, temperature, and pressure) on molecular crystals. The molecules within the periodic simulation cell are treated as rigid bodies, alleviating the requirement for a complex interatomic potential. Intermolecular interactions are described using generic, atom-centered pair potentials whose parameterization is taken from the literature [D. E. Williams, J. Comput. Chem., 22, 1154 (2001)] and electrostatic interactions arising from atom-centered, fixed, point partial charges. The primary uses of the MC3 code are the computation of i) the temperature and pressure dependence of lattice parameters and thermal expansion coefficients, ii) tensors of elastic constants and compliances via the Parrinello and Rahman\u2019s fluctuation formula [M. Parrinello and A. Rahman, J. Chem. Phys., 76, 2662 (1982)], and iii) the investigation of polymorphic phase transformations. The MC3 code is written in Fortran90 and requires LAPACK and BLAS linear algebra libraries to be linked during compilation. Computationally expensive loops are accelerated using OpenMP.", + "laborHours": 0.0, + "name": "MC3, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cawkwell/MC3", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MC3.json b/agency-indexes/DoE/MC3.json new file mode 100644 index 00000000..30830c53 --- /dev/null +++ b/agency-indexes/DoE/MC3.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-10-13", + "metadataLastUpdated": "2024-07-23" + }, + "description": "MC3 is a model checking solver that provides a more efficient tool for a widely studied class of problems currently solved by other open-source software tools. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-4549 O", + "laborHours": 1732.8, + "languages": [ + "Racket", + "Makefile" + ], + "name": "MC3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mc3", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MCM__Marine_Carbon_Management__[SWR-24-122].json b/agency-indexes/DoE/MCM__Marine_Carbon_Management__[SWR-24-122].json new file mode 100644 index 00000000..9db2b8e3 --- /dev/null +++ b/agency-indexes/DoE/MCM__Marine_Carbon_Management__[SWR-24-122].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-12-16", + "metadataLastUpdated": "2024-12-16" + }, + "description": "The marine carbon management software is an open-source Python based software that contains generic models for marine carbon capture, marine carbon dioxide removal, marine carbon capture and utilization, marine carbon capture and storage. The models include design parameters, operational conditions and scenarios and technology costs.", + "laborHours": 942.4, + "languages": [ + "Python" + ], + "name": "MCM (Marine Carbon Management) [SWR-24-122]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MarineCarbonManagement", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MCREX.json b/agency-indexes/DoE/MCREX.json new file mode 100644 index 00000000..b3c30470 --- /dev/null +++ b/agency-indexes/DoE/MCREX.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "MCREX Monte Carlo linear solvers project repository.\u00a0http://ornl-cees.github.io/MCREX/\n", + "laborHours": 2186413.6, + "name": "MCREX", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-CEES/MCREX", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MCR_Container_Tools.json b/agency-indexes/DoE/MCR_Container_Tools.json new file mode 100644 index 00000000..e1818ef5 --- /dev/null +++ b/agency-indexes/DoE/MCR_Container_Tools.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "MathWorks' MATLAB is widely used in academia and industry for prototyping, data analysis, data processing, etc. Many users compile their programs using the MATLAB Compiler to run on workstations/computing clusters via the free MATLAB Compiler Runtime (MCR). The MCR facilitates the execution of code calling Application Programming Interfaces (API) functions from both base MATLAB and MATLAB toolboxes. In a Linux environment, a sizable number of third-party runtime dependencies (i.e. shared libraries) are necessary. Unfortunately, to the MTLAB community's knowledge, these dependencies are not documented, leaving system administrators and/or end-users to find/install the necessary libraries either as runtime errors resulting from them missing or by inspecting the header information of Executable and Linkable Format (ELF) libraries of the MCR to determine which ones are missing from the system. To address various shortcomings, Docker Images based on Community Enterprise Operating System (CentOS) 7, a derivative of Redhat Enterprise Linux (RHEL) 7, containing recent (2015-2017) MCR releases and their dependencies were created. These images, along with a provided sample Docker Compose YAML Script, can be used to create a simulated computing cluster where MATLAB Compiler created binaries can be executed using a sample Slurm Workload Manager script.", + "laborHours": 45.6, + "languages": [ + "Bash 4.x, Docker 17.09" + ], + "name": "MCR Container Tools", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/mcr-container-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MDBEngine_v._1.0.json b/agency-indexes/DoE/MDBEngine_v._1.0.json new file mode 100644 index 00000000..6ac1c40d --- /dev/null +++ b/agency-indexes/DoE/MDBEngine_v._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2021-02-22" + }, + "description": "MDBEngine is a class library that provides Microsoft Access (.mdb) database functionality to applications that require complex data entry. Example functionality supports undo/redo, data verification and warnings, referential integrity checks, change history tracking, and other capabilities to simplify the task of using a database in an application. SAND2019-9689 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Visual Basic .NET" + ], + "name": "MDBEngine v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MEAM_interatomic_force_calculation_subroutine_for_LAMMPS.json b/agency-indexes/DoE/MEAM_interatomic_force_calculation_subroutine_for_LAMMPS.json new file mode 100644 index 00000000..fc57a1a4 --- /dev/null +++ b/agency-indexes/DoE/MEAM_interatomic_force_calculation_subroutine_for_LAMMPS.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Interatomic force and energy calculation subroutine tobe used with the molecular dynamics simulation code LAMMPS (Ref a.). The code evaluates the total energy and atomic forces (energy gradient) according to cubic spine-based variant (Ref b.) of the Modified Embedded Atom Method (MEAM).", + "homepageURL": "http://lammps.sandia.gov/download.html", + "laborHours": 0.0, + "name": "MEAM interatomic force calculation subroutine for LAMMPS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://lammps.sandia.gov/download.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MEASUR_-_Manufacturing_Energy_Assessment_Software_for_Utility_Reduction.json b/agency-indexes/DoE/MEASUR_-_Manufacturing_Energy_Assessment_Software_for_Utility_Reduction.json new file mode 100644 index 00000000..3c6ae3b3 --- /dev/null +++ b/agency-indexes/DoE/MEASUR_-_Manufacturing_Energy_Assessment_Software_for_Utility_Reduction.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "accawigk@ornl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-03-22" + }, + "description": "MEASUR your energy savings with the free DOE MEASUR software The Department of Energy (DOE), with Oak Ridge National Laboratory (ORNL), released version 1.0 of their energy efficiency software tool MEASUR (Manufacturing Energy Assessment Software for Utility Reduction). MEASUR has been available for several years as a beta version, being tested by industry experts and real users, and will continue to be updated and improved in the coming years. It is an integrated suite of tools to aid manufacturers in improving the efficiency of energy systems and equipment within a plant, including motors, pumps, fans, process heating, steam, and compressed air. Additionally, there are modules for wastewater energy analysis and to help perform energy treasure hunts. Several calculators are also included, allowing users to independently perform smaller calculations and analyses (such as estimating pump head, performing a fan traverse analysis, estimating waste heat recovery potential, and cataloging compressed air leaks). The MEASUR modules are based on previous DOE software tools that have been used by industry since the early 2000s (such as MotorMaster, AirMaster+, PSAT, PHAST, and FSAT). The original tools only ran on Windows operating systems, and by Windows 10, most of them were inoperable. DOE started their energy efficiency software tool revitalization effort in 2016, first with PSAT (for pumps), then began to integrate the other tools and expand their functionality and utility. The new MEASUR suite provides an extensively more user-friendly, modern, and versatile set of tools. All the assessment modules and most of the calculators have several visual components and graphs and detailed help text for every user input. To help reach international users, the tool utilizes Google translate and users can easily change unit systems, even converting existing user inputs if desired. The assessment files can be organized within the internal file system and easily shared to other users, regardless of their operating system. The entire suite is free, open-source, and can be downloaded on Windows, Mac, or Linux operating systems.", + "laborHours": 0.0, + "languages": [ + "TypeScript", + "CSS", + "HTML", + "Node.js", + "Angular8", + "Electron" + ], + "name": "MEASUR - Manufacturing Energy Assessment Software for Utility Reduction", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-AMO/AMO-Tools-Desktop/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-AMO/AMO-Tools-Desktop", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MEASUR_Tools_Suite.json b/agency-indexes/DoE/MEASUR_Tools_Suite.json new file mode 100644 index 00000000..7f2b4cb0 --- /dev/null +++ b/agency-indexes/DoE/MEASUR_Tools_Suite.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "accawigk@ornl.gov" + }, + "date": { + "created": "2017-12-21", + "metadataLastUpdated": "2025-02-10" + }, + "description": "MEASUR-Tools-Suite is an energy efficiency calculation library in C++ with WebAssembly (WASM) for the Department of Energy Advanced Manufacturing and Materials Technologies Office and the Industrial Efficiency & Decarbonization Office (DOE AMMTO IEDO) Desktop, also known as MEASUR.", + "laborHours": 165695.2, + "languages": [ + "C++" + ], + "name": "MEASUR Tools Suite", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-AMO/MEASUR-Tools-Suite/blob/develop/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-AMO/MEASUR-Tools-Suite", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.8" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MEGAHIT.json b/agency-indexes/DoE/MEGAHIT.json new file mode 100644 index 00000000..d48d4460 --- /dev/null +++ b/agency-indexes/DoE/MEGAHIT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "KBase module for running the MEGAHIT assembler.", + "laborHours": 1246.4, + "languages": [], + "name": "MEGAHIT", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/kb_megahit", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MEKED_Fit.json b/agency-indexes/DoE/MEKED_Fit.json new file mode 100644 index 00000000..61c5fdee --- /dev/null +++ b/agency-indexes/DoE/MEKED_Fit.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "obriense@ornl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "Determine uranium and plutonium concentrations of solutions using K-edge densitometry. Returns estimates, including the uncertainty, for the mass densities of U, Pu, Np, Am, Bi, and the matrix. GUI that allows users to select high resolution gamma spectrum files of measurements of vials of solutions containing U/Pu. These spectra are fit to find to find k-edge and x-ray fluorescence peaks. The user can adjust and set fit variables, such as vial size, spectrum parameters, detector specifications, and attenuation coefficients. Technique is an accurate and rapid assay technique commonly used in nuclear fuel reprocessing facilities. The measurement is a typical international safeguards tool for accountancy of U and Pu for dissolved product solutions.", + "laborHours": 0.0, + "languages": [ + "Fortran", + "Visual Basic" + ], + "name": "MEKED Fit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/meked/HybridKedge/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/meked/HybridKedge", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MELCOR.json b/agency-indexes/DoE/MELCOR.json new file mode 100644 index 00000000..c1bfa2fc --- /dev/null +++ b/agency-indexes/DoE/MELCOR.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2018-09-07" + }, + "description": "MELCOR is a severe accident code developed at Sandia National Laboratories for the US Nuclear Regulatory Commission. It is an integral code with models describing the important physics that come into play during a severe accident. Such physics includes, but is not limited to, the heat-up of reactor core components, thermal hydraulics, oxidation of materials, core degradation, release of fission products from components and the transport of those fission products and other important aerosols through a reactor system, molten core/concrete interactions, and modeling of reactor safety systems. MELCOR modeling is general and flexible, using a \u201ccontrol volume\u201d approach to describe the plant system which has also allowed it to successfully model spent fuel pools.", + "homepageURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "MELCOR", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrc.gov/about-nrc/regulatory/research/obtainingcodes.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MEMPHIS__Mesoscle_Multiphysics_Phase_Field_Simulator_v.0.json b/agency-indexes/DoE/MEMPHIS__Mesoscle_Multiphysics_Phase_Field_Simulator_v.0.json new file mode 100644 index 00000000..ca0df205 --- /dev/null +++ b/agency-indexes/DoE/MEMPHIS__Mesoscle_Multiphysics_Phase_Field_Simulator_v.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-19" + }, + "description": "SAND2024-01427O\nMesoscale Multiphysics Phase Field Simulator (MEMPHIS) is used for solving interfacial problems and can be applied to many evolutionary problems. Some examples are solidification dynamics, viscous fingering, fracture mechanics, hydrogen embrittlement, vesicle dynamics, electro-mechanical degradation of batteries, aging of microstructures, and segregation. MEMPHIS is written in Fortran 90 in a modular fashion, where model and numerical solvers are decoupled from one another. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "fortran 90" + ], + "name": "MEMPHIS (Mesoscle Multiphysics Phase Field Simulator v.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/METABENCH.json b/agency-indexes/DoE/METABENCH.json new file mode 100644 index 00000000..7e4e3979 --- /dev/null +++ b/agency-indexes/DoE/METABENCH.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-29" + }, + "description": "Software to test metadata performance of file systems and devices. A unique characteristic of this benchmark is its ability to be run in parallel.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "METABENCH", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/METRICS_FOR_INTERCOMPARISON_OF_REMAPPING_ALGORITHMS__MIRA_.json b/agency-indexes/DoE/METRICS_FOR_INTERCOMPARISON_OF_REMAPPING_ALGORITHMS__MIRA_.json new file mode 100644 index 00000000..e026ae4a --- /dev/null +++ b/agency-indexes/DoE/METRICS_FOR_INTERCOMPARISON_OF_REMAPPING_ALGORITHMS__MIRA_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "The MIRA project comprises of a set of Python drivers that enable rigorous intercomparison of remapping algorithms by providing the infrastructure for computing the numerical metrics of interest for ESM. This work is funded by the SciDAC Coupling Approaches for Next-Generation Architectures (CANGA) project.", + "laborHours": 0.0, + "languages": [], + "name": "METRICS FOR INTERCOMPARISON OF REMAPPING ALGORITHMS (MIRA)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CANGA/MIRA-Datasets", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MEUMAPPS__C++_Version_.json b/agency-indexes/DoE/MEUMAPPS__C++_Version_.json new file mode 100644 index 00000000..716cd930 --- /dev/null +++ b/agency-indexes/DoE/MEUMAPPS__C++_Version_.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "dewittsj@ornl.gov" + }, + "date": { + "created": "2022-01-13", + "metadataLastUpdated": "2022-01-14" + }, + "description": "Many materials, metal alloys in particular, have features on the on micrometer or nanometer scale that have a large impact on the properties of the material. These features are known as the microstructure of the material. Understanding why and how the microstructure forms in a material is of fundamental scientific interest as well as of significant technological interest. The capability to predict microstructure evolution in a material allows the intentional design of microstructures and hence the intentional design of material properties. The phase-field method is one of the leading methods for predicting microstructure evolution. One of the most significant problems for phase-field models is their computational expense. Even limited phase-field simulations can easily require thousands of CPU core-hours to complete, which significantly limits their use. This code provides both a general framework for creating scalable, GPU-accelerated phase-field model applications as well as several applications themselves. The code is capable of using hundreds of GPUs efficiently, which greatly reduces the time required to perform simulations. The code is written with an emphasis on performance portability, that is the ability for the code to run efficiently on a number of different computing architectures without modification of the source code. The performance portability of this code is primarily enabled through the use of two libraries, Kokkos (performance portable data structures and execution patterns) and heFFTe (performance portable distributed 3D fast Fourier transforms). The code consists of a core library, applications, and tests. The core library includes shared functionality between applications. This includes interfaces with fast Fourier transform (FFT) libraries such as heFFTe, data structures based on Kokkos, file input and output capabilities, and a solver for infinitesimal strain mechanical equilibrium problems. Five applications are included in the code. The flagship application is the MEUMAPPS-SS application, which implements the Kim-Kim-Suzuki phase-field model for precipitation for an arbitrary number of phases and components in a metal alloy. Five simpler applications are also included that solve the Eshelby inclusion problem, Allen-Cahn equation, the coupled Allen-Cahn and diffusion equations, and the Cahn-Hilliard equation. The code includes two applications to solve the Cahn-Hilliard equation, one with constant-step-size first-order time integration and the second with adaptive high-order time integration.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "MEUMAPPS (C++ Version)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/meumapps/meumapps/-/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/meumapps/meumapps", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MEUMAPPS__Microstructure_Evolution_Using_Massively_Parallel_Phase-field_Simulations_.json b/agency-indexes/DoE/MEUMAPPS__Microstructure_Evolution_Using_Massively_Parallel_Phase-field_Simulations_.json new file mode 100644 index 00000000..f21ab1b6 --- /dev/null +++ b/agency-indexes/DoE/MEUMAPPS__Microstructure_Evolution_Using_Massively_Parallel_Phase-field_Simulations_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The software \u201cMEUMAPPS\u201d is a h high-performance computing code used to simulate microstructure evolution associated with diffusional solid-state transformations in structural alloys. Understanding microstructure evolution during thermo-mechanical processing of structural alloys is the first step towards designing and processing alloys for specific applications by meeting property requirements demanded by the application. In this instance, the code is an important component in predicting processing-structure linkages during additive manufacturing of structural alloys as a function of processing parameters and alloy composition used in an additive manufacturing process. The code provides a detailed three-dimensional distribution of different types of phases / constituents and their morphologies, as well as the compositions of these phases that make up the microstructure. The microstructure is simulated by solving the governing partial differential equations using a Fourier Spectral Method.", + "laborHours": 851.2, + "languages": [ + "Fortran/PGI/19.9" + ], + "name": "MEUMAPPS (Microstructure Evolution Using Massively Parallel Phase-field Simulations)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/meumapps_ss", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MEXRF.json b/agency-indexes/DoE/MEXRF.json new file mode 100644 index 00000000..2adf74aa --- /dev/null +++ b/agency-indexes/DoE/MEXRF.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "obriense@ornl.gov" + }, + "date": { + "created": "2022-03-04", + "metadataLastUpdated": "2022-03-04" + }, + "description": "Uses spectral fitting of X-Ray fluorescence to obtain the density (g/L) of transuranics.", + "laborHours": 0.0, + "languages": [ + "Visual Basic" + ], + "name": "MEXRF", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/multTMU/MEXRF", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MF-LBM-nanopore.json b/agency-indexes/DoE/MF-LBM-nanopore.json new file mode 100644 index 00000000..3dbc508f --- /dev/null +++ b/agency-indexes/DoE/MF-LBM-nanopore.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "MF-LBM-nanopore is a high-performance lattice Boltzmann code for direct numerical simulation of flow in nano-porous media with confinement effects. The main features of the code include: 1) implemented with adsorption and slip modules that enable simulation of flow in nano-porous media with confinement effects; 2) extensively optimized for modern SIMD/SIMT processors/co-processors, such as GPU; 3) based on MPI-OpenACC/OpenMP hybrid programing model that enables high portability. The main application of the code is in modeling shale gas flow.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "MF-LBM-nanopore", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MF-LBM.json b/agency-indexes/DoE/MF-LBM.json new file mode 100644 index 00000000..0d4e0988 --- /dev/null +++ b/agency-indexes/DoE/MF-LBM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "MF-LBM is a high-performance lattice Boltzmann code for direct numerical simulation of three-dimensional multiphase flow in porous media. The main features of the code include: 1) implemented with advanced multiphase and wetting models that enable simulation of supercritical CO2 (scCO2) and brine displacement in real rock geometries; 2) extensively optimized for modern SIMD/SIMT processors/co-processors, such as GPU; 3) based on MPI-OpenACC/OpenMP hybrid programing model that enables high portability; 4) overlapped communication and computation that enables high scalability; 5) designed for flow simulations on digital rock images or complex microfluidic devices.", + "laborHours": 0.0, + "languages": [], + "name": "MF-LBM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MF-LBM", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MFDn_Kernels_v1.0.json b/agency-indexes/DoE/MFDn_Kernels_v1.0.json new file mode 100644 index 00000000..235579b9 --- /dev/null +++ b/agency-indexes/DoE/MFDn_Kernels_v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-21", + "metadataLastUpdated": "2021-10-21" + }, + "description": "MFDn kernels is a collection of small subroutines designed to capture essential characteristics of the Many-Fermion Dynamics---nuclear (MFDn) application (DOI: 10.1016/j.procs.2010.04.012). It features multiple implementations with different programming models/languages of simplified routines analogous to those found in the full application. The main use is to explore the performance and utility of different programming models, languages and compilers.", + "laborHours": 0.0, + "languages": [], + "name": "MFDn Kernels v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/nersc-proxies/mfdn-kernels", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MFEM.json b/agency-indexes/DoE/MFEM.json new file mode 100644 index 00000000..10778bde --- /dev/null +++ b/agency-indexes/DoE/MFEM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2019-07-11" + }, + "description": "Mirror of MFEM - a lightweight, general, scalable C++ library for finite element methods. MFEM is a modular parallel C++ library for finite element methods. Its goal is to enable the research and development of scalable finite element discretization and solver algorithms through general finite element abstractions, accurate and flexible visualization, and tight integration with the hypre library.\n", + "homepageURL": "https://mfem.org", + "laborHours": 0.0, + "languages": [], + "name": "MFEM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://mfem.org", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MGLToolsUtil.json b/agency-indexes/DoE/MGLToolsUtil.json new file mode 100644 index 00000000..6fc7df42 --- /dev/null +++ b/agency-indexes/DoE/MGLToolsUtil.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "This is the repository for \"MGLToolsUtil\" developed by KBase. This is a KBase module generated by the KBase Software Development Kit (SDK).", + "laborHours": 623.2, + "languages": [], + "name": "MGLToolsUtil", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/MGLToolsUtil", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MHKiT__Marine_and_Hydrokinetic_Toolkit__-_MATLAB.json b/agency-indexes/DoE/MHKiT__Marine_and_Hydrokinetic_Toolkit__-_MATLAB.json new file mode 100644 index 00000000..1df94ce1 --- /dev/null +++ b/agency-indexes/DoE/MHKiT__Marine_and_Hydrokinetic_Toolkit__-_MATLAB.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "chitra.sivaraman@pnnl.gov" + }, + "date": { + "created": "2020-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The MHKiT Code Hub is a collection of open-source marine renewable energy (MRE) software. The MHKiT code, developed in Python and MATLAB, includes modules for ingesting, quality controlling, processing, visualizing, and managing data. MHKiT-Python and MHKiT-MATLAB provide robust and verified functions in both Python and MATLAB that are needed by the MRE community to standardize data processing. Calculations and visualizations adhere to IEC technical specifications and other guidelines. Current functionality includes power performance, power quality, mechanical loads, resource tools, and data quality control for wave, tidal, and river applications.", + "laborHours": 579864.8, + "languages": [ + "MATLAB" + ], + "name": "MHKiT (Marine and Hydrokinetic Toolkit) - MATLAB", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MHKiT-Software/MHKiT-MATLAB", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MHKiT__Marine_and_Hydrokinetic_Toolkit__-_Python.json b/agency-indexes/DoE/MHKiT__Marine_and_Hydrokinetic_Toolkit__-_Python.json new file mode 100644 index 00000000..b863083b --- /dev/null +++ b/agency-indexes/DoE/MHKiT__Marine_and_Hydrokinetic_Toolkit__-_Python.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "chitra.sivaraman@pnnl.gov" + }, + "date": { + "created": "2020-01-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The MHKiT Code Hub is a collection of open-source marine renewable energy (MRE) software. The MHKiT code, developed in Python and MATLAB, includes modules for ingesting, quality controlling, processing, visualizing, and managing data. MHKiT-Python and MHKiT-MATLAB provide robust and verified functions in both Python and MATLAB that are needed by the MRE community to standardize data processing. Calculations and visualizations adhere to IEC technical specifications and other guidelines. Current functionality includes power performance, power quality, mechanical loads, resource tools, and data quality control for wave, tidal, and river applications.", + "laborHours": 593985.6, + "languages": [ + "Python" + ], + "name": "MHKiT (Marine and Hydrokinetic Toolkit) - Python", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MHKiT-Software/MHKiT-Python", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/MHKiT\342\204\242_-Python__Marine_Hydrokinetic_Toolkit__[SWR-20-42].json" "b/agency-indexes/DoE/MHKiT\342\204\242_-Python__Marine_Hydrokinetic_Toolkit__[SWR-20-42].json" new file mode 100644 index 00000000..7d45d000 --- /dev/null +++ "b/agency-indexes/DoE/MHKiT\342\204\242_-Python__Marine_Hydrokinetic_Toolkit__[SWR-20-42].json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-07-13", + "metadataLastUpdated": "2023-11-02" + }, + "description": "MHKiT\u2122 -Python is a Python package designed for marine renewable energy applications to assist in data processing and visualization. The software package include functionality for:\n\n-Data processing\n-Data visualization\n-Data quality control\n-Resource assessment\n-Device performance\n-Device loads", + "laborHours": 593985.6, + "languages": [ + "Python" + ], + "name": "MHKiT\u2122 -Python (Marine Hydrokinetic Toolkit) [SWR-20-42]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MHKiT-Software/MHKiT-Python", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/MHKit\342\204\242_-MATLAB__Marine_and_Hydrokinetic_Toolkit__[SWR-20-42].json" "b/agency-indexes/DoE/MHKit\342\204\242_-MATLAB__Marine_and_Hydrokinetic_Toolkit__[SWR-20-42].json" new file mode 100644 index 00000000..13e26c71 --- /dev/null +++ "b/agency-indexes/DoE/MHKit\342\204\242_-MATLAB__Marine_and_Hydrokinetic_Toolkit__[SWR-20-42].json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-07-13", + "metadataLastUpdated": "2023-11-02" + }, + "description": "MHKiT\u2122 -MATLAB is a MATLAB package designed for marine renewable energy applications to assist in data processing and visualization. The software package include functionality for: -Quality control analysis -Wave resource and wave performance -River resource and device -Tidal resource and device -Data visualization -Mechanical loads analysis -Power quality assessments", + "laborHours": 579864.8, + "languages": [ + "MATLAB" + ], + "name": "MHKit\u2122 -MATLAB (Marine and Hydrokinetic Toolkit) [SWR-20-42]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MHKiT-Software/MHKiT-MATLAB", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MIAMI-NW.json b/agency-indexes/DoE/MIAMI-NW.json new file mode 100644 index 00000000..32619598 --- /dev/null +++ b/agency-indexes/DoE/MIAMI-NW.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-14", + "metadataLastUpdated": "2020-12-14" + }, + "description": "MIAMI was designed for Pin 2. Unfortunately, Pin 2 is deprecated and no longer runs on modern versions of Linux. For example, it does not work on RHEL 7.x. In particular, Pin 2 requires a C++ ABI <= GCC 4.4.", + "laborHours": 0.0, + "languages": [], + "name": "MIAMI-NW", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab-hub/palm/miami-nw", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MIB,_the_MPI_I_O_Benchmark.json b/agency-indexes/DoE/MIB,_the_MPI_I_O_Benchmark.json new file mode 100644 index 00000000..40a0982e --- /dev/null +++ b/agency-indexes/DoE/MIB,_the_MPI_I_O_Benchmark.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "An MPI-based test for benchmarking parallel I/O beowulf-style clusters.", + "laborHours": 2416.8, + "name": "MIB, the MPI I/O Benchmark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mib", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MIDAS-DC-AC_Tool:_Fully_Automating_the_Acquisition_of_AC_Power_Flow_Solution__MIDAS-DC2AC_.json b/agency-indexes/DoE/MIDAS-DC-AC_Tool:_Fully_Automating_the_Acquisition_of_AC_Power_Flow_Solution__MIDAS-DC2AC_.json new file mode 100644 index 00000000..ee0b54d7 --- /dev/null +++ b/agency-indexes/DoE/MIDAS-DC-AC_Tool:_Fully_Automating_the_Acquisition_of_AC_Power_Flow_Solution__MIDAS-DC2AC_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-04-25", + "metadataLastUpdated": "2022-05-12" + }, + "description": "MIDAS DC2AC is an automated tool for achieving a converged AC power flow solution from any dispatch, e.g., determined using DC power flow model based optimal power flow. The entire process is free of human interference. It is usually encountered in practice that, even with a DC power flow solution, acquiring the solved AC power flow solution, if exists, sometimes could be a challenging task, especially during the planning stage. It is also difficult to distinguish the unsolvable cases from diverging iterations. Manual adjustments to approach the desired power flow condition has been largely relied on in the past using lots of engineering heuristics. This tool provides a systematic way to first achieve a solvable AC power flow case by modifying the power flow condition, and then try to track the AC power flow solution while gradually removing the adopted changes. If all adopted changes can be completely removed, then the original AC power flow solution is obtained. Otherwise, insights for actionable controls are derived to help operation and planning. Currently, this tool has been implemented in Python using SIEMENS PTI PSS/E as power flow solver, where only adjusting generator terminal voltage set point is considered as an available means to try to turn an unsolved power flow to a solved one. In future, more means should be considered, including the operation of tap-changing transformers, switched shunts and redispatch of active power.", + "laborHours": 0.0, + "languages": [ + "PYTHON" + ], + "name": "MIDAS-DC-AC Tool: Fully Automating the Acquisition of AC Power Flow Solution (MIDAS-DC2AC)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DC2AC", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MIJAMP.json b/agency-indexes/DoE/MIJAMP.json new file mode 100644 index 00000000..55b475b4 --- /dev/null +++ b/agency-indexes/DoE/MIJAMP.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "alexanderwg@ornl.gov" + }, + "date": { + "created": "2025-01-17", + "metadataLastUpdated": "2025-01-23" + }, + "description": "Here, we develop MIJAMP (MIJAMP Is Just A MethylBED Parser), a software package that was developed to discover methylated motifs from the output of ONT\u2019s Modkit or other data in the methylBED format. MIJAMP employs a human-driven refinement strategy that empirically validates all motifs against genome-wide methylation data, thus eliminating false, under-, or overexplained motifs. MIJAMP can also report methylation data on a specific, user-defined motif.", + "laborHours": 334.4, + "languages": [ + "Python" + ], + "name": "MIJAMP", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/alexander-public/mijamp", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MIMOSAS.json b/agency-indexes/DoE/MIMOSAS.json new file mode 100644 index 00000000..ae300976 --- /dev/null +++ b/agency-indexes/DoE/MIMOSAS.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "bethany@lbl.gov" + }, + "date": { + "created": "2020-03-14", + "metadataLastUpdated": "2020-03-14" + }, + "description": "A supervised machine learning pipeline, MIMOSAS (Multisource Input Model Output Security Analysis Suite), has been developed for classification of multimodal data to inform nuclear security and proliferation detection scenarios. MIMOSAS provides an end-to-end data processing workflow, from data ingestion and pre-processing to model training and test set classification. The pipeline is specified via an input deck, making workflow customization effortless, and the framework is modular allowing for the easy addition of new learning algorithms. In the current build, the user selects from decision tree, random forest, and feed-forward neural network classifiers to train customizable models with built-in cross validation methods for hyperparameter optimization. Trained model outputs are stored with the associated metadata for rapid deployment. These can be applied in supervised classification to assess previously unseen data or for further training as new observations are added to the existing data set. MIMOSAS provides the capability to fuse a wide range of data sources (e.g., radiation, environmental, acoustic, seismic, imagery, etc.) to make, confirm, and correlate machine learning predictions for nuclear security applications.", + "laborHours": 5198.4, + "languages": [ + "Python" + ], + "name": "MIMOSAS", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://complexity.berkeley.edu/wp-content/uploads/2019/09/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nonproliferation/mimosas", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MIPLearn.json b/agency-indexes/DoE/MIPLearn.json new file mode 100644 index 00000000..b438ed6e --- /dev/null +++ b/agency-indexes/DoE/MIPLearn.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-05-28", + "metadataLastUpdated": "2021-05-18" + }, + "description": "MIPLearn is an extensible framework for Learning-Enhanced Mixed-Integer Optimization, an approach targeted at discrete optimization problems that need to be repeatedly solved with only minor changes to input data. The package uses Machine Learning (ML) to automatically identify patterns in previously solved instances of the problem, or in the solution process itself, and produces hints that can guide a conventional MIP solver towards the optimal solution faster.", + "laborHours": 3024.8, + "languages": [], + "name": "MIPLearn", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-CEEESA/MIPLearn", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MIQS_v0.6.json b/agency-indexes/DoE/MIQS_v0.6.json new file mode 100644 index 00000000..0f4ecff5 --- /dev/null +++ b/agency-indexes/DoE/MIQS_v0.6.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-23", + "metadataLastUpdated": "2021-03-23" + }, + "description": "In this research, we propose a novel Metadata Indexing and Querying for Self-describing formats (MIQS), which removes the external DBMS and utilizes in-memory index to achieve efficient metadata searching. MIQS follows the self-contained data management paradigm and provides portable and schema-free metadata indexing and querying functionalities for self-describing file formats. We have evaluated MIQS with the state-of-the-art MongoDB-based metadata indexing solution. MIQS achieved up to 99% time reduction in index construction and up to 172,000X search performance improvement with up to 75% reduction in memory footprint.", + "laborHours": 0.0, + "languages": [], + "name": "MIQS v0.6", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/miqs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MISO.json b/agency-indexes/DoE/MISO.json new file mode 100644 index 00000000..e01de43e --- /dev/null +++ b/agency-indexes/DoE/MISO.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-09", + "metadataLastUpdated": "2022-09-12" + }, + "description": "Midcontinent ISO market data access.", + "laborHours": 0.0, + "languages": [], + "name": "MISO", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/miso", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MIST_paper.json b/agency-indexes/DoE/MIST_paper.json new file mode 100644 index 00000000..e86c7bcb --- /dev/null +++ b/agency-indexes/DoE/MIST_paper.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-01-24", + "metadataLastUpdated": "2025-01-24" + }, + "description": "Code to reproduce results from and implement functionality described in \"A Bayesian error model for synthesis and sequencing of oligonucleotides\", Marrs, FW, Gratz, D, and Erkkila, TH.", + "laborHours": 668.8, + "languages": [], + "name": "MIST_paper", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MIST_paper", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ML-PSA.json b/agency-indexes/DoE/ML-PSA.json new file mode 100644 index 00000000..65ad30d2 --- /dev/null +++ b/agency-indexes/DoE/ML-PSA.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gureckywl@ornl.gov" + }, + "date": { + "created": "2022-01-10", + "metadataLastUpdated": "2024-01-24" + }, + "description": "The computer code uses a parallel simulated annealing framework with embedded machine learning components to solve multi-constrained optimization problems. The software automatically balances the execution of low and high fidelity physics models within the optimization procedure. The low fidelity model is used to rapidly explore the design space while the high fidelity physics model is executed sparingly to account for complex design constraints that are not resolved by the quickly executing low fidelity model.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ML-PSA", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/ml-psa/ml-psa", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ML4Chem:_Machine_Learning_for_Chemistry_and_Materials_v0.0.1.json b/agency-indexes/DoE/ML4Chem:_Machine_Learning_for_Chemistry_and_Materials_v0.0.1.json new file mode 100644 index 00000000..18543458 --- /dev/null +++ b/agency-indexes/DoE/ML4Chem:_Machine_Learning_for_Chemistry_and_Materials_v0.0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-08-01", + "metadataLastUpdated": "2019-10-24" + }, + "description": "ML4Chem is a free, and open-source machine learning package for chemistry and materials sciences written in Python. It allows scientists to focus on applying the most commonly used machine learning models in chemistry and materials sciences with minimum effort.", + "laborHours": 2675.2, + "languages": [], + "name": "ML4Chem: Machine Learning for Chemistry and Materials v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/muammar/ml4chem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ML4PD__Machine_Learning_for_High_Throughput_Process_Design__[SWR-22-62].json b/agency-indexes/DoE/ML4PD__Machine_Learning_for_High_Throughput_Process_Design__[SWR-22-62].json new file mode 100644 index 00000000..0fc2a37c --- /dev/null +++ b/agency-indexes/DoE/ML4PD__Machine_Learning_for_High_Throughput_Process_Design__[SWR-22-62].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-06-21", + "metadataLastUpdated": "2023-04-24" + }, + "description": "ML4PD is a code base developed to use machine learning(ML)-based modular process units that can be combined to create whole process models. The package is developed within python and leverages tensorflow for the ML components.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ML4PD (Machine Learning for High Throughput Process Design) [SWR-22-62]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ml4pd", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MLClouds_[SWR-24-24].json b/agency-indexes/DoE/MLClouds_[SWR-24-24].json new file mode 100644 index 00000000..806799e6 --- /dev/null +++ b/agency-indexes/DoE/MLClouds_[SWR-24-24].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-24", + "metadataLastUpdated": "2024-04-25" + }, + "description": "The National Solar Radiation Database (NSRDB) is NREL\u2019s flagship solar data resource. With over 20 years of high-resolution surface irradiance data covering most of the western hemisphere, the NSRDB is a crucial public data asset. A fundamental input to accurate surface irradiance in the NSRDB is high quality cloud property data. Cloud properties are used in radiative transfer calculations and are sourced from satellite imagery. Improving the accuracy of cloud property inputs is a tractable method for improving the accuracy of the irradiance data in the NSRDB. For example, in July of 2018, an average location in the Continental United States is missing cloud property data for nearly one quarter of all daylight cloudy timesteps. This project aims to improve the cloud data inputs to the NSRDB by using machine learning techniques to exploit the NSRDB\u2019s massive data resources. More accurate cloud property input data will yield more accurate surface irradiance data in the NSRDB, providing direct benefit to researchers at NREL and to public data users everywhere.", + "laborHours": 1626.4, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "MLClouds [SWR-24-24]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mlclouds", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MLEC-Sim:_A_Simulator_for_Evaluating_Multi-Level_Erasure_Coding.json b/agency-indexes/DoE/MLEC-Sim:_A_Simulator_for_Evaluating_Multi-Level_Erasure_Coding.json new file mode 100644 index 00000000..22a090d5 --- /dev/null +++ b/agency-indexes/DoE/MLEC-Sim:_A_Simulator_for_Evaluating_Multi-Level_Erasure_Coding.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "georgea@ornl.gov" + }, + "date": { + "created": "2024-04-03", + "metadataLastUpdated": "2024-04-18" + }, + "description": "We present MLEC-Sim, a sophisticated simulator for Multi-Level Erasure Coding (MLEC), developed in approximately 13 KLOC. The simulator is engineered to analyze the impact of various system configurations and erasure coding policies on system durability and network overhead. It supports a comprehensive range of parameters including disk capacity, disk I/O bandwidth, failure rates, network bandwidth, and system scale, accommodating various erasure coding approaches such as Single-Level Erasure Coding (SLEC), Multi-Level Erasure Coding (MLEC), and Local Reconstruction Codes (LRC).\n\nMLEC-Sim provides support for multiple chunk placement policies, including clustered parity and declustered parity, and encompasses a variety of repair methods like Repair-ALL, Repair-FCO, Repair-HYB, and Repair-MIN. It is capable of simulating disk failures through a variety of means, including distribution-based or trace-based mechanisms, and can handle complex multi-level (de)clustered placements and repair processes.\n\nA key feature of MLEC-Sim is its adoption of the splitting simulation method for evaluating system durabilities at extremely high levels, which are challenging to assess with traditional simulation approaches. This feature allows for a detailed evaluation of system resilience under a range of conditions, aiding in the selection of appropriate erasure coding solutions for enhancing system durability.\n\nMLEC-Sim contributes to the field of data storage and reliability by providing a tool for the detailed evaluation of the durability and efficiency of erasure coding configurations, intended for use by researchers and practitioners in the design and optimization of storage systems.", + "laborHours": 15078.4, + "languages": [ + "Python" + ], + "name": "MLEC-Sim: A Simulator for Evaluating Multi-Level Erasure Coding", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ucare-uchicago/mlec-sim/blob/main/LICENSE.rtf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ucare-uchicago/mlec-sim", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MLExchange_v1.json b/agency-indexes/DoE/MLExchange_v1.json new file mode 100644 index 00000000..c7f96118 --- /dev/null +++ b/agency-indexes/DoE/MLExchange_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-05" + }, + "description": "A Machine Learning Platform that connects beamline scientists and machine learning (ML) researchers so that the ML researchers can quickly distribute their ML models to beamline scientists, and beamline scientists can give feedback to help ML researchers improve their models.", + "laborHours": 0.0, + "languages": [], + "name": "MLExchange v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mlexchange/mlex", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MLUQ__Uncertainty_quantification_for_ML_closure_models__[SWR-24-36].json b/agency-indexes/DoE/MLUQ__Uncertainty_quantification_for_ML_closure_models__[SWR-24-36].json new file mode 100644 index 00000000..40e5727b --- /dev/null +++ b/agency-indexes/DoE/MLUQ__Uncertainty_quantification_for_ML_closure_models__[SWR-24-36].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-02-22", + "metadataLastUpdated": "2024-04-01" + }, + "description": "Data-based closure models are increasingly being used to replace physic-based closure models because of their flexibility and the growing availability of data. However, closure models are subject to uncertainty because of lack of data in parts of the input space (epistemic uncertainty) or because of noise in the data (aleatoric uncertainty). This software contains a toolbox for training bayesian neural nets that can estimate both uncertainties. A specific treatment is provided to ensure accuracy outside of the data distribution. A set of tools are provided to reduce the dimensionality of the uncertain parameter space, thereby enabling fast uncertainty propagation.", + "laborHours": 3328.8, + "languages": [ + "PureBasic", + "Jupyter", + "Python", + "Shell" + ], + "name": "MLUQ (Uncertainty quantification for ML closure models) [SWR-24-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mluq-prop", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ML_Pipeline__Machine_Learning_Pipeline__[SWR-22-35].json b/agency-indexes/DoE/ML_Pipeline__Machine_Learning_Pipeline__[SWR-22-35].json new file mode 100644 index 00000000..6777f24f --- /dev/null +++ b/agency-indexes/DoE/ML_Pipeline__Machine_Learning_Pipeline__[SWR-22-35].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-05-19", + "metadataLastUpdated": "2022-10-06" + }, + "description": "The Machine Learning Pipeline (ML Pipeline) allows the user to fit a model to predict a dependent variable, y, based on a feature set, X. ML Pipeline gives the ability to automatically generate features with its Feature Engineering function, automatically select the most important features with its Feature Selection function, fit the model with its Fit function, and evaluate the model with its Evaluate function. ML Pipeline's functionality can not only help the user predict values for the desired variable it also gives the user a better understanding of which features are important and how effective the model is. ML Pipeline accomplishes all this, while remaining simple to use and interpret.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "ML Pipeline (Machine Learning Pipeline) [SWR-22-35]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Machine-Learning-Pipeline", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ML_for_microbiomes.json b/agency-indexes/DoE/ML_for_microbiomes.json new file mode 100644 index 00000000..67407ad9 --- /dev/null +++ b/agency-indexes/DoE/ML_for_microbiomes.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-03" + }, + "description": "The software provides machine learning analysis and visualization to detect patterns in microbiome data, including topic modeling, probabilistic graphical modeling, conventional machine learning methods, and deep learning. The software is written in python and R, it uses some python and R libraries as well as big open-source libraries like sklearn, networkX, pytorch (python), pgmpy (python), and bnlearn (R). It also has a script to use for MALLET and DTM (open-source packages for topic modeling, written in Java).", + "laborHours": 0.0, + "languages": [], + "name": "ML for microbiomes", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ML-for-microbiomes", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MODAQ__Modular_Offshore_Data_Acquisition_System__[SWR-24-58].json b/agency-indexes/DoE/MODAQ__Modular_Offshore_Data_Acquisition_System__[SWR-24-58].json new file mode 100644 index 00000000..dcc458b5 --- /dev/null +++ b/agency-indexes/DoE/MODAQ__Modular_Offshore_Data_Acquisition_System__[SWR-24-58].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-04", + "metadataLastUpdated": "2024-04-04" + }, + "description": "The National Renewable Energy Laboratory (NREL) has developed a data acquisition system to support laboratory (component) and in-water validation and testing of Marine Renewable Energy (MRE) technologies. The Modular Ocean Data AcQuisition System (MODAQ) is a robust system built on industrial grade hardware that can acquire high-quality and summary data from many sensor and instrument types. MODAQ includes modules to perform real-time QC screening, system health monitoring, and send alerts. MODAQ is also part of a larger data management, processing, visualization, and archiving system.", + "laborHours": 16917.6, + "languages": [ + "HTML", + "LabVIEW", + "SaltStack", + "JavaScript" + ], + "name": "MODAQ (Modular Offshore Data Acquisition System) [SWR-24-58]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MODAQ", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MOFA_Software_for_the_COBRA_Toolbox.json b/agency-indexes/DoE/MOFA_Software_for_the_COBRA_Toolbox.json new file mode 100644 index 00000000..bb69a182 --- /dev/null +++ b/agency-indexes/DoE/MOFA_Software_for_the_COBRA_Toolbox.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "MOFA-COBRA is a software code for Matlab that performs Multi-Objective Flux Analysis (MOFA), a solving of linear programming problems. The leading software package for conducting different types of analyses using constrain-based models is the COBRA Toolbox for Matlab. MOFA-COBRA is an added tool for COBRA that solves multi-objective problems using a novel algorithm.", + "laborHours": 0.0, + "languages": [ + "Matlab (100%)" + ], + "name": "MOFA Software for the COBRA Toolbox", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/mofa-software-for-the-cobra-toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MONTE_CARLO_CROSS_SECTION_LOOKUP_KERNEL_FOR_THE_CEREBRAS_WSE-2_IN_CSL.json b/agency-indexes/DoE/MONTE_CARLO_CROSS_SECTION_LOOKUP_KERNEL_FOR_THE_CEREBRAS_WSE-2_IN_CSL.json new file mode 100644 index 00000000..4cdce9d3 --- /dev/null +++ b/agency-indexes/DoE/MONTE_CARLO_CROSS_SECTION_LOOKUP_KERNEL_FOR_THE_CEREBRAS_WSE-2_IN_CSL.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-12", + "metadataLastUpdated": "2024-03-19" + }, + "description": "This is a small kernel that was used to collect data for an upcoming paper. We would like to have the code be open source so that the reviewers (and then readers) of the paper can see the whole code, and can reproduce/verify our results. This is not a fully featured application, it cannot produce any useful simulation results, it just executes a small abstracted kernel using synthetic data. The purpose of the kernel is to understand the basic performance characteristics of an HPC kernel on novel AI accelerator architectures. The main kernel is written in the CSL coding language for use with the Cerebras WSE-2 AI accelerator. The kernel represented is the Monte Carlo cross section lookup kernel, which is a small kernel used by the Monte Carlo neutral particle transport algorithm. There is also a baseline kernel written in CUDA that we will include in the repository to form a basis for comparing the WSE-2 to GPU.", + "laborHours": 0.0, + "languages": [], + "name": "MONTE CARLO CROSS SECTION LOOKUP KERNEL FOR THE CEREBRAS WSE-2 IN CSL", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-science/mc_on_accelerators", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MOOSE-Python_Binder.json b/agency-indexes/DoE/MOOSE-Python_Binder.json new file mode 100644 index 00000000..eca0f54e --- /dev/null +++ b/agency-indexes/DoE/MOOSE-Python_Binder.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "greenquistit@ornl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-11-03" + }, + "description": "This code is a wrapper for Python code so that it can be accessed by MOOSE and the two can pass variables back and forth.\n\nSince this code was developed by ORNL, it must be independently approved before being added to the MOOSE repository.", + "laborHours": 1085021.6, + "languages": [ + "C++" + ], + "name": "MOOSE-Python Binder", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/moose", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPAS-Analysis.json b/agency-indexes/DoE/MPAS-Analysis.json new file mode 100644 index 00000000..52b7def9 --- /dev/null +++ b/agency-indexes/DoE/MPAS-Analysis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-07-26", + "metadataLastUpdated": "2018-08-03" + }, + "description": "MPAS-Analysis is a software package designed to process and analyze output data of the Model for Prediction Across Scales (MPAS) Ocean, Sea-Ice and Land-Ice model components. It is built primarily on the python language, with remapping of model unstructured-grid fields onto regular grids performed through the ESMF package, and with the computation of climatologies performed through the NCO package. The main purpose of MPAS-Analysis is to analyze the MPAS simulations in terms of ocean and ice metrics, in comparison with available observations, and therefore provide an accurate model evaluation and simulation assessment.", + "laborHours": 20489.6, + "languages": [], + "name": "MPAS-Analysis", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MPAS-Dev/MPAS-Analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPAS-Dev_MPAS-Model.json b/agency-indexes/DoE/MPAS-Dev_MPAS-Model.json new file mode 100644 index 00000000..28103103 --- /dev/null +++ b/agency-indexes/DoE/MPAS-Dev_MPAS-Model.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "sprice@lanl.gov" + }, + "date": { + "created": "2019-05-02", + "metadataLastUpdated": "2019-05-06" + }, + "description": "The Model for Prediction Across Scales (MPAS) is a collaborative project for developing atmosphere, ocean, and other earth-system simulation components for use in climate, regional climate, and weather studies. The primary development partners are the climate modeling group at Los Alamos National Laboratory (COSIM) and the National Center for Atmospheric Research. Both primary partners are responsible for the MPAS framework, operators, and tools common to the applications; LANL has primary responsibility for the ocean, sea ice, and land ice models, and NCAR has primary responsibility for the atmospheric model.", + "laborHours": 244279.2, + "languages": [ + "C++", + "Fortran" + ], + "name": "MPAS-Dev/MPAS-Model", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MPAS-Dev/MPAS-Model", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "6.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPC4CLR__Model-Predictive-Control-for-Critical-Load-Restoration-in-Power-Distribution-Systems__[SWR-22-24].json b/agency-indexes/DoE/MPC4CLR__Model-Predictive-Control-for-Critical-Load-Restoration-in-Power-Distribution-Systems__[SWR-22-24].json new file mode 100644 index 00000000..d625c8ca --- /dev/null +++ b/agency-indexes/DoE/MPC4CLR__Model-Predictive-Control-for-Critical-Load-Restoration-in-Power-Distribution-Systems__[SWR-22-24].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2023-07-27" + }, + "description": "Model predictive control (MPC) is a system or process control technique for making decisions under uncertainty via rolling look-ahead optimizations at each control step where only the current step decisions are applied, and the rest are discarded. In this work, we developed an MPC for a critical load restoration (CLR) in power distribution systems to recover system service (electricity delivery) following an extreme event-triggered substation outage. The method considers the problem of controlling distributed energy resources (DERs) of the distribution system with the objective of achieving maximum load pick up while satisfying distribution network flow and voltage constraints. A linearized optimal power flow (OPF) model is employed to represent the physics of the network. The problem formulation is augmented with a ramping (up) reserve product for the DERs to ensure improved and upward monotonic load restoration as time evolves. Simulation analysis and performance tests are performed using a modified IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage battery. The software is developed using various software packages in Julia and Python. The MPC model is implemented using the JuMP optimization language in Julia while the data analytics including renewable generation and load demand forecasts, running the MPC simulation and visualizations is performed in Python.", + "laborHours": 0.0, + "languages": [ + "Julia", + "Python" + ], + "name": "MPC4CLR (Model-Predictive-Control-for-Critical-Load-Restoration-in-Power-Distribution-Systems) [SWR-22-24]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mpc4clr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPContribs.json b/agency-indexes/DoE/MPContribs.json new file mode 100644 index 00000000..22f47e5f --- /dev/null +++ b/agency-indexes/DoE/MPContribs.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "phuck@lbl.gov" + }, + "date": { + "created": "2018-06-14", + "metadataLastUpdated": "2018-06-14" + }, + "description": "Since its start in 2011, Materials Project (MP, https://materialsproject.org/) has grown into a world-wide resource for a materials sciences community of more than 27,000 users who rely on the portal as a trusted source to accelerate their research. As a result, they wish to help with MP's efforts by contributing back, but also ask for support in sharing their experimental and computational datasets alongside MP's curated results. This provides the opportunity for researchers in both domains to validate calculations or measurements almost instantaneously and use the disseminated data for integrated materials studies.\n\nWith the public announcement of our general contribution framework, MPContribs, we present a sustainable solution for well-curated data management, organization and dissemination in the context of MP. The framework serves the purpose of collectively maintaining contributions to local and MP community databases as annotations to existing MP materials. It subsequently disseminates them through a generic interactive gateway powered by Jupyter notebooks or through custom project web apps enabled by the webtzite app kit.", + "laborHours": 7949.6, + "languages": [ + "JavaScript", + "Python" + ], + "name": "MPContribs", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/materialsproject/MPContribs", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPI.jl_Contribution.json b/agency-indexes/DoE/MPI.jl_Contribution.json new file mode 100644 index 00000000..5f9c30fb --- /dev/null +++ b/agency-indexes/DoE/MPI.jl_Contribution.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "The work done on the open source MPI.jl package was done in order to allow it to work with a streaming, in-situ Gaussian process. The addition was to add the capability for the Julia package to use the MPI non-blocking Barrier, Ibarrier. This involved addition of a small chunk of code to the existing package basically replicating the function for the existing blocking MPI barrier but adapted handle the MPI Ibarrier interface.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "MPI.jl Contribution", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPICH.json b/agency-indexes/DoE/MPICH.json new file mode 100644 index 00000000..fbac07a6 --- /dev/null +++ b/agency-indexes/DoE/MPICH.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2023-08-11" + }, + "description": "MPICH is a high-performance and widely portable implementation of the MPI-4 standard from the Argonne National Laboratory. This release has all MPI 4 functions and features required by the standard with the exception of support for the user-defined data representations for I/O.", + "laborHours": 425797.6, + "languages": [], + "name": "MPICH", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pmodels/mpich/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/mpich", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPICPP.json b/agency-indexes/DoE/MPICPP.json new file mode 100644 index 00000000..7539f9d8 --- /dev/null +++ b/agency-indexes/DoE/MPICPP.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-09", + "metadataLastUpdated": "2022-10-09" + }, + "description": "SAND2022-3385 O MPICPP is a library that helps users use the Message Passing Interface (MPI), which is defined in the C language. MPICPP is lightweight and thoroughly applies the most tried-and-true features of the C++ language while avoiding the features that are not stable. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "MPICPP", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mpicpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPIDiff.json b/agency-indexes/DoE/MPIDiff.json new file mode 100644 index 00000000..8f5289b3 --- /dev/null +++ b/agency-indexes/DoE/MPIDiff.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "MPIDiff is a C++ library for pairing a correct version of an executable with a version that may have bugs\nor race conditions in it. The correct version checks that the data communicated from the other program\nmatches its own and reports any differences.", + "laborHours": 0.0, + "languages": [], + "name": "MPIDiff", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MPIDiff", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPI_File_Tree_Walk.json b/agency-indexes/DoE/MPI_File_Tree_Walk.json new file mode 100644 index 00000000..6c868484 --- /dev/null +++ b/agency-indexes/DoE/MPI_File_Tree_Walk.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "MPI-FTW is a scalable MPI based software application that navigates a directory tree by dynamically allocating processes to navigate sub-directories found. Upon completion, MPI-FTW provides statistics on the number of directories found, files found, and time to complete. In addition, commands can be executed at each directory level.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "mpicc compiler" + ], + "name": "MPI File Tree Walk", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPI_Multicore_Linktest_Benchmark.json b/agency-indexes/DoE/MPI_Multicore_Linktest_Benchmark.json new file mode 100644 index 00000000..660e58e9 --- /dev/null +++ b/agency-indexes/DoE/MPI_Multicore_Linktest_Benchmark.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The MPI Multicore Linktest (LinkTest) measures the aggregate bandwidth from/to a multicore node in a parallel system. It allows the user to specify a variety of different node layout and communication routine variations and reports the maximal observed bandwidth across all specified options. In particular, this benchmark is able to vary the number of tasks on the root node and thereby allows users to study the impact of multicore architectures on MPI communication performance.", + "laborHours": 0.0, + "languages": [], + "name": "MPI Multicore Linktest Benchmark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/mpi-multicore-linktest-benchmark", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPI_Multicore_Torus_Communication_Benchmark.json b/agency-indexes/DoE/MPI_Multicore_Torus_Communication_Benchmark.json new file mode 100644 index 00000000..3741e39c --- /dev/null +++ b/agency-indexes/DoE/MPI_Multicore_Torus_Communication_Benchmark.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The MPI Multicore Torus Communications Benchmark (TorusTest) measures the aggregate bandwidth across all six links from/to any multicore node in a logical torus. It can run in wo modi: using a static or a random mapping of tasks to torus locations. The former can be used to achieve optimal mappings and aggregate bandwidths that can be achieved with varying node mappings.", + "laborHours": 0.0, + "languages": [], + "name": "MPI Multicore Torus Communication Benchmark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/mpi-multicore-torus-communication-benchmark", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPI_Partix.json b/agency-indexes/DoE/MPI_Partix.json new file mode 100644 index 00000000..f12572b1 --- /dev/null +++ b/agency-indexes/DoE/MPI_Partix.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-10", + "metadataLastUpdated": "2022-10-20" + }, + "description": "SAND2022-6990 O MPI Partix is an application suite to test user-level threading (ULT) and partitioned communication in MPI. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "MPI Partix", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/MPI-Partix/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MPI-Partix", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPI_Profiler.json b/agency-indexes/DoE/MPI_Profiler.json new file mode 100644 index 00000000..401937f4 --- /dev/null +++ b/agency-indexes/DoE/MPI_Profiler.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "loupe is a PMPl-based library to profile MPI routines in a parallel application.", + "laborHours": 304.0, + "languages": [ + "C++, Python" + ], + "name": "MPI Profiler", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/loupe", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPI_Remote.json b/agency-indexes/DoE/MPI_Remote.json new file mode 100644 index 00000000..41042b33 --- /dev/null +++ b/agency-indexes/DoE/MPI_Remote.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2022-02-28", + "metadataLastUpdated": "2022-02-28" + }, + "description": "This package represents remote datasets. It provides a context object that acts as a proxy to an [mpi_list](https://pypi.org/project/mpi-list/) context running on a remote server.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "MPI Remote", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/99R/mpi-remote", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPI_Stages_:_A_Serializable_MPI_Library.json b/agency-indexes/DoE/MPI_Stages_:_A_Serializable_MPI_Library.json new file mode 100644 index 00000000..d30eda2f --- /dev/null +++ b/agency-indexes/DoE/MPI_Stages_:_A_Serializable_MPI_Library.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-07-30" + }, + "description": "MPI library that supports serializing (and check-pointing) its MPI Stages is a communication library that allows nodes and programs in a computer cluster to communicate via the Message-Passing Interface (MPI).\n\nThe internal data objects of the library are serializable, i.e., the user can convert the MPI state or objects, such as groups or communicators, into byte streams and save them into a checkpoint file. \n\nLater users can load the checkpoint file and de-serialize previous objects into the library. \n\nSerialization/de-serialization is useful in MPI applications to recover from node failures.", + "laborHours": 9636.8, + "languages": [], + "name": "MPI Stages : A Serializable MPI Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/mpi-stages", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPI_Usage.json b/agency-indexes/DoE/MPI_Usage.json new file mode 100644 index 00000000..d1c790f9 --- /dev/null +++ b/agency-indexes/DoE/MPI_Usage.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-10", + "metadataLastUpdated": "2019-04-11" + }, + "description": "MPI Usage is a python program that gathers statistics of MPI usage in MPI programs. It reports the MPI routines used in the program among other statistics, such as, the number of lines and languages used in the program (e.g., C, C++, Fortran, CUDA and OpenMP).", + "laborHours": 6900.8, + "languages": [], + "name": "MPI Usage", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MPI-Usage", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPNN.json b/agency-indexes/DoE/MPNN.json new file mode 100644 index 00000000..47ff3dcb --- /dev/null +++ b/agency-indexes/DoE/MPNN.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-10", + "metadataLastUpdated": "2022-10-10" + }, + "description": "SAND2022-6885 O Minima-Preserving Neural Network (MPNN) is a software library for learning functions with known minima location. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "MPNN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MPNN", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPRL__Multi-Pulse_Reinforcement_Learning_.json b/agency-indexes/DoE/MPRL__Multi-Pulse_Reinforcement_Learning_.json new file mode 100644 index 00000000..cb8be730 --- /dev/null +++ b/agency-indexes/DoE/MPRL__Multi-Pulse_Reinforcement_Learning_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-05-25", + "metadataLastUpdated": "2022-08-19" + }, + "description": "MPRL contains code for defining and deploying reinforcement learning control agents for multi-pulse, multi-fuel advanced compression ignition engines.", + "laborHours": 0.0, + "languages": [ + "Python", + "shell" + ], + "name": "MPRL (Multi-Pulse Reinforcement Learning)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MPRL", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPS++.json b/agency-indexes/DoE/MPS++.json new file mode 100644 index 00000000..eb35f4e3 --- /dev/null +++ b/agency-indexes/DoE/MPS++.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The MPS++ computer code simulates models of strongly correlated quantum lattice systems. The algorithm used is the density-matrix renormalization method formulated in the matrix product states language. These models and methods are used to obtain ground state, dynamic, finite temperature and time evolution properties of the underlying materials that are simulated. These materials are usually one- and quasi-one dimensional strongly correlated electronic systems, such as high temperature superconductors, manganites, and other transition metal oxides. This code is (mostly) an implementation of the paper \"The density-matrix renormalization group in the age of matrix product states\" by U. Schollwoeck, and references therein, found at http://arxiv.org/abs/1008.3477v2 , and that was also published in Annals of Physics 326,96 (2011).", + "laborHours": 1656.8, + "name": "MPS++", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/g1257/mpspp", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MPSCP.json b/agency-indexes/DoE/MPSCP.json new file mode 100644 index 00000000..051911c1 --- /dev/null +++ b/agency-indexes/DoE/MPSCP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "Non-encrypted, TCP-streams, host-to-host file copy utility intended to enable greater transfer rates, while having the basic user-interface concept of BSD rcp. The underlying design provides the opportunity to maximize performance by allocating supplemental IP sockets as dedicated and optimizable data-channels, in a mode similar to FTP. Additionally, a parallel I/O scheme, based on the HPSS paradigm, is also employed, offering potentials for multiple-sockets over a single network connection (which, in many circumstances, especially those in involving heterogeneous host platforms, or large latency situations, can capture more bandwidth), and also the distribution of the sockets across a manifold of parallel IP network connections.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "MPSCP", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MRE-Code-Hub_extract_loggernet.json b/agency-indexes/DoE/MRE-Code-Hub_extract_loggernet.json new file mode 100644 index 00000000..ff73d463 --- /dev/null +++ b/agency-indexes/DoE/MRE-Code-Hub_extract_loggernet.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This script is used to read the infinitely growing data files created by a Campbell Data Logger to extract hourly data and\nwrite the content to hourly output files.", + "laborHours": 0.0, + "languages": [], + "name": "MRE-Code-Hub/extract_loggernet", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MRE-Code-Hub/extract_loggernet", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MRG8_Random_Number_Generator_Library__MRG8__v1.0.json b/agency-indexes/DoE/MRG8_Random_Number_Generator_Library__MRG8__v1.0.json new file mode 100644 index 00000000..344b1cac --- /dev/null +++ b/agency-indexes/DoE/MRG8_Random_Number_Generator_Library__MRG8__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-29", + "metadataLastUpdated": "2021-07-14" + }, + "description": "Pseudo random number generators (PRNGs) are crucial for nu- merous applications in HPC ranging from molecular dynamics to quantum chemistry, and hydrodynamics. Our optimized implementation generates the same random number sequence as the original well-characterized MRG8. MRG8-AVX512 achieves a substantial 69% improvement compared to Intel's MKL, and MRG8-GPU shows a maximum 3.36x speedup compared to NVIDIA's cuRAND library.", + "laborHours": 0.0, + "languages": [], + "name": "MRG8 Random Number Generator Library (MRG8) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kenmiura/mrg8", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MRNet-based_Dynamic_Probe_Class_Library.json b/agency-indexes/DoE/MRNet-based_Dynamic_Probe_Class_Library.json new file mode 100644 index 00000000..8b7c1ae2 --- /dev/null +++ b/agency-indexes/DoE/MRNet-based_Dynamic_Probe_Class_Library.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-22", + "metadataLastUpdated": "2020-10-02" + }, + "description": "The Dynamic Probe Class Library (DPCL) is an API that allows for the modification of running code, or dynamic instrumentation. Dynamic instruction is an attractive technique for implementing performance analysis tools, debugging, or process steering because this method doesn't require the modification of the application's source code and hence avoids recompiling, re-linking, and restarting the application. The DPCL API is machine independent; hence DPCL-based tools built on one platform will work on another platform", + "homepageURL": "https://sourceforge.net/projects/dpcl/files", + "laborHours": 83296.0, + "languages": [ + "C, C++" + ], + "name": "MRNet-based Dynamic Probe Class Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/IPL-1.0", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/dpcl/files", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MRPA++.json b/agency-indexes/DoE/MRPA++.json new file mode 100644 index 00000000..aaa36a41 --- /dev/null +++ b/agency-indexes/DoE/MRPA++.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "The MRPA++ computer code simulates neutron scattering and superconductivity in correlated electron systems. It uses a random-phase approximation (RPA) / Bardeen-Cooper-Schrieffer (BCS) theory to predict the neutron scattering cross section of realistic multi-orbital tight-binding models with Hubbard-like electron-electron interactions for the normal and superconducting states. It can also be used to calculate the pairing interaction in these models using an RPA approximation and to predict the superconducting gap structure.", + "laborHours": 0.0, + "languages": [ + "C++/Gnu g++ (GCC)/4.1.2" + ], + "name": "MRPA++", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/maierta/MRPAPP/blob/master/Open%20Source%20Software%20License%20MRPAPP.doc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maierta/MRPAPP", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MRSH_Version_V2.0.json b/agency-indexes/DoE/MRSH_Version_V2.0.json new file mode 100644 index 00000000..4884df0a --- /dev/null +++ b/agency-indexes/DoE/MRSH_Version_V2.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The MRSH project is a collection of the following programs: MRSH, MRCP, MRLOGIN, MRSHD, MRLOGIND. These programs are modifications of the programs RSH, RCP, RLOGIN, RSHD, and RLOGIND. They have been modified to provide authentication via munge, an intra-cluster authentication service. Henceforth, \"MRSH\" implies the collective set of programs MRSH, MRCP, MRLOGIN, MRSHD, and MRLOGIND. Similarly RSH will refer to its collective set of programs.", + "laborHours": 24213.6, + "name": "MRSH Version V2.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/mrsh", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MSAUtils.json b/agency-indexes/DoE/MSAUtils.json new file mode 100644 index 00000000..c29b571a --- /dev/null +++ b/agency-indexes/DoE/MSAUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "This is the repository for \"MSAUtils\" developed by KBase. This is a KBase module generated by the KBase Software Development Kit (SDK).", + "laborHours": 623.2, + "languages": [], + "name": "MSAUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/MSAUtils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MSGFPlus_MASIC_Toolbox.json b/agency-indexes/DoE/MSGFPlus_MASIC_Toolbox.json new file mode 100644 index 00000000..bdf20fc3 --- /dev/null +++ b/agency-indexes/DoE/MSGFPlus_MASIC_Toolbox.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "DataProcessing toolbox for running MSGF+ and MASIC, then merging the results. Uses Windows batch files to automate the process for a folder of Thermo .Raw files", + "laborHours": 4575.2, + "languages": [], + "name": "MSGFPlus_MASIC_Toolbox", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MSGFPlus_MASIC_Toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MSRESOLVE.json b/agency-indexes/DoE/MSRESOLVE.json new file mode 100644 index 00000000..940f6f4d --- /dev/null +++ b/agency-indexes/DoE/MSRESOLVE.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "savaraa@ornl.gov" + }, + "date": { + "created": "2022-08-27", + "metadataLastUpdated": "2022-08-27" + }, + "description": "MSRESOLVE. A program for converting mass spectrometry signals to concentrations. Baseline corrections, smoothing, solving overlapping patterns, mass spectrometer tuning, and more.", + "laborHours": 0.0, + "languages": [ + "python" + ], + "name": "MSRESOLVE", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdityaSavara/MSRESOLVE", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MSU_Disentanglement_Analysis_Software.json b/agency-indexes/DoE/MSU_Disentanglement_Analysis_Software.json new file mode 100644 index 00000000..5a57b94b --- /dev/null +++ b/agency-indexes/DoE/MSU_Disentanglement_Analysis_Software.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-10-17", + "metadataLastUpdated": "2022-10-17" + }, + "description": "This software is used to disentangle the forced-versus-unforced components of tropospheric temperature change over the satellite era (after 1979) using maps of surface temperature change as a predictor. In general, the software assembles training datasets (from pre-computed surface temperature trend maps and domain averaged tropospheric warming rates), trains statistical/machine learning (ML) algorithms, applies the trained statistical/ML model to climate model data and observations, and then saves the results. A leave-one-out approach is used in which the statistical/ML models are iteratively trained on (N- 1) climate model and then applied to the remaining climate model (and observations). Each model includes a large ensemble (i.e., >10) of model simulations. The software relies on scikit-learn ridge regression, PLS regression, and neural network algorithms.", + "laborHours": 0.0, + "languages": [], + "name": "MSU Disentanglement Analysis Software", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MDAS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MS_File_Info_Scanner.json b/agency-indexes/DoE/MS_File_Info_Scanner.json new file mode 100644 index 00000000..90167840 --- /dev/null +++ b/agency-indexes/DoE/MS_File_Info_Scanner.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The MS File Info Scanner can be used to scan a series of MS data files (or data folders) and extract the acquisition start and end times, number of spectra, and the total size of the data. In addition, it can create 2D-plot graphics of the m/z values vs. time for QA purposes.", + "laborHours": 47348.0, + "languages": [], + "name": "MS File Info Scanner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MS-File-Info-Scanner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MS_MS_Automated_Selected_Ion_Chromatograms.json b/agency-indexes/DoE/MS_MS_Automated_Selected_Ion_Chromatograms.json new file mode 100644 index 00000000..ffa4ff35 --- /dev/null +++ b/agency-indexes/DoE/MS_MS_Automated_Selected_Ion_Chromatograms.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This program can be used to read a LC-MS/MS data file from either a Finnigan ion trap mass spectrometer (.Raw file) or an Agilent Ion Trap mass spectrometer (.MGF and .CDF files) and create a selected ion chromatogram (SIC) for each of the parent ion masses chosen for fragmentation. The largest peak in each SIC is also identified, with reported statistics including peak elution time, height, area, and signal to noise ratio. It creates several output files, including a base peak intensity (BPI) chromatogram for the survey scan, a BPI for the fragmentation scans, an XML file containing the SIC data for each parent ion, and a \"flat file\" (ready for import into a database) containing summaries of the SIC data statistics.", + "laborHours": 118225.6, + "name": "MS/MS Automated Selected Ion Chromatograms", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MASIC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MT-xGEMM_v1.0.json b/agency-indexes/DoE/MT-xGEMM_v1.0.json new file mode 100644 index 00000000..2f9f7bae --- /dev/null +++ b/agency-indexes/DoE/MT-xGEMM_v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2021-03-11" + }, + "description": "MT-xGEMM is a simple driver for benchmarking xGEMM Level 3 BLAS functions. Support includes multiple BLAS interfaces, including: CBLAS, MKL, CUBLAS and HIPBLAS.", + "laborHours": 0.0, + "languages": [], + "name": "MT-xGEMM v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/nersc-proxies/mt-gemm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MTDB-Creator.json b/agency-indexes/DoE/MTDB-Creator.json new file mode 100644 index 00000000..9cc6a4c1 --- /dev/null +++ b/agency-indexes/DoE/MTDB-Creator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Used to generate an Accurate Mass and Time tag database from local MS/MS search engine results (from SEQUEST, X!Tandem, or MSGF+)", + "laborHours": 36571.2, + "languages": [], + "name": "MTDB-Creator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MTDB-Creator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MTIP_Single_Particle_Imaging__Spinifel__v0.1.0.json b/agency-indexes/DoE/MTIP_Single_Particle_Imaging__Spinifel__v0.1.0.json new file mode 100644 index 00000000..e09a6be2 --- /dev/null +++ b/agency-indexes/DoE/MTIP_Single_Particle_Imaging__Spinifel__v0.1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-12-07", + "metadataLastUpdated": "2023-03-28" + }, + "description": "Performs Multi-Tiered Iterative Phasing for Single Particle Imaging. The Spinifel code uses distributed computing (using MPI and Legion) to spread work across many compute nodes. On-node computation is accelerated using GPGPUs (using CuPy, and CUDA).", + "laborHours": 0.0, + "languages": [], + "name": "MTIP Single Particle Imaging (Spinifel) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/mtip/spinifel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MUFFSgenMC:_An_Open_Source_MUon_Flexible_Framework_for_Spectral_GENeration_for_Monte_Carlo_Applications.json b/agency-indexes/DoE/MUFFSgenMC:_An_Open_Source_MUon_Flexible_Framework_for_Spectral_GENeration_for_Monte_Carlo_Applications.json new file mode 100644 index 00000000..785601ca --- /dev/null +++ b/agency-indexes/DoE/MUFFSgenMC:_An_Open_Source_MUon_Flexible_Framework_for_Spectral_GENeration_for_Monte_Carlo_Applications.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "A cosmic ray Muon Flexible Framework for Spectral GENeration for Monte Carlo Applications (MUFFSgenMC) has been developed to support state-of-the-art cosmic ray muon tomographic applications. The flexible framework allows for easy and fast creation of source terms for popular Monte Carlo applications like GEANT4 and MCNP. This code framework simplifies the process of simulations used for cosmic ray muon tomography.", + "homepageURL": "https://www.mathworks.com/matlabcentral/fileexchange/65585-muffsgenmc", + "laborHours": 167.2, + "languages": [ + "Matlab R2017" + ], + "name": "MUFFSgenMC: An Open Source MUon Flexible Framework for Spectral GENeration for Monte Carlo Applications", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.mathworks.com/matlabcentral/fileexchange/65585-muffsgenmc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.mathworks.com/matlabcentral/fileexchange/65585-muffsgenmc", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MUNGE.json b/agency-indexes/DoE/MUNGE.json new file mode 100644 index 00000000..4b7e1d1a --- /dev/null +++ b/agency-indexes/DoE/MUNGE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "MUNGE (MUNGE Uid 'N' Gid Emporium) is an authentication service for creating and validating credentials. It is designed to be highly scalable for use in an HPC cluster environment. It allows a process to authenticate the UID and GID of another local or remote process within a group of hosts having common users and groups. These hosts form a security realm that is defined by a shared cryptographic key. Clients within this security realm can create and validate credentials without the use of root privileges, reserved ports, or platform-specific methods.", + "laborHours": 14455.2, + "languages": [], + "name": "MUNGE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dun/munge", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MUPPET:_An_automated_OpenMP_mutation_testing_framework_for_performance_optimization.json b/agency-indexes/DoE/MUPPET:_An_automated_OpenMP_mutation_testing_framework_for_performance_optimization.json new file mode 100644 index 00000000..60e51fcc --- /dev/null +++ b/agency-indexes/DoE/MUPPET:_An_automated_OpenMP_mutation_testing_framework_for_performance_optimization.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-19", + "metadataLastUpdated": "2025-03-19" + }, + "description": "MUPPET is a tool for OpenMP programs that identifies program modifications, called mutations, aimed at\nimproving program performance. Existing performance optimization techniques, including profiling-based\nand auto-tuning techniques, fail to indicate program modifications at the source level thus preventing their\nportability across compilers. MUPPET aims to help HPC developers reason about performance defects\nand missed opportunities to improve performance at the source code level.", + "laborHours": 12570.4, + "languages": [], + "name": "MUPPET: An automated OpenMP mutation testing framework for performance optimization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MUPPET", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MVC_Framework.json b/agency-indexes/DoE/MVC_Framework.json new file mode 100644 index 00000000..c695c454 --- /dev/null +++ b/agency-indexes/DoE/MVC_Framework.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Provides a reusable model-view-controller application programming interface (API) for use in the rapid development of graphical user interface applications in the .NET 2.0 framework. This includes a mechanism for adding new data stores, data sources, data analyses, and visualizations in the form of plugins.] The MVC Framework is implemented in C# as a .NET 2.0 framework that can then be built against when developing applications. The infrastructure allows for presenting application specific views (visualizations) to the user to interact with. Based on the interactions the user makes with a view, requests are generated which in turn are handled by the central controller facility. The controller handles the request in an application specific manner by routing the request to appropriate data stores, data accessors or data analyzers. Retrieved or processed data is published to subscribed components for further processing or for presentation to the user.", + "homepageURL": "http://www.codeplex.com/mvcframework", + "laborHours": 0.0, + "languages": [ + ".NET Framework 2.0" + ], + "name": "MVC Framework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.codeplex.com/mvcframework", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MVC_Plugin_Lib.json b/agency-indexes/DoE/MVC_Plugin_Lib.json new file mode 100644 index 00000000..36110031 --- /dev/null +++ b/agency-indexes/DoE/MVC_Plugin_Lib.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Provides a basic collection of utility plugins for use in the MVC Shell or MVC Framework environment. The MVC PluginLib is implemented in C# as a collection of.NET 2.0 frameworks that implement MVC Framework and MVC Shell compatible plugins. Three plugins are provided at this time, with more to be added over time: ApplicationInfoPlugin - provides basic information about the running application IronPythonPlugin - provides an IronPython based interactive shell environment ProgressBarPlugin - provides a basic progress bar implementation.", + "homepageURL": "https://archive.codeplex.com/?p=mvcpluginlib", + "laborHours": 0.0, + "languages": [], + "name": "MVC Plugin Lib", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://archive.codeplex.com/?p=mvcpluginlib", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MVC_Shell.json b/agency-indexes/DoE/MVC_Shell.json new file mode 100644 index 00000000..9b65e535 --- /dev/null +++ b/agency-indexes/DoE/MVC_Shell.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Provides the shell of a plugin based application environment that builds on MVC Framework to allow one to rapidly construct an application by using a collection of plugins. The MVC Shell is implemented in C# as a .NET 2.0 application that can then be used as a shell for building a plugin based application. The infrastructure allows for dynamically processing a specified collection of plugins in order to determine the functionality of the application, where all plugins operate within the context of the underlying MVC Framework environment.", + "homepageURL": "http://www.codeplex.com/mvcshell", + "laborHours": 0.0, + "name": "MVC Shell", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.codeplex.com/mvcshell", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MaPPeRTrac.json b/agency-indexes/DoE/MaPPeRTrac.json new file mode 100644 index 00000000..30a72ab2 --- /dev/null +++ b/agency-indexes/DoE/MaPPeRTrac.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2021-08-20" + }, + "description": "Massively Parallel, Portable, and Reproducible Tractography (MaPPeRTrac) is a brain tractography workflow for high performance computing. It incorporates novel technologies to simplify and accelerate neuroimaging research.", + "laborHours": 0.0, + "languages": [], + "name": "MaPPeRTrac", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MaPPeRTrac", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MacPatch.json b/agency-indexes/DoE/MacPatch.json new file mode 100644 index 00000000..6e615a12 --- /dev/null +++ b/agency-indexes/DoE/MacPatch.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "MacPatch simplifies the act of patching and installing software on Mac OS X based systems. The client relies on using the built-in software update application for patching the Mac OS X system updates and it's own scan and patch engine for custom patches. MacPatch offers features and functionality that provide Mac OS X administrators with best possible patching solution to meet the challenges of supporting Mac OS X in a Workgroup or Enterprise.\n", + "laborHours": 97052.0, + "languages": [], + "name": "MacPatch", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MacPatch", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MacPatchImporter_for_AutoPkg.json b/agency-indexes/DoE/MacPatchImporter_for_AutoPkg.json new file mode 100644 index 00000000..843c3448 --- /dev/null +++ b/agency-indexes/DoE/MacPatchImporter_for_AutoPkg.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This processor adds the ability to upload AutoPkg packages to a MacPatch server.\n", + "laborHours": 288.8, + "languages": [], + "name": "MacPatchImporter for AutoPkg", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MacPatch-AutoPKG", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Macaw.json b/agency-indexes/DoE/Macaw.json new file mode 100644 index 00000000..e14de41c --- /dev/null +++ b/agency-indexes/DoE/Macaw.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-10-11", + "metadataLastUpdated": "2023-10-11" + }, + "description": "MaCaw is a MOOSE-based application that enables domain-decomposed neutral particle transport calculations in MOOSE. It leverages the ray tracing MOOSE module for unstructured mesh tracking and OpenMC for collision physics, handling material definitions, and tallying quantities.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Macaw", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/macaw", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Machine_Learning_Based_System_for_Automated_Estimation_of_Crystal_Unit_Cell_Parameters_from_X-ray_Diffraction_Powder_Patterns__MLCell__v0.1.json b/agency-indexes/DoE/Machine_Learning_Based_System_for_Automated_Estimation_of_Crystal_Unit_Cell_Parameters_from_X-ray_Diffraction_Powder_Patterns__MLCell__v0.1.json new file mode 100644 index 00000000..90added4 --- /dev/null +++ b/agency-indexes/DoE/Machine_Learning_Based_System_for_Automated_Estimation_of_Crystal_Unit_Cell_Parameters_from_X-ray_Diffraction_Powder_Patterns__MLCell__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "This software uses machine learning models to perform inference on X-ray diffraction powder patterns, output from a diffractometer, to estimate all 6 unit cell parameters of crystalline lattices. Novel aspects of this software originated from the incorporation of concepts from crystallography to an ML-based approach; The resulting method achieves new performance capabilities without significant loss of accuracy and with less computationally intensive models.", + "laborHours": 258.4, + "languages": [], + "name": "Machine Learning Based System for Automated Estimation of Crystal Unit Cell Parameters from X-ray Diffraction Powder Patterns (MLCell) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cctbx-xfel/MLCell", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Machine_Learning_Toolkit_for_Extreme_Scale.json b/agency-indexes/DoE/Machine_Learning_Toolkit_for_Extreme_Scale.json new file mode 100644 index 00000000..035f9dd6 --- /dev/null +++ b/agency-indexes/DoE/Machine_Learning_Toolkit_for_Extreme_Scale.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Support Vector Machines (SVM) is a popular machine learning technique, which has been applied to a wide range of domains such as science, finance, and social networks for supervised learning. MaTEx undertakes the challenge of designing a scalable parallel SVM training algorithm for large scale systems, which includes commodity multi-core machines, tightly connected supercomputers and cloud computing systems. Several techniques are proposed for improved speed and memory space usage including adaptive and aggressive elimination of samples for faster convergence , and sparse format representation of data samples. Several heuristics for earliest possible to lazy elimination of non-contributing samples are considered in MaTEx. In many cases, where an early sample elimination might result in a false positive, low overhead mechanisms for reconstruction of key data structures are proposed. The proposed algorithm and heuristics are implemented and evaluated on various publicly available datasets", + "laborHours": 647474.4, + "name": "Machine Learning Toolkit for Extreme Scale", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/matex-org/matex/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/matex-org/matex", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Machine_Learning_Travel_Time_emulator.json b/agency-indexes/DoE/Machine_Learning_Travel_Time_emulator.json new file mode 100644 index 00000000..900687b5 --- /dev/null +++ b/agency-indexes/DoE/Machine_Learning_Travel_Time_emulator.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-02-08", + "metadataLastUpdated": "2024-02-20" + }, + "description": "This notebook makes seismic phase travel time predictions using machine learning. There are 3 different\nmachine learning models corresponding to the three regimes: local, regional, and teleseismic. After\nreading in the test data and splitting into the 3 regimes, we use precomputed scalers to scale the input\nfeatures used to make the travel time predictions. We then load the machine learning models and use\nthem to predict travel times for test data.", + "homepageURL": "https://gdo-maltte.llnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Machine Learning Travel Time emulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gdo-maltte.llnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Machine_Learning_for_Automating_Analysis_of_Speckle_Dynamics.json b/agency-indexes/DoE/Machine_Learning_for_Automating_Analysis_of_Speckle_Dynamics.json new file mode 100644 index 00000000..a528d3f4 --- /dev/null +++ b/agency-indexes/DoE/Machine_Learning_for_Automating_Analysis_of_Speckle_Dynamics.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "abarbour@bnl.gov" + }, + "date": { + "created": "2022-08-05", + "metadataLastUpdated": "2022-08-05" + }, + "description": "Code used for generating results in the publication for automating analysis of non-equilibrium X-ray Photon Correlation Spectroscopy data, 'Machine Learning for analysis of speckle dynamics: quantification and outlier detection'.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Machine Learning for Automating Analysis of Speckle Dynamics", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bnl/automating_XPCS_analysis_pub", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Machine_Learning_for_Cardiac_Electrical_Imaging.json b/agency-indexes/DoE/Machine_Learning_for_Cardiac_Electrical_Imaging.json new file mode 100644 index 00000000..aab11eec --- /dev/null +++ b/agency-indexes/DoE/Machine_Learning_for_Cardiac_Electrical_Imaging.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-28", + "metadataLastUpdated": "2023-06-28" + }, + "description": "PyTorch code for cardiac electrical imaging using the 12-lead ECG. This code is associated with the\npaper from CINC 2022. If you use this code, please cite:\nPaper : https://cinc.org/2022/Program/accepted/26_Preprint.pdf\nDataset : https://library.ucsd.edu/dc/object/bb29449106\nThe code support two tasks:\nTask 1: Activation Map Reconstruction from ECG\nTask 2: Transmembrane potential Reconstruction from ECG", + "laborHours": 0.0, + "languages": [], + "name": "Machine Learning for Cardiac Electrical Imaging", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/landajuela/cardiac_ml", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0." +} \ No newline at end of file diff --git a/agency-indexes/DoE/Machine_Learning_for_Distributed_Acoustic_Sensing_data__MLDAS__v1.0.1.json b/agency-indexes/DoE/Machine_Learning_for_Distributed_Acoustic_Sensing_data__MLDAS__v1.0.1.json new file mode 100644 index 00000000..06f605ce --- /dev/null +++ b/agency-indexes/DoE/Machine_Learning_for_Distributed_Acoustic_Sensing_data__MLDAS__v1.0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-02", + "metadataLastUpdated": "2021-03-02" + }, + "description": "MLDAS is a Python-written package for exploratory data analysis and deep learning training on Distributed Acoustic Sensing data. The machine learning tools are powered by the PyTorch library and designed to work efficiently on large scale datasets using parallel computing. Various SLURM scripts as well as a tutorial have also been made available to allow geophysicists to quickly and easily implement the available tools in their analysis workflow on supercomputer facilities.", + "laborHours": 0.0, + "languages": [], + "name": "Machine Learning for Distributed Acoustic Sensing data (MLDAS) v1.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ml4science/mldas", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Machine_Learning_for_Sedov_Blast.json b/agency-indexes/DoE/Machine_Learning_for_Sedov_Blast.json new file mode 100644 index 00000000..a5f81a35 --- /dev/null +++ b/agency-indexes/DoE/Machine_Learning_for_Sedov_Blast.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-15" + }, + "description": "Machine learning for predicting physics variables in Sedov blast simulation.", + "laborHours": 668.8, + "languages": [], + "name": "Machine Learning for Sedov Blast", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Sedov-ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Machine_Optimized_Analysis_Tools.json b/agency-indexes/DoE/Machine_Optimized_Analysis_Tools.json new file mode 100644 index 00000000..bdae81ee --- /dev/null +++ b/agency-indexes/DoE/Machine_Optimized_Analysis_Tools.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This software package provides a common \"front end\" for various math operations that are relevant to astrophysical data processing. This includes special function evaluation, fast Fourier transforms, streamed random number generation and spherical geometry projections. Computer-vendor specific libraries and internal algorithms can be selected on different systems in order to achieve the best possible performance on all systems. This software is still in an early state of development. ", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Any Standard C++ compiler which supports the BOOST software package" + ], + "name": "Machine Optimized Analysis Tools", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Machine_learning_and_TDDFT_software_for_stopping_power_computation.json b/agency-indexes/DoE/Machine_learning_and_TDDFT_software_for_stopping_power_computation.json new file mode 100644 index 00000000..f20a37f8 --- /dev/null +++ b/agency-indexes/DoE/Machine_learning_and_TDDFT_software_for_stopping_power_computation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "(SF-24-012) Stopping power describes the rate that a material slows radiation particles passing through it and is useful in designing many technologies. Few organizations can perform new measurements, which require significant resources and rare equipment, and all others rely on coarse approximations \nrendered from pre-existing data. Methods for computing stopping power in new materials, such as time-dependent density functional theory (TD-DFT), have only recently (circa-2015) become available but are too computationally costly to use frequently enough to have a pronounced impact. We have created a method that opens a pathway to computing stopping power without any need for experimental \ndata by combining electronic structure computations and machine learning.", + "laborHours": 2979.2, + "languages": [], + "name": "Machine learning and TDDFT software for stopping power computation", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/globus-labs/stopping-power-ml", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Machine_learning_enabled_electron_microscopy_data_analysis_tool.json b/agency-indexes/DoE/Machine_learning_enabled_electron_microscopy_data_analysis_tool.json new file mode 100644 index 00000000..bae53917 --- /dev/null +++ b/agency-indexes/DoE/Machine_learning_enabled_electron_microscopy_data_analysis_tool.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-11-10", + "metadataLastUpdated": "2022-11-10" + }, + "description": "This software is for materials image and spectral data analysis. It consists machine learning models that can segment a large amount of image data in a high-throughput way, and an interface for image data and spectral data analysis.", + "laborHours": 0.0, + "languages": [], + "name": "Machine learning enabled electron microscopy data analysis tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xiaotingzhong/ML_microscopy_detection_segmentation", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Machine_learning_enabling_high-throughput_and_remote_operations_at_large-scale_user_facilities.json b/agency-indexes/DoE/Machine_learning_enabling_high-throughput_and_remote_operations_at_large-scale_user_facilities.json new file mode 100644 index 00000000..750f726d --- /dev/null +++ b/agency-indexes/DoE/Machine_learning_enabling_high-throughput_and_remote_operations_at_large-scale_user_facilities.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "tkonstant@bnl.gov" + }, + "date": { + "created": "2022-01-18", + "metadataLastUpdated": "2022-01-19" + }, + "description": "Code used for generating results in the publication: \"Machine learning enabling high-throughput and remote operations at large-scale user facilities\"", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Machine learning enabling high-throughput and remote operations at large-scale user facilities", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bnl/pub-ML_examples", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Machine_learning_methods_for_quantum_mechanics.json b/agency-indexes/DoE/Machine_learning_methods_for_quantum_mechanics.json new file mode 100644 index 00000000..6ed66661 --- /dev/null +++ b/agency-indexes/DoE/Machine_learning_methods_for_quantum_mechanics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "Exploratory implementations of possible algorithms for simulating small quantum mechanical systems on a classical computer.", + "laborHours": 0.0, + "languages": [], + "name": "Machine learning methods for quantum mechanics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MLQM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Machine_learning_tools_for_epigenetics.json b/agency-indexes/DoE/Machine_learning_tools_for_epigenetics.json new file mode 100644 index 00000000..92fd90eb --- /dev/null +++ b/agency-indexes/DoE/Machine_learning_tools_for_epigenetics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "The software provides machine learning analysis and visualization to detect patterns in epigenetic data, including conventional machine learning and statistical methods, and open-source packages like pyBigWig (https://github.com/deeptools/pyBigWig) for data processing. The software is written in python, it uses some python libraries.", + "laborHours": 1200.8, + "languages": [], + "name": "Machine learning tools for epigenetics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/epigen", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mads.jl.json b/agency-indexes/DoE/Mads.jl.json new file mode 100644 index 00000000..db623ef5 --- /dev/null +++ b/agency-indexes/DoE/Mads.jl.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Mads.jl (Model analysis and decision support in Julia) is a code that streamlines the process of using data and models for analysis and decision support. It is based on another open-source code developed at LANL and written in C/C++ (MADS; http://mads.lanl.gov; LA-CC-11- 035). Mads.jl can work with external models of arbitrary complexity as well as built-in models of flow and transport in porous media. It enables a number of data- and model-based analyses including model calibration, sensitivity analysis, uncertainty quantification, and decision analysis. The code also can use a series of alternative adaptive computational techniques for Bayesian sampling, Monte Carlo, and Bayesian Information-Gap Decision Theory. The code is implemented in the Julia programming language, and has high-performance (parallel) and memory management capabilities. The code uses a series of third party modules developed by others. The code development will also include contributions to the existing third party modules written in Julia; this contributions will be important for the efficient implementation of the algorithm used by Mads.jl. The code also uses a series of LANL developed modules that are developed by Dan O'Malley; these modules will be also a part of the Mads.jl release. Mads.jl will be released under GPL V3 license. The code will be distributed as a Git repo at gitlab.com and github.com. Mads.jl manual and documentation will be posted at madsjulia.lanl.gov.", + "laborHours": 150434.4, + "name": "Mads.jl", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/madsjulia/Mads.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mage.json b/agency-indexes/DoE/Mage.json new file mode 100644 index 00000000..ed9fe005 --- /dev/null +++ b/agency-indexes/DoE/Mage.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Mage suite of tools provide access to DMS files and metadata.", + "laborHours": 25262.4, + "languages": [], + "name": "Mage", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Mage", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mags__Metagenomic_assembled_genomes__Mash.json b/agency-indexes/DoE/Mags__Metagenomic_assembled_genomes__Mash.json new file mode 100644 index 00000000..768ebbbe --- /dev/null +++ b/agency-indexes/DoE/Mags__Metagenomic_assembled_genomes__Mash.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "Search for similar sequences in metagenome-assembled genome sequences.", + "laborHours": 2249.6, + "languages": [], + "name": "Mags (Metagenomic assembled genomes) Mash", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/mags_mash", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MalGen.json b/agency-indexes/DoE/MalGen.json new file mode 100644 index 00000000..f7f4f6e6 --- /dev/null +++ b/agency-indexes/DoE/MalGen.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-03-30", + "metadataLastUpdated": "2024-09-10" + }, + "description": "MalGen is helper code that includes a script for loading data in format for PyTorch neural network models. It also includes example models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.\nSAND2021-3078 O", + "laborHours": 15.2, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "MalGen", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/malgen-behavior_labels", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Malcolm.json b/agency-indexes/DoE/Malcolm.json new file mode 100644 index 00000000..4e4708da --- /dev/null +++ b/agency-indexes/DoE/Malcolm.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2019-07-03", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Malcolm is a powerful, easily deployable network traffic analysis tool suite for full packet capture artifacts (PCAP files) and Zeek logs.", + "laborHours": 44885.6, + "languages": [], + "name": "Malcolm", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Malcolm", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MaltQt.json b/agency-indexes/DoE/MaltQt.json new file mode 100644 index 00000000..6eea78f1 --- /dev/null +++ b/agency-indexes/DoE/MaltQt.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-01-24", + "metadataLastUpdated": "2025-01-24" + }, + "description": "The code allows users to visualize data collected by the open source malt memory profiler. It is written in python and contains no physics whatsoever.", + "laborHours": 684.0, + "languages": [], + "name": "MaltQt", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/maltQT", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ManiPIO_-_Manipulate_Process_I_O.json b/agency-indexes/DoE/ManiPIO_-_Manipulate_Process_I_O.json new file mode 100644 index 00000000..6bc27371 --- /dev/null +++ b/agency-indexes/DoE/ManiPIO_-_Manipulate_Process_I_O.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "SAND2021-15053 O ManiPIO is a Python-based tool used to test Programmable Logic Controllers (PLCs), Industrial Control Systems (ICS), and ICS networks. It reads an input script to construct complex Events on ICS networks and uses the ModBus communication standard to communicate. Users can use ManiPIO to construct complex timelines of ICS communication events to simulate any number of network-based scenarios. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ManiPIO - Manipulate Process I/O", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SMARTT", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mantisa.json b/agency-indexes/DoE/Mantisa.json new file mode 100644 index 00000000..b9368387 --- /dev/null +++ b/agency-indexes/DoE/Mantisa.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2022-10-05" + }, + "description": "SAND2021-15050 O\nMantisa is an application programming interface (API) developed for a robotic hardware platform used to foster open collaboration with university partners. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Python3" + ], + "name": "Mantisa", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Many-Body_Adaptive_Configuration_Interaction_Suite__MACIS__v0.1.0.json b/agency-indexes/DoE/Many-Body_Adaptive_Configuration_Interaction_Suite__MACIS__v0.1.0.json new file mode 100644 index 00000000..fb1cabb3 --- /dev/null +++ b/agency-indexes/DoE/Many-Body_Adaptive_Configuration_Interaction_Suite__MACIS__v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "The Many-Body Adaptive Configuration Interaction Suite (MACIS) is a modern C++ software infrastructure for the development of selected-configuration interaction (sCI) methods for the fermionic many-body problem in quantum chemistry and materials science. MACIS provides a high-performance, parallel implementation of the Adaptive Sampling Configuration Interaction (ASCI) method as related solvers such as self-consistent orbital optimization and the evaluation of excited states and spectral functions. Unlike existing sCI software, MACIS is developed as a modular software infrastructure which allows it to exist both as a standalone sCI solver and as a library to integrate into existing many-body codes. This modularity allows MACIS to be quickly extensible, including its integration with other sCI methods and high-performance solvers.", + "laborHours": 18696.0, + "languages": [], + "name": "Many-Body Adaptive Configuration Interaction Suite (MACIS) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wavefunction91/MACIS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MapRE_GIS_Tools_&_Data__MapRE_.json b/agency-indexes/DoE/MapRE_GIS_Tools_&_Data__MapRE_.json new file mode 100644 index 00000000..92b15860 --- /dev/null +++ b/agency-indexes/DoE/MapRE_GIS_Tools_&_Data__MapRE_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2022-06-15" + }, + "description": "The MapRE (Multi-criteria Analysis for Planning Renewable Energy) GIS (Geographic Information Systems) Tools are a set of ArcGIS tools to a) conduct site suitability analysis for wind and solar resources using inclusion and exclusion criteria, and create resource maps, b) create project opportunity areas and compute various attributes such as cost, distances to existing and planned infrastructure. and environmental impact factors; and c) calculate and update various attributes for already processed renewable energy zones. In addition, MapRE data sets are geospatial data of renewable energy project opportunity areas and zones with pre-calculated attributes for several countries. These tools and data are available at mapre.lbl.gov.", + "homepageURL": "http://mapre.lbl.gov", + "laborHours": 0.0, + "languages": [], + "name": "MapRE GIS Tools & Data (MapRE)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://mapre.lbl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MapReduceXMT_v._Beta_0.1.json b/agency-indexes/DoE/MapReduceXMT_v._Beta_0.1.json new file mode 100644 index 00000000..48d1e01b --- /dev/null +++ b/agency-indexes/DoE/MapReduceXMT_v._Beta_0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The MapReduceXMT library ports the MapReduce framework onto the Cray XMT. 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The MapReduceXMT implements the key aspects of MapReduce for the Cray XMT, a massively threaded system that is inherently difficult to program. MapReduceXMT allows users to utilize the machine effectively and efficiently without extensive training in multi-threaded programming.", + "laborHours": 0.0, + "languages": [], + "name": "MapReduceXMT v. Beta 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/map-reduce-xmt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MapReduce_MPI_library__MR-MPI__v._1.0.json b/agency-indexes/DoE/MapReduce_MPI_library__MR-MPI__v._1.0.json new file mode 100644 index 00000000..0623bf92 --- /dev/null +++ b/agency-indexes/DoE/MapReduce_MPI_library__MR-MPI__v._1.0.json @@ -0,0 +1,40 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The MapReduce MPI library is a software tool for performing MapReduce operations on a distributed memory parallel computer via message passing (MPI). These are data-processing or computational operations which achieve parallelism by breaking a large task into two stages, a map and a reduce . Each of these are formulated as simple on-processor functions which the user can easily write. The library assigns independent tasks to processors and performs the parallel data movement and transformations behind the scenes.", + "laborHours": 13315.2, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "HTML", + "Python", + "Odin" + ], + "name": "MapReduce MPI library (MR-MPI) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mapreduce", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mapdfn.py.json b/agency-indexes/DoE/Mapdfn.py.json new file mode 100644 index 00000000..250dcbdb --- /dev/null +++ b/agency-indexes/DoE/Mapdfn.py.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-04", + "metadataLastUpdated": "2021-05-05" + }, + "description": "SAND2021-4824 O mapdfn.py takes the output of dfnWorks describing a discrete fracture network (DFN) and converts the DFN to an equivalent porous medium representation. This is done by looping through cells in a 3-D model domain, tagging those intersected by fractures, and calculating effective properties. Coordinate transformations are imported from an open source script (transformations.py) developed at the University of California. An associated driver script, mapdfn2pflotran.py, calls the functions in mapdfn.py and writes the mapdfn.py output to hdf5 files for use with PFLOTRAN. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-4824 O", + "laborHours": 0.0, + "languages": [ + "Python3" + ], + "name": "Mapdfn.py", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/pflotran/mapdfn/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mappymatch_FKA:_YAMM__Yet_Another_Map-Matcher__[SWR_22-38]_.json b/agency-indexes/DoE/Mappymatch_FKA:_YAMM__Yet_Another_Map-Matcher__[SWR_22-38]_.json new file mode 100644 index 00000000..7b28313f --- /dev/null +++ b/agency-indexes/DoE/Mappymatch_FKA:_YAMM__Yet_Another_Map-Matcher__[SWR_22-38]_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-04-12", + "metadataLastUpdated": "2023-08-17" + }, + "description": "A surprisingly non-trivial technical challenge is to associate points in space (e.g., GPS data) with specific segments of a road network or map. The software package ( allows users to match GPS point data to a road network (commonly known as \"map matching\"). The software is designed such that a user could match a set of GPS points to a variety of different road network representations using a variety of map matching algorithms. There are currently several \"built-in\" road networks and map matching algorithms but the software has been designed to enable new ones to be added with minimal overhead.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Mappymatch FKA: YAMM (Yet Another Map-Matcher) [SWR 22-38] ", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/yamm", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mappymatch_[SWR_22-38].json b/agency-indexes/DoE/Mappymatch_[SWR_22-38].json new file mode 100644 index 00000000..35430d28 --- /dev/null +++ b/agency-indexes/DoE/Mappymatch_[SWR_22-38].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-15" + }, + "description": "Mappymatch is a pure-python package developed and open sourced by the National Renewable Energy Laboratory. It contains a collection of \"Matchers\" that enable matching a GPS trace (series of GPS coordinates) to a map.\n\nAs of 8/14/2023, The current matchers are:\n\nLCSSMatcher: A matcher that implements the LCSS algorithm described in this paper. Works best with high resolution GPS traces.\n\nOsrmMatcher: A light matcher that pings an OSRM server to request map matching results. See the official documentation for more info.\n\nValhallaMatcher: A matcher to ping a Valhalla server for map matching results.\nCurrently supported map formats are:\n\nOpen Street Maps\n\nNOTE: This software was formerly known as YAMM (Yet Another Map-Matcher)", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Mappymatch [SWR 22-38]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mappymatch", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.4.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MarFS,_Version_1.json b/agency-indexes/DoE/MarFS,_Version_1.json new file mode 100644 index 00000000..e031c65e --- /dev/null +++ b/agency-indexes/DoE/MarFS,_Version_1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2020-06-01" + }, + "description": "There is a sea (mar is Spanish for sea) of data out there that needs to be handled efficiently. Object Stores are filling the hole of managing large amounts of data efficiently. However, in many cases, and our HPC case in particular, we need a traditional file (POSIX) interface to this data as HPC I/O models have not moved to object interfaces, such as Amazon S3, CDMI, etc.Eventually Object Store providers may deliver file interfaces to their object stores, but at this point those interfaces are not ready to do the job that we need done. MarFS will glue together two existing scalable components: a file system's scalable metadata component that provides the file interface; and existing scalable object stores (from one or more providers). There will be utilities to do work that is not critical to be done in real-time so that MarFS can manage the space used by objects and allocated to individual users.", + "laborHours": 10244.8, + "languages": [], + "name": "MarFS, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mar-file-system/marfs", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Marble_MMC_v1.0.json b/agency-indexes/DoE/Marble_MMC_v1.0.json new file mode 100644 index 00000000..613d79e4 --- /dev/null +++ b/agency-indexes/DoE/Marble_MMC_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-22", + "metadataLastUpdated": "2021-07-22" + }, + "description": "Software toolchain to program the MMC on Marble boards", + "laborHours": 0.0, + "languages": [], + "name": "Marble MMC v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/Marble-MMC.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Margo_Microservice_Template.json b/agency-indexes/DoE/Margo_Microservice_Template.json new file mode 100644 index 00000000..7152ad04 --- /dev/null +++ b/agency-indexes/DoE/Margo_Microservice_Template.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-31", + "metadataLastUpdated": "2022-01-31" + }, + "description": "This project is a template to start developing a Mochi microservice based on Margo.", + "laborHours": 0.0, + "languages": [], + "name": "Margo Microservice Template", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/margo-microservice-template/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/margo-microservice-template", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Marmot.json b/agency-indexes/DoE/Marmot.json new file mode 100644 index 00000000..db815254 --- /dev/null +++ b/agency-indexes/DoE/Marmot.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-09-09", + "metadataLastUpdated": "2021-09-09" + }, + "description": "Marmot is a data formatting and visualization tool for production cost modelling results. It provides an efficient way to view PLEXOS production cost modeling results quickly, while also creating publication ready figures and data tables.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Marmot", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Marmot", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.7.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Masked_Language_Molecules.json b/agency-indexes/DoE/Masked_Language_Molecules.json new file mode 100644 index 00000000..4bd32794 --- /dev/null +++ b/agency-indexes/DoE/Masked_Language_Molecules.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gounleyjp@ornl.gov" + }, + "date": { + "created": "2022-05-19", + "metadataLastUpdated": "2022-05-19" + }, + "description": "Many scientific problems, such as drug design, involve exploring chemical space to identify molecules with specific properties. However, current rule-based and machine learning models for this purpose are limited in how efficiently and effectively they can do this. In Masked Language Molecules (MLMol), we used masked language modeling from natural language processing to learn motifs of chemical sequences and how they relate to certain chemical properties.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Masked Language Molecules", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/candle/mlmol", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mass_Spectrometry_Imaging_Quick_View.json b/agency-indexes/DoE/Mass_Spectrometry_Imaging_Quick_View.json new file mode 100644 index 00000000..2b6dcd7b --- /dev/null +++ b/agency-indexes/DoE/Mass_Spectrometry_Imaging_Quick_View.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "MSI QuickView is a software designed to provide a graphical user interface (GUI) for greatly speeding up experimental feedback (visualization and analysis) of mass spectrometry imaging (MSI or IMS) data during data acquisition. Often different software loads the entire data set, i.e., all lines of data into computer memory (RAM). This causes out of memory errors for larger datasets. We solved this in MSI QuickView by reading in the data one line at a time. Only the required information (e.g. the final pixel values for that line of heat map) is maintained in RAM. Interim analysis options include the mean intensity vs. m/z spectrum, intensity vs. time spectrums for up to 6 different m/z values or ranges chosen by the user and heat maps for each line. This assists in validating the usefulness of the particular experiment after scanning the first few lines. In addition, the tool facilitates further processing and analysis of the massive datasets. The user can manually pick different m/z values, time ranges, scroll through the spectra for any line in the data without having to load it in manually, save multiple images, change aspect ratios for the heat maps, and process the heat maps in multiple ways including overlaying images at different m/z values, displaying up to 9 different heat maps, alignment of scans along each line etc. There is no manipulation of the data required by the user to visualize the data.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "MATLAB, Java" + ], + "name": "Mass Spectrometry Imaging Quick View", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Massively_Parallel_and_Portable_Genomic_Sequence_Analysis.json b/agency-indexes/DoE/Massively_Parallel_and_Portable_Genomic_Sequence_Analysis.json new file mode 100644 index 00000000..9f82cf29 --- /dev/null +++ b/agency-indexes/DoE/Massively_Parallel_and_Portable_Genomic_Sequence_Analysis.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-14", + "metadataLastUpdated": "2021-12-16" + }, + "description": "Massively Parallel and Portable Genomic Sequence Analysis (mappgene) is a sequencing analysis workflow for high performance computing. It incorporates novel technologies to simplify and accelerate genetics research.", + "laborHours": 0.0, + "languages": [], + "name": "Massively Parallel and Portable Genomic Sequence Analysis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mappgene", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Master_of_Servers__MOSE__v._1.0.0.json b/agency-indexes/DoE/Master_of_Servers__MOSE__v._1.0.0.json new file mode 100644 index 00000000..672d5065 --- /dev/null +++ b/agency-indexes/DoE/Master_of_Servers__MOSE__v._1.0.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-05-28", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This tool helps red teamers and penetration testers to conduct post exploitation activities through various Configuration Management tools such as Puppet, Chef, Ansible, and Salt.", + "laborHours": 1109.6, + "languages": [], + "name": "Master of Servers (MOSE) v. 1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mose", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mastodon.json b/agency-indexes/DoE/Mastodon.json new file mode 100644 index 00000000..6d9d4039 --- /dev/null +++ b/agency-indexes/DoE/Mastodon.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2023-03-15" + }, + "description": "MASTODON has the capability to model stochastic nonlinear soil-structure interaction (NLSSI) in a dynamic probabilistic risk assessment framework. The NLSSI simulations include structural dynamics, time integration, dynamic porous media flow, nonlinear hysteretic soil constitutive models, geometric nonlinearities (gapping, sliding, and uplift). MASTODON is also the MOOSE based master application for dynamic PRA of external hazards.", + "laborHours": 28287.2, + "languages": [ + "C++" + ], + "name": "Mastodon", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/mastodon", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "Revision 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mat2exo.json b/agency-indexes/DoE/Mat2exo.json new file mode 100644 index 00000000..e8638a36 --- /dev/null +++ b/agency-indexes/DoE/Mat2exo.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "MAT2EXO is a program which translates mesh data from Matlab mat-file format to Exodus II format. This tool is the inverse of the commonly used tool exo2mat which translates Exodus II data to the Matlab mat-file format. These tools provide a means for preprocessing an Exodus II model file or postprocessing an Exodus II results file using Matlab", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "Mat2exo", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.6" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MatLab_Package_for_Whispering_Gallery_Mode_Data.json b/agency-indexes/DoE/MatLab_Package_for_Whispering_Gallery_Mode_Data.json new file mode 100644 index 00000000..27a98482 --- /dev/null +++ b/agency-indexes/DoE/MatLab_Package_for_Whispering_Gallery_Mode_Data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-06-15", + "metadataLastUpdated": "2022-06-15" + }, + "description": "Dye-doped whispering gallery mode resonator (WGMR) microspheres yield highly structured emission spectra that are extremely sensitive to their environment and are of intense interest for use in a variety of sensing applications. Efforts to leverage the unique sensitivities of WGMRs have relied on stringent experimental requirements to correlate specific spectral shifts/changes to an analyte/stimulus such as 1) precise positional knowledge, 2) reference spectra for each microsphere, and 3) high mechanical stability. Consequently, these can hinder adequate mixing or incorporation of analytes and creates challenges for remote sensing. The MATLAB codes provided here are to be used in conjunction with a continuous flow technique for measuring WGM spectra of dye-doped microspheres suspended in solution. One MATLAB script, smooths the data, automatically baseline corrects it to isolate the whispering gallery modes (WGM) from the unwanted bulk emission, and assesses the similarity of each spectrum to aid in selecting a set of unique WGM spectra for further analysis. The next script is designed to analyze WGM spectra to determine the size of the resonator and the refractive index (RI) of its local environment without a priori knowledge of the individual microsphere. The final script allows the user to cluster spheres based on the product of their RI and radius and the contrast ratio of the RI of the sphere material and that of its environment by using a shared nearest neighbor spectral clustering algorithm.", + "laborHours": 0.0, + "languages": [], + "name": "MatLab Package for Whispering Gallery Mode Data", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/WhisperingGalleryModeResonatorDataWU", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MatMCNP_v._4.0.json b/agency-indexes/DoE/MatMCNP_v._4.0.json new file mode 100644 index 00000000..a18c6f34 --- /dev/null +++ b/agency-indexes/DoE/MatMCNP_v._4.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-01-24", + "metadataLastUpdated": "2024-07-26" + }, + "description": "https://www.osti.gov/doecMatMCNP is a code for generating material cards for the MCNP radiation transport code. The program allows for material specification as either atomic or weight percent (fractions). MatMCNP also permits the specification of enriched lithium, boron, and/or uranium. In addition to producing the material cards for MCNP, the code calculates the atomic (or number) density in atoms/barn-cm as well as the multiplier that should be used to convert neutron and gamma fluences into dose in the material specified.", + "laborHours": 4544.8, + "languages": [ + "Fortran", + "Python" + ], + "name": "MatMCNP v. 4.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MatMCNP", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 4.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Material_Accountancy_Performance_Indicator_Toolkit.json b/agency-indexes/DoE/Material_Accountancy_Performance_Indicator_Toolkit.json new file mode 100644 index 00000000..07be791d --- /dev/null +++ b/agency-indexes/DoE/Material_Accountancy_Performance_Indicator_Toolkit.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-13", + "metadataLastUpdated": "2021-06-28" + }, + "description": "The MAPIT - Material Accountancy Performance Indicator Toolkit includes statistical tests and calculations based on open literature that calculate safeguards metrics. The tool can be used with user supplied datasets or with the several included datasets which are generated from models that are maintained at Sandia National Laboratories. The models are not included with the software. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-0467 O", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Material Accountancy Performance Indicator Toolkit", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MAPIT", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Materials_Informatics_ChemVis.json b/agency-indexes/DoE/Materials_Informatics_ChemVis.json new file mode 100644 index 00000000..939fc048 --- /dev/null +++ b/agency-indexes/DoE/Materials_Informatics_ChemVis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-16" + }, + "description": "A Browser-based visualization of morphology, material, and chemical data extracted from chemical papers. This UI is focused for specifically nanomaterial synthesis papers. The visual analytic environment allows the user to explore a large number of papers quickly, through an interactive, intuitive, and visual way that helps see possible trends in the data. This exploration-oriented systems allows domain experts who may not have an extensive background in writing analysis code or database queries to easily express their idea to experiment on the data and view the results.\nThe visualization software requires the data in JSON format. The data packaged with the software is the result of 35k nanomaterial synthesis papers queried from Elsevier, created through a separate software pipeline. The data contains information such as the title, authors, chemicals, and created material and morphology.", + "laborHours": 2773893.6, + "languages": [], + "name": "Materials Informatics ChemVis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MI-ChemVis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MathOptAI.jl.json b/agency-indexes/DoE/MathOptAI.jl.json new file mode 100644 index 00000000..09b638da --- /dev/null +++ b/agency-indexes/DoE/MathOptAI.jl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Optimization and Machine Learning Toolbox-Embed trained machine learning predictors in JuMP", + "laborHours": 2857.6, + "languages": [], + "name": "MathOptAI.jl", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/MathOptAI.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Matlab-Excel_Interface_for_OpenDSS.json b/agency-indexes/DoE/Matlab-Excel_Interface_for_OpenDSS.json new file mode 100644 index 00000000..2e8c3f32 --- /dev/null +++ b/agency-indexes/DoE/Matlab-Excel_Interface_for_OpenDSS.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The software allows users of the OpenDSS grid modeling software to access their load flow models using a GUI interface developed in MATLAB. The circuit definitions are entered into a Microsoft Excel spreadsheet which makes circuit creation and editing a much simpler process than the basic text-based editors used in the native OpenDSS interface. Plot tools have been developed which can be accessed through a MATLAB GUI once the desired parameters have been simulated.", + "homepageURL": "https://sourceforge.net/projects/electricdss", + "laborHours": 0.0, + "languages": [ + "MATLAB, Delphi (http://www.embarcadero.com), currently version Delphi XE2, Free Pascal" + ], + "name": "Matlab-Excel Interface for OpenDSS", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sourceforge.net/p/electricdss/code/HEAD/tree/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/electricdss", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Matlab_Cluster_Ensemble_Toolbox.json b/agency-indexes/DoE/Matlab_Cluster_Ensemble_Toolbox.json new file mode 100644 index 00000000..b069c66e --- /dev/null +++ b/agency-indexes/DoE/Matlab_Cluster_Ensemble_Toolbox.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "This is a Matlab toolbox for investigating the application of cluster ensembles to data classification, with the objective of improving the accuracy and/or speed of clustering. The toolbox divides the cluster ensemble problem into four areas, providing functionality for each. These include, (1) synthetic data generation, (2) clustering to generate individual data partitions and similarity matrices, (3) consensus function generation and final clustering to generate ensemble data partitioning, and (4) implementation of accuracy metrics. With regard to data generation, Gaussian data of arbitrary dimension can be generated. The kcenters algorithm can then be used to generate individual data partitions by either, (a) subsampling the data and clustering each subsample, or by (b) randomly initializing the algorithm and generating a clustering for each initialization. In either case an overall similarity matrix can be computed using a consensus function operating on the individual similarity matrices. A final clustering can be performed and performance metrics are provided for evaluation purposes.", + "homepageURL": "https://www.mathworks.com/matlabcentral/fileexchange/23941-matlab-cluster-ensemble-toolbox", + "laborHours": 0.0, + "languages": [], + "name": "Matlab Cluster Ensemble Toolbox", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.mathworks.com/matlabcentral/fileexchange/23941-matlab-cluster-ensemble-toolbox", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.mathworks.com/matlabcentral/fileexchange/23941-matlab-cluster-ensemble-toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Matlab_Code_for_Multiscale_Topology_Optimization.json b/agency-indexes/DoE/Matlab_Code_for_Multiscale_Topology_Optimization.json new file mode 100644 index 00000000..a2cde181 --- /dev/null +++ b/agency-indexes/DoE/Matlab_Code_for_Multiscale_Topology_Optimization.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-17" + }, + "description": "This Matlab script implements a simple topology optimization algorithm that minimizes the compliance of a structure within a 3D prismatic design domain. \n\nIt uses a simple linear elastic finite element solver to solve the equilibrium equations, and the optimality criterion (00) method to update the design iteratively.\n\nThis functionality is identical to, or the simplest possible extension from 2D to 3D of, a 99-line Matlab code released in 2001 in a journal article by Sigmund. \n\nWhat is new in this code is our implementation of simple surrogate models for several truss micro-architectures, which converts this code to a multiscale design tool, whereas the original code is single-scale. \n\nThe development of these surrogate models and their implementation is described in a journal article we intend to submit. \n\nWe plan to include the full source code in an Appendix in this paper. \n\nThe code\u2019s primary function is as a pedagogical tool rather than as a finished software product. \n\nSigmund\u2019s 2001 paper describes the implementation line-by-line.\n\nWe are including this updated version of the code to allow the reader to understand exactly what changes must be made to a \u201cstandard\u201d topology optimization code to implement the surrogate models and thus multiscale design optimization.", + "laborHours": 91.2, + "languages": [ + "MATLAB" + ], + "name": "Matlab Code for Multiscale Topology Optimization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MultiscaleTopOpt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Matrix-based_Omnidirectional_Pressure_Integratio.json b/agency-indexes/DoE/Matrix-based_Omnidirectional_Pressure_Integratio.json new file mode 100644 index 00000000..73ed39a4 --- /dev/null +++ b/agency-indexes/DoE/Matrix-based_Omnidirectional_Pressure_Integratio.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This software enables the calculation of the pressure field based on experimental velocity measurements utilizing the matrix-based omnidirectional pressure integration algorithm developed by Dr. John Charonko and Dr. Fernando Zigunov, which is several orders of magnitude faster than the current state of the art.", + "laborHours": 2401.6, + "languages": [], + "name": "Matrix-based Omnidirectional Pressure Integratio", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pressure-osmosis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Matrix_Models_for_ROSS.json b/agency-indexes/DoE/Matrix_Models_for_ROSS.json new file mode 100644 index 00000000..2fd0293a --- /dev/null +++ b/agency-indexes/DoE/Matrix_Models_for_ROSS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-01-31", + "metadataLastUpdated": "2019-02-01" + }, + "description": "These models demonstrate the usage of the LLNL-modified ROSS, including the time class, LP interface, and event cancellation.", + "laborHours": 486.4, + "languages": [], + "name": "Matrix Models for ROSS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ross-matrix-models", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Matrix_and_Array__MATAR__Library.json b/agency-indexes/DoE/Matrix_and_Array__MATAR__Library.json new file mode 100644 index 00000000..390ccdff --- /dev/null +++ b/agency-indexes/DoE/Matrix_and_Array__MATAR__Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "MATAR is a C++ software library to allow developers to easily create and use dense and sparse data representations that are also portable across disparate architectures using Kokkos.", + "laborHours": 0.0, + "languages": [], + "name": "Matrix and Array (MATAR) Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MATAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Maximum_Switching_Throughput_Density_Estimator.json b/agency-indexes/DoE/Maximum_Switching_Throughput_Density_Estimator.json new file mode 100644 index 00000000..00947016 --- /dev/null +++ b/agency-indexes/DoE/Maximum_Switching_Throughput_Density_Estimator.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-15", + "metadataLastUpdated": "2024-10-15" + }, + "description": "SAND2024-11125O\nThe Maximum Switching Throughput Density Estimator software performs a simple analysis that estimates the maximum logic switching throughput density that\u2019s achieved in various CMOS technology nodes on the International Roadmap for Devices and Systems. This software utilizes simple device models and optimization techniques, performing a simple sweep over a range of possible logic supply voltages, and analytically calculating the maximum switching frequency for the given logic voltage that meets the power density constraint. It does this by using simple models of power dissipation in conventional and fully adiabatic switching. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 167.2, + "languages": [ + "MATLAB" + ], + "name": "Maximum Switching Throughput Density Estimator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/max-cmos-throughput", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v.0.15w (beta) script version" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mbin_v1.0.json b/agency-indexes/DoE/Mbin_v1.0.json new file mode 100644 index 00000000..db3d6d4d --- /dev/null +++ b/agency-indexes/DoE/Mbin_v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-06", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The Mbin software, is a software toolkit that implements the IMG metagenome binning pipeline. The software allows the user to process input metagenome contigs, and produces metagenome assembled genomes (metagenome bins) and valuation metrics per bin including completion and contamination estimates, quality assignment, predicted lineage and eukaryotic potential. It is currently packed as a portable docker container and provides the advantage of running the process of binning and analysis of the bins generated, using a suite of tools run sequentially with controls in place to capture errors and optional arguments to run a modified version depending on individual needs and capabilities.", + "laborHours": 0.0, + "languages": [], + "name": "Mbin v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/metagenome-science-program/mbin-docker", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mcqueuer.json b/agency-indexes/DoE/Mcqueuer.json new file mode 100644 index 00000000..ca3c70d1 --- /dev/null +++ b/agency-indexes/DoE/Mcqueuer.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Mcqueuer is a simple tool that allows anyone from researchers to experienced developers to create multi-node/multi-core jobs by simply creating a file with a list of commands. Users simply combine tasks, which would otherwise each be their own job on the cluster, into a single file that is given to Mcqueuer. Mcqueuer then does the heavy lifting required to process the tasks in parallel in a single multi-node job. In addition, Mcqueuer provides load-balancing, which frees the user from having to worry about complex memory and CPU considerations, and instead focus on the processing itself.", + "laborHours": 198785.6, + "name": "Mcqueuer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/aaronrphillips/mcqr/blob/master/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aaronrphillips/mcqr", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Media_Compiler_v1.0.json b/agency-indexes/DoE/Media_Compiler_v1.0.json new file mode 100644 index 00000000..3225b24b --- /dev/null +++ b/agency-indexes/DoE/Media_Compiler_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-09-03", + "metadataLastUpdated": "2024-09-19" + }, + "description": "This software is used in a media optimization pipeline. It is used to calculate stock concentrations, volumes and instructions for the liquid handler used in ESE (Biomek NX-S8).", + "laborHours": 341969.6, + "languages": [], + "name": "Media Compiler v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/media_compiler", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Medium_and_Heavy-Duty_Electric_Vehicle_Infrastructure_-_Load_Operations_and_Deployment__HEVI-LOAD__v1.0.json b/agency-indexes/DoE/Medium_and_Heavy-Duty_Electric_Vehicle_Infrastructure_-_Load_Operations_and_Deployment__HEVI-LOAD__v1.0.json new file mode 100644 index 00000000..288280cc --- /dev/null +++ b/agency-indexes/DoE/Medium_and_Heavy-Duty_Electric_Vehicle_Infrastructure_-_Load_Operations_and_Deployment__HEVI-LOAD__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-12-07", + "metadataLastUpdated": "2021-12-20" + }, + "description": "In order to support the California state goals to reduce the carbon and pollution emissions (AB2127), The goal of this project (HEVI-Pro) is to project the charging infrastructure needs by future medium- and heavy- duty electric vehicles, and assess optimal deployment the infrastructure in California and provide grid impacts analysis. The MHDV projections will also consider transportation system and electric system interaction with light duty vehicles. The project consists of 2 approaches in general: top-down approach that takes aggregated MHDV adoptions as the inputs and provide the county-level projections of charging load profile and infrastructure need, and the bottom-up approach that that incorporates more granular (temporal, spatial and duty-cycle-specific) behaviors of a variety of MHDVs into activity simulations/optimizations for further analysis.", + "homepageURL": "https://sites.google.com/lbl.gov/2020-157/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Medium and Heavy-Duty Electric Vehicle Infrastructure - Load Operations and Deployment (HEVI-LOAD) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2020-157/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2020-157/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Megatux.json b/agency-indexes/DoE/Megatux.json new file mode 100644 index 00000000..57e9ec37 --- /dev/null +++ b/agency-indexes/DoE/Megatux.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The Megatux platform enables the emulation of large scale (multi-million node) distributed systems. In particular, it allows for the emulation of large-scale networks interconnecting a very large number of emulated computer systems. It does this by leveraging virtualization and associated technologies to allow hundreds of virtual computers to be hosted on a single moderately sized server or workstation. Virtualization technology provided by modern processors allows for multiple guest OSs to run at the same time, sharing the hardware resources. The Megatux platform can be deployed on a single PC, a small cluster of a few boxes or a large cluster of computers. With a modest cluster, the Megatux platform can emulate complex organizational networks. By using virtualization, we emulate the hardware, but run actual software enabling large scale without sacrificing fidelity.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C/Python" + ], + "name": "Megatux", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MelMACCS_ver._2.0.2.json b/agency-indexes/DoE/MelMACCS_ver._2.0.2.json new file mode 100644 index 00000000..3218d7b4 --- /dev/null +++ b/agency-indexes/DoE/MelMACCS_ver._2.0.2.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2018-09-07" + }, + "description": "MelMACCS is the interface tool that allows MELCOR plot files to be post processed to create MACCS source term data that can be imported directly into WinMACCS", + "homepageURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "laborHours": 0.0, + "languages": [ + "Visual Basic" + ], + "name": "MelMACCS ver. 2.0.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrc.gov/about-nrc/regulatory/research/obtainingcodes.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Melodee_.json b/agency-indexes/DoE/Melodee_.json new file mode 100644 index 00000000..481a22a4 --- /dev/null +++ b/agency-indexes/DoE/Melodee_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Melodee (Modular Expression Language for Ordinary Differential Equation Editing) is a new language for ODE modeling and development. It has been designed to make it easy for domain experts to write modular equation systems. Using a familiar Matlab-like syntax, modelers can describe their systems of interests and combine them in new and novel ways at run time. Existing models can easily be converted to MELODEE because of its familiar semantics and syntax.\n", + "laborHours": 2325.6, + "languages": [], + "name": "Melodee ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/melodee", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MemAxes.json b/agency-indexes/DoE/MemAxes.json new file mode 100644 index 00000000..545963e9 --- /dev/null +++ b/agency-indexes/DoE/MemAxes.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "MemAxes is a tool for visualizing memory access samples acquired by load/store sampling mechanisms like Intel PEBS or AMD IBS. It allows a user to view the data projected into various domains; specifically, the layout of the hardware resources, the code/variables, the dataset domain, and parallel coordinates.\n", + "laborHours": 5198.4, + "languages": [], + "name": "MemAxes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MemAxes", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MemAxes_Visualization_Software.json b/agency-indexes/DoE/MemAxes_Visualization_Software.json new file mode 100644 index 00000000..9dff9704 --- /dev/null +++ b/agency-indexes/DoE/MemAxes_Visualization_Software.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Hardware advancements such as Intel's PEBS and AMD's IBS, as well as software developments such as the perf_event API in Linux have made available the acquisition of memory access samples with performance information. MemAxes is a visualization and analysis tool for memory access sample data. By mapping the samples to their associated code, variables, node topology, and application dataset, MemAxes provides intuitive views of the data.", + "laborHours": 5198.4, + "name": "MemAxes Visualization Software", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/scalability-llnl/MemAxes", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MemLeap_GPU_Memory_Profiler.json b/agency-indexes/DoE/MemLeap_GPU_Memory_Profiler.json new file mode 100644 index 00000000..63a043b6 --- /dev/null +++ b/agency-indexes/DoE/MemLeap_GPU_Memory_Profiler.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-09-13" + }, + "description": "MemLeap is a GPU Memory Profiler built atop Nvbit (NVidia Binary Instrumentation Tool) framework. It\nanalyzes memory accesses to memory objects in GPU memory, including Unified Memory, to optimize\nmemory usage and reveal performance bottlenecks.", + "laborHours": 0.0, + "languages": [], + "name": "MemLeap GPU Memory Profiler", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IBPeng/memleap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MemSurfer.json b/agency-indexes/DoE/MemSurfer.json new file mode 100644 index 00000000..24d26348 --- /dev/null +++ b/agency-indexes/DoE/MemSurfer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-18" + }, + "description": "MemSurfer is a software tool to compute bilayer membrane surfaces. These surfaces are found in the biophysical simulations, and generally analyzed using a set of python packages. MemSurfer offers new robust functionalities to compute the undulations in the surfaces, and relevant properties of the lipids *along* the surface, rather than along the projections, as done in many existing tools.", + "laborHours": 4088.8, + "languages": [], + "name": "MemSurfer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MemSurfer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Memento_Protocol_Validator_Software.json b/agency-indexes/DoE/Memento_Protocol_Validator_Software.json new file mode 100644 index 00000000..ae91aa57 --- /dev/null +++ b/agency-indexes/DoE/Memento_Protocol_Validator_Software.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "The Memento Protocol Validator software provides a suite of tools to validate compliance with the Memento protocol. The Memento protocol is an interoperability solution for accessing web archiving information with the DateTime dimension.", + "laborHours": 0.0, + "languages": [], + "name": "Memento Protocol Validator Software", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/memento-validator", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Memento_Tracer_Extension.json b/agency-indexes/DoE/Memento_Tracer_Extension.json new file mode 100644 index 00000000..7e0e481e --- /dev/null +++ b/agency-indexes/DoE/Memento_Tracer_Extension.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-06-15", + "metadataLastUpdated": "2022-06-15" + }, + "description": "This browser extension records a user's interactions with a webpage so that it can be applied during the selective crawling of similar classes of webpages. This extension currently supports Chrome Browser only. The navigation steps (or trace) captured in JSON format.", + "laborHours": 0.0, + "languages": [], + "name": "Memento Tracer Extension", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Memento-Tracer-Extention", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Memory_Analysis_Tool.json b/agency-indexes/DoE/Memory_Analysis_Tool.json new file mode 100644 index 00000000..fdbefc6c --- /dev/null +++ b/agency-indexes/DoE/Memory_Analysis_Tool.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-03-03", + "metadataLastUpdated": "2020-03-03" + }, + "description": "This tool traces all memory accesses to stack (static allocation) and heap (dynamic allocation) on a trace run in a particular hardware and then estimates execution time on given arbitrary hardware configurations for hardware design space exploration.\n\nIt can also compute memory access statistics, such as reuse distance.", + "laborHours": 6353.6, + "languages": [], + "name": "Memory Analysis Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MenuFramework.json b/agency-indexes/DoE/MenuFramework.json new file mode 100644 index 00000000..103d8785 --- /dev/null +++ b/agency-indexes/DoE/MenuFramework.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-09-01", + "metadataLastUpdated": "2021-09-21" + }, + "description": "The Menu Framework is a reusable Extended Reality multi-level menu system for the Unity Development Platform. The menu structure is architected for reusability to suit whatever need the developer may have for a multi-level, reusable menu framework. Menu Framework's architecture, GUI, and functionality are based on the paper \"Extended Reality for Enhanced Training and Knowledge Capture\" (SAND2020-2361C). This tool uses the Microsoft Mixed Reality ToolKit (MRTK) built in functionality to provide a suite of functionalities including bounding box, follow me, minimize, maximize, settings, and help commands. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1507 O", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "MenuFramework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MenuFramework", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Meraculous2.json b/agency-indexes/DoE/Meraculous2.json new file mode 100644 index 00000000..0aed3068 --- /dev/null +++ b/agency-indexes/DoE/Meraculous2.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "meraculous2 is a whole genome shotgun assembler for short-reads that is capable of assembling large, polymorphic genomes with modest computational requirements. Meraculous relies on an efficient and conservative traversal of the subgraph of the k-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. Additional features include (1) handling of allelic variation using \"bubble\" structures within the deBruijn graph, (2) gap closing of repetitive and low quality regions using localized assemblies, and (3) an improved scaffolding algorithm that produces more complete assemblies without compromising on scaffolding accuracy", + "homepageURL": "https://sourceforge.net/projects/meraculous20", + "laborHours": 0.0, + "languages": [ + "GCC g++>=4.63" + ], + "name": "Meraculous2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/meraculous20", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mercat.json b/agency-indexes/DoE/Mercat.json new file mode 100644 index 00000000..0678b363 --- /dev/null +++ b/agency-indexes/DoE/Mercat.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Mercat is a highly scalable property software package for robust of analysis of features in next-generation sequencing data and observed unique peptides from metaproteomic data. Mercat is offered in python 3.5/anaconda3, is multiparellel and is easily installed using bioconda/conda recipes. Mercat inputs include assembled contigs, raw sequence reads from any platform, and unique peptide files obtained from proteomics with feature abundance counts tables. Mercat is the only software available that allows for direct analysis of data properties without a data-dependent search tools such as BLAST or diamond for compositional analysis of whole community shotgun sequencing (e.g. metagenomes and/or metatranscriptomes) or metaproteomic data.", + "laborHours": 380.0, + "name": "Mercat", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/mercat/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mercat", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mercury.json b/agency-indexes/DoE/Mercury.json new file mode 100644 index 00000000..ca396e79 --- /dev/null +++ b/agency-indexes/DoE/Mercury.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "Mercury is a C library for implementing RPC, optimized for HPC.", + "laborHours": 36449.6, + "languages": [], + "name": "Mercury", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mercury-hpc/mercury/blob/master/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mercury-hpc/mercury", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mercury_Metadata_Toolset.json b/agency-indexes/DoE/Mercury_Metadata_Toolset.json new file mode 100644 index 00000000..40746475 --- /dev/null +++ b/agency-indexes/DoE/Mercury_Metadata_Toolset.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "Mercury is a federated metadata harvesting, search and retrieval tool based on both open source software and software developed at Oak Ridge National Laboratory. It was originally developed for NASA, and the Mercury development consortium now includes funding from NASA, USGS, and DOE. A major new version of Mercury (version 3.0) was developed during 2007 and released in early 2008. This Mercury 3.0 version provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS delivery of search results, and ready customization to meet the needs of the multiple projects which use Mercury. For the end users, Mercury provides a single portal to very quickly search for data and information contained in disparate data management systems. It collects metadata and key data from contributing project servers distributed around the world and builds a centralized index. The Mercury search interfaces then allow the users to perform simple, fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data.", + "homepageURL": "https://cocatalog.loc.gov/cgi-bin/Pwebrecon.cgi?v1=1&ti=1,1&Search%5FArg=Mercury%20Metadata%20Data%20Management%20System&Search%5FCode=TALL&CNT=10&PID=iA_S84JMRUP_sLczQjkpAJv8Ce2k&SEQ=20220427154213&SID=2", + "laborHours": 0.0, + "languages": [], + "name": "Mercury Metadata Toolset", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://cocatalog.loc.gov/cgi-bin/Pwebrecon.cgi?v1=1&ti=1,1&Search%5FArg=Mercury%20Metadata%20Data%20Management%20System&Search%5FCode=TALL&CNT=10&PID=iA_S84JMRUP_sLczQjkpAJv8Ce2k&SEQ=20220427154213&SID=2", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cocatalog.loc.gov/cgi-bin/Pwebrecon.cgi?v1=1&ti=1,1&Search%5FArg=Mercury%20Metadata%20Data%20Management%20System&Search%5FCode=TALL&CNT=10&PID=iA_S84JMRUP_sLczQjkpAJv8Ce2k&SEQ=20220427154213&SID=2", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Merope:_Unsupervised_Learning_for_Network_Operations__Merope__v1.json b/agency-indexes/DoE/Merope:_Unsupervised_Learning_for_Network_Operations__Merope__v1.json new file mode 100644 index 00000000..69c2299d --- /dev/null +++ b/agency-indexes/DoE/Merope:_Unsupervised_Learning_for_Network_Operations__Merope__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-16", + "metadataLastUpdated": "2021-03-22" + }, + "description": "The ability to analyze network flow characteristics is critical to understand network patterns that can help us understand how our networks are behaving. Merope is a collection of many unsupervised learning approaches and visualizers to allow networks to be more visual and analytical.", + "laborHours": 0.0, + "languages": [], + "name": "Merope: Unsupervised Learning for Network Operations (Merope) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/hylia_networkprediction", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mesh2d.json b/agency-indexes/DoE/Mesh2d.json new file mode 100644 index 00000000..e7c6e5a8 --- /dev/null +++ b/agency-indexes/DoE/Mesh2d.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "bobby.kitchens@srnl.doe.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Mesh2d is a Fortran90 program designed to generate two-dimensional structured grids of the form [x(i),y(i,j)] where [x,y] are grid coordinates identified by indices (i,j). The x(i) coordinates alone can be used to specify a one-dimensional grid. Because the x-coordinates vary only with the i index, a two-dimensional grid is composed in part of straight vertical lines. However, the nominally horizontal y(i,j0) coordinates along index i are permitted to undulate or otherwise vary. Mesh2d also assigns an integer material type to each grid cell, mtyp(i,j), in a user-specified manner. The complete grid is specified through three separate input files defining the x(i), y(i,j), and mtyp(i,j) variations.", + "homepageURL": "http://srnl.doe.gov/downloads/Mesh2d_distribution.zip", + "laborHours": 0.0, + "languages": [ + "Fortran90 compiler / N/A" + ], + "name": "Mesh2d", + "organization": "Savannah River Site (SRS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://srnl.doe.gov/downloads/Mesh2d_distribution.zip", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://srnl.doe.gov/downloads/Mesh2d_distribution.zip", + "status": "Production", + "tags": [ + "DOE CODE", + "Savannah River Site (SRS)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MeshGraphNets.json b/agency-indexes/DoE/MeshGraphNets.json new file mode 100644 index 00000000..e1be1a31 --- /dev/null +++ b/agency-indexes/DoE/MeshGraphNets.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "A PyTorch implementation of \"Learning Mesh-based Simulation with Graph Networks\" (Pfaff et al., 2021) to build and train graph neural network surrogates for CFD simulation.", + "laborHours": 0.0, + "languages": [], + "name": "MeshGraphNets", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CCSI-Toolset/MGN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MeshKit.json b/agency-indexes/DoE/MeshKit.json new file mode 100644 index 00000000..33affca8 --- /dev/null +++ b/agency-indexes/DoE/MeshKit.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MeshKit is an open-source library of mesh generation functionality. MeshKit has general mesh manipulation and generation functions such as Copoy, Move, Rotate and Extrude mesh. In addition, new quad mesh and embedded boundary Cartesian mesh algorithm (EB Mesh) are included. Interfaces to several public domain meshing algorithms (TetGen, netgen, triangle, Gmsh, camal) are also offered. This library interacts with mesh data mostly through iMesh including accessing the mesh in parallel. It also can interact with iGeom interface to provide geometry functionality such as importing solid model based geometries. iGeom and IMesh are implemented in the CGM and MOAB packages, respectively. For some non-existing function in iMesh such as tree-construction and ray-tracing, MeshKit also interacts with MOAB functions directly.", + "laborHours": 128637.6, + "name": "MeshKit", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/fathomteam/meshkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mesh_Computing_Remote_Automatic_Workflow.json b/agency-indexes/DoE/Mesh_Computing_Remote_Automatic_Workflow.json new file mode 100644 index 00000000..80c2a006 --- /dev/null +++ b/agency-indexes/DoE/Mesh_Computing_Remote_Automatic_Workflow.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-09-12" + }, + "description": "The software suite uses a microservice architecture using Docker and `docker-compose`. The microservices are as follows:\n1. User interface. This interface is written in JavaScript using the Svelte framework. It exposes form elements and a 3D visualizer to prompt the user through the definition of microstructure parameters, and setting parameters for mesh generation and refinement.\n2. Mesh generator. This is a container running the Python package for DREAM3D to generate a voxelized mesh that represents a microstructure defined by the user in the interface.\n3. Cubit runner. This is a secure shell protocol tool that makes the submitting the DREAM mesh to an HPC instance and starts to run Cubit shell commands to smooth the grain boundaries with its `sculpt` library, applies user-defined boundary node sets, and bundles and returns the simulation-ready meshes and input files as a zipped directory.", + "laborHours": 10001.6, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Mesh Computing Remote Automatic Workflow", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/MURMUR", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mesh_independency_in_topology_optimization.json b/agency-indexes/DoE/Mesh_independency_in_topology_optimization.json new file mode 100644 index 00000000..0780f1b2 --- /dev/null +++ b/agency-indexes/DoE/Mesh_independency_in_topology_optimization.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "The topology optimization community has regularly employed optimization algorithms from the operations research community. However, these algorithms are implemented in the sequence space l2 instead of the\nproper function space where the design variable resides. In this software, we benchmark the mesh independent implementation of pyMMAopt with three common problems in topology optimization. We show how the volume fraction variable discretization on non-uniform meshes affects the convergence of\nl2 based optimization algorithms and how pyMMAopt successfully achieves mesh independent convergence.", + "homepageURL": "https://zenodo.org/record/5526481#.YU36FMZOmL8", + "laborHours": 0.0, + "languages": [], + "name": "Mesh independency in topology optimization", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://zenodo.org/record/5526481#.YU36FMZOmL8", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mesoscale_Science_Data_Analytics.json b/agency-indexes/DoE/Mesoscale_Science_Data_Analytics.json new file mode 100644 index 00000000..30995869 --- /dev/null +++ b/agency-indexes/DoE/Mesoscale_Science_Data_Analytics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "This is software that will be used to do data analytics in experimental workflows for x-ray mesoscale science. This tool set will provide a mechanism for supporting experiments in many ways, from collecting calibration information and raw data, to managing and viewing data to extracting crystallographic and physical parameters. It will eventually include development of a fully automated workflow that will include statistical information and prediction capabilities to support the scientists in decision-making and replanning their experiments when necessary.", + "laborHours": 0.0, + "languages": [], + "name": "Mesoscale Science Data Analytics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/fiteos", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MetConSIN.json b/agency-indexes/DoE/MetConSIN.json new file mode 100644 index 00000000..e9139e2d --- /dev/null +++ b/agency-indexes/DoE/MetConSIN.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "Metabolic Context Species Interaction Networks (MetConSIN) generates microbe-metabolte and metabolite-metabolite interaction networks using constraint based metabolic modeling. To do this, MetConSIN simulates with the dynamic FBA system and saves the sequence of interaction networks implied by that system, as well as the time-average network.", + "laborHours": 0.0, + "languages": [], + "name": "MetConSIN", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/metconsin", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MetISIS.json b/agency-indexes/DoE/MetISIS.json new file mode 100644 index 00000000..22abec3b --- /dev/null +++ b/agency-indexes/DoE/MetISIS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-11", + "metadataLastUpdated": "2025-04-11" + }, + "description": "The software enables identifying small molecules based on mass spectrometry data.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 11628.0, + "languages": [], + "name": "MetISIS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MetaBAT-LR_v1.0.0.json b/agency-indexes/DoE/MetaBAT-LR_v1.0.0.json new file mode 100644 index 00000000..aa8feb85 --- /dev/null +++ b/agency-indexes/DoE/MetaBAT-LR_v1.0.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-15", + "metadataLastUpdated": "2023-06-15" + }, + "description": "MetaBAT-LR is an extension to the metaBAT program, which adds functionalities to leverage various datasets (long-reads, Hi-C) to improve the completeness of metagenome binning while keeping contamination levels low. It trains a random forest model using the self-supervised training paradigm to predict linkage information among metagenome scaffolds, then uses this information to recruit unbinned scaffolds and merge incomplete bins that are from the same species.", + "laborHours": 0.0, + "languages": [], + "name": "MetaBAT-LR v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/project-metabat/metabat-lr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MetaGenomic_Assembly_by_Merging__MeGAMerge_.json b/agency-indexes/DoE/MetaGenomic_Assembly_by_Merging__MeGAMerge_.json new file mode 100644 index 00000000..a73bbf36 --- /dev/null +++ b/agency-indexes/DoE/MetaGenomic_Assembly_by_Merging__MeGAMerge_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"MetaGenomic Assembly by Merging\" (MeGAMerge)Is a novel method of merging of multiple genomic assembly or long read data sources for assembly by use of internal trimming/filtering of data, followed by use of two 3rd party tools to merge data by overlap based assembly.", + "laborHours": 288.8, + "name": "MetaGenomic Assembly by Merging (MeGAMerge)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/MeGAMerge/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MeGAMerge", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Meta_Allocator.json b/agency-indexes/DoE/Meta_Allocator.json new file mode 100644 index 00000000..d70fc3bd --- /dev/null +++ b/agency-indexes/DoE/Meta_Allocator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-10", + "metadataLastUpdated": "2019-04-10" + }, + "description": "Metall provides simplified memory allocation interfaces for out-of-core applications that use block-addressable persistent memory devices to extend the capacity of main memory and to persistently store data on such devices. Using Metall, users can dynamically allocate memory in persistent memory devices just as in main-memory. In order to store data persistently and reload the data easily, Metall also provides a key-value store like interface. Metall offers APIs to allocate contiguous memory regions like malloc(3) does and to construct C++ objects, including STL-like containers. Metall has a similar APIs to\nBoost.Interprocess (BIP).", + "laborHours": 5943.2, + "languages": [], + "name": "Meta Allocator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/metall", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MetaboliteValidation.json b/agency-indexes/DoE/MetaboliteValidation.json new file mode 100644 index 00000000..ea4229d2 --- /dev/null +++ b/agency-indexes/DoE/MetaboliteValidation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a simple C# console program to validate and update the data from\u00a0MetabolomicsCCS", + "laborHours": 988.0, + "languages": [], + "name": "MetaboliteValidation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/metaboliteValidation", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Metabolites_Annotations_and_Genes_Integrated__MAGI__v1.0.json b/agency-indexes/DoE/Metabolites_Annotations_and_Genes_Integrated__MAGI__v1.0.json new file mode 100644 index 00000000..3591c483 --- /dev/null +++ b/agency-indexes/DoE/Metabolites_Annotations_and_Genes_Integrated__MAGI__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-08", + "metadataLastUpdated": "2019-02-19" + }, + "description": "\tWith the benefit of hindsight, it is easy to see that the readout of the human genome, spectacular milestone that it was, represents only the beginning of the \"omics\" information explosion. The technical side of the 'omics explosion--enabling researchers to efficiently readout terabytes of information spelling out whole genomes, transcriptomes, proteomes and metabolomes, does not per se provide a clear picture of how life works. Nor does it show us how we can engineer biology to solve the grand challenges of the 21st century: feeding 10 billion people with declining per capita supplies of arable land and clean water, sustaining biological diversity and slowing the increase in greenhouse gas formation, primarily carbon dioxide and methane. \n\nThe 2017-063 invention--Metabolites and Genes Integration Technology--proposes an integrated approach to correcting and connecting the dots of the 'omics explosion: linking genes to proteins, proteins to pathways, pathways to biochemical reactions and metabolites. The '063 invention is potentially transformational in that it can generate testable hypotheses across thousands of genes to predict their chemical and metabolic products. It can also do the reverse; i.e., starting from chemical and metabolic products it can generate testable hypotheses about which genes and pathways those molecules are linked to. Since we know that genomic, transcriptomic, proteomic and metabolomic databases are chock full or erroneous information, MAGI also has the unique benefit of correcting these errors through its own independent pathway of bidirectional hypothesis generation (genes=>proteins=>metabolites + metabolites=>proteins=>genes). Perfectly amenable to high-throughput hypothesis generation and experimentation, MAGI can transform our understanding of human, animal, plant and microbial biology over several decades, laying the essential knowledge foundation to addressing the grand scientific challenges of the 21st century.", + "laborHours": 1352.8, + "languages": [], + "name": "Metabolites Annotations and Genes Integrated (MAGI) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biorack/magi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MetabolomicsTools.json b/agency-indexes/DoE/MetabolomicsTools.json new file mode 100644 index 00000000..8d208bcc --- /dev/null +++ b/agency-indexes/DoE/MetabolomicsTools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This is the repository for \"MetabolomicsTools\" developed by KBase. ", + "laborHours": 1231.2, + "languages": [], + "name": "MetabolomicsTools", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/MetabolomicsTools", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Metabolomics_Collision_Cross_Section_Database_and_Server.json b/agency-indexes/DoE/Metabolomics_Collision_Cross_Section_Database_and_Server.json new file mode 100644 index 00000000..ea30aa7b --- /dev/null +++ b/agency-indexes/DoE/Metabolomics_Collision_Cross_Section_Database_and_Server.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a the code and data for a website created to display collision cross section data for metabolites and small molecules. This repository hosts two things. First is the source code (js) for a website created to display collision cross section data for metabolites and other small molecules. The second is the underlying CCS dataset. The growing interest in metabolomic and exposomic studies is also inciting a need for new techniques to analyze these diverse molecules. Mass spectrometry-based studies are often preferred for the confident identification of small molecules. Ion mobility spectrometry (IMS) is capable of separating molecules that have the same m/z but different conformational arrangements, which is very useful in metabolomic and exposomic analyses. As the desire for IMS measurements of metabolites continues to grow, so does the need for high quality collision cross section (CCS) values.", + "laborHours": 57425.6, + "languages": [], + "name": "Metabolomics Collision Cross Section Database and Server", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MetabolomicsCCS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Metadata_management_staging_system.json b/agency-indexes/DoE/Metadata_management_staging_system.json new file mode 100644 index 00000000..d5d657e9 --- /dev/null +++ b/agency-indexes/DoE/Metadata_management_staging_system.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Django application providing a user-interface for building a file and metadata management system. An evolution of our Node.js and CouchDb metadata management system. This one focuses on server functionality and uses a well-documented, rational and REST-ful API for data access.", + "laborHours": 1763.2, + "name": "Metadata management staging system", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/metadata-server", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Metadata_staging_tools.json b/agency-indexes/DoE/Metadata_staging_tools.json new file mode 100644 index 00000000..2f0eac92 --- /dev/null +++ b/agency-indexes/DoE/Metadata_staging_tools.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Django application providing a user-interface for building a file and metadata management system. Operates in conjunction with https://github.com/usgin/metadata-server.", + "laborHours": 6444.8, + "name": "Metadata staging tools", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/metadata-repository", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MetagenomeAPI.json b/agency-indexes/DoE/MetagenomeAPI.json new file mode 100644 index 00000000..b2a2447a --- /dev/null +++ b/agency-indexes/DoE/MetagenomeAPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "KBase dynamic service module for caching and searching metagenomics data.", + "laborHours": 134200.8, + "languages": [], + "name": "MetagenomeAPI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/MetagenomeAPI", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MetagenomeUtils.json b/agency-indexes/DoE/MetagenomeUtils.json new file mode 100644 index 00000000..b0da91eb --- /dev/null +++ b/agency-indexes/DoE/MetagenomeUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "Set of utility functions and Apps for working with metagenomics data in KBase. A module generated by the KBase SDK for interacting with Metagenomic data in KBase. This module also contains the KIDL definition of the KBaseMetagenomes workspace data types.", + "laborHours": 2356.0, + "languages": [], + "name": "MetagenomeUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/MetagenomeUtils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Metaheuristic_Optimization_Tool__MOT_.json b/agency-indexes/DoE/Metaheuristic_Optimization_Tool__MOT_.json new file mode 100644 index 00000000..1b1bb032 --- /dev/null +++ b/agency-indexes/DoE/Metaheuristic_Optimization_Tool__MOT_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "baej@ornl.gov" + }, + "date": { + "created": "2025-04-14", + "metadataLastUpdated": "2025-04-14" + }, + "description": "This tool is a suite of optimization algorithms along with a structure that allows users to optimize and process result.\n\nGenerally, the optimization algorithm samples an input set from a user-defined range, runs it through simulation, extracts results (scores) from function, and iterates into an optimized solution.", + "laborHours": 1079.2, + "languages": [], + "name": "Metaheuristic Optimization Tool (MOT)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jbae11/mot", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MetallData.json b/agency-indexes/DoE/MetallData.json new file mode 100644 index 00000000..6356a568 --- /dev/null +++ b/agency-indexes/DoE/MetallData.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-28", + "metadataLastUpdated": "2023-02-28" + }, + "description": "MetallData is an HPC platform for interactive data science applications at HPC-scales. It provides an ecosystem for persistent distributed data structures, including algorithms, interactivity and storage.", + "laborHours": 0.0, + "languages": [], + "name": "MetallData", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/metalldata", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Metamesh,_Version_1.0.json b/agency-indexes/DoE/Metamesh,_Version_1.0.json new file mode 100644 index 00000000..90eae97a --- /dev/null +++ b/agency-indexes/DoE/Metamesh,_Version_1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-04" + }, + "description": "Metamesh is a general-purpose C++ language library for creating data structures that represent meshes. An important difference between Metamesh and other \"mesh\" libraries is that Metamesh does not provide a specific mesh format, in the usual sense, or tools or a GUI by which users build specific meshes. Rather, it provides a mechanism by which mesh formats themselves can be built, based on their constituent parts and the relationships between them.Consider that a mesh in up to three space dimensions can, in principle, contain nodes (0d entities, or points), edges (1d entities), faces (2d entities), and cells (3d, or volumetric, entities). A node might be defined in terms of (x), (x,y), or (x,y,z) in Cartesian coordinates; or perhaps something else, in a different coordinate system. An edge is typically defined from two nodes; say, \"edge E goes from node A=(ax,ay) to node B=(bx,by).\" Faces can reasonably be defined in terms of nodes or edges, and cells in terms of nodes, edges, or faces. Note also that someone might wish to support general faces or cells, or only specific variants - say, triangular faces and tetrahedral cells, or quadrilateral faces and hexahedral cells. Or, perhaps, both triangular and quadrilateral faces (but no others), with prisms for each cell. Consider also that a mesh can have the same or a lesser dimension than that of its enclosing space. In 3d, for example, one could have a full 3d mesh, a 2d \"sheet\" mesh with no cells, a 1d \"parametrized curve\" with neither faces nor cells, or even a 1d \"point cloud.\" And, in addition to defining a mesh scheme, a user might wish to place additional data onto one or more mesh entities. Imagine, for example, a velocity at each node, a flux across each edge or face, and a mass or average density per cell. Metamesh supports all of this, through the use of C++ class and function templates, and template metaprogramming techniques. Programmers begin with constructs that Metamesh provides (or, users can define their own), and assemble them in particular ways in order to create particular mesh formats. Metamesh then provides functionality automatically to meshes that are constructed in this manner. Finally, Metamesh provides very general functions for spinning, extruding, visualizing, and performing input/output of whatever meshes a user builds with it.", + "laborHours": 7052.8, + "languages": [], + "name": "Metamesh, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/staleyLANL/metamesh", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Method_of_Moving_Asymptotes_Optimization_Algorithm_in_Python.json b/agency-indexes/DoE/Method_of_Moving_Asymptotes_Optimization_Algorithm_in_Python.json new file mode 100644 index 00000000..7228516b --- /dev/null +++ b/agency-indexes/DoE/Method_of_Moving_Asymptotes_Optimization_Algorithm_in_Python.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-03", + "metadataLastUpdated": "2021-03-04" + }, + "description": "Python implementation of the Method of Moving Asymptotes optimization algorithm described in[Svanberg, K., The method of moving asymptotes- a new method for structural optimization. International journal for numerical methods in engineering, 1987. 24(2): p.359 (https://onlinelibrary.wiley.com/doi/abs/10.1002/nme.1620240207). Originally implemented in[GetDP](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=717799) [project](https://gitlab.onelab.info/getdp/getdp), although it has been deleted in their repository.", + "laborHours": 0.0, + "languages": [], + "name": "Method of Moving Asymptotes Optimization Algorithm in Python", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pyMMAopt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Methodology_for_Automated_Detection_of_Degradation_and_Faults_in_Packaged_Air_Conditioners_and_Heat_Pumps_Using_Only_Two_Sensors.json b/agency-indexes/DoE/Methodology_for_Automated_Detection_of_Degradation_and_Faults_in_Packaged_Air_Conditioners_and_Heat_Pumps_Using_Only_Two_Sensors.json new file mode 100644 index 00000000..1ca44803 --- /dev/null +++ b/agency-indexes/DoE/Methodology_for_Automated_Detection_of_Degradation_and_Faults_in_Packaged_Air_Conditioners_and_Heat_Pumps_Using_Only_Two_Sensors.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The software was created in the process of developing a system known as the Smart Monitoring and Diagnostic System (SMDS) for packaged air conditioners and heat pumps used on commercial buildings (known as RTUs). The SMDS provides automated remote monitoring and detection of performance degradation and faults in these RTUs and could increase the awareness by building owners and maintenance providers of the condition of the equipment, the cost of operating it in degraded condition, and the quality of maintenance and repair service when it is performed. The SMDS provides these capabilities and would enable conditioned-based maintenance rather than the reactive and schedule-based preventive maintenance commonly used today, when maintenance of RTUs is done at all. Improved maintenance would help ensure persistent peak operating efficiencies, reducing energy consumption by an estimated 10% to 30%.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C#, C++, PHP, JavaScript, MSSQL query, .NET" + ], + "name": "Methodology for Automated Detection of Degradation and Faults in Packaged Air Conditioners and Heat Pumps Using Only Two Sensors", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Methodology_for_Risk-informed_O&M_decision_making_in_power_plants.json b/agency-indexes/DoE/Methodology_for_Risk-informed_O&M_decision_making_in_power_plants.json new file mode 100644 index 00000000..c3a85092 --- /dev/null +++ b/agency-indexes/DoE/Methodology_for_Risk-informed_O&M_decision_making_in_power_plants.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Incorporation of real-time component information using equipment condition assessment (ECA) through the development of enhanced risk monitors (ERM) for active components in advanced reactor (AR) and advanced small modular reactor (SMR) designs. We incorporate time-dependent failure probabilities from prognostic health management (PHM) systems to dynamically update the risk metric of interest. This information is used to augment data used for supervisory control and plant-wide coordination of multiple modules by providing the incremental risk incurred due to aging and demands placed on components that support mission requirements.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "MS" + ], + "name": "Methodology for Risk-informed O&M decision making in power plants", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Methods_for_Determining_Likelihood_of_Tweet_Deletion.json b/agency-indexes/DoE/Methods_for_Determining_Likelihood_of_Tweet_Deletion.json new file mode 100644 index 00000000..d65297ec --- /dev/null +++ b/agency-indexes/DoE/Methods_for_Determining_Likelihood_of_Tweet_Deletion.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2025-04-14" + }, + "description": "Few works exist that attempt to build predictive models for tweet deletion. Zhou et al. (2015) focus on a subset of deleted tweets \u2013 regrettable tweets. These are tweets that the authors believe to contain inappropriate content. Inappropriate can range from vulgar language to sharing private content such as a personal email address. The presence of inappropriate content doesn\u2019t guarantee that a tweet will be deleted, however intuition dictates it can be in an important factor in the tweet being deleted. In their work, the authors create a predictive model for identifying regrettable tweets. It is important to note the authors focus on predicting regrettable tweets that are distinctly not spam and only written in English. Through manual investigation, the authors identify ten major topics including negative sentiment, cursing, and relationships that are prevalent in regrettable tweets. The authors then exploit WordNet and UrbanDictionary to create keyword lists related to the ten topics. Finally, using a combination of existing lexica and the topic keywords as features, the authors build classifiers to test the accuracy of their model. The authors complement 700 manually labeled regrettable tweets with 700 normal tweets to create their evaluation dataset. The authors\u2019 best performance from 10-fold cross-validation was an f1 score of 0.85 using a J48 classifier on a balanced dataset of deleted and non-deleted tweets.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 684.0, + "languages": [ + "Multiple possible" + ], + "name": "Methods for Determining Likelihood of Tweet Deletion", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MiGRIDS.json b/agency-indexes/DoE/MiGRIDS.json new file mode 100644 index 00000000..1c500ed2 --- /dev/null +++ b/agency-indexes/DoE/MiGRIDS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pcicilio@alaska.edu" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "MiGRIDS is a software that models islanded microgrid power systems with different controls and components. For example, using load and resource data from a microgrid, you could model it with additional wind turbines, battery etc. You could also try out different dispatch schemes to see which one worked best.\n\nMiGRIDS is designed to help optimize the size and dispatch of grid components in a microgrid. While a grid connect feature is expected to be added in the future, islanded operation is the focus. Note that this is a basic implementation and more features and functionality (such as a GUI) are coming!\n\nMiGRIDS runs time-step energy balance simulations for different grid components and controls. In smaller microgrid environments, dispatch decisions are being made on the order of seconds. In order to fully capture their effect, this tool lets you run simulations on the order of seconds. The end result is a more realistic representation of what can be achieved by integrating different components and control strategies in a grid.", + "laborHours": 0.0, + "languages": [], + "name": "MiGRIDS", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/acep-uaf/MiGRIDS_DOE_MarineMicrogrids", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Microbial_Ecology_Toy_Library.json b/agency-indexes/DoE/Microbial_Ecology_Toy_Library.json new file mode 100644 index 00000000..9e955d16 --- /dev/null +++ b/agency-indexes/DoE/Microbial_Ecology_Toy_Library.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-03-03", + "metadataLastUpdated": "2020-03-03" + }, + "description": "These are miscellaneous utility functions that I've developed and found useful in working with sequencing counts.\n\nPurpose: To collect often reused procedures in one open source location that can be shared and worked on publicly, and perhaps contributed back to other open source projects.\n\nFunction: Adds, divides, filters, summarizes tables of counts.\n\nCapabilities: Currently, the main capability is to reformat count tables for use with the ALDEx2 package.", + "laborHours": 34428.0, + "languages": [], + "name": "Microbial Ecology Toy Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/meco", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.9000" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Microcontroller-based_aerosol_jet_printer_control_software.json b/agency-indexes/DoE/Microcontroller-based_aerosol_jet_printer_control_software.json new file mode 100644 index 00000000..46f3f22a --- /dev/null +++ b/agency-indexes/DoE/Microcontroller-based_aerosol_jet_printer_control_software.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-03-02", + "metadataLastUpdated": "2024-09-10" + }, + "description": "This software is used with a microcontroller to control an aerosol jet printing system. It was written for a 32-bit ARM microcontroller, providing greater processing speed and complexity relative to more conventional low-cost printer controllers. The microcontroller software was written using a real-time operating system (FreeRTOS), which simplifies parallel operation of multiple functions and further customization. It supports simultaneous motion planning, pulse generation for stepper motors, reading encoder feedback, communicating with multiple mass flow controllers, controlling solid state relays, handling a software-based emergency stop, and sending data to the client PC. The program is written in C and communicates with the client PC via USB connection. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.\nSAND2021-0436 O", + "laborHours": 2036.8, + "languages": [ + "C", + "Batchfile" + ], + "name": "Microcontroller-based aerosol jet printer control software", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Low-cost-Aerosol-Jet-Printer", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Microscopy_Parser.json b/agency-indexes/DoE/Microscopy_Parser.json new file mode 100644 index 00000000..40e7b11b --- /dev/null +++ b/agency-indexes/DoE/Microscopy_Parser.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "39s@ornl.gov" + }, + "date": { + "created": "2022-10-20", + "metadataLastUpdated": "2022-10-20" + }, + "description": "Reads proprietary electron microscope vendor files and exports them in a standardized open source HDF5 format.", + "laborHours": 0.0, + "languages": [], + "name": "Microscopy Parser", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esrah-ap-niht/Microscopy-VB-GMM", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Middleware_for_Data_Intensive_Computing.json b/agency-indexes/DoE/Middleware_for_Data_Intensive_Computing.json new file mode 100644 index 00000000..7891eed9 --- /dev/null +++ b/agency-indexes/DoE/Middleware_for_Data_Intensive_Computing.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MeDICi is an evolving middleware platform for building complex, high performance analytical applications. These applications typically comprise a pipeline of software components, each of which performs some analysis on incoming data and passes on its results to the next step in the pipeline.", + "homepageURL": "http://medici.pnl.gov/download_mif", + "laborHours": 0.0, + "name": "Middleware for Data Intensive Computing", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://medici.pnl.gov/standard_pnnl_oss_liscense", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://medici.pnl.gov/download_mif", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Millstone.json b/agency-indexes/DoE/Millstone.json new file mode 100644 index 00000000..2b8fbd6a --- /dev/null +++ b/agency-indexes/DoE/Millstone.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-12-20" + }, + "description": "Millstone is a mechanics solver for geological processes, focusing on coupling to reservoir simulators. It solves the linear balance of momentum with incremental poroelastic stress rate formulations under quasistatic assumptions.", + "homepageURL": "https://link.springer.com/article/10.1007/s11242-019-01254-6", + "laborHours": 0.0, + "languages": [], + "name": "Millstone", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2018-140/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://link.springer.com/article/10.1007/s11242-019-01254-6", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MinCostFlows.jl.json b/agency-indexes/DoE/MinCostFlows.jl.json new file mode 100644 index 00000000..90069ba1 --- /dev/null +++ b/agency-indexes/DoE/MinCostFlows.jl.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-09-11", + "metadataLastUpdated": "2019-09-11" + }, + "description": "MinCostFlows.jl is a utility package in the Julia programming language for efficiently solving min-cost network flow problems through an implementation of the relaxation dual ascent method (Bertsekas, 1985, https://link.springer.com/article/10.1007/BF01586087). The use of a dual ascent method allows for warm-starting the solver with a solution from a previously-solved problem that need not be feasible for the new problem, providing computational performance benefits when repeatedly solving similar network flow problems. This approach is particularly useful for Monte Carlo power system resource adequacy models.", + "laborHours": 608.0, + "languages": [ + "Julia" + ], + "name": "MinCostFlows.jl", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MinCostFlows.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mingus_Discontinuous_Multiphysics.json b/agency-indexes/DoE/Mingus_Discontinuous_Multiphysics.json new file mode 100644 index 00000000..5c3bc86b --- /dev/null +++ b/agency-indexes/DoE/Mingus_Discontinuous_Multiphysics.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Mingus provides hybrid coupled local/non-local mechanics analysis capabilities that extend several traditional methods to applications with inherent discontinuities. Its primary features include adaptations of solid mechanics, fluid dynamics and digital image correlation that naturally accommodate dijointed data or irregular solution fields by assimilating a variety of discretizations (such as control volume finite elements, peridynamics and meshless control point clouds). The goal of this software is to provide an analysis framework form multiphysics engineering problems with an integrated image correlation capability that can be used for experimental validation and model", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++, CNU or Clang" + ], + "name": "Mingus Discontinuous Multiphysics", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mini-PIC.json b/agency-indexes/DoE/Mini-PIC.json new file mode 100644 index 00000000..b42157eb --- /dev/null +++ b/agency-indexes/DoE/Mini-PIC.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Mini-PIC is an electrostatic particle-in-cell (PIC} testbed application for development of MPl+X applications on next generation platforms.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++98" + ], + "name": "Mini-PIC", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MiniAero.json b/agency-indexes/DoE/MiniAero.json new file mode 100644 index 00000000..d84874ce --- /dev/null +++ b/agency-indexes/DoE/MiniAero.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "MiniAero is an MPl+X proxy app for gas dynamics problems. MiniAero can be used as a representative limited gas dynamics application to assess future computer architectures and programming models", + "laborHours": 2295.2, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "Python" + ], + "name": "MiniAero", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniAero", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MiniTensor_v._1.0.json b/agency-indexes/DoE/MiniTensor_v._1.0.json new file mode 100644 index 00000000..96670eac --- /dev/null +++ b/agency-indexes/DoE/MiniTensor_v._1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Algebra, calculus, manipulation and optimization for small vectors and tensors.", + "laborHours": 8344830.4, + "languages": [], + "name": "MiniTensor v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Minimond.json b/agency-indexes/DoE/Minimond.json new file mode 100644 index 00000000..32b1a006 --- /dev/null +++ b/agency-indexes/DoE/Minimond.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "minomond is a simple software package built to unobtrrusively collect large amounts of trending data on computer systems, and send that data to one or more external trending data aggregation services. The goal is to enable ongoing recording of many metrics from many nodes in order to identify historical patterns and provide historical visibility into systems problems. minimond is intended to replace large collections of ad hoc scripts that are commonly used for this purpose. minomond is built with an emphasis on simplicity and extensibility, and is intended to supplement, not replace, other availability and trending data monitoring systems.", + "laborHours": 0.0, + "languages": [], + "name": "Minimond", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NERSC/minimond/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/minimond", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Minions_Version_1.0.json b/agency-indexes/DoE/Minions_Version_1.0.json new file mode 100644 index 00000000..7fa48c5a --- /dev/null +++ b/agency-indexes/DoE/Minions_Version_1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-09-30" + }, + "description": "Establishes the input/output dependencies between individual application tasks, schedules and executes them on available computing resources in order of their dependencies. Uses statistical modeling algorithms to summarize the properties of the tasks to present to users a compact view of the surrent state of the overall application tasks and the effectiveness of various runtime optimizations on such tasks to improve utility of scheduling. Finally, uses statistical models to predict availability of computing resources", + "homepageURL": "https://sourceforge.net/projects/sched-minions", + "laborHours": 76121.6, + "languages": [ + "None" + ], + "name": "Minions Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/sched-minions", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MiscIndexer.json b/agency-indexes/DoE/MiscIndexer.json new file mode 100644 index 00000000..14e408e0 --- /dev/null +++ b/agency-indexes/DoE/MiscIndexer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "Indexer for miscellaneous object types.", + "laborHours": 319960.0, + "languages": [], + "name": "MiscIndexer", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/MiscIndexer", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mist.json b/agency-indexes/DoE/Mist.json new file mode 100644 index 00000000..3cc8be6e --- /dev/null +++ b/agency-indexes/DoE/Mist.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "dewittsj@ornl.gov" + }, + "date": { + "created": "2024-06-04", + "metadataLastUpdated": "2024-06-04" + }, + "description": "Determining the appropriate material data is often a bottleneck for performing calculations/simulations of industrial/experimental processes and resulting material structures and properties. Beyond the time it takes to find the appropriate values in the literature, many judgement calls are involved in choosing the values. These judgement calls can lead to inconsistencies between steps in research workflow, where different material parameter values are used.\n\nMist solves this problem by providing a mechanism to store, share, and use material information in convenient human-readable and machine-readable formats. Mist has an extensible ontology for defining a wide variety of material information, currently focused on metal alloy applications. Examples include: alloy composition, density, liquidus temperature, and the coefficient of thermal expansion.\n\nMist converts between standardized machine-readable data formats (e.g. JSON), specialized input format for simulation tools, and human-readable documents (e.g. LaTeX, Markdown). For parameters defined by an equation (e.g. a polynomial function) or a list of tabulated values, Mist can evaluate parameter values at requested conditions. Mist also provides an API for direct usage of the Mist data structures in calculations, if supported.", + "laborHours": 410.4, + "languages": [ + "Python" + ], + "name": "Mist", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-MDF/mist", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mitigation_of_External_Exposure_of_Energy_Delivery_System__MEEDS_..json b/agency-indexes/DoE/Mitigation_of_External_Exposure_of_Energy_Delivery_System__MEEDS_..json new file mode 100644 index 00000000..72a5716d --- /dev/null +++ b/agency-indexes/DoE/Mitigation_of_External_Exposure_of_Energy_Delivery_System__MEEDS_..json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MEEDS is a cybersecurity solution that empowers under resourced owners and operators of critical energy infrastructure to rapidly identify and detect the publicly exposed and vulnerable operational technology (OT) and other critical Industrial Control and Energy Delivery Systems.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Mitigation of External Exposure of Energy Delivery System (MEEDS).", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mitos.json b/agency-indexes/DoE/Mitos.json new file mode 100644 index 00000000..eee57535 --- /dev/null +++ b/agency-indexes/DoE/Mitos.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-08-05", + "metadataLastUpdated": "2022-08-12" + }, + "description": "Mitos is a library and a tool for collecting sampled memory performance data to view with MemAxes.", + "laborHours": 684.0, + "languages": [], + "name": "Mitos", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Mitos", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MixDown.json b/agency-indexes/DoE/MixDown.json new file mode 100644 index 00000000..89f0081c --- /dev/null +++ b/agency-indexes/DoE/MixDown.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MixDown is a meta-build tool that orchestrates and manages the building of multiple 3rd party libraries. It can manage the downloading, uncompressing, unpacking, patching, configuration, build, and installation of 3rd party libraries using a variety of configuration and build tools. As a meta-build tool, it relies on 3rd party tools such as GNU Autotools, make, Cmake, scons, etc. to actually confugure and build libraries. MixDown includes an extensive database of settings to be used for general machines and specific leadership class computing resources.", + "laborHours": 6536.0, + "name": "MixDown", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tepperly/MixDown", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mneme.json b/agency-indexes/DoE/Mneme.json new file mode 100644 index 00000000..1c5c7926 --- /dev/null +++ b/agency-indexes/DoE/Mneme.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-11-04", + "metadataLastUpdated": "2024-11-04" + }, + "description": "A simple tool allowing recording the execution of a GPU (CUDA) kernel and replaying that kernel as an\nindependent executable.\nThe tool operates in 3 phases. During compile time the user needs to apply a provided LLVM pass to\ninstrument the code. The pass detects all device global variables\nand device functions and stores this information with the respective LLVM-IR in the global device\nmemory. The compilation generates a record-able executable.\nThe second phase involves running the application executable with a desired input and using\nLD_PRELOAD to enable recording. When recording before invoking a device kernel\nthe pre-loaded library stores device memory in persistent storage and associates the memory with the\ndevice kernel and an LLVM IR file. At the end of the recorded execution\nthe pre-load library generates a database in the form of a JSON file containing information regarding the\nLLVM-IR files and the snapshots of device memory.\nDuring the third and last phase the user can replay the execution of an kernel as a separate independent\nexecutable. Besides executing it the user can modify the LLVM IR file and\nauto-tune parameters such as kernel launch-bounds or kernel runtime execution parameters (e.g. Kernel\nBlock and Grid Dimensions).\nIs", + "laborHours": 1687.2, + "languages": [], + "name": "Mneme", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Olympus-HPC/Mneme", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.0.alpha" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MoNA_-_Messaging_over_NA.json b/agency-indexes/DoE/MoNA_-_Messaging_over_NA.json new file mode 100644 index 00000000..8c38deda --- /dev/null +++ b/agency-indexes/DoE/MoNA_-_Messaging_over_NA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-31", + "metadataLastUpdated": "2022-01-31" + }, + "description": "MoNA is a Mochi library combining the NA layer of Mercury with the Argobots threading library, in a way similar to how Margo combines Mercury with Argobots. It provides a low-level messaging interface and hides the NA progress loop into Argobots ULTs.", + "laborHours": 0.0, + "languages": [], + "name": "MoNA - Messaging over NA", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-mona/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-mona", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mobile_Application_For_Conferences__MACo_.json b/agency-indexes/DoE/Mobile_Application_For_Conferences__MACo_.json new file mode 100644 index 00000000..9cd02230 --- /dev/null +++ b/agency-indexes/DoE/Mobile_Application_For_Conferences__MACo_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "fu@bnl.gov" + }, + "date": { + "created": "2019-09-24", + "metadataLastUpdated": "2019-09-24" + }, + "description": "A web based mobile application to show basic JACoW system conference information, paper information, paper searching, paper status, paper author searching, conference hotel map navigation, and many other conference related information. It works on all major web browsers on mobile devices (iOS based or Android based) and desk top devices. \n", + "homepageURL": "https://www.agsrhichome.bnl.gov/Controls/MACo/index.html", + "laborHours": 0.0, + "languages": [ + "Java", + "JavaScript" + ], + "name": "Mobile Application For Conferences (MACo)", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.agsrhichome.bnl.gov/Controls/MACo/index.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mobject.json b/agency-indexes/DoE/Mobject.json new file mode 100644 index 00000000..787a8a52 --- /dev/null +++ b/agency-indexes/DoE/Mobject.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "Mobject is a prototype Mochi object storage system based on RADOS.", + "laborHours": 0.0, + "languages": [], + "name": "Mobject", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mobject/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mobject", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ModME.json b/agency-indexes/DoE/ModME.json new file mode 100644 index 00000000..577d99ef --- /dev/null +++ b/agency-indexes/DoE/ModME.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-12-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ModME is a generalization and benchmark framework for the notion of semantic importance. It is primarily used in a stream reasoning context, where hidden information can be extracted out of the data streams.", + "laborHours": 18331.2, + "languages": [], + "name": "ModME", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/modme", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Modal_Analysis_for_Grid_Operation.json b/agency-indexes/DoE/Modal_Analysis_for_Grid_Operation.json new file mode 100644 index 00000000..27346849 --- /dev/null +++ b/agency-indexes/DoE/Modal_Analysis_for_Grid_Operation.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "MANGO software is to provide a solution for improving small signal stability of power systems through adjusting operator-controllable variables using PMU measurement. System oscillation problems are one of the major threats to the grid stability and reliability in California and the Western Interconnection. These problems result in power fluctuations, lower grid operation efficiency, and may even lead to large-scale grid breakup and outages. This MANGO software aims to solve this problem by automatically generating recommended operation procedures termed Modal Analysis for Grid Operation (MANGO) to improve damping of inter-area oscillation modes. The MANGO procedure includes three steps: recognizing small signal stability problems, implementing operating point adjustment using modal sensitivity, and evaluating the effectiveness of the adjustment. The MANGO software package is designed to help implement the MANGO procedure.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab, Python script, batch script, PSAT Python script" + ], + "name": "Modal Analysis for Grid Operation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ModbusXMLSchema.json b/agency-indexes/DoE/ModbusXMLSchema.json new file mode 100644 index 00000000..076074c9 --- /dev/null +++ b/agency-indexes/DoE/ModbusXMLSchema.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Modbus XML Schema Definition and utility software\n", + "laborHours": 577.6, + "name": "ModbusXMLSchema", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-BTRIC/ModbusXMLSchema", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Model_Analysis_ToolKit.json b/agency-indexes/DoE/Model_Analysis_ToolKit.json new file mode 100644 index 00000000..c731ac25 --- /dev/null +++ b/agency-indexes/DoE/Model_Analysis_ToolKit.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MATK provides basic functionality to facilitate model analysis within the Python computational environment. Model analysis setup within MATK includes: - define parameters - define observations - define model (python function) - define samplesets (sets of parameter combinations) Currently supported functionality includes: - forward model runs - Latin-Hypercube sampling of parameters - multi-dimensional parameter studies - parallel execution of parameter samples - model calibration using internal Levenberg-Marquardt algorithm - model calibration using lmfit package - model calibration using levmar package - Markov Chain Monte Carlo using pymc package MATK facilitates model analysis using: - scipy - calibration (scipy.optimize) - rpy2 - Python interface to R", + "laborHours": 54856.8, + "name": "Model Analysis ToolKit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dharp/MATK", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Model_Based_Real_Time_HVAC_Systems_Optimization.json b/agency-indexes/DoE/Model_Based_Real_Time_HVAC_Systems_Optimization.json new file mode 100644 index 00000000..917987ff --- /dev/null +++ b/agency-indexes/DoE/Model_Based_Real_Time_HVAC_Systems_Optimization.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Model for HVAC system optimization in multi-family housing market.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Model Based Real Time HVAC Systems Optimization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Model_Coupling_Toolkit_v2.10.json b/agency-indexes/DoE/Model_Coupling_Toolkit_v2.10.json new file mode 100644 index 00000000..dfbb9cc7 --- /dev/null +++ b/agency-indexes/DoE/Model_Coupling_Toolkit_v2.10.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2018-04-13", + "metadataLastUpdated": "2021-11-08" + }, + "description": "MCT is a set of open-source software tools for creating coupled models. MCT is fully parallel and can be used to couple message-passing parallel models to create a parallel coupled model. MCT is available as a small library and a set of Fortran90 modules. Interoperability is through a simple API. Two models that declare and use MCT datatypes can be coupled with a minimum of effort.", + "laborHours": 34184.8, + "languages": [], + "name": "Model Coupling Toolkit v2.10", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MCSclimate/MCT", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "v2.10" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Model_Coupling_Toolkit_v2.11.json b/agency-indexes/DoE/Model_Coupling_Toolkit_v2.11.json new file mode 100644 index 00000000..0e832c0a --- /dev/null +++ b/agency-indexes/DoE/Model_Coupling_Toolkit_v2.11.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jacob@anl.gov" + }, + "date": { + "created": "2021-11-08", + "metadataLastUpdated": "2021-11-08" + }, + "description": "Model Coupling Tookit", + "laborHours": 34184.8, + "languages": [], + "name": "Model Coupling Toolkit v2.11", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MCSclimate/MCT", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "2.11" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Model_for_Prediction_Across_Scales_-_Sea_ice__MPAS-Seaice_.json b/agency-indexes/DoE/Model_for_Prediction_Across_Scales_-_Sea_ice__MPAS-Seaice_.json new file mode 100644 index 00000000..bd5c6962 --- /dev/null +++ b/agency-indexes/DoE/Model_for_Prediction_Across_Scales_-_Sea_ice__MPAS-Seaice_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-10-28", + "metadataLastUpdated": "2021-10-28" + }, + "description": "The Model for Prediction Across Scales-Seaice (MPAS-Seaice) is an unstructured-mesh sea ice model (sea ice is the frozen surface of the sea at high latitudes) capable of using enhanced horizontal resolution in selected regions of the sea-ice domain. The model has the capability to perform high-resolution regional simulations without the need for lateral boundary conditions. MPAS-Seaice solves equations describing both the dynamics and thermodynamics of sea ice. For dynamics, MPAS-Seaice solves a momentum equations describing the balance between air and ocean surface stresses, inertia, Coriolis and sea surface tilt forces, and ice internal stresses, to determine the sea-ice velocity. This velocity is used in a transport scheme to advect mass and tracer variables. In the vertical direction, among other processes, freezing of sea-water and ice and snow melt are determined, as is the internal temperature and salinity of the ice. As external forcing, MPAS-Seaice uses wind and ocean current velocities, air and ocean temperatures and atmospheric radiation fluxes.", + "laborHours": 0.0, + "languages": [], + "name": "Model for Prediction Across Scales - Sea ice (MPAS-Seaice)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MPAS-Dev/MPAS-Model", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Modelica_Builder__ModBuild_.json b/agency-indexes/DoE/Modelica_Builder__ModBuild_.json new file mode 100644 index 00000000..6ecea265 --- /dev/null +++ b/agency-indexes/DoE/Modelica_Builder__ModBuild_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-04-08", + "metadataLastUpdated": "2020-04-09" + }, + "description": "Modelica is a modeling and simulation language similar to Matlab/Simulink. Modelica has many advantages, which will not be discussed here, over conventional software. The software project implements a parser of the Modelica language allowing for easy-to-implement transformations of Modelica files.\n", + "laborHours": 4985.6, + "languages": [ + "Modelica" + ], + "name": "Modelica Builder (ModBuild)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/urbanopt/modelica-builder", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Modelica_Buildings_Library.json b/agency-indexes/DoE/Modelica_Buildings_Library.json new file mode 100644 index 00000000..5b952530 --- /dev/null +++ b/agency-indexes/DoE/Modelica_Buildings_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2019-10-04" + }, + "description": "The Building Informatics Environment is a modeling environment based on the Modelica language. The environment allows users to create a computer model of a building and its energy systems with various time scales and physical resolutions. The environment can be used for rapid development of e.g. demand controls algorithms new HVAC system solutions and new operational strategies. Models for building energy and control systems are made available in the environment. The models can be used as provided or they can be changed or linked with each other in order to model the effects that a particular user is interested in.", + "laborHours": 100122.4, + "languages": [], + "name": "Modelica Buildings Library", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-srg/modelica-buildings", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Modelica_Buildings_Library_Extension_for_AC_and_DC_Building_Comparison__Modelica_DC_Buildings__v1.json b/agency-indexes/DoE/Modelica_Buildings_Library_Extension_for_AC_and_DC_Building_Comparison__Modelica_DC_Buildings__v1.json new file mode 100644 index 00000000..4e7b3e24 --- /dev/null +++ b/agency-indexes/DoE/Modelica_Buildings_Library_Extension_for_AC_and_DC_Building_Comparison__Modelica_DC_Buildings__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-01-07", + "metadataLastUpdated": "2020-01-07" + }, + "description": "This software simulates and compares the losses in AC and DC buildings. It uses formatted load profile data from EnergyPlus, PV generation data from PVWatts, realistic converter efficiency curves based on product data, a battery controller based on excess PV, and a realistic wire model. The software includes Modelica code, which is an extension of the Buildings Library Electrical models. It also includes Python code, which manages the Modelica parametric simulations and plots results.", + "laborHours": 36571.2, + "languages": [], + "name": "Modelica Buildings Library Extension for AC and DC Building Comparison (Modelica DC Buildings) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dgerb/DCBuildingSimModelica", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Modelica_IBPSA_Library_v1.json b/agency-indexes/DoE/Modelica_IBPSA_Library_v1.json new file mode 100644 index 00000000..eaf57696 --- /dev/null +++ b/agency-indexes/DoE/Modelica_IBPSA_Library_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-07", + "metadataLastUpdated": "2019-06-26" + }, + "description": "The Modelica IBPSA library is a free open-source library with basic models that codify best practices for the implementation of models for building and community energy and control systems. \n\nThe development of the IBPSA library is organized through the IBPSA Project 1 (https://ibpsa.github.io/project1) of the International Building Performance Simulation Association (IBPSA). \n\nThis library is typically not used directly by end-users. Rather, it is integrated by developers of other Modelica libraries for building and community energy systems, who then distribute it to end-users as part of their respective library.", + "laborHours": 36328.0, + "languages": [], + "name": "Modelica IBPSA Library v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ibpsa/modelica-ibpsa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Modelica_IBPSA_MPC_Library_v0.1.json b/agency-indexes/DoE/Modelica_IBPSA_MPC_Library_v0.1.json new file mode 100644 index 00000000..1d8a1a11 --- /dev/null +++ b/agency-indexes/DoE/Modelica_IBPSA_MPC_Library_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-11-25", + "metadataLastUpdated": "2019-11-25" + }, + "description": "The Modelica IBPSA MPC Library is a free open-source library with basic models that codify best practices for the implementation of models to be used in Nonlinear Model Predictive Control of building and community energy systems.\n\nThe development of the Modelica IBPSA MPC Library is organized through the IBPSA Project 1 (https://ibpsa.github.io/project1) of the International Building Performance Simulation Association (IBPSA).", + "laborHours": 15.2, + "languages": [], + "name": "Modelica IBPSA MPC Library v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ibpsa/modelica-ibpsa-mpc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Modeling_Script.json b/agency-indexes/DoE/Modeling_Script.json new file mode 100644 index 00000000..4b9f86d1 --- /dev/null +++ b/agency-indexes/DoE/Modeling_Script.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-30" + }, + "description": "This script illustrates the advantages of loychikSD_NP, e.g. acts as a demonstration of the higher-order spectral density.", + "laborHours": 0.0, + "languages": [], + "name": "Modeling Script", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SpectralDensities", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Modeling_Time_Series_Data_with_Ordinary_Differential_Equations_and_Neural_Networks.json b/agency-indexes/DoE/Modeling_Time_Series_Data_with_Ordinary_Differential_Equations_and_Neural_Networks.json new file mode 100644 index 00000000..bd9d5617 --- /dev/null +++ b/agency-indexes/DoE/Modeling_Time_Series_Data_with_Ordinary_Differential_Equations_and_Neural_Networks.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-10-11", + "metadataLastUpdated": "2019-10-11" + }, + "description": "This suite of code learns neural network models to emulate the dynamics of time series data. \n\nTo do so, it learns a set of \"neural shape functions\" that provide a common vocabulary for expressing the various dynamics operators. \n\nThe code is implemented in Python and TensorFlow.", + "laborHours": 152.0, + "languages": [ + "Python" + ], + "name": "Modeling Time Series Data with Ordinary Differential Equations and Neural Networks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tadesautels/PSINN", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Models_for_synthetic_data_generation.json b/agency-indexes/DoE/Models_for_synthetic_data_generation.json new file mode 100644 index 00000000..dd74c7f7 --- /dev/null +++ b/agency-indexes/DoE/Models_for_synthetic_data_generation.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-02-15", + "metadataLastUpdated": "2022-02-15" + }, + "description": "The software includes a suite of probabilistic statistical/machine learning models that can generate discrete synthetic data. Each model is trained on a set of real (private) data and then it can be used to generate synthetic but statistically similar data. Once ready, the model can generate as many samples as we want. Finally, in addition to the actual models, the software includes code to process data, evaluate results (based on cross validation), and produce reports.", + "laborHours": 0.0, + "languages": [], + "name": "Models for synthetic data generation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SYNDATA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Modifications_to_open_source_software_BioNetGen.json b/agency-indexes/DoE/Modifications_to_open_source_software_BioNetGen.json new file mode 100644 index 00000000..fb8552ab --- /dev/null +++ b/agency-indexes/DoE/Modifications_to_open_source_software_BioNetGen.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-02-11", + "metadataLastUpdated": "2022-02-11" + }, + "description": "Partial Scaling Algorithm (PSA), it is an accelerating algorithm for stochastic simulations of biochemical reaction networks. This algorithm is implemented in an open source computational modeling platform, BioNetGen.", + "laborHours": 0.0, + "languages": [], + "name": "Modifications to open source software BioNetGen", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/RuleWorld/bionetgen", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Modified_Embedded_Atom_Method.json b/agency-indexes/DoE/Modified_Embedded_Atom_Method.json new file mode 100644 index 00000000..b75bd5b1 --- /dev/null +++ b/agency-indexes/DoE/Modified_Embedded_Atom_Method.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Interatomic force and energy calculation subroutine to be used with the molecular dynamics simulation code LAMMPS (Ref a.). The code evaluated the total energy and atomic forces (energy gradient) according to a cubic spline-based variant (Ref b.) of the Modified Embedded Atom Method (MEAM) with a additional Stillinger-Weber (SW) contribution.", + "laborHours": 1281025.6, + "name": "Modified Embedded Atom Method", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lammps/lammps", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Modular_Aquatic_Simulation_System_1D.json b/agency-indexes/DoE/Modular_Aquatic_Simulation_System_1D.json new file mode 100644 index 00000000..dec202b7 --- /dev/null +++ b/agency-indexes/DoE/Modular_Aquatic_Simulation_System_1D.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MASS1 simulates open channel hydrodynamics and transport in branched channel networks, using cross-section averaged forms of the continuity, momentum, and convection diffusion equations. Thermal energy transport (temperature), including meteorological influences is supported. The thermodynamics of total dissolved gas (TDG) can be directly simulated. MASS1 has been developed over the last 20 years. It is currently being used on DOE projects that require MASS1 to beopen source. Hence, the authors would like to distribute MASS1 in source form.", + "laborHours": 9910.4, + "name": "Modular Aquatic Simulation System 1D", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/mass1/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mass1", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Modular_Environment_for_Graph_Research_and_Analysis_with_a_Persistent.json b/agency-indexes/DoE/Modular_Environment_for_Graph_Research_and_Analysis_with_a_Persistent.json new file mode 100644 index 00000000..3226c02b --- /dev/null +++ b/agency-indexes/DoE/Modular_Environment_for_Graph_Research_and_Analysis_with_a_Persistent.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The MEGRAPHS software package provides a front-end to graphs and vectors residing on special-purpose computing resources. It allows these data objects to be instantiated, destroyed, and manipulated. A variety of primitives needed for typical graph analyses are provided. An example program illustrating how MEGRAPHS can be used to implement a PageRank computation is included in the distribution.The MEGRAPHS software package is targeted towards developers of graph algorithms. Programmers using MEGRAPHS would write graph analysis programs in terms of high-level graph and vector operations. These computations are transparently executed on the Cray XMT compute nodes.", + "laborHours": 0.0, + "languages": [], + "name": "Modular Environment for Graph Research and Analysis with a Persistent", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/megraphs", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Modular_Finite_Element_Methods.json b/agency-indexes/DoE/Modular_Finite_Element_Methods.json new file mode 100644 index 00000000..27dddf77 --- /dev/null +++ b/agency-indexes/DoE/Modular_Finite_Element_Methods.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-03-03", + "metadataLastUpdated": "2020-05-27" + }, + "description": "MFEM is a free, lightweight, scalable C++ library for finite element methods. \n\nThe goal of MFEM is to enable research and development of scalable finite element discretization and solver algorithms through general finite element abstractions, accurate and flexible visualization, and tight integration with the hypre\nlibrary.\n\nConceptually, MFEM can be viewed as a finite element toolbox that provides the building blocks for developing finite element algorithms in a manner similar to that of MATLAB for linear algebra methods.", + "laborHours": 0.0, + "languages": [], + "name": "Modular Finite Element Methods", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfem/mfem/releases/tag/v4.1", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "4.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Modular_Finite_Element_Methods__MFEM_.json b/agency-indexes/DoE/Modular_Finite_Element_Methods__MFEM_.json new file mode 100644 index 00000000..d07e7a36 --- /dev/null +++ b/agency-indexes/DoE/Modular_Finite_Element_Methods__MFEM_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-08", + "metadataLastUpdated": "2020-05-08" + }, + "description": "MFEM is a modular parallel C++ library for finite element methods. Its goal is to enable high-performance scalable finite element discretization research and application development on a wide variety of platforms, ranging from laptops to supercomputers.", + "laborHours": 125658.4, + "languages": [], + "name": "Modular Finite Element Methods (MFEM)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfem/mfem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ModuleOT.json b/agency-indexes/DoE/ModuleOT.json new file mode 100644 index 00000000..1785c2d6 --- /dev/null +++ b/agency-indexes/DoE/ModuleOT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-25", + "metadataLastUpdated": "2021-01-26" + }, + "description": "ModuleOT is an open hardware security platform which provides all features necessary for securing remote energy resources. The platform consists of a physical bump in-the wire device which runs a custom-built application built with Go and Python and leverages AES-NI Instruction set available on modern hardware for cryptographic acceleration. By combining these features, ModuleOT acts as an all-in-one low-cost solution to enable cryptographically secured communications to any critical remote servers or devices. Because the software application has been built using Golang, this source can be easily compiled for different hardware platforms. The module is designed to provide the following core features: (1) encrypted communications across an untrusted network, (2) certificate-based authentication with secure storage, (3) hardware cryptographic acceleration, (4) IP-based whitelisting, (5) local firewall management, and (6) legacy (RS485) device support.\n", + "laborHours": 0.0, + "languages": [], + "name": "ModuleOT", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ModuleOT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Module_Cmonkey_version_1.0.json b/agency-indexes/DoE/Module_Cmonkey_version_1.0.json new file mode 100644 index 00000000..320df793 --- /dev/null +++ b/agency-indexes/DoE/Module_Cmonkey_version_1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "This module provides a method for work with cMonkey biclustering tool from the Baliga Lab at the Institute for Systems Biology. cMonkey takes as input gene expression data, promoter sequences, and gene-gene functional association/physical interaction data to find biclusters of conditionally co-regulated genes.", + "laborHours": 15291.2, + "languages": [], + "name": "Module Cmonkey version 1.0", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/cmonkey", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Module_Inferelator_Version_1.0.json b/agency-indexes/DoE/Module_Inferelator_Version_1.0.json new file mode 100644 index 00000000..19f90014 --- /dev/null +++ b/agency-indexes/DoE/Module_Inferelator_Version_1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This module provides a method to work with the Inferelator algorithm from the Baliga Lab at the Institute for Systems Biology. The Inferelator algorithm infers regulatory networks from gene expression data, and takes as input cMonkey biclusters, a list of regulators, and expression data.", + "laborHours": 13148.0, + "languages": [], + "name": "Module Inferelator Version 1.0", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/inferelator", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Module_MEME_version_1.0.json b/agency-indexes/DoE/Module_MEME_version_1.0.json new file mode 100644 index 00000000..626f76a2 --- /dev/null +++ b/agency-indexes/DoE/Module_MEME_version_1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "This module provides a set of functions for work with regulatory motifs. These functions integrate capabilities of three predictive tools into KBase: MEME is a tool for discovering motifs in a group of related DNA or protein sequences; TOMTOM is a tool for comparison of an input DNA motif to the elements of a database of known motifs; MAST is a tool for searching biological sequence databases for occurencies of known motifs.", + "laborHours": 13239.2, + "languages": [], + "name": "Module MEME version 1.0", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/meme", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Moertel_Fe_Package.json b/agency-indexes/DoE/Moertel_Fe_Package.json new file mode 100644 index 00000000..6792fe32 --- /dev/null +++ b/agency-indexes/DoE/Moertel_Fe_Package.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Moertel supplies capabilities for nonconforming mesh tying and contact formulations in 2 and 3 dimensions using Mortar methods. Motar methods are a type of Lagrange Multiplier constraints that can be used in contact formulations and in non-conforming or conforming mesh typing as well as in domain decomposition techniques. Suitable conditions at interfaces are formulated as weak continuity conditions in dual variables introducing Lagrange multiplers on the interface. By an appropriate choice of the function space of the Lagrange multipliers on an interface it is possible to locally condense Lagrange multipliers such that a sparse and definite system of equations can be formed which is equalivalent to the saddle point system resulting from the Lagrange multiplier formulation.", + "laborHours": 16020.8, + "languages": [ + "C++" + ], + "name": "Moertel Fe Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Moertel", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Moirai_Land_Data_System__Moirai__v3.0.0.json b/agency-indexes/DoE/Moirai_Land_Data_System__Moirai__v3.0.0.json new file mode 100644 index 00000000..aa54992a --- /dev/null +++ b/agency-indexes/DoE/Moirai_Land_Data_System__Moirai__v3.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-02", + "metadataLastUpdated": "2019-10-02" + }, + "description": "The Moirai Land Data System (Moirai LDS) is designed to produce recent historical land data inputs for the AgLU module of GCAM data system , but the Moirai LDS outputs could also be used by other models/applications. The Moirai are the Greek Fates, and this software is named Moirai to represent the fundamental influence of land data inputs on model outcomes. The primary function of the Moirai LDS is to combine spatially explicit input data (e.g., raster images) with tabular input data (e.g., crop price table) to generate tabular output data for a suite of variables. Some of these outputs replace the data provide by the Global Trade Analysis Project (GTAP), and other data replace and augment the original GCAM GIS processing. The Moirai LDS output data are aggregated by Geographic Land Unit (GLU) within each country. The GLU coverage is an input to the Moirai LDS (as a thematic raster image and an associated CSV file that maps the thematic integers to names), and the GLU boundaries can be determined arbitrarily. Previous versions of GCAM (and Moirai LDS) used only bioclimatic Agro-Ecological Zones (AEZs) and corresponding data that were provided by GTAP, as the GLUs. As a result, some AEZ terminology still exists in the code, but this terminology now refers more generally to GLUs. The Moirai LDS now enables any set of boundaries to be used as GLUs (including AEZs), allowing for more flexible generation of land use region boundaries (defined as the intersection of GLUs with geopolitical regions). The current default set of GLUs is the same set of 235 global watersheds as used by the GCAM water module. The GCAM 5.1 geopolitical regions (32 or 14) are included and used as inputs to Moirai to generate a mapping file between the Moirai outputs, which are at the level of the intersection between the GLUs and the country boundaries, and the geopolitical regions. The diagnostics scripts use this geopolitical region mapping in some cases. Moirai can also recalibrate three of the outputs (crop production, harvested area, and land rent) to a specified year that is the center of a five-year averaging window. No recalibration retains the circa 2000, 7-year average of the source data. The cucrrency-year for land rent can also be specified, and the default is 2001 to match the GTAP data.", + "laborHours": 7752.0, + "languages": [], + "name": "Moirai Land Data System (Moirai) v3.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/moirai", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mojo_Application_Monitoring_Tool_Suite.json b/agency-indexes/DoE/Mojo_Application_Monitoring_Tool_Suite.json new file mode 100644 index 00000000..ac474e30 --- /dev/null +++ b/agency-indexes/DoE/Mojo_Application_Monitoring_Tool_Suite.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-29" + }, + "description": "Mojo is a software tool suite that can be used to monitor the progress of compute jobs on Linux Clusters and other high-performance computing platforms. Mojo is designed to allow system administrators to monitor the health and progress of computing jobs, and to allow users to view the progress and status of their own jobs. The facilities provided include the ability to notify users of job \"hangs\", and to take an automated action (e.g killing the job) when something goes wrong. These operations can lead to a more efficient use of scarce resources.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "Mojo Application Monitoring Tool Suite", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Molecular_Weight_Calculator.json b/agency-indexes/DoE/Molecular_Weight_Calculator.json new file mode 100644 index 00000000..9057996c --- /dev/null +++ b/agency-indexes/DoE/Molecular_Weight_Calculator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This program can calculate the molecular weight and percent composition of chemical formulas and amino acids, providing a graphical user interface to edit the formulas and parsing options. It recognizes user-definable abbreviations, custom elemental isotopes, and can display up to 20 compounds simultaneously. It also includes a Mole/Mass Converter, Formula Finder, Capillary Flow Modeller, Amino Acid Notation Converter, Peptide Sequence Fragmentation Modeler, Isotopic Distribution Calculator, and built-in calculator. Full program documentation is available by pressing F1 during program operation.", + "laborHours": 30962.4, + "languages": [], + "name": "Molecular Weight Calculator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Molecular-Weight-Calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Molecular_Weight_Calculator_Library.json b/agency-indexes/DoE/Molecular_Weight_Calculator_Library.json new file mode 100644 index 00000000..9124fc3c --- /dev/null +++ b/agency-indexes/DoE/Molecular_Weight_Calculator_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MwtWinDLL contains utility functions for calculating the molecular weight and percent composition of chemical formulas and amino acids. It recognizes user-definable abbreviations and custom elemental isotopes. It also includes a Mole/Mass Converter, Formula Finder, Capillary Flow Modeller, Amino Acid Notation Converter, Isotopic Distribution Calculator, and Peptide Sequence Fragmentation Modeller. To use, simply include the DLL in a .NET project.", + "laborHours": 6596.8, + "languages": [], + "name": "Molecular Weight Calculator Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Molecular-Weight-Calculator-DLL", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Molecules_in_Studio_v._1.0.json b/agency-indexes/DoE/Molecules_in_Studio_v._1.0.json new file mode 100644 index 00000000..fd5ef1fe --- /dev/null +++ b/agency-indexes/DoE/Molecules_in_Studio_v._1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "A Powersim Studio implementation of the system dynamics\u2019 \u2018Molecules of Structure\u2019. The original implementation was in Ventana\u2019s Vensim language by James Hines. The molecules are fundamental constructs of the system dynamics simulation methodology.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Powersim Studio 7, Feature Pack 3, Service Release 9" + ], + "name": "Molecules in Studio v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Moment_Closures_on_Two-Dimensional_Cartesian_Grids.json b/agency-indexes/DoE/Moment_Closures_on_Two-Dimensional_Cartesian_Grids.json new file mode 100644 index 00000000..4f54be36 --- /dev/null +++ b/agency-indexes/DoE/Moment_Closures_on_Two-Dimensional_Cartesian_Grids.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Some moment methods for kinetic equations are complicated and take time to develop. Over the course of a couple years, this software was developed to test different closures on standard test problems in the literature. With this software, researchers in the field of moment closures will be able to rapidly test new methods.", + "laborHours": 22298.4, + "name": "Moment Closures on Two-Dimensional Cartesian Grids", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ckrisgarrett/closures-2d", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ckrisgarrett/closures-2d", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Moment_Tensor_Inversion_Toolkit.json b/agency-indexes/DoE/Moment_Tensor_Inversion_Toolkit.json new file mode 100644 index 00000000..d3c196e4 --- /dev/null +++ b/agency-indexes/DoE/Moment_Tensor_Inversion_Toolkit.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-09-20", + "metadataLastUpdated": "2024-09-20" + }, + "description": "The MTINV toolkit (2002-present) is a collection of computer codes and applications written to invert for\nthe moment tensor of a seismic source given the three components of ground motion recorded at regional\nseismic stations (e.g., Ichinose et al., 2003). The computer codes and workflow are organized to\ngenerate moment tensor solutions for a range of source depths and origin times because of the trade-off\nbetween these two quantities. The metric used is the variance reduction and variance reduction\nmodulated by the percent double-couple to determine the best-fit moment-tensor solution. We can solve\nfor a deviatoric moment tensor with a constraint added for no isotropic component although this constraint\ncan be lifted for estimating the full moment tensor like mining collapses or explosion sources.", + "laborHours": 40325.6, + "languages": [], + "name": "Moment Tensor Inversion Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mtinv", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "4.0.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Monte_Carlo_Markov_Chain_Biosensor_Analysis__MCMCBA__v1.0.json b/agency-indexes/DoE/Monte_Carlo_Markov_Chain_Biosensor_Analysis__MCMCBA__v1.0.json new file mode 100644 index 00000000..51567932 --- /dev/null +++ b/agency-indexes/DoE/Monte_Carlo_Markov_Chain_Biosensor_Analysis__MCMCBA__v1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-05-02", + "metadataLastUpdated": "2021-06-15" + }, + "description": "A pipeline to estimate the limits of detection and resolution of transcription factor encoded biosensors", + "laborHours": 0.0, + "languages": [], + "name": "Monte Carlo Markov Chain Biosensor Analysis (MCMCBA) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/biosensor_characterization_public", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Montepy.json b/agency-indexes/DoE/Montepy.json new file mode 100644 index 00000000..bf237a5a --- /dev/null +++ b/agency-indexes/DoE/Montepy.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2024-01-15", + "metadataLastUpdated": "2024-01-25" + }, + "description": "Montepy is an object-oriented Python interface for MCNP input files. It excels at reading, editing, creating, and writing MCNP input files. The Monte Carlo N Particle (MCNP) code is a Monte Carlo transport solver for simulating many different types of radiation problems and is developed by Los Alamos National Laboratory. Montepy creates an object-oriented interface for the MCNP input file to allow for efficient automated modifications to large, complex simulations.", + "laborHours": 0.0, + "languages": [ + "python3.8" + ], + "name": "Montepy", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/MontePy", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MoorPy__Quasi-Static_Mooring_Analysis_in_Python_.json b/agency-indexes/DoE/MoorPy__Quasi-Static_Mooring_Analysis_in_Python_.json new file mode 100644 index 00000000..2235ec46 --- /dev/null +++ b/agency-indexes/DoE/MoorPy__Quasi-Static_Mooring_Analysis_in_Python_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2021-07-26" + }, + "description": "MoorPy is a quasi-static mooring model and a suite of associated functions for mooring system analysis. The core model supports quasi-static analysis of moored floating systems including any arrangement of mooring lines and floating platforms. It solves the distributed position and tension of each mooring line segment using standard catenary equations. Floating platforms can be represented with linear hydrostatic characteristics. MoorPy automatically computes a floating system's equilibrium state and can be queried to identify a mooring system's nonlinear force-displacement relationships. Linearized stiffness matrices are efficiently computed using semi-analytic Jacobians. MoorPy also includes plotting functions and a library of mooring component property and cost coefficients. MoorPy can be used directly from Python scripts to perform mooring design and analysis tasks, or it can be coupled with other tools to compute quasi-static mooring reactions as part of a larger simulation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "MoorPy (Quasi-Static Mooring Analysis in Python)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MoorPy", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Mota_Mapper:_A_Multi-Objective_Topology-Aware_Mapper_Library.json b/agency-indexes/DoE/Mota_Mapper:_A_Multi-Objective_Topology-Aware_Mapper_Library.json new file mode 100644 index 00000000..6ed0b972 --- /dev/null +++ b/agency-indexes/DoE/Mota_Mapper:_A_Multi-Objective_Topology-Aware_Mapper_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-05-15", + "metadataLastUpdated": "2018-05-15" + }, + "description": "Mota is a library that provides several heuristics for mapping tasks to compute ranks (processes) on a networked computer cluster or supercomputer. It was originally designed for task placement of adaptive mesh refinement codes (AMR). It is multi-objective in the sense that it simultaneously balances (potentially multiple types of) computational load on each rank as well as the communication traffic between the boxes. The heuristics used for mapping include algorithms such as greedy list assignment and space-filling curves, as well as algorithms from graph analysis such as adjacency matrix bandwidth reduction, recursive bisection, and greedy graph placement.", + "laborHours": 1930.4, + "languages": [], + "name": "Mota Mapper: A Multi-Objective Topology-Aware Mapper Library", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-CoDEx/mota", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MotifEnsemble.json b/agency-indexes/DoE/MotifEnsemble.json new file mode 100644 index 00000000..a88401ca --- /dev/null +++ b/agency-indexes/DoE/MotifEnsemble.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"MotifEnsemble\" developed by KBase. This is a KBase module generated by the KBase Software Development Kit (SDK).", + "laborHours": 1231.2, + "languages": [], + "name": "MotifEnsemble", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/MotifEnsemble", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MotifFinderGibbs.json b/agency-indexes/DoE/MotifFinderGibbs.json new file mode 100644 index 00000000..816e6db9 --- /dev/null +++ b/agency-indexes/DoE/MotifFinderGibbs.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"MotifFinderGibbs\" developed by KBase. This is a KBase module generated by the KBase Software Development Kit (SDK).", + "laborHours": 2243808.8, + "languages": [], + "name": "MotifFinderGibbs", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/MotifFinderGibbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MotifFinderHomer.json b/agency-indexes/DoE/MotifFinderHomer.json new file mode 100644 index 00000000..a295fbc2 --- /dev/null +++ b/agency-indexes/DoE/MotifFinderHomer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"MotifFinderHomer\" developed by KBase. This is a KBase module generated by the KBase Software Development Kit (SDK).", + "laborHours": 1565.6, + "languages": [], + "name": "MotifFinderHomer", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/MotifFinderHomer", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MotifFinderMEME.json b/agency-indexes/DoE/MotifFinderMEME.json new file mode 100644 index 00000000..58d43bdf --- /dev/null +++ b/agency-indexes/DoE/MotifFinderMEME.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"MotifFinderMEME\" developed by KBase. This is a KBase module generated by the KBase Software Development Kit (SDK).", + "laborHours": 1702.4, + "languages": [], + "name": "MotifFinderMEME", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/MotifFinderMEME", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MotifUtils.json b/agency-indexes/DoE/MotifUtils.json new file mode 100644 index 00000000..7683dde5 --- /dev/null +++ b/agency-indexes/DoE/MotifUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"MotifUtils\" developed by KBase. This is a KBase module generated by the KBase Software Development Kit (SDK).", + "laborHours": 4438.4, + "languages": [], + "name": "MotifUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/MotifUtils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Motility_Analysis_of_T-Cell_Histories_in_Activation__Matcha__v0.1.0.json b/agency-indexes/DoE/Motility_Analysis_of_T-Cell_Histories_in_Activation__Matcha__v0.1.0.json new file mode 100644 index 00000000..6c53dff1 --- /dev/null +++ b/agency-indexes/DoE/Motility_Analysis_of_T-Cell_Histories_in_Activation__Matcha__v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-18", + "metadataLastUpdated": "2024-07-18" + }, + "description": "Despite advances in microscopy, imaging techniques only capture a very small spatial and temporal fraction of T cell activity within a tissue. For this reason, we have pursued the development of a virtual T cell model. Matcha's objective is to design virtual T cells that move like biological T cells. The virtual T cells will match the speed and turning angle distributions of biological cells. In addition, Matcha will also attempt to match the volume patrolled by the biological cells and the dependence on speed and turning angle on the previous speed.", + "laborHours": 790.4, + "languages": [], + "name": "Motility Analysis of T-Cell Histories in Activation (Matcha) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/matcha", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MountPointAttributes.json b/agency-indexes/DoE/MountPointAttributes.json new file mode 100644 index 00000000..2909170a --- /dev/null +++ b/agency-indexes/DoE/MountPointAttributes.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MountPointAttributes is a software component that provides client code with a technique to raise the local namespace of a file to a global namespace. Its abstractions and mechanisms allow the client code to gather global properties of a file and to use them in devising an effective storage access strategy on this file.", + "laborHours": 2872.8, + "name": "MountPointAttributes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/mountpointattributes", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MpsManager.json b/agency-indexes/DoE/MpsManager.json new file mode 100644 index 00000000..514b5e5e --- /dev/null +++ b/agency-indexes/DoE/MpsManager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-14", + "metadataLastUpdated": "2022-07-14" + }, + "description": "The MpsManager provides an extra security layer for important MPS configuration parameters: analog device thresholds and bypasses. The MpsManager server writes/reads information to/from the MPS runtime configuration database (https://github.com/slaclab/mps_database/tree/master/runtime).", + "laborHours": 0.0, + "languages": [], + "name": "MpsManager", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/mps_manager/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/mps_manager", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MrHyDE_v.1.0.json b/agency-indexes/DoE/MrHyDE_v.1.0.json new file mode 100644 index 00000000..8c425453 --- /dev/null +++ b/agency-indexes/DoE/MrHyDE_v.1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-21" + }, + "description": "SAND2024-01324O\nMrHyDE, which stands for Multi-resolution Hybridized Differential Equations, is a general-purpose C++ package for the solution of coupled multiphysics and multiscale systems on massively parallel computing systems. \n\nMrHyDE is designed to enable moving beyond forward simulation for multiscale applications which includes optimization, control, uncertainty quantification, and stochastic inversion. The framework provides interfaces to several packages within the Trilinos framework and leverages automatic differentiation to enable adjoint capabilities for large-scale, gradient-based optimization. MrHyDE provides automated multiscale capabilities through a subgrid model interface and multiscale Dirichlet-to-Neumann maps. \n\nFor extreme-scale applications, MrHyDE provides in situ data-compression algorithms to reduce memory requirements while maintaining performance. MrHyDE is a general-purpose, computational framework for the solution of multiscale and multiphysics applications. It uses a combination of structure-preserving, physics-compatible discretizations, fully implicit methods, multi-resolution schemes, or fully explicit methods. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python" + ], + "name": "MrHyDE v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MrHyDE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MsDataFileReader.json b/agency-indexes/DoE/MsDataFileReader.json new file mode 100644 index 00000000..d6851661 --- /dev/null +++ b/agency-indexes/DoE/MsDataFileReader.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A VB.NET DLL that can read mass spectrometry data from four file formats: mzXML, mzData, concatenated .dta files (_dta.txt), and Mascot Generic Format files (.mgf)", + "laborHours": 4225.6, + "languages": [], + "name": "MsDataFileReader", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MS-Data-File-Reader", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MueLu_Multigrid_Preconditioning_Package.json b/agency-indexes/DoE/MueLu_Multigrid_Preconditioning_Package.json new file mode 100644 index 00000000..bb94585f --- /dev/null +++ b/agency-indexes/DoE/MueLu_Multigrid_Preconditioning_Package.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "MueLu is intended for the research and development of multigrid algorithms used in the solution of sparse linear systems arising from systems of partial differential equations. The software provides multigrid source code, test programs, and short example programs to demonstrate the various interfaces for creating, accessing, and applying the solvers. MueLu currently provides an implementation of smoothed aggregation algebraic multigrid method and interfaces to many commonly used smoothers. However, the software is intended to be extensible, and new methods can be incorporated easily. MueLu also allows for advanced usage, such as combining multiple methods and segregated solves. The library supports point and block access to matrix data. All algorithms and methods in MueLu have been or will be published in the open scientific literature.", + "laborHours": 8344830.4, + "languages": [], + "name": "MueLu Multigrid Preconditioning Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-BGK.json b/agency-indexes/DoE/Multi-BGK.json new file mode 100644 index 00000000..366db1fa --- /dev/null +++ b/agency-indexes/DoE/Multi-BGK.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-04-11", + "metadataLastUpdated": "2018-04-11" + }, + "description": "This code package solves the multi-species 1D-3V BGK kinetic model of Haack, Hauck, and Murillo [J. Stat. Phys., 168, 2017, Phys. Rev. E, submitted, 2017]. This model conserves mass, momentum, and energy and satisfies Boltzmann's H Theorem, i.e. entropy dissipation. Additionally, the collision model matches either the momentum or temperature relaxation rate of the Boltzmann equation. It can be run in 0D-3V and 1D-3V modes.", + "laborHours": 3070.4, + "name": "Multi-BGK", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Multi-BGK", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-Channel_Time-Frequency_Analysis.json b/agency-indexes/DoE/Multi-Channel_Time-Frequency_Analysis.json new file mode 100644 index 00000000..95b39b26 --- /dev/null +++ b/agency-indexes/DoE/Multi-Channel_Time-Frequency_Analysis.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-28", + "metadataLastUpdated": "2023-02-28" + }, + "description": "This software contains models for multi-channel time series data. The models are time-frequency descriptions of the data. Also included are prediction performance evaluation tools. These models can be applied to electrophysiology data such as electrocorticography.", + "laborHours": 0.0, + "languages": [], + "name": "Multi-Channel Time-Frequency Analysis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/alankaplan/mctfa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-Configuration_Membrane_Distillation_Model_1.0_.json b/agency-indexes/DoE/Multi-Configuration_Membrane_Distillation_Model_1.0_.json new file mode 100644 index 00000000..509c2a26 --- /dev/null +++ b/agency-indexes/DoE/Multi-Configuration_Membrane_Distillation_Model_1.0_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-04-12", + "metadataLastUpdated": "2018-04-12" + }, + "description": "The MCMD 1.0 model is used to quantify mass and heat transfer for both direct contact and air gap membrane distillation technologies. The code is designed to be able to be extended to include many different membrane distillation configurations of which air-gap and direct contact are two examples that have already been implemented. ", + "laborHours": 6642.4, + "name": "Multi-Configuration Membrane Distillation Model 1.0 ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dlvilla/mcmd1", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-Energy_Differential_Evolution_Reconstruction__MEnDER_1D__for_Proton_Deflectometry.json b/agency-indexes/DoE/Multi-Energy_Differential_Evolution_Reconstruction__MEnDER_1D__for_Proton_Deflectometry.json new file mode 100644 index 00000000..b0ee309f --- /dev/null +++ b/agency-indexes/DoE/Multi-Energy_Differential_Evolution_Reconstruction__MEnDER_1D__for_Proton_Deflectometry.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-19", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This code is designed to reconstruct magnetic field deflections, and thus the path-integrated magnetic field, from sets of proton images at two distinct proton probe energies. A differential evolution (DE) algorithm is used to iteratively update a population of solution candidates of the magnetic deflections of the protons for reconstructing the input images, selecting improved candidates as they are discovered. This algorithm was written using MATLAB (R2019a) and makes use of the Image Processing and Parallel Processing Toolboxes.", + "laborHours": 0.0, + "languages": [], + "name": "Multi-Energy Differential Evolution Reconstruction (MEnDER 1D) for Proton Deflectometry", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MEnDER-1D", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-Phenotype_Association__MPA__Decomposition.json b/agency-indexes/DoE/Multi-Phenotype_Association__MPA__Decomposition.json new file mode 100644 index 00000000..e632c02d --- /dev/null +++ b/agency-indexes/DoE/Multi-Phenotype_Association__MPA__Decomposition.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "landryne@ornl.gov" + }, + "date": { + "created": "2022-03-10", + "metadataLastUpdated": "2022-03-10" + }, + "description": "This code is used to determine the different types of pleiotropy among genes and multiple phenotypes", + "laborHours": 0.0, + "languages": [], + "name": "Multi-Phenotype Association (MPA) Decomposition", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/daweighill/MPA_decomp", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-Purpose,_Application-Centric,_Scalable_I_O_Proxy_Application.json b/agency-indexes/DoE/Multi-Purpose,_Application-Centric,_Scalable_I_O_Proxy_Application.json new file mode 100644 index 00000000..01cf343f --- /dev/null +++ b/agency-indexes/DoE/Multi-Purpose,_Application-Centric,_Scalable_I_O_Proxy_Application.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MACSio is a Multi-purpose, Application-Centric, Scalable I/O proxy application. It is designed to support a number of goals with respect to parallel I/O performance testing and benchmarking including the ability to test and compare various I/O libraries and I/O paradigms, to predict scalable performance of real applications and to help identify where improvements in I/O performance can be made within the HPC I/O software stack.", + "laborHours": 36814.4, + "name": "Multi-Purpose, Application-Centric, Scalable I/O Proxy Application", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MACSio", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-Scenario_Extreme_Weather_Simulator.json b/agency-indexes/DoE/Multi-Scenario_Extreme_Weather_Simulator.json new file mode 100644 index 00000000..1a01ffda --- /dev/null +++ b/agency-indexes/DoE/Multi-Scenario_Extreme_Weather_Simulator.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2021-07-26" + }, + "description": "The Multi-scenario Extreme Weather Simulator (MEWS) takes existing historical weather data and inserts trends and extreme events such as heat waves, hurricanes, extreme precipitation, or winter storms. The code includes functionality for projecting increasing frequency and duration of such events over a large range of statistically sampled realizations of the future. These weather files can then be used in building energy simulations through the Energy Plus software created by DOE. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-8658 O", + "laborHours": 0.0, + "languages": [ + "Python", + "cython" + ], + "name": "Multi-Scenario Extreme Weather Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/MEWS", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-Task_Convolutional_Neural_Networks_for_Natural_Text_Classification.json b/agency-indexes/DoE/Multi-Task_Convolutional_Neural_Networks_for_Natural_Text_Classification.json new file mode 100644 index 00000000..a9175d38 --- /dev/null +++ b/agency-indexes/DoE/Multi-Task_Convolutional_Neural_Networks_for_Natural_Text_Classification.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Information extraction and coding of free-text pathology reports is an important activity for cancer registries to support national cancer surveillance. Cancer registrars must process high volumes of pathology reports on an annual basis. We investigated an automated approach using a convolutional neural networks (CNNs) for extracting the primary site, laterality, histology, behavior, and histological grade from unstructured cancer pathology text reports. Our multi-task learning (MTL) with hard parameter sharing approach is used to train a multi-task MT-CNN model for all the tasks. The performance of our proposed approach was compared against a state of-the-art CNN and the commonly used SVM classifier. We observed that the proposed model consistently outperformed the baseline models, especially for the less prevalent classes. Also, the results demonstrate the potential of the proposed method for handling class imbalance within each task.", + "laborHours": 273.6, + "languages": [ + "Python" + ], + "name": "Multi-Task Convolutional Neural Networks for Natural Text Classification", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CBIIT/pilot3_MT-CNN_ORNL", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-Task_Learning_Software_Suite.json b/agency-indexes/DoE/Multi-Task_Learning_Software_Suite.json new file mode 100644 index 00000000..4e26738d --- /dev/null +++ b/agency-indexes/DoE/Multi-Task_Learning_Software_Suite.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-11-26" + }, + "description": "Software suite with multitask learning models. The pipeline includes functionality to process data, train, evaluate models, and generate reports.", + "laborHours": 1444.0, + "languages": [], + "name": "Multi-Task Learning Software Suite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MTL-suite", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-area_Grid_Metrics_Analyzer.json b/agency-indexes/DoE/Multi-area_Grid_Metrics_Analyzer.json new file mode 100644 index 00000000..ee633857 --- /dev/null +++ b/agency-indexes/DoE/Multi-area_Grid_Metrics_Analyzer.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The MAGMA software package is a package created in the R scripting language that reads a SQL database and outputs tables and figures of important data. The SQL database is created by another R package called \u201crplexos\u201d and uses the .zip solution file output by PLEXOS, which is commercially available production cost modeling software.", + "laborHours": 3435.2, + "name": "Multi-area Grid Metrics Analyzer", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/MAGMA", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/MAGMA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-choice_Viromics_Pipeline__MVP__v1.json b/agency-indexes/DoE/Multi-choice_Viromics_Pipeline__MVP__v1.json new file mode 100644 index 00000000..ca1ef941 --- /dev/null +++ b/agency-indexes/DoE/Multi-choice_Viromics_Pipeline__MVP__v1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-09-28", + "metadataLastUpdated": "2023-09-28" + }, + "description": "MVP stands for Multi-choice Viromics Pipeline. It is a pipeline that utilizes a suite of state-of-art tools:\n\ngeNomad to identify viruses, proviruses, and plasmids in sequencing data,\n\nCheckV to assess the quality, and completeness of identified viral genomes, including identification of host contamination for integrated proviruses,\nA custom code for a rapid genome clustering based on pairwise ANI,\n\nBowtie2, Samtools, and CoverM to calculate coverage of individual viral genomes by read mapping,\nA custom code to create a vOTU table of abundance,\n\nMMseqs2 to compare viral proteins to multiple databases.\n\nIt provides a quick, and intuitive pipeline to get viral sequences and corresponding properties that can be used for downstream analyses.", + "laborHours": 0.0, + "languages": [], + "name": "Multi-choice Viromics Pipeline (MVP) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ccoclet/mvp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-feedstock_Supply_Chain_Optimization_Model.json b/agency-indexes/DoE/Multi-feedstock_Supply_Chain_Optimization_Model.json new file mode 100644 index 00000000..417b5bfc --- /dev/null +++ b/agency-indexes/DoE/Multi-feedstock_Supply_Chain_Optimization_Model.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-06", + "metadataLastUpdated": "2023-03-15" + }, + "description": "This tool can be used to determine a least-cost feedstock mix from crop residue, energy crop and MSW to meet conversion specifications, while also identifying appropriate depot locations and size, given that depot can be co-located with the biorefinery or can be located in any counties in the biofinery\u2019s supply shed.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Multi-feedstock Supply Chain Optimization Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/MFSCO", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-genome_Phage_Annotation_Toolkit_and_Evaluator.json b/agency-indexes/DoE/Multi-genome_Phage_Annotation_Toolkit_and_Evaluator.json new file mode 100644 index 00000000..fbbb78fd --- /dev/null +++ b/agency-indexes/DoE/Multi-genome_Phage_Annotation_Toolkit_and_Evaluator.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-14" + }, + "description": "Summary: To address the need for improved tools for annotation and comparative genomics of bacteriophage genomes, we developed multiPhATE2. As an extension of the multiPhATE code, multiPhATE2 includes comparative genomics codes for gene matching among sets of input bacteriophage genomes, and scales well to large input data sets due to incorporation of multiprocessing in the functional annotation and comparative genomics subsystems. Furthermore, additional search algorithms and databases have been added to the functional annotation subsystem. MultiPhATE2 was implemented in Python 3.7, and runs as a command-line code under Linux or MAC-OS.", + "laborHours": 0.0, + "languages": [], + "name": "Multi-genome Phage Annotation Toolkit and Evaluator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/multiPhATE2", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-modal_Free-moving_Data_Fusion__MFDF__v1.0.json b/agency-indexes/DoE/Multi-modal_Free-moving_Data_Fusion__MFDF__v1.0.json new file mode 100644 index 00000000..63f54ee2 --- /dev/null +++ b/agency-indexes/DoE/Multi-modal_Free-moving_Data_Fusion__MFDF__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-01", + "metadataLastUpdated": "2021-07-08" + }, + "description": "Multi-modal Free-moving Data Fusion (MFDF) is a python package that implements low and high-level functionality for performing qualitative and quantitative gamma-ray imaging analyses. Such analyses enable the use of gamma-ray spectrometers and/or imagers to estimate the distribution and quantity of radiological materials in an environment. Free-moving 3D imaging requires additional information about the 3D trajectory and orientation of the system, however all of these methods can be applied to 2D static gamma-ray imaging as well. The package includes methods (MLEM and MAP) for distributed source reconstruction, methods (PSL) for point source reconstruction, the ability to ingest and utilize quantitative detector response functions (for absolute analyses), and the ability to perform 3D estimation of dose-rates from quantitative reconstructions.", + "homepageURL": "https://ipo.lbl.gov/multimodal-free-moving-data-fusion-for-gamma-ray-imaging-analysis", + "laborHours": 0.0, + "languages": [], + "name": "Multi-modal Free-moving Data Fusion (MFDF) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/multimodal-free-moving-data-fusion-for-gamma-ray-imaging-analysis", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/multimodal-free-moving-data-fusion-for-gamma-ray-imaging-analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-period_Nash_bargaining_for_Coordination_of_Distributed_Energy_Resources.json b/agency-indexes/DoE/Multi-period_Nash_bargaining_for_Coordination_of_Distributed_Energy_Resources.json new file mode 100644 index 00000000..357f65cd --- /dev/null +++ b/agency-indexes/DoE/Multi-period_Nash_bargaining_for_Coordination_of_Distributed_Energy_Resources.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Flexibility from distributed energy resources presents an enormous potential to provide various services to the smart grid. In this paper, we propose a unified hierarchical framework for aggregation and coordination of various flexible loads, such as commercial building Heating, Ventilation, and Air-Conditioning (HVAC) systems, Thermostatically Controlled Loads (TCLs), Distributed Energy Storages (DESs), residential Pool Pumps (PPs), and Electric Vehicles (EVs). Moreover, a multistage Nash-bargaining-based control strategy is proposed to coordinate different aggregations of flexible loads for demand response. Case studies are provided to demonstrate the efficacy of our proposed framework and coordination strategy in managing peak power demand in a community.", + "homepageURL": "https://store.pnnl.gov/content/multi-period-nash-bargaining-coordination-distributed-energy-resources", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Multi-period Nash bargaining for Coordination of Distributed Energy Resources", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/multi-period-nash-bargaining-coordination-distributed-energy-resources", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/multi-period-nash-bargaining-coordination-distributed-energy-resources", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-scale_Shock_Technique.json b/agency-indexes/DoE/Multi-scale_Shock_Technique.json new file mode 100644 index 00000000..778a89fa --- /dev/null +++ b/agency-indexes/DoE/Multi-scale_Shock_Technique.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The code to be released is a new addition to the LAMMPS molecular dynamics code. LAMMPS is developed and maintained by Sandia, is publicly available, and is used widely by both natioanl laboratories and academics. The new addition to be released enables LAMMPS to perform molecular dynamics simulations of shock waves using the Multi-scale Shock Simulation Technique (MSST) which we have developed and has been previously published. This technique enables molecular dynamics simulations of shock waves in materials for orders of magnitude longer timescales than the direct, commonly employed approach.", + "laborHours": 1281025.6, + "name": "Multi-scale Shock Technique", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lammps/lammps", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-scale_and_Multi-phase_deformation_of_crystalline_materials.json b/agency-indexes/DoE/Multi-scale_and_Multi-phase_deformation_of_crystalline_materials.json new file mode 100644 index 00000000..7db71299 --- /dev/null +++ b/agency-indexes/DoE/Multi-scale_and_Multi-phase_deformation_of_crystalline_materials.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The MDEF package contains capabilities ofr modeling the deformation of materials at the crystal scale. Primary code capabilities are: xoth \"strength\" and \"equation of state\" aspects of material response, post-processing utilities, utilities for comparing results with data from diffraction experiments.", + "homepageURL": "https://anisotropy.mae.cornell.edu/dplab/mdef", + "laborHours": 0.0, + "name": "Multi-scale and Multi-phase deformation of crystalline materials", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://anisotropy.mae.cornell.edu/dplab/mdef", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi-tube-OD-reader_[SWR-24-126].json b/agency-indexes/DoE/Multi-tube-OD-reader_[SWR-24-126].json new file mode 100644 index 00000000..c162c6e2 --- /dev/null +++ b/agency-indexes/DoE/Multi-tube-OD-reader_[SWR-24-126].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2024-10-07" + }, + "description": "This software accompanies an NREL-designed machine for observing changes in optical density of 16 biological samples growing in Hungate tubes. It involves hardware & app for Multi-Tube OD Reader.\n\nOur Multi-Tube-OD-Reader device is based on the TubeOD reader (linked below), but with a housing to maximize throughput.\n\nThis repository contains the schematics for 3D printing an enclosure, a parts list for constructing, and the code for controlling the 16-tube, in-line optical density monitoring device. This device and software are particularly useful for researchers studying microbes that grow well in Hungate tubes, but are not amenable to growth in microplate readers.\n\nRelated publication: https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2021.790576/full", + "laborHours": 623.2, + "languages": [ + "Python" + ], + "name": "Multi-tube-OD-reader [SWR-24-126]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Multi-Tube-OD-Reader", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MultiAlign.json b/agency-indexes/DoE/MultiAlign.json new file mode 100644 index 00000000..6398d2ab --- /dev/null +++ b/agency-indexes/DoE/MultiAlign.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Aligns multiple LC-MS datasets to one another after which LC-MS features can be matched to a database of peptides (typically an AMT tag database)", + "laborHours": 132179.2, + "languages": [], + "name": "MultiAlign", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MultiAlign", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MultiDistTorch:_Generation_of_multiple_processes_groups_within_PyTorch_distributed_environments_for_hierarchical_parallelization.json b/agency-indexes/DoE/MultiDistTorch:_Generation_of_multiple_processes_groups_within_PyTorch_distributed_environments_for_hierarchical_parallelization.json new file mode 100644 index 00000000..02a65c2f --- /dev/null +++ b/agency-indexes/DoE/MultiDistTorch:_Generation_of_multiple_processes_groups_within_PyTorch_distributed_environments_for_hierarchical_parallelization.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "lupopasinim@ornl.gov" + }, + "date": { + "created": "2024-03-26", + "metadataLastUpdated": "2024-03-26" + }, + "description": "This repository provide capabilities to generate multiple process groups within the PyTorch distributed environment. \n\nThe partitions of processes into groups allows to generate multiple independent version of distributed data parallelism (DDP) in order to perform scalable ensemble learning (EL) and hyperparameter optimization (HPO).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "MultiDistTorch: Generation of multiple processes groups within PyTorch distributed environments for hierarchical parallelization", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/MultiDistTorch", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MultiMatTest,_Version_1.0.json b/agency-indexes/DoE/MultiMatTest,_Version_1.0.json new file mode 100644 index 00000000..049c94eb --- /dev/null +++ b/agency-indexes/DoE/MultiMatTest,_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MultiMatTest is a demonstration code to support a talk and paper titled A Comparative Study of Multi-material Data Structures for Computational Physics Applications. The application times basic operations for different representations of multi-material data structures.", + "laborHours": 1155.2, + "name": "MultiMatTest, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/MultiMatTest/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL/MultiMatTest", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MultiPEM_Toolbox.json b/agency-indexes/DoE/MultiPEM_Toolbox.json new file mode 100644 index 00000000..02e2defd --- /dev/null +++ b/agency-indexes/DoE/MultiPEM_Toolbox.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "Supports characterization of explosive events by providing estimates of device parameters such as yield, height of burst/depth of burial, geolocation, and event time with uncertainty quantification.", + "laborHours": 16932.8, + "languages": [], + "name": "MultiPEM Toolbox", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/MultiPEM_Toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MultiTheisDP.json b/agency-indexes/DoE/MultiTheisDP.json new file mode 100644 index 00000000..2d676d58 --- /dev/null +++ b/agency-indexes/DoE/MultiTheisDP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "This software simulates drawdown in an underground reservoir or aquifer using superposition of the Theis solution. Examples in the repository perform physics-informed machine learning in order to train a neural network to manage reservoir or aquifer pressures.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "MultiTheisDP", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi_Admin_System_Tracking-Environment_Resource.json b/agency-indexes/DoE/Multi_Admin_System_Tracking-Environment_Resource.json new file mode 100644 index 00000000..56a445a5 --- /dev/null +++ b/agency-indexes/DoE/Multi_Admin_System_Tracking-Environment_Resource.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Master stores information about each node in a computer cluster, similar to an asset tracking program. Records changes and events happening on the system. Master is a networked client/server with a database backend.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Multi Admin/System Tracking-Environment Resource", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multi_Infrastructure_Control_and_Optimization_Toolkit,_Resilient_Design_Module__MICOT-RDT_,_version_2.X.json b/agency-indexes/DoE/Multi_Infrastructure_Control_and_Optimization_Toolkit,_Resilient_Design_Module__MICOT-RDT_,_version_2.X.json new file mode 100644 index 00000000..5b68f1f8 --- /dev/null +++ b/agency-indexes/DoE/Multi_Infrastructure_Control_and_Optimization_Toolkit,_Resilient_Design_Module__MICOT-RDT_,_version_2.X.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-11-26" + }, + "description": "MICOT is a tool for optimizing and controlling infrastructure systems. In includes modules for optimizing the operations of an infrastructure structure (for example optimal dispatch), designing infrastructure systems, restoring infrastructures systems, resiliency, preparing for natural disasters, interdicting networks, state estimation, sensor placement, and simulation of infrastructure systems. It implements algorithms developed at LANL that have been published in the academic community. This is a release of the of resilient design module of the MICOT.", + "laborHours": 12281858.4, + "languages": [], + "name": "Multi Infrastructure Control and Optimization Toolkit, Resilient Design Module (MICOT-RDT), version 2.X", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl-ansi/micot-rdt/blob/master/LICENCE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/micot", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multicast_Reduction_Network_Source_Code.json b/agency-indexes/DoE/Multicast_Reduction_Network_Source_Code.json new file mode 100644 index 00000000..8f1f08b2 --- /dev/null +++ b/agency-indexes/DoE/Multicast_Reduction_Network_Source_Code.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MRNet is a software tree-based overlay network developed at the University of Wisconsin, Madison that provides a scalable communication mechanism for parallel tools. MRNet, uses a tree topology of networked processes between a user tool and distributed tool daemons. This tree topology allows scalable multicast communication from the tool to the daemons. The internal nodes of the tree can be used to distribute computation and alalysis on data sent from the tool daemons to the tool. This release covers minor implementation to port this software to the BlueGene/L architecuture and for use with a new implementation of the Dynamic Probe Class Library.", + "laborHours": 68460.8, + "name": "Multicast Reduction Network Source Code", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dyninst/mrnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multidimensional_Peak_Finding.json b/agency-indexes/DoE/Multidimensional_Peak_Finding.json new file mode 100644 index 00000000..f0500522 --- /dev/null +++ b/agency-indexes/DoE/Multidimensional_Peak_Finding.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Finds 3D XIC features across LC, m/z, and drift time dimensions", + "laborHours": 5472.0, + "languages": [], + "name": "Multidimensional Peak Finding", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Multidimensional-Peak-Finding", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multigrid_based_First-Principles_Molecular_Dynamics.json b/agency-indexes/DoE/Multigrid_based_First-Principles_Molecular_Dynamics.json new file mode 100644 index 00000000..afaae0a5 --- /dev/null +++ b/agency-indexes/DoE/Multigrid_based_First-Principles_Molecular_Dynamics.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "MGmol ls a First-Principles Molecular Dynamics code. It relies on the Born-Oppenheimer approximation and models the electronic structure using Density Functional Theory, either LDA or PBE. Norm-conserving pseudopotentials are used to model atomic cores.", + "laborHours": 62760.8, + "languages": [ + "C++, parallellsm based on MPI" + ], + "name": "Multigrid based First-Principles Molecular Dynamics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mgmol", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multilevel_Graph_Partitioning_and_Embedding.json b/agency-indexes/DoE/Multilevel_Graph_Partitioning_and_Embedding.json new file mode 100644 index 00000000..3a08570b --- /dev/null +++ b/agency-indexes/DoE/Multilevel_Graph_Partitioning_and_Embedding.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-08-13", + "metadataLastUpdated": "2019-08-14" + }, + "description": "A small library that supports multilevel graph partitioning and graph embedding.", + "laborHours": 1763.2, + "languages": [], + "name": "Multilevel Graph Partitioning and Embedding", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/graph-embed", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multimedia-Modeling_Environmental_Database_Editor.json b/agency-indexes/DoE/Multimedia-Modeling_Environmental_Database_Editor.json new file mode 100644 index 00000000..1bdb5ebf --- /dev/null +++ b/agency-indexes/DoE/Multimedia-Modeling_Environmental_Database_Editor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-28", + "metadataLastUpdated": "2023-01-17" + }, + "description": "MMEDE is a software tool designed by Battelle, PNL to support the maintenance of an environmental risk computation database.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Multimedia-Modeling Environmental Database Editor", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multimedia_Environmental_Pollutant_Assessment_System.json b/agency-indexes/DoE/Multimedia_Environmental_Pollutant_Assessment_System.json new file mode 100644 index 00000000..72393a04 --- /dev/null +++ b/agency-indexes/DoE/Multimedia_Environmental_Pollutant_Assessment_System.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-13", + "metadataLastUpdated": "2022-09-14" + }, + "description": "Integrated system to compute long-term public health risks as the result of the release of hazardous and/or radioactive materials to air, groundwater, surface water, and overland transport pathways.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Multimedia Environmental Pollutant Assessment System", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multimodal_CO2_Transportation_Cost_Model.json b/agency-indexes/DoE/Multimodal_CO2_Transportation_Cost_Model.json new file mode 100644 index 00000000..6477e2f7 --- /dev/null +++ b/agency-indexes/DoE/Multimodal_CO2_Transportation_Cost_Model.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-03-11", + "metadataLastUpdated": "2024-03-11" + }, + "description": "This model provides a cost estimate for transporting CO2 via truck or rail in the United States using\ncommercially available equipment and technologies. The model includes an analysis of direct and indirect\nCO2 emissions to determine costs per net tonne of CO2 transported. Publicly available data and methods\npublished in the peer-reviewed literature are used to the extent possible; references are available at the\nbottom of the \"Calculations\" sheet. Upstream (i.e., liquefaction, buffer storage) and downstream (i.e.,\nbuffer storage, reconditioning) activities are included in the model of emissions and costs. All capital and\noperating expenditures are estimated in the \"Calculations\" sheet. The cost of financing the project is\ndetermined in the \"FINEX\" sheet. All user inputs are done via drop down menus in on the \"User Interface\"\nsheet. Summary results are also provided on the \"User Interface\" sheet.", + "laborHours": 0.0, + "languages": [], + "name": "Multimodal CO2 Transportation Cost Model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/myers79/MuMo-CoCo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multiphysics_Application_Coupling_Toolkit.json b/agency-indexes/DoE/Multiphysics_Application_Coupling_Toolkit.json new file mode 100644 index 00000000..d3eb62f5 --- /dev/null +++ b/agency-indexes/DoE/Multiphysics_Application_Coupling_Toolkit.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This particular consortium implementation of the software integration infrastructure will, in large part, refactor portions of the Rocstar multiphysics infrastructure. Development of this infrastructure originated at the University of Illinois DOE ASCI Center for Simulation of Advanced Rockets (CSAR) to support the center's massively parallel multiphysics simulation application, Rocstar, and has continued at IllinoisRocstar, a small company formed near the end of the University-based program. IllinoisRocstar is now licensing these new developments as free, open source, in hopes to help improve their own and others' access to infrastructure which can be readily utilized in developing coupled or composite software systems; with particular attention to more rapid production and utilization of multiphysics applications in the HPC environment. There are two major pieces to the consortium implementation, the Application Component Toolkit (ACT), and the Multiphysics Application Coupling Toolkit (MPACT). The current development focus is the ACT, which is (will be) the substrate for MPACT. The ACT itself is built up from the components described in the technical approach. In particular, the ACT has the following major components: 1.The Component Object Manager (COM): The COM package provides encapsulation of user applications, and their data. COM also provides the inter-component function call mechanism. 2.The System Integration Manager (SIM): The SIM package provides constructs and mechanisms for orchestrating composite systems of multiply integrated pieces.", + "laborHours": 113452.8, + "name": "Multiphysics Application Coupling Toolkit", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IllinoisRocstar/IMPACT", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multiphysics_Object_Oriented_Simulation_Environment.json b/agency-indexes/DoE/Multiphysics_Object_Oriented_Simulation_Environment.json new file mode 100644 index 00000000..73217f06 --- /dev/null +++ b/agency-indexes/DoE/Multiphysics_Object_Oriented_Simulation_Environment.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The Multiphysics Object Oriented Simulation Environment (MOOSE) software library developed at Idaho National Laboratory is a tool. MOOSE, like other tools, doesn't actually complete a task. Instead, MOOSE seeks to reduce the effort required to create engineering simulation applications. MOOSE itself is a software library: a blank canvas upon which you write equations and then MOOSE can help you solve them. MOOSE is comparable to a spreadsheet application. A spreadsheet, by itself, doesn't do anything. Only once equations are entered into it will a spreadsheet application compute anything. Such is the same for MOOSE. An engineer or scientist can utilize the equation solvers within MOOSE to solve equations related to their area of study. For instance, a geomechanical scientist can input equations related to water flow in underground reservoirs and MOOSE can solve those equations to give the scientist an idea of how water could move over time. An engineer might input equations related to the forces in steel beams in order to understand the load bearing capacity of a bridge. Because MOOSE is a blank canvas it can be useful in many scientific and engineering pursuits.", + "laborHours": 1085021.6, + "languages": [], + "name": "Multiphysics Object Oriented Simulation Environment", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/moose", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multiplayer_Engineering.json b/agency-indexes/DoE/Multiplayer_Engineering.json new file mode 100644 index 00000000..c3b63918 --- /dev/null +++ b/agency-indexes/DoE/Multiplayer_Engineering.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-02-27", + "metadataLastUpdated": "2024-02-27" + }, + "description": "INL engineers developed a special purpose software framework designed to establish real-time connections between multiple running Unity instances.\n\nThe framework is developed in Unity, a game engine development platform. \n\nThis framework programmatically attaches functions to engineering models, enabling users to interact with, observe, and make changes to virtual models. These interactions are broadcasted through websocket connections, and received by other engineers in real-time.", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Multiplayer Engineering", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Multiplayer_Engineering", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multiplicity_TMU_Estimator.json b/agency-indexes/DoE/Multiplicity_TMU_Estimator.json new file mode 100644 index 00000000..ea28ed73 --- /dev/null +++ b/agency-indexes/DoE/Multiplicity_TMU_Estimator.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "obriense@ornl.gov" + }, + "date": { + "created": "2020-12-29", + "metadataLastUpdated": "2020-12-29" + }, + "description": "Neutron multiplicity analysis is a widely used technique in international safeguards and is most commonly applied to the assay of product and scrap materials in the production of mixed oxide fuel. The typical neutron multiplicity analysis applies only a crude, almost cursory, uncertainty\nanalysis limited to propagation of statistical errors in the derived singles, doubles, and triples count rates through the point source model. An assay result without a properly assigned uncertainty has little value, and an assay result with a significantly understated uncertainty can lead to\nboth unsafe facility operations and an increased misclassification rate for the item of interest. We have developed a complete and robust total measurement uncertainty treatment for multiplicity analysis that incorporates instrumental, environmental and nuclear data error contributions.", + "laborHours": 0.0, + "languages": [ + "Visual Basic .NET" + ], + "name": "Multiplicity TMU Estimator", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/multTMU/multTMU", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multiscale_Ecosystem_for_solving_Maxwell-Schrodinger_equations_of_open_quantum_systems__OpenMS__.json b/agency-indexes/DoE/Multiscale_Ecosystem_for_solving_Maxwell-Schrodinger_equations_of_open_quantum_systems__OpenMS__.json new file mode 100644 index 00000000..38e22f14 --- /dev/null +++ b/agency-indexes/DoE/Multiscale_Ecosystem_for_solving_Maxwell-Schrodinger_equations_of_open_quantum_systems__OpenMS__.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-06" + }, + "description": "Light-matter interactions play an important role in many branches of physics, chemistry, energy, and materials science. In the strong coupling regime, light-matter interactions are able to tune the materials properties via the formation of new quasiparticles, such as plasmons and polaritons. However, theoretical and numerical modeling of the light-matter interaction-mediated processes remain a big challenge because light-matter interactions are fundamentally multiscale and multiphysics problems involving multiple interactions between electrons, nuclei, and photons at different time/length scales. In the current community, light-matter interactions were treated at different levels of theoretical complexity in quantum chemistry and quantum optics. In quantum optics or quantum photonics, the matter is usually simplified as a few-level system, and the light is treated quantum-mechanically. On the other hand, quantum chemistry explores first-principles methods, including both single-particle and many-body-based techniques, to describe the electronic properties of matter in detail. However, light is usually prescribed as a classical electromagnetic field, and the light-matter interaction is taken into account as an external potential via classical approximations. This software is designed to fill current modeling shortcomings by delivering a first-ever scalable multiscale platform for simulating light-matter interactions in realistic electromagnetic environments. The software solves Maxwell and Schrodinger equations self-consistent on the heterogeneous platforms. It implements HF/DFT, TDDFT, and coupled-cluster counterparts for light-matter interactions and adopts modular programming to offload massively parallel algorithms on a large number of CPU/GPUs.", + "laborHours": 0.0, + "languages": [], + "name": "Multiscale Ecosystem for solving Maxwell-Schrodinger equations of open quantum systems (OpenMS) ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/OpenMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multiscale_Machine-Learned_Modeling_Infrastructure_Core.json b/agency-indexes/DoE/Multiscale_Machine-Learned_Modeling_Infrastructure_Core.json new file mode 100644 index 00000000..86c8d1c9 --- /dev/null +++ b/agency-indexes/DoE/Multiscale_Machine-Learned_Modeling_Infrastructure_Core.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "MuMMI Core is the central component of the Multiscale Machine-Learned Modeling Infrastructure (MuMMI), a scalable and generalizable framework that couples pairs of models using machine learning and in situ feedback across three scales of resolution.", + "laborHours": 0.0, + "languages": [], + "name": "Multiscale Machine-Learned Modeling Infrastructure Core", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mummi-framework/mummi-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multiscale_Machine-Learned_Modeling_Infrastructure_RAS.json b/agency-indexes/DoE/Multiscale_Machine-Learned_Modeling_Infrastructure_RAS.json new file mode 100644 index 00000000..711889ee --- /dev/null +++ b/agency-indexes/DoE/Multiscale_Machine-Learned_Modeling_Infrastructure_RAS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "MuMMI RAS is the application component of the Multiscale Machine-Learned Modeling Infrastructure (MuMMI). It simulates RAS protein interactions at three scales of resolution coupled with ML-based selection and in-situ feedback. MuMMI RAS is particularly configured for massive scale, running thousands of simultaneous jobs with several terabytes of data on Lassen and Summit.", + "laborHours": 0.0, + "languages": [], + "name": "Multiscale Machine-Learned Modeling Infrastructure RAS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mummi-framework/mummi-ras", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multiscale_Molecular_Dynamics_Simulations:_Accelerating_Conformational_Sampling_of_Biomolecular_Systems_by_Iterating_All-Atom_and_Coarse-Grained_Simulations.json b/agency-indexes/DoE/Multiscale_Molecular_Dynamics_Simulations:_Accelerating_Conformational_Sampling_of_Biomolecular_Systems_by_Iterating_All-Atom_and_Coarse-Grained_Simulations.json new file mode 100644 index 00000000..296b913f --- /dev/null +++ b/agency-indexes/DoE/Multiscale_Molecular_Dynamics_Simulations:_Accelerating_Conformational_Sampling_of_Biomolecular_Systems_by_Iterating_All-Atom_and_Coarse-Grained_Simulations.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "We developed the atomistic-coarse-grained multiscale MD simulation method in the OpenMM simulation package by iterating between the all-atom (AA) and coarse-grained (CG) MD simulations to enhance the sampling of biomolecular conformations. As the free energy surfaces are flattened during CG MD simulations, we can accelerate the transitions between different low-energy conformations. The AA-CG-AA cycles are repeated, facilitating the accelerated sampling of biomolecular conformations at a CG level, while the finer atomistic interactions are refined with AA simulators.", + "laborHours": 304.0, + "languages": [], + "name": "Multiscale Molecular Dynamics Simulations: Accelerating Conformational Sampling of Biomolecular Systems by Iterating All-Atom and Coarse-Grained Simulations", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/iMMD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multiscale_Solar_Water_Heating__MSWH__v1.0.json b/agency-indexes/DoE/Multiscale_Solar_Water_Heating__MSWH__v1.0.json new file mode 100644 index 00000000..02742264 --- /dev/null +++ b/agency-indexes/DoE/Multiscale_Solar_Water_Heating__MSWH__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-24", + "metadataLastUpdated": "2019-05-31" + }, + "description": "The main purpose of the software is to model energy use for individual and community scale solar water heating projects in California. \n\nUsage \n\nThe user provides a climate zone for a project, an occupancy for each household and whether any of the occupants stay at home during the day. The software can then load a set of example California specific hourly domestic hot water end-use load profiles from a database, size and locate the systems. The user can now simulate the hourly system performance over a period of one representative year, visualize and explore the simulation results using time-series plots for temperature profiles, heat and power rates, or look at annual summaries. Similarly the user can model individual household solar water heating projects and base case conventional gas tank water heater systems, such that the results can be compared between the individual, community and base case systems. \n\nThis functionality is readily available through a Jupyter notebook and a Django web framework, depending on what level of detail the user would like to access. \n\nFeatures \n\n- Python module to calculate solar irradiation on a tilted surface \n\n- Python module with simplified component models for Converter (solar collectors, electric resistance heater, gas burner, photovoltaic panels, heat pump), Storage (solar thermal tank, heat pump thermal tank, conventional gas tank water heater), and Distribution (distribution and solar pump, piping losses) components \n\n- Python module with preconfigured system simulation models for: base case gas tank water heaters, solar thermal water heaters (solar collector feeding a storage tank, with a tankeless gas water heater backup in a new installation cases and a base case gas tank water heater in a retrofit case) and solar electric water heaters (heat pump storage tank with an electric resistance backup) \n\n- Database with component performance parameters, California specific weather data and domestic hot water end-use load profiles \n\n- Django web framework to configure project, parametrize components and run simulation from a web browser \n\nThe package contains functional and unit tests and it is structured so that it can be extended with further technologies, applications and locations.", + "laborHours": 18285.6, + "languages": [], + "name": "Multiscale Solar Water Heating (MSWH) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/MSWH", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multispeaker.json b/agency-indexes/DoE/Multispeaker.json new file mode 100644 index 00000000..99df3922 --- /dev/null +++ b/agency-indexes/DoE/Multispeaker.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "MultiSpeaker is a software application that parses wsdl and xsd files that define the MultiSpeak protocol. The MultiSpeak protocol (www.multispeak.org) is a SOA-based integration architecture that defines the complex communications between various endpoints of a utility company. MultiSpeaker parses the files and presents an easy to read and understand representation of the underlying protocol. The user may then use visual clues to know what message elements are required, descriptions for the elements along with valid entries. The user may then edit or modify the payload of the actual messages. MultiSpeaker also provides a mechanism for scheduling multiple modified protocol messages.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Qt" + ], + "name": "Multispeaker", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multispecies_Hypersonic_Flow_Simulator.json b/agency-indexes/DoE/Multispecies_Hypersonic_Flow_Simulator.json new file mode 100644 index 00000000..3f25af6b --- /dev/null +++ b/agency-indexes/DoE/Multispecies_Hypersonic_Flow_Simulator.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-07", + "metadataLastUpdated": "2020-02-07" + }, + "description": "MHYSA is a conservative finite-difference code to solve the 1D, 2D, and 3D multispecies Navier-Stokes equations for hypersonic flow applications. \n\nIt supports Cartesian grids only and has the option of including immersed boundaries.\n- Solves 1D Euler and 2D and 3D Navier-Stokes equations.\n- Solves the PDEs over Cartesian grids.\n- Written entirely in C and uses the MPICH library. It also uses OpenMP threads but this is a work-inprogress.\n- Can be compiled with PETSc (http://www.mcs.anl.gov/petsc/), if available, where it can use PETSc's time integration module TS (http://www.mcs.anl.gov/petsc/petsc-current/src/ts/).\n- For 3-dimensional simulations, the immersed boundaries can be used to solve over non-Cartesian geometries.\n\nMHYSA has been developed to be scalable, and apart from the usual functionalities to solve a system of PDEs on distributed architectures, it provides scalable file I/O functions.\n", + "laborHours": 16704.8, + "languages": [], + "name": "Multispecies Hypersonic Flow Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/mhysa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multivariate_Curve_Resolution__MCR__using_Principal_Components_Inputs_and_Rigorous_Equality_and_Inequality_Constraints.json b/agency-indexes/DoE/Multivariate_Curve_Resolution__MCR__using_Principal_Components_Inputs_and_Rigorous_Equality_and_Inequality_Constraints.json new file mode 100644 index 00000000..c58b19d8 --- /dev/null +++ b/agency-indexes/DoE/Multivariate_Curve_Resolution__MCR__using_Principal_Components_Inputs_and_Rigorous_Equality_and_Inequality_Constraints.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This MATLAB pseudocode perform multivariate curve resolution (MCR) using PCA scores & loadings of data as inputs. It employs rigorous least squares equality and inequality constraints for all elements in the solution factor matrices. It also can be used to perform nonnegative matrix factorization.\nSAND2020-12650 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 91.2, + "languages": [ + "MATLAB" + ], + "name": "Multivariate Curve Resolution (MCR) using Principal Components Inputs and Rigorous Equality and Inequality Constraints", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mcr", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multivariate_Gaussian_Process_Model_for_Correlated_Time_Series_in_R.json b/agency-indexes/DoE/Multivariate_Gaussian_Process_Model_for_Correlated_Time_Series_in_R.json new file mode 100644 index 00000000..ffc81195 --- /dev/null +++ b/agency-indexes/DoE/Multivariate_Gaussian_Process_Model_for_Correlated_Time_Series_in_R.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-10" + }, + "description": "RmultiProcess software is designed to work with multiple correlated sensors. The characteristic that allows data to be filled in or the support to be changed is correlation, the interdependence between observations.", + "laborHours": 167.2, + "languages": [], + "name": "Multivariate Gaussian Process Model for Correlated Time Series in R", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/multivariate-gaussian-process-model-for-correlated-time-series-in-r", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multivariate_Time_Series_Intermittent_Fault_Detectionin_Controller_Area_Network_CAN.json b/agency-indexes/DoE/Multivariate_Time_Series_Intermittent_Fault_Detectionin_Controller_Area_Network_CAN.json new file mode 100644 index 00000000..97dd2b16 --- /dev/null +++ b/agency-indexes/DoE/Multivariate_Time_Series_Intermittent_Fault_Detectionin_Controller_Area_Network_CAN.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "hespelersc@ornl.gov" + }, + "date": { + "created": "2024-10-22", + "metadataLastUpdated": "2024-10-22" + }, + "description": "Fault detection in Controller Area Network (CAN) systems is crucial for ensuring the reliability and safety of automotive and industrial applications. This study investigates and compares the effectiveness of time series classification models for supervised fault detection in CAN data. This repository contains the code and data for our benchmarking experiment aimed at detecting intermittent faults in automotive Controller Area Network (CAN) data. The goal of this project is to compare various machine learning (ML) and deep learning (DL) models using different Time Series Cross-Validation (TSCV) techniques to evaluate their effectiveness in a streaming environment for fault detection.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Multivariate Time Series Intermittent Fault Detectionin Controller Area Network CAN", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/TovNephesh/Multivariate-Time-Series-Intermittent-Fault-Detection-in-Controller-Area-Network-CAN-", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Multiverse:_Bayesian_model_selection_for_neural_networks.json b/agency-indexes/DoE/Multiverse:_Bayesian_model_selection_for_neural_networks.json new file mode 100644 index 00000000..5c77947e --- /dev/null +++ b/agency-indexes/DoE/Multiverse:_Bayesian_model_selection_for_neural_networks.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-05-03" + }, + "description": "Multiverse is a code repository for a set of tools for Bayesian model selection for neural networks. The goal of the tools is to provide capabilities for selecting among prior and model specifications for Bayesian neural networks. Multiverse will include tools for creating Bayesian neural networks, evaluating the Bayesian model evidence, and performing inference in Bayesian neural networks. These components are written in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning and signal processing.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Multiverse: Bayesian model selection for neural networks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Muon_GUORE_-_Geant4_MACRO_for_nextGEN_0vBB.json b/agency-indexes/DoE/Muon_GUORE_-_Geant4_MACRO_for_nextGEN_0vBB.json new file mode 100644 index 00000000..3792c859 --- /dev/null +++ b/agency-indexes/DoE/Muon_GUORE_-_Geant4_MACRO_for_nextGEN_0vBB.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code is made to model the effect of muons in a future double beta decay array with the Geant4 software framework.", + "laborHours": 471.2, + "name": "Muon GUORE - Geant4 MACRO for nextGEN 0vBB", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/massarczyk/Muon_GUORE/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/massarczyk/Muon_GUORE", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Muster:_Massively_Scalable_Clustering.json b/agency-indexes/DoE/Muster:_Massively_Scalable_Clustering.json new file mode 100644 index 00000000..a1d9a1e2 --- /dev/null +++ b/agency-indexes/DoE/Muster:_Massively_Scalable_Clustering.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Muster is a framework for scalable cluster analysis. It includes implementations of classic K-Medoids partitioning algorithms, as well as infrastructure for making these algorithms run scalably on very large systems. In particular, Muster contains algorithms such as CAPEK (described in reference 1) that are capable of clustering highly distributed data sets in-place on a hundred thousand or more processes.", + "laborHours": 2052.0, + "name": "Muster: Massively Scalable Clustering", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/muster/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/muster", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MuyGPyS.json b/agency-indexes/DoE/MuyGPyS.json new file mode 100644 index 00000000..b7d3334b --- /dev/null +++ b/agency-indexes/DoE/MuyGPyS.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-23" + }, + "description": "MuyGPs is a GP estimation method that affords fast hyperparameter optimization by way of performing leave-one-out cross-validation. MuyGPs achieves best-in-class speed and scalability by limiting inference to the information contained in k nearest neighborhoods for prediction locations for both hyperparameter optimization and tuning. This feature affords the optimization of hyperparameters by way of leave-one-out cross-validation, as opposed to the more expensive loglikelihood evaluations requires by similar sparse methods", + "laborHours": 0.0, + "languages": [], + "name": "MuyGPyS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/MuyGPyS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MyEMSL.json b/agency-indexes/DoE/MyEMSL.json new file mode 100644 index 00000000..2bebb4c9 --- /dev/null +++ b/agency-indexes/DoE/MyEMSL.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "MyEMSL provides the following features: user-assisted upload of data from scientific instruments to an archive, tracking data though the upload process, providing metadata for recovery of uploaded data, providing users with access to the data. These features are supplied by a mixture of open source software and internally developed software. MyESML also provides a notification system that allows the system to communicate with users and other parts of the MyEMSL system. This allows the system to support automated workflows and user interaction. Reprocessing of already ingested data is also supported.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C, Python, PHP, Go, C#, Javascript" + ], + "name": "MyEMSL", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MyEMSL_MTS_File_Cache_Manager.json b/agency-indexes/DoE/MyEMSL_MTS_File_Cache_Manager.json new file mode 100644 index 00000000..9d6916ca --- /dev/null +++ b/agency-indexes/DoE/MyEMSL_MTS_File_Cache_Manager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MTS manager for retrieving files from MyEMSL; The MyEMSL MTS File Cache Manager is a part of PRISM, the Proteomics Research Information and Management System. The software processes the MyEMSL Download Queue in the Mass and Time Tag System (MTS) to download files required for processing.", + "laborHours": 456.0, + "languages": [], + "name": "MyEMSL MTS File Cache Manager", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MyEMSL-MTS-File-Cache-Manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MyEMSL_Reader.json b/agency-indexes/DoE/MyEMSL_Reader.json new file mode 100644 index 00000000..0474f26c --- /dev/null +++ b/agency-indexes/DoE/MyEMSL_Reader.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The MyEMSL Reader is a library used by manager programs in PRISM, the Proteomics Research Information and Management System. The library allows the managers to push files into MyEMSL and later search for and retrieve the files.", + "laborHours": 3024.8, + "languages": [], + "name": "MyEMSL Reader", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MyEMSL-Reader", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/MyTRIM.json b/agency-indexes/DoE/MyTRIM.json new file mode 100644 index 00000000..e5df88ea --- /dev/null +++ b/agency-indexes/DoE/MyTRIM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Three dimensional binary collision Monte Carlo library for sampling ion collision cascades in materials.", + "laborHours": 2568.8, + "languages": [], + "name": "MyTRIM", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/mytrim", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Myna.json b/agency-indexes/DoE/Myna.json new file mode 100644 index 00000000..290a6bfb --- /dev/null +++ b/agency-indexes/DoE/Myna.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "knappgl@ornl.gov" + }, + "date": { + "created": "2024-08-20", + "metadataLastUpdated": "2024-08-20" + }, + "description": "The additive manufacturing (AM) community has been developing digital factory tools over the past decade to better leverage the multi-modal process data coming out of the advanced manufacturing process. As a result, numerous databases of additive manufacturing process data exist in the literature and in the archival storage of disparate research groups. While some efforts have been made to create a standard ontology for storing and sharing AM data, in practice a variety of data structures are used to store AM build data, even within a single institution. This causes many problems for maintainability and extensibility when attempting to integrate computational modeling tools with experimental data to either validate models or to provide further insight into results and trends.\n\nMyna is a Python-based framework that aims to decrease the effort needed to connect individual computational models to the variety of AM process data that exist in different research groups and institutions. This type of software is sometimes referred to as \"middleware\" or \u201cglueware,\u201d in that it connects disparate databases and applications into a single computational ecosystem. Instead of maintaining unique interfaces between each application and each database, developers can create a single interface from each application to Myna and thereby gain access to the implemented database connections. Similarly, developing a database connection in Myna provides access to the developed simulation applications. This framework greatly simplifies the maintainability of model applications that rely on experimental data. Using external simulation tools, users will also be able to run pre-configured workflows using the built-in workflow manager. Several examples of input files are provided with Myna for different workflows, including melt pool geometry predictions and detailed melt pool and solidification microstructure predictions.", + "laborHours": 4043.2, + "languages": [ + "Python" + ], + "name": "Myna", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-MDF/Myna", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Myrmics_Memory_Allocator.json b/agency-indexes/DoE/Myrmics_Memory_Allocator.json new file mode 100644 index 00000000..d2ec8701 --- /dev/null +++ b/agency-indexes/DoE/Myrmics_Memory_Allocator.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MMA is a stand-alone memory management system for MPI clusters. It implements a shared Partitioned Global Address Space, where multiple MPI processes request objects from the allocator and the latter provides them with system-wide unique memory addresses for each object. It provides applications with an intuitive way of managing the memory system in a unified way, thus enabling easier writing of irregular application code.", + "homepageURL": "http://myrmics.com/download.php", + "laborHours": 0.0, + "name": "Myrmics Memory Allocator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://myrmics.com/downloads/mma_license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://myrmics.com/download.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/MzidToTsvConverter.json b/agency-indexes/DoE/MzidToTsvConverter.json new file mode 100644 index 00000000..a2b52313 --- /dev/null +++ b/agency-indexes/DoE/MzidToTsvConverter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Converts an mzIdentML created by MS-GF+ to a tab-delimited text file.", + "laborHours": 334.4, + "languages": [], + "name": "MzidToTsvConverter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Mzid-To-Tsv-Converter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/N-S3_Cellular_Vehicle-to-Everything__C-V2X__Cosimulation_Framework_[SWR-24-54].json b/agency-indexes/DoE/N-S3_Cellular_Vehicle-to-Everything__C-V2X__Cosimulation_Framework_[SWR-24-54].json new file mode 100644 index 00000000..bf59a7f7 --- /dev/null +++ b/agency-indexes/DoE/N-S3_Cellular_Vehicle-to-Everything__C-V2X__Cosimulation_Framework_[SWR-24-54].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-07-19" + }, + "description": "This is a vehicular networking simulator designed to enable synchronized network simulation with vehicle traffic simulation software. The communications model is based on the 3GPP LTE-V2X Mode 4 protocol, but includes several other wireless network protocol models as well. This simulator includes both a V2X network simulation implemented in ns-3 as well as an interface to automatically configure, run, and interact with a set of ns-3 instances based on network size and available hardware. This software has been tested with Aimsun NEXT 2.0 simulator (with V2X SDK), but uses a generic interface for compatibility with any comparable vehicle traffic simulator across the HELICS co-simulation framework. This software is intended as a generalized extension to vehicle traffic simulation, and does not model any vehicle traffic on its own.", + "laborHours": 755713.6, + "languages": [ + "C++", + "Python" + ], + "name": "N-S3 Cellular Vehicle-to-Everything (C-V2X) Cosimulation Framework [SWR-24-54]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NS3-C-V2X-Cosimulation-Framework", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/N-SCRAD.json b/agency-indexes/DoE/N-SCRAD.json new file mode 100644 index 00000000..2964d0da --- /dev/null +++ b/agency-indexes/DoE/N-SCRAD.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software tool implements a version of the N-SCRAD anomaly detection algorithm. This algorithm classifies a gamma-ray energy spectrum as either consistent or inconsistent with previously measured background and a set of predefined nuisance sources. N-SCRAD was originally developed for DOE/NNSA/NA-22 and has since been utilized in a variety of applications for various clients. The present software tool is intended to demonstrate the capabilities of N-SCRAD. The tool accepts input data as either text files or GADRAS binary files, and saves the output alarm metric as a text file. A separate parameter file allows advanced users to configure algorithm settings.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "N-SCRAD", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/N2A.json b/agency-indexes/DoE/N2A.json new file mode 100644 index 00000000..3f1750bb --- /dev/null +++ b/agency-indexes/DoE/N2A.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-09-30", + "metadataLastUpdated": "2021-09-30" + }, + "description": "N2A includes an object-oriented language for modeling neural systems as well as a software tool for editing and simulating models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-2695 O", + "laborHours": 46998.4, + "languages": [ + "C++", + "Java", + "Java", + "Python" + ], + "name": "N2A", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/frothga/n2a", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NAMSA.json b/agency-indexes/DoE/NAMSA.json new file mode 100644 index 00000000..66d94add --- /dev/null +++ b/agency-indexes/DoE/NAMSA.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "In NAMSA, we introduce two main solutions to address the limitations of MSA-type algorithms for simulation of electron scattering/microscopy data: just-in-time compilation and work partitioning via MPI and GPU-to-GPU communication. First, the just-in-time (JIT) compilation strategy produces optimally tuned CUDA C++ kernels due to the data layout being perfectly known at runtime and compiled via calls from the Python interpreter. NAMSA automatically optimizes the 2-D FFT planning, and CUDA multi-streams scheduling/launching of probe simulations. With NAMSA, we can simulate electron scattering/microscopy on hundreds to thousands of GPUs, while removing the major limitations of memory and bandwidth from MSA.", + "laborHours": 2766.4, + "languages": [ + "Python (2.7/3.X), CUDA C++ /NVCC/10.01" + ], + "name": "NAMSA", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/disMultiABM/namsa", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/NATS_Client_for_LabVIEW.json b/agency-indexes/DoE/NATS_Client_for_LabVIEW.json new file mode 100644 index 00000000..1b5b2896 --- /dev/null +++ b/agency-indexes/DoE/NATS_Client_for_LabVIEW.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "herronan@ornl.gov" + }, + "date": { + "created": "2022-08-06", + "metadataLastUpdated": "2022-08-09" + }, + "description": "LabVIEW client for NATS, the cloud native messaging system.", + "laborHours": 0.0, + "languages": [ + "LabVIEW" + ], + "name": "NATS Client for LabVIEW", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/drew-herron/nats.lv", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NATURF.json b/agency-indexes/DoE/NATURF.json new file mode 100644 index 00000000..4e36e78f --- /dev/null +++ b/agency-indexes/DoE/NATURF.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "allenmr@ornl.gov" + }, + "date": { + "created": "2022-08-03", + "metadataLastUpdated": "2022-08-04" + }, + "description": "The Neighborhood Adaptive Tissues for Urban Resilience Futures tool (NATURF) is a Python workflow that generates les readable by the Weather Research and Forecasting (WRF) model. The NATURF Python modules use shapefiles containing building footprint and height data as input to calculate 132 building parameters at any resolution and converts the parameters into a binary file format.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "NATURF", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/naturf", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NCAP_-_Non-Canonical_Amino_Acid_Parameterization.json b/agency-indexes/DoE/NCAP_-_Non-Canonical_Amino_Acid_Parameterization.json new file mode 100644 index 00000000..f83ecbb9 --- /dev/null +++ b/agency-indexes/DoE/NCAP_-_Non-Canonical_Amino_Acid_Parameterization.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-05", + "metadataLastUpdated": "2025-02-24" + }, + "description": "Our software is designed to only work on novel NCAA side chains and parameterize for the CHARMM potential. This works\naround the detailed analysis and manual parameter fitting of many existing software programs. Our approach is also more\nspecific than those used in Rosetta where we calculate parameters specific for each NCAA rather than assuming\ntransferability.", + "homepageURL": "https://github.com/pnnl/ncap", + "laborHours": 1626.4, + "languages": [], + "name": "NCAP - Non-Canonical Amino Acid Parameterization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://github.com/pnnl/ncap", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://github.com/pnnl/ncap", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NDCX-II_Python_Module.json b/agency-indexes/DoE/NDCX-II_Python_Module.json new file mode 100644 index 00000000..c842422c --- /dev/null +++ b/agency-indexes/DoE/NDCX-II_Python_Module.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Analysis scripts for data from the NDCX-II experiment.", + "laborHours": 0.0, + "languages": [], + "name": "NDCX-II Python Module", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/berkeleylab/atap-ndcxii-python/src/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/atap-ndcxii-python", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/NDDAV.json b/agency-indexes/DoE/NDDAV.json new file mode 100644 index 00000000..c4589ebf --- /dev/null +++ b/agency-indexes/DoE/NDDAV.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-10-25", + "metadataLastUpdated": "2019-10-25" + }, + "description": "Web-based Interface for the N-Dimensional Data Analysis and Visualization System.", + "laborHours": 10913.6, + "languages": [ + "Python" + ], + "name": "NDDAV", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/NDDAV", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NEB-Tool__Multiple_Non_Energy_Benefits_Tool__[SWR-24-08].json b/agency-indexes/DoE/NEB-Tool__Multiple_Non_Energy_Benefits_Tool__[SWR-24-08].json new file mode 100644 index 00000000..3da24a11 --- /dev/null +++ b/agency-indexes/DoE/NEB-Tool__Multiple_Non_Energy_Benefits_Tool__[SWR-24-08].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-05-28", + "metadataLastUpdated": "2024-05-28" + }, + "description": "A user friendly, graphical, open-source implementation of the multiple benefits framework to non-energy-benefits incorporating additional aspects to make the tool effective for use in the United States. The software will be distributed as web, desktop and/or mobile apps.", + "laborHours": 21128.0, + "languages": [ + "TypeScript", + "HTML" + ], + "name": "NEB-Tool (Multiple Non Energy Benefits Tool) [SWR-24-08]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/NEB-Tool/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NEB-Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NED_Asteroid_Energy_Deposition.json b/agency-indexes/DoE/NED_Asteroid_Energy_Deposition.json new file mode 100644 index 00000000..d3ab3950 --- /dev/null +++ b/agency-indexes/DoE/NED_Asteroid_Energy_Deposition.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-28", + "metadataLastUpdated": "2023-08-28" + }, + "description": "In the event of a potentially catastrophic asteroid impact, with sufficient warning time, deploying a nuclear\ndevice remains a powerful option for planetary defense if a kinetic impactor proves insufficient. Predicting\nthe effectiveness of a potential nuclear deflection or disruption mission depends on accurate multiphysics\nsimulations of the device's x-ray energy deposition into the asteroid and the resulting material ablation.\nThese simulations span many orders of magnitude, require a variety of different complex physics\npackages, and are computationally expensive. Having an efficient and accurate way of modeling this\nsystem is necessary for exploring a mission's sensitivity to the asteroid's range of physical properties. To\nexpedite future simulations, we present a completed x-ray energy deposition model developed using the\nradiation-hydrodynamics code Kull which can be used to initiate a nuclear mitigation mission hydrocode.\nThe model spans a wide variety of possible mission initial conditions: four different asteroid-like materials\n(Silicon Dioxide, Forsterite, Iron, and Ice), two different source spectra (1 and 2 keV blackbodies), and\nthen a broad range of radiation fluences (0.0001 to 1 kt per square meter), source durations (10 to 100\nns), and asteroid porosities (0 to 80 percent). Using blowoff momentum as the primary metric, the modelinitiated\nsimulation results match the full radiation-hydrodynamics results to within 10 percent. Please\nreference the journal article: Burkey et al., X-Ray Energy Deposition Model for Simulating Asteroid\nResponse to a Nuclear Planetary Defense Mitigation Mission, Planetary Science Journal, (2023) for more\ninformation.", + "laborHours": 0.0, + "languages": [], + "name": "NED_Asteroid_Energy_Deposition", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/NED_Asteroid_Energy_Deposition", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NEMA-Phase_Compliant_Traffic_Signal_Controller_Module_in_SUMO.json b/agency-indexes/DoE/NEMA-Phase_Compliant_Traffic_Signal_Controller_Module_in_SUMO.json new file mode 100644 index 00000000..6e7e7748 --- /dev/null +++ b/agency-indexes/DoE/NEMA-Phase_Compliant_Traffic_Signal_Controller_Module_in_SUMO.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2022-02-18", + "metadataLastUpdated": "2022-09-26" + }, + "description": "The controller modules in SUMO use a stage-based control structure. A phase is defined as a stage of all allowed movements at a time instance. However, traffic signal controllers used in North America widely use National Electrical Manufacturers Association (NEMA) phase definition. A NEMA phase is defined by a certain flow movement at an intersection. At one time, more than one NEMA phase could happen together as long as they do not conflict with each other. We can visualize the NEMA phases and timings in Ring-and-Barrier structured NEMA diagrams. For one controller, only one phase from a ring can be activated at a time. Phases from different rings could be activated together as long as they are not from the different sides of a barrier. When a controller is operated in fixed-time control mode, we can model the NEMA phase timing as a corresponding stage-based control timing without any issues. When introducing actuation into the signal control, a Ring-and-Barrier structured traffic signal controller can be more flexible than stage-based controller by allowing different possible phase combinations. We made two efforts in modeling Ring-and-Barrier structured controllers in SUMO. One is to translate a NEMA phases timing into SUMO-readable phases and timings as an additional file for SUMO. This translation worked well for fixed-time control. To model actuated control and coordinated actuated control, we augmented the SUMO source code by adding a Ring-and-Barrier structured controller module. This module could implement traffic signal timing from controllers using NEMA phases. We also augmented TraCI to be able to set new NEMA phase timings during simulations. We examined the Ring-and-Barrier structured traffic signal controller module by both visually observing the simulation animations and the simulation records. The developed control module can model the generalized Ring-and-Barrier structured traffic signal timing that is used in North America. SEE: https://github.com/eclipse/sumo/blob/main/src/microsim/traffic_lights/NEMAController.cpp", + "laborHours": 0.0, + "languages": [ + "Python", + "C++" + ], + "name": "NEMA-Phase Compliant Traffic Signal Controller Module in SUMO", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ATHENA-sumo", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NEML2_-_THE_NEW_ENGINEERING_MATERIAL_MODEL_LIBRARY,_VERSION_2.json b/agency-indexes/DoE/NEML2_-_THE_NEW_ENGINEERING_MATERIAL_MODEL_LIBRARY,_VERSION_2.json new file mode 100644 index 00000000..57687b67 --- /dev/null +++ b/agency-indexes/DoE/NEML2_-_THE_NEW_ENGINEERING_MATERIAL_MODEL_LIBRARY,_VERSION_2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2023-03-14" + }, + "description": "SF-22-157 NEML2 is an extension of an earlier open source code developed at ANL (SF-xxxx) called NEML. These libraries provide tools for constructing and using models of engineering materials, with a focus on high temperature materials for nuclear reactor applications. The software include tools for setting up material models, calibrating models, storing models for later use in other simulations, and running simple \"material point\" simulations of the material behavior. The main difference between NEML and NEML2 is the new software has been complete restructured to run on GPUs and other accelerators in order to improve the performance of methods used to train constitutive models against data and to improve the performance of the final models in production environments, like finite element software. While over time we expect NEML2 to become more-or-less feature complete with NEML we are filing a new software disclosure because (1) the library has been complete restructured and (2) we want to host NEML2 in a separate repository.", + "laborHours": 0.0, + "languages": [], + "name": "NEML2 - THE NEW ENGINEERING MATERIAL MODEL LIBRARY, VERSION 2", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/reverendbedford/neml2", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NEONiso_R_Package,_versions_greater_than_0.5.2.json b/agency-indexes/DoE/NEONiso_R_Package,_versions_greater_than_0.5.2.json new file mode 100644 index 00000000..703acfc8 --- /dev/null +++ b/agency-indexes/DoE/NEONiso_R_Package,_versions_greater_than_0.5.2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "Carbon fluxes in terrestrial ecosystems and their response to environmental change are a major source of uncertainty in the modern carbon cycle. The National Ecological Observatory Network (NEON) presents the opportunity to merge eddy covariance (EC)-derived fluxes with CO2 isotope ratio measurements to gain insights into carbon cycle processes. Collected continuously and consistently across >40 sites, NEON EC and isotope data facilitate novel integrative analyses. However, currently provisioned atmospheric isotope data are uncalibrated, greatly limiting ability to perform cross-site analyses. Here, we present two approaches to calibrating NEON CO2 isotope ratios, along with an R package to calibrate NEON data. We find that calibrating CO2 isotopologues independently yields a lower d13C bias (<0.05\u2030) and higher precision (<0.40\u2030) than directly correcting d13C with linear regression (bias: <0.11\u2030, precision: 0.42\u2030), but with slightly higher error and lower precision in calibrated CO2 mole fraction. The magnitude of the corrections to d13C and CO2 mole fractions vary substantially by site, underscoring the need for users to apply a consistent calibration framework to data in the NEON archive. Post-calibration data sets show that site mean annual d13C correlates negatively with precipitation, temperature, and aridity, but positively with elevation. Forested and agricultural ecosystems exhibit larger gradients in CO2 and d13C than other sites, particularly during the summer and at night. The overview and analysis tools developed here will facilitate cross-site analysis using NEON data, provide a model for other continental-scale observational networks, and enable new advances leveraging the isotope ratios of specific carbon fluxes.", + "laborHours": 0.0, + "languages": [], + "name": "NEONiso R Package, versions greater than 0.5.2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/NEONiso", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NERSC_Slurm_Software_Configurations_and_Plugins.json b/agency-indexes/DoE/NERSC_Slurm_Software_Configurations_and_Plugins.json new file mode 100644 index 00000000..68b953ff --- /dev/null +++ b/agency-indexes/DoE/NERSC_Slurm_Software_Configurations_and_Plugins.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "This software can be used to tune the HPC operations of a Cray system running Slurm workload manager software. This includes many of the customizations that NERSC has made over the past three years. In particular these customizations allow for complex site-local policies to be implemented and managed in a scalable way, or add unique capabilities to slurm via our plugins, including: * performance software integration and compute node staging * temporary directory/dynamic user content management automation * software defined networking integration", + "laborHours": 0.0, + "languages": [], + "name": "NERSC Slurm Software Configurations and Plugins", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/nersc-slurm-contrib", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/NEURAL_NETWORK_FOR_COHERENT_DIFFRACTION_IMAGE_INVERSION.json b/agency-indexes/DoE/NEURAL_NETWORK_FOR_COHERENT_DIFFRACTION_IMAGE_INVERSION.json new file mode 100644 index 00000000..4ed00a80 --- /dev/null +++ b/agency-indexes/DoE/NEURAL_NETWORK_FOR_COHERENT_DIFFRACTION_IMAGE_INVERSION.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-19", + "metadataLastUpdated": "2021-08-19" + }, + "description": "A deep neural network model plus automatic differentiation is developed for retrieving phase information from 3D coherent diffraction images. The model is implemented using Tensorflow and the training dataset is generated using physics-based atomistic simulations. Custom codes are written to handle the resampling of diffraction images to oversampling ratios appropriate for the neural network model.", + "laborHours": 0.0, + "languages": [], + "name": "NEURAL NETWORK FOR COHERENT DIFFRACTION IMAGE INVERSION", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hyiprc/3D-CDI-NN", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NEthing_v0.1.json b/agency-indexes/DoE/NEthing_v0.1.json new file mode 100644 index 00000000..aeed2a90 --- /dev/null +++ b/agency-indexes/DoE/NEthing_v0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-17" + }, + "description": "The program extends the analysis capabilities of existing profilers through additional analysis to provide insights about communication computation overlap, communication modeling, and broad performance summaries of CPU, GPU and memory. This allows users to understand how their applications are spending time and where performance bottlenecks are.", + "laborHours": 410.4, + "languages": [], + "name": "NEthing v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/nething", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/NGDS_Data_Archiver.json b/agency-indexes/DoE/NGDS_Data_Archiver.json new file mode 100644 index 00000000..dfe0b64f --- /dev/null +++ b/agency-indexes/DoE/NGDS_Data_Archiver.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is a Node.js command line utility for scraping XML metadata from CSW and WFS, downloading linkage data from CSW and WFS, pinging hosts and returning status codes, pinging data linkages and returning status codes, writing ping status to CSV files, and uploading data to Amazon S3.", + "laborHours": 790.4, + "name": "NGDS Data Archiver", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ngds/data-archiver", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NGDS_Data_Explorer.json b/agency-indexes/DoE/NGDS_Data_Explorer.json new file mode 100644 index 00000000..7022b179 --- /dev/null +++ b/agency-indexes/DoE/NGDS_Data_Explorer.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OpenLayers application to help search for features in a WFS. The publicly available site is at http://data.geothermaldatasystem.org/.", + "laborHours": 551957.6, + "name": "NGDS Data Explorer", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/NGDSDataExplorer", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NGFC-Lib_NGFC-Lib.json b/agency-indexes/DoE/NGFC-Lib_NGFC-Lib.json new file mode 100644 index 00000000..313a8599 --- /dev/null +++ b/agency-indexes/DoE/NGFC-Lib_NGFC-Lib.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-10-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Automated NGFC system design tool set to develop optimized, next-generation solid oxide fuel cell (SOFC)\nbased natural gas fuel cell (NGFC) system designs with >70% fuel efficiency and <30 g/kWh CO2 emissions", + "laborHours": 39261.6, + "languages": [], + "name": "NGFC-Lib/NGFC-Lib", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NGFC-Lib/NGFC-Lib", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NGSUtils.json b/agency-indexes/DoE/NGSUtils.json new file mode 100644 index 00000000..ddebbbad --- /dev/null +++ b/agency-indexes/DoE/NGSUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This KBase module wraps some functions of NGSUtils.", + "laborHours": 1064.0, + "languages": [], + "name": "NGSUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ngsutils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NHPP_for_FRBs,_Version_1.0.json b/agency-indexes/DoE/NHPP_for_FRBs,_Version_1.0.json new file mode 100644 index 00000000..7babd204 --- /dev/null +++ b/agency-indexes/DoE/NHPP_for_FRBs,_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code implements the non-homogeneous poisson process model for estimating the rate of fast radio bursts. It includes modeling terms for the distribution of events in the Universe and the detection sensitivity of the radio telescopes and arrays used in observation. The model is described in LA-UR-16-26261.", + "laborHours": 121.6, + "name": "NHPP for FRBs, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/NHPP-for-FRBs/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/NHPP-for-FRBs", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NIDR__New_Input_Deck_Reader__V2.0_2.json b/agency-indexes/DoE/NIDR__New_Input_Deck_Reader__V2.0_2.json new file mode 100644 index 00000000..a01fabb7 --- /dev/null +++ b/agency-indexes/DoE/NIDR__New_Input_Deck_Reader__V2.0_2.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-25" + }, + "description": "NIDR (New Input Deck Reader) is a facility for processing block-structured input to large programs. NIDR was written to simplify maintenance of DAKOTA (a program for uncertainty quantification and optimization), to provide better error checking of input and to allow use of aliases in the input. While written to support DAKOTA input conventions, NIDR itself is independent of DAKOTA and can be used in many kinds of programs. The initial version of NIDR was copyrighted in 2008. We have since extended NIDR to support a graphical user interface called Jaguar for DAKOTA. In the Review and Approval process for an updated paper on NIDR, the Classification Approver states that a new copyright assertion should be performed.processing input to programs. NIDR is not primarily for military applications.", + "laborHours": 0.0, + "languages": [ + "C++/C" + ], + "name": "NIDR (New Input Deck Reader) V2.0 2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/nidr", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.02" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NIMROD_magnetohydrodynamics_code.json b/agency-indexes/DoE/NIMROD_magnetohydrodynamics_code.json new file mode 100644 index 00000000..a1ca6ecb --- /dev/null +++ b/agency-indexes/DoE/NIMROD_magnetohydrodynamics_code.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "NIMROD uses a combination of semi-implicit and implicit time-stepping algorithms to advance the equations of extended magnetohydrodynamics. It uses 2D spectral elements and Fourier series for the third periodic direction.", + "homepageURL": "https://www.tibbartech.com/technology", + "laborHours": 0.0, + "languages": [ + "Fortran 90" + ], + "name": "NIMROD magnetohydrodynamics code", + "organization": "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.tibbartech.com/technology", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.tibbartech.com/technology", + "status": "Production", + "tags": [ + "DOE CODE", + "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/NINJA.json b/agency-indexes/DoE/NINJA.json new file mode 100644 index 00000000..816cfd21 --- /dev/null +++ b/agency-indexes/DoE/NINJA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Ninja (Noise INJection Agent) is a tool for reproducing subtle and unintended message races.\n", + "laborHours": 2812.0, + "languages": [], + "name": "NINJA", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PRUNERS/NINJA", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NISQ_Benchmarking.json b/agency-indexes/DoE/NISQ_Benchmarking.json new file mode 100644 index 00000000..b9f07832 --- /dev/null +++ b/agency-indexes/DoE/NISQ_Benchmarking.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2022-07-15" + }, + "description": "Test suite of quantum algorithms for Noisy Intermediate Scale Quantum (NISQ) computers. The test suite includes benchmark-style code for quantum volume circuits (QV), fairness sampling circuits, quantum telecloning circuits, and other NISQ benchmark style algorithms on small problems (i.e., up to 100 qubits), such as Variational Quantum Eigensolver (VQE), Hamiltonian Simulation, and Grover unstructured search example circuits. These benchmark-style applications are implemented in quantum software packages, mostly IBM's QISKIT, but may include vendor-specific frameworks, such as PyQuil (for Rigetti) or Q\\# for Microsoft, or CirQ (for Google) as the test suite grows with the vendor sample. The test suite also includes numerical simulation code for Quantum Alternating Operator Ansatz (QAOA) algorithms, VQE, Hamiltonian Simulation and search examples. Numerical simulation code simulates quantum computers on classical computers, which is only possible for small problem instances; the implementation framework of choice is typically within Python, using the numpy/scipy libraries as well as extensions to the Julia language.", + "laborHours": 0.0, + "languages": [], + "name": "NISQ Benchmarking", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Quantum-Volume-in-Practice", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NJOY2016.json b/agency-indexes/DoE/NJOY2016.json new file mode 100644 index 00000000..416eb11d --- /dev/null +++ b/agency-indexes/DoE/NJOY2016.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "NJOY2016 is used to convert evaluations in the Evaluated Nuclear Data Files (ENDF) format into forms useful for practical applications such as fission and fusion reactor analysis, criticality safety, radiation shielding, nuclear waste management, nuclear medicine procedures, and more. It begins with the generation of pointwise libraries, including reaction and resonance reconstruction, Doppler broadening, radiation heating and damage, thermal scattering data, unresolved resonance data, and gas production. It reviews the production of libraries for the continuous-energy Monte Carlo code MCNP, multigroup neutron, photon, and particle cross sections and matrices, and photon interaction data. Uncertainty information for ENDF data is processed, including the capability for calculating covariances of resonance data, angular distributions, energy distributions, and radioactive nuclide production. NJOY can prepare and process thermal scattering data evaluations into application libraries. It can also plot cross sections, angular distributions and secondary emission spectra.", + "laborHours": 1945.6, + "name": "NJOY2016", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/njoy/NJOY21/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/njoy/NJOY21.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NLPVis.json b/agency-indexes/DoE/NLPVis.json new file mode 100644 index 00000000..a17f53e8 --- /dev/null +++ b/agency-indexes/DoE/NLPVis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-20" + }, + "description": "NLPVis is a visualization system that, through a tight yet flexible integration between visualization elements and the underlying model, allows a user to interrogate the modal by perturbing the input, internal state, and prediction while observing changes. ", + "laborHours": 6551.2, + "languages": [], + "name": "NLPVis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/shusenl/nlpvis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NMACFoam__Numerical-model_for_Membrane-spacer_Assemblies_and_Configurations_in_OpenFOAM__[SWR-23-57].json b/agency-indexes/DoE/NMACFoam__Numerical-model_for_Membrane-spacer_Assemblies_and_Configurations_in_OpenFOAM__[SWR-23-57].json new file mode 100644 index 00000000..6c52b4f8 --- /dev/null +++ b/agency-indexes/DoE/NMACFoam__Numerical-model_for_Membrane-spacer_Assemblies_and_Configurations_in_OpenFOAM__[SWR-23-57].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-08-15", + "metadataLastUpdated": "2023-09-11" + }, + "description": "NMACFoam is a computational fluid dynamics tool for simulating flow and solids transport in membrane-spacer channels pertaining to reverse osmosis or nanofiltration applications. It is developed on the OpenFOAM framework and allows for simulating spacers with complex geometries. It includes porous wall boundary conditions for membranes and can accurately capture concentration polarization effects. One can perform large calculations at module-scale domain sizes using high performance computing resources with NMACFoam, which scales to 1000s of processors for problems with 1-10 million cells.", + "laborHours": 0.0, + "languages": [ + "C++", + "python", + "C" + ], + "name": "NMACFoam (Numerical-model for Membrane-spacer Assemblies and Configurations in OpenFOAM) [SWR-23-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NMACFoam", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NMDC_Field_Notes_Phone_Application__NMDC_Field_Notes__v1.0.json b/agency-indexes/DoE/NMDC_Field_Notes_Phone_Application__NMDC_Field_Notes__v1.0.json new file mode 100644 index 00000000..c2fd26d3 --- /dev/null +++ b/agency-indexes/DoE/NMDC_Field_Notes_Phone_Application__NMDC_Field_Notes__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2024-05-09", + "metadataLastUpdated": "2024-05-09" + }, + "description": "This software is for an application, designed for phones and/or tablets, to assist microbiome researchers collecting samples in the field to also collect metadata in a standardized and systematic way. The type of samples covered would be e.g. soil sample from a forest, sediment sample from a lake, or water sample in the ocean. The app allows users to collect sample information and metadata in an easy and intuitive way, and connects to the NMDC submission portal (https://data.microbiomedata.org/submission/home) a website from where users can review the samples they collected and add more information if necessary.", + "laborHours": 19076.0, + "languages": [], + "name": "NMDC Field Notes Phone Application (NMDC Field Notes) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/microbiomedata/nmdc-field-notes", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NMDC_sample_import.json b/agency-indexes/DoE/NMDC_sample_import.json new file mode 100644 index 00000000..cd35ffd5 --- /dev/null +++ b/agency-indexes/DoE/NMDC_sample_import.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "This is the repository for \"NMDC_sample_import\" developed by KBase.", + "laborHours": 136.8, + "languages": [], + "name": "NMDC_sample_import", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/NMDC_sample_import", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NMR_DIFFSIM_v._1.0.json b/agency-indexes/DoE/NMR_DIFFSIM_v._1.0.json new file mode 100644 index 00000000..bc4223d2 --- /dev/null +++ b/agency-indexes/DoE/NMR_DIFFSIM_v._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2019-03-12" + }, + "description": "The software generates and analyzes nuclear magnetic resonance spin diffusion simulations for the purpose of measuring domain sizes or spin diffusion constants in a heterogenous sample. Its primary capabilities are:\n1.\tIt solves the spin magnetization diffusion equation to simulate the results of a spin diffusion experiment using any structural input geometry, including structure models generated by molecular dynamics or other computational or experimental methods.\n2.\tIt compares the results of simulations on an input structure to experimental data, providing a data fitting algorithm to extract physical information from the experimental data via the simulation.\n3.\tIt can provide statistical measures to compare correlations between structural models, to determine domain clustering and connectedness, and to provide goodness-of-fit measures including chord length distributions, chi-squared values, Pearson coefficients and pair correlation functions.\n4.\tIt provides output reports, data files, and movies to visualize simulation results.\n", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 410.4, + "languages": [ + "MATLAB" + ], + "name": "NMR_DIFFSIM v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NMTRI_v_1.0.json b/agency-indexes/DoE/NMTRI_v_1.0.json new file mode 100644 index 00000000..d50b1547 --- /dev/null +++ b/agency-indexes/DoE/NMTRI_v_1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "This code consists of Matlab routines which enable the user to perform non-manifold surface reconstruction via triangulation from high dimensional point cloud data. The code was based on an algorithm originally developed in [Freedman (2007), An Incremental Algorithm for Reconstruction of Surfaces of Arbitrary Codimension Computational Geometry: Theory and Applications, 36(2):106-116]. This algorithm has been modified to accommodate non-manifold surface according to the work described in [S. Martin and J.-P. Watson (2009), Non-Manifold Surface Reconstruction from High Dimensional Point Cloud DataSAND #5272610].The motivation for developing the code was a point cloud describing the molecular conformation space of cyclooctane (C8H16). Cyclooctane conformation space was represented using points in 72 dimensions (3 coordinates for each molecule). The code was used to triangulate the point cloud and thereby study the geometry and topology of cyclooctane. Futures applications are envisioned for peptides and proteins.", + "laborHours": 0.0, + "languages": [], + "name": "NMTRI v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/NMTRI", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/NMTRI", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NOAA_Weather_Data_Scraper.json b/agency-indexes/DoE/NOAA_Weather_Data_Scraper.json new file mode 100644 index 00000000..90123c54 --- /dev/null +++ b/agency-indexes/DoE/NOAA_Weather_Data_Scraper.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-22", + "metadataLastUpdated": "2021-04-22" + }, + "description": "This python package pulls hourly weather information from the NCEI server, cleans the data and prepares it for use with LBNL's M&V2.0 tools.", + "laborHours": 0.0, + "languages": [], + "name": "NOAA Weather Data Scraper", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/NWDS", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NOODLES_[SWR-22-78].json b/agency-indexes/DoE/NOODLES_[SWR-22-78].json new file mode 100644 index 00000000..a3abeb83 --- /dev/null +++ b/agency-indexes/DoE/NOODLES_[SWR-22-78].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-09-29", + "metadataLastUpdated": "2022-11-07" + }, + "description": "NOODLES is a protocol specification for collaborative visualization. It allows software tools of any type to participate in an analysis or visualization session. Use cases include, but are not limited to, distributed analysis, workflow interoperability, computational steering, etc.", + "laborHours": 0.0, + "languages": [], + "name": "NOODLES [SWR-22-78]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/InsightCenterNoodles/message_spec", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NOUS:_A_Knowledge_Graph_Management_System.json b/agency-indexes/DoE/NOUS:_A_Knowledge_Graph_Management_System.json new file mode 100644 index 00000000..9b7fb8e1 --- /dev/null +++ b/agency-indexes/DoE/NOUS:_A_Knowledge_Graph_Management_System.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Knowledge graphs represent information as entities and relationships between them. For tasks such as natural language question answering or automated analysis of text, a knowledge graph provides valuable context to establish the specific type of entities being discussed. It allow us to derive better context about newly arriving information and leads to intelligent reasoning capabilities. We address two primary needs: A) Automated construction of knowledge graphs is a technically challenging, expensive process; and B) The ability to synthesize new information by monitoring newly emerging knowledge is a transformational capability that does not exist in state of the art systems.", + "laborHours": 19136.8, + "name": "NOUS: A Knowledge Graph Management System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/streaming-graphs/NOUS", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/streaming-graphs/NOUS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NOVA_NOVA-K.json b/agency-indexes/DoE/NOVA_NOVA-K.json new file mode 100644 index 00000000..00ba087f --- /dev/null +++ b/agency-indexes/DoE/NOVA_NOVA-K.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "ngorelen@pppl.gov" + }, + "date": { + "created": "2018-07-27", + "metadataLastUpdated": "2018-07-27" + }, + "description": "NOVA is a suite of codes including the linear ideal eigenmode solver to find the solutions of ideal magnetohydrodynamic (MHD) system of equations, including such effects as plasma compressibility and realistic tokamak geometry. The kinetic post-processor of the suite, NOVA-K, analyses those solutions to find their stability properties. NOVA-K evaluates the wave particle interaction of the eigenmodes such as Toroidal Alfv\u00e9n Eigenmodes (TAEs) or Reversed Shear Alfv\u00e9n Eigenmodes (RSAEs) by employing the quadratic form with the perturbed distribution function coming from the drift kinetic equations. In computations of the hot ion contribution to the growth rate NOVA-K makes use of the constant of motion to represent the hot particle drift orbits. \nNOVA is routinely used for AE structure computations and comparisons with the experimentally observed instabilities [M. A. Van Zeeland et al., Phys. Rev. Lett. 97, 135001 (2006), G. J. Kramer, Phys. Plasmas 13, 056104 (2006)]. The main limitations of NOVA code are caused by neglecting thermal ion finite Larmor radius (FLR), toroidal rotation, and drift effects for the eigenmode computations. Therefore it can not describe accurately radiative damping for example. Finite element methods are used in radial direction and Fourier harmonics are used in poloidal and toroidal directions.\n\nNOVA-K is able to predict various kinetic growth and damping rates perturbatively, such as the phase space gradient drive from energetic particles, continuum damping, radiative damping, ion/electron Landau damping and trapped electron collisional damping. ", + "homepageURL": "https://theory.pppl.gov/research/research.php?rid=10#h45", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "NOVA/NOVA-K", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://theory.pppl.gov/research/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://theory.pppl.gov/research/research.php?rid=10#h45", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/NPD_Hydro.json b/agency-indexes/DoE/NPD_Hydro.json new file mode 100644 index 00000000..928c0d27 --- /dev/null +++ b/agency-indexes/DoE/NPD_Hydro.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-04-15", + "metadataLastUpdated": "2024-04-15" + }, + "description": "This tool, the Non-Powered Dam Hydropower Development and Ranking Opportunity Tool (NPD HYDRO), allows users to prioritize or rank NPD sites for future development based on user-defined priorities. Benefits can be evaluated in several categories: the grid, community, industry, and environment (represented by the GCIE impact scores in the tool. In addition, the tool provides the user with a qualitative measure for the feasibility of adding energy storage during NPD conversion, specifically battery, hydrogen electrolysis, and pumped-storage hydropower (PSH). By taking a holistic approach to the potential range of benefits provided by NPD conversions with results tailored to the user\u2019s priorities, NPD HYDRO provides the opportunity for national-level screening and enables users to focus on the sites that are most closely aligned with their interests.", + "laborHours": 4696.8, + "languages": [ + "Python" + ], + "name": "NPD Hydro", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/NPD_Hydro", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NREL_OpenStudio.json b/agency-indexes/DoE/NREL_OpenStudio.json new file mode 100644 index 00000000..790ee4c5 --- /dev/null +++ b/agency-indexes/DoE/NREL_OpenStudio.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-05-18", + "metadataLastUpdated": "2018-05-18" + }, + "description": "OpenStudio is a cross-platform collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance.\n\nThis disclosure includes two OpenStudio measures: (1) data center prototype models, and (2) occupant schedule generator. The data center models cover two sizes (small computer server rooms, stand-alone large data centers) and two IT load densities (average and high).", + "laborHours": 4456883.2, + "languages": [], + "name": "NREL/OpenStudio", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NREL_Wind_Analysis_Library__NRWAL_.json b/agency-indexes/DoE/NREL_Wind_Analysis_Library__NRWAL_.json new file mode 100644 index 00000000..de02bc4c --- /dev/null +++ b/agency-indexes/DoE/NREL_Wind_Analysis_Library__NRWAL_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-18" + }, + "description": "The National Renewable Energy Laboratory Wind Analysis Library (NRWAL) contains --A library of wind cost equations, --Dynamic Python tools for intuitive equation handling, --Ready-to-use configs for basic users, and --Easy equation manipulation without editing source code.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "NREL Wind Analysis Library (NRWAL)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NRWAL", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NREL_Wind_Energy_Cost_and_Scaling_Model.json b/agency-indexes/DoE/NREL_Wind_Energy_Cost_and_Scaling_Model.json new file mode 100644 index 00000000..f1b8439d --- /dev/null +++ b/agency-indexes/DoE/NREL_Wind_Energy_Cost_and_Scaling_Model.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2022-09-19" + }, + "description": "NREL_CSM is a set of models that provide an overall cost of energy analysis for the wind plant.", + "laborHours": 2295.2, + "languages": [], + "name": "NREL Wind Energy Cost and Scaling Model", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/nrel_csm", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NREL_Wind_Integrated_System_Design_and_Engineering_Model.json b/agency-indexes/DoE/NREL_Wind_Integrated_System_Design_and_Engineering_Model.json new file mode 100644 index 00000000..c92c76f3 --- /dev/null +++ b/agency-indexes/DoE/NREL_Wind_Integrated_System_Design_and_Engineering_Model.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "NREL_WISDEM is an integrated model for wind turbines and plants developed In python based on the open source software OpenMDAO. NREL_WISDEM is a set of wrappers for various wind turbine and models that integrate pre-existing models together into OpenMDAO. It is organized into groups each with their own repositories including Plant_CostSE. Plant_EnergySE, Turbine_CostSE and TurbineSE. The wrappers are designed for licensed and non-licensed models though in both cases, one has to have access to and install the individual models themselves before using them in the overall software platform.", + "laborHours": 229778.4, + "name": "NREL Wind Integrated System Design and Engineering Model", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/WISDEM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NRIC_Digital_Engineering_Ecosystem.json b/agency-indexes/DoE/NRIC_Digital_Engineering_Ecosystem.json new file mode 100644 index 00000000..68313cca --- /dev/null +++ b/agency-indexes/DoE/NRIC_Digital_Engineering_Ecosystem.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-02-05", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The NRIC Digital Engineering Ecosystem is a software suite designed to eliminate procedural failures in the engineering lifecycle of complex projects. It focuses on improving the flow of scheduling data, safety information, engineering requirements, and CAD files among stakeholders of complex engineering projects. The project comprises software adapters that move engineering data from disparate software tools in and out of a central database. The ecosystem is designed to efficiently incorporate data sources from many different engineering toolsets, making it software agnostic, and adaptable to many different engineering applications.", + "laborHours": 0.0, + "languages": [ + "JavaScript" + ], + "name": "NRIC Digital Engineering Ecosystem", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/IDEAS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NRM.json b/agency-indexes/DoE/NRM.json new file mode 100644 index 00000000..f2182ce8 --- /dev/null +++ b/agency-indexes/DoE/NRM.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-20", + "metadataLastUpdated": "2020-05-20" + }, + "description": "Argo Node Resource Manager: dynamic resource management for Linux. Resource management daemon using communication with clients to control\npower usage of application.", + "laborHours": 1748.0, + "languages": [], + "name": "NRM", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://xgitlab.cels.anl.gov/argo/nrm", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSDD_Knowledge_Management_Mobile_App.json b/agency-indexes/DoE/NSDD_Knowledge_Management_Mobile_App.json new file mode 100644 index 00000000..6ab809cb --- /dev/null +++ b/agency-indexes/DoE/NSDD_Knowledge_Management_Mobile_App.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The US / DOE Office of Nuclear Smuggling Detection and Deterrence (NSDD) Knowledge Management Mobile App will\nprovide password-protected direct access to non-sensitive information regarding the operations, maintenance, and\nsustainability of deployed radiation detection systems. This Mobile App will serve content managed on the NSDD\nKnowledge Management Website to users in a more user-friendly manner. The Mobile App will be cross-platform,\nfunctioning for both iOS and Android devices. The Mobile App will operate both with and without a network connection,\nprovide access to KMW content based on the users' interests, and strengthen analysis of NSDD's training effectiveness.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "NSDD Knowledge Management Mobile App", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSLS-II.json b/agency-indexes/DoE/NSLS-II.json new file mode 100644 index 00000000..f6cf67f2 --- /dev/null +++ b/agency-indexes/DoE/NSLS-II.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-01", + "metadataLastUpdated": "2019-07-01" + }, + "description": "Repository of tools used for both data collection and analysis at NSLS-II. This is a home for facility-wide tools: code that is generalized for use at multiple beamlines but not necessarily generalized for use at multiple facilities.", + "laborHours": 1398.4, + "languages": [], + "name": "NSLS-II", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/nslsii", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSLS-II_analysisstore.json b/agency-indexes/DoE/NSLS-II_analysisstore.json new file mode 100644 index 00000000..be3364d0 --- /dev/null +++ b/agency-indexes/DoE/NSLS-II_analysisstore.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "Prototype analysis results database (for the MX beamlines).", + "laborHours": 1261.6, + "languages": [], + "name": "NSLS-II/analysisstore", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/analysisstore", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSLS-II_aps-trial.json b/agency-indexes/DoE/NSLS-II_aps-trial.json new file mode 100644 index 00000000..ae9d35c2 --- /dev/null +++ b/agency-indexes/DoE/NSLS-II_aps-trial.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "Testing pushing Event documents over 0MQ to a tomogrpahy analysis pipeline.\n", + "laborHours": 91.2, + "languages": [], + "name": "NSLS-II/aps-trial", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/aps-trial", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSLS-II_channelarchiver.json b/agency-indexes/DoE/NSLS-II_channelarchiver.json new file mode 100644 index 00000000..69818dd7 --- /dev/null +++ b/agency-indexes/DoE/NSLS-II_channelarchiver.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-03", + "metadataLastUpdated": "2019-07-03" + }, + "description": "A python client for retrieving data from an EPICS Channel Archiver.", + "laborHours": 729.6, + "languages": [], + "name": "NSLS-II/channelarchiver", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/channelarchiver", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSLS-II_controls-doctor.json b/agency-indexes/DoE/NSLS-II_controls-doctor.json new file mode 100644 index 00000000..a8c14178 --- /dev/null +++ b/agency-indexes/DoE/NSLS-II_controls-doctor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "A diagnostic tool for NSLS-II beamlines.", + "laborHours": 456.0, + "languages": [], + "name": "NSLS-II/controls-doctor", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/controls-doctor", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSLS-II_docker-collection.json b/agency-indexes/DoE/NSLS-II_docker-collection.json new file mode 100644 index 00000000..51147fb4 --- /dev/null +++ b/agency-indexes/DoE/NSLS-II_docker-collection.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "Docker with the lightsource2-tag/collection metapackage.", + "laborHours": 30.4, + "languages": [], + "name": "NSLS-II/docker-collection", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/docker-collection", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSLS-II_docs.json b/agency-indexes/DoE/NSLS-II_docs.json new file mode 100644 index 00000000..53ec7f09 --- /dev/null +++ b/agency-indexes/DoE/NSLS-II_docs.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "Standards Documentation for NSLS-II DAQ and Analysis.", + "laborHours": 1140.0, + "languages": [], + "name": "NSLS-II/docs", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/docs", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSLS-II_doct.json b/agency-indexes/DoE/NSLS-II_doct.json new file mode 100644 index 00000000..ba58a357 --- /dev/null +++ b/agency-indexes/DoE/NSLS-II_doct.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "A read-only dottable dictionary. Document is a light-weight sub-class of the built in dict which is read only, has . (getattr) access, and knows it's _name. ", + "laborHours": 121.6, + "languages": [], + "name": "NSLS-II/doct", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/doct/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/doct", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSLS-II_epics-modules.json b/agency-indexes/DoE/NSLS-II_epics-modules.json new file mode 100644 index 00000000..bb245056 --- /dev/null +++ b/agency-indexes/DoE/NSLS-II_epics-modules.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "This is a repository to build areaDetector and its dependencies out of the relevant git repositories. 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", + "laborHours": 45.6, + "languages": [], + "name": "NSLS-II/summer-interns", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/summer-interns", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSLS-II_summer-student-exercises.json b/agency-indexes/DoE/NSLS-II_summer-student-exercises.json new file mode 100644 index 00000000..b8d580fc --- /dev/null +++ b/agency-indexes/DoE/NSLS-II_summer-student-exercises.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "These are some additional exercises for the summer students to try to help them with using python in a scientific analysis environment.", + "laborHours": 76.0, + "languages": [], + "name": "NSLS-II/summer-student-exercises", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/summer-student-exercises", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSLS-II_synthetic-data.json b/agency-indexes/DoE/NSLS-II_synthetic-data.json new file mode 100644 index 00000000..58f7d8dc --- /dev/null +++ b/agency-indexes/DoE/NSLS-II_synthetic-data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "Data generation utility for testing.", + "laborHours": 456.0, + "languages": [], + "name": "NSLS-II/synthetic-data", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/synthetic-data", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSLS-II_vertical-integration.json b/agency-indexes/DoE/NSLS-II_vertical-integration.json new file mode 100644 index 00000000..509fd214 --- /dev/null +++ b/agency-indexes/DoE/NSLS-II_vertical-integration.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "Vertical integration testing for the NSLS-II data stack. vertical-integration is a fake library that tricks travis into building the outer product of the NSLS-II data stack for master and the latest point releases for all of our libraries on python 2.7 and 3.4.", + "laborHours": 91.2, + "languages": [], + "name": "NSLS-II/vertical-integration", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/vertical-integration", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSO_Processing_Scripts__NSO_wind_loading_data_set_processing_scripts__[SWR-23-86].json b/agency-indexes/DoE/NSO_Processing_Scripts__NSO_wind_loading_data_set_processing_scripts__[SWR-23-86].json new file mode 100644 index 00000000..cc2b80f0 --- /dev/null +++ b/agency-indexes/DoE/NSO_Processing_Scripts__NSO_wind_loading_data_set_processing_scripts__[SWR-23-86].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-30", + "metadataLastUpdated": "2024-04-05" + }, + "description": "NREL conducted comprehensive field measurements of the atmospheric turbulent wind conditions and the resulting structural wind loads on parabolic troughs at the Nevada Solar One plant from October 2021 to June, 2023. The measurement set-up included meteorological masts and structural load sensors on four trough rows. Additionally, NREL commissioned a lidar scanning the horizontal plane over the trough field. The high-resolution data set, characterizing the complex flow field and resulting structural loads, is available at https://data.openei.org/submissions/5938. The processing routines published here were used to create the data from the instruments' raw data.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "NSO Processing Scripts (NSO wind loading data set processing scripts) [SWR-23-86]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NSO_processing_scripts", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSRDB__National_Solar_Radiation_Database_Software__[SWR-23-77].json b/agency-indexes/DoE/NSRDB__National_Solar_Radiation_Database_Software__[SWR-23-77].json new file mode 100644 index 00000000..a07f010a --- /dev/null +++ b/agency-indexes/DoE/NSRDB__National_Solar_Radiation_Database_Software__[SWR-23-77].json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-02", + "metadataLastUpdated": "2024-01-09" + }, + "description": "This repository contains all of the methods for the NSRDB data processing pipeline. The NSRDB is a serially complete collection of hourly and half-hourly values of meteorological data and the three most common measurements of solar radiation: global horizontal, direct normal and diffuse horizontal irradiance.", + "laborHours": 0.0, + "languages": [ + "HTML", + "C", + "Jupyter Notebook", + "Python" + ], + "name": "NSRDB (National Solar Radiation Database Software) [SWR-23-77]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/nsrdb", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "4.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NSU_Hack-a-Thon_Workshop_v.2.0.json b/agency-indexes/DoE/NSU_Hack-a-Thon_Workshop_v.2.0.json new file mode 100644 index 00000000..01a56e2c --- /dev/null +++ b/agency-indexes/DoE/NSU_Hack-a-Thon_Workshop_v.2.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-05-31", + "metadataLastUpdated": "2023-06-07" + }, + "description": "SAND2021-6722 O\nThis is a fitness tracking mobile application and server created to train college-level students to build full stack software. The front end is written using an open-source framework called Flutter. The API server is written using an open-source python framework called Flask. The app functions as a workout tracker and is intentionally partially functional for the purpose of training students during the live workshops hosted by Sandia's HR recruiting teams. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Dart", + "Python" + ], + "name": "NSU Hack-a-Thon Workshop v.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ohon3/sandia-hackathon-fall2021", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NVIDIA_df-nvshmem-prototype.json b/agency-indexes/DoE/NVIDIA_df-nvshmem-prototype.json new file mode 100644 index 00000000..83edddfa --- /dev/null +++ b/agency-indexes/DoE/NVIDIA_df-nvshmem-prototype.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "spotluri@nvidia.com" + }, + "date": { + "created": "2018-06-12", + "metadataLastUpdated": "2020-09-08" + }, + "description": "Prototype of OpenSHMEM for NVIDIA GPUs, developed as part of DoE Design Forward project.", + "laborHours": 744.8, + "languages": [ + "C" + ], + "name": "NVIDIA/df-nvshmem-prototype", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NVIDIA/df-nvshmem-prototype", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NWChem.json b/agency-indexes/DoE/NWChem.json new file mode 100644 index 00000000..e0c79052 --- /dev/null +++ b/agency-indexes/DoE/NWChem.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "edoardo.apra@pnnl.gov" + }, + "date": { + "created": "2024-06-13", + "metadataLastUpdated": "2024-06-17" + }, + "description": "NWChem is a computational chemistry software package which includes quantum chemical and molecular dynamics functionality. 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This includes large surface models, functionalized surfaces, or supported clusters, relevant to many chemical problems in Separations and Catalysis. The program was developed to address these issues, and also solve the problem associated with the need to know the large number of structures that are energetically close. Knowing\nhow many structures are similar allows us to develop better starting models for large scale simulations.", + "homepageURL": "https://store.pnnl.gov/content/north-west-potential-energy-surface-search-engine-nwpesse", + "laborHours": 0.0, + "languages": [], + "name": "NWPEsSE (North West Potential Energy Surface Search Engine)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/north-west-potential-energy-surface-search-engine-nwpesse", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/NWQ-sim.json b/agency-indexes/DoE/NWQ-sim.json new file mode 100644 index 00000000..51d3c604 --- /dev/null +++ b/agency-indexes/DoE/NWQ-sim.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "NWQSim is a quantum circuit simulation environment developed at PNNL. 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The data are stored in HDF5 files, which conform to the NeXus data format standard. These files contain a comprehensive set of metadata, including the incident wavelength, powder calibration scans used to define detector distances, beam centers, and yaw, pitch, and roll corrections. Automated peak searches of the three-dimensional data arrays define a set of Bragg peaks that are used to define an orientation matrix, defined according to Busing and Levy, which is then used to transform the data from angular coordinates to reciprocal space coordinates using the CCTW program. Multiple rotations at different detector translations and offset rotation axes are combined to ensure that there are no gaps in the reconstructed data, and allow the construction of masks to eliminate detector artifacts due to Compton scattering within the sensor layers. Finally, the data can be transformed into 3D-\u0394PDF maps using the punch-and-fill method after symmetrization.", + "laborHours": 0.0, + "languages": [], + "name": "NXREFINE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/axmas-anl/nxrefine", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NaTGenPD__National_Thermal_Generator_Performance_Database_.json b/agency-indexes/DoE/NaTGenPD__National_Thermal_Generator_Performance_Database_.json new file mode 100644 index 00000000..164a8802 --- /dev/null +++ b/agency-indexes/DoE/NaTGenPD__National_Thermal_Generator_Performance_Database_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-09-17", + "metadataLastUpdated": "2020-11-12" + }, + "description": "The National Thermal Generator Performance Database (NaTGenPD) is a code base used for the processing (extraction, cleaning, filtering, and fitting) and analysis of EPA CEMS data to produce a National Thermal Generator Performance Database.", + "laborHours": 2538.4, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "NaTGenPD (National Thermal Generator Performance Database)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/NaTGenPD", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nacelle_Systems_Engineering_Model_and_Hub_Systems_Engineering_Model.json b/agency-indexes/DoE/Nacelle_Systems_Engineering_Model_and_Hub_Systems_Engineering_Model.json new file mode 100644 index 00000000..119cf5ad --- /dev/null +++ b/agency-indexes/DoE/Nacelle_Systems_Engineering_Model_and_Hub_Systems_Engineering_Model.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "nacelleSE and hubSE are a set of models that size wind turbine hub system and drivetrain components based on key turbine design parameters and load inputs from a rotor model.", + "laborHours": 3070.4, + "name": "Nacelle Systems Engineering Model and Hub Systems Engineering Model", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/drivese", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nalu-Wind_v.1.2.0.json b/agency-indexes/DoE/Nalu-Wind_v.1.2.0.json new file mode 100644 index 00000000..d2f9075f --- /dev/null +++ b/agency-indexes/DoE/Nalu-Wind_v.1.2.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-05" + }, + "description": "Nalu-Wind is derived from Nalu-CFD (for which Sandia has an existing copyright assertion). Nalu-Wind is specific to the wind energy simulation space. SAND2019-10379 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 134398.4, + "languages": [], + "name": "Nalu-Wind v.1.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exawind/nalu-wind", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nalu.json b/agency-indexes/DoE/Nalu.json new file mode 100644 index 00000000..6273c0eb --- /dev/null +++ b/agency-indexes/DoE/Nalu.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Nalu is a Sierra ToolKit (STK) based application module, and it has provided a set of \"lessons learned\" for the STK transition effort through its early adoption of STK. It makes use of the open-sourced Trilinos/ Tpetra library. Through the investment of LORD and ASCR projects, the Nalu code module has been extended beyond prototype status. Physics capability includes low Mach, variable density turbulent flow. The ongoing objective for Nalu is to facilitate partnerships with external organizations in order to extend code capability and knowledge; however, it is not intended to support routine CFD analysis. The targeted usage of this module is for non-NW applications that support work-for-others in the multiphysics energy sector.", + "laborHours": 50388.0, + "name": "Nalu", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/spdomin/Nalu/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spdomin/Nalu", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Name_Normalizer.json b/agency-indexes/DoE/Name_Normalizer.json new file mode 100644 index 00000000..82ebb321 --- /dev/null +++ b/agency-indexes/DoE/Name_Normalizer.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-09-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Our name normalizer and enrichment micro-service address the shortcomings of standard text normalization. Initially the\ntext input is split into tokens. This process takes into account some conventions of formatting. Any dashes present\nbetween two tokens preserves the relationship of those two tokens. Conversely a comma between two tokens ensures\nthat the separation between the two tokens is maintained. The order of tokens is also preserved. Standard text\nnormalization (conversion to lowercase, trimming extra white space, and canonicalization) is then applied to the tokens.\nOnce normalized every unique and sequence of tokens is given confidence values by comparing the normalized values to\npublicly available data.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Name Normalizer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nami.json b/agency-indexes/DoE/Nami.json new file mode 100644 index 00000000..e5a91cbe --- /dev/null +++ b/agency-indexes/DoE/Nami.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This is Nami, a library for parallel wavelet compression. \n", + "laborHours": 1976.0, + "languages": [], + "name": "Nami", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/nami", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nano-Second_Gated_CMOS_Camera_Software.json b/agency-indexes/DoE/Nano-Second_Gated_CMOS_Camera_Software.json new file mode 100644 index 00000000..89eba734 --- /dev/null +++ b/agency-indexes/DoE/Nano-Second_Gated_CMOS_Camera_Software.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "hill35@llnl.gov" + }, + "date": { + "created": "2022-08-03", + "metadataLastUpdated": "2022-09-07" + }, + "description": "nsCamera is a driver for nanosecond gated CMOS cameras developed at LLNL and Sandia. It serves as a uniform application interface regardless of the actual combination of camera electronics and sensors used. The software abstracts the hardware to enable a user to write applications without detailed knowledge of the inner workings of each of the boards an sensors they may wish to deploy.", + "laborHours": 0.0, + "languages": [], + "name": "Nano-Second Gated CMOS Camera Software", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nsgcc/nsCamera", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NanoGW.json b/agency-indexes/DoE/NanoGW.json new file mode 100644 index 00000000..f4d61613 --- /dev/null +++ b/agency-indexes/DoE/NanoGW.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "lioukaihsin@utexas.edu" + }, + "date": { + "created": "2021-06-27", + "metadataLastUpdated": "2021-06-27" + }, + "description": "NanoGW can perform the following calculations:\n\n1. Linear-response time-dependent density functional theory (by solving Casida equation)\n2. Full-frequency GW calculation with or without LDA vertex function (does not support spin-orbit coupling)\n3. Construct and solve Bethe-Salpeter equation\n\nNanoGW has been tested thoroughly and optimized for molecules and nanoclusters. It runs particularly efficient for small-size (less than 30 atoms) molecules or clusters. This package can also deal with crystalline systems. However, its functionality for dealing crystals has not been thoroughly tested yet.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "NanoGW", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/real-space/nanogw", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/NarrativeDownloadSupport.json b/agency-indexes/DoE/NarrativeDownloadSupport.json new file mode 100644 index 00000000..f6299618 --- /dev/null +++ b/agency-indexes/DoE/NarrativeDownloadSupport.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "This is the repository for \"NarrativeDownloadSupport\" developed by KBase. ", + "laborHours": 714.4, + "languages": [], + "name": "NarrativeDownloadSupport", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/NarrativeDownloadSupport", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NarrativeService.json b/agency-indexes/DoE/NarrativeService.json new file mode 100644 index 00000000..546000fe --- /dev/null +++ b/agency-indexes/DoE/NarrativeService.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-08", + "metadataLastUpdated": "2020-09-08" + }, + "description": "This is the repository for \"NarrativeService\" developed by KBase. ", + "laborHours": 2903.2, + "languages": [], + "name": "NarrativeService", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/NarrativeService", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NarrativeViewers.json b/agency-indexes/DoE/NarrativeViewers.json new file mode 100644 index 00000000..30e9dabc --- /dev/null +++ b/agency-indexes/DoE/NarrativeViewers.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is the repository for \"NarrativeViewers\" developed by KBase. ", + "laborHours": 2508.0, + "languages": [], + "name": "NarrativeViewers", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/NarrativeViewers", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Narrative_Method_&_App_Specifications.json b/agency-indexes/DoE/Narrative_Method_&_App_Specifications.json new file mode 100644 index 00000000..98f6efa1 --- /dev/null +++ b/agency-indexes/DoE/Narrative_Method_&_App_Specifications.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "This is a KBase repository for Narrative method and app specifications. These specifications are used to dynamically populate the set of narrative methods and apps that are available, in terms of both method & app functionality/behavior and display.", + "laborHours": 6992.0, + "languages": [], + "name": "Narrative Method & App Specifications", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/narrative_method_specs", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Narrative_Method_Store.json b/agency-indexes/DoE/Narrative_Method_Store.json new file mode 100644 index 00000000..4994e813 --- /dev/null +++ b/agency-indexes/DoE/Narrative_Method_Store.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-10", + "metadataLastUpdated": "2020-08-10" + }, + "description": "A KBase service for dynamically listing and accessing specifications and documentation for Narrative methods, apps, types, and categories of methods/apps. The Narrative Interface loads available methods/apps from this service.", + "laborHours": 12844.0, + "languages": [], + "name": "Narrative Method Store", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/narrative_method_store", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Narrative_Spawner.json b/agency-indexes/DoE/Narrative_Spawner.json new file mode 100644 index 00000000..7fb30858 --- /dev/null +++ b/agency-indexes/DoE/Narrative_Spawner.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "Narrative Spawner using Dockerhub's Configurable HTTP Proxy.", + "laborHours": 30.4, + "languages": [], + "name": "Narrative Spawner", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/narrative_spawner", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Narrows.json b/agency-indexes/DoE/Narrows.json new file mode 100644 index 00000000..115b35dd --- /dev/null +++ b/agency-indexes/DoE/Narrows.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2020-05-11" + }, + "description": "Narrows solves the discrete ordinates neutron transport equation using a neural network.", + "laborHours": 942.4, + "languages": [], + "name": "Narrows", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/narrows", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nation_Radiobiology_Archives_Distributed_Access.json b/agency-indexes/DoE/Nation_Radiobiology_Archives_Distributed_Access.json new file mode 100644 index 00000000..55b1a406 --- /dev/null +++ b/agency-indexes/DoE/Nation_Radiobiology_Archives_Distributed_Access.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-21", + "metadataLastUpdated": "2022-11-28" + }, + "description": "NRADA1.1 is a supplement to NRADA1.0. This version eliminates several bugs, and includes a few new features. The diskettes consist of a distributed subset of information representative of the extensive NRA databases and database access software maintained at the Pacific Northwest Laboratory which provide an introduction to the scope and style of the NRA Information Systems. Information in the NRA Summary, Inventory, and Bibliographic database is available upon request. Printed reports have been provided in the past. The completion of the NRADA1.1 is the realization of a long standing goal of the staff and advisory committee. Information may be easily distributed to the user in an electronic form which preserves the relationships between the various databases.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Nation Radiobiology Archives Distributed Access", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/National_Geothermal_Database.json b/agency-indexes/DoE/National_Geothermal_Database.json new file mode 100644 index 00000000..443380df --- /dev/null +++ b/agency-indexes/DoE/National_Geothermal_Database.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "THE NGDS IS A USER-FRIENDLY, WEB-BASED APPLICATION TO SUPPORT FINDING, VISUALIZING, MAPPING, AND ACQUISITION OF DATA BY END-USERS. THIS APPLICATION ALLOWS USERS TO DISCOVER AND ACCESS RESOURCES MADE AVAILABLE ACROSS ALL NGDS NODES, AND TO SEARCH FOR DATA ACROSS THE SYSTEM BASED ON TOPIC, LOCATION, AND OR OTHER CRITERIA. STANDARDIZED METADATA DESCRIBING EACH DATASET PROVIDES THE USER WITH THE INFORMATION NECESSARY TO DETERMINE THE UTILITY OF THAT DATASET FOR THEIR PURPOSES. GEOGRAPHIC DATASETS CAN BE VISUALIZED THROUGH A MAP INTERFACE THAT ALLOWS USERS TO INSPECT THE DETAILS OF INDIVIDUAL DATA POINTS (E.G. WELLS, TEMPERATURE MEASUREMENTS, ETC.) FROM PROPERLY FORMATTED DATASETS. IN ADDITION TO VISUALIZATION WITHIN THE APPLICATION, THE INTERFACE PROVIDES THE INFORMATION NECESSARY FOR USERS TO ACCESS THE DATA FROM OTHER APPLICATIONS.", + "laborHours": 8816.0, + "name": "National Geothermal Database", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ngds/documents", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Natural_Language_Processing_for_Biological_Relationship_Extraction.json b/agency-indexes/DoE/Natural_Language_Processing_for_Biological_Relationship_Extraction.json new file mode 100644 index 00000000..990fb818 --- /dev/null +++ b/agency-indexes/DoE/Natural_Language_Processing_for_Biological_Relationship_Extraction.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-07-23", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Code allows users to easily pull publications from PubMed, OSTI, and SCOPUS\u037e identify biological terms and extract\ntheir contexts from these papers\u037e and determine which terms are related to other terms using one of the eleven wrapped\nalgorithms", + "laborHours": 501.6, + "languages": [], + "name": "Natural Language Processing for Biological Relationship Extraction", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/biological_relationship_extraction", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NchooseK.json b/agency-indexes/DoE/NchooseK.json new file mode 100644 index 00000000..c4f312e9 --- /dev/null +++ b/agency-indexes/DoE/NchooseK.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-12", + "metadataLastUpdated": "2021-07-12" + }, + "description": "NchooseK represents a suite of software tools that seeks to unify and facilitate the exploitation of circuit-model quantum computers and quantum annealers. Numerous types of software will be included in this suite including compilers, preprocessors, optimizers, translators, run-time systems, support tools and scripts, and technology demonstrations.", + "laborHours": 0.0, + "languages": [], + "name": "NchooseK", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/NchooseK", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ncrc-client.json b/agency-indexes/DoE/Ncrc-client.json new file mode 100644 index 00000000..44e4477c --- /dev/null +++ b/agency-indexes/DoE/Ncrc-client.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2023-03-13" + }, + "description": "This is a simple wrapper script that will be used to enable the use of a two-factor authentication mechanism for downloading NCRC controlled codes through the popular \"Conda\" distribution mechanism.", + "laborHours": 0.0, + "languages": [], + "name": "Ncrc-client", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/ncrc-client", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Neighborhood_Adaptive_Tissues_for_Urban_Resilience_Futures__NATURF__V1.0.json b/agency-indexes/DoE/Neighborhood_Adaptive_Tissues_for_Urban_Resilience_Futures__NATURF__V1.0.json new file mode 100644 index 00000000..c399aae4 --- /dev/null +++ b/agency-indexes/DoE/Neighborhood_Adaptive_Tissues_for_Urban_Resilience_Futures__NATURF__V1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "allenmr@ornl.gov" + }, + "date": { + "created": "2024-05-31", + "metadataLastUpdated": "2024-06-05" + }, + "description": "This new version of NATURF, Version 1.0, builds on Version 0 by streamlining the code, decreasing its runtime and combining multiple modules into one convenient pip-installable package.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Neighborhood Adaptive Tissues for Urban Resilience Futures (NATURF) V1.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IMMM-SFA/naturf", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nek5000.json b/agency-indexes/DoE/Nek5000.json new file mode 100644 index 00000000..0c809366 --- /dev/null +++ b/agency-indexes/DoE/Nek5000.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Nek5000 is high-order spectral element code used for the simulation of incompressible fluid flow, MHD, and heat transfer in general three-dimensional domains that has been specifically developed for deployment on large-scale distributed memory parallel architectures. The code features state of the art matrix free multilevel iterative solvers coupled with stable second and third order operator-split stepping schemes. Scalable performance has been established onup to 32,000 processors and the overall quality of the algorithmic approach, implementation, and performance were recognized with the award of the Gordon Bell Prize in 1999.", + "laborHours": 0.0, + "languages": [ + "f77/C" + ], + "name": "Nek5000", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/Nek5000/Nek5000/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Nek5000/Nek5000", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nekton_Interaction_Monitoring_System.json b/agency-indexes/DoE/Nekton_Interaction_Monitoring_System.json new file mode 100644 index 00000000..c1c4f6e4 --- /dev/null +++ b/agency-indexes/DoE/Nekton_Interaction_Monitoring_System.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software provides a real-time processing system for sonar to detect and track animals, and to extract water column biomass statistics in order to facilitate continuous monitoring of an underwater environment. The Nekton Interaction Monitoring System (NIMS) extracts and archives tracking and backscatter statistics data from a real-time stream of data from a sonar device. NIMS also sends real-time tracking messages over the network that can be used by other systems to generate other metrics or to trigger instruments such as an optical video camera. A web-based user interface provides remote monitoring and control. NIMS currently supports three popular sonar devices: M3 multi-beam sonar (Kongsberg), EK60 split-beam echo-sounder (Simrad) and BlueView acoustic camera (Teledyne).", + "laborHours": 164707.2, + "name": "Nekton Interaction Monitoring System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/nims/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/nims", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nessus_Visualization.json b/agency-indexes/DoE/Nessus_Visualization.json new file mode 100644 index 00000000..c5c27946 --- /dev/null +++ b/agency-indexes/DoE/Nessus_Visualization.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "NV is a visualization tool for exploring vulnerabilities within a network. The data is created with a vulnerability assessment tool, such as Nessus (http://www.tenable.com/products/nessus).", + "laborHours": 270879.2, + "name": "Nessus Visualization", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/nv", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NetCDFFile_v.1.0.json b/agency-indexes/DoE/NetCDFFile_v.1.0.json new file mode 100644 index 00000000..7392e57b --- /dev/null +++ b/agency-indexes/DoE/NetCDFFile_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-19" + }, + "description": "SAND2024-02969O\nThe NetCDFFile provides a generic interface to NetCDF and/or PnetCDF library calls, allowing the user to write generic code to read and write from NetCDF files. The NetCDFFile library requires a C++20 compliant compiler as well as NetCDF and PnetCDF libraries installed on the machine. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "NetCDFFile v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NetMOD.json b/agency-indexes/DoE/NetMOD.json new file mode 100644 index 00000000..e5e237cc --- /dev/null +++ b/agency-indexes/DoE/NetMOD.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "NetMOD is a tool to model the performance of global ground-based explosion monitoring systems. The initial version of the software supports the simulation of seismic detection capability. The tool provides a user interface to execute simulations based upon a hypothetical definition of the monitoring system configuration, geophysical properties of the Earth, and detection analysis criteria.", + "laborHours": 15.2, + "languages": [ + "Java" + ], + "name": "NetMOD", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/netmod", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Net_Test.json b/agency-indexes/DoE/Net_Test.json new file mode 100644 index 00000000..03a52462 --- /dev/null +++ b/agency-indexes/DoE/Net_Test.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "Nettest is a secure, real-time network utility. The nettest framework is designed to incorporate existing and new network tests, and be run as a daemon or an interactive process. Requests for network tests are received via a SSL connection or the user interface and are authorized using a ACL list (in the future authorization using Akenti will also be supported). For tests that require coordination between the two ends of the test, Nettest establishes an SSL connection to accomplish this coordination. A test between two remote computers can be requested via the user interlace if the Nettest daemon is running on both remote machines and the user is authorized. Authorization for the test is through a chain of trust estabtished by the nettest daemons. Nettest is responsible for determining if the test request is authorized, but it does nothing further to secure the test once the test is running. Currently the Nettest framework incorporates lperf-vl.2, a simple ping type test, and a tuned TCP test that uses a given required throughput and ping results to determine the round trip time to set a buffer size (based on the delay bandwidth product) and then performs an iperf TCP throughput test. Additional network test tools can be integrated into the Nettest framework in the future.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Net Test", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Netfabb_to_IFF_XML_converter.json b/agency-indexes/DoE/Netfabb_to_IFF_XML_converter.json new file mode 100644 index 00000000..f0073767 --- /dev/null +++ b/agency-indexes/DoE/Netfabb_to_IFF_XML_converter.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "This software converts XML files created by the Netfabb software to the XML format used by the Intelligent Feed Forward (IFF) tools developed at LLNL.", + "laborHours": 0.0, + "languages": [], + "name": "Netfabb to IFF XML converter", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CLDruzgalski/AM_fileConverters", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Netmelt_v._1.0.json b/agency-indexes/DoE/Netmelt_v._1.0.json new file mode 100644 index 00000000..d9b1d558 --- /dev/null +++ b/agency-indexes/DoE/Netmelt_v._1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-10", + "metadataLastUpdated": "2020-09-08" + }, + "description": "System assessments typically yield large quantities of data from disparate sources for an analyst to scrutinize for issues. Netmeld is used to parse input from different file formats, store the data in a common format, allow users to easily query it, and enable analysts to tie different analysis tools together using a common back-end. ", + "laborHours": 10868.0, + "languages": [ + "C++", + "Python", + "SQL" + ], + "name": "Netmelt v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/netmeld/netmeld", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NetworkFoX.json b/agency-indexes/DoE/NetworkFoX.json new file mode 100644 index 00000000..afc36d0d --- /dev/null +++ b/agency-indexes/DoE/NetworkFoX.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-06-16", + "metadataLastUpdated": "2022-06-16" + }, + "description": "NetworkFoX is a fork of graphkit, which adds the ability to do computations on top of NetworkX graphs. It stands for Network F of X.", + "laborHours": 0.0, + "languages": [], + "name": "NetworkFoX", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slac-lcls/networkfox", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Network_Architecture_Verification_&_Validation_Tool.json b/agency-indexes/DoE/Network_Architecture_Verification_&_Validation_Tool.json new file mode 100644 index 00000000..ea93e86d --- /dev/null +++ b/agency-indexes/DoE/Network_Architecture_Verification_&_Validation_Tool.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-09-01", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The NAVV Tool is an automation of Linux commands run Zeek IDS software on a packet capture to create a Microsoft Excel spreadsheet table breaking down network traffic observed. The tool automates the Zeek software analysis, the collation of logs, and then the dissection of the Conn.log and DNS.logs to create a summary table within a Excel. This spreadsheet can then be updated with network segments using CIDR formatting and labels along with inventory information including name and IP address. Using the tool again will integrate these label and color coding into the existing analysis table to aid in conducting an evaluation of the network traffic.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Network Architecture Verification & Validation Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/NAVV", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git", + "version": "3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Network_Collapse.json b/agency-indexes/DoE/Network_Collapse.json new file mode 100644 index 00000000..254ba65e --- /dev/null +++ b/agency-indexes/DoE/Network_Collapse.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Network Collapse is a STEM education VR game for grade 6-12 students to interactively learn about how information is transmitted and protected on networks. Players assume the role of a router and must transfer incoming data packets to the correct outgoing pathway without losing too many. Eventually the player must also recognize a cyber-attack and turn on the best tool to protect their network. Six levels introduce core basic ideas with increasing complexity in game play to maintain engagement while learning new ideas. The game is designed to run on the standalone VR headset, Oculus Go.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "Network Collapse", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Network_Defense_Workforce_Development_System.json b/agency-indexes/DoE/Network_Defense_Workforce_Development_System.json new file mode 100644 index 00000000..fdf33863 --- /dev/null +++ b/agency-indexes/DoE/Network_Defense_Workforce_Development_System.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The software implements the methodology of cybersecurity training architecture and is leveraged to build a turn-key based simulated cyberattack game in which the player assumes the facility manager's role and must defend the OT network from adaptive cyberattacks by directly configuring the physical network environment and implementing security policies.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Network Defense Workforce Development System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Network_Traffic_Generator_for_Low-rate_Small_Network_Equipment_Software.json b/agency-indexes/DoE/Network_Traffic_Generator_for_Low-rate_Small_Network_Equipment_Software.json new file mode 100644 index 00000000..89e5581f --- /dev/null +++ b/agency-indexes/DoE/Network_Traffic_Generator_for_Low-rate_Small_Network_Equipment_Software.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Application that uses the Python low-level socket interface to pass network traffic between devices on the local side of a NAT router and the WAN side of the NAT router. This application is designed to generate traffic that complies with the Energy Star Small Network Equipment Test Method.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Python 2.7" + ], + "name": "Network Traffic Generator for Low-rate Small Network Equipment Software", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Network_performance_analysis_for_HPC_datacenters__net_perf__v1.0.json b/agency-indexes/DoE/Network_performance_analysis_for_HPC_datacenters__net_perf__v1.0.json new file mode 100644 index 00000000..d3292b9a --- /dev/null +++ b/agency-indexes/DoE/Network_performance_analysis_for_HPC_datacenters__net_perf__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-24", + "metadataLastUpdated": "2024-07-31" + }, + "description": "The software has two main features: (1) identify data movement trends in HPC data centers that use network flow monitoring (2) analyze the performance of individual data flows under the existing data movement management strategy and identify performance bottlenecks that impede timely data availability for science workflows. Its main advantage is that it is tailored for HPC network traffic by considering HPC data movement management intricacies.", + "laborHours": 349.6, + "languages": [], + "name": "Network performance analysis for HPC datacenters (net_perf) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/annna-gian/nersc_net_perf.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Networked_Microgrids_Optimization.json b/agency-indexes/DoE/Networked_Microgrids_Optimization.json new file mode 100644 index 00000000..9ae94af9 --- /dev/null +++ b/agency-indexes/DoE/Networked_Microgrids_Optimization.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "cheny4@ornl.gov" + }, + "date": { + "created": "2024-12-12", + "metadataLastUpdated": "2024-12-13" + }, + "description": "This project is mainly about the operation optimization of three networked microgrids (MG), including centralized optimization and distributed optimization. The alternating direction method of multipliers (ADMM) algorithm is used for distributed optimization. In the distribution network considered here, there is a Distribution Management system (DMS) as the system coordinator and several networked microgrids. In grid-connected mode, power could be imported or exported at the distribution substation bus according to the utility rate, and the exchanged power at point of common coupling (PCC) of any microgrid has a limitation. In islanded mode, the power\nimports/exports at the distribution substation are zero. In both grid-connected and islanded mode, the distribution substation is taken as a slack bus with fixed voltage magnitude.", + "homepageURL": "https://code.ornl.gov/cheny4/networked-microgrids-optimization", + "laborHours": 12372.8, + "languages": [ + "Python" + ], + "name": "Networked Microgrids Optimization", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/cheny4/networked-microgrids-optimization", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/NeuralRW-Loihi:_Spiking_Discrete_Time_Markov_Chain_Simulator_for_Intel_Loihi_v.json b/agency-indexes/DoE/NeuralRW-Loihi:_Spiking_Discrete_Time_Markov_Chain_Simulator_for_Intel_Loihi_v.json new file mode 100644 index 00000000..cc0d0856 --- /dev/null +++ b/agency-indexes/DoE/NeuralRW-Loihi:_Spiking_Discrete_Time_Markov_Chain_Simulator_for_Intel_Loihi_v.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2024-01302O\nNeuralRW-Loihi: Spiking Discrete Time Markov Chain Simulator for Intel Loihi is a neuromorphic script that generates a random walk simulation of a discrete-time Markov Chain for the Loihi neuromorphic hardware. The code was used to produce the paper \"Neuromorphic scaling advantages for energy-efficient random walk computations\" by Smith et al., 2021. It was published in Nature Electronics. \n\nThe software provides code for implementing the discrete time Markov chain random walks on Intel's Loihi Neuromorphic platform. In addition, it provides an example problem through a mini app.", + "laborHours": 1352.8, + "languages": [ + "Python" + ], + "name": "NeuralRW-Loihi: Spiking Discrete Time Markov Chain Simulator for Intel Loihi v", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Neural-Random-Walker", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Neural_Network_Code_MATLAB.json b/agency-indexes/DoE/Neural_Network_Code_MATLAB.json new file mode 100644 index 00000000..0ab15165 --- /dev/null +++ b/agency-indexes/DoE/Neural_Network_Code_MATLAB.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-10", + "metadataLastUpdated": "2022-10-10" + }, + "description": "SAND2022-12606 O\nNeural Network Code MATLAB reads in an excel file, processes the data, trains a neural network, and tests the neural network. The code generates predictions of diffusion constants based on the data in the excel file. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov//", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Neural Network Code MATLAB", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov//", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov//", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Neural_Network_Export_Package__nexport__v0.1.0.json b/agency-indexes/DoE/Neural_Network_Export_Package__nexport__v0.1.0.json new file mode 100644 index 00000000..96132351 --- /dev/null +++ b/agency-indexes/DoE/Neural_Network_Export_Package__nexport__v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "nexport is a lightweight python 3 package which enables neural network developers to export the weights and biases of trained networks to useful file types. It provides I/O support for applications which require specific data types for instantiating neural networks in various inference environments. It was initially developed to support exporting to the data structure used by 'inference-engine', a Fortran inference package.", + "laborHours": 471.2, + "languages": [], + "name": "Neural Network Export Package (nexport) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/nexport", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Neural_Networks_for_Supercapacitor_Modeling.json b/agency-indexes/DoE/Neural_Networks_for_Supercapacitor_Modeling.json new file mode 100644 index 00000000..00146f55 --- /dev/null +++ b/agency-indexes/DoE/Neural_Networks_for_Supercapacitor_Modeling.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-04-19", + "metadataLastUpdated": "2022-04-19" + }, + "description": "This software implements a one-dimensional model of a supercapacitor and calibrates it to experimental data. A system of coupled partial differential equation models the salt concentration and the ionic and electronic potentials. The term in the equation modeling the capacitance contains a neural network, whose parameters are optimized to fit the provided experimental data. The software is written in python using the open-source library JAX to calculate the gradients needed for the optimization.", + "laborHours": 0.0, + "languages": [], + "name": "Neural Networks for Supercapacitor Modeling", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/neuralcap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.01" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Neural_Phase_Simulation.json b/agency-indexes/DoE/Neural_Phase_Simulation.json new file mode 100644 index 00000000..20366595 --- /dev/null +++ b/agency-indexes/DoE/Neural_Phase_Simulation.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-11-23", + "metadataLastUpdated": "2022-11-23" + }, + "description": "The Neural Phase Simulation (NPS) is a package of codes for simulating microstructure evolution and accelerated molecular dynamics with deep neural-networks based surrogate models. NPS is designed to offer quantitatively accurate and computationally efficient simulation capabilities by leveraging modern machine-learning techniques. The primary intended use cases of NPS are training neural network surrogate models, though performing simulations on a single node is also supported. The NPS surrogate models can be trained from ground truth simulation methods, which are supposed to be accurate but expensive, such as molecular dynamics, phase field methods, kinetic Monte Carlo and discrete dislocation dynamics.", + "laborHours": 0.0, + "languages": [], + "name": "Neural Phase Simulation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Critical-Materials-Institute/NPS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NeuroCoreX:_Brain-Inspired_Computing_from_Code_to_Circuit.json b/agency-indexes/DoE/NeuroCoreX:_Brain-Inspired_Computing_from_Code_to_Circuit.json new file mode 100644 index 00000000..780216f7 --- /dev/null +++ b/agency-indexes/DoE/NeuroCoreX:_Brain-Inspired_Computing_from_Code_to_Circuit.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "gautama@ornl.gov" + }, + "date": { + "created": "2025-03-26", + "metadataLastUpdated": "2025-03-26" + }, + "description": "NeuroCoreX is an open-source codebase that enables the implementation of brain-inspired, energy-efficient neuromorphic computing models on FPGA hardware. Designed to support real-time learning, all-to-all neural connectivity, and flexible network architectures, NeuroCoreX offers a hands-on, accessible platform for exploring biologically inspired models of neural computation. It empowers researchers, students, and developers to implement and experiment with adaptive systems\u2014bringing the power of neuromorphic computing to a broader community through a low-cost, scalable, and reconfigurable framework.", + "laborHours": 0.0, + "languages": [ + "VHDL" + ], + "name": "NeuroCoreX: Brain-Inspired Computing from Code to Circuit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/NeuroCoreX", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Neurodata_Extensions_Catalog__NDX_Catalog__v1.0.0.json b/agency-indexes/DoE/Neurodata_Extensions_Catalog__NDX_Catalog__v1.0.0.json new file mode 100644 index 00000000..d27c1ee0 --- /dev/null +++ b/agency-indexes/DoE/Neurodata_Extensions_Catalog__NDX_Catalog__v1.0.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-01", + "metadataLastUpdated": "2021-03-01" + }, + "description": "The Neurodata Extensions Catalog (NDX Catalog) is a novel web archive and associated software tools that enable users to easily create, search for, test, review, and install extensions to the Neurodata Without Borders (NWB) data standard for neurophysiology. 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The software implements the neural circuit itself and a demonstration application where the MNIST dataset (a standard test problem) is used to train a neural network.", + "laborHours": 0.0, + "languages": [], + "name": "Neuromorphic Backpropagation Algorithm Software", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/spikingBackprop", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Neurons_to_Algorithms.json b/agency-indexes/DoE/Neurons_to_Algorithms.json new file mode 100644 index 00000000..40f20331 --- /dev/null +++ b/agency-indexes/DoE/Neurons_to_Algorithms.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "A framework for modeling and simulating biological neural systems", + "laborHours": 111902.4, + "languages": [ + "Java", + "C++", + "C", + "Python" + ], + "name": "Neurons to Algorithms", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/n2a", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Neutron_Gamma_LAMP_Software_version_1.json b/agency-indexes/DoE/Neutron_Gamma_LAMP_Software_version_1.json new file mode 100644 index 00000000..4a529160 --- /dev/null +++ b/agency-indexes/DoE/Neutron_Gamma_LAMP_Software_version_1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-05", + "metadataLastUpdated": "2019-12-05" + }, + "description": "The Localization and Mapping Platform (LAMP) software fuses radiation and contextual data to produce 3-D maps that locate and identify gamma-ray emitting sources in complex environments. It enables data collection, fusion, and processing onboard the LAMP system in handheld configurations, and enables near-real-time 3-D mapping from onboard an unmanned aerial system (UAS). This software enables a real-time 3-D gamma-ray mapping capability that is not available commercially. This software disclosure is for a new simultaneous gamma-ray and neutron mapping software update to the original LAMP software.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1124.8, + "languages": [], + "name": "Neutron Gamma LAMP Software version 1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/New_pair_style_for_molecular_dynamics_package_LAMMPS.json b/agency-indexes/DoE/New_pair_style_for_molecular_dynamics_package_LAMMPS.json new file mode 100644 index 00000000..61ea4978 --- /dev/null +++ b/agency-indexes/DoE/New_pair_style_for_molecular_dynamics_package_LAMMPS.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-05" + }, + "description": "This pair style will enable molecular dynamics simulations of hydrogen interaction with Fe-C steels. No such simulations are possible without such a pair style. This is significant because Fe-C steels are the most commonly used steels and improving their resistance to hydrogen embrittlement has attracted wide interests. SAND2020-12230 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1281025.6, + "languages": [ + "C++" + ], + "name": "New pair style for molecular dynamics package LAMMPS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lammps/lammps", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Next-Cycle_Optimal_Fuel_Control_for_Cycle-to-Cycle_Variability_Reduction_in_EGR-Diluted_Combustion.json b/agency-indexes/DoE/Next-Cycle_Optimal_Fuel_Control_for_Cycle-to-Cycle_Variability_Reduction_in_EGR-Diluted_Combustion.json new file mode 100644 index 00000000..f5226802 --- /dev/null +++ b/agency-indexes/DoE/Next-Cycle_Optimal_Fuel_Control_for_Cycle-to-Cycle_Variability_Reduction_in_EGR-Diluted_Combustion.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "maldonadopbp@ornl.gov" + }, + "date": { + "created": "2021-08-29", + "metadataLastUpdated": "2021-08-29" + }, + "description": "In this simulation study, cycle-to-cycle fuel control was used to reduce CCV by injecting additional fuel in operating conditions with sporadic misfires and partial burns. An optimal control policy was proposed that utilizes 1) a physics-based model that tracks in-cylinder gas composition and 2) a one-step-ahead prediction of the combustion efficiency based on a kernel density estimator. The optimal solution, however, presents a tradeoff between the reduction in combustion CCV and the increase in fuel injection quantity required to stabilize the charge. Such a tradeoff can be ad- just by a single parameter embedded in the cost function.", + "homepageURL": "https://codeocean.com/capsule/8130780/tree", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Next-Cycle Optimal Fuel Control for Cycle-to-Cycle Variability Reduction in EGR-Diluted Combustion", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://codeocean.com/capsule/8130780/tree", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Next_ALarM_System.json b/agency-indexes/DoE/Next_ALarM_System.json new file mode 100644 index 00000000..948b37e3 --- /dev/null +++ b/agency-indexes/DoE/Next_ALarM_System.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-07", + "metadataLastUpdated": "2022-07-07" + }, + "description": "NALMS is an alarm system application designed for availability, integrability, and extensibility. The NALMS development was driven by SLAC's efforts to replace the Alarm Handler, due for deprecation as a Motif-based application, and to introduce process improvements addressing hierarchy implementation overhead, limited operator engagement, and operator display integration.", + "laborHours": 0.0, + "languages": [], + "name": "Next ALarM System", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/nalms/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/nalms", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Next_Generation_Resource_Manager_Protoryping_Environment.json b/agency-indexes/DoE/Next_Generation_Resource_Manager_Protoryping_Environment.json new file mode 100644 index 00000000..90394a41 --- /dev/null +++ b/agency-indexes/DoE/Next_Generation_Resource_Manager_Protoryping_Environment.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ngrm-proto is a package of proff-of-concept utilities intended to demonstrate concepts that will be developed full in the FLUX resource manager.", + "laborHours": 0.0, + "name": "Next Generation Resource Manager Protoryping Environment", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/ngrm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NimbleSM.json b/agency-indexes/DoE/NimbleSM.json new file mode 100644 index 00000000..aa48da19 --- /dev/null +++ b/agency-indexes/DoE/NimbleSM.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-06-20", + "metadataLastUpdated": "2024-09-18" + }, + "description": "NimbleSM is a Lagrangian finite-element code for solid mechanics. Its primary application is the solution of mechanics problems on nonuniform, three-dimensional meshes using either explicit transient dynamic or implicit quasi-static time integration. Additional features include multiscale modeling and the simulation of contact. The NimbleSM code base is designed for performance portability across varying hardware architectures.", + "laborHours": 19729.6, + "languages": [ + "C++", + "Shell", + "C", + "Gnuplot", + "CMake", + "Python" + ], + "name": "NimbleSM", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/nimblesm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nitrogen_Fluid_Properties.json b/agency-indexes/DoE/Nitrogen_Fluid_Properties.json new file mode 100644 index 00000000..fd9de645 --- /dev/null +++ b/agency-indexes/DoE/Nitrogen_Fluid_Properties.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-08-30" + }, + "description": "This software is used to compute numerous properties for nitrogen.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Nitrogen Fluid Properties", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/nitrogen", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NoSQL_BigData_Project.json b/agency-indexes/DoE/NoSQL_BigData_Project.json new file mode 100644 index 00000000..8bdee378 --- /dev/null +++ b/agency-indexes/DoE/NoSQL_BigData_Project.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-09-28", + "metadataLastUpdated": "2019-03-22" + }, + "description": "The framework stores HEP event data into a database and provides fast and scalable access to the data for distributed Python- and numpy-based analysis.", + "homepageURL": "http://cdcvs.fnal.gov/projects/nosql-ldrd", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "NoSQL BigData Project", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://cdcvs.fnal.gov/projects/nosql-ldrd", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Noble-Lab_crema.json b/agency-indexes/DoE/Noble-Lab_crema.json new file mode 100644 index 00000000..83ee62c7 --- /dev/null +++ b/agency-indexes/DoE/Noble-Lab_crema.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Confidence Estimation for Mass Spectrometry Proteomics. Crema is an open-source Python tool that estimates the false discovery rate (FDR) of a set of peptide-spectrum matches\nthat result from proteomics data analysis. Crema implements standard FDR estimation methods that are widely used within\nthe field. This package is meant to be simple, easy to use, stand-along, and easy to maintain.", + "laborHours": 0.0, + "languages": [], + "name": "Noble-Lab/crema", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Noble-Lab/crema", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nodeman:_A_Node_Management_Tool_For_Hpc_Clusters.json b/agency-indexes/DoE/Nodeman:_A_Node_Management_Tool_For_Hpc_Clusters.json new file mode 100644 index 00000000..21040570 --- /dev/null +++ b/agency-indexes/DoE/Nodeman:_A_Node_Management_Tool_For_Hpc_Clusters.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-02-20", + "metadataLastUpdated": "2025-02-20" + }, + "description": "NodeMan is a command line tool to manage nodes in an HPC cluster. At it's core, it is an extensible framework composed of bash scripting and GNU parallel. HPC System Administrator will find it useful in that it encapsulates desired functions and allows them to be assembled in a way familiar to administrators - through pipes. In fact, NodeMan functions can work with common command line tools as long as they use stdin/stdout. System Administrators can construct moderately complex logic and filtering on a compact command line that would normally require a substantial shell script. In the spirit of clush and pdsh, it is able to run commands remotely on nodes. Additionally, NodeMan is more flexible. For example, it can interact with IPMI and naturally processes node lists for orchestrating different tools. The library of useful pre-built functions is growing. System administrators can easily create new functions and make it their own.", + "laborHours": 440.8, + "languages": [], + "name": "Nodeman: A Node Management Tool For Hpc Clusters", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/nodeman", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Non-Routine_Event_Detection_and_Adjustment__NRE__v1.json b/agency-indexes/DoE/Non-Routine_Event_Detection_and_Adjustment__NRE__v1.json new file mode 100644 index 00000000..73fd1f2d --- /dev/null +++ b/agency-indexes/DoE/Non-Routine_Event_Detection_and_Adjustment__NRE__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2019-06-26" + }, + "description": "The non-routine event (NRE) detection and adjustment module provides algorithms to detect and to adjust changes in energy use that are not attributable to installed efficiency measures, and not accounted for in the baseline model's independent variables. The detection algorithm is based on statistical change point algorithm and the adjustment uses a data driven approach to quantify the changes in the energy use that are induced by the NRE.", + "laborHours": 653.6, + "languages": [], + "name": "Non-Routine Event Detection and Adjustment (NRE) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/nre", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nonlinear_manifold_reduced_order_model.json b/agency-indexes/DoE/Nonlinear_manifold_reduced_order_model.json new file mode 100644 index 00000000..a7e7f596 --- /dev/null +++ b/agency-indexes/DoE/Nonlinear_manifold_reduced_order_model.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-04", + "metadataLastUpdated": "2024-09-19" + }, + "description": "Traditional linear subspace reduced order models (LS-ROMs) are able to accelerate physical simulations\nin which the intrinsic solution space falls into a subspace with a small dimension, i.e., the solution space\nhas a small Kolmogorov n-width. However, for physical phenomena not of this type, e.g., any advection-dominated\nflow phenomena such as in traffic flow, atmospheric flows, and air flow over vehicles, a lowdimensional\nlinear subspace poorly approximates the solution. To address cases such as these, we have\ndeveloped a fast and accurate physics-informed neural network ROM, namely nonlinear manifold ROM\n(NM-ROM), which can better approximate high-fidelity model solutions with a smaller latent space\ndimension than the LS-ROMs. Our software takes advantage of the existing numerical methods that are\nused to solve the corresponding full order models. The efficiency is achieved by developing a hyper-reduction\ntechnique in the context of the NM-ROM. Numerical results show that neural networks can learn\na more efficient latent space representation on advection-dominated data from 1D and 2D Burgers'\nequations. A speedup of up to 2.6 for 1D Burgers' and a speedup of 11.7 for 2D Burgers' equations are\nachieved with an appropriate treatment of the nonlinear terms through a hyper-reduction technique.", + "laborHours": 20170.4, + "languages": [], + "name": "Nonlinear manifold reduced order model", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/NM-ROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Norma_v.0.1.json b/agency-indexes/DoE/Norma_v.0.1.json new file mode 100644 index 00000000..aa6a5371 --- /dev/null +++ b/agency-indexes/DoE/Norma_v.0.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00731O\nNorma is a software tool that simplifies the testing of algorithms and concepts for coupling and multiphysics, with a focus on solid mechanics and heat conduction. It uses the Finite Element Method to allow researchers to explore and validate new approaches in these domains. Norma provides a flexible and efficient platform for computational experimentation and development. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 8876.8, + "languages": [ + "Julia" + ], + "name": "Norma v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Norma.jl", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Normalized_Elution_Time_Prediction_Utility.json b/agency-indexes/DoE/Normalized_Elution_Time_Prediction_Utility.json new file mode 100644 index 00000000..e2bc6f4f --- /dev/null +++ b/agency-indexes/DoE/Normalized_Elution_Time_Prediction_Utility.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This program is used to compute the predicted normalized elution time (NET) for a list of peptide sequences. It includes the Kangas/Petritis neural network trained model, the Krokhin hydrophobicity model, and the Mant hydrophobicity model. In addition, it can compute the predicted strong cation exchange (SCX) fraction (on a 0 to 1 scale) in which a given peptide will appear.", + "laborHours": 7296.0, + "name": "Normalized Elution Time Prediction Utility", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Protein-Digestion-Simulator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Notify_Validator.json b/agency-indexes/DoE/Notify_Validator.json new file mode 100644 index 00000000..274fd1c6 --- /dev/null +++ b/agency-indexes/DoE/Notify_Validator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "The Notify Validator software represents a web service that supports implementers of the COAR Notify protocol.", + "laborHours": 0.0, + "languages": [], + "name": "Notify Validator", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jepowell-LANL/coar-notify-validator-inbox", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/NuDustC++.json b/agency-indexes/DoE/NuDustC++.json new file mode 100644 index 00000000..38ab9625 --- /dev/null +++ b/agency-indexes/DoE/NuDustC++.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "NuDustc++ is a nucleating and sputtering dust code. It takes in the temperature-density profiles, abundance data, and chemistry network. It creates a binned size distribution from user input data to track certain grain sizes. NuDustc++ loads the data and calculates where and when a shock is detected in the input data. Using a runge-Kutta DoPri 5 integrator, it calculates nucleation and growth of grains by solving a system of coupled non-linear ODEs. It calculates sputtering based on the presence or lack of a shock by either integrating over energy or summing up the sputtering yield contributions per gas species. It is used to determine and track dust grain nucleation, growth, and erosion (sputtering) in gaseous systems to determine characteristics of the produced grain distribution.", + "laborHours": 0.0, + "languages": [], + "name": "NuDustC++", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/nuDustC", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nuclear_Canister_Corrosion_Detection.json b/agency-indexes/DoE/Nuclear_Canister_Corrosion_Detection.json new file mode 100644 index 00000000..d0fc7d58 --- /dev/null +++ b/agency-indexes/DoE/Nuclear_Canister_Corrosion_Detection.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The software titled \"nccd\" is used for running residual neural networks (ResNets) on images of nuclear canisters. The software provides only the code for the implementation (based on the fastai library), but it does not share the image data. The compute code allows the use of residual nets (and more generally of other deep learning models) for classifying images from nuclear canisters as corroded. or intact. An image is considered to be corroded if it contains pitting or stress corrosion cracks. The code trains ResNets on image tiles extracted from original images from nuclear canisters, and then implements a classification rule, which can be applied to a validation set to decide if each original image is corroded or intact. The software automates the process of using images taken from nuclear canisters to detect corrosion. It provides also scope for future research directions on the basis of the existing research and code.", + "laborHours": 486.4, + "languages": [ + "Python (v3.6 onwards)" + ], + "name": "Nuclear Canister Corrosion Detection", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/papamarkou/nccd", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nuclear_Criticality_Detector_Mark-III.json b/agency-indexes/DoE/Nuclear_Criticality_Detector_Mark-III.json new file mode 100644 index 00000000..f6ed62ad --- /dev/null +++ b/agency-indexes/DoE/Nuclear_Criticality_Detector_Mark-III.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is an improved system for detecting a nuclear criticality event at RPL (325) building, named the Mark III Nuclear Criticality Detector (NCD), replacing the 40 year old Mark II. The materials are primarily schematic diagrams and other technical information that is of interest to a commercial manufacturer of similar equipment.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Nuclear Criticality Detector Mark-III", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nuclear_Data_Access_Tool_Kit_NDATK.json b/agency-indexes/DoE/Nuclear_Data_Access_Tool_Kit_NDATK.json new file mode 100644 index 00000000..51018d55 --- /dev/null +++ b/agency-indexes/DoE/Nuclear_Data_Access_Tool_Kit_NDATK.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The Nuclear Data Access Tool Kit (NDATK) is a C++ API that provides continuous energy neutron and photon libraries corresponding to multigroup neutron libraries. It uses libraries named to match Nuclear Data Interface (NDI) libraries and tells the host code where the continuous energy data is. Like NDI, it includes multi-temperature data.", + "laborHours": 0.0, + "languages": [], + "name": "Nuclear Data Access Tool Kit NDATK", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/NDATK", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nuclear_Data_Specifications,_Utilities,_and_Libraries.json b/agency-indexes/DoE/Nuclear_Data_Specifications,_Utilities,_and_Libraries.json new file mode 100644 index 00000000..af1332b4 --- /dev/null +++ b/agency-indexes/DoE/Nuclear_Data_Specifications,_Utilities,_and_Libraries.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-16" + }, + "description": "Nuclear data provides descriptions of physical processes used by numerical simulation codes throughout the world. The data is provided in specified formats. Knowledge of the formats and what it represents is important for those that produce and read the data. Nuclear data is typically processed and made available to simulation codes at various temperatures applicable to the general class of problems that the simulation code is designed to model. These libraries are historically pre-processed and made available to the world. The libraries are based on fundamental physical data and are used by scientists and researchers.", + "laborHours": 820.8, + "languages": [ + "C++", + "Fortran", + "Python", + "C++", + "LaTex", + "Python" + ], + "name": "Nuclear Data Specifications, Utilities, and Libraries", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NuclearData/ACEFormat", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nuclear_Fallout_Super-Droplet_Method.json b/agency-indexes/DoE/Nuclear_Fallout_Super-Droplet_Method.json new file mode 100644 index 00000000..be146119 --- /dev/null +++ b/agency-indexes/DoE/Nuclear_Fallout_Super-Droplet_Method.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-09-09", + "metadataLastUpdated": "2022-09-12" + }, + "description": "Super-droplet method applied to modeling the formation and evolution of fallout post-detonation of a nuclear airburst.", + "laborHours": 0.0, + "languages": [], + "name": "Nuclear Fallout Super-Droplet Method", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/NFSDM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nuclear_Integrated_Hydrogen_Production_Analysis_Tool.json b/agency-indexes/DoE/Nuclear_Integrated_Hydrogen_Production_Analysis_Tool.json new file mode 100644 index 00000000..05e02a78 --- /dev/null +++ b/agency-indexes/DoE/Nuclear_Integrated_Hydrogen_Production_Analysis_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "This is an Excel-based time-independent discount cash flow calculator for LWR-HTSE systems. The tool incorporates (1) discounted cash flow and levelized cost of hydrogen (LCOH) analysis, (2) sensitivity analysis with respect to select financial performance metrics with output \u2018tornado\u2019 charts, (3) profitability analysis represented by heat maps using the two most sensitive parameters, (4) electricity versus hydrogen production preference analysis by comparing change in net present value (?NPV) between NPP-HTSE and business-as-usual electricity production for the grid, and (5) competitiveness analysis by comparing the calculated LCOH for NPP-HTSE with that of steam methane reforming, which is the conventional process to produce hydrogen.", + "laborHours": 0.0, + "languages": [ + "Visual Basic" + ], + "name": "Nuclear Integrated Hydrogen Production Analysis Tool", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/NIHPA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nudging_Technique_for_Robust_Meshing_of_Intersecting_Polygons_in_Discrete_Fracture_Networks_v1.x.json b/agency-indexes/DoE/Nudging_Technique_for_Robust_Meshing_of_Intersecting_Polygons_in_Discrete_Fracture_Networks_v1.x.json new file mode 100644 index 00000000..2b0cbc2e --- /dev/null +++ b/agency-indexes/DoE/Nudging_Technique_for_Robust_Meshing_of_Intersecting_Polygons_in_Discrete_Fracture_Networks_v1.x.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2021-09-10" + }, + "description": "Understanding flow and transport in fractured rock is an important national priority, which includes environmental protection, resource development, infrastructure development, and seismic risk. In energy resources formations, such as tight sandstone formations, shale formations and coal beds with very low permeability, as well as nuclear waste repository sites, networks of fractures are typically the principal pathways for fluid and gas flow and contaminant transport. A Discrete Fracture Network (DFN) approach is an advanced method to mimic discrete pathways for fluid flow through a fractured rock mass. DFN models represent deterministically and stochastically defined fractures observed at subsurface media and to predict flow and transport for individual sites. In order to achieve accurate flow and transport predictions, a high-quality computational mesh is required. The geometric features (fractures, fracture intersections, spaces between fracture intersections, etc.) that must be resolved in a generated DFN typically span a wide range of spatial scales and make the efficient automated generation of high-quality meshes a challenge. To deal with these challenges, many approaches deform the DFN to align its features with a mesh. The proposed nudging technique allows for the production of a high-quality conforming Delaunay triangulation of a DFN without significant modification of fractures location, size, orientation, and topology. The nudging technique is based on the feature rejection algorithm for meshing (FRAM). Using FRAM, the DFN mesh is constructed so that all the features in the network, e.g., length of intersections between fractures and distance between lines of intersection of a fracture are equal to or larger than a user-defined minimum length scale, h. FRAM performs well in the case of stochastically defined networks, where fractures size, positions, orientation, etc., are sampled from given probabilistic distributions. However, reproducing a DFN with deterministically defined fractures where fractures position, orientation and size are rigidly defined, is not possible using the standard version of FRAM. This nudging technique is developed to accompany FRAM and produce high quality mesh on a DFN with both stochastic and deterministic fractures. The essence of the nudging technique is in the fracture perturbation in fracture location and fracture orientation in the way that keeps the fracture within a distance h of their original position and do not create any features smaller than h. If needed, the nudging approach applies multiple times until the desired requirements on distance are met with no significant fracture network deformation and no original connectivity modification. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Nudging Technique for Robust Meshing of Intersecting Polygons in Discrete Fracture Networks v1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nuflood,_Version_1.x.json b/agency-indexes/DoE/Nuflood,_Version_1.x.json new file mode 100644 index 00000000..9e1b671d --- /dev/null +++ b/agency-indexes/DoE/Nuflood,_Version_1.x.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-01-29" + }, + "description": "Nuflood Version 1.x is a surface-water hydrodynamic package designed for the simulation of overland flow of fluids. It consists of various routines to address a wide range of applications (e.g., rainfall-runoff, tsunami, storm surge) and real time, interactive visualization tools. Nuflood has been designed for general-purpose computers and workstations containing multi-core processors and/or graphics processing units. The software is easy to use and extensible, constructed in mind for instructors, students, and practicing engineers. Nuflood is intended to assist the water resource community in planning against water-related natural disasters.", + "laborHours": 2325.6, + "languages": [], + "name": "Nuflood, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/nuflood/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/nuflood", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Numerical_Manufacturing_And_Design_tool.json b/agency-indexes/DoE/Numerical_Manufacturing_And_Design_tool.json new file mode 100644 index 00000000..848cd128 --- /dev/null +++ b/agency-indexes/DoE/Numerical_Manufacturing_And_Design_tool.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "NuMAD helps to enable efficient creation and use of high fidelity wind turbine blade models for structural and aerodynamic analysis. NuMAD is a GUI-based tool used to manage the specific geometry and materials inputs required to fully describe a wind turbine blade.", + "laborHours": 34321.6, + "languages": [ + "MATLAB", + "HTML" + ], + "name": "Numerical Manufacturing And Design tool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/NuMAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nux,_V.1.0.json b/agency-indexes/DoE/Nux,_V.1.0.json new file mode 100644 index 00000000..f59fea52 --- /dev/null +++ b/agency-indexes/DoE/Nux,_V.1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Nux is an open-source Java XML toolset geared towards embed:,ed use in high-throughput XML messaging middleware such as large- scale Peer-to-Peer infrastructures, message queues, publish- subscribe and matchmaking systems for Blogs/newsfeeds, text chat, data acquisition and distribution systems, application level routers firewalls, classifiers, etc. It is not an XML database, and does not attempt to be one. Features include: archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Seamless W3C XQuery and XPath support for XOM. archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Full-text search (fuzzy similarity queries) for on-the-fly matchmaking in realtime streaming applications combining structured and unstructured queries. archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Efficient and flexible pools and factories for documents, XQueries, XSL Transforms, as well as document Builders that validate against various schema languages, including W3C XML Schemas, DTDs, RELAX NG, Schematron, etc. archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Optional serialization and deserialization of XOM XML documents to and from an efficient and compact custom binary XML data format (bnux format), without loss or change of any information.", + "laborHours": 997621.6, + "name": "Nux, V.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/er1c/nux/blob/master/doc/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/er1c/nux", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nvd_Search_To_Stix.json b/agency-indexes/DoE/Nvd_Search_To_Stix.json new file mode 100644 index 00000000..824f3901 --- /dev/null +++ b/agency-indexes/DoE/Nvd_Search_To_Stix.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-01-17", + "metadataLastUpdated": "2025-01-17" + }, + "description": "This code is a python based application that queries the National Vulnerability Database (NVD) API search term and CPE endpoints. It then sifts through the API response and uses the STIX2 python package to create STIX SDOs, SROs, and SCOs from the applicable data. If there are CWEs associated with the bundle, it queries the OpenCVE API for information on the weakness, then translates that data to STIX as well. It then combines all the data into a STIX bundle and outputs it to a JSON file.", + "laborHours": 91.2, + "languages": [ + "Python" + ], + "name": "Nvd Search To Stix", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/NSTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Nyx.json b/agency-indexes/DoE/Nyx.json new file mode 100644 index 00000000..2b15e996 --- /dev/null +++ b/agency-indexes/DoE/Nyx.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "asalmgren@lbl.gov" + }, + "date": { + "created": "2021-04-14", + "metadataLastUpdated": "2021-04-14" + }, + "description": "Nyx is a highly parallel, adaptive mesh, finite-volume N-body compressible hydrodynamics solver for cosmological simulations. Nyx code solves equations of compressible hydrodynamics on an adaptive grid hierarchy coupled with an N-body treatment of dark matter. The gas dynamics in Nyx uses a finite volume methodology on a set of 3-D Eulerian grids; dark matter is represented as discrete particles moving under the influence of gravity. Particles are evolved via a particle-mesh method, using Cloud-in-Cell deposition/interpolation scheme. Both baryonic and dark matter contribute to the gravitational field. In addition, Nyx includes physics needed to accurately model the intergalactic medium: in optically thin limit and assuming ionization equilibrium, the code calculates heating and cooling processes of the primordial-composition gas in an ionizing ultraviolet background radiation field. Additional physics capabilities are under development.", + "laborHours": 0.0, + "languages": [ + "C++", + "C++" + ], + "name": "Nyx", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Astro/Nyx", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OBO-Data-Converter.json b/agency-indexes/DoE/OBO-Data-Converter.json new file mode 100644 index 00000000..93b0c98b --- /dev/null +++ b/agency-indexes/DoE/OBO-Data-Converter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The OBO Data Converter reads an Ontology file in the OBO format and converts the data to a tab-delimited text file.", + "laborHours": 395.2, + "languages": [], + "name": "OBO-Data-Converter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/OBO-Data-Converter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OCHRE\342\204\242_Gymnasium__ochre_gym__[SWR-23-47].json" "b/agency-indexes/DoE/OCHRE\342\204\242_Gymnasium__ochre_gym__[SWR-23-47].json" new file mode 100644 index 00000000..bbb61bcd --- /dev/null +++ "b/agency-indexes/DoE/OCHRE\342\204\242_Gymnasium__ochre_gym__[SWR-23-47].json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2024-07-01" + }, + "description": "OCHRE\u2122 Gymnasium is a Python framework for conducting reinforcement learning research on residential building energy management problems. It is a lightweight wrapper around OCHRE, a Python-based thermal-electric residential building simulator developed in-house at NREL. OCHRE Gymnasium adheres to the standard OpenAI Gym API for a reinforcement learning environment. Detailed Sphinx documentation will be auto-generated and accompany this codebase. This documentation will detail the API, provide examples of how to use the code, etc.", + "laborHours": 29928.8, + "languages": [ + "Python" + ], + "name": "OCHRE\u2122 Gymnasium (ochre_gym) [SWR-23-47]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ochre_gym", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OCHRE\342\204\242__Object-Oriented_Controllable_High-Resolution_Residential_Energy_Model__[SWR-19-71].json" "b/agency-indexes/DoE/OCHRE\342\204\242__Object-Oriented_Controllable_High-Resolution_Residential_Energy_Model__[SWR-19-71].json" new file mode 100644 index 00000000..d0896ed2 --- /dev/null +++ "b/agency-indexes/DoE/OCHRE\342\204\242__Object-Oriented_Controllable_High-Resolution_Residential_Energy_Model__[SWR-19-71].json" @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2023-09-11" + }, + "description": "OCHRE\u2122: Object-Oriented Controllable High-Resolution Residential Energy Model\n\nA high-fidelity, high-resolution residential building model with behind-the-meter DERs and flexible load models that integrates with controllers and distribution models in building-to-grid co-simulation platforms.\n\nThe full documentation for OCHRE can be found at https://ochre-docs-final.readthedocs.io/en/latest/", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "OCHRE\u2122 (Object-Oriented Controllable High-Resolution Residential Energy Model) [SWR-19-71]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OCHRE", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.8.3-beta" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ODD__Version_0.X_.json b/agency-indexes/DoE/ODD__Version_0.X_.json new file mode 100644 index 00000000..105b7348 --- /dev/null +++ b/agency-indexes/DoE/ODD__Version_0.X_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-04", + "metadataLastUpdated": "2023-01-04" + }, + "description": "The Orthogonal Diffusion Discretizations (ODD) library is a collection of low order (Diffusion, P1, Ray Tracing, and Variable Eddington Factor (VEF)) thermal radiation solvers for orthogonal structured grids driven by an application programing interface (API).", + "laborHours": 0.0, + "languages": [], + "name": "ODD (Version 0.X)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ODD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ODI_notebook_additive_manufacturing_video_2022.json b/agency-indexes/DoE/ODI_notebook_additive_manufacturing_video_2022.json new file mode 100644 index 00000000..cfd86e23 --- /dev/null +++ b/agency-indexes/DoE/ODI_notebook_additive_manufacturing_video_2022.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-11-15", + "metadataLastUpdated": "2022-11-15" + }, + "description": "Additive Manufacturing, video dataset Two-photon lithography (TPL) is a widely used 3D nanoprinting technique that uses laser light to create objects. Challenges to large-scale adoption of this additive manufacturing method include identifying light dosage parameters and monitoring during fabrication. A research team from LLNL, Iowa State University, and Georgia Tech is applying machine learning models to tackle these challenges-i.e., accelerate the process of identifying optimal light dosage parameters and automate the detection of part quality. Funded by LLNL's Laboratory Directed Research and Development Program, the project team has curated a video dataset of TPL processes for parameters such as light dosages, photo-curable resins, and structures. Both raw and labeled versions of the datasets are available on the links in the Open Data Initiative page. The code uses the labeled dataset. Notebook compiled by Nisha Mulakken (mulakken1@llnl.gov) for LLNL Open Data Initiative, Summer 2022. Original code provided by research team. Publications: X.Y. Lee, S.K. Saha, S. Sarkar, B. Giera. \"Automated detection of part quality during two-photon lithography via deep learning.\" Additive Manufacturing 36, December 2020: doi.org/10.1016/j.addma.2020.101444 X.Y. Lee, S.K. Saha, S. Sarkar, B. Giera. \"wo Photon lithography additive manufacturing: Video dataset of parameter sweep of light dosages, photo-curable resins, and structures.\" Data in Brief 32, October 2020. doi.org/10.1016/j.dib.2020.106119.", + "laborHours": 0.0, + "languages": [], + "name": "ODI notebook additive_manufacturing_video_2022", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnlopendata/additive_manufacturing_video_2022", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OIDC_Utils.json b/agency-indexes/DoE/OIDC_Utils.json new file mode 100644 index 00000000..95359276 --- /dev/null +++ b/agency-indexes/DoE/OIDC_Utils.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "yakubovs@ornl.gov" + }, + "date": { + "created": "2024-02-15", + "metadataLastUpdated": "2024-02-15" + }, + "description": "This project enables user authentication on servers using OpenID Connect tokens. It includes a PAM module for SSH login via an OIDC token and a utility for executing commands and copying files on behalf of a user, also utilizing an OIDC token for authentication.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "OIDC Utils", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PaNGalaxy/oidc-utils", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OKotevska_petina.json b/agency-indexes/DoE/OKotevska_petina.json new file mode 100644 index 00000000..0500f951 --- /dev/null +++ b/agency-indexes/DoE/OKotevska_petina.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "kotevskao@ornl.gov" + }, + "date": { + "created": "2025-01-16", + "metadataLastUpdated": "2025-04-15" + }, + "description": "This is a repository for PETINA: Privacy prEservaTIoN Algorithms.", + "laborHours": 106.4, + "languages": [ + "Python" + ], + "name": "OKotevska/petina", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/OKotevska/petina", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.11" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OLCF_Test_Harness.json b/agency-indexes/DoE/OLCF_Test_Harness.json new file mode 100644 index 00000000..f81e993e --- /dev/null +++ b/agency-indexes/DoE/OLCF_Test_Harness.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "dietzdt@ornl.gov" + }, + "date": { + "created": "2025-03-27", + "metadataLastUpdated": "2025-03-28" + }, + "description": "Acceptance and regression testing of a High Performance Computing (HPC) system requires an automated and reproducible framework and tool for running and logging results. Manually running tests across a system is labor intensive and prone to reproducibility errors. The OLCF Test Harness (OTH) provides a framework in which to document required tests for a HPC system. The OTH then provides tools to execute and log results of these tests in an automated fashion.", + "laborHours": 22496.0, + "languages": [ + "Python" + ], + "name": "OLCF Test Harness", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/olcf/olcf-test-harness/blob/devel/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/olcf-test-harness", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ONCat__ORNL_Neutron_Catalog_.json b/agency-indexes/DoE/ONCat__ORNL_Neutron_Catalog_.json new file mode 100644 index 00000000..fedd7884 --- /dev/null +++ b/agency-indexes/DoE/ONCat__ORNL_Neutron_Catalog_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "parkerpg@ornl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2023-04-13" + }, + "description": "ONCat is used to store information about neutron experiment data at SNS / HFIR. ONCat consists of an API with which various software clients can communicate to gain access to that information, as well as a web site (see landing page) which offers a way for experiment teams and instrument staff to easily view the metadata relating to experiments using just a web browser. The code is currently private and closed-source. Please contact oncat-support@ornl.gov for more information.", + "homepageURL": "https://oncat.ornl.gov", + "laborHours": 0.0, + "languages": [ + "Python", + "TypeScript" + ], + "name": "ONCat (ORNL Neutron Catalog)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://oncat.ornl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://oncat.ornl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OPENSTUDIO\302\256_[SWR-07-40].json" "b/agency-indexes/DoE/OPENSTUDIO\302\256_[SWR-07-40].json" new file mode 100644 index 00000000..119a988c --- /dev/null +++ "b/agency-indexes/DoE/OPENSTUDIO\302\256_[SWR-07-40].json" @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-01-31" + }, + "description": "OpenStudio\u00ae is a cross-platform (Windows, Mac, and Linux) collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance. OpenStudio is an open source (LGPL) project to facilitate community development, extension, and private sector adoption. OpenStudio includes graphical interfaces along with a Software Development Kit (SDK). In addition to the graphical interface, OpenStudio allows building researchers and software developers to quickly get started through its multiple entry levels, including access through C++, Ruby, and C#. 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It was developed to provide researchers with a standardized way to efficiently create AC OPF datasets that are representative of more of the AC OPF feasible load space compared to typical dataset creation methods. The OPFLearn dataset creation method uses a relaxed AC OPF formulation to reduce the volume of the unclassified input space throughout the dataset creation process. Over time this input space tightens around the relaxed AC OPF feasible region to increase the percentage of feasible load profiles found while uniformly sampling the input space. Load samples are processed using AC OPF formulations from PowerModels.jl. More information on the dataset creation method can be found in our publication, \"OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets\". To use OPFLearn.jl a PowerModels network data dictionary is required (can be loaded from Matpower \".m\" files) to define the network the dataset is being created for.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "OPFLearn.jl [SWR-21-109]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OPFLearn.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OPFLearn.jl_v0.1.2_5_18_2023_[SWR-21-109].json b/agency-indexes/DoE/OPFLearn.jl_v0.1.2_5_18_2023_[SWR-21-109].json new file mode 100644 index 00000000..c4c7b251 --- /dev/null +++ b/agency-indexes/DoE/OPFLearn.jl_v0.1.2_5_18_2023_[SWR-21-109].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-03-11", + "metadataLastUpdated": "2024-03-11" + }, + "description": "OPFLearn.jl is a Julia package for creating datasets for machine learning approaches to solving AC optimal power flow (AC OPF). It was developed to provide researchers with a standardized way to efficiently create AC OPF datasets that are representative of more of the AC OPF feasible load space compared to typical dataset creation methods. The OPFLearn dataset creation method uses a relaxed AC OPF formulation to reduce the volume of the unclassified input space throughout the dataset creation process. Over time this input space tightens around the relaxed AC OPF feasible region to increase the percentage of feasible load profiles found while uniformly sampling the input space. Load samples are processed using AC OPF formulations from PowerModels.jl. More information on the dataset creation method can be found in our publication, \"OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets\". To use OPFLearn.jl a PowerModels network data dictionary is required (can be loaded from Matpower \".m\" files) to define the network the dataset is being created for.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "OPFLearn.jl v0.1.2 5/18/2023 [SWR-21-109]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OPFLearn.jl", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.1.1" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/ORBIT__Offshore_Renewables_Balance_of_System_and_Installation_Tool__WISDEM\302\256__[SWR-20-11].json" "b/agency-indexes/DoE/ORBIT__Offshore_Renewables_Balance_of_System_and_Installation_Tool__WISDEM\302\256__[SWR-20-11].json" new file mode 100644 index 00000000..f870e62b --- /dev/null +++ "b/agency-indexes/DoE/ORBIT__Offshore_Renewables_Balance_of_System_and_Installation_Tool__WISDEM\302\256__[SWR-20-11].json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-12-23", + "metadataLastUpdated": "2024-10-25" + }, + "description": "Offshore Renewables Balance of System and Installation Tool (ORBIT) simulates balance of system and installation processes for offshore wind plants. It is intended to be used to study the effects of weather delays on offshore vessel logistics and for medium fidelity trade-off studies for offshore technologies.", + "laborHours": 10776.8, + "languages": [ + "Python" + ], + "name": "ORBIT (Offshore Renewables Balance of System and Installation Tool) WISDEM\u00ae [SWR-20-11]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/ORBIT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.8" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ORIGEN_Library_Manager.json b/agency-indexes/DoE/ORIGEN_Library_Manager.json new file mode 100644 index 00000000..a6d793b8 --- /dev/null +++ b/agency-indexes/DoE/ORIGEN_Library_Manager.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wieselquiswa@ornl.gov" + }, + "date": { + "created": "2024-02-12", + "metadataLastUpdated": "2024-02-15" + }, + "description": "OLM focuses on managing the ORIGEN reactor library, which is a special collection of data that enables rapid spent fuel calculations with SCALE/ORIGAMI.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ORIGEN Library Manager", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/scale/code/olm", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ORMATEX.json b/agency-indexes/DoE/ORMATEX.json new file mode 100644 index 00000000..cb021d1c --- /dev/null +++ b/agency-indexes/DoE/ORMATEX.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "gureckywl@ornl.gov" + }, + "date": { + "created": "2025-01-24", + "metadataLastUpdated": "2025-01-24" + }, + "description": "The Oak Ridge Matrix Exponential (ORMATEX) software library contains methods to compute the matrix exponential and the action of the matrix exponential on a vector. Additionally, this package contains the related methods for the phi-functions which commonly appear in a wide class of exponential time integration methods. Krylov methods are provided to evaluate the matrix exponential-vector and phi-vector products for cases where the matrix is large and sparse. Utilizing these methods, ORMATEX implements performant exponential integrators for large systems of coupled ordinary differential equations (ODEs). The exponential time integration routines in ORMATEX are particularly suitable to large, stiff systems of equations. These routines may be utilized as a competitive alternative to classical implicit and explicit time integration schemes for certain classes of differential equations where the problem stiffness can be predominately explained by the linear terms.", + "laborHours": 2523.2, + "languages": [ + "Rust", + "Python" + ], + "name": "ORMATEX", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/ORMATEX", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ORNL-EPICS.json b/agency-indexes/DoE/ORNL-EPICS.json new file mode 100644 index 00000000..43316323 --- /dev/null +++ b/agency-indexes/DoE/ORNL-EPICS.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "hartmansm@ornl.gov" + }, + "date": { + "created": "2021-10-11", + "metadataLastUpdated": "2021-10-12" + }, + "description": "This collection of applications provides additional capabilities and features to the EPICS toolkit (https://epics-controls.org) for building distributed controls systems and data acquisition systems. They have been developed for a particle accelerator control system and the control and data acquisition systems for neutron scattering and neutron imaging instruments but can be integrated in EPICS-based control systems for other types of machines.", + "homepageURL": "https://github.com/ornl-epics", + "laborHours": 0.0, + "languages": [], + "name": "ORNL-EPICS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://epics-controls.org/licensing", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-epics", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ORNL-QCI_TISCC.json b/agency-indexes/DoE/ORNL-QCI_TISCC.json new file mode 100644 index 00000000..14c77f86 --- /dev/null +++ b/agency-indexes/DoE/ORNL-QCI_TISCC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "leblondtr@ornl.gov" + }, + "date": { + "created": "2024-02-01", + "metadataLastUpdated": "2024-02-01" + }, + "description": "We introduce the Trapped-Ion Surface Code Compiler (TISCC), a software tool that generates circuits for a universal set of surface code patch operations in terms of a native trapped-ion gate set. To accomplish this, TISCC manages an internal representation of a trapped-ion system where a repeating pattern of trapping zones and junctions is arranged in an arbitrarily large rectangular grid. Surface code operations are compiled by instantiating surface code patches on the grid and using methods to generate transversal operations over data qubits, rounds of error correction over stabilizer plaquettes, and/or lattice surgery operations between neighboring patches. Beyond the implementation of a basic surface code instruction set, TISCC contains corner movement functionality and a patch translation that is implemented using ion movement alone. Except in the latter case, all TISCC functionality is extensible to alternative grid-like hardware architectures. TISCC output has been verified using the Oak Ridge Quasi-Clifford Simulator (ORQCS).", + "laborHours": 0.0, + "languages": [], + "name": "ORNL-QCI/TISCC", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-QCI/TISCC/blob/v1.0.0/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/TISCC", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ORNLJulia_Privacy.jl.json b/agency-indexes/DoE/ORNLJulia_Privacy.jl.json new file mode 100644 index 00000000..adc43aa8 --- /dev/null +++ b/agency-indexes/DoE/ORNLJulia_Privacy.jl.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "youngsr@ornl.gov" + }, + "date": { + "created": "2022-03-18", + "metadataLastUpdated": "2022-03-18" + }, + "description": "A Julia library for training neural networks with privacy.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "ORNLJulia/Privacy.jl", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNLJulia/Privacy.jl", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ORNL_MLMC.json b/agency-indexes/DoE/ORNL_MLMC.json new file mode 100644 index 00000000..8973ef9d --- /dev/null +++ b/agency-indexes/DoE/ORNL_MLMC.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2025-02-11", + "metadataLastUpdated": "2025-02-11" + }, + "description": "Multi-Level Monte Carlo Methods in Chemical Applications with Lennard-Jones Potentials and other Landscapes with Isolated Singularities", + "laborHours": 1854.4, + "languages": [ + "Python" + ], + "name": "ORNL/MLMC", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/MLMC", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ORNL_ParrLO.json b/agency-indexes/DoE/ORNL_ParrLO.json new file mode 100644 index 00000000..ce298eac --- /dev/null +++ b/agency-indexes/DoE/ORNL_ParrLO.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "fattebertj@ornl.gov" + }, + "date": { + "created": "2020-10-20", + "metadataLastUpdated": "2020-10-20" + }, + "description": "Loewdin orthonormalization of distributed tall-skinny matrix using Schulz iteration", + "laborHours": 1869.6, + "languages": [ + "C++" + ], + "name": "ORNL/ParrLO", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/ParrLO", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ORNL_Slicer_2_-_Open_Source_Copyright.json b/agency-indexes/DoE/ORNL_Slicer_2_-_Open_Source_Copyright.json new file mode 100644 index 00000000..daf3acd3 --- /dev/null +++ b/agency-indexes/DoE/ORNL_Slicer_2_-_Open_Source_Copyright.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "roschliac@ornl.gov" + }, + "date": { + "created": "2022-12-07", + "metadataLastUpdated": "2024-05-20" + }, + "description": "ORNL Slicer 2 is a slicing program for additive manufacturing. It takes a solid body mesh object, typically as .STL file, and converts that into machine readable instructions, called g-code, that a 3D printer can use to build the object. The functionality includes loading and positioning an object, slicing it into layers, fitting toolpaths to the layers, and outputting g-code to construct the object. All of this is contained within a graphical user interface (GUI) that allows the user to define all of the settings specific to their machine and process, then preview the resultant g-code before starting the printing process.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "ORNL Slicer 2 - Open Source Copyright", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNLSlicer/Slicer-2", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ORNL_Thermo4PFM.json b/agency-indexes/DoE/ORNL_Thermo4PFM.json new file mode 100644 index 00000000..46596bd7 --- /dev/null +++ b/agency-indexes/DoE/ORNL_Thermo4PFM.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "fattebertj@ornl.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2021-12-02" + }, + "description": "Library to compute equilibrium compositions and equal chemical potential compositions in binary and ternary alloys.\nThis library supports thermodynamic data formulated according to CALPHAD (Computer Coupling of Phase Diagrams and Thermochemistry) models, as well as dilute binary alloys.\nOne major aim is to solve the Kim-Kim-Suzuki (KKS) equations to obtain local compositions given a local mixture of two phases.\nThese quantities are then used to evaluate the phase-field model driving force (right handside of time-evolution equation), as well as the energy\ndensity", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "ORNL/Thermo4PFM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/Thermo4PFM", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ORNL_briar-api.json b/agency-indexes/DoE/ORNL_briar-api.json new file mode 100644 index 00000000..13459c08 --- /dev/null +++ b/agency-indexes/DoE/ORNL_briar-api.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "broganjr@ornl.gov" + }, + "date": { + "created": "2022-09-15", + "metadataLastUpdated": "2022-09-15" + }, + "description": "The open-source biometrics API and SDK for the IARPA BRIAR program", + "laborHours": 0.0, + "languages": [ + "C++", + "Python" + ], + "name": "ORNL/briar-api", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://raw.githubusercontent.com/ORNL/briar-api/main/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/briar-api", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ORNL_grit.json b/agency-indexes/DoE/ORNL_grit.json new file mode 100644 index 00000000..1750c0a9 --- /dev/null +++ b/agency-indexes/DoE/ORNL_grit.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "gew1@ornl.gov" + }, + "date": { + "created": "2023-06-22", + "metadataLastUpdated": "2023-06-22" + }, + "description": "Grit is a software library designed specifically for conducting particle-based Lagrangian simulations with CPU/GPUperformance portability. This library allows researchers and engineers to perform a wide range of simulations, including multiphase flow, and more. Grit employs Message Passing Interface (MPI) for distributed memory parallelism and Kokkos programming model for on-node shared memory parallelism with performance portability across different architectures of GPUs and multi-core/manycore CPUs. ", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "ORNL/grit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/grit/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/grit", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ORNL_mind_the_gap.json b/agency-indexes/DoE/ORNL_mind_the_gap.json new file mode 100644 index 00000000..5f7e6fdc --- /dev/null +++ b/agency-indexes/DoE/ORNL_mind_the_gap.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "gonzalesjj@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "Mind the Gap is an algorithm for detecting areas of missing data in building footprints.", + "laborHours": 440.8, + "languages": [ + "Python" + ], + "name": "ORNL/mind_the_gap", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/mind_the_gap/blob/main/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/mind_the_gap", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ORNL_pcapmunger.json b/agency-indexes/DoE/ORNL_pcapmunger.json new file mode 100644 index 00000000..2a1d083c --- /dev/null +++ b/agency-indexes/DoE/ORNL_pcapmunger.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jewellbc@ornl.gov" + }, + "date": { + "created": "2022-05-09", + "metadataLastUpdated": "2022-05-09" + }, + "description": "Project for overlaying attacks onto existing PCAP data. The included scripts were originally a part of the training pipeline for the Oak Ridge Cyber Analytics (ORCA) project and have been distributed now under an open source license to facilitate the publication of PCAP datasets.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ORNL/pcapmunger", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/pcapmunger", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ORNL_superneuro-mat.json b/agency-indexes/DoE/ORNL_superneuro-mat.json new file mode 100644 index 00000000..a3073de8 --- /dev/null +++ b/agency-indexes/DoE/ORNL_superneuro-mat.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "datepa@ornl.gov" + }, + "date": { + "created": "2023-03-22", + "metadataLastUpdated": "2023-03-28" + }, + "description": "A matrix-based simulator for neuromorphic computing.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ORNL/superneuro-mat", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/superneuromat", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OSCARS.json b/agency-indexes/DoE/OSCARS.json new file mode 100644 index 00000000..db005819 --- /dev/null +++ b/agency-indexes/DoE/OSCARS.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The ESnet On-Demand Secure Circuits and Advance Reservation System (OSCARS) is a prototype service enabling advance reservation of guaranteed bandwidth secure virtual circuits. OSCARS operates within the Energy Sciences Network (ESnet), and has provisions for interoperation with other network domains. OSCARS utilizes the Web services model and standards to implement communication with the system and between domains, and for authentication, authorization, and auditing (AAA). The management and operation of end-to-end virtual circuits within the network is done at the layer 3 network level. Multi-Protocol Label Switching (MPLS) and the Resource Reservation Protocol (RSVP) are used to create the virtual circuits or Label Switched Paths (LSP's). Quality of Service (QoS) is used to provide bandwidth guarantees.", + "homepageURL": "https://www.es.net/engineering-services/oscars", + "laborHours": 0.0, + "languages": [ + "None" + ], + "name": "Oscars", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.es.net/engineering-services/oscars", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/OSCARS_JSON_Topology_Publisher.json b/agency-indexes/DoE/OSCARS_JSON_Topology_Publisher.json new file mode 100644 index 00000000..b3ea94b3 --- /dev/null +++ b/agency-indexes/DoE/OSCARS_JSON_Topology_Publisher.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "Publishes the OSCARS NMWG topology and list of circuits in a JSON format.", + "laborHours": 7828.0, + "languages": [], + "name": "OSCARS JSON Topology Publisher", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/oscars-topology-json/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/oscars-topology-json", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OSEII__Open-Source_Energy_Intensity_Indicators_.json b/agency-indexes/DoE/OSEII__Open-Source_Energy_Intensity_Indicators_.json new file mode 100644 index 00000000..ccb0be7e --- /dev/null +++ b/agency-indexes/DoE/OSEII__Open-Source_Energy_Intensity_Indicators_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-03-02", + "metadataLastUpdated": "2021-03-22" + }, + "description": "Energy Intensity Indicators provides a framework to quantify how energy efficiency may or may not be affecting energy use relative to other economic trends.\n\nThe model enables the decomposition of energy use for economic sectors through the use of a Log Mean Divisia Index (LMDI) model. The LMDI methodology decomposes energy use into three main categories: activity, structure and intensity (i.e. energy efficiency). A user can thus explain changes to overall energy use in a sector through changes to sector output (activity), structural shifts within sectors (e.g. across transportation modes), and efficiency of energy use in that sector.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "OSEII (Open-Source Energy Intensity Indicators)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/EnergyIntensityIndicators", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OSHMPI:_Open_SHMEM_Implementation_over_MPI.json b/agency-indexes/DoE/OSHMPI:_Open_SHMEM_Implementation_over_MPI.json new file mode 100644 index 00000000..3b4d496c --- /dev/null +++ b/agency-indexes/DoE/OSHMPI:_Open_SHMEM_Implementation_over_MPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-03-19", + "metadataLastUpdated": "2021-03-19" + }, + "description": "Open SHMEM is an increasingly popular standard of the SHMEM programing model. OSHMPI provides a light weight Open SHMEM implementation on top of the portable MPI Interface", + "laborHours": 0.0, + "languages": [], + "name": "OSHMPI: Open SHMEM Implementation over MPI", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/oshmpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OSIF__Open_Source_Impedance_Fitter_.json b/agency-indexes/DoE/OSIF__Open_Source_Impedance_Fitter_.json new file mode 100644 index 00000000..228a89fe --- /dev/null +++ b/agency-indexes/DoE/OSIF__Open_Source_Impedance_Fitter_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-16", + "metadataLastUpdated": "2021-06-17" + }, + "description": "OSIF is a tool that allows the user to easily fit electrochemical impedance spectra of proton exchange membrane fuel cells to a commonly accepted equivalent circuit model. The fitted parameters provide insight into the physical properties of the cell which allow the user to support experimental hypotheses.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "OSIF (Open Source Impedance Fitter)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OSIF", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OSKI.json b/agency-indexes/DoE/OSKI.json new file mode 100644 index 00000000..ed62325a --- /dev/null +++ b/agency-indexes/DoE/OSKI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "OSKI is the Optimized Sparse Kernel Interface, a collection of low-level C primitives that provide automatically tuned computational kernels on sparse matrices, for use in solver libraries and applications. ", + "homepageURL": "http://bebop.cs.berkeley.edu/oski", + "laborHours": 0.0, + "languages": [], + "name": "OSKI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://bebop.cs.berkeley.edu/oski/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://bebop.cs.berkeley.edu/oski", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/OSOS__Open_Source_Ops_and_Statistics_.json b/agency-indexes/DoE/OSOS__Open_Source_Ops_and_Statistics_.json new file mode 100644 index 00000000..559cee52 --- /dev/null +++ b/agency-indexes/DoE/OSOS__Open_Source_Ops_and_Statistics_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-10-29", + "metadataLastUpdated": "2021-10-29" + }, + "description": "OSOS is a software package that helps track the usage and operations statistics for other open source software.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "OSOS (Open Source Ops and Statistics)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/osos", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OTM-MPI__Open_Traffic_Models_-_MPI_.json b/agency-indexes/DoE/OTM-MPI__Open_Traffic_Models_-_MPI_.json new file mode 100644 index 00000000..f1468002 --- /dev/null +++ b/agency-indexes/DoE/OTM-MPI__Open_Traffic_Models_-_MPI_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-30", + "metadataLastUpdated": "2019-09-23" + }, + "description": "This software is an extension to OTM (Open Traffic Models), which is an open-source traffic simulator maintained at the Institute of Transportation Studies at U.C. Berkeley. OTM-MPI provides functionality for running OTM simulations in distributed computing environments. Its functionality includes min-cut division of traffic networks (using METIS), deployment of sub-networks on multiple compute nodes, and inter-node MPI communications.", + "laborHours": 1155.2, + "languages": [], + "name": "OTM-MPI (Open Traffic Models - MPI)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ggomes/otm-mpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OT_Emulation_Data_Broker.json b/agency-indexes/DoE/OT_Emulation_Data_Broker.json new file mode 100644 index 00000000..321f0485 --- /dev/null +++ b/agency-indexes/DoE/OT_Emulation_Data_Broker.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-11-03", + "metadataLastUpdated": "2021-11-03" + }, + "description": "The OT Emulation Data Broker system allows Simulink models to be connected to an emulated control system network. The package includes a Simulink S-Function that allows communication to the data broker via inter process communication; a data broker, which orchestrates communication between the emulated control system network and the simulation; an endpoint, which facilitates communication between the data broker and PLC's on the control network using ModBus/TCP; and an example PLC structured text files that work with OpenPLC, an open source emulated PLC. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-11479 O", + "laborHours": 0.0, + "languages": [ + "Python", + "Simulink", + "S Function", + "C Code", + "Python" + ], + "name": "OT Emulation Data Broker", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SMARTT", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OT_Emulation_Data_Broker_v.2.0.json b/agency-indexes/DoE/OT_Emulation_Data_Broker_v.2.0.json new file mode 100644 index 00000000..c18df0e7 --- /dev/null +++ b/agency-indexes/DoE/OT_Emulation_Data_Broker_v.2.0.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-16", + "metadataLastUpdated": "2022-10-16" + }, + "description": "SAND2021-11479 O The OT Emulation Data Broker system allows Simulink models to be connected to an emulated control system network. The package includes a Simulink S-Function that allows communication to the data broker via inter process communication; a data broker, which orchestrates communication between the emulated control system network and the simulation; an endpoint, which facilitates communication between the data broker and PLC's on the control network using ModBus/TCP; and an example PLC structured text files that work with OpenPLC, an open source emulated PLC. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C", + "Python", + "Simulink", + "S Function" + ], + "name": "OT Emulation Data Broker v.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SMARTT", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OVIS.json b/agency-indexes/DoE/OVIS.json new file mode 100644 index 00000000..06c75666 --- /dev/null +++ b/agency-indexes/DoE/OVIS.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OVIS is a tool for intelligent, real-time monitoring of computational clusters. While current monitoring tools treat the cluster as singleton nodes, OVIS considers the cluster as comprised of comparative ensembles. OVIS provides a visual display of deterministic information about state variables and their aggregate statistics. Comparison to statistical quantities can be used for the automatic identification of abnormalities. OVIS collects and processes active data. OVIS can also process historical data files or database files.", + "laborHours": 98252.8, + "name": "OVIS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ovis-hpc/ovis", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Oak_Ridge_Graph_Analytics_for_Medical_Innovation__ORiGAMI_.json b/agency-indexes/DoE/Oak_Ridge_Graph_Analytics_for_Medical_Innovation__ORiGAMI_.json new file mode 100644 index 00000000..68d2cb1d --- /dev/null +++ b/agency-indexes/DoE/Oak_Ridge_Graph_Analytics_for_Medical_Innovation__ORiGAMI_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "In this era of data-driven decisions and discovery where Big Data is producing Bigger Data, data scientists at the Oak Ridge National Laboratory are leveraging unique leadership infrastructure (e.g., Urika XA and Urika GD appliances) to develop scalable algorithms for semantic, logical and statistical reasoning with Big Data (i.e., data stored in databases as well as unstructured data in documents). ORiGAMI is a next-generation knowledge-discovery framework that is: (a) knowledge nurturing (i.e., evolves seamlessly with newer knowledge and data), (b) smart and curious (i.e. using information-foraging and reasoning algorithms to digest content) and (c) synergistic (i.e., interfaces computers with what they do best to help subject-matter-experts do their best. ORiGAMI has been demonstrated using the National Library of Medicine's SEMANTIC MEDLINE (archive of medical knowledge since 1994).", + "laborHours": 136.8, + "name": "Oak Ridge Graph Analytics for Medical Innovation (ORiGAMI)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ssrangan/origami/blob/master/Open%20Source%20Software%20License.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ssrangan/origami", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Oak_Ridge_Wang-Landau__OWL_.json b/agency-indexes/DoE/Oak_Ridge_Wang-Landau__OWL_.json new file mode 100644 index 00000000..34f59554 --- /dev/null +++ b/agency-indexes/DoE/Oak_Ridge_Wang-Landau__OWL_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The code is a set of first-principles based thermodynamic properties calculations for materials properties at finite temperature. It provides a collection of commonly used Monte Carlo algorithms, interfaced with a few external codes that carry out density functional theory calculations, such as Quantum Espresso and Local Self-consistent Multiple Scattering. The code provides high accuracy thermodynamic calculations that are comparable to real-world materials properties.", + "laborHours": 4453.6, + "languages": [ + "C++11" + ], + "name": "Oak Ridge Wang-Landau (OWL)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/owl-suite/OWL", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Object_Relations_UI.json b/agency-indexes/DoE/Object_Relations_UI.json new file mode 100644 index 00000000..227b0e60 --- /dev/null +++ b/agency-indexes/DoE/Object_Relations_UI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-02", + "metadataLastUpdated": "2020-09-02" + }, + "description": "UI for showing workspace object relationships.", + "laborHours": 4727.2, + "languages": [], + "name": "Object Relations UI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/object_relations_ui", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Obtain3D_open.json b/agency-indexes/DoE/Obtain3D_open.json new file mode 100644 index 00000000..90b247d8 --- /dev/null +++ b/agency-indexes/DoE/Obtain3D_open.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-19", + "metadataLastUpdated": "2021-11-19" + }, + "description": "This computer code uses the concept of the parallax to compute the x, y and z coordinates of points found using transmission electron microscopy (TEM), or any transmission imaging technique, using two images, each taken at a different perspective of the region containing the points. Points correspond, but are not limited, to the center of cavities or precipitates, positions of irradiation black dot damage, positions along a dislocation line, or positions along where an interface meets a free surface. Features can include dislocations, interfaces, cavities, precipitates, inclusions etc. The x, y and z coordinates of the points are output in a text file. The code also allows the user to visualize the features containing the points in three dimensions.", + "laborHours": 0.0, + "languages": [], + "name": "Obtain3D_open", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Obtain3D_open", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Occupancy_Simulator_Solver_v1.0.json b/agency-indexes/DoE/Occupancy_Simulator_Solver_v1.0.json new file mode 100644 index 00000000..9085caf4 --- /dev/null +++ b/agency-indexes/DoE/Occupancy_Simulator_Solver_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-21", + "metadataLastUpdated": "2021-09-21" + }, + "description": "Occupant schedules at room level are crucial information to building energy modeling which quantifies occupant-related energy efficiency technologies and controls for new building design as well as existing building retrofits to reduce energy use and GHG emissions in buildings. The Occupancy Simulator Solver is an executable software component that simulates the stochastic behavior of occupant presence and movement in a building using the Markov-chain model. Occupancy Simulator Solver is the calculation engine of the web App Occupancy Simulator, which takes high level input on occupants, spaces and events, then calls the Solver to simulate occupant movement and generate occupant schedules for each space. The generated schedules capture diversity and stochastic nature of occupant activities (e.g., in office, meetings, breaks, lunch). These schedules are stored in CSV files and can be downloaded from the App and used for building performance simulation.", + "homepageURL": "https://sites.google.com/lbl.gov/2019-163/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Occupancy Simulator Solver v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2019-163/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2019-163/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ocean_Kite_Project.json b/agency-indexes/DoE/Ocean_Kite_Project.json new file mode 100644 index 00000000..88b38c2b --- /dev/null +++ b/agency-indexes/DoE/Ocean_Kite_Project.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcreed2@ncsu.edu" + }, + "date": { + "created": "2023-02-07", + "metadataLastUpdated": "2023-02-08" + }, + "description": "This project is a code base for a tethered energy-harvesting kite system, that is able to operate in both a water or wind environment. The project is broken into: Classes - containing classes for things such as the kite, the environment, the flight controller, the tethers, ect. Compositions - contains simulink block diagrams for using instances of the classes, for things such as the kite, the environment, the flight controller, the tethers, ect. Units - basically Simulink library files used in many places to perform fundamental operations Master Simulink model - where all the compositions are run together Test scripts - scripts to run the master Simulink model under various conditions The key components of the model are the kite vehicle, the tethers, the ground station, the environment, the flight controller, and high level controllers.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Simulink" + ], + "name": "Ocean Kite Project", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NCSUCORE/DoEOceanKiteProject/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NCSUCORE/DoEOceanKiteProject.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ocelot.json b/agency-indexes/DoE/Ocelot.json new file mode 100644 index 00000000..beafad7b --- /dev/null +++ b/agency-indexes/DoE/Ocelot.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-01", + "metadataLastUpdated": "2022-09-01" + }, + "description": "Ocelot is a multiphysics simulation toolkit designed for studying FEL and storage ring based light sources. Ocelot is written in Python. Its central concept is the writing of python's scripts for simulations with the usage of Ocelot's modules and functions and the standard Python libraries.", + "laborHours": 0.0, + "languages": [], + "name": "Ocelot", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ocelot", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ocelot_Optimizer.json b/agency-indexes/DoE/Ocelot_Optimizer.json new file mode 100644 index 00000000..3771d9fa --- /dev/null +++ b/agency-indexes/DoE/Ocelot_Optimizer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-10", + "metadataLastUpdated": "2022-08-10" + }, + "description": "Ocelot optimizer is a platform for automated optimization of accelerator performance.", + "laborHours": 0.0, + "languages": [], + "name": "Ocelot Optimizer", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/optimizer", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Octeres.json b/agency-indexes/DoE/Octeres.json new file mode 100644 index 00000000..d4c1e867 --- /dev/null +++ b/agency-indexes/DoE/Octeres.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SF-24-054 Octeres is a collection of tools and libraries for processing large amounts of\nsupercomputer data.", + "laborHours": 11688.8, + "languages": [], + "name": "Octeres", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.cels.anl.gov/aig-public/octeres", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Octopus.json b/agency-indexes/DoE/Octopus.json new file mode 100644 index 00000000..8f5a6bae --- /dev/null +++ b/agency-indexes/DoE/Octopus.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Octopus is a scientific program aimed at the ab initio virtual experimentation on a hopefully ever-increasing range of system types. Electrons are described quantum-mechanically within density-functional theory (DFT), in its time-dependent form (TDDFT) when doing simulations in time. Nuclei are described classically as point particles. Electron-nucleus interaction is described within the pseudopotential approximation.", + "laborHours": 3054820.0, + "languages": [], + "name": "Octopus", + "organization": "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/octopus-code/octopus/blob/develop/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/octopus-code/octopus", + "status": "Production", + "tags": [ + "DOE CODE", + "USDOE Advanced Research Projects Agency \u2013 Energy (ARPA-E) (United States) (ARPA-E)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/OddMon.json b/agency-indexes/DoE/OddMon.json new file mode 100644 index 00000000..400d5d2b --- /dev/null +++ b/agency-indexes/DoE/OddMon.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "OddMon reads statistics information from multiple Lustre OSS's, forwards it to a central aggregator and then processes the data into a form suitable to inserting into a Splunk data store.", + "laborHours": 836.0, + "languages": [ + "Python 2.6" + ], + "name": "OddMon", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-TechInt/oddmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OffshoreBOS__Offshore_Wind_Balance-of-Station__BOS__Model__\"S\"_was_originally_\"System\"_[SWR-16-27].json" "b/agency-indexes/DoE/OffshoreBOS__Offshore_Wind_Balance-of-Station__BOS__Model__\"S\"_was_originally_\"System\"_[SWR-16-27].json" new file mode 100644 index 00000000..2f67bde7 --- /dev/null +++ "b/agency-indexes/DoE/OffshoreBOS__Offshore_Wind_Balance-of-Station__BOS__Model__\"S\"_was_originally_\"System\"_[SWR-16-27].json" @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2023-08-10" + }, + "description": "+++ This repository was archived by the owner on May 4, 2020. It is now read-only. +++\n\nAn offshore balance of station (BOS) model for estimating the costs in assembly, installation, financing, and decommissioning of offshore wind plants.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python", + "makefile" + ], + "name": "OffshoreBOS (Offshore Wind Balance-of-Station (BOS) Model) \"S\" was originally \"System\" [SWR-16-27]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/OffshoreBOS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Offshore_Wind_ENergy_Simulation_Toolkit__OWENS_.json b/agency-indexes/DoE/Offshore_Wind_ENergy_Simulation_Toolkit__OWENS_.json new file mode 100644 index 00000000..947cdc54 --- /dev/null +++ b/agency-indexes/DoE/Offshore_Wind_ENergy_Simulation_Toolkit__OWENS_.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-09", + "metadataLastUpdated": "2024-10-09" + }, + "description": "SAND2021-2751 O\nThe Offshore Wind ENergy Simulation Toolkit (OWENS) is a collection of aerodynamic, structural, hydrodynamic, drivetrain, controls, composite structure and mesh preprocessing, and data postprocessing. OWENS is primarily an ontology, or glue code, pulling together many open-source and Sandia-developed libraries to model the aero-servo-hydro-elastic physics of wind and marine energy turbines. The toolkit\u2019s intended use is for arbitrary aeroelastic rotor configurations analysis including vertical-axis wind turbines, horizontal-axis wind turbines, and analogous marine energy applications for fixed-bottom and floating configurations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525", + "laborHours": 11962.4, + "languages": [ + "Julia", + "Fortran" + ], + "name": "Offshore Wind ENergy Simulation Toolkit (OWENS)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/OWENS.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.00" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Oineus_v1.0.json b/agency-indexes/DoE/Oineus_v1.0.json new file mode 100644 index 00000000..7574cfa6 --- /dev/null +++ b/agency-indexes/DoE/Oineus_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-07", + "metadataLastUpdated": "2021-04-07" + }, + "description": "A library for multi-threaded computation of persistence diagrams. The algorithm for computing persistence diagrams in a lock-free manner was published in the 'Towards Lock-free Persistent Homology' (D. Morozov, A. Nigmetov, Brief Announcement: SPAA 2020); it scales better than the only other shared-memory parallel implementation of persistent homology computation PHAT. Library includes python bindings to compute persistence diagrams and their vectorizations for lower-star filtrations on grid data. It is intended to be used by scientists working on Topological Data Analysis and its applications in different areas.", + "laborHours": 0.0, + "languages": [], + "name": "Oineus v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/grey-narn/oineus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Omega_h.json b/agency-indexes/DoE/Omega_h.json new file mode 100644 index 00000000..6d3f472f --- /dev/null +++ b/agency-indexes/DoE/Omega_h.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "daibane@sandia.gov" + }, + "date": { + "created": "2018-03-01", + "metadataLastUpdated": "2020-09-01" + }, + "description": "Omega_h is a C++11 library that implements tetrahedron and triangle mesh adaptativity, with a focus on scalable HPC performance using (optionally) MPI, OpenMP, or CUDA. It is intended to provided adaptive functionality to existing simulation codes. Mesh adaptivity allows one to minimize both discretization error and number of degrees of freedom live during the simulation, as well as enabling moving object and evolving geometry simulations. Omega_h will do this for you in a way that is fast, memory-efficient, and portable across many different architectures, including NVIDIA GPUs.", + "laborHours": 35826.4, + "languages": [], + "name": "Omega_h", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SNLComputation/omega_h", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Omics_Metadata_Management_Software_v._1__OMMS_.json b/agency-indexes/DoE/Omics_Metadata_Management_Software_v._1__OMMS_.json new file mode 100644 index 00000000..3339cb4d --- /dev/null +++ b/agency-indexes/DoE/Omics_Metadata_Management_Software_v._1__OMMS_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Our application, the Omics Metadata Management Software (OMMS), answers both needs, empowering experimentalists to generate intuitive, consistent metadata, and to perform bioinformatics analyses and information management tasks via a simple and intuitive web-based interface. Several use cases with short-read sequence datasets are provided to showcase the full functionality of the OMMS, from metadata curation tasks, to bioinformatics analyses and results management and downloading. The OMMS can be implemented as a stand alone-package for individual laboratories, or can be configured for web-based deployment supporting geographically dispersed research teams. Our software was developed with open-source bundles, is flexible, extensible and easily installed and run by operators with general system administration and scripting language literacy.", + "homepageURL": "http://omms.sandia.gov", + "laborHours": 0.0, + "name": "Omics Metadata Management Software v. 1 (OMMS)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://omms.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Omics_Mock_Generator_Library__OMG__v0.1.1.json b/agency-indexes/DoE/Omics_Mock_Generator_Library__OMG__v0.1.1.json new file mode 100644 index 00000000..e83b96b0 --- /dev/null +++ b/agency-indexes/DoE/Omics_Mock_Generator_Library__OMG__v0.1.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-02-17", + "metadataLastUpdated": "2021-02-17" + }, + "description": "The Omics Mock Generator (OMG) library is used to provide the synthetic multiomics data needed to test the computational tools for bioengineering metabolic models. Since experimental multiomics data is expensive and non-trivial to produce, OMG provides a quick and easy way to produce large amounts of multiomics data that are based on plausible metabolic assumptions.", + "laborHours": 0.0, + "languages": [], + "name": "Omics Mock Generator Library (OMG) v0.1.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AgileBioFoundry/multiomicspaper", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ompparser.json b/agency-indexes/DoE/Ompparser.json new file mode 100644 index 00000000..16b86069 --- /dev/null +++ b/agency-indexes/DoE/Ompparser.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-11", + "metadataLastUpdated": "2019-12-11" + }, + "description": "ompparser is a standalone and unified OpenMP parser, which is motivated by the facts that:\n\n1) The differences in terms of syntax and semantics of OpenMP constructs between C/C++ and Fortran\nare minor.\n\n2) Current OpenMP compilers often develop their own parsers, which represent redundant work.\n\nThe features of ompparser include:\n\n1) ompparser can be used standalone for static source code analysis, e.g. tools for semantics checking or similarity analysis between C/C++ and Fortran programs\n\n2) omppaser can be integrated into an OpenMP compiler implementation can reduce the development efforts, and there is no need to create and maintain two separate parsers for C/C++ and Fortran.\n\n3) ompparser provides a complete reference OpenMP grammar in the Backus-Naur Form that formally describes all the latest OpenMP language constructs.\n\nThis will help users understand the rules and restriction of the OpenMP standard, which no longer contains a reference grammar in its recent versions.\n", + "laborHours": 3769.6, + "languages": [], + "name": "Ompparser", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/passlab/ompparser", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OntologyRelations.json b/agency-indexes/DoE/OntologyRelations.json new file mode 100644 index 00000000..a1361f8f --- /dev/null +++ b/agency-indexes/DoE/OntologyRelations.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-21", + "metadataLastUpdated": "2020-08-21" + }, + "description": "A KBase module generated by the KBase SDK.", + "laborHours": 228.0, + "languages": [], + "name": "OntologyRelations", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/OntologyRelations", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ontology_API_for_KBase_using_Relation_Engine.json b/agency-indexes/DoE/Ontology_API_for_KBase_using_Relation_Engine.json new file mode 100644 index 00000000..07e8e9db --- /dev/null +++ b/agency-indexes/DoE/Ontology_API_for_KBase_using_Relation_Engine.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-08", + "metadataLastUpdated": "2020-09-08" + }, + "description": "This is an API for ontology data that queries the relation engine.", + "laborHours": 1094.4, + "languages": [], + "name": "Ontology API for KBase using Relation Engine", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ontology_api", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ontology_Service.json b/agency-indexes/DoE/Ontology_Service.json new file mode 100644 index 00000000..0a4ce56f --- /dev/null +++ b/agency-indexes/DoE/Ontology_Service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "The main functionality of ontology service is to allow the retrieval of ontology term distribution for a given a set of genes and additionally, identifies statistically overrepresented GO terms within given gene sets. Ontology term distribution and enrichment analysis are one of the main functions needed for the Plants Feb. Demo. Currently, this service provides GO annotation for 13 plant genomes (refer to documentation).", + "laborHours": 1322.4, + "languages": [], + "name": "Ontology Service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/ontology_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Open-Source_Ambient-Signal-Based_Inertia_Monitoring_Tool_for_Power_systems_[SWR-25-59].json b/agency-indexes/DoE/Open-Source_Ambient-Signal-Based_Inertia_Monitoring_Tool_for_Power_systems_[SWR-25-59].json new file mode 100644 index 00000000..a58eef23 --- /dev/null +++ b/agency-indexes/DoE/Open-Source_Ambient-Signal-Based_Inertia_Monitoring_Tool_for_Power_systems_[SWR-25-59].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-22", + "metadataLastUpdated": "2025-04-22" + }, + "description": "This script, developed by NREL, implements an inertia estimation algorithm using a sliding window approach. The inertia (H) is estimated based on frequency deviations and active power deviations, utilizing the swing equation from power system dynamics. An example application is provided using the WECC 240-bus system.", + "laborHours": 30.4, + "languages": [ + "Python" + ], + "name": "Open-Source Ambient-Signal-Based Inertia Monitoring Tool for Power systems [SWR-25-59]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Open-Source-Ambient-Signal-Based-Inertia-Monitoring-Tool-for-Power-systems", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenAD.json b/agency-indexes/DoE/OpenAD.json new file mode 100644 index 00000000..a46d7333 --- /dev/null +++ b/agency-indexes/DoE/OpenAD.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "OpenAD is a tool for automatic differentiation (AD) of C/C++ numerical computer programs. For the C/C++ side the entire pipeline is encapsulated in single binary. While the C/C++ tool incarnation shares components with OpenAD its development is a separate effort and it was decided to retain for it the name \"ADIC\" which goes back to the previous generation of tools. ", + "homepageURL": "http://www.mcs.anl.gov/OpenAD", + "laborHours": 0.0, + "languages": [], + "name": "OpenAD", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://mercurial.mcs.anl.gov/ad/OpenAD/file/tip/COPYRIGHT#l1", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.mcs.anl.gov/OpenAD", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenCSP_v.1.0.json b/agency-indexes/DoE/OpenCSP_v.1.0.json new file mode 100644 index 00000000..de59c6d2 --- /dev/null +++ b/agency-indexes/DoE/OpenCSP_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08987O\nOpenCSP analyzes and improves the performance of optical mirrors that reflect sunlight and concentrate it onto a receiver. The algorithms in this library analyze the flow of light from an original source\u2014such as the sun\u2014reflecting off one or more mirrors, and onto a receiver, optical screen, or camera. OpenCSP also analyzes optical systems using other techniques, such as shape or slope comparison. The software calculates aggregate properties of the optical system, such as its efficiency, manufacturing error, pointing control error, expected performance, and other useful parameters. \n\nOpenCSP also includes high-level tools, such as Open SOFAST, a program that obtains high-resolution measurement of CSP mirrors, full heliostats, and other CSP collectors. OpenCSP supports producing meaningful output data to help CSP designers and field operators improve the performance of their systems. OpenCSP also includes classes and functions that support these calculations, including input utilities, analysis output libraries, geometric constraint analysis for drone flight planning, and more. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 40188.8, + "languages": [ + "Python" + ], + "name": "OpenCSP v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/OpenCSP", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenDSS-wrapper__Distribution_System_Co-simulator_with_Distributed_Energy_Resource_Controls_.json b/agency-indexes/DoE/OpenDSS-wrapper__Distribution_System_Co-simulator_with_Distributed_Energy_Resource_Controls_.json new file mode 100644 index 00000000..d67343d6 --- /dev/null +++ b/agency-indexes/DoE/OpenDSS-wrapper__Distribution_System_Co-simulator_with_Distributed_Energy_Resource_Controls_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-28" + }, + "description": "Electric grid transformation with the proliferation of distributed energy resources (DER), such as solar photovoltaic (PV), wind, advanced energy storage technologies, and electric vehicles, and the growing use of communication technologies in both transmission and distribution systems are increasing the need to capture the interactions among these systems. Advanced modeling, control, and simulation tools that can perform co-simulation of electric power systems with other domains become indispensable to accurately model these interactions. To address this need, we have developed a codebase that integrates an electric power distribution system simulator, DER models, and DER controls. The codebase is based on OpenDSS, a distribution system simulator, and an existing open source co-simulation framework called HELICS. The contribution and uniqueness of the proposed codebase is that it tailors the generic HELICS framework specifically for distribution grid-related applications. The codebase includes an OpenDSS wrapper that controls the simulation, implements advanced DER controls, and extracts power flows, voltages, and other power system element information from the the distribution network modeled in OpenDSS. Sample HELICS federates, including a federate for OpenDSS, are provided that can communicate messages through the HELICS interface. Sample federates can be modified and additional HELICS federates can be added by the user depending on their use case requirements. SEE ALSO: https://github.com/NREL/dss-cosim", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "OpenDSS-wrapper (Distribution System Co-simulator with Distributed Energy Resource Controls)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenDSS-wrapper", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenDSSDirect.jl.json b/agency-indexes/DoE/OpenDSSDirect.jl.json new file mode 100644 index 00000000..136c57be --- /dev/null +++ b/agency-indexes/DoE/OpenDSSDirect.jl.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-02-11", + "metadataLastUpdated": "2019-02-11" + }, + "description": "OpenDSSDirect.jl is a cross-platform Julia package implements a \"direct\" library interface to OpenDSS using dss_capi. OpenDSS is an open-source distribution system simulator. See OpenDSSDirect.py for a similar package in Julia.\n\nThis package is now available for Windows, Mac, and Linux.", + "laborHours": 7022.4, + "languages": [ + "Julia" + ], + "name": "OpenDSSDirect.jl", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dss-extensions/OpenDSSDirect.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenDSSDirect.py.json b/agency-indexes/DoE/OpenDSSDirect.py.json new file mode 100644 index 00000000..1f3a7a04 --- /dev/null +++ b/agency-indexes/DoE/OpenDSSDirect.py.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-09-03" + }, + "description": "A Python direct-mode interface to OpenDSS, a distribution system simulator for electric power systems.", + "laborHours": 8238.4, + "languages": [ + "Python" + ], + "name": "OpenDSSDirect.py", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dss-extensions/OpenDSSDirect.py", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenLorenz.json b/agency-indexes/DoE/OpenLorenz.json new file mode 100644 index 00000000..d88ec509 --- /dev/null +++ b/agency-indexes/DoE/OpenLorenz.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "OpenLorenz is the open source version of the Lorenz suite of tools developed at Lawrence Livermore National Laboratory. The goal of Lorenz is to use modern web technologies to make HPC easier.", + "laborHours": 140873.6, + "languages": [], + "name": "OpenLorenz", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/OpenLorenz", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenMC.json b/agency-indexes/DoE/OpenMC.json new file mode 100644 index 00000000..ec9fd67d --- /dev/null +++ b/agency-indexes/DoE/OpenMC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "OpenMC is an open source, community-developed framework for performing Monte Carlo particle transport calculations.It is capable of simulating neutron and photon transport below ~50 MeV and also includes a model for bremsstrahlung\nproduction of photons by electrons/positrons. Fixed source, k-eigenvalue, and subcritical multiplication problems can be\nsolved. Problem geometries can be modeled either using constructive solid geometry or a CAD representation. A flexible and efficient tally system enables a wide variety of physical quantities to be tallied and analyzed. OpenMC can run in\nparallel using a hybrid MPI and OpenMP programming model and has been extensively tested on leadership class supercomputers. A built-in Bateman equation solver enables the modeling of material composition changes due to\nirradiation. One of the unique features of OpenMC is its rich, extensible Python and C/C++ programming interfaces that enable programming pre- and post-processing, multigroup cross section generation, workflow automation, multiphysics\ncoupling, and the visualization of geometry and tally results. In addition to the core Monte Carlo transport solver and associated APIs, OpenMC includes a Python-based nuclear data interface that enables power users to inspect, modify,and perform various types of nuclear data processing on ENDF, ACE, and OpenMC\u00bfs native HDF5 files", + "laborHours": 0.0, + "languages": [], + "name": "OpenMC", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openmc-dev/openmc", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenMPI.json b/agency-indexes/DoE/OpenMPI.json new file mode 100644 index 00000000..070ddf9e --- /dev/null +++ b/agency-indexes/DoE/OpenMPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "The Open MPI Project is an open source Message Passing Interface implementation that is developed and maintained by a consortium of academic, research, and industry partners. Open MPI is therefore able to combine the expertise, technologies, and resources from all across the High Performance Computing community in order to build the best MPI library available. Open MPI offers advantages for system and software vendors, application developers and computer science researchers.", + "laborHours": 454890.4, + "languages": [], + "name": "OpenMPI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/open-mpi/ompi/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/open-mpi/ompi", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenMP_4.5_Validation_and_Verification_Suite.json b/agency-indexes/DoE/OpenMP_4.5_Validation_and_Verification_Suite.json new file mode 100644 index 00000000..9a491ff0 --- /dev/null +++ b/agency-indexes/DoE/OpenMP_4.5_Validation_and_Verification_Suite.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "OpenMP, a directive-based programming API, introduce directives for accelerator devices that programmers are starting to use more frequently in production codes. To make sure OpenMP directives work correctly across architectures, it is critical to have a mechanism that tests for an implementation's conformance to the OpenMP standard. This testing process can uncover ambiguities in the OpenMP specification, which helps compiler developers and users make a better use of the standard. We fill this gap through our validation and verification test suite that focuses on the offload directives available in OpenMP 4.5.", + "laborHours": 12479.2, + "languages": [ + "C/C++/Fortran" + ], + "name": "OpenMP 4.5 Validation and Verification Suite", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/crpl_cisc/sollve_vv", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenMP_4.5_and_CUDA_C++_and_FORTRAN_code_samples.json b/agency-indexes/DoE/OpenMP_4.5_and_CUDA_C++_and_FORTRAN_code_samples.json new file mode 100644 index 00000000..06276751 --- /dev/null +++ b/agency-indexes/DoE/OpenMP_4.5_and_CUDA_C++_and_FORTRAN_code_samples.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-03", + "metadataLastUpdated": "2019-04-03" + }, + "description": "Brief Description for Public Release:\nA collection of general code samples demonstrating issues encountered with using OpenMP4.5 (and some CUDA) during efforts to port codes to a GPU platform using IBM XL. These independent examples include both C++ and FORTRAN language usage, along with attempts to use OpenMP and CUDA in an interoperable manner. This suite of code samples is meant to supplement the examples provided by openmp.org at https://github.com/OpenMP/Examples, especially in regards to FORTRAN language support and OpenMP/CUDA interoperability.", + "laborHours": 2158.4, + "languages": [], + "name": "OpenMP 4.5 and CUDA C++ and FORTRAN code samples", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/FGPU", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenMSI_Arrayed_Analysis_Tools__OMAAT__v2.0.json b/agency-indexes/DoE/OpenMSI_Arrayed_Analysis_Tools__OMAAT__v2.0.json new file mode 100644 index 00000000..213539c4 --- /dev/null +++ b/agency-indexes/DoE/OpenMSI_Arrayed_Analysis_Tools__OMAAT__v2.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-04-29", + "metadataLastUpdated": "2019-04-30" + }, + "description": "Mass spectrometry (MS) is an analytical technique that enables all chemical species within a complex mixture to be resolved and identified based on their mass:charge ratio. MS is an increasingly important tool in life science research and development because it can resolve or separate small molecules, peptides, lipids, proteins, biopolymers and fragments of all of these structures. Unfortunately, the use of MS has been limited for lack of software tools to visualize, manipulate, store and transfer MS data. Ben Bowen, Oliver Ruebel and colleagues made a huge advance on the resolution of these limitations with the invention of \"OpenMSI\" (#2013-004), a computational method that makes the handling of these very large files (up to 50 Tb) much easier, especially for scientists with limited background in bioinformatics or sophisticated software applications of the type needed to handle such data files. \n\nWith the OpenMSI Arrayed Analysis Tool (OMAAT, #2016-188) invention, the authors take MS data analysis one step further by providing tolls for automatic sample position optimization and ion selection. Even though sample deposition technologies have improved greatly, there is always the chance of encountering outliers in a predefined roster, especially in very large sample sets. Manual curation of the data would be extremely time consuming, so the inventors have included an algorithm that automatically finds the outliers. OMAAT is written in Python with accompanying Jupyter (formerly iPython) notebook and is fully integrated with OpenMSI.", + "laborHours": 623.2, + "languages": [], + "name": "OpenMSI Arrayed Analysis Tools (OMAAT) v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/biorack/omaat/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biorack/omaat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenMxP-Opensource_Mixed_Precision_Computing.json b/agency-indexes/DoE/OpenMxP-Opensource_Mixed_Precision_Computing.json new file mode 100644 index 00000000..a53385e0 --- /dev/null +++ b/agency-indexes/DoE/OpenMxP-Opensource_Mixed_Precision_Computing.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "luh1@ornl.gov" + }, + "date": { + "created": "2023-03-15", + "metadataLastUpdated": "2023-03-15" + }, + "description": "This is an opensource library for benchmarking the system's GPU mixed precision capabilities. The software calculates solution of the system of linear equation in 64bit accuracy using mixed precision techniques and iterative refinement. Original benchmark designed is done by ICL, and it is name HPL-MxP (HPL-AI)", + "laborHours": 0.0, + "languages": [ + "C++", + "C" + ], + "name": "OpenMxP-Opensource Mixed Precision Computing", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/at-aaims/openMxP", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OpenOA\342\204\242,_FKA:_Wind_Plant_Performance_Project__WP3__Benchmarking.json" "b/agency-indexes/DoE/OpenOA\342\204\242,_FKA:_Wind_Plant_Performance_Project__WP3__Benchmarking.json" new file mode 100644 index 00000000..bd49a19e --- /dev/null +++ "b/agency-indexes/DoE/OpenOA\342\204\242,_FKA:_Wind_Plant_Performance_Project__WP3__Benchmarking.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-23", + "metadataLastUpdated": "2023-05-05" + }, + "description": "This library provides a framework for working with large timeseries data from wind plants, such as SCADA. Its development has been motivated by the WP3 Benchmarking (PRUF) project, which aims to provide a reference implementation for plant-level performance assessment.", + "laborHours": 1337.6, + "languages": [ + "Python" + ], + "name": "OpenOA\u2122, FKA: Wind Plant Performance Project (WP3) Benchmarking", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenOA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.0rc2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenRES.json b/agency-indexes/DoE/OpenRES.json new file mode 100644 index 00000000..9537373d --- /dev/null +++ b/agency-indexes/DoE/OpenRES.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-10", + "metadataLastUpdated": "2019-04-10" + }, + "description": "The OpenRES is an open-source library of intermittent energy resources developed in the JModelica.org platform, and provides capability for performing long-term power grid dynamic simulation with renewable ancillary services (e.g., load ramp, frequency and voltage regulation).", + "laborHours": 45.6, + "languages": [], + "name": "OpenRES", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/OpenRES", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenSHMEM_over_MPI-3.json b/agency-indexes/DoE/OpenSHMEM_over_MPI-3.json new file mode 100644 index 00000000..82d751d6 --- /dev/null +++ b/agency-indexes/DoE/OpenSHMEM_over_MPI-3.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OpenSHMEM is a community effort to unifyt and standardize the SHMEM programming model. MPI (Message Passing Interface) is a well-known community standard for parallel programming using distributed memory. The most recen t release of MPI, version 3.0, was designed in part to support programming models like SHMEM.OSHMPI is an implementation of the OpenSHMEM standard using MPI-3 for the Linux operating system. It is the first implementation of SHMEM over MPI one-sided communication and has the potential to be widely adopted due to the portability and widely availability of Linux and MPI-3. OSHMPI has been tested on a variety of systems and implementations of MPI-3, includingInfiniBand clusters using MVAPICH2 and SGI shared-memory supercomputers using MPICH. Current support is limited to Linux but may be extended to Apple OSX if there is sufficient interest. The code is opensource via https://github.com/jeffhammond/oshmpi", + "laborHours": 15291.2, + "name": "OpenSHMEM over MPI-3", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeffhammond/oshmpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenSM_Monitoring_System.json b/agency-indexes/DoE/OpenSM_Monitoring_System.json new file mode 100644 index 00000000..195f1d44 --- /dev/null +++ b/agency-indexes/DoE/OpenSM_Monitoring_System.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The OpenSM Monitoring System includes a collection of diagnostic and monitoring tools for use on Infiniband networks. The information this system gathers is obtained from a service, which in turn is obtained directly from the OpenSM subnet manager.", + "laborHours": 34899.2, + "name": "OpenSM Monitoring System", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/meier/opensm-smt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenSSO_Project_Patches.json b/agency-indexes/DoE/OpenSSO_Project_Patches.json new file mode 100644 index 00000000..efe26fda --- /dev/null +++ b/agency-indexes/DoE/OpenSSO_Project_Patches.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "These are patches to Sun Microsystems open source OpenSSO project to fix various bugs and incorporate changes for Sandia and NNSA to use the product including fixes to improve OpenSSO's authentication and authorization abilities. These fixes will then by incorporated by Sun into their Sun Access Manager product, which is used by various DOE/NNSA plants and labs. Having Sun maintain these changes will relieve SNL and DOE from the cost of maintaining the changes themselves.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "OpenSSO Project Patches", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenSoC_Fabric.json b/agency-indexes/DoE/OpenSoC_Fabric.json new file mode 100644 index 00000000..c612ca2b --- /dev/null +++ b/agency-indexes/DoE/OpenSoC_Fabric.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Recent advancements in technology scaling have shown a trend towards greater integration with large-scale chips containing thousands of processors connected to memories and other I/O devices using non-trivial network topologies. Software simulation proves insufficient to study the tradeoffs in such complex systems due to slow execution time, whereas hardware RTL development is too time-consuming. We present OpenSoC Fabric, an on-chip network generation infrastructure which aims to provide a parameterizable and powerful on-chip network generator for evaluating future high performance computing architectures based on SoC technology. OpenSoC Fabric leverages a new hardware DSL, Chisel, which contains powerful abstractions provided by its base language, Scala, and generates both software (C++) and hardware (Verilog) models from a single code base. The OpenSoC Fabric2 infrastructure is modeled after existing state-of-the-art simulators, offers large and powerful collections of configuration options, and follows object-oriented design and functional programming to make functionality extension as easy as possible.", + "laborHours": 2888.0, + "name": "OpenSoC Fabric", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LBL-CoDEx/OpenSoCFabric/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBL-CoDEx/OpenSoCFabric", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenStudio-Occupant-Variability-Gem_v1.0.json b/agency-indexes/DoE/OpenStudio-Occupant-Variability-Gem_v1.0.json new file mode 100644 index 00000000..3e9041d4 --- /dev/null +++ b/agency-indexes/DoE/OpenStudio-Occupant-Variability-Gem_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-06-11", + "metadataLastUpdated": "2020-06-11" + }, + "description": "This gem contains methods to introduce occupant-related variability to extend core OpenStudio SDK. The goal of introducing the variability is to improve the assumptions related to stochastic occupant movement, occupant-related lighting and electric equipment, and thermostat set points schedules in traditional OpenStudio and EnergyPlus models.", + "laborHours": 216098.4, + "languages": [], + "name": "OpenStudio-Occupant-Variability-Gem v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/OpenStudio-Occupant-Variability-Gem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenStudio-Variability-Gem_v1.0.json b/agency-indexes/DoE/OpenStudio-Variability-Gem_v1.0.json new file mode 100644 index 00000000..19041788 --- /dev/null +++ b/agency-indexes/DoE/OpenStudio-Variability-Gem_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-06-11", + "metadataLastUpdated": "2020-06-11" + }, + "description": "This gem contains methods to introduce variability to extend core OpenStudio SDK. The term \"variability\" refers to changes in building systems efficiency, operation, or controls, which are non-routine events.", + "laborHours": 597390.4, + "languages": [], + "name": "OpenStudio-Variability-Gem v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/OpenStudio-Variability-Gem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenStudio.json b/agency-indexes/DoE/OpenStudio.json new file mode 100644 index 00000000..c9495859 --- /dev/null +++ b/agency-indexes/DoE/OpenStudio.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "OpenStudio is a cross-platform collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance.\u00a0http://openstudio.nrel.gov/\n", + "laborHours": 1326808.0, + "name": "OpenStudio", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-BTRIC/OpenStudio/blob/develop/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-BTRIC/OpenStudio", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenStudio_Occupant-centric_KPIs_Reporting_Measure_v1.0.json b/agency-indexes/DoE/OpenStudio_Occupant-centric_KPIs_Reporting_Measure_v1.0.json new file mode 100644 index 00000000..28ca5db4 --- /dev/null +++ b/agency-indexes/DoE/OpenStudio_Occupant-centric_KPIs_Reporting_Measure_v1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-07", + "metadataLastUpdated": "2021-03-07" + }, + "description": "This is an OpenStudio measure that calculates and reports the occupant-centric key performance indicators (KPIs) for evaluating building energy performance from occupant-centric perspectives. The measure automatically calculate the KPIs in the following categories: (1) visual & lighting, (2) thermal (3) air quality, and (4) others.", + "laborHours": 0.0, + "languages": [], + "name": "OpenStudio Occupant-centric KPIs Reporting Measure v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/OpenStudio-Occupant-KPIs-Reporting", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenStudio_System-level_KPI_Reporting_Measure_v1.0.json b/agency-indexes/DoE/OpenStudio_System-level_KPI_Reporting_Measure_v1.0.json new file mode 100644 index 00000000..b7ce3905 --- /dev/null +++ b/agency-indexes/DoE/OpenStudio_System-level_KPI_Reporting_Measure_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-16", + "metadataLastUpdated": "2021-03-16" + }, + "description": "This is a OpenStudio measure that calculates and reports the system-level key performance indicators (KPIs) for evaluating building energy performance at the system level. The systems are defined by the service it provides in commercial buildings, which include (1) lighting, (2) Miscellaneous Electric Loads (MELs), (3) Heating, Ventilation and Air Conditioning (HVAC), and (4) Service Water Heating (SWH).", + "homepageURL": "https://bcl.nrel.gov/node/85162", + "laborHours": 0.0, + "languages": [], + "name": "OpenStudio System-level KPI Reporting Measure v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bcl.nrel.gov/node/85162", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OpenStudio\302\256-ERI__Energy_Rating_Index__ERI__Workflow__[SWR-18-72]_1.7.0_Released_12_14_2023.json" "b/agency-indexes/DoE/OpenStudio\302\256-ERI__Energy_Rating_Index__ERI__Workflow__[SWR-18-72]_1.7.0_Released_12_14_2023.json" new file mode 100644 index 00000000..fa7468b2 --- /dev/null +++ "b/agency-indexes/DoE/OpenStudio\302\256-ERI__Energy_Rating_Index__ERI__Workflow__[SWR-18-72]_1.7.0_Released_12_14_2023.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-02-09", + "metadataLastUpdated": "2024-03-04" + }, + "description": "The OpenStudio\u00ae-ERI project allows calculating an Energy Rating Index (ERI) using the Department of Energy's open-source OpenStudio\u00ae/EnergyPlus\u00ae simulation platform. The building description is provided in an HPXML file format. \nThe project supports: \n- ANSI/RESNET/ICC 301\u00a9 Standard for the Calculation and Labeling of the Energy Performance of Dwelling and Sleeping Units using an Energy Rating Index \n- ENERGY STAR Certification System for Homes and Apartments Using an ERI Compliance Path \n- IECC ERI Compliance Alternative (Section R406) \n- DOE ZERH Certification Using an ERI Compliance Path For more information on running simulations, generating HPXML files, etc., please visit the documentation at https://openstudio-eri.readthedocs.io/en/latest/", + "laborHours": 249295.2, + "languages": [ + "Ruby" + ], + "name": "OpenStudio\u00ae-ERI (Energy Rating Index (ERI) Workflow) [SWR-18-72] 1.7.0 Released 12/14/2023", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-ERI", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.7.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OpenStudio\302\256_AWS_Gem_[SWR-07-40].json" "b/agency-indexes/DoE/OpenStudio\302\256_AWS_Gem_[SWR-07-40].json" new file mode 100644 index 00000000..3b1e55e6 --- /dev/null +++ "b/agency-indexes/DoE/OpenStudio\302\256_AWS_Gem_[SWR-07-40].json" @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "OpenStudio\u00ae AWS uses the OpenStudio AWS ruby class to launch a server and multiple workers for doing OpenStudio\u00ae/EnergyPlus\u00ae Analyses using Amazon AWS/EC2.", + "laborHours": 1261.6, + "languages": [ + "shell", + "Ruby" + ], + "name": "OpenStudio\u00ae AWS Gem [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-aws-gem/blob/develop/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-aws-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.8" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OpenStudio\302\256_Analysis_Gem_[SWR-07-40].json" "b/agency-indexes/DoE/OpenStudio\302\256_Analysis_Gem_[SWR-07-40].json" new file mode 100644 index 00000000..aff7c43d --- /dev/null +++ "b/agency-indexes/DoE/OpenStudio\302\256_Analysis_Gem_[SWR-07-40].json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "The OpenStudio\u00ae Analysis Gem is used to communicate files to the OpenStudio Distributed Analysis. The purpose of this gem is to generate the analysis.json file, analysis.zip, and communicate with the server to upload the simulations. This gem does not create the cluster. To manage cloud resources use the OpenStudio Analysis Framework Helm Charts.", + "laborHours": 7767.2, + "languages": [ + "Ruby" + ], + "name": "OpenStudio\u00ae Analysis Gem [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-analysis-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.3.5" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OpenStudio\302\256_Energy_Rating_Index__ERI__Workflow__SWR-18-72_.json" "b/agency-indexes/DoE/OpenStudio\302\256_Energy_Rating_Index__ERI__Workflow__SWR-18-72_.json" new file mode 100644 index 00000000..c659f724 --- /dev/null +++ "b/agency-indexes/DoE/OpenStudio\302\256_Energy_Rating_Index__ERI__Workflow__SWR-18-72_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-02-28", + "metadataLastUpdated": "2024-02-09" + }, + "description": "The OpenStudio\u00ae-ERI project allows calculating an Energy Rating Index (ERI) using the Department of Energy's open-source OpenStudio\u00ae/EnergyPlus\u00ae simulation platform. The building description is provided in an HPXML file format. The project supports: - ANSI/RESNET/ICC 301\u00a9 Standard for the Calculation and Labeling of the Energy Performance of Dwelling and Sleeping Units using an Energy Rating Index - ENERGY STAR Certification System for Homes and Apartments Using an ERI Compliance Path - IECC ERI Compliance Alternative (Section R406) - DOE ZERH Certification Using an ERI Compliance Path For more information on running simulations, generating HPXML files, etc., please visit the documentation at https://openstudio-eri.readthedocs.io/en/latest/", + "laborHours": 249295.2, + "languages": [ + "Ruby" + ], + "name": "OpenStudio\u00ae Energy Rating Index (ERI) Workflow (SWR-18-72)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-ERI", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.5.2" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OpenStudio\302\256_Fault_Models_Gem_[SWR-15-23].json" "b/agency-indexes/DoE/OpenStudio\302\256_Fault_Models_Gem_[SWR-15-23].json" new file mode 100644 index 00000000..a1f7805a --- /dev/null +++ "b/agency-indexes/DoE/OpenStudio\302\256_Fault_Models_Gem_[SWR-15-23].json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-03-04" + }, + "description": "Overview of the OpenStudio\u00ae Fault Models Gem: Creating a comprehensive library of OpenStudio\u00ae fault models.\nFeatures:\n - Physics-based fault impact simulation within the capability of EnergyPlus\u00ae/OpenStudio\u00ae\n- Fault intensity implementation simulating how severe faults are (e.g., how much portion is fouled in the condenser heat exchanger) and estimating the impact of a fault in different fault intensities. \n- Fault evolution implementation simulating evolving/increasing fault intensity through certain period of time. \nFuture goals:\n- what are common/typical faults in different sample spaces (e.g., HVAC system type, building operation type, building location etc.)? \n- how often (e.g., incidence and prevalence) faults occur in different sample spaces (e.g., HVAC system type, building operation type, building location etc.)?", + "laborHours": 0.0, + "languages": [ + "Ruby", + "HTML" + ], + "name": "OpenStudio\u00ae Fault Models Gem [SWR-15-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-fault-measure-gem/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-fault-measure-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OpenStudio\302\256_HPXML_workflow_[SWR-25-13].json" "b/agency-indexes/DoE/OpenStudio\302\256_HPXML_workflow_[SWR-25-13].json" new file mode 100644 index 00000000..aabfd50d --- /dev/null +++ "b/agency-indexes/DoE/OpenStudio\302\256_HPXML_workflow_[SWR-25-13].json" @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-25", + "metadataLastUpdated": "2024-11-25" + }, + "description": "OpenStudio-HPXML allows running residential EnergyPlus\u2122 simulations using an HPXML file for the building description. It is intended to be used by user interfaces or other automated software workflows that automatically produce the HPXML file.\n\nOpenStudio-HPXML can accommodate a wide range of different building technologies and geometries. End-to-end simulations typically run in 3-10 seconds, depending on complexity, computer platform and speed, etc.\n\nFor more information on running simulations, generating HPXML files with the appropriate inputs to run EnergyPlus, etc., please visit the documentation linked below.\n\nhttps://openstudio-hpxml.readthedocs.io/en/latest", + "laborHours": 418608.0, + "languages": [ + "Python", + "Ruby" + ], + "name": "OpenStudio\u00ae HPXML workflow [SWR-25-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-HPXML", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.9.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OpenStudio\302\256_Resources_[SWR-07-40].json" "b/agency-indexes/DoE/OpenStudio\302\256_Resources_[SWR-07-40].json" new file mode 100644 index 00000000..987a0d92 --- /dev/null +++ "b/agency-indexes/DoE/OpenStudio\302\256_Resources_[SWR-07-40].json" @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "This repository includes a suite of simulation tests that can be used to validate new OpenStudio\u00ae model objects as well as ensure that objects continue to work after they are added. Each new OpenStudio Model object should ideally have two simulation tests associated with it: - a Ruby one which verifies the Ruby API and, - an OSM one that verifies the OSM file can be loaded with future versions of OpenStudio. Both tests should result in a simulation-ready OpenStudio Model that can be simulated using EnergyPlus\u00ae. Both of these tests are located in the /model/simulationtests directory, the easiest way to add a new test is to find a related existing test and modify it. When new tests are added they must be added to the model_tests.rb file.", + "laborHours": 1593948.0, + "languages": [ + "Ruby", + "html", + "jupyter notebook" + ], + "name": "OpenStudio\u00ae Resources [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-resources/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-resources", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OpenStudio\302\256_Server_[SWR-07-40].json" "b/agency-indexes/DoE/OpenStudio\302\256_Server_[SWR-07-40].json" new file mode 100644 index 00000000..103977cf --- /dev/null +++ "b/agency-indexes/DoE/OpenStudio\302\256_Server_[SWR-07-40].json" @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "OpenStudio\u00ae Server is a web application and distributed computing tool, which is the backbone of the OpenStudio Analysis Framework (OSAF). It is intended to make parametric analysis of building energy models accessible to architects, engineers, and designers via the OpenStudio PAT GUI or the OpenStudio Analysis Gem. OpenStudio Server analyses are defined by PAT projects or OSA's. Each analysis may include many OpenStudio simulations, as determined by project configuration.", + "laborHours": 42803.2, + "languages": [ + "R", + "Shell", + "HTML", + "Ruby", + "SCSS", + "JavaScript" + ], + "name": "OpenStudio\u00ae Server [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-server/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-server", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "3.7.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OpenStudio\302\256_Standards_[SWR-07-40].json" "b/agency-indexes/DoE/OpenStudio\302\256_Standards_[SWR-07-40].json" new file mode 100644 index 00000000..984cb041 --- /dev/null +++ "b/agency-indexes/DoE/OpenStudio\302\256_Standards_[SWR-07-40].json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2024-02-09" + }, + "description": "OpenStudio\u00ae Standards is a Ruby Gem library that extends the OpenStudio SDK. It has four main use-cases:\n\nProvide higher level methods to help BEM users and developers to create OpenStudio models from existing geometry, or programmatically generated geometry\nCreate typical building models in OpenStudio format\nCreate a code baseline model from a proposed model\nCheck a model against a code/standard\nopenstudio-standards previously supported making the DOE/PNNL prototype buildings in OpenStudio format. This has since been deprecated, as the DOE/PNNL prototypes are intended for specific code comparisons under the Energy Policy Act and are not intended to accurately represent typical existing or new buildings. While openstudio-standards still creates typical buildings, these are not the same as the DOE/PNNL prototypes.", + "laborHours": 16303611.2, + "languages": [ + "Ruby" + ], + "name": "OpenStudio\u00ae Standards [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/openstudio-standards", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/OpenStudio\302\256_Workflow_Gem_[SWR-07-40].json" "b/agency-indexes/DoE/OpenStudio\302\256_Workflow_Gem_[SWR-07-40].json" new file mode 100644 index 00000000..bd01a602 --- /dev/null +++ "b/agency-indexes/DoE/OpenStudio\302\256_Workflow_Gem_[SWR-07-40].json" @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-02-09" + }, + "description": "This branch is the development branch for the OpenStudio\u00ae workflow gem.", + "laborHours": 216645.6, + "languages": [ + "Ruby", + "HTML" + ], + "name": "OpenStudio\u00ae Workflow Gem [SWR-07-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-workflow-gem/blob/develop/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-workflow-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.3.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenTurbine_[SWR-23-07].json b/agency-indexes/DoE/OpenTurbine_[SWR-23-07].json new file mode 100644 index 00000000..22cfde3f --- /dev/null +++ b/agency-indexes/DoE/OpenTurbine_[SWR-23-07].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-11-29", + "metadataLastUpdated": "2023-01-10" + }, + "description": "OpenTurbine is an open-source code designed for the simulation of wind turbine structural dynamics. It is a flexible multi-body dynamics solver wherein the wind turbine is modeled as a collection of beam finite elements, rigid bodies, and constraints. OpenTurbine is equipped with an application programming interface primarily designed for coupling to computational fluid dynamics codes, but it is also suited for coupling to aerodynamics solvers based on blade element momentum theory.", + "laborHours": 0.0, + "languages": [ + "CMake", + "C++" + ], + "name": "OpenTurbine [SWR-23-07]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exawind/openturbine", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OpenWARP.json b/agency-indexes/DoE/OpenWARP.json new file mode 100644 index 00000000..17a4f8de --- /dev/null +++ b/agency-indexes/DoE/OpenWARP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2018-09-12" + }, + "description": "OpenWARP is an open source boundary element simulation tool based on the\u00a0NEMOH code. OpenWARP and NEMOH provide the ability to determine the frequency dependent added mass, radiation damping, and excitation coefficients that describe the behavior of a floating or submerged body in a wave field. These coefficients are widely used in conjunction with the Cummins equation to model the behavior of wave energy conversion devices, ships, offshore platforms, and other floating structures.\n", + "laborHours": 54872.0, + "languages": [], + "name": "OpenWARP", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenWARP", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Open_Energy_Data_Initiative__OpenEDI__-_Open_Data_Access_Tools__OEDI-ODAT__[SWR_20-57].json b/agency-indexes/DoE/Open_Energy_Data_Initiative__OpenEDI__-_Open_Data_Access_Tools__OEDI-ODAT__[SWR_20-57].json new file mode 100644 index 00000000..aebe52aa --- /dev/null +++ b/agency-indexes/DoE/Open_Energy_Data_Initiative__OpenEDI__-_Open_Data_Access_Tools__OEDI-ODAT__[SWR_20-57].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-10-07", + "metadataLastUpdated": "2023-05-08" + }, + "description": "Open Energy Data Initiative (OpenEDI): Advancing Analytics and Research Innovation through Improved Data Access. The Open Energy Data Initiative (OEDI) aims to improve and automate access of high-value energy data sets across the U.S. Department of Energy\u2019s (DOE\u2019s) programs, offices, and national laboratories. Sponsored by the DOE, this platform is being implemented by the National Renewable Energy Laboratory (NREL) to make data actionable and discoverable by researchers and industry to accelerate analysis and advance innovation. Partners at other national laboratories will help utilize the platform for analysis, can be directly involved in determining requirements, and will be resources for providing new datasets that can be shared with the public to expand innovation.", + "laborHours": 20322.4, + "languages": [ + "Python", + "Dockerfile" + ], + "name": "Open Energy Data Initiative (OpenEDI) - Open Data Access Tools (OEDI-ODAT) [SWR 20-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openEDI/open-data-access-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.2.1" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Open_Energy_Data_Initiative_\342\200\223_Systems_Integration__OEDI-SI__f_k_a_GADAL__Grid_Algorithms_and_Data_Analytics_Library__[SWR-22-86].json" "b/agency-indexes/DoE/Open_Energy_Data_Initiative_\342\200\223_Systems_Integration__OEDI-SI__f_k_a_GADAL__Grid_Algorithms_and_Data_Analytics_Library__[SWR-22-86].json" new file mode 100644 index 00000000..d9616d6a --- /dev/null +++ "b/agency-indexes/DoE/Open_Energy_Data_Initiative_\342\200\223_Systems_Integration__OEDI-SI__f_k_a_GADAL__Grid_Algorithms_and_Data_Analytics_Library__[SWR-22-86].json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-02-01", + "metadataLastUpdated": "2023-02-06" + }, + "description": "OEDI-SI (formerly known as GADAL (Grid Algorithms and Data Analytics Library)) provides a library for connecting Algorithms and Datasets in a co-simulation framework can be found at the following URLS: https://github.com/openEDI/GADAL; https://github.com/openEDI/sgidal-example; https://github.com/openEDI/gadal-ieee123", + "laborHours": 0.0, + "languages": [], + "name": "Open Energy Data Initiative \u2013 Systems Integration (OEDI-SI) f/k/a GADAL (Grid Algorithms and Data Analytics Library) [SWR-22-86]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openEDI/gadal-ieee123", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Open_Energy_Information_System_version_2.0.json b/agency-indexes/DoE/Open_Energy_Information_System_version_2.0.json new file mode 100644 index 00000000..95417664 --- /dev/null +++ b/agency-indexes/DoE/Open_Energy_Information_System_version_2.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OpenEIS was created to provide standard methods for authoring, sharing, testing, using, and improving algorithms for operational building energy efficiency with building managers and building owners. OpenEIS is designed as a no-cost/low-cost solution that will propagate the fault detection and diagnostic (FDD) solutions into the marketplace by providing state- of- the-art analytical and diagnostic algorithms. As OpenEIS penetrates the market, demand by control system manufacturers and integrators serving small and medium commercial customers will help push these types of commercial software tool offerings into the broader marketplace.", + "laborHours": 1036123.2, + "name": "Open Energy Information System version 2.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/VOLTTRON/openeis/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/openeis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Open_Facility_Viewer.json b/agency-indexes/DoE/Open_Facility_Viewer.json new file mode 100644 index 00000000..3ba1cf81 --- /dev/null +++ b/agency-indexes/DoE/Open_Facility_Viewer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-19" + }, + "description": "The software Is an application for Oelta3D, QT and OpenSceneGraph, all of which are external open source software.", + "laborHours": 2447.2, + "languages": [], + "name": "Open Facility Viewer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Open-Facility-Viewer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Open_SHMEM_Reference_Implementation.json b/agency-indexes/DoE/Open_SHMEM_Reference_Implementation.json new file mode 100644 index 00000000..36d7c6d7 --- /dev/null +++ b/agency-indexes/DoE/Open_SHMEM_Reference_Implementation.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OpenSHMEM is an effort to create a specification for a standardized API for parallel programming in the Partitioned Global Address Space. Along with the specification the project is also creating a reference implementation of the API. This implementation attempts to be portable, to allow it to be deployed in multiple environments, and to be a starting point for implementations targeted to particular hardware platforms. It will also serve as a springboard for future development of the API.", + "laborHours": 9469.6, + "name": "Open SHMEM Reference Implementation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/openshmem-org/openshmem/blob/master/ACKNOWLEDGEMENT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openshmem-org/openshmem", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Open_Smart_Energy_Gateway__OpenSEG_.json b/agency-indexes/DoE/Open_Smart_Energy_Gateway__OpenSEG_.json new file mode 100644 index 00000000..5f8aa967 --- /dev/null +++ b/agency-indexes/DoE/Open_Smart_Energy_Gateway__OpenSEG_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The Open Smart Energy Gateway (OpenSEG) aims to provide near-real time smart meter data to consumers without the delays or latencies associated with it being transported to the utility data center and then back to the consumer's application. To do this, the gateway queries the local Smart Meter to which it is bound to get energy consumption information at pre-defined intervals (minimum interval is 4 seconds). OpenSEG then stores the resulting data internally for retrieval by an external application.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Open Smart Energy Gateway (OpenSEG)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Open_Source_Code_for_Advanced_Radiation_Simulation.json b/agency-indexes/DoE/Open_Source_Code_for_Advanced_Radiation_Simulation.json new file mode 100644 index 00000000..31080606 --- /dev/null +++ b/agency-indexes/DoE/Open_Source_Code_for_Advanced_Radiation_Simulation.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "OSCARS is a general purpose code for computation of radiation from charged particles in motion.", + "laborHours": 18559.2, + "name": "Open Source Code for Advanced Radiation Simulation", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/dhidas/OSCARS/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dhidas/OSCARS", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Open_Source_High_Fidelity_Modeling_Of_A_Type-5_Wind_Turbine_Drivetrain.json b/agency-indexes/DoE/Open_Source_High_Fidelity_Modeling_Of_A_Type-5_Wind_Turbine_Drivetrain.json new file mode 100644 index 00000000..f194e01f --- /dev/null +++ b/agency-indexes/DoE/Open_Source_High_Fidelity_Modeling_Of_A_Type-5_Wind_Turbine_Drivetrain.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-10-25", + "metadataLastUpdated": "2023-11-08" + }, + "description": "The purpose of this code is to provide a high-fidelity model of Type-5 wind turbine drivetrain for grid integration and transient stability studies. The increasing integration of renewable energy resources in evolving bulk power system (BPS) is impacting the system\u2019s inertia. Type-5 wind turbine generation has the potential to behave like a traditional synchronous generator and can help mitigate the aforementioned impact. A hydraulic torque converter (TC) and gearbox with torque limiting feature are integral parts of a Type-5 wind turbine unit. A generic and high-fidelity model of a Type-5 wind turbine drivetrain is not openly and widely available for grid integration and transient stability studies. This hinders appropriate assessment of Type-5 wind power plant's contribution to the BPS resilience. This work develops and validates a TC model based on those generally used in automobile's transmission system.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Open Source High Fidelity Modeling Of A Type-5 Wind Turbine Drivetrain", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Type_5_Wind_Turbine_Drivetrain", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Open_vSwitch.json b/agency-indexes/DoE/Open_vSwitch.json new file mode 100644 index 00000000..b1c18c92 --- /dev/null +++ b/agency-indexes/DoE/Open_vSwitch.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Open vSwitch is a multilayer software switch licensed under the open source Apache 2 license. Our goal is to implement a production quality switch platform that supports standard management interfaces and opens the forwarding functions to programmatic extension and control. Open vSwitch is well suited to function as a virtual switch in VM environments. In addition to exposing standard control and visibility interfaces to the virtual networking layer, it was designed to support distribution across multiple physical servers. Open vSwitch supports multiple Linux-based virtualization technologies including Xen/XenServer, KVM, and VirtualBox.\n", + "laborHours": 223212.0, + "name": "Open vSwitch", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/ovs", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Operational_Forecasting_of_Induced_Seismicity.json b/agency-indexes/DoE/Operational_Forecasting_of_Induced_Seismicity.json new file mode 100644 index 00000000..ecb41263 --- /dev/null +++ b/agency-indexes/DoE/Operational_Forecasting_of_Induced_Seismicity.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-07", + "metadataLastUpdated": "2023-10-20" + }, + "description": "Operational Forecasting of Induced Seismicity (ORION) is an open-source toolkit developed as part of the US Department of Energy SMART and NRAP programs. ORION is designed to help both expert and non-expert users understand the seismic hazard at a site. This tool analyzes how the seismic hazard evolves during injection of fluid, and can be used to identify potential mitigation strategies for observed or forecasted seismic activity. ORION is built using Python, and has an optional GUI where users can easily configure model parameters, evaluate temporal and spatial forecasts, and inspect key data (seismicity, fluid injection, pressure models, etc.).", + "laborHours": 0.0, + "languages": [], + "name": "Operational Forecasting of Induced Seismicity", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NRAP/orion", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "0.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OptML.json b/agency-indexes/DoE/OptML.json new file mode 100644 index 00000000..7322f2a0 --- /dev/null +++ b/agency-indexes/DoE/OptML.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-11-03", + "metadataLastUpdated": "2024-07-30" + }, + "description": "OptML is an open-source Python package that provides modeling and solution capabilities for optimization problems with embedded machine learning models. OptML is a collaborative open-source project that includes advanced algorithms from the academic community for efficient solution of these problems. Sandia contributions to this package include the development of interfaces between these algorithms and Pyomo. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10861 O", + "laborHours": 1155.2, + "languages": [ + "Python" + ], + "name": "OptML", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/OptML", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Optimal_Mitigation_Planning_For_Adversarial_Scenarios.json b/agency-indexes/DoE/Optimal_Mitigation_Planning_For_Adversarial_Scenarios.json new file mode 100644 index 00000000..7d1d901b --- /dev/null +++ b/agency-indexes/DoE/Optimal_Mitigation_Planning_For_Adversarial_Scenarios.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-20", + "metadataLastUpdated": "2025-02-20" + }, + "description": "We propose a generalized framework which performs an optimal partitioning of a limited budget into various\norganizational sectors in order to improve the cybersecurity of a smart device or component in the Cyber Physical Energy\nSystem (CPS). The framework identifies the adversarial threats and possible attack sequences which can be performed to\nexploit cyber vulnerabilities of the component. Thereafter, we formulate an Mixed Integer Linear Programming (MILP)\noptimization problem which aims to evaluate the optimal budget partitions in order to minimize the number of highly likely\nattack sequences. Though we provide results for using the framework in CPES, the proposed methodology can be\nextended for multiple domains with a set of known adversarial and mitigation actions.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 3526.4, + "languages": [], + "name": "Optimal Mitigation Planning For Adversarial Scenarios", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Optimal_Sizing_Tool_for_Battery_Storage_in_Grid_Applications.json b/agency-indexes/DoE/Optimal_Sizing_Tool_for_Battery_Storage_in_Grid_Applications.json new file mode 100644 index 00000000..5ebc6efc --- /dev/null +++ b/agency-indexes/DoE/Optimal_Sizing_Tool_for_Battery_Storage_in_Grid_Applications.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The battery storage sizing tool developed at Pacific Northwest National Laboratory can be used to evaluate economic performance and determine the optimal size of battery storage in different use cases considering multiple power system applications. The considered use cases include i) utility owned battery storage, and ii) battery storage behind customer meter. The power system applications from energy storage include energy arbitrage, balancing services, T&D deferral, outage mitigation, demand charge reduction etc. Most of existing solutions consider only one or two grid services simultaneously, such as balancing service and energy arbitrage. ES-select developed by Sandia and KEMA is able to consider multiple grid services but it stacks the grid services based on priorities instead of co-optimization. This tool is the first one that provides a co-optimization for systematic and local grid services.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Optimal Sizing Tool for Battery Storage in Grid Applications", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/OptimiSM_v.0.0.1.json b/agency-indexes/DoE/OptimiSM_v.0.0.1.json new file mode 100644 index 00000000..5801fbe4 --- /dev/null +++ b/agency-indexes/DoE/OptimiSM_v.0.0.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2022-10-05" + }, + "description": "SAND2021-15062 O OptimiSM is a library for solving solid mechanics problems and for rapid prototyping of computational solid mechanics research ideas. It was originally created to facilitate research and development of algorithms for contact mechanics. It is a realization of a philosophy that problems can be represented with variational least-action principles, even when there is history-dependent material behavior and contact. This opens the door to using powerful methods from non-convex optimization for solutions. The code was successful in its original purpose, but along the way, the authors realized that it could be of general use to the computational solid mechanics research community as an R&D platform. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "OptimiSM v.0.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/optimism", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Optimization,_Inference_and_Learning_for_Advanced_Networks.json b/agency-indexes/DoE/Optimization,_Inference_and_Learning_for_Advanced_Networks.json new file mode 100644 index 00000000..7dd0e294 --- /dev/null +++ b/agency-indexes/DoE/Optimization,_Inference_and_Learning_for_Advanced_Networks.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-04-10", + "metadataLastUpdated": "2018-04-10" + }, + "description": "This piece of software aims at providing an implementation of methods to perform efficient optimization, probabilistic inference and model selection and learning for various type of networked systems. The software contains a suite of methods and functions that: 1) perform probabilistic inference and random sampling on networked models 2) select or learn networked models from data 3) solve optimization tasks with a networked structure Network models that are supported by these features include, but are not limited to, factor graphs and Markov random fields such as Ising models, Potts models, p-spins models, Gaussian random fields and restricted Boltzmann machine.", + "laborHours": 440.8, + "name": "Optimization, Inference and Learning for Advanced Networks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/GraphicalModelLearning.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Optimization_Models_For_Drone_Deployment.json b/agency-indexes/DoE/Optimization_Models_For_Drone_Deployment.json new file mode 100644 index 00000000..44142f58 --- /dev/null +++ b/agency-indexes/DoE/Optimization_Models_For_Drone_Deployment.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-09-30", + "metadataLastUpdated": "2023-10-23" + }, + "description": "Model that supports drone deployment. Analysis on speed, package weight, energy consumption, # of drones, and battery replacements. This software developed tools for drone deployment optimization for direct delivery by introducing a new model that presents new insights addressing real-life issues. Specifically, this developed a new mixed-integer programming model with both time windows and battery replacements.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Optimization Models For Drone Deployment", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/OMDD", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Optimization_Of_Real-time_Capacity_Allocation.json b/agency-indexes/DoE/Optimization_Of_Real-time_Capacity_Allocation.json new file mode 100644 index 00000000..e6fbcd75 --- /dev/null +++ b/agency-indexes/DoE/Optimization_Of_Real-time_Capacity_Allocation.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-08-15", + "metadataLastUpdated": "2023-08-15" + }, + "description": "ORCA is a modeling toolset to accelerate real-time control and optimization of digital twins, including virtual models of facilities, physical facilities, and interconnections to allow optimal control of physical facilities using virtual models. ORCA is enabled by INL's RAVEN and DeepLynx software codes.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Optimization Of Real-time Capacity Allocation", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/ORCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Optimization_Plugin_Library.json b/agency-indexes/DoE/Optimization_Plugin_Library.json new file mode 100644 index 00000000..68a8e018 --- /dev/null +++ b/agency-indexes/DoE/Optimization_Plugin_Library.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-02-28", + "metadataLastUpdated": "2022-02-28" + }, + "description": "The Optimization Plugin library (\"op\") is a lightweight general optimization solver interface. The primary purpose of op is to simplify the process of integrating different optimization solvers (serial or parallel) with scalable parallel physics engines. By design it has several features that help make this a reality. The core abstraction interface was developed to encompass a large class of optimization problems in an optimizer-agnostic way. This enables us to describe the optimization problem once and then use a variety of supported \"op\" optimizers with ideally no code-changes. The abstraction interface is made up of lightweight wrappers that make it easy to integrate with existing simulation codes. This makes integration less intrusive and should minimize changes to existing physics codes. The \"op\" interface includes an assortment of utility methods that help specify parallel communication patterns as well as methods to convert from optimization-specific interfaces to the more general \"op\" interface. Lastly a dynamic library linking interface is provided to allow for use of proprietary optimization engines without explicit reference in the source code, along with standard shared library interfaces for opensource engines.", + "laborHours": 0.0, + "languages": [], + "name": "Optimization Plugin Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/op", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Optipack.json b/agency-indexes/DoE/Optipack.json new file mode 100644 index 00000000..7f67b251 --- /dev/null +++ b/agency-indexes/DoE/Optipack.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Used to solve basic unconstrained optimization problems that can produce smooth accurate gradients. These are standard published unconstrained optimization such as are described in the book Nocedal and Wright Numerical Optimization: 2nd edition, 2006. This software is generic to any mathematical optimization problem where smooth derivatives exist. There is no specific connection or mention whatsoever to any specific application, period. You cannot find more general mathematical software.OptiPack contains some simple optimization algorithms built on Thyra. Currently, only a few different nonlinear conjugate gradient methods are implemented.", + "laborHours": 8344830.4, + "name": "Optipack", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/optipack/copyright_header.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Optvis.json b/agency-indexes/DoE/Optvis.json new file mode 100644 index 00000000..3070a717 --- /dev/null +++ b/agency-indexes/DoE/Optvis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-11-15", + "metadataLastUpdated": "2021-11-16" + }, + "description": "Optvis is a web application to visualize control flow graphs, call graphs, disassembly code from a binary or executable. The main use case is visualizing the compiler optimizations in binary code.", + "laborHours": 0.0, + "languages": [], + "name": "Optvis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CcNav", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Orchard.json b/agency-indexes/DoE/Orchard.json new file mode 100644 index 00000000..d2c219fc --- /dev/null +++ b/agency-indexes/DoE/Orchard.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-04-13", + "metadataLastUpdated": "2021-05-25" + }, + "description": "Orchard is a collection of software that includes numerical models, enables model analysis, and seamlessly integrates numerical models machine learning tools. It is organized as a number of Julia packages. The primary packages are NonlinearEquations.jl and DPFEHM.jl. NonlinearEquations.jl enables automatic differentiation of numerical models, which is the component that enables seamless integration with machine learning tools. DPFEHM.jl is a numerical subsurface flow and transport model built using NonlinearEquations.jl. These packages integrate with other packages, including parts of Julia's open source ecosystem such as DifferentialEquations.jl, to demonstrate the value of the approach and enable modeling analysis such as inverse analysis, uncertainty quantification, and decision-support.", + "laborHours": 0.0, + "languages": [], + "name": "Orchard", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/DPFEHM.jl", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Orio.json b/agency-indexes/DoE/Orio.json new file mode 100644 index 00000000..1d7d21a5 --- /dev/null +++ b/agency-indexes/DoE/Orio.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "Orio is an annotation system implemented in Python that enables developers to insert annotations into their source code (in C or Fortran). These annotations are used to trigger performance optimizations on a specified code fragment. ", + "laborHours": 117511.2, + "languages": [], + "name": "Orio", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/brnorris03/Orio", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OrthoPhylo.json b/agency-indexes/DoE/OrthoPhylo.json new file mode 100644 index 00000000..e24e8200 --- /dev/null +++ b/agency-indexes/DoE/OrthoPhylo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-01-17", + "metadataLastUpdated": "2023-01-17" + }, + "description": "This software builds on PHAME developed at LANL to generate phylogenetic trees of bacterial whole genome sequences. Where PHAME uses whole genome alignments to generate informative sites to base tress on, PHAME-OuS annotates bacterial genes, identifies orthologous sequences, aligns related proteins, uses those alignments to inform transcript alignments, then builds trees with several methods. The first is a conventional gene concatenation and ML tree estemation method. The second attempts to reconcile gene tree with a unified species tree using quartets (ASTRAL). Both methods allow filtering of gene lists on number of species represented, length, and gappiness in order to tune noise-to-signal for tree estimation", + "laborHours": 0.0, + "languages": [], + "name": "OrthoPhylo", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/OrthoPhylo", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Oscillation_Baselining_and_Analysis_Tool.json b/agency-indexes/DoE/Oscillation_Baselining_and_Analysis_Tool.json new file mode 100644 index 00000000..8f09754c --- /dev/null +++ b/agency-indexes/DoE/Oscillation_Baselining_and_Analysis_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "PNNL developed a new tool for oscillation analysis and baselining. This tool has been developed under a new DOE Grid Modernization Laboratory Consortium (GMLC) Project (GM0072 - \u201cSuite of open-source applications and models for advanced synchrophasor analysis\u201d) and it is based on the open platform for PMU analysis. The Oscillation Baselining and Analysis Tool (OBAT) performs the oscillation analysis and identifies modes of oscillations (frequency, damping, energy, and shape). The tool also does oscillation event baselining (fining correlation between oscillations characteristics and system operating conditions).", + "homepageURL": "https://svn.pnl.gov/OBAT", + "laborHours": 0.0, + "languages": [ + "VB.NET (MS Visual Studio 2012)" + ], + "name": "Oscillation Baselining and Analysis Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://svn.pnl.gov/OBAT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.pnl.gov/OBAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Out-of-memory_SVD.json b/agency-indexes/DoE/Out-of-memory_SVD.json new file mode 100644 index 00000000..928ed735 --- /dev/null +++ b/agency-indexes/DoE/Out-of-memory_SVD.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "Singular value decomposition (SVD) is a matrix factorization widely used for dimensionality reduction, data analytics, information retrieval and unsupervised learning. In the SVD's applications for big-data, usually, only the singular values are calculated. However, new methods, such as the tensor network factorization, require an accurate retrieval of a substantial number of singular vectors for truncated SVD. Also, many real-world datasets are too big to fit directly into the memory, which mandates the development of out-of-memory algorithms that work with data that is primarily on the disk. Here, building upon a previous work, we present a method for computation of the singular vectors of matrices that cannot fit into the memory. We also describe ways for reducing the communication during the computation of the left and right reflectors, needed to compute the singular vectors, and introduce a method for reducing the block-sizes, needed to hide communication on parallel file systems.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Out-of-memory SVD", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Out_of_Distribution_Detection_with_Neural_Network_Anchoring.json b/agency-indexes/DoE/Out_of_Distribution_Detection_with_Neural_Network_Anchoring.json new file mode 100644 index 00000000..2b745191 --- /dev/null +++ b/agency-indexes/DoE/Out_of_Distribution_Detection_with_Neural_Network_Anchoring.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-09-07", + "metadataLastUpdated": "2022-09-07" + }, + "description": "This is code to reproduce and build on OOD detection from the paper \"Out of Distribution Detection with Neural Network Anchoring\". Our goal here is to exploit heteroscedastic temperature scaling as a calibration strategy for out of distribution (OOD) detection. Heteroscedasticity here refers to the fact that the optimal temperature parameter for each sample can be different, as opposed to conventional approaches that use the same value for the entire distribution. To enable this, we propose a new training strategy called anchoring that can estimate appropriate temperature values for each sample, leading to state-of-the-art OOD detection performance across several benchmarks. Using NTK theory, we show that this temperature function estimate is closely linked to the epistemic uncertainty of the classifier, which explains its behavior. In contrast to some of the best-performing OOD detection approaches, our method does not require exposure to additional outlier datasets, custom calibration objectives, or model ensembling. Through empirical studies with different OOD detection settings - far OOD, near OOD, and semantically coherent OOD - we establish a highly effective OOD detection approach.", + "laborHours": 0.0, + "languages": [], + "name": "Out of Distribution Detection with Neural Network Anchoring", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/AMP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Out_of_distribution_evaluation_for_neural_image_compression.json b/agency-indexes/DoE/Out_of_distribution_evaluation_for_neural_image_compression.json new file mode 100644 index 00000000..88059f56 --- /dev/null +++ b/agency-indexes/DoE/Out_of_distribution_evaluation_for_neural_image_compression.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-11-14", + "metadataLastUpdated": "2023-11-14" + }, + "description": "Official code for the NeurIPS 2023 paper \"Neural Image Compression: Generalization, Robustness, and\nSpectral Biases\". This code can be used to:\n- Computing spectral distortion errors of images compressed with traditional codes or neural image\ncompression models (as proposed in the aformentioned paper)\n- Visualize power spectral densities and fourier heatmaps (as proposed in the aformentioned paper)\n- Train and test a variety of neural image compression models", + "laborHours": 0.0, + "languages": [], + "name": "Out of distribution evaluation for neural image compression", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/klieberman/ood_nic", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Outbreak_analysis_from_case_count_and_survey_data.json b/agency-indexes/DoE/Outbreak_analysis_from_case_count_and_survey_data.json new file mode 100644 index 00000000..38d205d8 --- /dev/null +++ b/agency-indexes/DoE/Outbreak_analysis_from_case_count_and_survey_data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-07-28", + "metadataLastUpdated": "2023-07-28" + }, + "description": "This code enables fitting a model of an infectious disease outbreak, customized for when available data is a combination of case counts and symptom survey responses. This is just a small bit of code being used only for a publication; we need to release it to fulfill a journal's requirement that our work be reproducible.", + "laborHours": 0.0, + "languages": [], + "name": "Outbreak analysis from case count and survey data", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eeg-lanl/cov2-china2022", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Output_Viewer.json b/agency-indexes/DoE/Output_Viewer.json new file mode 100644 index 00000000..76d67990 --- /dev/null +++ b/agency-indexes/DoE/Output_Viewer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "The Output Viewer is designed to provide a framework for viewing arbitrary output from diagnostics scripts, metrics, or any program that produces a ton of different files that you want to look at it in an easy-to-use fashion. It also provides tooling that interacts with the data file (index.json) that gets generated, creating HTML pages based on the file with your output embedded in it, and also the ability to upload your results to a server to share with collaborators, sponsors, or anyone who's interested.\n", + "laborHours": 1444.0, + "languages": [], + "name": "Output Viewer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/output_viewer", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Oxide.json b/agency-indexes/DoE/Oxide.json new file mode 100644 index 00000000..9b48365f --- /dev/null +++ b/agency-indexes/DoE/Oxide.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Oxide is a modular framework for feature extraction and analysis of executable files. Oxide is useful in a variety of reverse engineering and categorization tasks relating to executable content.", + "laborHours": 10244.8, + "languages": [ + "Python" + ], + "name": "Oxide", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Oxide", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OxyDataPlotter.json b/agency-indexes/DoE/OxyDataPlotter.json new file mode 100644 index 00000000..4497e83b --- /dev/null +++ b/agency-indexes/DoE/OxyDataPlotter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The OxyDataPlotter library includes a WinForms control with a customizable instance of OxyPlot.", + "laborHours": 8284.0, + "languages": [], + "name": "OxyDataPlotter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/OxyDataPlotter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/P-Mart.json b/agency-indexes/DoE/P-Mart.json new file mode 100644 index 00000000..8c26a6b5 --- /dev/null +++ b/agency-indexes/DoE/P-Mart.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "P-Mart was designed specifically to allow cancer researchers to perform robust statistical processing of publicly available cancer proteomic datasets. To date an online statistical processing suite for proteomics does not exist. The P-Mart software is designed to allow statistical programmers to utilize these algorithms through packages in the R programming language as well as offering a web-based interface using the Azure cloud technology. The Azure cloud technology also allows the release of the software via Docker containers.", + "homepageURL": "https://pmart.labworks.org/index.html", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "P-Mart", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://pmart.labworks.org/index.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://pmart.labworks.org/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/P38_heterogeneous_multi-tiled_system_with_support_for_message_queues__MoSAIC__v0.1.json b/agency-indexes/DoE/P38_heterogeneous_multi-tiled_system_with_support_for_message_queues__MoSAIC__v0.1.json new file mode 100644 index 00000000..093e6ab6 --- /dev/null +++ b/agency-indexes/DoE/P38_heterogeneous_multi-tiled_system_with_support_for_message_queues__MoSAIC__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "semalek@lbl.gov" + }, + "date": { + "created": "2024-06-12", + "metadataLastUpdated": "2024-06-17" + }, + "description": "The proposed system is written in the hardware description language (HDL) verilog targeting an FPGA board. 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These equations are the fundamental way that physics models are written (\"f = ma\" for example). P3A provides a way to write in the C++ programming language similar to how one would do math on paper. P3A provides support tools for rapidly solving equations in a way that is common in scientific computing. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-3183 O", + "laborHours": 0.0, + "languages": [ + "C++ version 17" + ], + "name": "P3A", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/p3a", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/P6_Deeplynx_Adapter.json b/agency-indexes/DoE/P6_Deeplynx_Adapter.json new file mode 100644 index 00000000..980fe97c --- /dev/null +++ b/agency-indexes/DoE/P6_Deeplynx_Adapter.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-10-26", + "metadataLastUpdated": "2023-11-08" + }, + "description": "The purpose of this software is to pull data from the Oracle Primavera P6 scheduling tool and bring it into the DeepLynx data warehouse.", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "P6 Deeplynx Adapter", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/p6-deeplynx-adapter", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PACE.json b/agency-indexes/DoE/PACE.json new file mode 100644 index 00000000..338dc3f4 --- /dev/null +++ b/agency-indexes/DoE/PACE.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "sarat@ornl.gov" + }, + "date": { + "created": "2023-05-09", + "metadataLastUpdated": "2023-05-09" + }, + "description": "Performance Analytics for Computational Experiments (PACE) is an end-to-end performance monitoring infrastructure to summarize performance data collected from Department of Energy\u2019s (DOE) climate model experiments to derive insights and present them through a web portal. PACE automatically captures provenance/timing data from simulations run on DOE supercomputers.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "PACE", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/pace", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PAM_module_for_OAuth_2.0_Device_flow.json b/agency-indexes/DoE/PAM_module_for_OAuth_2.0_Device_flow.json new file mode 100644 index 00000000..ee969ed7 --- /dev/null +++ b/agency-indexes/DoE/PAM_module_for_OAuth_2.0_Device_flow.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "This is a PAM module that lets you log in via SSH to servers using OpenID Connect credentials, instead of SSH Keys or a username and password combination. It uses the OAuth2 Device Flow, which means that during the login process, you will click a link and log in to your OpenID Connect Provider, which will then authenticate you for the SSH session. This module will then check if you're in the right group(s) or have a specified username, and allow or deny access.", + "laborHours": 0.0, + "languages": [], + "name": "PAM module for OAuth 2.0 Device flow", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pam_oauth2_device", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PAO.json b/agency-indexes/DoE/PAO.json new file mode 100644 index 00000000..db0a26f9 --- /dev/null +++ b/agency-indexes/DoE/PAO.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-09-20" + }, + "description": "PAO supports the formulation and analysis of mathematical models for complex optimization applications. This capability is commonly associated with algebraic modeling languages (AMLs), which support the description and analysis of mathematical models with a high-level language. PAO is derived from the Pyomo subpackage pyomo.bilevel, which has been deprecated. PAO supports the formulation and solution of optimization models that explicitly represent adversarial behavior. This includes variances of bilevel programming, including methods that represent challenging problems with discrete decisions and uncertain model parameters.", + "laborHours": 12357.6, + "languages": [ + "Python" + ], + "name": "PAO", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pao", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PAPI.json b/agency-indexes/DoE/PAPI.json new file mode 100644 index 00000000..99d13160 --- /dev/null +++ b/agency-indexes/DoE/PAPI.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "The Performance Application Programming Interface (PAPI) provides tool designers and application engineers with a consistent interface and methodology for the use of low-level performance counter hardware found across the entire compute system (i.e. CPUs, GPUs, on/off-chip memory, interconnects, I/O system, energy/power, etc.). PAPI enables users to see, in near real time, the relations between software performance and hardware events across the entire computer system.", + "laborHours": 0.0, + "languages": [], + "name": "PAPI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/icl/papi/src/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/icl/papi/src/master", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PARADISE:_PostMoore_Architecture_and_Accelerator_Design_Space_Exploration_using_Device_Level_Experiments.json b/agency-indexes/DoE/PARADISE:_PostMoore_Architecture_and_Accelerator_Design_Space_Exploration_using_Device_Level_Experiments.json new file mode 100644 index 00000000..94b51374 --- /dev/null +++ b/agency-indexes/DoE/PARADISE:_PostMoore_Architecture_and_Accelerator_Design_Space_Exploration_using_Device_Level_Experiments.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2021-05-27" + }, + "description": "PARADISE will enable the research community to rapidly evaluate the impact of emerging technologies at the architectural level, and thus provide the means to select among available technologies to facilitate continued digital computing performance scaling.", + "homepageURL": "https://sites.google.com/lbl.gov/paradise/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "PARADISE: PostMoore Architecture and Accelerator Design Space Exploration using Device Level Experiments", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/paradise/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/paradise/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PARAFAC_T1.json b/agency-indexes/DoE/PARAFAC_T1.json new file mode 100644 index 00000000..c7559238 --- /dev/null +++ b/agency-indexes/DoE/PARAFAC_T1.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-08-07" + }, + "description": "This is a method of performing trilinear analysis on large data sets using a modification of the PARAFAC-ALS algorithm. It iteratively decomposes the data matrix into a core matrix and three loading matrices based on the Tucker1 model. The algorithm is particularly useful for data sets that are too large to upload into a computer?s main memory. While the performance advantage in utilizing our algorithm is dependent on the number of data elements and dimensions of the data array, we have seen a significant performance improvement over operating PARAFAC-ALS on the full data set.\nSAND2020-12649 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 60.8, + "languages": [ + "MATLAB" + ], + "name": "PARAFAC_T1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PARAFAC_T1", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PARMOO.json b/agency-indexes/DoE/PARMOO.json new file mode 100644 index 00000000..30ef0695 --- /dev/null +++ b/agency-indexes/DoE/PARMOO.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2023-03-14" + }, + "description": "ParMOO is a Python library for solving multiobjective simulation optimization problems, while exploiting problem structure. ParMOO stands for \"parallel multiobjective optimization\".", + "laborHours": 0.0, + "languages": [], + "name": "PARMOO", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/parmoo/parmoo", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PASTA.json b/agency-indexes/DoE/PASTA.json new file mode 100644 index 00000000..219aa156 --- /dev/null +++ b/agency-indexes/DoE/PASTA.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-06-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PASTA: A Parallel Sparse Tensor Algorithm Benchmark Suite.", + "laborHours": 44855.2, + "languages": [], + "name": "PASTA", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/tensorworld/pasta", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PASTIS_v0.1.json b/agency-indexes/DoE/PASTIS_v0.1.json new file mode 100644 index 00000000..54d5738e --- /dev/null +++ b/agency-indexes/DoE/PASTIS_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-01", + "metadataLastUpdated": "2021-03-02" + }, + "description": "PASTIS is a distributed-memory library for aligning large protein sequence sets and constructing protein similarity networks.", + "laborHours": 0.0, + "languages": [], + "name": "PASTIS v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aydinbuluc/PASTIS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PBE-HIL__Powering_the_Blue_Economy_Hardware-in-the-Loop_models__[SWR-25-37].json b/agency-indexes/DoE/PBE-HIL__Powering_the_Blue_Economy_Hardware-in-the-Loop_models__[SWR-25-37].json new file mode 100644 index 00000000..1501ae8e --- /dev/null +++ b/agency-indexes/DoE/PBE-HIL__Powering_the_Blue_Economy_Hardware-in-the-Loop_models__[SWR-25-37].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-01-08", + "metadataLastUpdated": "2025-01-08" + }, + "description": "Powering the Blue Economy Hardware-in-the-Loop models (PBE-HIL) is a repository of Power Hardware-in-the-loop models developed for typical Powering the Blue Economy market loads and power requirements. The HIL models were developed to be as generic and functional as possible, meaning that the user can easily configure these models to represent their unique PBE design. These PBE load and power requirement HIL models can then be used to inform marine energy converter (MEC) and power electronics design, as well as be used in laboratory testing using HIL equipment, leading to improved understanding of MEC performance and lower risk prior to open-water MEC deployment.", + "laborHours": 52318.4, + "languages": [ + "C", + "Python", + "HTML" + ], + "name": "PBE-HIL (Powering the Blue Economy Hardware-in-the-Loop models) [SWR-25-37]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PBE-HIL", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PBS_UTILS.json b/agency-indexes/DoE/PBS_UTILS.json new file mode 100644 index 00000000..2cfe57b8 --- /dev/null +++ b/agency-indexes/DoE/PBS_UTILS.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SF-24-051 PBS_Utils is a collection of tools and libraries for administrating a PBSPro/OpenPBS system.", + "laborHours": 3860.8, + "languages": [], + "name": "PBS_UTILS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.cels.anl.gov/aig-public/pbs_utils", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PCALC_v.3.1.1.json b/agency-indexes/DoE/PCALC_v.3.1.1.json new file mode 100644 index 00000000..4ebee92e --- /dev/null +++ b/agency-indexes/DoE/PCALC_v.3.1.1.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2024-07-19" + }, + "description": "PCalc is software to interrogate models of the seismic compressional and shear wave velocity distribution in the Earth and to compute predictions of seismic source-receiver travel time through such models.", + "laborHours": 291095.2, + "languages": [ + "Java", + "HTML" + ], + "name": "PCALC v.3.1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/Salsa3DSoftware?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Salsa3DSoftware", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PCCEServer.json b/agency-indexes/DoE/PCCEServer.json new file mode 100644 index 00000000..ddac87b1 --- /dev/null +++ b/agency-indexes/DoE/PCCEServer.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The PCCEServer application is a server that should be used in conjunction with the LBNLSecureMessaging user interface to enable secure synchronous and asynchronous messaging. It provides authentication and authorization services for members of a collaboration group via PKI/SSL and maintains an access control list. Members of collaboration groups using the LBNLSecureMessaging client must register identifying information. including username and password and an optional X.509 certificate, with the PCCEServer. This registration not only restricts access to instant messaging, but augments the LBNLSecureMessaging's IRC-based chat facility with persistence. Users register permanent unique user ids by which they are known to other users in the system and create permanent venues intended for group conversations on a tong-term or continuous basis. In addition, the PCCEServer enhances instant messaging with presence and awareness information such as user availability, and it allows users to leave notes asynchronously for other users who are online or offline. Written in Java, it is a standalone application that can run on any platform that supports a Java Virtual Machine.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Java Version 1.4 or higher (including JSSE)" + ], + "name": "PCCEServer", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PCDS_Devices.json b/agency-indexes/DoE/PCDS_Devices.json new file mode 100644 index 00000000..31149803 --- /dev/null +++ b/agency-indexes/DoE/PCDS_Devices.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Collection of Ophyd device subclasses for IOCs unique to LCLS PCDS.", + "laborHours": 3298.4, + "name": "PCDS Devices", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pcds-devices/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pcds-devices", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PCMDI_Metrics_Package.json b/agency-indexes/DoE/PCMDI_Metrics_Package.json new file mode 100644 index 00000000..23028132 --- /dev/null +++ b/agency-indexes/DoE/PCMDI_Metrics_Package.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-31", + "metadataLastUpdated": "2025-03-31" + }, + "description": "The Program for Climate Model Diagnosis & Intercomparison (PCMDI) Metrics Package (PMP) is used to\nprovide \"quick-look\" objective comparisons of Earth System Models (ESMs) with one another and\navailable observations. The PMP provides a diverse suite of analysis utilities each of which produce\nsummary statistics that gauge the consistency between climate model simulations and available\nobservations. The primary application of the PMP is to evaluate simulations from the Coupled Model\nIntercomparison Project (CMIP). It can also be used to provide objective performance summaries during\nthe model development process as well as selected research purposes.", + "laborHours": 173112.8, + "languages": [], + "name": "PCMDI Metrics Package", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PCMDI/pcmdi_metrics", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.8.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PCMDI_PMP_Interactive_Visualization_Web_Page,_Atmospheric_River_Metrics.json b/agency-indexes/DoE/PCMDI_PMP_Interactive_Visualization_Web_Page,_Atmospheric_River_Metrics.json new file mode 100644 index 00000000..5d747967 --- /dev/null +++ b/agency-indexes/DoE/PCMDI_PMP_Interactive_Visualization_Web_Page,_Atmospheric_River_Metrics.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-12-05", + "metadataLastUpdated": "2023-12-05" + }, + "description": "We present an open-source Python-based framework that can be used for objective evaluation of\nAtmospheric Rivers (ARs) in climate models. With a comprehensive pool of pre-defined metrics, this\npackage is useful for systematic AR evaluation across a range of model simulations, such as the MIPs in\nCMIP5/6 models and large ensemble experiments.", + "laborHours": 0.0, + "languages": [], + "name": "PCMDI PMP Interactive Visualization Web Page, Atmospheric River Metrics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kristinchang3/peak_season_cmec", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PCR_Amplicon_Prediction_from_Multiplex_Degenerate_Primer_and_Probe_Sets.json b/agency-indexes/DoE/PCR_Amplicon_Prediction_from_Multiplex_Degenerate_Primer_and_Probe_Sets.json new file mode 100644 index 00000000..2a896dbf --- /dev/null +++ b/agency-indexes/DoE/PCR_Amplicon_Prediction_from_Multiplex_Degenerate_Primer_and_Probe_Sets.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-09-30" + }, + "description": "Assessing primer specificity and predicting both desired and off-target amplification products is an essential step for robust PCR assay design. Code is described to predict potential polymerase chain reaction (PCR) amplicons in a large sequence database such as NCBI nt from either singleplex or a large multiplexed set of primers, allowing degenerate primer and probe bases, with target mismatch annotates amplicons with gene information automatically downloaded from NCBI, and optionally it can predict whether there are also TaqMan/Luminex probe matches within predicted amplicons.", + "homepageURL": "https://sourceforge.net/projects/simulatepcr", + "laborHours": 243.2, + "languages": [ + "PERL" + ], + "name": "PCR Amplicon Prediction from Multiplex Degenerate Primer and Probe Sets", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/simulatepcr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PCRamp.json b/agency-indexes/DoE/PCRamp.json new file mode 100644 index 00000000..12072a65 --- /dev/null +++ b/agency-indexes/DoE/PCRamp.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "Identifying nucleic acid sequences of interest in complex metagenomic samples is often likened to \u201cfinding a needle in haystack\u201d. While the polymerase chain reaction (PCR) can provide unparalleled, selective enrichment of known sequences from complex metagenomic samples, traditional (endpoint and real-time) PCR assays only provide \u201cyes\u201d or \u201cno\u201d results and, more significantly, can be prone to database \u201coverfitting\u201d. Overfitting occurs during the computational PCR primer design process, which typically uses all of the available target and near-neighbor sequences to predict highly specific PCR primers. Even though the number of known sequences continues to grow exponentially, we have still only sequenced a small fraction of the sequence diversity that occurs in nature. As a result, PCR primers that appear to offer \u201cperfect\u201d target discrimination (i.e. no false positives or negatives) fail when experimentally tested against unsequenced targets and/or near-neighbors. These assay failures can also become apparent when PCR primers are computationally screened against sequences that were not included in the original design process. As a result, PCR assays are said to suffer from \u201csignature erosion\u201d. A useful strategy to overcome signature erosion is to not rely on single, or even a handful, of target-specific PCR primers, but instead use hundreds or thousands of different primer pairs in a single \u201cmultiplexed\u201d (or even megaplex) PCR. In much the same way that financial index funds can outperform hand-picked individual stocks, an ensemble of primer pairs can tolerate the failure of many individual pairs and still provide robust target enrichment. Next generation sequencing enables a digital readout of all of the sequences (or \u201camplicons\u201d) that are amplified during a successful PCR. This amplicon sequence information can be used by bioinformatics analysis programs to identify the most likely organisms, reject closely-related near-neighbors and uncover phenotypic (e.g. antibiotic resistance) and forensic (e.g. informative SNP) markers.\n\nHowever, it is still challenging to design a large set of primer pairs for multiplex PCR. These challenges include selecting individual primers that do not form hairpins, homo-dimers or hetero-dimers, as these unwanted reactions reduce the assay sensitivity by reducing the effective concentration of the effected primers. Primers must bind to their intended target sequences with similar affinities and produce similar length amplicons to ensure uniform amplicon enrichment. Amplicons that form stable secondary structures should be avoided to prevent any \u201cstalling\u201d of the DNA polymerase that could reduce the enrichment level. In addition, unintended PCR amplification, caused by primers that happen to bind in close proximity and in the correct orientation to non-target sequences, must be avoided to maintain a sufficient signal to noise level for target enrichment and detection. Finally, it is essential to experimentally test a multiplex PCR design strategy. Experiments can uncover software bugs and design flaws that would otherwise reduce the level of target enrichment. In particular, experimentally measuring assay performance on both known (sequenced) and unknown (unsequenced) targets and backgrounds will help bound the expected target enrichment levels for deployed assays.", + "laborHours": 0.0, + "languages": [], + "name": "PCRamp", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Bioinformatics/PCRamp", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PCS_Security_Technology_Evaluation_Tool.json b/agency-indexes/DoE/PCS_Security_Technology_Evaluation_Tool.json new file mode 100644 index 00000000..24e84881 --- /dev/null +++ b/agency-indexes/DoE/PCS_Security_Technology_Evaluation_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "P-STET assists in the security technology decision making process from a costlbeneflt perspective. It aids in addressing such questions as whether to acquire and deploy new security technology, to re-configure an existing product or system, or to maintain status quo. P-STET offers both a qualitative and quantitative option. P-STET is most efficient when tailored to an organization's security cost/benefit environment. It then serves as both a guide to show what types of security questions should be addressed and as a means to analyze the data gathered from the questions to make an informed decision. The quantitative option provides a straightforward way to express costs/benefits in terms of dollars. It relies on the organization to quantify benefits or cost avoidances, and, therefore, best serves as a guide to ensure various cost and benefit angles are evaluated. The qualitative option allows the organization to assess costs by levels with respect to security and PCS budgets, operational impacts, and opportunity costs. Benefits are represented in terms of improvements to the organization's operations and are also assessed by levels with respect to some benchmark such as compliance with best practices. Results are displayed graphically using radar charts, allowing the user to make a more intuitive decision. The shaded area of each chart represents the overall cost and benefit of the security investment. A good investment is denoted when the ratio of benefit shaded area to cost shaded area is large.", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "PCS Security Technology Evaluation Tool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/P-STET", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PCircle.json b/agency-indexes/DoE/PCircle.json new file mode 100644 index 00000000..686eae59 --- /dev/null +++ b/agency-indexes/DoE/PCircle.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "A suite of parallel file system tools designed for performance and scalability\n", + "laborHours": 20185.6, + "name": "PCircle", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/pcircle", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PDC_VOL_Connector__PDCVOL__v0.1.json b/agency-indexes/DoE/PDC_VOL_Connector__PDCVOL__v0.1.json new file mode 100644 index 00000000..6840df83 --- /dev/null +++ b/agency-indexes/DoE/PDC_VOL_Connector__PDCVOL__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2023-08-01" + }, + "description": "PDCVOL is an extension software originated from the Proactive Data Containers (PDC) software (LBNL Track Code 2017-098), it is an HDF5 VOL connector that allows HDF5 applications to store and access data with the PDC system without the need to modify their code. The application can take advantage of the PDC optimization features and achieve better I/O performance.", + "laborHours": 0.0, + "languages": [], + "name": "PDC VOL Connector (PDCVOL) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/vol-pdc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PDLAMMPS_0.1.json b/agency-indexes/DoE/PDLAMMPS_0.1.json new file mode 100644 index 00000000..1063c0a2 --- /dev/null +++ b/agency-indexes/DoE/PDLAMMPS_0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PDLAMMPS is an add-on module to Sandia's LAMMPS molecular dynamics package that implements a simplified peridynamic model.", + "laborHours": 1281025.6, + "name": "PDLAMMPS 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lammps/lammps", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PDMATLAB2D.json b/agency-indexes/DoE/PDMATLAB2D.json new file mode 100644 index 00000000..bddb8e08 --- /dev/null +++ b/agency-indexes/DoE/PDMATLAB2D.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "reevest@ornl.gov" + }, + "date": { + "created": "2022-11-22", + "metadataLastUpdated": "2022-11-22" + }, + "description": "The PDMATLAB2D code is a meshfree peridynamics implementation in MATLAB suitable for simulation of two-dimensional fracture problems. The initial version implements bond-based brittle elastic peridynamics models and a critical stretch criterion for bond breaking. PDMATLAB2D provides an entry-level peridynamics computational tool for educational and training purposes. It also serves as an accessible and easily modifiable computational tool for peridynamics researchers who would like to adapt the code for a multitude of peridynamics simulations.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "PDMATLAB2D", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/PDMATLAB2D", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PECAN2.json b/agency-indexes/DoE/PECAN2.json new file mode 100644 index 00000000..1a52dc93 --- /dev/null +++ b/agency-indexes/DoE/PECAN2.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-12-20", + "metadataLastUpdated": "2023-12-20" + }, + "description": "PECAN2, Pose Classification with 3D Atomic Network 2, presents an innovative approach to pose\nclassification in computational modeling, particularly in the context of molecular docking. Traditional\nmethods like docking, which rely on physics-based calculations, are prone to inaccuracies in predicting\nbinding poses during experimental testing. While machine learning (ML) approaches, such as ML-driven\npose classification, have been introduced to address these issues, they often depend on the availability of\ncrystal structure data.\nIn contrast, PECAN2 introduces a novel pose classification method that operates independently of crystal\nstructures. Instead, it utilizes a 3D atomic neural network with Point Cloud Network (PCN) to establish\ncorrelations between docking scores and experimental data. This approach marks a departure from\nprevious studies that heavily relied on crystal structures for labeling.\nThe key innovation lies in the ability of PECAN2 to enhance the performance of molecular docking by\nfiltering out false positives and false negatives through the correlation between docking scores and\nexperimental data.", + "laborHours": 0.0, + "languages": [], + "name": "PECAN2", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/PECAN2", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PEDL.json b/agency-indexes/DoE/PEDL.json new file mode 100644 index 00000000..2a93aa24 --- /dev/null +++ b/agency-indexes/DoE/PEDL.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "QT inspired Python Interface for EDM Screen Creation", + "laborHours": 1337.6, + "name": "PEDL", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pedl/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pedl", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PELEC.json b/agency-indexes/DoE/PELEC.json new file mode 100644 index 00000000..631a78c2 --- /dev/null +++ b/agency-indexes/DoE/PELEC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2022-07-21" + }, + "description": "PeleC is an adaptive-mesh compressible hydrodynamics code for reacting flows. It solves the compressible Navier-Stokes with multispecies transport in a block structured framework. The resulting algorithm is well suited for flows with localized resolution requirements and robust to discontinuities. User controllable refinement crieteria has the potential to result in extremely small numerical dissipation and dispersion, making this code appropriate for both research and applied usage. The code is built on the AMReX library which facilitates hierarchical parallelism and manages distributed memory parallism. PeleC algorithms are implemented to express shared memory parallelism.", + "laborHours": 0.0, + "languages": [], + "name": "PELEC", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/AMReX-Combustion/PeleC/blob/development/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Combustion/PeleC", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PERCEPTIVE.json b/agency-indexes/DoE/PERCEPTIVE.json new file mode 100644 index 00000000..9a567d91 --- /dev/null +++ b/agency-indexes/DoE/PERCEPTIVE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-01-24", + "metadataLastUpdated": "2025-01-24" + }, + "description": "PERCEPTIVE: a pipeline for the prediction of epigenetic modulators in novel species", + "laborHours": 1398.4, + "languages": [], + "name": "PERCEPTIVE", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PERCEPTIVE", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PETSc.json b/agency-indexes/DoE/PETSc.json new file mode 100644 index 00000000..088ad842 --- /dev/null +++ b/agency-indexes/DoE/PETSc.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2018-04-17", + "metadataLastUpdated": "2020-06-01" + }, + "description": "PETSc is a suite of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations. It supports MPI, and GPUs through CUDA or OpenCL, as well as hybrid MPI-GPU parallelism. PETSc (sometimes called PETSc/Tao) also contains the Tao optimization software library.", + "laborHours": 723352.8, + "languages": [], + "name": "PETSc", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/petsc/petsc/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/petsc/petsc", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PETSc_TAO.json b/agency-indexes/DoE/PETSc_TAO.json new file mode 100644 index 00000000..2eccaedf --- /dev/null +++ b/agency-indexes/DoE/PETSc_TAO.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-13", + "metadataLastUpdated": "2018-07-13" + }, + "description": "TAO is the Toolkit for Advanced Optimization, focused on the development of software for large-scale optimization problems. Part of the PETSc suite of solver tools. ", + "homepageURL": "http://www.mcs.anl.gov/research/projects/tao", + "laborHours": 0.0, + "languages": [], + "name": "PETSc/TAO", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.mcs.anl.gov/research/projects/tao", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PFLOTRAN.json b/agency-indexes/DoE/PFLOTRAN.json new file mode 100644 index 00000000..318476e4 --- /dev/null +++ b/agency-indexes/DoE/PFLOTRAN.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-03" + }, + "description": "PFLOTRAN is a GNU LGPL licensed code that simulates single phase water and multiphase (air, co2, water) flow, energy transport, geochemical reaction and biological reaction in the earth's subsurface environment. The problem may be discretized on structured and unstructured grids. The code is designed to run in parallel on supercomputers and leverages the open source PETSc library for solvers and data structures and open source HDF5 for binary file I/O. See www.pflotran.org and/or doc-dev.pflotran.org for further information. SAND2020-12161 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 281686.4, + "languages": [ + "Fortran", + "Python" + ], + "name": "PFLOTRAN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PFLOTRAN_5.json b/agency-indexes/DoE/PFLOTRAN_5.json new file mode 100644 index 00000000..52e7a3f4 --- /dev/null +++ b/agency-indexes/DoE/PFLOTRAN_5.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-10-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PFLOTRAN leverages massively parallel, high performance computing to simulate large-scale non-isothermal multiphase\nflow, multicomponent reactive transport and electrical resistivity tomography (ERT) problems in the subsurface\nenvironment. Researchers have employed PFLOTRAN to simulate these Earth system processes on leadership class\nsupercomputers for over two decades. The code is designed to predict the future estate of environmental systems and\nbetter inform stakeholders in the regulatory decision making process (e.g., fate of contaminants, long-term stewardship for\nnuclear waste, impact of climate change, etc.). A diverse team of scientists oversees PFLOTRAN development and\nmaintenance under an open-source licensing agreement and manages contributions from an international community of\nresearchers.", + "laborHours": 0.0, + "languages": [], + "name": "PFLOTRAN 5", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/pflotran/pflotran/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PFLOW.json b/agency-indexes/DoE/PFLOW.json new file mode 100644 index 00000000..b4c966c8 --- /dev/null +++ b/agency-indexes/DoE/PFLOW.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-16", + "metadataLastUpdated": "2019-08-16" + }, + "description": "High performance parallel power flow solver that can be run in desktops as well as in high performance computing cluster. ", + "laborHours": 6216.8, + "languages": [], + "name": "PFLOW", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pflow-team/PFLOW", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PFPL.json b/agency-indexes/DoE/PFPL.json new file mode 100644 index 00000000..49d24452 --- /dev/null +++ b/agency-indexes/DoE/PFPL.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "burtscher@txstate.edu" + }, + "date": { + "created": "2025-03-14", + "metadataLastUpdated": "2025-03-14" + }, + "description": "This repository holds the PFPL code. PFPL is a guaranteed-error-bound lossy compressor/decompressor that produces bit-for-bit identical files on CPUs and GPUs. It supports absolute (ABS), relative (REL), and normalized-absolute (NOA) point-wise error bounds for single- and double-precision inputs in IEEE 754 binary format. It yields good compression ratios at high throughputs.", + "laborHours": 4316.8, + "languages": [], + "name": "PFPL", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/burtscher/PFPL", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PHYGNN__Physics_Guided_Neural_Networks_.json b/agency-indexes/DoE/PHYGNN__Physics_Guided_Neural_Networks_.json new file mode 100644 index 00000000..9d4476e7 --- /dev/null +++ b/agency-indexes/DoE/PHYGNN__Physics_Guided_Neural_Networks_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-08-20", + "metadataLastUpdated": "2020-08-28" + }, + "description": "This implementation of a Physics Guided Neural Network (PHYGNN) augments a traditional neural network loss function with a generic term that can be used to guide the neural network to learn physical or theoretical constraints. ", + "laborHours": 2675.2, + "languages": [ + "Python" + ], + "name": "PHYGNN (Physics Guided Neural Networks)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/phygnn", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PIACE_Project_v1.0.json b/agency-indexes/DoE/PIACE_Project_v1.0.json new file mode 100644 index 00000000..96c5ec32 --- /dev/null +++ b/agency-indexes/DoE/PIACE_Project_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-23", + "metadataLastUpdated": "2018-08-13" + }, + "description": "The PIACE software is an approach to the parallel integration and chromosomal expansion (PIACE) of metabolic pathways, which extends the Chemical-Induced Chromosomal Expansion (CIChE) method. The software has little to no application outside the specific use case of a specific approach to isopentanol production and analysis of specific related data.", + "laborHours": 273.6, + "languages": [], + "name": "PIACE Project v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/PIACE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PIDOTS:_Parallel_Integral_Discrete_Ordinates_Transport_Solver_v1.xx.json b/agency-indexes/DoE/PIDOTS:_Parallel_Integral_Discrete_Ordinates_Transport_Solver_v1.xx.json new file mode 100644 index 00000000..f2e9abf8 --- /dev/null +++ b/agency-indexes/DoE/PIDOTS:_Parallel_Integral_Discrete_Ordinates_Transport_Solver_v1.xx.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "PIDOTS is a software application for studying an alternative iterative and parallel solution technique for linear, deterministic neutral-particle radiation transport. The code solves a very generic, simplified\u2014i.e., dumb\u2014form of the system of relevant system of equations. PIDOTS is less capable than the open source proxy application SNAP. Given limitations introduced by the equations as well as limitations in data and meshing, PIDOTS is incapable of performing real physics simulations or addressing actual physics questions for transport. Instead of using transport mesh sweeps that we see in many production codes (and SNAP), PIDOTS uses a Jacobi or Jacobi-like iterative scheme that updates the flux information between adjacent, decoupled subdomains. By completely decoupling subdomains, PIDOTS permits massively large-scale decomposition (i.e., tens of thousands of processes or more) of the spatial mesh, making it an interesting alternative to mesh sweeps, worth continued studying and development. ", + "laborHours": 0.0, + "languages": [], + "name": "PIDOTS: Parallel Integral Discrete Ordinates Transport Solver v1.xx", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pidots", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PILGRIM.json b/agency-indexes/DoE/PILGRIM.json new file mode 100644 index 00000000..5318f25f --- /dev/null +++ b/agency-indexes/DoE/PILGRIM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-18" + }, + "description": "Pilgrim is a profiling tool for MPI applications. It tracks the communication activities in an MPI application and records them as logs for further analysis. It allows users to have a better insight into the execution of their application and identify potential performance bottlenecks.", + "laborHours": 0.0, + "languages": [], + "name": "PILGRIM", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/pilgrim", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PINNSTRIPES__Physics-Informed_Neural_Network_SurrogaTe_for_Rapidly_Identifying_Parameters_in_Energy_Systems__[SWR-22-12].json b/agency-indexes/DoE/PINNSTRIPES__Physics-Informed_Neural_Network_SurrogaTe_for_Rapidly_Identifying_Parameters_in_Energy_Systems__[SWR-22-12].json new file mode 100644 index 00000000..3687e192 --- /dev/null +++ b/agency-indexes/DoE/PINNSTRIPES__Physics-Informed_Neural_Network_SurrogaTe_for_Rapidly_Identifying_Parameters_in_Energy_Systems__[SWR-22-12].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-31", + "metadataLastUpdated": "2023-11-06" + }, + "description": "Energy systems models typically take the form of complex partial differential equations which make multiple forward calculations prohibitively expensive. Fast and data-efficient construction of surrogate models is of utmost importance for applications that require parameter exploration such as design optimization and Bayesian calibration. In presence of a large number of parameters, surrogate models that capture correct dependencies may be difficult to construct with traditional techniques. The issue is addressed here with the formulation of the surrogate model constructed via Physics-Informed Neural Networks (PINN) which capture the dependence with respect to the parameters to estimate, while using a limited amount of data. Since forward evaluations of the surrogate model are cheap, parameter exploration is made inexpensive, even when considering a large number of parameters.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PINNSTRIPES (Physics-Informed Neural Network SurrogaTe for Rapidly Identifying Parameters in Energy Systems) [SWR-22-12]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PINNSTRIPES", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PIO_Tools.json b/agency-indexes/DoE/PIO_Tools.json new file mode 100644 index 00000000..f0048b3e --- /dev/null +++ b/agency-indexes/DoE/PIO_Tools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "This is a set of utilities for reading and manipulating PIO files written in python and C++. These files are intended to be building blocks for other scripts / programs that will use them to do great things. The PIO format itself is described in LA-UR-05-7425 at page 102 and embodied in code LA-CC-05-052. In addition to reading the raw PIO files, the bundled utilities will expand variable that use a compressed sparse row notation", + "laborHours": 0.0, + "languages": [], + "name": "PIO Tools", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/piotools", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PIVAuth.json b/agency-indexes/DoE/PIVAuth.json new file mode 100644 index 00000000..70634c9e --- /dev/null +++ b/agency-indexes/DoE/PIVAuth.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2018-01-23", + "metadataLastUpdated": "2019-07-30" + }, + "description": "PIVAuth provides a key based OpenSSH authentication method for use with SmartCards, HSPD-12, PIV, CAC, and similar credentials that support PKCS11. PIVAuth validates the x509 client certificate chain of trust and revocation status on each authenticiation attempt before converting he certificate into a format that Open SSH can make use of. PIVAuth makes use of Bash shell code andi ndustry standard utilities like OpenSSL and OpenLDAP/ It aims to be audit friendly, and easily understood by any Linux administrator.", + "laborHours": 167.2, + "languages": [], + "name": "PIVAuth", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bensallen/pivauth", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PKPass.json b/agency-indexes/DoE/PKPass.json new file mode 100644 index 00000000..5f306b98 --- /dev/null +++ b/agency-indexes/DoE/PKPass.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Password management solutions exist, but few are designed for enterprise systems administrators sharing oncall rotations. Due to the Multi-Factor Level of Assurance 4 effort, DOE is now distributing PIV cards with cryptographically signed certificate and private key pairs to administrators and other security-significant users. We utilize this public key infrastructure (PKI) to encrypt passwords for other recipients in a secure way. This is cross platform (works on OSX and Linux systems), and has already been adopted internally by the NCCS systems administration staff to replace their old password book system.", + "laborHours": 1626.4, + "name": "PKPass", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/olcf/pkpass", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/pkpass", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PLASMA.json b/agency-indexes/DoE/PLASMA.json new file mode 100644 index 00000000..3852f9f5 --- /dev/null +++ b/agency-indexes/DoE/PLASMA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "PLASMA is the Parallel Linear Algebra for Scalable Multi-core Architectures library uses out-of-order scheduling as the basis for scalable and highly efficient computational linear algebra.", + "homepageURL": "https://bitbucket.org/icl/plasma", + "laborHours": 16993.6, + "languages": [], + "name": "PLASMA", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/icl/plasma/src/72d60b0a5d61fe4e31dfbb24065db28adf9ec8e8/LICENSE?at=default&fileviewer=file-view-default", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/icl/plasma", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PLEXOSUtils.jl.json b/agency-indexes/DoE/PLEXOSUtils.jl.json new file mode 100644 index 00000000..5bf8e34e --- /dev/null +++ b/agency-indexes/DoE/PLEXOSUtils.jl.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-08-12", + "metadataLastUpdated": "2021-10-29" + }, + "description": "PLEXOSUtils.jl provides functionality for loading in PLEXOS result zipfiles on disk into in-memory Julia data structures. The data structures mirror the relationships defined in the original PLEXOS result XML and provide a convenient starting point for writing application-specific code.", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "PLEXOSUtils.jl", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PLEXOSUtils.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PLEXOS_Input_Data_Generator.json b/agency-indexes/DoE/PLEXOS_Input_Data_Generator.json new file mode 100644 index 00000000..6806633e --- /dev/null +++ b/agency-indexes/DoE/PLEXOS_Input_Data_Generator.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The PLEXOS Input Data Generator (PIDG) is a tool that enables PLEXOS users to better version their data, automate data processing, collaborate in developing inputs, and transfer data between different production cost modeling and other power systems analysis software. PIDG can process data that is in a generalized format from multiple input sources, including CSV files, PostgreSQL databases, and PSS/E .raw files and write it to an Excel file that can be imported into PLEXOS with only limited manual intervention.", + "laborHours": 1687.2, + "name": "PLEXOS Input Data Generator", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/PIDG/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PIDG", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PLUMECALC,_Version_2.3.x.json b/agency-indexes/DoE/PLUMECALC,_Version_2.3.x.json new file mode 100644 index 00000000..aaf558c9 --- /dev/null +++ b/agency-indexes/DoE/PLUMECALC,_Version_2.3.x.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-12-05", + "metadataLastUpdated": "2018-12-06" + }, + "description": "PLUMECALC is a post processor to random walk particle tracking simulations of subsurface solute transport. PLUMECALC takes results of a single particle tracking run without retention processes and incorporates the effects of matrix diffusion or other retention processes for a user-specified solute source.", + "laborHours": 3511.2, + "languages": [], + "name": "PLUMECALC, Version 2.3.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PLUMECALC", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PLUMES_2.0.json b/agency-indexes/DoE/PLUMES_2.0.json new file mode 100644 index 00000000..e9ea696d --- /dev/null +++ b/agency-indexes/DoE/PLUMES_2.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-29", + "metadataLastUpdated": "2024-10-29" + }, + "description": "PLUMES2.0 is a revived version of the Visual Plumes model that was developed by Dr. Walter Frick at USEPA. PLUMES2.0\nand Visual Plumes are codes that compute initial and far-field dilution of buoyant discharges into receiving fresh or marine\nenvironments.", + "laborHours": 15.2, + "languages": [ + "Fortran" + ], + "name": "PLUMES 2.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ssmc-uw/PLUMES2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PMEDM-Legacy.json b/agency-indexes/DoE/PMEDM-Legacy.json new file mode 100644 index 00000000..412d8aca --- /dev/null +++ b/agency-indexes/DoE/PMEDM-Legacy.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "This package is part of the Likeness Python toolkit, which generates high-fidelity synthetic populations for human dynamics modeling. The PMEDM-Legacy package provides a Python interface for using the original implementation of Penalized-Maximum Entropy Dasymetric Modeling (P-MEDM) method, written in R/C++, for statistically matching population survey data from the American Community Survey's Public-Use Microdata Sample (PUMS) to sub-county spatial scales. To achieve this, it interfaces with a companion R package in the Likeness stack, PMEDMrcppPal, via the rpy2 Python-R bridge.", + "laborHours": 486.4, + "languages": [ + "Python" + ], + "name": "PMEDM-Legacy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/pmedm-legacy/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/pmedm-legacy", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PMEDMrcpp-Pal.json b/agency-indexes/DoE/PMEDMrcpp-Pal.json new file mode 100644 index 00000000..d0b68abe --- /dev/null +++ b/agency-indexes/DoE/PMEDMrcpp-Pal.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "This package is part of the Likeness Python toolkit, which generates high-fidelity synthetic populations for human dynamics modeling. It primarily supports the PMEDM-Legacy package, which provides a Python interface for using the original implementation of Penalized-Maximum Entropy Dasymetric Modeling (P-MEDM) method, written in R/C++, for statistically matching population survey data from the American Community Survey's Public-Use Microdata Sample (PUMS) to sub-county spatial scales. Model inputs specified in the Python environment are converted to R variables and passed to the PMEDMrcpp model with PMEDMrcppPal.", + "laborHours": 91.2, + "languages": [ + "R" + ], + "name": "PMEDMrcpp-Pal", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/pmedmrcpp-pal/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/pmedmrcpp-pal", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PMU_event_library_v1.0.json b/agency-indexes/DoE/PMU_event_library_v1.0.json new file mode 100644 index 00000000..1e5957ba --- /dev/null +++ b/agency-indexes/DoE/PMU_event_library_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-30", + "metadataLastUpdated": "2019-10-30" + }, + "description": "This is a library of 27 abnormal (electrical) grid events recorded at LBNL campus. Each event lasts for about 1 second. The library is published for other researchers to develop control algorithms.", + "laborHours": 45.6, + "languages": [], + "name": "PMU event library v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/pmu_event_library", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PMatch_v.1.0.json b/agency-indexes/DoE/PMatch_v.1.0.json new file mode 100644 index 00000000..c3a93a44 --- /dev/null +++ b/agency-indexes/DoE/PMatch_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-27", + "metadataLastUpdated": "2024-07-27" + }, + "description": "SAND2021-14236 O\nPMatch is a function matching plugin for Ghidra. PMatch uses hashing and p-code to create function databases and complete function matching on other binary files. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 349.6, + "languages": [ + "Python" + ], + "name": "PMatch v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/halucinator_PMatch", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNE_moment_tensor_inversions.json b/agency-indexes/DoE/PNE_moment_tensor_inversions.json new file mode 100644 index 00000000..fc551648 --- /dev/null +++ b/agency-indexes/DoE/PNE_moment_tensor_inversions.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-01-12", + "metadataLastUpdated": "2022-01-12" + }, + "description": "Data processing routines and moment tensor inversion of PNE data", + "laborHours": 0.0, + "languages": [], + "name": "PNE moment tensor inversions", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/PNE_MTINV", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-CIM-Tools_CIM-Builder.json b/agency-indexes/DoE/PNNL-CIM-Tools_CIM-Builder.json new file mode 100644 index 00000000..17a37152 --- /dev/null +++ b/agency-indexes/DoE/PNNL-CIM-Tools_CIM-Builder.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-01-15", + "metadataLastUpdated": "2025-01-15" + }, + "description": "Tool for building CIM models \"from scratch\"", + "laborHours": 48518.4, + "languages": [], + "name": "PNNL-CIM-Tools/CIM-Builder", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CIM-Tools/CIM-Builder", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-CIM-Tools_EASY-CIM.json b/agency-indexes/DoE/PNNL-CIM-Tools_EASY-CIM.json new file mode 100644 index 00000000..5eb2df56 --- /dev/null +++ b/agency-indexes/DoE/PNNL-CIM-Tools_EASY-CIM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-19", + "metadataLastUpdated": "2024-11-19" + }, + "description": "Extracting Attributes in a Simple DictionarY of CIM (EASY-CIM) is a python library to reduce the\ntime and burden of model queries using simplified data representations of CIM power system models.", + "laborHours": 2128.0, + "languages": [], + "name": "PNNL-CIM-Tools/EASY-CIM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CIM-Tools/EASY-CIM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-Comp-Mass-Spec_LIQUID.json b/agency-indexes/DoE/PNNL-Comp-Mass-Spec_LIQUID.json new file mode 100644 index 00000000..d3ed55c4 --- /dev/null +++ b/agency-indexes/DoE/PNNL-Comp-Mass-Spec_LIQUID.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The OMICS group at PNNL has developed a wide range of software utilities over the last 15+ years. These tools are used to manage data files, transform data, visualize data, and automate data processing. The software is distributed on GitHub as open source, typically under the Apache 2.0 license agreement. See https://github.com/PNNL-Comp-Mass-Spec Lipid analysis tool developed by PNNL", + "laborHours": 76015.2, + "languages": [], + "name": "PNNL-Comp-Mass-Spec/LIQUID", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LIQUID", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-Comp-Mass-Spec_LipidMiniOn.json b/agency-indexes/DoE/PNNL-Comp-Mass-Spec_LipidMiniOn.json new file mode 100644 index 00000000..bdfd96e6 --- /dev/null +++ b/agency-indexes/DoE/PNNL-Comp-Mass-Spec_LipidMiniOn.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-05-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Shiny interface for the Lipid Mining and Ontology (Lipid Mini-On) tool, which uses the Rodin R package\nThe software allows users to mine and perform enrichment of lipid based on their molecular characteristics, classification at multiple levels.", + "laborHours": 4985.6, + "languages": [], + "name": "PNNL-Comp-Mass-Spec/LipidMiniOn", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/LipidMiniOn", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-Comp-Mass-Spec_MSCC.json b/agency-indexes/DoE/PNNL-Comp-Mass-Spec_MSCC.json new file mode 100644 index 00000000..222e350d --- /dev/null +++ b/agency-indexes/DoE/PNNL-Comp-Mass-Spec_MSCC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Multidimensional Stoichiometric Compound Classification\nThis R code provides a quick access to the Multidimensional Stoichiometric Compound Classification (MSCC) constraints as published in Rivas-Ubach et al., 2018 Analytical Chemistry (DOI: 10.1021/acs.analchem.8b00529).", + "laborHours": 91.2, + "languages": [], + "name": "PNNL-Comp-Mass-Spec/MSCC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/MSCC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-CompBio_3D_Scaffold.json b/agency-indexes/DoE/PNNL-CompBio_3D_Scaffold.json new file mode 100644 index 00000000..b44572cf --- /dev/null +++ b/agency-indexes/DoE/PNNL-CompBio_3D_Scaffold.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-15", + "metadataLastUpdated": "2025-04-15" + }, + "description": "A domain-aware generative framework that takes 3D coordinates of the molecule and scaffold as an input\nand generates 3D coordinates of novel therapeutic candidates as an output while preserving the desired scaffolds. We\nshow that our model generates predominantly valid, unique, novel, and experimentally synthesizable molecules that have\ndrug-like properties similar to the molecules in the training set", + "laborHours": 2082.4, + "languages": [], + "name": "PNNL-CompBio/3D_Scaffold", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/3D_Scaffold", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-CompBio_BoltzmannMFX.json b/agency-indexes/DoE/PNNL-CompBio_BoltzmannMFX.json new file mode 100644 index 00000000..b1fabeda --- /dev/null +++ b/agency-indexes/DoE/PNNL-CompBio_BoltzmannMFX.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "BoltzmannMFX is a biological simulation code that solves chemical reaction networks using maximum entropy methods. It uses modules from MFiX-Exa and is based on the AMReX framework for massively parallel block-structured adaptive mesh applications.", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-CompBio/BoltzmannMFX", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/BoltzmannMFX", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-CompBio_bayesian-inference.json b/agency-indexes/DoE/PNNL-CompBio_bayesian-inference.json new file mode 100644 index 00000000..cf5da2ee --- /dev/null +++ b/agency-indexes/DoE/PNNL-CompBio_bayesian-inference.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Bayesian Metabolic Inference is a platform to integrate genome-scale multi-omics data into an iterative method to obtain optimized recommendations for optimal target compound production. This method uses a variational inference approach to approximate new posterior data to analyze in order to obtain useful correlations and control coefficients.", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-CompBio/bayesian-inference", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/bayesian-inference", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-CompBio_bmdrc.json b/agency-indexes/DoE/PNNL-CompBio_bmdrc.json new file mode 100644 index 00000000..f7e96f0b --- /dev/null +++ b/agency-indexes/DoE/PNNL-CompBio_bmdrc.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Python library for the calculation of benchmark dose response curves", + "laborHours": 1337.6, + "languages": [ + "Python" + ], + "name": "PNNL-CompBio/bmdrc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/bmdrc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-CompBio_perseq.json b/agency-indexes/DoE/PNNL-CompBio_perseq.json new file mode 100644 index 00000000..3da2dfed --- /dev/null +++ b/agency-indexes/DoE/PNNL-CompBio_perseq.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-05-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Per sequence functional classification and Functional annotation in addition to linking those functions to taxonomic groups presents a challenge due to many established tools performing one task and not the other creating disparate downstream data. PerSeq aims to address these challenges by performing local alignments against a reference database annotated for both aspects, function and taxonomy, to annotate sequences individually. Downstream results are merged into count tables facilitating complex analyses based on observed function or functional potential in addition to being able to separate out function by taxonomic level to determine metabolic contributions by present organisms.", + "laborHours": 775.2, + "languages": [], + "name": "PNNL-CompBio/perseq", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/perseq", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-CompBio_pf-gnn_pli.json b/agency-indexes/DoE/PNNL-CompBio_pf-gnn_pli.json new file mode 100644 index 00000000..f6d8cc15 --- /dev/null +++ b/agency-indexes/DoE/PNNL-CompBio_pf-gnn_pli.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "We have developed a deep learning based method to decode the protein-ligand interactions and predict their probability of binding. We use 3-Dimensional structure of proteins and ligand molecules with the ligand docked to the receptor and use the information at the interaction region to assess the binding of the protein-ligand complex.", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-CompBio/pf-gnn_pli", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/pf-gnn_pli", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-CompBio_srpAnalytics.json b/agency-indexes/DoE/PNNL-CompBio_srpAnalytics.json new file mode 100644 index 00000000..cc73988f --- /dev/null +++ b/agency-indexes/DoE/PNNL-CompBio_srpAnalytics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-20", + "metadataLastUpdated": "2025-02-20" + }, + "description": "This repository contains the code necessary to process any new data for the Superfund Research Program Analytics Portal.", + "laborHours": 2447.2, + "languages": [], + "name": "PNNL-CompBio/srpAnalytics", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/srpAnalytics", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-HubMAP-Proteoform-Suite_UnsupervisedSegmentation.json b/agency-indexes/DoE/PNNL-HubMAP-Proteoform-Suite_UnsupervisedSegmentation.json new file mode 100644 index 00000000..9a6119ff --- /dev/null +++ b/agency-indexes/DoE/PNNL-HubMAP-Proteoform-Suite_UnsupervisedSegmentation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-09-26", + "metadataLastUpdated": "2024-09-26" + }, + "description": "Automatically label regions of histology images.", + "laborHours": 684.0, + "languages": [], + "name": "PNNL-HubMAP-Proteoform-Suite/UnsupervisedSegmentation", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-HubMAP-Proteoform-Suite/UnsupervisedSegmentation", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-OE-Redox-Flow-Battery-Cost-Tool_PNNL-OE-Redox-Flow-Battery-Cost-Tool.json b/agency-indexes/DoE/PNNL-OE-Redox-Flow-Battery-Cost-Tool_PNNL-OE-Redox-Flow-Battery-Cost-Tool.json new file mode 100644 index 00000000..84a68db5 --- /dev/null +++ b/agency-indexes/DoE/PNNL-OE-Redox-Flow-Battery-Cost-Tool_PNNL-OE-Redox-Flow-Battery-Cost-Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL Cost-Performance Tool (DOE-OE sponsored) for Estimation of Capital Costs for Redox Flow Batteries. Battelle IPID 30401. Copyright \u00a9 2013, Battelle Memorial Institute.", + "laborHours": 11688.8, + "languages": [], + "name": "PNNL-OE-Redox-Flow-Battery-Cost-Tool/PNNL-OE-Redox-Flow-Battery-Cost-Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-OE-Redox-Flow-Battery-Cost-Tool/PNNL-OE-Redox-Flow-Battery-Cost-Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-PreProcessor_v5.x.json b/agency-indexes/DoE/PNNL-PreProcessor_v5.x.json new file mode 100644 index 00000000..11b1a592 --- /dev/null +++ b/agency-indexes/DoE/PNNL-PreProcessor_v5.x.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-02-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "a new release of the software tool that includes newly developed algorithms housed along\npreviously released ones within a single user interface.\nThe new functionalities are:\nCCS raw data converter (iEdison No. 0685901-23-0100), IPID 32762-E.\nIM-MS-DDA converter and data format (iEdison No. 0685901-23-0099), IPID 32761-E.\nThe previously developed functionalities are:\nPNNL-PreProcessor, IPID 31727-E.\n2DLC-MS to LC-IM-MS data file converter, IPID 32136-E.\nIMS data file transformations, IPID 32137-E.\nRemarks about the PNNL-PreProcessor:\nDirectly reads Agilent MassHunter (.d) data files and generates new Agilent MassHunter (.d) data files with\nenhanced raw signal quality and/or transformed data. Can also process UIMF files.\nHas both command-line and graphical user interfaces.\nPNNL provides the software executable, freely available for download (https://pnnl-comp-massspec.github.io/PNNL-PreProcessor) and it can be utilized by Agilent customers for non-commercial use.\nThe source code is not publicly available, an internal source code repository is maintained at PNNL", + "homepageURL": "https://pnnl-comp-mass-spec.github.io/PNNL-PreProcessor", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-PreProcessor v5.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://pnnl-comp-mass-spec.github.io/PNNL-PreProcessor", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://pnnl-comp-mass-spec.github.io/PNNL-PreProcessor", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-m-q_lipidimea.json b/agency-indexes/DoE/PNNL-m-q_lipidimea.json new file mode 100644 index 00000000..238d37e5 --- /dev/null +++ b/agency-indexes/DoE/PNNL-m-q_lipidimea.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-14", + "metadataLastUpdated": "2025-04-14" + }, + "description": "Lipidomics Integrated Multi-Experiment Analysis tool", + "laborHours": 6824.8, + "languages": [], + "name": "PNNL-m-q/lipidimea", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-m-q/lipidimea", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-m-q_lipidoz.json b/agency-indexes/DoE/PNNL-m-q_lipidoz.json new file mode 100644 index 00000000..0153aa3f --- /dev/null +++ b/agency-indexes/DoE/PNNL-m-q_lipidoz.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-04-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Python tool for determination of lipid double bond locations from OzID data", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-m-q/lipidoz", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-m-q/lipidoz", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-m-q_metabolomics_ensemble_score.json b/agency-indexes/DoE/PNNL-m-q_metabolomics_ensemble_score.json new file mode 100644 index 00000000..52d56c1d --- /dev/null +++ b/agency-indexes/DoE/PNNL-m-q_metabolomics_ensemble_score.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-16", + "metadataLastUpdated": "2024-12-16" + }, + "description": "An ensemble machine learning method to improve spectral similarity scores for GC-MS data", + "laborHours": 197.6, + "languages": [], + "name": "PNNL-m-q/metabolomics_ensemble_score", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-m-q/metabolomics_ensemble_score", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL-m-q_mzapy.json b/agency-indexes/DoE/PNNL-m-q_mzapy.json new file mode 100644 index 00000000..eafd961f --- /dev/null +++ b/agency-indexes/DoE/PNNL-m-q_mzapy.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Python package that provides an interface to raw MS data in the MZA format.", + "laborHours": 0.0, + "languages": [], + "name": "PNNL-m-q/mzapy", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-m-q/mzapy", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL_Biodiversity_Library_Plugin.json b/agency-indexes/DoE/PNNL_Biodiversity_Library_Plugin.json new file mode 100644 index 00000000..782224ec --- /dev/null +++ b/agency-indexes/DoE/PNNL_Biodiversity_Library_Plugin.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PNNL Biodiversity Plugin is a software tool for Skyline and is designed to allow pathway-centric browsing of peptides previously identified by LC-MS/MS. The plugin is designed to assist in SRM assay design or DIA data analysis. Users select an organism and biological pathway of interest, then the plugin shows information about the associated peptides.", + "laborHours": 282218.4, + "languages": [], + "name": "PNNL Biodiversity Library Plugin", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PNNL-Biodiversity-Library-Plugin", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PNNL_OMICS.json b/agency-indexes/DoE/PNNL_OMICS.json new file mode 100644 index 00000000..6d9a3221 --- /dev/null +++ b/agency-indexes/DoE/PNNL_OMICS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PNNL Omics Library (PNNLOmics.dll) is a collection of data analysis, file I/O, and visualization routines used by several of the omics-related software developed at PNNL.", + "laborHours": 19516.8, + "languages": [], + "name": "PNNL OMICS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PNNL-Omics", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/POEK.json b/agency-indexes/DoE/POEK.json new file mode 100644 index 00000000..78d7f8db --- /dev/null +++ b/agency-indexes/DoE/POEK.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-08-07" + }, + "description": "POEK (Python Optimization Expression Kernel) is a Python library that supports the expression and manipulation of algebraic expressions commonly used in optimization applications. POEK interfaces with the COEK library to support fast methods for defining and managing expressions and performing automatic differentiation. POEK also interfaces with COEK to directly interface with optimization solvers (i.e. without relying on file I/O). SAND2019-14492 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 98070.4, + "languages": [ + "C++", + "C", + "CMake", + "AMPL", + "NMODL", + "Python" + ], + "name": "POEK", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/coek", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/POESIE:_Embedding_Scripting_Languages_for_Mochi_Services.json b/agency-indexes/DoE/POESIE:_Embedding_Scripting_Languages_for_Mochi_Services.json new file mode 100644 index 00000000..7bd054a6 --- /dev/null +++ b/agency-indexes/DoE/POESIE:_Embedding_Scripting_Languages_for_Mochi_Services.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-31", + "metadataLastUpdated": "2022-01-31" + }, + "description": "POESIE is a Mochi microservice designed to run interpreters of various scripting languages (currently Lua and Python) and make them accessible remotely.", + "laborHours": 0.0, + "languages": [], + "name": "POESIE: Embedding Scripting Languages for Mochi Services", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-poesie/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-poesie", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/POSCArchitected_Composite_Data_Type_Framework.json b/agency-indexes/DoE/POSCArchitected_Composite_Data_Type_Framework.json new file mode 100644 index 00000000..c4427470 --- /dev/null +++ b/agency-indexes/DoE/POSCArchitected_Composite_Data_Type_Framework.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "With Exascale performance and its challenges in\nmind, one ubiquitous concern among architects is energy efficiency.\nPetascale systems projected to Exascale systems are\nunsustainable at current power consumption rates. One major\ncontributor to system-wide power consumption is the number of\nmemory operations leading to data movement and management\ntechniques applied by the runtime system. To address this\nproblem, we present the concept of the Architected Composite\nData Types (ACDT) framework. The framework is made aware of\ndata composites, assigning them a specific layout, transformations\nand operators. Data manipulation overhead is amortized over a\nlarger number of elements and program performance and power\nefficiency can be significantly improved.", + "homepageURL": "http://hpc.pnl.gov/projects/POCR", + "laborHours": 0.0, + "languages": [], + "name": "POSCArchitected Composite Data Type Framework", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://hpc.pnl.gov/projects/POCR", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/POWERSAS.m___A_POWER_GRID_ANALYSIS_TOOKBOX_BASED_ON_SEMI-ANALYTICAL_SOLUTION_APPROACH_.json b/agency-indexes/DoE/POWERSAS.m___A_POWER_GRID_ANALYSIS_TOOKBOX_BASED_ON_SEMI-ANALYTICAL_SOLUTION_APPROACH_.json new file mode 100644 index 00000000..5d62997d --- /dev/null +++ b/agency-indexes/DoE/POWERSAS.m___A_POWER_GRID_ANALYSIS_TOOKBOX_BASED_ON_SEMI-ANALYTICAL_SOLUTION_APPROACH_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-12-30", + "metadataLastUpdated": "2022-01-03" + }, + "description": "PowerSAS.m is a robust, efficient and scalable power grid analysis framework based on semi-analytical solutions (SAS) technology for MATLAB/Octave users. It provides various functionalities for power grid analysis including steady-state analysis, dynamic analysis and hybrid extended-term analysis. It features high numerical robustness, enhanced computational performance and highly customizable and extensible user interfaces.", + "laborHours": 0.0, + "languages": [], + "name": "POWERSAS.m ( A POWER GRID ANALYSIS TOOKBOX BASED ON SEMI-ANALYTICAL SOLUTION APPROACH)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ANL-CEEESA/powersas.m/blob/release/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-CEEESA/powersas.m", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PPO_And_Friends.json b/agency-indexes/DoE/PPO_And_Friends.json new file mode 100644 index 00000000..dffeaeb7 --- /dev/null +++ b/agency-indexes/DoE/PPO_And_Friends.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "PPO and Friends (PPOAF) is a pytorch implementation of proximal policy optimization for single- and\nmulti-agent reinforcement learning (the PPO), along with several optimizations and add-ons (the Friends)\nto enable efficient MPI-parallelized model training on HPC clusters.", + "laborHours": 6536.0, + "languages": [], + "name": "PPO And Friends", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ppo_and_friends", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PRESSURE-FILM_OPEN_SOURCE_SCANNING_AND_MAPPING.json b/agency-indexes/DoE/PRESSURE-FILM_OPEN_SOURCE_SCANNING_AND_MAPPING.json new file mode 100644 index 00000000..876263cb --- /dev/null +++ b/agency-indexes/DoE/PRESSURE-FILM_OPEN_SOURCE_SCANNING_AND_MAPPING.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-17", + "metadataLastUpdated": "2023-03-17" + }, + "description": "SF-22-099 Pressure-film Open Source Scanning and Mapping (POSSM) is software that analyses images of pressure-film (scans or photographs). POSSM collects data from that analysis in order to produce a number of visual aides, including pressure maps, histograms, and 3d surface plots. POSSM is designed to be able to analyze an entire folder full of images, exporting numeric data as .csv files and visual graphics as .png files.", + "laborHours": 0.0, + "languages": [], + "name": "PRESSURE-FILM OPEN SOURCE SCANNING AND MAPPING", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PatrickGrider/POSSM", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PRESTA_MPI_Benchmark.json b/agency-indexes/DoE/PRESTA_MPI_Benchmark.json new file mode 100644 index 00000000..b9e95363 --- /dev/null +++ b/agency-indexes/DoE/PRESTA_MPI_Benchmark.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-27", + "metadataLastUpdated": "2020-10-29" + }, + "description": "The PRESTA MPI Benchmark software is a project that is used to evaluate the network communication performance of computer systmes using the Message Passing Interface (MPI) communication library.", + "laborHours": 2705.6, + "languages": [], + "name": "PRESTA MPI Benchmark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/phloem", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PRIME.json b/agency-indexes/DoE/PRIME.json new file mode 100644 index 00000000..ca488061 --- /dev/null +++ b/agency-indexes/DoE/PRIME.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-12-02", + "metadataLastUpdated": "2021-12-02" + }, + "description": "SAND2021-0565 O PRIME is a modeling framework designed for the real-time characterization and forecasting of partially observed epidemics. The method is designed to help guide medical resource allocation in the early epoch of the outbreak. Characterization is the estimation of infection spread parameters using daily counts of symptomatic patients. The estimation problem is posed as one of Bayesian inference and solved using a Markov Chain Monte Carlo technique. The framework can accommodate multiple epidemic waves and can help identify different disease dynamics at the regional, state, and country levels. Examples are provided using publicly available COVID-19 data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PRIME", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PRIME", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PRISM.json b/agency-indexes/DoE/PRISM.json new file mode 100644 index 00000000..4069c5dd --- /dev/null +++ b/agency-indexes/DoE/PRISM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2019-05-13", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Progressive Resolution for Imaging & Storage Management - This software provides high resolution volume rendering for desktops & immersive environments regardless of scale.", + "laborHours": 27284.0, + "languages": [], + "name": "PRISM", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLab/PRISM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PRISM_Class_Library.json b/agency-indexes/DoE/PRISM_Class_Library.json new file mode 100644 index 00000000..06173927 --- /dev/null +++ b/agency-indexes/DoE/PRISM_Class_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PRISM Class Library (PRISM.dll) is a collection of routines used by many of the software tools that support the Proteomics Research Information and Management System (PRISM) at PNNL. Although written for use by PRISM tools, the methods in the PRISM class library are general utility methods, and are not dependent on any PNNL resources.", + "laborHours": 15549.6, + "languages": [], + "name": "PRISM Class Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PRISM-Class-Library", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PROCDN.json b/agency-indexes/DoE/PROCDN.json new file mode 100644 index 00000000..c0096b01 --- /dev/null +++ b/agency-indexes/DoE/PROCDN.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "Procdn is a collection of software that provides support in the Linux kernel for Globus distinguished name (DNs). The primary component is a Linux kernel module that creates data structures in the kernel for associating DNs with user processes. The other components included with the software help initiate this mapping in the kernel, including patches for the Flobus toolkit and a sample implementation for various batch scheduler systems. In addition, the software includes some utilities for listing current mappings in the kernel.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "PROCDN", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PROM__Probabilistic_Regulation_of_Metabolism__Service.json b/agency-indexes/DoE/PROM__Probabilistic_Regulation_of_Metabolism__Service.json new file mode 100644 index 00000000..468f1fce --- /dev/null +++ b/agency-indexes/DoE/PROM__Probabilistic_Regulation_of_Metabolism__Service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This service enables the creation of FBA model constraint objects that are based on regulatory networks and expression data. Constraints are constructed by either automatically aggregating necessary information from the CDS (if available for a given genome), or by adding user expression and regulatory data. PROM provides the capability to simulate transcription factor knockout phenotypes. PROM model constraint objects are created in a user's workspace, and can be operated on and used in conjunction with an FBA model with the KBase FBA Modeling Service.", + "laborHours": 1124.8, + "languages": [], + "name": "PROM (Probabilistic Regulation of Metabolism) Service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/prom_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PRUNERS_Toolset.json b/agency-indexes/DoE/PRUNERS_Toolset.json new file mode 100644 index 00000000..27e7606d --- /dev/null +++ b/agency-indexes/DoE/PRUNERS_Toolset.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "Reproducibility is highly desirable for parallel applications, but as they are run on increasingly large and heterogeneous platforms, reproducibility of numerical results or code behaviors is becoming less and less obtainable. The same code can produce different results or occasional failures such as a crash on different systems or even across different runs on the same hardware. PRUNERS is a research and development project that aims at innovating scalable techniques to aid applications to obtain the reproducibility. Specifically, our strategy is to accomplish this by developing a multilevel analysis and control toolset called the PRUNERS Toolset, which combines static and dynamic analysis techniques to detect, control and eliminate targeted sources of non-determinism, as introduced through parallel programming libraries and APIs.", + "laborHours": 516.8, + "languages": [], + "name": "PRUNERS Toolset", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PRUNERS/PRUNERS-Toolset/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PRUNERS/PRUNERS-Toolset", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PRUNERS_openmp.json b/agency-indexes/DoE/PRUNERS_openmp.json new file mode 100644 index 00000000..0c99b89f --- /dev/null +++ b/agency-indexes/DoE/PRUNERS_openmp.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "This is the repository for openmp, PRUNERS-PProviding Reproducibility for Uncovering Non-deterministic Errors in Runs on Supercomputers developed at Lawrence Livermore National Laboratory.\n", + "laborHours": 66150.4, + "languages": [], + "name": "PRUNERS/openmp", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PRUNERS/openmp", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PS-Samp__Phase-Space_Sampling_.json b/agency-indexes/DoE/PS-Samp__Phase-Space_Sampling_.json new file mode 100644 index 00000000..e3014350 --- /dev/null +++ b/agency-indexes/DoE/PS-Samp__Phase-Space_Sampling_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-11-10", + "metadataLastUpdated": "2022-01-28" + }, + "description": "PS-Samp is a software that reduces a given dataset by pruning data. Data is downselected such that it uniformly spans the phase-space, thereby ensuring that the full dataset is correctly represented. The algorithm relies on estimating the probability map of the data and using it to construct an acceptance probability. The software is designed to handle very large data sets.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PS-Samp (Phase-Space Sampling)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Phase-space-sampling", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PSBeam.json b/agency-indexes/DoE/PSBeam.json new file mode 100644 index 00000000..eca29069 --- /dev/null +++ b/agency-indexes/DoE/PSBeam.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Image Processing Pipelines for Photon Controls and Data Systems", + "laborHours": 1200.8, + "name": "PSBeam", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/psbeam/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/psbeam", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PSD_GMM_Trainer.json b/agency-indexes/DoE/PSD_GMM_Trainer.json new file mode 100644 index 00000000..b807ce02 --- /dev/null +++ b/agency-indexes/DoE/PSD_GMM_Trainer.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-24", + "metadataLastUpdated": "2020-01-24" + }, + "description": "Code takes a data file of input features of a set of digitized pulses and converts the file to three vectors describing a two-component Gaussian mixture model of the input pulses. \n\nThese three vectors can then be applied mathematically to a set of input feature data of digitized pulses to \ngenerate soft-scores describing the likelihood of each pulse's membership in each of the two Gaussian modeled components. \n\nThe operation of the code also displays graphics to the user for \ninterpreting the output vectors and\ndistribution of the soft-scores of the input data.", + "laborHours": 182.4, + "languages": [], + "name": "PSD GMM Trainer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/trainGMM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PSI_Interface.json b/agency-indexes/DoE/PSI_Interface.json new file mode 100644 index 00000000..7924f181 --- /dev/null +++ b/agency-indexes/DoE/PSI_Interface.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "C# reader/writer for mzIdentML files (.mzID). Also supports reading mzML files.", + "laborHours": 29609.6, + "languages": [], + "name": "PSI_Interface", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PSI-Interface", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PSI__PowerSimulations.jl__[SWR-23-104].json b/agency-indexes/DoE/PSI__PowerSimulations.jl__[SWR-23-104].json new file mode 100644 index 00000000..954147c9 --- /dev/null +++ b/agency-indexes/DoE/PSI__PowerSimulations.jl__[SWR-23-104].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-03", + "metadataLastUpdated": "2024-03-11" + }, + "description": "PowerSimulations.jl is a Julia-based BSD- licensed power system operations simulation tool developed as a flexible and open source software for quasi-static power systems simulations including Production Cost Models. PowerSimulations.jl tackles the issues of developing a simulation model in a modular way providing tools for the formulation of decision models and emulation models that can be solved independently or in an interconnected fashion. \n\nFor further information regarding the Sienna modeling framework at NREL, see: https://www.nrel.gov/analysis/sienna.html", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "PSI (PowerSimulations.jl) [SWR-23-104]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-Sienna/PowerSimulations.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.27.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PSL_Uncertainty_Calculator_v._1.2.json b/agency-indexes/DoE/PSL_Uncertainty_Calculator_v._1.2.json new file mode 100644 index 00000000..cf2a53b8 --- /dev/null +++ b/agency-indexes/DoE/PSL_Uncertainty_Calculator_v._1.2.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-01-14", + "metadataLastUpdated": "2019-01-14" + }, + "description": "The PSL Uncertainty Calculator can be used to determine the total uncertainty of a measurement system. In many measurement applications, the quantity of interest is not measured directly, but computed from a combination of several measured values. While the uncertainty of each measurand is typically straightforward to determine, total uncertainty of the output value requires calculation. This software calculates uncertainty using the framework provided by the Guide to Expression of Uncertainty in Measurements, JCGM100-2008E (GUM), and a Monte Carlo simulation as described by Supplement 1 to the GUM, by providing an easy to use graphical user interface and a Python package for running the calculations.", + "laborHours": 19228.0, + "languages": [ + "Python" + ], + "name": "PSL Uncertainty Calculator v. 1.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SandiaPSL/SandiaPSL.github.io", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PSP_Interface_for_EPICS_Channel_Access.json b/agency-indexes/DoE/PSP_Interface_for_EPICS_Channel_Access.json new file mode 100644 index 00000000..cc87eda0 --- /dev/null +++ b/agency-indexes/DoE/PSP_Interface_for_EPICS_Channel_Access.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Wrapper around pyca for simpler usage. Used in various LCLS apps to do handle access.", + "laborHours": 471.2, + "name": "PSP Interface for EPICS Channel Access", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/psp/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/psp", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PSSE_Network_Reduction.json b/agency-indexes/DoE/PSSE_Network_Reduction.json new file mode 100644 index 00000000..ddd9c24e --- /dev/null +++ b/agency-indexes/DoE/PSSE_Network_Reduction.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-05-11", + "metadataLastUpdated": "2021-05-11" + }, + "description": "This code can reduce power system network models in PSSE. The user selects single-port or two-port subnetworks for reduction, and the software reduces the subnetwork as described in the paper \"Power System Network Reduction for Power Hardware-in-the-Loop Simulation\" (submitted).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PSSE Network Reduction", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PSSE_Network_Reduction", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PSUADE.json b/agency-indexes/DoE/PSUADE.json new file mode 100644 index 00000000..90fd0f29 --- /dev/null +++ b/agency-indexes/DoE/PSUADE.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-02", + "metadataLastUpdated": "2023-02-07" + }, + "description": "PSUADE (Problem Solving testbed for Uncertainty Analysis and Design Exploration) is a mathematical software useful for performing uncertainty quantification and sensitivity analysis.", + "laborHours": 0.0, + "languages": [], + "name": "PSUADE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PSWALKER.json b/agency-indexes/DoE/PSWALKER.json new file mode 100644 index 00000000..81412482 --- /dev/null +++ b/agency-indexes/DoE/PSWALKER.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Beam Alignment module for Photon Controls and Data Systems", + "laborHours": 2766.4, + "name": "PSWALKER", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pswalker/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pswalker", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PSY__PowerSystems.jl__[SWR-23-105].json b/agency-indexes/DoE/PSY__PowerSystems.jl__[SWR-23-105].json new file mode 100644 index 00000000..46a30bb8 --- /dev/null +++ b/agency-indexes/DoE/PSY__PowerSystems.jl__[SWR-23-105].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-01-10", + "metadataLastUpdated": "2024-03-11" + }, + "description": "PowerSystems.jl is a package to organize and manipulate data for the study of energy systems with diverse modeling requirements. This software serves two main purposes: to reduce the burden of large power system data set development, and to promote reproducible research and simulation. PowerSystems.jl implements an abstract hierarchy to represent and customize power systems data and includes data containers for quasi-static and dynamic simulation applications. Key features include efficient management of large quantities of time series data, optimized serialization, and comprehensive validation capabilities.\n\nFor further information regarding the Sienna modeling framework at NREL, see: https://www.nrel.gov/analysis/sienna.html", + "laborHours": 0.0, + "languages": [ + "Julia" + ], + "name": "PSY (PowerSystems.jl) [SWR-23-105]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-Sienna/PowerSystems.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.2.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PTFREAD_v._188r.json b/agency-indexes/DoE/PTFREAD_v._188r.json new file mode 100644 index 00000000..cfa4af84 --- /dev/null +++ b/agency-indexes/DoE/PTFREAD_v._188r.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-04-02", + "metadataLastUpdated": "2019-04-02" + }, + "description": "PTFREAD is an Excel Add-In used to post-process MELCOR plotfile data for plotting and animation of MELCOR results. ", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 21888.0, + "languages": [], + "name": "PTFREAD v. 188r", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 188r" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PTMdiscoverer.json b/agency-indexes/DoE/PTMdiscoverer.json new file mode 100644 index 00000000..9cf59135 --- /dev/null +++ b/agency-indexes/DoE/PTMdiscoverer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-11", + "metadataLastUpdated": "2025-02-24" + }, + "description": "PTMdiscoverer is a new approach that leverages generative AI to accelerate the discovery of post-translational\nmodifications (PTMs) in proteomics experiments.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 182.4, + "languages": [], + "name": "PTMdiscoverer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PUFFIn.json b/agency-indexes/DoE/PUFFIn.json new file mode 100644 index 00000000..b821814d --- /dev/null +++ b/agency-indexes/DoE/PUFFIn.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PUFFIn software package is a graphical user interface that allows for photon and electron beam calculations using the\nPENELOPE computer code. It prepares the required input files and displays the resulting output data. It can be used by\nanyone interested in the interaction of photon or electron beams with matter", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "PUFFIn", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PV-Lab_SL-PerovskiteOpt.json b/agency-indexes/DoE/PV-Lab_SL-PerovskiteOpt.json new file mode 100644 index 00000000..24e920d2 --- /dev/null +++ b/agency-indexes/DoE/PV-Lab_SL-PerovskiteOpt.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "buonassisi@mit.edu" + }, + "date": { + "created": "2021-11-10", + "metadataLastUpdated": "2021-11-10" + }, + "description": "This is a code and data repository to conduct Bayesian Optimization with knowledge constraints for manufacturing process of perovskite solar cells ", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PV-Lab/SL-PerovskiteOpt", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PV-Lab/SL-PerovskiteOpt", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PVAnalytics_[SWR-20-33].json b/agency-indexes/DoE/PVAnalytics_[SWR-20-33].json new file mode 100644 index 00000000..61795be6 --- /dev/null +++ b/agency-indexes/DoE/PVAnalytics_[SWR-20-33].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-05-04", + "metadataLastUpdated": "2023-05-05" + }, + "description": "PVAnalytics inputs long term (multiple years) photovoltaic (PV) outdoor sensor data and completes autonomous quality assurance (QA) analysis on the data. Time series data from individual sensors such as electric meters, inverter outputs, irradiance, and temperature sensors are compared to physically expected outputs of these sensors under clear sky conditions based on the latitude, longitude, and orientation of the PV system. PVAnalytics outputs as QA pass or fail for each sensor, reasons determined for failure, time series flags identifying QA thresholds have been exceeded, flags for sunny days, the time zone found for the given sensor, sensor drift, time periods for passing data, and results of orientation checks.", + "laborHours": 0.0, + "languages": [ + "python" + ], + "name": "PVAnalytics [SWR-20-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pvlib/pvanalytics", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PV_DMFA_[SWR-21-105].json b/agency-indexes/DoE/PV_DMFA_[SWR-21-105].json new file mode 100644 index 00000000..1704f891 --- /dev/null +++ b/agency-indexes/DoE/PV_DMFA_[SWR-21-105].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-03-21", + "metadataLastUpdated": "2023-09-11" + }, + "description": "The Photovoltaic Dynamic Material Flow Assessment (PV DMFA) model (also referred to here as \u201cThe model\u201d) is a computational framework written in Python based on utility-scale PV electricity generation to quantify time-series stocks and flows of PV materials primarily in crystalline silicon PV technologies. The model evaluates cradle-to-cradle life cycle of utility-scale solar PV systems in the United States in the period 2000-2100. PV DMFA serves as a sustainability analysis tool to assess the impacts of different material circularity practices (i.e., reduce, reuse/refurbish, remanufacture, and recycle), PV module design shifts and sensitivity of material processing and technology related parameters to material installations, waste creation and raw material depletion in PV material supply chains. This tool enables advanced planning for future material needs and informs sustainable pathways for PV material management in the circular economy. This tool could be helpful to a wide range of stakeholders; Particularly, researchers and manufacturers looking for technoeconomic and/or environmental life cycle analysis (LCA) feedback for renewable energy (RE) systems.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "PV DMFA [SWR-21-105]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PV-DMFA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PV_Degradation_Tools_[SWR-20-71].json b/agency-indexes/DoE/PV_Degradation_Tools_[SWR-20-71].json new file mode 100644 index 00000000..bf042ec1 --- /dev/null +++ b/agency-indexes/DoE/PV_Degradation_Tools_[SWR-20-71].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-07-01", + "metadataLastUpdated": "2024-06-05" + }, + "description": "This open-source tool functions for calculating degradation of photovoltaic modules. For example, functions to calculate front and rear relative Humidity, as well as Acceleration Factors. A degradation calculation function is also being developed, considering humidity and spectral irradiances models.", + "laborHours": 3617.6, + "languages": [ + "Python" + ], + "name": "PV Degradation Tools [SWR-20-71]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PVDegradationTools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.3.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PV_Generation_and_Load_Forecasting_for_Adjuntas_PR_Community_Microgrids.json b/agency-indexes/DoE/PV_Generation_and_Load_Forecasting_for_Adjuntas_PR_Community_Microgrids.json new file mode 100644 index 00000000..5f31d038 --- /dev/null +++ b/agency-indexes/DoE/PV_Generation_and_Load_Forecasting_for_Adjuntas_PR_Community_Microgrids.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "sundararajaa@ornl.gov" + }, + "date": { + "created": "2024-12-04", + "metadataLastUpdated": "2025-01-06" + }, + "description": "Existing frameworks to forecast time-series photovoltaic (PV) output power and consumer load for microgrid operations and controls assume a near-continuous availability of real-time input features from the field assets such as PV inverters, energy meters, and weather station. These incoming data points are used to periodically retrain models and update forecast snapshots over a moving horizon window, be it one hour-ahead, one-day ahead, or one-week ahead. However, such frameworks are not resilient to disruptions in data availability caused by losses in communications between the field sensors and data loggers. Hence, there is a need for programs that assume no availability of real-time microgrid asset data and still make reliable forecasts that can be used for decision-making. Such programs would be apt to function in extreme weather events such as hurricanes and would use lightweight recursive time-series models to independently forecast solar irradiance and ambient temperature, then compute PV power from those forecasts, as well as independently forecast consumer load.\n\n\tThe codebase performs forecasting for the scenario of when the microgrid does not have a reliable access to forecasts or real-time observations of solar irradiance (I) and ambient temperature (AT) and load (Load) to be able to adequately forecast, in real-time, the PV power production or a business' load. In this case, using historical values of PV power and load, a univariate forecasting of generation and consumption are respectively made. The use-case in particular has two sub-scenarios: one, a normal 7-day ahead forecast where the unavailability of real-time data is assumed due to infrastructure issues such as loss of communication or sensor maintenance or service downtimes. Whereas a hurricane-caused unavailability of real-time data requires a second model trained specifically on historical hurricane days to be able to capture the extreme day behavior of generation in particular, and load if applicable.\n\nA gradient boosted regression tree comprises an ensemble of additive models that map between the input of historical values (be it irradiance, temperature, or load) and their corresponding output forecasts of a given horizon such that the individual learner predictions are summed up over the total number of such learners in the ensemble to produce an aggregate forecast. A weighting mechanism is applied to the training data in each iteration, where actual and forecast values are compared to penalize incorrect forecasts by increasing the weight and reducing it to reward correct forecasts.\n\nThe code's benefits are that it: (a) accounts for a contingency where communication loss renders newly measured real-time data unavailable for model tuning and snapshot updates; (b) presents blind forecasting that recursively determines the next time-step value in a horizon using the forecast of the same attribute from a prior step; and (c) employs lightweight models that, once trained, can reliably generalize for different horizons, which make them suitable for enhancing the resilience of field microgrids prone to extreme events that encounter disruptions to data availability.", + "homepageURL": "https://code.ornl.gov/6a6/pv-and-load-forecasting-use-case-3.git", + "laborHours": 182.4, + "languages": [ + "Python" + ], + "name": "PV Generation and Load Forecasting for Adjuntas PR Community Microgrids", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/6a6/pv-and-load-forecasting-use-case-3.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PV_ICE:_PV_in_the_Circular_Economy,_Dynamic_Energy_and_Materials_Tool__PV_ICE_.json b/agency-indexes/DoE/PV_ICE:_PV_in_the_Circular_Economy,_Dynamic_Energy_and_Materials_Tool__PV_ICE_.json new file mode 100644 index 00000000..08f9dabd --- /dev/null +++ b/agency-indexes/DoE/PV_ICE:_PV_in_the_Circular_Economy,_Dynamic_Energy_and_Materials_Tool__PV_ICE_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-03-24", + "metadataLastUpdated": "2021-08-17" + }, + "description": "This open-source tool implements Circular Economy metrics for photovoltaic (PV) materials. It can be used to quantify and assign a value framework to efforts on re-design, reduction, replacement, reuse, recycling, and lifetime and reliability increases in the PV value chain.\n\nThe PV_ICE is leveraging published data from different sources on PV manufacturing and predicted technological changes. Input data is being compiled here\n\nThis tool will help implement circularity metrics, quantify and assign a value framework to efforts on re-design, reduction, replacement, reusage, recycling, and lifetime and reliability increases on PV.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PV_ICE: PV in the Circular Economy, Dynamic Energy and Materials Tool (PV ICE)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PV_ICE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v. 2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PV_LIB_Toolbox.json b/agency-indexes/DoE/PV_LIB_Toolbox.json new file mode 100644 index 00000000..ee0265c6 --- /dev/null +++ b/agency-indexes/DoE/PV_LIB_Toolbox.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "While an organized source of reference information on PV performance modeling is certainly valuable, there is nothing to match the availability of actual examples of modeling algorithms being used in practice. To meet this need, Sandia has developed a PV performance modeling toolbox (PV_LIB) for Matlab. It contains a set of well-documented, open source functions and example scripts showing the functions being used in practical examples. This toolbox is meant to help make the multi-step process of modeling a PV system more transparent and provide the means for model users to validate and understand the models they use and or develop. It is fully integrated into Matlab's help and documentation utilities. The PV_LIB Toolbox provides more than 30 functions that are sorted into four categories", + "laborHours": 532.0, + "name": "PV_LIB Toolbox", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cwhanse/PVLIB_Python", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PV_LIB_Toolbox_v._1.3.json b/agency-indexes/DoE/PV_LIB_Toolbox_v._1.3.json new file mode 100644 index 00000000..0038630e --- /dev/null +++ b/agency-indexes/DoE/PV_LIB_Toolbox_v._1.3.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PV_LIB comprises a library of Matlab? code for modeling photovoltaic (PV) systems. Included are functions to compute solar position and to estimate irradiance in the PV system's plane of array, cell temperature, PV module electrical output, and conversion from DC to AC power. Also included are functions that aid in determining parameters for module performance models from module characterization testing. PV_LIB is open source code primarily intended for research and academic purposes. All algorithms are documented in openly available literature with the appropriate references included in comments within the code.", + "laborHours": 3359.2, + "name": "PV_LIB Toolbox v. 1.3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SandiaTestAccount/PVLIB_Matlab", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PV_Shading_Database_[SWR-16-36].json b/agency-indexes/DoE/PV_Shading_Database_[SWR-16-36].json new file mode 100644 index 00000000..94bc9287 --- /dev/null +++ b/agency-indexes/DoE/PV_Shading_Database_[SWR-16-36].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-02", + "metadataLastUpdated": "2025-03-26" + }, + "description": "The software is a simplified method for modeling the impact of arbitrary partial shading conditions on PV array performance.\nThe software implements a simple method for modeling shade loss: a database of shade impact results (loss percentages), generated using a validated, detailed simulation tool and encompassing a wide variety of shading scenarios. The database is intended to predict shading losses in crystalline silicon PV arrays and is accessed using basic inputs generally available in any PV simulation tool. Performance predictions using the database are within 1-2% of measured data for several partially shaded PV systems, and within 1% of those predicted by the full, detailed simulation tool on an annual basis. The shade loss database shows potential to considerably improve performance prediction for partially shaded PV systems.", + "homepageURL": "https://github.com/NREL/ssc/blob/develop/shared/lib_pv_shade_loss_mpp.cpp", + "laborHours": 2204.0, + "languages": [ + "C++" + ], + "name": "PV Shading Database [SWR-16-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ssc/blob/develop/shared/lib_pv_shade_loss_mpp.cpp", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PV_Soiling_Detection_[SWR-18-02].json b/agency-indexes/DoE/PV_Soiling_Detection_[SWR-18-02].json new file mode 100644 index 00000000..32939def --- /dev/null +++ b/agency-indexes/DoE/PV_Soiling_Detection_[SWR-18-02].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-23", + "metadataLastUpdated": "2023-01-20" + }, + "description": "A python library used to estimate soiling losses from PV energy production data.", + "laborHours": 744.8, + "languages": [ + "Python" + ], + "name": "PV Soiling Detection [SWR-18-02]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pv_soiling", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.2.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PV_TOMCAT.json b/agency-indexes/DoE/PV_TOMCAT.json new file mode 100644 index 00000000..a474c1da --- /dev/null +++ b/agency-indexes/DoE/PV_TOMCAT.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-05", + "metadataLastUpdated": "2018-11-05" + }, + "description": "PV TOMCAT predicts the outdoor operating temperature and output power of a PV module based on measured physical properties and outdoor conditions. It includes a ray tracing model of a PV module, which runs in the commercial SunSolve ray tracer. Output from this model is combined with meteorological time series data to produce a combined input file for a finite-element model of heat conduction and radiation. Finally, this finite-element model is run in the commercial COMSOL Multiphysics software, producing time series outputs of temperature and power.", + "laborHours": 349.6, + "languages": [ + "Python" + ], + "name": "PV TOMCAT", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pv_tomcat", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PV_Web_Socket.json b/agency-indexes/DoE/PV_Web_Socket.json new file mode 100644 index 00000000..91e2fe03 --- /dev/null +++ b/agency-indexes/DoE/PV_Web_Socket.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "kasemirk@ornl.gov" + }, + "date": { + "created": "2021-10-12", + "metadataLastUpdated": "2021-10-12" + }, + "description": "Web Socket for control system Process Variables, specifically EPICS. Part of ORNL-EPICS", + "laborHours": 0.0, + "languages": [ + "Java", + "JavaScript" + ], + "name": "PV Web Socket", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-epics/pvws", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PVade__PV_Aerodynamic_Design_Engineering__[SWR-23-49].json b/agency-indexes/DoE/PVade__PV_Aerodynamic_Design_Engineering__[SWR-23-49].json new file mode 100644 index 00000000..5de356a4 --- /dev/null +++ b/agency-indexes/DoE/PVade__PV_Aerodynamic_Design_Engineering__[SWR-23-49].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-26", + "metadataLastUpdated": "2023-12-08" + }, + "description": "PV Aerodynamic Design Engineering (PVade) is an open-source fluid-structure interaction (FSI) solver which can accurately simulate wind loads and aerodynamic stability in solar-tracking PV arrays. PVade\u2019s pressure profiles and inertial load time series can be used as inputs into mechanical module models to study degradation mechanisms including cracking of cells, weathering of cracked cells, and glass breakage. This software enables PV plant owners to predict optimal high-wind stow strategies under a variety of weather and site conditions.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PVade (PV Aerodynamic Design Engineering) [SWR-23-49]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PVade", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PVcircuit.json b/agency-indexes/DoE/PVcircuit.json new file mode 100644 index 00000000..a815f387 --- /dev/null +++ b/agency-indexes/DoE/PVcircuit.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-05-18", + "metadataLastUpdated": "2022-05-18" + }, + "description": "The software contains objects that are building blocks for PV modeling and interactive data fitting based on: Optoelectronic models for tandem/multijunction solar cells including resistive and luminescent coupling; simulation of modules composed of 2T, 3T, and 4T tandem solar cells; and energy yield analysis of PV systems composed of tandem solar cells.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "python" + ], + "name": "PVcircuit", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PVcircuit", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PVplr-stGNN_0.1.10.json b/agency-indexes/DoE/PVplr-stGNN_0.1.10.json new file mode 100644 index 00000000..02b5b515 --- /dev/null +++ b/agency-indexes/DoE/PVplr-stGNN_0.1.10.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "xuanji.yu@case.edu" + }, + "date": { + "created": "2023-04-29", + "metadataLastUpdated": "2023-04-29" + }, + "description": "PV Performance Loss Rate Estimation using Spatio-temporal Graph Neural Networks\n\nPVplr-stGNN is a Python 3 package developed by the SDLE Research Center at Case Western Reserve University in Cleveland OH. This repository contains the full source PVplr-stGNN package. The package contains the PV-stGAE for missingness data detection and imputation and PV-DynGNN for PLR estimation.", + "homepageURL": "https://pypi.org/project/PVplr-stGNN", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PVplr-stGNN 0.1.10", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://pypi.org/project/PVplr-stGNN", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "version": "0.1.10" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PVwindow__Photovoltaic_Window_Simulator__[SWR-22-01].json b/agency-indexes/DoE/PVwindow__Photovoltaic_Window_Simulator__[SWR-22-01].json new file mode 100644 index 00000000..dbf7635c --- /dev/null +++ b/agency-indexes/DoE/PVwindow__Photovoltaic_Window_Simulator__[SWR-22-01].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2023-07-11" + }, + "description": "PVwindow simulates photovoltaic window properties by allowing the user build stacks of thin film materials that compose the window layers. The only needed inputs are the complex refractive indices and thicknesses of the materials. The software will simulate the optical transmission, front reflection, and back reflection of the stack using the transfer matrix method. Properties specific to PV window optics such as visible transmittance and color are also calculated. The optics code extracts the number of absorbed photons in the PV absorber layer and solves the single diode equation to yield theoretical photovoltaic metrics such as power conversion efficiency, fill factor, open circuit voltage, and short circuit current of the PV window when illuminated at an arbitrary angle or from either side of the stack. The software tool ultimately allows researchers to design photovoltaic windows and simulate their properties. The software also exports files that can be read into LBL Window software or into the EnergyPlus and Open Studio building energy modeling software to determine larger scale energy impacts of PV window integration.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PVwindow (Photovoltaic Window Simulator) [SWR-22-01]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PVwindow", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PYB11Generator.json b/agency-indexes/DoE/PYB11Generator.json new file mode 100644 index 00000000..c1687b40 --- /dev/null +++ b/agency-indexes/DoE/PYB11Generator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-02-27", + "metadataLastUpdated": "2019-02-27" + }, + "description": "PYB11Generator is a code generator to simplify using the open-source pybind11 package for interoperability between C++ and Python. PYB11Generator parses a description of the C++ code to be exposed to Python written in pure Python syntax, and generates the pybind11 C++ coding which can be compiled into a shared library allowing the C++ code to be used from Python. The purpose of PYB11Generator is to simplify this process of binding together C++ and Python, removing much of the redundant code needed by pybind11 such as trampoline classes for providing virtual function overrides in Python.", + "laborHours": 1231.2, + "languages": [], + "name": "PYB11Generator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmikeowen/pyb11generator", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PYCREEP.json b/agency-indexes/DoE/PYCREEP.json new file mode 100644 index 00000000..0dbd82bd --- /dev/null +++ b/agency-indexes/DoE/PYCREEP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "pycreep is a Python software package for modeling and correlating time-dependent material data like the results of creep rupture and creep deformation tests. The package provides a means to generate models for these test data which can be used to determine design material properties, like those used in the ASME Boiler and Pressure Vessel Code.", + "laborHours": 0.0, + "languages": [], + "name": "PYCREEP", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/pycreep", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PYGRIFFIN.json b/agency-indexes/DoE/PYGRIFFIN.json new file mode 100644 index 00000000..7d58b350 --- /dev/null +++ b/agency-indexes/DoE/PYGRIFFIN.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-23" + }, + "description": "SF-23-061 A Python package that provides a streamlined interface to Griffin along with support for integration with PyARC and Workbench.\n", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "PYGRIFFIN", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PYGridWare_wsdl2python:_python_client_stub_generator.json b/agency-indexes/DoE/PYGridWare_wsdl2python:_python_client_stub_generator.json new file mode 100644 index 00000000..b12b1068 --- /dev/null +++ b/agency-indexes/DoE/PYGridWare_wsdl2python:_python_client_stub_generator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "PyGridWare wsdl2python stub generator is used to automatically generate Python bindings to a Web Service given a Web Service Description Language (WSDL) file.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "PYGridWare wsdl2python: python client stub generator", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PYOED:_AN_ETENSIBLE_SUITE_FOR_DATA_ASSIMILATION_AND_MODEL-CONSTRAINED_OPTIMAL_DESIGN_OF_EXPERIMENTS.json b/agency-indexes/DoE/PYOED:_AN_ETENSIBLE_SUITE_FOR_DATA_ASSIMILATION_AND_MODEL-CONSTRAINED_OPTIMAL_DESIGN_OF_EXPERIMENTS.json new file mode 100644 index 00000000..1b6c1a2d --- /dev/null +++ b/agency-indexes/DoE/PYOED:_AN_ETENSIBLE_SUITE_FOR_DATA_ASSIMILATION_AND_MODEL-CONSTRAINED_OPTIMAL_DESIGN_OF_EXPERIMENTS.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-03-13", + "metadataLastUpdated": "2023-03-13" + }, + "description": "SF-23-005 PyOED is a highly extensible scientific package that enables developing and testing model-constrained optimal experimental design (OED) for inverse problems. Specifically, PyOED aims to be a comprehensive Python toolkit for model-constrained OED. The package targets scientists and researchers interested in understanding the details of OED formulations and approaches. It is also meant to enable researchers to experiment with standard and innovative OED technologies with a wide range of test problems (e.g., simulation models). OED, inverse problems (e.g., Bayesian inversion), and data assimilation (DA) are closely related research fields, and their formulations overlap significantly. Thus, PyOED is continuously being expanded with a plethora of Bayesian inversion, DA, and OED methods as well as new scientific simulation models, observation error models, and observation operators. These pieces are added such that they can be permuted to enable testing OED methods in various settings of varying complexities. The PyOED core is completely written in Python and utilizes the inherent object-oriented capabilities; however, PyOED is meant to be extensible rather than scalable. Specifically, PyOED is developed to ``enable rapid development and benchmarking of OED methods with minimal coding effort and to maximize code reutilization.'' PyOED will be continuously expanded with a plethora of Bayesian inversion, DA, and OED methods as well as new scientific simulation models, observation error models, and observation operators.", + "laborHours": 0.0, + "languages": [], + "name": "PYOED: AN ETENSIBLE SUITE FOR DATA ASSIMILATION AND MODEL-CONSTRAINED OPTIMAL DESIGN OF EXPERIMENTS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/ahmedattia/pyoed", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PYRANDA.json b/agency-indexes/DoE/PYRANDA.json new file mode 100644 index 00000000..481345bb --- /dev/null +++ b/agency-indexes/DoE/PYRANDA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-05-10", + "metadataLastUpdated": "2018-05-22" + }, + "description": "Pyranda Is fortran 90 code which solves compact finite difference equations on a three dimensional fortran arrays, domain decomposed using the Message Passing Interface (MPI). The fortran source solves the linear system of equations which forms a pentadtagona1 matrix. Derivatives are used to construct hyperbolic partlal differential equation (PDE) operators, namely gradient, divergence, Laplacian, and curl operators. \n5. Solution Method:\nThe library provides a python Interface which facilitates problem setup and description. However, the core solver Is written in the fortran 90 language. The solver couples MPI communication and linear solves together so that a direct (non-iterative) solution to the linear system of equations can be computed with minimal communication. Domain decomposition is limited to a uniform data size but provides perfect load balancing. \n6. Computer for which the code Is written:", + "laborHours": 9849.6, + "languages": [], + "name": "PYRANDA", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pyranda", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PYSEQM.json b/agency-indexes/DoE/PYSEQM.json new file mode 100644 index 00000000..2151e6d3 --- /dev/null +++ b/agency-indexes/DoE/PYSEQM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-09-24" + }, + "description": "PYSEQM is a package for performing semi-empirical quantum mechanical (SEQM) simulations on molecular systems utilizing PyTorch. SEQM simulations determine molecular properties (energy, electron density, dipole moment, ect.) by solving an approximate Schr\u00f6dinger equation for the motions of electrons in a molecule. The use of PyTorch provides three specific advantages. First, it allows the calculations to be offloaded to GPU accelerators, giving an order of magnitude increase in speed. Second, back propagation is used to get atomic forces (derivative of the total energy with respect to atomic position) at the same computational cost as the energy calculation itself. Finally, the use of PyTorch makes for a natural interface to modern machine learning methods, which can be used to adjust the semi-empirical parameters build into SEQM methods. Additionally, PYSEQM implements various other optimizations for performing quantum mechanics based molecular dynamics, including SP2 for rapid GPU based solution of the self-consistent field algorithm, and the extended Lagrangian method for rapid QM-MD.", + "laborHours": 0.0, + "languages": [], + "name": "PYSEQM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PYSEQM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/P_Finder.json b/agency-indexes/DoE/P_Finder.json new file mode 100644 index 00000000..391f00f8 --- /dev/null +++ b/agency-indexes/DoE/P_Finder.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "P Finder is written in C# and has been tested in multiple 64-bit Windows environments (Windows 7/8/Vista). It has a user-friendly graphical user interface (GUI) that allows for intuitive RNase P RNA identification and/or annotation. The user can select from four search criteria including the use multiple threads. In addition, the user can determine what display data they wish to incorporate in the output such as: bitscore, E-value, percent ID, start location, end location, the strand in which the sequence is located, and of course the sequence itself. P Finder is the only available algorithm that is capable of not only identifying the RNase P RNA for annotation but also differentiating among the five different RNase P RNA structural types (A, B, C, M, and T) with the option to select these data types for display in the final output.", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "P Finder", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JChristopherEllis/P-Finder", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PaRSEC.json b/agency-indexes/DoE/PaRSEC.json new file mode 100644 index 00000000..e5b9739e --- /dev/null +++ b/agency-indexes/DoE/PaRSEC.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "PaRSEC is a generic framework for architecture aware scheduling and management of micro-tasks on distributed many-core heterogeneous architectures. Applications we consider can be expressed as a Direct Acyclic Graph of tasks with labeled edges designating data dependencies. PaRSEC assigns computation threads to the cores, overlaps communications and computations and uses a dynamic, fully-distributed scheduler based on architectural features such as NUMA nodes and algorithmic features such as data reuse.", + "laborHours": 56012.0, + "languages": [], + "name": "PaRSEC", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/icldistcomp/parsec/src/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/icldistcomp/parsec/src/master", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PaToH_Matlab_Interface.json b/agency-indexes/DoE/PaToH_Matlab_Interface.json new file mode 100644 index 00000000..d391f1ad --- /dev/null +++ b/agency-indexes/DoE/PaToH_Matlab_Interface.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "Matlab interface to PaToH, the Partitioning Tools for Hypergraph, a multilevel hypergraph partitioning tool that provides fast hypergraph partitioning.", + "homepageURL": "http://bmi.osu.edu/~umit/software.html#patoh", + "laborHours": 532.0, + "languages": [], + "name": "PaToH Matlab Interface", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://bmi.osu.edu/~umit/software.html#patoh", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pacifica.json b/agency-indexes/DoE/Pacifica.json new file mode 100644 index 00000000..7f123ddc --- /dev/null +++ b/agency-indexes/DoE/Pacifica.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pacifica is a data management system developed for use at the Environmental and Molecular Sciences Laboratory (EMSL) used to collect, analyze, search and track data from instruments.", + "laborHours": 304.0, + "name": "Pacifica", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pacifica/pacifica", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PackageRedvoxToHdf5.json b/agency-indexes/DoE/PackageRedvoxToHdf5.json new file mode 100644 index 00000000..ff691c9c --- /dev/null +++ b/agency-indexes/DoE/PackageRedvoxToHdf5.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2020-05-27" + }, + "description": "This is a program to convert a directory of Redvox JSON packets to a single HDF5 file.", + "laborHours": 228.0, + "languages": [], + "name": "PackageRedvoxToHdf5", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stevenmz/package-redvox-to-hdf5", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Packaged_HVAC_Unit_Diagnostician_version_1.0.json b/agency-indexes/DoE/Packaged_HVAC_Unit_Diagnostician_version_1.0.json new file mode 100644 index 00000000..d795b2ad --- /dev/null +++ b/agency-indexes/DoE/Packaged_HVAC_Unit_Diagnostician_version_1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The PHD automatically detects and diagnoses faults with respect to four major aspects of packaged heating, ventilating, and air conditioning (HVAC) unit operation: 1) air handling in which return-air and outdoor-air are mixed, then conditioned to appropriate temperature and humidity conditions, 2) vapor-compression refrigerant loop operation, 3) overall unit efficiency and its potential degradation over time, and 4) operation scheduling. When faults are detected, the software provides alarm codes corresponding to the detected problem(s). These alarms map into explanations of the faults, possible causes for them, and suggested actions to remedy the faults. For air handling, the software also estimates energy and cost impacts of faults. The software is intended for implementation on a hardware systems that includes sensors, sensor signal processing, micro-processor unit for running this software, and communication to a web server. Results are made available to users via the world wide web using a computer with Web browser and Internet connection for access. The graphical web-based interface must be provided by an application service provider (not part of this software).", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Packaged HVAC Unit Diagnostician version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Packet2Vec.json b/agency-indexes/DoE/Packet2Vec.json new file mode 100644 index 00000000..95f32bed --- /dev/null +++ b/agency-indexes/DoE/Packet2Vec.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-09", + "metadataLastUpdated": "2020-11-09" + }, + "description": "A repository of code that transforms packets into a vectorized representation to be used for classification of malicious/benign packets. SAND2019-13500 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1246.4, + "languages": [ + "C++" + ], + "name": "Packet2Vec", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/packet2vec", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pagoda.json b/agency-indexes/DoE/Pagoda.json new file mode 100644 index 00000000..52c384ac --- /dev/null +++ b/agency-indexes/DoE/Pagoda.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pagoda is a set of parallel tools as well as an application programmer interface for parallel data analysis of high-resolution climate data. Pagoda implements data parallel versions of some of the commonly used tools from the NetCDF Operators. These tools support data processing operations including subsetting, record and ensemble averages, binary operations, and interpolation. Pagoda also provides an application programmer interface for developing custom data analysis programs.", + "laborHours": 61392.8, + "name": "Pagoda", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jeffdaily/pagoda/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeffdaily/pagoda", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pairwise_Sequence_Alignment_Library.json b/agency-indexes/DoE/Pairwise_Sequence_Alignment_Library.json new file mode 100644 index 00000000..1102bf0b --- /dev/null +++ b/agency-indexes/DoE/Pairwise_Sequence_Alignment_Library.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Vector extensions, such as SSE, have been part of the x86 CPU since the 1990s, with applications in graphics, signal processing, and scientific applications. Although many algorithms and applications can naturally benefit from automatic vectorization techniques, there are still many that are difficult to vectorize due to their dependence on irregular data structures, dense branch operations, or data dependencies. Sequence alignment, one of the most widely used operations in bioinformatics workflows, has a computational footprint that features complex data dependencies. The trend of widening vector registers adversely affects the state-of-the-art sequence alignment algorithm based on striped data layouts. Therefore, a novel SIMD implementation of a parallel scan-based sequence alignment algorithm that can better exploit wider SIMD units was implemented as part of the Parallel Sequence Alignment Library (parasail). Parasail features: Reference implementations of all known vectorized sequence alignment approaches. Implementations of Smith Waterman (SW), semi-global (SG), and Needleman Wunsch (NW) sequence alignment algorithms. Implementations across all modern CPU instruction sets including AVX2 and KNC. Language interfaces for C/C++ and Python.", + "laborHours": 589045.6, + "name": "Pairwise Sequence Alignment Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jeffdaily/parasail/blob/master/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeffdaily/parasail", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pajarito_models.json b/agency-indexes/DoE/Pajarito_models.json new file mode 100644 index 00000000..97f3a50f --- /dev/null +++ b/agency-indexes/DoE/Pajarito_models.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-10-28", + "metadataLastUpdated": "2021-10-28" + }, + "description": "Pajarito models are developed to perform various types of model analyses related to the LANL-site groundwater contamination problems. Pajarito models include several models representing the LANL Chromium (Cr) and RDX sites. Pajarito models also include a model that is at the scale of the Pajarito Plateau. The models are designed to perform model prediction of groundwater flow and contaminant transport. The models are bundled in repositories. The model repositories include scripts, input control files, and drivers. A detailed description of the various files included in the repositories is provided in electronic form within the repositories.", + "laborHours": 0.0, + "languages": [], + "name": "Pajarito models", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/LANL-EM/chrotran-cr-bio", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Palm_FastFootprint.json b/agency-indexes/DoE/Palm_FastFootprint.json new file mode 100644 index 00000000..fcf3dc49 --- /dev/null +++ b/agency-indexes/DoE/Palm_FastFootprint.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-14", + "metadataLastUpdated": "2020-12-14" + }, + "description": "Palm/FastFootprints implements two method for rapid memory footprint access diagnostics. The two methods are whole program and precise. Current footprint analyses can cause 200\u00d7 or more slowdown with realistic inputs and are therefore impractical. The whole-program method reduces the overhead to 10% by computing upper bounds, but still yields interprocedural insight through a call path profile. Our precise method uses additional static analysis and profiling to refine the upper bounds for intra-procedural loop nests.", + "laborHours": 0.0, + "languages": [], + "name": "Palm/FastFootprint", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab-hub/palm/palm-memory", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pamgen.json b/agency-indexes/DoE/Pamgen.json new file mode 100644 index 00000000..a874a911 --- /dev/null +++ b/agency-indexes/DoE/Pamgen.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pamgen creates, in parallel, hexahedral or quadrilateral (in 2D) finite element meshes of cubes, cylinders, and portions of cylinders. For some analysis applications it can obviate the normally serial analysis preparation steps of mesh generation and decomposition. Bypassing these serial steps allows construction of large element count (over a billion) meshes. When linked to an application as a library, it allows each process of a parallel simulation to generate its own finite element domain representation at execution time. As a stand-alone application it can produce the representation of the mesh for processor n of k possible processors. The Pamgen library and application are serial as the mesh generation proceeds without reliance on inter-processor communication.", + "laborHours": 8344830.4, + "name": "Pamgen", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pan-YANG_RA-ABM.json b/agency-indexes/DoE/Pan-YANG_RA-ABM.json new file mode 100644 index 00000000..35b2b3d5 --- /dev/null +++ b/agency-indexes/DoE/Pan-YANG_RA-ABM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Crowd-sourcing incorporates common citizens as rich sources of data and is promising for environmental monitoring. In this paper, we propose and test the idea of incorporating incentives to crowd-sourcing management for rainfall monitoring. Specifically, we modeled the allocation of incentives (quantitatively measurable and limited rewards) among crowd-sourcing participants for a theoretical rainfall monitoring case. For this purpose, we developed an integrated model comprising a reward allocation component to represent the decision\u2010making process of a central manager, an agent\u2010based model to simulate the interactions between the manager and participants, and a rainfall simulation model to evaluate the effectiveness of various reward allocation policies. We simulated six reward allocation policies of varying levels of administrative cost, and consideration of participant and rainfall spatial heterogeneities. The results suggest the performance of each policy to improve with the reward budget and their spatial uniformity. Among the six policies tested, we found that the participant density weighted maximum participation policy yields the most accurate estimation of rainfall intensity due to its more explicit consideration of the spatial distribution of participants; however, this policy associates with a high administrative cost. This highlights the trade\u2010off between performance and cost in designing effective reward allocation policies. This paper provides a physical and behavior simulation modeling tool to study the feasibility and complexity of reward\u2010based participant management for crowd-sourcing rainfall monitoring. The proposed crowd-sourcing method is beneficial for a wide range of applications that require rainfall data with fine resolution, such as stormwater management and water availability and biomass assessment for food and energy crops.", + "laborHours": 319.2, + "languages": [], + "name": "Pan-YANG/RA-ABM", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pan-YANG/RA-ABM", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PanGenomeAPI.json b/agency-indexes/DoE/PanGenomeAPI.json new file mode 100644 index 00000000..ed36973a --- /dev/null +++ b/agency-indexes/DoE/PanGenomeAPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "This is the repository for \"PanGenomeAPI\" developed by KBase. A KBase module generated by the KBase SDK.", + "laborHours": 1580.8, + "languages": [], + "name": "PanGenomeAPI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/PanGenomeAPI", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Panel-Segmentation.json b/agency-indexes/DoE/Panel-Segmentation.json new file mode 100644 index 00000000..bfd6356d --- /dev/null +++ b/agency-indexes/DoE/Panel-Segmentation.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The Panel-Segmentation package is a computer vision (CV) framework for automated metadata extraction for solar PV arrays using satellite imagery. With Panel-Segmentation, a user inputs a set of latitude-longitude coordinates to automatically generate a satellite image using the Google Maps API, and runs the image through a deep learning framework to get a pixel-by-pixel representation of the solar panel(s) in an image. If a solar array is located, the user can then perform spectral clustering to cluster individual solar arrays in an image (if applicable), and run each cluster through an azimuth estimation algorithm. This package framework is versatile, allowing for future CV techniques to be added and/or modified. ", + "laborHours": 2158.4, + "languages": [ + "Python" + ], + "name": "Panel-Segmentation", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Panel-Segmentation", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PangenomeFileUtilImpl.json b/agency-indexes/DoE/PangenomeFileUtilImpl.json new file mode 100644 index 00000000..7a63319c --- /dev/null +++ b/agency-indexes/DoE/PangenomeFileUtilImpl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "Downloaders for KBase Pangenome objects.", + "laborHours": 5791.2, + "languages": [], + "name": "PangenomeFileUtilImpl", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/PangenomeFileUtilImpl", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PangenomeOrthomcl.json b/agency-indexes/DoE/PangenomeOrthomcl.json new file mode 100644 index 00000000..53ab4188 --- /dev/null +++ b/agency-indexes/DoE/PangenomeOrthomcl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "This module contains only one method called \"Build Pangenome with OrthoMCL\". It is using \"OrthoMCL\" software to calculate orthologous protein clusters and store them as KBase Pangenome object.", + "laborHours": 2067.2, + "languages": [], + "name": "PangenomeOrthomcl", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/PangenomeOrthomcl", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Panzer.json b/agency-indexes/DoE/Panzer.json new file mode 100644 index 00000000..b0da6755 --- /dev/null +++ b/agency-indexes/DoE/Panzer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Panzer is a finite element assembly engine used for research on solving partial differential equations (PDEs). Panzer takes a physics model implemented by a user and creates and populates the linear algrbra objects, such as residuals and Jacobians, for use in implicit finite element methods. Panzer can be considered \"glue code\" that pulls together the capabilities of a number of open-source Trilinos packages (Epetra, Intrepid, Sacado, FEI, and Phalanx). This code provides a generic framework for describing a set of partial differential equations. Panzer provides a simple example driver that solves the undergraduate textbook partial differential equation of heat transfer in a solid (see for example, \"Transport Phenomena\" by Bird Stewart, and Lightfoot 1960). Panzer is intended as a tool to simplify the use of the discretization tools in Trilinos (Intrepid and Phalanx) and is meant to aid in fundamental research on discretizations. Panzer will be released open-source as a package in Trilinos under a BSD license.", + "laborHours": 8344830.4, + "languages": [], + "name": "Panzer", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Papyrus.json b/agency-indexes/DoE/Papyrus.json new file mode 100644 index 00000000..f10289cf --- /dev/null +++ b/agency-indexes/DoE/Papyrus.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "Papyrus is a programming system that provides features for scalable, aggregate, persistent memory in an extreme-scale system for typical HPC usage scenarios. Papyrus provides a portable and scalable programming interface to access and manage parallel data structures on the distributed NVM storage.", + "laborHours": 3678.4, + "languages": [], + "name": "Papyrus", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/eck/papyrus", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ParChain:_A_Framework_for_Parallel_Hierarchical_Agglomerative_Clustering_using_Nearest-Neighbor_Chain.json b/agency-indexes/DoE/ParChain:_A_Framework_for_Parallel_Hierarchical_Agglomerative_Clustering_using_Nearest-Neighbor_Chain.json new file mode 100644 index 00000000..52857f9a --- /dev/null +++ b/agency-indexes/DoE/ParChain:_A_Framework_for_Parallel_Hierarchical_Agglomerative_Clustering_using_Nearest-Neighbor_Chain.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nShangdi Yu, Yiqiu Wang, Yan Gu, Laxman Dhulipala, and Julian Shun.\nParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain.\nProceedings of the VLDB Endowment, 15(2), pp. 285-298, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yushangdi/parChain", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ParFlow.json b/agency-indexes/DoE/ParFlow.json new file mode 100644 index 00000000..a79a12da --- /dev/null +++ b/agency-indexes/DoE/ParFlow.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "smith84@llnl.gov" + }, + "date": { + "created": "2022-04-05", + "metadataLastUpdated": "2022-04-05" + }, + "description": "ParFlow is an open-source, modular, parallel watershed flow model. It includes fully-integrated overland flow, the ability to simulate complex topography, geology and heterogeneity and coupled land-surface processes including the land-energy budget, biogeochemistry and snow (via CLM). It is multi-platform and runs with a common I/O structure from laptop to supercomputer. ParFlow is the result of a long, multi-institutional development history and is now a collaborative effort between CSM, LLNL, UniBonn and UCB. ParFlow has been coupled to the mesoscale, meteorological code ARPS and the NCAR code WRF.", + "laborHours": 138532.8, + "languages": [ + "C", + "C++", + "Python", + "Tcl" + ], + "name": "ParFlow", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/parflow/parflow", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.10.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ParGeo:_A_Library_for_Parallel_Computational_Geometry.json b/agency-indexes/DoE/ParGeo:_A_Library_for_Parallel_Computational_Geometry.json new file mode 100644 index 00000000..00430c08 --- /dev/null +++ b/agency-indexes/DoE/ParGeo:_A_Library_for_Parallel_Computational_Geometry.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper:\n\nYiqiu Wang, Rahul Yesantharao, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun.\nParGeo: A Library for Parallel Computational Geometry.\nProceedings of the European Symposium on Algorithms (ESA), pp. 88:1-88:19, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "ParGeo: A Library for Parallel Computational Geometry", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/ParGeo", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ParSplice,_Version_1.json b/agency-indexes/DoE/ParSplice,_Version_1.json new file mode 100644 index 00000000..47edebd4 --- /dev/null +++ b/agency-indexes/DoE/ParSplice,_Version_1.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The ParSplice code implements the Parallel Trajectory Splicing algorithm described in [1]. This method is part of the Accelerated Molecular Dynamics family of techniques developed in Los Alamos National Laboratory over the last 16 years. These methods aim at generating high-quality trajectories of ensembles of atoms in materials. ParSplice uses multiple independent replicas of the system in order to parallelize the generation of such trajectories in the time domain, enabling simulations of systems of modest size over very long timescales. ParSplice includes capabilities to store configurations of the system, to generate and distribute tasks across a large number of processors, and to harvest the results of these tasks to generate long trajectories. ParSplice is a management layer that orchestrate large number of calculations, but it does not perform the actual molecular dynamics itself; this is done by external molecular dynamics engines. [1] Danny Perez, Ekin D Cubuk, Amos Waterland, Efthimios Kaxiras, Arthur F Voter, Long-time dynamics through parallel trajectory splicing, Journal of chemical theory and computation 12, 18 (2015)", + "laborHours": 1398.4, + "name": "ParSplice, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/dannyperez/parsplice/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/dannyperez/parsplice", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ParSwarm:_A_C++_Framework_for_Evaluating_Distributed_Algorithms_for_Robot_Swarms.json b/agency-indexes/DoE/ParSwarm:_A_C++_Framework_for_Evaluating_Distributed_Algorithms_for_Robot_Swarms.json new file mode 100644 index 00000000..47b63851 --- /dev/null +++ b/agency-indexes/DoE/ParSwarm:_A_C++_Framework_for_Evaluating_Distributed_Algorithms_for_Robot_Swarms.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper: \n\nZhi Wei Gan, Grace Cai, Noble Harasha, Nancy Lynch, and Julian Shun.\nParSwarm: A C++ Framework for Evaluating Distributed Algorithms for Robot Swarms.\nProceedings of the Workshop on Advanced Tools, Programming Languages, and Platforms for Implementing and Evaluating Algorithms for Distributed Systems (ApPLIED), Article No. 14, pp. 1-5, 2023.\n", + "laborHours": 0.0, + "languages": [], + "name": "ParSwarm: A C++ Framework for Evaluating Distributed Algorithms for Robot Swarms", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zhiweigan/geo-swarm-framework", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ParaDIS_lib.json b/agency-indexes/DoE/ParaDIS_lib.json new file mode 100644 index 00000000..6dac39a4 --- /dev/null +++ b/agency-indexes/DoE/ParaDIS_lib.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The ParaDIS_lib software is a project that is funded by the DOE ASC Program. Its purpose is to provide visualization and analysis capabilities for the existing ParaDIS parallel dislocation dynamics simulation code.", + "laborHours": 4347.2, + "name": "ParaDIS_lib", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/paraDIS_lib", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ParaEMT__NREL's_EMT_Simulator:_An_Open_Source,_and_HPC-Compatible_Large-Scale_Power_System_Electro-Magnetic_Transient__EMT__Simulator__[SWR-22-16].json b/agency-indexes/DoE/ParaEMT__NREL's_EMT_Simulator:_An_Open_Source,_and_HPC-Compatible_Large-Scale_Power_System_Electro-Magnetic_Transient__EMT__Simulator__[SWR-22-16].json new file mode 100644 index 00000000..fc157db3 --- /dev/null +++ b/agency-indexes/DoE/ParaEMT__NREL's_EMT_Simulator:_An_Open_Source,_and_HPC-Compatible_Large-Scale_Power_System_Electro-Magnetic_Transient__EMT__Simulator__[SWR-22-16].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2023-01-17", + "metadataLastUpdated": "2023-08-24" + }, + "description": "This open-source tool aims to provide a powerful and flexible platform for simulating electromagnetic transients (EMT) of large-scale inverter-based resource (IBR)-dominated power systems. The purpose of making it open source is to foster a community of EMT simulation and assist in exploring new EMT algorithms and applying advanced computational techniques to EMT simulation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ParaEMT (NREL's EMT Simulator: An Open Source, and HPC-Compatible Large-Scale Power System Electro-Magnetic Transient (EMT) Simulator) [SWR-22-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ParaEMT_public", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ParaView-VTK_Collaborative_Software_Development_for_Data_Analysis_and_Visualization.json b/agency-indexes/DoE/ParaView-VTK_Collaborative_Software_Development_for_Data_Analysis_and_Visualization.json new file mode 100644 index 00000000..c42bf4fa --- /dev/null +++ b/agency-indexes/DoE/ParaView-VTK_Collaborative_Software_Development_for_Data_Analysis_and_Visualization.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Los Alamos National Laboratory has played key roles in the development of ParaView and the Visualization Toolkit (VTK). James Ahrens (Director, ISTI & Senior Staff Scientist, Data Science at Scale, CCS-7) is the founder and design lead of ParaView. With over a million downloads, ParaView is one of the leading data analysis and visualization applications and is widely used by scientific users within the Department of Energy Office of Science (SC) and the DOE National Nuclear Security Agency (NNSA). VTK is an open-source software visualization library based on C++ and includes interface layers for Python and Java. ParaView extensively uses the VTK libraries for its graphics and analysis. First open-sourced under LA_CC Number 99_44, this work has been continuously funded over the years under Department of Energy contracts. The goal of this software project is to continue the collaborative development of open-source general use case contributions to ParaView and VTK by LANL researchers. The developed software will provide open-source computer science algorithms, interfaces, filters, visualization approaches, and data analysis modules that will be merged into ParaView and VTK for general use by ParaView and VTK users. The primary users of these projects will include institutional users at Los Alamos National Laboratory, institutional users across the DOE complex and scientific users of VTK and ParaView as open-source tools for data analysis and visualization.", + "laborHours": 0.0, + "languages": [], + "name": "ParaView-VTK Collaborative Software Development for Data Analysis and Visualization", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/dav-pv-vtk", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ParaView.json b/agency-indexes/DoE/ParaView.json new file mode 100644 index 00000000..aec2e206 --- /dev/null +++ b/agency-indexes/DoE/ParaView.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-13", + "metadataLastUpdated": "2020-06-01" + }, + "description": "ParaView is an open-source, multi-platform data analysis and visualization application that allows users to quickly build visualizations to analyze their data using qualitative and quantitative techniques. ", + "laborHours": 767204.8, + "languages": [], + "name": "ParaView", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.paraview.org/paraview-license", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/paraview/paraview", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Paracousti_v._2.0.0.json b/agency-indexes/DoE/Paracousti_v._2.0.0.json new file mode 100644 index 00000000..a1bf10ab --- /dev/null +++ b/agency-indexes/DoE/Paracousti_v._2.0.0.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Paracousti simulates 3-D acoustic wave propagation in fixed (non-moving) complex media. It solves the linear acoustic equations of motion using the velocity-pressure system of first order linear differential equations on a finite-difference Cartesian grid using Newton\u2019s law of motion and mass continuity equations. It also has the ability to incorporate acoustic attenuation to simulate non-recoverable energy losses via the velocity-memory-pressure system of linear differential equations. We assume stationary, non-heat conducting, adiabatic media (fluid) where the background sound speed and material density are fixed in time. Capabilities include massively parallel design, optimization for high contrast media interfaces, inclusion of arbitrary pressure and force sources defined by the user, inclusion of arbitrary pressure and velocity receivers defined by the user, acoustic wavefield snapshots in time for visualization, and convolutional perfectly matched layers to minimize artificial grid boundary reflections. Paracousti was built upon the foundational framework of TDAAPS (Time-Domain Atmospheric Acoustic Propagation Suite) by Neill Symons, Dave Aldridge, and Leiph Preston.", + "laborHours": 29488.0, + "languages": [ + "C++", + "C", + "MATLAB", + "Makefile", + "JavaScript" + ], + "name": "Paracousti v. 2.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Paracousti", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 2.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Algorithms_for_Butterfly_Computations.json b/agency-indexes/DoE/Parallel_Algorithms_for_Butterfly_Computations.json new file mode 100644 index 00000000..753b10b1 --- /dev/null +++ b/agency-indexes/DoE/Parallel_Algorithms_for_Butterfly_Computations.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nJessica Shi and Julian Shun.\nParallel Algorithms for Butterfly Computations.\nMassive Graph Analytics, pp. 287-330, 2022. (Earlier version appears in APOCS 2020.)", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Algorithms for Butterfly Computations", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeshi96/parbutterfly", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Batch-Dynamic_Algorithms_for_k-Core_Decomposition_and_Related_Graph_Problems.json b/agency-indexes/DoE/Parallel_Batch-Dynamic_Algorithms_for_k-Core_Decomposition_and_Related_Graph_Problems.json new file mode 100644 index 00000000..cb4883e6 --- /dev/null +++ b/agency-indexes/DoE/Parallel_Batch-Dynamic_Algorithms_for_k-Core_Decomposition_and_Related_Graph_Problems.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nQuanquan Liu, Jessica Shi, Shangdi Yu, Laxman Dhulipala, and Julian Shun.\nParallel Batch-Dynamic Algorithms for k-Core Decomposition and Related Graph Problems.\nProceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), pp. 191-204, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Batch-Dynamic Algorithms for k-Core Decomposition and Related Graph Problems", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qqliu/batch-dynamic-kcore-decomposition", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Batch-Dynamic_k-Clique_Counting.json b/agency-indexes/DoE/Parallel_Batch-Dynamic_k-Clique_Counting.json new file mode 100644 index 00000000..37ff6859 --- /dev/null +++ b/agency-indexes/DoE/Parallel_Batch-Dynamic_k-Clique_Counting.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-11" + }, + "description": "Source code for paper (https://github.com/ParAlg/gbbs/tree/tri_merge/benchmarks/TriangleCounting/DhulipalaLiuShunYu20):\n\nLaxman Dhulipala, Quanquan Liu, Julian Shun, and Shangdi Yu.\nParallel Batch-Dynamic k-Clique Counting.\nProceedings of the SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS), pp. 129-143, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Batch-Dynamic k-Clique Counting", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Clique_Counting_and_Peeling_Algorithms.json b/agency-indexes/DoE/Parallel_Clique_Counting_and_Peeling_Algorithms.json new file mode 100644 index 00000000..b91d496e --- /dev/null +++ b/agency-indexes/DoE/Parallel_Clique_Counting_and_Peeling_Algorithms.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper (https://github.com/ParAlg/gbbs/tree/master/benchmarks/CliqueCounting):\n\nJessica Shi, Laxman Dhulipala, and Julian Shun.\nParallel Clique Counting and Peeling Algorithms.\nProceedings of the SIAM Conference on Applied and Computational Discrete Algorithms (ACDA), pp. 135-146, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Clique Counting and Peeling Algorithms", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Dislocation_Simulator.json b/agency-indexes/DoE/Parallel_Dislocation_Simulator.json new file mode 100644 index 00000000..d08e36fb --- /dev/null +++ b/agency-indexes/DoE/Parallel_Dislocation_Simulator.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-08-23", + "metadataLastUpdated": "2023-08-23" + }, + "description": "ParaDiS, or Parallel Dislocation Simulator, is a simulation tool that performs direct numerical simulation of\ndislocation ensembles, the carriers of plasticity, to predict the strength in crystalline materials from the\nfundamental physics of defect motion, evolution, and interaction.\nThe code has been successfully deployed on high performance computing architectures and used to\nstudy the origins of strength and strain hardening for cubic crystals, the strength of micro-pillars, and\nirradiated materials at LLNL. The ParaDiS code has been successfully deployed on more than one\nhundred thousand CPU's with over ten million active degrees of freedom.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Dislocation Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ParaDiS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "4.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Element_Agglomeration_Algebraic_Multigrid_and_Upscaling_Library.json b/agency-indexes/DoE/Parallel_Element_Agglomeration_Algebraic_Multigrid_and_Upscaling_Library.json new file mode 100644 index 00000000..8641ed7f --- /dev/null +++ b/agency-indexes/DoE/Parallel_Element_Agglomeration_Algebraic_Multigrid_and_Upscaling_Library.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ParFELAG is a parallel distributed memory C++ library for numerical upscaling of finite element discretizations. It provides optimal complesity algorithms ro build multilevel hierarchies and solvers that can be used for solving a wide class of partial differential equations (elliptic, hyperbolic, saddle point problems) on general unstructured mesh (under the assumption that the topology of the agglomerated entities is correct). Additionally, a novel multilevel solver for saddle point problems with divergence constraint is implemented.", + "laborHours": 31600.8, + "name": "Parallel Element Agglomeration Algebraic Multigrid and Upscaling Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/parelag", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Element_Agglomeration_Multilevel_Monte_Carlo_Library__ParELAGMC_.json b/agency-indexes/DoE/Parallel_Element_Agglomeration_Multilevel_Monte_Carlo_Library__ParELAGMC_.json new file mode 100644 index 00000000..b00cdc04 --- /dev/null +++ b/agency-indexes/DoE/Parallel_Element_Agglomeration_Multilevel_Monte_Carlo_Library__ParELAGMC_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-05-23", + "metadataLastUpdated": "2018-05-23" + }, + "description": "ParELAGMC is a parallel distributed memory C++ library for multilevel Monte Carlo (MLMC) simulations with algebraically constructed coarse spaces for estimating statistical moments of a quantity of interest involving solutions of partial differential equations with uncertain coefficients. A primary focus of the library is the scalable generation of Gaussian random fields using a novel stochastic PDE (SPDE) sampling technique for large-scale simulations. A key feature in the SPDE sampling technique is a novel non-matching mesh embedding technique to mitigate artificial boundary artifacts that are inherent in the method. Example applications to uncertainty quantification of subsurface flow simulations in the mixed finite element setting are provided as well.", + "laborHours": 17905.6, + "languages": [], + "name": "Parallel Element Agglomeration Multilevel Monte Carlo Library (ParELAGMC)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/parelagmc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Environment_for_the_Creation_of_Stochastics_1.0.json b/agency-indexes/DoE/Parallel_Environment_for_the_Creation_of_Stochastics_1.0.json new file mode 100644 index 00000000..f4ccee3b --- /dev/null +++ b/agency-indexes/DoE/Parallel_Environment_for_the_Creation_of_Stochastics_1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-10-08" + }, + "description": "PECOS is a computational library for creating and manipulating realizations of stochastic quantities, including scalar uncertain variables, random fields, and stochastic processes. It offers a unified interface to univariate and multivariate polynomial approximations using either orthogonal or interpolation polynomials; numerical integration drivers for Latin hypercube sampling, quadrature, cubature, and sparse grids; and fast Fourier transforms using third party libraries. The PECOS core also offers statistical utilities and transformations between various representations of stochastic uncertainty. PECOS provides a C++ API through which users can generate and transform realizations of stochastic quantities. It is currently used by Sandia's DAKOTA, Stokhos, and Encore software packages for uncertainty quantification and verification. PECOS generates random sample sets and multi-dimensional integration grids, typically used in forward propagation of scalar uncertainty in computational models (uncertainty quantification (UQ)). PECOS also generates samples of random fields (RFs) and stochastic processes (SPs) from a set of user-defined power spectral densities (PSDs). The RF/SP may be either Gaussian or non-Gaussian and either stationary or nonstationary, and the resulting sample is intended for run-time query by parallel finite element simulation codes. Finally, PECOS supports nonlinear transformations of random variables via the Nataf transformation and extensions.", + "homepageURL": "https://dakota.sandia.gov/content/packages?q=content/pecos", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Environment for the Creation of Stochastics 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dakota.sandia.gov/content/packages?q=content/pecos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Fenics_Implementation_of_Block_Solvers___pFibs_.json b/agency-indexes/DoE/Parallel_Fenics_Implementation_of_Block_Solvers___pFibs_.json new file mode 100644 index 00000000..dc1c497a --- /dev/null +++ b/agency-indexes/DoE/Parallel_Fenics_Implementation_of_Block_Solvers___pFibs_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2019-01-23" + }, + "description": "This software is a Python package designed to act as an interface between FEniCS and PETSc to facilitate the construction and application of parallel block solvers/preconditioners. The original intent of this software was to help enable Battery and Wind Farm simulations for use on high performance computing systems. The code is written in Python and uses the petsc4py module to access the more advance features of the PETSc Krylov Solver. In essence, pFibs is an interface to make accessing these features more streamlined. Additionally, pFibs also provides a template for building custom Python based preconditioning algorithms. ", + "laborHours": 1276.8, + "languages": [ + "Python" + ], + "name": "Parallel Fenics Implementation of Block Solvers (pFibs)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pfibs", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Filtered_Graphs_for_Hierarchical_Clustering.json b/agency-indexes/DoE/Parallel_Filtered_Graphs_for_Hierarchical_Clustering.json new file mode 100644 index 00000000..baceb22e --- /dev/null +++ b/agency-indexes/DoE/Parallel_Filtered_Graphs_for_Hierarchical_Clustering.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper:\n\nShangdi Yu and Julian Shun.\nParallel Filtered Graphs for Hierarchical Clustering.\nProceedings of the IEEE International Conference on Data Engineering (ICDE), 2023.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Filtered Graphs for Hierarchical Clustering", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yushangdi/par-filtered-graph-clustering", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Five-Cycle_Counting_Algorithms.json b/agency-indexes/DoE/Parallel_Five-Cycle_Counting_Algorithms.json new file mode 100644 index 00000000..be0e1b53 --- /dev/null +++ b/agency-indexes/DoE/Parallel_Five-Cycle_Counting_Algorithms.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for the following paper:\n\nJessica Shi, Louisa Huang, and Julian Shun.\nParallel Five-Cycle Counting Algorithms.\nACM Journal of Experimental Algorithmics (JEA), Vol. 27, Article No. 4:1, pp.1-23, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Five-Cycle Counting Algorithms", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Harness_for_Informatic_Stream_Hashing.json b/agency-indexes/DoE/Parallel_Harness_for_Informatic_Stream_Hashing.json new file mode 100644 index 00000000..f73f9d20 --- /dev/null +++ b/agency-indexes/DoE/Parallel_Harness_for_Informatic_Stream_Hashing.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "PHISH is a lightweight framework which a set of independent processes can use to exchange data as they run on the same desktop machine, on processors of a parallel machine, or on different machines across a network. This enables them to work in a coordinated parallel fashion to perform computations on either streaming, archived, or self-generated data. The PHISH distribution includes a simple, portable library for performing data exchanges in useful patterns either via MPI message-passing or ZMQ sockets. PHISH input scripts are used to describe a data-processing algorithm, and additional tools provided in the PHISH distribution convert the script into a form that can be launched as a parallel job.", + "laborHours": 6733.6, + "languages": [ + "C++", + "C", + "CMake", + "Makefile", + "Ring", + "Edge", + "Python" + ], + "name": "Parallel Harness for Informatic Stream Hashing", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/phish", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Index-Based_Structural_Graph_Clustering_and_Its_Approximation.json b/agency-indexes/DoE/Parallel_Index-Based_Structural_Graph_Clustering_and_Its_Approximation.json new file mode 100644 index 00000000..b9485cb4 --- /dev/null +++ b/agency-indexes/DoE/Parallel_Index-Based_Structural_Graph_Clustering_and_Its_Approximation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper (https://github.com/ParAlg/gbbs/tree/master/benchmarks/SCAN/IndexBased):\n\nTom Tseng, Laxman Dhulipala, and Julian Shun.\nParallel Index-Based Structural Graph Clustering and Its Approximation.\nProceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pp. 1851-1864, 2021.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Index-Based Structural Graph Clustering and Its Approximation", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Infrastructure_Modeling_and_Inversion_Module_for_E4D.json b/agency-indexes/DoE/Parallel_Infrastructure_Modeling_and_Inversion_Module_for_E4D.json new file mode 100644 index 00000000..a973c06e --- /dev/null +++ b/agency-indexes/DoE/Parallel_Infrastructure_Modeling_and_Inversion_Module_for_E4D.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Electrical resistivity tomography ERT is a method of imaging the electrical conductivity of the subsurface. Electrical conductivity is a useful metric for understanding the subsurface because it is governed by geomechanical and geochemical properties that drive subsurface systems. ERT works by injecting current into the subsurface across a pair of electrodes, and measuring the corresponding electrical potential response across another pair of electrodes. Many such measurements are strategically taken across an array of electrodes to produce an ERT data set. These data are then processed through a computationally demanding process known as inversion to produce an image of the subsurface conductivity structure that gave rise to the measurements. Data can be inverted to provide 2D images, 3D images, or in the case of time-lapse 3D imaging, 4D images. ERT is generally not well suited for environments with buried electrically conductive infrastructure such as pipes, tanks, or well casings, because these features tend to dominate and degrade ERT images. This reduces or eliminates the utility of ERT imaging where it would otherwise be highly useful for, for example, imaging fluid migration from leaking pipes, imaging soil contamination beneath leaking subsurface tanks, and monitoring contaminant migration in locations with dense network of metal cased monitoring wells. The location and dimension of buried metallic infrastructure is often known. If so, then the effects of the infrastructure can be explicitly modeled within the ERT imaging algorithm, and thereby removed from the corresponding ERT image. However, there are a number of obstacles limiting this application. 1) Metallic infrastructure cannot be accurately modeled with standard codes because of the large contrast in conductivity between the metal and host material. 2) Modeling infrastructure in true dimension requires the computational mesh to be highly refined near the metal inclusions, which increases computational demands. 3) The ERT imaging algorithm requires specialized modifications to accommodate high conductivity inclusions within the computational mesh. The solution to each of these challenges was implemented within E4D (formerly FERM3D), which is a parallel ERT imaging code developed at PNNL (IPID #30249). The infrastructure modeling module implement in E4D uses a method of decoupling the model at the metallic interface(s) boundaries, into several well posed sub-problems (one for each distinct metallic inclusion) that are subsequently solved and recombined to form the global solution. The approach is based on the immersed interface method, with has been applied for similar problems in other fields (e.g. semiconductor industry). Comparisons to analytic solutions have shown the results to be very accurate, addressing item 1 above. The solution is implemented about an unstructured mesh, which enables arbitrary shapes to be efficiently modelled, thereby addressing item 2 above. In addition, the algorithm is written in parallel and shows excellent scalability, which also addresses equation 2 above. Finally, because only the boundaries of metallic inclusions are modeled, there are no high conductivity cells within the modeling mesh, and the problem described by item 3 above is no longer applicable.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "gfortran/intel" + ], + "name": "Parallel Infrastructure Modeling and Inversion Module for E4D", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Interior_Point_Solver_-_Simple_Branch_&_Bound.json b/agency-indexes/DoE/Parallel_Interior_Point_Solver_-_Simple_Branch_&_Bound.json new file mode 100644 index 00000000..1fdd8a8a --- /dev/null +++ b/agency-indexes/DoE/Parallel_Interior_Point_Solver_-_Simple_Branch_&_Bound.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The purpose of this software package is to solve large-scale block-angular mixed-integer (linear) programs specified in SMPS format; the major application of this software package is to solving large-scale stochastic mixed-integer programs, which are block-angular.", + "laborHours": 3298.4, + "name": "Parallel Interior Point Solver - Simple Branch & Bound", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/PIPS-SBB", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Iterative_Reconstruction_for_Tomography.json b/agency-indexes/DoE/Parallel_Iterative_Reconstruction_for_Tomography.json new file mode 100644 index 00000000..670cab6f --- /dev/null +++ b/agency-indexes/DoE/Parallel_Iterative_Reconstruction_for_Tomography.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-30" + }, + "description": "PIRT is a tomography inversion code that incorporates center of rotation correction written with the goal of being scalable on HPC systems. PIRT is built upon PETSc (which handles the optimization routines, data management and parallel I/O), Boost (which handles geometry routines) and FFTW (for position correction cost function evaluation).", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Iterative Reconstruction for Tomography", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Lattice_Subpaving_Map__plsm_.json b/agency-indexes/DoE/Parallel_Lattice_Subpaving_Map__plsm_.json new file mode 100644 index 00000000..2afd0dd8 --- /dev/null +++ b/agency-indexes/DoE/Parallel_Lattice_Subpaving_Map__plsm_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "facklerpw@ornl.gov" + }, + "date": { + "created": "2020-11-17", + "metadataLastUpdated": "2020-11-17" + }, + "description": "Custom spatial subdivision of N-dimensional lattice region in GPU memory. An extension of the method of a hyper-octree is used to allow for arbitrary subdivision ratios in each dimension. In addition, the decision to refine (or select) a given sub-region is based on a user-provided callback, allowing for arbitrary refinement domains to be expressed either geometrically or programmatically.", + "laborHours": 2432.0, + "languages": [ + "C++" + ], + "name": "Parallel Lattice Subpaving Map (plsm)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-Fusion/plsm", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Mandelbrot.json b/agency-indexes/DoE/Parallel_Mandelbrot.json new file mode 100644 index 00000000..ecf66d1b --- /dev/null +++ b/agency-indexes/DoE/Parallel_Mandelbrot.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "This project creates an image of a Mandelbrot fractal. This repository contains three separate codes: a serial version, an OpenMP version, and a hybrid OpenMP and MPI version.\n", + "laborHours": 273.6, + "name": "Parallel Mandelbrot", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/Mandelbrot", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Markov_Random_Fields_for_Image_Segmentation__PMRF-IS__v1.0.json b/agency-indexes/DoE/Parallel_Markov_Random_Fields_for_Image_Segmentation__PMRF-IS__v1.0.json new file mode 100644 index 00000000..bccfd164 --- /dev/null +++ b/agency-indexes/DoE/Parallel_Markov_Random_Fields_for_Image_Segmentation__PMRF-IS__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-23", + "metadataLastUpdated": "2018-08-13" + }, + "description": "This software performs multi-label segmentation of 2D/3D images. It is highly accurate, results rely on use of an Markov random field (MRF) formulation. It runs in both shared and distributed memory parallel modes. MRF algorithms are powerful tools in image analysis to explore contextual information of data.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Markov Random Fields for Image Segmentation (PMRF-IS) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tperciano/PMRF-IS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Maximum_Cardinality_Matchings_via_Tree-Grafting.json b/agency-indexes/DoE/Parallel_Maximum_Cardinality_Matchings_via_Tree-Grafting.json new file mode 100644 index 00000000..d7e6f6e9 --- /dev/null +++ b/agency-indexes/DoE/Parallel_Maximum_Cardinality_Matchings_via_Tree-Grafting.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2019-09-23" + }, + "description": "This software implements a new algorithm and its shared-memory parallelization for computing maximum cardinality matchings in bipartite graphs. The algorithm searches for augmenting paths via specialized breadth-first searches (BFS) from multiple source vertices, hence creating more parallelism than single source algorithms.", + "laborHours": 1003.2, + "languages": [], + "name": "Parallel Maximum Cardinality Matchings via Tree-Grafting", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/azadcse/ms-bfs-graft/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Planes_Information_Visualization.json b/agency-indexes/DoE/Parallel_Planes_Information_Visualization.json new file mode 100644 index 00000000..79a0e432 --- /dev/null +++ b/agency-indexes/DoE/Parallel_Planes_Information_Visualization.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This software presents a user-provided multivariate dataset as an interactive three dimensional visualization so that the user can explore the correlation between variables in the observations and the distribution of observations among the variables.", + "laborHours": 896.8, + "name": "Parallel Planes Information Visualization", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/infovis-parallel", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_TOUGH+HYDRATE_.json b/agency-indexes/DoE/Parallel_TOUGH+HYDRATE_.json new file mode 100644 index 00000000..6493d1aa --- /dev/null +++ b/agency-indexes/DoE/Parallel_TOUGH+HYDRATE_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2019-09-24" + }, + "description": "Parallel TOUGH + Hydrate, and other Parallel modules, takes TOUGH code to the next level by enabling parallel processing. TOUGH+ codes can be used for the solution of problems of fluid flow and heat transport in complex geologic media.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Parallel TOUGH+HYDRATE ", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Tasking_Library__PTL__v1.0.0.json b/agency-indexes/DoE/Parallel_Tasking_Library__PTL__v1.0.0.json new file mode 100644 index 00000000..c4f09c69 --- /dev/null +++ b/agency-indexes/DoE/Parallel_Tasking_Library__PTL__v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-14", + "metadataLastUpdated": "2021-07-14" + }, + "description": "Lightweight C++11 multithreading tasking system featuring thread-pool, task-groups, and lock-free task queue.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel Tasking Library (PTL) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jrmadsen/PTL.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_Variable_Population_Multi-Objective_Optimizer__pvpmoo__v1.0.json b/agency-indexes/DoE/Parallel_Variable_Population_Multi-Objective_Optimizer__pvpmoo__v1.0.json new file mode 100644 index 00000000..869fc9bc --- /dev/null +++ b/agency-indexes/DoE/Parallel_Variable_Population_Multi-Objective_Optimizer__pvpmoo__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-24", + "metadataLastUpdated": "2024-06-24" + }, + "description": "This is a parallel variable population multi-objective optimizer with an adaptive unified differential evolution algorithm or a genetic algorithm.\nIt can also be used for single objective optimization.\nSome features of this code include:\n1) The population size varies from generation to generation to save the total # of objective function evaluations.\n2) The population is uniformly distributed to a number of parallel processors for simultaneous objective function evaluation.\n3) The objective function evaluation can be attained from an external simulation program with control variables in its input file and objectives calculated from its output files.\n4) The optimizer includes an adaptive unified differential evolution algorithm and a real value genetic algorithm. The parameters in the unified differential evolution algorithm can be chosen to attain any mutation schemes in the published literature.", + "laborHours": 836.0, + "languages": [], + "name": "Parallel Variable Population Multi-Objective Optimizer (pvpmoo) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qianglbl/PVPmoo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_k-means++.json b/agency-indexes/DoE/Parallel_k-means++.json new file mode 100644 index 00000000..3d9e7a83 --- /dev/null +++ b/agency-indexes/DoE/Parallel_k-means++.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "A parallelization of the k-means++ seed selection algorithm on three distinct hardware platforms: GPU, multicore CPU, and multithreaded architecture. K-means++ was developed by David Arthur and Sergei Vassilvitskii in 2007 as an extension of the k-means data clustering technique. These algorithms allow people to cluster multidimensional data, by attempting to minimize the mean distance of data points within a cluster. K-means++ improved upon traditional k-means by using a more intelligent approach to selecting the initial seeds for the clustering process. While k-means++ has become a popular alternative to traditional k-means clustering, little work has been done to parallelize this technique. We have developed original C++ code for parallelizing the algorithm on three unique hardware architectures: GPU using NVidia's CUDA/Thrust framework, multicore CPU using OpenMP, and the Cray XMT multithreaded architecture. By parallelizing the process for these platforms, we are able to perform k-means++ clustering much more quickly than it could be done before.", + "laborHours": 0.0, + "languages": [], + "name": "Parallel k-means++", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/patrickmackey/parallel_kpp/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/patrickmackey/parallel_kpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_netCDF.json b/agency-indexes/DoE/Parallel_netCDF.json new file mode 100644 index 00000000..33906f56 --- /dev/null +++ b/agency-indexes/DoE/Parallel_netCDF.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "PnetCDF is a parallel I/O library for accessing Unidata's NetCDF files in classic formats. The software development is a collaborative work of Northwestern University and Argonne National Laboratory.", + "laborHours": 150312.8, + "languages": [], + "name": "Parallel netCDF", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/Parallel-NetCDF/PnetCDF/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Parallel-NetCDF/PnetCDF", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parallel_time_integration_software.json b/agency-indexes/DoE/Parallel_time_integration_software.json new file mode 100644 index 00000000..ce669b67 --- /dev/null +++ b/agency-indexes/DoE/Parallel_time_integration_software.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This package implements an optimal-scaling multigrid solver for the (non) linear systems that arise from the discretization of problems with evolutionary behavior. Typically, solution algorithms for evolution equations are based on a time-marching approach, solving sequentially for one time step after the other. Parallelism in these traditional time-integrarion techniques is limited to spatial parallelism. However, current trends in computer architectures are leading twards system with more, but not faster. processors. Therefore, faster compute speeds must come from greater parallelism. One approach to achieve parallelism in time is with multigrid, but extending classical multigrid methods for elliptic poerators to this setting is a significant achievement. In this software, we implement a non-intrusive, optimal-scaling time-parallel method based on multigrid reduction techniques. The examples in the package demonstrate optimality of our multigrid-reduction-in-time algorithm (MGRIT) for solving a variety of parabolic equations in two and three sparial dimensions. These examples can also be used to show that MGRIT can achieve significant speedup in comparison to sequential time marching on modern architectures.", + "homepageURL": "https://computation.llnl.gov/projects/parallel-time-integration-multigrid/software", + "laborHours": 0.0, + "name": "Parallel time integration software", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://computation.llnl.gov/projects/parallel-time-integration-multigrid/software", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parameter_Optimization_Toolbox_for_NS-3_network_optimization,_NS-3_Parameter_Optimization_Framework_[SWR-18-60].json b/agency-indexes/DoE/Parameter_Optimization_Toolbox_for_NS-3_network_optimization,_NS-3_Parameter_Optimization_Framework_[SWR-18-60].json new file mode 100644 index 00000000..fce6df9e --- /dev/null +++ b/agency-indexes/DoE/Parameter_Optimization_Toolbox_for_NS-3_network_optimization,_NS-3_Parameter_Optimization_Framework_[SWR-18-60].json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-07-02", + "metadataLastUpdated": "2024-03-11" + }, + "description": "This simulation-based parameter optimization framework is proposed to tune parameters of different types of communication networks using ns-3 to achieve the optimal network performance. It consists of three main components: an ns-3 packet reporting module; a sampler running simulations with all possible parameter sets for the input parameter variables by using a parallel executor at each generation; and a hybrid optimization algorithm for tuning configurable parameters of hybrid designs and application parameter variables. The proposed hybrid metaheuristic optimization algorithm combines an evolutionary algorithm with a gradient descent function to quickly achieve an approximate globally optimum solution.\n\nThis software is designed to be used in a multi-core processing Linux environment and run over a long duration of time. The execution time varies depending mainly upon the nature of the ns-3 configuration being simulated. This software includes a custom ns-3 QoS measurement application which must be included with the ns-3 source code during installation of the software.", + "laborHours": 1048.8, + "languages": [ + "C++", + "Python", + "C++" + ], + "name": "Parameter Optimization Toolbox for NS-3 network optimization, NS-3 Parameter Optimization Framework [SWR-18-60]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/ParaOptimizationNS3", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ParaOptimizationNS3", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parameterized_Pseudo-Differential_Operators_for_Applying_CNNs_to_Unstructured_Mesh_Data.json b/agency-indexes/DoE/Parameterized_Pseudo-Differential_Operators_for_Applying_CNNs_to_Unstructured_Mesh_Data.json new file mode 100644 index 00000000..94bda278 --- /dev/null +++ b/agency-indexes/DoE/Parameterized_Pseudo-Differential_Operators_for_Applying_CNNs_to_Unstructured_Mesh_Data.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2022-10-05" + }, + "description": "SAND2021-15058 O\nThis code accompanies the International Conference on Learning Representations (ICLR) paper entitled \"Parameterized Pseudo-Differential Operators for Applying CNNs to Unstructured Mesh Data.\" Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 395.2, + "languages": [ + "Python" + ], + "name": "Parameterized Pseudo-Differential Operators for Applying CNNs to Unstructured Mesh Data", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parametric_Analysis_Tool__PAT_.json b/agency-indexes/DoE/Parametric_Analysis_Tool__PAT_.json new file mode 100644 index 00000000..af882b3f --- /dev/null +++ b/agency-indexes/DoE/Parametric_Analysis_Tool__PAT_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2018-09-12" + }, + "description": "The Parametric Analysis Tool (PAT) is part of the OpenStudio collection of software tools.\u00a0It is included in the OpenStudio installer.\n", + "laborHours": 1055837.6, + "languages": [], + "name": "Parametric Analysis Tool (PAT)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-PAT/blob/develop/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-PAT", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parapint.json b/agency-indexes/DoE/Parapint.json new file mode 100644 index 00000000..3ff358cd --- /dev/null +++ b/agency-indexes/DoE/Parapint.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-09", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Parapint is a Python package for parallel solution of dynamic optimization problems. SAND2020-12446 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 3359.2, + "languages": [ + "Python" + ], + "name": "Parapint", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/parapint", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pareto_v1.0.0.json b/agency-indexes/DoE/Pareto_v1.0.0.json new file mode 100644 index 00000000..3f84c478 --- /dev/null +++ b/agency-indexes/DoE/Pareto_v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-28", + "metadataLastUpdated": "2021-10-28" + }, + "description": "An Optimization Framework for Produced Water Management and Beneficial Reuse", + "laborHours": 0.0, + "languages": [], + "name": "Pareto v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/project-pareto/project-pareto", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ParseGen_v.1.0.0.json b/agency-indexes/DoE/ParseGen_v.1.0.0.json new file mode 100644 index 00000000..cbbb961f --- /dev/null +++ b/agency-indexes/DoE/ParseGen_v.1.0.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-10-01", + "metadataLastUpdated": "2021-10-01" + }, + "description": "ParseGen is a software library that helps users create software that parses, or reads and understand, text file formats. ParseGen is based on formal language theory and is aimed at helping larger software applications read input files. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2021-2714 O", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "ParseGen v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/parsegen-cpp", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parser_for_Sabin-to-Mahoney_Transition_Model_of_Quasispecies_Replication.json b/agency-indexes/DoE/Parser_for_Sabin-to-Mahoney_Transition_Model_of_Quasispecies_Replication.json new file mode 100644 index 00000000..a21578fb --- /dev/null +++ b/agency-indexes/DoE/Parser_for_Sabin-to-Mahoney_Transition_Model_of_Quasispecies_Replication.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code is a data parse for preparing output from the Qspp agent-based stochastic simulation model for plotting in Excel. This code is specific to a set of simulations that were run for the purpose of preparing data for a publication. It is necessary to make this code open-source in order to publish the model code (Qspp), which has already been released. There is a necessity of assuring that results from using Qspp for a publication", + "laborHours": 1915.2, + "name": "Parser for Sabin-to-Mahoney Transition Model of Quasispecies Replication", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.github.com/carolzhou/virus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parsl_parsl.json b/agency-indexes/DoE/Parsl_parsl.json new file mode 100644 index 00000000..5a60c049 --- /dev/null +++ b/agency-indexes/DoE/Parsl_parsl.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "ybabuji@anl.gov" + }, + "date": { + "created": "2021-03-05", + "metadataLastUpdated": "2021-03-05" + }, + "description": "Parsl - Parallel Scripting Library", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Parsl/parsl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Parsl/parsl", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Parsnip_Parser_Creation_Application.json b/agency-indexes/DoE/Parsnip_Parser_Creation_Application.json new file mode 100644 index 00000000..78c62d2f --- /dev/null +++ b/agency-indexes/DoE/Parsnip_Parser_Creation_Application.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-04-30", + "metadataLastUpdated": "2024-04-30" + }, + "description": "Parsnip has three parts. The first part is the front-end user experience. The front end will be a graphical representation of the intermediate language. Once a user is satisfied with the information on the front end, Parsnip translates the data from the visual application into the second part of Parsnip - the intermediate language. More advanced users may skip the front end and generate their own intermediate language files. The final part is the backend which takes the intermediate language files and generates Zeek and Spicy code.\nParsnip will not completely replace parser developers. Many protocols have unique challenges requiring manual effort; however, the goal of Parsnip is to automate at least 90% of the development that largely consists of repetitive tasks. Parsnip output will compile a functioning parser but may not include all PDU types or parse all data.", + "laborHours": 5973.6, + "languages": [ + "JavaScript", + "Python", + "Jinja2" + ], + "name": "Parsnip Parser Creation Application", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cisagov/parsnip", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Partial_ASL_extensions_for_stochastic_programming.json b/agency-indexes/DoE/Partial_ASL_extensions_for_stochastic_programming.json new file mode 100644 index 00000000..e45c03f3 --- /dev/null +++ b/agency-indexes/DoE/Partial_ASL_extensions_for_stochastic_programming.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-18" + }, + "description": "Partially completed extensions for stochastic programming to the AMPL/solver interface library (ASL).modeling and experimenting with stochastic recourse problems. This software is not primarily for military applications.", + "homepageURL": "https://www.netlib.org/ampl/solvers", + "laborHours": 0.0, + "languages": [], + "name": "Partial ASL extensions for stochastic programming", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://netlib.sandia.gov/ampl/solvers/README", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.netlib.org/ampl/solvers", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Particle-In-Cell_Accelerator_Modeling_Interface.json b/agency-indexes/DoE/Particle-In-Cell_Accelerator_Modeling_Interface.json new file mode 100644 index 00000000..c6e6219f --- /dev/null +++ b/agency-indexes/DoE/Particle-In-Cell_Accelerator_Modeling_Interface.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-21", + "metadataLastUpdated": "2019-09-23" + }, + "description": "The software, PICMI and AMI, establish conventions for the naming and structuring of input files for Particle-In-Cell and particle accelerator simulations.", + "laborHours": 501.6, + "languages": [], + "name": "Particle-In-Cell/Accelerator Modeling Interface", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/atap-ami", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Particle-in-cell_accelerator_code_for_space-charge_dominated_beam_simulation.json b/agency-indexes/DoE/Particle-in-cell_accelerator_code_for_space-charge_dominated_beam_simulation.json new file mode 100644 index 00000000..a4c1ae2e --- /dev/null +++ b/agency-indexes/DoE/Particle-in-cell_accelerator_code_for_space-charge_dominated_beam_simulation.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Warp is a multidimensional discrete-particle beam simulation program designed to be applicable where the beam space-charge is non-negligible or dominant. It is being developed in a collaboration among LLNL, LBNL and the University of Maryland. It was originally designed and optimized for heave ion fusion accelerator physics studies, but has received use in a broader range of applications, including for example laser wakefield accelerators, e-cloud studies in high enery accelerators, particle traps and other areas. At present it incorporates 3-D, axisymmetric (r,z) planar (x-z) and transverse slice (x,y) descriptions, with both electrostatic and electro-magnetic fields, and a beam envelope model. The code is guilt atop the Python interpreter language.", + "laborHours": 0.0, + "languages": [], + "name": "Particle-in-cell/accelerator code for space-charge dominated beam simulation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/warp/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Particle_learning_for_probabilistic_deterministic_finite_automata.json b/agency-indexes/DoE/Particle_learning_for_probabilistic_deterministic_finite_automata.json new file mode 100644 index 00000000..ee517fff --- /dev/null +++ b/agency-indexes/DoE/Particle_learning_for_probabilistic_deterministic_finite_automata.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The plpdfa software is a product of an LDRD project at LLNL entitked \"Adaptive Sampling for Very High Throughput Data Streams\" (tracking number 11-ERD-035). This software was developed by a graduate student summer intern, Chris Challis, who worked under project PI Dan Merl furing the summer of 2011. The software the source code is implementing is a statistical analysis technique for clustering and classification of text-valued data. The method had been previously published by the PI in the open literature.", + "homepageURL": "http://cran.r-project.org", + "laborHours": 0.0, + "name": "Particle learning for probabilistic deterministic finite automata", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://cran.r-project.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PathParser.json b/agency-indexes/DoE/PathParser.json new file mode 100644 index 00000000..11edf37d --- /dev/null +++ b/agency-indexes/DoE/PathParser.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-08-26", + "metadataLastUpdated": "2021-05-19" + }, + "description": "PathParser is a python-based computational tool for the thermodynamics and robustness analysis of native and designed metabolic pathways. The following functionalities are provided: 1 Max-min driving force (MDF) optimization. The Gibbs free energy change of the least favorable reaction will be maximized to evaluate thermodynamic feasibility of the entire pathway. 2 Protein cost estimation. The smallest enzyme investment will be assessed by calculating the minimal total enzyme cost supporting a given pathway flux. 3 Robustness analysis. Specifically, an ensemble of models is generated to simulate the system response to enzyme perturbation based on bifurcation theory and a continuation method. Probability of system failure and flux fold change against enzyme perturbation are estimated as well as a flux control index.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PathParser", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PathParser", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PathRepHAN:_Hierarchical_attention_networks_for_pathology_report_classification.json b/agency-indexes/DoE/PathRepHAN:_Hierarchical_attention_networks_for_pathology_report_classification.json new file mode 100644 index 00000000..568bc5c3 --- /dev/null +++ b/agency-indexes/DoE/PathRepHAN:_Hierarchical_attention_networks_for_pathology_report_classification.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "Developers at ORNL explored how a deep learning (DL) approach based on hierarchical attention networks (HANs) can improve model performance for multiple information extraction tasks from unstructured cancer pathology reports compared to conventional methods that do not sufficiently capture syntactic and semantic contexts from free-text documents. The HAN was implemented for 2 information extraction tasks: (1) primary site, matched to 12 International Classification of Diseases for Oncology topography codes (7 breast, 5 lung primary sites), and (2) histological grade classification, matched to G1\u2013G4. Our results demonstrate that for both information tasks, HAN performed significantly better compared to the conventional ML and DL techniques.", + "laborHours": 501.6, + "languages": [ + "Python 2.7" + ], + "name": "PathRepHAN: Hierarchical attention networks for pathology report classification", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/v33/PathRepHAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PathScan_for_Splunk.json b/agency-indexes/DoE/PathScan_for_Splunk.json new file mode 100644 index 00000000..51cc03d4 --- /dev/null +++ b/agency-indexes/DoE/PathScan_for_Splunk.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "A Splunk App designed to parse and tabulate PathScan data.", + "laborHours": 15.2, + "name": "PathScan for Splunk", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jwernicke/pathscan-splunk", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jwernicke/pathscan-splunk", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Path_Finder.json b/agency-indexes/DoE/Path_Finder.json new file mode 100644 index 00000000..576bd95c --- /dev/null +++ b/agency-indexes/DoE/Path_Finder.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "PathFinder is a graph search program, traversing a directed cyclic graph to find pathways between labeled nodes. Searches for paths through ordered sequences of labels are termed signatures. Determining the presence of signatures within one or more graphs is the primary function of Path Finder. Path Finder can work in either batch mode or interactively with an analyst. Results are limited to Path Finder whether or not a given signature is present in the graph(s).", + "laborHours": 7630.4, + "languages": [ + "Standard ML", + "ABC", + "Python" + ], + "name": "Path Finder", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PathFinder", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pathogen_Knowledge_Base.json b/agency-indexes/DoE/Pathogen_Knowledge_Base.json new file mode 100644 index 00000000..3c231551 --- /dev/null +++ b/agency-indexes/DoE/Pathogen_Knowledge_Base.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": " When faced with biological threats, our ability to provide early warning, situational awareness, and decision support will depend on whether we can rapidly and accurately detect threat pathogens in clinical and environmental samples. While next generation sequencing technology and advanced analytic methods provide the means to identify the organisms present in metagenomic samples from clinical and environmental sources, proper identification of pathogens in these samples requires a comprehensive resource providing in-depth knowledge of known pathogens. Because there are myriad species, including rare and uncommon taxa, in metagenomic samples, it is not always possible to recognize pathogens by name. As time will most likely be a critical factor in outbreak situations, it may not be possible to consult with subject matter experts for pathogen identification. \n To effectively safeguard the security and safety of people, animals and plants, we must have detailed knowledge of the biological agents (pathogens), infectious diseases, and food-borne illnesses that could potentially cause harm. Prior to any mass event, relevant information must be identified, gathered together and integrated in ways that will make it most useful to the biosurveillence analysts in real-time during an actual event. This type of knowledge falls within the realm of a disease ontology, which integrates the various types of data associated with disease states. Having a comprehensive, curated, globally applicable disease ontology is critical to determine the severity of disease outbreaks, which in turn can inform predictive epidemiological models. For a disease ontology to be useful in biosurveillance applications, detailed information about the organisms that cause particular diseases (pathogens), as well as vectors that transmit the disease-causing pathogens, must be included in the ontology. \n While various websites and publications provide lists of pathogens and a few relevant features that may be useful, there is currently no single resource that provides a comprehensive curated list of all known human, animal and agriculturally relevant pathogens. To remedy this deficiency, we are developing a comprehensive pathogen knowledgebase, encompassing all known pathogens of humans, animals and plants. Having pathogen information already integrated into a usable knowledgebase will enable real-time analyses during an actual event, will facilitate the analysis of post-event data on pathogen-mediated disease outbreaks, and may contribute to improved predictive epidemiological models. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Pathogen Knowledge Base", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pavilion_2.x.json b/agency-indexes/DoE/Pavilion_2.x.json new file mode 100644 index 00000000..12fdf58e --- /dev/null +++ b/agency-indexes/DoE/Pavilion_2.x.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-02-11", + "metadataLastUpdated": "2022-02-11" + }, + "description": "High Performance Computing clusters require a diverse set of methods to verify that they meet their intended performance, stability, and functional design objectives. One method, testing, takes place over the entire life-cycle of a system with an emphasis on testing before, and after it's shipped to the customer and after significant system changes. To efficiently use a set of tests that may have very different setup, user interface, and result footprints a framework is needed that can control and bundle all these tests and quickly produce a common set of interpretable results. This software, called Pavilion, is such a framework. \nPavilion was originally developed as a replacement for the similar, scheduler specific framework. Pavilion 1.0 (and its predecessor) were heavily reliant on hand written build and run scripts for each test in order to handle to handle the complexities of real computing environments and the output the test itself. Pavilion 2.0 provides a rich configuration system that allows for automatically generating build and run scripts and dynamically handling the differences between clusters. The vast majority of the system is now pluggable, giving users the ability to modify Pavilion's operation via easy to write plugins. This includes plugins for gathering system data for each test, adding support for additional schedulers, and much more. In addition, Pavilion 2.0 provides a dynamic system for gathering test results and converting them into a format that can be easily read and analyzed. ", + "laborHours": 0.0, + "languages": [], + "name": "Pavilion 2.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/hpc/pavilion2", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PayamDiba_CoNSEPT.json b/agency-indexes/DoE/PayamDiba_CoNSEPT.json new file mode 100644 index 00000000..0a7940e0 --- /dev/null +++ b/agency-indexes/DoE/PayamDiba_CoNSEPT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and underlying mechanisms; however, there has been no systematic comparison of these models characterizing their relative strengths and shortcomings. Here, we interrogated a rich data set of neuroectodermal enhancers in Drosophila, representing cis- and trans- sources of expression variation, with a suite of biophysical and machine learning models. We performed rigorous comparisons of thermodynamics-based models implementing different mechanisms of activation, repression and cooperativity. Moreover, we developed a convolutional neural network (CNN) model, called CoNSEPT, that learns enhancer \u2018grammar\u2019 in an unbiased manner. CoNSEPT is the first general-purpose CNN tool for predicting enhancer function in varying conditions, such as different cell types and experimental conditions, and we show that such complex models can suggest interpretable mechanisms. We found model-based evidence for mechanisms previously established for the studied system, including cooperative activation and short-range repression. The data also favored one hypothesized activation mechanism over another and suggested an intriguing role for a direct, distance-independent repression mechanism. Our modeling shows that while fundamentally different models can yield similar fits to data, they vary in their utility for mechanistic inference.", + "laborHours": 349.6, + "languages": [], + "name": "PayamDiba/CoNSEPT", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PayamDiba/CoNSEPT", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PayamDiba_Manuscript_tools.json b/agency-indexes/DoE/PayamDiba_Manuscript_tools.json new file mode 100644 index 00000000..bdf026da --- /dev/null +++ b/agency-indexes/DoE/PayamDiba_Manuscript_tools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-04", + "metadataLastUpdated": "2024-11-04" + }, + "description": "CoNSEPT is a tool to predict gene expression in various cis and trans contexts. Inputs to CoNSEPT are enhancer sequence, transcription factor levels in one or many trans conditions, TF motifs (PWMs), and any prior knowledge of TF-TF interactions.", + "laborHours": 90166.4, + "languages": [], + "name": "PayamDiba/Manuscript_tools", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PayamDiba/Manuscript_tools", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PbCdlComm.json b/agency-indexes/DoE/PbCdlComm.json new file mode 100644 index 00000000..6e75313e --- /dev/null +++ b/agency-indexes/DoE/PbCdlComm.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The open-source PBCdlComm software is designed for data acquisition from PakBus-protocol based Campbell Data loggers by the Scientific Data Management team at Pacific Northwest National Laboratory (www.pnl.gov). This effort was funded by US Department of Energy's Atmospheric Radiation Measurement program (www.arm.gov). As an alternative for Campbell Scientific's Loggernet software, this is ideal for deploying with rugged field PCs that have limited processing resources and do not require a full-blown GUI module. The software is designed so that it can be extended to implement a new data storage mechanism, a customized post-processing module and/or integrated with web-services for sophisticated monitoring or reporting.", + "laborHours": 2553.6, + "name": "PbCdlComm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sutanay/PbCdlComm/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sutanay/PbCdlComm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PcapDB:_Search_Optimized_Packet_Capture,_Version_0.1.0.0.json b/agency-indexes/DoE/PcapDB:_Search_Optimized_Packet_Capture,_Version_0.1.0.0.json new file mode 100644 index 00000000..c3419280 --- /dev/null +++ b/agency-indexes/DoE/PcapDB:_Search_Optimized_Packet_Capture,_Version_0.1.0.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PcapDB is a packet capture system designed to optimize the captured data for fast search in the typical (network incident response) use case. The technology involved in this software has been submitted via the IDEAS system and has been filed as a provisional patent. It includes the following primary components: capture: The capture component utilizes existing capture libraries to retrieve packets from network interfaces. Once retrieved the packets are passed to additional threads for sorting into flows and indexing. The sorted flows and indexes are passed to other threads so that they can be written to disk. These components are written in the C programming language. search: The search components provide a means to find relevant flows and the associated packets. A search query is parsed and represented as a search tree. Various search commands, written in C, are then used resolve this tree into a set of search results. The tree generation and search execution management components are written in python. interface: The PcapDB web interface is written in Python on the Django framework. It provides a series of pages, API's, and asynchronous tasks that allow the user to manage the capture system, perform searches, and retrieve results. Web page components are written in HTML,CSS and Javascript.", + "laborHours": 194301.6, + "name": "PcapDB: Search Optimized Packet Capture, Version 0.1.0.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dirtbags/pcapdb", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pdsh.json b/agency-indexes/DoE/Pdsh.json new file mode 100644 index 00000000..9f46bafb --- /dev/null +++ b/agency-indexes/DoE/Pdsh.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Pdsh is a multithreaded remote shell client which executes commands on multiple remote hosts in parallel. Pdsh can use several different remote shell services, including standard \"rsh\", Kerberos IV, and ssh.", + "laborHours": 10640.0, + "languages": [], + "name": "Pdsh", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/pdsh", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PeakFitGUI.json b/agency-indexes/DoE/PeakFitGUI.json new file mode 100644 index 00000000..429945f3 --- /dev/null +++ b/agency-indexes/DoE/PeakFitGUI.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "miskowiecaj@ornl.gov" + }, + "date": { + "created": "2019-09-04", + "metadataLastUpdated": "2019-09-04" + }, + "description": "A graphical user interface for multipeak fitting Raman spectra, strongly based on lmfit.", + "laborHours": 380.0, + "languages": [ + "Python" + ], + "name": "PeakFitGUI", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/gxm/peakfitgui", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PeakWorks.json b/agency-indexes/DoE/PeakWorks.json new file mode 100644 index 00000000..c60088c7 --- /dev/null +++ b/agency-indexes/DoE/PeakWorks.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The PeakWorks software is designed to assist in the quantitative analysis of atom probe tomography (APT) generated mass spectra. Specifically, through an interactive user interface, mass peaks can be identified automatically (defined by a threshold) and/or identified manually. The software then provides a means to assign specific elemental isotopes (including more than one) to each peak. The software also provides a means for the user to choose background subtraction of each peak based on background fitting functions, the choice of which is left to the users discretion. Peak ranging (the mass range over which peaks are integrated) is also automated allowing the user to chose a quantitative range (e.g. full-widthhalf- maximum). The software then integrates all identified peaks, providing a background-subtracted composition, which also includes the deconvolution of peaks (i.e. those peaks that happen to have overlapping isotopic masses). The software is also able to output a 'range file' that can be used in other software packages, such as within IVAS. A range file lists the peak identities, the mass range of each identified peak, and a color code for the peak. The software is also able to generate 'dummy' peak ranges within an outputted range file that can be used within IVAS to provide a means for background subtracted proximity histogram analysis.", + "homepageURL": "https://store.pnnl.gov/content/peakworks", + "laborHours": 0.0, + "languages": [ + "MatLab" + ], + "name": "PeakWorks", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://store.pnnl.gov/content/peakworks", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Peak_Map.json b/agency-indexes/DoE/Peak_Map.json new file mode 100644 index 00000000..90874efc --- /dev/null +++ b/agency-indexes/DoE/Peak_Map.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2020-11-02" + }, + "description": "Peak Map is a software tool that allows users to generate nuclide library files for gamma spectroscopy from a nuclear data reference. SAND2019-15220 M\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 7995.2, + "languages": [ + "C#" + ], + "name": "Peak Map", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/Peak-Map/blob/master/PeakMap/LICENSE.rtf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Peak-Map", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pececillo.json b/agency-indexes/DoE/Pececillo.json new file mode 100644 index 00000000..c163f78d --- /dev/null +++ b/agency-indexes/DoE/Pececillo.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Pececillo is a proxy-app for the open source Truchas metal processing code (LA-CC-15-097). It implements many of the physics models used in Truchas: free-surface, incompressible Navier-Stokes fluid dynamics (e.g., water waves); heat transport, material phase change, view factor thermal radiation; species advection-diffusion; quasi-static, elastic/plastic solid mechanics with contact; electomagnetics (Maxwell's equations). The models are simplified versions that retain the fundamental computational complexity of the Truchas models while omitting many non-essential features and modeling capabilities. The purpose is to expose Truchas algorithms in a greatly simplified context where computer science problems related to parallel performance on advanced architectures can be more easily investigated. While Pececillo is capable of performing simulations representative of typical Truchas metal casting, welding, and additive manufacturing simulations, it lacks many of the modeling capabilites needed for real applications.", + "laborHours": 21705.6, + "name": "Pececillo", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/truchas/pececillo/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/truchas/pececillo", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pecos_v._1.0.json b/agency-indexes/DoE/Pecos_v._1.0.json new file mode 100644 index 00000000..1c7b73e1 --- /dev/null +++ b/agency-indexes/DoE/Pecos_v._1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pecos is a python package designed to perform quality control analysis on time series data for system operations. The software loads time indexed databases, performs a series of quality control tests defined by the user, and creates automated reports which include summary statistics, tables, and graphics.", + "laborHours": 2295.2, + "name": "Pecos v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/pecos/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pecos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PeleLM.json b/agency-indexes/DoE/PeleLM.json new file mode 100644 index 00000000..677f3732 --- /dev/null +++ b/agency-indexes/DoE/PeleLM.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "marc.day@nrel.gov" + }, + "date": { + "created": "2021-04-14", + "metadataLastUpdated": "2021-04-14" + }, + "description": "An adaptive mesh hydrodynamics simulation code for low Mach number reacting flows", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "PeleLM", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Combustion/PeleLM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PeleLMeX.json b/agency-indexes/DoE/PeleLMeX.json new file mode 100644 index 00000000..0d935508 --- /dev/null +++ b/agency-indexes/DoE/PeleLMeX.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-05-02", + "metadataLastUpdated": "2022-06-21" + }, + "description": "PeleLMeX is an adaptive-mesh low Mach number hydrodynamics code for reacting flows. PeleLMeX supports Embedded Boundary method to represent complex geometries and is parallelized with MPI + OpenMP for CPUs and MPI + CUDA or MPI + HIP for GPUs.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "PeleLMeX", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Combustion/PeleLMeX", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PelePhysics_[SWR-17-36].json b/agency-indexes/DoE/PelePhysics_[SWR-17-36].json new file mode 100644 index 00000000..77a48a3f --- /dev/null +++ b/agency-indexes/DoE/PelePhysics_[SWR-17-36].json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-04-24" + }, + "description": "PelePhysics is a suite of physics packages that provides functionality of use to reacting hydrodynamics CFD codes. The initial release includes an interface to reaction rate mechanism evaluation, transport coefficient evaluation, and a generalized equation of state (EOS) facility. Both generic evaluators and interfaces to code from externally available tools (Fuego for chemical rates, EGLib for transport coefficients) are provided.", + "laborHours": 2114760.8, + "languages": [ + "C++", + "C", + "Fortran", + "Python" + ], + "name": "PelePhysics [SWR-17-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/AMReX-Combustion/PelePhysics/blob/development/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Combustion/PelePhysics", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PelePhysics_v2.0.json b/agency-indexes/DoE/PelePhysics_v2.0.json new file mode 100644 index 00000000..ed7e60c5 --- /dev/null +++ b/agency-indexes/DoE/PelePhysics_v2.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-20", + "metadataLastUpdated": "2019-09-23" + }, + "description": "Software to provide fluid properties, including thermodynamic relationships, transport properties and reaction kinetics, for computational fluid dynamics packages.", + "laborHours": 2114760.8, + "languages": [], + "name": "PelePhysics v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Combustion/PelePhysics", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PepAligner.json b/agency-indexes/DoE/PepAligner.json new file mode 100644 index 00000000..b3e76ffa --- /dev/null +++ b/agency-indexes/DoE/PepAligner.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PepAligner program can read a file containing peptides and align them to a file of protein sequences (.Fasta or delimited text) using Smith-Waterman alignment.", + "laborHours": 1550.4, + "languages": [], + "name": "PepAligner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PepAligner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PeptideListToXML.json b/agency-indexes/DoE/PeptideListToXML.json new file mode 100644 index 00000000..77698de8 --- /dev/null +++ b/agency-indexes/DoE/PeptideListToXML.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The PeptideListToXML application reads a tab-delimited text file created by the Peptide Hit Results Processor (PHRP) and creates a PepXML with the appropriate information. The various _SeqInfo files created by PHRP must be present in the same folder as the text file. If the MASIC Scan Stats file is also present, then elution time information will be extracted and included in the PepXML file. You should ideally also include the name of the parameter file used for the MS/MS search engine.", + "laborHours": 4104.0, + "languages": [], + "name": "PeptideListToXML", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PeptideListToXML", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Peptide_Fragmentation_Modeller.json b/agency-indexes/DoE/Peptide_Fragmentation_Modeller.json new file mode 100644 index 00000000..13de50d2 --- /dev/null +++ b/agency-indexes/DoE/Peptide_Fragmentation_Modeller.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Peptide Fragmentation Modeller is a command-line utility reads that reads in a text file of peptide sequences and generates the theoretical fragmentation pattern for each, outputting the results in a single concatenated DTA file, or in separate .Dta files. The ion intensity values are not predicted values; instead, b, c, y, and z ions are assigned an intensity of 100; while a ions and neutral loss ions receive an intensity of 20.", + "laborHours": 1717.6, + "languages": [], + "name": "Peptide Fragmentation Modeller", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Peptide-Fragmentation-Modeller", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Peptide_Hit_Results_Processor.json b/agency-indexes/DoE/Peptide_Hit_Results_Processor.json new file mode 100644 index 00000000..1da9dabd --- /dev/null +++ b/agency-indexes/DoE/Peptide_Hit_Results_Processor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Peptide Hit Results Processor (PHRP) can be used to convert an X!Tandem results file (XML format), MSGF+ .tsv search result file, Sequest Synopsis/First Hits file, or Inspect search result into a series of tab-delimited text files summarizing the results. It will insert modification symbols into the peptide sequences for modified peptides. Parallel files are created containing sequence information, modification details, and protein information. The user can optionally provide a modification definition file that specifies the symbol to use for each modification mass.", + "laborHours": 514444.0, + "languages": [], + "name": "Peptide Hit Results Processor", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PHRP", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Percept.json b/agency-indexes/DoE/Percept.json new file mode 100644 index 00000000..8e1522f1 --- /dev/null +++ b/agency-indexes/DoE/Percept.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "The Percept software package is a collection of libraries and executables that provide tools for verifying computer simulations of engineering components and systems. Percept is useful for simulations using the finite element or finite volume methods on unstructured meshes. Percept includes API's for adaptive mesh refinement, geometry representation, the method of manufactured solutions, analysis of convergence including the convergence of vibrational eigenmodes, and metrics for analyzing the difference between fields represented on two different overlapping unstructured grids.", + "laborHours": 99560.0, + "languages": [ + "Mathematica", + "C++", + "Shell", + "C", + "CMake", + "Python" + ], + "name": "Percept", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/percept", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Performance_Estimator_of_Codes_on_Surfaces__PECOS__v._0.1.0.json b/agency-indexes/DoE/Performance_Estimator_of_Codes_on_Surfaces__PECOS__v._0.1.0.json new file mode 100644 index 00000000..1942a19f --- /dev/null +++ b/agency-indexes/DoE/Performance_Estimator_of_Codes_on_Surfaces__PECOS__v._0.1.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-10-11", + "metadataLastUpdated": "2024-09-18" + }, + "description": "PECOS is Python package that provides a framework for studying, developing, and evaluating quantum error-correcting codes. The primary focus is the simulation of lattice-surgery operations on topological stabilizer codes.", + "laborHours": 7052.8, + "languages": [ + "Python", + "Cython", + "C++" + ], + "name": "Performance Estimator of Codes on Surfaces (PECOS) v. 0.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/quantum-pecos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Performance_Prediction_Toolkit.json b/agency-indexes/DoE/Performance_Prediction_Toolkit.json new file mode 100644 index 00000000..dde31f65 --- /dev/null +++ b/agency-indexes/DoE/Performance_Prediction_Toolkit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-04" + }, + "description": "The Performance Prediction Toolkit (PPT), is a scalable co-design tool that contains the hardware and middle-ware models, which accept proxy applications as input in runtime prediction. PPT relies on Simian, a parallel discrete event simulation engine in Python or Lua, that uses the process concept, where each computing unit (host, node, core) is a Simian entity. Processes perform their task through message exchanges to remain active, sleep, wake-up, begin and end. ", + "laborHours": 45478.4, + "languages": [], + "name": "Performance Prediction Toolkit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PPT", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Performance_and_Architecture_Lab_Modeling_Tool.json b/agency-indexes/DoE/Performance_and_Architecture_Lab_Modeling_Tool.json new file mode 100644 index 00000000..3db9deae --- /dev/null +++ b/agency-indexes/DoE/Performance_and_Architecture_Lab_Modeling_Tool.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Analytical application performance models are critical for diagnosing performance-limiting resources, optimizing systems, and designing machines. Creating models, however, is difficult. Furthermore, models are frequently expressed in forms that are hard to distribute and validate. The Performance and Architecture Lab Modeling tool, or Palm, is a modeling tool designed to make application modeling easier. Palm provides a source code modeling annotation language. Not only does the modeling language divide the modeling task into sub problems, it formally links an application's source code with its model. This link is important because a model's purpose is to capture application behavior. Furthermore, this link makes it possible to define rules for generating models according to source code organization. Palm generates hierarchical models according to well-defined rules. Given an application, a set of annotations, and a representative execution environment, Palm will generate the same model. A generated model is a an executable program whose constituent parts directly correspond to the modeled application. Palm generates models by combining top-down (human-provided) semantic insight with bottom-up static and dynamic analysis. A model's hierarchy is defined by static and dynamic source code structure. Because Palm coordinates models and source code, Palm's models are 'first-class' and reproducible. Palm automates common modeling tasks. For instance, Palm incorporates measurements to focus attention, represent constant behavior, and validate models. Palm's workflow is as follows. The workflow's input is source code annotated with Palm modeling annotations. The most important annotation models an instance of a block of code. Given annotated source code, the Palm Compiler produces executables and the Palm Monitor collects a representative performance profile. The Palm Generator synthesizes a model based on the static and dynamic mapping of annotations to program behavior. The model -- an executable program -- is a hierarchical composition of annotation functions, synthesized functions, statistics for runtime values, and performance measurements.", + "laborHours": 0.0, + "languages": [ + "C/C++ Language compiler" + ], + "name": "Performance and Architecture Lab Modeling Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.pnnl.gov/perf-lab-hub/palm/palm/-/blob/master/README-license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab-hub/palm/palm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Peridigm.json b/agency-indexes/DoE/Peridigm.json new file mode 100644 index 00000000..872b9cfe --- /dev/null +++ b/agency-indexes/DoE/Peridigm.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Peridigm is a multiphysics simulation code for peridynamic models. It provides the capability to simulate nonlocal models of solids undergoing large deformations and failure. It provides basic linear elastic and perfectly plastic peridynamic material models, and well as the capability to apply simply initial, boundary and loading conditions.", + "laborHours": 53534.4, + "languages": [ + "C++", + "Jupyter Notebook", + "CMake", + "Python" + ], + "name": "Peridigm", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/peridigm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Peridot.json b/agency-indexes/DoE/Peridot.json new file mode 100644 index 00000000..d3b55903 --- /dev/null +++ b/agency-indexes/DoE/Peridot.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "julia.dark@cfdrc.com" + }, + "date": { + "created": "2019-11-18", + "metadataLastUpdated": "2019-11-18" + }, + "description": "Peridot is a mesh free state-based peridynamics simulation developed using the Kokkos library for parallel execution. ", + "homepageURL": "https://www.cfd-research.com/products/peridot", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Peridot", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.cfd-research.com/products/peridot", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "version": "0.1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Perl_Extension_to_the_Bproc_Library.json b/agency-indexes/DoE/Perl_Extension_to_the_Bproc_Library.json new file mode 100644 index 00000000..b34269cf --- /dev/null +++ b/agency-indexes/DoE/Perl_Extension_to_the_Bproc_Library.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "The Beowulf Distributed process Space (Bproc) software stack is comprised of UNIX/Linux kernel modifications and a support library by which a cluster of machines, each running their own private kernel, can present itself as a unified process space to the user. A Bproc cluster contains a single front-end machine and many back-end nodes which receive and run processes given to them by the front-end. Any process which is migrated to a back-end node is also visible as a ghost process on the fron-end, and may be controlled there using traditional UNIX semantics (e.g. ps(1), kill(1), etc). This software is a Perl extension to the Bproc library which enables the Perl programmer to make direct calls to functions within the Bproc library. See http://www.clustermatic.org, http://bproc.sourceforge.net, and http://www.perl.org", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "gcc or equivalent ANSI C compiler." + ], + "name": "Perl Extension to the Bproc Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Persistent_heap_Management_library.json b/agency-indexes/DoE/Persistent_heap_Management_library.json new file mode 100644 index 00000000..9f7c58e9 --- /dev/null +++ b/agency-indexes/DoE/Persistent_heap_Management_library.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PERM is a C library for persistent heap management and is intended for use with a dynamic-memory allocator (e.g. malloc, free). The PERM memory allocator replaces the standard C dynamic memory allocation functions with compatible versions that provide persistent memory to application programs. Memory allocated with the PERM allocatory will persist between program invocations after a call to a checkpoint function. This function essentially saves the state of the heap and registered global variables to a file which may reside in flash memory or other node local storage. A few other functions are also provided by the library to manage checkpoint files. Global variables in an application can be marked persistent and be included in a checkpoint by using a compiler attribute defined as PERM. The PERM checkpoint methof is not dependent on the programming model ans works with distributed memory or shared memory programs.", + "homepageURL": "https://computation.llnl.gov/projects/memory-centric-architectures/download/perm-je-0.9.7.tgz", + "laborHours": 0.0, + "name": "Persistent heap Management library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://computation.llnl.gov/projects/memory-centric-architectures/download/perm-je-0.9.7.tgz", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Personal_Alarm_System.json b/agency-indexes/DoE/Personal_Alarm_System.json new file mode 100644 index 00000000..85f26a7c --- /dev/null +++ b/agency-indexes/DoE/Personal_Alarm_System.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Software that runs on smartphones and desktop web browsers and notifies border officials of radiation alarms. It displays images and data associated with an alarm and provides a variety of reports. DOE had a need for discrete notification. PAS replaces the lights and sounds of a Radiation Portal Monitor.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Personal Alarm System", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pervasive_Collaboratorive_Computing_Environment_Jabber_Toolkit.json b/agency-indexes/DoE/Pervasive_Collaboratorive_Computing_Environment_Jabber_Toolkit.json new file mode 100644 index 00000000..5ad77b0a --- /dev/null +++ b/agency-indexes/DoE/Pervasive_Collaboratorive_Computing_Environment_Jabber_Toolkit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "PCCE Project background: Our experience in building distributed collaboratories has shown us that there is a growing need for simple, non-intrusive, and flexible ways to stay in touch and work together. Towards this goal we are developing a Pervasive Collaborative Computing Environment (PCCE) within which participants can rendezvous and interact with each other. The PCCE aims to support continuous or ad hoc collaboration, target daily tasks and base connectivity, be easy to use and install across multiple platforms, leverage off of existing components when possible, use standards-based components, and leverage off of Grid services (e.g., security and directory services). A key concept for this work is \"incremental trust\", which allows the system's \"trust\" of a given user to change dynamically. PCCE Jabber client software: This leverages Jabber. an open Instant Messaging (IM) protocol and the related Internet Engineering Task Force (IETF) standards \"XMPP\" and \"XMPP-IM\" to allow collaborating parties to chat either one-on-one or in \"chat rooms\". Standard Jabber clients will work within this framework, but the software will also include extensions to a (multi-platform) GUI client (Gaim) for X.509-based security, search, and incremental trust. This software also includes Web interfaces for managing user registration to a Jabber server. PCCE Jabber server software: Extensions to the code, database, and configuration files for the dominant open-source Jabber server, \"jabberd\". Extensions for search, X.509 security, and incremental trust. Note that the jabberd software is not included as part of this software.", + "homepageURL": "https://dst.lbl.gov/ACSSoftware/pccejt/Home", + "laborHours": 0.0, + "languages": [], + "name": "Pervasive Collaboratorive Computing Environment Jabber Toolkit", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://dst.lbl.gov/ACSSoftware/pccejt/Home/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dst.lbl.gov/ACSSoftware/pccejt/Home", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pescan.json b/agency-indexes/DoE/Pescan.json new file mode 100644 index 00000000..5943a2f1 --- /dev/null +++ b/agency-indexes/DoE/Pescan.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The software calculates the interior eigenstates of a nanosystem with a given Hamiltonian. This is used for nonselfconsistent calculations of electron and hole states for large (a few thousands to hundreds of thousands of atoms) nanostructures. The electron wave function is represented by a planewave basis set. FFT is used to transform the wavefunction from reciprocal space to real space to be applied to the potential. Nonlocal pseudopotentlals are used in the Hamiltonian and spin-orbit interactions are included. One primary approach to calculate the interior eigenstates in the code is to use the folded spectrum method. Several numerical algorithms are implemented in this package, including the conjugated gradient method, the Jacobi-Davidson method, and the LOPCG method. The user can select different algorithms based on their particular problem and number of wavefunctions needed to be solved.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Fortran 90 and C" + ], + "name": "Pescan", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PetaVision_version_2.0.json b/agency-indexes/DoE/PetaVision_version_2.0.json new file mode 100644 index 00000000..61cfb298 --- /dev/null +++ b/agency-indexes/DoE/PetaVision_version_2.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-03-15", + "metadataLastUpdated": "2018-03-15" + }, + "description": "PetaVision is an open source, object oriented neural simulation toolbox optimized for high-performance multi-core, multi-node computer architectures. PetaVision is intended for computational neuroscientists who seek to apply neuromorphic models to hard signal processing problems; both to improve on the performance of existing algorithms and/or to gain insight into the computational mechanisms underlying biological neural processing. \n\nPlease note that this assertion and ESTSC deposit are only for the portions of PetaVision which have been funded and written by LANL developers.", + "laborHours": 69342.4, + "name": "PetaVision version 2.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PetaVision/OpenPV", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pfleger-Lab_Metabolic-Modeling---Yield-Analysis-of-PhaG.json b/agency-indexes/DoE/Pfleger-Lab_Metabolic-Modeling---Yield-Analysis-of-PhaG.json new file mode 100644 index 00000000..e270fd19 --- /dev/null +++ b/agency-indexes/DoE/Pfleger-Lab_Metabolic-Modeling---Yield-Analysis-of-PhaG.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-05", + "metadataLastUpdated": "2024-12-04" + }, + "description": "Microbial lipid metabolism is an attractive route for producing oleochemicals. The predominant strategy centers on heterologous thioesterases to synthesize desired chain-length fatty acids. To convert acids to oleochemicals (e.g., fatty alcohols, ketones), the narrowed fatty acid pool needs to be reactivated as coenzyme A thioesters at cost of one ATP per reactivation \u2013 an expense that could be saved if the acyl-chain was directly transferred from ACP- to CoA-thioester. Here, we demonstrate such an alternative acyl-transferase strategy by heterologous expression of PhaG, an enzyme first identified in Pseudomonads, that transfers 3-hydroxy acyl-chains between acyl-carrier protein and coenzyme A thioester forms for creating polyhydroxyalkanoate monomers. We use it to create a pool of acyl-CoA\u2019s that can be redirected to oleochemical products. Through bioprospecting, mutagenesis, and metabolic engineering, we develop three strains of Escherichia coli capable of producing over 1\u2009g/L of medium-chain free fatty acids, fatty alcohols, and methyl ketones.", + "laborHours": 157304.8, + "languages": [], + "name": "Pfleger-Lab/Metabolic-Modeling---Yield-Analysis-of-PhaG", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pfleger-Lab/Metabolic-Modeling---Yield-Analysis-of-PhaG", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PhATE__Phage_Annotation_Tool_and_Evaluator_.json b/agency-indexes/DoE/PhATE__Phage_Annotation_Tool_and_Evaluator_.json new file mode 100644 index 00000000..ffc83153 --- /dev/null +++ b/agency-indexes/DoE/PhATE__Phage_Annotation_Tool_and_Evaluator_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "nijhuis2@llnl.gov" + }, + "date": { + "created": "2018-02-23", + "metadataLastUpdated": "2018-07-19" + }, + "description": "A sequence-based annotation pipeline for phage", + "laborHours": 3830.4, + "languages": [], + "name": "PhATE (Phage Annotation Tool and Evaluator)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/phate", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Phalanx_V1.0.json b/agency-indexes/DoE/Phalanx_V1.0.json new file mode 100644 index 00000000..b72d2434 --- /dev/null +++ b/agency-indexes/DoE/Phalanx_V1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Phalanx is a software library to provide flexible dependency management for complex nonlinear partial differential equation operators. It breaks a complex set of equations into a manageable set of fields and evaluation routines. Users can flexibly swap evaluators to change the underlying dependency graph of the fields automatically. By constructing the dependency list, sensitivities can be calculated either analytically or by using embedded automatic differentiation software.", + "laborHours": 8344830.4, + "name": "Phalanx V1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/phalanx/copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Phase-Field_Method_Tutorial_Codes.json b/agency-indexes/DoE/Phase-Field_Method_Tutorial_Codes.json new file mode 100644 index 00000000..8fe1baff --- /dev/null +++ b/agency-indexes/DoE/Phase-Field_Method_Tutorial_Codes.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "dewittsj@ornl.gov" + }, + "date": { + "created": "2024-01-10", + "metadataLastUpdated": "2024-01-10" + }, + "description": "This repository contains example implementations of phase-field codes primarily for educational purposes. These codes demonstrate how a simple phase-field models can be implemented as an introduction for researchers new to the area (students, new staff, collaborators from different domains, etc.). \n\nThe computer code includes highly documented Jupyter notebooks that implement phase-field models and analyze the results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Phase-Field Method Tutorial Codes", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/pf_tutorial_codes", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Phase_Field_Dislocation_Dynamics__PFDD_.json b/agency-indexes/DoE/Phase_Field_Dislocation_Dynamics__PFDD_.json new file mode 100644 index 00000000..ff95f48d --- /dev/null +++ b/agency-indexes/DoE/Phase_Field_Dislocation_Dynamics__PFDD_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-05-01", + "metadataLastUpdated": "2018-05-01" + }, + "description": "Phase Field Dislocation Dynamics (PFDD) is a phase field approach for tracking the motion and interactions of individual dislocations in materials, mostly face-centered cubic (fcc) metals. The phase field approach relies on scalar order parameters or phase field variables to track a quantity of interest. In PFDD, these phase field variables represent the passage of perfect dislocations across each active slip system, with one order parameter defined in each slip system. Partial dislocations are represented with linear combinations of the order parameters. The system is evolved through minimization of the total system energy, which is directly dependent on the phase field variables. All of the physics is described by the total energy functional that is derived from a thermodynamic basis, and the system kinetics are evolved using a Ginzburg-Landau (GL) equation.", + "laborHours": 3024.8, + "name": "Phase Field Dislocation Dynamics (PFDD)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Phase-Field-Dislocation-Dynamics-PFDD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Phase_Field_Dislocation_Dynamics__PFDD__version_2.x.json b/agency-indexes/DoE/Phase_Field_Dislocation_Dynamics__PFDD__version_2.x.json new file mode 100644 index 00000000..f1f087ca --- /dev/null +++ b/agency-indexes/DoE/Phase_Field_Dislocation_Dynamics__PFDD__version_2.x.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-17", + "metadataLastUpdated": "2023-11-21" + }, + "description": "This disclosure is for version 2.x of a mesoscale model called Phase Field Dislocation Dynamics (PFDD). PFDD is used for investigating deformation in nanoscale (grain sizes of ~300 nm and less) materials, such as metals and alloys. This approach models the motion and interaction of individual defects, namely dislocations, in the material using scalar-valued phase field variables, also called order parameters. The system is evolved through energy minimization thus the model calculates the total energy density in terms of the phase field variables. The energy minimization is completed using the Ginzburg-Landau equation, and is implemented with explicit time integration. The total system energy can be comprised of several terms, including the strain energy (which describes dislocation-dislocation interactions), the energy due to an applied stress (dislocation interactions with the applied stress), and a core/lattice (perfect dislocations) or generalized stacking fault (partial dislocations) energy (described the dislocation core structure). The latter term in particular may vary based on the crystal structure being modeled and is typically informed using lower length scale (e.g., atomistic) approaches, although no such (atomistic) calculations are completed within the PFDD algorithm. This basic formulation was previously reviewed by Los Alamos National Laboratory and released under license number C17113. This previously reviewed version we will henceforth refer to as PFDD v1.0. \n\nPFDD v1.0 consisted of 2 codes (one parallel and one serial) plus input files, all written in the C language. This new disclosure is addressing the next versions of the PFDD, versions 2.x. There have been several enhancements of PFDD v1.0, which are described here and included in the attached code, which we will refer to as PFDD v2.0. There are also several new features described here that are either planned or already in process and are expected to be subsequent releases, i.e., v2.1, v2.2, ...v2.x.", + "laborHours": 0.0, + "languages": [], + "name": "Phase Field Dislocation Dynamics (PFDD) version 2.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Phase-Field-Dislocation-Dynamics-PFDD-2.x", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Phisherman_v_1.0.json b/agency-indexes/DoE/Phisherman_v_1.0.json new file mode 100644 index 00000000..bcf4ca3a --- /dev/null +++ b/agency-indexes/DoE/Phisherman_v_1.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Phisherman is an online software tool that was created to help experimenters study phishing. It can potentially be re-purposed to run other human studies. Phisherman enables studies to be run online, so that users can participate from their own computers. This means that experimenters can get data from subjects in their natural settings. Alternatively, an experimenter can also run the app online in a lab-based setting, if that is desired. The software enables the online deployment of a study that is comprised of three main parts: (1) a consent page, (2) a survey, and (3) an identification task, with instruction/transition screens between each part, allowing the experimenter to provide the user with instructions and messages. Upon logging in, the subject is taken to the permission page, where they agree to or do not agree to take part in the study. If the subject agrees to participate, then the software randomly chooses between doing the survey first (and identification task second) or the identification task first (and survey second). This is to balance possible order effects in the data. Procedurally, in the identification task, the software shows the stimuli to the subject, and asks if she thinks it is a phish (yes/no) and how confident she is about her answer. The subject is given 5 levels of certainty to select from, labeled \"low\" (1), to \"medium\" (3), to \"high\" (5), with the option of picking a level between low and medium (2), and between medium and high (4). After selecting his/her confidence level, then the \"Next\" button activates, allowing a user to move to the next email. The software saves a given subject's progress in the identification task, so that she may log in and out of the site. The consent page is a space for the experimenter to provide the subject with human studies board /internal review board information, and to formally consent to participate in the study. The survey is a space for the experimenter to provide questions and spaces for the users to input answers (allowing both multiple-choice and free-answer options). Phisherman includes administrative pages for managing the stimuli and users. This includes a tool for the experimenter to create, preview, edit, delete (if desired), and manage stimuli (emails). The stimuli may include pictures (uploaded to an appropriate folder) and links, for realism. The software includes a safety feature that prevents the user from going to any link location or opening a file/image. Instead of re-directing the subject's browser, the software provides a pop-up box with the URL location of where the user would have gone. Another administrative page may be used to create fake subject accounts for testing the software prior to deployment, as well as to delete subject accounts when necessary. Data from the experiment can be downloaded from another administrative page.", + "laborHours": 3800.0, + "languages": [ + "Groovy", + "CSS", + "JavaScript" + ], + "name": "Phisherman v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/phisherman", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Phoebus.json b/agency-indexes/DoE/Phoebus.json new file mode 100644 index 00000000..c0151714 --- /dev/null +++ b/agency-indexes/DoE/Phoebus.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "Phoebus is a performance portable code for simulating relativistic astrophysical phenomena. Phoebus includes the following physics: 1) general relativity, including both stationary and dynamical spacetimes, 2) magnetohydrodynamics closed by a general equation of state, 3) neutrino transport and weak interactions that couple neutrinos and matter, and 4) nuclear reactions. Capabilities for these physical ingredients are developed atop the open source Parthenon framework for performance portable, block-structured adaptive mesh refinement.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Phoebus", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Phoenix.json b/agency-indexes/DoE/Phoenix.json new file mode 100644 index 00000000..7eb956b0 --- /dev/null +++ b/agency-indexes/DoE/Phoenix.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "ezellma@ornl.gov" + }, + "date": { + "created": "2022-02-23", + "metadataLastUpdated": "2022-02-23" + }, + "description": "Phoenix is a library and set of tools to simplify cluster provisioning and management. It is intended to be lightweight yet powerful. Its design borrows the best ideas and corrects the worst sins from other cluster management systems used in the past.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Phoenix", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/phoenix", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Phoenix_v._1.0-SNAPSHOT.json b/agency-indexes/DoE/Phoenix_v._1.0-SNAPSHOT.json new file mode 100644 index 00000000..7c947a51 --- /dev/null +++ b/agency-indexes/DoE/Phoenix_v._1.0-SNAPSHOT.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Phoenix is a Java Virtual Machine (JVM) based library for performing mathematical and astrodynamics calculations. It consists of two primary sub-modules, phoenix-math and phoenix-astrodynamics. The mathematics package has a variety of mathematical classes for performing 3D transformations, geometric reasoning, and numerical analysis. The astrodynamics package has various classes and methods for computing locations, attitudes, accesses, and other values useful for general satellite modeling and simulation. Methods for computing celestial locations, such as the location of the Sun and Moon, are also included. Phoenix is meant to be used as a library within the context of a larger application. For example, it could be used for a web service, desktop client, or to compute simple values in a scripting environment.", + "laborHours": 7721.6, + "languages": [ + "Scala/scalac/2.11" + ], + "name": "Phoenix v. 1.0-SNAPSHOT", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/phoenix/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/phoenix", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Photovoltaic_Distributed_Energy_Resource__PV-DER__Simulation_Utility.json b/agency-indexes/DoE/Photovoltaic_Distributed_Energy_Resource__PV-DER__Simulation_Utility.json new file mode 100644 index 00000000..026e2b3e --- /dev/null +++ b/agency-indexes/DoE/Photovoltaic_Distributed_Energy_Resource__PV-DER__Simulation_Utility.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-02", + "metadataLastUpdated": "2019-08-02" + }, + "description": "This software allows the user to run simulations of a solar PV-Distributed energy resource connected to a stiff voltage source. It allows modifying DER parameters, introducing external disturbance events, and visualizing the simulation results. It models the PV-DER (inverter) using dynamic phasor concept. ", + "laborHours": 2401.6, + "languages": [], + "name": "Photovoltaic Distributed Energy Resource (PV-DER) Simulation Utility", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sibyjackgrove/SolarPV-DER-simulation-utility", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Photovoltaic_Reliability_Performance_Model_v_2.0.json b/agency-indexes/DoE/Photovoltaic_Reliability_Performance_Model_v_2.0.json new file mode 100644 index 00000000..497325e6 --- /dev/null +++ b/agency-indexes/DoE/Photovoltaic_Reliability_Performance_Model_v_2.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "PV-RPM is intended to address more \u201creal world\u201d situations by coupling a photovoltaic system performance model with a reliability model so that inverters, modules, combiner boxes, etc. can experience failures and be repaired (or left unrepaired). The model can also include other effects, such as module output degradation over time or disruptions such as electrical grid outages. In addition, PV-RPM is a dynamic probabilistic model that can be used to run many realizations (i.e., possible future outcomes) of a system\u2019s performance using probability distributions to represent uncertain parameter inputs.", + "homepageURL": "https://sam.nrel.gov/photovoltaic/pvrpm.html", + "laborHours": 0.0, + "languages": [ + "For existing proof-of-concept, it was written in Goldsim in an object oriented format. The next vers" + ], + "name": "Photovoltaic Reliability Performance Model v 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sam.nrel.gov/photovoltaic/pvrpm.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sam.nrel.gov/photovoltaic/pvrpm.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PhyCA-PhyloChip_Analysis.json b/agency-indexes/DoE/PhyCA-PhyloChip_Analysis.json new file mode 100644 index 00000000..b87f7c35 --- /dev/null +++ b/agency-indexes/DoE/PhyCA-PhyloChip_Analysis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-28", + "metadataLastUpdated": "2019-01-29" + }, + "description": "PhyCA allows interpretation of a PhyloChip assay. It takes as input, a text file containing the fluorescent intensity from each feature on the microarray surface. PhyCA will determine the background and noise levels, compare probes against controls and determine response scores for each probe pair. It then summarizes a set of probe pair results to determine presence of an operational taxonomic unit as well as its abundance. The PhyCA software is novel from other microarray interpretation software from the following reasons: 1) It leverages spiked-in Quantitative Standards and non-spike-in Negative Controls to build a per-chip model of positive and non-positive responses. 2) It allows a refinement of Presence/Absence calls by evaluating each responding probe against a putative cross-hybridization network. 3) It can be used with phylogenetic microarrays designed for Bacteria, Archaea or Eukaryotes. Hardware req.: PC, MAC; Software req.: OS: Windows, Mac, Linux; Types of files: source code, control information; user guide. The software depends on other software to be installed on the same machine as PhyCA.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1352.8, + "languages": [], + "name": "PhyCA-PhyloChip Analysis", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PhyML.json b/agency-indexes/DoE/PhyML.json new file mode 100644 index 00000000..8a5ee2d1 --- /dev/null +++ b/agency-indexes/DoE/PhyML.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-18", + "metadataLastUpdated": "2024-09-18" + }, + "description": "Python scripts for physics informed machine learning for time-dependent problems. The code implements\nhard constrained sequential physics-informed neural networks (HCSPINNs) using JAX library. The details\nof the method and implementation can be found in the following paper:\nRoy, P., & Castonguay, S. (2024). Exact Enforcement of Temporal Continuity in Sequential Physics-\nInformed Neural Networks. arXiv preprint arXiv:2403.03223. (https://arxiv.org/abs/2403.03223)", + "laborHours": 1444.0, + "languages": [], + "name": "PhyML", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/PhyML", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Phylogenetic_Tree_and_Multiple_Sequence_Alignment__MSA__Services.json b/agency-indexes/DoE/Phylogenetic_Tree_and_Multiple_Sequence_Alignment__MSA__Services.json new file mode 100644 index 00000000..00a0ac5c --- /dev/null +++ b/agency-indexes/DoE/Phylogenetic_Tree_and_Multiple_Sequence_Alignment__MSA__Services.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "This service provides a set of methods for querying, manipulating, and analyzing multiple sequence alignments and phylogenetic trees. It also has functions to build alignments and trees.", + "laborHours": 45676.0, + "languages": [], + "name": "Phylogenetic Tree and Multiple Sequence Alignment (MSA) Services", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/trees2", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Physics-Preserved_Graph_Networks_for_Real-Time_Fault_Location.json b/agency-indexes/DoE/Physics-Preserved_Graph_Networks_for_Real-Time_Fault_Location.json new file mode 100644 index 00000000..f86ed3a3 --- /dev/null +++ b/agency-indexes/DoE/Physics-Preserved_Graph_Networks_for_Real-Time_Fault_Location.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "We develop a software called Physics-Preserved Graph Network (PPGN) to accurately locate faults at the node level with limited observability and labeled training data. PPGN has a unique two-stage graph neural network architecture. The first stage learns the graph embedding to represent the entire network using a few measured nodes. The second stage finds relations between the labeled and unlabeled data samples to further improve the location accuracy.", + "laborHours": 471.2, + "languages": [], + "name": "Physics-Preserved Graph Networks for Real-Time Fault Location", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PPGN.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Physics_Integration_KErnels__PIKE_.json b/agency-indexes/DoE/Physics_Integration_KErnels__PIKE_.json new file mode 100644 index 00000000..28591cae --- /dev/null +++ b/agency-indexes/DoE/Physics_Integration_KErnels__PIKE_.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "Pike is a software library for coupling and solving multiphysics applications. It provides basic interfaces and utilities for performing code-to-code coupling. It provides simple \"black-box\" Picard iteration methods for solving the coupled system of equations including Jacobi and Gauss-Seidel solvers. Pike was developed originally to couple neutronics and thermal fluids codes to simulate a light water nuclear reactor for the Consortium for Simulation of Light-water Reactors (CASL) DOE Energy Innovation Hub. The Pike library contains no physics and just provides interfaces and utilities for coupling codes. It will be released open source under a BSD license as part of the Trilinos solver framework (trilinos.org) which is also BSD. This code provides capabilities similar to other open source multiphysics coupling libraries such as LIME, AMP, and MOOSE.", + "laborHours": 4043.2, + "languages": [ + "CMake", + "C++", + "Shell" + ], + "name": "Physics Integration KErnels (PIKE)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Pike", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pianola_Version_1.0.json b/agency-indexes/DoE/Pianola_Version_1.0.json new file mode 100644 index 00000000..7aa55b1a --- /dev/null +++ b/agency-indexes/DoE/Pianola_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pianola is a software benchmark for measuring the performance of input/output (I/O) hardware and software. It works by monitoring the I/O activity of an existing application and storing the sequence of events, along with their timing, in a script. After some additional processing, a separate piece of software in this package can replay these I/) events and replicate their timing without reference to the original application. Therefore, Pianola allows users to create standalone I/O benchmarks that mimic the behavior of applications that either cannot be released or that are difficult for nonspecialists to configure, build or run.", + "homepageURL": "https://computation.llnl.gov/software-catalog", + "laborHours": 0.0, + "name": "Pianola Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://computation.llnl.gov/software-catalog", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PickerXL.json b/agency-indexes/DoE/PickerXL.json new file mode 100644 index 00000000..65c752de --- /dev/null +++ b/agency-indexes/DoE/PickerXL.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "chaic@ornl.gov" + }, + "date": { + "created": "2025-01-29", + "metadataLastUpdated": "2025-01-30" + }, + "description": "Python scripts for using the PickerXL model, which operates on seismic single station data to pick primary and secondary waves.", + "laborHours": 121.6, + "languages": [ + "Python" + ], + "name": "PickerXL", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/picker-xl", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Picviewer_v0.0.1.json b/agency-indexes/DoE/Picviewer_v0.0.1.json new file mode 100644 index 00000000..12ecbf53 --- /dev/null +++ b/agency-indexes/DoE/Picviewer_v0.0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-03", + "metadataLastUpdated": "2019-09-23" + }, + "description": "PICviewer is an easy-to-use graphical user interface for data analysis and visualization of Particle-In-Cell (PIC) simulations.", + "laborHours": 2781.6, + "languages": [], + "name": "Picviewer v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/ecp_warpx/picviewer/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pinyon,_Version_0.json b/agency-indexes/DoE/Pinyon,_Version_0.json new file mode 100644 index 00000000..1ba83840 --- /dev/null +++ b/agency-indexes/DoE/Pinyon,_Version_0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Pinyon is a tool that stores steps involved in creating a model derived from a collection of data. The main function of Pinyon is to store descriptions of calculations used to analyze or visualize the data in a database, and allow users to view the results of these calculations via a web interface. Additionally, users may also use the web interface to make adjustments to the calculations and rerun the entire collection of analysis steps automatically.", + "laborHours": 6505.6, + "name": "Pinyon, Version 0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/pinyon/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pinyon", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pipeline_Hydrogen_Decarbonization_and_Repurposing_Analyzers__P-HyDRAs_.json b/agency-indexes/DoE/Pipeline_Hydrogen_Decarbonization_and_Repurposing_Analyzers__P-HyDRAs_.json new file mode 100644 index 00000000..0e6cb803 --- /dev/null +++ b/agency-indexes/DoE/Pipeline_Hydrogen_Decarbonization_and_Repurposing_Analyzers__P-HyDRAs_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "The Pipeline Hydrogen Decarbonization and Repurposing Analyzers (P-HyDRAs) are a set of prototype computational tools for simulating and optimizing midstream natural gas pipeline system operations subject to location and time-dependent hydrogen blending. The models can accurately resolve dynamic gas flows through large-scale pipeline networks using non-ideal gas equations of state. The codes can be used as decision support for planning and design decisions involving intra-day energy flow schedules as well as spatiotemporal economic values of natural gas, hydrogen, and net energy delivered to consumers while ensuring that pipeline hydraulic limitations, gas compressor station constraints, operational factors, and pre-existing shipping contracts are satisfied. The inputs to the codes are a model of the pipeline system as well as time-series data that specify boundary conditions on the network. For optimization, the code module requires price and quantity offers for natural gas and hydrogen and price and quantity bids for energy, which are used as time-dependent constraints in an optimal control problem. The outputs are time-series data that provide a predictive simulation of gas flows, mass fractions, and pressures, or with additional degrees of freedom give an approximately optimal solution for gas injections/withdrawals, compressor settings, and sensitivities to the objective function that provide locational values of energy.", + "laborHours": 5198.4, + "languages": [], + "name": "Pipeline Hydrogen Decarbonization and Repurposing Analyzers (P-HyDRAs)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/phydras", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pixie16_Python_Interface__Pixie16__v1.json b/agency-indexes/DoE/Pixie16_Python_Interface__Pixie16__v1.json new file mode 100644 index 00000000..29e3517b --- /dev/null +++ b/agency-indexes/DoE/Pixie16_Python_Interface__Pixie16__v1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-14", + "metadataLastUpdated": "2019-10-15" + }, + "description": "This module mostly wraps the XIA C-library to control and readout the XIA-pixie16 module. It also includes some functions to analyze the data and to make control of the pixie16 more convienent in python.", + "laborHours": 2401.6, + "languages": [], + "name": "Pixie16 Python Interface (Pixie16) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/pypixie16/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Place_polarized_neutron_reflectivity_data_in_bins_of_constant_wavevector_transfer.json b/agency-indexes/DoE/Place_polarized_neutron_reflectivity_data_in_bins_of_constant_wavevector_transfer.json new file mode 100644 index 00000000..d6fe076d --- /dev/null +++ b/agency-indexes/DoE/Place_polarized_neutron_reflectivity_data_in_bins_of_constant_wavevector_transfer.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "fitzsimmonsm@ornl.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-18" + }, + "description": "Code to place polarized neutron reflectivity into bins of constant Qz with regard for Zeeman energy change to the spin-flip channel.\n The code is written as a Jupyter notebook. Example data are included as separate files (spin_down.txt and spin_up.txt). As a first step, run all cells in the notebook. Opportunities are identified for users to make their own choices for analysis of the data.\n The code is written to be a stand-alone operation on data collected from a pulse neutron source that have been previously normalized to the wavelength dependence of the incident beam spectrum, background subtracted, etc. The constant Qz binning (this code) is the last step to perform in the analysis (reduction) workflow. This step yields the the reflectivities for the four neutron spin cross-sections.\n A future intention is to create a version of this code that will be one module of many in the data analysis workflow.\n", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "Place polarized neutron reflectivity data in bins of constant wavevector transfer", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfitzsimmons44/reflectometry-analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Plant_density_and_enhanced_plant_vigor_estimation_for_high-resolution_images_v1.json b/agency-indexes/DoE/Plant_density_and_enhanced_plant_vigor_estimation_for_high-resolution_images_v1.json new file mode 100644 index 00000000..8a4167ef --- /dev/null +++ b/agency-indexes/DoE/Plant_density_and_enhanced_plant_vigor_estimation_for_high-resolution_images_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-20" + }, + "description": "The package contains algorithms for the estimation of sprout/plant density and the corresponding enhanced plant vigor from remotely sensed (RS) images. These algorithms aim to improve the plant characterization and monitoring in the early season when the soil component is significant compared to the plant spatial coverage. In such a scenario, the identification of sprouts (or plants) and the estimation of plant vegetation indexes can be performed only using UAV-acquired images. Additionally, because of the extremely high resolution, gridding becomes necessary to improve visualization and provide more informative maps. However, to capture the real range of values of the VIs, it is important to avoid the inclusion of those pixels belonging to the soil component. The sprout/plant density estimation algorithm takes in input a classification map and uses the vegetation class to estimates the plant density within a user-defined grid using a floating window. Similarly, the enhanced plant vigor algorithm takes in input the vegetation index and the classification map. The enhanced vegetation index is computed for each pixel as the average value among those pixels that belong to the vegetation class within a floating window. The software is developed for the MATLAB environment.", + "homepageURL": "https://ipo.lbl.gov/plant-density-and-enhanced-plant-vigor-estimation-algorithms-for-high-resolution-images-2019-179", + "laborHours": 0.0, + "languages": [], + "name": "Plant density and enhanced plant vigor estimation for high-resolution images v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/plant-density-and-enhanced-plant-vigor-estimation-algorithms-for-high-resolution-images-2019-179", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/plant-density-and-enhanced-plant-vigor-estimation-algorithms-for-high-resolution-images-2019-179", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PlasMod0_v.1.0.json b/agency-indexes/DoE/PlasMod0_v.1.0.json new file mode 100644 index 00000000..6465f14c --- /dev/null +++ b/agency-indexes/DoE/PlasMod0_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-14", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-12609 O\nPlasMod0 is a 0-dimensional plasma modeling which approximates a plasma as a well-stirred reactor. The model uses two temperatures, one for electrons and one for ions and neutrals. This model was originally developed for laser produced plasma in single-particle aerosol mass spectrometers. As a result, there are some specialized capabilities that include spherical expansion into vacuum at a user-specified rate and photon reactions. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 486.4, + "languages": [ + "Python" + ], + "name": "PlasMod0 v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PlasMod0", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Platform_Of_Optimal_Experiment_Management.json b/agency-indexes/DoE/Platform_Of_Optimal_Experiment_Management.json new file mode 100644 index 00000000..579886c6 --- /dev/null +++ b/agency-indexes/DoE/Platform_Of_Optimal_Experiment_Management.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "The platform of optimal experiment management, POEM, powered with automated machine learning to accelerate the discovery of optimal solutions, and automatically guide the design of experiments to be evaluated. POEM currently supports 1) random model explorations for experiment design, 2) sparse grid model explorations with Gaussian Polynomial Chaos surrogate model to accelerate experiment design ,3) time-dependent model sensitivity and uncertainty analysis to identify the importance features for experiment design, 4) model calibrations via Bayesian inference to integrate experiments to improve model performance, and 5) Bayesian optimization for optimal experimental design. In addition, POEM aims to simplify the process of experimental design for users, enabling them to analyze the data with minimal human intervention, and improving the technological output from research activities.", + "laborHours": 2933.6, + "languages": [ + "Python" + ], + "name": "Platform Of Optimal Experiment Management", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/POEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Platform_for_Automated_Workflows_by_SSRL__paws_.json b/agency-indexes/DoE/Platform_for_Automated_Workflows_by_SSRL__paws_.json new file mode 100644 index 00000000..25d2723d --- /dev/null +++ b/agency-indexes/DoE/Platform_for_Automated_Workflows_by_SSRL__paws_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "paws stands for the Platform for Automated Workflows by SSRL. It was conceived to serve as a lean and modular workflow manager for image-like data. While there are many Python packages providing for a wide variety of processing tasks, we are often faced with a need to bring several packages together, and then to add some home-built scripts as well, to complete a data processing workflow. paws was designed to make this process easy, by providing interfaces to an ever-growing number of existing packages and providing easy ways for users to add their own operations. Occasionally, we have need of an operation that is not provided by a Python package that we know of. In these rare cases, we have developed original operations within PAWS, but such operations intend to live in a lower-level package as soon as they are mature.", + "laborHours": 1915.2, + "name": "Platform for Automated Workflows by SSRL (paws)", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/paws/blob/dev/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/paws", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Platform_for_Integrated_Land_use_And_Transportation_Experiments_and_Simulation__PILATES__v1.0.json b/agency-indexes/DoE/Platform_for_Integrated_Land_use_And_Transportation_Experiments_and_Simulation__PILATES__v1.0.json new file mode 100644 index 00000000..90d1adb8 --- /dev/null +++ b/agency-indexes/DoE/Platform_for_Integrated_Land_use_And_Transportation_Experiments_and_Simulation__PILATES__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-13", + "metadataLastUpdated": "2024-06-17" + }, + "description": "PILATES allows for flexibly and at-scale coupling of multiple models to allow for multi-scale and multi-resolution simulation of regional-scale transport networks. In particular, it couples the MATSim-derived transportation modeling framework for Behavior, Energy, Autonomy and Mobility (BEAM) with other models operating at different time scales. Rather than tightly coupling supply and demand models using shared agents and memory within the same software process, PILATES orchestrates different model runs in a containerized framework. This structure requires passing information from the demand models to BEAM in the format of a synthetic population and agent plans, and from BEAM to the demand models in terms or origin/destination tables (also known as \"skims\"). This allows it to take advantage of the behavioral sophistication of existing activity-based models as well as the reinforcement learning structure of MATSim replanning and adopted by BEAM, in a way that requires minimal changes to existing models. It also takes advantage of the computational performance of BEAM, which allows for simulations with millions of agents to complete in reasonable time as well as allowing for detailed mechanistic simulation of the operation of on-demand modes.", + "laborHours": 4894.4, + "languages": [], + "name": "Platform for Integrated Land use And Transportation Experiments and Simulation (PILATES) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-UCB-STI/PILATES", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Plato_Engine_v._1.0.json b/agency-indexes/DoE/Plato_Engine_v._1.0.json new file mode 100644 index 00000000..3ef6e9b4 --- /dev/null +++ b/agency-indexes/DoE/Plato_Engine_v._1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Provides testbed for optimization-based design.", + "laborHours": 129580.0, + "languages": [ + "C++", + "CMake" + ], + "name": "Plato Engine v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/platoengine?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/platoengine", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Plot_XML_files.json b/agency-indexes/DoE/Plot_XML_files.json new file mode 100644 index 00000000..35894542 --- /dev/null +++ b/agency-indexes/DoE/Plot_XML_files.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-11-15", + "metadataLastUpdated": "2022-11-15" + }, + "description": "Plots XML files; plots specified singular XML file or all XML files within a specified folder.", + "laborHours": 0.0, + "languages": [], + "name": "Plot XML files", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CLDruzgalski/AM_fileConverters", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "000" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pmix.json b/agency-indexes/DoE/Pmix.json new file mode 100644 index 00000000..eeb4741c --- /dev/null +++ b/agency-indexes/DoE/Pmix.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "The Process Management Interface (PMI) has been used for quite some time as a means of exchanging \nPMI Exascale (PMIx) provides an extended version of the PMI standard specifically designed to support clusters up to and including exascale sizes. The overall objective of the project is not to branch the existing pseudo-standard definitions - in fact, PMIx fully supports both of the existing PMI-1 and PMI-2 APIs - but rather to (a) augment and extend those APIs to eliminate some current restrictions that impact scalability, and (b) provide a reference implementation of the PMI-server that demonstrates the desired level of scalability.", + "laborHours": 120718.4, + "languages": [], + "name": "Pmix", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/openpmix/openpmix/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openpmix/openpmix", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PnMPI.json b/agency-indexes/DoE/PnMPI.json new file mode 100644 index 00000000..8e7eddef --- /dev/null +++ b/agency-indexes/DoE/PnMPI.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PnMPI is a tool infrastructure for parallel programs implemented using the message passing interface (MPI). It enables users to dynamically assemble multiple tools, both existing and newly developed ones, into a single tool chain and to execute them concurrently. This provides new options for scalable tools designs including (but not concurrently. This provides new options for scalable tool designs including (but not limited to) the transparent virtualization of MPI environments of an application. In addition, PnMPI allows tools to export support routines to other tools. This promotes a separation of tasks between tools which leads to enhanced tool modularity. PnMPI has been implemented for a variety of platforms including Linux and AIX clusters, and a static version of PnMPI is available on Blue Gene/L.", + "laborHours": 8451.2, + "name": "PnMPI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/pnmpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PoPsCpp.json b/agency-indexes/DoE/PoPsCpp.json new file mode 100644 index 00000000..8f9c53fc --- /dev/null +++ b/agency-indexes/DoE/PoPsCpp.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "A new format for storing particle information (i.e., mass, spin, parity) has been developed. \n\nThe format is a subset of the Generalized Nuclear Data Structure (GNDS) developed for storing nuclear reaction data. \n\nA C++ library dubbed \"Property of Particles\" (PoPs) has been developed to read particle data in the GNDS\nformat. \n\nThe PoPs library provides functions for reading in a GNDS particle database as well as for accessing a particle and its properties.", + "laborHours": 60359.2, + "languages": [ + "C++" + ], + "name": "PoPsCpp", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Poblano_v_1.0.json b/agency-indexes/DoE/Poblano_v_1.0.json new file mode 100644 index 00000000..8263d919 --- /dev/null +++ b/agency-indexes/DoE/Poblano_v_1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "Poblano is a Matlab toolbox of large-scale algorithms for nonlinear optimization. The algorithms in Poblano require only first-order derivative information (e.g., gradients for scalar-valued objective functions), and therefore can scale to very large problems [6].Poblano is a set of general purpose methods for solving unconstrained nonlinear optimization methods. It has been applied to standard test problems covering a range of application areas. The driving application for Poblano development has been tensor decompositions in data analysis applications (bibliometric analysis, social network analysis, chemometrics, etc.) [1].", + "laborHours": 1474.4, + "languages": [ + "MATLAB", + "M" + ], + "name": "Poblano v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/poblano_toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Podman-hpc_v1.0.json b/agency-indexes/DoE/Podman-hpc_v1.0.json new file mode 100644 index 00000000..de9f628a --- /dev/null +++ b/agency-indexes/DoE/Podman-hpc_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "We have developed some scripts and tools that compliment an existing open-source product (Podman, https://podman.io/). This enables podman to function as a high-performance container solution. This capability is similar to Shifter and Singularity (both developed at LBNL). The advantage of leveraging Podman is it has greater support in the broader community outside of HPC and has capabilities missing from many of the HPC-only solutions.\n\nThe specific enhancements we wish to share our how to enable Podman to scale to very large HPC jobs and our integrations we have done to utilize high-performance interconnects and GPUs.", + "laborHours": 1140.0, + "languages": [], + "name": "Podman-hpc v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/podman-hpc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Point_Source_Likelihood_Framework__psl__v1.0.json b/agency-indexes/DoE/Point_Source_Likelihood_Framework__psl__v1.0.json new file mode 100644 index 00000000..627d91cc --- /dev/null +++ b/agency-indexes/DoE/Point_Source_Likelihood_Framework__psl__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2021-05-27" + }, + "description": "PSL is a software framework for localizing radiation point sources in a 3D environment using a freely moving radiation detector system. The framework assumes a single point source of radiation is in the environment and uses known detector positions and orientations along with their radiation measurements to find the most likely location of the point source. This approach to the problem enables analyses that improve upon the capability of a standard Maximum Likelihood Expectation Maximization (MLEM) approach, such as setting a source detection threshold, finding a likelihood interval for the position of the source, finding a likelihood interval for the activity (intensity) of the source, determining whether more than one point source may be present, and generating a map of Minimum Detectable Activity (MDA) for a given source type. Applications include radiological and nuclear security, consequence management, decontamination and decommissioning of nuclear facilities, and radiological emergency response.", + "homepageURL": "https://gitlab.com/lbl-anp/ipo/psl", + "laborHours": 0.0, + "languages": [], + "name": "Point Source Likelihood Framework (psl) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://gitlab.com/lbl-anp/ipo/psl", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://gitlab.com/lbl-anp/ipo/psl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PoliMOR.json b/agency-indexes/DoE/PoliMOR.json new file mode 100644 index 00000000..e26a2cd5 --- /dev/null +++ b/agency-indexes/DoE/PoliMOR.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "georgea@ornl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-18" + }, + "description": "PoliMOR is a scalable, automated, and customizable policy engine framework for multi-tiered parallel file systems. It is composed of single-purpose agents that handle tasks such as gathering file metadata, making policy decisions, and then executing actions based on those policies. These agents are designed to communicate using distributed message queues, allowing the number of individual agents to be scaled up as needed. PoliMOR automates the data management tasks by precluding the need for admin intervention. The agents in PoliMOR can be customized to integrate any utilities/tools that perform tasks like metadata scanning and data placement management.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python" + ], + "name": "PoliMOR", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/olcf/polimor/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/polimor", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Polisher.json b/agency-indexes/DoE/Polisher.json new file mode 100644 index 00000000..6168e0b1 --- /dev/null +++ b/agency-indexes/DoE/Polisher.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Polisher is a software package designed to facilitate the error correction of an assembled genome using Illumia read data. The software addresses substandard regions by automatically correcting consensus errors and/or suggesting primer walking reactions to improve the quality of the bases.", + "laborHours": 0.0, + "languages": [ + "Perl" + ], + "name": "Polisher", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/polisher", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/PolyID\342\204\242__Polymer_Inverse_Design__[SWR-21-98].json" "b/agency-indexes/DoE/PolyID\342\204\242__Polymer_Inverse_Design__[SWR-21-98].json" new file mode 100644 index 00000000..c78f03ec --- /dev/null +++ "b/agency-indexes/DoE/PolyID\342\204\242__Polymer_Inverse_Design__[SWR-21-98].json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-08-31", + "metadataLastUpdated": "2023-04-24" + }, + "description": "PolyID\u2122 provides a framework for building, training, and predicting polymer properties using graph neural networks. The codes leverages Neural Fingerprint (nfp) (See DOE Code ID 22185) for building tensorflow-based message-passing neural networks, and Monomers to Polymers (m2p) (See DOE Code ID 44795) for building polymer structures. To understand and use the pipeline, the following examples have been provided: Building polymer structures: examples/example_generate_polymer_structures.ipynb Checking domain of validity: examples/example_determine_domain-of-validity.ipynb Training a graph neural network: examples/example_generate_and_train_models.ipynb Predicting with the trained model: examples/example_predict_with_trained_models.ipynb", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PolyID\u2122 (Polymer Inverse Design) [SWR-21-98]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/polyID", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PolyODENet.json b/agency-indexes/DoE/PolyODENet.json new file mode 100644 index 00000000..4e1d936e --- /dev/null +++ b/agency-indexes/DoE/PolyODENet.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "qinwu@bnl.gov" + }, + "date": { + "created": "2022-12-23", + "metadataLastUpdated": "2022-12-23" + }, + "description": "Kinetics of a reaction network that follows mass-action rate laws can be described with a system of ordinary differential equations (ODEs) with polynomial right-hand side. However, it is challenging to derive such kinetic differential equations from transient kinetic data without knowing the reaction network, especially when the data are incomplete due to experimental limitations. We introduce a program, PolyODENet, toward this goal. Based on the machine-learning method Neural ODE, PolyODENet defines a generative model and predicts concentrations at arbitrary time. As such, it is possible to include unmeasurable intermediate species in the kinetic equations. Importantly, we have implemented various measures to apply physical constraints and chemical knowledge in the training to regularize the solution space.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PolyODENet", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ICKMod/PolyODENet/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ICKMod/PolyODENet", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Polycube_Edge_Unfolder.json b/agency-indexes/DoE/Polycube_Edge_Unfolder.json new file mode 100644 index 00000000..08cffb5c --- /dev/null +++ b/agency-indexes/DoE/Polycube_Edge_Unfolder.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-13", + "metadataLastUpdated": "2019-05-13" + }, + "description": "Polycubes are arrangements of unit cubes connected by their faces. This code generates all possible polycubes with a specified number of unit cubes that are unique under 3D rotation (the family of polycubes of size N) and also finds a globally and locally valid edge unfolding for either a single polycube or a specified family of polycubes.", + "laborHours": 608.0, + "languages": [], + "name": "Polycube Edge Unfolder", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/polycube", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Polyglot_C_Library.json b/agency-indexes/DoE/Polyglot_C_Library.json new file mode 100644 index 00000000..1a30d99e --- /dev/null +++ b/agency-indexes/DoE/Polyglot_C_Library.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "The C library component of Polyglot.\nPolyglot utilizes a combination of custom and open source tools and libraries to provide developers with a consistent environment for building tools, etc. for a wide variety of targets with minimal changes to the code being built. It supports a variety of architectures and operating systems/firmware in as target-agnostic way as possible. This allows for developers to minimize the amount of time/effort required to port tools-in particular, forensic tools-to a wide variety of targets.\nThe project is comprised of two main components: a frontend toolchain that understands how to utilize other tools in order to build code for a specific target, and a minimalistic C library specific to Polyglot. These collectively provide the method to build code for a specific target, and the capability for code to interact with the underlying operating system when run on the target. Both components are written in a way to minimize the amount of target-specific knowledge required to both develop and utilize the project.", + "laborHours": 31129.6, + "languages": [ + "C" + ], + "name": "Polyglot C Library", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/polyglot-libc", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Polyglot_Framework.json b/agency-indexes/DoE/Polyglot_Framework.json new file mode 100644 index 00000000..fda07fe6 --- /dev/null +++ b/agency-indexes/DoE/Polyglot_Framework.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "Polyglot utilizes a combination of custom and open source tools and libraries to provide developers with a consistent environment for building tools, etc. for a wide variety of targets with minimal changes to the code being built. It supports a variety of architectures and operating systems/firmware in as target-agnostic way as possible. This allows for developers to minimize the amount of time/effort required to port tools\u2014in particular, forensic tools\u2014to a wide variety of targets.\nThe project is comprised of two main components: a frontend toolchain that understands how to utilize other tools in order to build code for a specific target, and a minimalistic C library specific to Polyglot. These collectively provide the method to build code for a specific target, and the capability for code to interact with the underlying operating system when run on the target. Both components are written in a way to minimize the amount of target-specific knowledge required to both develop and utilize the project.", + "laborHours": 4347.2, + "languages": [ + "C", + "C++", + "Python" + ], + "name": "Polyglot Framework", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/polyglot", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Polymer_Modeling_Library.json b/agency-indexes/DoE/Polymer_Modeling_Library.json new file mode 100644 index 00000000..3b5a7233 --- /dev/null +++ b/agency-indexes/DoE/Polymer_Modeling_Library.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-14", + "metadataLastUpdated": "2022-10-14" + }, + "description": "SAND2022-12598 O\nThe Polymer Modeling Library is a software package for modeling polymer chains, networks, and materials by applying existing theories and methods. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Rust", + "Python" + ], + "name": "Polymer Modeling Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Polymers", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Polypole_Program_For_The_Calculation_Of_Intra-granular_Fission_Gas_Release.json b/agency-indexes/DoE/Polypole_Program_For_The_Calculation_Of_Intra-granular_Fission_Gas_Release.json new file mode 100644 index 00000000..4d607e2d --- /dev/null +++ b/agency-indexes/DoE/Polypole_Program_For_The_Calculation_Of_Intra-granular_Fission_Gas_Release.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "PolyPole is a numerical algorithm for the calculation of intra-granular fission gas release. In particular, the algorithm solves the gas diffusion problem in a fuel grain in time-varying conditions. The program has been extensively tested. PolyPole combines a high accuracy with a high computational efficiency and is ideally suited for application in fuel performance codes.", + "laborHours": 0.0, + "languages": [], + "name": "Polypole Program For The Calculation Of Intra-granular Fission Gas Release", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/PolyPole", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Polytope.json b/agency-indexes/DoE/Polytope.json new file mode 100644 index 00000000..18e74339 --- /dev/null +++ b/agency-indexes/DoE/Polytope.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Polytope is a library that wraps several algorithms for generating the Voronoi diagram in both serial and distributed parallel.", + "homepageURL": "https://bitbucket.org/jjphatt/polytope", + "laborHours": 0.0, + "name": "Polytope", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/jjphatt/polytope/src/ef2ecd61b60b31a4b7ba95e88f893f2fd7382a80/LICENSE?at=default&fileviewer=file-view-default", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/jjphatt/polytope", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pond.js.json b/agency-indexes/DoE/Pond.js.json new file mode 100644 index 00000000..3fb57a0c --- /dev/null +++ b/agency-indexes/DoE/Pond.js.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "Pond.js is a library built on top of immutable.js and Typescript to provide time-based data structures, serialization and processing. For data structures it unifies the use of times, time ranges, events, collections and time series. For processing it provides a chained pipeline interface to aggregate, collect and process batches or streams of events. ", + "laborHours": 53169.6, + "languages": [], + "name": "Pond.js", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/pond/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/pond", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Population_Variation_Plug-In.json b/agency-indexes/DoE/Population_Variation_Plug-In.json new file mode 100644 index 00000000..2bf61af6 --- /dev/null +++ b/agency-indexes/DoE/Population_Variation_Plug-In.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Population Variation plug-in for the Skyline software program that can assist researchers in determining whether their target peptides have known mutations in the general human population.", + "laborHours": 5304.8, + "languages": [], + "name": "Population Variation Plug-In", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/PopulationVariationPlugin", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pore2Chip.json b/agency-indexes/DoE/Pore2Chip.json new file mode 100644 index 00000000..8ef09774 --- /dev/null +++ b/agency-indexes/DoE/Pore2Chip.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-02", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Pore2Chip is a Python module designed to streamline the process of analyzing X-ray computed tomography (XCT) images\nof soil and creating 2D micromodel designs based on that analysis.", + "laborHours": 11962.4, + "languages": [], + "name": "Pore2Chip", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-Computing/Pore2Chip", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Portable_Application_Code_Toolkit.json b/agency-indexes/DoE/Portable_Application_Code_Toolkit.json new file mode 100644 index 00000000..511a42d2 --- /dev/null +++ b/agency-indexes/DoE/Portable_Application_Code_Toolkit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "PACT is a set of tools to help software developers create applications that will run on any platform and data that can be written/read on any platform.", + "homepageURL": "https://code.google.com/p/pactnew", + "laborHours": 0.0, + "languages": [], + "name": "Portable Application Code Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.google.com/p/pactnew", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Portable_Approach_for_Novel_Arrangements_using_a_Cross_Entropy_Algorithm__PANACEA_.json b/agency-indexes/DoE/Portable_Approach_for_Novel_Arrangements_using_a_Cross_Entropy_Algorithm__PANACEA_.json new file mode 100644 index 00000000..9f817d98 --- /dev/null +++ b/agency-indexes/DoE/Portable_Approach_for_Novel_Arrangements_using_a_Cross_Entropy_Algorithm__PANACEA_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "PANACEA provides a means for generating unique configurations. The primary motivation for its development stems from the need to generate unique configurations for the purpose of training machine learned interatomic potentials. PANCEA is a C++ library with python and linux scripts. The C++ library is the engine which provides can be installed and used to measure the disorder/order of a system via the information entropy. The python and linux scripts provide useful helper functionality such as visualization of files that can be output from the library.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Portable Approach for Novel Arrangements using a Cross Entropy Algorithm (PANACEA)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Portage,_Version_1.0.json b/agency-indexes/DoE/Portage,_Version_1.0.json new file mode 100644 index 00000000..644ab2c6 --- /dev/null +++ b/agency-indexes/DoE/Portage,_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Portage is a software library system for physics remapping (mapping physics variables from one computational mesh to another) either within a single simulation code or between two disparate simulation codes. Portage is designed to utilize advanced-architecture compute platforms and to be easily extensible by third parties.", + "laborHours": 73157.6, + "name": "Portage, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/laristra/portage/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laristra/portage", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Portals_Reference_Implementation_v._1.0.json b/agency-indexes/DoE/Portals_Reference_Implementation_v._1.0.json new file mode 100644 index 00000000..7393476b --- /dev/null +++ b/agency-indexes/DoE/Portals_Reference_Implementation_v._1.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The Portals reference implementation is based on the Portals 4.X API, published by Sandia National Laboratories as a freely available public document. It is designed to be an implementation of the Portals Networking Application Programming Interface and is used by several other upper layer protocols like SHMEM, GASNet and MPI. It is implemented over existing networks, specifically Ethernet and InfiniBand networks. This implementation provides Portals networks functionality and serves as a software emulation of Portals compliant networking hardware. It can be used to develop software using the Portals API prior to the debut of Portals networking hardware, such as Bull\u2019s BXI interconnect, as well as a substitute for portals hardware on development platforms that do not have Portals compliant hardware. The reference implementation provides new capabilities beyond that of a typical network, namely the ability to have messages matched in hardware in a way compatible with upper layer software such as MPI or SHMEM. It also offers methods of offloading network operations via triggered operations, which can be used to create offloaded collective operations. Specific details on the Portals API can be found at http://portals4.org.", + "laborHours": 65496.8, + "languages": [ + "Makefile", + "C", + "M4" + ], + "name": "Portals Reference Implementation v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/portals4?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/portals4", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Post_Irradiation_Examination_Dislocation_Defect_Detection_Software.json b/agency-indexes/DoE/Post_Irradiation_Examination_Dislocation_Defect_Detection_Software.json new file mode 100644 index 00000000..44d51591 --- /dev/null +++ b/agency-indexes/DoE/Post_Irradiation_Examination_Dislocation_Defect_Detection_Software.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-10-10", + "metadataLastUpdated": "2024-10-10" + }, + "description": "This software provides dislocation-type defect identification and segmentation using a standard open source computer vision model, YOLOv8, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of expert annotated micrographs for training. This model demonstrates the ability to segment both dislocation lines and loops concurrently in micrographs with high pixel noise levels and on multiple alloys. It includes multiple layers of frozen layers used for transfer learning from multidisciplinary data and is extensible to alloys that are not included in the training dataset.", + "laborHours": 136.8, + "languages": [ + "Python" + ], + "name": "Post Irradiation Examination Dislocation Defect Detection Software", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/PANDA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Potassium_Fluid_Properties.json b/agency-indexes/DoE/Potassium_Fluid_Properties.json new file mode 100644 index 00000000..e8269472 --- /dev/null +++ b/agency-indexes/DoE/Potassium_Fluid_Properties.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-08-30" + }, + "description": "This software is used to compute numerous properties for the liquid and vapor phases of potassium.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Potassium Fluid Properties", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/potassium", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PowerGridworld:_A_Framework_for_Multi-Agent_Reinforcement_Learning_in_Power_Systems_[SWR-22-07].json b/agency-indexes/DoE/PowerGridworld:_A_Framework_for_Multi-Agent_Reinforcement_Learning_in_Power_Systems_[SWR-22-07].json new file mode 100644 index 00000000..5f14820b --- /dev/null +++ b/agency-indexes/DoE/PowerGridworld:_A_Framework_for_Multi-Agent_Reinforcement_Learning_in_Power_Systems_[SWR-22-07].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-11-10", + "metadataLastUpdated": "2024-03-11" + }, + "description": "NREL's PowerGridworld provides a modular simulation environment for training heterogenous, grid-aware, multi-agent reinforcement learning (RL) policies at scale. The package enables the user to create component gym environments that can be composed into more complex agents. For example, a grid interactive building environment can be created by composing together component environments each encapsulating the building, PV, and battery physics. These multi-component environments can then be combined into multi-agent simulation where each agent's power consumption/injection becomes an input for solving the optimal power flow on a distribution feeder modeled in OpenDSS. Information from OpenDSS, such as bus voltages and line flows, can be included in the agents' observation spaces to enable grid-aware rewards. The default API for the PowerGridworld simulator conforms to RLLib's MultiAgent API and thus enables distributed training using HPC and cloud resources.", + "laborHours": 0.0, + "languages": [], + "name": "PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems [SWR-22-07]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PowerGridworld", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PowerSlurm.json b/agency-indexes/DoE/PowerSlurm.json new file mode 100644 index 00000000..9255b331 --- /dev/null +++ b/agency-indexes/DoE/PowerSlurm.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "This is the Slurm Workload Manager. Slurm is an open-source cluster resource management and job scheduling system that strives to be simple, scalable, portable, fault-tolerant, and interconnect agnostic. Slurm currently has been tested only under Linux.\n\nAs a cluster resource manager, Slurm provides three key functions. First, it allocates exclusive and/or non-exclusive access to resources (compute nodes) to users for some duration of time so they can perform work. Second, it provides a framework for starting, executing, and monitoring work (normally a parallel job) on the set of allocated nodes. Finally, it arbitrates conflicting requests for resources by managing a queue of pending work.", + "laborHours": 406752.0, + "languages": [], + "name": "PowerSlurm", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/tpatki/power-slurm/blob/master/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tpatki/power-slurm", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PowerSystems.jl_and_PowerSimulations.jl_[SWR-18-23].json b/agency-indexes/DoE/PowerSystems.jl_and_PowerSimulations.jl_[SWR-18-23].json new file mode 100644 index 00000000..2e162800 --- /dev/null +++ b/agency-indexes/DoE/PowerSystems.jl_and_PowerSimulations.jl_[SWR-18-23].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2024-03-11" + }, + "description": "Data structures in Julia to enable power systems analysis. Also, PowerSimulations.jl is a Julia package for power system modeling and simulation found at https://github.com/NREL/PowerSimulations.jl. The objectives of the package are: Provide a flexible modeling framework that can accommodate problems of different complexity and at different time-scales. Streamline the construction of large scale optimization problems to avoid repetition of work when adding/modifying model details. Exploit Julia's capabilities to improve computational performance of large scale power system simulations. The flexible modeling framework is enabled through a modular set of capabilities that enable scalable power system analysis and exploration of new analysis methods. The modularity of PowerSimulations results from the structure of the simulations enabled by the package: Simulations define a set of problems that can be solved using numerical techniques. Problems are generated by expressing model formulations against system data For example, an annual production cost modeling simulation can be created by formulating a unit commitment model against system data to assemble a set of 365 daily time-coupled scheduling problems.", + "laborHours": 8466.4, + "languages": [ + "Julia" + ], + "name": "PowerSystems.jl and PowerSimulations.jl [SWR-18-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PowerSystems.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.15.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Power_API_Prototype.json b/agency-indexes/DoE/Power_API_Prototype.json new file mode 100644 index 00000000..d55914b9 --- /dev/null +++ b/agency-indexes/DoE/Power_API_Prototype.json @@ -0,0 +1,40 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software serves two purposes. The first purpose of the software is to prototype the Sandia High Performance Computing Power Application Programming Interface Specification effort. The specification can be found at http://powerapi.sandia.gov . Prototypes of the specification were developed in parallel with the development of the specification. Release of the prototype will be instructive to anyone who intends to implement the specification. More specifically, our vendor collaborators will benefit from the availability of the prototype. The second is in direct support of the PowerInsight power measurement device, which was co-developed with Penguin Computing. The software provides a cluster wide measurement capability enabled by the PowerInsight device. The software can be used by anyone who purchases a PowerInsight device. The software will allow the user to easily collect power and energy information of a node that is instrumented with PowerInsight. The software can also be used as an example prototype implementation of the High Performance Computing Power Application Programming Interface Specification.", + "laborHours": 40462.4, + "languages": [ + "C++", + "Shell", + "C", + "SWIG", + "Makefile", + "M4", + "Roff" + ], + "name": "Power API Prototype", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/power-api", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Power_Distribution_Designing_For_Resilience_Application.json b/agency-indexes/DoE/Power_Distribution_Designing_For_Resilience_Application.json new file mode 100644 index 00000000..f0f37aa2 --- /dev/null +++ b/agency-indexes/DoE/Power_Distribution_Designing_For_Resilience_Application.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The number of power outages have been on the rise as extreme weather patterns have been occurring more frequently due to climate change. These outages have an economic impact in the billions of dollar. The modernization of the power grid and adoption of high penetration of distributed generation such as wind and solar have the potential to reduce the number and length of time of these power outages. However, planners and operators need a way to value the resilience the distributed assets provide to the grid. PowDDeR is a tool that allows them to evaluate the resilience each asset provides as well as how they provide resilience over the connected network.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Power Distribution Designing For Resilience Application", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/PowDDeR-Python", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Power_Distribution_Designing_For_Resilience_Application__powdder_.json b/agency-indexes/DoE/Power_Distribution_Designing_For_Resilience_Application__powdder_.json new file mode 100644 index 00000000..f9434981 --- /dev/null +++ b/agency-indexes/DoE/Power_Distribution_Designing_For_Resilience_Application__powdder_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-06-26", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Power Distribution Designing for Resilience Application (PowDDeR) is a software application to succinctly capture the capabilities of a power system to respond to disturbances, including natural or human (malicious or errors) caused disturbances. The software provides a measure of resilience for power systems.", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Power Distribution Designing For Resilience Application (powdder)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/PowDDeR", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Power_Plant_Model_Validation_Tool.json b/agency-indexes/DoE/Power_Plant_Model_Validation_Tool.json new file mode 100644 index 00000000..f621dc69 --- /dev/null +++ b/agency-indexes/DoE/Power_Plant_Model_Validation_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The PPMV is used to validate generator model using disturbance recordings. The PPMV tool contains a collection of power plant models and model validation studies, as well as disturbance recordings from a number of historic grid events. The user can import data from a new disturbance into the database, which converts PMU and SCADA data into GE PSLF format, and then run the tool to validate (or invalidate) the model for a specific power plant against its actual performance. The PNNL PPMV tool enables the automation of the process of power plant model validation using disturbance recordings. The tool uses PMU and SCADA measurements as input information. The tool automatically adjusts all required EPCL scripts and interacts with GE PSLF in the batch mode. The main tool features includes: The tool interacts with GE PSLF; The tool uses GE PSLF Play-In Function for generator model validation; Database of projects (model validation studies); Database of the historic events; Database of the power plant; The tool has advanced visualization capabilities; and the tool automatically generates reports.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "EPCL" + ], + "name": "Power Plant Model Validation Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Practical_Parallel_Hypergraph_Algorithms.json b/agency-indexes/DoE/Practical_Parallel_Hypergraph_Algorithms.json new file mode 100644 index 00000000..9a011875 --- /dev/null +++ b/agency-indexes/DoE/Practical_Parallel_Hypergraph_Algorithms.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nJulian Shun.\nPractical Parallel Hypergraph Algorithms.\nProceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), pp. 232-249, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "Practical Parallel Hypergraph Algorithms", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jshun/ligra", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pragmatic-infiniband-utilities.json b/agency-indexes/DoE/Pragmatic-infiniband-utilities.json new file mode 100644 index 00000000..d582354b --- /dev/null +++ b/agency-indexes/DoE/Pragmatic-infiniband-utilities.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The package provides additional IB programs and scripts which are usefull in some way or another to the management of IB clusters.", + "laborHours": 18635.2, + "name": "Pragmatic-infiniband-utilities", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/weiny2/pragmatic-infiniband-utilities", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Predicting_2CS_protein_pairs_with_Deep_Learning.json b/agency-indexes/DoE/Predicting_2CS_protein_pairs_with_Deep_Learning.json new file mode 100644 index 00000000..570bdd86 --- /dev/null +++ b/agency-indexes/DoE/Predicting_2CS_protein_pairs_with_Deep_Learning.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-13", + "metadataLastUpdated": "2020-12-28" + }, + "description": "Neural network was trained on the amino acid sequences of known two-component systems (2CS) pairs. The recommender algorithm uses learned model to select the most likely 2CS pair from an arbitrary set of protein pairs whose amino acid sequences are known.", + "laborHours": 1717.6, + "languages": [], + "name": "Predicting 2CS protein pairs with Deep Learning", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.code.sf.net/p/kinaseorakle/code", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Predicting_Coculture_Substrate_Depletion__PCSD__v1.json b/agency-indexes/DoE/Predicting_Coculture_Substrate_Depletion__PCSD__v1.json new file mode 100644 index 00000000..4a961e40 --- /dev/null +++ b/agency-indexes/DoE/Predicting_Coculture_Substrate_Depletion__PCSD__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-08", + "metadataLastUpdated": "2019-04-29" + }, + "description": "(based on Erbilgin et al., BMC Bioinformatics, 2017, 18:57). Mixed cultures of microbial species are increasingly used to carry out a specific task in lieu of engineering a single microbe to do the same task. However, knowing how different species' metabolisms will integrate to reach a desired outcome is a difficult problem that has been studied in great detail--but only using steady-state models. Mixed cultures used for biotechnology processes, as well as microbial communities that exist in nature and crop agriculture, are metabolically dynamic systems. Studying the temporal substrate utilization by individuals is individuals in mixed cultures is an important first step in developing approaches to better model these biochemical processes and microbial communities found in nature. \n\nThe 2017-004 software is comprised of four custom iPython notebooks that were used for all computational tasks in the experimental work described in \"Dynamic substrate preferences predict metabolic properties of a simple microbial consortium\" (Erbilgin et al., BMC Bioinformatics, 2017). The results indicate that a significant portion of a model community's overall metabolism can be predicted based on the metabolism of the individuals. The results further suggest that, when the mixed culture's substrate depletion significantly deviates from such a prediction, this may highlight potential metabolic pathways affected by species-species microbial interactions, leading to hypotheses about how a particular microbial community's structure and function may be modulated to perform a particular biotechnological goal.", + "laborHours": 501.6, + "languages": [], + "name": "Predicting Coculture Substrate Depletion (PCSD) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biorack/bmc_bioinf_2016_erbilgin", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Prescient.json b/agency-indexes/DoE/Prescient.json new file mode 100644 index 00000000..f8bd8d04 --- /dev/null +++ b/agency-indexes/DoE/Prescient.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-01" + }, + "description": "Prescient is a software package for simulating electricity grid (power systems) operations, under both nominal and extreme event conditions. Core functionality includes discrete event simulation, commitment and dispatch optimization, probabilistic scenario construction, and reporting/visualization. SAND2020-0169 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 18620.0, + "languages": [], + "name": "Prescient", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/grid-parity-exchange/Prescient", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pressio.json b/agency-indexes/DoE/Pressio.json new file mode 100644 index 00000000..a43f7d60 --- /dev/null +++ b/agency-indexes/DoE/Pressio.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Reduced-order Models (ROMs). ROMs are \"compressed\" approximations of high-fidelity computational models. Implementing ROM methods in production codes is typically intrusive, i.e. the native codes must be adapted and modified, with individual ROM methods reimplemented in every application code. This clearly constitutes an obstacle to users who want to use ROMs. To address this, we have developed Pressio, which is a C++ header-only ROM library that can be used by an application code in a non-intrusive fashion. The main objectives behind the design of Pressio are: (a) support for general computational models (data structures, PDE types); (b) heterogeneous hardware (CPU, GPU); (c) performance; and (d) extensibility. Using metaprogramming techniques, Pressio detects and leverages the application?s native linear algebra data structures (e.g. vector and matrix) to run the ROM methods. The application only needs to expose the velocity vector and Jacobian matrix via an adapter class. Pressio checks at compile time that the target application meets the correct API. The library is structured in several modular packages including (a) non-linear least-square solvers (e.g. Gauss-Newton with and without line-search); (b) singular value decomposition (for the computation of the ROM generalized coordinates) and (c) algebraic hyper-reduction.SAND2019-5878 M", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 49354.4, + "languages": [ + "C++" + ], + "name": "Pressio", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pressio_v.1.0.json b/agency-indexes/DoE/Pressio_v.1.0.json new file mode 100644 index 00000000..4d56070c --- /dev/null +++ b/agency-indexes/DoE/Pressio_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-17", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Reduced-order Models (ROMs). ROMs are \"compressed\" approximations of high-fidelity computational models. Implementing ROM methods in production codes is typically intrusive, i.e. the native codes must be adapted and modified, with individual ROM methods reimplemented in every application code. This clearly constitutes an obstacle to users who want to use ROMs. To address this, we have developed Pressio, which is a C++ header-only ROM library that can be used by an application code in a non-intrusive fashion. The main objectives behind the design of Pressio are: (a) support for general computational models (data structures, PDE types); (b) heterogeneous hardware (CPU, GPU); (c) performance; and (d) extensibility. Using metaprogramming techniques, Pressio detects and leverages the application?s native linear algebra data structures (e.g. vector and matrix) to run the ROM methods. The application only needs to expose the velocity vector and Jacobian matrix via an adapter class. Pressio checks at compile time that the target application meets the correct API. The library is structured in several modular packages including (a) non-linear least-square solvers (e.g. Gauss-Newton with and without line-search); (b) singular value decomposition (for the computation of the ROM generalized coordinates) and (c) algebraic hyper-reduction.SAND2019-5878 M", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Pressio v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pressio", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pretty_Linter_GrumPhP.json b/agency-indexes/DoE/Pretty_Linter_GrumPhP.json new file mode 100644 index 00000000..e063672e --- /dev/null +++ b/agency-indexes/DoE/Pretty_Linter_GrumPhP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software takes JSON and YAML files, and after running them through a linter, sorts the keys of objects alphabetically. This helps prevent the following problems when checking these data/config files into repositories:\nProblems where the entire file looks like it was removed and added due to\nIndentation changes Key sorting differences\nMerging issues when 2 or more people add data to the same or similar locations", + "laborHours": 0.0, + "languages": [], + "name": "Pretty Linter GrumPhP", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pretty_lint", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PriMux.json b/agency-indexes/DoE/PriMux.json new file mode 100644 index 00000000..6dc46867 --- /dev/null +++ b/agency-indexes/DoE/PriMux.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PriMux is used to compute sets of compatible Polymerase Chain Reaction (PCR)signatures that can be used for detecting the presence of biological species in a small sample of material. Before use, the computed signatures must be empirically tested in a wet lab.", + "homepageURL": "https://sourceforge.net/projects/primux", + "laborHours": 0.0, + "name": "PriMux", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/primux", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Price_Based_Local_Power_Distribution_Management_System__Local_Power_Distribution_Manager__v1.0.json b/agency-indexes/DoE/Price_Based_Local_Power_Distribution_Management_System__Local_Power_Distribution_Manager__v1.0.json new file mode 100644 index 00000000..01ae09c2 --- /dev/null +++ b/agency-indexes/DoE/Price_Based_Local_Power_Distribution_Management_System__Local_Power_Distribution_Manager__v1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "A trans-active energy micro-grid controller is implemented in the VOLTTRON distributed control platform. The system uses the price of electricity as the mechanism for conducting transactions that are used to manage energy use and to balance supply and demand. In order to allow testing and analysis of the control system, the implementation is designed to run completely as a software simulation, while allowing the inclusion of selected hardware that physically manages power. Equipment to be integrated with the micro-grid controller must have an IP (Internet Protocol)-based network connection and a software \"driver\" must exist to translate data communications between the device and the controller.", + "laborHours": 0.0, + "languages": [ + "NA" + ], + "name": "Price Based Local Power Distribution Management System (Local Power Distribution Manager) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LBNL-ETA/LPDM/blob/CBERD/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/LPDM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Privacy_Algorithms_for_Streaming_Data.json b/agency-indexes/DoE/Privacy_Algorithms_for_Streaming_Data.json new file mode 100644 index 00000000..ddbba85e --- /dev/null +++ b/agency-indexes/DoE/Privacy_Algorithms_for_Streaming_Data.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "kotevskao@ornl.gov" + }, + "date": { + "created": "2022-02-17", + "metadataLastUpdated": "2023-11-30" + }, + "description": "This repository encompasses local differential privacy algorithms designed for streaming applications. Each algorithm is tailored to safeguard sensitive data received in discrete chunks. The evaluation criteria include absolute relative error and privacy spending variables. The techniques are categorized based on their methodology and showcased using a smart meter dataset", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Privacy Algorithms for Streaming Data", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/OKotevska/PrivacyAlgorithms", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ProDeGe:_A_Computational_Protocol_for_fully_Automated_Decontamination_of_Genomic_Data.json b/agency-indexes/DoE/ProDeGe:_A_Computational_Protocol_for_fully_Automated_Decontamination_of_Genomic_Data.json new file mode 100644 index 00000000..a554115b --- /dev/null +++ b/agency-indexes/DoE/ProDeGe:_A_Computational_Protocol_for_fully_Automated_Decontamination_of_Genomic_Data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The Single Cell Data Decontamination Pipeline is a fully-automated software tool which classifies unscreened contigs from single cell datasets through a combination of homology and feature-based methodologies using the organism's nucleotide sequences and known NCBI taxonomony. The software is freely available to download and install, and can be run on any system.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "ProDeGe: A Computational Protocol for fully Automated Decontamination of Genomic Data", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ProFAST__Production_Financial_Analysis_Scenario_Tool__[SWR-23-88].json b/agency-indexes/DoE/ProFAST__Production_Financial_Analysis_Scenario_Tool__[SWR-23-88].json new file mode 100644 index 00000000..ae8fe4be --- /dev/null +++ b/agency-indexes/DoE/ProFAST__Production_Financial_Analysis_Scenario_Tool__[SWR-23-88].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-12-11", + "metadataLastUpdated": "2024-02-09" + }, + "description": "The Production Financial Analysis Scenario Tool (ProFAST) provides a quick and convenient in-depth financial analysis for production facilities. The model uses a generally accepted accounting principles analysis framework and provides annual projections of income statements, cash flow statements, and balance sheets. ProFAST allows users to calculate the levelized cost of the produced commodity by providing an expected financial performance, or on the other hand, calculate the financial performance based on an input price. Model inputs generally capital expenditures, operating expenditures, and financing structure. The programmatic approach of ProFAST allows users to easily perform large sensitivity analyses and integrates easily with other python tools.", + "homepageURL": "https://github.com/NREL/ProFAST", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "ProFAST (Production Financial Analysis Scenario Tool) [SWR-23-88]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://github.com/NREL/ProFAST/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://github.com/NREL/ProFAST", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ProMat.json b/agency-indexes/DoE/ProMat.json new file mode 100644 index 00000000..d0743a96 --- /dev/null +++ b/agency-indexes/DoE/ProMat.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-17", + "metadataLastUpdated": "2024-01-31" + }, + "description": "ProMAT is a software tool for statistically analyzing data from enzyme-linked immunosorbent assay microarray experiments. The software estimates standard curves, sample protein concentrations and their uncertainties for multiple assays. ProMAT generates a set of comprehensive figures for assessing results and diagnosing process quality. The tool is available for Windows or Mac, and is distributed as open-source Java and R code.", + "homepageURL": "https://www.pnnl.gov/statistics/ProMAT", + "laborHours": 0.0, + "languages": [], + "name": "ProMat", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/statistics/ProMAT", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/statistics/ProMAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Proactive_Data_Containers__PDC__v0.1.json b/agency-indexes/DoE/Proactive_Data_Containers__PDC__v0.1.json new file mode 100644 index 00000000..5e8a8818 --- /dev/null +++ b/agency-indexes/DoE/Proactive_Data_Containers__PDC__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-25", + "metadataLastUpdated": "2021-03-25" + }, + "description": "As extreme-scale era software, we are developing novel object- based data abstractions and storage mechanisms that take advantage of the deep storage hierarchy and enable proactive automated performance tuning. In order to achieve these goals, we have developed a fundamental new data abstraction, called Proactive Data Containers (PDC). A PDC is a container within a locus of storage (memory, NVRAM, disk, etc.) that stores science data in an object-oriented manner.", + "laborHours": 0.0, + "languages": [], + "name": "Proactive Data Containers (PDC) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/pdc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Proactive_Intrusion_Detection_and_Mitigation_System.json b/agency-indexes/DoE/Proactive_Intrusion_Detection_and_Mitigation_System.json new file mode 100644 index 00000000..52880932 --- /dev/null +++ b/agency-indexes/DoE/Proactive_Intrusion_Detection_and_Mitigation_System.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2023-08-10" + }, + "description": "SAND2023-05661O\nThe proactive intrusion detection and mitigation system (PIDMS) provides grid-edge situational awareness for cybersecurity defense by capturing real-time distributed energy resource (DER) network traffic and performance data with a novel approach that improves the detection and prevention of cyber-physical attacks. \nThe PIDMS addresses the grid-edge security gap with real-time analysis of both network traffic and photovoltaic performance data to deliver a novel, cyber-physical intrusion detection system (IDS) approach that increases the accuracy and effectiveness of detection and mitigation. \nThis hybrid IDS analysis enables dual monitoring that increases the workload of the adversary; both cyber and physical data would have to be simultaneously spoofed to evade detection. Furthermore, monitoring and analyzing cyber data are insufficient in some cases. For example, in an insider threat aimed at disrupting inverter grid-support functions where proper credentials and authentication are achieved, only the altered PV performance would indicate abnormal behavior. All in all, the PIDMS provides novel capabilities for:\n\u2022\tDistributed, real-time cyber-physical detection and mitigation analysis\n\u2022\tCybersecurity defense for grid-edge systems\n\u2022\tAnalysis framework that can provide situational awareness across the transmission, distribution, and DER systems\nThe PIDMS sensor is designed to collect cyber-physical data, process the data using machine-learning algorithms, detect abnormal events, and deploy mitigations. \nWith these goals, the main functional PIDMS objectives are: \n\u2022\tCapability to collect cyber-physical data\n\u2022\tOnboard storage of cyber-physical data\n\u2022\tPeer-to-peer communication\n\u2022\tComputationally efficient machine-learning algorithms\n\u2022\tOnline cyber-physical data analysis\n\u2022\tAlerting/visualization capabilities\n\u2022\tMitigation deployment capability with bump-in-the-wire (BITW) implementation \nEach of these functional objectives enable PIDMS to perform effective cyber-physical intrusion detection and mitigation.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Bash Scripts", + "Python" + ], + "name": "Proactive Intrusion Detection and Mitigation System", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Probabilistic_Annotation.json b/agency-indexes/DoE/Probabilistic_Annotation.json new file mode 100644 index 00000000..4b687188 --- /dev/null +++ b/agency-indexes/DoE/Probabilistic_Annotation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "The purpose of the Probabilistic Annotation service is to provide users with alternative annotations for genes, each attached to a likelihood score, and to translate these likelihood scores into likelihood scores for the existence of reactions in metabolic models.", + "laborHours": 3009.6, + "languages": [], + "name": "Probabilistic Annotation", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/probabilistic_annotation", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Probabilistic_Resource_Adequacy_Suite__PRAS_.json b/agency-indexes/DoE/Probabilistic_Resource_Adequacy_Suite__PRAS_.json new file mode 100644 index 00000000..bf6d7934 --- /dev/null +++ b/agency-indexes/DoE/Probabilistic_Resource_Adequacy_Suite__PRAS_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "gord.stephen@nrel.gov" + }, + "date": { + "created": "2019-08-13", + "metadataLastUpdated": "2019-08-16" + }, + "description": "The Probabilistic Resource Adequacy Suite (PRAS) provides an open-source, research-oriented collection of tools for analysing the resource adequacy of a bulk power system. The simulation methods offered support everything from classical convolution-based analytical techniques through to high-performance sequential Monte Carlo methods supporting multi-region composite reliability assessment, including simulation of energy-limited resources such as storage.", + "laborHours": 76.0, + "languages": [ + "Julia" + ], + "name": "Probabilistic Resource Adequacy Suite (PRAS)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PRAS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Problem_Solving_Environment_for_Uncertainty_Analysis_and_Design_Exploration.json b/agency-indexes/DoE/Problem_Solving_Environment_for_Uncertainty_Analysis_and_Design_Exploration.json new file mode 100644 index 00000000..600e66e9 --- /dev/null +++ b/agency-indexes/DoE/Problem_Solving_Environment_for_Uncertainty_Analysis_and_Design_Exploration.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-02-07" + }, + "description": "PSUADE is an software system that is used to study the releationships between the inputs and outputs of gerneral simulation models for the purpose of performing uncertainty and sensitivity analyses on simulation models.", + "laborHours": 0.0, + "languages": [], + "name": "Problem Solving Environment for Uncertainty Analysis and Design Exploration", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.4" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Process_model_simulator_for_deception.json b/agency-indexes/DoE/Process_model_simulator_for_deception.json new file mode 100644 index 00000000..36ac9cc8 --- /dev/null +++ b/agency-indexes/DoE/Process_model_simulator_for_deception.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-04-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Software that runs a model of a physical process either generated from extrapolative machine learning or from canned physics simulators to generate realistic data for feeding deceptive controller decoys for defense.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Process model simulator for deception", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Processor_Emulator_with_Benchmark_Applications.json b/agency-indexes/DoE/Processor_Emulator_with_Benchmark_Applications.json new file mode 100644 index 00000000..5fa617b7 --- /dev/null +++ b/agency-indexes/DoE/Processor_Emulator_with_Benchmark_Applications.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A processor emulator and a suite of benchmark applications have been developed to assist in characterizing the performance of data-centric workloads on current and future computer architectures. Some of the applications have been collected from other open source projects. For more details on the emulator and an example of its usage, see reference [1].", + "laborHours": 21872.8, + "name": "Processor Emulator with Benchmark Applications", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/PerMA/emulator_st/src/2969fa5dab7e1b0ffe425869bd27158242c2ee27/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/perma/emulator_st", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Production-quality\302\240mdspan\302\240implementation.json" "b/agency-indexes/DoE/Production-quality\302\240mdspan\302\240implementation.json" new file mode 100644 index 00000000..cdee480a --- /dev/null +++ "b/agency-indexes/DoE/Production-quality\302\240mdspan\302\240implementation.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "Production-quality reference implementation of mdspan.", + "laborHours": 12068.8, + "languages": [], + "name": "Production-quality\u00a0mdspan\u00a0implementation", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/mdspan", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Production_Maintenance_Infrastructure.json b/agency-indexes/DoE/Production_Maintenance_Infrastructure.json new file mode 100644 index 00000000..333b2124 --- /dev/null +++ b/agency-indexes/DoE/Production_Maintenance_Infrastructure.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "PMI is a XML framework for formulating tests of software and software environments which operate in a relatively push button manner, i.e., can be automated, and that provide results that are readily consumable/publishable via RSS. Insofar as possible the tests are carried out in manner congruent with real usage. PMI drives shell scripts via a perl program which is charge of timing, validating each test, and controlling the flow through sets of tests. Testing in PMI is built up hierarchically. A suite of tests may start by testing basic functionalities (file system is writable, compiler is found and functions, shell environment behaves as expected, etc.) and work up to large more complicated activities (execution of parallel code, file transfers, etc.) At each step in this hierarchy a failure leads to generation of a text message or RSS that can be tagged as to who should be notified of the failure. There are two functionalities that PMI has been directed at. 1) regular and automated testing of multi user environments and 2) version-wise testing of new software releases prior to their deployment in a production mode.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "C, Fortran" + ], + "name": "Production Maintenance Infrastructure", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Productivity_frameworks_for_HPC.json b/agency-indexes/DoE/Productivity_frameworks_for_HPC.json new file mode 100644 index 00000000..b91a767f --- /dev/null +++ b/agency-indexes/DoE/Productivity_frameworks_for_HPC.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-27", + "metadataLastUpdated": "2023-03-27" + }, + "description": "Productivity Frameworks for HPC will include container recipes, build recipes, continuous integration scripts, and other software aimed at testing the portability of containerized HPC software across platforms and interconnects. In particular, it tests the utility of bind-mounting at the MPI layer (rather than the underlying fabric layer) to leverage a standardized protocol and avoid various technical debt and vendor lock-in. Since MPIs are often ABI-incompatible, trampolines such as the open-source Wi4MPI will be tested when such cases arise.", + "laborHours": 0.0, + "languages": [], + "name": "Productivity frameworks for HPC", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/productivity-frameworks", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Profile_Interface_Generator.json b/agency-indexes/DoE/Profile_Interface_Generator.json new file mode 100644 index 00000000..c91d656d --- /dev/null +++ b/agency-indexes/DoE/Profile_Interface_Generator.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Profile Interface Generator (PIG) is a tool for loosely coupling applications and performance tools. It enables applications to write code that looks like standard C and Fortran functions calls, without requiring that applications link to specific implementations of those function calls. Performance tools can register with PIG in order to listen to only the calls that give information they care about. This interface reduces the build and configuration burden on application developers and allows semantic instrumentation to live in production codes without interfering with production runs.", + "laborHours": 0.0, + "languages": [], + "name": "Profile Interface Generator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/profile-interface-generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Profugus.json b/agency-indexes/DoE/Profugus.json new file mode 100644 index 00000000..2dfbfaae --- /dev/null +++ b/agency-indexes/DoE/Profugus.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2020-09-01" + }, + "description": "A set of radiation transport mini-applications used for performance optimization on HPC systems.\u00a0http://ornl-cees.github.io/Profugus\n", + "laborHours": 66545.6, + "languages": [], + "name": "Profugus", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-CEES/Profugus", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ProgramFPGA.json b/agency-indexes/DoE/ProgramFPGA.json new file mode 100644 index 00000000..fe8e6a21 --- /dev/null +++ b/agency-indexes/DoE/ProgramFPGA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-10", + "metadataLastUpdated": "2022-08-10" + }, + "description": "The purpose of this bash script is to automatize the procedure of loading a new image into your FPGA.", + "laborHours": 0.0, + "languages": [], + "name": "ProgramFPGA", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/ProgramFPGA/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ProgramFPGA", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Program_Repository_for_Tools_for_Analyzing_Infectious_Disease_Sequence_Data_and_Forecasting_Public_Health_Outcomes.json b/agency-indexes/DoE/Program_Repository_for_Tools_for_Analyzing_Infectious_Disease_Sequence_Data_and_Forecasting_Public_Health_Outcomes.json new file mode 100644 index 00000000..f6999716 --- /dev/null +++ b/agency-indexes/DoE/Program_Repository_for_Tools_for_Analyzing_Infectious_Disease_Sequence_Data_and_Forecasting_Public_Health_Outcomes.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This software is being developed to link infectious disease sequence data to epidemiological models to support forecasting efforts for public health impact. More specifically, this software will allow data analysis, feature extraction, data synthesis, inference, and forecasting of sequence data for infectious diseases (e.g., COVID, flu, dengue) and forecasting of public health outcomes (e.g., cases, hospitalizations, deaths).", + "laborHours": 638.4, + "languages": [], + "name": "Program Repository for Tools for Analyzing Infectious Disease Sequence Data and Forecasting Public Health Outcomes", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/precog", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Program_Repository_for_Tools_for_Heliophysics_Science__Theseus_.json b/agency-indexes/DoE/Program_Repository_for_Tools_for_Heliophysics_Science__Theseus_.json new file mode 100644 index 00000000..c41e3066 --- /dev/null +++ b/agency-indexes/DoE/Program_Repository_for_Tools_for_Heliophysics_Science__Theseus_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "This software is being developed to support data analysis and simulation for the growing field of outer heliosphere physics. In particular, this software will allow data analysis, inference, and simulation of physical mechanisms describing how energetic neutral atoms behave that originate from the solar system's boundary with the interstellar medium. ", + "laborHours": 0.0, + "languages": [], + "name": "Program Repository for Tools for Heliophysics Science (Theseus)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Theseus", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Programming_Repository_for_In_Situ_Modeling.json b/agency-indexes/DoE/Programming_Repository_for_In_Situ_Modeling.json new file mode 100644 index 00000000..7d918ba2 --- /dev/null +++ b/agency-indexes/DoE/Programming_Repository_for_In_Situ_Modeling.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The Programming Repository for In Situ Modeling (PRISM) is a set of tools for fitting statistics and machine learning models to simulation data inside the simulations as they are running. By fitting models inside running simulations, PRISM can be used to analyze simulation data that is otherwise inaccessible because of I/O and storage bottlenecks associated with exascale and other future high performance computing architectures. The tools are designed to implement a wide variety of data analyses with an emphasis on spatiotemporal hierarchical Bayesian models. PRISM is efficient, scalable, and streaming with estimation based on variational inference, advanced Monte Carlo techniques, and fast optimization methods. The core modeling components aid this goal by imposing sparsity and approximate inference wherever possible. These components are written in Julia, a high-level programming language designed for high performance. PRISM also contains tools for interfacing with large-scale scientific simulations written in Fortran and C/C++. This layer of abstraction allows the data scientist to construct analysis models in Julia without concern for the implementation details of the simulation capability. With these components, PRISM can be used to unlock the full scientific potential of next-generation HPC simulations.", + "laborHours": 0.0, + "languages": [], + "name": "Programming Repository for In Situ Modeling", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PRISM", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Programming_at_SLAC.json b/agency-indexes/DoE/Programming_at_SLAC.json new file mode 100644 index 00000000..eec171d9 --- /dev/null +++ b/agency-indexes/DoE/Programming_at_SLAC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-06-05", + "metadataLastUpdated": "2018-06-05" + }, + "description": "A general repository of useful information for programming across the lab. This repository is oriented around tools, education, best practices, and general knowledge around programming and software development across the lab. We hope it will empower anyone who writes softare at the lab, whether it's analysis scripts in python, firmware for daq systems, web apps for communications, or just simple bash scripts.\n", + "laborHours": 60.8, + "languages": [], + "name": "Programming at SLAC", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/programming/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/programming", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Progress_Version_1.0.json b/agency-indexes/DoE/Progress_Version_1.0.json new file mode 100644 index 00000000..1f3b7a89 --- /dev/null +++ b/agency-indexes/DoE/Progress_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Software library for parallel rapid order N and graph-based recursive electronic structure solvers with applications to material science, chemistry, and molecular biology.", + "laborHours": 425.6, + "name": "Progress Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/progress/progress.github.io", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ProgressiveHedging.jl.json b/agency-indexes/DoE/ProgressiveHedging.jl.json new file mode 100644 index 00000000..e1b86f7d --- /dev/null +++ b/agency-indexes/DoE/ProgressiveHedging.jl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "Implementation of the Progressive Hedging algorithm written in Julia utilizing JuMP. This is used to solve multistage optimization problems (e.g. Stochastic programs or capacity expansion models). The user uses the StructJuMP extension of JuMP to create the model and build up the scenario tree.", + "laborHours": 820.8, + "languages": [], + "name": "ProgressiveHedging.jl", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ProgressiveHedging.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Project_Grandmaster.json b/agency-indexes/DoE/Project_Grandmaster.json new file mode 100644 index 00000000..d28cf758 --- /dev/null +++ b/agency-indexes/DoE/Project_Grandmaster.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The purpose of the Project Grandmaster Application is to allow individuals to opt-in and give the application access to data sources about their activities on social media sites. The application will cross-reference these data sources to build up a picture of each individual activities they discuss, either at present or in the past, and place this picture in reference to groups of all participants. The goal is to allow an individual to place themselves in the collective and to understand how their behavior patterns fit with the group and potentially find changes to make, such as activities they weren't already aware of or different groups of interest they might want to follow.", + "laborHours": 3967.2, + "name": "Project Grandmaster", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/grandmaster", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Project_Schedule_Comparison_and_Visualization.json b/agency-indexes/DoE/Project_Schedule_Comparison_and_Visualization.json new file mode 100644 index 00000000..07f86bf4 --- /dev/null +++ b/agency-indexes/DoE/Project_Schedule_Comparison_and_Visualization.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-03-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Project Schedule Comparison and Visualization allows project schedules to be compared across time scales. It also allows for visualization of schedules in the form of a network graph. This compliments Gantt chart view in major project risk management software. The software mimics complex networks and makes it easy to visualize tasks and links. It produces a list with differences between snapshots. Selecting these differences renders a view focused on these changes in the network.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Project Schedule Comparison and Visualization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ProkkaAnnotation.json b/agency-indexes/DoE/ProkkaAnnotation.json new file mode 100644 index 00000000..a5b89baa --- /dev/null +++ b/agency-indexes/DoE/ProkkaAnnotation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-08", + "metadataLastUpdated": "2020-09-08" + }, + "description": "This is the repository for \"ProkkaAnnotation\" developed by KBase. ", + "laborHours": 37680.8, + "languages": [], + "name": "ProkkaAnnotation", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ProkkaAnnotation", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Prompt-Based_Development_of_Domain-Specific_Taxonomies.json b/agency-indexes/DoE/Prompt-Based_Development_of_Domain-Specific_Taxonomies.json new file mode 100644 index 00000000..bac26eae --- /dev/null +++ b/agency-indexes/DoE/Prompt-Based_Development_of_Domain-Specific_Taxonomies.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-14", + "metadataLastUpdated": "2025-04-14" + }, + "description": "Framework for interacting with prompt-based LLMs (Large Language Models such as, but not\nlimited to, ChatGPT) in order to develop domain specific taxonomies. The software itself is a series of prompts designed to\nextract hierarchical taxonomy categories from an LLM, as well as guidelines for how to fine-tune LLMs in order to provide\nbetter domain-specific taxonomic categories.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 395.2, + "languages": [], + "name": "Prompt-Based Development of Domain-Specific Taxonomies", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Prony_Ringdown_GUI__CERTS_Prony_Ringdown,_part_of_the_DSI_Tool_Box_.json b/agency-indexes/DoE/Prony_Ringdown_GUI__CERTS_Prony_Ringdown,_part_of_the_DSI_Tool_Box_.json new file mode 100644 index 00000000..b63b8e4a --- /dev/null +++ b/agency-indexes/DoE/Prony_Ringdown_GUI__CERTS_Prony_Ringdown,_part_of_the_DSI_Tool_Box_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The PNNL Prony Ringdown graphical user interface is one analysis tool included in the Dynamic System Identification toolbox (DSI Toolbox). The Dynamic System Identification toolbox is a MATLAB-based collection of tools for parsing and analyzing phasor measurement unit data, especially in regards to small signal stability. It includes tools to read the data, preprocess it, and perform small signal analysis. 5. Method of Solution: The Dynamic System Identification Toolbox (DSI Toolbox) is designed to provide a research environment for examining phasor measurement unit data and performing small signal stability analysis. The software uses a series of text-driven menus to help guide users and organize the toolbox features. Methods for reading in populate phasor measurement unit data are provided, with appropriate preprocessing options for small-signal-stability analysis. The toolbox includes the Prony Ringdown GUI and basic algorithms to estimate information on oscillatory modes of the system, such as modal frequency and damping ratio.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Prony Ringdown GUI (CERTS Prony Ringdown, part of the DSI Tool Box)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ftuffner/DSIToolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Protection_settings_optimizer.json b/agency-indexes/DoE/Protection_settings_optimizer.json new file mode 100644 index 00000000..93b33e1b --- /dev/null +++ b/agency-indexes/DoE/Protection_settings_optimizer.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2023-08-10" + }, + "description": "SAND2023-06672O\nThe Protection Settings Optimizer (PSO) uses system and fault data as inputs to formulate the problem of calculating relay settings as a mixed integer, nonlinear optimization problem (MINLP). The MINLP is solved using a genetic algorithm-based optimizer that attempts to find settings to reduce the relay operating times. \n\nThe PSO protects the power system by using the steady-state fault voltages and currents, which then calculates the optimal device setting to protect the power system.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Protection settings optimizer", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Protection-settings-optimizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ProteinStructureUtils.json b/agency-indexes/DoE/ProteinStructureUtils.json new file mode 100644 index 00000000..9bda0684 --- /dev/null +++ b/agency-indexes/DoE/ProteinStructureUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "A KBase module generated by the KBase SDK. This module handles import and export of ProteinStructures in PDB format.", + "laborHours": 1702.4, + "languages": [], + "name": "ProteinStructureUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ProteinStructureUtils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Protein_Coverage_Summarizer.json b/agency-indexes/DoE/Protein_Coverage_Summarizer.json new file mode 100644 index 00000000..86732fa9 --- /dev/null +++ b/agency-indexes/DoE/Protein_Coverage_Summarizer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Protein Coverage Summarizer can be used to determine the percent of the residues in each protein sequence that have been identified, based on a list of identified peptides. A graphical user interface (GUI) is provided to allow the user to select the input files, set the options, and browse the coverage results.", + "laborHours": 7569.6, + "languages": [], + "name": "Protein Coverage Summarizer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/protein-coverage-summarizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Protein_Digestion_Simulator.json b/agency-indexes/DoE/Protein_Digestion_Simulator.json new file mode 100644 index 00000000..eb627448 --- /dev/null +++ b/agency-indexes/DoE/Protein_Digestion_Simulator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Protein Digestion Simulator is a utility for processing\u00a0FASTA files\u00a0including converting to/from tab delimited text. It also supports FASTA file validation.", + "laborHours": 7296.0, + "languages": [], + "name": "Protein Digestion Simulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Protein-Digestion-Simulator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ProteowizardWrapper.json b/agency-indexes/DoE/ProteowizardWrapper.json new file mode 100644 index 00000000..cfd0cd39 --- /dev/null +++ b/agency-indexes/DoE/ProteowizardWrapper.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The ProteowizardWrapper is a series of C# classes that can be used to interface with the ProteoWizard libraries.", + "laborHours": 44277.6, + "languages": [], + "name": "ProteowizardWrapper", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Proteowizard-Wrapper", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Proto-DUNE.json b/agency-indexes/DoE/Proto-DUNE.json new file mode 100644 index 00000000..a5c6087e --- /dev/null +++ b/agency-indexes/DoE/Proto-DUNE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2018-05-30" + }, + "description": "This repository contains instructions on the setup and building the DTM firmware for Proto-DUNE.\n", + "laborHours": 121356.8, + "languages": [], + "name": "Proto-DUNE", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/proto-dune/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/proto-dune", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Protocol_Compiler.json b/agency-indexes/DoE/Protocol_Compiler.json new file mode 100644 index 00000000..14803dbb --- /dev/null +++ b/agency-indexes/DoE/Protocol_Compiler.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-10-14", + "metadataLastUpdated": "2019-10-14" + }, + "description": "A command line tool that converts a protocol specification into a target language.", + "homepageURL": "https://cdcvs.fnal.gov/redmine/projects/protocol-compiler/repository", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Protocol Compiler", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cdcvs.fnal.gov/redmine/projects/protocol-compiler/repository", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Proton_Radiography_Imager:Generates_Synthetic_Proton_Radiographs.json b/agency-indexes/DoE/Proton_Radiography_Imager:Generates_Synthetic_Proton_Radiographs.json new file mode 100644 index 00000000..097dc4aa --- /dev/null +++ b/agency-indexes/DoE/Proton_Radiography_Imager:Generates_Synthetic_Proton_Radiographs.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ProRad is a computer program that is used to generate synthetic images of proton (or other charged particles) radiographs. The proton radiographs arc images that arc obtained by sending energetic protons (or electrons or positrons, for example) through 11 plasma where electric and/or magnetic fields alter the particles trajectory, Dnd the variations me imaged on RC film, image plate, or equivalent", + "laborHours": 988.0, + "name": "Proton Radiography Imager:Generates Synthetic Proton Radiographs", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/prorad/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/prorad", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Prove-It_v._0.3.json b/agency-indexes/DoE/Prove-It_v._0.3.json new file mode 100644 index 00000000..86ed297b --- /dev/null +++ b/agency-indexes/DoE/Prove-It_v._0.3.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Prove-It is a tool for proving and organizing general theorems using Python.", + "laborHours": 70953.6, + "languages": [ + "Python", + "Smarty", + "CSS", + "HTML", + "Jupyter Notebook", + "TeX" + ], + "name": "Prove-It v. 0.3", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Prove-It", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Provenance_Environment_Services_Software.json b/agency-indexes/DoE/Provenance_Environment_Services_Software.json new file mode 100644 index 00000000..3777fc74 --- /dev/null +++ b/agency-indexes/DoE/Provenance_Environment_Services_Software.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The ProvEn Software is designed to analyze and monitor distributed scientific workflow application behavior in the context of its environment.", + "laborHours": 349.6, + "name": "Provenance Environment Services Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ProvenanceEnvironment", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Provenance_VOL_Connector_for_HDF5__H5Prov__v0.1.json b/agency-indexes/DoE/Provenance_VOL_Connector_for_HDF5__H5Prov__v0.1.json new file mode 100644 index 00000000..52fabad3 --- /dev/null +++ b/agency-indexes/DoE/Provenance_VOL_Connector_for_HDF5__H5Prov__v0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-06-11", + "metadataLastUpdated": "2020-06-11" + }, + "description": "We have developed a Virtual Object Layer (VOL) connector for HDF5, the most popular I/O middleware on HPC systems. The VOL connector, called H5Prov, transparently intercepts HDF5 calls and records operations at multiple levels, namely file, group, dataset, and data element levels.", + "laborHours": 0.0, + "languages": [], + "name": "Provenance VOL Connector for HDF5 (H5Prov) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://tonglinli@bitbucket.hdfgroup.org/scm/hdf5vol/provenance.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Prozy_Visco-plasticity,_Fast_Fourier_Transform.json b/agency-indexes/DoE/Prozy_Visco-plasticity,_Fast_Fourier_Transform.json new file mode 100644 index 00000000..0487fb7c --- /dev/null +++ b/agency-indexes/DoE/Prozy_Visco-plasticity,_Fast_Fourier_Transform.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ProxyVPFFT computes the micromechanical reaponse of polycriystalline samples directly from images of their microstructures, usually captured using SEM. [2] ProxyVPFFT is proxy application, or a somplified version of existing software by Ricardo Lebensohn (VPFFT).", + "laborHours": 1900.0, + "name": "Prozy Visco-plasticity, Fast Fourier Transform", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/exmatex/VPFFT/blob/master/README-license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exmatex/vpfft", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PsDNS.json b/agency-indexes/DoE/PsDNS.json new file mode 100644 index 00000000..3c09ecf5 --- /dev/null +++ b/agency-indexes/DoE/PsDNS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "PsDNS is a Python package which makes it easy to solve partial differential equation using a pseudo-spectral method. The code uses Python classes and Numpy-like arrays to provide a simple interface with which users can construct equations, integrators, and diagnostics. It also includes implementation for common problems, in particular, the incompressible Navier-Stokes equation in a periodic domain, which is commonly used as a benchmark problem for turbulence research. PsDNS uses MPI to allow massively parallel computation for large problems.", + "laborHours": 0.0, + "languages": [], + "name": "PsDNS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PsDNS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pseudopotential_Algorithm_for_Real-Space_Electronic_Structure_Calculations.json b/agency-indexes/DoE/Pseudopotential_Algorithm_for_Real-Space_Electronic_Structure_Calculations.json new file mode 100644 index 00000000..639bf443 --- /dev/null +++ b/agency-indexes/DoE/Pseudopotential_Algorithm_for_Real-Space_Electronic_Structure_Calculations.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "lioukaihsin@utexas.edu" + }, + "date": { + "created": "2021-06-27", + "metadataLastUpdated": "2021-06-27" + }, + "description": "PARSEC is a computer code that solves the Kohn-Sham equations by expressing electron wave-functions directly in real space, without the use of explicit basis sets. It uses norm-conserving pseudopotentials (Troullier-Martins and other varieties). It is designed for ab initio quantum-mechanical calculations of the electronic structure of matter, within density-functional theory.\nPARSEC is optimized for massively parallel computing environment, but it is also compatible with serial machines. A finite-difference approach is used for the calculation of spatial derivatives. Owing to the sparsity of the Hamiltonian matrix, the Kohn-Sham equations are solved by direct diagonalization, with the use of extremely efficient sparse-matrix eigensolvers. Some of its features are: Choice of boundary conditions: periodic (on all three directions), or confined. Structural relaxation. Simulated annealing. Langevin molecular dynamics. Polarizability calculations (confined-system boundary conditions only). Spin-orbit coupling. Non-collinear magnetism.", + "laborHours": 0.0, + "languages": [ + "Fortran", + "Python" + ], + "name": "Pseudopotential Algorithm for Real-Space Electronic Structure Calculations", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/real-space/parsec", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "version": "1.4" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Psychrometric_Chart_v1.0.0.json b/agency-indexes/DoE/Psychrometric_Chart_v1.0.0.json new file mode 100644 index 00000000..0b6941b5 --- /dev/null +++ b/agency-indexes/DoE/Psychrometric_Chart_v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "Psychart is a graphical program developed for NERSC for accurately monitoring air conditions for the air cooled HPC equipment. Psychart will live directly in the OMNI system as a Grafana plugin. It employs the use of Psychrolib and the Grafana Starter Panel to create a front-end program that plots the state of the environmental air on a psychrometric chart. It is highly customizable, allowing the user to modify graph bounds, optionally show ASHRAE data center comfort regions, change the series point color, and more. What sets Psychart apart from other existing psychrometric charts is its ability to plot in real-time. Other psychrometric charts that can be found online require manual input of data and do not seamlessly integrate with Grafana.", + "laborHours": 12676.8, + "languages": [], + "name": "Psychrometric Chart v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nicfv/Psychart", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PuLP_XtraPuLP_:_Partitioning_Tools_for_Extreme-Scale_Graphs.json b/agency-indexes/DoE/PuLP_XtraPuLP_:_Partitioning_Tools_for_Extreme-Scale_Graphs.json new file mode 100644 index 00000000..2b6e99db --- /dev/null +++ b/agency-indexes/DoE/PuLP_XtraPuLP_:_Partitioning_Tools_for_Extreme-Scale_Graphs.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-26" + }, + "description": "PuLP/XtraPulp is software for partitioning graphs from several real-world problems. Graphs occur in several places in real world from road networks, social networks and scientific simulations. For efficient parallel processing these graphs have to be partitioned (split) with respect to metrics such as computation and communication costs. Our software allows such partitioning for massive graphs.", + "laborHours": 11795.2, + "languages": [ + "C++", + "C" + ], + "name": "PuLP/XtraPuLP : Partitioning Tools for Extreme-Scale Graphs", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PuLP", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Purge_Lock_Server.json b/agency-indexes/DoE/Purge_Lock_Server.json new file mode 100644 index 00000000..810eaaee --- /dev/null +++ b/agency-indexes/DoE/Purge_Lock_Server.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The software provides a simple web api to allow users to request a time window where a file will not be removed from cache. HPSS provides the concept of a \"purge lock\". When a purge lock is set on a file, the file will not be removed from disk, entering tape only state. A lot of network file protocols assume a file is on disk so it is good to purge lock a file before transferring using one of those protocols. HPSS's purge lock system is very coarse grained though. A file is either purge locked or not. Nothing enforces quotas, timely unlocking of purge locks, or managing the races inherent with multiple users wanting to lock/unlock the same file. The Purge Lock Server lets you, through a simple REST API, specify a list of files to purge lock and an expire time, and the system will ensure things happen properly.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C", + "PHP" + ], + "name": "Purge Lock Server", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Py-Bedrock.json b/agency-indexes/DoE/Py-Bedrock.json new file mode 100644 index 00000000..b6cf7b1e --- /dev/null +++ b/agency-indexes/DoE/Py-Bedrock.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "Py-Bedrock providers Python utilities to configure and deploy Mochi-based services using Python.", + "laborHours": 0.0, + "languages": [], + "name": "Py-Bedrock", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/py-mochi-bedrock/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/py-mochi-bedrock", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Py-Colza.json b/agency-indexes/DoE/Py-Colza.json new file mode 100644 index 00000000..ae70541e --- /dev/null +++ b/agency-indexes/DoE/Py-Colza.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-31", + "metadataLastUpdated": "2022-01-31" + }, + "description": "Py-Colza is a Python interface for the Colza Mochi microservice.", + "laborHours": 0.0, + "languages": [], + "name": "Py-Colza", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/py-mochi-colza/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/py-mochi-colza", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Py-Margo.json b/agency-indexes/DoE/Py-Margo.json new file mode 100644 index 00000000..19ebdbe7 --- /dev/null +++ b/agency-indexes/DoE/Py-Margo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-31", + "metadataLastUpdated": "2022-01-31" + }, + "description": "Py-Margo provides a Python wrapper on top of Margo. It enables one to develop Margo-based service in Python.", + "laborHours": 0.0, + "languages": [], + "name": "Py-Margo", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/py-mochi-margo/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/py-mochi-margo", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Py-Mobject.json b/agency-indexes/DoE/Py-Mobject.json new file mode 100644 index 00000000..bfadffb8 --- /dev/null +++ b/agency-indexes/DoE/Py-Mobject.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-28", + "metadataLastUpdated": "2022-01-28" + }, + "description": "Py-Mobject is a Python wrapper enabling one to write a daemon to deploy Mobject using python. Py-Mobject relies on Mobject, Py-Bake, Py-SDSKV, Py-SSG, and Py-Margo, as well as their respective dependencies. It also requires boost_python.", + "laborHours": 0.0, + "languages": [], + "name": "Py-Mobject", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/py-mobject/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/py-mobject", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Py-Sonata.json b/agency-indexes/DoE/Py-Sonata.json new file mode 100644 index 00000000..df09bce8 --- /dev/null +++ b/agency-indexes/DoE/Py-Sonata.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-28", + "metadataLastUpdated": "2022-01-28" + }, + "description": "Python binding to the Mochi Sonata microservice.", + "laborHours": 0.0, + "languages": [], + "name": "Py-Sonata", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/py-mochi-sonata/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/py-mochi-sonata", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyARC.json b/agency-indexes/DoE/PyARC.json new file mode 100644 index 00000000..9ca9c231 --- /dev/null +++ b/agency-indexes/DoE/PyARC.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-31" + }, + "description": "PyARC is a wrapper script developed to integrate the Argonne Reactor Computation suite of neutronic codes into the NEAMS Workbench user interface. It contains the Workbench \"common input\" definition, handles some pre-processing, writes the native codes inputs, handles the runtime environment, and performs some post-processing. It was developed to facilitate access and utilization of the ARC codes, and facilitate transition to higher fidelity NEAMS codes.", + "laborHours": 21356.0, + "languages": [], + "name": "PyARC", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/neams-workbench/PyARC", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyBioNetFit.json b/agency-indexes/DoE/PyBioNetFit.json new file mode 100644 index 00000000..74b20763 --- /dev/null +++ b/agency-indexes/DoE/PyBioNetFit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-11-26", + "metadataLastUpdated": "2018-11-27" + }, + "description": "Systems biology models written in the BioNetGen language often contain parameters that must be fit based on experimental data. PyBioNetFit is a software tool designed to fit parameters of BioNetGen models. The user is expected to provide a BioNetGen model that contains unknown parameters, along with one or more text files containing experimental data. PyBioNetFit will perform a series of calls to the BioNetGen simulator using different parameter sets, to identify the parameter set that best fits the data. The parameter search is dictated by the user's choice of one of several metaheuristic optimization algorithms, including differential evolution, particle swarm optimization, scatter search, and simulated annealing. The software supports parallelized computing on multi-core computers and on computing clusters. We expect this software to be a useful tool for researchers designing BioNetGen models in collaboration with experimentalists.", + "laborHours": 24715.2, + "languages": [], + "name": "PyBioNetFit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PyBNF", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyChargeModel__Oriented_Programming_Based_Electric_Vehicle_and_Electric_Vehicle_Supply_Equipment_Charging_Model_in_Python__[SWR-22-39].json b/agency-indexes/DoE/PyChargeModel__Oriented_Programming_Based_Electric_Vehicle_and_Electric_Vehicle_Supply_Equipment_Charging_Model_in_Python__[SWR-22-39].json new file mode 100644 index 00000000..358cde8a --- /dev/null +++ b/agency-indexes/DoE/PyChargeModel__Oriented_Programming_Based_Electric_Vehicle_and_Electric_Vehicle_Supply_Equipment_Charging_Model_in_Python__[SWR-22-39].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-08-19", + "metadataLastUpdated": "2023-04-24" + }, + "description": "The PyChargeModel creates two classes called \"ElectricVehicles\" and \"evse_class\", which can be used to create multiple instances of electric vehicles (EVs) and electric vehicle supply equipment (EVSE or charging ports) and simulate charging behavior. These objects can be instantiated with several properties such as battery chemistries, battery pack sizes, cell sizes, charging port power, dc or ac chargers etc. The objects can communicate with each other by calling different methods built within the classes. Through these methods, each EV object can be assigned to an EVSE, charged either using a default protocol or using setpoint values communicated from a site controller via the EVSE object.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "PyChargeModel (Oriented Programming Based Electric Vehicle and Electric Vehicle Supply Equipment Charging Model in Python) [SWR-22-39]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PyChargeModel", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyDBus.json b/agency-indexes/DoE/PyDBus.json new file mode 100644 index 00000000..98987fc6 --- /dev/null +++ b/agency-indexes/DoE/PyDBus.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "This software is an interface in Python for interacting with EPRI DBus software.", + "laborHours": 182.4, + "languages": [ + "Python" + ], + "name": "PyDBus", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pydbus", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyDDA__Pythonic_Direct_Data_Assimilation_.json b/agency-indexes/DoE/PyDDA__Pythonic_Direct_Data_Assimilation_.json new file mode 100644 index 00000000..d11e6ac2 --- /dev/null +++ b/agency-indexes/DoE/PyDDA__Pythonic_Direct_Data_Assimilation_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "This software is a package for assimilating data from multiple radars and models together to create a 3D wind retrieval over a region. The framework is based off of the minimization of a cost function related to the varying sensors, mass continuity, and model. Since it is open source the community is able to contribute and expand the package to use data from their own desired model or sensor. ", + "laborHours": 2675.2, + "languages": [], + "name": "PyDDA (Pythonic Direct Data Assimilation)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openradar/PyDDA", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyDM_PVAccess_Widgets.json b/agency-indexes/DoE/PyDM_PVAccess_Widgets.json new file mode 100644 index 00000000..7f76e162 --- /dev/null +++ b/agency-indexes/DoE/PyDM_PVAccess_Widgets.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-23", + "metadataLastUpdated": "2022-08-23" + }, + "description": "EPICS PVAccess PyDM Widget Library", + "laborHours": 0.0, + "languages": [], + "name": "PyDM PVAccess Widgets", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pydm_pva_widgets/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pydm_pva_widgets", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyDSS.json b/agency-indexes/DoE/PyDSS.json new file mode 100644 index 00000000..8a91ea10 --- /dev/null +++ b/agency-indexes/DoE/PyDSS.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-09-19", + "metadataLastUpdated": "2022-08-08" + }, + "description": "PyDSS is a high level Python interface for OpenDSS and provides the following functionalities: 1] Object oriented programming, 2] Dynamic visualization, 3] Custom controls, 4] Simulation parallelization, 5] Exporting results, 6] Improved error logging, and 7] Communication interface. Documentation on installation, setup and examples can be found here https://nrel.github.io/PyDSS/index.html", + "laborHours": 5304.8, + "languages": [ + "Python" + ], + "name": "PyDSS", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/PyDSS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyDislocDyn.json b/agency-indexes/DoE/PyDislocDyn.json new file mode 100644 index 00000000..f6aeb670 --- /dev/null +++ b/agency-indexes/DoE/PyDislocDyn.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2018-06-19" + }, + "description": "PyDislocDyn is a suite of python programs designed to perform various calculations for basic research in dislocation dynamics in metals with simple crystal symmetries in the continuum limit. In particular, one of its main purposes is to calculate dislocation drag from phonon wind (i.e. the friction coefficient of a moving crystal defect called a \u201cdislocation\u201d due to its interaction with crystal lattice vibrations or phonons). Additional features include the averaging of elastic constants for polycrystals, the calculation of the dislocation field and the calculation of dislocation self-energy and line tension. ", + "laborHours": 1352.8, + "languages": [], + "name": "PyDislocDyn", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dblaschke-LANL/PyDislocDyn", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyDynamicWindow_v1.json b/agency-indexes/DoE/PyDynamicWindow_v1.json new file mode 100644 index 00000000..f9eeaa3d --- /dev/null +++ b/agency-indexes/DoE/PyDynamicWindow_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This software is developed for researchers to evaluate the energy performance of of dynamic windows in the world-wide climate, and this first version focuses on thermochromic windows. We bring new indicators (necessity level and recommendation index) to the evaluation system for thermochromic windows. We estimate the majority users of this software tool will be non-commercial academic researchers. But commercial companies can also use it to optimize their products and estimate where their product has the most promising market.", + "laborHours": 258.4, + "languages": [], + "name": "PyDynamicWindow v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/PyDynamicWindow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyEPANET_v._0.1.0.json b/agency-indexes/DoE/PyEPANET_v._0.1.0.json new file mode 100644 index 00000000..394156d8 --- /dev/null +++ b/agency-indexes/DoE/PyEPANET_v._0.1.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2024-09-17" + }, + "description": "The PyEPANET package is a set of commands for the Python programming language that are built to wrap the EPANET toolkit library commands, without requiring the end user to program using the ctypes package. This package does not contain the \nEPANET code, nor does it implement the functions within the EPANET software, and it requires the separately downloaded or compiled EPANET2 toolkit dynamic library (epanet.dll, libepanet.so, or epanet.dylib) and/or the EPANET-MSX dynamic library in order to function. \n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 147744.0, + "languages": [ + "Python", + "C++", + "C" + ], + "name": "PyEPANET v. 0.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PyEPANET", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyEmittance.json b/agency-indexes/DoE/PyEmittance.json new file mode 100644 index 00000000..cecb17fa --- /dev/null +++ b/agency-indexes/DoE/PyEmittance.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-06-16", + "metadataLastUpdated": "2022-06-16" + }, + "description": "PyEmittance is a tool for the adaptive measurement of beam emittance (e.g. of an electron beam at OTR/YAG beam profile monitors) using a single quadrupole scan developed at SLAC National Accelerator Laboratory. The Twiss parameters and the 'Bmag' match parameter can also be obtained. It can be used in different beamlines/machines by defining machine-specific configuration files.", + "laborHours": 0.0, + "languages": [], + "name": "PyEmittance", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/PyEmittance", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyEnvBuilder_-_Python_Environment_Builder.json b/agency-indexes/DoE/PyEnvBuilder_-_Python_Environment_Builder.json new file mode 100644 index 00000000..07456602 --- /dev/null +++ b/agency-indexes/DoE/PyEnvBuilder_-_Python_Environment_Builder.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-09", + "metadataLastUpdated": "2022-08-09" + }, + "description": "PyEnvBuilder is a python package that can be used to parse a well-defined YAML file and generate a packed conda environment, which can be later deployed and unpacked on different machines that do not require conda/python.", + "laborHours": 0.0, + "languages": [], + "name": "PyEnvBuilder - Python Environment Builder", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pyenvbuilder/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pyenvbuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyEpics.json b/agency-indexes/DoE/PyEpics.json new file mode 100644 index 00000000..e900a1a0 --- /dev/null +++ b/agency-indexes/DoE/PyEpics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "PyEpics is a Python interface to the EPICS Channel Access (CA) library for the EPICS control system. The PyEpics module includes both low-level (C-like) and higher-level access (with Python objects) to the EPICS Channel Access (CA) protocol. Python's ctypes library is used to wrap the basic CA functionality, with higher level objects on top of that basic interface. This approach has several advantages including no need for extension code written in C, better thread-safety, and easier installation on multiple platforms.", + "laborHours": 7736.8, + "languages": [], + "name": "PyEpics", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/pyepics/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/pyepics", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyFloT_v0.1.json b/agency-indexes/DoE/PyFloT_v0.1.json new file mode 100644 index 00000000..3fe541e3 --- /dev/null +++ b/agency-indexes/DoE/PyFloT_v0.1.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-02-28", + "metadataLastUpdated": "2021-06-15" + }, + "description": "PyFlot is a combination of python and C++ which aims at tuning floating point precision inside scientific applications. PyFloT uses link time interposition for portability and generality. The set of functions of interest are wrapped with code that enables either profiling or their lowering based on the classification criteria: SLOC (Source code LOCation) or backtrace. PyFloT implementation has only be validated using the GNU compiler toolchain.", + "laborHours": 0.0, + "languages": [], + "name": "PyFloT v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hbrunie/PyFloT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyForecastTools.json b/agency-indexes/DoE/PyForecastTools.json new file mode 100644 index 00000000..b729f88c --- /dev/null +++ b/agency-indexes/DoE/PyForecastTools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2020-09-01" + }, + "description": "This package provides a basic toolkit for model validation and forecast verification, implemented in Python. The code is designed to aid model validation tasks for users of the standard scientific python stack. Functions and classes are provided to calculate a broad range of metrics for continuous and categorical predictions.", + "laborHours": 866.4, + "languages": [], + "name": "PyForecastTools", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/drsteve/PyForecastTools", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyFrame3DD_[SWR-14-22].json b/agency-indexes/DoE/PyFrame3DD_[SWR-14-22].json new file mode 100644 index 00000000..6acec2c6 --- /dev/null +++ b/agency-indexes/DoE/PyFrame3DD_[SWR-14-22].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "A module that allows Frame3DD to interact with codes developed at NREL within the Systems Engineering WIDEM toolbox.", + "laborHours": 7448.0, + "languages": [ + "C", + "Python" + ], + "name": "PyFrame3DD [SWR-14-22]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/pyFrame3DD", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyGeoTess_0.2.0.json b/agency-indexes/DoE/PyGeoTess_0.2.0.json new file mode 100644 index 00000000..7bd6b0f1 --- /dev/null +++ b/agency-indexes/DoE/PyGeoTess_0.2.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PyGeoTess is a Python interface module to the GeoTess gridding and earth model library from Sandia National Laboratories. It provides simplified access to a subset of the GeoTess C++ library, and takes advantage of Python's interactive interpreter and inline documentation system.", + "laborHours": 8299.2, + "name": "PyGeoTess 0.2.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LANL-Seismoacoustics/PyGeoTess/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-seismoacoustics/pygeotess", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyGrid_WSDL_and_XML_Schema_interpreter.json b/agency-indexes/DoE/PyGrid_WSDL_and_XML_Schema_interpreter.json new file mode 100644 index 00000000..d0d474c7 --- /dev/null +++ b/agency-indexes/DoE/PyGrid_WSDL_and_XML_Schema_interpreter.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "PyGridWare WSDL and XMLSchema interpreter is used to automatically generate python code that maps directly to the XMLSchema objects and WSLD PortTypes.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Python 2.0+" + ], + "name": "PyGrid WSDL and XML Schema interpreter", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyGridware_OGSI_Hosting_Container.json b/agency-indexes/DoE/PyGridware_OGSI_Hosting_Container.json new file mode 100644 index 00000000..01b22652 --- /dev/null +++ b/agency-indexes/DoE/PyGridware_OGSI_Hosting_Container.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "PyGridWare OGSI Hosting Container provides a Python container for building Open Grid Services Infrastructure (OGSI) services. It provides a complete implementation of the OGSI standards.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "PyGridware OGSI Hosting Container", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyKilonova.json b/agency-indexes/DoE/PyKilonova.json new file mode 100644 index 00000000..94f5cddf --- /dev/null +++ b/agency-indexes/DoE/PyKilonova.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This is a software package to predict electromagnetic counterpart production associated with gravitational-wave observations from binary neutron star and neutron star - black hole mergers. This reads in posterior distributions of signal parameters produced by parameter estimation pipelines analyzing gravitational-wave data and predicts whether an electromagnetic transient will be produced and observable in the sky. The code relies on open-source, easy-to-use software tools.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "PyKilonova", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyMDA.json b/agency-indexes/DoE/PyMDA.json new file mode 100644 index 00000000..bb030fc3 --- /dev/null +++ b/agency-indexes/DoE/PyMDA.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "rgrandy@bnl.gov" + }, + "date": { + "created": "2020-03-30", + "metadataLastUpdated": "2020-03-30" + }, + "description": "PyMDA allows for processing individual microcrystal data sets as progressive wedges to address radiation damage and allows for robust extraction of diffraction signals including weak anomalous signals through the implementation of unit-cell-based classification and an iterative outlier rejection strategy. PyMDA may be used routinely to process microcrystal data sets to produce one or more assembled data sets for structural analysis.", + "laborHours": 395.2, + "languages": [ + "Python" + ], + "name": "PyMDA", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/qun-liu/PyMDA", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyMEDM.json b/agency-indexes/DoE/PyMEDM.json new file mode 100644 index 00000000..71d1883d --- /dev/null +++ b/agency-indexes/DoE/PyMEDM.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "tuccillojv@ornl.gov" + }, + "date": { + "created": "2025-03-20", + "metadataLastUpdated": "2025-03-20" + }, + "description": "The PyMEDM package is a Python-native port of Penalized-Maximum Entropy Dasymetric Modeling (P-MEDM) method. While the original implementation of P-MEDM consists of an R interface over a model written in C++, PyMEDM combines both capabilities in a common language that interfaces with other utilities in the Likeness stack. PyMEDM is also GPU-enabled via JAX , which supports High-Performance Computing (HPC) applications.", + "laborHours": 1580.8, + "languages": [ + "Python" + ], + "name": "PyMEDM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/likeness-pop/pymedm/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/likeness-pop/pymedm", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "2.2.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyMFEM.json b/agency-indexes/DoE/PyMFEM.json new file mode 100644 index 00000000..e24ebae7 --- /dev/null +++ b/agency-indexes/DoE/PyMFEM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Python wrapper for MFEM", + "laborHours": 890431.2, + "languages": [], + "name": "PyMFEM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfem/PyMFEM", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyMSI.json b/agency-indexes/DoE/PyMSI.json new file mode 100644 index 00000000..4b586a88 --- /dev/null +++ b/agency-indexes/DoE/PyMSI.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-15", + "metadataLastUpdated": "2024-04-15" + }, + "description": "A python package that helps with working with MSI Windows installers, by providing a library and utilities\nto read information from the file, extract embedded files, and update/write MSI files. Functionality is\nsimilar to https://wiki.gnome.org/msitools and https://github.com/mdsteele/rust-msi but written in pure\nPython so that it can easily be installed and used on a wider variety of systems.", + "laborHours": 288.8, + "languages": [], + "name": "PyMSI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nightlark/pymsi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyMTensor_1.0.0.json b/agency-indexes/DoE/PyMTensor_1.0.0.json new file mode 100644 index 00000000..d25c471a --- /dev/null +++ b/agency-indexes/DoE/PyMTensor_1.0.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2021-1654 O\nThe Python Material Tensor code (PyMTensor) applies crystal symmetries to arbitrary material tensors. It uses symbolic algebra to exactly determine the zero tensor components and the relationships between the nonzero components for all crystallographic point groups. It is capable of computing components of higher-order material tensors needed when treating nonlinear effects. It has a simple and flexible interface for inputting tensor rank information and any known symmetries between tensor indices.Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 562.4, + "languages": [ + "Python", + "Sage" + ], + "name": "PyMTensor 1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pymtensor", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyNetUQ.json b/agency-indexes/DoE/PyNetUQ.json new file mode 100644 index 00000000..01cbc238 --- /dev/null +++ b/agency-indexes/DoE/PyNetUQ.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-03-18", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2021-3242 O\nPyNetUQ is a Python library for network uncertainty propagation. Custom interface classes for components are modeled individually with potentially distinct simulation tools. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 972.8, + "languages": [ + "Python", + "SWIG", + "Assembly" + ], + "name": "PyNetUQ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PyNetUQ", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyNucleus.json b/agency-indexes/DoE/PyNucleus.json new file mode 100644 index 00000000..3ef5edde --- /dev/null +++ b/agency-indexes/DoE/PyNucleus.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "SAND2021-15054 O PyNucleus is a finite element code for nonlocal equations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python", + "C++" + ], + "name": "PyNucleus", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PyNucleus", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyOECP:_A_flexible_open-source_software_for_the_measurement_and_modeling_of_the_dielectric_spectrum_from_the_reflection_coefficient.json b/agency-indexes/DoE/PyOECP:_A_flexible_open-source_software_for_the_measurement_and_modeling_of_the_dielectric_spectrum_from_the_reflection_coefficient.json new file mode 100644 index 00000000..b38f2230 --- /dev/null +++ b/agency-indexes/DoE/PyOECP:_A_flexible_open-source_software_for_the_measurement_and_modeling_of_the_dielectric_spectrum_from_the_reflection_coefficient.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "We present PyOECP, a Python-based flexible open-source software for estimating and modeling the complex permittivity obtained from the open-ended coaxial probe (OECP) technique. The transformation of the measured reflection coefficient to complex permittivity is performed based on two different models, including the capacitance model and the antenna model. The software library contains dielectric spectra of common reference liquids, which can be used to transform the reflection coefficient into the dielectric spectra. Several Python routines that are commonly employed (e.g., SciPy and NumPy) are only required so that the users can alter the software structure depending on their needs. The modeling algorithm exploits the Markov chain Monte Carlo method for the data regression. The discrete relaxation models can be built by a proper combination of well-known relaxation models. In addition to these models, the electrode polarization, which is a common measurement artifact for interpreting the dielectric spectra, can be incorporated in the modeling algorithm. A continuous relaxation model, which solves the Fredholm integral equation of the first kind (a mathematically ill-posed problem) is also included.", + "laborHours": 0.0, + "languages": [], + "name": "PyOECP: A flexible open-source software for the measurement and modeling of the dielectric spectrum from the reflection coefficient", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tyoon124/PyOECP", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyPond.json b/agency-indexes/DoE/PyPond.json new file mode 100644 index 00000000..c63b3595 --- /dev/null +++ b/agency-indexes/DoE/PyPond.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "PyPond is a Python implementation of the JavaScript Pond timeseries library. At a very high level, both implementations offer classes and structures to collect, manipulate and transmit timeseries data. Time series transmission is done via a JSON-based wire format.", + "laborHours": 5016.0, + "languages": [], + "name": "PyPond", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/pypond/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/pypond", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyRIID_v.2.0.0.json b/agency-indexes/DoE/PyRIID_v.2.0.0.json new file mode 100644 index 00000000..3dd4b919 --- /dev/null +++ b/agency-indexes/DoE/PyRIID_v.2.0.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-06-29", + "metadataLastUpdated": "2022-10-17" + }, + "description": "SAND2021-8720 O PyRIID is a Python package that provides methods for generating gamma spectra synthetically and offers models that can input a gamma spectrum and predict what radioisotope is present in it. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525", + "laborHours": 0.0, + "languages": [ + "Python 3.5 +" + ], + "name": "PyRIID v.2.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyriid", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyROGUE_General_Purpose_Control_Server.json b/agency-indexes/DoE/PyROGUE_General_Purpose_Control_Server.json new file mode 100644 index 00000000..471a63c9 --- /dev/null +++ b/agency-indexes/DoE/PyROGUE_General_Purpose_Control_Server.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "This packages generates a general purpose control server interface to an FPGA using PyRogue.", + "laborHours": 486.4, + "name": "PyROGUE General Purpose Control Server", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pyrogue-control-server/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pyrogue-control-server", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/PySAM__Python_Wrapper_for_System_Advisor_Model_\"SAM\"__[SWR-19-57].json" "b/agency-indexes/DoE/PySAM__Python_Wrapper_for_System_Advisor_Model_\"SAM\"__[SWR-19-57].json" new file mode 100644 index 00000000..1b079397 --- /dev/null +++ "b/agency-indexes/DoE/PySAM__Python_Wrapper_for_System_Advisor_Model_\"SAM\"__[SWR-19-57].json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-09-03", + "metadataLastUpdated": "2023-07-07" + }, + "description": "PySAM is a Python wrapper for the National Renewable Energy Laboratory\u2019s System Advisor Model (SAM). SAM is a performance and financial model designed to facilitate decision making for people involved in the renewable energy industry. PySAM provides a native Python interface for the models found in SAM Simulation Core, SSC.", + "laborHours": 127999.2, + "languages": [ + "Python" + ], + "name": "PySAM (Python Wrapper for System Advisor Model \"SAM\") [SWR-19-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pysam", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v4.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PySCL.json b/agency-indexes/DoE/PySCL.json new file mode 100644 index 00000000..5f9892c8 --- /dev/null +++ b/agency-indexes/DoE/PySCL.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The PySCL (Python Standard Composition Library) is a library that provides a standard and consistent method of specifying the material mixtures for a given problem. The library enables software to use standard nuclide names and convenient naturally occurring composition and elemental abundances.", + "laborHours": 22055.2, + "languages": [ + "Python" + ], + "name": "PySCL", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/neams-workbench/PySCL", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PySTK:_Python-Based_Sampling_Toolkit.json b/agency-indexes/DoE/PySTK:_Python-Based_Sampling_Toolkit.json new file mode 100644 index 00000000..2114fce8 --- /dev/null +++ b/agency-indexes/DoE/PySTK:_Python-Based_Sampling_Toolkit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2022-01-11" + }, + "description": "Python-based Sampling Toolkit (PySTK) is a set of python functions developed for efficient data reduction via sampling for large-scale time-varying complex scientific datasets. PySTK provides a range of capabilities: starting from naive random sampling of data to a more sophisticated data-drives feature-preserving sampling for regular grid datasets. PySTK further includes the option of visualization the samples using open-source library Visualization ToolKit (VTK), reconstruction from the samples, and fast sample-based query mechanism for scientific datasets. PySTK is designed to be efficient yet extendable, as it strives to handle large datasets using primarily the Numpy-based operations. This toolkit uses the python-based multi-threading for effective use of available resources. Not only the big supercomputers, modern day laptops and desktops are used for data analysis purposes by the domain experts and data analysts. PySTK seamlessly enables the use of such hardware to handle big data sets. PySTK can be used to explore large datasets generated by HPC simulations with intelligent sampling algorithms and exploit the existing hardware for efficient data analysis. Aside from the sampling code, PySTK will further contain the related documentation, test/demo cases, details of its build system, unit test harness, and a scholarly bibliography.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "PySTK: Python-Based Sampling Toolkit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyTREES.json b/agency-indexes/DoE/PyTREES.json new file mode 100644 index 00000000..bee398f7 --- /dev/null +++ b/agency-indexes/DoE/PyTREES.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-09-15", + "metadataLastUpdated": "2022-09-22" + }, + "description": "PyTREES (Python tool for Training/Testing Robust Explainable Ensembles on Spectra) is software that implements a data-driven approach to predicting the amount of specific oxides present in materials samples of laser-induced breakdown spectroscopy (LIBS); such as from the ChemCam instrument suite onboard the NASA Curiosity rover. PyTREES is designed to input LIBS data in the format provided by the ChemCam team [1]. PyTREES then applies appropriate pre-processing to this data [2], and implements several regression methods for predicting oxides from spectra. The regression methods include: ensemble methods (random forest, extra trees, and gradient boosting regression) and blended submodels using the \u201cdouble blending\u201d technique. PyTREES additionally implements methods for quantifying the importance of features in regression model: (1) mean decrease in impurity (MDI) and (2) permutation importance to investigate the wavelengths used by the regression methods. [1] Gasda et al. (2021). Spectrochim Acta B, 181, 106223. [2] Clegg et al. (2017). Spectrochim Acta B , 129, 64\u201385.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "PyTREES", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyTorch_Circuit-Aware_Bit-Cell_Modeling.json b/agency-indexes/DoE/PyTorch_Circuit-Aware_Bit-Cell_Modeling.json new file mode 100644 index 00000000..dde9cb95 --- /dev/null +++ b/agency-indexes/DoE/PyTorch_Circuit-Aware_Bit-Cell_Modeling.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08549O\nPyTorch Circuit-Aware Bit-Cell Modeling, a Python library, demonstrates circuit-aware training for analog machine learning accelerators. Built upon PyTorch, this software provides hardware-aware versions of common neural network layers to mitigate non-ideal behavior from novel hardware. The software provides accurate forward and backward pass estimates for hardware-mapped neural networks that are implemented in crossbars (arrays) that contain a non-linear transistor selector device. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 3784.8, + "languages": [ + "python" + ], + "name": "PyTorch Circuit-Aware Bit-Cell Modeling", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyTorch_Implementation_of_Log-Additive_Convolutional_Neural_Networks.json b/agency-indexes/DoE/PyTorch_Implementation_of_Log-Additive_Convolutional_Neural_Networks.json new file mode 100644 index 00000000..bdf89098 --- /dev/null +++ b/agency-indexes/DoE/PyTorch_Implementation_of_Log-Additive_Convolutional_Neural_Networks.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This code is a collection of python code that defines, trains, and tests Log-Additive Convolutional Neural Networks. The model components and training routine are based on the PyTorch python library. The code implements the Log-Additive Convolutional Neural Networks as described in Pagendam et al. 2023. In addition to the Log-Additive Convolutional Neural Networks, this library also defines the Log-Normal Density loss function as described in Pagendam et al. 2023. Code from this paper is not publicly available, so the Pytorch implementation of this type of model is unique to this library.", + "laborHours": 744.8, + "languages": [], + "name": "PyTorch Implementation of Log-Additive Convolutional Neural Networks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pagendam-callis-groundwaterML", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyTrilinos.json b/agency-indexes/DoE/PyTrilinos.json new file mode 100644 index 00000000..18311892 --- /dev/null +++ b/agency-indexes/DoE/PyTrilinos.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-12" + }, + "description": "PyTrilinos is a Python interface to selected Trilinos packages. This makes Trilinos linear algebra classes, linear solvers, preconditioners, nonlinear solvers, eigensolvers, and tools available to Python programmers. This broadens the user base of Trilinos, and facilitates rapid prototyping of scientific codes and interactive manipulation of large, distributed data sets.", + "laborHours": 8344830.4, + "languages": [], + "name": "PyTrilinos", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyUtilib:_A_Pythos_Utility_Library_v._1.0.json b/agency-indexes/DoE/PyUtilib:_A_Pythos_Utility_Library_v._1.0.json new file mode 100644 index 00000000..d015748b --- /dev/null +++ b/agency-indexes/DoE/PyUtilib:_A_Pythos_Utility_Library_v._1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "PyUtilib is a collection of Python utilities that are used by Python packages developed at Sandia National Laboratories, including the Coopr and FAST Python packages. PyUtilib includes facilities for managing factories, subprocess management, interfacing with Excel, and applying numerical techniques.", + "laborHours": 14972.0, + "languages": [ + "Shell", + "Python" + ], + "name": "PyUtilib: A Pythos Utility Library v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyutilib", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyWSSecurity.json b/agency-indexes/DoE/PyWSSecurity.json new file mode 100644 index 00000000..49a676c1 --- /dev/null +++ b/agency-indexes/DoE/PyWSSecurity.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "PyWSSecurity provides a Python implementation of the XML Digital Signature standard. It also provides an implementation of WS-Secure Convresation protocol.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "PyWSSecurity", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyXAS.json b/agency-indexes/DoE/PyXAS.json new file mode 100644 index 00000000..93414291 --- /dev/null +++ b/agency-indexes/DoE/PyXAS.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "rgrandy@bnl.gov" + }, + "date": { + "created": "2020-03-02", + "metadataLastUpdated": "2020-03-02" + }, + "description": "An open-source package for 2D X-ray near-edge spectroscopy analysis", + "laborHours": 10761.6, + "languages": [ + "Python" + ], + "name": "PyXAS", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gmysage/pyxas", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PyXRF.json b/agency-indexes/DoE/PyXRF.json new file mode 100644 index 00000000..5daebdf1 --- /dev/null +++ b/agency-indexes/DoE/PyXRF.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "PyXRF is a python-based sophisticated fluorescence analysis package for fitting and visualizing X-ray fluorescence data.", + "laborHours": 12251.2, + "languages": [], + "name": "PyXRF", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/PyXRF/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/PyXRF", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pycheron.json b/agency-indexes/DoE/Pycheron.json new file mode 100644 index 00000000..cb44da67 --- /dev/null +++ b/agency-indexes/DoE/Pycheron.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2024-08-07" + }, + "description": "A clear way to increase current capabilities for seismic nuclear explosion monitoring is to supplement the global International Monitoring System (IMS) network with openly available stations. The quality of openly available data is typically much lower than that of the IMS, given the wide variety of experimental goals and deployment conditions. Incorporating additional stations without properly identifying and mitigating data quality problems can actually degrade overall monitoring capabilities. Towards that objective, Pycheron, a python-based library for seismic data quality control (QC) was developed. Pycheron began as a translation of the Incorporated Research Institutions for Seismology (IRIS) Modular Utility for STAtistical kNowledge Gathering (MUSTANG) package (written in R) into Python, but has grown into a stand-alone package that includes significant additional functionality. Pycheron is intended to be implemented at the beginning of the data processing pipeline. The objectives of the library are to: automatically assess data quality and instrumentation health; maintain the highest quality of data possible; identify specific and key problems; alert downstream processing algorithms to any degradation in quality; improve our ability to process orders of magnitudes more data; and, serve as a basic service that all data processing within our program builds upon. Pycheron calculates metrics characterizing quality over time as well as creating QC masks to identify each interval with a QC problem. SAND2019-11607 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 34124.0, + "languages": [ + "Python", + "CSS", + "Fortran" + ], + "name": "Pycheron", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pycheron", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/PylotDB_-_A_Database_Management,_Graphing,_and_Analysis_Tool_Written_in_Python.json b/agency-indexes/DoE/PylotDB_-_A_Database_Management,_Graphing,_and_Analysis_Tool_Written_in_Python.json new file mode 100644 index 00000000..b12baabf --- /dev/null +++ b/agency-indexes/DoE/PylotDB_-_A_Database_Management,_Graphing,_and_Analysis_Tool_Written_in_Python.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "PylotDB, written completely in Python, provides a user interface (UI) with which to interact with, analyze, graph data from, and manage open source databases such as MySQL. The UI mitigates the user having to know in-depth knowledge of the database application programming interface (API). PylotDB allows the user to generate various kinds of plots from user-selected data; generate statistical information on text as well as numerical fields; backup and restore databases; compare database tables across different databases as well as across different servers; extract information from any field to create new fields; generate, edit, and delete databases, tables, and fields; generate or read into a table CSV data; and similar operations. Since much of the database information is brought under control of the Python computer language, PylotDB is not intended for huge databases for which MySQL and Oracle, for example, are better suited. PylotDB is better suited for smaller databases that might be typically needed in a small research group situation. PylotDB can also be used as a learning tool for database applications in general.", + "laborHours": 64448.0, + "languages": [ + "Python" + ], + "name": "PylotDB - A Database Management, Graphing, and Analysis Tool Written in Python", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PYLOTDB", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pymplot:_An_open-source,_lightweight_plotting_package_based_on_Python_and_matplotlib.json b/agency-indexes/DoE/Pymplot:_An_open-source,_lightweight_plotting_package_based_on_Python_and_matplotlib.json new file mode 100644 index 00000000..be777bc1 --- /dev/null +++ b/agency-indexes/DoE/Pymplot:_An_open-source,_lightweight_plotting_package_based_on_Python_and_matplotlib.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-02" + }, + "description": "We develop a lightweight, easy-to-use plotting package based on Python and matplotlib for scalar data visualization. The package contains eight plotting functions that can efficiently and conveniently render one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) regular-grid scalar data into publication-quality figures of various formats. These plotting functions include plotting 1D scalar data as a curve or a set of colored scatter points, showing 2D regular-grid scalar data as an image, wiggles, or contours, and displaying 3D regular-grid scalar data as a volume or three orthogonal slices in the image or contour form. We develop this package to facilitate quick rendering of 1D, 2D and 3D scalar data into visually decent forms with simple commands and options. The package is also capable of rendering various fonts, subscripts, superscripts, and mathematical symbols on plots in a consistent manner. Example plots demonstrate the efficiency, convenience, and versatility of our plotting package in generating high-quality plots. We make our plotting package open-source at GitHub, a United States-based global company that provides hosting for software development version control.", + "laborHours": 0.0, + "languages": [], + "name": "Pymplot: An open-source, lightweight plotting package based on Python and matplotlib", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pymplot", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pynamic.json b/agency-indexes/DoE/Pynamic.json new file mode 100644 index 00000000..6ebe3248 --- /dev/null +++ b/agency-indexes/DoE/Pynamic.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Pynamic is a benchmark designed to test a system's ability to handle the Dynamic Linking and Loading requirements of Python-based scientific applications. This benchmark is developed to add a workload to our testing environment, workload that represents a newly emerging class of DLL behaviors. Pynamic builds on pyMPI, an MPI extension to Python. Our augmentation includes a code generator that automatically generates Python C-extension dummy codes and a glue layer that facilitates linking and loading of the generated dynamic modules into the resulting pyMPI. Pynamic is configurable, enabling modeling the static properties of a specific code. It does not, however, model any significant computations of the target and hence it is not subjected to the same level of control as the target code. In fact, HPC computer vendors and tool developers will be encouraged to add it to their testing suite once the code release is completed. An ability to produce and run this benchmark is an effective test for validating the capability of a compiler and a linker/loader as well as an OS kernel and other runtime systems of HPC computer vendors. In addition, the benchmark is designed as a stress test case for code development tools. Though Python has recently gained popularity in the HPC community, its heavy DLL operations have hindered certain HPC code development tools, notably parallel debuggers, from performing optimally.\n", + "laborHours": 14029.6, + "languages": [], + "name": "Pynamic", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pynamic", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pynta_v._1.0.0.json b/agency-indexes/DoE/Pynta_v._1.0.0.json new file mode 100644 index 00000000..6de97f04 --- /dev/null +++ b/agency-indexes/DoE/Pynta_v._1.0.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2021-02-17" + }, + "description": "SAND2021-1508 O\nThe Pynta code is designed to automatically characterize chemical reactions relevant to heterogeneous catalysis in which gas-phase molecules interact with crystal facets of a solid. It organizes multiple quantum chemistry calculations to carry out this task. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python 3", + "bash script" + ], + "name": "Pynta v. 1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zadorlab/pynta", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pyomo.json b/agency-indexes/DoE/Pyomo.json new file mode 100644 index 00000000..436436cf --- /dev/null +++ b/agency-indexes/DoE/Pyomo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "wehart@sandia.gov" + }, + "date": { + "created": "2018-02-08", + "metadataLastUpdated": "2020-09-01" + }, + "description": "The main repository for the Pyomo optimization modeling software.", + "laborHours": 314837.6, + "languages": [], + "name": "Pyomo", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pyomo/pyomo", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pyomo_Optimization_Example_Problems_v.1.0.json b/agency-indexes/DoE/Pyomo_Optimization_Example_Problems_v.1.0.json new file mode 100644 index 00000000..3fbaeb52 --- /dev/null +++ b/agency-indexes/DoE/Pyomo_Optimization_Example_Problems_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2021-10-01" + }, + "description": "This code is comprised of example problems to show implementation details of our SCITECH 2021 paper :Open-Source, Object-Oriented, Multi-Phase Pseudospectral Optimization Using Pyomo.\" Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2020-13973", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Pyomo Optimization Example Problems v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyomo_optimization_example_problems", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pyomo_v5.0.json b/agency-indexes/DoE/Pyomo_v5.0.json new file mode 100644 index 00000000..a0f9fc1a --- /dev/null +++ b/agency-indexes/DoE/Pyomo_v5.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Pyomo supports the formulation and analysis of mathematical models for complex optimization applications. This capability is commonly associated with algebraic modeling languages (AMLs), which support the description and analysis of mathematical models with a high-level language. Although most AMLs are implemented in custom modeling languages, Pyomo's modeling objects are embedded within Python, a full- featured high-level programming language that contains a rich set of supporting libraries.", + "laborHours": 0.0, + "languages": [ + "Python 2.6, 2.7, 3.4, 3.5" + ], + "name": "Pyomo v5.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pyomo/pyomo/releases/tag/5.0.1", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pyomo_v6.2.json b/agency-indexes/DoE/Pyomo_v6.2.json new file mode 100644 index 00000000..8b8353fd --- /dev/null +++ b/agency-indexes/DoE/Pyomo_v6.2.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-16", + "metadataLastUpdated": "2022-10-16" + }, + "description": "SAND2022-4010 O Pyomo supports the formulation and analysis of mathematical models for complex optimization applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 314837.6, + "languages": [ + "Python 2.6, 2.7, 3.4, 3.5" + ], + "name": "Pyomo v6.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Pyomo/pyomo", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "6.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Pyre.json b/agency-indexes/DoE/Pyre.json new file mode 100644 index 00000000..bc9d35f1 --- /dev/null +++ b/agency-indexes/DoE/Pyre.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "This is a Python port of\u00a0Zyre\u00a01.0, implementing the same\u00a0ZRE protocol. Pyre does local area discovery and clustering. A Pyre node broadcasts UDP beacons, and connects to peers that it finds. This class wraps a Pyre node with a message-based API.", + "laborHours": 1216.0, + "name": "Pyre", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pyre", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python-ARM_Radar_Toolkit.json b/agency-indexes/DoE/Python-ARM_Radar_Toolkit.json new file mode 100644 index 00000000..789ccf69 --- /dev/null +++ b/agency-indexes/DoE/Python-ARM_Radar_Toolkit.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Python-ARM Radar Toolkit (Py-ART) is a collection of radar quality control and retrieval codes which all work on two unifying Python objects: the PyRadar and PyGrid objects. By building ingests to several popular radar formats and then abstracting the interface Py-ART greatly simplifies data processing over several other available utilities. In addition Py-ART makes use of Numpy arrays as its primary storage mechanism enabling use of existing and extensive community software tools.", + "laborHours": 159980.0, + "name": "Python-ARM Radar Toolkit", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/pyart", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_Approximation_Toolbox__PyApprox__v._1.0.json b/agency-indexes/DoE/Python_Approximation_Toolbox__PyApprox__v._1.0.json new file mode 100644 index 00000000..aa44c776 --- /dev/null +++ b/agency-indexes/DoE/Python_Approximation_Toolbox__PyApprox__v._1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2020-11-04" + }, + "description": "PyApprox provides flexible and efficient tools for high-dimensional approximation and uncertainty quantification. PyApprox implements methods addressing various issues surrounding high-dimensional parameter spaces and limited evaluations of expensive simulation models with the goal of facilitating simulation-aided knowledge discovery, prediction and design. Tools are provided for: (i) building surrogates using polynomial chaos expansions using least squares, compressive sensing and interpolation; (ii) sparse grid interpolation and quadrature; (iii) low-rank tensor-decompositions; (iv) multi-fidelity approximation and sampling; (v) large-scale Bayesian inference; (vi) numerical solvers for canonical ordinary and partial differential equations useful for demonstration purposes; compressive sensing solvers (vii) and (viii) visualization. The code is intended to as a python toolbox but provides c++ code with Python interfaces to computationally expensive algorithms to increase performance. SANDS2019-5458 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. \n", + "laborHours": 48807.2, + "languages": [ + "C++", + "Python" + ], + "name": "Python Approximation Toolbox (PyApprox) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/pyapprox/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyapprox", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_Class_for_Github_Application_Development__Py-CGAD_.json b/agency-indexes/DoE/Python_Class_for_Github_Application_Development__Py-CGAD_.json new file mode 100644 index 00000000..719dd537 --- /dev/null +++ b/agency-indexes/DoE/Python_Class_for_Github_Application_Development__Py-CGAD_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "A python class has been developed to help streamline the creation of customizable Github applications Python Class for Github Application Development (Py-CGAD). Py-CGAD contains an interface for interacting with Github\u2019s RESTful API by automatically handling authentication and providing common functionality through simple methods. These methods include uploading files to a repository, posting and getting statuses among others. Py-CGAD is generic and can be used as a template for quickly building a variety of different application of interest to the mission of the lab and the public in general.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Python Class for Github Application Development (Py-CGAD)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_Codebase_and_Jupyter_Notebooks_-_Applications_of_Machine_Learning_Techniques_to_Geothermal_Play_Fairway_Analysis_in_the_Great_Basin_Region,_Nevada.json b/agency-indexes/DoE/Python_Codebase_and_Jupyter_Notebooks_-_Applications_of_Machine_Learning_Techniques_to_Geothermal_Play_Fairway_Analysis_in_the_Great_Basin_Region,_Nevada.json new file mode 100644 index 00000000..c6f55aee --- /dev/null +++ b/agency-indexes/DoE/Python_Codebase_and_Jupyter_Notebooks_-_Applications_of_Machine_Learning_Techniques_to_Geothermal_Play_Fairway_Analysis_in_the_Great_Basin_Region,_Nevada.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "emlawsky@unr.edu" + }, + "date": { + "created": "2023-09-06", + "metadataLastUpdated": "2023-09-06" + }, + "description": "Git archive containing Python modules and resources used to generate machine-learning models used in the \"Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada\" project. This software is licensed as free to use, modify, and distribute with attribution. Full license details are included within the archive. See \"documentation.zip\" for setup instructions and file trees annotated with module descriptions.", + "homepageURL": "https://dx.doi.org/10.15121/1897035", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Python Codebase and Jupyter Notebooks - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dx.doi.org/10.15121/1897035", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_Display_Manager.json b/agency-indexes/DoE/Python_Display_Manager.json new file mode 100644 index 00000000..89ef7d65 --- /dev/null +++ b/agency-indexes/DoE/Python_Display_Manager.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "pydm is a PyQt-based framework for building user interfaces for control systems. The goal is to provide a no-code, drag-and-drop system to make simple screens, as well as a straightforward python framework to build complex applications.", + "laborHours": 17586.4, + "name": "Python Display Manager", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pydm/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pydm", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_Display_Manager_Tutorial.json b/agency-indexes/DoE/Python_Display_Manager_Tutorial.json new file mode 100644 index 00000000..dc6c5797 --- /dev/null +++ b/agency-indexes/DoE/Python_Display_Manager_Tutorial.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-10", + "metadataLastUpdated": "2022-08-10" + }, + "description": "PyDM is a PyQt-based framework for building user interfaces for control systems. The goal is to provide a no-code, drag-and-drop system to make simple screens, as well as a straightforward python framework to build complex applications.", + "laborHours": 0.0, + "languages": [], + "name": "Python Display Manager Tutorial", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pydm-tutorial/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pydm-tutorial", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_GST_Implementation__PyGSTi__v._0.9.json b/agency-indexes/DoE/Python_GST_Implementation__PyGSTi__v._0.9.json new file mode 100644 index 00000000..e56cd912 --- /dev/null +++ b/agency-indexes/DoE/Python_GST_Implementation__PyGSTi__v._0.9.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2024-07-23" + }, + "description": "PyGSTi is a Python package for modeling and characterizing noise (errors) in small quantum information processors. In addition to being a basic framework for describing quantum circuits and noise models, it implements mainstream quantum characterization, verification, and validation (QCVV) protocols such as Gate Set Tomography (GST), Randomized Benchmarking (RB), Robust Phase Estimation, and Idle Tomography. It also implements prototype protocols used for timeseries analysis and crosstalk detection, all of which have the goal of better understanding the noise found in existing as-built experimental devices. The central protocol of pyGSTi (from where it derives its name) is Gate Set Tomography. GST is a theory and protocol for simultaneously estimating the state preparation, gate operations, and measurement effects of a physical system of one or many quantum bits (qubits). These estimates are based entirely on the statistics of experimental measurements, and their interpretation and analysis can provide a detailed understanding of the types of errors/imperfections in the physical system. In this way, GST provides not only a means of certifying the \u201cgoodness\u201d of qubits but also a means of debugging (i.e.\nimproving) them. The other protocols follow this similar pattern in that they use statistical inference and analysis of experimental data to estimate one or more properties of the noise in a\ndevice.", + "laborHours": 317619.2, + "languages": [ + "C++", + "CSS", + "HTML", + "Jupyter Notebook", + "Cython", + "Python" + ], + "name": "Python GST Implementation (PyGSTi) v. 0.9", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyGSTi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.9.12" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_GST_Implementation_v._0.9_beta.json b/agency-indexes/DoE/Python_GST_Implementation_v._0.9_beta.json new file mode 100644 index 00000000..d2298d73 --- /dev/null +++ b/agency-indexes/DoE/Python_GST_Implementation_v._0.9_beta.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "PyGSTi is an implementation of Gate Set Tomography in the python programming language. Gate Set Tomography (GST) is a theory and protocol for simultaneously estimating the state preparation, gate operations, and measurement effects of a physical system of one or many quantum bits (qubits). These estimates are based entirely on the statistics of experimental measurements, and their interpretation and analysis can provide a detailed understanding of the types of errors/imperfections in the physical system. In this way, GST provides not only a means of certifying the \"goodness\" of qubits but also a means of debugging (i.e. improving) them.", + "laborHours": 95425.6, + "name": "Python GST Implementation v. 0.9 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pyGSTio/pyGSTi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_HITMIX.json b/agency-indexes/DoE/Python_HITMIX.json new file mode 100644 index 00000000..0ae55370 --- /dev/null +++ b/agency-indexes/DoE/Python_HITMIX.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-15", + "metadataLastUpdated": "2024-10-15" + }, + "description": "SAND2024-10158O\nPython HITMIX is a software package for computing hitting time moments of vertices in a graph. Hitting time moments can be used to rank the strengths of relationships between vertices in a graph. Examples are provided for computing and using hitting time moments on generic graphs and similarity graphs arising from the analysis of text documents in information retrieval applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 243.2, + "languages": [ + "python" + ], + "name": "Python HITMIX", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/hitmix", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_ISMAGS_subgraph_isomorphism_algorithm.json b/agency-indexes/DoE/Python_ISMAGS_subgraph_isomorphism_algorithm.json new file mode 100644 index 00000000..deb933ef --- /dev/null +++ b/agency-indexes/DoE/Python_ISMAGS_subgraph_isomorphism_algorithm.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2023-08-08" + }, + "description": "SAND2022-14468 O\nThe Python ISMAGS subgraph isomorphism algorithm is a translation of a java-based algorithm. It used for finding unique occurrences of a motif subgraph within a larger network graph. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Python ISMAGS subgraph isomorphism algorithm", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ISMAGS-in-Python", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_Library_For_Vehicular_Emission_Estimation.json b/agency-indexes/DoE/Python_Library_For_Vehicular_Emission_Estimation.json new file mode 100644 index 00000000..1ce3b4bb --- /dev/null +++ b/agency-indexes/DoE/Python_Library_For_Vehicular_Emission_Estimation.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2023-03-13" + }, + "description": "PyEmission is a Python library for estimation of vehicular emissions and fuel consumption. This tool covers a wide range of light duty motor vehicles including passenger car, SUV, passenger truck, and light commercial truck. The tool only takes second-by-second driving cycle and vehicle characteristics data as inputs and generate results of vehicular emissions (CO2, CO, NOx, and HC) and fuel consumption.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Python Library For Vehicular Emission Estimation", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/PyEmission", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_Lua_Benchmarks.json b/agency-indexes/DoE/Python_Lua_Benchmarks.json new file mode 100644 index 00000000..c5a42435 --- /dev/null +++ b/agency-indexes/DoE/Python_Lua_Benchmarks.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is an adaptation of the pre-existing Scimark benchmark code to a variety of Python and Lua implementations. It also measures performance of the Fparser expression parser and C and C++ code on a variety of simple scientific expressions.", + "laborHours": 5654.4, + "name": "Python/Lua Benchmarks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/lebusby/splb/src/e1b801db07cbb8fd0eab2a50fdb3b1f25906fbef/Copyright", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/lebusby/splb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_Residual_Stress_Analysis__pyRS_.json b/agency-indexes/DoE/Python_Residual_Stress_Analysis__pyRS_.json new file mode 100644 index 00000000..b497f2c6 --- /dev/null +++ b/agency-indexes/DoE/Python_Residual_Stress_Analysis__pyRS_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "fanchercm@ornl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "pyRS is a python software package that was designed to meet the data reduction and analysis needs of the neutron residual stress mapping user community at Oak Ridge National Laboratory (ORNL). pyRS incorporates separate modules that provide a streamlined workflow for reducing raw neutron events into 1D intensity vs. scattering angle and subsequent analysis to extract the interatomic spacing and intensity for residual stress and texture analysis. Users can access the modules through either a graphical or command-line interface. pyRS saves data into a single HDF5 file, in which the metadata, reduced diffraction data, and peak analysis results are passed between different modules.", + "laborHours": 0.0, + "languages": [], + "name": "Python Residual Stress Analysis (pyRS)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/neutrons/PyRS.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_Robust_Phase_Estimation__PyRPE_.json b/agency-indexes/DoE/Python_Robust_Phase_Estimation__PyRPE_.json new file mode 100644 index 00000000..f85457c2 --- /dev/null +++ b/agency-indexes/DoE/Python_Robust_Phase_Estimation__PyRPE_.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2024-08-07" + }, + "description": "Robust Phase Estimation (RPE) is a quantum algorithm to determine the relative phases of eigenstates of a unitary operator. This code implements the classical portion of the RPE algorithm, useful both in simulation (e.g., Sandia's pyGSTi or IBM's Qiskit simulators) and on actual quantum hardware (e.g., IBM's Qiskit Quantum Experience). It additionally implements improvements in these dependent software packages, for both required core function of the RPE and improved usability. SAND2020-12547 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 91.2, + "languages": [ + "Python" + ], + "name": "Python Robust Phase Estimation (PyRPE)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyRPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_catemis_package_for_DARHT_Axis-II_Dispenser-Cathode_Emissivity_and_Temperature_Analysis.json b/agency-indexes/DoE/Python_catemis_package_for_DARHT_Axis-II_Dispenser-Cathode_Emissivity_and_Temperature_Analysis.json new file mode 100644 index 00000000..5e977c22 --- /dev/null +++ b/agency-indexes/DoE/Python_catemis_package_for_DARHT_Axis-II_Dispenser-Cathode_Emissivity_and_Temperature_Analysis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-05-09", + "metadataLastUpdated": "2022-05-09" + }, + "description": "The catemis python package includes the analysis methods used in paper \"DARHT Axis-II Dispenser-Cathode Emissivity and Temperature\", which was presented at the 2021 Weapons Engineering Symposium and Journal (WESJ) hosted by Los Alamos National Laboratory. The paper (LA-UR-21-25647) and presentation (LA-UR-21-28231) report on a temperature and emissivity model that has been developed and applied to data from diagnostics used to measure the surface temperature of the DARHT Axis-II hot dispenser cathode over more than a decade of operation. The catemis package provides all the methods used in reporting these results along with the data files used to create the plots and tables in the paper. This includes methods for loading and processing FAR spectral pyrometer data along with methods for temperature calibration of cathode images.", + "laborHours": 0.0, + "languages": [], + "name": "Python catemis package for DARHT Axis-II Dispenser-Cathode Emissivity and Temperature Analysis", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/koglin-LANL/catemis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Python_codes_for_the_paper_-__\"Trade-offs_in_the_latent_representation_of_microstructure_evolution\".json" "b/agency-indexes/DoE/Python_codes_for_the_paper_-__\"Trade-offs_in_the_latent_representation_of_microstructure_evolution\".json" new file mode 100644 index 00000000..811074ae --- /dev/null +++ "b/agency-indexes/DoE/Python_codes_for_the_paper_-__\"Trade-offs_in_the_latent_representation_of_microstructure_evolution\".json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-06", + "metadataLastUpdated": "2024-06-11" + }, + "description": "SAND2024-00946O\nPython codes used in \"Trade-offs in the latent representation of microstructure evolution,\" a manuscript accepted for publication in Acta Materialia, are part of a repository. The code was developed to perform analysis of microstructure evolution. \n\nThe repository consists of two main directories: models, which train and test models such as autoencoders and diffusion maps, and analysis, which analyzes microstructures. Source code is used to perform dimensionality reduction of microstructure data for analysis of its evolution in time. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Python codes for the paper - \"Trade-offs in the latent representation of microstructure evolution\"", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_import_replacement.json b/agency-indexes/DoE/Python_import_replacement.json new file mode 100644 index 00000000..ddc915ac --- /dev/null +++ b/agency-indexes/DoE/Python_import_replacement.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "SmartImport.py is a Python source-code file that implements a replacement for the standard Python module importer. The code is derived from knee.py, a file in the standard Python diestribution , and adds functionality to improve the performance of Python module imports in massively parallel contexts.", + "laborHours": 243.2, + "name": "Python import replacement", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/langton/MPI_Import", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/langton/mpi_import", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_interface_generator_for_Fortran_based_codes__a_code_development_aid_.json b/agency-indexes/DoE/Python_interface_generator_for_Fortran_based_codes__a_code_development_aid_.json new file mode 100644 index 00000000..019b3367 --- /dev/null +++ b/agency-indexes/DoE/Python_interface_generator_for_Fortran_based_codes__a_code_development_aid_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Forthon generates links between Fortran and Python. Python is a high level, object oriented, interactive and scripting language that allows a flexible and versatile interface to computational tools. The Forthon package generates the necessary wrapping code which allows access to the Fortran database and to the Fortran subroutines and functions. This provides a development package where the computationally intensive parts of a code can be written in efficient Fortran, and the high level controlling code can be written in the much more versatile Python language.", + "laborHours": 3906.4, + "name": "Python interface generator for Fortran based codes (a code development aid)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/dpgrote/Forthon/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dpgrote/Forthon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_package_for_machine-readable_access_to_PDG_data__PDG_Python_API__v0.1.json b/agency-indexes/DoE/Python_package_for_machine-readable_access_to_PDG_data__PDG_Python_API__v0.1.json new file mode 100644 index 00000000..722ca29e --- /dev/null +++ b/agency-indexes/DoE/Python_package_for_machine-readable_access_to_PDG_data__PDG_Python_API__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "This Python package implements a high-level interface to access the data published by the Particle Data Group (PDG) in the Review of Particle Physics (the \"Review\").\n\nThe Particle Data Group is an international collaboration led by the PDG group at LBNL. The PDG summarizes the established knowledge in the field of particle physics in a single publication, the Review of Particle Physics. The Review is published and updated online (see https://pdg.lbl.gov) each year, and published in a scientific journal every other year. It is currently licensed under a CC BY-NC 4.0 license. In 2021 PDG was designated by the Office of Science as a SC PuRe Data Resource. The Review is one of the most highly cited publications in the field of particle physics.\n\nThe PDG Python API is part of PDG's efforts to make all data provided in the Review available in machine-readable format. This data includes the PDG world averages (or best limits) on particle masses, widths or lifetimes, branching fractions, magnetic moments, form factors, coupling constant ratios, and searches, as well as particle quantum numbers. It also includes detailed information on how PDG arrived at its averages, such as e.g. tables of published measurements with comments and footnotes, information on the consistency of published measurements, and detailed fit information.", + "laborHours": 988.0, + "languages": [], + "name": "Python package for machine-readable access to PDG data (PDG Python API) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/particledatagroup/api", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Python_wrapper_library_and_analysis_functions_for_Geotab_Altitude_API_[SWR-24-77].json b/agency-indexes/DoE/Python_wrapper_library_and_analysis_functions_for_Geotab_Altitude_API_[SWR-24-77].json new file mode 100644 index 00000000..2d0072c8 --- /dev/null +++ b/agency-indexes/DoE/Python_wrapper_library_and_analysis_functions_for_Geotab_Altitude_API_[SWR-24-77].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-09-30" + }, + "description": "This software library serves as a Python wrapper for Geotab's Altitude API. It streamlines querying of the API, converts loosely structured API outputs into a standardized tabular data format, and enables analysis of the resulting data tables. It also includes example notebooks showing how to use the library.", + "laborHours": 668.8, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "Python wrapper library and analysis functions for Geotab Altitude API [SWR-24-77]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Geotab_Altitude_Wrapper", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QASMTrans.json b/agency-indexes/DoE/QASMTrans.json new file mode 100644 index 00000000..68479fbc --- /dev/null +++ b/agency-indexes/DoE/QASMTrans.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A transpiler that incorporates several key features. It includes a mapping and routing method, a\nprocess for decomposing gates into basis gates compatible with IBM machines, and a remapping method designed to\nenhance simulation performance. Compared to the state-of-art transpiler qiskit, we have dramatically speed up in various\nbenchmarks.", + "laborHours": 0.0, + "languages": [], + "name": "QASMTrans", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/qasmtrans", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QBTNs_-_Quantum_Boolean_Tensor_Networks.json b/agency-indexes/DoE/QBTNs_-_Quantum_Boolean_Tensor_Networks.json new file mode 100644 index 00000000..d133fecd --- /dev/null +++ b/agency-indexes/DoE/QBTNs_-_Quantum_Boolean_Tensor_Networks.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "We develop algorithms and software that uses the D-Wave 2000Q quantum annealer to solve several types of Boolean tensor factorization problems. Boolean tensor factorization refers to the problem of representing a high-dimensional tensor filled with Boolean values as a product of smaller Boolean core tensors and Boolean matrices. We consider different tensor factorization models, including Boolean Tensor Train, Boolean Tucker, and Boolean Hierarchical Tucker. As an exact decomposition of a given type may not exist in the general case, the objective is to minimize the difference between the input high-dimensional tensor and the product of the lower-dimensional tensors of the proposed factorization, using a specified tensor norm. In our approach, we reduce the Boolean tensor factorization problem to a sequence of quadratic unconstrained binary optimization problems suitable for the D-Wave 2000Q quantum annealer. Although current quantum technology is still fairly restricted in the problems it can tackle, we show that complex tensor factorization problems as the ones addressed by us can be solved efficiently and accurately.", + "laborHours": 0.0, + "languages": [], + "name": "QBTNs - Quantum Boolean Tensor Networks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyQBTNs", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QC-GN2OMS2.json b/agency-indexes/DoE/QC-GN2OMS2.json new file mode 100644 index 00000000..43cf2e4b --- /dev/null +++ b/agency-indexes/DoE/QC-GN2OMS2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The QC-GN2OMS2 neural network was designed to predict mass spectra better than currently available approaches. Fundamentally the neural net is designed to input the structure of a molecule and collision energy value then output a spectra datafile for the end user. This software is able to make predictions orders of magnitude faster (milliseconds) than QC methods and with 50-60% greater accuracy than rules approaches.", + "laborHours": 0.0, + "languages": [], + "name": "QC-GN2OMS2", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-m-q/qcgnoms", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QCD_For_Intel_R__Xeon_Phi_tm__and_Xeon_tm__processors.json b/agency-indexes/DoE/QCD_For_Intel_R__Xeon_Phi_tm__and_Xeon_tm__processors.json new file mode 100644 index 00000000..41039973 --- /dev/null +++ b/agency-indexes/DoE/QCD_For_Intel_R__Xeon_Phi_tm__and_Xeon_tm__processors.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kindrew@jlab.org" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This library provides a library containing highly optimized Wilson-Dslash, Wilson Clover operator and Krylov subspace solvers for Lattice QCD simulations. The library is targeted at Intel(R) Xeon Phi(tm), and Intel(R) Xeon(tm) processors.", + "laborHours": 70041.6, + "name": "QCD For Intel(R) Xeon Phi(tm) and Xeon(tm) processors", + "organization": "Thomas Jefferson National Accelerator Facility (TJNAF)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/JeffersonLab/qphix/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JeffersonLab/qphix.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Thomas Jefferson National Accelerator Facility (TJNAF)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QCI_Common.json b/agency-indexes/DoE/QCI_Common.json new file mode 100644 index 00000000..cbfc4092 --- /dev/null +++ b/agency-indexes/DoE/QCI_Common.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "There are many common software patterns and utilities for the ORNL Quantum Computing Institute that can and should be shared across projects. Otherwise we find duplication of code which adds unwanted complexity. This is a software product seeks to alleviate this by providing common utilities such as object factories, graph data structures, parameter input mechanisms, etc., for other software products within the ORNL Quantum Computing Institute. 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"metadataLastUpdated": "2023-01-05" + }, + "description": "QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support.", + "laborHours": 0.0, + "languages": [ + "C++17" + ], + "name": "QMCPACK v3.14.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/NCSA", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QMCPACK/qmcpack/releases/tag/v3.14.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v3.14.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QMCPACK_v3.15.0.json b/agency-indexes/DoE/QMCPACK_v3.15.0.json new file mode 100644 index 00000000..cbba7366 --- /dev/null +++ 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portable GPU support.", + "laborHours": 1334484.0, + "languages": [ + "C++17" + ], + "name": "QMCPACK v4.0.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/license/uoi-ncsa-php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/QMCPACK/qmcpack", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v4.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QMP.json b/agency-indexes/DoE/QMP.json new file mode 100644 index 00000000..45a2ce13 --- /dev/null +++ b/agency-indexes/DoE/QMP.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "bjoo@jlab.org" + }, + "date": { + "created": "2018-05-08", + "metadataLastUpdated": "2018-05-08" + }, + "description": "QMP Message Passing Library. 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Generates Kernels for Wilson-Dslash, and Wilson-Clover kernels. 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It can be used to perform queries useful for data analysis of the accounting data alone or for integrative analysis in the context of a larger query.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "gcc/4.8 or higher" + ], + "name": "QQACCT", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/QStone.json b/agency-indexes/DoE/QStone.json new file mode 100644 index 00000000..72dff778 --- /dev/null +++ b/agency-indexes/DoE/QStone.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "coellopereea@ornl.gov" + }, + "date": { + "created": "2025-02-25", + "metadataLastUpdated": "2025-02-25" + }, + "description": "An utility to benchmark the quality of an HPC and Quantum Computers integration. The benchmark allows the definition of a set of users for which a set of configurable quantum applications will be randomly selected. Example of currently supported quantum applications: VQE, PyMatching, RB. Users can create custom applications and use them together with the core applications. QStone generates different portable files (.tar.gz), each supporting a different user and a different scheduler (currently supporting: slurm, lsf, bare_metal). During execution of the benchmark, QStone gathers information on each steps of the applications, allowing investigations on bottlenecks and/or resource constraints at the interface between Quantum and HPC.", + "laborHours": 1611.2, + "languages": [ + "Python" + ], + "name": "QStone", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/riverlane/QStone", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.2.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QTENSOR.json b/agency-indexes/DoE/QTENSOR.json new file mode 100644 index 00000000..e91862cf --- /dev/null +++ b/agency-indexes/DoE/QTENSOR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-11-09", + "metadataLastUpdated": "2022-01-05" + }, + "description": "QTensor is a quantum circuit simulator designed to run efficiently in parallel mode on large supercomputers. It is based on the tensor network representation of quantum circuits. The simulator is flexible and agnostic to both the connectivity map of the quantum device and the types of gates used in the circuit.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "QTENSOR", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/QUESTS:_Quick_Uncertainty_and_Entropy_from_STructural_Similarity.json b/agency-indexes/DoE/QUESTS:_Quick_Uncertainty_and_Entropy_from_STructural_Similarity.json new file mode 100644 index 00000000..c1973493 --- /dev/null +++ b/agency-indexes/DoE/QUESTS:_Quick_Uncertainty_and_Entropy_from_STructural_Similarity.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-08", + "metadataLastUpdated": "2024-09-12" + }, + "description": "QUESTS provides a strategy to quantify the uncertainty and the information content (entropy) of datasets\nof atomistic simulations. The code implements the calculation of a descriptor, compares information\ncontents of datasets, verifies whether given structures are contained in specific datasets, and more. This\ncode base enables better design of training sets for machine learning force fields as well as\nunderstanding some thermodynamic properties of materials.", + "laborHours": 714.4, + "languages": [], + "name": "QUESTS: Quick Uncertainty and Entropy from STructural Similarity", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dskoda/quests", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QUE_LDRD_Tools.json b/agency-indexes/DoE/QUE_LDRD_Tools.json new file mode 100644 index 00000000..764a7d9b --- /dev/null +++ b/agency-indexes/DoE/QUE_LDRD_Tools.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Experiment scripts and analysis tools created for the QUE LDRD. SAND2020-12250 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 866.4, + "languages": [ + "Shell", + "Python" + ], + "name": "QUE LDRD Tools", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/que-ldrd-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QUO.json b/agency-indexes/DoE/QUO.json new file mode 100644 index 00000000..7000a0b3 --- /dev/null +++ b/agency-indexes/DoE/QUO.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "QUO (as in \"status quo\") is a runtime library that aids in accommodating thread-level heterogeneity in dynamic, phased MPI+X applications comprising single- and multi-threaded libraries.", + "laborHours": 77869.6, + "languages": [], + "name": "QUO", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/libquo", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QUiNN.json b/agency-indexes/DoE/QUiNN.json new file mode 100644 index 00000000..092640e3 --- /dev/null +++ b/agency-indexes/DoE/QUiNN.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-13", + "metadataLastUpdated": "2023-08-13" + }, + "description": "SAND2023-05484O\nQuantification of Uncertainties in Neural Networks (QUiNN) is a python library centered around various probabilistic wrappers over PyTorch modules in order to provide uncertainty estimation in neural network (NN) predictions. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "QUiNN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/quinn", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QVPRO.json b/agency-indexes/DoE/QVPRO.json new file mode 100644 index 00000000..d7da28ed --- /dev/null +++ b/agency-indexes/DoE/QVPRO.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "diazab@nv.doe.gov" + }, + "date": { + "created": "2022-01-20", + "metadataLastUpdated": "2022-01-20" + }, + "description": "QuickView PRO (QVPRO) is similar to QuickView but designed to focus on analysis. QuickView was designed for visualization only, adding analysis capabilities later. This made QuickView complicated when using it as an analysis tool. QVPRO uses the same analysis algorithms in a more streamlined workflow and has a user friendly GUI. QVPRO provides the unique capability of analyzing Photonic Doppler Velocimetry (PDV) data records from different PDV systems and still allows for processing hundreds of PDV data records in a practical manner.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "QVPRO", + "organization": "Nevada National Security Site/Mission Support and Test Services LLC (MSTS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://gitlab.osti.gov/doecode/dc-31683", + "status": "Development", + "tags": [ + "DOE CODE", + "Nevada National Security Site/Mission Support and Test Services LLC (MSTS)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Qbox_First-principles_Molecular_Dynamics__Qball_branch,_svn_release_081.json b/agency-indexes/DoE/Qbox_First-principles_Molecular_Dynamics__Qball_branch,_svn_release_081.json new file mode 100644 index 00000000..21952463 --- /dev/null +++ b/agency-indexes/DoE/Qbox_First-principles_Molecular_Dynamics__Qball_branch,_svn_release_081.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Qball is a modified version of the open source Qbox first-principles molecular dynamics code which was originally developed at LLNL by Francois Gygi.", + "laborHours": 3030135.2, + "name": "Qbox First-principles Molecular Dynamics (Qball branch, svn release 081", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/qball", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Qthreads.json b/agency-indexes/DoE/Qthreads.json new file mode 100644 index 00000000..3ff4277f --- /dev/null +++ b/agency-indexes/DoE/Qthreads.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The qthread library provides a software mechanism for programs to execute a large number of run-to-completion threads at low cost. It provides the ability to perform lightweight synchronization on memory locations. Finally, modules within the library (\"futurelib\", \"qloop\", and \"qutil\") provide the optional ability to manage the number of threads created in C and C++ by providing parallel loop constructs.", + "laborHours": 47393.6, + "languages": [ + "C++", + "C", + "HMTL", + "Makefile", + "Assembly", + "M4" + ], + "name": "Qthreads", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/qthreads?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/qthreads", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QuCLEAR.json b/agency-indexes/DoE/QuCLEAR.json new file mode 100644 index 00000000..b46107b7 --- /dev/null +++ b/agency-indexes/DoE/QuCLEAR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2025-02-23", + "metadataLastUpdated": "2025-02-23" + }, + "description": "SF-25-008 This software optimizes quantum circuits using a two-step process. The first step, Clifford Extraction, moves the Clifford gates to the end of the circuit and includes circuit\noptimizations. The second step, Clifford Absorption, then addresses these extracted gates on a classical computer. By reducing the number of gates that need to run on the quantum device, the software achieves a significantly lower gate count.", + "laborHours": 66956.0, + "languages": [], + "name": "QuCLEAR", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/revilooliver/QuCLEAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QuEST_v._1.6.json b/agency-indexes/DoE/QuEST_v._1.6.json new file mode 100644 index 00000000..ac402699 --- /dev/null +++ b/agency-indexes/DoE/QuEST_v._1.6.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2024-08-07" + }, + "description": "QuESt is an open source, Python-based application suite for energy storage simulation and analysis. The initial release will include an application for energy storage valuation, an analysis where the maximum revenue of a hypothetical energy storage device is estimated using historical energy market data. This is done by determining the sequence of state of charge management actions that optimize revenue generation, assuming perfect foresight of the historical data. The initial release will also include a utility to obtain historical data directly from supported market operating entities for use in analysis. More applications will be added as they are developed. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python", + "CSS", + "HTML", + "Batchfile", + "kvlang", + "JavaScript" + ], + "name": "QuEST v. 1.6", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/snl-quest", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.6" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QuESt_Equity_v.1.json b/agency-indexes/DoE/QuESt_Equity_v.1.json new file mode 100644 index 00000000..fc4145a8 --- /dev/null +++ b/agency-indexes/DoE/QuESt_Equity_v.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08793O\nQuESt Equity cross-references several public databases for power plant pollution and demographics to assess energy equity and environmental justice for energy storage projects. It also calculates the impacts of power plant pollution in disadvantaged communities. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 387828.0, + "languages": [ + "Python" + ], + "name": "QuESt Equity v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/snl-quest-equity", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Qualm.json b/agency-indexes/DoE/Qualm.json new file mode 100644 index 00000000..ac1c3131 --- /dev/null +++ b/agency-indexes/DoE/Qualm.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-01-14", + "metadataLastUpdated": "2022-01-14" + }, + "description": "To date, quantitative prediction on CPUs has been limited to laborious `white-box' methods\u037e and learning has been limited to special cases such as best-case (throughput) performance. We present Qualm, a method for learning quantitative performance of optimized latency", + "laborHours": 0.0, + "languages": [], + "name": "Qualm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/perf-lab/qualm/qualm", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QuanSimBench.json b/agency-indexes/DoE/QuanSimBench.json new file mode 100644 index 00000000..6b372bdc --- /dev/null +++ b/agency-indexes/DoE/QuanSimBench.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "QuanSimBench is a software program that performs a gate-by-gate simulation of a quantum computer with a full state vector formulation. It simulates a simplified version of Shor's algorithm with increasing number of qubits until resources are exhausted. The score (states/s) is how fast the Approximate Quantum Fourier Transform can be computed (the modular exponentiation is not timed). The goal is to quantify the ability of a computer to simulate ideal quantum circuits.", + "laborHours": 0.0, + "languages": [], + "name": "QuanSimBench", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/datavortex/QuanSimBench", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quandary.json b/agency-indexes/DoE/Quandary.json new file mode 100644 index 00000000..35974214 --- /dev/null +++ b/agency-indexes/DoE/Quandary.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "Quandary numerically simulates and optimizes the time-evolution of open quantum systems. The underlying dynamics are modelled by Lindblad's master equation, a linear ordinary differential equation (ODE) describing quantum systems interacting with the environment. Quandary solves this ODE numerically by applying a time-stepping integration scheme, and utilizes a gradient-based optimization approach to determine optimal control pulses that drive the quantum system to a desired target state. Two optimization objectives are considered: (a) Unitary gate optimization that finds controls to realize a unitary gate transformation, and (b) optimal reset that aims to drive the quantum system to the ground states. Gradient-based optimization schemes utilizing Petsc's Tao optimization package are applied to generate control pulses that minimize the respective measure. To evaluate the gradient of the objective function, the discrete adjoint method is used while leveraging techniques from Algorithmic Differentiation to produce exact and consistent gradients. To mitigate excessive execution run times, the software can be build together with the XBraid software library which provides a parallelization strategy to distribute the time-evolution of the underlying dynamics onto multiple processor.", + "laborHours": 0.0, + "languages": [], + "name": "Quandary", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/quandary", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantifying_uncertainty_in_Pareto_estimates_of_global_lake_area.json b/agency-indexes/DoE/Quantifying_uncertainty_in_Pareto_estimates_of_global_lake_area.json new file mode 100644 index 00000000..9e7d449a --- /dev/null +++ b/agency-indexes/DoE/Quantifying_uncertainty_in_Pareto_estimates_of_global_lake_area.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-02-24", + "metadataLastUpdated": "2023-02-24" + }, + "description": "This software contains the code for Bayesian uncertainty analysis of global lake area. Computed uncertainties are compared against more conventional estimation using lake size-abundance distributions. Routines are included to explore sensitivity to observational errors and ad-hoc \"censoring\" strategies.", + "laborHours": 0.0, + "languages": [], + "name": "Quantifying uncertainty in Pareto estimates of global lake area", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VeinsOfTheEarth/pareto_lake_area", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantile_Kriging_R_Package.json b/agency-indexes/DoE/Quantile_Kriging_R_Package.json new file mode 100644 index 00000000..6561ad87 --- /dev/null +++ b/agency-indexes/DoE/Quantile_Kriging_R_Package.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-02", + "metadataLastUpdated": "2019-12-02" + }, + "description": "A re-implementation of Quantile Kriging.\n\nQuantile Kriging was described by Matthew Plumlee & Rui Tuo in their 2014 paper \"Building Accurate Emulators for Stochastic Simulations via Quantile Kriging.\" \n\nWith computational savings when dealing with replication from the recent paper \"Practical heteroskedastic Gaussian process modeling for large simulation experiments\u201d, it is now possible to apply Quantile Kriging to a wider class of problems. \n\nIn addition to fitting the model, other useful tools are provided such as the ability to automatically perform leave-one-out cross validation.", + "laborHours": 288.8, + "languages": [], + "name": "Quantile Kriging R Package", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/quantkriging", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantitative_Uncertainty_Analysis_for_Diffraction.json b/agency-indexes/DoE/Quantitative_Uncertainty_Analysis_for_Diffraction.json new file mode 100644 index 00000000..68ce192f --- /dev/null +++ b/agency-indexes/DoE/Quantitative_Uncertainty_Analysis_for_Diffraction.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Current software uses a least squares statistical method. For each model parameter, current software yields a point estimate and estimated standard error for each point estimate. In contrast, we have employed a Bayesian approach with sampling algorithm to provide a full posterior probability density function on each model parameter. This yields a different type of solution (probabilistic) with better fidelity. The Quantitative Uncertainty Analysis for Diffraction (QUAD) package returns a matrix of affect model parameters as a function of iteration through the MCMC analysis. QUAD is a Python code that allows for analysis of X-ray and neutron diffraction data to infer the structure of materials with quantifiable certainty. The code uses Bayesian statistics and Markov chain sampling algorithms to create posterior probability distributions on all material structure parameters that are modeled by a researcher. The statistical packages use the open source GSASII project as a library to calculate model diffraction patterns.", + "laborHours": 653.6, + "languages": [ + "Python" + ], + "name": "Quantitative Uncertainty Analysis for Diffraction", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/rabroughton/QUAD/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rabroughton/QUAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantitative_Universal_Option_Prioritizer__QUOP__v1.0.0.json b/agency-indexes/DoE/Quantitative_Universal_Option_Prioritizer__QUOP__v1.0.0.json new file mode 100644 index 00000000..f9b27032 --- /dev/null +++ b/agency-indexes/DoE/Quantitative_Universal_Option_Prioritizer__QUOP__v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-07-06", + "metadataLastUpdated": "2023-07-06" + }, + "description": "\tQuantitative Universal Option Prioritizer (QUOP) is a three-layer analytical hierarchy process (AHP) based multi-criteria decision-making option evaluation and prioritization tool. Decision-making often entails evaluation of options. Such competing options can either be mutual substitutes or cumulative means to achieve an objective. The options themselves can be methods, tools, technologies, processes, etc. Stakeholders involved in achieving the objective may view each option characteristic differently, depending on their needs and preferences. The QUOP tool enables a streamlined quantitative collaborative process of weighing the opinion of each stakeholder in evaluating the options. The evaluation may also be performed under different scenarios, for instance, various option potential estimates, prices, or end-user demand projections. The QUOP tool can find application in both public and private sectors, as well as on an individual level. The major advantage of using the QUOP decision-making tool is in documenting the quantified stakeholder opinion, therefore the background to each decision made, while simultaneously maintaining high transparency and stakeholder involvement. The tool is particularly suitable for decisions involving a high number of options and option characteristics, that is, aspects of each option that matter to the stakeholders", + "laborHours": 0.0, + "languages": [], + "name": "Quantitative Universal Option Prioritizer (QUOP) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/QUOP", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantitative_analysis_method_for_multi-color_microscopy.json b/agency-indexes/DoE/Quantitative_analysis_method_for_multi-color_microscopy.json new file mode 100644 index 00000000..b65dfbbd --- /dev/null +++ b/agency-indexes/DoE/Quantitative_analysis_method_for_multi-color_microscopy.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "We developed an analysis framework for quantitatively interpreting results from multi-color fluorescence microscopy data. When the emission signal from fluorescent probes (i.e. from biological microscopy or in single-particle microscopy) is spectrally separated before detection, the resulting signals contain information about the strengths of each probe. We built a model to deconvolve the raw data into quantitative descriptions of either of the wavelength of a single probe or the relative strengths among multiple probes. This approach requires only spectrally separating the image data into two or more channels, as opposed to fully resolving the spectral profile, thus allowing other microscopy techniques to be used simultaneously. Our analysis framework incorporates the response features of the optical and imaging elements used to produce the spectral separation, yielding highly quantitative interpretations of the underlying behaviors that give rise to the data.", + "laborHours": 0.0, + "languages": [], + "name": "Quantitative analysis method for multi-color microscopy", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ryand-LANL/DualColorAnalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantities_need_Representation,_Unit_and_Scale.json b/agency-indexes/DoE/Quantities_need_Representation,_Unit_and_Scale.json new file mode 100644 index 00000000..0c16e2bc --- /dev/null +++ b/agency-indexes/DoE/Quantities_need_Representation,_Unit_and_Scale.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2020-05-11" + }, + "description": "C++ template library to represent quantities in scientific computing. It enables a strong, compile-time,\ntyping of physical quantities. This typing includes information about:\n- representation: float, double, ...\n- unit: [ mass, length, time, angle ]\n- scale: kilo, milli, micro, ...\nIs", + "laborHours": 3040.0, + "languages": [], + "name": "Quantities need Representation, Unit and Scale", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/QRUS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantized_State_Systems__QSS__Solver_with_Functional_Mock-Up_Units__FMU__Support.json b/agency-indexes/DoE/Quantized_State_Systems__QSS__Solver_with_Functional_Mock-Up_Units__FMU__Support.json new file mode 100644 index 00000000..d3c883f8 --- /dev/null +++ b/agency-indexes/DoE/Quantized_State_Systems__QSS__Solver_with_Functional_Mock-Up_Units__FMU__Support.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Quantized State Systems (QSS) Solver with Functional Mock-Up Units (FMU) Support", + "laborHours": 23560.0, + "name": "Quantized State Systems (QSS) Solver with Functional Mock-Up Units (FMU) Support", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/SOEP-QSS/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SOEP-QSS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantum_Application_Specifications_and_Benchmarks.json b/agency-indexes/DoE/Quantum_Application_Specifications_and_Benchmarks.json new file mode 100644 index 00000000..e33625e0 --- /dev/null +++ b/agency-indexes/DoE/Quantum_Application_Specifications_and_Benchmarks.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-09-22" + }, + "description": "This software describes computational tasks for quantum computers that are derived from LANL basic science research applications such as the modeling of materials, chemicals and compounds at atomic scales. The computations focus on quantum simulation tasks, such as quantum dynamics, thermal state preparation and ground state estimation. The primary function of the software is to develop estimates of the requirements for large-scale fault-tolerant quantum computers to solve these scientific computations. The secondary focus of the software are codes for assessing the limitations of conducting quantum computations on classical computers.", + "laborHours": 0.0, + "languages": [], + "name": "Quantum Application Specifications and Benchmarks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/qc-applications", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantum_Approximate_Optimization_Algorithm_in_Python.json b/agency-indexes/DoE/Quantum_Approximate_Optimization_Algorithm_in_Python.json new file mode 100644 index 00000000..06978561 --- /dev/null +++ b/agency-indexes/DoE/Quantum_Approximate_Optimization_Algorithm_in_Python.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-07-29" + }, + "description": "This is software in Python that simulates the quantum approximate optimization algorithm (QAOA) as described in https://arxiv.org/abs/1411.4028. The software has customization that speeds up simulation and provides interface to the Rapid Optimization Library (ROL) developed at Sandia. SAND2019-8935 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 820.8, + "languages": [ + "Python" + ], + "name": "Quantum Approximate Optimization Algorithm in Python", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyQAOA", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantum_Fast_Approximate_Synthesis_Tool__QFAST__v1.0.0.json b/agency-indexes/DoE/Quantum_Fast_Approximate_Synthesis_Tool__QFAST__v1.0.0.json new file mode 100644 index 00000000..7c3685d4 --- /dev/null +++ b/agency-indexes/DoE/Quantum_Fast_Approximate_Synthesis_Tool__QFAST__v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-08-20", + "metadataLastUpdated": "2020-08-20" + }, + "description": "We present QFAST, a quantum synthesis tool designed to produce short circuits and to scale well in practice. Our contributions are: 1) a novel representation of circuits able to encode placement and topology; 2) a hierarchical approach with an iterative refinement formulation that combines \"coarse-grained\" fast optimization during circuit structure search with a good, but slower, optimization stage only in the final circuit instantiation stage. When compared against state-of-the-art techniques, although not optimal, QFAST can generate much shorter circuits for \"time dependent evolution\" algorithms used by domain scientists. We also show the composability and tunability of our formulation in terms of circuit depth and running time. For example, we show how to generate shorter circuits by plugging in the best available third party synthesis algorithm at a given hierarchy level. Composability enables portability across chip architectures, which is missing from the available approaches.", + "laborHours": 1580.8, + "languages": [], + "name": "Quantum Fast Approximate Synthesis Tool (QFAST) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/edyounis/qfast", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantum_Fast_Circuit_Optimizer__qFactor__v1.json b/agency-indexes/DoE/Quantum_Fast_Circuit_Optimizer__qFactor__v1.json new file mode 100644 index 00000000..4f3daa51 --- /dev/null +++ b/agency-indexes/DoE/Quantum_Fast_Circuit_Optimizer__qFactor__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-04-09", + "metadataLastUpdated": "2021-06-15" + }, + "description": "Quantum programs are represented as circuits, or sequences of gates. A common problem during quantum compilation to find a circuit that implements a target program. This is an optimizer, it optimizes a circuit's distance to the target by solving for the best fit gates. It is not a standard optimizer, it only optimizes circuits. It is not a compiler or synthesizer, it cannot build circuits, but given a circuit structure, it will solve for the gates. Quantum compilers (qsearch, qfast) use standard numerical optimizers. This has advantages over those general-purpose optimizers since it is domain-specific.", + "laborHours": 0.0, + "languages": [], + "name": "Quantum Fast Circuit Optimizer (qFactor) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/edyounis/qFactor", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantum_Graph_Algorithms.json b/agency-indexes/DoE/Quantum_Graph_Algorithms.json new file mode 100644 index 00000000..9529b60c --- /dev/null +++ b/agency-indexes/DoE/Quantum_Graph_Algorithms.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Two quantum graph algorithms (as python scripts) that run on the D-Wave Quantum Annealer are included for copyright. The Quantum Graph Partitioning software takes a graph as input and the number of partitions of equal size desired. This is transformed into a quadratic unconstrained binary optimization (QUBO) that is run as a quantum-classical algorithm using D-Wave/qbsolv. The Quantum Community Detection software takes a graph and the maximum number of communities/clusters desired. This is transformed into a quadratic unconstrained binary optimization (QUBO) that is run as a quantum-classical algorithm using D-Wave/qbsolv.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Quantum Graph Algorithms", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantum_Image_Pixel_Library__QPIXL++__v0.1.0.json b/agency-indexes/DoE/Quantum_Image_Pixel_Library__QPIXL++__v0.1.0.json new file mode 100644 index 00000000..76efbe83 --- /dev/null +++ b/agency-indexes/DoE/Quantum_Image_Pixel_Library__QPIXL++__v0.1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-21", + "metadataLastUpdated": "2021-10-21" + }, + "description": "QPIXL++ is a software package to compile quantum circuits for compressed representation of images on quantum hardware.", + "laborHours": 0.0, + "languages": [], + "name": "Quantum Image Pixel Library (QPIXL++) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/LBL_TBI/autoct/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantum_Instrumentation_Control_Kit_Defect_Arbitrary_Waveform_Generator__QICKDAWG__v.0.json b/agency-indexes/DoE/Quantum_Instrumentation_Control_Kit_Defect_Arbitrary_Waveform_Generator__QICKDAWG__v.0.json new file mode 100644 index 00000000..70b2c30b --- /dev/null +++ b/agency-indexes/DoE/Quantum_Instrumentation_Control_Kit_Defect_Arbitrary_Waveform_Generator__QICKDAWG__v.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-30" + }, + "description": "SAND2024-08598O\nThe Quantum Instrumentation Control Kit Defect Arbitrary Waveform Generator (QICKDAWG) characterizes nitrogen-vacancy centers in diamond and other defects. It does this by using a radio frequency system-on-a-chip (RFSoC) field programmable gate array (FPGA). QICKDAWG synthesizes microwave pulses from the RFSoC to change the spin state of the defects. The software also allows for laser control using the RFSoC, which optically pumps defects. Ultimately, QICKDAWG supports the implementation of RFSoC FPGAs in defect characterization. This replaces the slow, expensive, traditional hardware, thus lowering the cost and time for defect characterization. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 144278.4, + "languages": [ + "Python" + ], + "name": "Quantum Instrumentation Control Kit Defect Arbitrary Waveform Generator (QICKDAWG) v.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/qick-dawg", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantum_Manifold_Learning.json b/agency-indexes/DoE/Quantum_Manifold_Learning.json new file mode 100644 index 00000000..3c5492fb --- /dev/null +++ b/agency-indexes/DoE/Quantum_Manifold_Learning.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-14", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-12600 O\nQuantum Manifold Learning is a Python code to perform manifold learning from point clouds. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 2690.4, + "languages": [ + "Python3", + "Cuda" + ], + "name": "Quantum Manifold Learning", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/QML", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.9" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantum_Process_Matrix_Computation_by_Monte_Carlo.json b/agency-indexes/DoE/Quantum_Process_Matrix_Computation_by_Monte_Carlo.json new file mode 100644 index 00000000..1037c390 --- /dev/null +++ b/agency-indexes/DoE/Quantum_Process_Matrix_Computation_by_Monte_Carlo.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The software package, processMC, is a python script that allows for the rapid modeling of small , noisy quantum systems and the computation of the averaged quantum evolution map.", + "laborHours": 228.0, + "languages": [ + "Python 2.6" + ], + "name": "Quantum Process Matrix Computation by Monte Carlo", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/processMC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantum_Search_Compiler__Qsearch__v2.0.json b/agency-indexes/DoE/Quantum_Search_Compiler__Qsearch__v2.0.json new file mode 100644 index 00000000..5f5cb4b7 --- /dev/null +++ b/agency-indexes/DoE/Quantum_Search_Compiler__Qsearch__v2.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-07", + "metadataLastUpdated": "2021-03-07" + }, + "description": "Quantum Gate Synthesis is the process of taking a desired quantum gate operation, in this case specified as a unitary matrix, and decomposing it into a list of operations that can actually be performed on a quantum computer.\n\nQsearch is an implementation of a quantum synthesis algorithm based on combining A* search with numerical optimization. It is designed to minimize CNOT count at the expense of having a long runtime. It produces particularly efficient quantum circuits in terms of CNOT count, up until about 4 qubits. It is generally impractical to run Qsearch on circuits with more than 4 qubits, but it can be used as a subroutine in algorithms designed to work with these larger circuits.\n\nQsearch takes the form of a Python package, taking advantage of Numpy and Scipy, with part of the package written in Rust and taking advantage of OpenBLAS, NLOPT, and Google Ceres for faster runtime.", + "laborHours": 0.0, + "languages": [], + "name": "Quantum Search Compiler (Qsearch) v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BQSKit/qsearch", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantum_Virtual_Machine__QVM_.json b/agency-indexes/DoE/Quantum_Virtual_Machine__QVM_.json new file mode 100644 index 00000000..c8b3333d --- /dev/null +++ b/agency-indexes/DoE/Quantum_Virtual_Machine__QVM_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "There is a lack of state-of-the-art HPC simulation tools for simulating general quantum computing. Furthermore, there are no real software tools that integrate current quantum computers into existing classical HPC workflows. This product, the Quantum Virtual Machine (QVM), solves this problem by providing an extensible framework for pluggable virtual, or physical, quantum processing units (QPUs). It enables the execution of low level quantum assembly codes and returns the results of such executions.", + "laborHours": 15.2, + "name": "Quantum Virtual Machine (QVM)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-QCI/qvm", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/qvm", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quantum_process_inversion_at_the_Pulse_Level.json b/agency-indexes/DoE/Quantum_process_inversion_at_the_Pulse_Level.json new file mode 100644 index 00000000..246f9ed8 --- /dev/null +++ b/agency-indexes/DoE/Quantum_process_inversion_at_the_Pulse_Level.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "leytonorteva@ornl.gov" + }, + "date": { + "created": "2022-08-05", + "metadataLastUpdated": "2022-08-08" + }, + "description": "This code creates the pulse structure of a given gate or quantum operation on the IBM superconducting quantum processors. The script constructs the pulse sequence for the gate inverse, not the mirror, that can be applied in a quantum circuit.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Quantum process inversion at the Pulse Level", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/leytonorteva/gate-inversion-at-the-pulse-level.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/QuarkNet_DAQ_Kit.json b/agency-indexes/DoE/QuarkNet_DAQ_Kit.json new file mode 100644 index 00000000..52c9f931 --- /dev/null +++ b/agency-indexes/DoE/QuarkNet_DAQ_Kit.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2019-04-17" + }, + "description": "The QuarkNet Data Acquisition (DAQ) circuit board is provided in a kit that includes a power supply, GPS capability with temperature sensor and cabling, and a USB link to the user\u2019s computer. The DAQ circuit board has 4 analog discriminator inputs and produces trigger time and pulse edge time data for 1- to 4-fold coincidence levels. The DAQ then checks for user-defined trigger multiplicity across the four inputs. If the pulses satisfy the trigger requirement, the DAQ encodes time information for each input. Timing on the DAQ is done with a local clock synchronized to GPS time (via local module) once per second. This gives local times of nearly one nanosecond precision recorded with the accuracy inherent in GPS time. The DAQ kit is equipped to measure ambient temperature and atmospheric pressure; it also can determine its latitude and longitude from the GPS unit. A laptop or desktop computer connects to the DAQ via USB for control and collection of formatted raw data. ", + "homepageURL": "http://quarknet.fnal.gov/toolkits/ati/fnaldet.html", + "laborHours": 0.0, + "languages": [ + "C", + "VHDL" + ], + "name": "QuarkNet DAQ Kit", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://partnerships.fnal.gov/licensing", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://quarknet.fnal.gov/toolkits/ati/fnaldet.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quasi-Newton_Variational_Bayes_v.3.0.json b/agency-indexes/DoE/Quasi-Newton_Variational_Bayes_v.3.0.json new file mode 100644 index 00000000..d05dcf74 --- /dev/null +++ b/agency-indexes/DoE/Quasi-Newton_Variational_Bayes_v.3.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-09052O\nQuasi-Newton Variational Bayes (QNVB) is a training algorithm that performs high-dimensional variational inference on machine learning models. It provides mechanisms to calibrate and control model uncertainty during training. The PyTorch implementation of projective integral updates for Gaussian mean-fields supports the manuscript, \"Projective Integral Updates for High-Dimensional Variational Inference.\"\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 243.2, + "languages": [ + "Python", + "PyTorch" + ], + "name": "Quasi-Newton Variational Bayes v.3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/qnvb", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Qubit-efficient_entanglement_spectroscopy.json b/agency-indexes/DoE/Qubit-efficient_entanglement_spectroscopy.json new file mode 100644 index 00000000..ba2b6b76 --- /dev/null +++ b/agency-indexes/DoE/Qubit-efficient_entanglement_spectroscopy.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "Two Python files, entSpectroscopy.py and simulateCircuitsScript.py, containing the necessary code to reproduce the experiments for our recent work \"Qubit-efficient entanglement spectroscopy using qubit resets\" LA-UR-20-25416 (https://arxiv.org/abs/2010.03080). This paper described new quantum algorithms, also known as circuits, and described experiments testing these algorithms both on real quantum hardware and in simulators. The file entSpectroscopy.py contains functions which take parameters describing the input (e.g. input size) and output descriptions of quantum circuits by implementing the algorithms described in our paper. These circuit descriptions are created as `QuantumCircuit` objects using the Python library qiskit, and our simulation experiments use simulators provided by qiskit. The file also contains helper functions for processing the results of these circuits and for calculating the statistical uncertainty in the results, both according to formulas given in our paper. Finally, entSpectroscopy.py includes helper functions for easily preparing the qiskit simulator according to given noise parameters. The file simulateCircuitsScript.py demonstrates how we performed our experiments by calling functions in entSpectroscopy.py. This script takes as input parameters from the command line and hardcoded data, uses functions in entSpectroscopy.py to get circuit descriptions, simulates those circuits using qiskit, and outputs and plots the results.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Qubit-efficient entanglement spectroscopy", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Qubit_Control_System__QubiC__v1.0.json b/agency-indexes/DoE/Qubit_Control_System__QubiC__v1.0.json new file mode 100644 index 00000000..b99f395a --- /dev/null +++ b/agency-indexes/DoE/Qubit_Control_System__QubiC__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-13", + "metadataLastUpdated": "2021-04-13" + }, + "description": "We design a modular FPGA (field-programmable gate array) based system called QubiC to control and measure a superconducting quantum processing unit. The system includes room temperature electronics hardware, FPGA gateware, and engineering software.", + "laborHours": 0.0, + "languages": [], + "name": "Qubit Control System (QubiC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/LBL-QubiC/qubic", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/QuickNXS.json b/agency-indexes/DoE/QuickNXS.json new file mode 100644 index 00000000..b2a8a808 --- /dev/null +++ b/agency-indexes/DoE/QuickNXS.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Data reduction software for the Oak Ridge National Laboratory Spallation Neutron Source's Magnetism Reflectometer beam line 4A, used to extract reflectivity, off-specular and GISANS scattering from raw data in NeXus file format. The package consists of a Python library for the extraction and a Qt4 based graphical user interface to work with the data.", + "laborHours": 31631.2, + "name": "QuickNXS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aglavic/quicknxs", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QuickView_PRO,_QVPRO.json b/agency-indexes/DoE/QuickView_PRO,_QVPRO.json new file mode 100644 index 00000000..bdcfabde --- /dev/null +++ b/agency-indexes/DoE/QuickView_PRO,_QVPRO.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "burnsrl1@nv.doe.gov" + }, + "date": { + "created": "2019-10-24", + "metadataLastUpdated": "2019-11-19" + }, + "description": "QuickView PRO (QVPRO) is similar to QuickView but designed to focus on analysis. QuickView was designed for visualization only, adding analysis capabilities later. This made QuickView complicated when using it as an analysis tool. QVPRO uses the same analysis algorithms in a more streamlined workflow and has a user friendly GUI. QVPRO provides the unique capability of analyzing Photonic Doppler Velocimetry (PDV) data records from different PDV systems and still allows for processing hundreds of PDV data records in a practical manner.", + "homepageURL": "http://gitlab.osti.gov/doecode/dc-31683", + "laborHours": 881.6, + "languages": [], + "name": "QuickView PRO, QVPRO", + "organization": "Nevada National Security Site/Mission Support and Test Services LLC (MSTS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://gitlab.osti.gov/doecode/dc-31683", + "status": "Production", + "tags": [ + "DOE CODE", + "Nevada National Security Site/Mission Support and Test Services LLC (MSTS)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quick_n_Dirty.json b/agency-indexes/DoE/Quick_n_Dirty.json new file mode 100644 index 00000000..d2cfe583 --- /dev/null +++ b/agency-indexes/DoE/Quick_n_Dirty.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-12", + "metadataLastUpdated": "2020-05-12" + }, + "description": "QnD is a pure Python package for working with binary files. It has built-in support for HDF5, NetCDF3,\nand PDB formats. It provides a Pythonic, dict-like interface, and allows easy movement among time-like\n\"records\". Both reading and writing are enabled. The HDF and NetCDF capabilities rely on external\nlibraries, while the PDB support is part of QnD itself and entirely in Python. QnD works under Python 2\nand 3. For interactive use, much less typing is involved than for some other packages.", + "laborHours": 2310.4, + "languages": [], + "name": "Quick n Dirty", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/qnd", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/QuinnsWakeCalculator.json b/agency-indexes/DoE/QuinnsWakeCalculator.json new file mode 100644 index 00000000..d4fa4e3f --- /dev/null +++ b/agency-indexes/DoE/QuinnsWakeCalculator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "Matlab Resistive Wake Calculator \nThis is a Matlab code that calculates the resistive wake from an undulator beam pipe. The code is based on a published paper by Bane and Stupakov [1]. The code can calculate the wake for a round or a flat beam pipe, and can calculate the wake for different types of metal (for example, Aluminum or Copper). The code can be used to simply calculate the wake (\u201cGenericACWakeForGen\u201d), or it can be used to append a wake calculation to an input file for the free electron laser code Genesis [2] (\u201cReadFullBeam\u201d). The code can also be used to simply plot out the impedances or wakes of a round or flat beam (\u201cCalcZbarFlat\u201d and \u201cZbarAC\u201d). The top level code, \u201cReadFullBeam\u201d is designed to read an output from the beam code Elegant [3] that has been converted to Genesis format using the command \u201cElegant2Genesis.\u201d \n\n\nReferences:\n[1] K. Bane and G. Stupakov, \u201cResistive Wall Wakefield in the LCLS Undulator,\u201d Proc. Of 2005 Part. Accel. Conf., Knoxville, TN, p. 3390 \u2013 3392.\n[2] S. Reiche, \u201cGENESIS 1.3: a fully 3D time-dependent FEL simulation code,\u201d Nucl. Inst. Methods in Phys. A, 429 (1999) 243-248.\n[3] M. Borland, \u201celegant: A Flexible SDDS-Compliant Code for Accelerator Simulation,\u201d Advanced Photon Source LS-287, September 2000.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "QuinnsWakeCalculator", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quinoa,_Version_0.1.json b/agency-indexes/DoE/Quinoa,_Version_0.1.json new file mode 100644 index 00000000..49dc0e43 --- /dev/null +++ b/agency-indexes/DoE/Quinoa,_Version_0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Quinoa is a set of computational tools that enables research and numerical analysis in fluid dynamics. At this time it is a test-bed to experiment with various algorithms using fully asynchronous runtime systems.", + "laborHours": 130020.8, + "name": "Quinoa, Version 0.1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/quinoacomputing/quinoa/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/quinoacomputing/quinoa", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quinoa,_Version_0.2.json b/agency-indexes/DoE/Quinoa,_Version_0.2.json new file mode 100644 index 00000000..3b4ca8ea --- /dev/null +++ b/agency-indexes/DoE/Quinoa,_Version_0.2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-09-04", + "metadataLastUpdated": "2018-09-04" + }, + "description": "Quinoa is a set of computational tools that enables research and numerical analysis in fluid dynamics. At this time it remains a test-bed to experiment with various algorithms using fully asynchronous runtime systems. Currently, Quinoa consists of the following tools: (1) Walker, a numerical integrator for systems of stochastic differential equations in time. It is a mathematical tool to analyze and design the behavior of stochastic differential equations. It allows the estimation of arbitrary coupled statistics and probability density functions and is currently used for the design of statistical moment approximations for multiple mixing materials in variable-density turbulence. (2) Inciter, an overdecomposition-aware finite element field solver for partial differential equations using 3D unstructured grids. Inciter is used to research asynchronous mesh-based algorithms and to experiment with coupling asynchronous to bulk-synchronous parallel code. Two planned new features of Inciter, compared to the previous release (LA-CC-16-015), to be implemented in 2017, are (a) a simple Navier-Stokes solver for ideal single-material compressible gases, and (b) solution-adaptive mesh refinement (AMR), which enables dynamically concentrating compute resources to regions with interesting physics. Using the NS-AMR problem we plan to explore how to scale such high-load-imbalance simulations, representative of large production multiphysics codes, to very large problems on very large computers using an asynchronous runtime system. (3) RNGTest, a test harness to subject random number generators to stringent statistical tests enabling quantitative ranking with respect to their quality and computational cost. (4) UnitTest, a unit test harness, running hundreds of tests per second, capable of testing serial, synchronous, and asynchronous functions. (5) MeshConv, a mesh file converter that can be used to convert 3D tetrahedron meshes from and to either of the following formats: Gmsh, http://www.geuz.org/gmsh, Netgen, http://sourceforge.net/apps/mediawiki/netgen-mesher, ExodusII, http://sourceforge.net/projects/exodusii, HyperMesh, http://www.altairhyperworks.com/product/HyperMesh.", + "laborHours": 130020.8, + "languages": [], + "name": "Quinoa, Version 0.2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/quinoacomputing/quinoa", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quinoa,_Version_1.0.json b/agency-indexes/DoE/Quinoa,_Version_1.0.json new file mode 100644 index 00000000..d7d8d676 --- /dev/null +++ b/agency-indexes/DoE/Quinoa,_Version_1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-11-15" + }, + "description": "Quinoa is a set of computational tools that enables research and numerical analysis in fluid and solid dynamics.", + "laborHours": 130020.8, + "languages": [], + "name": "Quinoa, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/quinoacomputing/quinoa", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Quo_Vadis__libqv_.json b/agency-indexes/DoE/Quo_Vadis__libqv_.json new file mode 100644 index 00000000..5baa80b9 --- /dev/null +++ b/agency-indexes/DoE/Quo_Vadis__libqv_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-02-11", + "metadataLastUpdated": "2022-02-11" + }, + "description": "Quo Vadis (libqv) is a next-generation, machine-independent coordination layer to arbitrate computer resource access among multiple runtime components and map tasks efficiently to heterogeneous computer architectures.", + "laborHours": 0.0, + "languages": [], + "name": "Quo Vadis (libqv)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/quo-vadis", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/R2X__ReEDS\342\204\242_to_X__[SWR-24-91].json" "b/agency-indexes/DoE/R2X__ReEDS\342\204\242_to_X__[SWR-24-91].json" new file mode 100644 index 00000000..a60ae923 --- /dev/null +++ "b/agency-indexes/DoE/R2X__ReEDS\342\204\242_to_X__[SWR-24-91].json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-09-18", + "metadataLastUpdated": "2024-09-18" + }, + "description": "R2X is a tool that allows modeler to convert input/output models to other input/out models (e.g., ReEDS\u2122 to Plexos). This is tools is built as a parser of inputs that uses infrasys to create a network representation that then is used to create custom files as input for other models.", + "laborHours": 6672.8, + "languages": [ + "Python" + ], + "name": "R2X (ReEDS\u2122 to X) [SWR-24-91]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/R2X", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/R3IT:_Rapid,_Rural,_Resilient_Interconnection_Toolkit.json b/agency-indexes/DoE/R3IT:_Rapid,_Rural,_Resilient_Interconnection_Toolkit.json new file mode 100644 index 00000000..46627617 --- /dev/null +++ b/agency-indexes/DoE/R3IT:_Rapid,_Rural,_Resilient_Interconnection_Toolkit.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2022-04-11", + "metadataLastUpdated": "2022-04-11" + }, + "description": "R3IT is a free and open-source web application that allows utilities to automate the processing of solar interconnection requests. It handles request submission, request review workflows, payment collection, signature collection, email notifications for any status changes, and optionally an automated engineering screening and approval process.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "R3IT: Rapid, Rural, Resilient Interconnection Toolkit", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dpinney/r3it", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RADA.json b/agency-indexes/DoE/RADA.json new file mode 100644 index 00000000..9fe7fe0e --- /dev/null +++ b/agency-indexes/DoE/RADA.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "The code for regularized adversarial domain adaption is provided here. The RADA methodology is developed for correcting climate model biases using an adversarial learning strategy. The code here covers the data processing, the algorithm, the baseline models, and the evaluation.", + "laborHours": 0.0, + "languages": [], + "name": "RADA", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/panbaoxiang/RADA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RADT_Scripts_for_Network_Research.json b/agency-indexes/DoE/RADT_Scripts_for_Network_Research.json new file mode 100644 index 00000000..3491bb6b --- /dev/null +++ b/agency-indexes/DoE/RADT_Scripts_for_Network_Research.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "cwang@renci.org" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-20" + }, + "description": "This repository provides a set of scripts and tools for conducting network research, including performance analysis, buffer status inspection, and RTT probing. It is designed to streamline network data collection and post-processing, primarily leveraging iperf and other network utilities. The primary goal of the RADT dataset is to provide researchers with detailed insights into the interactions between TCP Congestion Control Algorithms (CCAs) and Active Queue Management (AQM) algorithms under different network conditions, enabling the development of more advanced, AI-driven CCAs.", + "laborHours": 1368.0, + "languages": [], + "name": "RADT Scripts for Network Research", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PoSeiDon-Workflows/RADT_scripts_for_network_research", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RAFT__Response_Amplitudes_of_Floating_Turbines__[SWR-22-40].json b/agency-indexes/DoE/RAFT__Response_Amplitudes_of_Floating_Turbines__[SWR-22-40].json new file mode 100644 index 00000000..4a10e8c2 --- /dev/null +++ b/agency-indexes/DoE/RAFT__Response_Amplitudes_of_Floating_Turbines__[SWR-22-40].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-07-13", + "metadataLastUpdated": "2023-04-24" + }, + "description": "RAFT is a Python code for frequency-domain analysis of floating wind turbines. RAFT works in the frequency domain to provide efficient computations of a floating wind system's response spectra accounting for platform hydrodynamics, quasi-static mooring reactions, rotor aerodynamics, and linearized control. It can be used to calculate response amplitude operators (RAO's), power spectral densities, mean/static properties, and response metrics based on mean and root-mean-square values of each output. RAFT serves as the Level 1 model in the WEIS (Wind Energy with Integrated Servo-control) toolkit, and features an OpenMDAO wrapper.", + "laborHours": 0.0, + "languages": [ + "Python", + "roff" + ], + "name": "RAFT (Response Amplitudes of Floating Turbines) [SWR-22-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/RAFT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RAJA_-_LLNL_HPC_Architecture_Portability_Encapsulation_Layer_Version_1.0.json b/agency-indexes/DoE/RAJA_-_LLNL_HPC_Architecture_Portability_Encapsulation_Layer_Version_1.0.json new file mode 100644 index 00000000..398c07e8 --- /dev/null +++ b/agency-indexes/DoE/RAJA_-_LLNL_HPC_Architecture_Portability_Encapsulation_Layer_Version_1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "RAJA is a collection of C++ software abstractions designed to make HPC applications portable across a range of hardware architectures and programming models. The main conceptual abstraction in FAJA is a loop. RAJA provides abstractions for types, loop execution and scheduling, and loop iteration space portioning and ordering cooperate to insulate algorithms in application code that domain experts write from implementations details of those algorithms that may need to depend on the underlying computer hardware for high performance.", + "laborHours": 22708.8, + "languages": [], + "name": "RAJA - LLNL HPC Architecture Portability Encapsulation Layer Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RAJA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RAJA_Performance_Suite.json b/agency-indexes/DoE/RAJA_Performance_Suite.json new file mode 100644 index 00000000..a5bbaf64 --- /dev/null +++ b/agency-indexes/DoE/RAJA_Performance_Suite.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The RAJA Performance Suite is designed to evaluate performance of the RAJA performance portability library on a wide variety of important high performance computing (HPC) algorithmic lulmels. These kernels assess compiler optimizations and various parallel programming model backends accessible through RAJA, such as OpenMP, CUDA, etc. The Initial version of the suite contains 25 computational kernels, each of which appears in 6 variants: Baseline SequcntiaJ, RAJA SequentiaJ, Baseline OpenMP, RAJA OpenMP, Baseline CUDA, RAJA CUDA. All variants of each kernel perform essentially the same mathematical operations and the loop body code for each kernel is identical across all variants. There are a few kernels, such as those that contain reduction operations, that require CUDA-specific coding for their CUDA variants. ActuaJ computer instructions executed and how they run in parallel differs depending on the parallel programming model backend used and which optimizations are perfonned by the compiler used to build the Perfonnance Suite executable. The Suite will be used primarily by RAJA developers to perform regular assessments of RAJA performance across a range of hardware platforms and compilers as RAJA features are being developed. It will also be used by LLNL hardware and software vendor panners for new defining requirements for future computing platform procurements and acceptance testing. In particular, the RAJA Performance Suite will be used for compiler acceptance testing of the upcoming CORAUSierra machine {initial LLNL delivery expected in late-2017/early 2018) and the CORAL-2 procurement. The Suite will aJso be used to generate concise source code reproducers of compiler and runtime issues we uncover so that we may provide them to relevant vendors to be fixed.", + "laborHours": 12813.6, + "languages": [ + "CC++ I I standard required" + ], + "name": "RAJA Performance Suite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RAJAPerf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RAPID.json b/agency-indexes/DoE/RAPID.json new file mode 100644 index 00000000..d314f5b3 --- /dev/null +++ b/agency-indexes/DoE/RAPID.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "allus@ornl.gov" + }, + "date": { + "created": "2021-07-20", + "metadataLastUpdated": "2021-09-28" + }, + "description": "Parallel computer code for the simulator for dynamics of power systems which has the capability to initiate the system and create different faults for the dynamic analysis. The code is based on time-parallel method (Parareal) with Adaptive Method Reduction (AMR). The coarse solvers for the Parareal algorithm include several Semi Analytical Solution methods. Also, Integrated simulation of coupled transmission and distribution systems can be studied.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "RAPID", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/PowerSystems/rapid", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/RASE_OSS.json b/agency-indexes/DoE/RASE_OSS.json new file mode 100644 index 00000000..61282d78 --- /dev/null +++ b/agency-indexes/DoE/RASE_OSS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-19" + }, + "description": "The Replicative Assessment of Spectroscopic Equipment (RASE) methodology is a semi-empirical approach to generating synthetic gamma-ray spectra for injection into a radionuclide identification algorithm of a vendor-provided detection system. RASE facilitates studies of the spectroscopic device performance and a quantitative assessment of its capabilities to correctly distinguish and identify isotopes of interest in realistic scenarios.", + "laborHours": 4088.8, + "languages": [], + "name": "RASE OSS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RASE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RA_Decay.json b/agency-indexes/DoE/RA_Decay.json new file mode 100644 index 00000000..5a847716 --- /dev/null +++ b/agency-indexes/DoE/RA_Decay.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The concept of the software is for a user to input the desired decay period and initial isotopic distribution and radioactivity, and RA-Decay will return the new isotopic distribution and radioactivity including the progeny ingrowth.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "RA Decay", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/RBigData_release.json b/agency-indexes/DoE/RBigData_release.json new file mode 100644 index 00000000..3a756af9 --- /dev/null +++ b/agency-indexes/DoE/RBigData_release.json @@ -0,0 +1,50 @@ +{ + "contact": { + "email": "ostrouchovg@ornl.gov" + }, + "date": { + "created": "2018-04-13", + "metadataLastUpdated": "2018-06-28" + }, + "description": "pbdR: This release script for pbdR 1.0 combines several repositories on GitHub and on CRAN with an installer script. We list authors of the subject repositories who are active maintainers.\n\nPackages are released under a variety of licenses noted in the release script.", + "laborHours": 136.8, + "languages": [ + "R" + ], + "name": "RBigData/release", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mpl-2.0", + "name": "MPL-2.0" + }, + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + }, + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + }, + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/RBigData/release", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RDPTools_Services.json b/agency-indexes/DoE/RDPTools_Services.json new file mode 100644 index 00000000..595537bd --- /dev/null +++ b/agency-indexes/DoE/RDPTools_Services.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "KBase service code for RDP. A classifier of rRNA amplicon data contributed by the RDB Project. Deploys both client and service.", + "laborHours": 608.0, + "languages": [], + "name": "RDPTools Services", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/rdptools", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RDycore_RDycore.json b/agency-indexes/DoE/RDycore_RDycore.json new file mode 100644 index 00000000..ef36792b --- /dev/null +++ b/agency-indexes/DoE/RDycore_RDycore.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "A River dynamical core for E3SM", + "laborHours": 11400.0, + "languages": [], + "name": "RDycore/RDycore", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rdycore/rdycore", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/REAL-TIME_EDGE_INFERENCE_FOR_PTYCHOGRAPHIC_NANOSCALE_XRAY_IMAGING.json b/agency-indexes/DoE/REAL-TIME_EDGE_INFERENCE_FOR_PTYCHOGRAPHIC_NANOSCALE_XRAY_IMAGING.json new file mode 100644 index 00000000..afa1a9ab --- /dev/null +++ b/agency-indexes/DoE/REAL-TIME_EDGE_INFERENCE_FOR_PTYCHOGRAPHIC_NANOSCALE_XRAY_IMAGING.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "The consolidated code is deployed in an embedded GPU System (Jetson AGX Xavier Developer Kit), performs inference on the pVA stream sent from the X-ray detector. The inferred output is sent back to the local detector machine as a PVA stream and can be viewed in an ImageJ viewer.", + "laborHours": 0.0, + "languages": [], + "name": "REAL-TIME EDGE INFERENCE FOR PTYCHOGRAPHIC NANOSCALE XRAY IMAGING", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/vbanakha/edgePtychoNN", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RECELL.json b/agency-indexes/DoE/RECELL.json new file mode 100644 index 00000000..6c50d344 --- /dev/null +++ b/agency-indexes/DoE/RECELL.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2018-08-23", + "metadataLastUpdated": "2019-12-19" + }, + "description": "A Microsoft Excel based closed-loop cycle model that analyses the entire life-cycle of batteries and other systems with a predominate focus on cost, energy and environment impact", + "laborHours": 0.0, + "languages": [], + "name": "RECELL", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/qdai/everbatt.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/RECONCILE:_a_machine-learning_coreference_resolution_system.json b/agency-indexes/DoE/RECONCILE:_a_machine-learning_coreference_resolution_system.json new file mode 100644 index 00000000..b555a99b --- /dev/null +++ b/agency-indexes/DoE/RECONCILE:_a_machine-learning_coreference_resolution_system.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "RECONCILE is a noun phrase conference resolution system: it identifies noun phrases in a text document and determines which subsets refer to each real world entity referenced in the text. The heart of the system is a combination of supervised and unsupervised machine learning systems. It uses a machine learning algorithm (chosen from an extensive suite, including Weka) for training noun phrase coreference classifier models and implements a variety of clustering algorithms to coordinate the pairwise classifications. A number of features have been implemented, including all of the features employed in Ng & Cardie [2002].", + "laborHours": 144856.0, + "name": "RECONCILE: a machine-learning coreference resolution system", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/davidbuttler/reconcile", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/REDUCE:_Statistically-Guided_Reverse_Engineering_Toolkit.json b/agency-indexes/DoE/REDUCE:_Statistically-Guided_Reverse_Engineering_Toolkit.json new file mode 100644 index 00000000..43fe86b5 --- /dev/null +++ b/agency-indexes/DoE/REDUCE:_Statistically-Guided_Reverse_Engineering_Toolkit.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-01-09", + "metadataLastUpdated": "2018-01-10" + }, + "description": "REDUCE is a software toolset enabling cyber security analysts to rapidly discover relationships between malware samples, to extract temporal threat intelligence, and to develop actionable signatures for known and emerging threats. REDUCE performs automated static code analysis and identifies similarities between malware samples in order to support knowledge sharing about related pieces of malware. By integrating with well-established reverse engineering tools, REDUCE speeds up both deep-dive reverse engineering efforts and custom signature generation.", + "homepageURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "name": "REDUCE: Statistically-Guided Reverse Engineering Toolkit", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/REFERENCE_GOVERNOR_PLUG-IN_FOR_RAVEN.json b/agency-indexes/DoE/REFERENCE_GOVERNOR_PLUG-IN_FOR_RAVEN.json new file mode 100644 index 00000000..670d65b9 --- /dev/null +++ b/agency-indexes/DoE/REFERENCE_GOVERNOR_PLUG-IN_FOR_RAVEN.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-05" + }, + "description": "The software being disclosed is the Reference Governor plug-in for Risk Analysis Virtual Environment (RAVEN) developed in Idaho National Laboratory. This software is used as a part of the supervisory control system for integrated energy system project, which can receive the original control variable issued by the upstream control system, then adjust the control variable based on the system states and performance projection of the downstream power-generating systems, in order to keep the response of the downstream systems within all the thermal mechanical constraints.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "REFERENCE GOVERNOR PLUG-IN FOR RAVEN", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/RELOG.json b/agency-indexes/DoE/RELOG.json new file mode 100644 index 00000000..3348a01b --- /dev/null +++ b/agency-indexes/DoE/RELOG.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-10-19", + "metadataLastUpdated": "2020-10-19" + }, + "description": "RELOG is a supply chain optimization package focusing on reverse logistics and reverse manufacturing. For example,the package can be used to determine where to build recycling plants, what sizes should they have and which customers should be served by which plants. The package supports customized reverse logistics pipelines, with multiple types of\nplants, multiple types of product and multiple time periods.\n", + "laborHours": 24411.2, + "languages": [], + "name": "RELOG", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-CEEESA/RELOG", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/REMORA_v1.0.json b/agency-indexes/DoE/REMORA_v1.0.json new file mode 100644 index 00000000..65bacdc1 --- /dev/null +++ b/agency-indexes/DoE/REMORA_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "REMORA (previously known as ROMS-X) is a GPU-enabled regional ocean modeling code with the same core capabilities as the Regional Ocean Modeling System (ROMS) code.", + "laborHours": 11187.2, + "languages": [], + "name": "REMORA v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/seahorce-scidac/REMORA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/REPACT_Tool.json b/agency-indexes/DoE/REPACT_Tool.json new file mode 100644 index 00000000..962ea7d9 --- /dev/null +++ b/agency-indexes/DoE/REPACT_Tool.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "john.brewer@netl.doe.gov" + }, + "date": { + "created": "2024-11-26", + "metadataLastUpdated": "2024-11-26" + }, + "description": "Reuse of Existing Pipelines for Adapted Carbon Transport (REPACT) is an Excel-based screening tool. This tool enables the user to determine whether a pipeline originally deployed for natural gas transport, can be reused for CO2 transport. The tool along with its associated user's manual walk through an intended usage statement, setup instructions, a list of inputs and outputs in the tool, and frequently used protocols. Please note that this is a first-pass screening tool. The approach presented within this tool is valid for high-level evaluation only and should not be used to make engineering, financial, and/or regulatory decisions. See the User Manual at this link: https://www.netl.doe.gov/energy-analysis/details?id=126f2dad-6d53-423e-8aaa-70954e0a2a9c.", + "homepageURL": "https://netl.doe.gov/energy-analysis/details?id=c699a604-ded1-45cd-b1c0-247b1405aeeb", + "laborHours": 0.0, + "languages": [], + "name": "REPACT Tool", + "organization": "National Energy Technology Laboratory (NETL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://netl.doe.gov/energy-analysis/details?id=c699a604-ded1-45cd-b1c0-247b1405aeeb", + "status": "Development", + "tags": [ + "DOE CODE", + "National Energy Technology Laboratory (NETL)" + ], + "version": "0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/REPRA__Renewable_Energy_Probabilistic_Resource_Assessment__[SWR-14-18].json b/agency-indexes/DoE/REPRA__Renewable_Energy_Probabilistic_Resource_Assessment__[SWR-14-18].json new file mode 100644 index 00000000..896c47b7 --- /dev/null +++ b/agency-indexes/DoE/REPRA__Renewable_Energy_Probabilistic_Resource_Assessment__[SWR-14-18].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-11-26" + }, + "description": "This package is the R implementation of the Renewable Energy Probabilistic Resource Assessment (REPRA) tool, developed at the National Renewable Energy Laboratory (NREL). REPRA is a statistical tool that models the effect of variable generation in the calculation of resource adequacy metrics. It is built as a research tool to explore different methodologies and technologies.", + "laborHours": 319.2, + "languages": [ + "C++", + "R" + ], + "name": "REPRA (Renewable Energy Probabilistic Resource Assessment) [SWR-14-18]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/REPRA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RESCue_Model__RESCue_Experiment_and_Model__[SWR-24-84].json b/agency-indexes/DoE/RESCue_Model__RESCue_Experiment_and_Model__[SWR-24-84].json new file mode 100644 index 00000000..3c59d907 --- /dev/null +++ b/agency-indexes/DoE/RESCue_Model__RESCue_Experiment_and_Model__[SWR-24-84].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-24", + "metadataLastUpdated": "2024-10-24" + }, + "description": "The Renewable Energy and Storage Cybersecurity Research (RESCue) project is a collaborative effort aimed at securing the rapidly growing deployment of transmission-connected hybrid renewable energy systems, consisting of a combination of wind, solar, and/or energy storage equipment, against escalating cyber threats. This project brings together major original equipment manufacturers (OEMs) of wind, solar, and energy storage, along with major asset owners and DOE National Laboratories, to collectively identify cyber threats, assess risks, and develop robust cybersecurity strategies and solutions. The development of hybrid reference architectures has provided comprehensive blueprints for the secure design and integration of hybrid renewable energy systems, accounting for their unique characteristics and interdependencies. Additionally, NREL has created a cyber-resilient design framework that integrates cybersecurity considerations from the start of the system lifecycle, ensuring security is \"baked in\" from the initial design phase.\n\nThe research thrusts for the project included (i) development of hybrid reference architectures and (ii) a cyber-resilient design framework for hybrid energy systems. The reference architectures has provided comprehensive blueprints for the secure design and integration of hybrid renewable energy systems, accounting for their unique characteristics and interdependencies. Additionally, NREL has created a cyber-resilient design framework that integrates cybersecurity considerations from the start of the system lifecycle, ensuring security is \"baked in\" from the initial design phase. A demonstration experiment was developed for one of the architectures using NREL's Cyber Range resources. This experiment configuration, deployable using open-source tools, is provided here in this repository. Additional models were developed for the wind and solar architectures as well, however the configurations for only the Energy Storage scenario are provided here: https://www.nrel.gov/docs/fy24osti/89921.pdf", + "laborHours": 2173.6, + "languages": [ + "Python", + "Shell" + ], + "name": "RESCue Model (RESCue Experiment and Model) [SWR-24-84]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/RESCue", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RESKESearchDemo.json b/agency-indexes/DoE/RESKESearchDemo.json new file mode 100644 index 00000000..b8163ba2 --- /dev/null +++ b/agency-indexes/DoE/RESKESearchDemo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This is the repository for \"RESKESearchDemo\" developed by KBase. ", + "laborHours": 1991.2, + "languages": [], + "name": "RESKESearchDemo", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/RESKESearchDemo", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/REST2_[SWR-23-96].json b/agency-indexes/DoE/REST2_[SWR-23-96].json new file mode 100644 index 00000000..a584d714 --- /dev/null +++ b/agency-indexes/DoE/REST2_[SWR-23-96].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-04-04", + "metadataLastUpdated": "2024-04-16" + }, + "description": "REST2 is the high-performance solar radiation model for cloudless-sky irradiance, illuminance, and photosynthetically active radiation.", + "laborHours": 288.8, + "languages": [ + "Python" + ], + "name": "REST2 [SWR-23-96]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rest2", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/REST_Interface_Generator__RESTInG__v0.1.json b/agency-indexes/DoE/REST_Interface_Generator__RESTInG__v0.1.json new file mode 100644 index 00000000..4b388c69 --- /dev/null +++ b/agency-indexes/DoE/REST_Interface_Generator__RESTInG__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "From a single data description file, this package generates a simple but complete RESTful web interface to a relational database, in the form of containers that run in a Docker environment. This initial version produces containers that are intended for use on the NERSC Spin platform. It was developed as a foundation for the smart catalog created for LDRD FY20 ACTS: Accelerating COVID-19 Testing with Screening.", + "laborHours": 0.0, + "languages": [], + "name": "REST Interface Generator (RESTInG) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dani-lbnl/resting.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/REopt\302\256_[SWR-12-19].json" "b/agency-indexes/DoE/REopt\302\256_[SWR-12-19].json" new file mode 100644 index 00000000..e2833d97 --- /dev/null +++ "b/agency-indexes/DoE/REopt\302\256_[SWR-12-19].json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-23", + "metadataLastUpdated": "2023-12-13" + }, + "description": "The REopt\u00ae techno-economic decision support platform is used by NREL researchers to optimize energy systems for buildings, campuses, communities, microgrids, and more. REopt recommends the optimal mix of renewable energy, conventional generation, and energy storage technologies to meet cost savings, resilience, emissions reductions, and energy performance goals. The REopt\u00ae model provides concurrent, multiple technology integration and optimization capabilities to help organizations meet their cost savings and energy performance goals. Formulated as a mixed integer linear program, the REopt model recommends an optimally sized mix of renewable energy, conventional generation, and energy storage technologies; estimates the net present value of implementing those technologies; and provides a dispatch strategy for operating the technology mix at maximum economic efficiency. The REopt model was initially created to identify and prioritize cost-effective renewable energy projects across a portfolio of sites. The model is now also used to optimize the size and operating strategy of microgrids, storage, and energy/water systems.", + "homepageURL": "https://reopt.nrel.gov", + "laborHours": 130932.8, + "languages": [], + "name": "REopt\u00ae [SWR-12-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://reopt.nrel.gov/contacts.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://reopt.nrel.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/REopt\302\256_web_tool_FKA:_REopt_Lite\302\256_[SWR-19-21].json" "b/agency-indexes/DoE/REopt\302\256_web_tool_FKA:_REopt_Lite\302\256_[SWR-19-21].json" new file mode 100644 index 00000000..f52ce362 --- /dev/null +++ "b/agency-indexes/DoE/REopt\302\256_web_tool_FKA:_REopt_Lite\302\256_[SWR-19-21].json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-09-12", + "metadataLastUpdated": "2023-12-13" + }, + "description": "The REopt\u00ae web tool (formerly known as REopt Lite\u00ae) evaluates the economic viability of grid-connected solar photovoltaics (PV), wind and battery storage at a commercial site. It allows building owners to identify the system sizes and dispatch strategy that minimize the site's life cycle cost of energy. REopt Lite\u00ae also estimates the amount of time a PV and/or wind and battery system can sustain the site's critical load during a grid outage and allows the user the choice of optimizing for energy resilience. The REopt\u00ae web tool may be found here: https://reopt.nrel.gov/tool/.", + "laborHours": 6581.6, + "languages": [], + "name": "REopt\u00ae web tool FKA: REopt Lite\u00ae [SWR-19-21]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/REopt-API-Analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/REsource_Migration_Interface.json b/agency-indexes/DoE/REsource_Migration_Interface.json new file mode 100644 index 00000000..03a57bab --- /dev/null +++ b/agency-indexes/DoE/REsource_Migration_Interface.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-28", + "metadataLastUpdated": "2022-01-28" + }, + "description": "REMI is a Mochi microservice designed to handle the migration of sets of files from a node to another. It uses RDMA and memory mapping to efficiently transfer potentially large groups of files at once.", + "laborHours": 0.0, + "languages": [], + "name": "REsource Migration Interface", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-remi/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-remi", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RF_mixing_modules_for_superconducting_qubit_room_temperature_control_systems_v1.0.json b/agency-indexes/DoE/RF_mixing_modules_for_superconducting_qubit_room_temperature_control_systems_v1.0.json new file mode 100644 index 00000000..1fe28ca5 --- /dev/null +++ b/agency-indexes/DoE/RF_mixing_modules_for_superconducting_qubit_room_temperature_control_systems_v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-10", + "metadataLastUpdated": "2021-06-11" + }, + "description": "We have developed a series of compact RF mixing boards by integrating I/Q quadrature mixing, IF(intermediate frequency)/LO(local oscillator)/RF power level adjustments, and DC (direct current) bias fine tuning on a 40 mm \u00d7 80 mm 4-layer PCB (printed circuit board) board with EMI (electromagnetic interference) shielding.", + "laborHours": 0.0, + "languages": [], + "name": "RF mixing modules for superconducting qubit room temperature control systems v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/LBL-QubiC/rfmixingmodules", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/RGM:__Random_Geological_Model_Generation_Package.json b/agency-indexes/DoE/RGM:__Random_Geological_Model_Generation_Package.json new file mode 100644 index 00000000..5ba93dba --- /dev/null +++ b/agency-indexes/DoE/RGM:__Random_Geological_Model_Generation_Package.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "This Fortran code is to accompany a manuscript to be submitted to Computers & Geosciences, a high-impact, peer-reviewed journal in computer methods for geosciences research. \n\nThis Fortran code focuses on generation of synthetic geological models using a multi-randomization strategy. Generating high-fidelity synthetic geological models, including realistic seismic reflector migration images, faults, salt bodies, and relative geological time images, is the key for many supervised machine learning methods that aim to delineate faults and other geological properties of interest from seismic migration images. Our package contains two major functionalities: generating 2D synthetic random geological models and generating 3D synthetic random geological models. In each step of the generation process, we set random values for key properties of a geological model to improve the fidelity of the resulting geological model. The package also includes example codes on how to use the random geological model generation subroutines. We name this package RGM \u2013 Random Geological Model generation package.", + "laborHours": 2280.0, + "languages": [], + "name": "RGM: Random Geological Model Generation Package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/rgm", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RIAPS_riaps-pycom.json b/agency-indexes/DoE/RIAPS_riaps-pycom.json new file mode 100644 index 00000000..1bf44ad1 --- /dev/null +++ b/agency-indexes/DoE/RIAPS_riaps-pycom.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "gabor.karsai@vanderbilt.edu" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2021-05-27" + }, + "description": "Python implementation of the RIAPS component model", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "RIAPS/riaps-pycom", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/RIAPS/riaps-pycom", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git", + "version": "1.1.18" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RLC4CLR__Reinforcement_Learning_Controller_for_Critical_Load_Restoration_Problems_.json b/agency-indexes/DoE/RLC4CLR__Reinforcement_Learning_Controller_for_Critical_Load_Restoration_Problems_.json new file mode 100644 index 00000000..0f303a45 --- /dev/null +++ b/agency-indexes/DoE/RLC4CLR__Reinforcement_Learning_Controller_for_Critical_Load_Restoration_Problems_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-09-19" + }, + "description": "RLC4CLR demonstrates using a reinforcement learning controller (RLC) to solve a critical load restoration (CLR) problem, which improves the grid resilience after a substation outage event. RLC4CLR consists of two parts. (1) RL environment: This environment encapsulates the CLR problem to be solved and provides interfacing functions to follow the standard OpenAI Gym format. A power system simulator, i.e., OpenDSS, is included to provide the power flow solution. Controller inputs and outputs (RL state and action) as well as the reward are defined in this environment as well. In summary, the RL environment is the problem formulation from which the RL agent can learn. (2) RL training script: The training script enables the RL agent to learn its control policy by interacting with the RL environment. For RL training, an open-sourced RL library, i.e., RLlib, is leveraged which is based on a distributed computing framework (Ray). The training script is designed to be able to be run on both local machine or the NREL HPC system. Other components of RLC4CLR include input data, e.g., grid model (standard IEEE test feeders), and other files used for results analysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "RLC4CLR (Reinforcement Learning Controller for Critical Load Restoration Problems)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rlc4clr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RMA-MT_Benchmarks_.json b/agency-indexes/DoE/RMA-MT_Benchmarks_.json new file mode 100644 index 00000000..af883063 --- /dev/null +++ b/agency-indexes/DoE/RMA-MT_Benchmarks_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-05-09", + "metadataLastUpdated": "2018-05-09" + }, + "description": "The RMA-MT benchmarks are a suite of performance tests for multi-threaded Message Passing Interface (MPI) Remote Memory Access (RMA) implementations. The suite includes tests for bandwidth and latency with any number of threads. This suite was originally developed and release by Sandia National Laboratory. LANL modifications to the suite include a complete re-write of much of the source code, bi-directional bandwidth, and message rate tests.", + "laborHours": 1155.2, + "name": "RMA-MT Benchmarks ", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/rma-mt", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RMEM-REMOTE_MEMORY.json b/agency-indexes/DoE/RMEM-REMOTE_MEMORY.json new file mode 100644 index 00000000..964d8466 --- /dev/null +++ b/agency-indexes/DoE/RMEM-REMOTE_MEMORY.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-09", + "metadataLastUpdated": "2024-03-26" + }, + "description": "RMEM - a prototyping platform to explore the usage of RMA-based strategies in GPU-to-GPU communication.\nThe implementation relies on libfabric (BSD-2 or GNUv2) to explore different synchronization approach and their associated performance. It is compatible with different network technologies such as InfiniBand, SlingShot-11, and TCP. It provides to the user host-to-host and device-to-device communication. The latter can be initiated either from the host, or from the device.", + "laborHours": 0.0, + "languages": [], + "name": "RMEM-REMOTE MEMORY", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/rmem", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RNA-seq_latent_featurizer_using_center_loss_cost_function.json b/agency-indexes/DoE/RNA-seq_latent_featurizer_using_center_loss_cost_function.json new file mode 100644 index 00000000..26f86f9c --- /dev/null +++ b/agency-indexes/DoE/RNA-seq_latent_featurizer_using_center_loss_cost_function.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-09-15", + "metadataLastUpdated": "2021-09-15" + }, + "description": "Predictive modeling of patient tumor growth response to drug treatment is severely limited by a lack of experimental data for training. Combining experimental data from several studies is an attractive approach, but presents two problems: batch effects and limited data for individual drugs and cell lines. Batch effects are caused by systematic procedural differences among studies, which causes systematic experimental outcome differences. Directly using these experimental results as features for machine learning commonly causes problems when training on one study and testing on another. This severely limits a model's ability to perform well on new experiments. Even after combining studies, predicting outcomes on new patient tumors remains an open challenge. We propose a semi-supervised, autoencoder-based, machine learning procedure, which learns a smaller set of gene expression features that are robust to batch effects using background information on a cell line or tissue's tumor type. We implemented this reduced feature representation and show that the new feature space clusters strongly according to tumor type. This experiment is carried out across multiple studies: CCLE, CTRP, gCSI, GDSC, NCI60, and patient derived tumors. We hypothesize that using a batch effect resistant feature set across studies will improve prediction performance. Genome Data Commons (GDC) gene expression profiles for publicly available human tissues and cell lines from NCI60 and CCLE were processed using the semi-supervised learning procedure. Our autoencoder repurposes the 'center loss' (CL) cost function of Wen et. al. to learn a more generalized set of features using the cell line or tissue's tumor type. ", + "laborHours": 0.0, + "languages": [], + "name": "RNA-seq latent featurizer using center loss cost function", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CBIIT/NCI-DOE-Collab-Pilot1-Semi-Supervised-Feature-Learning-with-Center-Loss", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RNA_virus_annotation_pipeline__RVAP__v1.0.json b/agency-indexes/DoE/RNA_virus_annotation_pipeline__RVAP__v1.0.json new file mode 100644 index 00000000..27d3da12 --- /dev/null +++ b/agency-indexes/DoE/RNA_virus_annotation_pipeline__RVAP__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "The code consists of two scripts that assign functional domains to RNA virus proteins. They achieve this by aggregating the outputs of multiple freely available tools and clustering the domains into high hierarchy clusters.", + "laborHours": 0.0, + "languages": [], + "name": "RNA virus annotation pipeline (RVAP) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/rvmt-jgi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/RODeO__Revenue_Operation_and_Device_Optimization_Model__[SWR_20-67].json b/agency-indexes/DoE/RODeO__Revenue_Operation_and_Device_Optimization_Model__[SWR_20-67].json new file mode 100644 index 00000000..fa56bf07 --- /dev/null +++ b/agency-indexes/DoE/RODeO__Revenue_Operation_and_Device_Optimization_Model__[SWR_20-67].json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2023-05-16" + }, + "description": "The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.", + "laborHours": 0.0, + "languages": [ + "GAMS", + "Batchfile", + "MATLAB", + "Python", + "Python" + ], + "name": "RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/RODeO", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ROI_Hide_and_Seek_Protocol_v1.json b/agency-indexes/DoE/ROI_Hide_and_Seek_Protocol_v1.json new file mode 100644 index 00000000..d548fa48 --- /dev/null +++ b/agency-indexes/DoE/ROI_Hide_and_Seek_Protocol_v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-11", + "metadataLastUpdated": "2021-08-13" + }, + "description": "1. Segmentation We provide scripts for the model definition of the U-net architecture adapted from: https://github.com/jvanvugt/pytorch-unet/blob/master/unet.py We developed scripts for preparing the lung segmentation data set. We developed scripts for training the U-Net architecture. We developed scripts for applying the trained U-Net model to perform the ROI Hide and Seek protocol on the classification dataset to create the modified dataset. 2. Classification We provide scripts for the training of the COVID-Net models provided by Linda Wang, this code is adapted from her github repository: https://github.com/lindawangg/COVID-Net/tree/d7b36831d854f57de5bc7557217f5439e86e016f. These scripts were modified to save training log information as well as to load the provided models in their github repo. We developed scripts for training standard Neural Network Models (resnet 50, vgg 11, Alexnet) on the COVID datsets along with the ROI Hide and Seek altered datasets.", + "laborHours": 0.0, + "languages": [], + "name": "ROI Hide and Seek Protocol v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electro1111/COVID_19_CXR_CLASSIFICATION", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ROMNet:_Neural-Network-Based_Surrogates_for_Reduced-Order_Model_Dynamics.json b/agency-indexes/DoE/ROMNet:_Neural-Network-Based_Surrogates_for_Reduced-Order_Model_Dynamics.json new file mode 100644 index 00000000..06298dbc --- /dev/null +++ b/agency-indexes/DoE/ROMNet:_Neural-Network-Based_Surrogates_for_Reduced-Order_Model_Dynamics.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-08", + "metadataLastUpdated": "2024-07-29" + }, + "description": "SAND2023-05829O\nROMNet is a toolbox built on the Tensorflow library for training reduced-order, neural operator surrogate models. The software is used for training reduced order neural operator surrogate models for dynamical systems applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 16446.4, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "ROMNet: Neural-Network-Based Surrogates for Reduced-Order Model Dynamics", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/romnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ROMPIO_v_1.0.0.json b/agency-indexes/DoE/ROMPIO_v_1.0.0.json new file mode 100644 index 00000000..d330b139 --- /dev/null +++ b/agency-indexes/DoE/ROMPIO_v_1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "ROMPIO is a software-based test designed to measure MPI collective, independent, asynchronous, and POSIX file I/O performance, synthesizing how applications utilize file systems in the LANL ASC computing environment. File layouts include N processors to N files and N processors to 1 file. Write access patterns include non-strided and strided. Pure network performance measure can also be obtained for relevant MPI collective calls.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [], + "name": "ROMPIO v 1.0.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ROSE-EDG_Binaries.json b/agency-indexes/DoE/ROSE-EDG_Binaries.json new file mode 100644 index 00000000..b8f1d51c --- /dev/null +++ b/agency-indexes/DoE/ROSE-EDG_Binaries.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2019-06-04" + }, + "description": "This repository contains ROSE-EDG binaries.", + "laborHours": 5605912.0, + "languages": [], + "name": "ROSE-EDG Binaries", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rose-compiler/rose", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ROSE.json b/agency-indexes/DoE/ROSE.json new file mode 100644 index 00000000..cf9cdffb --- /dev/null +++ b/agency-indexes/DoE/ROSE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-13", + "metadataLastUpdated": "2020-06-01" + }, + "description": "ROSE is a compiler infrastructure that builds source-to-source program transformation for a variety of programming languages. These transformations can be used for static analysis, program optimization, performance analysis, and cyber-security purposes. ", + "laborHours": 5605912.0, + "languages": [], + "name": "ROSE", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/rose-compiler/rose/blob/master/LicenseInformation/ROSE_BSD_License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rose-compiler/rose", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ROSE_Compiler_Framework_.json b/agency-indexes/DoE/ROSE_Compiler_Framework_.json new file mode 100644 index 00000000..74489138 --- /dev/null +++ b/agency-indexes/DoE/ROSE_Compiler_Framework_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-16" + }, + "description": "The purpose of the ROSE Complier Framework Is to automate source code porting, source and binary code analysis, and source code translations such as platform optimization, binary code analysis, Identification of source code and binary code vulnerablllttes.", + "laborHours": 5605912.0, + "languages": [], + "name": "ROSE Compiler Framework ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rose-compiler/rose", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ROSE_LCOM_Tools.json b/agency-indexes/DoE/ROSE_LCOM_Tools.json new file mode 100644 index 00000000..445e14a8 --- /dev/null +++ b/agency-indexes/DoE/ROSE_LCOM_Tools.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-01-08", + "metadataLastUpdated": "2024-01-08" + }, + "description": "This project provides a tool to compute LCOM metrics for important Ada abstraction mechanisms (e.g.,\npackages, protected objects). It analyzes data accesses and routine calls to compute an abstract\nrepresentation of an Ada package (or some other abstraction). Different LCOM metrics (1-5) are\ncomputed from the abstract representation. The project also provides support for representing the\nabstraction graphically (via graphviz). The LCOM tool requires an existing ROSE installation configured\nwith the GNAT 2019 compiler.", + "laborHours": 0.0, + "languages": [], + "name": "ROSE LCOM Tools", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ROSE-LCOM-Tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ROSSTEP_v1.3.json b/agency-indexes/DoE/ROSSTEP_v1.3.json new file mode 100644 index 00000000..dd31be50 --- /dev/null +++ b/agency-indexes/DoE/ROSSTEP_v1.3.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ROSSTEP is a system for sequentially running roslaunch, rosnode, and bash scripts automatically, for use in Robot Operating System (ROS) applications. The system consists of YAML files which define actions and conditions. A python file parses the code and runs actions sequentially using the sys and subprocess python modules. Between actions, it uses various ROS-based code to check conditions required to proceed, and only moves on to the next action when all the necessary conditions have been met. Included is rosstep-creator, a QT application designed to create the YAML files required for ROSSTEP. It has a nearly one-to-one mapping from interface elements to YAML output, and serves as a convenient GUI for working with the ROSSTEP system.", + "laborHours": 714.4, + "name": "ROSSTEP v1.3", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/Kukanani/rosstep/blob/8747daaa86110b2456711906177073ba7d511f92/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Kukanani/ROSSTEP", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ROVER.json b/agency-indexes/DoE/ROVER.json new file mode 100644 index 00000000..09d95aa5 --- /dev/null +++ b/agency-indexes/DoE/ROVER.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2018-06-19" + }, + "description": "ROVER Is an application for distributed-memory volume rendering and simulated radiography focused on many-core architectures (e.g., GPU, CPU, and MIC). Volume rendering, also known as volume visualization, is a commonly used scientific visualization algorithm that enables users to visualize an entire scalar field at once by mapping scalar values to colors and transparency. Simulated radiography Is a generalization of the volume rendering algorithm from four color channels (I.e., red, green, blue, and transparency) to an arbitrary number of channels representing material opacities in discrete energy groups, measured In electron volts.", + "laborHours": 81943.2, + "languages": [ + "C++" + ], + "name": "ROVER", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/rover", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RSBench.json b/agency-indexes/DoE/RSBench.json new file mode 100644 index 00000000..a4564202 --- /dev/null +++ b/agency-indexes/DoE/RSBench.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "A mini-app to represent the multipole resonance representation lookup cross section algorithm.\n", + "laborHours": 319.2, + "name": "RSBench", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/RSBench", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RUS-ORNL_RUScal.json b/agency-indexes/DoE/RUS-ORNL_RUScal.json new file mode 100644 index 00000000..ae005a66 --- /dev/null +++ b/agency-indexes/DoE/RUS-ORNL_RUScal.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "hermannrp@ornl.gov" + }, + "date": { + "created": "2022-02-01", + "metadataLastUpdated": "2022-02-01" + }, + "description": "Software to analyze resonant ultrasound spectroscopy measurements.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "RUS-ORNL/RUScal", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/RUS-ORNL/RUScal", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RVA:_A_Plugin_for_ParaView_3.14.json b/agency-indexes/DoE/RVA:_A_Plugin_for_ParaView_3.14.json new file mode 100644 index 00000000..eb3fdae7 --- /dev/null +++ b/agency-indexes/DoE/RVA:_A_Plugin_for_ParaView_3.14.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "ryan.morrone@netl.doe.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "RVA is a plugin developed for the 64-bit Windows version of the ParaView 3.14 visualization package. RVA is designed to provide support in the visualization and analysis of complex reservoirs being managed using multi-fluid EOR techniques. RVA, for Reservoir Visualization and Analysis, was developed at the University of Illinois at Urbana-Champaign, with contributions from the Illinois State Geological Survey, Department of Computer Science and National Center for Supercomputing Applications. RVA was designed to utilize and enhance the state-of-the-art visualization capabilities within ParaView, readily allowing joint visualization of geologic framework and reservoir fluid simulation model results. Particular emphasis was placed on enabling visualization and analysis of simulation results highlighting multiple fluid phases, multiple properties for each fluid phase (including flow lines), multiple geologic models and multiple time steps. Additional advanced functionality was provided through the development of custom code to implement data mining capabilities. The built-in functionality of ParaView provides the capacity to process and visualize data sets ranging from small models on local desktop systems to extremely large models created and stored on remote supercomputers. The RVA plugin that we developed and the associated User Manual provide improved functionality through new software tools, and instruction in the use of ParaView-RVA, targeted to petroleum engineers and geologists in industry and research. The RVA web site (http://rva.cs.illinois.edu) provides an overview of functions, and the development web site (https://github.com/shaffer1/RVA) provides ready access to the source code, compiled binaries, user manual, and a suite of demonstration data sets. Key functionality has been included to support a range of reservoirs visualization and analysis needs, including: sophisticated connectivity analysis, cross sections through simulation results between selected wells, simplified volumetric calculations, global vertical exaggeration adjustments, ingestion of UTChem simulation results, ingestion of Isatis geostatistical framework models, interrogation of joint geologic and reservoir modeling results, joint visualization and analysis of well history files, location-targeted visualization, advanced correlation analysis, visualization of flow paths, and creation of static images and animations highlighting targeted reservoir features.", + "laborHours": 7220.0, + "name": "RVA: A Plugin for ParaView 3.14", + "organization": "National Energy Technology Laboratory (NETL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/shaffer1/RVA/blob/master/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/shaffer1/RVA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Energy Technology Laboratory (NETL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RadSim:_ENSDF,_Xray_and_N42.json b/agency-indexes/DoE/RadSim:_ENSDF,_Xray_and_N42.json new file mode 100644 index 00000000..1154ef24 --- /dev/null +++ b/agency-indexes/DoE/RadSim:_ENSDF,_Xray_and_N42.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-21" + }, + "description": "This package includes three parts, (1) gov.bnl.nndc.ensdf, (2) gov.nist.xray and (3) gov.nist.physics.n42, which are utilized in the development of Radiation Detector Simulator (RadSim) project. RadSim is being developed to provide the capability to: (1) simulate radiation source emissions, (2) interpolate results from radiation transport tools into a common format to prepare incident flux, and (3) model radiation detector response to rapidly produce synthetic radiation measurement templates. RadSim is targeted for open-source release, which will enable researchers and industry partners to model gamma-ray detectors response to simulated flux from the transport tool of their choice. The first tool of the package, gov.bnl.nndc.ensdf, includes functionality to parse and split publicly available decay records in ENSDF format, and pull the relevant information from ENSDF libraries. The second tool, gov.nist.xray, provides Xray information using the public NIST database. Lastly, gov.nist.physics.n42, is a tool used to convert an N42 xml file into a Java object that can be interfaced within a Java program.", + "laborHours": 93373.6, + "languages": [], + "name": "RadSim: ENSDF, Xray and N42", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RadSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RadSim:_Math,_Utility_&_RTK.json b/agency-indexes/DoE/RadSim:_Math,_Utility_&_RTK.json new file mode 100644 index 00000000..a3c45ef1 --- /dev/null +++ b/agency-indexes/DoE/RadSim:_Math,_Utility_&_RTK.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-06-13", + "metadataLastUpdated": "2024-06-13" + }, + "description": "This package includes three parts, (1) gov.llnl.math, (2)gov.llnl.utility and (3)gov.llnl.rtk, which are utilized\nin the development of Radiation Detector Simulator (RadSim) project. RadSim is being developed to\nprovide the capability to: (1) simulate radiation source emissions, (2) interpolate results from radiation\ntransport tools into a common format to prepare incident flux, and (3) model radiation detector response\nto rapidly produce synthetic radiation measurement templates. RadSim is targeted for open-source\nrelease, which will enable researchers and industry partners to model gamma-ray detectors response to\nsimulated flux from the transport tool of their choice. The techniques and implementation will be entirely\ntransparent, which will allow for improvements and boutique modifications by future researchers beyond\nthe lifespan of this specific project.\nThe first tool of the package, gov.llnl.math, includes classes and functions to define and perform basic\nmath operations. Some of the example features available in the package include defining statistical\ndistributions and performing algebra and matrix operations, all of which are already accessible on publicly\navailable software packages such as MATLAB and ROOT. The second package gov.llnl.utility includes\ntools commonly used to enable optimization and readability of various data structures such as Java lists\nand external xml files. Lastly, the gov.llnl.rtk package includes classes and functions to implement\nmethods commonly used in radiation physics, such as data structures to represent and characterize\nphoton spectra and tools to apply well-defined and published methods to calibrate a given spectra.", + "laborHours": 93373.6, + "languages": [], + "name": "RadSim: Math, Utility & RTK", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RadSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RadTraQ__Radar_Tracking_and_Quality_Toolkit.json b/agency-indexes/DoE/RadTraQ__Radar_Tracking_and_Quality_Toolkit.json new file mode 100644 index 00000000..86e1caa9 --- /dev/null +++ b/agency-indexes/DoE/RadTraQ__Radar_Tracking_and_Quality_Toolkit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-10-18", + "metadataLastUpdated": "2021-10-18" + }, + "description": "RadTraQ is a python library housing routines related to assessing and monitoring the quality of a radar's quality and calibration. This library is a work in progress, currently housing scripts to plot radar CFADs, plot and analyze corner reflector scans, calculate noise floors, create cloud masks, and plot up average profiles for comparisons.", + "laborHours": 0.0, + "languages": [], + "name": "RadTraQ (Radar Tracking and Quality Toolkit", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Arm-Development/RadTraQ", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Radiation_Heat_Transfer_in_3_Dimensions_for_Semi-Transparent_Materials.....json b/agency-indexes/DoE/Radiation_Heat_Transfer_in_3_Dimensions_for_Semi-Transparent_Materials.....json new file mode 100644 index 00000000..6c4ff49c --- /dev/null +++ b/agency-indexes/DoE/Radiation_Heat_Transfer_in_3_Dimensions_for_Semi-Transparent_Materials.....json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The RAD3D software solves the critical heat transfer mechanisms that occur in production glass furnaces. The code includes state-of-the-art solution algorithms for efficient radiant interaction of the heating elements, furnace walls and internal furnace components. The code specifically solves the coupled radiative and conductive heating of semi-transparent materials such as glass to calculate the temperature distribution in the glass during processing.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Radiation Heat Transfer in 3 Dimensions for Semi-Transparent Materials....", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Radiological_Anomaly_Detection_And_Identification__RADAI__v1.0.json b/agency-indexes/DoE/Radiological_Anomaly_Detection_And_Identification__RADAI__v1.0.json new file mode 100644 index 00000000..63c4b7a3 --- /dev/null +++ b/agency-indexes/DoE/Radiological_Anomaly_Detection_And_Identification__RADAI__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-21", + "metadataLastUpdated": "2021-09-21" + }, + "description": "The Radiological Anomaly Detection and Identification (RADAI) software package is a python library for implementing, training, and storing algorithms that detect and identify anomalies in gamma-ray spectra. The library defines a general framework for implementing detection (binary) and identification (classification) algorithms, objects to encapsulate the results of analyses, a variety of temporal filtering tools that can be used in constructing algorithms, and conceptual design that allows easy reading and writing of algorithms (and their time dependent state). In addition to this framework, the library includes implementations of a variety of algorithms from the scientific literature including: gross-counts k-sigma, SPRT, N-SCRAD, Region of Interest, and Censored Energy Window. The implementation of these algorithms within the RADAI package was done to facilitate user-initiated training and configuration to by applied to different gamma-ray detector types. Finally, benchmarked and synthetic datasets will be made available for standardized algorithm characterization with corresponding utilities in the RADAI package for data access and processing.", + "laborHours": 0.0, + "languages": [], + "name": "Radiological Anomaly Detection And Identification (RADAI) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/lbl-anp/radai/radai", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ramen.json b/agency-indexes/DoE/Ramen.json new file mode 100644 index 00000000..4aeb53e7 --- /dev/null +++ b/agency-indexes/DoE/Ramen.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "dewittsj@ornl.gov" + }, + "date": { + "created": "2024-06-04", + "metadataLastUpdated": "2024-06-04" + }, + "description": "Many computationally unintensive models for material process-structure-property connections exist in the literature (e.g. journal articles and textbooks). However, to our knowledge there is no existing compilation of these models in one package. Many industrially and research relevant workflows involve combinations of many of these models and if the models have inconsistent interfaces, building these workflows can be challenging.\n\nRamen provides a collection of computationally unintensive models for calculating material process-structure-property relationships from the literature, as well as related tools (e.g. for plotting results). These models use a consistent interface structure and all leverage material data files and data structures from the Mist library (also developed at ORNL).\n\nRamen provides a structured package for combining many standard models in one place, with a standardized interface. This approach makes combining models in long/complex chains easy and straightforward.", + "laborHours": 228.0, + "languages": [ + "Python" + ], + "name": "Ramen", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-MDF/ramen", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ramping_and_Uncertainty_Prediction_Tool_-_Analysis_and_Visualization_of_Wind_Generation_Impact_on_Electrical_Grid.json b/agency-indexes/DoE/Ramping_and_Uncertainty_Prediction_Tool_-_Analysis_and_Visualization_of_Wind_Generation_Impact_on_Electrical_Grid.json new file mode 100644 index 00000000..4983a7d1 --- /dev/null +++ b/agency-indexes/DoE/Ramping_and_Uncertainty_Prediction_Tool_-_Analysis_and_Visualization_of_Wind_Generation_Impact_on_Electrical_Grid.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "RUT software is designed for use by the Balancing Authorities to predict and display additional requirements caused by the variability and uncertainty in load and generation. The prediction is made for the next operating hours as well as for the next day. The tool predicts possible deficiencies in generation capability and ramping capability. This deficiency of balancing resources can cause serious risks to power system stability and also impact real-time market energy prices. The tool dynamically and adaptively correlates changing system conditions with the additional balancing needs triggered by the interplay between forecasted and actual load and output of variable resources. The assessment is performed using a specially developed probabilistic algorithm incorporating multiple sources of uncertainty including wind, solar and load forecast errors. The tool evaluates required generation for a worst case scenario, with a user-specified confidence level.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "VB.NET" + ], + "name": "Ramping and Uncertainty Prediction Tool - Analysis and Visualization of Wind Generation Impact on Electrical Grid", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ranger-based_Iterative_Random_Forest.json b/agency-indexes/DoE/Ranger-based_Iterative_Random_Forest.json new file mode 100644 index 00000000..4e86359d --- /dev/null +++ b/agency-indexes/DoE/Ranger-based_Iterative_Random_Forest.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Iterative Random Forest (iRF) is an improvement upon the classic Random Forest, using weighted iterations to distill the forests. Ranger is a C++ implementation of random forest or recursive partitioning, particularly suited for high dimensional data. Ranger-Based iRF uses Ranger as a base Random Forest codebase upon which iterative and scalability aspects have been added.", + "laborHours": 6976.8, + "languages": [ + "C++/gnu-cmake" + ], + "name": "Ranger-based Iterative Random Forest", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Jromero1208/RangerBasediRF", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Rapid_Analytics_for_Disaster_Response__RADR_.json b/agency-indexes/DoE/Rapid_Analytics_for_Disaster_Response__RADR_.json new file mode 100644 index 00000000..aae3e8bb --- /dev/null +++ b/agency-indexes/DoE/Rapid_Analytics_for_Disaster_Response__RADR_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Rapid Analytics for Disaster Response (RADR) is a disaster response and situational awareness system that provides actionable insights using image analytics derived from optical and radar-based remotely-sensed imagery (optical and radar satellite, airborne, UAS). Geospatial analysis can also interface with the image analytic results to understand potential impacts to critical infrastructure assets. The rapid response is driven by a lifecycle workflow that spans event monitoring and action, image acquisition and retrieval, image pre-processing, image analytics algorithm deployment, analytics packaging, and analytics delivery.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Rapid Analytics for Disaster Response (RADR)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Rapid_Optimization_Library.json b/agency-indexes/DoE/Rapid_Optimization_Library.json new file mode 100644 index 00000000..a339aaf3 --- /dev/null +++ b/agency-indexes/DoE/Rapid_Optimization_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "ROL provides interfaces to and implementations of algorithms for gradient-based unconstrained and constrained optimization. ROL can be used to optimize the response of any client simulation code that evaluates scalar-valued response functions. If the client code can provide gradient information for the response function, ROL will take advantage of it, resulting in faster runtimes. ROL's interfaces are matrix-free, in other words ROL only uses evaluations of scalar-valued and vector-valued functions. ROL can be used to solve optimal design problems and inverse problems based on a variety of simulation software.", + "laborHours": 8344830.4, + "languages": [], + "name": "Rapid Optimization Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Rapid_Threat_Organism_Recognition_Pipeline.json b/agency-indexes/DoE/Rapid_Threat_Organism_Recognition_Pipeline.json new file mode 100644 index 00000000..38a5e999 --- /dev/null +++ b/agency-indexes/DoE/Rapid_Threat_Organism_Recognition_Pipeline.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The RAPTOR computational pipeline identifies microbial nucleic acid sequences present in sequence data from clinical samples. It takes as input raw short-read genomic sequence data (in particular, the type generated by the Illumina sequencing platforms) and outputs taxonomic evaluation of detected microbes in various human-readable formats. This software was designed to assist in the diagnosis or characterization of infectious disease, by detecting pathogen sequences in nucleic acid sequence data from clinical samples. It has also been applied in the detection of algal pathogens, when algal biofuel ponds became unproductive. RAPTOR first trims and filters genomic sequence reads based on quality and related considerations, then performs a quick alignment to the human (or other host) genome to filter out host sequences, then performs a deeper search against microbial genomes. Alignment to a protein sequence database is optional. Alignment results are summarized and placed in a taxonomic framework using the Lowest Common Ancestor algorithm.", + "homepageURL": "http://bioinformatics.sandia.gov/software", + "laborHours": 0.0, + "name": "Rapid Threat Organism Recognition Pipeline", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://bioinformatics.sandia.gov/software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://bioinformatics.sandia.gov/software", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Rapsodia.json b/agency-indexes/DoE/Rapsodia.json new file mode 100644 index 00000000..41c299c8 --- /dev/null +++ b/agency-indexes/DoE/Rapsodia.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "Rapide Surcharge d'Op\u00e9rateur pour la Diff\u00e9rentiation Automatique, a code generator to efficiently compute higher order derivatives via operator overloading. Rapsodia is intended for the computation of higher order derivative information of numerical models written in Fortran, C or C++ by automatic differentiation. ", + "homepageURL": "http://www.mcs.anl.gov/Rapsodia", + "laborHours": 0.0, + "languages": [], + "name": "Rapsodia", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.mcs.anl.gov/Rapsodia", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/RastKmerV2.json b/agency-indexes/DoE/RastKmerV2.json new file mode 100644 index 00000000..45d4d0f5 --- /dev/null +++ b/agency-indexes/DoE/RastKmerV2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This is the repository for \"RastKmerV2\" developed by KBase. ", + "laborHours": 1808.8, + "languages": [], + "name": "RastKmerV2", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/RastKmerV2", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ratpac-Two_v1.0.0.json b/agency-indexes/DoE/Ratpac-Two_v1.0.0.json new file mode 100644 index 00000000..ae87f5f6 --- /dev/null +++ b/agency-indexes/DoE/Ratpac-Two_v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-25" + }, + "description": "Geant-4 based detector simulations in c++ which combines simulation and analysis into a single framework to precisely model detector components and analyze experimental data. Ratpac allows the user to easily build new detector geometries and configurations through both the source library and through configurable text files at runtime.", + "laborHours": 48883.2, + "languages": [], + "name": "Ratpac-Two v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rat-pac/ratpac-two", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Rattlesnake_Vibration_Controller_v.2.0.json b/agency-indexes/DoE/Rattlesnake_Vibration_Controller_v.2.0.json new file mode 100644 index 00000000..033255dc --- /dev/null +++ b/agency-indexes/DoE/Rattlesnake_Vibration_Controller_v.2.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2022-08-02" + }, + "description": "SAND2021-7300 O The Rattlesnake Vibration Controller is a combined-environments, multiple input/multiple output control system for dynamic excitation of structures under test. It provides capabilities to control multiple responses on the part using multiple exciters and control strategies. Rattlesnake is written in the Python programming language to facilitate multiple input/multiple output vibration research by allowing users to prescribe custom control laws to the controller. Rattlesnake can target multiple hardware devices, or even perform synthetic control to simulate a test virtually. Rattlesnake has been used to execute control problems with up to 200 response channels and 12 drives. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "Rattlesnake Vibration Controller v.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/rattlesnake-vibration-controller", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ravel.json b/agency-indexes/DoE/Ravel.json new file mode 100644 index 00000000..624774b1 --- /dev/null +++ b/agency-indexes/DoE/Ravel.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Ravel is a trace visualization tool for MPI with recent experimental support for Charm++. Ravel is unique in that it shows not only physical timelines, but also logical ones structured to better capture the intended organization of communication operations. Ravel calculates logical structure from Open Trace Format or Charm++ Projections logs and presents the results using multiple coordinated views.\n", + "laborHours": 12555.2, + "languages": [], + "name": "Ravel", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ravel", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Raven.json b/agency-indexes/DoE/Raven.json new file mode 100644 index 00000000..7a8e9449 --- /dev/null +++ b/agency-indexes/DoE/Raven.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2023-03-15" + }, + "description": "RAVEN (Risk Analysis Virtual Environment) is a flexible and multi-purpose probabilistic risk analysis, uncertainty quantification, parameter optimization and data knowledge-discovering framework. https://raven.inl.gov/", + "laborHours": 770108.0, + "languages": [], + "name": "Raven", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/raven", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/RdTools\342\204\242_[SWR-17-40].json" "b/agency-indexes/DoE/RdTools\342\204\242_[SWR-17-40].json" new file mode 100644 index 00000000..42c44048 --- /dev/null +++ "b/agency-indexes/DoE/RdTools\342\204\242_[SWR-17-40].json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-01-31" + }, + "description": "RdTools\u2122 provides a set of tools for quantifying the degradation of photovoltaic systems and modules.", + "laborHours": 1003.2, + "languages": [ + "Python" + ], + "name": "RdTools\u2122 [SWR-17-40]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rdtools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2.2.0-beta.1" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/ReEDS\342\204\242_2.0__Regional_Energy_Deployment_System_Model__Version_2.0_[SWR-20-36_and_SWR-09-14].json" "b/agency-indexes/DoE/ReEDS\342\204\242_2.0__Regional_Energy_Deployment_System_Model__Version_2.0_[SWR-20-36_and_SWR-09-14].json" new file mode 100644 index 00000000..0d578ed0 --- /dev/null +++ "b/agency-indexes/DoE/ReEDS\342\204\242_2.0__Regional_Energy_Deployment_System_Model__Version_2.0_[SWR-20-36_and_SWR-09-14].json" @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-28", + "metadataLastUpdated": "2023-08-28" + }, + "description": "The Regional Energy Deployment System (ReEDS\u2122) Model 2.0 is a free, open-access tool that empowers users to explore least-cost pathways for large-scale power sector transformation. NREL's flagship energy capacity planning model for the North American electricity system allows users to examine the interactions between policy, technology, economics, and the environment when integrating renewables onto the grid from now through 2050.\n\nThis GitHub repository contains the source code for NREL's ReEDS\u2122 2.0model. Users of this source code agree to the ReEDS licensing agreement: https://nrel.gov/analysis/reeds/request-access.html.\n\n The ReEDS 2.0 model source code is available at no cost from the National Renewable Energy Laboratory (NREL). The ReEDS 2.0 model can be downloaded or cloned from https://github.com/NREL/ReEDS_OpenAccess. New users must request access to the ReEDS repository through https://nrel.gov/analysis/reeds/request-access.html.\n\nA ReEDS training video (recorded in July 2020 and based on the 2019 version of ReEDS) is available on the NREL YouTube channel at https://youtu.be/Cdo27F18AZA. In addition, the Open-Access ReEDS Webinar from October 2019 gives an overview of the 2019 ReEDS model and how it works (https://www.youtube.com/watch?v=QpRtvs_0kkA).", + "laborHours": 0.0, + "languages": [ + "Python", + "R", + "GAMS", + "Jupyter Notebook" + ], + "name": "ReEDS\u2122 2.0 (Regional Energy Deployment System Model) Version 2.0 [SWR-20-36 and SWR-09-14]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ReEDS-2.0", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "Version 2.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/ReEDS\342\204\242__Regional_Energy_Deployment_System__[SWR-20-36_and_SWR-09-14].json" "b/agency-indexes/DoE/ReEDS\342\204\242__Regional_Energy_Deployment_System__[SWR-20-36_and_SWR-09-14].json" new file mode 100644 index 00000000..1a91e195 --- /dev/null +++ "b/agency-indexes/DoE/ReEDS\342\204\242__Regional_Energy_Deployment_System__[SWR-20-36_and_SWR-09-14].json" @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-28", + "metadataLastUpdated": "2024-01-03" + }, + "description": "The Regional Energy Deployment System (ReEDS\u2122) is a free, open-access tool that empowers users to explore least-cost pathways for large-scale power sector transformation. NREL\u2019s flagship energy capacity planning model for the North American electricity system allows users to examine the interactions between policy, technology, economics, and the environment when integrating renewables onto the grid from now through 2050.", + "homepageURL": "https://www.nrel.gov/analysis/reeds", + "laborHours": 0.0, + "languages": [ + "GAMS", + "R", + "Python" + ], + "name": "ReEDS\u2122 (Regional Energy Deployment System) [SWR-20-36 and SWR-09-14]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/analysis/reeds/request-access.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/analysis/reeds", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ReFeX_RolX.json b/agency-indexes/DoE/ReFeX_RolX.json new file mode 100644 index 00000000..a41b10ec --- /dev/null +++ b/agency-indexes/DoE/ReFeX_RolX.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "This is the repository for ReFeX/RolX developed at Lawrence Livermore National Laboratory. \n", + "laborHours": 1048.8, + "languages": [], + "name": "ReFeX/RolX", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/refex-rolx", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ReMPI.json b/agency-indexes/DoE/ReMPI.json new file mode 100644 index 00000000..a20057d2 --- /dev/null +++ b/agency-indexes/DoE/ReMPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "ReMPI (MPI Record-and-Replay) is a record-and-replay tool for MPI applications written in C/C++ and/or fortran.", + "laborHours": 12980.8, + "languages": [], + "name": "ReMPI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PRUNERS/ReMPI", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ReSolve.json b/agency-indexes/DoE/ReSolve.json new file mode 100644 index 00000000..181f7533 --- /dev/null +++ b/agency-indexes/DoE/ReSolve.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "peless@ornl.gov" + }, + "date": { + "created": "2023-10-13", + "metadataLastUpdated": "2023-10-17" + }, + "description": "Library of GPU-resident linear solvers", + "laborHours": 0.0, + "languages": [ + "C++", + "CUDA", + "HIP" + ], + "name": "ReSolve", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/ReSolve", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/React_ART.json b/agency-indexes/DoE/React_ART.json new file mode 100644 index 00000000..19ff2861 --- /dev/null +++ b/agency-indexes/DoE/React_ART.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "React ART is a JavaScript library for drawing vector graphics using React. It provides declarative and reactive bindings to the ART library. Using the same declarative API you can render the output to either Canvas, SVG or VML (IE8). The examples directory contains a simple example of using React ART; you can also test out the art branch of the react-page project.", + "laborHours": 501.6, + "languages": [], + "name": "React ART", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/react-art", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/React_Axis.json b/agency-indexes/DoE/React_Axis.json new file mode 100644 index 00000000..7fd80fd8 --- /dev/null +++ b/agency-indexes/DoE/React_Axis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "Axis components built for React.", + "laborHours": 8451.2, + "languages": [], + "name": "React Axis", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/react-axis/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/react-axis", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/React_Dynamic_Forms.json b/agency-indexes/DoE/React_Dynamic_Forms.json new file mode 100644 index 00000000..5f21f210 --- /dev/null +++ b/agency-indexes/DoE/React_Dynamic_Forms.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "Dynamic forms library for React. This repository contains a set of React based forms components which are used within ESnet for our network database application (ESDB), but could be used by any React based project needing to build complex forms.", + "laborHours": 22450.4, + "languages": [], + "name": "React Dynamic Forms", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/react-dynamic-forms/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/react-dynamic-forms", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/React_Network_Diagrams.json b/agency-indexes/DoE/React_Network_Diagrams.json new file mode 100644 index 00000000..88588a59 --- /dev/null +++ b/agency-indexes/DoE/React_Network_Diagrams.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "This repository contains an initial set of React circuit drawing and network mapping components which are used within the ESnet Portal, but are not tied to ESnet, or even to network visualization.", + "laborHours": 38820.8, + "languages": [], + "name": "React Network Diagrams", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/react-network-diagrams/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/react-network-diagrams", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/React_Timeseries_Barchart.json b/agency-indexes/DoE/React_Timeseries_Barchart.json new file mode 100644 index 00000000..d9de8b59 --- /dev/null +++ b/agency-indexes/DoE/React_Timeseries_Barchart.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "A horizontal barchart that summarizes a list of TimeSeries objects. It was formally part of react-timeseries-charts. For charts visualizing a single TimeSeries in many different ways, see that library.", + "laborHours": 1048.8, + "languages": [], + "name": "React Timeseries Barchart", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/react-timeseries-barchart/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/react-timeseries-barchart", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/React_Timeseries_Charts.json b/agency-indexes/DoE/React_Timeseries_Charts.json new file mode 100644 index 00000000..cdb68d08 --- /dev/null +++ b/agency-indexes/DoE/React_Timeseries_Charts.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "Declarative and modular timeseries charting components for React. This library contains a set of modular charting components used for building flexible interactive charts. It was built for React from the ground up, specifically to visualize timeseries data and network traffic data in particular. Low level elements are constructed using d3, while higher level composability is provided by React. Charts can be stacked as rows, overlaid on top of each other, or any combination, all in a highly declarative manner. The library is used throughout the public facing ESnet Portal. Current features of the library include: Declarative layout of charts using JSX, interactivity, including pan and zoom, add new chart types or overlays, multiple axis, multiple rows, line, area, scatter, bar and boxplot charts, brushing, legends and overlay markers. ", + "laborHours": 251818.4, + "languages": [], + "name": "React Timeseries Charts", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/react-timeseries-charts/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/react-timeseries-charts", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/React_Timeseries_Table.json b/agency-indexes/DoE/React_Timeseries_Table.json new file mode 100644 index 00000000..a3f352ee --- /dev/null +++ b/agency-indexes/DoE/React_Timeseries_Table.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "This library contains a Table component for rendering pond.js TimeSeries objects. The library is used on the public facing ESnet Portal.", + "laborHours": 447913.6, + "languages": [], + "name": "React Timeseries Table", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/react-timeseries-table/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/react-timeseries-table", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/React_User_Profile_View_as_a_Plugin.json b/agency-indexes/DoE/React_User_Profile_View_as_a_Plugin.json new file mode 100644 index 00000000..23cb04d0 --- /dev/null +++ b/agency-indexes/DoE/React_User_Profile_View_as_a_Plugin.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-02", + "metadataLastUpdated": "2020-09-02" + }, + "description": "Profile view and edit page as a KBase-UI Plugin.", + "laborHours": 20732.8, + "languages": [], + "name": "React User Profile View as a Plugin", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/kbase-ui-plugin-react-profile-view", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Reaction_Rover.json b/agency-indexes/DoE/Reaction_Rover.json new file mode 100644 index 00000000..3dc39332 --- /dev/null +++ b/agency-indexes/DoE/Reaction_Rover.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2022-03-10", + "metadataLastUpdated": "2022-03-10" + }, + "description": "Reaction Rover is a software application designed to enable reaction optimization with little or no human intervention and to provide a flexible platform to facilitate rapid testing, automation, and implementation of new reaction optimization algorithms. Toward these goals, Reaction Rover is designed to be modular, allowing the optimization algorithm, analyzer, and reactor components to be changed for any given process using easily integrated plugins. The Reaction Rover platform is a key development that enables the testing, use, and automation of machine learning (ML) and non-ML optimizers in a variety of laboratory situations.", + "laborHours": 0.0, + "languages": [ + "LabVIEW", + "Python" + ], + "name": "Reaction Rover", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/RxnRover/RxnRover/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/RxnRover/RxnRover", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ReadsAPI.json b/agency-indexes/DoE/ReadsAPI.json new file mode 100644 index 00000000..60f88c9f --- /dev/null +++ b/agency-indexes/DoE/ReadsAPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "Service for fast retrieval of basic reads metadata for UI. 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", + "laborHours": 881.6, + "languages": [], + "name": "ReadsSetEditor", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ReadsSetEditor", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ReadsUtils.json b/agency-indexes/DoE/ReadsUtils.json new file mode 100644 index 00000000..5f9ef775 --- /dev/null +++ b/agency-indexes/DoE/ReadsUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "Functions for uploading and downloading reads to and from KBase.", + "laborHours": 3952.0, + "languages": [], + "name": "ReadsUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ReadsUtils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Real-Sim_Flexible_Interface_for_X-in-the-loop_Simulation__FIXS_.json b/agency-indexes/DoE/Real-Sim_Flexible_Interface_for_X-in-the-loop_Simulation__FIXS_.json new file mode 100644 index 00000000..9454f6c4 --- /dev/null +++ b/agency-indexes/DoE/Real-Sim_Flexible_Interface_for_X-in-the-loop_Simulation__FIXS_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "realsimxil@gmail.com" + }, + "date": { + "created": "2023-07-27", + "metadataLastUpdated": "2023-07-28" + }, + "description": "Real-Sim is a multi-resolution X-in-the-loop simulation framework to support inclusive testing and evaluation of CAVs before actual implementation in the real world. Real-Sim framework connects different simulation components and integrates various traffic and vehicle simulation tools, virtual environments, and XIL systems through a Flexible Interface for XIL Simulation (FIXS). Connections among different tools are transparent to users and handled by the interface behind the scenes. Co-simulation of various vehicle and traffic simulation tools with different XIL systems can be easily achieved and become a transparent \"plug-and-play\" process to users.", + "laborHours": 0.0, + "languages": [], + "name": "Real-Sim Flexible Interface for X-in-the-loop Simulation (FIXS)", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Real-Sim-XIL/FIXS", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Real-Time_Distributed_Energy_Resource_Energy_Dispatch_Using_Distributed_Control.json b/agency-indexes/DoE/Real-Time_Distributed_Energy_Resource_Energy_Dispatch_Using_Distributed_Control.json new file mode 100644 index 00000000..d11d6af6 --- /dev/null +++ b/agency-indexes/DoE/Real-Time_Distributed_Energy_Resource_Energy_Dispatch_Using_Distributed_Control.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-11-19", + "metadataLastUpdated": "2019-11-19" + }, + "description": "This software is to implement real-time energy dispatch for distributed energy resources such as distributed PV, using distributed control algorithm that NREL has developed. The software is developed using Python and is available as open-source. ", + "laborHours": 957.6, + "languages": [ + "Python" + ], + "name": "Real-Time Distributed Energy Resource Energy Dispatch Using Distributed Control", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DER-Dispatch", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Real-Time_Optimization_of_Distribution-level_Energy_Resources_[SWR-18-27].json b/agency-indexes/DoE/Real-Time_Optimization_of_Distribution-level_Energy_Resources_[SWR-18-27].json new file mode 100644 index 00000000..cf6f259a --- /dev/null +++ b/agency-indexes/DoE/Real-Time_Optimization_of_Distribution-level_Energy_Resources_[SWR-18-27].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-08-08", + "metadataLastUpdated": "2023-04-24" + }, + "description": "Researchers at NREL have developed a novel real-time control architecture to optimize the operation of DERs at residential, commercial, and industrial levels. The real-time system enables (portions of) feeders to emulate virtual power plants providing services to the rest of the grid, while ensuring satisfaction of electrical limits and maximizing customers\u2019 benefits. This system can be integrated with legacy hardware and/or new advanced systems to optimally manage both individually-controlled DERs and aggregations of DERs. By virtue of the proposed engineering approach, the DERs collectively regulate the powers at an electrical point to respond to grid dispatch signals such as an automatic generation control, a ramping signal, or a 5-minute dispatch. Overall, this architecture allows end customers to minimize their payments and partake in grid operations while guaranteeing power quality in the distribution network.", + "homepageURL": "https://www.labpartnering.org/p/lab-technologies/ce8d218e-4826-497d-aa9b-af23282648ec", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Real-Time Optimization of Distribution-level Energy Resources [SWR-18-27]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.federallabs.org/technology/real-time-optimization-of-distribution-level-energy-resources", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.labpartnering.org/p/lab-technologies/ce8d218e-4826-497d-aa9b-af23282648ec", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Real-time_time-dependent_density_functional_theory_in_Quantum_Espresso_and_related_codes.json b/agency-indexes/DoE/Real-time_time-dependent_density_functional_theory_in_Quantum_Espresso_and_related_codes.json new file mode 100644 index 00000000..5592aac9 --- /dev/null +++ b/agency-indexes/DoE/Real-time_time-dependent_density_functional_theory_in_Quantum_Espresso_and_related_codes.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2024-09-18" + }, + "description": "A set of subroutines that interact with an existing computer program, Quantum Espresso (QE), that takes a set of electronic orbitals from QE and propagates them forward in time in response to a number of perturbations. These perturbations include the motion of ions and a wide spectrum of applied electromagnetic fields (e.g., static magnetic fields, slowly-varying electric fields, x-rays, etc.). From the time evolution of the electronic orbitals comes time-varying values of physical observables like the electronic charge and current densities and atomic forces. These are further post-processed to yield properties of interest like stopping powers, conductivities, and the dynamic structure factor. The electronic orbitals are described in a plane wave basis and the equations of motion are carried out using a unitary or approximately unitary time propagation algorithm. Related work will include subroutines for interfacing this capability, as well as others that already exist within QE, with a fork of QE that is more extensible and modular.SAND2019-12611 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1519589.6, + "languages": [ + "Shell", + "HTML", + "C", + "Roff", + "Fortran", + "PostScript" + ], + "name": "Real-time time-dependent density functional theory in Quantum Espresso and related codes", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/qe-rt-tddft", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RealGasBrine_v1.0_option_of_TOUGH+_v1.5.json b/agency-indexes/DoE/RealGasBrine_v1.0_option_of_TOUGH+_v1.5.json new file mode 100644 index 00000000..f2a68eed --- /dev/null +++ b/agency-indexes/DoE/RealGasBrine_v1.0_option_of_TOUGH+_v1.5.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-11", + "metadataLastUpdated": "2018-10-15" + }, + "description": "RealGasBrine v1.0 is a numerical code that for the simulation of the behavior of gas-bearing porous and/fractured geologic media. It is an option of TOUGH+ v1.5 [Moridis, 2014], a successor to the TOUGH2 [Pruess et al., 1999; 2012] family of codes for multi-component, multiphase \ufb02uid and heat \ufb02ow developed at the Lawrence Berkeley National Laboratory. RealGasBrine v1.0 needs the TOUGH+ v1.5 core code in order to compile and execute. It is written in standard FORTRAN 95/2003, and can be run on any computational platform (workstation, PC, Macintosh) for which such compilers are available. \nRealGasBrine v1.0 describes the non-isothermal two- (for pure water) or three-phase (for brine) flow of an aqueous phase and a real gas mixture in a gas-bearing medium, with a particular focus in ultra-tight (such as tight-sand and shale gas) systems. Up to 12 individual real gases can be tracked, and salt can precipitate as solid halite. The capabilities of the code include coupled flow and thermal effects, real gas behavior, Darcy and non-Darcy flow, several isotherm options of gas sorption onto the grains of the porous media, complex fracture descriptions, gas solubility into water, and geomechanical effects on flow properties. RealGasBrine v1.0 allows the study of flow and transport of fluids and heat over a wide range of time frames and spatial scales not only in gas reservoirs, but also in any problem involving the flow of gases in geologic media, including the geologic storage of greenhouse gas mixtures, the behavior of geothermal reservoirs with multi-component condensable (H2O and CO2) and non-condensable gas mixtures, the transport of water and released H2 in nuclear waste storage applications, etc.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 6414.4, + "languages": [], + "name": "RealGasBrine v1.0 option of TOUGH+ v1.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Real_Time_Streaming_Data_visualization_tooling__RTS_Data_Vis_App_.json b/agency-indexes/DoE/Real_Time_Streaming_Data_visualization_tooling__RTS_Data_Vis_App_.json new file mode 100644 index 00000000..7ea98313 --- /dev/null +++ b/agency-indexes/DoE/Real_Time_Streaming_Data_visualization_tooling__RTS_Data_Vis_App_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-21" + }, + "description": "NREL's RTS Data Vis App contains the following sub-projects: (1) Conditioner: A tool to resample high-rate data from the relay for low-rate visualization and (2) Chart: A tool to plot the data from the relay, including a specialized copy of the Conditioner. The Conditioner is a command-line tool for reading ADMS data from ZMQ, resampling, and exporting over a websocket. The Chart is an example of a charting tool for ADMS applications, using a ZMQ message bus.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Real Time Streaming Data visualization tooling (RTS Data Vis App)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rts-vis-app", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Realistic_Simulation_of_Property_Graphs.json b/agency-indexes/DoE/Realistic_Simulation_of_Property_Graphs.json new file mode 100644 index 00000000..904d206b --- /dev/null +++ b/agency-indexes/DoE/Realistic_Simulation_of_Property_Graphs.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Building on the existing Multiplicative Attribute Graph (MAG) model, the software relaxes the assumptions of the MAG model allowing dataset expansion while replicating statistical properties.", + "laborHours": 349.6, + "name": "Realistic Simulation of Property Graphs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/propgraph/pgm/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/propgraph/pgm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Recombinant_And_Mix-Infection_Finder_for_SARS-CoV-2_sample.json b/agency-indexes/DoE/Recombinant_And_Mix-Infection_Finder_for_SARS-CoV-2_sample.json new file mode 100644 index 00000000..4f77d026 --- /dev/null +++ b/agency-indexes/DoE/Recombinant_And_Mix-Infection_Finder_for_SARS-CoV-2_sample.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-05" + }, + "description": "The scientific and public health communities responded to the COVID-19 pandemic with\nsample acquisition and genome sequencing on a scale that eclipsed all prior sequencing\nefforts. While this can only be characterized as a resounding success story that has\ncemented the use of genomics for epidemiological investigations for any future infectious\ndisease outbreak, several retrospective studies are cataloging an array of lessons learned\nand issues that have yet to be addressed in order to realize the full potential of genomics as\na routine biosurveillance tool. We have been both developing methods to accurately assess\nSARS-CoV-2 genomes from complex samples, and analyzing the large volumes of\ninternational data, both at the consensus level and the raw sequencing data. During the\ncourse of our investigations and similar to other groups, we have examined COVID-19\nsamples with signatures from multiple lineages of SARS-CoV-2 and will describe some of\nour findings during the development of a novel workflow that incorporates detection and\nreporting of potential co-infection within samples and also highlights any evidence of\nwithin-host recombination.", + "laborHours": 0.0, + "languages": [], + "name": "Recombinant And Mix-Infection Finder for SARS-CoV-2 sample", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ramifi", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Reconductoring_Economic_and_Financial_Analysis_Tool__REFA__v1.0.json b/agency-indexes/DoE/Reconductoring_Economic_and_Financial_Analysis_Tool__REFA__v1.0.json new file mode 100644 index 00000000..fdacae74 --- /dev/null +++ b/agency-indexes/DoE/Reconductoring_Economic_and_Financial_Analysis_Tool__REFA__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-11", + "metadataLastUpdated": "2024-07-11" + }, + "description": "REFA is designed to help transmission planners better understand the financial, environmental and economic benefits of reconductoring upgrades, using traditional or advanced conductors. More specifically, the tool enables grid planners and utilities to demonstrate the entire lifetime value of reconductoring projects, providing potential justifications for projects with higher Capex - the purchase of long-term physical or fixed assets used in a business's operations. Existing tools are designed to compare technical aspects of different conductor applications. They typically do not allow a cost-benefit analysis over the lifetime of the conductor's operations.", + "homepageURL": "https://gridintegration.lbl.gov/refa", + "laborHours": 98800.0, + "languages": [], + "name": "Reconductoring Economic and Financial Analysis Tool (REFA) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://gridintegration.lbl.gov/refa", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://gridintegration.lbl.gov/refa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Reduced-order_model_for_biomass_pyrolysis.json b/agency-indexes/DoE/Reduced-order_model_for_biomass_pyrolysis.json new file mode 100644 index 00000000..b840596d --- /dev/null +++ b/agency-indexes/DoE/Reduced-order_model_for_biomass_pyrolysis.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "albertop@iastate.edu" + }, + "date": { + "created": "2022-03-31", + "metadataLastUpdated": "2022-03-31" + }, + "description": "Reduced-order model that takes the biomass biochemical composition as input and returns the primary pyrolysis products in a dictionary. ", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Reduced-order model for biomass pyrolysis", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Biomass-Autothermal-Pyrolysis/ReducedOrderModel", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Reduced_Order_Model_Basis_Vector_Generation:_Generates_Basis_Vectors_fro_ROMs.json b/agency-indexes/DoE/Reduced_Order_Model_Basis_Vector_Generation:_Generates_Basis_Vectors_fro_ROMs.json new file mode 100644 index 00000000..311f5ecc --- /dev/null +++ b/agency-indexes/DoE/Reduced_Order_Model_Basis_Vector_Generation:_Generates_Basis_Vectors_fro_ROMs.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "libROM is a library that implements order reduction via singular value decomposition (SVD) of sampled state vectors. It implements 2 parallel, incremental SVD algorithms and one serial, non-incremental algorithm. It also provides a mechanism for adaptive sampling of basis vectors.", + "laborHours": 16887.2, + "name": "Reduced Order Model Basis Vector Generation: Generates Basis Vectors fro ROMs", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/libROM/blob/master/README_BSD_NOTICE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/libROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Reduced_Order_Modeling_for_Accelerating_Numerical_Simulations__ROMANS_.json b/agency-indexes/DoE/Reduced_Order_Modeling_for_Accelerating_Numerical_Simulations__ROMANS_.json new file mode 100644 index 00000000..3afac435 --- /dev/null +++ b/agency-indexes/DoE/Reduced_Order_Modeling_for_Accelerating_Numerical_Simulations__ROMANS_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-02-23", + "metadataLastUpdated": "2022-02-24" + }, + "description": "SAND2021-15064 O ROMANS, or Reduced Order Modeling for Accelerating Numerical Simulations, is an open source software for accelerating numerical simulations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "python 3" + ], + "name": "Reduced Order Modeling for Accelerating Numerical Simulations (ROMANS)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/romans", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Reeber_v2.0.json b/agency-indexes/DoE/Reeber_v2.0.json new file mode 100644 index 00000000..3edc7437 --- /dev/null +++ b/agency-indexes/DoE/Reeber_v2.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-01", + "metadataLastUpdated": "2021-03-01" + }, + "description": "Reeber is a library for shared- and distributed-memory parallel computation of merge trees", + "laborHours": 0.0, + "languages": [], + "name": "Reeber v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mrzv/reeber", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Reegle_Tagging_API__CKAN_Extension__[SWR-14-28].json b/agency-indexes/DoE/Reegle_Tagging_API__CKAN_Extension__[SWR-14-28].json new file mode 100644 index 00000000..2de5f036 --- /dev/null +++ b/agency-indexes/DoE/Reegle_Tagging_API__CKAN_Extension__[SWR-14-28].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "The software consists of a CKAN extension to an existing REEGLE Tagging API.", + "laborHours": 106.4, + "languages": [], + "name": "Reegle Tagging API (CKAN Extension) [SWR-14-28]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/REEEP/ckanext-climate-tagger/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/REEEP/ckanext-climate-tagger", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Refdata_Sync.json b/agency-indexes/DoE/Refdata_Sync.json new file mode 100644 index 00000000..65355b0f --- /dev/null +++ b/agency-indexes/DoE/Refdata_Sync.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "Sync genomic reference data to the local file system.", + "laborHours": 30.4, + "languages": [], + "name": "Refdata Sync", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/refdata_sync", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ReferenceDataManager.json b/agency-indexes/DoE/ReferenceDataManager.json new file mode 100644 index 00000000..d77a4aeb --- /dev/null +++ b/agency-indexes/DoE/ReferenceDataManager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "This SDK module contains functions related to the loading, updating, and management of reference data in KBase.", + "laborHours": 13330.4, + "languages": [], + "name": "ReferenceDataManager", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ReferenceDataManager", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Reframe_v._1.0.json b/agency-indexes/DoE/Reframe_v._1.0.json new file mode 100644 index 00000000..74eeb15d --- /dev/null +++ b/agency-indexes/DoE/Reframe_v._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Reframe enables the parsing of a document in the PDF format and the recovery of the hierarchical structure of the content within.", + "homepageURL": "https://github.com/sandialabs/reframe", + "laborHours": 3040.0, + "languages": [ + "Java" + ], + "name": "Reframe v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://github.com/sandialabs/reframe", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Regex-Stream.json b/agency-indexes/DoE/Regex-Stream.json new file mode 100644 index 00000000..45b67a2d --- /dev/null +++ b/agency-indexes/DoE/Regex-Stream.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Log files are typically semi-or un-structured. To be useable, they need to be parsed into a standard, structured format. Regex-Stream facilitates parsing text files into structured data (JSON) in streams of data.", + "laborHours": 34488.8, + "name": "Regex-Stream", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/regex-stream", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Regional_Seismic_Travel_Time_v.3.2.0.json b/agency-indexes/DoE/Regional_Seismic_Travel_Time_v.3.2.0.json new file mode 100644 index 00000000..8bf0320c --- /dev/null +++ b/agency-indexes/DoE/Regional_Seismic_Travel_Time_v.3.2.0.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-09-30", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The RSTT software computes predictions of the travel time of seismic energy traveling from a source to a receiver through 2.5D models of the seismic velocity distribution within the Earth. The two primary applications for the RSTT library are tomographic inversion studies and seismic event location calculations. In tomographic inversions studies, a seismologist begins with number of source-receiver travel time observations and an initial starting model of the velocity distribution within the Earth. A forward travel time calculator, such as the RSTT library, is used to compute predictions of each observed travel time and all of the residuals (observed minus predicted travel time) are calculated. The Earth model is then modified in some systematic way with the goal of minimizing the residuals. The Earth model obtained in this way is assumed to be a better model than the starting model if it has lower residuals. The other major application for the RSTT library is seismic event location. Given an Earth model, an initial estimate of the location of a seismic event, and some number of observations of seismic travel time thought to have originated from that event, location codes systematically modify the estimate of the location of the event with the goal of minimizing the difference between the observed and predicted travel times. The second application, seismic event location, is routinely implemented by the military as part of its effort to monitor the Earth for nuclear tests conducted by foreign countries.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Fortran", + "Java", + "C++", + "C" + ], + "name": "Regional Seismic Travel Time v.3.2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/rstt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Regression_of_3D_Sky_Map_to_Cosmological_Parameters__CosmoFlow__v1.0.json b/agency-indexes/DoE/Regression_of_3D_Sky_Map_to_Cosmological_Parameters__CosmoFlow__v1.0.json new file mode 100644 index 00000000..31066373 --- /dev/null +++ b/agency-indexes/DoE/Regression_of_3D_Sky_Map_to_Cosmological_Parameters__CosmoFlow__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-22", + "metadataLastUpdated": "2021-04-22" + }, + "description": "The neural network constructed of 3D convolutional and fully connected layers was trained on the simulated mass distribution of the Universe with the purpose to recover the values of cosmological parameters used to generate the Universe.", + "laborHours": 0.0, + "languages": [], + "name": "Regression of 3D Sky Map to Cosmological Parameters (CosmoFlow) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/balewski/cosmoflow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Reinforcement_Learning_for_Distribution_Grid_Optimization__PyCIGAR__v0.1.json b/agency-indexes/DoE/Reinforcement_Learning_for_Distribution_Grid_Optimization__PyCIGAR__v0.1.json new file mode 100644 index 00000000..2ad075fa --- /dev/null +++ b/agency-indexes/DoE/Reinforcement_Learning_for_Distribution_Grid_Optimization__PyCIGAR__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-09-16" + }, + "description": "PyCIGAR is a python software package that merges off-the-shelf reinforcement learning libraries (RLLib and Ray) with electric power distribution system simulation tools (OpenDSS and a custom power flow solver built by LBL). PyCIGAR enables the training of neural networks to optimize the behavior of different components in the electric distribution grid, such as control systems in photovoltaic rooftop solar inverters and electric battery storage systems. The software package has been used to train neural networks to update settings in photovoltaic rooftop solar inverter control systems to mitigate cyber attacks on other solar photovoltaic rooftop devices.", + "laborHours": 13391.2, + "languages": [], + "name": "Reinforcement Learning for Distribution Grid Optimization (PyCIGAR) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/ceds-cigar", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RelationEngineEval.json b/agency-indexes/DoE/RelationEngineEval.json new file mode 100644 index 00000000..1290d295 --- /dev/null +++ b/agency-indexes/DoE/RelationEngineEval.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": " This is the repository for \"Relation Engine Evaluation\" developed by KBase.", + "laborHours": 212.8, + "languages": [], + "name": "RelationEngineEval", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/RelationEngineEval", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Relation_Engine_API.json b/agency-indexes/DoE/Relation_Engine_API.json new file mode 100644 index 00000000..d0b3e451 --- /dev/null +++ b/agency-indexes/DoE/Relation_Engine_API.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "A simple API that allows KBase community developers to interact with the Relation Engine graph database. You can run stored queries or do bulk updates on documents.", + "laborHours": 972.8, + "languages": [], + "name": "Relation Engine API", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/relation_engine_api", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Relation_Engine_Import_Coordinator.json b/agency-indexes/DoE/Relation_Engine_Import_Coordinator.json new file mode 100644 index 00000000..0d8587ac --- /dev/null +++ b/agency-indexes/DoE/Relation_Engine_Import_Coordinator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "This is the repository for \"Relation Engine Import Coordinator\" developed by KBase.", + "laborHours": 45.6, + "languages": [], + "name": "Relation Engine Import Coordinator", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/re_import_coordinator", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Relation_Engine_Incubator.json b/agency-indexes/DoE/Relation_Engine_Incubator.json new file mode 100644 index 00000000..c9388699 --- /dev/null +++ b/agency-indexes/DoE/Relation_Engine_Incubator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "An area for developing scripts / loaders etc before moving them into the RE repositories proper.", + "laborHours": 1945.6, + "languages": [], + "name": "Relation Engine Incubator", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/relation_engine_incubator", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Relation_Engine_Spec.json b/agency-indexes/DoE/Relation_Engine_Spec.json new file mode 100644 index 00000000..8485b267 --- /dev/null +++ b/agency-indexes/DoE/Relation_Engine_Spec.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "Specifications and config for the KBase Relation Engine. This repo holds the stored queries, schemas, and migrations for the relation engine graph database service. These specifications are used by the Relation Engine API.", + "laborHours": 3891.2, + "languages": [], + "name": "Relation Engine Spec", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/relation_engine_spec", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Relational_Blackboard.json b/agency-indexes/DoE/Relational_Blackboard.json new file mode 100644 index 00000000..f41ccf5d --- /dev/null +++ b/agency-indexes/DoE/Relational_Blackboard.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The Relational Blackboard (RBB) is an extension of the H2 Relational Database to support discrete events and timeseries data. The original motivation for RBB is as a knowledge base for cognitive systems and simulations. It is useful wherever there is a need for persistent storage of timeseries (i.e. samples of a continuous process generating numerical data) and semantic labels for the data. The RBB is an extension to the H2 Relational Database, which is open-source. RBB is a set of stored procedures for H2 allowing data to be labeled, queried, and resampled.", + "laborHours": 62107.2, + "languages": [ + "Java", + "HTML" + ], + "name": "Relational Blackboard", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/RelationalBlackboard", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Reliability_Availability_Serviceability.json b/agency-indexes/DoE/Reliability_Availability_Serviceability.json new file mode 100644 index 00000000..6e89d5d2 --- /dev/null +++ b/agency-indexes/DoE/Reliability_Availability_Serviceability.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Our work is aimed at providing a data store for system-level events and presenting a flexible query interface to those events. The work extends the functinality provided by the open source Request Tracker (RT) (http://www.bestpractical.com/rt) project witht the Asset Tracker (AT) addon (http://atwiki.chaka.net). We have developed an Event Tracker add-on to RT and an interface for gathering, dispatching, and inserting system events into Event Tracker. Data sources include data from all components of the system. Data is initially sent to a defined set of data filters. The data filters are capable of discarding specified data, throttling input, handling context-sensitive input, passing data through an external shell pipe command, and compressing multiple data enteries into a single event. The filters then pass the data on to an event dispatch engine. The dispatcher can print events to the screen as they happen, track them in the database, forward them on, or pass them on to an external command. By collecting all of the data into a single database, we are able to leverage the Query Builder interface supplied by RT to create, save, and restore almost any kind of query imaginable.", + "homepageURL": "https://sourceforge.net/projects/rasilience", + "laborHours": 0.0, + "name": "Reliability Availability Serviceability", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/rasilience", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Relleno.json b/agency-indexes/DoE/Relleno.json new file mode 100644 index 00000000..d1f88fe7 --- /dev/null +++ b/agency-indexes/DoE/Relleno.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-09-04", + "metadataLastUpdated": "2020-09-18" + }, + "description": "Relleno is a library built atop the general-purpose symbolic mathematics known as SageMath. Relleno facilitates the derivation of new techniques for numerically solving conservation laws in scientific computing.SAND2019-11608 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.\n", + "laborHours": 16340.0, + "languages": [], + "name": "Relleno", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Relleno", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Remedial_Action_Assessment_System.json b/agency-indexes/DoE/Remedial_Action_Assessment_System.json new file mode 100644 index 00000000..7da35aa7 --- /dev/null +++ b/agency-indexes/DoE/Remedial_Action_Assessment_System.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-28", + "metadataLastUpdated": "2023-01-17" + }, + "description": "RAAS1.1 is a software-based system designed to assist remediation professionals at each stage of the environmental analysis process. RAAS1.1 provides a template for environmental restoration analysis, and provides the user with key results at each step in the analysis. RAAS1.1 assists the user to develop a coherent and consistent site description, estimate baseline and residual risk to public health from the contaminated site, identify applicable environmental restoration technologies, and formulate feasible remedial response alternatives. In addition, the RAAS1.1 methodology allows the user to then assess and compare those remedial response alternatives across EPA criteria, including: compliance with objectives; short-term and long-term effectiveness; extent of treatment; and implementability of the technologies. The analytic methodology is segmented and presented in a standardized, concise, easy-to-use format that can be viewed on the personal computer screen, saved and further manipulated, or printed for later use. Each screen and analytic step is accessed via a user-friendly personal computer graphical interface. Intuitively-designed buttons, menus, and lists help the user focus in on the particular information and analysis component of interest; the corresponding results are presented in a format that facilitates their use in decision-making.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Remedial Action Assessment System", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Remedy_Application_Statistics.json b/agency-indexes/DoE/Remedy_Application_Statistics.json new file mode 100644 index 00000000..95384da4 --- /dev/null +++ b/agency-indexes/DoE/Remedy_Application_Statistics.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-05-09", + "metadataLastUpdated": "2018-05-09" + }, + "description": "The forms and workflow developed were designed to collect additional statistical information not normally available in out of- the-box implementations of the Remedy Action Request System designed by BMC Software. This workflow is used to collect additional information about users accessing the Remedy application, such as operating system and browser type. This information along with frequency of user logins, number of emails sent and received, and overall license usage help provide Remedy Administrators a better overview of the application they support. These custom forms and workflow work heavily with existing out-of-the-box forms in Remedy, and display the collected data to users through the product BMC\u2019s companion product Smart Reporting. ", + "laborHours": 60420.0, + "name": "Remedy Application Statistics", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Remedy-Application-Statistics", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Remote_Mirror_Security.json b/agency-indexes/DoE/Remote_Mirror_Security.json new file mode 100644 index 00000000..60ab8664 --- /dev/null +++ b/agency-indexes/DoE/Remote_Mirror_Security.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-01-28", + "metadataLastUpdated": "2020-01-28" + }, + "description": "The Remote Mirror Security project is a git hook used to evaluate a remote repository from which changes are mirrored and enforce a security policy before accepting changes.", + "laborHours": 866.4, + "languages": [], + "name": "Remote Mirror Security", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/remote-mirror-security", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Remote_Sensor_Design_for_Visual_Recognition_with_Convolutional_Neural_Networks.json b/agency-indexes/DoE/Remote_Sensor_Design_for_Visual_Recognition_with_Convolutional_Neural_Networks.json new file mode 100644 index 00000000..b7510237 --- /dev/null +++ b/agency-indexes/DoE/Remote_Sensor_Design_for_Visual_Recognition_with_Convolutional_Neural_Networks.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-03", + "metadataLastUpdated": "2019-05-06" + }, + "description": "While deep learning technologies for computer vision have developed rapidly since 2012, modeling of remote sensing systems has remained focused around human vision. In particular, remote sensing systems are usually constructed to optimize sensing cost-quality trade-offs with respect to human image interpretability. While some recent studies have explored remote sensing system design as a function of simple computer vision algorithm performance, there has been little work relating this design to the state-of-the-art in computer vision: deep learning with convolutional neural networks. We develop experimental systems to conduct this analysis, showing results with modern deep learning algorithms and recent overhead image data. Our results are compared to standard image quality measurements based on human visual perception, and we conclude not only that machine and human interpretability differ significantly, but that computer vision performance is largely self-consistent across a range of disparate conditions.\nThis repository contains all the code required to replicate the results of our research paper, and the corresponding docker environment in which that code can be executed. All code is written in Python3 and utilizes the PyTorch library (v1.0) for neural network model training and evaluation. Jupyter notebooks are used to visualize images transformed with our code, in addition to plotting experimental results. We also include the specific parameter files used to execute our experiments, with the intent that these experiments can be replicated.", + "laborHours": 2340.8, + "languages": [], + "name": "Remote Sensor Design for Visual Recognition with Convolutional Neural Networks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sepsense", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Renewable_Resource_and_Power_Data_tool__R2PD_.json b/agency-indexes/DoE/Renewable_Resource_and_Power_Data_tool__R2PD_.json new file mode 100644 index 00000000..ef19531d --- /dev/null +++ b/agency-indexes/DoE/Renewable_Resource_and_Power_Data_tool__R2PD_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-10", + "metadataLastUpdated": "2019-07-10" + }, + "description": "Power system modeler-friendly tool for downloading wind and solar power and forecast data.", + "laborHours": 790.4, + "languages": [ + "Python" + ], + "name": "Renewable Resource and Power Data tool (R2PD)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Smart-DS/R2PD", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Repast_for_High-Performance_Computing__Repast_HPC.json b/agency-indexes/DoE/Repast_for_High-Performance_Computing__Repast_HPC.json new file mode 100644 index 00000000..8362007c --- /dev/null +++ b/agency-indexes/DoE/Repast_for_High-Performance_Computing__Repast_HPC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "MPI-distributed expert-focused C++-based modeling system that is designed for use on large computing clusters and supercomputers.", + "laborHours": 0.0, + "languages": [], + "name": "Repast for High-Performance Computing )Repast HPC", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Repast/repast.hpc", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Replay-Stream.json b/agency-indexes/DoE/Replay-Stream.json new file mode 100644 index 00000000..eeb84222 --- /dev/null +++ b/agency-indexes/DoE/Replay-Stream.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "For testing and demonstration purposes, it is often necessary to replay saved network and log data. This library facilitates replaying these saved data streams. This module will take in a stream of JSON strings, read their specified timestamp field, and output according to the given criteria. This can include restricting output to a certain time range, and/or outputting the items with some delay based on their timestamp.", + "laborHours": 40736.0, + "name": "Replay-Stream", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/replay-stream", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Replete_v._1.0.json b/agency-indexes/DoE/Replete_v._1.0.json new file mode 100644 index 00000000..7194e7ef --- /dev/null +++ b/agency-indexes/DoE/Replete_v._1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-29" + }, + "description": "Replete is a generic Java utility library comprised of basic user interface, file, string, pipeline, expression parsing, and multi-threading utilities.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Replete v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Replete_v._2.0.json b/agency-indexes/DoE/Replete_v._2.0.json new file mode 100644 index 00000000..d9de4612 --- /dev/null +++ b/agency-indexes/DoE/Replete_v._2.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-09-30", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SAND2021-15136 O\nReplete is a Java library that contains several common and useful utilities in a variety of categories including expression parsing, multi-threading, data pipelines, user interface, database connectivity, Unix shell emulation, information generalization, and Maven standardization. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 138168.0, + "languages": [ + "Java" + ], + "name": "Replete v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/replete", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Replication_Package_for_\"Union-Find_and_Usability:_A_Case_Study_and_Analysis_of_Rust_Formal_Verifier.json" "b/agency-indexes/DoE/Replication_Package_for_\"Union-Find_and_Usability:_A_Case_Study_and_Analysis_of_Rust_Formal_Verifier.json" new file mode 100644 index 00000000..0242b780 --- /dev/null +++ "b/agency-indexes/DoE/Replication_Package_for_\"Union-Find_and_Usability:_A_Case_Study_and_Analysis_of_Rust_Formal_Verifier.json" @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-10-03", + "metadataLastUpdated": "2024-10-03" + }, + "description": "This replication package is a case study on automated deductive verification for Rust for practical\nprograms. It is a companion artifact to a corresponding usability study on verification titled \"Union-Find\nand Usability: A Case Study and Analysis of Rust Formal Verifiers\". It seeks to answer the question \"Can\nRust developers today use Rust verifiers to verify their code?\". To answer this question, the study\ncontrasts the verification experience of two mature Rust verifiers, Creusot and Prusti, by using the tools to\ndevelop a verified implementation of union-find in Rust. The union-find implementation is based on real-world code as used in the popular egg E-graph library. The artifact consists of two different verified\nlibraries, one using Creusot and one using Prusti. The libraries have similar Rust interfaces and high-level\nproofs but differ in their details: Creusot and Prusti have different annotation languages and support\ndifferent proof styles. Each implementation can be verified with its respective tool and compiles as a\ntraditional Rust development.", + "homepageURL": "https://zenodo.org/records/13887654", + "laborHours": 456.0, + "languages": [], + "name": "Replication Package for \"Union-Find and Usability: A Case Study and Analysis of Rust Formal Verifier", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://zenodo.org/records/13887654", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Replicative_Assessment_of_Spectroscopic_Equipment.json b/agency-indexes/DoE/Replicative_Assessment_of_Spectroscopic_Equipment.json new file mode 100644 index 00000000..fe963dc0 --- /dev/null +++ b/agency-indexes/DoE/Replicative_Assessment_of_Spectroscopic_Equipment.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-14", + "metadataLastUpdated": "2021-12-14" + }, + "description": "The Replicative Assessment of Spectrometric Equipment (RASE) is a software for evaluating the performance of radiation detectors and isotope identification algorithms. It uses a semi-empirical approach to rapidly generate synthetic spectra and inject into detector's software to obtain nuclide identification response. RASE facilitates studies of spectroscopic device performance and a quantitative assessment of its capabilities to correctly distinguish and identify isotopes of interest in realistic scenarios.", + "laborHours": 4088.8, + "languages": [], + "name": "Replicative Assessment of Spectroscopic Equipment", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RASE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Replicative_Assessment_of_Spectroscopic_Equipment_v3.0.json b/agency-indexes/DoE/Replicative_Assessment_of_Spectroscopic_Equipment_v3.0.json new file mode 100644 index 00000000..74beb843 --- /dev/null +++ b/agency-indexes/DoE/Replicative_Assessment_of_Spectroscopic_Equipment_v3.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "moorea@osti.gov" + }, + "date": { + "created": "2025-01-10", + "metadataLastUpdated": "2025-01-10" + }, + "description": "The Replicative Assessment of Spectrometric Equipment (RASE) is a software for evaluating the\nperformance of radiation detectors and isotope identification algorithms. It uses a semi-empirical\napproach to rapidly generate synthetic spectra and inject into detector's software to obtain nuclide\nidentification response. RASE facilitates studies of spectroscopic device performance and a quantitative\nassessment of its capabilities to correctly distinguish and identify isotopes of interest in realistic scenarios", + "laborHours": 4088.8, + "languages": [], + "name": "Replicative Assessment of Spectroscopic Equipment v3.0", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RASE", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Repometer_v.1.0.json b/agency-indexes/DoE/Repometer_v.1.0.json new file mode 100644 index 00000000..5dd2be54 --- /dev/null +++ b/agency-indexes/DoE/Repometer_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-27", + "metadataLastUpdated": "2024-07-27" + }, + "description": "SAND2022-4256 O\nOnline version control platforms offer insight into traffic and engagement with source code repositories, but only in limited ways and over short windows of time. Scientific software teams at Sandia National Laboratories and elsewhere want to collect and store engagement data to help tell their story and the impact their work has on the community. Repometer aims to supplement existing capabilities by collecting timely and insightful data from GitHub and GitLab repositories and passing it to a database for longer-term storage.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1793.6, + "languages": [ + "Python" + ], + "name": "Repometer v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Repometer", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Reposcanner_.json b/agency-indexes/DoE/Reposcanner_.json new file mode 100644 index 00000000..9398f546 --- /dev/null +++ b/agency-indexes/DoE/Reposcanner_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2023-08-10" + }, + "description": "SAND2023-05455O\nReposcanner provides a highly modular, extensible framework for defining routines for mining data from software repositories and performing analyses on that data to yield valuable insights on team behaviors. Reposcanner features seamless support for different version control platforms like GitHub, Gitlab, and Bitbucket; smart parsing of URLs; intelligent credential management capabilities; and a comprehensive test suite. Reposcanner is connected to the Exascale Computing Project and is intended for research purposes.", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "Reposcanner ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bssw-psip/bssw-psip.github.io", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/ResStock\342\204\242_[SWR-19-15_and_SWR-20-07].json" "b/agency-indexes/DoE/ResStock\342\204\242_[SWR-19-15_and_SWR-20-07].json" new file mode 100644 index 00000000..62cb4395 --- /dev/null +++ "b/agency-indexes/DoE/ResStock\342\204\242_[SWR-19-15_and_SWR-20-07].json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-11", + "metadataLastUpdated": "2024-04-26" + }, + "description": "The ResStock\u2122 analysis tool is helping states, municipalities, utilities, and manufacturers identify which home improvements save the most energy and money.With support from the U.S. Department of Energy (DOE), researchers at NREL developed ResStock. It's a versatile tool that takes a new approach to large-scale residential energy analysis by combining:\n\n- Large public and private data sources\n- Statistical sampling\n- Detailed subhourly building simulations\n- High-performance computing.\n- This combination achieves unprecedented granularity and most importantly\u2014accuracy\u2014in modeling the diversity of the single-family housing stock.", + "laborHours": 4008133.6, + "languages": [], + "name": "ResStock\u2122 [SWR-19-15 and SWR-20-07]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/OpenStudio-BuildStock/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/OpenStudio-BuildStock", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/ResStock\342\204\242_v3.2.0_[SWR-19-15_and_SWR-20-07].json" "b/agency-indexes/DoE/ResStock\342\204\242_v3.2.0_[SWR-19-15_and_SWR-20-07].json" new file mode 100644 index 00000000..12d4485b --- /dev/null +++ "b/agency-indexes/DoE/ResStock\342\204\242_v3.2.0_[SWR-19-15_and_SWR-20-07].json" @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-04-26", + "metadataLastUpdated": "2024-04-26" + }, + "description": "The ResStock\u2122 analysis tool was built on NREL's OpenStudio\u00ae platform, and is a project geared at modeling existing residential building stocks at national, regional, or local scales with a high-degree of granularity (e.g., one physics-based simulation model for every 200 dwelling units), using the EnergyPlus\u00ae simulation engine. Information about ComStock\u2122, a sister tool for modeling the commercial building stock, can be found here: https://www.nrel.gov/buildings/comstock.html\nThis repository contains:\nHousing characteristics of the U.S. residential building stock, in the form of conditional probability distributions stored as tab-separated value (.tsv) files. Comments at the bottom of each file document data sources and assumptions for each.\nA library of housing characteristic \"options\" that translate high-level characteristic parameters into arguments for OpenStudio measures, and which are referenced by the housing characteristic .tsv files and building energy upgrades defined in project definition files\nProject definition files:\nv2.3.0 and later: buildstockbatch YML files openable in any text editor\nv2.2.5 and prior: Project folder openable in PAT\nUnit-level OpenStudio Measures for automatically constructing OpenStudio Models of each representative dwelling unit model:\nv3.0.0 and later: OpenStudio-HPXML Measures\nv2.5.0 and prior: OpenStudio Measures\nHigher-level OpenStudio Measures for controlling simulation inputs and outputs\nThis repository does not contain software for running ResStock simulations, which can be found as follows:\n\nVersions 2.3.0 and later only support the use of buildstockbatch for deploying simulations on high-performance or cloud computing. Version 2.3.0 also removed separate projects for single-family detached and multifamily buildings, in lieu of a combined project_national representing the U.S. residential building stock. See the changelog for more details.\nVersions 2.2.5 and prior support the use of the publicly available OpenStudio-PAT software as an interface for deploying simulations on cloud computing. Read the documentation for v2.2.5.", + "laborHours": 2638370.4, + "languages": [ + "Python", + "Ruby" + ], + "name": "ResStock\u2122 v3.2.0 [SWR-19-15 and SWR-20-07]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/resstock/blob/develop/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/resstock", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Research_Network_Transfer_Performance_Predictor__netperf-predict__v_0.9.json b/agency-indexes/DoE/Research_Network_Transfer_Performance_Predictor__netperf-predict__v_0.9.json new file mode 100644 index 00000000..3b0973e2 --- /dev/null +++ b/agency-indexes/DoE/Research_Network_Transfer_Performance_Predictor__netperf-predict__v_0.9.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-09", + "metadataLastUpdated": "2019-06-26" + }, + "description": "Research Network Transfer Performance Predictor (netperf-predict) v 0.9", + "laborHours": 152.0, + "languages": [], + "name": "Research Network Transfer Performance Predictor (netperf-predict) v 0.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/tstat-dtn-analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "0.9" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Residential_Simulation_Tool.json b/agency-indexes/DoE/Residential_Simulation_Tool.json new file mode 100644 index 00000000..127ffdf2 --- /dev/null +++ b/agency-indexes/DoE/Residential_Simulation_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Residential Simulation Tool was developed to understand the impact of residential load consumption on utilities including the role of demand response. This is complicated as many different residential loads exist and are utilized for different purposes. The tool models human behavior and contributes this to load utilization, which contributes to the electrical consumption prediction by the tool. The tool integrates a number of different databases from Department of Energy and other Government websites to support the load consumption prediction.", + "laborHours": 8694.4, + "languages": [ + "Matlab" + ], + "name": "Residential Simulation Tool", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/starkemr/Residential-Simulation-Tool/blob/master/LICENSE.md/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/starkemr/Residential-Simulation-Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Resilience_Development_For_Electric_Energy_Delivery_Systems.json b/agency-indexes/DoE/Resilience_Development_For_Electric_Energy_Delivery_Systems.json new file mode 100644 index 00000000..402e2b9b --- /dev/null +++ b/agency-indexes/DoE/Resilience_Development_For_Electric_Energy_Delivery_Systems.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-07-20", + "metadataLastUpdated": "2023-07-20" + }, + "description": "The Resilience Development for Electric Energy Delivery Systems (ResDEEDS) tool walks users through the process of evaluating electric energy delivery systems (EEDS) for resiliency. It implements the steps of the INL Resilience Framework for EEDS and provides automated tracking of resilience planning and suggestions for mitigating hazards.", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Resilience Development For Electric Energy Delivery Systems", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/ResDEEDS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Resilience_Of_Microgrids_With_Adaptive_Capacity_And_Inertia.json b/agency-indexes/DoE/Resilience_Of_Microgrids_With_Adaptive_Capacity_And_Inertia.json new file mode 100644 index 00000000..a06a8744 --- /dev/null +++ b/agency-indexes/DoE/Resilience_Of_Microgrids_With_Adaptive_Capacity_And_Inertia.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-02-09", + "metadataLastUpdated": "2023-03-13" + }, + "description": "Resilience of Microgrids with Adaptive capacity and Inertia calculates the maximum size of a disturbance a microgrid could withstand before frequency limits are violated. The results are based on power generation assets in the microgrid and its inertia.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Resilience Of Microgrids With Adaptive Capacity And Inertia", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/ReMAIn", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Resonance_Control_GUI_for_LCLS-II_ResCtl_System.json b/agency-indexes/DoE/Resonance_Control_GUI_for_LCLS-II_ResCtl_System.json new file mode 100644 index 00000000..55561086 --- /dev/null +++ b/agency-indexes/DoE/Resonance_Control_GUI_for_LCLS-II_ResCtl_System.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-02-08", + "metadataLastUpdated": "2019-03-22" + }, + "description": "Resonance Control GUI for LCLS-II ResCtl System is a Qt5-based, python GUI used for interacting with an LCLS-II resonance control system for an 8-cavity cryomodule. The code is written in Python, and can use auxiliary software Qt5, pyqtgraph, numpy, and scipy. The code is operating system-agnostic, has no specific hardware requirements, and has no embedded source code.", + "homepageURL": "http://pip2.fnal.gov", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Resonance Control GUI for LCLS-II ResCtl System", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://pip2.fnal.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Resonance_Inspection_Techniques_&_Analysis__RITA_.json b/agency-indexes/DoE/Resonance_Inspection_Techniques_&_Analysis__RITA_.json new file mode 100644 index 00000000..e1f95cf1 --- /dev/null +++ b/agency-indexes/DoE/Resonance_Inspection_Techniques_&_Analysis__RITA_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-03-06", + "metadataLastUpdated": "2018-03-15" + }, + "description": "Resonance Inspection encompasses a suite of techniques for the purpose of materials characterization and nondestructive evaluation. These techniques utilize the mechanical resonances of the sample(s) to determine and monitor material properties (e.g., elastic moduli, phase changes), sort mechanically defective parts, determine the presence/level of mechanical damage (micro-cracking, delaminations, disbonding, etc.) and monitor mass/density fluctuations to name a few applications. The Resonance Inspection Techniques & Analyses (RITA) system has been developed to facilitate these and other applications in a user friendly and cost effective package.", + "homepageURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "name": "Resonance Inspection Techniques & Analysis (RITA)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "http://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Resonant_Ultrasound_Spectroscopy_Software.json b/agency-indexes/DoE/Resonant_Ultrasound_Spectroscopy_Software.json new file mode 100644 index 00000000..5321347c --- /dev/null +++ b/agency-indexes/DoE/Resonant_Ultrasound_Spectroscopy_Software.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-01-29", + "metadataLastUpdated": "2018-01-29" + }, + "description": "Software programs Red Pitaya to sweep frequency and records the in phase and quadrature response.", + "laborHours": 1489.6, + "name": "Resonant Ultrasound Spectroscopy Software", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ffb-LANL/resonant-ultrasound", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Resource_Extraction_Tool__rex_.json b/agency-indexes/DoE/Resource_Extraction_Tool__rex_.json new file mode 100644 index 00000000..40fa8f13 --- /dev/null +++ b/agency-indexes/DoE/Resource_Extraction_Tool__rex_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-04-17", + "metadataLastUpdated": "2020-04-20" + }, + "description": "The Resource Extraction Tool (rex) includes tools developed for reV and reVX related to the efficient access of, extraction from, and computation on NREL's renewable resource datasets (NSRDB and WTK).", + "laborHours": 8040.8, + "languages": [ + "Python" + ], + "name": "Resource Extraction Tool (rex)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/rex", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Resource_Forecast_and_Ramp_Visualization_for_Situational_Awareness__RAVIS_.json b/agency-indexes/DoE/Resource_Forecast_and_Ramp_Visualization_for_Situational_Awareness__RAVIS_.json new file mode 100644 index 00000000..a2f08e45 --- /dev/null +++ b/agency-indexes/DoE/Resource_Forecast_and_Ramp_Visualization_for_Situational_Awareness__RAVIS_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-04-18", + "metadataLastUpdated": "2021-04-18" + }, + "description": "The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an open-source tool for visualizing variable renewable resource forecasts and ramp alerts for significant up/down ramps in renewable resource and the consequent net-load. The modular dashboard of RAVIS contains configurable panes for viewing- probabilistic time series forecasts, ramp event alerts on the look-ahead timeline, spatially resolved resource sites and forecasts, and system simulation and market clearing data such as transmission lines utilization, nodal prices and available generation flexibility.", + "laborHours": 0.0, + "languages": [ + "JavaScript" + ], + "name": "Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ravis-nrel/ravis", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Resource_Tracking_and_Workflow_System_-_part_of_the_CORE_system.json b/agency-indexes/DoE/Resource_Tracking_and_Workflow_System_-_part_of_the_CORE_system.json new file mode 100644 index 00000000..2f2ce0f2 --- /dev/null +++ b/agency-indexes/DoE/Resource_Tracking_and_Workflow_System_-_part_of_the_CORE_system.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Resource management and workflow capability applied to engineering design situational awareness, providing the ability to make assignments and track progress through the construction and maintenance life cycle of an engineered structure.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Resource Tracking and Workflow System - part of the CORE system", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Response_Surface_Modeling_Tool_Suite,_Version_1.x.json b/agency-indexes/DoE/Response_Surface_Modeling_Tool_Suite,_Version_1.x.json new file mode 100644 index 00000000..be7d3ad4 --- /dev/null +++ b/agency-indexes/DoE/Response_Surface_Modeling_Tool_Suite,_Version_1.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Response Surface Modeling (RSM) Tool Suite is a collection of three codes used to generate an empirical interpolation function for a collection of drag coefficient calculations computed with Test Particle Monte Carlo (TPMC) simulations. The first code, \"Automated RSM\", automates the generation of a drag coefficient RSM for a particular object to a single command. \"Automated RSM\" first creates a Latin Hypercube Sample (LHS) of 1,000 ensemble members to explore the global parameter space. For each ensemble member, a TPMC simulation is performed and the object drag coefficient is computed. In the next step of the \"Automated RSM\" code, a Gaussian process is used to fit the TPMC simulations. In the final step, Markov Chain Monte Carlo (MCMC) is used to evaluate the non-analytic probability distribution function from the Gaussian process. The second code, \"RSM Area\", creates a look-up table for the projected area of the object based on input limits on the minimum and maximum allowed pitch and yaw angles and pitch and yaw angle intervals. The projected area from the look-up table is used to compute the ballistic coefficient of the object based on its pitch and yaw angle. An accurate ballistic coefficient is crucial in accurately computing the drag on an object. The third code, \"RSM Cd\", uses the RSM generated by the \"Automated RSM\" code and the projected area look-up table generated by the \"RSM Area\" code to accurately compute the drag coefficient and ballistic coefficient of the object. The user can modify the object velocity, object surface temperature, the translational temperature of the gas, the species concentrations of the gas, and the pitch and yaw angles of the object. Together, these codes allow for the accurate derivation of an object's drag coefficient and ballistic coefficient under any conditions with only knowledge of the object's geometry and mass.", + "laborHours": 3708.8, + "name": "Response Surface Modeling Tool Suite, Version 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AndrewCWalker/rsm_tool_suite", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RetSynth_v._1.0.json b/agency-indexes/DoE/RetSynth_v._1.0.json new file mode 100644 index 00000000..5314e3cf --- /dev/null +++ b/agency-indexes/DoE/RetSynth_v._1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "This software uses a database of existing biological pathways to determine efficient routes for genetic engineering.", + "laborHours": 1413296.0, + "languages": [ + "Python" + ], + "name": "RetSynth v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/RetSynth", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ReteBiome.json b/agency-indexes/DoE/ReteBiome.json new file mode 100644 index 00000000..4f854fd1 --- /dev/null +++ b/agency-indexes/DoE/ReteBiome.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software provides a web interface means to upload, generate, analyze, manage and store DNA fragment length polymorphism data. This tool can easily be configured to accommodate other bio data.", + "laborHours": 380.0, + "name": "ReteBiome", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/ReteBiome/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ReteBiome", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Retro-Commissioning_Sensor_Suitcase.json b/agency-indexes/DoE/Retro-Commissioning_Sensor_Suitcase.json new file mode 100644 index 00000000..c2c0a44f --- /dev/null +++ b/agency-indexes/DoE/Retro-Commissioning_Sensor_Suitcase.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2019-04-22" + }, + "description": "This software package is the Graphic User Interface (GUI) software component for the Sensor Suitcase Retro-Commissioning project, which is a sensor and analysis system to support monitoring-based retro-commissioning of small commercial buildings, performed by non-experts. \n\nSmall commercial buildings typically do not have the budgets or business economics to allow investing in energy efficiency enhancements the building retro-commissioning provides. In addition, they do not have in-house staff with expertise in building systems who can perform building retro-commissioning or identify energy efficiency improvement opportunities. \n\nThe solution to this problem is to develop a turn-key hardware/software solution (the RCx Sensor Suitcase) that can be used by non-experts to automatically generate low and no-cost energy efficiency rec commendations that will improve building operating costs, occupant comfort and building energy performance. \n\nThis is a joint project between Lawrence Berkeley National Laboratory, leading the development of the software and analysis elements, and Pacific Northwest National Laboratory (PNNL), leading the development of the hardware and sensor elements with an associated table-based configuration support tool. The project is funded by the U.S. Department of Energy. \n\nThis software package was developed as a proof-of-concept prototype for the sensor suitcase software component. The software component was developed with a Microsoft Excel spreadsheet which reads the sensor data and calls a MATLAB DLL to analyze the sensor data.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Retro-Commissioning Sensor Suitcase", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Retro-Future.json b/agency-indexes/DoE/Retro-Future.json new file mode 100644 index 00000000..c065eeaa --- /dev/null +++ b/agency-indexes/DoE/Retro-Future.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A system for processing network packet capture streams, extracting metadata and generating flow records (via Argus). The system can be used by network security operators and analysts to enable forensic investigations for network security events.", + "laborHours": 1094.4, + "name": "Retro-Future", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cardi/timefind", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Retrospective_Mobility_Analysis.json b/agency-indexes/DoE/Retrospective_Mobility_Analysis.json new file mode 100644 index 00000000..88cd3597 --- /dev/null +++ b/agency-indexes/DoE/Retrospective_Mobility_Analysis.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "An application that provides users with ex post information on foregone travel conclusions to induce travel behavioral change.", + "homepageURL": "https://www.nrel.gov/workingwithus/licensing.html", + "laborHours": 0.0, + "languages": [ + "Python 2.7, Javascript, Ruby" + ], + "name": "Retrospective Mobility Analysis", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/workingwithus/licensing.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/workingwithus/licensing.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Reversible_Gene_Drive_Mechanism_Utilizing_Trana_Inactivating_Paramutatlons_In_Insects__paramutale_0.9_.json b/agency-indexes/DoE/Reversible_Gene_Drive_Mechanism_Utilizing_Trana_Inactivating_Paramutatlons_In_Insects__paramutale_0.9_.json new file mode 100644 index 00000000..243d01f4 --- /dev/null +++ b/agency-indexes/DoE/Reversible_Gene_Drive_Mechanism_Utilizing_Trana_Inactivating_Paramutatlons_In_Insects__paramutale_0.9_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The paramutate software package Is a tool to calculate the genotyplc and phenotyplc propagation of a gene drive that can be silenced with a homologuus trans-Inactivating panmutatlon, ln dlptera or other species with a slmUar-acttng pl RNA system/Plwi pathway. Method of SolaUon: paramutate uses rults of Mendelian, gene drive (I.e.. stimulated conversion), and maternal Inheritance to compute the propaptlon of a notional gene drive construct and Its trans-lnactlvat1n1 paramutatlon, throu1b a panmlctlc, fixed-size population reproducing In synchronous generations.", + "laborHours": 12813.6, + "name": "Reversible Gene Drive Mechanism Utilizing Trana Inactivating Paramutatlons In Insects (paramutale 0.9)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/RAJAPerf/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/RAJAPerf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Review_materials_for_Computationally_Restoring_the_Potency_of_a_Clinical_Antibody.json b/agency-indexes/DoE/Review_materials_for_Computationally_Restoring_the_Potency_of_a_Clinical_Antibody.json new file mode 100644 index 00000000..ffc90491 --- /dev/null +++ b/agency-indexes/DoE/Review_materials_for_Computationally_Restoring_the_Potency_of_a_Clinical_Antibody.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-11", + "metadataLastUpdated": "2024-04-11" + }, + "description": "Train and use machine learning models; select protein sequences for simulation and laboratory testing.\nCode implements key decision steps in this process. Provided for review purposes and public release.", + "laborHours": 2736.0, + "languages": [], + "name": "Review materials for Computationally Restoring the Potency of a Clinical Antibody", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/CRPCA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "v2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RhizoNet:_semantic_segmentation_of_plant_roots_using_CNN__RhizoNet__v0.0.1.json b/agency-indexes/DoE/RhizoNet:_semantic_segmentation_of_plant_roots_using_CNN__RhizoNet__v0.0.1.json new file mode 100644 index 00000000..6fd22063 --- /dev/null +++ b/agency-indexes/DoE/RhizoNet:_semantic_segmentation_of_plant_roots_using_CNN__RhizoNet__v0.0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-12", + "metadataLastUpdated": "2024-06-12" + }, + "description": "RhizoNet is designed for the semantic segmentation of plant root scans, utilizing a sophisticated deep learning network known as Residual Unet. It specializes in processing color images of plants cultivated in a hydroponic EcoFAB system, captured using an Epson scanner. The core of the algorithm is based on Residual U-nets, which significantly improve prediction accuracy. This is achieved through the implementation of a convex hull operation, which effectively delineates the primary root component by leveraging spatio-temporal image data. This enables researchers to accurately assess predicted biomass and monitor plant growth over time.", + "laborHours": 608.0, + "languages": [], + "name": "RhizoNet: semantic segmentation of plant roots using CNN (RhizoNet) v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/rhizonet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Rhizogrids_and_3D_molecular_root_imaging_workflow.json b/agency-indexes/DoE/Rhizogrids_and_3D_molecular_root_imaging_workflow.json new file mode 100644 index 00000000..0c76e1e4 --- /dev/null +++ b/agency-indexes/DoE/Rhizogrids_and_3D_molecular_root_imaging_workflow.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Rhizogrid guided molecular root imaging workflow enables investigating root rhizosphere interactions in a near native\nenvironment. Non-invasive root images are captured, and three-dimensional root images are reconstructed using x-ray\ncomputed tomography technique. Root and rhizosphere samples are then harvested and processed for root-rhizosphere\nmetabolite and microbial profiling.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Rhizogrids and 3D molecular root imaging workflow", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ring_Pull_Strain_Analysis.json b/agency-indexes/DoE/Ring_Pull_Strain_Analysis.json new file mode 100644 index 00000000..39166fc1 --- /dev/null +++ b/agency-indexes/DoE/Ring_Pull_Strain_Analysis.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-05-03" + }, + "description": "Ring Pull Strain Analysis (RPSA) is a framework for analysis of Digital Image Correlation (DIC) data of gaugeless ring pull testing. It is meant for analysis of rings cut from tube cross sections and pulled in a displacement-controlled tensile test. This code takes load frame data, images take during testing, and csv files from the DIC analysis of those images and allows the user to analyze and plot data from the test. Some important features of the software include getting the strain values as a function of radial distance and angle, plotting of the strain around the ring, and stress-strain analysis of the load frame\ndata. Additional capability is included with Ring Pull Coating Analysis (RPCA, also part of the software). Additional images are taken of samples with an outer coating and are used to correlate failure of the coating with strain values measured with DIC.", + "laborHours": 0.0, + "languages": [], + "name": "Ring Pull Strain Analysis", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/RingPullStrainAnalysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ring_current_Atmosphere_interactions_Model_with_Self-Consistent_Magnetic_field.json b/agency-indexes/DoE/Ring_current_Atmosphere_interactions_Model_with_Self-Consistent_Magnetic_field.json new file mode 100644 index 00000000..26df5961 --- /dev/null +++ b/agency-indexes/DoE/Ring_current_Atmosphere_interactions_Model_with_Self-Consistent_Magnetic_field.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Ring current Atmosphere interactions Model with Self-Consistent magnetic field (B) is a unique code that combines a kinetic model of ring current plasma with a three dimensional force-balanced model of the terrestrial magnetic field. The kinetic portion, RAM, solves the kinetic equation to yield the bounce-averaged distribution function as a function of azimuth, radial distance, energy and pitch angle for three ion species (H+, He+, and O+) and, optionally, electrons. The domain is a circle in the Solar-Magnetic (SM) equatorial plane with a radial span of 2 to 6.5 RE. It has an energy range of approximately 100 eV to 500 KeV. The 3-D force balanced magnetic field model, SCB, balances the JxB force with the divergence of the general pressure tensor to calculate the magnetic field configuration within its domain. The domain ranges from near the Earth\u2019s surface, where the field is assumed dipolar, to the shell created by field lines passing through the SM equatorial plane at a radial distance of 6.5 RE. The two codes work in tandem, with RAM providing anisotropic pressure to SCB and SCB returning the self-consistent magnetic field through which RAM plasma is advected.", + "laborHours": 81259.2, + "name": "Ring current Atmosphere interactions Model with Self-Consistent Magnetic field", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/RAM-SCB/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/RAM-SCB", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RiskCat_v1.0.json b/agency-indexes/DoE/RiskCat_v1.0.json new file mode 100644 index 00000000..bcc1cbb4 --- /dev/null +++ b/agency-indexes/DoE/RiskCat_v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-06-10", + "metadataLastUpdated": "2020-06-10" + }, + "description": "RiskCat is designed to calculate probabilistic seismic hazard and risk at specified locations on the Earth's surface. 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The software utilizes Bayesian methods to combine subject matter expert judgement and small performance test datasets in a consistent and defensible way. It allows a more holistic view of delay performance that provides distributions of task times and task success probabilities to account for tasks that, if failed, would result in failure of the attack. The RIT methodology is meant to enable security risk managers to begin the transition into more comprehensive delay timeline analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8294 O", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C#", + "C++", + "C#" + ], + "name": "Risk Informed Timelines (RIT) v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/River_and_Basin_Profiler.json b/agency-indexes/DoE/River_and_Basin_Profiler.json new file mode 100644 index 00000000..7ea10472 --- /dev/null +++ b/agency-indexes/DoE/River_and_Basin_Profiler.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-27", + "metadataLastUpdated": "2021-08-27" + }, + "description": "The River and Basin Profiler (RaBPro) represents a set of python tools that help characterize and analyze rivers and watersheds from a digital elevation model (DEM). RaBPro contains three primary functions: First, RaBPro will delineate watersheds for any given points within a DEM. Second, RaBPro will extract the elevation and slope profiles for flowlines (rivers) within the DEM. Finally, RaBPro provides convenient zonal statistics functionality for characterizing watersheds using auxiliary data the the user provides.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "River and Basin Profiler", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Rneshaps.json b/agency-indexes/DoE/Rneshaps.json new file mode 100644 index 00000000..1df5b914 --- /dev/null +++ b/agency-indexes/DoE/Rneshaps.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "This software is used to combine output files US EPA CAp88-PC software (http://www.epa.gov/radiation/assessment/CAP88/aboutcap88.html) and estimate input parameters for CAP88-PC. Also includes features for tabular and graphical review of results.", + "homepageURL": "http://rneshaps.r-forge.r-project.org", + "laborHours": 0.0, + "languages": [], + "name": "Rneshaps", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://rneshaps.r-forge.r-project.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Rnnotator_3.0.json b/agency-indexes/DoE/Rnnotator_3.0.json new file mode 100644 index 00000000..a7a55be0 --- /dev/null +++ b/agency-indexes/DoE/Rnnotator_3.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "Rnnotator is an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads.", + "homepageURL": "https://sites.google.com/a/lbl.gov/rnnotator/home", + "laborHours": 0.0, + "languages": [], + "name": "Rnnotator 3.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sites.google.com/a/lbl.gov/rnnotator/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sites.google.com/a/lbl.gov/rnnotator/home", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Roary.json b/agency-indexes/DoE/Roary.json new file mode 100644 index 00000000..ee5d48c2 --- /dev/null +++ b/agency-indexes/DoE/Roary.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "Roary is a high speed Pan Genome pipeline. Roary is not intended for meta-genomics or for comparing extremely diverse sets of genomes. In order to achieve this speed up of the NP-hard task of Pan Genome assembly, Roary is non-deterministic.", + "laborHours": 1444.0, + "languages": [], + "name": "Roary", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/Roary", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Robust_Event_Simulation_Variants_Endowed_to_Ns-3_for_General_Exploration.json b/agency-indexes/DoE/Robust_Event_Simulation_Variants_Endowed_to_Ns-3_for_General_Exploration.json new file mode 100644 index 00000000..27e3003e --- /dev/null +++ b/agency-indexes/DoE/Robust_Event_Simulation_Variants_Endowed_to_Ns-3_for_General_Exploration.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-09-18" + }, + "description": "Sandia's ns-3 contributions are modifications to the open source ns-3 network simulator that enable simulation speedup. 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Methods and capabilities include construction, evaluation, and application of models for infrasound signal analysis, construction of synthetic data useful for construction and evaluation, as well as various other advanced data science tools enabling infrasound signal detection and categorization as well as downstream analysis methods such as localization and characterization of detected sources.", + "laborHours": 760.0, + "languages": [], + "name": "Robust Infrasound Detection via Deep Learning (RIDDL)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Seismoacoustics/riddl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Robust_Machine_Learning.json b/agency-indexes/DoE/Robust_Machine_Learning.json new file mode 100644 index 00000000..5c862cdf --- /dev/null +++ b/agency-indexes/DoE/Robust_Machine_Learning.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-09-22", + "metadataLastUpdated": "2023-10-17" + }, + "description": "UQ4ML is a code repository for a set of tools for the development of robust machine learning methods, uncertainty quantification and explainability of machine learning methods. The goal of these tools is to develop more robust and statistically rigorous machine learning methods for scientific applications. These tools are developed in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Robust Machine Learning", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Robust_Temperature_Control_for_Friction_Stir_Welding.json b/agency-indexes/DoE/Robust_Temperature_Control_for_Friction_Stir_Welding.json new file mode 100644 index 00000000..59597610 --- /dev/null +++ b/agency-indexes/DoE/Robust_Temperature_Control_for_Friction_Stir_Welding.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is collection of methods to control weld power and temperature with unprecedented accuracy, precision and process robustness. These control techniques are implemented on the spindle axis only and run independently from weld path and forge axis motion.", + "homepageURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "laborHours": 0.0, + "languages": [], + "name": "Robust Temperature Control for Friction Stir Welding", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov/default.aspx", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov/default.aspx", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Role-Based_Access_Control_for_Distributed_Energy_Resources_v.1.0.json b/agency-indexes/DoE/Role-Based_Access_Control_for_Distributed_Energy_Resources_v.1.0.json new file mode 100644 index 00000000..d8c4d187 --- /dev/null +++ b/agency-indexes/DoE/Role-Based_Access_Control_for_Distributed_Energy_Resources_v.1.0.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2024-09-19" + }, + "description": "The Role-Based Access Control (RBAC) for Distributed Energy Resources (DER) software is an automated and transparent stack for RBAC administrators to interact with RBAC policy. The package includes demonstrations of centralized and decentralized RBAC implementation. Both include simulated DER entities that are stored automatically in a centralized Lightweight Directory Access Protocol (LDAP) server. It also includes a REST-API to serve the HTTP requests of the RBAC administrators. A complete front-end is included to serve the users' needs. This software may be used by industry (DER vendors/utilities) as well as the research community to determine if a centralized or decentralized solution fits better the needs of an RBAC model in a DER environment. Additionally, parts of this software may be useful for developing implementations for specific needs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8292 O", + "laborHours": 87582.4, + "languages": [ + "JavaScript", + "Vue", + "CSS", + "Python", + "Makerfile", + "SCSS" + ], + "name": "Role-Based Access Control for Distributed Energy Resources v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/RBAC_Centralized", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Rootless_Operations_for_MPI__RLO__v0.1.json b/agency-indexes/DoE/Rootless_Operations_for_MPI__RLO__v0.1.json new file mode 100644 index 00000000..416da306 --- /dev/null +++ b/agency-indexes/DoE/Rootless_Operations_for_MPI__RLO__v0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-09-19", + "metadataLastUpdated": "2019-10-02" + }, + "description": "Flexible communication routines that enable high-performance computing (HPC) applications to operate with less synchronization are a great benefit to application algorithm creation and developer productivity. Further, communication operations that reduce synchronization in HPC applications while continuing to scale well are critical to application performance in the exascale era. We have implemented mechanisms that allow an application to scalably execute bcast/iAllReduce from any MPI rank without specifying the origin of the message in advance, demonstrating application development flexibility, highly scalable operation, and reduced application synchronization.", + "laborHours": 11536.8, + "languages": [], + "name": "Rootless Operations for MPI (RLO) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/tonylbl/rootless-operations", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Rossi_Alpha_View.json b/agency-indexes/DoE/Rossi_Alpha_View.json new file mode 100644 index 00000000..20f578ce --- /dev/null +++ b/agency-indexes/DoE/Rossi_Alpha_View.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "Rossi Alpha View (RAV) is a teaching aid for explaining what a Rossi-alpha distribution is and how it is generated. The software provides graphical user interface (GUI) in which a pulse train is shown from which a Rossi-alpha distribution is generated as pulses appear. The source strength, correlated fraction, and speed of the pulse train can be adjusted as well as the die-away time and efficiency of the hypothetical detector from which the pulses would be generated. Additionally, neutron coincidence counting principles are illustrated through the software by showing a reals plus accidentals (R+A) gate and an accidentals (A) gate with an adjustable pre-delay, gate width, and long delay.", + "laborHours": 0.0, + "languages": [], + "name": "Rossi Alpha View", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/RossiAlphaView", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RotorSE.json b/agency-indexes/DoE/RotorSE.json new file mode 100644 index 00000000..dd2e0db6 --- /dev/null +++ b/agency-indexes/DoE/RotorSE.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A module for static aerodynamic and structural analysis of wind turbine rotors", + "laborHours": 15960.0, + "name": "RotorSE", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/rotorse", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RouteE-Compass_[SWR-23-95].json b/agency-indexes/DoE/RouteE-Compass_[SWR-23-95].json new file mode 100644 index 00000000..a660879c --- /dev/null +++ b/agency-indexes/DoE/RouteE-Compass_[SWR-23-95].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-09", + "metadataLastUpdated": "2024-01-17" + }, + "description": "RouteE Compass is an energy-aware routing engine for the NREL-developed RouteE ecosystem of software tools with the following key features:\n\n- Dynamic and extensible search objectives that allow customized blends of distance, time, cost, and energy (via RouteE Powertrain) at query-time\n\n- Core engine written in Rust for improved runtimes, parallel query execution, and the ability to load nation-sized road networks into memory\n\n-Rust, HTTP, and Python APIs for integration into different research pipelines and other software\n\nRouteE Compass is a part of the RouteE family of mobility tools created at the National Renewable Energy Laboratory (NREL).", + "laborHours": 0.0, + "languages": [ + "Rust", + "Python" + ], + "name": "RouteE-Compass [SWR-23-95]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/routee-compass", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.6.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RouteE-Powertrain_[SWR-19-19].json b/agency-indexes/DoE/RouteE-Powertrain_[SWR-19-19].json new file mode 100644 index 00000000..7be476c2 --- /dev/null +++ b/agency-indexes/DoE/RouteE-Powertrain_[SWR-19-19].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-10-09", + "metadataLastUpdated": "2023-10-30" + }, + "description": "RouteE-Powertrain is a tool for predicting energy usage over a set of road links.\n\nRouteE-Powertrain is a Python package that allows users to work with a set of pre-trained mesoscopic vehicle energy prediction models for a varity of vehicle types. Additionally, users can train their own models if \"ground truth\" energy consumption and driving data are available. RouteE-Powertrain models predict vehicle energy consumption over links in a road network, so the features considered for prediction often include traffic speeds, road grade, turns, etc.\n\nThe typical user will utilize RouteE's catalog of pre-trained models. Currently, the catalog consists of light-duty vehicle models, including conventional gasoline, diesel, hybrid electric (HEV), and battery electric (BEV). These models can be applied to link-level driving data (in the form of pandas dataframes) to output energy consumption predictions.\n\nUsers that wish to train new RouteE models can do so. The model training function of RouteE enables users to use their own drive-cycle data, powertrain modeling system, and road network data to train custom models.\n\nhttps://pypi.org/project/nrel.routee.powertrain/\npip install nrel.routee.powertrain", + "laborHours": 0.0, + "languages": [ + "Shell", + "Rust", + "Python" + ], + "name": "RouteE-Powertrain [SWR-19-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/routee-powertrain", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Route_Sanitizer:_Connected_Vehicle_Trajectory_De-Identification_Tool.json b/agency-indexes/DoE/Route_Sanitizer:_Connected_Vehicle_Trajectory_De-Identification_Tool.json new file mode 100644 index 00000000..35e4e140 --- /dev/null +++ b/agency-indexes/DoE/Route_Sanitizer:_Connected_Vehicle_Trajectory_De-Identification_Tool.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Route Sanitizer is ORNL's connected vehicle moving object database de-identification tool and a graphical user interface to ORNL's connected vehicle de-identification algorithm. It uses the Google Chrome (soon to be Electron) platform so it will run on different computing platforms. The basic de-identification strategy is record redaction: portions of a vehicle trajectory (e.g. sequences of precise temporal spatial records) are removed. It does not alter retained records. The algorithm uses custom techniques to find areas within trajectories that may be considered private, then it suppresses those in addition to enough of the trajectory surrounding those locations to protect against \"inference attacks\" in a mathematically sound way. Map data is integrated into the process to make this possible.", + "laborHours": 0.0, + "name": "Route Sanitizer: Connected Vehicle Trajectory De-Identification Tool", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmcarter9t/route-sanitizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Routing_and_Infrastructure_simulation_for_Shared_Electric_vehicles__RISE_.json b/agency-indexes/DoE/Routing_and_Infrastructure_simulation_for_Shared_Electric_vehicles__RISE_.json new file mode 100644 index 00000000..dea47794 --- /dev/null +++ b/agency-indexes/DoE/Routing_and_Infrastructure_simulation_for_Shared_Electric_vehicles__RISE_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-06", + "metadataLastUpdated": "2019-10-04" + }, + "description": "FERIS is an agent-based model that simulates the activity of a fleet of electric taxis in a metropolitan area. Agent activities include serving trips, rebalancing to anticipate future demand, and relocating to charge. The modeling framework allows researchers to study the impact of different routing algorithms, battery range, and charging infrastructure on fleet performance, energy consumption, environmental impact, and cost of service.", + "laborHours": 912.0, + "languages": [], + "name": "Routing and Infrastructure simulation for Shared Electric vehicles (RISE)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gb4uer/RISE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Rubik.json b/agency-indexes/DoE/Rubik.json new file mode 100644 index 00000000..9f009677 --- /dev/null +++ b/agency-indexes/DoE/Rubik.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Rubik is a tool that simplifies the process of creating task mappings for structured applications. Rubik allows an application developer to specify communicating groups of processes in a virtual application topology succinctly and map them onto groups of processors in a physical network topology. Both the application topology and the network topology must be Cartesian, but the dimensionality of either is arbitrary. This allows users to easily map low-dimensional structures such as planes to higher-dimensional structures like cubes to increase the number of links used for routing.", + "laborHours": 896.8, + "name": "Rubik", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/rubik/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/rubik", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Rucio_-_Scientific_Data_Management.json b/agency-indexes/DoE/Rucio_-_Scientific_Data_Management.json new file mode 100644 index 00000000..11fa44b2 --- /dev/null +++ b/agency-indexes/DoE/Rucio_-_Scientific_Data_Management.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "Rucio is a software framework that provides functionality to organize, manage, and access large volumes of scientific data using customisable policies. The data can be spread across globally distributed locations and across heterogeneous data centers, uniting different storage and network technologies as a single federated entity. Rucio offers advanced features such as distributed data recovery or adaptive replication, and is highly scalable, modular, and extensible. Rucio has been originally developed to meet the requirements of the high-energy physics experiment ATLAS, and is continuously extended to support LHC experiments and other diverse scientific communities.", + "laborHours": 0.0, + "languages": [], + "name": "Rucio - Scientific Data Management", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/rucio", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RuleBuilder.json b/agency-indexes/DoE/RuleBuilder.json new file mode 100644 index 00000000..c54cb57a --- /dev/null +++ b/agency-indexes/DoE/RuleBuilder.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-01-29", + "metadataLastUpdated": "2018-01-29" + }, + "description": "RuleBuilder is a tool for drawing graphs represented by the BioNetGen rule-based modeling language (BNGL), a domain-specific language used to formulate mathematical models of biochemical interaction networks. This framework provides an intuitive plain-text representation of such networks using a graph-based formalism. The interactions between the model's components are graph-rewriting rules that denote the minimum context needed for the interaction to occur. In some cases the context required for reactions to occur can grow quite large, and the lengthy textual description of the interaction can be difficult to interpret or debug. RuleBuilder is designed to make this process simpler through visualization of individual rule or pattern strings. The software assists in the reading of existing models by converting the BNGL strings of interest into a graph-based representation composed of nodes and edges. RuleBuilder also enables the user to build the visual representation directly from its interface, composing the BNGL string as components and operators are added to the graphical object.", + "laborHours": 1368.0, + "name": "RuleBuilder", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/RuleWorld/RuleBuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/RunTester.json b/agency-indexes/DoE/RunTester.json new file mode 100644 index 00000000..3ff4a6a2 --- /dev/null +++ b/agency-indexes/DoE/RunTester.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "This is a mock app to help with testing the SDK Method Runner.", + "laborHours": 760.0, + "languages": [], + "name": "RunTester", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/RunTester", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SAAMGE.json b/agency-indexes/DoE/SAAMGE.json new file mode 100644 index 00000000..e51fce7e --- /dev/null +++ b/agency-indexes/DoE/SAAMGE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Smoothed aggregation spectral element-based algebraic multigrid.\n", + "laborHours": 10852.8, + "languages": [], + "name": "SAAMGE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/saamge", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SABATH:_Surrogate_AI_Benchmarking_Applications'_Testing_Harness.json b/agency-indexes/DoE/SABATH:_Surrogate_AI_Benchmarking_Applications'_Testing_Harness.json new file mode 100644 index 00000000..51b1ce9a --- /dev/null +++ b/agency-indexes/DoE/SABATH:_Surrogate_AI_Benchmarking_Applications'_Testing_Harness.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "luszczek@icl.utk.edu" + }, + "date": { + "created": "2023-07-30", + "metadataLastUpdated": "2023-07-30" + }, + "description": "SABATH provides benchmarking infrastructure for evaluating scientific ML/AI models. It contains support for scientific machine learning surrogates from external repositories. The software dependences are explicitly exposed in the surrogate model definition, which allows the use of advanced optimization, communication, and hardware features.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SABATH: Surrogate AI Benchmarking Applications' Testing Harness", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/icl-utk-edu/sabath.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SAFIRE_:_Scalable_and_Accurate_Fault_Injection_for_Parallel_Multi-threaded_Applications.json b/agency-indexes/DoE/SAFIRE_:_Scalable_and_Accurate_Fault_Injection_for_Parallel_Multi-threaded_Applications.json new file mode 100644 index 00000000..9263ecd8 --- /dev/null +++ b/agency-indexes/DoE/SAFIRE_:_Scalable_and_Accurate_Fault_Injection_for_Parallel_Multi-threaded_Applications.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-11-14", + "metadataLastUpdated": "2019-11-14" + }, + "description": "The software SAFIRE implements a fault injection tool to evaluate the impact of soft errors on parallel, multi-threaded applications.\n\nIt implements instruction-level fault models that emulate soft errors by flipping bits in the register operands of executed machine instructions.\n\nSAFIRE is based on the LLVM compiler and utilizes novel techniques to optimize instruction instrumentation and fault injection. \n\nBy detailed measurements, SAFIRE is multiple times faster than other state-of-the-art fault injection techniques, while having the same accuracy.", + "laborHours": 1362148.0, + "languages": [], + "name": "SAFIRE : Scalable and Accurate Fault Injection for Parallel Multi-threaded Applications", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/safire", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "v1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SAGESim.json b/agency-indexes/DoE/SAGESim.json new file mode 100644 index 00000000..f11b8128 --- /dev/null +++ b/agency-indexes/DoE/SAGESim.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "gunaratnecs@ornl.gov" + }, + "date": { + "created": "2024-03-27", + "metadataLastUpdated": "2024-03-27" + }, + "description": "SAGESim: Scalable Agent-based GPU-Enabled Simulator is a distributed GPU agent-based modeling framework in Python. SAGESim enables researchers to study complex adaptive systems at large scales on high-performance computing systems", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SAGESim", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl/sagesim", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SAMMY.json b/agency-indexes/DoE/SAMMY.json new file mode 100644 index 00000000..120b4f67 --- /dev/null +++ b/agency-indexes/DoE/SAMMY.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "wiardada@ornl.gov" + }, + "date": { + "created": "2020-05-20", + "metadataLastUpdated": "2020-05-20" + }, + "description": "SAMMY is an R-matrix Bayesian fitting program used in the analysis of nuclear cross section data.", + "laborHours": 199621.6, + "languages": [ + "Fortran and C++" + ], + "name": "SAMMY", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/RNSD/SAMMY", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "8.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SAMPA__Solar_and_Moon_Position_Algorithm_.json b/agency-indexes/DoE/SAMPA__Solar_and_Moon_Position_Algorithm_.json new file mode 100644 index 00000000..6e7df7ef --- /dev/null +++ b/agency-indexes/DoE/SAMPA__Solar_and_Moon_Position_Algorithm_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-09-09", + "metadataLastUpdated": "2019-09-10" + }, + "description": "SAMPA calculates the location of the Sun and Moon in the sky for the purpose of solar eclipse monitoring and for estimating the influence on solar irradiance. Valid from the year -2000 to 6000, with an uncertainty of +/- 0.0003 degrees for the Sun position and +/- 0.003 degrees for the Moon position. \n", + "homepageURL": "https://midcdmz.nrel.gov/solpos/sampa.html", + "laborHours": 0.0, + "languages": [], + "name": "SAMPA (Solar and Moon Position Algorithm)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://midcdmz.nrel.gov/sampa/#license", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://midcdmz.nrel.gov/solpos/sampa.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/SAM\342\204\242__System_Advisor_Model\342\204\242_.json" "b/agency-indexes/DoE/SAM\342\204\242__System_Advisor_Model\342\204\242_.json" new file mode 100644 index 00000000..be3a9ee9 --- /dev/null +++ "b/agency-indexes/DoE/SAM\342\204\242__System_Advisor_Model\342\204\242_.json" @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-16", + "metadataLastUpdated": "2023-07-25" + }, + "description": "The SAM\u2122 Open Source Project repository contains the source code, tools, and instructions to build a desktop version of the National Renewable Energy Laboratory's (NREL's) System Advisor Model\u2122 (SAM). SAM is a simulation program for electricity generation projects. It has models for different kinds of renewable energy systems and financial models for residential, commercial, and utility-scale projects. For more details about SAM's capabilities, see the SAM website at https://sam.nrel.gov/. For a short video describing the SAM repositories, see https://youtu.be/E5z1iiZfZ3M.", + "laborHours": 552915.2, + "languages": [ + "C++", + "LK script" + ], + "name": "SAM\u2122 (System Advisor Model\u2122)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SAM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/SAM\342\204\242__System_Advisor_Model\342\204\242__[SWR-16-02,_SWR-10-13].json" "b/agency-indexes/DoE/SAM\342\204\242__System_Advisor_Model\342\204\242__[SWR-16-02,_SWR-10-13].json" new file mode 100644 index 00000000..29fef243 --- /dev/null +++ "b/agency-indexes/DoE/SAM\342\204\242__System_Advisor_Model\342\204\242__[SWR-16-02,_SWR-10-13].json" @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-07-25", + "metadataLastUpdated": "2023-07-25" + }, + "description": "See the SAM\u2122 website to build a desktop version of the National Renewable Energy Laboratory's (NREL's) System Advisor Model\u2122 (SAM). https://sam.nrel.gov/\n\nThe System Advisor Model\u2122 (SAM\u2122) is a free techno-economic software model that facilitates decision-making for people in the renewable energy industry:\n\n-Project managers and engineers\n-Policy analysts\n-Technology developers\n-Researchers\nSAM can model many types of renewable energy systems:\n\n-Photovoltaic systems, from small residential rooftop to large utility-scale systems\n-Battery storage with Lithium ion, lead acid, or flow batteries for front-of-meter or behind-the-meter applications\n-Concentrating Solar Power systems for electric power generation, including parabolic trough, power tower, and linear Fresnel\n-Industrial process heat from parabolic trough and linear Fresnel systems\n-Wind power, from individual turbines to large wind farms\n-Marine energy wave and tidal systems\n-Solar water heating\n-Fuel cells\n-Geothermal power generation\n-Biomass combustion for power generation\n-High concentration photovoltaic systems\n\nSAM's financial models are for the following types of projects:\n\n-Residential and commercial projects where the renewable energy system is on the customer side of the electric utility meter (behind the meter), and power from the system is used to reduce the customer's electricity bill.\n\n-Power purchase agreement (PPA) projects where the system is connected to the grid at an interconnection point, and the project earns revenue through power sales. The project may be owned and operated by a single owner or by a partnership involving a flip or leaseback arrangement.\n\n-Third party ownership where the system is installed on the customer's (host) property and owned by a separate entity (developer), and the host is compensated for power generated by the system through either a PPA or lease agreement.\n\nFor a more detailed description of SAM, see Blair et al. (2018), System Advisor Model (SAM) General Description (Version 2017.9.5), NREL/TP-6A20-70414. \n\nhttps://www.nrel.gov/docs/fy18osti/70414.pdf\n", + "laborHours": 552915.2, + "languages": [ + "C++", + "LK script" + ], + "name": "SAM\u2122 (System Advisor Model\u2122) [SWR-16-02, SWR-10-13]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SAM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "2020.2.29" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SANSMIC_v.1.0.json b/agency-indexes/DoE/SANSMIC_v.1.0.json new file mode 100644 index 00000000..1c75f789 --- /dev/null +++ b/agency-indexes/DoE/SANSMIC_v.1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SAND2024-01036O\nThe updated Sandia Solution Mining Code (SANSMIC) modeling software models the dissolution of underground salt cavern walls due to raw-water injection (leaching), assuming an oil blanket. A previous version of this software modeled the impacts of leaching at the Strategic Petroleum Reserve and has been used in research for several decades, but the source code was not available. The new version will enhance current research as additional subsurface storage of energy in solution-mined caverns increases. It will also allow research reproducibility by making the software available to the wider research community. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 2021.6, + "languages": [ + "C++", + "Python" + ], + "name": "SANSMIC v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sansmic", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SANS_Holiday_Hack_2018.json b/agency-indexes/DoE/SANS_Holiday_Hack_2018.json new file mode 100644 index 00000000..91419a79 --- /dev/null +++ b/agency-indexes/DoE/SANS_Holiday_Hack_2018.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "ESnet Security Team's SANS Holiday Hack 2018 Report.", + "laborHours": 73431.2, + "languages": [], + "name": "SANS Holiday Hack 2018", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/sans-holiday-hack-2018", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SBLLmalloc_V1.0.json b/agency-indexes/DoE/SBLLmalloc_V1.0.json new file mode 100644 index 00000000..1f91efe0 --- /dev/null +++ b/agency-indexes/DoE/SBLLmalloc_V1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Memory size has long limited large-scale applications on high-performance computing (HPC) systems. Increasing core counts per chip and power density constraints, which limit the number of DIMMs per node, have exacerbated this problem. Mechanisms to manage memory usage - preferably transparently - more efficiently could increase effective DRAM capacity and, thus, the benefit of multicore similarity. These data regions occupy multiple physical locations within a multicore node and thus offer a potential savings in memory capacity. These data, primarily residing in heap, are quite dynamic, which makes them difficult to manage statically. SBLLmalloc is a memory allocation library that automatically identifies the replicated memory blocks and merges them into a single copy. SBLLmalloc does not require application or OS changes since we implement it as a user-level library that can be linked at runtime. SBLLmalloc provides the capability to run larger problems using the same hardware configuration in multicore nodes. SBLLmalloc has been implemented for Linux clusters.", + "laborHours": 4681.6, + "name": "SBLLmalloc V1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SBLLmalloc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SCALE_DB-Public.json b/agency-indexes/DoE/SCALE_DB-Public.json new file mode 100644 index 00000000..3c0da042 --- /dev/null +++ b/agency-indexes/DoE/SCALE_DB-Public.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "brownjm@ornl.gov" + }, + "date": { + "created": "2024-02-27", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This is a collection of public data produced by AMPX or curated from quality sources that the SCALE code system relies on for user problem input.", + "laborHours": 15.2, + "languages": [], + "name": "SCALE/DB-Public", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/scale/code/db-public/-/blob/main/LICENSE", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/scale/data/db-public", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SCC__Step_characteristics_calculator__[SWR-21-80].json b/agency-indexes/DoE/SCC__Step_characteristics_calculator__[SWR-21-80].json new file mode 100644 index 00000000..19108e10 --- /dev/null +++ b/agency-indexes/DoE/SCC__Step_characteristics_calculator__[SWR-21-80].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2023-06-16" + }, + "description": "The SCC software calculates the step response characteristics based on the data collected from the plant. The tools available to characterize the step response needs a plant model. Our tool calculates the characteristics based on the data captured from the plant. This prevents the user from building a plant model and directly calculates the response.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SCC (Step characteristics calculator) [SWR-21-80]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/scc", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SCEPTRE__v._2.0__Sandia_Computational_Engine_for_Particle_Transport_for_Radiat.json b/agency-indexes/DoE/SCEPTRE__v._2.0__Sandia_Computational_Engine_for_Particle_Transport_for_Radiat.json new file mode 100644 index 00000000..402515d1 --- /dev/null +++ b/agency-indexes/DoE/SCEPTRE__v._2.0__Sandia_Computational_Engine_for_Particle_Transport_for_Radiat.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-20", + "metadataLastUpdated": "2020-11-03" + }, + "description": "SCEPTRE solves the linear Boltzmann transport equation for general one-, two- and three-dimensional unstructured-mesh Cartesian geometries. SCEPTRE can handle any particle type for which multigroup-Legendre cross sections are available. However, the code is designed primarily to model the transport of photons, electrons, and positrons through matter. SCEPTRE 2.0 includes several auxiliary packages for pre- and post-processing, regression testing, stochastic radiation transport, thermal radiation transport, and charged-particle transport in the presence of electromagnetic fields. SCEPTRE 2.0 includes sophisticated transport-synthetic acceleration and ray-effects mitigation capabilities.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "SCEPTRE v. 2.0 (Sandia Computational Engine for Particle Transport for Radiat", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SCF:_Seismicity-Constrained_Fault_Detection_and_Characterization.json b/agency-indexes/DoE/SCF:_Seismicity-Constrained_Fault_Detection_and_Characterization.json new file mode 100644 index 00000000..92869f30 --- /dev/null +++ b/agency-indexes/DoE/SCF:_Seismicity-Constrained_Fault_Detection_and_Characterization.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "SCF: Seismicity-Constrained Fault Detection and Characterization", + "laborHours": 2143.2, + "languages": [], + "name": "SCF: Seismicity-Constrained Fault Detection and Characterization", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/scf", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SCIRun.json b/agency-indexes/DoE/SCIRun.json new file mode 100644 index 00000000..340bd34f --- /dev/null +++ b/agency-indexes/DoE/SCIRun.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "SciRun is a problem solving environment for modeling, simulation and visualization of scientific problems; VACET extends the visualization component. ", + "laborHours": 612924.8, + "languages": [], + "name": "SCIRun", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SCIInstitute/SCIRun", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SCORPIO.json b/agency-indexes/DoE/SCORPIO.json new file mode 100644 index 00000000..a0bc8d7d --- /dev/null +++ b/agency-indexes/DoE/SCORPIO.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jayesh@mcs.anl.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-06-08" + }, + "description": "The SCORPIO (Software for Caching Output and Reads for Parallel I/O) library provides a portable application programming interface (API) for describing, reading and storing array-oriented data that is distributed in memory across multiple processes. It is used by all the model components in DOE's Energy Exascale Earth System Model (E3SM) for reading input data and writing model output. The library also supports rearranging data distributed across multiple processes before using low-level I/O libraries like PnetCDF, NetCDF, and ADIOS to write the data to the file system. The library was derived from the Parallel I/O library.", + "laborHours": 142074.4, + "languages": [ + "C", + "C++", + "Fortran" + ], + "name": "SCORPIO", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/scorpio", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SCPACK_vR1.0.json b/agency-indexes/DoE/SCPACK_vR1.0.json new file mode 100644 index 00000000..265b2982 --- /dev/null +++ b/agency-indexes/DoE/SCPACK_vR1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-11-12", + "metadataLastUpdated": "2019-11-12" + }, + "description": "User-defined elements in ANSYS enable programming of the finite element method to simulate the unique behavior of superconducting magnets. A set of electromagnetic and thermal user elements incorporate both quench and interfilament coupling current (IFCC) effects in a consistent manner, allowing for simulation of strongly coupled, multiphysics behavior typical of superconducting devices.", + "laborHours": 6870.4, + "languages": [], + "name": "SCPACK vR1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lnbrouwer/ANSYS_UEL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SCRIBE_3D-Tabletop_Recorder_v._1.1.json b/agency-indexes/DoE/SCRIBE_3D-Tabletop_Recorder_v._1.1.json new file mode 100644 index 00000000..490c32c4 --- /dev/null +++ b/agency-indexes/DoE/SCRIBE_3D-Tabletop_Recorder_v._1.1.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-28", + "metadataLastUpdated": "2018-10-23" + }, + "description": "The Scribetabletop recorder allows usersto visually record and play backscenariosdeveloped during atabletop exercise. It offers a set of tools to visualize,organize, record data, and make decisions while usersdevelop scenarios.Datacan be viewed in both 2D and 3D and played backin real-time or at various speeds", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "SCRIBE 3D-Tabletop Recorder v. 1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SDE_quark.json b/agency-indexes/DoE/SDE_quark.json new file mode 100644 index 00000000..2b0777da --- /dev/null +++ b/agency-indexes/DoE/SDE_quark.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-03-12", + "metadataLastUpdated": "2024-03-19" + }, + "description": "This program provides a fixed-grid quadrature algorithm to compute integrals in the self-energy of the quark propagator within the Maris-Tandy model. The quark propagator both on t he spacelike real axis and at complex-valued momenta is determined from its Schwinger-Dyson equation (SDE). We first apply an iterative solver to find the quark propagator on the spacelike real axis. The propagator at complex-valued momenta is then computed from its self-energy based on this solution, where \ndemanding integrals are encountered. In order to compute of these integrals, we apply customized variable transformations for the radial integral after subtracting the asymptotics. We subsequently apply an optional compound of quadrature rules for the angular integral.", + "laborHours": 0.0, + "languages": [], + "name": "SDE_quark", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/shaoyangjia/SDE_quark", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SDOM__Storage_Deployment_Optimization_Model__[SWR-21-73].json b/agency-indexes/DoE/SDOM__Storage_Deployment_Optimization_Model__[SWR-21-73].json new file mode 100644 index 00000000..377454ac --- /dev/null +++ b/agency-indexes/DoE/SDOM__Storage_Deployment_Optimization_Model__[SWR-21-73].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-08-08", + "metadataLastUpdated": "2023-09-19" + }, + "description": "SDOM is designed to accurately represent the operation of energy storage across different timescales, including long-duration and seasonal applications, and the spatiotemporal diversity and complementarity among VRE sources. SDOM uses an hourly temporal resolution, a fine spatial resolution for VRE sources, and a 1-year optimization window. SDOM assumes that all builds of VRE are accompanied by sufficient additional transmission capacity to allow full utilization of these additional resources. Nuclear, hydropower, and other renewable generation (e.g., biomass and geothermal energy sources) are fixed based on operational data (time series) for a given year; thus, SDOM minimizes total system cost using conventional generators as balancing units and using VRE and storage technologies to achieve a user-defined carbon-free or renewable energy target. The total system cost includes capital costs, fixed operation-and-maintenance (FO&M) costs, variable operation-and-maintenance (VO&M) costs, and fuel cost for power generation and storage technologies.", + "laborHours": 0.0, + "languages": [ + "GAMS", + "Python" + ], + "name": "SDOM (Storage Deployment Optimization Model) [SWR-21-73]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SDOM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SDSKV__SDS_Key_Val_.json b/agency-indexes/DoE/SDSKV__SDS_Key_Val_.json new file mode 100644 index 00000000..9375593d --- /dev/null +++ b/agency-indexes/DoE/SDSKV__SDS_Key_Val_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-28", + "metadataLastUpdated": "2022-01-28" + }, + "description": "Simple margo-projected keyval service.", + "laborHours": 0.0, + "languages": [], + "name": "SDSKV (SDS Key/Val)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-sdskv/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-sdskv", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SDS_Distributed_Key-Value.json b/agency-indexes/DoE/SDS_Distributed_Key-Value.json new file mode 100644 index 00000000..58e0549f --- /dev/null +++ b/agency-indexes/DoE/SDS_Distributed_Key-Value.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-31", + "metadataLastUpdated": "2022-01-31" + }, + "description": "SDSDKV is a configurable distributed key-value service.", + "laborHours": 0.0, + "languages": [], + "name": "SDS Distributed Key-Value", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-sdsdkv", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SDynPy:_A_Structural_Dynamics_Python_Library.json b/agency-indexes/DoE/SDynPy:_A_Structural_Dynamics_Python_Library.json new file mode 100644 index 00000000..782a240d --- /dev/null +++ b/agency-indexes/DoE/SDynPy:_A_Structural_Dynamics_Python_Library.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2023-08-07" + }, + "description": "SAND2023-11957O\nSDynPy software can be used in digital signal processing, modal analysis, and geometry algorithms that are available in open literature, specifically the Synthesize Modes and Correlate and polynomial-based multiple reference modal fitters. This software can be used to perform structural dynamic testing and analysis. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SDynPy: A Structural Dynamics Python Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sdynpy", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": " v.0.6.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SEACAS_Trilinos.json b/agency-indexes/DoE/SEACAS_Trilinos.json new file mode 100644 index 00000000..3265c7f3 --- /dev/null +++ b/agency-indexes/DoE/SEACAS_Trilinos.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "SEACAS Trilinos is the packaging of the SEACAS applications inside the Trilinos software package in a manner such that the Trilinos build and configurationprocess can be used to build and configure the SEACAS applications.", + "laborHours": 8344830.4, + "languages": [], + "name": "SEACAS Trilinos", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SEEDling.json b/agency-indexes/DoE/SEEDling.json new file mode 100644 index 00000000..19a7a655 --- /dev/null +++ b/agency-indexes/DoE/SEEDling.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-11-18", + "metadataLastUpdated": "2020-11-20" + }, + "description": "SEEDling is intended to simplify the merging of multiple data sources prior to importing into the SEED platform. Geographic information about buildings and taxlots is often obtained from various data sources, and the process of synthesizing this information for many buildings across a city can be burdensome for city data managers. SEEDling uses GIS tools to automate and simplify this process, as well as apply criteria for SEED inclusion (ex: sqft > 50k) and assign UBIDs, to create records that can be easily imported into the SEED platform.", + "laborHours": 87628.0, + "languages": [], + "name": "SEEDling", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SEED-platform/seedling", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SEMS_Pipeline_Framework_Infrastructure.json b/agency-indexes/DoE/SEMS_Pipeline_Framework_Infrastructure.json new file mode 100644 index 00000000..6642da30 --- /dev/null +++ b/agency-indexes/DoE/SEMS_Pipeline_Framework_Infrastructure.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-12" + }, + "description": "The SEMS Pipeline Framework Infrastructure (SPiFI) library is a collection of utilities that simplify the development of Continuous Integration (CI) / Continuous Delivery (CD) pipelines within the Jenkins testing application.\nThe goal of SPiFI is to provide a layer of convenience functions for common tasks a pipeline developer will need to implement, such as timeouts, automatic retries, dry-run testing, concurrent test launching, results aggregation, and email notifications to accelerate pipeline development. SPiFI enables the DevOPs engineer to focus more on what their pipeline should do rather than how to implement certain details within the restricted programming environment provided by the Jenkins application.SAND2020-12550 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 8664.0, + "languages": [ + "Groovy" + ], + "name": "SEMS Pipeline Framework Infrastructure", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SPiFI", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SENSE_Network_Resource_Manager__NRM_.json b/agency-indexes/DoE/SENSE_Network_Resource_Manager__NRM_.json new file mode 100644 index 00000000..633c48f6 --- /dev/null +++ b/agency-indexes/DoE/SENSE_Network_Resource_Manager__NRM_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "This is the repository for esnet/sense-nrm-oscars developed by Energy Sciences Network (ESnet). ", + "laborHours": 2219.2, + "languages": [], + "name": "SENSE Network Resource Manager (NRM)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/sense-nrm-oscars/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/sense-nrm-oscars", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SENSE_Resource_Manager.json b/agency-indexes/DoE/SENSE_Resource_Manager.json new file mode 100644 index 00000000..d986cf4f --- /dev/null +++ b/agency-indexes/DoE/SENSE_Resource_Manager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "This is prototype software supporting the SENSE-RM API over an NSI network.", + "laborHours": 17480.0, + "languages": [], + "name": "SENSE Resource Manager", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/sense-rm/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/sense-rm", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SEPIA__Simulation-Enabled_Prediction,_Inference,_and_Analysis_.json b/agency-indexes/DoE/SEPIA__Simulation-Enabled_Prediction,_Inference,_and_Analysis_.json new file mode 100644 index 00000000..c478a5fb --- /dev/null +++ b/agency-indexes/DoE/SEPIA__Simulation-Enabled_Prediction,_Inference,_and_Analysis_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "SEPIA (Simulation-Enabled Prediction, Inference, and Analysis) is a Python port, with user interface enhancements, of GPMSA software. GPMSA is released as LACC-06-079. \nThe software performs analysis and uncertainty quantification, by comparing experimental observations to ensembles of computer simulations. \nThis software is based on the methodology of Higdon et.al 2008, https://doi.org/10.1198/016214507000000888 .", + "laborHours": 0.0, + "languages": [], + "name": "SEPIA (Simulation-Enabled Prediction, Inference, and Analysis)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SEPIA", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SERAC.json b/agency-indexes/DoE/SERAC.json new file mode 100644 index 00000000..30c08c11 --- /dev/null +++ b/agency-indexes/DoE/SERAC.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-06", + "metadataLastUpdated": "2020-03-03" + }, + "description": "The purpose of this code is to enable collaborative research in simulation of large deformation structural mechanics.\n\nParticularly, it will be used to investigate abstract physics coupling methods and algorithms for implicit solves on emerging computing hardware.", + "laborHours": 24836.8, + "languages": [], + "name": "SERAC", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/serac", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SERI_QC_Solar_Data_Quality_Assessment_Software.json b/agency-indexes/DoE/SERI_QC_Solar_Data_Quality_Assessment_Software.json new file mode 100644 index 00000000..b41e6973 --- /dev/null +++ b/agency-indexes/DoE/SERI_QC_Solar_Data_Quality_Assessment_Software.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-13" + }, + "description": "SERI QC is a mathematical software package that assesses the quality of solar radiation data. The SERI QC software is a function written in the C programming language. IT IS NOT A STANDALONE SOFTWARE APPLICATION. The user must write the calling application that requires quality assessment of solar data. The C function returns data quality flags to the calling program. A companion program, QCFIT, is a standalone Windows application that provides support files for the SERI QC function (data quality boundaries). The QCFIT software can also be used as an analytical tool for visualizing solar data quality independent of the SERI QC function.", + "laborHours": 319.2, + "languages": [ + "C" + ], + "name": "SERI QC Solar Data Quality Assessment Software", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SolarResourceTools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SF-19-055_deer.json b/agency-indexes/DoE/SF-19-055_deer.json new file mode 100644 index 00000000..066dc2ec --- /dev/null +++ b/agency-indexes/DoE/SF-19-055_deer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-12-19", + "metadataLastUpdated": "2024-12-19" + }, + "description": "deer is an application based on the MOOSE framework (https://mooseframework.org/) developed at Idaho National\nLaboratory. The application extends the framework to handle structural problems with a consistent large deformation\nframework as well as adding miscellaneous utility routines we have found useful in our work on high temperature\nstructural design.\n(Provide additional information if necessary in Supplemental section below.)\nYear code", + "laborHours": 10503.2, + "languages": [], + "name": "SF-19-055 deer", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/deer", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SF_Microbe_Methane__SFMM__v1.json b/agency-indexes/DoE/SF_Microbe_Methane__SFMM__v1.json new file mode 100644 index 00000000..11f3b926 --- /dev/null +++ b/agency-indexes/DoE/SF_Microbe_Methane__SFMM__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-20", + "metadataLastUpdated": "2024-06-20" + }, + "description": "Scripts for analyzing microbial community taxonomy and function, running statistical tests, and making complex graphics.", + "laborHours": 14440.0, + "languages": [], + "name": "SF_Microbe_Methane (SFMM) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cliffbueno/SF_microbe_methane", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SHIELDS-PTM.json b/agency-indexes/DoE/SHIELDS-PTM.json new file mode 100644 index 00000000..46591b93 --- /dev/null +++ b/agency-indexes/DoE/SHIELDS-PTM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "The SHIELDS Particle Tracing Model (PTM) is a large-scale particle tracing code, primarily intended for magnetospheric applications. It provides a fast, parallel computing-friendly, and versatile framework for tracing charged particles in arbitrary electric and magnetic fields. To support a broad range of test particle applications, full Lorentz motion can be modeled as well as guiding center motion. Switching strategies allow accurate and efficient test particle tracing across regions where the guiding center approximation may not be maintained. PTM supports tracing of particle motion both forwards and backwards in time. For backwards tracing, PTM can launch particles from a specified location and trace until stopping criteria are met. These stopping criteria can include crossing a surface in space, or a time limit. For forwards tracing particles can be launched from specified points or spatial regions. The code is designed to allow many applications without requiring recompilation, instead providing a rich, user-configurable interface that allows use of different modes at runtime. Model results are stored in user-selected format for post-processing including Liouville mapping of particle fluxes from source to target location. PTM includes pre-processing for field configurations, tools for setting up runs, and post-processing capabilities to enable scientific use. Sample applications include specifying the geosynchronous particle boundary for inner magnetosphere modeling, and determining access of solar energetic protons.", + "laborHours": 0.0, + "languages": [], + "name": "SHIELDS-PTM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SHIELDS-PTM", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SHIFT__Simple_Synthetic_Distribution_Feeder_Generation_Tool__[SWR-22-52].json b/agency-indexes/DoE/SHIFT__Simple_Synthetic_Distribution_Feeder_Generation_Tool__[SWR-22-52].json new file mode 100644 index 00000000..fc0ecba1 --- /dev/null +++ b/agency-indexes/DoE/SHIFT__Simple_Synthetic_Distribution_Feeder_Generation_Tool__[SWR-22-52].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-06-09", + "metadataLastUpdated": "2023-04-24" + }, + "description": "SHIFT is a light weight software package that allows user to to build synthetic feeders around any locations in India. It uses open street data such as roads and buildings and distribution system design principles to generate distribution system model aka feeder model.", + "laborHours": 0.0, + "languages": [ + "PYTHON" + ], + "name": "SHIFT (Simple Synthetic Distribution Feeder Generation Tool) [SWR-22-52]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/shift", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SHIVER.json b/agency-indexes/DoE/SHIVER.json new file mode 100644 index 00000000..5cfa3aa0 --- /dev/null +++ b/agency-indexes/DoE/SHIVER.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "SHIVER (SARS CoV-2 Historically Identified Variants in Epitope Regions) analyzes and summarizes the historical record of amino acid sequences for the Spike protein of the SARS Cov-2 virus. The analysis is focused on the N-terminal domain (NTD) and Receptor Binding domain (RBD) epitope regions, and aims to choose a set of variant forms that collectively cover a large fraction of the sequences in the alignment as a whole (globally) but also that cover large fractions of sequences collected on the different continents. The software provides a set of Spike protein sequences in a standard (fasta) sequence format.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "SHIVER", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SHOCCS.json b/agency-indexes/DoE/SHOCCS.json new file mode 100644 index 00000000..66403dfd --- /dev/null +++ b/agency-indexes/DoE/SHOCCS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "The Stable, High-Order, Cut-Cell Solver (SHOCCS), solves a variety of partial differential equations (PDE's) involving complicated bodies on a simple Cartesian mesh through the use of a novel cut-cell approach.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "SHOCCS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SHOMS.json b/agency-indexes/DoE/SHOMS.json new file mode 100644 index 00000000..9adf0447 --- /dev/null +++ b/agency-indexes/DoE/SHOMS.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SHOMS is a micro benchmark designed to test vendor implementations of the OpenSHMEM 1.1 spec. It seeks to test both bandwidth and latencies for small and large messages.", + "laborHours": 1276.8, + "name": "SHOMS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MattBBaker/shoms", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SHRED:_Stochastic_and_Hybrid_Representation_Electronic_structure_by_Density_functional_theory.json b/agency-indexes/DoE/SHRED:_Stochastic_and_Hybrid_Representation_Electronic_structure_by_Density_functional_theory.json new file mode 100644 index 00000000..33cc8c7b --- /dev/null +++ b/agency-indexes/DoE/SHRED:_Stochastic_and_Hybrid_Representation_Electronic_structure_by_Density_functional_theory.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "The stochastic and hybrid representation electronic structure by density functional theory (SHRED) calculates microscopic material properties using time-dependent, nonadiabatic, and ground-state density functional theory (DFT) with a periodic basis. It can utilize deterministic, stochastic, and hybrid representations of the electronic orbitals. This provides a capability for highly parallelized computation of DFT for larger systems and/or higher temperatures. Thus, the code is particularly suited for calculation of material properties in the warm and hot dense matter regimes.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "SHRED: Stochastic and Hybrid Representation Electronic structure by Density functional theory", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SIERRA_Toolkit_v._1.0.json b/agency-indexes/DoE/SIERRA_Toolkit_v._1.0.json new file mode 100644 index 00000000..c027edd8 --- /dev/null +++ b/agency-indexes/DoE/SIERRA_Toolkit_v._1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The SIERRA Toolkit is a collection of libraries to facilitate the development of parallel engineering analysis applications. These libraries supply basic core services that an engineering analysis application may need such as a parallel distributed and dynamic mesh database (for unstructured meshes), mechanics algorithm support (parallel infrastructure only), interfaces to parallel solvers, parallel mesh and data I/O, and various utilities (timers, diagnostic tools, etc.).The toolkit is intended to reduce the effort required to develop an engineering analysis application by removing the need to develop core capabilities that most every application would require.", + "laborHours": 8344830.4, + "name": "SIERRA Toolkit v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/stk/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SIERRA_Toolkit_v._2.0.json b/agency-indexes/DoE/SIERRA_Toolkit_v._2.0.json new file mode 100644 index 00000000..a503ca7c --- /dev/null +++ b/agency-indexes/DoE/SIERRA_Toolkit_v._2.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The SIERRA Toolkit is a collection of libraries to facilitate the development of parallel engineering analysis applications. These libraries supply basic core services that an engineering application may need such as a parallel distributed and dynamic mesh database (for unstructured meshes), mechanics algorithm support (parallel infrastructure only), interfaces to parallel solvers, parallel mesh and data I/O, and various utilities (timers, diagnostic tools, etc.)", + "laborHours": 8344830.4, + "languages": [ + "C++" + ], + "name": "SIERRA Toolkit v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SING__Synthetic_dIstribution_Network_Generator__[SWR-22-57].json b/agency-indexes/DoE/SING__Synthetic_dIstribution_Network_Generator__[SWR-22-57].json new file mode 100644 index 00000000..5ee04ca6 --- /dev/null +++ b/agency-indexes/DoE/SING__Synthetic_dIstribution_Network_Generator__[SWR-22-57].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-05-25", + "metadataLastUpdated": "2023-04-12" + }, + "description": "Synthetic dIstribution Network Generator is a standalone python module that is able to create synthetic distribution models for OpenDSS using GIS datasets. The software uses road and building information from OpenStreetMaps to generate these synthetic models.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SING (Synthetic dIstribution Network Generator) [SWR-22-57]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SING", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SIRT-FILTER_v1.0.0.json b/agency-indexes/DoE/SIRT-FILTER_v1.0.0.json new file mode 100644 index 00000000..12683974 --- /dev/null +++ b/agency-indexes/DoE/SIRT-FILTER_v1.0.0.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Small Python package to compute tomographic reconstructions using a reconstruction method published in: Pelt, D.M., & De Andrade, V. (2017). Improved tomographic reconstruction of large-scale real-world data by filter optimization. Advanced Structural and Chemical Imaging 2: 17; and Pelt, D. M., & Batenburg, K. J. (2015). Accurately approximating algebraic tomographic reconstruction by filtered backprojection. In Proceedings of The 13th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (pp. 158-161).", + "laborHours": 395.2, + "name": "SIRT-FILTER v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.com/dmpelt/sirtfilter/blob/master/license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/dmpelt/sirtfilter", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SISSO__Sure-independence-screening_sparsifying-operator_regressor_.json b/agency-indexes/DoE/SISSO__Sure-independence-screening_sparsifying-operator_regressor_.json new file mode 100644 index 00000000..9b7306c5 --- /dev/null +++ b/agency-indexes/DoE/SISSO__Sure-independence-screening_sparsifying-operator_regressor_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2021-01-14" + }, + "description": "Implementation of the SISSO regression algorithm in MATLAB. The SISSO regression algorithm iteratively selects model features from candidates, converging even when the number of possible features is much greater than the number of available data points.\n\nIncludes a test script that validates the algorithm by replicating the results using data and procedure from https://analytics-toolkit.nomad-coe.eu/hub/user-redirect/notebooks/tutorials/compressed_sensing.ipynb.\n\nPython code from the SISSO regressor in 'sisso.py', from the link above, was used as the basis for developing the MATLAB implementation. The SISSO regression algorithm is detailed by the original authors in R. Ouyang, S. Curtarolo, E. Ahmetcik et al., Phys. Rev. Mater. 2, 083802 (2018), R. Ouyang, E. Ahmetcik, C. Carbogno, M. Scheffler, and L. M. Ghiringhelli, J. Phys.: Mater. 2, 024002 (2019).", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "SISSO (Sure-independence-screening sparsifying-operator regressor)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SISSORegressor_MATLAB", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SKAT_GWAS.json b/agency-indexes/DoE/SKAT_GWAS.json new file mode 100644 index 00000000..91b2c5c7 --- /dev/null +++ b/agency-indexes/DoE/SKAT_GWAS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "KBase application for Genome-wide association studies (GWAS) utilizing Sequence Kernel Association Tests (SKAT).", + "laborHours": 395.2, + "languages": [], + "name": "SKAT_GWAS", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/SKAT_GWAS", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SKYSTRATA.json b/agency-indexes/DoE/SKYSTRATA.json new file mode 100644 index 00000000..5e6bb058 --- /dev/null +++ b/agency-indexes/DoE/SKYSTRATA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-10-08", + "metadataLastUpdated": "2022-01-05" + }, + "description": "SKYSTRATA is a software as a service framework for managing and orchestrating containers across cloud systems.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "SKYSTRATA", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SLAC's_EPICS_building_RHEL6_CentOS_6_environment_Docker_image.json b/agency-indexes/DoE/SLAC's_EPICS_building_RHEL6_CentOS_6_environment_Docker_image.json new file mode 100644 index 00000000..d7f124f0 --- /dev/null +++ b/agency-indexes/DoE/SLAC's_EPICS_building_RHEL6_CentOS_6_environment_Docker_image.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2022-08-02" + }, + "description": "This is a Docker image builder. The final result of the script build_docker.sh is an image containing the SLAC's EPICS environment needed to build EPICS IOCs in RHEL6 or CentOS 6, including EPICS base, modules, packages, and environment variables. The builder can work with only one EPICS base version of choice, but it can contain multiple versions of the same module and package.", + "laborHours": 0.0, + "languages": [], + "name": "SLAC's EPICS building RHEL6/CentOS 6 environment Docker image", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/smurf-epics-slac/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/smurf-epics-slac", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SLAC_Alarm_Manager.json b/agency-indexes/DoE/SLAC_Alarm_Manager.json new file mode 100644 index 00000000..930b0d8f --- /dev/null +++ b/agency-indexes/DoE/SLAC_Alarm_Manager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-06-16", + "metadataLastUpdated": "2022-06-16" + }, + "description": "A python based user interface for monitoring and managing alarms.", + "laborHours": 0.0, + "languages": [], + "name": "SLAC Alarm Manager", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/slac-alarm-manager/blob/main/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/slac-alarm-manager", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SLAC_TMO_Template_for_GIT_DOECODE.json b/agency-indexes/DoE/SLAC_TMO_Template_for_GIT_DOECODE.json new file mode 100644 index 00000000..b0281f46 --- /dev/null +++ b/agency-indexes/DoE/SLAC_TMO_Template_for_GIT_DOECODE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "coffee@slac.stanford.edu" + }, + "date": { + "created": "2023-09-20", + "metadataLastUpdated": "2023-09-20" + }, + "description": "Template for development of TMO related code at LCLS(-II)", + "laborHours": 0.0, + "languages": [], + "name": "SLAC TMO Template for GIT/DOECODE", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slac-lcls-tmo/tmo-template", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SLADS-Net.json b/agency-indexes/DoE/SLADS-Net.json new file mode 100644 index 00000000..c759605d --- /dev/null +++ b/agency-indexes/DoE/SLADS-Net.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "Supervised Learning Approach for Dynamic Sampling using Deep Neural Networks.", + "laborHours": 608.0, + "languages": [], + "name": "SLADS-Net", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cphatak/SLADS-Net", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SLAPI.json b/agency-indexes/DoE/SLAPI.json new file mode 100644 index 00000000..5c7d7bdd --- /dev/null +++ b/agency-indexes/DoE/SLAPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-13", + "metadataLastUpdated": "2019-05-13" + }, + "description": "SLAPI is a command line tool that communicates with Spectra Logic tape libraries using their XML command reference. This provides a simple way to administer and monitor Spectra Logic tape libraries in large data centers.", + "laborHours": 2264.8, + "languages": [], + "name": "SLAPI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/slapi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SLATE.json b/agency-indexes/DoE/SLATE.json new file mode 100644 index 00000000..c3458024 --- /dev/null +++ b/agency-indexes/DoE/SLATE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-06-03", + "metadataLastUpdated": "2020-06-03" + }, + "description": "Software for Linear Algebra Targeting Exascale (SLATE) will deliver fundamental dense linear algebra capabilities for current and upcoming distributed-memory systems, including GPU-accelerated systems as well as more traditional multi core-only systems.", + "homepageURL": "https://bitbucket.org/icl/slate/src/default", + "laborHours": 52713.6, + "languages": [], + "name": "SLATE", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/icl/slate/src/default/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/icl/slate/src/default", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SLIC.json b/agency-indexes/DoE/SLIC.json new file mode 100644 index 00000000..216f8fb1 --- /dev/null +++ b/agency-indexes/DoE/SLIC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "Simulation for the Linear Collider (SLIC) Geant4 simulation application.\n", + "laborHours": 4104.0, + "languages": [], + "name": "SLIC", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/slic/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/slic", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SLICE.json b/agency-indexes/DoE/SLICE.json new file mode 100644 index 00000000..fc6bf17a --- /dev/null +++ b/agency-indexes/DoE/SLICE.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bostelmannf@ornl.gov" + }, + "date": { + "created": "2024-10-03", + "metadataLastUpdated": "2024-10-03" + }, + "description": "For most of their lifetime, pebble-bed reactors (PBRs) operate at an equilibrium state in which the core is filled with fuel pebbles at various levels of burnup. A fuel pebble travels multiple times in so-called passes through the reactor before it reaches its target discharge burnup and is replaced with a fresh fuel pebble. Given the stochastic nature of the fuel pebble travel paths and consequently the individual fuel pebble histories, it is not possible with standard methods developed for traditional reactor concepts to calculate the fuel inventory in the reactor core. \nAn iterative approach, the SCALE Leap-In method for Cores at Equilibrium (SLICE), was developed to generate region-average fuel inventory for a PBR. The SLICE code enables automatic generation of input files for the SCALE code system (https://www.ornl.gov/scale), management of the SCALE result files, and analysis of results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SLICE", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/scale/code/slice", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SLIP__Surrogate_Launching_and_Integration_Platform_.json b/agency-indexes/DoE/SLIP__Surrogate_Launching_and_Integration_Platform_.json new file mode 100644 index 00000000..b2d24a9d --- /dev/null +++ b/agency-indexes/DoE/SLIP__Surrogate_Launching_and_Integration_Platform_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "luszczek@icl.utk.edu" + }, + "date": { + "created": "2023-07-30", + "metadataLastUpdated": "2023-07-30" + }, + "description": "SLIP (Surrogate Launching and Integration Platform) is a software ecosystem for downloading and running ML/AI benchmarks.\nSLIP automatically downloads and sets up the code and data running a benchmark. The large data sets and model code are cached locally with a specific ID within a designated cache directory.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SLIP (Surrogate Launching and Integration Platform)", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/icl-utk-edu/slip.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SLMod.json b/agency-indexes/DoE/SLMod.json new file mode 100644 index 00000000..ff94a041 --- /dev/null +++ b/agency-indexes/DoE/SLMod.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The software is a modular framework for controlling data acquisition systems (DAQs) for radiation detectors. Its capabilities include hardware configuration and control as well as data readout and storage. In addition to a generalized extensible framework for building DAQs, the package also includes specific implementations for a number of commercially available hardware devices commonly used in nuclear instrumentation (digitizers, high voltage controllers, etc.).", + "laborHours": 9667.2, + "languages": [ + "Lua" + ], + "name": "SLMod", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DCS-Slmod", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SLURM.json b/agency-indexes/DoE/SLURM.json new file mode 100644 index 00000000..98477e3a --- /dev/null +++ b/agency-indexes/DoE/SLURM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "This is SLURM, the Simple Linux Utility for Resource Management. SLURM is an open-source cluster resource management and job scheduling system that strives to be simple, scalable, portable, fault-tolerant, and interconnect agnostic. SLURM currently has been tested only under Linux.", + "laborHours": 307465.6, + "languages": [], + "name": "SLURM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/slurm", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SLURM_spank_plugins.json b/agency-indexes/DoE/SLURM_spank_plugins.json new file mode 100644 index 00000000..6b2c981c --- /dev/null +++ b/agency-indexes/DoE/SLURM_spank_plugins.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "This package includes several SLURM spank plugins developed at LLNL and used on production compute clusters onsite. A few of these plugins are only valid when used on LLNL's software stack (oom-detect.so, for example, requires LLNL-specific patches to track job's terminated by the OOM killer). However, the source for all plugins is provided here in the hope that they might be useful to other plugin developers. The following is a short description of most of the plugins in this package.", + "laborHours": 8314.4, + "languages": [], + "name": "SLURM spank plugins", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/slurm-spank-plugins", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SMAQC.json b/agency-indexes/DoE/SMAQC.json new file mode 100644 index 00000000..9783b723 --- /dev/null +++ b/agency-indexes/DoE/SMAQC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SMAQC computes quality metrics for a LC-MS/MS dataset. The quality metrics are based on the metrics proposed by Rudnick and Stein, as described in \"Performance metrics for liquid chromatography-tandem mass spectrometry systems in proteomics analyses.\", Mol Cell Proteomics. 2010 Feb;9(2):225-41. SMAQC requires that the dataset first be processed with MASIC, then processed with MSGF+ or X!Tandem. The MSGF+ or X!Tandem results must be post-processed with the PeptideHitResultsProcessor (PHRP).", + "laborHours": 5548.0, + "languages": [], + "name": "SMAQC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/SMAQC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SMAQC_Website.json b/agency-indexes/DoE/SMAQC_Website.json new file mode 100644 index 00000000..89117e5c --- /dev/null +++ b/agency-indexes/DoE/SMAQC_Website.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "CodeIgniter based website for browsing QC Metrics stored in DMS", + "laborHours": 51725.6, + "languages": [], + "name": "SMAQC_Website", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/SMAQC_Website", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SMuRF_Cryostat_board_PIC_code.json b/agency-indexes/DoE/SMuRF_Cryostat_board_PIC_code.json new file mode 100644 index 00000000..7f078557 --- /dev/null +++ b/agency-indexes/DoE/SMuRF_Cryostat_board_PIC_code.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "This is the original code for the SMuRF cryostat board. The board is bases on the microchip's microcontroller PIC32MX795F512L. The code was developed using Microchip's MPLAB X and the MPLAB Harmony Configuration (MHC) framework.", + "laborHours": 0.0, + "languages": [], + "name": "SMuRF Cryostat board PIC code", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/smurfc/blob/C04/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/smurfc", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SMuRF_Processor.json b/agency-indexes/DoE/SMuRF_Processor.json new file mode 100644 index 00000000..188ad1e1 --- /dev/null +++ b/agency-indexes/DoE/SMuRF_Processor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-09", + "metadataLastUpdated": "2022-08-09" + }, + "description": "This repository contains the SMuRF data processor. This processor receive each data frame from coming from the SMuRF FPGA, and average the data by a configurable number of samples.", + "laborHours": 0.0, + "languages": [], + "name": "SMuRF Processor", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/smurf-processor/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/smurf-processor", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SNL-NJOY-2016.json b/agency-indexes/DoE/SNL-NJOY-2016.json new file mode 100644 index 00000000..c151790b --- /dev/null +++ b/agency-indexes/DoE/SNL-NJOY-2016.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This is a wrapper around the LANL NJOY-2016 code that interfaces with extended code capabilities and minor modification of the LANL NJOY-2016 code that supports modeling radiation damage to materials. The NJOY Nuclear Data Processing System is a modular computer code designed to read evaluated data in ENDF format, transform the data in various ways, and output the results as libraries designed to be used in various applications. The wrapper provided here permits Sandia-specific control parameters to be used in the input data file. The modifications incorporated here enhance the ability of NJOY to address material damage response functions for many materials, e.g. to include the NRT and arc-dpa forms of the damage energy in addition to the default NJOY-2016 implementation of the sharp-threshold Kinchin-Pease threshold energy treatment. All of the modifications provided here are being made available to the GitHub-based NJOY-2016 code. As useful enhancements found here are incorporated into the baseline NJOY-2016 code, they will be eliminated from this version so as to maintain our compatibility with the baseline NJOY-2016 code. SAND2020-13060 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA00035", + "laborHours": 79344.0, + "languages": [ + "Fortran", + "Postscript", + "LSL", + "CMake", + "Makefile", + "Python" + ], + "name": "SNL-NJOY-2016", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/NJOY2016", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SNL-SWAN.json b/agency-indexes/DoE/SNL-SWAN.json new file mode 100644 index 00000000..040a2ed3 --- /dev/null +++ b/agency-indexes/DoE/SNL-SWAN.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Sandia National Laboratories has modified Simulating WAves Nearshore (SWAN), the Delft University of Technology code,, to include functionality to better model wave energy converters (WECs). The code modified by SNL has been named SNL-SWAN. SNL-SWAN includes a frequency dependent WEC Module that builds upon the traditional obstacle module in SWAN. In SNL-SWAN, a frequency dependent transmission coefficient is calculated to model power absorbed by WEC devices. The power transmission coefficients are calculated based on the WEC's power performance, which is defined by the user in the input text files. Two methods of defining WEC power performance have been implemented: a user-specified power matrix, and a user-specified relative capture width. These methods allow the user to define the WEC's frequency dependent energy absorption as a function of period and/or wave height. SWAN test cases were run to verify the compiled code's functionality, and verification of the frequency dependent WEC Module in SNL-SWAN has also been performed. SNL-SWAN code is will be released as open source code and will be made publicly available.", + "laborHours": 23985.6, + "languages": [ + "Fortran" + ], + "name": "SNL-SWAN", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SNL-SWAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SNL_cxxtest_v._1.0.json b/agency-indexes/DoE/SNL_cxxtest_v._1.0.json new file mode 100644 index 00000000..2c1d0fe7 --- /dev/null +++ b/agency-indexes/DoE/SNL_cxxtest_v._1.0.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "SNL cxxtest is a set of Python routines that support software testing for C++ codes. This software augments the open-source cxxtest project to provide a more comprehensive capability for software testing.", + "laborHours": 11552.0, + "languages": [ + "Smarty", + "C++", + "Shell", + "C", + "CMake", + "Python" + ], + "name": "SNL cxxtest v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/cxxtest", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SNP-VISTA.json b/agency-indexes/DoE/SNP-VISTA.json new file mode 100644 index 00000000..e485be89 --- /dev/null +++ b/agency-indexes/DoE/SNP-VISTA.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-29" + }, + "description": "SNP-VISTA aids in analyses of the following types of data: A. Large-scale re-sequence data of disease-related genes for discovery of associated and/or causative alleles (GeneSNP-VISTA). B. Massive amounts of ecogenomics data for studying homologous recombination in microbial populations (EcoSNP-VISTA). The main features and capabilities of SNP-VISTA are: 1) Mapping of SNPs to gene structure; 2) classification of SNPs, based on their location in the gene, frequency of occurrence in samples and allele composition; 3) clustering, based on user-defined subsets of SNPs, highlighting haplotypes as well as recombinant sequences; 4) integration of protein conservation visualization; and 5) display of automatically calculated recombination points that are user-editable. The main strength of SNP-VISTA is its graphical interface and use of visual representations, which support interactive exploration and hence better understanding of large-scale SNPs data.", + "homepageURL": "http://genome.lbl.gov/vista/snpvista", + "laborHours": 0.0, + "languages": [ + "GNU C++compiler" + ], + "name": "SNP-VISTA", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://genome.lbl.gov/vista/contact.shtml", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://genome.lbl.gov/vista/snpvista", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOAR_experiment_data_and_code.json b/agency-indexes/DoE/SOAR_experiment_data_and_code.json new file mode 100644 index 00000000..5625d15f --- /dev/null +++ b/agency-indexes/DoE/SOAR_experiment_data_and_code.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "bridgesra@ornl.gov" + }, + "date": { + "created": "2022-08-22", + "metadataLastUpdated": "2022-08-23" + }, + "description": "Contains anonymized and obfuscated data from the SOAR (AI ATAC 3) user study and code to produce correlation plots. The experiment, data, and our results are found in our paper https://arxiv.org/abs/2208.06075. Please cite our paper when using this data or code. @article{bridges2022testing, title={Testing SOAR Tools in Use}, author={Bridges, Robert A and Rice, Ashley E and Oesch, Sean and Nichols, Jeff A and Watson, Cory and Spakes, Kevin and Norem, Savannah and Huettel, Mike and Jewell, Brian and Weber, Brian and others}, journal={arXiv preprint arXiv:2208.06075}, year={2022} } file: anonymized_obfuscated_data.csv The data in this table is not the \"raw\" data. It has been user- and SOAR-tool anonymized; SOAR tool names have been removed, as have participant user ids. Probabilistic techniques to obfuscate the data by adding noise while retaining its characteristics have been performed. To ensure utility of the anonymized data, we provide code to reproduce the Subcategory Average Correlation heatmap, found in the publication. While the SOAR tool names have been removed, a binary indicator for if the test data per row is from a SOAR tool or from a baseline environment (full SOC tool suite but no SOAR tool). The likert columns correspond to questions posed to the users (participants) during and after working investigations with a SOAR tool or in a baseline environment (full SOC tool stack but with no SOAR tool). Sentiment columns correspond to answers given by analysts to free response questions. Transcriptions of their responses are quantified with sentiment analysis. The ticket columns report quality and completion of tickets from the test investigations based on percent of correctness according to a gold standard (rubric). The window swapping and time columns report the number of times the participant changed windows in an investigation (quantifying context switching), and the duration of the investigation (quantifying efficiency), respectively. User identification information has been removed. There are four columns of user/participant demographics documenting their familiarity with SOAR tools, job role (SOC analyst or other), number of years working in their security-related job role, and the number of different security operation centers (SOCs) they have supported. These have all been converted to binary variables. Descriptions of all algorithms reside in the paper, along with comments at top of each script and in each function.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "SOAR experiment data and code", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bridgesra/soar_experiment_data_code/releases/tag/ipo", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "pi" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOCRATES.json b/agency-indexes/DoE/SOCRATES.json new file mode 100644 index 00000000..0993b6e7 --- /dev/null +++ b/agency-indexes/DoE/SOCRATES.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SOCRATES is a Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites. It provides tools to retrieve, filter,\nselect, and view Hanford data and to perform multiple types of data analyses. SOCRATES currently includes four data\nanalytics modules", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "SOCRATES", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SODA_frontend.json b/agency-indexes/DoE/SODA_frontend.json new file mode 100644 index 00000000..5329cd1f --- /dev/null +++ b/agency-indexes/DoE/SODA_frontend.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-07-15", + "metadataLastUpdated": "2021-07-15" + }, + "description": "Frontend for the Software Defined Accelerators from Machine Learning Tools Environment (SODALITE) and the Software Defined Architectures for Data Analytics (SO(DA)^2) projects. This frontend takes in input json files from trained neural networks from the most common machine learning tools (PyTorch, TensorFlow, MxNet, etc.) and the related h5 files with weights, and generate the related MLIR (multilevel intermediate representation) linear algebra dialect. This allows the neural networks to be ingested by the rest of the SODA toolchain.", + "laborHours": 0.0, + "languages": [], + "name": "SODA frontend", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.pnnl.gov/sodalite/soda-frontend", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOLARUN__SolarResourceTools_.json b/agency-indexes/DoE/SOLARUN__SolarResourceTools_.json new file mode 100644 index 00000000..5a5f857e --- /dev/null +++ b/agency-indexes/DoE/SOLARUN__SolarResourceTools_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-23", + "metadataLastUpdated": "2019-07-25" + }, + "description": "A critical component of designing solar energy projects that will have long-term profitability is the availability and access to accurate \u201cbankable data\u201d, methodologies and tools to understand the uncertainties in the data. The current solar energy performance and economic models used to convert solar resource data to power generation do not factor in or provide adequate information regarding the uncertainty in the solar resource information. The Solar resource uncertainty (SOLARUN) application assists stakeholders to quantify solar resource measurement uncertainty from radiometers which ultimately support in the decision-making process, speeds up the acceptance and deployment of projects and reduces risk to the financiers and developers.", + "laborHours": 319.2, + "languages": [], + "name": "SOLARUN (SolarResourceTools)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SolarResourceTools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOLCALC.json b/agency-indexes/DoE/SOLCALC.json new file mode 100644 index 00000000..7e862d77 --- /dev/null +++ b/agency-indexes/DoE/SOLCALC.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-10-11", + "metadataLastUpdated": "2019-03-22" + }, + "description": "SolCalc is a software suite that computes and displays magnetic fields generated by a three dimensional (3D) solenoid system. Examples of such systems are the Mu2e magnet system and Helical Solenoids for muon cooling systems. ", + "homepageURL": "http://partnerships.fnal.gov", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "SOLCALC", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://partnerships.fnal.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOLLVE_ECP-ST-CAR-PUBLIC.json b/agency-indexes/DoE/SOLLVE_ECP-ST-CAR-PUBLIC.json new file mode 100644 index 00000000..93a6b25d --- /dev/null +++ b/agency-indexes/DoE/SOLLVE_ECP-ST-CAR-PUBLIC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "The Exascale Computing Project Software Technologies Capability Assessment Report - Public Version", + "laborHours": 7478.4, + "languages": [], + "name": "SOLLVE/ECP-ST-CAR-PUBLIC", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SOLLVE/ECP-ST-CAR-PUBLIC", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOLLVE_argobots.json b/agency-indexes/DoE/SOLLVE_argobots.json new file mode 100644 index 00000000..08fa74b1 --- /dev/null +++ b/agency-indexes/DoE/SOLLVE_argobots.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "Argobots is a lightweight, low-level threading and tasking framework.", + "laborHours": 24289.6, + "languages": [], + "name": "SOLLVE/argobots", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/SOLLVE/argobots/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SOLLVE/argobots", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOLLVE_benchmarks.json b/agency-indexes/DoE/SOLLVE_benchmarks.json new file mode 100644 index 00000000..ecb6c1a3 --- /dev/null +++ b/agency-indexes/DoE/SOLLVE_benchmarks.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "This is the repository for SOLLVE/benchmarks containing cusplibrary, miniVite, and rodinia_3.1. ", + "laborHours": 151544.0, + "languages": [], + "name": "SOLLVE/benchmarks", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/SOLLVE/benchmarks/blob/master/rodinia_3.1/LICENSE", + "name": "Other" + }, + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SOLLVE/benchmarks", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOLLVE_clang.json b/agency-indexes/DoE/SOLLVE_clang.json new file mode 100644 index 00000000..69dcbe6c --- /dev/null +++ b/agency-indexes/DoE/SOLLVE_clang.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "This is a compiler front-end for the C family of languages (C, C++, Objective-C, and Objective-C++) which is built as part of the LLVM compiler infrastructure project.", + "laborHours": 1653532.0, + "languages": [], + "name": "SOLLVE/clang", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SOLLVE/clang", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOLLVE_compiler-rt.json b/agency-indexes/DoE/SOLLVE_compiler-rt.json new file mode 100644 index 00000000..d7669aea --- /dev/null +++ b/agency-indexes/DoE/SOLLVE_compiler-rt.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2021-01-29" + }, + "description": "This is the source code for the compiler support routines developed by the Exascale Computing Project (ECP).", + "homepageURL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "laborHours": 248413.6, + "languages": [], + "name": "SOLLVE/compiler-rt", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOLLVE_libcxx.json b/agency-indexes/DoE/SOLLVE_libcxx.json new file mode 100644 index 00000000..b1d83106 --- /dev/null +++ b/agency-indexes/DoE/SOLLVE_libcxx.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2021-01-29" + }, + "description": "libc++ is an implementation of the C++ standard library, targeting C++11, C++14 and above.", + "homepageURL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "laborHours": 394318.4, + "languages": [], + "name": "SOLLVE/libcxx", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOLLVE_libcxxabi.json b/agency-indexes/DoE/SOLLVE_libcxxabi.json new file mode 100644 index 00000000..7a11c610 --- /dev/null +++ b/agency-indexes/DoE/SOLLVE_libcxxabi.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2021-01-29" + }, + "description": "This is the code for libc++abi developed by the Exascale Computing Project (ECP). ", + "homepageURL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "laborHours": 34139.2, + "languages": [], + "name": "SOLLVE/libcxxabi", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOLLVE_llvm.json b/agency-indexes/DoE/SOLLVE_llvm.json new file mode 100644 index 00000000..9a1f44fc --- /dev/null +++ b/agency-indexes/DoE/SOLLVE_llvm.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "This directory and its subdirectories contain source code for LLVM, a toolkit for the construction of highly optimized compilers, optimizers, and runtime environments.", + "laborHours": 2482798.4, + "languages": [], + "name": "SOLLVE/llvm", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SOLLVE/llvm", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOLLVE_openmp.json b/agency-indexes/DoE/SOLLVE_openmp.json new file mode 100644 index 00000000..680aa0c3 --- /dev/null +++ b/agency-indexes/DoE/SOLLVE_openmp.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2021-01-29" + }, + "description": "This is the code for SOLLVE/openmp developed by the Exascale Computing Project (ECP). ", + "homepageURL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "laborHours": 62715.2, + "languages": [], + "name": "SOLLVE/openmp", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOLLVE_polly.json b/agency-indexes/DoE/SOLLVE_polly.json new file mode 100644 index 00000000..e08a1759 --- /dev/null +++ b/agency-indexes/DoE/SOLLVE_polly.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2021-01-29" + }, + "description": "Polly uses a mathematical representation, the polyhedral model, to represent and transform loops and other control flow structures. Using an abstract\nrepresentation it is possible to reason about transformations in a more general way and to use highly optimized linear programming libraries to figure out the optimal loop structure. These transformations can be used to do constant\npropagation through arrays, remove dead loop iterations, optimize loops for cache locality, optimize arrays, apply advanced automatic parallelization, drive vectorization, or they can be used to do software pipelining.", + "homepageURL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "laborHours": 229945.6, + "languages": [], + "name": "SOLLVE/polly", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOLLVE_test-suite.json b/agency-indexes/DoE/SOLLVE_test-suite.json new file mode 100644 index 00000000..56d10d1a --- /dev/null +++ b/agency-indexes/DoE/SOLLVE_test-suite.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2021-01-29" + }, + "description": "This is the code for SOLLVE/test--suite developed by the Exascale Computing Project (ECP). ", + "homepageURL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "laborHours": 1643560.8, + "languages": [], + "name": "SOLLVE/test-suite", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOLVENT_EXTRACTION_PROCESS_SIMULATOR.json b/agency-indexes/DoE/SOLVENT_EXTRACTION_PROCESS_SIMULATOR.json new file mode 100644 index 00000000..b72ba978 --- /dev/null +++ b/agency-indexes/DoE/SOLVENT_EXTRACTION_PROCESS_SIMULATOR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-09-04", + "metadataLastUpdated": "2019-09-04" + }, + "description": "MODEL FOR DESIGN, SIMULATION AND OPTIMIZATION OF MULTI-STAGE, MULTIPHASE SOLVENT EXTRACTION PROCESS", + "laborHours": 1611.2, + "languages": [], + "name": "SOLVENT EXTRACTION PROCESS SIMULATOR", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.github.com/solventx/gym-solventx", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SOURCES4D.json b/agency-indexes/DoE/SOURCES4D.json new file mode 100644 index 00000000..3c573487 --- /dev/null +++ b/agency-indexes/DoE/SOURCES4D.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "SOURCES is a code for computing neutron source rates and spectra from spontaneous fission (including delayed neutrons) and (alpha,n) reactions in homogeneous materials and (alpha,n) reactions in single-interface and two-interface geometries. SOURCES is a Los Alamos National Laboratory (LANL) code that is written in FORTRAN and distributed through the Radiation Safety Information Computation Center (RSICC). LANL\u2019s last release of SOURCES to RSICC was SOURCES4C in 2002. This disclosure covers the latest version of SOURCES, SOURCES4D. This version adds sensitivity capabilities for (alpha,n) sources in homogeneous materials. Specifically, SOURCES4D writes new output that can be used to calculate, in post-processing, first and second derivatives of the (alpha,n) source rate density and spectrum with respect to nuclide densities in a homogeneous material and first derivatives of the (alpha,n) source rate density and spectrum with respect to nuclide stopping powers and (alpha,n) cross sections (nuclear data). These derivatives are useful for uncertainty quantification, predictive modeling, and other applications in neutron transport problems.", + "laborHours": 2310.4, + "languages": [], + "name": "SOURCES4D", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SOURCES4D", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SPALLMAP.json b/agency-indexes/DoE/SPALLMAP.json new file mode 100644 index 00000000..062450ce --- /dev/null +++ b/agency-indexes/DoE/SPALLMAP.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Boiler tubes in steam power plants experience exfoliation of oxide grown on the inner side of the tubes. In extreme cases, the exfoliation cause significant tube blockages that lead to forced power plant outages. It is thus desired to predict through modeling the propensity of exfoliation events in order to inform power plant operators of possible tube blockages. SpallMap solves for the stress-strain equations in an axisymmetric geometry, tracking the stress/strain evolution during boiler operation including outages at one-location along a boiler tube and compares it with scale damage criteria represented by Armitt diagram. The SPALLMAP code contains modules developed for oxide growth, stress analysis, and classical fracture mechanics correlations by taking into account the following phenomena and features, (a) Non-uniform thermal expansion coefficient of oxides and metal substrates, (b) Plant operation schedule with periodic alternate full-load and partial-load regimes, (c) axisymmetric formulation for cylindrical tubes, (d) Multiple oxide layers, (e) oxide-growth induced stresses, and (f) damage criteria from classical fracture mechanics. The computer program is written in FORTRAN90. Its modular structure was sought for allowing the best flexibility in updating the program by implementing new constitutive equations due to availability of new material property data and/or new physical phenomena.", + "laborHours": 0.0, + "languages": [ + "Fortran90" + ], + "name": "SPALLMAP", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/adisoft17/spallmap/blob/master/License_SpallMap_OpenSourceSoftware_ORNL.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/adisoft17/spallmap", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SPALLOOP.json b/agency-indexes/DoE/SPALLOOP.json new file mode 100644 index 00000000..d654743b --- /dev/null +++ b/agency-indexes/DoE/SPALLOOP.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "radercd@ornl.gov" + }, + "date": { + "created": "2023-04-24", + "metadataLastUpdated": "2023-04-24" + }, + "description": "Boiler tubes in steam power plants experience tube blockages due to exfoliation of oxide grown on the inner side of the tubes. In extreme cases, significant tube blockages can lead to forced power plant outages. It is thus desired to predict through modeling the amount of tube blockage in order to inform power plant operators of possible forced outages. SpalLoop solves for the stress-strain equations in an axisymmetric geometry, tracking the stress/strain evolution during boiler operation including outages for the entire boiler tube length. At each operational outage, i.e., temperature excursions down to room temperature, the amount of exfoliated area for the entire tube loop is estimated the amount of tube blockage is predicted based assumed blockage geometry and site. The SpaLLoop code contains modules developed for oxide growth, stress analysis, tube loop geometry, blockage area by taking into account the following phenomena and features, (a) Plant operation schedule with periodic alternate full-load and partial-load regimes and shut-downs, i.e., temperature excursions from high-load to room temperature, (b) axisymmetric formulation for cylindrical tubes, (c) oxide growth in a temperature gradient with multiple oxide layers, (d) geometry of a boiler tube with a single tube loop or two tube loops, (e) temperature variation along the tube length based on hot gas temperature distribution outside the tube and inlet steam temperature, (f) non-uniform oxide growth along the tube length according to the local steam tube temperature, (g) exfoliated area module: at each operational outage considered, the amount of exfoliated area and exfoliated volume along the tube is estimated, (h) blockage module: at each operational outage considered, the exfoliated volume/mass for each tube loop is estimated from which the amount of tube blockage is predicted based on given blockage geometry (length, location, and geometry). The computer program is written in FORTRAN90. Its modular structure was sought for allowing the best flexibility in updating the program by implementing new constitutive equations due to availability of new material property data and/or new physical phenomena.", + "laborHours": 0.0, + "languages": [ + "Fortran90" + ], + "name": "SPALLOOP", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/adisoft17/spallop/blob/master/License_Spalloop_OpenSourceSoftware_ORNL.pdf", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/adisoft17/spallop", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SPL:_Solaris_Porting_Layer.json b/agency-indexes/DoE/SPL:_Solaris_Porting_Layer.json new file mode 100644 index 00000000..023fc682 --- /dev/null +++ b/agency-indexes/DoE/SPL:_Solaris_Porting_Layer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-31", + "metadataLastUpdated": "2018-07-31" + }, + "description": "The Solaris Porting Layer, SPL, is a Linux kernel module which provides a compatibility layer used by the\u00a0ZFS on Linux\u00a0project.", + "laborHours": 5213.6, + "languages": [], + "name": "SPL: Solaris Porting Layer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zfsonlinux/spl", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SPPARKS.json b/agency-indexes/DoE/SPPARKS.json new file mode 100644 index 00000000..e438a065 --- /dev/null +++ b/agency-indexes/DoE/SPPARKS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2023-03-15" + }, + "description": "SPPARKS is a kinetic Monte Carlo (KMC) code designed to run efficiently on parallel computers using both KMC and Metropolis Monte Carlo algorithms.", + "laborHours": 25703.2, + "languages": [], + "name": "SPPARKS", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/SPPARKS", + "status": "Development", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SPRFSim.json b/agency-indexes/DoE/SPRFSim.json new file mode 100644 index 00000000..522b0c14 --- /dev/null +++ b/agency-indexes/DoE/SPRFSim.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-11" + }, + "description": "SPRFSim is a code that performs RF/Beam interaction simulations for an ion LINAC. The input files can be constructed from scratch or parsed from PARMELA or TraceWin simulations. The code is written in Python, and relies on matplotlib and numpy. ", + "laborHours": 364.8, + "languages": [ + "Python" + ], + "name": "SPRFSim", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeinstei/SPRFSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SPRNG_Scalable_Parallel_Random_Number_Generator_LIbrary.json b/agency-indexes/DoE/SPRNG_Scalable_Parallel_Random_Number_Generator_LIbrary.json new file mode 100644 index 00000000..8ca16272 --- /dev/null +++ b/agency-indexes/DoE/SPRNG_Scalable_Parallel_Random_Number_Generator_LIbrary.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This revision corrects some errors in SPRNG 1. Users of newer SPRNG versions can obtain the corrected files and build their version with it. This version also improves the scalability of some of the application-based tests in the SPRNG test suite. It also includes an interface to a parallel Mersenne Twister, so that if users install the Mersenne Twister, then they can test this generator with the SPRNG test suite and also use some SPRNG features with that generator.", + "homepageURL": "http://www.sprng.org", + "laborHours": 0.0, + "name": "SPRNG Scalable Parallel Random Number Generator LIbrary", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://creativecommons.org/licenses/by-nc-sa/4.0", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.sprng.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SSCA1-K1.json b/agency-indexes/DoE/SSCA1-K1.json new file mode 100644 index 00000000..3665b1f8 --- /dev/null +++ b/agency-indexes/DoE/SSCA1-K1.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SSCA1-K1 is a parallel implementation of kernel 1 of the SSCA1 benchmark suite released by the DARPA HPCS program. This kernel is able to run in parallel on a distributed shared memory system at extreme scales using OpenSHMEM.", + "laborHours": 775.2, + "name": "SSCA1-K1", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/MattBBaker/ssca1", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SSGUI_v1.0.json b/agency-indexes/DoE/SSGUI_v1.0.json new file mode 100644 index 00000000..ae94001a --- /dev/null +++ b/agency-indexes/DoE/SSGUI_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-09-28", + "metadataLastUpdated": "2023-09-28" + }, + "description": "SSGUI is a web-based application that integrates the integrative genomics browser (IGV) with upstream alignment pipelines enabling rapid analysis of a batch of next-generation sequencing (NGS) samples. The input to SSGUI is an NGS file system directory that is organized by experiment and reference sequence. The output is an online dashboard containing various sequencing statistics for each sample and an integrated IGV plugin enabling rapid analysis of aligned NGS reads.", + "laborHours": 0.0, + "languages": [], + "name": "SSGUI v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/ssgui", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SSG__Scalable_Service_Groups_.json b/agency-indexes/DoE/SSG__Scalable_Service_Groups_.json new file mode 100644 index 00000000..ddb4f284 --- /dev/null +++ b/agency-indexes/DoE/SSG__Scalable_Service_Groups_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "SSG is a group membership microservice based on the Mercury RPC system. It provides mechanisms for bootstrapping sets of Mercury processes into logical groups and for managing the membership of these process groups over time. At a high-level, each group collectively maintains a group view, which is just a mapping from group member identifiers to Mercury address information. The initial group membership view is specified completely when the group is bootstrapped (created).", + "laborHours": 0.0, + "languages": [], + "name": "SSG (Scalable Service Groups)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-ssg/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-ssg", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SSHSpawner.json b/agency-indexes/DoE/SSHSpawner.json new file mode 100644 index 00000000..c2c5f03c --- /dev/null +++ b/agency-indexes/DoE/SSHSpawner.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-02", + "metadataLastUpdated": "2019-05-02" + }, + "description": "Extends the JupyterHub LocalProcessSpawner to instead launch notebooks on a remote host (e.g. a login node).", + "laborHours": 243.2, + "languages": [], + "name": "SSHSpawner", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SSHSpawner", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SSH_Proxy__sshproxy__v1.0.json b/agency-indexes/DoE/SSH_Proxy__sshproxy__v1.0.json new file mode 100644 index 00000000..2ad55d9b --- /dev/null +++ b/agency-indexes/DoE/SSH_Proxy__sshproxy__v1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-05-09", + "metadataLastUpdated": "2021-06-15" + }, + "description": "SSHProxy is a service that generates and manages ssh keys. This service can be used to allow a user to create an sshkey and then use that for a period of time defined by a configuration file. The service also supports custom \"scopes\" that can be used to allow longer lived keys under certain conditions. The service also supports using SSH certificates for signing the keys.", + "laborHours": 0.0, + "languages": [], + "name": "SSH Proxy (sshproxy) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nersc/sshproxy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SSLearningPipeLine.json b/agency-indexes/DoE/SSLearningPipeLine.json new file mode 100644 index 00000000..a632937f --- /dev/null +++ b/agency-indexes/DoE/SSLearningPipeLine.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-07", + "metadataLastUpdated": "2022-09-07" + }, + "description": "Script that provides the basic functionality for labeling user data data by crawling through an image directory, displaying the image to the user, and then saving the inputted label in an output directory.", + "laborHours": 0.0, + "languages": [], + "name": "SSLearningPipeLine", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/SSLearningPipeLine/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/SSLearningPipeLine", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SSRS__Stochastic_Soaring_Raptor_Simulator_.json b/agency-indexes/DoE/SSRS__Stochastic_Soaring_Raptor_Simulator_.json new file mode 100644 index 00000000..a0d8d038 --- /dev/null +++ b/agency-indexes/DoE/SSRS__Stochastic_Soaring_Raptor_Simulator_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "charles.tripp@nrel.gov" + }, + "date": { + "created": "2021-09-03", + "metadataLastUpdated": "2021-11-30" + }, + "description": "SSRS (Stochastic Soaring Raptor Simulator) is a generalizable, probabilistic, and predictive tool for wind energy developers, ecologists, wildlife managers and industry consultants to estimate the potential for soaring raptors to interact with operating wind turbines, without the need for site-specific data collection. Rapid expansion of wind energy development across the world has exposed the risk of turbine collisions for birds and bats. The risk to obligate soaring raptors such as golden eagles is of particular concern due to their small population and influence on ecological balance. Golden eagles rely heavily on updrafts to subsidize their flight, putting them in direct conflict with operational wind turbines that utilize the same wind resource. Understanding the behavior of soaring raptors with varying atmospheric conditions is crucial for predicting and mitigating the risk of turbine collision. This software contains a predictive movement model that simulates individual flight paths of golden eagles during updraft-subsidized long-distance flight, including migration. For a given set of atmospheric conditions, the model simulates thousands of eagles at turbine-scale spatial resolution (50m) to produce a relative presence density map. The simulated eagles rely on updrafts to pursue uninterrupted directional flight with minimal energy expenditure, following fluid-flow principles. The simulator includes a stochastic model of eagle behavior and a systematic method of accounting for spatiotemporal variations in atmospheric conditions. This framework only requires publicly available atmospheric data to estimate orographic and thermal updrafts, ensuring general usability.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SSRS (Stochastic Soaring Raptor Simulator)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SSRS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/STAR.json b/agency-indexes/DoE/STAR.json new file mode 100644 index 00000000..ecd59317 --- /dev/null +++ b/agency-indexes/DoE/STAR.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-13" + }, + "description": "Structured Threat Automated Response (STAR) is a script that creates a python run-time for automated response action included in the Structure Threat Information Expression (STIX) Course of Action object. This script can parse a valid STIX json file and execute the included Course of Action.", + "laborHours": 76.0, + "languages": [ + "Python" + ], + "name": "STAR", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/STAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/STAYSL_PNNL_Suite.json b/agency-indexes/DoE/STAYSL_PNNL_Suite.json new file mode 100644 index 00000000..68b03b6b --- /dev/null +++ b/agency-indexes/DoE/STAYSL_PNNL_Suite.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "This announcement is for the \"STAYSL PNNL Suite\" software developed by Pacific Northwest National Laboratory (PNNL).", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "STAYSL PNNL Suite", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/STELLOPT.json b/agency-indexes/DoE/STELLOPT.json new file mode 100644 index 00000000..147d2e68 --- /dev/null +++ b/agency-indexes/DoE/STELLOPT.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "czhu@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2020-05-07" + }, + "description": "The STELLOPT code is designed to optimize 3D MHD equilibria to a set of target physics parameters encompassing stellarator design and 3D equilibrium reconstructions.", + "laborHours": 173812.0, + "languages": [ + "Fortran" + ], + "name": "STELLOPT", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PrincetonUniversity/STELLOPT", + "status": "Production", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "vcs": "git", + "version": "2.7.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/STEMDL.json b/agency-indexes/DoE/STEMDL.json new file mode 100644 index 00000000..2dc840f0 --- /dev/null +++ b/agency-indexes/DoE/STEMDL.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The code \"STEMDL\" provides highly-optimized multi-gpu implementations of DL models of applicability in electron microscopy via the use of mixed-precision arithmetic, native graph construction and evaluation in Tensorflow, and adaptive scaling of learning parameters to avoid numerical instabilities due to reduced precision. STEMDL also uses low-level methods from the Horovod library for gradient communication and reduction and adds an additional optimization by allowing the user to scheduling the gradient reduction operations based on their position within the layers of a neural net. STEMDL provides optimized I/O routines for data staging and data reading/writing in both Tensorflow and Pytorch using multi-processing and asynchronous transfer between host and device.\r\n.", + "laborHours": 147014.4, + "languages": [ + "Python 2.7/3.x" + ], + "name": "STEMDL", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/disMultiABM/stemdl", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/STIG.json b/agency-indexes/DoE/STIG.json new file mode 100644 index 00000000..c56f2f1e --- /dev/null +++ b/agency-indexes/DoE/STIG.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2019-05-13", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Structured Threat Intelligence Graph", + "laborHours": 6064.8, + "languages": [], + "name": "STIG", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLab/STIG", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/STJ_PV:_Subtropical_Jet_Finding_Framework.json b/agency-indexes/DoE/STJ_PV:_Subtropical_Jet_Finding_Framework.json new file mode 100644 index 00000000..f6784ce7 --- /dev/null +++ b/agency-indexes/DoE/STJ_PV:_Subtropical_Jet_Finding_Framework.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "kelleherme@ornl.gov" + }, + "date": { + "created": "2019-10-10", + "metadataLastUpdated": "2019-11-06" + }, + "description": "This software provides a framework for comparing different methods of finding the subtropical jet.\n\nIncluded in these is a new method for locating the subtropical jet. The tropopause gradient method uses the peak gradient in potential temperature along the dynamic tropopause to locate the subtropical jet.", + "laborHours": 2736.0, + "languages": [ + "Python" + ], + "name": "STJ_PV: Subtropical Jet Finding Framework", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mkstratos/stj_pv", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/STOMP-W.json b/agency-indexes/DoE/STOMP-W.json new file mode 100644 index 00000000..65ce0234 --- /dev/null +++ b/agency-indexes/DoE/STOMP-W.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Fortran 90 source code, example problems, and output conversion scripts for the STOMP-W simulator.\u00a0STOMP-W is a numerical simulator written in Fortran 90 for solving problems involving fluid flow and solute/species transport in variably saturated geologic media. The zipped file contains five directories: 1) src (the source code), 2) scripts (output conversion scripts written in perl, 3) prb-w-1 (example problem 1), 4) prb-w-2 (example problem 2), and 5) prb-w-3 (example problem 3). After downloading and unzipping the file, the user must create an executable from the files stored in the src directory. Generic instructions for compiling the source code is shown below as a UNIX/Linux command line, with f90 representing the user's Fortran 90 compiler.", + "laborHours": 73735.2, + "languages": [], + "name": "STOMP-W", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/STOMP-W", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/STOMPX.json b/agency-indexes/DoE/STOMPX.json new file mode 100644 index 00000000..abe17f30 --- /dev/null +++ b/agency-indexes/DoE/STOMPX.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-10-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "STOMPX is an OpenMPI implementation of selected operational modes of the Subsurface Transport Over Multiple Phases\nnumerical simulator. STOMPX is designed to execute with both shared- and distributed-memory computer architectures.\nThis implementation of the simulator is designed to solve the same problems as the STOMP simulator, but taking\nadvantage of multiple processor execution through the OpenMPI language and libraries. The STOMP simulator is written in\nFortran 90 and operates on single processors or shared-memory computer architectures. The STOMPX simulator extends\nexecution to distributed-memory computer architectures, including super computers", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "STOMPX", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/STPPHAWKES.json b/agency-indexes/DoE/STPPHAWKES.json new file mode 100644 index 00000000..cbf7aaaa --- /dev/null +++ b/agency-indexes/DoE/STPPHAWKES.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08541O\nSTTPHAWKES software solution is a Bayesian estimation approach to a Hawkes process model that treats missing data as a latent variable in the estimation. The open-source software will be released to the R CRAN repository and Sandia National Labs\u2019 Github.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 3526.4, + "languages": [ + "R", + "C++" + ], + "name": "STPPHAWKES", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/stpphawkes", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/STREAM:_Strategic_Technology_Roadmapping_and_Energy,_Environmental,_and_Economic_Analysis_Model.json b/agency-indexes/DoE/STREAM:_Strategic_Technology_Roadmapping_and_Energy,_Environmental,_and_Economic_Analysis_Model.json new file mode 100644 index 00000000..5eda2312 --- /dev/null +++ b/agency-indexes/DoE/STREAM:_Strategic_Technology_Roadmapping_and_Energy,_Environmental,_and_Economic_Analysis_Model.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-17", + "metadataLastUpdated": "2025-01-09" + }, + "description": "This is the implementation of the framework for the planning of the technological makeup of the industrial sector.\nMotivated by the efforts to achieve carbon neutrality, the model of this framework modifies the portfolio of technologies over time for the sector of interest such that,\n- Net Present Value (NPV) is minimized\n- Constraint on Greenhouse Emissions (GHG), e.g. carbon dioxide, is satisfied\n- Demand of the underlying commodity is satisfied\n- The current implementation reflects a case study for the electric power sector.\nThe for a given initial set of capacities of different vintages, the space of decisions include,\n- Retirement of the existing capacities.\n- Retrofitting the existing capacities to alternative characteristics.\n- Creation of new capacities from a technology portfolio.\nAll the associated quantities with the deployments, e.g. CO2, heat requirement, etc.", + "laborHours": 2690.4, + "languages": [], + "name": "STREAM: Strategic Technology Roadmapping and Energy, Environmental, and Economic Analysis Model", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-CEEESA/dre4m", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/STREAMM-tools-tests.json b/agency-indexes/DoE/STREAMM-tools-tests.json new file mode 100644 index 00000000..ec44847d --- /dev/null +++ b/agency-indexes/DoE/STREAMM-tools-tests.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "Testing suite for the STREAMM-tools source code. In-depth documentation can be found at\u00a0STREAMM website.", + "laborHours": 988.0, + "languages": [], + "name": "STREAMM-tools-tests", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/streamm-tools-tests", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/STREAMM-tools__Simulation_Toolkit_for_Renewable_Energy_Advanced_Materials_Modeling__[SWR-15-29].json b/agency-indexes/DoE/STREAMM-tools__Simulation_Toolkit_for_Renewable_Energy_Advanced_Materials_Modeling__[SWR-15-29].json new file mode 100644 index 00000000..7676e712 --- /dev/null +++ b/agency-indexes/DoE/STREAMM-tools__Simulation_Toolkit_for_Renewable_Energy_Advanced_Materials_Modeling__[SWR-15-29].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-06" + }, + "description": "The Simulation Toolkit for Renewable Energy and Advanced Materials Modeling (STREAMM) is a python package that generates structures and input files for quantum chemical and molecular dynamics codes. STREAMM does not directly conduct simulations rather it is meant to drive quantum chemical and molecular dynamics codes to allow for high-throughput computational analysis of materials. The STREAMM package is written for python2.7 (https://www.python.org/download/releases/2.7/) and incorporates some of the core modules from the pymatgen (http://pymatgen.org/) code.", + "laborHours": 12205.6, + "languages": [ + "Python" + ], + "name": "STREAMM-tools (Simulation Toolkit for Renewable Energy Advanced Materials Modeling) [SWR-15-29]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/streamm-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/STRUMPACK.json b/agency-indexes/DoE/STRUMPACK.json new file mode 100644 index 00000000..1cb44f02 --- /dev/null +++ b/agency-indexes/DoE/STRUMPACK.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "STRUMPACK - STRUctured Matrix PACKage - is a software library providing linear algebra routines for sparse matrices and for dense rank-structured matrices, i.e., matrices that exhibit some kind of low-rank property. In particular, STRUMPACK uses the Hierarchically Semi-Separable matrix format (HSS). Such matrices appear in many applications, e.g., Finite Element Methods, Boundary Element Methods ... In sparse matrix factorization, the fill-in in the triangular factors often has a low-rank structure. Hence, the sparse linear solve in STRUMPACK exploits the HSS matrix format to compress the fill-in. Exploiting this structure using a compression algorithm allows for fast solution of linear systems and/or fast computation of matrix-vector products, which are two of the main building blocks of matrix computations. STRUMPACK has two main components: a distributed-memory dense matrix computations package (for dense matrices that have the HSS structure) and a distributed memory fully algebraic sparse general solver and preconditioner. The preconditioner is mostly aimed at large sparse linear systems which result from the discretization of a partial differential equation, but is not limited to any particular type of problem. STRUMPACK also provides preconditioned GMRES and BiCGStab iterative solvers.", + "laborHours": 60906.4, + "languages": [], + "name": "STRUMPACK", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pghysels/STRUMPACK/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pghysels/STRUMPACK", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/STUCCO.json b/agency-indexes/DoE/STUCCO.json new file mode 100644 index 00000000..cc545f90 --- /dev/null +++ b/agency-indexes/DoE/STUCCO.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-05-04" + }, + "description": "STUCCO will be a scalable visual analytics solution that identifies and collects endogenous and exogenous data from data sources not traditionally associated with cyber security to enable both the identification of relevant, non-security data with cyber security event data and the display of an overview of global security threats.", + "homepageURL": "https://stucco.github.io", + "laborHours": 0.0, + "languages": [ + "Node.js 0.6 or higher" + ], + "name": "STUCCO", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/stucco/stucco.github.io/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://stucco.github.io", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/STreCH.json b/agency-indexes/DoE/STreCH.json new file mode 100644 index 00000000..5524e4c0 --- /dev/null +++ b/agency-indexes/DoE/STreCH.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "Symbolic regression software that formulates a symbolic regression problem as a mixed-integer nonlinear optimization problem, and solves it using a sequential tree construction heuristic", + "laborHours": 0.0, + "languages": [], + "name": "STreCH", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jongeunkim/STreCH", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SUNDIALS.json b/agency-indexes/DoE/SUNDIALS.json new file mode 100644 index 00000000..41a2e9e0 --- /dev/null +++ b/agency-indexes/DoE/SUNDIALS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2020-06-01" + }, + "description": "The SUite of Nonlinear and DIfferential/ALgebraic equation Solvers was implemented with the goal of providing robust time integrators and nonlinear solvers that can easily be incorporated into existing simulation codes. The primary design goals were to require minimal information from the user, allow users to easily supply their own data structures underneath the solvers, and allow for easy incorporation of user-supplied linear solvers and preconditioners. ", + "laborHours": 213088.8, + "languages": [], + "name": "SUNDIALS", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SUNDIALS_CVODE.json b/agency-indexes/DoE/SUNDIALS_CVODE.json new file mode 100644 index 00000000..4ac1b6e8 --- /dev/null +++ b/agency-indexes/DoE/SUNDIALS_CVODE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "CVODE solves initial value problems for ordinary differential equation (ODE) systems. Part of the SUNDIALS SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. ", + "laborHours": 213088.8, + "languages": [], + "name": "SUNDIALS/CVODE", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SUNDIALS_CVODES.json b/agency-indexes/DoE/SUNDIALS_CVODES.json new file mode 100644 index 00000000..bca198be --- /dev/null +++ b/agency-indexes/DoE/SUNDIALS_CVODES.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "CVODES solves ordinary differential equation (ODE) systems and includes sensitivity analysis capabilities (forward and adjoint). Part of the SUNDIALS SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. ", + "laborHours": 213088.8, + "languages": [], + "name": "SUNDIALS/CVODES", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SUNDIALS_IDA.json b/agency-indexes/DoE/SUNDIALS_IDA.json new file mode 100644 index 00000000..617813ca --- /dev/null +++ b/agency-indexes/DoE/SUNDIALS_IDA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-10" + }, + "description": "IDA solves initial value problems for differential-algebraic equation (DAE) systems. Part of the SUNDIALS SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. ", + "laborHours": 213088.8, + "languages": [], + "name": "SUNDIALS/IDA", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/sundials/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sundials", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SUPESv.4.1.2.json b/agency-indexes/DoE/SUPESv.4.1.2.json new file mode 100644 index 00000000..c51e21fa --- /dev/null +++ b/agency-indexes/DoE/SUPESv.4.1.2.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "SUPES is a collection of subprograms that perform frequently used non-numerical services for the engineering applications programmer. The three functional categories of SUPES are: (1) input command parsing, (2) dynamic memory management, and (3) system dependent utilities. The subprograms in categories one and two are written in standard FORTRAN-77, while the subprograms in category three are written provide a standardized FORTRAN interface to several system dependent features.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "SUPESv.4.1.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "4.1.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SVDI_Ver._1.1.json b/agency-indexes/DoE/SVDI_Ver._1.1.json new file mode 100644 index 00000000..336fd058 --- /dev/null +++ b/agency-indexes/DoE/SVDI_Ver._1.1.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "SVDI is the Sandia Virtual Device Interface library which is an internal library used by SEAMS codes (blot and fastq) to provide graphics to multiple device types; primarily X11R6 clients.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "SVDI Ver. 1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SW4_Curvilinear_Kernels.json b/agency-indexes/DoE/SW4_Curvilinear_Kernels.json new file mode 100644 index 00000000..07fbb5c9 --- /dev/null +++ b/agency-indexes/DoE/SW4_Curvilinear_Kernels.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-06-03", + "metadataLastUpdated": "2021-06-04" + }, + "description": "Five computationally expensive stencil evaluation routines from SW4(https://github.com/geodynamics/sw4 GPL license) have been extracted and packaged with a driver to create a mini-app for evaluating compiler and GPU performance. The kernels can executed on AMD and Nvidia GPUs with and without RAJA. The kernel driver generates synthetic inputs, checks for correctness and measures kernel run times. ", + "laborHours": 0.0, + "languages": [], + "name": "SW4 Curvilinear Kernels", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SW4CK", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SWQM:_Source_Water_Quality_Modeling_Software.json b/agency-indexes/DoE/SWQM:_Source_Water_Quality_Modeling_Software.json new file mode 100644 index 00000000..f6d35410 --- /dev/null +++ b/agency-indexes/DoE/SWQM:_Source_Water_Quality_Modeling_Software.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The Source Water Quality Modeling software (SWQM) simulates the water quality conditions that reflect properties of water generated by water treatment facilities. SWQM consists of a set of Matlab scripts that model the statistical variation that is expected in a water treatment facility's water, such as pH and chlorine levels.", + "homepageURL": "https://software.sandia.gov/trac/canary/downloader/download/category/10", + "laborHours": 0.0, + "name": "SWQM: Source Water Quality Modeling Software", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://software.sandia.gov/trac/canary/downloader/download/category/10", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://software.sandia.gov/trac/canary/downloader/download/category/10", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SWTools.json b/agency-indexes/DoE/SWTools.json new file mode 100644 index 00000000..8df98141 --- /dev/null +++ b/agency-indexes/DoE/SWTools.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The SWTools code is an infrastructure to facilitate the management of third-party software installations. SWTools is infrastructure code that works with user-supplied build and test scripts resulting in a mostly-automated software build and test framework. The framework tries to simplify the work required to deal with upgrades, whether they be compiler, operating system, or application upgrades. The code also automates the collection of as much reporting data as possible including user-facing web pages. Inventory and user documentation will be kept up to date dynamically; that is, the same documentation that the installer writes for local users of the system will be made available online, and all web based inventory information will be dynamically updated.", + "homepageURL": "https://www.olcf.ornl.gov/center-projects/swtools", + "laborHours": 0.0, + "languages": [ + "Python 2.5 or Korn shell script" + ], + "name": "SWTools", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.olcf.ornl.gov/center-projects/swtools", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.olcf.ornl.gov/center-projects/swtools", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SWinzip_v._2.0.json b/agency-indexes/DoE/SWinzip_v._2.0.json new file mode 100644 index 00000000..700b7101 --- /dev/null +++ b/agency-indexes/DoE/SWinzip_v._2.0.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2024-08-07" + }, + "description": "SWinzip is a Matlab and C++ library for scientific lossy data compression and reconstruction using compressed sensing and tree-wavelets transforms. These methods are known for their large compression and usefulness in data analytics such as features extraction. Compressed sensing and wavelets methods rely heavily on sparse and dense linear algebra operations implemented through the Boost codes in our library. SWinzip accommodates data represented on both regular grids (e.g. image data) and point-clouds (e.g. unstructured meshes).\n\nIn SWinzip v2.0, there is more focus on wavelet compression and the following\nfeatures are added:\n\n- The matrix-free (direct) wavelet transform is implemented in both C++ and Matlab. A threshold-based compression can now be used. Examples for distributed compression are also added.\n- Python implementation of Alpert wavelet transforms\n- Field data comparison using wavelets in Matlab with global and local metrics", + "laborHours": 13740.8, + "languages": [ + "C++", + "C", + "MATLAB", + "Makefile", + "Python" + ], + "name": "SWinzip v. 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SWinzip", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SYNTH_-_Gamma_Ray_Spectrum_Synthesizer.json b/agency-indexes/DoE/SYNTH_-_Gamma_Ray_Spectrum_Synthesizer.json new file mode 100644 index 00000000..2a9daac5 --- /dev/null +++ b/agency-indexes/DoE/SYNTH_-_Gamma_Ray_Spectrum_Synthesizer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "SYNTH was designed to synthesize the results of typical gamma-ray spectroscopy experiments. The code allows a user to specify the physical characteristics of a gamma-ray source, the quantity of radionuclides emitting gamma radiation, the source-to-detector distance and the presence and type of any intervening absorbers, the size and type of the gamma-ray detector, and the electronic set-up used to gather the data.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "SYNTH - Gamma Ray Spectrum Synthesizer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SZ:_Error-bounded_Lossy_Compressor_for_HPC_Data.json b/agency-indexes/DoE/SZ:_Error-bounded_Lossy_Compressor_for_HPC_Data.json new file mode 100644 index 00000000..15cea0db --- /dev/null +++ b/agency-indexes/DoE/SZ:_Error-bounded_Lossy_Compressor_for_HPC_Data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "Error-bounded Lossy Data Compressor (for floating-point/integer datasets).", + "laborHours": 115550.4, + "languages": [], + "name": "SZ: Error-bounded Lossy Compressor for HPC Data", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/disheng222/SZ/blob/master/copyright-and-BSD-license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/disheng222/SZ", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sabin-to-Mahoney_Transition_Model_of_Quasispecies_Replication.json b/agency-indexes/DoE/Sabin-to-Mahoney_Transition_Model_of_Quasispecies_Replication.json new file mode 100644 index 00000000..9e5961b9 --- /dev/null +++ b/agency-indexes/DoE/Sabin-to-Mahoney_Transition_Model_of_Quasispecies_Replication.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Qspp is an agent-based stochastic simulation model of the Poliovirus Sabin-to-Mahoney transition. This code simulates a cell-to-cell model of Poliovirus replication. The model tracks genotypes (virus genomes) as they are replicated in cells, and as the cells burst and release particles into the medium of a culture dish. An inoculum is then taken from the pool of virions and is used to inoculate cells on a new dish. This process repeats. The Sabin genotype comprises the initial inoculum. Nucleotide positions that match the Sabin1 (vaccine strain) and Mahoney (wild type) genotypes, as well as the neurovirulent phenotype (from the literature) are enumerated as constants.", + "laborHours": 1915.2, + "name": "Sabin-to-Mahoney Transition Model of Quasispecies Replication", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/carolzhou/Virus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sabot.json b/agency-indexes/DoE/Sabot.json new file mode 100644 index 00000000..0cac110e --- /dev/null +++ b/agency-indexes/DoE/Sabot.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Sabot is a quantum state simulator with a client-server architecture. This makes possible distributed simulations with many clients accessing a single instance of the simulator. This design is useful when more than one client wishes to access one quantum state. This occurs during quantum communication, for example. It is also possible to have users running on personal machines with the simulator running on a much more powerful machine.\n", + "laborHours": 1900.0, + "name": "Sabot", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/sabot", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Safety_Risk_Reliability_Model_Library.json b/agency-indexes/DoE/Safety_Risk_Reliability_Model_Library.json new file mode 100644 index 00000000..b7338d3b --- /dev/null +++ b/agency-indexes/DoE/Safety_Risk_Reliability_Model_Library.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-01-19", + "metadataLastUpdated": "2023-03-13" + }, + "description": "SR2ML is a software package which contains a set of safety and reliability models designed to be interfaced with the INL developed RAVEN code. These models can be employed to perform both static and dynamic system risk analysis and determine risk importance of specific elements of the considered system. Two classes of reliability models have been developed; the first class includes all classical reliability models (Fault-Trees, Event-Trees, Markov models and Reliability Block Diagrams) which have been extended to deal not only with Boolean logic values but also time dependent values. The second class includes several components aging models. Models of these two classes are designed to be included in a RAVEN ensemble model to perform time dependent system reliability analysis (dynamic analysis). Similarly, these models can be interfaced with system analysis codes to determine failure time of systems and evaluate accident progression (static analysis).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Safety Risk Reliability Model Library", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/SR2ML", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sage:_Parallel_Semi-Asymmetric_Graph_Algorithms_for_NVRAMs.json b/agency-indexes/DoE/Sage:_Parallel_Semi-Asymmetric_Graph_Algorithms_for_NVRAMs.json new file mode 100644 index 00000000..995e53ff --- /dev/null +++ b/agency-indexes/DoE/Sage:_Parallel_Semi-Asymmetric_Graph_Algorithms_for_NVRAMs.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-11" + }, + "description": "Source code for paper (https://github.com/ParAlg/gbbs/tree/semi_asymmetric): \n\nLaxman Dhulipala, Charles McGuffey, Hongbo Kang, Yan Gu, Guy Blelloch, Phillip Gibbons, and Julian Shun.\nSage: Parallel Semi-Asymmetric Graph Algorithms for NVRAMs.\nProceedings of the VLDB Endowment, 13(9), pp. 1598-1613, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "Sage: Parallel Semi-Asymmetric Graph Algorithms for NVRAMs", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Saleae_Logic_2_Output_File_Parser.json b/agency-indexes/DoE/Saleae_Logic_2_Output_File_Parser.json new file mode 100644 index 00000000..7ba9df31 --- /dev/null +++ b/agency-indexes/DoE/Saleae_Logic_2_Output_File_Parser.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-07-18", + "metadataLastUpdated": "2023-07-18" + }, + "description": "A Python script that parsers Saleae Logic 2 output files into useful data sets.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Saleae Logic 2 Output File Parser", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Saleae_Output_Parser", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Saline.json b/agency-indexes/DoE/Saline.json new file mode 100644 index 00000000..56527ffe --- /dev/null +++ b/agency-indexes/DoE/Saline.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "hendersonsc@ornl.gov" + }, + "date": { + "created": "2022-03-14", + "metadataLastUpdated": "2022-03-21" + }, + "description": "Saline is an Application Programming Interface (API) which provides a useful quality assured interface to data from thermo-physical property data models.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Saline", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/neams/saline", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SalineMoose.json b/agency-indexes/DoE/SalineMoose.json new file mode 100644 index 00000000..104a0e33 --- /dev/null +++ b/agency-indexes/DoE/SalineMoose.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "salkork@ornl.gov" + }, + "date": { + "created": "2022-11-08", + "metadataLastUpdated": "2022-11-08" + }, + "description": "SalineMoose is a MOOSE wrapper for the open-source Saline code, which is an interface for fluid property databsae files. This code is meant to provide access to Saline, which can easily be integrated into MOOSE-based codes that need access to the fluid thermophysical properties that Saline can provide. Wrapping Saline in SalineMoose allows MOOSE codes to use the native MOOSE build system for linking Saline to their MOOSE application.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "SalineMoose", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/neams/saline_moose/-/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/neams/saline_moose", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Saloon.json b/agency-indexes/DoE/Saloon.json new file mode 100644 index 00000000..34f8f670 --- /dev/null +++ b/agency-indexes/DoE/Saloon.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-24", + "metadataLastUpdated": "2021-02-24" + }, + "description": "Saloon is a Vim plugin that simplifies Python code linter / fixer configuration and usage.\nSaloon's menu lets developers toggle which static analysis tools to use and delegates those changes to\nALE's (Asynchronous Lint Engine) API. Since prospector (python linter aggregate) already handles multiple tools, and is integrated with ALE, most of the actual linting will initially be handled via prospector calls.", + "laborHours": 0.0, + "languages": [], + "name": "Saloon", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Saloon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SaltAtlas.json b/agency-indexes/DoE/SaltAtlas.json new file mode 100644 index 00000000..73a390ef --- /dev/null +++ b/agency-indexes/DoE/SaltAtlas.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-01", + "metadataLastUpdated": "2023-03-01" + }, + "description": "An HPC library for distributed nearest neighbor tools based on LLNL-developed distributed communication and graph processing frameworks.", + "laborHours": 0.0, + "languages": [], + "name": "SaltAtlas", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/saltatlas", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SampleService.json b/agency-indexes/DoE/SampleService.json new file mode 100644 index 00000000..fc9493f4 --- /dev/null +++ b/agency-indexes/DoE/SampleService.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "Service for creating, modifying, and retrieving samples. The Sample Service stores information regarding experimental samples taken from the environment. It supports Access Control Lists for each sample, subsample trees, and modular metadata validation.", + "laborHours": 14151.2, + "languages": [], + "name": "SampleService", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/sample_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Sample_Code_for_\"An_automated_approach_to_the_alignment_of_compound_refractive_lenses\".json" "b/agency-indexes/DoE/Sample_Code_for_\"An_automated_approach_to_the_alignment_of_compound_refractive_lenses\".json" new file mode 100644 index 00000000..e1a2931d --- /dev/null +++ "b/agency-indexes/DoE/Sample_Code_for_\"An_automated_approach_to_the_alignment_of_compound_refractive_lenses\".json" @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "burnsrl1@nv.doe.gov" + }, + "date": { + "created": "2022-02-10", + "metadataLastUpdated": "2022-02-10" + }, + "description": "This sample code is intended to be publicly released on DOECODE. It is an accompaniment to \"n automated approach to the alignment of compoundrefractive lenses\". It's two small, mostly self-contained scripts that include the complete details necessary to implement the to-be published article's algorithm at a scientific beamline.", + "laborHours": 0.0, + "languages": [], + "name": "Sample Code for \"An automated approach to the alignment of compound refractive lenses\"", + "organization": "Nevada National Security Site/Mission Support and Test Services LLC (MSTS)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/BurnsRL1/doe-nv-03624-1278", + "status": "Production", + "tags": [ + "DOE CODE", + "Nevada National Security Site/Mission Support and Test Services LLC (MSTS)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia's_Current_Energy_Conversion_module_for_Flexible-Mesh_Delft3D_flow_solver_v._1.0.json b/agency-indexes/DoE/Sandia's_Current_Energy_Conversion_module_for_Flexible-Mesh_Delft3D_flow_solver_v._1.0.json new file mode 100644 index 00000000..19b7268f --- /dev/null +++ b/agency-indexes/DoE/Sandia's_Current_Energy_Conversion_module_for_Flexible-Mesh_Delft3D_flow_solver_v._1.0.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-10", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The DOE has funded Sandia National Labs (SNL) to develop an open-source modeling tool to guide the design and layout of marine hydrokinetic (MHK) arrays to maximize power production while minimizing environmental effects. This modeling framework simulates flows through and around a MHK arrays while quantifying environmental responses. As an augmented version of the Dutch company, Deltares\u2019s, environmental hydrodynamics code, Delft3D, SNL-Delft3D-CEC-FM includes a new module that simulates energy conversion (momentum withdrawal) by MHK current energy conversion devices with commensurate changes in the turbulent kinetic energy and its dissipation rate. SNL-Delft3D-CEC-FM modified the Delft3D flexible mesh flow solver, DFlowFM. The Following is a description of Deltares\u2019s open-source code Delft3D from which Delft3D-CEC is built upon. \u201cDelft3D is a world leading 3D modeling suite to investigate hydrodynamics, sediment transport and morphology and water quality for fluvial, estuarine and coastal environments. As per 1 January 2011, the Delft3D flow (FLOW), morphology (MOR) and waves (WAVE) modules are available in open source. The software is used and has proven his capabilities on many places around the world, like the Netherlands, USA, Hong Kong, Singapore, Australia, Venice, etc. The software is continuously improved and developed with innovating advanced modelling techniques as consequence of the research work of our institute and to stay world leading. The FLOW module is the heart of Delft3D and is a multi-dimensional (2D or 3D) hydrodynamic (and transport) simulation program which calculates non-steady flow and transport phenomena resulting from tidal and meteorological forcing on a curvilinear, boundary fitted grid or spherical coordinates. In 3D simulations, the vertical grid is defined following the so-called sigma coordinate approach or Z-layer approach. The MOR module computes sediment transport (both suspended and bed total load) and morphological changes for an arbitrary number of cohesive and non-cohesive fractions. Both currents and waves act as driving forces and a wide variety of transport formulae have been incorporated. For the suspended load this module connects to the 2D or 3D advection-diffusion solver of the FLOW module; density effects may be taken into account. An essential feature of the MOR module is the dynamic feedback with the FLOW and WAVE modules, which allow the flows and waves to adjust themselves to the local bathymetry and allows for simulations on any time scale from days (storm impact) to centuries (system dynamics). It can keep track of the bed composition to build up a stratigraphic record. The MOR module may be extended to include extensive features to simulate dredging and dumping scenarios. For over 30 years Deltares has been in the forefront of these types of combined morphological simulation techniques.\u201d", + "laborHours": 1149545.6, + "languages": [ + "Fortran", + "C++", + "Shell", + "C", + "MATLAB", + "Makefile" + ], + "name": "Sandia's Current Energy Conversion module for Flexible-Mesh Delft3D flow solver v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SNL-Delft3D-FM-CEC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Sandia_Analysis_Workbench_\342\200\223_Integration_Framework.json" "b/agency-indexes/DoE/Sandia_Analysis_Workbench_\342\200\223_Integration_Framework.json" new file mode 100644 index 00000000..79010283 --- /dev/null +++ "b/agency-indexes/DoE/Sandia_Analysis_Workbench_\342\200\223_Integration_Framework.json" @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-29" + }, + "description": "The Workbench Integration Framework is an application platform designed to facilitate the creation of desktop software for engineering analysis.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 243154.4, + "languages": [ + "Java" + ], + "name": "Sandia Analysis Workbench \u2013 Integration Framework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Cloud_Forensics_and_Incident_Response_Platform_v_1.0.json b/agency-indexes/DoE/Sandia_Cloud_Forensics_and_Incident_Response_Platform_v_1.0.json new file mode 100644 index 00000000..2005b9e2 --- /dev/null +++ b/agency-indexes/DoE/Sandia_Cloud_Forensics_and_Incident_Response_Platform_v_1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-14", + "metadataLastUpdated": "2019-03-18" + }, + "description": "As systems and devices become virtualized and deployed in the cloud, the hypervisor becomes an increasingly appropriate place to collect performance data, system state, system landscape, function calls, transaction traces, and other characteristics. We developed a method by which an introspection application may be coupled with a hypervisor to \u201creach into\u201d the VM with minimal intrusiveness to collect data critical to the reconstruction of events, files, and operations. Such a capability is required to take advantage of the hypervisor as an instrumentation platform and to integrate that data with more traditional collection mechanisms. The concept of a VM serviced by a lightweight hypervisor is a relatively new paradigm for forensic practitioners. Traditional forensic techniques, based on assumptions that the filesystem was directly interacting with the hardware through an abstraction, afforded the forensic practitioner the assumption that there was nothing controlling the application below the filesystem. This is not the case when using virtualized technologies. Hypervisors can covertly monitor, introspect and interact with the guest in a transparent fashion. The problems of storage and collection of actionable data are exhausting. The current challenge is most hypervisors do not expose a useful application programming interface (API) at a sufficient level to do transparent, fine-grained and customizable introspection. Scalable VM instrumentation and introspection at an in-depth level requires fast handling of events, as well as direct access to VM state. Furthermore, deep introspection benefits greatly from the ability to gather data from the hardware during the VM\u2019s exit to the hypervisor. All of this requires identical access to the system as the hypervisor itself; improper use of this ability could easily cause system instability. It is for this reason we believe that the hypervisor developers have been hesitant to grant this much control through their APIs. However, our approach leverages other means to collect and monitor the guests in a targeted fashion. Virtual machine introspection (VMI) is a technique used to monitor the runtime state of a system-level virtual machine. The runtime state can be may include processor registers, memory, disk, network, and any other hardware-level events\nA review of research literature and current VMI technologies exposed several limitations and tradeoffs in VMI approaches, including: the use of in-guest agents; kernel to user space transitions (dramatically slowing down processing); VMI tool pre-configuration requirements; hypervisor version lock-in or source code patching; reliance on operating system symbols; limited processor features due to hypervisor (even if the hardware could do more).\nTo address these constraints, a VMI tool was envisioned to provide the cloud forensic capabilities while having as few of these limitations as possible. The Kernel-based Virtual Machine Introspection (KVMi) tool was developed for hypervisors on Intel\u2019s x86-64 architecture. To meet performance, scoping and use-case demands, the follow criteria were applied to KVMi to support live, forensic data collection:\n\u2022\tShall not require in-guest agents.\n\u2022\tShall work with any recent version of modern hypervisors.\n\u2022\tShall introspect upon any guest (VM) running modern versions of Windows, Linux and OS X.\n\u2022\tShall have the ability to find and track operating system artifacts\n\u2022\tShall not require operating system symbol files.\n\u2022\tShall be able to fully handle VM-exits, bypassing execution of the hypervisor if necessary, to facilitate new features the hypervisor may not support.\n\u2022\tShall be compilable/loadable on a running system with standard build tools.\n", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 38273.6, + "languages": [ + "C" + ], + "name": "Sandia Cloud Forensics and Incident Response Platform v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Contributions_to_WaterTAP.json b/agency-indexes/DoE/Sandia_Contributions_to_WaterTAP.json new file mode 100644 index 00000000..82718c3a --- /dev/null +++ b/agency-indexes/DoE/Sandia_Contributions_to_WaterTAP.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-06591O\nThrough National Alliance for Water Innovation funding, Sandia will be contributing to the Water treatment Technoeconomic Assessment Platform (WaterTAP) project. WaterTAP is an open-source, Python-based software package that supports the technoeconomic assessment of full water treatment trains. WaterTAP includes a modular water treatment model library spanning a broad set of water treatment processes composed of unit, property, and costing models.", + "laborHours": 1656.8, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "Sandia Contributions to WaterTAP", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/watertap-org/watertap-renrtl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Cyber_Omni_Tracker.json b/agency-indexes/DoE/Sandia_Cyber_Omni_Tracker.json new file mode 100644 index 00000000..22bad04e --- /dev/null +++ b/agency-indexes/DoE/Sandia_Cyber_Omni_Tracker.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SCOT cyber security team enhancement tool that coordinates activities, captures knowledge, and serves as a platform to automate time-consuming tasks that a cyber security team needs to perform in its daily operations.", + "laborHours": 370393.6, + "name": "Sandia Cyber Omni Tracker", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/scot/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/scot", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Engineering_Analysis_Code_Access_System_v._2.0.1.json b/agency-indexes/DoE/Sandia_Engineering_Analysis_Code_Access_System_v._2.0.1.json new file mode 100644 index 00000000..0c0f8936 --- /dev/null +++ b/agency-indexes/DoE/Sandia_Engineering_Analysis_Code_Access_System_v._2.0.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-12-03" + }, + "description": "The Sandia Engineering Analysis Code Access System (SEACAS) is a suite of preprocessing, post processing, translation, visualization, and utility applications supporting finite element analysis software using the Exodus database file format.", + "laborHours": 692284.0, + "languages": [ + "MATLAB" + ], + "name": "Sandia Engineering Analysis Code Access System v. 2.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Equation_of_State_Model_Library.json b/agency-indexes/DoE/Sandia_Equation_of_State_Model_Library.json new file mode 100644 index 00000000..da1ee7cc --- /dev/null +++ b/agency-indexes/DoE/Sandia_Equation_of_State_Model_Library.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software provides a general interface for querying thermodynamic states of material models along with implementation of both general and specific equation of state models. In particular, models are provided for the IAPWS-IF97 and IAPWS95 water standards as well as the associated water standards for viscosity, thermal conductivity, and surface tension. The interface supports implementation of models in a variety of independent variable spaces. Also, model support routines are included that allow for coupling of models and determination and representation of phase boundaries.", + "laborHours": 3009.6, + "languages": [ + "CMake", + "C++", + "C" + ], + "name": "Sandia Equation of State Model Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/SESML?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SESML", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Generated_Matrix_Tool__SGMT__v._1.0.json b/agency-indexes/DoE/Sandia_Generated_Matrix_Tool__SGMT__v._1.0.json new file mode 100644 index 00000000..ba24a823 --- /dev/null +++ b/agency-indexes/DoE/Sandia_Generated_Matrix_Tool__SGMT__v._1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Provides a tool with which create and characterize a very large set of matrix-based visual analogy problems that have properties that are similar to Raven's Progressive Matrices (RPMs)\u2122. The software uses the same underlying patterns found in RPMs to generate large numbers of unique matrix problems using parameters chosen by the researcher. Specifically, the software is designed so that researchers can choose the type, direction, and number of relations in a problem and then create any number of unique matrices that share the same underlying structure (e.g. changes in numerosity in a diagonal pattern) but have different surface features (e.g. shapes, colors).Raven's Progressive Matrices (RPMs) \u2122 are a widely-used test for assessing intelligence and reasoning ability. Since the test is non-verbal, it can be applied to many different populations and has been used all over the world. However, there are relatively few matrices in the sets developed by Raven, which limits their use in experiments requiring large numbers of stimuli. This tool creates a matrix set in a systematic way that allows researchers to have a great deal of control over the underlying structure, surface features, and difficulty of the matrix problems while providing a large set of novel matrices with which to conduct experiments.", + "laborHours": 0.0, + "languages": [], + "name": "Sandia Generated Matrix Tool (SGMT) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Matrices", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Higher_Order_Elements__SHOE__v_0.5_alpha.json b/agency-indexes/DoE/Sandia_Higher_Order_Elements__SHOE__v_0.5_alpha.json new file mode 100644 index 00000000..0ee0cbda --- /dev/null +++ b/agency-indexes/DoE/Sandia_Higher_Order_Elements__SHOE__v_0.5_alpha.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-19" + }, + "description": "SHOE is research code for characterizing and visualizing higher-order finite elements; it contains a framework for defining classes of interpolation techniques and element shapes; methods for interpolating triangular, quadrilateral, tetrahedral, and hexahedral cells using Lagrange and Legendre polynomial bases of arbitrary order; methods to decompose each element into domains of constant gradient flow (using a polynomial solver to identify critical points); and an isocontouring technique that uses this decomposition to guarantee topological correctness. Please note that this is an alpha release of research software and that some time has passed since it was actively developed; build- and run-time issues likely exist.", + "laborHours": 13360.8, + "languages": [ + "C++", + "C", + "CMake", + "Python" + ], + "name": "Sandia Higher Order Elements (SHOE) v 0.5 alpha", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/shoe", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Hyperspectral_Upper-Bound_Spectrum_Version_1.0.json b/agency-indexes/DoE/Sandia_Hyperspectral_Upper-Bound_Spectrum_Version_1.0.json new file mode 100644 index 00000000..9441966d --- /dev/null +++ b/agency-indexes/DoE/Sandia_Hyperspectral_Upper-Bound_Spectrum_Version_1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The Sandia hyperspectral upper-bound spectrum algorithm (hyper-UBS) is a cosmic ray despiking algorithm for hyperspectral data sets. When naturally-occurring, high-energy (gigaelectronvolt) cosmic rays impact the earth\u2019s atmosphere, they create an avalanche of secondary particles which will register as a large, positive spike on any spectroscopic detector they hit. Cosmic ray spikes are therefore an unavoidable spectroscopic contaminant which can interfere with subsequent analysis. A variety of cosmic ray despiking algorithms already exist and can potentially be applied to hyperspectral data matrices, most notably the upper-bound spectrum data matrices (UBS-DM) algorithm by Dongmao Zhang and Dor Ben-Amotz which served as the basis for the hyper-UBS algorithm. However, the existing algorithms either cannot be applied to hyperspectral data, require information that is not always available, introduce undesired spectral bias, or have otherwise limited effectiveness for some experimentally relevant conditions. Hyper-UBS is more effective at removing a wider variety of cosmic ray spikes from hyperspectral data without introducing undesired spectral bias. In addition to the core algorithm the Sandia hyper-UBS software package includes additional source code useful in evaluating the effectiveness of the hyper-UBS algorithm. The accompanying source code includes code to generate simulated hyperspectral data contaminated by cosmic ray spikes, several existing despiking algorithms, and code to evaluate the performance of the despiking algorithms on simulated data.", + "laborHours": 0.0, + "languages": [ + "Mathworks Matlab R2015b" + ], + "name": "Sandia Hyperspectral Upper-Bound Spectrum Version 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Hyper-UBS", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Injury_Biomechanics_Laboratory_Library.json b/agency-indexes/DoE/Sandia_Injury_Biomechanics_Laboratory_Library.json new file mode 100644 index 00000000..c70ad31a --- /dev/null +++ b/agency-indexes/DoE/Sandia_Injury_Biomechanics_Laboratory_Library.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-02", + "metadataLastUpdated": "2020-11-04" + }, + "description": "The Sandia Injury Biomechanics Laboratory (SIBL) Library is a collection of scripts and tools used to preprocess, process, and postprocess data for analysis of injury biomechanics data. SAND2020-3663 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 54081.6, + "languages": [ + "Python", + "Python" + ], + "name": "Sandia Injury Biomechanics Laboratory Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sibl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Machine_Learning_Laboratory.json b/agency-indexes/DoE/Sandia_Machine_Learning_Laboratory.json new file mode 100644 index 00000000..604b38fe --- /dev/null +++ b/agency-indexes/DoE/Sandia_Machine_Learning_Laboratory.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "Samlab provides a workflow and data storage for machine learning experiment inputs and outputs using mongodb, and a web service to manage, search, visualize, and analyze the results.", + "laborHours": 7296.0, + "languages": [ + "Python" + ], + "name": "Sandia Machine Learning Laboratory", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/samlab/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/samlab", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Matlab_AnalysiS_Hierarchy_toolbox_v._1.0.json b/agency-indexes/DoE/Sandia_Matlab_AnalysiS_Hierarchy_toolbox_v._1.0.json new file mode 100644 index 00000000..7dacaf55 --- /dev/null +++ b/agency-indexes/DoE/Sandia_Matlab_AnalysiS_Hierarchy_toolbox_v._1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-26" + }, + "description": "SMASH is a collection of MATLAB programs, packages, and class definitions for analyzing experimental data.", + "laborHours": 330980.0, + "languages": [ + "MATLAB", + "HTML" + ], + "name": "Sandia Matlab AnalysiS Hierarchy toolbox v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SMASHtoolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_National_Laboratories_Environmental_Fluid_Dynamics_Code_V._1_0.0__Beta_.json b/agency-indexes/DoE/Sandia_National_Laboratories_Environmental_Fluid_Dynamics_Code_V._1_0.0__Beta_.json new file mode 100644 index 00000000..2a850cd4 --- /dev/null +++ b/agency-indexes/DoE/Sandia_National_Laboratories_Environmental_Fluid_Dynamics_Code_V._1_0.0__Beta_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The DOE has funded Sandia National Labs (SNL) to develop an open-source modeling tool to guide the design and layout of marine hydrokinetic (MHK) arrays to maximize power production while minimizing environmental effects. This modeling framework simulates flows through and around MHK arrays while quantifying environmental responses. As an augmented version of US EPA's Environmental Fluid Dynamics Code (EFDC), SNL-EFDC includes: (1) a new module that simulates energy conversion (momentum withdrawal) by MHK devices with commensurate changes in the turbulent kinetic energy and its dissipation rate, (2) new, advanced sediment dynamics routines, and (3) augmented water quality modules.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Sandia National Laboratories Environmental Fluid Dynamics Code V. 1 0.0 (Beta)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/EFDC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "10.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_OpenSHMEM.json b/agency-indexes/DoE/Sandia_OpenSHMEM.json new file mode 100644 index 00000000..20cdf8fa --- /dev/null +++ b/agency-indexes/DoE/Sandia_OpenSHMEM.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Sandia OpenSHMEM is an implementation of the OpenSHMEM Standard over the Portals 4 Networking API and the OpenFabrics Interface (OFI). Sandia OpenSHMEM is designed to be a low-overhead implementation of the OpenSHMEM standard which takes advantage of the many features of the Portals 4 specification.", + "laborHours": 18559.2, + "languages": [ + "Shell", + "Perl", + "C", + "Makefile", + "M4", + "Python" + ], + "name": "Sandia OpenSHMEM", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Sandia-OpenSHMEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Optical_Fringe_Analysis_Slope_Tool__SOFAST__v._2018.11.20.json b/agency-indexes/DoE/Sandia_Optical_Fringe_Analysis_Slope_Tool__SOFAST__v._2018.11.20.json new file mode 100644 index 00000000..76921553 --- /dev/null +++ b/agency-indexes/DoE/Sandia_Optical_Fringe_Analysis_Slope_Tool__SOFAST__v._2018.11.20.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-01-09", + "metadataLastUpdated": "2019-03-25" + }, + "description": "SOFAST is used to characterize the surface slope of reflective mirrors for solar applications. SOFAST uses a large monitor or projection screen to display fringe patterns, and a machine vision camera to image the reflection of these patterns in the subject mirror. From these images, a detailed map of surface normals can be generated and compared to design or fitted mirror shapes. SOFAST uses standard Fringe Reflection (Deflectometry) approaches to measure the mirror surface normals. SOFAST uses an extrinsic analysis of key points on the facet to locate the camera and monitor relative to the facet coordinate system. It then refines this position based on the measured surface slope and integrated shape of the mirror facet. The facet is placed into a reference frame such that key points on the facet match the design facet in orientation and position. This is key to evaluating a facet as suitable for a specific solar application. SOFAST reports the measurements of the facet as detailed surface normal location in a format suitable for ray tracing optical analysis codes. SOFAST also reports summary information as to the facet fitted shape (monomial) and error parameters. Useful plots of the error distribution are also presented.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 10822.4, + "languages": [], + "name": "Sandia Optical Fringe Analysis Slope Tool (SOFAST) v. 2018.11.20", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 2018.11.20" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_PUF_Analysis_Tool.json b/agency-indexes/DoE/Sandia_PUF_Analysis_Tool.json new file mode 100644 index 00000000..c38158d9 --- /dev/null +++ b/agency-indexes/DoE/Sandia_PUF_Analysis_Tool.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This program is a graphical user interface for measuring and performing inter-active analysis of physical unclonable functions (PUFs). It is intended for demonstration and education purposes. See license.txt for license details. The program features a PUF visualization that demonstrates how signatures differ between PUFs and how they exhibit noise over repeated measurements. A similarity scoreboard shows the user how close the current measurement is to the closest chip signatures in the database. Other metrics such as average noise and inter-chip Hamming distances are presented to the user. Randomness tests published in NIST SP 800-22 can be computed and displayed. Noise and inter-chip histograms for the sample of PUFs and repeated PUF measurements can be drawn.", + "laborHours": 2082.4, + "name": "Sandia PUF Analysis Tool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_RPM_Lane_Simulator_.json b/agency-indexes/DoE/Sandia_RPM_Lane_Simulator_.json new file mode 100644 index 00000000..adb423e4 --- /dev/null +++ b/agency-indexes/DoE/Sandia_RPM_Lane_Simulator_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-10", + "metadataLastUpdated": "2020-11-10" + }, + "description": "Software application: Sandia RPM Lane Simulator.\nSimulates Rapiscan radiation portal monitors and network cameras that are in use in the NNSA Nuclear Smuggling Detection and Deterrence (NSDD) program. SAND2019-3741 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 28728.0, + "languages": [], + "name": "Sandia RPM Lane Simulator ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SRLS", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Simple_Particle_Tracking__Sandia_SPT__v._1.0.json b/agency-indexes/DoE/Sandia_Simple_Particle_Tracking__Sandia_SPT__v._1.0.json new file mode 100644 index 00000000..4c7198ae --- /dev/null +++ b/agency-indexes/DoE/Sandia_Simple_Particle_Tracking__Sandia_SPT__v._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "Sandia SPT is designed as software to accompany a book chapter being published a methods chapter which provides an introduction on how to label and track individual proteins. The Sandia Simple Particle Tracking code uses techniques common to the image processing community, where its value is that it facilitates implementing the methods described in the book chapter by providing the necessary open-source code. The code performs single particle spot detection (or segmentation and localization) followed by tracking (or connecting the detected particles into trajectories). The book chapter, which along with the headers in each file, constitutes the documentation for the code is: Anthony, S.M.; Carroll-Portillo, A.; Timlon, J.A., Dynamics and Interactions of Individual Proteins in the Membrane of Living Cells. In Anup K. Singh (Ed.) Single Cell Protein Analysis Methods in Molecular Biology. Springer", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Sandia Simple Particle Tracking (Sandia SPT) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Strehl_Calculator_Version.json b/agency-indexes/DoE/Sandia_Strehl_Calculator_Version.json new file mode 100644 index 00000000..fdadb4d6 --- /dev/null +++ b/agency-indexes/DoE/Sandia_Strehl_Calculator_Version.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-06", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The Sandia Strehl Calculator is designed to calculate the Gibson and Lanni point spread function (PSF), Strehl ratio, and ensquared energy, allowing non-design immersion, coverslip, and sample layers. It also uses Abbe number calculations to determine the refractive index at specific wavelengths when given the refractive index at a different wavelength and the dispersion. The theory behind the code is all fully developed in standard optics references. The novelty of the code is packaging it in a format that is accessible to general microscope users, not limited to individuals with expertise in both optics and computer programming.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "Sandia Strehl Calculator Version", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Strehl", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Unstructured_Triangle_Table_Generator.json b/agency-indexes/DoE/Sandia_Unstructured_Triangle_Table_Generator.json new file mode 100644 index 00000000..483cf55d --- /dev/null +++ b/agency-indexes/DoE/Sandia_Unstructured_Triangle_Table_Generator.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The software generates data tables for thermodynamic and transport properties of materials as described by a set of input models. For each input model parameterization, an associated table is created on an unstructured triangular grid. These grids all conform to the same topology. A statistical accuracy guarantee is provided for the tabular representation of the model. Details of the model and table specification are given in a XML input deck.", + "laborHours": 69798.4, + "languages": [ + "lc/C++/FORTRAN" + ], + "name": "Sandia Unstructured Triangle Table Generator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/SUTTG?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SUTTG", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sandia_Unstructured_Triangle_Tabular_Interpolation_Package_v_0.1_beta.json b/agency-indexes/DoE/Sandia_Unstructured_Triangle_Tabular_Interpolation_Package_v_0.1_beta.json new file mode 100644 index 00000000..5b377114 --- /dev/null +++ b/agency-indexes/DoE/Sandia_Unstructured_Triangle_Tabular_Interpolation_Package_v_0.1_beta.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The software interpolates tabular data, such as for equations of state, provided on an unstructured triangular grid. In particular, interpolation occurs in a two dimensional space by looking up the triangle in which the desired evaluation point resides and then performing a linear interpolation over the n-tuples associated with the nodes of the chosen triangle. The interface to the interpolation routines allows for automated conversion of units from those tabulated to the desired output units. when multiple tables are included in a data file, new tables may be generated by on-the-fly mixing of the provided tables", + "laborHours": 1656.8, + "languages": [ + "C", + "Fortran" + ], + "name": "Sandia Unstructured Triangle Tabular Interpolation Package v 0.1 beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/UTri", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Saturn_v1.0.json b/agency-indexes/DoE/Saturn_v1.0.json new file mode 100644 index 00000000..eb62c975 --- /dev/null +++ b/agency-indexes/DoE/Saturn_v1.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-03", + "metadataLastUpdated": "2021-03-03" + }, + "description": "Plain-text Python notebooks with checkpointing.", + "laborHours": 0.0, + "languages": [], + "name": "Saturn v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mrzv/saturn", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ScaLAPACK_-_Scalable_Linear_Algebra_PACKage.json b/agency-indexes/DoE/ScaLAPACK_-_Scalable_Linear_Algebra_PACKage.json new file mode 100644 index 00000000..0a284dcc --- /dev/null +++ b/agency-indexes/DoE/ScaLAPACK_-_Scalable_Linear_Algebra_PACKage.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-12-19", + "metadataLastUpdated": "2018-01-19" + }, + "description": "ScaLAPACK is a library of high-performance linear algebra routines for parallel distributed memory machines. ScaLAPACK solves dense and banded linear systems, least squares problems, eigenvalue problems, and singular value problems.", + "homepageURL": "http://www.netlib.org/scalapack", + "laborHours": 0.0, + "name": "ScaLAPACK - Scalable Linear Algebra PACKage", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.netlib.org/scalapack/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.netlib.org/scalapack", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ScaffCC.json b/agency-indexes/DoE/ScaffCC.json new file mode 100644 index 00000000..9dc54cef --- /dev/null +++ b/agency-indexes/DoE/ScaffCC.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Compilation, analysis and optimization framework for the Scaffold quantum programming language.\n", + "laborHours": 1278776.0, + "name": "ScaffCC", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-QCI/ScaffCC/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/ScaffCC", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scalable,_Physical_Effects_Measureable_Microgridfor_Cyber_Resilience_Analysis.json b/agency-indexes/DoE/Scalable,_Physical_Effects_Measureable_Microgridfor_Cyber_Resilience_Analysis.json new file mode 100644 index 00000000..14b9e88f --- /dev/null +++ b/agency-indexes/DoE/Scalable,_Physical_Effects_Measureable_Microgridfor_Cyber_Resilience_Analysis.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-04-13", + "metadataLastUpdated": "2023-03-13" + }, + "description": "SPEMMCRA provides a low-cost simulated method to provide for testing of control theory and cybersecurity approaches to microgrid implementations. Specifically, this physics-based approach provides realistic responses to compare control strategies in simulation, but also to demonstrate actions that can or cannot be taken in taking cybersecurity actions . As communications interfaces or other actions are taken that affect the flow of data, SPEMMCRA can show whether the microgrid operation is adversely affected by what is intended to mitigate a cybersecurity event.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Scalable, Physical Effects Measureable Microgridfor Cyber Resilience Analysis", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/SPEMMCRA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scalable_Electronic_Structure__ScalES__v1.0.json b/agency-indexes/DoE/Scalable_Electronic_Structure__ScalES__v1.0.json new file mode 100644 index 00000000..2e80a1bc --- /dev/null +++ b/agency-indexes/DoE/Scalable_Electronic_Structure__ScalES__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-21", + "metadataLastUpdated": "2021-10-21" + }, + "description": "ScalES is a high performance software package for performing large scale electronic structure calculations on high performance supercomputers.", + "laborHours": 0.0, + "languages": [], + "name": "Scalable Electronic Structure (ScalES) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/scales/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scalable_Linked_Dynamic_Equilibrium__SLiDE_.json b/agency-indexes/DoE/Scalable_Linked_Dynamic_Equilibrium__SLiDE_.json new file mode 100644 index 00000000..dbe78728 --- /dev/null +++ b/agency-indexes/DoE/Scalable_Linked_Dynamic_Equilibrium__SLiDE_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2022-02-15" + }, + "description": "SLiDE (Scalable Linked Dynamic Equilibrium) replicates the blueNOTE (National Open source Tools for general Equilibrium analysis) datastream from the Wisconsin National Data Consortium. From there, it produces a recursive dynamic computable general equilibrium model of the US states and eventually the global/national economies. The datastream operations have been set up to allow for scalability of both regions and sectors represented. The model has the capability to flexibly define functional forms similar to other general equilibrium model construction software.", + "laborHours": 3724.0, + "languages": [ + "Julia" + ], + "name": "Scalable Linked Dynamic Equilibrium (SLiDE)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/slide", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scalable_Object_Store_v._1.0.0.json b/agency-indexes/DoE/Scalable_Object_Store_v._1.0.0.json new file mode 100644 index 00000000..2b0ce33a --- /dev/null +++ b/agency-indexes/DoE/Scalable_Object_Store_v._1.0.0.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SOS is software that stores data values in a set of structured flat files. The data is organized in the files based upon functions specified by the user in order to enable fast insertion and retrieval of data.", + "laborHours": 54036.0, + "languages": [ + "C", + "Roff", + "RPC", + "Cython", + "M4", + "Python" + ], + "name": "Scalable Object Store v. 1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ovis-hpc/sos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scalable_Reasoning_System__SRS_.json b/agency-indexes/DoE/Scalable_Reasoning_System__SRS_.json new file mode 100644 index 00000000..3479f34e --- /dev/null +++ b/agency-indexes/DoE/Scalable_Reasoning_System__SRS_.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-06-12", + "metadataLastUpdated": "2025-04-14" + }, + "description": "SRS is a web-based and mobile toolkit for information visualization and collaboration. It includes server-side components in the form of web services that provide analytical functions such as data clustering and temporal analysis. The SRS client is accessed via a web browser and uses asynchronous javascript and XML (AJAX) to interact with and visualize the results of these web services. Users of SRS can query data sources that are connected to the SRS backend, and query results are presented in the form of coordinated visual displays in a web browser that depict temporal, topical, and spatial relationships in the results. SRS also includes an early stage graphical reasoning diagram interface that helps analysts express and test hypotheses. \nThis software was developed with funding from the Science and Technology Directorate of the U.S. Department of Homeland Security.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 35112.0, + "languages": [], + "name": "Scalable Reasoning System (SRS)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "2.x" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scalable_Reduced_Order_Model_with_Discontinuous_Galerkin_Domain_Decomposition.json b/agency-indexes/DoE/Scalable_Reduced_Order_Model_with_Discontinuous_Galerkin_Domain_Decomposition.json new file mode 100644 index 00000000..50dc35c6 --- /dev/null +++ b/agency-indexes/DoE/Scalable_Reduced_Order_Model_with_Discontinuous_Galerkin_Domain_Decomposition.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-12-05", + "metadataLastUpdated": "2023-12-05" + }, + "description": "scaleupROM is a scalable, physics-constrained reduced order model (ROM). It aims to provide robust,\naccelerated physics predictions at extrapolated scales, based on the small, component-level data. This is\nimplemented by combining projection-based ROM with discontinuous Galerkin domain decomposition, in\nthe framework of MFEM and libROM. It currently supports the Poisson equation and Stokes flow\nequation, and more work is in progress toward general, nonlinear physics systems.", + "laborHours": 0.0, + "languages": [], + "name": "Scalable Reduced Order Model with Discontinuous Galerkin Domain Decomposition", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/scaleupROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scalable_Unusual_Syslog_Message_Detector.json b/agency-indexes/DoE/Scalable_Unusual_Syslog_Message_Detector.json new file mode 100644 index 00000000..130bf6f4 --- /dev/null +++ b/agency-indexes/DoE/Scalable_Unusual_Syslog_Message_Detector.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "The Scalable Unusual Message Detector (SUD) is a scalable software program for finding anomalous log messages on a single machine or cluster in near real time. This program is able to detect unusual messages by turning the text into sets of ngrams, which are multiple sets of tokens/words per message, and comparing incoming messages with the saved ngrams. A set of rules are used for determining if the saved ngrams match an incoming message based on the size of the incoming message. This tools is intended to final unusual/anomalous messages to find critical events that system administrators are not expecting. Currently the algorithms/methods are being used on HPC\u2019s scalalble log analysis machine. Work is being done to port the algorithms/methods to a standalone tool.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Scalable Unusual Syslog Message Detector", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Schema_Grapher.json b/agency-indexes/DoE/Schema_Grapher.json new file mode 100644 index 00000000..6e6b4300 --- /dev/null +++ b/agency-indexes/DoE/Schema_Grapher.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-01-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL contributions to project site managed by federal agency. Schema Grapher is an application that takes in CSV datasets and converts them to RDF for loading into a graph database. Schema Grapher is responsible for the extract and transform part of an ETL (i.e., extract, transform, load) pipeline.", + "laborHours": 0.0, + "languages": [], + "name": "Schema Grapher", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/schema-grapher", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Schematics.json b/agency-indexes/DoE/Schematics.json new file mode 100644 index 00000000..8e5a3042 --- /dev/null +++ b/agency-indexes/DoE/Schematics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2023-03-07" + }, + "description": "Create schematics of thermal-hydraulic systems.", + "laborHours": 1520.0, + "languages": [], + "name": "Schematics", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/schematics", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ScholarGuard.json b/agency-indexes/DoE/ScholarGuard.json new file mode 100644 index 00000000..81d30439 --- /dev/null +++ b/agency-indexes/DoE/ScholarGuard.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "The ScholarGuard framework aims to address the gap in archiving and preservation efforts for scholarly artifacts beyond traditional research papers, such as software source code, datasets, presentation slides, workflows, protocols, videos, and more. It introduces a prototype system designed to automatically track researchers' outputs across various scholarly productivity portals on the open web, including platforms like GitHub, Slideshare, Figshare, and Wikipedia.\nThe system detects the availability of new scholarly artifacts and applies modern web archiving technology to create a durable archival record, including high-level metadata for each artifact. This metadata is displayed within the system, linking both to the live version and the archived version of the resource, ensuring long-term accessibility and preservation of diverse research outputs.\nThe software serves as a critical tool for preserving the broader spectrum of scholarly contributions, facilitating visibility, searchability, and long-term access to research artifacts beyond the traditional scope of journal publications.", + "laborHours": 52531.2, + "languages": [], + "name": "ScholarGuard", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ScholarGuard", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sci-Vis_Framework.json b/agency-indexes/DoE/Sci-Vis_Framework.json new file mode 100644 index 00000000..7915aded --- /dev/null +++ b/agency-indexes/DoE/Sci-Vis_Framework.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SVF is a full featured OpenGL 3d framework that allows for rapid creation of complex visualizations. The SVF framework handles much of the lifecycle and complex tasks required for a 3d visualization. Unlike a game framework SVF was designed to use fewer resources, work well in a windowed environment, and only render when necessary. The scene also takes advantage of multiple threads to free up the UI thread as much as possible. Shapes (actors) in the scene are created by adding or removing functionality (through support objects) during runtime. This allows a highly flexible and dynamic means of creating highly complex actors without the code complexity (it also helps overcome the lack of multiple inheritance in Java.) All classes are highly customizable and there are abstract classes which are intended to be subclassed to allow a developer to create more complex and highly performant actors. There are multiple demos included in the framework to help the developer get started and shows off nearly all of the functionality. Some simple shapes (actors) are already created for you such as text, bordered text, radial text, text area, complex paths, NURBS paths, cube, disk, grid, plane, geometric shapes, and volumetric area. It also comes with various camera types for viewing that can be dragged, zoomed, and rotated. Picking or selecting items in the scene can be accomplished in various ways depending on your needs (raycasting or color picking.) The framework currently has functionality for tooltips, animation, actor pools, color gradients, 2d physics, text, 1d/2d/3d textures, children, blending, clipping planes, view frustum culling, custom shaders, and custom actor states", + "laborHours": 41602.4, + "name": "Sci-Vis Framework", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/svf/blob/master/svf-core/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/svf", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SciPy.json b/agency-indexes/DoE/SciPy.json new file mode 100644 index 00000000..f9d24b51 --- /dev/null +++ b/agency-indexes/DoE/SciPy.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-31", + "metadataLastUpdated": "2018-07-31" + }, + "description": "SciPy (pronounced \"Sigh Pie\") is open-source software for mathematics, science, and engineering. It includes modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, ODE solvers, and more.", + "laborHours": 303817.6, + "languages": [], + "name": "SciPy", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/scipy/scipy", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ScienceSearch_Metadata_Infrastructure__ScienceSearch-MI__v1.2.json b/agency-indexes/DoE/ScienceSearch_Metadata_Infrastructure__ScienceSearch-MI__v1.2.json new file mode 100644 index 00000000..8a82bed7 --- /dev/null +++ b/agency-indexes/DoE/ScienceSearch_Metadata_Infrastructure__ScienceSearch-MI__v1.2.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-06-11", + "metadataLastUpdated": "2020-06-11" + }, + "description": "ScienceSearch-MI is a framework that generates metadata from scientific artifacts (papers, proposals, images) that is used to enable search.", + "laborHours": 11202.4, + "languages": [], + "name": "ScienceSearch Metadata Infrastructure (ScienceSearch-MI) v1.2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/sciencesearch/sciencesearch-mi/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Science_Capsule:_Capturing_the_Data_Life_Cycle__Science_Capsule__v0.1.0.json b/agency-indexes/DoE/Science_Capsule:_Capturing_the_Data_Life_Cycle__Science_Capsule__v0.1.0.json new file mode 100644 index 00000000..7518b272 --- /dev/null +++ b/agency-indexes/DoE/Science_Capsule:_Capturing_the_Data_Life_Cycle__Science_Capsule__v0.1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-02-25", + "metadataLastUpdated": "2021-02-25" + }, + "description": "Science Capsule captures the processing and data life cycle across machines, organizations, people, and science domains. Our approach combines user engagement methods from social sciences with innovations in workflow and data management.", + "laborHours": 0.0, + "languages": [], + "name": "Science Capsule: Capturing the Data Life Cycle (Science Capsule) v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/sciencecapsule/sciencecapsule", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scientific_&_Intelligence_Exascale_Visualization_Analysis_System.json b/agency-indexes/DoE/Scientific_&_Intelligence_Exascale_Visualization_Analysis_System.json new file mode 100644 index 00000000..599996e3 --- /dev/null +++ b/agency-indexes/DoE/Scientific_&_Intelligence_Exascale_Visualization_Analysis_System.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "SIEVAS provides an immersive visualization framework for connecting multiple systems in real time for data science. SIEVAS provides the ability to connect multiple COTS and GOTS products in a seamless fashion for data fusion, data analysis, and viewing. It provides this capability by using a combination of micro services, real time messaging, and web service compliant back-end system.", + "laborHours": 15929.6, + "languages": [], + "name": "Scientific & Intelligence Exascale Visualization Analysis System", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/SIEVAS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scientific_Computational_Imaging_COde__SCICO_.json b/agency-indexes/DoE/Scientific_Computational_Imaging_COde__SCICO_.json new file mode 100644 index 00000000..b1c39e5c --- /dev/null +++ b/agency-indexes/DoE/Scientific_Computational_Imaging_COde__SCICO_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "This software is an open-source Python library that provides a collection of advanced algorithms to address computational imaging and inverse problems arising in the analysis of scientific data. The main goal is to deliver a unified mathematical formulation that applies state-of-the art methods developed within the computational imaging community to inversion problems. This includes computational algorithms that are able to reconstruct the quantities of interest given specific collections of experimental data and enable the inversion even for cases where there are not enough measurements to uniquely specify the solution (ill-posed problems). The core of the library consists of optimization algorithms with the flexibility to incorporate explicit analytical priors, explicit regularization constraints, as well as implicit regularization models which can be learned offline via machine learning methods. The library will interface with well-known Python packages providing support for forward models relevant to tomographic imaging and coherent diffraction imaging, as well as Python libraries for machine learning. Supporting visualization and analysis of results will also be provided. The software will include thorough documentation and extensive application examples.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Scientific Computational Imaging COde (SCICO)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scientific_Python_Cookiecutter.json b/agency-indexes/DoE/Scientific_Python_Cookiecutter.json new file mode 100644 index 00000000..12838d14 --- /dev/null +++ b/agency-indexes/DoE/Scientific_Python_Cookiecutter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "This repository contains a cookiecutter template for generating a scientific Python project complete with CI testing and documentation. Separately, beside the cookiecutter template, it contains tutorial documentation on how to use this template to organize scientific Python code into a package and use popular tools for testing, documentation, and maintenance.", + "laborHours": 1322.4, + "languages": [], + "name": "Scientific Python Cookiecutter", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/scientific-python-cookiecutter/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/scientific-python-cookiecutter", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scientific_sofTware_Research_for_User_experience,_Design,_Engagement,_and_Learning__STRUDEL__v1.0.0.json b/agency-indexes/DoE/Scientific_sofTware_Research_for_User_experience,_Design,_Engagement,_and_Learning__STRUDEL__v1.0.0.json new file mode 100644 index 00000000..0a307077 --- /dev/null +++ b/agency-indexes/DoE/Scientific_sofTware_Research_for_User_experience,_Design,_Engagement,_and_Learning__STRUDEL__v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-27", + "metadataLastUpdated": "2024-06-27" + }, + "description": "The Scientific sofTware Research for User experience, Design, Engagement, and Learning project (STRUDEL) will create, using user research methodologies, a planning framework and design system for scientific software that will guide and support the development of highly functional and usable user interfaces.", + "laborHours": 323243.2, + "languages": [], + "name": "Scientific sofTware Research for User experience, Design, Engagement, and Learning (STRUDEL) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/strudel-science/strudel-kit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scramble.json b/agency-indexes/DoE/Scramble.json new file mode 100644 index 00000000..f894c18f --- /dev/null +++ b/agency-indexes/DoE/Scramble.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-04-01", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The purpose of Scramble is to provide a cross validation method to ensure machine learning model accuracy in cases where model classes have heterogeneous N values.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Scramble", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/Scramble", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scraper.json b/agency-indexes/DoE/Scraper.json new file mode 100644 index 00000000..02bc82a0 --- /dev/null +++ b/agency-indexes/DoE/Scraper.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Scraper is a tool for scraping and visualizing open source data from GitHub.\n", + "laborHours": 1170.4, + "languages": [], + "name": "Scraper", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/scraper", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Screamer_version_4.1.json b/agency-indexes/DoE/Screamer_version_4.1.json new file mode 100644 index 00000000..1b89f72e --- /dev/null +++ b/agency-indexes/DoE/Screamer_version_4.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Screamer is a special purpose circuit code developed for the design of Pulsed Power systems. It models electrical circuits which have a restricted topology in order to provide a fast-running tool while still allowing configurations general enough for most Pulsed Power system designs", + "laborHours": 0.0, + "languages": [ + "Fortran and C++" + ], + "name": "Screamer version 4.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/screamer", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "4.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scribe_Network_API_v.1.0.0.json b/agency-indexes/DoE/Scribe_Network_API_v.1.0.0.json new file mode 100644 index 00000000..e51b8138 --- /dev/null +++ b/agency-indexes/DoE/Scribe_Network_API_v.1.0.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-07", + "metadataLastUpdated": "2024-06-07" + }, + "description": "SAND2023-07864O\nScribe Network API is an add-on tool for Scribe3D software. Scribe Network API documents tabletop exercises in trainings and plays back simulated videos of the scenarios and responses. Users can apply the software to compiled projects, or to a simple visual studio project solution package. The software runs a web application that relays information between computers using Scribe3D through a web application, or web app. The web app involves a representational state transfer (REST) application programming interface that handles sending and receiving Scribe save files and an SQL server that stores the save files. This follow-on package allows users to facilitate a networked tabletop exercise. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 11764.8, + "languages": [ + "C#", + "SQL" + ], + "name": "Scribe Network API v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/scribe3d-api", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Scripts_for_\"A_Global_Phylogenomic_Analysis_of_the_Shiitake_Genus_Lentinula\"_v1.0.json" "b/agency-indexes/DoE/Scripts_for_\"A_Global_Phylogenomic_Analysis_of_the_Shiitake_Genus_Lentinula\"_v1.0.json" new file mode 100644 index 00000000..9aadd4ec --- /dev/null +++ "b/agency-indexes/DoE/Scripts_for_\"A_Global_Phylogenomic_Analysis_of_the_Shiitake_Genus_Lentinula\"_v1.0.json" @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-23", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This is a repository for scripts and documents to help reproduce the results in \"A Global Phylogenomic Analysis of the Shiitake Genus Lentinula\".", + "laborHours": 516.8, + "languages": [], + "name": "Scripts for \"A Global Phylogenomic Analysis of the Shiitake Genus Lentinula\" v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/jgi-lentinula/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scripts_for_Running_Multiple_Lines_of_Evidence_Analysis.json b/agency-indexes/DoE/Scripts_for_Running_Multiple_Lines_of_Evidence_Analysis.json new file mode 100644 index 00000000..4d965727 --- /dev/null +++ b/agency-indexes/DoE/Scripts_for_Running_Multiple_Lines_of_Evidence_Analysis.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-30", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The software code titled \u201cScripts for Running Multiple Lunes of Evidence Analysis\u201d enables high throughput network analysis; efficient analysis of large multi-omic networks in order to rank genes by connectivity. This code creates a set of scripts that take omic networks as input as well as list of known genes and calculates scores for all other genes in genome based on connectivity to those genes and does so accurately and efficiently. In addition, it aids the user in performing a validation check of observed data to random. The code outputs a table of all genes in the genome with LOE scores and scores observed data versus random.", + "laborHours": 76.0, + "languages": [ + "Python 3.6" + ], + "name": "Scripts for Running Multiple Lines of Evidence Analysis", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/afurches/Cell_Wall_LOE", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Scrub.json b/agency-indexes/DoE/Scrub.json new file mode 100644 index 00000000..e73ad434 --- /dev/null +++ b/agency-indexes/DoE/Scrub.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Scrub iteratively writes patterns on files or disk devices to make retrieving the data more difficult.", + "laborHours": 2675.2, + "languages": [], + "name": "Scrub", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/scrub", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ScrubJay.json b/agency-indexes/DoE/ScrubJay.json new file mode 100644 index 00000000..82fb6537 --- /dev/null +++ b/agency-indexes/DoE/ScrubJay.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-04-08", + "metadataLastUpdated": "2019-04-08" + }, + "description": "ScrubJay allows users to query large collections of heterogeneous numerical dawets. Scrubjay v 1.0 a general and scalable framework for analyzing big he1erogeneous HPC performance data. ScrubJay decouples the task of specifying data relationships from the task of analyzing d111a 11nd automates performance 1111alysis. ScrubJay makes large-scale analysis tractable, reproducible, and provides insights into HPC facilities.", + "laborHours": 1626.4, + "languages": [], + "name": "ScrubJay", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ScrubJay", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Search_API.json b/agency-indexes/DoE/Search_API.json new file mode 100644 index 00000000..0d354e0f --- /dev/null +++ b/agency-indexes/DoE/Search_API.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is a small HTTP interface around KBase's elasticsearch indexes.\n\n", + "laborHours": 5730.4, + "languages": [], + "name": "Search API", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/search_api2", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Search_Type_Specification_and_Mapping.json b/agency-indexes/DoE/Search_Type_Specification_and_Mapping.json new file mode 100644 index 00000000..bd0a3a8d --- /dev/null +++ b/agency-indexes/DoE/Search_Type_Specification_and_Mapping.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "Type transformation specifications for the KBase search system. This repo contains specifications for how Workspace objects will be indexed in various KBase environments. Each environment(prod, next, appdev and ci) has a dedicated subdirectory with a set of type and typemapping yaml files.", + "laborHours": 608.0, + "languages": [], + "name": "Search Type Specification and Mapping", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/search_index_specs", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Search_tool_plug-in:_imploements_latent_topic_feedback.json b/agency-indexes/DoE/Search_tool_plug-in:_imploements_latent_topic_feedback.json new file mode 100644 index 00000000..7f242cdc --- /dev/null +++ b/agency-indexes/DoE/Search_tool_plug-in:_imploements_latent_topic_feedback.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "IRIS is a search tool plug-in that is used to implement latent topic feedback for enhancing text navigation. It accepts a list of returned documents from an information retrieval wywtem that is generated from keyword search queries. Data is pulled directly from a topic information database and processed by IRIS to determine the most prominent and relevant topics, along with topic-ngrams, associated with the list of returned documents. User selected topics are then used to expand the query and presumabley refine the search results.", + "laborHours": 592.8, + "name": "Search tool plug-in: imploements latent topic feedback", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/iris", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Searchlight_Source_Code.json b/agency-indexes/DoE/Searchlight_Source_Code.json new file mode 100644 index 00000000..47363026 --- /dev/null +++ b/agency-indexes/DoE/Searchlight_Source_Code.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-15", + "metadataLastUpdated": "2024-03-15" + }, + "description": "SAND2024-01982O\nThe Searchlight Source Code is software for creating, managing, and dismantling experiments. It also is a simple web server that mimics an online training module with scripts to automate a client. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python", + "html", + "CSS", + "PHP" + ], + "name": "Searchlight Source Code", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Seccubus_V2.json b/agency-indexes/DoE/Seccubus_V2.json new file mode 100644 index 00000000..67d34566 --- /dev/null +++ b/agency-indexes/DoE/Seccubus_V2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "Seccubus automates regular vulnerability scans with various tools and aids security people in the fast analysis of its output, both on the first scan and on repeated scans. On repeated scan delta reporting ensures that findings only need to be judged when they first appear in the scan results or when their output changes.", + "laborHours": 128333.6, + "languages": [], + "name": "Seccubus V2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/Seccubus_v2", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Secondary_Pore_Network_Design_Optimization_Analytical_Diffusion_Model_for_Lithium_Ion_Battery.json b/agency-indexes/DoE/Secondary_Pore_Network_Design_Optimization_Analytical_Diffusion_Model_for_Lithium_Ion_Battery.json new file mode 100644 index 00000000..6e06c300 --- /dev/null +++ b/agency-indexes/DoE/Secondary_Pore_Network_Design_Optimization_Analytical_Diffusion_Model_for_Lithium_Ion_Battery.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-09-16", + "metadataLastUpdated": "2021-09-16" + }, + "description": "Fast ion transport along the electrode thickness is required for Lithium ion battery (LIB) to sustain continuous high-rate discharge or charge currents, which is a desired feature for the fast charging of electric vehicle batteries. Advance in LIB electrode manufacturing allows to control, to a certain extent, the electrode microstructure architecture in order to improve the macroscopic performances of these devices. For instance, several groups have experimentally tested architectures tailored specifically to increase the through plane ionic diffusion in regards for fast charge application by adding channels or groove-like large pores oriented along the electrode thickness. These voids do not replace the existing pores of the electrode microstructure but consist in a second, coarser, pore network, called the secondary pore network (SPN). The model quantifies the impact of SPN on ionic diffusion with a composite electrode through a simple analytical approach, considering various pore channel geometries and comparing to standard electrodes with identical gravimetric and identical volumetric specific theoretical capacity. The goal is to find optimal SPN design parameters according to three optimization objectives aiming to balance the improved overall through-plane, thanks to the coarse aligned channels, and the degraded in-plane diffusion, due to the porous matrix densification required to maintain gravimetric and volumetric specific theoretical capacity. The analytical model must be considered as a pre-screening tool to quickly investigate large design space, that can be refined later with more complex electrochemical CPU-expensive numerical models.", + "laborHours": 0.0, + "languages": [], + "name": "Secondary Pore Network Design Optimization Analytical Diffusion Model for Lithium Ion Battery", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Secondary_pore_network", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Secure_Design_and_Development_Cyber_Security_Capability_Maturity_Model\342\200\235__SD2-CM2_.json" "b/agency-indexes/DoE/Secure_Design_and_Development_Cyber_Security_Capability_Maturity_Model\342\200\235__SD2-CM2_.json" new file mode 100644 index 00000000..33815142 --- /dev/null +++ "b/agency-indexes/DoE/Secure_Design_and_Development_Cyber_Security_Capability_Maturity_Model\342\200\235__SD2-CM2_.json" @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-05-11", + "metadataLastUpdated": "2025-04-14" + }, + "description": "The \"Secure Design and Development Cyber Security Capability Maturity Model\" (SD2-CM2) allows electrical system managers to assess the maturity of their cybersecurity systems, including designs reflecting internet of things devices (IOT). The content provides best practices in the field and users can assess the level of their designs. Modules are \"Content\" and \"Infrastructure\"", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 3986352.0, + "languages": [], + "name": "Secure Design and Development Cyber Security Capability Maturity Model\u201d (SD2-CM2)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Secure_Grid_Data_Exchange__SGDX__Secure_Emergency_Management__SEM_.json b/agency-indexes/DoE/Secure_Grid_Data_Exchange__SGDX__Secure_Emergency_Management__SEM_.json new file mode 100644 index 00000000..4fdb878a --- /dev/null +++ b/agency-indexes/DoE/Secure_Grid_Data_Exchange__SGDX__Secure_Emergency_Management__SEM_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "terry.nielsen@gridbright.com" + }, + "date": { + "created": "2022-04-20", + "metadataLastUpdated": "2022-04-21" + }, + "description": "Grideon suite of Software as a Service (SaaS) is a highly secure cloud platform for the use case of Secure Resource Integration (SRI).", + "laborHours": 0.0, + "languages": [], + "name": "Secure Grid Data Exchange (SGDX) Secure Emergency Management (SEM)", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/sgdx/sgdx-gem", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Secure_Grid_Data_Exchange__SGDX__Secure_Grid_Collaboration__SGC_.json b/agency-indexes/DoE/Secure_Grid_Data_Exchange__SGDX__Secure_Grid_Collaboration__SGC_.json new file mode 100644 index 00000000..f75470a5 --- /dev/null +++ b/agency-indexes/DoE/Secure_Grid_Data_Exchange__SGDX__Secure_Grid_Collaboration__SGC_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "terry.nielsen@gridbright.com" + }, + "date": { + "created": "2022-04-20", + "metadataLastUpdated": "2022-04-21" + }, + "description": "Grideon suite of Software as a Service (SaaS) is a highly secure cloud platform for the use case of Secure Grid Collaboration (SGC).", + "laborHours": 0.0, + "languages": [], + "name": "Secure Grid Data Exchange (SGDX) Secure Grid Collaboration (SGC)", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/sgdx/sgdx-sgc", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Secure_IRC_Server.json b/agency-indexes/DoE/Secure_IRC_Server.json new file mode 100644 index 00000000..2049db05 --- /dev/null +++ b/agency-indexes/DoE/Secure_IRC_Server.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The IRCD is an IRC server that was originally distributed by the IRCD Hybrid developer team for use as a server in IRC message over the public Internet. By supporting the IRC protocol defined in the IRC RFC, IRCD allows the users to create and join channels for group or one-to-one text-based instant messaging. It stores information about channels (e.g., whether it is public, secret, or invite-only, the topic set, membership) and users (who is online and what channels they are members of). It receives messages for a specific user or channel and forwards these messages to the targeted destination. Since server-to-server communication is also supported, these targeted destinations may be connected to different IRC servers. Messages are exchanged over TCP connections that remain open between the client and the server. The IRCD is being used within the Pervasive Computing Collaboration Environment (PCCE) as the 'chat server' for message exchange over public and private channels. After an LBNLSecureMessaging(PCCE chat) client has been authenticated, the client connects to IRCD with its assigned nickname or 'nick.' The client can then create or join channels for group discussions or one-to-one conversations. These channels can have an initial mode of public or invite-only and the mode may be changed after creation. If a channel is public, any one online can join the discussion; if a channel is invite-only, users can only join if existing members of the channel explicitly invite them. Users can be invited to any type of channel and users may be members of multiple channels simultaneously. For use with the PCCE environment, the IRCD application (which was written in C) was ported to Linux and has been tested and installed under Linux Redhat 7.2. The source code was also modified with SSL so that all messages exchanged over the network are encrypted. This modified IRC server also verifies with an authentication server that the client is who he or she claims to be and that this user is authorized to ain access to the IRCD.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Secure IRC Server", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Secure_Information_Sharing.json b/agency-indexes/DoE/Secure_Information_Sharing.json new file mode 100644 index 00000000..c650e09b --- /dev/null +++ b/agency-indexes/DoE/Secure_Information_Sharing.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "We are developing a peer-to-peer system to support secure, location independent information sharing in the scientific community. Once complete, this system will allow seamless and secure sharing of information between multiple collaborators. The owners of information will be able to control how the information is stored, managed, and shared. In addition, users will have faster access to information updates within a collaboration. Groups collaborating on scientific experiments have a need to share information and data. This information and data is often represented in the form of files and database entries. In a typical scientific collaboration, there are many different locations where data would naturally be stored. This makes It difficult for collaborators to find and access the information they need. Our goal is to create a lightweight file-sharing system that makes it easy for collaborators to find and use the data they need. This system must be easy-to-use, easy-to-administer, and secure. Our information-sharing tool uses group communication, in particular the InterGroup protocols, to reliably deliver each query to all of the current participants in a scalable manner, without having to discover all of their identities. We will use the Secure Group Layer (SGL) and Akenti to provide security to the participants of our environment, SGL will provide confidentiality, integrity, authenticity, and authorization enforcement for the InterGroup protocols and Akenti will provide access control to other resources.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "Java 1.4 or higher" + ], + "name": "Secure Information Sharing", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Security_Catch_and_Release_Automation_Manager__SCRAM__v1.0.json b/agency-indexes/DoE/Security_Catch_and_Release_Automation_Manager__SCRAM__v1.0.json new file mode 100644 index 00000000..d415ef4e --- /dev/null +++ b/agency-indexes/DoE/Security_Catch_and_Release_Automation_Manager__SCRAM__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-17" + }, + "description": "This is a security automation tool heavily influenced by the tool written at NCSA https://github.com/ncsa/bhr-site.\n\nThe tool is a web interface that aims to centralize information on blocking malicious traffic. There is a list of currently blocked traffic, a place for other tools to automatically add traffic they deem malicious, as well as for human users to input blocks.\n\n* Logging and auditing, to determine who made what change and when\n* Automated expiration of changes (e.g. an exception is added for 2 weeks, after which time it will be removed)\n* Validation of changes and verification that the change has been applied\n* Fine-grained role-based access", + "laborHours": 2888.0, + "languages": [], + "name": "Security Catch and Release Automation Manager (SCRAM) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet-security/scram", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Seismic_Analysis_Code_2000.json b/agency-indexes/DoE/Seismic_Analysis_Code_2000.json new file mode 100644 index 00000000..16c5876e --- /dev/null +++ b/agency-indexes/DoE/Seismic_Analysis_Code_2000.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-07-05", + "metadataLastUpdated": "2022-07-06" + }, + "description": "The Seismic Analysis Code (SAC2000) is a general purpose interactive program designed for the study of sequential signals, especially time-series data. Emphasis has been placed on analysis tools used by research seismologists in the detailed study of seismic events. Analysis capabilities include general arithmetic operations, Fourier transforms, spectral estimation techniques, IIR and FIR filtering, signal stacking, decimation, interpolation, correlation, and seismic phase picking. SAC2000 also contains an extensive graphics capability. Versions are available for a wide variety of computer systems. SAC2000 was developed at Lawrence Livermore National Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "Seismic Analysis Code 2000", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SAC2000", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "07.10.8" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Seismic_Response_Processing_Module.json b/agency-indexes/DoE/Seismic_Response_Processing_Module.json new file mode 100644 index 00000000..b5f16fb8 --- /dev/null +++ b/agency-indexes/DoE/Seismic_Response_Processing_Module.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-10-30", + "metadataLastUpdated": "2023-10-30" + }, + "description": "The seismic response processing module is a Java based library that provides support for removing\ninstrument response signals from seismic recordings. The response module provides support for\nEvalResp, PZF, PAZ, FAP, PAZFIR, PAZFAP, FIRFAP, and CSS response types and parallel processing\nsupport for transfer operations. Additionally, the response module uses the JSR-363 units of\nmeasurement specification to allow for transfer to and from a wide range of units types to represent the\ntime-series.", + "laborHours": 0.0, + "languages": [], + "name": "Seismic Response Processing Module", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/response", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Seismic_Waves,_4th_order_accurate.json b/agency-indexes/DoE/Seismic_Waves,_4th_order_accurate.json new file mode 100644 index 00000000..8300246c --- /dev/null +++ b/agency-indexes/DoE/Seismic_Waves,_4th_order_accurate.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SW4 is a program for simulating seismic wave propagation on parallel computers. SW4 colves the seismic wave equations in Cartesian corrdinates. It is therefore appropriate for regional simulations, where the curvature of the earth can be neglected. SW4 implements a free surface boundary condition on a realistic topography, absorbing super-grid conditions on the far-field boundaries, and a kinematic source model consisting of point force and/or point moment tensor source terms. SW4 supports a fully 3-D heterogeneous material model that can be specified in several formats. SW4 can output synthetic seismograms in an ASCII test format, or in the SAC finary format. It can also present simulation information as GMT scripts, whixh can be used to create annotated maps. Furthermore, SW4 can output the solution as well as the material model along 2-D grid planes.", + "laborHours": 75817.6, + "name": "Seismic Waves, 4th order accurate", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/geodynamics/sw4", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Seismic_waveform_viewer,_processor_and_calculator.json b/agency-indexes/DoE/Seismic_waveform_viewer,_processor_and_calculator.json new file mode 100644 index 00000000..99dabc85 --- /dev/null +++ b/agency-indexes/DoE/Seismic_waveform_viewer,_processor_and_calculator.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "SWIFT is a computer code that is designed to do research level signal analysis on seismic waveforms, including visualization, filtering and measurement. LLNL is using this code, amplitude and global tomography efforts.", + "laborHours": 0.0, + "languages": [ + "JAVA 100%" + ], + "name": "Seismic waveform viewer, processor and calculator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/seismic-waveform-viewer-processor-and-calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Self-Configuring_Network_Monitor.json b/agency-indexes/DoE/Self-Configuring_Network_Monitor.json new file mode 100644 index 00000000..a6656c25 --- /dev/null +++ b/agency-indexes/DoE/Self-Configuring_Network_Monitor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "Self-Configuring Network Monitor (SCNM) is a passive monitoring that can collect packet headers from any point in a network path. SCNM uses special activation packets to automatically activate monitors deployed at the layer three ingress and egress routers of the wide-area network, and at critical points within the site networks. Monitoring output data is sent back to the application data source or destination host. No modifications are required to the application or network routing infrastructure in order to activate monitoring of traffic for an application. This ensures that the monitoring operation does not add a burden to the networks administrator.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Self-Configuring Network Monitor", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sella_Beta_Version_0.0.1.json b/agency-indexes/DoE/Sella_Beta_Version_0.0.1.json new file mode 100644 index 00000000..b4c33be8 --- /dev/null +++ b/agency-indexes/DoE/Sella_Beta_Version_0.0.1.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-04-11", + "metadataLastUpdated": "2019-04-12" + }, + "description": "Sella is a tool for locating and optimizing first order saddle points of arbitrary functions, with an emphasis on the potential energy surfaces of molecules. Sella uses ASE to interface with a variety of electronic structure theory packages. Sella can also be used to minimize functions, or find higher-order saddle points.", + "laborHours": 1869.6, + "languages": [], + "name": "Sella Beta Version 0.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zadorlab/sella", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "Beta Version 0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Semi-analytic_model_of_magnetized_liner_inertial_fusion.json b/agency-indexes/DoE/Semi-analytic_model_of_magnetized_liner_inertial_fusion.json new file mode 100644 index 00000000..75bfcb8b --- /dev/null +++ b/agency-indexes/DoE/Semi-analytic_model_of_magnetized_liner_inertial_fusion.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-09", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The code that was developed is called SAMM (Semi-Analytic MagLIF Model). In 2015, McBride and Slutz published all of the equations that are solved by the code in the original SAMM paper: R. D. McBride and S. A. Slutz, ?A semi-analytic model of magnetized liner inertial fusion?, Phys. Plasmas 22, 052708 (2015); http://doi.org/10.1063/1.4918953. The SAMM code is now implemented in both the MATLAB and Python programming languages. Students from multiple universities have requested copies of the code so that they can become more familiar with the MagLIF concept. We would like to seek an open-source solution. There is no market value to this code, as there are plenty of more sophisticated simulation codes already available; SAMM is merely a simplified model that is purely for educational purposes. In fact, at least one graduate student (from the University of California, San Diego) has already implemented and published his own modified version of the model: J. Narkis, H. U. Rahman, J. C. Valenzuela, F. Conti, R. D. McBride, D. Venosa, and F. N. Beg, ?A semi-analytic model of gas-puff liner-on-target magneto-inertial fusion?, Phys. Plasmas 26, 032708 (2019); https://doi.org/10.1063/1.5086056. SAND2020-12244 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 4438.4, + "languages": [ + "Python" + ], + "name": "Semi-analytic model of magnetized liner inertial fusion", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pysamm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sensor_Data_Analytics_and_Data_Quality_Assessment_Software.json b/agency-indexes/DoE/Sensor_Data_Analytics_and_Data_Quality_Assessment_Software.json new file mode 100644 index 00000000..53491a54 --- /dev/null +++ b/agency-indexes/DoE/Sensor_Data_Analytics_and_Data_Quality_Assessment_Software.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-09-10", + "metadataLastUpdated": "2025-02-24" + }, + "description": "The proposed framework derives a set of\nquality metrics to provide critical insights into and tracking of grid operations, sensor performance, sensor longevity, and\nevent statistics. Power grid engineers can utilize this information to identify problems with existing sensor locations and\nproblematic power grid assets including generators, transmission lines, load centers, and substations. This information\ncan also be used to identify unexpected/abnormal behavior of power grid components, improve power grid observability,\nand operational monitoring, and thus enhance real-time decision-making support system. Power grid planners can utilize\nthis information to augment existing sensing architecture with new sensors and improve the observability of the network.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Sensor Data Analytics and Data Quality Assessment Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sensor_Fish_Communicator.json b/agency-indexes/DoE/Sensor_Fish_Communicator.json new file mode 100644 index 00000000..060da456 --- /dev/null +++ b/agency-indexes/DoE/Sensor_Fish_Communicator.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The Sensor Fish collects information that can be used to evaluate conditions encountered by juvenile salmonids and other fish as they pass through hydroelectric dams on their way to the ocean. Sensor Fish are deployed in turbines, spillways, and sluiceways and measure changes in pressure, angular rate of change, and linear acceleration during passage. The software is need to make Sensor Fish fully functional and easy to use. Sensor Fish Communicator (SFC) links to Sensor Fish, allowing users to control data collection settings and download data. It may also be used to convert native raw data (.raw2) files into Comma Separated Variable (.csv) files and plot the results. The multiple capabilities of the SFC allow hardware communication, data conversion, and data plotting with one application.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "c++" + ], + "name": "Sensor Fish Communicator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sensor_Suitcase_Tablet_Software.json b/agency-indexes/DoE/Sensor_Suitcase_Tablet_Software.json new file mode 100644 index 00000000..768795a2 --- /dev/null +++ b/agency-indexes/DoE/Sensor_Suitcase_Tablet_Software.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The Retrocommissioning Sensor Suitcase is targeted for use in small commercial buildings of less than 50,000 square feet of floor space that regularly receive basic services such as maintenance and repair, but don't have in-house energy management staff or buildings experts. The Suitcase is designed to be easy-to-use by building maintenance staff, or other professionals such as telecom and alarm technicians. The software in the hand-held is designed to guide the staff to input the building and system information, deploy the sensors in proper location, configure the sensor hardware, and start the data collection.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "MS" + ], + "name": "Sensor Suitcase Tablet Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sequedex_V2.json b/agency-indexes/DoE/Sequedex_V2.json new file mode 100644 index 00000000..10506f53 --- /dev/null +++ b/agency-indexes/DoE/Sequedex_V2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-20" + }, + "description": "Sequedex is computer software to rapidly assign phylogeny and function to short sequences of nucleic acid or protein. In addition, Sequedex comprises functions required to generate underlying data modules as well as tools for analyzing assignments in a variety of contexts.", + "laborHours": 8724.8, + "languages": [], + "name": "Sequedex V2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/sequedex-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SequenceSetUtils.json b/agency-indexes/DoE/SequenceSetUtils.json new file mode 100644 index 00000000..7debd61f --- /dev/null +++ b/agency-indexes/DoE/SequenceSetUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"SequenceSetUtils\" developed by KBase. This is a KBase module generated by the KBase Software Development Kit (SDK).", + "laborHours": 866.4, + "languages": [], + "name": "SequenceSetUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/SequenceSetUtils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sequence_ID_Map__SeqIDMap__v1.0.json b/agency-indexes/DoE/Sequence_ID_Map__SeqIDMap__v1.0.json new file mode 100644 index 00000000..13543441 --- /dev/null +++ b/agency-indexes/DoE/Sequence_ID_Map__SeqIDMap__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "This is a web service that allows users to request an identifier for a sequence in a specific database, given another identifier for the same sequence with respect to another given database. This process is called ID mapping. It's a minimalist service (fast, no database server) that will be significantly easier to use in a container environment.", + "laborHours": 0.0, + "languages": [], + "name": "Sequence ID Map (SeqIDMap) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/jgi-kbase/seqidmap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sequential_Training_ToolKit_-_STTK.json b/agency-indexes/DoE/Sequential_Training_ToolKit_-_STTK.json new file mode 100644 index 00000000..297ef4c3 --- /dev/null +++ b/agency-indexes/DoE/Sequential_Training_ToolKit_-_STTK.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-09-01", + "metadataLastUpdated": "2021-09-21" + }, + "description": "Sequential Training ToolKit, or STTK, is a software toolkit plugin for the Unity development platform that enables software developers to easily develop structured Sequential Training applications for gaming and extended reality (XR) environments. STTK is architected to easily import the toolkit as a plugin for the Unity platform and then interact with the graphical user interface (GUI) for drag-and-drop functionality. STTK also includes easy add-on plugins for Prefabs and auto-builds a State Machine. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-3059 O", + "laborHours": 0.0, + "languages": [ + "C#" + ], + "name": "Sequential Training ToolKit - STTK", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/STTK", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sequentially_Executed_Model_Evaluation_Framework.json b/agency-indexes/DoE/Sequentially_Executed_Model_Evaluation_Framework.json new file mode 100644 index 00000000..7426fb80 --- /dev/null +++ b/agency-indexes/DoE/Sequentially_Executed_Model_Evaluation_Framework.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Provides a message passing framework between generic input, model and output drivers, and specifies an API for developing such drivers. Also provides batch and real-time controllers which step the model and 1/0 through the time domain (or other discrete domain), and sample 1/0 drivers. This is a Framework library framework, and does not, itself, solve any problems or execute any modelling. The SeMe framework aids in development of models which operate on sequential information, such as time-series, where evaluation is based on prior results combined with new data for this iteration. Ha) applications in quality monitoring, and was developed as part of the CANARY-EDS software, where real-time water quality data is being analyzed", + "laborHours": 4772.8, + "languages": [ + "Java", + "Perl", + "HTML", + "TeX" + ], + "name": "Sequentially Executed Model Evaluation Framework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seme-framework", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sequoia_Messaging_Rate_Benchmark.json b/agency-indexes/DoE/Sequoia_Messaging_Rate_Benchmark.json new file mode 100644 index 00000000..05b3ee1f --- /dev/null +++ b/agency-indexes/DoE/Sequoia_Messaging_Rate_Benchmark.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The purpose of this benchmark is to measure the maximal message rate of a single compute node. The first num_cores ranks are expected to reside on the 'core' compute node for which message rate is being tested. After that, the next num_nbors ranks are neighbors for the first core rank, the next set of num_nbors ranks are neighbors for the second core rank, and so on. For example, testing an 8-core node (num_cores = 8) with 4 neighbors (num_nbors = 4) requires 8 + 8 * 4 - 40 ranks. The first 8 of those 40 ranks are expected to be on the 'core' node being benchmarked, while the rest of the ranks are on separate nodes.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Sequoia Messaging Rate Benchmark", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/sequoia-messaging-rate-benchmark", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Serial2Parallel.json b/agency-indexes/DoE/Serial2Parallel.json new file mode 100644 index 00000000..56d4d286 --- /dev/null +++ b/agency-indexes/DoE/Serial2Parallel.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "In the era of machine learning, we often need to run the same code/script many times with little or no variations (e.g., performance evaluation, data preprocessing, data generation, hyperparameter tuning, etc.). It is not a problem when you just need to do that a few times, but when the number of repetitions becomes very large, it can be a daunting task. The code \u201cSerial2Parallel\u201d provides an easy way for users to be able to run many numbers of any serial code/scripts in a parallel manner across multiple nodes in an message passing interface (MPI) cluster. The code includes the server program that deals with task pool management and client program that processes task. The server gets the tasks ready and waits for clients' connections. The client code pulls tasks from the server and processes them. The client code will run in parallel.", + "laborHours": 136.8, + "languages": [ + "Python 3" + ], + "name": "Serial2Parallel", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/liza183/Serial2Parallel", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/liza183/Serial2Parallel", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Serial_to_Parallel:_A_Monte_Carlo_Operation.json b/agency-indexes/DoE/Serial_to_Parallel:_A_Monte_Carlo_Operation.json new file mode 100644 index 00000000..9d7f8744 --- /dev/null +++ b/agency-indexes/DoE/Serial_to_Parallel:_A_Monte_Carlo_Operation.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "This tutorial covers how to write a parallel program to calculate \u03c0 using the Monte Carlo method with MPI and OpenMP\n", + "laborHours": 197.6, + "name": "Serial to Parallel: A Monte Carlo Operation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/Serial-to-Parallel--Monte-Carlo-Pi", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Service-Poke.json b/agency-indexes/DoE/Service-Poke.json new file mode 100644 index 00000000..ca501002 --- /dev/null +++ b/agency-indexes/DoE/Service-Poke.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Service-Poke is a system which manages running services ensuring only one copy is running and potentially up to one more copy is marked for future execution.", + "laborHours": 562.4, + "name": "Service-Poke", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/service-poke", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ServiceNow_CrayPort_Integration_v2.1.5.json b/agency-indexes/DoE/ServiceNow_CrayPort_Integration_v2.1.5.json new file mode 100644 index 00000000..9285f972 --- /dev/null +++ b/agency-indexes/DoE/ServiceNow_CrayPort_Integration_v2.1.5.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-04", + "metadataLastUpdated": "2019-12-04" + }, + "description": "The National Energy Research Scientific Computing Center (NERSC) is the primary scientific computing facility for the Office of Science in the U.S. Department of Energy. NERSC houses top-ranked Cray supercomputers, and our staff works very closely with on-site Cray engineers, submitting 75 Cray cases per month on average. Until recently, submitting a Cray case was only possible by phone or email, and all subsequent updates were delivered manually. This process led to delays, errors during manual data entry, and greatly increased incident processing and resolution time. In 2018, NERSC deployed an API-based bidirectional integration that allowed to submit and update Cray cases directly from our Incident Management platform, thus streamlining our 24x7 operations and enhancing communication between our engineering teams. This solution is applicable to any Incident Management platform.", + "laborHours": 5532.8, + "languages": [], + "name": "ServiceNow/CrayPort Integration v2.1.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/crayport/crayport-app-code.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ServiceWizard.json b/agency-indexes/DoE/ServiceWizard.json new file mode 100644 index 00000000..ca71384a --- /dev/null +++ b/agency-indexes/DoE/ServiceWizard.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-10", + "metadataLastUpdated": "2020-08-10" + }, + "description": "KBase Service Wizard to manage dynamic services.", + "laborHours": 1383.2, + "languages": [], + "name": "ServiceWizard", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/service_wizard", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SetAPI.json b/agency-indexes/DoE/SetAPI.json new file mode 100644 index 00000000..8ae6d53d --- /dev/null +++ b/agency-indexes/DoE/SetAPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-08", + "metadataLastUpdated": "2020-09-08" + }, + "description": "Dynamic service for managing sets.", + "laborHours": 3648.0, + "languages": [], + "name": "SetAPI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/SetAPI", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ShadeLab_RefSoil_plasmids.json b/agency-indexes/DoE/ShadeLab_RefSoil_plasmids.json new file mode 100644 index 00000000..b4873020 --- /dev/null +++ b/agency-indexes/DoE/ShadeLab_RefSoil_plasmids.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Plasmids harbor transferable genes that contribute to the functional repertoire of microbial communities, yet their contributions to metagenomes are often overlooked. Environmental plasmids have the potential to spread antibiotic resistance to clinical microbial strains. In soils, high microbiome diversity and high variability in plasmid characteristics present a challenge for studying plasmids. To improve the understanding of soil plasmids, we present RefSoil+, a database containing plasmid sequences from 922 soil microorganisms. Soil plasmids were larger than other described plasmids, which is a trait associated with plasmid mobility. There was a weak relationship between chromosome size and plasmid size and no relationship between chromosome size and plasmid number, suggesting that these genomic traits are independent in soil. We used RefSoil+ to inform the distributions of antibiotic resistance genes among soil microorganisms compared to those among nonsoil microorganisms. Soil-associated plasmids, but not chromosomes, had fewer antibiotic resistance genes than other microorganisms. These data suggest that soils may offer limited opportunity for plasmid-mediated transfer of described antibiotic resistance genes. RefSoil+ can serve as a reference for the diversity, composition, and host associations of plasmid-borne functional genes in soil, a utility that will be enhanced as the database expands. Our study improves the understanding of soil plasmids and provides a resource for assessing the dynamics of the genes that they carry, especially genes conferring antibiotic resistances.", + "laborHours": 304.0, + "languages": [], + "name": "ShadeLab/RefSoil_plasmids", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ShadeLab/RefSoil_plasmids", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Shadow.json b/agency-indexes/DoE/Shadow.json new file mode 100644 index 00000000..ca172c52 --- /dev/null +++ b/agency-indexes/DoE/Shadow.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2021-03-05" + }, + "description": "Semi-supervised machine learning via consistency regularization", + "laborHours": 820.8, + "languages": [], + "name": "Shadow", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/shadow", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/shadow", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ShareAnalytics.json b/agency-indexes/DoE/ShareAnalytics.json new file mode 100644 index 00000000..58154599 --- /dev/null +++ b/agency-indexes/DoE/ShareAnalytics.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "ShareAnalytics is a lightweight extensible platform for collaborative data analytics and facility characterization via Non-intrusive Load Monitoring (NILM). It consists of three core components: a full stack web application, a dashboard tool for analyzing streaming data and a High Performance Computing (HPC) cluster leveraging slurm for resource management to perform real time analysis. The entire framework is implemented in Docker for ease of deployment and to allow the user to test the platform before making a significant investment in hardware if they require additional computing resources. While many other platforms for analyzing streaming data exists, ShareAnalytics is unique in that HPC capabilities and facility characterization via scored analytics are fully integrated into the platform.", + "laborHours": 8755.2, + "languages": [ + "JavaScript / Bash" + ], + "name": "ShareAnalytics", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/ShareAnalytics", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Shared_Component_Library_-_Utilities.json b/agency-indexes/DoE/Shared_Component_Library_-_Utilities.json new file mode 100644 index 00000000..6e53e0ac --- /dev/null +++ b/agency-indexes/DoE/Shared_Component_Library_-_Utilities.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This license is for a computer-science focused subset of the XCP-3 developed shared component libraries (SHACL), referred to as SHACL Utilities. The SHACL Utilities product is a collection of repositories developed to help XCP-3 developers quickly write maintainable and efficient computational physics software. This collection of libraries provides software abstractions, algorithms, and tools based on modern software practices and design idioms, while supporting interfaces to other programming languages when required by production codes. The libraries are semi-independent repositories and are developed with an emphasis on performance and sharing code between applications.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Shared Component Library - Utilities", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Shasta_Wrapper.json b/agency-indexes/DoE/Shasta_Wrapper.json new file mode 100644 index 00000000..0024b472 --- /dev/null +++ b/agency-indexes/DoE/Shasta_Wrapper.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "shasta wrapper was written as an interface with which to manage clusters running CSM (Cray System Management) with the purpose being: * Showcase the shortcomings of the provided Cray System Management software to the vendor * Provide practical and easy to use tool to manage a clsuter running Cray System Management", + "laborHours": 0.0, + "languages": [], + "name": "Shasta Wrapper", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/shasta_wrapper", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ShiftNMFk_1.2.json b/agency-indexes/DoE/ShiftNMFk_1.2.json new file mode 100644 index 00000000..48c1fc85 --- /dev/null +++ b/agency-indexes/DoE/ShiftNMFk_1.2.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The ShiftNMFk1.2 code, or as we call it, GreenNMFk, represents a hybrid algorithm combining unsupervised adaptive machine learning and Green's function inverse method. GreenNMFk allows an efficient and high performance de-mixing and feature extraction of a multitude of nonnegative signals that change their shape propagating through the medium. The signals are mixed and recorded by a network of uncorrelated sensors. The code couples Non-negative Matrix Factorization (NMF) and inverse-analysis Green's functions method. GreenNMF synergistically performs decomposition of the recorded mixtures, finds the number of the unknown sources and uses the Green's function of the governing partial differential equation to identify the unknown sources and their charecteristics. GreenNMF can be applied directly to any problem controlled by a known partial-differential parabolic equation where mixtures of an unknown number of sources are measured at multiple locations. Full GreenNMFk method is a subject LANL U.S. Patent application S133364.000 August, 2017. The ShiftNMFk 1.2 version here is a toy version of this method that can work with a limited number of unknown sources (4 or less).", + "laborHours": 760.0, + "languages": [ + "Matlab" + ], + "name": "ShiftNMFk 1.2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/rNMF/HNMF/blob/master/License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rNMF/HNMF", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Shock_Mini_Container_Image.json b/agency-indexes/DoE/Shock_Mini_Container_Image.json new file mode 100644 index 00000000..b739ccf2 --- /dev/null +++ b/agency-indexes/DoE/Shock_Mini_Container_Image.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-18", + "metadataLastUpdated": "2020-08-18" + }, + "description": "An object store for scientific data. Shock is a platform to support computation, storage, and distribution. Designed from the ground up to be fast, scalable, fault tolerant, federated. Shock is RESTful. Accessible from desktops, HPC systems, exotic hardware, the cloud and your smartphone. Shock is for scientific data. One of the challenges of large volume scientific data is that without often complex metadata it is of little to no value. Shock allows storage and querying of complex metadata. Shock is a data management system. The long term goals of Shock include the ability to annotate, anonymize, convert, filter, perform quality control, and statically subsample at line speed bioinformatics sequence data. Extensible plug-in architecture is in development.", + "laborHours": 5502.4, + "languages": [], + "name": "Shock Mini Container Image", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/Shock", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Shock_to_S3_Scripts.json b/agency-indexes/DoE/Shock_to_S3_Scripts.json new file mode 100644 index 00000000..20636b2f --- /dev/null +++ b/agency-indexes/DoE/Shock_to_S3_Scripts.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "Scripts for moving / transforming KBase data files and database records as part of the Shock to S3 data storage conversion.", + "laborHours": 91.2, + "languages": [], + "name": "Shock to S3 Scripts", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/shockToS3Scripts", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sidekick.json b/agency-indexes/DoE/Sidekick.json new file mode 100644 index 00000000..c8ae77ed --- /dev/null +++ b/agency-indexes/DoE/Sidekick.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "oeschts@ornl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2021-09-23" + }, + "description": "To reduce hand/wrist pain from frequent computer use I decided to create a program that will convert voice to common keyboard/mouse actions in order to reduce clicks/keypresses. It is not intended to replace the keyboard and mouse, but rather to reduce their use, hence the name Sidekick. Sidekick handles transcription, mouse movement/click/wheel, and common commands.\n", + "laborHours": 0.0, + "languages": [], + "name": "Sidekick", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/oeschsec/Sidekick---voice-controlled-keyboard-and-mouse", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sidekiq_DSP_v._0.4.json b/agency-indexes/DoE/Sidekiq_DSP_v._0.4.json new file mode 100644 index 00000000..a152cb45 --- /dev/null +++ b/agency-indexes/DoE/Sidekiq_DSP_v._0.4.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-05-10", + "metadataLastUpdated": "2019-05-13" + }, + "description": "This is a follow on to a subset of SCR#2291.0, and represents a set of FPGA and Linux driver software that serves to enhance the Epiq Solutions Sidekiq line of products with very standard and well defined digital signal processing capabilities that are found on other such software defined radio hardware. This includes timed command support, sub-band tuners, and other generic DSP capabilities.\nSAND2019-3719 M", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "Sidekiq DSP v. 0.4", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 0.4" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sight_Version_0.1.json b/agency-indexes/DoE/Sight_Version_0.1.json new file mode 100644 index 00000000..6116fa58 --- /dev/null +++ b/agency-indexes/DoE/Sight_Version_0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Enables applications to emit log information into an output file and produced a structured visual summary of the log data, as well as various statistical analyses of it. This makes it easier for developers to understand the behavior of their applications.", + "laborHours": 170893.6, + "name": "Sight Version 0.1", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bronevet/sight", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sign_Drawings__Electronic_Signatures_.json b/agency-indexes/DoE/Sign_Drawings__Electronic_Signatures_.json new file mode 100644 index 00000000..defb82a2 --- /dev/null +++ b/agency-indexes/DoE/Sign_Drawings__Electronic_Signatures_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "Software is used to apply digital signatures to pdf drawings. The signatures applied must be consistent in role, size and placement on the pdf drawings. The software provides the ability to process these signatures in a batch mode, signing multiple pdf drawings, selectable by either folder and/or file selections.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Sign Drawings (Electronic Signatures)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SignalGen.json b/agency-indexes/DoE/SignalGen.json new file mode 100644 index 00000000..f6960ae5 --- /dev/null +++ b/agency-indexes/DoE/SignalGen.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-01-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL contribution to project managed by federal agency. SignalGen is a software application that generates synthetic RDF graphs that satisfy the constraints specified in a search template. The purpose of this tool is most to aid in the development of the graph search engine and ensure it is able to find known graph patterns.", + "laborHours": 0.0, + "languages": [], + "name": "SignalGen", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/signalgen", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Silo.json b/agency-indexes/DoE/Silo.json new file mode 100644 index 00000000..64e0b74f --- /dev/null +++ b/agency-indexes/DoE/Silo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-09-30", + "metadataLastUpdated": "2020-10-08" + }, + "description": "Silo is a library for reading and writing a wide variety of scientific data to binary, disk files. The files Silo produces and the data within them can be easily shared and exchanged between wholly independently developed applications running on disparate computing platforms. Consequently, Silo facilitates the development of general purpose tools for processing scientific data. One of the more popular tools that process Silo data files is the VisIt visualization tool.", + "homepageURL": "https://wci.llnl.gov/simulation/computer-codes/silo", + "laborHours": 110929.6, + "languages": [], + "name": "Silo", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://wci.llnl.gov/simulation/computer-codes/silo", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SimApp_1.8.x.json b/agency-indexes/DoE/SimApp_1.8.x.json new file mode 100644 index 00000000..6bd0213f --- /dev/null +++ b/agency-indexes/DoE/SimApp_1.8.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "System for converting DESIRE (Direct Executing Simulation in Real Time) simulation models to executable code models (C# / C++). These converted models are used as the basis for 2 products, one of which is the focus of this review: an engineering design interface for Fissile Solution Systems. ModelConverter.exe (C#) converts DESIRE model inputs to a C++ plug-in subclass. SimApp.exe (C# / C++) has a C++ dll that is a numerical integration engine that the Converted models plug into. The engineering design interface is a C# GUI that calls on the C++ dll to execute a particular converted model. The GUI allows the user to specify the length of a simulation, run the simulation, view data plots and data tables. Stability plots may also be produced and manipulated. The engineering design interface will be released as source code and executable; the model converter source is also intended for release.", + "laborHours": 13710.4, + "name": "SimApp 1.8.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/determan/SimApp1.8x/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/determan/SimApp1.8x.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simple_Example_of_Backtest_Overfitting__SEBO_.json b/agency-indexes/DoE/Simple_Example_of_Backtest_Overfitting__SEBO_.json new file mode 100644 index 00000000..3b96eb06 --- /dev/null +++ b/agency-indexes/DoE/Simple_Example_of_Backtest_Overfitting__SEBO_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "In the field of mathematical finance, a \"backtest\" is the usage of historical market data to assess the performance of a proposed trading strategy. It is a relatively simple matter for a present-day computer system to explore thousands, millions or even billions of variations of a proposed strategy, and pick the best performing variant as the \"optimal\" strategy \"in sample\" (i.e., on the input dataset). Unfortunately, such an \"optimal\" strategy often performs very poorly \"out of sample\" (i.e. on another dataset), because the parameters of the invest strategy have been oversit to the in-sample data, a situation known as \"backtest overfitting\". While the mathematics of backtest overfitting has been examined in several recent theoretical studies, here we pursue a more tangible analysis of this problem, in the form of an online simulator tool. Given a input random walk time series, the tool develops an \"optimal\" variant of a simple strategy by exhaustively exploring all integer parameter values among a handful of parameters. That \"optimal\" strategy is overfit, since by definition a random walk is unpredictable. Then the tool tests the resulting \"optimal\" strategy on a second random walk time series. In most runs using our online tool, the \"optimal\" strategy derived from the first time series performs poorly on the second time series, demonstrating how hard it is not to overfit a backtest. We offer this online tool, \"Simple Example of Backtest Overfitting (SEBO)\", to facilitate further research in this area.", + "homepageURL": "http://datagrid.lbl.gov/backtest", + "laborHours": 0.0, + "languages": [ + "Phython 2.7" + ], + "name": "Simple Example of Backtest Overfitting (SEBO)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://datagrid.lbl.gov/backtest", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://datagrid.lbl.gov/backtest", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simple_Linux_Utility_for_Resource_Management.json b/agency-indexes/DoE/Simple_Linux_Utility_for_Resource_Management.json new file mode 100644 index 00000000..cfdf6fb1 --- /dev/null +++ b/agency-indexes/DoE/Simple_Linux_Utility_for_Resource_Management.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SLURM is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small computer clusters. As a cluster resource manager, SLURM has three key functions. First, it allocates exclusive and/or non exclusive access to resources (compute nodes) to users for some duration of time so they can perform work. Second, it provides a framework for starting, executing, and monitoring work (normally a parallel job) on the set of allciated nodes. Finally, it arbitrates conflicting requests for resouces by managing a queue of pending work.", + "laborHours": 405900.8, + "name": "Simple Linux Utility for Resource Management", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/schedmd/slurm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simple_Ontology_Format__SOFT_.json b/agency-indexes/DoE/Simple_Ontology_Format__SOFT_.json new file mode 100644 index 00000000..6d0db8c6 --- /dev/null +++ b/agency-indexes/DoE/Simple_Ontology_Format__SOFT_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Simple Ontology Format (SOFT) library and file format specification provides a set of simple tools for developing and maintaining ontologies. The library, implemented as a perl module, supports parsing and verification of the files in SOFt format, operations with ontologies (adding, removing, or filtering of entities), and converting of ontologies into other formats. SOFT allows users to quickly create ontologies using only a basic text editor, verify it, and portray it in a graph layout system using customized styles.", + "laborHours": 684.0, + "name": "Simple Ontology Format (SOFT)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sorokine/SOFT/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sorokine/SOFT", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simple_Supernova_Light-Curve_Code.json b/agency-indexes/DoE/Simple_Supernova_Light-Curve_Code.json new file mode 100644 index 00000000..1c608eaa --- /dev/null +++ b/agency-indexes/DoE/Simple_Supernova_Light-Curve_Code.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "This is a one-temperature diffusion code designed to model supernova explosions.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Simple Supernova Light-Curve Code", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simple_and_Flexible_Scene_Graph.json b/agency-indexes/DoE/Simple_and_Flexible_Scene_Graph.json new file mode 100644 index 00000000..c640a66a --- /dev/null +++ b/agency-indexes/DoE/Simple_and_Flexible_Scene_Graph.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The system implements a flexible and extensible scene graph for the visualization and analysis of scientific information.", + "laborHours": 0.0, + "languages": [], + "name": "Simple and Flexible Scene Graph", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/simple-and-flexible-scene-graph", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simple_rANDom_wALk_simulation.json b/agency-indexes/DoE/Simple_rANDom_wALk_simulation.json new file mode 100644 index 00000000..d8e9cca4 --- /dev/null +++ b/agency-indexes/DoE/Simple_rANDom_wALk_simulation.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SANDAL is a particle-mesh simulation mini-app. The simple simulated physics propagates a set of particles in a constant, 2D wind field with Gaussian turbulence. SANDAL demonstrates the feasibility of formulating a computational physics problem using an alternative, modern design. Specifically, it is implemented using relational tables and queries, rather than array-based data model. It also is implemented with functional language design and cloud deployment, Scala and Apache Spark, rather than Fortran and MPI+X.", + "laborHours": 456.0, + "name": "Simple rANDom wALk simulation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/Sandal/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/Sandal", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simple_utility_for_creat1n1_and_signing_SSL_certificates..json b/agency-indexes/DoE/Simple_utility_for_creat1n1_and_signing_SSL_certificates..json new file mode 100644 index 00000000..48df1faf --- /dev/null +++ b/agency-indexes/DoE/Simple_utility_for_creat1n1_and_signing_SSL_certificates..json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-07-20", + "metadataLastUpdated": "2018-07-20" + }, + "description": "Generally, for encrypted communication to occur, a root trust must be established (usually In the form of a certificate authority) and used to sign communlcatln1 component's certificates that are used to perform encryption. This process ls rather Involved In a number of manual steps with arcane command syntax. Certlpy wraps the standard Python PyOpenSSL library to simplify the calls to create the above mentioned PKI (public key infrastructure) with both a command line and programming Interface. Certlpy was orlglnally created to automate and manage PKI within the open source JupyterHub project so that It could be deployed safely In Uvennore Computing. JupyterHub Is a collection of software components enabling Interactive python notebooks and reproducible science. To ensure secure communication throuahout, Certlpy signs and Issues certs to each component: enabling encryption and authentication (SSL). ", + "laborHours": 380.0, + "languages": [], + "name": "Simple utility for creat1n1 and signing SSL certificates.", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/certipy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simplex_Design_for_Stochastic_Simulations_and_Agent_Based_Models.json b/agency-indexes/DoE/Simplex_Design_for_Stochastic_Simulations_and_Agent_Based_Models.json new file mode 100644 index 00000000..060da554 --- /dev/null +++ b/agency-indexes/DoE/Simplex_Design_for_Stochastic_Simulations_and_Agent_Based_Models.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-02", + "metadataLastUpdated": "2019-12-02" + }, + "description": "Simplexdesign is a small collection of tools for the design of statistical experiments on Agent \nBased Models.\n\nIt includes a coordinate exchange algorithm for homogeneous agents, and more generally any simplex. \n\nThere is also an optimization algorithm for the case with multiple classes of homogeneous agents.", + "laborHours": 136.8, + "languages": [], + "name": "Simplex Design for Stochastic Simulations and Agent Based Models", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/simplexdesign", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simplified_Interface_to_Complex_Memory_Hierarchies_1.x.json b/agency-indexes/DoE/Simplified_Interface_to_Complex_Memory_Hierarchies_1.x.json new file mode 100644 index 00000000..10692d1b --- /dev/null +++ b/agency-indexes/DoE/Simplified_Interface_to_Complex_Memory_Hierarchies_1.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Memory systems are expected to get evermore complicated in the coming years, and it isn't clear exactly what form that complexity will take. On the software side, a simple, flexible way of identifying and working with memory pools is needed. Additionally, most developers seek code portability and do not want to learn the intricacies of complex memory. Hence, we believe that a library for interacting with complex memory systems should expose two kinds of abstraction: First, a low-level, mechanism-based interface designed for the runtime or advanced user that wants complete control, with its focus on simplified representation but with all decisions left to the caller. Second, a high-level, policy-based interface designed for ease of use for the application developer, in which we aim for best-practice decisions based on application intent. We have developed such a library, called SICM: Simplified Interface to Complex Memory.", + "laborHours": 17829.6, + "name": "Simplified Interface to Complex Memory Hierarchies 1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SICM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simulacrum:_The_LCLS_Accelerator_Simulator.json b/agency-indexes/DoE/Simulacrum:_The_LCLS_Accelerator_Simulator.json new file mode 100644 index 00000000..f8e1124b --- /dev/null +++ b/agency-indexes/DoE/Simulacrum:_The_LCLS_Accelerator_Simulator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-06-16", + "metadataLastUpdated": "2022-06-16" + }, + "description": "Simulacrum is a system for simulating the LCLS accelerator and its control system.", + "laborHours": 0.0, + "languages": [], + "name": "Simulacrum: The LCLS Accelerator Simulator", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/simulacrum/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/simulacrum", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simulated_5g_Network_Traffic_Dataset.json b/agency-indexes/DoE/Simulated_5g_Network_Traffic_Dataset.json new file mode 100644 index 00000000..5258f662 --- /dev/null +++ b/agency-indexes/DoE/Simulated_5g_Network_Traffic_Dataset.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2022-08-11", + "metadataLastUpdated": "2023-03-07" + }, + "description": "This is a dataset of 5G network traffic for use with machine learning tools to benchmark attack detection capabilities for multiple different models. The dataset contains simulated normal and attack 5G network traffic. There is no software in this dataset, only simulated network traffic data.", + "laborHours": 0.0, + "languages": [], + "name": "Simulated 5g Network Traffic Dataset", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/5GAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simulation_Environment_For_Radiotherapy_Applications.json b/agency-indexes/DoE/Simulation_Environment_For_Radiotherapy_Applications.json new file mode 100644 index 00000000..92888001 --- /dev/null +++ b/agency-indexes/DoE/Simulation_Environment_For_Radiotherapy_Applications.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-07-19", + "metadataLastUpdated": "2024-05-07" + }, + "description": "SERA is a simulation environment for planning three-dimensional neutron capture therapy. SERA can allows creating models of the geometry of the tumor and surrounding tissue from CT or MRI data, and then planning and simulating the treatment of the tumor with Boron Neutron Capture Therapy. Boron Neutron Capture Therapy uses the combination of a boron containing drug and a neutron source to treat a tumor.", + "laborHours": 0.0, + "languages": [ + "C", + "Fortran" + ], + "name": "Simulation Environment For Radiotherapy Applications", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/SERA", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simulation_INsight_and_Analysis.json b/agency-indexes/DoE/Simulation_INsight_and_Analysis.json new file mode 100644 index 00000000..4eace59f --- /dev/null +++ b/agency-indexes/DoE/Simulation_INsight_and_Analysis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "Sina is a tool set for modern scientific data management that provides flexible, light-weight support of non-bulk data capture for retention in and queries against SQL and noSQL data stores. HPC simulations traditionally maintain their data in files. Extracting data of interest for subsequent analysis then requires the time-consuming process of traversing directories and scraping data from files in a variety of formats. Sina facilitates capturing relevant data during execution or post-processing of simulation runs for retention in and queries from a modern data store. The tools are sufficiently general to allow for the inclusion of new fields as scientists learn more about their data. Libraries, currently in C++ and Python, and a command line interface (CLI) are provided.\nSina's flexibility starts with a general schema, in JSON, for the collection of non-bulk simulation data. JSON provides a flexible, human-readable representation of the data that of interest. Sina currently has a C++ library for simulations to write data to and read from a schema-compliant file for subsequent ingestion into one of the supported data stores. However, applications are free to write their data directly into a schema-compliant file. Python packages provide data ingestion, management, query, and export capabilities. A command line interface (CLI) provides simplified access to these features. A common application programming interface (API) is used to maintain and query data in any of the supported data stores, which are currently limited to SQL and Apache Cassandra (a column store). Tutorials, demonstrations, and examples illustrate aspects of the process using scripts and Jupyter notebooks.", + "laborHours": 5487.2, + "languages": [], + "name": "Simulation INsight and Analysis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Sina", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simulation_Utility_Library_for_HPC_codes.json b/agency-indexes/DoE/Simulation_Utility_Library_for_HPC_codes.json new file mode 100644 index 00000000..5b992553 --- /dev/null +++ b/agency-indexes/DoE/Simulation_Utility_Library_for_HPC_codes.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-18" + }, + "description": "SimUtil contains various small utility functions used in multiple HPC simulation codes here at LLNL, such as: simulation parameter input parsing, parallel file-IO, memory allocation, unit parsing, and helper functions for using MPI.", + "laborHours": 3024.8, + "languages": [], + "name": "Simulation Utility Library for HPC codes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/simutil", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simulation_of_water_flow_in_terrestrial_systems.json b/agency-indexes/DoE/Simulation_of_water_flow_in_terrestrial_systems.json new file mode 100644 index 00000000..efd607b1 --- /dev/null +++ b/agency-indexes/DoE/Simulation_of_water_flow_in_terrestrial_systems.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ParFlow is a parallel, variabley saturated groundwater flow code that is especially suitable for large scale problem. ParFlow simulates the three-dimensional saturated and variably saturated subsurface flow in heterogeneous porous media in three spatial dimensions. ParFlow's developemt and appkication has been on-ging for more than 10 uear. ParFlow has recently been extended to coupled surface-subsurface flow to enabel the simulation of hillslope runoff and channel routing in a truly integrated fashion. ParFlow simulates the three-dimensional varably saturated subsurface flow in strongly heterogeneous porous media in three spatial dimension.", + "laborHours": 138532.8, + "name": "Simulation of water flow in terrestrial systems", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/parflow/parflow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simulations_of_State_for_Biology.json b/agency-indexes/DoE/Simulations_of_State_for_Biology.json new file mode 100644 index 00000000..bab71d9f --- /dev/null +++ b/agency-indexes/DoE/Simulations_of_State_for_Biology.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Simulation software for biochemical systems that use mass action kinetics based on maximum entropy production.", + "laborHours": 47560.8, + "languages": [], + "name": "Simulations of State for Biology", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-CompBio/Boltzmann", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SimulatorToFMU_v0.1.json b/agency-indexes/DoE/SimulatorToFMU_v0.1.json new file mode 100644 index 00000000..06f9d2e8 --- /dev/null +++ b/agency-indexes/DoE/SimulatorToFMU_v0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SimulatorToFMU is a software package written in Python which allows users to export a memoryless Python-driven simulation program or script as a Functional Mock-up Unit (FMU) for model exchange or co-simulation.In CyDER (Cyber Physical Co-simulation Platform for Distributed Energy Resources in Smart Grids), SimulatorToFMU will allow exporting OPAL-RT as an FMU. This will enable OPAL-RT to be linked to CYMDIST and GridDyn FMUs through a standardized open source interface.", + "laborHours": 4332.0, + "name": "SimulatorToFMU v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LBNL-ETA/SimulatorToFMU/blob/master/simulatortofmu/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/SimulatorToFMU", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Simulator_for_Wind_Farm_Applications__SOWFA__[SWR-14-12].json b/agency-indexes/DoE/Simulator_for_Wind_Farm_Applications__SOWFA__[SWR-14-12].json new file mode 100644 index 00000000..1cc5330d --- /dev/null +++ b/agency-indexes/DoE/Simulator_for_Wind_Farm_Applications__SOWFA__[SWR-14-12].json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "A modular tool for simulating wind plant aerodynamics with computational fluid dynamics and turbine structural and control response to the incoming flow.", + "laborHours": 16963.2, + "languages": [ + "C++", + "C", + "Roff", + "shell", + "Fortran" + ], + "name": "Simulator for Wind Farm Applications (SOWFA) [SWR-14-12]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/SOWFA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Single_Episode_Policy_Transfer.json b/agency-indexes/DoE/Single_Episode_Policy_Transfer.json new file mode 100644 index 00000000..ccb6afc3 --- /dev/null +++ b/agency-indexes/DoE/Single_Episode_Policy_Transfer.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-02-12", + "metadataLastUpdated": "2020-02-12" + }, + "description": "Reinforcement learning (RL) aims to learn optimal strategies for control problems with complex, stochastic dynamics. \n\nStandard RL formulations assume that transition dynamics are the same across episodes. \n\nHowever, this is not the case for many real-world environments, e.g. a disease process in which each patient is unique. \n\nTransfer learning in RL aims to solve this problem; however, existing methods allow for multiple trials on a test episode.\n\nWe consider the \"single episode transfer\" setting in which a policy is evaluated on one and only one test episode; thus, any adaptation must occur during that episode. \n\nSingle episode policy transfer (SEPT) is a framework for finding optimal control policies in this setting. \n\nIn SEPT, a \"probe policy\" initially probes the environment to gain information about how that episode is unique. \n\nThen, the information gained from the probe becomes an additional input to the \"universal policy\" that controls the remainder of the episode. \n\nSEPT is a general algorithm and can be used with any existing RL algorithm, including in batch learning mode.\n", + "laborHours": 4058.4, + "languages": [], + "name": "Single Episode Policy Transfer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/011235813/sept", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Single_Model_Uncertainty_Estimation_via_Stochastic_Data_Centering.json b/agency-indexes/DoE/Single_Model_Uncertainty_Estimation_via_Stochastic_Data_Centering.json new file mode 100644 index 00000000..d3e24bb7 --- /dev/null +++ b/agency-indexes/DoE/Single_Model_Uncertainty_Estimation_via_Stochastic_Data_Centering.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-28", + "metadataLastUpdated": "2023-02-28" + }, + "description": "DeltaUQ is a PyTorch library for uncertainty quantification with deep neural networks. It is designed to be used transform any deep neural network to produce uncertainties on any task (classification, regression).", + "laborHours": 0.0, + "languages": [], + "name": "Single Model Uncertainty Estimation via Stochastic Data Centering", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/DeltaUQ", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Single_Sided_Messaging_v._0.6.6.json b/agency-indexes/DoE/Single_Sided_Messaging_v._0.6.6.json new file mode 100644 index 00000000..9b1f4cc7 --- /dev/null +++ b/agency-indexes/DoE/Single_Sided_Messaging_v._0.6.6.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Single-Sided Messaging (SSM) is a portable, multitransport networking library that enables applications to leverage potential one-sided capabilities of underlying network transports. It also provides desirable semantics that services for highperformance, massively parallel computers can leverage, such as an explicit cancel operation for pending transmissions, as well as enhanced matching semantics favoring large numbers of buffers attached to a single match entry. This release supports TCP/IP, shared memory, and Infiniband.", + "laborHours": 37741.6, + "languages": [], + "name": "Single Sided Messaging v. 0.6.6", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/single-sided-messaging", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.6.6" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Singularity_v1.x.json b/agency-indexes/DoE/Singularity_v1.x.json new file mode 100644 index 00000000..51994e83 --- /dev/null +++ b/agency-indexes/DoE/Singularity_v1.x.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Singularity is a container solution designed to facilitate mobility of compute across systems and HPC infrastructures. It does this by creating minimal containers that are defined by a specfile and files from the host system are used to build the container. The resulting container can then be launched by any Linux computer with Singularity installed regardless if the programs inside the container are present on the target system, or if they are a different version, or even incompatible versions. Singularity achieves extreme portability without sacrificing usability thus solving the need of mobility of compute. Singularity containers can be executed within a normal/standard command line process flow.", + "laborHours": 0.0, + "languages": [ + "ANY C COMPLIER" + ], + "name": "Singularity v1.x", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpcng/singularity", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sipper.json b/agency-indexes/DoE/Sipper.json new file mode 100644 index 00000000..0bab7865 --- /dev/null +++ b/agency-indexes/DoE/Sipper.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SIPPER can be used to automatically detect and quantify partially labeled C13 peptides in a single dataset. It includes a GUI for manual visualization and annotation of detected LC-MS features. It also includes a Simple MS Viewer for exploring mass spectral data. Supports Thermo .Raw files, plus also mzXML, mzML, and mz5.", + "laborHours": 22906.4, + "languages": [], + "name": "Sipper", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Sipper", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sirepo_-_Warp.json b/agency-indexes/DoE/Sirepo_-_Warp.json new file mode 100644 index 00000000..a055fcbf --- /dev/null +++ b/agency-indexes/DoE/Sirepo_-_Warp.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Sirepo is an open source framework for cloud computing. The graphical user interface (GUI) for Sirepo, also known as the client, executes in any HTML5 compliant web browser on any computing platform, including tablets. The client is built in JavaScript, making use of the following open source libraries: Bootstrap, which is fundamental for cross-platform web applications; AngularJS, which provides a model\u2013view\u2013controller (MVC) architecture and GUI components; and D3.js, which provides interactive plots and data-driven transformations. The Sirepo server is built on the following Python technologies: Flask, which is a lightweight framework for web development; Jin-ja, which is a secure and widely used templating language; and Werkzeug, a utility library that is compliant with the WSGI standard. We use Nginx as the HTTP server and proxy, which provides a scalable event-driven architecture. The physics codes supported by Sirepo execute inside a Docker container. One of the codes supported by Sirepo is Warp. Warp is a particle-in-cell (PIC) code de-signed to simulate high-intensity charged particle beams and plasmas in both the electrostatic and electromagnetic regimes, with a wide variety of integrated physics models and diagnostics. At pre-sent, Sirepo supports a small subset of Warp\u2019s capabilities. Warp is open source and is part of the Berkeley Lab Accelerator Simulation Toolkit.", + "laborHours": 158824.8, + "name": "Sirepo - Warp", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/radiasoft/sirepo", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sirepo_for_Synchrotron_Radiation_Workshop.json b/agency-indexes/DoE/Sirepo_for_Synchrotron_Radiation_Workshop.json new file mode 100644 index 00000000..a40c21b3 --- /dev/null +++ b/agency-indexes/DoE/Sirepo_for_Synchrotron_Radiation_Workshop.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-03-28" + }, + "description": "Sirepo is an open source framework for cloud computing. The graphical user interface (GUI) for Sirepo, also known as the client, executes in any HTML5 compliant web browser on any computing platform, including tablets. The client is built in JavaScript, making use of the following open source libraries: Bootstrap, which is fundamental for cross-platform web applications; AngularJS, which provides a model\u2013view\u2013controller (MVC) architecture and GUI components; and D3.js, which provides interactive plots and data-driven transformations. The Sirepo server is built on the following Python technologies: Flask, which is a lightweight framework for web development; Jinja, which is a secure and widely used templating language; and Werkzeug, a utility library that is compliant with the WSGI standard. We use Nginx as the HTTP server and proxy, which provides a scalable event-driven architecture. The physics codes supported by Sirepo execute inside a Docker container. One of the codes supported by Sirepo is the Synchrotron Radiation Workshop (SRW). SRW computes synchrotron radiation from relativistic electrons in arbitrary magnetic fields and propagates the radiation wavefronts through optical beamlines. SRW is open source and is primarily supported by Dr. Oleg Chubar of NSLS-II at Brookhaven National Laboratory.", + "laborHours": 158824.8, + "name": "Sirepo for Synchrotron Radiation Workshop", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/radiasoft/sirepo", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sirocco_Storage_Server_v._pre-alpha_0.1.json b/agency-indexes/DoE/Sirocco_Storage_Server_v._pre-alpha_0.1.json new file mode 100644 index 00000000..47aafb05 --- /dev/null +++ b/agency-indexes/DoE/Sirocco_Storage_Server_v._pre-alpha_0.1.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Sirocco is a parallel storage system under development, designed for write-intensive workloads on large-scale HPC platforms. It implements a keyvalue object store on top of a set of loosely federated storage servers that cooperate to ensure data integrity and performance. It includes support for a range of different types of storage transactions. This software release constitutes a conformant storage server, along with the client-side libraries to access the storage over a network.", + "laborHours": 42848.8, + "languages": [ + "Shell", + "C++", + "C", + "RPC", + "Makefile" + ], + "name": "Sirocco Storage Server v. pre-alpha 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/sirocco-release?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sirocco-release", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Siting_Lab_[SWR-24-95].json b/agency-indexes/DoE/Siting_Lab_[SWR-24-95].json new file mode 100644 index 00000000..66d4283f --- /dev/null +++ b/agency-indexes/DoE/Siting_Lab_[SWR-24-95].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-07", + "metadataLastUpdated": "2024-10-07" + }, + "description": "Siting Lab contains a collection of user-friendly tutorials and guides for working with the Siting Lab (https://data.openei.org/siting_lab) data within the context of the reV model. The python code examples demonstrate the creation and transformation of Siting Lab data into reV compliant format as well as working with the reV model inputs and outputs.\n\nSpecifically, Siting Lab provides a collection of Jupyter Notebooks that serve as guides for working with data from NREL's spatial analysis portfolio. These notebooks teach users how to create and interact with reV data in order to facilitate external use of the model. The guides in this repository reference NREL's Supply Curve data as well as Siting Lab spatial data available on OEDI.", + "laborHours": 532.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "Siting Lab [SWR-24-95]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SitingLab", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Situational_Awareness_for_Strategic_Leadership__part_of_CORE_system_.json b/agency-indexes/DoE/Situational_Awareness_for_Strategic_Leadership__part_of_CORE_system_.json new file mode 100644 index 00000000..31dfa782 --- /dev/null +++ b/agency-indexes/DoE/Situational_Awareness_for_Strategic_Leadership__part_of_CORE_system_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "System allows for information to be collected, shared, and commented on by a large group of users. The interaction with the system is independent of time and location, so that input of information and conversations can occur more naturally as they currently do with email.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Situational Awareness for Strategic Leadership (part of CORE system)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SkX_NN:_Neural_Network_for_skyrmion_identification_in_Lorentz_TEM.json b/agency-indexes/DoE/SkX_NN:_Neural_Network_for_skyrmion_identification_in_Lorentz_TEM.json new file mode 100644 index 00000000..f3df5508 --- /dev/null +++ b/agency-indexes/DoE/SkX_NN:_Neural_Network_for_skyrmion_identification_in_Lorentz_TEM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-03-14", + "metadataLastUpdated": "2022-03-14" + }, + "description": "A neural network for segmenting and processing Lorentz TEM images of skyrmion lattices. This software based on U-Net architecture is capable of identifying skyrmions in out-of-focus Lorentz TEM images based on training data. This isspecifically useful for analyzing large area data from in-situ experiments.", + "laborHours": 0.0, + "languages": [], + "name": "SkX_NN: Neural Network for skyrmion identification in Lorentz TEM", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Art-MC/SkX_NN", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Skummee.json b/agency-indexes/DoE/Skummee.json new file mode 100644 index 00000000..dde98f26 --- /dev/null +++ b/agency-indexes/DoE/Skummee.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Skummee is a collection of cluster monitoring tools.", + "homepageURL": "https://sourceforge.net/projects/skummee", + "laborHours": 0.0, + "languages": [], + "name": "Skummee", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/skummee", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SkySpark_psychrometricsExt_.json b/agency-indexes/DoE/SkySpark_psychrometricsExt_.json new file mode 100644 index 00000000..c07a84e3 --- /dev/null +++ b/agency-indexes/DoE/SkySpark_psychrometricsExt_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "psychrometricsExt is a SkySpark extension that provides a set of psychrometric functions using equations from the ASHRAE Fundamentals handbook.", + "laborHours": 30.4, + "languages": [], + "name": "SkySpark psychrometricsExt ", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/psychrometricsExt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Skywalker_v.2.json b/agency-indexes/DoE/Skywalker_v.2.json new file mode 100644 index 00000000..34cd8548 --- /dev/null +++ b/agency-indexes/DoE/Skywalker_v.2.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-09", + "metadataLastUpdated": "2022-10-09" + }, + "description": "SAND2022-2193 O\nSkywalker is a software library that facilitates the creation of test drivers for atmospheric parameterizations used in climate models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 3131.2, + "languages": [ + "C", + "C++", + "Fortran" + ], + "name": "Skywalker v.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Skywing.json b/agency-indexes/DoE/Skywing.json new file mode 100644 index 00000000..0688ad2c --- /dev/null +++ b/agency-indexes/DoE/Skywing.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "vogl2@llnl.gov" + }, + "date": { + "created": "2022-11-09", + "metadataLastUpdated": "2022-11-15" + }, + "description": "A platform for building collaborative autonomy-focused applications.", + "laborHours": 0.0, + "languages": [], + "name": "Skywing", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Skywing/releases/tag/v0.1", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Slepians.jl.json b/agency-indexes/DoE/Slepians.jl.json new file mode 100644 index 00000000..99f627fa --- /dev/null +++ b/agency-indexes/DoE/Slepians.jl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-03" + }, + "description": "Slepians.jl is a package that solves the concentration problem of Slepian, Landau and Pollak, numerically. Loosely speaking, we find a function that is both finite in extent and has a Fourier transform which lies in a certain domain. In a single dimension, with discrete sampling, the discrete prolate spheroidal sequences solve this optimization problem.", + "laborHours": 0.0, + "languages": [], + "name": "Slepians.jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lootie/Slepians.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Slicing_D-Wave_Quantum_Annealers.json b/agency-indexes/DoE/Slicing_D-Wave_Quantum_Annealers.json new file mode 100644 index 00000000..c6d63eba --- /dev/null +++ b/agency-indexes/DoE/Slicing_D-Wave_Quantum_Annealers.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "To solve an optimization problem using a commercial quantum annealer, one has to represent the problem of interest as an Ising or a quadratic unconstrained binary optimization (QUBO) problem and submit its coefficients to the annealer, which then returns a user-specified number of low-energy solutions. It would be useful to know what happens in the quantum processor during the anneal process so that one could design better algorithms or suggest improvements to the hardware. However, existing quantum annealers are not able to directly extract such information from the processor. Hence, in this work we develop methods to use advanced features of D-Wave 2000Q to indirectly infer information about the dynamics of the state evolution during the anneal process. Specifically, D-Wave 2000Q allows the user to customize the anneal schedule, that is, the schedule with which the anneal fraction is changed from the start to the end of the anneal. Using this feature, we design a set of modified anneal schedules whose outputs can be used to generate information about the states of the system at user-defined time points during a standard anneal. With this process, called slicing, we obtain approximate distributions of lowest-energy anneal solutions as the anneal time evolves. We use our technique to obtain a variety of insights into the annealer, such as the state evolution during annealing, when individual bits in an evolving solution flip during the anneal process and when they stabilize, and we introduce a technique to estimate the freeze-out point of both the system as well as of individual qubits. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Slicing D-Wave Quantum Annealers", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Slope_Extensions_to_ASL_Library.json b/agency-indexes/DoE/Slope_Extensions_to_ASL_Library.json new file mode 100644 index 00000000..bb446b08 --- /dev/null +++ b/agency-indexes/DoE/Slope_Extensions_to_ASL_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-15" + }, + "description": "Extensions to the AMPL/solver interface library (http://netlib.sandia.gov/ampl/solvers) to compute bounds on algebraic expressions, plus a test program. use in uncertainty quantification and global optimization algorithms. This software is not primarily for military applications.", + "homepageURL": "https://netlib.sandia.gov/ampl/solvers", + "laborHours": 0.0, + "languages": [], + "name": "Slope Extensions to ASL Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://netlib.sandia.gov/ampl/solvers/README", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://netlib.sandia.gov/ampl/solvers", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Slycat_v_2.0.json b/agency-indexes/DoE/Slycat_v_2.0.json new file mode 100644 index 00000000..b1426e5d --- /dev/null +++ b/agency-indexes/DoE/Slycat_v_2.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-04-18" + }, + "description": "Slycat\u2122 is a web-based system for analysis of large, high-dimensional data such as that produced by High Performance Computing (HPC) platforms. The Slycat\u2122 server integrates data ingestion, scalable analysis, data management, and visualization with commodity web clients using a multi-tiered hierarchy of data and model storage. Analysis inputs are pushed or pulled into Slycat\u2122, where models are generated and analysis artifacts are stored in a project database. These artifacts are the basis for visualizations that are delivered to users\u2019 desktops through ordinary web browsers, eliminating the need to build and deploy platform-specific client applications. Slycat\u2122 currently provides four types of analysis: canonical correlation analysis (CCA) to model relationships between inputs and output metrics, time series analysis featuring clustering and comparative visualization of waveforms, parameter space visualization including remote retrieval of images and movies from HPC disks, and VideoSwarm for modeling video similarities over time.", + "laborHours": 66758.4, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Slycat v 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/slycat", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Small,_Fast_S-Expression_Library,_Version_1.0.json b/agency-indexes/DoE/Small,_Fast_S-Expression_Library,_Version_1.0.json new file mode 100644 index 00000000..7a08d305 --- /dev/null +++ b/agency-indexes/DoE/Small,_Fast_S-Expression_Library,_Version_1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This software is a library for C and C++ programmers to use for fast and efficient parsing and processing of symbolic expressions, or s-expressions. An s-expression is a text-representation of a tree data structure, and is the basis for the syntax of the LISP and Scheme programming languages. Multiple similar libraries exist, but this one was designed from the ground up for speed, efficiency, and simplicity.", + "laborHours": 0.0, + "languages": [ + "Any ANSI-C compiler" + ], + "name": "Small, Fast S-Expression Library, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mjsottile/sfsexp/blob/master/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mjsottile/sfsexp", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Small_Molecule_Evaluator.json b/agency-indexes/DoE/Small_Molecule_Evaluator.json new file mode 100644 index 00000000..e3f66f48 --- /dev/null +++ b/agency-indexes/DoE/Small_Molecule_Evaluator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-19", + "metadataLastUpdated": "2018-12-19" + }, + "description": "Using machine learning to score potential drug candidates may offer an advantage over traditional imprecise scoring functions because the parameters and model structure can be learned from the data. However, models may lack interpretability, are often overfit to the data, and are not generalizable to drug targets and chemotypes not in the training data. Benchmark datasets are prone to artificial enrichment and analogue bias due to the overrepresentation of certain scaffolds in experimentally determined active sets. Datasets can be evaluated using spatial statistics to quantify the dataset topology and better understand potential biases. Dataset clumping comprises a combination of self-similarity of actives and separation from decoys in chemical space and is associated with overoptimistic virtual screening results. This code explores methods of quantifying potential biases and examines some common benchmark datasets.", + "laborHours": 304.0, + "languages": [], + "name": "Small Molecule Evaluator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SmallMolEval", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Small_Non-Linear_Solver.json b/agency-indexes/DoE/Small_Non-Linear_Solver.json new file mode 100644 index 00000000..53d22150 --- /dev/null +++ b/agency-indexes/DoE/Small_Non-Linear_Solver.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "SNLS (small non-linear solver) is a C++ library for solving non-linear systems. The emphasis is on small systems on equations for which direct factorization of the Jacobian is appropriate. The systems of equations may be numerically ill-conditioned. Implementation is amenable to GPU usage, with the idea that class instantiate would occur within device functions.", + "laborHours": 699.2, + "languages": [], + "name": "Small Non-Linear Solver", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SNLS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SmartBlock_v._1.0.json b/agency-indexes/DoE/SmartBlock_v._1.0.json new file mode 100644 index 00000000..4e22fe61 --- /dev/null +++ b/agency-indexes/DoE/SmartBlock_v._1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "SmartBlock offers reusable components that can provide data manipulation and transformation operations on different data streams without requiring recompilation for the new data types.", + "laborHours": 1292.0, + "languages": [ + "C++, C" + ], + "name": "SmartBlock v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gflofst/SmartBlock", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Smart_Control_of_Distributed_Energy_Resources__SCooDER__v1.0.json b/agency-indexes/DoE/Smart_Control_of_Distributed_Energy_Resources__SCooDER__v1.0.json new file mode 100644 index 00000000..dfd970bb --- /dev/null +++ b/agency-indexes/DoE/Smart_Control_of_Distributed_Energy_Resources__SCooDER__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-30", + "metadataLastUpdated": "2019-10-30" + }, + "description": "This package includes a variety of simulation models for distributed energy resources (i.e. photovoltacis, storage, inverter, controls, grid) in the language Modelica.", + "laborHours": 15.2, + "languages": [], + "name": "Smart Control of Distributed Energy Resources (SCooDER) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/SCooDER", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Smart_Monitoring_and_Diagnostic_System__SMDS_.json b/agency-indexes/DoE/Smart_Monitoring_and_Diagnostic_System__SMDS_.json new file mode 100644 index 00000000..30ba9304 --- /dev/null +++ b/agency-indexes/DoE/Smart_Monitoring_and_Diagnostic_System__SMDS_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The SMDS detects RTU performance degradation and select operational faults and provides estimates of the accrued energy and cost impacts weekly after detection of a performance issue. It uses only two sensors per each RTU, outdoor-air temperature and total power demand, both collected at one-minute intervals. Software code based on the methodology and algorithms developed by PNNL in a collaborative develop effort with NorthWrite Inc. and Universal Devices implement the detection processes and estimation of energy and cost impacts. The methodology, algorithms and original prototype software were developed exclusively by PNNL. Two versions of the SMDS, the Hardware SMDS and the Cloud SMDS, have been prototyped and tested on buildings in the field and/or on data from buildings. Both versions use the same methodologies for detection of performance degradation and for detection of specific faults.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Smart Monitoring and Diagnostic System (SMDS)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Smart_Preprocessing_&_Robust_Integration_Emulator.json b/agency-indexes/DoE/Smart_Preprocessing_&_Robust_Integration_Emulator.json new file mode 100644 index 00000000..4ac1fe01 --- /dev/null +++ b/agency-indexes/DoE/Smart_Preprocessing_&_Robust_Integration_Emulator.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-12-13", + "metadataLastUpdated": "2023-12-13" + }, + "description": "To achieve the desired particle size of biomass feedstocks during preprocessing for trouble-free handling and conversion to produce biofuels and bioproducts, the raw materials must undergo a crucial milling process. The particle size of biomass plays a critical role in subsequent biofuel manufacturing, where a larger area-to-volume ratio facilitates efficient synthesis while balancing the impact of moisture on biomass storage. To optimize biofuel production efficiency and overcome these challenges, it is imperative to accurately predict the particle size distribution (PSD) of the biomass in the design of efficient preprocessing systems. The population balance model (PBM), upon empirical calibration and validation, can provide rapid prediction of post-milling PSD of granular biomass. However, PSD has limitations related to mass conservation and the absence of moisture considerations. To overcome these drawbacks, a deep learning model called the enhanced deep neural operator (DNO+) is implemented in the code. This model not only retains the capabilities of the PBM in handling complex mapping functions but also incorporates additional factors influencing the system. By considering various experimental conditions such as sieve size and moisture content, the trained DNO+ model can effectively predict the PSD after milling for any given feed PSD. To further reduce the reliance on experimental data, the PBM is integrated into the DNO+ model, resulting in a physics-informed DNO+ (PIDNO+). The PIDNO+ model addresses the non-conservation of quality exhibited by the PBM while inheriting the advantages of the DNO+ model in considering multiple influencing factors. Moreover, the PIDNO+ model significantly reduces the amount of data required for model training. Both deep learning models, i.e., DNO+ and PIDNO+, are excellent in predictive performance, offering swift and accurate machine learning-based predictions. The use of this code that contains these models will assist in guiding the proper milling equipment selection and operational conditions to achieve the desired biomass particle sizes, ensuring the efficiency of subsequent biofuel and bioproduct production processes.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Smart Preprocessing & Robust Integration Emulator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/SPRITE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Smart_Spectral_Matching__SSM_.json b/agency-indexes/DoE/Smart_Spectral_Matching__SSM_.json new file mode 100644 index 00000000..47079b82 --- /dev/null +++ b/agency-indexes/DoE/Smart_Spectral_Matching__SSM_.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "mcdonnellmt@ornl.gov" + }, + "date": { + "created": "2022-12-05", + "metadataLastUpdated": "2022-12-05" + }, + "description": "Smart Spectral Matching (SSM) catalogs spectroscopic data and, within the platform, investigates subtle attributes of spectral signatures from Raman and infrared spectroscopic data and enables statistical identification of connections between underlying structural units and spectroscopic information, particularly in fuel cycle materials that are amorphous or a mixture of several phases. Catalogs spectroscopic data, provides UIs for machine learning training either via JupyterHub for notebooks or domain scientist-specific views, machine learning and catalog REST API Python client libraries, and ability to identify features in files uploaded using pre-trained machine learning models. This is a \"service-based\" architecture with multiple applications represented by each repository in the group https://github.com/smart-spectral-matching", + "laborHours": 0.0, + "languages": [ + "Java", + "JavaScript", + "Python" + ], + "name": "Smart Spectral Matching (SSM)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/smart-spectral-matching/smart-spectral-matching.github.io", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Smelly-Odor_Webtool__Smelly__v1.json b/agency-indexes/DoE/Smelly-Odor_Webtool__Smelly__v1.json new file mode 100644 index 00000000..444c036c --- /dev/null +++ b/agency-indexes/DoE/Smelly-Odor_Webtool__Smelly__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-21" + }, + "description": "Smelly is an interactive webtool displaying odor dispersion from various potential waste-to-energy sites across California. It currently displays data for dry anaerobic digestion technology with organic waste intake of 90,000 tons per year. The model addresses meteorological and geographical differences in offsite odor impacts (Jin et al. 2019). In addition to interactive display of odor dispersions, the embedded emission calculator provides two additional functionalities: (1) determine the impact distance for given onsite odor emission rates; and (2) determine allowable odor emission rates at given separation distance between the facility and its downwind communities. Please note that data and model is preliminary at this point and serve as a Proof of Concept. Additional data collection, modeling and research is needed for final application.", + "homepageURL": "https://smelly.lbl.gov/About_Smelly.html", + "laborHours": 0.0, + "languages": [], + "name": "Smelly-Odor Webtool (Smelly) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://smelly.lbl.gov/License.txt", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://smelly.lbl.gov/About_Smelly.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Smisc_-_A_collection_of_miscellaneous_functions.json b/agency-indexes/DoE/Smisc_-_A_collection_of_miscellaneous_functions.json new file mode 100644 index 00000000..128a0e2e --- /dev/null +++ b/agency-indexes/DoE/Smisc_-_A_collection_of_miscellaneous_functions.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A collection of functions for statistical computing and data manipulation. These include routines for rapidly aggregating heterogeneous matrices, manipulating file names, loading R objects, sourcing multiple R files, formatting datetimes, multi-core parallel computing, stream editing, specialized plotting, etc. Smisc-package A collection of miscellaneous functions allMissing Identifies missing rows or columns in a data frame or matrix as.numericSilent Silent wrapper for coercing a vector to numeric comboList Produces all possible combinations of a set of linear model predictors cumMax Computes the maximum of the vector up to the current index cumsumNA Computes the cummulative sum of a vector without propogating NAs d2binom Probability functions for the sum of two independent binomials dataIn A flexible way to import data into R. dbb The Beta-Binomial Distribution df2list Row-wise conversion of a data frame to a list dfplapply Parallelized single row processing of a data frame dframeEquiv Examines the equivalence of two dataframes or matrices dkbinom Probability functions for the sum of k independent binomials factor2character Converts all factor variables in a dataframe to character variables findDepMat Identify linearly dependent rows or columns in a matrix formatDT Converts date or datetime strings into alternate formats getExtension Filename manipulations: remove the extension or path, extract the extension or path getPath Filename manipulations: remove the extension or path, extract the extension or path grabLast Filename manipulations: remove the extension or path, extract the extension or path ifelse1 Non-vectorized version of ifelse integ Simple numerical integration routine interactionPlot Two-way Interaction Plot with Error Bar linearMap Linear mapping of a numerical vector or scalar list2df Convert a list to a data frame loadObject Loads and returns the object(s) in an \".Rdata\" file more Display the contents of a file to the R terminal movAvg2 Calculate the moving average using a 2-sided window openDevice Opens a graphics device based on the filename extension p2binom Probability functions for the sum of two independent binomials padZero Pad a vector of numbers with zeros parseJob Parses a collection of elements into (almost) equal sized groups pbb The Beta-Binomial Distribution pcbinom A continuous version of the binomial cdf pkbinom Probability functions for the sum of k independent binomials plapply Simple parallelization of lapply plotFun Plot one or more functions on a single plot PowerData An example of power data pvar Prints the name and value of one or more objects qbb The Beta-Binomial Distribution rbb And numerous others (space limits reporting).", + "laborHours": 2568.8, + "name": "Smisc - A collection of miscellaneous functions", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/Smisc/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Smisc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Smithy.json b/agency-indexes/DoE/Smithy.json new file mode 100644 index 00000000..dbeb5f9e --- /dev/null +++ b/agency-indexes/DoE/Smithy.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Smithy provides sane software installation and modulefile management\n", + "laborHours": 3693.6, + "name": "Smithy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/olcf/smithy/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/smithy", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Smoothed_Particle_Hydrodynamic_Simulator.json b/agency-indexes/DoE/Smoothed_Particle_Hydrodynamic_Simulator.json new file mode 100644 index 00000000..a3daa2ea --- /dev/null +++ b/agency-indexes/DoE/Smoothed_Particle_Hydrodynamic_Simulator.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This code is a highly modular framework for developing smoothed particle hydrodynamic (SPH) simulations running on parallel platforms. The compartmentalization of the code allows for rapid development of new SPH applications and modifications of existing algorithms. The compartmentalization also allows changes in one part of the code used by many applications to instantly be made available to all applications.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Linux" + ], + "name": "Smoothed Particle Hydrodynamic Simulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Snorri_Version_1.0.json b/agency-indexes/DoE/Snorri_Version_1.0.json new file mode 100644 index 00000000..41872d7a --- /dev/null +++ b/agency-indexes/DoE/Snorri_Version_1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-10-25", + "metadataLastUpdated": "2018-10-26" + }, + "description": "The software decomposes n-component time-series data into persistence vectors and provide visualizations of various summaries of this information. Persistence vectors are a type of vector, based on multidimensional persistent homology theory, which have magnitudes and directions that reflect dominant trends in the multi-component data. The software is a collection of MATLAB scripts, and thus MATLAB runs the scripts. The master script that calls other scripts is called Snorri. The purpose is thus analysis of time-series data to extract dominant trends or events and to classify the type of event. The software produces characteristic vectors (an average of the persistence vectors), which can have directions that reflect the overall dominant trend in a time-series data set. The MATLAB scripts have been partially converted to the PYTHON language and no do not have the full functionality of the MATLAB and are not fully tested; the python scripts are to be covered under this copyright assertion. Two versions of the PYTHON scripts are included, called: mph25.py and mph38.py, each with their own main.py file.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 1444.0, + "languages": [ + "MATLAB" + ], + "name": "Snorri Version 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Snow_Micro-Structure_Model.json b/agency-indexes/DoE/Snow_Micro-Structure_Model.json new file mode 100644 index 00000000..6a3b1abc --- /dev/null +++ b/agency-indexes/DoE/Snow_Micro-Structure_Model.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-07" + }, + "description": "PIKA is a MOOSE-based application for modeling micro-structure evolution of seasonal snow. The model will be useful for environmental, atmospheric, and climate scientists. Possible applications include application to energy balance models, ice sheet modeling, and avalanche forecasting. The model implements physics from published, peer-reviewed articles. The main purpose is to foster university and laboratory collaboration to build a larger multi-scale snow model using MOOSE. The main feature of the code is that it is implemented using the MOOSE framework, thus making features such as multiphysics coupling, adaptive mesh refinement, and parallel scalability native to the application. PIKA implements three equations: the phase-field equation for tracking the evolution of the ice-air interface within seasonal snow at the grain-scale; the heat equation for computing the temperature of both the ice and air within the snow; and the mass transport equation for monitoring the diffusion of water vapor in the pore space of the snow.", + "laborHours": 6840.0, + "languages": [], + "name": "Snow Micro-Structure Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/pika", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SoDa:_An_Irradiance-Based_Synthetic_Solar_Data_Generation_Tool__SoDa__v0.1.json b/agency-indexes/DoE/SoDa:_An_Irradiance-Based_Synthetic_Solar_Data_Generation_Tool__SoDa__v0.1.json new file mode 100644 index 00000000..ba093350 --- /dev/null +++ b/agency-indexes/DoE/SoDa:_An_Irradiance-Based_Synthetic_Solar_Data_Generation_Tool__SoDa__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-11-23", + "metadataLastUpdated": "2021-11-23" + }, + "description": "SoDa is an irradiance-based synthetic Solar Data generation tool to generate realistic sub-minute solar photovoltaic (PV) power time series, that emulate the weather pattern for a certain geographical location. Our tool relies on the National Solar Radiation Database (NSRDB) to obtain irradiance and weather data patterns for the site. Irradiance is mapped onto a PV model estimate of a solar plant's 30-min power output, based on the configuration of the panel. We use a stochastic model with a switching behavior due to different weather regimes as provided by the cloud type label in the NSRDB, with parameters for the cloudy states trained on the high-resolution solar power measurements from a Phasor Measurement Unit (PMU).", + "laborHours": 0.0, + "languages": [], + "name": "SoDa: An Irradiance-Based Synthetic Solar Data Generation Tool (SoDa) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Ignacio-Losada/SoDa", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SoRa:_Symbolic_Regression_in_Python.json b/agency-indexes/DoE/SoRa:_Symbolic_Regression_in_Python.json new file mode 100644 index 00000000..6c6c57e4 --- /dev/null +++ b/agency-indexes/DoE/SoRa:_Symbolic_Regression_in_Python.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "Symbolic Regression (SR) is a genetic programming algorithm for finding mathematical functions that match a given set of data. It works by evolving an approximation function from a set of primitives. This makes it able to discover the form of the function, in addition to it's coefficients. It has even been shown to be able to discover natural physical laws from experimental data. Given that SR is one of the biggest success stories in genetic programming, it's surprising that there doesn't seem to be an easy-to-use, open-source SR program available. SoRa attempts to fill that gap. With SoRa any user should easily be able to provide experimental data and write a simple configuration file such that SoRa can find a set of good mathematical functions to match the data.\n", + "laborHours": 1550.4, + "languages": [], + "name": "SoRa: Symbolic Regression in Python", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SoRa", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Soar_Survey_Scoring.json b/agency-indexes/DoE/Soar_Survey_Scoring.json new file mode 100644 index 00000000..0cb73d94 --- /dev/null +++ b/agency-indexes/DoE/Soar_Survey_Scoring.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "weberb@ornl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2021-12-10" + }, + "description": "ORNL conducted an experiment to test COTS (commercial off the shelf) SOAR tools. Vendors interested in entering their tool into the experiment were asked to submit information videos about their tool for phase 1 to down-select which tools should make it through to the testing phase. SOC operators were assigned to watch a subset of the videos such that each video was assigned to the same number of operators. After watching all the videos, operators completed surveys which asked them to grade basic aspects about the tool as best as they could based on the provided video, and asked them to rank the order of their interest in the vendors they were assigned to watch videos on. The problem solved was how do we aggregate the results of the surveys and each of the operator's ranked lists into an overall ranking of all the tools. In addition, it was desirable to be able to work on this code before final results were collected from operators, so code to generate fake data was developed to output in the same output as the survey results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Soar Survey Scoring", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/soar_survey_scoring", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Socorro_Electronic_Structure_Software.json b/agency-indexes/DoE/Socorro_Electronic_Structure_Software.json new file mode 100644 index 00000000..281d769d --- /dev/null +++ b/agency-indexes/DoE/Socorro_Electronic_Structure_Software.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "Socorro can be used to compute the ground-state electron density for a periodically repeated simulation cell in which the external potential is obtained from norm-conserving pseudopotentials or projector-augmented-wave functions. The ground-state electron density is computed by summation over one-electron orbitals which are obtained using the Kohn-Sham formulation of density-functional theory and which are expanded in a plane-wave basis. Various quantities can be computed from the ground-state solution, including atomic forces which can be used to optimize atom positions in the simulation cell and to perform molecular dynamics simulations.", + "laborHours": 0.0, + "languages": [ + "C", + "Fortran" + ], + "name": "Socorro Electronic Structure Software", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/socorro", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sodium_Fluid_Properties.json b/agency-indexes/DoE/Sodium_Fluid_Properties.json new file mode 100644 index 00000000..4ae17308 --- /dev/null +++ b/agency-indexes/DoE/Sodium_Fluid_Properties.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2023-08-30", + "metadataLastUpdated": "2023-08-30" + }, + "description": "This software is used to compute numerous properties for the liquid and vapor phases of sodium.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Sodium Fluid Properties", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/sodium", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Software_Library_for_Bruker_TopSpin_NMR_Data_Files.json b/agency-indexes/DoE/Software_Library_for_Bruker_TopSpin_NMR_Data_Files.json new file mode 100644 index 00000000..353fc61f --- /dev/null +++ b/agency-indexes/DoE/Software_Library_for_Bruker_TopSpin_NMR_Data_Files.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "A software library for parsing and manipulating frequency-domain data files that have been processed using the Bruker TopSpin NMR software package. In the context of NMR, the term \"processed\" indicates that the end-user of the Bruker TopSpin NMR software package has (a) Fourier transformed the raw, time-domain data (the Free Induction Decay) into the frequency-domain and (b) has extracted the list of NMR peaks.", + "laborHours": 0.0, + "languages": [ + "Ruby" + ], + "name": "Software Library for Bruker TopSpin NMR Data Files", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/EMSL-NMR-EPR/Ruby-Bruker-TopSpin-Library/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-NMR-EPR/Ruby-Bruker-TopSpin-Library", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Software_Suite_for_Endothelial_Function_Assessment.json b/agency-indexes/DoE/Software_Suite_for_Endothelial_Function_Assessment.json new file mode 100644 index 00000000..7e10b303 --- /dev/null +++ b/agency-indexes/DoE/Software_Suite_for_Endothelial_Function_Assessment.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Suite of programs for evaluating endothelial function, including protocol execution, data acquisition, and analysis", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "GCC 4.x" + ], + "name": "Software Suite for Endothelial Function Assessment", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Software_for_Computing,_Archiving,_and_Querying_Semisimple_Braided_Monoidal_Category_Data.json b/agency-indexes/DoE/Software_for_Computing,_Archiving,_and_Querying_Semisimple_Braided_Monoidal_Category_Data.json new file mode 100644 index 00000000..1c5fc3bd --- /dev/null +++ b/agency-indexes/DoE/Software_for_Computing,_Archiving,_and_Querying_Semisimple_Braided_Monoidal_Category_Data.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "This software package collects various open source and freely available codes and algorithms to compute and archive the categorical data for certain semisimple braided monoidal categories. In particular, it computes the data for of group theoretical categories for academic research.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "GAP / Python" + ], + "name": "Software for Computing, Archiving, and Querying Semisimple Braided Monoidal Category Data", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Software_for_Heliospheric_Science.json b/agency-indexes/DoE/Software_for_Heliospheric_Science.json new file mode 100644 index 00000000..f9ffe3b6 --- /dev/null +++ b/agency-indexes/DoE/Software_for_Heliospheric_Science.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-10-20", + "metadataLastUpdated": "2023-10-20" + }, + "description": "This software is being developed to support data analysis, modeling, and simulation for the growing field of heliosphere physics. In particular, this software will implement data analysis, modeling, inference, and simulation of physical mechanisms describing how energetic neutral atoms behave within the Earth\u2019s heliosphere and in the interstellar medium beyond.", + "laborHours": 0.0, + "languages": [], + "name": "Software for Heliospheric Science", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/IBEX_RibbonSeparation", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Software_for_Machine_Learning_a_Flux_Limiter.json b/agency-indexes/DoE/Software_for_Machine_Learning_a_Flux_Limiter.json new file mode 100644 index 00000000..ff032ae9 --- /dev/null +++ b/agency-indexes/DoE/Software_for_Machine_Learning_a_Flux_Limiter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-05-09", + "metadataLastUpdated": "2022-05-09" + }, + "description": "This software consists of a set of codes designed to learn flux limiters from direct numerical simulation data.", + "laborHours": 0.0, + "languages": [], + "name": "Software for Machine Learning a Flux Limiter", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/fluxlimiter", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Software_for_Predicting_Bacterial_Minimum_Inhibitory_Concentrations_From_Genome_Sequence_Data.json b/agency-indexes/DoE/Software_for_Predicting_Bacterial_Minimum_Inhibitory_Concentrations_From_Genome_Sequence_Data.json new file mode 100644 index 00000000..d56caf9a --- /dev/null +++ b/agency-indexes/DoE/Software_for_Predicting_Bacterial_Minimum_Inhibitory_Concentrations_From_Genome_Sequence_Data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-03", + "metadataLastUpdated": "2019-07-03" + }, + "description": "This package predicts the minimum inhibitory concentration of a genome using a trained XGBoost model. A set of data files are stored in the data_files directory for use with the Klebsiella genus. A pkl model is also provided for testing purposes as well as a fasta file.", + "laborHours": 136.8, + "languages": [], + "name": "Software for Predicting Bacterial Minimum Inhibitory Concentrations From Genome Sequence Data", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PATRIC3/mic_prediction", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Software_for_Transformative_Remedial_Action_Scheme_Tool__TRAST_.json b/agency-indexes/DoE/Software_for_Transformative_Remedial_Action_Scheme_Tool__TRAST_.json new file mode 100644 index 00000000..f4a6cd53 --- /dev/null +++ b/agency-indexes/DoE/Software_for_Transformative_Remedial_Action_Scheme_Tool__TRAST_.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-09-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The transformative remedial action scheme tool (TRAST) can be applied to improve and validate the power system remedial action scheme (RAS), and further improve the performance of power system operation and control. This tool provides a full suite of advanced functionalities, which are given as follows:\n1. Advanced statistical data analysis\u037e\n2. OPF-based automated power flow case generation\u037e\n3. Customized dynamic simulation in HPC/cloud platform\u037e\n4. Machine learning based RAS coefficient prediction\u037e\n5. A reliable RAS validation strategy in multiple commercial platforms.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Software for Transformative Remedial Action Scheme Tool (TRAST)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Soil_Carbon_Data:_long_tail_recovery.json b/agency-indexes/DoE/Soil_Carbon_Data:_long_tail_recovery.json new file mode 100644 index 00000000..11c2b3b7 --- /dev/null +++ b/agency-indexes/DoE/Soil_Carbon_Data:_long_tail_recovery.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software is intended to be part of an open source effort regarding soils data. The software provides customized data ingestion scripts for soil carbon related data sets and scripts for output databases that conform to common templates.", + "laborHours": 714.4, + "name": "Soil Carbon Data: long tail recovery", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ktoddbrown/soils-long-tail-recovery", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SolTrace__Optical_Analysis_Software_.json b/agency-indexes/DoE/SolTrace__Optical_Analysis_Software_.json new file mode 100644 index 00000000..96610630 --- /dev/null +++ b/agency-indexes/DoE/SolTrace__Optical_Analysis_Software_.json @@ -0,0 +1,43 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2022-06-27" + }, + "description": "SolTrace is a software tool developed at the National Renewable Energy Laboratory (NREL) to model concentrating solar power (CSP) systems and analyze their optical performance.\n\nAlthough ideally suited for solar applications, the code can also be used to model and characterize many general optical systems. The creation of the code evolved out of a need to model more complex solar optical systems than could be modeled with existing tools.\n\nSolTrace can be installed either using the official NREL packaged distribution or from source code at the SolTrace open source project website. NREL welcomes contributions from programmers to the simulation engine or to the interface and encourages interested persons to get involved. More information on contributing, compiling the source code, and license requirements is available on the project website.(https://www.nrel.gov/csp/soltrace.html). For details on integration with SAM, see the SAM website. (https://sam.nrel.gov/)", + "laborHours": 10381.6, + "languages": [ + "C++", + "css", + "html", + "Tex", + "JavaScript", + "Python" + ], + "name": "SolTrace (Optical Analysis Software)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SolTrace", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Solar-Forecast_GridAPPS-D_Application_[SWR-18-36].json b/agency-indexes/DoE/Solar-Forecast_GridAPPS-D_Application_[SWR-18-36].json new file mode 100644 index 00000000..d22edf2b --- /dev/null +++ b/agency-indexes/DoE/Solar-Forecast_GridAPPS-D_Application_[SWR-18-36].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-12-19", + "metadataLastUpdated": "2023-05-08" + }, + "description": "Persistent model serves as the baseline in the intra-hour forecasting of solar radiation due to the extensive computing efforts from the numerical weather prediction (NWP) models and the lack of surface observations in cloud as well as other atmospheric properties. The smart persistent model actively updates the extraterrestrial solar radiation with time and is an important improvement from the persistent model while the cloud conditions are assumed unchanged by giving constant clear-sky indexes. We developed a Physics-based Smart Persistent model for Intra-hour solar forecasting (PSPI) to further improve the accuracy of the smart persistent model. We used a cloud retrieval technique developed by Xie and Liu (2013) to estimate cloudy fraction and cloud albedo using surface-based observations of solar radiation. The solar radiation in future time steps is accurately given by actively computing individual cloud albedo related to the future solar position. Our evaluation studies indicated that the PSPI model significantly increased the accuracy in the short-term forecast of solar radiation, especially in thin cloud conditions or those covered by broken clouds.", + "laborHours": 410.4, + "languages": [ + "Python", + "Dockerfile" + ], + "name": "Solar-Forecast GridAPPS-D Application [SWR-18-36]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Solar-Forecasting", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/SolarPILOT\342\204\242.json" "b/agency-indexes/DoE/SolarPILOT\342\204\242.json" new file mode 100644 index 00000000..e5ae6970 --- /dev/null +++ "b/agency-indexes/DoE/SolarPILOT\342\204\242.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-05-22", + "metadataLastUpdated": "2018-05-22" + }, + "description": "SolarPILOT\u2122advances the analytical flux image Hermite series approximation used in DELSOL3 by applying it to individual heliostat images rather than \"zones\", allowing characterization of a wide variety of heliostat field layouts. SolarPILOT also integrates the SolTrace Monte-Carlo ray tracing engine, providing improved receiver optical modeling capability, a user-friendly front end for geometry definition, and side-by-side validation of the analytical algorithms. The tool and source code are publicly available and are designed for third-party modification and extendability. The software is intended as a replacement for the more antiquated DELSOL3 algorithm originally developed at Sandia National Laboratory. The software will be used at NREL for power tower component design analysis and may be used at other laboratories, in academia, or as a third-party validation tool by some industry groups.", + "laborHours": 28743.2, + "languages": [], + "name": "SolarPILOT\u2122", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SolarPILOT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SolarPlus-Optimizer_v0.1.json b/agency-indexes/DoE/SolarPlus-Optimizer_v0.1.json new file mode 100644 index 00000000..4f76d7d2 --- /dev/null +++ b/agency-indexes/DoE/SolarPlus-Optimizer_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "With the falling costs of solar arrays and battery storage and reduced reliability of the grid due to natural disasters, small-scale local generation and storage resources are beginning to proliferate. However, very few software options exist for integrated control of building loads, batteries and other distributed energy resources. The available software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice, and are often incapable of operating independently of the grid during blackouts. In this software package, we present the \"Solar+ Optimizer\" (SPO), a control platform that provides demand flexibility, resiliency and reduced utility bills, built using open-source software. SPO employs Model Predictive Control (MPC) to produce real time optimal control strategies for the building loads and the distributed energy resources on site. SPO is designed to be vendor-agnostic, protocol-independent and resilient to loss of wide-area network connectivity. The software was evaluated in a real convenience store in northern California with on-site solar generation, battery storage and control of HVAC and commercial refrigeration loads. Preliminary tests showed price responsiveness of the building and cost savings of more than 10% in energy costs alone.", + "laborHours": 20200.8, + "languages": [], + "name": "SolarPlus-Optimizer v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/SolarPlus-Optimizer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Solar_Cell_Phase_and_Defect_Formation_Energy_Diagram.json b/agency-indexes/DoE/Solar_Cell_Phase_and_Defect_Formation_Energy_Diagram.json new file mode 100644 index 00000000..4253b050 --- /dev/null +++ b/agency-indexes/DoE/Solar_Cell_Phase_and_Defect_Formation_Energy_Diagram.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "CKAN plugin for computing and displaying the phase diagram and defect formation energy diagram of a solar cell compound, when given the formation energies and defect formation energies.", + "laborHours": 9408.8, + "languages": [], + "name": "Solar Cell Phase and Defect Formation Energy Diagram", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SC-PD-FED", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Solar_Hot_Water_Hourly_Simulation.json b/agency-indexes/DoE/Solar_Hot_Water_Hourly_Simulation.json new file mode 100644 index 00000000..25df56e2 --- /dev/null +++ b/agency-indexes/DoE/Solar_Hot_Water_Hourly_Simulation.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2021-05-11" + }, + "description": "The Software consists of a spreadsheet written in Microsoft Excel which provides an hourly simulation of a solar hot water heating system (including solar geometry, solar collector efficiency as a function of temperature, energy balance on storage tank and lifecycle cost analysis).", + "homepageURL": "https://www.labpartnering.org/lab-technologies/abbc8ccf-3984-416e-b276-4c9d8d192a9f", + "laborHours": 0.0, + "languages": [ + "excel" + ], + "name": "Solar Hot Water Hourly Simulation", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.labpartnering.org/lab-technologies/abbc8ccf-3984-416e-b276-4c9d8d192a9f", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.labpartnering.org/lab-technologies/abbc8ccf-3984-416e-b276-4c9d8d192a9f", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Solar_Radiation_Empirical_Quality_Assessment.json b/agency-indexes/DoE/Solar_Radiation_Empirical_Quality_Assessment.json new file mode 100644 index 00000000..48fab39d --- /dev/null +++ b/agency-indexes/DoE/Solar_Radiation_Empirical_Quality_Assessment.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-29" + }, + "description": "The SERIQC1 subroutine performs quality assessment of one, two, or three-component solar radiation data (global horizontal, direct normal, and diffuse horizontal) obtained from one-minute to one-hour integrations. Included in the package is the QCFIT tool to derive expected values from historical data, and the SERIQC1 subroutine to assess the quality of measurement data.", + "laborHours": 319.2, + "languages": [], + "name": "Solar Radiation Empirical Quality Assessment", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SolarResourceTools", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Solar_System_Initial_Abundnace_Reader.json b/agency-indexes/DoE/Solar_System_Initial_Abundnace_Reader.json new file mode 100644 index 00000000..087d20f7 --- /dev/null +++ b/agency-indexes/DoE/Solar_System_Initial_Abundnace_Reader.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-01-09", + "metadataLastUpdated": "2020-01-09" + }, + "description": "This code is a simply python module that allows the user to read in the solar system value from a\nprovided database. It simply reads in the database, and calculates ratios with various values. Currently,\nthe solar system values from Lodders et al. (2009) are solely included. The tool is designed to assist a\nastrophysics / cosmochemist user in their daily life of calculating those ratios for programs and was\nwritten by the author to simplify his own life. A setup.py routine has been written as well. Release is\nanticipated via github as well as in the form of a pypi package.", + "laborHours": 121.6, + "languages": [], + "name": "Solar System Initial Abundnace Reader", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/iniabu", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Solaris_Porting_Layer__SPL_.json b/agency-indexes/DoE/Solaris_Porting_Layer__SPL_.json new file mode 100644 index 00000000..d7cd7698 --- /dev/null +++ b/agency-indexes/DoE/Solaris_Porting_Layer__SPL_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "The Solaris Porting Layer (SPL) is a Linux kernel module which provides many of the Solaris kernel APIs. This shim layer makes it possible to run Solaris kernel code in the Linux kernel with relatively minimal modification. This can be particularly useful when you want to track upstream Solaris development closely and do not want the overhead of maintaining a large patch which converts Solaris primitives to Linux primitives.\n", + "laborHours": 11643.2, + "languages": [], + "name": "Solaris Porting Layer (SPL)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/spl", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Solergy__Beta_Version_1_.json b/agency-indexes/DoE/Solergy__Beta_Version_1_.json new file mode 100644 index 00000000..4f7f52b7 --- /dev/null +++ b/agency-indexes/DoE/Solergy__Beta_Version_1_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "SOLERGY simulates the operation and power output of a user-defined solar central receiver power plant for a time period of up to one year. SOLERGY utilizes recorded or simulated weather data and plant component performance models to calculate the power flowing through each part of the solar plant. A plant control subroutine monitors these powers and determines when to operate the various plant subsystems. The original version of the code was released in May 1987, within SAND86-8060 and was widely distributed. The Beta Version 1 to be released in 2009, includes some relatively small modifications to the original code.", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Solergy (Beta Version 1)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/solergy", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SolidPAC.json b/agency-indexes/DoE/SolidPAC.json new file mode 100644 index 00000000..25bec420 --- /dev/null +++ b/agency-indexes/DoE/SolidPAC.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "dixitmb@ornl.gov" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2022-08-02" + }, + "description": "SolidPAC: Solid-State Battery Performance Analyzer and Calculator SolidPAC is an interactive experimental toolkit developed at Oak Ridge National Laboratory to enable the design of a solid-state battery for user-specified application requirements. The toolkit is flexible enough to assist the battery community in quantifying the impact of materials chemistry and fractions, electrode thicknesses and loadings, and electron flows on cell energy density and cost, and to be able to utilize inverse engineering concepts to correlate cell energy density output to materials and cell design inputs. The toolkit allows users to assess and extrapolate the impact of battery design and choice of cell components on cell-level energy density of a solid-state battery. SolidPAC brings practicality to the design of solid-state batteries.", + "homepageURL": "https://www.ornl.gov/content/solidpac", + "laborHours": 0.0, + "languages": [ + "LabVIEW" + ], + "name": "SolidPAC", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.ornl.gov/content/solidpac", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SolidShperal.json b/agency-indexes/DoE/SolidShperal.json new file mode 100644 index 00000000..c0fbaeba --- /dev/null +++ b/agency-indexes/DoE/SolidShperal.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SolidSpheral is an extension of the Spheral open source meshless hydrodynamics method. SolidSpheral adds the capability to model solid materials using analytic equations of state, and a simple damage model to allow for the modeled materials to undergo dynamic damage evolution. SolidSpheral is a distributed parallel code employing MPI for the parallel framework.", + "homepageURL": "https://sourceforge.net/projects/spheral", + "laborHours": 0.0, + "name": "SolidShperal", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/spheral", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Solid_Oxide_Fuel_Cell_-_Multi-Physics_and_GUI.json b/agency-indexes/DoE/Solid_Oxide_Fuel_Cell_-_Multi-Physics_and_GUI.json new file mode 100644 index 00000000..55bb8e1a --- /dev/null +++ b/agency-indexes/DoE/Solid_Oxide_Fuel_Cell_-_Multi-Physics_and_GUI.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "SOFC-MP is a simulation tool developed at PNNL to evaluate the tightly coupled multi-physical phenomena in SOFCs. The purpose of the tool is to allow SOFC manufacturers to numerically test changes in planar stack design to meet DOE technical targets. The SOFC-MP 2D module is designed for computational efficiency to enable rapid engineering evaluations for operation of tall symmetric stacks. It can quickly compute distributions for the current density, voltage, temperature, and species composition in tall stacks with co-flow or counter-flow orientations. The 3D module computes distributions in entire 3D domain and handles all planner configurations: co-flow, counter-flow, and cross-flow. The detailed data from 3D simulation can be used as input for structural analysis. SOFC-MP GUI integrates both 2D and 3D modules, and it provides user friendly pre-processing and post-processing capabilities.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++, FORTRAN, C#" + ], + "name": "Solid Oxide Fuel Cell - Multi-Physics and GUI", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Solidify,_An_LLVM_pass_to_compile_LLVM_IR_into_Solidity.json b/agency-indexes/DoE/Solidify,_An_LLVM_pass_to_compile_LLVM_IR_into_Solidity.json new file mode 100644 index 00000000..44a182fd --- /dev/null +++ b/agency-indexes/DoE/Solidify,_An_LLVM_pass_to_compile_LLVM_IR_into_Solidity.json @@ -0,0 +1,40 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The software currently compiles LLVM IR into Solidity (Ethereum\u2019s dominant programming language) using LLVM\u2019s pass library. Specifically, his compiler allows us to convert an arbitrary DSL into Solidity. We focus specifically on converting Domain Specific Languages into Solidity due to their ease of use, and provable properties. By creating a toolchain to compile lightweight domain-specific languages into Ethereum's dominant language, Solidity, we allow non-specialists to effectively develop safe and useful smart contracts. For example lawyers from a certain firm can have a proprietary DSL that codifies basic laws safely converted to Solidity to be securely executed on the blockchain. In another example, a simple provenance tracking language can be compiled and securely executed on the blockchain.", + "laborHours": 4377.6, + "languages": [ + "C++, build and test scripts written in bash", + "C++", + "C", + "ANTLR", + "CMake", + "Makefile", + "Python" + ], + "name": "Solidify, An LLVM pass to compile LLVM IR into Solidity", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/abhiramkothapalli/EthereumCompiler/blob/master/solidify/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/EthereumCompiler", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sonar.json b/agency-indexes/DoE/Sonar.json new file mode 100644 index 00000000..c25fcca5 --- /dev/null +++ b/agency-indexes/DoE/Sonar.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-01-31", + "metadataLastUpdated": "2019-02-01" + }, + "description": "Sonar contains software for managing a HPC performance-monitoring software stack. This includes streaming data into a distributed Kafka message queue, storing/querying from a distributed Cassandra database, and front-end tools for secure access, visualization, and analytics of facility-wide performance data.", + "laborHours": 790.4, + "languages": [], + "name": "Sonar", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/sonar-driver", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sonata.json b/agency-indexes/DoE/Sonata.json new file mode 100644 index 00000000..f883fad6 --- /dev/null +++ b/agency-indexes/DoE/Sonata.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-28", + "metadataLastUpdated": "2022-01-28" + }, + "description": "Sonata is a Mochi service for JSON document storage. It is based on UnQLite and Thallium.", + "laborHours": 0.0, + "languages": [], + "name": "Sonata", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-sonata/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-sonata", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SpaceWire_Light.json b/agency-indexes/DoE/SpaceWire_Light.json new file mode 100644 index 00000000..bc5c2f7c --- /dev/null +++ b/agency-indexes/DoE/SpaceWire_Light.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-10", + "metadataLastUpdated": "2022-08-10" + }, + "description": "SpaceWire Light is a SpaceWire encoder-decoder. It is synthesizable for FPGA targets (up to 200 Mbit on Spartan-3). Application interfaces include a simple FIFO interface, as well as an AMBA bus interface for LEON3 system-on-chip designs.", + "laborHours": 0.0, + "languages": [], + "name": "SpaceWire Light", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/spacewire_light/blob/master/README.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/spacewire_light", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Space_Situational_Awareness_for_Python.json b/agency-indexes/DoE/Space_Situational_Awareness_for_Python.json new file mode 100644 index 00000000..c7cfa098 --- /dev/null +++ b/agency-indexes/DoE/Space_Situational_Awareness_for_Python.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-04-17", + "metadataLastUpdated": "2024-04-17" + }, + "description": "SSAPy is a python package allowing for fast and precise orbital modeling. SSAPy is designed with speed\nand accuracy in mind and offers the following capabilities:\n- A variety of integrators, including Runge-Kutta, SciPy, SGP4, etc.\n- Customizable force propagation models, including a variety of Earth gravity models, lunar gravity,\nradiation pressure, etc.\n- Multiple-hypothesis tracking (MHT) UCT linker\n- Vectorized computations\n- Short arc probabilistic orbit determination\n- Conjunction probability estimation\n- Uncertainty quantification\n- Monte Carlo data fusion\n- Support for multiple coordinate frames (with coordinate frame conversions)", + "laborHours": 6976.8, + "languages": [], + "name": "Space Situational Awareness for Python", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SSAPy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spack-Manager.json b/agency-indexes/DoE/Spack-Manager.json new file mode 100644 index 00000000..7eecdd75 --- /dev/null +++ b/agency-indexes/DoE/Spack-Manager.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-09", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SAND2022-3282 O Spack-Manager is a lightweight wrapper for streamlining the software development and deployment cycle using Spack. Spack-Manager creates a uniform framework for developing, testing, and deploying specific software stacks for projects across multiple platforms while utilizing Spack as much as possible. It organizes Spack extensions, machine configurations, project customizations, and tools for features that are mostly project specific. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 2036.8, + "languages": [ + "Python", + "Shell" + ], + "name": "Spack-Manager", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spack-manager", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spack.json b/agency-indexes/DoE/Spack.json new file mode 100644 index 00000000..3ee37d85 --- /dev/null +++ b/agency-indexes/DoE/Spack.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-06-24", + "metadataLastUpdated": "2020-06-24" + }, + "description": "A flexible package manager that supports multiple versions, configurations, platforms, and compilers.", + "laborHours": 169312.8, + "languages": [], + "name": "Spack", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spack/spack", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spack:_the_Supercomputing_Package_Manager.json b/agency-indexes/DoE/Spack:_the_Supercomputing_Package_Manager.json new file mode 100644 index 00000000..ddf2f1f2 --- /dev/null +++ b/agency-indexes/DoE/Spack:_the_Supercomputing_Package_Manager.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-02-09" + }, + "description": "The HPC software ecosystem is growing larger and more complex, but software distribution mechanisms have not kept up with this trend. Tools, Libraries, and applications need to run on multiple platforms and build with multiple compliers. Increasingly, packages leverage common software components, and building any one component requires building all of its dependencies. In HPC environments, ABI-incompatible interfaces (likeMPI), binary-incompatible compilers, and cross-compiled environments converge to make the build process a combinatoric nightmare. This obstacle deters many users from adopting useful tools, and others waste countless hours building and rebuilding tools. Many package managers exist to solve these problems for typical desktop environments, but none suits the unique needs of supercomputing facilities or users. To address these problems, we have Spack, a package manager that eases the task of managing software for end-users, across multiple platforms, package versions, compilers, and ABI incompatibilities.", + "laborHours": 169312.8, + "languages": [], + "name": "Spack: the Supercomputing Package Manager", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spack/spack", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spark-hdf5.json b/agency-indexes/DoE/Spark-hdf5.json new file mode 100644 index 00000000..7cdb7b80 --- /dev/null +++ b/agency-indexes/DoE/Spark-hdf5.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The spark-hdf5 package is an extension to the Apache Spark program to allow native access to HDF5 files. It allows users to query the structured files using SQL-like syntax, and can parallelize large queries across several workers.", + "laborHours": 334.4, + "name": "Spark-hdf5", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/spark-hdf5", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sparx_PCA_Module.json b/agency-indexes/DoE/Sparx_PCA_Module.json new file mode 100644 index 00000000..64e24234 --- /dev/null +++ b/agency-indexes/DoE/Sparx_PCA_Module.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Sparx, a new environment for Cryo-EM image processing; Cryo-EM, Single particle reconstruction, principal component analysis; Hardware Req.: PC, MAC, Supercomputer, Mainframe, Multiplatform, Workstation. Software Req.: operating system is Unix; Compiler C++; type of files: source code, object library, executable modules, compilation instructions; sample problem input data. Location/transmission: http://sparx-em.org; User manual & paper: http://sparx-em.org;", + "homepageURL": "http://sparx-em.org", + "laborHours": 0.0, + "languages": [], + "name": "Sparx PCA Module", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://sparx-em.org/sparxwiki/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://sparx-em.org", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spatial_Environmental_Assessment_Tool__SEAT_.json b/agency-indexes/DoE/Spatial_Environmental_Assessment_Tool__SEAT_.json new file mode 100644 index 00000000..ce25f1fe --- /dev/null +++ b/agency-indexes/DoE/Spatial_Environmental_Assessment_Tool__SEAT_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08551O\nThe Spatial Environmental Assessment Tool (SEAT) evaluates potential environmental risk associated with marine energy device deployment by coupling modeled impacts with risk severity maps. As a graphical user interface-based software, it interacts with marine energy stressor and receptor data to evaluate the risk of changes to marine environment. SEAT, which relies on spatial and temporal data, is a plug-in for geospatial software QGIS. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 4286.4, + "languages": [ + "python" + ], + "name": "Spatial Environmental Assessment Tool (SEAT)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seat-qgis-plugin", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SpawnNet.json b/agency-indexes/DoE/SpawnNet.json new file mode 100644 index 00000000..e6bc2e50 --- /dev/null +++ b/agency-indexes/DoE/SpawnNet.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SpawnNet provides a networking interface similar to Linux sockets that runs natively on High-performance network interfaces. It is intended to be used to bootstrap parallel jobs and communication libraries like MPI.", + "laborHours": 8436.0, + "name": "SpawnNet", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/spawnnet/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/spawnnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spawn_[SWR-SWR-20-10].json b/agency-indexes/DoE/Spawn_[SWR-SWR-20-10].json new file mode 100644 index 00000000..35e8714b --- /dev/null +++ b/agency-indexes/DoE/Spawn_[SWR-SWR-20-10].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-01-22" + }, + "description": "Spawn is a next generation building simulation engine designed to build on the strengths of NREL's venerable EnergyPlus engine, and add new advanced HVAC and controls modeling capability by incorporating the Modelica equation based modeling language. In effect, Spawn is a hybrid of the existing EnergyPlus and Modelica software products, with some new software to provide glue between the components in order to provide a seamless end user experience.", + "laborHours": 0.0, + "languages": [ + "C++", + "C" + ], + "name": "Spawn [SWR-SWR-20-10]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Spawn", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spawn_v.0.5.0_Released_12.15.2023_[SWR-SWR-20-10].json b/agency-indexes/DoE/Spawn_v.0.5.0_Released_12.15.2023_[SWR-SWR-20-10].json new file mode 100644 index 00000000..8e6402ef --- /dev/null +++ b/agency-indexes/DoE/Spawn_v.0.5.0_Released_12.15.2023_[SWR-SWR-20-10].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-01-22", + "metadataLastUpdated": "2024-01-22" + }, + "description": "Spawn is a software package for performing co-simulations involving NREL's EnergyPlus\u2122 tool and Modelica. This package bundles the following items in one self-contained package.\n\n1. A method for connecting EnergyPlus models to Modelica\n2. A Modelica compiler toolchain for compiling and running Modelica models\n3. Modelica libraries and content, including the Modelica Buildings Library (MBL) and the Modelica Standard Library.\n\nThe Spawn installation package is fully self-contained, and there are no external third-party dependencies. Together the capabilities in this package provide a single integrated environment for performing hybrid Modelica and EnergyPlus simulations. The primary entry point is the Spawn command line interface.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "CMake" + ], + "name": "Spawn v.0.5.0 Released 12.15.2023 [SWR-SWR-20-10]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Spawn", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.5.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SpecTAD.json b/agency-indexes/DoE/SpecTAD.json new file mode 100644 index 00000000..890b9f47 --- /dev/null +++ b/agency-indexes/DoE/SpecTAD.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The SpecTAD software represents a refactoring of the Temperature Accelerated Dynamics (TAD2) code authored by Arthur F. Voter and Blas P. Uberuaga (LA-CC-02-05). SpecTAD extends the capabilities of TAD2, by providing algorithms for both temporal and spatial parallelism. The novel algorithms for temporal parallelism include both speculation and replication based techniques. SpecTAD also offers the optional capability to dynamically link to the open-source LAMMPS package.", + "laborHours": 29032.0, + "languages": [ + "Fortran" + ], + "name": "SpecTAD", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/spectad", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SpeciesTreeBuilder.json b/agency-indexes/DoE/SpeciesTreeBuilder.json new file mode 100644 index 00000000..51b331d6 --- /dev/null +++ b/agency-indexes/DoE/SpeciesTreeBuilder.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "This is the repository for \"SpeciesTreeBuilder\" developed by KBase. ", + "laborHours": 14440.0, + "languages": [], + "name": "SpeciesTreeBuilder", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/SpeciesTreeBuilder", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spectral.json b/agency-indexes/DoE/Spectral.json new file mode 100644 index 00000000..9581ebf0 --- /dev/null +++ b/agency-indexes/DoE/Spectral.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "zimmercj@ornl.gov" + }, + "date": { + "created": "2022-03-02", + "metadataLastUpdated": "2022-03-02" + }, + "description": "Spectral is a portable and transparent middleware library to enable use of the node-local burst buffers for accelerated application output on Summit and Frontier. It is used to enable large scientific applications to leverage the performance benefit of the in-node NVMe storage for periodic checkpoints without having to modify the application code. Spectral acheives this by intercepting write only file creates, redirecting the output, and then transfering the file to the original destination when the file is closed. Spectrals migration agent runs on the isolated core of each reserved node, so it does not occupy resources and based on some parameters the user could define which folder to be copied to the GPFS.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Spectral", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/cz7/spectral-io/-/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/cz7/spectral-io", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spectral_Efficiency_and_Tandem_Performance_Calculators_[SWR-24-92].json b/agency-indexes/DoE/Spectral_Efficiency_and_Tandem_Performance_Calculators_[SWR-24-92].json new file mode 100644 index 00000000..52efc5f4 --- /dev/null +++ b/agency-indexes/DoE/Spectral_Efficiency_and_Tandem_Performance_Calculators_[SWR-24-92].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-09-24", + "metadataLastUpdated": "2024-09-24" + }, + "description": "The Spectral Efficiency and Tandem Performance Calculators allow users to test material types for use in tandem photovoltaic devices to better understand if a given material could work well. The Spectral Efficiency (SE) calculator takes a set of current vs voltage (I-V) and quantum efficiency (QE) data along with a spectrum input and plots the spectral efficiency of the cells represented by the datasets for the spectrum provided. The Tandem Performance calculator uses the calculated spectral efficiency of top and bottom cells and the transmission data of the top cell to calculate performance metrics for a tandem device in either a two or four terminal architecture. The SE and Tandem Performance calculators are based on the following publication: Yu, Z., Leilaeioun, M. & Holman, Z. Selecting tandem partners for silicon solar cells. Nat Energy 1, 16137 (2016).", + "laborHours": 957.6, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "Spectral Efficiency and Tandem Performance Calculators [SWR-24-92]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SE-and-Tandems", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spectral_Plasma_Solver__SPS_.json b/agency-indexes/DoE/Spectral_Plasma_Solver__SPS_.json new file mode 100644 index 00000000..f257d84d --- /dev/null +++ b/agency-indexes/DoE/Spectral_Plasma_Solver__SPS_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2021-09-10" + }, + "description": "This is a framework for the solution of the Vlasov-Maxwell equations that describe the dynamics of charged particles (plasmas) and electromagnetic fields at the microscopic (kinetic) level. These equations represent a very fundamental mathematical model of plasmas and are commonly used in plasma physics for a variety of problems.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Spectral Plasma Solver (SPS)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SpectrumLook.json b/agency-indexes/DoE/SpectrumLook.json new file mode 100644 index 00000000..3972c353 --- /dev/null +++ b/agency-indexes/DoE/SpectrumLook.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SpectrumLook can be used to visually inspect the peptide sequence matches (PSMs) against fragmentation spectra in an LC-MS/MS dataset.", + "laborHours": 11430.4, + "languages": [], + "name": "SpectrumLook", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/SpectrumLook", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spherical_nanoindentation_stress-strain_analysis,_Version_1.json b/agency-indexes/DoE/Spherical_nanoindentation_stress-strain_analysis,_Version_1.json new file mode 100644 index 00000000..9b5e97a5 --- /dev/null +++ b/agency-indexes/DoE/Spherical_nanoindentation_stress-strain_analysis,_Version_1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Nanoindentation is a tool that allows the mechanical response of a variety of materials at the nano to micron length scale to be measured. Recent advances in spherical nanoindentation techniques have allowed for a more reliable and meaningful characterization of the mechanical response from nanoindentation experiments in the form on an indentation stress-strain curve. This code base, Spin, is written in MATLAB (The Mathworks, Inc.) and based on the analysis protocols developed by S.R. Kalidindi and S. Pathak [1, 2]. The inputs include the displacement, load, harmonic contact stiffness, harmonic displacement, and harmonic load from spherical nanoindentation tests in the form of an Excel (Microsoft) spreadsheet. The outputs include indentation stress-strain curves and indentation properties as well their variance due to the uncertainty of the zero-point correction in the form of MATLAB data (.mat) and figures (.png). [1] S. Pathak, S.R. Kalidindi. Spherical nanoindentation stress\u2013strain curves, Mater. Sci. Eng R-Rep 91 (2015). [2] S.R. Kalidindi, S. Pathak. Determination of the effective zero-point and the extraction of spherical nanoindentation stress-strain curves, Acta Materialia 56 (2008) 3523-3532.", + "laborHours": 440.8, + "name": "Spherical nanoindentation stress-strain analysis, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jsweaver/Spin", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sphynx.json b/agency-indexes/DoE/Sphynx.json new file mode 100644 index 00000000..3551f621 --- /dev/null +++ b/agency-indexes/DoE/Sphynx.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-09-18" + }, + "description": "Sphynx is a software library for parallel graph partitioning and load balancing. It partitions a set of vertices in a graph such that the vertex parts are balanced, and the edge cut is approximately minimized. The primary use case is to partition a computational graph into smaller tasks that can be assigned to processors (cores) for efficient parallel computing. Sphynx is based on the Trilinos scientific computing toolkit so can run on both multi-CPU and multi-GPU systems. SAND2020-12183 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 8344830.4, + "languages": [], + "name": "Sphynx", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spify_Parser_of_Input_Files_with_YAML_syntax.json b/agency-indexes/DoE/Spify_Parser_of_Input_Files_with_YAML_syntax.json new file mode 100644 index 00000000..ea73c9f4 --- /dev/null +++ b/agency-indexes/DoE/Spify_Parser_of_Input_Files_with_YAML_syntax.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-16" + }, + "description": "SPIFY is a C++ library for parsing input files to be used in scientific computing applications.\n\nThe library allows an application developer to define a full set of required and optional input variable of different types\nand handles all of the parsing and validation.", + "laborHours": 912.0, + "languages": [ + "C++" + ], + "name": "Spify Parser of Input Files with YAML syntax", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/spify", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spin_Wave_Genie.json b/agency-indexes/DoE/Spin_Wave_Genie.json new file mode 100644 index 00000000..e3049413 --- /dev/null +++ b/agency-indexes/DoE/Spin_Wave_Genie.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The four-dimensional scattering function S(Q,w) obtained by inelastic neutron scattering measurements provides unique \"dynamical fingerprints\" of the spin state and interactions present in complex magnetic materials. Extracting this information however is currently a slow and complex process that may take an expert -depending on the complexity of the system- up to several weeks of painstaking work to complete. Spin Wave Genie was created to abstract and automate this process. It strives to both reduce the time to complete this analysis and make these calculations more accessible to a broader group of scientists and engineers.", + "laborHours": 11658.4, + "name": "Spin Wave Genie", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SpinWaveGenie/SpinWaveGenie", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spinbox:_tools_for_many-body_quantum_systems_in_a_Monte_Carlo_context.json b/agency-indexes/DoE/Spinbox:_tools_for_many-body_quantum_systems_in_a_Monte_Carlo_context.json new file mode 100644 index 00000000..03005c92 --- /dev/null +++ b/agency-indexes/DoE/Spinbox:_tools_for_many-body_quantum_systems_in_a_Monte_Carlo_context.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-02", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Spinbox is a piece of software that facilitates quantum mechanical calculations relevant to Monte Carlo simulation of atomic nuclei. At the front lines of research on the nuclear many-body problem are a large number of supercomputer-scale simulation codes. These codes produce valuable results but can be hard to understand, especially for those without intimate knowledge of the relevant theoretical methods.\nThus, tools that fill pedagogical roles are extremely valuable. Spinbox makes it easy for one to replicate and analyze the computational processes relevant to a Quantum Monte Carlo (QMC) simulation that may be difficult to\nunderstand/debug/analyze due to the scale of the corresponding simulation software.\nSpinbox is written in Python using other state-of-the-art Python modules for numerical calculations. While a number of Python libraries exist that are suited to general quantum many-body calculations, the motivation of Spinbox is quite particular.\nIn Diffusion Monte Carlo methods (DMC, GFMC, AFDMC), the central calculation is the imaginary-time propagation of individual samples of the many-body wavefunction.\nAlthough quantum wavefunctions generally must be described by a probability distribution over a basis, DMC imbues particles (within one sample) with classical spatial coordinates. This method is unusual, so other Python packages are typically not set up to do this easily. Furthermore, the software has built-in options for nuclear systems assuming isospin symmetry, which can be set up with other libraries but is a nontrivial process to do so. Features:\n- numerical representation of samples of the many-body wavefunctions, including tensor-product states (used in AFDMC)\n- numerical representation of many-body operators, including tensor-product operators: general, spin, imaginary-time propagation, etc.\n- the correct associated arithmetic and algebra, implemented as class methods\n- classes for representing realistic nuclear two- and three-body Hamiltonians (e.g. Argonne V18, Illinois NNN)\n- large-scale parallel integration over random variables, crucial for the AFDMC method\nMy goal is to make this package open source so that anyone may use it and contribute to it, particularly other researchers doing AFDMC calculations", + "laborHours": 7022.4, + "languages": [], + "name": "Spinbox: tools for many-body quantum systems in a Monte Carlo context", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmrfox/spinbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spindle.json b/agency-indexes/DoE/Spindle.json new file mode 100644 index 00000000..9ab9bb41 --- /dev/null +++ b/agency-indexes/DoE/Spindle.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Spindle is software infrastructure that solves file system scalability problems associated with starting dynamically linked applications in HPC environments. When an HPC applications starts up thousands of processes at once, and those processes simultaneously access a shared file system to look for shared libraries, it can cause significant performance problems for both the application and other users. Spindle scalably coordinates the distribution of shared libraries to an application to avoid hammering the shared file system.", + "laborHours": 0.0, + "languages": [], + "name": "Spindle", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/hpc/Spindle/blob/devel/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/spindle", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spitfire.json b/agency-indexes/DoE/Spitfire.json new file mode 100644 index 00000000..c7f52271 --- /dev/null +++ b/agency-indexes/DoE/Spitfire.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Spitfire is a Python and C++ code for solving canonical flame structure problems to build tabulated chemistry models for the simulation of large-scale fires. Spitfire is a modular software with performance critical code written in C++, abstract numerical methods provided in Python, and chemistry tabulation techniques made convenient for high-level use by non-expert users. It facilitates both high-level usage and novel research in tabulated chemistry approaches. SAND2019-11791 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 60739.2, + "languages": [ + "C++", + "Cython", + "Python" + ], + "name": "Spitfire", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Spitfire", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Splash-ML_v0.1.json b/agency-indexes/DoE/Splash-ML_v0.1.json new file mode 100644 index 00000000..d498208d --- /dev/null +++ b/agency-indexes/DoE/Splash-ML_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-08-20", + "metadataLastUpdated": "2020-08-20" + }, + "description": "The Splash database and portal, also under development (https://lbl.wellspringsoftware.net/kms/invention/detail/3980/), ingests experimental data and references to datasets from a variety of sources, primarily lightsource beamlines. After deployment, it will contain a great deal of metadata and references to data from which many insights can be extracted.", + "laborHours": 668.8, + "languages": [], + "name": "Splash-ML v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/als-computing/splash-ml", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Splash_v1.0.json b/agency-indexes/DoE/Splash_v1.0.json new file mode 100644 index 00000000..2af59cfd --- /dev/null +++ b/agency-indexes/DoE/Splash_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-11", + "metadataLastUpdated": "2019-07-12" + }, + "description": "A database, web API and portal will be developed that stores data from synchotron experiments. The data stored will be: \n- metadata about the experiment (who ran it, when it was conducted, what proposal and ESAF were covered) \n- references to raw data (e.g. images taken at the beamline) \n- references to derived data \n\nBeamline users and Beamline staff will have private access to view experiment data and assign web-friendly visualizations to it. They will also be use the portal to download some of the data taken at the beamline. They we will be able to create and approve experiment pages that can be viewed publicly. \n\nThe software created for this project will include replication and fail over technologies to maintain a high level of uptime. \n\nSoftware developed in this project will be: \n- database schema \n- web middleware to create a web API \n- web-based user interface code", + "laborHours": 4833.6, + "languages": [], + "name": "Splash v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/als-computing/splash", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SplitML.json b/agency-indexes/DoE/SplitML.json new file mode 100644 index 00000000..52a70a00 --- /dev/null +++ b/agency-indexes/DoE/SplitML.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2022-07-15" + }, + "description": "SplitML (Signal Processing Library for Interference rejecTion by Machine Learning) is a code repository for a set of tools for interference rejection in complex time-domain signals. The goal of the tools is to provide machine learning modeling capabilities for rejecting interference. Recent related machine learning algorithms for signal processing have focused mostly on speech enhancement or multi-speaker speech separation; the tools in SplitML will extend these innovations to generic time-domain signals of interest. SplitML includes tools for generating synthetic noisy signals, code for customized machine learning models applicable to interference rejection, and tools for evaluating such algorithms against standard signal processing techniques. These components are written in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning and signal processing.", + "laborHours": 0.0, + "languages": [], + "name": "SplitML", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SplitML", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SpokeDarts.json b/agency-indexes/DoE/SpokeDarts.json new file mode 100644 index 00000000..53e3beac --- /dev/null +++ b/agency-indexes/DoE/SpokeDarts.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SpokeDarts software produces sample distributions with blue noise characteristics over arbitrary-dimensional spaces. More generally, spoke darts enable efficient searches and tailored distributions over high dimensional spaces. The software includes underlying geometric routines which are useful in their own right, such as efficient neighbor searches, random points on a sphere, and line-sphere intersections.", + "laborHours": 5000.8, + "languages": [ + "CMake", + "C++" + ], + "name": "SpokeDarts", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/SpokeDartsPublic?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SpokeDartsPublic", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sponge.json b/agency-indexes/DoE/Sponge.json new file mode 100644 index 00000000..ea4266ed --- /dev/null +++ b/agency-indexes/DoE/Sponge.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Sponge provides a web interface to Pulp (http://pulpproject.org/) that implements a particular workflow as described in the paper \"Staging Package Deployment via Repository Management\" (http://www.usenix.org/events/lisa11/tech/full_papers/Pierre.pdf). Namely, it implements a process for intensive management of software repositories to apply more deterministic updates to clients of those repositories.", + "laborHours": 2021.6, + "name": "Sponge", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stpierre/sponge", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Spot-Hadoop.json b/agency-indexes/DoE/Spot-Hadoop.json new file mode 100644 index 00000000..9761df91 --- /dev/null +++ b/agency-indexes/DoE/Spot-Hadoop.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Set of scripts (Python and Bash) to help users configure, run, and benchmark Hadoop clusters on ORNL computing infrastructure.", + "laborHours": 304.0, + "name": "Spot-Hadoop", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jhorey/SpotHadoop", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/StCUDA.json b/agency-indexes/DoE/StCUDA.json new file mode 100644 index 00000000..5c34feea --- /dev/null +++ b/agency-indexes/DoE/StCUDA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-12-07", + "metadataLastUpdated": "2018-12-10" + }, + "description": "StCUDA is a software package for VisualWorks Smalltalk that contains classes and methods that interfaces Smalltalk to CUDA API's.\nSupporting class StCUDA contains the low level calls to the CUDA API's", + "laborHours": 440.8, + "languages": [], + "name": "StCUDA", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/StCUDA", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stabilizer_Rank_Strong_Simulation_v.0.1.json b/agency-indexes/DoE/Stabilizer_Rank_Strong_Simulation_v.0.1.json new file mode 100644 index 00000000..0957fa63 --- /dev/null +++ b/agency-indexes/DoE/Stabilizer_Rank_Strong_Simulation_v.0.1.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This software improves upon the Clifford gate+T gate magic state strong simulation algorithm by Brayvi and Gosset. It provides a better stabilizer state decomposition that scales as 2^{0.463t}, an improvement over 2^{0.468t}, for t T gate magic states. This code enables simulations of universal quantum computing with that asymptotic scaling cost. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525 SAND2020-14293 O", + "laborHours": 0.0, + "languages": [], + "name": "Stabilizer Rank Strong Simulation v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Stabilizer-Rank-Strong-Simulation", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/StackP.json b/agency-indexes/DoE/StackP.json new file mode 100644 index 00000000..e76d9432 --- /dev/null +++ b/agency-indexes/DoE/StackP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "StackP is a static MPI tool enabling to run multiple PMPI tools.", + "laborHours": 121.6, + "languages": [], + "name": "StackP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PRUNERS/StackP", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stack_Trace_Analysis_Tool__STAT_.json b/agency-indexes/DoE/Stack_Trace_Analysis_Tool__STAT_.json new file mode 100644 index 00000000..db74c178 --- /dev/null +++ b/agency-indexes/DoE/Stack_Trace_Analysis_Tool__STAT_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-05-10", + "metadataLastUpdated": "2020-05-27" + }, + "description": "STAT is a light weight debugging tool that gathers and merges stack traces from all of the processes in a parallel application. STAT uses the MRNet tree based overlay network to broadcast commands from the tool front-end to the STAT daemons and for the front-end to gather the traces from the STAT daemons. As the traces propagate through the MRNet network tree, they are merged across all tasks to fonn a single call prefix tree. The call prefix tree can be examined to identify tuks with similar function call patterns and to delineate a small set of equivalence classes. A representative task from each of these classes can then be fed into a full feature debugger like TotalView for root cause analysis. ", + "laborHours": 27755.2, + "languages": [], + "name": "Stack Trace Analysis Tool (STAT)", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/STAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Staged_Event_Architecture.json b/agency-indexes/DoE/Staged_Event_Architecture.json new file mode 100644 index 00000000..81316f07 --- /dev/null +++ b/agency-indexes/DoE/Staged_Event_Architecture.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "Sea is a framework for a Staged Event Architecture, designed around non-blocking asynchronous communication facilities that are decoupled from the threading model chosen by any given application, Components for P networking and in-memory communication are provided. The Sea Java library encapsulates these concepts. Sea is used to easily build efficient and flexible low-level network clients and servers, and in particular as a basic communication substrate for Peer-to-Peer applications.", + "homepageURL": "https://dst.lbl.gov/ACSSoftware/sea", + "laborHours": 0.0, + "languages": [], + "name": "Staged Event Architecture", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://dst.lbl.gov/ACSSoftware/sea/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://dst.lbl.gov/ACSSoftware/sea", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Standard_Energy_Efficiency_Data_Platform.json b/agency-indexes/DoE/Standard_Energy_Efficiency_Data_Platform.json new file mode 100644 index 00000000..8046819a --- /dev/null +++ b/agency-indexes/DoE/Standard_Energy_Efficiency_Data_Platform.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The SEED platform is expected to be a building energy performance data management tool that provides federal, state and local governments, building owners and operators with an easy, flexible and cost-effective method to collect information about groups of buildings, oversee compliance with energy disclosure laws and demonstrate the economic and environmental benefits of energy efficiency. It will allow users to leverage a local application to manage data disclosure and large data sets without the IT investment of developing custom applications. The first users of SEED will be agencies that need to collect, store, and report/share large data sets generated by benchmarking, energy auditing, retro-commissioning or retrofitting of many buildings. Similarly, building owners and operators will use SEED to manage their own energy data in a common format and centralized location. SEED users will also control the disclosure of their information for compliance requirements, recognition programs such as ENERGY STAR, or data sharing with the Buildings Performance Database and/or other third parties at their discretion.", + "laborHours": 81031.2, + "name": "Standard Energy Efficiency Data Platform", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/SEED-platform/seed/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SEED-platform/seed", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Standard_Energy_Efficiency_Data_Platform\302\256.json" "b/agency-indexes/DoE/Standard_Energy_Efficiency_Data_Platform\302\256.json" new file mode 100644 index 00000000..d3321d58 --- /dev/null +++ "b/agency-indexes/DoE/Standard_Energy_Efficiency_Data_Platform\302\256.json" @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Standard Energy Efficiency Data Platform\u00ae (SEED Platform) provides public agencies and other organizations with a standardized but flexible, cost-effective, secure, enterprise data platform to manage portfolio scale building performance data from a variety of sources. The SEED Platform streamlines the administrative effort required by public agencies implementing building performance and transparency programs.", + "laborHours": 81031.2, + "name": "Standard Energy Efficiency Data Platform\u00ae", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/SEED-platform/seed/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SEED-platform/seed", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Standard_Energy_Efficiency_Data__SEED__Platform.json b/agency-indexes/DoE/Standard_Energy_Efficiency_Data__SEED__Platform.json new file mode 100644 index 00000000..193ced5f --- /dev/null +++ b/agency-indexes/DoE/Standard_Energy_Efficiency_Data__SEED__Platform.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-11-26" + }, + "description": "The SEED Platform is a web-based application that helps organizations easily manage data on the energy performance of large groups of buildings. Users can combine data from multiple sources, clean and validate it, and share the information with others. The software application provides an easy, flexible, and cost-effective method to improve the quality and availability of data to help demonstrate the economic and environmental benefits of energy efficiency, to implement programs, and to target investment activity.", + "laborHours": 81031.2, + "languages": [], + "name": "Standard Energy Efficiency Data (SEED) Platform", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/seed/blob/develop/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SEED-platform/seed", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stardust_Network_Measurement_Components__esnet-stardust-components__v1.json b/agency-indexes/DoE/Stardust_Network_Measurement_Components__esnet-stardust-components__v1.json new file mode 100644 index 00000000..09cc0fff --- /dev/null +++ b/agency-indexes/DoE/Stardust_Network_Measurement_Components__esnet-stardust-components__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "This software contains a set of components that allow us to measure and analyze the use and performance of computer networks using existing off the shelf Open Source components organized into a scalable and extensible system. The components were developed for and used within ESnet's Stardust Measurement Environment. The components are used to collect, process and display network measurement data in an architecture that employs a combination of Elasticsearch, Logstash and Grafana. The advantage of this approach is we can tailor system behavior to our analytical needs and expand its capability with new types of network measurement without waiting for a commercial vendor to support our fairly niche use cases. Additionally we have existing collaborations within our community that came about from prior research efforts that will benefit from the release of this software so that others can also contribute features.", + "laborHours": 16340.0, + "languages": [], + "name": "Stardust Network Measurement Components (esnet-stardust-components) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/stardust-snmp-pipeline", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/State-variable_model_of_porous_electrode_batteries_1-D_electrochemical_thermal_behavior.json b/agency-indexes/DoE/State-variable_model_of_porous_electrode_batteries_1-D_electrochemical_thermal_behavior.json new file mode 100644 index 00000000..bddf9a9c --- /dev/null +++ b/agency-indexes/DoE/State-variable_model_of_porous_electrode_batteries_1-D_electrochemical_thermal_behavior.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-23", + "metadataLastUpdated": "2019-01-30" + }, + "description": "Compared to full-order numerical models, the state-variable model (SVM) achieves multiple orders of reduction in computation time for simulation of electrochemical/thermal transport and reaction processes occurring inside lithium-ion and similar batteries with porous electrode construction. The model efficiently describes Li diffusion dynamics in active material and electrolyte phases, charge transfer kinetics, charge balance, and electron transport processes. The model requires a separate pre-processing step to identify SVM parameters.\n", + "homepageURL": "https://www.nrel.gov/workingwithus/licensing.html", + "laborHours": 0.0, + "languages": [ + "C", + "MATLAB" + ], + "name": "State-variable model of porous electrode batteries 1-D electrochemical/thermal behavior", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrel.gov/workingwithus/licensing.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrel.gov/workingwithus/licensing.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/State_Geothermal_Data_data_delivery_tools.json b/agency-indexes/DoE/State_Geothermal_Data_data_delivery_tools.json new file mode 100644 index 00000000..ed9af8ea --- /dev/null +++ b/agency-indexes/DoE/State_Geothermal_Data_data_delivery_tools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "This web site provides a single online system for AASG State Geothermal Data participants to integrate their data into the NGDS, discovering how to digitize at-risk, legacy, geothermal-relevant data and combine it with existing digital data to create a publicly accessible system.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "State Geothermal Data data delivery tools", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/State_of_Stress_Analysis_Tool__SOSAT_.json b/agency-indexes/DoE/State_of_Stress_Analysis_Tool__SOSAT_.json new file mode 100644 index 00000000..e8bec543 --- /dev/null +++ b/agency-indexes/DoE/State_of_Stress_Analysis_Tool__SOSAT_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-05-14", + "metadataLastUpdated": "2019-05-14" + }, + "description": "The State of Stress Assessment Tool (SOSAT) is a set of routines that take in information about a geologic carbon storage reservoir and generates a probability distribution for the state of stress in the reservoir before and during injection. As part of this, the tool reports the estimated probability of a critically-oriented fault becoming activated as a result of the injection. The tool also allows a storage site operator to evaluate the likely value of different types of characterization on the knowledge of the geomechanical conditions and probability of induced seismicity. ", + "homepageURL": "https://edx.netl.doe.gov/dataset/state-of-stress-analysis-tool", + "laborHours": 334.4, + "languages": [], + "name": "State of Stress Analysis Tool (SOSAT)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://edx.netl.doe.gov/dataset/state-of-stress-analysis-tool", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stateful_BACnet_Scraper_[SWR-13-26].json b/agency-indexes/DoE/Stateful_BACnet_Scraper_[SWR-13-26].json new file mode 100644 index 00000000..f9af2dd2 --- /dev/null +++ b/agency-indexes/DoE/Stateful_BACnet_Scraper_[SWR-13-26].json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This application works with the\u00a0Building Agent BACnet\u00a0library to provide stateful and modular control of device discovery, device OID lookup, and device polling/data scraping. Discovered devices and oids are persisted to a Mongo database, decoupling discovery from the polling process.", + "laborHours": 836.0, + "languages": [], + "name": "Stateful BACnet Scraper [SWR-13-26]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/BACnet-state", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Static_Narrative_Service.json b/agency-indexes/DoE/Static_Narrative_Service.json new file mode 100644 index 00000000..33a0e418 --- /dev/null +++ b/agency-indexes/DoE/Static_Narrative_Service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "A dynamic service for creating and managing Static Narratives.", + "laborHours": 45341.6, + "languages": [], + "name": "Static Narrative Service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/StaticNarrative", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/StatisticalClearSky.json b/agency-indexes/DoE/StatisticalClearSky.json new file mode 100644 index 00000000..eae84dd1 --- /dev/null +++ b/agency-indexes/DoE/StatisticalClearSky.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-13", + "metadataLastUpdated": "2022-09-13" + }, + "description": "Statistical estimation of a clear sky signal from PV system power data.", + "laborHours": 0.0, + "languages": [], + "name": "StatisticalClearSky", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/StatisticalClearSky", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Statistical_Mechanics_on_Lattices__smol__v0.0.1.json b/agency-indexes/DoE/Statistical_Mechanics_on_Lattices__smol__v0.0.1.json new file mode 100644 index 00000000..b17631bf --- /dev/null +++ b/agency-indexes/DoE/Statistical_Mechanics_on_Lattices__smol__v0.0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "smol is a Python implementation of the Cluster Expansion Method and extensions of this methodology; which is used to fit applied lattice models from first principle calculations for subsequent use in Monte Carlo simulations for computing thermodynamic and statistical properties of atomic configuration. smol has a several notable advantages over other similar software packages. The first being its Python implementation which makes it easy to use even for users with little software and coding skills. Despite being implemented in Python, essential Monte Carlo routines are implemented in Cython such that performance is not compromised and is competitive even to similar software implemented in C/C++. Furthermore, the package has specific functionality for handling complex ionic materials (such as cathodes and electrolytes) that is not readily available in other packages. Lastly, the software has a flexible and modular design with the intention of making it fast and efficient to develop and extend the methodology.", + "laborHours": 0.0, + "languages": [], + "name": "Statistical Mechanics on Lattices (smol) v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CederGroupHub/smol", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Statistical_modeling_with_Stan.json b/agency-indexes/DoE/Statistical_modeling_with_Stan.json new file mode 100644 index 00000000..9f821838 --- /dev/null +++ b/agency-indexes/DoE/Statistical_modeling_with_Stan.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2021-09-10" + }, + "description": "The material consists of a collection of simple Stan, python and R scripts, that serve as an example how to write statistical models with Stan.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Statistical modeling with Stan", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stellgap.json b/agency-indexes/DoE/Stellgap.json new file mode 100644 index 00000000..c1571eac --- /dev/null +++ b/agency-indexes/DoE/Stellgap.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Stellgap calculates the shear Alfven gap structure for 3D configurations (stellarators, RFPs, 3D tokamaks). These codes are used to calculate shear Alfven continua for 3D configurations, both with and without sound wave coupling effects.", + "laborHours": 2462.4, + "name": "Stellgap", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-Fusion/Stellgap", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stepped-Pressure_Equilibrium_Code__SPEC_.json b/agency-indexes/DoE/Stepped-Pressure_Equilibrium_Code__SPEC_.json new file mode 100644 index 00000000..0acee2ee --- /dev/null +++ b/agency-indexes/DoE/Stepped-Pressure_Equilibrium_Code__SPEC_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "czhu@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2018-06-27" + }, + "description": "Building on the theoretical foundations of Bruno & Laurence, that three-dimensional, (3D) magnetohydrodynamic (MHD) equilibria with \u201cstepped\u201d-pressure profiles are well-defined and guaranteed to exist, whereas 3D equilibria with integrable magnetic-fields and smooth pressure (or with non-integrable fields and continuous-but-fractal pressure) are pathological. 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Dewar.", + "homepageURL": "https://princetonuniversity.github.io/SPEC", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "Stepped-Pressure Equilibrium Code (SPEC)", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://princetonuniversity.github.io/SPEC", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stepwise_v._2.21.json b/agency-indexes/DoE/Stepwise_v._2.21.json new file mode 100644 index 00000000..13f78141 --- /dev/null +++ b/agency-indexes/DoE/Stepwise_v._2.21.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The statistical code, STEPWISE, evaluates variable importance by developing regression models between the observed response and input variables using either a forward, backward, or stepwise regression procedure on the raw or ranked data. The software will be used for performing sensitivity analysis on probabilistic results. Stepwise creates linear (or monotonic) regression of the output of interest using a set of input data in a stepwise fashion (i.e., adding one variable at a time). The program estimates parameters such as regression and standardized regressions coefficients for each selected input variables as well as the coefficient of determination of the resulting model", + "laborHours": 0.0, + "languages": [ + "FORTRAN" + ], + "name": "Stepwise v. 2.21", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/stepwise", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.21" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stiff_DAE_integrator_with_sensitivity_analysis_capabilities.json b/agency-indexes/DoE/Stiff_DAE_integrator_with_sensitivity_analysis_capabilities.json new file mode 100644 index 00000000..fc2e3f85 --- /dev/null +++ b/agency-indexes/DoE/Stiff_DAE_integrator_with_sensitivity_analysis_capabilities.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-07-13" + }, + "description": "IDAS is a general purpose (serial and parallel) solver for differential equation (ODE) systems with senstivity analysis capabilities. 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It improves storage efficiency by only storing the changed data and constructs on request a view of an arbitrary region at a given time by stitching together parts of various outputs. This enables scaling from a single process to 100s of nodes.", + "laborHours": 113270.4, + "languages": [ + "C", + "Python" + ], + "name": "Stitch v. 1.0 IO Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gflofst/stitch-io", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stitch_v._1.1_IO_Library.json b/agency-indexes/DoE/Stitch_v._1.1_IO_Library.json new file mode 100644 index 00000000..e6d737b0 --- /dev/null +++ b/agency-indexes/DoE/Stitch_v._1.1_IO_Library.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-02-16", + "metadataLastUpdated": "2024-07-19" + }, + "description": "Stitch is a new IO library focused around supporting simulations where only a small portion of the simulation space changes at each timestep. 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Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 113270.4, + "languages": [ + "C", + "Python", + "C++" + ], + "name": "Stitch v. 1.1 IO Library", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Stitch-IO", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stochastic_Energy_Deployment_System.json b/agency-indexes/DoE/Stochastic_Energy_Deployment_System.json new file mode 100644 index 00000000..2306bed1 --- /dev/null +++ b/agency-indexes/DoE/Stochastic_Energy_Deployment_System.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "SEDS is an economy-wide energy model of the U.S. The model captures dynamics between supply, demand, and pricing of the major energy types consumed and produced within the U.S. These dynamics are captured by including: the effects of macroeconomics; the resources and costs of primary energy types such as oil, natural gas, coal, and biomass; the conversion of primary fuels into energy products like petroleum products, electricity, biofuels, and hydrogen; and lastly the end- use consumption attributable to residential and commercial buildings, light and heavy transportation, and industry. Projections from SEDS extend to the year 2050 by one-year time steps and are generally projected at the national level. SEDS differs from other economy-wide energy models in that it explicitly accounts for uncertainty in technology, markets, and policy. SEDS has been specifically developed to avoid the computational burden, and sometimes fruitless labor, that comes from modeling significantly low-level details. Instead, SEDS focuses on the major drivers within the energy economy and evaluates the impact of uncertainty around those drivers.", + "homepageURL": "https://www.nrel.gov/analysis/seds", + "laborHours": 0.0, + "languages": [ + "Ruby" + ], + "name": "Stochastic Energy Deployment System", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/analysis/seds/download-model.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/analysis/seds", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stochastic_Energy_Deployment_System__SEDS__World_Oil_Model__WOM_.json b/agency-indexes/DoE/Stochastic_Energy_Deployment_System__SEDS__World_Oil_Model__WOM_.json new file mode 100644 index 00000000..48164694 --- /dev/null +++ b/agency-indexes/DoE/Stochastic_Energy_Deployment_System__SEDS__World_Oil_Model__WOM_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The function of the World Oil Market Model (WOMM) is to calculate a world oil price. SEDS will set start and end dates for the forecast period, and a time increment (assumed to be 1 year in the initial version). The WOMM will then randomly select an Annual Energy Outlook (AEO) oil price case and calibrate itself to that case. As it steps through each year, the WOMM will generate a stochastic supply shock to OPEC output and accept a new estimate of U.S. petroleum demand from SEDS. The WOMM will then calculate a new oil market equilibrium for the current year. The world oil price at the new equilibrium will be sent back to SEDS. When the end year is reached, the process will begin again with the selection of a new AEO forecast. Iterations over forecasts will continue until SEDS has completed all its simulation runs.", + "homepageURL": "https://www.nrel.gov/analysis/seds/oil-market-module.html", + "laborHours": 0.0, + "languages": [ + "Lumina Decision System's Analytica version 4.3" + ], + "name": "Stochastic Energy Deployment System (SEDS) World Oil Model (WOM)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.nrel.gov/analysis/seds/download-model.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/analysis/seds/oil-market-module.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stochastic_Hybrid_Models_and_Algorithms_for_Fluids__FHDeX__v1.json b/agency-indexes/DoE/Stochastic_Hybrid_Models_and_Algorithms_for_Fluids__FHDeX__v1.json new file mode 100644 index 00000000..7271e415 --- /dev/null +++ b/agency-indexes/DoE/Stochastic_Hybrid_Models_and_Algorithms_for_Fluids__FHDeX__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-22", + "metadataLastUpdated": "2019-09-23" + }, + "description": "This software contains numerical modules and application codes for studying the behavior of fluid dynamical systems where fluctuations play an important role in the dynamics. There is support for finite-volume/finite-difference solvers for partial differential equations, particle methods, and hybrid fluid-particle approaches.", + "laborHours": 40964.0, + "languages": [], + "name": "Stochastic Hybrid Models and Algorithms for Fluids (FHDeX) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-FHD/FHDeX.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stochastic_PArallel_Rarefied-gas_Time-accurate_Analyzer.json b/agency-indexes/DoE/Stochastic_PArallel_Rarefied-gas_Time-accurate_Analyzer.json new file mode 100644 index 00000000..8d060a8d --- /dev/null +++ b/agency-indexes/DoE/Stochastic_PArallel_Rarefied-gas_Time-accurate_Analyzer.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The SPARTA package is software for simulating low-density fluids via the Direct Simulation Monte Carlo (DSMC) method, which is a particle-based method for tracking particle trajectories and collisions as a model of a multi-species gas. The main component of SPARTA is a simulation code which allows the user to specify a simulation domain, populate it with particles, embed triangulated surfaces as boundary conditions for the flow, overlay a grid for finding pairs of collision partners, and evolve the system in time via explicit timestepping. The package also includes various pre- and post-processing tools, useful for setting up simulations and analyzing the results. The simulation code runs either in serial on a single processor or desktop machine, or can be run in parallel using the MPI message-passing library, to enable faster performance on large problems.", + "laborHours": 267930.4, + "languages": [ + "C++", + "Shell", + "C", + "Roff", + "CMake", + "Python" + ], + "name": "Stochastic PArallel Rarefied-gas Time-accurate Analyzer", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sparta/sparta", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stochastic_Parallel_PARticle_Kinetic_Simulator.json b/agency-indexes/DoE/Stochastic_Parallel_PARticle_Kinetic_Simulator.json new file mode 100644 index 00000000..48b87e77 --- /dev/null +++ b/agency-indexes/DoE/Stochastic_Parallel_PARticle_Kinetic_Simulator.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-09-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "SPPARKS is a kinetic Monte Carlo simulator which implements kinetic and Metropolis Monte Carlo solvers in a general way so that they can be hooked to applications of various kinds. Specific applications are implemented in SPPARKS as physical models which generate events (e.g. a diffusive hop or chemical reaction) and execute them one-by-one. Applications can run in parallel so long as the simulation domain can be partitioned spatially so that multiple events can be invoked simultaneously. SPPARKS is used to model various kinds of mesoscale materials science scenarios such as grain growth, surface deposition and growth, and reaction kinetics. It can also be used to develop new Monte Carlo models that hook to the existing solver and parallel infrastructure provided by the code.", + "laborHours": 165102.4, + "languages": [ + "C++", + "C" + ], + "name": "Stochastic Parallel PARticle Kinetic Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spparks", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stochastic_Techno_Economic_Model.json b/agency-indexes/DoE/Stochastic_Techno_Economic_Model.json new file mode 100644 index 00000000..5016c0ed --- /dev/null +++ b/agency-indexes/DoE/Stochastic_Techno_Economic_Model.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-05-28", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The Stochastic Techno-Economic Model or STEM is an analytical tool that estimates the logistics cost of different biomass feedstocks by incorporating uncertainty into the modeling framework. The scope of the model covers multiple stages of the biomass life cycle spanning feedstock harvest, collection, transportation and handling, preprocessing, and storage. The model determines the total logistics cost per dry metric ton ($/DM ton) for biomass and breaks down the costs for important cost categories including ownership related costs such as interest and depreciation, insurance, housing, and taxes as well as operating costs like repairs and maintenance, labor costs, and fuel and lube costs.", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Stochastic Techno Economic Model", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/STEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stokhos_v_1.0.json b/agency-indexes/DoE/Stokhos_v_1.0.json new file mode 100644 index 00000000..81e44831 --- /dev/null +++ b/agency-indexes/DoE/Stokhos_v_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A Trilinos package for applying stochastic Galerkin uncertainty quantification methods to large-scale C++ application codes, primarily stochastic partial differential equations. Stokhos is intended for use in estimating uncertainties for general scientific computations and is based on published algorithms. It provides no capability for implementing those computations itself. Estimating uncertainties and errors from solution algorithms or simulations, primarily simulations of partial differential equations, arising from uncertainties or errors in solution algorithm or simulation input data, including statistical moments, probabilities, and coefficients of variation.", + "laborHours": 8344830.4, + "name": "Stokhos v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stonix,_Version_0.x.json b/agency-indexes/DoE/Stonix,_Version_0.x.json new file mode 100644 index 00000000..a814a5c9 --- /dev/null +++ b/agency-indexes/DoE/Stonix,_Version_0.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "STONIX is a program for configuring UNIX and Linux computer operating systems. It applies configurations based on the guidance from publicly accessible resources such as: NSA Guides, DISA STIGs, the Center for Internet Security (CIS), USGCB and vendor security documentation. STONIX is written in the Python programming language using the QT4 and PyQT4 libraries to provide a GUI. The code is designed to be easily extensible and customizable.", + "laborHours": 56878.4, + "name": "Stonix, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CSD-Public/stonix", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stots__structured_Threat_Observation_Tool_Set_.json b/agency-indexes/DoE/Stots__structured_Threat_Observation_Tool_Set_.json new file mode 100644 index 00000000..10d2b9c2 --- /dev/null +++ b/agency-indexes/DoE/Stots__structured_Threat_Observation_Tool_Set_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-06-26", + "metadataLastUpdated": "2023-03-07" + }, + "description": "STOTS (Structured Threat Observation Tool Set) is a collection of tools that allow users in a test environment to create STIX v2 observable objects.", + "laborHours": 1140.0, + "languages": [ + "Python" + ], + "name": "Stots (structured Threat Observation Tool Set)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/STOTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stratimikos_Wrapper_Package.json b/agency-indexes/DoE/Stratimikos_Wrapper_Package.json new file mode 100644 index 00000000..e7bb6e5d --- /dev/null +++ b/agency-indexes/DoE/Stratimikos_Wrapper_Package.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Stratimikos is a small package of C++ wrappers for linear solver and preconditioning functionality exposed through Thyra interfaces. This package makes is possible to aggregate all of the general linear solver capability from the packages Amesos, AztecOO, Belos, lfpack, ML and others into a simple to use, parameter-list driven, interface to linear solvers. This initial version of Stratimikos contains just one utility class for building linear solvrs and preconditioners out of Epetra-based linear operators.", + "laborHours": 8344830.4, + "name": "Stratimikos Wrapper Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Strawman.json b/agency-indexes/DoE/Strawman.json new file mode 100644 index 00000000..2c4e8f70 --- /dev/null +++ b/agency-indexes/DoE/Strawman.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "A many-core capable lightweight in situ visualization and analysis infrastructure for multi-physics HPC simulations.\n", + "laborHours": 101490.4, + "languages": [], + "name": "Strawman", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/strawman", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stream-Processing_Architecture_for_Real-time_Cyber-physical_Security__SPARCS__v0.9.json b/agency-indexes/DoE/Stream-Processing_Architecture_for_Real-time_Cyber-physical_Security__SPARCS__v0.9.json new file mode 100644 index 00000000..150bb4eb --- /dev/null +++ b/agency-indexes/DoE/Stream-Processing_Architecture_for_Real-time_Cyber-physical_Security__SPARCS__v0.9.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-31", + "metadataLastUpdated": "2018-07-31" + }, + "description": "The Stream-Processing Architecture for Real-time Cyber-physical Security is a generalized framework for extracting power-related sensor information from sensors, optionally analyzing that data on computing platforms local to the sensors, transmitting that information to a central location, storing that information, running centralized analytics on the information, and providing both API and visual access to that information.", + "laborHours": 25444.8, + "languages": [], + "name": "Stream-Processing Architecture for Real-time Cyber-physical Security (SPARCS) v0.9", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnl-cybersecurity/sparcs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Streaming_Analytics_Machine__SAM__v._0.0.1.json b/agency-indexes/DoE/Streaming_Analytics_Machine__SAM__v._0.0.1.json new file mode 100644 index 00000000..455c61cc --- /dev/null +++ b/agency-indexes/DoE/Streaming_Analytics_Machine__SAM__v._0.0.1.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-08-15", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This is software developed in the course of my dissertation work, which was funded by Sandia. The software includes a library (the Streaming Analytics Machine or SAM) for expressing machine learning and subgraph matching over streaming data sources. It also includes a utility that will convert from a high-level language, the Streaming Analytics Language (SAL) to SAM.\n\nSAND2019-4322 M", + "laborHours": 13604.0, + "languages": [ + "C++", + "Jupyter Notebook", + "Scala", + "Python" + ], + "name": "Streaming Analytics Machine (SAM) v. 0.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Streaming_Analytics_and_Data_Engineering.json b/agency-indexes/DoE/Streaming_Analytics_and_Data_Engineering.json new file mode 100644 index 00000000..0f513784 --- /dev/null +++ b/agency-indexes/DoE/Streaming_Analytics_and_Data_Engineering.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "SADE is a software package for rapidly assembling analytic pipelines to manipulate data. The packages consists of the engine that manages the data and coordinates the movement of data between the tasks performing a function, a set of core libraries consisting of plugins that perform common tasks, and a framework to extend the system supporting the development of new plugins. Currently through configuration files, a pipeline can be defined that maps the routing of data through a series of plugins. Pipelines can be run in a batch mode or can process streaming data; they can be executed from the command line or run through a Windows background service. There currently exists over a hundred plugins, over fifty pipeline configurations, and the software is now being used by about a half-dozen projects.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Windows.Net framework 4.5, C#" + ], + "name": "Streaming Analytics and Data Engineering", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Streaming_Canvas.json b/agency-indexes/DoE/Streaming_Canvas.json new file mode 100644 index 00000000..74071480 --- /dev/null +++ b/agency-indexes/DoE/Streaming_Canvas.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Streaming Canvas is an interactive data visualization tool for high dimensional data such as text documents. It allows the user to interactively analyze documents.", + "laborHours": 104226.4, + "name": "Streaming Canvas", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/aim-science-of-interaction/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/aim-science-of-interaction", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Streaming_Statistics.json b/agency-indexes/DoE/Streaming_Statistics.json new file mode 100644 index 00000000..121f92c7 --- /dev/null +++ b/agency-indexes/DoE/Streaming_Statistics.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2022-03-24" + }, + "description": "In the context of a larger effort for in situ data analytics, there is a need to calculate basic statistics metrics (e.g., count, mean, median) online as new data points become available. Originally, the code for such online, or in other words streaming, statistics was part of the TALASS (Topological Analysis of Large- Scale Simulations) library. We isolated the relevant code and created a standalone library from it called Streaming Statistics. We also added an ability to serialize and deserialize the statistics objects so that the library can be used in distributed, task-based processing. To use the Streaming Statistics library, the user chooses a statistic, constructs an object for it, and then \"adds\" values to it, which means the statistic is augmented.", + "laborHours": 0.0, + "languages": [], + "name": "Streaming Statistics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/STREAMSTAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stride_Search_v._1.0.json b/agency-indexes/DoE/Stride_Search_v._1.0.json new file mode 100644 index 00000000..41d4b005 --- /dev/null +++ b/agency-indexes/DoE/Stride_Search_v._1.0.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Stride Search provides a flexible tool for detecting storms or other extreme climate events in high-resolution climate data sets saved on uniform latitude-longitude grids in standard NetCDF format. Users provide the software a quantitative description of a meteorological event they are interested in; the software searches a data set for locations in space and time that meet the user\u2019s description. In its first stage, Stride Search performs a spatial search of the data set at each timestep by dividing a search domain into circular sectors of constant geodesic radius. Data from a netCDF file is read into memory for each circular search sector. If the data meet or exceed a set of storm identification criteria (defined by the user), a storm is recorded to a linked list. Finally, the linked list is examined and duplicate detections of the same storm are removed and the results are written to an output file. The first stage\u2019s output file is read by a second program that builds storm. Additional identification criteria may be applied at this stage to further classify storms. Storm tracks are the software\u2019s ultimate output and routines are provided for formatting that output for various external software libraries for plotting and tabulating data.", + "laborHours": 8116.8, + "languages": [ + "C++", + "CMake", + "Fortran", + "Python" + ], + "name": "Stride Search v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/StrideSearch", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Stride_Version_1.0.json b/agency-indexes/DoE/Stride_Version_1.0.json new file mode 100644 index 00000000..1a896d6a --- /dev/null +++ b/agency-indexes/DoE/Stride_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "STRIDE is a suite of benchmarks, 8 in total, which access a computers low level caches and memory in a variety of patterns. The resulting performance of the kernels provides significant insight into the performance that a real application may incur and dictate how certain algorithmic choices should be made.", + "homepageURL": "https://asc.llnl.gov/sequoia/benchmarks", + "laborHours": 0.0, + "name": "Stride Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://asc.llnl.gov/sequoia/benchmarks", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/String_Length_Calculator_v0.0.3.json b/agency-indexes/DoE/String_Length_Calculator_v0.0.3.json new file mode 100644 index 00000000..31447ac1 --- /dev/null +++ b/agency-indexes/DoE/String_Length_Calculator_v0.0.3.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-02-27", + "metadataLastUpdated": "2021-03-01" + }, + "description": "The string length calculator simplifies the choice of string length for photovoltaic power plants. It uses open source tools to model the system open-circuit voltage over time based on established approaches used in the field by principal engineers and suggests a string length.", + "laborHours": 0.0, + "languages": [], + "name": "String Length Calculator v0.0.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/toddkarin/vocmax", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Structural_Simluation_Toolkit__SST__V_2.0.json b/agency-indexes/DoE/Structural_Simluation_Toolkit__SST__V_2.0.json new file mode 100644 index 00000000..d1f22666 --- /dev/null +++ b/agency-indexes/DoE/Structural_Simluation_Toolkit__SST__V_2.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The SST provides a parallel framework to perform system simulation of computer architectures to determine their performance and power consumption. Additionally, the SST contains basic models of a computer processor, and interconnect and can connect to an external memory simulator (DRAMSim II). The SST framework provides a simple interface by which other computer simulation models can be combined under a common parallel discrete event-based simulation environment. This allows design exploration of future architectures, analysis of how current computer programs will function on future architectures. The SST provides a parallel discrete event simulation framework, including partitioning and object distribution over MPI. It also provides a mechanism by which components can report their power consumption for analysis.", + "laborHours": 25384.0, + "name": "Structural Simluation Toolkit (SST) V 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sstsimulator/sst-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Structural_Simluation_Toolkit__SST__v.11.0.json b/agency-indexes/DoE/Structural_Simluation_Toolkit__SST__v.11.0.json new file mode 100644 index 00000000..b1dab3de --- /dev/null +++ b/agency-indexes/DoE/Structural_Simluation_Toolkit__SST__v.11.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-09-30", + "metadataLastUpdated": "2021-09-30" + }, + "description": "The SST provides a parallel framework to perform system simulation of computer architectures to determine their performance and power consumption. Additionally, the SST contains basic models of a computer processor, and interconnect and can connect to an external memory simulator (DRAMSim II). The SST framework provides a simple interface by which other computer simulation models can be combined under a common parallel discrete event-based simulation environment. This allows design exploration of future architectures, analysis of how current computer programs will function on future architectures. The SST provides a parallel discrete event simulation framework, including partitioning and object distribution over MPI. It also provides a mechanism by which components can report their power consumption for analysis.", + "laborHours": 25384.0, + "languages": [], + "name": "Structural Simluation Toolkit (SST) v.11.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sstsimulator/sst-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "11.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Structural_Simluation_Toolkit__SST__v.12.0.json b/agency-indexes/DoE/Structural_Simluation_Toolkit__SST__v.12.0.json new file mode 100644 index 00000000..b9d37645 --- /dev/null +++ b/agency-indexes/DoE/Structural_Simluation_Toolkit__SST__v.12.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-10", + "metadataLastUpdated": "2022-10-10" + }, + "description": "The Structural Simulation Toolkit (SST) was developed to explore innovations in highly concurrent computing systems where the instruction set architecture (ISA), micro-architecture, and memory interact with the programming model and communications system. The package provides a fully modular design for extensive exploration of an individual system parameter as well as a parallel simulation environment based on message passing interface (MPI) which enable a high level of performance as well as the ability to look at large systems. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 25384.0, + "languages": [ + "Python", + "C++" + ], + "name": "Structural Simluation Toolkit (SST) v.12.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sstsimulator/sst-core", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "12.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Structured_Adaptive_Mesh_Refinement_Application_Infrastructure.json b/agency-indexes/DoE/Structured_Adaptive_Mesh_Refinement_Application_Infrastructure.json new file mode 100644 index 00000000..ca416954 --- /dev/null +++ b/agency-indexes/DoE/Structured_Adaptive_Mesh_Refinement_Application_Infrastructure.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SAMRAI is an object-oriented support library for structured adaptice mesh refinement (SAMR) simulation of computational science problems, modeled by systems of partial differential equations (PDEs). SAMRAI is developed and maintained in the Center for Applied Scientific Computing (CASC) under ASCI ITS and PSE support. SAMRAI is used in a variety of application research efforts at LLNL and in academia. These applications are developed in collaboration with SAMRAI development team members.", + "laborHours": 279938.4, + "name": "Structured Adaptive Mesh Refinement Application Infrastructure", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SAMRAI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Structured_Multifrontal_Sparse_Solver.json b/agency-indexes/DoE/Structured_Multifrontal_Sparse_Solver.json new file mode 100644 index 00000000..bae7fa83 --- /dev/null +++ b/agency-indexes/DoE/Structured_Multifrontal_Sparse_Solver.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "StruMF is an algebraic structured preconditioner for the interative solution of large sparse linear systems. The preconditioner corresponds to a multifrontal variant of sparse LU factorization in which some dense blocks of the factors are approximated with low-rank matrices. It is algebraic in that it only requires the linear system itself, and the approximation threshold that determines the accuracy of individual low-rank approximations. Favourable rank properties are obtained using a block partitioning which is a refinement of the partitioning induced by nested dissection ordering.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "C compilers" + ], + "name": "Structured Multifrontal Sparse Solver", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SubKit.json b/agency-indexes/DoE/SubKit.json new file mode 100644 index 00000000..e4d1ab6a --- /dev/null +++ b/agency-indexes/DoE/SubKit.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "radercd@ornl.gov" + }, + "date": { + "created": "2019-06-13", + "metadataLastUpdated": "2020-09-09" + }, + "description": "Generating a CTF (thermal-hydraulics subchannel code) model can be time consuming and error prone because of the rigid formatting of the input file and the amount of input requirements. Because of the structured input format, making small changes to a model can require large scale changes to the input file. Furthermore, a user typically has to perform calculations to develop CTF input parameters from actual model geometry. Changing model geometry requires re-calculating input parameters and copying them from wherever the calculation was performed, be it a script, spreadsheet, or piece of paper. This process complicates the quality assurance process for that model and makes changing the model more difficult. CtfDeckBuilder is an object-oriented Python interface to CTF that allows the user to build a CTF model in Python. The user no longer needs to interface with the CTF input file when using the CtfDeckBuilder. The interface reduces the information required of the user by offering defaults for most modeling options provided by CTF. The user can perform calculations directly in Python when building the model so that calculations stay with the model itself. ", + "laborHours": 461852.0, + "languages": [ + "Python 2.7.13" + ], + "name": "SubKit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/CTF/SubKit", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Subsurface_Transport_Over_Multiple_Phases_Demonstration_Software.json b/agency-indexes/DoE/Subsurface_Transport_Over_Multiple_Phases_Demonstration_Software.json new file mode 100644 index 00000000..c0c5469a --- /dev/null +++ b/agency-indexes/DoE/Subsurface_Transport_Over_Multiple_Phases_Demonstration_Software.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The STOMP simulator is a suite of numerical simulators developed by Pacific Northwest National Laboratory for addressing problems involving coupled multifluid hydrologic, thermal, geochemical, and geomechanical processes in the subsurface. The simulator has been applied to problems concerning environmental remediation, environmental stewardship, carbon sequestration, conventional petroleum production, and the production of unconventional hydrocarbon fuels. The simulator is copyrighted by Battelle Memorial Institute, and is available outside of PNNL via use agreements. To promote the open exchange of scientific ideas the simulator is provided as source code. A demonstration version of the simulator has been developed, which will provide potential new users with an executable (not source code) implementation of the software royalty free. Demonstration versions will be offered via the STOMP website for all currently available operational modes of the simulator. The demonstration versions of the simulator will be configured with the direct banded linear system solver and have a limit of 1,000 active grid cells. This will provide potential new users with an opportunity to apply the code to simple problems, including many of the STOMP short course problems, without having to pay a license fee. Users will be required to register on the STOMP website prior to receiving an executable.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Fortran 90" + ], + "name": "Subsurface Transport Over Multiple Phases Demonstration Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sudoku_Online_Testing_Framework_v.0.2.json b/agency-indexes/DoE/Sudoku_Online_Testing_Framework_v.0.2.json new file mode 100644 index 00000000..534ba5ea --- /dev/null +++ b/agency-indexes/DoE/Sudoku_Online_Testing_Framework_v.0.2.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2021-08-16" + }, + "description": "The Sudoku Online Testing Framework provides a configurable basis for testing user interactions to solve visualization-related problems with sudoku puzzles and games. It consists of a server, a client, and test code. The python server implements sudoku puzzle logic and board selection functions. The JavaScript client implements a graphical user interface (GUI) front-end to display the puzzles and facilitate interactions with users. Within the GUI, logical rules may be selected. Cells may be selected to \u201cpivot\u201d on to make a board for each possible value in the cell. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-6409 O", + "laborHours": 0.0, + "languages": [ + "JavaScript", + "Python" + ], + "name": "Sudoku Online Testing Framework v.0.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sudoku-online", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sulfur_TES_ML_[SWR-23-02].json b/agency-indexes/DoE/Sulfur_TES_ML_[SWR-23-02].json new file mode 100644 index 00000000..7d242ed8 --- /dev/null +++ b/agency-indexes/DoE/Sulfur_TES_ML_[SWR-23-02].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-11-14", + "metadataLastUpdated": "2022-11-22" + }, + "description": "Sulfur TES ML contains code originally created to develop surrogate ML models to mimic the utility of CFD simulations of Sulfur TES systems. It has been adapted to provide a comprehensive package for building, training, validating, testing, and optimizing regression models with customizable features and targets.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "Sulfur TES ML [SWR-23-02]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/sulfur_tes_ml", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sunlamp.json b/agency-indexes/DoE/Sunlamp.json new file mode 100644 index 00000000..ce770877 --- /dev/null +++ b/agency-indexes/DoE/Sunlamp.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The purpose of this model was to facilitate the design of a control system that uses fine grained control of residential and small commercial HVAC loads to counterbalance voltage swings caused by intermittent solar power sources (e.g., rooftop panels) installed in that distribution circuit. Included is the source code and pre-compiled 64 bit dll for adding building HVAC loads to an OpenDSS distribution circuit. As written, the Makefile assumes you are using the Microsoft C++ development tools.", + "homepageURL": "https://sourceforge.net/projects/sunlamp", + "laborHours": 1246.4, + "languages": [ + "Visual Studio 2015" + ], + "name": "Sunlamp", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sourceforge.net/p/sunlamp/code/ci/master/tree/copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/sunlamp", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Super-Cell_Random_APproximates_SCRAPs_:_A_Multicomponent_Alloy_Structure_Design_Tool.json b/agency-indexes/DoE/Super-Cell_Random_APproximates_SCRAPs_:_A_Multicomponent_Alloy_Structure_Design_Tool.json new file mode 100644 index 00000000..e4465d29 --- /dev/null +++ b/agency-indexes/DoE/Super-Cell_Random_APproximates_SCRAPs_:_A_Multicomponent_Alloy_Structure_Design_Tool.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2023-09-29", + "metadataLastUpdated": "2023-09-29" + }, + "description": "A novel Hybrid CUCKOO SEARCH determines combinatorial global optimum SCRAPs for specified point and pair correlations in high-entropy alloys having proper distributions.", + "laborHours": 0.0, + "languages": [ + "C++", + "Python" + ], + "name": "Super-Cell Random APproximates(SCRAPs): A Multicomponent Alloy Structure Design Tool", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DuaneDJohnson/Hybrid-Cuckoo-Search", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SuperLU.json b/agency-indexes/DoE/SuperLU.json new file mode 100644 index 00000000..457838fc --- /dev/null +++ b/agency-indexes/DoE/SuperLU.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2022-02-01" + }, + "description": "SuperLU is a general purpose library for the direct solution of large, sparse, nonsymmetric systems of linear equations on high performance machines.", + "laborHours": 119426.4, + "languages": [], + "name": "SuperLU", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/xiaoyeli/superlu/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xiaoyeli/superlu", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SuperNeuroABM.json b/agency-indexes/DoE/SuperNeuroABM.json new file mode 100644 index 00000000..87a34f6f --- /dev/null +++ b/agency-indexes/DoE/SuperNeuroABM.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "gunaratnecs@ornl.gov" + }, + "date": { + "created": "2023-03-22", + "metadataLastUpdated": "2023-03-28" + }, + "description": "A GPU-based multi-agent simulation framework for neuromorphic computing", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "SuperNeuroABM", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/superneuroabm", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SuperNu_Version_4.x.json b/agency-indexes/DoE/SuperNu_Version_4.x.json new file mode 100644 index 00000000..e6b5f886 --- /dev/null +++ b/agency-indexes/DoE/SuperNu_Version_4.x.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-29" + }, + "description": "We seek to release SuperNu, Version 4.x, as a continuation of development for the open source SuperNu software. The SuperNu, Version 3.x Monte Carlo radiative transfer code for astrophysical transients was released with GPLv3 copyright, asserted by LANL in 2015. For the next release we have features planned for development , including: opacity implementation (including non-local thermodynamic equilibrium effects), generalized source implementation (e.g. for emulating shock heating in Type II supernovae), 3T (electron, ion, radiation) internal energy update, special relativity corrections through O(v^2/c^2), light polarization (e.g. for comparison to spectroplarimetry observations of supernovae and kilonovae), and infrastructure features (checkpoint and restart of simulations, and tools including setup and Slurm batch scripts and simulation post-processing/analysis scripts). These features are intended to improve the fidelity and/or better understand uncertainty in supernova and kilonova light curve calculations.", + "laborHours": 0.0, + "languages": [], + "name": "SuperNu Version 4.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/SuperNu", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Superstrider_simulator.json b/agency-indexes/DoE/Superstrider_simulator.json new file mode 100644 index 00000000..f360a9ac --- /dev/null +++ b/agency-indexes/DoE/Superstrider_simulator.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "A simulation of a research processor-in-memory class computer architecture running the accumulation function of sparse matrix-matrix multiply.", + "laborHours": 1352.8, + "languages": [ + "C++" + ], + "name": "Superstrider simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.debenedictis.org/SuperStrider.cpp", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/superstrider", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Supplemental_Information_to_'Data_visualization_heuristics_for_the_physical_sceinces'.json b/agency-indexes/DoE/Supplemental_Information_to_'Data_visualization_heuristics_for_the_physical_sceinces'.json new file mode 100644 index 00000000..7699fb9d --- /dev/null +++ b/agency-indexes/DoE/Supplemental_Information_to_'Data_visualization_heuristics_for_the_physical_sceinces'.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "radercd@ornl.gov" + }, + "date": { + "created": "2019-06-12", + "metadataLastUpdated": "2020-09-09" + }, + "description": "The code was developed to produce figures for an associated Journal of Materials and Design publication.", + "laborHours": 334.4, + "languages": [ + "Python" + ], + "name": "Supplemental Information to 'Data visualization heuristics for the physical sceinces'", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/nmp/data_visualization_paper", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0,0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Supplemental_Material_for_Bernstein-2017-founders-species.json b/agency-indexes/DoE/Supplemental_Material_for_Bernstein-2017-founders-species.json new file mode 100644 index 00000000..b77354b5 --- /dev/null +++ b/agency-indexes/DoE/Supplemental_Material_for_Bernstein-2017-founders-species.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2018-07-19" + }, + "description": "The software was produced to reproduce biologically relevant results and present them using clear and elegant graphs.", + "laborHours": 3632.8, + "languages": [], + "name": "Supplemental Material for Bernstein-2017-founders-species", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/bernstein-2017-founders-species", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/brislawn-2018-founders-species", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SurFE-XD__Surface_curvature-driven_Finite_Elements_model_for_Diffusion_under_eXtreme_conditions_.json b/agency-indexes/DoE/SurFE-XD__Surface_curvature-driven_Finite_Elements_model_for_Diffusion_under_eXtreme_conditions_.json new file mode 100644 index 00000000..172ebf1e --- /dev/null +++ b/agency-indexes/DoE/SurFE-XD__Surface_curvature-driven_Finite_Elements_model_for_Diffusion_under_eXtreme_conditions_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-01-26" + }, + "description": "SurFE-XD is a mesoscale finite element framework to model surface diffusion under mutliphysics environments. The code uses legacy C++ library dolphin wrapped with python in a FEniCS driven unified form language and just-in-time (JIT) compilation setting. The purpose of the release is to attract wide-ranging usage of the code along with publication supplementation to support reproducibility of scientific data. SurFE-XD has been originally conceived under the LDRD-DR funding for \u201cHigh-Gradient (C-BAND) Breakdown tolerant accelerator materials project. Currently SrFE-XD support electrostatics and Thermo-elasticity driven surface diffusion kernels. Releasing the code will also enable to include contributions from other physical regimes e.g., plasticity and electrodynamics etc as well portability to GPU-based platforms.", + "laborHours": 0.0, + "languages": [], + "name": "SurFE-XD (Surface curvature-driven Finite Elements model for Diffusion under eXtreme conditions)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sbagchi-LANL/SurFE-XD", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Surface_Method_Raytracer.json b/agency-indexes/DoE/Surface_Method_Raytracer.json new file mode 100644 index 00000000..767df67c --- /dev/null +++ b/agency-indexes/DoE/Surface_Method_Raytracer.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-05-28", + "metadataLastUpdated": "2024-05-28" + }, + "description": "Matlab based experiments that implement multiple ray tracing methods for deterministic radiation\ntransport, including the Surface Method as described in the PhD Thesis, \"CONSERVATIVE FIRSTCOLLISION\nSOURCE TREATMENT FOR RAY EFFECT MITIGATION IN DISCRETE-ORDINATE\nRADIATION TRANSPORT SOLUTIONS\" by Alex Christensen.", + "laborHours": 1550.4, + "languages": [], + "name": "Surface Method Raytracer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/abcbitz/First_Collision_Source_Treatment", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Surfactant.json b/agency-indexes/DoE/Surfactant.json new file mode 100644 index 00000000..503eb347 --- /dev/null +++ b/agency-indexes/DoE/Surfactant.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-07-14", + "metadataLastUpdated": "2023-07-14" + }, + "description": "Surfactant is a tool to generate an SBOM for the files in a directory/system based on information contained in various file format, including but not limited to PE, ELF, Mach-O, Java classes, .NET\nassemblies, and various source code files/scripts. Gathered information can be output in a variety of different SBOM formats, and functionality is provided to manipulate and analyze SBOMs (merging, manual additions, querying info, etc). Users are able to add new features via a plugin system.", + "laborHours": 0.0, + "languages": [], + "name": "Surfactant", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Surfactant", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Surrogate_Optimization_of_Computationally_Expensive_Black-Box_Problems_with_Hidden_Constraints__SHEBO__v1.0.json b/agency-indexes/DoE/Surrogate_Optimization_of_Computationally_Expensive_Black-Box_Problems_with_Hidden_Constraints__SHEBO__v1.0.json new file mode 100644 index 00000000..20c4e97d --- /dev/null +++ b/agency-indexes/DoE/Surrogate_Optimization_of_Computationally_Expensive_Black-Box_Problems_with_Hidden_Constraints__SHEBO__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-16", + "metadataLastUpdated": "2019-10-16" + }, + "description": "SHEBO (surrogate optimization of problems with hidden constraints and expensive black-box objectives) is an efficient optimization algorithm that employs surrogate models to solve computationally expensive black-box simulation optimization problems that have hidden constraints. Hidden constraints are encountered when the objective function evaluation does not return a value for a parameter vector. These constraints are often encountered in optimization problems in which the objective function is computed by a black-box simulation code. SHEBO uses a combination of local and global search strategies together with an evaluability prediction function and a dynamically adjusted evaluability threshold to iteratively select new sample points.", + "laborHours": 319.2, + "languages": [], + "name": "Surrogate Optimization of Computationally Expensive Black-Box Problems with Hidden Constraints (SHEBO) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/julianem/shebo-hidden-constraint-optimization/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Survey_Administration_Tool.json b/agency-indexes/DoE/Survey_Administration_Tool.json new file mode 100644 index 00000000..bf9b4a71 --- /dev/null +++ b/agency-indexes/DoE/Survey_Administration_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "This software allows a student/user at some point during the flow of content on a web page to input comments and rate the content with things such as: 1) True false 2) Text Comments 3) Ratings 1-5 4) etc. This information is stored anonymously in the database and can be retrieved and reported on.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + ".NET 4.5x" + ], + "name": "Survey Administration Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Sustainable_Data_Evolution_Technology_for_Power_Grid_Optimization.json b/agency-indexes/DoE/Sustainable_Data_Evolution_Technology_for_Power_Grid_Optimization.json new file mode 100644 index 00000000..95f0d56f --- /dev/null +++ b/agency-indexes/DoE/Sustainable_Data_Evolution_Technology_for_Power_Grid_Optimization.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The SDET Tool is used to create open-access power grid data sets and facilitate updates of these data sets by the community. Pacific Northwest National Laboratory (PNNL) and its power industry and software vendor partners are developing an innovative sustainable data evolution technology (SDET) to create open-access power grid datasets and facilitate updates to these datasets by the power grid community. The objective is to make this a sustained effort within and beyond the ARPA-E GRID DATA program so that the datasets can evolve over time and meet the current and future needs for power grid optimization and potentially other applications in power grid operation and planning.", + "homepageURL": "https://egriddata.org/dataset/sdet-tool", + "laborHours": 0.0, + "name": "Sustainable Data Evolution Technology for Power Grid Optimization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://egriddata.org/dataset/sdet-tool", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://egriddata.org/dataset/sdet-tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Swift.json b/agency-indexes/DoE/Swift.json new file mode 100644 index 00000000..c18bfe19 --- /dev/null +++ b/agency-indexes/DoE/Swift.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2025-01-02", + "metadataLastUpdated": "2025-01-02" + }, + "description": "Swift is a fast Fourier transform based spectral solver based on the MOOSE framework. It supports GPU accelerated semi-implicit solves of partial differential equations, such as those used for phase field mesoscale microstructure evolution.", + "laborHours": 140736.8, + "languages": [ + "C++" + ], + "name": "Swift", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/swift", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Swift_T.json b/agency-indexes/DoE/Swift_T.json new file mode 100644 index 00000000..84e0c0bd --- /dev/null +++ b/agency-indexes/DoE/Swift_T.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "woz@anl.gov" + }, + "date": { + "created": "2021-03-05", + "metadataLastUpdated": "2021-05-06" + }, + "description": "Swift/T is an MPI-oriented workflow language and runtime system that provides automatic parallelization via the dataflow paradigm. It runs on any MPI-capable system, from laptops to the largest supercomputers. Swift/T can orchestrate jobs that contain tasks written in C, C++, Fortran, Python, R, and other languages, including multi-process parallel tasks.", + "laborHours": 0.0, + "languages": [ + "C", + "Java", + "Tcl" + ], + "name": "Swift/T", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/swift-lang/swift-t.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "1.4.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Swiftbat_Python_Library.json b/agency-indexes/DoE/Swiftbat_Python_Library.json new file mode 100644 index 00000000..b0c30064 --- /dev/null +++ b/agency-indexes/DoE/Swiftbat_Python_Library.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-01-25", + "metadataLastUpdated": "2018-01-26" + }, + "description": "Swiftbat is a set of Python library routines and command-line utilities that have been developed for the purpose of retrieving, analyzing, and displaying data from NASA's Swift spacecraft, especially the data from the Swift Burst Alert Telescope (BAT).", + "laborHours": 744.8, + "name": "Swiftbat Python Library", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/swiftbat_python", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SynBio_QC-Library_QC__LibQC__v2.0.0.json b/agency-indexes/DoE/SynBio_QC-Library_QC__LibQC__v2.0.0.json new file mode 100644 index 00000000..2dcecc01 --- /dev/null +++ b/agency-indexes/DoE/SynBio_QC-Library_QC__LibQC__v2.0.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-11-06" + }, + "description": "This software is a pipeline used to identify the distribution of user-specified sequences in oligo pools that have been sequenced on the MiSeq platform for quality control purposes. The software counts instances of user-specified sequences (inserts or spacers) identified in sequencing data, returning the distribution of sequences in each pool and the length distribution of all the sequences. Among other types similar types of projects, this can be used to assess the quality of a guideRNA library once it has been inserted into the vector of choice to ensure that there is an even distribution of all the individual protospacers in the pool.\n\nThis pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up.", + "laborHours": 1960.8, + "languages": [], + "name": "SynBio QC-Library QC (LibQC) v2.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.jgi.doe.gov/jgi-synbio-public/synbioqc-libqc/-/blob/main/LICENSE?ref_type=heads", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/jgi-synbio-public/synbioqc-libqc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SynBio_QC_Dual_Barcode_QC__DBC__v1.0.json b/agency-indexes/DoE/SynBio_QC_Dual_Barcode_QC__DBC__v1.0.json new file mode 100644 index 00000000..63f294a2 --- /dev/null +++ b/agency-indexes/DoE/SynBio_QC_Dual_Barcode_QC__DBC__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-06-27", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This software was designed as a sequence validation tool for the assembly of synthetic constructs, where the constructs have a high degree of similarity and thus are barcoded prior to the sequencing library prep. It demultiplexes each FASTQ file for each barcode, then analyzes the resulting FASTQ files against a list of reference sequences for that barcode/library, combining the results from eight sequencing libraries to generate a summary, and the files needed to view the results in the Integrative Genomics Viewer (IGV) application for manual verification. This was developed for FASTQ files generated by PacBio sequencing, but could be used on any FASTQ files that do not have paired end reads. It can be used to analyze one - eight libraries at a time. Each construct is independently analyzed with only the sequences with the same barcode, in the same pooled library. Then the results are combined into a user friendly summary. This is used to identify which libraries of pooled sequences contains a perfect match, or fixable match to the reference file. This pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up, as well as the user friendly html summary that is generated.", + "laborHours": 3800.0, + "languages": [], + "name": "SynBio QC Dual Barcode QC (DBC) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/jgi-synbio-public/synbioqc-dual_barcode", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Synchrotron_Radiation_Workshop__SRW_.json b/agency-indexes/DoE/Synchrotron_Radiation_Workshop__SRW_.json new file mode 100644 index 00000000..7dd2f399 --- /dev/null +++ b/agency-indexes/DoE/Synchrotron_Radiation_Workshop__SRW_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"Synchrotron Radiation Workshop\" (SRW) is a physical optics computer code for calculation of detailed characteristics of Synchrotron Radiation (SR) generated by relativistic electrons in magnetic fields of arbitrary configuration and for simulation of the radiation wavefront propagation through optical systems of beamlines. Frequency-domain near-field methods are used for the SR calculation, and the Fourier-optics based approach is generally used for the wavefront propagation simulation. The code enables both fully- and partially-coherent radiation propagation simulations in steady-state and in frequency-/time-dependent regimes. With these features, the code has already proven its utility for a large number of applications in infrared, UV, soft and hard X-ray spectral range, in such important areas as analysis of spectral performances of new synchrotron radiation sources, optimization of user beamlines, development of new optical elements, source and beamline diagnostics, and even complete simulation of SR based experiments. Besides the SR applications, the code can be efficiently used for various simulations involving conventional lasers and other sources. SRW versions interfaced to Python and to IGOR Pro (WaveMetrics), as well as cross-platform library with C API, are available.", + "laborHours": 131008.8, + "name": "Synchrotron Radiation Workshop (SRW)", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ochubar/SRW/blob/master/COPYRIGHT.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ochubar/SRW", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Synthetic_Ancillary_Service_Generator__SynAS__v1.json b/agency-indexes/DoE/Synthetic_Ancillary_Service_Generator__SynAS__v1.json new file mode 100644 index 00000000..ce85abfb --- /dev/null +++ b/agency-indexes/DoE/Synthetic_Ancillary_Service_Generator__SynAS__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-02", + "metadataLastUpdated": "2021-03-02" + }, + "description": "The balance of demand and supply in the electric power grid is a crucial element to grid reliability. While balancing is typically provided by conventional power plants, with spinning generators, distributed energy resources (DER) and especially electric vehicles (EVs) pose a great potential to provide such service. This project conducted a field demonstration at the Los Angeles Air Force Base (LA-AFB) where a fleet of mixed-use bi-directional EVs were actively participating in the California Independent System Operator (CAISO) market for frequency regulation. While participation in regulation markets is promising, a major drawback in designing control systems and assessing potential revenue is the lack of example frequency regulation signals. This project introduces an open-source dataset for 143 days of four-second regulation data, and the SynAS Python module to synthetically generate frequency regulation signals of arbitrary length.", + "laborHours": 0.0, + "languages": [], + "name": "Synthetic Ancillary Service Generator (SynAS) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/SynAS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Synthetic_Biology_PacBio_JAWS_QC_Analysis__PBJ__v3.0.json b/agency-indexes/DoE/Synthetic_Biology_PacBio_JAWS_QC_Analysis__PBJ__v3.0.json new file mode 100644 index 00000000..f7439443 --- /dev/null +++ b/agency-indexes/DoE/Synthetic_Biology_PacBio_JAWS_QC_Analysis__PBJ__v3.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-25", + "metadataLastUpdated": "2024-06-25" + }, + "description": "This software was designed as a sequence validation tool for the assembly of synthetic constructs. It analyzes FASTQ files against a list of reference sequences, combining the results from eight sequencing libraries to generate a summary, and the files needed to view the results in the Integrative Genomics Viewer (IGV) application for manual verification. This was developed for FASTQ files generated by PacBio sequencing, but could be used on any FASTQ files that do not have paired end reads. It can be used to analyze one - eight libraries at a time, and assumes that each construct sequence in the reference will be in each pool, however, this is not a requirement. This is used to identify which libraries of pooled sequences contains a perfect match, or fixable match to the reference file.\n\nThis pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up, as well as the user friendly html summary that is generated.", + "laborHours": 9363.2, + "languages": [], + "name": "Synthetic Biology PacBio/JAWS QC Analysis (PBJ) v3.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.jgi.doe.gov/jgi-synbio-public/synbioqc-pbj", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Synthetic_Proxy_Infrastructure_for_Task_Evaluation.json b/agency-indexes/DoE/Synthetic_Proxy_Infrastructure_for_Task_Evaluation.json new file mode 100644 index 00000000..802c196a --- /dev/null +++ b/agency-indexes/DoE/Synthetic_Proxy_Infrastructure_for_Task_Evaluation.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Synthetic Proxy Infrastructure for Task Evaluation is a proxy application designed to support application developers in gauging the performance of various task granularities when determining how best to utilize task based programming models.The infrastructure is designed to provide examples of common communication patterns with a synthetic workload intended to provide performance data to evaluate programming model and platform overheads for the purpose of determining task granularity for task decomposition purposes. This is presented as a reference implementation of a proxy application with run-time configurable input and output task dependencies ranging from an embarrassingly parallel scenario to patterns with stencil-like dependencies upon their nearest neighbors. Once all, if any, inputs are satisfied each task will execute a synthetic workload (a simple DGEMM of in this case) of varying size and output all, if any, outputs to the next tasks.The intent is for this reference implementation to be implemented as a proxy app in different programming models so as to provide the same infrastructure and to allow for application developers to simulate their own communication needs to assist in task decomposition under various models on a given platform.", + "laborHours": 106.4, + "name": "Synthetic Proxy Infrastructure for Task Evaluation", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/spite/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/spite", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Synthetic_Transaction_Test_Generator_for_Websites.json b/agency-indexes/DoE/Synthetic_Transaction_Test_Generator_for_Websites.json new file mode 100644 index 00000000..ad176e09 --- /dev/null +++ b/agency-indexes/DoE/Synthetic_Transaction_Test_Generator_for_Websites.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "Python script for querying a list of web sites and their details from Splunk and dynamically creating tests for monitoring uptime. The data generated from this script is then sent back to Splunk for creating reports and alerts.", + "laborHours": 212.8, + "name": "Synthetic Transaction Test Generator for Websites", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/justinatpnnl/splunk_web_transactions_generator", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/justinatpnnl/splunk_web_transactions_generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SysCaps__Language_Interfaces_for_Simulation_Surrogates_of_Complex_Systems__[SWR-24-97].json b/agency-indexes/DoE/SysCaps__Language_Interfaces_for_Simulation_Surrogates_of_Complex_Systems__[SWR-24-97].json new file mode 100644 index 00000000..3703a23e --- /dev/null +++ b/agency-indexes/DoE/SysCaps__Language_Interfaces_for_Simulation_Surrogates_of_Complex_Systems__[SWR-24-97].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-18", + "metadataLastUpdated": "2024-11-18" + }, + "description": "You've found the official code repository for the paper \"SysCaps: Language Interfaces for Simulation Surrogates of Complex Systems,\" presented at the Foundation Models for Science: Progress, Opportunities, and Challenges workshop at NeurIPS 2024. Our paper conjectures that interfaces (both text templates as well as conversational) makes interacting with simulation surrogate models for complex systems more intuitive and accessible for both non-experts and experts. \"System captions\", or SysCaps, are text-based descriptions of systems based on information contained in simulation metadata. Our paper's goal is to train multimodal regression models that take text inputs (SysCaps) and timeseries inputs (exogenous system conditions such as hourly weather) and regress timeseries simulation outputs (e.g. hourly building energy consumption). The experiments in our paper with building and wind farm simulators, which can be reproduced using this codebase, aim to help us understand whether a) accurate regression in this setting is possible and b) if so, how well can we do it.\n\nPaper: https://arxiv.org/abs/2405.19653", + "laborHours": 4651.2, + "languages": [ + "Python", + "Jupyter Notebook", + "Shell" + ], + "name": "SysCaps (Language Interfaces for Simulation Surrogates of Complex Systems) [SWR-24-97]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/SysCaps", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SystemBurn.json b/agency-indexes/DoE/SystemBurn.json new file mode 100644 index 00000000..71c1a911 --- /dev/null +++ b/agency-indexes/DoE/SystemBurn.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "SystemBurn is a software package designed to allow users to methodically create maximal loads on systems ranging from desktops to supercomputers.\n", + "laborHours": 17510.4, + "name": "Systemburn", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/systemburn", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/SystemConfidence.json b/agency-indexes/DoE/SystemConfidence.json new file mode 100644 index 00000000..ca28532f --- /dev/null +++ b/agency-indexes/DoE/SystemConfidence.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "SystemConfidence is a benchmark developed at ORNL which can measure statistical variation in which the user can plot. The portions of the code which manage the collection of the histograms and computing statistics on the histograms were designed with the intent that we could use these functions in other codes.", + "laborHours": 1216.0, + "name": "SystemConfidence", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jlothian/sysconfidence", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/System_Administration_Tools.json b/agency-indexes/DoE/System_Administration_Tools.json new file mode 100644 index 00000000..17e24840 --- /dev/null +++ b/agency-indexes/DoE/System_Administration_Tools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-08-27", + "metadataLastUpdated": "2018-08-28" + }, + "description": "High Performance Computing clusters and supercomputers are expensive and complex systems to manage. The software tools to manage these systems are also aging to the point where they are no longer actively developed and their methodology is antiquated. There has been a surge of new methodologies and software tools developed by the cloud providers to maximize availability of services and scalability of server deployment. The authors would like to utilize these new software tools to distribute our proof of concept, named Kraken, that will be responsible for booting and managing LANL's HPC systems in the future", + "laborHours": 91.2, + "languages": [], + "name": "System Administration Tools", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/fast-image-creation", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/System_Architecture_for_Real-time_HVAC_optimization.json b/agency-indexes/DoE/System_Architecture_for_Real-time_HVAC_optimization.json new file mode 100644 index 00000000..e16764d3 --- /dev/null +++ b/agency-indexes/DoE/System_Architecture_for_Real-time_HVAC_optimization.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Optimization of HVAC systems in multi-family housing market.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "System Architecture for Real-time HVAC optimization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/System_Validation_Platform_Working_Directories.json b/agency-indexes/DoE/System_Validation_Platform_Working_Directories.json new file mode 100644 index 00000000..6ad8e403 --- /dev/null +++ b/agency-indexes/DoE/System_Validation_Platform_Working_Directories.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-12", + "metadataLastUpdated": "2024-08-07" + }, + "description": "A suite of software tools used to interface with power electronic equipment for laboratory testing and device certification. They are typically used as equipment drivers with using the System Validation Platform (SVP) graphical user interface (GUI). Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1185 O", + "laborHours": 18665.6, + "languages": [ + "Python 2.7", + "Scilab" + ], + "name": "System Validation Platform Working Directories", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/svp_energy_lab", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/System_for_Information_Discovery.json b/agency-indexes/DoE/System_for_Information_Discovery.json new file mode 100644 index 00000000..99c1639e --- /dev/null +++ b/agency-indexes/DoE/System_for_Information_Discovery.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "SID characterizes natural language based documents so that they may be related and retrieved based on content similarity. This technology processes textual documents, autonomously identifies the major topics of the document set, and constructs an interpretable, high dimensional representation of each document. SID also provides the ability to interactively re-weight representations based on user needs, so that users may analyze the data set from multiple points of view. The particular advantages SID offers are speed, data compression, flexibility in representation, and incremental processing.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "System for Information Discovery", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/System_for_Information_Discovery_-_SPIRE.json b/agency-indexes/DoE/System_for_Information_Discovery_-_SPIRE.json new file mode 100644 index 00000000..f789a51b --- /dev/null +++ b/agency-indexes/DoE/System_for_Information_Discovery_-_SPIRE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "SID characterizes natural language based documents so that they may be related and retrieved based on content similarity. This technology processes textual documents, autonomously identifies the major topics of the document set, and constructs an interpretable, high dimensional representation of each document. SID also provides the ability to interactively reweight representations based on user need, so users may analyze the dataset from multiple points of view. The particular advantages SID offers are speed, data compression, flexibility in representation, and incremental processing. SPIRE consists of software for visual analysis of text-based information sources. This technology enables users to make discoveries about the content of very large sets of textual documents without requiring the user to read or presort the documents. It employs algorithms for text and word proximity analysis to identify the key themes within the documents. The results of this analysis are projected onto a visual spatial proximity display (Galaxies or Themescape) where document proximity represents the degree of relatedness of theme.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "System for Information Discovery - SPIRE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/System_for_NIS_Forecasting_Based_on_Ensembles_Analysis.json b/agency-indexes/DoE/System_for_NIS_Forecasting_Based_on_Ensembles_Analysis.json new file mode 100644 index 00000000..862ca0d3 --- /dev/null +++ b/agency-indexes/DoE/System_for_NIS_Forecasting_Based_on_Ensembles_Analysis.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "BMA-NIS is a package/library designed to be called by a script (e.g. Perl or Python). The software itself is written in the language of R. The software assists electric power delivery systems in planning resource availability and demand, based on historical data and current data variables. Net Interchange Schedule (NIS) is the algebraic sum of all energy scheduled to flow into or out of a balancing area during any interval. Accurate forecasts for NIS are important so that the Area Control Error (ACE) stays within an acceptable limit. To date, there are many approaches for forecasting NIS but all none of these are based on single models that can be sensitive to time of day and day of week effects.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "R" + ], + "name": "System for NIS Forecasting Based on Ensembles Analysis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Systemd_Snapshot.json b/agency-indexes/DoE/Systemd_Snapshot.json new file mode 100644 index 00000000..22ff6c66 --- /dev/null +++ b/agency-indexes/DoE/Systemd_Snapshot.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "huettelmr@ornl.gov" + }, + "date": { + "created": "2024-04-26", + "metadataLastUpdated": "2024-04-26" + }, + "description": "Systemd Snapshot is a static analysis tool for Linux systems that use systemd. It aims to enumerate, aggregate, and investigate systemd services without requiring an operational system. The tool produces a set of JSON files that consolidates not only systemd information, but additional forensic information associated with systemd artifacts. A graph is also produced based on the relationships and ordering defined in systemd unit files and the binaries they specify.", + "laborHours": 0.0, + "languages": [], + "name": "Systemd Snapshot", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/Systemd_Snapshot", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Systems_Approach_to_Blur_Estimation_and_Removal.json b/agency-indexes/DoE/Systems_Approach_to_Blur_Estimation_and_Removal.json new file mode 100644 index 00000000..431f723c --- /dev/null +++ b/agency-indexes/DoE/Systems_Approach_to_Blur_Estimation_and_Removal.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-12-02", + "metadataLastUpdated": "2019-12-02" + }, + "description": "Python package for a systems approach to blur estimation and reduction", + "laborHours": 440.8, + "languages": [], + "name": "Systems Approach to Blur Estimation and Removal", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sabersw/pysaber", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/T.Rex.json b/agency-indexes/DoE/T.Rex.json new file mode 100644 index 00000000..2be73a14 --- /dev/null +++ b/agency-indexes/DoE/T.Rex.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "T.Rex is used to explore tabular data sets containing up to ten million records to help rapidly understand a previously unknown data set. Analysis can quickly identify patterns of interest and the records and fields that capture those patterns. T.Rex contains a growing set of deep analytical tools and supports robust export capabilities that selected data can be incorporated into to other specialized tools for further analysis. T.Rex is flexible in ingesting different types and formats of data, allowing the user to interactively experiment and perform trial and error guesses on the structure of the data; and also has a variety of linked visual analytic tools that enable exploration of the data to find relevant content, relationships among content, trends within the content, and capture knowledge about the content. Finally, T.Rex has a rich export capability, to extract relevant subsets of a larger data source, to further analyze their data in other analytic tools.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "T.Rex", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/T2DM_v1.0.json b/agency-indexes/DoE/T2DM_v1.0.json new file mode 100644 index 00000000..1846158b --- /dev/null +++ b/agency-indexes/DoE/T2DM_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-29", + "metadataLastUpdated": "2024-08-30" + }, + "description": "T2DM adds two-dimensional hydrodynamic dispersion to TOUGH2/EOS7C. T2DM can be used when modeling flow and transport of brine in porous media to account for hydrodynamic dispersion.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 775.2, + "languages": [], + "name": "T2DM v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/T2Well_ECO2N_Version_1.0:_Multiphase_and_Non-Isothermal_Model_for_Coupled_Wellbore-Reservoir_Flow_of_Carbon_Dioxide_and_Variable_Salinity_Water.json b/agency-indexes/DoE/T2Well_ECO2N_Version_1.0:_Multiphase_and_Non-Isothermal_Model_for_Coupled_Wellbore-Reservoir_Flow_of_Carbon_Dioxide_and_Variable_Salinity_Water.json new file mode 100644 index 00000000..07514f13 --- /dev/null +++ b/agency-indexes/DoE/T2Well_ECO2N_Version_1.0:_Multiphase_and_Non-Isothermal_Model_for_Coupled_Wellbore-Reservoir_Flow_of_Carbon_Dioxide_and_Variable_Salinity_Water.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-19", + "metadataLastUpdated": "2018-09-20" + }, + "description": "T2Well/ECO2N is a coupled wellbore and reservoir model for simulating the dynamics of CO2 injection and leakage through wellbores. It can be seen as an extension to standard TOUGH/ECO2N V2.0, and can be applied to situations relevant to geologic CO2 storage involving upward flow (e.g., leakage) and downward flow (injection). The new simulator integrates a wellbore-reservoir system by assigning the wellbore and reservoir to two different sub-domains in which flow is controlled by appropriate physical laws. In the reservoir, we model flow using a standard multiphase Darcy flow approach. In the wellbores, we use the Drift-Flux Model and related conservation equations for describing transient two-phase non-isothermal wellbore flow of CO2-water mixtures. The mass and thermal energy balance equations are solved numerically by a finite difference scheme with wellbore heat transmission to the surrounding rock handled either semi-analytically or numerically. The momentum balance equation for the flow in the wellbore is solved numerically with a semi-explicit scheme.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 7904.0, + "languages": [], + "name": "T2Well/ECO2N Version 1.0: Multiphase and Non-Isothermal Model for Coupled Wellbore-Reservoir Flow of Carbon Dioxide and Variable Salinity Water", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/T3CO-Go:_A_web-based_dashboard_for_the_Transportation_Technology_Total_Cost_of_Ownership_tool_[SWR-25-38].json b/agency-indexes/DoE/T3CO-Go:_A_web-based_dashboard_for_the_Transportation_Technology_Total_Cost_of_Ownership_tool_[SWR-25-38].json new file mode 100644 index 00000000..63372d15 --- /dev/null +++ b/agency-indexes/DoE/T3CO-Go:_A_web-based_dashboard_for_the_Transportation_Technology_Total_Cost_of_Ownership_tool_[SWR-25-38].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-04-22", + "metadataLastUpdated": "2025-04-22" + }, + "description": "T3CO-Go is a web-based dashboard with a user interface to modify input assumptions, run the T3CO tool, and visualize results. The dashboard, built using Python, can be run on a local server when installed from PyPI or hosted on the cloud and embedded in a webpage. T3CO-Go allows even non-Python-proficient users to customize their T3CO experience and gain insights from results customized for their analysis purpose.\n\nSee also, PyPI Package: https://pypi.org/project/t3co-go/", + "laborHours": 410.4, + "languages": [ + "Python" + ], + "name": "T3CO-Go: A web-based dashboard for the Transportation Technology Total Cost of Ownership tool [SWR-25-38]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/t3co_go", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/T3CO__Transportation_Technology_Total_Cost_of_Ownership__Open_Source_[SWR-21-54].json b/agency-indexes/DoE/T3CO__Transportation_Technology_Total_Cost_of_Ownership__Open_Source_[SWR-21-54].json new file mode 100644 index 00000000..43c6c303 --- /dev/null +++ b/agency-indexes/DoE/T3CO__Transportation_Technology_Total_Cost_of_Ownership__Open_Source_[SWR-21-54].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-03-07", + "metadataLastUpdated": "2024-10-28" + }, + "description": "T3CO (Transportation Technology Total Cost of Ownership), is open source software for modeling total cost of ownership for commercial vehicles with advanced powertrains.\n\nT3CO is a modeling framework for determining geospatially and temporally optimized total cost of ownership (TCO) for vehicle powertrain technologies. T3CO runs NREL's FASTSim\u2122 software for a representative set of operating conditions to minimize TCO based on vehicle parameters that affect purchase and operating costs (e.g., fuel/electricity consumption, asset depreciation, opportunity costs associated with charging time) while simultaneously ensuring that firm performance constraints (e.g. zero-to-sixty time, gradeability) are satisfied. T3CO will enable the user to control which powertrain parameters are used in optimizing TCO, and these parameters will be modified by a multi-objective optimization (MOO) algorithm to identify a Pareto-optimal solution set. The optimization algorithm will be modular so that users can choose from many different MOO options or insert their own user-defined optimization tool.\n\nNREL T3CO Homepage: https://www.nrel.gov/transportation/t3co.html\nPyPI package: https://pypi.org/project/t3co/", + "laborHours": 5289.6, + "languages": [ + "Python" + ], + "name": "T3CO (Transportation Technology Total Cost of Ownership) Open Source [SWR-21-54]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/T3CO", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TACPLUS-DO-AUTH.json b/agency-indexes/DoE/TACPLUS-DO-AUTH.json new file mode 100644 index 00000000..9b44b74d --- /dev/null +++ b/agency-indexes/DoE/TACPLUS-DO-AUTH.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-21", + "metadataLastUpdated": "2023-08-21" + }, + "description": "SF-23-084\nThis software provides enhanced authorization and access control support to be used in tandem with the open source\nTerminal Access Controller Access Control System (TACACS+) software tac_plus; providing Authentication,\nAuthorization and Auditing (AAA) capabilities for networking devices.\n", + "laborHours": 0.0, + "languages": [], + "name": "TACPLUS-DO-AUTH", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/argonne-lcf/tacplus-do-auth", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TAP_-_Tools_for_Adaptive_Partitioning_v._0.99_Beta.json b/agency-indexes/DoE/TAP_-_Tools_for_Adaptive_Partitioning_v._0.99_Beta.json new file mode 100644 index 00000000..c23c3d92 --- /dev/null +++ b/agency-indexes/DoE/TAP_-_Tools_for_Adaptive_Partitioning_v._0.99_Beta.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "TAP is a set of tools which are essential for conducting research on adaptive partitioners. The basic premise is that a single partitioner may not be a good choice for adaptive mesh simulations; rather one must match a partitioner (obtained from a partitioning package like Zoltan, ParMetis etc) with the mesh being partitioned. TAP provides the tools that can judge the suitability of a partitioning algorithm to a given mesh.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "TAP - Tools for Adaptive Partitioning v. 0.99 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TASQC_Quantum_Key_Transfer_Program.json b/agency-indexes/DoE/TASQC_Quantum_Key_Transfer_Program.json new file mode 100644 index 00000000..9b2e30d4 --- /dev/null +++ b/agency-indexes/DoE/TASQC_Quantum_Key_Transfer_Program.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Securely transferring timing information in the electrical grid is a critical component of securing the nation's infrastructure from cyber attacks. One solution to this problem is to use quantum information to securely transfer the timing information across sites. This software provides such an infrastructure using a standard Java webserver that pulls the quantum information from associated hardware.", + "laborHours": 699.2, + "name": "TASQC Quantum Key Transfer Program", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/TASQC/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/TASQC", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TA_solver_--_Traffic_Assignment_solver_package.json b/agency-indexes/DoE/TA_solver_--_Traffic_Assignment_solver_package.json new file mode 100644 index 00000000..467c17cb --- /dev/null +++ b/agency-indexes/DoE/TA_solver_--_Traffic_Assignment_solver_package.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-30", + "metadataLastUpdated": "2019-09-23" + }, + "description": "TA_solver is a modular software framework for solving user equilibrium traffic assignment problems, both static and dynamic, utilizing the OTM (Open Traffic Models) API to encode traffic scenarios. The design is based on the formulation of the problem as a variational inequality. Unlike most existing traffic assignment software which focus on specific traffic models, TA_solver accommodates various traffic models, but also enables using parallel computation in high performance computing environments to speed up large-scale equilibrium calculations.", + "laborHours": 39033.6, + "languages": [], + "name": "TA_solver -- Traffic Assignment solver package", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ugirumurera/TA_solver", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TCE_Spack_Stacks.json b/agency-indexes/DoE/TCE_Spack_Stacks.json new file mode 100644 index 00000000..d2870170 --- /dev/null +++ b/agency-indexes/DoE/TCE_Spack_Stacks.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-02-11", + "metadataLastUpdated": "2022-02-14" + }, + "description": "The TCE spack stacks project aims to produce a replicable, standard software compilation environment for super computers on Trilab (Los Alamos, Livermore, and Sandia) supercomputers. This process is based on Spack, an open source package manager for supercomputers created by LLNL. The software to be released consists of a series of scripts and configurations for creating the described software environments using Spack.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "TCE Spack Stacks", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TCP-monitor.json b/agency-indexes/DoE/TCP-monitor.json new file mode 100644 index 00000000..dac54f67 --- /dev/null +++ b/agency-indexes/DoE/TCP-monitor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "Simple Python Program to monitor TCP sockets.", + "laborHours": 228.0, + "languages": [], + "name": "TCP-monitor", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/TCP-monitor", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TChem-atm_v1.0.json b/agency-indexes/DoE/TChem-atm_v1.0.json new file mode 100644 index 00000000..29aaee57 --- /dev/null +++ b/agency-indexes/DoE/TChem-atm_v1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-25", + "metadataLastUpdated": "2024-09-25" + }, + "description": "SAND2024-11300O\nTChem-atm is a software library that was developed to solve complex kinetic models for atmospheric chemistry applications. TChem-atm interface employs a hierarchical parallelism design to exploit the massive parallelism available from modern computing platforms. It also supports gas atmospheric chemistry applications, e.g., the energy exascale earth system model. TChem can be used as a box model or coupled with a climate model to compute the time evolution of gas tracer species. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 34519.2, + "languages": [ + "C++" + ], + "name": "TChem-atm v1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TChem-atm", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TChem.json b/agency-indexes/DoE/TChem.json new file mode 100644 index 00000000..158d7977 --- /dev/null +++ b/agency-indexes/DoE/TChem.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The TChem toolkit is a software library that enables numerical simulations using complex chemistry and facilitates the analysis of detailed kinetic models. The toolkit provide capabilities for thermodynamic properties based on NASA polynomials and species production and consumption rates. It incorporates methods that can selectively modify reaction parameters for sensitivity analysis and uncertainty quantification. The library also contains several functions that provide analytically computed Jacobian matrices necessary for the efficient time advancement and analysis of detailed kinetic models.", + "homepageURL": "http://www.sandia.gov/tchem", + "laborHours": 0.0, + "name": "TChem", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.sandia.gov/tchem", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TChem_2.0.json b/agency-indexes/DoE/TChem_2.0.json new file mode 100644 index 00000000..ffc62beb --- /dev/null +++ b/agency-indexes/DoE/TChem_2.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-09-30", + "metadataLastUpdated": "2021-09-30" + }, + "description": "The TChem toolkit is an object-oriented C++ software library that enables numerical simulations using complex chemistry and facilitates the analysis of detailed kinetic models. The toolkit provides capabilities for thermodynamic properties and gas-phase and surface chemistry. The computations rely on the Kokkos framework for parallel execution on many-core and GPU-based platforms. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2021-2752 O", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "TChem 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TChem", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TDcosim_-_Transmission_and_Distribution_System_Co-simulation_Tool.json b/agency-indexes/DoE/TDcosim_-_Transmission_and_Distribution_System_Co-simulation_Tool.json new file mode 100644 index 00000000..0802a81d --- /dev/null +++ b/agency-indexes/DoE/TDcosim_-_Transmission_and_Distribution_System_Co-simulation_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-08-01", + "metadataLastUpdated": "2019-08-01" + }, + "description": "This software couples commercial and existing transmission system simulation software PSSE and distribution system simulation software OpenDSS to enable transmission and distribution (T&D) co-simulation. This tool is capable of both steady-state and dynamic T&D co-simulation. It is written in Python. It also integrates dynamic distributed energy resource (DER) models (Python-based standalone models developed under an EERE project) into OpenDSS to involve dynamics of DER. This tool allows transmission system entities to understand the full spectrum impact of DER on the bulk electric system (BES) and assists in ensuring secure and reliable grid planning and operations. ", + "laborHours": 4848.8, + "languages": [], + "name": "TDcosim - Transmission and Distribution System Co-simulation Tool", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tdcosim/TDcoSim", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TDycores-Project_TDycore.json b/agency-indexes/DoE/TDycores-Project_TDycore.json new file mode 100644 index 00000000..cd675075 --- /dev/null +++ b/agency-indexes/DoE/TDycores-Project_TDycore.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The terrestrial dycores will solve tightly coupled conservation of water and energy equations. While the land dycore will simulate processes for a three-dimensional subsurface coupled to a one-dimensional plant\u2019s vascular system, the river dycore will simulate two-dimensional processes in the river.", + "laborHours": 0.0, + "languages": [], + "name": "TDycores-Project/TDycore", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/TDycores-Project/Tdycore", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TEAL.json b/agency-indexes/DoE/TEAL.json new file mode 100644 index 00000000..b4d20169 --- /dev/null +++ b/agency-indexes/DoE/TEAL.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-13" + }, + "description": "TEAL is a financial performance calculator plugin for the RAVEN code, framework, resolving around the computation of Net Present Value and associated financial metrics. TEAL can make use of inflation rates, taxation, escalation factors, capital expenditure economy of scale scaling factors. The unique feature of TEAL is the capability to be linked with RAVEN external models and build corresponding cash flows using the variables computed by those external models. In addition to be able to use the capability to generate cash flows derived from complex physical models generated by RAVEN, another distinctive feature of TEAL is the capability to provide financial risk/probabilistic metrics that can empower RAVEN to perform optimization/analysis driven by financial risk augmentations. Optimization, robust optimization, parametric studies, large parallel simulations, sensitivity analysis, data mining, etc. are just some of the capabilities that can be leveraged.", + "laborHours": 4788.0, + "languages": [ + "Python" + ], + "name": "TEAL", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/TEAL", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TEAM-TDM:_A_Tool_for_Evaluating_an_Array_of_Machine_Learning_Travel_Demand_Models_[SWR-18-64].json b/agency-indexes/DoE/TEAM-TDM:_A_Tool_for_Evaluating_an_Array_of_Machine_Learning_Travel_Demand_Models_[SWR-18-64].json new file mode 100644 index 00000000..f3ae30d1 --- /dev/null +++ b/agency-indexes/DoE/TEAM-TDM:_A_Tool_for_Evaluating_an_Array_of_Machine_Learning_Travel_Demand_Models_[SWR-18-64].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2023-05-08" + }, + "description": "This is a package for easy application of multiple machine learning models to a single problem, and comparison via various metrics. For a pretty detailed description of the models that are available in the tool, and a quite detailed description of the metrics that it pumps out, see the paper, \"A Machine Learning Decision Support Tool for Travel Demand Modeling\". Accessible at: https://github.com/NREL/TEAM-TDM/blob/master/paper/team_tdm.pdf\n", + "laborHours": 4119.2, + "languages": [ + "Perl", + "Jupyter Notebook", + "Tex", + "Python" + ], + "name": "TEAM-TDM: A Tool for Evaluating an Array of Machine Learning Travel Demand Models [SWR-18-64]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/TEAM-TDM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TEE-ACM2.json b/agency-indexes/DoE/TEE-ACM2.json new file mode 100644 index 00000000..0eb64081 --- /dev/null +++ b/agency-indexes/DoE/TEE-ACM2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-10-27", + "metadataLastUpdated": "2022-10-27" + }, + "description": "TEE-ACM2 is a library that computes matrix chain multiplication efficiently on GPUs, using a blocking strategy to load data. The library will provide an energy efficient algorithm for chain Matrix Multiplication, by minimizing both computations and off chip data transfers on the GPUs.", + "laborHours": 0.0, + "languages": [], + "name": "TEE-ACM2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/TEE-ACM2", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TEMWizard_pyCHIP.gui.json b/agency-indexes/DoE/TEMWizard_pyCHIP.gui.json new file mode 100644 index 00000000..789b1ee8 --- /dev/null +++ b/agency-indexes/DoE/TEMWizard_pyCHIP.gui.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "TEMWizard pyCHIP.gui is used to visualize intermediate and final results from Atomap, an open-source software tool for determining the position and other features of atomic columns in transmission electron microscopy images. Also known as pyCHIP.gui.", + "laborHours": 0.0, + "languages": [], + "name": "TEMWizard pyCHIP.gui", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/temwizard", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TEM_Instruction.json b/agency-indexes/DoE/TEM_Instruction.json new file mode 100644 index 00000000..1a7611ed --- /dev/null +++ b/agency-indexes/DoE/TEM_Instruction.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Prototype software for virtual reality based instruction manual for transmission electron microscopy (TEM).", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "TEM Instruction", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TESS.json b/agency-indexes/DoE/TESS.json new file mode 100644 index 00000000..50ffc5b9 --- /dev/null +++ b/agency-indexes/DoE/TESS.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Computing a Voronoi or Delaunay tessellation from a set of points is a core part of the analysis of many simulated and measured datasets. As the scale of simulations and observations surpasses billions of particles, a distributed-memory scalable parallel algorithm is the only feasible approach. The primary contribution of this software is a distributed-memory parallel Delaunay and Voronoi tessellation algorithm based on existing serial computational geometry libraries that automatically determines which neighbor points need to be exchanged among the subdomains of a spatial decomposition. Other contributions include the addition of periodic and wall boundary conditions.", + "laborHours": 5502.4, + "name": "TESS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/diatomic/tess2", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TEVA-SPOT_Toolkit_1.2.json b/agency-indexes/DoE/TEVA-SPOT_Toolkit_1.2.json new file mode 100644 index 00000000..9ae4c79f --- /dev/null +++ b/agency-indexes/DoE/TEVA-SPOT_Toolkit_1.2.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The TEVA-SPOT Toolkit (SPOT) supports the design of contaminant warning systems (CWSs) that use real-time sensors to detect contaminants in municipal water distribution networks. Specifically, SPOT provides the capability to select the locations for installing sensors in order to maximize the utility and effectiveness of the CWS. SPOT models the sensor placement process as an optimization problem, and the user can specify a wide range of performance objectives for contaminant warning system design, including population health effects, time to detection, extent of contamination, volume consumed and number of failed detections. For example, a SPOT user can integrate expert knowledge during the design process by specigying required sensor placements or designating network locations as forbidden. Further, cost considerations can be integrated by limiting the design with user-specified installation costs at each location.", + "laborHours": 30.4, + "languages": [ + "C++", + "C", + "Python" + ], + "name": "TEVA-SPOT Toolkit 1.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TEVA-SPOT-Toolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TF-MoE.json b/agency-indexes/DoE/TF-MoE.json new file mode 100644 index 00000000..d893773a --- /dev/null +++ b/agency-indexes/DoE/TF-MoE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-05-27", + "metadataLastUpdated": "2021-07-07" + }, + "description": "TF-MoE is a software that employs a mixture of experts (MoE) approach to bifurcate high-dimensional tabulated flamelet (TF) data into simpler manifolds. It employs a divide-and-conquer competitive approach, where different zones in the manifold are assigned to various neural networks for inference. It consists of two classes of neural networks, namely, a gating network which is a neural network classifier, and a number of experts which are neural network regressors. The software bifurcates the manifold by having different neural networks compete for each input signal. The gating network rewards the best predictors with stronger signals during subsequent training episodes and feeds poor-performing networks with weaker signals. The gating network and experts are trained using a standard backpropagation approach. The TF-MoE software enhances predictive modeling via machine learning by improves accuracy within lower inference time.", + "laborHours": 45.6, + "languages": [], + "name": "TF-MoE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/owoyeleope/TFM-MoE", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TFDA__Transient_Fault_Detection_Algorithm__[SWR-24-23].json b/agency-indexes/DoE/TFDA__Transient_Fault_Detection_Algorithm__[SWR-24-23].json new file mode 100644 index 00000000..653c1a27 --- /dev/null +++ b/agency-indexes/DoE/TFDA__Transient_Fault_Detection_Algorithm__[SWR-24-23].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-05-23", + "metadataLastUpdated": "2024-09-25" + }, + "description": "The Transient Fault Detection Algorithm (TFDA) is an algorithm to detect the non-fault and transient fault conditions, and classify the fault types. This is part of OEDI-SI project (https://data.openei.org/search?q=oedi%20si).", + "laborHours": 45.6, + "languages": [ + "Python" + ], + "name": "TFDA (Transient Fault Detection Algorithm) [SWR-24-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Transient-Fault-Detection", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/THYME:_Toolkit_for_Hybrid_Modeling_of_Electric_Power_Systems.json b/agency-indexes/DoE/THYME:_Toolkit_for_Hybrid_Modeling_of_Electric_Power_Systems.json new file mode 100644 index 00000000..0a803b6a --- /dev/null +++ b/agency-indexes/DoE/THYME:_Toolkit_for_Hybrid_Modeling_of_Electric_Power_Systems.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "THYME is an object oriented library for building models of wide area control and communications in electric power systems. This software is designed as a module to be used with existing open source simulators for discrete event systems in general and communication systems in particular. THYME consists of a typical model for simulating electro-mechanical transients (e.g., as are used in dynamic stability studies), data handling objects to work with CDF and PTI formatted power flow data, and sample models of discrete sensors and controllers.", + "homepageURL": "http://www.ornl.gov/~1qn/thyme/docs", + "laborHours": 0.0, + "name": "THYME: Toolkit for Hybrid Modeling of Electric Power Systems", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://web.ornl.gov/~nutarojj/thyme/docs/license.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.ornl.gov/~1qn/thyme/docs", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TICC_Clustering_Library_v.1.0.json b/agency-indexes/DoE/TICC_Clustering_Library_v.1.0.json new file mode 100644 index 00000000..434da373 --- /dev/null +++ b/agency-indexes/DoE/TICC_Clustering_Library_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-03-20" + }, + "description": "SAND2024-01234O\nTICC is a clustering algorithm that labels a sequence of data points according to numerical properties. This library is a Python implementation of the algorithm described in \"Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data\" (Hallac et al. 2017). It includes documentation, performance improvements, examples, and test coverage. \n\nThis library allows users to automatically segment a series of multivariate data points according to their covariance\u2014that is, the way the values at each data point are changing in relation to one another. This is useful for identifying periods in which a system is behaving. For example, if a sensor is measuring a car's velocity, steering wheel angle, braking and acceleration, TICC can determine when the car was stopped, beginning/exiting a turn, slowing or accelerating at an intersection, or driving on straight or curved roads. TICC can be applied to measure multiple quantities at known times.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "TICC Clustering Library v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fast_ticc", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TIFF_Image_Writer_patch_for_OpenSceneGraph.json b/agency-indexes/DoE/TIFF_Image_Writer_patch_for_OpenSceneGraph.json new file mode 100644 index 00000000..ea5b0219 --- /dev/null +++ b/agency-indexes/DoE/TIFF_Image_Writer_patch_for_OpenSceneGraph.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "This software consists of code modifications to the open-source OpenSceneGraph software package to enable the creation of TlFF images containing 16 bit unsigned data. They also allow the user to disable compression and set the DPI tags in the resulting TIFF Images. Some image analysis programs require uncompressed, 16 bit unsigned input data. These code modifications allow programs based on OpenSceneGraph to write out such images, improving connectivity between applications.", + "laborHours": 367292.8, + "languages": [ + "Objective-C", + "C++", + "HTML", + "C", + "CMake", + "Objective-C++" + ], + "name": "TIFF Image Writer patch for OpenSceneGraph", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/OpenSceneGraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TINES_-_Time_Integration,_Newton_and_Eigen_Solver_v._1.0.json b/agency-indexes/DoE/TINES_-_Time_Integration,_Newton_and_Eigen_Solver_v._1.0.json new file mode 100644 index 00000000..cf466661 --- /dev/null +++ b/agency-indexes/DoE/TINES_-_Time_Integration,_Newton_and_Eigen_Solver_v._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2021-02-17" + }, + "description": "SAND2021-1505 O. TINES is an open source software providing math infrastructure for solving many stiff time ordinary differential equations (ODEs) and/or differential algebraic equations (DAEs) using a batch hierarchical parallelism. The code is written using a parallel programming model (i.e., Kokkos) to future-proof the next generation parallel computing platforms such as GPU accelerators. This code is developed to support Exascale Catalytic Chemistry (ECC) Project. The code provides fundamental math helpers that can aid other research projects. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "TINES - Time Integration, Newton and Eigen Solver v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Tines", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TMAP8.json b/agency-indexes/DoE/TMAP8.json new file mode 100644 index 00000000..0e5e7ed9 --- /dev/null +++ b/agency-indexes/DoE/TMAP8.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-02-05", + "metadataLastUpdated": "2023-03-13" + }, + "description": "TMAP8 is a MOOSE application for solving 0-1D scalar diffusion-reactive transport. It contains unique custom syntax for 0D or 1D geometric/algebraic entities that make it more usable for 0-1D transport than standard MOOSE syntax.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "TMAP8", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/TMAP8", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOBA.json b/agency-indexes/DoE/TOBA.json new file mode 100644 index 00000000..daf052fa --- /dev/null +++ b/agency-indexes/DoE/TOBA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Toba is an extensible personal information retrieval system. It supports various plugins which the user uses to create and store bits of information. It comes configured to store meeting notes, task items, issue, and business development opportunities. Plugins could be written to support almost any kind of digital information. So with the right plugins, Toba could become a full fledged contact manager, project management application, programmer's toolkit, or almost any other type of data storage/search/retrieval application imaginable. Toba comes with a built in command line interface and via a plugin it has a fully scripting language (jython). The information stored can be searched by keyword or through SQL queries.", + "laborHours": 0.0, + "languages": [], + "name": "TOBA", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/toba", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOC_-_the_Typed_Object_Converter.json b/agency-indexes/DoE/TOC_-_the_Typed_Object_Converter.json new file mode 100644 index 00000000..b9a3ff41 --- /dev/null +++ b/agency-indexes/DoE/TOC_-_the_Typed_Object_Converter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "Typed object conversion service.", + "laborHours": 1322.4, + "languages": [], + "name": "TOC - the Typed Object Converter", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/typed_obj_converter", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOGA:_A_TOUGH_code_for_modeling_three-phase,_multi-component,_and_non-isothermal_processes_involved_in_CO2-based_Enhanced_Oil_Recovery__TOGA__v1.0.json b/agency-indexes/DoE/TOGA:_A_TOUGH_code_for_modeling_three-phase,_multi-component,_and_non-isothermal_processes_involved_in_CO2-based_Enhanced_Oil_Recovery__TOGA__v1.0.json new file mode 100644 index 00000000..41d5c4e0 --- /dev/null +++ b/agency-indexes/DoE/TOGA:_A_TOUGH_code_for_modeling_three-phase,_multi-component,_and_non-isothermal_processes_involved_in_CO2-based_Enhanced_Oil_Recovery__TOGA__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-12", + "metadataLastUpdated": "2021-05-14" + }, + "description": "TOGA (TOUGH Oil, Gas, Aqueous) is a numerical reservoir simulator for modeling non-isothermal flow and transport of water, CO2, multicomponent oil, and related gas components for applications including CO2-enhanced oil recovery (CO2-EOR) and geologic carbon sequestration in depleted oil and gas reservoirs. TOGA uses an approach based on the Peng-Robinson equation of state (PR-EOS) to calculate the thermophysical properties of the gas and oil phases including the gas/oil components dissolved in the aqueous phase, and uses a mixing model to estimate the thermophysical properties of the aqueous phase.", + "homepageURL": "https://tough.lbl.gov/licensing-download/tough-related-codes-licensing-download", + "laborHours": 0.0, + "languages": [], + "name": "TOGA: A TOUGH code for modeling three-phase, multi-component, and non-isothermal processes involved in CO2-based Enhanced Oil Recovery (TOGA) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://marketplace.lbl.gov/search?q=toga", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://tough.lbl.gov/licensing-download/tough-related-codes-licensing-download", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOMOCUPY.json b/agency-indexes/DoE/TOMOCUPY.json new file mode 100644 index 00000000..8d12387b --- /dev/null +++ b/agency-indexes/DoE/TOMOCUPY.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-19", + "metadataLastUpdated": "2022-09-19" + }, + "description": "ANL REFERENCE SF-22-102 DESCRIPTION: Tomocupy is a Python package and a command-line interface for GPU reconstruction of tomographic/laminographic data in 16-bit and 32-bit precision. It implements an efficient data processing conveyor allowing to overlap all data transfers with computations. First, independent Python threads are started for reading data chunks from the hard disk into a Python data queue and for writing reconstructed chunks from the Python queue to the hard disk. Second, CPU-GPU data transfers are overlapped with GPU computations by using CUDA streams.", + "laborHours": 0.0, + "languages": [], + "name": "TOMOCUPY", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tomography/tomocupy", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOOLKIT_FOR_ADVANCED_OPTIMIZATION.json b/agency-indexes/DoE/TOOLKIT_FOR_ADVANCED_OPTIMIZATION.json new file mode 100644 index 00000000..5f7210d3 --- /dev/null +++ b/agency-indexes/DoE/TOOLKIT_FOR_ADVANCED_OPTIMIZATION.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-08-23" + }, + "description": "The TAO project focuses on the development of software for large scale optimization problems. TAO uses an object-oriented design to create a flexible toolkit with strong emphasis on the reuse of external tools where appropriate. Our design enables bi-directional connection to lower level linear algebra support (for example, parallel sparse matrix data structures) as well as higher level application frameworks. The Toolkist for Advanced Optimization (TAO) is aimed at teh solution of large-scale optimization problems on high-performance architectures. Our main goals are portability, performance, scalable parallelism, and an interface independent of the architecture. TAO is suitable for both single-processor and massively-parallel architectures. The current version of TAO has algorithms for unconstrained and bound-constrained optimization.", + "laborHours": 738613.6, + "languages": [], + "name": "TOOLKIT FOR ADVANCED OPTIMIZATION", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/petsc/petsc", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOSS_STIG.json b/agency-indexes/DoE/TOSS_STIG.json new file mode 100644 index 00000000..1f190dc5 --- /dev/null +++ b/agency-indexes/DoE/TOSS_STIG.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-12-13", + "metadataLastUpdated": "2022-12-13" + }, + "description": "LLNL HPC systems run a custom version of RedHat's RHEL operating system known as TOSS. In 2022, after working with DISA, Livermore Computing staff completed the STIG (Security Technical Implementation Guide) for the TOSS 4 operating system. This software project contains the source code associated with that STIG and implements checks and remediations for configuring a system in compliance with that STIG.", + "laborHours": 0.0, + "languages": [], + "name": "TOSS STIG", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/toss-stig", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOUGH+_v1.5_Core_Code.json b/agency-indexes/DoE/TOUGH+_v1.5_Core_Code.json new file mode 100644 index 00000000..327510a0 --- /dev/null +++ b/agency-indexes/DoE/TOUGH+_v1.5_Core_Code.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-11", + "metadataLastUpdated": "2018-10-15" + }, + "description": "TOUGH+ v1.5 is a numerical code for the simulation of multi-phase, multi-component flow and transport of mass and heat through porous and fractured media, and represents the third update of the code since its first release [Moridis et al., 2008]. TOUGH+ is a successor to the TOUGH2 [Pruess et al., 1991; 2012] family of codes for multi-component, multiphase \ufb02uid and heat \ufb02ow developed at the Lawrence Berkeley National Laboratory. It is written in standard FORTRAN 95/2003, and can be run on any computational platform (workstations, PC, Macintosh). \n\nTOUGH+ v1.5 employs dynamic memory allocation, thus minimizing storage requirements. It has a completely modular structure, follows the tenets of Object-Oriented Programming (OOP), and involves the advanced features of FORTRAN 95/2003, i.e., modules, derived data types, the use of pointers, lists and trees, data encapsulation, defined operators and assignments, operator extension and overloading, use of generic procedures, and maximum use of the powerful intrinsic vector and matrix processing operations. \n\nTOUGH+ v1.5 is the core code for its family of applications, i.e., the part of the code that is common to all its applications. It provides a description of the underlying physics and thermodynamics of non-isothermal flow, of the mathematical and numerical approaches, as well as a detailed explanation of the general (common to all applications) input requirements, options, capabilities and output specifications. The core code cannot run by itself: it needs to be coupled with the code for the specific TOUGH+ application option that describes a particular type of problem. The additional input requirements specific to a particular TOUGH+ application options and related illustrative examples can be found in the corresponding User's Manual.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 8876.8, + "languages": [], + "name": "TOUGH+ v1.5 Core Code", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOUGH2-MP_Ver_2.0,_the_parallel_version_of_TOUGH2.json b/agency-indexes/DoE/TOUGH2-MP_Ver_2.0,_the_parallel_version_of_TOUGH2.json new file mode 100644 index 00000000..fc3254ee --- /dev/null +++ b/agency-indexes/DoE/TOUGH2-MP_Ver_2.0,_the_parallel_version_of_TOUGH2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-27", + "metadataLastUpdated": "2019-09-24" + }, + "description": "This is a significant upgrade on the TOUGH2 code, which is only distributed via ESTSC. The executable version contains two pieces of third party code. The developer is in the process of obtaining permission to release an executable version with these third party libraries. At this point we will only release source code.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TOUGH2-MP Ver 2.0, the parallel version of TOUGH2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOUGH2_V2.1.json b/agency-indexes/DoE/TOUGH2_V2.1.json new file mode 100644 index 00000000..bb886968 --- /dev/null +++ b/agency-indexes/DoE/TOUGH2_V2.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-25", + "metadataLastUpdated": "2018-09-27" + }, + "description": "TOUGH2 is a numerical simulator for nonisothermal flows of multicomponent, multiphase fluids in one-, two-, and three-dimensional porous and fracture media. The chief applications for which TOUGH2 is designed are in geothermal reservoir engineering, nuclear waste disposal, environmental assessment and remediation, geologic carbon sequestration, and unsaturated and saturated zone hydrology. \n\nThe TOUGH2 V2.1 package is an upgrade of TOUGH2 V2.0 (CR-1574) and includes the following improvements and enhancements relative to TOUGH2 V2.0: \n\n- Includes all known bug fixes \n\n- The module TMVOC (CR-1820) is fully integrated \n\n- The module ECO2N (CR-2202) is fully integrated \n\n- A fluid property module ECO2M has been added, that can seamlessly model CO2 storage and leakage scenarios, including transitions between super- and sub-critical fluids, and phase changes between liquid and gaseous CO2. \n\nThe TOUGH2 V2.1 package also supports all legacy fluid property modules, i.e., those packaged into TOUGH2 V2.0 (CR-1574), which includes T2VOC (CR-1254).", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 5715.2, + "languages": [], + "name": "TOUGH2 V2.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOUGH3_EOS7MG__EOS7MG__v1.1.json b/agency-indexes/DoE/TOUGH3_EOS7MG__EOS7MG__v1.1.json new file mode 100644 index 00000000..c2cf8d5a --- /dev/null +++ b/agency-indexes/DoE/TOUGH3_EOS7MG__EOS7MG__v1.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2024-05-09", + "metadataLastUpdated": "2024-05-15" + }, + "description": "EOS7MG is a new TOUGH3 module for modeling water, brine, and multiple gas mixtures in the subsurface multiphase flow system. The module allows mixture of as more as three gas components selecting from a list of predefined gases (CH4, C2H6, C3H8, H2S, CO2, N2, NO2, H2, and AIR). EOS7MG was developed based on EOS7C and inherited the general modeling capabilities of the TOUGH3 platform. It uses cubic equation of states for gas density, viscosity, and enthalpy calculation. The module provides the selection options for Peng-Robinson, Redlich-Kwong, or Soave-Redlich-Kwong equations of state. The subsurface flow and transport of gas and aqueous phase mixtures over a wide range of pressures and temperatures is modeled with a multiphase Darcy's Law and an accurate chemical equilibrium approach as originally implemented in EOS7C is used for calculation of the solubilities of different mass components. EOS7MG was designed to allow flexible number of components based on the number of gases included in the model. The potential application of this module may include subsurface gas storage, energy storage, CCS, enhanced gas recovery, and more.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 36039.2, + "languages": [], + "name": "TOUGH3/EOS7MG (EOS7MG) v1.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://marketplace.lbl.gov/tough", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOUGH3_v1.0.json b/agency-indexes/DoE/TOUGH3_v1.0.json new file mode 100644 index 00000000..fdb1d458 --- /dev/null +++ b/agency-indexes/DoE/TOUGH3_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-01", + "metadataLastUpdated": "2019-02-01" + }, + "description": "The invention simulates multi-dimensional, multi-phase, multi-component, non-isothermal flow and transport in fractured porous media, with applications in geosciences and reservoir engineering among others. The invention supports a number of different combinations of fluids and components from previous software versions.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TOUGH3 v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOUGHREACT-Pitzer_V1.21.json b/agency-indexes/DoE/TOUGHREACT-Pitzer_V1.21.json new file mode 100644 index 00000000..18b779ca --- /dev/null +++ b/agency-indexes/DoE/TOUGHREACT-Pitzer_V1.21.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-13", + "metadataLastUpdated": "2018-11-16" + }, + "description": "TOUGHREACT is a numerical simulation program for chemically reactive non-isothermal flows of multiphase fluids in porous and fractured media. The program is written in Fortran 77 and was developed by introducing reactive chemistry into the multiphase flow code TOUGH2 V2. Interactions between mineral assemblages and fluids can occur under local equilibrium or kinetic rates. The gas phase can be chemically active. Precipitation and dissolution reactions can change formation porosity and permeability, and can also modify the unsaturated flow properties of the rock.\nThe code is distributed with a comprehensive user's guide that includes sample problems addressing geothermal reservoirs and hydrothermal systems, nuclear waste isolation, groundwater quality, sequestration of carbon dioxide in saline aquifers, and supergene copper enrichment. The TOUGHREACT-Pitzer V1.21 package supports the following fluid property modules packaged into TOUGH2 V2.0 (CR-1574): EOS1, EOS2, EOS3, EOS4, EOS7, EOS9, and ECO2N. This version incorporates a Pitzer ion interaction model for application to saline solutions. It is NOT compatible with the most recent TOUGHREACT V2 and relies on the previous TOUGHREACT V1.21.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TOUGHREACT-Pitzer V1.21", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOUGHREACT_Pitzer_Ion-Interaction_Model.json b/agency-indexes/DoE/TOUGHREACT_Pitzer_Ion-Interaction_Model.json new file mode 100644 index 00000000..b4ed66bb --- /dev/null +++ b/agency-indexes/DoE/TOUGHREACT_Pitzer_Ion-Interaction_Model.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-19", + "metadataLastUpdated": "2019-09-24" + }, + "description": "The TOUGHREACT Pitzer ion-interaction model version was developed based on the previous versions of TOUGHREACT. The main extensions include the Pitzer ion-interaction model for ionic activity calculation of solutions over a broad range of concentrations and the coupling of the vapor-pressure-lowering effect of salinity to phase partitioning.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TOUGHREACT Pitzer Ion-Interaction Model", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOUGHREACT_V4.12.json b/agency-indexes/DoE/TOUGHREACT_V4.12.json new file mode 100644 index 00000000..463638a4 --- /dev/null +++ b/agency-indexes/DoE/TOUGHREACT_V4.12.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "TOUGHREACT V4.12 is a 3-D reactive transport code that handles to non-isothermal, multiphase/multicomponent fluid flow, heat transport, aqueous and gaseous species advection-diffusion, and equilibrium/kinetic water-gas-rock-biological reactions.\n\nTOUGHREACT V4.12 is based on TOUGHREACT V3.3, with several new features including: an option to compute activity coefficients using the Pitzer ion interaction model; implementation of ECO2N V2.0 for temperatures up to 300 C; options to simulate forward and reverse osmosis, including 2D Poiseuille flow; addition of EOS8 and revisions for EOS5 and EWASG with H2(g); addition of gas species decay, various new output formats and time step control options; many bug fixes.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 39428.8, + "languages": [], + "name": "TOUGHREACT V4.12", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TOUGHREACT__TREACT__v3.32.json b/agency-indexes/DoE/TOUGHREACT__TREACT__v3.32.json new file mode 100644 index 00000000..d8b30248 --- /dev/null +++ b/agency-indexes/DoE/TOUGHREACT__TREACT__v3.32.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-01-30", + "metadataLastUpdated": "2019-02-01" + }, + "description": "TOUGHREACT V3.32 is a 3-D reactive transport code that handles to non-isothermal, multiphase/multicomponent fluid flow, heat transport, aqueous and gaseous species advection-diffusion, and equilibrium/kinetic water-gas-rock-biological reactions. TOUGHREACT V3.32 is based on TOUGHREACT V3.0-OMP, with several new features including temperature and species-dependent aqueous species diffusion coefficients, addition of the EWASG EOS module, a new generalized Monod kinetics function, time-dependent pressure-temperature boundary conditions, new VisIt-compatible tecplot-format output files (with new flux and velocity vector component outputs), new input and output options, and improved global water mass balance and coupling between flow, transport and reactive chemistry.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TOUGHREACT (TREACT) v3.32", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TRACE.json b/agency-indexes/DoE/TRACE.json new file mode 100644 index 00000000..4628ed3a --- /dev/null +++ b/agency-indexes/DoE/TRACE.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-02-26", + "metadataLastUpdated": "2019-03-22" + }, + "description": "TRACE is a debugging and logging utility written in C/C++, perl, and shell", + "homepageURL": "https://cdcvs.fnal.gov/redmine/projects/trace", + "laborHours": 0.0, + "languages": [ + "C", + "C++" + ], + "name": "TRACE", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cdcvs.fnal.gov/redmine/projects/trace", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TRANSFORM_-_TRANsient_Simulation_Framework_of_Reconfigurable_Models.json b/agency-indexes/DoE/TRANSFORM_-_TRANsient_Simulation_Framework_of_Reconfigurable_Models.json new file mode 100644 index 00000000..351ffaa7 --- /dev/null +++ b/agency-indexes/DoE/TRANSFORM_-_TRANsient_Simulation_Framework_of_Reconfigurable_Models.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-03-28" + }, + "description": "A Modelica based library for modeling thermal hydraulic energy systems and other multi-physics systems. \n\nExisting development tools for early stage design and scoping of energy systems are often time consuming to use, proprietary, and do not contain the necessary function to model complete systems (i.e., controls, primary, and secondary systems) in a common platform. The Modelica programming language based TRANSFORM tool (1) provides a standardized, common simulation environment for early design of energy systems (i.e., power plants), (2) provides a library of baseline component modules to be assembled into full plant models using available geometry, design, and thermal-hydraulic data, (3) defines modeling conventions for interconnecting component models, and (4) establishes user interfaces and support tools to facilitate simulation development (i.e., configuration and parameterization), execution, and results display and capture.", + "laborHours": 1732.8, + "languages": [], + "name": "TRANSFORM - TRANsient Simulation Framework of Reconfigurable Models", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-Modelica/TRANSFORM-Library/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-Modelica/TRANSFORM-Library", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TRANSP.json b/agency-indexes/DoE/TRANSP.json new file mode 100644 index 00000000..06b19783 --- /dev/null +++ b/agency-indexes/DoE/TRANSP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "fpoli@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2022-01-02" + }, + "description": "TRANSP is a 1.5D equilibrium and transport solver for interpretation and prediction of tokamak discharges.", + "homepageURL": "https://transp.pppl.gov", + "laborHours": 1936723.2, + "languages": [], + "name": "TRANSP", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://transp.pppl.gov/license.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://transp.pppl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TRINIDI__Time-of-Flight_Resonance_Imaging_with_Neutrons_for_Isotopic_Density_Inference_.json b/agency-indexes/DoE/TRINIDI__Time-of-Flight_Resonance_Imaging_with_Neutrons_for_Isotopic_Density_Inference_.json new file mode 100644 index 00000000..ef53771a --- /dev/null +++ b/agency-indexes/DoE/TRINIDI__Time-of-Flight_Resonance_Imaging_with_Neutrons_for_Isotopic_Density_Inference_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-17", + "metadataLastUpdated": "2023-11-17" + }, + "description": "This software is an open-source Python library that provides tools for processing hyperspectral neutron time-of-flight radiography data. This type of data allows material decomposed reconstructions to be generated with the use of material characteristic spectral responses and the algorithms provided in this code library. The software library will contain tools for pre-processing the neutron measurement data, estimating measurement system parameters, reconstructing material decomposed radiographs, and computing material decomposed computed tomography (CT). Furthermore, it will have capability to generate and process simulated neutron time-of-flight data with the goal of benchmarking and demonstrating the tools that are provided. The software will include thorough documentation and application examples.", + "laborHours": 0.0, + "languages": [], + "name": "TRINIDI (Time-of-Flight Resonance Imaging with Neutrons for Isotopic Density Inference)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/trinidi", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TRITON.json b/agency-indexes/DoE/TRITON.json new file mode 100644 index 00000000..a187d203 --- /dev/null +++ b/agency-indexes/DoE/TRITON.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "TRITON is a 2D hydraulic, digital elevation model (DEM)-based model that accepts a variety of flow inputs including point-based inflow hydrographs, external boundary conditions, and runoff (i.e., excess rainfall). It provides information of flood maps and temporal evolution of water depth at each grid cell point at user-specified output time. Its unique feature is that TRITON can run on single or multiple CPUs and GPUs, proving to be very flexible in terms of system architecture.", + "laborHours": 5168.0, + "languages": [ + "C++, CUDA" + ], + "name": "TRITON", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/hydro/triton/-/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/hydro/triton", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TRUST_REGION_METHOD_FOR_BOUND-CONSTRAINED_MPCCS_WITH_NONLINEAR_OBJECTIVE.json b/agency-indexes/DoE/TRUST_REGION_METHOD_FOR_BOUND-CONSTRAINED_MPCCS_WITH_NONLINEAR_OBJECTIVE.json new file mode 100644 index 00000000..ca5c99f3 --- /dev/null +++ b/agency-indexes/DoE/TRUST_REGION_METHOD_FOR_BOUND-CONSTRAINED_MPCCS_WITH_NONLINEAR_OBJECTIVE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-03", + "metadataLastUpdated": "2022-01-04" + }, + "description": "The code is a python implementation of the optimization algorithm that is proposed in \"Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints\" (Apt# 163042). The code is not a general purpose optimization software but is designed to solve the specific class of optimization problems in the aforementioned article. To allow reproducibility it is implemented close to the theoretical framework that has been developed in the aforementioned article. It will be published without any third-party dependencies except for python and some popular and widespread python libraries.", + "laborHours": 0.0, + "languages": [], + "name": "TRUST REGION METHOD FOR BOUND-CONSTRAINED MPCCS WITH NONLINEAR OBJECTIVE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/paulmanns/slpcc", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TRuML.json b/agency-indexes/DoE/TRuML.json new file mode 100644 index 00000000..9de34591 --- /dev/null +++ b/agency-indexes/DoE/TRuML.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2018-06-19" + }, + "description": "Kappa and BioNetGen (BNGL) are prominent rule-based modeling languages for representing complex biochemical reaction networks. Each language is distributed with a distinct software suite and modelers may wish to take advantage of both toolsets. This application, TRuML, translates models written in either Kappa or BNGL into the other language. While similar in many respects, key differences between the two languages makes translation sufficiently complex that automation becomes a useful tool. TRuML accommodates the languages' complexities and produces a semantically equivalent model in the alternate language of the input model when possible, and an approximate model in certain other cases.", + "laborHours": 1565.6, + "languages": [], + "name": "TRuML", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/TRuML", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TTW__Transition_to_Wire_Device__[SWR-25-02].json b/agency-indexes/DoE/TTW__Transition_to_Wire_Device__[SWR-25-02].json new file mode 100644 index 00000000..1a9f3d78 --- /dev/null +++ b/agency-indexes/DoE/TTW__Transition_to_Wire_Device__[SWR-25-02].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-01-27", + "metadataLastUpdated": "2025-03-11" + }, + "description": "The Transition to Wire (TTW) hardware project is a method for connecting solar research samples with fragile interconnects to robust, weatherproof and consistent commercial connectors. The Transition to Wire device is a printed circuit board designed to facilitate the transition from tab ribbon or other unsecured electrical contacts on research samples to either wires or a connector. The four pin connector provides a kelvin (4 wire) connection at the solder pad where the sample connects.", + "laborHours": 45.6, + "languages": [], + "name": "TTW (Transition to Wire Device) [SWR-25-02]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/TTW/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/TTW", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TabVar:_Tabulated_Variables.json b/agency-indexes/DoE/TabVar:_Tabulated_Variables.json new file mode 100644 index 00000000..0707355c --- /dev/null +++ b/agency-indexes/DoE/TabVar:_Tabulated_Variables.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "TabVar: A Python library for manipulating datasets in the form of tabulated variables. Tables in tabvar contain many columns representing independent variables, but exactly one distinguished column for the dependent variable. Having a single distinguished column allows a natural lifting of arithmetic operators to tables, much (and in fact fully generalizing) multidimensional array arithmetic. The convenient syntax of whole-table arithmetic, along with the usual operations of filtering and aggregation, and all in the setting of python's interactive REPL allows for rapid exploration of datasets.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "TabVar: Tabulated Variables", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tacho.json b/agency-indexes/DoE/Tacho.json new file mode 100644 index 00000000..9d37964c --- /dev/null +++ b/agency-indexes/DoE/Tacho.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-10", + "metadataLastUpdated": "2022-10-20" + }, + "description": "SAND2022-7470 O Tacho is a performance portable sparse direct solver for use with various sparse matrix problems which typically arise from finite element methods. The code relies on the Kokkos parallel programming model porting to both CPUs and GPUs. It is also part of the Trilinos library. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Tacho", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tacho", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tafel_Fitter_v1.5.json b/agency-indexes/DoE/Tafel_Fitter_v1.5.json new file mode 100644 index 00000000..e99bd272 --- /dev/null +++ b/agency-indexes/DoE/Tafel_Fitter_v1.5.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-11", + "metadataLastUpdated": "2019-07-11" + }, + "description": "This program a new physical insight regarding efforts to evaluate electrochemical catalysts being developed for electrochemical energy conversion and storage. In particular, we ask: The methodology described here offers a solution to the problem of how to conduct Tafel analysis, which is used in determining electrocatalyst performance, in a quantitative manner, rather than through the qualitative guesswork it currently requires. This enables the measurement of electrocatalyst Tafel slopes and their associated parameters in a way that avoids the introduction of researcher bias, a problem to which current methods of Tafel fitting are prone. This procedure should significantly improve the ability of researchers working in the field of electrochemical energy conversion to rate and compare the catalyst materials being developed, advancing the characterization toolkit available to experimental electrochemists. \n\nThis work is born out of our general hypothesis that it should be possible to determine the proper regions for unambiguously fitting Tafel data by applying some set of physical constraints that link aspects of a Tafel plot to its corresponding J-V polarization curve. This algorithm applies such constraints and achieves the extraction of Tafel slopes in a wholly quantifiable and reliable fashion. Verification of this approach is achieved by pairing the theory with experiment, as the algorithm was tested using experimentally acquired data of three distinct, electrochemical reactions: platinum hydrogen evolution, iridium-catalyzed oxygen evolution, and platinum-catalyzed dioxygen reduction. For each of these cases, the algorithm predicts the same Tafel slope as those reported in long-established bodies of electrochemical literature, results suggesting the general applicability of this method for determining electrocatalyst Tafel slopes.", + "laborHours": 0.0, + "languages": [], + "name": "Tafel Fitter v1.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MEG-LBNL/Tafel_Fitter", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TaiPS.json b/agency-indexes/DoE/TaiPS.json new file mode 100644 index 00000000..2674d5dc --- /dev/null +++ b/agency-indexes/DoE/TaiPS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "The TAIl Particle Solver (TaiPS) described in this abstract evaluates the fast ion and electron distribution for inertial confinement fusion applications (ICF). The code was developed under a Laboratory Directed Research and Development (LDRD) project. The code falls under the Los Alamos Plasma Simulation (LAPS) framework, though it operates as a stand alone code. We would like to make it open source in order to enable its use by the broader ICF community. TaiPS solves the non-relativistic Fokker-Planck equation in 1D-2V geometry for a fast particle tail. Up to four ion species are evolved along with the electron population. A suite of approximate collision operators is present: (i) a test particle collision operator, (ii) a linearized Fokker-Planck collision operator, and (iii) and a nonlinear Fokker-Planck collision operator. The tail solution is matched to a bulk distribution function, whose form is evaluated from a Braginskii closure [S. Braginskii, Reviews of plasma physics]. The code utilizes a Chang-Cooper discretization in energy [J. Chang and G. Cooper, Journal of Computational Physics 6, 1 (1970)], a Legendre expansion in the pitch coordinate, and finite different in configuration space. The code has mostly been used to evaluate steady state solutions, though time stepping can be done utilizing PETSc's suite of explicit and implicit schemes. The primary applications of the code are to take the fast ion or electron tail distribution and use them to evaluate the fusion reactivity or various diagnostic signals such as Bremsstrahlung radiation. A separate code has been written to evaluate the fusion reactivity, whereas Bremsstrahlung radiation is evaluated by codes developed by Grisha Kagan's collaborators. Publications that have utilized this code are contained in Refs. [X.-Z. Tang, H. Berk, Z. Guo, and C. McDevitt, Physics of Plasmas 21, 032707 (2014), X.-Z. Tang, C. McDevitt, Z. Guo, and H. Berk, EPL (Europhysics Letters) 105, 32001 (2014), X.-Z. Tang, C. McDevitt, Z. Guo, and H. Berk, Physics of Plasmas 21, 032706 (2014), C. McDevitt, X.-Z. Tang, Z. Guo, and H. Berk, Physics of Plasmas 21, 032708 (2014), C. J. McDevitt, X.-Z. Tang, and Z. Guo, Physics of Plasmas 24, 112702 (2017), C. J. McDevitt, X.-Z. Tang, and Z. Guo, Plasma Physics and Controlled Fusion 61, 025005 (2018), C. McDevitt, X.-Z. Tang, Z. Guo, and H. Berk, Physics of Plasmas 21, 102705 (2014)].", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "TaiPS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tango.json b/agency-indexes/DoE/Tango.json new file mode 100644 index 00000000..55d45aba --- /dev/null +++ b/agency-indexes/DoE/Tango.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2020-09-01" + }, + "description": "Tango is a transport solver intended for coupling with codes that return turbulent fluxes. In many physics problems, including magnetically confined fusion plasmas such as a tokamak, a separation of timescales exists between the timescale of turbulence and the timescale for evolution of mean, macroscopic quantities such as density and temperature in response to turbulent fluxes. In the numerical simulation of such scenarios, it is desirable to efficiently exploit the separation of timescales. Furthermore, because in general the turbulent fluxes depend nonlinearly on the macroscopic quantities and their derivatives, certain numerical instabilities arise and special methods are required to handle them.\n", + "laborHours": 4438.4, + "languages": [], + "name": "Tango", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/tango", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tapsolver:_A_Python_Package_For_The_Simulation_And_Analysis_Of_Tap_Reactor_Experiments.json b/agency-indexes/DoE/Tapsolver:_A_Python_Package_For_The_Simulation_And_Analysis_Of_Tap_Reactor_Experiments.json new file mode 100644 index 00000000..107fb754 --- /dev/null +++ b/agency-indexes/DoE/Tapsolver:_A_Python_Package_For_The_Simulation_And_Analysis_Of_Tap_Reactor_Experiments.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-03-11", + "metadataLastUpdated": "2023-03-15" + }, + "description": "TAPsolver is a python package, which automates TAP simulation and analysis routines. TAPsolver is built around the python packages FEniCS and Dolfin-Adjoint, which help take advantage of model adjoints to provide automatic derivatives. TAPsolver is flexible, with reaction mechanisms and rate constants that can be set through input files that allow users to take advantage of the different functionalities, which include sensitivity analyses, parameter optimization and uncertainty quantification.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Tapsolver: A Python Package For The Simulation And Analysis Of Tap Reactor Experiments", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/medford-group/TAPsolver", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TaqMan_PCR_Simulator.json b/agency-indexes/DoE/TaqMan_PCR_Simulator.json new file mode 100644 index 00000000..7a806fc5 --- /dev/null +++ b/agency-indexes/DoE/TaqMan_PCR_Simulator.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "TaqSim simulates various types of PRC reactions, including multiplex reactions. Given a set of primers and dearch databases, TaqSim identifies amplicons that match user defined criteria and can generate output files in a number of formats allowing it to serve as a front-end or back-end for other software.", + "homepageURL": "http://staff.vbi.vt.edu/dyermd/publications/taqsim.html", + "laborHours": 0.0, + "name": "TaqMan PCR Simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://staff.vbi.vt.edu/dyermd/publications/taqsim.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tardigrade,_Version_1.1x.json b/agency-indexes/DoE/Tardigrade,_Version_1.1x.json new file mode 100644 index 00000000..753c8d57 --- /dev/null +++ b/agency-indexes/DoE/Tardigrade,_Version_1.1x.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-01-26", + "metadataLastUpdated": "2024-02-22" + }, + "description": "Tardigrade is a collection of functions, libraries, and stand-alone code which enables the simulation of materials using the higher-order micromorphic framework. The tools present are the interface to INL's MOOSE code which is used as the underlying FEA solver, several constitutive equations (linear elasticity, a pressure-sensitive elasto-plastic model, crystal plasticity, and additional models for geo-materials) useful for demonstration purposes and the simulation of some materials, the micromorphic filter which converts DNS information to micromorphic stress-deformation quantities, and the overlap coupling framework which enables multi-scale simulations of a coupled higher-order macroscale and a classically defined microscale.", + "laborHours": 0.0, + "languages": [], + "name": "Tardigrade, Version 1.1x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/tardigrade", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "1.1x" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tardigrade-examples_V0.1.0.json b/agency-indexes/DoE/Tardigrade-examples_V0.1.0.json new file mode 100644 index 00000000..ae78d88a --- /dev/null +++ b/agency-indexes/DoE/Tardigrade-examples_V0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2025-01-30" + }, + "description": "Tardigrade-examples is a repository of computational workflows that exercise the Tardigrade software package. The Tardigrade software package is an implementation of Eringen\u2019s micromorphic continuum theory with capabilities to support multiscale material modeling. These capabilities include homogenization through the Micromorphic Filter, calibration of micromorphic material models, and macroscale simulation in Tardigrade-MOOSE. This repository investigates continuum upscaling of various direct numerical simulations (DNS) conducted in Abaqus finite element (FE), Ratel FE, and GEOS material point method (MPM) software. Verification of the upscaling workflow is first investigated by considering DNS of trivial stress states for homogeneous materials, results of which indicate that classical continuum behavior is recovered as expected. DNS of heterogeneous materials are then considered.", + "laborHours": 10579.2, + "languages": [], + "name": "Tardigrade-examples V0.1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Tardigrade-examples", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tardigrade-examples_V0.2.0.json b/agency-indexes/DoE/Tardigrade-examples_V0.2.0.json new file mode 100644 index 00000000..484e3917 --- /dev/null +++ b/agency-indexes/DoE/Tardigrade-examples_V0.2.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-01-24", + "metadataLastUpdated": "2025-01-30" + }, + "description": "Tardigrade-examples (LANL code O4735) is a repository of computational workflows that exercise the Tardigrade software package.", + "laborHours": 15397.6, + "languages": [], + "name": "Tardigrade-examples V0.2.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-aea/Tardigrade-examples", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "0.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tardigrade.json b/agency-indexes/DoE/Tardigrade.json new file mode 100644 index 00000000..2a8f7e9e --- /dev/null +++ b/agency-indexes/DoE/Tardigrade.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "This code contains an implementation of Micromorphic continuum mechanics in the style of Eringen and Suhubi [1] developed during Nathan Miller's PhD thesis under the supervision of Richard Regueiro. The code is written in a finite deformation framework and contains micromoprhic constitutive models which can be used to simulate various solid mechanics problems. Interfaces to Abaqus and the Idaho National Laboratory code MOOSE are included as a part of the functionality with the possibility of extending to additional codes in the future.\n\n[1] A.Cemal Eringen, E.S. Suhubi, \"Nonlinear theory of simple micro-elastic solids\u2014I\", International Journal of Engineering Science, Volume 2, Issue 2, 1964, Pages 189-20", + "laborHours": 0.0, + "languages": [], + "name": "Tardigrade", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/tardigrade", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TaskAMR.json b/agency-indexes/DoE/TaskAMR.json new file mode 100644 index 00000000..6f5ce18a --- /dev/null +++ b/agency-indexes/DoE/TaskAMR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-06-08", + "metadataLastUpdated": "2018-06-14" + }, + "description": "TaskAMR is a Cartesian Block Adaptive Mesh Refinement (AMR) code, written using the Regent/Legion parallel programming system, that solves Finite Volume calculations. We provide implementations for linear advection and gas dynamics.", + "laborHours": 380.0, + "languages": [], + "name": "TaskAMR", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/TaskAMR", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TaskWorks_v1.0.json b/agency-indexes/DoE/TaskWorks_v1.0.json new file mode 100644 index 00000000..2fa87e81 --- /dev/null +++ b/agency-indexes/DoE/TaskWorks_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-01", + "metadataLastUpdated": "2021-04-01" + }, + "description": "TaskWorks is a portable, high-level, task engine designed for HPC workloads. Applications can create tasks and define dependencies between them with the task engine. Once the task is defined and submitted to TaskWorks, the TaskWorks engine will execute it according to the specified dependencies, without additional input from the application. TaskWorks has an integrated event manager monitors files, sockets, timers, and MPI operations, and these events can be used as task dependencies. TaskWorks is compatible with MPI and is designed to work efficiently with HPC applications that perform.", + "laborHours": 0.0, + "languages": [], + "name": "TaskWorks v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc-io/taskworks", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Task_Time_Tracker.json b/agency-indexes/DoE/Task_Time_Tracker.json new file mode 100644 index 00000000..7b924b85 --- /dev/null +++ b/agency-indexes/DoE/Task_Time_Tracker.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This client-side web app tracks the amount of time spent on arbitrary tasks. It allosw the creation of an unlimited number of arbitrarily named tasks ans via simple interactions, tracks the amount of time spent working on the drfined tasks.", + "laborHours": 3602.4, + "name": "Task Time Tracker", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Task-Time-Tracker", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tasmanian.json b/agency-indexes/DoE/Tasmanian.json new file mode 100644 index 00000000..6bff6356 --- /dev/null +++ b/agency-indexes/DoE/Tasmanian.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-01" + }, + "description": "The Toolkit for Adaptive Stochastic Modeling and Non-Intrusive ApproximatioN is a collection of robust libraries for high dimensional integration and interpolation as well as parameter calibration. The code consists of several modules that can be used individually or conjointly.", + "laborHours": 24624.0, + "languages": [], + "name": "Tasmanian", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/Tasmanian", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tau_SDSKV_Plugin.json b/agency-indexes/DoE/Tau_SDSKV_Plugin.json new file mode 100644 index 00000000..b3e650a1 --- /dev/null +++ b/agency-indexes/DoE/Tau_SDSKV_Plugin.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-28", + "metadataLastUpdated": "2022-01-28" + }, + "description": "The TAU SDSKV Plugin logs TAU Profiling events to an SDSKV Key-Value Database.", + "laborHours": 0.0, + "languages": [], + "name": "Tau SDSKV Plugin", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/tau-sdskv/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/tau-sdskv", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TaxonAPI.json b/agency-indexes/DoE/TaxonAPI.json new file mode 100644 index 00000000..fb31e9db --- /dev/null +++ b/agency-indexes/DoE/TaxonAPI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-13", + "metadataLastUpdated": "2020-08-13" + }, + "description": "This module provides a dynamic service to interact with the Taxon objects and was based on the original data_api spec for the taxon object.", + "laborHours": 957.6, + "languages": [], + "name": "TaxonAPI", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/taxon_api", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TaxonomyTools.json b/agency-indexes/DoE/TaxonomyTools.json new file mode 100644 index 00000000..9bf234a0 --- /dev/null +++ b/agency-indexes/DoE/TaxonomyTools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "This is the repository for \"TaxonomyTools\" developed by KBase. This is a KBase module generated by the KBase Software Development Kit (SDK).", + "laborHours": 1231.2, + "languages": [], + "name": "TaxonomyTools", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/TaxonomyTools", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Taxonomy_API_for_KBase_using_the_Relation_Engine.json b/agency-indexes/DoE/Taxonomy_API_for_KBase_using_the_Relation_Engine.json new file mode 100644 index 00000000..de43a802 --- /dev/null +++ b/agency-indexes/DoE/Taxonomy_API_for_KBase_using_the_Relation_Engine.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is an API for taxonomy data (updated from taxon_api) that queries the relation engine. This service is a registered as a KBase dynamic service under the module name taxonomy_re_api.", + "laborHours": 820.8, + "languages": [], + "name": "Taxonomy API for KBase using the Relation Engine", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/taxonomy_re_api", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Technical_Resilience_Navigator.json b/agency-indexes/DoE/Technical_Resilience_Navigator.json new file mode 100644 index 00000000..cae914c9 --- /dev/null +++ b/agency-indexes/DoE/Technical_Resilience_Navigator.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Technical Resilience Navigator (TRN) is a systematic approach to identifying vulnerabilities with energy and water systems, and prioritizing solutions that reduce risk. The ultimate outcome of the TRN is a set of actionable resilience solutions that address the site's most important gaps in resilience and enhance the ability to maintain mission continuity.\nThe TRN is designed to step users through this planning process, providing a framework to: assign roles and responsibilities\u037e collect and document information and data\u037e document key inputs and outputs for each of the TRN modules (Site Level Planning, Baseline Development, Risk Assessment, Solution Development, and Solution Prioritization)\u037e document prioritized list of resilience solutions\u037e and track progress through the entire process.\nCurrently \"software as a service\" at the listed website.", + "homepageURL": "https://trn.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Technical Resilience Navigator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://trn.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://trn.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Technical_Support_Guidelines_Calculator_Tool.json b/agency-indexes/DoE/Technical_Support_Guidelines_Calculator_Tool.json new file mode 100644 index 00000000..c32b3bb8 --- /dev/null +++ b/agency-indexes/DoE/Technical_Support_Guidelines_Calculator_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2018-10-23" + }, + "description": "Sandia National Laboratories has taken a set of calculation aids from the Boiling Water Reactor Owners\u2019 Group (BWROG) Technical Support Guidelines (TSG), which assist operators and engineers using Emergency Operating Procedures and Severe Accident Management Guidelines, and integrated them into a user-friendly Java-based software. This effort has begun the conversion of these TSG calculations into a Java application format from the original Excel spreadsheets. The original set of Excel spreadsheet calculation aids do not provide the same level of integration, usability, intuitiveness, and speed as a well-designed Java-based application. Achieving the best combination of these characteristics is highly important in an emergency response tool to mitigate a high stress situation and allow a faster, more robust response. Integration in a Java-based application allows for data to be better organized and communicated during the incident.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Java" + ], + "name": "Technical Support Guidelines Calculator Tool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Teko_v._1.0.json b/agency-indexes/DoE/Teko_v._1.0.json new file mode 100644 index 00000000..b35641d0 --- /dev/null +++ b/agency-indexes/DoE/Teko_v._1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Teko is a C++ library for implementation of blocked and segregated preconditioners in the context of iterative solvers for linear systems. Capabilities for decomposing larger matrices into user defined sub blocks are also provided. Additional functionality for creating approximate inverse operators utilizing solver and preconditioning packages in the Trilinos framework has also been implemented. Teko's primary application is in multiphysics simulation environment where a decomposition of the linear system in to physically meaningful blocks can be utilized to enhance performance of an iterative solver. However, applicability may extend to other problem domains where matrices can be decomposed into meaningful blocks.", + "laborHours": 8344830.4, + "name": "Teko v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Temperature_controlled_friction_extrusion_process.json b/agency-indexes/DoE/Temperature_controlled_friction_extrusion_process.json new file mode 100644 index 00000000..fbd89bc4 --- /dev/null +++ b/agency-indexes/DoE/Temperature_controlled_friction_extrusion_process.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Processing temperature is decisive to the properties and performance of the product in friction extrusion. However, the constantly varying thermal boundary conditions result in an unstable processing temperature even fixed die rotational speed and feed rate were implemented, which extensively disturb the stability of the process and the quality of the\nproduct. It is key to maintain the process temperature to ensure the properties of the product is uniform. What's more, a controlled processing temperature enables the properties of the product to be manipulatable between parts and between\ndifferent locations of one part", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Temperature controlled friction extrusion process", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Temperature_for_Spent_Fuel_Dry_Storage__DATING-A_.json b/agency-indexes/DoE/Temperature_for_Spent_Fuel_Dry_Storage__DATING-A_.json new file mode 100644 index 00000000..f1591edd --- /dev/null +++ b/agency-indexes/DoE/Temperature_for_Spent_Fuel_Dry_Storage__DATING-A_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-19", + "metadataLastUpdated": "2024-01-19" + }, + "description": "DATING (Determining Allowable Temperatures in Inert and Nitrogen Gases) calculates allowable initial temperatures for dry storage of light-water-reactor spent fuel and the cumulative damage fraction of Zircaloy cladding for specified initial storage temperature and stress and cooling histories. It is made available to ensure compliance with NUREG 10CFR Part 72, Licensing Requirements for the Storage of Spent Fuel in an Independent Spent Fuel Storage Installation (ISFSI). Although the program's principal purpose is to calculate estimates of allowable temperature limits, estimates for creep strain, annealing fraction, and life fraction as a function of storage time are also provided. Equations for the temperature of spent fuel in inert and nitrogen gas storage are included explicitly in the code; in addition, an option is included for a user-specified cooling history in tabular form, and tables of the temperature and stress dependencies of creep-strain rate and creep-rupture time for Zircaloy at constant temperature and constant stress or constant ratio of stress/modulus can be created. DATING includes the GEAR package for the numerical solution of the rate equations and DPLOT for plotting the time-dependence of the calculated cumulative damage-fraction, creep strain, radiation damage recovery, and temperature decay.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "None" + ], + "name": "Temperature for Spent Fuel Dry Storage (DATING-A)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Temperature_for_Spent_Fuel_Dry_Storage__DATING-M_.json b/agency-indexes/DoE/Temperature_for_Spent_Fuel_Dry_Storage__DATING-M_.json new file mode 100644 index 00000000..6a39f737 --- /dev/null +++ b/agency-indexes/DoE/Temperature_for_Spent_Fuel_Dry_Storage__DATING-M_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-19", + "metadataLastUpdated": "2024-01-19" + }, + "description": "DATING (Determining Allowable Temperatures in Inert and Nitrogen Gases) calculates allowable initial temperatures for dry storage of light-water-reactor spent fuel and the cumulative damage fraction of Zircaloy cladding for specified initial storage temperature and stress and cooling histories. It is made available to ensure compliance with NUREG 10CFR Part 72, Licensing Requirements for the Storage of Spent Fuel in an Independent Spent Fuel Storage Installation (ISFSI). Although the program's principal purpose is to calculate estimates of allowable temperature limits, estimates for creep strain, annealing fraction, and life fraction as a function of storage time are also provided. Equations for the temperature of spent fuel in inert and nitrogen gas storage are included explicitly in the code; in addition, an option is included for a user-specified cooling history in tabular form, and tables of the temperature and stress dependencies of creep-strain rate and creep-rupture time for Zircaloy at constant temperature and constant stress or constant ratio of stress/modulus can be created. DATING includes the GEAR package for the numerical solution of the rate equations and DPLOT for plotting the time-dependence of the calculated cumulative damage-fraction, creep strain, radiation damage recovery, and temperature decay.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "None" + ], + "name": "Temperature for Spent Fuel Dry Storage (DATING-M)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Template_Interfaces_for_Agile_Parallel_Data-Intensive_Science.json b/agency-indexes/DoE/Template_Interfaces_for_Agile_Parallel_Data-Intensive_Science.json new file mode 100644 index 00000000..5c82f60d --- /dev/null +++ b/agency-indexes/DoE/Template_Interfaces_for_Agile_Parallel_Data-Intensive_Science.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Tigres provides a programming library to compose and execute large-scale data-intensive scientific workflows from desktops to supercomputers. DOE User Facilities and large science collaborations are increasingly generating large enough data sets that it is no longer practical to download them to a desktop to operate on them. They are instead stored at centralized compute and storage resources such as high performance computing (HPC) centers. Analysis of this data requires an ability to run on these facilities, but with current technologies, scaling an analysis to an HPC center and to a large data set is difficult even for experts. Tigres is addressing the challenge of enabling collaborative analysis of DOE Science data through a new concept of reusable \"templates\" that enable scientists to easily compose, run and manage collaborative computational tasks. These templates define common computation patterns used in analyzing a data set.", + "homepageURL": "http://tigres.lbl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Template Interfaces for Agile Parallel Data-Intensive Science", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://dst.lbl.gov/ACSSoftware/tigres/docs/tigres-0.2.0/license_agreement.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://tigres.lbl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Template_Prompt_Permutation.json b/agency-indexes/DoE/Template_Prompt_Permutation.json new file mode 100644 index 00000000..761c0f1b --- /dev/null +++ b/agency-indexes/DoE/Template_Prompt_Permutation.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "klaskyhb@ornl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "This project evaluates a set of prompts to test their performance on specific summarization tasks for large language models (LLMs), in order to find the optimal prompt to enhance task performance. This is a slightly more generalized version of the complete-prompt-permutation project, with different strengths.", + "laborHours": 304.0, + "languages": [ + "Python" + ], + "name": "Template Prompt Permutation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/summer_2024/prompt_engineering/template-prompt-permutation", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "Summer 2024" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Temporal_Analysis_Of_Products_Statistical_Analysis_Processing.json b/agency-indexes/DoE/Temporal_Analysis_Of_Products_Statistical_Analysis_Processing.json new file mode 100644 index 00000000..dbab07bf --- /dev/null +++ b/agency-indexes/DoE/Temporal_Analysis_Of_Products_Statistical_Analysis_Processing.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-09-17", + "metadataLastUpdated": "2023-03-13" + }, + "description": "Temporal analysis of products statistical analysis package (tapsap) is a package for reading, cleaning, analyzing and making inference of temporal analysis of products (TAP) information. This package is designed with the intent for collaboration within the TAP community for advancing TAP analysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Temporal Analysis Of Products Statistical Analysis Processing", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/tapsap", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Temporal_Subgraph_Isomorphism_Detector.json b/agency-indexes/DoE/Temporal_Subgraph_Isomorphism_Detector.json new file mode 100644 index 00000000..23940102 --- /dev/null +++ b/agency-indexes/DoE/Temporal_Subgraph_Isomorphism_Detector.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Software for detecting matching subgraphs within a temporal network dataset, such that the chronology ordering of the edges is identical to the query graph. This can be used to find patterns of behavior in temporal graph data that may be of interest for a particular use case. The resulting matching nodes, edges and subgraphs are then output for the user, including the number of times a particular node was found to be associated with a temporal subgraph match. The number of times a node is associated with a match may indicate that node is more noteworthy for the given use case.", + "laborHours": 2249.6, + "languages": [], + "name": "Temporal Subgraph Isomorphism Detector", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/temporal_subgraph_isomorphism", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tempus_v._1.0.json b/agency-indexes/DoE/Tempus_v._1.0.json new file mode 100644 index 00000000..e5e28705 --- /dev/null +++ b/agency-indexes/DoE/Tempus_v._1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Tempus is a software framework for the time integration of ordinary differential equations (ODEs), partial differential equations (PDEs), and differential-algebraic equations (DAEs). Examples of time-integration methods available are Forward Euler, Backward Euler, Explicit Runge-Kutta and Implicit Runge-Kutta methods. Tempus can be used from small systems of equations (e.g., single ODEs for the time evolution of plasticity models) to large-scale transient simulations requiring exascale computing (e.g., flow fields around reentry vehicles and magneto-hydrodynamics). Tempus will be released as part of Trilinos under a BSD open source license.", + "laborHours": 8344830.4, + "languages": [], + "name": "Tempus v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TenSQL_v.2023.01.20.json b/agency-indexes/DoE/TenSQL_v.2023.01.20.json new file mode 100644 index 00000000..ce0baf96 --- /dev/null +++ b/agency-indexes/DoE/TenSQL_v.2023.01.20.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-19" + }, + "description": "SAND2024-02520O\nTensor SQL Database performs certain relational database management system/structured query language (RDBMS/SQL) queries faster than is possible using existing state-of-the-art databases. Tensor SQL is optimized for sparse linear algebra problems and other whole-table queries. Currently, the database is being used only for research and program development. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "TenSQL v.2023.01.20", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TenSQL", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2023.01.20" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tensor_Algebra_Library_for_NVidia_Graphics_Processing_Units.json b/agency-indexes/DoE/Tensor_Algebra_Library_for_NVidia_Graphics_Processing_Units.json new file mode 100644 index 00000000..0f8e6fec --- /dev/null +++ b/agency-indexes/DoE/Tensor_Algebra_Library_for_NVidia_Graphics_Processing_Units.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2022-03-28" + }, + "description": "This is a general purpose math library implementing basic tensor algebra operations on NVidia GPU accelerators. This software is a tensor algebra library that can perform basic tensor algebra operations, including tensor contractions, tensor products, tensor additions, etc., on NVidia GPU accelerators, asynchronously with respect to the CPU host. It supports a simultaneous use of multiple NVidia GPUs. Each asynchronous API function returns a handle which can later be used for querying the completion of the corresponding tensor algebra operation on a specific GPU. The tensors participating in a particular tensor operation are assumed to be stored in local RAM of a node or GPU RAM. The main research area where this library can be utilized is the quantum many-body theory (e.g., in electronic structure theory).", + "laborHours": 19258.4, + "languages": [], + "name": "Tensor Algebra Library for NVidia Graphics Processing Units", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/DmitryLyakh/TAL_SH", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tensor_Basis_Neural_Network_v._1.0__beta_.json b/agency-indexes/DoE/Tensor_Basis_Neural_Network_v._1.0__beta_.json new file mode 100644 index 00000000..46aee1f5 --- /dev/null +++ b/agency-indexes/DoE/Tensor_Basis_Neural_Network_v._1.0__beta_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "This software package can be used to build, train, and test a neural network machine learning model. The neural network architecture is specifically designed to embed tensor invariance properties by enforcing that the model predictions sit on an invariant tensor basis. This neural network architecture can be used in developing constitutive models for applications such as turbulence modeling, materials science, and electromagnetism.", + "laborHours": 380.0, + "languages": [ + "Python 2.7" + ], + "name": "Tensor Basis Neural Network v. 1.0 (beta)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tbnn", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tensor_Extraction_of_Latent_Features__TELF_.json b/agency-indexes/DoE/Tensor_Extraction_of_Latent_Features__TELF_.json new file mode 100644 index 00000000..7e2c08be --- /dev/null +++ b/agency-indexes/DoE/Tensor_Extraction_of_Latent_Features__TELF_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "Tensor ELF is a user-friendly parallel tensor decomposition Python toolbox that includes a suite of machine learning algorithms for CPU and GPU architectures for the analysis of sparse and dense data including utility tools for pre-processing and post-processing.", + "laborHours": 32756.0, + "languages": [], + "name": "Tensor Extraction of Latent Features (TELF)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/T-ELF", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tensor_Network_Quantum_Virtual_Machine__TNQVM_.json b/agency-indexes/DoE/Tensor_Network_Quantum_Virtual_Machine__TNQVM_.json new file mode 100644 index 00000000..46e4d43c --- /dev/null +++ b/agency-indexes/DoE/Tensor_Network_Quantum_Virtual_Machine__TNQVM_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "There is a lack of state-of-the-art quantum computing simulation software that scales on heterogeneous systems like Titan. Tensor Network Quantum Virtual Machine (TNQVM) provides a quantum simulator that leverages a distributed network of GPUs to simulate quantum circuits in a manner that leverages recent results from tensor network theory.", + "laborHours": 23332.0, + "name": "Tensor Network Quantum Virtual Machine (TNQVM)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-QCI/tnqvm/blob/master/examples/CMakeLists.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/tnqvm", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tensor_Toolbox_for_MATLAB_v._3.0.json b/agency-indexes/DoE/Tensor_Toolbox_for_MATLAB_v._3.0.json new file mode 100644 index 00000000..50ceb523 --- /dev/null +++ b/agency-indexes/DoE/Tensor_Toolbox_for_MATLAB_v._3.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-25" + }, + "description": "Tensors (also known as multidimensional arrays or N-way arrays) are used in a variety of applications ranging from chemometrics to network analysis. The Tensor Toolbox provides classes for manipulating dense, sparse, and structured tensors using MATLAB's object-oriented features. It also provides algorithms for tensor decomposition and factorization, algorithms for computing tensor eigenvalues, and methods for visualization of results.", + "laborHours": 21386.4, + "languages": [ + "MATLAB", + "XSLT", + "C" + ], + "name": "Tensor Toolbox for MATLAB v. 3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tensor_toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Terascale_Simulation_Tolls_and_Technologies.json b/agency-indexes/DoE/Terascale_Simulation_Tolls_and_Technologies.json new file mode 100644 index 00000000..a6df9a1e --- /dev/null +++ b/agency-indexes/DoE/Terascale_Simulation_Tolls_and_Technologies.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The Terascale Simulation Tools and Technologies (TSTT) center is a collaboration between several universities and DOE laboratories, and is funded by the DOE Scientific Discovery for Advanced Computing (SciDAC) program. The primary objective of the (TSTT) center is to develop technologies that enable application scientists to easily use multiple mesh and discretization strageties within a single simulation on terascale computers. This is accomplished through the development of common functional interfaces to geometry, mesh, and other simulation data. This package is Sandia's implementation of these interfaces.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Terascale Simulation Tolls and Technologies", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Terraform_oVirt_Provider.json b/agency-indexes/DoE/Terraform_oVirt_Provider.json new file mode 100644 index 00000000..b29602d3 --- /dev/null +++ b/agency-indexes/DoE/Terraform_oVirt_Provider.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This code creates a new \"provider\" plugin to the terraform utility that allows it control virtual machines running in oVirt.", + "laborHours": 228.0, + "languages": [], + "name": "Terraform oVirt Provider", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-MSC/terraform-provider-ovirt", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TestSNAP.json b/agency-indexes/DoE/TestSNAP.json new file mode 100644 index 00000000..6cd0762d --- /dev/null +++ b/agency-indexes/DoE/TestSNAP.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-29", + "metadataLastUpdated": "2024-07-30" + }, + "description": "TestSNAP is a stand-alone prototype of the SNAP force kernel used in the LAMMPS molecular dynamics code. 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It provides an easy way to define user friendly command line interfaces. It uses cdp for parsing arguments.", + "laborHours": 653.6, + "languages": [], + "name": "TestsRunner", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/TestsRunner", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Teuchos_Utility_Package.json b/agency-indexes/DoE/Teuchos_Utility_Package.json new file mode 100644 index 00000000..e4e0d661 --- /dev/null +++ b/agency-indexes/DoE/Teuchos_Utility_Package.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-16" + }, + "description": "Teuchos is designed to provide portable, object-oriented tools for Trillnos developers and users. This includes templated wrappers to BLAS/LAPACK, a serial dense matrix class, a parameter list, XML parsing utilities, reference counted pointer (smart pointer) utilities, and more. These tools are designed to run on both serial and parallel computers.", + "laborHours": 8344830.4, + "languages": [], + "name": "Teuchos Utility Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Thallium.json b/agency-indexes/DoE/Thallium.json new file mode 100644 index 00000000..66d9d275 --- /dev/null +++ b/agency-indexes/DoE/Thallium.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-31", + "metadataLastUpdated": "2022-01-31" + }, + "description": "Thallium is a C++14 library wrapping Margo, Mercury, and Argobots and providing an object-oriented way to use these libraries.", + "laborHours": 0.0, + "languages": [], + "name": "Thallium", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-thallium/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-thallium", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Thallium_Microservice_Template.json b/agency-indexes/DoE/Thallium_Microservice_Template.json new file mode 100644 index 00000000..379a6df2 --- /dev/null +++ b/agency-indexes/DoE/Thallium_Microservice_Template.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-31", + "metadataLastUpdated": "2022-01-31" + }, + "description": "This project is a template to start developing a Mochi microservice based on Thallium.", + "laborHours": 0.0, + "languages": [], + "name": "Thallium Microservice Template", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/thallium-microservice-template/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/thallium-microservice-template", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Chicago_Social_Interaction_Model__ChiSIM_.json b/agency-indexes/DoE/The_Chicago_Social_Interaction_Model__ChiSIM_.json new file mode 100644 index 00000000..2619324c --- /dev/null +++ b/agency-indexes/DoE/The_Chicago_Social_Interaction_Model__ChiSIM_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2021-09-28" + }, + "description": "ChiSIM is a framework for implementing agent-based models that simulate the mixing of a synthetic population. In a ChiSIM based model, each agent, that is, each person in the simulated population, resides in a place (a household, dormitory or retirement home/long term care facility, for example), and moves among other places such as workplaces, homes, clinics, and community resources. Agents typically move between places according to their domain specific activity profile, such that each agent has a profile that determines at what times throughout the day they occupy a particular location. Once in a place, an agent mixes with other agents in some model or domain-specific way. For example, an agent may expose other agents to a disease in an epidemiological model.", + "laborHours": 0.0, + "languages": [], + "name": "The Chicago Social Interaction Model (ChiSIM)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Repast/chiSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Cinema_Science_Project.json b/agency-indexes/DoE/The_Cinema_Science_Project.json new file mode 100644 index 00000000..274d037a --- /dev/null +++ b/agency-indexes/DoE/The_Cinema_Science_Project.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "This repository holds the website files for the Cinema Science project. ", + "laborHours": 18072.8, + "languages": [], + "name": "The Cinema Science Project", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinemascience.github.io/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinemascience.github.io", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Datatype_Compare_Library_v.1.0.json b/agency-indexes/DoE/The_Datatype_Compare_Library_v.1.0.json new file mode 100644 index 00000000..9ed87203 --- /dev/null +++ b/agency-indexes/DoE/The_Datatype_Compare_Library_v.1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Datatype Compare (DTCMP) library provides routines that sort, search, merge, partition, rank, and select items using operations that compare MPI datatypes. Such routines are needed im MPI applications dealing with large distributed latasets, where the amount of data is too large to gather to a single process.", + "laborHours": 10047.2, + "name": "The Datatype Compare Library v.1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/dtcmp/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/dtcmp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Defender's_Role_in_Cyber_Security.json b/agency-indexes/DoE/The_Defender's_Role_in_Cyber_Security.json new file mode 100644 index 00000000..8711c0ed --- /dev/null +++ b/agency-indexes/DoE/The_Defender's_Role_in_Cyber_Security.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The embodiment of this work is a table top game to explore cyber security and network defense concepts and cost. The game structure is such that it provides players an immersive environment to play a given role in cyber security to investigate the result of infrastructure and response decisions.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "The Defender's Role in Cyber Security", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Dynamic_Analyzer_for_MPI:_the_first_dynamic_analyzer_of_MPI.json b/agency-indexes/DoE/The_Dynamic_Analyzer_for_MPI:_the_first_dynamic_analyzer_of_MPI.json new file mode 100644 index 00000000..1afda150 --- /dev/null +++ b/agency-indexes/DoE/The_Dynamic_Analyzer_for_MPI:_the_first_dynamic_analyzer_of_MPI.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "DAMPI is a dynamic testing/verification tool that scalably covers non-deterministic interactions of MPI (e.g., sildcard-receives).", + "laborHours": 0.0, + "languages": [], + "name": "The Dynamic Analyzer for MPI: the first dynamic analyzer of MPI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/the-dynamic-analyzer-for-mpi-the-first-dynamic-analyzer-of-mpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Functionally-Assembled_Terrestrial_Ecosystem_Simulator_Version_1.json b/agency-indexes/DoE/The_Functionally-Assembled_Terrestrial_Ecosystem_Simulator_Version_1.json new file mode 100644 index 00000000..5d4d44d8 --- /dev/null +++ b/agency-indexes/DoE/The_Functionally-Assembled_Terrestrial_Ecosystem_Simulator_Version_1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2021-10-01" + }, + "description": "The Functionally-Assembled Terrestrial Ecosystem Simulator (FATES) is a vegetation model for use in Earth system models (ESMs). The model includes a size- and age-structured representation of tree dynamics, competition between functionally diverse plant functional types, and the biophysics underpinning plant growth, competition, mortality, as well as the carbon, water, and energy exchange with the atmosphere. The FATES model is designed as a modular vegetation model that can be integrated within a host land model for inclusion in ESMs. The model is designed for use in global change studies to understand and project the responses and feedbacks between terrestrial ecosystems and the Earth system under changing climate and other forcings.", + "homepageURL": "https://zenodo.org/record/3825474", + "laborHours": 0.0, + "languages": [], + "name": "The Functionally-Assembled Terrestrial Ecosystem Simulator Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NGEET/fates-release/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://zenodo.org/record/3825474", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Generalized_Spallation_Model.json b/agency-indexes/DoE/The_Generalized_Spallation_Model.json new file mode 100644 index 00000000..4ad53613 --- /dev/null +++ b/agency-indexes/DoE/The_Generalized_Spallation_Model.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2022-01-06" + }, + "description": "The Generalized Spallation Model (GSM) event generator is an advanced, robust, and scalable Fortran code developed from an extended and improved version of the earlier event generator codes CEM03.03 and LAQGSM03.03. The GSM implements its algorithms within the context of cascade exciton, particle equilibration, particle evaporation, and particle disintegration models sampled via Monte-Carlo techniques. Coalescence of particles is also considered. The GSM assumes the incident particles has sufficient energy to satisfy the assumptions utilized in the GSM. The GSM calculates reactions induced by hadrons and nuclei incident on nuclear targets at incident energies ranging from ~20 MeV up to several TeV per nucleon. Usage of GSM is recommended however for particles with incident energies exceeding ~100 MeV to ensure model-assumptions are satisfied. The GSM additionally provides its clients with sub-model libraries to allow them to model desired physics within their own physical models.", + "laborHours": 0.0, + "languages": [], + "name": "The Generalized Spallation Model", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/generalized-spallation-model", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Genome_Taxonomy_Network__GTNet__v0.1.json b/agency-indexes/DoE/The_Genome_Taxonomy_Network__GTNet__v0.1.json new file mode 100644 index 00000000..dcfd3b9b --- /dev/null +++ b/agency-indexes/DoE/The_Genome_Taxonomy_Network__GTNet__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "GTNet is a neural network capable of identifying the species from which a genomic sequence was derived. Its main use will be in processing metagenomic sequences generated in microbiome research.", + "laborHours": 714.4, + "languages": [], + "name": "The Genome Taxonomy Network (GTNet) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exabiome/gtnet", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Graph_Based_Benchmark_Suite__GBBS_.json b/agency-indexes/DoE/The_Graph_Based_Benchmark_Suite__GBBS_.json new file mode 100644 index 00000000..f79073b6 --- /dev/null +++ b/agency-indexes/DoE/The_Graph_Based_Benchmark_Suite__GBBS_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nLaxman Dhulipala, Jessica Shi, Tom Tseng, Guy Blelloch, and Julian Shun.\nThe Graph Based Benchmark Suite (GBBS).\nProceedings of the Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA), pp. 1-8, 2020.\n\nWebsite: https://paralg.github.io/gbbs/", + "laborHours": 0.0, + "languages": [], + "name": "The Graph Based Benchmark Suite (GBBS)", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ParAlg/gbbs", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Hierarchical_Self-Attention_Network.json b/agency-indexes/DoE/The_Hierarchical_Self-Attention_Network.json new file mode 100644 index 00000000..150715af --- /dev/null +++ b/agency-indexes/DoE/The_Hierarchical_Self-Attention_Network.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "lakeje@ornl.gov" + }, + "date": { + "created": "2022-01-28", + "metadataLastUpdated": "2022-01-28" + }, + "description": "We introduce a deep learning architecture, the hierarchical self-attention network (HiSAN), that is specifically designed to overcome many of the difficulties associated with cancer pathology reports. HiSAN utilizes a hierarchical architecture similar to the hierarchical attention network models, but replaces the computationally expensive recurrent neural network layers with self-attention. HiSANs are superior to other machine learning and deep learning text classifiers in both accuracy and macro F-score across classification tasks of interest. Compared to the previous state-of-the-art, hierarchical attention networks and in our research, HiSANs not only are an order of magnitude faster to train, but also achieve about 1% better relative accuracy and 5% better relative macro F-score.", + "laborHours": 0.0, + "languages": [], + "name": "The Hierarchical Self-Attention Network", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-CANDLE/Benchmarks", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Hybrid_Toolkit.json b/agency-indexes/DoE/The_Hybrid_Toolkit.json new file mode 100644 index 00000000..181bc1fe --- /dev/null +++ b/agency-indexes/DoE/The_Hybrid_Toolkit.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "The Hybrid Toolkit facilitates moving research algorithms into a production environment by creating useful abstractions that separate analytics developers from the intricacies of the production data formats, data flows, and result representations. The toolkit also assists developers with activities such as creating analysis feature vectors, converting between data structures, and creating data pipelines.", + "laborHours": 13087.2, + "name": "The Hybrid Toolkit", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/The-Hybrid-Toolkit/tree/master/docs", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/The-Hybrid-Toolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_KBase_Narrative_Interface.json b/agency-indexes/DoE/The_KBase_Narrative_Interface.json new file mode 100644 index 00000000..f29dba73 --- /dev/null +++ b/agency-indexes/DoE/The_KBase_Narrative_Interface.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "The KBase Narrative Interface builds on the Jupyter Notebook and contains elements to interact with various KBase tools and data stores.", + "laborHours": 317528.0, + "languages": [], + "name": "The KBase Narrative Interface", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/narrative", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_LLNL_MPI_Tool_Suite.json b/agency-indexes/DoE/The_LLNL_MPI_Tool_Suite.json new file mode 100644 index 00000000..99ff009e --- /dev/null +++ b/agency-indexes/DoE/The_LLNL_MPI_Tool_Suite.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MPI_T is an interface for tools introduced in the 3.0 version of MPI. The interface provides mechanisms for tools to access and set performance and control variables that are exposed by an MPI implementation. We have developed an MPI_T tool suite to provide a first set of tools exploiting the new interface and to get tool writers started on the path to more sophisticated support.", + "laborHours": 1033.6, + "name": "The LLNL MPI_Tool Suite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/mpi-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Legion_Programming_System.json b/agency-indexes/DoE/The_Legion_Programming_System.json new file mode 100644 index 00000000..882ee4c3 --- /dev/null +++ b/agency-indexes/DoE/The_Legion_Programming_System.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "This disclosure covers LANL's contributions of source code to the already open source Legion Programming System. This covers example codes, contributions to the system's base source code, new features, bug fixes, associated documentation, and benchmarks. \n\nLegion is a data-centric parallel programming system for writing portable high performance programs targeted at distributed heterogeneous architectures. Legion presents abstractions which allow programmers to describe properties of program data (e.g. independence, locality). By making the Legion programming system aware of the structure of program data, it can automate many of the tedious tasks programmers currently face, including correctly extracting task- and data-level parallelism and moving data around complex memory hierarchies. A novel mapping interface provides explicit programmer controlled placement of data in the memory hierarchy and assignment of tasks to processors in a way that is orthogonal to correctness, thereby enabling easy porting and tuning of Legion applications to new architectures. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "The Legion Programming System", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Light-Weight_Group_Library.json b/agency-indexes/DoE/The_Light-Weight_Group_Library.json new file mode 100644 index 00000000..6de19b68 --- /dev/null +++ b/agency-indexes/DoE/The_Light-Weight_Group_Library.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Light-Weight Group (LWGRP) bibrary provides data structures and collective routines to define and operate on groups of MPI processes. Groups can be created and freed efficiently in O(log N) time space requiring less overhead that constructing full MPI communicators. This facilitates faster development of applications and libraries that need to rapidly create, use, and destroy process groups.", + "laborHours": 24289.6, + "name": "The Light-Weight Group Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/lwgrp/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lwgrp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Microgrid_Performance_Reliability_Model__MPRM__v._1.50_Beta.json b/agency-indexes/DoE/The_Microgrid_Performance_Reliability_Model__MPRM__v._1.50_Beta.json new file mode 100644 index 00000000..621cfd16 --- /dev/null +++ b/agency-indexes/DoE/The_Microgrid_Performance_Reliability_Model__MPRM__v._1.50_Beta.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2019-03-12", + "metadataLastUpdated": "2019-03-12" + }, + "description": "The MPRM is a simulation code that is used to statistically quantify the performance and reliability of a microgrid operating in islanded mode. Performance can be expressed in terms of fuel efficiency, renewable penetration, and other operational characteristics of the grid. Reliability can be expressed in terms of frequency and magnitude of load loss on a tier-by-tier, bus-by-bus basis or on an", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 30612.8, + "languages": [], + "name": "The Microgrid Performance Reliability Model (MPRM) v. 1.50 Beta", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.50 Beta" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_MultiThreaded_Graph_Library__MTGL_.json b/agency-indexes/DoE/The_MultiThreaded_Graph_Library__MTGL_.json new file mode 100644 index 00000000..f6065cca --- /dev/null +++ b/agency-indexes/DoE/The_MultiThreaded_Graph_Library__MTGL_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The MultiThreaded Graph Library (MTGL) is a set of header files that implement graph algorithm in such a way that they can run on massively multithreaded architectures. It is based upon the Boost Graph Library, but doesn't use Boost since the latter doesn't run well on these architectures.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "The MultiThreaded Graph Library (MTGL)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mtgl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_NEAMS_Integrated_Computational_Environment__NiCE_.json b/agency-indexes/DoE/The_NEAMS_Integrated_Computational_Environment__NiCE_.json new file mode 100644 index 00000000..dc4d4e1d --- /dev/null +++ b/agency-indexes/DoE/The_NEAMS_Integrated_Computational_Environment__NiCE_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Many new, high-performance nuclear energy modeling and simulation tools are under development in the United States and many more existing projects are moving to high-performance computing. This shift to state-of-the-art modeling and simulation will not only result in an unprecedented use of computing resources but it will generate extremely large amounts of data in extraordinary detail. Domain scientists will find themselves simultaneously in two positions: managing the complexity of their own problem domain and managing the complexity of a nightmarish scenario of high-performance computational tools. We believe that the computational science community should develop integrated tools for coupling, working with and analyzing data from simulation codes instead of leaving domains scientists and students to fend for themselves and come up with a \"working\" solution. While many projects offer some set of tools to work with their codes, to launch jobs remotely or to setup input files, most of these tools are rarely integrated in a holistic way to provide an easy, common and high-productivity environment for users. For that matter, most remote jobs are launched on \"the machine in the other room,\" but that certainly will not work for larger problems that require Leadership Class computing resources found only at U.S. National Laboratories or similar facilities. Overcoming the challenges of launching on these machines and even on public or private \"clouds\" are left as a challenge to the user.", + "laborHours": 92902.4, + "name": "The NEAMS Integrated Computational Environment (NiCE)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/eclipse/ice/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eclipse/ice", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_National_Solar_Permitting_Database.json b/agency-indexes/DoE/The_National_Solar_Permitting_Database.json new file mode 100644 index 00000000..96e8abe9 --- /dev/null +++ b/agency-indexes/DoE/The_National_Solar_Permitting_Database.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"The soft costs of solar \u2014 costs not associated with hardware \u2014 remain stubbornly high. Among the biggest soft costs are those associated with inefficiencies in local permitting and inspection. A study by the National Renewable Energy Laboratory and Lawrence Berkeley National Laboratory estimates that these costs add an average of $0.22/W per residential installation. This project helps reduce non-hardware/balance of system (BOS) costs by creating and maintaining a free and available site of permitting requirements and solar system verification software that installers can use to reduce time, capital, and resource investments in tracking permitting requirements. Software tools to identify best permitting practices can enable government stakeholders to optimize their permitting process and remove superfluous costs and requirements. Like \"\"a Wikipedia for solar permitting\"\", users can add, edit, delete, and update information for a given jurisdiction. We incentivize this crowdsourcing approach by recognizing users for their contributions in the form of SEO benefits to their company or organization by linking back to users' websites.\"", + "laborHours": 113817.6, + "name": "The National Solar Permitting Database", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/solarpermit/solarpermit", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Natural_Helmholtz-Hodge_Decomposition.json b/agency-indexes/DoE/The_Natural_Helmholtz-Hodge_Decomposition.json new file mode 100644 index 00000000..7c1d75c2 --- /dev/null +++ b/agency-indexes/DoE/The_Natural_Helmholtz-Hodge_Decomposition.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "nHHD is a C++ library to decompose a flow field into three components exhibiting specific types of behaviors. These components allow more targeted analysis of flow behavior and can be applied to a variety of application areas.", + "laborHours": 10396.8, + "name": "The Natural Helmholtz-Hodge Decomposition", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bhatiaharsh/naturalHHD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_NetLogger_Toolkit_V2.0.json b/agency-indexes/DoE/The_NetLogger_Toolkit_V2.0.json new file mode 100644 index 00000000..ac9da617 --- /dev/null +++ b/agency-indexes/DoE/The_NetLogger_Toolkit_V2.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "The NetLogger Toolkit is designed to monitor, under actual operating conditions, the behavior of all the elements of the application-to-application communication path in order to determine exactly where time is spent within a complex system. Using NetLogger, distributed application components are modified to produce timestamped logs of \"interesting\" events at all the critical points of the distributed system. Events from each component are correlated, which allows one to characterize the performance of all aspects of the system and network in detail. The NetLogger Toolkit itself consists of four components an API and library of functions to simplify the generation of application-level event logs, a set of tools for collecting and sorting log files, an event archive system, and a tool for visualization and analysis of the log files. In order to instrument an application to produce event logs, the application developer inserts calls to the NetLogger API at all the critical points in the code, then links the application with the NetLogger library. All the tools in the NetLogger Toolkit share a common log format, and assume the existence of accurate and synchronized system clocks. NetLogger messages can be logged using an easy-to-read text based format based on the lETF-proposed ULM format, or a binary format that can still be used through the same API but that is several times faster and smaller, with performance comparable or better than binary message formats such as MPI, XDR, SDDF-Binary, and PBIO. The NetLogger binary format is both highly efficient and self-describing, thus optimized for the dynamic message construction and parsing of application instrumentation. NetLogger includes an \"activation\" API that allows NetLogger logging to be turned on, off, or modified by changing an external file This IS useful for activating logging in daemons/services (e g GndFTP server). The NetLogger reliability API provides the ability to specify backup logging locations and periodically try to reconnect broken TCP pipe. A typical use for this is to store data on local disk while net is down. An event archiver can log one or more incoming NetLogger streams to a local disk file (netlogd) or to a mySQL database (netarchd). We have found exploratory, visual analysis of the log event data to be the most useful means of determining the causes of performance anomalies The NetLogger Visualization tool, niv, has been developed to provide a flexible and interactive graphical representation of system-level and application-level events.", + "homepageURL": "http://netlogger.lbl.gov", + "laborHours": 0.0, + "languages": [], + "name": "The NetLogger Toolkit V2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://netlogger.lbl.gov/software/netlogger-license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://netlogger.lbl.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_OpenSHMEM_Analyzer.json b/agency-indexes/DoE/The_OpenSHMEM_Analyzer.json new file mode 100644 index 00000000..ea386ce0 --- /dev/null +++ b/agency-indexes/DoE/The_OpenSHMEM_Analyzer.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The OpenSHMEM Analyzer is a compiler-based tool that can help users detect errors and provide useful analyses about their OpenSHMEM applications. The tool is built on top of the OpenUH compiler (a branch of Open64 compiler) and presents OpenSHMEM information as feedback to the user. Some of the analyses it provides include checks for correct usage of symmetric variables in OpenSHMEM calls, out-of-bounds checks for symmetric data, checks for the correct initialization of pointers to symmetric data, and symmetric data alias information.", + "homepageURL": "http://www.openshmem.org/site/OSA", + "laborHours": 0.0, + "languages": [ + "C, C++ / GCC / 4.3.4" + ], + "name": "The OpenSHMEM Analyzer", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.openshmem.org/site/node/58", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://www.openshmem.org/site/OSA", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Open_Host_Network_Packet_Process_Correlator_for_Windows.json b/agency-indexes/DoE/The_Open_Host_Network_Packet_Process_Correlator_for_Windows.json new file mode 100644 index 00000000..2242e5bb --- /dev/null +++ b/agency-indexes/DoE/The_Open_Host_Network_Packet_Process_Correlator_for_Windows.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The Hone sensors are packet-process correlation engines that log the relationships between applications and the communications they are responsible for. Hone sensors are available for a variety of platforms including Linux, Windows, and MacOSX. Hone sensors are designed to help analysts understand the meaning of communications on a deeper level by associating the origin or destination process to the communication. They do this by tracing communications on a per-packet basis, through the kernel of the operating system to determine their ultimate source/destination on the monitored machine.", + "laborHours": 3252.8, + "name": "The Open Host Network Packet Process Correlator for Windows", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/HoneProject/Windows-Sensor/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HoneProject/Windows-Sensor", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Power_and_Energy_Storage_Systems_Toolbox_--_PSTess_v.1.0.json b/agency-indexes/DoE/The_Power_and_Energy_Storage_Systems_Toolbox_--_PSTess_v.1.0.json new file mode 100644 index 00000000..116fcbd9 --- /dev/null +++ b/agency-indexes/DoE/The_Power_and_Energy_Storage_Systems_Toolbox_--_PSTess_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-09-30", + "metadataLastUpdated": "2021-09-30" + }, + "description": "The Power and Energy Storage Systems Toolbox (PSTess) is a MATLAB-based computing package for dynamic simulation and analysis of utility-scale battery storage systems. This codebase is a fork of the Power Systems Toolbox Version 3.0, developed at Rensselaer Polytechnic Institute (RPI) and Cherry Tree Scientific Software. While PSTess shares a common lineage with PST, it is a substantially different application. As the name implies, the main distinguishing characteristic of PSTess is its ability to model inverter-based energy storage systems (ESS). The model that enables this is called ess.m, and it serves the dual role of representing ESS operational constraints and the generator/converter interface. With PSTess, the generator/converter interface is modeled as a controllable current source with the ability to modulate both active and reactive current. The model ess.m permits four-quadrant modulation, which allows it to represent a wide variety of inverter-based resources beyond energy storage when paired with an appropriate supplemental control model. Examples include utility-scale photovoltaic (PV) power plants, type 4 wind plants, and static synchronous compensators (STATCOM). This capability is especially useful for modeling hybrid plants that combine energy storage with renewable resources. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8322 O", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "The Power and Energy Storage Systems Toolbox -- PSTess v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/snl-pstess", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Process_Manager_Collective_Library.json b/agency-indexes/DoE/The_Process_Manager_Collective_Library.json new file mode 100644 index 00000000..91aa3297 --- /dev/null +++ b/agency-indexes/DoE/The_Process_Manager_Collective_Library.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The PMGR_COLLECTIVE library provides an interface that MPI implemenataions may call to initialize ranks in a scalable way. It was developed to reduce the startup time MPI appkications, however, other tools such as debugger infrastructures have also found use cases for it. When first developed, it reduced the startup time from 15 minutes to 10 seconds on as 8192-node cluster.", + "laborHours": 3283.2, + "name": "The Process Manager Collective Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/pmgr_collective/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pmgr_collective", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Scalable_Checkpoint_Restart_Library.json b/agency-indexes/DoE/The_Scalable_Checkpoint_Restart_Library.json new file mode 100644 index 00000000..208a9c63 --- /dev/null +++ b/agency-indexes/DoE/The_Scalable_Checkpoint_Restart_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-05-27" + }, + "description": "The Scalable Checkpoint/Restart (SCR) library provides an interface that codes may use to worite our and read in application-level checkpoints in a scalable fashion. In the current implementation, checkpoint files are cached in local storage (hard disk or RAM disk) on the compute nodes. This technique provides scalable aggregate bandwidth and uses storage resources that are fully dedicated to the job. This approach addresses the two common drawbacks of checkpointing a large-scale application to a shared parallel file system, namely, limited bandwidth and file system contention. In fact, on current platforms, SCR scales linearly with the number of compute nodes. It has been benchmarked as high as 720GB/s on 1094 nodes of Atlas, which is nearly two orders of magnitude faster thanthe parallel file system.", + "laborHours": 24198.4, + "languages": [], + "name": "The Scalable Checkpoint/Restart Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/scr/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/scr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Suite_for_Embedded_Applications_and_Kernels.json b/agency-indexes/DoE/The_Suite_for_Embedded_Applications_and_Kernels.json new file mode 100644 index 00000000..5f18c5b3 --- /dev/null +++ b/agency-indexes/DoE/The_Suite_for_Embedded_Applications_and_Kernels.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Many applications of high performance embedded computing are limited by performance or power bottlenecks. We have designed SEAK, a new benchmark suite, (a) to capture these bottlenecks in a way that encourages creative solutions to these bottlenecks? and (b) to facilitate rigorous, objective, end-user evaluation for their solutions. To avoid biasing solutions toward existing algorithms, SEAK benchmarks use a mission-centric (abstracted from a particular algorithm) and goal-oriented (functional) specification. To encourage solutions that are any combination of software or hardware, we use an end-user blackbox evaluation that can capture tradeoffs between performance, power, accuracy, size, and weight. The tradeoffs are especially informative for procurement decisions. We call our benchmarks future proof because each mission-centric interface and evaluation remains useful despite shifting algorithmic preferences. It is challenging to create both concise and precise goal-oriented specifications for mission-centric problems. This paper describes the SEAK benchmark suite and presents an evaluation of sample solutions that highlights power and performance tradeoffs.", + "homepageURL": "https://hpc.pnl.gov/SEAK", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "The Suite for Embedded Applications and Kernels", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://hpc.pnl.gov/SEAK", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://hpc.pnl.gov/SEAK", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Unobtrusive_Memory_Allocator.json b/agency-indexes/DoE/The_Unobtrusive_Memory_Allocator.json new file mode 100644 index 00000000..159d3016 --- /dev/null +++ b/agency-indexes/DoE/The_Unobtrusive_Memory_Allocator.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This library implements a memory allocator/manager which ask its host program or library for memory refions to manage rather than requesting them from the operating system. This allocator supports multiple distinct heaps within a single executable, each of which may grow either upward or downward in memory. The GNU mmalloc library has been modified in such a way that its allocation algorithms have been preserved, but the manner in which it obtains regions to manage has been changed to request memory from the host program or library. Additional modifications allow the allocator to manage each heap as either upward or downward-growing. By allowing the hosting program or library to determine what memory is managed, this package allows a greater degree of control than other memory allocation/management libraries. Additional distinguishing features include the ability to manage multiple distinct heaps with in a single executable, each of which may grow either upward or downward in memory. The most common use of this library is in conjunction with the Berkeley Unified Parallel C (UPC) Runtime Library. This package is a modified version of the LGPL-licensed \"mmalloc\" allocator from release 5.2 of the \"gdb\" debugger's source code.", + "laborHours": 0.0, + "languages": [ + "Any ANSI C compiler." + ], + "name": "The Unobtrusive Memory Allocator", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upc-runtime/src/master/umalloc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_Well_Logging_Mobile_Source_Transit_Security__WL-MSTS__system.json b/agency-indexes/DoE/The_Well_Logging_Mobile_Source_Transit_Security__WL-MSTS__system.json new file mode 100644 index 00000000..f3c817ff --- /dev/null +++ b/agency-indexes/DoE/The_Well_Logging_Mobile_Source_Transit_Security__WL-MSTS__system.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Well Logging Mobile Source Transit Security (WL-MSTS) system was developed under funding from the National Nuclear Security Administration (NNSA) Office of Radiological Security (ORS). The objective of the system is to track mobile radioactive sources used in the well-logging service industry in support of oil and gas exploration. The individual software applications and libraries, and firmware executables work together and in conjunction with the electronic hardware components to provide situational awareness of the radioactive sources as they are transported from the home base of operations to a job site and back again. Information flows in near real time from the transport vehicle carrying the sources to the end user's central monitoring center using both cellular and satellite communications. A combination of active radio-frequency (RF) tags (attached to source shields) and radiation sensing is used to monitor the proximity of the radioactive sources to the transport vehicle. A Global Positioning System (GPS) is used to track the geographic location of the transport vehicle. Various sensors are used to detect and report tamper of the WL-MSTS components. An in-Cab Unit (iCU) is used to provide local status of the monitoring system to the driver of the transport vehicle. A browser based application allows authorized engineers to interact with the monitoring system to configure it and check status. Base Station application software allows qualified personnel to track alarms, source information and source locations and provides contact info of individuals that need to be notified should anomalous conditions be detected.\nWell Logging Master Control Unit (MCU)\t31390\nWell Logging MSTS rTag firmware\t31433\nWell Logging - In Cab Unit firmware\t31432\nBLE Beacon Electronic Tag (eTag) Firmware\t31480\nHome Base Security Solution (HBSS) Vault Extender Scanner\t31566\nHome Base Security Solution (HBSS) Master Scanner Firmware\t31567\nWell Logging MSTS Message Parser Library\t31568\nWell Logging MSTS GSOC Viewer\t31569\nWell Logging MSTS Admin Tool\t31570\nWell Logging HBSS Bunker Automated Data Service (BADS)\t31571\nWell Logging HBSS Bunker Inventory Graphical System (BIGS)\t31572\nWell Logging Master Control Unit Overpack (WL-MCU-OP) Firmware\t31583", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "The Well Logging Mobile Source Transit Security (WL-MSTS) system", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_absolute_path_command.json b/agency-indexes/DoE/The_absolute_path_command.json new file mode 100644 index 00000000..645e5c46 --- /dev/null +++ b/agency-indexes/DoE/The_absolute_path_command.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The ap command traveres all symlinks in a given file, directory, or executable name to identify the final absolute path. It can print just the final path, each intermediate link along with the symlink chan, and the permissions and ownership of each directory component in the final path. It has functionality similar to \"which\", except that it shows the final path instead of the first path. It is also similar to \"pwd\", but it can provide the absolute path to a relative directory from the current working directory.", + "laborHours": 76.0, + "name": "The absolute path command", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/ap/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/The_openPMD_Standard.json b/agency-indexes/DoE/The_openPMD_Standard.json new file mode 100644 index 00000000..575ac88a --- /dev/null +++ b/agency-indexes/DoE/The_openPMD_Standard.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-10", + "metadataLastUpdated": "2022-08-10" + }, + "description": "Open Standard for Particle-Mesh Data Files.", + "laborHours": 0.0, + "languages": [], + "name": "The openPMD Standard", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/openPMD-standard/blob/latest/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/openPMD-standard", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Theoretically-Efficient_and_Practical_Parallel_DBSCAN.json b/agency-indexes/DoE/Theoretically-Efficient_and_Practical_Parallel_DBSCAN.json new file mode 100644 index 00000000..408874f0 --- /dev/null +++ b/agency-indexes/DoE/Theoretically-Efficient_and_Practical_Parallel_DBSCAN.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\n\nYiqiu Wang, Yan Gu, and Julian Shun.\nTheoretically-Efficient and Practical Parallel DBSCAN.\nProceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pp. 2555-2571, 2020.", + "laborHours": 0.0, + "languages": [], + "name": "Theoretically-Efficient and Practical Parallel DBSCAN", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wangyiqiu/dbscan", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Theoretically-Efficient_and_Practical_Parallel_In-Place_Radix_Sorting.json b/agency-indexes/DoE/Theoretically-Efficient_and_Practical_Parallel_In-Place_Radix_Sorting.json new file mode 100644 index 00000000..9b6f9a0a --- /dev/null +++ b/agency-indexes/DoE/Theoretically-Efficient_and_Practical_Parallel_In-Place_Radix_Sorting.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nOmar Obeya, Endrias Kahssay, Edward Fan, and Julian Shun.\nTheoretically-Efficient and Practical Parallel In-Place Radix Sorting.\nProceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), pp. 213-224, 2019.", + "laborHours": 0.0, + "languages": [], + "name": "Theoretically-Efficient and Practical Parallel In-Place Radix Sorting", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/omarobeya/parallel-inplace-radixsort", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Theoretically_and_Practically_Efficient_Parallel_Nucleus_Decomposition.json b/agency-indexes/DoE/Theoretically_and_Practically_Efficient_Parallel_Nucleus_Decomposition.json new file mode 100644 index 00000000..808a9453 --- /dev/null +++ b/agency-indexes/DoE/Theoretically_and_Practically_Efficient_Parallel_Nucleus_Decomposition.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jshun@mit.edu" + }, + "date": { + "created": "2023-07-10", + "metadataLastUpdated": "2023-07-10" + }, + "description": "Source code for paper:\n\nJessica Shi, Laxman Dhulipala, and Julian Shun.\nTheoretically and Practically Efficient Parallel Nucleus Decomposition.\nProceedings of the VLDB Endowment, 15(3), pp. 583-596, 2022.", + "laborHours": 0.0, + "languages": [], + "name": "Theoretically and Practically Efficient Parallel Nucleus Decomposition", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jeshi96/arb-nucleus-decomp", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ThermalNetwork_[SWR-23-101].json b/agency-indexes/DoE/ThermalNetwork_[SWR-23-101].json new file mode 100644 index 00000000..44af4b29 --- /dev/null +++ b/agency-indexes/DoE/ThermalNetwork_[SWR-23-101].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-11-14", + "metadataLastUpdated": "2023-11-16" + }, + "description": "ThermalNetwork is software to size distributed ground heat exchangers for district-connected ground-source heat pump systems. The intended audience includes Ground Source Heat Pump Designers.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "ThermalNetwork [SWR-23-101]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/thermalNetwork", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ThermalTracker.json b/agency-indexes/DoE/ThermalTracker.json new file mode 100644 index 00000000..965fc08e --- /dev/null +++ b/agency-indexes/DoE/ThermalTracker.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-05", + "metadataLastUpdated": "2025-02-24" + }, + "description": "This technology was developed to address the need for monitoring bird and bat activity at offshore locations for wind\nenergy", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 12844.0, + "languages": [], + "name": "ThermalTracker", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ThermalTracker_3D.json b/agency-indexes/DoE/ThermalTracker_3D.json new file mode 100644 index 00000000..4651aba9 --- /dev/null +++ b/agency-indexes/DoE/ThermalTracker_3D.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ThermalTracker-3D is a stereo-vision solution for evaluating flight tracks of birds and bats around offshore wind turbines. Using a pair of thermal video cameras, the technology remotely senses movement of animals and objects, day and night, near critical assets. It generates motion tracks by collapsing a sequence of video frames from each camera into a single image that contains an entire flight track and then applies stereo-vision processing to transform the flight track into three dimensions. The approach allows tracking in near real time and automatically identifies moving objects based on features from the motion track and object size.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "ThermalTracker 3D", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Thermal_Analysis_of_Closed_Systems.json b/agency-indexes/DoE/Thermal_Analysis_of_Closed_Systems.json new file mode 100644 index 00000000..afb00525 --- /dev/null +++ b/agency-indexes/DoE/Thermal_Analysis_of_Closed_Systems.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-20", + "metadataLastUpdated": "2022-11-17" + }, + "description": "TAP-LOOP is a finite-difference program designed for steady-state and transient thermal analysis of recirculating fluid loops and associated heat transfer equipment; however, it is not limited to loop analysis. TAP-LOOP was developed to perform scoping and conceptual design analyses for closed test loops in the Fast Flux Test Facility (FFTF), but it can handle a variety of problems which can be described in terms of potentials, sources, sinks, and storage including, in addition to heat transfer problems, studies of potential fluid flow, electrical networks, and stress analysis.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Thermal Analysis of Closed Systems", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Thermal_Hydraulic_Analysis_of_Spent_Fuel_Casks.json b/agency-indexes/DoE/Thermal_Hydraulic_Analysis_of_Spent_Fuel_Casks.json new file mode 100644 index 00000000..0722cbcb --- /dev/null +++ b/agency-indexes/DoE/Thermal_Hydraulic_Analysis_of_Spent_Fuel_Casks.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-13", + "metadataLastUpdated": "2022-09-14" + }, + "description": "COBRA-SFS (Spent Fuel Storage) is a code for thermal-hydraulic analysis of multi-assembly spent fuel storage and transportation systems. It uses a lumped parameter finite difference approach to predict flow and temperature distributions in spent fuel storage systems and fuel assemblies, under forced and natural convection heat transfer conditions. Derived from the COBRA family of codes, which have been extensively evaluated against in-pile and out-of-pile data, COBRA-SFS retains all the important features of the COBRA codes for single phase fluid analysis, and extends the range application to include problems with two-dimensional radiative and three-dimensional conductive heat transfer. COBRA-SFS has been used to analyze various single- and multi-assembly spent fuel storage systems containing unconsolidated and consolidated fuel rods, with a variety of fill media, including air, helium and vacuum. Cycle 0 of COBRA-SFS was released in 1986. Subsequent applications of the code led to development of additional capabilities, which resulted in the release of Cycle 1 in February 1989. Since then, the code has undergone an independent technical review as part of a submittal to the Nuclear Regulatory Commission for a generic license to apply the code to spent fuel storage system analysis. Modifications and improvements to the code have been combined to form Cycle 2. Cycle 3., the newest version of COBRA-SFS, has been validated and verified for transient applications, such as a storage cask thermal response to a pool fire.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Thermal Hydraulic Analysis of Spent Fuel Casks", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Thermal_anomaly_and_rooftop_unit__RTU__detection_in_buildings_through_machine_learning__TAR__v1.json b/agency-indexes/DoE/Thermal_anomaly_and_rooftop_unit__RTU__detection_in_buildings_through_machine_learning__TAR__v1.json new file mode 100644 index 00000000..e0818a89 --- /dev/null +++ b/agency-indexes/DoE/Thermal_anomaly_and_rooftop_unit__RTU__detection_in_buildings_through_machine_learning__TAR__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-19", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This work applies thermography (Thermal infrared imaging) on building images to identify defects inside of them. The objective is to segment the defect area from the non-defect area automatically without human intervention\u2014a machine vision approach.", + "laborHours": 471.2, + "languages": [], + "name": "Thermal anomaly and rooftop unit (RTU) detection in buildings through machine learning (TAR) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/TAR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ThermoPhonon.json b/agency-indexes/DoE/ThermoPhonon.json new file mode 100644 index 00000000..ee250bdc --- /dev/null +++ b/agency-indexes/DoE/ThermoPhonon.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "joiner@ameslab.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "ThermoPhonon is a stand-alone code, which can be integrated into other software packages. Typically, it is used together with a density functional theory (DFT) code (such as VASP, Wien2k, AbInit, SIESTA) and a phonon code (such as Phonopy or Phon). The workflow is the following. Molecular dynamics (MD) in a supercell at a given temperature T is performed using another code. After sufficient equilibration, the output in the form of atomic positions and forces for a large number of selected MD steps is recorded into a file. If needed, one can modify this file by applying additional constraints, such as enforced crystal symmetry or subtracted motion of the center of mass. ThermoPhonon reads the file with atomic positions and forces and writes a new file with the force constants. Force constants can be used by another code (such as Phonopy or Phon) to produce phonon spectrum for plotting, in the assumption of known equilibrium atomic positions provided in a separate file.", + "homepageURL": "http://lib.dr.iastate.edu/ameslab_software/2", + "laborHours": 0.0, + "name": "ThermoPhonon", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://lib.dr.iastate.edu/ameslab_software/2", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Thermo_Raw_File_Reader.json b/agency-indexes/DoE/Thermo_Raw_File_Reader.json new file mode 100644 index 00000000..217c32d2 --- /dev/null +++ b/agency-indexes/DoE/Thermo_Raw_File_Reader.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Thermo Raw File Reader is a .NET DLL wrapper for Thermo's MS File Reader, which is accessible by creating an account at https://thermo.flexnetoperations.com/control/thmo/login then logging in and choosing \"Utility Software\". The Thermo Raw File Reader DLL provides several methods for parsing the information returned by MSFileReader, including: Determining the parent ion m/z and fragmentation mode in a given scan filter, determining the Ionization mode from a given scan filter, extracting MRM masses listed in a given scan filter, reporting the number of spectra in the .Raw file, returning details on a specific spectrum, and Obtaining the raw m/z and intensity values for a given spectrum.", + "laborHours": 3116.0, + "languages": [], + "name": "Thermo Raw File Reader", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Thermo-Raw-File-Reader", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Thermochimica.json b/agency-indexes/DoE/Thermochimica.json new file mode 100644 index 00000000..74b47ac7 --- /dev/null +++ b/agency-indexes/DoE/Thermochimica.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "radercd@ornl.gov" + }, + "date": { + "created": "2018-02-01", + "metadataLastUpdated": "2020-09-24" + }, + "description": "Thermochimica is a software library that determines a unique combination of phases and their compositions at thermochemical equilibrium. Thermochimica can be used for stand-alone calculations or it can be directly coupled to other codes. This release of the software does not have a graphical user interface (GUI) and it can be executed from the command line or from an Application Programming Interface (API). Also, it is not intended for thermodynamic model development or for constructing phase diagrams. The main purpose of the software is to be directly coupled with a multi-physics code to provide material properties and boundary conditions for various physical phenomena. Significant research efforts have been dedicated to enhance computational performance through advanced algorithm development, such as improved estimation techniques and non-linear solvers. Various useful parameters can be provided as output from Thermochimica, such as: determination of which phases are stable at equilibrium, the mass of solution species and phases at equilibrium, mole fractions of solution phase constituents, thermochemical activities (which are related to partial pressures for gaseous species), chemical potentials of solution species and phases, and integral Gibbs energy (referenced relative to standard state). The overall goal is to provide an open source computational tool to enhance the predictive capability of multi-physics codes without significantly impeding computational performance.", + "laborHours": 5654.4, + "languages": [], + "name": "Thermochimica", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-CEES/thermochimica", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Thermodynamics-informed_latent_space_dynamics_identification.json b/agency-indexes/DoE/Thermodynamics-informed_latent_space_dynamics_identification.json new file mode 100644 index 00000000..cb6b357e --- /dev/null +++ b/agency-indexes/DoE/Thermodynamics-informed_latent_space_dynamics_identification.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-05", + "metadataLastUpdated": "2024-09-19" + }, + "description": "This software showcases a latent space dynamics identification method, namely tLaSDI, that embeds the\nfirst and second principles of thermodynamics. The latent variables are learned through an autoencoder\nas a nonlinear dimension reduction model. The latent dynamics are constructed by a neural network-based\nmodel that precisely preserves certain structures for the thermodynamic laws through the\nGENERIC formalism. An abstract error estimate is established, which provides a new loss formulation\ninvolving the Jacobian computation of autoencoder. The autoencoder and the latent dynamics are\nsimultaneously trained to minimize the new loss. Computational examples demonstrate the effectiveness\nof tLaSDI, which exhibits robust generalization ability, even in extrapolation. In addition, an intriguing\ncorrelation is empirically observed between a quantity from tLaSDI in the latent space and the behaviors\nof the full-state solution.", + "laborHours": 2188.8, + "languages": [], + "name": "Thermodynamics-informed latent space dynamics identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pjss1223/tLaSDI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Thick-Restart_Laczos_Method_for_Symmetric_Eigenvalue_Problems.json b/agency-indexes/DoE/Thick-Restart_Laczos_Method_for_Symmetric_Eigenvalue_Problems.json new file mode 100644 index 00000000..bf2d522c --- /dev/null +++ b/agency-indexes/DoE/Thick-Restart_Laczos_Method_for_Symmetric_Eigenvalue_Problems.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "This software package implements the thick-restart Lanczos method. It can be used on either a single address space machine or distributed parallel machine. The user can choose to implement or use a matrix-vector multiplication routine in any form convenient. Most of the arithmetic computations in the software are done through calls to BLAS and LAPACK. The software is written in Fortran 90. Because Fortran 90 offers many utility functions such functions such as dynamic memory management, timing functions, random number generator and so on, the program is easily portable to different machines without modifying the source code. It can also be easily accessed from other language such as C or C-+. Since the software is highly modularized, it is relatively easy to adopt it for different type of situations. For example if the eigenvalue problem may have some symmetry and only a portion of the physical domain is discretized, then the dot-product routine needs to be modified. In this software, this modification is limited to one subroutine. It also can be instructed to write checkpoint files so that it can be restarted at a later time.", + "homepageURL": "https://sdm.lbl.gov/~kewu/trlan.html", + "laborHours": 0.0, + "languages": [ + "Fortran 90" + ], + "name": "Thick-Restart Laczos Method for Symmetric Eigenvalue Problems", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://sdm.lbl.gov/~kewu/trlan-license.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sdm.lbl.gov/~kewu/trlan.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Thomson_scattering_Cross_section_Calculator.json b/agency-indexes/DoE/Thomson_scattering_Cross_section_Calculator.json new file mode 100644 index 00000000..7d7673d1 --- /dev/null +++ b/agency-indexes/DoE/Thomson_scattering_Cross_section_Calculator.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-14", + "metadataLastUpdated": "2021-12-14" + }, + "description": "Code to calculate Thomson scattering cross sections.", + "laborHours": 0.0, + "languages": [], + "name": "Thomson scattering Cross section Calculator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Thomson-Scattering-Cross-Section-Calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Thread_Pool_Interface__TPI_.json b/agency-indexes/DoE/Thread_Pool_Interface__TPI_.json new file mode 100644 index 00000000..6ebacd4a --- /dev/null +++ b/agency-indexes/DoE/Thread_Pool_Interface__TPI_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Thread Pool Interface (TpI) provides a simple interface for running functions written in C or C++ in a thread-parallel mode. Application or library codes may need to perform operations thread-parallel on machines with multicore processors. the TPI library provides a simple mechanism for managing thread activation, deactivation, and thread-parallel execution of application-provided subprograms.", + "laborHours": 8344830.4, + "name": "Thread Pool Interface (TPI)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ThreatView.json b/agency-indexes/DoE/ThreatView.json new file mode 100644 index 00000000..0ea68d28 --- /dev/null +++ b/agency-indexes/DoE/ThreatView.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "The ThreatView project is based on our prior work with the existing ParaView open-source scientific visualization application. Where ParaView provides a grapical client optimized scientific visualization over the VTK parallel client server architecture, ThreatView provides a client optimized for more generic visual analytics over the same architecture. Because ThreatView is based on the VTK parallel client-server architecture, data sources can reside on remote hosts, and processing and rendering can be performed in parallel. As seen in Fig. 1, ThreatView provides four main methods for visualizing data: Landscape View, which displays a graph using a landscape metaphor where clusters of graph nodes produce \"hills\" in the landscape; Graph View, which displays a graph using a traditional \"ball-and-stick\" style; Table View, which displays tabular data in a standard spreadsheet; and Attribute View, which displays a tabular \"histogram\" of input data - for a selected table column, the Attribute View displays each unique value within the column, and the number of times that value appears in the data. There are two supplemental view types: Text View, which displays tabular data one-record-at-a-time; and the Statistics View, which displays input metadata, such as the number of vertices and edges in a graph, the number of rows in a table, etc.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [], + "name": "ThreatView", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Three-point_Analysis_for_Butler-Volmer_Electrochemical_Kinetics.json b/agency-indexes/DoE/Three-point_Analysis_for_Butler-Volmer_Electrochemical_Kinetics.json new file mode 100644 index 00000000..7661125a --- /dev/null +++ b/agency-indexes/DoE/Three-point_Analysis_for_Butler-Volmer_Electrochemical_Kinetics.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-04-10", + "metadataLastUpdated": "2025-04-10" + }, + "description": "This file contains a spreadsheet and equations that evaluate corrosion test data. The data (which can be\ninserted by the user) is current vs voltage data. This spreadsheet will be part of the supplemental\ninformation of a journal article that is under review.\nSpecifically, the spreadsheet evaluates the classical Butler Volmer equation in the presence of several\ndifferent forms of noise found in electrochemical systems. The forms of noise are: 1) solution resistance,\n2) random noise in the current, 3) drift of the open circuit potential voltage.", + "homepageURL": "https://doi.org/10.1016/j.corsci.2025.112900", + "laborHours": 0.0, + "languages": [], + "name": "Three-point Analysis for Butler-Volmer Electrochemical Kinetics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://doi.org/10.1016/j.corsci.2025.112900", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "version": "1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ThunderBoltz_API.json b/agency-indexes/DoE/ThunderBoltz_API.json new file mode 100644 index 00000000..c91093db --- /dev/null +++ b/agency-indexes/DoE/ThunderBoltz_API.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "The ThunderBoltz application programming interface (API) code is written in Python and is comprised of a set of tools to facilitate compilation of the ThunderBoltz code, as well as fast assembly and formatting of input files for the ThunderBoltz code, post-processing tools of ThunderBoltz results, plotting tools, and runs/schedules the ThunderBoltz code executable for calculations. The ThunderBoltz API code is utilized for importing and manipulating input cross section sets, input conditions, and any other simulation settings made available within the ThunderBoltz input deck via user-defined settings or via automatic generation. The API comes with a set of plotting capabilities of input cross sections, results from ThunderBoltz, and post-processed results carried out with the API.", + "laborHours": 5502.4, + "languages": [], + "name": "ThunderBoltz API", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ThunderBoltz", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tidal_Disruption_Event_Galaxy_Binner.json b/agency-indexes/DoE/Tidal_Disruption_Event_Galaxy_Binner.json new file mode 100644 index 00000000..4ae85004 --- /dev/null +++ b/agency-indexes/DoE/Tidal_Disruption_Event_Galaxy_Binner.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-10-28", + "metadataLastUpdated": "2021-10-28" + }, + "description": "This software simulates astronomical survey detections of tidal disruptions of stars by super-massive black holes. It begins with the synthetic galaxy catalogue described in van Velzen 2008 (https://arxiv.org/abs/1707.03458). The stellar disruption rate in each galaxy is estimated based on Stone & Metzger 2016 (https://arxiv.org/abs/1410.7772). Based on these rates, and the present-day stellar mass function in the galaxy, disruptions are randomly sampled, and the properties of the resulting flares are sampled based on empirical distributions. The code also accounts for obscuration by dust in the host galaxy. Finally, the survey selection effects are applied. The detectable simulated flares are stored in a database, allowing histograms of their properties to be created.", + "laborHours": 0.0, + "languages": [], + "name": "Tidal Disruption Event Galaxy Binner", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nroth/tdegb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tiered_Energy_Use_in_Buildings__TEB_.json b/agency-indexes/DoE/Tiered_Energy_Use_in_Buildings__TEB_.json new file mode 100644 index 00000000..51efa3cb --- /dev/null +++ b/agency-indexes/DoE/Tiered_Energy_Use_in_Buildings__TEB_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-03-06", + "metadataLastUpdated": "2021-03-09" + }, + "description": "This tool creates a set of building energy simulations and organizes them according to a tier-based model representing circuits that will be on or off depending on a microgrid controller (not included in this software). This Python based code uses the open-source RCBuildingSimulator that is under an amended MIT license. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.\nSAND2021-2528 O", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Tiered Energy Use in Buildings (TEB)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TEB", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tifpack_v_1.0.json b/agency-indexes/DoE/Tifpack_v_1.0.json new file mode 100644 index 00000000..5f25bd75 --- /dev/null +++ b/agency-indexes/DoE/Tifpack_v_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A package for computing and applying algebraic preconditioners in the context of preconditioned iterative methods. It is related to the existing Ifpack package in Trilinos but provides support for template scalar and ordinal types and explicitly relies on Tpetra and Kokkos instead of Epetra. Algebraic preconditioners are used by iterative solvers as solution method in engineering and scientific applications, including nonlinear equation solving, time integration, sensitivity analysis, stability analysis, optimization, and uncertainty quantification.", + "laborHours": 8344830.4, + "name": "Tifpack v 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tight-binding_model_for_materials_at_mesoscale.json b/agency-indexes/DoE/Tight-binding_model_for_materials_at_mesoscale.json new file mode 100644 index 00000000..b10eb11f --- /dev/null +++ b/agency-indexes/DoE/Tight-binding_model_for_materials_at_mesoscale.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "TBM3 is an open source package for computational simulations of quantum materials at multiple scales in length and time. The project originated to investigate the multiferroic behavior in transition-metal oxide heterostructures. The framework has also been designed to study emergent phemona in other quantum materials like 2-dimensional transition-metal dichalcogenides, graphene, topological insulators, and skyrmion in materials, etc. In the long term, we will enable the package for transport and time-resolved phenomena. TBM3 is currently a C++ based numerical tool package and framework for the design and construction of any kind of lattice structures with multi-orbital and spin degrees of freedom. The fortran based portion of the package will be added in the near future. The design of TBM3 is in a highly flexible and reusable framework and the tight-binding parameters can be modeled or informed by DFT calculations. It is currently GPU enabled and feature of CPU enabled MPI will be added in the future.", + "laborHours": 4286.4, + "name": "Tight-binding model for materials at mesoscale", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/TDIV/TBM3/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/TDIV/TBM3", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tike.json b/agency-indexes/DoE/Tike.json new file mode 100644 index 00000000..49cc7181 --- /dev/null +++ b/agency-indexes/DoE/Tike.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "dching@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2023-02-02" + }, + "description": "Tike is a library for reconstructing a 3D object from its diffraction measurements.", + "laborHours": 0.0, + "languages": [ + "CUDA", + "Python" + ], + "name": "Tike", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdvancedPhotonSource/tike.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Time-Based_CAN_IDS_Paper_Results_Code.json b/agency-indexes/DoE/Time-Based_CAN_IDS_Paper_Results_Code.json new file mode 100644 index 00000000..f3f9ad8d --- /dev/null +++ b/agency-indexes/DoE/Time-Based_CAN_IDS_Paper_Results_Code.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "moriano@ornl.gov" + }, + "date": { + "created": "2022-01-12", + "metadataLastUpdated": "2022-01-12" + }, + "description": "Modern vehicles are complex cyber-physical systems made of hundreds of electronic control units (ECUs) that communicate over controller area networks (CANs). This inherited complexity has expanded the CAN attack surface which is vulnerable to message injection attacks. These injections change the overall timing characteristics of messages on the bus, and thus, to detect these malicious messages, time-based intrusion detection systems (IDSs) have been proposed. However, time-based IDSs are usually trained and tested on low-fidelity datasets with unrealistic, labeled attacks. This makes difficult the task of evaluating, comparing, and validating IDSs. Here we detail and benchmark four time-based IDSs against the newly published ROAD dataset, the first open CAN IDS dataset with real (non-simulated) stealthy attacks with physically verified effects. We found that methods that perform hypothesis testing by explicitly estimating message timing distributions have lower performance than methods that seek anomalies in a distribution related statistic. In particular, these \u201cdistribution-agnostic\u201d based methods outperform \u201cdistribution-based\u201d methods by at least 55% in area under the precision-recall curve (AUC-PR). Our results expand the body of knowledge of CAN time-based IDSs by providing details of these methods and reporting their results when tested on datasets with real advanced attacks. Finally, we develop an after-market plug-in detector using lightweight hardware, which can be used to deploy the best performing IDS method on nearly any vehicle.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Time-Based CAN IDS Paper Results Code", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmoriano/can-time-based-ids-benchmark", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TimeChart.json b/agency-indexes/DoE/TimeChart.json new file mode 100644 index 00000000..aef09bf9 --- /dev/null +++ b/agency-indexes/DoE/TimeChart.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-14", + "metadataLastUpdated": "2022-07-14" + }, + "description": "TimeChart is a Python Qt-based graphing application for control systems. It is intended to be the modern, feature-by-feature matching alternative to the Motif EPICS Strip Tool application. Comparing with Strip Tool, TimeChart possesses the inherent cross-platform, responsive, and regularly maintained and supported advantages offered by Python Display Manager (PyDM). As a Python Qt-based framework, PyDM is also created and maintained by SLAC. Its charting capability is built upon pyqtgraph, and the PyDM's TimePlot is the central widget in TimeChart.", + "laborHours": 0.0, + "languages": [], + "name": "TimeChart", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/timechart/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/timechart", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TimeToolFlow.json b/agency-indexes/DoE/TimeToolFlow.json new file mode 100644 index 00000000..da7c61d4 --- /dev/null +++ b/agency-indexes/DoE/TimeToolFlow.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-01", + "metadataLastUpdated": "2022-09-01" + }, + "description": "Deep learning for time-tool readouts.", + "laborHours": 0.0, + "languages": [], + "name": "TimeToolFlow", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/TimeToolFlow", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Time_Domain_Moment_Tensor_Inversion_in_Python.json b/agency-indexes/DoE/Time_Domain_Moment_Tensor_Inversion_in_Python.json new file mode 100644 index 00000000..473a8e59 --- /dev/null +++ b/agency-indexes/DoE/Time_Domain_Moment_Tensor_Inversion_in_Python.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2020-03-03", + "metadataLastUpdated": "2022-07-28" + }, + "description": "MTtime is a software tool developed for time domain inversion of complete seismic waveform data to obtain the seismic moment tensor. It supports both deviatoric and full moment tensor inversions as well as 1-D and 3-D basis Green's functions.", + "laborHours": 0.0, + "languages": [], + "name": "Time Domain Moment Tensor Inversion in Python", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mttime", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Time_Ordered_Astrophysics_Scalable_Tools.json b/agency-indexes/DoE/Time_Ordered_Astrophysics_Scalable_Tools.json new file mode 100644 index 00000000..daf0f468 --- /dev/null +++ b/agency-indexes/DoE/Time_Ordered_Astrophysics_Scalable_Tools.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "This software package provides tools for astrophysical experiments which record data in the form of individual time streams from discrete detectors. TOAST provides tools from meta-data manipulation and job set up, I/O operation, telescope pointing reconstruction, and map-making. It also provides tools for constructing simulated observations.", + "laborHours": 0.0, + "languages": [ + "Any Standard C++ complier which supports the BOOST software package" + ], + "name": "Time Ordered Astrophysics Scalable Tools", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/tskisner/toast/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tskisner/TOAST", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Time_Resolved_Phonon_Spectroscopy,_Version_1.0.json b/agency-indexes/DoE/Time_Resolved_Phonon_Spectroscopy,_Version_1.0.json new file mode 100644 index 00000000..29e8fc93 --- /dev/null +++ b/agency-indexes/DoE/Time_Resolved_Phonon_Spectroscopy,_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-12-13" + }, + "description": "TRPS code was developed for the project \"Time Resolved Phonon Spectroscopy\". Routines contained in this piece of software were specially created to model phonon generation and tracking within materials that interact with ionizing radiation, particularly applicable to the modeling of cryogenic radiation detectors for dark matter and neutrino research. These routines were created to link seamlessly with the open source Geant4 framework for the modeling of radiation transport in matter, with the explicit intent of open sourcing them for eventual integration into that code base.", + "laborHours": 1124.8, + "name": "Time Resolved Phonon Spectroscopy, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/goett/TRPS/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/goett/TRPS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Time_Series_Fortran_90_Modules.json b/agency-indexes/DoE/Time_Series_Fortran_90_Modules.json new file mode 100644 index 00000000..75a2a410 --- /dev/null +++ b/agency-indexes/DoE/Time_Series_Fortran_90_Modules.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This provides several Fortran for consistent handling of time series data. These are used by PNNL's\u00a0MASS1\u00a0and MASS2 codes.", + "laborHours": 2994.4, + "languages": [], + "name": "Time Series Fortran 90 Modules", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/time_series/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/time_series", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tomcat,_Oracle_&_XML_Web_Archive.json b/agency-indexes/DoE/Tomcat,_Oracle_&_XML_Web_Archive.json new file mode 100644 index 00000000..911936e9 --- /dev/null +++ b/agency-indexes/DoE/Tomcat,_Oracle_&_XML_Web_Archive.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The TOX (Tomcat Oracle & XML) web archive is a foundation for development of HTTP-based applications using Tomcat (or some other servlet container) and an Oracle RDBMS. Use of TOX requires coding primarily in PL/SQL, JavaScript, and XSLT, but also in HTML, CSS and potentially Java. Coded in Java and PL/SQL itself, TOX provides the foundation for more complex applications to be built.", + "laborHours": 714.4, + "name": "Tomcat, Oracle & XML Web Archive", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/tox", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tomo2Mesh:_Fast_Reconstruction_and_Visualization_of_Tomography_Data_in_Mesh_Format.json b/agency-indexes/DoE/Tomo2Mesh:_Fast_Reconstruction_and_Visualization_of_Tomography_Data_in_Mesh_Format.json new file mode 100644 index 00000000..f08022e4 --- /dev/null +++ b/agency-indexes/DoE/Tomo2Mesh:_Fast_Reconstruction_and_Visualization_of_Tomography_Data_in_Mesh_Format.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-08-03", + "metadataLastUpdated": "2022-08-03" + }, + "description": "Tomo2Mesh is an open-source project targeted towards real-time reconstruction, segmentation, and visualization of computed tomography (CT) data in mesh format. The CT reconstruction scheme is based on filtered back-projection of voxel subsets. The segmentation scheme uses a 3D convolutional neural network. To allow for fast, real-time reconstruction, voxel subsets are first identified by coarse reconstruction. The detail in specific regions of interest is improved through full reconstruction of voxel subsets in that region. Data structures are implemented to store and process voxel subsets. Finally, voxel data is labeled using connected components to detect disconnected regions such as voids whose morphological attributes (e.g., Feret diameter, principal axis orientation, local number density, size, etc.) can be measured also in real-time. Finally, a fast marching cubes implementation processes labeled voxel data into a triangular face mesh (vertices and faces) in .ply format for visualization in Paraview or other mesh visualization tools. The code provides a simple programming interface for detecting, classifying, and visualizing regions of interest based on morphology. For example, detected voids can be classified as round pores or extended cracks. Highly porous neighborhoods can be identified based on local number density. The mesh texture (or color) is assigned based these morphological attributes to allow smart visualization scenarios in real-time (e.g., show only long cracks). At the time of first release (July 2022), extraction of face mesh for visualization for raw CT data from a 2 megapixel camera would take between 1-5 minutes for most scenarios.", + "laborHours": 0.0, + "languages": [], + "name": "Tomo2Mesh: Fast Reconstruction and Visualization of Tomography Data in Mesh Format", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aniketkt/Tomo2Mesh", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TomoEncoders:_3D_Autoencoders_for_feature_extraction_in_X-ray_tomography.json b/agency-indexes/DoE/TomoEncoders:_3D_Autoencoders_for_feature_extraction_in_X-ray_tomography.json new file mode 100644 index 00000000..e13a8010 --- /dev/null +++ b/agency-indexes/DoE/TomoEncoders:_3D_Autoencoders_for_feature_extraction_in_X-ray_tomography.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-18" + }, + "description": "Real-time steering of time-resolved or in-situ X-ray tomography requires capturing changes in morphological descriptors in a sample (e.g., porosity, particle size, and crack width) during continuous data acquisition. Image segmentation (2D or3D) followed by quantitative measurement is the conventional method for tracking changes in these descriptors with respect to a previous time-step or a 3D search in a volume. However, image segmentation is expensive. As a faster and unsupervised alternative, a feature-extraction approach using a convolutional autoencoders was developed, where the latent space of the encoder responds to relative changes in morphology with-out prior knowledge of the morphological descriptors.", + "laborHours": 0.0, + "languages": [], + "name": "TomoEncoders: 3D Autoencoders for feature extraction in X-ray tomography", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aniketkt/TomoEncoders", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TomoTwin:_A_simple_digital_twin_for_synchrotron_tomography.json b/agency-indexes/DoE/TomoTwin:_A_simple_digital_twin_for_synchrotron_tomography.json new file mode 100644 index 00000000..d6fcd301 --- /dev/null +++ b/agency-indexes/DoE/TomoTwin:_A_simple_digital_twin_for_synchrotron_tomography.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-18" + }, + "description": "A digital twin for synchrotron-based tomography for generating synthetic datasets from ground-truth phantoms. The code outputs greyscale projection images / tomographic volumes with realistic artifacts such as noise and phase-contrast and emulates their dependence on the acquisition parameters defining the beam and detector configuration. Some ground-truth phantoms are included with the code.", + "laborHours": 0.0, + "languages": [], + "name": "TomoTwin: A simple digital twin for synchrotron tomography", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aniketkt/TomoTwin", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tomopy:_A_Python_toolbox_to_perform_X-Ray_data_proessing_and_image_reconstruction..json b/agency-indexes/DoE/Tomopy:_A_Python_toolbox_to_perform_X-Ray_data_proessing_and_image_reconstruction..json new file mode 100644 index 00000000..8387b5f0 --- /dev/null +++ b/agency-indexes/DoE/Tomopy:_A_Python_toolbox_to_perform_X-Ray_data_proessing_and_image_reconstruction..json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Tomopy is a Python toolbox to perform x-ray data processing, image reconstruction and data exchange tasks at synchrotron facilities. The dependencies of the software are currently as follows: -Python related python standard library (http://docs.python.org/2/library/) numpy (http://www.numpy.org/) scipy (http://scipy.org/) matplotlib (http://matplotlip.org/) sphinx (http://sphinx-doc.org) pil (http://www.pythonware.com/products/pil/) pyhdf (http://pysclint.sourceforge.net/pyhdf/) h5py (http://www.h5py.org) pywt (http://www.pybytes.com/pywavelets/) file.py (https://pyspec.svn.sourceforge.net/svnroot/pyspec/trunk/pyspec/ccd/files.py) -C/C++ related: gridec (anonymous?? C-code written back in 1997 that uses standard C library) fftw (http://www.fftw.org/) tomoRecon (multi-threaded C++ verion of gridrec. Author: Mark Rivers from APS. http://cars9.uchicago.edu/software/epics/tomoRecon.html) epics (http://www.aps.anl.gov/epics/)", + "laborHours": 9986.4, + "name": "Tomopy: A Python toolbox to perform X-Ray data proessing and image reconstruction.", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/tomopy/tomopy/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tomopy/tomopy", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tool_Gear_Version_2.3.json b/agency-indexes/DoE/Tool_Gear_Version_2.3.json new file mode 100644 index 00000000..f7476de9 --- /dev/null +++ b/agency-indexes/DoE/Tool_Gear_Version_2.3.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Tool Gear Version 2 is an expanded collection of programs and software libraries that form the infrastructure on which software tools may be built. The software tools help application developers understand the performance of the programs or help them find programming errors. Tool Gear includes components for gathering data from target programs, either through direct instrumentations or by parsing the output of third-party tools, transmitting the data to a database, organizing and storing the data, presenting it through a variety of graphical interfaces. Tool Gear is designed to be an extensible system, so users can manage a variety of data and create new ways to present it. Tool Gear is designed to work with both sequential and parallel programs on multiple computer platforms", + "laborHours": 0.0, + "languages": [], + "name": "Tool Gear Version 2.3", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/tool-gear-version-2.3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Toolkit_for_Integrated_Impact_Assessments_version_1.0.json b/agency-indexes/DoE/Toolkit_for_Integrated_Impact_Assessments_version_1.0.json new file mode 100644 index 00000000..227cbd58 --- /dev/null +++ b/agency-indexes/DoE/Toolkit_for_Integrated_Impact_Assessments_version_1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-08" + }, + "description": "TIIA is designed to perform ecological and human risk assessments for environmental contaminants in air, water, soil, and sediment. It uses a novel approach that applies to radionuclides and hazardous chemicals, based on a food web approach. Stochastic calculations (i.e., those that allow for propagation of uncertainty in a numerical fashion) are allowed.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Toolkit for Integrated Impact Assessments version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tools_for_analysis_of_optimization_models.json b/agency-indexes/DoE/Tools_for_analysis_of_optimization_models.json new file mode 100644 index 00000000..10d0370f --- /dev/null +++ b/agency-indexes/DoE/Tools_for_analysis_of_optimization_models.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-04-26", + "metadataLastUpdated": "2023-04-26" + }, + "description": "The software is code for analyzing, debugging, and solving optimization models. The code implements several algorithms and provides convenient APIs to apply these algorithms to optimization models. The algorithms are primarily based on graph theory. They compute well-known partitions of graphs, and use these partitions to provide the user information about their optimization model, including diagnosing certain types of structural modeling errors. Some algorithms may be used as a subroutine to solve an optimization problem, and may call an optimization solver to facilitate this. Well-known linear algebra routines are called to provide further diagnostics. The software contains no data and no models other than toy models used for testing.", + "laborHours": 0.0, + "languages": [], + "name": "Tools for analysis of optimization models", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-ansi/JuMPIn.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Tools_to_perform_data_reduction_of_time-of-flight_data_taken_on_BL4A__MagRef_\342\200\224a_Jupyter_notebook_approach_.json" "b/agency-indexes/DoE/Tools_to_perform_data_reduction_of_time-of-flight_data_taken_on_BL4A__MagRef_\342\200\224a_Jupyter_notebook_approach_.json" new file mode 100644 index 00000000..84a80c97 --- /dev/null +++ "b/agency-indexes/DoE/Tools_to_perform_data_reduction_of_time-of-flight_data_taken_on_BL4A__MagRef_\342\200\224a_Jupyter_notebook_approach_.json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "fitzsimmonsm@ornl.gov" + }, + "date": { + "created": "2020-07-31", + "metadataLastUpdated": "2020-07-31" + }, + "description": "A collection of modules or tools to produce reflectivity profiles from data acquired with unpolarized and polarized neutron beams using the BL4A (MagRef) instrument at the Spallation Neutron Source.\n\nThe Jupyter notebook approach offers transparency to the user on what is done with the data, and once the event mode data are stored as NumPy binary files empowers the user to perform the steps from their own laptop without the need for Mantid. The notebook offers two options for background subtraction, applies corrections for the wavelength dependence of the polarizer and flipper efficiencies, accounts for Zeeman energy splitting of the spin-flip channels, Qz-bins the data along contours of constant Qz, propagates errors and writes results in text format suitable for analysis with tools such as GenX.", + "laborHours": 1687.2, + "languages": [ + "Python" + ], + "name": "Tools to perform data reduction of time-of-flight data taken on BL4A (MagRef)\u2014a Jupyter notebook approach ", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfitzsimmons44/BL4A_MagRef_Data_Reduction_Tools", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TopN-Pareto_Front_Search.json b/agency-indexes/DoE/TopN-Pareto_Front_Search.json new file mode 100644 index 00000000..bc9f0f65 --- /dev/null +++ b/agency-indexes/DoE/TopN-Pareto_Front_Search.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The JMP Add-In TopN-PFS provides an automated tool for finding layered Pareto front to identify the top N solutions from an enumerated list of candidates subject to optimizing multiple criteria. The approach constructs the N layers of Pareto fronts, and then provides a suite of graphical tools to explore the alternatives based on different prioritizations of the criteria. The tool is designed to provide a set of alternatives from which the decision-maker can select the best option for their study goals.", + "laborHours": 0.0, + "name": "TopN-Pareto Front Search", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/candcook/TopN-PFS/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/candcook/TopN-PFS", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Topness,_Version_1.json b/agency-indexes/DoE/Topness,_Version_1.json new file mode 100644 index 00000000..38a9923d --- /dev/null +++ b/agency-indexes/DoE/Topness,_Version_1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The code would be used in analyses of data from the LHC, to improve the sensitivity of their experiments to new exotic particles. The software minimizes a certain function, as defined in the above reference, for some input provided by the user. The output to the user is the global minimum of that function. The code finds the global minimum using the Nelder-Mead algorithm. All the codes for the minimization including the Nelder-Mead algorithm, is written by the author. The software is written in c++.", + "laborHours": 0.0, + "name": "Topness, Version 1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/michaelgraesser/topness/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/michaelgraesser/topness", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TopoMS,_Version_1.0.json b/agency-indexes/DoE/TopoMS,_Version_1.0.json new file mode 100644 index 00000000..aa914151 --- /dev/null +++ b/agency-indexes/DoE/TopoMS,_Version_1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "TopoMS Is an analysis tool for molecular and condensed-matter systems. It can be used for Bader analysis, study of charge transfer, bond detection, and computation of complete molecular graph.", + "laborHours": 23286.4, + "languages": [ + "C++" + ], + "name": "TopoMS, Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/TopoMS/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TopoMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TopoMS-UI.json b/agency-indexes/DoE/TopoMS-UI.json new file mode 100644 index 00000000..12f96df0 --- /dev/null +++ b/agency-indexes/DoE/TopoMS-UI.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "\"TopoMS\" is a visualization and analysis tool developed to enable interactive exploration of molecular systems, allowing the users perform Bader analysis as well as detailed analysis of molecular graph in complex systems.", + "laborHours": 23286.4, + "languages": [ + "C++" + ], + "name": "TopoMS-UI", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TopoMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Topographical_Risk_Assessment.json b/agency-indexes/DoE/Topographical_Risk_Assessment.json new file mode 100644 index 00000000..02987599 --- /dev/null +++ b/agency-indexes/DoE/Topographical_Risk_Assessment.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "TRA was developed as a computer tool for the DOE Office of River Protection (ORP) that will provides the capability to visualize and rapidly understand information about the risks associated with the River protection Project (RPP). Previously, technical and programmatic risk management within ORP had relied heavily on risk lists and other techniques that presented risk information but did not place it in perspective of the overall project. This made it difficult for ORP senior management to understand the risk information presented, prioritize their activities, and provide direction to ORP staff and contractors about how to manage specific risk events. The TRA visualization tool, provides the appropriate context and perspective that allows senior management to effectively manage risks. Basically, the TRA overlays information about risks associated with specific activities and their magnitudes on top of the project baseline schedule. this provides senior management with information about the magnitudes of specific risk events as well as their timing, and allows them to focus their attention and resources on the risks that merit attention and possible further action. The TRA tool can also be used to display other types of information associated with scheduled activities, such as cost to date, technical performance, schedule performance, etc. Additionally, the base of the 3-dimensional representation can be changed to other types of graphics, such as maps, process flow diagrams, etc., which allows the display of other types of information, such as hazards, health and safety risks, and system availability.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Topographical Risk Assessment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Topology-aware_task-assIGnment_mappER__TIGER__v0.1.json b/agency-indexes/DoE/Topology-aware_task-assIGnment_mappER__TIGER__v0.1.json new file mode 100644 index 00000000..07a2ecbd --- /dev/null +++ b/agency-indexes/DoE/Topology-aware_task-assIGnment_mappER__TIGER__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-07-03", + "metadataLastUpdated": "2019-07-03" + }, + "description": "The general topology-aware task assignment problem is an NP-complete graph isomorphism problem. Existing task scheduling approaches are either heuristic or based on physical optimization algorithms, providing different speed and solution quality trade-offs. Physical Ising machines such as quantum and digital annealers have recently become available offering an alternative hardware solution to solve certain types of optimization problems. We propose an algorithm that allows expressing the problem in the compatible format. We present a domain specific partition strategy that enables to execute larger scale problems. TIGER - topology-aware task assignment mapper tool - implements the proposed algorithm and automatically integrates task- communication graph and an architecture graph into the quantum software environment.", + "laborHours": 380.0, + "languages": [], + "name": "Topology-aware task-assIGnment mappER (TIGER) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnlcomputerarch/tiger", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Topology_Generator.json b/agency-indexes/DoE/Topology_Generator.json new file mode 100644 index 00000000..28e9094b --- /dev/null +++ b/agency-indexes/DoE/Topology_Generator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-04-24", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The ns-3 topology generator provides a quick and easy way to create a network topology, and generate C++ simulation code for ns-3.", + "laborHours": 3116.0, + "languages": [], + "name": "Topology_Generator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Topology_Generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Topology_Optimization_for_Full-Cell_Electrochemical_Energy_Storage_Device.json b/agency-indexes/DoE/Topology_Optimization_for_Full-Cell_Electrochemical_Energy_Storage_Device.json new file mode 100644 index 00000000..eb5c55c1 --- /dev/null +++ b/agency-indexes/DoE/Topology_Optimization_for_Full-Cell_Electrochemical_Energy_Storage_Device.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-31", + "metadataLastUpdated": "2025-03-31" + }, + "description": "This code is used to conduct topology optimization of a general full cell energy storage device. The anode\nand cathode designs are optimized simultaneously, allowing possibility for interdigitation. The charging\nmechanism can consist of both electric double layer charging (EDLC) typically observed in capacitors and\nredox reaction typically observed in batteries.", + "laborHours": 942.4, + "languages": [], + "name": "Topology Optimization for Full-Cell Electrochemical Energy Storage Device", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TOPEFC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Topology_Optimization_for_Porous_Electrodes.json b/agency-indexes/DoE/Topology_Optimization_for_Porous_Electrodes.json new file mode 100644 index 00000000..20a1e609 --- /dev/null +++ b/agency-indexes/DoE/Topology_Optimization_for_Porous_Electrodes.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-03-21", + "metadataLastUpdated": "2022-04-08" + }, + "description": "This code is for the topology optimization of porous electrodes. It was used to produce the results in Roy, T., Salazar de Troya, M.A., Worsley, M.A. and Beck, V.A., 2021. Topology optimization for the design of porous electrodes. arXiv preprint arXiv:2111.12059.", + "laborHours": 0.0, + "languages": [], + "name": "Topology Optimization for Porous Electrodes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TOPE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Topology_Reconfiguration_and_distributed_Volt_Var_Control__TR-dVVC__v1.json b/agency-indexes/DoE/Topology_Reconfiguration_and_distributed_Volt_Var_Control__TR-dVVC__v1.json new file mode 100644 index 00000000..ed985fdd --- /dev/null +++ b/agency-indexes/DoE/Topology_Reconfiguration_and_distributed_Volt_Var_Control__TR-dVVC__v1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-09-19", + "metadataLastUpdated": "2019-10-01" + }, + "description": "Topology Reconfiguation is a simple algorithm to choose a network configuration with the least losses in a system with high penetration of renewable energy. It uses a linearized optimal power flow algorithm to identify the optimal setpoints of PV in a system, then performs an exhaustive search of switch configurations to find the loss minimizing solution, it repeats this process until convergence. At the end, the operator has a switch schedule for a 24 hour period that should minimize losses. VVC is a distributed algorithm in which PV units drive voltage at points within the network to 1 per unit through reactive power control. The VVC algorithm relies on extremum seeking control to provide the control. The software package is a simulation of VVC on a standard IEEE 34 bus three phase network.", + "laborHours": 1231.2, + "languages": [], + "name": "Topology Reconfiguration and distributed Volt Var Control (TR-dVVC) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/jsmacdonald/tr-dvvc_energise/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TorchBraid.json b/agency-indexes/DoE/TorchBraid.json new file mode 100644 index 00000000..d28fe061 --- /dev/null +++ b/agency-indexes/DoE/TorchBraid.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-04" + }, + "description": "Torchbraid is a python package designed for interaction with the PyTorch library. It enables training of neural networks in a layer-parallel fashion.SAND2020-12228 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 972.8, + "languages": [ + "Python" + ], + "name": "TorchBraid", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TowerSE.json b/agency-indexes/DoE/TowerSE.json new file mode 100644 index 00000000..b9bfe96b --- /dev/null +++ b/agency-indexes/DoE/TowerSE.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A module for static aerodynamic and structural analysis of wind turbine towers", + "laborHours": 2219.2, + "name": "TowerSE", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/towerse", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ToyProblem-EthyleneOx.json b/agency-indexes/DoE/ToyProblem-EthyleneOx.json new file mode 100644 index 00000000..5b8278c8 --- /dev/null +++ b/agency-indexes/DoE/ToyProblem-EthyleneOx.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-10-20", + "metadataLastUpdated": "2023-10-20" + }, + "description": "This is a toy problem intended as an example on which to test V/UQ tools for multi-physics problems (coupled sub-models). It has grown from the solution to a graduate-school homework problem that has been posted on open-source (https://github.com/PhilipSmith-Canada/EthyleneOxideHomeWork).", + "laborHours": 0.0, + "languages": [], + "name": "ToyProblem-EthyleneOx", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/smith-LANL/ToyProblem-EthyleneOx", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tpetra_Next-Generation_Templated_Petra_V1.0.json b/agency-indexes/DoE/Tpetra_Next-Generation_Templated_Petra_V1.0.json new file mode 100644 index 00000000..9a7f29f0 --- /dev/null +++ b/agency-indexes/DoE/Tpetra_Next-Generation_Templated_Petra_V1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A package of classes for constructing and using distributed sparse and dense matries, vectors and graphs. Templated o the scalar and ordinal types so that any valid floating-point type, as well as any valid integer type can be used with these classes. Other non-standard types, such as 3-by-3 matrices for the scalar type and mod-based integers for ordinal can also be used.", + "laborHours": 8344830.4, + "name": "Tpetra Next-Generation Templated Petra V1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/tpetra/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TraVerSE:_Trajectory_Veracity_for_Simple_Errors.json b/agency-indexes/DoE/TraVerSE:_Trajectory_Veracity_for_Simple_Errors.json new file mode 100644 index 00000000..a866764c --- /dev/null +++ b/agency-indexes/DoE/TraVerSE:_Trajectory_Veracity_for_Simple_Errors.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-05-06", + "metadataLastUpdated": "2019-10-04" + }, + "description": "This package is a set of tools in the Python language for preprocessing GPS trajectory data gathered from consumer devices, to detect and flag potentially erroneous data.", + "laborHours": 1048.8, + "languages": [], + "name": "TraVerSE: Trajectory Veracity for Simple Errors", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/bgerke/traverse", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trace_Crawler_SOFTWARE.json b/agency-indexes/DoE/Trace_Crawler_SOFTWARE.json new file mode 100644 index 00000000..12dd769e --- /dev/null +++ b/agency-indexes/DoE/Trace_Crawler_SOFTWARE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-06-15", + "metadataLastUpdated": "2022-06-15" + }, + "description": "The trace crawler is a tool for selective web crawling to archive web resources with well-defined boundaries. The specific web navigation steps (or trace) are formulated for the families of webpages, where layout or HTML structure can be similar but the content is different, for example, GitHub, Slideshare, blogs, etc. The trace is recorded in a json file format.", + "laborHours": 0.0, + "languages": [], + "name": "Trace Crawler SOFTWARE", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/trace-crawler", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trace_Replay_and_Network_Simulation_Tool.json b/agency-indexes/DoE/Trace_Replay_and_Network_Simulation_Tool.json new file mode 100644 index 00000000..d30439ff --- /dev/null +++ b/agency-indexes/DoE/Trace_Replay_and_Network_Simulation_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "TraceR Is a trace replay tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performance and understanding network behavior by simulating messaging In High Performance Computing applications on interconnection networks.", + "laborHours": 4803.2, + "languages": [ + "C++" + ], + "name": "Trace Replay and Network Simulation Tool", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpcgroup/TraceR", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TrackTable_Trajectory_Analysis.json b/agency-indexes/DoE/TrackTable_Trajectory_Analysis.json new file mode 100644 index 00000000..1f108ba2 --- /dev/null +++ b/agency-indexes/DoE/TrackTable_Trajectory_Analysis.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-26" + }, + "description": "Tracktable is designed for analysis and rendering of the trajectories of moving objects such as planes, trains, automobiles and ships. Its purpose is to operate on large sets of trajectories (millions) to help a user detect, analyze and display patterns. It will also be used to disseminate trajectory research results from Sandia's PANTHER Grand Challenge LDRD.", + "laborHours": 0.0, + "languages": [ + "C++", + "Shell", + "C", + "Jupyter Notebook", + "CMake", + "Python" + ], + "name": "TrackTable Trajectory Analysis", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tracktable", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tracking_as_a_Service.json b/agency-indexes/DoE/Tracking_as_a_Service.json new file mode 100644 index 00000000..1c6b204d --- /dev/null +++ b/agency-indexes/DoE/Tracking_as_a_Service.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "xju@lbl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "This repository contains a set of Tracking models that can be used as a service.", + "laborHours": 562.4, + "languages": [ + "Python" + ], + "name": "Tracking as a Service", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xju2/tracking-as-a-service/releases/tag/v1.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tracknodes.json b/agency-indexes/DoE/Tracknodes.json new file mode 100644 index 00000000..af6d6c96 --- /dev/null +++ b/agency-indexes/DoE/Tracknodes.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "Tracknodes keeps a history of node state and comment changes. It allows system administrators of HPC systems to determine when nodes were down and discover trends such as recurring issues. Supports Torque, PBSpro and has limited support for SLURM.\n", + "laborHours": 486.4, + "languages": [], + "name": "Tracknodes", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/tracknodes", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tracktable_.json b/agency-indexes/DoE/Tracktable_.json new file mode 100644 index 00000000..b68e8137 --- /dev/null +++ b/agency-indexes/DoE/Tracktable_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-01-22", + "metadataLastUpdated": "2021-01-22" + }, + "description": "Tracktable is a toolkit for analysis and visualization of the trajectories of moving objects. Its main focus is on air and sea traffic. It can also work with more abstract trajectories such as eye tracking data. We supply a set of core data structures, input/output routines, math and machine learning algorithms that operate on those data structures, and visualization algorithms to produce movies and still images of the results.\n", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Tracktable ", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/tracktable", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tracktable", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1 (Alpha)" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Training_Data_Regarding_Optimal_Power_Flow_For_Efficient_Machine_Learning.json b/agency-indexes/DoE/Training_Data_Regarding_Optimal_Power_Flow_For_Efficient_Machine_Learning.json new file mode 100644 index 00000000..5e5bbc5b --- /dev/null +++ b/agency-indexes/DoE/Training_Data_Regarding_Optimal_Power_Flow_For_Efficient_Machine_Learning.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-05-18", + "metadataLastUpdated": "2023-05-18" + }, + "description": "The code is intended to take the data outputted by the MATPOWER OPF solver tools and restructures the data in a way that is best suited for machine learning. The variables are read and the desired values are taken and added to an array in the correct format. This array is then converted into a python array for future use. The code also utilizes MATPOWER's ability to construct different power flow scenarios and repeat them a chosen number of times. Each iteration will add a new line to the formatted array so that the final output is a matrix has a height equal to the number of repetition used.", + "laborHours": 0.0, + "languages": [ + "Matlab Programming Language" + ], + "name": "Training Data Regarding Optimal Power Flow For Efficient Machine Learning", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/TROPFE", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trajectory_Balance_with_Asynchrony.json b/agency-indexes/DoE/Trajectory_Balance_with_Asynchrony.json new file mode 100644 index 00000000..66a754b8 --- /dev/null +++ b/agency-indexes/DoE/Trajectory_Balance_with_Asynchrony.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-04-10", + "metadataLastUpdated": "2025-04-10" + }, + "description": "Finetune large language models (LLMs) quicker via parallelization. Specifically, this implements\nasynchronous reinforcement learning with a trajectory balance objective function", + "laborHours": 1596.0, + "languages": [], + "name": "Trajectory Balance with Asynchrony", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bbartoldson/TBA", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tramonto.json b/agency-indexes/DoE/Tramonto.json new file mode 100644 index 00000000..fc2aafc2 --- /dev/null +++ b/agency-indexes/DoE/Tramonto.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "Tramonto is a code for performing molecular theory calculations using a matrix-based Newton's method approach for 1D, 2D, and 3D geometries. More specifically the code solves the integral equations of a particular class of liquid state theory namely density functional theories (DFT) of inhomogeneous fluids in order to predict the structure and thermodynamic properties of fluids near surfaces, in porous media, or near macromolecules. It can also be used to study self-assembling systems such as lamellae forming diblock copolymers or lipid bilayers. The types of fluids currently treated by the code include atomistic fluids (hard spheres, Lennard-Jones, ions, etc), freely-jointed polymers, and small molecules with bond constraints. The system of equations solved by this code are integral equations of finite range. They lead to sparse matrices for large physical systems, but rather dense matrices when the physical systems are small. The systems of equations are solved using a real space matrix based Newton's method. Standard freely available parallel iterative solvers many be used to solve the problem (see Aztecoo from Sandia's Trilinos project). Alternatively, specialized Schur complement based solvers developed for more efficient solution of these semi-dense matrices may be used.", + "laborHours": 46876.8, + "languages": [ + "C++", + "C", + "CMake", + "Python" + ], + "name": "Tramonto", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tramonto", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TransPlatformer.json b/agency-indexes/DoE/TransPlatformer.json new file mode 100644 index 00000000..88be7deb --- /dev/null +++ b/agency-indexes/DoE/TransPlatformer.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "congg@ornl.gov" + }, + "date": { + "created": "2025-03-17", + "metadataLastUpdated": "2025-03-17" + }, + "description": "We propose TransPlatformer for translating toxicogenomics from one platform to another. Transcriptomic profiling has evolved through multiple generations of technology, from microarrays (e.g., Affymetrix, CodeLink) to more recent high-throughput sequencing and targeted panels such as S1500+. Microarrays, which dominated gene expression studies in the early 2000s, provided affordable and high-throughput transcript quantification but suffered from cross-hybridization issues and limited dynamic range . RNA-Seq, introduced in the late 2000s, revolutionized transcriptomics by enabling unbiased and comprehensive gene expression analysis, albeit at higher costs and computational demands .\n\nDespite advances, many studies rely on historical microarray data, necessitating the translation of legacy data into modern platforms to ensure continuity and comparability. This translation is complicated by factors such as platform-specific probe design, differences in transcript coverage, and batch effects . Existing methods for cross-platform mapping include statistical normalization, machine learning models, and biological anchoring approaches.\n\nThe ability to translate transcriptomic data between platforms has broad implications, including enhanced meta-analyses, improved toxicological modeling, and better integration of historical datasets with contemporary research. TransPlatformer seeks to contribute to this effort by evaluating translation methodologies and proposing novel strategies to improve cross-platform gene expression harmonization.\n\nIn this repository there are code examples for TransPlatformer implementation", + "laborHours": 592.8, + "languages": [ + "Python" + ], + "name": "TransPlatformer", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/goooopy/TransPlatformer", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Transactive_Energy_Service_System__TESS_.json b/agency-indexes/DoE/Transactive_Energy_Service_System__TESS_.json new file mode 100644 index 00000000..5dc5393d --- /dev/null +++ b/agency-indexes/DoE/Transactive_Energy_Service_System__TESS_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-07", + "metadataLastUpdated": "2022-09-07" + }, + "description": "The Transactive Energy Service System (TESS) is a platform to design, deploy, and operate transactive energy systems in electric utility retail environments. TESS provides retail market clearing mechanisms for peer-to-peer trading of behind-the-meter distributed energy resources based on ramping, capacity, and storage prices.", + "laborHours": 0.0, + "languages": [], + "name": "Transactive Energy Service System (TESS)", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/TESS", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Transactive_Energy_Simulation_Platform.json b/agency-indexes/DoE/Transactive_Energy_Simulation_Platform.json new file mode 100644 index 00000000..0bf039fa --- /dev/null +++ b/agency-indexes/DoE/Transactive_Energy_Simulation_Platform.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2022-11-18" + }, + "description": "Transactive Energy Simulation Platform (TESP) combines existing domain simulators in the electric power grid, buildings, and communication systems, with new transactive agents, growth models and evaluation scripts. The existing domain simulators include GridLAB-D for the distribution grid and single-family residential buildings, MATPOWER for transmission and bulk generation, EnergyPlus for large buildings and ns-3 for communication systems. More are planned for subsequent versions of TESP. The new elements are: TEAgents - simulate market participants and transactive systems for market clearing. Some of this functionality was extracted from GridLAB-D and implemented in Python for customization by PNNL and others. Growth Model - a means for simulating system changes over a multiyear period, including both normal load growth and specific investment decisions. Customizable in Python code. Evaluation Script - a means of evaluating different transactive systems through customizable post-processing in Python code. TESP will run on Linux, Windows and Mac OS X.", + "laborHours": 46892.0, + "languages": [], + "name": "Transactive Energy Simulation Platform", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/tesp", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Transformer_eXplainability_and_eXploration.json b/agency-indexes/DoE/Transformer_eXplainability_and_eXploration.json new file mode 100644 index 00000000..588c4b01 --- /dev/null +++ b/agency-indexes/DoE/Transformer_eXplainability_and_eXploration.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "stewartsl@ornl.gov" + }, + "date": { + "created": "2021-01-29", + "metadataLastUpdated": "2022-02-08" + }, + "description": "The Transformer eXplainability and eXploration library is intended to aid in the explorability and explainability of transformer classification networks, or transformer language models with sequence classification heads. The basic function of this library is to take a trained transformer and test/train dataset and produce an ipywidget dashboard which can be displayed in a jupyter notebook or in jupyter lab.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Transformer eXplainability and eXploration", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/tx2", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Transmission_Planning_Analysis_Tool.json b/agency-indexes/DoE/Transmission_Planning_Analysis_Tool.json new file mode 100644 index 00000000..ddd30764 --- /dev/null +++ b/agency-indexes/DoE/Transmission_Planning_Analysis_Tool.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "Developed to solve specific problem: Assist transmission planning for regional transfers in interconnected power systems. This work was originated in a study for the U.S. Department of State, to recommend transmission reinforcements for the Central American regional system that interconnects 6 countries. Transmission planning analysis is currently performed by engineers with domain-specific and system-specific knowledge without a unique methodology. The software codes of this disclosure assists engineers by defining systematic analysis procedures to help identify weak points and make decisions on transmission planning of regional interconnected power systems. Transmission Planning Analysis Tool groups PSS/E results of multiple AC contingency analysis and voltage stability analysis and QV analysis of many scenarios of study and arrange them in a systematic way to aid power system planning engineers or transmission operators in effective decision-making process or in the offline study environment.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Matlab/ 7.11.0" + ], + "name": "Transmission Planning Analysis Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Transparent_Asynchronous_Zero-copy_Remote_I_O__TAZeR_.json b/agency-indexes/DoE/Transparent_Asynchronous_Zero-copy_Remote_I_O__TAZeR_.json new file mode 100644 index 00000000..85158cc4 --- /dev/null +++ b/agency-indexes/DoE/Transparent_Asynchronous_Zero-copy_Remote_I_O__TAZeR_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Transparent Asynchronous Zero-copy Remote I/O (TAZeR) is a framework built to facilitate grid computing by easing the memory movement and management across geographically separated computing resources. TAZeR employs a multiclient/\nmulti-server paradigm where data is stored at on a remote server. Users preload an interposing library which upon application start-up, stands up an ephemeral lightweight client. The client captures POSIX I/O calls to TAZeR meta-files which contains the IP address/port of the remote server, the location of the file on remote server, and additional meta-data.\nThe client connects to the server using this information and begins downloading the file in parts optionally compressing the data.", + "laborHours": 8648.8, + "languages": [], + "name": "Transparent Asynchronous Zero-copy Remote I/O (TAZeR)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/tazer", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Transport_Version_3.json b/agency-indexes/DoE/Transport_Version_3.json new file mode 100644 index 00000000..9fff314d --- /dev/null +++ b/agency-indexes/DoE/Transport_Version_3.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The Transport version 3 (T3) system uses the Network News Transfer Protocol (NNTP) to move data from sources to a Data Repository (DR). Interested recipients subscribe to newsgroups to retrieve data. Data in transport is protected by AES-256 and RSA cryptographic services provided by the external OpenSSL cryptographic libraries.", + "homepageURL": "https://svn.pnl.gov/transport", + "laborHours": 0.0, + "languages": [ + "Python and Perl" + ], + "name": "Transport Version 3", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://svn.pnl.gov/transport", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.pnl.gov/transport", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/TreeScope_Visualization_Tool_for_Fat-tree_Networks.json b/agency-indexes/DoE/TreeScope_Visualization_Tool_for_Fat-tree_Networks.json new file mode 100644 index 00000000..e3f8542e --- /dev/null +++ b/agency-indexes/DoE/TreeScope_Visualization_Tool_for_Fat-tree_Networks.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "TreeScope Is a visualization tool to view and analyze network traffic on fat-tree networks, e.g., on cab.", + "laborHours": 2219.2, + "languages": [ + "D3, JavaScript" + ], + "name": "TreeScope Visualization Tool for Fat-tree Networks", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/TreeScope", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TreeUtils.json b/agency-indexes/DoE/TreeUtils.json new file mode 100644 index 00000000..393994f3 --- /dev/null +++ b/agency-indexes/DoE/TreeUtils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "This is the repository for \"TreeUtils\" developed by KBase. A KBase module generated by the KBase SDK.", + "laborHours": 1276.8, + "languages": [], + "name": "TreeUtils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/TreeUtils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trees.json b/agency-indexes/DoE/Trees.json new file mode 100644 index 00000000..1a1ecc8f --- /dev/null +++ b/agency-indexes/DoE/Trees.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-17", + "metadataLastUpdated": "2023-11-17" + }, + "description": "The Trees program is a pre-processing tool used to virtually build forest fuel arrays to be read into FIRETEC, QUIC-Fire, or similar wildland fire related tool which requires the conversion of raw collected forest data to a digitalized voxelization of the fuels.", + "laborHours": 0.0, + "languages": [], + "name": "Trees", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Trees", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trestles.json b/agency-indexes/DoE/Trestles.json new file mode 100644 index 00000000..9fe71f9b --- /dev/null +++ b/agency-indexes/DoE/Trestles.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "kallander2@llnl.gov" + }, + "date": { + "created": "2023-02-07", + "metadataLastUpdated": "2023-02-17" + }, + "description": "Trestles is a modified H.264 decoder that allows access to the uncompressed transformed residual pixel and motion vector values that are contained (in compressed form) in the H.264 NAL units (a.k.a. video bitstream).", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Trestles", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/trestles", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TriBITS.json b/agency-indexes/DoE/TriBITS.json new file mode 100644 index 00000000..d46da915 --- /dev/null +++ b/agency-indexes/DoE/TriBITS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "The Tribal Build, Integrate, and Test System (TriBITS) is a framework designed to handle large software development projects involving multiple independent development teams and multiple source repositories which is built on top of the open-source CMake set of tools. TriBITS also defines a complete software development, testing, and deployment system supporting processes consistent with modern agile software development best practices.", + "laborHours": 82703.2, + "languages": [], + "name": "TriBITS", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/TriBITSPub/TriBITS/blob/master/tribits/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tribitspub/tribits", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TriBITS__Tribal_Build,_Integrate,_and_Test_System_.json b/agency-indexes/DoE/TriBITS__Tribal_Build,_Integrate,_and_Test_System_.json new file mode 100644 index 00000000..5586f54c --- /dev/null +++ b/agency-indexes/DoE/TriBITS__Tribal_Build,_Integrate,_and_Test_System_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "TriBITS is a configuration, build, test, and reporting system that uses the Kitware open-source CMake/CTest/CDash system. TriBITS contains a number of custom CMake/CTest scripts and python scripts that extend the functionality of the out-of-the-box CMake/CTest/CDash system.", + "laborHours": 8344830.4, + "name": "TriBITS (Tribal Build, Integrate, and Test System)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TriPoll.json b/agency-indexes/DoE/TriPoll.json new file mode 100644 index 00000000..d8fc6da1 --- /dev/null +++ b/agency-indexes/DoE/TriPoll.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-12-22", + "metadataLastUpdated": "2022-12-22" + }, + "description": "TriPoll is software to perform surveys of triangles within large graphs containing metadata. In TriPoll, users define their own callback functions that get executed on the metadata of each triangle within a\ngraph as triangles are identified. This functionality makes it possible for users to perform advanced analyses and gather statistics about specific classes of triangles of interest.", + "laborHours": 0.0, + "languages": [], + "name": "TriPoll", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/tripoll", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TriUtils_Trilinos_Utilities_Package.json b/agency-indexes/DoE/TriUtils_Trilinos_Utilities_Package.json new file mode 100644 index 00000000..afaa87f8 --- /dev/null +++ b/agency-indexes/DoE/TriUtils_Trilinos_Utilities_Package.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-19" + }, + "description": "TriUtils is a package of utilities for other Trilinos packages. TriUtils contains utilities to perform common operations such as command line parsing, and input file reading.", + "laborHours": 8344830.4, + "languages": [], + "name": "TriUtils Trilinos Utilities Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tribol_Interface_Physics_Library.json b/agency-indexes/DoE/Tribol_Interface_Physics_Library.json new file mode 100644 index 00000000..f962aeed --- /dev/null +++ b/agency-indexes/DoE/Tribol_Interface_Physics_Library.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-23", + "metadataLastUpdated": "2023-06-23" + }, + "description": "Tribol is a modular interface physics library featuring Lagrangian contact algorithms for explicit and implicit solid mechanics applications. More broadly, Tribol supports the research, development, and\nimplementation of numerical methods for interface physics.\n", + "laborHours": 0.0, + "languages": [], + "name": "Tribol Interface Physics Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Tribol", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trilinos.json b/agency-indexes/DoE/Trilinos.json new file mode 100644 index 00000000..cba30f1a --- /dev/null +++ b/agency-indexes/DoE/Trilinos.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2020-06-01" + }, + "description": "The Trilinos Project is an effort to develop algorithms and enabling technologies within an object-oriented software framework for the solution of large-scale, complex multi-physics engineering and scientific problems. ", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://trilinos.org/download/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trilinos_Anasazi.json b/agency-indexes/DoE/Trilinos_Anasazi.json new file mode 100644 index 00000000..b298aef7 --- /dev/null +++ b/agency-indexes/DoE/Trilinos_Anasazi.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-12" + }, + "description": "Anasazi is an extensible and interoperable framework for large-scale eigenvalue algorithms. Abstract interface supports Epetra and other linear algebra objects. To access the Anasazi package, please refer to the packages directory within the main Trilinos GitHub repository. \n\n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/Anasazi", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trilinos_AztecOO.json b/agency-indexes/DoE/Trilinos_AztecOO.json new file mode 100644 index 00000000..fc7eb202 --- /dev/null +++ b/agency-indexes/DoE/Trilinos_AztecOO.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-10", + "metadataLastUpdated": "2018-07-12" + }, + "description": "AztecOO provides an object-oriented interface the the well-known Aztec Krylov-space iterative solver library. Uses the Epetra linear algebra services to define vector and operator objects. To access the AztecOO package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/AztecOO", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/tree/master/packages/aztecoo", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trilinos_IFPACK.json b/agency-indexes/DoE/Trilinos_IFPACK.json new file mode 100644 index 00000000..bf8ca787 --- /dev/null +++ b/agency-indexes/DoE/Trilinos_IFPACK.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "IFPACK provides a suite of object-oriented algebraic preconditioners for the solution of preconditioned iterative solvers. To access the IFPACK package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/IFPACK", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/ifpack/Copyright.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trilinos_Isorropia.json b/agency-indexes/DoE/Trilinos_Isorropia.json new file mode 100644 index 00000000..bc912af8 --- /dev/null +++ b/agency-indexes/DoE/Trilinos_Isorropia.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "Isorropia performs combinatorial scientific computing, with focus on partitioning and load balancing, but also supports coloring and ordering of sparse matrices. Isorropia provides an object-oriented interface to Zoltan using the Epetra linear algebra services. To access the Isorropia package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/Isorropia", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://trilinos.org/download/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trilinos_LOCA.json b/agency-indexes/DoE/Trilinos_LOCA.json new file mode 100644 index 00000000..63035ec6 --- /dev/null +++ b/agency-indexes/DoE/Trilinos_LOCA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "LOCA is the Library of Continuation Algorithms, whose objective is to compute families of solutions to the parameterized nonlinear equation F(x,p) = 0 and their bifurcations. To access the LOCA package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/LOCA", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/nox/Copyright_LOCA.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trilinos_ML.json b/agency-indexes/DoE/Trilinos_ML.json new file mode 100644 index 00000000..cbfd6c19 --- /dev/null +++ b/agency-indexes/DoE/Trilinos_ML.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "ML is the Trilinos multigrid preconditioning package designed to solve large sparse linear systems of equations arising primarily from elliptic PDE discretizations. To access the ML package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/ML", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/ml/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trilinos_NOX.json b/agency-indexes/DoE/Trilinos_NOX.json new file mode 100644 index 00000000..f3de5569 --- /dev/null +++ b/agency-indexes/DoE/Trilinos_NOX.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "NOX is the Nonlinear Object-Oriented Solutions package of Trilinos, which enables the robust and efficient solution of the nonlinear equations of the form F(x) = 0. To access the NOX package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/NOX", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/nox/Copyright_NOX.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trilinos_Web_Interface_Package.json b/agency-indexes/DoE/Trilinos_Web_Interface_Package.json new file mode 100644 index 00000000..3c0380a1 --- /dev/null +++ b/agency-indexes/DoE/Trilinos_Web_Interface_Package.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "WebTrilinos is a scientific portal, a web-based environment to use several Trilinos packages through the web. If you are a teaching sparse linear algebra, you can use WebTrilinos to present code snippets and simple scripts, and let the students execute them from their browsers. If you want to test linear algebra solvers, you can use the MatrixPortal module, and you just have to select problems and options, then plot the results in nice graphs.", + "laborHours": 2705.6, + "languages": [], + "name": "Trilinos Web Interface Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/WebTrilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trilinos_Zoltan.json b/agency-indexes/DoE/Trilinos_Zoltan.json new file mode 100644 index 00000000..a11898bc --- /dev/null +++ b/agency-indexes/DoE/Trilinos_Zoltan.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-12", + "metadataLastUpdated": "2018-07-12" + }, + "description": "Zoltan provides dynamic load balancing for parallel computing with a procedural C interface, with a variety of redistribution algorithms available. To access the Zoltan package, please refer to the packages directory within the main Trilinos GitHub repository. \n", + "laborHours": 8344830.4, + "languages": [], + "name": "Trilinos/Zoltan", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/trilinos/Trilinos/blob/master/packages/zoltan/COPYRIGHT_AND_LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Trios.json b/agency-indexes/DoE/Trios.json new file mode 100644 index 00000000..7b34cb3c --- /dev/null +++ b/agency-indexes/DoE/Trios.json @@ -0,0 +1,40 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "The Trilinos I/O support (Trios) software provides general I/O support for applications using Trilinos libraries. In particular, this software will include parallel I/O support to read and write selected Trilinos data structures to commonly-used file formats such as netCDF, hdf5, and Exodus.", + "laborHours": 39231.2, + "languages": [ + "C++", + "Shell", + "C", + "RPC", + "CMake", + "Makefile", + "Fortran" + ], + "name": "Trios", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/trios", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TripleGraph.json b/agency-indexes/DoE/TripleGraph.json new file mode 100644 index 00000000..1c9b497a --- /dev/null +++ b/agency-indexes/DoE/TripleGraph.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "RDF triplestores are great tools for online graph analytic processing (i.e., graph pattern query processing), but they do not provide graph mining capabilities (e.g., PageRank, connected-component analysis, node eccentricity, etc.). The software title \u201cTripleGraph\u201d is a graph analysis toolkit, which uses an RDF triplestore as its backend for creating, manipulating, mining, and programming with large scale property graphs. It allows users to run various graph mining algorithms easily. User can import edgelist-formatted (homogeneous graph) or JSON-formatted graph (property graph) into the RDF triplestore using the provided tool and perform various analysis such as (1) Node/edge retrieval and manipulation, (2) Pathfinding between two given nodes, (3) Running graph mining algorithms (PageRank/Personalized PageRank, Single Source Shortest Path/Multi-Source Shortest Path, Connected Component, Node Eccentricity, Peer Pressure Clustering). It supports standard graph data format and works with a standard SPARQL endpoint like Jena Fuseki. It allows users to perform online graph analytic processing and graph mining on the same platform (a triplestore).", + "laborHours": 380.0, + "languages": [ + "Python 2.7" + ], + "name": "TripleGraph", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/liza183/TripleGraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Truchas-PBF.json b/agency-indexes/DoE/Truchas-PBF.json new file mode 100644 index 00000000..5c143c7d --- /dev/null +++ b/agency-indexes/DoE/Truchas-PBF.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-07-12" + }, + "description": "Truchas-PBF is a specialization of LANL's open source Truchas software (LA-CC-15-097) that is designed to simulate the powder bed fusion (PBF) additive manufacturing process for metal materials. The software uses physics-based continuum models of heat conduction, phase change, fluid flow, and solid mechanics to simulate the detailed dynamics of the traveling liquid melt pool to predict the extent of the fusion zone, solidification microstructure, and resulting residual stress in the fused material.", + "laborHours": 0.0, + "languages": [], + "name": "Truchas-PBF", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/truchas-pbf/truchas-pbf", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tsuchinoko_v1.0.0.json b/agency-indexes/DoE/Tsuchinoko_v1.0.0.json new file mode 100644 index 00000000..8429cf8d --- /dev/null +++ b/agency-indexes/DoE/Tsuchinoko_v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Tsuchinoko is a Qt application for adaptive experiment execution and tuning. Live visualizations show details of measurements, and provide feedback on the adaptive engine's decision-making process. The parameters of the adaptive engine can also be tuned live to explore and optimize the search procedure.\n\nWhile Tsuchinoko is designed to allow custom adaptive engines to drive experiments, the gpCAM engine is a featured inclusion. This tool is based on a flexible and powerful Gaussian process regression at the core.\n\nA Tsuchinoko system includes 4 distinct components: the GUI client, an adaptive engine, and execution engine, and a core service. These components are separable to allow flexibility with a variety of distributed designs.", + "laborHours": 3967.2, + "languages": [], + "name": "Tsuchinoko v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/tsuchinoko", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TuckerCompressMPI_v._1.0.json b/agency-indexes/DoE/TuckerCompressMPI_v._1.0.json new file mode 100644 index 00000000..f2c3df83 --- /dev/null +++ b/agency-indexes/DoE/TuckerCompressMPI_v._1.0.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "As parallel computing trends towards the exascale, scientific data produced by high-fidelity simulations are growing increasingly massive. For instance, a simulation on a three-dimensional spatial grid with 512 points per dimension that tracks 64 variables per grid point for 128 time steps yields 8 TB of data. By viewing the data as a dense five-way tensor, we can compute a Tucker decomposition to find inherent low-dimensional multilinear structure, achieving compression ratios of up to 10000 on real-world data sets with negligible loss in accuracy. So that we can operate on such massive data, we present the first-ever distributed-memory parallel implementation for the Tucker decomposition, whose key computations correspond to parallel linear algebra operations, albeit with nonstandard data layouts. Our approach specifies a data distribution for tensors that avoids any tensor data redistribution, either locally or in parallel. This software provides a method for compressing large-scale multiway data.", + "laborHours": 19364.8, + "languages": [ + "C++", + "Shell", + "CMake", + "MATLAB", + "Makefile", + "Python" + ], + "name": "TuckerCompressMPI v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TuckerMPI", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tuning_and_Analysis_Utilities__TAU_.json b/agency-indexes/DoE/Tuning_and_Analysis_Utilities__TAU_.json new file mode 100644 index 00000000..984526b3 --- /dev/null +++ b/agency-indexes/DoE/Tuning_and_Analysis_Utilities__TAU_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "TAU Performance System\u00ae is a portable profiling and tracing toolkit for performance analysis of parallel programs written in Fortran, C, C++, UPC, Java, Python.", + "homepageURL": "https://www.cs.uoregon.edu/research/tau/home.php", + "laborHours": 568495.2, + "languages": [], + "name": "Tuning and Analysis Utilities (TAU)", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.cs.uoregon.edu/research/tau/tau_releases/tau-2.20.1/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.cs.uoregon.edu/research/tau/home.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Turbine_CostSE__Turbine_Cost_Systems_Engineering_Model__DEPRECATED_[SWR-13-30].json b/agency-indexes/DoE/Turbine_CostSE__Turbine_Cost_Systems_Engineering_Model__DEPRECATED_[SWR-13-30].json new file mode 100644 index 00000000..134798c1 --- /dev/null +++ b/agency-indexes/DoE/Turbine_CostSE__Turbine_Cost_Systems_Engineering_Model__DEPRECATED_[SWR-13-30].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-19" + }, + "description": "This repository has been archived by the owner on Jun 19, 2020. It is now read-only. \n\nTurbine_CostsSE is a set of models for assessing the costs of a wind turbine. The first model is a new version of NREL's turbine Cost and Scaling Model that uses 2015 survey data to compute component mass properties from key turbine parameters such as rotor diameter, rated power and hub height. A second model is a new mass-to-cost model which takes the individual component masses as inputs to estimate each component costs with additional cost factors for assembly, overhead, and profits.", + "laborHours": 2340.8, + "languages": [ + "Python" + ], + "name": "Turbine_CostSE (Turbine Cost Systems Engineering Model) DEPRECATED [SWR-13-30]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/turbine_costsse", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Turbo-Turtle_v0.12.1.json b/agency-indexes/DoE/Turbo-Turtle_v0.12.1.json new file mode 100644 index 00000000..f3d28fba --- /dev/null +++ b/agency-indexes/DoE/Turbo-Turtle_v0.12.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "A collection of solid body modeling tools for 2D sketched, 2D axisymmetric, and 3D revolved models. It also contains general purpose meshing and image generation utilities appropriate for any model, not just those created with this package. Implemented for Abaqus and Cubit as backend modeling and meshing software. Orginal implementation targeted Abaqus so most options and descriptions use Abaqus modeling concepts and language.\n\nTurbo-Turtle makes a best effort to maintain common behaviors and features across each third-party software\u2019s modeling concepts. As much as possible, the work for each subcommand is performed in Python 3 to minimize solution approach duplication in third-party tools. The third-party scripting interface is only accessed when creating the final tool specific objects and output. The tools contained in this project can be expanded to drive other meshing utilities in the future, as needed by the user community.\n\nThis project derives its name from the origins as a sphere partitioning utility following the turtle shell (or soccer ball) pattern.s.", + "laborHours": 5000.8, + "languages": [], + "name": "Turbo-Turtle v0.12.1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-aea/turbo-turtle", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tusas,_Version_1.0.json b/agency-indexes/DoE/Tusas,_Version_1.0.json new file mode 100644 index 00000000..903a7f28 --- /dev/null +++ b/agency-indexes/DoE/Tusas,_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Tusas is a general / flexible software framework for solving coupled systems of onlinear partial differential equations. Tusas was originally developed for phase-field simulation of solidification. In order for Tusas to be effective, the PDEs must be compatible with structured or unstructured Lagrange (nodal) finite element discretizations and explicit (Euler) or implicit (Euler, Trapezoid, BDF2) temporal discretizations.", + "laborHours": 10442.4, + "name": "Tusas, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chrisknewman/tusas", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/TwinMe4AD:_WGAN-based_Digital_Twins_for_Anomaly_Detection.json b/agency-indexes/DoE/TwinMe4AD:_WGAN-based_Digital_Twins_for_Anomaly_Detection.json new file mode 100644 index 00000000..14f32be2 --- /dev/null +++ b/agency-indexes/DoE/TwinMe4AD:_WGAN-based_Digital_Twins_for_Anomaly_Detection.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-03", + "metadataLastUpdated": "2024-07-03" + }, + "description": "SAND2024-08373O\nTwinMe4AD is a Python-based software tool designed for anomaly detection using digital twins that closely mimic real, wearable healthcare datasets. The tool is invaluable for scenarios where collecting data is either expensive or impractical, serving as a privacy-preserving solution. Sensitive information is protected by training deep learning models on synthetic data derived from real datasets. One of TwinMe4AD's key features is its anomaly detection capability, which is based on fourth-order moments of parameters. This versatile approach can be applied across a range of datasets, from univariate to multivariate, making it compatible with various types of data. It also generates synthetic twins using Wasserstein Generative Adversarial Networks (WGANs), allowing users to create a small cohort of a population similar to that of a village population. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1550.4, + "languages": [ + "Python 3.6" + ], + "name": "TwinMe4AD: WGAN-based Digital Twins for Anomaly Detection", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/TwinMe4AD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Two_dimensional_topology_optimization_of_heat_exchangers_with_the_volume_fraction_method.json b/agency-indexes/DoE/Two_dimensional_topology_optimization_of_heat_exchangers_with_the_volume_fraction_method.json new file mode 100644 index 00000000..17771cbc --- /dev/null +++ b/agency-indexes/DoE/Two_dimensional_topology_optimization_of_heat_exchangers_with_the_volume_fraction_method.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-02-03", + "metadataLastUpdated": "2021-02-03" + }, + "description": "We perform a comparison study of two topology optimizations methods applied to the design of a two fluids heat exchanger modeled with a coupled thermal-flow problem. The flow follows an isothermal and\nincompressible Stokes-Brinkman equation and the heat transfer is governed by a convection-diffusion\nequation without internal generation and high Peclet number. To keep the two fluid phases separated, we solve two Stokes-Brinkman equations, where the Brinkman term models the other phase as a solid. These two velocity fields are then fed to the heat transfer equation. Our goal is to maximize the enthalpy at the cold outlet while constraining the pressure drop. We first solve the design modeling the solid and fluid phases with a volume fraction variable. A SIMP-like penalization in the Brinkman term drives the optimization to a discrete design. The cost and constraint function\nderivatives are calculated with the library pyadjoint and the optimization is performed by IPOPT. We present optimized designs in two dimensions and discuss the influence of the parameters.\n", + "laborHours": 0.0, + "languages": [], + "name": "Two dimensional topology optimization of heat exchangers with the volume fraction method", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/2DHEVF", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Two_linear_time,_low_overhead_algorithms_for_graph_layout.json b/agency-indexes/DoE/Two_linear_time,_low_overhead_algorithms_for_graph_layout.json new file mode 100644 index 00000000..1fa07ae5 --- /dev/null +++ b/agency-indexes/DoE/Two_linear_time,_low_overhead_algorithms_for_graph_layout.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The software comprises two algorithms designed to perform a 2D layout of a graph structure in time linear with respect to the vertices and edges in the graph, whereas most other layout algorithms have a running time that is quadratic with respect to the number of vertices or greater. Although these layout algorithms run in a fraction of the time as their competitors, they provide competitive results when applied to most real-world graphs. These algorithms also have a low constant running time and small memory footprint, making them useful for small to large graphs.", + "laborHours": 3149576.8, + "name": "Two linear time, low overhead algorithms for graph layout", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Txtexov.1.9.json b/agency-indexes/DoE/Txtexov.1.9.json new file mode 100644 index 00000000..9cf32ecd --- /dev/null +++ b/agency-indexes/DoE/Txtexov.1.9.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-08-06" + }, + "description": "Txtexo will convert a file in the structured text output format created by exotxt back to an exodusII database file. The text file must conform to the format written by the exotxt program but it can be modified as long as the data are consistent. Txtexo is used to convert the structured text file created by the exotxt code to a binary exodusII database.", + "laborHours": 692284.0, + "languages": [], + "name": "Txtexov.1.9", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.9" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Tycho_2,_Version_0.1.json b/agency-indexes/DoE/Tycho_2,_Version_0.1.json new file mode 100644 index 00000000..baa9a38c --- /dev/null +++ b/agency-indexes/DoE/Tycho_2,_Version_0.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Tycho 2 is a mini-app for testing performance of new algorithms and computational optimizations of neutral particle transport sweeps on 3D tetrahedral, unstructured grids.", + "laborHours": 6110.4, + "name": "Tycho 2, Version 0.1", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl/tycho2/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/tycho2", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Typeforge.json b/agency-indexes/DoE/Typeforge.json new file mode 100644 index 00000000..61606a04 --- /dev/null +++ b/agency-indexes/DoE/Typeforge.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-08", + "metadataLastUpdated": "2020-05-08" + }, + "description": "Typeforge is a tool for type refactoring in C/C++ programs. It enables users to transform the type of any\nvariables or operations. It guarantees the syntactic and semantic correctness of the generated code -- it\nwill always compile!\nIs", + "laborHours": 9697.6, + "languages": [], + "name": "Typeforge", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/typeforge", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Typeview_KBase_UI_Plugin.json b/agency-indexes/DoE/Typeview_KBase_UI_Plugin.json new file mode 100644 index 00000000..aa66f487 --- /dev/null +++ b/agency-indexes/DoE/Typeview_KBase_UI_Plugin.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "A simple plugin to view KBase types, type modules, and function specifications.", + "laborHours": 9393.6, + "languages": [], + "name": "Typeview KBase UI Plugin", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-typeview", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/U-Net_Decoder_CRF_v0.1.0.json b/agency-indexes/DoE/U-Net_Decoder_CRF_v0.1.0.json new file mode 100644 index 00000000..8c2aa305 --- /dev/null +++ b/agency-indexes/DoE/U-Net_Decoder_CRF_v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-08-15", + "metadataLastUpdated": "2024-08-15" + }, + "description": "We introduce a new encoder-decoder system that overcomes adaptability and scalability issues. We adapt multiple CNNs as encoders, allowing for the definition of multiple function parameter arguments to structure the models according to the targeted datasets and scientific problem.\n\nWe leverage the flexibility of the U-Net architecture to act as a scalable decoder. The CRF-RNN layer is integrated into the decoder as an optional final layer, keeping the entire system fully compatible with back-propagation.", + "laborHours": 1474.4, + "languages": [], + "name": "U-Net Decoder CRF v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mavaylon1/UNet_Decoder_CRF", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UCNB_Analyzer.json b/agency-indexes/DoE/UCNB_Analyzer.json new file mode 100644 index 00000000..291b4add --- /dev/null +++ b/agency-indexes/DoE/UCNB_Analyzer.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The purpose of this software is to interpret and analyze data taken using the NI PXIe-5171R digitizer based data acquisition system for the UCNB and Nab experiments. The detection and data acquisition systems are identical for the 2 experiments, with some differences in analysis requirements. The software converts raw binary files produced by the NI DAQ into ROOT TTree format, performs waveform analysis using trapezoidal filter algorithms, pulse fitting, and noise analysis routines, and applies variable criteria to identify valid events in the data stream. The software will be used to perform analysis of the events for multi-channel coincidences, timing and energy studies, and event rates under different experimental conditions.", + "laborHours": 5456.8, + "name": "UCNB_Analyzer", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/losalamos/UCNB_Analyzer", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UEDGE_toolbox.json b/agency-indexes/DoE/UEDGE_toolbox.json new file mode 100644 index 00000000..75a29dc5 --- /dev/null +++ b/agency-indexes/DoE/UEDGE_toolbox.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-03-28", + "metadataLastUpdated": "2023-03-29" + }, + "description": "The UEDGE Toolbox supplies an object-based interface and a wide array of tools used for running and analyzing UEDGE simulations. The toolbox provides routines for setting up UEDGE cases using YAML input files, shorthand commands for restoring converged solutions, as well as plotting profiles and surface plots of any of the parameters in UEDGE. Furthermore, the toolbox provides the necessary objects for compiling and analyzing parameter scans consisiting of several UEDGE simulations.", + "laborHours": 0.0, + "languages": [], + "name": "UEDGE toolbox", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/UETOOLS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UIMF_Library.json b/agency-indexes/DoE/UIMF_Library.json new file mode 100644 index 00000000..c4583fe5 --- /dev/null +++ b/agency-indexes/DoE/UIMF_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software package includes a library of C# functions to create, modify and extract data from UIMF files. UIMF files are SQLite databases of mass spectrometry data acquired at Pacific Northwest National Laboratory (PNNL).", + "laborHours": 25475.2, + "languages": [], + "name": "UIMF Library", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/UIMF-Library/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/UIMF-Library", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UIService.json b/agency-indexes/DoE/UIService.json new file mode 100644 index 00000000..26ec9070 --- /dev/null +++ b/agency-indexes/DoE/UIService.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "This is the repository for \"UIService\" developed by KBase. A KBase module generated by the KBase SDK.", + "laborHours": 2964.0, + "languages": [], + "name": "UIService", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/kbase-sdk-module-ui-service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UI_Common.json b/agency-indexes/DoE/UI_Common.json new file mode 100644 index 00000000..ebc888dc --- /dev/null +++ b/agency-indexes/DoE/UI_Common.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "Common user interface components and libraries for the KBase Project.", + "laborHours": 473358.4, + "languages": [], + "name": "UI Common", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/ui-common", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UMAP_v2.0.0.json b/agency-indexes/DoE/UMAP_v2.0.0.json new file mode 100644 index 00000000..9fe3f29b --- /dev/null +++ b/agency-indexes/DoE/UMAP_v2.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "Umap is a library that provides an mmap()-like interface to a simple, user- space page fault handler based on the userfaultfd Linux feature (starting with 4.3 linux kernel). The use case is to have an application specific buffer of pages cached from a large file, i.e. out-of-core execution using memory map.", + "laborHours": 3952.0, + "languages": [], + "name": "UMAP v2.0.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/umap", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UMT.json b/agency-indexes/DoE/UMT.json new file mode 100644 index 00000000..8cd4d876 --- /dev/null +++ b/agency-indexes/DoE/UMT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "UMT is a Sn deterministic thermal radiative transport Fortran proxy application. Its primary purpose is to research how data layout, programming paradigms and architectures effect the implementation and performance of Sn transport in Fortran on unstructured meshes. It is based on the LLNL Teton Sn deterministic thermal radiative transport code.", + "laborHours": 0.0, + "languages": [], + "name": "UMT", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/UMT", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UOWDetection.json b/agency-indexes/DoE/UOWDetection.json new file mode 100644 index 00000000..f830c318 --- /dev/null +++ b/agency-indexes/DoE/UOWDetection.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-08-09", + "metadataLastUpdated": "2024-08-09" + }, + "description": "The code provides machine learning, data collection, and computer science tools used to detect undocumented orphaned wells in United States from aerial imagery.", + "laborHours": 258.4, + "languages": [], + "name": "UOWDetection", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/uow", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UPC++.json b/agency-indexes/DoE/UPC++.json new file mode 100644 index 00000000..0bbd67ef --- /dev/null +++ b/agency-indexes/DoE/UPC++.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2019-07-23" + }, + "description": "UPC++ is a Partitioned Global Address Space (PGAS) extension for C++, with three main objectives: 1) to provide an object-oriented PGAS programming model in the context of the popular C++ language; 2) to add useful parallel programming idioms unavailable in UPC, such as asynchronous remote function invocation and multidimensional arrays, to support complex scientific applications; 3) to offer an easy on-ramp to PGAS programming through interoperability with other existing parallel programming systems (e.g., MPI, OpenMP, CUDA). UPC++ includes two main features beyond UPC: 1) One of the major limitations of UPC in the context of DOE application is the relatively weak notion of multidimensional arrays, which it inherited from C. To remedy this problem in UPC++, we included a multidimensional domain and array library based on that of Titanium. Titanium's library is similar to Chapel's dense and strided domains, as both were inspired by the dense and strided regions and arrays in ZPL. 2) Another feature provided by UPC++ but not by UPC is remote function invocation, which is inspired by Phalanx, X10, Habanero-C, and C++11. The user may start an asynchronous remote function invocation with the following syntax: \"async(place)(function, args...);\". UPC++ provides two programming constructs for specifying dynamic dependencies among tasks: 1) event-driven execution as in Phalanx and Habanero-C; 2) finish-async as in X10. We implemented UPC++ with a \"compiler-free\" approach using C++ templates and runtime libraries. The UPC++ front-end consists of a set of C++ header files that enables the C++ compiler to \"translate\" UPC++ features in a user program to runtime library calls. In particular, we use templates and operator overloading to customize the behavior of UPC++ types.\n\nThis software package has been replaced with UPCC++ V 1.0", + "laborHours": 20702.4, + "languages": [], + "name": "UPC++", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/berkeleylab/upcxx/src/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upcxx.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/UPC++_V1.0.json b/agency-indexes/DoE/UPC++_V1.0.json new file mode 100644 index 00000000..fc65625e --- /dev/null +++ b/agency-indexes/DoE/UPC++_V1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-07", + "metadataLastUpdated": "2020-06-01" + }, + "description": "UPC++ is a C++11 library providing classes and functions that support Partitioned \nGlobal Address Space (PGAS) programming. We are revising the library under the auspices of the DOE's Exascale Computing Project, to meet the needs of applications requiring PGAS support. UPC++ is intended for implementing elaborate distributed data structures where communication is irregular or fine-grained. The UPC++ interfaces for moving non-contiguous data and handling memories with different optimal access methods are composable and similar to those used in conventional C++. The UPC++ programmer can expect communication to run at close to hardware speeds. \n\nThe key facilities in UPC++ are global pointers, that enable the programmer to express \nownership information for improving locality, one-sided communication, both put/get and RPC, futures and continuations. Futures capture data readiness state, which is useful in making scheduling decisions, and continuations provide for completion handling via callbacks. Together, these enable the programmer to chain together a DAG of operations to execute asynchronously as high-latency dependencies become satisfied.\n", + "laborHours": 20702.4, + "languages": [], + "name": "UPC++ V1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/upcxx/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/UQ_Toolkit_v_2.0.json b/agency-indexes/DoE/UQ_Toolkit_v_2.0.json new file mode 100644 index 00000000..84847ea0 --- /dev/null +++ b/agency-indexes/DoE/UQ_Toolkit_v_2.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "The Uncertainty Quantification (UQ) Toolkit is a software library for the characterizaton and propagation of uncertainties in computational models. For the characterization of uncertainties, Bayesian inference tools are provided to infer uncertain model parameters, as well as Bayesian compressive sensing methods for discovering sparse representations of high-dimensional input-output response surfaces, and also Karhunen-Lo\u00e8ve expansions for representing stochastic processes. Uncertain parameters are treated as random variables and represented with Polynomial Chaos expansions (PCEs). The library implements several spectral basis function types (e.g. Hermite basis functions in terms of Gaussian random variables or Legendre basis functions in terms of uniform random variables) that can be used to represent random variables with PCEs. For propagation of uncertainty, tools are provided to propagate PCEs that describe the input uncertainty through the computational model using either intrusive methods (Galerkin projection of equations onto basis functions) or non-intrusive methods (perform deterministic operation at sampled values of the random values and project the obtained results onto basis functions).", + "laborHours": 217101.6, + "languages": [ + "C++", + "C", + "Fortran" + ], + "name": "UQ Toolkit v 2.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/UQTk", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UQ_combustion.json b/agency-indexes/DoE/UQ_combustion.json new file mode 100644 index 00000000..69b7d66f --- /dev/null +++ b/agency-indexes/DoE/UQ_combustion.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This repository contains companion code and data for the SAE paper \"A Framework for Quantifying Measurement Uncertainties and Uncertainty Propagation in HCCI/LTGC Engine Experiments\", G. Petitpas, M. J. McNenly, R. A. Whitesides.\n", + "laborHours": 410.4, + "languages": [], + "name": "UQ_combustion", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/UQ_combustion", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/URBANopt__Urban_Renewable_Building_And_Neighborhood_Optimization__[SWR-16-33].json b/agency-indexes/DoE/URBANopt__Urban_Renewable_Building_And_Neighborhood_Optimization__[SWR-16-33].json new file mode 100644 index 00000000..eeff69ea --- /dev/null +++ b/agency-indexes/DoE/URBANopt__Urban_Renewable_Building_And_Neighborhood_Optimization__[SWR-16-33].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2025-03-26" + }, + "description": "URBANopt is a user interface for creating and running district and city scale building energy simulations. The framework is built around the OpenStudio Urban Measures which are part of the OpenStudio project. Building footprints, building height, building type, and other data can be imported from public records or other sources. Footprints and locations for new buildings and district systems can also be specified. OpenStudio Measures are used to create starting point energy models and to model energy design features and efficiency measures for each building. URBANopt allows a user to pose several scenarios such as \u201cwhat if 30% of the commercial retail buildings added roof top solar\u201d or \u201cwhat if all elementary schools converted to ground source heat pumps\u201d and then visualize the impacts at a district or city scale. URBANopt is capable of modeling existing buildings, new construction, and district energy systems. URBANopt can be used to explore options for achieving Zero Energy across a collection of buildings (e.g., Zero Energy Districts).", + "homepageURL": "https://www.nrel.gov/buildings/urbanopt.html", + "laborHours": 635147.2, + "languages": [], + "name": "URBANopt (Urban Renewable Building And Neighborhood Optimization) [SWR-16-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.nrel.gov/buildings/urbanopt.html", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git "a/agency-indexes/DoE/URBANopt\342\204\242_District_Energy_Systems_HVAC_Measures__DES_HVAC__[SWR-21-30].json" "b/agency-indexes/DoE/URBANopt\342\204\242_District_Energy_Systems_HVAC_Measures__DES_HVAC__[SWR-21-30].json" new file mode 100644 index 00000000..4babf60b --- /dev/null +++ "b/agency-indexes/DoE/URBANopt\342\204\242_District_Energy_Systems_HVAC_Measures__DES_HVAC__[SWR-21-30].json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-27", + "metadataLastUpdated": "2024-03-04" + }, + "description": "DES_HVAC is a repository of a Parametric Analysis Tool (PAT) project and for scripts related to modeling of different HVAC systems for buildings in a district served by a district thermal energy system.\n\nThe Measures directory contains the new measures developed to extract data from the simulations. Update these measures and not the measures in the Test Suite measures directory. PAT should be used to update the measures in the Test Suite project.\n\nThe Test directory contains a PAT project for testing the functionality of the measures. The PAT project is named HVAC_Test and can be opened in PAT > 3.x.", + "laborHours": 0.0, + "languages": [], + "name": "URBANopt\u2122 District Energy Systems HVAC Measures (DES_HVAC) [SWR-21-30]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/urbanopt/DES_HVAC", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/USGIN_Lab_site.json b/agency-indexes/DoE/USGIN_Lab_site.json new file mode 100644 index 00000000..a3c3fc98 --- /dev/null +++ b/agency-indexes/DoE/USGIN_Lab_site.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This web site provides information related to service profiles and implementation in development for the US Geoscience information network (USGIN). It is meant to be a site where developers can learn about the standard in use, the objectives of the application profiles being developed, software being used or tested for implementation of services, and details about particular implementations. Forums are provided for asking questions about the services, profiles, and implemenation issues.", + "laborHours": 268842.4, + "name": "USGIN Lab site", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/lab-usgin-site", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/USGIN_content_models_API.json b/agency-indexes/DoE/USGIN_content_models_API.json new file mode 100644 index 00000000..9c2b0dd7 --- /dev/null +++ b/agency-indexes/DoE/USGIN_content_models_API.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is a Python API for interacting with USGIN Content Models.", + "laborHours": 243.2, + "name": "USGIN content models API", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/usginmodels/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/usginmodels", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UV-CDAT_scientific_examples.json b/agency-indexes/DoE/UV-CDAT_scientific_examples.json new file mode 100644 index 00000000..407d0ba5 --- /dev/null +++ b/agency-indexes/DoE/UV-CDAT_scientific_examples.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "In purpose of easy UV-CDAT usage for beginners.", + "laborHours": 592.8, + "languages": [], + "name": "UV-CDAT_scientific_examples", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/UV-CDAT_scientific_examples", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UWLi__Universal_Workflow_Language_Interface__[SWR-24-12].json b/agency-indexes/DoE/UWLi__Universal_Workflow_Language_Interface__[SWR-24-12].json new file mode 100644 index 00000000..64909ea2 --- /dev/null +++ b/agency-indexes/DoE/UWLi__Universal_Workflow_Language_Interface__[SWR-24-12].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-12-07", + "metadataLastUpdated": "2024-11-01" + }, + "description": "UWLi is a user interface for modifying Universal Workflow Language (UWL) files. UWL is a data format used to represent high fidelity scientific procedures in a generalized, field agnostic workflow format.\n\nSee related publication: https://arxiv.org/pdf/2409.05899", + "laborHours": 3040.0, + "languages": [ + "Smarty", + "Python" + ], + "name": "UWLi (Universal Workflow Language Interface) [SWR-24-12]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Universal-Workflow-Language-Interface", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ubiquitous_Traffic_Volume_Estimation_System.json b/agency-indexes/DoE/Ubiquitous_Traffic_Volume_Estimation_System.json new file mode 100644 index 00000000..924baa00 --- /dev/null +++ b/agency-indexes/DoE/Ubiquitous_Traffic_Volume_Estimation_System.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2022-06-16" + }, + "description": "The Ubiquitous Traffic Volume Estimation System uses Machine Learning (ML) algorithms to provide accurate estimates of number vehicles on the roadway (ubiquitous traffic volume) based on inputs such as commercial probe traffic data that includes average vehicle speed and probe counts, roadway characteristics, weather, time of day, and day of week, and reference volume counts from a limited number of automatic traffic recorder stations. The Ubiquitous Traffic Volume Estimation System estimates traffic volumes 24 hours a day, 7 days a week, and 365 days a year on all major corridors and freeways in Denver metropolitan area and is being expanded to the whole state of Colorado. The methodology and code developed in this effort can be easily customized to other states and cities where similar data is available.", + "laborHours": 0.0, + "languages": [ + "R", + "Jupyter Notebook" + ], + "name": "Ubiquitous Traffic Volume Estimation System", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/TrafficVolumeEstimation", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ultrascale_visualization_capabilities_for_the_ParaView_VTK_framework.json b/agency-indexes/DoE/Ultrascale_visualization_capabilities_for_the_ParaView_VTK_framework.json new file mode 100644 index 00000000..0baa6894 --- /dev/null +++ b/agency-indexes/DoE/Ultrascale_visualization_capabilities_for_the_ParaView_VTK_framework.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "The software is a set of technologies developed by the SciDAC Institute for Ultrascale Visualization in order to address the visualization needs for petascale computing and beyond. These technologies include improved I/O performance, simulation co-processing, advanced rendering capabilities, and specialized visualization techniques developed for SciDAC applications.", + "laborHours": 82095.2, + "languages": [ + "C++", + "C" + ], + "name": "Ultrascale visualization capabilities for the ParaView/VTK framework", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/paraview/catalyst", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ultrasonic_Welding_Bond_Characterization.json b/agency-indexes/DoE/Ultrasonic_Welding_Bond_Characterization.json new file mode 100644 index 00000000..74b7bb76 --- /dev/null +++ b/agency-indexes/DoE/Ultrasonic_Welding_Bond_Characterization.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-06-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Ultrasonic Consolidation (UC) of dissimilar materials. The software also allows for embedding sensors for smart structures. The software relates to Battelle patents.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Ultrasonic Welding Bond Characterization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Ume:_Unstructured_Mesh_Explorations.json b/agency-indexes/DoE/Ume:_Unstructured_Mesh_Explorations.json new file mode 100644 index 00000000..39f393ed --- /dev/null +++ b/agency-indexes/DoE/Ume:_Unstructured_Mesh_Explorations.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "Ume is an open-source collection of data structures for unstructured computational meshes and some simple algorithms that operate on them. These algorithms mimic the memory access patterns of a common class of operations found in several of the computational physics simulation codes developed at Los Alamos National Laboratory. The intent is that Ume can be used by hardware vendors to understand the memory traffic created by complex codes in a simplified environment, and to explore new means of optimization for that traffic. Ume is provided as a source-code C++ library and includes several applications that demonstrate the use of that library.", + "laborHours": 0.0, + "languages": [], + "name": "Ume: Unstructured Mesh Explorations", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/UME", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Umpire.json b/agency-indexes/DoE/Umpire.json new file mode 100644 index 00000000..c143e455 --- /dev/null +++ b/agency-indexes/DoE/Umpire.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2020-05-27" + }, + "description": "The Umpire library consists of a collection of software components that provide memory and resource management capabilities that can be used by diverse high performance computing (HPC) applications. The current set of capabilities that Umpire provides Includes: \n\u2022\tFlexible allocators to provision memory In the range of available memory resources on a target system.\n\u2022\tAn extensible allocation strategy model, allowing custom algorithms to be used to allocate memory resources in a scalable and high\u00adperformance fashion.\n\u2022\tMemory-location aware operations that can be used to migrate and modify memory using specialized functions dependent on source and target data locations\n\u2022\tA set of Introspection capabilities to allow the user to query the state of the different allocators and memory allocations.", + "laborHours": 30096.0, + "languages": [], + "name": "Umpire", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Umpire", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Unambiguous_Metabolite_Identification_in_High-Throughput_Metabolomics_by_Hybrid_1H-NMR_ESI-MS1_Approach.json b/agency-indexes/DoE/Unambiguous_Metabolite_Identification_in_High-Throughput_Metabolomics_by_Hybrid_1H-NMR_ESI-MS1_Approach.json new file mode 100644 index 00000000..1503a583 --- /dev/null +++ b/agency-indexes/DoE/Unambiguous_Metabolite_Identification_in_High-Throughput_Metabolomics_by_Hybrid_1H-NMR_ESI-MS1_Approach.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-10-05", + "metadataLastUpdated": "2020-10-05" + }, + "description": "The invention improves accuracy of metabolite identification by combining direct infusion ESI-MS with one-dimensional 1H-NMR spectroscopy. First, we apply a standard 1H-NMR metabolite identification protocol by matching the chemical shift, J-coupling and intensity information of experimental NMR signals against the NMR signals of standard metabolites in a metabolomics reference libraries. This generates a list of candidate metabolites. The list contains both false positive and ambiguous identifications. The software tool (the invention) takes the list of candidate metabolites, generated from NMRbased metabolite identification, and then calculates, for each of the candidate metabolites, the monoisotopic mass-tocharge (m/z) ratios for each commonly observed ion, fragment and adduct feature. These are then used to assign m/z ratios in experimental ESI-MS spectra of the same sample. Detection of the signals of a given metabolite in both NMR and MS spectra resolves the ambiguities, and therefore, significantly improves the confidence of the identification.", + "laborHours": 15.2, + "languages": [ + "Software is compiled and interpreted for the Java Virtual Machine (JVM) version 6 or higher." + ], + "name": "Unambiguous Metabolite Identification in High-Throughput Metabolomics by Hybrid 1H-NMR/ESI-MS1 Approach", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://store.pnnl.gov/content/unambiguous-metabolite-identification-hybrid-1d-1h-nmresi-ms1-approach", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/EMSL-NMR-EPR/MATLAB-1D_1H_NMR_ESI_MS1-WebApp", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Uncertainty_Quantification_for_Electronic_Hamiltonian.json b/agency-indexes/DoE/Uncertainty_Quantification_for_Electronic_Hamiltonian.json new file mode 100644 index 00000000..ef66bee7 --- /dev/null +++ b/agency-indexes/DoE/Uncertainty_Quantification_for_Electronic_Hamiltonian.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-09", + "metadataLastUpdated": "2024-09-19" + }, + "description": "This program will generate random points for electrons within the dimensions given by a parameter input\nfile. Based on these randomly generated electron positions and the nuclear positions given by a position\ninput file it will generate a value for the total electronic energy of an isolated system. This total electronic\nenergy is calculated using the electronic Hamiltonian for a monoatomic system with atoms having the\nsame number of protons and neutrons. The size of the system is defined by the parameter input file. The\nprogram will do this many times to generate a distribution of theoretically possible electronic total energies\nof the system. A user can then compare the total electronic energy given by their electronic structure\nmethod to make sure it falls within the distribution of theoretically possible values.", + "laborHours": 243.2, + "languages": [], + "name": "Uncertainty Quantification for Electronic Hamiltonian", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/linyang-121/UQEH-p", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Unicorn_Face.json b/agency-indexes/DoE/Unicorn_Face.json new file mode 100644 index 00000000..c2e1851b --- /dev/null +++ b/agency-indexes/DoE/Unicorn_Face.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Unicorn Face provides novel \"n-shot learning\" capabilities, which enables conducting machine learning with small amounts of data in real time. The package is written in Python and provides mechanisms for training neural networks on CPUs and GPUs.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Unicorn Face", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Unified_EDGE.json b/agency-indexes/DoE/Unified_EDGE.json new file mode 100644 index 00000000..22faf5cc --- /dev/null +++ b/agency-indexes/DoE/Unified_EDGE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "UEDGE is an interactive suite of physics packages using the Python or BASIS scripting systems. The original (circa 2007) Python version has been supplanted by a version developed under the FACETS SciDAC project [Cary 2008, Mccourt 2012]. The plasma is described by time-dependent 2D plasma fluid equations that include equations for density, velocity, ion temperature, electron temperature, electrostatic potential, and gas density in the edge region of a magnetic fusion energy confinement device. Slab, cylindrical, and toroidal geometries are allowed, and closed Wld open magnetic field-line regions are included. Classical transport is assumed along magnetic field lines, and anomalous transport is assumed across field lines. Multi-charge state impurities can be included with the corresponding line-radiation energy loss. ", + "laborHours": 71576.8, + "languages": [], + "name": "Unified EDGE", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/UEDGE", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Unified_Reaction_Structures_for_Astrophysics__URSA_.json b/agency-indexes/DoE/Unified_Reaction_Structures_for_Astrophysics__URSA_.json new file mode 100644 index 00000000..b9450366 --- /dev/null +++ b/agency-indexes/DoE/Unified_Reaction_Structures_for_Astrophysics__URSA_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "Unified Reaction Structures for Astrophysics (URSA) defines a format for nuclear inputs used in the simulation of astrophysical nucleosynthesis. Data of this type is currently stored, transferred, and implemented using a disparate patchwork of data formats and supporting codes. URSA intends to unify these disparate data sources/formats into a single data structure that accommodates the fullest possible range of different reaction types arising in astrophysical environments (e.g., transfer, pickup, or capture reactions; radioactive decay; or delayed particle emission, among many other possibilities). Furthermore, URSA provides a modern and efficient C++ library that existing and/or future astrophysics simulation codes may link against to directly implement nuclear data libraries constructed within the URSA format. In this approach, URSA will ensure that nuclear data inferred from measurements and generated by new facilities such as the Facility for Rare Isotope Beams (FRIB) is appropriately and consistently used in astrophysical applications.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Unified Reaction Structures for Astrophysics (URSA)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/UnifyFS:_A_Distributed_Burst_Buffer_File_System_-_0.1.0.json b/agency-indexes/DoE/UnifyFS:_A_Distributed_Burst_Buffer_File_System_-_0.1.0.json new file mode 100644 index 00000000..ee821c0b --- /dev/null +++ b/agency-indexes/DoE/UnifyFS:_A_Distributed_Burst_Buffer_File_System_-_0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-10-29" + }, + "description": "UnifyFS is a user-level burst buffer file system under active development. UnifyFS supports scalable and efficient aggregation of I/O bandwidth from burst buffers while having the same life cycle as a batch-submitted job. While UnifyFS is designed for N-N write/read, UnifyFS compliments its functionality with the support for N-1 write/read. It efficiently accelerates scientific I/O based on scalable metadata indexing, co-located I/O delegation, and server-side read clustering and pipelining.", + "laborHours": 38167.2, + "languages": [], + "name": "UnifyFS: A Distributed Burst Buffer File System - 0.1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/UnifyFS/blob/dev/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/UnifyFS", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Uniprot-DAT-File-Parser.json b/agency-indexes/DoE/Uniprot-DAT-File-Parser.json new file mode 100644 index 00000000..49b248e6 --- /dev/null +++ b/agency-indexes/DoE/Uniprot-DAT-File-Parser.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This program can read a Uniprot .Dat file and parse out the information for each entry, creating a tab delimited text file or a FASTA file.", + "laborHours": 790.4, + "languages": [], + "name": "Uniprot-DAT-File-Parser", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Uniprot-DAT-File-Parser", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Unique_Building_Identifier_Generator.json b/agency-indexes/DoE/Unique_Building_Identifier_Generator.json new file mode 100644 index 00000000..dbd01fed --- /dev/null +++ b/agency-indexes/DoE/Unique_Building_Identifier_Generator.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-01-26", + "metadataLastUpdated": "2018-01-26" + }, + "description": "We developed a grid reference system-based Unique Building Identifier (UBID). The method converts a building footprint on a map to a unique code. Unlike geographic coordinates (latitude and longitude), which require high precision and can only locate points on the earth, the UBID code records two-dimensional information about a building footprint in a concise and practical manner. The UBID itself is neither a database nor a data schema. Rather, it acts as an external common key between databases to facilitate data mapping. The developed ruleset ensures that individual implementers can reach the same conclusion utilizing publicly available digital maps. It can also automatically resolve discrepancies, caused by physical space or structure changes over time, during data exchange. The method is also flexible and scalable to identify a portion of a building or a group of buildings.", + "laborHours": 440.8, + "name": "Unique Building Identifier Generator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Unique_Building_Identifier__UBID__cross-reference_using_intersection-over-union__IoU__over_quadtreebased_spatial_index.json b/agency-indexes/DoE/Unique_Building_Identifier__UBID__cross-reference_using_intersection-over-union__IoU__over_quadtreebased_spatial_index.json new file mode 100644 index 00000000..e54b3318 --- /dev/null +++ b/agency-indexes/DoE/Unique_Building_Identifier__UBID__cross-reference_using_intersection-over-union__IoU__over_quadtreebased_spatial_index.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Public release of a version of the cross-reference capability of the UBID software that is\nfeature-limited to cross-reference via Jaccard similarity coefficient (viz., intersection-over-union or \"IoU\") [2] over a\nquadtree-based spatial index only.", + "laborHours": 440.8, + "languages": [], + "name": "Unique Building Identifier (UBID) cross-reference using intersection-over-union (IoU) over quadtreebased spatial index", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UnitCommitment.jl.json b/agency-indexes/DoE/UnitCommitment.jl.json new file mode 100644 index 00000000..1334dbaa --- /dev/null +++ b/agency-indexes/DoE/UnitCommitment.jl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-05-17", + "metadataLastUpdated": "2021-05-19" + }, + "description": "UnitCommitment.jl is an optimization package for the Security-Constrained Unit Commitment Problem (SCUC), afundamental optimization problem in power systems used, for example, to clear the day-ahead electricity markets. The package provides a Julia/JuMP implementation of state-of-the-art mixed-integer programming formulations and algorithms to solve the problem.", + "laborHours": 0.0, + "languages": [], + "name": "UnitCommitment.jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ANL-CEEESA/UnitCommitment.jl", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UnitTesterSG.json b/agency-indexes/DoE/UnitTesterSG.json new file mode 100644 index 00000000..8a8f77a1 --- /dev/null +++ b/agency-indexes/DoE/UnitTesterSG.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "savaraa@ornl.gov" + }, + "date": { + "created": "2020-04-13", + "metadataLastUpdated": "2020-09-25" + }, + "description": "UnitTesterSG is a unit testing framework that is designed for nested and/or scientific/engineering data structures. It is designed primarily for testing the outputs if a single function or simulation run by storing the expected results file such that comparisons to the stored output can be made with unit tests after the function or software has been edited.\n\nThis module is designed to be able to unit test arrays, strings, as well as nested and deeply nested objects (including arrays with tuples inside, arrays with strings inside, etc.). The module is compatable with nested objects, and thus has a dependency on the nestedObjectsFunctions module within. The module takes *calculated* results and then compares them to *expected* results. If no expected results are available (or they do not match the calculated results) the module then offers to store the calculated results as expected results for next time.", + "laborHours": 319.2, + "languages": [ + "Python" + ], + "name": "UnitTesterSG", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdityaSavara/UnitTesterSG", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "5.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UnityMol-APBS.json b/agency-indexes/DoE/UnityMol-APBS.json new file mode 100644 index 00000000..67314dda --- /dev/null +++ b/agency-indexes/DoE/UnityMol-APBS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Virtual reality for biomolecular electrostatics UnityMol-APBS (NIH iEdison No. 0685901-19-0009, Grant No. GM069702)\nVisualization of molecular electrostatics on a two-dimensional screen greatly diminishes the associated depth component.\nUsing a virtual world to explore molecular electrostatics allows researchers to be immersed within their data.", + "laborHours": 15.2, + "languages": [], + "name": "UnityMol-APBS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Electrostatics/VR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Unity_Viewer_for_Cinema_Multicamera_Databases.json b/agency-indexes/DoE/Unity_Viewer_for_Cinema_Multicamera_Databases.json new file mode 100644 index 00000000..74fb766e --- /dev/null +++ b/agency-indexes/DoE/Unity_Viewer_for_Cinema_Multicamera_Databases.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "This project is a prototype viewer for Cinema multicamera databases using the Unity Game Engine. It is intended to demonstrate the initial capability and vision for exploring multicamera spaces in Cinema. Currently, it only works with SpecA databases.", + "laborHours": 2067.2, + "languages": [], + "name": "Unity Viewer for Cinema Multicamera Databases", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cinemascience/cinema_unityviewer/blob/master/license.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cinemascience/cinema_unityviewer", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Universal_Automated_Refrigerator_Door_Opener.json b/agency-indexes/DoE/Universal_Automated_Refrigerator_Door_Opener.json new file mode 100644 index 00000000..46a5a65d --- /dev/null +++ b/agency-indexes/DoE/Universal_Automated_Refrigerator_Door_Opener.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-25", + "metadataLastUpdated": "2018-07-27" + }, + "description": "This creation is used for standard energy performance tests of household and commercial refrigerators and other refrigeration equipment. It automates the door opening at a preset duration and velocity specified by the test procedure.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Universal Automated Refrigerator Door Opener", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Unpivot_Tool.json b/agency-indexes/DoE/Unpivot_Tool.json new file mode 100644 index 00000000..6280bd36 --- /dev/null +++ b/agency-indexes/DoE/Unpivot_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This program reads in a delimited text file that is in crosstab (aka PivotTable) format and writes out a new file where the data has been unpivotted.", + "laborHours": 1398.4, + "languages": [], + "name": "Unpivot Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Unpivot-Tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Unsupervised_Machine_Learning_Framework_for_Dynamical_Regime_Identification.json b/agency-indexes/DoE/Unsupervised_Machine_Learning_Framework_for_Dynamical_Regime_Identification.json new file mode 100644 index 00000000..37874c20 --- /dev/null +++ b/agency-indexes/DoE/Unsupervised_Machine_Learning_Framework_for_Dynamical_Regime_Identification.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-02-11", + "metadataLastUpdated": "2022-02-11" + }, + "description": "The code objectively identifies dynamical regimes by selecting regions of data in which the observed values of governing equation terms can be reduced to a truncated to a subset of governing equation terms. It is written in python and uses SciKit Learn open source machine learning libraries.", + "homepageURL": "https://github.com/bekaiser-LANL/id_dominant_balances.git", + "laborHours": 0.0, + "languages": [], + "name": "Unsupervised Machine Learning Framework for Dynamical Regime Identification", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bekaiser-LANL/id_dominant_balances.git", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Update_to_the_Microcontroller_Benchmark_for_Radiation_Testing.json b/agency-indexes/DoE/Update_to_the_Microcontroller_Benchmark_for_Radiation_Testing.json new file mode 100644 index 00000000..536ed5d6 --- /dev/null +++ b/agency-indexes/DoE/Update_to_the_Microcontroller_Benchmark_for_Radiation_Testing.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-03" + }, + "description": "LANL developed a benchmark of software code for radiation testing of microprocessors several years ago, and it was published under an open-source license on GitHub. Publishing the software is necessary for other researchers to adopt and implement this benchmark for radiation testing of other microprocessors to standardize test practices so that test data can be compared across different microprocessors. The original codes have been used several times by other organizations to test a wide range of microcontrollers and microprocessors. \nAfter several years of research, LANL is ready to update the benchmark. Changes include:\n1.\tAddition of new codes that allow common software codes to be tested,\n2.\tAddition of new codes that instrument more microprocessor circuitry, \n3.\tAddition of input patterns that allow for a more compressive understanding of how the memory layout affects the sensitivity to radiation-induced faults and better use of automated test pattern generation standards, and\n4.\tModification of current codes for faster and more resilient detection, reporting and correction of radiation-induced faults.\nThese codes have been tested by LANL researchers over the last few years, which has been published in the open literature. As the code base for the new benchmarks are stable, it is time to release the update to the GitHub repository, where the original codes were released.", + "laborHours": 0.0, + "languages": [], + "name": "Update to the Microcontroller Benchmark for Radiation Testing", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/benchmark_codes", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Upper_Rio_Grande_Simulation_Model__URGSIM_.json b/agency-indexes/DoE/Upper_Rio_Grande_Simulation_Model__URGSIM_.json new file mode 100644 index 00000000..f50cc473 --- /dev/null +++ b/agency-indexes/DoE/Upper_Rio_Grande_Simulation_Model__URGSIM_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-29" + }, + "description": "URGSIM estimates the location of surface water and groundwater resources in the upper Rio Grande Basin between the Colorado-New Mexico state line, and Caballo Reservoir from 1975 - 2045. It is a mass balance hydrology model of the Upper Rio Grande surface water, groundwater, and water demand systems which runs at a monthly timestep from 1975-1999 in calibration mode, 2000-2004 in validation mode, and 2005-2045 in scenario analysis mode.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Powersim Studio 2005 or later" + ], + "name": "Upper Rio Grande Simulation Model (URGSIM)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Urban_Deployment_Model__UDM__v1.0.json b/agency-indexes/DoE/Urban_Deployment_Model__UDM__v1.0.json new file mode 100644 index 00000000..7b2ff068 --- /dev/null +++ b/agency-indexes/DoE/Urban_Deployment_Model__UDM__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-17", + "metadataLastUpdated": "2021-05-18" + }, + "description": "The software, called the Urban Deployment Model (UDM), is an integrated set of tools for the simulation and analysis of static and mobile radiation detection systems in complex urban environments. The UDM includes a graphical user interface through which the workflow associated with setting up and executing a simulation may be established. The modular toolsets combine aspects of radiation transport, navigation, graph theory, optimization, and visualization to allow the complete end-to-end simulation of large scale, highly-distributed sensor networks.", + "homepageURL": "https://sites.google.com/lbl.gov/udm/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "Urban Deployment Model (UDM) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://marketplace.lbl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/udm/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Urbansim_to_Isomodel.json b/agency-indexes/DoE/Urbansim_to_Isomodel.json new file mode 100644 index 00000000..b22bf50c --- /dev/null +++ b/agency-indexes/DoE/Urbansim_to_Isomodel.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "This is python software couples UrbanSim, a free software package to the Argonne Isomodel building energy model and provides a few analysis tools.", + "laborHours": 0.0, + "languages": [], + "name": "Urbansim to Isomodel", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/urbansim-isomodel", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/UseLATEX.cmake.json b/agency-indexes/DoE/UseLATEX.cmake.json new file mode 100644 index 00000000..a14b2408 --- /dev/null +++ b/agency-indexes/DoE/UseLATEX.cmake.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "UseLATEX.cmake is a collection of script functions and examples for building LaTeX documents. It simplifies the process of building LaTeX documents, which requires the execution of multiple programs and the management of several input files. UseLATEX.cmake also provides several options to customize the LaTeX build process.", + "laborHours": 1520.0, + "languages": [ + "CMake", + "Shell", + "TeX" + ], + "name": "UseLATEX.cmake", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/UseLATEX", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Useful_python_scripts.json b/agency-indexes/DoE/Useful_python_scripts.json new file mode 100644 index 00000000..c59801c2 --- /dev/null +++ b/agency-indexes/DoE/Useful_python_scripts.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-08", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2023-11904O\nThis collection of original scripts is made up of Python, Makefile, and Vim. Each script performs a single commonly used function in an encapsulated manner that can easily integrate into larger application-specific software. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1641.6, + "languages": [ + "C", + "Python", + "Vim Script" + ], + "name": "Useful python scripts", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/penney-scripts", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/User_Profile_Plugin.json b/agency-indexes/DoE/User_Profile_Plugin.json new file mode 100644 index 00000000..fa9566bb --- /dev/null +++ b/agency-indexes/DoE/User_Profile_Plugin.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-24", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This kbase-ui plugin is responsible for displaying a user profile - either the current user's profile if the path is #people or #user, or a given user profile if the path is #people/USERNAME or #user/USERNAME.", + "laborHours": 107737.6, + "languages": [], + "name": "User Profile Plugin", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/kbase-ui-plugin-user-profile", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/User_and_Job_State_Service.json b/agency-indexes/DoE/User_and_Job_State_Service.json new file mode 100644 index 00000000..53b631b9 --- /dev/null +++ b/agency-indexes/DoE/User_and_Job_State_Service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-18", + "metadataLastUpdated": "2020-08-18" + }, + "description": "Service to maintain global user state and job status.", + "laborHours": 22313.6, + "languages": [], + "name": "User and Job State Service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/user_and_job_state", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Using_Linear_Algebra_Libaries.json b/agency-indexes/DoE/Using_Linear_Algebra_Libaries.json new file mode 100644 index 00000000..4ab7efd5 --- /dev/null +++ b/agency-indexes/DoE/Using_Linear_Algebra_Libaries.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "This repository shows how to use various linear algebra libraries (MAGMA, CULA, and LAPACK) on Titan with Fortran and C. MAGMA and CULA are accelerated libraries that take advantage of Titan's GPUs.\n", + "laborHours": 2325.6, + "name": "Using Linear Algebra Libaries", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/AccelLinAlgebraLibraries", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Utility_Stock_Analysis_Tool__USAT_.json b/agency-indexes/DoE/Utility_Stock_Analysis_Tool__USAT_.json new file mode 100644 index 00000000..cc2701db --- /dev/null +++ b/agency-indexes/DoE/Utility_Stock_Analysis_Tool__USAT_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-20", + "metadataLastUpdated": "2018-07-20" + }, + "description": "The Utility Stock Analysis Tool is a pro-forma spreadsheet tool used to model changes in utility cost of equity and return on equity.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Utility Stock Analysis Tool (USAT)", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/VADER-Analytics.json b/agency-indexes/DoE/VADER-Analytics.json new file mode 100644 index 00000000..b351e349 --- /dev/null +++ b/agency-indexes/DoE/VADER-Analytics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-17", + "metadataLastUpdated": "2022-08-17" + }, + "description": "Visualization and Analytics for Distributed Energy Resources.", + "laborHours": 0.0, + "languages": [], + "name": "VADER-Analytics", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/VADER-Analytics/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/VADER-Analytics", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VALENCE.json b/agency-indexes/DoE/VALENCE.json new file mode 100644 index 00000000..2256d893 --- /dev/null +++ b/agency-indexes/DoE/VALENCE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "To the author's knowledge, VALENCE is the only implementation of the variational subspace valence bond (VSVB) method. At Argonne, VSVB was developed from the ground up with extreme scalability and high performance on emerging hardware paradigms in mind. Thus, VSVB is the only quantum chemistry method that promises high accuracy with cross-cutting applicability at the exascale. VSVB also offers unique opportunities for machine learning and stands to revolutionize many fields across materials science, chemistry, and biology. The existence of an open-source software implementation of VSVB is an essential step in its development and support for the benefit of the community. ", + "laborHours": 4924.8, + "languages": [], + "name": "VALENCE", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gdfletcher/VALENCE", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VARS_Framework.json b/agency-indexes/DoE/VARS_Framework.json new file mode 100644 index 00000000..31ecda90 --- /dev/null +++ b/agency-indexes/DoE/VARS_Framework.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-07-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Verification and Validation Assuring Reliability and Security (VARS) project team has developed the proof-of-concept VARS framework which will be implemented in the form of a software tool called Risk-Informed Verification and Validation Recommendation (RIVVR). The framework will provide Energy Delivery System (EDS) stakeholders with cybersecurity focused verification and validation (V&V) approach which includes list of potentially relevant vulnerabilities to test or address, pre-procurement guidance, and separate lists of relevant standards, tools, and techniques (ST2) to be considered by utilities and vendors", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "VARS Framework", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/VEESA_R_package.json b/agency-indexes/DoE/VEESA_R_package.json new file mode 100644 index 00000000..ed266f37 --- /dev/null +++ b/agency-indexes/DoE/VEESA_R_package.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-05", + "metadataLastUpdated": "2024-06-05" + }, + "description": "SAND2024-04584O\nR package for applying the VEESA pipeline method is a technique used for explainable machine learning with functional data. The VEESA pipeline makes use of the elastic-shape analysis framework for functional data. It also implements functional principal component analysis and permutation feature importance. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 486.4, + "languages": [ + "R" + ], + "name": "VEESA R package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/veesa", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VERAIn.json b/agency-indexes/DoE/VERAIn.json new file mode 100644 index 00000000..c46969d8 --- /dev/null +++ b/agency-indexes/DoE/VERAIn.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "CASL's modeling and simulation technology, the Virtual Environment for Reactor Applications (VERA), incorporates coupled physics and science-based models, state-of-the-art numerical methods, modern computational science, integrated uncertainty quantification (UQ) and validation against data from operating pressurized water reactors (PWRs), single-effect experiments, and integral tests. The computational simulation component of VERA is the VERA Core Simulator (VERA-CS). The core simulator is the specific collection of multi-physics computer codes used to model and deplete a LWR core over multiple cycles. The core simulator has a single common input file that drives all of the different physics codes. The parser code, VERAIn, converts VERA Input into an XML file that is used as input to different VERA codes.", + "laborHours": 13786.4, + "name": "VERAIn", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/CASL/VERAin/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CASL/VERAin", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VERAView.json b/agency-indexes/DoE/VERAView.json new file mode 100644 index 00000000..3f6fa4d8 --- /dev/null +++ b/agency-indexes/DoE/VERAView.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "In order to support engineering analysis of Virtual Environment for Reactor Analysis (VERA) model results, the Consortium for Advanced Simulation of Light Water Reactors (CASL) needs a tool that provides visualizations of HDF5 files that adhere to the VERAOUT specification. VERAView provides an interactive graphical interface for the visualization and engineering analyses of output data from VERA. The Python-based software provides instantaneous 2D and 3D images, 1D plots, and alphanumeric data from VERA multi-physics simulations.", + "laborHours": 21675.2, + "name": "VERAView", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CASL/VERAview", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VERTEX-CFD.json b/agency-indexes/DoE/VERTEX-CFD.json new file mode 100644 index 00000000..53675aec --- /dev/null +++ b/agency-indexes/DoE/VERTEX-CFD.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "delchinimg@ornl.gov" + }, + "date": { + "created": "2024-09-30", + "metadataLastUpdated": "2024-10-01" + }, + "description": "VERTEX-CFD is primary used for safety analysis and design optimization of fusion blankets. VERTEX-CFD has a highly flexible code structure that facilitates the addition of new features such as equations, boundary conditions, and source terms. VERTEX-CFD is designed to run on CPU- and GPU-enabled high-performance computing (HPC) platforms by relying on Kokkos. The code architecture supports a plug-and-play approach allowing equations to be coupled by selecting the correct set of input parameters in the XML format input file. A set of verification and validation problems were run to test VERTEX-CFD solver. VERTEX-CFD implements the incompressible Navier-Stokes equations coupled to a temperature equation and magneto-hydrodynamic equations. This code is being developed for fusion applications.", + "laborHours": 34792.8, + "languages": [ + "C++", + "Python", + "CUDA" + ], + "name": "VERTEX-CFD", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/delcmo/Vertex-CFD", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "Version 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VISAPULT.json b/agency-indexes/DoE/VISAPULT.json new file mode 100644 index 00000000..e2f78164 --- /dev/null +++ b/agency-indexes/DoE/VISAPULT.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "Visapult is software pipeline of two components, a backend and viewer, used to perform pipelined and distributed memory parallel, Image Based Rendering assisted volume rendering of 3D scalar data on structured rectilinear grids. Visapult implements a two-stage volume rendering pipeline using two software components called the \"backend\" and the \"viewer.\" The backend reads 3D scientific data from some source in a domain-decomposed fashion, and performs software volume rendering on each block of data. Results, which consist of six images per block (representing the six primary view axes) are transmitted over parallel sockets to the viewer. The viewer receives each block's worth of data, constructs an internal scene graph, and presents the resulting rendering to the human viewer. The human user can interactively transform the 3D model to obtain a view from any angle. Whereas full-resolution volume rendering is extremely computer and bandwidth intensive, the Visapult architecture is designed to perform the most demanding part of volume rendering on a parallel computer. Yet, the viewer maintains interactive rendering rates independent of the size of the original volume, and independent of network bandwidth.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [ + "C and C++" + ], + "name": "VISAPULT", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/VOLTTRON_Version_3.x.json b/agency-indexes/DoE/VOLTTRON_Version_3.x.json new file mode 100644 index 00000000..7e1fd6b0 --- /dev/null +++ b/agency-indexes/DoE/VOLTTRON_Version_3.x.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-11-06" + }, + "description": "VOLTTRON\u2122 is an agent execution platform providing services to its agents that allow them to easily communicate with physical devices and other resources. VOLTTRON\u2122 delivers an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls. It enables mobile and stationary software agents to perform information gathering, processing, and control actions. VOLTTRON\u2122 can independently manage a wide range of applications, such as HVAC systems, electric vehicles, distributed energy or entire building loads, leading to improved operational efficiency.", + "laborHours": 0.0, + "languages": [], + "name": "VOLTTRON Version 3.x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/VOLTTRON/volttron/blob/3.x/TERMS.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron/releases/tag/3.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VOLTTRON_Version_4.json b/agency-indexes/DoE/VOLTTRON_Version_4.json new file mode 100644 index 00000000..110206ec --- /dev/null +++ b/agency-indexes/DoE/VOLTTRON_Version_4.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-11-06" + }, + "description": "VOLTTRON\u2122 is an agent execution platform providing services to its agents that allow them to easily communicate with physical devices and other resources. VOLTTRON\u2122 delivers an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls. It enables mobile and stationary software agents to perform information gathering, processing, and control actions. VOLTTRON\u2122 can independently manage a wide range of applications, such as HVAC systems, electric vehicles, distributed energy or entire building loads, leading to improved operational efficiency.", + "laborHours": 0.0, + "languages": [], + "name": "VOLTTRON Version 4", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron/releases/tag/4.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "4.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VOLTTRON_Version_5.0.json b/agency-indexes/DoE/VOLTTRON_Version_5.0.json new file mode 100644 index 00000000..6af1babf --- /dev/null +++ b/agency-indexes/DoE/VOLTTRON_Version_5.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-11-06" + }, + "description": "VOLTTRON is an agent execution platform providing services to its agents that allow them to easily communicate with physical devices and other resources. VOLTTRON delivers an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls. It enables mobile and stationary software agents to perform information gathering, processing, and control actions. VOLTTRON can independently manage a wide range of applications, such as HVAC systems, electric vehicles, distributed energy or entire building loads, leading to improved operational efficiency.", + "laborHours": 0.0, + "languages": [], + "name": "VOLTTRON Version 5.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/VOLTTRON/volttron/blob/master/TERMS.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron/releases/tag/5.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "5.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VOLTTRON_Version_7.0.json b/agency-indexes/DoE/VOLTTRON_Version_7.0.json new file mode 100644 index 00000000..b3716e83 --- /dev/null +++ b/agency-indexes/DoE/VOLTTRON_Version_7.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-07", + "metadataLastUpdated": "2020-11-06" + }, + "description": "VOLTTRON\u2122 Distributed Control System Platform\nVersion 7.0\nVOLTTRON\u2122 is an agent execution platform providing services to its agents that allow them to easily communicate with physical devices and other resources.\nVOLTTRON\u2122 delivers an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls. It enables mobile and stationary software agents to perform information gathering, processing, and control actions. VOLTTRON\u2122 can independently manage a wide range of applications, such as HVAC systems, electric vehicles, distributed energy or entire building loads, leading to improved operational efficiency.", + "laborHours": 0.0, + "languages": [], + "name": "VOLTTRON Version 7.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron/releases/tag/7.0", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "7.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VOLTTRON_Version_8.json b/agency-indexes/DoE/VOLTTRON_Version_8.json new file mode 100644 index 00000000..2e69be58 --- /dev/null +++ b/agency-indexes/DoE/VOLTTRON_Version_8.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-11-05", + "metadataLastUpdated": "2020-11-06" + }, + "description": "VOLTTRON Distributed Control System Platform VOLTTRON\u2122 delivers an innovative distributed control and sensing software platform that supports modern control strategies, including agent-based and transaction-based controls.", + "laborHours": 0.0, + "languages": [], + "name": "VOLTTRON Version 8", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron/releases/tag/8.0rc1", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "8" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VOLTTRON_econ-dispatch.json b/agency-indexes/DoE/VOLTTRON_econ-dispatch.json new file mode 100644 index 00000000..fa916898 --- /dev/null +++ b/agency-indexes/DoE/VOLTTRON_econ-dispatch.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-10-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Work space for in development Economic Dispatch Application.\nMulti-purpose open-source control algorithms that will ensure real-time optimal operation, increase electric grid reliability, and lead to the goal of clean, efficient, reliable and affordable next generation building-integrated combine cooling, heating and power (CHP) system.The CHP system could include conventional heating, ventilation, air conditioning (HVAC) systems, distributed generation (DG), local storage (both thermal and electric) and local solar photovoltaic (PV) systems.", + "laborHours": 1459.2, + "languages": [], + "name": "VOLTTRON/econ-dispatch", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/volttron/econ-dispatch", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VOLTTRON_volttron-GS.json b/agency-indexes/DoE/VOLTTRON_volttron-GS.json new file mode 100644 index 00000000..eda0bdc8 --- /dev/null +++ b/agency-indexes/DoE/VOLTTRON_volttron-GS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-12-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PNNL grid related applications\nObject oriented design intended to facilitate reuse and extensibility of system features. The template enforces that needed structure and behaviors are available. Users may inherit and adapt these structures and behaviors to meet their specific requirements. Recognizes separation of the transactive system calculations into (1) scheduling of assets, (2) balancing of\nsupply and demand, and (3) coordination among independent agents. This separation facilitates useful computation boundaries in which computations can be completed without requiring end-to-end communication for each update. The code provides fundamental market solutions for balancing. The code provides mechanisms for inter-agent coordination. Allows event-driven agent interactions\u037e not limited to prescribed time intervals. Aggregates value and electricity at nodes and conveys opportunities up and down through the network.", + "laborHours": 8952.8, + "languages": [], + "name": "VOLTTRON/volttron-GS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron-GS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VOLTTRON_volttron-applications.json b/agency-indexes/DoE/VOLTTRON_volttron-applications.json new file mode 100644 index 00000000..bcd95def --- /dev/null +++ b/agency-indexes/DoE/VOLTTRON_volttron-applications.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-12-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "VOLTTRON Application tree (moved from volttron/applications)\nAutomated Identification of Re-tuning Measures", + "laborHours": 109880.8, + "languages": [], + "name": "VOLTTRON/volttron-applications", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron-applications", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VOLTTRON_volttron.json b/agency-indexes/DoE/VOLTTRON_volttron.json new file mode 100644 index 00000000..8c809b0a --- /dev/null +++ b/agency-indexes/DoE/VOLTTRON_volttron.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "VOLTTRON Distributed Control System Platform", + "laborHours": 196657.6, + "languages": [], + "name": "VOLTTRON/volttron", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VOLTTRON_volttron_Version_9.json b/agency-indexes/DoE/VOLTTRON_volttron_Version_9.json new file mode 100644 index 00000000..5ab25375 --- /dev/null +++ b/agency-indexes/DoE/VOLTTRON_volttron_Version_9.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-19", + "metadataLastUpdated": "2025-02-20" + }, + "description": "VOLTTRON Distributed Control System Platform", + "laborHours": 196657.6, + "languages": [], + "name": "VOLTTRON/volttron Version 9", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VOLTTRON/volttron", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "VOLTTRON v. 9" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VORO++.json b/agency-indexes/DoE/VORO++.json new file mode 100644 index 00000000..2c88c906 --- /dev/null +++ b/agency-indexes/DoE/VORO++.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Voro++ is a software library for the Computation of 3D Voronoi cells. It is primarily designed for applications in physics and materials science, where Voronoi cells can be a useful tool in the analysis of densely-packed particle systems. For a set of points in a space, the Voronoi cell of each particle is defined as the region which is closer to that particle than any other. Originally defined by Georgy Voronci [1], it has become a powerful tool in many scientific fields, whenever region of space must be divided between constituent points or particles [2]. Over the past twenty years, the algorithms for computing Voronoi cells have been well-studied, and several high-quality software packages are available. However, some (such as Triangle [3] are designed for the 2D case. Others, such as QHull [4], make use of algorithms for computing complete tessellations. This can offer limited flexibility, such as for handling complex boundary conditions, where direct cell-by-cell manipulation is beneficial. Voro++ is a library of C++ classes for direct computation of 3D Voronoi cells. The author believes this the first general purpose library that takes full advantage of the C++ class structure, making it simple to use, modify, and incorporate into other programs. The author has received considerable interest from other academic institutions about making use of the code. Features include: -- Rapid computation times, two to three times faster than Qhull in some typical cases -- Support for floating point inaccuracies and degenerate cases -- Support for curved and planar walls; periodic and non-periodic boundary conditions -- Support for radical Voronoi tessellations and neighbor list computations --Straightforward generalization to a parallel/ multicore architecture.", + "homepageURL": "http://math.lbl.gov/voro++", + "laborHours": 0.0, + "languages": [], + "name": "VORO++", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://math.lbl.gov/voro++/download", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://math.lbl.gov/voro++", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/VPIC-Kokkos.json b/agency-indexes/DoE/VPIC-Kokkos.json new file mode 100644 index 00000000..9b104ba1 --- /dev/null +++ b/agency-indexes/DoE/VPIC-Kokkos.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-05-09", + "metadataLastUpdated": "2022-05-09" + }, + "description": "VPIC is a particle-in-cell (PIC) code that solves the Maxwell-Boltzmann system of equations and can be used to simulate a wide variety of plasmas, including those that are fully kinetic and relativistic. Utilizing the Kokkos performance-portable framework, VPIC achieves high performance on multiple CPU and GPU architectures and is adaptable to future platforms with minimal developer effort. VPIC features very powerful input decks, allowing insertion of arbitrary C++ code for custom diagnostics, boundary conditions, and additional physics models.", + "laborHours": 0.0, + "languages": [], + "name": "VPIC-Kokkos", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vpic-kokkos", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VPIC.json b/agency-indexes/DoE/VPIC.json new file mode 100644 index 00000000..806e0035 --- /dev/null +++ b/agency-indexes/DoE/VPIC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "VPIC is a general-purpose Particle-In-Cell (PIC) simulation code for modeling multi-species kinetic plasmas in one, two, or three spatial dimensions. VPIC can solve equations of motion for different plasma species using kinetic or fluid descriptions. To solve for the kinetic species, VPIC employs a variety of explicit and implicit time-stepping schemes to update charged particle positions and velocities. In contrast, the fluid species is advanced in time by solving a number of fluid moment equations on a spatial grid using finite-difference methods. The electromagnetic fields are also solved on a spatial grid using either the full Maxwell equations, or a low frequency quasi-neutral approximation that uses an Ohm's law for the electric field. To couple the kinetic particle quantities with the grid-based field and fluid-moment descriptions requires that electromagnetic fields are interpolated from spatial grid points to the particle positions, and current densities are collected from the particles onto the spatial grid points. The VPIC code has been optimized for modern computing architectures and uses Message Passing Interface (MPI) calls for multi-node execution, in addition to exploiting node-level data-parallelism. The current feature set for VPIC includes a flexible input deck format capable of treating a wide variety of problems. These include: the ability to treat electromagnetic materials (scalar and tensor dielectric, conductivity, and diamagnetic material properties); multiple emission models, including user-configurable models; arbitrary, user-configurable boundary conditions for particles and fields; user-definable simulation units; a suite of \"standard\" diagnostics, as well as user-configurable diagnostics; a Monte-Carlo treatment of collisional processes capable of treating binary and unary collisions and secondary particle generation; and, flexible checkpoint-restart semantics enabling VPIC checkpoint files to be read as input for subsequent simulations. While the common use cases for VPIC employ low-order particles on rectilinear meshes, a framework exists to treat higher-order particles and curvilinear meshes, as well as more advanced field solvers.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "VPIC", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/VPIC_IO_utilities.json b/agency-indexes/DoE/VPIC_IO_utilities.json new file mode 100644 index 00000000..72db9034 --- /dev/null +++ b/agency-indexes/DoE/VPIC_IO_utilities.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-12-18", + "metadataLastUpdated": "2018-12-18" + }, + "description": "VPIC I/O Utilities provide scalable input and output code for writing and reading HDF5 data by the Vector Particle-in-cell (VPIC) simulation codes. The I/O utility writes particle, field, and hydro data from VPIC to HDF5 files. The filed and hydro codes also write XDMF files, which can be used by visualization tools such as ParaView to read and visualize the HDF5 data written.", + "laborHours": 744.8, + "languages": [], + "name": "VPIC IO utilities", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/dbin_sdm/viou/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/VPIC_v.1.2.json b/agency-indexes/DoE/VPIC_v.1.2.json new file mode 100644 index 00000000..abb8d081 --- /dev/null +++ b/agency-indexes/DoE/VPIC_v.1.2.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "sluedtke@lanl.gov" + }, + "date": { + "created": "2021-04-15", + "metadataLastUpdated": "2021-06-28" + }, + "description": "Vector Particle-in-Cell (VPIC) is a general purpose particle-in-cell simulation code for modeling kinetic plasmas in one, two, or three spatial dimensions. It employs a second-order, explicit, leapfrog algorithm to update charged particle positions and velocities in order to solve the relativistic kinetic equation for each species in the plasma, along with a full Maxwell description for the electric and magnetic fields evolved via a second- order finite-difference-time-domain (FDTD) solve. The VPIC code has been optimized for modern computing architectures and uses Message Passing Interface (MPI) calls for multi-node application as well as data parallelism using threads. VPIC employs a variety of short-vector, single-instruction-multiple-data (SIMD) intrinsics for high performance and has been designed so that the data structures align with cache boundaries. The current feature set for VPIC includes a flexible input deck format capable of treating a wide variety of problems. These include: the ability to treat electromagnetic materials (scalar and tensor dielectric, conductivity, and diamagnetic material properties); multiple emission models, including user-configurable models; arbitrary, user-configurable boundary conditions for particles and fields; user- definable simulation units; a suite of \"standard\" diagnostics, as well as user-configurable diagnostics; a Monte-Carlo treatment of collisional processes capable of treating binary and unary collisions and secondary particle generation; and, flexible checkpoint-restart semantics enabling VPIC checkpoint files to be read as input for subsequent simulations. VPIC has a native I/O format that interfaces with the high-performance visualization software Ensight and Paraview. While the common use cases for VPIC employ low-order particles on rectilinear meshes, a framework exists to treat higher-order particles and curvilinear meshes, as well as more advanced field solvers.", + "laborHours": 0.0, + "languages": [ + "C++", + "C" + ], + "name": "VPIC v.1.2", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vpic", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git", + "version": "1.2" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/VSProj_NuGet_Version_Updater\302\240.json" "b/agency-indexes/DoE/VSProj_NuGet_Version_Updater\302\240.json" new file mode 100644 index 00000000..def58adc --- /dev/null +++ "b/agency-indexes/DoE/VSProj_NuGet_Version_Updater\302\240.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "VSProj NuGet Version Updater searches for Visual Studio project files (.csproj and.vsproj) that reference a specific NuGet package and updates the referenced version to a newer version if necessary.", + "laborHours": 288.8, + "languages": [], + "name": "VSProj NuGet Version Updater\u00a0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/VSProj-NuGet-Version-Updater", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VTK-m.json b/agency-indexes/DoE/VTK-m.json new file mode 100644 index 00000000..c189d6f5 --- /dev/null +++ b/agency-indexes/DoE/VTK-m.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2020-06-01" + }, + "description": "VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures. 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VTK-m supports the fine-grained concurrency for data analysis and visualization algorithms required to drive extreme scale computing by providing abstract models for data and execution that can be applied to a variety of algorithms across many different processor architectures.", + "laborHours": 204652.8, + "languages": [ + "C++" + ], + "name": "VTK-m v. 2.0", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk-m", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ValidateFastaFile.json b/agency-indexes/DoE/ValidateFastaFile.json new file mode 100644 index 00000000..5ff13590 --- /dev/null +++ b/agency-indexes/DoE/ValidateFastaFile.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ValidateFastaFile.exe reads a Fasta File and displays statistics on the number of proteins and number of residues. 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The software performs this task faster than the traditional Kalman filtering technique. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Variational Kalman Filtering with Hinf-Based Correction v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/VKF-with-Hinf-Based-Correction-for-Robust-Bayesian-Learning", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Varity.json b/agency-indexes/DoE/Varity.json new file mode 100644 index 00000000..2afe130b --- /dev/null +++ b/agency-indexes/DoE/Varity.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-01-09", + "metadataLastUpdated": "2020-07-27" + }, + "description": "Brief Description for Public Release:\nVarity is a framework to identify variations in floating-point programs through randomized differential testing. 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Varity helps users of a system to identify the compilers that produce the most similar results in the system.", + "laborHours": 15732.0, + "languages": [], + "name": "Varity", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Varity", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Vaultbot_ROS_Package.json b/agency-indexes/DoE/Vaultbot_ROS_Package.json new file mode 100644 index 00000000..4976cb7a --- /dev/null +++ b/agency-indexes/DoE/Vaultbot_ROS_Package.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Operating software for MET-2 Vaultbot project. Pan-tilt camera control, autonomous task planning, inventory integration functions.", + "laborHours": 1048.8, + "name": "Vaultbot ROS Package", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/UTNuclearRoboticsPublic/task_planning", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VeloC.json b/agency-indexes/DoE/VeloC.json new file mode 100644 index 00000000..21b1cbe3 --- /dev/null +++ b/agency-indexes/DoE/VeloC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "VeloC (Very-Low Overhead Checkpointing System) is a multi-level checkpoint/restart runtime that delivers high performance and scalability for complex heterogeneous storage hierarchies without sacrificing ease of use and flexibility.", + "laborHours": 2614.4, + "languages": [], + "name": "VeloC", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ecp-veloc/veloc", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VelocityGAN.json b/agency-indexes/DoE/VelocityGAN.json new file mode 100644 index 00000000..f1a53cb8 --- /dev/null +++ b/agency-indexes/DoE/VelocityGAN.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-09-15", + "metadataLastUpdated": "2022-09-19" + }, + "description": "VelocityGAN is a software to solve subsurface imaging problems. It leverages a generative adversarial network to model the correspondence from seismic data to subsurface velocity structures.", + "laborHours": 0.0, + "languages": [], + "name": "VelocityGAN", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/OpenFWI", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Velvet_1.2.10.json b/agency-indexes/DoE/Velvet_1.2.10.json new file mode 100644 index 00000000..19e12cfb --- /dev/null +++ b/agency-indexes/DoE/Velvet_1.2.10.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "This is the repository for \"Velvet 1.2.10\" developed by KBase.", + "laborHours": 1307.2, + "languages": [], + "name": "Velvet 1.2.10", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/kb_Velvet", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Venn_Diagram_Plotter.json b/agency-indexes/DoE/Venn_Diagram_Plotter.json new file mode 100644 index 00000000..8f61842e --- /dev/null +++ b/agency-indexes/DoE/Venn_Diagram_Plotter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Venn Diagram Plotter draws correctly proportioned and positioned two and three circle Venn diagrams (aka Euler diagrams) whose colors can be customized and the diagrams copied to the clipboard or saved to disk.", + "laborHours": 5152.8, + "languages": [], + "name": "Venn Diagram Plotter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/Venn-Diagram-Plotter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VeraRun.json b/agency-indexes/DoE/VeraRun.json new file mode 100644 index 00000000..5710ec3f --- /dev/null +++ b/agency-indexes/DoE/VeraRun.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "VeraRun provides users a command-line utility that determines the sequence of VERA codes and utilities to be executed, calculates and determines PBS directives and job parameters, creates a job script, and submits the script on behalf of the user. While hiding all the details, the script allows the user to set PBS parameters explicitly. VeraRun is implemented as a Python package with host-specific configurations and job script templates. Host configurations are stored in JavaScript Object Notation (JSON) files and specify machine characteristics (e.g., number of nodes, number of processors per node, memory available per node, location of VERA installations). Job templates are Bash scripts with parameters substituting for host-specific PBS directives and controls. These files are named by the hostname, thus making VeraRun extensible to other systems and environments. VeraRun reads the VERA input file to determine code and execution environment requirements, creating and optionally submitting a job script.", + "laborHours": 21675.2, + "languages": [ + "Python 2 or 3" + ], + "name": "VeraRun", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/casl/VeraView", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Verdict.json b/agency-indexes/DoE/Verdict.json new file mode 100644 index 00000000..c4533c05 --- /dev/null +++ b/agency-indexes/DoE/Verdict.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2024-09-12" + }, + "description": "The Verdict code verifies the correctness of a finite element mesh stored in the Exodus II fine format. Verdict calculates multiple quality metrics for each individual element, verifies local and global connectivity, analyzes interfaces between element blocks, predicts the probability topology of the mesh, and prints out any problems discovered. SAND2019-7026 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 10138.4, + "languages": [ + "C++", + "CMake" + ], + "name": "Verdict", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/verdict", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VerifyIO:_Verifying_Adherence_to_Parallel_I_O_Consistency_Semantics.json b/agency-indexes/DoE/VerifyIO:_Verifying_Adherence_to_Parallel_I_O_Consistency_Semantics.json new file mode 100644 index 00000000..931d698c --- /dev/null +++ b/agency-indexes/DoE/VerifyIO:_Verifying_Adherence_to_Parallel_I_O_Consistency_Semantics.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "VerifyIO is a tool designed for verifying I/O consistency semantics in High-Performance Computing (HPC)\napplications. It addresses the challenges of ensuring correctness and portability across different I/O\nconsistency models, such as POSIX, Commit, Session, and MPI-IO. By analyzing execution traces,\ndetecting conflicts, and verifying synchronization adherence, VerifyIO provides actionable insights for both\napplication developers and I/O library designers.", + "laborHours": 760.0, + "languages": [], + "name": "VerifyIO: Verifying Adherence to Parallel I/O Consistency Semantics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wangvsa/VerifyIO", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Verilator_Testbench_Environment__VTE__v0.1.json b/agency-indexes/DoE/Verilator_Testbench_Environment__VTE__v0.1.json new file mode 100644 index 00000000..83329485 --- /dev/null +++ b/agency-indexes/DoE/Verilator_Testbench_Environment__VTE__v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-01", + "metadataLastUpdated": "2018-10-02" + }, + "description": "VTE is a library that allows fast and simple generation of C++ testers for modules written in Chisel and build an efficient interface to existing C++ based simulators. It contains Scala-based interface and C++ testbench class. Scala interface interacts with Firtl Interpreter and generates a basic set of C++ testbench files. These files contain the list of the Device Under Test (DUT) input-output ports as well as their parameters. C++ testbench provides functionalities similar to the Chisel PeekPokeTester, such as poke, expect, step functions. As a backend it uses Verilator.\n", + "laborHours": 562.4, + "languages": [], + "name": "Verilator Testbench Environment (VTE) v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbnlcomputerarch/vte", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Vertical-Axis_Wind_Turbine_Mesh_Generator.json b/agency-indexes/DoE/Vertical-Axis_Wind_Turbine_Mesh_Generator.json new file mode 100644 index 00000000..799b78bf --- /dev/null +++ b/agency-indexes/DoE/Vertical-Axis_Wind_Turbine_Mesh_Generator.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "VAWTGen is a mesh generator for creating a finite element beam mesh of arbitrary vertical-axis wind turbines (VAWT). The software accepts input files specifying tower and blade structural and aerodynamic descriptions and constructs a VAWT using a minimal set of inputs. VAWTs with an arbitrary number of blades can be constructed with or without a central tower. Strut connections between the tower and blades can be specified in an arbitrary manner. The software also facilitates specifying arbitrary joints between structural components and concentrated structural tenns (mass and stiffness). The output files which describe the VAWT configuration are intended to be used with the Offshore Wind ENergy Simulation (OWENS) Toolkit software for structural dynamics analysis of VAWTs. Furthermore, VAWTGen is useful for visualizing output from the OWENS analysis software.", + "laborHours": 912.0, + "languages": [ + "MATLAB" + ], + "name": "Vertical-Axis Wind Turbine Mesh Generator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/VAWTGen?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/VAWTGen", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Very_Low_Overhead_Transparent_Multilevel_.json b/agency-indexes/DoE/Very_Low_Overhead_Transparent_Multilevel_.json new file mode 100644 index 00000000..d247f719 --- /dev/null +++ b/agency-indexes/DoE/Very_Low_Overhead_Transparent_Multilevel_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-07-20", + "metadataLastUpdated": "2018-07-20" + }, + "description": "VeloC: Very Low Overhead Transparent Multilevel Checkpoint/Restart. The VeloC software suite will be a multilevel checkpoint/restart interface and implementation for exascale applications. VeloC will have three major impacts. It will: (1) optimize checkpoint/restart perfonnance for applications and workflows (2) increase programmer productivity by dramatically reducing the difficulty of handling varied and complex storage architectures and the need for\nperformance/reliability optimizations. (3) benefit a wide community.\nVeloC is a collaboration between LLNL and ANL as part of the Exascale Computing Project. ", + "laborHours": 1276.8, + "languages": [], + "name": "Very Low Overhead Transparent Multilevel ", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-VeloC/AXL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Vessel_Integrated_Turbine_Assessment_for_LCOE__VITAL__v.1.0.json b/agency-indexes/DoE/Vessel_Integrated_Turbine_Assessment_for_LCOE__VITAL__v.1.0.json new file mode 100644 index 00000000..5e3a8b92 --- /dev/null +++ b/agency-indexes/DoE/Vessel_Integrated_Turbine_Assessment_for_LCOE__VITAL__v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "SAND2025-00929O\nVessel Integrated Turbine Assessment for LCOE (VITAL) is a user-friendly software tool that optimizes the design and control of hydrokinetic turbines deployed from floating vessels. It uses data about rotor blade performance, vessel parameters, tidal data, and cost models. This data is used to determine the best turbine design and control strategies to minimize the levelized cost of energy (LCOE). This application can enhance the efficiency and cost-effectiveness of tidal energy projects. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov", + "laborHours": 653.6, + "languages": [ + "Python" + ], + "name": "Vessel Integrated Turbine Assessment for LCOE (VITAL) v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Vidyut3d:_A_Non-Equilibrium_Plasma_Modeling_Tool_[SWR-24-101].json b/agency-indexes/DoE/Vidyut3d:_A_Non-Equilibrium_Plasma_Modeling_Tool_[SWR-24-101].json new file mode 100644 index 00000000..ccf5b51c --- /dev/null +++ b/agency-indexes/DoE/Vidyut3d:_A_Non-Equilibrium_Plasma_Modeling_Tool_[SWR-24-101].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-10-14", + "metadataLastUpdated": "2024-10-14" + }, + "description": "Vidyut3d is a massively-parallel plasma-fluid solver for low-temperature plasmas (LTPs) that supports both local field (LFA) and local mean energy (LMEA) approximations, as well as complex gas and surface-phase chemistry. The solver supports 2D and 3D domains, and uses AMReX's adaptive mesh refinement capabilities to increase the grid resolution around complex structures (e.g. streamer heads and sheaths) while maintaining a tractable problem size. Vidyut specializes in simulating various types of gas-phase discharges, as well as plasma/surface interactions and surface chemistry (e.g. for plasma-mediated catalysis applications). The solver also supports hybrid CPU/GPU parallelization strategies, and has demonstrated excellent scaling on various HPC architectures for problem sizes consisting of O(100 M) control volumes.", + "laborHours": 21173.6, + "languages": [ + "C++", + "Python" + ], + "name": "Vidyut3d: A Non-Equilibrium Plasma Modeling Tool [SWR-24-101]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/vidyut3d", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/View3D.json b/agency-indexes/DoE/View3D.json new file mode 100644 index 00000000..0f8dbfa4 --- /dev/null +++ b/agency-indexes/DoE/View3D.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-11-29", + "metadataLastUpdated": "2018-11-29" + }, + "description": "This is View3D, version 3.2, a C program for the computation of geometric view factors. This version of View3D is included as part of the EnergyPlus installer package. The program utilizes a number of integration techniques to compute view factors between planar triangles or quadrilaterals in three dimensions.", + "laborHours": 3252.8, + "languages": [ + "C" + ], + "name": "View3D", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/View3D-3.2", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "3.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VinaLC:_Parallel_Molecular_Docking_Program.json b/agency-indexes/DoE/VinaLC:_Parallel_Molecular_Docking_Program.json new file mode 100644 index 00000000..936bfd63 --- /dev/null +++ b/agency-indexes/DoE/VinaLC:_Parallel_Molecular_Docking_Program.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-03-20", + "metadataLastUpdated": "2018-03-20" + }, + "description": "VinaLC is based on a very popular PC-based molecular docking program, AutoDock Vina. The original Vina docking program was modified and parallelized, using an MPI and multithreading hybrid scheme, and potentially can be used in the future on exascale machines, without sacrificing accuracy.", + "laborHours": 4727.2, + "name": "VinaLC: Parallel Molecular Docking Program", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/XiaohuaZhangLLNL/VinaLC", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Virtreg.json b/agency-indexes/DoE/Virtreg.json new file mode 100644 index 00000000..11f4e8e2 --- /dev/null +++ b/agency-indexes/DoE/Virtreg.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Virtual register for performing addition and subtraction of floating-point numbers without loss of precision", + "laborHours": 440.8, + "languages": [], + "name": "Virtreg", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Virtreg", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Virtual_Battery_Aggregator__Virtual_Battery_Aggregator_for_Distributed_Energy_Resource_Management_Systems_.json b/agency-indexes/DoE/Virtual_Battery_Aggregator__Virtual_Battery_Aggregator_for_Distributed_Energy_Resource_Management_Systems_.json new file mode 100644 index 00000000..34a337b2 --- /dev/null +++ b/agency-indexes/DoE/Virtual_Battery_Aggregator__Virtual_Battery_Aggregator_for_Distributed_Energy_Resource_Management_Systems_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-12", + "metadataLastUpdated": "2021-07-12" + }, + "description": "Distributed energy resource management systems (DERMS) are being deployed in feeders with high distributed energy resource (DER) penetration to provide visibility of DERs and enable DER control strategies for grid operators. DERMS can support centralized grid controls by aggregating individual DER information into a single virtual DER model. This codebase creates algorithms for a DERMS platform that are able to aggregate a set of DERs that can be modeled as batteries, create a virtual battery model for centralized grid controls, and dispatch power setpoints to the individual DERs based on a desired virtual power setpoint received from the centralized grid control. It integrates with existing co-simulation frameworks and models for buildings, DERs, and distribution systems. While the DERMS is designed to work with batteries, it can be used with any DER that can be defined by a generalized battery model.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Virtual Battery Aggregator (Virtual Battery Aggregator for Distributed Energy Resource Management Systems)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/virtual-battery-aggregator", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Virtual_Engineering__VE___vebio_.json b/agency-indexes/DoE/Virtual_Engineering__VE___vebio_.json new file mode 100644 index 00000000..4d72a697 --- /dev/null +++ b/agency-indexes/DoE/Virtual_Engineering__VE___vebio_.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-03-21", + "metadataLastUpdated": "2022-04-18" + }, + "description": "The Virtual Engineering (VE, vebio) project provides a set of Python modules to enable users to connect mathematical models of unit operations to predict outcomes for an entire chemical process. This VE approach is currently being developed to support the beginning-to-end simulation of the low-temperature conversion of lignocellulosic biomass to a fuel precursor, but the underlying communication functions can be readily extended to connect models from other domains. The models and features currently included in the VE library include a models/simulations for pretreatment, enzymatic hydrolysis, and aerobic bioreaction.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Fortran", + "Python", + "Tex", + "shell" + ], + "name": "Virtual Engineering (VE) (vebio)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/VirtualEngineering", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Virtual_Flow_Simulator.json b/agency-indexes/DoE/Virtual_Flow_Simulator.json new file mode 100644 index 00000000..6ba689b4 --- /dev/null +++ b/agency-indexes/DoE/Virtual_Flow_Simulator.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Virtual Flow Simulator (VFS) is a state-of-the-art computational fluid mechanics (CFD) package that is capable of simulating multi-physics/multi-phase flows with the most advanced turbulence models (RANS, LES) over complex terrains. The flow solver is based on the Curvilinear Immersed Boundary (CURVIB) method to handle geometrically complex and moving domains. Different modules of the VFS package can provide different simulation capabilities for specific applications ranging from the fluid-structure interaction (FSI) of solid and deformable bodies, the two-phase free surface flow solver based on the level set method for ocean waves, sediment transport models in rivers and the large-scale models of wind farms based on actuator lines and surfaces. All numerical features of VFS package have been validated with known analytical and experimental data as reported in the related journal articles. VFS package is suitable for a broad range of engineering applications within different industries. VFS has been used in different projects with applications in wind and hydrokinetic energy, offshore and near-shore ocean studies, cardiovascular and biological flows, and natural streams and river morphodynamics. Over the last decade, the development of VFS has been supported and assisted with the help of various United States companies and federal agencies that are listed in the sponsor lists. In this version, VFS-Wind contains all the necessary modeling tools for wind energy applications, including land-based and offshore wind farms. VFS is highly scalable to run on either desktop computers or high performance clusters (up to 16,000 CPUs). This released version comes with a detailed user\u2019s manual and a set of case studies designed to facilitate the learning of the various aspects of the code in a comprehensive manner. The included documentation and support material has been elaborated in a collaboration effort with Sandia National Labs under the contract DE-EE0005482. The VFS-Wind source code is distributed under the GNU General Public License (GPL 2.0), offering to the community the flexibility to use and expand the capabilities of the package. We note that future publications including academic journals that result from the use of VFS must be cited appropriately under the GPL v.2 license agreement.", + "laborHours": 31053.6, + "name": "Virtual Flow Simulator", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SAFL-CFD-Lab/VFS-Wind", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Virtual_Machine_Builder.json b/agency-indexes/DoE/Virtual_Machine_Builder.json new file mode 100644 index 00000000..80c206de --- /dev/null +++ b/agency-indexes/DoE/Virtual_Machine_Builder.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Virtual Machine Builder is a graphical user interface for use and modification of virtual machine templates using Hashi Corp packer to perform virtual machine creation.", + "laborHours": 6566.4, + "name": "Virtual Machine Builder", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csd-dev-tools/VmBuilder", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VisTrails.json b/agency-indexes/DoE/VisTrails.json new file mode 100644 index 00000000..5a92db36 --- /dev/null +++ b/agency-indexes/DoE/VisTrails.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-13", + "metadataLastUpdated": "2018-07-13" + }, + "description": "VisTrails is an open-source scientific workflow and provenance management system developed at the University of Utah that provides support for data exploration and visualization.", + "laborHours": 376960.0, + "languages": [], + "name": "VisTrails", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/VisTrails/VisTrails", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Viscoplastic_selfconsistent__VPSC__code__version_8,_open_source_.json b/agency-indexes/DoE/Viscoplastic_selfconsistent__VPSC__code__version_8,_open_source_.json new file mode 100644 index 00000000..e898eeff --- /dev/null +++ b/agency-indexes/DoE/Viscoplastic_selfconsistent__VPSC__code__version_8,_open_source_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-11-03", + "metadataLastUpdated": "2023-11-08" + }, + "description": "VPSC is a mean-field polycrystal plasticity code for the prediction of the mechanical response and microstructure evolution\nof polycrystalline aggregates. The VPSC code is the computational realization of the visco-plastic self-consistent theory of polycrystal deformation. Both the theory and details of its numerical implementation were originally reported by R.A.\nLebensohn and C.N. Tom\u00e9: \"A self-consistent approach for the simulation of plastic deformation and texture development\nof polycrystals: application to Zirconium alloys\", Acta Metallurgica et Materialia 41, 2611 (1993). Since then, the VPSC code\nhas experienced several improvements and extensions and it is nowadays extensively used to simulate plastic deformation\nof polycrystalline aggregates and to interpret experimental evidence on metals, minerals and polymers.", + "laborHours": 0.0, + "languages": [], + "name": "Viscoplastic selfconsistent (VPSC) code (version 8, open source)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vpsc_code", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Vistransformers_Explained.json b/agency-indexes/DoE/Vistransformers_Explained.json new file mode 100644 index 00000000..84d2e5bc --- /dev/null +++ b/agency-indexes/DoE/Vistransformers_Explained.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-03-22", + "metadataLastUpdated": "2024-03-22" + }, + "description": "The Vistransformers Explained library is a collection of python notebooks that demonstrate the internal mechanics and uses of visual-transformer (ViT) machine learning models. The code implements, with mild modifications, ViT models that have been made publicly available through publication and GitHub code. The value added by this code is in-depth explanations of the mathematics behind the sub-modules of the ViT models, including original figures. Additionally, the library contains the code necessary to implement and train the ViT models. The library does not include example training data for the models; instead, it would rely on users generating their own datasets. The code is based on the PyTorch python library. It does not include any files other than python scripts, modules, or notebooks.", + "laborHours": 0.0, + "languages": [], + "name": "Vistransformers Explained", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vision_transformers_explained", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Visual_Information_for_the_Desktop,_version_1.0.json b/agency-indexes/DoE/Visual_Information_for_the_Desktop,_version_1.0.json new file mode 100644 index 00000000..cca7df60 --- /dev/null +++ b/agency-indexes/DoE/Visual_Information_for_the_Desktop,_version_1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "VZIN integrates visual analytics capabilities into popular desktop tools to aid a user in searching and understanding an information space. VZIN allows users to Drag-Drop-Visualize-Explore-Organize information within tools such as Microsoft Office, Windows Explorer, Excel, and Outlook. VZIN is tailorable to specific client or industry requirements. VZIN follows the desktop metaphors so that advanced analytical capabilities are available with minimal user training.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Visual Information for the Desktop, version 1.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Visual_Inspection_of_Peak_Elution_Relationships__VIPER_.json b/agency-indexes/DoE/Visual_Inspection_of_Peak_Elution_Relationships__VIPER_.json new file mode 100644 index 00000000..71ad80e7 --- /dev/null +++ b/agency-indexes/DoE/Visual_Inspection_of_Peak_Elution_Relationships__VIPER_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "VIPER (Visual Inspection of Peak/Elution Relationships) can be used to visualize and characterize the features detected during LC-MS analyses.", + "laborHours": 106263.2, + "languages": [], + "name": "Visual Inspection of Peak/Elution Relationships (VIPER)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/VIPER", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Visual_Sample_Plan.json b/agency-indexes/DoE/Visual_Sample_Plan.json new file mode 100644 index 00000000..5994d22a --- /dev/null +++ b/agency-indexes/DoE/Visual_Sample_Plan.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-17", + "metadataLastUpdated": "2024-01-31" + }, + "description": "VSP selects the appropriate number and location of environmental samples to ensure that the results of statistical tests performed to provide input to risk decisions have the required confidence and performance. VSP Version 5.0 provides sample-size equations or algorithms needed by specific statistical tests appropriate for specific environmental sampling objectives. It also provides data quality assessment and statistical analysis functions to support evaluation of the data and determine whether the data support decisions regarding sites suspected of contamination. The easy-to-use program is highly visual and graphic. VSP runs on personal computers with Microsoft Windows operating systems (98, NT, 2000, Millennium Edition, CE, and XP) Designed primarily for project managers and users without expertise in statistics, VSP is applicable to two- and three-dimensional populations to be sampled (e.g., rooms and buildings, surface soil, a defined layer of subsurface soil, water bodies, and other similar applications) for studies of environmental quality. VSP is also applicable for designing sampling plans for assessing chem./rad/bio threat and hazard identification within rooms and buildings, and for designing geophysical surveys for UXO identification.", + "homepageURL": "https://www.pnnl.gov/projects/visual-sample-plan", + "laborHours": 0.0, + "languages": [], + "name": "Visual Sample Plan", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/projects/visual-sample-plan", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/projects/visual-sample-plan", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Visualization_Quality_Assessment.json b/agency-indexes/DoE/Visualization_Quality_Assessment.json new file mode 100644 index 00000000..dc17a04e --- /dev/null +++ b/agency-indexes/DoE/Visualization_Quality_Assessment.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-06-02" + }, + "description": "Understanding how inaccuracies in visualizations affect users\u2019 perception and understanding of scientific data is hard. Inaccuracies in visualizations are quite common and could arise from a range of sources such as errors in the original dataset arising from compression artifacts, errors in the capturing device, noise during transmission of the data, effects due to the algorithm being used to convert data to visualization images, images generated from neural networks, and sources we have yet to discover. Many image quality assessment metrics have been developed to quantify image errors. However, these are usually focused on \u201cnatural images\u201d rather than visualizations of scientific data. Common image quality assessment metrics (IQAs) include MSE, PSNR, perceptual metrics such SSIM, FSIM as well as perceptual metrics using deep learning approaches. However, a critical part of understanding how errors are perceived by humans, and subsequently developing more accurate quality assessment metrics, is through user evaluation studies.\n\nThe goal of this software is to develop a visualization quality assessment (VQA) process that will enable the generation of VQAs that can be used to quantify errors in scientific data visualizations. The VQA development process will include software to support user evaluation experimental design, analysis of visualization differences against standard quality metrics, and the ability to develop additional VQA metrics specific to scientific visualization images. ", + "laborHours": 0.0, + "languages": [], + "name": "Visualization Quality Assessment", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/vizStudy", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Visualization_Software_for_VisIT_Java_Client.json b/agency-indexes/DoE/Visualization_Software_for_VisIT_Java_Client.json new file mode 100644 index 00000000..f6a641fe --- /dev/null +++ b/agency-indexes/DoE/Visualization_Software_for_VisIT_Java_Client.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The VisIT Java Client (JVC) library is a lightweight thin client that is designed and written purely in the native language of Java (the Python & JavaScript versions of the library use the same concept) and communicates with any new unmodified standalone version of VisIT, a high performance computing parallel visualization toolkit, over traditional or web sockets and dynamically determines capabilities of the running VisIT instance whether local or remote.", + "laborHours": 1383.2, + "name": "Visualization Software for VisIT Java Client", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/visit-vis/visit_java_client/blob/master/gov.lbnl.visit.swt/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/visit-vis/visit_java_client", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VizBrick.json b/agency-indexes/DoE/VizBrick.json new file mode 100644 index 00000000..b32add9c --- /dev/null +++ b/agency-indexes/DoE/VizBrick.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "lees4@ornl.gov" + }, + "date": { + "created": "2022-06-09", + "metadataLastUpdated": "2022-06-23" + }, + "description": "Brick (https://brickschema.org/) is a unified metadata schema to address the problem of building data standardization. Creating Brick models for building datasets means that the contents of the datasets are semantically described using the standard terms defined in the Brick ontology, and it will enable the benefits of data standardization, without having to recollect or reorganize the data. The challenge is that building brick models for building datasets leads to repeated manual trial and error processes, which can be time-consuming. VizBrick is a tool with a graphic/Web-based user interface that can assist users to create Brick models visually and interactively without having to understand the Resource Description Framework (RDF) syntax. VizBrick contains a web server that renders VizBrick web interface pages for browsers. The web server utilizes software components that (1) provide Brick ontology entity mapping to data column suggestions to users so that they can efficiently create their model; (2) provide keyword/Metadata-based search capability for easy find of relevant brick concepts and relations to their data columns", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "VizBrick", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/liza183/vizbrick", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Volttime_[SWR_17-33].json b/agency-indexes/DoE/Volttime_[SWR_17-33].json new file mode 100644 index 00000000..aace01f9 --- /dev/null +++ b/agency-indexes/DoE/Volttime_[SWR_17-33].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2023-05-15" + }, + "description": "Volttime enables running a VOLTTRON experiment/simulation at a specific but arbitrary date, hour, minute, second and at faster or slower than actual time.", + "laborHours": 2158.4, + "languages": [ + "Python" + ], + "name": "Volttime [SWR 17-33]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/volttime/blob/master/TERMS.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/volttime", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/VoroCrust-Meshing_v.1.0.json b/agency-indexes/DoE/VoroCrust-Meshing_v.1.0.json new file mode 100644 index 00000000..8073780f --- /dev/null +++ b/agency-indexes/DoE/VoroCrust-Meshing_v.1.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-14", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-12900 O\nVoroCrust-Meshing is an automated code for Voronoi meshing, which is useful for many types of simulations in diverse fields. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 11278.4, + "languages": [ + "C++", + "Groovy", + "CMake" + ], + "name": "VoroCrust-Meshing v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/vorocrust-meshing", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Vulcan_Digital_Engineering_Application.json b/agency-indexes/DoE/Vulcan_Digital_Engineering_Application.json new file mode 100644 index 00000000..dd825f56 --- /dev/null +++ b/agency-indexes/DoE/Vulcan_Digital_Engineering_Application.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2021-08-20", + "metadataLastUpdated": "2023-03-13" + }, + "description": "The application is being developed with the goal of preventing the entropy of all the different single purpose applications. This application utilizes a framework that enables different file formats to be read and understood through plugins dynamically loaded to the main application containing the framework. The main application provides interoperability to all the different plugins, this allows each file format to convert to every other file format that has been read. There is no theoretical limit to the number of plugins that can be used by the application. Even though the plugins may be individually written and serve a purpose like single use scripts, the plugins can only be used with the main application, this forces the application and plugins to be linked. In theory this will force better data management, or at least the bundling of the main application with the plugins.", + "laborHours": 0.0, + "languages": [ + "C++", + "JavaScript" + ], + "name": "Vulcan Digital Engineering Application", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/VDEA", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Vulnerability_Research_Development_Program_Guide_v.1.json b/agency-indexes/DoE/Vulnerability_Research_Development_Program_Guide_v.1.json new file mode 100644 index 00000000..68465fa6 --- /dev/null +++ b/agency-indexes/DoE/Vulnerability_Research_Development_Program_Guide_v.1.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2024-09-09" + }, + "description": "SAND2021-15515 O\nThe Vulnerability Research Development Program (VRDP) Guide is a training program developed to help general purpose computer science staff become independently capable vulnerability researchers. VRDP Guide is both a course description and curriculum for the program. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 2234.4, + "languages": [ + "JavaScript", + "python", + "CSS", + "Shell", + "Makefile", + "HTML" + ], + "name": "Vulnerability Research Development Program Guide v.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/vrdp-snl-course", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WARP.json b/agency-indexes/DoE/WARP.json new file mode 100644 index 00000000..3db129fb --- /dev/null +++ b/agency-indexes/DoE/WARP.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "WARP, which can stand for ``Weaving All the Random Particles,'' is a three-dimensional (3D) continuous energy Monte Carlo neutron transport code developed at UC Berkeley to efficiently execute on NVIDIA graphics processing unit (GPU) platforms. WARP accelerates Monte Carlo simulations while preserving the benefits of using the Monte Carlo method, namely, that very few physical and geometrical simplifications are applied. WARP is able to calculate multiplication factors, neutron flux distributions (in both space and energy), and fission source distributions for time-independent neutron transport problems. It can run in both criticality or fixed source modes, but fixed source mode is currently not robust, optimized, or maintained in the newest version. WARP can transport neutrons in unrestricted arrangements of parallelepipeds, hexagonal prisms, cylinders, and spheres. The goal of developing WARP is to investigate algorithms that can grow into a full-featured, continuous energy, Monte Carlo neutron transport code that is accelerated by running on GPUs. The crux of the effort is to make Monte Carlo calculations faster while producing accurate results. Modern supercomputers are commonly being built with GPU coprocessor cards in their nodes to increase their computational efficiency and performance. GPUs execute efficiently on data-parallel problems, but most CPU codes, including those for Monte Carlo neutral particle transport, are predominantly task-parallel. WARP uses a data-parallel neutron transport algorithm to take advantage of the computing power GPUs offer.", + "laborHours": 7083.2, + "name": "WARP", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sellitforcache/warp/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sellitforcache/warp", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WAVES:_WAVES_Analysis_for_Verified_Engineering_Simulatio.json b/agency-indexes/DoE/WAVES:_WAVES_Analysis_for_Verified_Engineering_Simulatio.json new file mode 100644 index 00000000..e5c6a25d --- /dev/null +++ b/agency-indexes/DoE/WAVES:_WAVES_Analysis_for_Verified_Engineering_Simulatio.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-02-24", + "metadataLastUpdated": "2023-02-24" + }, + "description": "WAVES is a computational workflow tool that integrates parametric studies with traditional software build systems. In addition to the parametric study Python package and command line utilities, WAVES also includes task definitions for common computational software used by model simulation (modsim) repositories. The tutorial simulations in this project use SCons as the automated build system and translate software build system concepts in the language of simulation and analysis. This project includes a template WAVES modsim repository which is used for the tutorials and for integration and regression testing of the WAVES extensions to SCons.", + "laborHours": 0.0, + "languages": [], + "name": "WAVES: WAVES Analysis for Verified Engineering Simulatio", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/waves", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WAVES__Wind_Asset_Value_Estimation_System__[SWR-23-81].json b/agency-indexes/DoE/WAVES__Wind_Asset_Value_Estimation_System__[SWR-23-81].json new file mode 100644 index 00000000..89102a8b --- /dev/null +++ b/agency-indexes/DoE/WAVES__Wind_Asset_Value_Estimation_System__[SWR-23-81].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-11-27", + "metadataLastUpdated": "2023-12-20" + }, + "description": "The Wind Asset Value Estimation System (WAVES) model is a coupling framework for core NREL techno economic analysis software models to estimate capital expenditures (ORBIT), operational expenditures (WOMBAT), and energy production (FLORIS) for offshore wind power plants. Existing workflows to couple the three models for lifecycle performance and cost estimation require a large amount of manual and error-prone setup to combine both shared inputs and dependent outputs, as such WAVES's primary functionality is to wrap the core logic for running standard modeling workflows to ensure shared settings and entangled results are correctly and efficiently combined every time. SEE ALSO: https://pypi.org/project/WAVES/", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "WAVES (Wind Asset Value Estimation System) [SWR-23-81]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WAVES", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v0.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WEBAT__Wind_Energy_with_Bat_AI-based_Tracker__[SWR-24-121].json b/agency-indexes/DoE/WEBAT__Wind_Energy_with_Bat_AI-based_Tracker__[SWR-24-121].json new file mode 100644 index 00000000..58855b8e --- /dev/null +++ b/agency-indexes/DoE/WEBAT__Wind_Energy_with_Bat_AI-based_Tracker__[SWR-24-121].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-19", + "metadataLastUpdated": "2024-12-12" + }, + "description": "The WEBAT (Wind Energy with Bat AI-based Tracker) is a Python-based bat tracking software, integrating machine learning and computer vision with infrared thermal sensors to enhance the monitoring and protection of bats in proximity to wind turbines.", + "laborHours": 440.8, + "languages": [ + "Python", + "Shell" + ], + "name": "WEBAT (Wind Energy with Bat AI-based Tracker) [SWR-24-121]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WEBAT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WEC-GRID.json b/agency-indexes/DoE/WEC-GRID.json new file mode 100644 index 00000000..cf3afecf --- /dev/null +++ b/agency-indexes/DoE/WEC-GRID.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pcicilio@alaska.edu" + }, + "date": { + "created": "2023-09-27", + "metadataLastUpdated": "2023-09-27" + }, + "description": "WEC-GRID is an open-source Python library crafted to simulate the integration of Wave Energy Converters (WECs) and Current Energy Converters (CECs) into renowned power grid simulators like PSS\u00aeE & PyPSA.", + "laborHours": 0.0, + "languages": [], + "name": "WEC-GRID", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/acep-uaf/WEC-GRID", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WEC-Sim__Wave_Energy_Converter_-_SIMulator_.json b/agency-indexes/DoE/WEC-Sim__Wave_Energy_Converter_-_SIMulator_.json new file mode 100644 index 00000000..ca177db0 --- /dev/null +++ b/agency-indexes/DoE/WEC-Sim__Wave_Energy_Converter_-_SIMulator_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "WEC-Sim (Wave Energy Converter SIMulator) is a code developed by Sandia National Laboratories and the National Renewable Energy Laboratory to model wave energy converters (WECs) when they are subject to operational waves. The code is a time-domain modeling tool developed in MATLAB/Simulink using the multi-body dynamics solver SimMechanics. In WEC-Sim, WECs are modeled by connecting rigid bodies to one another with joint or constraint blocks from the WEC-Sim library. WEC-Sim is a publicly available, open-source code to model WECs.", + "laborHours": 3131.2, + "name": "WEC-Sim (Wave Energy Converter - SIMulator)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WEC-Sim/WEC-Sim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WEC_Design_Response_Toolbox_v._1.0.json b/agency-indexes/DoE/WEC_Design_Response_Toolbox_v._1.0.json new file mode 100644 index 00000000..9ebd5426 --- /dev/null +++ b/agency-indexes/DoE/WEC_Design_Response_Toolbox_v._1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-26" + }, + "description": "The WEC Design Response Toolbox (WDRT) is a numerical toolbox for design-response analysis of wave energy converters (WECs). The WDRT was developed during a series of efforts to better understand WEC survival design. The WDRT has been designed as a tool for researchers and developers, enabling the straightforward application of statistical and engineering methods. The toolbox includes methods for short-term extreme response, environmental characterization, long-term extreme response and risk analysis, fatigue, and design wave composition.", + "laborHours": 537806.4, + "languages": [ + "Powershell", + "Python" + ], + "name": "WEC Design Response Toolbox v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/WDRT", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WETO_Stack_[SWR-24-81].json b/agency-indexes/DoE/WETO_Stack_[SWR-24-81].json new file mode 100644 index 00000000..cf6e06a1 --- /dev/null +++ b/agency-indexes/DoE/WETO_Stack_[SWR-24-81].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2025-03-26" + }, + "description": "The WETO Stack software is a collection of data, data analysis scripts, and website content produced through the Holistic Modeling Project\u2019s Portfolio Coordination task. The purpose of the software is to characterize the collection of wind energy software projects supported by the U.S. Department of Energy\u2019s Wind Energy Technologies Office. The included data contains characteristics of the actively funded software projects, and the data analysis scripts provide insights into the breadth, depth, and maturity of the collection of software projects. The website content presents the results of the analyses as well as reports from workshops and other events. It can be viewed at https://nrel.github.io/WETOStack/index.html.", + "homepageURL": "https://github.com/NREL/WETOStack", + "laborHours": 5076.8, + "languages": [ + "Python", + "TeX", + "Makefile" + ], + "name": "WETO Stack [SWR-24-81]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://creativecommons.org/licenses/by-nc-nd/4.0/?ref=chooser-v1", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://github.com/NREL/WETOStack", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WHATSUP_Version1.3.json b/agency-indexes/DoE/WHATSUP_Version1.3.json new file mode 100644 index 00000000..50a31500 --- /dev/null +++ b/agency-indexes/DoE/WHATSUP_Version1.3.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "WHATSUP determines which nodes in a cluster are up and which nodes are down.", + "laborHours": 58793.6, + "name": "WHATSUP Version1.3", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/whatsup", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WHO_FLUMART_scraper.json b/agency-indexes/DoE/WHO_FLUMART_scraper.json new file mode 100644 index 00000000..7603f2d8 --- /dev/null +++ b/agency-indexes/DoE/WHO_FLUMART_scraper.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-09-15", + "metadataLastUpdated": "2022-09-15" + }, + "description": "This code scrapes global influenza data that are publicly provided by the World Health Organization (WHO) through an interface called FLUMART.", + "laborHours": 0.0, + "languages": [], + "name": "WHO FLUMART scraper", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/WHO-FLUMART-scraper", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WIND_Toolkit_Highly_Scalable_Data_Service__HSDS__API_Examples_[SWR-18-05].json b/agency-indexes/DoE/WIND_Toolkit_Highly_Scalable_Data_Service__HSDS__API_Examples_[SWR-18-05].json new file mode 100644 index 00000000..0045babf --- /dev/null +++ b/agency-indexes/DoE/WIND_Toolkit_Highly_Scalable_Data_Service__HSDS__API_Examples_[SWR-18-05].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-19", + "metadataLastUpdated": "2025-03-03" + }, + "description": "The WIND Toolkit Highly Scalable Data Service (HSDS) API examples provide example python software notebooks (software) and a javascript visualization that demonstrate use of the HDF Group's HSDS API utilizing data for NREL's WIND Toolkit.", + "laborHours": 699.2, + "languages": [ + "Jupyter Notebook" + ], + "name": "WIND Toolkit Highly Scalable Data Service (HSDS) API Examples [SWR-18-05]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/hsds-examples", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/WISDEM\302\256__Wind-Plant_Integrated_System_Design_and_Engineering_Model__[SWR-14-05].json" "b/agency-indexes/DoE/WISDEM\302\256__Wind-Plant_Integrated_System_Design_and_Engineering_Model__[SWR-14-05].json" new file mode 100644 index 00000000..9deac884 --- /dev/null +++ "b/agency-indexes/DoE/WISDEM\302\256__Wind-Plant_Integrated_System_Design_and_Engineering_Model__[SWR-14-05].json" @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2024-05-02" + }, + "description": "The Wind-Plant Integrated System Design and Engineering Model (WISDEM\u00ae) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM\u00ae is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM\u00ae turbine design capability. Please install all of the pre-requisites prior to installing WISDEM\u00ae by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM\u00ae development, please visit the official NREL systems engineering for wind energy website. https://www.nrel.gov/wind/systems-engineering.html", + "laborHours": 229778.4, + "languages": [ + "C", + "Fortran", + "Python" + ], + "name": "WISDEM\u00ae (Wind-Plant Integrated System Design and Engineering Model) [SWR-14-05]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/WISDEM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.4.1" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/WISDEM\302\256_v3.15.2_2024__Wind-Plant_Integrated_System_Design_and_Engineering_Model__[SWR-14-05].json" "b/agency-indexes/DoE/WISDEM\302\256_v3.15.2_2024__Wind-Plant_Integrated_System_Design_and_Engineering_Model__[SWR-14-05].json" new file mode 100644 index 00000000..369bff60 --- /dev/null +++ "b/agency-indexes/DoE/WISDEM\302\256_v3.15.2_2024__Wind-Plant_Integrated_System_Design_and_Engineering_Model__[SWR-14-05].json" @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-05-02", + "metadataLastUpdated": "2024-05-02" + }, + "description": "The Wind-Plant Integrated System Design and Engineering Model (WISDEM\u00ae) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM\u00ae is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM\u00ae turbine design capability. Please install all of the pre-requisites prior to installing WISDEM\u00ae by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM\u00ae development, please visit the official NREL systems engineering for wind energy website. https://www.nrel.gov/wind/systems-engineering.html", + "laborHours": 229778.4, + "languages": [ + "C", + "Fortran", + "Python" + ], + "name": "WISDEM\u00ae v3.15.2 2024 (Wind-Plant Integrated System Design and Engineering Model) [SWR-14-05]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/WISDEM", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v3.15.2" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/WOMBAT__Windfarm_Operations_and_Maintenance_cost-Benefit_Analysis_Tool__WISDEM\302\256_[SWR-21-68].json" "b/agency-indexes/DoE/WOMBAT__Windfarm_Operations_and_Maintenance_cost-Benefit_Analysis_Tool__WISDEM\302\256_[SWR-21-68].json" new file mode 100644 index 00000000..09c573c5 --- /dev/null +++ "b/agency-indexes/DoE/WOMBAT__Windfarm_Operations_and_Maintenance_cost-Benefit_Analysis_Tool__WISDEM\302\256_[SWR-21-68].json" @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-06-07", + "metadataLastUpdated": "2024-10-25" + }, + "description": "The windfarm operations and maintenance cost-benefit analysis tool (WOMBAT) is software to simulate the operations and maintenance phase of either onshore or offshore windfarms. WOMBAT is a medium-fidelity tool that is designed to model turbine, cable, and substation failures at the subassembly level, but is flexible enough that individual component or asset-level modeling can also be performed. WOMBAT enables users to model technological improvements, the use of a wide range of service equipment from drone repairs and remote resets to heavy lift vessels and crawler cranes, to analyze cost trends with varying trade-offs in conjunction with energy production, availability and a growing range of metrics. \n\nThis library provides a tool to simulate the operation and maintenance phase (O&M) of distributed, land-based, and offshore windfarms using a discrete event simulation framework.\n\nWOMBAT is written around the SimPy discrete event simulation framework. Additionally, this is supported using a flexible and modular object-oriented code base, which enables the modeling of arbitrarily large (or small) windfarms with as many or as few failure and maintenance tasks that can be encoded.\n\nPlease note that this is still heavily under development, so you may find some functionality to be incomplete at the current moment, but rest assured the functionality is expanding. With that said, it would be greatly appreciated for issues or PRs to be submitted for any improvements at all, from fixing typos (guaranteed to be a few) to features to testing.\n\nAlso available at: https://pypi.org/project/wombat/", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "WOMBAT (Windfarm Operations and Maintenance cost-Benefit Analysis Tool) WISDEM\u00ae [SWR-21-68]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WISDEM/WOMBAT", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "V0.9.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WOODCOM.json b/agency-indexes/DoE/WOODCOM.json new file mode 100644 index 00000000..2ffc2ed2 --- /dev/null +++ b/agency-indexes/DoE/WOODCOM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2019-05-14", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Woody Biomass Companion Markets Model", + "laborHours": 15.2, + "languages": [], + "name": "WOODCOM", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabResearch/WOODCOM", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WORM__Write_One,_Read_Many_.json b/agency-indexes/DoE/WORM__Write_One,_Read_Many_.json new file mode 100644 index 00000000..33a9894f --- /dev/null +++ b/agency-indexes/DoE/WORM__Write_One,_Read_Many_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "WORM (Write One, Run Many) is an easy to use, cross platform, embedded and extensible, functional programming language designed to facilitate the creation of input-decks for computer codes that use standard ASCII text files for input. WORM makes it easy to create generic (yet, complex and powerful) reusable models. Additionally its nature allows for complex calculations and routines to be coded once and easily reused, further simplifying the creation of input decks. WORM (Write One, Run Many) is a powerful and versatile tool designed to improve the efficiency of today\u2019s criticality safety analyst by allowing: + input decks for parametric studies to be created quickly and easily, + calculations and variables to be imbedded into any input deck, thus allowing for meaningful parameter specifications, + problems to be specified using any combination of units, and + complex mathematically defined models to be created. A very simple syntax is employed, and therefore the WORM is easy to learn. A WORM model is essentially a standard input deck with some of its numerical values replaced by WORM code. WORM code may include and evaluate the following mathematical operators and functions: addition, subtraction, multiplication, division, exponentiation, modulus, sine, cosine, tangent, arcsine, arccosine, arctangent, the natural logarithm, logarithm base 10, integer truncation, absolute value, and random number. Several common constants, e.g., pi, e, and Avogadros\u2019s Number (both as 6.022e23 and 0.6022), are predefined in WORM. Additionally, many unit conversion factors are also predefined: millimeters, meters, inches, feet, yards, and mils to centimeters; kilograms, pounds, and ounces to grams; liters, milliliters, gallons, and fluid ounces to cubic centimeters; and angular degrees to radians. For parametric studies, WORM supports various shorthand list specifications: the explicit step size, linear interpolation, and logarithmic interpolation. The list notation sequentially assigns multiple values to a name. WORM creates an input deck for each value of the name. If multiple lists are used, WORM steps through each list individually, i.e., WORM creates input decks corresponding to each and every permutation of the list values. Additionally, a library of standard material definitions and Perl subroutines are included. Any one of these files can be incorporated into the subject model with a simple WORM read command. WORM is completely written in Perl, the Practical Extraction and Reporting Language. Perl is one of the most portable programming languages available today. As such, the WORM works on practically any computer platform.", + "laborHours": 0.0, + "languages": [], + "name": "WORM (Write One, Read Many)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rsartor-lanl/worm-1.7.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WPGNN_and_PLayGen__Wind_Plant_Graph_Neural_Network_and_Plant_Layout_Generator__[SWR-21-90].json b/agency-indexes/DoE/WPGNN_and_PLayGen__Wind_Plant_Graph_Neural_Network_and_Plant_Layout_Generator__[SWR-21-90].json new file mode 100644 index 00000000..55abc683 --- /dev/null +++ b/agency-indexes/DoE/WPGNN_and_PLayGen__Wind_Plant_Graph_Neural_Network_and_Plant_Layout_Generator__[SWR-21-90].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-05-06", + "metadataLastUpdated": "2023-10-25" + }, + "description": "WPGNN is the graph neural network machine learning based surrogate model and software that provides a streamlined approximation of wind plant wake models. It can rapidly estimate the energy production of the plant and turbines for any arbitrarily sized wind plant and layout under any inflow condition. Associated tools include graphing and visualization capabilities as well as a wind plant generator capable of creating randomized realizations of canonical wind plant layouts. The WPGNN architecture and application is extendable to multiple wake models, turbine technologies and features, and supports downstream optimizations of wind plant layouts and control strategies. In addition to the WPGNN, we include the code for the plant layout generator (PLayGen) playgen.py. This generator can produce random realizations of realistic wind plant layouts from one of the four canonical styles: cluster, single string, multiple string, or parallel string. The PLayGen_demo.ipynb notebook provides a demonstration of how to use the generator tool.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "WPGNN and PLayGen (Wind Plant Graph Neural Network and Plant Layout Generator) [SWR-21-90]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WPGNN", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/WUFI__W\303\244rme_and_Feuchte_Instation\303\244r_-Oak_Ridge_National_Laboratory__ORNL__Fraunhofer_IBP.json" "b/agency-indexes/DoE/WUFI__W\303\244rme_and_Feuchte_Instation\303\244r_-Oak_Ridge_National_Laboratory__ORNL__Fraunhofer_IBP.json" new file mode 100644 index 00000000..31e3e30a --- /dev/null +++ "b/agency-indexes/DoE/WUFI__W\303\244rme_and_Feuchte_Instation\303\244r_-Oak_Ridge_National_Laboratory__ORNL__Fraunhofer_IBP.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-15" + }, + "description": "WUFI - Oak Ridge National Laboratory (ORNL)/Fraunhofer IBP is a menu-driven PC program which allows realistic calculation of the transient coupled one-dimensional heat and moisture transport in multi-layer building components exposed to natural weather. It is based on the newest findings regarding vapor diffusion and liquid transport in building materials and has been validated by detailed comparison with measurements obtained in the laboratory and on outdoor testing fields. Together with Oak Ridge National Laboratory (ORNL) Fraunhofer IBP has developed a special version of WUFI \u00ae for North America. WUFI\u00ae ORNL is a functionally limited free version of WUFI\u00ae Pro for non-commercial purposes. It contains climate data for 62 cities in the USA and Canada which are all available in the free version.", + "homepageURL": "https://web.ornl.gov/sci/buildings/tools/wufi", + "laborHours": 0.0, + "languages": [], + "name": "WUFI (W\u00e4rme and Feuchte Instation\u00e4r)-Oak Ridge National Laboratory (ORNL)/Fraunhofer IBP", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://web.ornl.gov/sci/buildings/tools/wufi", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://web.ornl.gov/sci/buildings/tools/wufi", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/WVL.json b/agency-indexes/DoE/WVL.json new file mode 100644 index 00000000..b02c2fd1 --- /dev/null +++ b/agency-indexes/DoE/WVL.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "The software runs using the Priithon image analysis platform (https://github.com/sebhaase/priithon), which is part of this release. The version of this mac distribution is: Priithon_27_mac-20151127, which expands to a folder named Priithon_27_mac. The paper is the reference source for the wavelet algorithm in this distribution; \"A novel 3D wavelet-based filter for visualizing features in noisy biological data,\" J. Microsc. 219, 43-49 (2005). This distribution has been tested on Mac OS 10.9.5, 10.10.3, and 10.11.1\n", + "laborHours": 1069350.4, + "languages": [], + "name": "WVL", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/WVL", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Warewulf_3.0.json b/agency-indexes/DoE/Warewulf_3.0.json new file mode 100644 index 00000000..b44d9495 --- /dev/null +++ b/agency-indexes/DoE/Warewulf_3.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Warewulf is a scalable systems management suite originally developed to manage large high-performance Linux clusters. Focused on general scalable systems management, it includes a framework for system configuration, management, provisioning/installation, monitoring, event notification, and more via a modular plugin architecture. Install the components and features you need or leverage the existing system configuration stored within Warewulf to create custom solutions to meet your performance needs. One of the goals of the project is to grow the project by allowing other organizations and developers to contribute back to the project under an open source BSD license. We have been successful with gaining support within the open source community already and have contributors and support in not only the government and academic space but also the commercial sector (e.g. Intel). Being both open source and vendor neutral puts Warewulf in a unique position to be supported and utilized as an open standard in High Performance Computing (HPC). Warewulf is an active member of various HPC initiatives and groups and is considered one of the most utilized, extensible and scalable clustering toolkits available.", + "laborHours": 0.0, + "languages": [], + "name": "Warewulf 3.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://warewulf.lbl.gov/trac/browser/trunk/common/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/warewulf/warewulf3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WarpX_v0.1.0.json b/agency-indexes/DoE/WarpX_v0.1.0.json new file mode 100644 index 00000000..e99899b0 --- /dev/null +++ b/agency-indexes/DoE/WarpX_v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-30", + "metadataLastUpdated": "2019-09-23" + }, + "description": "WarpX is a fully electromagnetic Particle-In-Cell code for the modeling of plasma-based particle accelerators. The code includes unique features such as mesh refinement and arbitrary-order analytical pseudo-spectral Maxwell solvers.", + "laborHours": 23712.0, + "languages": [], + "name": "WarpX v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ECP-WarpX/WarpX", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Watchdog_for_ARM_Radar_Network_Operations.json b/agency-indexes/DoE/Watchdog_for_ARM_Radar_Network_Operations.json new file mode 100644 index 00000000..04c3fa5a --- /dev/null +++ b/agency-indexes/DoE/Watchdog_for_ARM_Radar_Network_Operations.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "WARNO is a software system designed to monitor the radars in the ARM Radar Network. It allows real time monitoring and tracking of instrument state and condition. It provides a web portal on the front end to interact with users, a REST API webpoint for interactions with third party systems, and an internal distributed architecture to allow it to be deployed at multiple sites.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Watchdog for ARM Radar Network Operations", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ARM-DOE/warno/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ARM-DOE/warno", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Watchr_3.0.0.json b/agency-indexes/DoE/Watchr_3.0.0.json new file mode 100644 index 00000000..72ae0fb5 --- /dev/null +++ b/agency-indexes/DoE/Watchr_3.0.0.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-02-15", + "metadataLastUpdated": "2021-05-18" + }, + "description": "SAND2021-0624 O Watchr is a Jenkins plugin for tracking the performance of subroutines over many individual builds. It reads build-generated performance reports and displays the data contained in these performance reports as a series of graphs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Java", + "JavaScript", + "Java", + "Java" + ], + "name": "Watchr 3.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/watchr-jenkins/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/watchr-jenkins", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Water,_Energy_and_Carbon_Sequestration_Model__WECSsim__v._1.0.json b/agency-indexes/DoE/Water,_Energy_and_Carbon_Sequestration_Model__WECSsim__v._1.0.json new file mode 100644 index 00000000..09a9c5b8 --- /dev/null +++ b/agency-indexes/DoE/Water,_Energy_and_Carbon_Sequestration_Model__WECSsim__v._1.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-08-06" + }, + "description": "The national Water, Energy and Carbon Sequestration Simulation Model (WECSsim) is an analysis tool that can be used at the local, regional and national scale to address a potentially combined system using a coal or natural gas-fired power plant, a geologic carbon sequestration system in saline formations, and water extraction and treatment. With this combined system for geologic storage of CO2 in saline formations, the treated saline formation water could be used as cooling water in the power plant. The key areas addressed in this tool include applying a data reduction process to existing NatCarb saline formation data to select the most viable formations for CO2 injection, water withdrawal and treatment metrics, and developing a national model to address the multiple combinations of power plants and saline formations. This model can be utilized by decision makers to understand the economic benefits and tradeoffs of this combined system. WECSsim allows for sensitivity analyses for capital costs, variables costs, CO2 sequestration and water treatment systems' costs. The main goal of the WECSsim model is to allow interested individuals or groups the ability to run custom power plant, CO2 sequestration and water use scenarios for different regions of the country and understand the associated economics, longevity and potential of the CO2 sequestration and water extraction systems.", + "laborHours": 0.0, + "languages": [ + "PowerSim Studio 7" + ], + "name": "Water, Energy and Carbon Sequestration Model (WECSsim) v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/WECSSim", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WaterModelsAnalytics.jl.json b/agency-indexes/DoE/WaterModelsAnalytics.jl.json new file mode 100644 index 00000000..8391472f --- /dev/null +++ b/agency-indexes/DoE/WaterModelsAnalytics.jl.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-08-10", + "metadataLastUpdated": "2020-08-10" + }, + "description": "WaterModelsAnalytics.jl is an analytics package for visualizing water distribution networks in Julia.", + "laborHours": 4012.8, + "languages": [ + "Julia", + "Julia" + ], + "name": "WaterModelsAnalytics.jl", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL-SIIP/WaterModelsAnalytics.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WaterSystems.jl.json b/agency-indexes/DoE/WaterSystems.jl.json new file mode 100644 index 00000000..d888fccc --- /dev/null +++ b/agency-indexes/DoE/WaterSystems.jl.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-17" + }, + "description": "WaterSystems.jl is a Julia package for defining water delivery infrastructure system data and problem definitions. The WaterSystems.jl package enables parsing from the EPANET *.inp file format and the expression of data for WaterSimulations.jl models. WaterSystems.jl defines a data schema for water infrastructure networks. ", + "laborHours": 167.2, + "languages": [ + "julia" + ], + "name": "WaterSystems.jl", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WaterSystems.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WaterTAP3__The_Water_Technoeconomic_Assessment_Pipe-Parity_Platform_.json b/agency-indexes/DoE/WaterTAP3__The_Water_Technoeconomic_Assessment_Pipe-Parity_Platform_.json new file mode 100644 index 00000000..4b24f6c1 --- /dev/null +++ b/agency-indexes/DoE/WaterTAP3__The_Water_Technoeconomic_Assessment_Pipe-Parity_Platform_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-07-08", + "metadataLastUpdated": "2021-10-01" + }, + "description": "The Water Technoeconomic Assessment Pipe-Parity Platform (WaterTAP3) was developed under the National Alliance for Water Innovation (NAWI) to facilitate consistent technoeconomic assessments of desalination treatment trains. The WaterTAP3 is an analytically robust modeling tool that can be used to evaluate water technology cost, energy, environmental, and resiliency tradeoffs across different water sources, sectors, and scales. The model simulates steady-state water treatment train performance and costs including flow and constituent mass balance across unit processes, based on source water conditions, configurations of treatment technologies, and system-level techno-economic assumptions. Users can build a new treatment train by connecting any number of unit processes, specific for their context and system, or selecting a train from the treatment train library. The model contains various technical and cost parameter options for a range of treatment processes and a library of influent water quality characteristics for a variety of source waters and case studies. Users can customize water quality parameters to evaluate the technology performance in their context. The model can be set up for different assessment needs including simulation, optimization, and uncertainty and sensitivity analyses. The results from WaterTAP3 can help identify trade-offs among the different system performance metrics, with insight on how particular technologies or systems promote pipe-parity. The flexibility and comprehensive scope of the tool makes it a promising solution to industry-wide water technoeconomic evaluations, leading to more informed water investment decisions and technologies. As a user-friendly, open-source platform, WaterTAP3 can be used by industry, academia, policymakers, planners, and those with or without extensive analytical experience.", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "WaterTAP3 (The Water Technoeconomic Assessment Pipe-Parity Platform)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WaterTAP3", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WaterTAP_v1.0.0.json b/agency-indexes/DoE/WaterTAP_v1.0.0.json new file mode 100644 index 00000000..27b1b3f9 --- /dev/null +++ b/agency-indexes/DoE/WaterTAP_v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-05-27", + "metadataLastUpdated": "2022-06-13" + }, + "description": "WaterTAP is a new open source library of water-specific models built on the IDAES Integrated Platform to support the design and optimization of integrated water treatment systems, improve existing systems and enable the analysis of new designs incorporating emerging technologies. WaterTAP enables advanced modeling and optimization for: conceptual and multiscale design, dynamics and model predictive control of water systems and networks.", + "laborHours": 0.0, + "languages": [], + "name": "WaterTAP v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/watertap-org/watertap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Water_Energy_Simulation_Toolset.json b/agency-indexes/DoE/Water_Energy_Simulation_Toolset.json new file mode 100644 index 00000000..bf32f12b --- /dev/null +++ b/agency-indexes/DoE/Water_Energy_Simulation_Toolset.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The Water-Energy Simulation Toolset (WEST) is an interactive simulation model that helps visualize impacts of different stakeholders on water quantity and quality of a watershed. The case study is applied for the Snake River Basin with the fictional name Cutthroat River Basin. There are four groups of stakeholders of interest: hydropower, agriculture, flood control, and environmental protection. Currently, the quality component depicts nitrogen-nitrate contaminant. Users can easily interact with the model by changing certain inputs (climate change, fertilizer inputs, etc.) to observe the change over the entire system. Users can also change certain parameters to test their management policy.", + "laborHours": 0.0, + "languages": [], + "name": "Water Energy Simulation Toolset", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/WEST", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Water_Network_Tool_for_Resilience__WNTR_.json b/agency-indexes/DoE/Water_Network_Tool_for_Resilience__WNTR_.json new file mode 100644 index 00000000..d09abd94 --- /dev/null +++ b/agency-indexes/DoE/Water_Network_Tool_for_Resilience__WNTR_.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "The Water Network Tool for Resilience (WNTR) is an open source Python package designed to simulate and analyze resilience of water distribution networks. The United States Environmental Protection Agency, in partnership with Sandia National Laboratories, developed WNTR to integrate critical aspects of resilience modeling for water distribution networks into a single software framework.\nThe software includes capability to:\n\u2022\tGenerate water network models\n\u2022\tModify network structure and operations\n\u2022\tAssign fragility and survival curves to network components\n\u2022\tModel disruptive events such as power outages, earthquakes, fires, pipe breaks, and contamination incidents\n\u2022\tModel response and repair strategies\n\u2022\tSimulate hydraulics and water quality\n\u2022\tEvaluate resilience using a wide range of metrics\n\u2022\tIntegrate dependency with other critical infrastructure and supply chains\n\u2022\tAnalyze results and generate graphics\nSAND2019-450 M", + "laborHours": 147561.6, + "languages": [ + "C++", + "C", + "Python" + ], + "name": "Water Network Tool for Resilience (WNTR)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/WNTR", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Water_Security_Toolkit.json b/agency-indexes/DoE/Water_Security_Toolkit.json new file mode 100644 index 00000000..7cc9fb93 --- /dev/null +++ b/agency-indexes/DoE/Water_Security_Toolkit.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The Water Security Toolkit (WST) provides software for modeling and analyzing water distribution systems to minimize the potential impact of contamination incidents. WST wraps capabilities for contaminant transport, impact assessment, and sensor network design with response action plans, including source identification, rerouting, and decontamination, to provide a range of water security planning and real-time applications.", + "laborHours": 695460.8, + "languages": [ + "C++", + "HTML", + "C", + "JavaScript", + "M4", + "Python" + ], + "name": "Water Security Toolkit", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/Water-Security-Toolkit?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Water-Security-Toolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Water_Technoeconomic_Assessment_Pipe-Parity_Platform__WaterTAP3_.json b/agency-indexes/DoE/Water_Technoeconomic_Assessment_Pipe-Parity_Platform__WaterTAP3_.json new file mode 100644 index 00000000..f41f7bfa --- /dev/null +++ b/agency-indexes/DoE/Water_Technoeconomic_Assessment_Pipe-Parity_Platform__WaterTAP3_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2021-10-01", + "metadataLastUpdated": "2021-10-01" + }, + "description": "The Water Technoeconomic Assessment Pipe-Parity Platform (WaterTAP3) was developed under the National Alliance for Water Innovation (NAWI) to facilitate consistent technoeconomic assessments of desalination treatment trains. The WaterTAP3 is an analytically robust modeling tool that can be used to evaluate water technology cost, energy, environmental, and resiliency tradeoffs across different water sources, sectors, and scales. The model simulates steady-state water treatment train performance and costs including flow and constituent mass balance across unit processes, based on source water conditions, configurations of treatment technologies, and system-level techno-economic assumptions. Users can build a new treatment train by connecting any number of unit processes, specific for their context and system, or selecting a train from the treatment train library. The model contains various technical and cost parameter options for a range of treatment processes and a library of influent water quality characteristics for a variety of source waters and case studies. Users can customize water quality parameters to evaluate the technology performance in their context. The model can be set up for different assessment needs including simulation, optimization, and uncertainty and sensitivity analyses. The results from WaterTAP3 can help identify trade-offs among the different system performance metrics, with insight on how particular technologies or systems promote pipe-parity. The flexibility and comprehensive scope of the tool makes it a promising solution to industry-wide water technoeconomic evaluations, leading to more informed water investment decisions and technologies. As a user-friendly, open-source platform, WaterTAP3 can be used by industry, academia, policymakers, planners, and those with or without extensive analytical experience. A publicly available graphical user interface is currently under development.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Water Technoeconomic Assessment Pipe-Parity Platform (WaterTAP3)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WaterTAP3", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Water_and_Heat_Balance_Model_for_Predicting_Drainage_Below_the_Plant_Root_Zone.json b/agency-indexes/DoE/Water_and_Heat_Balance_Model_for_Predicting_Drainage_Below_the_Plant_Root_Zone.json new file mode 100644 index 00000000..aa56a640 --- /dev/null +++ b/agency-indexes/DoE/Water_and_Heat_Balance_Model_for_Predicting_Drainage_Below_the_Plant_Root_Zone.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2022-11-10" + }, + "description": "UNSAT-H Version 2.0 is a one-dimensional model that simulates the dynamic processes of infiltration, drainage, redistribution, surface evaporation, and the uptake of water from soil by plants. The model was developed for assessing the water dynamics of arid sites used or proposed for near-surface waste disposal. In particular, the model is used for simulating the water balance of cover systems over buried waste and for estimating the recharge rate (i.e., the drainage rate beneath the plant root zone when a sizable vadose zone is present). The mathematical base of the model are Richards'' equation for water flow, Ficks'' law for vapor diffusion, and Fouriers law for heat flow. The simulated profile can be homogeneous or layered. The boundary conditions can be controlled as either constant (potential or temperature) or flux conditions to reflect actual conditions at a given site.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Water and Heat Balance Model for Predicting Drainage Below the Plant Root Zone", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Watershed_Workflow.json b/agency-indexes/DoE/Watershed_Workflow.json new file mode 100644 index 00000000..c7b74a95 --- /dev/null +++ b/agency-indexes/DoE/Watershed_Workflow.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "coonet@ornl.gov" + }, + "date": { + "created": "2021-10-08", + "metadataLastUpdated": "2021-10-08" + }, + "description": "Watershed Workflow aims to lower the bar on leveraging open data products in hyperresolution watershed hydrologic models. Integrated, distributed hydrologic models of watersheds require large amounts and complexity of data including meteorological forcing datasets; land cover datasets; watershed geometry, hydrogography, and elevation datasets; and subsurface soil and rock structural datasets. Increasingly open data products meeting this need are available through U.S. governmental and other agencies via APIs and other electronic means, but are not available in the same format, through the same API, or in the same coordinate system as one another, and present other challenges in manipulations across scales. This product automates the discovery, download, curation, and integration of these types of datasets into a common format for use with hydrologic models.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Watershed Workflow", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ecoon/watershed-workflow", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Wattile:_Probabilistic_Deep_Learning-based_Forecasting_of_Building_Energy_Consumption_[SWR-20-94].json b/agency-indexes/DoE/Wattile:_Probabilistic_Deep_Learning-based_Forecasting_of_Building_Energy_Consumption_[SWR-20-94].json new file mode 100644 index 00000000..e74dd9b4 --- /dev/null +++ b/agency-indexes/DoE/Wattile:_Probabilistic_Deep_Learning-based_Forecasting_of_Building_Energy_Consumption_[SWR-20-94].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-03-30", + "metadataLastUpdated": "2023-04-06" + }, + "description": "Accurate energy forecasting is becoming critical due to many reasons: i ) optimal distributed energy resources operations and dispatch, ii) fault detection and diagnostics, and iii) meeting operational energy efficiency targets. Wattile uses deep learning (DL) for the building's short-term load forecasting application. Two specific types of neural networks called, Long Short Term Memory (LSTM) and Sequence-to-Sequence (S2S) models are used to make predictions. Forecasting models are trained using online historical weather and occupancy indicator data streams from the Intelligent Campus Program's data acquisition systems at the National Renewable Energy Laboratory (NREL) for main meters and sub-meters of multiple building types. These models use probabilistic methods to provide quantile-based forecasts in addition to nominal conditional median predictions of electricity consumption.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook" + ], + "name": "Wattile: Probabilistic Deep Learning-based Forecasting of Building Energy Consumption [SWR-20-94]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/Wattile", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Wcomp__Wind_Farm_Wake_Comparison_Framework__[SWR-23-72].json b/agency-indexes/DoE/Wcomp__Wind_Farm_Wake_Comparison_Framework__[SWR-23-72].json new file mode 100644 index 00000000..ed6028c5 --- /dev/null +++ b/agency-indexes/DoE/Wcomp__Wind_Farm_Wake_Comparison_Framework__[SWR-23-72].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-07-25", + "metadataLastUpdated": "2023-11-13" + }, + "description": "The Wind Farm Wake Comparison Framework (Wcomp) is a software tool to facilitate the comparison of a specific collection of wind farm wake modeling tools: Python-based, steady-state, analytical wake modeling utilities. Wcomp integrates another software project, windIO, to create a consistent method for describing a wind farm flow control problem. Additionally, a data structure is included to represent the outputs a wind farm flow control simulation. Well-described interfaces allow existing wake modeling tools to plug into this framework.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Wcomp (Wind Farm Wake Comparison Framework) [SWR-23-72]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nrel/wcomp", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Weak-Form_Latent_Space_Dynamics_Identification.json b/agency-indexes/DoE/Weak-Form_Latent_Space_Dynamics_Identification.json new file mode 100644 index 00000000..813049c3 --- /dev/null +++ b/agency-indexes/DoE/Weak-Form_Latent_Space_Dynamics_Identification.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-04", + "metadataLastUpdated": "2024-09-04" + }, + "description": "This software showcases the enhanced capabilities of the Latent Space Dynamics Identification (LaSDI)\nalgorithm through the application of the weak form, resulting in WLaSDI. WLaSDI first compresses the\ndata, then projects it onto test functions, and subsequently learns the local latent space models. Notably,\nWLaSDI demonstrates significantly improved robustness to noise. Using weak-form equation learning\ntechniques, WLaSDI achieves local latent space modeling. Compared to the standard sparse\nidentification of nonlinear dynamics (SINDy) used in LaSDI, the variance reduction of the weak form\nensures robust and precise latent space recovery, enabling fast, robust, and accurate simulations.\nWe demonstrate the efficacy of WLaSDI against LaSDI using several common benchmark examples,\nincluding viscid and inviscid Burgers', radial advection, and heat conduction. For instance, in 1D inviscid\nBurgers' simulations with up to 100% Gaussian white noise, WLaSDI maintains relative errors\nconsistently below 6%, whereas LaSDI errors can exceed 10,000%. Similarly, in radial advection\nsimulations, WLaSDI keeps relative errors below 16%, compared to potential errors of up to 10,000% with\nLaSDI. Additionally, WLaSDI achieves significant speedups, such as a 140X speedup in 1D Burgers'\nsimulations compared to the corresponding full order model.", + "laborHours": 2690.4, + "languages": [], + "name": "Weak-Form Latent Space Dynamics Identification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MathBioCU/PyWLaSDI", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Weak_Simulation_v.0.1.json b/agency-indexes/DoE/Weak_Simulation_v.0.1.json new file mode 100644 index 00000000..7b19f563 --- /dev/null +++ b/agency-indexes/DoE/Weak_Simulation_v.0.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-08-18", + "metadataLastUpdated": "2021-08-18" + }, + "description": "The SPARSIFY algorithm implemented by the code allows for classical simulation of universal quantum computer sample outcomes. The code sparsifies the stabilizer decomposition of a qubit t-tensored T gate magic state to some additive error. This is accomplished by either independent L1 sampling or with correlated L1 sampling to supplement an independent subset, which offers a more efficient decomposition: for a given t, a sparser decomposition is sufficient with correlated L1 sampling to satisfy a given additive error. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8296 O", + "homepageURL": "https://s3miclassical.com/gitweb", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Weak Simulation v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://s3miclassical.com/gitweb", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Weak_Simulation_v.1.0.json b/agency-indexes/DoE/Weak_Simulation_v.1.0.json new file mode 100644 index 00000000..16ef9785 --- /dev/null +++ b/agency-indexes/DoE/Weak_Simulation_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-16", + "metadataLastUpdated": "2022-10-21" + }, + "description": "SAND2022-3281 O Weak Simulation sparsifies the stabilizer decomposition of a qubit t-tensored T gate magic state to some additive error. It can accomplish this either by independent L1 sampling like in the popular SPARSIFY algorithm or with correlated L1 sampling, which offers a more efficient decomposition. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://s3miclassical.com/gitweb", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "Weak Simulation v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://s3miclassical.com/gitweb", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Weatherization_Assistant_NEAT_MHEA.json b/agency-indexes/DoE/Weatherization_Assistant_NEAT_MHEA.json new file mode 100644 index 00000000..f2b5ba51 --- /dev/null +++ b/agency-indexes/DoE/Weatherization_Assistant_NEAT_MHEA.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "accawigk@ornl.gov" + }, + "date": { + "created": "2021-11-01", + "metadataLastUpdated": "2021-11-03" + }, + "description": "The software provides a measure selection technique indicating cost effective retrofit activities that can be applied to a home using a standard Savings to Investment Ratio (SIR). Users must provide an input file describing the characteristics of the home to be evaluated. The software takes the input data provided and calculates energy savings and cost savings predicted for a standard set of measures given the input parameters. The Weatherization Assistant computes estimates of pre-retrofit whole building space heating and cooling energy consumptions based on the house description data supplied by the user. The consumptions are computed using a monthly heating and cooling variable base degree-day method by algorithms similar to those developed for the CIRA program [LBL, 1982]. The building consumptions are needed in computing the energy savings from measures affecting the efficiencies of the heating and cooling equipment. Weatherization Assistant then computes the energy savings and costs for each individual measure applicable to the building described as if it were the only measure installed in the house. From these energy savings, a discounted dollar savings over the life of each measure is computed. The ratio of this dollar savings to the cost of installing the measure, the \"savings-to-investment ratio\" (SIR), is used in an initial ranking of the measures' effectiveness. The \"interacted\" savings and SIR of measures are then determined assuming the measures are added to the house collectively, in order of their ranking, e.g., the second ranked measure is installed in the house initially described by the user after having been modified by the first ranked measure. If this second-ranked measure's updated SIR is greater than a user-defined limit, the measure is left implemented, else it is removed so that the next measure's effectiveness is not dependent on it. The choice between two mutually exclusive measures (such as different levels of insulation) is made on the basis of their \"net present value\" (NPV), the difference of life-time savings and installation cost, rather than their SIR. This has been shown to be the more correct criterion on which to base the selection between two measures, both of which cannot be installed. The audit computes and reports to the user the energy savings, discounted dollar savings, installation cost, and SIR for each measure considered cost-effective. For those with SIR greater than the user-designated cutoff, a materials list gives the material name, type, and quantity required for installation of the measure. Weatherization Assistant permits entry of pre-retrofit billing data for gas or electrically heated homes or homes with electric air-conditioning. The user may then make the decision to have the savings of the measures adjusted to reflect the difference in billed consumption and that predicted by the program.", + "laborHours": 0.0, + "languages": [ + "C", + "C++" + ], + "name": "Weatherization Assistant NEAT/MHEA", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL-BTRIC/weatherization-assistant-neat-mhea/blob/main/license", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-BTRIC/weatherization-assistant-neat-mhea", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v11.00.000" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WebComms_v._1.0.json b/agency-indexes/DoE/WebComms_v._1.0.json new file mode 100644 index 00000000..767a8a56 --- /dev/null +++ b/agency-indexes/DoE/WebComms_v._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-23" + }, + "description": "WebComms is a lightweight wrapper around the popular open source Apache HttpClient library and enables developers to quickly fetch resources on the internet.", + "laborHours": 8314.4, + "languages": [ + "Java" + ], + "name": "WebComms v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/webcomms?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/webcomms", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WebExpress.json b/agency-indexes/DoE/WebExpress.json new file mode 100644 index 00000000..c6a3f869 --- /dev/null +++ b/agency-indexes/DoE/WebExpress.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-07-03", + "metadataLastUpdated": "2023-01-17" + }, + "description": "WEBEXPRESS is a web interface to the Express for Unix batch scheduling product by Tidal Software. It offers web access from any client on the network and increased functionality in some areas.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "WebExpress", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/WebLogo.json b/agency-indexes/DoE/WebLogo.json new file mode 100644 index 00000000..79bca187 --- /dev/null +++ b/agency-indexes/DoE/WebLogo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "WebLogo is a web based application designed to make the generation of sequence logos as easy and painless as possible. Sequence logos are a graphical representation of an amino acid or nucleic acid multiple sequence alignment developed by Tom Schneider and Mike Stephens. Each logo consists of stacks of symbols, one stack for each position in the sequence. The overall height of the stack indicates the sequence conservation at that position, while the height of symbols within the stack indicates the relative frequency of each amino or nucleic acid at that position. In general, a sequence logo provides a richer and more precise description of, for example, a binding site, than would a consensus sequence.", + "homepageURL": "http://weblogo.berkeley.edu", + "laborHours": 0.0, + "languages": [], + "name": "WebLogo", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://weblogo.berkeley.edu", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Web_Feature_Service_Validator.json b/agency-indexes/DoE/Web_Feature_Service_Validator.json new file mode 100644 index 00000000..67f274fc --- /dev/null +++ b/agency-indexes/DoE/Web_Feature_Service_Validator.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This site allows state data contributors to validate their WFS services against a specified schema for tier 3 data. The application uses the USGIN models API at https://github.com/usgin/usginmodels.", + "laborHours": 4636.0, + "name": "Web Feature Service Validator", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/usgin/ContentModelCMS/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/ContentModelCMS", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Web_Operational_Status_Boards.json b/agency-indexes/DoE/Web_Operational_Status_Boards.json new file mode 100644 index 00000000..3ffe90e6 --- /dev/null +++ b/agency-indexes/DoE/Web_Operational_Status_Boards.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Web Operational Status Boards (WebOSB)is a web-based application designed to acquire, display, and update highly dynamic status information between multiple users and jurisdictions. WebOSB is able to disseminate real-time status information support the timely sharing of information with constant, dynamic updates via personal computers and the Internet between emergency operations centers (EOCs), incident command centers, and to users outside the EOC who need to know the information (hospitals, shelters, schools). The WebOSB application far exceeds outdated information-sharing methods used by emergency workers: whiteboards, Word and Excel documents, or even locality-specific Web sites. WebOSB's capabilities include the following elements: - Secure access. Multiple users can access information on WebOSB from any personal computer with Internet access and a secure ID. Privileges are use to control access and distribution of status information and to identify users who are authorized to add or edit information. - Simultaneous update. WebOSB provides options for users to add, display, and update dynamic information simultaneously at all locations involved in the emergency management effort, A single status board can be updated from multiple locations enabling shelters and hospitals to post bed availability or list decontamination capability. - On-the-fly modification. Allowing the definition of an existing status board to be modified on-the-fly can be an asset during an emergency, where information requirements can change quickly. The status board designer feature allows an administrator to quickly define, modi,, add to, and implement new status boards in minutes without needing the help of Web designers and computer programmers. - Publisher/subscriber notification. As a subscriber, each user automatically receives notification of any new information relating to specific status boards. The publisher/subscriber feature automatically notified each user of any new information relating to specific status boards. WebOSB can be installed to fit the specific needs of an emergency management community. Because it was originally developed to concurrently support multiple EOCs at the local, county, and state level, it can also support multi-user environments for other types of projects.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Web Operational Status Boards", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Web_of_Registries_Search__WoRS__v1.0.0.json b/agency-indexes/DoE/Web_of_Registries_Search__WoRS__v1.0.0.json new file mode 100644 index 00000000..e84a43db --- /dev/null +++ b/agency-indexes/DoE/Web_of_Registries_Search__WoRS__v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-01", + "metadataLastUpdated": "2021-07-01" + }, + "description": "The Web of Registries Search (WoRs) is a web based software application that enables users to search for publicly available biological parts using keywords or sequence fragments. For the initial version (1.0.0) of the application, WoRS targets 10 sources of biological part data: the GenBank NIH genetic sequence database (https://www.ncbi.nlm.nih.gov/genbank/), the iGem parts registry (parts.igem.org), the Addgene plasmid repository (https://www.addgene.org/), and 7 Inventory of Composable Elements (ACS Synbio, JGI, JBEI, JBEI Public, ABF, SynBerc, ABF Public) registry instances. WoRs has built-in automated web scrapers which extract data from sources that do not have a public or well-defined application programming interface (API). They extract as much public data as they can find and create a searchable index to speed up searches. Included in the indexed information is the source of the information.", + "laborHours": 0.0, + "languages": [], + "name": "Web of Registries Search (WoRS) v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JBEI/wors", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Web_service_performance_script.json b/agency-indexes/DoE/Web_service_performance_script.json new file mode 100644 index 00000000..675ecfa6 --- /dev/null +++ b/agency-indexes/DoE/Web_service_performance_script.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This python script, available from ESRI and modified here, checks a server at specified intervals to ensure that web services remain up and running. If any are found to be off, they are automatically turned back on.", + "laborHours": 45.6, + "name": "Web service performance script", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ngds/CheckRunningArcGISservices/blob/master/License.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ngds/CheckRunningArcGISservices", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WeightedAFL.json b/agency-indexes/DoE/WeightedAFL.json new file mode 100644 index 00000000..18dd75ff --- /dev/null +++ b/agency-indexes/DoE/WeightedAFL.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2021-03-30" + }, + "description": "WeightedAFL (WAFL) is an improvement to open source fuzzer, American Fuzzy Lop (AFL). Fuzzers modify input to target programs in order to produce crashes and other unintended output in those target programs. WAFL integrates directly with AFL to determine offsets within a buffer that will improve performance metrics. WAFL uses various machine learning techniques to learn these offsets. WAFL also provides a novel software engineering solution to integrate with AFL and allows contributors to quickly write and test algorithms in python. SAND2020-12546 O\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [], + "name": "WeightedAFL", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/sandialabs/wafl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WeldPredictor.json b/agency-indexes/DoE/WeldPredictor.json new file mode 100644 index 00000000..b33714b4 --- /dev/null +++ b/agency-indexes/DoE/WeldPredictor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "This is the repository for WeldPredictor developed at Oak Ridge National Laboratory. ", + "laborHours": 0.0, + "languages": [], + "name": "WeldPredictor", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/WeldPredictor", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Well_Log_ETL_tool.json b/agency-indexes/DoE/Well_Log_ETL_tool.json new file mode 100644 index 00000000..84826fc3 --- /dev/null +++ b/agency-indexes/DoE/Well_Log_ETL_tool.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "vowelll@osti.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This is an executable python script which offers two different conversions for well log data: 1) Conversion from a BoreholeLASLogData.xls model to a LAS version 2.0 formatted XML file. 2) Conversion from a LAS 2.0 formatted XML file to an entry in the WellLog Content Model. Example templates for BoreholeLASLogData.xls and WellLogsTemplate.xls can be found in the package after download.", + "laborHours": 228.0, + "name": "Well Log ETL tool", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usgin/WellLogDataTools", + "status": "Production", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Wetlands_Geoprocessor__v_1.0_.json b/agency-indexes/DoE/Wetlands_Geoprocessor__v_1.0_.json new file mode 100644 index 00000000..dbb458c7 --- /dev/null +++ b/agency-indexes/DoE/Wetlands_Geoprocessor__v_1.0_.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2024-06-07", + "metadataLastUpdated": "2024-06-07" + }, + "description": "Wetlands have often been described as the \u201cEarth\u2019s kidneys\u201d because wetlands have the ability filter pollutants and purify water. Based upon wetland storage capacity, average daily flow, and inflow nutrient loading this model estimates potential load reductions of nitrate and orthophosphate) from a constructed surface flow wetland (CW). The model relies upon equations, coefficients, and models provided by Cheng et al. 2020 and Cheng & Basu 2017.\nNitrogen (N) and phosphorus are important nutrients to ecosystems, but high concentrations can lead to water quality issues. Major sources of these nutrients come from agricultural areas where fertilizer is applied in large quantitates and/or animal waste is present. Excess nitrate and phosphorus may result in overgrowth of algae, which can decrease the dissolved oxygen in water, thereby harming and killing fish and other aquatic species. This model evaluates water purification results and estimates cost to install a surface flow constructed wetlands.", + "laborHours": 197.6, + "languages": [ + "Python" + ], + "name": "Wetlands Geoprocessor (v 1.0)", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/IdahoLabUnsupported/Wetlands_Geoprocessor", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Whetstone_v.0.9.2.json b/agency-indexes/DoE/Whetstone_v.0.9.2.json new file mode 100644 index 00000000..7c924f97 --- /dev/null +++ b/agency-indexes/DoE/Whetstone_v.0.9.2.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2024-07-30" + }, + "description": "Whetstone is a deep learning software library for spiking/binary threshold neuromorphic hardware. Built to integrate with Keras models, Whetstone provides a collection of layers, callbacks, and utility functions designed to allow the training of integrate-and-fire neurons rather than traditional analog activation functions (e.g. rectified linear units). Generally, training a network for neuromorphic hardware is challenging due to the discontinuity of the activation function. Whetstone overcomes this challenge by using ever-closer continuous approximations of a threshold activation, modified during training time. This allows rapid and consistent training for ultra-low powered neuromorphic hardware.", + "laborHours": 577.6, + "languages": [ + "Python" + ], + "name": "Whetstone v.0.9.2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Whetstone", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.9.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Whole_Building_Energy_Diagnostician,_version_3.0.json b/agency-indexes/DoE/Whole_Building_Energy_Diagnostician,_version_3.0.json new file mode 100644 index 00000000..203b3c01 --- /dev/null +++ b/agency-indexes/DoE/Whole_Building_Energy_Diagnostician,_version_3.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The Whole Building Energy Diagnostician v. 3.x software detects anomalies in energy consumption of buildings and major building systems using metered energy-use data and measured values of driving variables (e.g., outdoor-air temperature, outdoor-air relative humidity, and building occupancy schedule). The software then provides alarms for anomalous consumption and information on energy and cost impacts. This version is intended to be implemented as a world wide web application and made accessible to end users by use of a Web browser and an Internet connection, but the web interface is not provided as part of the software - a web service provider must provide the web-based graphical user interface.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Whole Building Energy Diagnostician, version 3.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Whole_cell_simulator.json b/agency-indexes/DoE/Whole_cell_simulator.json new file mode 100644 index 00000000..9eb71a65 --- /dev/null +++ b/agency-indexes/DoE/Whole_cell_simulator.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-12", + "metadataLastUpdated": "2020-05-12" + }, + "description": "A whole cell model (WCM) is a comprehensive multi-scale computational model representing all the\nknown biochemical processes in a cell. It relies on a variety of intracellular pathway models and omics\ndata.\nThis computational framework enables seamless integration of diverse simulation methods used in WCM\nsuch as stochastic simulation algorithm (SSA), ordinary differential equations (ODE), flux balance\nanalysis (FBA), and logic-based approaches. These methods run simultaneously, not only for whole\npathways but also for subsets of reactions. Furthermore, we aim to enable dynamic switching between\nthe methods when beneficial.\nIs", + "laborHours": 12084.0, + "languages": [], + "name": "Whole cell simulator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/wcs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.4.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WiiBin.json b/agency-indexes/DoE/WiiBin.json new file mode 100644 index 00000000..1acb5d71 --- /dev/null +++ b/agency-indexes/DoE/WiiBin.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "philip.gaskill@inl.gov" + }, + "date": { + "created": "2020-09-29", + "metadataLastUpdated": "2023-03-13" + }, + "description": "WiiBin is a framework to determine architecture of an unknown binary and locate opcode sections within the same binary via supervised machine learning.", + "laborHours": 486.4, + "languages": [ + "Python" + ], + "name": "WiiBin", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/WiiBin", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Wildfires_Risk_Evaluation_of_the_System__WiRES__Framework_Tool.json b/agency-indexes/DoE/Wildfires_Risk_Evaluation_of_the_System__WiRES__Framework_Tool.json new file mode 100644 index 00000000..5a5fc4c4 --- /dev/null +++ b/agency-indexes/DoE/Wildfires_Risk_Evaluation_of_the_System__WiRES__Framework_Tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The invention is a set of algorithms and calculations for a performance-based\nmodel to translate wildfire burn potential to actual transmission line outages\nin real-time in an interactive application that uses geospatial data sets on the\nwildfire burn potential as well as detailed grid topographical datasets.", + "homepageURL": "https://availabletechnologies.pnnl.gov", + "laborHours": 0.0, + "languages": [], + "name": "Wildfires Risk Evaluation of the System (WiRES) Framework Tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://availabletechnologies.pnnl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/WinGridder-A_graphic_grid_generator_for_TOUGH2_simulators__WinGridder__v3.0.json b/agency-indexes/DoE/WinGridder-A_graphic_grid_generator_for_TOUGH2_simulators__WinGridder__v3.0.json new file mode 100644 index 00000000..2d97102e --- /dev/null +++ b/agency-indexes/DoE/WinGridder-A_graphic_grid_generator_for_TOUGH2_simulators__WinGridder__v3.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-02-25", + "metadataLastUpdated": "2019-05-31" + }, + "description": "WINGRIDDER V3.0 is a Windows-based software for designing and generating numerical grids for numerical simulators that are based on the \"integral finite difference\" or the \"control volume\" numerical scheme (e.g., TOUGH2, Pruess et al., 1996). The user can design and generate grid that properly represents the stratigraphic features, inclined faults, and repository. WINGRIDDER V3.0 is an upgrade from WINGRIDDER V2.0. This revision includes testable requirements as listed in the Requirements Document (RD), 10024-RD-3.0-00, Section 2. With new features, WINGRIDDER V3.0 adds the ability to generate a multiple-interactive-continuum (MINC) grid.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "WinGridder-A graphic grid generator for TOUGH2 simulators (WinGridder) v3.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/WinMACCS.json b/agency-indexes/DoE/WinMACCS.json new file mode 100644 index 00000000..8960f3a3 --- /dev/null +++ b/agency-indexes/DoE/WinMACCS.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2018-09-07" + }, + "description": "MACCS is the NRC code used to estimate the offsite radiological consequences of potential severe accidents at nuclear power plants (NPPs). The code is used to perform probabilistic health and economic consequence assessment of hypothetical releases of radioactive material. Atmospheric dispersion and transport, wet and dry deposition, probabilistic treatment of meteorology, environmental transfer, countermeasure strategies, dosimetry, health effects, site specific characteristics, evacuation/sheltering activities, and economic impacts are addressed in the code.", + "homepageURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "WinMACCS", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.nrc.gov/about-nrc/regulatory/research/obtainingcodes.html", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.nrc.gov/about-nrc/regulatory/research/safetycodes.html", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WindSE:_Wind_Systems_Engineering_[SWR-17-03].json b/agency-indexes/DoE/WindSE:_Wind_Systems_Engineering_[SWR-17-03].json new file mode 100644 index 00000000..3fecd8d8 --- /dev/null +++ b/agency-indexes/DoE/WindSE:_Wind_Systems_Engineering_[SWR-17-03].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-01-22", + "metadataLastUpdated": "2024-01-22" + }, + "description": "WindSE is a python package that uses a FEniCS backend to perform wind farm simulations and optimization. Documentation can be found at: https://windse.readthedocs.io/en/latest/", + "laborHours": 3146.4, + "languages": [ + "Python", + "Shell" + ], + "name": "WindSE: Wind Systems Engineering [SWR-17-03]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/WindSE", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "FY23Q3 Release" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WindView.json b/agency-indexes/DoE/WindView.json new file mode 100644 index 00000000..2f2f586e --- /dev/null +++ b/agency-indexes/DoE/WindView.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-01-28", + "metadataLastUpdated": "2019-01-29" + }, + "description": "The National Renewable Energy Laboratory, NREL and Argonne National Laboratory, ANL are creating an open-source situational awareness and decision support platform called WindView that provides grid operators with knowledge on the state and performance of wind power on their system. University Texas Dallas is contracted by NREL to create a wind power forecaster that will be integrated into WindView. WindView does not provide any data, it is a visualization platform which requires the user to provide their own data. During the three year project, there has been collaboration with industry through technical review committees and specifically the Western Area Power Authority's, WAPA's Energy Training Power Center, EPTC to develop a production-level version of WindView which will work for industry. Once complete, it will be publicly available for industry and academic researchers.", + "laborHours": 9971.2, + "languages": [ + "JavaScript", + "css", + "html" + ], + "name": "WindView", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/windview/client", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WindWatts_Computational_Framework_and_Web_UI_[SWR-20-100].json b/agency-indexes/DoE/WindWatts_Computational_Framework_and_Web_UI_[SWR-20-100].json new file mode 100644 index 00000000..7f82d5a2 --- /dev/null +++ b/agency-indexes/DoE/WindWatts_Computational_Framework_and_Web_UI_[SWR-20-100].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-09-25", + "metadataLastUpdated": "2025-02-10" + }, + "description": "This software provides a collection of algorithms, an API, and a functional Web UI for the Distributed Wind\u2019s WindWatts project. DW WindWatts is a DOE WETO-funded project aimed at the development of tools to supporting the distributed wind industry, particularly with respect to siting and resource assessment. The computational framework and the back-end API are powering the easy to use front-end services available at: https://windwatts.nrel.gov.\n\nhttps://github.com/NREL/dw-tap-api; https://github.com/NREL/dw-tap; https://github.com/NREL/windwatts-data\n\nFor reference, this software was previously known as DW TAP Computational Framework.", + "laborHours": 9895.2, + "languages": [ + "JavaScript", + "Python" + ], + "name": "WindWatts Computational Framework and Web UI [SWR-20-100]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dw-tap-api", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Wind_Energy_Intrusion_Detection_System.json b/agency-indexes/DoE/Wind_Energy_Intrusion_Detection_System.json new file mode 100644 index 00000000..b5bd33b4 --- /dev/null +++ b/agency-indexes/DoE/Wind_Energy_Intrusion_Detection_System.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-01-06", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-14659 O The Wind Energy Intrusion Detection System uses a human-machine interface (HMI) to parse results and analyze for anomalies. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "Wind Energy Intrusion Detection System", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/wind_hids", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Wind_Wake_Watcher_v._1.0.json b/agency-indexes/DoE/Wind_Wake_Watcher_v._1.0.json new file mode 100644 index 00000000..d653a736 --- /dev/null +++ b/agency-indexes/DoE/Wind_Wake_Watcher_v._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-24" + }, + "description": "This software enables the user to produce Google Earth visualizations of turbine wake effects for wind farms. The visualizations are based on computations of statistical quantities that vary with wind direction and help quantify the effects on power production of upwind turbines on turbines in their wakes. The results of the software are plot images and kml files that can be loaded into Google Earth. The statistics computed are described in greater detail in the paper: S. Martin, C. H. Westergaard, and J. White (2016), Visualizing Wind Farm Wakes Using SCADA Data, in Wither Turbulence and Big Data in the 21st Century? Eds. A. Pollard, L. Castillo, L. Danaila, and M. Glauser. Springer, pgs. 231-254.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "Wind Wake Watcher v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/Wind-Wake-Watcher", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Wintap.json b/agency-indexes/DoE/Wintap.json new file mode 100644 index 00000000..509e9937 --- /dev/null +++ b/agency-indexes/DoE/Wintap.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-28", + "metadataLastUpdated": "2023-02-28" + }, + "description": "Wintap is an extensible, general purpose agent framework for the Windows operating system. It provides an easy-to-use plugin architecture, an integrated streaming analytics engine, and real-time event subscriptions for host-based data. Wintap can support a wide variety of applications across production operations, cyber security operations, and cyber security research.", + "laborHours": 0.0, + "languages": [], + "name": "Wintap", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Wintap", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "6.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Wiretap.json b/agency-indexes/DoE/Wiretap.json new file mode 100644 index 00000000..ee5220e1 --- /dev/null +++ b/agency-indexes/DoE/Wiretap.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2023-08-07" + }, + "description": "SAND2023-12116O\nWiretap is an offensive security software package meant for penetration testers and red teams. Unlike a traditional VPN, Wiretap transparently proxies networking traffic without requiring administrator privileges. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Golang", + "Go" + ], + "name": "Wiretap", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/wiretap", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WizEM.json b/agency-indexes/DoE/WizEM.json new file mode 100644 index 00000000..168ae6e5 --- /dev/null +++ b/agency-indexes/DoE/WizEM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-17", + "metadataLastUpdated": "2025-04-17" + }, + "description": "The software provides a flexible pipeline for artificial intelligence (AI) assisted analysis of data collected from an electron\nmicroscope. This tool distinctly provides near real-time image quantification results during data collection, incorporating\nfeedback from a user to tune performance.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 380.0, + "languages": [], + "name": "WizEM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Workbench_Analysis_Sequence_Processor.json b/agency-indexes/DoE/Workbench_Analysis_Sequence_Processor.json new file mode 100644 index 00000000..752b971b --- /dev/null +++ b/agency-indexes/DoE/Workbench_Analysis_Sequence_Processor.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-11-25", + "metadataLastUpdated": "2020-11-30" + }, + "description": "The Workbench Analysis Sequence Processor (WASP) was developed to streamline lexing, parsing, access, validation, and analysis of ascii text files.", + "laborHours": 81426.4, + "languages": [], + "name": "Workbench Analysis Sequence Processor", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://code.ornl.gov/neams-workbench/wasp/-/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/neams-workbench/wasp", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Workspace_Browser.json b/agency-indexes/DoE/Workspace_Browser.json new file mode 100644 index 00000000..50612868 --- /dev/null +++ b/agency-indexes/DoE/Workspace_Browser.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "This is a KBase Dev Tool for browsing workspaces.", + "laborHours": 3921.6, + "languages": [], + "name": "Workspace Browser", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/workspace_browser", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Workspace_Services.json b/agency-indexes/DoE/Workspace_Services.json new file mode 100644 index 00000000..277c6509 --- /dev/null +++ b/agency-indexes/DoE/Workspace_Services.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for managing the workspace service. The workspace represents a scientific team's data as a collection of objects with a standard set of permissions over all objects within a workspace. The workspace also implements revert and restore functionality on each object in a workspace.", + "laborHours": 9013.6, + "languages": [], + "name": "Workspace Services", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/workspace_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Wrapper_Induction_Software.json b/agency-indexes/DoE/Wrapper_Induction_Software.json new file mode 100644 index 00000000..fd77e2cc --- /dev/null +++ b/agency-indexes/DoE/Wrapper_Induction_Software.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "Wrapper Induction is a software package that allows for unsupervised, semi-supervised, and manual extraction of social media data independent of language or site architecture. A large range of blog formats is available to individuals as means of publishing data to the internet. Blogs are a source of rich information for analysts. With a growing volume of information and blog engines, there is an increased need for automatic or semi-automatic extraction of that data for processing to help deliver results to analysts. Wrapper Induction is designed to automatically or semi-automatically create a template that can be used to harvest blog data from websites. Blogs are in a variety of formats and languages. Wrapper Induction creates a template and extracts blog data in a way that is independent of a specified blog format or language.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "Java, Javascript" + ], + "name": "Wrapper Induction Software", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Wrapper_for_the_optimization_of_cross-section_generation_in_OpenMC.json b/agency-indexes/DoE/Wrapper_for_the_optimization_of_cross-section_generation_in_OpenMC.json new file mode 100644 index 00000000..fd6499dc --- /dev/null +++ b/agency-indexes/DoE/Wrapper_for_the_optimization_of_cross-section_generation_in_OpenMC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "The \"Wrapper for the optimization of cross-section generation in OpenMC\" is Python-based software that runs the open-source Monte Carlo code OpenMC (https://docs.openmc.org/en/stable/ ) to generate cross-sections for any reactor geometry. The wrapper then optimizes those cross sections. The optimization aims to choose an energy group structure and a scattering representation that maximize accuracy with respect to continuous-energy results while avoiding significant computational expense. It then outputs these cross-sections in an ISOXML format readable by the Idaho National Lab code suite MOOSE (Olin William Calvin, Mark D DeHart, \u201cArchitecture for the Performance of Nuclear Fuel Depletion Calculations\u201d, Idaho National Laboratory report, November 2019). The expected use-cases of this software include: -finding the best group structure and scattering representation for a specific reactor -testing the appropriateness of energy group structures for different reactor types -comparing energy group structures and scattering representations to each other -generating cross sections for use in deterministic codes, including ones found in the MOOSE suite The example reactor geometry included in this release is a generic reactor design, not based on any reactor in existence or in development. It was fabricated for the sole purpose of being a \u201ctestbed-geometry\u201d upon which to develop this tool. Since the tool is designed to be generic, the nature of the test geometry is not very important, however, it is valuable to include as an example for users who are unfamiliar with developing reactor geometries for OpenMC.", + "laborHours": 0.0, + "languages": [], + "name": "Wrapper for the optimization of cross-section generation in OpenMC", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/TOGA.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/WsLargeDataIO.json b/agency-indexes/DoE/WsLargeDataIO.json new file mode 100644 index 00000000..c941f998 --- /dev/null +++ b/agency-indexes/DoE/WsLargeDataIO.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "This is the repository for \"WsLargeDataIO\" developed by KBase. ", + "laborHours": 1216.0, + "languages": [], + "name": "WsLargeDataIO", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/WsLargeDataIO", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/X-RAY_DETECTOR_GAIN_MAP_CALCULATION.json b/agency-indexes/DoE/X-RAY_DETECTOR_GAIN_MAP_CALCULATION.json new file mode 100644 index 00000000..7028642c --- /dev/null +++ b/agency-indexes/DoE/X-RAY_DETECTOR_GAIN_MAP_CALCULATION.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-27" + }, + "description": "The \"X-RAY DETECTOR GAIN MAP CALCULATION\" was developed by Argonne National Laboratory.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "X-RAY DETECTOR GAIN MAP CALCULATION", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/X-Ray_Analysis_Software.json b/agency-indexes/DoE/X-Ray_Analysis_Software.json new file mode 100644 index 00000000..c8494627 --- /dev/null +++ b/agency-indexes/DoE/X-Ray_Analysis_Software.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "XRAYS is a suite of programs related to scientific software in general and xray and neutron scattering problems in particular. It is expected to bean ongoing program involving collaboration with other facilities. It is expected to include legacy and other existing software as well as new applications and new interfaces for existing applications.", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "X-Ray Analysis Software", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.anl.gov/partnerships/licensable-software", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/X-Ray_Toolkit_Mobile__Android_.json b/agency-indexes/DoE/X-Ray_Toolkit_Mobile__Android_.json new file mode 100644 index 00000000..2a8c4f38 --- /dev/null +++ b/agency-indexes/DoE/X-Ray_Toolkit_Mobile__Android_.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-27", + "metadataLastUpdated": "2021-08-30" + }, + "description": "X-Ray Toolkit Mobile (Android) is a software application for acquiring and processing digital images. The application runs on mobile devices running Android operating systems. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525 SAND2021-1981 O", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Java", + "Java" + ], + "name": "X-Ray Toolkit Mobile (Android)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "1.X.X. - Android" +} \ No newline at end of file diff --git a/agency-indexes/DoE/X-Ray_Toolkit__XTK__v._3.1.x.json b/agency-indexes/DoE/X-Ray_Toolkit__XTK__v._3.1.x.json new file mode 100644 index 00000000..a985fb28 --- /dev/null +++ b/agency-indexes/DoE/X-Ray_Toolkit__XTK__v._3.1.x.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-28", + "metadataLastUpdated": "2021-09-07" + }, + "description": "Radiographic Image Acquisition & Processing Software for Security Markets", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C#", + "WPF" + ], + "name": "X-Ray Toolkit (XTK) v. 3.1.x", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 3.1.x" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XACC_-_eXtreme-scale_Accelerator_Programming_Framework.json b/agency-indexes/DoE/XACC_-_eXtreme-scale_Accelerator_Programming_Framework.json new file mode 100644 index 00000000..d7e97be2 --- /dev/null +++ b/agency-indexes/DoE/XACC_-_eXtreme-scale_Accelerator_Programming_Framework.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Hybrid programming models for beyond-CMOS technologies will prove critical for integrating new computing technologies alongside our existing infrastructure. Unfortunately the software infrastructure required to enable this is lacking or not available. XACC is a programming framework for extreme-scale, post-exascale accelerator architectures that integrates alongside existing conventional applications. It is a pluggable framework for programming languages developed for next-gen computing hardware architectures like quantum and neuromorphic computing. It lets computational scientists efficiently off-load classically intractable work to attached accelerators through user-friendly Kernel definitions. XACC makes post-exascale hybrid programming approachable for domain computational scientists.", + "laborHours": 454860.0, + "name": "XACC - eXtreme-scale Accelerator Programming Framework", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/xacc", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XFEMParaviewPlugin.json b/agency-indexes/DoE/XFEMParaviewPlugin.json new file mode 100644 index 00000000..40c7d440 --- /dev/null +++ b/agency-indexes/DoE/XFEMParaviewPlugin.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The XFEMClipPartialElements tool is a plugin for the open-source Paraview visualization software to correctly visualize results with discontinuities represented using the extended finite element method (XFEM) in MOOSE-based codes.", + "laborHours": 182.4, + "languages": [], + "name": "XFEMParaviewPlugin", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/XFEMParaviewPlugin", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XGC.json b/agency-indexes/DoE/XGC.json new file mode 100644 index 00000000..51d05838 --- /dev/null +++ b/agency-indexes/DoE/XGC.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "sku@pppl.gov" + }, + "date": { + "created": "2018-06-27", + "metadataLastUpdated": "2021-04-13" + }, + "description": "XGC (X-point included gyrokinetic code), Version 3 Primary Author: Seunghoe Ku (PPPL, sku@pppl.gov), Robert Hager (PPPL, rhager@pppl.gov) 31 July 2017 XGC is a gyrokinetic particle-in-cell code, which is sepeciallized in tokamak edge simulatin. The simulation domain can include the magnetic separatrix, magnetic axis and the biased material wall. XGC can run in full-f, total-delta-f, and conventional delta-f mode. The ion is kinetic always except ETG simulation. The electron can be adiabatic, fluid, drift kinetic, or gyrokinetic (for ETG). XGC is written in Fortran 90 and is designed for HPCs utilizing MPI, OpenMP, CUDA (GPU), OpenACC (GPU), and vectorization (Intel MIC-KNL). The weak scaling is roughly linear to the maximal nodes of leading HPCs in US. There several versions of XGCs for different purpose: XGC0 is earlist version of XGC0 which is designed for neoclassical transport in the tokamak edge. It uses full-f method, and 00-mode electrostatic field is solved only. RMP and current response can be calculated with coupling with M3D. XGC1 is for turbulence simulation with low parallel wavenumber. Piecewise field following coordinates are used to handle low k-parallel perturbation with small (~64) number of toroidal resolution. In total-delta-f method, it utilizes phase space grid in addition to particles, to handel non-maxwellian distribution in the tokamak edge. XGCa is axisymmetric version of XGC1 to simulate neoclassical transport. References: [1] S. Ku et al., Nuclear Fusion 49, 115021 (2009) [2] S. Ku, R. Hager, C.S. Chang et al., J. Comp. Physics, 315, 467 (2016) https://doi.org/10.1016/j.jcp.2016.03.062 [2] R. Hager. E.S. Yoon. S.Ku et al., J. Comp. Physics, 315, 644 (2016) https://doi.org/10.1016/j.jcp.2016.03.064 [3] R. Hager, J. Lang et al., Phys. Plasmas 24,054508 (2017) http://dx.doi.org/10.1063/1.4983320", + "homepageURL": "https://xgc.pppl.gov", + "laborHours": 0.0, + "languages": [ + "Fortran", + "C++" + ], + "name": "XGC", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://theory.pppl.gov/research/TheoryCodeLicenseReleaseForm.pdf", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://xgc.pppl.gov", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/XML_Engineering_Environment.json b/agency-indexes/DoE/XML_Engineering_Environment.json new file mode 100644 index 00000000..4ade87db --- /dev/null +++ b/agency-indexes/DoE/XML_Engineering_Environment.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-19" + }, + "description": "The XML Engineering Environment is a reconfigurable software system that allows users to translate, enhance and route data from sources to sinks.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "XML Engineering Environment", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/XMOF2D.json b/agency-indexes/DoE/XMOF2D.json new file mode 100644 index 00000000..3efbaa37 --- /dev/null +++ b/agency-indexes/DoE/XMOF2D.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-03-15", + "metadataLastUpdated": "2018-03-15" + }, + "description": "XMOF2D is a library implementing the X-MOF (eXtended Moments of Fluid) interface reconstruction method on unstructured polygonal meshes with convex cells. Given a computational mesh with multi-material cells, for which volume fractions and centroids of contained materials are provided, piecewise linear material interfaces are constructed inside such cells using the Moment-of-Fluid (MOF) method. Additionally, a hierarchical mesh is created, where every multi-material cell of the computational mesh contains a local mesh with fully established local topology, as well as the parentage information to relate mesh entities from the local and the computational \nmeshes.", + "laborHours": 2082.4, + "name": "XMOF2D", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laristra/XMOF2D", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XPCA_-Python_Implementation.json b/agency-indexes/DoE/XPCA_-Python_Implementation.json new file mode 100644 index 00000000..b6c3d321 --- /dev/null +++ b/agency-indexes/DoE/XPCA_-Python_Implementation.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-11", + "metadataLastUpdated": "2024-08-07" + }, + "description": "Principal component analysis (PCA) is arguably the most popular tool in multivariate exploratory data analysis. We consider the question of how to handle heterogeneous variables that include continuous, binary, and ordinal. In the probabilistic interpretation of low-rank PCA, the data has a normal multivariate distribution and, therefore, normal marginal distributions for each column. If some marginals are continuous but not normal, the semiparametric copula-based principal component analysis (COCA) method is an alternative to PCA that combines a Gaussian copula with nonparametric marginals. If some marginals are discrete or semi-continuous, we present a new extended PCA (XPCA) method that also uses a Gaussian copula and nonparametric marginals and accounts for discrete variables in the likelihood calculation by integrating over appropriate intervals. Like PCA, the factors produced by XPCA can be used to find latent structure in data, build predictive models, and perform dimensionality reduction. We implement the new model, XPCA, and its ancestors PCA and COCA in both R and Python. This software provides implementations of XPCA, COCA, and probabilistic PCA in both R and Python. XPCA is written in arXiv report https://arxiv.org/abs/1808.07510. SAND2019-10591 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 425.6, + "languages": [ + "Python" + ], + "name": "XPCA -Python Implementation", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/xpca", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XPCA_-_R_Implementation.json b/agency-indexes/DoE/XPCA_-_R_Implementation.json new file mode 100644 index 00000000..c40012dd --- /dev/null +++ b/agency-indexes/DoE/XPCA_-_R_Implementation.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-03-21", + "metadataLastUpdated": "2024-08-07" + }, + "description": "Principal component analysis (PCA) is arguably the most popular tool in multivariate exploratory data analysis. We consider the question of how to handle heterogeneous variables that include continuous, binary, and ordinal. In the probabilistic interpretation of low-rank PCA, the data has a normal multivariate distribution and, therefore, normal marginal distributions for each column. If some marginals are continuous but not normal, the semiparametric copula-based principal component analysis (COCA) method is an alternative to PCA that combines a Gaussian copula with nonparametric marginals. If some marginals are discrete or semi-continuous, we present a new extended PCA (XPCA) method that also uses a Gaussian copula and nonparametric marginals and accounts for discrete variables in the likelihood calculation by integrating over appropriate intervals. Like PCA, the factors produced by XPCA can be used to find latent structure in data, build predictive models, and perform dimensionality reduction. We implement the new model, XPCA, and its ancestors PCA and COCA in both R and Python. This software provides implementations of XPCA, COCA, and probabilistic PCA in both R and Python. XPCA is written in arXiv report https://arxiv.org/abs/1808.07510. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.\nSAND2019-10591 M", + "laborHours": 592.8, + "languages": [ + "R" + ], + "name": "XPCA - R Implementation", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/xpcaR", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XPlacer_Machine_Learning_Guided_Data_Placement.json b/agency-indexes/DoE/XPlacer_Machine_Learning_Guided_Data_Placement.json new file mode 100644 index 00000000..b918ff19 --- /dev/null +++ b/agency-indexes/DoE/XPlacer_Machine_Learning_Guided_Data_Placement.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "XPlacer Machine Learning Guided Data Placement uses machine learning model to assist programmers to select the data placement advises for application running on HPC system with Nvidia GPUs. XPlacer Machine Learning Guided Data Placement consists three components: (1) 4 revised benchmarks from Rodinia benchmarks; (2) compiler script and execution script to generate variants, and collect training data for the machine learning model; (3) the scripts to post-process the collected data and generate the machine leaning model.", + "laborHours": 0.0, + "languages": [], + "name": "XPlacer Machine Learning Guided Data Placement", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/peihunglin/XPlacer-ML-DataPlacement", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.9" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XPlacer_Tracer.json b/agency-indexes/DoE/XPlacer_Tracer.json new file mode 100644 index 00000000..3b72b980 --- /dev/null +++ b/agency-indexes/DoE/XPlacer_Tracer.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-01-07" + }, + "description": "XPlacer/Tracer is a dynamic analysis tool that finds bad memory access patterns in heterogeneous codes. XPlacer/Tracer consists of two components. (1) A configurable ROSE plugin for source code instrumentation of heterogeneous code written in the C/C++ and CUDA programming languages. (2) A sample configuration that instruments memory accesses to dynamic memory in CPU and GPU codes, and a runtime library that tracks these memory accesses at runtime. The collected information is reported in form of a textual summary or as memory map that can be converted to images.", + "laborHours": 0.0, + "languages": [], + "name": "XPlacer/Tracer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/XPL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XRF-MAPS.json b/agency-indexes/DoE/XRF-MAPS.json new file mode 100644 index 00000000..85acd8b3 --- /dev/null +++ b/agency-indexes/DoE/XRF-MAPS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-24", + "metadataLastUpdated": "2021-08-24" + }, + "description": "x-ray fluorescence (XRF) imaging typically involves the creation and analysis of 3D data sets, where at each scan position a full energy dispersive x-ray spectrum is recorded. This allows one to later process the data in a variety of different approaches, e.g., by spectral region of interest (ROI) summation with or without background subtraction, principal component analysis, or fitting. XRF-Maps is a C++ open source software package that implements these functions to provide a tool set for the analysis of XRF data sets.", + "laborHours": 0.0, + "languages": [], + "name": "XRF-MAPS", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdvancedPhotonSource/XRF-Maps", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XRF-ROI_Finder:_Machine_Learning_to_Guide_Region-of-Interest_Scanning_for_X-ray_Fluorescence_Microscopy.json b/agency-indexes/DoE/XRF-ROI_Finder:_Machine_Learning_to_Guide_Region-of-Interest_Scanning_for_X-ray_Fluorescence_Microscopy.json new file mode 100644 index 00000000..d1cfe1eb --- /dev/null +++ b/agency-indexes/DoE/XRF-ROI_Finder:_Machine_Learning_to_Guide_Region-of-Interest_Scanning_for_X-ray_Fluorescence_Microscopy.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-04-01" + }, + "description": "The ROI-finder software is being developed for use by several Microscopy Group beamlines at Argonne National Laboratory, including 2-ID microprobes and 9-ID-B Bionanoprobe which use multi-scale scanning fluorescence microscopy to acquire elemental maps (multi-modal image data). Microscopy experiments require scan of samples at a coarse resolution followed by ROI identification using feature detection based on domain expertise. Finer resolution scans are then conducted based on identified ROI. The decision-making process based on domain expertise will be difficult to perform for faster data rates and much larger sampling volumes anticipated after APS-U necessitating the need for the ROI-finder software. The ROI- finder detects regions of interest through a continuous learning process, starting with a unsupervised representation learning and improving its recommendations through supervised learning and an interactive tool for user annotation. The scope of ongoing development efforts includes the integration of image registration module to correlate optical and X-ray images, extraction of feature morphology as well as elemental signatures in the image space and incorporation of beamtime streaming data by the scanning probe via EPICS.", + "laborHours": 0.0, + "languages": [], + "name": "XRF-ROI Finder: Machine Learning to Guide Region-of-Interest Scanning for X-ray Fluorescence Microscopy", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/arshadzahangirchowdhury/ROI-Finder", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XRF-XFS-XAS-Auto_v1.0_-_Beta_release.json b/agency-indexes/DoE/XRF-XFS-XAS-Auto_v1.0_-_Beta_release.json new file mode 100644 index 00000000..ea4b7334 --- /dev/null +++ b/agency-indexes/DoE/XRF-XFS-XAS-Auto_v1.0_-_Beta_release.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-12", + "metadataLastUpdated": "2024-06-12" + }, + "description": "This software allows to analyze XRF maps, XFS spectra and XAS spectra collected at the Advanced Light Source's Beamline 10.3.2.\n\nFeatures include:\n1) XRF maps:\n- process XRF maps, all elemental maps are saved as bmp automatically and labeled with the incident energy used, the scale bar is also labeled and can be controlled.\n- XRF elemental correlation plots, save the correlation plots automatically\n- Extract single or multiple transects in XRF maps on one or several regions of interest, each transect profile is numbered and saved in a corresponding folder, along with the corresponding maps showing transect location.\n\n2) XFS spectra\n- save in log10 scale the XFS spectra, either a single or multiple files all at once. The files are saved as .bmp.\n- XFS spectra are labeled according to tabulated fluorescence emission lines.\n\n3) XAS spectra\n- allows to plot individual scalers in the raw data.\n- allows calibration of the spectra using an Io internal glitch present in all spectra and performing 1st derivative.\n- Least-square linear combination fitting of XANES or extended XANES spectra using a database of standards using 1, 2 or 3 components maximum. It also provides the 5 top combinations and provide the user for the possibility of saving the 2nd, 3rd, 4th and 5th best combinations in addition to the best one. The processed spectra (pre-edge background substracted, post-edge normalized), the fits and residuals are automatically saved.\nA table of the component, with fit% and SSN is provided and saved automatically as well.", + "laborHours": 16400.8, + "languages": [], + "name": "XRF-XFS-XAS-Auto v1.0 - Beta release", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/als-computing/bl1032", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XRFtomo.json b/agency-indexes/DoE/XRFtomo.json new file mode 100644 index 00000000..7ec7c8c7 --- /dev/null +++ b/agency-indexes/DoE/XRFtomo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-09-12", + "metadataLastUpdated": "2020-09-17" + }, + "description": "Based on [1], XRFtomo brings together a variety of image processing tools used for preparing, processing and reconstructing 3D renditions of samples imaged using a synchrotron-based x-ray fluorescence (XRF) microprobe or nanoprobe at the Advanced Photon Source (APS). This software bridges the gap between data acquisition and visualization by providing tools to adjust for misalignment in the imaging process and tools for running reconstructions[2], all with the use of a GUI or command line. XRFtomo accepts .h5 files processed through MAPS[3] and it outputs reconstructed cross-sections, projections, sinograms, metadata, and a configuration file with last-used parameters for rapid processing the next time the program is launched. These images serve as inputs for other 3D visualization software for generating volumetric renderings and animations. ", + "laborHours": 6764.0, + "languages": [], + "name": "XRFtomo", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tomography/XRFtomo", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XRIPL.json b/agency-indexes/DoE/XRIPL.json new file mode 100644 index 00000000..3bba68d0 --- /dev/null +++ b/agency-indexes/DoE/XRIPL.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-06-15", + "metadataLastUpdated": "2022-06-15" + }, + "description": "XRIPL is a library of tools for processing x-ray radiographs and extracting contours of interest within the image using computer vision techniques. Features include spatial calibration, denoising, background and attenuation correction through pseudo-flatfielding, watershed segmentation, contour processing, and visualization. The details of the XRIPL analysis pipeline are published in the Proceedings of the 23rd Topical Conference on High-Temperature Plasma Diagnostics Proceedings (LA-UR-20-30133) [1]. [1] P. M. Kozlowski, Y. Kim, B. M. Haines, H. F. Robey, T. J. Murphy, H. M. Johns, and T. S. Perry. Use of Computer Vision for analysis of image data sets from high temperature plasma experiments. Review of Scientific Instruments 92, 033532 (2021) https://doi.org/10.1063/5.0040285", + "laborHours": 0.0, + "languages": [], + "name": "XRIPL", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/xripl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XScope.json b/agency-indexes/DoE/XScope.json new file mode 100644 index 00000000..fd4fcdc5 --- /dev/null +++ b/agency-indexes/DoE/XScope.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-06-27", + "metadataLastUpdated": "2022-06-27" + }, + "description": "XScope finds inputs that trigger floating-point exceptions, such as NaN (not a number) and infinity, in CUDA functions using Bayesian optimization (BO). XScope assumes that the CUDA functions are a black box, i.e., the source code is not available. It searches the input space using several methods to guide BO into extreme cases. When an input is found to trigger an exception in the target CUDA function, the input is shown to the user.", + "laborHours": 0.0, + "languages": [], + "name": "XScope", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Xscope", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XTL_Converter.json b/agency-indexes/DoE/XTL_Converter.json new file mode 100644 index 00000000..338d2d37 --- /dev/null +++ b/agency-indexes/DoE/XTL_Converter.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"XTL Converter\" is a short Python script for electron microscopy simulation. The program takes an input crystal file in the VESTA *.XTL format and converts it to a text format readable by the multislice simulation program \u00ecSTEM. The process of converting a crystal *.XTL file to the format used by the \u00ecSTEM simulation program is quite tedious; it generally requires the user to select dozens or hundreds of atoms, rearranging and reformatting their position. Header information must also be reformatted to a specific style to be read by \u00ecSTEM. \"XTL Converter\" simplifies this process, saving the user time and allowing for easy batch processing of crystals.", + "laborHours": 136.8, + "name": "XTL Converter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/stevenspurgeon/xtl-converter/blob/master/License", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stevenspurgeon/xtl-converter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/XVC_FTDI_JTAG_v1.0.json b/agency-indexes/DoE/XVC_FTDI_JTAG_v1.0.json new file mode 100644 index 00000000..11c21e8f --- /dev/null +++ b/agency-indexes/DoE/XVC_FTDI_JTAG_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-21", + "metadataLastUpdated": "2021-04-21" + }, + "description": "the Xilinx tools relay on a component on the board (FTDI chip) to have a small memory from a particular manufacturer (Digilent) to serve as a bridge to the FPGA. What the software we're requesting to release simply does is to run between the Xilinx tools (one of them is called Vivado but there are others) and our boards so that we don't need that memory on our boards. The protocol the software uses to communicate with the Xilinx tools is called XVC (Xilinx Virtual Cable). This server code runs on the computer that is physically connected to the FPGA board, but the Xilinx tools that communicate with it can run either on that computer or some other computer connected to it over the network, this is where the network component comes into play.", + "laborHours": 0.0, + "languages": [], + "name": "XVC FTDI JTAG v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BerkeleyLab/XVC-FTDI-JTAG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Xanthos.json b/agency-indexes/DoE/Xanthos.json new file mode 100644 index 00000000..4165b8f6 --- /dev/null +++ b/agency-indexes/DoE/Xanthos.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Xanthos is a Python package designed to quantify and analyze global water availability in history and in future at 0.5\u00b0 \u00d7 0.5\u00b0 spatial resolution and a monthly time step under a changing climate. Its performance was also tested through real applications. It is open-source, extendable and convenient to researchers who work on long-term climate data for studies of global water supply, and Global Change Assessment Model (GCAM). This package integrates inherent global gridded data maps, I/O modules, Water-Balance Model modules and diagnostics modules by user-defined configuration.", + "laborHours": 1656.8, + "name": "Xanthos", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/JGCRI/xanthos", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Xarray_Climate_Data_Analysis_Tools.json b/agency-indexes/DoE/Xarray_Climate_Data_Analysis_Tools.json new file mode 100644 index 00000000..db5da73e --- /dev/null +++ b/agency-indexes/DoE/Xarray_Climate_Data_Analysis_Tools.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-03-31", + "metadataLastUpdated": "2023-03-31" + }, + "description": "xCDAT is an extension of xarray for climate data analysis on structured grids. It serves as a modern successor to the Community Data Analysis Tools (CDAT) library. Xarray is an \"open source project and Python package that introduces labels in the form of dimensions, coordinates, and attributes on top of raw NumPy-like arrays, which allows for more intuitive, more concise, and less error-prone user experience. Xarray includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures\" (source: https://xarray.dev/). The goal of xCDAT is to provide generalizable features and utilities for simple and robust analysis of climate data. xCDAT's design philosophy is focused on reducing the overhead required to accomplish certain tasks in xarray. Some key xCDAT features are inspired by or ported from the core CDAT library, while others leverage powerful libraries in the xarray ecosystem (e.g., xESMF and cf_xarray) to deliver robust APIs.", + "laborHours": 0.0, + "languages": [], + "name": "Xarray Climate Data Analysis Tools", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xCDAT/xcdat", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.5.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Xavier:_High-Performance_X-Drop_Adaptive_Banded_Pairwise_Alignment__Xavier__v1.0.json b/agency-indexes/DoE/Xavier:_High-Performance_X-Drop_Adaptive_Banded_Pairwise_Alignment__Xavier__v1.0.json new file mode 100644 index 00000000..31b08c06 --- /dev/null +++ b/agency-indexes/DoE/Xavier:_High-Performance_X-Drop_Adaptive_Banded_Pairwise_Alignment__Xavier__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-30", + "metadataLastUpdated": "2019-10-30" + }, + "description": "Pairwise sequence alignment is one of the most compute-intense challenges for the analysis of genomics data and it can account for more than 90% of the runtime depending on the application. Despite the effort to reduce the computational cost introducing heuristics such as banded and x-drop alignment, the performance of state-of-the-art software is often unsatisfactory for long sequences. Recent advances in single-molecule sequencing technologies keep increasing the length of the sequences to align at the cost of higher error rates b ranging from 5% to 15% b, emphasizing the need for fast and accurate software.\n\nOur long-read alignment software, named Xavier, computes high-performance x-drop adaptive banded pairwise alignment exploiting instruction-level parallelism via Single-Instruction-Multiple-Data (SIMD) operations. Xavier uses a narrow bandwidth that appreciably improves performance reducing the search space for the optimal alignment. In our experiment, the adaptive mechanism enables Xavier to find the optimal alignment between related sequences even when the error rate is as high as 50%. Xavier achieves speed-up up to 5X over competitor software when enabling the x-drop termination and up to 415X when disabling it, with negligible accuracy loss.", + "laborHours": 456.0, + "languages": [], + "name": "Xavier: High-Performance X-Drop Adaptive Banded Pairwise Alignment (Xavier) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/giuliaguidi/xavier", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Xenon_International_Automated_Control.json b/agency-indexes/DoE/Xenon_International_Automated_Control.json new file mode 100644 index 00000000..97e69748 --- /dev/null +++ b/agency-indexes/DoE/Xenon_International_Automated_Control.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-18", + "metadataLastUpdated": "2022-07-20" + }, + "description": "The Xenon International Automated Control software monitors, displays status, and allows for manual operator control as well as fully automatic control of multiple commercial and PNNL designed hardware components to generate and transmit atmospheric radioxenon concentration measurements every six hours.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "gcc-c++" + ], + "name": "Xenon International Automated Control", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Xi-CAM_v1.2.3.json b/agency-indexes/DoE/Xi-CAM_v1.2.3.json new file mode 100644 index 00000000..e9fa21f8 --- /dev/null +++ b/agency-indexes/DoE/Xi-CAM_v1.2.3.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "Xi-CAM aims to provide a community driven platform for multimodal analysis in synchrotron science. The platform core provides a robust plugin infrastructure for extensibility, allowing continuing development to simply add further functionality. Current modules include tools for characterization with (GI)SAXS, Tomography, and XAS. This will continue to serve as a development base as algorithms for multimodal analysis develop. Seamless remote data access, visualization and analysis are key elements of Xi-CAM, and will become critical to synchrotron data infrastructure as expectations for future data volume and acquisition rates rise with continuously increasing throughputs. The highly interactive design elements of Xi-cam will similarly support a generation of users which depend on immediate data quality feedback during high-throughput or burst acquisition modes.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 0.0, + "languages": [], + "name": "Xi-CAM v1.2.3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Xolotl.json b/agency-indexes/DoE/Xolotl.json new file mode 100644 index 00000000..8963d83f --- /dev/null +++ b/agency-indexes/DoE/Xolotl.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "bernholdtde@ornl.gov" + }, + "date": { + "created": "2021-09-05", + "metadataLastUpdated": "2021-09-07" + }, + "description": "Xolotl is a continuum simulator under development within two DOE SciDAC project. It is a high-performance computing code using advection-reaction-diffusion (ADR) kinetic rate theory to model the time evolution of the divertor material in next generation tokamaks like ITER, as well as nuclear fuel in fission reactors.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "Xolotl", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-Fusion/xolotl", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Xpetra_Package.json b/agency-indexes/DoE/Xpetra_Package.json new file mode 100644 index 00000000..69a9c269 --- /dev/null +++ b/agency-indexes/DoE/Xpetra_Package.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Xpetra provides a single interface that allows the use of either Epetra or Tpetra linear algebra libraries from the same source code. Library developers need only learn and use the syntax of Xpetra; the resulting libraries can use either Epetra or Tpetra.", + "laborHours": 8344830.4, + "languages": [ + "C++", + "C", + "Roff", + "MATLAB", + "Fortran", + "Python" + ], + "name": "Xpetra Package", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Xyce_\342\204\242__Parallel_Electronic_Simulator.json" "b/agency-indexes/DoE/Xyce_\342\204\242__Parallel_Electronic_Simulator.json" new file mode 100644 index 00000000..e6d13cf7 --- /dev/null +++ "b/agency-indexes/DoE/Xyce_\342\204\242__Parallel_Electronic_Simulator.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-11-01" + }, + "description": "The Xyce Parallel Electronic Simulator simulates electronic circuit behavior in DC, AC, HB, MPDE and transient mode using standard analog (DAE) and/or device (PDE) device models including several age and radiation aware devices. It supports a variety of computing platforms (both serial and parallel) computers. Lastly, it uses a variety of modern solution algorithms dynamic parallel load-balancing and iterative solvers.! ! Xyce is primarily used to simulate the voltage and current behavior of a circuit network (a network of electronic devices connected via a conductive network). As a tool, it is mainly used for the design and analysis of electronic circuits.! ! Kirchoff's conservation laws are enforced over a network using modified nodal analysis. This results in a set of differential algebraic equations (DAEs). The resulting nonlinear problem is solved iteratively using a fully coupled Newton method, which in turn results in a linear system that is solved by either a standard sparse-direct solver or iteratively using Trilinos linear solver packages, also developed at Sandia National Laboratories.", + "laborHours": 491233.6, + "languages": [], + "name": "Xyce(\u2122) Parallel Electronic Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Xycedev/Xyce", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Xyce_\342\204\242__Parallel_Electronic_Simulator_v.7.5.json" "b/agency-indexes/DoE/Xyce_\342\204\242__Parallel_Electronic_Simulator_v.7.5.json" new file mode 100644 index 00000000..7c5bd398 --- /dev/null +++ "b/agency-indexes/DoE/Xyce_\342\204\242__Parallel_Electronic_Simulator_v.7.5.json" @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-08-02", + "metadataLastUpdated": "2023-11-01" + }, + "description": "The Xyce Parallel Electronic Simulator simulates electronic circuit behavior in DC, AC, HB, MPDE and transient mode using standard analog (DAE) and/or device (PDE) device models including several age and radiation aware devices. It supports a variety of computing platforms (both serial and parallel) computers. Lastly, it uses a variety of modern solution algorithms dynamic parallel load-balancing and iterative solvers.! ! Xyce is primarily used to simulate the voltage and current behavior of a circuit network (a network of electronic devices connected via a conductive network). As a tool, it is mainly used for the design and analysis of electronic circuits.! ! Kirchoff's conservation laws are enforced over a network using modified nodal analysis. This results in a set of differential algebraic equations (DAEs). The resulting nonlinear problem is solved iteratively using a fully coupled Newton method, which in turn results in a linear system that is solved by either a standard sparse-direct solver or iteratively using Trilinos linear solver packages, also developed at Sandia National Laboratories.", + "laborHours": 0.0, + "languages": [], + "name": "Xyce(\u2122) Parallel Electronic Simulator v.7.5", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Xyce/Xyce", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "7.5" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/Xyce_\342\204\242__Parallel_Electronic_Simulator_v.7.6.json" "b/agency-indexes/DoE/Xyce_\342\204\242__Parallel_Electronic_Simulator_v.7.6.json" new file mode 100644 index 00000000..d1e45fcf --- /dev/null +++ "b/agency-indexes/DoE/Xyce_\342\204\242__Parallel_Electronic_Simulator_v.7.6.json" @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-04-14", + "metadataLastUpdated": "2023-11-01" + }, + "description": "The Xyce Parallel Electronic Simulator simulates electronic circuit behavior in DC, AC, HB, MPDE and transient mode using standard analog (DAE) and/or device (PDE) device models including several age and radiation aware devices. It supports a variety of computing platforms (both serial and parallel) computers. Lastly, it uses a variety of modern solution algorithms dynamic parallel load-balancing and iterative solvers.! ! Xyce is primarily used to simulate the voltage and current behavior of a circuit network (a network of electronic devices connected via a conductive network). As a tool, it is mainly used for the design and analysis of electronic circuits.! ! Kirchoff's conservation laws are enforced over a network using modified nodal analysis. This results in a set of differential algebraic equations (DAEs). The resulting nonlinear problem is solved iteratively using a fully coupled Newton method, which in turn results in a linear system that is solved by either a standard sparse-direct solver or iteratively using Trilinos linear solver packages, also developed at Sandia National Laboratories.", + "laborHours": 0.0, + "languages": [ + "C++", + "Perl", + "Python" + ], + "name": "Xyce(\u2122) Parallel Electronic Simulator v.7.6", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Xyce/Xyce", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "7.6" +} \ No newline at end of file diff --git a/agency-indexes/DoE/YADAS,_Version_0.json b/agency-indexes/DoE/YADAS,_Version_0.json new file mode 100644 index 00000000..f961cb0e --- /dev/null +++ b/agency-indexes/DoE/YADAS,_Version_0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "YADAS is a software system for statistical analysis using Markov chain Monte Carlo (MCMC). As such, it performs Monte Carlo integration of probability distributions and generates estimates of unknown quantities based on data and expert opinion if available. Its architecture makes it extensible enough to be helpful in the analysis of any statistical model, so it is particularly useful for statistic researchers. YADAS features a versatile scheme for defining models, and another versatile scheme for defining sampling algorithms that includes a default starting place for most analyses.", + "laborHours": 3222.4, + "name": "YADAS, Version 0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/gertvv/yadas/blob/master/COPYING.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gertvv/yadas", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/YADAS.json b/agency-indexes/DoE/YADAS.json new file mode 100644 index 00000000..5d1ea5c2 --- /dev/null +++ b/agency-indexes/DoE/YADAS.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "YADAS is a software system for statistical analysis, using Markov chain Monte carlo (MCMC). As such, it performs Monte Carlo integration of probability distributions and generates estimates of unknown quantities based on data and expert opinion if available. Its architecture makes it extensible enought to be helpful in the analysis of any statistical model, so it is particularly useful for statistic researchers. YADAS features a versatile scheme for defining models, and another versatile scheme for defining sampling algorithms that includes a default starting place for most analyses. Models are specified using bonds, which relate unknown parameters using a probability density function through functions that convert the parameters into arguments of the probability density. This structure appears to be versatile enough to be useful for virtually all statistical models. The updating algorighms emphasize componentwise random walk Metropolis algorighm updates, but YADAS also contains a framework for updating correlated parameters together. Reversible jump updates are also supported.", + "homepageURL": "http://yadas.lanl.gov/index.html", + "laborHours": 0.0, + "name": "YADAS", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://yadas.lanl.gov/node34.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://yadas.lanl.gov/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/YASKA.json b/agency-indexes/DoE/YASKA.json new file mode 100644 index 00000000..64ca9300 --- /dev/null +++ b/agency-indexes/DoE/YASKA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2020-05-28", + "metadataLastUpdated": "2020-05-28" + }, + "description": "Yaksa is a high-performance data-layout management library for noncontiguous data movement. It \nenables users to express noncontiguous data patterns and pack/unpack them to/from contiguous \nbuffers or to convert them to an IO vector describing a series of contiguous elements.\n\n\n\n", + "laborHours": 15975.2, + "languages": [], + "name": "YASKA", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pmodels/yaksa", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/YGM.json b/agency-indexes/DoE/YGM.json new file mode 100644 index 00000000..3063dc89 --- /dev/null +++ b/agency-indexes/DoE/YGM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-08" + }, + "description": "YGM provides a simplified distributed memory communication framework based on a mailbox abstraction for HPC applications. YGM is designed for irregular data-driven applications that communicate small message payloads in an all-to-all fashion. YGM aggregates and routes messages into larger payloads to gain greater bandwidth utilization on modern HPC interconnects. YGM has been demonstrated up to 131k cores of IBM BG/P Sequoia and 96k cores of Catalyst at LLNL, and contains a set of graph-inspired benchmarks.", + "laborHours": 0.0, + "languages": [], + "name": "YGM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ygm", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Yearly_Energy_Costs_for_Buildings.json b/agency-indexes/DoE/Yearly_Energy_Costs_for_Buildings.json new file mode 100644 index 00000000..b58c1591 --- /dev/null +++ b/agency-indexes/DoE/Yearly_Energy_Costs_for_Buildings.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gilmorem@osti.gov" + }, + "date": { + "created": "2018-06-19", + "metadataLastUpdated": "2022-11-10" + }, + "description": "COSTSAFR3.0 generates a set of compliance forms which will be attached to housing Requests for Proposals (RFPs) issued by Departments or Agencies of the Federal Government. The compliance forms provide a uniform method for estimating the total yearly energy cost for each proposal. COSTSAFR3.0 analyzes specific housing projects at a given site, using alternative fuel types, and considering alternative housing types. The program is designed around the concept of minimizing overall costs through energy conservation design, including first cost and future utility costs, and estabilishes a standard design to which proposed housing designs are compared. It provides a point table for each housing type that can be used to determine whether a proposed design meets the standard and how a design can be modified to meet the standard.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [], + "name": "Yearly Energy Costs for Buildings", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Yet_Another_Hauser-Feshbach_Code.json b/agency-indexes/DoE/Yet_Another_Hauser-Feshbach_Code.json new file mode 100644 index 00000000..46b64b0b --- /dev/null +++ b/agency-indexes/DoE/Yet_Another_Hauser-Feshbach_Code.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "Code framework to perform simulations of nuclear reactions with incident particles including gammas, protons, neutrons, deuterons, tritons, helium-3, and alphas to develop nuclear data libraries and study nuclear reaction phenomona. The code can model nuclear reactions or initial populations specified by the user. The decays principally follow the compound-nucleus hypothesis and the statistical decay of Hauser and Feshbach. The code models nuclear decays with a Monte Carlo process that tracks the decay of each state. Data libraries are produced that can be translated into GNDS (generalized Nuclear Data Structure). YAHFC can also be used as an event generator, with individual decays written to disk for offline analysis. Both serial and MPI versions are provided. YAHFC does NOT perform transport of nuclear reactions through materials, only the primary reaction with a target material.", + "laborHours": 0.0, + "languages": [], + "name": "Yet Another Hauser-Feshbach Code", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/Yet-Another-Hauser-Feshbach-Code", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/YoDawg_CI_Runner.json b/agency-indexes/DoE/YoDawg_CI_Runner.json new file mode 100644 index 00000000..7afb4f10 --- /dev/null +++ b/agency-indexes/DoE/YoDawg_CI_Runner.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-07", + "metadataLastUpdated": "2024-09-10" + }, + "description": "SAND2022-15186 O\nYoDawg CI Runner builds a container that hosts a Gitlab runner as a service. It provides the ability to run Podman in a nested fashion as part of a CI workflow (i.e., \"Podman-in-Podman\u201d). This allows CI jobs to be run on HPC resources by standard users through an on-demand batch scheduler. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 45.6, + "languages": [ + "Dockerfile", + "Shell" + ], + "name": "YoDawg CI Runner", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/yodawg-ci-runner", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Yokan.json b/agency-indexes/DoE/Yokan.json new file mode 100644 index 00000000..82f8ba1b --- /dev/null +++ b/agency-indexes/DoE/Yokan.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "Remote Key/Value storage service for Mochi.", + "laborHours": 0.0, + "languages": [], + "name": "Yokan", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-yokan/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-yokan", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Yoke.json b/agency-indexes/DoE/Yoke.json new file mode 100644 index 00000000..0bc95094 --- /dev/null +++ b/agency-indexes/DoE/Yoke.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-04-18", + "metadataLastUpdated": "2025-04-18" + }, + "description": "System for prototyping, training, and testing of deep ML models", + "laborHours": 9165.6, + "languages": [], + "name": "Yoke", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Yoke", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Z-CHECKER.json b/agency-indexes/DoE/Z-CHECKER.json new file mode 100644 index 00000000..0938918c --- /dev/null +++ b/agency-indexes/DoE/Z-CHECKER.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-05-17", + "metadataLastUpdated": "2021-05-18" + }, + "description": "This is a library to characterize the data and check the compression results of lossy compressors. For lossy compressor developers, Z-checker can be used to characterize critical properties (such as entropy, distribution, power spectrum, principal component analysis, and autocorrelation) of any data set to improve compression strategies. For lossy compression users, Z-checker can detect the compression quality (compression ratio and bit rate) and provide various global distortion analysis comparing the original data with the decompressed data (peak signal-to-noise ratio, normalized mean squared error, rate distortion, rate-compression error, spectral, distribution, and derivatives) and statistical analysis of the compression error (maximum, minimum, and average error; autocorrelation; and distribution of errors).Z-checker can perform the analysis with either coarse granularity (throughout the whole data set) or fine granularity (by user-defined blocks), such that the users and developers can select the best fit, adaptive compressors for different parts of the data set. Z-checker features a visualization interface displaying all analysis results in addition to some basic views of the data sets such as time series", + "laborHours": 0.0, + "languages": [], + "name": "Z-CHECKER", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CODARcode/Z-checker", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ZFP_Hardware_Implementation.json b/agency-indexes/DoE/ZFP_Hardware_Implementation.json new file mode 100644 index 00000000..6f1e77b5 --- /dev/null +++ b/agency-indexes/DoE/ZFP_Hardware_Implementation.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-27" + }, + "description": "ZFP is a floating-point compression format gaining traction in high-performance computing applications. A\nsoftware implementation has demonstrated the ability to reduce data movement across communication\nchannels and to reduce the footprint of floating-point arrays in memory. Nevertheless, any benefit in\nperformance is limited to the spare compute cycles available before reaching bandwidth limitations. A\nhardware implementation of ZFP has the potential to substantially improve HPC application performance.\nHardware compression speedup over software alone on a single CPU core ranges from 15x for 1-D\narrays to over 200x for 3-D arrays.\nThe implementation of ZFP is sourced in SystemC to facilitate its evaluation in various architectures. The\nencode pipeline consists of several modules. Uncompressed blocks of floating-point numbers in IEEE\nformat flow into the pipeline in a stream and a compressed bitstream flows out from the pipeline. The\ndecode pipeline is the inverse of the encode pipeline. A modular design enables formats other than IEEE\n(such as posits) to be considered with minor adaptations. Best performance will be realized from the\nhardware ZFP unit when batches of blocks are processed at a time. The implementation supports 1-D, 2-\nD and 3-D blocks of floating-point numbers.\nThe hardware implementation of ZFP has been validated with the software implementation of ZFP. C++\ntemplate parameters are used to specify the bit width of floating-point numbers and the array dimension\nof the encoder. A test bench program has been created with several test cases, some with continuous\ndata that is ideal for ZFP, and others with extreme cases containing numbers near or at the maximum or\nminimum values supported by the number format.", + "laborHours": 2766.4, + "languages": [], + "name": "ZFP Hardware Implementation", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/zhw.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ZFS_Interface_For_Accelerators.json b/agency-indexes/DoE/ZFS_Interface_For_Accelerators.json new file mode 100644 index 00000000..a705627e --- /dev/null +++ b/agency-indexes/DoE/ZFS_Interface_For_Accelerators.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "As data volume increases in HPC centers, storing data in reasonable amounts of space and time while maintaining data integrity and recoverability becomes ever more difficult. ZFS is a filesystem that provides these features, among many others, that make it attractive for usage in HPC environments. It has the ability to compress data, compute checksums, and compute redundancy codes within the same runtime, rather than compute each separately, without knowledge of the underlying structure of the filesystem. However, measurements have shown that compression on CPUs can be incredibly inefficient and significantly reduce the performance of ZFS. The ZFS Interface for Accelerators (Z.I.A.) was developed to provide an interface to route data to accelerators while being processed by ZFS, so that the ZFS infrastructure and features are maintained, while allowing for ZFS administrators to provide faster implementations of compression, or other features, to their instance of ZFS.", + "laborHours": 0.0, + "languages": [], + "name": "ZFS Interface For Accelerators", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/zfs", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ZFS_on_Linux.json b/agency-indexes/DoE/ZFS_on_Linux.json new file mode 100644 index 00000000..c61215cc --- /dev/null +++ b/agency-indexes/DoE/ZFS_on_Linux.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "ZFS on Linux is an advanced file system and volume manager which was originally developed for Solaris and is now maintained by the OpenZFS community.\n", + "laborHours": 238579.2, + "languages": [], + "name": "ZFS on Linux", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/zfs/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/zfs", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ZHW_hardware_library.json b/agency-indexes/DoE/ZHW_hardware_library.json new file mode 100644 index 00000000..56aed21e --- /dev/null +++ b/agency-indexes/DoE/ZHW_hardware_library.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-28", + "metadataLastUpdated": "2023-02-28" + }, + "description": "Hardware library implementation of the open source ZFP CODEC. ZHP provides a sub-set of the ZFP library compression and decompression functionality, but in the SystemC language rather than the C/C++ and Fortran languages used in the ZFP implementation.", + "laborHours": 2766.4, + "languages": [], + "name": "ZHW hardware library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/zhw", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ZPAL_v.1.0.0.json b/agency-indexes/DoE/ZPAL_v.1.0.0.json new file mode 100644 index 00000000..b8eff1ef --- /dev/null +++ b/agency-indexes/DoE/ZPAL_v.1.0.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-06", + "metadataLastUpdated": "2024-06-06" + }, + "description": "SAND2024-01003O\nZPAL is a Python software development kit designed for use by network automation engineers. It is an application programming interface (API) wrapper that is compatible with ZPE System's Nodegrid API. ZPE produces networking equipment. ZPAL simplifies connections to the ZPE Nodegrid API and makes configuration changes on the associated networking equipment.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 896.8, + "languages": [ + "Python" + ], + "name": "ZPAL v.1.0.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/ZPAL", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ZTF_image_classification.json b/agency-indexes/DoE/ZTF_image_classification.json new file mode 100644 index 00000000..8318446c --- /dev/null +++ b/agency-indexes/DoE/ZTF_image_classification.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "This repo demonstrates how to use the LLNL developed Gaussian process hyperparameter estimation method, MuyGPS, for image classification using Zwicky Transient Facility (ZTF) data.", + "laborHours": 0.0, + "languages": [], + "name": "ZTF_image_classification", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Kerianne28/ZTF_image_classification", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Zapp.json b/agency-indexes/DoE/Zapp.json new file mode 100644 index 00000000..cbf489f7 --- /dev/null +++ b/agency-indexes/DoE/Zapp.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "This code package computes the multi-species BGK kinetic model of Haack, Hauck, and Murillo [J. Stat. Phys., 168, 2017]. It uses a block adaptive mesh refinement (AMR) framework derived from the open-source, Parthenon performance portable AMR framework to provide refinement in the (up to) six dimensional phase space. It includes an atomic ionization model, accurate collision physics across coupling regimes, self-consistent electric fields, and allows for degeneracy in the electronic screening. This kinetic model greatly extends the temperature regime and the spatiotemporal scales for modeling moderately coupled plasmas.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "Zapp", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Zed_Context_Driver__ZedCD__v1.0.json b/agency-indexes/DoE/Zed_Context_Driver__ZedCD__v1.0.json new file mode 100644 index 00000000..7678209d --- /dev/null +++ b/agency-indexes/DoE/Zed_Context_Driver__ZedCD__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-08-10", + "metadataLastUpdated": "2018-08-14" + }, + "description": "The software takes the data stream generated using the ZedSDK from a Zed or Zed Mini (fancy camera that mimics human depth perception), and loads selected data streams into a rolling shared memory buffer for use in analysis codes. Essentially, the software streams data into a shared memory buffer to be analyzed only when the analysis software is triggered.", + "laborHours": 476626.4, + "languages": [], + "name": "Zed Context Driver (ZedCD) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cosama/zed-context-driver.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ZeptoOS.json b/agency-indexes/DoE/ZeptoOS.json new file mode 100644 index 00000000..16c6313d --- /dev/null +++ b/agency-indexes/DoE/ZeptoOS.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-13", + "metadataLastUpdated": "2018-07-13" + }, + "description": "ZeptoOS is a research project that focuses on operating systems for petascale architectures. It provides a complete software stack for Blue Gene/P, covering both compute and I/O nodes. ", + "laborHours": 448415.2, + "languages": [], + "name": "ZeptoOS", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://wiki.mcs.anl.gov/zeptoos/index.php/Licensing", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://svn.mcs.anl.gov/repos/ZeptoOS/trunk", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/Zero-Order_Reaction_Kinetics.json b/agency-indexes/DoE/Zero-Order_Reaction_Kinetics.json new file mode 100644 index 00000000..5be549f4 --- /dev/null +++ b/agency-indexes/DoE/Zero-Order_Reaction_Kinetics.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-01-07" + }, + "description": "Zero-RK is a software package that simulates 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b/agency-indexes/DoE/Zero-Order_Reaction_Kinetics_v._3.4.hip.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-06-06", + "metadataLastUpdated": "2023-06-16" + }, + "description": "Zero-RK is a software package that simulates chemically reacting systems using sparse, preconditioned,\nadaptive matrix methods to achieve orders-of-magnitude reduction in simulation time while maintaining\naccurate results.", + "laborHours": 13497.6, + "languages": [], + "name": "Zero-Order Reaction Kinetics v. 3.4.hip", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/zero-rk", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "3.4.hip" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Zero-Order_Reaction_Kinetics_v3.0.json b/agency-indexes/DoE/Zero-Order_Reaction_Kinetics_v3.0.json new file mode 100644 index 00000000..19ddd532 --- /dev/null +++ b/agency-indexes/DoE/Zero-Order_Reaction_Kinetics_v3.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-08", + "metadataLastUpdated": "2021-12-10" + }, + "description": "Zero-RK is a software package that simulates chemically reacting systems using sparse, preconditioned, adaptive matrix methods to achieve orders-of-magnitude reduction in simulation time while maintaining accurate results.", + "laborHours": 13497.6, + "languages": [], + "name": "Zero-Order Reaction Kinetics v3.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": 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"https://github.com/slaclab/zerorm", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Zoltan2.json b/agency-indexes/DoE/Zoltan2.json new file mode 100644 index 00000000..cc5045b7 --- /dev/null +++ b/agency-indexes/DoE/Zoltan2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-09-17" + }, + "description": "Zoltan2 is a refactoring of the open-source Zoltan library that enables Zoltan users to take better advantage of current and emerging high performance computing architectures and software tools. 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It will be available as part of Sandia's Trilinos framework of scientific computing packages.", + "laborHours": 8344830.4, + "languages": [], + "name": "Zoltan2", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Zonetool.json b/agency-indexes/DoE/Zonetool.json new file mode 100644 index 00000000..191e0bd0 --- /dev/null +++ b/agency-indexes/DoE/Zonetool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Zonetool is a utility for managing signed DNS zones and managing DNSSEC keys. It maintains the state of managed DNS zones and uses the BIND utilities to actually perform key generation, zone signing, and validation. DNS administrators will use Zonetool to initially deploy and further maintain a signed DNS zone.", + "laborHours": 0.0, + "languages": [], + "name": "Zonetool", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/zonetool", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Zotero_Robust_Links_Extension.json b/agency-indexes/DoE/Zotero_Robust_Links_Extension.json new file mode 100644 index 00000000..77f614ef --- /dev/null +++ b/agency-indexes/DoE/Zotero_Robust_Links_Extension.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-08-19" + }, + "description": "The Zotero Robust Links extension automatically creates an archival copy (memento) of the URI of an item ingested into a Zotero library. The extension can also manually be triggered to create mementos. The software also contains a \"translator\" that enables the export of \"robustified\" items with Robust Links-enhanced HTML code.", + "laborHours": 0.0, + "languages": [], + "name": "Zotero Robust Links Extension", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/Zotero-Robust-Links-Extension", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/_DG_2__Distributed_Generation_for_Distribution_Grids__[SWR-18-63].json b/agency-indexes/DoE/_DG_2__Distributed_Generation_for_Distribution_Grids__[SWR-18-63].json new file mode 100644 index 00000000..7817ce7e --- /dev/null +++ b/agency-indexes/DoE/_DG_2__Distributed_Generation_for_Distribution_Grids__[SWR-18-63].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2020-06-05", + "metadataLastUpdated": "2023-04-27" + }, + "description": "(DG)2 is an impact analysis tool for electrical utilities to perform spatio-temporal analysis with solar and battery energy storage systems. The purpose of the tool is to help distribution utilities with identifying impacts and costs associated with locating a MW-scale solar farm and energy storage system at a certain location over other choices. This tool also assists utilities to assess the amount of reverse power flow at the transmission lines.", + "laborHours": 1854.4, + "languages": [ + "HTML", + "Python" + ], + "name": "(DG)2 (Distributed Generation for Distribution Grids) [SWR-18-63]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/DG2", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/_HPCToolkit.json b/agency-indexes/DoE/_HPCToolkit.json new file mode 100644 index 00000000..fe954ba8 --- /dev/null +++ b/agency-indexes/DoE/_HPCToolkit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-06", + "metadataLastUpdated": "2020-06-01" + }, + "description": "HPCToolkit is a suite of tools for measurement and analysis of program performance. It uses hardware counters to sample the execution of a multithreaded and/or multiprocess program, enabling fine-grain measurement without modifying the source code.\n", + "laborHours": 104697.6, + "languages": [], + "name": " HPCToolkit", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HPCToolkit/hpctoolkit", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/abt-io.json b/agency-indexes/DoE/abt-io.json new file mode 100644 index 00000000..578005cb --- /dev/null +++ b/agency-indexes/DoE/abt-io.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-28", + "metadataLastUpdated": "2022-01-28" + }, + "description": "abt-io provides Argobots-aware wrappers to common POSIX I/O functions.", + "laborHours": 0.0, + "languages": [], + "name": "abt-io", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-abt-io/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-abt-io", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/adamantine-sim_adamantine.json b/agency-indexes/DoE/adamantine-sim_adamantine.json new file mode 100644 index 00000000..ecc1579a --- /dev/null +++ b/agency-indexes/DoE/adamantine-sim_adamantine.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "turcksinbr@ornl.gov" + }, + "date": { + "created": "2021-11-29", + "metadataLastUpdated": "2021-11-29" + }, + "description": "Thermal field simulation of the additive manufacturing process enhanced using data assimilation.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "adamantine-sim/adamantine", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/adamantine-sim/adamantine", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/admin_tools.json b/agency-indexes/DoE/admin_tools.json new file mode 100644 index 00000000..584a0ee3 --- /dev/null +++ b/agency-indexes/DoE/admin_tools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "Repo to hold various admin tools and utiliites.", + "laborHours": 349.6, + "languages": [], + "name": "admin_tools", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/admin_tools", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/advcubit.json b/agency-indexes/DoE/advcubit.json new file mode 100644 index 00000000..25de74c6 --- /dev/null +++ b/agency-indexes/DoE/advcubit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2023-03-15" + }, + "description": "A script package for an advanced cubit interface. Provides a lot of functionality, that is not included in the official python interface.", + "laborHours": 547.2, + "languages": [], + "name": "advcubit", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/advcubit", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/aes-stream-drivers.json b/agency-indexes/DoE/aes-stream-drivers.json new file mode 100644 index 00000000..f114c0e5 --- /dev/null +++ b/agency-indexes/DoE/aes-stream-drivers.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Common repository for streaming kernel drivers (PGP, AxiStream, ExoTem).", + "laborHours": 5168.0, + "name": "aes-stream-drivers", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/aes-stream-drivers/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/aes-stream-drivers", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/album.json b/agency-indexes/DoE/album.json new file mode 100644 index 00000000..3d67b7d2 --- /dev/null +++ b/agency-indexes/DoE/album.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "A simple web app for browsing experiments.", + "laborHours": 501.6, + "languages": [], + "name": "album", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/album", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/aldsim.json b/agency-indexes/DoE/aldsim.json new file mode 100644 index 00000000..f3aca8b4 --- /dev/null +++ b/agency-indexes/DoE/aldsim.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-09-23", + "metadataLastUpdated": "2024-09-23" + }, + "description": "SF-24-041 aldsim is a Python module that provides a set of ALD models that allow the user to explore the \nbehavior of self-limited chemistries inside common reactor configurations.", + "laborHours": 106.4, + "languages": [], + "name": "aldsim", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aldsim/aldsim", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/alignts.json b/agency-indexes/DoE/alignts.json new file mode 100644 index 00000000..20dc0c15 --- /dev/null +++ b/agency-indexes/DoE/alignts.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "Alignment of replicate time series can be useful for identifying shared but time-warps behavior in time series data such as monitoring temperature or network communication patterns for cyberphysical systems. This learning of common behavior is a first step for identifying abnormal behavior such as intrusion or anomalies. We developed the alignts R package to provide an R implementation of Listgarten (2004) with advancements described in Grosskopf (submitted 2021). The package is programmed in R and Fortran 95 with OpenMP support. The package includes functions for aligning a collection of nominally replicate time series, making forecast predictions of future states conditioned on the current data, and carrying out particle filtering for estimating uncertainty in the state of the system in an on-line data collection environment. ", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "alignts", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/als_microct_recon__microct__v1.json b/agency-indexes/DoE/als_microct_recon__microct__v1.json new file mode 100644 index 00000000..6bfe02d8 --- /dev/null +++ b/agency-indexes/DoE/als_microct_recon__microct__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Jupyter notebooks to reconstruct and visualize microCT data from ALS beamline 8.3.2. Relies on standard tomography and image processing tools (astra, tomopy, itk, scikit-image) and ipywidgets (sliders, drop down menus, etc) to make parameter selection and data visualization easy for users.", + "laborHours": 1854.4, + "languages": [], + "name": "als microct recon (microct) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/als-computing/microct", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/amerifluxr_v1.0.0.json b/agency-indexes/DoE/amerifluxr_v1.0.0.json new file mode 100644 index 00000000..b46c0da0 --- /dev/null +++ b/agency-indexes/DoE/amerifluxr_v1.0.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "An R programmatic interface for querying, handling, and summarizing AmeriFlux (https://ameriflux.lbl.gov/) data and metadata. The target users are those 1) who use data from many AmeriFlux sites, and 2) who handle data from multiple sources, e.g., AmeriFlux, PhenoCam, MODIS. The tentative features include 1) listing the sites with basic site general info, 2) querying how much data & metadata are available, 3) subsetting a target site list for download, 4) parsing data & metadata, 5) cleaning & summarizing data, 6) data visualization and 7) listing target sites' contacts & DOI.", + "laborHours": 0.0, + "languages": [], + "name": "amerifluxr v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chuhousen/amerifluxr", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ames-market_psst.json b/agency-indexes/DoE/ames-market_psst.json new file mode 100644 index 00000000..2084bcf1 --- /dev/null +++ b/agency-indexes/DoE/ames-market_psst.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-06-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python version of the AMES Wholesale Power Market Test Bed; no GUI. Previously hosted by Iowa State University; PNNL has assumed hosting. AMES existed in a non-version controlled and inconsistent form. PNNL added price-sensitive loads for transactive systems, with various other bug fixes and features.", + "laborHours": 2644.8, + "languages": [], + "name": "ames-market/psst", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ames-market/psst", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/amethst_service.json b/agency-indexes/DoE/amethst_service.json new file mode 100644 index 00000000..87c56cea --- /dev/null +++ b/agency-indexes/DoE/amethst_service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "AMETHST, or Analysis METHod Selection Tool, is an automated pipeline that makes it possible to objectively assess the relative performance of multiple analysis methods applied to annotation abundance data. Utilizing objective, permutation-based statistics, it can determine the best performing analysis from any arbitrary collection of analyses, and can also determine the degree to which each analysis step (e.g. normalization and reprocessing of the data, selection of distance/dissimilarity metric) affects the results produced by each analysis method.", + "laborHours": 288.8, + "languages": [], + "name": "amethst_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/amethst_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/amostra.json b/agency-indexes/DoE/amostra.json new file mode 100644 index 00000000..5cbfa979 --- /dev/null +++ b/agency-indexes/DoE/amostra.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "amostra is a collection of light-weight sample management classes.", + "laborHours": 912.0, + "languages": [], + "name": "amostra", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/amostra/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/amostra", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ampworks:_Battery_analysis_tools_in_Python_[SWR-25-39].json b/agency-indexes/DoE/ampworks:_Battery_analysis_tools_in_Python_[SWR-25-39].json new file mode 100644 index 00000000..4ff5ee7b --- /dev/null +++ b/agency-indexes/DoE/ampworks:_Battery_analysis_tools_in_Python_[SWR-25-39].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-03-13", + "metadataLastUpdated": "2025-03-13" + }, + "description": "Ampworks is a collection of tools designed to process experimental battery data with a focus on model-relevant analyses. It currently provides functions for incremental capacity analysis and GITT data processing, helping extract key properties for life and physics-based models (e.g., SPM and P2D). Some tools, like the incremental capacity analysis module, also include graphical user interfaces for ease of use.\n\nhttps://github.com/NREL/ampworks/\nhttps://pypi.org/project/ampworks/", + "laborHours": 2082.4, + "languages": [ + "Python" + ], + "name": "ampworks: Battery analysis tools in Python [SWR-25-39]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ampworks", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/amsession_Kmer-based-Subgenome-Mapping.json b/agency-indexes/DoE/amsession_Kmer-based-Subgenome-Mapping.json new file mode 100644 index 00000000..1f2c7e38 --- /dev/null +++ b/agency-indexes/DoE/amsession_Kmer-based-Subgenome-Mapping.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "Hybridization brings together chromosome sets from two or more distinct progenitor species. Genome duplication associated with hybridization, or allopolyploidy, allows these chromosome sets to persist as distinct subgenomes during subsequent meioses. Here, we present a general method for identifying the subgenomes of a polyploid based on shared ancestry as revealed by the genomic distribution of repetitive elements that were active in the progenitors. This subgenome-enriched transposable element signal is intrinsic to the polyploid, allowing broader applicability than other approaches that depend on the availability of sequenced diploid relatives. We develop the statistical basis of the method, demonstrate its applicability in the well-studied cases of tobacco, cotton, and Brassica napus, and apply it to several cases: allotetraploid cyprinids, allohexaploid false flax, and allooctoploid strawberry. These analyses provide insight into the origins of these polyploids, revise the subgenome identities of strawberry, and provide perspective on subgenome dominance in higher polyploids.", + "laborHours": 91.2, + "languages": [], + "name": "amsession/Kmer-based-Subgenome-Mapping", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/amsession/Kmer-based-Subgenome-Mapping", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/anarel-manage.json b/agency-indexes/DoE/anarel-manage.json new file mode 100644 index 00000000..4de789d5 --- /dev/null +++ b/agency-indexes/DoE/anarel-manage.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Manage the conda based analysis release environments that include psana at LCLS.", + "laborHours": 8740.0, + "name": "anarel-manage", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/anarel-manage/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/anarel-manage", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/anarel-test.json b/agency-indexes/DoE/anarel-test.json new file mode 100644 index 00000000..0f95e02e --- /dev/null +++ b/agency-indexes/DoE/anarel-test.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Repository to test conda based LCLS ana release system.", + "laborHours": 1048.8, + "name": "anarel-test", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/anarel-test/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/anarel-test", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/annie-rose.json b/agency-indexes/DoE/annie-rose.json new file mode 100644 index 00000000..76467b99 --- /dev/null +++ b/agency-indexes/DoE/annie-rose.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "This is the repository for annie-rose developed at Oak Ridge National Laboratory. ", + "laborHours": 516.8, + "languages": [], + "name": "annie-rose", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/annie-rose", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ansible-role-kubeadm.json b/agency-indexes/DoE/ansible-role-kubeadm.json new file mode 100644 index 00000000..de3ce511 --- /dev/null +++ b/agency-indexes/DoE/ansible-role-kubeadm.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "Basic kubeadm installation", + "laborHours": 0.0, + "languages": [], + "name": "ansible-role-kubeadm", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ansible-role-kubeadm", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ansible-role-sudo.json b/agency-indexes/DoE/ansible-role-sudo.json new file mode 100644 index 00000000..7f5ca953 --- /dev/null +++ b/agency-indexes/DoE/ansible-role-sudo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-23", + "metadataLastUpdated": "2022-08-23" + }, + "description": "Ansible role for managing sudo.", + "laborHours": 0.0, + "languages": [], + "name": "ansible-role-sudo", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ansible-role-sudo", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ansible-spark.json b/agency-indexes/DoE/ansible-spark.json new file mode 100644 index 00000000..cb3c3ccb --- /dev/null +++ b/agency-indexes/DoE/ansible-spark.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Ansible role to deploy a spark cluster.", + "laborHours": 76.0, + "name": "ansible-spark", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/ansible-role-spark/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ansible-role-spark", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/api-umbrella-cookbook_[SWR-12-16].json b/agency-indexes/DoE/api-umbrella-cookbook_[SWR-12-16].json new file mode 100644 index 00000000..6b099e26 --- /dev/null +++ b/agency-indexes/DoE/api-umbrella-cookbook_[SWR-12-16].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-09-12", + "metadataLastUpdated": "2023-06-06" + }, + "description": "This is the repository for api-umbrella-cookbook developed at National Renewable Energy Laboratory. This repository has been archived by the owner, as it is no longer used. The files are now available as read-only.", + "laborHours": 136.8, + "languages": [ + "Ruby" + ], + "name": "api-umbrella-cookbook [SWR-12-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/api-umbrella-cookbook", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/app_hybridPotts-phasefield.cpp.json b/agency-indexes/DoE/app_hybridPotts-phasefield.cpp.json new file mode 100644 index 00000000..c9491cdd --- /dev/null +++ b/agency-indexes/DoE/app_hybridPotts-phasefield.cpp.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "This application simulates microstructural and compositional evolution in two-phase, two-component systems. It is designed to run within the SPPARKS solver and combines the kMC with solution to the Cahn-Hilliard Eq. for phase field.", + "laborHours": 165102.4, + "languages": [ + "C++", + "C" + ], + "name": "app_hybridPotts-phasefield.cpp", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spparks", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/app_sintering.cpp.json b/agency-indexes/DoE/app_sintering.cpp.json new file mode 100644 index 00000000..3907e751 --- /dev/null +++ b/agency-indexes/DoE/app_sintering.cpp.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This application simulates simple solid state sintering by incorporating all the active mechanisms, namely, curvature-driven gain growth, pore shaping and migration by surface diffusion, and creation, diffusion and annihilation of vacancies. It is an application developed for SPPARKS and has to be run within this framework.", + "homepageURL": "http://spparks.sandia.gov", + "laborHours": 0.0, + "name": "app_sintering.cpp", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://spparks.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/apricots.json b/agency-indexes/DoE/apricots.json new file mode 100644 index 00000000..73b3eceb --- /dev/null +++ b/agency-indexes/DoE/apricots.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-01-24", + "metadataLastUpdated": "2025-01-24" + }, + "description": "APRICOTS: Averaged-Polarization Resampled Integrated Correlated Omnidirectional Test Statistics (O4835)", + "laborHours": 562.4, + "languages": [], + "name": "apricots", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/apricots", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/arVpyf.json b/agency-indexes/DoE/arVpyf.json new file mode 100644 index 00000000..d97037c2 --- /dev/null +++ b/agency-indexes/DoE/arVpyf.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "Archiver Python Frontend represents a collection of Python classes associated with the EPICS Archiver Appliance middle layer and other data sources for building composite and extandable applications and integrating them with general (like Apache Spark) or domain-wide (like NSLS-II Databroker) data management and processing systems.", + "laborHours": 805.6, + "languages": [], + "name": "arVpyf", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/arvpyf/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/arvpyf", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/arborq.json b/agency-indexes/DoE/arborq.json new file mode 100644 index 00000000..ecf0299b --- /dev/null +++ b/agency-indexes/DoE/arborq.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "Python library for querying Arbor PeakFlow devices.", + "laborHours": 942.4, + "languages": [], + "name": "arborq", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/arborq/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/arborq", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/archapp.json b/agency-indexes/DoE/archapp.json new file mode 100644 index 00000000..ae4c8d45 --- /dev/null +++ b/agency-indexes/DoE/archapp.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "Python interface to archiver appliance that most closely matches the legacy xpppython api.\n", + "laborHours": 440.8, + "languages": [], + "name": "archapp", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/archapp/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/archapp", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/archspec.json b/agency-indexes/DoE/archspec.json new file mode 100644 index 00000000..66ee5f9a --- /dev/null +++ b/agency-indexes/DoE/archspec.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "Archspec aims at providing a standard set of human-understandable labels for various aspects of a system architecture like CPU, network fabrics, etc. and APIs to detect, query and compare them. This project grew out of Spack and is currently under active development. At present it supports APIs to detect and model compatibility relationships among different CPU microarchitectures.", + "laborHours": 0.0, + "languages": [], + "name": "archspec", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/archspec/archspec", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/arduino-base64.json b/agency-indexes/DoE/arduino-base64.json new file mode 100644 index 00000000..ca009d31 --- /dev/null +++ b/agency-indexes/DoE/arduino-base64.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-16", + "metadataLastUpdated": "2022-08-16" + }, + "description": "This library provides methods for encoding binary into base64 strings and the reverse operation.", + "laborHours": 0.0, + "languages": [], + "name": "arduino-base64", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/arduino-base64", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/areaDetector.json b/agency-indexes/DoE/areaDetector.json new file mode 100644 index 00000000..0d72d31f --- /dev/null +++ b/agency-indexes/DoE/areaDetector.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "The top-level repository for the EPICS areaDetector software. This repository contains mostly documentation, configuration files, and a top-level Makefile to build the entire areaDetector package.", + "laborHours": 866.4, + "languages": [], + "name": "areaDetector", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/areaDetector/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/areaDetector", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/arianna-ppl.json b/agency-indexes/DoE/arianna-ppl.json new file mode 100644 index 00000000..d1c5b378 --- /dev/null +++ b/agency-indexes/DoE/arianna-ppl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-04-18", + "metadataLastUpdated": "2025-04-18" + }, + "description": "A probabilistic programming language for python built on numpy", + "laborHours": 1124.8, + "languages": [], + "name": "arianna-ppl", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/arianna-ppl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/arista-tapagg-ansible.json b/agency-indexes/DoE/arista-tapagg-ansible.json new file mode 100644 index 00000000..7a16218e --- /dev/null +++ b/agency-indexes/DoE/arista-tapagg-ansible.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "This is the repository for arista-tapagg-ansible, developed by the Energy Sciences Network (ESnet). ", + "laborHours": 15.2, + "languages": [], + "name": "arista-tapagg-ansible", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/arista-tapagg-ansible", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/armish-fireplace.json b/agency-indexes/DoE/armish-fireplace.json new file mode 100644 index 00000000..6501679d --- /dev/null +++ b/agency-indexes/DoE/armish-fireplace.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Armish-fireplace is a middleware container. It allows asynchronous rx and tx for the client implemented with a multithreaded buffer. It contains modules which organizes module-specific processing units. These processing units are the heart of the processing armish-fireplace does. A processing unit may be a hardware device driver or a hardware simulation driver. 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The scoring tool will store user-provided data and generate an asset score and system evaluation for your building envelope and mechanical and electrical systems. The tool will also identify cost-effective upgrade opportunities and help you gain insight into the energy efficiency potential of your building.", + "laborHours": 2705.6, + "languages": [], + "name": "asset-score-api-test-harness", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/asset-score-api-test-harness/blob/master/Readme.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/asset-score-api-test-harness", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/atlas-chess2.json b/agency-indexes/DoE/atlas-chess2.json new file mode 100644 index 00000000..328b86b4 --- /dev/null +++ b/agency-indexes/DoE/atlas-chess2.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Project for ATLAS CHESS2 ASIC Development.", + "laborHours": 21386.4, + "name": "atlas-chess2", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/atlas-chess2/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/atlas-chess2", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/auth_lite.json b/agency-indexes/DoE/auth_lite.json new file mode 100644 index 00000000..d46c7b64 --- /dev/null +++ b/agency-indexes/DoE/auth_lite.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is a C implementation of the authentication clients.", + "laborHours": 10184.0, + "languages": [], + "name": "auth_lite", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/auth_lite", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/awe_monitor.json b/agency-indexes/DoE/awe_monitor.json new file mode 100644 index 00000000..eda3a940 --- /dev/null +++ b/agency-indexes/DoE/awe_monitor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "Support for a pool of production awe clients.", + "laborHours": 106.4, + "languages": [], + "name": "awe_monitor", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/awe_monitor", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/awe_service.json b/agency-indexes/DoE/awe_service.json new file mode 100644 index 00000000..ab12d630 --- /dev/null +++ b/agency-indexes/DoE/awe_service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-25", + "metadataLastUpdated": "2020-08-25" + }, + "description": "The awe_service repository provides KBase release engineering tools for the deployment of the AWE client and server. The AWE repository is included as a submodule in the awe_service repository and is maintained at http://github.com/MG-RAST/AWE. ", + "laborHours": 182.4, + "languages": [], + "name": "awe_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/awe_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/awe_utils.json b/agency-indexes/DoE/awe_utils.json new file mode 100644 index 00000000..316ff8d0 --- /dev/null +++ b/agency-indexes/DoE/awe_utils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "A collection of utilities for working with AWE.", + "laborHours": 30.4, + "languages": [], + "name": "awe_utils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/awe_utils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/axi-pcie-core.json b/agency-indexes/DoE/axi-pcie-core.json new file mode 100644 index 00000000..7477710a --- /dev/null +++ b/agency-indexes/DoE/axi-pcie-core.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-06", + "metadataLastUpdated": "2022-07-06" + }, + "description": "This GIT repository is intended to be a common firmware library submodule used by many other applications.", + "laborHours": 0.0, + "languages": [], + "name": "axi-pcie-core", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/axi-pcie-core/blob/main/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/axi-pcie-core", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/backstroke.json b/agency-indexes/DoE/backstroke.json new file mode 100644 index 00000000..0494a24c --- /dev/null +++ b/agency-indexes/DoE/backstroke.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Backstroke is a tool for reversible computation and supports C++11. It is a command line tool for generating reversible C++ source code and is distributed with a runtime library that can maintain all data necessary to support reversibility. The runtime library implements a so called Runtime State Store (RTSS) and is called rtss library. Backstroke implements a technique for incremental state saving (also called incremental check-pointing). Backstroke supports the simulator ROSS for parallel discrete event simulation (PDES) and can establish automatically the reversibility of ROSS models.\n", + "laborHours": 5031.2, + "languages": [], + "name": "backstroke", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/backstroke", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/basecRAWller_v0.1.json b/agency-indexes/DoE/basecRAWller_v0.1.json new file mode 100644 index 00000000..b5c8c811 --- /dev/null +++ b/agency-indexes/DoE/basecRAWller_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-31", + "metadataLastUpdated": "2019-10-31" + }, + "description": "This software implements the first base caller for nanopore data that calls bases directly from raw data. The basecRAWller algorithm has two major advantages over current nanopore base calling software: (1) streaming base calling and (2) base calling from information rich raw signal. The ability to perform truly streaming base calling as signal is received from the sequencer can be very powerful as this is one of the major advantages of this technology as compared to other sequencing technologies. As such enabling as much streaming potential as possible will be incredibly important as this technology continues to become more widely applied in biosciences. All other base callers currently employ the Viterbi algorithm which requires the whole sequence to employ the complete base calling procedure and thus precludes a natural streaming base calling procedure. The other major advantage of the basecRAWller algorithm is the prediction of bases from raw signal which contains much richer information than the segmented chunks that current algorithms employ. This leads to the potential for much more accurate base calls which would make this technology much more valuable to all of the growing user base for this technology.", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 1976.0, + "languages": [], + "name": "basecRAWller v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/batoid.json b/agency-indexes/DoE/batoid.json new file mode 100644 index 00000000..3c2608f4 --- /dev/null +++ b/agency-indexes/DoE/batoid.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-08", + "metadataLastUpdated": "2020-07-08" + }, + "description": "Batoid is a c++ backed python optical raytracer. It uses geometric optics to characterize the optical\nperformance of survey telescopes such as LSST, Subaru-HSC, Blanco-DECam, or Mayall-DESI.", + "laborHours": 39702.4, + "languages": [], + "name": "batoid", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmeyers314/batoid", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/battery-data-toolkit.json b/agency-indexes/DoE/battery-data-toolkit.json new file mode 100644 index 00000000..6564f084 --- /dev/null +++ b/agency-indexes/DoE/battery-data-toolkit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-19", + "metadataLastUpdated": "2021-08-19" + }, + "description": "This software package contains utilities for ingesting battery cycling data from various equipment and converting it to a common file format including metadata. Further development of the package will include utilities for further processing the data for a variety of machine learning tasks.", + "laborHours": 0.0, + "languages": [], + "name": "battery-data-toolkit", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/materials-data-facility/battery-data-toolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/batteryNET_v0.0.1.json b/agency-indexes/DoE/batteryNET_v0.0.1.json new file mode 100644 index 00000000..373c6cab --- /dev/null +++ b/agency-indexes/DoE/batteryNET_v0.0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-07-30", + "metadataLastUpdated": "2024-07-30" + }, + "description": "Code to organize, prepare, and segment multi-scan, larger-than-memory, volumetric dataset. Deep learning segmentation uses pytorch-lightning for code organization, logging and metrics, and multi-GPU parallelization of training and prediction. Also uses moani for volumetric data augmentation and model implementation (currently U-Net++). Training can be done slice-by-slice with 2D models trained on 2D patches either aligned with or perpendicular to the electrode plane, or with 3D models on 3D patches. Sparse labels can be used to minimize required hand-labeling -- less than 0.1% of the entire dataset was labeled. Also includes code for data preparation (alignment/cropping/patching).", + "laborHours": 714.4, + "languages": [], + "name": "batteryNET v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-camera/batteryNET", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bbcp.json b/agency-indexes/DoE/bbcp.json new file mode 100644 index 00000000..d9727b61 --- /dev/null +++ b/agency-indexes/DoE/bbcp.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-06-21", + "metadataLastUpdated": "2018-06-21" + }, + "description": "Securely and quickly copy data from source to target. bbcp is a point-to-point network file copy application. It is capable of transferring files at approaching line speeds in the WAN.\n", + "laborHours": 7919.2, + "languages": [], + "name": "bbcp", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.slac.stanford.edu/~abh/bbcp/#_Toc392015168", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/bbcp", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bcsio.json b/agency-indexes/DoE/bcsio.json new file mode 100644 index 00000000..d88c90e9 --- /dev/null +++ b/agency-indexes/DoE/bcsio.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "An asynchronous Bascamp API library.", + "laborHours": 121.6, + "languages": [], + "name": "bcsio", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/bcsio", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/becquerel__bq__v0.4.0.json b/agency-indexes/DoE/becquerel__bq__v0.4.0.json new file mode 100644 index 00000000..91ff8c07 --- /dev/null +++ b/agency-indexes/DoE/becquerel__bq__v0.4.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-10-07", + "metadataLastUpdated": "2021-10-07" + }, + "description": "Becquerel is a Python package for analyzing nuclear spectroscopic measurements. The core functionalities are reading and writing different spectrum file types, fitting spectral features, rebinning spectrum counts to different bin edges, performing detector calibrations and interpreting measurement results. It also includes tools for visualizing radiation spectra and fits of different spectral features, as well as convenient access to tabulated nuclear data both from remote servers and local caches. It relies heavily on the standard scientific Python stack of numpy, scipy, matplotlib, pandas, and numba. It is intended to be general-purpose enough that it can be useful to anyone from an undergraduate taking a laboratory course to the advanced", + "laborHours": 4757.6, + "languages": [], + "name": "becquerel (bq) v0.4.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-anp/becquerel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/beluga.json b/agency-indexes/DoE/beluga.json new file mode 100644 index 00000000..34de848c --- /dev/null +++ b/agency-indexes/DoE/beluga.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-10-01", + "metadataLastUpdated": "2024-09-20" + }, + "description": "beluga is an open-source optimal control software that uses publicly available, indirect methods from GitHub. beluga's indirect optimization engine has been reworked to follow a lazy functional paradigm. This improves the software's flexibility and enables users to create their own optimization processes without modification of the source code. beluga is general-purpose and therefore very broad in scope and application. SAND2020-12847 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 19015.2, + "languages": [ + "Python", + "Shell" + ], + "name": "beluga", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/beluga", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.4.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/berkeleylab_reproducible.json b/agency-indexes/DoE/berkeleylab_reproducible.json new file mode 100644 index 00000000..4a4500a6 --- /dev/null +++ b/agency-indexes/DoE/berkeleylab_reproducible.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2019-04-22" + }, + "description": "The software is a research tool for improving the reproducibility of simulations. It does this by keeping a log file of the input file and the input parameters; it also helps with running the same simulations on different computers such as desktops and clusters. It's should be useful for anyone who runs many simulations with input files that are kept in a git repository.", + "laborHours": 395.2, + "languages": [], + "name": "berkeleylab/reproducible", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/reproducible", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/bernstein-2016-productivity-and-diversity.json b/agency-indexes/DoE/bernstein-2016-productivity-and-diversity.json new file mode 100644 index 00000000..3c63ada1 --- /dev/null +++ b/agency-indexes/DoE/bernstein-2016-productivity-and-diversity.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Trade-offs between microbiome diversity and productivity in a stratified microbial mat", + "laborHours": 456.0, + "languages": [], + "name": "bernstein-2016-productivity-and-diversity", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/bernstein-2016-productivity-and-diversity/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/bernstein-2016-productivity-and-diversity", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bernstein-2017-productivity-and-diversity-2.json b/agency-indexes/DoE/bernstein-2017-productivity-and-diversity-2.json new file mode 100644 index 00000000..3b33574f --- /dev/null +++ b/agency-indexes/DoE/bernstein-2017-productivity-and-diversity-2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Primary and heterotrophic productivity relate to multi-kingdom diversity in a hypersaline mat", + "laborHours": 1292.0, + "languages": [], + "name": "bernstein-2017-productivity-and-diversity-2", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/bernstein-2017-productivity-and-diversity-2", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bhr-client-exabgp.json b/agency-indexes/DoE/bhr-client-exabgp.json new file mode 100644 index 00000000..3bee4794 --- /dev/null +++ b/agency-indexes/DoE/bhr-client-exabgp.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-07-05" + }, + "description": "BHR Block manager that uses ExaBGP.\n", + "laborHours": 91.2, + "languages": [], + "name": "bhr-client-exabgp", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ncsa/bhr-client-exabgp/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/bhr-client-exabgp", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bhr-client.json b/agency-indexes/DoE/bhr-client.json new file mode 100644 index 00000000..3be4e535 --- /dev/null +++ b/agency-indexes/DoE/bhr-client.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "This is the repository for the client for the BHR site. ", + "laborHours": 395.2, + "languages": [], + "name": "bhr-client", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ncsa/bhr-client/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/bhr-client", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bifacialVF_-_Bifacial_PV_View_Factor_model_2022_[SWR_17-58].json b/agency-indexes/DoE/bifacialVF_-_Bifacial_PV_View_Factor_model_2022_[SWR_17-58].json new file mode 100644 index 00000000..2247a274 --- /dev/null +++ b/agency-indexes/DoE/bifacialVF_-_Bifacial_PV_View_Factor_model_2022_[SWR_17-58].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-14" + }, + "description": "bifacialvf is a self-contained view factor (or configuration factor) model which replicates a 5-row PV system of infinite extent perpendicular to the module rows. \nSingle-axis tracking is supported, and hourly output files based on TMY inputs are saved. Spatial nonuniformity is reported, with multiple rear-facing irradiances collected on the back of each module row.\n\nBilinear interpolation code add-on to bifacialvf (description below) to pre-generate IV arrays and bifacial coefficients, and to examine the energy production with back side irradiance mismatch for either a portrait or landscape module.\nIncluded are IV curves and bifacial info for a Yingli (standard) module.\n\nBased on the publication: \"A Practical Irradiance Model for Bifacial PV Modules\" B. Marion, S. MacAlpine, C. Deline, A. Asgharzadeh, F. Toor, D. Riley, J. Stein, C. Hansen 2017 IEEE Photovoltaic Specialists Conference, Washington DC, 2017 URL: https://www.nrel.gov/docs/fy17osti/67847.pdf\n", + "laborHours": 1018.4, + "languages": [ + "Python" + ], + "name": "bifacialVF - Bifacial PV View Factor model 2022 [SWR 17-58]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bifacialvf", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.8.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bifacialVF_-_Bifacial_PV_View_Factor_model_[SWR_17-58].json b/agency-indexes/DoE/bifacialVF_-_Bifacial_PV_View_Factor_model_[SWR_17-58].json new file mode 100644 index 00000000..5b96364e --- /dev/null +++ b/agency-indexes/DoE/bifacialVF_-_Bifacial_PV_View_Factor_model_[SWR_17-58].json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-04-19", + "metadataLastUpdated": "2023-08-16" + }, + "description": "bifacialvf is a self-contained view factor (or configuration factor) model which replicates a 5-row PV system of infinite extent perpendicular to the module rows. Single-axis tracking is supported, and hourly output files based on TMY inputs are saved. Spatial nonuniformity is reported, with multiple rear-facing irradiances collected on the back of each module row.\n\nBilinear interpolation code add-on to bifacialvf (description below) to pre-generate IV arrays and bifacial coefficients, and to examine the energy production with back side irradiance mismatch for either a portrait or landscape module.\nIncluded are IV curves and bifacial info for a Yingli (standard) module.\n\nBased on the publication: \"A Practical Irradiance Model for Bifacial PV Modules\" B. Marion, S. MacAlpine, C. Deline, A. Asgharzadeh, F. Toor, D. Riley, J. Stein, C. Hansen 2017 IEEE Photovoltaic Specialists Conference, Washington DC, 2017 URL: https://www.nrel.gov/docs/fy17osti/67847.pdf\n", + "laborHours": 1018.4, + "languages": [], + "name": "bifacialVF - Bifacial PV View Factor model [SWR 17-58]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bifacialvf", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/biochem_modeling_api.json b/agency-indexes/DoE/biochem_modeling_api.json new file mode 100644 index 00000000..67ee51c4 --- /dev/null +++ b/agency-indexes/DoE/biochem_modeling_api.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This is the repository for \"biochem_modeling_api\" developed by KBase. ", + "laborHours": 5168.0, + "languages": [], + "name": "biochem_modeling_api", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/biochem_modeling_api", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/biodataganache_SIEVE-Ub.json b/agency-indexes/DoE/biodataganache_SIEVE-Ub.json new file mode 100644 index 00000000..512798e3 --- /dev/null +++ b/agency-indexes/DoE/biodataganache_SIEVE-Ub.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-06-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Code and data for the SIEVE-Ub prediction algorithm for prediction of E3 ubiquitin ligase mimics\nThe SIEVEUb approach is a novel approach to determination of sequence similarity that retains flexibility in sequence via a reduced amino acid alphabet and does not require sequence alignment, a prohibitive step for many applications.", + "laborHours": 1094.4, + "languages": [], + "name": "biodataganache/SIEVE-Ub", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biodataganache/SIEVE-Ub", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/blockbuster.json b/agency-indexes/DoE/blockbuster.json new file mode 100644 index 00000000..0b3b951e --- /dev/null +++ b/agency-indexes/DoE/blockbuster.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Blockbuster is a movie player designed for playing movies in the \"Streaming Movie\" format on large power walls. It includes a Sidecar component for controlling the movie player from a remote workstation, and for executing \"movie cues\" to facilitate one-click execution of a planned series of movie transitions, window placements, and other actions that might occur during a presentation.\n", + "laborHours": 137377.6, + "languages": [], + "name": "blockbuster", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/blockbuster", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bluesky-kafka.json b/agency-indexes/DoE/bluesky-kafka.json new file mode 100644 index 00000000..5e385184 --- /dev/null +++ b/agency-indexes/DoE/bluesky-kafka.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "This is the repository for the bluesky-kafka module. Meant to use with databroker.", + "laborHours": 516.8, + "languages": [], + "name": "bluesky-kafka", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/bluesky-kafka/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/bluesky-kafka", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bluesky-zmq-debian.json b/agency-indexes/DoE/bluesky-zmq-debian.json new file mode 100644 index 00000000..e625d7ec --- /dev/null +++ b/agency-indexes/DoE/bluesky-zmq-debian.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "This is the repository for bluesky-zmq-debian developed at Brookhaven National Laboratory. ", + "laborHours": 30.4, + "languages": [], + "name": "bluesky-zmq-debian", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/bluesky-zmq-debian", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bnl_pub-Maffettone_2020_08.json b/agency-indexes/DoE/bnl_pub-Maffettone_2020_08.json new file mode 100644 index 00000000..1e7fb116 --- /dev/null +++ b/agency-indexes/DoE/bnl_pub-Maffettone_2020_08.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "pmaffetto@bnl.gov" + }, + "date": { + "created": "2021-03-16", + "metadataLastUpdated": "2021-03-16" + }, + "description": "The application of the XCA package as first demonstrated in aXiv:2008.00283. \n\nABSTRACT: The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain manual, time consuming, error prone, and impossible to scale. With the advent of autonomous robotic scientists or self-driving labs, contemporary techniques prohibit the integration of XRD. Here, we describe a computer program for the autonomous characterization of XRD data, driven by artificial intelligence (AI), for the discovery of new materials. Starting from structural databases, we train an ensemble model using a physically accurate synthetic dataset, which output probabilistic classifications --- rather than absolutes --- to overcome the overconfidence in traditional neural networks. This AI agent behaves as a companion to the researcher, improving accuracy and offering unprecedented time savings, and is demonstrated on a diverse set of organic and inorganic materials challenges. This innovation is directly applicable to inverse design approaches, robotic discovery systems, and can be immediately considered for other forms of characterization such as spectroscopy and the pair distribution function.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "bnl/pub-Maffettone_2020_08", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bnl/pub-Maffettone_2020_08", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bnl_pub-Maffettone_2021_02.json b/agency-indexes/DoE/bnl_pub-Maffettone_2021_02.json new file mode 100644 index 00000000..afaf55f8 --- /dev/null +++ b/agency-indexes/DoE/bnl_pub-Maffettone_2021_02.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "scampbell@bnl.gov" + }, + "date": { + "created": "2021-03-03", + "metadataLastUpdated": "2021-03-03" + }, + "description": "Code relating to publication doi:10.1088/2632-2153/abc9fc", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "bnl/pub-Maffettone_2021_02", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/BNL/pub-Maffettone_2021_02", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bokeh_streaming_[SWR_19-08].json b/agency-indexes/DoE/bokeh_streaming_[SWR_19-08].json new file mode 100644 index 00000000..1caadf84 --- /dev/null +++ b/agency-indexes/DoE/bokeh_streaming_[SWR_19-08].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-04-02", + "metadataLastUpdated": "2023-08-16" + }, + "description": "Simple examples of bokeh streaming data. The plots are intended to be generic and able to infer some of the plot data from the structure of the data sent. The receiver accepts zlib compressed pickled python dictionaries.", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "bokeh streaming [SWR 19-08]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/bokeh-streaming", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/brokerStreamServer.json b/agency-indexes/DoE/brokerStreamServer.json new file mode 100644 index 00000000..729885fe --- /dev/null +++ b/agency-indexes/DoE/brokerStreamServer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-03", + "metadataLastUpdated": "2019-07-03" + }, + "description": "This service provides means to stream data from data collection interface to analysis, while logging data into metadataStore.", + "laborHours": 106.4, + "languages": [], + "name": "brokerStreamServer", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/brokerStreamServer", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/brulilo,_Version_0.x.json b/agency-indexes/DoE/brulilo,_Version_0.x.json new file mode 100644 index 00000000..f9f6fcf1 --- /dev/null +++ b/agency-indexes/DoE/brulilo,_Version_0.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "brulilo is a Python package for building and evolving thermonuclear reaction networks, such as those used in astrophysical explosion calculations. It is very much a current work in progress, and much of the intended functionality is still under development. The main goal of brulilo is an easy-to-use code for quick calculations or post-processing, as well as a learning tool to test various implementations of solvers on both CPUs and GPUs. Currently, brulilo parses an input text file that specifies the reactions to be included in the network. The notation of the inputs are in the typical astrophysical notation; i.e. hydrogen burning to deuterium in the sun, \"p + p + e --> d + neutrino\", is given as \"p(p,)d.\" Each reaction is added to a list comprising the reaction network, and once completed, the network contains a list of all isotopes and reactions involved. brulilo then parses publicly available nuclear data (binding energy, spin, partition function data, etc.) for each isotope from the WebNucleo group's data at nucleo.ces.clemson.edu. Fits to reaction rate data for each reaction are obtained from the publicly available data provided by the Joint Institute for Nuclear Astrophysics' Reaclib database. Reverse reactions are calculated from detailed balance. The reaction network then consists of a sparse system of mathematically stiff ordinary differential equations (ODEs). Physically, \"stiffness\" here means that there are some reaction rates that are occurring much faster than others; the ratio of the fast to slow often being greater than 10^15 in astrophysics. Numerical integration of such systems typically involves implicit integration schemes, which brulilo will leverage from the scientific computing Python package, Numpy, as well as implement its own. There has recently been work from researchers at Oak Ridge National Lab who have found good results from applying quasi-equilibrium and quasi-asymptotic conditions to the stiff system of ODEs, which effectively remove some of the stiffness and allow for efficient explicit integration techniques to be used. The original intent of brulilo was to implement these stiffness-alleviating techniques with explicit integrators and compare the performance to traditional implicit integrations of the full stiff system. This is still underway, as the code is very much in an alpha-release state. Furthermore, explicit integrators are often much easier to parallelize than their implicit counterparts. brulilo will implement parallelization of these techniques, leveraging both the Python implementation of MPI, mpi4py, as well as highly parallelized versions targeted at GPUs with PyOpenCL and/or PyCUDA.", + "laborHours": 1743379.2, + "name": "brulilo, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cmsquared/brulilo/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmsquared/brulilo", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bsas.json b/agency-indexes/DoE/bsas.json new file mode 100644 index 00000000..dd4ebb94 --- /dev/null +++ b/agency-indexes/DoE/bsas.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-09", + "metadataLastUpdated": "2022-08-09" + }, + "description": "Beam Synchronous data Acquisition Service.", + "laborHours": 0.0, + "languages": [], + "name": "bsas", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/bsas/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/bsas", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bsf-py.json b/agency-indexes/DoE/bsf-py.json new file mode 100644 index 00000000..2c00ce50 --- /dev/null +++ b/agency-indexes/DoE/bsf-py.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python wrapper for Blazing Signature Filter; The Blazing Signature Filter (BSF) is a highly efficient pairwise similarity algorithm which enables extensive data mining within a reasonable amount of time.", + "laborHours": 319.2, + "languages": [], + "name": "bsf-py", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/bsf-py", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bueno.json b/agency-indexes/DoE/bueno.json new file mode 100644 index 00000000..9e2c2ca7 --- /dev/null +++ b/agency-indexes/DoE/bueno.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "System benchmarking provides a means to compare or assess the performance of hardware or software against a point of reference. Because of the multitude of factors that ultimately influence a benchmark\u2019s results, reproducibility is challenging. To aid in this, we present a software framework named bueno that provides mechanisms to automate many arduous, error-prone benchmarking tasks: environmental setup; program compilation/execution; data storage and analysis.", + "laborHours": 0.0, + "languages": [], + "name": "bueno", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/bueno", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/build-blocker-plugin.json b/agency-indexes/DoE/build-blocker-plugin.json new file mode 100644 index 00000000..7275649f --- /dev/null +++ b/agency-indexes/DoE/build-blocker-plugin.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2020-05-27" + }, + "description": "build-blocker-plugin is a Jenkins build blocker plugin. ", + "laborHours": 136.8, + "languages": [], + "name": "build-blocker-plugin", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rose-compiler/build-blocker-plugin", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/buildtest-cori_v0.1.json b/agency-indexes/DoE/buildtest-cori_v0.1.json new file mode 100644 index 00000000..5df35760 --- /dev/null +++ b/agency-indexes/DoE/buildtest-cori_v0.1.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-04-09", + "metadataLastUpdated": "2021-06-15" + }, + "description": "Testsuite for Cori system using buildtest", + "laborHours": 0.0, + "languages": [], + "name": "buildtest-cori v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/buildtesters/buildtest-cori", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/buildtest_v0.9.1.json b/agency-indexes/DoE/buildtest_v0.9.1.json new file mode 100644 index 00000000..8d73f73a --- /dev/null +++ b/agency-indexes/DoE/buildtest_v0.9.1.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-07", + "metadataLastUpdated": "2021-03-07" + }, + "description": "Buildtest is used on Cori system to run regression test, there is a Cori test suite at https://github.com/buildtesters/buildtest-cori that leverages buildtest to run the tests.", + "laborHours": 0.0, + "languages": [], + "name": "buildtest v0.9.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/buildtesters/buildtest", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v.0.9.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bulkS3upload.json b/agency-indexes/DoE/bulkS3upload.json new file mode 100644 index 00000000..4b33ae67 --- /dev/null +++ b/agency-indexes/DoE/bulkS3upload.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "This is a tool written in Go that uses S3 client libraries and Go workers to concurrently upload large numbers of files into an S3 destination.", + "laborHours": 106.4, + "languages": [], + "name": "bulkS3upload", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/bulkS3upload", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/burtscher_LICO.json b/agency-indexes/DoE/burtscher_LICO.json new file mode 100644 index 00000000..5e86f6e5 --- /dev/null +++ b/agency-indexes/DoE/burtscher_LICO.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "burtscher@txstate.edu" + }, + "date": { + "created": "2024-01-08", + "metadataLastUpdated": "2024-01-08" + }, + "description": "LICO is a fast lossless image compressor. It takes BMP files (in 24-bit BMP3 format) as input.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "burtscher/LICO", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/burtscher/LICO", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/bus.py_[SWR-15-14].json b/agency-indexes/DoE/bus.py_[SWR-15-14].json new file mode 100644 index 00000000..f3f267fd --- /dev/null +++ b/agency-indexes/DoE/bus.py_[SWR-15-14].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-03-11" + }, + "description": "Bus.py is a transmission bus emulator with functionality for communicating with the distribution simulation software GridLAB-D.", + "laborHours": 1535.2, + "languages": [ + "Python" + ], + "name": "bus.py [SWR-15-14]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/buspy", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "v1.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/c-lime.json b/agency-indexes/DoE/c-lime.json new file mode 100644 index 00000000..4aae0837 --- /dev/null +++ b/agency-indexes/DoE/c-lime.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "bjoo@jlab.org" + }, + "date": { + "created": "2018-05-08", + "metadataLastUpdated": "2018-05-08" + }, + "description": "A library to read LIME files. LIME is a record oriented file format allowing binary and textual records to be kept in the same file. It is based on a proposed Internet standard by Microsoft called DIME which is now part of the .NET framework.", + "laborHours": 1869.6, + "name": "c-lime", + "organization": "Thomas Jefferson National Accelerator Facility (TJNAF)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://raw.githubusercontent.com/usqcd-software/c-lime/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/usqcd-software/c-lime", + "status": "Development", + "tags": [ + "DOE CODE", + "Thomas Jefferson National Accelerator Facility (TJNAF)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cDF_Theory_Software_for_mesoscopic_modeling_of_equilibrium_and_transport_phenomena.json b/agency-indexes/DoE/cDF_Theory_Software_for_mesoscopic_modeling_of_equilibrium_and_transport_phenomena.json new file mode 100644 index 00000000..791aa7a5 --- /dev/null +++ b/agency-indexes/DoE/cDF_Theory_Software_for_mesoscopic_modeling_of_equilibrium_and_transport_phenomena.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-10" + }, + "description": "The approach is based on classical Density Functional Theory (cDFT) coupled with the Poisson-Nernst-Planck (PNP) transport kinetics model and quantum mechanical description of short-range interaction and elementary transport processes. The model we proposed and implemented is fully atomistic, taking into account pairwise short-range and manybody long-range interactions. But in contrast to standard molecular dynamics (MD) simulations, where long-range manybody interactions are evaluated as a sum of pair-wise atom-atom contributions, we include them analytically based on well-established theories of electrostatic and excluded volume interactions in multicomponent systems. This feature of the PNP/cDFT approach allows us to reach well beyond the length-scales accessible to MD simulations, while retaining the essential physics of interatomic interactions from first principles and in a parameter-free fashion.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 0.0, + "languages": [ + "FORTRAN" + ], + "name": "cDF Theory Software for mesoscopic modeling of equilibrium and transport phenomena", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/cabbi-bio_BECT-ABM.json b/agency-indexes/DoE/cabbi-bio_BECT-ABM.json new file mode 100644 index 00000000..f20237c2 --- /dev/null +++ b/agency-indexes/DoE/cabbi-bio_BECT-ABM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-06", + "metadataLastUpdated": "2024-11-06" + }, + "description": "The emergence of the cellulosic bioeconomy requires not only adequate technological, economic, and policy advances, but also effective communication and coordination among the multiple stakeholders in the bioeconomy community. Aiming to facilitate stakeholder communication and collaboration for cellulosic bioeconomy growth, an agent-based model is developed as a community communication tool in this study. The tool simulates the behaviors and interactions of key stakeholders, as well as the responses and interactions between the stakeholders and biophysical, socioeconomic, and environmental conditions. The agent behavior rules are developed and validated based on behavior and economic theories and information attained from a stakeholder focus group study and a land use survey.", + "laborHours": 3891.2, + "languages": [], + "name": "cabbi-bio/BECT-ABM", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cabbi-bio/BECT-ABM", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cabbi-bio_ESM-R-script.json b/agency-indexes/DoE/cabbi-bio_ESM-R-script.json new file mode 100644 index 00000000..9f6e20c2 --- /dev/null +++ b/agency-indexes/DoE/cabbi-bio_ESM-R-script.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "This script is intended to provide a starting point for users to implement the equivalent soil mass (ESM) approach for calculating soil organic carbon (SOC) stocks and SOC mass percentages (commonly called \u201cSOC concentration\u201d). The user should read this readme file and understand how the script works before using it. The script contains some basic error checking algorithms, but it cannot catch all data entry mistakes. It is possible to misuse the script and produce invalid results. The script was designed to work on individual soil cores that have been divided into three or more contiguous segments, as the cubic spline function contains four coefficients. The script has not been tested on soil cores containing fewer than three contiguous segments. If only one segment is present, interpolation will necessarily be linear rather than cubic, which is expected to result in higher predictive error (Wendt & Hauser, 2013). Considering the wide range of potential applications, the script should not be expected to function correctly in all situations. The user is encouraged to modify or rewrite the script to meet their specific needs.", + "laborHours": 76.0, + "languages": [], + "name": "cabbi-bio/ESM-R-script", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/cabbi-bio/ESM-R-script/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cabbi-bio/ESM-R-script", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/calibers.json b/agency-indexes/DoE/calibers.json new file mode 100644 index 00000000..401efc2d --- /dev/null +++ b/agency-indexes/DoE/calibers.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "Exploring shaping traffic at the edge of the network.", + "laborHours": 1444.0, + "languages": [], + "name": "calibers", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/calibers", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/camoco.json b/agency-indexes/DoE/camoco.json new file mode 100644 index 00000000..98e1b8e0 --- /dev/null +++ b/agency-indexes/DoE/camoco.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "KBase module for coexpression analysis and GWAS overlap analysis.", + "laborHours": 790.4, + "languages": [], + "name": "camoco", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/KB-CAMOCO", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/camocokb.json b/agency-indexes/DoE/camocokb.json new file mode 100644 index 00000000..1e355947 --- /dev/null +++ b/agency-indexes/DoE/camocokb.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "KBase interface to Camoco coexpression database framework.", + "laborHours": 836.0, + "languages": [], + "name": "camocokb", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/camocokb", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/capistrano_nrel_ext_[no_known_SWR].json b/agency-indexes/DoE/capistrano_nrel_ext_[no_known_SWR].json new file mode 100644 index 00000000..65f03398 --- /dev/null +++ b/agency-indexes/DoE/capistrano_nrel_ext_[no_known_SWR].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2024-07-01" + }, + "description": "This is the repository for capistrano_nrel_ext developed at National Renewable Energy Laboratory.", + "laborHours": 1003.2, + "languages": [ + "Ruby" + ], + "name": "capistrano_nrel_ext [no known SWR]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/capistrano_nrel_ext", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/catgym.json b/agency-indexes/DoE/catgym.json new file mode 100644 index 00000000..7b1d4302 --- /dev/null +++ b/agency-indexes/DoE/catgym.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "zulissi@andrew.cmu.edu" + }, + "date": { + "created": "2022-11-18", + "metadataLastUpdated": "2022-11-18" + }, + "description": "CatGym is a deep reinforcement learning (DRL) environment for predicting the thermal surface reconstruction pathways and their associated kinetic barriers in crystalline solids under reaction conditions. The DRL agent iteratively changes the positions of atoms in the near-surface region to generate kinetic pathways to accessible local minima involving changes in the surface compositions.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "catgym", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ulissigroup/catgym", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ccp137_SUGAR.json b/agency-indexes/DoE/ccp137_SUGAR.json new file mode 100644 index 00000000..186af499 --- /dev/null +++ b/agency-indexes/DoE/ccp137_SUGAR.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "chaic@ornl.gov" + }, + "date": { + "created": "2022-01-06", + "metadataLastUpdated": "2022-01-06" + }, + "description": "This package (SUrface-wave Grader with ARtificial intelligence or SUGAR) automatically assigns a quality score to surface-wave seismograms (SAC format) using a trained artificial neural network model (included). Specifically, the python script 01_apply_ann.py calculates probability scores for a list of SAC files. You may consider seismograms with probability scores larger than 0.5 as acceptable data. Note no scores will be given to seismograms that do not pass an initial check (e.g., insufficient number of data points). 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", + "laborHours": 167.2, + "languages": [], + "name": "cdd_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/cdd_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cdf_normalize.json b/agency-indexes/DoE/cdf_normalize.json new file mode 100644 index 00000000..03825116 --- /dev/null +++ b/agency-indexes/DoE/cdf_normalize.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-09", + "metadataLastUpdated": "2021-12-09" + }, + "description": "The code performs image intensity normalization. A new intensity normalization method is presented, which works well with images whose pixel intensity distribution follow a Gamma Probability Distribution. Some examples are provided to show the normalization effect. This new intensity normalization method is also compared to some other well-established intensity normalization methods.", + "laborHours": 0.0, + "languages": [], + "name": "cdf_normalize", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xiaotingzhong/image_intensity_gamma_normalization", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cdtime.json b/agency-indexes/DoE/cdtime.json new file mode 100644 index 00000000..fd6dc621 --- /dev/null +++ b/agency-indexes/DoE/cdtime.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-28", + "metadataLastUpdated": "2020-05-28" + }, + "description": "Climate calendar manipulation tools.", + "laborHours": 942.4, + "languages": [], + "name": "cdtime", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/cdtime", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cdutil.json b/agency-indexes/DoE/cdutil.json new file mode 100644 index 00000000..d8e6edb8 --- /dev/null +++ b/agency-indexes/DoE/cdutil.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-28", + "metadataLastUpdated": "2020-05-28" + }, + "description": "Climate Utilities for 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+ "name": "celegans.aging", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://opensource.org/licenses/Artistic-2.0", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/celegans.aging", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/central_node_engine.json b/agency-indexes/DoE/central_node_engine.json new file mode 100644 index 00000000..69e842d8 --- /dev/null +++ b/agency-indexes/DoE/central_node_engine.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "LCLS-II MPS central node software.\n", + "laborHours": 629310.4, + "languages": [], + "name": 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"central_node_ioc", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/central_node_ioc/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/central_node_ioc", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/centroid_identification_from_cloud_photon-sparse_images.json b/agency-indexes/DoE/centroid_identification_from_cloud_photon-sparse_images.json new file mode 100644 index 00000000..28fa816a --- /dev/null +++ b/agency-indexes/DoE/centroid_identification_from_cloud_photon-sparse_images.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andreasv@uidaho.edu" + }, + "date": { + "created": "2022-12-21", + "metadataLastUpdated": "2023-02-02" + }, + "description": "A Matlab script that allows the computation of single-photon centroids from photon-sparse cloud images.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "centroid identification from cloud photon-sparse images", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/aevasdekis/photon-sparse", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ceph_initialize.json b/agency-indexes/DoE/ceph_initialize.json new file mode 100644 index 00000000..f8eb3d9e --- /dev/null +++ b/agency-indexes/DoE/ceph_initialize.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-10", + "metadataLastUpdated": "2020-08-10" + }, + "description": "Docker image that can be used to initialize a ceph cluster (until the ceph docker images catch up).", + "laborHours": 197.6, + "languages": [], + "name": "ceph_initialize", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/ceph_initialize", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/certified.json b/agency-indexes/DoE/certified.json new file mode 100644 index 00000000..6c1e7dc8 --- /dev/null +++ b/agency-indexes/DoE/certified.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2024-10-02", + "metadataLastUpdated": "2024-10-02" + }, + "description": "The missing certificate infrastructure for web APIs.", + "laborHours": 1383.2, + "languages": [ + "Python" + ], + "name": "certified", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/certified.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ch-placement.json b/agency-indexes/DoE/ch-placement.json new file mode 100644 index 00000000..04256a03 --- /dev/null +++ b/agency-indexes/DoE/ch-placement.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-28", + "metadataLastUpdated": "2022-01-28" + }, + "description": "libch-placement is a modular 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Users have the option of directly imbedding the ChIMES calculator within their codes, or evaluating interactions through the beginner-friendly serial interface, each of which have\nPython, C++, C, and Fortran API's.", + "laborHours": 0.0, + "languages": [], + "name": "chimes_calculator", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rk-lindsey/chimes_calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cinema_dora.json b/agency-indexes/DoE/cinema_dora.json new file mode 100644 index 00000000..35db6107 --- /dev/null +++ b/agency-indexes/DoE/cinema_dora.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": 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b/agency-indexes/DoE/cisagov_RedEye.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-10-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "RedEye is a visual analytic tool for supporting Red & Blue Team operations", + "laborHours": 0.0, + "languages": [], + "name": "cisagov/RedEye", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cisagov/redeye", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cisagov_STOAT.json b/agency-indexes/DoE/cisagov_STOAT.json new file mode 100644 index 00000000..090eb0b5 --- /dev/null +++ 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Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 22161.6, + "languages": [ + "python" + ], + "name": "clif", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/clif", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.2.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/climextremes_v0.2.1.json b/agency-indexes/DoE/climextremes_v0.2.1.json new file mode 100644 index 00000000..9f8d5aad --- /dev/null +++ b/agency-indexes/DoE/climextremes_v0.2.1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2019-10-29" + }, + "description": "Software package for R and Python for analysis of extremes in climate data. Functions for fitting GEV and POT (via point process fitting) models for extremes in climate data, providing return values, return probabilities, and return periods for stationary and nonstationary models. Also provides differences in return values and differences in log return probabilities for contrasts of covariate values. Functions for estimating risk ratios for event attribution analyses, including uncertainty. Under the hood, many of the functions use functions from 'extRemes', including for fitting the statistical models.", + "laborHours": 8679.2, + "languages": [], + "name": "climextremes v0.2.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/lbl-cascade/climextremes-dev", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/cloud_fs__Cloud_File_System_Utilities__10.6.2021_[SWR-21-83].json b/agency-indexes/DoE/cloud_fs__Cloud_File_System_Utilities__10.6.2021_[SWR-21-83].json new file mode 100644 index 00000000..57f4b7d1 --- /dev/null +++ b/agency-indexes/DoE/cloud_fs__Cloud_File_System_Utilities__10.6.2021_[SWR-21-83].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2024-07-01", + "metadataLastUpdated": "2024-07-01" + }, + "description": "cloud-fs (Cloud File System Utilities) is a generalized file-system handler that will dynamically determine if files are local or on the cloud (currently AWS) and perform basic file-system operations.", + "laborHours": 0.0, + "languages": [ + "Python", + "Shell" + ], + "name": "cloud_fs (Cloud File System Utilities) 10.6.2021 [SWR-21-83]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/cloud_fs", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.0.8" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cloud_fs__Cloud_File_System_Utilities__[SWR-21-83].json b/agency-indexes/DoE/cloud_fs__Cloud_File_System_Utilities__[SWR-21-83].json new file mode 100644 index 00000000..107afde0 --- /dev/null +++ b/agency-indexes/DoE/cloud_fs__Cloud_File_System_Utilities__[SWR-21-83].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-06-24", + "metadataLastUpdated": "2024-07-01" + }, + "description": "cloud-fs (Cloud File System Utilities) is a generalized file-system handler that will dynamically determine if files are local or on the cloud (currently AWS) and perform basic file-system operations.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "cloud_fs (Cloud File System Utilities) [SWR-21-83]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/cloud_fs", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cluster_trials_v._1.0.json b/agency-indexes/DoE/cluster_trials_v._1.0.json new file mode 100644 index 00000000..27d4724c --- /dev/null +++ b/agency-indexes/DoE/cluster_trials_v._1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This software contains a set of python modules \u2013 input, search, cluster, analysis; these modules read input files containing spatial coordinates and associated attributes which can be used to perform nearest neighbor search (spatial indexing via kdtree), cluster analysis/identification, and calculation of spatial statistics for analysis.", + "homepageURL": "http://spparks.sandia.gov", + "laborHours": 0.0, + "name": "cluster trials v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://spparks.sandia.gov", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/clustra.json b/agency-indexes/DoE/clustra.json new file mode 100644 index 00000000..cccfa99f --- /dev/null +++ b/agency-indexes/DoE/clustra.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "ostrouchovg@ornl.gov" + }, + "date": { + "created": "2021-11-20", + "metadataLastUpdated": "2021-11-23" + }, + "description": "Clusters medical trajectories (unequally spaced and unequal length time series) aligned by an intervention time. Performs k-means clustering, where each mean is a thin plate spline fit to all points in a cluster. Distance is MSE across trajectory points to cluster spline. Provides silhouette plots and Adjusted Rand Index evaluations of the number of clusters. Scales well to large data with multicore parallelism available to speed computation.", + "homepageURL": "https://cran.r-project.org/package=clustra", + "laborHours": 0.0, + "languages": [ + "R" + ], + "name": "clustra", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cran.r-project.org/package=clustra", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0.1.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cms-geovar.json b/agency-indexes/DoE/cms-geovar.json new file mode 100644 index 00000000..88391e15 --- /dev/null +++ b/agency-indexes/DoE/cms-geovar.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "CMS geographic variation map visualization\u00a0http://ornl-sava.github.io/cms-geovar/\n", + "laborHours": 632213.6, + "name": "cms-geovar", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/cms-geovar", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cmu-sei_gbtl.json b/agency-indexes/DoE/cmu-sei_gbtl.json new file mode 100644 index 00000000..c49f81ac --- /dev/null +++ b/agency-indexes/DoE/cmu-sei_gbtl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-07-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "GraphBLAS Template Library (GBTL): graph algorithms and primitives using semiring algebra as defined at graphblas.org", + "laborHours": 54856.8, + "languages": [], + "name": "cmu-sei/gbtl", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmu-sei/gbtl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/coh3.json b/agency-indexes/DoE/coh3.json new file mode 100644 index 00000000..526d5d9c --- /dev/null +++ b/agency-indexes/DoE/coh3.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "CoH3 (CoH ver.3) is an optical model, exciton pre-equilibrium, and Hauser-Feshbach statistical model code, which calculates nuclear reaction cross sections for medium to heavy targets in the keV to MeV energy region. This program is written in standard C++, divided into approximately 200 source and header files. CoH solves the Schroedinger equation for optical potentials defined in the code, and calculates differential elastic scattering, reaction, and total cross sections, for neutron, proton, deuteron, triton, 3He, and alpha-particle. Deformed optical potentials are solved with the coupled-channels method, in which the ground state rotational band members, or vibrational phonon states are coupled. The optical model gives particle transmission coefficients that are fed into the statistical model calculations. CoH includes the pre-equilibrium model (exciton model), the direct/semidirect capture model, and the multi-stage Hauser-Feshbach statistical decay with width fluctuation correction based on the Gaussian orthogonal ensemble. For weakly coupled levels, the DWBA (distorted wave Born approximation) method is used to calculate the direct inelastic scattering process to the excited states.", + "laborHours": 31251.2, + "languages": [], + "name": "coh3", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/toshihikokawano/coh3", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/coloring_v.1.0.json b/agency-indexes/DoE/coloring_v.1.0.json new file mode 100644 index 00000000..4e369bc5 --- /dev/null +++ b/agency-indexes/DoE/coloring_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-03-19", + "metadataLastUpdated": "2024-03-19" + }, + "description": "SAND2024-02435O\nThe software coloring allows applications written in the C++ language to generate publication-quality 2D plots. Its functionality is similar to Microsoft Excel's chart functionality or the Python language's matplotlib package. The value of coloring is that it is written purely in C++ and thus can be compiled on systems where Python is not available and linked into high performance computing software. \n\nFor drawing shapes onto an image, coloring uses the mathematical definition of quadratic Bezier splines and uses Newton's method to search for the closest point on a spline to a given query point. This is then used to do accurate sub-pixel sampling to get clean, non-pixelated images. For working with the actual plot data, coloring has basic statistical methods such as finding maxima and minima as well as axis scaling such as logarithms. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++17 version" + ], + "name": "coloring v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/coloring", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/colormap_util.json b/agency-indexes/DoE/colormap_util.json new file mode 100644 index 00000000..786ff4e1 --- /dev/null +++ b/agency-indexes/DoE/colormap_util.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Our Python module, colormap_module, presented here can be used to analyze and manipulate colormaps and has two main aims: (i) compare existing and new custom colormaps quantitatively by comparing their values in a color space, called CAM02-UCS, that directly shows how a human perceives their hue, saturation, and lightness values and (ii) create isoluminant colormaps from existing or custom colormaps and (iii) mix isoluminant colormap data with a 4th dimension of data by manipulating lightness values across the image and present the new image. Our module was designed to be a tool for the community to use as a whole, allowing scientists to present, analyze, and manipulate colormaps they have created and/or decided to use for a particular type of data. By being able to do this, the scientific community as a whole will think more about the colormaps they choose, see why particular colormaps are bad to use for certain types of data, and move toward using colormaps our eyes can interpret much more efficiently.", + "laborHours": 304.0, + "name": "colormap_util", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/jamienunez/cmaputil/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jamienunez/cmaputil", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/communities_api.json b/agency-indexes/DoE/communities_api.json new file mode 100644 index 00000000..b8d47cfa --- /dev/null +++ b/agency-indexes/DoE/communities_api.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "This repository was created for the purpose of bundling the communities API code. ", + "laborHours": 3480.8, + "languages": [], + "name": "communities_api", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/communities_api", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/communities_qc.json b/agency-indexes/DoE/communities_qc.json new file mode 100644 index 00000000..dca53325 --- /dev/null +++ b/agency-indexes/DoE/communities_qc.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "This is the repository for \"communities_qc\" developed by KBase.", + "laborHours": 3024.8, + "languages": [], + "name": "communities_qc", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/communities_qc", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/components_for_the_MuMMI_software_release.json b/agency-indexes/DoE/components_for_the_MuMMI_software_release.json new file mode 100644 index 00000000..10c5dc4b --- /dev/null +++ b/agency-indexes/DoE/components_for_the_MuMMI_software_release.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "The Department of Energy and the National Cancer Institute have developed new software for conducting multi-scale simulations of complex systems. This software, called the Multiscale Machine-Learned Modeling Infrastructure (MuMMI), couples simulations on three spatial scales to study slow, large-scale reorganizations of biomolecular systems with the speed of continuum and coarse-grained models while revealing selected interactions at full atomic precision. In these simulations, coarse-to-fine model conversions are used to spawn relevant fine-scale simulations along chosen order parameters, and fine-to-coarse feedback is used to iteratively improve the accuracy and multi-scale consistency of coarse-scale and continuum simulations. The complete MuMMI framework will be reviewed and released as open-source software by Lawrence Livermore National Laboratory. This review covers a subset of the MuMMI components that were developed exclusively at the Los Alamos National Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "components for the MuMMI software release", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cneale-LANL/MuMMI-C21095", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/compute_graph.json b/agency-indexes/DoE/compute_graph.json new file mode 100644 index 00000000..a7d11c28 --- /dev/null +++ b/agency-indexes/DoE/compute_graph.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "A library for tracking, serializing, and deriving values from a graph of operations.", + "laborHours": 228.0, + "languages": [], + "name": "compute_graph", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/compute_graph", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/concierge.json b/agency-indexes/DoE/concierge.json new file mode 100644 index 00000000..d5f98cfa --- /dev/null +++ b/agency-indexes/DoE/concierge.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "This is the repository for \"concierge\" developed by KBase.\n", + "laborHours": 562.4, + "languages": [], + "name": "concierge", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/concierge", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/conda-recipes.json b/agency-indexes/DoE/conda-recipes.json new file mode 100644 index 00000000..149d12a1 --- /dev/null +++ b/agency-indexes/DoE/conda-recipes.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-28", + "metadataLastUpdated": "2020-05-28" + }, + "description": "This is the repository for conda-recipes, developed at Lawrence Livermore National Laboratory (LLNL). ", + "laborHours": 1018.4, + "languages": [], + "name": "conda-recipes", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/conda-recipes", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/condor-worker_requirements.json b/agency-indexes/DoE/condor-worker_requirements.json new file mode 100644 index 00000000..c9a72818 --- /dev/null +++ b/agency-indexes/DoE/condor-worker_requirements.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "This is the repository for \"condor-worker requirements\" developed by KBase.", + "laborHours": 592.8, + "languages": [], + "name": "condor-worker requirements", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/condor-worker", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/condor.json b/agency-indexes/DoE/condor.json new file mode 100644 index 00000000..650e03db --- /dev/null +++ b/agency-indexes/DoE/condor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "KBase specific Condor scheduler image. Based on the andypohl/htcondor image.", + "laborHours": 45.6, + "languages": [], + "name": "condor", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/condor", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/condor_restd.json b/agency-indexes/DoE/condor_restd.json new file mode 100644 index 00000000..6f539baa --- /dev/null +++ b/agency-indexes/DoE/condor_restd.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-10", + "metadataLastUpdated": "2020-08-10" + }, + "description": "htcondor-restd fork with auth and dockerfile. REST-based API for HTCondor, using the Python bindings. 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"description": "coreFPU is a simple test code designed to detect bac CPU's.", + "laborHours": 0.0, + "languages": [], + "name": "coreFPUtest Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/coreFPUtest/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/coreFPUtest", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/core_stack_merge.json b/agency-indexes/DoE/core_stack_merge.json new file mode 100644 index 00000000..06f54325 --- /dev/null +++ b/agency-indexes/DoE/core_stack_merge.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "This is a script to merge IBM BlueGene lightweight core files into STAT prefix trees.\n", + "laborHours": 3997.6, + "languages": [], + "name": "core_stack_merge", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/core_stack_merge", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cowc.json b/agency-indexes/DoE/cowc.json new file mode 100644 index 00000000..a5243ab7 --- /dev/null +++ b/agency-indexes/DoE/cowc.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2020-10-29" + }, + "description": "Cars Overhead With Context related scripts described in Mundhenk et al. 2016 ECCV.\u00a0http://gdo152.ucllnl.org/cowc/\n", + "laborHours": 380.0, + "languages": [ + "Python" + ], + "name": "cowc", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/cowc", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cppyy.json b/agency-indexes/DoE/cppyy.json new file mode 100644 index 00000000..1c05185c --- /dev/null +++ b/agency-indexes/DoE/cppyy.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "wlavrijsen@lbl.gov" + }, + "date": { + "created": "2024-12-19", + "metadataLastUpdated": "2024-12-19" + }, + "description": "cppyy provides 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This F90 version uses derived types, modules, fixes several bugs, is distributed with a Centos7 (Docker) container, and includes automated CI tests.", + "homepageURL": "https://princetonuniversity.github.io/cql3d_f90", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "cql3d_f90", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://princetonuniversity.github.io/cql3d_f90", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/cryoem-airflow.json b/agency-indexes/DoE/cryoem-airflow.json new file mode 100644 index 00000000..6a75e7e6 --- /dev/null +++ b/agency-indexes/DoE/cryoem-airflow.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-07", + "metadataLastUpdated": "2022-07-07" + }, + "description": "This repo contains airflow based workflows for cryoem data collection and analysis at the SLAC National Accelerator Center.", + "laborHours": 0.0, + "languages": [], + "name": "cryoem-airflow", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/cryoem-airflow", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cs_uploader.json b/agency-indexes/DoE/cs_uploader.json new file mode 100644 index 00000000..81035166 --- /dev/null +++ b/agency-indexes/DoE/cs_uploader.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "Enables object relational mapping for CS schema. 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The software allows selecting, configuring and editing the control sequences. It also allows exporting the sequence for use in building project design documents in Modelica-based simulations. The export will be in a json intermediate format, in the Modelica Language, in the Control Description Language and in English language format, such as in a Word document. The software functions as a web based application that includes a graphical user interface.", + "laborHours": 0.0, + "languages": [], + "name": "ctrl-flow v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-srg/ctrl-flow-dev.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cuOrbit.json b/agency-indexes/DoE/cuOrbit.json new file mode 100644 index 00000000..ba7afe34 --- /dev/null +++ b/agency-indexes/DoE/cuOrbit.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "gwright@pppl.gov" + }, + "date": { + "created": "2020-01-16", + "metadataLastUpdated": "2020-02-25" + }, + "description": "CUDA C Orbit Model\n\nNumerical guiding center code for toroidally confined plasma.", + "laborHours": 2812.0, + "languages": [ + "C", + "C", + "CUDA" + ], + "name": "cuOrbit", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PrincetonUniversity/cuOrbit", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "vcs": "git", + "version": "validation-alpha-rc1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cuRAND_back-end_v0.1.0.json b/agency-indexes/DoE/cuRAND_back-end_v0.1.0.json new file mode 100644 index 00000000..fb0e81a7 --- /dev/null +++ b/agency-indexes/DoE/cuRAND_back-end_v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-13", + "metadataLastUpdated": "2021-04-13" + }, + "description": "This contribution to Intel oneMKL adds functionality to generate pseudorandom numbers within SYCL on NVIDIA devices.", + "laborHours": 0.0, + "languages": [], + "name": "cuRAND back-end v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/oneapi-src/oneMKL", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cuSZ:CUDA-based_Error-Bounded_Lossy_Compressor_for_Scientific_Data_Scientific_Data.json b/agency-indexes/DoE/cuSZ:CUDA-based_Error-Bounded_Lossy_Compressor_for_Scientific_Data_Scientific_Data.json new file mode 100644 index 00000000..d160f5a6 --- /dev/null +++ b/agency-indexes/DoE/cuSZ:CUDA-based_Error-Bounded_Lossy_Compressor_for_Scientific_Data_Scientific_Data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2021-08-24", + "metadataLastUpdated": "2021-08-24" + }, + "description": "cuSZ is a CUDA implementation of the world-widely used SZ lossy compressor. It is the first error-bounded lossy compressor on GPUs for scientific data, which significantly improves SZ's throughput in GPU-based heterogeneous HPC systems.", + "laborHours": 0.0, + "languages": [], + "name": "cuSZ:CUDA-based Error-Bounded Lossy Compressor for Scientific Data Scientific Data", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/szcompressor/cuSZ", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cubacpp.json b/agency-indexes/DoE/cubacpp.json new file mode 100644 index 00000000..33dfbc32 --- /dev/null +++ b/agency-indexes/DoE/cubacpp.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2020-01-16", + "metadataLastUpdated": "2020-01-16" + }, + "description": "cubacpp provides a C++ binding for the excellent CUBA library, and to a lesser extent, to the GSL integration library GSL. cubacpp provides no new integration facilities. It merely provides a more convenient syntax for use of the CUBA (and GSL) integration routines, made possible by the features of the C++ programming language.", + "laborHours": 7995.2, + "languages": [], + "name": "cubacpp", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/mpaterno/cubacpp", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/cvmfs-contrib_cvmfs-user-pub.json b/agency-indexes/DoE/cvmfs-contrib_cvmfs-user-pub.json new file mode 100644 index 00000000..5560e720 --- /dev/null +++ b/agency-indexes/DoE/cvmfs-contrib_cvmfs-user-pub.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-07-08", + "metadataLastUpdated": "2019-07-09" + }, + "description": "Service for publishing user code tarballs in cvmfs repositories", + "laborHours": 288.8, + "languages": [ + "Python" + ], + "name": "cvmfs-contrib/cvmfs-user-pub", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cvmfs-contrib/cvmfs-user-pub", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cyme-launcher.json b/agency-indexes/DoE/cyme-launcher.json new file mode 100644 index 00000000..ad53882b --- /dev/null +++ b/agency-indexes/DoE/cyme-launcher.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-10-25", + "metadataLastUpdated": "2022-08-22" + }, + "description": "cyme-launcher is a script for helping launch CYME on HPC clusters. It ensures that a license manager is running on a node, that sufficient licenses for the software are available to run, and running CYME using WINE on Linux.", + "laborHours": 0.0, + "languages": [], + "name": "cyme-launcher", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/cyme-launcher", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/cyqc.json b/agency-indexes/DoE/cyqc.json new file mode 100644 index 00000000..a88a07f4 --- /dev/null +++ b/agency-indexes/DoE/cyqc.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2022-05-19", + "metadataLastUpdated": "2022-05-19" + }, + "description": "A collection of codes which implement quantum algorithms for correlated materials simulations.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "cyqc", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/gqce/cyqc", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/cyquandyn.json b/agency-indexes/DoE/cyquandyn.json new file mode 100644 index 00000000..8dc33733 --- /dev/null +++ b/agency-indexes/DoE/cyquandyn.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2023-08-15" + }, + "description": "CyQuanDyn is a collection of codes developed for modelling the phonon-induced carrier pumping in ZrTe5 system. Codes in the collection include 1) TLS: time-dependent two-orbital spinless fermion Bogoliubov-de Gennes Hamiltonian simulation, 2) TDSE: ab initio time-dependent Schr\u00f6dinger equation simulation of the ZrTe5 system under the periodic modulation of A1g Raman mode. Associated publication is T. Jiang, P. P. Orth, L. Luo, L.-L. Wang, F. Zhang, C.-Z. Wang, J. Zhao, K.-M. Ho, J. Wang, and Y.-X. Yao, Ab-Initio Simulations of Coherent Phonon-Induced Pumping of Carriers in ZrTe5. [arXiv:2304.08449 (2023).](https://arxiv.org/abs/2304.08449)", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "cyquandyn", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/lmqc/cyquandyn", + "status": "Production", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "version": "3.8" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/dGen\342\204\242__Distributed_Generation_Market_Demand_Model__[SWR-17-09].json" "b/agency-indexes/DoE/dGen\342\204\242__Distributed_Generation_Market_Demand_Model__[SWR-17-09].json" new file mode 100644 index 00000000..60366fe0 --- /dev/null +++ "b/agency-indexes/DoE/dGen\342\204\242__Distributed_Generation_Market_Demand_Model__[SWR-17-09].json" @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-12-11", + "metadataLastUpdated": "2024-01-04" + }, + "description": "The Distributed Generation Market Demand (dGen\u2122) model is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The National Renewable Energy Laboratory (NREL) developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States within a single modeling platform. The dGen model builds on, extends, and provides significant advances over NREL\u2019s SolarDS model (Denholm et al. 2009), which is now deprecated.", + "laborHours": 17540.8, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "dGen\u2122 (Distributed Generation Market Demand Model) [SWR-17-09]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dgen", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/daft_[SWR-17-53].json b/agency-indexes/DoE/daft_[SWR-17-53].json new file mode 100644 index 00000000..1a3d9ed9 --- /dev/null +++ b/agency-indexes/DoE/daft_[SWR-17-53].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-16", + "metadataLastUpdated": "2024-07-01" + }, + "description": "Daft is a Haskell library that implements the key constructs of relational algebra via static structural typing. Its DataCube typeclass supports selection, projection, aggregation, disaggregation, natural joins, semijoins, and antijoins. Instances of DataCube include both map- and function-based representations. An additional abstract data type provides Vinyl-style, keyed relational tables for which an embedded domain-specific language compactly represents relational operations. Utility types and functions support serialization to tab-separated-value data files, JSON arrays, MongoDB documents, and PostgreSQL tables, including automatic detection and verification of the schema for the input data.", + "laborHours": 1094.4, + "languages": [ + "Haskell" + ], + "name": "daft [SWR-17-53]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/daft", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/danish.json b/agency-indexes/DoE/danish.json new file mode 100644 index 00000000..004eb785 --- /dev/null +++ b/agency-indexes/DoE/danish.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-12-22", + "metadataLastUpdated": "2021-12-22" + }, + "description": "Danish is a forward modeling package for curvature wavefront sensing in the geometric limit.", + "laborHours": 0.0, + "languages": [], + "name": "danish", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jmeyers314/danish", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/data_api_js_clients.json b/agency-indexes/DoE/data_api_js_clients.json new file mode 100644 index 00000000..91231036 --- /dev/null +++ b/agency-indexes/DoE/data_api_js_clients.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "Javascript clients for the KBase Data API services.", + "laborHours": 836.0, + "languages": [], + "name": "data_api_js_clients", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/data_api_js_clients", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/data_api_perl_clients.json b/agency-indexes/DoE/data_api_perl_clients.json new file mode 100644 index 00000000..0a821ddf --- /dev/null +++ b/agency-indexes/DoE/data_api_perl_clients.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "Perl clients for the KBase Data API services.", + "laborHours": 2629.6, + "languages": [], + "name": "data_api_perl_clients", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/data_api_perl_clients", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/databroker-elasticsearch.json b/agency-indexes/DoE/databroker-elasticsearch.json new file mode 100644 index 00000000..8fc43286 --- /dev/null +++ b/agency-indexes/DoE/databroker-elasticsearch.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "Integration of elasticsearch with databroker - databroker-elasticsearch provides export bridge of databroker records to Elasticsearch (ES). The package provides configurable mapping of databroker documents to ES records, filtering of permitted entries, facility to export all prior databroker records and a bluesky callback mechanism to export new measurements in real time.", + "laborHours": 957.6, + "languages": [], + "name": "databroker-elasticsearch", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/databroker-elasticsearch/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/databroker-elasticsearch", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/datacenterCoolingModel.json b/agency-indexes/DoE/datacenterCoolingModel.json new file mode 100644 index 00000000..92678f81 --- /dev/null +++ b/agency-indexes/DoE/datacenterCoolingModel.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "kumarv@ornl.gov" + }, + "date": { + "created": "2024-06-28", + "metadataLastUpdated": "2025-03-31" + }, + "description": "ExaDigiT is a framework for developing comprehensive digital twins of liquid-cooled supercomputers, which has three main modules: (1) a python-based Resource Allocator and Power Simulator (RAPS), (2) a Modelica-based Thermo-Fluidic cooling model, and (3) a C++-based augmented reality model built on Unreal Engine 5. The Modelica-based cooling model is primarily built-on the open-source Transient Simulation Framework\nof Reconfigurable Models (TRANSFORM) library and the open-source autocsm library.\nThe library follows the templating architecture developed in the TRANSFORM and the autocsm libraries. This tool can be easily extended to model other Frontier-like liquid cooled supercomputers.", + "laborHours": 395.2, + "languages": [], + "name": "datacenterCoolingModel", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/exadigit/datacenterCoolingModel", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/db,_Version_0.x.json b/agency-indexes/DoE/db,_Version_0.x.json new file mode 100644 index 00000000..95dc928d --- /dev/null +++ b/agency-indexes/DoE/db,_Version_0.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "A set of programs and utilities for generating and manipulating data files in TSV (tab-separated value) or JSON format.", + "laborHours": 8755.2, + "name": "db, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/lanl-chash/db/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-chash/db", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/db_initialize.json b/agency-indexes/DoE/db_initialize.json new file mode 100644 index 00000000..215b1eb8 --- /dev/null +++ b/agency-indexes/DoE/db_initialize.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "Small docker image for initializing databases (mongo and mysql).", + "laborHours": 30.4, + "languages": [], + "name": "db_initialize", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/db_initialize", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dbglog.json b/agency-indexes/DoE/dbglog.json new file mode 100644 index 00000000..dfeda5d2 --- /dev/null +++ b/agency-indexes/DoE/dbglog.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Enables applications to emit debug log information into an output file and provides developers with a way to visually structure the output to make it easier for them to navigate it to understand the sources of application errors.", + "laborHours": 192477.6, + "name": "dbglog", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/bronevet/dbglog", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dbprocessing.json b/agency-indexes/DoE/dbprocessing.json new file mode 100644 index 00000000..bfb60a0d --- /dev/null +++ b/agency-indexes/DoE/dbprocessing.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2021-09-24" + }, + "description": "dbprocessing is a python framework for automating data processing pipelines. The dbprocessing package uses a configuration file to define the input, intermediate, and output data products for a particular data type as well as the processes that connect those data products. In addition, dbprocessing uses python scripts called inspectors to determine if a particular file matches a configured data product. If a particular data product is found, it is ingested into the dbprocessing database (sqlite3 or postgres) which then triggers all of the chained processes to the final data product. While the framework is written in python, it can run software in any language but may require a \u201cwrapper\u201d to translate the dbprocessing command line arguments to the form expected by the software.", + "laborHours": 0.0, + "languages": [], + "name": "dbprocessing", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/dbprocessing", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dcTrackClient_v0.0.24.json b/agency-indexes/DoE/dcTrackClient_v0.0.24.json new file mode 100644 index 00000000..b7cbfc26 --- /dev/null +++ b/agency-indexes/DoE/dcTrackClient_v0.0.24.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-05-17", + "metadataLastUpdated": "2023-05-17" + }, + "description": "This is an API client for dcTrack - a data center infrastructure management tool created by Sunbird.", + "laborHours": 0.0, + "languages": [], + "name": "dcTrackClient v0.0.24", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/nicfv/dcTrackClient", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ddcMD.os.json b/agency-indexes/DoE/ddcMD.os.json new file mode 100644 index 00000000..287c92ed --- /dev/null +++ b/agency-indexes/DoE/ddcMD.os.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-27" + }, + "description": "ddcMD is a general purpose molecular dynamics (MD) code that supports MPI parallelism. MD codes are\nused for simulation of particles systems and capture all the many-body effects of the underlying particle\npotential that defines the physical system. Though MD can be used to model systems from the\nsubatomic to astrological length scales ddcMD is mainly focused on the atomic scale length scale, In\nthis release of ddcMD the support will be mainly for systems using the coarse-grain Martini potential, a\nparticle potential for biological systems.", + "laborHours": 38197.6, + "languages": [], + "name": "ddcMD.os", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ddcMD", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ddcMD_converter.json b/agency-indexes/DoE/ddcMD_converter.json new file mode 100644 index 00000000..c80afc08 --- /dev/null +++ b/agency-indexes/DoE/ddcMD_converter.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-30" + }, + "description": "This Python package is developed for converting GROMACS files to ddcMD inputs. The code makes it\neasier for ddcMD users to convert GROMACS MD simulations into ddcMD. It is used in the MuMMI\nframework for multiscale MD simulations.", + "laborHours": 7812.8, + "languages": [], + "name": "ddcMD converter", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ddcMDconverter", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.3" +} \ No newline at end of file diff --git a/agency-indexes/DoE/debian-with-miniconda.json b/agency-indexes/DoE/debian-with-miniconda.json new file mode 100644 index 00000000..911beb98 --- /dev/null +++ b/agency-indexes/DoE/debian-with-miniconda.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "A docker for auto-building conda packages.", + "laborHours": 45.6, + "languages": [], + "name": "debian-with-miniconda", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/debian-with-miniconda", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/deep-taxon_v0.1.json b/agency-indexes/DoE/deep-taxon_v0.1.json new file mode 100644 index 00000000..07b362bd --- /dev/null +++ b/agency-indexes/DoE/deep-taxon_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-08-02", + "metadataLastUpdated": "2023-08-02" + }, + "description": "deep-taxon is a package for training neural networks for classifying genomic sequence data. deep-taxon provides tools for converting genomic sequence data into high performance computing file formats capable of training neural networks at scale.", + "laborHours": 0.0, + "languages": [], + "name": "deep-taxon v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exabiome/deep-taxon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dencity-scripts.json b/agency-indexes/DoE/dencity-scripts.json new file mode 100644 index 00000000..30fbcc9b --- /dev/null +++ b/agency-indexes/DoE/dencity-scripts.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "This is the repository for dencity-scripts developed at National Renewable Energy Laboratory. ", + "laborHours": 273.6, + "languages": [], + "name": "dencity-scripts", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dencity-scripts", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dencity-web.json b/agency-indexes/DoE/dencity-web.json new file mode 100644 index 00000000..c7395414 --- /dev/null +++ b/agency-indexes/DoE/dencity-web.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "This is the repository for dencity-web developed at National Renewable Energy Laboratory.\n", + "laborHours": 17206.4, + "languages": [], + "name": "dencity-web", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dencity-web", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/densegranFoam.json b/agency-indexes/DoE/densegranFoam.json new file mode 100644 index 00000000..7e1724b7 --- /dev/null +++ b/agency-indexes/DoE/densegranFoam.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2022-03-31", + "metadataLastUpdated": "2022-03-31" + }, + "description": "densegranFoam is a dense granular material flow solver developed using the OpenFoam Computational Fluid Dynamics (CFD) tool. It is developed using Euler-Euler framework. The transport model is implemented using the shear rate dependant constitutive model. The primary focus of the solver is to simulate shear rate dependency on the dense granular flow bulk behavior.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "Python" + ], + "name": "densegranFoam", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/densegranFoam", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/depfinder.json b/agency-indexes/DoE/depfinder.json new file mode 100644 index 00000000..73c52c8b --- /dev/null +++ b/agency-indexes/DoE/depfinder.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "Find all the unique imports in your library.", + "laborHours": 349.6, + "languages": [], + "name": "depfinder", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/depfinder", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/detrot.json b/agency-indexes/DoE/detrot.json new file mode 100644 index 00000000..0c3de0a5 --- /dev/null +++ b/agency-indexes/DoE/detrot.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-06-05", + "metadataLastUpdated": "2018-06-05" + }, + "description": "This module performs abstractions for the CXI detector stands in order to manipulate them as rigid bodies. By first manipulating pairs of motors as joints, and then the stand as a collection of three unieque joints, higher level functions such as translate and rotate are created to help the operator quickly adjust the stand.\n", + "laborHours": 820.8, + "languages": [], + "name": "detrot", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/detrot/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/detrot", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dev-board-examples.json b/agency-indexes/DoE/dev-board-examples.json new file mode 100644 index 00000000..e3312b08 --- /dev/null +++ b/agency-indexes/DoE/dev-board-examples.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2022-07-28" + }, + "description": "Development Board Firmware/Software Examples", + "laborHours": 0.0, + "languages": [], + "name": "dev-board-examples", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.osti.gov/osti-public/dev-board-examples/-/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/dev-board-examples", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/devenv.json b/agency-indexes/DoE/devenv.json new file mode 100644 index 00000000..30114d37 --- /dev/null +++ b/agency-indexes/DoE/devenv.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "lyon@fnal.gov" + }, + "date": { + "created": "2019-12-13", + "metadataLastUpdated": "2019-12-13" + }, + "description": "Linux style development, like what we do for particle physics experiments at Fermilab, is becoming more difficult on the Mac. Apple is moving to its own style of development that is often incompatible. For example,\n\n* System Integrity Protection (SIP) prevents using DYLD_LIBRARY_PATH, breaking the mechanism used by our development environment system, ups.\n\n* Mac headers and system libraries are not always compatible with those on Linux, necessitating platform dependent code.\n\n* XCode is more focused on Swift, Objective-C, and Mac or iOS-style development. XCode does not understand CMake builds natively.\n\nThe differences that Mac and XCode introduce are difficult to manage and many experiments have stopped making Mac builds. Despite these problems, Mac laptops remain powerful machines and the MacOS environment is advantageous in many other areas. Therefore, mitigating the problems with Linux style development is motivated.\n\nThis package contains a configuration for docker containers along with instructions for integrating with the Mac that make for an effective and efficient development platform for Linux style development of physics code. Instructions for using CLion for C++ development in this environment are given in the documentation for running CLion within the linux container or from the Mac host.\n\nNote that the containers and techniques here may also work on Windows. You will have to adapt the instructions for that platform.", + "laborHours": 410.4, + "languages": [ + "Bash", + "docker" + ], + "name": "devenv", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lyon-fnal/devenv", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dfdjaxGP.json b/agency-indexes/DoE/dfdjaxGP.json new file mode 100644 index 00000000..cb8ce7f0 --- /dev/null +++ b/agency-indexes/DoE/dfdjaxGP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2022-07-15" + }, + "description": "A small python package to fit Gaussian processes using Jax and leveraging the automatic differentiation in Jax to predict arbitrary derivatives from the GP. This package is meant to supplement the scientific community use of Gaussian process prediction with derivatives. The package is designed to smoothly work standalone or be used with the numpyro probabilistic programming language.", + "laborHours": 0.0, + "languages": [], + "name": "dfdjaxGP", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/dfdjaxGP", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dfnWorks,_Version_1.0.json b/agency-indexes/DoE/dfnWorks,_Version_1.0.json new file mode 100644 index 00000000..e4e883ca --- /dev/null +++ b/agency-indexes/DoE/dfnWorks,_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DFNWorks is a suite of software for generating and solving flow and transport physics on a Discrete Fracture Network (DFN). The suite is composed of three components: DFNGen: Stochastic fracture generation, mesh generation, model setup; DFNFlow: Flow solution using PFLOTRAN or FEHM control volume formulation solver; DFNTrans: Particle tracking transport; DFNGen Algorithm Description: This is a workflow that uses Mathematica software, Python scripts written by the authors and the LaGriT software to generate; DFNFlow; The solution of flow in porous media is accomplished by coupling DFNGen output with the existing software packages FEHM and PFLOTRAN. The DFNWorks workflow involves modules and scripts that translate DFNGen output to formats compatible with FEHM and PFLOTRAN input. FEHM LA-CC-2012-083 PFLOTRAN LA-CC-09-047 LaGriT LA-CC-07-38 DFNTrans Stand alone particle tracking algorithm that takes FEHM/PFLOTRAN flow solution as output and computes velocity field and advects particles.", + "laborHours": 10700.8, + "name": "dfnWorks, Version 1.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/dfnWorks/dfnWorks-Version1.0/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dfnWorks/dfnWorks-Version1.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dfnWorks,_Version_2.0.json b/agency-indexes/DoE/dfnWorks,_Version_2.0.json new file mode 100644 index 00000000..a4065d44 --- /dev/null +++ b/agency-indexes/DoE/dfnWorks,_Version_2.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "DFNWorks is a suite of software for generating and solving flow and transport physics on a Discrete Fracture Network (DFN). The suite is composed of three components: DFNGen: Stochastic fracture generation, mesh generation, model setup; DFNFlow: Flow solution using PFLOTRAN or FEHM control volume formulation solver; DFNTrans: Particle tracking transport; DFNGen Algorithm Description: This is a workflow that uses C++ software version for fracture generation, Python scripts written by the authors and the LaGriT software to generate computational mesh. DFNFlow The solution of flow in porous media is accomplished by coupling DFNGen output with the existing software packages FEHM and PFLOTRAN. The DFNWorks workflow involves modules and scripts that translate DFNGen output to formats compatible with FEHM and PFLOTRAN input. FEHM LA-CC-2012-083 PFLOTRAN LA-CC-09-047 LaGriT LA-CC-07-38 DFNTrans Stand-alone particle tracking algorithm that takes FEHM/PFLOTRAN flow solution as output and computes velocity field and advects particles.", + "laborHours": 0.0, + "name": "dfnWorks, Version 2.0", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dfnWorks/dfnWorks-Version2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/diamond-sampling.json b/agency-indexes/DoE/diamond-sampling.json new file mode 100644 index 00000000..c428d2a7 --- /dev/null +++ b/agency-indexes/DoE/diamond-sampling.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This software provides a means for computing only the largest few entries of the product of two matrices, both exactly and approximately (using randomized sampling techniques). The purpose of the code is to demonstrate both the time it takes to solve the problem as well as the accuracy of the approximate approach. It is also meant to serve as a foundation to test the applicability of the sampling technique to related problems in data mining, including maximum inner product search, nearest neighbor search, and maximum cosine similarity.", + "laborHours": 6794.4, + "languages": [ + "Matlab, C, C++", + "Java", + "Makefile", + "HTML" + ], + "name": "diamond-sampling", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/DiamondSampling", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/diod_-_distributed_I_O_daemon.json b/agency-indexes/DoE/diod_-_distributed_I_O_daemon.json new file mode 100644 index 00000000..cde1e723 --- /dev/null +++ b/agency-indexes/DoE/diod_-_distributed_I_O_daemon.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "diod is an I/O forwarding daemon used to improve scalability of file systems on large Linux clusters.", + "laborHours": 28576.0, + "name": "diod - distributed I/O daemon", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/diod", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/distarray.json b/agency-indexes/DoE/distarray.json new file mode 100644 index 00000000..1ea3ba92 --- /dev/null +++ b/agency-indexes/DoE/distarray.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "This is the repository for distarray developed at Lawrence Livermore National Laboratory (LLNL). ", + "laborHours": 228.0, + "languages": [], + "name": "distarray", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/distarray", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/distro_utils.json b/agency-indexes/DoE/distro_utils.json new file mode 100644 index 00000000..d3d44a68 --- /dev/null +++ b/agency-indexes/DoE/distro_utils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-25", + "metadataLastUpdated": "2020-08-25" + }, + "description": "This module contains utility code and data used in the creation of KBase distributions.", + "laborHours": 942.4, + "languages": [], + "name": "distro_utils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/distro_utils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dkainer_RWRtoolkit.json b/agency-indexes/DoE/dkainer_RWRtoolkit.json new file mode 100644 index 00000000..674c9296 --- /dev/null +++ b/agency-indexes/DoE/dkainer_RWRtoolkit.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "kainerd@ornl.gov" + }, + "date": { + "created": "2022-06-07", + "metadataLastUpdated": "2022-06-23" + }, + "description": "a set of command-line and R tools for performing Random-walk with Restart analyses on multiplex networks in any species", + "laborHours": 0.0, + "languages": [ + "R" + ], + "name": "dkainer/RWRtoolkit", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/dkainer/rwrtoolkit", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dlCC_Optimization.json b/agency-indexes/DoE/dlCC_Optimization.json new file mode 100644 index 00000000..ad7024fc --- /dev/null +++ b/agency-indexes/DoE/dlCC_Optimization.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-11-20", + "metadataLastUpdated": "2019-11-20" + }, + "description": "There are numerous options for renewable energy systems development. Location, size, type of system, and a number of other criteria need to be considered. The objective of this program is to determine the optimal size (capacity, Kilowatt (kW)) of a renewable energy generator, based on minimizing life cycle cost (LCC). The reason for developing such a program is driven by three major issues. First, the need to evaluate a very large number (tens of thousands) of project opportunity sites. Next, the need for data transfer efficiency and computational efficiency in on-line and mobile applications. And lastly, to increase the accuracy of screening studies, which are the earliest indicators of project opportunities. Many existing programs require the user to enter the size (kW) of the renewable energy system in order to start calculations. \n \nHowever, there are many factors that affect what the size should be including: renewable energy resources, utility rates, initial and maintenance costs, and economic parameters. NREL scientists have developed an algorithm that addresses the previous three major issues. Lifecycle cost is calculated based on: the sum of initial cost, plus the present value of operations and maintenance costs, costs involved with purchasing power from the utility company, and revenue involved with the sale of excess electricity back to the utility.\n\nThe algorithm computes the derivative of an equation for LCC as a function of the size of the renewable energy generator (P), then sets the derivative equal to zero (dLCC/dP=0), and solves for the value of (P) that minimizes life cycle cost. Once the size (P) has been determined, other project details may be calculated. This algorithm develops a closed-form solution for the optimal size of a renewable energy generator. Having a closed-form solution avoids problems of scale and speed that can be encountered with optimization algorithms. Incentives that affect initial cost or provide a payment for energy production are also represented.\n\nBecause the algorithm was built in terms of analytics (calculus) and not numeric methods, it can be easily implemented in any platform such as spreadsheets or mobile computing applications. The program is very accurate as long as the simplifying assumptions in the derivation apply: constant load (during daylight hours for PV, all hours for wind); a single rate for all power purchased from the utility; and a single rate for all power sold back to the utility. The program calculates energy saved on-site and energy sold back to the utility using a duration curve based on capacity factor. 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Docker is a container management platform. OpenResty is a full-fledged web application server by bundling the standard nginx core, lots of 3rd-party nginx modules, as well as most of their external dependencies.", + "laborHours": 486.4, + "languages": [], + "name": "docker-openresty", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/docker-openresty", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dockerize.json b/agency-indexes/DoE/dockerize.json new file mode 100644 index 00000000..451c5c61 --- /dev/null +++ b/agency-indexes/DoE/dockerize.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { 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"metadataLastUpdated": "2024-06-18" + }, + "description": "This repository contains the\u00a0tutorial and package reference\u00a0for the\u00a0Smisc\u00a0package.", + "laborHours": 4043.2, + "languages": [], + "name": "docs-Smisc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/docs-Smisc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/docs-rsed.json b/agency-indexes/DoE/docs-rsed.json new file mode 100644 index 00000000..40a941ca --- /dev/null +++ b/agency-indexes/DoE/docs-rsed.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + 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"metadataLastUpdated": "2017-10-25" + }, + "description": "A pipeline for scanning domains to measure things like speed, accessibility, and HTTPS.", + "laborHours": 2781.6, + "name": "domain-scan", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/18F/domain-scan/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/18F/domain-scan", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dracut.json b/agency-indexes/DoE/dracut.json new file mode 100644 index 00000000..991c68a9 --- /dev/null +++ b/agency-indexes/DoE/dracut.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-31", + "metadataLastUpdated": "2018-07-31" + 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collected data as well as test hypothetical or simulated neutron events data. Instrument scientists can use the advance features of drtsans to calibrate their instruments and reduced large quantities of datasets in a streamlined mode. Users can correct the collected data with dark current subtraction and normalization by neutron flux, detector sensitivity, solid angle subtended by the detectors, and scaling to absolute units. Conversion from time-of-flight and/or wavelength to 1D or 2D momentum transfer renders the final scattering quantities amenable to analysis.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "drtsans", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/sns-hfir-scse/sans/sans-backend", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "1.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dsgrid__Demand-Side_Grid_Toolkit__[SWR-21-52].json b/agency-indexes/DoE/dsgrid__Demand-Side_Grid_Toolkit__[SWR-21-52].json new file mode 100644 index 00000000..109a83ae --- /dev/null +++ b/agency-indexes/DoE/dsgrid__Demand-Side_Grid_Toolkit__[SWR-21-52].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-03-10", + "metadataLastUpdated": "2024-01-29" + }, + "description": "The demand-side grid model harnesses decades of sector-specific energy modeling expertise to understand current and future U.S. electricity load for power systems analyses. The API provides tools for submitting datasets to dsgrid projects, validating individual datasets and project data as a whole, querying, analysis, and visualization.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook", + "Shell" + ], + "name": "dsgrid (Demand-Side Grid Toolkit) [SWR-21-52]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dsgrid/dsgrid", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.4.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dumbno.json b/agency-indexes/DoE/dumbno.json new file mode 100644 index 00000000..f55fc38b --- /dev/null +++ b/agency-indexes/DoE/dumbno.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-07-05" + }, + "description": "No elephant flows - flow shuting for Arista switches using EOS API.\n", + "laborHours": 167.2, + "languages": [], + "name": "dumbno", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ncsa/dumbno/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/dumbno", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/duqling.json b/agency-indexes/DoE/duqling.json new file mode 100644 index 00000000..b91ff29a --- /dev/null +++ b/agency-indexes/DoE/duqling.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "The duqling R package is a tool for facilitating reproducible research in UQ and ML by providing easy-to-use and consistent access to a wide variety of popular (public) test functions", + "laborHours": 0.0, + "languages": [], + "name": "duqling", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/knrumsey/duqling", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/dynamo.json b/agency-indexes/DoE/dynamo.json new file mode 100644 index 00000000..3cf64481 --- /dev/null +++ b/agency-indexes/DoE/dynamo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-06-26", + "metadataLastUpdated": "2018-06-26" + }, + "description": "The Software is a toolbox for Dynamic Programming and Adaptive Dynamic Programming (ADP) that enables stochastic, multi-period decision optimization for arbitrary \"black box\" models. It\u2019s modular framework is designed to serve as a wrapper for other simulation tools. This enables forward-looking optimization under uncertainty to aid decision making by a variety of stakeholders when facing an increasingly uncertain future. ", + "laborHours": 5122.4, + "languages": [], + "name": "dynamo", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/dynamo", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/e3nn_tutorial_v0.2.json b/agency-indexes/DoE/e3nn_tutorial_v0.2.json new file mode 100644 index 00000000..728fd062 --- /dev/null +++ b/agency-indexes/DoE/e3nn_tutorial_v0.2.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-25", + "metadataLastUpdated": "2021-03-31" + }, + "description": "Repository and website for tutorials on 3d Euclidean equivariant neural networks.", + "laborHours": 0.0, + "languages": [], + "name": "e3nn tutorial v0.2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/blondegeek/e3nn_tutorial", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "0.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/e3sm_nex.json b/agency-indexes/DoE/e3sm_nex.json new file mode 100644 index 00000000..9d5d26be --- /dev/null +++ b/agency-indexes/DoE/e3sm_nex.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-28", + "metadataLastUpdated": "2020-05-28" + }, + "description": "A set of tools to view E3SM data on native grids.", + "laborHours": 471.2, + "languages": [], + "name": "e3sm_nex", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/e3sm_nex", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/eBPF_Community_ID_Calculation.json b/agency-indexes/DoE/eBPF_Community_ID_Calculation.json new file mode 100644 index 00000000..b64b4033 --- /dev/null +++ b/agency-indexes/DoE/eBPF_Community_ID_Calculation.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The code titled \u201ceBPF Community ID Calculation\u201d allows easy correlation of monitoring logs with existing network forensics logs on high-performance computing (HPC) systems. This code implements the Community ID Flow Hashing standard to calculate community ID Flow identifiers. These identifiers will be used to correlate host forensics logs with network forensics logs. The correlation provides valuable insight and the ability to easily pivot between disparate data sources. The computer code removes the libpcap dependency from the code base.", + "laborHours": 167.2, + "languages": [ + "Golang. 1.13" + ], + "name": "eBPF Community ID Calculation", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stefanmaerz/eBPF_communityID", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/eCo-Pylot_-_A_Python-Based_Script_for_Sending_Parsed_Email_Data_to_a_Database.json b/agency-indexes/DoE/eCo-Pylot_-_A_Python-Based_Script_for_Sending_Parsed_Email_Data_to_a_Database.json new file mode 100644 index 00000000..4e282f4d --- /dev/null +++ b/agency-indexes/DoE/eCo-Pylot_-_A_Python-Based_Script_for_Sending_Parsed_Email_Data_to_a_Database.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "eCo-PylotDB, written completely in Python, provides a script that parses incoming emails and prepares extracted data for submission to a database table. The script extracts the database server, the database table, the server password, and the server username all from the email address to which the email is sent. The database table is specified on the Subject line. Any text in the body of the email is extracted as user comments for the database table. Attached files are extracted as data files with each file submitted to a specified table field but in separate rows of the targeted database table. Other information such as sender, date, time, and machine from which the email was sent is extracted and submitted to the database table as well. An email is sent back to the user specifying whether the data from the initial email was accepted or rejected by the database server. If rejected, the return email includes details as to why.", + "laborHours": 64448.0, + "languages": [], + "name": "eCo-Pylot - A Python-Based Script for Sending Parsed Email Data to a Database", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/PYLOTDB", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/eProject_Builder__ePB__v3.1.json b/agency-indexes/DoE/eProject_Builder__ePB__v3.1.json new file mode 100644 index 00000000..123dd2c0 --- /dev/null +++ b/agency-indexes/DoE/eProject_Builder__ePB__v3.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-05", + "metadataLastUpdated": "2021-08-05" + }, + "description": "eProject Builder (ePB) is a secure, web-based system that enables agencies and ESCOs to securely: (1) preserve, track, and access energy project information for the life of the contract (2) quickly generate data and reports for their portfolio of projects (3) develop project scenarios using standardized amortization calculations (4) benchmark new projects against historical project data", + "homepageURL": "https://sites.google.com/lbl.gov/2021-124/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "eProject Builder (ePB) v3.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2021-124/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-124/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/eSTOMP-WR.json b/agency-indexes/DoE/eSTOMP-WR.json new file mode 100644 index 00000000..4463d4c9 --- /dev/null +++ b/agency-indexes/DoE/eSTOMP-WR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "eSTOMP-WR (exascale Subsurface Transport Over Multiple Phases) is a highly scalable (parallel), general-purpose tool for simulating subsurface flow and reactive transport in variably saturated geologic media. It's written in Fortran 90.", + "laborHours": 33728.8, + "languages": [], + "name": "eSTOMP-WR", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/eSTOMP-WR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/eZeeKonfigurator_v1.0.json b/agency-indexes/DoE/eZeeKonfigurator_v1.0.json new file mode 100644 index 00000000..6f0646f1 --- /dev/null +++ b/agency-indexes/DoE/eZeeKonfigurator_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-02", + "metadataLastUpdated": "2019-10-02" + }, + "description": "eZeeKonfigurator is a web application and supporting tools for configuring Zeek (formerly Bro) systems.\n\nZeek is an open-source tool developed at LBNL that's used to secure computer networks. A recent version of Zeek introduced the configuration framework, where changes can be made while the system is running. However, the provided method is difficult to operationalize, as it requires a set of text files to be deployed and updated across all the Zeek systems.\n\neZeeKonfigurator provides an easy-to-use web interface to this. Users can view and modify options in a web application, and then those changes are deployed to the desired Zeek systems. Additionally, users benefit from additional features, such as:\n\n* Logging and auditing, to determine who made what change and when\n* Automated expiration of changes (e.g. an exception is added for 2 weeks, after which time it will be removed)\n* Validation of changes and verification that the change has been applied\n* Fine-grained role-based access", + "laborHours": 1991.2, + "languages": [], + "name": "eZeeKonfigurator v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/eZeeKonfigurator", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/eagles-project_asediag.json b/agency-indexes/DoE/eagles-project_asediag.json new file mode 100644 index 00000000..fa1f5dd8 --- /dev/null +++ b/agency-indexes/DoE/eagles-project_asediag.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-25", + "metadataLastUpdated": "2024-11-25" + }, + "description": "Aerosol process analysis in model-native Spectral Element (SE) grid. Aerosol Diagnostics on Model Native Grid is a Python-based tool designed for diagnosing aerosol processes in E3SM. It is\nparticularly designed to analyze simulation data on the model-native spectral element (SE) grid, soit is also known as\nAerosol SE Diagnostics or \u201casediag\u201d", + "laborHours": 1884.8, + "languages": [], + "name": "eagles-project/asediag", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eagles-project/asediag", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/eclipse_eavp.json b/agency-indexes/DoE/eclipse_eavp.json new file mode 100644 index 00000000..e7deb5e2 --- /dev/null +++ b/agency-indexes/DoE/eclipse_eavp.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "billingsjj@ornl.gov" + }, + "date": { + "created": "2017-11-15", + "metadataLastUpdated": "2017-12-19" + }, + "description": "Eclipse advanced visualization project", + "laborHours": 40052.0, + "name": "eclipse/eavp", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eclipse/eavp", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/eclipse_ice.json b/agency-indexes/DoE/eclipse_ice.json new file mode 100644 index 00000000..5ed005a3 --- /dev/null +++ b/agency-indexes/DoE/eclipse_ice.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "billingsjj@ornl.gov" + }, + "date": { + "created": "2017-11-15", + "metadataLastUpdated": "2017-11-15" + }, + "description": "Ice Project Main repo", + "laborHours": 92902.4, + "name": "eclipse/ice", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/epl-1.0", + "name": "EPL-1.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/eclipse/ice", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/edit-initramfs.sh.json b/agency-indexes/DoE/edit-initramfs.sh.json new file mode 100644 index 00000000..a5befc8a --- /dev/null +++ b/agency-indexes/DoE/edit-initramfs.sh.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-30", + "metadataLastUpdated": "2023-06-30" + }, + "description": "edit-initramfs.sh is a simple script to extract, edit, and rebuild an initramfs image. This makes it easy to quickly make edits to the contents of an initramfs.\n", + "laborHours": 0.0, + "languages": [], + "name": "edit-initramfs.sh", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tonyhutter/edit-initramfs", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/edmbutton.json b/agency-indexes/DoE/edmbutton.json new file mode 100644 index 00000000..4bfa4a9f --- /dev/null +++ b/agency-indexes/DoE/edmbutton.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "A PyDM widget for launching EDM displays.", + "laborHours": 0.0, + "languages": [], + "name": "edmbutton", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/edmbutton/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/edmbutton", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/edrixs.json b/agency-indexes/DoE/edrixs.json new file mode 100644 index 00000000..812fbfb0 --- /dev/null +++ b/agency-indexes/DoE/edrixs.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-01", + "metadataLastUpdated": "2019-07-01" + }, + "description": "An open source toolkit for simulating RIXS spectra based on exact diagonalization (ED) for strongly correlated materials. It is developed as part of COMSCOPE project in the Center for Computational Material Spectroscopy and Design, Brookhaven National Laboratory.", + "laborHours": 9363.2, + "languages": [], + "name": "edrixs", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/edrixs", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/eeyore.json b/agency-indexes/DoE/eeyore.json new file mode 100644 index 00000000..6d46f479 --- /dev/null +++ b/agency-indexes/DoE/eeyore.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The software \"eeyore\" solves the problem of running Markov chain Monte Carlo (MCMC) algorithms on Bayesian neural networks. There is software for MCMC algorithms and software for neural network (such as PyTorch and TensorFlow), but there are limited solutions for combining the two. The main idea is to create a subclass of the 'torch.nn.Module' for defining Bayesian neural networks with the desired functionality required by MCMC taking the form of additional methods in that sub-class. This way, neural network functionality of PyTorch is exposed to the developer and user, allowing to develop MCMC methods on top of it through a simple API. The code implements Langevin Monte Carlo algorithms and population MCMC algorithms, as well as combinations of these, for Bayesian neural networks. This kind of functionality is not available elsewhere, to the best of the authors' knowledge. Moreover, a simple API is available that allows to implement new MCMC algorithms in the future.", + "laborHours": 2614.4, + "languages": [ + "Python (v3.6 onwards)" + ], + "name": "eeyore", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/papamarkou/eeyore", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/eiger-io.json b/agency-indexes/DoE/eiger-io.json new file mode 100644 index 00000000..8f155df0 --- /dev/null +++ b/agency-indexes/DoE/eiger-io.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "I/O tools for the Eiger detector.", + "laborHours": 532.0, + "languages": [], + "name": "eiger-io", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/eiger-io", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/eldispacho.json b/agency-indexes/DoE/eldispacho.json new file mode 100644 index 00000000..57fac0b2 --- /dev/null +++ b/agency-indexes/DoE/eldispacho.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "eldispacho (Dispatcher) is a singleton that simulates the quantum network itself. Each quantum client connects to the dispatcher, which then simulates channels for communication. Eldispacho has a sense of time and space and thus is where the noise model is located.\n", + "laborHours": 1580.8, + "name": "eldispacho", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/eldispacho", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/epJSON_Editor.json b/agency-indexes/DoE/epJSON_Editor.json new file mode 100644 index 00000000..ba577c6c --- /dev/null +++ b/agency-indexes/DoE/epJSON_Editor.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "degrawjw@ornl.gov" + }, + "date": { + "created": "2022-10-10", + "metadataLastUpdated": "2022-10-20" + }, + "description": "The software provides an interface to the EnergyPlus input file, providing similar functionality to the IdfEditor tool but written in Python and specifically targeting the JSON-formatted input file. This interface occupies (as IdfEditor did previously) the niche between directly editing the input file and use of a more full-featured graphical user interface, providing both advanced and novice users with a simple interface. An extensive effort was made to gather stakeholder feedback in order to avoid merely duplicating the features of IdfEditor and to build an interface that met the needs of users both now and into the future.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "epJSON Editor", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-BTRIC/epJSON-Editor", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/epi_inference_v._1.0.json b/agency-indexes/DoE/epi_inference_v._1.0.json new file mode 100644 index 00000000..1170c7ca --- /dev/null +++ b/agency-indexes/DoE/epi_inference_v._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-09-11", + "metadataLastUpdated": "2024-09-18" + }, + "description": "SAND2021-0503 O\n\nThe epi_inference software supports the prediction of disease transmission parameters from data.\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 7637437.6, + "languages": [ + "Python" + ], + "name": "epi_inference v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/epi_inference", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/epicsarchiver_automation.json b/agency-indexes/DoE/epicsarchiver_automation.json new file mode 100644 index 00000000..0909b853 --- /dev/null +++ b/agency-indexes/DoE/epicsarchiver_automation.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "A set of python scripts that can be used to automate maintenance of an EPICS Archiver Appliance.", + "laborHours": 152.0, + "name": "epicsarchiver_automation", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/epicsarchiver_automation", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/epicsuite_EAS_.json b/agency-indexes/DoE/epicsuite_EAS_.json new file mode 100644 index 00000000..784d5fe4 --- /dev/null +++ b/agency-indexes/DoE/epicsuite_EAS_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-12" + }, + "description": "Software, Documentation, Tutorials, Testing data, Example data for processing, analysis, filtering, querying, visualization and otherwise transforming genomic data for scientific analysis and discovery.", + "laborHours": 45.6, + "languages": [], + "name": "epicsuite(EAS)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/epicsuite/epicsuite-readthedocs", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/equivariant_electron_density.json b/agency-indexes/DoE/equivariant_electron_density.json new file mode 100644 index 00000000..84e36fed --- /dev/null +++ b/agency-indexes/DoE/equivariant_electron_density.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SAND2022-3548 O This code contains scripts that allow users to generate molecular electron densities, train a machine learning model to predict electron densities, and analyze the accuracy of machine learned electron densities. It accompanies a publication titled \"Cracking the Quantum Scaling Limit with Machine Learned Electron Densities.\u201d Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1565.6, + "languages": [ + "Python", + "Jupyter notebook" + ], + "name": "equivariant_electron_density", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/equivariant_electron_density", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/era-opt.json b/agency-indexes/DoE/era-opt.json new file mode 100644 index 00000000..eb3e9c03 --- /dev/null +++ b/agency-indexes/DoE/era-opt.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-10-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "An algorithm to reduce the enumeration of possible metamers to be examined from multi-primary LED systems when searching (optimizing) for combinations with particular chromaticity characteristics.", + "laborHours": 0.0, + "languages": [], + "name": "era-opt", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/era_opt.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-artifacts.json b/agency-indexes/DoE/esgf-artifacts.json new file mode 100644 index 00000000..d96b0641 --- /dev/null +++ b/agency-indexes/DoE/esgf-artifacts.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "Maven Repo Of ESGF Project Artifacts\n", + "laborHours": 3268.0, + "languages": [], + "name": "esgf-artifacts", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-artifacts", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-build.json b/agency-indexes/DoE/esgf-build.json new file mode 100644 index 00000000..64f77587 --- /dev/null +++ b/agency-indexes/DoE/esgf-build.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "Scripts for building ESGF releases, creating repo mirrors and pushing binaries.\u00a0https://esgf.github.io/esgf-build/\n", + "laborHours": 197.6, + "languages": [], + "name": "esgf-build", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-build", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-ca.json b/agency-indexes/DoE/esgf-ca.json new file mode 100644 index 00000000..4859e582 --- /dev/null +++ b/agency-indexes/DoE/esgf-ca.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "The Earth System Grid Federation (ESGF), uses three internal Certification Authorities (Cas), to issue CA and identify certificates for the systems in ESGF. The ESGF CA infrastrucutre supports grid and e-science activities in the ESGF.\n", + "laborHours": 212.8, + "languages": [], + "name": "esgf-ca", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-ca", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-dashboard-ui.json b/agency-indexes/DoE/esgf-dashboard-ui.json new file mode 100644 index 00000000..d8cb57d9 --- /dev/null +++ b/agency-indexes/DoE/esgf-dashboard-ui.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "New Dashboard front-end for ESGF.\n", + "laborHours": 52029.6, + "languages": [], + "name": "esgf-dashboard-ui", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-dashboard-ui", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-dist.json b/agency-indexes/DoE/esgf-dist.json new file mode 100644 index 00000000..0e8eea06 --- /dev/null +++ b/agency-indexes/DoE/esgf-dist.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "Repository containing ESGF distributions.\n", + "laborHours": 0.0, + "languages": [], + "name": "esgf-dist", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-dist", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-docker.json b/agency-indexes/DoE/esgf-docker.json new file mode 100644 index 00000000..1338cd2d --- /dev/null +++ b/agency-indexes/DoE/esgf-docker.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "ESGF software stack as Docker images.\n", + "laborHours": 10822.4, + "languages": [], + "name": "esgf-docker", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-docker", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-drslib.json b/agency-indexes/DoE/esgf-drslib.json new file mode 100644 index 00000000..7d90ed62 --- /dev/null +++ b/agency-indexes/DoE/esgf-drslib.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This is a Python library for processing the 5th Climate Model Intercomparison Project [CMIP5]_ Data Reference Syntax [DRS]_. http://esgf.org/esgf-drslib/\n", + "laborHours": 4818.4, + "languages": [], + "name": "esgf-drslib", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-drslib", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-getcert.json b/agency-indexes/DoE/esgf-getcert.json new file mode 100644 index 00000000..38119549 --- /dev/null +++ b/agency-indexes/DoE/esgf-getcert.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "This branch of esgf-getcert explores use MyProxyLogon of http://grid.ncsa.illinois.edu/myproxy/MyProxyLogon/ instead of MyProxy and implements a own implementation to convert private key PKCS#8 in PKCS#1. So it can avoid the bug with openJDK versions (https://github.com/ESGF/esgf-getcert/issues/2). Also, this new implementation allows generate a getcert.jar smaller than MyProxy version getcert.jar.\n", + "laborHours": 1033.6, + "languages": [], + "name": "esgf-getcert", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-getcert", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-ingestion.json b/agency-indexes/DoE/esgf-ingestion.json new file mode 100644 index 00000000..0fe76f08 --- /dev/null +++ b/agency-indexes/DoE/esgf-ingestion.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "ESGF Ingestion Software developed at Lawrence Livermore National Laboratory. \n", + "laborHours": 0.0, + "languages": [], + "name": "esgf-ingestion", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-ingestion", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-publisher-resources.json b/agency-indexes/DoE/esgf-publisher-resources.json new file mode 100644 index 00000000..7b269b8f --- /dev/null +++ b/agency-indexes/DoE/esgf-publisher-resources.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-16", + "metadataLastUpdated": "2018-07-16" + }, + "description": "ESGF Next Generation Publishing Resource files; Repository of project schema and resource files needed for \"next generation\" publishing.\n", + "laborHours": 1535.2, + "languages": [], + "name": "esgf-publisher-resources", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-publisher-resources", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-pyclient.json b/agency-indexes/DoE/esgf-pyclient.json new file mode 100644 index 00000000..8d7bedca --- /dev/null +++ b/agency-indexes/DoE/esgf-pyclient.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This package contains API code for calling the\u00a0ESGF Search API\u00a0within client code. The initial implementation is in Python.\n", + "laborHours": 1033.6, + "languages": [], + "name": "esgf-pyclient", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-pyclient", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-slcs-server-playbook.json b/agency-indexes/DoE/esgf-slcs-server-playbook.json new file mode 100644 index 00000000..f0af33f5 --- /dev/null +++ b/agency-indexes/DoE/esgf-slcs-server-playbook.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This repository provides an Ansible playbook that can deploy the ESGF SLCS Server.\n", + "laborHours": 273.6, + "languages": [], + "name": "esgf-slcs-server-playbook", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-slcs-server-playbook", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-slcs-server.json b/agency-indexes/DoE/esgf-slcs-server.json new file mode 100644 index 00000000..cecbd9a5 --- /dev/null +++ b/agency-indexes/DoE/esgf-slcs-server.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "This package provides a SLCS server that can provide short-lived X509 certificates for users in an ESGF user database.\n", + "laborHours": 167.2, + "languages": [], + "name": "esgf-slcs-server", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-slcs-server", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-srm.json b/agency-indexes/DoE/esgf-srm.json new file mode 100644 index 00000000..8d698325 --- /dev/null +++ b/agency-indexes/DoE/esgf-srm.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "ESGF Transparent access files from deep storage.\n", + "laborHours": 2508.0, + "languages": [], + "name": "esgf-srm", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/esgf-stager", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esgf-stats-api.json b/agency-indexes/DoE/esgf-stats-api.json new file mode 100644 index 00000000..9d22a00c --- /dev/null +++ b/agency-indexes/DoE/esgf-stats-api.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, 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"permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/esmond-test/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/esmond-test", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esnet-gh-pages-base.json b/agency-indexes/DoE/esnet-gh-pages-base.json new file mode 100644 index 00000000..0facb50e --- /dev/null +++ b/agency-indexes/DoE/esnet-gh-pages-base.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "Base templates for ESnet's GitHub pages. These pages are created using the Sphinx documentation package using the sphinx-bootstrap-theme with some pages. This repo is meant to be included into a project using git subtree and provides the overrides and customizations to the base theme.", + "laborHours": 152.0, + "languages": [], + "name": "esnet-gh-pages-base", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/esnet-gh-pages-base", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esnet_relay-test.json b/agency-indexes/DoE/esnet_relay-test.json new file mode 100644 index 00000000..9dc215de --- /dev/null +++ b/agency-indexes/DoE/esnet_relay-test.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "A test of Relay and GraphQL for the ESnet Software Summit. 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They were developed for use in the [MyESnet portal](https://my.es.net/)\nbut are general enough to be used other places. The widgets are built using the d3.js library.", + "laborHours": 106.4, + "languages": [], + "name": "esviz", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/esviz/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/esviz", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/esxsnmp-tsdb.json b/agency-indexes/DoE/esxsnmp-tsdb.json new file mode 100644 index 00000000..0ff7d192 --- /dev/null +++ b/agency-indexes/DoE/esxsnmp-tsdb.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "Simple time series database for ESxSNMP.", + "laborHours": 1048.8, + "languages": [], + "name": "esxsnmp-tsdb", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/esxsnmp-tsdb/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/esxsnmp-tsdb", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ex1ex2v2_Version_2.10.json b/agency-indexes/DoE/ex1ex2v2_Version_2.10.json new file mode 100644 index 00000000..df4366ca --- /dev/null +++ b/agency-indexes/DoE/ex1ex2v2_Version_2.10.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "ex1ex2v2 is a translator program which will convert a database in exodus1 format to exodusII format. The exodus 1 format is a defined series of Fortran unformatted writes/reads; the exodusII format is defined by the ExodusII API.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "ex1ex2v2 Version 2.10", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.10" +} \ No newline at end of file diff --git a/agency-indexes/DoE/exadigitUE5.json b/agency-indexes/DoE/exadigitUE5.json new file mode 100644 index 00000000..1f78d37c --- /dev/null +++ b/agency-indexes/DoE/exadigitUE5.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "maiterthm@ornl.gov" + }, + "date": { + "created": "2024-02-14", + "metadataLastUpdated": "2024-06-21" + }, + "description": "This project provides the AR/VR interface to ORNL's exascale digital twin.\nThe main functionality is implemented using Unreal Engine 5.1 for Desktop or\nMicrosoft Hololens2 based visualization and interation with the system.\nThe digital twin provides data ingestion from telemetry, as well as triggering\nand interacting with simulations developed for the wider ExaDigiT project at\nORNL, as well as for the LUMI system at CSC and other CrayEX Supercomputers.\nFor the overarching project, see ExaDigiT at https://exadigit.github.io,\nwith the code repositories at https://code.ornl.gov/exadigit.", + "laborHours": 25262.4, + "languages": [], + "name": "exadigitUE5", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/exadigit/exadigitue5.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/example_cmec_module.json b/agency-indexes/DoE/example_cmec_module.json new file mode 100644 index 00000000..43758c55 --- /dev/null +++ b/agency-indexes/DoE/example_cmec_module.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "This is an example CMEC module intended for use in demonstrations and tutorials. It does not produce any scientific results.", + "laborHours": 0.0, + "languages": [], + "name": "example_cmec_module", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmecmetrics/example_cmec_module", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/exawind-driver_[SWR-23-10].json b/agency-indexes/DoE/exawind-driver_[SWR-23-10].json new file mode 100644 index 00000000..08f9a483 --- /dev/null +++ b/agency-indexes/DoE/exawind-driver_[SWR-23-10].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-09-11", + "metadataLastUpdated": "2023-09-11" + }, + "description": "Exawind-driver is a C++ code that is part of the ExaWind software stack. It was designed to couple and drive hybrid-solver computational fluid dynamics (CFD) simulations where NREL's AMR-Wind (SWR-20-85) software and NREL's Nalu-Wind (SWR-20-27) CFD codes are run simultaneously and are two-way coupled via overset meshes and the TIOGA overset-mesh library.", + "laborHours": 0.0, + "languages": [ + "C++", + "CMake" + ], + "name": "exawind-driver [SWR-23-10]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Exawind/exawind-driver", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/exnehilo7_fielddata-lite-iOS-app.json b/agency-indexes/DoE/exnehilo7_fielddata-lite-iOS-app.json new file mode 100644 index 00000000..cec15770 --- /dev/null +++ b/agency-indexes/DoE/exnehilo7_fielddata-lite-iOS-app.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "martins@ornl.gov" + }, + "date": { + "created": "2024-09-12", + "metadataLastUpdated": "2024-09-19" + }, + "description": "Field Expedition Routing and Navigation (FERN) is an IOS app funded by the Center for Bioenergy Innovation (CBI). It allows an end user to make trips to collect novel data points. It allows user to return to previously surveyed points to collect more data. It calculates the optimal route to use to sample points needed for return trips. A companion php/database application is required for full functionality. Links to this open source project are in the README. FERN can use the default GPS on an Iphone but it also optimized for Arrow Gold GPS. Other external GPS could be supported by modifying this code and adding the proper routines.", + "laborHours": 2097.6, + "languages": [ + "Swift" + ], + "name": "exnehilo7/fielddata-lite-iOS-app", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/exnehilo7/fielddata-lite-iOS-app", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/exodus.py.json b/agency-indexes/DoE/exodus.py.json new file mode 100644 index 00000000..a18ec49d --- /dev/null +++ b/agency-indexes/DoE/exodus.py.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "exodus.py is a Python wrapper of the open source Exodusll API intended for efficient pre-and post-processing finite element model data stored in the Exodusll file format.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "exodus.py", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/exodus_helper.json b/agency-indexes/DoE/exodus_helper.json new file mode 100644 index 00000000..b003ec4d --- /dev/null +++ b/agency-indexes/DoE/exodus_helper.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2023-08-01", + "metadataLastUpdated": "2024-09-09" + }, + "description": "SAND2022-7288 O\nThe exodus_helper Python package is a set of tools that allows a user to query and create datasets in the Exodus II format for use in finite element analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 2280.0, + "languages": [ + "Python" + ], + "name": "exodus_helper", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov/contact-form", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/exodus_helper", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/exomatlab.json b/agency-indexes/DoE/exomatlab.json new file mode 100644 index 00000000..5aac449f --- /dev/null +++ b/agency-indexes/DoE/exomatlab.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-30" + }, + "description": "EXOMATLAB extracts the global transient variable data from an exodus file and writes it to a text-based file readable by the Matlab program.", + "laborHours": 692284.0, + "languages": [ + "MATLAB" + ], + "name": "exomatlab", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.9.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/experiment_orchestration.json b/agency-indexes/DoE/experiment_orchestration.json new file mode 100644 index 00000000..2b053efd --- /dev/null +++ b/agency-indexes/DoE/experiment_orchestration.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "weberb@ornl.gov" + }, + "date": { + "created": "2022-09-30", + "metadataLastUpdated": "2024-01-18" + }, + "description": "This framework allows experiment authors to use one local process to orchestrate many simultaneous trials of an experiment on remote resources. When several of these processes are run in parallel, it becomes possible to orchestrate thousands of remote experiment trials on an entire remote cluster using a single orchestration, or \"boss\" node.", + "laborHours": 0.0, + "languages": [], + "name": "experiment_orchestration", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/experiment_orchestration", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/extendFromReads.json b/agency-indexes/DoE/extendFromReads.json new file mode 100644 index 00000000..edc3e610 --- /dev/null +++ b/agency-indexes/DoE/extendFromReads.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This package assists in genome assembly. extendFromReads takes as input a set of Illumina (eg, MiSeq) DNA sequencing reads, a query seed sequence and a direction to extend the seed. The algorithm collects all seed-- ]matching reads (flipping reverse-- ]orientation hits), trims off the seed and additional sequence in the other direction, sorts the remaining sequences alphabetically, and prints them aligned without gaps from the point of seed trimming. This produces a visual display distinguishing the flanks of multi- ]copy seeds. A companion script hitMates.pl collects the mates of seed-- ]hi]ng reads, whose alignment reveals longer extensions from the seed. The collect/trim/sort strategy was made iterative and scaled up in the script denovo.pl, for de novo contig assembly. An index is pre-- ]built using indexReads.pl that for each unique 21-- ]mer found in all the reads, records its gfate h of extension (whether extendable, blocked by low coverage, or blocked by branching after a duplicated sequence) and other characteristics. Importantly, denovo.pl records all branchings that follow a branching contig endpoint, providing contig- ]extension information", + "laborHours": 30.4, + "languages": [ + "perl" + ], + "name": "extendFromReads", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/extendFromReads", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ezAlign.json b/agency-indexes/DoE/ezAlign.json new file mode 100644 index 00000000..b04257e8 --- /dev/null +++ b/agency-indexes/DoE/ezAlign.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-04-04", + "metadataLastUpdated": "2023-04-04" + }, + "description": "The ezAlign is aimed at clustering coarse grain simulation to find common or uncommon occurrences and convert coarse (CG) grained coordinate and topology files to atomistic formats. We use a PointNet based approach to map individual frames of simulation to points in a latent space. These points are then clustered using a variety of clustering methods. Clusters are analyzed to associate them with states in the simulation. Frames can be chosen from these clusters based on proximity to cluster centers. ezAlign takes CG coordinate and topology files and converts and outputs their corresponding atomistic formats using an alignment and relaxation procedure. ezAlign is designed to convert complex, solvated biological systems including lipid membranes with drug-like molecules using GROMACS. A GROMACS checkpoint (.cpt) file is also outputted to enable continuation simulations that retain the equilibrated atomic velocities. Independent atomistic coordinates and topologies for every molecule must already be included in ezAlign/files. A number of commonly simulated biological molecules are currently provided.", + "laborHours": 0.0, + "languages": [], + "name": "ezAlign", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/ezAlign", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ezECM.json b/agency-indexes/DoE/ezECM.json new file mode 100644 index 00000000..cd653754 --- /dev/null +++ b/agency-indexes/DoE/ezECM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "Allows the user to fit a classical event categorization matrix (ECM) model, and a novel Bayesian event categorization matrix model, both of which are used for nuclear detonation detection.", + "laborHours": 1276.8, + "languages": [], + "name": "ezECM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/skoermer-LANL/ezECM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/facet2-lattice.json b/agency-indexes/DoE/facet2-lattice.json new file mode 100644 index 00000000..0e0fa70f --- /dev/null +++ b/agency-indexes/DoE/facet2-lattice.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-11", + "metadataLastUpdated": "2022-07-11" + }, + "description": "Lattice files for the FACET-II accelerator.", + "laborHours": 0.0, + "languages": [], + "name": "facet2-lattice", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/facet2-lattice", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fast-matmul.json b/agency-indexes/DoE/fast-matmul.json new file mode 100644 index 00000000..2ce1bc82 --- /dev/null +++ b/agency-indexes/DoE/fast-matmul.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "This software provides implementations of fast matrix multiplication algorithms. These algorithms perform fewer floating point operations than the classical cubic algorithm. The software uses code generation to automatically implement the fast algorithms based on high-level descriptions. The code serves two general purposes. The first is to demonstrate that these fast algorithms can out-perform vendor matrix multiplication algorithms for modest problem sizes on a single machine. The second is to rapidly prototype many variations of fast matrix multiplication algorithms to encourage future research in this area. The implementations target sequential and shared memory parallel execution.", + "laborHours": 79724.0, + "languages": [ + "Objective-C", + "C++", + "Shell", + "Roff", + "MATLAB", + "Python" + ], + "name": "fast-matmul", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fast-matmul", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/favela3_Maize.N-cycle.Function.json b/agency-indexes/DoE/favela3_Maize.N-cycle.Function.json new file mode 100644 index 00000000..a214828f --- /dev/null +++ b/agency-indexes/DoE/favela3_Maize.N-cycle.Function.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "Supplemental sequence processing and R statistical analysis for publication which compares the microbiome of 27 Zea cultivars: 12 Inbred maize genotypes, 9 hybrids, and 6 wild teosinte. The project contains amplicon data for various genes: 16S rRNA, ITS, bacterial amoA, Archeal amoA, nirS, nirK, and nosZ. In addition to functional potential assay data, and N2O flux.", + "laborHours": 927.2, + "languages": [], + "name": "favela3/Maize.N-cycle.Function", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/favela3/Maize.N-cycle.Function", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fbWecCntrl.json b/agency-indexes/DoE/fbWecCntrl.json new file mode 100644 index 00000000..086aa9cd --- /dev/null +++ b/agency-indexes/DoE/fbWecCntrl.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2024-07-23" + }, + "description": "fbWecCntrl is set of MATLAB functions and scripts demonstrating a causal impedance matching approach to wave energy converter (WEC) control design. SAND2020-12219 M\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1246.4, + "languages": [ + "MATLAB", + "Python" + ], + "name": "fbWecCntrl", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fbWecCntrl", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fba_tools.json b/agency-indexes/DoE/fba_tools.json new file mode 100644 index 00000000..ca4ec2df --- /dev/null +++ b/agency-indexes/DoE/fba_tools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "A suite of metabolic modeling tools created using the KBase SDK.", + "laborHours": 3008703.2, + "languages": [], + "name": "fba_tools", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/fba_tools", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fdtree.json b/agency-indexes/DoE/fdtree.json new file mode 100644 index 00000000..f6388cc5 --- /dev/null +++ b/agency-indexes/DoE/fdtree.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Recursive generator of directory trees.\n", + "laborHours": 121.6, + "languages": [], + "name": "fdtree", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/fdtree", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/femtotime.json b/agency-indexes/DoE/femtotime.json new file mode 100644 index 00000000..46e6aadb --- /dev/null +++ b/agency-indexes/DoE/femtotime.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "femtotime is a library for time tracking which uses 128 bit integers\nto allow tracking time with femtosecond resolution.\n\nThe API takes the form of a C++ class GPStime, which allows setting,\ngetting, manipulation, and conversion of time. The conversion to and\nfrom UTC tracks leapseconds.", + "laborHours": 1033.6, + "languages": [], + "name": "femtotime", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/agpl-3.0", + "name": "AGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/femtotime", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fermilab-qc_docker-quantum.json b/agency-indexes/DoE/fermilab-qc_docker-quantum.json new file mode 100644 index 00000000..56cbf8b5 --- /dev/null +++ b/agency-indexes/DoE/fermilab-qc_docker-quantum.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-11-06", + "metadataLastUpdated": "2019-11-06" + }, + "description": "Dockerfiles for quantum simulators", + "laborHours": 152.0, + "languages": [ + "make", + "dockerfile" + ], + "name": "fermilab-qc/docker-quantum", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fermilab-qc/docker-quantum", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fermitools_htvault-config.json b/agency-indexes/DoE/fermitools_htvault-config.json new file mode 100644 index 00000000..e00e8c1a --- /dev/null +++ b/agency-indexes/DoE/fermitools_htvault-config.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2021-07-15", + "metadataLastUpdated": "2021-07-15" + }, + "description": "Configure a Hashicorp Vault server for use with htgettoken", + "laborHours": 0.0, + "languages": [ + "Bash", + "Python" + ], + "name": "fermitools/htvault-config", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fermitools/htvault-config", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fftMPI,_a_library_for_performing_2d_and_3d_FFTs_in_parallel.json b/agency-indexes/DoE/fftMPI,_a_library_for_performing_2d_and_3d_FFTs_in_parallel.json new file mode 100644 index 00000000..33d7039a --- /dev/null +++ b/agency-indexes/DoE/fftMPI,_a_library_for_performing_2d_and_3d_FFTs_in_parallel.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The fftMPI library enables two and three dimensional Fast Fourier Transforms (FFTs) to be\r\nperformed efficiently in parallel on a variety of platforms from desktop machines to supercomputers. It allows for flexibility in the initial distribution of the FFT grid across processors, as well as the final output. It handles the data communication and reordering necessary to perform multi-dimensional FFTs in parallel. It relies on open-source or vendor-provided libraries to perform one dimensional FFTs on a single processor. It uses MPI for inter-processor communication, which is a standard distributed memory message-passing library.", + "laborHours": 8907.2, + "languages": [ + "The CSlib can be used from programs written in C++, C, Fortran, or Python.", + "Shell", + "Makefile" + ], + "name": "fftMPI, a library for performing 2d and 3d FFTs in parallel", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/fftmpi?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/fftmpi", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fifemon-graphql-datasource.json b/agency-indexes/DoE/fifemon-graphql-datasource.json new file mode 100644 index 00000000..74e34645 --- /dev/null +++ b/agency-indexes/DoE/fifemon-graphql-datasource.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-11-13", + "metadataLastUpdated": "2019-11-13" + }, + "description": "A plugin for the Grafana monitoring/dashboarding web application that provides \nan interface to data provided by GraphQL APIs, such as the \"Lens\" API service\nthat SCD maintains for batch job monitoring data.", + "laborHours": 1520.0, + "languages": [ + "JavaScript", + "TypeScript" + ], + "name": "fifemon-graphql-datasource", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fifemon/graphql-datasource", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/filebeat.json b/agency-indexes/DoE/filebeat.json new file mode 100644 index 00000000..347bffda --- /dev/null +++ b/agency-indexes/DoE/filebeat.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "The file ingest tool for Logstash and Elasticsearch, with KBase specific configuration.", + "laborHours": 15.2, + "languages": [], + "name": "filebeat", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/filebeat", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fireworks.json b/agency-indexes/DoE/fireworks.json new file mode 100644 index 00000000..0011661b --- /dev/null +++ b/agency-indexes/DoE/fireworks.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "phuck@lbl.gov" + }, + "date": { + "created": "2018-06-14", + "metadataLastUpdated": "2018-06-14" + }, + "description": "FireWorks is a free, open-source code for defining, managing, and executing workflows. 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It consists of a Flask blueprint for web sockets and some client Javascript.", + "laborHours": 0.0, + "languages": [], + "name": "flask_socket_util", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/flask_socket_util", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/flasquiz.json b/agency-indexes/DoE/flasquiz.json new file mode 100644 index 00000000..4f3fce97 --- /dev/null +++ b/agency-indexes/DoE/flasquiz.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-04" + }, + "description": "This is a small but pretty quiz application written in Python for Flask that is meant to be easy to understand for new users of Flask, but not necessarily optimized for performance or security.SAND2020-12216 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 501.6, + "languages": [], + "name": "flasquiz", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/flasquiz", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/flecsi.json b/agency-indexes/DoE/flecsi.json new file mode 100644 index 00000000..e6e8fdc1 --- /dev/null +++ b/agency-indexes/DoE/flecsi.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "junghans@lanl.gov" + }, + "date": { + "created": "2018-02-08", + "metadataLastUpdated": "2020-12-15" + }, + "description": "set of computational science infrastructure tools designed to aid in the implementation of multi-physics application development", + "laborHours": 38668.8, + "languages": [], + "name": "flecsi", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laristra/flecsi", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/flecsolve.json b/agency-indexes/DoE/flecsolve.json new file mode 100644 index 00000000..c1a8182d --- /dev/null +++ b/agency-indexes/DoE/flecsolve.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-04-18", + "metadataLastUpdated": "2025-04-18" + }, + "description": "FleCSI Linear Algebra Package", + "laborHours": 7964.8, + "languages": [], + "name": "flecsolve", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/flecsolve", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/flexbox-react.json b/agency-indexes/DoE/flexbox-react.json new file mode 100644 index 00000000..2be37b3d --- /dev/null +++ b/agency-indexes/DoE/flexbox-react.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "Unopinionated, standard compliant flexbox components.", + "laborHours": 258.4, + "languages": [], + "name": "flexbox-react", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/flexbox-react", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/flifish.json b/agency-indexes/DoE/flifish.json new file mode 100644 index 00000000..2484af70 --- /dev/null +++ b/agency-indexes/DoE/flifish.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Identifying single molecules from fluorescence images obtained by a camera and obtain their location and intensity has\nmany applications. We have developed an efficient mathematical algorithm for this task and translate it into computer\nsoftware. Our algorithm are fast, stable and accurate comparing other programs to do the similar task. We have used our\nsoftware in several scientific research areas, such as tracking receptors in live cells, super resolution fluorescence\nmicroscopy, and counting mRNA copies in cells.", + "laborHours": 0.0, + "languages": [], + "name": "flifish", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hudehong/flifish", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/flume-plugins.json b/agency-indexes/DoE/flume-plugins.json new file mode 100644 index 00000000..93608910 --- /dev/null +++ b/agency-indexes/DoE/flume-plugins.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "A small collection of Flume Plugins and scripts.\n", + "laborHours": 592.8, + "languages": [], + "name": "flume-plugins", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/flume-plugins", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/flume-plugins_Version_1.0.json b/agency-indexes/DoE/flume-plugins_Version_1.0.json new file mode 100644 index 00000000..872de2fd --- /dev/null +++ b/agency-indexes/DoE/flume-plugins_Version_1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Flume-plugins are plugins for Apache Flume, which are used for managing data transferred through Apache Flume.", + "laborHours": 592.8, + "name": "flume-plugins Version 1.0", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/flume-plugins/blob/master/DISCLAIMER", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chu11/flume-plugins", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/flux-scalability.json b/agency-indexes/DoE/flux-scalability.json new file mode 100644 index 00000000..6783ff4c --- /dev/null +++ b/agency-indexes/DoE/flux-scalability.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Performance and scalability regression test suite for the flux resource manager core and potentially other flux projects.", + "laborHours": 820.8, + "languages": [], + "name": "flux-scalability", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/flux-framework/flux-scalability", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/flux-sched.json b/agency-indexes/DoE/flux-sched.json new file mode 100644 index 00000000..755fa7db --- /dev/null +++ b/agency-indexes/DoE/flux-sched.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "flux-sched contains the job scheduling facility for the Flux resource manager framework. It consists of an engine that handles all the functionality common to scheduling. The engine has the ability to load one or more scheduling plugins that provide specific scheduling behavior.\n", + "laborHours": 177672.8, + "languages": [], + "name": "flux-sched", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/flux-framework/flux-sched", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fountainpen.json b/agency-indexes/DoE/fountainpen.json new file mode 100644 index 00000000..458447b5 --- /dev/null +++ b/agency-indexes/DoE/fountainpen.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-03-01", + "metadataLastUpdated": "2023-03-01" + }, + "description": "FountainPen is a notepad++ plugin that provides the ability to automatically save files to a user specified web server.", + "laborHours": 0.0, + "languages": [], + "name": "fountainpen", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/fountainpen", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fperras_INTERFACES.json b/agency-indexes/DoE/fperras_INTERFACES.json new file mode 100644 index 00000000..060724d2 --- /dev/null +++ b/agency-indexes/DoE/fperras_INTERFACES.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "pieper@ameslab.gov" + }, + "date": { + "created": "2022-11-15", + "metadataLastUpdated": "2022-11-15" + }, + "description": "INTERFACES is a program that uses NMR REDOR and RESPDOR data in addition to constraints to determine the three-dimensional structures of surface-supported molecules using distance geometry and a brute force structure search.", + "laborHours": 0.0, + "languages": [ + "C++", + "g++11" + ], + "name": "fperras/INTERFACES", + "organization": "Ames Laboratory (AMES)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fperras/INTERFACES", + "status": "Development", + "tags": [ + "DOE CODE", + "Ames Laboratory (AMES)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/frobnitzem_aiowire.json b/agency-indexes/DoE/frobnitzem_aiowire.json new file mode 100644 index 00000000..d6275d64 --- /dev/null +++ b/agency-indexes/DoE/frobnitzem_aiowire.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2022-02-28", + "metadataLastUpdated": "2022-02-28" + }, + "description": "This package implements a EventLoop class that manages concurrent coroutines.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "frobnitzem/aiowire", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/frobnitzem/aiowire", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "2.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/frobnitzem_mpi_list.json b/agency-indexes/DoE/frobnitzem_mpi_list.json new file mode 100644 index 00000000..5426faee --- /dev/null +++ b/agency-indexes/DoE/frobnitzem_mpi_list.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2022-02-28", + "metadataLastUpdated": "2022-02-28" + }, + "description": "A package for working with lists distributed over MPI.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "frobnitzem/mpi_list", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/frobnitzem/mpi_list", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "0.3.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fstest.json b/agency-indexes/DoE/fstest.json new file mode 100644 index 00000000..4023122f --- /dev/null +++ b/agency-indexes/DoE/fstest.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-31", + "metadataLastUpdated": "2018-07-31" + }, + "description": "POSIX Filesystem Test Suite.", + "laborHours": 3465.6, + "languages": [], + "name": "fstest", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zfsonlinux/fstest", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ftp_service.json b/agency-indexes/DoE/ftp_service.json new file mode 100644 index 00000000..943f163a --- /dev/null +++ b/agency-indexes/DoE/ftp_service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This is the repository for \"ftp_service\" developed by KBase. ", + "laborHours": 5000.8, + "languages": [], + "name": "ftp_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ftp_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fudge.json b/agency-indexes/DoE/fudge.json new file mode 100644 index 00000000..ca21c476 --- /dev/null +++ b/agency-indexes/DoE/fudge.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-15" + }, + "description": "FUDGEFudge provides (Python based) tools to:\n\u2022 Store and modify nuclear data.\n\u2022 Convert ENDF-6 formatted nuclear data [1] into Generalized Nuclear\nData (GND) structure [2].\n\u2022 Convert LLNL\u2019s ENDL formatted nuclear data [3] into GND.\n\u2022 Plot data from GND files.\n\u2022 Check for physics problems in GND files.\n\u2022 Process nuclear data for use by Monte Carlo and/or deterministic\ncodes. Fudge contains hooks for the future addition of nuclear data\nprocessing routines.\nThe Fudge release includes samples of published ENDF-6 formatted data that\ncan be converted to the new GND format.\nThis software is the next release in a series of releases that began with GND\nversion 0.1 [2].", + "laborHours": 84664.0, + "languages": [], + "name": "fudge", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/paulromano/fudge", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fuelcell:_A_Python_package_and_graphical_user_interface_for_electrochemical_data_analysis__fuelcell__v1.json b/agency-indexes/DoE/fuelcell:_A_Python_package_and_graphical_user_interface_for_electrochemical_data_analysis__fuelcell__v1.json new file mode 100644 index 00000000..5bcea766 --- /dev/null +++ b/agency-indexes/DoE/fuelcell:_A_Python_package_and_graphical_user_interface_for_electrochemical_data_analysis__fuelcell__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-28" + }, + "description": "fuelcell is a Python package designed to standardize and streamline the analysis of electrochemical data. This package includes modules for data processing and data visualization, as well as a graphical user interface (GUI) for interactive use.", + "laborHours": 0.0, + "languages": [], + "name": "fuelcell: A Python package and graphical user interface for electrochemical data analysis (fuelcell) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/samaygarg/fuelcell.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/funnel_v0.0.1.json b/agency-indexes/DoE/funnel_v0.0.1.json new file mode 100644 index 00000000..55a1f3b6 --- /dev/null +++ b/agency-indexes/DoE/funnel_v0.0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-16", + "metadataLastUpdated": "2018-10-17" + }, + "description": "fcompare is a software package that applies for comparing two curves generated from datasets in csv format. A funnel is generated around the reference curve and the other curve is checked to verify if it is inside the funnel. The funnel can be reshaped by setting a tolerance. One potential application is to verify the development of building HVAC control sequence, in which it compares data curves from real operation with data curves from simulation using developed control sequences, to verify if the developed control sequences have been implemented correctly. In addition, it can be used for Modelica library developer to do the unit test that verifies new model developments.", + "laborHours": 1018.4, + "languages": [], + "name": "funnel v0.0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lbl-srg/funnel", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/fvGP_v2.2.0.json b/agency-indexes/DoE/fvGP_v2.2.0.json new file mode 100644 index 00000000..1b91df7b --- /dev/null +++ b/agency-indexes/DoE/fvGP_v2.2.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-03-07", + "metadataLastUpdated": "2021-03-15" + }, + "description": "fvGP is a flexible Gaussian process API that enables gpCAM, a software recently submitted, to do uncertainty quantification and steer data acquisition autonomously. In short, given a bunch of data, fvGP can find the most likely model creating the data and the model's uncertainty.", + "laborHours": 0.0, + "languages": [], + "name": "fvGP v2.2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/MarcusMichaelNoack/fvgp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "version": "v2.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gNMI_-_gRPC_Network_Management_Interface.json b/agency-indexes/DoE/gNMI_-_gRPC_Network_Management_Interface.json new file mode 100644 index 00000000..efa6a01b --- /dev/null +++ b/agency-indexes/DoE/gNMI_-_gRPC_Network_Management_Interface.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "This repository contains reference Go implementations for gNMI. The implementations include: client library implementation using gnmi.proto, CLI for interacting with gNMI service, and caching collector that connects to multiple gNMI targets and makes the data available over a single gNMI Subscribe RPC to clients.", + "laborHours": 12996.0, + "languages": [], + "name": "gNMI - gRPC Network Management Interface", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/gnmi", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gait.json b/agency-indexes/DoE/gait.json new file mode 100644 index 00000000..1997e521 --- /dev/null +++ b/agency-indexes/DoE/gait.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-10", + "metadataLastUpdated": "2022-10-10" + }, + "description": "SAND2022-6991 O gait is an extension to zeek, an open-source network analyzer that adds metadata to the existing connection and SSL logs. Most of this metadata is already exposed by the zeek script API. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "zeek scripting" + ], + "name": "gait", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/gait", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gaprice_SPAdes.json b/agency-indexes/DoE/gaprice_SPAdes.json new file mode 100644 index 00000000..329c3ec9 --- /dev/null +++ b/agency-indexes/DoE/gaprice_SPAdes.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "This is a wrapper for the SPAdes assembler.", + "laborHours": 1307.2, + "languages": [], + "name": "gaprice_SPAdes", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/gaprice_SPAdes", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gcm_eval__NREL_Global_Climate_Model_Evaluation__[SWR-24-37].json b/agency-indexes/DoE/gcm_eval__NREL_Global_Climate_Model_Evaluation__[SWR-24-37].json new file mode 100644 index 00000000..12ad1792 --- /dev/null +++ b/agency-indexes/DoE/gcm_eval__NREL_Global_Climate_Model_Evaluation__[SWR-24-37].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-05", + "metadataLastUpdated": "2024-03-14" + }, + "description": "The interplay between energy, climate, and weather is becoming more complex as our changing climate continues to affect the weather we experience which in turn drives changes in the ever increasing share of renewable energy generation and energy demand. Energy system analyses commonly rely on meteorological inputs to estimate renewable energy generation and energy demand; however, these inputs rarely represent the estimated impacts of future climate change. Climate models and publicly available climate change datasets can be used for this purpose, but the selection of inputs from the myriad of available models and datasets is a nuanced and often subjective process. There is no single perfect climate model or dataset for all applications. In this repository, we include software and the corresponding assessments of various global climate models (GCMs) from the Coupled Model Intercomparison Project (CMIP6), evaluating their skills with respect to the historical climate and comparing of their future projections of climate change. We focus on variables that directly affect the energy system including the representation of extreme values that can drive grid resilience events. The objective of this repository is not to recommend the best climate model and dataset for a given analysis, but instead to provide a reference to facilitate the selection of climate models and datasets in subsequent work.", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "gcm_eval (NREL Global Climate Model Evaluation) [SWR-24-37]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/gcm_eval", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gecko.json b/agency-indexes/DoE/gecko.json new file mode 100644 index 00000000..633aaba1 --- /dev/null +++ b/agency-indexes/DoE/gecko.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "Gecko is a C++ library for solving graph linear arrangement problems. Gecko orders the nodes of a\ngraph, representing data elements, that are connected by edges, representing affinity relations, with the\ngoal of minimizing a chosen functional of edge length. Gecko was primarily designed to minimize the\nproduct of edge lengths but can also be used to reduce bandwidth (maximum edge length) and 1-sum\n(sum of edge lengths), among others. Minimum-edge-product orderings generalize space-filling curve\norderings to geometryless graphs and find applications in data locality optimization, graph partitioning,\nand dimensionality reduction.\n", + "laborHours": 1216.0, + "languages": [], + "name": "gecko", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gecko", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gen_publication_geneset.json b/agency-indexes/DoE/gen_publication_geneset.json new file mode 100644 index 00000000..8cab34d1 --- /dev/null +++ b/agency-indexes/DoE/gen_publication_geneset.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"gen_publication_geneset\" developed by KBase. ", + "laborHours": 2188.8, + "languages": [], + "name": "gen_publication_geneset", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/gen_publication_geneset", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gene_families.json b/agency-indexes/DoE/gene_families.json new file mode 100644 index 00000000..45a5dc2a --- /dev/null +++ b/agency-indexes/DoE/gene_families.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "The Gene Families service finds domains (from public protein domain libraries such as COGs and Pfam) in proteins in a user-supplied genome.", + "laborHours": 4301.6, + "languages": [], + "name": "gene_families", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/gene_families", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/genome_annotation.json b/agency-indexes/DoE/genome_annotation.json new file mode 100644 index 00000000..ffb0d7b2 --- /dev/null +++ b/agency-indexes/DoE/genome_annotation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-10", + "metadataLastUpdated": "2020-08-10" + }, + "description": "The genome annotation service provides automated gene annotation based on the RAST system. This deploys both client and service components.", + "laborHours": 35081.6, + "languages": [], + "name": "genome_annotation", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/genome_annotation", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/genome_comparison.json b/agency-indexes/DoE/genome_comparison.json new file mode 100644 index 00000000..8f7be522 --- /dev/null +++ b/agency-indexes/DoE/genome_comparison.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "This is the repository for \"genome_comparison\" developed by KBase.", + "laborHours": 8922.4, + "languages": [], + "name": "genome_comparison", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/genome_comparison", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/genome_transform.json b/agency-indexes/DoE/genome_transform.json new file mode 100644 index 00000000..e6e17881 --- /dev/null +++ b/agency-indexes/DoE/genome_transform.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This is the repository for \"genome_transform\" developed by KBase. ", + "laborHours": 13011.2, + "languages": [], + "name": "genome_transform", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/genome_transform", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/genomeset_indexer.json b/agency-indexes/DoE/genomeset_indexer.json new file mode 100644 index 00000000..3ba0dd0e --- /dev/null +++ b/agency-indexes/DoE/genomeset_indexer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "This is an elasticsearch indexer for KBaseSets.GenomeSet KBase datatype.", + "laborHours": 638.4, + "languages": [], + "name": "genomeset_indexer", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/genomeset_indexer", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/genshell.json b/agency-indexes/DoE/genshell.json new file mode 100644 index 00000000..31043be1 --- /dev/null +++ b/agency-indexes/DoE/genshell.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "GENSHELL is a three-dimensional shell mesh generation program. The threedimensional shell mesh is generated by mapping a two-dimensional quadrilateral mesh into three dimensions according to one of several types of transformations: translation, mapping onto a spherical, ellipsoidal, or cylindrical surface, and mapping onto a user-defined spline surface. The generated three-dimensional mesh can then be reoriented by offsetting, reflecting about an axis, revolving about an axis, and scaling the coordinates. GENSHELL can be used to mesh complex three-dimensional geometries composed of several sections when the sections can be defined in terms of transformations of two-dimensional geometries. The code GJOIN is then used to join the separate sections into a single body. GENSHELL updates the EXODUS quality assurance and information records to help track the codes and files used to generate the mesh. GENSHELL reads and writes two-dimensional and three-dimensional mesh databases in the GENESIS database format; there, it is compatible with the preprocessing, postprocessing, and analysis codes in the Sandia National Laboratories Engineering Analysis Code Access System (SEACAS).", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "genshell", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.15" +} \ No newline at end of file diff --git a/agency-indexes/DoE/geothermal_osr__Energy_Predictor_for_Geothermal_Open_Source_Reservoir__[SWR-22-23].json b/agency-indexes/DoE/geothermal_osr__Energy_Predictor_for_Geothermal_Open_Source_Reservoir__[SWR-22-23].json new file mode 100644 index 00000000..61ec14af --- /dev/null +++ b/agency-indexes/DoE/geothermal_osr__Energy_Predictor_for_Geothermal_Open_Source_Reservoir__[SWR-22-23].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2023-07-07" + }, + "description": "This is a repository with the tools developed for predicting energy produced at Open-Source Reservoir (OSR). It includes both simulation data for OSR, as well as Jupyter notebooks for training and evaluating prediction models. OSR was constructed based on the data from Brady Hot Springs reservoir (Nevada, USA) but has a number of sufficiently modified characteristics and does not disclose any sensitive data.", + "laborHours": 0.0, + "languages": [ + "JUPYTER NOTEBOOK" + ], + "name": "geothermal_osr (Energy Predictor for Geothermal Open Source Reservoir) [SWR-22-23]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/geothermal_osr", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/geryon_v._0.1.json b/agency-indexes/DoE/geryon_v._0.1.json new file mode 100644 index 00000000..c3294fc7 --- /dev/null +++ b/agency-indexes/DoE/geryon_v._0.1.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Geryon is intended to be a simple library for managing the CUDA Runtime, CUDA Driver, and OpenCL APIs with a consistent interface archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Change from one API to another by simply changing the namespace archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Use multiple APIs in the same code archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Lightweight (only include files no build required) archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Manage device query and selection archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple vector and matrix containers archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple routines for data copy and type casting archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple routines for data I/O archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple classes for managing device timing archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Simple classes for managing kernel compilation and execution The primary application is to facilitate writing a single code that can be compiled using the CUDA Runtime API, the CUDA Driver API, or OpenCL.", + "laborHours": 7569.6, + "languages": [ + "C++", + "C" + ], + "name": "geryon v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/geryon?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/geryon", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gismo-cloud-deployment.json 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end of file diff --git a/agency-indexes/DoE/github_license_update.json b/agency-indexes/DoE/github_license_update.json new file mode 100644 index 00000000..2e837fe1 --- /dev/null +++ b/agency-indexes/DoE/github_license_update.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "This is a quick little tool to add LICENSE.md files to a list of GitHub repos.", + "laborHours": 15.2, + "languages": [], + "name": "github_license_update", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/github_license_update", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gitlab-executor-podman.json b/agency-indexes/DoE/gitlab-executor-podman.json new file mode 100644 index 00000000..8e30d559 --- /dev/null +++ b/agency-indexes/DoE/gitlab-executor-podman.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "heiseda@ornl.gov" + }, + "date": { + "created": "2022-01-31", + "metadataLastUpdated": "2022-01-31" + }, + "description": "A GitLab custom executor using Podman containers.", + "laborHours": 0.0, + "languages": [ + "Bash" + ], + "name": "gitlab-executor-podman", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/daheise/gitlab-executor-podman", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/glm-plotter.json b/agency-indexes/DoE/glm-plotter.json new file mode 100644 index 00000000..4ea25a1a --- /dev/null +++ b/agency-indexes/DoE/glm-plotter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-14", + "metadataLastUpdated": "2022-09-14" + }, + "description": "An interactive visualization app for power system networks described in Gridlab-D Model files.", + "laborHours": 0.0, + "languages": [], + "name": "glm-plotter", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slacgismo/glm-plotter/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/glm-plotter", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/glm.json b/agency-indexes/DoE/glm.json new file mode 100644 index 00000000..8777c054 --- /dev/null +++ b/agency-indexes/DoE/glm.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-23", + "metadataLastUpdated": "2018-10-24" + }, + "description": "Fast GridLAB-D file format parser", + "laborHours": 2006.4, + "languages": [], + "name": "glm", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/glm", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/glmgen.json b/agency-indexes/DoE/glmgen.json new file mode 100644 index 00000000..944f3617 --- /dev/null +++ b/agency-indexes/DoE/glmgen.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2021-03-16" + }, + "description": "Python scripting of GridLAB-D input files (.glm) derived from the Open Modeling Framework (OMF).", + "laborHours": 4666.4, + "languages": [], + "name": "glmgen", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/glmgen", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "4.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/glmnetGLR.json b/agency-indexes/DoE/glmnetGLR.json new file mode 100644 index 00000000..e9e0dafd --- /dev/null +++ b/agency-indexes/DoE/glmnetGLR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The primary goal was to build a classifier that accurately predicts a binary response. We utilized a Lasso logistic regression classifier (LLRC) which simultaneously restricts the size of model coefficients and the number of quality metrics included the model.\u00a0Importantly the model does not treat false-negatives and false-positives as equally deleterious events.", + "laborHours": 364.8, + "languages": [], + "name": "glmnetGLR", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/PNNL-Comp-Mass-Spec/glmnetGLR/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/glmnetGLR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/glmnetLRC_f_k_a_lrc_package:_Logistic_Regression_Classification.json b/agency-indexes/DoE/glmnetLRC_f_k_a_lrc_package:_Logistic_Regression_Classification.json new file mode 100644 index 00000000..3486b559 --- /dev/null +++ b/agency-indexes/DoE/glmnetLRC_f_k_a_lrc_package:_Logistic_Regression_Classification.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Methods for fitting and predicting logistic regression classifiers (LRC) with an arbitrary loss function using elastic net or best subsets. This package adds additional model fitting features to the existing glmnet and bestglm R packages. This package was created to perform the analyses described in Amidan BG, Orton DJ, LaMarche BL, et al. 2014. Signatures for Mass Spectrometry Data Quality. Journal of Proteome Research. 13(4), 2215-2222. It makes the model fitting available in the glmnet and bestglm packages more general by identifying optimal model parameters via cross validation with an customizable loss function. It also identifies the optimal threshold for binary classification.", + "laborHours": 744.8, + "name": "glmnetLRC f/k/a lrc package: Logistic Regression Classification", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/glmnetLRC/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/glmnetLRC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/goTLS.json b/agency-indexes/DoE/goTLS.json new file mode 100644 index 00000000..8a75b865 --- /dev/null +++ b/agency-indexes/DoE/goTLS.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-16" + }, + "description": "goTLS is an automated TLS certificate issuance and management tool for Windows, Mac, and Linux. \n\nIt can generate keys, CSRs, and optionally obtain the certificate with an internal Active Directory Certificate Services (ADCS) endpoint.", + "laborHours": 243.2, + "languages": [], + "name": "goTLS", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gotls", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gopcap.json b/agency-indexes/DoE/gopcap.json new file mode 100644 index 00000000..1fd2a904 --- /dev/null +++ b/agency-indexes/DoE/gopcap.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "gopcap is a pure Go implementation of the\u00a0pcap file format. Pcap is the standard open-source packet capture format, and is defined by the\u00a0libpcap\u00a0C library.\n", + "laborHours": 638.4, + "name": "gopcap", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/JoelWesleyReed/gopcap/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/gopcap", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gpCAM_v3.json b/agency-indexes/DoE/gpCAM_v3.json new file mode 100644 index 00000000..6f474808 --- /dev/null +++ b/agency-indexes/DoE/gpCAM_v3.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-12-05", + "metadataLastUpdated": "2020-02-05" + }, + "description": "A central goal in experimental science is to explore and understand the composition-processing-structure-property relations of materials in their associated multi-dimensional parameter spaces, These parameter spaces can be thought of as the set of all conceivable combinations of the parameters affecting an experiment, including synthesis and processing conditions, material composition, and environmental conditions during the experiment. gpCAM analyzes data to steer the experiment. The software tool creates a surrogate model and associated uncertainties by performing a Gaussian process regression. Mathematical function optimization is then used to find measurements of maximum value.", + "laborHours": 1869.6, + "languages": [], + "name": "gpCAM v3", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/MarcusMichaelNoack/gpcamv3", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/gpCAM_v6.json b/agency-indexes/DoE/gpCAM_v6.json new file mode 100644 index 00000000..0858a24a --- /dev/null +++ b/agency-indexes/DoE/gpCAM_v6.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-02-17", + "metadataLastUpdated": "2021-02-18" + }, + "description": "gpCAM is tailored to be used by experimentalists who want to steer experiments autonomously. It is based on a Gaussian process (GP). Its strength compared to other software lies in its flexibility, which together with the right training, makes it more powerful than any GP-based software. However, that means, that the software in as-is mode cannot reach its full potential.", + "laborHours": 0.0, + "languages": [], + "name": "gpCAM v6", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/MarcusMichaelNoack/gpcam", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/gp_blendclass_singleband.json b/agency-indexes/DoE/gp_blendclass_singleband.json new file mode 100644 index 00000000..df81bad8 --- /dev/null +++ b/agency-indexes/DoE/gp_blendclass_singleband.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-10-26", + "metadataLastUpdated": "2021-10-26" + }, + "description": "The code used for the data preprocessing, image simulation, and model training and analysis reported in the paper \"Gaussian Process Classification for Galaxy Blend Identification in LSST\" (arXiv:2107.09246).", + "laborHours": 0.0, + "languages": [], + "name": "gp_blendclass_singleband", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jjbuchanan/gp_blendclass_singleband", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gpde.json b/agency-indexes/DoE/gpde.json new file mode 100644 index 00000000..0593c872 --- /dev/null +++ b/agency-indexes/DoE/gpde.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-02-24", + "metadataLastUpdated": "2023-02-24" + }, + "description": "The R package gpde is an R implementation of a probabilistic differential equation solver. The package has a basic implementation of the Chkrebtii (2013) probabilistic ODE solver and an extension using the connection between Kalman Filtering for SDEs and Gaussian Processes from work by Simo Sarkka. The package also implements the Integrated Wiener covariance function from Schober 2014 to obtain probabilistic ODE solutions with the Runge-Kutta solution as the mean result. This collection of tools has been built into an R package for easy use at LANL and in the probabilistic numerics community.", + "laborHours": 0.0, + "languages": [], + "name": "gpde", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/gpde", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gpmaxlik.jl.json b/agency-indexes/DoE/gpmaxlik.jl.json new file mode 100644 index 00000000..b0aec83f --- /dev/null +++ b/agency-indexes/DoE/gpmaxlik.jl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-23", + "metadataLastUpdated": "2022-09-23" + }, + "description": "A suite of tools for efficient maximum likelihood optimization of parametric Gaussian process models", + "homepageURL": "https://www.anl.gov/partnerships/licensable-software", + "laborHours": 0.0, + "languages": [], + "name": "gpmaxlik.jl", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.anl.gov/partnerships/licensable-software", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/gr-uaslink.json b/agency-indexes/DoE/gr-uaslink.json new file mode 100644 index 00000000..af7e76a2 --- /dev/null +++ b/agency-indexes/DoE/gr-uaslink.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The gr-uaslink software is an out of tree (OOT) module for GNU Radio. It provides a wrapper around pymavlink to allow MAVlink messages to be sent with GNU Radio.", + "laborHours": 7372.0, + "name": "gr-uaslink", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/deptofdefense/gr-uaslink", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/graphMC:_A_package_for_testing_the_independence_of_graphs.json b/agency-indexes/DoE/graphMC:_A_package_for_testing_the_independence_of_graphs.json new file mode 100644 index 00000000..45fa16e9 --- /dev/null +++ b/agency-indexes/DoE/graphMC:_A_package_for_testing_the_independence_of_graphs.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "graphMC consists of an implementation of a set of statistical tests that ensure that a Markov chain in the space of graphs has converged to its stationary distribution. The tests are applicable when the graphs have labelled nodes. The tests are applied to the binary time-series traced out by an edge between two selected nodes. The software fits models of a first-order Markov process and an independent draws from a binary distribution to the time-series and selects one based on the BIC scores of the two models. The package consists of (1) an implementation of a Markov chain driving a graph rewiring process that preserves the joint degree distribution of the graph, (2) implementation of the statistical test mentioned above and (3) two examples that show how the Markov chain infrastructure and the statistical tests can be used.", + "laborHours": 0.0, + "languages": [], + "name": "graphMC: A package for testing the independence of graphs", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/graphMC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/graphite-web.json b/agency-indexes/DoE/graphite-web.json new file mode 100644 index 00000000..1ec2f62e --- /dev/null +++ b/agency-indexes/DoE/graphite-web.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-07-05", + "metadataLastUpdated": "2019-07-05" + }, + "description": "Graphite consists of two major components: the frontend Django webapp that runs under Apache/mod_wsgi and the the backend carbon-cache.py daemon.", + "laborHours": 42833.6, + "languages": [], + "name": "graphite-web", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/graphite-web", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gridlabd-weather.json b/agency-indexes/DoE/gridlabd-weather.json new file mode 100644 index 00000000..c58659e6 --- /dev/null +++ b/agency-indexes/DoE/gridlabd-weather.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-13", + "metadataLastUpdated": "2022-09-13" + }, + "description": "GridLAB-D weather data files.", + "laborHours": 0.0, + "languages": [], + "name": "gridlabd-weather", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slacgismo/gridlabd-weather/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/gridlabd-weather", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/guideRna_and_Sequence_Region_Extraction_Tool__gRNA-SeqRET__v1.0.json b/agency-indexes/DoE/guideRna_and_Sequence_Region_Extraction_Tool__gRNA-SeqRET__v1.0.json new file mode 100644 index 00000000..be146cf4 --- /dev/null +++ b/agency-indexes/DoE/guideRna_and_Sequence_Region_Extraction_Tool__gRNA-SeqRET__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-06-11", + "metadataLastUpdated": "2020-06-11" + }, + "description": "The JGI's gRNA Designer software is a a web application for doing whole genome guide RNA selection. It uses open source software, CCTop to identify potential guide RNA sequences, but adds value.", + "laborHours": 4408.0, + "languages": [], + "name": "guideRna and Sequence Region Extraction Tool (gRNA-SeqRET) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/grnadesigner/src/master", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/guideline36_conformance_test_0.1.json b/agency-indexes/DoE/guideline36_conformance_test_0.1.json new file mode 100644 index 00000000..41a4116e --- /dev/null +++ b/agency-indexes/DoE/guideline36_conformance_test_0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2019-10-23", + "metadataLastUpdated": "2019-10-23" + }, + "description": "The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) has established a set of standardized high performance sequences of operation for Heating, Ventilation and Air Conditioning (HVAC) systems in buildings through their \"Guideline 36\". In order to achieve the intended performance, these sequences must be translated and programmed accurately in the Building Automation System (BAS) controllers. Standardizing these sequences will allow for a more efficient product delivery mechanism where the sequences are programmed and tested centrally by each manufacturer, and then distributed to their dealers/engineering contractors. This approach would minimize the need for each installer to re-interpret and program the sequences, reduces risk of errors, and reduces the time required for commissioning in the field.\n\nTo achieve this goal, a performance validation method is needed to provide independent confirmation that each manufacturer has programmed the Guideline 36 sequences accurately. A standardized method of test would also avoid the need for manual interpretation (and the associated human variability) that is required with typical functional testing approaches by automating the inputs and the range of expected responses. This software \"guideline36_conformance_test\" has been developed to conduct standardized, repeatable and manufacturer independent tests to validate that a BAS controller has been programmed in conformance with Guideline 36. Manufacturers would provide the controller (or the control program) and the software would run a suite of tests by setting a set of inputs to the controller and verifying the output signals from the controller matches the expected output as set by Guideline 36.\n\n", + "laborHours": 197.6, + "languages": [], + "name": "guideline36_conformance_test 0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LBNL-ETA/guideline36_conformance_test", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/gwas.json b/agency-indexes/DoE/gwas.json new file mode 100644 index 00000000..40fe48d0 --- /dev/null +++ b/agency-indexes/DoE/gwas.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "Genome-wide association studies have emerged as popular tools for identifying genetic variants that are associated with traits of interest. This service allows user to do genome-wide association analysis through narrative interface.", + "laborHours": 1778.4, + "languages": [], + "name": "gwas", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/gwas", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/h5-batch-reader.json b/agency-indexes/DoE/h5-batch-reader.json new file mode 100644 index 00000000..6e37d4a1 --- /dev/null +++ b/agency-indexes/DoE/h5-batch-reader.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Package to prepare minibatches from h5 input for a machine learning framework.", + "laborHours": 410.4, + "name": "h5-batch-reader", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/h5-batch-reader/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/h5-batch-reader", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/hFlux.json b/agency-indexes/DoE/hFlux.json new file mode 100644 index 00000000..a8109c91 --- /dev/null +++ b/agency-indexes/DoE/hFlux.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-11-15", + "metadataLastUpdated": "2024-11-15" + }, + "description": "hFlux is open source, lightweight, easy-to-use toolkit for simulation code developers working with magnetic fields to seamlessly check their intermediate results throughout the development of simulation codes.", + "laborHours": 76.0, + "languages": [], + "name": "hFlux", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/obeznosov-LANL/hFlux", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/halotools.json b/agency-indexes/DoE/halotools.json new file mode 100644 index 00000000..c87d8a85 --- /dev/null +++ b/agency-indexes/DoE/halotools.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "ahearin@anl.gov" + }, + "date": { + "created": "2021-07-13", + "metadataLastUpdated": "2021-07-13" + }, + "description": "Halotools is a specialized python package for building simulation-based models of cosmological structure formation.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "halotools", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/astropy/halotools", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git", + "version": "0.7" +} \ No newline at end of file diff --git a/agency-indexes/DoE/handle_mngr.json b/agency-indexes/DoE/handle_mngr.json new file mode 100644 index 00000000..8e01d2da --- /dev/null +++ b/agency-indexes/DoE/handle_mngr.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-21", + "metadataLastUpdated": "2020-08-21" + }, + "description": "Provides user access capabilities to handles.", + "laborHours": 608.0, + "languages": [], + "name": "handle_mngr", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/handle_mngr", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/handle_service.json b/agency-indexes/DoE/handle_service.json new file mode 100644 index 00000000..5fed876c --- /dev/null +++ b/agency-indexes/DoE/handle_service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-18", + "metadataLastUpdated": "2020-08-18" + }, + "description": "An application programming interface for managing files. This service provides an AbstractHandle that can be used to reference data in different stores. This deploys both the client and service.", + "laborHours": 3252.8, + "languages": [], + "name": "handle_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/handle_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/hayai_annotation.json b/agency-indexes/DoE/hayai_annotation.json new file mode 100644 index 00000000..127395f5 --- /dev/null +++ b/agency-indexes/DoE/hayai_annotation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "This is the repository for \"hayai_annotation\" developed by KBase. ", + "laborHours": 1489.6, + "languages": [], + "name": "hayai_annotation", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/hayai_annotation", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/hdsullivan_ResSR.json b/agency-indexes/DoE/hdsullivan_ResSR.json new file mode 100644 index 00000000..0980d23f --- /dev/null +++ b/agency-indexes/DoE/hdsullivan_ResSR.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "sullivanhe@ornl.gov" + }, + "date": { + "created": "2025-02-21", + "metadataLastUpdated": "2025-02-21" + }, + "description": "This is the official implementation of ResSR [1]. ResSR is a computationally efficient MSI-SR method that achieves high-quality reconstructions by using a closed-form spectral decomposition along with a spatial residual correction. ResSR applies singular value decomposition to identify correlations across spectral bands, uses pixel-wise computation to upsample the MSI, and then applies a residual correction process to correct the high-spatial frequency components of the upsampled bands. While ResSR is formulated as the solution to a spatially-coupled optimization problem, we use pixel-wise regularization and derive an approximate closed-form solution, resulting in a pixel-wise algorithm with a dramatic reduction in computation that achieves state-of-the-art reconstructions.\n\n[1] Duba-Sullivan, H., Reid, E. J., Voisin, S., Bouman, C. A., & Buzzard, G. T. (2024). ResSR: A Computationally Efficient Residual Approach to Super-Resolving Multispectral Images. arXiv preprint arXiv:2408.13225.", + "laborHours": 532.0, + "languages": [ + "Python" + ], + "name": "hdsullivan/ResSR", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hdsullivan/ResSR", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/hippogryph.json b/agency-indexes/DoE/hippogryph.json new file mode 100644 index 00000000..4511d032 --- /dev/null +++ b/agency-indexes/DoE/hippogryph.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "degrawjw@ornl.gov" + }, + "date": { + "created": "2024-05-06", + "metadataLastUpdated": "2024-10-01" + }, + "description": "hippogryph is a Python package for the generation of multiblock structured grids with the grid locations determined by a mapping. A structured grid is a grid for which there is a relationship between the physical space coordinates x, y, and z and three indices i, j, and k and a multiblock grid is constructed from a set of subgrids (\"blocks\"). A \"mapped\" grid is a grid for which there is a transformation f such that the nodal locations are determined by applying this mapping to the indices: (x, y, z) = f(i, j, k). While it is possible to represent most structured grids in this form, the focus here is on mappings that are known beforehand and not computed using the numerical calculations that are commonly used within the field of numerical grid generation. The grid is first constructed in index space using primitive shapes, and then the physical space grid is constructed from the mapping, usually a tensor-product type mapping where x=f(i), y=f(j), and z=f(k), though more mappings may be added in the future. hippogryph can read and write grids in the structured Plot3D format as well as the unstructured Exodus II format.", + "laborHours": 5274.4, + "languages": [ + "Python" + ], + "name": "hippogryph", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jasondegraw/hippogryph", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/hires-lattice.json b/agency-indexes/DoE/hires-lattice.json new file mode 100644 index 00000000..40e1caaf --- /dev/null +++ b/agency-indexes/DoE/hires-lattice.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-06-16", + "metadataLastUpdated": "2022-06-16" + }, + "description": "Lattice and input files to model HiRES at LBNL.", + "laborHours": 0.0, + "languages": [], + "name": "hires-lattice", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/hires-lattice", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/hklpy.json b/agency-indexes/DoE/hklpy.json new file mode 100644 index 00000000..15bd5b4d --- /dev/null +++ b/agency-indexes/DoE/hklpy.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "Diffractometer computation library with ophyd pseudopositioner support.", + "laborHours": 1489.6, + "languages": [], + "name": "hklpy", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/hklpy/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/hklpy", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/homology_service.json b/agency-indexes/DoE/homology_service.json new file mode 100644 index 00000000..1fc8c5d5 --- /dev/null +++ b/agency-indexes/DoE/homology_service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "Callable service that provides access to a homolog database that covers prokaryotes, eukaryotes and metagenomes. It can be used for navigation between sequences as well as for computation on protein families defined on the homologs.", + "laborHours": 1064.0, + "languages": [], + "name": "homology_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/homology_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/hosamkf_DOEDesalinationLCOW.json b/agency-indexes/DoE/hosamkf_DOEDesalinationLCOW.json new file mode 100644 index 00000000..50b8af90 --- /dev/null +++ b/agency-indexes/DoE/hosamkf_DOEDesalinationLCOW.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "cmmcguir@ncsu.edu" + }, + "date": { + "created": "2025-01-29", + "metadataLastUpdated": "2025-01-29" + }, + "description": "Simple code for computing levelized cost of desalinated water using a dual Markov representation of the financial reward as well as the cost of the desalination system, taking into account a (potentially stochastic) representation of system aging as a function of utilization and current age.", + "laborHours": 30.4, + "languages": [ + "MATLAB" + ], + "name": "hosamkf/DOEDesalinationLCOW", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hosamkf/DOEDesalinationLCOW", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/hpcswtest.json b/agency-indexes/DoE/hpcswtest.json new file mode 100644 index 00000000..05bfaea9 --- /dev/null +++ b/agency-indexes/DoE/hpcswtest.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-08-29", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The HPC Software stack testing framework", + "laborHours": 42240.8, + "languages": [], + "name": "hpcswtest", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/hpcswtest", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/hxdhome.json b/agency-indexes/DoE/hxdhome.json new file mode 100644 index 00000000..3ff57583 --- /dev/null +++ b/agency-indexes/DoE/hxdhome.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-06-05", + "metadataLastUpdated": "2018-06-05" + }, + "description": "This is the repository for hxdhome developed at SLAC National Accelerator Laboratory.", + "laborHours": 836.0, + "languages": [], + "name": "hxdhome", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/hxdhome/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/hxdhome", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/hypre.json b/agency-indexes/DoE/hypre.json new file mode 100644 index 00000000..6968db3f --- /dev/null +++ b/agency-indexes/DoE/hypre.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "Parallel solvers for sparse linear systems featuring multigrid methods.", + "laborHours": 458036.8, + "languages": [], + "name": "hypre", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/hypre-space/hypre/blob/master/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hypre-space/hypre", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/hypredrive:_high-level_interface_for_solving_linear_systems_with_hypre.json b/agency-indexes/DoE/hypredrive:_high-level_interface_for_solving_linear_systems_with_hypre.json new file mode 100644 index 00000000..49dcae28 --- /dev/null +++ b/agency-indexes/DoE/hypredrive:_high-level_interface_for_solving_linear_systems_with_hypre.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-03-20", + "metadataLastUpdated": "2024-04-22" + }, + "description": "This software introduces a high-level interface designed to simplify solving linear systems using hypre, a\nrenowned library for such computational challenges. It is crafted to be accessible and user-friendly,\nmaking the powerful capabilities of hypre available to a broader audience without requiring in-depth\ntechnical knowledge. The interface is characterized by its use of YAML for input, a format celebrated for\nits structured yet straightforward readability. This choice ensures that users can easily configure the\nsoftware to meet their specific needs. Additionally, the software boasts an intuitive API that encapsulates\nhypre's functionalities, making it easier for users to interact with the process of solving linear systems. It is\nparticularly beneficial for prototyping, offering a quick and efficient means to test various solver and\npreconditioner configurations. Furthermore, the software allows for the creation of an offline testing\nframework in which predefined linear systems are read from files and benchmarked with user-defined\nsolution strategies. This makes it an invaluable tool for developers and researchers exploring and\nvalidating their computational models. Overall, the software serves as a bridge, bringing the advanced\ncomputational capabilities of hypre closer to users who may need more specialized technical expertise,\nthereby facilitating innovation and exploration in the field of numerical linear algebra.", + "laborHours": 3845.6, + "languages": [], + "name": "hypredrive: high-level interface for solving linear systems with hypre", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hypre-space/hypredrive", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/i2mex.json b/agency-indexes/DoE/i2mex.json new file mode 100644 index 00000000..90b21c79 --- /dev/null +++ b/agency-indexes/DoE/i2mex.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jbreslau@pppl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-21" + }, + "description": "Ideal 2-d Magnetohydrodynamic Equilibrium on Xplasma", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "i2mex", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PrincetonUniversity/i2mex", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "vcs": "git", + "version": "1.1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/iDASH_2018:_Task_1.json b/agency-indexes/DoE/iDASH_2018:_Task_1.json new file mode 100644 index 00000000..aa7c7461 --- /dev/null +++ b/agency-indexes/DoE/iDASH_2018:_Task_1.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2018-09-07" + }, + "description": "The goal of this track is to develop blockchain-based ledgering solutions to log and query the user activities of accessing genomic datasets (e.g., GTEx) across multiple sites.", + "laborHours": 121.6, + "languages": [ + "Python" + ], + "name": "iDASH 2018: Task 1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.github.com/sandialabs/idash2018task1", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/iGlobe:_An_Interactive_Visualization_and_Analysis_Framework_for_Geospatial_Data.json b/agency-indexes/DoE/iGlobe:_An_Interactive_Visualization_and_Analysis_Framework_for_Geospatial_Data.json new file mode 100644 index 00000000..da72b1f6 --- /dev/null +++ b/agency-indexes/DoE/iGlobe:_An_Interactive_Visualization_and_Analysis_Framework_for_Geospatial_Data.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-28" + }, + "description": "The iGlobe system is a desktop-based visualization and analysis environment which allows seamless integration of multiple geospatial data sets from varied sources and provides an interface to interactively analyze the different data sets and apply sophisticated data analysis and mining algorithms in a near real time fashion. The framework is highly desirable in domains such as earth and climate sciences where great emphasis is placed on simultaneous analysis of different data sets such as remote sensing images, climate model simulation outputs, and other environmental and demographic databases, to understand weather and climate systems and the impact of climate change in nature and people.", + "homepageURL": "https://cse.buffalo.edu/~chandola/iglobe/iglobe.html", + "laborHours": 0.0, + "languages": [ + "JAVA Java (TM) SE runtime Environment Version 1.6.0" + ], + "name": "iGlobe: An Interactive Visualization and Analysis Framework for Geospatial Data", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://cse.buffalo.edu/~chandola/iglobe/iglobe.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://cse.buffalo.edu/~chandola/iglobe/iglobe.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/iMesh_GRUMMP.json b/agency-indexes/DoE/iMesh_GRUMMP.json new file mode 100644 index 00000000..cb9a5f38 --- /dev/null +++ b/agency-indexes/DoE/iMesh_GRUMMP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2018-07-06", + "metadataLastUpdated": "2018-07-06" + }, + "description": "iMesh interface to GRUMMP, the Generation and Refinement of Unstructured, Mixed-Element Meshes in Parallel. Supports all mesh topologies except septahedra, polygons, and polyhedra (no edges in 3D), all upward and downward adjacencies (again, no edges in 3D), 2D and 3D, full implementation. ", + "homepageURL": "http://tetra.mech.ubc.ca/GRUMMP", + "laborHours": 0.0, + "languages": [], + "name": "iMesh/GRUMMP", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://tetra.mech.ubc.ca/GRUMMP/License.html", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://tetra.mech.ubc.ca/GRUMMP", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/iPython_Molecular_Dynamics.json b/agency-indexes/DoE/iPython_Molecular_Dynamics.json new file mode 100644 index 00000000..d26ccb0f --- /dev/null +++ b/agency-indexes/DoE/iPython_Molecular_Dynamics.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Simple Molecular Dynamics Simulation and Analysis using iPython\n", + "laborHours": 91.2, + "name": "iPython Molecular Dynamics", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/iPython-Molecular-Dynamics", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/iRF_v2.0.json b/agency-indexes/DoE/iRF_v2.0.json new file mode 100644 index 00000000..b6f695b1 --- /dev/null +++ b/agency-indexes/DoE/iRF_v2.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-29", + "metadataLastUpdated": "2021-04-29" + }, + "description": "A predictive, stable, and interpretable machine learning tool: the iterative random forest algorithm (iRF). iRF discovers high-order interactions among variables with the same order of computational cost as random forests (RF). We have demonstrated the utility of iRF in several applications in the biological and environmental sciences. It is a general purpose machine learning framework for building \"explainable\" predictive engines.", + "laborHours": 0.0, + "languages": [], + "name": "iRF v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/karlkumbier/iRF2.0", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/iScore:_news_filtering_software.json b/agency-indexes/DoE/iScore:_news_filtering_software.json new file mode 100644 index 00000000..ea926311 --- /dev/null +++ b/agency-indexes/DoE/iScore:_news_filtering_software.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "iScore measures the interestingness of news article in a limited user environment. it is an online learning algorithm that combines a large set of disparate features to classify documents.", + "homepageURL": "https://sourceforge.net/projects/iscore", + "laborHours": 0.0, + "name": "iScore: news filtering software", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/iscore", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/iTOUGH2_v7.1.json b/agency-indexes/DoE/iTOUGH2_v7.1.json new file mode 100644 index 00000000..5a0d9edd --- /dev/null +++ b/agency-indexes/DoE/iTOUGH2_v7.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-09-18", + "metadataLastUpdated": "2019-09-24" + }, + "description": "iTOUGH2 (inverse TOUGH2) provides inverse modeling capabilities for TOUGH2, a simulator for multi-dimensional, multi-phase, multi-component, non-isothermal flow and transport in fractured porous media. \n\niTOUGH2 performs sensitivity analyses, data-worth analyses, parameter estimation, and uncertainty propagation analyses in geosciences and reservoir engineering and other application areas. \n\niTOUGH2 supports a number of different combinations of fluids and components (equation-of-state (EOS) modules). In addition, the optimization routines implemented in iTOUGH2 can also be used for sensitivity analysis, automatic model calibration, and uncertainty quantification of any external code that uses text-based input and output files using the PEST protocol. \n\niTOUGH2 solves the inverse problem by minimizing a non-linear objective function of the weighted differences between model output and the corresponding observations. Multiple minimization algorithms (derivative-free, gradient-based, and second-order; local and global) are available. iTOUGH2 also performs Latin Hypercube Monte Carlo simulations for uncertainty propagation analyses. A detailed residual and error analysis is provided. \n\nThis upgrade includes (a) global sensitivity analysis methods, (b) dynamic memory allocation (c) additional input features and output analyses, (d) increased forward simulation capabilities, (e) parallel execution on multicore PCs and Linux clusters, and (f) bug fixes. \n", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 74130.4, + "languages": [], + "name": "iTOUGH2 v7.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/icnwg.json b/agency-indexes/DoE/icnwg.json new file mode 100644 index 00000000..4526e939 --- /dev/null +++ b/agency-indexes/DoE/icnwg.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-17", + "metadataLastUpdated": "2018-07-17" + }, + "description": "Repository for the International Climate Network Working Group.\n", + "laborHours": 5244.0, + "languages": [], + "name": "icnwg", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ESGF/icnwg", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/id_map.json b/agency-indexes/DoE/id_map.json new file mode 100644 index 00000000..dfbd7814 --- /dev/null +++ b/agency-indexes/DoE/id_map.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "A service for assisting in mapping external ids to KBase IDs.", + "laborHours": 364.8, + "languages": [], + "name": "id_map", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/id_map", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/idaholab_Code_Generator.json b/agency-indexes/DoE/idaholab_Code_Generator.json new file mode 100644 index 00000000..f91538d5 --- /dev/null +++ b/agency-indexes/DoE/idaholab_Code_Generator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-04-24", + "metadataLastUpdated": "2023-03-15" + }, + "description": "The ns-3 code generator provides a way to automatically generate C++ simulation code for ns-3 from a high level network topology description.", + "laborHours": 1854.4, + "languages": [], + "name": "idaholab/Code_Generator", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/Code_Generator", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/idaholab_DaRT.json b/agency-indexes/DoE/idaholab_DaRT.json new file mode 100644 index 00000000..33bcb5a8 --- /dev/null +++ b/agency-indexes/DoE/idaholab_DaRT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "autumn.willard@inl.gov" + }, + "date": { + "created": "2022-11-30", + "metadataLastUpdated": "2023-03-08" + }, + "description": "The purpose of this code is to disassemble potentially malicious code into benign pieces that can safely be transported via any number of traditional methods without fear of infection.", + "laborHours": 0.0, + "languages": [], + "name": "idaholab/DaRT", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/DaRT", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/idaholab_cape2stix.json b/agency-indexes/DoE/idaholab_cape2stix.json new file mode 100644 index 00000000..94bd86b1 --- /dev/null +++ b/agency-indexes/DoE/idaholab_cape2stix.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-06-21", + "metadataLastUpdated": "2023-06-21" + }, + "description": "This software allows for the conversion, extraction, and transformation of malware behavior data from \"Malware Configuration And Payload Extraction\" (CAPEv2) sandbox reports, to Structured Threat Information eXpression (STIX). This allows for further analysis to be performed, sharing of threat data, and transit to a graph database.", + "laborHours": 0.0, + "languages": [ + "Python3" + ], + "name": "idaholab/cape2stix", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/cape2stix", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/idaholab_malamute.json b/agency-indexes/DoE/idaholab_malamute.json new file mode 100644 index 00000000..6c89d8e7 --- /dev/null +++ b/agency-indexes/DoE/idaholab_malamute.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "katy.longfellow@inl.gov" + }, + "date": { + "created": "2023-03-13", + "metadataLastUpdated": "2023-03-13" + }, + "description": "MALAMUTE combines MOOSE module functionality with realistic materials and geometries for arbitrary-Eulerian-Lagrangian (ALE) and level-set based laser melting and welding applications and electric-field assisted sintering (EFAS) applications.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "idaholab/malamute", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/malamute", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/idserver.json b/agency-indexes/DoE/idserver.json new file mode 100644 index 00000000..60e5a85a --- /dev/null +++ b/agency-indexes/DoE/idserver.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "The KBase ID service provides access to the mappings between KBase identifiers and external identifiers (the original identifiers for data that was migrated from other databases into KBase). This deploys both the client and service.", + "laborHours": 425.6, + "languages": [], + "name": "idserver", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/idserver", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/iiasa_emissions_downscaling.json b/agency-indexes/DoE/iiasa_emissions_downscaling.json new file mode 100644 index 00000000..bfc00b95 --- /dev/null +++ b/agency-indexes/DoE/iiasa_emissions_downscaling.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-11-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software tool, written in R, performs manipulations necessary to translate Human-Earth system model regional/sector emission outputs, such as those from PNNL's Global Change Assessment Model (GCAM), to gridded form needed by Earth System Models, such as DOEs E3SM (Energy Exascale Earth System Model) model. The tool takes as its primary input emissions in a standard community format, and produces CF-compliant netCDF gridded emission as its primary output. As intermediate output the tool produces downscaled emissions at the country level.", + "laborHours": 2508.0, + "languages": [ + "R" + ], + "name": "iiasa/emissions_downscaling", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/iiasa/emissions_downscaling", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/image-compare:_A_Simple_Package_for_Comparing_Images.json b/agency-indexes/DoE/image-compare:_A_Simple_Package_for_Comparing_Images.json new file mode 100644 index 00000000..75472720 --- /dev/null +++ b/agency-indexes/DoE/image-compare:_A_Simple_Package_for_Comparing_Images.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "This project provides a few components that combine together to provide a command-line utility for viewing the difference between two images.", + "laborHours": 106.4, + "languages": [], + "name": "image-compare: A Simple Package for Comparing Images", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/image-compare", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/inet.json b/agency-indexes/DoE/inet.json new file mode 100644 index 00000000..4e59d6ad --- /dev/null +++ b/agency-indexes/DoE/inet.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-05-25" + }, + "description": "INET's was developed in the 80's when the Internet was in it's infancy and various vendors were attempting to get into the ball game with half baked code that indicated a lack of understanding about basic IP standards in the area of IP and ICMP. Various test applications were written to test conformance to the early Internet RFC's especially ICMP. The INET program allows the user to exercise various minor internet services provided by a specified service host. See the DDN Protocol Handbook, Volume Two, Section 8 for a detailed description of various minor applications which one might attempt to exercise. The unix network daemon \"inetd\" was the inspiration for the name \"inet\". A simple C library generated at the time was recently used to build a program called 'dp' shich GROK uses to transfer BAG session information to some backend data collector such as DISARM (LA-CC number 05-D47)", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "laborHours": 0.0, + "languages": [ + "gcc 3.2.3 through gcc 4.0.3" + ], + "name": "inet", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/index.php", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/initAnalysis.json b/agency-indexes/DoE/initAnalysis.json new file mode 100644 index 00000000..735ca4b9 --- /dev/null +++ b/agency-indexes/DoE/initAnalysis.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "craigca@ornl.gov" + }, + "date": { + "created": "2022-01-07", + "metadataLastUpdated": "2022-01-07" + }, + "description": "A tool to quickly perform recon in the init process of a given firmware.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "initAnalysis", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Codeman655/initAnalysis", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/intercoolr.json b/agency-indexes/DoE/intercoolr.json new file mode 100644 index 00000000..d8480d9b --- /dev/null +++ b/agency-indexes/DoE/intercoolr.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-20", + "metadataLastUpdated": "2020-05-20" + }, + "description": "'intercoolr' is a collection of APIs that allow userspace codes to directly monitor and control hardware features such as P-state.", + "laborHours": 486.4, + "languages": [], + "name": "intercoolr", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/coolr-hpc/intercoolr/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/coolr-hpc/intercoolr", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/iperf.json b/agency-indexes/DoE/iperf.json new file mode 100644 index 00000000..48945630 --- /dev/null +++ b/agency-indexes/DoE/iperf.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "iperf is a tool for active measurements of the maximum achievable bandwidth on IP networks. It supports tuning of various parameters related to timing, protocols, and buffers. For each test it reports the measured throughput / bitrate, loss, and other parameters.", + "laborHours": 31357.6, + "languages": [], + "name": "iperf", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/iperf/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/iperf", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ipmi-dcmi.json b/agency-indexes/DoE/ipmi-dcmi.json new file mode 100644 index 00000000..0155ea5c --- /dev/null +++ b/agency-indexes/DoE/ipmi-dcmi.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Ipmi-dcmi supports motherboards compliant to the Data Center Management Interface (DCMI) specification, DCMI features include asset management and power limit management.", + "homepageURL": "https://www.gnu.org/software/freeipmi/index.html", + "laborHours": 0.0, + "languages": [], + "name": "ipmi-dcmi", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ipmi-fru.json b/agency-indexes/DoE/ipmi-fru.json new file mode 100644 index 00000000..21591f64 --- /dev/null +++ b/agency-indexes/DoE/ipmi-fru.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Ipmi-fru retrieves field replacement unit (FRU) information, such as product name, manufacturer, and serial numbers, from a motherboard. It retrieves this information using the IPMI protocol.", + "homepageURL": "https://www.gnu.org/software/freeipmi/index.html", + "laborHours": 0.0, + "languages": [], + "name": "ipmi-fru", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ipmiconsole.json b/agency-indexes/DoE/ipmiconsole.json new file mode 100644 index 00000000..b31ab6e6 --- /dev/null +++ b/agency-indexes/DoE/ipmiconsole.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "Ipmiconsole is a tool and library that allows a user to establish a console session with a remote machine using the IPMI Serial over LAN (SOL) protocol", + "homepageURL": "https://www.gnu.org/software/freeipmi/index.html", + "laborHours": 0.0, + "languages": [ + "C" + ], + "name": "ipmiconsole", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ipmipower.json b/agency-indexes/DoE/ipmipower.json new file mode 100644 index 00000000..612bf165 --- /dev/null +++ b/agency-indexes/DoE/ipmipower.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-19" + }, + "description": "Ipmipower implements power control through IPMI over LAN v1.5. It allows users to remotely power on, power off, power cycle, reset, or determine the power status of a machine.", + "homepageURL": "https://www.gnu.org/software/freeipmi/index.html", + "laborHours": 0.0, + "languages": [], + "name": "ipmipower", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ipmiseld.json b/agency-indexes/DoE/ipmiseld.json new file mode 100644 index 00000000..ff161cb8 --- /dev/null +++ b/agency-indexes/DoE/ipmiseld.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Impiseld stores IPMI based hardware events into normal system logs.", + "homepageURL": "https://www.gnu.org/software/freeipmi/index.html", + "laborHours": 0.0, + "languages": [], + "name": "ipmiseld", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.gnu.org/software/freeipmi/index.html", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/ipyanchorviz.json b/agency-indexes/DoE/ipyanchorviz.json new file mode 100644 index 00000000..32014fc1 --- /dev/null +++ b/agency-indexes/DoE/ipyanchorviz.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stewartsl@ornl.gov" + }, + "date": { + "created": "2022-11-28", + "metadataLastUpdated": "2022-11-28" + }, + "description": "ipyanchorviz is a novel method for viewing and sorting textual snippets using concept anchors. The component includes a circular display with textual snippets embedded in the center. Snippets respond to user defined concept anchors around the ring based on their affinity with the concept. It is implemented in the ipywidget ecosystem. As an ipywidget, this visualization is a first class citizen in the Jupyter ecosystem and can easily be used by researchers.", + "laborHours": 0.0, + "languages": [], + "name": "ipyanchorviz", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/ipyanchorviz", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ipylus.json b/agency-indexes/DoE/ipylus.json new file mode 100644 index 00000000..1d7e1ea2 --- /dev/null +++ b/agency-indexes/DoE/ipylus.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "Data Processing Software for SIX.", + "laborHours": 0.0, + "languages": [], + "name": "ipylus", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/ipylus", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ispyb-bnl.json b/agency-indexes/DoE/ispyb-bnl.json new file mode 100644 index 00000000..2ca05dc7 --- /dev/null +++ b/agency-indexes/DoE/ispyb-bnl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "Code relating to ISPyB at NSLS-II.", + "laborHours": 288.8, + "languages": [], + "name": "ispyb-bnl", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/ispyb-bnl", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/iv_parems_[SWR-22-79].json b/agency-indexes/DoE/iv_parems_[SWR-22-79].json new file mode 100644 index 00000000..2d557d6a --- /dev/null +++ b/agency-indexes/DoE/iv_parems_[SWR-22-79].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-09-30", + "metadataLastUpdated": "2022-11-07" + }, + "description": "iv_parems follows the ASTM E1036 standard to extract parameters (open-circuit voltage, short-circuit current, maximum power point) from photovoltaic current-voltage characteristics.", + "laborHours": 0.0, + "languages": [ + "Juniper", + "Python" + ], + "name": "iv_parems [SWR-22-79]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/iv_params", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.0.5" +} \ No newline at end of file diff --git a/agency-indexes/DoE/jShyLU_Scalable_Hybrid_Preconditioner_and_Solver.json b/agency-indexes/DoE/jShyLU_Scalable_Hybrid_Preconditioner_and_Solver.json new file mode 100644 index 00000000..948a681d --- /dev/null +++ b/agency-indexes/DoE/jShyLU_Scalable_Hybrid_Preconditioner_and_Solver.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-19" + }, + "description": "ShyLU is numerical software to solve sparse linear systems of equations. ShyLU uses a hybrid direct-iterative Schur complement method, and may be used either as a preconditioner or as a solver. ShyLU is parallel and optimized for a single compute Solver node. ShyLU will be a package in the Trilinos software framework.", + "laborHours": 8344830.4, + "languages": [], + "name": "jShyLU Scalable Hybrid Preconditioner and Solver", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/jacobteter_CropWatR.json b/agency-indexes/DoE/jacobteter_CropWatR.json new file mode 100644 index 00000000..f8c936c4 --- /dev/null +++ b/agency-indexes/DoE/jacobteter_CropWatR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-10-30", + "metadataLastUpdated": "2024-10-30" + }, + "description": "Biofuels policies induce land use changes (LUC), including cropland expansion and crop switching, and this in turn alters water and soil management practices. Policies differ in the extent and type of land use changes they induce and therefore in their impact on water resources. We quantify and compare the spatially varying water impacts of biofuel crops stemming from LUC induced by two different biofuels policies by coupling a biophysical model with an economic model to simulate the economically viable mix of crops, land uses, and crop management choices under alternative policy scenarios. We assess the outputs of an economic model with a high-resolution crop-water model for major agricultural crops and potential cellulosic feedstocks in the US to analyze the impacts of three alternative policy scenarios on water balances: a counterfactual \u2018no-biofuels policy\u2019 (BAU) scenario, a volumetric mandate (Mandate) scenario, and a clean fuel-intensity standard (CFS) scenario incentivizing fuels based on their carbon intensities. While both biofuel policies incentivize more biofuels than in the counterfactual, they differ in the mix of corn ethanol and advanced biofuels from miscanthus and switchgrass (more corn ethanol in Mandate and more cellulosic biofuels in CFS). The two policies differ in their impact on irrigated acreage, irrigation demand, groundwater use and runoff. Net irrigation requirements increase 0.7% in Mandate and decrease 3.8% in CFS, but in both scenarios increases are concentrated in regions of Kansas and Nebraska that rely upon the Ogallala aquifer for irrigation water. Our study illustrates the importance of accounting for the overall LUC and shifts in agricultural production and management practices in response to policies when assessing the water impacts of biofuels.", + "laborHours": 1185.6, + "languages": [], + "name": "jacobteter/CropWatR", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jacobteter/CropWatR", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/jansson_snijders_collaborative_cross.json b/agency-indexes/DoE/jansson_snijders_collaborative_cross.json new file mode 100644 index 00000000..1bef2ab7 --- /dev/null +++ b/agency-indexes/DoE/jansson_snijders_collaborative_cross.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is supplemental material for a scientific paper. This project 'bernstein-2017-founders-species', explores community succession using a lake biofilm as a model. The code here was used to process and analyze environmental metadata and genetic sequencing data. Statistical tests and data visualization are included.\nThis code makes use of commodity software that is freely available and commonly used in this field. No new methods or techniques are introduced in this code.", + "laborHours": 167.2, + "languages": [], + "name": "jansson_snijders_collaborative_cross", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/jansson_snijders_collaborative_cross/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/jansson_snijders_collaborative_cross", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/java_common.json b/agency-indexes/DoE/java_common.json new file mode 100644 index 00000000..87488fcf --- /dev/null +++ b/agency-indexes/DoE/java_common.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-10", + "metadataLastUpdated": "2020-08-10" + }, + "description": "Common java code used in multiple KBase applications. In particular, this repo includes KB-SDK code that is shared between servers and apps.", + "laborHours": 5046.4, + "languages": [], + "name": "java_common", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/java_common", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/java_type_generator.json b/agency-indexes/DoE/java_type_generator.json new file mode 100644 index 00000000..66382954 --- /dev/null +++ b/agency-indexes/DoE/java_type_generator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "This is the repository for type generation with java developed by KBase.", + "laborHours": 4377.6, + "languages": [], + "name": "java_type_generator", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/java_type_generator", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/jgi_gateway.json b/agency-indexes/DoE/jgi_gateway.json new file mode 100644 index 00000000..bd10c20e --- /dev/null +++ b/agency-indexes/DoE/jgi_gateway.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "JGI Gateway Service to sit between KBase and a JGI service.", + "laborHours": 1641.6, + "languages": [], + "name": "jgi_gateway", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/jgi_gateway", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/jgi_mg_assembly_wdl.json b/agency-indexes/DoE/jgi_mg_assembly_wdl.json new file mode 100644 index 00000000..f0f2ec50 --- /dev/null +++ b/agency-indexes/DoE/jgi_mg_assembly_wdl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-08", + "metadataLastUpdated": "2020-09-08" + }, + "description": "JGI Metagenome Assembly WDL Edition developed by KBase. ", + "laborHours": 1702.4, + "languages": [], + "name": "jgi_mg_assembly_wdl", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/jgi_mg_assembly_wdl", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/jgoodall_mercury.json b/agency-indexes/DoE/jgoodall_mercury.json new file mode 100644 index 00000000..f76326ab --- /dev/null +++ b/agency-indexes/DoE/jgoodall_mercury.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jgoodall@ornl.gov" + }, + "date": { + "created": "2021-11-17", + "metadataLastUpdated": "2021-11-17" + }, + "description": "Capture packet data from a computer's network interface in a scalable manner and making it available to search and filter across the most commonly used fields", + "laborHours": 0.0, + "languages": [ + "Go" + ], + "name": "jgoodall/mercury", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jgoodall/mercury", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/jialiu232_MetaFunPrimer_paper_info.json b/agency-indexes/DoE/jialiu232_MetaFunPrimer_paper_info.json new file mode 100644 index 00000000..a8d60dd5 --- /dev/null +++ b/agency-indexes/DoE/jialiu232_MetaFunPrimer_paper_info.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-05", + "metadataLastUpdated": "2024-11-05" + }, + "description": "Genes belonging to the same functional group may include numerous and variable gene sequences, making characterizing and quantifying difficult. Therefore, high-throughput design tools are needed to simultaneously create primers for improved quantification of target genes. We developed MetaFunPrimer, a bioinformatic pipeline, to design primers for numerous genes of interest. This tool also enables gene target prioritization based on ranking the presence of genes in user-defined references, such as environment-specific metagenomes. Given inputs of protein and nucleotide sequences for gene targets of interest and an accompanying set of reference metagenomes or genomes, MetaFunPrimer generates primers for ranked genes of interest. To demonstrate the usage and benefits of MetaFunPrimer, a total of 78 primer pairs were designed to target observed ammonia monooxygenase subunit A (amoA) genes of ammonia-oxidizing bacteria (AOB) in 1,550 publicly available soil metagenomes. We demonstrate computationally that these amoA-AOB primers can cover 94% of the amoA-AOB genes observed in the 1,550 soil metagenomes compared with a 49% estimated coverage by previously published primers. Finally, we verified the utility of these primer sets in incubation experiments that used long-term nitrogen fertilized or unfertilized soils. High-throughput quantitative PCR (qPCR) results and statistical analyses showed significant differences in relative quantification patterns between the two soils, and subsequent absolute quantifications also confirmed that target genes enumerated by six selected primer pairs were significantly more abundant in the nitrogen-fertilized soils. This new tool gives microbial ecologists a new approach to assess functional gene abundance and related microbial community dynamics quickly and affordably.", + "laborHours": 136.8, + "languages": [], + "name": "jialiu232/MetaFunPrimer_paper_info", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jialiu232/MetaFunPrimer_paper_info", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/jupyterhub-announcement_v0.8.json b/agency-indexes/DoE/jupyterhub-announcement_v0.8.json new file mode 100644 index 00000000..c5949d80 --- /dev/null +++ b/agency-indexes/DoE/jupyterhub-announcement_v0.8.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-17", + "metadataLastUpdated": "2024-07-17" + }, + "description": "This is an announcement service for JupyterHub that JupyterHub admins can manage through a JupyterHub-styled UI. JupyterHub administrators can use it to communicate with their hub's users about status, upcoming outages, or share news. It allows admins to post a current announcement, and show previous announcements in reverse chronological order. It provides a REST API hook that admins can use to post the latest announcement on JupyterHub itself (with custom templates).", + "laborHours": 440.8, + "languages": [], + "name": "jupyterhub-announcement v0.8", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rcthomas/jupyterhub-announcement", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/jupyterlab-tutorial-extension.json b/agency-indexes/DoE/jupyterlab-tutorial-extension.json new file mode 100644 index 00000000..5eedeb09 --- /dev/null +++ b/agency-indexes/DoE/jupyterlab-tutorial-extension.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-28", + "metadataLastUpdated": "2020-05-28" + }, + "description": "An extension that allows you to incorporate interactive tutorials within jupyterlab.", + "laborHours": 60.8, + "languages": [], + "name": "jupyterlab-tutorial-extension", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/jupyterlab-tutorial-extension", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/jupyterlab-tutorial.json b/agency-indexes/DoE/jupyterlab-tutorial.json new file mode 100644 index 00000000..2fff2af5 --- /dev/null +++ b/agency-indexes/DoE/jupyterlab-tutorial.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-28", + "metadataLastUpdated": "2020-05-28" + }, + "description": "A package which provides a tutorial manager for incorporating interactive tutorials within JupyterLab. Front-end components provided by React Joyride: https://github.com/gilbarbara/react-joyride", + "laborHours": 319.2, + "languages": [], + "name": "jupyterlab-tutorial", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/jupyterlab-tutorial", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/kaleidoscope.json b/agency-indexes/DoE/kaleidoscope.json new file mode 100644 index 00000000..bb81cc11 --- /dev/null +++ b/agency-indexes/DoE/kaleidoscope.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2023-08-10" + }, + "description": "kaleidoscope is an R package developed to visualize PLEXOS scenarios as packaged by the rplexos R package. The package provides three types of visualizations intended to be used as coordinated views: a geographic diagram, a chord diagram, and dispatch charts. The geographic diagram provides a qualitative view of the study domain representing individual generator output and interregional transmission flows. The chord diagrams provide a more quantitative view of the net interchange between each of the regions. 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The main component of this repository is the workspace browser app that is contained in the ui-common repository. 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We use Kokkos because it provides abstractions for both parallel execution of code and data management, which can be used to support portable implementation across different accelerator technologies. Kokkos can support OpenMP/OpenMPTarget, oneAPI, Pthreads, and CUDA as backend programming models.", + "laborHours": 0.0, + "languages": [], + "name": "kokkosSZ (kSZ) A Portable Cellerator Implementation of SZ using Kokkos Programming Model", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/szcompressor/kokkosSZ", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/kokkos_Kernels.json b/agency-indexes/DoE/kokkos_Kernels.json new file mode 100644 index 00000000..a800e017 --- /dev/null +++ b/agency-indexes/DoE/kokkos_Kernels.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "This suite contains a number of kernel operations, called Parallel Research Kernels, plus a simple build system intended for a Linux-compatible environment. 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A script to set the process mask, OMP environment variables and CUDA environment variables to sane values if possible. Uses hwloc and nvidia-smi if available. Will preserve the current process binding, so it is safe to use with a queuing system or mpiexec.", + "laborHours": 228.0, + "languages": [], + "name": "kokkos/hpcbind", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kokkos/hpcbind", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/kokkos_mdarray.json b/agency-indexes/DoE/kokkos_mdarray.json new file mode 100644 index 00000000..511fdf4c --- /dev/null +++ b/agency-indexes/DoE/kokkos_mdarray.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-14", + "metadataLastUpdated": "2020-05-14" + }, + "description": "This is the repository for kokkos/mdarray developed by the Exascale Computing Project (ECP). 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The workflow of training the models for labquake future predictions and the multiple GPU\u2019s rapid model hyperparameter optimization as described in the journal article, are demonstrated in accompanying python script files and Jupyter notebooks.", + "laborHours": 0.0, + "languages": [], + "name": "labquake_future_prediction", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cjohnson-LANL/labquake_future_prediction", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/labrat.json b/agency-indexes/DoE/labrat.json new file mode 100644 index 00000000..da91908c --- /dev/null +++ b/agency-indexes/DoE/labrat.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "christopher.kowalczyk@inl.gov" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2023-03-15" + }, + "description": "Test repository used for CIVET demonstration purposes.", + "laborHours": 121.6, + "languages": [], + "name": "labrat", + "organization": "Idaho National Laboratory (INL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/idaholab/labrat", + "status": "Production", + "tags": [ + "DOE CODE", + "Idaho National Laboratory (INL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lacquer.json b/agency-indexes/DoE/lacquer.json new file mode 100644 index 00000000..3b8b14fb --- /dev/null +++ b/agency-indexes/DoE/lacquer.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "SQL Parser derived from Presto, written in Python with the PLY framework", + "laborHours": 1596.0, + "name": "lacquer", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/lacquer", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lalibe_v1.0.json b/agency-indexes/DoE/lalibe_v1.0.json new file mode 100644 index 00000000..82a5412e --- /dev/null +++ b/agency-indexes/DoE/lalibe_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-12", + "metadataLastUpdated": "2019-09-23" + }, + "description": "This is top-level lattice QCD code developed by employees at LBNL and LLNL. It currently compiles on top of the USQCD Chroma software stack. This code contains high-performance routines that are used in our research, and we intend to release this code publicly to ensure reproducibility and to meet our obligations for complying with the DOE Digital Data rules.", + "laborHours": 10822.4, + "languages": [], + "name": "lalibe v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/callat-qcd/lalibe", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lanl_ews.json b/agency-indexes/DoE/lanl_ews.json new file mode 100644 index 00000000..18fe46c0 --- /dev/null +++ b/agency-indexes/DoE/lanl_ews.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-10-04", + "metadataLastUpdated": "2024-10-04" + }, + "description": "EWSMod-2D: A Fortran Code for 2D Elastic-Wave Sensitivity Modeling", + "laborHours": 547.2, + "languages": [], + "name": "lanl/ews", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/ews", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lanl_jaybenne.json b/agency-indexes/DoE/lanl_jaybenne.json new file mode 100644 index 00000000..03c6b66d --- /dev/null +++ b/agency-indexes/DoE/lanl_jaybenne.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-12-13", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Monte Carlo thermal radiation transport code", + "laborHours": 1687.2, + "languages": [], + "name": "lanl/jaybenne", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/jaybenne", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lanl_nubhlight.json b/agency-indexes/DoE/lanl_nubhlight.json new file mode 100644 index 00000000..51b91535 --- /dev/null +++ b/agency-indexes/DoE/lanl_nubhlight.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2020-03-17", + "metadataLastUpdated": "2020-03-17" + }, + "description": "nubhlight is a code for simulating disks of materials around black holes formed after the in-spiral and merger of two-black holes. It is based on the open-source code bhlight. nubhlight models all relevant physics required to solve the post-merger disk problem. This includes: general relativity in a static spacetime, neutrino and weak physics, relativistic magnetohydrodynamics, and the ability to use open-sourced tabulated equations of state provided by stellarcollapse.org.\n", + "laborHours": 27344.8, + "languages": [], + "name": "lanl/nubhlight", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/nubhlight", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lasy_v0.1.json b/agency-indexes/DoE/lasy_v0.1.json new file mode 100644 index 00000000..8a6f4f0b --- /dev/null +++ b/agency-indexes/DoE/lasy_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-16", + "metadataLastUpdated": "2024-07-16" + }, + "description": "Lasy is a Python library that facilitates numerical simulations of the interaction of complex laser pulses with plasmas.\n\nMore specifically, lasy offers many ways to define complex laser pulses (e.g. from commonly-known analytical formulas, from experimental measurements, etc.) and then computes and saves the corresponding laser field in a standardized file. This file can then be read by external plasma simulation codes, that will then simulate the interaction between the complex laser pulse and a plasma.\n\nLasy is useful for instance for numerical simulations of plasma-based particle accelerators, plasma-based laser amplification, etc. Lasy avoids having to duplicate the code that defines complex laser pulses in each plasma simulation codes, and instead provides a trusted, centralized implementation.", + "laborHours": 1763.2, + "languages": [], + "name": "lasy v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LASY-org/lasy", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lats.json b/agency-indexes/DoE/lats.json new file mode 100644 index 00000000..bc39d946 --- /dev/null +++ b/agency-indexes/DoE/lats.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "This is the repository for legacy lats library code developed at Lawrence Livermore National Laboratory (LLNL). ", + "laborHours": 18437.6, + "languages": [], + "name": "lats", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/lats", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lattice_light_sheet_microscope_dataset_visualization_and_analysis.json b/agency-indexes/DoE/lattice_light_sheet_microscope_dataset_visualization_and_analysis.json new file mode 100644 index 00000000..b715ea50 --- /dev/null +++ b/agency-indexes/DoE/lattice_light_sheet_microscope_dataset_visualization_and_analysis.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-04-27", + "metadataLastUpdated": "2022-05-09" + }, + "description": "This is a collection of tools for the visualization and analysis of lattice light sheet microscope datasets.", + "laborHours": 0.0, + "languages": [], + "name": "lattice light sheet microscope dataset visualization and analysis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xiyuyi-at-LLNL/llsmvis", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/layerstack.json b/agency-indexes/DoE/layerstack.json new file mode 100644 index 00000000..c77f4433 --- /dev/null +++ b/agency-indexes/DoE/layerstack.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-05-23", + "metadataLastUpdated": "2018-05-23" + }, + "description": "Lightweight Python package for assembling, sharing, and running workflows, especially those associated with modifying, running, and analyzing simulation models.", + "laborHours": 699.2, + "languages": [], + "name": "layerstack", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Smart-DS/layerstack", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lc2-hdf5-110.json b/agency-indexes/DoE/lc2-hdf5-110.json new file mode 100644 index 00000000..129addfe --- /dev/null +++ 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It includes utilities such as input parsing, commonly used mathematical routines, scientific units, etc.", + "laborHours": 18012.0, + "name": "libristra", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/laristra/libristra", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/libyogrt.json b/agency-indexes/DoE/libyogrt.json new file mode 100644 index 00000000..7c7ac319 --- /dev/null +++ b/agency-indexes/DoE/libyogrt.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "Your One Get Remaining Time library; This library provides functions to query a resource manager for the time remaining in a job.", + "laborHours": 805.6, + "languages": [], + "name": "libyogrt", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/libyogrt", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lightsource2-recipes.json b/agency-indexes/DoE/lightsource2-recipes.json new file mode 100644 index 00000000..05298d66 --- /dev/null +++ b/agency-indexes/DoE/lightsource2-recipes.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-01", + "metadataLastUpdated": "2019-07-01" + }, + "description": "Recipes to build the nsls2 stack.", + "laborHours": 9424.0, + "languages": [], + "name": "lightsource2-recipes", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/lightsource2-recipes", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/linux-kstat.json b/agency-indexes/DoE/linux-kstat.json new file mode 100644 index 00000000..6b7bc8c3 --- /dev/null +++ b/agency-indexes/DoE/linux-kstat.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-31", + "metadataLastUpdated": "2018-07-31" + }, + "description": "This is an implementation of the Sun::Solaris::Kstat Perl module for Linux ZFS. It should behave identically to the Solaris version.", + "laborHours": 15.2, + "languages": [], + "name": "linux-kstat", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zfsonlinux/linux-kstat", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/llvm_archer.json b/agency-indexes/DoE/llvm_archer.json new file mode 100644 index 00000000..19a1943a --- /dev/null +++ b/agency-indexes/DoE/llvm_archer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Automatic installation script for Clang/LLVM with Archer support.", + "laborHours": 410.4, + "languages": [], + "name": "llvm_archer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PRUNERS/llvm_archer", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lume-base.json b/agency-indexes/DoE/lume-base.json new file mode 100644 index 00000000..a8b8fcce --- /dev/null +++ b/agency-indexes/DoE/lume-base.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-06", + "metadataLastUpdated": "2022-07-06" + }, + "description": "Base classes and architecture for LUME Python projects.", + "laborHours": 0.0, + "languages": [], + "name": "lume-base", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/lume-base", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lume-epics.json b/agency-indexes/DoE/lume-epics.json new file mode 100644 index 00000000..cb007c65 --- /dev/null +++ b/agency-indexes/DoE/lume-epics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-06-16", + "metadataLastUpdated": "2022-06-16" + }, + "description": "Lume-epics is a dedicated API for serving LUME model variables with EPICS.", + "laborHours": 0.0, + "languages": [], + "name": "lume-epics", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/lume-epics/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/lume-epics", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lume-genesis.json b/agency-indexes/DoE/lume-genesis.json new file mode 100644 index 00000000..949f63ff --- /dev/null +++ b/agency-indexes/DoE/lume-genesis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-06", + "metadataLastUpdated": "2022-07-06" + }, + "description": "Genesis tools for use in LUME.", + "laborHours": 0.0, + "languages": [], + "name": "lume-genesis", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/lume-genesis", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lustre-tools-llnl.json b/agency-indexes/DoE/lustre-tools-llnl.json new file mode 100644 index 00000000..6b254536 --- /dev/null +++ b/agency-indexes/DoE/lustre-tools-llnl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Some lustre-related scripts and utilities in use at LLNL.\n", + "laborHours": 1033.6, + "languages": [], + "name": "lustre-tools-llnl", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lustre-tools-llnl", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lustre.json b/agency-indexes/DoE/lustre.json new file mode 100644 index 00000000..f79a6e71 --- /dev/null +++ b/agency-indexes/DoE/lustre.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "This repository contains yet another branch of lustre. \n", + "laborHours": 374254.4, + "languages": [], + "name": "lustre", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hpc/lustre", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lustre_fssync.json b/agency-indexes/DoE/lustre_fssync.json new file mode 100644 index 00000000..c29e8c94 --- /dev/null +++ b/agency-indexes/DoE/lustre_fssync.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-06-23", + "metadataLastUpdated": "2023-06-30" + }, + "description": "lustre_fssync is a tool used to sync an entire Lustre file system from one cluster to another. It uses Lustre user quotas, parallel I/O utilities and the SLURM resource manager to balance and synchronize all contents between systems.", + "laborHours": 1033.6, + "languages": [], + "name": "lustre_fssync", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/lustre-tools-llnl", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/lvPortDriver_1.X.json b/agency-indexes/DoE/lvPortDriver_1.X.json new file mode 100644 index 00000000..b788995c --- /dev/null +++ b/agency-indexes/DoE/lvPortDriver_1.X.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" + }, + "description": "lvPortDriver and the lvPortDriver virtual library are functions that enable LabVIEW code to run an EPICS (Experimental Physics and\nIndustrial Control System) IOC (Input/Output Controller), and communicate with it.\nThe EPICS records interface just as they would with any other asynPortDriver device.\nlvPortDriver is an asynPortDriver class (asynPortDriver is written by Mark Rivers, University of Chicago) that stores parameters in the parameter library (inherits from the base class). Arrays functions have been overridden to store data in LabVIEW's (LabVIEW is developed by National Instruments) native format.\nC wrappers permit LabVIEW to call the C++ code necessary to read and write parameters, and to be notified of changes in parameters by asyn. This notification is achieved though a user event that provides LabVIEW with the new value and status.\nA LabVIEW virtual library includes VIs that call these wrapper functions. The LabVIEW code is responsible for initializing the driver, and creating all the parameters that will be used. Parameter names are stored as variant properties, so their indicies can be looked-up via an O(log(N)) mechanism.\nThe example code included consists of a queue-driven state machine that does a simulated diagnostic measurement (does a specified number of waits for a specified time, and records the actual time between steps). A caQtDM screen is used to control the example measurement and plot the results by interfacing via an EPICS IOC with the included database.", + "laborHours": 0.0, + "languages": [], + "name": "lvPortDriver 1.X", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/lvPortDriver", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/m2p__Monomers_to_Polymers_.json b/agency-indexes/DoE/m2p__Monomers_to_Polymers_.json new file mode 100644 index 00000000..1d6c6ebe --- /dev/null +++ b/agency-indexes/DoE/m2p__Monomers_to_Polymers_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-09-22", + "metadataLastUpdated": "2022-08-31" + }, + "description": "The software is Python-based code that takes monomers, represented as SMILES, and \"reacts\" them together to form long polymer chains, represented as SMILES, based on known polymer chemistries. The software is used in a machine-learning pipeline where a database and machine-learning approaches are used to predict polymer properties base on molecular structure. This software is necessary to represent the polymer chain, instead of simple repeat units, as the software statistically represents different molecular architectures that occur during reactions (e.g. head-to-head, head-to-tail, and tail-to-tail). It is capable of building polymer chains with five different chemistries: vinyl/olefin, polyamide, polycarbonate, polyester, and polyimides. The user is able to specify different monomer pairings and degree of polymerization for different polymer chains.", + "laborHours": 1216.0, + "languages": [ + "Python", + "Python" + ], + "name": "m2p (Monomers to Polymers)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/m2p", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/m5nr.json b/agency-indexes/DoE/m5nr.json new file mode 100644 index 00000000..b46a9523 --- /dev/null +++ b/agency-indexes/DoE/m5nr.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "The m5nr is a MD5 based non-redundant sequence database that includes both protein and rRNA sequences. The m5nr allows rapid lookup of annotations from different public sources.", + "laborHours": 486.4, + "languages": [], + "name": "m5nr", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/m5nr", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/maestro.json b/agency-indexes/DoE/maestro.json new file mode 100644 index 00000000..e2c7d237 --- /dev/null +++ b/agency-indexes/DoE/maestro.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-09-25", + "metadataLastUpdated": "2022-09-27" + }, + "description": "M\u00c6STRO stands for Multi-fidelity Adaptive Ensemble Stochastic Trust Region Optimization and it is a plug n play derivate fee stochastic optimization solver. The problem being considered in M\u00c6STRO involves fitting Monte Carlo simulations that describe complex phenomena to experiments. This is done by finding parameters of the resource intensive and noisy simulation that yield the least squares objective function value to the noisy experimental data. This problem is solved using a stochastic trust-region optimization algorithm where in each iteration, a local approximation of the simulation signal and of the simulation noise is constructed over data, which is obtained by running the simulation at strategically placed design points within the trust-region around the current iterate. Then the simulation components of the objective are replaced by their approximations and this analytical and closed-form optimization problem is solved to find the next iterate within the trust-region. Then the trust region is moved and the iterations continue until a satisfactory convergence criteria is met.", + "laborHours": 0.0, + "languages": [], + "name": "maestro", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/HEPonHPC/maestro", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/magos.json b/agency-indexes/DoE/magos.json new file mode 100644 index 00000000..11273a52 --- /dev/null +++ b/agency-indexes/DoE/magos.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-10-26", + "metadataLastUpdated": "2021-10-26" + }, + "description": "Solves AC optimal power flow problem for formulation in ARPA-E Grid Optimization Competition Challenge 2", + "laborHours": 0.0, + "languages": [], + "name": "magos", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/SCR-model", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/magpie.json b/agency-indexes/DoE/magpie.json new file mode 100644 index 00000000..9e2d8976 --- /dev/null +++ b/agency-indexes/DoE/magpie.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2020-02-05" + }, + "description": "Magpie contains a number of scripts for running Big Data software in HPC environments, including Hadoop and Spark. There is support for Lustre, Slurm, Moab, Torque. and LSF.\n", + "laborHours": 52607.2, + "languages": [], + "name": "Magpie", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/magpie", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/maranasgroup_KETCHUP.json b/agency-indexes/DoE/maranasgroup_KETCHUP.json new file mode 100644 index 00000000..e9602256 --- /dev/null +++ b/agency-indexes/DoE/maranasgroup_KETCHUP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "Repository for Kinetic Estimation Tool Capturing Heterogeneous Datasets Using Pyomo (KETCHUP), a flexible parameter estimation tool that leverages a primal-dual interior-point algorithm to solve a nonlinear programming (NLP) problem that identifies a set of parameters capable of recapitulating the steady-state fluxes and concentrations in wild-type and perturbed metabolic networks.", + "laborHours": 76577.6, + "languages": [], + "name": "maranasgroup/KETCHUP", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/KETCHUP", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/maranasgroup_k-sacce306.json b/agency-indexes/DoE/maranasgroup_k-sacce306.json new file mode 100644 index 00000000..ea63b6ee --- /dev/null +++ b/agency-indexes/DoE/maranasgroup_k-sacce306.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.", + "laborHours": 1246.4, + "languages": [], + "name": "maranasgroup/k-sacce306", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/k-sacce306", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/maranasgroup_scRBA.json b/agency-indexes/DoE/maranasgroup_scRBA.json new file mode 100644 index 00000000..313e0682 --- /dev/null +++ b/agency-indexes/DoE/maranasgroup_scRBA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-08", + "metadataLastUpdated": "2024-11-08" + }, + "description": "Saccharomyces cerevisiae is an important model organism and a workhorse in bioproduction. Here, we reconstructed a compact and tractable genome-scale resource balance analysis (RBA) model (i.e., named scRBA) to analyze metabolic fluxes and proteome allocation in a computationally efficient manner. Resource capacity models such as scRBA provide the quantitative means to identify bottlenecks in biosynthetic pathways due to enzyme, compartment size, and/or ribosome availability limitations. ATP maintenance rate and in vivo apparent turnover numbers (kapp) were regressed from metabolic flux and protein concentration data to capture observed physiological growth yield and proteome efficiency and allocation, respectively. Estimated parameter values were found to vary with oxygen and nutrient availability. Overall, this work (i) provides condition-specific model parameters to recapitulate phenotypes corresponding to different extracellular environments, (ii) alludes to the enhancing effect of substrate channeling and post-translational activation on in vivo enzyme efficiency in glycolysis and electron transport chain, and (iii) reveals that the Crabtree effect is underpinned by specific limitations in mitochondrial proteome capacity and secondarily ribosome availability rather than overall proteome capacity.", + "laborHours": 1134406.4, + "languages": [], + "name": "maranasgroup/scRBA", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/scRBA", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/maranasgroup_uncFBA.json b/agency-indexes/DoE/maranasgroup_uncFBA.json new file mode 100644 index 00000000..efdf0b8b --- /dev/null +++ b/agency-indexes/DoE/maranasgroup_uncFBA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-05", + "metadataLastUpdated": "2024-11-05" + }, + "description": "In the repository are example scripts that perform uncertainty injection and propagation to flux balance analysis with outputs for a small sample size (for demonstration purpose only). For proper analysis, user should download the scripts and run for a large sample size (e.g., 10,000 samples).\n\nIf you use the scripts, please cite the following Metabolic Engineering article: \u201cQuantifying the propagation of parametric uncertainty on flux balance analysis\u201d (https://doi.org/10.1016/j.ymben.2021.10.012)\n\nThere are two subdirectories:\n\n/uncFBA/uncBiom: injection of normally distributed noise to biomass precursor coeffcients and ATP maintenance (growth-associated ATP maintenance (GAM) and non-growth associated ATP maintenance (NGAM))\n/uncFBA/uncRHS: departure from steady-state by adding noise drawn from normal distribution to the RHS terms of mass balance constraints", + "laborHours": 108452.0, + "languages": [], + "name": "maranasgroup/uncFBA", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/uncFBA", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/maranasgroup_yeastsMFA.json b/agency-indexes/DoE/maranasgroup_yeastsMFA.json new file mode 100644 index 00000000..8a9c498e --- /dev/null +++ b/agency-indexes/DoE/maranasgroup_yeastsMFA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.", + "laborHours": 24441.6, + "languages": [], + "name": "maranasgroup/yeastsMFA", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maranasgroup/yeastsMFA", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/maslov-group_FUN-PROSE.json b/agency-indexes/DoE/maslov-group_FUN-PROSE.json new file mode 100644 index 00000000..9e862659 --- /dev/null +++ b/agency-indexes/DoE/maslov-group_FUN-PROSE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE\u2014a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.", + "laborHours": 592.8, + "languages": [], + "name": "maslov-group/FUN-PROSE", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/maslov-group/FUN-PROSE", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/matR.json b/agency-indexes/DoE/matR.json new file mode 100644 index 00000000..e2cf1600 --- /dev/null +++ b/agency-indexes/DoE/matR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "This is the repository for \"matR\" developed by KBase.", + "laborHours": 15.2, + "languages": [], + "name": "matR", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/matR", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/materialsCloudCompute.json b/agency-indexes/DoE/materialsCloudCompute.json new file mode 100644 index 00000000..be094f9a --- /dev/null +++ b/agency-indexes/DoE/materialsCloudCompute.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-19", + "metadataLastUpdated": "2021-11-19" + }, + "description": "materialsCloudCompute (mCC) is a software package for running easily parallelizable materials science theoretical computations on Amazon Web Services (AWS) infrastructure. mCC provides tools to partition out computational problem into smaller subproblems which can be run in parallel, and ensure that each of those subproblems completes successfully. It utilizes the following AWS services: EC2, S3, and RDS. It operates by launch a managing EC2 instance, which can launch worker instances that perform the calculations. The Managing instance tracks the subproblems and ensures that the Worker instances continue to operation, killing and relaunching them if they fail.", + "laborHours": 0.0, + "languages": [], + "name": "materialsCloudCompute", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/materialsCloudCompute", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/maximize_phylogenetic_diversity_taxa_selection_script__maxPD.pl__v1.json b/agency-indexes/DoE/maximize_phylogenetic_diversity_taxa_selection_script__maxPD.pl__v1.json new file mode 100644 index 00000000..947f17ab --- /dev/null +++ b/agency-indexes/DoE/maximize_phylogenetic_diversity_taxa_selection_script__maxPD.pl__v1.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "john.rinck@lbl.gov" + }, + "date": { + "created": "2024-08-30", + "metadataLastUpdated": "2024-08-30" + }, + "description": "The software contains only one perl script that take advantage of a module published 8 years ago from the public domain (https://github.com/dongyingwu/TreeOTU) . It take a phylogenetic tree, and select a give number (user defined) of taxa that represent the maximize phylogenetic diversity from the tree.", + "laborHours": 577.6, + "languages": [], + "name": "maximize phylogenetic diversity taxa selection script (maxPD.pl) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/maxpd/src/master", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/mazeau_project-euler.json b/agency-indexes/DoE/mazeau_project-euler.json new file mode 100644 index 00000000..038bef0b --- /dev/null +++ b/agency-indexes/DoE/mazeau_project-euler.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "mazeauej@ornl.gov" + }, + "date": { + "created": "2024-01-11", + "metadataLastUpdated": "2024-01-11" + }, + "description": "C++ Project Euler files", + "laborHours": 0.0, + "languages": [], + "name": "mazeau/project-euler", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mazeau/project-euler", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/md_viscoplastic_v._1.0.json b/agency-indexes/DoE/md_viscoplastic_v._1.0.json new file mode 100644 index 00000000..db9badbf --- /dev/null +++ b/agency-indexes/DoE/md_viscoplastic_v._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-26", + "metadataLastUpdated": "2018-12-04" + }, + "description": "The md_viscoplastic software is a numerical implementation of the Munson-Dawson material model for rock salt. One inputs a deformation increment, a temperature increment, and the current stress state to md_viscoplastic. It returns the new stress state by numerically integrating ordinary differential equations. ", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "md_viscoplastic v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "v. 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mdtest.json b/agency-indexes/DoE/mdtest.json new file mode 100644 index 00000000..d160f942 --- /dev/null +++ b/agency-indexes/DoE/mdtest.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Used for testing the metadata performance of a file system.\n", + "laborHours": 1565.6, + "languages": [], + "name": "mdtest", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mdtest", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/memP.json b/agency-indexes/DoE/memP.json new file mode 100644 index 00000000..b48ecde7 --- /dev/null +++ b/agency-indexes/DoE/memP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-10-27", + "metadataLastUpdated": "2020-10-29" + }, + "description": "The lightweight heap profiling tool memP Version 1 provides a library that can be used with MPI applications that make use of heap memory allocations to provide profile data based on the per-task high-water-mark of heap allocation. The memP output is generated as a text report that can present summary information or specific detail of the allocation call site data for each task The memP library source code is based on teh mpiP MPI profiling library (http://mpip.sourceforge.net), but is substantially different in functionality and organization.", + "homepageURL": "https://sourceforge.net/projects/memp", + "laborHours": 9226.4, + "languages": [], + "name": "memP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/memp", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/mesoflow_[SWR-22-56].json b/agency-indexes/DoE/mesoflow_[SWR-22-56].json new file mode 100644 index 00000000..d5495300 --- /dev/null +++ b/agency-indexes/DoE/mesoflow_[SWR-22-56].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-05-25", + "metadataLastUpdated": "2023-04-24" + }, + "description": "Mesoflow is a continuum scale simulation tool developed specifically for modeling transport and chemistry at the mesoscale. Our solver utilizes Cartesian block-structured adaptive mesh refinement to resolve complex surface morphologies (of catalysts/biomass particles among others) directly obtained from X-ray tomography data. An immersed boundary based formulation enables rapid representation of complex geometries prevalent in most mesoporous interfaces. The solver is developed on top of open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Our flexible software framework enables integration of complex chemical mechanisms at heterogenous interfaces and time-split algorithms for circumventing highly disparate reaction and flow time-scales. Our current studies indicate a ten-fold performance gain by using graphics-processing-units (GPU) compared to a single processor for representative problem sizes (2 million cell mesh).", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "mesoflow [SWR-22-56]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/mesoflow", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/metabolite_atlas.json b/agency-indexes/DoE/metabolite_atlas.json new file mode 100644 index 00000000..697e0b41 --- /dev/null +++ b/agency-indexes/DoE/metabolite_atlas.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "Metabolic ATLAS repository developed by KBase.", + "laborHours": 395.2, + "languages": [], + "name": "metabolite_atlas", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/metabolite_atlas", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/metadataservice.json b/agency-indexes/DoE/metadataservice.json new file mode 100644 index 00000000..b6f88547 --- /dev/null +++ b/agency-indexes/DoE/metadataservice.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "metadatastore web service implementation. Uses metadatastore in the backend Python 3.4, 3.5. Requires tornado, metadatastore, pymongo, ujson, and requests.\n\n", + "laborHours": 592.8, + "languages": [], + "name": "metadataservice", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/metadataservice", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mfem_data.json b/agency-indexes/DoE/mfem_data.json new file mode 100644 index 00000000..e50ed9b1 --- /dev/null +++ b/agency-indexes/DoE/mfem_data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Additional (large) datafiles for MFEM.", + "laborHours": 0.0, + "languages": [], + "name": "mfem/data", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfem/data", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mfem_doxygen.json b/agency-indexes/DoE/mfem_doxygen.json new file mode 100644 index 00000000..f74523af --- /dev/null +++ b/agency-indexes/DoE/mfem_doxygen.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "This repository contains Doxygen Documentation for MFEM (a lightweight, general, scalable C++ library for finite element methods) developed at Lawrence Livermore National Laboratory.", + "laborHours": 1291832.8, + "languages": [], + "name": "mfem/doxygen", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfem/doxygen", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mfem_releases.json b/agency-indexes/DoE/mfem_releases.json new file mode 100644 index 00000000..d9ea72b3 --- /dev/null +++ b/agency-indexes/DoE/mfem_releases.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "This repository contains release archives for MFEM, a lightweight, general, scalable C++ library for finite element methods, developed at Lawrence Livermore National Laboratory. \n", + "laborHours": 0.0, + "languages": [], + "name": "mfem/releases", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfem/releases", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mfem_web.json b/agency-indexes/DoE/mfem_web.json new file mode 100644 index 00000000..e41b3aed --- /dev/null +++ b/agency-indexes/DoE/mfem_web.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "This repo contains the MFEM website\u00a0MkDocs\u00a0sources.", + "laborHours": 5700.0, + "languages": [], + "name": "mfem/web", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfem/web", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mgrast_pipeline.json b/agency-indexes/DoE/mgrast_pipeline.json new file mode 100644 index 00000000..d4d7354c --- /dev/null +++ b/agency-indexes/DoE/mgrast_pipeline.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "The mgrast_pipeline repository provides KBase release engineering tools for the deployment of the MG-RAST pipeline. The MG-RAST pipeline repository is included as a submodule in the mgrast_pipeline repository and is maintained at http://github.com/MG-RAST/pipeline.", + "laborHours": 15.2, + "languages": [], + "name": "mgrast_pipeline", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/mgrast_pipeline", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mgsflib.json b/agency-indexes/DoE/mgsflib.json new file mode 100644 index 00000000..9c065c54 --- /dev/null +++ b/agency-indexes/DoE/mgsflib.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-05-17", + "metadataLastUpdated": "2024-05-17" + }, + "description": "Code for my PhD thesis that creates meshes using gmsh and code I wrote to create high-order hybrid meshes to use for testing a hybrid method between spectral element method and generalized finite differences. It also uses a tetrahedral mesh improvement method called \"stellar\" to improve mesh quality near a curved boundary.", + "laborHours": 1900.0, + "languages": [], + "name": "mgsflib", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Jacobj-LANL/mgsflib", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mie_scat.json b/agency-indexes/DoE/mie_scat.json new file mode 100644 index 00000000..22a12209 --- /dev/null +++ b/agency-indexes/DoE/mie_scat.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-07-29", + "metadataLastUpdated": "2022-07-29" + }, + "description": "This is a standalone Fortran code (mie_scat) that calculates the mie scattering cross sections, absorption cross sections, and efficiency coefficients of dust grains. It includes a separate file (miegrn) that functions as a wrapper function between PHOENIX (a proprietary radiative transfer code to model stellar atmospheres) and the mie scattering calculations. Miegrn works to determine the input parameters for mie_scat and then feeds the resultant data back into PHOENIX.", + "laborHours": 0.0, + "languages": [], + "name": "mie_scat", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/mie_scat", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mily.json b/agency-indexes/DoE/mily.json new file mode 100644 index 00000000..ace81061 --- /dev/null +++ b/agency-indexes/DoE/mily.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "A collection of Qt building blocks for scientific GUIs.", + "laborHours": 729.6, + "languages": [], + "name": "mily", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/mily", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/minervachem.json b/agency-indexes/DoE/minervachem.json new file mode 100644 index 00000000..3ef79cc6 --- /dev/null +++ b/agency-indexes/DoE/minervachem.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-04-19", + "metadataLastUpdated": "2024-04-19" + }, + "description": "Minervachem is a tool for cheminformatics and machine learning in chemistry. It includes both algorithms from existing literature and algorithms which we have developed. Its features center around two main themes: molecular representations and algorithms, both for molecular machine learning. It provides a scikit-learn transformer interface for molecular featurization and an estimator interface for machine learning algorithms. It also provides visualization tools for explaining machine learning predictions. We aim to continue developing this software to improve its performance and usability and expand its capabilities within the realm of molecular machine learning, cheminformatics, and visualization.", + "laborHours": 1398.4, + "languages": [], + "name": "minervachem", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/minervachem", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mini-portal.json b/agency-indexes/DoE/mini-portal.json new file mode 100644 index 00000000..ddd3c774 --- /dev/null +++ b/agency-indexes/DoE/mini-portal.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "This \"mini-portal\" is a demonstration of several of the packages used in the MyESnet Portal. In particular it shows an example of using: react-timeseries-charts, react-network-diagrams, and pond. This was built using create-react-app which is a great way to bootstrap a React project.", + "laborHours": 7341.6, + "languages": [], + "name": "mini-portal", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/mini-portal/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/mini-portal", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/miniAMR.json b/agency-indexes/DoE/miniAMR.json new file mode 100644 index 00000000..50a14e69 --- /dev/null +++ b/agency-indexes/DoE/miniAMR.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "miniAMR is a \"miniapp\" which will be added to the Mantevo project. It provides a platform to experiment with different aspects of Adaptive Mesh Refinement (AMR). The calculations are performed on random data and the refinement is driven by simple objects moving through the mesh, so no real problem is solved. By having a small code that runs quickly, we can use to study different aspects of AMR and easily port the code to new testbed machines", + "laborHours": 10989.6, + "languages": [ + "Makefile", + "C" + ], + "name": "miniAMR", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniAMR", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.9" +} \ No newline at end of file diff --git a/agency-indexes/DoE/miniGAN:_a_proxy_application_for_generative_adversarial_networks.json b/agency-indexes/DoE/miniGAN:_a_proxy_application_for_generative_adversarial_networks.json new file mode 100644 index 00000000..cc8d40ff --- /dev/null +++ b/agency-indexes/DoE/miniGAN:_a_proxy_application_for_generative_adversarial_networks.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2024-07-29" + }, + "description": "miniGAN is a python-based machine learning proxy application for generative adversarial networks, developed through the Exascale Computing Project's (ECP) ExaLearn project. It will be included in the main ECP proxy application and the machine learning proxy application suite. It is a proxy for ECP cosmological(CosmoFlow, ExaGAN) and wind energy(ExaWind) applications. miniGAN will be distributed to ECP hardware vendors as part of hardware codesign. miniGAN uses the Numpy/PyTorch/TensorFlow/Keras/Horovod frameworks and libraries. It also relies on the Kokkos and Kokkos-Kernels packages developed here at Sandia Labs. SAND2020-2038 M\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 516.8, + "languages": [ + "Shell", + "Python" + ], + "name": "miniGAN: a proxy application for generative adversarial networks", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniGAN", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/miniGhost_Mantevo_miniapp.json b/agency-indexes/DoE/miniGhost_Mantevo_miniapp.json new file mode 100644 index 00000000..be53a797 --- /dev/null +++ b/agency-indexes/DoE/miniGhost_Mantevo_miniapp.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MiniGhost is a miniapp in the Mantevo project. Using a finite difference method, it mimics the inter-process communication requirements commonly found in applications of this sort. Random values are inserts into the grid, and therefore no \"real problem\" is solved.", + "laborHours": 5016.0, + "name": "miniGhost Mantevo miniapp", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Mantevo/miniGhost", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/miniGraphics_v._1.0.json b/agency-indexes/DoE/miniGraphics_v._1.0.json new file mode 100644 index 00000000..78a1348d --- /dev/null +++ b/agency-indexes/DoE/miniGraphics_v._1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-11-07", + "metadataLastUpdated": "2018-11-07" + }, + "description": "The miniGraphics package provides a collection of reference implementations for parallel rendering. In particular, miniGraphics is focused on sort-last parallel rendering, which is the rendering algorithm of choice for HPC rendering. The miniGraphics package provides a collection of simple serial rendering systems and a collection of parallel image compositing methods, which can be combined to test the behavior of parallel rendering under different conditions.", + "laborHours": 42423.2, + "languages": [ + "C++" + ], + "name": "miniGraphics v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniGraphics", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/miniMD_v._1.0.json b/agency-indexes/DoE/miniMD_v._1.0.json new file mode 100644 index 00000000..7a1635a2 --- /dev/null +++ b/agency-indexes/DoE/miniMD_v._1.0.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Simple parallel MD code that serves as a microapplication in the Mantevo suite. Study of computer system design and implementation, benchmarking of new and existing computer systems.", + "laborHours": 11096.0, + "languages": [ + "C++", + "Shell", + "C", + "Makefile" + ], + "name": "miniMD v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniMD", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/miniMDock.json b/agency-indexes/DoE/miniMDock.json new file mode 100644 index 00000000..416733e9 --- /dev/null +++ b/agency-indexes/DoE/miniMDock.json @@ -0,0 +1,43 @@ +{ + "contact": { + "email": "thavappiragm@ornl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "A molecular docking mini-app, GPU-accelerated particle-grid based protein ligand docking programs that can be used for virtual drug discovery compound screens based on a molecular recognition model, that analysis a three-dimensional model of an interaction between a protein and a small molecule (ligand). The miniMDock is developed using multiple programming models/APIs and can be used to evaluate performance portability of molecular docking applications over different heterogeneous systems.", + "laborHours": 0.0, + "languages": [ + "C", + "C++", + "C", + "C++", + "Cuda", + "Hip" + ], + "name": "miniMDock", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + }, + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-PE/miniMDock", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/miniSMAC2D.json b/agency-indexes/DoE/miniSMAC2D.json new file mode 100644 index 00000000..082d5df8 --- /dev/null +++ b/agency-indexes/DoE/miniSMAC2D.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-23" + }, + "description": "In the drive to make exascale computing a reality, significant effort is being invested in efficiently implementing and improving current numerical algorithms on various vendors' newest testbeds acquired by DOE's Advanced Simulation and Computing program. Porting large-scale applications to these testbeds is prohibitive in labor and time. Instead, it is more advantageous to run small-scale programs that capture the essence of the large-scale application and that can be more easily modified, improved, and distributed to other collaborators focused on hardware/software co-design. These small-scale applications are called miniapps are are being developed under the aegis of the Mantevo project.", + "laborHours": 6490.4, + "languages": [ + "C", + "Fortran", + "Python" + ], + "name": "miniSMAC2D", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniSMAC", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/miniTri_Mantevo_miniapp_v._1.0.json b/agency-indexes/DoE/miniTri_Mantevo_miniapp_v._1.0.json new file mode 100644 index 00000000..4da4cc2d --- /dev/null +++ b/agency-indexes/DoE/miniTri_Mantevo_miniapp_v._1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-23" + }, + "description": "miniTri is a miniapplication developed as part of the Mantevo project. Given a graph, miniTri enumerates all triangles in this graph and computes a metric for each triangle based on the triangle edge and vertex degree. The output of miniTri is a summary of this metric. miniTri mimics the computational requirements of an important set of data science applications. Several approaches to this problem are included in the miniTri software.", + "laborHours": 5791.2, + "languages": [ + "C, C++", + "Makefile" + ], + "name": "miniTri Mantevo miniapp v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/sandialabs/miniTri?tab=License-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniTri", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/miniWeather.json b/agency-indexes/DoE/miniWeather.json new file mode 100644 index 00000000..e2e3b823 --- /dev/null +++ b/agency-indexes/DoE/miniWeather.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "The code \u201cminiWeather\u201d solves the 2-D Euler equations with a Finite-Volume method on a regular Cartesian grid with Runge-Kutta time stepping, 4th-order hypervisocisty, and 4th-order spatial accuracy. The code is primarily a parallel programming training mini application in Fortran, C, and C++ with MPI, OpenMP, OpenMP offload, OpenACC, and C++ portability approaches. It can also serve as a mini application for acceptance testing for new machines and compilers for both functionality and performance.", + "laborHours": 7828.0, + "languages": [ + "C++11, any C++11 compiler can be used" + ], + "name": "miniWeather", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mrnorman/miniWeather", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/miniXyce.json b/agency-indexes/DoE/miniXyce.json new file mode 100644 index 00000000..0ad6eae0 --- /dev/null +++ b/agency-indexes/DoE/miniXyce.json @@ -0,0 +1,40 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-25" + }, + "description": "miniXyce uses a modified nodal analysis to approximate the governing differential algebraic equations (DAEs) for electronic devices and their coupling via a network and Kirchoff's conservation laws. The resulting nonlinear problem is solved iteratively using a fully coupled Newton method,which in turn results in a linear system that is solved using an iterative method.", + "laborHours": 1748.0, + "languages": [ + "C++", + "Shell", + "C", + "Makefile", + "Perl", + "MATLAB", + "Python" + ], + "name": "miniXyce", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniXyce", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mini_kb.json b/agency-indexes/DoE/mini_kb.json new file mode 100644 index 00000000..f5a6af5e --- /dev/null +++ b/agency-indexes/DoE/mini_kb.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "Docker-compose configuration that brings up a mini-KBase. This includes configurations for all of the services to setup a minimal test environment.", + "laborHours": 790.4, + "languages": [], + "name": "mini_kb", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/mini_kb", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/minilosurface.json b/agency-indexes/DoE/minilosurface.json new file mode 100644 index 00000000..4a3de74b --- /dev/null +++ b/agency-indexes/DoE/minilosurface.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "awander@sandia.gov" + }, + "date": { + "created": "2018-08-24", + "metadataLastUpdated": "2024-07-19" + }, + "description": "The miniIsosurface package provides a collection of reference implementations for finding a representation for a contour of a scalar field in a volume. Contouring is a well-studied algorithm in scientific visualization and there are many algorithm variations to solve it. The miniIsosurface package provides a convenient collection of the most popular variations of the contour algorithm and some variations to run in different parallel environments.", + "laborHours": 12737.6, + "languages": [ + "C++", + "CMakefile", + "C", + "Makefile", + "Cuda" + ], + "name": "minilosurface", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/miniIsosurface", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/minimega.json b/agency-indexes/DoE/minimega.json new file mode 100644 index 00000000..9b6c395d --- /dev/null +++ b/agency-indexes/DoE/minimega.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Minimega is a simple emulytics platform for creating testbeds of networked devices. The platform consists of easily deployable tools to facilitate bringing up large networks of virtual machines including Windows, Linux, and Android. Minimega attempts to allow experiments to be brought up quickly with nearly no configuration. Minimega also includes tools for simple cluster management, as well as tools for creating Linux based virtual machine images.", + "laborHours": 399334.4, + "name": "minimega", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandia-minimega/minimega", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/minimega_v._3.0.json b/agency-indexes/DoE/minimega_v._3.0.json new file mode 100644 index 00000000..ae848c50 --- /dev/null +++ b/agency-indexes/DoE/minimega_v._3.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "minimega is an emulytics platform for creating testbeds of networked devices. The platoform consists of easily deployable tools to facilitate bringing up large networks of virtual machines including Windows, Linux, and Android. minimega allows experiments to be brought up quickly with almost no configuration. minimega also includes tools for simple cluster, management, as well as tools for creating Linux-based virtual machines. This release of minimega includes new emulated sensors for Android devices to improve the fidelity of testbeds that include mobile devices. Emulated sensors include GPS and", + "laborHours": 399334.4, + "name": "minimega v. 3.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandia-minimega/minimega", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mirror-SPECTER.json b/agency-indexes/DoE/mirror-SPECTER.json new file mode 100644 index 00000000..10f42b15 --- /dev/null +++ b/agency-indexes/DoE/mirror-SPECTER.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "passarellals@ornl.gov" + }, + "date": { + "created": "2023-02-06", + "metadataLastUpdated": "2023-02-06" + }, + "description": "This model uses an unsupervised sentence encoder proposed by Liu et al. (2021) to create better sentence representations for the SPECTER transformer model.", + "laborHours": 0.0, + "languages": [], + "name": "mirror-SPECTER", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://huggingface.co/Linseypass/mirror-SPECTER", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/mkite.json b/agency-indexes/DoE/mkite.json new file mode 100644 index 00000000..2b8a107d --- /dev/null +++ b/agency-indexes/DoE/mkite.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-05-02", + "metadataLastUpdated": "2023-05-02" + }, + "description": "mkite is a distributed computing platform for materials simulation. mkite is built with the server-client pattern, decoupling production databases from client runners. When used in combination with message brokers, mkite enables any available client to perform calculations without prior hardware specification on the server side. Furthermore, the software enables the creation of complex workflows with multiple inputs and branches, facilitating the exploration of combinatorial chemical spaces. The mkite suite provides recipes and tools to interact with package such as VASP, but is extensible to any other simulation package. Finally, mkite helps keeping the provenance of calculations in a SQL database. A complete description of the software is available at https://arxiv.org/abs/2301.08841.", + "laborHours": 0.0, + "languages": [], + "name": "mkite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mkite-group/mkite_db", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mochi-colza.json b/agency-indexes/DoE/mochi-colza.json new file mode 100644 index 00000000..4c2c1571 --- /dev/null +++ b/agency-indexes/DoE/mochi-colza.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "Mochi-based staging service for in situ analysis and visualization.", + "laborHours": 0.0, + "languages": [], + "name": "mochi-colza", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-colza/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-colza", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mochi-hpc_mochi-margo.json b/agency-indexes/DoE/mochi-hpc_mochi-margo.json new file mode 100644 index 00000000..841d3bfd --- /dev/null +++ b/agency-indexes/DoE/mochi-hpc_mochi-margo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "Margo provides Argobots-aware bindings to the Mercury RPC library. Margo combines Mercury and Argobots to simplify development of distributed services. Mercury operations are presented as conventional blocking operations, and RPC handlers are presented as sequential threads. This configuration enables high degree of concurrency while hiding the complexity associated with asynchronous communication progress and callback management.", + "laborHours": 0.0, + "languages": [], + "name": "mochi-hpc/mochi-margo", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-margo/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-margo", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mochi-quintain.json b/agency-indexes/DoE/mochi-quintain.json new file mode 100644 index 00000000..08ff1305 --- /dev/null +++ b/agency-indexes/DoE/mochi-quintain.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-27", + "metadataLastUpdated": "2022-01-27" + }, + "description": "mochi-quintain is a microservice (i.e., a Mochi provider) that responds to parameterized RPCs to generate synthetic concurrent server load.", + "laborHours": 0.0, + "languages": [], + "name": "mochi-quintain", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/mochi-quintain/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/mochi-quintain", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mock_kbase.json b/agency-indexes/DoE/mock_kbase.json new file mode 100644 index 00000000..ce3c447d --- /dev/null +++ b/agency-indexes/DoE/mock_kbase.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-03", + "metadataLastUpdated": "2020-09-03" + }, + "description": "A fully functional packaging of the KBase data platform and mock auth to facilitate unit testing and integration testing.", + "laborHours": 349.6, + "languages": [], + "name": "mock_kbase", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/mock_kbase", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/molecule-tda_v0.1.0.json b/agency-indexes/DoE/molecule-tda_v0.1.0.json new file mode 100644 index 00000000..ca3d0f6a --- /dev/null +++ b/agency-indexes/DoE/molecule-tda_v0.1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-04-25", + "metadataLastUpdated": "2021-06-15" + }, + "description": "A general framework to extract topological information (via topological data analysis) from some type of point cloud data, to be used in downstream machine learning tasks.", + "laborHours": 0.0, + "languages": [], + "name": "molecule-tda v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/a1k12/molecule-tda", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/morph.json b/agency-indexes/DoE/morph.json new file mode 100644 index 00000000..562e2cd8 --- /dev/null +++ b/agency-indexes/DoE/morph.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "Morph is a framework and domain-specific language (DSL) that helps parse and transform structured documents. It currently supports several file formats including XML, JSON, and CSV, and custom formats are usable as well.", + "laborHours": 0.0, + "languages": [ + "Scala 2.10x/. JVM 1.7+" + ], + "name": "morph", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stucco-archive/morph", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mpiGraph.json b/agency-indexes/DoE/mpiGraph.json new file mode 100644 index 00000000..89022680 --- /dev/null +++ b/agency-indexes/DoE/mpiGraph.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "MpiGraph consists of an MPI application called mpiGraph written in C to measure message bandwidth and an associated crunch_mpiGraph script written in Perl to process the application output into an HTMO report. The mpiGraph application is designed to inspect the health and scalability of a high-performance interconnect while under heavy load. This is useful to detect hardware and software problems in a system, such as slow nodes, links, switches, or contention in switch routing. It is also useful to characterize how interconnect performance changes with different settings or how one interconnect type compares to another.", + "homepageURL": "https://sourceforge.net/projects/mpigraph", + "laborHours": 0.0, + "name": "mpiGraph", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://sourceforge.net/projects/mpigraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/mpiP.json b/agency-indexes/DoE/mpiP.json new file mode 100644 index 00000000..cf8b291e --- /dev/null +++ b/agency-indexes/DoE/mpiP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "A light-weight MPI profiler.\u00a0http://llnl.github.io/mpiP\n", + "laborHours": 13558.4, + "languages": [], + "name": "mpiP", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mpiP", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mpileaks_-_an_MPI_opject_leak_debugging_library.json b/agency-indexes/DoE/mpileaks_-_an_MPI_opject_leak_debugging_library.json new file mode 100644 index 00000000..cadd1809 --- /dev/null +++ b/agency-indexes/DoE/mpileaks_-_an_MPI_opject_leak_debugging_library.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The mpileaks tool is to be used by MPI application developers to track and report leaked MPI objects, such as requests, groups, and datatypes. This debugging tool is useful as a quality assurance check for MPI applications, or it can be used to identify leaks fatal to long-running MPI applications. It provides an efficient method to report bugs that are otherwise fifficult to identify.", + "laborHours": 22450.4, + "name": "mpileaks - an MPI opject leak debugging library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/LLNL/mpileaks/blob/master/LICENSE.TXT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mpileaks", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/msdlive-cli-distro.json b/agency-indexes/DoE/msdlive-cli-distro.json new file mode 100644 index 00000000..84285f96 --- /dev/null +++ b/agency-indexes/DoE/msdlive-cli-distro.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-08-22", + "metadataLastUpdated": "2024-09-16" + }, + "description": "MSD-LIVE, the MultiSector Dynamics \u2013 Living, Intuitive, Value-adding, Environment, is a flexible and scalable data and code\nmanagement system combined with a distributed computational platform that will enable MSD researchers to document\nand archive their data, run their models and analysis tools, and share their data, software, and multi-model workflows\nwithin a robust Community of Practice. MSD-LIVE will facilitate a new open, collaborative, resource-rich, technology-facilitated,\ncommunity-driven way of doing MSD research.", + "laborHours": 0.0, + "languages": [], + "name": "msdlive-cli-distro", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/MSD-LIVE/msdlive-cli-distro", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/msr-genie.json b/agency-indexes/DoE/msr-genie.json new file mode 100644 index 00000000..7d1f6663 --- /dev/null +++ b/agency-indexes/DoE/msr-genie.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-11-02", + "metadataLastUpdated": "2023-11-02" + }, + "description": "MSR-Genie is a vendor-neutral tool for fast and efficient queries about model-specific registers (MSRs).\nThe tool allows end users to query bi-directionally across MSR lists as well as processor families and\nmodels, and provides them with guidance on appropriate bitmasks. The msr-genie tool is open-source\nand easily extensible, and currently supports 30 Intel processor models and two-thousand unique MSRs.", + "laborHours": 0.0, + "languages": [], + "name": "msr-genie", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/msr-genie", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/msr-safe.json b/agency-indexes/DoE/msr-safe.json new file mode 100644 index 00000000..33b86408 --- /dev/null +++ b/agency-indexes/DoE/msr-safe.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-05-13", + "metadataLastUpdated": "2020-09-11" + }, + "description": "Modern processors offer a wide range of control and measurement features, such as performance\ncounters, power capping, and thermal control. These features are ultimately controlled through Model\nSpecific Registers (MSRs), which require elevated privileges for access. While this is often no problem on\nindividual workstations, it is a significant security risk on multi-user systems and large-scale compute\nclusters. The msr-safe kernel module provides controlled user-level access to MSRs through a\nwhitelisting mechanism.\nIs", + "laborHours": 2614.4, + "languages": [], + "name": "msr-safe", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/msr-safe", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.4.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/mstk-docker.json b/agency-indexes/DoE/mstk-docker.json new file mode 100644 index 00000000..8b41aedf --- /dev/null +++ b/agency-indexes/DoE/mstk-docker.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-02-12", + "metadataLastUpdated": "2019-02-13" + }, + "description": "Enable developers to run the Granta MI Scripting Toolkit (MSTK) within a docker container. Developers who work with the MSTK can use this tool to test their code on various operating systems, as well as load custom Python libraries as desired. This can help to replicate an environment as close to production as possible. The MSTK does not officially support macOS, as such this docker project allows macOS users to quickly spin up an environment to develop with the toolkit without the need to use a dedicated VM.", + "laborHours": 106.4, + "languages": [], + "name": "mstk-docker", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/mstk-docker", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/muMatScale.json b/agency-indexes/DoE/muMatScale.json new file mode 100644 index 00000000..d50039ef --- /dev/null +++ b/agency-indexes/DoE/muMatScale.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "sabaua@ornl.gov" + }, + "date": { + "created": "2024-01-12", + "metadataLastUpdated": "2024-01-30" + }, + "description": "Code for modeling solidification microstructure based on the Cellular Automata method for binary/pseudo-binary alloys.\n\nThis code is derived from the open-source software uMatIC developed at the Imperial College London https://www.imperial.ac.uk/engineering-alloys/research/software", + "laborHours": 0.0, + "languages": [ + "C", + "cmake" + ], + "name": "muMatScale", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lang-yuan/muMatScale", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/multiBreath.py.json b/agency-indexes/DoE/multiBreath.py.json new file mode 100644 index 00000000..df563073 --- /dev/null +++ b/agency-indexes/DoE/multiBreath.py.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-22", + "metadataLastUpdated": "2025-04-22" + }, + "description": "This is a research code which is intended to be made available to researchers to the password-protected simtk.org\nwebsite which hosts the lung deposition simulation project \"In-silico LADDER: Lung Aerosol Dosimetry for Drug and\nEnvironmental Research\" headed by NIH PI Prof. Chantal Darquenne (UCSD). Industrial applications are more accurate\ndeposition predictions of medical aerosols, including potentially subject-specific exposures.\nAccessing the code requires registration.", + "homepageURL": "https://simtk.org/projects/insilico_ladder", + "laborHours": 851.2, + "languages": [], + "name": "multiBreath.py", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://simtk.org/projects/insilico_ladder", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/multimat_1drdg.json b/agency-indexes/DoE/multimat_1drdg.json new file mode 100644 index 00000000..58863369 --- /dev/null +++ b/agency-indexes/DoE/multimat_1drdg.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The multimat_1drdg code is a one-dimensional code which is used to prototype the numerical method published in \u201cPandare, A. K., Waltz, J., & Bakosi, J. (2019). A Reconstructed Discontinuous Galerkin method for Multi-Material Hydrodynamics with Sharp-Interfaces. International Journal for Numerical Methods in Fluids.\u201d It solves the multi-fluid dynamics equations (arbitrary number of fluids) using the third-order Reconstructed Discontinuous Galerkin (rDG) method. A few academic test problems from previous published literature are included as initial setup options.", + "laborHours": 0.0, + "languages": [], + "name": "multimat_1drdg", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/multimat_1drdg", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/n-dimensional_Statistical_Inverse_Graphical_Hydraulic_Test_Simulator.json b/agency-indexes/DoE/n-dimensional_Statistical_Inverse_Graphical_Hydraulic_Test_Simulator.json new file mode 100644 index 00000000..d875bc33 --- /dev/null +++ b/agency-indexes/DoE/n-dimensional_Statistical_Inverse_Graphical_Hydraulic_Test_Simulator.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-17" + }, + "description": "nSIGHTS (n-dimensional Statistical Inverse Graphical Hydraulic Test Simulator) is a comprehensive well test analysis software package. It provides a user-interface, a well test analysis model and many tools to analyze both field and simulated data. The well test analysis model simulates a single-phase, one-dimensional, radial/non-radial flow regime, with a borehole at the center of the modeled flow system. nSIGHTS solves the radially symmetric n-dimensional forward flow problem using a solver based on a graph-theoretic approach. The results of the forward simulation are pressure, and flow rate, given all the input parameters. The parameter estimation portion of nSIGHTS uses a perturbation-based approach to interpret the best-fit well and reservoir parameters, given an observed dataset of pressure and flow rate.", + "laborHours": 269587.2, + "languages": [ + "Objective-C", + "C++", + "HTML", + "C", + "CMake", + "Makefile" + ], + "name": "n-dimensional Statistical Inverse Graphical Hydraulic Test Simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/nSIGHTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git "a/agency-indexes/DoE/nSnare\342\204\242.json" "b/agency-indexes/DoE/nSnare\342\204\242.json" new file mode 100644 index 00000000..8e7e8135 --- /dev/null +++ "b/agency-indexes/DoE/nSnare\342\204\242.json" @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-02-19", + "metadataLastUpdated": "2019-02-20" + }, + "description": "nSnare\u2122 analyses and categorizes log messages generated by various and customizable third party software packages using a custom multi-tiered rules engine. Each log message is either determined to be a false positive, or it is assigned a score based on the severity of the potential attack and confidence that the activity described by the log message is not a false positive. Log messages are then assigned to an event, which is a collection of log messages related to a single potential attack. Meta-analysis rules run on the collection of all logs within an event to correlate multiple related logs into a single known attack signature. When the sum of the scores of all logs within an event exceeds a pre-defined threshold, the event is labelled as an attack and an automated response is generated to block the attacker from connecting to any protected resources, called quarantining within the application, for a variable length of time. The length of time that the quarantine lasts for is based on the severity and frequency of the attack, along with historical information on the attacker and any third party provided threat intelligence data that the system has gathered. An additional random length of time is added to each quarantine so the algorithm cannot easily be learned and bypassed by a persistent attacker. A confidence score is generated based on a proprietary algorithm that determines the likelihood that the data which lead to the attacker getting quarantined was a false positive. A threat intelligence record is created for each detected attack, with details on the attacker, a summary of what triggered the quarantine, the severity of the attack and the confidence the system has that the attack is not the result of false data, which can then be shared with external entities so that they can also protect themselves from a related attack.\n\nThe software also includes a web based front end for analyzing the current quarantined attacks, removing a quarantine in the case of a false positive, viewing previously quarantined attacks, and tracking suspicious activity that the system is currently evaluating. The web interface also allows the creation and modification of rules used by the rules engine, and the maintenance of a whitelist of known good systems that should never be automatically quarantined.\n", + "homepageURL": "https://www.labpartnering.org/lab-technologies/09425b12-3332-4a90-892d-44dbb8e1be34", + "laborHours": 0.0, + "languages": [], + "name": "nSnare\u2122", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.labpartnering.org/lab-technologies/09425b12-3332-4a90-892d-44dbb8e1be34", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.labpartnering.org/lab-technologies/09425b12-3332-4a90-892d-44dbb8e1be34", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/nanoPOTS_robot.json b/agency-indexes/DoE/nanoPOTS_robot.json new file mode 100644 index 00000000..2826ce1b --- /dev/null +++ b/agency-indexes/DoE/nanoPOTS_robot.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-04-11", + "metadataLastUpdated": "2025-04-11" + }, + "description": "In conjunction with other nanoPOTS related IP, we are disclosing the robotic platform including specific parts used to\nconstruct the nanopipetting instrument.", + "homepageURL": "https://www.pnnl.gov/available-technologies", + "laborHours": 304.0, + "languages": [], + "name": "nanoPOTS robot", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://www.pnnl.gov/available-technologies", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://www.pnnl.gov/available-technologies", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/narrative-jupyterlab.json b/agency-indexes/DoE/narrative-jupyterlab.json new file mode 100644 index 00000000..34b458f6 --- /dev/null +++ b/agency-indexes/DoE/narrative-jupyterlab.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-02", + "metadataLastUpdated": "2020-09-02" + }, + "description": "Research and prototyping KBase extensions in Jupyterlab.", + "laborHours": 10518.4, + "languages": [], + "name": "narrative-jupyterlab", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/narrative-jupyterlab", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/narrative-traefiker.json b/agency-indexes/DoE/narrative-traefiker.json new file mode 100644 index 00000000..74a359f8 --- /dev/null +++ b/agency-indexes/DoE/narrative-traefiker.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-23", + "metadataLastUpdated": "2020-07-31" + }, + "description": "Narrative container lifecycle management for traefik. This is a replacement for the original OpenRESTy based Lua narrative lifecycle management code. ", + "laborHours": 927.2, + "languages": [], + "name": "narrative-traefiker", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/narrative-traefiker", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/narrative-utils.json b/agency-indexes/DoE/narrative-utils.json new file mode 100644 index 00000000..fb6316d1 --- /dev/null +++ b/agency-indexes/DoE/narrative-utils.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-02", + "metadataLastUpdated": "2020-09-02" + }, + "description": "Utility modules and APIs and such for the Jupyterlab Narrative.", + "laborHours": 2310.4, + "languages": [], + "name": "narrative-utils", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/narrative-utils", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/narrativeReaper.json b/agency-indexes/DoE/narrativeReaper.json new file mode 100644 index 00000000..96e5f635 --- /dev/null +++ b/agency-indexes/DoE/narrativeReaper.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "Scan and delete narrative sessions which have not been active for a period of time.", + "laborHours": 45.6, + "languages": [], + "name": "narrativeReaper", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/narrativeReaper", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/narrative_job_proxy.json b/agency-indexes/DoE/narrative_job_proxy.json new file mode 100644 index 00000000..da4cad0f --- /dev/null +++ b/agency-indexes/DoE/narrative_job_proxy.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "Thin wrapper for the user_and_job_state service that allows querying jobs as the narrative job listener user.", + "laborHours": 744.8, + "languages": [], + "name": "narrative_job_proxy", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/narrative_job_proxy", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/narrative_method_specs_ci_.json b/agency-indexes/DoE/narrative_method_specs_ci_.json new file mode 100644 index 00000000..288ae937 --- /dev/null +++ b/agency-indexes/DoE/narrative_method_specs_ci_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" + }, + "description": "Narrative method specs repo for use in the -ci (or other nonproduction) environments.", + "laborHours": 592.8, + "languages": [], + "name": "narrative_method_specs_ci ", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/narrative_method_specs_ci", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nbexamples.json b/agency-indexes/DoE/nbexamples.json new file mode 100644 index 00000000..7bdc3931 --- /dev/null +++ b/agency-indexes/DoE/nbexamples.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "This is a Jupyter extension that shows a list of example notebooks that users can easily preview and copy for their own use. The targeted application is a JupyterHub deployment, where it is useful to distribute a collection of curated examples or templates and make it possible for hub uses to quickly share examples.", + "laborHours": 760.0, + "languages": [], + "name": "nbexamples", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/nbexamples/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/nbexamples", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nem_slice_ver._3.34.json b/agency-indexes/DoE/nem_slice_ver._3.34.json new file mode 100644 index 00000000..ac1dde9e --- /dev/null +++ b/agency-indexes/DoE/nem_slice_ver._3.34.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Nem_slice reads in a finite element model description of the geometry of a problem from an ExodusII file and generates either a nodal or elemental graph of the problem. It then calls Chaco to load balance the graph and then outputs a NemesisI load-balance file.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "nem_slice ver. 3.34", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "3.34" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nem_spread_Ver._5.10.json b/agency-indexes/DoE/nem_spread_Ver._5.10.json new file mode 100644 index 00000000..fdff4d37 --- /dev/null +++ b/agency-indexes/DoE/nem_spread_Ver._5.10.json @@ -0,0 +1,39 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-22" + }, + "description": "Nem_spread reads it's input command file (default name nem_spread.inp), takes the named ExodusII geometry definition and spreads out the geometry (and optionally results) contained in that file out to a parallel disk system. The decomposition is taken from a scalar Nemesis load balance file generated by the companion utility nem_slice.", + "laborHours": 692284.0, + "languages": [ + "C++", + "HTML", + "C", + "CMake", + "Fortran", + "Python" + ], + "name": "nem_spread Ver. 5.10", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/seacas", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "5.10" +} \ No newline at end of file diff --git a/agency-indexes/DoE/netroot.json b/agency-indexes/DoE/netroot.json new file mode 100644 index 00000000..497a483a --- /dev/null +++ b/agency-indexes/DoE/netroot.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "netroot\u00a0is a package of utilities for network root file systems. It was designed for the TOSS Linux distribution for clusters, developed at Lawrence Livermore National Laboratory, but will work with other Red Hat Enterprise Linux derived distros.\n", + "laborHours": 729.6, + "languages": [], + "name": "netroot", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/netroot", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/netshell.json b/agency-indexes/DoE/netshell.json new file mode 100644 index 00000000..842aa0dd --- /dev/null +++ b/agency-indexes/DoE/netshell.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "Kernel and companion software that support ENOS applications.", + "laborHours": 8952.8, + "languages": [], + "name": "netshell", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/netshell/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/netshell", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nextgen.json b/agency-indexes/DoE/nextgen.json new file mode 100644 index 00000000..386eddcc --- /dev/null +++ b/agency-indexes/DoE/nextgen.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "Next generation of KBase documents and code experiments. This repository is a collection point for KBase documents and code experiments (etc.) for the \"next generation\" of the KBase infrastructure.", + "laborHours": 7265.6, + "languages": [], + "name": "nextgen", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/nextgen", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nexus_emulation.json b/agency-indexes/DoE/nexus_emulation.json new file mode 100644 index 00000000..41c4a567 --- /dev/null +++ b/agency-indexes/DoE/nexus_emulation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2020-08-26" + }, + "description": "This provides an emulation of the Globus Nexus API that can be used to support authentication back ends other than Globus Nexus.", + "laborHours": 334.4, + "languages": [], + "name": "nexus_emulation", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/nexus_emulation", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nfsroot.json b/agency-indexes/DoE/nfsroot.json new file mode 100644 index 00000000..7a07c9d0 --- /dev/null +++ b/agency-indexes/DoE/nfsroot.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "nfsroot\u00a0is a package designed to help make Linux root file system images network-bootable and sharable by many clients. It was designed for the CHAOS Linux distribution (now renamed to TOSS) for clusters, developed at Lawrence Livermore National Laboratory, but will work with other Red Hat Enterprise Linux derived distros.", + "laborHours": 1079.2, + "languages": [], + "name": "nfsroot", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/nfsroot", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nginx.json b/agency-indexes/DoE/nginx.json new file mode 100644 index 00000000..12d5a5ac --- /dev/null +++ b/agency-indexes/DoE/nginx.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "Version of standard nginx image that supports KBase configuration.", + "laborHours": 30.4, + "languages": [], + "name": "nginx", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/nginx", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ninterp:_N-dimensional_interpolation_Rust_crate_[SWR-25-25].json b/agency-indexes/DoE/ninterp:_N-dimensional_interpolation_Rust_crate_[SWR-25-25].json new file mode 100644 index 00000000..a48c2c6d --- /dev/null +++ b/agency-indexes/DoE/ninterp:_N-dimensional_interpolation_Rust_crate_[SWR-25-25].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-26", + "metadataLastUpdated": "2024-12-11" + }, + "description": "The ninterp crate provides multivariate interpolation over a regular, sorted, nonrepeating grid of any dimensionality. A variety of interpolation strategies are implemented, however more are likely to be added. Extrapolation beyond the range of the supplied coordinates is supported for 1-D linear interpolators, using the slope of the nearby points.\n\nThere are hard-coded interpolators for lower dimensionalities (up to N = 3) for better runtime performance.\n\nAll interpolation is handled through instances of the Interpolator enum, with the selected tuple variant containing relevant data. Interpolation is executed by calling Interpolator::interpolate.", + "laborHours": 820.8, + "languages": [ + "Rust" + ], + "name": "ninterp: N-dimensional interpolation Rust crate [SWR-25-25]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ninterp", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nml-mrs-model.json b/agency-indexes/DoE/nml-mrs-model.json new file mode 100644 index 00000000..096f2189 --- /dev/null +++ b/agency-indexes/DoE/nml-mrs-model.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-19", + "metadataLastUpdated": "2019-06-19" + }, + "description": "Network Markup Language (NML) - Multi-Resource Service (MRS) - Modeling schemas and tools.", + "laborHours": 2188.8, + "languages": [], + "name": "nml-mrs-model", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/nml-mrml/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/nml-mrml", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nmrfit.json b/agency-indexes/DoE/nmrfit.json new file mode 100644 index 00000000..9a4afc94 --- /dev/null +++ b/agency-indexes/DoE/nmrfit.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Nmrfit reads the output from a nuclear magnetic resonance (NMR) experiment and, through a number of intuitive API calls, produces a least-squares fit of Voigt-function approximations via particle swarm optimization.", + "laborHours": 380.0, + "name": "nmrfit", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/nmrfit/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/nmrfit", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nng_stream.json b/agency-indexes/DoE/nng_stream.json new file mode 100644 index 00000000..4378c1be --- /dev/null +++ b/agency-indexes/DoE/nng_stream.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "rogersdm@ornl.gov" + }, + "date": { + "created": "2024-09-05", + "metadataLastUpdated": "2024-09-05" + }, + "description": "This project uses the NanoMsg next-generation library to receive data, temporarily store in an in-memory buffer, and then send it out. The buffer handles a high-bandwidth stream from multiple producers (sources) to multiple consumers (sinks).", + "laborHours": 456.0, + "languages": [ + "Python" + ], + "name": "nng_stream", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/frobnitzem/nng_stream", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "0.6" +} \ No newline at end of file diff --git a/agency-indexes/DoE/node-red-contrib-oadr-ven.json b/agency-indexes/DoE/node-red-contrib-oadr-ven.json new file mode 100644 index 00000000..4f9a0722 --- /dev/null +++ b/agency-indexes/DoE/node-red-contrib-oadr-ven.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "OpenADR 2.0 a/b Virtual End Node (VEN) node for Node-Red.", + "laborHours": 1930.4, + "languages": [], + "name": "node-red-contrib-oadr-ven", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/node-red-contrib-oadr-ven", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/node-red-contrib-ocpp2.json b/agency-indexes/DoE/node-red-contrib-ocpp2.json new file mode 100644 index 00000000..1dc5816d --- /dev/null +++ b/agency-indexes/DoE/node-red-contrib-ocpp2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-26" + }, + "description": "Open source Node-Red \"nodes\" to support the Open Charge Point Protocol (OCPP) 2.0.1 protocol.", + "laborHours": 15899.2, + "languages": [], + "name": "node-red-contrib-ocpp2", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Argonne-National-Laboratory/node-red-contrib-ocpp2", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nodediag.json b/agency-indexes/DoE/nodediag.json new file mode 100644 index 00000000..fed1c430 --- /dev/null +++ b/agency-indexes/DoE/nodediag.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "nodediag is an extensible framework for packaging system diagnostics for Linux clusters.", + "laborHours": 592.8, + "name": "nodediag", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/nodediag", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/noncompact_u1__qed_m__v1.0.5.json b/agency-indexes/DoE/noncompact_u1__qed_m__v1.0.5.json new file mode 100644 index 00000000..173a6a6d --- /dev/null +++ b/agency-indexes/DoE/noncompact_u1__qed_m__v1.0.5.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-06-07", + "metadataLastUpdated": "2023-06-12" + }, + "description": "This software generates QED fields in which the photon has a finite mass, and also the 0-mode subtracted scheme. They are intended to be used with lattice QCD calculations to understand the QED corrections to nuclear physics processes that are being computed with lattice QCD. To the best of my knowledge, this will be the only publicly available software that generates background QED configurations with massive photons. ", + "laborHours": 0.0, + "languages": [], + "name": "noncompact_u1 (qed_m) v1.0.5", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/callat-qcd/qed_m", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nph_-_PH_Client_and_Library.json b/agency-indexes/DoE/nph_-_PH_Client_and_Library.json new file mode 100644 index 00000000..a5026842 --- /dev/null +++ b/agency-indexes/DoE/nph_-_PH_Client_and_Library.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "nph is a modern client and API library for accessing PH servers.", + "laborHours": 8056.0, + "languages": [], + "name": "nph - PH Client and Library", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/nph", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nrelWattileExt__SkySpark_Wattile_Extension__[SWR-24-73].json b/agency-indexes/DoE/nrelWattileExt__SkySpark_Wattile_Extension__[SWR-24-73].json new file mode 100644 index 00000000..b9a8f739 --- /dev/null +++ b/agency-indexes/DoE/nrelWattileExt__SkySpark_Wattile_Extension__[SWR-24-73].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-06-14", + "metadataLastUpdated": "2024-09-16" + }, + "description": "The NREL Wattile extension, nrelWattileExt, provides an interface between SkySpark, an energy management and analytics software, and Wattile, an NREL-developed Python package for probabilistic prediction of building energy consumption. Wattile models predict discrete quantiles of the probability distribution of a target quantity (typically energy consumption) using the historical time series data from one or more predictors (typically weather data). Within SkySpark, predictions from Wattile models can be used for measurement & verification of building performance, detection of energy anomalies, and fault detection.\n\nRelated to: https://github.com/NREL/Wattile", + "laborHours": 182.4, + "languages": [ + "Dockerfile", + "Fantom" + ], + "name": "nrelWattileExt (SkySpark Wattile Extension) [SWR-24-73]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/nrelWattileExt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nsi-lib.json b/agency-indexes/DoE/nsi-lib.json new file mode 100644 index 00000000..45526422 --- /dev/null +++ b/agency-indexes/DoE/nsi-lib.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "NSI-related Java Libraries.", + "laborHours": 6095.2, + "languages": [], + "name": "nsi-lib", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/nsi-lib/blob/master/README.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/nsi-lib", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nsls2-ci.json b/agency-indexes/DoE/nsls2-ci.json new file mode 100644 index 00000000..703f3ce4 --- /dev/null +++ b/agency-indexes/DoE/nsls2-ci.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "This is the repository for nsls2-ci developed at Brookhaven National Laboratory. ", + "laborHours": 91.2, + "languages": [], + "name": "nsls2-ci", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/nsls2-ci", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nuclear-score-maximization_v1.0.json b/agency-indexes/DoE/nuclear-score-maximization_v1.0.json new file mode 100644 index 00000000..7aed1815 --- /dev/null +++ b/agency-indexes/DoE/nuclear-score-maximization_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-07-24", + "metadataLastUpdated": "2024-07-24" + }, + "description": "This software library presents efficient and multithreaded implementations of matrix low rank approximation via column selection in C++17 code. The algorithms are described in Fornace, Mark, and Michael Lindsey. \"Column and row subset selection using nuclear scores: algorithms and theory for Nystro m approximation, CUR decomposition, and graph Laplacian reduction.\" arXiv preprint arXiv:2407.01698 (2024). The presented methods are by-and-large ver novel, have provable approximation guarantees, multiple use-cases, and exhibit higher quality approximations on a variety of studied examples.", + "laborHours": 927.2, + "languages": [], + "name": "nuclear-score-maximization v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mfornace/nuclear-score-maximization", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nuctools.json b/agency-indexes/DoE/nuctools.json new file mode 100644 index 00000000..b691de18 --- /dev/null +++ b/agency-indexes/DoE/nuctools.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "brownjm@ornl.gov" + }, + "date": { + "created": "2021-10-21", + "metadataLastUpdated": "2021-10-21" + }, + "description": "Nuctools is a python package designed to provide tools for analysis of nuclear interaction data.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "nuctools", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/brownjm1968/nuctools", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/numa-maps.json b/agency-indexes/DoE/numa-maps.json new file mode 100644 index 00000000..9506de4e --- /dev/null +++ b/agency-indexes/DoE/numa-maps.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The numa-maps program displays information about how memory for processes is laid out on a NUMA (Non-Uniform Memory Architecture) system running Linux.", + "laborHours": 106.4, + "name": "numa-maps", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/grondo/numa-maps", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/numericalFunctions.json b/agency-indexes/DoE/numericalFunctions.json new file mode 100644 index 00000000..7920fc81 --- /dev/null +++ b/agency-indexes/DoE/numericalFunctions.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-15", + "metadataLastUpdated": "2019-07-16" + }, + "description": "The numericalFunction C library is designed to handle point-wise interpolative data representing a mathematical function. The library currently handles 1-d functions (i.e., functions of the format f(x)). \n\nThe main object is the ptwXYPoints C struct that holds list of x,y pairs sorted by ascending x-values with an interpolation rule. That is, it contains the 1-d function f(x) = y(x). \n\nFunctions are included that support common unitary and binary operations (e.g., negation, addition, multiplication). \n\nAs example, if f(x) and g(x) are two ptwXYPoints instances, then routines to calculate f(x) + g(x) and f(x) * g(x) are included.\n\nThe library support storage of data with lin-lin, lin-log, log-lin, log-log and flat (or histogram) interpolation.\n\nFunctions to convert any of the supported interpolation to lin-lin are included. However, many of the binary functions only support lin-lin interpolation.\n\nThe library also contains a C struct for storing a Legendre series representation of a 1-d function, and functions to convert Legendre series to and from a ptwXYPoints instance.\n\nA python interface to the library is included, with the ptwXYPoints C struct treated as a class. This class has many of the standard python math methods (e.g., __add__, __mul__).", + "laborHours": 60359.2, + "languages": [ + "Python" + ], + "name": "numericalFunctions", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/nvidia_dataframe_library_patch_to_support_parquet_indexing.json b/agency-indexes/DoE/nvidia_dataframe_library_patch_to_support_parquet_indexing.json new file mode 100644 index 00000000..a44eb299 --- /dev/null +++ b/agency-indexes/DoE/nvidia_dataframe_library_patch_to_support_parquet_indexing.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2023-02-28", + "metadataLastUpdated": "2023-02-28" + }, + "description": "On behalf of our WFO sponsors/collaborators, we are working closely with NVIDIA to improve their public, open-source GPU dataframes library. We are improving the library's support for reading and writing Parquet (an open source file format) for general-purpose cloud storage and processing. This patch better supports the indexing found in the more recent Parquet specifications. Is there", + "laborHours": 0.0, + "languages": [], + "name": "nvidia dataframe library patch to support parquet indexing", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rapidsai/cudf", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/obstac10.json b/agency-indexes/DoE/obstac10.json new file mode 100644 index 00000000..ff456300 --- /dev/null +++ b/agency-indexes/DoE/obstac10.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2019-10-07", + "metadataLastUpdated": "2019-10-08" + }, + "description": "Software infrastructure for using a custom (user-written) scheduler with the SISPI control system of DECam, and an example template for such a scheduler. This version of the obstac code is only infrastructure for supporting writing a scheduler, not a functional scheduler in itself: earlier versions of obstac that include the DES scheduler are part of SISPI, and not included as part of this package.", + "laborHours": 623.2, + "languages": [ + "Python" + ], + "name": "obstac10", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ehneilsen/obstac10", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ocd-release.json b/agency-indexes/DoE/ocd-release.json new file mode 100644 index 00000000..59d741f4 --- /dev/null +++ b/agency-indexes/DoE/ocd-release.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-01-14", + "metadataLastUpdated": "2019-01-15" + }, + "description": "OCD-release is a package that contains the meta data for CentOS and other RPM based packages tested together. It will be used to create tested OS releases.", + "laborHours": 0.0, + "languages": [], + "name": "ocd-release", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trentdhooge/ocd-release", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/olcf_GLS.json b/agency-indexes/DoE/olcf_GLS.json new file mode 100644 index 00000000..f938bbe5 --- /dev/null +++ b/agency-indexes/DoE/olcf_GLS.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "wynnejr@ornl.gov" + }, + "date": { + "created": "2022-12-14", + "metadataLastUpdated": "2022-12-14" + }, + "description": "Clone of ls that includes file annotation based upon GPFS extended attributes", + "laborHours": 0.0, + "languages": [ + "C++", + "Go" + ], + "name": "olcf/GLS", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/olcf/GLS", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/omp-selfishloop.json b/agency-indexes/DoE/omp-selfishloop.json new file mode 100644 index 00000000..bc9124e0 --- /dev/null +++ b/agency-indexes/DoE/omp-selfishloop.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-20", + "metadataLastUpdated": "2020-05-20" + }, + "description": "omp-selfishloop is a tool to measure OS activities using a busy rdtsc-sampling loop on a multicore machine.", + "laborHours": 167.2, + "languages": [], + "name": "omp-selfishloop", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/coolr-hpc/selfishloop/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/coolr-hpc/selfishloop", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ompi.json b/agency-indexes/DoE/ompi.json new file mode 100644 index 00000000..0967c3d3 --- /dev/null +++ b/agency-indexes/DoE/ompi.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Clone of Open MPI", + "laborHours": 680017.6, + "name": "ompi", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/ORNL/ompi/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/ompi", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ontology-annotator.json b/agency-indexes/DoE/ontology-annotator.json new file mode 100644 index 00000000..4da194d4 --- /dev/null +++ b/agency-indexes/DoE/ontology-annotator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"ontology-annotator\" developed by KBase. This is a KBase module generated by the KBase Software Development Kit (SDK).", + "laborHours": 866.4, + "languages": [], + "name": "ontology-annotator", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/ontology-annotator", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/openPMD-viewer.json b/agency-indexes/DoE/openPMD-viewer.json new file mode 100644 index 00000000..0f19b35d --- /dev/null +++ b/agency-indexes/DoE/openPMD-viewer.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Many simulation software produce data in the form of a set of field values or of a set of particle positions. (one such example is that of particle-in-cell codes, which produce data on the electromagnetic fields that they simulate.) However, each particular software uses its own particular format and layout, for the output data. This makes it difficult to compare the results of different simulation software, or to have a common visualization tool for these results. However, a standardized layout for fields and particles has recently been developed: the openPMD format ( HYPERLINK \"http://www.openpmd.org/\"www.openpmd.org) This format is open- source, and specifies a standard way in which field data and particle data should be written. The openPMD format is already implemented in the particle-in-cell code Warp (developed at LBL) and in PIConGPU (developed at HZDR, Germany). In this context, the proposed software (openPMD-viewer) is a Python package, which allows to access and visualize any data which has been formatted according to the openPMD standard. This package contains two main components: - a Python API, which allows to read and extract the data from a openPMD file, so as to be able to work with it within the Python environment. (e.g. plot the data and reprocess it with particular Python functions) - a graphical interface, which works with the ipython notebook, and allows to quickly visualize the data and browse through a set of openPMD files. The proposed software will be typically used when analyzing the results of numerical simulations. It will be useful to quickly extract scientific meaning from a set of numerical data.", + "laborHours": 1246.4, + "name": "openPMD-viewer", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/openPMD/openPMD-viewer/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/openPMD/openPMD-viewer", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/openmp-lws.json b/agency-indexes/DoE/openmp-lws.json new file mode 100644 index 00000000..926d09b1 --- /dev/null +++ b/agency-indexes/DoE/openmp-lws.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "This is a repository for lightweight scheduling. ", + "laborHours": 15.2, + "languages": [], + "name": "openmp-lws", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SOLLVE/openmp-lws", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/openmp_bck.json b/agency-indexes/DoE/openmp_bck.json new file mode 100644 index 00000000..74427fb8 --- /dev/null +++ b/agency-indexes/DoE/openmp_bck.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2021-01-29" + }, + "description": "This is the code for openmp_bck developed by the Exascale Computing Project (ECP). ", + "homepageURL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "laborHours": 59994.4, + "languages": [], + "name": "openmp_bck", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.bnl.gov/compsci/projects/SOLLVE/software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/optimas_v0.1.json b/agency-indexes/DoE/optimas_v0.1.json new file mode 100644 index 00000000..4d6fe690 --- /dev/null +++ b/agency-indexes/DoE/optimas_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-05-17", + "metadataLastUpdated": "2023-05-17" + }, + "description": "\toptimas is a Python library that can coordinate a large number of numerical simulations on high-performance computing resources, with the aim of optimizing a given simulation result.\nMore specifically, this library is currently used for design optimization of laser-plasma particle accelerators. In this context, the performance of particle accelerator designs are often evaluated with large-scale simulation codes, and many separate simulations need to be run - with different design parameters - in order to find the most performant design. optimas facilitates this process by providing a convenient interface to advanced optimizers (e.g. Bayesian optimization), and by coordinating the execution of the different simulations on HPC resources. (This is done by leveraging the library libensemble.)\n\nCompared to other open-source optimization libraries (e.g. Ax), optimas is more tailored towards execution on DOE HPC resources (e.g. Perlmutter, Summit, etc.) and is specialized for the type of simulation codes and workflows that are used in the community of laser-plasma acceleration.", + "laborHours": 0.0, + "languages": [], + "name": "optimas v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/optimas-org/optimas", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ornladios_ADIOS2.json b/agency-indexes/DoE/ornladios_ADIOS2.json new file mode 100644 index 00000000..d0109360 --- /dev/null +++ b/agency-indexes/DoE/ornladios_ADIOS2.json @@ -0,0 +1,38 @@ +{ + "contact": { + "email": "pnorbert@ornl.gov" + }, + "date": { + "created": "2022-07-05", + "metadataLastUpdated": "2022-07-07" + }, + "description": "ADIOS 2: The Adaptable Input Output (I/O) System version 2 is an open-source framework that addresses scientific data management challenges, e.g. scalable parallel I/O, as we approach the exascale era in high-performance computing (HPC). ADIOS 2 bindings are available in C++, C, Fortran, Python and can be used on supercomputers, personal computers, and cloud systems running on Linux, macOS and Windows. ADIOS 2 has out-of-the-box support for MPI and serial environments.", + "laborHours": 428229.6, + "languages": [ + "C++", + "C", + "C", + "Fortran", + "Python" + ], + "name": "ornladios/ADIOS2", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornladios/ADIOS2", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "2.8.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ornlneutronimaging_mcpevent2hist.json b/agency-indexes/DoE/ornlneutronimaging_mcpevent2hist.json new file mode 100644 index 00000000..e5edf481 --- /dev/null +++ b/agency-indexes/DoE/ornlneutronimaging_mcpevent2hist.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "zhangc@ornl.gov" + }, + "date": { + "created": "2024-01-08", + "metadataLastUpdated": "2024-01-08" + }, + "description": "Contains software that is used to process the raw tpx3 data into hit and events.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "ornlneutronimaging/mcpevent2hist", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornlneutronimaging/mcpevent2hist", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "2.2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/orsoqs.json b/agency-indexes/DoE/orsoqs.json new file mode 100644 index 00000000..be944921 --- /dev/null +++ b/agency-indexes/DoE/orsoqs.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-18" + }, + "description": "This is the repository for orsoqs developed at Oak Ridge National Laboratory. ", + "laborHours": 516.8, + "languages": [], + "name": "orsoqs", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-QCI/orsoqs", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/oscars-frontend.json b/agency-indexes/DoE/oscars-frontend.json new file mode 100644 index 00000000..895ab049 --- /dev/null +++ b/agency-indexes/DoE/oscars-frontend.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "This is the repository for oscars-frontend developed by Energy Sciences Network (ESnet). 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The specific modification included in the initial version of owsim is for triggered follow-up of transient events, but the tool is general enough to support different kinds of modifications as well.", + "laborHours": 12479.2, + "languages": [ + "Python" + ], + "name": "owsim", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LSSTDESC/ObsStrat", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pBEAM__Polynomial_Beam_Element_Analysis_Module__[SWR-13-20].json b/agency-indexes/DoE/pBEAM__Polynomial_Beam_Element_Analysis_Module__[SWR-13-20].json new file mode 100644 index 00000000..5708893b --- /dev/null +++ b/agency-indexes/DoE/pBEAM__Polynomial_Beam_Element_Analysis_Module__[SWR-13-20].json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2023-12-14" + }, + "description": "pBEAM (Polynomial Beam Element Analysis Module) is a finite element method for beam-like structures.", + "laborHours": 75118.4, + "languages": [ + "C++", + "C", + "Fortran", + "Python" + ], + "name": "pBEAM (Polynomial Beam Element Analysis Module) [SWR-13-20]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/pbeam", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pCamal.json b/agency-indexes/DoE/pCamal.json new file mode 100644 index 00000000..cc547f7c --- /dev/null +++ b/agency-indexes/DoE/pCamal.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-22" + }, + "description": "The Parallel CUBIT Adaptive Mesh Algorithm Library (pCAMAL) is a distributed-memory embarrassingly parallel hexahedral mesh generator. pCAMAL utilizes the sweeping method following a serial step of geometry decomposition conducted in the CUBIT geometry preparation and mesh generation tool. pCAMAL also reports mesh quality statistics as calculated in parallel from per-element quality metrics.", + "laborHours": 13725.6, + "languages": [ + "C++", + "C" + ], + "name": "pCamal", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pCAMAL", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pLiner.json b/agency-indexes/DoE/pLiner.json new file mode 100644 index 00000000..d9dbedb6 --- /dev/null +++ b/agency-indexes/DoE/pLiner.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-07-27", + "metadataLastUpdated": "2020-07-27" + }, + "description": "Compiler optimizations can alter significantly the numerical results of scientific computing applications.\nWhen numerical results differ significantly between compilers, optimization levels, and floating-point\nhardware, these numerical inconsistencies can impact programming productivity. pLiner is a framework\nthat helps programmers identify locations in the source code that are highly affected by compiler\noptimizations. pLiner uses a novel approach to identify such code locations by enhancing the floatingpoint\nprecision of variables and expressions. Using a guided search to locate the most significant code\nregions, pLiner can report to users such locations at different granularities, file, function, and line of code.", + "laborHours": 18194.4, + "languages": [], + "name": "pLiner", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pLiner", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/panda-k8s.json b/agency-indexes/DoE/panda-k8s.json new file mode 100644 index 00000000..16bf7467 --- /dev/null +++ b/agency-indexes/DoE/panda-k8s.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-21", + "metadataLastUpdated": "2022-07-21" + }, + "description": "This is the repository for \"panda-k8s\" developed by SLAC National Accelerator Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "panda-k8s", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/rubin-panda-deploy", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pandas-sacct_v1.0.0.json b/agency-indexes/DoE/pandas-sacct_v1.0.0.json new file mode 100644 index 00000000..15ac6da2 --- /dev/null +++ b/agency-indexes/DoE/pandas-sacct_v1.0.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-03-02", + "metadataLastUpdated": "2021-03-02" + }, + "description": "pandas-sacct is a small python utility which provides a pandas dataframe based interface to Slurm's accounting database.", + "laborHours": 0.0, + "languages": [], + "name": "pandas-sacct v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/pandas-sacct", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/pathwalk.json b/agency-indexes/DoE/pathwalk.json new file mode 100644 index 00000000..12e428ee --- /dev/null +++ b/agency-indexes/DoE/pathwalk.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "The pathwalk benchmark simulates the file system load created by path search.", + "laborHours": 167.2, + "languages": [], + "name": "pathwalk", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/pathwalk", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pcds-recipes.json b/agency-indexes/DoE/pcds-recipes.json new file mode 100644 index 00000000..98ee7da7 --- /dev/null +++ b/agency-indexes/DoE/pcds-recipes.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "Collection of conda recipes for PCDS software at LCLS.\n", + "laborHours": 425.6, + "languages": [], + "name": "pcds-recipes", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pcds-recipes/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pcds-recipes", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pcds_expresults.json b/agency-indexes/DoE/pcds_expresults.json new file mode 100644 index 00000000..c06075c5 --- /dev/null +++ b/agency-indexes/DoE/pcds_expresults.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "Maps URLs into experiment results folders after authz.\n", + "laborHours": 6779.2, + "languages": [], + "name": "pcds_expresults", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pcds_expresults", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pcircle_-_A_Suite_of_Scalable_Parallel_File_System_Tools.json b/agency-indexes/DoE/pcircle_-_A_Suite_of_Scalable_Parallel_File_System_Tools.json new file mode 100644 index 00000000..e3a8b403 --- /dev/null +++ b/agency-indexes/DoE/pcircle_-_A_Suite_of_Scalable_Parallel_File_System_Tools.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Most of the software related to file system are written for conventional local file system, they are serialized and can't take advantage of the benefit of a large scale parallel file system. \"pcircle\" software builds on top of ubiquitous MPI in cluster computing environment and \"work-stealing\" pattern to provide a scalable, high-performance suite of file system tools. In particular - it implemented parallel data copy and parallel data checksumming, with advanced features such as async progress report, checkpoint and restart, as well as integrity checking.", + "laborHours": 3085.6, + "name": "pcircle - A Suite of Scalable Parallel File System Tools", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL-TechInt/pcircle", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/perf-dump.json b/agency-indexes/DoE/perf-dump.json new file mode 100644 index 00000000..e83d77c8 --- /dev/null +++ b/agency-indexes/DoE/perf-dump.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "perf-dump is a library for dumping performance data in much the same way physics simulations dump checkpoints. It records per-process, per-timestep, per-phase, and per-thread performance counter data and dumps this large data periodically into an HDF5 data file.", + "laborHours": 334.4, + "name": "perf-dump", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/llnl/perf-dump", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/phdMesh.json b/agency-indexes/DoE/phdMesh.json new file mode 100644 index 00000000..4f613b55 --- /dev/null +++ b/agency-indexes/DoE/phdMesh.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Parallel Heterogeneous Dynamic unstructured Mesh (phdMesh) data structure library and integration testing code that performs dynamic load balancing of the data structure and parallel geometric proximity search on a contrived test problem. The phdMesh library is intended to be module within a finite element or finite volume library or code. The integration testing code is intended to provide a compact and highly portable performance evaluation code for parallel computing systems.", + "laborHours": 8344830.4, + "name": "phdMesh", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/Trilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/phenix_v._7.0.json b/agency-indexes/DoE/phenix_v._7.0.json new file mode 100644 index 00000000..32d1f052 --- /dev/null +++ b/agency-indexes/DoE/phenix_v._7.0.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-08", + "metadataLastUpdated": "2024-07-16" + }, + "description": "SAND2021-6741 O\nphenix is Sandia's orchestration tool that allows users to quickly deploy, un-deploy, and interact with SCEPTRE ICS environments. phenix is an orchestration tool used for managing the creation, configuration, and deployment of modeling and simulation environments. As an abstraction layer on top of an underlying virtual machine manager called minimega, phenix organizes the network, application, and scenario information for a given deployment. It allows users to create, configure, and deploy experiments in a repeatable and rapid fashion. An application framework provides the flexibility to manipulate an experiment to suit various needs and requirements. phenix also includes a web-based graphical user interface (GUI) where experiments can be created, configured, and interacted with.", + "laborHours": 131145.6, + "languages": [ + "Go", + "Javascript", + "Vue" + ], + "name": "phenix v. 7.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sceptre-phenix", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "7.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/picassodev_picasso.json b/agency-indexes/DoE/picassodev_picasso.json new file mode 100644 index 00000000..96761460 --- /dev/null +++ b/agency-indexes/DoE/picassodev_picasso.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "slatterysr@ornl.gov" + }, + "date": { + "created": "2021-02-17", + "metadataLastUpdated": "2021-02-17" + }, + "description": "Picasso is a C++ template library for the development of exascale-class particle-in-cell methods. It contains data structures for particle and grid management using the ECP Kokkos and Cabana libraries, abstractions for particle and grid discretizations, and tools for interface tracking and reconstruction with particles.", + "laborHours": 0.0, + "languages": [ + "C++" + ], + "name": "picassodev/picasso", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/picassodev/picasso", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pinacles.json b/agency-indexes/DoE/pinacles.json new file mode 100644 index 00000000..9f07f228 --- /dev/null +++ b/agency-indexes/DoE/pinacles.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-09-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Predicting Interactions of Aerosol and Clouds in Large Eddy Simulation (PINACLES) is a high-performance, massively\nparallel, anelastic atmospheric model written in Python", + "laborHours": 0.0, + "languages": [], + "name": "pinacles", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pinacles", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/plant_fba.json b/agency-indexes/DoE/plant_fba.json new file mode 100644 index 00000000..a8bc97f4 --- /dev/null +++ b/agency-indexes/DoE/plant_fba.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-10", + "metadataLastUpdated": "2020-09-10" + }, + "description": "GitHub repository and kb-sdk module for FBA applications involving plants.", + "laborHours": 1474.4, + "languages": [], + "name": "plant_fba", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/plant_fba", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/plexos-coad__Plexos_Class-Object-Attribute_Data_manipulation_tool_.json b/agency-indexes/DoE/plexos-coad__Plexos_Class-Object-Attribute_Data_manipulation_tool_.json new file mode 100644 index 00000000..c5b7db51 --- /dev/null +++ b/agency-indexes/DoE/plexos-coad__Plexos_Class-Object-Attribute_Data_manipulation_tool_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2019-05-22", + "metadataLastUpdated": "2019-05-22" + }, + "description": "Clean energy systems including the future power grid are enabled via the development, analysis and application of advanced simulation of complex systems based on large datasets. The ability to handle and enable the simulation of complex systems allows researchers and analysts to address significant problems with greater confidence and greater levels of integrity. Parallel execution of complex systems is paramount to addressing increasing complexity. Programmatic interfaces for software configuration and parallel execution enable handling greater complexity and improving simulation integrity. The Class Object Attribute Data (COAD) software is written as a programmatic interface to the PLEXOS dataset that enables the decomposition of the dataset in time and execution in parallel without loss of integrity. COAD also enable the recomposition of solution datasets that are the output of distributed parallel execution of the core simulator. 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The Pathway/Genome database (PGDB) can subsequently be curated manually\nLicensed under the CC-BY-4.0 license", + "laborHours": 106.4, + "languages": [], + "name": "pnnl-predictive-phenomics/csc052cyc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl-predictive-phenomics/csc052cyc", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/csc052cyc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl-predictive-phenomics_emll.json b/agency-indexes/DoE/pnnl-predictive-phenomics_emll.json new file mode 100644 index 00000000..7e8d8e5d --- /dev/null +++ b/agency-indexes/DoE/pnnl-predictive-phenomics_emll.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-04", + "metadataLastUpdated": "2025-02-04" + }, + "description": "This codebase was designed to tackle the problem of how to directly utilize experimental omics measurements with a\ngenome scale metabolic model of the organism of the study. 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"created": "2025-02-05", + "metadataLastUpdated": "2025-02-05" + }, + "description": "Code for implementing BMCA for Synechococcus elongatus", + "laborHours": 377689.6, + "languages": [], + "name": "pnnl-predictive-phenomics/syn_bmca", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl-predictive-phenomics/Syn_bmca", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_ADTKM.json b/agency-indexes/DoE/pnnl_ADTKM.json new file mode 100644 index 00000000..550f164f --- /dev/null +++ b/agency-indexes/DoE/pnnl_ADTKM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ADTKM Disruption Tolerant Key Management", + "laborHours": 2158.4, + "languages": [], + "name": "pnnl/ADTKM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ADTKM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_ANIMATE.json b/agency-indexes/DoE/pnnl_ANIMATE.json new file mode 100644 index 00000000..66233129 --- /dev/null +++ b/agency-indexes/DoE/pnnl_ANIMATE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A data-driven performance verification framework, which conducts automated output-based verification of building performance (especially control requirements which be only verified via time-series output)", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/ANIMATE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ANIMATE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_APTVIZ.json b/agency-indexes/DoE/pnnl_APTVIZ.json new file mode 100644 index 00000000..19dcbc0c --- /dev/null +++ b/agency-indexes/DoE/pnnl_APTVIZ.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-14", + "metadataLastUpdated": "2024-10-14" + }, + "description": "APT Clustering Visualizer", + "laborHours": 197.6, + "languages": [], + "name": "pnnl/APTVIZ", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/APTVIZ", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_ARTS.json b/agency-indexes/DoE/pnnl_ARTS.json new file mode 100644 index 00000000..d4e51804 --- /dev/null +++ b/agency-indexes/DoE/pnnl_ARTS.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-04-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Abstract RunTime System (ARTS) aims to provide different levels of abstraction that trade-off performance and programmability and helps to connect upper layers of the software stack with the different computational substrates.", + "laborHours": 10108.0, + "languages": [], + "name": "pnnl/ARTS", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ARTS", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_Active-Sampling-for-Atomistic-Potentials.json b/agency-indexes/DoE/pnnl_Active-Sampling-for-Atomistic-Potentials.json new file mode 100644 index 00000000..78307375 --- /dev/null +++ b/agency-indexes/DoE/pnnl_Active-Sampling-for-Atomistic-Potentials.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software contains a routine for active sampling of a DFT-generated dataset for training a neural network potential (SchNet). Major updates to the base SchNet code are also included to accommodate large systems (100s of atoms). We also provide code to apply the neural network potential in dynamic shear simulations.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Active-Sampling-for-Atomistic-Potentials", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Active-Sampling-for-Atomistic-Potentials", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_BIM2RDF.json b/agency-indexes/DoE/pnnl_BIM2RDF.json new file mode 100644 index 00000000..5bd86817 --- /dev/null +++ b/agency-indexes/DoE/pnnl_BIM2RDF.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-01-30", + "metadataLastUpdated": "2025-01-30" + }, + "description": "This software tool automatically creates the semantic model that building system applications need by leveraging data that exists in existing practice building design tools.", + "laborHours": 1170.4, + "languages": [], + "name": "pnnl/BIM2RDF", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/BIM2RDF", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_COMET.json b/agency-indexes/DoE/pnnl_COMET.json new file mode 100644 index 00000000..9580ec7d --- /dev/null +++ b/agency-indexes/DoE/pnnl_COMET.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-06-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "COMET: Domain Specific Compilation in Multi-level IR COMET is a compiler for dense and sparse tensor algebra and a domain-specific-language (DSL) that facilitates development and implementation of high-performance computing, graph analytics, and artificial intelligence (AI) applications.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/COMET", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/comet", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_CPACE.json b/agency-indexes/DoE/pnnl_CPACE.json new file mode 100644 index 00000000..8c26508f --- /dev/null +++ b/agency-indexes/DoE/pnnl_CPACE.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-12-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "C-PACE Market Assessment Tool This tool was developed for the U.S. Department of Energy\u2019s Commercial Property Assessed Clean Energy (C-PACE) Working Group to support state and local governments creating, joining, and implementing C-PACE programs. This tool allows users to input a jurisdiction (city, county, or state) and automate a report with building characteristics, energy use, and energy efficiency savings opportunities for commercial buildings in that jurisdiction. 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The three core regression techniques within this toolbox are classical least squares\n(CLS), principal component regression (PCR), and partial least squares (PLS). This is demonstrated using a supplied\ndataset of infrared (FTIR) spectral data with their corresponding concentrations", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Chemometric_Toolbox", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Chemometric_Toolbox", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_DM-Sim.json b/agency-indexes/DoE/pnnl_DM-Sim.json new file mode 100644 index 00000000..5ef02173 --- /dev/null +++ b/agency-indexes/DoE/pnnl_DM-Sim.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "DM-Sim: Quantum Simulator on GPU Cluster using Density Matrix: a new simulation approach that significantly reduces communication overhead.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/DM-Sim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/DM-Sim", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_DPVPROT.json b/agency-indexes/DoE/pnnl_DPVPROT.json new file mode 100644 index 00000000..e3f44400 --- /dev/null +++ b/agency-indexes/DoE/pnnl_DPVPROT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Distributed photovoltaics protection software toolkit The code package includes several important functions for design and analysis of new grid protection schemes, for scenarios of distributed photovoltaic (DPV) generation approaching 100% of the peak feeder load, i.e., high-penetration DPV. Convert distribution feeder models, used by planning engineers, to electromagnetic transient (EMT) models that produce waveforms for advanced relay algorithms. Visualize the results of protection scheme operation. Tools to determine distance relay settings on distribution systems. Tools to predict the performance of time-domain, incremental distance relay algorithms", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/DPVPROT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/DPVPROT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_Deep-Learning-Control-with-Embedded-Physical-Structure.json b/agency-indexes/DoE/pnnl_Deep-Learning-Control-with-Embedded-Physical-Structure.json new file mode 100644 index 00000000..4ad6a7ce --- /dev/null +++ b/agency-indexes/DoE/pnnl_Deep-Learning-Control-with-Embedded-Physical-Structure.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Framework that can produce visually compelling articles for project research. The design of our framework is centered around simplifying content creation so that researchers unfamiliar with the underlying technology stack can still produce informative, beautiful research documents with interactive and visual features.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Deep-Learning-Control-with-Embedded-Physical-Structure", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Deep-Learning-Control-with-Embedded-Physical-Structure", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_DeepDataProfiler.json b/agency-indexes/DoE/pnnl_DeepDataProfiler.json new file mode 100644 index 00000000..38d26b9c --- /dev/null +++ b/agency-indexes/DoE/pnnl_DeepDataProfiler.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-06-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python library for analyzing the internal structure of deep neural networks.", + "laborHours": 22374.4, + "languages": [ + "Python" + ], + "name": "pnnl/DeepDataProfiler", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/deepdataprofiler", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_EELSTM.json b/agency-indexes/DoE/pnnl_EELSTM.json new file mode 100644 index 00000000..e38c7508 --- /dev/null +++ b/agency-indexes/DoE/pnnl_EELSTM.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "EELSTM: Time Series Prediction on Electron Energy Loss Spectra - long short-term memory model approach to forecasting of electron energy loss spectroscopy, based on a Bayesian deep learning model", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/EELSTM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/EELSTM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_EXPERT.json b/agency-indexes/DoE/pnnl_EXPERT.json new file mode 100644 index 00000000..e8cdce72 --- /dev/null +++ b/agency-indexes/DoE/pnnl_EXPERT.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-08-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The EXPERT toolkit contains next-gen AI capabilities to detect, anticipate, and reason about proliferation expertise evolution from unstructured dynamic multilingual real-world data.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/EXPERT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/EXPERT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_EXPERT2.json b/agency-indexes/DoE/pnnl_EXPERT2.json new file mode 100644 index 00000000..27a40560 --- /dev/null +++ b/agency-indexes/DoE/pnnl_EXPERT2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-10-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software includes the Jupyter notebooks, model pretraining and evaluation code for the EXPERT 2.0 Human-AI\nReasoning Engine V0.1. It supports pre-training a Human-AI model for reasoning over multi-layer network representations.\nIt includes prompt-based evaluation framework in a Jupyter notebook for AI reasoning and Jupyter widgets with AI-based\ntechniques for evidence generation and uncertainty quantification to support human-AI reasoning.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/EXPERT2", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/EXPERT2", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_EZBattery.json b/agency-indexes/DoE/pnnl_EZBattery.json new file mode 100644 index 00000000..a34b11cc --- /dev/null +++ b/agency-indexes/DoE/pnnl_EZBattery.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-10-04", + "metadataLastUpdated": "2024-10-04" + }, + "description": "Cell performance optimization is important for improving the system efficiency of a redox flow battery. To gain better insights into key controlling factors Of system efficiency, this work first proposed a theoretical model for a unit cell by extending a two-dimensional analytic model to a full cell. The model is then used for cell performance optimization after validating it with experimental and numerical modeling data.", + "laborHours": 1808.8, + "languages": [], + "name": "pnnl/EZBattery", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/EZBattery", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_EyeSea.json b/agency-indexes/DoE/pnnl_EyeSea.json new file mode 100644 index 00000000..9230ee02 --- /dev/null +++ b/agency-indexes/DoE/pnnl_EyeSea.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-20", + "metadataLastUpdated": "2025-02-20" + }, + "description": "Underwater video analysis software.", + "laborHours": 13771.2, + "languages": [], + "name": "pnnl/EyeSea", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/EyeSea", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_FLOWER.json b/agency-indexes/DoE/pnnl_FLOWER.json new file mode 100644 index 00000000..14e27011 --- /dev/null +++ b/agency-indexes/DoE/pnnl_FLOWER.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-05-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Network FLOW analyzER - Network bi-directional deep packet header inspection. This software is designed to generate custom network flow records by monitoring bi-directional traffic from a span port, tap or other source. This function is independent of proprietary hardware or software solutions. This tool solves the problem of existing COTS solutions being either too complex or too slow.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/FLOWER", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/FLOWER", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_FermionicSwap.json b/agency-indexes/DoE/pnnl_FermionicSwap.json new file mode 100644 index 00000000..095cf125 --- /dev/null +++ b/agency-indexes/DoE/pnnl_FermionicSwap.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-09-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The software allows rapid development of simulations using the fermionic swap method on Microsoft's Quantum\nDevelopment Kit (QDK) framework. Gate, circuit, etc. costs can be estimated using Microsoft's resource estimator", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/FermionicSwap", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/FermionicSwap", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_FlexyAirDeepMPC.json b/agency-indexes/DoE/pnnl_FlexyAirDeepMPC.json new file mode 100644 index 00000000..40882f2d --- /dev/null +++ b/agency-indexes/DoE/pnnl_FlexyAirDeepMPC.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-03-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a trained machine learning model written in Pytorch for automated control of the FlexyAir\n(https://ocl.sk/hardware/flexyair/) dynamical system control educational device. This software is to be released to support our demonstration of our deepMPC methods on embedded hardware to control a real (albeit tutorial) physical system with control actuators.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/FlexyAirDeepMPC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/FlexyAirDeepMPC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_Forte.json b/agency-indexes/DoE/pnnl_Forte.json new file mode 100644 index 00000000..eb212cb4 --- /dev/null +++ b/agency-indexes/DoE/pnnl_Forte.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-10-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Interactive user-interface application for deep probabilistic day-ahead net-load forecasting. This application allows a utility\noperator and/or other end-user to access through an easy interface the powers of advanced deep AI/ML algorithms for\ngenerating day-ahead probabilistic forecast of net-load. Also known as \"VRN3P\"", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Forte", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Forte", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_GeoCLUSTER.json b/agency-indexes/DoE/pnnl_GeoCLUSTER.json new file mode 100644 index 00000000..44c0bc96 --- /dev/null +++ b/agency-indexes/DoE/pnnl_GeoCLUSTER.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "GeoCLUSTER is a Python-based web application that provides a collection of interactive methods for streamlining the visualization of the technical and economic modeling of closed-loop geothermal systems.", + "laborHours": 4240.8, + "languages": [], + "name": "pnnl/GeoCLUSTER", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/GeoCLUSTER", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_HNSRigidBodySimulator.json b/agency-indexes/DoE/pnnl_HNSRigidBodySimulator.json new file mode 100644 index 00000000..dfb969cf --- /dev/null +++ b/agency-indexes/DoE/pnnl_HNSRigidBodySimulator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "HNS Rigid Body Simulatoris a tool for performing rigid-body dynamics simulations of nanoscale systems (e.g., macromolecular\nassemblies) in Python.", + "laborHours": 988.0, + "languages": [], + "name": "pnnl/HNSRigidBodySimulator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/HNSRigidBodySimulator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_Haskell-IDF-Executable.json b/agency-indexes/DoE/pnnl_Haskell-IDF-Executable.json new file mode 100644 index 00000000..dbe2604a --- /dev/null +++ b/agency-indexes/DoE/pnnl_Haskell-IDF-Executable.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-03-06", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Executables for working with EnergyPlus Input Files (IDF) This project aims to provide a suite of executables for working with EnergyPlus Input Files (IDF). The project is developed using the Haskell programming language (c.f., https://www.haskell.org/).\nThe current release (version 0.1.0.0) includes a utility that \"pretty prints\" the input file (i.e., that decodes and then, immediately, re-encodes and displays the input file, viz., that sanitizes the input) and a utility that converts the input file into\na labeled graph in the DOT language (c.f., https://www.graphviz.org/doc/info/lang.html) for subsequent rendering using\nGraphviz Visualization Software (c.f., https://www.graphviz.org/).\n\nAn example workflow is to pipe the input file into the pretty printer, to pipe the result into the labeled graph converter, and then to pipe the result into Graphviz, yielding an image file that depicts the hierarchical and referential relationships between EnergyPlus Data Dictionary (IDD) classes that are detected within the input file.", + "laborHours": 152.0, + "languages": [], + "name": "pnnl/Haskell-IDF-Executable", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Haskell-IDF-Executable", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_HiParTI.json b/agency-indexes/DoE/pnnl_HiParTI.json new file mode 100644 index 00000000..925612d6 --- /dev/null +++ b/agency-indexes/DoE/pnnl_HiParTI.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Hierarchical Parallel Tensor Infrastructure (HiParTI), is to support fast essential sparse tensor operations and tensor decompositions on multicore CPU and GPU architectures. It consists of sparse tensor decompositions, CANDECOMP/PARAFAC (CP) and Tucker decompositions, fundamental tensor operations, and tensor transformations", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/HiParTI", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/HiParTI", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_HyperNetX.json b/agency-indexes/DoE/pnnl_HyperNetX.json new file mode 100644 index 00000000..64951df6 --- /dev/null +++ b/agency-indexes/DoE/pnnl_HyperNetX.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-01-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "HyperNetX is a Python library of classes, algorithms, and generators for working with multi-way and nested relational data. Given a network of nodes and relationships, the base class HyperNetX.Entity is used to instantiate individual data elements along with their relationships to other elements of the network. By exploiting Python's dictionary data structure we capture both multi-way and nested data structures with constant time lookup. The base class HyperNetX.Hypergraph instantiates a network of this data into a hypergraph structure. Many of the common metrics and features of graphs, such as diameter, connectedness, and clustering coefficient, have analogous definitions with respect to hypergraphs, which are computed using algorithms in the HyperNetX library.", + "laborHours": 14789.6, + "languages": [ + "Python" + ], + "name": "pnnl/HyperNetX", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/HyperNetX", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_HypoGen.json b/agency-indexes/DoE/pnnl_HypoGen.json new file mode 100644 index 00000000..8cb96d39 --- /dev/null +++ b/agency-indexes/DoE/pnnl_HypoGen.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-01-29", + "metadataLastUpdated": "2025-01-29" + }, + "description": "An innovative workflow for automatic knowledge discovery in material science, combining experimental\nautomation with advanced machine learning and artificial intelligence techniques", + "laborHours": 851.2, + "languages": [], + "name": "pnnl/HypoGen", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/hypogen", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_IMIC.json b/agency-indexes/DoE/pnnl_IMIC.json new file mode 100644 index 00000000..8290ae08 --- /dev/null +++ b/agency-indexes/DoE/pnnl_IMIC.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-12-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The first step toward the design of good error detection/correction techniques involves an understanding of an application\u2019s vulnerability to soft errors.\nTo study the behavior of iterative methods in the presence of soft errors, we inject errors during the execution of these methods. In particular, we study the impact of one error (single- or multi-bit) on the execution of iterative methods. We use real life datasets from the SuiteSparse Matrix Collection (https://sparse.tamu.edu) and widely used iterative solver library (Iterative Methods Library, IML++ v1.2a). We instrument the iterative solver implementations so that our error injection methodology can control the iteration, vector, position, number of bits and position of the bits of the error injection. We employed 6 solvers and 28 datasets, performed a total of 1,744,800 error injection runs and collected more than 2.5TB data.", + "laborHours": 60.8, + "languages": [], + "name": "pnnl/IMIC", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/IMIC", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_JAX-CanVeg.json b/agency-indexes/DoE/pnnl_JAX-CanVeg.json new file mode 100644 index 00000000..3004ce9a --- /dev/null +++ b/agency-indexes/DoE/pnnl_JAX-CanVeg.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-09-26", + "metadataLastUpdated": "2024-09-26" + }, + "description": "Differentiable land surface model reimplementing an existing simulator, CANOAK, in JAX\u2014a Google-developed Python package for high-performance machine learning research using automatic differentiation. The model's\npurpose is to perform hybrid land surface modeling that seamlessly couples process-based components with deep neural\nnetworks", + "laborHours": 18118.4, + "languages": [], + "name": "pnnl/JAX-CanVeg", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/JAX-CanVeg", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_LAP.json b/agency-indexes/DoE/pnnl_LAP.json new file mode 100644 index 00000000..baa25fef --- /dev/null +++ b/agency-indexes/DoE/pnnl_LAP.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "A software framework to study, from the performance and energy perspective, the efficacy of GPU-resident\nparallel Conjugate Gradient (CG) linear solver with different preconditioner options, including Gauss-Seidel, Jacobi, and\nincomplete Cholesky. We also propose a novel GPU-based preconditioner, in which the triangular solves are approximated\nby an iterative process", + "laborHours": 3556.8, + "languages": [], + "name": "pnnl/LAP", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/LAP", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "LAP v 2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_Lagrangian-Droplets.json b/agency-indexes/DoE/pnnl_Lagrangian-Droplets.json new file mode 100644 index 00000000..da9d268b --- /dev/null +++ b/agency-indexes/DoE/pnnl_Lagrangian-Droplets.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-18", + "metadataLastUpdated": "2025-02-18" + }, + "description": "The Lagrangian Droplet cloud microphysics scheme uses high-resolution data of air velocity, temperature, and water\nvapor mixing ratio to drive particle-based simulations of cloud microphysics. The model was first implemented using a\nhigh-resolution Large Eddy Simulation of the Pi Chamber at Michigan Tech, which is small-scale convection chamber the\ngenerates clouds in a laboratory setting", + "laborHours": 820.8, + "languages": [], + "name": "pnnl/Lagrangian-Droplets", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Lagrangian-Droplets", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_MBDRL.json b/agency-indexes/DoE/pnnl_MBDRL.json new file mode 100644 index 00000000..37e3be3f --- /dev/null +++ b/agency-indexes/DoE/pnnl_MBDRL.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-11-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Model-based Deep Reinforcement Learning for Real-time Grid Emergency Voltage Control. A model-based Deep Reinforcement Learning (DRL) framework where a deep neural network (DNN)-based\nsurrogate model is utilized within the control policy learning framework, making the learning process faster and more\nsample efficient", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/MBDRL", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/MBDRL", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_MCOR.json b/agency-indexes/DoE/pnnl_MCOR.json new file mode 100644 index 00000000..0b8f72b2 --- /dev/null +++ b/agency-indexes/DoE/pnnl_MCOR.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Microgrid Component Optimization for Resiliency Tool (MCOR) The MCOR tool provides several viable microgrid configurations that can meet the resilience goals of a site and maximize economic benefits.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/MCOR", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/MCOR", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_MCRASTA.json b/agency-indexes/DoE/pnnl_MCRASTA.json new file mode 100644 index 00000000..b624181d --- /dev/null +++ b/agency-indexes/DoE/pnnl_MCRASTA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-01-30", + "metadataLastUpdated": "2025-02-04" + }, + "description": "McRasta (Markov Chain Rate and State Analysis) was developed to estimate parameter uncertainty in constitutive friction\nmodels via Bayesian inverse and Markov Chain Monte Carlo (MCMC) methods.", + "laborHours": 912.0, + "languages": [], + "name": "pnnl/MCRASTA", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/MCRASTA", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_MemFriend.json b/agency-indexes/DoE/pnnl_MemFriend.json new file mode 100644 index 00000000..80e428f3 --- /dev/null +++ b/agency-indexes/DoE/pnnl_MemFriend.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-09-11", + "metadataLastUpdated": "2024-10-25" + }, + "description": "MemFriend was developed to focus on providing a comprehensive view of access patterns by analysing spatial-temporal\nlocality between pairs of memory locations. It is intended to aid in data layout optimizations, and data placement decisions.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/MemFriend", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/memgaze", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_Multimodal-Few-Shot.json b/agency-indexes/DoE/pnnl_Multimodal-Few-Shot.json new file mode 100644 index 00000000..fac1eec4 --- /dev/null +++ b/agency-indexes/DoE/pnnl_Multimodal-Few-Shot.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This project combines few-shot machine learning with a multimodal framework for electron microscope data quantification.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Multimodal-Few-Shot", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Multimodal-Few-Shot", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_NEURALMIE.json b/agency-indexes/DoE/pnnl_NEURALMIE.json new file mode 100644 index 00000000..e3b71601 --- /dev/null +++ b/agency-indexes/DoE/pnnl_NEURALMIE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-11", + "metadataLastUpdated": "2024-11-11" + }, + "description": "NeuralMie was developed to improve the representation of aerosol optical properties in E3SM, the DOE's Earth system\nmodel. NeuralMie is able to closely emulate numerical solutions to the problem at a fraction of the computational cost.\nTAMie was written to generate training data for NeuralMie.", + "laborHours": 182.4, + "languages": [], + "name": "pnnl/NEURALMIE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/NEURALMIE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_NWGraph.json b/agency-indexes/DoE/pnnl_NWGraph.json new file mode 100644 index 00000000..da37da43 --- /dev/null +++ b/agency-indexes/DoE/pnnl_NWGraph.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-06-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "NWGraph aims to fill the role of a reusable library of generic graph algorithms for C++,\nsimilar to the algorithms available in the standard template library (STL) in C++.\nThe library draws lessons learned from Boost Graph Library (BGL) and other libraries (PBGL,\nGalois, Gunrock, GraphX etc.), the evolution of the C++ language, and the evolution of C++\npractice over the last 20 years.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/NWGraph", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/NWGraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_NWHypergraph.json b/agency-indexes/DoE/pnnl_NWHypergraph.json new file mode 100644 index 00000000..b3b0eec6 --- /dev/null +++ b/agency-indexes/DoE/pnnl_NWHypergraph.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-06-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "NWHypergraph is a C++ hypergraph processing framework for shared-memory architecture. NWHypergraph provides\nefficient algorithms to construct s-line graphs, a lower-order approximation of a given hypergraph, and computes different\ngraph metrics of a s-line graph such as s-connected components, s-betweenness centrality, s-closeness centrality, etc. It\nalso provides Python APIs for s-line graph computation. The Python APIs are provided using Pybind11", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/NWHypergraph", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/NWHypergraph", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_Netviz.json b/agency-indexes/DoE/pnnl_Netviz.json new file mode 100644 index 00000000..2846b5b7 --- /dev/null +++ b/agency-indexes/DoE/pnnl_Netviz.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-04-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "NetViz is an app built to visualize communication and power networks. Developed under the CINDER project at PNNL.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Netviz", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Netviz", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_OpenCGRA.json b/agency-indexes/DoE/pnnl_OpenCGRA.json new file mode 100644 index 00000000..22c87890 --- /dev/null +++ b/agency-indexes/DoE/pnnl_OpenCGRA.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "OpenCGRA is an open-source framework for modeling, testing, and evaluating CGRAs. The first open-source integrated framework able to support the full top-to-bottom design flow for specializing and implementing CGRAs: modeling at different abstraction levels (functional level, cycle level, register-transfer level) with compiler support, verification at different granularities (unit testing, integration testing, property-based testing), simulation, generation of synthesizable Verilog, and characterization (area, power, and timing).", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/OpenCGRA", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/OpenCGRA", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_PHANTOM.json b/agency-indexes/DoE/pnnl_PHANTOM.json new file mode 100644 index 00000000..d53a53af --- /dev/null +++ b/agency-indexes/DoE/pnnl_PHANTOM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A topology-based anomaly detection tool for temporal varying data. The input is json or CSV formatted data with a timestamp field identified. The algorithm computes vectorizations (using a vectorization config file) of time windows of data and computes a topological measure of anomalousness. The output is a sequence of anomaly scores for each time window", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/PHANTOM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/PHANTOM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_PTMPSI.json b/agency-indexes/DoE/pnnl_PTMPSI.json new file mode 100644 index 00000000..f93daa48 --- /dev/null +++ b/agency-indexes/DoE/pnnl_PTMPSI.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-07-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PTM-Psi is a Python 3 package that combines several capabilities to streamline the workflow to interrogate the impact of\nPTMs on proteins using well-established software packages. The workflow of the PTM-Psi software package includes\ninput files and launch instances from standard packages such as AlphaFold, NWChem, GROMACS, and the Autodock\nSuite", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/PTMPSI", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ptmpsi", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_Pathway_Controlled_Optimization.json b/agency-indexes/DoE/pnnl_Pathway_Controlled_Optimization.json new file mode 100644 index 00000000..e1bdbeb0 --- /dev/null +++ b/agency-indexes/DoE/pnnl_Pathway_Controlled_Optimization.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A method for prediction of cell regulation to maximize cell growth rate while maintaining the solvent capacity\nof the cell. Prediction is formulated as an optimization problem using a thermodynamic framework that can leverage\nexperimental data. We develop a formulation and variable initialization procedure that allows for computing solutions of\nthe optimization with an interior point method", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Pathway_Controlled_Optimization", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Pathway_Controlled_Optimization", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_PolyCheck.json b/agency-indexes/DoE/pnnl_PolyCheck.json new file mode 100644 index 00000000..9f80be60 --- /dev/null +++ b/agency-indexes/DoE/pnnl_PolyCheck.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-07-19", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The program employs a novel approach to assess the correctness of arbitrary iteration reordering transformations on an affine program, including non-affine transformations.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/PolyCheck", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/PolyCheck", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_QASMBench.json b/agency-indexes/DoE/pnnl_QASMBench.json new file mode 100644 index 00000000..c57174b9 --- /dev/null +++ b/agency-indexes/DoE/pnnl_QASMBench.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-06-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A low-level OpenQASM benchmark suite for NISQ evaluation and simulation. Please see our paper for details.\nn this repository you will find a low-level and light-weighted benchmark suite based on IBM OpenQASM language (see spec). It collects commonly seen quantum algorithms and routines from various domains including chemistry, simulation, linear algebra, searching, optimization, arithmetic, machine learning, fault tolerance, cryptography, etc. QASMBench trades-off between generality and usability, covering the number of qubits ranging from 2 to 60K, and the circuit depth from 4 to 12M", + "laborHours": 4666.4, + "languages": [], + "name": "pnnl/QASMBench", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/QASMBench", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_Remote-QA-Web-App.json b/agency-indexes/DoE/pnnl_Remote-QA-Web-App.json new file mode 100644 index 00000000..5345e571 --- /dev/null +++ b/agency-indexes/DoE/pnnl_Remote-QA-Web-App.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-05-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "set of data collection forms implemented as a web app to be used for quality assurance purposes by residential efficiency contractors during the installation process. There are data collection forms for several efficiency measures including heat pump, heat pump water heater, attic weatherization, and basement weatherization.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Remote-QA-Web-App", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Remote-QA-Web-App", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_Rooftop-Unit-LCI-Template.json b/agency-indexes/DoE/pnnl_Rooftop-Unit-LCI-Template.json new file mode 100644 index 00000000..8bc23dd5 --- /dev/null +++ b/agency-indexes/DoE/pnnl_Rooftop-Unit-LCI-Template.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-25", + "metadataLastUpdated": "2025-02-25" + }, + "description": "A content repository for the life cycle inventory (LCI) rooftop unit (RTU) data collection template, a data collection template for the linked openLCA model Life Cycle Assessment (LCA) for automated Environmental Product Declaration (EPD) results generation.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Rooftop-Unit-LCI-Template", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Rooftop-Unit-LCI-Template", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_SAMIAm.json b/agency-indexes/DoE/pnnl_SAMIAm.json new file mode 100644 index 00000000..4d11119f --- /dev/null +++ b/agency-indexes/DoE/pnnl_SAMIAm.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-20", + "metadataLastUpdated": "2024-11-20" + }, + "description": "We apply semantic\nboosting to the Segment Anything Model (SAM) to obtain microstructure segmentation for transmission electron\nmicroscopy. Our booster, SAM-I-Am, extracts geometric and textural features of various intermediate masks to perform\nmask removal and mask merging operations", + "laborHours": 1155.2, + "languages": [], + "name": "pnnl/SAMIAm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SAMIAm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_SHAD.json b/agency-indexes/DoE/pnnl_SHAD.json new file mode 100644 index 00000000..a707920d --- /dev/null +++ b/agency-indexes/DoE/pnnl_SHAD.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-02", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Scalable High-performance Algorithms and Data-structures.\nScalable High-performance Algorithms and Data-structures (SHAD) is an application programming interface based on a generic software library. It has a modular design that enables reuse of modules. The core of this software tool set is built on an Abstract Runtime interface and it's library includes the common data structures such as array, vector, map and set. It is designed to accommodate significant amount of data which can be accessed in massively parallel environments, and used as building blocks for SHAD extensions, i.e. higher level software libraries.", + "laborHours": 13573.6, + "languages": [], + "name": "pnnl/SHAD", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SHAD", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_SLiCE.json b/agency-indexes/DoE/pnnl_SLiCE.json new file mode 100644 index 00000000..ce715b00 --- /dev/null +++ b/agency-indexes/DoE/pnnl_SLiCE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Subgraph Based Learning of Contextual Embedding\na framework bridging static representation learning methods using global information from the entire graph with localized attention driven mechanisms to learn contextual node representations.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/SLiCE", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SLiCE", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_SNAP.json b/agency-indexes/DoE/pnnl_SNAP.json new file mode 100644 index 00000000..b180118a --- /dev/null +++ b/agency-indexes/DoE/pnnl_SNAP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-25", + "metadataLastUpdated": "2025-03-25" + }, + "description": "In this work, we detail two uncertainty quantification (UQ) methods that provide complementary information. Readout\nensembling, by finetuning only the readout layers of an ensemble of foundation models, provides information about model\nuncertainty. Amending the final readout layer to predict upper and lower quantiles replaces point predictions with\ndistributional predictions, which provide information about uncertainty within the underlying training data. We\ndemonstrate our approach with the MACE-MP-0 model, applying UQ to both the foundation model and a series of finetuned\nmodels. The uncertainties produced by the ensemble and quantile methods are demonstrated to be distinct measures by\nwhich the quality of the NNP output can be judged.", + "laborHours": 33485.6, + "languages": [], + "name": "pnnl/SNAP", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/snap", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_SOSAT.json b/agency-indexes/DoE/pnnl_SOSAT.json new file mode 100644 index 00000000..f0698288 --- /dev/null +++ b/agency-indexes/DoE/pnnl_SOSAT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "State of Stress Analysis Tool (for carbon sequestration). The SOSAT tool provides value during GCS site screening and characterization phases to target collection of specific additional data to constrain uncertainties in geomechanical risk and to help operators to make informed decisions during the operational phase (Appriou et al., 2019). The capability represented in SOSAT, therefore, helps build stakeholder confidence that geomechanical risks are understood and manageable", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/SOSAT", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SOSAT", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_SciTune.json b/agency-indexes/DoE/pnnl_SciTune.json new file mode 100644 index 00000000..3a364dae --- /dev/null +++ b/agency-indexes/DoE/pnnl_SciTune.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-01-23", + "metadataLastUpdated": "2025-01-23" + }, + "description": "Scientific multimodal instruction tuning with large language and vision models.", + "laborHours": 6688.0, + "languages": [], + "name": "pnnl/SciTune", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/scitune", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_SuperSAM.json b/agency-indexes/DoE/pnnl_SuperSAM.json new file mode 100644 index 00000000..2b710731 --- /dev/null +++ b/agency-indexes/DoE/pnnl_SuperSAM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-20", + "metadataLastUpdated": "2024-12-13" + }, + "description": "Our SuperSAM approach transforms the\nSegment Anything Model (SAM) into an `elastic' supernetwork, enabling the derivation of subnetworks with\nvarying architectures tailored to a wide range of resource constraints.", + "laborHours": 3663.2, + "languages": [], + "name": "pnnl/SuperSAM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SuperSAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_TCBNN.json b/agency-indexes/DoE/pnnl_TCBNN.json new file mode 100644 index 00000000..de543050 --- /dev/null +++ b/agency-indexes/DoE/pnnl_TCBNN.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-07-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "New bit capability for GPUs, bit-tensor-core.", + "laborHours": 4894.4, + "languages": [], + "name": "pnnl/TCBNN", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/TCBNN", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_Temwizard.json b/agency-indexes/DoE/pnnl_Temwizard.json new file mode 100644 index 00000000..51b0a679 --- /dev/null +++ b/agency-indexes/DoE/pnnl_Temwizard.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-24", + "metadataLastUpdated": "2024-06-18" + }, + "description": "TEMWizard is used to visualize results from Atomap, an open-source software tool for determining the position and other features of atomic columns in transmission electron microscopy images.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/Temwizard", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/Temwizard", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_TransMED.json b/agency-indexes/DoE/pnnl_TransMED.json new file mode 100644 index 00000000..5a1cc393 --- /dev/null +++ b/agency-indexes/DoE/pnnl_TransMED.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Transfer Learning From Existing Diseases Via Hierarchical Multi-Modal BERT Models", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/TransMED", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/TransMED", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_UUDEX.json b/agency-indexes/DoE/pnnl_UUDEX.json new file mode 100644 index 00000000..1563e1af --- /dev/null +++ b/agency-indexes/DoE/pnnl_UUDEX.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "UUDEX describes a communications architecture and protocol suite that allows organizations to exchange data and information. It does this by defining relations between a set of client nodes that share data via a set of server nodes. The primary focus of UUDEX is to facilitate communications between control centers, operations centers, and other trusted organization.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/UUDEX", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/UUDEX", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_UrbanBEM.json b/agency-indexes/DoE/pnnl_UrbanBEM.json new file mode 100644 index 00000000..2adbc09d --- /dev/null +++ b/agency-indexes/DoE/pnnl_UrbanBEM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-17", + "metadataLastUpdated": "2025-02-17" + }, + "description": "a new urban scale building energy simulation framework", + "laborHours": 28636.8, + "languages": [], + "name": "pnnl/UrbanBEM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/UrbanBEM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_ZebrafishBMD.json b/agency-indexes/DoE/pnnl_ZebrafishBMD.json new file mode 100644 index 00000000..90f6fe72 --- /dev/null +++ b/agency-indexes/DoE/pnnl_ZebrafishBMD.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ZebrafishBMD: A software tool to perform benchmark dose calculations using toxicity screening data of high-throughput zebrafish assays.\nHigh-content imaging of larval zebrafish behavior can be used as a screening approach to rapidly evaluate the relative potential for chemicals to cause toxicity. However, most statistical methods applied to these data transform movement values to incidence-based \u201chits\u201d and calculate lowest effect levels (LELs), which loses individual fish resolution of behavior and defies hazard ranking due to reliance on applied dose levels. We developed a parallelizable workflow to calculate benchmark dose (BMD) values from dynamic, high-content zebrafish behavior data that scales for high throughput chemical screening. To capture the zebrafish movement response from light to dark stimulus, we summarized time-dependent data using both area under the curve and the immediate change at the transition point into two novel metrics that characterized abnormal behavior as a function of chemical concentration. The BMD workflow was applied to calculate BMD10 values of 1,060 ToxCast chemicals for 24 zebrafish endpoints, including behavior, mortality and morphology.\nZebrafishBMD implements the BMD workflow and provides Matlab scripts to read the data (stored in a specific structure) from a .mat file, to calculate the behavioral endpoint values from movement versus time data, to construct concentrationresponse\ncurves, to perform curve-fitting, and to calculate BMD10 values.", + "laborHours": 15.2, + "languages": [], + "name": "pnnl/ZebrafishBMD", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ZebrafishBMD", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_apt.json b/agency-indexes/DoE/pnnl_apt.json new file mode 100644 index 00000000..eea38b53 --- /dev/null +++ b/agency-indexes/DoE/pnnl_apt.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-10-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The current scripts utilize a well-known cluster analysis algorithm, called ordering points to identify the clustering structures (OPTICS), and an automatic cluster extraction algorithm for clustering analysis of 3D spatial data, specifically for the Atom Probe Tomography data. A hierarchical clustering scheme, together with density-based clustering, were implemented.", + "laborHours": 1778.4, + "languages": [], + "name": "pnnl/apt", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/apt", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_archive-sprinter.json b/agency-indexes/DoE/pnnl_archive-sprinter.json new file mode 100644 index 00000000..f85ad8ff --- /dev/null +++ b/agency-indexes/DoE/pnnl_archive-sprinter.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Archive Sprinter tool is designed to efficiently process synchrophasor measurements from electric power grids and\nexport data signatures that summarize the grid's behavior. Parallel processing will allow data to be processed quickly to\nenable practical analyses of archives spanning years. The grid's behavior will be summarized using a wide-array of\nsignatures calculated from the input data.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/archive-sprinter", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/archive-sprinter", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_archive_walker.json b/agency-indexes/DoE/pnnl_archive_walker.json new file mode 100644 index 00000000..e191bf4d --- /dev/null +++ b/agency-indexes/DoE/pnnl_archive_walker.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Archive Walker Software to read and examine PMU data to detect events and conditions for further analysis.", + "laborHours": 219837.6, + "languages": [], + "name": "pnnl/archive_walker", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/archive_walker", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_arena.json b/agency-indexes/DoE/pnnl_arena.json new file mode 100644 index 00000000..461d1db1 --- /dev/null +++ b/agency-indexes/DoE/pnnl_arena.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-06-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "CFA ARENA is a novel programming model with the support of a runtime targeting asynchronous data-centric execution paradigm in a distributed system. All the machine nodes in ARENA are connected by a ring network to bring the specialized computation to the data rather than the reverse to minimize data movement. The programming interfaces are implemented using C++", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/arena", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/arena", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_battery-degradation-prognosis.json b/agency-indexes/DoE/pnnl_battery-degradation-prognosis.json new file mode 100644 index 00000000..5ed9c63c --- /dev/null +++ b/agency-indexes/DoE/pnnl_battery-degradation-prognosis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-21", + "metadataLastUpdated": "2025-03-21" + }, + "description": "This is a tool for long term prognosis of redox flow battery parameter degradation which uses Transformer-based deep\nlearning models for time series forecasting which was developed as part of the ROVI project.", + "laborHours": 19592.8, + "languages": [], + "name": "pnnl/battery-degradation-prognosis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/battery-degradation-prognosis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_biota.json b/agency-indexes/DoE/pnnl_biota.json new file mode 100644 index 00000000..e3b60ae8 --- /dev/null +++ b/agency-indexes/DoE/pnnl_biota.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-10-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Fortran 90 source code and an example problem for the Toolkit for Integrated Impact Assessments (TIIA).", + "laborHours": 35780.8, + "languages": [], + "name": "pnnl/biota", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/biota", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_blueprint-styler.json b/agency-indexes/DoE/pnnl_blueprint-styler.json new file mode 100644 index 00000000..9b8b35f4 --- /dev/null +++ b/agency-indexes/DoE/pnnl_blueprint-styler.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-01-31", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Make custom blueprint.css styles A framework for creating custom visual themes and styles for the Blueprintjs React component library: https://blueprintjs.com/docs/ Features create custom css themes and styles for Blueprintjs components visualize the effect of the custom styles during development publish an example application that includes all available themes: https://stash.pnnl.gov/pages/UXRSRC/blueprint-styler/master/browse/build/index.html publish the compiled theme to npm (or artifactory)", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/blueprint-styler", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/blueprint-styler", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_brain_ohsu.json b/agency-indexes/DoE/pnnl_brain_ohsu.json new file mode 100644 index 00000000..37bbd21c --- /dev/null +++ b/agency-indexes/DoE/pnnl_brain_ohsu.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-10-04", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Light sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as\nthe entire mouse brain. We fine-tuned an existing model, TrailMap, using expert labeled data from axonal structures in neocortex. Without\nchanging the network architecture, we implemented nnU-Net framework modifications in data augmentation, data\nforeground sampling, window learning rate, and the inference overlap method. The resulting model from these combined\napproaches yielded an improved F1 score", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/brain_ohsu", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/brain_ohsu", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_building-energy-standards-data.json b/agency-indexes/DoE/pnnl_building-energy-standards-data.json new file mode 100644 index 00000000..8baaaa06 --- /dev/null +++ b/agency-indexes/DoE/pnnl_building-energy-standards-data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-12-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Database of building energy standards data for building energy simulation.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/building-energy-standards-data", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/building-energy-standards-data", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_building_sync_rails.json b/agency-indexes/DoE/pnnl_building_sync_rails.json new file mode 100644 index 00000000..25e2549e --- /dev/null +++ b/agency-indexes/DoE/pnnl_building_sync_rails.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "BuildingSyncRails is a library for the Ruby on Rails [1] web application development framework that leverages the Isomorphic library for the Ruby programming language (IPID Submission #11610) in order to provide BuildingSync [2] XML capabilities to Ruby on Rails applications. BuildingSyncRails provides the following capabilities:\nCapability to download the most recent version of the BuildingSync XML schema document from GitHub and to automatically convert said document into Ruby code.\nToolkit for constructing and manipulating Ruby objects that represent BuildingSync XML elements.\nBuildingSyncRails builds upon the capabilities of the Isomorphic library for the Ruby programming language\u037e specializing the generic capabilities of the Isomorphic library for BuildingSync specifically, e.g., by providing a library of BuildingSyncfriendly methods to simplify the construction of BuildingSync XML documents.", + "laborHours": 304.0, + "languages": [], + "name": "pnnl/building_sync_rails", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/building_sync_rails", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_buildingid-js.json b/agency-indexes/DoE/pnnl_buildingid-js.json new file mode 100644 index 00000000..eaaea251 --- /dev/null +++ b/agency-indexes/DoE/pnnl_buildingid-js.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-11-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Unique Building Identification (UBID) for JavaScript\nThis is a line-for-line translation from the Python programming language to the JavaScript programming language of the UBID application programming interface (API): the \"encode\", \"decode\" and \"isValid\" UBID functions. No new functionality is introduced.", + "laborHours": 76.0, + "languages": [ + "Java" + ], + "name": "pnnl/buildingid-js", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid-js", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_buildingid-rb.json b/agency-indexes/DoE/pnnl_buildingid-rb.json new file mode 100644 index 00000000..a119f274 --- /dev/null +++ b/agency-indexes/DoE/pnnl_buildingid-rb.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-11-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Unique Building Identification (UBID) for Ruby\nAn implementation of the Unique Building Identification (UBID) concept for the Ruby programming language. This work is a line-for-line port of the original implementation for the Python programming language (IPID: 31437-E). No new functionality is added.", + "laborHours": 76.0, + "languages": [ + "Ruby" + ], + "name": "pnnl/buildingid-rb", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid-rb", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_buildingid.json b/agency-indexes/DoE/pnnl_buildingid.json new file mode 100644 index 00000000..04e37430 --- /dev/null +++ b/agency-indexes/DoE/pnnl_buildingid.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-10-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Unique Building Identifier (UBID)\nThis \"invention\" is an enhanced version of the UBID library and command-line executable that, in addition to encoding, decoding and validating UBIDs, also calculates UBID-based statistics and generates figures.", + "laborHours": 440.8, + "languages": [], + "name": "pnnl/buildingid", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/buildingid", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_capratTX.json b/agency-indexes/DoE/pnnl_capratTX.json new file mode 100644 index 00000000..a66b5222 --- /dev/null +++ b/agency-indexes/DoE/pnnl_capratTX.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-12-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Thermoelectric Capacity at Risk Analysis Tool for ERCOT. capratTX is a unique R package, featuring algorithms for simulating water storages that provide cooling water for thermoelectric power plants. The tool may be used to compute long-term \"capacity at risk\" under a range of future climate\nprojections.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/capratTX", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/capratTX", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_chemreasoner.json b/agency-indexes/DoE/pnnl_chemreasoner.json new file mode 100644 index 00000000..71757465 --- /dev/null +++ b/agency-indexes/DoE/pnnl_chemreasoner.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-01-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ChemReasoner - Catalyst Discovery via Large Language Model-driven Reasoning", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/chemreasoner", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/chemreasoner", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_chgl.json b/agency-indexes/DoE/pnnl_chgl.json new file mode 100644 index 00000000..a30a46f4 --- /dev/null +++ b/agency-indexes/DoE/pnnl_chgl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-09-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "CHGL is a hypergraph computation library for Chapel. It's primary contributions are data structures for hypergraphs and the algorithms to operate on these data structures.", + "laborHours": 6414.4, + "languages": [], + "name": "pnnl/chgl", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/chgl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_chissl.json b/agency-indexes/DoE/pnnl_chissl.json new file mode 100644 index 00000000..25779257 --- /dev/null +++ b/agency-indexes/DoE/pnnl_chissl.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-04-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Interactive machine learning interface\nOur invention allows the user to interact with individual instances, see recommendations for similar items, and make\nadjustments. The scalable nature of our solution allows it to perform instantaneously from the user's perspective, even for\n100K+ data items.", + "laborHours": 13421.6, + "languages": [], + "name": "pnnl/chissl", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/chissl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_copper.json b/agency-indexes/DoE/pnnl_copper.json new file mode 100644 index 00000000..a56bd03e --- /dev/null +++ b/agency-indexes/DoE/pnnl_copper.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Performance curve generator for building energy simulation. Copper is a tool in the form of Python package that can be used to generate metric specific performance curves for\nbuilding energy simulations.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/copper", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/copper", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_datalife.json b/agency-indexes/DoE/pnnl_datalife.json new file mode 100644 index 00000000..509f07cc --- /dev/null +++ b/agency-indexes/DoE/pnnl_datalife.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-09-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "data flow lifecycle analysis", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/datalife", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/datalife", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_deep_scoreMS1.json b/agency-indexes/DoE/pnnl_deep_scoreMS1.json new file mode 100644 index 00000000..027a0d96 --- /dev/null +++ b/agency-indexes/DoE/pnnl_deep_scoreMS1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-11-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Similarity learning of two mass spectrometry runs solely using MS1 data", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/deep_scoreMS1", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/deep_scoreMS1", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_defect_detection.json b/agency-indexes/DoE/pnnl_defect_detection.json new file mode 100644 index 00000000..4af5cf63 --- /dev/null +++ b/agency-indexes/DoE/pnnl_defect_detection.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-11-08", + "metadataLastUpdated": "2024-11-08" + }, + "description": "The code takes expert-labeled segmented images of irradiated and unirradiated pellets and trains DeepConvolutional\nNeural Networks to segment these images into defects, backgrounds, and boundaries. The code calculated qualitative\nmicrostructural information from these segmented images to facilitate the comparison of unirradiated and irradiated\npellets", + "laborHours": 3404.8, + "languages": [], + "name": "pnnl/defect_detection", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/defect_detection", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_deimos_gui.json b/agency-indexes/DoE/pnnl_deimos_gui.json new file mode 100644 index 00000000..efebb262 --- /dev/null +++ b/agency-indexes/DoE/pnnl_deimos_gui.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-09-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The DEIMoS Graphical User Interface was created as an interface for DEIMoS: Data Extraction for Integrated\nMultidimensional Spectrometry. DEIMoS is a Python package to process data from mass spectrometry instrument\ndeveloped at PNNL.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/deimos_gui", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/deimos_gui", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_deps_arXiv2020.json b/agency-indexes/DoE/pnnl_deps_arXiv2020.json new file mode 100644 index 00000000..ec755035 --- /dev/null +++ b/agency-indexes/DoE/pnnl_deps_arXiv2020.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-06-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software implements data-driven control and dynamic systems models using deep learning methods. The particular application is building temperature control.", + "laborHours": 3359.2, + "languages": [], + "name": "pnnl/deps_arXiv2020", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/deps_arXiv2020", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_diet-parselantro.json b/agency-indexes/DoE/pnnl_diet-parselantro.json new file mode 100644 index 00000000..72031f0d --- /dev/null +++ b/agency-indexes/DoE/pnnl_diet-parselantro.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A data annotation tool that integrates with the python Jupyter notebook environment.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/diet-parselantro", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/diet-parselantro", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_doa.json b/agency-indexes/DoE/pnnl_doa.json new file mode 100644 index 00000000..deca48d6 --- /dev/null +++ b/agency-indexes/DoE/pnnl_doa.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-12-19", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a set of Python scripts designed to implement a method of determining the domain of applicability for a trained machine model for molecular property prediction. Additionally, the scripts implement analysis methods to evaluate and explore the results of the method. These scripts are designed to support the submission of a manuscript describing the methods for publication.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/doa", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/doa", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_dream_v3.json b/agency-indexes/DoE/pnnl_dream_v3.json new file mode 100644 index 00000000..856d725c --- /dev/null +++ b/agency-indexes/DoE/pnnl_dream_v3.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Designs for Risk Evaluation and Management (DREAM) tool was developed as part of the effort to quantify the risk of\ngeologic storage of carbon dioxide (CO2) under the U.S. Department of Energy\u2019s National Risk Assessment Partnership\n(NRAP). DREAM is an optimization tool created to identify optimal monitoring schemes that minimize the time to first\ndetection of CO2 leakage from a subsurface storage formation. DREAM acts as a post-processer on user-provided output\nfrom subsurface leakage simulations. While DREAM was developed for CO2 leakage scenarios, it is applicable to any\nsubsurface leakage simulation of the same output format", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/dream_v3", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/dream_v3", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_emp-gnn.json b/agency-indexes/DoE/pnnl_emp-gnn.json new file mode 100644 index 00000000..6f02986d --- /dev/null +++ b/agency-indexes/DoE/pnnl_emp-gnn.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-02-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Efficient Graph Neural Network for Predicting Molecular Properties software can compare the prediction quality with ab initio DFT results reported by the high-performance state-of-theart NWChem quantum chemistry package [1] through Mean Absolute Error (MAE) obtained by the fitting between DFT and\nmodel predictions i.e, MPNN [2]. We also demonstrated the performance benefits by grouping large molecules by atom\nsizes, and executing GNN models on different types of resources. Since the training times depend on the number of\natoms, we demonstrate the impact of distributing the workloads on two GPUs with varying capabilities (e.g., NVIDIA A100\nvs. GeForce RTX 2080 Ti) to optimize the efficiency. We are at the precipice of broad adoption of GNNs for molecular\nproperty prediction tasks\u037e hence, our work is timely by comparing model prediction against classical approaches with the\nintent of providing initial screening for specific classes of molecules.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/emp-gnn", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/emp-gnn", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_eqc.json b/agency-indexes/DoE/pnnl_eqc.json new file mode 100644 index 00000000..8b170bd8 --- /dev/null +++ b/agency-indexes/DoE/pnnl_eqc.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "EQC is a software framework for smart distributed quantum computer management and organization for variational quantum algorithms. EQC utilizes smart real time management of multiple independent quantum processors to maximize variational quantum algorithm throughput, for improved converged performance and improved rate of convergance.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/eqc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/eqc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_femp-water-balance.json b/agency-indexes/DoE/pnnl_femp-water-balance.json new file mode 100644 index 00000000..a3eb0a66 --- /dev/null +++ b/agency-indexes/DoE/pnnl_femp-water-balance.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-12-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Analysis and reporting for water and irrigation usage\nPNNL developed the Water Balance Tool, which provides a method to determine potable water consumption, by end-use, of a campus. A water balance compares the total water supply to the volume of water consumed by water-using equipment and applications. The output of the tool provides the estimated potable water consumption by major end-use and compares the sum of the end-uses to the total potable water supplied to the campus.", + "laborHours": 6824.8, + "languages": [], + "name": "pnnl/femp-water-balance", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/femp-water-balance", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_fieryfuture.json b/agency-indexes/DoE/pnnl_fieryfuture.json new file mode 100644 index 00000000..3cfe8410 --- /dev/null +++ b/agency-indexes/DoE/pnnl_fieryfuture.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Deep learning approaches which incorporate geophysical data and readings from multiple remote sensing platforms for predictive mapping of vegetation over very large, ecologically diverse regions.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/fieryfuture", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/fieryfuture", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_frequency_sensitivity.json b/agency-indexes/DoE/pnnl_frequency_sensitivity.json new file mode 100644 index 00000000..c263d51d --- /dev/null +++ b/agency-indexes/DoE/pnnl_frequency_sensitivity.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-04-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This research code base includes functions to compute statistics of image distributions in (spatial DFT) frequency space, train deep learning image classifiers on these distributions with variable depth and weight decay, and finally measure the sensitivity of the trained models to perturbations along (spatial DFT) frequency components.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/frequency_sensitivity", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/frequency_sensitivity", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_galas.json b/agency-indexes/DoE/pnnl_galas.json new file mode 100644 index 00000000..fa18a6c9 --- /dev/null +++ b/agency-indexes/DoE/pnnl_galas.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Codebase for analyzing large atomistic simulation results using graph analytics. Analysis of large molecular simulations is difficult due to size and memory constrains in commonly used analysis software. This code was developed to analyze an ~8 million atom polycrystalline Al system under shear, with a particular emphasis on identifying defect structures. This code applies graph theory to reduce the system to components of interest and applies associated algorithms to characterize these components.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/galas", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/galas", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_glad.json b/agency-indexes/DoE/pnnl_glad.json new file mode 100644 index 00000000..964998ee --- /dev/null +++ b/agency-indexes/DoE/pnnl_glad.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-03-07", + "metadataLastUpdated": "2025-03-07" + }, + "description": "The Graph-based Learning of Aerosol Dynamics (GLAD) package implements a Graph Network-based Simulator (GNS), a machine learning framework that has been used to simulate particle-based fluid dynamics models", + "laborHours": 1079.2, + "languages": [], + "name": "pnnl/glad", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/glad", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_gmt.json b/agency-indexes/DoE/pnnl_gmt.json new file mode 100644 index 00000000..a6b6b71a --- /dev/null +++ b/agency-indexes/DoE/pnnl_gmt.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-05-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Global Memory and Threading runtime system", + "laborHours": 5228.8, + "languages": [], + "name": "pnnl/gmt", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/gmt", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_gparm.json b/agency-indexes/DoE/pnnl_gparm.json new file mode 100644 index 00000000..010deec5 --- /dev/null +++ b/agency-indexes/DoE/pnnl_gparm.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A tool for developing parametric inputs for other software.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/gparm", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/gparm", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_graph_merge.json b/agency-indexes/DoE/pnnl_graph_merge.json new file mode 100644 index 00000000..2105c6ad --- /dev/null +++ b/agency-indexes/DoE/pnnl_graph_merge.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-12-20", + "metadataLastUpdated": "2024-12-23" + }, + "description": "A novel method for pairwise graph comparison that includes both the graph structure and\napplicable metadata. The resulting visual component allows a greater and more interpretable understanding of the\ncomparison than current methods", + "laborHours": 957.6, + "languages": [], + "name": "pnnl/graph_merge", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/graph_merge", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_grid_prediction.json b/agency-indexes/DoE/pnnl_grid_prediction.json new file mode 100644 index 00000000..fc392465 --- /dev/null +++ b/agency-indexes/DoE/pnnl_grid_prediction.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Two datadriven predictive approaches, namely, {\\em Koopman Operator Theoretic (KOT)-based} model and {\\em Graph Neural Network (GNN)-based model}, to enable effective power system state predictions. The KOT-based approaches (Robust\nDMD, deepDMD) capture the power system evolution as a linear dynamical system on an abstract space. The GNNs model the spatio-temporal correlations using graph convolutional network and are called Spatio-Temporal Graph Convolutional\nNetwork (STGCN). These predictive models are trained, tested and compared rigorously based on their predictions of frequencies in the IEEE 68 bus system when subjected to a disturbance. GridSTAGE framework developed at Pacific Northwest National Laboratory is leveraged to generate multiple datasets (in the form of PMU measurements) for training and testing by strategically creating load changes across the spatial locations of the network", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/grid_prediction", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/grid_prediction", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_gumby-spectral-imaging.json b/agency-indexes/DoE/pnnl_gumby-spectral-imaging.json new file mode 100644 index 00000000..164560a8 --- /dev/null +++ b/agency-indexes/DoE/pnnl_gumby-spectral-imaging.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-09-29", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Deep Learning models for multi- and hyper-spectral imaging data", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/gumby-spectral-imaging", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/gumby-spectral-imaging", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_hexwatershed.json b/agency-indexes/DoE/pnnl_hexwatershed.json new file mode 100644 index 00000000..af3e791b --- /dev/null +++ b/agency-indexes/DoE/pnnl_hexwatershed.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Flow routing using a hexagonal grid.", + "laborHours": 2158.4, + "languages": [], + "name": "pnnl/hexwatershed", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://availabletechnologies.pnnl.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/hexwatershed", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_hexwatershed_v2.0.json b/agency-indexes/DoE/pnnl_hexwatershed_v2.0.json new file mode 100644 index 00000000..373d5c5b --- /dev/null +++ b/agency-indexes/DoE/pnnl_hexwatershed_v2.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Flow routing using a hexagonal grid.", + "laborHours": 2158.4, + "languages": [ + "Python" + ], + "name": "pnnl/hexwatershed v2.0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/hexwatershed", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_hundo.json b/agency-indexes/DoE/pnnl_hundo.json new file mode 100644 index 00000000..3f02f008 --- /dev/null +++ b/agency-indexes/DoE/pnnl_hundo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-08-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": ":bar_chart: Snakemake-based amplicon processing protocol for 16S and ITS sequences.", + "laborHours": 1155.2, + "languages": [], + "name": "pnnl/hundo", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/hundo", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_hydraconda.json b/agency-indexes/DoE/pnnl_hydraconda.json new file mode 100644 index 00000000..f8547076 --- /dev/null +++ b/agency-indexes/DoE/pnnl_hydraconda.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-06-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A framework for developing scientific computing codes for projects was developed that accommodates both explorations as well as, simultaneously, software engineering rigor. This is accomplished by organizing modular yet composable and related computational environments. Also known as Management of Multiple Computational Environments", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/hydraconda", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/hydraconda", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_hyperedge-triplets.json b/agency-indexes/DoE/pnnl_hyperedge-triplets.json new file mode 100644 index 00000000..a14a642b --- /dev/null +++ b/agency-indexes/DoE/pnnl_hyperedge-triplets.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This software implements an algorithm for finding triplets of hyperedges with specified size relations. Specifically, this is an\nimplementation of the pseudo-code in Algorithm 2 of our preprint manuscript \"Size-aware hypergraph motifs\", see:\nhttps://arxiv.org/pdf/2311.07783.pdf", + "laborHours": 7113.6, + "languages": [], + "name": "pnnl/hyperedge-triplets", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/hyperedge-triplets", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_hypernetx-widget.json b/agency-indexes/DoE/pnnl_hypernetx-widget.json new file mode 100644 index 00000000..15e6eac2 --- /dev/null +++ b/agency-indexes/DoE/pnnl_hypernetx-widget.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Hnx-widget is a Jupyter notebook widget for visualizing hyper graphs that is intended to work in conjunction with the HyperNetX open source package developed by PNNL. It renders hyper graphs using Euler diagrams (a Venn diagram is a special type of Euler diagram). The tool contains simple interactions that allow the user to select nodes and change their appearance. It scales to small to medium sized (100 node) hyper graphs", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/hypernetx-widget", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/hypernetx-widget", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_i2x.json b/agency-indexes/DoE/pnnl_i2x.json new file mode 100644 index 00000000..1a7f26b9 --- /dev/null +++ b/agency-indexes/DoE/pnnl_i2x.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-03-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Interconnection Innovation e-Xchange (i2x) Test Systems allows for scripted customizations of social behavior, recovery operations, investment decisions, and metrics in a simplified Python module. Public test systems allow for replication of results by other stakeholders", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/i2x", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/i2x", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_idpp_rtp.json b/agency-indexes/DoE/pnnl_idpp_rtp.json new file mode 100644 index 00000000..f984a26f --- /dev/null +++ b/agency-indexes/DoE/pnnl_idpp_rtp.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-02-07", + "metadataLastUpdated": "2025-02-07" + }, + "description": "IdPP is a Python package that provides a framework for the curation and analysis of molecular properties from\nmultidimensional mass spectrometry (MS) measurements. The main components of the package are organized around a\nmolecular property database and identification probability analysis", + "laborHours": 349.6, + "languages": [], + "name": "pnnl/idpp_rtp", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/idpp_rtp", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_interflow.json b/agency-indexes/DoE/pnnl_interflow.json new file mode 100644 index 00000000..30a76782 --- /dev/null +++ b/agency-indexes/DoE/pnnl_interflow.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-25", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A Python package for organizing and calculating cross-sectoral interdependency flow values. The interflow package collects known resource flow values (e.g., water demand) between sectors provided by the user and calculates new sector flows for a secondary resource type (e.g., energy demand) based on provided resource intensity estimates, source sector fractions, and downstream sector discharge fractions.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/interflow", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/interflow", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_isicle.json b/agency-indexes/DoE/pnnl_isicle.json new file mode 100644 index 00000000..99c73585 --- /dev/null +++ b/agency-indexes/DoE/pnnl_isicle.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2025-01-08" + }, + "description": "In silico chemical library engine for high-accuracy chemical property prediction", + "laborHours": 3815.2, + "languages": [], + "name": "pnnl/isicle", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/isicle", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_isomorphic.json b/agency-indexes/DoE/pnnl_isomorphic.json new file mode 100644 index 00000000..c7763e60 --- /dev/null +++ b/agency-indexes/DoE/pnnl_isomorphic.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-02-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Isomorphic is a Ruby library for specifying isomorphisms between Ruby objects.\nThe inventive features of the new Ruby library are as follows:\nDomain-specific language (DSL) for declaration of isomorphisms between Ruby objects.\nFunctional references (viz., \"lenses\") for getter/setter operations.\nTo our knowledge, this is the first library of its kind for the Ruby programming language. Moreover, to our knowledge, this is the first implementation of the \"functional references\" concept within the Ruby programming language.", + "laborHours": 714.4, + "languages": [], + "name": "pnnl/isomorphic", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/isomorphic", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_jira-aperture.json b/agency-indexes/DoE/pnnl_jira-aperture.json new file mode 100644 index 00000000..e3f07432 --- /dev/null +++ b/agency-indexes/DoE/pnnl_jira-aperture.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-07-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A JIRA Add-on that adds custom workflows and automation hooks for provisioning services within other Atlassian tools like Confluence, Bitbucket, and Crucible/Fisheye based on project keys", + "laborHours": 4727.2, + "languages": [], + "name": "pnnl/jira-aperture", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/jira-aperture", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_lpNNPS4SPH.json b/agency-indexes/DoE/pnnl_lpNNPS4SPH.json new file mode 100644 index 00000000..a651e8fd --- /dev/null +++ b/agency-indexes/DoE/pnnl_lpNNPS4SPH.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-11-09", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Low precision-based nearest neighboring particle searching algorithm.This work introduces a computationally efficient Nearest Neighbor Particles Searching (NNPS) algorithm tailored for the\nmeshfree Smoothed Particle Hydrodynamics (SPH) method in large-deformation problems simulations. The innovation lies\nin the strategic use of low-precision float-point 16 (FP16) in NNPS for efficiency purpose.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/lpNNPS4SPH", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/lpNNPS4SPH", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_mass2.json b/agency-indexes/DoE/pnnl_mass2.json new file mode 100644 index 00000000..6178bf0b --- /dev/null +++ b/agency-indexes/DoE/pnnl_mass2.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2025-02-12" + }, + "description": "Two dimension, depth-averaged hydrodynamic and transport model.", + "laborHours": 46284.0, + "languages": [ + "Fortran 90" + ], + "name": "pnnl/mass2", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mass2", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_maximojsonclient.json b/agency-indexes/DoE/pnnl_maximojsonclient.json new file mode 100644 index 00000000..bcb930bf --- /dev/null +++ b/agency-indexes/DoE/pnnl_maximojsonclient.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-10-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Maximo Json Client is a Microsoft .Net core class library. The function of the library is to abstract Http requests from\n.Net code to the IBM Maximo Json API (Json API). The library assumes the responsibility for handshaking with the Json\nAPI (authentication, session management, etc.) and converting to a common syntax.", + "laborHours": 592.8, + "languages": [], + "name": "pnnl/maximojsonclient", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/maximojsonclient", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_mcl-runtime.json b/agency-indexes/DoE/pnnl_mcl-runtime.json new file mode 100644 index 00000000..3b046f2c --- /dev/null +++ b/agency-indexes/DoE/pnnl_mcl-runtime.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-03-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Minos Computing Library (MCL) is a task-based programming language and runtime for extremely heterogeneous systems. MCL facilitates writing program for heterogeneous devices and porting applications across different systems and devices. MCL supports asynchronous execution of computing tasks on all available heterogeneous devices, including GPUs, FGPAs, fixed-point accelerators, and AI accelerators. MCL provides a high-level programming interface and automatically and autonomously performs resource management, load balancing, and locality-aware scheduling.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/mcl-runtime", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mcl-runtime", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_memgaze.json b/agency-indexes/DoE/pnnl_memgaze.json new file mode 100644 index 00000000..70fb29eb --- /dev/null +++ b/agency-indexes/DoE/pnnl_memgaze.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-09-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "MemGaze is a memory analysis toolset that combines high-resolution trace analysis and low overhead measurement, both with respect to time and space. It provides high-resolution by collecting world-level memory access traces, where the highest resolution supported is back-to-back sequences. It achieves low-overhead in space and time by leveraging sampling and various methods of hardware support for collecting traces. Its post-mortem trace processing provides multiresolution analysis for locations vs. operations\u037e accesses vs. spatio-temporal reuse, and reuse (distance, rate, volume) vs. access patterns.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/memgaze", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/memgaze", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_metagenomic_analysis.json b/agency-indexes/DoE/pnnl_metagenomic_analysis.json new file mode 100644 index 00000000..da25b655 --- /dev/null +++ b/agency-indexes/DoE/pnnl_metagenomic_analysis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-08-20", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Metagenomic analysis is a computationally intensive task, this problem is compounded when many hundreds of samples need to be analyzed. We needed a program that would process the metagenomic sequencing data, manage computing resources, and combine the results into a unified output. We developed a script that prepares raw metagenomic sequencing data for analysis, configures analysis parameters, launches analysis jobs, keeps track of analysis progress, and combines analysis output. The analysis itself itself is done by the functionality provided by mothur (https://www.mothur.org/).", + "laborHours": 76.0, + "languages": [], + "name": "pnnl/metagenomic_analysis", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/metagenomic_analysis", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_mlprotein.json b/agency-indexes/DoE/pnnl_mlprotein.json new file mode 100644 index 00000000..8c6fe4a5 --- /dev/null +++ b/agency-indexes/DoE/pnnl_mlprotein.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The molecular graphics program, PyMol, was employed to produce all images in the training/validation/testing datasets. A\nPyMol script identified the clusters of interest from a list of all proteins containing 1) Fe (III) and Fe (II) ion and 2) FeS,\nrespectively. A PyMol script and a Python webscraper were also used to classify [2Fe-2S] cofactors into three classes:\nstandard, Rieske, and other and to identify iron atoms with four cysteine residues. We also used the pyMol script to rotate\namino acids for training", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/mlprotein", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mlprotein", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_mlxrd.json b/agency-indexes/DoE/pnnl_mlxrd.json new file mode 100644 index 00000000..61ee23b3 --- /dev/null +++ b/agency-indexes/DoE/pnnl_mlxrd.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-12-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A multi-task neural network for the simultaneous identification of multiple compounds from XRD data obtained in a synchrotron-based hydrothermal fluid system. To enhance the alignment between the training and test datasets, random noise is introduced into the synthetic training dataset, and minor labeled experimental data is incorporated. Additionally, we employ a weighted cross-entropy loss function to address data imbalances and ensure smoother model training.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/mlxrd", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mlxrd", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_modelsym.json b/agency-indexes/DoE/pnnl_modelsym.json new file mode 100644 index 00000000..84beb45d --- /dev/null +++ b/agency-indexes/DoE/pnnl_modelsym.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-08", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Code to run the experiments of the Neurips 2022 paper [On the Symmetries of Deep Learning Models and their Internal Representations](https://arxiv.org/abs/2205.14258).", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/modelsym", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/modelsym", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_mol_dgnn.json b/agency-indexes/DoE/pnnl_mol_dgnn.json new file mode 100644 index 00000000..496c1057 --- /dev/null +++ b/agency-indexes/DoE/pnnl_mol_dgnn.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-05-04", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Molecular dynamics simulations often rely on parameterized atomistic potentials, which can be inaccurate compared to ab initio simulation methods. However, dynamic ab initio simulations come with high computational cost. Deep learning techniques offer a method to obtain both high accuracy and low cost predictions of dynamics. Our method gives a prediction of the structural dynamics of a molecule accounting for the prior dynamics, giving high-accuracy predictions at low computational cost", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/mol_dgnn", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/mol_dgnn", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_ms-speak.json b/agency-indexes/DoE/pnnl_ms-speak.json new file mode 100644 index 00000000..f216a489 --- /dev/null +++ b/agency-indexes/DoE/pnnl_ms-speak.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Multi-Speak - Secure Protocol Enterprise Access Kit", + "laborHours": 159189.6, + "languages": [], + "name": "pnnl/ms-speak", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ms-speak", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_neural_ODE_ICLR2020.json b/agency-indexes/DoE/pnnl_neural_ODE_ICLR2020.json new file mode 100644 index 00000000..46affd08 --- /dev/null +++ b/agency-indexes/DoE/pnnl_neural_ODE_ICLR2020.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-11-16", + "metadataLastUpdated": "2024-06-18" + }, + "description": "We show how to model discrete ordinary differential equations (ODE) with algebraic nonlinearities as deep neural networks with varying degrees of prior knowledge.\nWe derive the stability guarantees of the network layers based on the implicit constraints imposed on the weight's eigenvalues. Moreover, we show how to use barrier methods to generically handle additional inequality constraints.\nWe demonstrate the prediction accuracy of learned neural ODEs evaluated on open-loop simulations compared to ground truth dynamics with bi-linear terms.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/neural_ODE_ICLR2020", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/neural_ODE_ICLR2020", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_neuromancer.json b/agency-indexes/DoE/pnnl_neuromancer.json new file mode 100644 index 00000000..f4ad0c77 --- /dev/null +++ b/agency-indexes/DoE/pnnl_neuromancer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Dynamics-based deep learning methods to modernize current scientific computing methods. Neuromancer is currently capable of solving inverse problems for a system of ordinary differential equations. The functionality includes system identification and constrained optimal control of unknown or partially known ODEs.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/neuromancer", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/neuromancer", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_oedisi_dopf.json b/agency-indexes/DoE/pnnl_oedisi_dopf.json new file mode 100644 index 00000000..2b0a4c21 --- /dev/null +++ b/agency-indexes/DoE/pnnl_oedisi_dopf.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2024-04-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "OpenEDI - System Integration (OEDI-SI) - PNNL Distributed Optimal Power Flow (DOPF)", + "laborHours": 3404.8, + "languages": [], + "name": "pnnl/oedisi_dopf", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/oedisi_dopf", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_openstudio-building-energy-standard-measures-gem.json b/agency-indexes/DoE/pnnl_openstudio-building-energy-standard-measures-gem.json new file mode 100644 index 00000000..31d5ae1f --- /dev/null +++ b/agency-indexes/DoE/pnnl_openstudio-building-energy-standard-measures-gem.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2025-01-30", + "metadataLastUpdated": "2025-01-30" + }, + "description": "A framework for automatically verifying building controls function.", + "laborHours": 40644.8, + "languages": [], + "name": "pnnl/openstudio-building-energy-standard-measures-gem", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/openstudio-building-energy-standard-measures-gem", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_pakman.json b/agency-indexes/DoE/pnnl_pakman.json new file mode 100644 index 00000000..256d690b --- /dev/null +++ b/agency-indexes/DoE/pnnl_pakman.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-02-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PaKman: A Scalable Algorithm for Generating Genomic Contigs on Distributed Memory Machines. PaKman presents a fully distributed method that tackles assembly of large genomes through the combinationof a novel data-structure (PaK-Graph) and algorithmic strategies to simplify communication and I/O footprint during the\nassembly process.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/pakman", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pakman", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_parking.json b/agency-indexes/DoE/pnnl_parking.json new file mode 100644 index 00000000..94cc6b3d --- /dev/null +++ b/agency-indexes/DoE/pnnl_parking.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-08-10", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Commercial Parking Application is a web-based application that alerts delivery drivers in real time to available parking\nspaces near their destinations. Parking availability can be viewed on a map in real-time, using sensor data supplied by\nexternal services. The app can be viewed with a web browser on a mobile device or PC. Currently the app supports\nconnections to real time sensors from Lacuna, Fybr, Cleverciti, and Automotus", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/parking", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/parking", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_pecblocks.json b/agency-indexes/DoE/pnnl_pecblocks.json new file mode 100644 index 00000000..b3a84fb4 --- /dev/null +++ b/agency-indexes/DoE/pnnl_pecblocks.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "ConverterBlocks uses the output of detailed electromagnetic transient (EMT) simulations to produce generalized block diagram models of power electronic systems. The process uses deep learning with customized block architectures. The outputs are reduced-order models that meet specified accuracy requirements, while providing important advantages over the original EMT models: ConverterBlock models have fewer nodes and can take longer time steps, resulting in shorter simulation times ConverterBlock models are continuously differentiable, making them compatible with control design methodsGeneralized block diagram modeling of power electronic converters for grid solar and storage applications.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/pecblocks", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pecblocks", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_pg-histogram.json b/agency-indexes/DoE/pnnl_pg-histogram.json new file mode 100644 index 00000000..e4a9db54 --- /dev/null +++ b/agency-indexes/DoE/pnnl_pg-histogram.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-12-03", + "metadataLastUpdated": "2024-06-18" + }, + "description": "PostgreSQL histograms for ActiveRecord relations.\nA plugin for the Ruby on Rails (RoR) web application development framework web application development framework that leverages the \"Active Relation\" relational algebra component to automatically formulate SQL statements for the construction of histograms.", + "laborHours": 76.0, + "languages": [ + "Ruby" + ], + "name": "pnnl/pg-histogram", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pg-histogram", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_portfoliomanager-rb.json b/agency-indexes/DoE/pnnl_portfoliomanager-rb.json new file mode 100644 index 00000000..5a8b7e24 --- /dev/null +++ b/agency-indexes/DoE/pnnl_portfoliomanager-rb.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This invention is a Ruby \"gem\" (library) that provides clients for ENERGY STAR Portfolio Manager (ESPM) Web Services,\nInventive features:\n100% coverage of version 18.0 of the ESPM API.\nAutomated mapping between ESPM XML schemas and Ruby objects.\nClients for both the \"live\" and \"test\" ESPM API environments.\nDebugging mode with HTTP request/response logging.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/portfoliomanager-rb", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/portfoliomanager-rb", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_projection_ntk.json b/agency-indexes/DoE/pnnl_projection_ntk.json new file mode 100644 index 00000000..08de18c9 --- /dev/null +++ b/agency-indexes/DoE/pnnl_projection_ntk.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-11-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a repository for work conducted in our research paper we would like to make open source. The main features are\nthat we forked another open source library and added functionality that enabled us to compute neural-kernel objects using\nrandom vector projection software for both computer vision and large language text models. The new features are\nspecifically code that enables the calculation of objects we define and refer to as the projection pseudo neural tangent\nkernel and the projection trace neural tangent kernel\u037e both of which are approximations of the empirical neural tangent\nkernel. The software that computes the projections themselves are not part of the invention, but are necessarily tied to our\nsoftware and licensed via MIT license, and BSD 2 license.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/projection_ntk", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/projection_ntk", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_psl.json b/agency-indexes/DoE/pnnl_psl.json new file mode 100644 index 00000000..68d97fb8 --- /dev/null +++ b/agency-indexes/DoE/pnnl_psl.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "software library of structured linear maps that can be used as drop in replacements for Pytorch linear layers.\nThese maps can be used to enforce physically realistic outcomes to data-driven machine learning scientific modeling problems.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/psl", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/psl", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_pyraabe.json b/agency-indexes/DoE/pnnl_pyraabe.json new file mode 100644 index 00000000..5289f72b --- /dev/null +++ b/agency-indexes/DoE/pnnl_pyraabe.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-05-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Automated Raabe table generationPyRaabe is a Python package to automate Raabe table -- a graph representation of airway geometry -- generation from a triangulated surface of an airway geometry. With a single command, it extracts a centerline from an input 3D surface mesh and subsequently computes the relevant attributes for the Raabe table, including length, diameter, bifurcation angle, and gravity angle. These can be used to inform downstream models, such as the Multiple-Path Particle Dosimetry (MPPD) model.", + "laborHours": 91.2, + "languages": [], + "name": "pnnl/pyraabe", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pyraabe", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_pysensing.json b/agency-indexes/DoE/pnnl_pysensing.json new file mode 100644 index 00000000..63a126f8 --- /dev/null +++ b/agency-indexes/DoE/pnnl_pysensing.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-06-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python Remote Sensing", + "laborHours": 15.2, + "languages": [], + "name": "pnnl/pysensing", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/pysensing", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_rhizo_phosph.json b/agency-indexes/DoE/pnnl_rhizo_phosph.json new file mode 100644 index 00000000..b7aee815 --- /dev/null +++ b/agency-indexes/DoE/pnnl_rhizo_phosph.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-11-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Python package to be used when working with the DDAO method of visualizing phosphatase activity in the rhizosphere. Includes a module with functions that generate figures for analysis of phosphatase levels in images of soil and root based on pixel intensity. These functions can be used on images with a single root or multiple roots. Figures include distance maps to show how phosphatase levels change as you move away from the root and along the roots themselves, line plots to show average phosphatase levels moving down the root and the soil surrounding the root, 2D histograms to show how phosphatase levels change moving away from the root, and 1D histograms to show overall differences in phosphatase distribution depending on whether a root was grown next to a phosphorus source or not.", + "laborHours": 273.6, + "languages": [], + "name": "pnnl/rhizo_phosph", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/rhizo_phosph", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_ripples.json b/agency-indexes/DoE/pnnl_ripples.json new file mode 100644 index 00000000..535032e7 --- /dev/null +++ b/agency-indexes/DoE/pnnl_ripples.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-07-07", + "metadataLastUpdated": "2024-06-18" + }, + "description": "A C++ Library for Influence Maximization", + "laborHours": 1687.2, + "languages": [], + "name": "pnnl/ripples", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ripples", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_ruleset-checking-tool.json b/agency-indexes/DoE/pnnl_ruleset-checking-tool.json new file mode 100644 index 00000000..c026305c --- /dev/null +++ b/agency-indexes/DoE/pnnl_ruleset-checking-tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Ruleset Checking Tool (RCT) will be a tool for verifying implementation of a ruleset (such as ASHRAE Standard 90.1 Appendix G) in building performance modeling (BPM) tools.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/ruleset-checking-tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ruleset-checking-tool", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_safekit.json b/agency-indexes/DoE/pnnl_safekit.json new file mode 100644 index 00000000..480dd15d --- /dev/null +++ b/agency-indexes/DoE/pnnl_safekit.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-12-12", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Some of the most pressing machine learning applications such as cyber security and object recognition lack enough ground-truth training data to build a classifier. We solve this problem by using unsupervised deep learning techniques to determine when data were anomalous or deviated from the norm. Traditional methods require either specific context dependent expertise to construct models, or prior examples of events and large amounts of well-labeled data to perform machine learning. Some cutting-edge deep learning approaches have been used to characterize complex events, but these have not been applied to the streaming environment and require a great deal of data. We demonstrated the use of an autoencoder and relevant featurization techniques to both learn a feature space and then identify anomalous portions without the aid of labeled data or domain knowledge. In this way, we demonstrated the detection of anomalous features without domain knowledge or tagged examples, and delivered these features to users.", + "laborHours": 40371.2, + "languages": [], + "name": "pnnl/safekit", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/safekit", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_sensitivity.json b/agency-indexes/DoE/pnnl_sensitivity.json new file mode 100644 index 00000000..0b549abf --- /dev/null +++ b/agency-indexes/DoE/pnnl_sensitivity.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-08-15", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Sensitivity calculator for low-background experiments", + "laborHours": 167.2, + "languages": [], + "name": "pnnl/sensitivity", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/sensitivity", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_simple-building-calculator.json b/agency-indexes/DoE/pnnl_simple-building-calculator.json new file mode 100644 index 00000000..8c39ed05 --- /dev/null +++ b/agency-indexes/DoE/pnnl_simple-building-calculator.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-07-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The Simple Building Calculator is a web application that estimates annual energy\nuse using regression models that have been fit to simulation results for the DOE\nCommercial Prototype Building Models. The tool is a single-page application that\nwill allow a user to rapidly analyze the impact of energy efficiency measures and\ndesign options on building performance. As it uses linear regression models rather\nthan more complicated machine learning models or physics based simulation, the\ntool can deploy easily and run client-side.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/simple-building-calculator", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/simple-building-calculator", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_slim.json b/agency-indexes/DoE/pnnl_slim.json new file mode 100644 index 00000000..36af1b1e --- /dev/null +++ b/agency-indexes/DoE/pnnl_slim.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Open source release of Python Systems Library which contains benchmark datasets, system emulators, and data loading codes.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/slim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/slim", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_socialsim.json b/agency-indexes/DoE/pnnl_socialsim.json new file mode 100644 index 00000000..16a151a8 --- /dev/null +++ b/agency-indexes/DoE/pnnl_socialsim.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-03-28", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The goal of Computational Simulation of Online Social Behavior (SocialSim) is to develop innovative technologies for highfidelity computational simulation of online social behavior. SocialSim will focus specifically on information spread and evolution. Current computational approaches to social and behavioral simulation are limited in this regard. Top-down simulation approaches focus on the dynamics of a population as a whole, and model behavioral phenomena by assuming uniform or mostly-uniform behavior across that population. Such methods can easily scale to simulate massive populations, but can be inaccurate if there are specific, distinct variations in the characteristics of the population. In contrast, bottom-up simulation approaches treat population dynamics as an emergent property of the activities and interactions taking place within a diverse population. While such approaches can enable more accurate simulation of information spread, they do not readily scale to represent large populations. SocialSim aims to develop novel approaches to address these challenges.", + "laborHours": 8086.4, + "languages": [], + "name": "pnnl/socialsim", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/socialsim", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_socialsim_package.json b/agency-indexes/DoE/pnnl_socialsim_package.json new file mode 100644 index 00000000..42586e77 --- /dev/null +++ b/agency-indexes/DoE/pnnl_socialsim_package.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-03-13", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Collection of measurements and metrics to be used on social network data. The task was to develop a set of measurements and metrics that can be used to measure the effectiveness of various social network simulations. Provides a collection of measurements and metrics. This takes a variety of metrics and measurements and packages them into a consistent framework.", + "laborHours": 23134.4, + "languages": [], + "name": "pnnl/socialsim_package", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/socialsim_package", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_solubility-prediction-paper.json b/agency-indexes/DoE/pnnl_solubility-prediction-paper.json new file mode 100644 index 00000000..debbd3a3 --- /dev/null +++ b/agency-indexes/DoE/pnnl_solubility-prediction-paper.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-07-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "We are using existing deep learning modeling architectures and data representation techniques, but we are consolidating the methods into a single set of training and evaluation scripts. Additionally, we test and evaluate the performance of the models on the largest set of solubility measurements available to date.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/solubility-prediction-paper", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/solubility-prediction-paper", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git", + "version": "1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_ssass-e.json b/agency-indexes/DoE/pnnl_ssass-e.json new file mode 100644 index 00000000..c16973d7 --- /dev/null +++ b/agency-indexes/DoE/pnnl_ssass-e.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-11-17", + "metadataLastUpdated": "2024-06-18" + }, + "description": "SSASSE software is responsible for validating, and verifying\u202finnovative safe scanning methodologies, models, architectures, and prototypes to\u202fsafely assess\u202foperational technology (OT) installed in critical energy infrastructure.", + "laborHours": 0.0, + "languages": [], + "name": "pnnl/ssass-e", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/ssass-e", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_sven.json b/agency-indexes/DoE/pnnl_sven.json new file mode 100644 index 00000000..ccfaea13 --- /dev/null +++ b/agency-indexes/DoE/pnnl_sven.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This is a JavaScript library for a storyline layout\nalgorithm. Storylines are adept at communicating\ncomplex change by encoding time on the x-axis and\nusing the proximity of lines in the y direction to\nrepresent interaction between entities. The library in\nthis disclosure takes as input a list of objects\ncontaining an id, time, and state. The output is a\ndata structure that can be used to conveniently\nrender a storyline visualization. Most importantly, the\nlibrary computes the y-coordinate of the entities over\ntime that decreases layout artifacts including\ncrossings, wiggles, and whitespace. This is\naccomplished through multi-objective, multi-stage\noptimization problem, where the output of one stage\nproduces input and constraints for the next stage.", + "laborHours": 15671.2, + "languages": [], + "name": "pnnl/sven", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/sven", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pnnl_velo.json b/agency-indexes/DoE/pnnl_velo.json new file mode 100644 index 00000000..054f4ebc --- /dev/null +++ b/agency-indexes/DoE/pnnl_velo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-10-31", + "metadataLastUpdated": "2018-11-01" + }, + "description": "Velo is the domain independent collaboration environment originally created as the basis of the Geological Sequestration Software Suite (GS3) under the Carbon Sequestration Initiative (CSI) LDRD program at PNNL. The enviroment supports teams in performing scientific research including setting up computational models, running simulations, and\nanalyzing/visualizing simulation output.", + "laborHours": 461517.6, + "languages": [], + "name": "pnnl/velo", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/velo", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/poly-cmake.json b/agency-indexes/DoE/poly-cmake.json new file mode 100644 index 00000000..72abec5e --- /dev/null +++ b/agency-indexes/DoE/poly-cmake.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2021-04-14", + "metadataLastUpdated": "2021-04-14" + }, + "description": "An Emacs \"major mode\" using the polymode infrastructure to enable language-specific in-place editing of documentation in the ReStructuredText format.", + "laborHours": 0.0, + "languages": [ + "Emacs Lisp" + ], + "name": "poly-cmake", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-3.0", + "name": "GPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FNALssi/poly-cmake", + "status": "Development", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/popclass.json b/agency-indexes/DoE/popclass.json new file mode 100644 index 00000000..34aa5f63 --- /dev/null +++ b/agency-indexes/DoE/popclass.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2024-09-17", + "metadataLastUpdated": "2024-09-17" + }, + "description": "popclass is a lightweight python package that allows fast, probabilistic classification of the lens of a\nmicrolensing event given the event's posterior distribution and a model of the Galaxy. popclass provides\nthe bridge between Galactic simulation and lens classification, an interface to common Bayesian\ninference libraries, and the ability for users to flexibly specify their own Galactic model and classification\nparameters.", + "laborHours": 775.2, + "languages": [], + "name": "popclass", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/popclass", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/powerman.json b/agency-indexes/DoE/powerman.json new file mode 100644 index 00000000..85070007 --- /dev/null +++ b/agency-indexes/DoE/powerman.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "powerman is free UNIX/Linux software that controls (remotely and in parallel) switched power distribution units. It was designed for remote power control of Linux systems in a data center or cluster environment, but has been used in other environments such as embedded management appliances, home automation, and high availability service management. powerman can be extended to support new devices using an expect-like scripting language. It communicates with devices natively using telnet, raw socket, and serial protocols. It also can drive virtual power control devices via a coprocess interface. The coprocess mechanism has been used to extend powerman to communicate with devices using other protocols such as SNMP, IPMI, Insteon, X-10, and VXI-11. powerman can control equipment connected using any combination of the above methods and provide unified naming for the equipment and parallel execution of control actions.\n", + "laborHours": 11354.4, + "languages": [], + "name": "powerman", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/powerman", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/powerscenarios_[SWR-20-50].json b/agency-indexes/DoE/powerscenarios_[SWR-20-50].json new file mode 100644 index 00000000..94b3d8b1 --- /dev/null +++ b/agency-indexes/DoE/powerscenarios_[SWR-20-50].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-08-26", + "metadataLastUpdated": "2024-03-11" + }, + "description": "Realistic data-driven renewable energy scenarios for stochastic grid operation problems", + "laborHours": 39200.8, + "languages": [ + "MATLAB", + "Python", + "Jupyter Notebook", + "Tex" + ], + "name": "powerscenarios [SWR-20-50]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/powerscenarios", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/procmon.json b/agency-indexes/DoE/procmon.json new file mode 100644 index 00000000..b170e573 --- /dev/null +++ b/agency-indexes/DoE/procmon.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "procmon performs large-scale monitoring, data collection, and analysis of user processes running on Linux systems. It is intended to be used to aid in performing an automated workload analysis of very large scale systems, but may also be useful for live monitoring of the running processes on large scale systems.", + "laborHours": 17358.4, + "name": "procmon", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://bitbucket.org/berkeleylab/nersc-procmon/src/c6e67d63e7c9c24f85a46b6d8965b8c615097edc/LICENSE?at=master&fileviewer=file-view-default", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/berkeleylab/nersc-procmon", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/progressbar2.json b/agency-indexes/DoE/progressbar2.json new file mode 100644 index 00000000..be2bce80 --- /dev/null +++ b/agency-indexes/DoE/progressbar2.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "New contributions to the existing open source project called 'progressbars2.\" Improvements were created for use in JBEI software, but are generally useful to the open source software community.", + "laborHours": 2188.8, + "name": "progressbar2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/WoLpH/python-progressbar", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/project_0vbb_v1.0-beta.json b/agency-indexes/DoE/project_0vbb_v1.0-beta.json new file mode 100644 index 00000000..9afb3492 --- /dev/null +++ b/agency-indexes/DoE/project_0vbb_v1.0-beta.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-10-15", + "metadataLastUpdated": "2018-10-17" + }, + "description": "This software is designed for the sole purpose of analyzing numerical lattice QCD results computed for one of the developers' research projects related to neutrinoless double beta decay, and will be distributed with their research publication. This software is provided to maximize the dissemination of the research results, to enable other scientists and the general public to easily check the results of their analysis, and also to be in compliance with the public availability of \"digital data\" as required by the DOE.", + "laborHours": 957.6, + "languages": [], + "name": "project_0vbb v1.0-beta", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/callat-qcd/project_0vbb", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/protein_info_service.json b/agency-indexes/DoE/protein_info_service.json new file mode 100644 index 00000000..1ddf34b2 --- /dev/null +++ b/agency-indexes/DoE/protein_info_service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "The protein_info service returns certain protein annotations about fids, such as domain assignments, operons, and orthologs. ", + "laborHours": 4605.6, + "languages": [], + "name": "protein_info_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/protein_info_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/protein_structure_service.json b/agency-indexes/DoE/protein_structure_service.json new file mode 100644 index 00000000..f98c7f6c --- /dev/null +++ b/agency-indexes/DoE/protein_structure_service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This service has methods for finding Protein Structure Databank (PDB) entries with sequences similar to a KBase protein sequence, specified by either a MD5 id or a feature or coding sequence id. There are two functions, one for searching by MD5, and the other searching by feature ID (FID). ", + "laborHours": 1140.0, + "languages": [], + "name": "protein_structure_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/protein_structure_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/prototype-processing.json b/agency-indexes/DoE/prototype-processing.json new file mode 100644 index 00000000..e1b18b44 --- /dev/null +++ b/agency-indexes/DoE/prototype-processing.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "Prototype live processing developed at Brookhaven National Laboratory.", + "laborHours": 91.2, + "languages": [], + "name": "prototype-processing", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/prototype-processing", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/prune_quant_vit.json b/agency-indexes/DoE/prune_quant_vit.json new file mode 100644 index 00000000..e23ca9f5 --- /dev/null +++ b/agency-indexes/DoE/prune_quant_vit.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "This tool provides codes to prune and quantize vision transformers (ViTs). The tool will allow developers and researchers to speed up inference of ViTs and deploy them on CPUs.", + "laborHours": 425.6, + "languages": [], + "name": "prune_quant_vit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kshitij11/PQV-Mobile", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/psdm-ws-template.json b/agency-indexes/DoE/psdm-ws-template.json new file mode 100644 index 00000000..dcb47dca --- /dev/null +++ b/agency-indexes/DoE/psdm-ws-template.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-25", + "metadataLastUpdated": "2022-08-25" + }, + "description": "This repo contains a template app for PSDM web services; use this repo as the basis for any new application.", + "laborHours": 0.0, + "languages": [], + "name": "psdm-ws-template", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/psdm_ws_template", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/psdm_mongo_ws.json b/agency-indexes/DoE/psdm_mongo_ws.json new file mode 100644 index 00000000..1ff95bc4 --- /dev/null +++ b/agency-indexes/DoE/psdm_mongo_ws.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-27", + "metadataLastUpdated": "2022-07-27" + }, + "description": "A simple application that exposes a MongoDB instance as a read only REST service.", + "laborHours": 0.0, + "languages": [], + "name": "psdm_mongo_ws", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/psdm_mongo_ws", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/psgeom.json b/agency-indexes/DoE/psgeom.json new file mode 100644 index 00000000..860bd4f2 --- /dev/null +++ b/agency-indexes/DoE/psgeom.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Python code for detector geometries, supporting translation between different programs, easy manipulation of the geometry, and access to the real-space coordinates of pixels. Currently we support interfaces to: psana, CrystFEL, and cheetah. An interface to cctbx.xfel is planned.", + "laborHours": 5608.8, + "name": "psgeom", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/psgeom/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/psgeom", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/psmlearn.json b/agency-indexes/DoE/psmlearn.json new file mode 100644 index 00000000..0aa6fdc7 --- /dev/null +++ b/agency-indexes/DoE/psmlearn.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Package to support photon science machine learning projects at SLAC/LCLS/AD", + "laborHours": 3708.8, + "name": "psmlearn", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/psmlearn/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/psmlearn", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/psmon.json b/agency-indexes/DoE/psmon.json new file mode 100644 index 00000000..7813922d --- /dev/null +++ b/agency-indexes/DoE/psmon.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Remote data visualization tool used at LCLS for online analysis/monitoring. psmon is a remote and local data visualization tool used at LCLS for online analysis/monitoring developed originally to work with LCLS psana analysis framework. ZeroMQ is used as the data trasport layer and it provides two different rendering clients based on matplotlib and pyqtgraph.", + "laborHours": 1535.2, + "name": "psmon", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/psmon/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/psmon", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/psuade-lite.json b/agency-indexes/DoE/psuade-lite.json new file mode 100644 index 00000000..a92604ad --- /dev/null +++ b/agency-indexes/DoE/psuade-lite.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-01-13", + "metadataLastUpdated": "2022-01-13" + }, + "description": "Lighter version of the Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE)", + "laborHours": 0.0, + "languages": [], + "name": "psuade-lite", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.1", + "name": "GPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/psuade-lite", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.9.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ptychopy.json b/agency-indexes/DoE/ptychopy.json new file mode 100644 index 00000000..2529469f --- /dev/null +++ b/agency-indexes/DoE/ptychopy.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-30" + }, + "description": "X-ray ptychography imaging at synchrotron facilities like the Advanced Photon Source (APS) involves controlling instrument hardwares to collect a set of diffraction patterns from overlapping coherent illumination spots on extended samples, managing data storage, reconstructing ptychographic images from acquired diffraction patterns, and providing the visualization of results and feedback. This brings up the need to develop a flexible, robust and user friendly processing pipeline for ptychographic data analysis. Here we present a software framework including visualization and ptychographic data reconstruction for streaming data analysis and reconstruction. ", + "laborHours": 4666.4, + "languages": [], + "name": "ptychopy", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kyuepublic/ptychopy", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ptyrodactyl.json b/agency-indexes/DoE/ptyrodactyl.json new file mode 100644 index 00000000..8633b59f --- /dev/null +++ b/agency-indexes/DoE/ptyrodactyl.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "mukherjeed@ornl.gov" + }, + "date": { + "created": "2024-11-24", + "metadataLastUpdated": "2024-11-24" + }, + "description": "Ptychography through Differentiable Programming\nThe aim of this project is to write the forward problem: aka writing the microscope data generation, both for electron and optical microscopes in JAX so that it's end to end differentiable and using this differentiability to run modern optimizers such as Adam and Adagrad to solve for the inverse problem - which is ptychography in our case.", + "laborHours": 577.6, + "languages": [ + "Python" + ], + "name": "ptyrodactyl", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/intersect-em/pterodactyl", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "version": "2024.08.26" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pv-system-profiler.json b/agency-indexes/DoE/pv-system-profiler.json new file mode 100644 index 00000000..daf63fab --- /dev/null +++ b/agency-indexes/DoE/pv-system-profiler.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-13", + "metadataLastUpdated": "2022-09-13" + }, + "description": "Estimating PV array location and orientation from real-world power datasets.", + "laborHours": 0.0, + "languages": [], + "name": "pv-system-profiler", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/pv-system-profiler", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pvOps_v.0.1.json b/agency-indexes/DoE/pvOps_v.0.1.json new file mode 100644 index 00000000..9483cba4 --- /dev/null +++ b/agency-indexes/DoE/pvOps_v.0.1.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-03-31", + "metadataLastUpdated": "2024-09-10" + }, + "description": "This python package contains a series of functions to facilitate fusion of text-based and time series production data collected at photovoltaic sites. The package also contains example datasets and tutorials to help demonstrate how the functions can be used. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.\nSAND2021-1554 O", + "laborHours": 12418.4, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "pvOps v.0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pvOps", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pvcracks.json b/agency-indexes/DoE/pvcracks.json new file mode 100644 index 00000000..f7f31c27 --- /dev/null +++ b/agency-indexes/DoE/pvcracks.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-06-06", + "metadataLastUpdated": "2024-06-06" + }, + "description": "SAND2024-00922O\nThis software uses electroluminescence images to predict power loss due to cell cracks in photovoltaic modules. The software will incorporate trained variational autoencoder(s) to parameterize cell cracks detected in electroluminescence images of photovoltaic modules and relate cracks to electrical properties; reduced-order models of finite element simulations of electrical behavior of photovoltaic modules under thermomechanical stresses; reduced-order models of stress distributions; inside photovoltaic modules resulting from x-ray topography experiments; and image segmentation and splining methods to analyze x-ray topography measurements of cracked photovoltaic cells. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python 3" + ], + "name": "pvcracks", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pvcracks", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/py-hostlist.json b/agency-indexes/DoE/py-hostlist.json new file mode 100644 index 00000000..ae6376fa --- /dev/null +++ b/agency-indexes/DoE/py-hostlist.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2018-12-17", + "metadataLastUpdated": "2018-12-18" + }, + "description": "py-hostlist processes slurm-style hostlist strings and can return those strings in manipulated fashion.", + "laborHours": 653.6, + "languages": [], + "name": "py-hostlist", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/py-hostlist", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/py-mochi-bake.json b/agency-indexes/DoE/py-mochi-bake.json new file mode 100644 index 00000000..8ab56ddf --- /dev/null +++ b/agency-indexes/DoE/py-mochi-bake.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-28", + "metadataLastUpdated": "2022-01-28" + }, + "description": "Python wrapper for BAKE.", + "laborHours": 0.0, + "languages": [], + "name": "py-mochi-bake", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/mochi-hpc/py-mochi-bake/blob/main/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/mochi-hpc/py-mochi-bake", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/py-mochi-remi.json b/agency-indexes/DoE/py-mochi-remi.json new file mode 100644 index 00000000..b90cb1cd --- /dev/null +++ b/agency-indexes/DoE/py-mochi-remi.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2022-01-28", + "metadataLastUpdated": "2022-01-28" + }, + "description": "Python wrapper to the REMI Mochi microservice.", + "laborHours": 0.0, + "languages": [], + "name": "py-mochi-remi", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": 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"name": "pyAMReX v23.08", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AMReX-Codes/pyamrex", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pyCP_APR.json b/agency-indexes/DoE/pyCP_APR.json new file mode 100644 index 00000000..da3c4da8 --- /dev/null +++ b/agency-indexes/DoE/pyCP_APR.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "pyCP_APR is a tensor decomposition and anomaly detection Python library that is designed for the fast analysis of large datasets by accelerating computation speed using GPUs. pyCP_APR uses the CANDECOMP/PARAFAC Alternating Poisson Regression (CP-APR) tensor factorization algorithm utilizing both Numpy and PyTorch backend. While the Numpy backend can be used for the analysis of both sparse and dense tensors, the PyTorch backend provides a faster decomposition of large and sparse tensors on the GPU. pyCP_APR's Scikit-learn like API allows comfortable interaction with the library, and includes the methods for statistical anomaly detection via the p-values obtained from the CP-APR factorization.", + "laborHours": 0.0, + "languages": [], + "name": "pyCP_APR", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyCP_APR", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pyCroscopy.json b/agency-indexes/DoE/pyCroscopy.json new file mode 100644 index 00000000..39ec4b9a --- /dev/null +++ b/agency-indexes/DoE/pyCroscopy.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Suite of Python Libraries that implement structure data format processing, multivariate analysis, and interactive visualization of microscopy data and other spectral imaging modalities, including scanning probe microscopy, electron microscopy, Bragg diffraction microscopy, and chemical imaging.", + "laborHours": 12783.2, + "name": "pyCroscopy", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pycroscopy/pycroscopy", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pyDAKOTA__Dakota_Driver__[SWR-13-16].json b/agency-indexes/DoE/pyDAKOTA__Dakota_Driver__[SWR-13-16].json new file mode 100644 index 00000000..2bcd456e --- /dev/null +++ b/agency-indexes/DoE/pyDAKOTA__Dakota_Driver__[SWR-13-16].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-11" + }, + "description": "pyDAKOTA is an interface to Sandia Laboratory's Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) analysis suite.\n\nAllows for users to construct DAKOTA input, feed the input to DAKOTA, and for DAKOTA to call a python object with a \"dakota_callback\" function for function evaluations.\n\nThis allows for a light-weight custom python interface to DAKOTA.\n\nThis is intended to be used with the OpenMDAO dakota driver\n\nAuthor: NREL WISDEM Team", + "laborHours": 699.2, + "languages": [ + "C++", + "Shell", + "CMake", + "Python" + ], + "name": "pyDAKOTA (Dakota Driver) [SWR-13-16]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wisdem/pyDAKOTA", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pyDRESCALk.json b/agency-indexes/DoE/pyDRESCALk.json new file mode 100644 index 00000000..cc93e3c0 --- /dev/null +++ b/agency-indexes/DoE/pyDRESCALk.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2022-01-06" + }, + "description": "Modern data scientists are tasked to analyze ever-growing data sets with increasingly complex relationships. Tensor decompositions have come to play a central role in identifying underlying latent structures in higher-order data. The problem of fitting tensor models to different distributions is complicated by the combinations of size, dimensionality, and sparsity present in real world data. The situation demands efficient algorithms designed for shared-memory and distributed systems. This work will present new research that tackles these challenges on several different fronts, leveraging optimizations in numerical algorithms and sparse tensor representations in heterogeneous high performance computing environments.", + "laborHours": 0.0, + "languages": [], + "name": "pyDRESCALk", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyDRESCALk", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pyDnMFk__Python_Distributed_Non_Negative_Matrix_Factorization_with_determination_of_hidden_features_.json b/agency-indexes/DoE/pyDnMFk__Python_Distributed_Non_Negative_Matrix_Factorization_with_determination_of_hidden_features_.json new file mode 100644 index 00000000..c6146288 --- /dev/null +++ b/agency-indexes/DoE/pyDnMFk__Python_Distributed_Non_Negative_Matrix_Factorization_with_determination_of_hidden_features_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-06-04", + "metadataLastUpdated": "2021-06-04" + }, + "description": "The capacity for big data manipulation and analysis has greatly evolved in the modern digital world due to varying sources such as social networks, medical scans, surveillance and monitoring systems, etc. Data mining and deep learning techniques are currently being utilized to understand the latent representation of the data using unsupervised approaches and also are known for their fast processing time. Even though these frameworks exhibit superior performance in supervised learning applications, however they are restricted in their algorithmic complexity and prove ineffective in computing the optimal latent representations for unsupervised applications. Non-Negative Matrix Factorization (NMF) techniques have proven effective in finding the most complex latent representations applied to a wide field of applications involving dimension reduction techniques applied to the fields of topic modeling, text mining, background separation in image/video datasets, anomaly detections and cancer detection. However NMF needs apriori information about the latent dimensionality. PyDnNMFk has NMF coupled with custom clustering that enables the recognition of the unknown latent dimensionality of the data along with the ability for an accurate reconstruction of the Factors. As the data size grows, the bottleneck due to the hardware computing/memory abilities grows too. Even though shared-memory based multiprocessing NMF frameworks perform faster compared to single core implementations, still the latency gives rise to the long wait times which might be an issue for time constraint applications. This raises the need for an optimal high performance implementation of NMF where the distributed memory and inter-process communication across massively parallel cores across multiple nodes tends to address the challenge. Hence we also provide Distributed implementation of NMFk, which can effectively factorize with identifying the latent dimensionality on exa-scale data. The implementations include a shared-memory multiprocessing based k estimation( pynNMFk), distributed memory inter-processor implementation(pyDnNMFk) and GPU factorization based implementation(pyGnNMFk) . The factor updates are based on Forbenius norm/KL divergence minimization criteria. ", + "laborHours": 0.0, + "languages": [], + "name": "pyDnMFk (Python Distributed Non Negative Matrix Factorization with determination of hidden features)", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pyDNMFk", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pyFEHM.json b/agency-indexes/DoE/pyFEHM.json new file mode 100644 index 00000000..76c8ea39 --- /dev/null +++ b/agency-indexes/DoE/pyFEHM.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kbadura@lanl.gov" + }, + "date": { + "created": "2018-04-10", + "metadataLastUpdated": "2018-04-11" + }, + "description": "PyFEHM is an open-source Python library that provides classes and methods to support a scripting environment for the subsurface heat and mass transfer, and geomechanics code FEHM. It is inspired by a similar library, PyTOUGH, available for use with the TOUGH2 family of codes. ", + "laborHours": 34382.4, + "name": "pyFEHM", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/PyFEHM", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pyGlobus.json b/agency-indexes/DoE/pyGlobus.json new file mode 100644 index 00000000..c43b4c5a --- /dev/null +++ b/agency-indexes/DoE/pyGlobus.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-05-21", + "metadataLastUpdated": "2021-06-07" + }, + "description": "pyGlobus provides a high-level object-oriented interface to the Globus Toolkit(r). 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The availability these networks in mainstream ML packages makes it easier to attach standard expansions and other approaches to make it more flexible and user friendly.", + "homepageURL": "https://pymsdtorch.readthedocs.io/en/latest", + "laborHours": 0.0, + "languages": [], + "name": "pyMSDtorch v0.1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://bitbucket.org/berkeleylab/pymsdtorch/src/main/LICENSE", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://pymsdtorch.readthedocs.io/en/latest", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/pyNuMAD_v.0.1.json b/agency-indexes/DoE/pyNuMAD_v.0.1.json new file mode 100644 index 00000000..e628c9dd --- /dev/null +++ b/agency-indexes/DoE/pyNuMAD_v.0.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-08-26", + "metadataLastUpdated": "2024-08-26" + }, + "description": "SAND2024-08606O\nThe pyNuMAD software is used for managing wind turbine blade model data. pyNuMAD specializes in defining the geometry, materials, and boundary conditions for structural analysis of wind turbine blades. 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SMARTS software can be obtained from: https://www.nrel.gov/grid/solar-resource/smarts.html Users will be responsible to obtain a copy of SMARTS from NREL, honor it's license, and download the SMART files into their PVLib folder. This wrapper is shared under a BSD-3-Clause License, and was originally coded in Matlab by Juan Russo (2001), updated and ported to python by Silvana Ayala (2019-2020).", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "pySMARTS: SMARTS Python Wrapper (Simple Model of the Atmospheric Radiative Transfer of Sunshine)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pySMARTS", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "Version: 0.18" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pySimFrac.json b/agency-indexes/DoE/pySimFrac.json new file mode 100644 index 00000000..bbc2aa31 --- /dev/null +++ b/agency-indexes/DoE/pySimFrac.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2024-07-12", + "metadataLastUpdated": "2024-07-12" + }, + "description": "pySimFrac is a python library for generating 3D synthetic fracture realizations, integrating with fluid simulators, and performing analysis.", + "laborHours": 1398.4, + "languages": [], + "name": "pySimFrac", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/pySimFrac", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pyWeb100.json b/agency-indexes/DoE/pyWeb100.json new file mode 100644 index 00000000..c3c7ea1b --- /dev/null +++ b/agency-indexes/DoE/pyWeb100.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2022-04-27" + }, + "description": "Provides an easy to use high-level interface to Web100. 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It acts as a channel access client, much like pyepics. The intention of the module is to provide better performance for embedded applications, rather than to provide an interactive interface. The most significant gains will be found when monitoring large waveforms that need to be processed before exposing them the Python layer.", + "laborHours": 2021.6, + "name": "pyca", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pyca/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pyca", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pycaserver.json b/agency-indexes/DoE/pycaserver.json new file mode 100644 index 00000000..857a2674 --- /dev/null +++ b/agency-indexes/DoE/pycaserver.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Python-based Channel Access Websockets Server. This is a tiny web server for getting channel access data via a WebSockets connection. Useful if you want to make a website that displays a real-time updating value of some PVs. 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It is currently the core analysis code powering the Materials Project.", + "laborHours": 1902280.0, + "languages": [ + "Python" + ], + "name": "pymatgen", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/materialsproject/pymatgen", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pyolog2.json b/agency-indexes/DoE/pyolog2.json new file mode 100644 index 00000000..37514f70 --- /dev/null +++ b/agency-indexes/DoE/pyolog2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "This is intended to be a simpler Python client to the Olog. It has one class, Client, with methods corresponding to each command in Olog's REST API. It includes automated tests that can be run without an Olog server, relying on previously recorded requests and responses in the source tree.", + "laborHours": 60.8, + "languages": [], + "name": "pyolog2", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/pyolog2", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pyperc_v._0.1.json b/agency-indexes/DoE/pyperc_v._0.1.json new file mode 100644 index 00000000..654b843d --- /dev/null +++ b/agency-indexes/DoE/pyperc_v._0.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2018-12-03", + "metadataLastUpdated": "2018-12-04" + }, + "description": "pyperc is a Python package for invasion percolation which models multiphase fluid migration in porous \nmedia. The model accounts for capillary pressure, buoyancy, and gravity. Regular and unstructured grids can be used. A tuning parameter can be set to adjust the stochastic nature of the process. Graphics depict fluid migration according to the invasion pressure.\n", + "laborHours": 410.4, + "languages": [ + "Python" + ], + "name": "pyperc v. 0.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pyperc", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "v. 0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pypm.json b/agency-indexes/DoE/pypm.json new file mode 100644 index 00000000..a8921475 --- /dev/null +++ b/agency-indexes/DoE/pypm.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "wehart@sandia.gov" + }, + "date": { + "created": "2024-01-02", + "metadataLastUpdated": "2024-01-02" + }, + "description": "Pypm supports the analysis of time series data to identify patterns that reflect the execution of a known process. Pypm uses a process model to identify patterns, where the execution of a process is decomposed into a sequence of related activities. A process model describes the activities used in the process, dependencies between activities that constrain their execution, resources needed to execute each activity and information about the activities that are observable.\n\nPypm implements process matching algorithms that infer a schedule of the activities in a process model to maximize the alignement of the process with observational data. Pypm uses numerical optimization to search for a maximal match score. When data is labeled and associated with the resources in the process model, then integer programming methods are used to find an optimal match. For unlabeled data, tabu search methods are used to predict data labels, which can then be used by integer programming methods.\n\nPypm solvers address a variety of complicating concerns, including variable-duration process activities, gaps in activity execution, preferences for compact matches, and tailored methods that depend on data characteristics.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "pypm", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/pypm", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "2.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pypressxrd.json b/agency-indexes/DoE/pypressxrd.json new file mode 100644 index 00000000..289f2689 --- /dev/null +++ b/agency-indexes/DoE/pypressxrd.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "Calibrate high-pressure using Au or Ag powder diffraction. Designed to be used with spec files from the 4-ID-D beamline, Advanced Photon Source, Argonne National Laboratory. ", + "laborHours": 851.2, + "languages": [], + "name": "pypressxrd", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gfabbris/pypressxrd", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pysmurf.json b/agency-indexes/DoE/pysmurf.json new file mode 100644 index 00000000..75cf4331 --- /dev/null +++ b/agency-indexes/DoE/pysmurf.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-06-16", + "metadataLastUpdated": "2022-06-16" + }, + "description": "The python control software for SMuRF. Includes scripts to do low level commands as well as higher level analysis.", + "laborHours": 0.0, + "languages": [], + "name": "pysmurf", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/pysmurf/blob/main/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/pysmurf", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pysnow.json b/agency-indexes/DoE/pysnow.json new file mode 100644 index 00000000..fde3ee86 --- /dev/null +++ b/agency-indexes/DoE/pysnow.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "Python library for the ServiceNow REST API focused on ease of use, simple code and elegant syntax. The REST API is active by default in all instances, starting with the Eureka release.", + "laborHours": 653.6, + "languages": [], + "name": "pysnow", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/pysnow", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pysofi_-_a_python_package_for_SOFI_analysis.json b/agency-indexes/DoE/pysofi_-_a_python_package_for_SOFI_analysis.json new file mode 100644 index 00000000..8ec71675 --- /dev/null +++ b/agency-indexes/DoE/pysofi_-_a_python_package_for_SOFI_analysis.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-10-28", + "metadataLastUpdated": "2021-10-28" + }, + "description": "this is a python package for SOFI analysis.", + "laborHours": 0.0, + "languages": [], + "name": "pysofi - a python package for SOFI analysis", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xiyuyi-at-LLNL/pysofi", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pytank__Python_Thermal_Tank_Model__[SWR-22-76].json b/agency-indexes/DoE/pytank__Python_Thermal_Tank_Model__[SWR-22-76].json new file mode 100644 index 00000000..9011110d --- /dev/null +++ b/agency-indexes/DoE/pytank__Python_Thermal_Tank_Model__[SWR-22-76].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-03-08", + "metadataLastUpdated": "2023-09-18" + }, + "description": "Thermal tank model that accounts for phase change of the tank medium.", + "laborHours": 0.0, + "languages": [ + "Jupyter Notebook", + "Python" + ], + "name": "pytank (Python Thermal Tank Model) [SWR-22-76]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/ThermalTank", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/python-lora.json b/agency-indexes/DoE/python-lora.json new file mode 100644 index 00000000..6d79fae6 --- /dev/null +++ b/agency-indexes/DoE/python-lora.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Python library for interacting with LLNL's Lorenz REST API.\n", + "laborHours": 273.6, + "languages": [], + "name": "python-lora", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/python-lora", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/python_binder_for_libROM.json b/agency-indexes/DoE/python_binder_for_libROM.json new file mode 100644 index 00000000..36c378e8 --- /dev/null +++ b/agency-indexes/DoE/python_binder_for_libROM.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2023-08-09", + "metadataLastUpdated": "2023-08-09" + }, + "description": "pylibROM introduces python binder for libROM through pybind11. Through python interface, users who are familiar with python can take advantage of capabilities available in libROM that is fully parallelized C++ library for reduced order modeling. libROM itself is an open source code developed at LLNL. libROM is available at https://github.com/LLNL/libROM .", + "laborHours": 0.0, + "languages": [], + "name": "python binder for libROM", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/pylibROM", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pyvisco_[SWR-22-30].json b/agency-indexes/DoE/pyvisco_[SWR-22-30].json new file mode 100644 index 00000000..e509d239 --- /dev/null +++ b/agency-indexes/DoE/pyvisco_[SWR-22-30].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2023-07-27" + }, + "description": "pyvisco is a Python library that supports the identification of Prony series parameters for linear viscoelastic materials described by a Generalized Maxwell model. The necessary material model parameters are identified by fitting a Prony series to the experimental measurement data. pyvisco allows for the identification of Prony series parameters from experimental data measured in either the frequency-domain (via Dynamic Mechanical Thermal Analysis) or time-domain (via relaxation measurements). The experimental data can be provided as raw measurement sets at different temperatures or as pre-processed master curves. An optional minimization routine is included to reduce the number of Prony elements. This routine is helpful in Finite Element simulations where reducing the computational complexity of the linear viscoelastic material models can shorten the simulation time.\n\nSee also, https://pypi.org/project/pyvisco/", + "laborHours": 0.0, + "languages": [ + "Python", + "Jupyter Notebook" + ], + "name": "pyvisco [SWR-22-30]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/pyvisco", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/pyvnc_client.json b/agency-indexes/DoE/pyvnc_client.json new file mode 100644 index 00000000..e500fa1f --- /dev/null +++ b/agency-indexes/DoE/pyvnc_client.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "weberb@ornl.gov" + }, + "date": { + "created": "2021-12-03", + "metadataLastUpdated": "2024-01-18" + }, + "description": "A python VNC client written from scratch using python's socket library", + "laborHours": 0.0, + "languages": [ + "Python", + "Python" + ], + "name": "pyvnc_client", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ORNL/pyvnc_client", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/qFeature.json b/agency-indexes/DoE/qFeature.json new file mode 100644 index 00000000..45c76908 --- /dev/null +++ b/agency-indexes/DoE/qFeature.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This package contains statistical routines for extracting features from multivariate time-series data which can then be used for subsequent multivariate statistical analysis to identify patterns and anomalous behavior. It calculates local linear or quadratic regression model fits to moving windows for each series and then summarizes the model coefficients across user-defined time intervals for each series. These methods are domain agnostic-but they have been successfully applied to a variety of domains, including commercial aviation and electric power grid data.", + "laborHours": 988.0, + "name": "qFeature", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/qFeature/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL/qFeature", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/qcintiming.json b/agency-indexes/DoE/qcintiming.json new file mode 100644 index 00000000..03e1c91b --- /dev/null +++ b/agency-indexes/DoE/qcintiming.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "Timing and fCRIC editor for the Berkeley FastCCD.", + "laborHours": 440.8, + "languages": [], + "name": "qcintiming", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/qcintiming", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/radkit_v1.2.json b/agency-indexes/DoE/radkit_v1.2.json new file mode 100644 index 00000000..10b91349 --- /dev/null +++ b/agency-indexes/DoE/radkit_v1.2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-08", + "metadataLastUpdated": "2021-09-08" + }, + "description": "The radkit software suite (python) consists of three primary libraries: stark, trajan, and curie. The trajan library provides the tools to analyze and manipulate data from lidar and inertial measurement unit (IMU) devices as well as trajectories from algorithms such as simultaneous localization and mapping (SLAM). These components allow reading and writing standard data formats, performing rigid affine transformations, discretizing three-dimensional space, and visualizing data products. The curie library comprises a standard set of object-oriented tools for radiation data and analysis in the following modules: (1) listmode and binmode data classes with methods for manipulation, plotting, slicing and file IO; (2) radiological/nuclear source detection/identification analysis results; (3) source encounters of correlated analyses and (4) energy-dependent angular detector response functions. The stark package provides low-level tools that are leveraged by both curie and trajan. The tools are flexible for offline analysis as well as performant for real-time integrations. The radkit libraries have associated Robot Operating System packages for use in real-time and robotic systems.", + "homepageURL": "https://sites.google.com/lbl.gov/2021-084/landing-page", + "laborHours": 0.0, + "languages": [], + "name": "radkit v1.2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://sites.google.com/lbl.gov/2021-084/landing-page", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://sites.google.com/lbl.gov/2021-084/landing-page", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/radolc.json b/agency-indexes/DoE/radolc.json new file mode 100644 index 00000000..85950e98 --- /dev/null +++ b/agency-indexes/DoE/radolc.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-31", + "metadataLastUpdated": "2019-07-31" + }, + "description": "Derivatives are required in many contexts: optimization, sensitivity analysis, uncertainty analysis, and parameter estimation. The radolc package is an interface to ADOL-C == a C++ library that facilitates the computation of first and higher derivatives of vector functions that are defined by computer programs. ADOL-C can compute gradients, the Jacobian matrix, the Hessian matrix, Jacobian vector products and Hessian vector products.", + "laborHours": 24852.0, + "languages": [], + "name": "radolc", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sriharikrishna/radolc", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ramdisk,_Version_0.x.json b/agency-indexes/DoE/ramdisk,_Version_0.x.json new file mode 100644 index 00000000..17c24011 --- /dev/null +++ b/agency-indexes/DoE/ramdisk,_Version_0.x.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The intent of the software is eventually to become a middleware library to provide a cross platform interface for creating and managing a ramdisk. Eventually it will cover many platforms (*nix, Windows, Mac), and have the library written in several languages. At this point, the library is a functional python library for managing a Mac ramdisk. Some code is also included in how to use the library. Initial intended uses for the library: archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Provide a throw-away filesystem for unit testing filesystem related functionality. archive deleteone.sql elink_2017_10_20.json file.json fix_on_records.sh just-doi-it.sh onrecords postfile.sh postit.sh solr-delete testrepos.sh wipe.postgresql Improve compile time when building software.", + "laborHours": 3754.4, + "name": "ramdisk, Version 0.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/csd-dev-tools/ramdisk", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rce-gen3-fw-lib.json b/agency-indexes/DoE/rce-gen3-fw-lib.json new file mode 100644 index 00000000..53cae948 --- /dev/null +++ b/agency-indexes/DoE/rce-gen3-fw-lib.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Firmware Libraries for RCE Platform Development", + "laborHours": 34260.8, + "name": "rce-gen3-fw-lib", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/rce-gen3-fw-lib/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/rce-gen3-fw-lib", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/reVX__The_Renewable_Energy_Potential_Exchange_Tool__[SWR-20-19].json b/agency-indexes/DoE/reVX__The_Renewable_Energy_Potential_Exchange_Tool__[SWR-20-19].json new file mode 100644 index 00000000..759cf35e --- /dev/null +++ b/agency-indexes/DoE/reVX__The_Renewable_Energy_Potential_Exchange_Tool__[SWR-20-19].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-03-04", + "metadataLastUpdated": "2023-05-31" + }, + "description": "reVX is a complementary toolset that enables the extraction, translation, and loading (ETL) of reV results into formats required by downstream models, such as RPM, ReEDS, and PLEXOS.\n\nSEE ALSO: https://github.com/NREL/revruns", + "laborHours": 12737.6, + "languages": [ + "Python" + ], + "name": "reVX (The Renewable Energy Potential Exchange Tool) [SWR-20-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/reVX", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/reV__The_Renewable_Energy_Potential_Model_-_Open_Source__[SWR-21-59,_SWR-20-20_and_SWR-17-34].json b/agency-indexes/DoE/reV__The_Renewable_Energy_Potential_Model_-_Open_Source__[SWR-21-59,_SWR-20-20_and_SWR-17-34].json new file mode 100644 index 00000000..1a6c881f --- /dev/null +++ b/agency-indexes/DoE/reV__The_Renewable_Energy_Potential_Model_-_Open_Source__[SWR-21-59,_SWR-20-20_and_SWR-17-34].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2023-08-25", + "metadataLastUpdated": "2023-08-25" + }, + "description": "The Renewable Energy Potential (reV) model is a first-of-its-kind detailed spatio-temporal modeling assessment tool that empowers users to calculate renewable energy capacity, generation, and cost based on geospatial intersection with grid infrastructure and land-use characteristics.\n\nThe National Renewable Energy Laboratory (NREL) developed the reV model to help utility planners, regional and national agencies, project and land developers, and researchers assess renewable energy resource potential. Available as open source since February 2020, the reV model currently supports photovoltaic, concentrating solar power, and wind turbine technologies. The tool can model a single site up to an entire continent at temporal resolutions ranging from five minutes to hourly, spanning a single year or multiple decades.\n\nBy automating access to resource data at unprecedented scale, fidelity, and flexibility, the reV model integrates formerly disparate analysis frameworks in the fields of resource modeling, technical potential, and renewable energy cost supply curves.\n\nThe reV model currently provides broad coverage across North America, South and Central Asia, the Middle East, South America, and South Africa to inform national- and international-scale analyses as well as regional infrastructure and deployment planning.", + "laborHours": 250526.4, + "languages": [ + "Python", + "PowerBuilder" + ], + "name": "reV (The Renewable Energy Potential Model - Open Source) [SWR-21-59, SWR-20-20 and SWR-17-34]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/reV", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.8.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/recordwhat.json b/agency-indexes/DoE/recordwhat.json new file mode 100644 index 00000000..27ff28ca --- /dev/null +++ b/agency-indexes/DoE/recordwhat.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "EPICS record debugging using ophyd Devices.", + "laborHours": 3207.2, + "languages": [], + "name": "recordwhat", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/recordwhat", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/redis-pubsub-stream.json b/agency-indexes/DoE/redis-pubsub-stream.json new file mode 100644 index 00000000..0365224e --- /dev/null +++ b/agency-indexes/DoE/redis-pubsub-stream.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Node.js module to send a stream of items to a Redis pubsub channel\n", + "laborHours": 25080.0, + "name": "redis-pubsub-stream", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/redis-pubsub-stream", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/redis-row-stream.json b/agency-indexes/DoE/redis-row-stream.json new file mode 100644 index 00000000..280d0b2f --- /dev/null +++ b/agency-indexes/DoE/redis-row-stream.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Node.js module to persist a stream of items to Redis\n", + "laborHours": 34975.2, + "name": "redis-row-stream", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/redis-row-stream", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/reference_data.json b/agency-indexes/DoE/reference_data.json new file mode 100644 index 00000000..f1529087 --- /dev/null +++ b/agency-indexes/DoE/reference_data.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-25", + "metadataLastUpdated": "2020-08-25" + }, + "description": "Codes for aggregating public reference data from remote sources.", + "laborHours": 395.2, + "languages": [], + "name": "reference_data", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/reference_data", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/refseq_importer.json b/agency-indexes/DoE/refseq_importer.json new file mode 100644 index 00000000..78ddaddb --- /dev/null +++ b/agency-indexes/DoE/refseq_importer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-08", + "metadataLastUpdated": "2020-09-08" + }, + "description": "This is the repository for \"refseq_importer\" developed by KBase. This is a KBase module generated by the KBase Software Development Kit (SDK).", + "laborHours": 851.2, + "languages": [], + "name": "refseq_importer", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/refseq_importer", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/relation_engine_bulk_update.json b/agency-indexes/DoE/relation_engine_bulk_update.json new file mode 100644 index 00000000..567fefbf --- /dev/null +++ b/agency-indexes/DoE/relation_engine_bulk_update.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-11", + "metadataLastUpdated": "2020-09-11" + }, + "description": "This is the repository for \"relation_engine_bulk_update\" developed by KBase. A KBase module generated by the KBase SDK.\n", + "laborHours": 972.8, + "languages": [], + "name": "relation_engine_bulk_update", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/relation_engine_bulk_update", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/repligit.json b/agency-indexes/DoE/repligit.json new file mode 100644 index 00000000..7a55c510 --- /dev/null +++ b/agency-indexes/DoE/repligit.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2025-03-21", + "metadataLastUpdated": "2025-03-21" + }, + "description": "repligit will be a python library which implements the git transfer protocol allowing git repositories to be\nmirrored between two locations without storing state locally.", + "laborHours": 152.0, + "languages": [], + "name": "repligit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/repligit", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/reveal.js.json b/agency-indexes/DoE/reveal.js.json new file mode 100644 index 00000000..67fc4d91 --- /dev/null +++ b/agency-indexes/DoE/reveal.js.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-03", + "metadataLastUpdated": "2019-07-03" + }, + "description": "A framework for easily creating beautiful presentations using HTML. reveal.js comes with a broad range of features including nested slides, Markdown contents, PDF export, speaker notes and a JavaScript API. There's also a fully featured visual editor and platform for sharing reveal.js presentations at slides.com.", + "laborHours": 10564.0, + "languages": [], + "name": "reveal.js", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/caproto-lightning-slides", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rhelhostinfo.json b/agency-indexes/DoE/rhelhostinfo.json new file mode 100644 index 00000000..7cfdc900 --- /dev/null +++ b/agency-indexes/DoE/rhelhostinfo.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-03-11", + "metadataLastUpdated": "2022-03-11" + }, + "description": "The goal of the isrhostinfo project is to enumerate security-significant Red Hat host application configuration data and send that data via syslog to an enterprise log server for analysis and monitoring. The project includes binaries for the RHEL7 and RHEL8 distros, python3 source code for RHEL6 support, bash helper scripts and the .yml configurations to enable another individual or organization to modify the source code and build organization-specific rpms through Gitlab and open-source CentOS Docker images.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "rhelhostinfo", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/rhelhostinfo_v1.x.json b/agency-indexes/DoE/rhelhostinfo_v1.x.json new file mode 100644 index 00000000..242b23ef --- /dev/null +++ b/agency-indexes/DoE/rhelhostinfo_v1.x.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-05-09", + "metadataLastUpdated": "2022-05-10" + }, + "description": "rhelhostinfo v1.x adds some functionality to the existing approved C21099 rhelhostinfo by identifying host configuration changes over time. It provides a framework that allows organizations to modify the application functionality for their own requirements, including the ability to configure or return a host to DoD STIG standards per the open-source openSCAP project using the XCCDF framework, identify user command-line history, enumerate the local OSI layer 3 environment, identify and assist with configuring the host firewall, conduct limited packet capture and identify relevant network information.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "rhelhostinfo v1.x", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/rhizome.json b/agency-indexes/DoE/rhizome.json new file mode 100644 index 00000000..0884fcec --- /dev/null +++ b/agency-indexes/DoE/rhizome.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "This software does the pre-processing necessary to use the iris latent topic feedback plugin for information retrieval.\n", + "laborHours": 304.0, + "languages": [], + "name": "rhizome", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/rhizome", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rishipillai_CSP-CorrCreep_ORNL.json b/agency-indexes/DoE/rishipillai_CSP-CorrCreep_ORNL.json new file mode 100644 index 00000000..f8099288 --- /dev/null +++ b/agency-indexes/DoE/rishipillai_CSP-CorrCreep_ORNL.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "pillairr@ornl.gov" + }, + "date": { + "created": "2022-03-28", + "metadataLastUpdated": "2022-03-28" + }, + "description": "The modeling tool developed in the current project provides lifetime assessment of three candidate materials 740H, 282 and 625 for sCO2/molten salts heat exchanger. The tool incorporated physics-based models that accounted for all relevant underlying degradation mechanisms (creep and corrosion). Reduced-order models enabled rapid simulations of realistic component lifetimes (~100kh) while still retaining the fidelity of the complex models.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "rishipillai/CSP-CorrCreep_ORNL", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rishipillai/CSP-CorrCreep_ORNL", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rkmlviewer.json b/agency-indexes/DoE/rkmlviewer.json new file mode 100644 index 00000000..04edfe73 --- /dev/null +++ b/agency-indexes/DoE/rkmlviewer.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-11-05", + "metadataLastUpdated": "2021-11-05" + }, + "description": "rkmlviewer is an application designed to read and display data encoded in the Keyhole Markup Language.\nThe application provides a graphical window with a first person style camera to view KML files in 3d.\nThe application is built to display \"large scale\" data (not suitable for resolution > 100km)\nrkmlviewer is written in Go, uses OpenGL 3.3 for rendering, and GLFW for cross platform windowing support.\nrkmlviewer contains a command line (ncurses style) gui to select application options at runtime.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "rkmlviewer", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/rlmolecule:_A_library_for_general-purpose_material_and_molecular_optimization_using_AlphaZero-style_reinforcement_learning.json b/agency-indexes/DoE/rlmolecule:_A_library_for_general-purpose_material_and_molecular_optimization_using_AlphaZero-style_reinforcement_learning.json new file mode 100644 index 00000000..856fc95f --- /dev/null +++ b/agency-indexes/DoE/rlmolecule:_A_library_for_general-purpose_material_and_molecular_optimization_using_AlphaZero-style_reinforcement_learning.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2020-12-18", + "metadataLastUpdated": "2020-12-21" + }, + "description": "This library includes in-progress code for the optimization of materials and molecules using reinforcement learning. This project seeks to develop a generalized machine learning approach for optimizing targeted, and often complex, functional properties over the space of possible material structures, allowing faster identification of promising candidates. Electronic and transport properties of materials are determined by their molecular structure (for molecules) or their crystal structure (for in-organic crystalline materials). The atomic composition, bonding, and 3-D-spatial arrangement in these systems therefore represent a vast, discontinuous search space for optimal candidates. This library implements AlphaZero style reinforcement learning applied to two worked examples: the optimization of stable organic radicals for redox flow batteries, and the determination of stable electrolyte species for solid state batteries. The current code contains proof-of-concept results run on the Eagle HPC system, while the completed package will be a flexible tool for material optimization across of number of energy-relevant fields, which leverages cloud compute resources for the majority of the computational heavy lifting.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "rlmolecule: A library for general-purpose material and molecular optimization using AlphaZero-style reinforcement learning", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rlmolecule", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rmd-runs.json b/agency-indexes/DoE/rmd-runs.json new file mode 100644 index 00000000..692fd56a --- /dev/null +++ b/agency-indexes/DoE/rmd-runs.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-21", + "metadataLastUpdated": "2024-06-18" + }, + "description": "The RMD_RUNS function will log10 transform peptide peak intensity, that is, peptide abundance data and determine if any LC-MS analyses (ie,runs) in a N x P peptide data set are statistical outliers. The statistical analysis is based on summarizing each LC-MS run as a vector of q=5 summary statistics which describe the peptide abundance distribution for a specific run; a N x q matrix is then analyzed using robust PCA to compute a robust estimate of the covariance matrix used in a the calculation of a robut Mahalanobis distance.", + "laborHours": 243.2, + "languages": [], + "name": "rmd-runs", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PNNL-Comp-Mass-Spec/rmd-runs", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rogue-example.json b/agency-indexes/DoE/rogue-example.json new file mode 100644 index 00000000..518a0ef3 --- /dev/null +++ b/agency-indexes/DoE/rogue-example.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2022-07-28" + }, + "description": "Example project for rogue", + "laborHours": 0.0, + "languages": [], + "name": "rogue-example", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://gitlab.osti.gov/osti-public/rogue-example/-/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.osti.gov/osti-public/rogue-example", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/rogue.json b/agency-indexes/DoE/rogue.json new file mode 100644 index 00000000..4d3cd608 --- /dev/null +++ b/agency-indexes/DoE/rogue.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "SLAC Python Based Hardware Abstraction & Data Acquisition System", + "laborHours": 14546.4, + "name": "rogue", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/rogue/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/rogue", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rollerball.json b/agency-indexes/DoE/rollerball.json new file mode 100644 index 00000000..c2291a1c --- /dev/null +++ b/agency-indexes/DoE/rollerball.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "wasim1@llnl.gov" + }, + "date": { + "created": "2022-10-06", + "metadataLastUpdated": "2022-10-06" + }, + "description": "RollerBall is a notepad++ plugin that provides the ability to automatically save files to a user specified web server.", + "laborHours": 0.0, + "languages": [], + "name": "rollerball", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/rollerball", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rose-compiler_matlab-frontend.json b/agency-indexes/DoE/rose-compiler_matlab-frontend.json new file mode 100644 index 00000000..0b5bd239 --- /dev/null +++ b/agency-indexes/DoE/rose-compiler_matlab-frontend.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2020-05-27" + }, + "description": "This is the repository for rose-compiler/matlab-frontend developed at Lawrence Livermore National Laboratory. \n", + "laborHours": 334.4, + "languages": [], + "name": "rose-compiler/matlab-frontend", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rose-compiler/matlab-frontend", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rose-compiler_rose-develop.json b/agency-indexes/DoE/rose-compiler_rose-develop.json new file mode 100644 index 00000000..d0144fc4 --- /dev/null +++ b/agency-indexes/DoE/rose-compiler_rose-develop.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "The latest development version of rose. It may not pass all regression tests.", + "laborHours": 5902403.2, + "languages": [], + "name": "rose-compiler/rose-develop", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rose-compiler/rose-develop", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rose-compiler_rose-edg3.json b/agency-indexes/DoE/rose-compiler_rose-edg3.json new file mode 100644 index 00000000..e5467fbc --- /dev/null +++ b/agency-indexes/DoE/rose-compiler_rose-edg3.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2019-06-04" + }, + "description": "This is the repository for rose-compiler/rose-edg3 developed at Lawrence Livermore National Laboratory. \n", + "laborHours": 5605912.0, + "languages": [], + "name": "rose-compiler/rose-edg3", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rose-compiler/rose", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rose-compiler_spack.json b/agency-indexes/DoE/rose-compiler_spack.json new file mode 100644 index 00000000..588a93ee --- /dev/null +++ b/agency-indexes/DoE/rose-compiler_spack.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-19", + "metadataLastUpdated": "2020-05-19" + }, + "description": "A flexible package manager that supports multiple versions, configurations, platforms, and compilers.", + "laborHours": 172520.0, + "languages": [], + "name": "rose-compiler/spack", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/rose-compiler/spack/blob/develop/COPYRIGHT", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rose-compiler/spack", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rox2vtk_v0.1.json b/agency-indexes/DoE/rox2vtk_v0.1.json new file mode 100644 index 00000000..40ca3230 --- /dev/null +++ b/agency-indexes/DoE/rox2vtk_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "ntheodore@lbl.gov" + }, + "date": { + "created": "2024-06-21", + "metadataLastUpdated": "2024-06-27" + }, + "description": "For the development of magnets for particle accellerators, the tool ROXIE from CERN has become a de facto standard. This script interprets the output files of ROXIE and translates them into a VTK file that can be read in ParaView for visualization.", + "laborHours": 273.6, + "languages": [], + "name": "rox2vtk v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/cmesse/rox2vtk.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rplexos_[SWR-14-19].json b/agency-indexes/DoE/rplexos_[SWR-14-19].json new file mode 100644 index 00000000..c4a3e0e7 --- /dev/null +++ b/agency-indexes/DoE/rplexos_[SWR-14-19].json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-09-16" + }, + "description": "rplexos is a R (statistical software framework; more? details below) package that processes and facilitates analysis of solution from PLEXOS. PLEXOS is a production cost model that is utilize to simulate the behavior of the power.systems and is developed and commercialized by Energy Exomplar. The intention is to make rptexos open-source so other PLEXOS users can utilize it.", + "laborHours": 2173.6, + "languages": [ + "C++", + "R" + ], + "name": "rplexos [SWR-14-19]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NREL/rplexos/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rplexos", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "1.1.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rquota.json b/agency-indexes/DoE/rquota.json new file mode 100644 index 00000000..026b068a --- /dev/null +++ b/agency-indexes/DoE/rquota.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "rquota provides drop-in replacements for the quota and repquota utilities on Linux and other UNIX-like operating systems. Its configuration file makes it possible to limit the file systems queried to only those of interest, and to alias them for human readability in quota output. Block counts are converted to human readable units. rquota supports remote NFS and, if configured --with-lustre, Lustre file systems. At this time it does not support quotas on local file systems.", + "laborHours": 1656.8, + "languages": [], + "name": "rquota", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/chaos/rquota", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rsed.json b/agency-indexes/DoE/rsed.json new file mode 100644 index 00000000..d66aa35a --- /dev/null +++ b/agency-indexes/DoE/rsed.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "\"rsed\" is an R package that contains tools for stream editing: manipulating text files by making insertions, replacements, deletions, substitutions, or commenting. It hails from the powerful Unix command, \"sed\". While the \"rsed\" package is not nearly as powerful as \"see\", it is much simpler to use. R programmers often write scripts that may require simple manipulation of text files. \"rsed\" addresses that need.", + "laborHours": 136.8, + "name": "rsed", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/rsed/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/rsed", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rubblepy.json b/agency-indexes/DoE/rubblepy.json new file mode 100644 index 00000000..64ea779f --- /dev/null +++ b/agency-indexes/DoE/rubblepy.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This code can be used to generate a damage map based on the presence of rubble. Rubble is often detectable in images with submeter resolution, and can indicate damage to structures from high winds or earthquakes. The process_images.py script outputs a mask indicating the pixels in the original image where rubble was detected. The mask can be used in a geospatial software application like ArcMap to generate a damage map based on the rubble density. The rubble detection mask will contain some false positives which are usually more isolated than true rubble, so a density map will provide a more accurate indication of affected areas than the indivdidual rubble detections will.", + "laborHours": 91.2, + "languages": [], + "name": "rubblepy", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pnnl/rubblepy/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/rubblepy", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ruckus.json b/agency-indexes/DoE/ruckus.json new file mode 100644 index 00000000..f2f72844 --- /dev/null +++ b/agency-indexes/DoE/ruckus.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "Vivado build system", + "laborHours": 1444.0, + "name": "ruckus", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/ruckus/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ruckus", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/rust_eng_fmt__Rust_Engineering_Format__[SWR-23-80].json b/agency-indexes/DoE/rust_eng_fmt__Rust_Engineering_Format__[SWR-23-80].json new file mode 100644 index 00000000..62bbbbd7 --- /dev/null +++ b/agency-indexes/DoE/rust_eng_fmt__Rust_Engineering_Format__[SWR-23-80].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-09-11", + "metadataLastUpdated": "2023-09-26" + }, + "description": "Rust Engineering Format is a small package that provides engineering notation formatting for float precision numbers in Rust.", + "laborHours": 0.0, + "languages": [ + "Rust" + ], + "name": "rust_eng_fmt (Rust Engineering Format) [SWR-23-80]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/rust_eng_fmt", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/s-blas.json b/agency-indexes/DoE/s-blas.json new file mode 100644 index 00000000..cf1e577b --- /dev/null +++ b/agency-indexes/DoE/s-blas.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-03-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "This package includes the implementation for four sparse linear algebra kernels: Sparse-Matrix-Vector-Multiplication (SpMV), Sparse-Triangular-Solve (SpTRSV), Sparse-Matrix-Transposition (SpTrans) and Sparse-Matrix-Matrix-Multiplication (SpMM) for Single-node Multi-GPU (scale-up) platforms such as NVIDIA DGX-1 and DGX-2.", + "laborHours": 5715.2, + "languages": [], + "name": "s-blas", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/s-blas", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/s3-browser.json b/agency-indexes/DoE/s3-browser.json new file mode 100644 index 00000000..7b93ba5e --- /dev/null +++ b/agency-indexes/DoE/s3-browser.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-05-09", + "metadataLastUpdated": "2022-05-10" + }, + "description": "Web application that interacts with the Amazon AWS S3 REST API to allow users to manage files and buckets without having to use the aws command line application.", + "laborHours": 0.0, + "languages": [], + "name": "s3-browser", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/s3-browser", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sCO2_heat_exchanger_control_software.json b/agency-indexes/DoE/sCO2_heat_exchanger_control_software.json new file mode 100644 index 00000000..cb4e8432 --- /dev/null +++ b/agency-indexes/DoE/sCO2_heat_exchanger_control_software.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-10", + "metadataLastUpdated": "2022-10-10" + }, + "description": "SAND2022-6992 O The sCO2 Heat Exchanger Control Software was written for control and operation of high temperature, high pressure supercritical CO2 systems designed for use as heat exchangers. The software was written using the basic LabVIEW package with LabVIEW modules added to it. The software controls valves and actuators, displays data from pressure transducers and thermocouples, and is able to record data at different storage rates. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "LabVIEW" + ], + "name": "sCO2 heat exchanger control software", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/SCO2_CONTROL_SOFTWARE", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sample_service_validator_config.json b/agency-indexes/DoE/sample_service_validator_config.json new file mode 100644 index 00000000..0fea93e7 --- /dev/null +++ b/agency-indexes/DoE/sample_service_validator_config.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-31", + "metadataLastUpdated": "2020-08-31" + }, + "description": "Stores the sample service metadata validation configuration file.", + "laborHours": 4286.4, + "languages": [], + "name": "sample_service_validator_config", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseIncubator/sample_service_validator_config", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sandialabs_BioCompoundML.json b/agency-indexes/DoE/sandialabs_BioCompoundML.json new file mode 100644 index 00000000..11818fd7 --- /dev/null +++ b/agency-indexes/DoE/sandialabs_BioCompoundML.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-03-01", + "metadataLastUpdated": "2024-09-17" + }, + "description": "BioCompoundML is a software tool for rapidly screening chemicals by chemical properties, using machine learning.", + "laborHours": 8876.8, + "languages": [ + "Python" + ], + "name": "sandialabs/BioCompoundML", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/BioCompoundML", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sandialabs_lapart-python.json b/agency-indexes/DoE/sandialabs_lapart-python.json new file mode 100644 index 00000000..8841018e --- /dev/null +++ b/agency-indexes/DoE/sandialabs_lapart-python.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-05-02", + "metadataLastUpdated": "2018-05-02" + }, + "description": "LAPART is an artificial neural network algorithm written in the Python programming language. The algorithm can learn patterns using multi-dimensional hyper boxes. It can also perfrom regression and classification calculations based on learned associations.", + "laborHours": 258.4, + "name": "sandialabs/lapart-python", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/unlicense", + "name": "Unlicense" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/lapart-python", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sandialabs_mac-sandbox.json b/agency-indexes/DoE/sandialabs_mac-sandbox.json new file mode 100644 index 00000000..84e3477c --- /dev/null +++ b/agency-indexes/DoE/sandialabs_mac-sandbox.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "ndbrook@sandia.gov" + }, + "date": { + "created": "2018-05-02", + "metadataLastUpdated": "2018-05-02" + }, + "description": "The software is an analyzer for automated sandbox analysis of malware on the OS X operating system. It runs inside an OS X virtual machine to collect data about what happens when a given file opened or run. As of August 2014, there was no sandbox software for Mac OS X malware, as it requires different methods from those used on the Windows OS (which most sandboxes are written for). This software adds OS X analysis capabilities to an existing open-source sandbox, Cuckoo Sandbox (https://cuckoosandbox.org/), which previously only worked for Windows. \n\nThe analyzer itself can take many different types of files as input: the traditional Mach-O and FAT executables, .app files, zip files, Python scripts, Java archives, and web pages, as well as PDFs and other documents. While the file is running, the analyzer also simulates rudimentary human interaction with clicks and mouse movements in order to bypass the tests some malware use to see if they are being analyzed. The analyzer outputs several different kinds of data: functions call traces, network captures, screenshots, and all created and modified files. This work also includes a static analysis Cuckoo module for Mach-O binary files. It extracts file structures, code library imports and exports, and signatures. This data can be used along with the analyzer results to create signatures for malware. ", + "laborHours": 1276.8, + "name": "sandialabs/mac-sandbox", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/mac-sandbox", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sandialabs_xyz.json b/agency-indexes/DoE/sandialabs_xyz.json new file mode 100644 index 00000000..d827742a --- /dev/null +++ b/agency-indexes/DoE/sandialabs_xyz.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-10-30", + "metadataLastUpdated": "2020-11-05" + }, + "description": "Tools for extracting and viewing information from zip archives. Simply extracts and displays zip file metadata in a format convenient for analysts.SAND2020-0168 M\n", + "laborHours": 364.8, + "languages": [ + "Python" + ], + "name": "sandialabs/xyz", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/xyz", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.20181129" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sas-temper.json b/agency-indexes/DoE/sas-temper.json new file mode 100644 index 00000000..28d9058a --- /dev/null +++ b/agency-indexes/DoE/sas-temper.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "hellerwt@ornl.gov" + }, + "date": { + "created": "2021-08-19", + "metadataLastUpdated": "2021-08-19" + }, + "description": "Modeling remains a considerable challenge for practitioners of SAXS and SANS because the materials being studied are not highly ordered, the length scales being studied are large, and the information content of the data is low. Data analysis is both challenging and time consuming. Novices often rely on the assistance of an expert, such as the instrument scientist who supported them at the facility where the experiment was performed, to analyze their data. The high flux provided by modern facilities makes it possible to study dozens of samples or sample conditions during a single trip. Ultimately, the high throughput of modern instruments limits access to instrument scientists. A bottleneck in the research effort results that reduces facility productivity. Sas-temper seeks to address this problem, as well as the intrinsic difficulties of being confident in non-linear least squared fitting of data, by providing tools that automate much of the manual process of initial data fitting and refinement, as well as by providing tools for characterizing the nature of the parameter space that fits the measured data. The tools provided by sas-temper help small-angle scattering practitioners transition data into results.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "sas-temper", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/wt3/sas_temper", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/sbang.json b/agency-indexes/DoE/sbang.json new file mode 100644 index 00000000..2721f3c5 --- /dev/null +++ b/agency-indexes/DoE/sbang.json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2021-10-28", + "metadataLastUpdated": "2021-10-28" + }, + "description": "sbang lets users run scripts with very long shebang (#!) lines. Many operating systems limit the length and number of possible arguments in shebang lines, making it hard to use interpreters that are deep in the directory hierarchy or require special arguments. To use it, a user puts the long shebang on the second line of their script, and makes sbang the interpreter, like this: #!/bin/sh /path/to/sbang #!/long/path/to/real/interpreter with arguments. sbang will run the real interpreter with the script as its argument.", + "laborHours": 0.0, + "languages": [], + "name": "sbang", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + }, + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spack/sbang", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sbovqaopt:_Surrogate-based_optimizer_for_variational_quantum_algorithms_v.0.1.0.json b/agency-indexes/DoE/sbovqaopt:_Surrogate-based_optimizer_for_variational_quantum_algorithms_v.0.1.0.json new file mode 100644 index 00000000..55b3de21 --- /dev/null +++ b/agency-indexes/DoE/sbovqaopt:_Surrogate-based_optimizer_for_variational_quantum_algorithms_v.0.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-07-27", + "metadataLastUpdated": "2024-09-12" + }, + "description": "SAND2022-13232 O\nThe sbovqaopt package provides a surrogate-based optimizer for variational quantum algorithms as introduced in the journal publication of the same title. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "sbovqaopt: Surrogate-based optimizer for variational quantum algorithms v.0.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sbovqaopt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/scikit-SUNDAE___SUN_DIALS_Differential_Algebraic_Equations__[SWR-24-137].json b/agency-indexes/DoE/scikit-SUNDAE___SUN_DIALS_Differential_Algebraic_Equations__[SWR-24-137].json new file mode 100644 index 00000000..a7f729cc --- /dev/null +++ b/agency-indexes/DoE/scikit-SUNDAE___SUN_DIALS_Differential_Algebraic_Equations__[SWR-24-137].json @@ -0,0 +1,36 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-04", + "metadataLastUpdated": "2024-11-19" + }, + "description": "Scikit-SUNDAE provides Python bindings to SUNDIALS integrators. The implicit differential algebraic (IDA) solver and C-based variable-coefficient ordinary differential equations (CVODE) solver are both included.\n\nThe name SUNDAE combines (SUN)DIALS and DAE, which stands for differential algebraic equations. Solvers specific to DAE problems are not frequently available in Python. An ordinary differential equation (ODE) solver is also included for completeness. ODEs can be categorized as a subset of DAEs (i.e., DAEs with no algebraic constraints).\n\nhttps://pypi.org/project/scikit-sundae", + "laborHours": 8375.2, + "languages": [ + "Makefile", + "C", + "Python", + "Cython" + ], + "name": "scikit-SUNDAE ((SUN)DIALS Differential Algebraic Equations) [SWR-24-137]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/scikit-sundae", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sciprovenance.json b/agency-indexes/DoE/sciprovenance.json new file mode 100644 index 00000000..aefd7890 --- /dev/null +++ b/agency-indexes/DoE/sciprovenance.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-01", + "metadataLastUpdated": "2019-07-01" + }, + "description": "Files relating to the Provenance Driven LDRD project between NSLS-II and CSI.", + "laborHours": 17449.6, + "languages": [], + "name": "sciprovenance", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/sciprovenance", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/scisample.json b/agency-indexes/DoE/scisample.json new file mode 100644 index 00000000..378bed73 --- /dev/null +++ b/agency-indexes/DoE/scisample.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-10-29", + "metadataLastUpdated": "2021-10-29" + }, + "description": "A package that implements a number of parameter sampling methods for scientific computing.", + "laborHours": 0.0, + "languages": [], + "name": "scisample", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/scisample", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/scllrf.json b/agency-indexes/DoE/scllrf.json new file mode 100644 index 00000000..796a3842 --- /dev/null +++ b/agency-indexes/DoE/scllrf.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "EPICS IOC code for LCLS-II superconducting low level RF system, talking to FPGAs using LBNL's protocol.\n", + "laborHours": 27572.8, + "languages": [], + "name": "scllrf", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/scllrf/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/scllrf", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/scons-novice.json b/agency-indexes/DoE/scons-novice.json new file mode 100644 index 00000000..31645548 --- /dev/null +++ b/agency-indexes/DoE/scons-novice.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2025-04-18", + "metadataLastUpdated": "2025-04-18" + }, + "description": "scons-novice is a re-write of the Software Carpentry https://software-carpentry.org/ \"make-novice\" source material https://github.com/swcarpentry/make-novice used to create the webpage lesson plan \"Automation and Make\" http://swcarpentry.github.io/make-novice/ which is licensed as under the Creative Commons Attribution license (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/.\n\nscons-novice changes the lesson to teach SCons instead of Make.", + "laborHours": 2264.8, + "languages": [], + "name": "scons-novice", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl-aea/scons-novice", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sdet-tool.json b/agency-indexes/DoE/sdet-tool.json new file mode 100644 index 00000000..5d60c9c2 --- /dev/null +++ b/agency-indexes/DoE/sdet-tool.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-08-30", + "metadataLastUpdated": "2018-08-30" + }, + "description": "The SDET Tool is used to create open-access power\ngrid data sets and facilitate updates of these data\nsets by the community. Pacific Northwest National\nLaboratory (PNNL) and its power industry and\nsoftware vendor partners are developing an\ninnovative sustainable data evolution technology\n(SDET) to create open-access power grid datasets\nand facilitate updates to these datasets by the power\ngrid community. The objective is to make this a\nsustained effort within and beyond the ARPA-E\nGRID DATA program so that the datasets can evolve\nover time and meet the current and future needs for\npower grid optimization and potentially other\napplications in power grid operation and planning.", + "homepageURL": "https://egriddata.org/dataset/sdet-tool", + "laborHours": 152.0, + "languages": [], + "name": "sdet-tool", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://egriddata.org/dataset/sdet-tool", + "status": "Development", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/sdk_ontology.json b/agency-indexes/DoE/sdk_ontology.json new file mode 100644 index 00000000..ace86df8 --- /dev/null +++ b/agency-indexes/DoE/sdk_ontology.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This is the repository for \"sdk_ontology\" developed by KBase. ", + "laborHours": 4788.0, + "languages": [], + "name": "sdk_ontology", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/ontology_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sdkbase.json b/agency-indexes/DoE/sdkbase.json new file mode 100644 index 00000000..7e3c4e37 --- /dev/null +++ b/agency-indexes/DoE/sdkbase.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "Repo for sdk base images.", + "laborHours": 182.4, + "languages": [], + "name": "sdkbase", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/sdkbase2", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sesh.json b/agency-indexes/DoE/sesh.json new file mode 100644 index 00000000..7cb90d36 --- /dev/null +++ b/agency-indexes/DoE/sesh.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "brownjm@ornl.gov" + }, + "date": { + "created": "2021-10-01", + "metadataLastUpdated": "2021-10-01" + }, + "description": "`sesh` calculates resonance self-shielding corrections for time-of-flight experimental data", + "laborHours": 0.0, + "languages": [ + "Fortran" + ], + "name": "sesh", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/brownjm1968/sesh", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sf-23-021_SONICC__SCALE-DEPENDENT_OMEGA_FOR_NEUTRINO_INITIAL_CONDITION_CODES_.json b/agency-indexes/DoE/sf-23-021_SONICC__SCALE-DEPENDENT_OMEGA_FOR_NEUTRINO_INITIAL_CONDITION_CODES_.json new file mode 100644 index 00000000..b001b44e --- /dev/null +++ b/agency-indexes/DoE/sf-23-021_SONICC__SCALE-DEPENDENT_OMEGA_FOR_NEUTRINO_INITIAL_CONDITION_CODES_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-17", + "metadataLastUpdated": "2023-08-17" + }, + "description": "SONICC computes density and velocity transfer functions for use in the initial conditions of \nmassive neutrino\ncosmological simulations. The transfer functions are backscaled using a scale-dependent growth \nfunction that produces self-consistent evolution for all three matter species (cold dark matter, \nbaryons, massive neutrinos) in the Newtonian forward model of cosmological simulations.\n\n", + "laborHours": 0.0, + "languages": [], + "name": "sf-23-021 SONICC (SCALE-DEPENDENT OMEGA FOR NEUTRINO INITIAL CONDITION CODES)", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://git.cels.anl.gov/hacc/sonicc", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/sf-24-103.json b/agency-indexes/DoE/sf-24-103.json new file mode 100644 index 00000000..500f0b9d --- /dev/null +++ b/agency-indexes/DoE/sf-24-103.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-12-09", + "metadataLastUpdated": "2024-12-09" + }, + "description": "pyzag is a library for efficiently training generic models defined with a recursive nonlinear function. We developed it primarily to provide an efficient means to train NEML2 models\n it can be used to train other, more general types of models.", + "laborHours": 1079.2, + "languages": [], + "name": "sf-24-103", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/applied-material-modeling/pyzag", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sfapi_client_v1.0.json b/agency-indexes/DoE/sfapi_client_v1.0.json new file mode 100644 index 00000000..0a4d171c --- /dev/null +++ b/agency-indexes/DoE/sfapi_client_v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2023-05-17", + "metadataLastUpdated": "2023-05-17" + }, + "description": "This software is a client designed to interact with the Superfacility API developed at NERSC. It allows users to easily access the api in python and programmatically interact with the compute resources available at NERSC. Other implementations are ad-hoc and made by our user base, the goal of the project is to encourage more users to adopt the API by making it easier to start building complex HPC workflows.", + "laborHours": 0.0, + "languages": [], + "name": "sfapi_client v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/sfapi_client", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/shadow-ssml.json b/agency-indexes/DoE/shadow-ssml.json new file mode 100644 index 00000000..9d0c5468 --- /dev/null +++ b/agency-indexes/DoE/shadow-ssml.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "dzander@sandia.gov" + }, + "date": { + "created": "2020-03-12", + "metadataLastUpdated": "2021-03-05" + }, + "description": "Shadow is a PyTorch based library for semi-supervised machine learning via consistency regularization.", + "laborHours": 820.8, + "languages": [ + "Python" + ], + "name": "shadow-ssml", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/shadow", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/shibboleth_session_auth.json b/agency-indexes/DoE/shibboleth_session_auth.json new file mode 100644 index 00000000..49e83820 --- /dev/null +++ b/agency-indexes/DoE/shibboleth_session_auth.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "Simplistic Shibboleth integration for Django sessions. This is a very simple way of allowing users to be authenticated via Shibboleth but to be a part of Django groups and users. This is accomplished by using Apache mod_shib to protect the provided view. If the user is able to authenticate then we extract certain details from the data provided by Shibboleth. The view will create Django Users and Groups as necessary.", + "laborHours": 288.8, + "languages": [], + "name": "shibboleth_session_auth", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/shibboleth_session_auth/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/shibboleth_session_auth", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/shiftNMFk_1.1:_Robust_Nonnegative_matrix_factorization_with_kmeans_clustering_and_signal_shift,_for_allocation_of_unknown_physical_sources,_toy_version_for_open_sourcing_with_publications.json b/agency-indexes/DoE/shiftNMFk_1.1:_Robust_Nonnegative_matrix_factorization_with_kmeans_clustering_and_signal_shift,_for_allocation_of_unknown_physical_sources,_toy_version_for_open_sourcing_with_publications.json new file mode 100644 index 00000000..155865a8 --- /dev/null +++ b/agency-indexes/DoE/shiftNMFk_1.1:_Robust_Nonnegative_matrix_factorization_with_kmeans_clustering_and_signal_shift,_for_allocation_of_unknown_physical_sources,_toy_version_for_open_sourcing_with_publications.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This code is a toy (short) version of CODE-2016-83. From a general perspective, the code represents an unsupervised adaptive machine learning algorithm that allows efficient and high performance de-mixing and feature extraction of a multitude of non-negative signals mixed and recorded by a network of uncorrelated sensor arrays. The code identifies the number of the mixed original signals and their locations. Further, the code also allows deciphering of signals that have been delayed in regards to the mixing process in each sensor. This code is high customizable and it can be efficiently used for a fast macro-analyses of data. The code is applicable to a plethora of distinct problems: chemical decomposition, pressure transient decomposition, unknown sources/signal allocation, EM signal decomposition. An additional procedure for allocation of the unknown sources is incorporated in the code.", + "laborHours": 1960.8, + "name": "shiftNMFk 1.1: Robust Nonnegative matrix factorization with kmeans clustering and signal shift, for allocation of unknown physical sources, toy version for open sourcing with publications", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/rNMF/ShiftNMFk.jl/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/rNMF/ShiftNMFk.jl", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/shifter.json b/agency-indexes/DoE/shifter.json new file mode 100644 index 00000000..37250274 --- /dev/null +++ b/agency-indexes/DoE/shifter.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "aespiritu@lbl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Shifter enables application virtualization or containerization in large-scale HPC environments. This technology decreases the effort to port applications to or between HPC sites while increasing reproducibility and scientific productivity. Shifter works by converting application/container images to a common format, and then leverages basic Linux functionality to make that image available to batch jobs run in the HPC environment.", + "laborHours": 13756.0, + "name": "shifter", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NERSC/shifter/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/shifter", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/shock_java_client.json b/agency-indexes/DoE/shock_java_client.json new file mode 100644 index 00000000..18101a36 --- /dev/null +++ b/agency-indexes/DoE/shock_java_client.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-13", + "metadataLastUpdated": "2020-08-13" + }, + "description": "Basic java client for the Shock service. Supports node creation, deletion and retrieval of a subset of node data, streaming file up/download, viewing ACLs, and limited ACL modification.", + "laborHours": 1520.0, + "languages": [], + "name": "shock_java_client", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/shock_java_client", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/shock_service.json b/agency-indexes/DoE/shock_service.json new file mode 100644 index 00000000..feb084d8 --- /dev/null +++ b/agency-indexes/DoE/shock_service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-21", + "metadataLastUpdated": "2020-08-21" + }, + "description": "Enables deployment of shock server and clients within the kbase release environment.", + "laborHours": 21371.2, + "languages": [], + "name": "shock_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/shock_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sim_service.json b/agency-indexes/DoE/sim_service.json new file mode 100644 index 00000000..7bfd549a --- /dev/null +++ b/agency-indexes/DoE/sim_service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "A module for sequence similarity service.", + "laborHours": 197.6, + "languages": [], + "name": "sim_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/sim_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/simcov_v0.1.json b/agency-indexes/DoE/simcov_v0.1.json new file mode 100644 index 00000000..566b78af --- /dev/null +++ b/agency-indexes/DoE/simcov_v0.1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-09-22", + "metadataLastUpdated": "2021-09-22" + }, + "description": "Simcov is an agent-based model of the spread of viral infections and the immune response in human lung at the cellular level. It is designed to scale well on HPC systems. No other software like it currently exists.", + "laborHours": 0.0, + "languages": [], + "name": "simcov v0.1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/AdaptiveComputationLab/simcov.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/simple-lookup-service.json b/agency-indexes/DoE/simple-lookup-service.json new file mode 100644 index 00000000..c8830508 --- /dev/null +++ b/agency-indexes/DoE/simple-lookup-service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "ESnet has designed a REST/JSON based lookup service called the \"simple Lookup Service\", or sLS. Clients can use simple HTTP POST to register list of key-value pairs called \"records\" and use HTTP GET to search and retrieve existing records from server. The lookup service may be run as a simple stand-alone server or as a distributed service. This service is initially targeted at perfSONAR, but also can be used as a general purpose search mechanism for any key-value pairs.", + "laborHours": 7873.6, + "languages": [], + "name": "simple-lookup-service", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/simple-lookup-service/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/simple-lookup-service", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/simple_fba.json b/agency-indexes/DoE/simple_fba.json new file mode 100644 index 00000000..514f5a01 --- /dev/null +++ b/agency-indexes/DoE/simple_fba.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "Simple wrappers around fba tools.", + "laborHours": 258.4, + "languages": [], + "name": "simple_fba", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/simple_fba", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/simsee.json b/agency-indexes/DoE/simsee.json new file mode 100644 index 00000000..154c790b --- /dev/null +++ b/agency-indexes/DoE/simsee.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "asauers@fnal.gov" + }, + "date": { + "created": "2018-03-26", + "metadataLastUpdated": "2019-04-17" + }, + "description": "Simsee is a program for generating artificial seeing data for simulations of astronomical surveys. It includes a jupyter notebook for deriving model parameters from Dual Image Motion Monitor (DIMM) data, and a program that reads these model parameters and creates a data file suitable for use by survey strategy simulation code (which is outside the scope of this package). It is specifically designed to provide input data for LSST\u2019s opsim4 survey simulator, but may be adapted for use with different simulators as well. The code is verified to work on a Linux workstation with an Intel Xeon E5-6980 CPU and 256GB or memory, but should work fine on systems with far more limited resources.", + "laborHours": 12479.2, + "languages": [], + "name": "simsee", + "organization": "Fermi National Accelerator Laboratory (FNAL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LSSTDESC/ObsStrat", + "status": "Production", + "tags": [ + "DOE CODE", + "Fermi National Accelerator Laboratory (FNAL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/simul.json b/agency-indexes/DoE/simul.json new file mode 100644 index 00000000..377ec0b2 --- /dev/null +++ b/agency-indexes/DoE/simul.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "\"simul\" is an MPI coordinated test of parallel filesystem system calls and library functions. It was designed to perform filesystem operations simultaneously from many nodes and processes to test the correctness and coherence of parallel filesystems.\n", + "laborHours": 486.4, + "languages": [], + "name": "simul", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/simul", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/singularity-eos.json b/agency-indexes/DoE/singularity-eos.json new file mode 100644 index 00000000..902576a3 --- /dev/null +++ b/agency-indexes/DoE/singularity-eos.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-02", + "metadataLastUpdated": "2021-07-02" + }, + "description": "singularity-eos is a library that provides a unified interface and performance portable implementations of equations of state (EOS). The library includes a set of simple analytic models that are all published in the open literature and generic tabulated EOS capabilities that build on a generic table interpolation library that is being released under a separate disclosure. However, absolutely no tabulated data for material EOS is included in singularity-eos. Instead, users of singularity-eos need to provide the tabulated data.", + "laborHours": 0.0, + "languages": [], + "name": "singularity-eos", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/singularity-eos", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/singularity-opac.json b/agency-indexes/DoE/singularity-opac.json new file mode 100644 index 00000000..98b5e360 --- /dev/null +++ b/agency-indexes/DoE/singularity-opac.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-07-30", + "metadataLastUpdated": "2021-07-30" + }, + "description": "singularity-opac is a library for providing a unified interface for opacities, emissivities, and scattering cross-sections for materials and use in simulation codes. 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+ ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/slaclab_lcls-cu-inj-live.json b/agency-indexes/DoE/slaclab_lcls-cu-inj-live.json new file mode 100644 index 00000000..c76db730 --- /dev/null +++ b/agency-indexes/DoE/slaclab_lcls-cu-inj-live.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-09", + "metadataLastUpdated": "2022-08-09" + }, + "description": "This project contains the tools for running the live online model for the lcls-cu injector. 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index 00000000..a778444c --- /dev/null +++ b/agency-indexes/DoE/slaclab_smurf-atca-monitor.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-10", + "metadataLastUpdated": "2022-08-10" + }, + "description": "Rogue application which uses IPMI to monitor information from an ATCA system.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/smurf-atca-monitor", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/smurf-atca-monitor/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/smurf-atca-monitor", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/slaclab_smurf-base-docker.json 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a/agency-indexes/DoE/slaclab_smurf-matlab-ioc.json b/agency-indexes/DoE/slaclab_smurf-matlab-ioc.json new file mode 100644 index 00000000..d59f6958 --- /dev/null +++ b/agency-indexes/DoE/slaclab_smurf-matlab-ioc.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-24", + "metadataLastUpdated": "2022-08-24" + }, + "description": "SLAC's Matlab support IOC Docker image for the SMuRF project.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/smurf-matlab-ioc", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/smurf-matlab-ioc/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/smurf-matlab-ioc", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/slaclab_smurf-pcie-docker.json b/agency-indexes/DoE/slaclab_smurf-pcie-docker.json new file mode 100644 index 00000000..c4073062 --- /dev/null +++ b/agency-indexes/DoE/slaclab_smurf-pcie-docker.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-10", + "metadataLastUpdated": "2022-08-10" + }, + "description": "This docker image, named smurf-pcie contains debugging tools for the SMuRF project.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/smurf-pcie-docker", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/smurf-pcie-docker/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/smurf-pcie-docker", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/slaclab_smurf-pcie.json b/agency-indexes/DoE/slaclab_smurf-pcie.json new file mode 100644 index 00000000..0e955bd4 --- /dev/null +++ b/agency-indexes/DoE/slaclab_smurf-pcie.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-15", + "metadataLastUpdated": "2022-08-16" + }, + "description": "This is the repository for \"smurf-pcie\" developed by SLAC National Accelerator Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/smurf-pcie", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/smurf-pcie/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/smurf-pcie", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/slaclab_smurf-processor-base-docker.json b/agency-indexes/DoE/slaclab_smurf-processor-base-docker.json new file mode 100644 index 00000000..d33b92ac --- /dev/null +++ b/agency-indexes/DoE/slaclab_smurf-processor-base-docker.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-17", + "metadataLastUpdated": "2022-08-17" + }, + "description": "This docker image, named smurf-processor-base contains smurf-processor and additional tools used by the SMuRF project. It is based on the smurf-rogue docker image and contains smurf-processor.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/smurf-processor-base-docker", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/smurf-processor-base-docker/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/smurf-processor-base-docker", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/slaclab_smurf-rogue-docker.json b/agency-indexes/DoE/slaclab_smurf-rogue-docker.json new file mode 100644 index 00000000..da21486d --- /dev/null +++ b/agency-indexes/DoE/slaclab_smurf-rogue-docker.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-09", + "metadataLastUpdated": "2022-08-09" + }, + "description": "This docker image, named smurf-rogue contains Rogue and additional tools used by the SMuRF project. 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is the repository for \"smurf2mce\" developed by SLAC National Accelerator Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/smurf2mce", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/smurf2mce/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/smurf2mce", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/slaclab_smurftestapps.json b/agency-indexes/DoE/slaclab_smurftestapps.json new file mode 100644 index 00000000..fa5ad646 --- /dev/null +++ b/agency-indexes/DoE/slaclab_smurftestapps.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-17", + "metadataLastUpdated": 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"2022-08-10", + "metadataLastUpdated": "2022-08-10" + }, + "description": "This is the repository for \"surf-axi-protocol-checking\" developed by SLAC National Accelerator Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/surf-axi-protocol-checking", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/surf-axi-protocol-checking/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/surf-axi-protocol-checking", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/slaclab_surf-dcp-targets.json b/agency-indexes/DoE/slaclab_surf-dcp-targets.json new file mode 100644 index 00000000..e11c5348 --- /dev/null +++ b/agency-indexes/DoE/slaclab_surf-dcp-targets.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-16", + "metadataLastUpdated": "2022-08-16" + }, + "description": "This is the repository for \"surf-dcp-targets\" developed by SLAC National Accelerator Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/surf-dcp-targets", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/surf-dcp-targets/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/surf-dcp-targets", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/slaclab_tid-id-smartsheets.json b/agency-indexes/DoE/slaclab_tid-id-smartsheets.json new file mode 100644 index 00000000..49f7ec12 --- /dev/null +++ b/agency-indexes/DoE/slaclab_tid-id-smartsheets.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-07-07", + "metadataLastUpdated": "2022-07-07" + }, + "description": "TID ID Smartsheets Scripts.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/tid-id-smartsheets", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/tid-id-smartsheets/blob/main/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/tid-id-smartsheets", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/slaclab_timetool-spatial.json b/agency-indexes/DoE/slaclab_timetool-spatial.json new file mode 100644 index 00000000..90da8dde --- /dev/null +++ b/agency-indexes/DoE/slaclab_timetool-spatial.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-17", + "metadataLastUpdated": "2022-08-17" + }, + "description": "This is the repository for \"timetool-spatial\" developed by SLAC National Accelerator Laboratory.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/timetool-spatial", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/timetool-spatial/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/timetool-spatial", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/slaclab_ttdatabenchmarking.json b/agency-indexes/DoE/slaclab_ttdatabenchmarking.json new file mode 100644 index 00000000..a05f79ce --- /dev/null +++ b/agency-indexes/DoE/slaclab_ttdatabenchmarking.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-01", + "metadataLastUpdated": "2022-09-01" + }, + "description": "Benchmarking ml algorithms against TimeTool data.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/ttdatabenchmarking", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/ttdatabenchmarking/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/ttdatabenchmarking", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/slaclab_uboot-xlnx-rce.json b/agency-indexes/DoE/slaclab_uboot-xlnx-rce.json new file mode 100644 index 00000000..3225f46d --- /dev/null +++ b/agency-indexes/DoE/slaclab_uboot-xlnx-rce.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-16", + "metadataLastUpdated": "2022-08-16" + }, + "description": "This directory contains the source code for U-Boot, a boot loader for Embedded boards based on PowerPC, ARM, MIPS and several other processors, which can be installed in a boot ROM and used to initialize and test the hardware or to download and run application code.", + "laborHours": 0.0, + "languages": [], + "name": "slaclab/uboot-xlnx-rce", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": 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In addition, smoothG also provides efficient linear solvers for the reduced models. Other than pure graph problem, the software finds its application in subsurface flow and power grid simulations in which graph Laplacians are found", + "laborHours": 9986.4, + "languages": [ + "C++ (100%)" + ], + "name": "smoothG", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "http://github.com/LLNL/smoothG", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/smwflow.v2018.05.0.json b/agency-indexes/DoE/smwflow.v2018.05.0.json new file mode 100644 index 00000000..f9188b33 --- /dev/null +++ b/agency-indexes/DoE/smwflow.v2018.05.0.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-07-18", + "metadataLastUpdated": "2018-07-19" + }, + "description": "smwflow imports and exports Cray system management configurations to and from git repositories. smwflow implements both the mechanism for this and, in combination with git, implements a systems engineering workflow that can be used to manage multiple systems, enable rational implementation of features, and add traceability to systems management activities.", + "laborHours": 836.0, + "languages": [ + "SMW 8.0 / CLE 6.0" + ], + "name": "smwflow.v2018.05.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NERSC/smwflow", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sndust.json b/agency-indexes/DoE/sndust.json new file mode 100644 index 00000000..4d2e3167 --- /dev/null +++ b/agency-indexes/DoE/sndust.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-10", + "metadataLastUpdated": "2021-09-10" + }, + "description": "A collection of python scripts to load in data from supernovae simulations and use that data to model chemistry and astrophysical dust formation.", + "laborHours": 0.0, + "languages": [], + "name": "sndust", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/sndust", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/snp2gene.json b/agency-indexes/DoE/snp2gene.json new file mode 100644 index 00000000..f20e4801 --- /dev/null +++ b/agency-indexes/DoE/snp2gene.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-17", + "metadataLastUpdated": "2020-09-17" + }, + "description": "This is the repository for \"snp2gene\" developed by KBase. This is a KBase module generated by the KBase Software Development Kit (SDK).", + "laborHours": 988.0, + "languages": [], + "name": "snp2gene", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbasecollaborations/snp2gene", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/solar-data-pipeline.json b/agency-indexes/DoE/solar-data-pipeline.json new file mode 100644 index 00000000..397912d7 --- /dev/null +++ b/agency-indexes/DoE/solar-data-pipeline.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-14", + "metadataLastUpdated": "2022-09-14" + }, + "description": "Gets solar data from various sources.", + "laborHours": 0.0, + "languages": [], + "name": "solar-data-pipeline", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/solar-data-pipeline", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/solar-data-retrieval.json b/agency-indexes/DoE/solar-data-retrieval.json new file mode 100644 index 00000000..8a139a9a --- /dev/null +++ b/agency-indexes/DoE/solar-data-retrieval.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-14", + "metadataLastUpdated": "2022-09-14" + }, + "description": "Retrieving and preprocessing solar data to be used for dictionary learning based on random choice of sites and sizes.", + "laborHours": 0.0, + "languages": [], + "name": "solar-data-retrieval", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/solar-data-retrieval", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/solar-data-tools.json b/agency-indexes/DoE/solar-data-tools.json new file mode 100644 index 00000000..7ceb3d13 --- /dev/null +++ b/agency-indexes/DoE/solar-data-tools.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-07", + "metadataLastUpdated": "2022-09-07" + }, + "description": "Tools for performing common tasks on solar PV data signals. These tasks include finding clear days in a data set, common data transforms, and fixing time stamp issues. These tools are designed to be automatic and require little if any input from the user. Libraries are included to help with data IO and plotting as well.", + "laborHours": 0.0, + "languages": [], + "name": "solar-data-tools", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/solar-data-tools", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/solar-fingerprinting.json b/agency-indexes/DoE/solar-fingerprinting.json new file mode 100644 index 00000000..95468125 --- /dev/null +++ b/agency-indexes/DoE/solar-fingerprinting.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-09-09", + "metadataLastUpdated": "2022-09-12" + }, + "description": "An algorithm for creating a low-dimensional representation (fingerprint) of daily photovoltaic solar power generation signals.", + "laborHours": 0.0, + "languages": [], + "name": "solar-fingerprinting", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slacgismo/solar-fingerprinting", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sollve_vv.json b/agency-indexes/DoE/sollve_vv.json new file mode 100644 index 00000000..6d35efd3 --- /dev/null +++ b/agency-indexes/DoE/sollve_vv.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-15", + "metadataLastUpdated": "2020-05-15" + }, + "description": "OpenMP Offloading Validation & Verification Suite", + "laborHours": 27314.4, + "languages": [], + "name": "sollve_vv", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/SOLLVE/sollve_vv", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/spammpack,_Version_2013-06-18.json b/agency-indexes/DoE/spammpack,_Version_2013-06-18.json new file mode 100644 index 00000000..4eb58de8 --- /dev/null +++ b/agency-indexes/DoE/spammpack,_Version_2013-06-18.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kathleen_m@lanl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "This library is an implementation of the Sparse Approximate Matrix Multiplication (SpAMM) algorithm introduced. It provides a matrix data type, and an approximate matrix product, which exhibits linear scaling computational complexity for matrices with decay. The product error and the performance of the multiply can be tuned by choosing an appropriate tolerance. The library can be compiled for serial execution or parallel execution on shared memory systems with an OpenMP capable compiler", + "laborHours": 588726.4, + "name": "spammpack, Version 2013-06-18", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/FreeON/spammpack", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sparse-msrf:A_package_for_sparse_modeling_and_estimation_of_fossil-fuel_CO2_emission_fields.json b/agency-indexes/DoE/sparse-msrf:A_package_for_sparse_modeling_and_estimation_of_fossil-fuel_CO2_emission_fields.json new file mode 100644 index 00000000..e38b1a5c --- /dev/null +++ b/agency-indexes/DoE/sparse-msrf:A_package_for_sparse_modeling_and_estimation_of_fossil-fuel_CO2_emission_fields.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2024-07-24" + }, + "description": "The software is used to fit models of emission fields (e.g., fossil-fuel CO2 emissions) to sparse measurements of gaseous concentrations. Its primary aim is to provide an implementation and a demonstration for the algorithms and models developed in J. Ray, V. Yadav, A. M. Michalak, B. van Bloemen Waanders and S. A. McKenna, \"A multiresolution spatial parameterization for the estimation of fossil-fuel carbon dioxide emissions via atmospheric inversions\", accepted, Geoscientific Model Development, 2014. The software can be used to estimate emissions of non-reactive gases such as fossil-fuel CO2, methane etc. The software uses a proxy of the emission field being estimated (e.g., for fossil-fuel CO2, a population density map is a good proxy) to construct a wavelet model for the emission field. It then uses a shrinkage regression algorithm called Stagewise Orthogonal Matching Pursuit (StOMP) to fit the wavelet model to concentration measurements, using an atmospheric transport model to relate emission and concentration fields. Algorithmic novelties described in the paper above (1) ensure that the estimated emission fields are non-negative, (2) allow the use of guesses for emission fields to accelerate the estimation processes and (3) ensure that under/overestimates in the guesses do not skew the estimation.", + "laborHours": 0.0, + "languages": [ + "MATLAB" + ], + "name": "sparse-msrf:A package for sparse modeling and estimation of fossil-fuel CO2 emission fields", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/sparse-msrf", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/spdlayers.json b/agency-indexes/DoE/spdlayers.json new file mode 100644 index 00000000..b7d8f208 --- /dev/null +++ b/agency-indexes/DoE/spdlayers.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2021-11-29", + "metadataLastUpdated": "2021-11-29" + }, + "description": "Symmetric Positive Definite (SPD) enforcement layers for PyTorch. Regardless of the input, the output of these layers will always be a SPD tensor! The `Cholesky` layer uses a cholesky factorization to enforce SPD, and the `Eigen` layer uses an eigendecomposition to enforce SPD. Both layers take in some tensor of shape `[batch_size, input_shape]` and output a SPD tensor of shape`[batch_size, output_shape, output_shape]`. The relationship between input and output is defined by the following. ```python input_shape = sum([i for i in range(output_shape + 1)]) ``` The layers have no learnable parameters, and merely serve to transform a vector space to a SPD matrix space.", + "laborHours": 0.0, + "languages": [], + "name": "spdlayers", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/spdlayers", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/spec-org_gfcc.json b/agency-indexes/DoE/spec-org_gfcc.json new file mode 100644 index 00000000..191aa560 --- /dev/null +++ b/agency-indexes/DoE/spec-org_gfcc.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2022-10-14", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Green's Function Coupled Cluster Library SPEC GFCC library enables calculations for spectral functions and binding energies of molecular systems using highly scalable implementation of the Green's function coupled cluster (GFCC) approach", + "laborHours": 0.0, + "languages": [], + "name": "spec-org/gfcc", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/spec-org/gfcc", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/spectral_processing__spectral_processing__v1.json b/agency-indexes/DoE/spectral_processing__spectral_processing__v1.json new file mode 100644 index 00000000..8da3e0bd --- /dev/null +++ b/agency-indexes/DoE/spectral_processing__spectral_processing__v1.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-04-29", + "metadataLastUpdated": "2021-04-29" + }, + "description": "Metabolomics, or the identification and cataloging of biologically relevant compounds, is required for the dynamic study of living systems. Plants, for instance, have thousands of compounds which may vary by tissue compartment, life cycle status, weather, soil and water. Even with the most advanced chemical detection systems at our disposal, the identification of metabolites is an exhaustive exercise and filled with uncertainty. What is different about LBNL #2019-106 is the use of machine learning and chemical spectra to add specificity to the provisional identification of a chemical species; e.g., chromatographic retention or the fragmentation spectrum of a selected ion. However, even under the best of circumstances, the provisional identification is associated with a very high level of uncertainty unless and until it is cross-referenced to similar compounds and other deductive approaches. Here, the inventors introduce a machine-learning which promises to enhance the productivity of post-mass spectrometry assessment.", + "laborHours": 0.0, + "languages": [], + "name": "spectral processing (spectral_processing) v1", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/biorack/simile", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sphinx-multibuild.json b/agency-indexes/DoE/sphinx-multibuild.json new file mode 100644 index 00000000..99fc2a14 --- /dev/null +++ b/agency-indexes/DoE/sphinx-multibuild.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "Build sphinx documentation from multiple source directories. Also includes an automatic build on change feature. This works by symlinking all the input directories to a single temporary directory and then running sphinx on that temporary directory.", + "laborHours": 182.4, + "languages": [], + "name": "sphinx-multibuild", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/sphinx-multibuild", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/spot_bt_ros_v.0.1.0.json b/agency-indexes/DoE/spot_bt_ros_v.0.1.0.json new file mode 100644 index 00000000..44d308ce --- /dev/null +++ b/agency-indexes/DoE/spot_bt_ros_v.0.1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08478O\nThe spot_bt_ros tool allows users to easily construct complex autonomous behaviors for Boston Dynamic's Spot robot without having to overly rely on the Spot software development kit (SDK). This package specifically allows a user to run the Robot Operating System 2 alongside the SDK. Using a form-of-state machine called a \"behavior tree,\u201d the software develops different \"leaves\" or actions that the robot undergoes. Attaching multiple actions in sequence creates a \"branch\" and several of these make up the \"tree.\"\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 1687.2, + "languages": [ + "python 3.10", + "ROS Humble" + ], + "name": "spot_bt_ros v.0.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spot_bt_ros", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/spot_bt_v.0.1.1.json b/agency-indexes/DoE/spot_bt_v.0.1.1.json new file mode 100644 index 00000000..b1b3dd90 --- /dev/null +++ b/agency-indexes/DoE/spot_bt_v.0.1.1.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08430O\nspot_bt allows users to easily construct complex, autonomous behaviors without having to overly rely on Boston Dynamic\u2019s Spot robot software development kit. Using a form-of-state machine called a \"behavior tree,\" the software develops and applies different \"leaves\" or actions to the robot. Attaching multiple actions in sequence creates a \"branch,\" and a series of these make up the \"tree.\" The software works on any x86 or aarch64 hardware but must run on a Linux OS. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525", + "laborHours": 1550.4, + "languages": [ + "Python 3.10" + ], + "name": "spot_bt v.0.1.1", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/spot_bt", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sracat.json b/agency-indexes/DoE/sracat.json new file mode 100644 index 00000000..ffbc058b --- /dev/null +++ b/agency-indexes/DoE/sracat.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-09-24", + "metadataLastUpdated": "2021-09-24" + }, + "description": "The Sequence Read Archive (SRA) is a cloud-based repository of biological sequence data provided by the National Center for Biotechnology Information. The SRA is a database of \u201craw\u201d sequencing data \u2013 typically short (100 bp \u2013 1000 bp) nucleotide sequences generated by modern, next-generation sequencing instruments and submitted by researchers around the world. Data in the SRA is stored in a highly-compressed binary format that can be directly read by most bioinformatics analysis tools. Existing tools to convert this binary data into standard nucleic acid sequence formats (like FASTA and FASTQ) are slow and error prone (due to a computationally demanding reordering step to place the sequenced reads in their originally submitted order). The \u201csracat\u201d tool provides a fast, reliable conversion utility for use-cases that do not require ordered reads.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "sracat", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/srlife.json b/agency-indexes/DoE/srlife.json new file mode 100644 index 00000000..834f5842 --- /dev/null +++ b/agency-indexes/DoE/srlife.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2024-12-19", + "metadataLastUpdated": "2024-12-19" + }, + "description": "Solar receiver structural life estimation tool. This software estimates the life of a tubular concentrating solar power\nreceiver given user input describing the working fluid pressures and temperatures. sf-20-068", + "laborHours": 9241.6, + "languages": [], + "name": "srlife", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/applied-material-modeling/srlife", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sssmatch__Standard_ScenarioS_Match_.json b/agency-indexes/DoE/sssmatch__Standard_ScenarioS_Match_.json new file mode 100644 index 00000000..a331ae64 --- /dev/null +++ b/agency-indexes/DoE/sssmatch__Standard_ScenarioS_Match_.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-05-02", + "metadataLastUpdated": "2018-05-02" + }, + "description": "The standard scenarios match (sssmatch) tool accepts limited information about an existing transmission system model and computes a new generation mix based on a.) matching a particular NREL Standard Scenario generation mix and b.) minimizing the distance between the system\u2019s original mix and the final one. The distance metric is computed on a nodal basis.", + "laborHours": 562.4, + "name": "sssmatch (Standard ScenarioS Match)", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/Smart-DS/sssmatch", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sta-imex__scripts_to_investigate_stability_of_IMEX_methods_.json b/agency-indexes/DoE/sta-imex__scripts_to_investigate_stability_of_IMEX_methods_.json new file mode 100644 index 00000000..82861f2c --- /dev/null +++ b/agency-indexes/DoE/sta-imex__scripts_to_investigate_stability_of_IMEX_methods_.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2020-11-01", + "metadataLastUpdated": "2020-11-13" + }, + "description": "Set of Matlab scripts to investigate properties of IMEX time stepping methods. Scripts include discretization of a system of linearized equations. One script plots numerical dispersion against analytical dispersion of the system. Another set of scripts uses the system to break it into stiff and non stiff part to investigate stability of Implicit-Explicit Runge-Kutta methods. \n\nScripts are based on \nThuburn, J. and Woollings, T. J., Vertical Discretizations for Compressible Euler Equation Atmospheric Models Giving Optimal Representation of Normal Modes , 2005 and\nLock, S.-J. and Wood, N. and Weller, H., Numerical analyses of Runge-Kutta implicit-explicit schemes for horizontally explicit, vertically implicit solutions of atmospheric models, 2014\nexpanding ideas from these two papers.\n\nScripts are used to develop IMEX schemes. SAND2020-12594 M\n\nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 668.8, + "languages": [ + "MATLAB" + ], + "name": "sta-imex (scripts to investigate stability of IMEX methods)", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/E3SM-Project/sta-imex", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.01" +} \ No newline at end of file diff --git a/agency-indexes/DoE/stacked_predictive_sparse_decomposition__SPSD__v1.0.json b/agency-indexes/DoE/stacked_predictive_sparse_decomposition__SPSD__v1.0.json new file mode 100644 index 00000000..5b42bea5 --- /dev/null +++ b/agency-indexes/DoE/stacked_predictive_sparse_decomposition__SPSD__v1.0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-08-30", + "metadataLastUpdated": "2021-08-30" + }, + "description": "It is an unsupervised representation algorithm used to learn morphometric properties from cellular objects. Many similar/identical open source implementations are widely available in tensorflow, pytorch, etc. And ours is implemented in matlab.", + "homepageURL": "https://bbds.lbl.gov/project/lgg-cms", + "laborHours": 0.0, + "languages": [], + "name": "stacked predictive sparse decomposition (SPSD) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bbds.lbl.gov/project/lgg-cms", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/staging_service.json b/agency-indexes/DoE/staging_service.json new file mode 100644 index 00000000..b07d0490 --- /dev/null +++ b/agency-indexes/DoE/staging_service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-04", + "metadataLastUpdated": "2020-08-04" + }, + "description": "This is the repository for \"staging_service\" developed by KBase.", + "laborHours": 4149.6, + "languages": [], + "name": "staging_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/staging_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/stanfill_QC-ART.json b/agency-indexes/DoE/stanfill_QC-ART.json new file mode 100644 index 00000000..358abfc7 --- /dev/null +++ b/agency-indexes/DoE/stanfill_QC-ART.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-03-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Dynamic, unsupervised quality control methodology for mass spectrometry", + "laborHours": 167.2, + "languages": [], + "name": "stanfill/QC-ART", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stanfill/QC-ART", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/statMechCrack.json b/agency-indexes/DoE/statMechCrack.json new file mode 100644 index 00000000..91a1c6df --- /dev/null +++ b/agency-indexes/DoE/statMechCrack.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-14", + "metadataLastUpdated": "2024-07-27" + }, + "description": "SAND2022-12599 O statMechCrack is a Python package providing an API to run calculations based on certain statistical mechanical models for cracks and crack growth. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "statMechCrack", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/statMechCrack", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/staticView.json b/agency-indexes/DoE/staticView.json new file mode 100644 index 00000000..b788cbfc --- /dev/null +++ b/agency-indexes/DoE/staticView.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "Tools to view pre-generated pictures.", + "laborHours": 45.6, + "languages": [], + "name": "staticView", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/staticView", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/statusMessageReporting.json b/agency-indexes/DoE/statusMessageReporting.json new file mode 100644 index 00000000..7b21684d --- /dev/null +++ b/agency-indexes/DoE/statusMessageReporting.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "arroyo7@llnl.gov" + }, + "date": { + "created": "2019-07-16", + "metadataLastUpdated": "2019-07-16" + }, + "description": "Unlike computer languages like C++ which has throw/catch, Python which has try/except and other newer computer languages, C has no built-in mechanism for handling exceptions (e.g., memory allocate failure or a divide by zero exceptions).\n\nWhile simple exception handling in the form of an integer parameter (e.g, errno) or an enum are often implemented in C programs, the richer types of exception reporting possible with newer computer languages are rarely implemented in C. \n\nThe statusMessageReporting package was created to facilitate rich exception reporting by C functions to their calling functions.\n\nThe statusMessageReporting (smr) package allows a function, called the generator, to communicate an exception to its calling function using a statusMessageReporting report. \n\nThe main parts of a report are:\n\n1)the level of the report called the status (valid levels are smr_status_Ok, smr_status_Info, smr_statusWarning and smr_status_Error)\n\n2) a string called the report's message and 3) two integer values, one representing the generator's ID, called the libraryID, and the other is the library's specific integer, called the code, that represents the type of exception the generator is reporting.\n\nThe code is similar to the errno for the C standard library. Since libraries are often developed independent of one another, they often use the same code values to represent different exceptions (e.g., one library may define the code 3 to be an error opening a file while another library may define the code 3 to be a divide-by-zero error) which is why the libraryID is needed. \n\nThat is, the equivalent of errno is the combination libraryID:code. To insure that each library's libraryID is unique, libraryIDs must be obtained from the function smr_registerLibrary.\n", + "laborHours": 60359.2, + "languages": [ + "Python" + ], + "name": "statusMessageReporting", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/gidiplus", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/stochprop.json b/agency-indexes/DoE/stochprop.json new file mode 100644 index 00000000..778ea22e --- /dev/null +++ b/agency-indexes/DoE/stochprop.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2023-12-15", + "metadataLastUpdated": "2023-12-15" + }, + "description": "Software tools for quantifying atmospheric variability and uncertainty for use in uncertainty quantification of acoustic/infrasound propagation simulations.", + "laborHours": 0.0, + "languages": [], + "name": "stochprop", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LANL-Seismoacoustics/stochprop", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/strep_repeats.json b/agency-indexes/DoE/strep_repeats.json new file mode 100644 index 00000000..9dce259b --- /dev/null +++ b/agency-indexes/DoE/strep_repeats.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-28", + "metadataLastUpdated": "2020-08-28" + }, + "description": "Detects Streptococcus repeats in genome sequences.", + "laborHours": 7888.8, + "languages": [], + "name": "strep_repeats", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/strep_repeats", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/su3_bench:_Lattice_QCD_SU_3__matrix-matrix_multiply_microbenchmark__su3_bench__v1.0.json b/agency-indexes/DoE/su3_bench:_Lattice_QCD_SU_3__matrix-matrix_multiply_microbenchmark__su3_bench__v1.0.json new file mode 100644 index 00000000..fe760020 --- /dev/null +++ b/agency-indexes/DoE/su3_bench:_Lattice_QCD_SU_3__matrix-matrix_multiply_microbenchmark__su3_bench__v1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-06-10", + "metadataLastUpdated": "2020-06-10" + }, + "description": "The purpose of this microbenchmark is to provide a means to explore different programming methodologies using a simple, but not trivial, mathematical kernel. The kernel is based on the mult_su3_nn() SU(3) matrix-matrix multiply routine in the MILC Lattice Quantum Chromodynamics(LQCD) code.", + "laborHours": 0.0, + "languages": [], + "name": "su3_bench: Lattice QCD SU(3) matrix-matrix multiply microbenchmark (su3_bench) v1.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://bitbucket.org/dwdoerf/su3_bench", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/suitcase.fabio.json b/agency-indexes/DoE/suitcase.fabio.json new file mode 100644 index 00000000..67c87d4c --- /dev/null +++ b/agency-indexes/DoE/suitcase.fabio.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "This is a suitcase subpackage for reading a particular file format.", + "laborHours": 608.0, + "languages": [], + "name": "suitcase.fabio", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/suitcase-fabio/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/suitcase-fabio", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/suitcase.germ.json b/agency-indexes/DoE/suitcase.germ.json new file mode 100644 index 00000000..59dec80f --- /dev/null +++ b/agency-indexes/DoE/suitcase.germ.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "This is a suitcase subpackage for reading a particular file format.", + "laborHours": 501.6, + "languages": [], + "name": "suitcase.germ", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/suitcase-germ", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/suitcase.json.json b/agency-indexes/DoE/suitcase.json.json new file mode 100644 index 00000000..08c8374a --- /dev/null +++ b/agency-indexes/DoE/suitcase.json.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "This is a suitcase subpackage for reading a particular file format.", + "laborHours": 547.2, + "languages": [], + "name": "suitcase.json", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/suitcase-json/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/suitcase-json", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/suitcase.nexus.json b/agency-indexes/DoE/suitcase.nexus.json new file mode 100644 index 00000000..ed1b0934 --- /dev/null +++ b/agency-indexes/DoE/suitcase.nexus.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "This is a suitcase subpackage for reading a particular file format.", + "laborHours": 547.2, + "languages": [], + "name": "suitcase.nexus", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/suitcase-nexus/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/suitcase-nexus", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/suitcase.pizza_box.json b/agency-indexes/DoE/suitcase.pizza_box.json new file mode 100644 index 00000000..41fd5097 --- /dev/null +++ b/agency-indexes/DoE/suitcase.pizza_box.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "This is a suitcase subpackage for reading a particular file format.", + "laborHours": 516.8, + "languages": [], + "name": "suitcase.pizza_box", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/suitcase-pizza-box", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/suitcase.pyxrf.json b/agency-indexes/DoE/suitcase.pyxrf.json new file mode 100644 index 00000000..c84c550f --- /dev/null +++ b/agency-indexes/DoE/suitcase.pyxrf.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-09-25", + "metadataLastUpdated": "2019-09-25" + }, + "description": "This is a suitcase subpackage for reading a particular file format.", + "laborHours": 471.2, + "languages": [], + "name": "suitcase.pyxrf", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/suitcase-pyxrf", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/suitcase.xdi.json b/agency-indexes/DoE/suitcase.xdi.json new file mode 100644 index 00000000..484a97c4 --- /dev/null +++ b/agency-indexes/DoE/suitcase.xdi.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "This is a suitcase subpackage for writing XAS Data Interchange (XDI).", + "laborHours": 577.6, + "languages": [], + "name": "suitcase.xdi", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/NSLS-II/suitcase-xdi/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/suitcase-xdi", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sup3r__Super_Resolution_for_Renewable_Resource_Data__[SWR-22-65].json b/agency-indexes/DoE/sup3r__Super_Resolution_for_Renewable_Resource_Data__[SWR-22-65].json new file mode 100644 index 00000000..7af1eb94 --- /dev/null +++ b/agency-indexes/DoE/sup3r__Super_Resolution_for_Renewable_Resource_Data__[SWR-22-65].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2022-07-08", + "metadataLastUpdated": "2023-04-24" + }, + "description": "The Super Resolution for Renewable Resource Data (sup3r) software uses generative adversarial networks to create synthetic high-resolution wind and solar spatiotemporal data from coarse low-resolution inputs.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "sup3r (Super Resolution for Renewable Resource Data) [SWR-22-65]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/sup3r", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sup3ruhi__Super_Resolution_for_Renewable_Resource_Data_and_Urban_Heat_Islands__[SWR-25-05].json b/agency-indexes/DoE/sup3ruhi__Super_Resolution_for_Renewable_Resource_Data_and_Urban_Heat_Islands__[SWR-25-05].json new file mode 100644 index 00000000..0aaf2852 --- /dev/null +++ b/agency-indexes/DoE/sup3ruhi__Super_Resolution_for_Renewable_Resource_Data_and_Urban_Heat_Islands__[SWR-25-05].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2025-03-26", + "metadataLastUpdated": "2025-03-26" + }, + "description": "Urban heat is a growing concern, particularly in dense metropolitan areas where high temperatures increase the risk of heat-related illness and drive energy expenses for cooling. Estimating the effects of urban heat remains a challenge due to limitations in describing the built environment, computational constraints, and the need for high-resolution data. This software presents open-source, computationally efficient machine learning methods that enhance the accuracy of urban temperature estimates compared to historical reanalysis data. Models trained using this software have been applied to urban microclimates in Los Angeles and Seattle showing greater accuracy and less bias when compared to low-resolution reanalysis datasets like ERA5 and even when compared to high-resolution mesoscale numerical weather models like WRF with an urban canopy model. Initial findings highlight how machine learning can support urban heat resilience planning by enabling improved assessments of local heat islands, mitigation strategies, and their energy implications.\n\nThis software is an extension of (sup3r).\n\nThis software supports the following publication:\n\nBuster, Grant, et al. Tackling Extreme Urban Heat: A Machine Learning Approach to Assess the Impacts of Climate Change and the Efficacy of Climate Adaptation Strategies in Urban Microclimates. arXiv:2411.05952, arXiv, 8 Nov. 2024. arXiv.org, https://doi.org/10.48550/arXiv.2411.05952.\n\nAnd has related public data records available at:\n\nBuster, Grant, Cox, Jordan, Benton, Brandon, and King, Ryan. Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI). United States: N.p., 16 Oct, 2024. Web. https://data.openei.org/submissions/6220.", + "laborHours": 775.2, + "languages": [ + "Python" + ], + "name": "sup3ruhi (Super Resolution for Renewable Resource Data and Urban Heat Islands) [SWR-25-05]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/sup3ruhi", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/surf.json b/agency-indexes/DoE/surf.json new file mode 100644 index 00000000..4eb8def7 --- /dev/null +++ b/agency-indexes/DoE/surf.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-02-14", + "metadataLastUpdated": "2018-03-14" + }, + "description": "SLAC Ultimate RTL Framework", + "laborHours": 195016.0, + "name": "surf", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/slaclab/surf/blob/master/LICENSE.txt", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/surf", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/sycl-reduction_benchmark_v1.0.0.json b/agency-indexes/DoE/sycl-reduction_benchmark_v1.0.0.json new file mode 100644 index 00000000..a3e8078d --- /dev/null +++ b/agency-indexes/DoE/sycl-reduction_benchmark_v1.0.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "kms@lbl.gov" + }, + "date": { + "created": "2021-07-22", + "metadataLastUpdated": "2021-07-22" + }, + "description": "Some different SYCL implementations of the reduction operation. The parallel reduction kernel aggregates vector elements into a single result. It consists of four ways to implement the reduction operation using two different data management strategies, which we could not find elsewhere as a single package.", + "laborHours": 0.0, + "languages": [], + "name": "sycl-reduction benchmark v1.0.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.com/NERSC/nersc-proxies/sycl-reduction.git", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/symPACK_v2.0.json b/agency-indexes/DoE/symPACK_v2.0.json new file mode 100644 index 00000000..00ed7a71 --- /dev/null +++ b/agency-indexes/DoE/symPACK_v2.0.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "gelipauline@lbl.gov" + }, + "date": { + "created": "2021-04-06", + "metadataLastUpdated": "2021-04-06" + }, + "description": "SymPACK is a parallel direct solver for sparse symmetric systems of linear equations. SymPACK is implemented for large- scale distributed-memory platforms. It employs several innovative ideas, including the use of an asynchronous task paradigm, one-sided communication, and dynamic scheduling.", + "laborHours": 0.0, + "languages": [], + "name": "symPACK v2.0", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/symPACK/symPACK", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git", + "version": "v2.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/system2atoms.json b/agency-indexes/DoE/system2atoms.json new file mode 100644 index 00000000..77a79e82 --- /dev/null +++ b/agency-indexes/DoE/system2atoms.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "cabrera11@llnl.gov" + }, + "date": { + "created": "2024-07-26", + "metadataLastUpdated": "2024-07-26" + }, + "description": "system2atoms is a suite of models that can simulate the performance of hydrogen\ninfrastructure across multiple scales. Examples of the different scale levels include:\n1. System Scale - techno-economic analysis for hydrogen applications,\nintegration of hydrogen infrastructure with the electrical grid,\nand supply and demand constraints across applications\n2. Component Scale - continuous-flow catalyst beds, electrochemical conversion\nunits, gas-phase separators, pumps, compressors, storage tanks, evaporators,\nheaters, and coolers\n3. Material Scale - surface reactions, degradation mechanisms, and catalyst\npoisoning", + "laborHours": 20079.2, + "languages": [], + "name": "system2atoms", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/systems2atoms", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/t24compliance-web.json b/agency-indexes/DoE/t24compliance-web.json new file mode 100644 index 00000000..b011094d --- /dev/null +++ b/agency-indexes/DoE/t24compliance-web.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "suzanne.hoffman@nrel.gov" + }, + "date": { + "created": "2018-10-05", + "metadataLastUpdated": "2018-10-05" + }, + "description": "Source code for the California Title 24 Compliance Website. The website performs compliance checks on commercial buildings using a combination of OpenStudio, EnergyPlus, and CBECC-Com.", + "laborHours": 749116.8, + "languages": [], + "name": "t24compliance-web", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/t24compliance-web", + "status": "Development", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/taxonomy_service.json b/agency-indexes/DoE/taxonomy_service.json new file mode 100644 index 00000000..c786dbe0 --- /dev/null +++ b/agency-indexes/DoE/taxonomy_service.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-14", + "metadataLastUpdated": "2020-09-14" + }, + "description": "This is the repository for \"taxonomy_service\" developed by KBase. ", + "laborHours": 2447.2, + "languages": [], + "name": "taxonomy_service", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseapps/taxonomy_service", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/temporal-graphs_STM.json b/agency-indexes/DoE/temporal-graphs_STM.json new file mode 100644 index 00000000..2d7e88ed --- /dev/null +++ b/agency-indexes/DoE/temporal-graphs_STM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2019-06-05", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Structural Temporal Modeling\nGenerating a synthetic graph that is similar to a given real- world graph is a critical requirement for privacy preservation and benchmarking purposes. This software presents a temporal-motif based approach to generate synthetic temporal graph datasets.", + "laborHours": 8755.2, + "languages": [], + "name": "temporal-graphs/STM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/temporal-graphs/STM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/tenzing.json b/agency-indexes/DoE/tenzing.json new file mode 100644 index 00000000..a7bae65a --- /dev/null +++ b/agency-indexes/DoE/tenzing.json @@ -0,0 +1,37 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-03-29", + "metadataLastUpdated": "2022-03-29" + }, + "description": "SAND2022-3576 O tenzing provides techniques for improving the performance of key applications and libraries. The program is specified as a directed acyclic graph of operations. It uses Monte-Carlo tree search to explore the design space of possible implementations and applies machine learning to the observed empirical performance to deliver design guidance to users. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 0.0, + "languages": [ + "C++", + "C++", + "CUDA", + "Python 3" + ], + "name": "tenzing", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tenzing", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/test-grid-buildouts_[SWR-23-112].json b/agency-indexes/DoE/test-grid-buildouts_[SWR-23-112].json new file mode 100644 index 00000000..45e6e8ac --- /dev/null +++ b/agency-indexes/DoE/test-grid-buildouts_[SWR-23-112].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-03-08", + "metadataLastUpdated": "2025-04-03" + }, + "description": "Test-grid-buildouts is a set of notebooks for creating buildouts of synthetic transmission grids with various levels of renewable energy. Workflows can be used to augment various test grid with varying levels of wind/solar generation. Aggregated renewable energy time series (actuals and scenarios) at grid buses can then be used for various transmission grid operation problems. Highly customizable workflow consists of parsing of synthetic grid files, setting up SAM & reV simulations, application of exclusion masks, creating of custom renewable generators on the grid, aggregating of power time series, and writing of modified grid description files.", + "laborHours": 6824.8, + "languages": [ + "Jupyter Notebook" + ], + "name": "test-grid-buildouts [SWR-23-112]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/test-grid-buildouts", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/tesuract_v.1.0.json b/agency-indexes/DoE/tesuract_v.1.0.json new file mode 100644 index 00000000..eb9d0748 --- /dev/null +++ b/agency-indexes/DoE/tesuract_v.1.0.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-05", + "metadataLastUpdated": "2024-07-23" + }, + "description": "SAND2021-14370 O Tesuract (tensor surrogate approximation and computation) provides Python tools to build machine learning regressors that include polynomial chaos expansions. The software also offers methods for creation regressors for tensor outputs such as spatially varying fields and using a reduced order modeling methodology. The library is built on and compatible with the scikit-learn API, which allows integration with one of the most ubiquitous machine learning Python libraries out there. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 24639.2, + "languages": [ + "Python" + ], + "name": "tesuract v.1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/tesuract", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/the_SHAD_Exploration_System__SHADes_.json b/agency-indexes/DoE/the_SHAD_Exploration_System__SHADes_.json new file mode 100644 index 00000000..e3ae9319 --- /dev/null +++ b/agency-indexes/DoE/the_SHAD_Exploration_System__SHADes_.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Client / Server with server with server commands implemented in the SHAD library.", + "laborHours": 0.0, + "languages": [], + "name": "the SHAD Exploration System (SHADes)", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/SHADes", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/thevenin:_An_Equivalent_Circuit_Modeling_Package_[SWR-24-132].json b/agency-indexes/DoE/thevenin:_An_Equivalent_Circuit_Modeling_Package_[SWR-24-132].json new file mode 100644 index 00000000..23855b38 --- /dev/null +++ b/agency-indexes/DoE/thevenin:_An_Equivalent_Circuit_Modeling_Package_[SWR-24-132].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-11-25", + "metadataLastUpdated": "2024-11-25" + }, + "description": "This package is a wrapper for the well-known Thevenin equivalent circuit model for simulating battery behavior with a focus on ease of use. The model is comprised of a single series resistor followed by any number of parallel RC pairs. \n\nThe package includes an intuitive \"experiment\" interface, which simplifies the programming of constant or dynamic current, voltage, and/or power-driven loads, making it ideal for a wide range of applications, from basic tests to complex simulations. It also supports state-of-charge (SOC) and temperature-dependent properties, allowing the model to be more easily calibrated against real cells.", + "laborHours": 2036.8, + "languages": [ + "Python" + ], + "name": "thevenin: An Equivalent Circuit Modeling Package [SWR-24-132]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/thevenin", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/thrust_iterators.json b/agency-indexes/DoE/thrust_iterators.json new file mode 100644 index 00000000..6da02a08 --- /dev/null +++ b/agency-indexes/DoE/thrust_iterators.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2022-10-27", + "metadataLastUpdated": "2022-10-27" + }, + "description": "A collection of iterators built on NVIDIA's thrust library driven by a small domain specific language", + "laborHours": 0.0, + "languages": [], + "name": "thrust iterators", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/lanl/thrust-iterators", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/tih_vqe_[SWR-23-32].json b/agency-indexes/DoE/tih_vqe_[SWR-23-32].json new file mode 100644 index 00000000..1bb55e94 --- /dev/null +++ b/agency-indexes/DoE/tih_vqe_[SWR-23-32].json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2023-06-02", + "metadataLastUpdated": "2023-09-18" + }, + "description": "This software supports the paper, \"Exploring the scaling limitations of the variational quantum eigensolver with the bond dissociation of hydride diatomic molecules,\" published in the International Journal of Quantum Chemistry, whose abstract is as follows: Materials simulations involving strongly correlated electrons pose fundamental challenges to state-of-the-art electronic structure methods but are hypothesized to be the ideal use case for quantum computing. To date, no quantum computer has simulated a molecule of a size and complexity relevant to real-world applications, despite the fact that the variational quantum eigensolver (VQE) algorithm can predict chemically accurate total energies. Nevertheless, because of the many applications of moderately-sized, strongly correlated systems, such as molecular catalysts, the successful use of the VQE stands as an important waypoint in the advancement toward useful chemical modeling on near-term quantum processors. In this paper, we take a significant step in this direction. We lay out the steps, write, and run parallel code for an (emulated) quantum computer to compute the bond dissociation curves of the TiH, LiH, NaH, and KH diatomic hydride molecules using VQE. TiH was chosen as a relatively simple chemical system that incorporates d orbitals and strong electron correlation. Because current VQE implementations on existing quantum hardware are limited by qubit error rates, the number of qubits available, and the allowable gate depth, recent studies have focused on chemical systems involving s and p block elements. Through VQE + UCCSD calculations of TiH, we evaluate the near-term feasibility of modeling a molecule with d-orbitals on real quantum hardware. We demonstrate that the inclusion of d-orbitals and the use of the UCCSD ansatz, which are both necessary to capture the correct TiH physics, dramatically increase the cost of this problem. We estimate the approximate error rates necessary to model TiH on current quantum computing hardware using VQE+UCCSD and show them to likely be prohibitive until significant improvements in hardware and error correction algorithms are available.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "tih_vqe [SWR-23-32]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/tih-vqe", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/timescans.json b/agency-indexes/DoE/timescans.json new file mode 100644 index 00000000..cfaa0462 --- /dev/null +++ b/agency-indexes/DoE/timescans.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2018-05-30" + }, + "description": "Timescan control for cxi.\n", + "laborHours": 364.8, + "languages": [], + "name": "timescans", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/timescans", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/timesphere6.f_software.json b/agency-indexes/DoE/timesphere6.f_software.json new file mode 100644 index 00000000..9491e7a1 --- /dev/null +++ b/agency-indexes/DoE/timesphere6.f_software.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2018-11-20", + "metadataLastUpdated": "2018-11-20" + }, + "description": "Solves the electromagnetic forward problem for a plane wave or magnetic dipole fields impingent on a set of spherical shells in a whole space of uniform resistivity, relative permeability , and relative permitivity for electric fields and magnetic fields of internal origin at nrcv receivers and nf frequencies. For receivers outside the largest sphere these are standard secondary fields. Results are given in either time or frequency domain. Time domain results allow modelling turn-on or turn-off step function transmitter wave forms, or square pulse and half sine pulse wave funcitons with arbitrary pulse length and repetition rate. Pulses may be either uni-modal or bi-modal (alternating sign each half period).", + "homepageURL": "https://ipo.lbl.gov/marketplace", + "laborHours": 4848.8, + "languages": [], + "name": "timesphere6.f software", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": "This source code is restricted by patent and / or intellectual property law.", + "licenses": [ + { + "URL": "https://ipo.lbl.gov/marketplace", + "name": "Other" + } + ], + "usageType": "exemptByLaw" + }, + "repositoryURL": "https://ipo.lbl.gov/marketplace", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/toughio_v1.2.2.json b/agency-indexes/DoE/toughio_v1.2.2.json new file mode 100644 index 00000000..1595227d --- /dev/null +++ b/agency-indexes/DoE/toughio_v1.2.2.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2020-08-20", + "metadataLastUpdated": "2020-08-20" + }, + "description": "TOUGH is a widely used general purpose numerical simulator designed for fluid and heat flows of multiphase, multicomponent fluid mixtures in porous and fractured media, which has been applied to many real-world problems such as underground geological storage, geothermal reservoir engineering or nuclear waste disposal, to name a few.\n\n`toughio` is a lightweight, object-oriented and vectorized Python library that aims to provide user-friendly routines to facilitate pre- and post-processing of a TOUGH simulation. Although its primary target is the latest version TOUGH3, `toughio` can also be used to read/write TOUGH2 input/output files. Currently, to the best of our knowledge, only PyTOUGH offers an exhaustive number of features to carry out a complete TOUGH simulation using a scripting language. `toughio` and PyTOUGH share the same objectives, yet with different approaches and philosophies. On the one hand, a PyTOUGH mesh is represented as a MULGRAPH geometry where elements can be unstructured horizontally but only layered vertically. It also checks that the model parameters are valid to ensure that a TOUGH simulation runs smoothly. On the other hand, although it provides basic meshing features, `toughio` mostly relies on common third-party softwares (e.g. Abaqus, FLAC3D, Gmsh, LaGriT) to generate the mesh by importing and converting it to a TOUGH mesh, which also conveniently facilitates the coupling of TOUGH with any other simulator that also supports the same mesh formats. Besides, `toughio` is designed to be just a TOUGH input and output file reader/writer. It assumes that the user knows what he is doing and does not verify the validity of the model parameters (`toughio` does verify the functional arguments).", + "laborHours": 9652.0, + "languages": [], + "name": "toughio v1.2.2", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/keurfonluu/toughio", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/tovox.json b/agency-indexes/DoE/tovox.json new file mode 100644 index 00000000..65913442 --- /dev/null +++ b/agency-indexes/DoE/tovox.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "nutarojj@ornl.gov" + }, + "date": { + "created": "2023-01-19", + "metadataLastUpdated": "2023-01-19" + }, + "description": "Convert Collada 3D model files to a voxel model.", + "laborHours": 0.0, + "languages": [], + "name": "tovox", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://code.ornl.gov/1qn/tovox", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/toyplot.json b/agency-indexes/DoE/toyplot.json new file mode 100644 index 00000000..4370b83f --- /dev/null +++ b/agency-indexes/DoE/toyplot.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Toyplot integrates high quality interactive, animated plotting capabilities into web browsers using the Python programming language.", + "laborHours": 15032.8, + "name": "toyplot", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/toyplot", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/traefik_poc.json b/agency-indexes/DoE/traefik_poc.json new file mode 100644 index 00000000..f22c950a --- /dev/null +++ b/agency-indexes/DoE/traefik_poc.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-10", + "metadataLastUpdated": "2020-08-10" + }, + "description": "This is the repository for traefik_poc developed by KBase. ", + "laborHours": 60.8, + "languages": [], + "name": "traefik_poc", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/traefik_poc", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/transBEAM.json b/agency-indexes/DoE/transBEAM.json new file mode 100644 index 00000000..1e0059cc --- /dev/null +++ b/agency-indexes/DoE/transBEAM.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-04-23", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Toolkit to implement and explore transfer learning-based strategies to address unsatisfactory accuracy of models for estimating building energy consumption when available field data for training is sparse or of unacceptable quality", + "laborHours": 0.0, + "languages": [], + "name": "transBEAM", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/jainmilan/transBEAM", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/transfocate.json b/agency-indexes/DoE/transfocate.json new file mode 100644 index 00000000..6b8172f2 --- /dev/null +++ b/agency-indexes/DoE/transfocate.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-30", + "metadataLastUpdated": "2018-05-30" + }, + "description": "Automated calculation of beryllium lens focusing optics for MFX Transfocator.\n", + "laborHours": 805.6, + "languages": [], + "name": "transfocate", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/pcdshub/transfocate/blob/master/LICENSE.md", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/transfocate", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/trueSIG.json b/agency-indexes/DoE/trueSIG.json new file mode 100644 index 00000000..4c701506 --- /dev/null +++ b/agency-indexes/DoE/trueSIG.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-10-28", + "metadataLastUpdated": "2021-10-28" + }, + "description": "Sensitivity testing software package with improved performance for small samples.", + "laborHours": 0.0, + "languages": [], + "name": "trueSIG", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sky-sjue-lanl/true-sig", + "status": "Production", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/tsdat_ncconvert.json b/agency-indexes/DoE/tsdat_ncconvert.json new file mode 100644 index 00000000..479b36df --- /dev/null +++ b/agency-indexes/DoE/tsdat_ncconvert.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2023-09-01", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Converts netCDF to other formats", + "laborHours": 0.0, + "languages": [], + "name": "tsdat/ncconvert", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tsdat/ncconvert", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/tsdat_tsdat.json b/agency-indexes/DoE/tsdat_tsdat.json new file mode 100644 index 00000000..f95fcf1a --- /dev/null +++ b/agency-indexes/DoE/tsdat_tsdat.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-02-26", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Time series data utilities for declaratively applying standardization, Q/C, and transformations to datastreams.", + "laborHours": 0.0, + "languages": [], + "name": "tsdat/tsdat", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/tsdat/tsdat", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/turbine-models.json b/agency-indexes/DoE/turbine-models.json new file mode 100644 index 00000000..cf7cfd55 --- /dev/null +++ b/agency-indexes/DoE/turbine-models.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-01-11", + "metadataLastUpdated": "2021-01-12" + }, + "description": "The (wind) turbine-models GitHub repo hosts an archive/database of turbine models already in the public domain. This includes mainly tabular power and thrust (when available) curve data in .csv files, other technical data, as well as documentation and references built with Sphinx/GitHub Pages. There is a script called \"curve_parser.py\" to assist with the parsing of power and thrust curves, but this repo is mostly a central location for turbine model data.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "turbine-models", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/turbine-models", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/uh2sc_simulator.json b/agency-indexes/DoE/uh2sc_simulator.json new file mode 100644 index 00000000..e15e5ecc --- /dev/null +++ b/agency-indexes/DoE/uh2sc_simulator.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2024-10-23", + "metadataLastUpdated": "2024-10-23" + }, + "description": "SAND2024-08546O\nThe underground hydrogen gas salt cavern (uh2sc) simulator software will be used to understand how hydrogen gas injection and extraction rates affect energy efficiency of weekly to monthly H2 storage. Salt cavern dynamics include: Heat transfer to the surrounding walls, gas dynamics, dissolution into brine at the bottom of caverns, multi-species gas mixtures of H2 and natural gas or other cushion gasses, and structural creep of the salt cavern or closure due to under-pressure in the cavern. The model is designed to interface with surface hydrogen system dynamics models via co-simulation. This is so it can be used as an individual tool to understand injection and extraction of H2, common faults in caverns (i.e. a leak vs. creep closure or other issues), model predictive control, and other applications. \nSandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "laborHours": 15.2, + "languages": [ + "Python" + ], + "name": "uh2sc simulator", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/uh2sc", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "0.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/ultra_fast_tomo.json b/agency-indexes/DoE/ultra_fast_tomo.json new file mode 100644 index 00000000..6b98d8bb --- /dev/null +++ b/agency-indexes/DoE/ultra_fast_tomo.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "mtatonett@bnl.gov" + }, + "date": { + "created": "2025-03-13", + "metadataLastUpdated": "2025-03-13" + }, + "description": "It is a pre-trained model for processing blurred and noisy tomographic reconstruction taken from a fast fly-scan.", + "laborHours": 167.2, + "languages": [ + "Python" + ], + "name": "ultra_fast_tomo", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/gmysage/ultra_fast_tomo", + "status": "Production", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/units.json b/agency-indexes/DoE/units.json new file mode 100644 index 00000000..1b3543df --- /dev/null +++ b/agency-indexes/DoE/units.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2019-05-15", + "metadataLastUpdated": "2019-05-15" + }, + "description": "A unit library was needed to be able to represent units of a wide range of disciplines and be able to separate them from the numerical values for use in calculations. The main driver is converting units to a standardized unit set when dealing with user input and output. And be able to use the unit as a singular type that could contain any unit, and not introduce a huge number of types to represent all possible units. Because sometimes the unit type needs to be used inside virtual function calls which must strictly define a type. The libary also has its origin in power systems so support for per-unit operations was also lacking in the alternatives.", + "laborHours": 42985.6, + "languages": [], + "name": "units", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/units", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/unum.json b/agency-indexes/DoE/unum.json new file mode 100644 index 00000000..265df5ce --- /dev/null +++ b/agency-indexes/DoE/unum.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "Universal Number Library; This floating-point arithmetic library contains a software implementation of Universal Numbers (unums) in 'C' as described by John Gustafson in the book \"The End of Error: Unum Computing\". The implementation is patterned after the prototype code printed in the book.\n", + "laborHours": 8208.0, + "languages": [], + "name": "unum", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/unum", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/uq.json b/agency-indexes/DoE/uq.json new file mode 100644 index 00000000..7720e516 --- /dev/null +++ b/agency-indexes/DoE/uq.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2018-02-22", + "metadataLastUpdated": "2024-06-18" + }, + "description": "Uncertainty quantification code from PNNL", + "laborHours": 5882.4, + "languages": [], + "name": "uq", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/pnnl/uq", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/user_profile.json b/agency-indexes/DoE/user_profile.json new file mode 100644 index 00000000..038d5a17 --- /dev/null +++ b/agency-indexes/DoE/user_profile.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-08-18", + "metadataLastUpdated": "2020-08-18" + }, + "description": "User profile service (including basic Social profile).", + "laborHours": 1824.0, + "languages": [], + "name": "user_profile", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbase/user_profile", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/uvcdat-testdata.json b/agency-indexes/DoE/uvcdat-testdata.json new file mode 100644 index 00000000..a819bdee --- /dev/null +++ b/agency-indexes/DoE/uvcdat-testdata.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-28", + "metadataLastUpdated": "2020-05-28" + }, + "description": "This repository is to store testing data for the UV-CDAT project.", + "laborHours": 380.0, + "languages": [], + "name": "uvcdat-testdata", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/uvcdat-testdata", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/uvcmetrics.json b/agency-indexes/DoE/uvcmetrics.json new file mode 100644 index 00000000..30979be4 --- /dev/null +++ b/agency-indexes/DoE/uvcmetrics.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "Metrics aka diagnostics for comparing models with observations or each other.", + "laborHours": 42286.4, + "languages": [], + "name": "uvcmetrics", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/uvcmetrics", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/vCDAT.json b/agency-indexes/DoE/vCDAT.json new file mode 100644 index 00000000..7f03fb06 --- /dev/null +++ b/agency-indexes/DoE/vCDAT.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-28", + "metadataLastUpdated": "2020-05-28" + }, + "description": "vCDAT is a desktop application that provides the graphical frontend for the CDAT package. It uses CDAT's VCS and CDMS modules to render high quality visualizations within a browser.", + "laborHours": 18969.6, + "languages": [], + "name": "vCDAT", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/vcdat", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/vcs.js.json b/agency-indexes/DoE/vcs.js.json new file mode 100644 index 00000000..610ef37f --- /dev/null +++ b/agency-indexes/DoE/vcs.js.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "VCS is a general purpose visualization library, optimized for climate data which is part of the UV-CDAT system. It provides Python API for drawing 2D plots such as lineplots, scatter plots, Taylor diagrams, map data colored by scalar values, vector glyphs, isocontours and map projections.\nVcs.js is the corresponding JavaScript API, designed to be as close as possible to the original VCS Python API and to provide similar functionality for the Web. \nVcs.js includes additional functionality when compared with VCS. This additional API is used to introspect data files available on the server and variables available in a data file. Next we are going to provide a high level description of the APIs provided by Vcs.js including session management, data introspection and subsetting and plotting.\n", + "laborHours": 17176.0, + "languages": [], + "name": "vcs.js", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/vcs-js", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/vcsaddons.json b/agency-indexes/DoE/vcsaddons.json new file mode 100644 index 00000000..0aa3c2dc --- /dev/null +++ b/agency-indexes/DoE/vcsaddons.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-28", + "metadataLastUpdated": "2020-05-28" + }, + "description": "Add-ons for CDAT's VCS.", + "laborHours": 5107.2, + "languages": [], + "name": "vcsaddons", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/vcsaddons", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/via-wind__A_Visual_Impact_Assessment_Tool_for_Wind_Turbines__[SWR-24-87].json b/agency-indexes/DoE/via-wind__A_Visual_Impact_Assessment_Tool_for_Wind_Turbines__[SWR-24-87].json new file mode 100644 index 00000000..99383329 --- /dev/null +++ b/agency-indexes/DoE/via-wind__A_Visual_Impact_Assessment_Tool_for_Wind_Turbines__[SWR-24-87].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "angela.hupp@nrel.gov" + }, + "date": { + "created": "2024-08-07", + "metadataLastUpdated": "2024-12-11" + }, + "description": "Via-wind is an open-source tool for conducting visual impact assessments for wind turbines.\n\nIt combines geographic information system (GIS) and 3D simulation methods to account for the key factors driving the visual impact of installed wind turbines, including distance, viewing angle, turbine orientation, visual exposure, and the cumulative effects of multiple turbines.\n\nThis software is optimized for use in high-performance computing environments to enable large scale (e.g., country-wide) analysis, but can also be run on a single server or personal computer.\n\nFor more information, please see the related journal article: https://www.sciencedirect.com/science/article/pii/S0306261924021846", + "laborHours": 1900.0, + "languages": [ + "Python" + ], + "name": "via-wind (A Visual Impact Assessment Tool for Wind Turbines) [SWR-24-87]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/via-wind", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git", + "version": "0.1.12" +} \ No newline at end of file diff --git a/agency-indexes/DoE/vis-react-components.json b/agency-indexes/DoE/vis-react-components.json new file mode 100644 index 00000000..3418e18c --- /dev/null +++ b/agency-indexes/DoE/vis-react-components.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "garrettmw@ornl.gov" + }, + "date": { + "created": "2020-10-01", + "metadataLastUpdated": "2020-10-01" + }, + "description": "In developing visualizations for different data sets, the end solution often become dependent on the data being visualized. This causes engineers to have to re-develop many common components multiple times. The vis-react components library was designed to help enable creating visualizations that are independent of the underlying data. This library utilizes the React.js pattern of instantiating components that may be re-used. The library exposes an example application that allows other developers to understand how to use the components in the library.", + "laborHours": 691539.2, + "languages": [ + "Javascript" + ], + "name": "vis-react-components", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/vis-react-components", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/vivaldi.json b/agency-indexes/DoE/vivaldi.json new file mode 100644 index 00000000..bf2c1aab --- /dev/null +++ b/agency-indexes/DoE/vivaldi.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "stipekcw@ornl.gov" + }, + "date": { + "created": "2024-04-16", + "metadataLastUpdated": "2024-04-16" + }, + "description": "This project's goal is to ingest morphology features (2D) and infer height (3D) for individual buildings:\n\nThe following breaks the vivald process into the respective steps\nIdentify 2D buildings from AOI\nGenerate morphology features using the Gauntlet feature morphology process\nPlease see Clinton Stipek for availability of Gauntlet features\nRun a recursive feature eliminator to streamline modelling process\nHyper-tune parameters via bayesian optimization\nInfer building heights at a building-by-building level leveraging a XGBoost algorithm", + "laborHours": 136.8, + "languages": [ + "Python" + ], + "name": "vivaldi", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/stipekcw/vivaldi/blob/main/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/stipekcw/vivaldi", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git", + "version": "v0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/vtkPNetCDFPOPReader:_a_new_C++_class_for_Visualization_Toolkit__VTK_.json b/agency-indexes/DoE/vtkPNetCDFPOPReader:_a_new_C++_class_for_Visualization_Toolkit__VTK_.json new file mode 100644 index 00000000..242193e5 --- /dev/null +++ b/agency-indexes/DoE/vtkPNetCDFPOPReader:_a_new_C++_class_for_Visualization_Toolkit__VTK_.json @@ -0,0 +1,29 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "VTK is a software library used for scientific visualization tasks. My specific contribution is a new class that improves the I/O performance when reading certain input files.", + "laborHours": 3149576.8, + "name": "vtkPNetCDFPOPReader: a new C++ class for Visualization Toolkit (VTK)", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "http://www.vtk.org/licensing", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://gitlab.kitware.com/vtk/vtk", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/vvtools_v._1.0.json b/agency-indexes/DoE/vvtools_v._1.0.json new file mode 100644 index 00000000..c626ffda --- /dev/null +++ b/agency-indexes/DoE/vvtools_v._1.0.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-04-14", + "metadataLastUpdated": "2024-07-23" + }, + "description": "Vvtools is a suite of testing tools, with a focus on reproducible verification and validation. They are written in pure Python, and contain a test harness and an automated process management tool. Users of vvtools can develop suites of verification and validation tests and run them on small to large high performance computing resources in an automated and reproducible way. The test harness enables complex processes to be performed in each test and even supports a one-level parent/child dependency between tests. It includes a built in capability to manage workloads requiring multiple processors and platforms that use batch queueing systems.", + "laborHours": 26326.4, + "languages": [ + "Python", + "Shell" + ], + "name": "vvtools v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://ip.sandia.gov", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/vvtest", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/watchr-core.json b/agency-indexes/DoE/watchr-core.json new file mode 100644 index 00000000..d6c10d67 --- /dev/null +++ b/agency-indexes/DoE/watchr-core.json @@ -0,0 +1,35 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2021-07-06", + "metadataLastUpdated": "2021-07-06" + }, + "description": "Watchr is a Java library that processes time-series data and generates HTML graphs. It is primarily used to track the performance of subroutines over time. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.\nSAND2021-7299 O", + "laborHours": 0.0, + "languages": [ + "Java", + "Java" + ], + "name": "watchr-core", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/sandialabs/watchr-core", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git", + "version": "1.0.0" +} \ No newline at end of file diff --git a/agency-indexes/DoE/wavepy.json b/agency-indexes/DoE/wavepy.json new file mode 100644 index 00000000..ebd31c82 --- /dev/null +++ b/agency-indexes/DoE/wavepy.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-30", + "metadataLastUpdated": "2019-07-30" + }, + "description": "X-ray grating interferometry has been employed for a wide range of imaging applications by using the Talbot self-images of a grating. At synchrotron facilities, it has also been exploited to characterize the coherence and wavefront of the x-ray beam. The method is relatively straightforward, easy to implement, and provides accurate quantitative data. However, to exploit its full potential, it requires highly specialized, robust data analysis. If this works, we have set the framework for the development and dissemination of a robust open-source code called wavepy that is tailored to the data analysis for imaging and beam characterization using grating interferometry. Wavepy consists of a Python library for data analysis of x-ray grating interferometry. The library takes advantage of the python programming language capabilities and flexibility, and aims to be easy to collaborate, distribute, and integrate with other imaging packages. The main reason for using Python is twofold: to take advantage of a widely used language in the scientific community, and also to make extensive use of the existing Python libraries for numerical calculation and plotting, namely numpy, scipy and matplotlib. Installation is facilitated by using conda to solve dependencies. The development makes use of git for version control and collaborative development. The code is hosted in the GitHub repository https://github.com/APS-XSD-OPT-Group/wavepy. One of the reasons for using Python is to be able to integrate wavey with other projects, mainly DXchange to seamlessly load images of different formats, and TomoPy for tomography. The main code is a collection of functions that can be used in different ways, for instance, inside a development environment (DE) or by creating a graphical interface that uses wavepy underneath. ", + "laborHours": 3040.0, + "languages": [], + "name": "wavepy", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/APS-XSD-OPT-Group/wavepy", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/wbstats.json b/agency-indexes/DoE/wbstats.json new file mode 100644 index 00000000..7ceb91ec --- /dev/null +++ b/agency-indexes/DoE/wbstats.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "laymancelk@ornl.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "Availability of accessing the World Bank Data API through the R language was limited to one existing package, which is limited in its ability. The software provides access to all of the features in World Bank API in one software package for the R language and provides functions for searching and downloading data from the World Bank API.", + "laborHours": 729.6, + "name": "wbstats", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/GIST-ORNL/wbstats/blob/master/LICENSE", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/GIST-ORNL/wbstats", + "status": "Production", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/web_view.json b/agency-indexes/DoE/web_view.json new file mode 100644 index 00000000..b2a08b1b --- /dev/null +++ b/agency-indexes/DoE/web_view.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2019-07-29", + "metadataLastUpdated": "2019-07-29" + }, + "description": "A C++ implementation of a web_view interface being proposed for standardization by the C++ standards committee.", + "laborHours": 319.2, + "languages": [], + "name": "web_view", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/hfinkel/web_view", + "status": "Development", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/webspinner.json b/agency-indexes/DoE/webspinner.json new file mode 100644 index 00000000..df12fdfe --- /dev/null +++ b/agency-indexes/DoE/webspinner.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "andrew.hess@nrel.gov" + }, + "date": { + "created": "2021-03-09", + "metadataLastUpdated": "2021-03-10" + }, + "description": "Python utilities for working with data source types used by NREL's dsgrid (Demand-Side Grid Model) project (i.e. AWS, PostgreSQL, and .parquet). https://www.nrel.gov/analysis/dsgrid.html", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "webspinner", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/dsgrid/webspinner", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/wrap.json b/agency-indexes/DoE/wrap.json new file mode 100644 index 00000000..beadbf8d --- /dev/null +++ b/agency-indexes/DoE/wrap.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2018-07-30" + }, + "description": "MPI wrapper generator, for writing PMPI tool libraries.\n", + "laborHours": 547.2, + "languages": [], + "name": "wrap", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/wrap", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/wtDigiTwin__Wind_Turbine_Digital_Twin__[SWR-21-15].json b/agency-indexes/DoE/wtDigiTwin__Wind_Turbine_Digital_Twin__[SWR-21-15].json new file mode 100644 index 00000000..0d0d3c38 --- /dev/null +++ b/agency-indexes/DoE/wtDigiTwin__Wind_Turbine_Digital_Twin__[SWR-21-15].json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "noah.kobayashi@nrel.gov" + }, + "date": { + "created": "2021-07-26", + "metadataLastUpdated": "2023-08-14" + }, + "description": "This wind turbine digital twin software (wtDigiTwin) provides a digital twin solution for wind turbine applications. The focus of wtDigiTwin is to estimate loads, motions and environmental conditions for an operating wind turbine. The program uses supervisory control and data acquisition (SCADA) measurements as inputs, together with a wind turbine model. The wind industry is currently challenged by the high cost of operation and maintenance. These costs could be mitigated if component failures are predicted, but such predictions are difficult unless the turbines are equipped with expensive measuring devices. The alternative is to use a digital twin such as wtDigiTwin to estimate the necessary signals. wtDigiTwin can perform online prediction of signals that are otherwise not measured, using a limited set of reliable measurements and a physics-based model. The predicted signals can be used in applications that have direct cost benefits: 1) real-time estimation of the fatigue consumption of key components of the wind turbine; 2) root cause analyses and failure detections ; 3) lifetime reassessments ; 4) improvements to follow-on designs. The current version provides examples to estimate wind speed, thrust, torque, tower-top position, and tower loads on an onshore wind turbine using the following measurements tower top acceleration, generator torque, pitch, and rotational speed. The model combines a linear state-space model, a wind speed estimator, and a Kalman filter algorithm that integrates measurements with the state model to perform state estimations. The state space model is obtained either using OpenFAST linearizations, or using the yams package provided with the software.", + "laborHours": 0.0, + "languages": [ + "MATLAB", + "Python" + ], + "name": "wtDigiTwin (Wind Turbine Digital Twin) [SWR-21-15]", + "organization": "National Renewable Energy Laboratory (NREL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NREL/wtDigiTwin", + "status": "Production", + "tags": [ + "DOE CODE", + "National Renewable Energy Laboratory (NREL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/wuhrlab_BACIQ.json b/agency-indexes/DoE/wuhrlab_BACIQ.json new file mode 100644 index 00000000..fad5be59 --- /dev/null +++ b/agency-indexes/DoE/wuhrlab_BACIQ.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-01", + "metadataLastUpdated": "2024-11-01" + }, + "description": "Multiplexed proteomics has emerged as a powerful tool to measure relative protein expression levels across multiple conditions. The relative protein abundances are inferred by comparing the signals generated by isobaric tags, which encode the samples\u2019 origins. Intuitively, the trust associated with a protein measurement depends on the similarity of ratios from the protein\u2019s peptides and the signal-strength of these measurements. However, typically the average peptide ratio is reported as the estimate of relative protein abundance, which is only the most likely ratio with a very naive model. Moreover, there is no sense on the confidence in these measurements. Here, we present a mathematically rigorous approach that integrates peptide signal strengths and peptide-measurement agreement into an estimation of the true protein ratio and the associated confidence (BACIQ).\n\nThe main advantages of BACIQ are:\n\nIt removes the need to threshold reported peptide signal based on an arbitrary cut-off, thereby reporting more measurements from a given experiment;\nConfidence can be assigned without replicates;\nFor repeated experiments BACIQ provides confidence intervals for the union, not the intersection, of quantified proteins; and\nFor repeated experiments, BACIQ confidence intervals are more predictive than confidence intervals based on protein measurement agreement.\nTo demonstrate the power of BACIQ, we reanalyzed previously published data on subcellular protein movement upon treatment with an Exportin-1 inhibiting drug. We detect ~2x more highly significant movers, down to subcellular localization changes of ~1% . Thus, our method drastically increases the value obtainable from quantitative proteomics experiments helping researchers to interpret their data and prioritize resources. To make our approach easily accessible we distribute it via a Python/Stan package.", + "laborHours": 364.8, + "languages": [], + "name": "wuhrlab/BACIQ", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/wuhrlab/BACIQ/?tab=GPL-3.0-1-ov-file#readme", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/wuhrlab/BACIQ", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/xSDK.json b/agency-indexes/DoE/xSDK.json new file mode 100644 index 00000000..023bd72a --- /dev/null +++ b/agency-indexes/DoE/xSDK.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-05-18", + "metadataLastUpdated": "2020-05-18" + }, + "description": "Rapid, efficient production of high-quality, sustainable extreme-scale scientific applications is best accomplished using a rich ecosystem of state-of-the art reusable libraries, tools, lightweight frameworks, and defined software methodologies, developed by a community of scientists who are striving to identify, adapt, and adopt best practices in software engineering. The vision of the xSDK is to provide infrastructure for and interoperability of a collection of related and complementary software elements\u2014developed by diverse, independent teams throughout the high-performance computing (HPC) community\u2014that provide the building blocks, tools, models, processes, and related artifacts for rapid and efficient development of high-quality applications.", + "homepageURL": "https://xsdk.info", + "laborHours": 197402.4, + "languages": [], + "name": "xSDK", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://xsdk.info/faq", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://xsdk.info", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/xSDKTrilinos_v._1.0.json b/agency-indexes/DoE/xSDKTrilinos_v._1.0.json new file mode 100644 index 00000000..dd4d982d --- /dev/null +++ b/agency-indexes/DoE/xSDKTrilinos_v._1.0.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "jcrouch@sandia.gov" + }, + "date": { + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" + }, + "description": "The main purpose of the xSDKTrilinos package is to provide an interoperability layer that enables easy installation and combined usage of the IDEAS libraries, including PETSc, Hypre, and SuperLU. The package can be used for any project that uses or will use different libraries, such as Trilinos, PETSc, HYPRE and SuperLU, together. One particular example is AMANZI code from Los Alamos National Laboratories, that uses PETSc and Trilinos at the same time.", + "laborHours": 3739.2, + "name": "xSDKTrilinos v. 1.0", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/trilinos/xSDKTrilinos", + "status": "Production", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/xSpike.json b/agency-indexes/DoE/xSpike.json new file mode 100644 index 00000000..1a7258cf --- /dev/null +++ b/agency-indexes/DoE/xSpike.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "chan@lanl.gov" + }, + "date": { + "created": "2021-08-12", + "metadataLastUpdated": "2021-08-12" + }, + "description": "XSPIKE (eXplore the SPIKE protein) identifies sites of high variability (high entropy) in amino acid sequences of the Spike protein of the SARS CoV-2 virus. Among these sites, it further identifies correlations between pairs of them, and provides both graphical and tabular display of that information. It also provides a table of occurrences of co-occurring patterns found among natural sequences, featuring associations within those most highly variable sites to emphasize common covariation patterns; this table includes information about the number of sequences in which those patterns are seen, broken out by continent, and provides as context a list of mutations for each pattern that corresponds to the differences between the reference sequence (usually the Wuhan form) and the most common full sequence that exhibits that pattern.", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "laborHours": 0.0, + "languages": [], + "name": "xSpike", + "organization": "Los Alamos National Laboratory (LANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "status": "Development", + "tags": [ + "DOE CODE", + "Los Alamos National Laboratory (LANL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/xicsrt.json b/agency-indexes/DoE/xicsrt.json new file mode 100644 index 00000000..5b2f134a --- /dev/null +++ b/agency-indexes/DoE/xicsrt.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "npablant@pppl.gov" + }, + "date": { + "created": "2021-04-22", + "metadataLastUpdated": "2021-04-22" + }, + "description": "XICSRT is a general purpose, photon based, raytracing code intended for both optical and x-ray raytracing.", + "laborHours": 0.0, + "languages": [ + "Python" + ], + "name": "xicsrt", + "organization": "Princeton Plasma Physics Laboratory (PPPL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/PrincetonUniversity/xicsrt", + "status": "Development", + "tags": [ + "DOE CODE", + "Princeton Plasma Physics Laboratory (PPPL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/xmgrace.json b/agency-indexes/DoE/xmgrace.json new file mode 100644 index 00000000..868e3d59 --- /dev/null +++ b/agency-indexes/DoE/xmgrace.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2020-05-29", + "metadataLastUpdated": "2020-05-29" + }, + "description": "Python API for xmgrace.", + "laborHours": 3952.0, + "languages": [], + "name": "xmgrace", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/CDAT/xmgrace", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/xspress3.json b/agency-indexes/DoE/xspress3.json new file mode 100644 index 00000000..4f649588 --- /dev/null +++ b/agency-indexes/DoE/xspress3.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "pgarvey@bnl.gov" + }, + "date": { + "created": "2019-07-02", + "metadataLastUpdated": "2019-07-02" + }, + "description": "An EPICS driver based on areaDetector for Quantum Detector Xspress3 electronics.", + "laborHours": 78766.4, + "languages": [], + "name": "xspress3", + "organization": "Brookhaven National Laboratory (BNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/lgpl-3.0", + "name": "LGPL-3.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/NSLS-II/xspress3", + "status": "Development", + "tags": [ + "DOE CODE", + "Brookhaven National Laboratory (BNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/xvalid.json b/agency-indexes/DoE/xvalid.json new file mode 100644 index 00000000..78160b6b --- /dev/null +++ b/agency-indexes/DoE/xvalid.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2018-05-24", + "metadataLastUpdated": "2018-05-24" + }, + "description": "Work to cross validate on mutli GPU host.\n", + "laborHours": 516.8, + "languages": [], + "name": "xvalid", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/xvalid", + "status": "Development", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/xxing9703_PAVE.json b/agency-indexes/DoE/xxing9703_PAVE.json new file mode 100644 index 00000000..ab5239b4 --- /dev/null +++ b/agency-indexes/DoE/xxing9703_PAVE.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-10-31", + "metadataLastUpdated": "2024-10-31" + }, + "description": "Untargeted metabolomics can detect more than 10\u202f000 peaks in a single LC\u2013MS run. The correspondence between these peaks and metabolites, however, remains unclear. Here, we introduce a Peak Annotation and Verification Engine (PAVE) for annotating untargeted microbial metabolomics data. The workflow involves growing cells in 13C and 15N isotope-labeled media to identify peaks from biological compounds and their carbon and nitrogen atom counts. Improved deisotoping and deadducting are enabled by algorithms that integrate positive mode, negative mode, and labeling data. To distinguish metabolites and their fragments, PAVE experimentally measures the response of each peak to weak in-source collision induced dissociation, which increases the peak intensity for fragments while decreasing it for their parent ions. The molecular formulas of the putative metabolites are then assigned based on database searching using both m/z and C/N atom counts. Application of this procedure to Saccharomyces cerevisiae and Escherichia coli revealed that more than 80% of peaks do not label, i.e., are environmental contaminants. More than 70% of the biological peaks are isotopic variants, adducts, fragments, or mass spectrometry artifacts yielding \u223c2000 apparent metabolites across the two organisms. About 650 match to a known metabolite formula based on m/z and C/N atom counts, with 220 assigned structures based on MS/MS and/or retention time to match to authenticated standards. Thus, PAVE enables systematic annotation of LC\u2013MS metabolomics data with only \u223c4% of peaks annotated as apparent metabolites.", + "laborHours": 562.4, + "languages": [], + "name": "xxing9703/PAVE", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/xxing9703/PAVE", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/y0-causal-inference_y0.json b/agency-indexes/DoE/y0-causal-inference_y0.json new file mode 100644 index 00000000..70b16a3f --- /dev/null +++ b/agency-indexes/DoE/y0-causal-inference_y0.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "david.long@pnnl.gov" + }, + "date": { + "created": "2021-09-27", + "metadataLastUpdated": "2024-06-18" + }, + "description": "\u2753y0 (pronounced \"why not?\") is for causal inference in Python: a software library intended to support the scientific discovery process.", + "laborHours": 0.0, + "languages": [], + "name": "y0-causal-inference/y0", + "organization": "Pacific Northwest National Laboratory (PNNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/y0-causal-inference/y0", + "status": "Production", + "tags": [ + "DOE CODE", + "Pacific Northwest National Laboratory (PNNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/yaml-config-node.json b/agency-indexes/DoE/yaml-config-node.json new file mode 100644 index 00000000..7d3e7d33 --- /dev/null +++ b/agency-indexes/DoE/yaml-config-node.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Manage your node.js app configuration based on NODE_ENV, all configuration defined in yaml\n", + "laborHours": 167.2, + "name": "yaml-config-node", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/yaml-config-node", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/yaml-cpp.json b/agency-indexes/DoE/yaml-cpp.json new file mode 100644 index 00000000..ea7a9381 --- /dev/null +++ b/agency-indexes/DoE/yaml-cpp.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "maggiel@slac.stanford.edu" + }, + "date": { + "created": "2022-08-17", + "metadataLastUpdated": "2022-08-17" + }, + "description": "A YAML parser and emitter in C++.", + "laborHours": 0.0, + "languages": [], + "name": "yaml-cpp", + "organization": "SLAC National Accelerator Laboratory (SLAC)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/slaclab/yaml-cpp", + "status": "Production", + "tags": [ + "DOE CODE", + "SLAC National Accelerator Laboratory (SLAC)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/yayaml-config.json b/agency-indexes/DoE/yayaml-config.json new file mode 100644 index 00000000..c235c86a --- /dev/null +++ b/agency-indexes/DoE/yayaml-config.json @@ -0,0 +1,30 @@ +{ + "contact": { + "email": "simsdl@ornl.gov" + }, + "date": { + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" + }, + "description": "Yet Another Yaml configuration module for loading multiple environment settings from a single settings file\n", + "laborHours": 152.0, + "name": "yayaml-config", + "organization": "Oak Ridge National Laboratory (ORNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/ornl-sava/yayaml-config", + "status": "Development", + "tags": [ + "DOE CODE", + "Oak Ridge National Laboratory (ORNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/yihuishen_T_cell_MFA.json b/agency-indexes/DoE/yihuishen_T_cell_MFA.json new file mode 100644 index 00000000..e9715f87 --- /dev/null +++ b/agency-indexes/DoE/yihuishen_T_cell_MFA.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "Metabolic efficiency profoundly influences organismal fitness. Heterotrophs, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. While respiration is more energy-efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (i.e. faster). Through quantitative flux analysis and proteomics, we find however that mitochondrial respiration is actually more proteome-efficient than aerobic glycolysis. This is shown across yeasts, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which is valuable for hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth, but outgrow respiratory cells in oxygen limitation. Thus, aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.", + "laborHours": 11415.2, + "languages": [], + "name": "yihuishen/T_cell_MFA", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yihuishen/T_cell_MFA", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/yihuishen_metabolic_flux_regulation.json b/agency-indexes/DoE/yihuishen_metabolic_flux_regulation.json new file mode 100644 index 00000000..a7813f87 --- /dev/null +++ b/agency-indexes/DoE/yihuishen_metabolic_flux_regulation.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-14", + "metadataLastUpdated": "2024-11-14" + }, + "description": "Metabolic efficiency profoundly influences organismal fitness. Heterotrophs, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. While respiration is more energy-efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (i.e. faster). Through quantitative flux analysis and proteomics, we find however that mitochondrial respiration is actually more proteome-efficient than aerobic glycolysis. This is shown across yeasts, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which is valuable for hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth, but outgrow respiratory cells in oxygen limitation. Thus, aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.", + "laborHours": 1535.2, + "languages": [], + "name": "yihuishen/metabolic_flux_regulation", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yihuishen/metabolic_flux_regulation", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/yuwangcn_C4_dynamic_model.json b/agency-indexes/DoE/yuwangcn_C4_dynamic_model.json new file mode 100644 index 00000000..fae65a5f --- /dev/null +++ b/agency-indexes/DoE/yuwangcn_C4_dynamic_model.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "krhodges@illinois.edu" + }, + "date": { + "created": "2024-11-04", + "metadataLastUpdated": "2024-11-04" + }, + "description": "A dynamic systems model of C4 photosynthesis was developed based on the previous NADP-ME metabolic model for maize (Wang et al., 2014 ab). The NADP-ME metabolic model is an ordinary differential equation model including all individual steps in C4 photosynthetic carbon metabolism. Here, the model is extended to include posttranslational regulation and temperature response of enzyme activities, dynamic stomata conductance, and leaf energy balance. This model is written in Matlab (R2019a)\n\nSteady-state and dynamic gas exchange data for maize (B73), sugarcane (CP88-1762) and sorghum (Tx430) were measured in a greenhouse in Urbana, IL from July 25, 2019 through August 8, 2019. Data include:\n\nCO2 response curves\nLight response curves\nPhotosynthetic induction curves measured in the transition from darkness to high light (1800 \u03bcmol m-2 s-1), data logged every 1 min.\nPhotosynthetic induction in the transition from darkness to high light (1800 \u03bcmol m-2 s-1) to determine the kinetics of rubisco activation in these C4 crops (\u03c4_Rubisco), data logged every 10 s.\nGas exchange under fluctuating light. After dark adaptation, the leaves undergo three light change steps, light intensity was set as 1800 \u00b5mol m-2 s-1, 200 \u00b5mol m-2 s-1 and 1800 \u00b5mol m-2 s-1 for each 1800 s step.", + "laborHours": 1261.6, + "languages": [], + "name": "yuwangcn/C4_dynamic_model", + "organization": "Contractor (CONTR)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/yuwangcn/C4_dynamic_model", + "status": "Development", + "tags": [ + "DOE CODE", + "Contractor (CONTR)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/zeek_perfsonar_owamp.json b/agency-indexes/DoE/zeek_perfsonar_owamp.json new file mode 100644 index 00000000..f9129340 --- /dev/null +++ b/agency-indexes/DoE/zeek_perfsonar_owamp.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "svince@lbl.gov" + }, + "date": { + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" + }, + "description": "OWAMP protocol analyzer plugin for Bro/Zeek.", + "laborHours": 197.6, + "languages": [], + "name": "zeek_perfsonar_owamp", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://github.com/esnet/zeek_perfsonar_owamp/blob/master/COPYING", + "name": "Other" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/esnet/zeek_perfsonar_owamp", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/zfs-auto-snapshot.json b/agency-indexes/DoE/zfs-auto-snapshot.json new file mode 100644 index 00000000..107fba2f --- /dev/null +++ b/agency-indexes/DoE/zfs-auto-snapshot.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-31", + "metadataLastUpdated": "2018-07-31" + }, + "description": "An alternative implementation of the zfs-auto-snapshot service for Linux that is compatible with zfs-linux and zfs-fuse. Automatically create, rotate, and destroy periodic ZFS snapshots. This is the utility that creates the @zfs-auto-snap_frequent, @zfs-auto-snap_hourly, @zfs-auto-snap_daily, @zfs-auto-snap_weekly, and @zfs-auto-snap_monthly snapshots if it is installed. This program is a posixly correct bourne shell script. It depends only on the zfs utilities and cron, and can run in the dash shell.", + "laborHours": 212.8, + "languages": [], + "name": "zfs-auto-snapshot", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zfsonlinux/zfs-auto-snapshot", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/zfs-buildbot.json b/agency-indexes/DoE/zfs-buildbot.json new file mode 100644 index 00000000..3142494e --- /dev/null +++ b/agency-indexes/DoE/zfs-buildbot.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-31", + "metadataLastUpdated": "2018-07-31" + }, + "description": "This is the buildbot infrastructure used by the ZFS on Linux project. It's used to automate the process of testing new pull requests.", + "laborHours": 2325.6, + "languages": [], + "name": "zfs-buildbot", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-2-clause", + "name": "BSD-2-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/zfsonlinux/zfs-buildbot", + "status": "Development", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoT-index.json b/agency-indexes/DoT-index.json new file mode 100644 index 00000000..ff766be5 --- /dev/null +++ b/agency-indexes/DoT-index.json @@ -0,0 +1,271 @@ +{ + "agency": "TREASURY", + "version": "2.0.0", + "measurementType": { + "ifOther": "", + "method": "other" + }, + "releases": [ + { + "contact": { + "URL": "https://fedspendingtransparency.github.io/", + "email": "Renata.Maziarz@fiscal.treasury.gov", + "name": "Renata Maziarz", + "phone": "(202) 874-5732" + }, + "date": { + "created": "2019-06-05", + "lastModified": "2019-06-05" + }, + "downloadURL": "https://github.com/fedspendingtransparency/data-act-broker-web-app/archive/dev.zip", + "homepageURL": "https://fedspendingtransparency.github.io/", + "disclaimerURL": "https://github.com/fedspendingtransparency/data-act-broker-web-app/blob/dev/LICENSE", + "disclaimerText": "The Creative Commons CC0 Public Domain Dedication waives copyright interest in a work you've created and dedicates it to the world-wide public domain. Use CC0 to opt out of copyright entirely and ensure your work has the widest reach. As with the Unlicense and typical software licenses, CC0 disclaims warranties. CC0 is very similar to the Unlicense.", + "laborHours": 1, + "languages": [ + "HTML", + "CSS", + "JavaScript" + ], + "name": "data-act-broker-web-app", + "version": "1.0.0", + "description": "The DATA Act broker website is the front-end to the DATA Act broker backend. To increase access to and use of federal financial data in order to strengthen government-wide decision-making and accountability through data transparency, the broker relies on hundreds of distinct data elements to tell the story of how federal dollars are spent.", + "organization": "Bureau of the Fiscal Service(BFS)", + "permissions": { + "licenses": [ + { + "name": "Creative Commons Zero v1.0 Universal", + "URL": "http://creativecommons.org/publicdomain/zero/1.0/" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fedspendingtransparency/data-act-broker-web-app", + "status": "Development", + "tags": [ + "spending", + "government", + "transparency", + "github" + ], + "vcs": "git" + }, + { + "contact": { + "URL": "https://fedspendingtransparency.github.io/", + "email": "Renata.Maziarz@fiscal.treasury.gov", + "name": "Renata Maziarz", + "phone": "(202) 874-5732" + }, + "date": { + "created": "2019-06-05", + "lastModified": "2019-06-05" + }, + "downloadURL": "https://github.com/fedspendingtransparency/data-act-broker-backend/archive/development.zip", + "homepageURL": "https://broker.usaspending.gov/", + "disclaimerURL": "https://github.com/fedspendingtransparency/data-act-broker-backend/blob/development/LICENSE", + "disclaimerText": "The Creative Commons CC0 Public Domain Dedication waives copyright interest in a work you've created and dedicates it to the world-wide public domain. Use CC0 to opt out of copyright entirely and ensure your work has the widest reach. As with the Unlicense and typical software licenses, CC0 disclaims warranties. CC0 is very similar to the Unlicense.", + "laborHours": 1, + "languages": [ + "HTML", + "CSS", + "Python" + ], + "name": "data-act-broker-backend", + "version": "1.0.0", + "description": "The DATA Act broker backend is a collection of services that power the DATA Act's central data submission platform. To increase access to and use of federal financial data in order to strengthen government-wide decision-making and accountability through data transparency, the broker relies on hundreds of distinct data elements to tell the story of how federal dollars are spent.", + "organization": "Bureau of the Fiscal Service(BFS)", + "permissions": { + "licenses": [ + { + "name": "Creative Commons Zero v1.0 Universal", + "URL": "http://creativecommons.org/publicdomain/zero/1.0/" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fedspendingtransparency/data-act-broker-backend", + "status": "Development", + "tags": [ + "spending", + "government", + "transparency", + "broker", + "github" + ], + "vcs": "git" + }, + { + "contact": { + "URL": "https://fedspendingtransparency.github.io/", + "email": "Renata.Maziarz@fiscal.treasury.gov", + "name": "Renata Maziarz", + "phone": "(202) 874-5732" + }, + "date": { + "created": "2019-06-05", + "lastModified": "2019-06-05" + }, + "downloadURL": "https://github.com/fedspendingtransparency/fedspendingtransparency.github.io/archive/master.zip", + "homepageURL": "https://github.com/fedspendingtransparency", + "disclaimerURL": "https://github.com/fedspendingtransparency/fedspendingtransparency.github.io/blob/master/LICENSE", + "disclaimerText": "The Creative Commons CC0 Public Domain Dedication waives copyright interest in a work you've created and dedicates it to the world-wide public domain. Use CC0 to opt out of copyright entirely and ensure your work has the widest reach. As with the Unlicense and typical software licenses, CC0 disclaims warranties. CC0 is very similar to the Unlicense.", + "laborHours": 1, + "languages": [ + "HTML", + "CSS" + ], + "name": "federal spending transparency", + "version": "1.0.0", + "description": "This collaboration space is designed to make federal spending data more accessible, searchable, reliable and meet the transparency requirements of the DATA Act.", + "organization": "Bureau of the Fiscal Service(BFS)", + "permissions": { + "licenses": [ + { + "name": "Creative Commons Zero v1.0 Universal", + "URL": "http://creativecommons.org/publicdomain/zero/1.0/" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fedspendingtransparency/fedspendingtransparency.github.io", + "status": "Development", + "tags": [ + "spending", + "government", + "transparency", + "Federal", + "github" + ], + "vcs": "git" + }, + { + "contact": { + "URL": "https://fedspendingtransparency.github.io/", + "email": "Renata.Maziarz@fiscal.treasury.gov", + "name": "Renata Maziarz", + "phone": "(202) 874-5732" + }, + "date": { + "created": "2019-06-05", + "lastModified": "2019-06-05" + }, + "downloadURL": "https://github.com/fedspendingtransparency/usaspending-api/archive/dev.zip", + "homepageURL": "https://github.com/fedspendingtransparency", + "disclaimerURL": "https://github.com/fedspendingtransparency/fedspendingtransparency.github.io/blob/master/LICENSE", + "disclaimerText": "This project is in the public domain within the United States, and copyright and related rights in the work worldwide are waived through the CC0 1.0 Universal public domain dedication. All contributions to this project will be released under the CC0 dedication. By submitting a pull request, you are agreeing to comply with this waiver of copyright interest.", + "laborHours": 1, + "languages": [ + "PostgreSQL", + "Python" + ], + "name": "usa spending api", + "version": "1.0.0", + "description": "An RESTful API for U.S. federal spending data. It is designed to make federal spending data more accessible, searchable, reliable and meet the transparency requirements of the DATA Act.", + "organization": "Bureau of the Fiscal Service(BFS)", + "permissions": { + "licenses": [ + { + "name": "Creative Commons Zero v1.0 Universal", + "URL": "http://creativecommons.org/publicdomain/zero/1.0/" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/fedspendingtransparency/usaspending-api", + "status": "Development", + "tags": [ + "spending", + "government", + "transparency", + "API", + "github" + ], + "vcs": "git" + }, + { + "contact": { + "URL": "https://github.com/IRSgov/", + "email": "lbi.fatca.ides@irs.gov", + "name": "Ortiz Hahnemann" + }, + "date": { + "created": "2019-06-05", + "lastModified": "2019-06-05" + }, + "downloadURL": "https://github.com/IRSgov/IDES-Data-Preparation-Dot-Net/zipball/master", + "homepageURL": "https://github.com/IRSgov/", + "disclaimerURL": "https://github.com/IRSgov/IDES-Data-Preparation-Dot-Net/blob/master/LICENSE", + "disclaimerText": "We waive copyright and related rights in the work worldwide through the CC0 1.0 Universal public domain dedication. Unless expressly stated otherwise, the person who associated a work with this deed makes no warranties about the work, and disclaims liability for all uses of the work, to the fullest extent permitted by applicable law. When using or citing the work, you should not imply endorsement by the author or the affirmer.", + "laborHours": 1, + "languages": [ + "HTML", + ".NET" + ], + "name": "IDES-Data-Preparation-Dot-Net", + "version": "1.0.0", + "description": "The International Data Exchange Service (IDES) is a secure managed file transfer service that allows financial institutions and tax authorities to securely send information on financial accounts held by U.S. taxpayers in accordance with the Foreign Account Tax Compliance Act (FATCA). 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Unless expressly stated otherwise, the person who associated a work with this deed makes no warranties about the work, and disclaims liability for all uses of the work, to the fullest extent permitted by applicable law. When using or citing the work, you should not imply endorsement by the author or the affirmer.", + "laborHours": 1, + "languages": [ + "HTML", + "JAVA" + ], + "name": "IDES-Data-Preparation-Dot-Java", + "version": "1.0.0", + "description": "The International Data Exchange Service (IDES) is a secure managed file transfer service that allows financial institutions and tax authorities to securely send information on financial accounts held by U.S. taxpayers in accordance with the Foreign Account Tax Compliance Act (FATCA). 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at end of file diff --git a/agency-indexes/HHS/fdns-ms-crypto.json b/agency-indexes/HHS/fdns-ms-crypto.json new file mode 100644 index 00000000..c72cfedb --- /dev/null +++ b/agency-indexes/HHS/fdns-ms-crypto.json @@ -0,0 +1,27 @@ +{ + "contact": { + "URL": "https://github.com/CDCgov", + "email": "cdcinfo@cdc.gov" + }, + "date": { + "created": "2018-08-09", + "lastModified": "2020-03-04" + }, + "description": "This is the repository for the cryptography microservice.", + "downloadURL": "https://api.github.com/repos/CDCgov/fdns-ms-crypto/downloads", + "homepageURL": "https://github.com/CDCgov/fdns-ms-crypto", + "laborHours": 0, + "languages": [], + "name": "fdns-ms-crypto", + "organization": "Centers for Disease Control and Prevention", + "permissions": { + "licenses": null, + "usageType": "openSource" + }, + "repositoryURL": "git://github.com/CDCgov/fdns-ms-crypto.git", + "status": "Development", + "tags": [ + "github" + ], + "vcs": "git" +} \ No newline at end of file diff --git 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For example, database queries are stored in external stored procedures." + }, + "laborHours": 1512, + "date": { + "created": "2016-02-23", + "lastModified": "2019-03-11", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "solicitation-data-service", + "description": "Contains routes that retrieve solicitation and related unit of consideration data.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "psm", + "external" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-solicitation-data", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-solicitation-data/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 922, + "date": { + "created": "2018-10-17", + "lastModified": "2018-10-17", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "proposal-management-service", + "description": "Edge service that support business processes of PSM clients.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "psm", + "external" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-proposal-management", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-proposal-management/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 1618, + "date": { + "created": "2018-10-17", + "lastModified": "2018-10-17", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "profile-service", + "description": "Capability in MyNSF to allow MyNSF Program Staff to associate themselves to a Program Element. At this point UPM shall still be used to assign POs for a particular PEC.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "shared" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 688, + "date": { + "created": "2016-08-02", + "lastModified": "2018-08-14", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "reference-data-service", + "description": "Returns mostly static reference data that can be easily cached. Some of the items include: GSA Committee Codes, Hotels, NSF Orgs & Divisions, and Program Elements.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "shared" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 1360, + "date": { + "created": "2015-04-02", + "lastModified": "2019-03-11", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "participant-group-service", + "description": "Service to provide functionality to create Availability Request to determine the availability of the external reviewers.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "pars", + "business" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 1360, + "date": { + "created": "2018-06-08", + "lastModified": "2019-03-11", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "staff-assignment-service", + "description": "Service to assign an NSF staff to an NSF organization (e.g. directorate, division, section, program element).", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "business" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 750, + "date": { + "created": "2018-06-18", + "lastModified": "2019-03-13", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "system-advisory-service", + "description": "The System Advisory Service is used to display System Advisories on the MyNSF system. This does not limit it to MyNSF. The Service itself is generic and allows for namespacing if other teams wish to use the service.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "shared" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "status": "Beta", + "vcs": "git", + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-system-advisory", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-system-advisory/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 744, + "date": { + "created": "2015-08-10", + "lastModified": "2018-07-24", + "metadataLastUpdated": "2019-03-14" + }, + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "email-service", + "description": "Send, Store and Search system generated emails.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "shared" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "status": "Beta", + "vcs": "git", + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-email", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-email/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 1079, + "date": { + "created": "2018-08-18", + "lastModified": "2018-08-18", + "metadataLastUpdated": "2019-03-14" + }, + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "inbox-service", + "description": "Inbox Service is enables system messages to be displayed on the MyNSF home page. This service is not related to emails.", + "tags": [ + "java", + "email", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "shared" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "status": "Beta", + "vcs": "git", + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-inbox", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-inbox/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 836, + "date": { + "created": "2017-08-10", + "lastModified": "2017-08-10", + "metadataLastUpdated": "2019-03-14" + }, + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "template-service", + "description": "Service provides Letter Template Management operations. Templates are use when sending standard Letters (emails). They can also contain placeholder values.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "shared" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 775, + "date": { + "created": "2016-09-21", + "lastModified": "2018-12-18", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "toggle-service", + "description": "The Toggle Service will return available feature toggles for a particular user (based off SSO).", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "shared" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "status": "Beta", + "vcs": "git", + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-toggle", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-toggle/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 464, + "date": { + "created": "2017-08-10", + "lastModified": "2017-08-10", + "metadataLastUpdated": "2019-03-14" + }, + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "document-generation-service", + "description": "Contains routes that generate and concatenate documents from stored PSM data.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "psm", + "external" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-document-generation", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-document-generation/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 1018, + "date": { + "created": "2018-10-03", + "lastModified": "2018-10-03", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "document-compliance-service", + "description": "Service retrieves document attributes and metadata for compliance checks.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "psm", + "external" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-document-compliance", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-document-compliance/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": -1, + "date": { + "created": "2018-10-03", + "lastModified": "2018-10-03", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "compliance-validation-service", + "description": "Checks proposal compliance to rules and policies", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "psm", + "external" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-compliance-validation", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-compliance-validation/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": -1, + "date": { + "created": "2018-10-03", + "lastModified": "2018-10-03", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "file-upload-service", + "description": "Contains routes that upload files to file store (AWS S3).", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "psm", + "external" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-file-storage", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-file-storage/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 578, + "date": { + "created": "2018-10-03", + "lastModified": "2018-10-03", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "search-program-officer-service", + "description": "Service returns the Program Officers pertaining to the given Organization, Program Element, and for the given Fiscal year. The search parameters - organization code, program element code and numerical fiscal year.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "iam", + "internal" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 169, + "date": { + "created": "2017-05-31", + "lastModified": "2017-12-21", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "get-user-data-service", + "description": "Service retrieves the user profile attribute and the access details. By default, the Get User data service returns the given user\u00c3\u00a2\u00e2\u201a\u00ac\u00e2\u201e\u00a2s attribute list. Applications that intend to request the access details (functional organization, associated program elements, role/entitlement etc.) should request the service with a filter org=true as a request parameter. The Access Details object includes the list of functional organizations with their associated program elements and roles for the given user.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "iam", + "internal" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 169, + "date": { + "created": "2017-05-31", + "lastModified": "2017-05-31", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "search-user-data-service", + "description": "Service searches for the identity in IDM and UPM repository by using the firstname, lastName and OrgCode as the search field. API supports various combinations of the search patterns to generalize the search function.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "iam", + "internal" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 168, + "date": { + "created": "2017-05-31", + "lastModified": "2017-05-31", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "export-user-service", + "description": "Service is designed to export all identities and their respective attribute for system integration purpose. Optionally it does support numerous search filters to retrieve defined set of users from the IDM repository. Export user service is NOT designed to retrieve information managed by UPM and Role Manager.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "iam", + "internal" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 168, + "date": { + "created": "2017-05-31", + "lastModified": "2017-05-31", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + }, + { + "name": "search-divsion-org-service", + "description": "Service returns Division Director, Delegated Division Director, Administrative Officer, Delegated Administrative Officer, Financial Reviewer for the given organization to the consumer API.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "iam", + "internal" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 168, + "date": { + "created": "2017-05-31", + "lastModified": "2017-05-31", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" + } + ] +} \ No newline at end of file diff --git a/agency-indexes/NSF/access-management-service.json b/agency-indexes/NSF/access-management-service.json new file mode 100644 index 00000000..5e3292f4 --- /dev/null +++ b/agency-indexes/NSF/access-management-service.json @@ -0,0 +1,40 @@ +{ + "name": "access-management-service", + "description": "Provides User, Permission, Division and Role information. Proxies some information from IAM's RoleManager Service.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 728, + "date": { + "created": "2016-06-25", + "lastModified": "2018-09-20", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/adhoc-review-service.json b/agency-indexes/NSF/adhoc-review-service.json new file mode 100644 index 00000000..8b886245 --- /dev/null +++ b/agency-indexes/NSF/adhoc-review-service.json @@ -0,0 +1,47 @@ +{ + "name": "adhoc-review-service", + "description": "Contains the routes for creating, updating, and deleting proposal adhoc reviews.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "pars" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 1712, + "date": { + "created": "2016-12-08", + "lastModified": "2019-03-13", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "": [ + { + "codeName": "", + "codeURL": "", + "isGovernmentRepo": true + } + ] +} \ No newline at end of file diff --git a/agency-indexes/NSF/award-budget-service.json b/agency-indexes/NSF/award-budget-service.json new file mode 100644 index 00000000..0070a6f8 --- /dev/null +++ b/agency-indexes/NSF/award-budget-service.json @@ -0,0 +1,40 @@ +{ + "name": "award-budget-service", + "description": "Contains methods that perform Increment Maintenance on Award Budget objects.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "awards" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 1618, + "date": { + "created": "2016-04-13", + "lastModified": "2018-11-02", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/award-service.json b/agency-indexes/NSF/award-service.json new file mode 100644 index 00000000..fede3891 --- /dev/null +++ b/agency-indexes/NSF/award-service.json @@ -0,0 +1,40 @@ +{ + "name": "award-service", + "description": "Provides NSF award specific data and functions.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "awards" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 2266, + "date": { + "created": "2016-04-25", + "lastModified": "2019-03-11", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/compliance-validation-service.json b/agency-indexes/NSF/compliance-validation-service.json new file mode 100644 index 00000000..fb66b197 --- /dev/null +++ b/agency-indexes/NSF/compliance-validation-service.json @@ -0,0 +1,39 @@ +{ + "name": "compliance-validation-service", + "description": "Checks proposal compliance to rules and policies", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "psm", + "external" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-compliance-validation", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-compliance-validation/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": -1, + "date": { + "created": "2018-10-03", + "lastModified": "2018-10-03", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/document-compliance-service.json b/agency-indexes/NSF/document-compliance-service.json new file mode 100644 index 00000000..23e361a3 --- /dev/null +++ b/agency-indexes/NSF/document-compliance-service.json @@ -0,0 +1,39 @@ +{ + "name": "document-compliance-service", + "description": "Service retrieves document attributes and metadata for compliance checks.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "psm", + "external" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-document-compliance", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-document-compliance/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": -1, + "date": { + "created": "2018-10-03", + "lastModified": "2018-10-03", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/document-generation-service.json b/agency-indexes/NSF/document-generation-service.json new file mode 100644 index 00000000..4b7c2a32 --- /dev/null +++ b/agency-indexes/NSF/document-generation-service.json @@ -0,0 +1,39 @@ +{ + "name": "document-generation-service", + "description": "Contains routes that generate and concatenate documents from stored PSM data.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "psm", + "external" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-document-generation", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-document-generation/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 1018, + "date": { + "created": "2018-10-03", + "lastModified": "2018-10-03", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/email-service.json b/agency-indexes/NSF/email-service.json new file mode 100644 index 00000000..b73c6d81 --- /dev/null +++ b/agency-indexes/NSF/email-service.json @@ -0,0 +1,41 @@ +{ + "name": "email-service", + "description": "Send, Store and Search system generated emails.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "shared" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "status": "Beta", + "vcs": "git", + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-email", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-email/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 1079, + "date": { + "created": "2018-08-18", + "lastModified": "2018-08-18", + "metadataLastUpdated": "2019-03-14" + }, + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/ember-common-components.json b/agency-indexes/NSF/ember-common-components.json new file mode 100644 index 00000000..18adbe2a --- /dev/null +++ b/agency-indexes/NSF/ember-common-components.json @@ -0,0 +1,39 @@ +{ + "name": "ember-common-components", + "description": "A useful set of common Ember JavaScript components used at NSF which include DataGrid, Tool Tips, Calendar Widgets, and more.", + "tags": [ + "javascript", + "government", + "ember", + "common", + "nsf" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "status": "Beta", + "vcs": "git", + "languages": [ + "JavaScript" + ], + "repositoryURL": "https://github.com/nsf-open/nsf-common-ember-components", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/nsf-common-ember-components/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": -1, + "date": { + "created": "2017-12-12", + "lastModified": "2017-12-12", + "metadataLastUpdated": "2019-03-14" + }, + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/enterprise-reporting-service.json b/agency-indexes/NSF/enterprise-reporting-service.json new file mode 100644 index 00000000..56fe18f8 --- /dev/null +++ b/agency-indexes/NSF/enterprise-reporting-service.json @@ -0,0 +1,40 @@ +{ + "name": "enterprise-reporting-service", + "description": "Queries the BI system for Recent, Frequent, and Custom BI reports for a particular user.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 1429, + "date": { + "created": "2015-12-03", + "lastModified": "2018-09-13", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/export-user-service.json b/agency-indexes/NSF/export-user-service.json new file mode 100644 index 00000000..e286eefc --- /dev/null +++ b/agency-indexes/NSF/export-user-service.json @@ -0,0 +1,40 @@ +{ + "name": "export-user-service", + "description": "Service is designed to export all identities and their respective attribute for system integration purpose. Optionally it does support numerous search filters to retrieve defined set of users from the IDM repository. Export user service is NOT designed to retrieve information managed by UPM and Role Manager.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "iam", + "internal" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 168, + "date": { + "created": "2017-05-31", + "lastModified": "2017-05-31", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/file-upload-service.json b/agency-indexes/NSF/file-upload-service.json new file mode 100644 index 00000000..ba31946d --- /dev/null +++ b/agency-indexes/NSF/file-upload-service.json @@ -0,0 +1,39 @@ +{ + "name": "file-upload-service", + "description": "Contains routes that upload files to file store (AWS S3).", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "psm", + "external" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-file-storage", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-file-storage/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 578, + "date": { + "created": "2018-10-03", + "lastModified": "2018-10-03", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/get-user-data-service.json b/agency-indexes/NSF/get-user-data-service.json new file mode 100644 index 00000000..8c25f374 --- /dev/null +++ b/agency-indexes/NSF/get-user-data-service.json @@ -0,0 +1,40 @@ +{ + "name": "get-user-data-service", + "description": "Service retrieves the user profile attribute and the access details. By default, the Get User data service returns the given user\u00c3\u00a2\u00e2\u201a\u00ac\u00e2\u201e\u00a2s attribute list. Applications that intend to request the access details (functional organization, associated program elements, role/entitlement etc.) should request the service with a filter org=true as a request parameter. The Access Details object includes the list of functional organizations with their associated program elements and roles for the given user.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "iam", + "internal" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 169, + "date": { + "created": "2017-05-31", + "lastModified": "2017-05-31", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/inbox-service.json b/agency-indexes/NSF/inbox-service.json new file mode 100644 index 00000000..51176b8b --- /dev/null +++ b/agency-indexes/NSF/inbox-service.json @@ -0,0 +1,42 @@ +{ + "name": "inbox-service", + "description": "Inbox Service is enables system messages to be displayed on the MyNSF home page. This service is not related to emails.", + "tags": [ + "java", + "email", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "shared" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "status": "Beta", + "vcs": "git", + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-inbox", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-inbox/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 836, + "date": { + "created": "2017-08-10", + "lastModified": "2017-08-10", + "metadataLastUpdated": "2019-03-14" + }, + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/meeting-service.json b/agency-indexes/NSF/meeting-service.json new file mode 100644 index 00000000..bff55586 --- /dev/null +++ b/agency-indexes/NSF/meeting-service.json @@ -0,0 +1,40 @@ +{ + "name": "meeting-service", + "description": "Contains the routes for creating, updating, and deleting Meetings for Proposal Reviews at NSF", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "meeting" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 2735, + "date": { + "created": "2015-02-13", + "lastModified": "2019-03-13", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/nsf-ember-psm.json b/agency-indexes/NSF/nsf-ember-psm.json new file mode 100644 index 00000000..7c4b6156 --- /dev/null +++ b/agency-indexes/NSF/nsf-ember-psm.json @@ -0,0 +1,39 @@ +{ + "name": "nsf-ember-psm", + "description": "Contains javascript front-end for NSF's new proposal submission system.", + "tags": [ + "javascript", + "government", + "ember", + "nsf", + "psm", + "external" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "JavaScript" + ], + "repositoryURL": "https://github.com/nsf-open/nsf-ember-psm", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/nsf-ember-psm/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": -1, + "date": { + "created": "2018-10-17", + "lastModified": "2018-10-17", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/nsf-ember-tooltip.json b/agency-indexes/NSF/nsf-ember-tooltip.json new file mode 100644 index 00000000..6765fd78 --- /dev/null +++ b/agency-indexes/NSF/nsf-ember-tooltip.json @@ -0,0 +1,39 @@ +{ + "name": "nsf-ember-tooltip", + "description": "An ember-cli addon for using Tooltipster in Ember applications. The default sideTip, and the ScrollableTip plugins come preconfigured.", + "tags": [ + "javascript", + "government", + "ember", + "common", + "nsf" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "status": "Beta", + "vcs": "git", + "languages": [ + "JavaScript" + ], + "repositoryURL": "https://github.com/nsf-open/nsf-ember-tooltip", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/nsf-ember-tooltip/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": -1, + "date": { + "created": "2017-12-12", + "lastModified": "2017-12-12", + "metadataLastUpdated": "2019-03-14" + }, + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/participant-group-service.json b/agency-indexes/NSF/participant-group-service.json new file mode 100644 index 00000000..a1684397 --- /dev/null +++ b/agency-indexes/NSF/participant-group-service.json @@ -0,0 +1,41 @@ +{ + "name": "participant-group-service", + "description": "Service to provide functionality to create Availability Request to determine the availability of the external reviewers.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "pars", + "business" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 1360, + "date": { + "created": "2018-06-08", + "lastModified": "2019-03-11", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/profile-service.json b/agency-indexes/NSF/profile-service.json new file mode 100644 index 00000000..8d4f1f8b --- /dev/null +++ b/agency-indexes/NSF/profile-service.json @@ -0,0 +1,41 @@ +{ + "name": "profile-service", + "description": "Capability in MyNSF to allow MyNSF Program Staff to associate themselves to a Program Element. At this point UPM shall still be used to assign POs for a particular PEC.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "shared" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 688, + "date": { + "created": "2016-08-02", + "lastModified": "2018-08-14", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/proposal-data-service.json b/agency-indexes/NSF/proposal-data-service.json new file mode 100644 index 00000000..d0784f82 --- /dev/null +++ b/agency-indexes/NSF/proposal-data-service.json @@ -0,0 +1,39 @@ +{ + "name": "proposal-data-service", + "description": "Contains routes that perform CRUD operations on in-progress proposals.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "psm", + "external" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-proposal-data", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-proposal-data/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 1892, + "date": { + "created": "2018-10-17", + "lastModified": "2018-10-17", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/proposal-management-service.json b/agency-indexes/NSF/proposal-management-service.json new file mode 100644 index 00000000..b18ae517 --- /dev/null +++ b/agency-indexes/NSF/proposal-management-service.json @@ -0,0 +1,39 @@ +{ + "name": "proposal-management-service", + "description": "Edge service that support business processes of PSM clients.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "psm", + "external" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-proposal-management", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-proposal-management/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 1618, + "date": { + "created": "2018-10-17", + "lastModified": "2018-10-17", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/proposal-service.json b/agency-indexes/NSF/proposal-service.json new file mode 100644 index 00000000..b19bacc1 --- /dev/null +++ b/agency-indexes/NSF/proposal-service.json @@ -0,0 +1,40 @@ +{ + "name": "proposal-service", + "description": "Contains routes to search and retrieve NSF proposal information.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "meeting" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 864, + "date": { + "created": "2016-02-23", + "lastModified": "2019-03-12", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/reference-data-service.json b/agency-indexes/NSF/reference-data-service.json new file mode 100644 index 00000000..8163ef3d --- /dev/null +++ b/agency-indexes/NSF/reference-data-service.json @@ -0,0 +1,41 @@ +{ + "name": "reference-data-service", + "description": "Returns mostly static reference data that can be easily cached. Some of the items include: GSA Committee Codes, Hotels, NSF Orgs & Divisions, and Program Elements.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "shared" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 1360, + "date": { + "created": "2015-04-02", + "lastModified": "2019-03-11", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/reviewer-service.json b/agency-indexes/NSF/reviewer-service.json new file mode 100644 index 00000000..d077a725 --- /dev/null +++ b/agency-indexes/NSF/reviewer-service.json @@ -0,0 +1,41 @@ +{ + "name": "reviewer-service", + "description": "Contains routes to search and retrieve NSF reviewer information.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "meeting", + "internal" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 1512, + "date": { + "created": "2016-02-23", + "lastModified": "2019-03-11", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/search-divsion-org-service.json b/agency-indexes/NSF/search-divsion-org-service.json new file mode 100644 index 00000000..72056bf7 --- /dev/null +++ b/agency-indexes/NSF/search-divsion-org-service.json @@ -0,0 +1,40 @@ +{ + "name": "search-divsion-org-service", + "description": "Service returns Division Director, Delegated Division Director, Administrative Officer, Delegated Administrative Officer, Financial Reviewer for the given organization to the consumer API.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "iam", + "internal" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 168, + "date": { + "created": "2017-05-31", + "lastModified": "2017-05-31", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/search-program-officer-service.json b/agency-indexes/NSF/search-program-officer-service.json new file mode 100644 index 00000000..eaa78512 --- /dev/null +++ b/agency-indexes/NSF/search-program-officer-service.json @@ -0,0 +1,40 @@ +{ + "name": "search-program-officer-service", + "description": "Service returns the Program Officers pertaining to the given Organization, Program Element, and for the given Fiscal year. The search parameters - organization code, program element code and numerical fiscal year.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "iam", + "internal" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 169, + "date": { + "created": "2017-05-31", + "lastModified": "2017-12-21", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/search-user-data-service.json b/agency-indexes/NSF/search-user-data-service.json new file mode 100644 index 00000000..fe3fe5c5 --- /dev/null +++ b/agency-indexes/NSF/search-user-data-service.json @@ -0,0 +1,40 @@ +{ + "name": "search-user-data-service", + "description": "Service searches for the identity in IDM and UPM repository by using the firstname, lastName and OrgCode as the search field. API supports various combinations of the search patterns to generalize the search function.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "iam", + "internal" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 168, + "date": { + "created": "2017-05-31", + "lastModified": "2017-05-31", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/solicitation-data-service.json b/agency-indexes/NSF/solicitation-data-service.json new file mode 100644 index 00000000..353106e2 --- /dev/null +++ b/agency-indexes/NSF/solicitation-data-service.json @@ -0,0 +1,39 @@ +{ + "name": "solicitation-data-service", + "description": "Contains routes that retrieve solicitation and related unit of consideration data.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "psm", + "external" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-solicitation-data", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-solicitation-data/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 922, + "date": { + "created": "2018-10-17", + "lastModified": "2018-10-17", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/staff-assignment-service.json b/agency-indexes/NSF/staff-assignment-service.json new file mode 100644 index 00000000..f94035e4 --- /dev/null +++ b/agency-indexes/NSF/staff-assignment-service.json @@ -0,0 +1,41 @@ +{ + "name": "staff-assignment-service", + "description": "Service to assign an NSF staff to an NSF organization (e.g. directorate, division, section, program element).", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "business" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. For example, database queries are stored in external stored procedures." + }, + "laborHours": 750, + "date": { + "created": "2018-06-18", + "lastModified": "2019-03-13", + "metadataLastUpdated": "2019-03-14" + }, + "vcs": "", + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/system-advisory-service.json b/agency-indexes/NSF/system-advisory-service.json new file mode 100644 index 00000000..90bb8ed4 --- /dev/null +++ b/agency-indexes/NSF/system-advisory-service.json @@ -0,0 +1,41 @@ +{ + "name": "system-advisory-service", + "description": "The System Advisory Service is used to display System Advisories on the MyNSF system. This does not limit it to MyNSF. The Service itself is generic and allows for namespacing if other teams wish to use the service.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "shared" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "status": "Beta", + "vcs": "git", + "languages": [ + "Java" + ], + "repositoryURL": "https://github.com/nsf-open/rest-service-system-advisory", + "permissions": { + "licenses": [ + { + "URL": "https://github.com/nsf-open/rest-service-system-advisory/blob/master/LICENSE", + "name": "GPL.v3" + } + ], + "usageType": "openSource" + }, + "laborHours": 744, + "date": { + "created": "2015-08-10", + "lastModified": "2018-07-24", + "metadataLastUpdated": "2019-03-14" + }, + "disclaimerText": "", + "disclaimerURL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf" +} \ No newline at end of file diff --git a/agency-indexes/NSF/template-service.json b/agency-indexes/NSF/template-service.json new file mode 100644 index 00000000..937f1dc6 --- /dev/null +++ b/agency-indexes/NSF/template-service.json @@ -0,0 +1,41 @@ +{ + "name": "template-service", + "description": "Service provides Letter Template Management operations. Templates are use when sending standard Letters (emails). They can also contain placeholder values.", + "tags": [ + "java", + "government", + "microservice", + "nsf", + "mynsf", + "features", + "shared" + ], + "contact": { + "email": "esivagna@nsf.gov", + "name": "Elanchezhian Sivagnanam", + "phone": "7032928088" + }, + "languages": [ + "Java" + ], + "repositoryURL": "http://www.nsf.gov", + "permissions": { + "licenses": [ + { + "URL": "https://www.nsf.gov/digitalstrategy/Alternative_Analysis_Report_Template_Process.pdf", + "name": "NSF" + } + ], + "usageType": "exemptByAgencySystem", + "exemptionText": "Internal system not suitable for open source. 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The second (known as SSPT - SSA Processing Time) will express the confidence that the determination can be reached quickly.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Predictive", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Front End Capture System", + "repositoryURL": "", + "description": "Front-end document capture system for DMA. 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Travel reimbursements are generated through an interface between the eTravel system and the Social Security Online Accounting Reporting System (SSOARS).", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "GIS Direct Deposit Maps", + "repositoryURL": "", + "description": "GISSDD maps application creates U.S. and State/County maps and reports, to provide the percentage of Title II and Title XVI payments made through direct deposit in those areas. 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It maintains a variety of financial information including, but not limited to, funding data, commitments, obligations, receivables, and payables.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reporting", + "Accounting" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Mini Learning Management System", + "repositoryURL": "", + "description": "This LMS supports the Seattle Region Studio 6 in managing course content that they are responsible for, mainly the Transition to Leadership Courses, Core, and ASC/SLC training.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Learning Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Third Party Payment System", + "repositoryURL": "", + "description": "The Third Party Payment System (TPPS) is a register of paper checks that are known as Third Party Drafts. 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It replaced the Death Alert Control and Update System (DACUS) CICS screens in PCOM.", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Death" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Earnings Modernization Itemized Statement of Earnings Requests", + "repositoryURL": "", + "description": "Earnings Modernization Itemized Statement of Earnings Report (EMISER) is an interactive CICS control system that processes requests for Itemized Statements of Earnings (SSA-1826).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Earnings Requests", + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Volume Death", + "repositoryURL": "", + "description": "Updates the SSA Death Master File.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Death" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Rep Payee System", + "repositoryURL": "", + "description": "The Representative Payee System (RPS) is an online system used to store and process current and prior Rep Payee applications (both approved and denied). Data is stored on the Master Rep Payee File (MRPF) as applicants, beneficiaries, or recipients, and the relationship between the Rep Payee and beneficiary. The RPS data is also useful to adjudicators in processing subsequent actions.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Representative Payee" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "VIEWS - Data Exchange Inventory", + "repositoryURL": "", + "description": "DEXI is an inventory database that contains information about data exchanges between SSA and various partners. It interfaces with external applications to retrieve project code data, financial accounting data, management information data, and electronic reimbursable agreement documentation, and can be queried in various ways.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Data Exchange" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Numident Online Verification Utility", + "repositoryURL": "", + "description": "A mainframe application that accesses the NUMIDENT to perform real-time SSN verifications. This program is called by other SSA online programs that serve as interfaces to end-users.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Work Experience Reporting System", + "repositoryURL": "", + "description": "WERS is an MI system that captures and reports workload volumes and the hours needed to process items in each workload category. Weekly, monthly, quarterly, and yearly reports are produced for the Office of Budget, Finance and Management (OBFM).", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Reporting" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Medicare Non-Utilization Project", + "repositoryURL": "", + "description": "The Medicare Non-Usage Project (MNUP) objective is to use Medicare non-utilization information furnished to us by CMS as an indicator to select and prioritize cases for review to determine continued eligibility to SSA Title II benefits. We will obtain an initial data extract of individuals age 90 or over who are living in the United States, in current pay status and have not used Medicare during the previous three years. Subsequent data extracts will be obtained bi-annually. The data received from CMS will include Title II beneficiaries who reside in nursing homes, are enrolled in HMOs, or have private health insurance.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Medicare" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Medicare - IRMAA", + "repositoryURL": "", + "description": "Imposes higher Medicare Part B and Part D premium rates on high-income earners as defined by statute, adjusts those additional amounts on the basis of beneficiary allegations, and verifies the accuracy of those allegations.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "medicare" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Military Service Reimbursement", + "repositoryURL": "", + "description": "The Military Service Reimbursement System (MSRS) was developed to replace the process within the Title II AERO system that calculates Primary Insurance Amounts (PIA) for the Office of the Chief Actuary (OCACT).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reimbursement", + "Military" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Legal Automated Workflow System", + "repositoryURL": "", + "description": "A new system replacing the Program Litigation functions in the National Docketing Management Information System (NDMIS). LAWS electronically receives information contained in the Certified Administrative Record (CAR), interacts with Electronic Folder, allows OGC users access to historical data, accurately captures workloads, and enables users to produce and communicate management information.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workflow" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Cost Analysis System", + "repositoryURL": "", + "description": "The Cost Analysis System gathers workload counts and costs.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Cost Analysis" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Federal Assistance Award Data System", + "repositoryURL": "", + "description": "A central collection of selected, computer-based domestic financial assistance programs data for the Federal Government mandated by the Federal Funding Accountability and Transparency Act and is compiled quarterly.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Federal Assistance" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Quality Performance Management System / DARES", + "repositoryURL": "", + "description": "Performance management data extracted from multiple sources is consolidated into the QPMS data warehouse, providing a \"one-stop\" source for generating quality performance measures. 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DARES also serves as the front-end starting point for QPMS DARES, which offers web-based, parameter-driven reports that are based on the breakdown of ODAR workloads within the context of how they relate to key hearing backlog initiatives.\u00c2 ", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Review", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Case Processing Management System", + "repositoryURL": "", + "description": "An intranet application used by the Office of Disability Adjudication and Review's (ODAR) hearing offices to process cases and manage office workloads.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Management", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Work Reporting Front End", + "repositoryURL": "", + "description": "A Web-based application used by all SSA technicians (TSC, FO, PC, and OCO), which fully automates the initiation, development, adjudication, and effectuation of Title II Work CDRs.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Work Reporting", + "Title II" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Consent Based Social Security Number Verification", + "repositoryURL": "", + "description": "A fee-based SSN verification service that permits private businesses, as well as Federal, State and Local governments, to use the Internet or a Web Service to verify an individual's SSN once a valid signed consent form is obtained from the SSN holder.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Number Verification", + "repositoryURL": "", + "description": "An application within Business Services Online (BSO). SSNVS allows registered users to verify names and SSNs of their employees against SSA's master files via the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Internet", + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "National Instant Criminal Background Check System", + "repositoryURL": "", + "description": "The purpose of the National Instant Criminal Background Check System (NICS) is to process potential NICS candidates for inclusion to the FBI, prohibiting firearm ownership.\nThis is an Intranet application for CRs to gather information from potential candidates who are identified by EDCS. CRs will then process the candidates who are legally incompetent and provide notification of NICS determinations to the appropriate parties, such as legal guardians, appointed representatives, and representative payees. All candidates found eligible will have identifying information submitted to the FBI.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Criminal", + "Background Check" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Internet Ticket Operations Provider Support System", + "repositoryURL": "", + "description": "An automated system that allows users to award contracts, provide ticket assignment/unassignment, and payments for Employment Networks (EN). It allows users to process, verify, and cancel payments before they reach Treasury.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Payments", + "Employment Networks", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Internet Application Status", + "repositoryURL": "", + "description": "An application that allows an individual to enter their Social Security Number (SSN) and follow the progress of all available claims using the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claim Status", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Audit Trail System", + "repositoryURL": "", + "description": "Collects application-specific transaction data and provides search capability for the Center Directors for Security and Integrity and their staffs for the purpose of deterring, detecting, and investigating instances of fraud and abuse.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Fraud Prevention", + "Security", + "Audit" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "UniForms", + "repositoryURL": "", + "description": "UniForms is a replacement for eForms, allowing Agency-wide retrieval of administrative forms.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Forms" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Manual Adjustment Credit & Award Data Entry", + "repositoryURL": "", + "description": "CICS data collection system consists of data entered/received via MACADE or data that comes to MACADE via A101, and propagates information into the SPS database to create a payment record.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Payment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Processing Center Action Control System", + "repositoryURL": "", + "description": "PCACS provides timely, accurate, and detailed online information regarding the status and location of actions and folders in progress in all processing centers (PCs).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Processing Center" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Electronic Remittance System", + "repositoryURL": "", + "description": "The Social Security Electronic Remittance System (SERS) collects standard fees for non-program-related requests for information. The system allows field office personnel to quickly process payments and eliminates the need to bundle and send payment requests to the Office of Finance at headquarters.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Fee Collection" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Returned Check Action", + "repositoryURL": "", + "description": "The program generates an electronic alert file to the servicing Processing Center (PC) when Title II benefit payments are returned, indicating the beneficiary is deceased. It will automatically send a call-in letter to each beneficiary indicating the stop payment and the reason why.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Death", + "Title II", + "Processing Center" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Fugitive Felon Matching Agreements", + "repositoryURL": "", + "description": "APPLICATION TO COLLECT INFORMATION ON SSA EFFORTS TO NEGOTIATE MATCHING AGREEMENTS WITH LAW ENFORCEMENT AGENCIES TO IDENTIFY FUGITIVE FELONS AND PAROLE AND PROBATION VIOLATORS", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Felon" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "National Docketing Management Information System", + "repositoryURL": "", + "description": "Centralized system for tracking and managing legal matters as a system-of-record for all OGC regions and at OGC headquarters. Tracks due dates to ensure that responsive documents are filed in a timely manner.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Legal", + "Docket Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Employee Retirement Income Security Act", + "repositoryURL": "", + "description": "Produces notices to inform retirees of their possible eligibility for pensions under a private pension plan. There is also an online system for users in OCO and the field offices to query the ERISA master files.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Private Pensions", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Modernized Integrated Disability Adjudicative System", + "repositoryURL": "", + "description": "A federal disability case processing system used in Disability Determination Services, Disability Processing Branches, and some federal components that process disability claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claims", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Target Notice Architecture - Mainframe", + "repositoryURL": "", + "description": "TNA is the agency's standard for the systems development of 508-compliant notice language.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "508", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Earnings Case Management System", + "repositoryURL": "", + "description": "This is a case management system which tracks many different earnings workloads.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Earnings Requests", + "Case Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Disability Collection System (EDCS\\eView)", + "repositoryURL": "", + "description": "An automated system for SSA field personnel to electronically collect information about the applicant and his or her medical condition, and transfer the data to the EF for use by a local case management system.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Management", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Folder Interface", + "repositoryURL": "", + "description": "An interface between the electronic folder and the case processing systems (CPMS for ODAR). Enables transactions that allow: Messages and alerts to be sent to case processing systems; Electronic cases to be transferred between processing locations and closed when processing is complete; and Case processing systems to electronically send data to the CEF when case processing actions are complete.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Access for Cross-Platform Intranet Services", + "repositoryURL": "", + "description": "Access to Cross-Platform Intranet Services (AXIS), a Web Service environment, is a part of Core Services for security logon. It allows ColdFusion applications to leverage the security infrastructure in order to access mainframe resources on z/OS.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Security", + "Web Services" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Work History Assistant Tool", + "repositoryURL": "", + "description": "A web-based application, available on a need-to-know basis, that retrieves Detail Earnings Query (DEQY) data and makes it easier to interpret.wh", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Employment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Employee Office Sampler", + "repositoryURL": "", + "description": "Capture/store/manage end-user work activities at designated times as needed for DOWS sampling", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Field Office" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Medical Evidence Gathering & Analysis Health Information Technology", + "repositoryURL": "", + "description": "An application called through Health IT that requests, receives, and analyzes electronic medical records in a fully automated manner. Upon transfer of a claim to a disability case processing unit, MEGAHIT automatically identifies a health IT participating source and gathers electronic medical records.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Medical Records" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Document Generation System", + "repositoryURL": "", + "description": "DGS is a Windows-based application used to create Office of Hearings and Appeals (OHA) Distributed Online Correspondence System (DOCS) and notices.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Notices", + "Document Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Access Control Utility", + "repositoryURL": "", + "description": "Access Control Utility (ACU) provides access only to applications that employ Knowledge Based Authentication (KBA).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Authentication", + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Access - (RIR)", + "repositoryURL": "", + "description": "ID Proofing and Authentication system for SSA online applications.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Security", + "Authentication" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "EMR-Framework", + "repositoryURL": "", + "description": "The Enterprise Metadata Repository Framework is built on an open architecture using relational databases and provides an infrastructure for retrieving data to load to the EMR, as well as controlling the load process.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Framework", + "Data", + "Metadata Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "EMR-UI/API", + "repositoryURL": "", + "description": "Provides front-end and API access to the Enterprise Metadata Repository, which stores metadata about SSA's applications and databases. The Enterprise Metadata Repository (EMR) is a data management tool used to coordinate enterprise-wide information. It ties physical and logical metadata which may be used in data administration and application development efforts. The EMR is built on an open architecture using relational databases. It serves as a central location for documentation of SSA's data infrastructure.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Front End", + "Data", + "Metadata Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Health informationTechnology management information", + "repositoryURL": "", + "description": "Health IT Management Information (HIT MI) is part of the WebFocus Business Intelligence Dashboard. It provides data analysis to monitor work loads and trend analysis and information on a variety of variables such as time and location, allowing users to make further improvements and enhancements to the disability process.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "HealthIT" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "WMI for IC and Appeals", + "repositoryURL": "", + "description": "Legacy Workload Management Information (WMI) for IC and appeals batch programs and CICS screens.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Appeals", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "VIEWS - Agreement Workflow Tool", + "repositoryURL": "", + "description": "AWT is a workflow tool and repository for the reimbursable agreement documents. The agreement process begins in AWT, which allows related documentation to be circulated electronically for approval and signature.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Agreements", + "Workflow Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MI Central", + "repositoryURL": "", + "description": "Facilitates access to management information and workload control reports by providing centralized access to workload counts, workload control listings, processing time reports, performance measurement reports and managerial cost analysis data/reports.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Management Information" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Detailed Office Organization Resource System", + "repositoryURL": "", + "description": "The Detailed Office/Organization Resource System (DOORS) is SSA's official Agency repository of office information, such as location and phone numbers, for all SSA offices. DOORS has a user and customer base of all SSA employees, hundreds of SSA systems, and members of the public who use SSA.GOV on the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Inventory Management", + "Office", + "Administrative" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Automatic Earnings Reappraisal Operation", + "repositoryURL": "", + "description": "The process that \"automatically\" screens the earning records of Retirement, Survivors, and Disability Insurance (RSDI) beneficiaries for additional earnings and computes necessary changes. The beneficiary does NOT have to initiate this process.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Automated", + "Disability", + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Number Application Process", + "repositoryURL": "", + "description": "An Enumeration software application that will perform a cross-reference check of a new SSN.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Application", + "Enumeration" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Verifications Account Management System", + "repositoryURL": "", + "description": "Verification Account Management System (VAMS) is a centralized location for maintaining Enumeration Verification Systems (EVS) accounts. VAMS allows users to create new accounts, search for existing accounts, update current accounts, and generate MI count reports. DEVO interfaces with VAMS to perform the administrative functions of registration, access control and tracking, and to manage assignment of the functional processes.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Account Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Integrated Client Database System", + "repositoryURL": "", + "description": "The Integrated Client Database (ICDB) System allows data to be shared among SSA's major application systems (e.g., Title II and Title XVI Claims Processing). ICDB is comprised of a set of databases, common screens and access software that collects, maintains, and provides access to common Client data.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Client" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Earnings Use - SEQY", + "repositoryURL": "", + "description": "A Master File online query request screen that adds earnings from up to 10 SSNs to the query response. The system then combines the earnings from the SSNs in the yearly totals on the query response.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Person Information", + "repositoryURL": "", + "description": "The Person Information web application was created to provide a common set of screens to display and collect person data. It is available as an independent application through the Person Information link on iMain. It can also be included in another application's path.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Person" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Folder Interface - Data Access", + "repositoryURL": "", + "description": "Allows shared access via eView to legacy information and documents within a case.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Document", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "AccuWage", + "repositoryURL": "", + "description": "AccuWage is used for testing the Electronic Filing of Wage and Tax Statement (EFW2). The software is downloaded from the SSA Web site by a submitter and used to check the format of a wage report submission file.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Taxes", + "Employment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Comprehensive Integrity Review Process - Mainframe", + "repositoryURL": "", + "description": "Collects and evaluates electronic transactions entered into the programmatic systems. Identifies those transactions that may indicate abuse or fraudulent activity involving SSA employees or the public.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Review", + "Fraud Prevention" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "DCS Budget Tracking System", + "repositoryURL": "", + "description": "Tracks Other Objects budget allocations for the Office of Systems and tracks some Information Technology budgets. Monitors and tracks allocations, expenditures and generates Management Information (MI) reports for planning budget requests and allocations.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Management Information", + "Administrative", + "Budget Tracking" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Internet Special Notices Option", + "repositoryURL": "", + "description": "An Internet/Intranet application designed to collect notice preferences from applicants, beneficiaries, recipients, and representative payees who allege blindness or visual impairment. These individuals can select to receive all notices and written communication from SSA via a Microsoft Word CD or in Braille.", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "SNO", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Performance Assessment and Communication System", + "repositoryURL": "", + "description": "PACS assists supervisors in preparing employee performance plans, documenting expectations and progress reviews and preparing performance appraisals.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Performance Appraisals", + "Human Resources" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Security Administration Reports Application", + "repositoryURL": "", + "description": "SARA is the automated solution to an existing manual review\nprocess, and it will provide the ability to capture trending data to\nassist in management decisions. Yes, The Security Administration Reports\nApplication SARA will allow Information Security Officers ISOs,\nAlternate Information Security Officers ALT ISOs and Management Designee\nMD to access, review and take appropriate action on Security\nAdministration Reports.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reporting", + "Management Information", + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Document Processing System", + "repositoryURL": "", + "description": "The Document Processing System (DPS) is an SSA developed, browser based application that will provide the user with functionality similar to the client server based system, Distributed Online Correspondence System (DOCS).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Document Processing", + "Document Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Personal Enrollment Credential System", + "repositoryURL": "", + "description": "The HSPD-12 Electronic Personal Enrollment Credential System (EPECS) supports the HSPD-12 credentialing process at SSA. It automates the sponsoring, vetting, and issuing of HSPD-12 credentials. It interfaces with other SSA systems for compliance with various directives.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Bench Book", + "repositoryURL": "", + "description": "A web-based application used by the office of Disability Adjudication and Review/ODAR to aid with documentation, analysis, and adjudication of disability cases.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Adjudication", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Visitor Intake Process - Rewrite", + "repositoryURL": "", + "description": "Manages appointments and walk-ins for Field Office (FO) and assigns them to the FO staff in an effective way to minimize the wait time of the users.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Scheduling", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Hires and Losses Tracking System", + "repositoryURL": "", + "description": "This application tracks the hires and losses of employees to the Office of Systems. It provides an automated way of approving hires and tracking both hires and losses in Systems. It also provides many reports from captured data on individuals joining the Office of Systems, leaving the Office of Systems, or moving from one Associate Commissioner's office within Systems to another Associate Commissioner's office within Systems. 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The DDFP web application also requires input of the reason for the block - Fraud Alleged or Preventive Measure. Both the adding and removal of the block are updated in real time allowing the application to access the data for display the block request history.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Direct Deposit", + "Fraud Prevention" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "SSI Claims System - Web", + "repositoryURL": "", + "description": "Enables SSI claim submissions via a web-based intranet data collection process. 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DEVO interfaces with the Verification Account Management System (VAMS) to determine account status, obtain processing parameters, and store transaction counts for Management Information (MI).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Verification", + "Data Exchange" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Core Services", + "repositoryURL": "", + "description": "A suite of Intranet-based utilities designed to simplify central or common routines required by many web based applications. The utilities leverage open, accessible technologies eliminating the drawbacks commonly seen in proprietary coding techniques. 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It consumes Programmatic Workload data to provide information to the 1,394 field offices to assist SSA employees in adjudicating initial disability claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Disability", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MySSA Benefit Verification - Backend", + "repositoryURL": "", + "description": "Accessed through the MySocialSecurity portal, it provides instant verification of SSA benefits for proof of income purposes. It also provides immediate view, print, and save of benefit verification letters to prove receipt/non-receipt of SSA benefits, Supplemental Income (SSI) or Medicare.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Registration", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "iAppeals (i3441)", + "repositoryURL": "", + "description": "Allows electronic submission of requests from individuals and/or third parties for the Request for Reconsideration (SSA-561), Request for Hearing (HA-501) on medically denied claims for both Title II and Title XVI claims, and allows an individual to appeal the decision directly on-line.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Appeals", + "Medical", + "Forms" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Number Verification - BSO", + "repositoryURL": "", + "description": "Allows employers to verify name/SSNs for wage reporting purposes.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Identity", + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Calendar Availability Services", + "repositoryURL": "", + "description": "The calendar availability service allows the ability to add availability, update availability, get availability, update available resources, and delete availability for one or many offices and calendar configurations.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Spring Boot", + "RESTful", + "Calendar Management", + "Calendar Availability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "CET Dynamic Help", + "repositoryURL": "", + "description": "mySSA Dynamic Help application", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "mySSA" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "codeMetadata.json Generator", + "repositoryURL": "", + "description": "A single page application for generating a codeMetadata.json file. 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SSNVS allows registered users to verify names and SSNs of their employees against SSA's master files via the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Internet", + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "National Instant Criminal Background Check System", + "repositoryURL": "", + "description": "The purpose of the National Instant Criminal Background Check System (NICS) is to process potential NICS candidates for inclusion to the FBI, prohibiting firearm ownership.\nThis is an Intranet application for CRs to gather information from potential candidates who are identified by EDCS. CRs will then process the candidates who are legally incompetent and provide notification of NICS determinations to the appropriate parties, such as legal guardians, appointed representatives, and representative payees. All candidates found eligible will have identifying information submitted to the FBI.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Criminal", + "Background Check" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Internet Ticket Operations Provider Support System", + "repositoryURL": "", + "description": "An automated system that allows users to award contracts, provide ticket assignment/unassignment, and payments for Employment Networks (EN). It allows users to process, verify, and cancel payments before they reach Treasury.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Payments", + "Employment Networks", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Internet Application Status", + "repositoryURL": "", + "description": "An application that allows an individual to enter their Social Security Number (SSN) and follow the progress of all available claims using the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claim Status", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Audit Trail System", + "repositoryURL": "", + "description": "Collects application-specific transaction data and provides search capability for the Center Directors for Security and Integrity and their staffs for the purpose of deterring, detecting, and investigating instances of fraud and abuse.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Fraud Prevention", + "Security", + "Audit" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "UniForms", + "repositoryURL": "", + "description": "UniForms is a replacement for eForms, allowing Agency-wide retrieval of administrative forms.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Forms" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Manual Adjustment Credit & Award Data Entry", + "repositoryURL": "", + "description": "CICS data collection system consists of data entered/received via MACADE or data that comes to MACADE via A101, and propagates information into the SPS database to create a payment record.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Payment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Processing Center Action Control System", + "repositoryURL": "", + "description": "PCACS provides timely, accurate, and detailed online information regarding the status and location of actions and folders in progress in all processing centers (PCs).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Processing Center" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Electronic Remittance System", + "repositoryURL": "", + "description": "The Social Security Electronic Remittance System (SERS) collects standard fees for non-program-related requests for information. The system allows field office personnel to quickly process payments and eliminates the need to bundle and send payment requests to the Office of Finance at headquarters.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Fee Collection" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Returned Check Action", + "repositoryURL": "", + "description": "The program generates an electronic alert file to the servicing Processing Center (PC) when Title II benefit payments are returned, indicating the beneficiary is deceased. It will automatically send a call-in letter to each beneficiary indicating the stop payment and the reason why.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Death", + "Title II", + "Processing Center" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Fugitive Felon Matching Agreements", + "repositoryURL": "", + "description": "APPLICATION TO COLLECT INFORMATION ON SSA EFFORTS TO NEGOTIATE MATCHING AGREEMENTS WITH LAW ENFORCEMENT AGENCIES TO IDENTIFY FUGITIVE FELONS AND PAROLE AND PROBATION VIOLATORS", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Felon" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "National Docketing Management Information System", + "repositoryURL": "", + "description": "Centralized system for tracking and managing legal matters as a system-of-record for all OGC regions and at OGC headquarters. Tracks due dates to ensure that responsive documents are filed in a timely manner.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Legal", + "Docket Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Employee Retirement Income Security Act", + "repositoryURL": "", + "description": "Produces notices to inform retirees of their possible eligibility for pensions under a private pension plan. There is also an online system for users in OCO and the field offices to query the ERISA master files.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Private Pensions", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Modernized Integrated Disability Adjudicative System", + "repositoryURL": "", + "description": "A federal disability case processing system used in Disability Determination Services, Disability Processing Branches, and some federal components that process disability claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claims", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Target Notice Architecture - Mainframe", + "repositoryURL": "", + "description": "TNA is the agency's standard for the systems development of 508-compliant notice language.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "508", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Earnings Case Management System", + "repositoryURL": "", + "description": "This is a case management system which tracks many different earnings workloads.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Earnings Requests", + "Case Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Disability Collection System (EDCS\\eView)", + "repositoryURL": "", + "description": "An automated system for SSA field personnel to electronically collect information about the applicant and his or her medical condition, and transfer the data to the EF for use by a local case management system.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Management", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Folder Interface", + "repositoryURL": "", + "description": "An interface between the electronic folder and the case processing systems (CPMS for ODAR). Enables transactions that allow: Messages and alerts to be sent to case processing systems; Electronic cases to be transferred between processing locations and closed when processing is complete; and Case processing systems to electronically send data to the CEF when case processing actions are complete.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Access for Cross-Platform Intranet Services", + "repositoryURL": "", + "description": "Access to Cross-Platform Intranet Services (AXIS), a Web Service environment, is a part of Core Services for security logon. It allows ColdFusion applications to leverage the security infrastructure in order to access mainframe resources on z/OS.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Security", + "Web Services" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Work History Assistant Tool", + "repositoryURL": "", + "description": "A web-based application, available on a need-to-know basis, that retrieves Detail Earnings Query (DEQY) data and makes it easier to interpret.wh", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Employment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Employee Office Sampler", + "repositoryURL": "", + "description": "Capture/store/manage end-user work activities at designated times as needed for DOWS sampling", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Field Office" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Medical Evidence Gathering & Analysis Health Information Technology", + "repositoryURL": "", + "description": "An application called through Health IT that requests, receives, and analyzes electronic medical records in a fully automated manner. Upon transfer of a claim to a disability case processing unit, MEGAHIT automatically identifies a health IT participating source and gathers electronic medical records.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Medical Records" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Document Generation System", + "repositoryURL": "", + "description": "DGS is a Windows-based application used to create Office of Hearings and Appeals (OHA) Distributed Online Correspondence System (DOCS) and notices.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Notices", + "Document Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Access Control Utility", + "repositoryURL": "", + "description": "Access Control Utility (ACU) provides access only to applications that employ Knowledge Based Authentication (KBA).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Authentication", + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Access - (RIR)", + "repositoryURL": "", + "description": "ID Proofing and Authentication system for SSA online applications.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Security", + "Authentication" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "EMR-Framework", + "repositoryURL": "", + "description": "The Enterprise Metadata Repository Framework is built on an open architecture using relational databases and provides an infrastructure for retrieving data to load to the EMR, as well as controlling the load process.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Framework", + "Data", + "Metadata Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "EMR-UI/API", + "repositoryURL": "", + "description": "Provides front-end and API access to the Enterprise Metadata Repository, which stores metadata about SSA's applications and databases. The Enterprise Metadata Repository (EMR) is a data management tool used to coordinate enterprise-wide information. It ties physical and logical metadata which may be used in data administration and application development efforts. The EMR is built on an open architecture using relational databases. It serves as a central location for documentation of SSA's data infrastructure.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Front End", + "Data", + "Metadata Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Health informationTechnology management information", + "repositoryURL": "", + "description": "Health IT Management Information (HIT MI) is part of the WebFocus Business Intelligence Dashboard. It provides data analysis to monitor work loads and trend analysis and information on a variety of variables such as time and location, allowing users to make further improvements and enhancements to the disability process.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "HealthIT" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "WMI for IC and Appeals", + "repositoryURL": "", + "description": "Legacy Workload Management Information (WMI) for IC and appeals batch programs and CICS screens.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Appeals", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "VIEWS - Agreement Workflow Tool", + "repositoryURL": "", + "description": "AWT is a workflow tool and repository for the reimbursable agreement documents. The agreement process begins in AWT, which allows related documentation to be circulated electronically for approval and signature.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Agreements", + "Workflow Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MI Central", + "repositoryURL": "", + "description": "Facilitates access to management information and workload control reports by providing centralized access to workload counts, workload control listings, processing time reports, performance measurement reports and managerial cost analysis data/reports.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Management Information" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Detailed Office Organization Resource System", + "repositoryURL": "", + "description": "The Detailed Office/Organization Resource System (DOORS) is SSA's official Agency repository of office information, such as location and phone numbers, for all SSA offices. DOORS has a user and customer base of all SSA employees, hundreds of SSA systems, and members of the public who use SSA.GOV on the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Inventory Management", + "Office", + "Administrative" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Automatic Earnings Reappraisal Operation", + "repositoryURL": "", + "description": "The process that \"automatically\" screens the earning records of Retirement, Survivors, and Disability Insurance (RSDI) beneficiaries for additional earnings and computes necessary changes. The beneficiary does NOT have to initiate this process.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Automated", + "Disability", + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Number Application Process", + "repositoryURL": "", + "description": "An Enumeration software application that will perform a cross-reference check of a new SSN.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Application", + "Enumeration" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Verifications Account Management System", + "repositoryURL": "", + "description": "Verification Account Management System (VAMS) is a centralized location for maintaining Enumeration Verification Systems (EVS) accounts. VAMS allows users to create new accounts, search for existing accounts, update current accounts, and generate MI count reports. DEVO interfaces with VAMS to perform the administrative functions of registration, access control and tracking, and to manage assignment of the functional processes.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Account Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Integrated Client Database System", + "repositoryURL": "", + "description": "The Integrated Client Database (ICDB) System allows data to be shared among SSA's major application systems (e.g., Title II and Title XVI Claims Processing). ICDB is comprised of a set of databases, common screens and access software that collects, maintains, and provides access to common Client data.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Client" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Earnings Use - SEQY", + "repositoryURL": "", + "description": "A Master File online query request screen that adds earnings from up to 10 SSNs to the query response. The system then combines the earnings from the SSNs in the yearly totals on the query response.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Person Information", + "repositoryURL": "", + "description": "The Person Information web application was created to provide a common set of screens to display and collect person data. It is available as an independent application through the Person Information link on iMain. It can also be included in another application's path.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Person" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Folder Interface - Data Access", + "repositoryURL": "", + "description": "Allows shared access via eView to legacy information and documents within a case.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Document", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "AccuWage", + "repositoryURL": "", + "description": "AccuWage is used for testing the Electronic Filing of Wage and Tax Statement (EFW2). The software is downloaded from the SSA Web site by a submitter and used to check the format of a wage report submission file.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Taxes", + "Employment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Comprehensive Integrity Review Process - Mainframe", + "repositoryURL": "", + "description": "Collects and evaluates electronic transactions entered into the programmatic systems. Identifies those transactions that may indicate abuse or fraudulent activity involving SSA employees or the public.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Review", + "Fraud Prevention" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "DCS Budget Tracking System", + "repositoryURL": "", + "description": "Tracks Other Objects budget allocations for the Office of Systems and tracks some Information Technology budgets. Monitors and tracks allocations, expenditures and generates Management Information (MI) reports for planning budget requests and allocations.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Management Information", + "Administrative", + "Budget Tracking" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Internet Special Notices Option", + "repositoryURL": "", + "description": "An Internet/Intranet application designed to collect notice preferences from applicants, beneficiaries, recipients, and representative payees who allege blindness or visual impairment. These individuals can select to receive all notices and written communication from SSA via a Microsoft Word CD or in Braille.", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "SNO", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Performance Assessment and Communication System", + "repositoryURL": "", + "description": "PACS assists supervisors in preparing employee performance plans, documenting expectations and progress reviews and preparing performance appraisals.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Performance Appraisals", + "Human Resources" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Security Administration Reports Application", + "repositoryURL": "", + "description": "SARA is the automated solution to an existing manual review\nprocess, and it will provide the ability to capture trending data to\nassist in management decisions. Yes, The Security Administration Reports\nApplication SARA will allow Information Security Officers ISOs,\nAlternate Information Security Officers ALT ISOs and Management Designee\nMD to access, review and take appropriate action on Security\nAdministration Reports.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reporting", + "Management Information", + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Document Processing System", + "repositoryURL": "", + "description": "The Document Processing System (DPS) is an SSA developed, browser based application that will provide the user with functionality similar to the client server based system, Distributed Online Correspondence System (DOCS).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Document Processing", + "Document Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Personal Enrollment Credential System", + "repositoryURL": "", + "description": "The HSPD-12 Electronic Personal Enrollment Credential System (EPECS) supports the HSPD-12 credentialing process at SSA. It automates the sponsoring, vetting, and issuing of HSPD-12 credentials. It interfaces with other SSA systems for compliance with various directives.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Bench Book", + "repositoryURL": "", + "description": "A web-based application used by the office of Disability Adjudication and Review/ODAR to aid with documentation, analysis, and adjudication of disability cases.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Adjudication", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Visitor Intake Process - Rewrite", + "repositoryURL": "", + "description": "Manages appointments and walk-ins for Field Office (FO) and assigns them to the FO staff in an effective way to minimize the wait time of the users.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Scheduling", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Hires and Losses Tracking System", + "repositoryURL": "", + "description": "This application tracks the hires and losses of employees to the Office of Systems. It provides an automated way of approving hires and tracking both hires and losses in Systems. It also provides many reports from captured data on individuals joining the Office of Systems, leaving the Office of Systems, or moving from one Associate Commissioner's office within Systems to another Associate Commissioner's office within Systems. 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The DDFP web application also requires input of the reason for the block - Fraud Alleged or Preventive Measure. Both the adding and removal of the block are updated in real time allowing the application to access the data for display the block request history.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Direct Deposit", + "Fraud Prevention" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "SSI Claims System - Web", + "repositoryURL": "", + "description": "Enables SSI claim submissions via a web-based intranet data collection process. 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DEVO interfaces with the Verification Account Management System (VAMS) to determine account status, obtain processing parameters, and store transaction counts for Management Information (MI).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Verification", + "Data Exchange" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Core Services", + "repositoryURL": "", + "description": "A suite of Intranet-based utilities designed to simplify central or common routines required by many web based applications. The utilities leverage open, accessible technologies eliminating the drawbacks commonly seen in proprietary coding techniques. They help prevent duplication of effort by reusing what already exists.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Intranet", + "Services" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "StaRZ & Stripes - The Next Generation", + "repositoryURL": "", + "description": "StarRZ and Stripes the Next Generation (SSTNG) provides the full range of detailed workload monitoring, management reports and listings used by Claims Reps, Operation Supervisors and FO Managers to identify, track and successfully complete their annual Redetermination/Limited (RZ/LI) workloads.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MI for Debt Management System", + "repositoryURL": "", + "description": "Provides an summary of the financial Debt Management screens at the regional field offices and the processing center levels", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Processing Center", + "Debt Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Customer Help and Information Program", + "repositoryURL": "", + "description": "CHIP is an Intranet application currently used by National 800 Number (N8NN) Agents to respond to inquiries made by the public. Provides instant access to facts, policies and reference material found in the Teleservice Center Operating Guide (TSCOG), as well as information from certain mainframe records.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Policy", + "Call Center", + "Phone" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Prisoner Tracking MI", + "repositoryURL": "", + "description": "The Prisoner Tracking Management Information (PTMI) provides aggregate and workload data for Title II and Title XVI prisoner transactions processed in SSA field offices (FO's) and Processing Service Centers (PSC's), provides correctional facility names, and correctional facility reporting and incentive payment information.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Management Information", + "Prisoner" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Access to State Records Online", + "repositoryURL": "", + "description": "Social Security Access to State Records Online (SASRO) provides authorized SSA employees access to state agency benefit information, in order to correctly process many of its entitlement and post-entitlement actions.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Entitlments", + "Benefits", + "State" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "My Human Resources", + "repositoryURL": "", + "description": "This application is part of the application hub, Human Resources Services Portal. The e7B creates a secure, electronic centralized repository accessed through the agency's Intranet for all information maintained in the 7B, 7B Extension File, and holding file to reduce the amount of required time and expenditures associated with file maintenance.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Human Resources" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Security Oversight Command & Control System", + "repositoryURL": "", + "description": "SOCCS is utilized to coordinate disaster planning, evacuation and security.\n\nSOCCS is used for security oversight and disaster planning for SSA HQ complex, leased buildings and facilities assigned to SSA HQ.\n\nOffice of Security and Emergency Preparedness (OSEP) will capitalize on SOCCS ability to read and receive live data feeds, ensuring the safety of SSA personnel and the public.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Safety", + "Disaster Planning" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Integrated Registration Services - Internet", + "repositoryURL": "", + "description": "An internet application that provides registration, authentication and authorization gateway services for the Business Services Online (BSO) suite of Business-to-Government (B2G) services.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Registration", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Disability Quality Review", + "repositoryURL": "", + "description": "The Disability Quality Review system is an JAVA web-based application that allows in-line quality reviews of cases/claims adjudicated by the Disability Determination Services.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claims Review", + "Review", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Official Union Time Tracking System", + "repositoryURL": "", + "description": "OUTTS will collect and load into MTAS the number and type of regular hours, as well as the number and type of credit hours that were worked on official union time for the current pay period or amended union activity for a prior pay period.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Human Resources", + "Time and Attendance", + "Union" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "National Disability Determination Services System", + "repositoryURL": "", + "description": "NDDSS is a software application that provides case control management and reporting capabilities. NDDSS gives the state Disability Determination Services offices the ability to track the receipt, development and closures of claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Management", + "Determination", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Disability Case Processing System", + "repositoryURL": "", + "description": "The Disability Case Processing System is used by disability determination components to process disability claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claims Processing", + "Disability", + "Case Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Employer Balancing Intranet Processing System", + "repositoryURL": "", + "description": "The Annual Wage reporting (AWR) Employer Balancing Intranet Processing System (EBIPS) enables users to view submitter, employer, submission, W-3, W-2, and report of contact information.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Wage Reporting", + "Employer" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "myAPS Web Application", + "repositoryURL": "", + "description": "As part of the mySSA suite of applications, myAPS provides detailed status information for all pending T2, T16, and T18 claims, including Appeals up to the Hearing Request level for denied claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claims", + "Claims Tracking", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Global Reference Table Portal", + "repositoryURL": "", + "description": "Application used to collect data to update the Global Reference Tables, which store common information used throughout SSA, and standardize code structures and code usage of SSA business and Policy-approved values.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Metadata Management", + "Data", + "Common" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Workload Action Center", + "repositoryURL": "", + "description": "The Workload Action Center (WAC) allows users to view, analyze, and work initial claims and appeals pending lists, as well as mainframe tickle lists. It consumes Programmatic Workload data to provide information to the 1,394 field offices to assist SSA employees in adjudicating initial disability claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Disability", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MySSA Benefit Verification - Backend", + "repositoryURL": "", + "description": "Accessed through the MySocialSecurity portal, it provides instant verification of SSA benefits for proof of income purposes. It also provides immediate view, print, and save of benefit verification letters to prove receipt/non-receipt of SSA benefits, Supplemental Income (SSI) or Medicare.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Registration", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "iAppeals (i3441)", + "repositoryURL": "", + "description": "Allows electronic submission of requests from individuals and/or third parties for the Request for Reconsideration (SSA-561), Request for Hearing (HA-501) on medically denied claims for both Title II and Title XVI claims, and allows an individual to appeal the decision directly on-line.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Appeals", + "Medical", + "Forms" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Number Verification - BSO", + "repositoryURL": "", + "description": "Allows employers to verify name/SSNs for wage reporting purposes.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Identity", + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Calendar Availability Services", + "repositoryURL": "", + "description": "The calendar availability service allows the ability to add availability, update availability, get availability, update available resources, and delete availability for one or many offices and calendar configurations.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Spring Boot", + "RESTful", + "Calendar Management", + "Calendar Availability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "CET Dynamic Help", + "repositoryURL": "", + "description": "mySSA Dynamic Help application", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "mySSA" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "codeMetadata.json Generator", + "repositoryURL": "", + "description": "A single page application for generating a codeMetadata.json file. The codeMetadata.json file contains basic data about a code asset such as it's name, description, languages, and the like.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "node.js", + "REACT", + "SPA", + "Single Page Application" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "EPMO Web Application", + "repositoryURL": "", + "description": "EPMO Application is developed in MDE using AngualrJS, HTML front end and Java (Jax-RS ) backend. This is a RESTful app with authentication and authorization done using WebSeal.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "AngularJS", + "JAX-RS", + "EJB", + "SPA", + "JWT" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "iAppointment", + "repositoryURL": "", + "description": "An Internet application that allows individuals to schedule appointments with SSA's Field Offices.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Appointments", + "MVC", + "UEF", + "FlexWeb" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Main Complex Conference Rooms System", + "repositoryURL": "", + "description": "The MCCR system is a web application tool used to reserve conference rooms for meetings, events, presentations, etc.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "facilities, conference room, reservations, coldfusion" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MDE Control Center", + "repositoryURL": "", + "description": "Self-serve control center application for SSA MDE.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Spring", + "Thymeleaf", + "LDAP", + "SMTP" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MDE JSON Generator", + "repositoryURL": "", + "description": "Self-serve application for SSA mde.json generation.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Spring", + "Thymeleaf", + "JSON" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Message Center", + "repositoryURL": "", + "description": "CET Message Center for mySSA", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "CET", + "mySSA" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Message Service", + "repositoryURL": "", + "description": "Web Service for CET Message Center", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "SOAP" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MessageAdmin", + "repositoryURL": "", + "description": "CET Message Center Admin Console", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "CET" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "openshift-upgrade-testing", + "repositoryURL": "", + "description": "Java code to create a sample web app - 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Identifies those transactions that may indicate abuse or fraudulent activity involving SSA employees or the public.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Review", + "Fraud Prevention" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Consent_Based_Social_Security_Number_Verification.json b/agency-indexes/SSA/Consent_Based_Social_Security_Number_Verification.json new file mode 100644 index 00000000..07ad218d --- /dev/null +++ b/agency-indexes/SSA/Consent_Based_Social_Security_Number_Verification.json @@ -0,0 +1,18 @@ +{ + "name": "Consent Based Social Security Number Verification", + "repositoryURL": "", + "description": "A fee-based SSN verification service that permits private businesses, as well as Federal, State and Local governments, to use the Internet or a Web Service to verify an individual's SSN once a valid signed consent form is obtained from the SSN holder.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Core_Services.json b/agency-indexes/SSA/Core_Services.json new file mode 100644 index 00000000..bb25cbe3 --- /dev/null +++ b/agency-indexes/SSA/Core_Services.json @@ -0,0 +1,19 @@ +{ + "name": "Core Services", + "repositoryURL": "", + "description": "A suite of Intranet-based utilities designed to simplify central or common routines required by many web based applications. The utilities leverage open, accessible technologies eliminating the drawbacks commonly seen in proprietary coding techniques. They help prevent duplication of effort by reusing what already exists.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Intranet", + "Services" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Cornhusker.json b/agency-indexes/SSA/Cornhusker.json new file mode 100644 index 00000000..eb6323ef --- /dev/null +++ b/agency-indexes/SSA/Cornhusker.json @@ -0,0 +1,19 @@ +{ + "name": "Cornhusker", + "repositoryURL": "", + "description": "Legacy Disability system used by the Nebraska DDS.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Processing", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Cost_Analysis_System.json b/agency-indexes/SSA/Cost_Analysis_System.json new file mode 100644 index 00000000..9159262e --- /dev/null +++ b/agency-indexes/SSA/Cost_Analysis_System.json @@ -0,0 +1,18 @@ +{ + "name": "Cost Analysis System", + "repositoryURL": "", + "description": "The Cost Analysis System gathers workload counts and costs.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Cost Analysis" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Customer_Help_and_Information_Program.json b/agency-indexes/SSA/Customer_Help_and_Information_Program.json new file mode 100644 index 00000000..72bfd227 --- /dev/null +++ b/agency-indexes/SSA/Customer_Help_and_Information_Program.json @@ -0,0 +1,20 @@ +{ + "name": "Customer Help and Information Program", + "repositoryURL": "", + "description": "CHIP is an Intranet application currently used by National 800 Number (N8NN) Agents to respond to inquiries made by the public. Provides instant access to facts, policies and reference material found in the Teleservice Center Operating Guide (TSCOG), as well as information from certain mainframe records.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Policy", + "Call Center", + "Phone" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/DCE-Document_Conversion_Engine.json b/agency-indexes/SSA/DCE-Document_Conversion_Engine.json new file mode 100644 index 00000000..241e29d3 --- /dev/null +++ b/agency-indexes/SSA/DCE-Document_Conversion_Engine.json @@ -0,0 +1,27 @@ +{ + "name": "DCE-Document Conversion Engine", + "repositoryURL": "https://github.com/SSAgov/dce-web", + "description": "DCE UI is a modern web architecture using .NET WebApi2 and React Application acting as an independent front end. DCE UI is a single page web app using ReactJS, React-Router for URL routing, React-Form API for the conversion forms, Fetch API to make calls to the DCE-WebAPI, and Gulp to automate deployments to our DEV environments.", + "permissions": { + "licenses": [ + { + "URL": "www.apache.org/licenses/LICENSE-2.0", + "name": "Apache" + } + ], + "usageType": "openSource", + "exemptionText": "" + }, + "laborHours": 1140, + "tags": [ + "DCE", + "Conversion", + "Document", + "Document Conversion", + "Document Conversion Engine" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/DCS_Budget_Tracking_System.json b/agency-indexes/SSA/DCS_Budget_Tracking_System.json new file mode 100644 index 00000000..afb2ef62 --- /dev/null +++ b/agency-indexes/SSA/DCS_Budget_Tracking_System.json @@ -0,0 +1,20 @@ +{ + "name": "DCS Budget Tracking System", + "repositoryURL": "", + "description": "Tracks Other Objects budget allocations for the Office of Systems and tracks some Information Technology budgets. Monitors and tracks allocations, expenditures and generates Management Information (MI) reports for planning budget requests and allocations.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Management Information", + "Administrative", + "Budget Tracking" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Data_Exchange_and_Verification_Online.json b/agency-indexes/SSA/Data_Exchange_and_Verification_Online.json new file mode 100644 index 00000000..3218a508 --- /dev/null +++ b/agency-indexes/SSA/Data_Exchange_and_Verification_Online.json @@ -0,0 +1,20 @@ +{ + "name": "Data Exchange and Verification Online", + "repositoryURL": "", + "description": "DEVO is the back-end application for processing SSN verifications and data exchanges. DEVO uses modern technology for parameter driven processing of both batch and real time requests. DEVO provides the capability for SSA to accurately and rapidly respond to customized requests, legislative mandates, and court orders. Legacy verification and data exchange applications (Enumeration Verification System (EVS), Numident Online Verification Utility (NOVU), State Verification Exchange System (SVES), and State Online Query System (SOLQ)) are methodically being reengineered into DEVO, which will make use of reusable, flexible software. DEVO interfaces with the Verification Account Management System (VAMS) to determine account status, obtain processing parameters, and store transaction counts for Management Information (MI).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Verification", + "Data Exchange" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Death_Information_Processing_System_Web.json b/agency-indexes/SSA/Death_Information_Processing_System_Web.json new file mode 100644 index 00000000..92f6afe5 --- /dev/null +++ b/agency-indexes/SSA/Death_Information_Processing_System_Web.json @@ -0,0 +1,18 @@ +{ + "name": "Death Information Processing System Web", + "repositoryURL": "", + "description": "The Death Information Processing System (DIPS) is a web-based iMain application used to add, change, or delete death data on the NUMIDENT. It replaced the Death Alert Control and Update System (DACUS) CICS screens in PCOM.", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Death" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Detailed_Office_Organization_Resource_System.json b/agency-indexes/SSA/Detailed_Office_Organization_Resource_System.json new file mode 100644 index 00000000..5b3e4253 --- /dev/null +++ b/agency-indexes/SSA/Detailed_Office_Organization_Resource_System.json @@ -0,0 +1,20 @@ +{ + "name": "Detailed Office Organization Resource System", + "repositoryURL": "", + "description": "The Detailed Office/Organization Resource System (DOORS) is SSA's official Agency repository of office information, such as location and phone numbers, for all SSA offices. DOORS has a user and customer base of all SSA employees, hundreds of SSA systems, and members of the public who use SSA.GOV on the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Inventory Management", + "Office", + "Administrative" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Direct_Deposit_Fraud_Prevention.json b/agency-indexes/SSA/Direct_Deposit_Fraud_Prevention.json new file mode 100644 index 00000000..9c8758b6 --- /dev/null +++ b/agency-indexes/SSA/Direct_Deposit_Fraud_Prevention.json @@ -0,0 +1,19 @@ +{ + "name": "Direct Deposit Fraud Prevention", + "repositoryURL": "", + "description": "An intranet web application developed to collect and processes requests to block direct deposit auto-enrollment changes that are received and processed in the SSA Notification of Change (SANOC) System. The DDFP web application also requires input of the reason for the block - Fraud Alleged or Preventive Measure. Both the adding and removal of the block are updated in real time allowing the application to access the data for display the block request history.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Direct Deposit", + "Fraud Prevention" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Disability_Case_Adjudication_and_Review_System.json b/agency-indexes/SSA/Disability_Case_Adjudication_and_Review_System.json new file mode 100644 index 00000000..a13d8569 --- /dev/null +++ b/agency-indexes/SSA/Disability_Case_Adjudication_and_Review_System.json @@ -0,0 +1,19 @@ +{ + "name": "Disability Case Adjudication and Review System", + "repositoryURL": "", + "description": "Disability Case Adjudication and Review System (DICARS) is the legacy system supporting business processes in the Disability Quality Branches (DQBs) and the simultaneous, blind, pre-effectuation consistency review of initial Disability Determination Service (DDS) clearances processed in Division of Disability Quality Operations DDQO). Works in conjunction with the Disability Quality Review (DQR) application which will eventually replace it.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Processing", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Disability_Case_Processing_System.json b/agency-indexes/SSA/Disability_Case_Processing_System.json new file mode 100644 index 00000000..3b71113b --- /dev/null +++ b/agency-indexes/SSA/Disability_Case_Processing_System.json @@ -0,0 +1,20 @@ +{ + "name": "Disability Case Processing System", + "repositoryURL": "", + "description": "The Disability Case Processing System is used by disability determination components to process disability claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claims Processing", + "Disability", + "Case Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Disability_Predictive_Model.json b/agency-indexes/SSA/Disability_Predictive_Model.json new file mode 100644 index 00000000..e9843679 --- /dev/null +++ b/agency-indexes/SSA/Disability_Predictive_Model.json @@ -0,0 +1,19 @@ +{ + "name": "Disability Predictive Model", + "repositoryURL": "", + "description": "Dual score card application based on the Predictive Model design architecture written by IBM. It is called when initial adjudicative disability cases are transferred to the DDS for a medical determination. It will analyze the date electronically and produce two values, each between 0 and 1. The first value will express the confidence that a favorable determination will be made (known as SSAL - SSA Allowance). The second (known as SSPT - SSA Processing Time) will express the confidence that the determination can be reached quickly.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Predictive", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Disability_Quality_Review.json b/agency-indexes/SSA/Disability_Quality_Review.json new file mode 100644 index 00000000..0a69ae43 --- /dev/null +++ b/agency-indexes/SSA/Disability_Quality_Review.json @@ -0,0 +1,20 @@ +{ + "name": "Disability Quality Review", + "repositoryURL": "", + "description": "The Disability Quality Review system is an JAVA web-based application that allows in-line quality reviews of cases/claims adjudicated by the Disability Determination Services.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claims Review", + "Review", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Document_Generation_System.json b/agency-indexes/SSA/Document_Generation_System.json new file mode 100644 index 00000000..f5e92982 --- /dev/null +++ b/agency-indexes/SSA/Document_Generation_System.json @@ -0,0 +1,19 @@ +{ + "name": "Document Generation System", + "repositoryURL": "", + "description": "DGS is a Windows-based application used to create Office of Hearings and Appeals (OHA) Distributed Online Correspondence System (DOCS) and notices.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Notices", + "Document Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Document_Processing_System.json b/agency-indexes/SSA/Document_Processing_System.json new file mode 100644 index 00000000..92f30dc2 --- /dev/null +++ b/agency-indexes/SSA/Document_Processing_System.json @@ -0,0 +1,19 @@ +{ + "name": "Document Processing System", + "repositoryURL": "", + "description": "The Document Processing System (DPS) is an SSA developed, browser based application that will provide the user with functionality similar to the client server based system, Distributed Online Correspondence System (DOCS).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Document Processing", + "Document Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/EMR-Framework.json b/agency-indexes/SSA/EMR-Framework.json new file mode 100644 index 00000000..4e5d4288 --- /dev/null +++ b/agency-indexes/SSA/EMR-Framework.json @@ -0,0 +1,20 @@ +{ + "name": "EMR-Framework", + "repositoryURL": "", + "description": "The Enterprise Metadata Repository Framework is built on an open architecture using relational databases and provides an infrastructure for retrieving data to load to the EMR, as well as controlling the load process.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Framework", + "Data", + "Metadata Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/EMR-UI_API.json b/agency-indexes/SSA/EMR-UI_API.json new file mode 100644 index 00000000..9e6fba59 --- /dev/null +++ b/agency-indexes/SSA/EMR-UI_API.json @@ -0,0 +1,20 @@ +{ + "name": "EMR-UI/API", + "repositoryURL": "", + "description": "Provides front-end and API access to the Enterprise Metadata Repository, which stores metadata about SSA's applications and databases. The Enterprise Metadata Repository (EMR) is a data management tool used to coordinate enterprise-wide information. It ties physical and logical metadata which may be used in data administration and application development efforts. The EMR is built on an open architecture using relational databases. It serves as a central location for documentation of SSA's data infrastructure.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Front End", + "Data", + "Metadata Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/EPMO_Web_Application.json b/agency-indexes/SSA/EPMO_Web_Application.json new file mode 100644 index 00000000..7873ddb9 --- /dev/null +++ b/agency-indexes/SSA/EPMO_Web_Application.json @@ -0,0 +1,22 @@ +{ + "name": "EPMO Web Application", + "repositoryURL": "", + "description": "EPMO Application is developed in MDE using AngualrJS, HTML front end and Java (Jax-RS ) backend. This is a RESTful app with authentication and authorization done using WebSeal.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "AngularJS", + "JAX-RS", + "EJB", + "SPA", + "JWT" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Earnings_Case_Management_System.json b/agency-indexes/SSA/Earnings_Case_Management_System.json new file mode 100644 index 00000000..5d0f337a --- /dev/null +++ b/agency-indexes/SSA/Earnings_Case_Management_System.json @@ -0,0 +1,20 @@ +{ + "name": "Earnings Case Management System", + "repositoryURL": "", + "description": "This is a case management system which tracks many different earnings workloads.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Earnings Requests", + "Case Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Earnings_Modernization_Itemized_Statement_of_Earnings_Requests.json b/agency-indexes/SSA/Earnings_Modernization_Itemized_Statement_of_Earnings_Requests.json new file mode 100644 index 00000000..e211cd2b --- /dev/null +++ b/agency-indexes/SSA/Earnings_Modernization_Itemized_Statement_of_Earnings_Requests.json @@ -0,0 +1,19 @@ +{ + "name": "Earnings Modernization Itemized Statement of Earnings Requests", + "repositoryURL": "", + "description": "Earnings Modernization Itemized Statement of Earnings Report (EMISER) is an interactive CICS control system that processes requests for Itemized Statements of Earnings (SSA-1826).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Earnings Requests", + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Earnings_Use_-_SEQY.json b/agency-indexes/SSA/Earnings_Use_-_SEQY.json new file mode 100644 index 00000000..555811bb --- /dev/null +++ b/agency-indexes/SSA/Earnings_Use_-_SEQY.json @@ -0,0 +1,18 @@ +{ + "name": "Earnings Use - SEQY", + "repositoryURL": "", + "description": "A Master File online query request screen that adds earnings from up to 10 SSNs to the query response. The system then combines the earnings from the SSNs in the yearly totals on the query response.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Electronic_Access_-__RIR_.json b/agency-indexes/SSA/Electronic_Access_-__RIR_.json new file mode 100644 index 00000000..bf767d16 --- /dev/null +++ b/agency-indexes/SSA/Electronic_Access_-__RIR_.json @@ -0,0 +1,19 @@ +{ + "name": "Electronic Access - (RIR)", + "repositoryURL": "", + "description": "ID Proofing and Authentication system for SSA online applications.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Security", + "Authentication" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Electronic_Bench_Book.json b/agency-indexes/SSA/Electronic_Bench_Book.json new file mode 100644 index 00000000..00c199f3 --- /dev/null +++ b/agency-indexes/SSA/Electronic_Bench_Book.json @@ -0,0 +1,20 @@ +{ + "name": "Electronic Bench Book", + "repositoryURL": "", + "description": "A web-based application used by the office of Disability Adjudication and Review/ODAR to aid with documentation, analysis, and adjudication of disability cases.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Adjudication", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Electronic_Claims_Analysis_Tool.json b/agency-indexes/SSA/Electronic_Claims_Analysis_Tool.json new file mode 100644 index 00000000..e8f3c92d --- /dev/null +++ b/agency-indexes/SSA/Electronic_Claims_Analysis_Tool.json @@ -0,0 +1,18 @@ +{ + "name": "Electronic Claims Analysis Tool", + "repositoryURL": "", + "description": "eCAT is a web-based application that guides Disability Examiners and Medical Consultants through the sequential evaluation of a disability claim. The tool aids in documenting, analyzing, and adjudicating the claim in accordance with SSA regulations.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git "a/agency-indexes/SSA/Electronic_Disability_Collection_System__EDCS\\eView_.json" "b/agency-indexes/SSA/Electronic_Disability_Collection_System__EDCS\\eView_.json" new file mode 100644 index 00000000..35f781c4 --- /dev/null +++ "b/agency-indexes/SSA/Electronic_Disability_Collection_System__EDCS\\eView_.json" @@ -0,0 +1,19 @@ +{ + "name": "Electronic Disability Collection System (EDCS\\eView)", + "repositoryURL": "", + "description": "An automated system for SSA field personnel to electronically collect information about the applicant and his or her medical condition, and transfer the data to the EF for use by a local case management system.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Management", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Electronic_Folder_Interface.json b/agency-indexes/SSA/Electronic_Folder_Interface.json new file mode 100644 index 00000000..ab59e70b --- /dev/null +++ b/agency-indexes/SSA/Electronic_Folder_Interface.json @@ -0,0 +1,18 @@ +{ + "name": "Electronic Folder Interface", + "repositoryURL": "", + "description": "An interface between the electronic folder and the case processing systems (CPMS for ODAR). Enables transactions that allow: Messages and alerts to be sent to case processing systems; Electronic cases to be transferred between processing locations and closed when processing is complete; and Case processing systems to electronically send data to the CEF when case processing actions are complete.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Electronic_Folder_Interface_-_Data_Access.json b/agency-indexes/SSA/Electronic_Folder_Interface_-_Data_Access.json new file mode 100644 index 00000000..30867685 --- /dev/null +++ b/agency-indexes/SSA/Electronic_Folder_Interface_-_Data_Access.json @@ -0,0 +1,19 @@ +{ + "name": "Electronic Folder Interface - Data Access", + "repositoryURL": "", + "description": "Allows shared access via eView to legacy information and documents within a case.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Document", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Electronic_Freedom_of_Information_Act_System_-Intranet.json b/agency-indexes/SSA/Electronic_Freedom_of_Information_Act_System_-Intranet.json new file mode 100644 index 00000000..f658ea76 --- /dev/null +++ b/agency-indexes/SSA/Electronic_Freedom_of_Information_Act_System_-Intranet.json @@ -0,0 +1,19 @@ +{ + "name": "Electronic Freedom of Information Act System -Intranet", + "repositoryURL": "", + "description": "An Intranet application used by the Office of Public Disclosure (OPD) and the Division of Earnings Record Operations (DERO) to process the different types of FOIA requests that are received.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Intranet", + "FOIA" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Electronic_Personal_Enrollment_Credential_System.json b/agency-indexes/SSA/Electronic_Personal_Enrollment_Credential_System.json new file mode 100644 index 00000000..1e6c310b --- /dev/null +++ b/agency-indexes/SSA/Electronic_Personal_Enrollment_Credential_System.json @@ -0,0 +1,18 @@ +{ + "name": "Electronic Personal Enrollment Credential System", + "repositoryURL": "", + "description": "The HSPD-12 Electronic Personal Enrollment Credential System (EPECS) supports the HSPD-12 credentialing process at SSA. It automates the sponsoring, vetting, and issuing of HSPD-12 credentials. It interfaces with other SSA systems for compliance with various directives.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Electronic_Sign-in_Sheet.json b/agency-indexes/SSA/Electronic_Sign-in_Sheet.json new file mode 100644 index 00000000..8da8e390 --- /dev/null +++ b/agency-indexes/SSA/Electronic_Sign-in_Sheet.json @@ -0,0 +1,25 @@ +{ + "name": "Electronic Sign-in Sheet", + "repositoryURL": "https://github.com/SSAgov/ELSO", + "description": "The Electronic Sign-in Sheet (ELSO) is a web-based application used to record meeting attendance. The ELSO application allows the creation of an electronic attendance record, saving time and resources by eliminating the need to manually record and transcribe attendance using paper sign-in sheets.", + "permissions": { + "licenses": [ + { + "URL": "www.apache.org/licenses/LICENSE-2.0", + "name": "Apache" + } + ], + "usageType": "openSource", + "exemptionText": "" + }, + "laborHours": 1657, + "tags": [ + "Electronic Sign-in Sheet", + "ASP.NET Web API", + "ASP.NET MVC" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Electronic_Work_Reporting_Front_End.json b/agency-indexes/SSA/Electronic_Work_Reporting_Front_End.json new file mode 100644 index 00000000..80631c12 --- /dev/null +++ b/agency-indexes/SSA/Electronic_Work_Reporting_Front_End.json @@ -0,0 +1,19 @@ +{ + "name": "Electronic Work Reporting Front End", + "repositoryURL": "", + "description": "A Web-based application used by all SSA technicians (TSC, FO, PC, and OCO), which fully automates the initiation, development, adjudication, and effectuation of Title II Work CDRs.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Work Reporting", + "Title II" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Employee_Office_Sampler.json b/agency-indexes/SSA/Employee_Office_Sampler.json new file mode 100644 index 00000000..d9527329 --- /dev/null +++ b/agency-indexes/SSA/Employee_Office_Sampler.json @@ -0,0 +1,19 @@ +{ + "name": "Employee Office Sampler", + "repositoryURL": "", + "description": "Capture/store/manage end-user work activities at designated times as needed for DOWS sampling", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Field Office" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Employee_Retirement_Income_Security_Act.json b/agency-indexes/SSA/Employee_Retirement_Income_Security_Act.json new file mode 100644 index 00000000..6bf77817 --- /dev/null +++ b/agency-indexes/SSA/Employee_Retirement_Income_Security_Act.json @@ -0,0 +1,19 @@ +{ + "name": "Employee Retirement Income Security Act", + "repositoryURL": "", + "description": "Produces notices to inform retirees of their possible eligibility for pensions under a private pension plan. There is also an online system for users in OCO and the field offices to query the ERISA master files.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Private Pensions", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Employer_Balancing_Intranet_Processing_System.json b/agency-indexes/SSA/Employer_Balancing_Intranet_Processing_System.json new file mode 100644 index 00000000..21cb5b76 --- /dev/null +++ b/agency-indexes/SSA/Employer_Balancing_Intranet_Processing_System.json @@ -0,0 +1,19 @@ +{ + "name": "Employer Balancing Intranet Processing System", + "repositoryURL": "", + "description": "The Annual Wage reporting (AWR) Employer Balancing Intranet Processing System (EBIPS) enables users to view submitter, employer, submission, W-3, W-2, and report of contact information.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Wage Reporting", + "Employer" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Enumeration_Verification_System.json b/agency-indexes/SSA/Enumeration_Verification_System.json new file mode 100644 index 00000000..bbb2fb24 --- /dev/null +++ b/agency-indexes/SSA/Enumeration_Verification_System.json @@ -0,0 +1,18 @@ +{ + "name": "Enumeration Verification System", + "repositoryURL": "", + "description": "A batch application that provides SSN, corresponding name, DOB, and/or gender match validation to federal, state, local and foreign government agencies, private companies and internal SSA customers and systems.", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Federal_Assistance_Award_Data_System.json b/agency-indexes/SSA/Federal_Assistance_Award_Data_System.json new file mode 100644 index 00000000..2593d816 --- /dev/null +++ b/agency-indexes/SSA/Federal_Assistance_Award_Data_System.json @@ -0,0 +1,18 @@ +{ + "name": "Federal Assistance Award Data System", + "repositoryURL": "", + "description": "A central collection of selected, computer-based domestic financial assistance programs data for the Federal Government mandated by the Federal Funding Accountability and Transparency Act and is compiled quarterly.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Federal Assistance" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Front_End_Capture_System.json b/agency-indexes/SSA/Front_End_Capture_System.json new file mode 100644 index 00000000..cc3625bb --- /dev/null +++ b/agency-indexes/SSA/Front_End_Capture_System.json @@ -0,0 +1,19 @@ +{ + "name": "Front End Capture System", + "repositoryURL": "", + "description": "Front-end document capture system for DMA. Processes unstructured data and sends a receipt notification to the requesting application.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Document Capture", + "Document Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Fugitive_Felon_Matching_Agreements.json b/agency-indexes/SSA/Fugitive_Felon_Matching_Agreements.json new file mode 100644 index 00000000..98085e8e --- /dev/null +++ b/agency-indexes/SSA/Fugitive_Felon_Matching_Agreements.json @@ -0,0 +1,18 @@ +{ + "name": "Fugitive Felon Matching Agreements", + "repositoryURL": "", + "description": "APPLICATION TO COLLECT INFORMATION ON SSA EFFORTS TO NEGOTIATE MATCHING AGREEMENTS WITH LAW ENFORCEMENT AGENCIES TO IDENTIFY FUGITIVE FELONS AND PAROLE AND PROBATION VIOLATORS", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Felon" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/GIS_Direct_Deposit_Maps.json b/agency-indexes/SSA/GIS_Direct_Deposit_Maps.json new file mode 100644 index 00000000..8f9807d5 --- /dev/null +++ b/agency-indexes/SSA/GIS_Direct_Deposit_Maps.json @@ -0,0 +1,19 @@ +{ + "name": "GIS Direct Deposit Maps", + "repositoryURL": "", + "description": "GISSDD maps application creates U.S. and State/County maps and reports, to provide the percentage of Title II and Title XVI payments made through direct deposit in those areas. The information is updated monthly and uploaded to the SSA Internet site.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Maps", + "Geospatial" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/GSO_-_Interim_Assistance_Reimbursement.json b/agency-indexes/SSA/GSO_-_Interim_Assistance_Reimbursement.json new file mode 100644 index 00000000..18ce26de --- /dev/null +++ b/agency-indexes/SSA/GSO_-_Interim_Assistance_Reimbursement.json @@ -0,0 +1,19 @@ +{ + "name": "GSO - Interim Assistance Reimbursement", + "repositoryURL": "", + "description": "An online mechanism for state agencies to report to SSA the amount of state or local assistance the agencies paid to individuals who are now eligible for SSI payments.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Data Exchanges", + "Payments" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Global_Reference_Table_Portal.json b/agency-indexes/SSA/Global_Reference_Table_Portal.json new file mode 100644 index 00000000..771002d8 --- /dev/null +++ b/agency-indexes/SSA/Global_Reference_Table_Portal.json @@ -0,0 +1,20 @@ +{ + "name": "Global Reference Table Portal", + "repositoryURL": "", + "description": "Application used to collect data to update the Global Reference Tables, which store common information used throughout SSA, and standardize code structures and code usage of SSA business and Policy-approved values.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Metadata Management", + "Data", + "Common" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Health_informationTechnology_management_information.json b/agency-indexes/SSA/Health_informationTechnology_management_information.json new file mode 100644 index 00000000..c9a1dbc9 --- /dev/null +++ b/agency-indexes/SSA/Health_informationTechnology_management_information.json @@ -0,0 +1,18 @@ +{ + "name": "Health informationTechnology management information", + "repositoryURL": "", + "description": "Health IT Management Information (HIT MI) is part of the WebFocus Business Intelligence Dashboard. It provides data analysis to monitor work loads and trend analysis and information on a variety of variables such as time and location, allowing users to make further improvements and enhancements to the disability process.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "HealthIT" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Hires_and_Losses_Tracking_System.json b/agency-indexes/SSA/Hires_and_Losses_Tracking_System.json new file mode 100644 index 00000000..63494eba --- /dev/null +++ b/agency-indexes/SSA/Hires_and_Losses_Tracking_System.json @@ -0,0 +1,18 @@ +{ + "name": "Hires and Losses Tracking System", + "repositoryURL": "", + "description": "This application tracks the hires and losses of employees to the Office of Systems. It provides an automated way of approving hires and tracking both hires and losses in Systems. It also provides many reports from captured data on individuals joining the Office of Systems, leaving the Office of Systems, or moving from one Associate Commissioner's office within Systems to another Associate Commissioner's office within Systems. The data from these reports are used by management to make budget decisions.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Human Resources" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Integrated_Client_Database_System.json b/agency-indexes/SSA/Integrated_Client_Database_System.json new file mode 100644 index 00000000..660c50aa --- /dev/null +++ b/agency-indexes/SSA/Integrated_Client_Database_System.json @@ -0,0 +1,18 @@ +{ + "name": "Integrated Client Database System", + "repositoryURL": "", + "description": "The Integrated Client Database (ICDB) System allows data to be shared among SSA's major application systems (e.g., Title II and Title XVI Claims Processing). ICDB is comprised of a set of databases, common screens and access software that collects, maintains, and provides access to common Client data.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Client" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Integrated_Registration_Services_-_Internet.json b/agency-indexes/SSA/Integrated_Registration_Services_-_Internet.json new file mode 100644 index 00000000..01c7ecc1 --- /dev/null +++ b/agency-indexes/SSA/Integrated_Registration_Services_-_Internet.json @@ -0,0 +1,19 @@ +{ + "name": "Integrated Registration Services - Internet", + "repositoryURL": "", + "description": "An internet application that provides registration, authentication and authorization gateway services for the Business Services Online (BSO) suite of Business-to-Government (B2G) services.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Registration", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Internet_Application_Status.json b/agency-indexes/SSA/Internet_Application_Status.json new file mode 100644 index 00000000..d8fb5c14 --- /dev/null +++ b/agency-indexes/SSA/Internet_Application_Status.json @@ -0,0 +1,19 @@ +{ + "name": "Internet Application Status", + "repositoryURL": "", + "description": "An application that allows an individual to enter their Social Security Number (SSN) and follow the progress of all available claims using the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claim Status", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Internet_Special_Notices_Option.json b/agency-indexes/SSA/Internet_Special_Notices_Option.json new file mode 100644 index 00000000..31718e82 --- /dev/null +++ b/agency-indexes/SSA/Internet_Special_Notices_Option.json @@ -0,0 +1,19 @@ +{ + "name": "Internet Special Notices Option", + "repositoryURL": "", + "description": "An Internet/Intranet application designed to collect notice preferences from applicants, beneficiaries, recipients, and representative payees who allege blindness or visual impairment. These individuals can select to receive all notices and written communication from SSA via a Microsoft Word CD or in Braille.", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "SNO", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Internet_Ticket_Operations_Provider_Support_System.json b/agency-indexes/SSA/Internet_Ticket_Operations_Provider_Support_System.json new file mode 100644 index 00000000..02ebf530 --- /dev/null +++ b/agency-indexes/SSA/Internet_Ticket_Operations_Provider_Support_System.json @@ -0,0 +1,20 @@ +{ + "name": "Internet Ticket Operations Provider Support System", + "repositoryURL": "", + "description": "An automated system that allows users to award contracts, provide ticket assignment/unassignment, and payments for Employment Networks (EN). It allows users to process, verify, and cancel payments before they reach Treasury.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Payments", + "Employment Networks", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Legal_Automated_Workflow_System.json b/agency-indexes/SSA/Legal_Automated_Workflow_System.json new file mode 100644 index 00000000..7a301fac --- /dev/null +++ b/agency-indexes/SSA/Legal_Automated_Workflow_System.json @@ -0,0 +1,18 @@ +{ + "name": "Legal Automated Workflow System", + "repositoryURL": "", + "description": "A new system replacing the Program Litigation functions in the National Docketing Management Information System (NDMIS). LAWS electronically receives information contained in the Certified Administrative Record (CAR), interacts with Electronic Folder, allows OGC users access to historical data, accurately captures workloads, and enables users to produce and communicate management information.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workflow" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/MDE_Control_Center.json b/agency-indexes/SSA/MDE_Control_Center.json new file mode 100644 index 00000000..f6f1996c --- /dev/null +++ b/agency-indexes/SSA/MDE_Control_Center.json @@ -0,0 +1,21 @@ +{ + "name": "MDE Control Center", + "repositoryURL": "", + "description": "Self-serve control center application for SSA MDE.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Spring", + "Thymeleaf", + "LDAP", + "SMTP" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/MDE_JSON_Generator.json b/agency-indexes/SSA/MDE_JSON_Generator.json new file mode 100644 index 00000000..aee390a8 --- /dev/null +++ b/agency-indexes/SSA/MDE_JSON_Generator.json @@ -0,0 +1,20 @@ +{ + "name": "MDE JSON Generator", + "repositoryURL": "", + "description": "Self-serve application for SSA mde.json generation.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Spring", + "Thymeleaf", + "JSON" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/MI_Central.json b/agency-indexes/SSA/MI_Central.json new file mode 100644 index 00000000..26c99c6c --- /dev/null +++ b/agency-indexes/SSA/MI_Central.json @@ -0,0 +1,18 @@ +{ + "name": "MI Central", + "repositoryURL": "", + "description": "Facilitates access to management information and workload control reports by providing centralized access to workload counts, workload control listings, processing time reports, performance measurement reports and managerial cost analysis data/reports.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Management Information" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/MI_for_Debt_Management_System.json b/agency-indexes/SSA/MI_for_Debt_Management_System.json new file mode 100644 index 00000000..eb6630fc --- /dev/null +++ b/agency-indexes/SSA/MI_for_Debt_Management_System.json @@ -0,0 +1,19 @@ +{ + "name": "MI for Debt Management System", + "repositoryURL": "", + "description": "Provides an summary of the financial Debt Management screens at the regional field offices and the processing center levels", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Processing Center", + "Debt Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Main_Complex_Conference_Rooms_System.json b/agency-indexes/SSA/Main_Complex_Conference_Rooms_System.json new file mode 100644 index 00000000..dccf54da --- /dev/null +++ b/agency-indexes/SSA/Main_Complex_Conference_Rooms_System.json @@ -0,0 +1,18 @@ +{ + "name": "Main Complex Conference Rooms System", + "repositoryURL": "", + "description": "The MCCR system is a web application tool used to reserve conference rooms for meetings, events, presentations, etc.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "facilities, conference room, reservations, coldfusion" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Manual_Adjustment_Credit_&_Award_Data_Entry.json b/agency-indexes/SSA/Manual_Adjustment_Credit_&_Award_Data_Entry.json new file mode 100644 index 00000000..3b7af277 --- /dev/null +++ b/agency-indexes/SSA/Manual_Adjustment_Credit_&_Award_Data_Entry.json @@ -0,0 +1,18 @@ +{ + "name": "Manual Adjustment Credit & Award Data Entry", + "repositoryURL": "", + "description": "CICS data collection system consists of data entered/received via MACADE or data that comes to MACADE via A101, and propagates information into the SPS database to create a payment record.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Payment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Medical_Evidence_Gathering_&_Analysis_Health_Information_Technology.json b/agency-indexes/SSA/Medical_Evidence_Gathering_&_Analysis_Health_Information_Technology.json new file mode 100644 index 00000000..3109791a --- /dev/null +++ b/agency-indexes/SSA/Medical_Evidence_Gathering_&_Analysis_Health_Information_Technology.json @@ -0,0 +1,18 @@ +{ + "name": "Medical Evidence Gathering & Analysis Health Information Technology", + "repositoryURL": "", + "description": "An application called through Health IT that requests, receives, and analyzes electronic medical records in a fully automated manner. Upon transfer of a claim to a disability case processing unit, MEGAHIT automatically identifies a health IT participating source and gathers electronic medical records.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Medical Records" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Medicare_-_IRMAA.json b/agency-indexes/SSA/Medicare_-_IRMAA.json new file mode 100644 index 00000000..6471fb9d --- /dev/null +++ b/agency-indexes/SSA/Medicare_-_IRMAA.json @@ -0,0 +1,18 @@ +{ + "name": "Medicare - IRMAA", + "repositoryURL": "", + "description": "Imposes higher Medicare Part B and Part D premium rates on high-income earners as defined by statute, adjusts those additional amounts on the basis of beneficiary allegations, and verifies the accuracy of those allegations.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "medicare" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Medicare_Non-Utilization_Project.json b/agency-indexes/SSA/Medicare_Non-Utilization_Project.json new file mode 100644 index 00000000..5019a903 --- /dev/null +++ b/agency-indexes/SSA/Medicare_Non-Utilization_Project.json @@ -0,0 +1,18 @@ +{ + "name": "Medicare Non-Utilization Project", + "repositoryURL": "", + "description": "The Medicare Non-Usage Project (MNUP) objective is to use Medicare non-utilization information furnished to us by CMS as an indicator to select and prioritize cases for review to determine continued eligibility to SSA Title II benefits. We will obtain an initial data extract of individuals age 90 or over who are living in the United States, in current pay status and have not used Medicare during the previous three years. Subsequent data extracts will be obtained bi-annually. The data received from CMS will include Title II beneficiaries who reside in nursing homes, are enrolled in HMOs, or have private health insurance.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Medicare" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/MessageAdmin.json b/agency-indexes/SSA/MessageAdmin.json new file mode 100644 index 00000000..53aa67b9 --- /dev/null +++ b/agency-indexes/SSA/MessageAdmin.json @@ -0,0 +1,18 @@ +{ + "name": "MessageAdmin", + "repositoryURL": "", + "description": "CET Message Center Admin Console", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "CET" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Message_Center.json b/agency-indexes/SSA/Message_Center.json new file mode 100644 index 00000000..4ffe635a --- /dev/null +++ b/agency-indexes/SSA/Message_Center.json @@ -0,0 +1,19 @@ +{ + "name": "Message Center", + "repositoryURL": "", + "description": "CET Message Center for mySSA", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "CET", + "mySSA" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Message_Service.json b/agency-indexes/SSA/Message_Service.json new file mode 100644 index 00000000..a433fa80 --- /dev/null +++ b/agency-indexes/SSA/Message_Service.json @@ -0,0 +1,18 @@ +{ + "name": "Message Service", + "repositoryURL": "", + "description": "Web Service for CET Message Center", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "SOAP" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Military_Service_Reimbursement.json b/agency-indexes/SSA/Military_Service_Reimbursement.json new file mode 100644 index 00000000..281afd0b --- /dev/null +++ b/agency-indexes/SSA/Military_Service_Reimbursement.json @@ -0,0 +1,19 @@ +{ + "name": "Military Service Reimbursement", + "repositoryURL": "", + "description": "The Military Service Reimbursement System (MSRS) was developed to replace the process within the Title II AERO system that calculates Primary Insurance Amounts (PIA) for the Office of the Chief Actuary (OCACT).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reimbursement", + "Military" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Mini_Learning_Management_System.json b/agency-indexes/SSA/Mini_Learning_Management_System.json new file mode 100644 index 00000000..38d2d720 --- /dev/null +++ b/agency-indexes/SSA/Mini_Learning_Management_System.json @@ -0,0 +1,18 @@ +{ + "name": "Mini Learning Management System", + "repositoryURL": "", + "description": "This LMS supports the Seattle Region Studio 6 in managing course content that they are responsible for, mainly the Transition to Leadership Courses, Core, and ASC/SLC training.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Learning Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Modernized_Integrated_Disability_Adjudicative_System.json b/agency-indexes/SSA/Modernized_Integrated_Disability_Adjudicative_System.json new file mode 100644 index 00000000..eb6167a7 --- /dev/null +++ b/agency-indexes/SSA/Modernized_Integrated_Disability_Adjudicative_System.json @@ -0,0 +1,19 @@ +{ + "name": "Modernized Integrated Disability Adjudicative System", + "repositoryURL": "", + "description": "A federal disability case processing system used in Disability Determination Services, Disability Processing Branches, and some federal components that process disability claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claims", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Modernized_Supplemental_Security_Income_Claims_System.json b/agency-indexes/SSA/Modernized_Supplemental_Security_Income_Claims_System.json new file mode 100644 index 00000000..ce9579f5 --- /dev/null +++ b/agency-indexes/SSA/Modernized_Supplemental_Security_Income_Claims_System.json @@ -0,0 +1,20 @@ +{ + "name": "Modernized Supplemental Security Income Claims System", + "repositoryURL": "", + "description": "Web-based Intranet pages that collect and document application information about the claimant, provide a modernized data-collection environment for most post-eligibility (PE) events - regardless of whether the action taken is an initial claim or a PE event - and allow online claims initiation for the majority of SSI claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Internet", + "Claim", + "SSI" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/MongoCodeWrapper.json b/agency-indexes/SSA/MongoCodeWrapper.json new file mode 100644 index 00000000..eb576c30 --- /dev/null +++ b/agency-indexes/SSA/MongoCodeWrapper.json @@ -0,0 +1,26 @@ +{ + "name": "MongoCodeWrapper", + "repositoryURL": "https://github.com/SSAgov/MongoCodeWrapper", + "description": "MongoCodeWrapper is a standalone Python library to perform Create, Read, Update, and Delete (CRUD) against MongoDB.", + "permissions": { + "licenses": [ + { + "URL": "www.apache.org/licenses/LICENSE-2.0", + "name": "Apache" + } + ], + "usageType": "openSource", + "exemptionText": "" + }, + "laborHours": 532, + "tags": [ + "MongoDB", + "CRUD", + "MongoDB Utilities", + "Python" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/MySSA_Benefit_Verification_-_Backend.json b/agency-indexes/SSA/MySSA_Benefit_Verification_-_Backend.json new file mode 100644 index 00000000..4ed6b9de --- /dev/null +++ b/agency-indexes/SSA/MySSA_Benefit_Verification_-_Backend.json @@ -0,0 +1,19 @@ +{ + "name": "MySSA Benefit Verification - Backend", + "repositoryURL": "", + "description": "Accessed through the MySocialSecurity portal, it provides instant verification of SSA benefits for proof of income purposes. It also provides immediate view, print, and save of benefit verification letters to prove receipt/non-receipt of SSA benefits, Supplemental Income (SSI) or Medicare.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Registration", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/My_Human_Resources.json b/agency-indexes/SSA/My_Human_Resources.json new file mode 100644 index 00000000..8d7f184b --- /dev/null +++ b/agency-indexes/SSA/My_Human_Resources.json @@ -0,0 +1,18 @@ +{ + "name": "My Human Resources", + "repositoryURL": "", + "description": "This application is part of the application hub, Human Resources Services Portal. The e7B creates a secure, electronic centralized repository accessed through the agency's Intranet for all information maintained in the 7B, 7B Extension File, and holding file to reduce the amount of required time and expenditures associated with file maintenance.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Human Resources" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/National_Disability_Determination_Services_System.json b/agency-indexes/SSA/National_Disability_Determination_Services_System.json new file mode 100644 index 00000000..59f9fe98 --- /dev/null +++ b/agency-indexes/SSA/National_Disability_Determination_Services_System.json @@ -0,0 +1,20 @@ +{ + "name": "National Disability Determination Services System", + "repositoryURL": "", + "description": "NDDSS is a software application that provides case control management and reporting capabilities. NDDSS gives the state Disability Determination Services offices the ability to track the receipt, development and closures of claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Management", + "Determination", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/National_Docketing_Management_Information_System.json b/agency-indexes/SSA/National_Docketing_Management_Information_System.json new file mode 100644 index 00000000..dfbcf810 --- /dev/null +++ b/agency-indexes/SSA/National_Docketing_Management_Information_System.json @@ -0,0 +1,20 @@ +{ + "name": "National Docketing Management Information System", + "repositoryURL": "", + "description": "Centralized system for tracking and managing legal matters as a system-of-record for all OGC regions and at OGC headquarters. Tracks due dates to ensure that responsive documents are filed in a timely manner.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Legal", + "Docket Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/National_Instant_Criminal_Background_Check_System.json b/agency-indexes/SSA/National_Instant_Criminal_Background_Check_System.json new file mode 100644 index 00000000..5115deff --- /dev/null +++ b/agency-indexes/SSA/National_Instant_Criminal_Background_Check_System.json @@ -0,0 +1,19 @@ +{ + "name": "National Instant Criminal Background Check System", + "repositoryURL": "", + "description": "The purpose of the National Instant Criminal Background Check System (NICS) is to process potential NICS candidates for inclusion to the FBI, prohibiting firearm ownership.\nThis is an Intranet application for CRs to gather information from potential candidates who are identified by EDCS. CRs will then process the candidates who are legally incompetent and provide notification of NICS determinations to the appropriate parties, such as legal guardians, appointed representatives, and representative payees. All candidates found eligible will have identifying information submitted to the FBI.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Criminal", + "Background Check" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Numident_Online_Verification_Utility.json b/agency-indexes/SSA/Numident_Online_Verification_Utility.json new file mode 100644 index 00000000..64f5cb2c --- /dev/null +++ b/agency-indexes/SSA/Numident_Online_Verification_Utility.json @@ -0,0 +1,18 @@ +{ + "name": "Numident Online Verification Utility", + "repositoryURL": "", + "description": "A mainframe application that accesses the NUMIDENT to perform real-time SSN verifications. This program is called by other SSA online programs that serve as interfaces to end-users.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Official_Union_Time_Tracking_System.json b/agency-indexes/SSA/Official_Union_Time_Tracking_System.json new file mode 100644 index 00000000..7741ba9a --- /dev/null +++ b/agency-indexes/SSA/Official_Union_Time_Tracking_System.json @@ -0,0 +1,20 @@ +{ + "name": "Official Union Time Tracking System", + "repositoryURL": "", + "description": "OUTTS will collect and load into MTAS the number and type of regular hours, as well as the number and type of credit hours that were worked on official union time for the current pay period or amended union activity for a prior pay period.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Human Resources", + "Time and Attendance", + "Union" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Performance_Assessment_and_Communication_System.json b/agency-indexes/SSA/Performance_Assessment_and_Communication_System.json new file mode 100644 index 00000000..86e4c517 --- /dev/null +++ b/agency-indexes/SSA/Performance_Assessment_and_Communication_System.json @@ -0,0 +1,19 @@ +{ + "name": "Performance Assessment and Communication System", + "repositoryURL": "", + "description": "PACS assists supervisors in preparing employee performance plans, documenting expectations and progress reviews and preparing performance appraisals.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Performance Appraisals", + "Human Resources" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Person_Information.json b/agency-indexes/SSA/Person_Information.json new file mode 100644 index 00000000..c59889c2 --- /dev/null +++ b/agency-indexes/SSA/Person_Information.json @@ -0,0 +1,18 @@ +{ + "name": "Person Information", + "repositoryURL": "", + "description": "The Person Information web application was created to provide a common set of screens to display and collect person data. It is available as an independent application through the Person Information link on iMain. It can also be included in another application's path.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Person" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Prisoner_Tracking_MI.json b/agency-indexes/SSA/Prisoner_Tracking_MI.json new file mode 100644 index 00000000..2e366aca --- /dev/null +++ b/agency-indexes/SSA/Prisoner_Tracking_MI.json @@ -0,0 +1,19 @@ +{ + "name": "Prisoner Tracking MI", + "repositoryURL": "", + "description": "The Prisoner Tracking Management Information (PTMI) provides aggregate and workload data for Title II and Title XVI prisoner transactions processed in SSA field offices (FO's) and Processing Service Centers (PSC's), provides correctional facility names, and correctional facility reporting and incentive payment information.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Management Information", + "Prisoner" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Processing_Center_Action_Control_System.json b/agency-indexes/SSA/Processing_Center_Action_Control_System.json new file mode 100644 index 00000000..b190d608 --- /dev/null +++ b/agency-indexes/SSA/Processing_Center_Action_Control_System.json @@ -0,0 +1,19 @@ +{ + "name": "Processing Center Action Control System", + "repositoryURL": "", + "description": "PCACS provides timely, accurate, and detailed online information regarding the status and location of actions and folders in progress in all processing centers (PCs).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Processing Center" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Quality_Performance_Management_System___DARES.json b/agency-indexes/SSA/Quality_Performance_Management_System___DARES.json new file mode 100644 index 00000000..98e9be0d --- /dev/null +++ b/agency-indexes/SSA/Quality_Performance_Management_System___DARES.json @@ -0,0 +1,19 @@ +{ + "name": "Quality Performance Management System / DARES", + "repositoryURL": "", + "description": "Performance management data extracted from multiple sources is consolidated into the QPMS data warehouse, providing a \"one-stop\" source for generating quality performance measures. The Disability Adjudication Review Evaluation System (DARES) provides a dashboard display of necessary management/decision support and risk information to Office of Disability Adjudication and Review (ODAR) officials, allowing them to effectively monitor and control the hearings backlog reduction initiatives and to determine the health of the overall hearings backlog reduction program at SSA. DARES also serves as the front-end starting point for QPMS DARES, which offers web-based, parameter-driven reports that are based on the breakdown of ODAR workloads within the context of how they relate to key hearing backlog initiatives.\u00c2 ", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Review", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Rep_Payee_System.json b/agency-indexes/SSA/Rep_Payee_System.json new file mode 100644 index 00000000..1f98288d --- /dev/null +++ b/agency-indexes/SSA/Rep_Payee_System.json @@ -0,0 +1,18 @@ +{ + "name": "Rep Payee System", + "repositoryURL": "", + "description": "The Representative Payee System (RPS) is an online system used to store and process current and prior Rep Payee applications (both approved and denied). Data is stored on the Master Rep Payee File (MRPF) as applicants, beneficiaries, or recipients, and the relationship between the Rep Payee and beneficiary. The RPS data is also useful to adjudicators in processing subsequent actions.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Representative Payee" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Returned_Check_Action.json b/agency-indexes/SSA/Returned_Check_Action.json new file mode 100644 index 00000000..d866e65c --- /dev/null +++ b/agency-indexes/SSA/Returned_Check_Action.json @@ -0,0 +1,20 @@ +{ + "name": "Returned Check Action", + "repositoryURL": "", + "description": "The program generates an electronic alert file to the servicing Processing Center (PC) when Title II benefit payments are returned, indicating the beneficiary is deceased. It will automatically send a call-in letter to each beneficiary indicating the stop payment and the reason why.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Death", + "Title II", + "Processing Center" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/SSI_Claims_System_-_Web.json b/agency-indexes/SSA/SSI_Claims_System_-_Web.json new file mode 100644 index 00000000..806a266f --- /dev/null +++ b/agency-indexes/SSA/SSI_Claims_System_-_Web.json @@ -0,0 +1,20 @@ +{ + "name": "SSI Claims System - Web", + "repositoryURL": "", + "description": "Enables SSI claim submissions via a web-based intranet data collection process. It replaces the previous set of CICS MSSICS screens.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Data Collection", + "Claim", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Security_Administration_Reports_Application.json b/agency-indexes/SSA/Security_Administration_Reports_Application.json new file mode 100644 index 00000000..065c16bc --- /dev/null +++ b/agency-indexes/SSA/Security_Administration_Reports_Application.json @@ -0,0 +1,20 @@ +{ + "name": "Security Administration Reports Application", + "repositoryURL": "", + "description": "SARA is the automated solution to an existing manual review\nprocess, and it will provide the ability to capture trending data to\nassist in management decisions. Yes, The Security Administration Reports\nApplication SARA will allow Information Security Officers ISOs,\nAlternate Information Security Officers ALT ISOs and Management Designee\nMD to access, review and take appropriate action on Security\nAdministration Reports.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reporting", + "Management Information", + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Security_Oversight_Command_&_Control_System.json b/agency-indexes/SSA/Security_Oversight_Command_&_Control_System.json new file mode 100644 index 00000000..5cd0cd88 --- /dev/null +++ b/agency-indexes/SSA/Security_Oversight_Command_&_Control_System.json @@ -0,0 +1,19 @@ +{ + "name": "Security Oversight Command & Control System", + "repositoryURL": "", + "description": "SOCCS is utilized to coordinate disaster planning, evacuation and security.\n\nSOCCS is used for security oversight and disaster planning for SSA HQ complex, leased buildings and facilities assigned to SSA HQ.\n\nOffice of Security and Emergency Preparedness (OSEP) will capitalize on SOCCS ability to read and receive live data feeds, ensuring the safety of SSA personnel and the public.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Safety", + "Disaster Planning" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Social_Security_Access_to_State_Records_Online.json b/agency-indexes/SSA/Social_Security_Access_to_State_Records_Online.json new file mode 100644 index 00000000..74f705d0 --- /dev/null +++ b/agency-indexes/SSA/Social_Security_Access_to_State_Records_Online.json @@ -0,0 +1,20 @@ +{ + "name": "Social Security Access to State Records Online", + "repositoryURL": "", + "description": "Social Security Access to State Records Online (SASRO) provides authorized SSA employees access to state agency benefit information, in order to correctly process many of its entitlement and post-entitlement actions.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Entitlments", + "Benefits", + "State" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Social_Security_Electronic_Remittance_System.json b/agency-indexes/SSA/Social_Security_Electronic_Remittance_System.json new file mode 100644 index 00000000..987e5fdd --- /dev/null +++ b/agency-indexes/SSA/Social_Security_Electronic_Remittance_System.json @@ -0,0 +1,18 @@ +{ + "name": "Social Security Electronic Remittance System", + "repositoryURL": "", + "description": "The Social Security Electronic Remittance System (SERS) collects standard fees for non-program-related requests for information. The system allows field office personnel to quickly process payments and eliminates the need to bundle and send payment requests to the Office of Finance at headquarters.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Fee Collection" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Social_Security_Number_Application_Process.json b/agency-indexes/SSA/Social_Security_Number_Application_Process.json new file mode 100644 index 00000000..7232e672 --- /dev/null +++ b/agency-indexes/SSA/Social_Security_Number_Application_Process.json @@ -0,0 +1,19 @@ +{ + "name": "Social Security Number Application Process", + "repositoryURL": "", + "description": "An Enumeration software application that will perform a cross-reference check of a new SSN.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Application", + "Enumeration" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Social_Security_Number_Verification.json b/agency-indexes/SSA/Social_Security_Number_Verification.json new file mode 100644 index 00000000..99de2964 --- /dev/null +++ b/agency-indexes/SSA/Social_Security_Number_Verification.json @@ -0,0 +1,19 @@ +{ + "name": "Social Security Number Verification", + "repositoryURL": "", + "description": "An application within Business Services Online (BSO). SSNVS allows registered users to verify names and SSNs of their employees against SSA's master files via the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Internet", + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Social_Security_Number_Verification_-_BSO.json b/agency-indexes/SSA/Social_Security_Number_Verification_-_BSO.json new file mode 100644 index 00000000..4c6c5676 --- /dev/null +++ b/agency-indexes/SSA/Social_Security_Number_Verification_-_BSO.json @@ -0,0 +1,19 @@ +{ + "name": "Social Security Number Verification - BSO", + "repositoryURL": "", + "description": "Allows employers to verify name/SSNs for wage reporting purposes.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Identity", + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Social_Security_Online_Accounting_and_Reporting_System_-_MF_Batch.json b/agency-indexes/SSA/Social_Security_Online_Accounting_and_Reporting_System_-_MF_Batch.json new file mode 100644 index 00000000..87cd8d7e --- /dev/null +++ b/agency-indexes/SSA/Social_Security_Online_Accounting_and_Reporting_System_-_MF_Batch.json @@ -0,0 +1,19 @@ +{ + "name": "Social Security Online Accounting and Reporting System - MF Batch", + "repositoryURL": "", + "description": "SSOARS is SSA's centralized accounting system for recording, classifying and summarizing information on SSA's financial position and operation. It maintains a variety of financial information including, but not limited to, funding data, commitments, obligations, receivables, and payables.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reporting", + "Accounting" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/StaRZ_&_Stripes_-_The_Next_Generation.json b/agency-indexes/SSA/StaRZ_&_Stripes_-_The_Next_Generation.json new file mode 100644 index 00000000..550f6b50 --- /dev/null +++ b/agency-indexes/SSA/StaRZ_&_Stripes_-_The_Next_Generation.json @@ -0,0 +1,18 @@ +{ + "name": "StaRZ & Stripes - The Next Generation", + "repositoryURL": "", + "description": "StarRZ and Stripes the Next Generation (SSTNG) provides the full range of detailed workload monitoring, management reports and listings used by Claims Reps, Operation Supervisors and FO Managers to identify, track and successfully complete their annual Redetermination/Limited (RZ/LI) workloads.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Target_Notice_Architecture_-_Mainframe.json b/agency-indexes/SSA/Target_Notice_Architecture_-_Mainframe.json new file mode 100644 index 00000000..c97fffa4 --- /dev/null +++ b/agency-indexes/SSA/Target_Notice_Architecture_-_Mainframe.json @@ -0,0 +1,19 @@ +{ + "name": "Target Notice Architecture - Mainframe", + "repositoryURL": "", + "description": "TNA is the agency's standard for the systems development of 508-compliant notice language.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "508", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Third_Party_Payment_System.json b/agency-indexes/SSA/Third_Party_Payment_System.json new file mode 100644 index 00000000..e3d911cd --- /dev/null +++ b/agency-indexes/SSA/Third_Party_Payment_System.json @@ -0,0 +1,20 @@ +{ + "name": "Third Party Payment System", + "repositoryURL": "", + "description": "The Third Party Payment System (TPPS) is a register of paper checks that are known as Third Party Drafts. These drafts are issued to vendors for goods and services, to SSA employees for reimbursement of payments and to beneficiaries for Programmatic Immediate Payments (IPs) and Emergency Advance Payments (EAPs). TPPS enforces payment limits, maintains office draft stock, records and validates accounting data, and generates daily activity and monthly accountability reports.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reimbursements", + "Third Party", + "Payment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/UEF_Core.json b/agency-indexes/SSA/UEF_Core.json new file mode 100644 index 00000000..4dcae5e4 --- /dev/null +++ b/agency-indexes/SSA/UEF_Core.json @@ -0,0 +1,18 @@ +{ + "name": "UEF Core", + "repositoryURL": "", + "description": "UEF patterns", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "uef, inputs, web, containers, buttons, notices, links, design, page, standard, 508 compliance" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/UEF_Website.json b/agency-indexes/SSA/UEF_Website.json new file mode 100644 index 00000000..ccefbfb7 --- /dev/null +++ b/agency-indexes/SSA/UEF_Website.json @@ -0,0 +1,20 @@ +{ + "name": "UEF Website", + "repositoryURL": "", + "description": "Standards Website for the User Experience Framework", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "UEF", + "Standards", + "User Experience Framework" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/UniForms.json b/agency-indexes/SSA/UniForms.json new file mode 100644 index 00000000..5e747884 --- /dev/null +++ b/agency-indexes/SSA/UniForms.json @@ -0,0 +1,19 @@ +{ + "name": "UniForms", + "repositoryURL": "", + "description": "UniForms is a replacement for eForms, allowing Agency-wide retrieval of administrative forms.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Forms" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/VIEWS_-_Agreement_Workflow_Tool.json b/agency-indexes/SSA/VIEWS_-_Agreement_Workflow_Tool.json new file mode 100644 index 00000000..d434cc65 --- /dev/null +++ b/agency-indexes/SSA/VIEWS_-_Agreement_Workflow_Tool.json @@ -0,0 +1,19 @@ +{ + "name": "VIEWS - Agreement Workflow Tool", + "repositoryURL": "", + "description": "AWT is a workflow tool and repository for the reimbursable agreement documents. The agreement process begins in AWT, which allows related documentation to be circulated electronically for approval and signature.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Agreements", + "Workflow Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/VIEWS_-_Data_Exchange_Inventory.json b/agency-indexes/SSA/VIEWS_-_Data_Exchange_Inventory.json new file mode 100644 index 00000000..8b36abe1 --- /dev/null +++ b/agency-indexes/SSA/VIEWS_-_Data_Exchange_Inventory.json @@ -0,0 +1,18 @@ +{ + "name": "VIEWS - Data Exchange Inventory", + "repositoryURL": "", + "description": "DEXI is an inventory database that contains information about data exchanges between SSA and various partners. It interfaces with external applications to retrieve project code data, financial accounting data, management information data, and electronic reimbursable agreement documentation, and can be queried in various ways.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Data Exchange" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Verifications_Account_Management_System.json b/agency-indexes/SSA/Verifications_Account_Management_System.json new file mode 100644 index 00000000..34cafa96 --- /dev/null +++ b/agency-indexes/SSA/Verifications_Account_Management_System.json @@ -0,0 +1,18 @@ +{ + "name": "Verifications Account Management System", + "repositoryURL": "", + "description": "Verification Account Management System (VAMS) is a centralized location for maintaining Enumeration Verification Systems (EVS) accounts. VAMS allows users to create new accounts, search for existing accounts, update current accounts, and generate MI count reports. DEVO interfaces with VAMS to perform the administrative functions of registration, access control and tracking, and to manage assignment of the functional processes.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Account Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Visitor_Intake_Process_-_Rewrite.json b/agency-indexes/SSA/Visitor_Intake_Process_-_Rewrite.json new file mode 100644 index 00000000..098b3d3b --- /dev/null +++ b/agency-indexes/SSA/Visitor_Intake_Process_-_Rewrite.json @@ -0,0 +1,19 @@ +{ + "name": "Visitor Intake Process - Rewrite", + "repositoryURL": "", + "description": "Manages appointments and walk-ins for Field Office (FO) and assigns them to the FO staff in an effective way to minimize the wait time of the users.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Scheduling", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Volume_Death.json b/agency-indexes/SSA/Volume_Death.json new file mode 100644 index 00000000..8641dcdd --- /dev/null +++ b/agency-indexes/SSA/Volume_Death.json @@ -0,0 +1,18 @@ +{ + "name": "Volume Death", + "repositoryURL": "", + "description": "Updates the SSA Death Master File.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Death" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/WMI_for_IC_and_Appeals.json b/agency-indexes/SSA/WMI_for_IC_and_Appeals.json new file mode 100644 index 00000000..b4f4d357 --- /dev/null +++ b/agency-indexes/SSA/WMI_for_IC_and_Appeals.json @@ -0,0 +1,19 @@ +{ + "name": "WMI for IC and Appeals", + "repositoryURL": "", + "description": "Legacy Workload Management Information (WMI) for IC and appeals batch programs and CICS screens.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Appeals", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Work_Experience_Reporting_System.json b/agency-indexes/SSA/Work_Experience_Reporting_System.json new file mode 100644 index 00000000..4b372a3f --- /dev/null +++ b/agency-indexes/SSA/Work_Experience_Reporting_System.json @@ -0,0 +1,19 @@ +{ + "name": "Work Experience Reporting System", + "repositoryURL": "", + "description": "WERS is an MI system that captures and reports workload volumes and the hours needed to process items in each workload category. Weekly, monthly, quarterly, and yearly reports are produced for the Office of Budget, Finance and Management (OBFM).", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Reporting" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Work_History_Assistant_Tool.json b/agency-indexes/SSA/Work_History_Assistant_Tool.json new file mode 100644 index 00000000..7d9799fe --- /dev/null +++ b/agency-indexes/SSA/Work_History_Assistant_Tool.json @@ -0,0 +1,18 @@ +{ + "name": "Work History Assistant Tool", + "repositoryURL": "", + "description": "A web-based application, available on a need-to-know basis, that retrieves Detail Earnings Query (DEQY) data and makes it easier to interpret.wh", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Employment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/Workload_Action_Center.json b/agency-indexes/SSA/Workload_Action_Center.json new file mode 100644 index 00000000..27d676fe --- /dev/null +++ b/agency-indexes/SSA/Workload_Action_Center.json @@ -0,0 +1,19 @@ +{ + "name": "Workload Action Center", + "repositoryURL": "", + "description": "The Workload Action Center (WAC) allows users to view, analyze, and work initial claims and appeals pending lists, as well as mainframe tickle lists. It consumes Programmatic Workload data to provide information to the 1,394 field offices to assist SSA employees in adjudicating initial disability claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Disability", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/YANKI.json b/agency-indexes/SSA/YANKI.json new file mode 100644 index 00000000..57d9d0b6 --- /dev/null +++ b/agency-indexes/SSA/YANKI.json @@ -0,0 +1,28 @@ +{ + "name": "YANKI", + "repositoryURL": "https://github.com/SSAgov/YANKI", + "description": "When certain attributes are used improperly, they can cause issues with screen readers. YANKI can be used to 'yank' the attributes and allow a retest of the page with the attributes removed.", + "permissions": { + "licenses": [ + { + "URL": "www.apache.org/licenses/LICENSE-2.0", + "name": "Apache" + } + ], + "usageType": "openSource", + "exemptionText": "" + }, + "laborHours": 456, + "tags": [ + "YANKI", + "attribute", + "WAI-ARIA", + "favelet", + "tabindex", + "javascript" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/codeMetadata.json_Generator.json b/agency-indexes/SSA/codeMetadata.json_Generator.json new file mode 100644 index 00000000..f45a559d --- /dev/null +++ b/agency-indexes/SSA/codeMetadata.json_Generator.json @@ -0,0 +1,21 @@ +{ + "name": "codeMetadata.json Generator", + "repositoryURL": "", + "description": "A single page application for generating a codeMetadata.json file. The codeMetadata.json file contains basic data about a code asset such as it's name, description, languages, and the like.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "node.js", + "REACT", + "SPA", + "Single Page Application" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/data.JSON_URL_Checker.json b/agency-indexes/SSA/data.JSON_URL_Checker.json new file mode 100644 index 00000000..89998693 --- /dev/null +++ b/agency-indexes/SSA/data.JSON_URL_Checker.json @@ -0,0 +1,27 @@ +{ + "name": "data.JSON URL Checker", + "repositoryURL": "https://github.com/SSAgov/data.json-url-checker", + "description": "For federal government agencies required to deliver data.JSON file, this scripts helps agencies test URLs and make sure that they are valid that are present in their data.JSON files before publishing.", + "permissions": { + "licenses": [ + { + "URL": "www.apache.org/licenses/LICENSE-2.0", + "name": "Apache" + } + ], + "usageType": "openSource", + "exemptionText": "" + }, + "laborHours": 426, + "tags": [ + "JSON", + "Java Script Object Notation", + "URL", + "Uniform Resource Locator", + "JSON Validator" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } +} \ No newline at end of file diff --git a/agency-indexes/SSA/eTravel.json b/agency-indexes/SSA/eTravel.json new file mode 100644 index 00000000..3384ca09 --- /dev/null +++ b/agency-indexes/SSA/eTravel.json @@ -0,0 +1,18 @@ +{ + "name": "eTravel", + "repositoryURL": "", + "description": "An on-demand/full travel service providing capabilities to make travel reservations and create, route and approve travel documents. 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Information forthcoming.", + "vcs": "git", + "laborHours": 1, + "tags": [ + "WIIW", + "Production", + "governmentWideReuse" + ], + "languages": [ + "Cache", + "Massachusetts General Hospital Utility Multi-Programming System (MUMPS)", + "VMware vSphere" + ], + "contact": { + "name": "DSO Code Sharing Services", + "email": "OSSOFT@va.gov", + "URL": "https://www.va.gov", + "phone": "844-698-2311" + }, + "date": { + "created": "2020-04-28", + "lastModified": "2021-01-26", + "metadataLastUpdated": "2021-01-26" + }, + "description": "Repository containing the FOIA Releases for VistA - Wounded Injured Ill Warriors" +} \ No newline at end of file diff --git a/agency-indexes/VA/VistA_Integration_Adapter.json b/agency-indexes/VA/VistA_Integration_Adapter.json new file mode 100644 index 00000000..a709f7e1 --- /dev/null +++ b/agency-indexes/VA/VistA_Integration_Adapter.json @@ -0,0 +1,48 @@ +{ + "id": 2025, + "name": "VistA Integration Adapter", + "organization": "OIT DSO", + "version": null, + "status": "Production", + "permissions": { + "usageType": "governmentWideReuse", + "licenses": [ + { + "name": "", + "opRL": "" + } + ] + }, + "homepageURL": "https://github.com/department-of-veterans-affairs", + "downloadURL": "https://github.com/department-of-veterans-affairs", + "repositoryURL": "https://github.com/department-of-veterans-affairs/foia-viab-vista-integration-adaptor", + "disclaimerText": "License information not currently available. Information forthcoming.", + "vcs": "git", + "laborHours": 1, + "tags": [ + "VIA", + "Production", + "governmentWideReuse" + ], + "languages": [ + "ASP.NET Core", + "Red Hat Enterprise Linux", + "Microsoft .NET Framework", + "Oracle Database", + "WebLogic Server", + "Java Enterprise Edition (Java EE)", + "Java Runtime Environment (JRE) - Oracle" + ], + "contact": { + "name": "DSO Code Sharing Services", + "email": "OSSOFT@va.gov", + "URL": "https://www.va.gov", + "phone": "844-698-2311" + }, + "date": { + "created": "2020-04-28", + "lastModified": "2021-01-26", + "metadataLastUpdated": "2021-01-26" + }, + "description": "Repository containing the FOIA Releases for VistA Integration Adapter" +} \ No newline at end of file diff --git a/agency-indexes/VA/VistA_Services_Assembler_[INACTIVE].json b/agency-indexes/VA/VistA_Services_Assembler_[INACTIVE].json new file mode 100644 index 00000000..4fd2407f --- /dev/null +++ b/agency-indexes/VA/VistA_Services_Assembler_[INACTIVE].json @@ -0,0 +1,46 @@ +{ + "id": 2095, + "name": "VistA Services Assembler [INACTIVE]", + "organization": "OIT DSO", + "version": null, + "status": "Archival", + "permissions": { + "usageType": "governmentWideReuse", + "licenses": [ + { + "name": "", + "opRL": "" + } + ] + }, + "homepageURL": "https://github.com/department-of-veterans-affairs", + "downloadURL": "https://github.com/department-of-veterans-affairs", + "repositoryURL": "https://github.com/department-of-veterans-affairs/Redacted-Public-Release-VSA-P2.5-v3.0.12-Jan-2017", + "disclaimerText": "License information not currently available. Information forthcoming.", + "vcs": "git", + "laborHours": 1, + "tags": [ + "VSA", + "Archival", + "governmentWideReuse" + ], + "languages": [ + "Cache", + "Windows Server", + "Red Hat Enterprise Linux", + "WebLogic Server", + "Enterprise Web Developer (EWD).js" + ], + "contact": { + "name": "DSO Code Sharing Services", + "email": "OSSOFT@va.gov", + "URL": "https://www.va.gov", + "phone": "844-698-2311" + }, + "date": { + "created": "2020-04-28", + "lastModified": "2020-08-20", + "metadataLastUpdated": "2020-08-20" + }, + "description": "Repository containing the CIF submission for VistA Services Assembler Phase 2.5, v3.0.12 rec Jan 2017." +} \ No newline at end of file diff --git a/agency-indexes/VA/Voluntary_Service_System.json b/agency-indexes/VA/Voluntary_Service_System.json new file mode 100644 index 00000000..2e4b5242 --- /dev/null +++ b/agency-indexes/VA/Voluntary_Service_System.json @@ -0,0 +1,44 @@ +{ + "id": 1483, + "name": "Voluntary Service System", + "organization": "OIT DSO", + "version": null, + "status": "Production", + "permissions": { + "usageType": "governmentWideReuse", + "licenses": [ + { + "name": "", + "opRL": "" + } + ] + }, + "homepageURL": "https://github.com/department-of-veterans-affairs", + "downloadURL": "https://github.com/department-of-veterans-affairs", + "repositoryURL": "https://github.com/department-of-veterans-affairs/foia-vss-voluntary-timekeeping-service", + "disclaimerText": "License information not currently available. Information forthcoming.", + "vcs": "git", + "laborHours": 1, + "tags": [ + "VSS", + "Production", + "governmentWideReuse" + ], + "languages": [ + "Microsoft Structured Query Language (SQL) Server", + "Windows Server", + "Microsoft .NET Framework" + ], + "contact": { + "name": "DSO Code Sharing Services", + "email": "OSSOFT@va.gov", + "URL": "https://www.va.gov", + "phone": "844-698-2311" + }, + "date": { + "created": "2020-04-28", + "lastModified": "2021-01-26", + "metadataLastUpdated": "2021-01-26" + }, + "description": "Repository containing the FOIA Releases for Voluntary Service System" +} \ No newline at end of file diff --git a/agency-indexes/VA/Web_VistA_Remote_Access_Management.json b/agency-indexes/VA/Web_VistA_Remote_Access_Management.json new file mode 100644 index 00000000..08b2159d --- /dev/null +++ b/agency-indexes/VA/Web_VistA_Remote_Access_Management.json @@ -0,0 +1,43 @@ +{ + "id": 2298, + "name": "Web VistA Remote Access Management", + "organization": "OIT DSO", + "version": "1.3", + "status": "Production", + "permissions": { + "usageType": "governmentWideReuse", + "licenses": [ + { + "name": "", + "opRL": "" + } + ] + }, + "homepageURL": "https://github.com/department-of-veterans-affairs", + "downloadURL": "https://github.com/department-of-veterans-affairs", + "repositoryURL": "https://github.com/department-of-veterans-affairs/Redacted-Public-Release-WebVRAM-v1.3-build-7-Sep-2020", + "disclaimerText": "License information not currently available. Information forthcoming.", + "vcs": "git", + "laborHours": 1, + "tags": [ + "WebVRam", + "Production", + "governmentWideReuse" + ], + "languages": [ + "Windows Server", + "Microsoft .NET Framework" + ], + "contact": { + "name": "DSO Code Sharing Services", + "email": "OSSOFT@va.gov", + "URL": "https://www.va.gov", + "phone": "844-698-2311" + }, + "date": { + "created": "2020-07-27", + "lastModified": "2020-12-03", + "metadataLastUpdated": "2020-12-03" + }, + "description": "Repository containing the CIF submission for A Telehealth Hub Initiative and Interfacility Access - WebVRAM, v1.3, build 7 rec Sep 2020." +} \ No newline at end of file diff --git a/scripts/pull-legacy-assets.py b/scripts/pull-legacy-assets.py new file mode 100644 index 00000000..61738525 --- /dev/null +++ b/scripts/pull-legacy-assets.py @@ -0,0 +1,126 @@ +import requests +import json +import os + +# the commented out links are not valid or cant be found +agencies_links = { + "DoA": "https://usda.gov/code.json", + # "Department of Commerce": "https://www.commerce.gov/code.json", + "DoD": "https://www.code.mil/code.json", + # "Department of Education": "https://ed.gov/code.json", + "DoE": "https://www.energy.gov/code.json", + "HHS": "https://www.hhs.gov/code.json", + # "Department of Housing and Urban Development": "https://www.hud.gov/code.json", + "DHS": "https://www.dhs.gov/code.json", + # "Department of Justice": "https://www.justice.gov/d9/code.json", + # "Department of Labor": "https://www.dol.gov/code.json", + # "Department of Transportation": "https://www.transportation.gov/code.json", + "DoT": "https://www.treasury.gov/code.json", + "VA": "https://www.va.gov/code.json", + "EPA": "https://www.epa.gov/code.json", + # "National Aeronautics and Space Administration": "https://code.nasa.gov/code.json", + # "Agency for International Development": "https://www.usaid.gov/code.json", + # "General Services Administration": "https://www.gsa.gov/code.json", + "NSF": "https://www.nsf.gov/code.json", + # "Office of Personnel Management": "https://www.opm.gov/code.json", + # "Small Business Administration": "https://www.sba.gov/code.json", + "SSA": "https://www.ssa.gov/code.json", + "FEC": "https://www.fec.gov/code.json" +} + +headers = { + 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36', + 'Accept': 'application/json, text/plain, */*', +} + +def add_directories_to_directory(data, agency_name): + directory_name = f"../agency-indexes/{agency_name}" + + try: + if not os.path.exists(directory_name): + os.mkdir(directory_name) + else: + print("Directory already exists!") + except Exception as e: + print(f"Failed to create directory for {agency_name}: {e}") + + try: + for item in data: + safe_name = item['name'].replace('/', '_').replace('(', '_').replace(')', '_').replace(' ', '_') + file_path = os.path.join(directory_name, f"{safe_name}.json") + + with open(file_path, 'w', encoding='utf-8') as file: + json.dump(item, file, indent = 4) + except Exception as e: + print(f"Failed to add files to {agency_name} directory: {e}") + +def add_indexes_to_directory(data, agency_name): + file_name = f"../agency-indexes/{agency_name}-index.json" + + if os.path.exists(file_name): + try: + with open(file_name, 'r', encoding='utf-8') as file: + existing_data = json.load(file) + + existing_releases = existing_data.get('releases', []) + new_releases = data.get('releases', []) + + existing_repos = set() + unique_new_releases = [] + + for release in existing_releases: + repo_url = release.get('repositoryURL') + if repo_url: + existing_repos.add(repo_url) + + for release in new_releases: + repo_url = release.get('repositoryURL') + if repo_url not in existing_repos: + unique_new_releases.append(release) + + merged_releases = existing_releases + unique_new_releases + data['releases'] = merged_releases + + except Exception as e: + print(f"Failed to read existing file: {e}") + + try: + with open(file_name, 'w', encoding='utf-8') as file: + json.dump(data, file, indent = 4) + except Exception as e: + print(f"Failed to save JSON file: {e}") + +def main(): + try: + for agency, link in agencies_links.items(): + response = requests.get(link, headers = headers) + + # print(agency) + # print(f"Status code: {response.status_code}") + + if response.status_code == 200: + # print("Data received:", len(response.text)) + data = response.json() + + add_indexes_to_directory(data, agency) + add_directories_to_directory(data["releases"], agency) + else: + print("Error message from API:", response.text) + + # print("\n") + + except Exception as e: + print(f"Function failed: {e}") + return + +if __name__ == "__main__": + main() + +# merging logic +# once we have the legacy files pulled, they need to be stored in three places +# 1. the agency-index file as a whole lives in the agency-index directory +# 2. a directory with the agency name that contains all the repos from the agency index +# 3. within the codegov.json where they will be merged all together + + + diff --git a/scripts/web-scraper.py b/scripts/web-scraper.py deleted file mode 100644 index d73374b0..00000000 --- a/scripts/web-scraper.py +++ /dev/null @@ -1,62 +0,0 @@ -import requests -import json - -agencies_links = { - "Department of Agriculture": "https://usda.gov/code.json", - # "Department of Commerce": "https://www.commerce.gov/code.json", - "Department of Defense": "https://www.code.mil/code.json", - # "Department of Education": "https://ed.gov/code.json", - "Department of Energy": "https://www.energy.gov/code.json", - "Department of Health and Human Services": "https://www.hhs.gov/code.json", - # "Department of Housing and Urban Development": "https://www.hud.gov/code.json", - "Department of Homeland Security": "https://www.dhs.gov/code.json", - # "Department of Justice": "https://www.justice.gov/d9/code.json", - # "Department of Labor": "https://www.dol.gov/code.json", - # "Department of Transportation": "https://www.transportation.gov/code.json", - "Department of Treasury": "https://www.treasury.gov/code.json", - "Department of Veterans Affairs": "https://www.va.gov/code.json", - "Environmental Protection Agency": "https://www.epa.gov/code.json", - # "National Aeronautics and Space Administration": "https://code.nasa.gov/code.json", - # "Agency for International Development": "https://www.usaid.gov/code.json", - # "General Services Administration": "https://www.gsa.gov/code.json", - "National Science Foundation": "https://www.nsf.gov/code.json", - # "Office of Personnel Management": "https://www.opm.gov/code.json", - # "Small Business Administration": "https://www.sba.gov/code.json", - "Social Security Administration": "https://www.ssa.gov/code.json", - "Federal Election Commission": "https://www.fec.gov/code.json" -} - -headers = { - 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36', - 'Accept': 'application/json, text/plain, */*', -} - -file_path = "../legacy-codegov.json" -legacy_codegov = {} - -try: - for agency, link in agencies_links.items(): - response = requests.get(link, headers = headers) - - print(agency) - print(f"Status code: {response.status_code}") - - if response.status_code == 200: - print("Data received:", len(response.text)) - data = response.json() - legacy_codegov[agency] = data["releases"] - else: - print("Error message from API:", response.text) - - print("\n") - -except requests.exceptions.RequestException as e: - print(f"Request failed: {e}") - -try: - with open(file_path, 'w', encoding='utf-8') as file: - json.dump(legacy_codegov, file, indent=4, ensure_ascii=False) -except Exception as e: - print(f"Failed to save JSON file: {e}") - -print(legacy_codegov) \ No newline at end of file From 55aad2c5ee19018b2363b962490c8d9db4d1be32 Mon Sep 17 00:00:00 2001 From: Natalia Luzuriaga Date: Thu, 5 Jun 2025 07:26:35 -0700 Subject: [PATCH 06/14] Fixed button urls in home page Signed-off-by: Natalia Luzuriaga --- index.html | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/index.html b/index.html index 940b2d75..aa298ccd 100644 --- a/index.html +++ b/index.html @@ -28,13 +28,13 @@

{{ title }}

Developers

- +

The Code.gov website is developed publicly on GitHub. Learn how to contribute here. Help improve America's Code by exploring projects.

- Explore projects + Explore projects

Connect with Us

@@ -47,7 +47,7 @@

Agency Partners

Federal agency partners use Code.gov to share usable open source code, promote open source projects, and track compliance with federal open source policy.

- Agency Compliance + Agency Compliance
@@ -81,4 +81,4 @@

MISSION

- + \ No newline at end of file From 4ec665a7cec41d68b1697ee20c61ed78afc01da9 Mon Sep 17 00:00:00 2001 From: Isaac Milarsky Date: Thu, 5 Jun 2025 11:52:04 -0500 Subject: [PATCH 07/14] create parent script to call other scripts. Also modulize the code to add a util function for merging the data from differant indexes Signed-off-by: Isaac Milarsky --- agency-indexes/GSA_index.json | 8 - agency-indexes/HHS_index.json | 954 ------------------ scripts/__init__.py | 0 scripts/pull_all_assets.py | 12 + ...legacy-assets.py => pull_legacy_assets.py} | 28 +- ...public-assets.py => pull_public_assets.py} | 9 +- scripts/util.py | 27 + 7 files changed, 52 insertions(+), 986 deletions(-) delete mode 100644 agency-indexes/GSA_index.json delete mode 100644 agency-indexes/HHS_index.json create mode 100644 scripts/__init__.py create mode 100644 scripts/pull_all_assets.py rename scripts/{pull-legacy-assets.py => pull_legacy_assets.py} (80%) rename scripts/{pull-public-assets.py => pull_public_assets.py} (87%) create mode 100644 scripts/util.py diff --git a/agency-indexes/GSA_index.json b/agency-indexes/GSA_index.json deleted file mode 100644 index 0915afc4..00000000 --- a/agency-indexes/GSA_index.json +++ /dev/null @@ -1,8 +0,0 @@ -{ - "agency": "GSA", - "version": "0.0.1", - "measurementType": { - "method": "projects" - }, - "releases": [] -} \ No newline at end of file diff --git a/agency-indexes/HHS_index.json b/agency-indexes/HHS_index.json deleted file mode 100644 index 1768d6c2..00000000 --- a/agency-indexes/HHS_index.json +++ /dev/null @@ -1,954 +0,0 @@ -{ - "agency": "HHS", - "version": "0.0.1", - "measurementType": { - "method": "projects" - }, - "releases": [ - { - "organization": "Centers for Medicare & Medicaid Services", - "name": "automated-codejson-generator", - "description": "Tooling that allows for code.json creation through automation", - "longDescription": "This project provides a GitHub Action that helps federal agencies maintain their code.json files, which are required for compliance with the Federal Source Code Policy. The action automatically calculates and updates various metadata fields including labor hours, programming languages used, repository information, and timestamps. It creates pull requests with these updates, making it easier to keep code.json files accurate and up-to-date.", - "status": "Production", - "permissions": { - "licenses": [ - { - "name": "CC0-1.0", - "URL": "https://creativecommons.org/publicdomain/zero/1.0/" - } - ], - "usageType": "openSource", - "exemptionText": "" - }, - "repositoryURL": "https://github.com/DSACMS/automated-codejson-generator", - "vcs": "git", - "laborHours": 11702, - "platforms": [ - "web", - "linux" - ], - "categories": [ - "developer-tools", - "automation" - ], - "softwareType": "standalone/backend", - "languages": [ - "TypeScript", - "JavaScript" - ], - "maintenance": "internal", - "date": { - "created": "2025-02-07T16:29:38Z", - "lastModified": "2025-02-07T21:44:41Z", - "metaDataLastUpdated": "2025-02-07T21:45:22.738Z" - }, - "tags": [ - "github-action", - "codejson" - ], - "contact": { - "email": "opensource@cms.hhs.gov", - "name": "CMS Open Source Team" - }, - "localisation": false, - "repositoryType": "tools", - "userInput": false, - "fismaLevel": "Low", - "group": "CMS/OA/DSAC", - "subsetInHealthcare": [ - "Operational" - ], - "userType": [ - "Government" - ], - "repositoryHost": "github.com/DSACMS", - "maturityModelTier": 3 - }, - { - "organization": "Centers for Medicare & Medicaid Services", - "name": "beneficiary-fhir-data", - "description": "The BFD Server is an API designed to serve Medicare beneficiaries' demographic, enrollment, and claims data using the HL7\u00ae FHIR\u00ae Standard format.", - "longDescription": "It's the vision of this project to provide a comprehensive, performant, and trustworthy platform to transform the way that the CMS enterprise shares and uses data. This aligns with the overarching mission to enable the CMS Enterprise to drive innovation in data sharing so that beneficiaries and their healthcare partners have the data they need to make informed decisions about their healthcare.", - "status": "Production", - "permissions": { - "licenses": [ - { - "URL": "https://github.com/CMSgov/beneficiary-fhir-data/blob/master/LICENSE.md", - "name": "CC0-1.0" - } - ], - "usageType": "openSource", - "exemptionText": "" - }, - "repositoryURL": "https://github.com/CMSgov/beneficiary-fhir-data", - "repositoryHost": "github.com/CMSgov", - "repositoryVisibility": "public", - "vcs": "git", - "laborHours": 34495, - "reuseFrequency": { - "forks": 33 - }, - "platforms": [ - "windows", - "mac", - "linux" - ], - "categories": [ - "API", - "Server" - ], - "softwareType": "standalone/backend", - "languages": [ - "Java", - "HCL", - "Python", - "Shell", - "PLpgSQL", - "Groovy", - "Rust", - "GLSL", - "Kotlin", - "Jinja", - "Dockerfile", - "Liquid", - "HTML", - "Go", - "Ruby", - "CSS", - "Smarty", - "JavaScript", - "SCSS" - ], - "maintenance": "internal", - "contractNumber": "0", - "date": { - "created": "2019-08-22T18:41:16Z", - "lastModified": "2025-05-06T13:34:00Z", - "metaDataLastUpdated": "2025-05-08T15:31:44.414Z" - }, - "tags": [ - "fhir", - "cms", - "api", - "BFD", - "blue-button", - "medicare", - "beneficiary", - "data" - ], - "contact": { - "email": "opensource@cms.hhs.gov", - "name": "CMS Open Source Program Office" - }, - "feedbackMechanisms": [ - "https://github.com/CMSgov/beneficiary-fhir-data/issues" - ], - "localisation": false, - "repositoryType": "APIs", - "userInput": true, - "fismaLevel": "Moderate", - "group": "CMS/OEDA/DASG", - "projects": [ - "blue-button" - ], - "systems": [], - "upstream": "https://github.com/CMSgov/beneficiary-fhir-data/network/dependencies", - "subsetInHealthcare": [ - "Operational", - "Medicare" - ], - "userType": [ - "Providers", - "Patients", - "Government" - ], - "maturityModelTier": 3 - }, - { - "organization": "Centers for Medicare & Medicaid Services", - "name": "cms-gource", - "description": "Gource.io Visualization of Developer.CMS.gov Open Source repositories", - "longDescription": "This repository contains configuration scripts, log files, and graphic assets used to generate a source code repository visualization using Gource.", - "status": "Production", - "permissions": { - "license": [ - { - "name": "CC0 1.0 Universal", - "URL": "https://github.com/DSACMS/cms-gource/blob/main/LICENSE" - } - ], - "usageType": "openSource", - "exemptionText": "" - }, - "repositoryURL": "https://github.com/DSACMS/cms-gource", - "vcs": "git", - "laborHours": 17736, - "platforms": [ - "web" - ], - "categories": [ - "applicant-tracking", - "data-collection", - "data-visualization" - ], - "softwareType": "standalone/web", - "languages": [ - "python" - ], - "maintenance": "internal", - "date": { - "created": "2023-08-21T15:47:26Z", - "lastModified": "2025-02-12T18:25:06Z", - "metaDataLastUpdated": "2025-02-12T18:27:00.385Z" - }, - "tags": [ - "repository" - ], - "contact": { - "email": "opensource@cms.hhs.gov", - "name": "CMS/OA/DSAC" - }, - "localisation": false, - "repositoryType": "data", - "userInput": false, - "fismaLevel": "low", - "group": "CMS/OA/DSAC", - "subsetInHealthcare": [ - "Operational" - ], - "userType": [ - "government" - ], - "repositoryHost": "github.com/DSACMS", - "maturityModelTier": 3 - }, - { - "organization": "Centers for Medicare & Medicaid Services", - "name": "cms-open-source-policy", - "description": "CMS' Open Source Policy", - "longDescription": "The Centers for Medicare & Medicaid Services (CMS) has been an active supporter of and has utilized the Open Source Software (OSS) on several IT projects for its mission-critical programs. Several CMS business units and offices have been actively releasing OSS as part of IT modernization projects. CMS has many active open source communities, such as our Developer APIs like Bluebutton, our CMS Design System, and hundreds of other repos across our many organizations (https://dsacms.github.io/metrics/organizations/). CMS has embraced Open Source development and is looking forward to releasing software to the community to promote reuse. This policy will help CMS achieve the goals outlined in the OMB directive M-16-21 for Federal agencies.", - "status": "Production", - "permissions": { - "license": [ - { - "name": "CC0 1.0 Universal", - "URL": "https://github.com/DSACMS/cms-open-source-policy/blob/main/LICENSE" - } - ], - "usageType": "governmentWideReuse", - "exemptionText": "" - }, - "repositoryURL": "https://github.com/DSACMS/cms-open-source-policy", - "vcs": "git", - "laborHours": 1381, - "platforms": [ - "web" - ], - "categories": [ - "procurement", - "hr" - ], - "softwareType": "standalone/web", - "languages": [ - "Markdown" - ], - "maintenance": "internal", - "date": { - "created": "2024-09-05T18:22:39Z", - "lastModified": "2025-02-13T20:26:40Z", - "metaDataLastUpdated": "2025-02-13T20:27:21.834Z" - }, - "tags": [ - "Policy", - "OSPO", - "Open Source" - ], - "contact": { - "email": "opensource@cms.hhs.gov", - "name": "CMS Open Source Team" - }, - "localisation": false, - "repositoryType": "standards", - "userInput": false, - "fismaLevel": "Low", - "group": "CMS/OA/DSAC", - "upstream": [ - "https://github.com/CMSgov/cms-open-source-policy" - ], - "subsetInHealthcare": [ - "Policy" - ], - "userType": [ - "Government" - ], - "repositoryHost": "github.com/DSACMS", - "maturityModelTier": 1 - }, - { - "organization": "Centers for Medicare & Medicaid Services", - "name": "codejson-generator", - "description": "Form to generate a CMS code.json", - "longDescription": "A web form where project teams fill out information about their project and creates a completed code.json for local download to add to repositories.", - "status": "Production", - "permissions": { - "license": [ - { - "name": "CC0 1.0 Universal", - "URL": "https://github.com/DSACMS/codejson-generator/blob/main/LICENSE" - } - ], - "usageType": "openSource", - "exemptionText": "" - }, - "repositoryURL": "https://github.com/DSACMS/codejson-generator", - "vcs": "git", - "laborHours": 3347, - "platforms": [ - "web" - ], - "categories": [ - "it-asset-management", - 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It doesn't send the data anywhere.", - "status": "Production", - "permissions": { - "license": [ - { - "name": "CC0 1.0 Universal", - "URL": "https://github.com/DSACMS/form-demo/blob/main/LICENSE" - } - ], - "usageType": "openSource", - "exemptionText": "" - }, - "repositoryURL": "https://github.com/DSACMS/form-demo", - "vcs": "git", - "laborHours": 11466, - "platforms": [ - "web" - ], - "categories": [ - "design-system" - ], - "softwareType": "standalone/web", - "languages": [ - "JavaScript", - "HTML" - ], - "maintenance": "internal", - "date": { - "created": "2024-02-23T19:59:09Z", - "lastModified": "2025-02-13T19:14:34Z", - "metaDataLastUpdated": "2025-02-13T19:15:27.869Z" - }, - "tags": [ - "repository", - "form" - ], - "contact": { - "email": "opensource@cms.hhs.gov", - "name": "CMS/OA/DSAC" - }, - "localisation": false, - "repositoryType": "website", - "userInput": false, - "fismaLevel": "low", - "group": "CMS/OA/DSAC", - "subsetInHealthcare": [ - "operational" - ], - "userType": [ - "government" - ], - "repositoryHost": "github.com/DSACMS", - "maturityModelTier": 1 - }, - { - "organization": "Centers for Medicare & Medicaid Services", - "name": "gource-log", - "description": "GitHub Action to run Gource on the desired repository and store the log for later use.", - "longDescription": "A Custom Built GitHub Action that helps Automate Gource and Gource Log Creation", - "status": "Production", - "permissions": { - "license": [ - { - "name": "CC0 1.0 Universal", - "URL": "https://github.com/DSACMS/gource-log/blob/main/LICENSE" - } - ], - "usageType": "openSource", - "exemptionText": "" - }, - "repositoryURL": "https://github.com/DSACMS/gource-log", - "vcs": "git", - "laborHours": 2621, - "platforms": [ - "web" - ], - "categories": [ - "data-collection", - "data-visualization" - ], - "softwareType": "standalone/web", - "languages": [ - "Python", - "Dockerfile" - ], - "maintenance": "internal", - "date": { - "created": "2024-11-05T15:52:01Z", - "lastModified": "2025-02-13T19:29:35Z", - "metaDataLastUpdated": "2025-02-13T19:31:25.332Z" - }, - "tags": [ - "gource", - "data visualization", - "logs" - ], - "contact": { - "email": "opensource@cms.hhs.gov", - "name": "CMS Open Source Team" - }, - "localisation": false, - "repositoryType": "tools", - "userInput": false, - "fismaLevel": "Low", - "group": "CMS/OA/DSAC", - "subsetInHealthcare": [ - "Operational" - ], - "userType": [ - "Government" - ], - "repositoryHost": "github.com/DSACMS", - "maturityModelTier": 3 - }, - { - "organization": "Centers for Medicare & Medicaid Services", - "name": "gov-codejson", - "description": "code.json: An agency-wide metadata standard for software projects", - "longDescription": "This repository contains documentation on code.json, a metadata standard used to collect information on the agency's software projects in compliance with M-16-21 and the SHARE IT Act.", - "status": "Production", - "permissions": { - "license": [ - { - "name": "CC0 1.0 Universal", - "URL": "https://github.com/DSACMS/gov-codejson/blob/main/LICENSE" - } - ], - "usageType": "openSource", - "exemptionText": "" - }, - "repositoryURL": "https://github.com/DSACMS/gov-codejson", - "vcs": "git", - "laborHours": 3479, - "platforms": [ - "web" - ], - "categories": [ - "knowledge-management", - "help-desk" - ], - "softwareType": "standalone/web", - "languages": [ - "Markdown" - ], - "maintenance": "internal", - "date": { - "created": "2025-02-04T21:59:53Z", - "lastModified": "2025-02-11T18:45:30Z", - "metaDataLastUpdated": "2025-02-11T18:47:02.924Z" - }, - "tags": [ - "guide", - "codejson", - "OSPO", - "metadata", - "SHAREIT", - "M-16-21" - ], - "contact": { - "email": "opensource@cms.hhs.gov", - "name": "CMS Open Source Team" - }, - "localisation": false, - "repositoryType": "standards", - "userInput": false, - "fismaLevel": "Low", - "group": "CMS/OA/DSAC", - "subsetInHealthcare": [ - "Operational" - ], - "userType": [ - "Government" - ], - "repositoryHost": "github.com/DSACMS", - "maturityModelTier": 3 - }, - { - "organization": "Centers for Medicare & Medicaid Services", - "name": "income-reporting-playbook", - "description": "The Income Reporting Playbook will offer guidance and templates to improve the client experience of providing income during benefit applications and renewals. It is currently being developed by Nava in conjunction with USDS and DSAC.", - "longDescription": "This project is being developed by Nava in collaboration with USDS. The Income Reporting Playbook will offer guidance and templates to improve the client experience of providing income during benefit applications and renewals. In this playbook, you\u2019ll find: Recommended best practices, Common terms and plain language definitions, Example language and visual templates for income Following this guidance can improve application form accessibility, equity, and usability.", - "status": "Production", - "permissions": { - "license": [ - { - "name": "CC0 1.0 Universal", - "URL": "https://github.com/DSACMS/income-reporting-playbook/blob/main/LICENSE" - } - ], - "usageType": "openSource", - "exemptionText": "" - }, - "repositoryURL": "https://github.com/DSACMS/income-reporting-playbook", - "vcs": "git", - "laborHours": 2295, - "platforms": [ - "web" - ], - "categories": [ - "resource-management", - "knowledge-management" - ], - "softwareType": "standalone/web", - "languages": [ - "HTML", - "SCSS", - "JavaScript", - "Makefile", - "Ruby" - ], - "maintenance": "internal", - "date": { - "created": "2023-09-29T19:39:30Z", - "lastModified": "2025-02-12T18:57:31Z", - "metaDataLastUpdated": "2025-02-12T18:58:41.245Z" - }, - "tags": [ - "repository", - "playbook" - ], - "contact": { - "email": "opensource@cms.hhs.gov", - "name": "CMS/OA/DSAC" - }, - "localisation": false, - "repositoryType": "website", - "userInput": false, - "fismaLevel": "low", - "group": "CMS/OA/DSAC", - "subsetInHealthcare": [ - "operational" - ], - "userType": [ - "government" - ], - "repositoryHost": "github.com/DSACMS", - "maturityModelTier": 1 - } - ] -} \ No newline at end of file diff --git a/scripts/__init__.py b/scripts/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/scripts/pull_all_assets.py b/scripts/pull_all_assets.py new file mode 100644 index 00000000..6b41b2ff --- /dev/null +++ b/scripts/pull_all_assets.py @@ -0,0 +1,12 @@ +from .pull_legacy_assets import agencies_links, headers, add_directories_to_directory, add_indexes_to_directory +from .pull_legacy_assets import main as legacy_pull_function +from .pull_public_assets import main as public_pull_function + +def main(): + legacy_pull_function() + public_pull_function() + + +if __name__ == "__main__": + main() + \ No newline at end of file diff --git a/scripts/pull-legacy-assets.py b/scripts/pull_legacy_assets.py similarity index 80% rename from scripts/pull-legacy-assets.py rename to scripts/pull_legacy_assets.py index 61738525..879497b8 100644 --- a/scripts/pull-legacy-assets.py +++ b/scripts/pull_legacy_assets.py @@ -1,6 +1,7 @@ import requests import json import os +from .util import merge_indexes # the commented out links are not valid or cant be found agencies_links = { @@ -54,35 +55,16 @@ def add_directories_to_directory(data, agency_name): except Exception as e: print(f"Failed to add files to {agency_name} directory: {e}") + def add_indexes_to_directory(data, agency_name): file_name = f"../agency-indexes/{agency_name}-index.json" if os.path.exists(file_name): try: - with open(file_name, 'r', encoding='utf-8') as file: - existing_data = json.load(file) - - existing_releases = existing_data.get('releases', []) - new_releases = data.get('releases', []) - - existing_repos = set() - unique_new_releases = [] - - for release in existing_releases: - repo_url = release.get('repositoryURL') - if repo_url: - existing_repos.add(repo_url) - - for release in new_releases: - repo_url = release.get('repositoryURL') - if repo_url not in existing_repos: - unique_new_releases.append(release) - - merged_releases = existing_releases + unique_new_releases - data['releases'] = merged_releases - + merge_indexes(data,file_name) except Exception as e: - print(f"Failed to read existing file: {e}") + print("Failed to merge existing file with new data!") + print(e) try: with open(file_name, 'w', encoding='utf-8') as file: diff --git a/scripts/pull-public-assets.py b/scripts/pull_public_assets.py similarity index 87% rename from scripts/pull-public-assets.py rename to scripts/pull_public_assets.py index 4bc97c44..ca5653b4 100644 --- a/scripts/pull-public-assets.py +++ b/scripts/pull_public_assets.py @@ -2,6 +2,7 @@ import os from codejson_index_generator import IndexGenerator +from .util import merge_indexes AGENCY_CODEJSON_DIR = "agency-indexes" VERSION = '0.0.1' @@ -65,7 +66,13 @@ def main(): print(e) - indexGen.save_index(os.path.join(AGENCY_CODEJSON_DIR, agency + "_index.json")) + path_to_save = os.path.join(AGENCY_CODEJSON_DIR, agency + "-index.json") + + #Merge with existing data. + if os.path.exists(path_to_save): + merge_indexes(indexGen.index,path_to_save) + + indexGen.save_index(path_to_save) print(f"\nIndexing complete. Results saved to {AGENCY_CODEJSON_DIR}") except Exception as e: diff --git a/scripts/util.py b/scripts/util.py new file mode 100644 index 00000000..9366e577 --- /dev/null +++ b/scripts/util.py @@ -0,0 +1,27 @@ +def merge_indexes(data,existing_file): + try: + with open(existing_file, 'r', encoding='utf-8') as file: + existing_data = json.load(file) + + existing_releases = existing_data.get('releases', []) + new_releases = data.get('releases', []) + + existing_repos = set() + unique_new_releases = [] + + for release in existing_releases: + repo_url = release.get('repositoryURL') + if repo_url: + existing_repos.add(repo_url) + + for release in new_releases: + repo_url = release.get('repositoryURL') + if repo_url not in existing_repos: + unique_new_releases.append(release) + + merged_releases = existing_releases + unique_new_releases + data['releases'] = merged_releases + + except Exception as e: + print(f"Failed to read existing file: {e}") + raise e \ No newline at end of file From 4b96a149f69d3aeee52a8be16f4dc90b341d7a9c Mon Sep 17 00:00:00 2001 From: Isaac Milarsky Date: Thu, 5 Jun 2025 12:05:55 -0500 Subject: [PATCH 08/14] syntax Signed-off-by: Isaac Milarsky --- .gitignore | 1 + agency-indexes/DoE/CAP.json | 31 + agency-indexes/DoE/Cap.json | 23 +- ...nchronous_VisitOr_Queue_Graph_Toolkit.json | 21 +- ...nchronous_Visitor_Queue_Graph_Toolkit.json | 32 + agency-indexes/DoE/JOBRUNNER.json | 31 + agency-indexes/DoE/JobRunner.json | 24 +- agency-indexes/DoE/Kokkos_Spack.json | 17 +- agency-indexes/DoE/LUNA.json | 25 +- agency-indexes/DoE/Luna.json | 34 + agency-indexes/DoE/Magpie.json | 31 + agency-indexes/DoE/OSCARS.json | 28 +- agency-indexes/DoE/Oscars.json | 33 + agency-indexes/DoE/SystemBurn.json | 14 +- agency-indexes/DoE/Systemburn.json | 30 + agency-indexes/DoE/kokkos_spack.json | 31 + agency-indexes/DoE/magpie.json | 22 +- agency-indexes/GSA-index.json | 8 + agency-indexes/HHS-index.json | 40556 ++++++++-------- agency-indexes/HHS/Artemis.json | 58 +- agency-indexes/HHS/artemis.json | 37 + agency-indexes/SSA-index.json | 2381 + scripts/pull_all_assets.py | 6 +- scripts/pull_legacy_assets.py | 6 +- scripts/pull_public_assets.py | 2 +- scripts/util.py | 2 + 26 files changed, 23078 insertions(+), 20406 deletions(-) create mode 100644 agency-indexes/DoE/CAP.json create mode 100644 agency-indexes/DoE/Highly_Asynchronous_Visitor_Queue_Graph_Toolkit.json create mode 100644 agency-indexes/DoE/JOBRUNNER.json create mode 100644 agency-indexes/DoE/Luna.json create mode 100644 agency-indexes/DoE/Magpie.json create mode 100644 agency-indexes/DoE/Oscars.json create mode 100644 agency-indexes/DoE/Systemburn.json create mode 100644 agency-indexes/DoE/kokkos_spack.json create mode 100644 agency-indexes/GSA-index.json create mode 100644 agency-indexes/HHS/artemis.json diff --git a/.gitignore b/.gitignore index b9c8e8de..a098e67a 100644 --- a/.gitignore +++ b/.gitignore @@ -106,6 +106,7 @@ web_modules/ .env.production.local .env.local .venv/ +__pycache__/ # VSCode files, e.g. launch configuration .vscode diff --git a/agency-indexes/DoE/CAP.json b/agency-indexes/DoE/CAP.json new file mode 100644 index 00000000..f5258324 --- /dev/null +++ b/agency-indexes/DoE/CAP.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "stooksburys@osti.gov" + }, + "date": { + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" + }, + "description": "Identification of core annotation pipeline (CAP). The repository for workflow development to integrate in-house workflows into KBase. These scripts integrate assemblies, abundances, and annotations into a Phyloseq object, specifically genes which are core among multiple metagenomes.", + "laborHours": 136.8, + "languages": [], + "name": "CAP", + "organization": "Office of Scientific and Technical Information (OSTI)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/kbaseattic/cap", + "status": "Development", + "tags": [ + "DOE CODE", + "Office of Scientific and Technical Information (OSTI)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Cap.json b/agency-indexes/DoE/Cap.json index f5258324..365bb72d 100644 --- a/agency-indexes/DoE/Cap.json +++ b/agency-indexes/DoE/Cap.json @@ -1,31 +1,30 @@ { "contact": { - "email": "stooksburys@osti.gov" + "email": "simsdl@ornl.gov" }, "date": { - "created": "2020-09-16", - "metadataLastUpdated": "2020-09-16" + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" }, - "description": "Identification of core annotation pipeline (CAP). The repository for workflow development to integrate in-house workflows into KBase. These scripts integrate assemblies, abundances, and annotations into a Phyloseq object, specifically genes which are core among multiple metagenomes.", - "laborHours": 136.8, - "languages": [], - "name": "CAP", - "organization": "Office of Scientific and Technical Information (OSTI)", + "description": "A library for modeling energy storage devices.\u00a0http://cap.readthedocs.org\n", + "laborHours": 6232.0, + "name": "Cap", + "organization": "Oak Ridge National Laboratory (ORNL)", "permissions": { "exemptionText": null, "licenses": [ { - "URL": "https://api.github.com/licenses/mit", - "name": "MIT" + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" } ], "usageType": "openSource" }, - "repositoryURL": "https://github.com/kbaseattic/cap", + "repositoryURL": "https://github.com/ORNL-CEES/Cap", "status": "Development", "tags": [ "DOE CODE", - "Office of Scientific and Technical Information (OSTI)" + "Oak Ridge National Laboratory (ORNL)" ], "vcs": "git" } \ No newline at end of file diff --git a/agency-indexes/DoE/Highly_Asynchronous_VisitOr_Queue_Graph_Toolkit.json b/agency-indexes/DoE/Highly_Asynchronous_VisitOr_Queue_Graph_Toolkit.json index f70943e8..6700a650 100644 --- a/agency-indexes/DoE/Highly_Asynchronous_VisitOr_Queue_Graph_Toolkit.json +++ b/agency-indexes/DoE/Highly_Asynchronous_VisitOr_Queue_Graph_Toolkit.json @@ -1,32 +1,29 @@ { "contact": { - "email": "bledsoe2@llnl.gov" + "email": "holdensanchez2@llnl.gov" }, "date": { - "created": "2020-12-16", - "metadataLastUpdated": "2020-12-16" + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" }, - "description": "HavoqGT (Highly Asynchronous Visitor Queue Graph Toolkit) is a framework for expressing\nasynchronous vertex-centric graph algorithms, and executing them on High Performance Computing (HPC) systems. It provides a vertex 'visitor' interface, where actions are defined at an individual vertex level, and contains a suite of classic graph algorithms. HavoqGT is capable of processing large graphs stored in NVRAM (SSDs) using a memory mapped interface.\n", + "description": "HAVOQGT is a C++ framework that can be used to create highly parallel graph traversal algorithms. The framework stores the graph and algorithmic data structures on external memory that is typically mapped to high performance locally attached NAND FLASH arrays. The framework supports a vertex-centered visitor programming model. The frameworkd has been used to implement breadth first search, connected components, and single source shortest path.", "laborHours": 15139.2, - "languages": [], - "name": "Highly Asynchronous Visitor Queue Graph Toolkit", + "name": "Highly Asynchronous VisitOr Queue Graph Toolkit", "organization": "Lawrence Livermore National Laboratory (LLNL)", "permissions": { "exemptionText": null, "licenses": [ { - "URL": "https://api.github.com/licenses/mit", - "name": "MIT" + "URL": "https://api.github.com/licenses/lgpl-2.1", + "name": "LGPL-2.1" } ], "usageType": "openSource" }, - "repositoryURL": "https://github.com/LLNL/havoqgt", + "repositoryURL": "https://bitbucket.org/PerMA/havoqgt", "status": "Production", "tags": [ "DOE CODE", "Lawrence Livermore National Laboratory (LLNL)" - ], - "vcs": "git", - "version": "0.2" + ] } \ No newline at end of file diff --git a/agency-indexes/DoE/Highly_Asynchronous_Visitor_Queue_Graph_Toolkit.json b/agency-indexes/DoE/Highly_Asynchronous_Visitor_Queue_Graph_Toolkit.json new file mode 100644 index 00000000..f70943e8 --- /dev/null +++ b/agency-indexes/DoE/Highly_Asynchronous_Visitor_Queue_Graph_Toolkit.json @@ -0,0 +1,32 @@ +{ + "contact": { + "email": "bledsoe2@llnl.gov" + }, + "date": { + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" + }, + "description": "HavoqGT (Highly Asynchronous Visitor Queue Graph Toolkit) is a framework for expressing\nasynchronous vertex-centric graph algorithms, and executing them on High Performance Computing (HPC) systems. It provides a vertex 'visitor' interface, where actions are defined at an individual vertex level, and contains a suite of classic graph algorithms. HavoqGT is capable of processing large graphs stored in NVRAM (SSDs) using a memory mapped interface.\n", + "laborHours": 15139.2, + "languages": [], + "name": "Highly Asynchronous Visitor Queue Graph Toolkit", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/havoqgt", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git", + "version": "0.2" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JOBRUNNER.json b/agency-indexes/DoE/JOBRUNNER.json new file mode 100644 index 00000000..7195850e --- /dev/null +++ b/agency-indexes/DoE/JOBRUNNER.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "dkrakowski@anl.gov" + }, + "date": { + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-21" + }, + "description": "SF-23-071\nJobrunner is a command line tool to manage and deploy computing jobs, organize complex workloads, and enforce a\ndirectory based hierarchy to enable reuse of files and bash scripts within a project. Organization details of a directory\ntree are encoded in Jobfiles which serve as an index of files/scripts, and indicate their purpose when deploying or\nsetting up a job. It is a flexible tool that allows users to design 16 their own directory structure, perserve their design,\nand maintain 17 consistency with increase in complexity of the project.\n", + "laborHours": 0.0, + "languages": [], + "name": "JOBRUNNER", + "organization": "Argonne National Laboratory (ANL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/akashdhruv/Jobrunner", + "status": "Production", + "tags": [ + "DOE CODE", + "Argonne National Laboratory (ANL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/JobRunner.json b/agency-indexes/DoE/JobRunner.json index 7195850e..66b635a3 100644 --- a/agency-indexes/DoE/JobRunner.json +++ b/agency-indexes/DoE/JobRunner.json @@ -1,31 +1,31 @@ { "contact": { - "email": "dkrakowski@anl.gov" + "email": "stooksburys@osti.gov" }, "date": { - "created": "2023-08-18", - "metadataLastUpdated": "2023-08-21" + "created": "2020-07-30", + "metadataLastUpdated": "2020-07-31" }, - "description": "SF-23-071\nJobrunner is a command line tool to manage and deploy computing jobs, organize complex workloads, and enforce a\ndirectory based hierarchy to enable reuse of files and bash scripts within a project. Organization details of a directory\ntree are encoded in Jobfiles which serve as an index of files/scripts, and indicate their purpose when deploying or\nsetting up a job. It is a flexible tool that allows users to design 16 their own directory structure, perserve their design,\nand maintain 17 consistency with increase in complexity of the project.\n", - "laborHours": 0.0, + "description": "The job runner is started by the batch/resource manager system and is the component that actually executes the SDK module. It also provides the callback handler and pushes logs to the execution engine logging system.", + "laborHours": 2036.8, "languages": [], - "name": "JOBRUNNER", - "organization": "Argonne National Laboratory (ANL)", + "name": "JobRunner", + "organization": "Office of Scientific and Technical Information (OSTI)", "permissions": { "exemptionText": null, "licenses": [ { - "URL": "https://api.github.com/licenses/apache-2.0", - "name": "Apache-2.0" + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" } ], "usageType": "openSource" }, - "repositoryURL": "https://github.com/akashdhruv/Jobrunner", - "status": "Production", + "repositoryURL": "https://github.com/kbase/JobRunner", + "status": "Development", "tags": [ "DOE CODE", - "Argonne National Laboratory (ANL)" + "Office of Scientific and Technical Information (OSTI)" ], "vcs": "git" } \ No newline at end of file diff --git a/agency-indexes/DoE/Kokkos_Spack.json b/agency-indexes/DoE/Kokkos_Spack.json index ab5640f8..8d6cd2d9 100644 --- a/agency-indexes/DoE/Kokkos_Spack.json +++ b/agency-indexes/DoE/Kokkos_Spack.json @@ -4,28 +4,27 @@ }, "date": { "created": "2020-05-14", - "metadataLastUpdated": "2020-05-14" + "metadataLastUpdated": "2022-07-28" }, - "description": "A flexible package manager that supports multiple versions, configurations, platforms, and compilers.", - "laborHours": 133364.8, + "description": "The most up-to-date location for Spack packages for Kokkos and Kokkos Kernels.", + "laborHours": 0.0, "languages": [], - "name": "kokkos/spack", + "name": "Kokkos Spack", "organization": "Office of Scientific and Technical Information (OSTI)", "permissions": { "exemptionText": null, "licenses": [ { - "URL": "https://github.com/kokkos/spack/blob/develop/COPYRIGHT", - "name": "Other" + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" } ], "usageType": "openSource" }, - "repositoryURL": "https://github.com/kokkos/spack", + "repositoryURL": "https://gitlab.osti.gov/osti-public/kokkos-spack", "status": "Development", "tags": [ "DOE CODE", "Office of Scientific and Technical Information (OSTI)" - ], - "vcs": "git" + ] } \ No newline at end of file diff --git a/agency-indexes/DoE/LUNA.json b/agency-indexes/DoE/LUNA.json index 0c0b5bac..a7605e4f 100644 --- a/agency-indexes/DoE/LUNA.json +++ b/agency-indexes/DoE/LUNA.json @@ -1,19 +1,17 @@ { "contact": { - "email": "copyrightadmin@sandia.gov" + "email": "chan@lanl.gov" }, "date": { - "created": "2022-10-05", - "metadataLastUpdated": "2022-10-05" + "created": "2021-06-17", + "metadataLastUpdated": "2021-06-17" }, - "description": "SAND2021-15051 O\nLuna is an experimental cognitive architecture that seeks to enable continuous learning in an embodied agent. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", - "homepageURL": "https://ip.sandia.gov/contact-form", + "description": "We have developed a mechanistic model of leaf utilization of nitrogen for assimilation (LUNA V1.0) to predict the photosynthetic capacity at the global scale under different environmental conditions. We adopt an optimality hypothesis to nitrogen allocation among light capture, electron transport, carboxylation, and respiration. The LUNA model is able to reasonably capture the measured spatial and temporal patterns of the photosynthetic capacity as it explains ~55% of the global variation in the observed values of maximum carboxylation rate (Vc,max25) and ~65% of the variation in the observed values of maximum electron transport rate (Jmax25).", + "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", "laborHours": 0.0, - "languages": [ - "Python3" - ], - "name": "Luna", - "organization": "Sandia National Laboratories (SNL)", + "languages": [], + "name": "LUNA", + "organization": "Los Alamos National Laboratory (LANL)", "permissions": { "exemptionText": null, "licenses": [ @@ -24,11 +22,10 @@ ], "usageType": "openSource" }, - "repositoryURL": "https://ip.sandia.gov/contact-form", + "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", "status": "Development", "tags": [ "DOE CODE", - "Sandia National Laboratories (SNL)" - ], - "version": "0.1" + "Los Alamos National Laboratory (LANL)" + ] } \ No newline at end of file diff --git a/agency-indexes/DoE/Luna.json b/agency-indexes/DoE/Luna.json new file mode 100644 index 00000000..0c0b5bac --- /dev/null +++ b/agency-indexes/DoE/Luna.json @@ -0,0 +1,34 @@ +{ + "contact": { + "email": "copyrightadmin@sandia.gov" + }, + "date": { + "created": "2022-10-05", + "metadataLastUpdated": "2022-10-05" + }, + "description": "SAND2021-15051 O\nLuna is an experimental cognitive architecture that seeks to enable continuous learning in an embodied agent. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", + "laborHours": 0.0, + "languages": [ + "Python3" + ], + "name": "Luna", + "organization": "Sandia National Laboratories (SNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://ip.sandia.gov/contact-form", + "status": "Development", + "tags": [ + "DOE CODE", + "Sandia National Laboratories (SNL)" + ], + "version": "0.1" +} \ No newline at end of file diff --git a/agency-indexes/DoE/Magpie.json b/agency-indexes/DoE/Magpie.json new file mode 100644 index 00000000..9e2d8976 --- /dev/null +++ b/agency-indexes/DoE/Magpie.json @@ -0,0 +1,31 @@ +{ + "contact": { + "email": "holdensanchez2@llnl.gov" + }, + "date": { + "created": "2018-07-30", + "metadataLastUpdated": "2020-02-05" + }, + "description": "Magpie contains a number of scripts for running Big Data software in HPC environments, including Hadoop and Spark. There is support for Lustre, Slurm, Moab, Torque. and LSF.\n", + "laborHours": 52607.2, + "languages": [], + "name": "Magpie", + "organization": "Lawrence Livermore National Laboratory (LLNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/gpl-2.0", + "name": "GPL-2.0" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://github.com/LLNL/magpie", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Livermore National Laboratory (LLNL)" + ], + "vcs": "git" +} \ No newline at end of file diff --git a/agency-indexes/DoE/OSCARS.json b/agency-indexes/DoE/OSCARS.json index db005819..ca8908ef 100644 --- a/agency-indexes/DoE/OSCARS.json +++ b/agency-indexes/DoE/OSCARS.json @@ -1,33 +1,31 @@ { "contact": { - "email": "jhaemmerle@lbl.gov" + "email": "svince@lbl.gov" }, "date": { - "created": "2021-04-16", - "metadataLastUpdated": "2021-04-20" + "created": "2019-06-20", + "metadataLastUpdated": "2019-06-20" }, - "description": "The ESnet On-Demand Secure Circuits and Advance Reservation System (OSCARS) is a prototype service enabling advance reservation of guaranteed bandwidth secure virtual circuits. OSCARS operates within the Energy Sciences Network (ESnet), and has provisions for interoperation with other network domains. OSCARS utilizes the Web services model and standards to implement communication with the system and between domains, and for authentication, authorization, and auditing (AAA). The management and operation of end-to-end virtual circuits within the network is done at the layer 3 network level. Multi-Protocol Label Switching (MPLS) and the Resource Reservation Protocol (RSVP) are used to create the virtual circuits or Label Switched Paths (LSP's). Quality of Service (QoS) is used to provide bandwidth guarantees.", - "homepageURL": "https://www.es.net/engineering-services/oscars", - "laborHours": 0.0, - "languages": [ - "None" - ], - "name": "Oscars", + "description": "Short for On-demand Secure Circuits and Advance Reservation System, OSCARS is a freely available open-source product. As developed by the Department of Energy\u2019s high-performance science network ESnet, OSCARS was designed by network engineers who specialize in supporting the U.S. national laboratory system and its data-intensive collaborations.", + "laborHours": 127877.6, + "languages": [], + "name": "OSCARS", "organization": "Lawrence Berkeley National Laboratory (LBNL)", "permissions": { "exemptionText": null, "licenses": [ { - "URL": "https://api.github.com/licenses/bsd-3-clause", - "name": "BSD-3-Clause" + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" } ], "usageType": "openSource" }, - "repositoryURL": "https://www.es.net/engineering-services/oscars", - "status": "Production", + "repositoryURL": "https://github.com/esnet/oscars", + "status": "Development", "tags": [ "DOE CODE", "Lawrence Berkeley National Laboratory (LBNL)" - ] + ], + "vcs": "git" } \ No newline at end of file diff --git a/agency-indexes/DoE/Oscars.json b/agency-indexes/DoE/Oscars.json new file mode 100644 index 00000000..db005819 --- /dev/null +++ b/agency-indexes/DoE/Oscars.json @@ -0,0 +1,33 @@ +{ + "contact": { + "email": "jhaemmerle@lbl.gov" + }, + "date": { + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" + }, + "description": "The ESnet On-Demand Secure Circuits and Advance Reservation System (OSCARS) is a prototype service enabling advance reservation of guaranteed bandwidth secure virtual circuits. OSCARS operates within the Energy Sciences Network (ESnet), and has provisions for interoperation with other network domains. OSCARS utilizes the Web services model and standards to implement communication with the system and between domains, and for authentication, authorization, and auditing (AAA). The management and operation of end-to-end virtual circuits within the network is done at the layer 3 network level. Multi-Protocol Label Switching (MPLS) and the Resource Reservation Protocol (RSVP) are used to create the virtual circuits or Label Switched Paths (LSP's). Quality of Service (QoS) is used to provide bandwidth guarantees.", + "homepageURL": "https://www.es.net/engineering-services/oscars", + "laborHours": 0.0, + "languages": [ + "None" + ], + "name": "Oscars", + "organization": "Lawrence Berkeley National Laboratory (LBNL)", + "permissions": { + "exemptionText": null, + "licenses": [ + { + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" + } + ], + "usageType": "openSource" + }, + "repositoryURL": "https://www.es.net/engineering-services/oscars", + "status": "Production", + "tags": [ + "DOE CODE", + "Lawrence Berkeley National Laboratory (LBNL)" + ] +} \ No newline at end of file diff --git a/agency-indexes/DoE/SystemBurn.json b/agency-indexes/DoE/SystemBurn.json index 71c1a911..43008ed4 100644 --- a/agency-indexes/DoE/SystemBurn.json +++ b/agency-indexes/DoE/SystemBurn.json @@ -1,14 +1,14 @@ { "contact": { - "email": "simsdl@ornl.gov" + "email": "laymancelk@ornl.gov" }, "date": { - "created": "2018-04-18", - "metadataLastUpdated": "2018-04-18" + "created": "2017-10-25", + "metadataLastUpdated": "2017-10-25" }, - "description": "SystemBurn is a software package designed to allow users to methodically create maximal loads on systems ranging from desktops to supercomputers.\n", + "description": "SystemBurn is a tool for creating a synthetic computational load for the purpose of measuring how much power a computer will draw under that type of load. The loads include fundamental library function calls like matrix multiply, memory copies, fourier transforms, bit manipulation, I/O, network packet transfers, and some code contrived to cause the processor to dray more or less power. 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Travel reimbursements are generated through an interface between the eTravel system and the Social Security Online Accounting Reporting System (SSOARS).", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "GIS Direct Deposit Maps", + "repositoryURL": "", + "description": "GISSDD maps application creates U.S. and State/County maps and reports, to provide the percentage of Title II and Title XVI payments made through direct deposit in those areas. 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It maintains a variety of financial information including, but not limited to, funding data, commitments, obligations, receivables, and payables.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reporting", + "Accounting" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Mini Learning Management System", + "repositoryURL": "", + "description": "This LMS supports the Seattle Region Studio 6 in managing course content that they are responsible for, mainly the Transition to Leadership Courses, Core, and ASC/SLC training.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Learning Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Third Party Payment System", + "repositoryURL": "", + "description": "The Third Party Payment System (TPPS) is a register of paper checks that are known as Third Party Drafts. These drafts are issued to vendors for goods and services, to SSA employees for reimbursement of payments and to beneficiaries for Programmatic Immediate Payments (IPs) and Emergency Advance Payments (EAPs). TPPS enforces payment limits, maintains office draft stock, records and validates accounting data, and generates daily activity and monthly accountability reports.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reimbursements", + "Third Party", + "Payment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Death Information Processing System Web", + "repositoryURL": "", + "description": "The Death Information Processing System (DIPS) is a web-based iMain application used to add, change, or delete death data on the NUMIDENT. It replaced the Death Alert Control and Update System (DACUS) CICS screens in PCOM.", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Death" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Earnings Modernization Itemized Statement of Earnings Requests", + "repositoryURL": "", + "description": "Earnings Modernization Itemized Statement of Earnings Report (EMISER) is an interactive CICS control system that processes requests for Itemized Statements of Earnings (SSA-1826).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Earnings Requests", + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Volume Death", + "repositoryURL": "", + "description": "Updates the SSA Death Master File.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Death" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Rep Payee System", + "repositoryURL": "", + "description": "The Representative Payee System (RPS) is an online system used to store and process current and prior Rep Payee applications (both approved and denied). Data is stored on the Master Rep Payee File (MRPF) as applicants, beneficiaries, or recipients, and the relationship between the Rep Payee and beneficiary. The RPS data is also useful to adjudicators in processing subsequent actions.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Representative Payee" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "VIEWS - Data Exchange Inventory", + "repositoryURL": "", + "description": "DEXI is an inventory database that contains information about data exchanges between SSA and various partners. It interfaces with external applications to retrieve project code data, financial accounting data, management information data, and electronic reimbursable agreement documentation, and can be queried in various ways.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Data Exchange" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Numident Online Verification Utility", + "repositoryURL": "", + "description": "A mainframe application that accesses the NUMIDENT to perform real-time SSN verifications. This program is called by other SSA online programs that serve as interfaces to end-users.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Work Experience Reporting System", + "repositoryURL": "", + "description": "WERS is an MI system that captures and reports workload volumes and the hours needed to process items in each workload category. Weekly, monthly, quarterly, and yearly reports are produced for the Office of Budget, Finance and Management (OBFM).", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Reporting" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Medicare Non-Utilization Project", + "repositoryURL": "", + "description": "The Medicare Non-Usage Project (MNUP) objective is to use Medicare non-utilization information furnished to us by CMS as an indicator to select and prioritize cases for review to determine continued eligibility to SSA Title II benefits. We will obtain an initial data extract of individuals age 90 or over who are living in the United States, in current pay status and have not used Medicare during the previous three years. Subsequent data extracts will be obtained bi-annually. The data received from CMS will include Title II beneficiaries who reside in nursing homes, are enrolled in HMOs, or have private health insurance.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Medicare" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Medicare - IRMAA", + "repositoryURL": "", + "description": "Imposes higher Medicare Part B and Part D premium rates on high-income earners as defined by statute, adjusts those additional amounts on the basis of beneficiary allegations, and verifies the accuracy of those allegations.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "medicare" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Military Service Reimbursement", + "repositoryURL": "", + "description": "The Military Service Reimbursement System (MSRS) was developed to replace the process within the Title II AERO system that calculates Primary Insurance Amounts (PIA) for the Office of the Chief Actuary (OCACT).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reimbursement", + "Military" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Legal Automated Workflow System", + "repositoryURL": "", + "description": "A new system replacing the Program Litigation functions in the National Docketing Management Information System (NDMIS). LAWS electronically receives information contained in the Certified Administrative Record (CAR), interacts with Electronic Folder, allows OGC users access to historical data, accurately captures workloads, and enables users to produce and communicate management information.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workflow" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Cost Analysis System", + "repositoryURL": "", + "description": "The Cost Analysis System gathers workload counts and costs.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Cost Analysis" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Federal Assistance Award Data System", + "repositoryURL": "", + "description": "A central collection of selected, computer-based domestic financial assistance programs data for the Federal Government mandated by the Federal Funding Accountability and Transparency Act and is compiled quarterly.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Federal Assistance" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Quality Performance Management System / DARES", + "repositoryURL": "", + "description": "Performance management data extracted from multiple sources is consolidated into the QPMS data warehouse, providing a \"one-stop\" source for generating quality performance measures. The Disability Adjudication Review Evaluation System (DARES) provides a dashboard display of necessary management/decision support and risk information to Office of Disability Adjudication and Review (ODAR) officials, allowing them to effectively monitor and control the hearings backlog reduction initiatives and to determine the health of the overall hearings backlog reduction program at SSA. DARES also serves as the front-end starting point for QPMS DARES, which offers web-based, parameter-driven reports that are based on the breakdown of ODAR workloads within the context of how they relate to key hearing backlog initiatives.\u00c2 ", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Review", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Case Processing Management System", + "repositoryURL": "", + "description": "An intranet application used by the Office of Disability Adjudication and Review's (ODAR) hearing offices to process cases and manage office workloads.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Management", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Work Reporting Front End", + "repositoryURL": "", + "description": "A Web-based application used by all SSA technicians (TSC, FO, PC, and OCO), which fully automates the initiation, development, adjudication, and effectuation of Title II Work CDRs.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Work Reporting", + "Title II" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Consent Based Social Security Number Verification", + "repositoryURL": "", + "description": "A fee-based SSN verification service that permits private businesses, as well as Federal, State and Local governments, to use the Internet or a Web Service to verify an individual's SSN once a valid signed consent form is obtained from the SSN holder.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Number Verification", + "repositoryURL": "", + "description": "An application within Business Services Online (BSO). SSNVS allows registered users to verify names and SSNs of their employees against SSA's master files via the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Internet", + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "National Instant Criminal Background Check System", + "repositoryURL": "", + "description": "The purpose of the National Instant Criminal Background Check System (NICS) is to process potential NICS candidates for inclusion to the FBI, prohibiting firearm ownership.\nThis is an Intranet application for CRs to gather information from potential candidates who are identified by EDCS. CRs will then process the candidates who are legally incompetent and provide notification of NICS determinations to the appropriate parties, such as legal guardians, appointed representatives, and representative payees. All candidates found eligible will have identifying information submitted to the FBI.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Criminal", + "Background Check" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Internet Ticket Operations Provider Support System", + "repositoryURL": "", + "description": "An automated system that allows users to award contracts, provide ticket assignment/unassignment, and payments for Employment Networks (EN). It allows users to process, verify, and cancel payments before they reach Treasury.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Payments", + "Employment Networks", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Internet Application Status", + "repositoryURL": "", + "description": "An application that allows an individual to enter their Social Security Number (SSN) and follow the progress of all available claims using the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claim Status", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Audit Trail System", + "repositoryURL": "", + "description": "Collects application-specific transaction data and provides search capability for the Center Directors for Security and Integrity and their staffs for the purpose of deterring, detecting, and investigating instances of fraud and abuse.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Fraud Prevention", + "Security", + "Audit" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "UniForms", + "repositoryURL": "", + "description": "UniForms is a replacement for eForms, allowing Agency-wide retrieval of administrative forms.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Forms" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Manual Adjustment Credit & Award Data Entry", + "repositoryURL": "", + "description": "CICS data collection system consists of data entered/received via MACADE or data that comes to MACADE via A101, and propagates information into the SPS database to create a payment record.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Payment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Processing Center Action Control System", + "repositoryURL": "", + "description": "PCACS provides timely, accurate, and detailed online information regarding the status and location of actions and folders in progress in all processing centers (PCs).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Processing Center" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Electronic Remittance System", + "repositoryURL": "", + "description": "The Social Security Electronic Remittance System (SERS) collects standard fees for non-program-related requests for information. The system allows field office personnel to quickly process payments and eliminates the need to bundle and send payment requests to the Office of Finance at headquarters.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Fee Collection" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Returned Check Action", + "repositoryURL": "", + "description": "The program generates an electronic alert file to the servicing Processing Center (PC) when Title II benefit payments are returned, indicating the beneficiary is deceased. It will automatically send a call-in letter to each beneficiary indicating the stop payment and the reason why.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Death", + "Title II", + "Processing Center" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Fugitive Felon Matching Agreements", + "repositoryURL": "", + "description": "APPLICATION TO COLLECT INFORMATION ON SSA EFFORTS TO NEGOTIATE MATCHING AGREEMENTS WITH LAW ENFORCEMENT AGENCIES TO IDENTIFY FUGITIVE FELONS AND PAROLE AND PROBATION VIOLATORS", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Felon" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "National Docketing Management Information System", + "repositoryURL": "", + "description": "Centralized system for tracking and managing legal matters as a system-of-record for all OGC regions and at OGC headquarters. 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There is also an online system for users in OCO and the field offices to query the ERISA master files.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Private Pensions", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Modernized Integrated Disability Adjudicative System", + "repositoryURL": "", + "description": "A federal disability case processing system used in Disability Determination Services, Disability Processing Branches, and some federal components that process disability claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claims", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Target Notice Architecture - Mainframe", + "repositoryURL": "", + "description": "TNA is the agency's standard for the systems development of 508-compliant notice language.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "508", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Earnings Case Management System", + "repositoryURL": "", + "description": "This is a case management system which tracks many different earnings workloads.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Earnings Requests", + "Case Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Disability Collection System (EDCS\\eView)", + "repositoryURL": "", + "description": "An automated system for SSA field personnel to electronically collect information about the applicant and his or her medical condition, and transfer the data to the EF for use by a local case management system.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Management", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Folder Interface", + "repositoryURL": "", + "description": "An interface between the electronic folder and the case processing systems (CPMS for ODAR). 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It provides data analysis to monitor work loads and trend analysis and information on a variety of variables such as time and location, allowing users to make further improvements and enhancements to the disability process.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "HealthIT" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "WMI for IC and Appeals", + "repositoryURL": "", + "description": "Legacy Workload Management Information (WMI) for IC and appeals batch programs and CICS screens.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Appeals", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "VIEWS - Agreement Workflow Tool", + "repositoryURL": "", + "description": "AWT is a workflow tool and repository for the reimbursable agreement documents. 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DOORS has a user and customer base of all SSA employees, hundreds of SSA systems, and members of the public who use SSA.GOV on the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Inventory Management", + "Office", + "Administrative" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Automatic Earnings Reappraisal Operation", + "repositoryURL": "", + "description": "The process that \"automatically\" screens the earning records of Retirement, Survivors, and Disability Insurance (RSDI) beneficiaries for additional earnings and computes necessary changes. The beneficiary does NOT have to initiate this process.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Automated", + "Disability", + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Number Application Process", + "repositoryURL": "", + "description": "An Enumeration software application that will perform a cross-reference check of a new SSN.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Application", + "Enumeration" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Verifications Account Management System", + "repositoryURL": "", + "description": "Verification Account Management System (VAMS) is a centralized location for maintaining Enumeration Verification Systems (EVS) accounts. VAMS allows users to create new accounts, search for existing accounts, update current accounts, and generate MI count reports. DEVO interfaces with VAMS to perform the administrative functions of registration, access control and tracking, and to manage assignment of the functional processes.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Account Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Integrated Client Database System", + "repositoryURL": "", + "description": "The Integrated Client Database (ICDB) System allows data to be shared among SSA's major application systems (e.g., Title II and Title XVI Claims Processing). ICDB is comprised of a set of databases, common screens and access software that collects, maintains, and provides access to common Client data.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Client" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Earnings Use - SEQY", + "repositoryURL": "", + "description": "A Master File online query request screen that adds earnings from up to 10 SSNs to the query response. The system then combines the earnings from the SSNs in the yearly totals on the query response.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Person Information", + "repositoryURL": "", + "description": "The Person Information web application was created to provide a common set of screens to display and collect person data. It is available as an independent application through the Person Information link on iMain. It can also be included in another application's path.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Person" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Folder Interface - Data Access", + "repositoryURL": "", + "description": "Allows shared access via eView to legacy information and documents within a case.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Document", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "AccuWage", + "repositoryURL": "", + "description": "AccuWage is used for testing the Electronic Filing of Wage and Tax Statement (EFW2). The software is downloaded from the SSA Web site by a submitter and used to check the format of a wage report submission file.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Taxes", + "Employment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Comprehensive Integrity Review Process - Mainframe", + "repositoryURL": "", + "description": "Collects and evaluates electronic transactions entered into the programmatic systems. Identifies those transactions that may indicate abuse or fraudulent activity involving SSA employees or the public.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Review", + "Fraud Prevention" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "DCS Budget Tracking System", + "repositoryURL": "", + "description": "Tracks Other Objects budget allocations for the Office of Systems and tracks some Information Technology budgets. Monitors and tracks allocations, expenditures and generates Management Information (MI) reports for planning budget requests and allocations.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Management Information", + "Administrative", + "Budget Tracking" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Internet Special Notices Option", + "repositoryURL": "", + "description": "An Internet/Intranet application designed to collect notice preferences from applicants, beneficiaries, recipients, and representative payees who allege blindness or visual impairment. These individuals can select to receive all notices and written communication from SSA via a Microsoft Word CD or in Braille.", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "SNO", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Performance Assessment and Communication System", + "repositoryURL": "", + "description": "PACS assists supervisors in preparing employee performance plans, documenting expectations and progress reviews and preparing performance appraisals.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Performance Appraisals", + "Human Resources" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Security Administration Reports Application", + "repositoryURL": "", + "description": "SARA is the automated solution to an existing manual review\nprocess, and it will provide the ability to capture trending data to\nassist in management decisions. Yes, The Security Administration Reports\nApplication SARA will allow Information Security Officers ISOs,\nAlternate Information Security Officers ALT ISOs and Management Designee\nMD to access, review and take appropriate action on Security\nAdministration Reports.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reporting", + "Management Information", + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Document Processing System", + "repositoryURL": "", + "description": "The Document Processing System (DPS) is an SSA developed, browser based application that will provide the user with functionality similar to the client server based system, Distributed Online Correspondence System (DOCS).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Document Processing", + "Document Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Personal Enrollment Credential System", + "repositoryURL": "", + "description": "The HSPD-12 Electronic Personal Enrollment Credential System (EPECS) supports the HSPD-12 credentialing process at SSA. It automates the sponsoring, vetting, and issuing of HSPD-12 credentials. It interfaces with other SSA systems for compliance with various directives.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Bench Book", + "repositoryURL": "", + "description": "A web-based application used by the office of Disability Adjudication and Review/ODAR to aid with documentation, analysis, and adjudication of disability cases.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Adjudication", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Visitor Intake Process - Rewrite", + "repositoryURL": "", + "description": "Manages appointments and walk-ins for Field Office (FO) and assigns them to the FO staff in an effective way to minimize the wait time of the users.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Scheduling", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Hires and Losses Tracking System", + "repositoryURL": "", + "description": "This application tracks the hires and losses of employees to the Office of Systems. It provides an automated way of approving hires and tracking both hires and losses in Systems. It also provides many reports from captured data on individuals joining the Office of Systems, leaving the Office of Systems, or moving from one Associate Commissioner's office within Systems to another Associate Commissioner's office within Systems. The data from these reports are used by management to make budget decisions.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Human Resources" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "GSO - Interim Assistance Reimbursement", + "repositoryURL": "", + "description": "An online mechanism for state agencies to report to SSA the amount of state or local assistance the agencies paid to individuals who are now eligible for SSI payments.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Data Exchanges", + "Payments" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Modernized Supplemental Security Income Claims System", + "repositoryURL": "", + "description": "Web-based Intranet pages that collect and document application information about the claimant, provide a modernized data-collection environment for most post-eligibility (PE) events - regardless of whether the action taken is an initial claim or a PE event - and allow online claims initiation for the majority of SSI claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Internet", + "Claim", + "SSI" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Affordable Care Act - Batch Redetermination/Renewal Process", + "repositoryURL": "", + "description": "A batch application exchanges data with CMS related to eligibility Redeterminations and Renewal decisions for Insurance Affordability Programs.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Medical", + "Insurance" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Freedom of Information Act System -Intranet", + "repositoryURL": "", + "description": "An Intranet application used by the Office of Public Disclosure (OPD) and the Division of Earnings Record Operations (DERO) to process the different types of FOIA requests that are received.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Intranet", + "FOIA" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Direct Deposit Fraud Prevention", + "repositoryURL": "", + "description": "An intranet web application developed to collect and processes requests to block direct deposit auto-enrollment changes that are received and processed in the SSA Notification of Change (SANOC) System. The DDFP web application also requires input of the reason for the block - Fraud Alleged or Preventive Measure. Both the adding and removal of the block are updated in real time allowing the application to access the data for display the block request history.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Direct Deposit", + "Fraud Prevention" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "SSI Claims System - Web", + "repositoryURL": "", + "description": "Enables SSI claim submissions via a web-based intranet data collection process. It replaces the previous set of CICS MSSICS screens.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Data Collection", + "Claim", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Access to Financial Institutions", + "repositoryURL": "", + "description": "Electronically verifies depository account balances for Supplemental Security Income (SSI) applicants, recipients, and deemors. It also searches for undisclosed depository accounts and detects unreported excess resources, reducing improper SSI payments.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Direct Deposit", + "Financial" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "electronic Representative Payee System", + "repositoryURL": "", + "description": "The Electronic Representative Payee Accounting (eRPA) system is an intranet-based system that has automated the processing of Representative Payee Accounting forms.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Forms", + "Intranet", + "Representative Payee" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Data Exchange and Verification Online", + "repositoryURL": "", + "description": "DEVO is the back-end application for processing SSN verifications and data exchanges. DEVO uses modern technology for parameter driven processing of both batch and real time requests. DEVO provides the capability for SSA to accurately and rapidly respond to customized requests, legislative mandates, and court orders. Legacy verification and data exchange applications (Enumeration Verification System (EVS), Numident Online Verification Utility (NOVU), State Verification Exchange System (SVES), and State Online Query System (SOLQ)) are methodically being reengineered into DEVO, which will make use of reusable, flexible software. DEVO interfaces with the Verification Account Management System (VAMS) to determine account status, obtain processing parameters, and store transaction counts for Management Information (MI).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Verification", + "Data Exchange" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Core Services", + "repositoryURL": "", + "description": "A suite of Intranet-based utilities designed to simplify central or common routines required by many web based applications. The utilities leverage open, accessible technologies eliminating the drawbacks commonly seen in proprietary coding techniques. They help prevent duplication of effort by reusing what already exists.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Intranet", + "Services" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "StaRZ & Stripes - The Next Generation", + "repositoryURL": "", + "description": "StarRZ and Stripes the Next Generation (SSTNG) provides the full range of detailed workload monitoring, management reports and listings used by Claims Reps, Operation Supervisors and FO Managers to identify, track and successfully complete their annual Redetermination/Limited (RZ/LI) workloads.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MI for Debt Management System", + "repositoryURL": "", + "description": "Provides an summary of the financial Debt Management screens at the regional field offices and the processing center levels", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Processing Center", + "Debt Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Customer Help and Information Program", + "repositoryURL": "", + "description": "CHIP is an Intranet application currently used by National 800 Number (N8NN) Agents to respond to inquiries made by the public. Provides instant access to facts, policies and reference material found in the Teleservice Center Operating Guide (TSCOG), as well as information from certain mainframe records.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Policy", + "Call Center", + "Phone" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Prisoner Tracking MI", + "repositoryURL": "", + "description": "The Prisoner Tracking Management Information (PTMI) provides aggregate and workload data for Title II and Title XVI prisoner transactions processed in SSA field offices (FO's) and Processing Service Centers (PSC's), provides correctional facility names, and correctional facility reporting and incentive payment information.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Management Information", + "Prisoner" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Access to State Records Online", + "repositoryURL": "", + "description": "Social Security Access to State Records Online (SASRO) provides authorized SSA employees access to state agency benefit information, in order to correctly process many of its entitlement and post-entitlement actions.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Entitlments", + "Benefits", + "State" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "My Human Resources", + "repositoryURL": "", + "description": "This application is part of the application hub, Human Resources Services Portal. The e7B creates a secure, electronic centralized repository accessed through the agency's Intranet for all information maintained in the 7B, 7B Extension File, and holding file to reduce the amount of required time and expenditures associated with file maintenance.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Human Resources" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Security Oversight Command & Control System", + "repositoryURL": "", + "description": "SOCCS is utilized to coordinate disaster planning, evacuation and security.\n\nSOCCS is used for security oversight and disaster planning for SSA HQ complex, leased buildings and facilities assigned to SSA HQ.\n\nOffice of Security and Emergency Preparedness (OSEP) will capitalize on SOCCS ability to read and receive live data feeds, ensuring the safety of SSA personnel and the public.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Safety", + "Disaster Planning" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Integrated Registration Services - Internet", + "repositoryURL": "", + "description": "An internet application that provides registration, authentication and authorization gateway services for the Business Services Online (BSO) suite of Business-to-Government (B2G) services.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Registration", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Disability Quality Review", + "repositoryURL": "", + "description": "The Disability Quality Review system is an JAVA web-based application that allows in-line quality reviews of cases/claims adjudicated by the Disability Determination Services.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claims Review", + "Review", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Official Union Time Tracking System", + "repositoryURL": "", + "description": "OUTTS will collect and load into MTAS the number and type of regular hours, as well as the number and type of credit hours that were worked on official union time for the current pay period or amended union activity for a prior pay period.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Human Resources", + "Time and Attendance", + "Union" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "National Disability Determination Services System", + "repositoryURL": "", + "description": "NDDSS is a software application that provides case control management and reporting capabilities. NDDSS gives the state Disability Determination Services offices the ability to track the receipt, development and closures of claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Management", + "Determination", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Disability Case Processing System", + "repositoryURL": "", + "description": "The Disability Case Processing System is used by disability determination components to process disability claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claims Processing", + "Disability", + "Case Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Employer Balancing Intranet Processing System", + "repositoryURL": "", + "description": "The Annual Wage reporting (AWR) Employer Balancing Intranet Processing System (EBIPS) enables users to view submitter, employer, submission, W-3, W-2, and report of contact information.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Wage Reporting", + "Employer" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "myAPS Web Application", + "repositoryURL": "", + "description": "As part of the mySSA suite of applications, myAPS provides detailed status information for all pending T2, T16, and T18 claims, including Appeals up to the Hearing Request level for denied claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claims", + "Claims Tracking", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Global Reference Table Portal", + "repositoryURL": "", + "description": "Application used to collect data to update the Global Reference Tables, which store common information used throughout SSA, and standardize code structures and code usage of SSA business and Policy-approved values.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Metadata Management", + "Data", + "Common" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Workload Action Center", + "repositoryURL": "", + "description": "The Workload Action Center (WAC) allows users to view, analyze, and work initial claims and appeals pending lists, as well as mainframe tickle lists. It consumes Programmatic Workload data to provide information to the 1,394 field offices to assist SSA employees in adjudicating initial disability claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Disability", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MySSA Benefit Verification - Backend", + "repositoryURL": "", + "description": "Accessed through the MySocialSecurity portal, it provides instant verification of SSA benefits for proof of income purposes. It also provides immediate view, print, and save of benefit verification letters to prove receipt/non-receipt of SSA benefits, Supplemental Income (SSI) or Medicare.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Registration", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "iAppeals (i3441)", + "repositoryURL": "", + "description": "Allows electronic submission of requests from individuals and/or third parties for the Request for Reconsideration (SSA-561), Request for Hearing (HA-501) on medically denied claims for both Title II and Title XVI claims, and allows an individual to appeal the decision directly on-line.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Appeals", + "Medical", + "Forms" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Number Verification - BSO", + "repositoryURL": "", + "description": "Allows employers to verify name/SSNs for wage reporting purposes.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Identity", + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Calendar Availability Services", + "repositoryURL": "", + "description": "The calendar availability service allows the ability to add availability, update availability, get availability, update available resources, and delete availability for one or many offices and calendar configurations.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Spring Boot", + "RESTful", + "Calendar Management", + "Calendar Availability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "CET Dynamic Help", + "repositoryURL": "", + "description": "mySSA Dynamic Help application", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "mySSA" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "codeMetadata.json Generator", + "repositoryURL": "", + "description": "A single page application for generating a codeMetadata.json file. The codeMetadata.json file contains basic data about a code asset such as it's name, description, languages, and the like.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "node.js", + "REACT", + "SPA", + "Single Page Application" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "EPMO Web Application", + "repositoryURL": "", + "description": "EPMO Application is developed in MDE using AngualrJS, HTML front end and Java (Jax-RS ) backend. This is a RESTful app with authentication and authorization done using WebSeal.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "AngularJS", + "JAX-RS", + "EJB", + "SPA", + "JWT" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "iAppointment", + "repositoryURL": "", + "description": "An Internet application that allows individuals to schedule appointments with SSA's Field Offices.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Appointments", + "MVC", + "UEF", + "FlexWeb" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Main Complex Conference Rooms System", + "repositoryURL": "", + "description": "The MCCR system is a web application tool used to reserve conference rooms for meetings, events, presentations, etc.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "facilities, conference room, reservations, coldfusion" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MDE Control Center", + "repositoryURL": "", + "description": "Self-serve control center application for SSA MDE.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Spring", + "Thymeleaf", + "LDAP", + "SMTP" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MDE JSON Generator", + "repositoryURL": "", + "description": "Self-serve application for SSA mde.json generation.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Spring", + "Thymeleaf", + "JSON" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Message Center", + "repositoryURL": "", + "description": "CET Message Center for mySSA", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "CET", + "mySSA" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Message Service", + "repositoryURL": "", + "description": "Web Service for CET Message Center", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "SOAP" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MessageAdmin", + "repositoryURL": "", + "description": "CET Message Center Admin Console", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "CET" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "openshift-upgrade-testing", + "repositoryURL": "", + "description": "Java code to create a sample web app - to be deployed in Open shift to perform regression testing on any major releases.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "MUT", + "paas", + "MDE", + "OpenShift" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "property-services", + "repositoryURL": "", + "description": "Property Services is an independent component that is used to read the configuration files and resources and make them available for accessing as per the environment/scope.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Property Services" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "UEF Core", + "repositoryURL": "", + "description": "UEF patterns", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "uef, inputs, web, containers, buttons, notices, links, design, page, standard, 508 compliance" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, { "name": "UEF Website", "repositoryURL": "", diff --git a/scripts/pull_all_assets.py b/scripts/pull_all_assets.py index 6b41b2ff..b499005c 100644 --- a/scripts/pull_all_assets.py +++ b/scripts/pull_all_assets.py @@ -1,6 +1,6 @@ -from .pull_legacy_assets import agencies_links, headers, add_directories_to_directory, add_indexes_to_directory -from .pull_legacy_assets import main as legacy_pull_function -from .pull_public_assets import main as public_pull_function +from pull_legacy_assets import agencies_links, headers, add_directories_to_directory, add_indexes_to_directory +from pull_legacy_assets import main as legacy_pull_function +from pull_public_assets import main as public_pull_function def main(): legacy_pull_function() diff --git a/scripts/pull_legacy_assets.py b/scripts/pull_legacy_assets.py index 879497b8..f21e6d19 100644 --- a/scripts/pull_legacy_assets.py +++ b/scripts/pull_legacy_assets.py @@ -1,7 +1,7 @@ import requests import json import os -from .util import merge_indexes +from util import merge_indexes # the commented out links are not valid or cant be found agencies_links = { @@ -35,7 +35,7 @@ } def add_directories_to_directory(data, agency_name): - directory_name = f"../agency-indexes/{agency_name}" + directory_name = f"agency-indexes/{agency_name}" try: if not os.path.exists(directory_name): @@ -57,7 +57,7 @@ def add_directories_to_directory(data, agency_name): def add_indexes_to_directory(data, agency_name): - file_name = f"../agency-indexes/{agency_name}-index.json" + file_name = f"agency-indexes/{agency_name}-index.json" if os.path.exists(file_name): try: diff --git a/scripts/pull_public_assets.py b/scripts/pull_public_assets.py index ca5653b4..7bdef403 100644 --- a/scripts/pull_public_assets.py +++ b/scripts/pull_public_assets.py @@ -2,7 +2,7 @@ import os from codejson_index_generator import IndexGenerator -from .util import merge_indexes +from util import merge_indexes AGENCY_CODEJSON_DIR = "agency-indexes" VERSION = '0.0.1' diff --git a/scripts/util.py b/scripts/util.py index 9366e577..e967f02c 100644 --- a/scripts/util.py +++ b/scripts/util.py @@ -1,3 +1,5 @@ +import json + def merge_indexes(data,existing_file): try: with open(existing_file, 'r', encoding='utf-8') as file: From c50b43a418fc4d06f2b357f51d57c9b74cf1771e Mon Sep 17 00:00:00 2001 From: Isaac Milarsky Date: Thu, 5 Jun 2025 12:41:31 -0500 Subject: [PATCH 09/14] update script to sort codejson by date last updated by Signed-off-by: Isaac Milarsky --- scripts/pull_public_assets.py | 19 +++++++++++++++++-- scripts/util.py | 14 +++++++++++++- 2 files changed, 30 insertions(+), 3 deletions(-) diff --git a/scripts/pull_public_assets.py b/scripts/pull_public_assets.py index 7bdef403..6fb7855f 100644 --- a/scripts/pull_public_assets.py +++ b/scripts/pull_public_assets.py @@ -2,7 +2,7 @@ import os from codejson_index_generator import IndexGenerator -from util import merge_indexes +from util import merge_indexes, which_code_json_is_most_up_to_date AGENCY_CODEJSON_DIR = "agency-indexes" VERSION = '0.0.1' @@ -55,10 +55,25 @@ def main(): continue repoPath = os.path.join(agency_subdir, (repo_obj.name + '.json')) - code_json = indexGen.save_code_json(repo_obj,repoPath) + + code_json = indexGen.get_code_json(repo_obj) + if code_json: print(f"✅ Found code.json in {repo}") + + if os.path.exists(repoPath): + try: + with open(repoPath, 'r', encoding='utf-8') as file: + existing_code_json = json.load(file) + + code_json = which_code_json_is_most_up_to_date(code_json,existing_code_json) + except Exception: + print("could not open existing codejson File!") + + with open(repoPath, 'w') as f: + json.dump(code_json,f,indent=2) + indexGen.update_index(indexGen.index,code_json,repo_obj.organization, repo_obj.name) else: print(f"❌ No code.json found in {repo}") diff --git a/scripts/util.py b/scripts/util.py index e967f02c..01e36846 100644 --- a/scripts/util.py +++ b/scripts/util.py @@ -1,4 +1,5 @@ import json +from datetime import datetime def merge_indexes(data,existing_file): try: @@ -26,4 +27,15 @@ def merge_indexes(data,existing_file): except Exception as e: print(f"Failed to read existing file: {e}") - raise e \ No newline at end of file + raise e + + +def which_code_json_is_most_up_to_date(*args): + + sorted_code_json_list = sorted( + args, + key=lambda d : datetime.strptime( + d['date']['metadataLastUpdated'],'%Y-%m-%d' + ), + reverse=True) + return sorted_code_json_list[0] \ No newline at end of file From 9a3a5ba72edf24d0b84d89bb25c1bd40c1317ee1 Mon Sep 17 00:00:00 2001 From: Isaac Milarsky Date: Thu, 5 Jun 2025 12:48:39 -0500 Subject: [PATCH 10/14] update Signed-off-by: Isaac Milarsky --- agency-indexes/SSA-index.json | 2381 +++++++++++++++++++++++++++++++++ 1 file changed, 2381 insertions(+) diff --git a/agency-indexes/SSA-index.json b/agency-indexes/SSA-index.json index 8065c584..b016803d 100644 --- a/agency-indexes/SSA-index.json +++ b/agency-indexes/SSA-index.json @@ -7288,6 +7288,2387 @@ "name": "Open Source Administrator" } }, + { + "name": "UEF Website", + "repositoryURL": "", + "description": "Standards Website for the User Experience Framework", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "UEF", + "Standards", + "User Experience Framework" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Disability Case Adjudication and Review System", + "repositoryURL": "", + "description": "Disability Case Adjudication and Review System (DICARS) is the legacy system supporting business processes in the Disability Quality Branches (DQBs) and the simultaneous, blind, pre-effectuation consistency review of initial Disability Determination Service (DDS) clearances processed in Division of Disability Quality Operations DDQO). Works in conjunction with the Disability Quality Review (DQR) application which will eventually replace it.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Processing", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Disability Predictive Model", + "repositoryURL": "", + "description": "Dual score card application based on the Predictive Model design architecture written by IBM. It is called when initial adjudicative disability cases are transferred to the DDS for a medical determination. It will analyze the date electronically and produce two values, each between 0 and 1. The first value will express the confidence that a favorable determination will be made (known as SSAL - SSA Allowance). The second (known as SSPT - SSA Processing Time) will express the confidence that the determination can be reached quickly.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Predictive", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Front End Capture System", + "repositoryURL": "", + "description": "Front-end document capture system for DMA. 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Travel reimbursements are generated through an interface between the eTravel system and the Social Security Online Accounting Reporting System (SSOARS).", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "GIS Direct Deposit Maps", + "repositoryURL": "", + "description": "GISSDD maps application creates U.S. and State/County maps and reports, to provide the percentage of Title II and Title XVI payments made through direct deposit in those areas. 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It maintains a variety of financial information including, but not limited to, funding data, commitments, obligations, receivables, and payables.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reporting", + "Accounting" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Mini Learning Management System", + "repositoryURL": "", + "description": "This LMS supports the Seattle Region Studio 6 in managing course content that they are responsible for, mainly the Transition to Leadership Courses, Core, and ASC/SLC training.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Learning Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Third Party Payment System", + "repositoryURL": "", + "description": "The Third Party Payment System (TPPS) is a register of paper checks that are known as Third Party Drafts. These drafts are issued to vendors for goods and services, to SSA employees for reimbursement of payments and to beneficiaries for Programmatic Immediate Payments (IPs) and Emergency Advance Payments (EAPs). TPPS enforces payment limits, maintains office draft stock, records and validates accounting data, and generates daily activity and monthly accountability reports.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reimbursements", + "Third Party", + "Payment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Death Information Processing System Web", + "repositoryURL": "", + "description": "The Death Information Processing System (DIPS) is a web-based iMain application used to add, change, or delete death data on the NUMIDENT. It replaced the Death Alert Control and Update System (DACUS) CICS screens in PCOM.", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Death" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Earnings Modernization Itemized Statement of Earnings Requests", + "repositoryURL": "", + "description": "Earnings Modernization Itemized Statement of Earnings Report (EMISER) is an interactive CICS control system that processes requests for Itemized Statements of Earnings (SSA-1826).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Earnings Requests", + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Volume Death", + "repositoryURL": "", + "description": "Updates the SSA Death Master File.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Death" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Rep Payee System", + "repositoryURL": "", + "description": "The Representative Payee System (RPS) is an online system used to store and process current and prior Rep Payee applications (both approved and denied). Data is stored on the Master Rep Payee File (MRPF) as applicants, beneficiaries, or recipients, and the relationship between the Rep Payee and beneficiary. The RPS data is also useful to adjudicators in processing subsequent actions.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Representative Payee" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "VIEWS - Data Exchange Inventory", + "repositoryURL": "", + "description": "DEXI is an inventory database that contains information about data exchanges between SSA and various partners. It interfaces with external applications to retrieve project code data, financial accounting data, management information data, and electronic reimbursable agreement documentation, and can be queried in various ways.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Data Exchange" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Numident Online Verification Utility", + "repositoryURL": "", + "description": "A mainframe application that accesses the NUMIDENT to perform real-time SSN verifications. This program is called by other SSA online programs that serve as interfaces to end-users.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Work Experience Reporting System", + "repositoryURL": "", + "description": "WERS is an MI system that captures and reports workload volumes and the hours needed to process items in each workload category. Weekly, monthly, quarterly, and yearly reports are produced for the Office of Budget, Finance and Management (OBFM).", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Reporting" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Medicare Non-Utilization Project", + "repositoryURL": "", + "description": "The Medicare Non-Usage Project (MNUP) objective is to use Medicare non-utilization information furnished to us by CMS as an indicator to select and prioritize cases for review to determine continued eligibility to SSA Title II benefits. We will obtain an initial data extract of individuals age 90 or over who are living in the United States, in current pay status and have not used Medicare during the previous three years. Subsequent data extracts will be obtained bi-annually. The data received from CMS will include Title II beneficiaries who reside in nursing homes, are enrolled in HMOs, or have private health insurance.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Medicare" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Medicare - IRMAA", + "repositoryURL": "", + "description": "Imposes higher Medicare Part B and Part D premium rates on high-income earners as defined by statute, adjusts those additional amounts on the basis of beneficiary allegations, and verifies the accuracy of those allegations.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "medicare" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Military Service Reimbursement", + "repositoryURL": "", + "description": "The Military Service Reimbursement System (MSRS) was developed to replace the process within the Title II AERO system that calculates Primary Insurance Amounts (PIA) for the Office of the Chief Actuary (OCACT).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reimbursement", + "Military" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Legal Automated Workflow System", + "repositoryURL": "", + "description": "A new system replacing the Program Litigation functions in the National Docketing Management Information System (NDMIS). LAWS electronically receives information contained in the Certified Administrative Record (CAR), interacts with Electronic Folder, allows OGC users access to historical data, accurately captures workloads, and enables users to produce and communicate management information.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workflow" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Cost Analysis System", + "repositoryURL": "", + "description": "The Cost Analysis System gathers workload counts and costs.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Cost Analysis" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Federal Assistance Award Data System", + "repositoryURL": "", + "description": "A central collection of selected, computer-based domestic financial assistance programs data for the Federal Government mandated by the Federal Funding Accountability and Transparency Act and is compiled quarterly.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Federal Assistance" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Quality Performance Management System / DARES", + "repositoryURL": "", + "description": "Performance management data extracted from multiple sources is consolidated into the QPMS data warehouse, providing a \"one-stop\" source for generating quality performance measures. The Disability Adjudication Review Evaluation System (DARES) provides a dashboard display of necessary management/decision support and risk information to Office of Disability Adjudication and Review (ODAR) officials, allowing them to effectively monitor and control the hearings backlog reduction initiatives and to determine the health of the overall hearings backlog reduction program at SSA. DARES also serves as the front-end starting point for QPMS DARES, which offers web-based, parameter-driven reports that are based on the breakdown of ODAR workloads within the context of how they relate to key hearing backlog initiatives.\u00c2 ", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Review", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Case Processing Management System", + "repositoryURL": "", + "description": "An intranet application used by the Office of Disability Adjudication and Review's (ODAR) hearing offices to process cases and manage office workloads.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Management", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Work Reporting Front End", + "repositoryURL": "", + "description": "A Web-based application used by all SSA technicians (TSC, FO, PC, and OCO), which fully automates the initiation, development, adjudication, and effectuation of Title II Work CDRs.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Work Reporting", + "Title II" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Consent Based Social Security Number Verification", + "repositoryURL": "", + "description": "A fee-based SSN verification service that permits private businesses, as well as Federal, State and Local governments, to use the Internet or a Web Service to verify an individual's SSN once a valid signed consent form is obtained from the SSN holder.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Number Verification", + "repositoryURL": "", + "description": "An application within Business Services Online (BSO). SSNVS allows registered users to verify names and SSNs of their employees against SSA's master files via the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Internet", + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "National Instant Criminal Background Check System", + "repositoryURL": "", + "description": "The purpose of the National Instant Criminal Background Check System (NICS) is to process potential NICS candidates for inclusion to the FBI, prohibiting firearm ownership.\nThis is an Intranet application for CRs to gather information from potential candidates who are identified by EDCS. CRs will then process the candidates who are legally incompetent and provide notification of NICS determinations to the appropriate parties, such as legal guardians, appointed representatives, and representative payees. All candidates found eligible will have identifying information submitted to the FBI.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Criminal", + "Background Check" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Internet Ticket Operations Provider Support System", + "repositoryURL": "", + "description": "An automated system that allows users to award contracts, provide ticket assignment/unassignment, and payments for Employment Networks (EN). It allows users to process, verify, and cancel payments before they reach Treasury.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Payments", + "Employment Networks", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Internet Application Status", + "repositoryURL": "", + "description": "An application that allows an individual to enter their Social Security Number (SSN) and follow the progress of all available claims using the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claim Status", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Audit Trail System", + "repositoryURL": "", + "description": "Collects application-specific transaction data and provides search capability for the Center Directors for Security and Integrity and their staffs for the purpose of deterring, detecting, and investigating instances of fraud and abuse.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Fraud Prevention", + "Security", + "Audit" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "UniForms", + "repositoryURL": "", + "description": "UniForms is a replacement for eForms, allowing Agency-wide retrieval of administrative forms.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Forms" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Manual Adjustment Credit & Award Data Entry", + "repositoryURL": "", + "description": "CICS data collection system consists of data entered/received via MACADE or data that comes to MACADE via A101, and propagates information into the SPS database to create a payment record.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Payment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Processing Center Action Control System", + "repositoryURL": "", + "description": "PCACS provides timely, accurate, and detailed online information regarding the status and location of actions and folders in progress in all processing centers (PCs).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Processing Center" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Electronic Remittance System", + "repositoryURL": "", + "description": "The Social Security Electronic Remittance System (SERS) collects standard fees for non-program-related requests for information. The system allows field office personnel to quickly process payments and eliminates the need to bundle and send payment requests to the Office of Finance at headquarters.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Fee Collection" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Returned Check Action", + "repositoryURL": "", + "description": "The program generates an electronic alert file to the servicing Processing Center (PC) when Title II benefit payments are returned, indicating the beneficiary is deceased. It will automatically send a call-in letter to each beneficiary indicating the stop payment and the reason why.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Death", + "Title II", + "Processing Center" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Fugitive Felon Matching Agreements", + "repositoryURL": "", + "description": "APPLICATION TO COLLECT INFORMATION ON SSA EFFORTS TO NEGOTIATE MATCHING AGREEMENTS WITH LAW ENFORCEMENT AGENCIES TO IDENTIFY FUGITIVE FELONS AND PAROLE AND PROBATION VIOLATORS", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Felon" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "National Docketing Management Information System", + "repositoryURL": "", + "description": "Centralized system for tracking and managing legal matters as a system-of-record for all OGC regions and at OGC headquarters. 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There is also an online system for users in OCO and the field offices to query the ERISA master files.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Private Pensions", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Modernized Integrated Disability Adjudicative System", + "repositoryURL": "", + "description": "A federal disability case processing system used in Disability Determination Services, Disability Processing Branches, and some federal components that process disability claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Claims", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Target Notice Architecture - Mainframe", + "repositoryURL": "", + "description": "TNA is the agency's standard for the systems development of 508-compliant notice language.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "508", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Earnings Case Management System", + "repositoryURL": "", + "description": "This is a case management system which tracks many different earnings workloads.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Earnings Requests", + "Case Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Disability Collection System (EDCS\\eView)", + "repositoryURL": "", + "description": "An automated system for SSA field personnel to electronically collect information about the applicant and his or her medical condition, and transfer the data to the EF for use by a local case management system.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Case Management", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Folder Interface", + "repositoryURL": "", + "description": "An interface between the electronic folder and the case processing systems (CPMS for ODAR). 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It provides data analysis to monitor work loads and trend analysis and information on a variety of variables such as time and location, allowing users to make further improvements and enhancements to the disability process.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "HealthIT" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "WMI for IC and Appeals", + "repositoryURL": "", + "description": "Legacy Workload Management Information (WMI) for IC and appeals batch programs and CICS screens.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Appeals", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "VIEWS - Agreement Workflow Tool", + "repositoryURL": "", + "description": "AWT is a workflow tool and repository for the reimbursable agreement documents. 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DOORS has a user and customer base of all SSA employees, hundreds of SSA systems, and members of the public who use SSA.GOV on the Internet.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Inventory Management", + "Office", + "Administrative" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Automatic Earnings Reappraisal Operation", + "repositoryURL": "", + "description": "The process that \"automatically\" screens the earning records of Retirement, Survivors, and Disability Insurance (RSDI) beneficiaries for additional earnings and computes necessary changes. The beneficiary does NOT have to initiate this process.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Automated", + "Disability", + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Number Application Process", + "repositoryURL": "", + "description": "An Enumeration software application that will perform a cross-reference check of a new SSN.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Application", + "Enumeration" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Verifications Account Management System", + "repositoryURL": "", + "description": "Verification Account Management System (VAMS) is a centralized location for maintaining Enumeration Verification Systems (EVS) accounts. VAMS allows users to create new accounts, search for existing accounts, update current accounts, and generate MI count reports. DEVO interfaces with VAMS to perform the administrative functions of registration, access control and tracking, and to manage assignment of the functional processes.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Account Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Integrated Client Database System", + "repositoryURL": "", + "description": "The Integrated Client Database (ICDB) System allows data to be shared among SSA's major application systems (e.g., Title II and Title XVI Claims Processing). ICDB is comprised of a set of databases, common screens and access software that collects, maintains, and provides access to common Client data.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Client" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Earnings Use - SEQY", + "repositoryURL": "", + "description": "A Master File online query request screen that adds earnings from up to 10 SSNs to the query response. The system then combines the earnings from the SSNs in the yearly totals on the query response.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Earnings" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Person Information", + "repositoryURL": "", + "description": "The Person Information web application was created to provide a common set of screens to display and collect person data. It is available as an independent application through the Person Information link on iMain. It can also be included in another application's path.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Person" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Folder Interface - Data Access", + "repositoryURL": "", + "description": "Allows shared access via eView to legacy information and documents within a case.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Document", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "AccuWage", + "repositoryURL": "", + "description": "AccuWage is used for testing the Electronic Filing of Wage and Tax Statement (EFW2). The software is downloaded from the SSA Web site by a submitter and used to check the format of a wage report submission file.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Taxes", + "Employment" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Comprehensive Integrity Review Process - Mainframe", + "repositoryURL": "", + "description": "Collects and evaluates electronic transactions entered into the programmatic systems. Identifies those transactions that may indicate abuse or fraudulent activity involving SSA employees or the public.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Review", + "Fraud Prevention" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "DCS Budget Tracking System", + "repositoryURL": "", + "description": "Tracks Other Objects budget allocations for the Office of Systems and tracks some Information Technology budgets. Monitors and tracks allocations, expenditures and generates Management Information (MI) reports for planning budget requests and allocations.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Management Information", + "Administrative", + "Budget Tracking" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Internet Special Notices Option", + "repositoryURL": "", + "description": "An Internet/Intranet application designed to collect notice preferences from applicants, beneficiaries, recipients, and representative payees who allege blindness or visual impairment. These individuals can select to receive all notices and written communication from SSA via a Microsoft Word CD or in Braille.", + "permissions": { + "licenses": [], + "usageType": "exemptByNationalSecurity", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "SNO", + "Notices" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Performance Assessment and Communication System", + "repositoryURL": "", + "description": "PACS assists supervisors in preparing employee performance plans, documenting expectations and progress reviews and preparing performance appraisals.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Performance Appraisals", + "Human Resources" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Security Administration Reports Application", + "repositoryURL": "", + "description": "SARA is the automated solution to an existing manual review\nprocess, and it will provide the ability to capture trending data to\nassist in management decisions. Yes, The Security Administration Reports\nApplication SARA will allow Information Security Officers ISOs,\nAlternate Information Security Officers ALT ISOs and Management Designee\nMD to access, review and take appropriate action on Security\nAdministration Reports.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Reporting", + "Management Information", + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Document Processing System", + "repositoryURL": "", + "description": "The Document Processing System (DPS) is an SSA developed, browser based application that will provide the user with functionality similar to the client server based system, Distributed Online Correspondence System (DOCS).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Document Processing", + "Document Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Personal Enrollment Credential System", + "repositoryURL": "", + "description": "The HSPD-12 Electronic Personal Enrollment Credential System (EPECS) supports the HSPD-12 credentialing process at SSA. It automates the sponsoring, vetting, and issuing of HSPD-12 credentials. It interfaces with other SSA systems for compliance with various directives.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Security" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Bench Book", + "repositoryURL": "", + "description": "A web-based application used by the office of Disability Adjudication and Review/ODAR to aid with documentation, analysis, and adjudication of disability cases.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Workload Management", + "Adjudication", + "Disability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Visitor Intake Process - Rewrite", + "repositoryURL": "", + "description": "Manages appointments and walk-ins for Field Office (FO) and assigns them to the FO staff in an effective way to minimize the wait time of the users.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Scheduling", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Hires and Losses Tracking System", + "repositoryURL": "", + "description": "This application tracks the hires and losses of employees to the Office of Systems. It provides an automated way of approving hires and tracking both hires and losses in Systems. It also provides many reports from captured data on individuals joining the Office of Systems, leaving the Office of Systems, or moving from one Associate Commissioner's office within Systems to another Associate Commissioner's office within Systems. The data from these reports are used by management to make budget decisions.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Human Resources" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "GSO - Interim Assistance Reimbursement", + "repositoryURL": "", + "description": "An online mechanism for state agencies to report to SSA the amount of state or local assistance the agencies paid to individuals who are now eligible for SSI payments.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Data Exchanges", + "Payments" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Modernized Supplemental Security Income Claims System", + "repositoryURL": "", + "description": "Web-based Intranet pages that collect and document application information about the claimant, provide a modernized data-collection environment for most post-eligibility (PE) events - regardless of whether the action taken is an initial claim or a PE event - and allow online claims initiation for the majority of SSI claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Internet", + "Claim", + "SSI" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Affordable Care Act - Batch Redetermination/Renewal Process", + "repositoryURL": "", + "description": "A batch application exchanges data with CMS related to eligibility Redeterminations and Renewal decisions for Insurance Affordability Programs.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Medical", + "Insurance" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Electronic Freedom of Information Act System -Intranet", + "repositoryURL": "", + "description": "An Intranet application used by the Office of Public Disclosure (OPD) and the Division of Earnings Record Operations (DERO) to process the different types of FOIA requests that are received.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Intranet", + "FOIA" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Direct Deposit Fraud Prevention", + "repositoryURL": "", + "description": "An intranet web application developed to collect and processes requests to block direct deposit auto-enrollment changes that are received and processed in the SSA Notification of Change (SANOC) System. The DDFP web application also requires input of the reason for the block - Fraud Alleged or Preventive Measure. Both the adding and removal of the block are updated in real time allowing the application to access the data for display the block request history.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Direct Deposit", + "Fraud Prevention" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "SSI Claims System - Web", + "repositoryURL": "", + "description": "Enables SSI claim submissions via a web-based intranet data collection process. It replaces the previous set of CICS MSSICS screens.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Data Collection", + "Claim", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Access to Financial Institutions", + "repositoryURL": "", + "description": "Electronically verifies depository account balances for Supplemental Security Income (SSI) applicants, recipients, and deemors. It also searches for undisclosed depository accounts and detects unreported excess resources, reducing improper SSI payments.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Direct Deposit", + "Financial" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "electronic Representative Payee System", + "repositoryURL": "", + "description": "The Electronic Representative Payee Accounting (eRPA) system is an intranet-based system that has automated the processing of Representative Payee Accounting forms.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Forms", + "Intranet", + "Representative Payee" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Data Exchange and Verification Online", + "repositoryURL": "", + "description": "DEVO is the back-end application for processing SSN verifications and data exchanges. DEVO uses modern technology for parameter driven processing of both batch and real time requests. DEVO provides the capability for SSA to accurately and rapidly respond to customized requests, legislative mandates, and court orders. Legacy verification and data exchange applications (Enumeration Verification System (EVS), Numident Online Verification Utility (NOVU), State Verification Exchange System (SVES), and State Online Query System (SOLQ)) are methodically being reengineered into DEVO, which will make use of reusable, flexible software. DEVO interfaces with the Verification Account Management System (VAMS) to determine account status, obtain processing parameters, and store transaction counts for Management Information (MI).", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencySystem", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Administrative", + "Verification", + "Data Exchange" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Core Services", + "repositoryURL": "", + "description": "A suite of Intranet-based utilities designed to simplify central or common routines required by many web based applications. The utilities leverage open, accessible technologies eliminating the drawbacks commonly seen in proprietary coding techniques. 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It consumes Programmatic Workload data to provide information to the 1,394 field offices to assist SSA employees in adjudicating initial disability claims.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Disability", + "Workload Management" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MySSA Benefit Verification - Backend", + "repositoryURL": "", + "description": "Accessed through the MySocialSecurity portal, it provides instant verification of SSA benefits for proof of income purposes. It also provides immediate view, print, and save of benefit verification letters to prove receipt/non-receipt of SSA benefits, Supplemental Income (SSI) or Medicare.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Registration", + "Internet" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "iAppeals (i3441)", + "repositoryURL": "", + "description": "Allows electronic submission of requests from individuals and/or third parties for the Request for Reconsideration (SSA-561), Request for Hearing (HA-501) on medically denied claims for both Title II and Title XVI claims, and allows an individual to appeal the decision directly on-line.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Appeals", + "Medical", + "Forms" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Social Security Number Verification - BSO", + "repositoryURL": "", + "description": "Allows employers to verify name/SSNs for wage reporting purposes.", + "permissions": { + "licenses": [], + "usageType": "exemptByAgencyMission", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Identity", + "Verification" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Calendar Availability Services", + "repositoryURL": "", + "description": "The calendar availability service allows the ability to add availability, update availability, get availability, update available resources, and delete availability for one or many offices and calendar configurations.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Spring Boot", + "RESTful", + "Calendar Management", + "Calendar Availability" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "CET Dynamic Help", + "repositoryURL": "", + "description": "mySSA Dynamic Help application", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "mySSA" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "codeMetadata.json Generator", + "repositoryURL": "", + "description": "A single page application for generating a codeMetadata.json file. The codeMetadata.json file contains basic data about a code asset such as it's name, description, languages, and the like.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "node.js", + "REACT", + "SPA", + "Single Page Application" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "EPMO Web Application", + "repositoryURL": "", + "description": "EPMO Application is developed in MDE using AngualrJS, HTML front end and Java (Jax-RS ) backend. This is a RESTful app with authentication and authorization done using WebSeal.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "AngularJS", + "JAX-RS", + "EJB", + "SPA", + "JWT" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "iAppointment", + "repositoryURL": "", + "description": "An Internet application that allows individuals to schedule appointments with SSA's Field Offices.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Appointments", + "MVC", + "UEF", + "FlexWeb" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Main Complex Conference Rooms System", + "repositoryURL": "", + "description": "The MCCR system is a web application tool used to reserve conference rooms for meetings, events, presentations, etc.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "facilities, conference room, reservations, coldfusion" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MDE Control Center", + "repositoryURL": "", + "description": "Self-serve control center application for SSA MDE.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Spring", + "Thymeleaf", + "LDAP", + "SMTP" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MDE JSON Generator", + "repositoryURL": "", + "description": "Self-serve application for SSA mde.json generation.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Spring", + "Thymeleaf", + "JSON" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Message Center", + "repositoryURL": "", + "description": "CET Message Center for mySSA", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "CET", + "mySSA" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "Message Service", + "repositoryURL": "", + "description": "Web Service for CET Message Center", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "SOAP" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "MessageAdmin", + "repositoryURL": "", + "description": "CET Message Center Admin Console", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "CET" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "openshift-upgrade-testing", + "repositoryURL": "", + "description": "Java code to create a sample web app - to be deployed in Open shift to perform regression testing on any major releases.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "MUT", + "paas", + "MDE", + "OpenShift" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "property-services", + "repositoryURL": "", + "description": "Property Services is an independent component that is used to read the configuration files and resources and make them available for accessing as per the environment/scope.", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "Property Services" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, + { + "name": "UEF Core", + "repositoryURL": "", + "description": "UEF patterns", + "permissions": { + "licenses": [], + "usageType": "governmentWideReuse", + "exemptionText": "" + }, + "laborHours": 0, + "tags": [ + "uef, inputs, web, containers, buttons, notices, links, design, page, standard, 508 compliance" + ], + "contact": { + "email": "Open.Source@ssa.gov", + "name": "Open Source Administrator" + } + }, { "name": "UEF Website", "repositoryURL": "", From c112e6395a31e4cc7ac613ef3d6497bcfa49a4a5 Mon Sep 17 00:00:00 2001 From: Isaac Milarsky Date: Thu, 5 Jun 2025 13:10:04 -0500 Subject: [PATCH 11/14] fix dates and add check to pull legacy assets Signed-off-by: Isaac Milarsky --- agency-indexes/DoE/Cap.json | 23 +++++++-------- ...nchronous_VisitOr_Queue_Graph_Toolkit.json | 21 ++++++++------ agency-indexes/DoE/JobRunner.json | 24 ++++++++-------- agency-indexes/DoE/LUNA.json | 25 +++++++++-------- agency-indexes/DoE/OSCARS.json | 28 ++++++++++--------- agency-indexes/DoE/SystemBurn.json | 14 +++++----- scripts/pull_legacy_assets.py | 9 ++++-- 7 files changed, 79 insertions(+), 65 deletions(-) diff --git a/agency-indexes/DoE/Cap.json b/agency-indexes/DoE/Cap.json index 365bb72d..f5258324 100644 --- a/agency-indexes/DoE/Cap.json +++ b/agency-indexes/DoE/Cap.json @@ -1,30 +1,31 @@ { "contact": { - "email": "simsdl@ornl.gov" + "email": "stooksburys@osti.gov" }, "date": { - "created": "2018-04-18", - "metadataLastUpdated": "2018-04-18" + "created": "2020-09-16", + "metadataLastUpdated": "2020-09-16" }, - "description": "A library for modeling energy storage devices.\u00a0http://cap.readthedocs.org\n", - "laborHours": 6232.0, - "name": "Cap", - "organization": "Oak Ridge National Laboratory (ORNL)", + "description": "Identification of core annotation pipeline (CAP). The repository for workflow development to integrate in-house workflows into KBase. These scripts integrate assemblies, abundances, and annotations into a Phyloseq object, specifically genes which are core among multiple metagenomes.", + "laborHours": 136.8, + "languages": [], + "name": "CAP", + "organization": "Office of Scientific and Technical Information (OSTI)", "permissions": { "exemptionText": null, "licenses": [ { - "URL": "https://api.github.com/licenses/bsd-3-clause", - "name": "BSD-3-Clause" + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" } ], "usageType": "openSource" }, - "repositoryURL": "https://github.com/ORNL-CEES/Cap", + "repositoryURL": "https://github.com/kbaseattic/cap", "status": "Development", "tags": [ "DOE CODE", - "Oak Ridge National Laboratory (ORNL)" + "Office of Scientific and Technical Information (OSTI)" ], "vcs": "git" } \ No newline at end of file diff --git a/agency-indexes/DoE/Highly_Asynchronous_VisitOr_Queue_Graph_Toolkit.json b/agency-indexes/DoE/Highly_Asynchronous_VisitOr_Queue_Graph_Toolkit.json index 6700a650..f70943e8 100644 --- a/agency-indexes/DoE/Highly_Asynchronous_VisitOr_Queue_Graph_Toolkit.json +++ b/agency-indexes/DoE/Highly_Asynchronous_VisitOr_Queue_Graph_Toolkit.json @@ -1,29 +1,32 @@ { "contact": { - "email": "holdensanchez2@llnl.gov" + "email": "bledsoe2@llnl.gov" }, "date": { - "created": "2017-10-25", - "metadataLastUpdated": "2017-10-25" + "created": "2020-12-16", + "metadataLastUpdated": "2020-12-16" }, - "description": "HAVOQGT is a C++ framework that can be used to create highly parallel graph traversal algorithms. The framework stores the graph and algorithmic data structures on external memory that is typically mapped to high performance locally attached NAND FLASH arrays. The framework supports a vertex-centered visitor programming model. The frameworkd has been used to implement breadth first search, connected components, and single source shortest path.", + "description": "HavoqGT (Highly Asynchronous Visitor Queue Graph Toolkit) is a framework for expressing\nasynchronous vertex-centric graph algorithms, and executing them on High Performance Computing (HPC) systems. It provides a vertex 'visitor' interface, where actions are defined at an individual vertex level, and contains a suite of classic graph algorithms. HavoqGT is capable of processing large graphs stored in NVRAM (SSDs) using a memory mapped interface.\n", "laborHours": 15139.2, - "name": "Highly Asynchronous VisitOr Queue Graph Toolkit", + "languages": [], + "name": "Highly Asynchronous Visitor Queue Graph Toolkit", "organization": "Lawrence Livermore National Laboratory (LLNL)", "permissions": { "exemptionText": null, "licenses": [ { - "URL": "https://api.github.com/licenses/lgpl-2.1", - "name": "LGPL-2.1" + "URL": "https://api.github.com/licenses/mit", + "name": "MIT" } ], "usageType": "openSource" }, - "repositoryURL": "https://bitbucket.org/PerMA/havoqgt", + "repositoryURL": "https://github.com/LLNL/havoqgt", "status": "Production", "tags": [ "DOE CODE", "Lawrence Livermore National Laboratory (LLNL)" - ] + ], + "vcs": "git", + "version": "0.2" } \ No newline at end of file diff --git a/agency-indexes/DoE/JobRunner.json b/agency-indexes/DoE/JobRunner.json index 66b635a3..7195850e 100644 --- a/agency-indexes/DoE/JobRunner.json +++ b/agency-indexes/DoE/JobRunner.json @@ -1,31 +1,31 @@ { "contact": { - "email": "stooksburys@osti.gov" + "email": "dkrakowski@anl.gov" }, "date": { - "created": "2020-07-30", - "metadataLastUpdated": "2020-07-31" + "created": "2023-08-18", + "metadataLastUpdated": "2023-08-21" }, - "description": "The job runner is started by the batch/resource manager system and is the component that actually executes the SDK module. It also provides the callback handler and pushes logs to the execution engine logging system.", - "laborHours": 2036.8, + "description": "SF-23-071\nJobrunner is a command line tool to manage and deploy computing jobs, organize complex workloads, and enforce a\ndirectory based hierarchy to enable reuse of files and bash scripts within a project. Organization details of a directory\ntree are encoded in Jobfiles which serve as an index of files/scripts, and indicate their purpose when deploying or\nsetting up a job. It is a flexible tool that allows users to design 16 their own directory structure, perserve their design,\nand maintain 17 consistency with increase in complexity of the project.\n", + "laborHours": 0.0, "languages": [], - "name": "JobRunner", - "organization": "Office of Scientific and Technical Information (OSTI)", + "name": "JOBRUNNER", + "organization": "Argonne National Laboratory (ANL)", "permissions": { "exemptionText": null, "licenses": [ { - "URL": "https://api.github.com/licenses/mit", - "name": "MIT" + "URL": "https://api.github.com/licenses/apache-2.0", + "name": "Apache-2.0" } ], "usageType": "openSource" }, - "repositoryURL": "https://github.com/kbase/JobRunner", - "status": "Development", + "repositoryURL": "https://github.com/akashdhruv/Jobrunner", + "status": "Production", "tags": [ "DOE CODE", - "Office of Scientific and Technical Information (OSTI)" + "Argonne National Laboratory (ANL)" ], "vcs": "git" } \ No newline at end of file diff --git a/agency-indexes/DoE/LUNA.json b/agency-indexes/DoE/LUNA.json index a7605e4f..0c0b5bac 100644 --- a/agency-indexes/DoE/LUNA.json +++ b/agency-indexes/DoE/LUNA.json @@ -1,17 +1,19 @@ { "contact": { - "email": "chan@lanl.gov" + "email": "copyrightadmin@sandia.gov" }, "date": { - "created": "2021-06-17", - "metadataLastUpdated": "2021-06-17" + "created": "2022-10-05", + "metadataLastUpdated": "2022-10-05" }, - "description": "We have developed a mechanistic model of leaf utilization of nitrogen for assimilation (LUNA V1.0) to predict the photosynthetic capacity at the global scale under different environmental conditions. We adopt an optimality hypothesis to nitrogen allocation among light capture, electron transport, carboxylation, and respiration. The LUNA model is able to reasonably capture the measured spatial and temporal patterns of the photosynthetic capacity as it explains ~55% of the global variation in the observed values of maximum carboxylation rate (Vc,max25) and ~65% of the variation in the observed values of maximum electron transport rate (Jmax25).", - "homepageURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "description": "SAND2021-15051 O\nLuna is an experimental cognitive architecture that seeks to enable continuous learning in an embodied agent. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy\u2019s National Nuclear Security Administration under contract DE-NA0003525.", + "homepageURL": "https://ip.sandia.gov/contact-form", "laborHours": 0.0, - "languages": [], - "name": "LUNA", - "organization": "Los Alamos National Laboratory (LANL)", + "languages": [ + "Python3" + ], + "name": "Luna", + "organization": "Sandia National Laboratories (SNL)", "permissions": { "exemptionText": null, "licenses": [ @@ -22,10 +24,11 @@ ], "usageType": "openSource" }, - "repositoryURL": "https://www.lanl.gov/projects/feynman-center/deploying-innovation/intellectual-property/software-tools/open-source-software.php", + "repositoryURL": "https://ip.sandia.gov/contact-form", "status": "Development", "tags": [ "DOE CODE", - "Los Alamos National Laboratory (LANL)" - ] + "Sandia National Laboratories (SNL)" + ], + "version": "0.1" } \ No newline at end of file diff --git a/agency-indexes/DoE/OSCARS.json b/agency-indexes/DoE/OSCARS.json index ca8908ef..db005819 100644 --- a/agency-indexes/DoE/OSCARS.json +++ b/agency-indexes/DoE/OSCARS.json @@ -1,31 +1,33 @@ { "contact": { - "email": "svince@lbl.gov" + "email": "jhaemmerle@lbl.gov" }, "date": { - "created": "2019-06-20", - "metadataLastUpdated": "2019-06-20" + "created": "2021-04-16", + "metadataLastUpdated": "2021-04-20" }, - "description": "Short for On-demand Secure Circuits and Advance Reservation System, OSCARS is a freely available open-source product. As developed by the Department of Energy\u2019s high-performance science network ESnet, OSCARS was designed by network engineers who specialize in supporting the U.S. national laboratory system and its data-intensive collaborations.", - "laborHours": 127877.6, - "languages": [], - "name": "OSCARS", + "description": "The ESnet On-Demand Secure Circuits and Advance Reservation System (OSCARS) is a prototype service enabling advance reservation of guaranteed bandwidth secure virtual circuits. OSCARS operates within the Energy Sciences Network (ESnet), and has provisions for interoperation with other network domains. OSCARS utilizes the Web services model and standards to implement communication with the system and between domains, and for authentication, authorization, and auditing (AAA). The management and operation of end-to-end virtual circuits within the network is done at the layer 3 network level. Multi-Protocol Label Switching (MPLS) and the Resource Reservation Protocol (RSVP) are used to create the virtual circuits or Label Switched Paths (LSP's). Quality of Service (QoS) is used to provide bandwidth guarantees.", + "homepageURL": "https://www.es.net/engineering-services/oscars", + "laborHours": 0.0, + "languages": [ + "None" + ], + "name": "Oscars", "organization": "Lawrence Berkeley National Laboratory (LBNL)", "permissions": { "exemptionText": null, "licenses": [ { - "URL": "https://api.github.com/licenses/mit", - "name": "MIT" + "URL": "https://api.github.com/licenses/bsd-3-clause", + "name": "BSD-3-Clause" } ], "usageType": "openSource" }, - "repositoryURL": "https://github.com/esnet/oscars", - "status": "Development", + "repositoryURL": "https://www.es.net/engineering-services/oscars", + "status": "Production", "tags": [ "DOE CODE", "Lawrence Berkeley National Laboratory (LBNL)" - ], - "vcs": "git" + ] } \ No newline at end of file diff --git a/agency-indexes/DoE/SystemBurn.json b/agency-indexes/DoE/SystemBurn.json index 43008ed4..71c1a911 100644 --- a/agency-indexes/DoE/SystemBurn.json +++ b/agency-indexes/DoE/SystemBurn.json @@ -1,14 +1,14 @@ { "contact": { - "email": "laymancelk@ornl.gov" + "email": "simsdl@ornl.gov" }, "date": { - "created": "2017-10-25", - "metadataLastUpdated": "2017-10-25" + "created": "2018-04-18", + "metadataLastUpdated": "2018-04-18" }, - "description": "SystemBurn is a tool for creating a synthetic computational load for the purpose of measuring how much power a computer will draw under that type of load. The loads include fundamental library function calls like matrix multiply, memory copies, fourier transforms, bit manipulation, I/O, network packet transfers, and some code contrived to cause the processor to dray more or less power. The code produces some diagnostic and progress output, but the actual measurements would be recorded from the power panels within the computer room.", + "description": "SystemBurn is a software package designed to allow users to methodically create maximal loads on systems ranging from desktops to supercomputers.\n", "laborHours": 17510.4, - "name": "SystemBurn", + "name": "Systemburn", "organization": "Oak Ridge National Laboratory (ORNL)", "permissions": { "exemptionText": null, @@ -20,8 +20,8 @@ ], "usageType": "openSource" }, - "repositoryURL": "https://github.com/jlothian/systemburn", - "status": "Production", + "repositoryURL": "https://github.com/ORNL/systemburn", + "status": "Development", "tags": [ "DOE CODE", "Oak Ridge National Laboratory (ORNL)" diff --git a/scripts/pull_legacy_assets.py b/scripts/pull_legacy_assets.py index f21e6d19..1f7db23d 100644 --- a/scripts/pull_legacy_assets.py +++ b/scripts/pull_legacy_assets.py @@ -1,7 +1,7 @@ import requests import json import os -from util import merge_indexes +from util import merge_indexes, which_code_json_is_most_up_to_date # the commented out links are not valid or cant be found agencies_links = { @@ -50,8 +50,13 @@ def add_directories_to_directory(data, agency_name): safe_name = item['name'].replace('/', '_').replace('(', '_').replace(')', '_').replace(' ', '_') file_path = os.path.join(directory_name, f"{safe_name}.json") + if os.path.exists(file_path): + with open(file_path, 'r', encoding='utf-8') as f: + existing_code_json = json.load(f) + + with open(file_path, 'w', encoding='utf-8') as file: - json.dump(item, file, indent = 4) + json.dump(which_code_json_is_most_up_to_date(item,existing_code_json), file, indent = 4) except Exception as e: print(f"Failed to add files to {agency_name} directory: {e}") From d58afe782fd34ff51ddbadf7c7bfb39729e4f129 Mon Sep 17 00:00:00 2001 From: Isaac Milarsky Date: Thu, 5 Jun 2025 13:31:59 -0500 Subject: [PATCH 12/14] add parse function and dep Signed-off-by: Isaac Milarsky --- legacy-codegov.json | 2 +- scripts/pull_legacy_assets.py | 8 +++++++- scripts/requirements.txt | 3 ++- scripts/util.py | 7 ++++--- 4 files changed, 14 insertions(+), 6 deletions(-) diff --git a/legacy-codegov.json b/legacy-codegov.json index d8fb9a42..d9660784 100644 --- a/legacy-codegov.json +++ b/legacy-codegov.json @@ -3178,7 +3178,7 @@ "date": { "created": "2016-11-01", "lastModified": "2018-03-16T13:00-04:00", - "metadataLastUpdated": "2018-03-15T20:31:00Z" + "LastUpdated": "2018-03-15T20:31:00Z" } }, { diff --git a/scripts/pull_legacy_assets.py b/scripts/pull_legacy_assets.py index 1f7db23d..bd78c3ac 100644 --- a/scripts/pull_legacy_assets.py +++ b/scripts/pull_legacy_assets.py @@ -50,13 +50,19 @@ def add_directories_to_directory(data, agency_name): safe_name = item['name'].replace('/', '_').replace('(', '_').replace(')', '_').replace(' ', '_') file_path = os.path.join(directory_name, f"{safe_name}.json") + to_save = item if os.path.exists(file_path): with open(file_path, 'r', encoding='utf-8') as f: existing_code_json = json.load(f) + try: + to_save = which_code_json_is_most_up_to_date(item,existing_code_json) + except Exception as e: + print(f"Ran into {e} when trying to sort code_json files by date!") + with open(file_path, 'w', encoding='utf-8') as file: - json.dump(which_code_json_is_most_up_to_date(item,existing_code_json), file, indent = 4) + json.dump(to_save, file, indent = 4) except Exception as e: print(f"Failed to add files to {agency_name} directory: {e}") diff --git a/scripts/requirements.txt b/scripts/requirements.txt index 457dee47..bff4364e 100644 --- a/scripts/requirements.txt +++ b/scripts/requirements.txt @@ -1 +1,2 @@ -codejson-index-generator \ No newline at end of file +codejson-index-generator +python-dateutil \ No newline at end of file diff --git a/scripts/util.py b/scripts/util.py index 01e36846..8e724544 100644 --- a/scripts/util.py +++ b/scripts/util.py @@ -1,5 +1,6 @@ import json from datetime import datetime +from dateutil.parser import parse def merge_indexes(data,existing_file): try: @@ -32,10 +33,10 @@ def merge_indexes(data,existing_file): def which_code_json_is_most_up_to_date(*args): + sorted_code_json_list = sorted( args, - key=lambda d : datetime.strptime( - d['date']['metadataLastUpdated'],'%Y-%m-%d' - ), + key=lambda d : parse( + d['date']['metadataLastUpdated']), reverse=True) return sorted_code_json_list[0] \ No newline at end of file From dc14fa969311ac0cdd76f6a2c05e97f82cf6849e Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" <41898282+github-actions[bot]@users.noreply.github.com> Date: Fri, 6 Jun 2025 17:31:45 +0000 Subject: [PATCH 13/14] update contributors information --- COMMUNITY.md | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/COMMUNITY.md b/COMMUNITY.md index b9d1297e..17320233 100644 --- a/COMMUNITY.md +++ b/COMMUNITY.md @@ -78,17 +78,17 @@ Total number of contributors: 8